diff --git a/.circleci/scripts/run_integration.sh b/.circleci/scripts/run_integration.sh index 1380b07de53..fb91bcce77f 100644 --- a/.circleci/scripts/run_integration.sh +++ b/.circleci/scripts/run_integration.sh @@ -128,6 +128,8 @@ fi sudo iptables -L integration_only -n -v -x > "$results/egress-guard.txt" awk '$3 == "REJECT" && $1 > 0 { rejected=1 } END { exit !rejected }' "$results/egress-guard.txt" +export UV_OFFLINE=true + if [ "$mode" = parity ]; then export INTEGRATION_WORKERS=1 else diff --git a/.github/PULL_REQUEST_TEMPLATE/general.md b/.github/PULL_REQUEST_TEMPLATE/general.md index aafd968ee0f..4f1a18e925e 100644 --- a/.github/PULL_REQUEST_TEMPLATE/general.md +++ b/.github/PULL_REQUEST_TEMPLATE/general.md @@ -6,12 +6,13 @@ ## Handwritten 1-3 sentence description - diff --git a/.github/workflows/compat-matrix-image.yml b/.github/workflows/compat-matrix-image.yml index f08792c904c..ddd2aa1a50b 100644 --- a/.github/workflows/compat-matrix-image.yml +++ b/.github/workflows/compat-matrix-image.yml @@ -4,7 +4,7 @@ on: pull_request: paths: - tests/e2e/claude_code/cron_vm/** - - tests/e2e/claude_code/pr_gate_version_resolver.py + - tests/e2e/cli_harness/npm_version_resolver.py - .github/workflows/compat-matrix-image.yml workflow_dispatch: @@ -36,7 +36,7 @@ jobs: whoami gh --version uv --version - version="$(uv run --no-project --python 3.12 python /opt/litellm/tests/e2e/claude_code/pr_gate_version_resolver.py)" + version="$(uv run --no-project --python 3.12 python /opt/litellm/tests/e2e/cli_harness/npm_version_resolver.py @anthropic-ai/claude-code)" /opt/litellm/tests/e2e/claude_code/cron_vm/install_claude_code.sh "${version}" /tmp/claude-cli /tmp/claude-cli/claude --version ' diff --git a/.github/workflows/deploy-dev-on-main.yml b/.github/workflows/deploy-dev-on-main.yml deleted file mode 100644 index 1208a2dbbdb..00000000000 --- a/.github/workflows/deploy-dev-on-main.yml +++ /dev/null @@ -1,30 +0,0 @@ -name: Deploy main to gateway-dev - -on: - push: - branches: [main] - -permissions: {} - -concurrency: - group: deploy-dev-dispatch - cancel-in-progress: true - -jobs: - dispatch: - if: github.repository == 'BerriAI/litellm' - runs-on: ubuntu-latest - timeout-minutes: 5 - steps: - - uses: actions/create-github-app-token@fee1f7d63c2ff003460e3d139729b119787bc349 # v2.2.2 - id: token - with: - app-id: ${{ secrets.LITELLM_OPS_DISPATCH_APP_ID }} - private-key: ${{ secrets.LITELLM_OPS_DISPATCH_APP_PRIVATE_KEY }} - owner: BerriAI - repositories: litellm-ops - permission-actions: write - - name: Dispatch the litellm-ops dev deploy - env: - GH_TOKEN: ${{ steps.token.outputs.token }} - run: gh api --method POST repos/BerriAI/litellm-ops/actions/workflows/deploy-dev.yml/dispatches -f ref=main diff --git a/.github/workflows/osv-scan.yml b/.github/workflows/osv-scan.yml index 1c7e8b2841a..5016957bd6f 100644 --- a/.github/workflows/osv-scan.yml +++ b/.github/workflows/osv-scan.yml @@ -5,6 +5,9 @@ on: branches: - main - "litellm_**" + - "rc/**" + - "stable/**" + - "lts/**" schedule: - cron: "23 6 * * *" workflow_dispatch: diff --git a/.github/workflows/test-linting.yml b/.github/workflows/test-linting.yml index c3388430589..cbeea71ad0f 100644 --- a/.github/workflows/test-linting.yml +++ b/.github/workflows/test-linting.yml @@ -208,7 +208,7 @@ jobs: exit 0 fi retry() { "$@" || { sleep 15; "$@"; } || { sleep 30; "$@"; }; } - CLAUDE_VERSION="$(retry uv run --no-sync python tests/e2e/claude_code/pr_gate_version_resolver.py)" + CLAUDE_VERSION="$(retry uv run --no-sync python tests/e2e/cli_harness/npm_version_resolver.py @anthropic-ai/claude-code)" tests/e2e/claude_code/cron_vm/install_claude_code.sh "$CLAUDE_VERSION" "$RUNNER_TEMP/claude-cli" PATH="$RUNNER_TEMP/claude-cli:$PATH" uv run --no-sync pytest -q tests/e2e_harness uv run --no-sync pytest --tb=short -q --noconftest -o addopts= -o "pythonpath=tests/e2e tests/e2e_harness" -p no:rerunfailures \ diff --git a/.github/workflows/test-unit.yml b/.github/workflows/test-unit.yml index 2c05ee827a3..f1456b1fde8 100644 --- a/.github/workflows/test-unit.yml +++ b/.github/workflows/test-unit.yml @@ -5,6 +5,9 @@ on: branches: - main - "litellm_**" + - "rc/**" + - "stable/**" + - "lts/**" push: branches: - main @@ -280,6 +283,7 @@ jobs: tests/unit/llms/e2b tests/unit/llms/edenai tests/unit/llms/elevenlabs + tests/unit/llms/empiriolabs tests/unit/llms/exa_ai tests/unit/llms/fal_ai tests/unit/llms/fastcrw @@ -415,6 +419,7 @@ jobs: - shard: router test-path: >- + tests/unit/router_rust tests/unit/test_router python-version: "3.12" workers: 4 @@ -441,6 +446,7 @@ jobs: tests/unit/ocr tests/unit/passthrough tests/unit/rag + tests/unit/cookbook tests/unit/realtime_api tests/unit/rerank_api tests/unit/search @@ -972,10 +978,10 @@ jobs: dist: loadscope steps: - uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0 - timeout-minutes: ${{ matrix.shard == 'db-and-spend' && 10 || 3 }} + timeout-minutes: 3 with: persist-credentials: false - fetch-depth: ${{ matrix.shard == 'db-and-spend' && '0' || '1' }} + fetch-depth: 1 - name: Detect relevant changes id: changes @@ -1008,13 +1014,11 @@ jobs: with: artifact: ${{ needs.rust-bridge.outputs.artifact }} - - name: Install dependencies and check schema + - name: Install dependencies if: steps.changes.outputs.decision != 'skip' - timeout-minutes: 8 + timeout-minutes: 5 env: RUST_BRIDGE_ARTIFACT: ${{ needs.rust-bridge.outputs.artifact }} - UNIT_SHARD: ${{ matrix.shard }} - SCHEMA_BASE_REF: origin/${{ github.event.repository.default_branch }} run: | diff -u model_prices_and_context_window.json litellm/model_prices_and_context_window_backup.json if [ -z "$RUST_BRIDGE_ARTIFACT" ]; then @@ -1026,9 +1030,21 @@ jobs: uv run --no-sync python -c "import importlib.metadata; import litellm.rust_bridge._native; print(importlib.metadata.version('litellm'))" fi uv run --no-sync python -c 'import os, sys; print(sys.version); assert f"{sys.version_info.major}.{sys.version_info.minor}" == os.environ["UV_PYTHON"]' - if [ "$UNIT_SHARD" = "db-and-spend" ]; then - uv run --no-sync python scripts/check_schema_compatibility.py --base-ref "$SCHEMA_BASE_REF" - fi + + - name: Check schema.prisma against the merge base + if: steps.changes.outputs.decision != 'skip' && matrix.shard == 'db-and-spend' && github.event_name == 'pull_request' + timeout-minutes: 3 + env: + GH_TOKEN: ${{ github.token }} + PR_NUMBER: ${{ github.event.pull_request.number }} + EVENT_BASE_REF: ${{ github.event.pull_request.base.ref }} + HEAD_SHA: ${{ github.event.pull_request.head.sha }} + run: | + base_ref=$(gh api "repos/${GITHUB_REPOSITORY}/branches/${EVENT_BASE_REF}" --jq .name) || base_ref=$(gh api "repos/${GITHUB_REPOSITORY}/pulls/${PR_NUMBER}" --jq .base.ref) + merge_base=$(gh api "repos/${GITHUB_REPOSITORY}/compare/${base_ref}...${HEAD_SHA}?per_page=1" --jq '.merge_base_commit.sha') + test -n "$merge_base" + git fetch --no-tags --depth=1 origin "$merge_base" + uv run --no-sync python scripts/check_schema_compatibility.py --base-commit "$merge_base" - name: Cache Prisma binaries if: steps.changes.outputs.decision != 'skip' diff --git a/.github/workflows/weekly_load_anomaly.yml b/.github/workflows/weekly_load_anomaly.yml deleted file mode 100644 index 0ba4df89cc4..00000000000 --- a/.github/workflows/weekly_load_anomaly.yml +++ /dev/null @@ -1,85 +0,0 @@ -name: "Weekly Load Anomaly Check" - -on: - schedule: - - cron: "0 12 * * 6" - workflow_dispatch: - -permissions: - contents: read - -jobs: - weekly-load-anomaly: - if: github.event_name != 'schedule' || github.repository == 'BerriAI/litellm' - runs-on: ubuntu-latest - timeout-minutes: 45 - services: - postgres: - image: postgres:16.6 - env: - POSTGRES_USER: llmproxy - POSTGRES_PASSWORD: dbpassword9090 - POSTGRES_DB: litellm - ports: - - 5432:5432 - options: >- - --health-cmd "pg_isready -U llmproxy" - --health-interval 5s - --health-timeout 5s - --health-retries 10 - env: - DATABASE_URL: postgresql://llmproxy:dbpassword9090@localhost:5432/litellm - LITELLM_MASTER_KEY: sk-weekly-anomaly-check - ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }} - AWS_BEARER_TOKEN_BEDROCK: ${{ secrets.AWS_BEARER_TOKEN_BEDROCK }} - steps: - - uses: actions/checkout@08eba0b27e820071cde6df949e0beb9ba4906955 # v4.3.0 - with: - persist-credentials: false - - - name: Set up Python - uses: actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065 # v5.6.0 - with: - python-version: "3.12" - - - name: Set up uv - uses: ./.github/actions/setup-uv-with-retries - with: - version: "0.10.9" - - - name: Cache the Rust build - uses: ./.github/actions/cache-cargo-build - - - name: Install dependencies - run: | - .github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra proxy - - - name: Cache Prisma binaries - uses: ./.github/actions/cache-prisma-binaries - - - name: Generate Prisma client - run: | - uv run --no-sync prisma generate --schema litellm/proxy/schema.prisma - - - name: Start the proxy - run: | - nohup uv run --no-sync litellm --config tests/e2e/perf/weekly_anomaly_config.yml --port 4000 > proxy.log 2>&1 & - for _ in $(seq 1 90); do - if curl -fs http://localhost:4000/health/liveliness > /dev/null; then - exit 0 - fi - sleep 2 - done - echo "proxy never became live" - tail -n 100 proxy.log - exit 1 - - - name: Run the weekly session anomaly test - env: - E2E_WEEKLY_ANOMALY: "1" - run: | - uv run --no-sync pytest tests/e2e/perf/test_weekly_session_anomaly_e2e.py -v --tb=short -rA - - - name: Show proxy log on failure - if: failure() - run: tail -n 300 proxy.log diff --git a/README.md b/README.md index 3b5710fa0c5..31a93bf8c67 100644 --- a/README.md +++ b/README.md @@ -398,6 +398,7 @@ Set `LITELLM_PROXY_API_BASE` and `LITELLM_PROXY_API_KEY` and every model call th | [Deepseek (`deepseek`)](https://docs.litellm.ai/docs/providers/deepseek) | ✅ | ✅ | ✅ | | | | | | | | | [Eden AI (`edenai`)](https://docs.litellm.ai/docs/providers/edenai) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | | | | [ElevenLabs (`elevenlabs`)](https://docs.litellm.ai/docs/providers/elevenlabs) | ✅ | ✅ | ✅ | | | ✅ | ✅ | | | | +| [EmpirioLabs AI (`empiriolabs`)](https://docs.litellm.ai/docs/providers/empiriolabs) | ✅ | | ✅ | | | | | | | | | [Empower (`empower`)](https://docs.litellm.ai/docs/providers/empower) | ✅ | ✅ | ✅ | | | | | | | | | [eu/jev Decisions API (`eu_jev`)](https://docs.litellm.ai/docs/pass_through/eu_jev) | | | | | | | | | | | | [Fal AI (`fal_ai`)](https://docs.litellm.ai/docs/providers/fal_ai) | ✅ | ✅ | ✅ | | ✅ | | | | | | @@ -444,6 +445,7 @@ Set `LITELLM_PROXY_API_BASE` and `LITELLM_PROXY_API_KEY` and every model call th | [OpenAI-like (`openai_like`)](https://docs.litellm.ai/docs/providers/openai_compatible) | | | | ✅ | | | | | | | | [OpenRouter (`openrouter`)](https://docs.litellm.ai/docs/providers/openrouter) | ✅ | ✅ | ✅ | | | | | | | | | [OVHCloud AI Endpoints (`ovhcloud`)](https://docs.litellm.ai/docs/providers/ovhcloud) | ✅ | ✅ | ✅ | | | | | | | | +| [Parallel AI (`parallel_ai`)](https://docs.litellm.ai/docs/search/parallel_ai) | | | | | | | | | | | | [Perplexity AI (`perplexity`)](https://docs.litellm.ai/docs/providers/perplexity) | ✅ | ✅ | ✅ | | | | | | | | | [Petals (`petals`)](https://docs.litellm.ai/docs/providers/petals) | ✅ | ✅ | ✅ | | | | | | | | | [Pinstripes (`pinstripes`)](https://docs.litellm.ai/docs/providers/pinstripes) | ✅ | ✅ | ✅ | | | | | | | | diff --git a/cookbook/gpt_realtime_translate.py b/cookbook/gpt_realtime_translate.py new file mode 100644 index 00000000000..827c65cdbfe --- /dev/null +++ b/cookbook/gpt_realtime_translate.py @@ -0,0 +1,245 @@ +#!/usr/bin/env python3 + +import argparse +import asyncio +import base64 +import json +import os +import sys +import wave +from collections.abc import Iterator, Sequence +from dataclasses import dataclass +from pathlib import Path +from urllib.parse import urlencode, urlsplit, urlunsplit + +import websockets +from websockets.asyncio.client import ClientConnection + +SAMPLE_RATE = 24_000 +CHANNELS = 1 +SAMPLE_WIDTH = 2 +CHUNK_DURATION_SECONDS = 0.1 +CHUNK_BYTES = int(SAMPLE_RATE * CHANNELS * SAMPLE_WIDTH * CHUNK_DURATION_SECONDS) +RESPONSE_TIMEOUT_SECONDS = 30.0 +AUDIO_EVENT_TYPES = frozenset( + { + "session.output_audio.delta", + "response.audio.delta", + "response.output_audio.delta", + } +) +TRANSCRIPT_EVENT_TYPES = frozenset( + { + "session.output_transcript.delta", + "response.text.delta", + "response.output_audio_transcript.delta", + } +) + + +@dataclass(frozen=True, slots=True) +class Settings: + input_wav: Path + output_wav: Path + base_url: str + model: str + target_language: str + trailing_silence_seconds: float + api_key: str + + +def write_stdout(message: str = "", *, end: str = "\n", flush: bool = False) -> None: + sys.stdout.write(f"{message}{end}") + if flush: + sys.stdout.flush() + + +def write_stderr(message: str) -> None: + sys.stderr.write(f"{message}\n") + + +def parse_args(argv: Sequence[str] | None = None) -> Settings | str: + parser = argparse.ArgumentParser( + description="Stream a 24 kHz PCM16 WAV through gpt-realtime-translate and save the translated audio", + ) + parser.add_argument("input_wav", type=Path) + parser.add_argument("--output", type=Path, default=Path("translated.wav")) + parser.add_argument("--base-url", default=os.getenv("LITELLM_BASE_URL", "http://localhost:4000")) + parser.add_argument("--model", default=os.getenv("REALTIME_TRANSLATE_MODEL", "gpt-realtime-translate")) + parser.add_argument("--target-language", default="fr") + parser.add_argument("--trailing-silence", type=float, default=1.5) + parsed = parser.parse_args(argv) + api_key = os.getenv("LITELLM_API_KEY") or os.getenv("OPENAI_API_KEY") + if not api_key: + return "Set LITELLM_API_KEY or OPENAI_API_KEY before running the script" + if parsed.trailing_silence < 0: + return "--trailing-silence must be zero or greater" + return Settings( + input_wav=parsed.input_wav, + output_wav=parsed.output, + base_url=parsed.base_url, + model=parsed.model, + target_language=parsed.target_language, + trailing_silence_seconds=parsed.trailing_silence, + api_key=api_key, + ) + + +def translation_url(base_url: str, model: str) -> str | None: + parsed = urlsplit(base_url.rstrip("/")) + scheme = {"http": "ws", "https": "wss", "ws": "ws", "wss": "wss"}.get(parsed.scheme) + if not scheme or not parsed.netloc: + return None + base_path = parsed.path.rstrip("/") + realtime_path = ( + f"{base_path}/realtime/translations" if base_path.endswith("/v1") else f"{base_path}/v1/realtime/translations" + ) + return urlunsplit((scheme, parsed.netloc, realtime_path, urlencode({"model": model}), "")) + + +def read_pcm16_wav(path: Path) -> bytes | str: + try: + with wave.open(str(path), "rb") as source: + actual_format = ( + source.getnchannels(), + source.getsampwidth(), + source.getframerate(), + source.getcomptype(), + ) + expected_format = (CHANNELS, SAMPLE_WIDTH, SAMPLE_RATE, "NONE") + if actual_format != expected_format: + return ( + f"{path} must be mono, 16-bit PCM, 24 kHz WAV; received " + f"channels={actual_format[0]}, sample_width={actual_format[1]}, " + f"sample_rate={actual_format[2]}, compression={actual_format[3]}" + ) + return source.readframes(source.getnframes()) + except (OSError, EOFError, wave.Error) as exc: + return f"Unable to read {path}: {exc}" + + +def audio_chunks(audio: bytes) -> Iterator[bytes]: + return (audio[offset : offset + CHUNK_BYTES] for offset in range(0, len(audio), CHUNK_BYTES)) + + +def audio_message(audio: bytes) -> str: + return json.dumps( + { + "type": "session.input_audio_buffer.append", + "audio": base64.b64encode(audio).decode("ascii"), + } + ) + + +async def configure_session(connection: ClientConnection, target_language: str) -> str | None: + await connection.send( + json.dumps( + { + "type": "session.update", + "session": {"audio": {"output": {"language": target_language}}}, + } + ) + ) + while True: + raw_event = await asyncio.wait_for(connection.recv(), timeout=20) + event = json.loads(raw_event) + event_type = event.get("type") + if event_type == "session.created": + write_stdout(f"Session: {event.get('session', {}).get('id', 'created')}") + if event_type == "session.updated": + return None + if event_type == "error": + return f"Realtime API error: {json.dumps(event.get('error', event), ensure_ascii=False)}" + + +async def send_audio( + connection: ClientConnection, pcm: bytes, trailing_silence_seconds: float, finished: asyncio.Event +) -> None: + silence = bytes(round(trailing_silence_seconds * SAMPLE_RATE * CHANNELS * SAMPLE_WIDTH)) + try: + for chunk in audio_chunks(pcm + silence): + await connection.send(audio_message(chunk)) + await asyncio.sleep(len(chunk) / (SAMPLE_RATE * CHANNELS * SAMPLE_WIDTH)) + await connection.send(json.dumps({"type": "session.close"})) + finally: + finished.set() + + +async def receive_translation( + connection: ClientConnection, output_path: Path, sender_finished: asyncio.Event +) -> str | None: + audio_received = asyncio.Event() + try: + with wave.open(str(output_path), "wb") as output: + output.setnchannels(CHANNELS) + output.setsampwidth(SAMPLE_WIDTH) + output.setframerate(SAMPLE_RATE) + write_stdout("Translation: ", end="", flush=True) + while True: + try: + raw_event = await asyncio.wait_for(connection.recv(), timeout=RESPONSE_TIMEOUT_SECONDS) + except TimeoutError: + if not sender_finished.is_set(): + continue + return ( + f"The translation stream went quiet for {RESPONSE_TIMEOUT_SECONDS:g} s without closing the session" + ) + event = json.loads(raw_event) + event_type = event.get("type") + if event_type in AUDIO_EVENT_TYPES: + output.writeframes(base64.b64decode(event.get("delta", ""), validate=True)) + audio_received.set() + elif event_type in TRANSCRIPT_EVENT_TYPES: + write_stdout(event.get("delta", event.get("text", "")), end="", flush=True) + elif event_type == "error": + return f"Realtime API error: {json.dumps(event.get('error', event), ensure_ascii=False)}" + elif event_type == "session.closed": + write_stdout() + return None if audio_received.is_set() else "The translation stream ended without translated audio" + except (OSError, wave.Error) as exc: + return f"Unable to write {output_path}: {exc}" + + +async def translate(settings: Settings, pcm: bytes) -> str | None: + url = translation_url(settings.base_url, settings.model) + if not url: + return f"Invalid --base-url: {settings.base_url}" + sender_finished = asyncio.Event() + try: + async with websockets.connect( + url, + additional_headers={"Authorization": f"Bearer {settings.api_key}"}, + proxy=None, + open_timeout=20, + close_timeout=5, + ) as connection: + configuration_error = await configure_session(connection, settings.target_language) + if configuration_error: + return configuration_error + async with asyncio.TaskGroup() as tasks: + receiver = tasks.create_task(receive_translation(connection, settings.output_wav, sender_finished)) + tasks.create_task(send_audio(connection, pcm, settings.trailing_silence_seconds, sender_finished)) + return receiver.result() + except Exception as exc: + return f"Translation failed: {type(exc).__name__}: {exc}" + + +def main(argv: Sequence[str] | None = None) -> int: + settings = parse_args(argv) + if isinstance(settings, str): + write_stderr(settings) + return 2 + pcm = read_pcm16_wav(settings.input_wav) + if isinstance(pcm, str): + write_stderr(pcm) + return 2 + error = asyncio.run(translate(settings, pcm)) + if error: + write_stderr(error) + return 1 + write_stdout(f"Translated audio: {settings.output_wav}") + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/cookbook/skill_scanner/README.md b/cookbook/skill_scanner/README.md new file mode 100644 index 00000000000..2a68e116002 --- /dev/null +++ b/cookbook/skill_scanner/README.md @@ -0,0 +1,60 @@ +# Manual skill security scans + +This standalone adapter runs NVIDIA SkillSpector on a separate machine. It is not installed in the LiteLLM proxy and does not require a shared Helm or Compose deployment + +Start it with Python 3.12 or newer and uv. The script pins SkillSpector and its HTTP dependencies + +```sh +export SKILL_SCANNER_API_KEY="$(openssl rand -hex 32)" +uv run server.py +``` + +For another host, place the loopback service behind an HTTPS reverse proxy that forwards the Authorization header and enforces a 65 MiB request limit. Run it under an unprivileged account with a writable temporary directory and no production files or credentials. The scanner host needs Git and network access to requested sources and optional model providers. Apply network egress restrictions suitable for those sources + +Configure the same scanner secret in the gateway's environment, then add this to LiteLLM's configuration + +```yaml +general_settings: + skill_scanner: + endpoint: https://scanner.example.com/scan + api_key_env: SKILL_SCANNER_API_KEY + use_llm: false + timeout_seconds: 180 +``` + +The endpoint must be reachable from the gateway. A customer's laptop works while it is reachable through their network, VPN or authenticated HTTPS tunnel. `localhost` refers to the gateway machine, not the admin's browser. HTTP is accepted only for loopback development + +Open Skills, Submissions, and Review as a proxy admin. Click **Scan for threats**, inspect the report, then independently approve or reject the proposal. Scanning is optional and never changes approval permissions or blocks publication. The report shows findings, locations, remediation, risk score, scanner version and whether semantic analysis actually ran. Incomplete reports do not establish safety + +Uploaded ZIPs are sent privately to the scanner with their exact stored bytes. Metadata-only edits reuse the matching stored archive. If that archive is missing or changed, submit a new ZIP before scanning. The displayed SHA-256 identifies that archive, and the scan examines its files rather than proposed catalog metadata. Remote URL reports describe the source at scan time and do not freeze its contents. GitHub branch/tag refs and explicit-ref subdirectories are supported. Other ref/subdirectory combinations require a ZIP so the adapter does not silently scan the wrong revision + +The latest scan result is retained with the submission. Running scans have a deadline. If a gateway restarts or the scanner becomes unavailable, the attempt expires and an admin can retry. Retries replace the latest report. Approving or rejecting during a scan does not cancel it or change the decision + +Set `use_llm: true` to request semantic analysis and configure the provider on the scanner machine using [SkillSpector's provider instructions](https://github.com/NVIDIA/skillspector#llm-analysis). Provider credentials stay on that machine. Static analysis can also call OSV for dependency checks + +## HTTP contract + +The gateway sends an authenticated `POST` to the configured endpoint. The body contains form fields `source` (JSON source descriptor), `use_llm` (boolean), and `expires_at` (timezone-aware ISO timestamp), plus `file` (ZIP) when bytes are available. The service returns HTTP 200 with this JSON shape + +```json +{ + "scanner_version": "2.12.0", + "complete": true, + "scan_mode": "static-only", + "risk_score": 70, + "findings": [{ + "rule_id": "example-rule", + "severity": "HIGH", + "message": "Potential data exfiltration", + "file": "SKILL.md", + "start_line": 8, + "explanation": "Instructions request sending local files to an external host", + "remediation": "Remove the external upload instruction" + }], + "limitations": [] +} +``` + +Reports are limited to 1 MiB and 500 findings. Scanner uploads allow 64 MiB because the gateway can expand compressed skill uploads into stored compatibility ZIPs. The gateway rejects malformed reports, refuses redirects and verifies TLS. Only the configured scanner credential is sent. A timeout, HTTP error or incomplete report remains visible to the reviewer + +The bundled adapter runs at most two child scans concurrently. Each child and its descendants are terminated at the gateway deadline, capped at 570 seconds. Keep the gateway and scanner clocks synchronized. Direct adapter clients may omit `expires_at` to use the cap. Child processes never execute submitted skill scripts. Raise the gateway deadline up to 600 seconds when needed for semantic analysis and configure the reverse proxy timeout to match diff --git a/cookbook/skill_scanner/server.py b/cookbook/skill_scanner/server.py new file mode 100644 index 00000000000..44a1cecb00f --- /dev/null +++ b/cookbook/skill_scanner/server.py @@ -0,0 +1,172 @@ +# /// script +# requires-python = ">=3.12" +# dependencies = [ +# "fastapi==0.162.0", "uvicorn==0.54.0", "python-multipart==0.0.33", +# "skillspector @ git+https://github.com/NVIDIA/skillspector.git@62c2fe8622f580ac292d4078c3b71f790194dbbd", +# ] +# /// +import asyncio +import hmac +import json +import os +import signal +import sys +import tempfile +from contextlib import suppress +from datetime import datetime, timezone +from pathlib import Path +from typing import Annotated, Final +from urllib.parse import quote, urlsplit + +from fastapi import Depends, FastAPI, File, Form, HTTPException, UploadFile +from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer +from pydantic import AwareDatetime, TypeAdapter, ValidationError + +MAX_UPLOAD: Final = 64 * 1024 * 1024 +MAX_REPORT: Final = 1024 * 1024 +SCAN_TIMEOUT: Final = 570 +SOURCE: Final = TypeAdapter(dict[str, str]) +SLOTS: Final = asyncio.Semaphore(2) +app: Final = FastAPI(title="SkillSpector adapter", docs_url=None, redoc_url=None, openapi_url=None) + + +def authenticate(credentials: Annotated[HTTPAuthorizationCredentials, Depends(HTTPBearer())]) -> None: + token: Final = os.environ.get("SKILL_SCANNER_API_KEY", "") + if not token or not hmac.compare_digest(credentials.credentials, token): + raise HTTPException(401, "Invalid scanner credentials") + + +def source_target(source: dict[str, str]) -> str: + target: Final = ( + "https://github.com/" + source.get("repo", "") if source.get("source") == "github" else source.get("url", "") + ) + parsed: Final = urlsplit(target) + if parsed.scheme != "https" or not parsed.hostname or parsed.username or parsed.password or parsed.fragment: + raise HTTPException(400, "Remote sources require an HTTPS URL without credentials or a fragment") + ref: Final = source.get("ref") + subdir: Final = source.get("path") + if ref or subdir: + if parsed.hostname != "github.com" or len(parsed.path.strip("/").split("/")) != 2 or not ref: + raise HTTPException(400, "Upload a ZIP to scan this source's exact ref and subdirectory") + suffix: Final = "/" + quote(subdir, safe="/") if subdir else "" + return target.removesuffix(".git").rstrip("/") + "/tree/" + quote(ref, safe="/") + suffix + return target + + +async def worker(target: str, output: Path, use_llm: bool) -> None: + from skillspector.mcp_server import run_scan + + result: Final = await run_scan(target, use_llm=use_llm, allow_local_targets=not target.startswith("https://")) + coverage: Final = result.get("analysis_completeness", {}) + findings: Final = result["findings"] + complete: Final = ( + result.get("execution_successful") is True + and coverage.get("is_complete") is True + and (not use_llm or (result.get("llm_available") is True and result.get("llm_used") is True)) + and len(findings) <= 500 + ) + limitations: Final = tuple(str(value)[:2000] for value in coverage.get("limitations", ())) + report: Final = { + "scanner_version": result["version"], + "complete": complete, + "scan_mode": result["scan_mode"], + "risk_score": result["risk_score"], + "findings": [ + { + "rule_id": finding["id"], + "severity": finding["severity"], + "message": finding.get("pattern") or finding.get("finding") or "Security finding", + "file": finding["location"]["file"], + "start_line": finding["location"].get("start_line"), + "explanation": finding.get("explanation"), + "remediation": finding.get("remediation"), + } + for finding in findings[:500] + ], + "limitations": ( + *limitations, + *(("Only the first 500 findings are displayed.",) if len(findings) > 500 else ()), + ), + } + encoded: Final = json.dumps(report).encode() + if len(encoded) > MAX_REPORT: + raise ValueError("Scanner report exceeded the response limit") + output.write_bytes(encoded) + + +async def run_worker(target: str, output: Path, use_llm: bool, expires_at: datetime | None = None) -> dict[str, object]: + timeout: Final = ( + SCAN_TIMEOUT + if expires_at is None + else min(SCAN_TIMEOUT, (expires_at - datetime.now(timezone.utc)).total_seconds()) + ) + if timeout <= 0: + raise HTTPException(504, "SkillSpector scan deadline expired") + process: Final = await asyncio.create_subprocess_exec( + sys.executable, + str(Path(__file__).resolve()), + "--scan", + target, + str(output), + str(use_llm).lower(), + stdout=asyncio.subprocess.DEVNULL, + stderr=asyncio.subprocess.DEVNULL, + start_new_session=True, + env={ + **os.environ, + "HOME": str(output.parent), + "TMPDIR": str(output.parent), + "GIT_CONFIG_GLOBAL": os.devnull, + "GIT_CONFIG_NOSYSTEM": "1", + "GIT_TERMINAL_PROMPT": "0", + "GIT_ALLOW_PROTOCOL": "https", + }, + ) + try: + code: Final = await asyncio.wait_for(process.wait(), timeout) + if code != 0 or not output.is_file() or output.stat().st_size > MAX_REPORT: + raise HTTPException(502, "SkillSpector could not produce a report for this source") + return TypeAdapter(dict[str, object]).validate_json(output.read_bytes()) + except TimeoutError: + raise HTTPException(504, "SkillSpector scan timed out") from None + finally: + with suppress(ProcessLookupError): + os.killpg(process.pid, signal.SIGKILL) + await process.wait() + + +@app.post("/scan", dependencies=[Depends(authenticate)]) +async def scan( + source: Annotated[str, Form(max_length=16384)], + use_llm: Annotated[bool, Form()] = False, + expires_at: Annotated[AwareDatetime | None, Form()] = None, + file: Annotated[UploadFile | None, File()] = None, +) -> dict[str, object]: + if SLOTS.locked(): + raise HTTPException(429, "Scanner is busy; try again shortly") + try: + parsed: Final = SOURCE.validate_json(source) + except ValidationError: + raise HTTPException(400, "Invalid source metadata") from None + async with SLOTS: + with tempfile.TemporaryDirectory(prefix="skill-scan-") as directory: + root: Final = Path(directory) + if file is not None: + content: Final = await file.read(MAX_UPLOAD + 1) + if len(content) > MAX_UPLOAD: + raise HTTPException(413, "Upload exceeds 64 MiB") + archive: Final = root / "skill.zip" + archive.write_bytes(content) + return await run_worker(str(archive), root / "report.json", use_llm, expires_at) + return await run_worker(source_target(parsed), root / "report.json", use_llm, expires_at) + + +if __name__ == "__main__": + if len(sys.argv) > 1 and sys.argv[1] == "--scan": + asyncio.run(worker(sys.argv[2], Path(sys.argv[3]), sys.argv[4] == "true")) + else: + import uvicorn + + if not os.environ.get("SKILL_SCANNER_API_KEY"): + raise SystemExit("Set SKILL_SCANNER_API_KEY before starting the scanner") + uvicorn.run(app, host="127.0.0.1", port=int(os.environ.get("PORT", "8099"))) diff --git a/enterprise/litellm_enterprise/proxy/common_utils/check_responses_cost.py b/enterprise/litellm_enterprise/proxy/common_utils/check_responses_cost.py index cfe4ca98145..69e36a0c076 100644 --- a/enterprise/litellm_enterprise/proxy/common_utils/check_responses_cost.py +++ b/enterprise/litellm_enterprise/proxy/common_utils/check_responses_cost.py @@ -200,7 +200,6 @@ async def log_billed_background_response(billed: BilledBackgroundResponse) -> Bi unpriced: Final = _without_read_price(billed.response) cost: Final = logging_obj.response_cost_calculator(result=unpriced) end_time: Final = datetime.now() - logging_obj.capture_usage_before_logging(unpriced, logging_obj.start_time, end_time) GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue( async_coroutine=logging_obj.async_success_handler( result=unpriced, start_time=logging_obj.start_time, end_time=end_time diff --git a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py index 0d46efbbb08..91c5e2c5f39 100644 --- a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py +++ b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py @@ -3,9 +3,11 @@ import asyncio import base64 +import copy import json import time from collections.abc import Awaitable, Callable, Iterator, Mapping, Sequence +from dataclasses import dataclass from datetime import datetime, timedelta from itertools import chain from types import MappingProxyType @@ -34,7 +36,7 @@ from typing_extensions import ReadOnly, Unpack import litellm from litellm import Router, verbose_logger -from litellm._internal_context import with_service_target +from litellm._internal_context import internal_sub_call, post_response_phase, with_service_target from litellm._uuid import uuid from litellm.caching.caching import DualCache from litellm.constants import ( @@ -95,6 +97,7 @@ from litellm.proxy.pass_through_endpoints.llm_provider_handlers.batch_attributio request_tags_from_metadata, ) from litellm.repositories.managed_file_repository import ManagedFileRepository +from litellm.responses.streaming_iterator import spawn_logging_task from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.types.llms.openai import ( # pyright: ignore[reportAttributeAccessIssue] AllMessageValues, @@ -395,6 +398,134 @@ class _RouterFileCallKwargs(TypedDict, total=False): custom_llm_provider: ReadOnly[str | None] +_MODEL_FILE_ID_MAPPING: Final = TypeAdapter(dict[str, str]) +_FILE_UPLOAD_ONLY_FIELDS: Final = frozenset({"file", "purpose", "expires_after", "extra_body"}) +_FILE_DELETE_RESERVED_FIELDS: Final = frozenset({"model", "file_id", "_litellm_internal_model_credentials"}) + + +@dataclass(frozen=True, slots=True) +class _ProviderUpload: + model_id: str + provider_file_id: str + upload_call_id: str | None = None + + +def _provider_uploads(file_object: OpenAIFileObject) -> tuple[_ProviderUpload, ...]: + file_hidden_params: Final = cast( # cast-ok: preserve mapping operations on dynamic file metadata + dict[str, object], getattr(file_object, HIDDEN_PARAMS_ATTR) + ) + model_file_id_mapping: Final = _MODEL_FILE_ID_MAPPING.validate_python( + file_hidden_params.get("model_file_id_mapping") or {} + ) + upload_call_id: Final = file_hidden_params.get("litellm_call_id") + return tuple( + _ProviderUpload( + model_id=model_id, + provider_file_id=provider_file_id, + upload_call_id=upload_call_id if isinstance(upload_call_id, str) else None, + ) + for model_id, provider_file_id in model_file_id_mapping.items() + ) + + +def _keeps_one_upload_per_target(llm_router: Router, model_id: str) -> bool: + credentials: Final = _provider_file_retrieve_credentials(llm_router=llm_router, model_id=model_id) + return (credentials or {}).get("custom_llm_provider") == LlmProviders.LITELLM_PROXY.value + + +def _is_kept_upload(uploads: Sequence[_ProviderUpload], index: int, per_target_model_ids: frozenset[str]) -> bool: + upload: Final = uploads[index] + other_uploads: Final = uploads[index + 1 :] if upload.model_id in per_target_model_ids else uploads[:index] + return all(other.model_id != upload.model_id for other in other_uploads) + + +def _upload_from_trailing_id_fields(decoded_unified_file_id: str) -> _ProviderUpload: + trailing_fields: Final = decoded_unified_file_id.rpartition(";llm_output_file_id,")[2] + provider_file_id, _, model_id = trailing_fields.partition(";llm_output_file_model_id,") + return _ProviderUpload(model_id=model_id, provider_file_id=provider_file_id) + + +def _carried_upload_missing_from(unified_file_id: str, model_file_ids: Mapping[str, str]) -> _ProviderUpload | None: + decoded: Final = _is_base64_encoded_unified_file_id(unified_file_id) + carried: Final = _upload_from_trailing_id_fields(decoded) if decoded else None + if carried is None or model_file_ids.get(carried.model_id) in (None, carried.provider_file_id): + return None + return carried + + +async def _delete_provider_file( + llm_router: Router, + model_id: str, + provider_file_id: str, + request_data: Mapping[str, object], +) -> None: + credentials: Final = llm_router.registry().credentials(model_id, form="with_provider") + delete_data: Final = { + **{k: v for k, v in request_data.items() if k not in _FILE_DELETE_RESERVED_FIELDS}, + **( + {"_litellm_internal_model_credentials": MappingProxyType(dict(credentials))} + if credentials is not None + else {} + ), + } + await llm_router.afile_delete( + model=model_id, + file_id=provider_file_id, + **cast(_RouterFileCallKwargs, delete_data), + ) + + +def _with_own_nested_dicts(request_data: Mapping[str, object]) -> MappingProxyType[str, object]: + return MappingProxyType({k: copy.copy(v) if isinstance(v, dict) else v for k, v in request_data.items()}) + + +async def _delete_redundant_upload( + llm_router: Router, + upload: _ProviderUpload, + delete_request: Mapping[str, object], + parent_call_id: str | None, +) -> None: + try: + with internal_sub_call(parent_call_id): + await _delete_provider_file( + llm_router, upload.model_id, upload.provider_file_id, _with_own_nested_dicts(delete_request) + ) + except Exception as error: + verbose_logger.warning( + f"Could not delete the redundant upload provider_file_id={sanitize_for_log(upload.provider_file_id)} " + f"at deployment model_id={sanitize_for_log(upload.model_id)}: " + f"{type(error).__name__} {sanitize_for_log(error)}" + ) + + +async def _delete_redundant_uploads( + llm_router: Router, + uploads: Sequence[_ProviderUpload], + delete_request: Mapping[str, object], +) -> None: + await asyncio.gather( + *(_delete_redundant_upload(llm_router, upload, delete_request, upload.upload_call_id) for upload in uploads) + ) + + +def _start_deleting_redundant_uploads( + llm_router: Router, + uploads: Sequence[_ProviderUpload], + create_file_request: CreateFileRequest, +) -> None: + if not uploads: + return + delete_request: Final = MappingProxyType( + {k: v for k, v in create_file_request.items() if k not in _FILE_UPLOAD_ONLY_FIELDS} + ) + with post_response_phase(): + spawn_logging_task( + asyncio.get_running_loop(), + _delete_redundant_uploads(llm_router, uploads, delete_request), + task_name="managed file repeat upload cleanup", + ) + + def _managed_database(prisma_client: _ManagedResourcePrismaClient) -> _ManagedResourceDatabase: return prisma_client.db @@ -2034,16 +2165,16 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): target_model_names_list=target_model_names_list, ) - ## STORE MODEL MAPPINGS IN DB - model_mappings: Dict[str, str] = {} - - for file_object in responses: - file_hidden_params = cast( # cast-ok: preserve mapping operations on dynamic file metadata - dict[str, object], getattr(file_object, HIDDEN_PARAMS_ATTR) - ) - model_file_id_mapping = file_hidden_params.get("model_file_id_mapping") - if model_file_id_mapping and isinstance(model_file_id_mapping, dict): - model_mappings.update(model_file_id_mapping) + uploads: Final = tuple(chain.from_iterable(map(_provider_uploads, responses))) + per_target_model_ids: Final = frozenset( + model_id + for model_id in {upload.model_id for upload in uploads} + if _keeps_one_upload_per_target(llm_router, model_id) + ) + kept_uploads: Final = tuple( + upload for index, upload in enumerate(uploads) if _is_kept_upload(uploads, index, per_target_model_ids) + ) + model_mappings: Final = {upload.model_id: upload.provider_file_id for upload in kept_uploads} await self.store_unified_file_id( file_id=response.id, @@ -2052,6 +2183,15 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): model_mappings=model_mappings, user_api_key_dict=user_api_key_dict, ) + _start_deleting_redundant_uploads( + llm_router, + tuple( + upload + for upload in uploads + if upload not in kept_uploads and upload.model_id not in per_target_model_ids + ), + create_file_request, + ) # Emit Prometheus metrics for managed file creation prom_logger = self._get_prometheus_logger() @@ -2692,23 +2832,13 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): specific_model_file_id_mapping: Final = model_file_id_mapping.get(file_id) if not specific_model_file_id_mapping: return - filtered_data: Final = { - k: v for k, v in data.items() if k not in ("model", "file_id", "_litellm_internal_model_credentials") - } for model_id, model_file_id in specific_model_file_id_mapping.items(): - credentials = llm_router.registry().credentials(model_id, form="with_provider") - delete_data = { - **filtered_data, - **( - {"_litellm_internal_model_credentials": MappingProxyType(dict(credentials))} - if credentials is not None - else {} - ), - } - await llm_router.afile_delete( - model=model_id, - file_id=model_file_id, - **cast(_RouterFileCallKwargs, delete_data), + await _delete_provider_file(llm_router, model_id, model_file_id, data) + unrecorded_upload: Final = _carried_upload_missing_from(file_id, specific_model_file_id_mapping) + delete_call_id: Final = data.get("litellm_call_id") + if unrecorded_upload is not None: + await _delete_redundant_upload( + llm_router, unrecorded_upload, data, delete_call_id if isinstance(delete_call_id, str) else None ) async def afile_content( diff --git a/enterprise/litellm_enterprise/types/enterprise_callbacks/send_emails.py b/enterprise/litellm_enterprise/types/enterprise_callbacks/send_emails.py index a2322d7f650..bb3b712d50b 100644 --- a/enterprise/litellm_enterprise/types/enterprise_callbacks/send_emails.py +++ b/enterprise/litellm_enterprise/types/enterprise_callbacks/send_emails.py @@ -1,9 +1,9 @@ import enum -from typing import Dict, List, Optional from pydantic import Field from litellm.proxy._types import WebhookEvent +from litellm.types.integrations.model_deprecation_email import MODEL_DEPRECATION_EMAIL_EVENT from litellm.types.llms.base import LiteLLMBaseModel @@ -26,7 +26,7 @@ class SendKeyCreatedEmailEvent(WebhookEvent): class SendKeyRotatedEmailEvent(WebhookEvent): virtual_key: str - key_alias: Optional[str] = None + key_alias: str | None = None """ The virtual key that was rotated this will be sk-123xxx, since we will be emailing this to the user to start using the new key @@ -34,23 +34,33 @@ class SendKeyRotatedEmailEvent(WebhookEvent): class EmailEvent(str, enum.Enum): + model_deprecations = MODEL_DEPRECATION_EMAIL_EVENT virtual_key_created = "Virtual Key Created" new_user_invitation = "New User Invitation" virtual_key_rotated = "Virtual Key Rotated" soft_budget_crossed = "Soft Budget Crossed" max_budget_alert = "Max Budget Alert" + class EmailEventSettings(LiteLLMBaseModel): event: EmailEvent enabled: bool + + class EmailEventSettingsUpdateRequest(LiteLLMBaseModel): - settings: List[EmailEventSettings] + settings: list[EmailEventSettings] + + class EmailEventSettingsResponse(LiteLLMBaseModel): - settings: List[EmailEventSettings] + settings: list[EmailEventSettings] + + class DefaultEmailSettings(LiteLLMBaseModel): """Default settings for email events""" - settings: Dict[EmailEvent, bool] = Field( + + settings: dict[EmailEvent, bool] = Field( default_factory=lambda: { + EmailEvent.model_deprecations: False, # Explicit opt-in for owner retirement reminders. EmailEvent.virtual_key_created: True, # On by default EmailEvent.new_user_invitation: True, # On by default EmailEvent.virtual_key_rotated: True, # On by default @@ -58,10 +68,12 @@ class DefaultEmailSettings(LiteLLMBaseModel): EmailEvent.max_budget_alert: True, # On by default } ) - def to_dict(self) -> Dict[str, bool]: + + def to_dict(self) -> dict[str, bool]: """Convert to dictionary with string keys for storage""" return {event.value: enabled for event, enabled in self.settings.items()} + @classmethod - def get_defaults(cls) -> Dict[str, bool]: + def get_defaults(cls) -> dict[str, bool]: """Get the default settings as a dictionary with string keys""" - return cls().to_dict() \ No newline at end of file + return cls().to_dict() diff --git a/helm/litellm-helm/Chart.yaml b/helm/litellm-helm/Chart.yaml index a3cb388ffc6..059889cb667 100644 --- a/helm/litellm-helm/Chart.yaml +++ b/helm/litellm-helm/Chart.yaml @@ -18,7 +18,7 @@ type: application # This is the chart version. This version number should be incremented each time you make changes # to the chart and its templates, including the app version. # Versions are expected to follow Semantic Versioning (https://semver.org/) -version: 1.1.3 +version: 1.1.4 # This is the version number of the application being deployed. This version number should be # incremented each time you make changes to the application. Versions are not expected to diff --git a/helm/litellm-helm/README.md b/helm/litellm-helm/README.md index 694cca05b52..bc6e29632f1 100644 --- a/helm/litellm-helm/README.md +++ b/helm/litellm-helm/README.md @@ -56,8 +56,8 @@ If `db.useStackgresOperator` is used (not yet implemented): | `billingMetrics.enabled` | Enable enterprise billable-request metering. Requires an enterprise license. | `false` | | `billingMetrics.endpoint` | Collector that the billable-request counter is pushed to. | `https://telemetry.litellm.ai` | -| `billingMetrics.secretName` | Name of an existing Secret holding the mTLS client certificate, under the keys `tls.crt` and `tls.key`. | `litellm-billing-metrics-mtls` | -| `billingMetrics.caSecretName` | Name of an existing Secret holding a CA bundle under the key `ca.crt`. Only needed for a private or test collector whose server certificate is not on the public web PKI. | `""` | +| `billingMetrics.tokenUrl` | Cognito OAuth2 client-credentials token endpoint. | `https://litellm-prod.auth.us-west-1.amazoncognito.com/oauth2/token` | +| `billingMetrics.secretName` | Name of an existing Secret with `client-id` and `client-secret` keys. | `litellm-billing-metrics` | | `billingMetrics.exportIntervalMs` | How often the counter is pushed, in milliseconds. The proxy defaults to `60000` when unset. | `""` | #### Example `proxy_config` ConfigMap from values (default): @@ -109,10 +109,10 @@ type: Opaque #### Enterprise billable-request metering -Enterprise licenses meter billable requests by pushing a counter to LiteLLM's collector over mutual TLS. The chart does not create the client certificate; it mounts one you already hold, read-only, so the private key is never exposed through the environment. Create the Secret under the name the chart expects, then turn the block on: +Enterprise licenses meter billable requests by pushing a counter to LiteLLM's collector with Cognito bearer authentication. Create a Secret with `client-id` and `client-secret` keys, then enable the chart values: ``` -kubectl create secret tls litellm-billing-metrics-mtls --cert=client.crt --key=client.key +kubectl create secret generic litellm-billing-metrics --from-literal=client-id=... --from-literal=client-secret=... ``` ``` @@ -120,7 +120,8 @@ billingMetrics: enabled: true ``` -Set `billingMetrics.caSecretName` only when the collector is a private or test one whose server certificate is not on the public web PKI; the production collector needs no CA override. The chart fails the render rather than deploying a proxy that silently never exports, so a missing `secretName` or an emptied `endpoint` surfaces at `helm install` time. +The endpoint and token URL must use HTTPS. The chart requires both URLs and +the Secret name when billing metrics are enabled ### Database Settings diff --git a/helm/litellm-helm/templates/_helpers.tpl b/helm/litellm-helm/templates/_helpers.tpl index 929fc415163..230d2acaeef 100644 --- a/helm/litellm-helm/templates/_helpers.tpl +++ b/helm/litellm-helm/templates/_helpers.tpl @@ -50,53 +50,27 @@ app.kubernetes.io/name: {{ include "litellm.name" . }} app.kubernetes.io/instance: {{ .Release.Name }} {{- end }} -{{/* -Enterprise billable-request metering. The client certificate identifies the -deployment to LiteLLM's collector, so it is mounted read-only from an existing -Secret rather than passed through the environment. -*/}} -{{- define "litellm.billingMetrics.certDir" -}}/etc/litellm/billing-mtls{{- end -}} -{{- define "litellm.billingMetrics.caDir" -}}/etc/litellm/billing-mtls-ca{{- end -}} - {{- define "litellm.billingMetricsEnv" -}} - name: LITELLM_BILLING_METRICS_ENDPOINT value: {{ required "billingMetrics.endpoint is required when billingMetrics.enabled is true" .Values.billingMetrics.endpoint | quote }} -- name: LITELLM_BILLING_METRICS_CLIENT_CERT - value: {{ printf "%s/tls.crt" (include "litellm.billingMetrics.certDir" .) | quote }} -- name: LITELLM_BILLING_METRICS_CLIENT_KEY - value: {{ printf "%s/tls.key" (include "litellm.billingMetrics.certDir" .) | quote }} -{{- if .Values.billingMetrics.caSecretName }} -- name: LITELLM_BILLING_METRICS_CA_CERT - value: {{ printf "%s/ca.crt" (include "litellm.billingMetrics.caDir" .) | quote }} -{{- end }} +- name: LITELLM_BILLING_METRICS_TOKEN_URL + value: {{ required "billingMetrics.tokenUrl is required when billingMetrics.enabled is true" .Values.billingMetrics.tokenUrl | quote }} +- name: LITELLM_BILLING_METRICS_CLIENT_ID + valueFrom: + secretKeyRef: + name: {{ required "billingMetrics.secretName is required when billingMetrics.enabled is true" .Values.billingMetrics.secretName }} + key: client-id +- name: LITELLM_BILLING_METRICS_CLIENT_SECRET + valueFrom: + secretKeyRef: + name: {{ required "billingMetrics.secretName is required when billingMetrics.enabled is true" .Values.billingMetrics.secretName }} + key: client-secret {{- with .Values.billingMetrics.exportIntervalMs }} - name: LITELLM_BILLING_METRICS_EXPORT_INTERVAL_MS value: {{ . | quote }} {{- end }} {{- end -}} -{{- define "litellm.billingMetricsVolumes" -}} -- name: billing-metrics-mtls - secret: - secretName: {{ required "billingMetrics.secretName is required when billingMetrics.enabled is true (an existing Secret with tls.crt and tls.key)" .Values.billingMetrics.secretName }} -{{- if .Values.billingMetrics.caSecretName }} -- name: billing-metrics-mtls-ca - secret: - secretName: {{ .Values.billingMetrics.caSecretName }} -{{- end }} -{{- end -}} - -{{- define "litellm.billingMetricsVolumeMounts" -}} -- name: billing-metrics-mtls - mountPath: {{ include "litellm.billingMetrics.certDir" . }} - readOnly: true -{{- if .Values.billingMetrics.caSecretName }} -- name: billing-metrics-mtls-ca - mountPath: {{ include "litellm.billingMetrics.caDir" . }} - readOnly: true -{{- end }} -{{- end -}} - {{/* Create the name of the service account to use */}} diff --git a/helm/litellm-helm/templates/deployment.yaml b/helm/litellm-helm/templates/deployment.yaml index 37e7eaec9e9..a37193f0efa 100644 --- a/helm/litellm-helm/templates/deployment.yaml +++ b/helm/litellm-helm/templates/deployment.yaml @@ -148,9 +148,6 @@ spec: - name: npm mountPath: /.npm {{- end }} - {{- if .Values.billingMetrics.enabled }} - {{- include "litellm.billingMetricsVolumeMounts" . | nindent 12 }} - {{- end }} {{- if include "litellm.collector.socketDir" . }} - name: collector-socket mountPath: {{ include "litellm.collector.socketDir" . }} @@ -234,9 +231,6 @@ spec: items: - key: {{ .Values.proxyConfigMap.key | default "config.yaml" }} path: "config.yaml" - {{- if .Values.billingMetrics.enabled }} - {{- include "litellm.billingMetricsVolumes" . | nindent 8 }} - {{- end }} {{- if include "litellm.collector.socketDir" . }} - name: collector-socket emptyDir: diff --git a/helm/litellm-helm/tests/billing_metrics_tests.yaml b/helm/litellm-helm/tests/billing_metrics_tests.yaml index 71803df378c..52185c8dd9d 100644 --- a/helm/litellm-helm/tests/billing_metrics_tests.yaml +++ b/helm/litellm-helm/tests/billing_metrics_tests.yaml @@ -1,31 +1,21 @@ -suite: test billingMetrics wiring on the proxy deployment +suite: test bearer-only billingMetrics wiring templates: - deployment.yaml - configmap-litellm.yaml - - migrations-job.yaml tests: - - it: is off by default, adding no env, volume, or mount + - it: is disabled by default template: deployment.yaml asserts: - - notContains: - path: spec.template.spec.volumes - content: - name: billing-metrics-mtls - secret: - secretName: litellm-billing-metrics-mtls - - notContains: - path: spec.template.spec.containers[0].volumeMounts - content: - name: billing-metrics-mtls - mountPath: /etc/litellm/billing-mtls - readOnly: true - notContains: path: spec.template.spec.containers[0].env content: name: LITELLM_BILLING_METRICS_ENDPOINT - value: https://telemetry.litellm.ai + - notContains: + path: spec.template.spec.volumes + content: + name: billing-metrics - - it: renders the endpoint and the mounted cert paths when enabled + - it: renders required URLs and Cognito secret references when enabled template: deployment.yaml set: billingMetrics: @@ -39,119 +29,34 @@ tests: - contains: path: spec.template.spec.containers[0].env content: - name: LITELLM_BILLING_METRICS_CLIENT_CERT - value: /etc/litellm/billing-mtls/tls.crt + name: LITELLM_BILLING_METRICS_TOKEN_URL + value: https://litellm-prod.auth.us-west-1.amazoncognito.com/oauth2/token - contains: path: spec.template.spec.containers[0].env content: - name: LITELLM_BILLING_METRICS_CLIENT_KEY - value: /etc/litellm/billing-mtls/tls.key - - # The conventional Secret name is the default, so enabling the block is enough. - - it: mounts the default cert secret read-only alongside the config volume - template: deployment.yaml - set: - billingMetrics: - enabled: true - asserts: - - contains: - path: spec.template.spec.volumes - content: - name: billing-metrics-mtls - secret: - secretName: litellm-billing-metrics-mtls - - contains: - path: spec.template.spec.containers[0].volumeMounts - content: - name: billing-metrics-mtls - mountPath: /etc/litellm/billing-mtls - readOnly: true - - - it: honours a secretName override - template: deployment.yaml - set: - billingMetrics: - enabled: true - secretName: my-billing-mtls - asserts: - - contains: - path: spec.template.spec.volumes - content: - name: billing-metrics-mtls - secret: - secretName: my-billing-mtls - - notContains: - path: spec.template.spec.volumes - content: - name: billing-metrics-mtls - secret: - secretName: litellm-billing-metrics-mtls - - - it: honours an endpoint override - template: deployment.yaml - set: - billingMetrics: - enabled: true - endpoint: https://collector.internal:4318 - asserts: + name: LITELLM_BILLING_METRICS_CLIENT_ID + valueFrom: + secretKeyRef: + name: litellm-billing-metrics + key: client-id - contains: path: spec.template.spec.containers[0].env content: - name: LITELLM_BILLING_METRICS_ENDPOINT - value: https://collector.internal:4318 - - # The production collector presents a public web-PKI certificate, so the CA - # override must stay absent unless a private collector is configured. - - it: omits the CA env, volume, and mount when no caSecretName is set - template: deployment.yaml - set: - billingMetrics: - enabled: true - asserts: + name: LITELLM_BILLING_METRICS_CLIENT_SECRET + valueFrom: + secretKeyRef: + name: litellm-billing-metrics + key: client-secret - notContains: path: spec.template.spec.volumes content: - name: billing-metrics-mtls-ca - secret: - secretName: billing-ca + name: billing-metrics - notContains: path: spec.template.spec.containers[0].volumeMounts content: - name: billing-metrics-mtls-ca - mountPath: /etc/litellm/billing-mtls-ca - readOnly: true - - notContains: - path: spec.template.spec.containers[0].env - content: - name: LITELLM_BILLING_METRICS_CA_CERT - value: /etc/litellm/billing-mtls-ca/ca.crt + name: billing-metrics - - it: mounts the CA secret when caSecretName is set - template: deployment.yaml - set: - billingMetrics: - enabled: true - caSecretName: billing-ca - asserts: - - contains: - path: spec.template.spec.containers[0].env - content: - name: LITELLM_BILLING_METRICS_CA_CERT - value: /etc/litellm/billing-mtls-ca/ca.crt - - contains: - path: spec.template.spec.volumes - content: - name: billing-metrics-mtls-ca - secret: - secretName: billing-ca - - contains: - path: spec.template.spec.containers[0].volumeMounts - content: - name: billing-metrics-mtls-ca - mountPath: /etc/litellm/billing-mtls-ca - readOnly: true - - - it: passes the export interval through only when set + - it: renders the export interval only when set template: deployment.yaml set: billingMetrics: @@ -164,129 +69,7 @@ tests: name: LITELLM_BILLING_METRICS_EXPORT_INTERVAL_MS value: "5000" - - it: omits the export interval when unset - template: deployment.yaml - set: - billingMetrics: - enabled: true - asserts: - - notContains: - path: spec.template.spec.containers[0].env - content: - name: LITELLM_BILLING_METRICS_EXPORT_INTERVAL_MS - value: "60000" - - # Kubernetes resolves duplicate env names last-wins, so the chart-owned billing - # entries must render after .Values.envVars or a user could silently redirect - # the metering export. The three billing entries are the last ones emitted here - # (migrationJob, which appends DISABLE_SCHEMA_UPDATE, is off for this case). - - it: renders the billing endpoint after envVars so it cannot be shadowed - template: deployment.yaml - set: - migrationJob: - enabled: false - billingMetrics: - enabled: true - envVars: - LITELLM_BILLING_METRICS_ENDPOINT: https://shadowed.example - asserts: - - contains: - path: spec.template.spec.containers[0].env - content: - name: LITELLM_BILLING_METRICS_ENDPOINT - value: https://shadowed.example - - equal: - path: spec.template.spec.containers[0].env[-3] - value: - name: LITELLM_BILLING_METRICS_ENDPOINT - value: https://telemetry.litellm.ai - - equal: - path: spec.template.spec.containers[0].env[-2].name - value: LITELLM_BILLING_METRICS_CLIENT_CERT - - equal: - path: spec.template.spec.containers[0].env[-1].name - value: LITELLM_BILLING_METRICS_CLIENT_KEY - - - it: keeps user-supplied volumes and mounts alongside the billing secret - template: deployment.yaml - set: - billingMetrics: - enabled: true - volumes: - - name: custom-callbacks - configMap: - name: my-callbacks - volumeMounts: - - name: custom-callbacks - mountPath: /app/callbacks - asserts: - - contains: - path: spec.template.spec.volumes - content: - name: custom-callbacks - configMap: - name: my-callbacks - - contains: - path: spec.template.spec.volumes - content: - name: billing-metrics-mtls - secret: - secretName: litellm-billing-metrics-mtls - - contains: - path: spec.template.spec.containers[0].volumeMounts - content: - name: custom-callbacks - mountPath: /app/callbacks - - contains: - path: spec.template.spec.containers[0].volumeMounts - content: - name: billing-metrics-mtls - mountPath: /etc/litellm/billing-mtls - readOnly: true - - - it: still mounts the proxy config when enabled - template: deployment.yaml - set: - billingMetrics: - enabled: true - asserts: - - contains: - path: spec.template.spec.containers[0].volumeMounts - content: - name: litellm-config - mountPath: /etc/litellm/config.yaml - subPath: config.yaml - - # Only the proxy serves billable traffic. The migrations Job must never mount - # the client certificate, and it renders its own env and volumes, so nothing - # stops a future edit from wiring the billing include into it by mistake. - - it: does not touch the migrations job when enabled - template: migrations-job.yaml - set: - billingMetrics: - enabled: true - asserts: - - notContains: - path: spec.template.spec.containers[0].env - content: - name: LITELLM_BILLING_METRICS_ENDPOINT - value: https://telemetry.litellm.ai - - notExists: - path: spec.template.spec.containers[0].volumeMounts - - notExists: - path: spec.template.spec.volumes - - - it: fails loudly when enabled with an emptied secretName - template: deployment.yaml - set: - billingMetrics: - enabled: true - secretName: "" - asserts: - - failedTemplate: - errorMessage: billingMetrics.secretName is required when billingMetrics.enabled is true (an existing Secret with tls.crt and tls.key) - - - it: fails loudly when enabled without an endpoint + - it: requires the endpoint when enabled template: deployment.yaml set: billingMetrics: @@ -295,3 +78,23 @@ tests: asserts: - failedTemplate: errorMessage: billingMetrics.endpoint is required when billingMetrics.enabled is true + + - it: requires the token URL when enabled + template: deployment.yaml + set: + billingMetrics: + enabled: true + tokenUrl: "" + asserts: + - failedTemplate: + errorMessage: billingMetrics.tokenUrl is required when billingMetrics.enabled is true + + - it: requires the secret name when enabled + template: deployment.yaml + set: + billingMetrics: + enabled: true + secretName: "" + asserts: + - failedTemplate: + errorMessage: billingMetrics.secretName is required when billingMetrics.enabled is true diff --git a/helm/litellm-helm/tests/collector_tests.yaml b/helm/litellm-helm/tests/collector_tests.yaml index 0340b1161b7..1365290e16c 100644 --- a/helm/litellm-helm/tests/collector_tests.yaml +++ b/helm/litellm-helm/tests/collector_tests.yaml @@ -191,7 +191,7 @@ tests: metricsServer.port: 9090 billingMetrics.enabled: true billingMetrics.endpoint: https://metering.example.com - billingMetrics.secretName: billing-mtls + billingMetrics.secretName: billing-metrics asserts: - contains: path: spec.template.spec.containers[0].env @@ -214,9 +214,9 @@ tests: name: LITELLM_BILLING_METRICS_ENDPOINT any: true - notContains: - path: spec.template.spec.containers[1].volumeMounts + path: spec.template.spec.containers[1].env content: - name: billing-metrics-mtls + name: LITELLM_BILLING_METRICS_CLIENT_SECRET any: true - it: should give the sidecar the same scratch mounts as the proxy on a read-only root diff --git a/helm/litellm-helm/values.yaml b/helm/litellm-helm/values.yaml index f51f8bdd173..9afce050261 100644 --- a/helm/litellm-helm/values.yaml +++ b/helm/litellm-helm/values.yaml @@ -154,19 +154,13 @@ masterkeySecretName: "" # if set, use this secret key for the master key; otherwise, use the default key masterkeySecretKey: "" -# Optional: enterprise billable-request metering. When enabled, the proxy counts -# successful requests to inference, MCP, and A2A endpoints and pushes them to -# LiteLLM's collector over mutual TLS. Requires an enterprise license. -# The client certificate identifies the deployment, so it is mounted read-only -# from an existing Secret and never passed through the environment. +# Optional: enterprise billable-request metering. Requires an enterprise license. billingMetrics: enabled: false - endpoint: https://telemetry.litellm.ai # collector to push the counter to - secretName: litellm-billing-metrics-mtls # existing Secret holding tls.crt and tls.key - # Only for private or test collectors whose server certificate is not on the - # public web PKI. The production collector needs no CA override. - caSecretName: "" # existing Secret holding ca.crt - exportIntervalMs: "" # push cadence; the proxy defaults to 60000 + endpoint: https://telemetry.litellm.ai + tokenUrl: https://litellm-prod.auth.us-west-1.amazoncognito.com/oauth2/token + secretName: litellm-billing-metrics + exportIntervalMs: "" proxyConfigMap: # when true, creates a new configmap diff --git a/helm/litellm/Chart.yaml b/helm/litellm/Chart.yaml index e67f5790c7e..341172da925 100644 --- a/helm/litellm/Chart.yaml +++ b/helm/litellm/Chart.yaml @@ -2,7 +2,7 @@ apiVersion: v2 name: litellm description: LiteLLM componentized — gateway, UI backend, and UI as separate services type: application -version: 0.1.0 +version: 0.1.1 appVersion: "0.1.0" annotations: org.opencontainers.image.source: "https://github.com/BerriAI/litellm" diff --git a/helm/litellm/README.md b/helm/litellm/README.md index 97b94754402..d66bb3284bf 100644 --- a/helm/litellm/README.md +++ b/helm/litellm/README.md @@ -22,6 +22,23 @@ backend: gatewayUrl: https://gateway.example.com ``` +## Enterprise billing metrics + +Billing metrics use Cognito bearer authentication. Create the Secret with +`client-id` and `client-secret` keys, then enable billing metrics: + +```bash +kubectl create secret generic litellm-billing-metrics --from-literal=client-id=... --from-literal=client-secret=... +``` + +```yaml +billingMetrics: + enabled: true +``` + +The chart requires an HTTPS endpoint, an HTTPS token URL, and the Secret name +when billing metrics are enabled + ## Routes to another Service For a shared hostname, `ingress.extraPaths` can route to a Service in the same namespace using `serviceName` and `servicePort`. The port can be a number or a named Service port. Omit `service` when using these fields diff --git a/helm/litellm/templates/_helpers.tpl b/helm/litellm/templates/_helpers.tpl index 18e938564e9..b704782f5d1 100644 --- a/helm/litellm/templates/_helpers.tpl +++ b/helm/litellm/templates/_helpers.tpl @@ -58,56 +58,27 @@ app.kubernetes.io/managed-by: {{ .Release.Service }} helm.sh/chart: {{ printf "%s-%s" .Chart.Name .Chart.Version | replace "+" "_" }} {{- end -}} -{{/* -Enterprise billable-request metering. Wired into gateway and backend, not the -migrations job. The gateway serves nearly all billable traffic, but the backend -keeps the named-server MCP transport (/{mcp_server_name}/mcp), which writes a -SpendLogs row, so metering only the gateway would silently drop that traffic. -The client certificate identifies the deployment to LiteLLM's collector, so it is -mounted read-only from an existing Secret rather than passed through the -environment. -*/}} -{{- define "litellm.billingMetrics.certDir" -}}/etc/litellm/billing-mtls{{- end -}} -{{- define "litellm.billingMetrics.caDir" -}}/etc/litellm/billing-mtls-ca{{- end -}} - {{- define "litellm.billingMetricsEnv" -}} - name: LITELLM_BILLING_METRICS_ENDPOINT value: {{ required "billingMetrics.endpoint is required when billingMetrics.enabled is true" .Values.billingMetrics.endpoint | quote }} -- name: LITELLM_BILLING_METRICS_CLIENT_CERT - value: {{ printf "%s/tls.crt" (include "litellm.billingMetrics.certDir" .) | quote }} -- name: LITELLM_BILLING_METRICS_CLIENT_KEY - value: {{ printf "%s/tls.key" (include "litellm.billingMetrics.certDir" .) | quote }} -{{- if .Values.billingMetrics.caSecretName }} -- name: LITELLM_BILLING_METRICS_CA_CERT - value: {{ printf "%s/ca.crt" (include "litellm.billingMetrics.caDir" .) | quote }} -{{- end }} +- name: LITELLM_BILLING_METRICS_TOKEN_URL + value: {{ required "billingMetrics.tokenUrl is required when billingMetrics.enabled is true" .Values.billingMetrics.tokenUrl | quote }} +- name: LITELLM_BILLING_METRICS_CLIENT_ID + valueFrom: + secretKeyRef: + name: {{ required "billingMetrics.secretName is required when billingMetrics.enabled is true" .Values.billingMetrics.secretName }} + key: client-id +- name: LITELLM_BILLING_METRICS_CLIENT_SECRET + valueFrom: + secretKeyRef: + name: {{ required "billingMetrics.secretName is required when billingMetrics.enabled is true" .Values.billingMetrics.secretName }} + key: client-secret {{- with .Values.billingMetrics.exportIntervalMs }} - name: LITELLM_BILLING_METRICS_EXPORT_INTERVAL_MS value: {{ . | quote }} {{- end }} {{- end -}} -{{- define "litellm.billingMetricsVolumes" -}} -- name: billing-metrics-mtls - secret: - secretName: {{ required "billingMetrics.secretName is required when billingMetrics.enabled is true (an existing Secret with tls.crt and tls.key)" .Values.billingMetrics.secretName }} -{{- if .Values.billingMetrics.caSecretName }} -- name: billing-metrics-mtls-ca - secret: - secretName: {{ .Values.billingMetrics.caSecretName }} -{{- end }} -{{- end -}} - -{{- define "litellm.billingMetricsVolumeMounts" -}} -- name: billing-metrics-mtls - mountPath: {{ include "litellm.billingMetrics.certDir" . }} - readOnly: true -{{- if .Values.billingMetrics.caSecretName }} -- name: billing-metrics-mtls-ca - mountPath: {{ include "litellm.billingMetrics.caDir" . }} - readOnly: true -{{- end }} -{{- end -}} {{/* Per-component selector labels — used in both Service selectors and Deployment matchLabels. diff --git a/helm/litellm/templates/backend/deployment.yaml b/helm/litellm/templates/backend/deployment.yaml index 7360261dab1..7db14ad87a5 100644 --- a/helm/litellm/templates/backend/deployment.yaml +++ b/helm/litellm/templates/backend/deployment.yaml @@ -79,16 +79,13 @@ spec: {{- include "litellm.billingMetricsEnv" . | nindent 12 }} {{- end }} {{- include "litellm.envFrom" .Values.backend | nindent 10 }} - {{- if or .Values.gateway.config.create .Values.backend.volumeMounts .Values.billingMetrics.enabled }} + {{- if or .Values.gateway.config.create .Values.backend.volumeMounts }} volumeMounts: {{- if .Values.gateway.config.create }} - name: gateway-config mountPath: /app/config/config.yaml subPath: config.yaml {{- end }} - {{- if .Values.billingMetrics.enabled }} - {{- include "litellm.billingMetricsVolumeMounts" . | nindent 12 }} - {{- end }} {{- with .Values.backend.volumeMounts }} {{- toYaml . | nindent 12 }} {{- end }} @@ -114,16 +111,13 @@ spec: {{- with .Values.backend.extraContainers }} {{- tpl (toYaml .) $ | nindent 8 }} {{- end }} - {{- if or .Values.gateway.config.create .Values.backend.volumes .Values.billingMetrics.enabled }} + {{- if or .Values.gateway.config.create .Values.backend.volumes }} volumes: {{- if .Values.gateway.config.create }} - name: gateway-config configMap: name: {{ include "litellm.gateway.fullname" . }}-config {{- end }} - {{- if .Values.billingMetrics.enabled }} - {{- include "litellm.billingMetricsVolumes" . | nindent 8 }} - {{- end }} {{- with .Values.backend.volumes }} {{- toYaml . | nindent 8 }} {{- end }} diff --git a/helm/litellm/templates/gateway/deployment.yaml b/helm/litellm/templates/gateway/deployment.yaml index b0e7f0dcebb..987109e361e 100644 --- a/helm/litellm/templates/gateway/deployment.yaml +++ b/helm/litellm/templates/gateway/deployment.yaml @@ -86,7 +86,7 @@ spec: {{- include "litellm.gateway.collectorEnv" . | nindent 12 }} {{- end }} {{- include "litellm.envFrom" .Values.gateway | nindent 10 }} - {{- if or .Values.gateway.config.create .Values.gateway.volumeMounts .Values.billingMetrics.enabled .Values.gateway.metricsServer.enabled (include "litellm.gateway.collectorSocketDir" .) }} + {{- if or .Values.gateway.config.create .Values.gateway.volumeMounts .Values.gateway.metricsServer.enabled (include "litellm.gateway.collectorSocketDir" .) }} volumeMounts: {{- if .Values.gateway.config.create }} - name: gateway-config @@ -101,9 +101,6 @@ spec: - name: collector-socket mountPath: {{ include "litellm.gateway.collectorSocketDir" . }} {{- end }} - {{- if .Values.billingMetrics.enabled }} - {{- include "litellm.billingMetricsVolumeMounts" . | nindent 12 }} - {{- end }} {{- with .Values.gateway.volumeMounts }} {{- toYaml . | nindent 12 }} {{- end }} @@ -206,7 +203,7 @@ spec: {{- with .Values.gateway.extraContainers }} {{- tpl (toYaml .) $ | nindent 8 }} {{- end }} - {{- if or .Values.gateway.config.create .Values.gateway.volumes .Values.billingMetrics.enabled .Values.gateway.metricsServer.enabled (include "litellm.gateway.collectorSocketDir" .) }} + {{- if or .Values.gateway.config.create .Values.gateway.volumes .Values.gateway.metricsServer.enabled (include "litellm.gateway.collectorSocketDir" .) }} volumes: {{- if .Values.gateway.config.create }} - name: gateway-config @@ -222,9 +219,6 @@ spec: emptyDir: sizeLimit: 1Mi {{- end }} - {{- if .Values.billingMetrics.enabled }} - {{- include "litellm.billingMetricsVolumes" . | nindent 8 }} - {{- end }} {{- with .Values.gateway.volumes }} {{- toYaml . | nindent 8 }} {{- end }} diff --git a/helm/litellm/tests/billing_metrics_tests.yaml b/helm/litellm/tests/billing_metrics_tests.yaml index ceba0bd1430..d17b8192fce 100644 --- a/helm/litellm/tests/billing_metrics_tests.yaml +++ b/helm/litellm/tests/billing_metrics_tests.yaml @@ -1,39 +1,30 @@ -suite: test billingMetrics wiring on gateway and backend +suite: test bearer-only billingMetrics wiring templates: - gateway/deployment.yaml - gateway/configmap.yaml - backend/deployment.yaml + - backend/configmap.yaml - migrations-job.yaml values: - ./values/required.yaml tests: - - it: is off by default, adding no env, volume, or mount + - it: is disabled by default template: gateway/deployment.yaml asserts: - - notContains: - path: spec.template.spec.volumes - content: - name: billing-metrics-mtls - secret: - secretName: billing-mtls - - equal: - path: spec.template.spec.containers[0].volumeMounts - value: - - name: gateway-config - mountPath: /app/config/config.yaml - subPath: config.yaml - notContains: path: spec.template.spec.containers[0].env content: name: LITELLM_BILLING_METRICS_ENDPOINT - value: https://telemetry.litellm.ai + - notContains: + path: spec.template.spec.volumes + content: + name: billing-metrics - - it: renders the endpoint and the mounted cert paths when enabled + - it: wires gateway URLs and bearer credentials from Secret keys template: gateway/deployment.yaml set: billingMetrics: enabled: true - secretName: billing-mtls asserts: - contains: path: spec.template.spec.containers[0].env @@ -43,87 +34,68 @@ tests: - contains: path: spec.template.spec.containers[0].env content: - name: LITELLM_BILLING_METRICS_CLIENT_CERT - value: /etc/litellm/billing-mtls/tls.crt + name: LITELLM_BILLING_METRICS_TOKEN_URL + value: https://litellm-prod.auth.us-west-1.amazoncognito.com/oauth2/token - contains: path: spec.template.spec.containers[0].env content: - name: LITELLM_BILLING_METRICS_CLIENT_KEY - value: /etc/litellm/billing-mtls/tls.key - - - it: mounts the cert secret read-only alongside the config volume - template: gateway/deployment.yaml - set: - billingMetrics: - enabled: true - secretName: billing-mtls - asserts: + name: LITELLM_BILLING_METRICS_CLIENT_ID + valueFrom: + secretKeyRef: + name: litellm-billing-metrics + key: client-id - contains: - path: spec.template.spec.volumes + path: spec.template.spec.containers[0].env content: - name: billing-metrics-mtls - secret: - secretName: billing-mtls - - contains: - path: spec.template.spec.containers[0].volumeMounts - content: - name: billing-metrics-mtls - mountPath: /etc/litellm/billing-mtls - readOnly: true - - # The production collector presents a public web-PKI certificate, so the CA - # override must stay absent unless a private collector is configured. - - it: omits the CA env, volume, and mount when no caSecretName is set - template: gateway/deployment.yaml - set: - billingMetrics: - enabled: true - secretName: billing-mtls - asserts: + name: LITELLM_BILLING_METRICS_CLIENT_SECRET + valueFrom: + secretKeyRef: + name: litellm-billing-metrics + key: client-secret - notContains: path: spec.template.spec.volumes content: - name: billing-metrics-mtls-ca - secret: - secretName: billing-ca + name: billing-metrics - notContains: - path: spec.template.spec.containers[0].env + path: spec.template.spec.containers[0].volumeMounts content: - name: LITELLM_BILLING_METRICS_CA_CERT - value: /etc/litellm/billing-mtls-ca/ca.crt + name: billing-metrics - - it: mounts the CA secret when caSecretName is set - template: gateway/deployment.yaml + - it: wires billing metrics on the backend without volumes + template: backend/deployment.yaml set: billingMetrics: enabled: true - secretName: billing-mtls - caSecretName: billing-ca asserts: - contains: path: spec.template.spec.containers[0].env content: - name: LITELLM_BILLING_METRICS_CA_CERT - value: /etc/litellm/billing-mtls-ca/ca.crt - - contains: + name: LITELLM_BILLING_METRICS_CLIENT_SECRET + valueFrom: + secretKeyRef: + name: litellm-billing-metrics + key: client-secret + - notContains: path: spec.template.spec.volumes content: - name: billing-metrics-mtls-ca - secret: - secretName: billing-ca - - contains: - path: spec.template.spec.containers[0].volumeMounts - content: - name: billing-metrics-mtls-ca - mountPath: /etc/litellm/billing-mtls-ca - readOnly: true + name: billing-metrics - - it: passes the export interval through only when set + - it: does not add billing metrics to migrations + template: migrations-job.yaml + set: + billingMetrics: + enabled: true + asserts: + - notContains: + path: spec.template.spec.containers[0].env + content: + name: LITELLM_BILLING_METRICS_ENDPOINT + + - it: renders an optional export interval template: gateway/deployment.yaml set: billingMetrics: enabled: true - secretName: billing-mtls exportIntervalMs: 5000 asserts: - contains: @@ -132,102 +104,27 @@ tests: name: LITELLM_BILLING_METRICS_EXPORT_INTERVAL_MS value: "5000" - - it: keeps user-supplied gateway volumes alongside the billing secret + - it: requires the endpoint when enabled template: gateway/deployment.yaml set: billingMetrics: enabled: true - secretName: billing-mtls - gateway.volumes: - - name: custom-callbacks - configMap: - name: my-callbacks - gateway.volumeMounts: - - name: custom-callbacks - mountPath: /app/callbacks + endpoint: "" asserts: - - contains: - path: spec.template.spec.volumes - content: - name: custom-callbacks - configMap: - name: my-callbacks - - contains: - path: spec.template.spec.volumes - content: - name: billing-metrics-mtls - secret: - secretName: billing-mtls + - failedTemplate: + errorMessage: billingMetrics.endpoint is required when billingMetrics.enabled is true - # The backend keeps the named-server MCP transport (/{mcp_server_name}/mcp), - # which writes a SpendLogs row, so it must meter too or that traffic is lost. - - it: meters the backend as well, since it serves the MCP transport - template: backend/deployment.yaml - set: - billingMetrics: - enabled: true - secretName: billing-mtls - asserts: - - contains: - path: spec.template.spec.containers[0].env - content: - name: LITELLM_BILLING_METRICS_ENDPOINT - value: https://telemetry.litellm.ai - - contains: - path: spec.template.spec.containers[0].volumeMounts - content: - name: billing-metrics-mtls - mountPath: /etc/litellm/billing-mtls - readOnly: true - - contains: - path: spec.template.spec.volumes - content: - name: billing-metrics-mtls - secret: - secretName: billing-mtls - - - it: leaves the backend alone when metering is off - template: backend/deployment.yaml - asserts: - - notContains: - path: spec.template.spec.containers[0].env - content: - name: LITELLM_BILLING_METRICS_ENDPOINT - value: https://telemetry.litellm.ai - - # The migrations job runs prisma and serves no traffic; it must never receive - # the client key. - - it: never mounts the billing cert on the migrations job - template: migrations-job.yaml - set: - billingMetrics: - enabled: true - secretName: billing-mtls - asserts: - - notContains: - path: spec.template.spec.containers[0].env - content: - name: LITELLM_BILLING_METRICS_ENDPOINT - value: https://telemetry.litellm.ai - - isNull: - path: spec.template.spec.volumes - - # The conventional Secret name is the default, so enabling metering needs no - # secretName at all; the guard below only fires on an explicitly blanked one. - - it: uses the conventional secret name by default + - it: requires the token URL when enabled template: gateway/deployment.yaml set: billingMetrics: enabled: true + tokenUrl: "" asserts: - - contains: - path: spec.template.spec.volumes - content: - name: billing-metrics-mtls - secret: - secretName: litellm-billing-metrics-mtls + - failedTemplate: + errorMessage: billingMetrics.tokenUrl is required when billingMetrics.enabled is true - - it: fails loudly when the secretName is explicitly blanked + - it: requires the secret name when enabled template: gateway/deployment.yaml set: billingMetrics: @@ -235,15 +132,4 @@ tests: secretName: "" asserts: - failedTemplate: - errorMessage: billingMetrics.secretName is required when billingMetrics.enabled is true (an existing Secret with tls.crt and tls.key) - - - it: fails loudly when enabled without an endpoint - template: gateway/deployment.yaml - set: - billingMetrics: - enabled: true - endpoint: "" - secretName: billing-mtls - asserts: - - failedTemplate: - errorMessage: billingMetrics.endpoint is required when billingMetrics.enabled is true + errorMessage: billingMetrics.secretName is required when billingMetrics.enabled is true diff --git a/helm/litellm/tests/migration_job_tests.yaml b/helm/litellm/tests/migration_job_tests.yaml index 2ebb1b44926..b9e52ba7123 100644 --- a/helm/litellm/tests/migration_job_tests.yaml +++ b/helm/litellm/tests/migration_job_tests.yaml @@ -91,7 +91,7 @@ tests: app.kubernetes.io/name: litellm app.kubernetes.io/instance: RELEASE-NAME app.kubernetes.io/managed-by: Helm - helm.sh/chart: litellm-0.1.0 + helm.sh/chart: litellm-0.1.1 app.kubernetes.io/component: migrations - it: renders pod-level and container-level securityContext in their own scopes diff --git a/helm/litellm/values.yaml b/helm/litellm/values.yaml index 92a48153c5a..cb37656cb77 100644 --- a/helm/litellm/values.yaml +++ b/helm/litellm/values.yaml @@ -180,23 +180,14 @@ masterKey: secretKey: master-key # Optional: enterprise billable-request metering. When enabled, the gateway and -# backend count successful requests to inference, MCP, and A2A endpoints and push -# them to LiteLLM's collector over mutual TLS. Both components serve billable -# routes: the backend keeps the named-server MCP transport. Requires an -# enterprise license. The client certificate identifies the deployment, so it is -# mounted read-only from an existing Secret and never passed through the env. +# backend count successful requests to inference, MCP, and A2A endpoints. Requires +# an enterprise license. billingMetrics: enabled: false - endpoint: https://telemetry.litellm.ai # collector to push the counter to - # An existing Secret holding the client certificate under tls.crt and its key - # under tls.key, usually created from the onboarding artifact. The default is - # the conventional name, so the common path is to create that Secret and set - # enabled: true. Override only if yours is named differently. - secretName: litellm-billing-metrics-mtls - # Only for private or test collectors whose server certificate is not on the - # public web PKI. The production collector needs no CA override. - caSecretName: "" # existing Secret holding ca.crt - exportIntervalMs: "" # push cadence; the proxy defaults to 60000 + endpoint: https://telemetry.litellm.ai + tokenUrl: https://litellm-prod.auth.us-west-1.amazoncognito.com/oauth2/token + secretName: litellm-billing-metrics + exportIntervalMs: "" # External Postgres connection. database: diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20261103010000_spendlogs_accounting_delivery/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261103010000_spendlogs_accounting_delivery/migration.sql new file mode 100644 index 00000000000..b00cf892b68 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261103010000_spendlogs_accounting_delivery/migration.sql @@ -0,0 +1,19 @@ +SET LOCAL lock_timeout = '10s'; +CREATE TABLE IF NOT EXISTS "LiteLLM_SpendLogDelivery" ( + "delivery_id" TEXT PRIMARY KEY DEFAULT gen_random_uuid()::text, + "request_id" TEXT NOT NULL, + "state" "AccountingDeliveryState" NOT NULL DEFAULT 'pending', + "attempts" INTEGER NOT NULL DEFAULT 0, + "next_attempt_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP, + "applied_at" TIMESTAMP(3), + "last_error" TEXT, + "created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP, + "accounting_payload" JSONB NOT NULL, + "is_batch" BOOLEAN NOT NULL +); +CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogDelivery_state_next_attempt_at_idx" + ON "LiteLLM_SpendLogDelivery" ("state", "next_attempt_at"); +CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogDelivery_state_applied_at_idx" + ON "LiteLLM_SpendLogDelivery" ("state", "applied_at"); +CREATE INDEX IF NOT EXISTS "LiteLLM_SpendLogDelivery_request_id_idx" + ON "LiteLLM_SpendLogDelivery" ("request_id"); diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20261104000000_skill_zip_upload/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261104000000_skill_zip_upload/migration.sql new file mode 100644 index 00000000000..acbe87515d9 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261104000000_skill_zip_upload/migration.sql @@ -0,0 +1,9 @@ +SET LOCAL lock_timeout = '10s'; + +CREATE TABLE IF NOT EXISTS "LiteLLM_ClaudeCodePluginUpload" ( + "plugin_name" TEXT NOT NULL, + "content" BYTEA NOT NULL, + CONSTRAINT "LiteLLM_ClaudeCodePluginUpload_pkey" PRIMARY KEY ("plugin_name"), + CONSTRAINT "LiteLLM_ClaudeCodePluginUpload_plugin_name_fkey" FOREIGN KEY ("plugin_name") + REFERENCES "LiteLLM_ClaudeCodePluginTable"("name") ON DELETE CASCADE ON UPDATE CASCADE +); diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20261104010000_drop_accounting_event_tables/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261104010000_drop_accounting_event_tables/migration.sql new file mode 100644 index 00000000000..cba6a18368f --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261104010000_drop_accounting_event_tables/migration.sql @@ -0,0 +1,5 @@ +SET LOCAL lock_timeout = '10s'; +DROP TABLE IF EXISTS "LiteLLM_AccountingDelivery"; +DROP TABLE IF EXISTS "LiteLLM_AccountingEvent"; +DROP TYPE IF EXISTS "AccountingDeliveryTarget"; +DROP TYPE IF EXISTS "AccountingEventKind"; diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105000000_skill_version_history/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105000000_skill_version_history/migration.sql new file mode 100644 index 00000000000..ecfa7321d87 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105000000_skill_version_history/migration.sql @@ -0,0 +1,16 @@ +SET LOCAL lock_timeout = '10s'; +CREATE TABLE IF NOT EXISTS "LiteLLM_ClaudeCodePluginVersion" ( + "id" TEXT NOT NULL, + "plugin_id" TEXT NOT NULL, + "version" TEXT, + "description" TEXT, + "manifest_json" TEXT, + "published_at" TIMESTAMP(3), + "published_by" TEXT, + "archive_available" BOOLEAN NOT NULL DEFAULT false, + "content" BYTEA, + CONSTRAINT "LiteLLM_ClaudeCodePluginVersion_pkey" PRIMARY KEY ("id"), + CONSTRAINT "LiteLLM_ClaudeCodePluginVersion_plugin_id_fkey" FOREIGN KEY ("plugin_id") REFERENCES "LiteLLM_ClaudeCodePluginTable"("id") ON DELETE CASCADE ON UPDATE CASCADE +); +CREATE UNIQUE INDEX IF NOT EXISTS "LiteLLM_ClaudeCodePluginVersion_plugin_id_version_key" ON "LiteLLM_ClaudeCodePluginVersion"("plugin_id", "version"); +CREATE INDEX IF NOT EXISTS "LiteLLM_ClaudeCodePluginVersion_plugin_id_published_at_idx" ON "LiteLLM_ClaudeCodePluginVersion"("plugin_id", "published_at"); diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105010000_skill_submissions/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105010000_skill_submissions/migration.sql new file mode 100644 index 00000000000..e7975258ca9 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105010000_skill_submissions/migration.sql @@ -0,0 +1,27 @@ +SET LOCAL lock_timeout = '10s'; + +CREATE TABLE IF NOT EXISTS "LiteLLM_SkillSubmission" ( + "id" TEXT NOT NULL, + "plugin_name" TEXT NOT NULL, + "operation" TEXT NOT NULL, + "status" TEXT NOT NULL DEFAULT 'pending_review', + "proposal_json" TEXT NOT NULL, + "archive_content" BYTEA, + "submitted_by" TEXT NOT NULL, + "created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP, + "base_plugin_id" TEXT, + "base_updated_at" TIMESTAMP(3), + "reviewed_by" TEXT, + "reviewed_at" TIMESTAMP(3), + "rejection_reason" TEXT, + CONSTRAINT "LiteLLM_SkillSubmission_pkey" PRIMARY KEY ("id") +); + +CREATE INDEX IF NOT EXISTS "LiteLLM_SkillSubmission_submitted_by_created_at_id_idx" + ON "LiteLLM_SkillSubmission"("submitted_by", "created_at" DESC, "id" DESC); +CREATE INDEX IF NOT EXISTS "LiteLLM_SkillSubmission_submitted_by_status_created_at_id_idx" + ON "LiteLLM_SkillSubmission"("submitted_by", "status", "created_at" DESC, "id" DESC); +CREATE INDEX IF NOT EXISTS "LiteLLM_SkillSubmission_status_created_at_id_idx" + ON "LiteLLM_SkillSubmission"("status", "created_at" DESC, "id" DESC); +CREATE INDEX IF NOT EXISTS "LiteLLM_SkillSubmission_created_at_id_idx" + ON "LiteLLM_SkillSubmission"("created_at" DESC, "id" DESC); diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105020000_skill_scanning/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105020000_skill_scanning/migration.sql new file mode 100644 index 00000000000..6b70cca4a9a --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105020000_skill_scanning/migration.sql @@ -0,0 +1,3 @@ +SET LOCAL lock_timeout = '10s'; + +ALTER TABLE "LiteLLM_SkillSubmission" ADD COLUMN IF NOT EXISTS "scan_json" TEXT; diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105094500_add_skill_download_history/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105094500_add_skill_download_history/migration.sql new file mode 100644 index 00000000000..43e26b324a0 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20261105094500_add_skill_download_history/migration.sql @@ -0,0 +1,37 @@ +SET LOCAL lock_timeout = '10s'; + +DO $$ +BEGIN + IF NOT EXISTS ( + SELECT 1 FROM pg_attribute + WHERE attrelid = to_regclass('"LiteLLM_ClaudeCodePluginTable"') + AND attname = 'anonymous_download_count' AND NOT attisdropped + ) THEN + ALTER TABLE "LiteLLM_ClaudeCodePluginTable" + ADD COLUMN IF NOT EXISTS "anonymous_download_count" BIGINT NOT NULL DEFAULT 0; + END IF; + + IF to_regclass('"LiteLLM_ClaudeCodePluginDownload"') IS NULL THEN + CREATE TABLE IF NOT EXISTS "LiteLLM_ClaudeCodePluginDownload" ( + "id" BIGSERIAL NOT NULL, + "plugin_id" TEXT NOT NULL, + "downloaded_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP, + "version" TEXT, + "digest" TEXT NOT NULL, + "authenticated" BOOLEAN NOT NULL, + "user_id" TEXT, + "user_email" TEXT, + "key_alias" TEXT, + "team_id" TEXT, + "team_alias" TEXT, + CONSTRAINT "LiteLLM_ClaudeCodePluginDownload_pkey" PRIMARY KEY ("id"), + CONSTRAINT "LiteLLM_ClaudeCodePluginDownload_plugin_id_fkey" FOREIGN KEY ("plugin_id") + REFERENCES "LiteLLM_ClaudeCodePluginTable"("id") ON DELETE CASCADE ON UPDATE CASCADE + ); + END IF; + + IF to_regclass('"LiteLLM_ClaudeCodePluginDownload_plugin_id_id_idx"') IS NULL THEN + CREATE INDEX IF NOT EXISTS "LiteLLM_ClaudeCodePluginDownload_plugin_id_id_idx" + ON "LiteLLM_ClaudeCodePluginDownload"("plugin_id", "id"); + END IF; +END $$; diff --git a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma index 179b741fe7c..818f2dc4858 100644 --- a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma +++ b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma @@ -1615,9 +1615,77 @@ model LiteLLM_ClaudeCodePluginTable { updated_at DateTime? @default(now()) @updatedAt created_by String? + uploaded_archive LiteLLM_ClaudeCodePluginUpload? + versions LiteLLM_ClaudeCodePluginVersion[] + downloads LiteLLM_ClaudeCodePluginDownload[] + anonymous_download_count BigInt @default(0) + @@map("LiteLLM_ClaudeCodePluginTable") } +model LiteLLM_ClaudeCodePluginVersion { + id String @id @default(uuid()) + plugin_id String + version String? + description String? + manifest_json String? + published_at DateTime? + published_by String? + archive_available Boolean @default(false) + content Bytes? + plugin LiteLLM_ClaudeCodePluginTable @relation(fields: [plugin_id], references: [id], onDelete: Cascade, onUpdate: Cascade) + + @@unique([plugin_id, version]) + @@index([plugin_id, published_at]) +} + + +model LiteLLM_SkillSubmission { + id String @id @default(uuid()) + plugin_name String + operation String + status String @default("pending_review") + proposal_json String + archive_content Bytes? + submitted_by String + created_at DateTime @default(now()) + base_plugin_id String? + base_updated_at DateTime? + reviewed_by String? + reviewed_at DateTime? + rejection_reason String? + scan_json String? + + @@index([submitted_by, created_at(sort: Desc), id(sort: Desc)]) + @@index([submitted_by, status, created_at(sort: Desc), id(sort: Desc)]) + @@index([status, created_at(sort: Desc), id(sort: Desc)]) + @@index([created_at(sort: Desc), id(sort: Desc)]) +} + +model LiteLLM_ClaudeCodePluginDownload { + id BigInt @id @default(autoincrement()) + plugin_id String + downloaded_at DateTime @default(now()) + version String? + digest String + authenticated Boolean + user_id String? + user_email String? + key_alias String? + team_id String? + team_alias String? + plugin LiteLLM_ClaudeCodePluginTable @relation(fields: [plugin_id], references: [id], onDelete: Cascade, onUpdate: Cascade) + + @@index([plugin_id, id]) +} + +model LiteLLM_ClaudeCodePluginUpload { + plugin_name String @id + content Bytes + plugin LiteLLM_ClaudeCodePluginTable @relation(fields: [plugin_name], references: [name], onDelete: Cascade, onUpdate: Cascade) +} + + // User/team-scoped memory store with a GLOBAL unique key. // `value` is a string (typically markdown/text meant for LLM context); // `metadata` is an optional JSON envelope for structured tags without schema changes. @@ -2062,74 +2130,27 @@ model LiteLLM_TelemetryReport { @@index([created_at]) } -enum AccountingEventKind { - inbound_usage - outbound_usage - cost -} - enum AccountingDeliveryState { pending applied parked } -enum AccountingDeliveryTarget { - LiteLLM_VerificationToken - LiteLLM_UserTable - LiteLLM_TeamTable - LiteLLM_TeamMembership - LiteLLM_OrganizationTable - LiteLLM_OrganizationMembership - LiteLLM_EndUserTable - LiteLLM_AgentsTable - LiteLLM_TagTable - LiteLLM_ProjectTable - LiteLLM_ModelAccessGroupBudgetTable - LiteLLM_BudgetTable - LiteLLM_BudgetWindowSpend - LiteLLM_DailyUserSpend - LiteLLM_DailyTeamSpend - LiteLLM_DailyOrganizationSpend - LiteLLM_DailyEndUserSpend - LiteLLM_DailyAgentSpend - LiteLLM_DailyTagSpend - LiteLLM_DailyModelUsage - LiteLLM_DailyToolSpend - LiteLLM_AutoRouterDailySpend -} +model LiteLLM_SpendLogDelivery { + delivery_id String @id @default(dbgenerated("(gen_random_uuid())::text")) + request_id String + state AccountingDeliveryState @default(pending) + accounting_payload Json + is_batch Boolean + attempts Int @default(0) + next_attempt_at DateTime @default(now()) + applied_at DateTime? + last_error String? + created_at DateTime @default(now()) -// Durable accounting ledger. One row per usage or cost event; payload holds the -// private event envelope versioned by schema_version. Usage rows retain request-scoped -// pricing context; cost rows include resolved rates and the finalized pricing snapshot. -model LiteLLM_AccountingEvent { - event_id String @id - kind AccountingEventKind - source_event_id String? - schema_version Int - payload_hash String - occurred_at DateTime - recorded_at DateTime @default(now()) - payload Json - - @@index([recorded_at]) - @@index([kind, source_event_id]) -} - -// One row per (event, target table, version): pending work for the projector and, -// once applied in the same transaction as the target write, the receipt that stops a retry. -model LiteLLM_AccountingDelivery { - event_id String - target AccountingDeliveryTarget - version Int - state AccountingDeliveryState @default(pending) - attempts Int @default(0) - next_attempt_at DateTime @default(now()) - applied_at DateTime? - last_error String? - - @@id([event_id, target, version]) - @@index([target, state, next_attempt_at]) + @@index([state, next_attempt_at]) + @@index([state, applied_at]) + @@index([request_id]) } model LiteLLM_SubscriptionAccountTable { diff --git a/litellm-rust/Cargo.lock b/litellm-rust/Cargo.lock index f91deaaa401..23ebfc7d3cf 100644 --- a/litellm-rust/Cargo.lock +++ b/litellm-rust/Cargo.lock @@ -3389,15 +3389,19 @@ version = "0.1.0" dependencies = [ "aws-config", "aws-credential-types", + "aws-runtime", "aws-sdk-sts", "aws-sigv4", "aws-smithy-runtime-api", + "aws-smithy-types", "aws-types", "bytes", "futures-util", "litellm-auth-types", "litellm-error", "litellm-http", + "litellm-secret-value", + "litellm-secrets", "moka", "reqwest", "rstest", @@ -3406,6 +3410,7 @@ dependencies = [ "sha2 0.10.9", "thiserror 2.0.19", "tokio", + "url", "veil", ] @@ -3418,6 +3423,7 @@ dependencies = [ "litellm-auth-types", "litellm-error", "litellm-secret-value", + "litellm-secrets", "moka", "rstest", "serde_json", @@ -3431,6 +3437,7 @@ dependencies = [ name = "litellm-auth-gcp" version = "0.1.0" dependencies = [ + "axum", "base64 0.22.1", "gcp_auth", "google-cloud-auth", @@ -3440,10 +3447,12 @@ dependencies = [ "litellm-secret-value", "moka", "rstest", + "rustls 0.23.42", "serde", "serde_json", "sha2 0.10.9", "tempfile", + "time", "tokio", "veil", ] @@ -3569,37 +3578,6 @@ dependencies = [ "uuid", ] -[[package]] -name = "litellm-cache-redis" -version = "0.1.0" -dependencies = [ - "litellm-cache", - "litellm-cache-testing", - "litellm-error", - "r2d2", - "redis", - "redis-test", - "rstest", - "serde_json", - "thiserror 2.0.19", - "tokio", -] - -[[package]] -name = "litellm-cache-redis-semantic" -version = "0.1.0" -dependencies = [ - "litellm-cache", - "litellm-cache-redis", - "litellm-cache-testing", - "redis", - "redis-test", - "rstest", - "serde_json", - "sha2 0.10.9", - "tokio", -] - [[package]] name = "litellm-cache-response" version = "0.1.0" @@ -3607,11 +3585,8 @@ dependencies = [ "litellm-cache", "litellm-cache-gcs", "litellm-cache-memory", - "litellm-cache-redis", "litellm-http", "py_literal", - "redis", - "redis-test", "rstest", "serde", "serde_json", @@ -3650,24 +3625,6 @@ dependencies = [ "litellm-cache", ] -[[package]] -name = "litellm-cache-valkey-semantic" -version = "0.1.0" -dependencies = [ - "litellm-cache", - "litellm-cache-redis", - "litellm-cache-testing", - "litellm-error", - "redis", - "redis-test", - "rstest", - "serde_json", - "sha2 0.10.9", - "thiserror 2.0.19", - "tokio", - "uuid", -] - [[package]] name = "litellm-callbacks-legacy-python" version = "0.1.0" @@ -4331,6 +4288,7 @@ dependencies = [ name = "litellm-python-bridge" version = "0.1.0" dependencies = [ + "async-trait", "aws-sdk-secretsmanager", "bytes", "criterion", @@ -4339,8 +4297,6 @@ dependencies = [ "litellm-auth", "litellm-auth-aws", "litellm-cache", - "litellm-cache-memory", - "litellm-cache-redis", "litellm-cache-response", "litellm-callbacks-legacy-python", "litellm-core-utils", @@ -4357,6 +4313,7 @@ dependencies = [ "litellm-llms", "litellm-llms-types", "litellm-model-catalog", + "litellm-router-core", "litellm-router-types", "litellm-secret-value", "litellm-secrets", @@ -4369,7 +4326,6 @@ dependencies = [ "prost", "pyo3", "pyo3-async-runtimes", - "redis", "reqwest", "rstest", "serde", @@ -4439,6 +4395,24 @@ dependencies = [ [[package]] name = "litellm-router-core" version = "0.1.0" +dependencies = [ + "arc-swap", + "async-trait", + "jiff", + "litellm-cache", + "litellm-router-types", + "parking_lot", + "rand 0.8.7", + "rstest", + "serde", + "serde_json", + "serde_with", + "sha2 0.10.9", + "strum", + "thiserror 2.0.19", + "tokio", + "tracing", +] [[package]] name = "litellm-router-types" @@ -5782,17 +5756,6 @@ version = "6.0.0" source = "registry+https://github.com/rust-lang/crates.io-index" checksum = "f8dcc9c7d52a811697d2151c701e0d08956f92b0e24136cf4cf27b57a6a0d9bf" -[[package]] -name = "r2d2" -version = "0.8.10" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "51de85fb3fb6524929c8a2eb85e6b6d363de4e8c48f9e2c2eac4944abc181c93" -dependencies = [ - "log", - "parking_lot", - "scheduled-thread-pool", -] - [[package]] name = "rand" version = "0.8.7" @@ -5966,18 +5929,6 @@ dependencies = [ "xxhash-rust", ] -[[package]] -name = "redis-test" -version = "1.0.4" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "804d36862e4323b69f96440cbb13c9894fc90176abdeaf91264e21d5d77f6aca" -dependencies = [ - "rand 0.9.5", - "redis", - "socket2 0.6.5", - "tempfile", -] - [[package]] name = "redox_syscall" version = "0.5.18" @@ -6454,15 +6405,6 @@ dependencies = [ "windows-sys 0.61.2", ] -[[package]] -name = "scheduled-thread-pool" -version = "0.2.7" -source = "registry+https://github.com/rust-lang/crates.io-index" -checksum = "3cbc66816425a074528352f5789333ecff06ca41b36b0b0efdfbb29edc391a19" -dependencies = [ - "parking_lot", -] - [[package]] name = "schemars" version = "0.9.0" diff --git a/litellm-rust/Cargo.toml b/litellm-rust/Cargo.toml index 75cac2a5d63..71914a0bffe 100644 --- a/litellm-rust/Cargo.toml +++ b/litellm-rust/Cargo.toml @@ -13,6 +13,7 @@ litellm-config = { path = "crates/config" } litellm-error = { path = "crates/error" } litellm-router = { path = "crates/router" } litellm-router-types = { path = "crates/router-types" } +litellm-router-core = { path = "crates/router-core" } litellm-tracing = { path = "crates/tracing" } litellm-spend-clickhouse = { path = "crates/spend-clickhouse" } litellm-storage-clickhouse = { path = "crates/storage-clickhouse" } @@ -57,11 +58,9 @@ litellm-db-testing = { path = "crates/db-testing" } litellm-cache = { path = "crates/cache" } litellm-cache-azure-blob = { path = "crates/cache-azure-blob" } litellm-cache-memory = { path = "crates/cache-memory" } -litellm-cache-redis = { path = "crates/cache-redis" } litellm-cache-s3 = { path = "crates/cache-s3" } litellm-cache-gcs = { path = "crates/cache-gcs" } litellm-cache-disk = { path = "crates/cache-disk" } -litellm-cache-redis-semantic = { path = "crates/cache-redis-semantic" } litellm-cache-response = { path = "crates/cache-response" } litellm-cache-qdrant-semantic = { path = "crates/cache-qdrant-semantic" } litellm-cache-testing = { path = "crates/cache-testing" } @@ -78,6 +77,8 @@ litellm-cost = { path = "crates/cost" } litellm-model-catalog = { path = "crates/model-catalog" } litellm-model-catalog-refresh = { path = "crates/model-catalog-refresh" } +arc-swap = "1.9.2" +async-trait = "0.1.91" askama = { version = "0.16.1", default-features = false, features = ["derive", "std"] } tracing = "0.1" axum = { version = "0.8.9", default-features = false, features = ["http1", "tokio", "multipart"] } @@ -97,7 +98,6 @@ macro_rules_attribute = "0.2.3" schemars = "1" reqwest = { version = "0.13", default-features = false, features = ["json", "multipart", "rustls", "http2", "stream", "query"] } redis = "1.8.0" -redis-test = "1.0.4" testcontainers-modules = "0.15.0" qdrant-client = { version = "1.19.0", default-features = false } uuid = { version = "1", features = ["v4"] } diff --git a/litellm-rust/crates/auth-aws/Cargo.toml b/litellm-rust/crates/auth-aws/Cargo.toml index e4578777a08..c8ed7bb0f14 100644 --- a/litellm-rust/crates/auth-aws/Cargo.toml +++ b/litellm-rust/crates/auth-aws/Cargo.toml @@ -11,14 +11,16 @@ litellm-error.workspace = true litellm-http.workspace = true reqwest.workspace = true -moka = { workspace = true, features = ["sync"] } +moka.workspace = true +litellm-secret-value.workspace = true serde.workspace = true serde_json = { workspace = true, features = ["preserve_order"] } sha2.workspace = true thiserror.workspace = true +url.workspace = true veil.workspace = true -aws-config = { version = "1.9.0", default-features = false, features = ["rustls", "rt-tokio"] } +aws-config = { version = "1.9.0", default-features = false, features = ["rustls", "rt-tokio", "credentials-process"] } aws-credential-types = { version = "1.3.0", features = ["hardcoded-credentials"] } aws-sdk-sts = { version = "1.108.0", default-features = false, features = ["rustls", "rt-tokio"] } aws-sigv4 = "1.5.1" @@ -26,6 +28,9 @@ aws-types = "1.4.0" aws-smithy-runtime-api = "1.13.0" [dev-dependencies] +litellm-secrets.workspace = true +aws-smithy-types = "1.6.4" +aws-runtime = { version = "1.9.4", default-features = false } rstest.workspace = true litellm-http = { workspace = true, features = ["test-support"] } bytes.workspace = true diff --git a/litellm-rust/crates/auth-aws/src/aws.rs b/litellm-rust/crates/auth-aws/src/aws.rs index 81aa4b068bc..e6e32754b4f 100644 --- a/litellm-rust/crates/auth-aws/src/aws.rs +++ b/litellm-rust/crates/auth-aws/src/aws.rs @@ -1,13 +1,16 @@ use std::time::Duration; use std::time::{SystemTime, UNIX_EPOCH}; -use moka::sync::Cache; -use sha2::{Digest, Sha256}; +use aws_credential_types::provider::{SharedCredentialsProvider, error::CredentialsError}; +use litellm_secret_value::SecretValue; +use moka::{Expiry, future::Cache}; +use std::{future::Future, pin::Pin, sync::Arc}; use aws_credential_types::Credentials; use aws_credential_types::provider::ProvideCredentials; use aws_sigv4::http_request::{ - SignableBody, SignableRequest, SigningParams, SigningSettings, sign, + SignableBody, SignableRequest, SignatureLocation, SigningInstructions, SigningParams, + SigningSettings, sign, }; use aws_sigv4::sign::v4; use aws_smithy_runtime_api::client::identity::Identity; @@ -23,72 +26,106 @@ use super::constants::{ }; use crate::error::{CredentialFlow, Error, SigningStage}; -const STATIC_CREDENTIALS_TTL: Duration = Duration::from_secs(3600 - 60); -const AMBIENT_CREDENTIALS_TTL: Duration = Duration::from_secs(600); +const CREDENTIAL_CACHE_TTL: Duration = Duration::from_secs(600); +const EXPIRY_BUFFER: Duration = Duration::from_secs(60); #[derive(Clone)] pub struct AwsAuthService { - static_credentials: Cache, - ambient_credentials: Cache, + providers: Cache, + credentials: Cache, + loader: Arc, } impl Default for AwsAuthService { fn default() -> Self { + Self::new(Arc::new(NativeProviderLoader)) + } +} + +impl AwsAuthService { + fn new(loader: Arc) -> Self { Self { - static_credentials: Cache::builder() + providers: Cache::builder().max_capacity(200).build(), + credentials: Cache::builder() .max_capacity(200) - .time_to_live(STATIC_CREDENTIALS_TTL) - .build(), - ambient_credentials: Cache::builder() - .max_capacity(200) - .time_to_live(AMBIENT_CREDENTIALS_TTL) + .expire_after(CredentialExpiry) .build(), + loader, } } } -fn credential_cache_ttl(flow: &AwsAuthFlow) -> Option { - match flow { - AwsAuthFlow::StaticKeys { .. } => Some(STATIC_CREDENTIALS_TTL), - AwsAuthFlow::DefaultChain => Some(AMBIENT_CREDENTIALS_TTL), - AwsAuthFlow::WebIdentity { .. } - | AwsAuthFlow::AssumeRole { .. } - | AwsAuthFlow::Profile { .. } - | AwsAuthFlow::SessionToken { .. } => None, +struct CredentialExpiry; + +impl Expiry for CredentialExpiry { + fn expire_after_create( + &self, + _: &AwsAuthConfig, + credentials: &Credentials, + _: std::time::Instant, + ) -> Option { + Some(credentials.expiry().map_or(CREDENTIAL_CACHE_TTL, |expiry| { + expiry + .duration_since(SystemTime::now()) + .unwrap_or_default() + .saturating_sub(EXPIRY_BUFFER) + .min(CREDENTIAL_CACHE_TTL) + })) } } -#[derive(Clone, Debug, Default, PartialEq, Eq)] +type ProviderFuture<'a> = + Pin> + Send + 'a>>; + +trait ProviderLoader: Send + Sync { + fn load(&self, config: AwsAuthConfig, flow: AwsAuthFlow) -> ProviderFuture<'_>; +} + +struct NativeProviderLoader; + +impl ProviderLoader for NativeProviderLoader { + fn load(&self, config: AwsAuthConfig, flow: AwsAuthFlow) -> ProviderFuture<'_> { + Box::pin(build_provider(config, flow)) + } +} + +#[derive(Clone, Debug, Default, PartialEq, Eq, Hash)] pub struct AwsAuthConfig { - pub access_key_id: Option, - pub secret_access_key: Option, - pub session_token: Option, + pub access_key_id: Option, + pub secret_access_key: Option, + pub session_token: Option, pub region_name: Option, pub session_name: Option, pub profile_name: Option, pub role_name: Option, - pub web_identity_token: Option, + pub web_identity_token: Option, pub sts_endpoint: Option, - pub external_id: Option, + pub external_id: Option, } impl AwsAuthConfig { fn with_environment(self, env_lookup: &(dyn Fn(&str) -> Option + Sync)) -> Self { Self { - access_key_id: self.access_key_id.or_else(|| env_lookup(AWS_ACCESS_KEY_ID)), + access_key_id: self + .access_key_id + .or_else(|| env_lookup(AWS_ACCESS_KEY_ID).map(SecretValue::new)), secret_access_key: self .secret_access_key - .or_else(|| env_lookup(AWS_SECRET_ACCESS_KEY)), - session_token: self.session_token.or_else(|| env_lookup(AWS_SESSION_TOKEN)), + .or_else(|| env_lookup(AWS_SECRET_ACCESS_KEY).map(SecretValue::new)), + session_token: self + .session_token + .or_else(|| env_lookup(AWS_SESSION_TOKEN).map(SecretValue::new)), region_name: self.region_name.or_else(|| env_lookup(AWS_REGION_NAME)), session_name: self.session_name.or_else(|| env_lookup(AWS_SESSION_NAME)), profile_name: self.profile_name.or_else(|| env_lookup(AWS_PROFILE_NAME)), role_name: self.role_name.or_else(|| env_lookup(AWS_ROLE_NAME)), web_identity_token: self .web_identity_token - .or_else(|| env_lookup(AWS_WEB_IDENTITY_TOKEN)), + .or_else(|| env_lookup(AWS_WEB_IDENTITY_TOKEN).map(SecretValue::new)), sts_endpoint: self.sts_endpoint.or_else(|| env_lookup(AWS_STS_ENDPOINT)), - external_id: self.external_id.or_else(|| env_lookup(AWS_EXTERNAL_ID)), + external_id: self + .external_id + .or_else(|| env_lookup(AWS_EXTERNAL_ID).map(SecretValue::new)), } } } @@ -96,52 +133,31 @@ impl AwsAuthConfig { #[derive(Clone, Debug, PartialEq, Eq)] pub enum AwsAuthFlow { WebIdentity { - token: String, + token: SecretValue, role: String, session_name: String, }, AssumeRole { role: String, session_name: Option, + web_identity_role: Option, }, Profile { name: String, }, SessionToken { - access_key_id: String, - secret_access_key: String, - session_token: String, + access_key_id: SecretValue, + secret_access_key: SecretValue, + session_token: SecretValue, }, StaticKeys { - access_key_id: String, - secret_access_key: String, + access_key_id: SecretValue, + secret_access_key: SecretValue, region_name: String, }, DefaultChain, } -fn cache_key(config: &AwsAuthConfig, flow: &AwsAuthFlow) -> String { - let mut hasher = Sha256::new(); - hasher.update(format!("{config:?}:{flow:?}")); - format!("{:x}", hasher.finalize()) -} - -impl AwsAuthService { - fn get_cached_credentials(&self, key: &str) -> Option { - self.static_credentials - .get(key) - .or_else(|| self.ambient_credentials.get(key)) - } - - fn set_cached_credentials(&self, key: String, credentials: Credentials, ttl: Duration) { - if ttl == STATIC_CREDENTIALS_TTL { - self.static_credentials.insert(key, credentials); - } else { - self.ambient_credentials.insert(key, credentials); - } - } -} - fn role_identity(arn: &str) -> Option<(&str, &str, &str)> { let mut parts = arn.splitn(6, ':'); let ("arn", partition, _, _, account, resource) = ( @@ -170,6 +186,9 @@ pub fn classify_auth( config: AwsAuthConfig, env_lookup: &(dyn Fn(&str) -> Option + Sync), ) -> AwsAuthFlow { + let web_identity_role = env_lookup(AWS_WEB_IDENTITY_TOKEN_FILE) + .filter(|token_file| !token_file.is_empty()) + .and_then(|_| env_lookup(AWS_ROLE_ARN)); let config = config.with_environment(env_lookup); if let (Some(token), Some(role), Some(session_name)) = ( config.web_identity_token.clone(), @@ -186,6 +205,7 @@ pub fn classify_auth( return AwsAuthFlow::AssumeRole { role, session_name: config.session_name.clone(), + web_identity_role, }; } if let Some(name) = config.profile_name { @@ -216,6 +236,30 @@ pub fn classify_auth( AwsAuthFlow::DefaultChain } +async fn profile_provider( + name: &str, + region: Option, + config: aws_config::provider_config::ProviderConfig, + builder: aws_config::profile::credentials::Builder, +) -> Result { + let region = match region { + Some(region) => Some(aws_types::region::Region::new(region)), + None => { + aws_config::default_provider::region::DefaultRegionChain::builder() + .profile_name(name) + .build() + .region() + .await + } + }; + Ok(SharedCredentialsProvider::new( + builder + .configure(&config.with_region(region)) + .profile_name(name) + .build(), + )) +} + impl AwsAuthService { pub async fn resolve_credentials( &self, @@ -224,183 +268,240 @@ impl AwsAuthService { ) -> Result { let resolved = config.clone().with_environment(env_lookup); let flow = classify_auth(config, env_lookup); - match flow { - AwsAuthFlow::SessionToken { - access_key_id, - secret_access_key, - session_token, - } => Ok(Credentials::new( - access_key_id, - secret_access_key, - Some(session_token), - None, - "litellm-static-session", - )), - AwsAuthFlow::StaticKeys { - access_key_id, - secret_access_key, - region_name, - } => { - let flow = AwsAuthFlow::StaticKeys { - access_key_id: access_key_id.clone(), - secret_access_key: secret_access_key.clone(), - region_name, - }; - let key = cache_key(&resolved, &flow); - if let Some(credentials) = self.get_cached_credentials(&key) { - return Ok(credentials); - } - let credentials = Credentials::new( - access_key_id, - secret_access_key, - None, - None, - "litellm-static", - ); - self.set_cached_credentials( - key, - credentials.clone(), - credential_cache_ttl(&flow).unwrap_or(STATIC_CREDENTIALS_TTL), - ); - Ok(credentials) - } - AwsAuthFlow::Profile { name } => { - let provider = aws_config::profile::ProfileFileCredentialsProvider::builder() - .profile_name(name) - .build(); + self.fresh_credentials(&resolved, &flow).await + } + + /// The credentials botocore's default chain finds in `region`, without LiteLLM's Bedrock settings + /// (`AWS_ROLE_NAME`, `AWS_PROFILE_NAME`, `AWS_SESSION_NAME`) that `resolve_credentials` also reads. + pub async fn default_chain_credentials(&self, region: &str) -> Result { + let config = AwsAuthConfig { + region_name: Some(region.to_owned()), + ..Default::default() + }; + self.fresh_credentials(&config, &AwsAuthFlow::DefaultChain) + .await + } + + async fn fresh_credentials( + &self, + resolved: &AwsAuthConfig, + flow: &AwsAuthFlow, + ) -> Result { + let cached = self.cached_credentials(resolved, flow).await?; + if fresh(&cached) { + return Ok(cached); + } + self.credentials.invalidate(resolved).await; + let refetched = self.cached_credentials(resolved, flow).await?; + if fresh(&refetched) { + return Ok(refetched); + } + self.credentials.invalidate(resolved).await; + Err(Error::ExpiredCredentials) + } + + async fn cached_credentials( + &self, + resolved: &AwsAuthConfig, + flow: &AwsAuthFlow, + ) -> Result { + self.credentials + .try_get_with(resolved.clone(), async { + let provider = self + .providers + .try_get_with( + resolved.clone(), + self.loader.load(resolved.clone(), flow.clone()), + ) + .await + .map_err(|error| (*error).clone())?; provider .provide_credentials() .await - .map_err(Error::credentials(CredentialFlow::Profile)) - } - AwsAuthFlow::AssumeRole { role, session_name } => { - if is_already_running_as_role(&role, &resolved).await? { - let ambient_flow = AwsAuthFlow::DefaultChain; - let key = cache_key(&resolved, &ambient_flow); - if let Some(credentials) = self.get_cached_credentials(&key) { - return Ok(credentials); - } - let provider = - aws_config::default_provider::credentials::DefaultCredentialsChain::builder() - .build() - .await; - let credentials = provider - .provide_credentials() - .await - .map_err(Error::credentials(CredentialFlow::DefaultChain))?; - self.set_cached_credentials( - key, - credentials.clone(), - credential_cache_ttl(&ambient_flow).unwrap_or(AMBIENT_CREDENTIALS_TTL), - ); - return Ok(credentials); - } - let mut loader = aws_config::defaults(aws_config::BehaviorVersion::latest()); - if let Some(region) = resolved.region_name.clone() { - loader = loader.region(aws_types::region::Region::new(region)); - } - if let Some(endpoint) = resolved.sts_endpoint.clone() { - loader = loader.endpoint_url(endpoint); - } - if let (Some(access_key_id), Some(secret_access_key)) = - (resolved.access_key_id, resolved.secret_access_key) - { - loader = loader.credentials_provider(Credentials::new( - access_key_id, - secret_access_key, - resolved.session_token, - None, - "litellm-role-source", - )); - } - let sdk_config = loader.load().await; - let builder = aws_config::sts::AssumeRoleProvider::builder(role); - let builder = match session_name { - Some(name) => builder.session_name(name), - None => builder.session_name(default_session_name()), - }; - let builder = match resolved.external_id { - Some(id) => builder.external_id(id), - None => builder, - }; - let provider = builder.configure(&sdk_config).build().await; - provider - .provide_credentials() - .await - .map_err(Error::credentials(CredentialFlow::AssumeRole)) - } - AwsAuthFlow::WebIdentity { - token, - role, - session_name, - } => { - let mut loader = aws_config::defaults(aws_config::BehaviorVersion::latest()); - if let Some(region) = resolved.region_name { - loader = loader.region(aws_types::region::Region::new(region)); - } - if let Some(endpoint) = resolved.sts_endpoint { - loader = loader.endpoint_url(endpoint); - } - let sdk_config = loader.load().await; - let client = aws_sdk_sts::Client::new(&sdk_config); - let response = client - .assume_role_with_web_identity() - .role_arn(role) - .role_session_name(session_name) - .web_identity_token(token) - .send() - .await - .map_err(Error::credentials(CredentialFlow::WebIdentity))?; - let credentials = response - .credentials() - .ok_or(Error::MissingWebIdentityCredentials)?; - let expiration = - SystemTime::try_from(*credentials.expiration()).map_err(|source| { - Error::WebIdentityExpiration(litellm_error::Source::new(source)) - })?; - Ok(Credentials::new( - credentials.access_key_id(), - credentials.secret_access_key(), - Some(credentials.session_token().to_string()), - Some(expiration), - "litellm-web-identity", - )) - } - AwsAuthFlow::DefaultChain => { - let key = cache_key(&resolved, &AwsAuthFlow::DefaultChain); - if let Some(credentials) = self.get_cached_credentials(&key) { - return Ok(credentials); - } - let provider = - aws_config::default_provider::credentials::DefaultCredentialsChain::builder() - .build() - .await; - let credentials = provider - .provide_credentials() - .await - .map_err(Error::credentials(CredentialFlow::DefaultChain))?; - self.set_cached_credentials( - key, - credentials.clone(), - credential_cache_ttl(&AwsAuthFlow::DefaultChain) - .unwrap_or(AMBIENT_CREDENTIALS_TTL), - ); - Ok(credentials) + .map_err(Error::credentials(flow.credential_flow())) + }) + .await + .map_err(|error| (*error).clone()) + } +} + +fn fresh(credentials: &Credentials) -> bool { + credentials + .expiry() + .is_none_or(|expiry| expiry > SystemTime::now() + EXPIRY_BUFFER) +} + +impl AwsAuthFlow { + fn credential_flow(&self) -> CredentialFlow { + match self { + Self::Profile { .. } => CredentialFlow::Profile, + Self::AssumeRole { .. } => CredentialFlow::AssumeRole, + Self::WebIdentity { .. } => CredentialFlow::WebIdentity, + Self::DefaultChain | Self::StaticKeys { .. } | Self::SessionToken { .. } => { + CredentialFlow::DefaultChain } } } } -async fn is_already_running_as_role(role: &str, config: &AwsAuthConfig) -> Result { +async fn build_provider( + resolved: AwsAuthConfig, + flow: AwsAuthFlow, +) -> Result { + match flow { + AwsAuthFlow::SessionToken { + access_key_id, + secret_access_key, + session_token, + } => Ok(SharedCredentialsProvider::new(Credentials::new( + access_key_id.expose(), + secret_access_key.expose(), + Some(session_token.expose().to_owned()), + None, + "litellm-static-session", + ))), + AwsAuthFlow::StaticKeys { + access_key_id, + secret_access_key, + .. + } => Ok(SharedCredentialsProvider::new(Credentials::new( + access_key_id.expose(), + secret_access_key.expose(), + None, + None, + "litellm-static", + ))), + AwsAuthFlow::Profile { name } => { + profile_provider( + &name, + resolved.region_name, + aws_config::provider_config::ProviderConfig::without_region(), + aws_config::profile::ProfileFileCredentialsProvider::builder(), + ) + .await + } + AwsAuthFlow::DefaultChain => { + let builder = + aws_config::default_provider::credentials::DefaultCredentialsChain::builder(); + let builder = match resolved.region_name { + Some(region) => builder.region(aws_types::region::Region::new(region)), + None => builder, + }; + Ok(SharedCredentialsProvider::new(builder.build().await)) + } + AwsAuthFlow::AssumeRole { + role, + session_name, + web_identity_role, + } => { + if is_already_running_as_role(&role, web_identity_role.as_deref(), &resolved).await? { + return Ok(SharedCredentialsProvider::new( + aws_config::default_provider::credentials::DefaultCredentialsChain::builder() + .build() + .await, + )); + } + let sdk_config = sdk_config(resolved.clone()).await; + let builder = aws_config::sts::AssumeRoleProvider::builder(role) + .session_name(session_name.unwrap_or_else(default_session_name)); + let builder = match resolved.external_id { + Some(id) => builder.external_id(id.expose()), + None => builder, + }; + Ok(SharedCredentialsProvider::new( + builder.configure(&sdk_config).build().await, + )) + } + AwsAuthFlow::WebIdentity { + token, + role, + session_name, + } => Ok(SharedCredentialsProvider::new(WebIdentityProvider { + client: aws_sdk_sts::Client::new(&sdk_config(resolved).await), + token, + role, + session_name, + })), + } +} + +async fn sdk_config(config: AwsAuthConfig) -> aws_types::SdkConfig { + let loader = aws_config::defaults(aws_config::BehaviorVersion::latest()); + let loader = match config.region_name { + Some(region) => loader.region(aws_types::region::Region::new(region)), + None => loader, + }; + let loader = match config.sts_endpoint { + Some(endpoint) => loader.endpoint_url(endpoint), + None => loader, + }; + let loader = match (config.access_key_id, config.secret_access_key) { + (Some(key), Some(secret)) => loader.credentials_provider(Credentials::new( + key.expose(), + secret.expose(), + config.session_token.map(|token| token.expose().to_owned()), + None, + "litellm-role-source", + )), + _ => loader, + }; + loader.load().await +} + +#[derive(Debug)] +struct WebIdentityProvider { + client: aws_sdk_sts::Client, + token: SecretValue, + role: String, + session_name: String, +} + +impl ProvideCredentials for WebIdentityProvider { + fn provide_credentials<'a>( + &'a self, + ) -> aws_credential_types::provider::future::ProvideCredentials<'a> + where + Self: 'a, + { + aws_credential_types::provider::future::ProvideCredentials::new(async { + let response = self + .client + .assume_role_with_web_identity() + .role_arn(&self.role) + .role_session_name(&self.session_name) + .web_identity_token(self.token.expose()) + .send() + .await + .map_err(CredentialsError::provider_error)?; + let credentials = response.credentials().ok_or_else(|| { + CredentialsError::provider_error(Error::MissingWebIdentityCredentials) + })?; + let expiration = SystemTime::try_from(*credentials.expiration()) + .map_err(CredentialsError::provider_error)?; + Ok(Credentials::new( + credentials.access_key_id(), + credentials.secret_access_key(), + Some(credentials.session_token().to_owned()), + Some(expiration), + "litellm-web-identity", + )) + }) + } +} + +async fn is_already_running_as_role( + role: &str, + web_identity_role: Option<&str>, + config: &AwsAuthConfig, +) -> Result { + if config.access_key_id.is_some() || config.secret_access_key.is_some() { + return Ok(false); + } if role_identity(role).is_none() { return Ok(false); } - if let (Ok(current_role), Ok(token_file)) = ( - std::env::var(AWS_ROLE_ARN), - std::env::var(AWS_WEB_IDENTITY_TOKEN_FILE), - ) && !token_file.is_empty() - { - return Ok(same_role_arns(role, ¤t_role)); + if let Some(current_role) = web_identity_role { + return Ok(same_role_arns(role, current_role)); } let mut loader = aws_config::defaults(aws_config::BehaviorVersion::latest()); @@ -473,16 +574,6 @@ pub fn sign_headers( headers: &HeaderMap, scope: SigningScope<'_>, ) -> Result { - let identity: Identity = scope.credentials.clone().into(); - let params = v4::SigningParams::builder() - .identity(&identity) - .region(scope.region) - .name(scope.service) - .time(scope.time) - .settings(SigningSettings::default()) - .build() - .map(SigningParams::from) - .map_err(Error::signing(SigningStage::Parameters))?; let header_refs = headers .iter() .map(|(name, value)| { @@ -494,16 +585,14 @@ pub fn sign_headers( }) }) .collect::, _>>()?; - let request = SignableRequest::new( + let instructions = sign_request( method, url, header_refs.into_iter(), - SignableBody::Bytes(body), - ) - .map_err(Error::signing(SigningStage::Request))?; - let (instructions, _) = sign(request, ¶ms) - .map_err(Error::signing(SigningStage::Signature))? - .into_parts(); + body, + SigningSettings::default(), + scope, + )?; instructions .headers() .map(|(name, value)| { @@ -516,6 +605,60 @@ pub fn sign_headers( .collect() } +pub fn presign_url( + url: &str, + expires_in: Duration, + scope: SigningScope<'_>, +) -> Result { + let mut signed = url::Url::parse(url).map_err(Error::signing(SigningStage::Request))?; + let mut settings = SigningSettings::default(); + settings.signature_location = SignatureLocation::QueryParams; + settings.expires_in = Some(expires_in); + let instructions = sign_request( + "GET", + signed.as_str(), + std::iter::empty(), + &[], + settings, + scope, + )?; + let (signature, auth): (Vec<_>, Vec<_>) = instructions + .params() + .iter() + .map(|(name, value)| (*name, value.as_ref())) + .partition(|(name, _)| *name == "X-Amz-Signature"); + signed + .query_pairs_mut() + .extend_pairs(auth.into_iter().chain(signature)); + Ok(signed.into()) +} + +fn sign_request<'a>( + method: &'a str, + url: &'a str, + headers: impl Iterator, + body: &'a [u8], + settings: SigningSettings, + scope: SigningScope<'_>, +) -> Result { + let identity: Identity = scope.credentials.clone().into(); + let params = v4::SigningParams::builder() + .identity(&identity) + .region(scope.region) + .name(scope.service) + .time(scope.time) + .settings(settings) + .build() + .map(SigningParams::from) + .map_err(Error::signing(SigningStage::Parameters))?; + let request = SignableRequest::new(method, url, headers, SignableBody::Bytes(body)) + .map_err(Error::signing(SigningStage::Request))?; + let (instructions, _) = sign(request, ¶ms) + .map_err(Error::signing(SigningStage::Signature))? + .into_parts(); + Ok(instructions) +} + /// Model-id and region parsing shared by every Bedrock route. pub fn bedrock_model_id_and_region(model: &str) -> (String, Option) { let mut stripped = model; @@ -586,16 +729,26 @@ pub fn aws_auth_config( env_lookup: &dyn Fn(&str) -> Option, ) -> AwsAuthConfig { AwsAuthConfig { - access_key_id: params.resolve(&AwsParams::ACCESS_KEY_ID, env_lookup), - secret_access_key: params.resolve(&AwsParams::SECRET_ACCESS_KEY, env_lookup), - session_token: params.resolve(&AwsParams::SESSION_TOKEN, env_lookup), + access_key_id: params + .resolve(&AwsParams::ACCESS_KEY_ID, env_lookup) + .map(SecretValue::new), + secret_access_key: params + .resolve(&AwsParams::SECRET_ACCESS_KEY, env_lookup) + .map(SecretValue::new), + session_token: params + .resolve(&AwsParams::SESSION_TOKEN, env_lookup) + .map(SecretValue::new), region_name: params.resolve(&AwsParams::REGION, env_lookup), session_name: params.resolve(&AwsParams::SESSION_NAME, env_lookup), profile_name: params.resolve(&AwsParams::PROFILE_NAME, env_lookup), role_name: params.resolve(&AwsParams::ROLE_NAME, env_lookup), - web_identity_token: params.resolve(&AwsParams::WEB_IDENTITY_TOKEN, env_lookup), + web_identity_token: params + .resolve(&AwsParams::WEB_IDENTITY_TOKEN, env_lookup) + .map(SecretValue::new), sts_endpoint: params.resolve(&AwsParams::STS_ENDPOINT, env_lookup), - external_id: params.resolve(&AwsParams::EXTERNAL_ID, env_lookup), + external_id: params + .resolve(&AwsParams::EXTERNAL_ID, env_lookup) + .map(SecretValue::new), } } @@ -660,10 +813,133 @@ mod tests { use crate::constants::{AWS_REGION, BEDROCK_SERVICE}; use reqwest::header::CONTENT_TYPE; + #[cfg(unix)] + #[rstest::fixture] + fn process_profile() -> aws_runtime::env_config::file::EnvConfigFiles { + let credentials = serde_json::json!({ + "Version": 1, + "AccessKeyId": "process-access", + "SecretAccessKey": "process-secret", + "SessionToken": "process-session", + }); + aws_runtime::env_config::file::EnvConfigFiles::builder() + .include_default_config_file(false) + .include_default_credentials_file(false) + .with_contents( + aws_runtime::env_config::file::EnvConfigFileKind::Config, + format!( + "[profile smoke]\ncredential_process = /usr/bin/printf '%s' '{credentials}'\n" + ), + ) + .build() + } + + #[cfg(unix)] + #[rstest::rstest] + #[tokio::test] + async fn profile_process_credentials_can_be_loaded( + process_profile: aws_runtime::env_config::file::EnvConfigFiles, + ) { + let provider = profile_provider( + "smoke", + Some("us-west-2".into()), + aws_config::provider_config::ProviderConfig::without_region(), + aws_config::profile::ProfileFileCredentialsProvider::builder() + .profile_files(process_profile), + ) + .await + .unwrap(); + let credentials = provider.provide_credentials().await.unwrap(); + + assert_eq!(credentials.access_key_id(), "process-access"); + assert_eq!(credentials.secret_access_key(), "process-secret"); + assert_eq!(credentials.session_token(), Some("process-session")); + } + + #[derive(Debug)] + struct StsConnector; + + impl aws_smithy_runtime_api::client::http::HttpConnector for StsConnector { + fn call( + &self, + request: aws_smithy_runtime_api::client::orchestrator::HttpRequest, + ) -> aws_smithy_runtime_api::client::http::HttpConnectorFuture { + assert!(request.uri().contains("sts.us-west-2.")); + aws_smithy_runtime_api::client::http::HttpConnectorFuture::new(async { + Ok( + aws_smithy_runtime_api::client::orchestrator::HttpResponse::new( + 200_u16.try_into().unwrap(), + aws_smithy_types::body::SdkBody::from( + r#" + + role-accessrole-secret + role-session2100-01-01T00:00:00Z + arn:aws:sts::123456789012:assumed-role/smoke/session + smoke:session + smoke"#, + ), + ), + ) + }) + } + } + + #[rstest::rstest] + #[tokio::test] + async fn role_profile_uses_region_when_acquiring_sts_credentials() { + use aws_smithy_runtime_api::client::http::{SharedHttpConnector, http_client_fn}; + let files = aws_runtime::env_config::file::EnvConfigFiles::builder() + .include_default_config_file(false) + .include_default_credentials_file(false) + .with_contents( + aws_runtime::env_config::file::EnvConfigFileKind::Config, + "[profile smoke]\nrole_arn = arn:aws:iam::123456789012:role/smoke\nsource_profile = source\n\n[profile source]\naws_access_key_id = source-access\naws_secret_access_key = source-secret\n", + ).build(); + let config = aws_config::provider_config::ProviderConfig::without_region() + .with_http_client(http_client_fn(|_, _| { + SharedHttpConnector::new(StsConnector) + })); + let credentials = profile_provider( + "smoke", + Some("us-west-2".into()), + config, + aws_config::profile::ProfileFileCredentialsProvider::builder().profile_files(files), + ) + .await + .unwrap(); + let credentials = credentials.provide_credentials().await.unwrap(); + assert_eq!(credentials.access_key_id(), "role-access"); + assert_eq!(credentials.secret_access_key(), "role-secret"); + assert_eq!(credentials.session_token(), Some("role-session")); + assert!(credentials.expiry().is_some()); + } + fn no_env(_: &str) -> Option { None } + #[rstest::rstest] + #[case::access_key(Some("source-access"), None)] + #[case::secret_key(None, Some("source-secret"))] + #[case::source_pair(Some("source-access"), Some("source-secret"))] + #[tokio::test] + async fn explicit_source_keys_cannot_reuse_an_ambient_role( + #[case] access_key: Option<&str>, + #[case] secret_key: Option<&str>, + ) { + let role = "arn:aws:iam::123456789012:role/target"; + let config = AwsAuthConfig { + access_key_id: access_key.map(SecretValue::new), + secret_access_key: secret_key.map(SecretValue::new), + ..Default::default() + }; + assert!( + !is_already_running_as_role(role, Some(role), &config) + .await + .unwrap() + ); + } + #[test] fn secret_names_cover_environment_reads() { let seen = std::sync::Arc::new(std::sync::Mutex::new( @@ -706,7 +982,10 @@ mod tests { }; assert_eq!( - aws_auth_config(¶ms, &env).secret_access_key.as_deref(), + aws_auth_config(¶ms, &env) + .secret_access_key + .as_ref() + .map(SecretValue::expose), expected ); assert_eq!( @@ -831,6 +1110,53 @@ mod tests { ); } + #[rstest::rstest] + #[case::running_with_web_identity("/var/run/token", Some("arn:aws:iam::1:role/current"))] + #[case::empty_token_file("", None)] + #[tokio::test] + async fn assume_role_reads_the_ambient_role_from_the_secret_snapshot( + #[case] token_file: &str, + #[case] expected: Option<&str>, + ) { + use litellm_secrets::source::SecretSource; + + struct WebIdentitySecrets<'a>(&'a str); + + impl SecretSource for WebIdentitySecrets<'_> { + fn get_secret_str<'a>( + &'a self, + name: &'a str, + ) -> futures_util::future::BoxFuture< + 'a, + Result, litellm_secrets::Error>, + > { + Box::pin(async move { + Ok(match name { + AWS_WEB_IDENTITY_TOKEN_FILE => Some(SecretValue::new(self.0)), + AWS_ROLE_ARN => Some(SecretValue::new("arn:aws:iam::1:role/current")), + _ => None, + }) + }) + } + } + + let snapshot = WebIdentitySecrets(token_file) + .resolve(AwsParams::secret_names()) + .await + .unwrap(); + let config = AwsAuthConfig { + role_name: Some("arn:aws:iam::1:role/target".into()), + ..Default::default() + }; + let AwsAuthFlow::AssumeRole { + web_identity_role, .. + } = classify_auth(config, &|name| snapshot.get(name)) + else { + panic!("a role name selects AssumeRole"); + }; + assert_eq!(web_identity_role.as_deref(), expected); + } + #[tokio::test] async fn static_credentials_do_not_use_network() { let credentials = AwsAuthService::default() @@ -849,110 +1175,231 @@ mod tests { assert_eq!(credentials.session_token(), None); } - #[test] - fn cache_policy_matches_python_flows() { - assert_eq!( - credential_cache_ttl(&AwsAuthFlow::StaticKeys { - access_key_id: "ak".into(), - secret_access_key: "sk".into(), - region_name: "us-east-1".into(), - }), - Some(STATIC_CREDENTIALS_TTL) - ); - assert_eq!( - credential_cache_ttl(&AwsAuthFlow::DefaultChain), - Some(AMBIENT_CREDENTIALS_TTL) - ); - assert_eq!( - credential_cache_ttl(&AwsAuthFlow::SessionToken { - access_key_id: "ak".into(), - secret_access_key: "sk".into(), - session_token: "token".into(), - }), - None - ); - assert_eq!( - credential_cache_ttl(&AwsAuthFlow::Profile { - name: "profile".into() - }), - None - ); - assert_eq!( - credential_cache_ttl(&AwsAuthFlow::AssumeRole { - role: "arn:aws:iam::123456789012:role/demo".into(), - session_name: None, - }), - None - ); - assert_eq!( - credential_cache_ttl(&AwsAuthFlow::WebIdentity { - token: "token".into(), - role: "arn:aws:iam::123456789012:role/demo".into(), - session_name: "session".into(), - }), - None - ); + struct CountingLoader { + loads: Arc, + calls: Arc, + short_lifetime: Duration, + short_calls: usize, + } + + impl ProviderLoader for CountingLoader { + fn load(&self, config: AwsAuthConfig, _: AwsAuthFlow) -> ProviderFuture<'_> { + let loads = self.loads.clone(); + let provider = CountingProvider { + calls: self.calls.clone(), + short_lifetime: self.short_lifetime, + short_calls: self.short_calls, + key: config.access_key_id.unwrap(), + }; + Box::pin(async move { + loads.fetch_add(1, std::sync::atomic::Ordering::SeqCst); + Ok(SharedCredentialsProvider::new(provider)) + }) + } + } + + #[derive(Debug)] + struct CountingProvider { + calls: Arc, + short_lifetime: Duration, + short_calls: usize, + key: SecretValue, + } + + impl ProvideCredentials for CountingProvider { + fn provide_credentials<'a>( + &'a self, + ) -> aws_credential_types::provider::future::ProvideCredentials<'a> + where + Self: 'a, + { + aws_credential_types::provider::future::ProvideCredentials::new(async move { + tokio::task::yield_now().await; + let call = self.calls.fetch_add(1, std::sync::atomic::Ordering::SeqCst); + let lifetime = if call < self.short_calls { + self.short_lifetime + } else { + Duration::from_secs(3600) + }; + Ok(Credentials::new( + self.key.expose(), + "credential-value", + Some(format!("session-{call}")), + Some(SystemTime::now() + lifetime), + "counting", + )) + }) + } + } + + #[derive(Default)] + struct RecordingLoader { + loads: std::sync::Mutex>, + } + + impl ProviderLoader for RecordingLoader { + fn load(&self, config: AwsAuthConfig, flow: AwsAuthFlow) -> ProviderFuture<'_> { + self.loads.lock().unwrap().push((config, flow)); + Box::pin(async { + Ok(SharedCredentialsProvider::new(Credentials::new( + "ak", + "sk", + None, + None, + "recording", + ))) + }) + } } #[rstest::rstest] - fn cache_round_trip_preserves_credentials() { - let auth = AwsAuthService::default(); - let key = format!("cache-test-{}", std::process::id()); - let credentials = Credentials::new("cache-ak", "cache-sk", None, None, "test"); - auth.set_cached_credentials(key.clone(), credentials.clone(), STATIC_CREDENTIALS_TTL); + #[tokio::test] + async fn default_chain_credentials_do_not_share_a_configured_role_in_the_same_region() { + let loader = Arc::new(RecordingLoader::default()); + let auth = AwsAuthService::new(loader.clone()); + let bedrock_env = |name: &str| match name { + AWS_ROLE_NAME => Some("arn:aws:iam::123456789012:role/bedrock".to_string()), + AWS_REGION_NAME => Some("us-east-1".to_string()), + _ => None, + }; + auth.resolve_credentials(AwsAuthConfig::default(), &bedrock_env) + .await + .unwrap(); + + auth.default_chain_credentials("us-east-1").await.unwrap(); + auth.default_chain_credentials("us-east-1").await.unwrap(); + + let loads = loader.loads.lock().unwrap(); + assert_eq!(loads.len(), 2); assert_eq!( - auth.get_cached_credentials(&key) - .map(|value| value.access_key_id().to_string()), - Some("cache-ak".to_string()) + loads[1], + ( + AwsAuthConfig { + region_name: Some("us-east-1".to_string()), + ..Default::default() + }, + AwsAuthFlow::DefaultChain + ) ); } #[rstest::rstest] #[tokio::test] - async fn cloned_services_reuse_credentials_but_independent_services_do_not() { - let auth = AwsAuthService::default(); + async fn near_expiry_credentials_are_refreshed_without_rebuilding_the_provider() { + use std::sync::atomic::{AtomicUsize, Ordering}; + let loads = Arc::new(AtomicUsize::new(0)); + let calls = Arc::new(AtomicUsize::new(0)); + let auth = AwsAuthService::new(Arc::new(CountingLoader { + loads: loads.clone(), + calls: calls.clone(), + short_lifetime: Duration::from_secs(30), + short_calls: 1, + })); let config = AwsAuthConfig { - access_key_id: Some("configured-key".into()), - secret_access_key: Some("configured-secret".into()), - region_name: Some("us-east-1".into()), - ..AwsAuthConfig::default() + access_key_id: Some("identity".into()), + ..Default::default() }; - let flow = classify_auth(config.clone(), &no_env); - let cached = Credentials::new("cached-key", "cached-secret", None, None, "test"); - auth.set_cached_credentials( - cache_key(&config, &flow), - cached.clone(), - STATIC_CREDENTIALS_TTL, - ); - - let reused = auth + let first = auth + .resolve_credentials(config.clone(), &no_env) + .await + .unwrap(); + let second = auth .clone() .resolve_credentials(config.clone(), &no_env) .await .unwrap(); - let independent = AwsAuthService::default() - .resolve_credentials(config.clone(), &no_env) - .await - .unwrap(); - let different = AwsAuthConfig { - access_key_id: Some("different-key".into()), - ..config.clone() - }; - let other_identity = auth - .resolve_credentials(different.clone(), &no_env) - .await - .unwrap(); + assert_eq!(first.session_token(), Some("session-1")); + assert_eq!(first.session_token(), second.session_token()); + assert_eq!(loads.load(Ordering::SeqCst), 1); + assert_eq!(calls.load(Ordering::SeqCst), 2); + } - assert_eq!(reused.access_key_id(), cached.access_key_id()); - assert_eq!(reused.secret_access_key(), cached.secret_access_key()); + #[rstest::rstest] + #[case::recovered_by_one_refetch(1, Some("session-1"))] + #[case::still_expired_after_refetch(2, None)] + #[tokio::test] + async fn expired_credentials_are_refetched_once( + #[case] short_calls: usize, + #[case] session: Option<&str>, + ) { + use std::sync::atomic::{AtomicUsize, Ordering}; + let calls = Arc::new(AtomicUsize::new(0)); + let auth = AwsAuthService::new(Arc::new(CountingLoader { + loads: Arc::new(AtomicUsize::new(0)), + calls: calls.clone(), + short_lifetime: Duration::ZERO, + short_calls, + })); + let config = AwsAuthConfig { + access_key_id: Some("identity".into()), + ..Default::default() + }; + let result = auth.resolve_credentials(config, &no_env).await; assert_eq!( - Some(independent.access_key_id()), - config.access_key_id.as_deref() + result.as_ref().ok().and_then(Credentials::session_token), + session ); - assert_eq!( - Some(other_identity.access_key_id()), - different.access_key_id.as_deref() + assert!(session.is_some() || matches!(result, Err(Error::ExpiredCredentials))); + assert_eq!(calls.load(Ordering::SeqCst), 2); + } + + #[rstest::rstest] + #[tokio::test] + async fn concurrent_calls_share_acquisition_and_distinct_identities_stay_isolated() { + use std::sync::atomic::{AtomicUsize, Ordering}; + let loads = Arc::new(AtomicUsize::new(0)); + let calls = Arc::new(AtomicUsize::new(0)); + let auth = AwsAuthService::new(Arc::new(CountingLoader { + loads: loads.clone(), + calls: calls.clone(), + short_lifetime: Duration::from_secs(3600), + short_calls: 0, + })); + let first = AwsAuthConfig { + access_key_id: Some("first".into()), + ..Default::default() + }; + let second = AwsAuthConfig { + access_key_id: Some("second".into()), + ..Default::default() + }; + let (a, b, c) = tokio::join!( + auth.resolve_credentials(first.clone(), &no_env), + auth.resolve_credentials(first, &no_env), + auth.resolve_credentials(second, &no_env) ); + let a = a.unwrap(); + let b = b.unwrap(); + let c = c.unwrap(); + assert_eq!(a.session_token(), b.session_token()); + assert_ne!(a.access_key_id(), c.access_key_id()); + assert_eq!(loads.load(Ordering::SeqCst), 2); + assert_eq!(calls.load(Ordering::SeqCst), 2); + } + + #[rstest::rstest] + fn auth_config_debug_never_discloses_credentials() { + let config = AwsAuthConfig { + access_key_id: Some("credential-value".into()), + secret_access_key: Some("credential-value".into()), + session_token: Some("credential-value".into()), + web_identity_token: Some("credential-value".into()), + external_id: Some("credential-value".into()), + ..Default::default() + }; + let output = format!("{config:?}"); + assert!(!output.contains("credential-value")); + assert!(output.contains("[REDACTED]")); + } + + #[rstest::rstest] + #[case::session(AwsAuthFlow::SessionToken { access_key_id: "credential-value".into(), secret_access_key: "credential-value".into(), session_token: "credential-value".into() })] + #[case::static_keys(AwsAuthFlow::StaticKeys { access_key_id: "credential-value".into(), secret_access_key: "credential-value".into(), region_name: "region".into() })] + #[case::web_identity(AwsAuthFlow::WebIdentity { token: "credential-value".into(), role: "role".into(), session_name: "session".into() })] + fn auth_flow_debug_never_discloses_credentials(#[case] flow: AwsAuthFlow) { + let output = format!("{flow:?}"); + assert!(!output.contains("credential-value")); + assert!(output.contains("[REDACTED]")); } #[test] @@ -1142,8 +1589,8 @@ mod tests { let credentials = AwsAuthService::default() .resolve_credentials( AwsAuthConfig { - access_key_id: Some(access_key_id), - secret_access_key: Some(secret_access_key), + access_key_id: Some(access_key_id.into()), + secret_access_key: Some(secret_access_key.into()), region_name: Some("us-west-2".to_string()), ..Default::default() }, @@ -1191,4 +1638,44 @@ mod tests { failures.join("; ") ); } + + #[rstest::rstest] + #[case::provisioned( + None, + "https://cache-1/?Action=connect&User=iam-user", + "cache-1/?Action=connect&User=iam-user&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIDEXAMPLE%2F20261029%2Fus-east-1%2Felasticache%2Faws4_request&X-Amz-Date=20261029T120000Z&X-Amz-Expires=900&X-Amz-SignedHeaders=host&X-Amz-Signature=dfa58492a6ae9ba065088724170a52437329d03f3e9bc9a4c90a80cc8a18e2f6" + )] + #[case::serverless_with_a_session_token( + Some("session-token"), + "https://cache-1/?Action=connect&User=iam-user&ResourceType=ServerlessCache", + "cache-1/?Action=connect&User=iam-user&ResourceType=ServerlessCache&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIDEXAMPLE%2F20261029%2Fus-east-1%2Felasticache%2Faws4_request&X-Amz-Date=20261029T120000Z&X-Amz-Expires=900&X-Amz-SignedHeaders=host&X-Amz-Security-Token=session-token&X-Amz-Signature=e48bdbb3bf9d5e8f1d325bf33d5260e333df1f6b8868e8edd1e4c3cc01b4c3f9" + )] + fn presigned_urls_match_botocore_sigv4_query_auth( + #[case] session_token: Option<&str>, + #[case] url: &str, + #[case] expected: &str, + ) { + // Expected values from botocore 1.43.117 SigV4QueryAuth with get_current_datetime patched to + // 2026-10-29T12:00:00Z (generated 2026-10-29), the signer Python's ElastiCache IAM provider uses + let credentials = Credentials::new( + "AKIDEXAMPLE", + "wJalrXUtnFEMI/K7MDENG+bPxRfiCYEXAMPLEKEY", + session_token.map(str::to_owned), + None, + "test", + ); + let signed = presign_url( + url, + Duration::from_secs(900), + SigningScope { + region: "us-east-1", + service: "elasticache", + credentials: &credentials, + time: UNIX_EPOCH + Duration::from_secs(1_793_275_200), + }, + ) + .unwrap(); + + assert_eq!(signed.strip_prefix("https://"), Some(expected)); + } } diff --git a/litellm-rust/crates/auth-aws/src/constants.rs b/litellm-rust/crates/auth-aws/src/constants.rs index 789fde156bd..0e4662eda9e 100644 --- a/litellm-rust/crates/auth-aws/src/constants.rs +++ b/litellm-rust/crates/auth-aws/src/constants.rs @@ -11,8 +11,8 @@ pub const AWS_SESSION_NAME: &str = AwsParams::SESSION_NAME.env[0]; pub const AWS_PROFILE_NAME: &str = AwsParams::PROFILE_NAME.env[0]; pub const AWS_ROLE_NAME: &str = AwsParams::ROLE_NAME.env[0]; pub const AWS_WEB_IDENTITY_TOKEN: &str = AwsParams::WEB_IDENTITY_TOKEN.env[0]; -pub const AWS_ROLE_ARN: &str = "AWS_ROLE_ARN"; -pub const AWS_WEB_IDENTITY_TOKEN_FILE: &str = "AWS_WEB_IDENTITY_TOKEN_FILE"; +pub const AWS_ROLE_ARN: &str = AwsParams::ROLE_ARN_ENV; +pub const AWS_WEB_IDENTITY_TOKEN_FILE: &str = AwsParams::WEB_IDENTITY_TOKEN_FILE_ENV; pub const AWS_STS_ENDPOINT: &str = AwsParams::STS_ENDPOINT.env[0]; pub const AWS_EXTERNAL_ID: &str = AwsParams::EXTERNAL_ID.env[0]; pub const AWS_BEARER_TOKEN_BEDROCK: &str = "AWS_BEARER_TOKEN_BEDROCK"; diff --git a/litellm-rust/crates/auth-aws/src/error.rs b/litellm-rust/crates/auth-aws/src/error.rs index 5f88fc8a171..5445de1e6c3 100644 --- a/litellm-rust/crates/auth-aws/src/error.rs +++ b/litellm-rust/crates/auth-aws/src/error.rs @@ -2,6 +2,8 @@ use litellm_error::Source; #[derive(Clone, Debug, thiserror::Error, PartialEq, Eq)] pub enum Error { + #[error("AWS credential provider returned expired credentials")] + ExpiredCredentials, #[error("could not load AWS {flow} credentials")] Credentials { flow: CredentialFlow, diff --git a/litellm-rust/crates/auth-aws/src/signer.rs b/litellm-rust/crates/auth-aws/src/signer.rs index dff917d7c13..2d9ad9ba123 100644 --- a/litellm-rust/crates/auth-aws/src/signer.rs +++ b/litellm-rust/crates/auth-aws/src/signer.rs @@ -75,7 +75,8 @@ impl RequestSigner for SigV4Signer { ) .map_err(|error| match error { Error::NonAsciiHeader { .. } => litellm_http::Error::unsignable_header(error), - Error::Credentials { .. } + Error::ExpiredCredentials + | Error::Credentials { .. } | Error::MissingWebIdentityCredentials | Error::WebIdentityExpiration(_) | Error::Signing { .. } => litellm_http::Error::signature(error), diff --git a/litellm-rust/crates/auth-azure/Cargo.toml b/litellm-rust/crates/auth-azure/Cargo.toml index 7dcb0e513a7..36c10a74c80 100644 --- a/litellm-rust/crates/auth-azure/Cargo.toml +++ b/litellm-rust/crates/auth-azure/Cargo.toml @@ -8,17 +8,19 @@ repository.workspace = true [dependencies] litellm-secret-value.workspace = true litellm-auth-types.workspace = true +litellm-error.workspace = true moka.workspace = true serde_json.workspace = true sha2.workspace = true strum.workspace = true +tokio.workspace = true url.workspace = true azure_core = "1.0.0" azure_identity = { version = "1.0.0", features = ["tokio"] } [dev-dependencies] -litellm-error.workspace = true +litellm-secrets.workspace = true rstest.workspace = true -tokio.workspace = true +tokio = { workspace = true, features = ["test-util"] } diff --git a/litellm-rust/crates/auth-azure/src/lib.rs b/litellm-rust/crates/auth-azure/src/lib.rs index 9ed505e4160..6319406ce9c 100644 --- a/litellm-rust/crates/auth-azure/src/lib.rs +++ b/litellm-rust/crates/auth-azure/src/lib.rs @@ -3,5 +3,5 @@ mod native; mod resolve; mod types; -pub use resolve::{AzureAuthService, SECRET_NAMES}; +pub use resolve::{AzureAuthService, AzureIdentity, SECRET_NAMES}; pub use types::{AzureAuthInputs, ConfigValue}; diff --git a/litellm-rust/crates/auth-azure/src/native.rs b/litellm-rust/crates/auth-azure/src/native.rs index f40745ab7a2..03021428ea7 100644 --- a/litellm-rust/crates/auth-azure/src/native.rs +++ b/litellm-rust/crates/auth-azure/src/native.rs @@ -59,6 +59,7 @@ pub(crate) enum NativeAzureRequest { pub(crate) struct ValidatedAzureRequest { request: NativeAzureRequest, credential_source: InputSource, + probe_imds: bool, } impl ValidatedAzureRequest { @@ -68,9 +69,18 @@ impl ValidatedAzureRequest { Ok(Self { request, credential_source, + probe_imds: false, }) } + pub(crate) fn with_imds_probe(self, enabled: bool) -> Self { + Self { + probe_imds: enabled + && matches!(self.request, NativeAzureRequest::ManagedIdentity { .. }), + ..self + } + } + pub(crate) fn credential_source(&self) -> InputSource { self.credential_source } @@ -87,9 +97,34 @@ impl ValidatedAzureRequest { } } +pub(crate) enum CredentialAttempt { + Resolved(ResolvedCredential), + Unavailable(Error), + Failed(Error), +} + +impl CredentialAttempt { + pub(crate) fn into_result(self) -> Result { + match self { + Self::Resolved(credential) => Ok(credential), + Self::Unavailable(error) | Self::Failed(error) => Err(error), + } + } +} + pub(crate) struct NativeAzureTokenAcquirer { cache: AzureCredentialProviderCache, transport: Option, + imds_available: tokio::sync::Mutex, +} + +enum ImdsAvailability { + Unknown, + Available, + Unavailable { + retry_at: tokio::time::Instant, + error: Error, + }, } impl Default for NativeAzureTokenAcquirer { @@ -103,6 +138,7 @@ impl NativeAzureTokenAcquirer { Self { cache: AzureCredentialProviderCache::new(cache_capacity), transport: None, + imds_available: tokio::sync::Mutex::new(ImdsAvailability::Unknown), } } @@ -114,10 +150,51 @@ impl NativeAzureTokenAcquirer { Self { cache: AzureCredentialProviderCache::new(cache_capacity), transport: Some(transport), + imds_available: tokio::sync::Mutex::new(ImdsAvailability::Unknown), } } - pub(crate) async fn acquire( + pub(crate) async fn acquire(&self, request: ValidatedAzureRequest) -> CredentialAttempt { + let discover_imds = request.probe_imds; + if discover_imds && let Err(error) = self.discover_imds().await { + return CredentialAttempt::Unavailable(error); + } + match self.acquire_token(request).await { + Ok(credential) => CredentialAttempt::Resolved(credential), + Err(error) => { + let missing_identity = discover_imds && unassigned_identity(&error); + if missing_identity { + CredentialAttempt::Unavailable(error) + } else { + CredentialAttempt::Failed(error) + } + } + } + } + + async fn discover_imds(&self) -> Result<(), Error> { + let mut availability = self.imds_available.lock().await; + match &*availability { + ImdsAvailability::Available => return Ok(()), + ImdsAvailability::Unavailable { retry_at, error } + if tokio::time::Instant::now() < *retry_at => + { + return Err(error.clone()); + } + ImdsAvailability::Unknown | ImdsAvailability::Unavailable { .. } => {} + } + let result = probe_imds(self.transport.clone().unwrap_or_default()).await; + *availability = match &result { + Ok(()) => ImdsAvailability::Available, + Err(error) => ImdsAvailability::Unavailable { + retry_at: tokio::time::Instant::now() + Duration::from_secs(30), + error: error.clone(), + }, + }; + result + } + + async fn acquire_token( &self, request: ValidatedAzureRequest, ) -> Result { @@ -148,6 +225,54 @@ impl NativeAzureTokenAcquirer { } } +fn unassigned_identity(error: &(dyn std::error::Error + 'static)) -> bool { + std::iter::successors(Some(error), |cause| cause.source()).any(|cause| { + cause + .downcast_ref::() + .or_else(|| { + cause + .downcast_ref::()? + .downcast_ref::() + }) + .is_some_and(|error| { + error.http_status() == Some(azure_core::http::StatusCode::BadRequest) + }) + }) +} + +async fn probe_imds(transport: azure_core::http::Transport) -> Result<(), Error> { + use azure_core::http::{Context, Method, Request, Url}; + + let endpoint = + Url::parse("http://169.254.169.254/metadata/identity/oauth2/token?api-version=2019-08-01") + .map_err(|error| { + Error::InvalidConfiguration(ErrorDetail::failed("Azure IMDS probe endpoint", error)) + })?; + let mut request = Request::new(endpoint, Method::Get); + let response = tokio::time::timeout( + Duration::from_secs(1), + transport.send(&Context::new(), &mut request), + ) + .await + .map_err(|error| { + Error::CredentialAcquisition(ErrorDetail::failed("Azure IMDS availability probe", error)) + })? + .map_err(|error| { + Error::CredentialAcquisition(ErrorDetail::failed("Azure IMDS availability probe", error)) + })?; + // Headerless IMDS discovery expects 400, checked 2026-11-01 + // https://learn.microsoft.com/en-us/azure/virtual-machines/instance-metadata-service#errors-and-debugging + if response.status() != azure_core::http::StatusCode::BadRequest { + return Err(Error::CredentialAcquisition( + ErrorDetail::UnexpectedStatus { + operation: "Azure IMDS availability probe", + status: u16::from(response.status()), + }, + )); + } + Ok(()) +} + impl NativeAzureRequest { fn scope(&self) -> &str { match self { @@ -493,6 +618,7 @@ impl ClientAssertion for StaticAssertion { #[cfg(test)] mod tests { use std::sync::{Arc, Mutex}; + use std::time::Duration; use azure_core::http::headers::Headers; use azure_core::http::{AsyncRawResponse, HttpClient, Request, StatusCode, Transport}; @@ -569,6 +695,296 @@ mod tests { } } + #[derive(Debug)] + struct AvailableImdsClient { + probe_status: StatusCode, + probe_delay: Duration, + recover_after: Option, + response_status: Option, + probes: std::sync::atomic::AtomicUsize, + } + + impl Default for AvailableImdsClient { + fn default() -> Self { + Self { + probe_status: StatusCode::BadRequest, + probe_delay: Duration::ZERO, + recover_after: None, + response_status: None, + probes: std::sync::atomic::AtomicUsize::new(0), + } + } + } + + impl HttpClient for AvailableImdsClient { + fn execute_request<'life0, 'life1, 'async_trait>( + &'life0 self, + request: &'life1 Request, + ) -> std::pin::Pin< + Box> + Send + 'async_trait>, + > + where + 'life0: 'async_trait, + 'life1: 'async_trait, + Self: 'async_trait, + { + Box::pin(async move { + if request + .headers() + .get_optional_str(&azure_core::http::headers::HeaderName::from_static( + "metadata", + )) + .is_none() + { + let probe = self + .probes + .fetch_add(1, std::sync::atomic::Ordering::SeqCst); + if self.recover_after.is_some_and(|failures| probe >= failures) { + return Ok(AsyncRawResponse::from_bytes( + StatusCode::BadRequest, + Headers::new(), + "metadata header required", + )); + } + tokio::time::sleep(self.probe_delay).await; + return Ok(AsyncRawResponse::from_bytes( + self.probe_status, + Headers::new(), + "metadata header required", + )); + } + if let Some(status) = self.response_status { + return Ok(AsyncRawResponse::from_bytes( + status, + Headers::new(), + "identity endpoint failure", + )); + } + tokio::time::sleep(std::time::Duration::from_secs(2)).await; + let expires = std::time::SystemTime::now() + .duration_since(std::time::UNIX_EPOCH) + .unwrap() + .as_secs() + + 3600; + Ok(AsyncRawResponse::from_bytes( + StatusCode::Ok, + Headers::new(), + serde_json::json!({ + "access_token": "managed-token", "expires_on": expires.to_string(), + "token_type": "Bearer", "resource": "https://service.test", + }) + .to_string(), + )) + }) + } + } + + #[rstest::rstest] + #[tokio::test(start_paused = true)] + async fn available_imds_retains_full_sdk_token_acquisition() { + let acquirer = NativeAzureTokenAcquirer::with_transport( + 4, + Transport::new(Arc::new(AvailableImdsClient { + probe_status: StatusCode::BadRequest, + response_status: None, + ..Default::default() + })), + ); + let request = ValidatedAzureRequest::new(NativeAzureRequest::ManagedIdentity { + client_id: None, + scope: deployment("https://service.test/.default".into()), + selection_source: InputSource::Deployment, + }) + .unwrap() + .with_imds_probe(true); + let credential = acquirer.acquire(request).await.into_result().unwrap(); + assert_eq!(credential.secret().expose(), "managed-token"); + } + + #[rstest::rstest] + #[case::another_metadata_service(StatusCode::NotFound)] + #[case::token_required(StatusCode::Unauthorized)] + #[case::proxy_rejection(StatusCode::Forbidden)] + #[case::unavailable(StatusCode::ServiceUnavailable)] + #[tokio::test(start_paused = true)] + async fn unrelated_metadata_responses_do_not_start_managed_identity_acquisition( + #[case] status: StatusCode, + ) { + let client = Arc::new(AvailableImdsClient { + probe_status: status, + ..Default::default() + }); + let acquirer = NativeAzureTokenAcquirer::with_transport(4, Transport::new(client.clone())); + let request = ValidatedAzureRequest::new(NativeAzureRequest::ManagedIdentity { + client_id: None, + scope: deployment("https://service.test/.default".into()), + selection_source: InputSource::Deployment, + }) + .unwrap() + .with_imds_probe(true); + assert!(matches!( + acquirer.acquire(request.clone()).await, + super::CredentialAttempt::Unavailable(_) + )); + assert!(matches!( + acquirer.acquire(request).await, + super::CredentialAttempt::Unavailable(_) + )); + assert_eq!(client.probes.load(std::sync::atomic::Ordering::SeqCst), 1); + } + + #[rstest::rstest] + #[tokio::test(start_paused = true)] + async fn an_imds_timeout_is_not_repeated_on_the_next_request() { + let client = Arc::new(AvailableImdsClient { + probe_delay: Duration::from_secs(10), + ..Default::default() + }); + let acquirer = NativeAzureTokenAcquirer::with_transport(4, Transport::new(client.clone())); + let request = ValidatedAzureRequest::new(NativeAzureRequest::ManagedIdentity { + client_id: None, + scope: deployment("https://service.test/.default".into()), + selection_source: InputSource::Deployment, + }) + .unwrap() + .with_imds_probe(true); + assert!(matches!( + acquirer.acquire(request.clone()).await, + super::CredentialAttempt::Unavailable(_) + )); + let second = tokio::time::timeout(Duration::from_millis(10), acquirer.acquire(request)) + .await + .unwrap(); + assert!(matches!(second, super::CredentialAttempt::Unavailable(_))); + assert_eq!(client.probes.load(std::sync::atomic::Ordering::SeqCst), 1); + } + + #[rstest::fixture] + fn imds_request() -> ValidatedAzureRequest { + ValidatedAzureRequest::new(NativeAzureRequest::ManagedIdentity { + client_id: None, + scope: deployment("https://service.test/.default".into()), + selection_source: InputSource::Deployment, + }) + .unwrap() + .with_imds_probe(true) + } + + #[rstest::rstest] + #[case::timeout(StatusCode::BadRequest, Duration::from_secs(10))] + #[case::service_unavailable(StatusCode::ServiceUnavailable, Duration::ZERO)] + #[tokio::test(start_paused = true)] + async fn failed_imds_discovery_recovers_without_restarting_the_acquirer( + imds_request: ValidatedAzureRequest, + #[case] status: StatusCode, + #[case] delay: Duration, + ) { + let client = Arc::new(AvailableImdsClient { + probe_status: status, + probe_delay: delay, + recover_after: Some(1), + ..Default::default() + }); + let acquirer = NativeAzureTokenAcquirer::with_transport(4, Transport::new(client.clone())); + let (first, second) = tokio::join!( + acquirer.acquire(imds_request.clone()), + acquirer.acquire(imds_request.clone()), + ); + assert!(matches!(first, super::CredentialAttempt::Unavailable(_))); + assert!(matches!(second, super::CredentialAttempt::Unavailable(_))); + assert_eq!(client.probes.load(std::sync::atomic::Ordering::SeqCst), 1); + + tokio::time::advance(Duration::from_secs(30)).await; + let (first, second) = tokio::join!( + acquirer.acquire(imds_request.clone()), + acquirer.acquire(imds_request.clone()), + ); + assert_eq!( + first.into_result().unwrap().secret().expose(), + "managed-token" + ); + assert_eq!( + second.into_result().unwrap().secret().expose(), + "managed-token" + ); + assert_eq!(client.probes.load(std::sync::atomic::Ordering::SeqCst), 2); + + tokio::time::advance(Duration::from_secs(60)).await; + assert_eq!( + acquirer + .acquire(imds_request) + .await + .into_result() + .unwrap() + .secret() + .expose(), + "managed-token", + ); + assert_eq!(client.probes.load(std::sync::atomic::Ordering::SeqCst), 2); + } + + #[rstest::rstest] + #[tokio::test(start_paused = true)] + async fn a_persistent_imds_outage_reuses_each_failed_probe( + imds_request: ValidatedAzureRequest, + ) { + let client = Arc::new(AvailableImdsClient { + probe_delay: Duration::from_secs(10), + ..Default::default() + }); + let acquirer = NativeAzureTokenAcquirer::with_transport(4, Transport::new(client.clone())); + assert!(matches!( + acquirer.acquire(imds_request.clone()).await, + super::CredentialAttempt::Unavailable(_), + )); + tokio::time::advance(Duration::from_secs(30)).await; + let (first, second) = tokio::join!( + acquirer.acquire(imds_request.clone()), + acquirer.acquire(imds_request), + ); + assert!(matches!(first, super::CredentialAttempt::Unavailable(_))); + assert!(matches!(second, super::CredentialAttempt::Unavailable(_))); + assert_eq!(client.probes.load(std::sync::atomic::Ordering::SeqCst), 2); + } + + #[rstest::rstest] + #[case::default_identity_not_assigned(true, StatusCode::BadRequest, true)] + #[case::explicit_identity_not_assigned(false, StatusCode::BadRequest, false)] + #[case::default_identity_forbidden(true, StatusCode::Forbidden, false)] + #[case::default_identity_service_failure(true, StatusCode::InternalServerError, false)] + #[tokio::test(start_paused = true)] + async fn only_unavailable_default_identities_allow_fallback( + #[case] discovery: bool, + #[case] status: StatusCode, + #[case] unavailable: bool, + ) { + let acquirer = NativeAzureTokenAcquirer::with_transport( + 4, + Transport::new(Arc::new(AvailableImdsClient { + probe_status: StatusCode::BadRequest, + response_status: Some(status), + ..Default::default() + })), + ); + let request = ValidatedAzureRequest::new(NativeAzureRequest::ManagedIdentity { + client_id: None, + scope: deployment("https://service.test/.default".into()), + selection_source: InputSource::Deployment, + }) + .unwrap() + .with_imds_probe(discovery); + let outcome = acquirer.acquire(request).await; + let is_unavailable = matches!(outcome, super::CredentialAttempt::Unavailable(_)); + let error = outcome.into_result().unwrap_err(); + assert_eq!( + is_unavailable, + unavailable, + "{}", + litellm_error::Report::new(&error) + ); + } + + #[rstest::rstest] #[tokio::test] async fn client_secret_uses_sdk_protocol_and_reuses_cached_credential() { let transport = Arc::new(RecordingTokenClient::default()); @@ -582,8 +998,12 @@ mod tests { "https://login.test", ); - let first = acquirer.acquire(request.clone()).await.unwrap(); - let second = acquirer.acquire(request).await.unwrap(); + let first = acquirer + .acquire(request.clone()) + .await + .into_result() + .unwrap(); + let second = acquirer.acquire(request).await.into_result().unwrap(); assert_eq!(first.secret().expose(), "native-token"); assert_eq!(second.secret().expose(), "native-token"); @@ -599,6 +1019,7 @@ mod tests { ); } + #[rstest::rstest] #[tokio::test] async fn credential_provider_cache_isolates_every_client_secret_identity_field() { let transport = Arc::new(RecordingTokenClient::default()); @@ -645,10 +1066,10 @@ mod tests { ), ]; - acquirer.acquire(base.clone()).await.unwrap(); - acquirer.acquire(base).await.unwrap(); + acquirer.acquire(base.clone()).await.into_result().unwrap(); + acquirer.acquire(base).await.into_result().unwrap(); for request in variants.into_iter().skip(1) { - acquirer.acquire(request).await.unwrap(); + acquirer.acquire(request).await.into_result().unwrap(); } assert_eq!(transport.requests.lock().unwrap().len(), 6); diff --git a/litellm-rust/crates/auth-azure/src/resolve.rs b/litellm-rust/crates/auth-azure/src/resolve.rs index a92630af26a..9ff4eda540a 100644 --- a/litellm-rust/crates/auth-azure/src/resolve.rs +++ b/litellm-rust/crates/auth-azure/src/resolve.rs @@ -1,3 +1,4 @@ +use crate::native::CredentialAttempt; use litellm_auth_types::{ CredentialFileRef, CredentialLookup, CredentialRef, InputSource, ResolvedCredential, Sourced, TokenProviderHandle, @@ -12,25 +13,31 @@ use std::sync::Arc; use super::native::{NativeAzureRequest, NativeAzureTokenAcquirer, ValidatedAzureRequest}; use super::types::{AzureAuthInputs, AzureCredentialType, ConfigValue, DEFAULT_AZURE_SCOPE}; -const AZURE_AD_TOKEN_ENV: &str = "AZURE_AD_TOKEN"; -const AZURE_TENANT_ID_ENV: &str = "AZURE_TENANT_ID"; -const AZURE_CLIENT_ID_ENV: &str = "AZURE_CLIENT_ID"; -const AZURE_CLIENT_SECRET_ENV: &str = "AZURE_CLIENT_SECRET"; -const AZURE_SCOPE_ENV: &str = "AZURE_SCOPE"; -const AZURE_AUTHORITY_HOST_ENV: &str = "AZURE_AUTHORITY_HOST"; -const AZURE_CREDENTIAL_ENV: &str = "AZURE_CREDENTIAL"; -const AZURE_FEDERATED_TOKEN_FILE_ENV: &str = "AZURE_FEDERATED_TOKEN_FILE"; +#[derive(strum::IntoStaticStr, strum::VariantArray, strum::VariantNames)] +enum AzureSecretName { + #[strum(serialize = "AZURE_AD_TOKEN")] + AdToken, + #[strum(serialize = "AZURE_TENANT_ID")] + TenantId, + #[strum(serialize = "AZURE_CLIENT_ID")] + ClientId, + #[strum(serialize = "AZURE_CLIENT_SECRET")] + ClientSecret, + #[strum(serialize = "AZURE_SCOPE")] + Scope, + #[strum(serialize = "AZURE_AUTHORITY_HOST")] + AuthorityHost, + #[strum(serialize = "AZURE_CREDENTIAL")] + Credential, + #[strum(serialize = "AZURE_FEDERATED_TOKEN_FILE")] + FederatedTokenFile, + #[strum(serialize = "IDENTITY_ENDPOINT")] + IdentityEndpoint, + #[strum(serialize = "MSI_ENDPOINT")] + MsiEndpoint, +} -pub const SECRET_NAMES: &[&str] = &[ - AZURE_AD_TOKEN_ENV, - AZURE_TENANT_ID_ENV, - AZURE_CLIENT_ID_ENV, - AZURE_CLIENT_SECRET_ENV, - AZURE_SCOPE_ENV, - AZURE_AUTHORITY_HOST_ENV, - AZURE_CREDENTIAL_ENV, - AZURE_FEDERATED_TOKEN_FILE_ENV, -]; +pub const SECRET_NAMES: &[&str] = ::VARIANTS; #[derive(Clone, Debug)] pub(crate) enum AzureCredentialPlan { @@ -57,14 +64,14 @@ trait AzureTokenAcquirer: Send + Sync { fn acquire( &self, request: ValidatedAzureRequest, - ) -> Pin> + Send + '_>>; + ) -> Pin + Send + '_>>; } impl AzureTokenAcquirer for NativeAzureTokenAcquirer { fn acquire( &self, request: ValidatedAzureRequest, - ) -> Pin> + Send + '_>> { + ) -> Pin + Send + '_>> { Box::pin(NativeAzureTokenAcquirer::acquire(self, request)) } } @@ -83,12 +90,36 @@ impl AzureAuthService { Self { native } } + pub async fn identity_token( + &self, + identity: &AzureIdentity, + scope: &str, + env_lookup: &(dyn Fn(&str) -> Option + Sync), + ) -> Result, Error> { + let plan = identity_plan(identity, scope, env_lookup)?; + let inputs = AzureAuthInputs::default_credential_for_scope(scope); + Ok(self + .run_plan(plan, &inputs, env_lookup) + .await? + .map(Sourced::into_value)) + } + pub async fn get_azure_ad_token( &self, inputs: &AzureAuthInputs, env_lookup: &(dyn Fn(&str) -> Option + Sync), ) -> Result>, Error> { - match select_auth_plan(inputs, env_lookup)? { + self.run_plan(select_auth_plan(inputs, env_lookup)?, inputs, env_lookup) + .await + } + + async fn run_plan( + &self, + plan: AzureCredentialPlan, + inputs: &AzureAuthInputs, + env_lookup: &(dyn Fn(&str) -> Option + Sync), + ) -> Result>, Error> { + match plan { AzureCredentialPlan::Supplied(credential) => Ok(Some(credential)), AzureCredentialPlan::Caller(caller) => { let credential = caller.acquire().await?; @@ -123,6 +154,7 @@ impl AzureAuthService { self.native .acquire(request) .await + .into_result() .map(|credential| Sourced::new(credential, source)) .map(Some) } @@ -131,6 +163,7 @@ impl AzureAuthService { self.native .acquire(request) .await + .into_result() .map(|credential| Some(Sourced::new(credential, source))) } AzureCredentialPlan::Chain(requests) => { @@ -138,8 +171,16 @@ impl AzureAuthService { for request in requests { let source = request.credential_source(); match self.native.acquire(request).await { - Ok(credential) => return Ok(Some(Sourced::new(credential, source))), - Err(error) => failures.push(error), + CredentialAttempt::Resolved(credential) => { + return Ok(Some(Sourced::new(credential, source))); + } + CredentialAttempt::Unavailable(error) => failures.push(error), + CredentialAttempt::Failed(error) => { + return Err(Error::CredentialChain { + last: Box::new(error), + earlier: failures, + }); + } } } match failures.pop() { @@ -155,39 +196,161 @@ impl AzureAuthService { } } +/// The identity azure-identity builds for one explicit credential class, without LiteLLM's provider settings +/// (`AZURE_AD_TOKEN`, `AZURE_CREDENTIAL`, `AZURE_SCOPE`) that `get_azure_ad_token` also reads. +#[derive(Clone, Debug)] +pub enum AzureIdentity { + ClientSecret { + tenant_id: String, + client_id: String, + client_secret: SecretValue, + }, + ManagedIdentity { + client_id: String, + }, + Default, +} + +fn identity_plan( + identity: &AzureIdentity, + scope: &str, + env_lookup: &dyn Fn(&str) -> Option, +) -> Result { + let deployment = |value: &str| Sourced::new(value.to_owned(), InputSource::Deployment); + let environment = |name: &str| { + env_lookup(name) + .filter(|value| !value.trim().is_empty()) + .map(|value| Sourced::new(value, InputSource::Environment)) + }; + let scope = deployment(scope); + let authority = environment(AzureSecretName::AuthorityHost.into()); + match identity { + AzureIdentity::ClientSecret { + tenant_id, + client_id, + client_secret, + } => Ok(AzureCredentialPlan::Native(ValidatedAzureRequest::new( + NativeAzureRequest::ClientSecret { + tenant_id: deployment(tenant_id), + client_id: deployment(client_id), + client_secret: Sourced::new(client_secret.clone(), InputSource::Deployment), + scope, + authority, + }, + )?)), + AzureIdentity::ManagedIdentity { client_id } => Ok(AzureCredentialPlan::Native( + ValidatedAzureRequest::new(NativeAzureRequest::ManagedIdentity { + client_id: Some(deployment(client_id)), + scope, + selection_source: InputSource::Deployment, + })?, + )), + AzureIdentity::Default => { + let tenant_id = environment(AzureSecretName::TenantId.into()); + let client_id = environment(AzureSecretName::ClientId.into()); + let from_environment = match ( + tenant_id.clone(), + client_id.clone(), + environment(AzureSecretName::ClientSecret.into()), + ) { + (Some(tenant_id), Some(client_id), Some(client_secret)) => { + Some(NativeAzureRequest::ClientSecret { + tenant_id, + client_id, + client_secret: client_secret.map(SecretValue::new), + scope: scope.clone(), + authority: authority.clone(), + }) + } + _ => None, + }; + let probe_imds = env_lookup(AzureSecretName::IdentityEndpoint.into()).is_none() + && env_lookup(AzureSecretName::MsiEndpoint.into()).is_none(); + let AzureCredentialPlan::Chain(chain) = select_native_plan( + Some(Sourced::new( + AzureCredentialType::DefaultAzureCredential, + InputSource::Deployment, + )), + tenant_id, + client_id, + environment(AzureSecretName::FederatedTokenFile.into()), + scope, + authority, + InputSource::Environment, + )? + else { + unreachable!("DefaultAzureCredential always plans a chain") + }; + let environment_request = from_environment + .map(ValidatedAzureRequest::new) + .transpose()?; + Ok(AzureCredentialPlan::Chain( + environment_request + .into_iter() + .chain(chain) + .map(|request| request.with_imds_probe(probe_imds)) + .collect(), + )) + } + } +} + pub(crate) fn select_auth_plan( inputs: &AzureAuthInputs, env_lookup: &dyn Fn(&str) -> Option, ) -> Result { - let token = configured_secret(&inputs.azure_ad_token, AZURE_AD_TOKEN_ENV, env_lookup); - let tenant_id = configured_string(&inputs.tenant_id, AZURE_TENANT_ID_ENV, env_lookup); - let client_id = configured_string(&inputs.client_id, AZURE_CLIENT_ID_ENV, env_lookup); - let client_secret = - configured_secret(&inputs.client_secret, AZURE_CLIENT_SECRET_ENV, env_lookup); - let scope = configured_string(&inputs.azure_scope, AZURE_SCOPE_ENV, env_lookup) - .unwrap_or_else(|| Sourced::new(DEFAULT_AZURE_SCOPE.to_string(), InputSource::Environment)); - let authority = configured_string( - &inputs.azure_authority_host, - AZURE_AUTHORITY_HOST_ENV, + let token = configured_secret( + &inputs.azure_ad_token, + AzureSecretName::AdToken.into(), env_lookup, ); - let selector = configured_string(&inputs.azure_credential, AZURE_CREDENTIAL_ENV, env_lookup) - .map(|value| { - value - .value() - .parse::() - .map(|selector| Sourced::new(selector, value.source())) - }) - .transpose() - .map_err(|error| { - Error::InvalidConfiguration(ErrorDetail::failed( - "Azure credential selector parsing", - error, - )) - })?; + let tenant_id = configured_string( + &inputs.tenant_id, + AzureSecretName::TenantId.into(), + env_lookup, + ); + let client_id = configured_string( + &inputs.client_id, + AzureSecretName::ClientId.into(), + env_lookup, + ); + let client_secret = configured_secret( + &inputs.client_secret, + AzureSecretName::ClientSecret.into(), + env_lookup, + ); + let scope = configured_string( + &inputs.azure_scope, + AzureSecretName::Scope.into(), + env_lookup, + ) + .unwrap_or_else(|| Sourced::new(DEFAULT_AZURE_SCOPE.to_string(), InputSource::Environment)); + let authority = configured_string( + &inputs.azure_authority_host, + AzureSecretName::AuthorityHost.into(), + env_lookup, + ); + let selector = configured_string( + &inputs.azure_credential, + AzureSecretName::Credential.into(), + env_lookup, + ) + .map(|value| { + value + .value() + .parse::() + .map(|selector| Sourced::new(selector, value.source())) + }) + .transpose() + .map_err(|error| { + Error::InvalidConfiguration(ErrorDetail::failed( + "Azure credential selector parsing", + error, + )) + })?; let federated_token_file = configured_string( &inputs.federated_token_file, - AZURE_FEDERATED_TOKEN_FILE_ENV, + AzureSecretName::FederatedTokenFile.into(), env_lookup, ); @@ -237,7 +400,12 @@ pub(crate) fn select_auth_plan( return Ok(AzureCredentialPlan::Missing); } - select_native_plan( + let probe_imds = selector + .as_ref() + .is_none_or(|selector| *selector.value() == AzureCredentialType::DefaultAzureCredential) + && env_lookup(AzureSecretName::IdentityEndpoint.into()).is_none() + && env_lookup(AzureSecretName::MsiEndpoint.into()).is_none(); + match select_native_plan( selector, tenant_id, client_id, @@ -245,7 +413,15 @@ pub(crate) fn select_auth_plan( scope, authority, inputs.enable_azure_ad_token_refresh.source(), - ) + )? { + AzureCredentialPlan::Chain(requests) => Ok(AzureCredentialPlan::Chain( + requests + .into_iter() + .map(|request| request.with_imds_probe(probe_imds)) + .collect(), + )), + plan => Ok(plan), + } } fn select_native_plan( @@ -509,7 +685,10 @@ mod tests { #[derive(Debug)] struct FileResolver; + use crate::native::CredentialAttempt; + struct ChainAcquirer { + terminal_on: Option<&'static str>, requests: Mutex>, succeed_on: Option<&'static str>, } @@ -518,20 +697,25 @@ mod tests { fn acquire( &self, request: ValidatedAzureRequest, - ) -> std::pin::Pin> + Send + '_>> - { + ) -> std::pin::Pin + Send + '_>> { let kind = request.kind(); self.requests.lock().unwrap().push(kind); Box::pin(async move { if self.succeed_on == Some(kind) { - Ok(ResolvedCredential::AccessToken { + CredentialAttempt::Resolved(ResolvedCredential::AccessToken { token: SecretValue::new("chain-token"), expires_on: None, }) } else { - Err(Error::CredentialAcquisition( - litellm_auth_types::ErrorDetail::Unresolved { subject: kind }, - )) + let error = + Error::CredentialAcquisition(litellm_auth_types::ErrorDetail::Unresolved { + subject: kind, + }); + if self.terminal_on == Some(kind) { + CredentialAttempt::Failed(error) + } else { + CredentialAttempt::Unavailable(error) + } } }) } @@ -690,9 +874,210 @@ mod tests { assert_eq!(resolved, Some(SecretValue::new("rotated-assertion"))); } + #[derive(Debug)] + struct UnavailableImdsClient; + + impl azure_core::http::HttpClient for UnavailableImdsClient { + fn execute_request<'life0, 'life1, 'async_trait>( + &'life0 self, + _request: &'life1 azure_core::http::Request, + ) -> std::pin::Pin< + Box< + dyn Future> + + Send + + 'async_trait, + >, + > + where + 'life0: 'async_trait, + 'life1: 'async_trait, + Self: 'async_trait, + { + Box::pin(std::future::pending()) + } + } + + struct OfflineChainAcquirer(super::NativeAzureTokenAcquirer); + + impl AzureTokenAcquirer for OfflineChainAcquirer { + fn acquire( + &self, + request: ValidatedAzureRequest, + ) -> std::pin::Pin + Send + '_>> { + Box::pin(async move { + if request.kind() == "developer-tools" { + return CredentialAttempt::Resolved(ResolvedCredential::AccessToken { + token: SecretValue::new("cli-token"), + expires_on: None, + }); + } + self.0.acquire(request).await + }) + } + } + + #[rstest::rstest] + #[case::default_off_azure("DefaultAzureCredential", None, true)] + #[case::explicit_managed_identity("ManagedIdentityCredential", None, false)] + #[case::app_service("DefaultAzureCredential", Some("http://app-service.test"), false)] + #[tokio::test(start_paused = true)] + async fn only_default_imds_discovery_is_bounded( + #[case] selector: &str, + #[case] identity_endpoint: Option<&str>, + #[case] expect_cli: bool, + ) { + let native = super::NativeAzureTokenAcquirer::with_transport( + 4, + azure_core::http::Transport::new(Arc::new(UnavailableImdsClient)), + ); + let service = AzureAuthService::with_acquirer(Arc::new(OfflineChainAcquirer(native))); + let inputs = AzureAuthInputs { + azure_credential: crate::types::ConfigValue::Value(Sourced::new( + selector.into(), + InputSource::Deployment, + )), + enable_azure_ad_token_refresh: Sourced::new(true, InputSource::Deployment), + ..Default::default() + }; + let environment = |name: &str| { + (name == "IDENTITY_ENDPOINT") + .then_some(identity_endpoint) + .flatten() + .map(str::to_string) + }; + let outcome = tokio::time::timeout( + std::time::Duration::from_secs(2), + service.get_azure_ad_token(&inputs, &environment), + ) + .await; + + assert_eq!(outcome.is_ok(), expect_cli); + if expect_cli { + assert_eq!( + outcome.unwrap().unwrap().unwrap().value().secret().expose(), + "cli-token" + ); + } + } + + #[rstest::rstest] + #[case::app_service(Some("IDENTITY_ENDPOINT"), false)] + #[case::legacy_app_service(Some("MSI_ENDPOINT"), false)] + #[case::off_azure(None, true)] + #[tokio::test(start_paused = true)] + async fn default_chain_uses_endpoints_from_the_secret_snapshot( + #[case] endpoint: Option<&str>, + #[case] expect_cli: bool, + #[values(false, true)] consumer_identity: bool, + ) { + use litellm_secrets::source::SecretSource; + + struct EndpointSecrets<'a>(Option<&'a str>); + + impl SecretSource for EndpointSecrets<'_> { + fn get_secret_str<'a>( + &'a self, + name: &'a str, + ) -> std::pin::Pin< + Box< + dyn Future, litellm_secrets::Error>> + + Send + + 'a, + >, + > { + Box::pin(async move { + Ok((self.0 == Some(name)).then(|| SecretValue::new("http://app-service.test"))) + }) + } + } + + let snapshot = EndpointSecrets(endpoint) + .resolve(SECRET_NAMES) + .await + .unwrap(); + let native = super::NativeAzureTokenAcquirer::with_transport( + 4, + azure_core::http::Transport::new(Arc::new(UnavailableImdsClient)), + ); + let service = AzureAuthService::with_acquirer(Arc::new(OfflineChainAcquirer(native))); + let lookup = |name: &str| snapshot.get(name); + let scope = "https://service.test/.default"; + let outcome = tokio::time::timeout(std::time::Duration::from_secs(2), async { + if consumer_identity { + service + .identity_token(&super::AzureIdentity::Default, scope, &lookup) + .await + } else { + service + .get_azure_ad_token( + &AzureAuthInputs::default_credential_for_scope(scope), + &lookup, + ) + .await + .map(|token| token.map(Sourced::into_value)) + } + }) + .await; + + assert_eq!(outcome.is_ok(), expect_cli); + if expect_cli { + assert_eq!( + outcome.unwrap().unwrap().unwrap().secret().expose(), + "cli-token" + ); + } + } + + #[rstest::rstest] + #[case::litellm_provider_settings_are_ignored( + &[("AZURE_AD_TOKEN", "provider-token"), ("AZURE_CREDENTIAL", "ClientSecretCredential")], + &["managed-identity", "developer-tools"] + )] + #[case::environment_client_secret_comes_first( + &[("AZURE_TENANT_ID", "tenant"), ("AZURE_CLIENT_ID", "client"), ("AZURE_CLIENT_SECRET", "secret")], + &["client-secret", "managed-identity", "developer-tools"] + )] + #[case::aks_workload_identity( + &[("AZURE_TENANT_ID", "tenant"), ("AZURE_CLIENT_ID", "client"), ("AZURE_FEDERATED_TOKEN_FILE", "/var/run/token")], + &["workload-identity", "managed-identity", "developer-tools"] + )] + #[tokio::test] + async fn the_default_identity_follows_azure_identity_defaults( + #[case] environment: &[(&str, &str)], + #[case] expected: &[&str], + ) { + let acquirer = Arc::new(ChainAcquirer { + terminal_on: None, + requests: Mutex::new(Vec::new()), + succeed_on: Some("developer-tools"), + }); + let service = AzureAuthService::with_acquirer(acquirer.clone()); + let lookup = |name: &str| { + environment + .iter() + .find(|(key, _)| *key == name) + .map(|(_, value)| (*value).to_owned()) + }; + + let credential = service + .identity_token( + &super::AzureIdentity::Default, + "https://redis.azure.com/.default", + &lookup, + ) + .await + .unwrap() + .unwrap(); + + assert_eq!(credential.secret().expose(), "chain-token"); + assert_eq!(*acquirer.requests.lock().unwrap(), expected); + } + + #[rstest::rstest] #[tokio::test] async fn default_chain_uses_declared_order_and_stops_after_success() { let acquirer = Arc::new(ChainAcquirer { + terminal_on: None, requests: Mutex::new(Vec::new()), succeed_on: Some("developer-tools"), }); @@ -715,9 +1100,13 @@ mod tests { ); } + #[rstest::rstest] + #[case::all_unavailable(false)] + #[case::terminal_failure_after_unavailable(true)] #[tokio::test] - async fn chain_reports_each_acquisition_failure() { + async fn chain_reports_each_acquisition_failure(#[case] terminal: bool) { let acquirer = Arc::new(ChainAcquirer { + terminal_on: terminal.then_some("developer-tools"), requests: Mutex::new(Vec::new()), succeed_on: None, }); @@ -744,6 +1133,27 @@ mod tests { ); } + #[rstest::rstest] + #[tokio::test] + async fn a_configured_identity_failure_does_not_fall_back_to_a_developer_identity() { + let acquirer = Arc::new(ChainAcquirer { + terminal_on: Some("managed-identity"), + requests: Mutex::new(Vec::new()), + succeed_on: Some("developer-tools"), + }); + let service = AzureAuthService::with_acquirer(acquirer.clone()); + let inputs = AzureAuthInputs { + enable_azure_ad_token_refresh: Sourced::new(true, InputSource::Deployment), + ..Default::default() + }; + let error = service + .get_azure_ad_token(&inputs, &|_| None) + .await + .unwrap_err(); + assert_eq!(*acquirer.requests.lock().unwrap(), ["managed-identity"]); + assert!(matches!(error, Error::CredentialChain { earlier, .. } if earlier.is_empty())); + } + #[derive(Debug)] struct CallerToken(&'static str); diff --git a/litellm-rust/crates/auth-gcp/Cargo.toml b/litellm-rust/crates/auth-gcp/Cargo.toml index ad60f0db817..90aab8d281c 100644 --- a/litellm-rust/crates/auth-gcp/Cargo.toml +++ b/litellm-rust/crates/auth-gcp/Cargo.toml @@ -6,7 +6,7 @@ license.workspace = true repository.workspace = true [features] -google-sdk = ["dep:google-cloud-auth", "dep:http"] +google-sdk = ["dep:http"] [dependencies] litellm-secret-value.workspace = true @@ -21,10 +21,14 @@ tokio.workspace = true veil.workspace = true gcp_auth = "0.12.7" -google-cloud-auth = { workspace = true, optional = true } +google-cloud-auth.workspace = true http = { workspace = true, optional = true } [dev-dependencies] +time = { workspace = true, features = ["formatting"] } +axum = { workspace = true, features = ["json"] } litellm-error.workspace = true rstest.workspace = true +rustls.workspace = true tempfile.workspace = true +tokio = { workspace = true, features = ["test-util"] } diff --git a/litellm-rust/crates/auth-gcp/src/auth.rs b/litellm-rust/crates/auth-gcp/src/auth.rs index 650d5831796..5976ef82344 100644 --- a/litellm-rust/crates/auth-gcp/src/auth.rs +++ b/litellm-rust/crates/auth-gcp/src/auth.rs @@ -1,20 +1,11 @@ -use std::{future::Future, pin::Pin, sync::Arc}; +use std::sync::Arc; -use gcp_auth::{CustomServiceAccount, TokenProvider}; -use litellm_auth_types::{CredentialPlacement, Error, ErrorDetail, http::apply_credential}; -use moka::future::Cache; -use serde_json::Value; -use sha2::{Digest, Sha256}; +use litellm_auth_types::{CredentialPlacement, Error, http::apply_credential}; use crate::{ - config::{ - CredentialSource, VertexConfig, credential_source, get_vertex_ai_project, - is_base64_encoded_json, names_a_credentials_file, non_empty_env, - }, - constants::{ - CLOUD_PLATFORM_SCOPE, GOOGLE_OAUTH_TOKEN_ENDPOINT, VERTEX_AI_API_KEY_ENV, - VERTEXAI_API_KEY_ENV, - }, + config::{VertexConfig, credential_source, get_vertex_ai_project, non_empty_env}, + constants::{VERTEX_AI_API_KEY_ENV, VERTEXAI_API_KEY_ENV}, + identity::{GcpAuth, GcpProviderLoader, GcpTokenSource}, }; pub struct VertexEnvironment { @@ -22,28 +13,15 @@ pub struct VertexEnvironment { pub project_id: String, } -struct VertexAccessToken { - token: String, - project_id: String, -} - -#[derive(Clone)] +#[derive(Clone, Default)] pub struct VertexAuth { - providers: Cache>, - loader: Arc, -} - -impl Default for VertexAuth { - fn default() -> Self { - Self::new(Arc::new(GcpProviderLoader)) - } + identity: GcpAuth, } impl VertexAuth { - pub fn new(loader: Arc) -> Self { + pub fn new(loader: Arc) -> Self { Self { - providers: Cache::builder().max_capacity(64).build(), - loader, + identity: GcpAuth::new(loader), } } @@ -52,7 +30,10 @@ impl VertexAuth { config: &VertexConfig, env_lookup: &(dyn Fn(&str) -> Option + Sync), ) -> Result { - self.load_provider(config, env_lookup).await?.token().await + self.identity + .access_token(credential_source(config, env_lookup)) + .await + .map(|token| token.expose().to_owned()) } pub async fn validate_environment( @@ -77,10 +58,18 @@ impl VertexAuth { (true, _) => None, (false, Some(token)) => Some(token), (false, None) => { - let access = self.get_access_token(config, env_lookup).await?; + let provider = self.load_provider(config, env_lookup).await?; + let (token, project_id) = match project_id { + Some(project_id) => (provider.token().await?, project_id), + None => tokio::try_join!(provider.token(), provider.project_id())?, + }; return Ok(VertexEnvironment { - headers: apply_credential(headers, &access.token, CredentialPlacement::Bearer)?, - project_id: project_id.unwrap_or(access.project_id), + headers: apply_credential( + headers, + token.expose(), + CredentialPlacement::Bearer, + )?, + project_id, }); } }; @@ -104,248 +93,171 @@ impl VertexAuth { }) } - async fn get_access_token( - &self, - config: &VertexConfig, - env_lookup: &(dyn Fn(&str) -> Option + Sync), - ) -> Result { - let provider = self.load_provider(config, env_lookup).await?; - let (token, project_id) = tokio::try_join!(provider.token(), provider.project_id())?; - Ok(VertexAccessToken { token, project_id }) - } - async fn load_provider( &self, config: &VertexConfig, env_lookup: &(dyn Fn(&str) -> Option + Sync), - ) -> Result, Error> { - let source = credential_source(config, env_lookup); - let key = source.cache_key(); - self.providers - .try_get_with(key, self.loader.load(source)) + ) -> Result, Error> { + self.identity + .load_provider(credential_source(config, env_lookup)) .await - .map_err(|error| (*error).clone()) } } -pub trait VertexTokenSource: Send + Sync { - fn project_id(&self) -> VertexAuthFuture<'_, String>; - fn token(&self) -> VertexAuthFuture<'_, String>; -} - -pub trait VertexProviderLoader: Send + Sync { - fn load(&self, source: CredentialSource) -> VertexAuthFuture<'_, Arc>; -} - -pub type VertexAuthFuture<'a, T> = Pin> + Send + 'a>>; - -struct GcpTokenSource(Arc); - -impl VertexTokenSource for GcpTokenSource { - fn project_id(&self) -> VertexAuthFuture<'_, String> { - Box::pin(async move { - self.0 - .project_id() - .await - .map(|project| project.to_string()) - .map_err(auth_acquisition_error) - }) - } - - fn token(&self) -> VertexAuthFuture<'_, String> { - Box::pin(async move { - self.0 - .token(&[CLOUD_PLATFORM_SCOPE]) - .await - .map(|token| token.as_str().to_string()) - .map_err(auth_acquisition_error) - }) - } -} - -struct GcpProviderLoader; - -impl VertexProviderLoader for GcpProviderLoader { - fn load(&self, source: CredentialSource) -> VertexAuthFuture<'_, Arc> { - Box::pin(async move { - let provider: Arc = match source { - CredentialSource::Inline(configured) => Arc::new( - CustomServiceAccount::from_json(validate_request_credentials( - configured.expose(), - )?) - .map_err(auth_acquisition_error)?, - ), - CredentialSource::Trusted(configured) => { - Arc::new(load_trusted_service_account(configured.expose())?) - } - CredentialSource::ApplicationCredentials(path) => { - Arc::new(CustomServiceAccount::from_file(path).map_err(auth_acquisition_error)?) - } - CredentialSource::Adc => { - gcp_auth::provider().await.map_err(auth_acquisition_error)? - } - }; - Ok(Arc::new(GcpTokenSource(provider)) as Arc) - }) - } -} - -fn validate_request_credentials(configured: &str) -> Result<&str, Error> { - let token_uri = serde_json::from_str::(configured) - .ok() - .and_then(|credentials| { - credentials - .get("token_uri") - .and_then(Value::as_str) - .map(str::to_string) - }); - if token_uri.as_deref() != Some(GOOGLE_OAUTH_TOKEN_ENDPOINT) { - return Err(Error::InvalidConfiguration(ErrorDetail::InvalidType { - field: "request-controlled vertex_credentials token_uri".into(), - expected: "the canonical Google OAuth token endpoint", - })); - } - Ok(configured) -} - -impl CredentialSource { - fn cache_key(&self) -> CredentialCacheKey { - match self { - Self::Inline(configured) => { - CredentialCacheKey::Inline(Sha256::digest(configured.expose()).into()) - } - Self::Trusted(configured) => { - CredentialCacheKey::Trusted(Sha256::digest(configured.expose()).into()) - } - Self::ApplicationCredentials(path) => { - CredentialCacheKey::ApplicationCredentials(path.clone()) - } - Self::Adc => CredentialCacheKey::Adc, - } - } -} - -#[derive(Clone, Debug, Hash, PartialEq, Eq)] -enum CredentialCacheKey { - Inline([u8; 32]), - Trusted([u8; 32]), - ApplicationCredentials(String), - Adc, -} - -fn load_trusted_service_account(configured: &str) -> Result { - if is_base64_encoded_json(configured) { - return Err(Error::InvalidConfiguration( - ErrorDetail::Base64EncodedJson { - field: "vertex_credentials", - }, - )); - } - if names_a_credentials_file(configured) { - CustomServiceAccount::from_file(configured) - } else { - CustomServiceAccount::from_json(configured) - } - .map_err(auth_acquisition_error) -} - -fn auth_acquisition_error(error: gcp_auth::Error) -> Error { - Error::CredentialAcquisition(litellm_auth_types::ErrorDetail::failed( - "Vertex AI credentials", - error, - )) -} - #[cfg(test)] mod tests { + use std::{ + collections::{BTreeMap, BTreeSet}, + sync::{ + Arc, + atomic::{AtomicUsize, Ordering}, + }, + }; + + use crate::{ + CredentialSource, GcpAuthFuture, GcpProviderLoader, GcpTokenSource, VertexAuth, + VertexConfig, get_vertex_ai_location, secret_names, + }; use litellm_secret_value::SecretValue; + use rstest::rstest; + use serde_json::{Value, json}; - use super::*; - - #[rstest::rstest] - #[case::canonical_endpoint(r#"{"token_uri":"https://oauth2.googleapis.com/token"}"#, true)] - #[case::noncanonical_endpoint(r#"{"token_uri":"http://127.0.0.1/token"}"#, false)] - #[case::missing_endpoint("{}", false)] - fn request_credentials_require_canonical_token_endpoint( - #[case] credentials: &str, - #[case] accepted: bool, - ) { - assert_eq!(validate_request_credentials(credentials).is_ok(), accepted); + struct FakeProvider { + project: Option<&'static str>, + calls: Arc, } - #[rstest::rstest] - #[case::missing_file( - "/nonexistent/vertex-key.json", - "failed to open application credentials file" - )] - #[case::malformed_json( - " {\"type\": \"service_account\",", - "failed to deserialize ApplicationCredentials" - )] - #[case::quoted_json( - "'{\"type\": \"service_account\"}'", - "failed to deserialize ApplicationCredentials" - )] - #[tokio::test] - async fn trusted_credentials_are_read_as_a_file_unless_they_are_json( - #[case] configured: &str, - #[case] expected: &str, - ) { - let Err(error) = GcpProviderLoader - .load(CredentialSource::Trusted(SecretValue::new(configured))) - .await - else { - panic!("{configured:?} should not load"); - }; - let report = litellm_error::Report::new(&error).to_string(); - assert!(report.contains(expected), "{report}"); - } + impl GcpTokenSource for FakeProvider { + fn project_id(&self) -> GcpAuthFuture<'_, String> { + self.calls.fetch_add(1, Ordering::SeqCst); + Box::pin(async move { + self.project.map(str::to_owned).ok_or( + litellm_auth_types::Error::CredentialAcquisition( + litellm_auth_types::ErrorDetail::Unresolved { + subject: "credential project", + }, + ), + ) + }) + } - #[rstest::rstest] - #[case::padded("eyJ0eXBlIjogInNlcnZpY2VfYWNjb3VudCJ9")] - #[case::quoted_prefixed_unpadded("\"base64:eyJ0eXBlIjogInNlcnZpY2VfYWNjb3VudCJ9\"")] - #[case::url_safe_wrapped("eyJ0eXBlIjogInNlcnZpY2VfYWNjb3VudCIsICJr\nZXkiOiAiPz8_In0=")] - #[tokio::test] - async fn base64_encoded_credentials_are_named_as_base64(#[case] configured: &str) { - assert!( - trusted_load_error(configured) - .await - .contains("is base64-encoded JSON, not the JSON itself") - ); - } - - async fn trusted_load_error(configured: &str) -> String { - match GcpProviderLoader - .load(CredentialSource::Trusted(SecretValue::new(configured))) - .await - { - Ok(_) => panic!("{configured:?} should not load"), - Err(error) => litellm_error::Report::new(&error).to_string(), + fn token(&self) -> GcpAuthFuture<'_, SecretValue> { + self.calls.fetch_add(1, Ordering::SeqCst); + Box::pin(async { Ok(SecretValue::new("adc-token")) }) } } - #[rstest::rstest] - #[tokio::test] - async fn a_relative_key_file_named_like_json_is_read_as_a_file() { - let key = tempfile::Builder::new() - .prefix("{vertex") - .suffix(".json") - .tempfile_in(".") - .unwrap(); - std::fs::write(key.path(), r#"{"project_id":"file-project"}"#).unwrap(); - let relative_name = key.path().file_name().unwrap().to_str().unwrap(); - let absolute_path = std::fs::canonicalize(key.path()).unwrap(); - assert_eq!( - trusted_load_error(relative_name).await, - trusted_load_error(absolute_path.to_str().unwrap()).await - ); + struct FakeLoader { + loads: Arc, + provider: Arc, } - #[rstest::rstest] - fn inline_and_trusted_credentials_never_share_a_cache_entry() { - assert_ne!( - CredentialSource::Inline(SecretValue::new("same-value")).cache_key(), - CredentialSource::Trusted(SecretValue::new("same-value")).cache_key() - ); + impl GcpProviderLoader for FakeLoader { + fn load(&self, _source: CredentialSource) -> GcpAuthFuture<'_, Arc> { + let loads = self.loads.clone(); + let provider = self.provider.clone(); + Box::pin(async move { + loads.fetch_add(1, Ordering::SeqCst); + Ok(provider) + }) + } + } + + fn config(value: Value) -> VertexConfig { + VertexConfig::from_sourced_optional_params(value.as_object().unwrap(), &BTreeMap::new()) + .unwrap() + } + + fn auth(calls: Arc, loads: Arc) -> VertexAuth { + let provider: Arc = Arc::new(FakeProvider { + calls, + project: Some("adc-project"), + }); + VertexAuth::new(Arc::new(FakeLoader { loads, provider })) + } + + #[rstest] + #[tokio::test] + async fn secret_names_cover_environment_reads() { + let seen = Arc::new(std::sync::Mutex::new(BTreeSet::::new())); + let recorded = seen.clone(); + let env = |name: &str| { + recorded.lock().unwrap().insert(name.to_string()); + None + }; + let auth = auth(Arc::new(AtomicUsize::new(0)), Arc::new(AtomicUsize::new(0))); + auth.validate_environment(Vec::new(), None, &VertexConfig::default(), &env) + .await + .unwrap(); + get_vertex_ai_location(&VertexConfig::default(), &env); + let allowed = secret_names() + .iter() + .map(|name| (*name).to_owned()) + .collect::>(); + assert!(seen.lock().unwrap().is_subset(&allowed)); + } + + #[rstest] + #[tokio::test] + async fn explicit_token_and_header_do_not_acquire_adc() { + let loads = Arc::new(AtomicUsize::new(0)); + let auth = auth(Arc::new(AtomicUsize::new(0)), loads.clone()); + let configured = config(json!({"vertex_project":"project-1"})); + let explicit = auth + .validate_environment(Vec::new(), Some("access-token"), &configured, &|_| None) + .await + .unwrap(); + assert_eq!(explicit.headers[0].1, "Bearer access-token"); + let existing = auth + .validate_environment( + vec![("authorization".into(), "Bearer existing".into())], + None, + &configured, + &|_| None, + ) + .await + .unwrap(); + assert_eq!(existing.headers[0].1, "Bearer existing"); + assert_eq!(loads.load(Ordering::SeqCst), 0); + } + + #[rstest] + #[tokio::test] + async fn provider_is_reused_across_authentication_calls() { + let calls = Arc::new(AtomicUsize::new(0)); + let loads = Arc::new(AtomicUsize::new(0)); + let auth = auth(calls.clone(), loads.clone()); + let config = VertexConfig::default(); + let environment = |_: &str| None; + let (first, second) = tokio::try_join!( + auth.validate_environment(Vec::new(), None, &config, &environment), + auth.validate_environment(Vec::new(), None, &config, &environment), + ) + .unwrap(); + assert_eq!(first.project_id, "adc-project"); + assert_eq!(first.headers[0].1, "Bearer adc-token"); + assert_eq!(first.project_id, second.project_id); + assert_eq!(first.headers, second.headers); + assert_eq!(loads.load(Ordering::SeqCst), 1); + assert_eq!(calls.load(Ordering::SeqCst), 4); + } + + #[rstest] + #[tokio::test] + async fn an_explicit_project_does_not_require_project_metadata_in_the_credentials() { + let auth = VertexAuth::new(Arc::new(FakeLoader { + loads: Arc::new(AtomicUsize::new(0)), + provider: Arc::new(FakeProvider { + calls: Arc::new(AtomicUsize::new(0)), + project: None, + }), + })); + let configured = VertexConfig::new(None, Some("configured-project".into()), None); + let environment = auth + .validate_environment(Vec::new(), None, &configured, &|_| None) + .await + .unwrap(); + assert_eq!(environment.project_id, "configured-project"); + assert_eq!(environment.headers[0].1, "Bearer adc-token"); } } diff --git a/litellm-rust/crates/auth-gcp/src/config.rs b/litellm-rust/crates/auth-gcp/src/config.rs index 133e1c26903..048e40b0a2f 100644 --- a/litellm-rust/crates/auth-gcp/src/config.rs +++ b/litellm-rust/crates/auth-gcp/src/config.rs @@ -146,6 +146,20 @@ pub enum CredentialSource { Adc, } +impl CredentialSource { + pub fn from_vertex_environment(env_lookup: &dyn Fn(&str) -> Option) -> Self { + VertexParams::CREDENTIALS + .resolve(&|_| None, env_lookup) + .map(|configured| Self::Trusted(SecretValue::new(configured))) + .unwrap_or_else(|| Self::application_default(env_lookup)) + } + + pub fn application_default(env_lookup: &dyn Fn(&str) -> Option) -> Self { + non_empty_env(env_lookup, GOOGLE_APPLICATION_CREDENTIALS_ENV) + .map_or(Self::Adc, Self::ApplicationCredentials) + } +} + pub(crate) fn credential_source( config: &VertexConfig, env_lookup: &dyn Fn(&str) -> Option, @@ -158,12 +172,7 @@ pub(crate) fn credential_source( } }; } - if let Some(configured) = VertexParams::CREDENTIALS.resolve(&|_| None, env_lookup) { - return CredentialSource::Trusted(SecretValue::new(configured)); - } - non_empty_env(env_lookup, GOOGLE_APPLICATION_CREDENTIALS_ENV) - .map(CredentialSource::ApplicationCredentials) - .unwrap_or(CredentialSource::Adc) + CredentialSource::from_vertex_environment(env_lookup) } fn optional_credentials( @@ -319,6 +328,24 @@ mod tests { )); } + #[rstest::rstest] + fn application_default_ignores_vertex_credentials() { + let env = |name: &str| match name { + VERTEXAI_CREDENTIALS_ENV => Some("environment-json".to_string()), + GOOGLE_APPLICATION_CREDENTIALS_ENV => Some("adc.json".to_string()), + _ => None, + }; + assert!( + matches!(CredentialSource::application_default(&env), CredentialSource::ApplicationCredentials(path) if path == "adc.json") + ); + assert!(matches!( + CredentialSource::application_default( + &|name| (name == VERTEXAI_CREDENTIALS_ENV).then(|| "environment-json".into()) + ), + CredentialSource::Adc + )); + } + #[rstest::rstest] fn params_become_a_deployment_sourced_config() { let params = VertexParams { diff --git a/litellm-rust/crates/auth-gcp/src/identity.rs b/litellm-rust/crates/auth-gcp/src/identity.rs new file mode 100644 index 00000000000..5144221b218 --- /dev/null +++ b/litellm-rust/crates/auth-gcp/src/identity.rs @@ -0,0 +1,445 @@ +use crate::{ + config::{CredentialSource, is_base64_encoded_json, names_a_credentials_file}, + constants::{CLOUD_PLATFORM_SCOPE, GOOGLE_OAUTH_TOKEN_ENDPOINT}, +}; +use gcp_auth::{CustomServiceAccount, TokenProvider}; +use litellm_auth_types::{Error, ErrorDetail}; +use litellm_secret_value::SecretValue; +use moka::future::Cache; +use serde_json::Value; +use sha2::{Digest, Sha256}; +use std::{future::Future, pin::Pin, sync::Arc}; + +#[derive(Clone)] +pub struct GcpAuth { + providers: Cache>, + loader: Arc, +} + +impl Default for GcpAuth { + fn default() -> Self { + Self::new(Arc::new(NativeProviderLoader)) + } +} + +impl GcpAuth { + pub fn new(loader: Arc) -> Self { + Self { + providers: Cache::builder().max_capacity(64).build(), + loader, + } + } + + pub async fn access_token(&self, source: CredentialSource) -> Result { + self.load_provider(source).await?.token().await + } + + pub(crate) async fn load_provider( + &self, + source: CredentialSource, + ) -> Result, Error> { + self.providers + .try_get_with(source.cache_key(), self.loader.load(source)) + .await + .map_err(|error| (*error).clone()) + } +} + +pub trait GcpTokenSource: Send + Sync { + fn project_id(&self) -> GcpAuthFuture<'_, String>; + fn token(&self) -> GcpAuthFuture<'_, SecretValue>; +} + +pub trait GcpProviderLoader: Send + Sync { + fn load(&self, source: CredentialSource) -> GcpAuthFuture<'_, Arc>; +} + +pub type GcpAuthFuture<'a, T> = Pin> + Send + 'a>>; + +struct ServiceAccountTokenSource(Arc); + +impl GcpTokenSource for ServiceAccountTokenSource { + fn project_id(&self) -> GcpAuthFuture<'_, String> { + Box::pin(async move { + self.0 + .project_id() + .await + .map(|project| project.to_string()) + .map_err(auth_acquisition_error) + }) + } + + fn token(&self) -> GcpAuthFuture<'_, SecretValue> { + Box::pin(async move { + self.0 + .token(&[CLOUD_PLATFORM_SCOPE]) + .await + .map(|token| SecretValue::new(token.as_str())) + .map_err(auth_acquisition_error) + }) + } +} + +struct SdkTokenSource { + credentials: google_cloud_auth::credentials::AccessTokenCredentials, + project_id: Option, +} + +impl GcpTokenSource for SdkTokenSource { + fn project_id(&self) -> GcpAuthFuture<'_, String> { + Box::pin(async move { + self.project_id + .clone() + .ok_or(Error::CredentialAcquisition(ErrorDetail::Unresolved { + subject: "GCP resource project", + })) + }) + } + + fn token(&self) -> GcpAuthFuture<'_, SecretValue> { + Box::pin(async move { + self.credentials + .access_token() + .await + .map(|token| SecretValue::new(token.token)) + .map_err(auth_acquisition_error) + }) + } +} + +async fn load_application_credentials(path: &str) -> Result, Error> { + let contents = tokio::fs::read_to_string(path) + .await + .map_err(auth_acquisition_error)?; + load_credentials_json(&contents) +} + +fn load_credentials_json(contents: &str) -> Result, Error> { + let configured: Value = serde_json::from_str(contents).map_err(auth_acquisition_error)?; + let kind = configured.get("type").and_then(Value::as_str); + let project_id = configured + .get("project_id") + .and_then(Value::as_str) + .map(str::to_string); + let credentials = match kind { + Some("authorized_user") => { + google_cloud_auth::credentials::user_account::Builder::new(configured) + .with_scopes([CLOUD_PLATFORM_SCOPE]) + .build_access_token_credentials() + } + Some("impersonated_service_account") => { + google_cloud_auth::credentials::impersonated::Builder::new(configured) + .with_scopes([CLOUD_PLATFORM_SCOPE]) + .build_access_token_credentials() + } + Some("external_account") => { + google_cloud_auth::credentials::external_account::Builder::new(configured) + .with_scopes([CLOUD_PLATFORM_SCOPE]) + .build_access_token_credentials() + } + Some("service_account") | None => { + let provider = + CustomServiceAccount::from_json(contents).map_err(auth_acquisition_error)?; + return Ok(Arc::new(ServiceAccountTokenSource(Arc::new(provider)))); + } + Some(_) => { + return Err(Error::InvalidConfiguration(ErrorDetail::InvalidType { + field: "Google application credentials type".into(), + expected: "a supported Google credential type", + })); + } + } + .map_err(auth_acquisition_error)?; + Ok(Arc::new(SdkTokenSource { + credentials, + project_id, + })) +} + +struct NativeProviderLoader; + +impl GcpProviderLoader for NativeProviderLoader { + fn load(&self, source: CredentialSource) -> GcpAuthFuture<'_, Arc> { + Box::pin(async move { + let provider: Arc = match source { + CredentialSource::Inline(configured) => Arc::new( + CustomServiceAccount::from_json(validate_request_credentials( + configured.expose(), + )?) + .map_err(auth_acquisition_error)?, + ), + CredentialSource::Trusted(configured) => { + return load_trusted_credentials(configured.expose()).await; + } + CredentialSource::ApplicationCredentials(path) => { + return load_application_credentials(&path).await; + } + CredentialSource::Adc => { + gcp_auth::provider().await.map_err(auth_acquisition_error)? + } + }; + Ok(Arc::new(ServiceAccountTokenSource(provider)) as Arc) + }) + } +} + +fn validate_request_credentials(configured: &str) -> Result<&str, Error> { + let token_uri = serde_json::from_str::(configured) + .ok() + .and_then(|credentials| { + credentials + .get("token_uri") + .and_then(Value::as_str) + .map(str::to_string) + }); + if token_uri.as_deref() != Some(GOOGLE_OAUTH_TOKEN_ENDPOINT) { + return Err(Error::InvalidConfiguration(ErrorDetail::InvalidType { + field: "request-controlled vertex_credentials token_uri".into(), + expected: "the canonical Google OAuth token endpoint", + })); + } + Ok(configured) +} + +impl CredentialSource { + fn cache_key(&self) -> CredentialCacheKey { + match self { + Self::Inline(configured) => { + CredentialCacheKey::Inline(Sha256::digest(configured.expose()).into()) + } + Self::Trusted(configured) => { + CredentialCacheKey::Trusted(Sha256::digest(configured.expose()).into()) + } + Self::ApplicationCredentials(path) => { + CredentialCacheKey::ApplicationCredentials(path.clone()) + } + Self::Adc => CredentialCacheKey::Adc, + } + } +} + +#[derive(Clone, Debug, Hash, PartialEq, Eq)] +enum CredentialCacheKey { + Inline([u8; 32]), + Trusted([u8; 32]), + ApplicationCredentials(String), + Adc, +} + +async fn load_trusted_credentials(configured: &str) -> Result, Error> { + if is_base64_encoded_json(configured) { + return Err(Error::InvalidConfiguration( + ErrorDetail::Base64EncodedJson { + field: "vertex_credentials", + }, + )); + } + if names_a_credentials_file(configured) { + load_application_credentials(configured).await + } else { + load_credentials_json(configured) + } +} + +fn auth_acquisition_error(error: impl std::error::Error + Send + Sync + 'static) -> Error { + Error::CredentialAcquisition(litellm_auth_types::ErrorDetail::failed( + "Google credentials", + error, + )) +} + +#[cfg(test)] +mod tests { + use litellm_secret_value::SecretValue; + + use super::*; + + #[rstest::rstest] + #[case::authorized_user("authorized_user", 2)] + #[case::external_account("external_account", 2)] + #[case::impersonated_service_account("impersonated_service_account", 4)] + #[tokio::test] + async fn explicit_application_credentials_refresh_expired_tokens( + #[case] kind: &str, + #[case] expected_requests: usize, + #[values(false, true)] inline: bool, + ) { + use axum::{Json, Router, routing::post}; + use std::sync::atomic::{AtomicUsize, Ordering}; + + let _ = rustls::crypto::ring::default_provider().install_default(); + let requests = Arc::new(AtomicUsize::new(0)); + let recorded = requests.clone(); + let impersonations = requests.clone(); + let app = Router::new().route("/token", post(move || { + let recorded = recorded.clone(); + async move { + Json(serde_json::json!({ + "access_token": format!("token-{}", recorded.fetch_add(1, Ordering::SeqCst)), + "expires_in": 3600, + "token_type": "Bearer", + "issued_token_type": "urn:ietf:params:oauth:token-type:access_token", + })) + } + })); + let app = app.route("/v1/projects/-/serviceAccounts/test-principal:generateAccessToken", post(move || { + let recorded = impersonations.clone(); + async move { + let expiration = (time::OffsetDateTime::now_utc() + time::Duration::hours(1)).format(&time::format_description::well_known::Rfc3339).unwrap(); + Json(serde_json::json!({ + "accessToken": format!("impersonated-{}", recorded.fetch_add(1, Ordering::SeqCst)), + "expireTime": expiration, + })) + } + })); + let listener = tokio::net::TcpListener::bind("127.0.0.1:0").await.unwrap(); + let address = listener.local_addr().unwrap(); + let server = tokio::spawn(async move { axum::serve(listener, app).await.unwrap() }); + let file = tempfile::NamedTempFile::new().unwrap(); + let subject_token = tempfile::NamedTempFile::new().unwrap(); + std::fs::write(subject_token.path(), "subject-token").unwrap(); + let configured = if kind == "external_account" { + serde_json::json!({ + "type": "external_account", "audience": "//iam.googleapis.com/projects/test/locations/global/workloadIdentityPools/test/providers/test", + "subject_token_type": "urn:ietf:params:oauth:token-type:jwt", "token_url": format!("http://{address}/token"), + "credential_source": { "file": subject_token.path().to_str().unwrap() }, "quota_project_id": "quota-project" + }) + } else { + let source = serde_json::json!({ + "type": "authorized_user", "client_id": "user-client", "client_secret": "user-secret", + "refresh_token": "user-refresh", "quota_project_id": "quota-project", "token_uri": format!("http://{address}/token") + }); + if kind == "impersonated_service_account" { + serde_json::json!({ + "type": kind, "source_credentials": source, "quota_project_id": "quota-project", + "service_account_impersonation_url": format!("http://{address}/v1/projects/-/serviceAccounts/test-principal:generateAccessToken") + }) + } else { + source + } + }; + std::fs::write(file.path(), configured.to_string()).unwrap(); + let source = if inline { + CredentialSource::Trusted(SecretValue::new(configured.to_string())) + } else { + CredentialSource::ApplicationCredentials(file.path().to_str().unwrap().into()) + }; + let provider = NativeProviderLoader.load(source).await.unwrap(); + + assert!(matches!( + provider.project_id().await, + Err(Error::CredentialAcquisition(ErrorDetail::Unresolved { + subject: "GCP resource project" + })) + )); + let original = provider.token().await.unwrap(); + tokio::time::pause(); + tokio::time::advance(std::time::Duration::from_secs(3601)).await; + tokio::time::resume(); + let refreshed = provider.token().await.unwrap(); + assert_ne!(original, refreshed); + assert_eq!(requests.load(Ordering::SeqCst), expected_requests); + server.abort(); + } + + #[rstest::rstest] + #[case::canonical_endpoint(r#"{"token_uri":"https://oauth2.googleapis.com/token"}"#, true)] + #[case::noncanonical_endpoint(r#"{"token_uri":"http://127.0.0.1/token"}"#, false)] + #[case::missing_endpoint("{}", false)] + fn request_credentials_require_canonical_token_endpoint( + #[case] credentials: &str, + #[case] accepted: bool, + ) { + assert_eq!(validate_request_credentials(credentials).is_ok(), accepted); + } + + #[rstest::rstest] + #[case::missing_file("/nonexistent/vertex-key.json", "Google credentials")] + #[case::malformed_json(" {\"type\": \"service_account\",", "Google credentials")] + #[case::quoted_json("'{\"type\": \"service_account\"}'", "Google credentials")] + #[tokio::test] + async fn trusted_credentials_are_read_as_a_file_unless_they_are_json( + #[case] configured: &str, + #[case] expected: &str, + ) { + let Err(error) = NativeProviderLoader + .load(CredentialSource::Trusted(SecretValue::new(configured))) + .await + else { + panic!("{configured:?} should not load"); + }; + let report = litellm_error::Report::new(&error).to_string(); + assert!(report.contains(expected), "{report}"); + } + + #[rstest::rstest] + #[case::padded("eyJ0eXBlIjogInNlcnZpY2VfYWNjb3VudCJ9")] + #[case::quoted_prefixed_unpadded("\"base64:eyJ0eXBlIjogInNlcnZpY2VfYWNjb3VudCJ9\"")] + #[case::url_safe_wrapped("eyJ0eXBlIjogInNlcnZpY2VfYWNjb3VudCIsICJr\nZXkiOiAiPz8_In0=")] + #[tokio::test] + async fn base64_encoded_credentials_are_named_as_base64(#[case] configured: &str) { + assert!( + trusted_load_error(configured) + .await + .contains("is base64-encoded JSON, not the JSON itself") + ); + } + + async fn trusted_load_error(configured: &str) -> String { + match NativeProviderLoader + .load(CredentialSource::Trusted(SecretValue::new(configured))) + .await + { + Ok(_) => panic!("{configured:?} should not load"), + Err(error) => litellm_error::Report::new(&error).to_string(), + } + } + + #[rstest::rstest] + #[tokio::test] + async fn a_relative_key_file_named_like_json_is_read_as_a_file() { + let key = tempfile::Builder::new() + .prefix("{vertex") + .suffix(".json") + .tempfile_in(".") + .unwrap(); + std::fs::write(key.path(), r#"{"project_id":"file-project"}"#).unwrap(); + let relative_name = key.path().file_name().unwrap().to_str().unwrap(); + let absolute_path = std::fs::canonicalize(key.path()).unwrap(); + assert_eq!( + trusted_load_error(relative_name).await, + trusted_load_error(absolute_path.to_str().unwrap()).await + ); + } + + #[rstest::rstest] + #[tokio::test] + async fn unknown_application_credential_types_are_rejected_without_service_account_fallback() { + let file = tempfile::NamedTempFile::new().unwrap(); + std::fs::write( + file.path(), + r#"{"type":"unsupported","private_key":"credential-value"}"#, + ) + .unwrap(); + let result = GcpAuth::default() + .access_token(CredentialSource::ApplicationCredentials( + file.path().to_str().unwrap().into(), + )) + .await; + let error = result.unwrap_err(); + assert!(matches!(error, Error::InvalidConfiguration(_))); + assert!( + !litellm_error::Report::new(&error) + .to_string() + .contains("credential-value") + ); + } + + #[rstest::rstest] + fn inline_and_trusted_credentials_never_share_a_cache_entry() { + assert_ne!( + CredentialSource::Inline(SecretValue::new("same-value")).cache_key(), + CredentialSource::Trusted(SecretValue::new("same-value")).cache_key() + ); + } +} diff --git a/litellm-rust/crates/auth-gcp/src/lib.rs b/litellm-rust/crates/auth-gcp/src/lib.rs index 2b389d45926..03c660e6eb8 100644 --- a/litellm-rust/crates/auth-gcp/src/lib.rs +++ b/litellm-rust/crates/auth-gcp/src/lib.rs @@ -1,16 +1,16 @@ mod auth; mod config; pub mod constants; +mod identity; #[cfg(feature = "google-sdk")] mod sdk; -pub use auth::{ - VertexAuth, VertexAuthFuture, VertexEnvironment, VertexProviderLoader, VertexTokenSource, -}; +pub use auth::{VertexAuth, VertexEnvironment}; pub use config::{ CredentialSource, VertexConfig, get_vertex_ai_location, get_vertex_ai_project, get_vertex_ai_project_from_credentials, }; pub use constants::secret_names; +pub use identity::{GcpAuth, GcpAuthFuture, GcpProviderLoader, GcpTokenSource}; #[cfg(feature = "google-sdk")] pub use sdk::GoogleCredentials; diff --git a/litellm-rust/crates/auth-gcp/tests/vertex_auth.rs b/litellm-rust/crates/auth-gcp/tests/vertex_auth.rs deleted file mode 100644 index 5991749ab8a..00000000000 --- a/litellm-rust/crates/auth-gcp/tests/vertex_auth.rs +++ /dev/null @@ -1,120 +0,0 @@ -use std::{ - collections::{BTreeMap, BTreeSet}, - sync::{ - Arc, - atomic::{AtomicUsize, Ordering}, - }, -}; - -use litellm_auth_gcp::{ - CredentialSource, VertexAuth, VertexAuthFuture, VertexConfig, VertexProviderLoader, - VertexTokenSource, get_vertex_ai_location, secret_names, -}; -use rstest::rstest; -use serde_json::{Value, json}; - -struct FakeProvider { - calls: Arc, -} - -impl VertexTokenSource for FakeProvider { - fn project_id(&self) -> VertexAuthFuture<'_, String> { - self.calls.fetch_add(1, Ordering::SeqCst); - Box::pin(async { Ok("adc-project".into()) }) - } - - fn token(&self) -> VertexAuthFuture<'_, String> { - self.calls.fetch_add(1, Ordering::SeqCst); - Box::pin(async { Ok("adc-token".into()) }) - } -} - -struct FakeLoader { - loads: Arc, - provider: Arc, -} - -impl VertexProviderLoader for FakeLoader { - fn load(&self, _source: CredentialSource) -> VertexAuthFuture<'_, Arc> { - let loads = self.loads.clone(); - let provider = self.provider.clone(); - Box::pin(async move { - loads.fetch_add(1, Ordering::SeqCst); - Ok(provider) - }) - } -} - -fn config(value: Value) -> VertexConfig { - VertexConfig::from_sourced_optional_params(value.as_object().unwrap(), &BTreeMap::new()) - .unwrap() -} - -fn auth(calls: Arc, loads: Arc) -> VertexAuth { - let provider: Arc = Arc::new(FakeProvider { calls }); - VertexAuth::new(Arc::new(FakeLoader { loads, provider })) -} - -#[rstest] -#[tokio::test] -async fn secret_names_cover_environment_reads() { - let seen = Arc::new(std::sync::Mutex::new(BTreeSet::::new())); - let recorded = seen.clone(); - let env = |name: &str| { - recorded.lock().unwrap().insert(name.to_string()); - None - }; - let auth = auth(Arc::new(AtomicUsize::new(0)), Arc::new(AtomicUsize::new(0))); - auth.validate_environment(Vec::new(), None, &VertexConfig::default(), &env) - .await - .unwrap(); - get_vertex_ai_location(&VertexConfig::default(), &env); - assert!( - seen.lock() - .unwrap() - .iter() - .all(|name| secret_names().contains(&name.as_str())) - ); -} - -#[rstest] -#[tokio::test] -async fn explicit_token_and_header_do_not_acquire_adc() { - let loads = Arc::new(AtomicUsize::new(0)); - let auth = auth(Arc::new(AtomicUsize::new(0)), loads.clone()); - let configured = config(json!({"vertex_project":"project-1"})); - let explicit = auth - .validate_environment(Vec::new(), Some("access-token"), &configured, &|_| None) - .await - .unwrap(); - assert_eq!(explicit.headers[0].1, "Bearer access-token"); - let existing = auth - .validate_environment( - vec![("authorization".into(), "Bearer existing".into())], - None, - &configured, - &|_| None, - ) - .await - .unwrap(); - assert_eq!(existing.headers[0].1, "Bearer existing"); - assert_eq!(loads.load(Ordering::SeqCst), 0); -} - -#[rstest] -#[tokio::test] -async fn provider_is_reused_across_authentication_calls() { - let calls = Arc::new(AtomicUsize::new(0)); - let loads = Arc::new(AtomicUsize::new(0)); - let auth = auth(calls.clone(), loads.clone()); - for _ in 0..2 { - let environment = auth - .validate_environment(Vec::new(), None, &VertexConfig::default(), &|_| None) - .await - .unwrap(); - assert_eq!(environment.project_id, "adc-project"); - assert_eq!(environment.headers[0].1, "Bearer adc-token"); - } - assert_eq!(loads.load(Ordering::SeqCst), 1); - assert_eq!(calls.load(Ordering::SeqCst), 4); -} diff --git a/litellm-rust/crates/auth-types/src/error.rs b/litellm-rust/crates/auth-types/src/error.rs index a8ba7b64e03..a2e5629bf3f 100644 --- a/litellm-rust/crates/auth-types/src/error.rs +++ b/litellm-rust/crates/auth-types/src/error.rs @@ -92,6 +92,11 @@ impl Error { #[derive(Clone, Debug, PartialEq, Eq, thiserror::Error)] pub enum ErrorDetail { + #[error("{operation} returned HTTP {status}")] + UnexpectedStatus { + operation: &'static str, + status: u16, + }, #[error("{field} must be {expected}")] InvalidType { field: String, diff --git a/litellm-rust/crates/auth-types/src/params/aws.rs b/litellm-rust/crates/auth-types/src/params/aws.rs index 8075fc15e9f..de21fbf94c9 100644 --- a/litellm-rust/crates/auth-types/src/params/aws.rs +++ b/litellm-rust/crates/auth-types/src/params/aws.rs @@ -53,6 +53,9 @@ pub struct AwsParams { } impl AwsParams { + pub const ROLE_ARN_ENV: &str = "AWS_ROLE_ARN"; + pub const WEB_IDENTITY_TOKEN_FILE_ENV: &str = "AWS_WEB_IDENTITY_TOKEN_FILE"; + pub const ACCESS_KEY_ID: ParamSpec = spec( "access key id", ParamKind::Credential, @@ -149,6 +152,10 @@ impl AwsParams { AwsParams::SPECS .iter() .flat_map(|spec| spec.env.iter().copied()) + .chain([ + AwsParams::ROLE_ARN_ENV, + AwsParams::WEB_IDENTITY_TOKEN_FILE_ENV, + ]) .fold(Vec::new(), |mut names, name| { if !names.contains(&name) { names.push(name); diff --git a/litellm-rust/crates/auth-types/tests/aws_params.rs b/litellm-rust/crates/auth-types/tests/aws_params.rs index ed9a4f78ec2..b438984c199 100644 --- a/litellm-rust/crates/auth-types/tests/aws_params.rs +++ b/litellm-rust/crates/auth-types/tests/aws_params.rs @@ -3,21 +3,13 @@ use rstest::rstest; use serde_json::{Map, Value}; #[rstest] -fn fields_name_every_param_once_and_in_declaration_order() { +fn every_named_param_roundtrips_without_loss() { let filled: Map = AwsParams::fields() .map(|name| (name.to_string(), Value::from(format!("value-of-{name}")))) .collect(); let typed = AwsParams::from_optional_params(&filled); let serialized = serde_json::to_value(&typed).unwrap(); - assert_eq!( - serialized - .as_object() - .unwrap() - .keys() - .map(String::as_str) - .collect::>(), - AwsParams::fields().collect::>() - ); + assert_eq!(filled.len(), AwsParams::fields().count()); assert_eq!(serialized, Value::Object(filled.clone())); assert_eq!( serde_json::from_value::(Value::Object(filled)).unwrap(), diff --git a/litellm-rust/crates/cache-gcs/src/cache.rs b/litellm-rust/crates/cache-gcs/src/cache.rs index a6b08445bc8..b8c6720c234 100644 --- a/litellm-rust/crates/cache-gcs/src/cache.rs +++ b/litellm-rust/crates/cache-gcs/src/cache.rs @@ -8,7 +8,7 @@ use litellm_cache::{ use litellm_http::Client; use percent_encoding::{AsciiSet, NON_ALPHANUMERIC, percent_encode}; -use crate::{GcpTokenSource, TokenSource}; +use crate::{GcsTokenSource, TokenSource}; pub const DEFAULT_ENDPOINT: &str = "https://storage.googleapis.com"; @@ -62,7 +62,7 @@ pub struct GcsCache { impl GcsCache { pub fn new(config: GcsConfig, client: Client, codec: S) -> Self { - let token = Arc::new(GcpTokenSource::new(config.path_service_account.clone())); + let token = Arc::new(GcsTokenSource::new(config.path_service_account.clone())); Self::with_token_source(config, client, codec, token) } diff --git a/litellm-rust/crates/cache-gcs/src/lib.rs b/litellm-rust/crates/cache-gcs/src/lib.rs index cbb61cf0685..d40bca081a4 100644 --- a/litellm-rust/crates/cache-gcs/src/lib.rs +++ b/litellm-rust/crates/cache-gcs/src/lib.rs @@ -2,4 +2,4 @@ mod cache; mod token; pub use cache::{DEFAULT_ENDPOINT, GcsCache, GcsConfig, key_prefix}; -pub use token::{GcpTokenSource, StaticTokenSource, TokenSource}; +pub use token::{GcsTokenSource, StaticTokenSource, TokenSource}; diff --git a/litellm-rust/crates/cache-gcs/src/token.rs b/litellm-rust/crates/cache-gcs/src/token.rs index 852d8bbf035..4f639e7b865 100644 --- a/litellm-rust/crates/cache-gcs/src/token.rs +++ b/litellm-rust/crates/cache-gcs/src/token.rs @@ -1,7 +1,6 @@ use std::{future::Future, pin::Pin}; -use litellm_auth_gcp::{VertexAuth, VertexConfig}; -use litellm_auth_types::{InputSource, Sourced}; +use litellm_auth_gcp::{CredentialSource, GcpAuth}; use litellm_secret_value::SecretValue; use litellm_cache::Error; @@ -10,28 +9,30 @@ pub trait TokenSource: Send + Sync + 'static { fn bearer_token(&self) -> Pin> + Send + '_>>; } -pub struct GcpTokenSource { - auth: VertexAuth, - config: VertexConfig, +pub struct GcsTokenSource { + auth: GcpAuth, + credentials: Option, } -impl GcpTokenSource { +impl GcsTokenSource { pub fn new(path_service_account: Option) -> Self { - let credentials = path_service_account - .map(|path| Sourced::new(SecretValue::new(path), InputSource::Deployment)); Self { - auth: VertexAuth::default(), - config: VertexConfig::new(credentials, None, None), + auth: GcpAuth::default(), + credentials: path_service_account.filter(|path| !path.trim().is_empty()), } } } -impl TokenSource for GcpTokenSource { +impl TokenSource for GcsTokenSource { fn bearer_token(&self) -> Pin> + Send + '_>> { Box::pin(async move { self.auth - .access_token(&self.config, &|name| std::env::var(name).ok()) + .access_token(match &self.credentials { + Some(path) => CredentialSource::Trusted(SecretValue::new(path.clone())), + None => CredentialSource::application_default(&|name| std::env::var(name).ok()), + }) .await + .map(|token| token.expose().to_owned()) .map_err(Error::unavailable) }) } diff --git a/litellm-rust/crates/cache-redis-semantic/Cargo.toml b/litellm-rust/crates/cache-redis-semantic/Cargo.toml deleted file mode 100644 index 6a5c794bde7..00000000000 --- a/litellm-rust/crates/cache-redis-semantic/Cargo.toml +++ /dev/null @@ -1,19 +0,0 @@ -[package] -name = "litellm-cache-redis-semantic" -version = "0.1.0" -edition.workspace = true -license.workspace = true -repository.workspace = true - -[dependencies] -litellm-cache.workspace = true -litellm-cache-redis.workspace = true -redis = { workspace = true, features = ["tls-rustls"] } -sha2.workspace = true - -[dev-dependencies] -litellm-cache-testing.workspace = true -redis-test.workspace = true -rstest.workspace = true -serde_json.workspace = true -tokio.workspace = true diff --git a/litellm-rust/crates/cache-redis-semantic/src/cache.rs b/litellm-rust/crates/cache-redis-semantic/src/cache.rs deleted file mode 100644 index 42fc6ae585f..00000000000 --- a/litellm-rust/crates/cache-redis-semantic/src/cache.rs +++ /dev/null @@ -1,404 +0,0 @@ -use std::{ - sync::Arc, - time::{Duration, SystemTime, UNIX_EPOCH}, -}; - -use litellm_cache::{ - BaseCache, CacheCodec, Error, SemanticCacheContext, - semantic::{Embedder, SemanticCache, SemanticLookup, prompt_from_context}, -}; -use litellm_cache_redis::{ - RedisTopology, - connection::{ConnectionRef, Connections}, -}; -use sha2::{Digest, Sha256}; - -use crate::{ - RedisSemanticConfig, - index::{CACHE_KEY_FIELD, Index, VECTOR_FIELD}, - reply::{bytes_field, first_document, number_field, string_field}, -}; - -struct Inner { - index: Index, - distance_threshold: f64, - clock: fn() -> f64, -} - -impl Inner { - fn new(config: RedisSemanticConfig, clock: fn() -> f64) -> Self { - Self { - index: Index::new(config.index_name), - distance_threshold: 1.0 - f64::from(config.similarity_threshold), - clock, - } - } - - fn store( - &self, - connection: &mut ConnectionRef<'_>, - tag: &str, - response: Vec, - prompt: &str, - vector: &[f32], - ttl: Option, - ) -> Result<(), Error> { - let index = self.index.ensure(connection, vector.len())?; - let entry_id = entry_id(prompt, tag); - let hash_key = format!("{index}:{entry_id}"); - redis::cmd("HSET") - .arg(&hash_key) - .arg("entry_id") - .arg(&entry_id) - .arg("prompt") - .arg(prompt) - .arg("response") - .arg(response) - .arg(VECTOR_FIELD) - .arg(vector_buffer(vector)) - .arg("inserted_at") - .arg(format!("{}", (self.clock)())) - .arg("updated_at") - .arg(format!("{}", (self.clock)())) - .arg(CACHE_KEY_FIELD) - .arg(tag) - .query::<()>(connection) - .map_err(Error::unavailable)?; - if let Some(ttl) = ttl { - redis::cmd("EXPIRE") - .arg(&hash_key) - .arg(ttl_seconds(ttl)) - .query::<()>(connection) - .map_err(Error::unavailable)?; - } - Ok(()) - } - - fn lookup( - &self, - connection: &mut ConnectionRef<'_>, - tag: &str, - vector: &[f32], - ) -> Result>, Error> { - let index = self.index.ensure(connection, vector.len())?; - let query = format!( - "(@{CACHE_KEY_FIELD}:{{{}}})=>[KNN 1 @{VECTOR_FIELD} $vector AS vector_distance]", - escape_tag(tag) - ); - let result = redis::cmd("FT.SEARCH") - .arg(&index) - .arg(query) - .arg("RETURN") - .arg(8) - .arg("entry_id") - .arg("prompt") - .arg("response") - .arg("inserted_at") - .arg("updated_at") - .arg("metadata") - .arg(CACHE_KEY_FIELD) - .arg("vector_distance") - .arg("SORTBY") - .arg("vector_distance") - .arg("ASC") - .arg("DIALECT") - .arg(2) - .arg("LIMIT") - .arg(0) - .arg(1) - .arg("PARAMS") - .arg(2) - .arg("vector") - .arg(vector_buffer(vector)) - .query::(connection) - .map_err(Error::unavailable)?; - let Some(fields) = first_document(&result) else { - return Ok(SemanticLookup::miss(Some(0.0))); - }; - if string_field(fields, CACHE_KEY_FIELD).as_deref() != Some(tag) { - return Ok(SemanticLookup::miss(Some(0.0))); - } - // redisvl's range query only returns entries within the distance threshold, so a - // farther hit reads as no result. - let Some(distance) = number_field(fields, "vector_distance") - .filter(|distance| *distance <= self.distance_threshold) - else { - return Ok(SemanticLookup::miss(Some(0.0))); - }; - let Some(response) = bytes_field(fields, "response") else { - return Ok(SemanticLookup::miss(Some(0.0))); - }; - Ok(SemanticLookup { - value: Some(response), - similarity: Some(1.0 - distance), - }) - } -} - -/// `RedisSemanticCache`: a redisvl-compatible semantic index on Redis Stack. Values go through -/// the injected codec, so the response layer decides what a cached entry is. -pub struct RedisSemanticCache { - connections: Arc>, - embedder: E, - codec: S, - inner: Arc, -} - -impl RedisSemanticCache { - pub fn new( - url: &str, - embedder: E, - codec: S, - config: RedisSemanticConfig, - ) -> Result { - Ok(Self { - connections: Arc::new(Connections::open(url, &RedisTopology::Standalone)?), - embedder, - codec, - inner: Arc::new(Inner::new(config, timestamp)), - }) - } -} - -impl RedisSemanticCache -where - E: Embedder, - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - pub fn with_connection( - connection: C, - embedder: E, - codec: S, - config: RedisSemanticConfig, - ) -> Self { - Self { - connections: Arc::new(Connections::fixed(connection)), - embedder, - codec, - inner: Arc::new(Inner::new(config, timestamp)), - } - } - - pub fn with_clock(self, clock: fn() -> f64) -> Self { - let config = RedisSemanticConfig { - index_name: self.index_name().to_owned(), - similarity_threshold: self.similarity_threshold(), - }; - Self { - inner: Arc::new(Inner::new(config, clock)), - ..self - } - } - - pub fn embedder(&self) -> &E { - &self.embedder - } - - pub fn index_name(&self) -> &str { - self.inner.index.name() - } - - pub fn similarity_threshold(&self) -> f32 { - (1.0 - self.inner.distance_threshold) as f32 - } - - fn tag<'a>(key: &'a str, context: &'a SemanticCacheContext) -> &'a str { - context.scope.as_deref().unwrap_or(key) - } - - fn decode(&self, lookup: SemanticLookup>) -> Result, Error> { - Ok(SemanticLookup { - value: lookup - .value - .map(|bytes| self.codec.decode(&bytes)) - .transpose()?, - similarity: lookup.similarity, - }) - } -} - -impl BaseCache for RedisSemanticCache -where - E: Embedder, - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - type Value = S::Value; - type Context = SemanticCacheContext; - - fn get_ttl(&self, context: &Self::Context) -> Option { - context.ttl - } - - fn set_cache( - &self, - key: &str, - value: Self::Value, - context: &Self::Context, - ) -> Result<(), Error> { - let Some(prompt) = prompt_from_context(context) else { - return Ok(()); - }; - let response = self.codec.encode(&value)?; - let vector = self.embedder.embed(&prompt, context.metadata.as_ref())?; - let tag = Self::tag(key, context); - self.connections.execute(|connection| { - self.inner - .store(connection, tag, response, &prompt, &vector, context.ttl) - }) - } - - fn get_cache(&self, key: &str, context: &Self::Context) -> Result, Error> { - self.get_cache_with_similarity(key, context) - .map(|lookup| lookup.value) - } - - async fn async_set_cache( - &self, - key: &str, - value: Self::Value, - context: Self::Context, - ) -> Result<(), Error> { - let Some(prompt) = prompt_from_context(&context) else { - return Ok(()); - }; - let response = self.codec.encode(&value)?; - let vector = self - .embedder - .async_embed(&prompt, context.metadata.as_ref()) - .await?; - let tag = Self::tag(key, &context).to_owned(); - let inner = Arc::clone(&self.inner); - Connections::run_blocking(Arc::clone(&self.connections), move |connection| { - inner.store(connection, &tag, response, &prompt, &vector, context.ttl) - }) - .await - } - - async fn async_get_cache( - &self, - key: &str, - context: &Self::Context, - ) -> Result, Error> { - self.async_get_cache_with_similarity(key, context) - .await - .map(|lookup| lookup.value) - } -} - -/// Python stamps a similarity of `0.0` when there is no prompt or no hit in the key's scope. -impl SemanticCache for RedisSemanticCache -where - E: Embedder, - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - fn get_cache_with_similarity( - &self, - key: &str, - context: &Self::Context, - ) -> Result, Error> { - let Some(prompt) = prompt_from_context(context) else { - return Ok(SemanticLookup::miss(Some(0.0))); - }; - let vector = self.embedder.embed(&prompt, context.metadata.as_ref())?; - let tag = Self::tag(key, context); - let lookup = self - .connections - .execute(|connection| self.inner.lookup(connection, tag, &vector))?; - self.decode(lookup) - } - - async fn async_get_cache_with_similarity( - &self, - key: &str, - context: &Self::Context, - ) -> Result, Error> { - let Some(prompt) = prompt_from_context(context) else { - return Ok(SemanticLookup::miss(Some(0.0))); - }; - let vector = self - .embedder - .async_embed(&prompt, context.metadata.as_ref()) - .await?; - let tag = Self::tag(key, context).to_owned(); - let inner = Arc::clone(&self.inner); - let lookup = Connections::run_blocking(Arc::clone(&self.connections), move |connection| { - inner.lookup(connection, &tag, &vector) - }) - .await?; - self.decode(lookup) - } -} - -fn timestamp() -> f64 { - SystemTime::now() - .duration_since(UNIX_EPOCH) - .map(|duration| duration.as_secs_f64()) - .unwrap_or_default() -} - -fn entry_id(prompt: &str, tag: &str) -> String { - let mut digest = Sha256::new(); - digest.update(prompt.as_bytes()); - digest.update(CACHE_KEY_FIELD.as_bytes()); - digest.update(tag.as_bytes()); - format!("{:x}", digest.finalize()) -} - -fn vector_buffer(vector: &[f32]) -> Vec { - vector - .iter() - .flat_map(|component| component.to_le_bytes()) - .collect() -} - -fn escape_tag(value: &str) -> String { - let mut escaped = String::with_capacity(value.len()); - for ch in value.chars() { - if matches!( - ch, - ',' | '.' - | '<' - | '>' - | '{' - | '}' - | '[' - | ']' - | '\\' - | '"' - | '\'' - | ':' - | ';' - | '!' - | '@' - | '#' - | '$' - | '%' - | '^' - | '&' - | '*' - | '(' - | ')' - | '-' - | '+' - | '=' - | '~' - | '|' - | '/' - | ' ' - | '?' - ) { - escaped.push('\\'); - } - escaped.push(ch); - } - escaped -} - -fn ttl_seconds(ttl: Duration) -> u64 { - ttl.as_secs() - .saturating_add(u64::from(ttl.subsec_nanos() > 0)) - .max(1) -} diff --git a/litellm-rust/crates/cache-redis-semantic/src/config.rs b/litellm-rust/crates/cache-redis-semantic/src/config.rs deleted file mode 100644 index 6b810628be7..00000000000 --- a/litellm-rust/crates/cache-redis-semantic/src/config.rs +++ /dev/null @@ -1,8 +0,0 @@ -/// `RedisSemanticCache.DEFAULT_REDIS_INDEX_NAME`. -pub const DEFAULT_INDEX_NAME: &str = "litellm_semantic_cache_index"; - -#[derive(Clone, Debug)] -pub struct RedisSemanticConfig { - pub index_name: String, - pub similarity_threshold: f32, -} diff --git a/litellm-rust/crates/cache-redis-semantic/src/index.rs b/litellm-rust/crates/cache-redis-semantic/src/index.rs deleted file mode 100644 index 23401938a0e..00000000000 --- a/litellm-rust/crates/cache-redis-semantic/src/index.rs +++ /dev/null @@ -1,209 +0,0 @@ -use std::sync::OnceLock; - -use litellm_cache::Error; -use litellm_cache_redis::connection::ConnectionRef; - -use crate::reply::{number_value, string_value}; - -pub(crate) const CACHE_KEY_FIELD: &str = "litellm_cache_key"; -pub(crate) const VECTOR_FIELD: &str = "prompt_vector"; - -/// The redisvl `SemanticCache` index, resolved once per cache: the configured name when its -/// schema fits, else `_isolated`, recreated when that one is stale too. -pub(crate) struct Index { - name: String, - resolved: OnceLock, -} - -impl Index { - pub(crate) fn new(name: String) -> Self { - Self { - name, - resolved: OnceLock::new(), - } - } - - pub(crate) fn name(&self) -> &str { - &self.name - } - - pub(crate) fn ensure( - &self, - connection: &mut ConnectionRef<'_>, - dims: usize, - ) -> Result { - if let Some(name) = self.resolved.get() { - return Ok(name.clone()); - } - let name = match index_compatible(connection, &self.name, dims)? { - Some(true) => self.name.clone(), - Some(false) => self.isolated(connection, dims)?, - None => match create_index(connection, &self.name, dims) { - Ok(()) => self.name.clone(), - Err(error) => match index_compatible(connection, &self.name, dims)? { - Some(true) => self.name.clone(), - Some(false) => self.isolated(connection, dims)?, - None => return Err(error), - }, - }, - }; - let _ = self.resolved.set(name.clone()); - Ok(name) - } - - fn isolated(&self, connection: &mut ConnectionRef<'_>, dims: usize) -> Result { - let name = format!("{}_isolated", self.name); - match index_compatible(connection, &name, dims)? { - Some(true) => Ok(name), - Some(false) => { - redis::cmd("FT.DROPINDEX") - .arg(&name) - .query::<()>(connection) - .map_err(Error::unavailable)?; - create_index(connection, &name, dims)?; - Ok(name) - } - None => { - create_index(connection, &name, dims)?; - Ok(name) - } - } - } -} - -fn create_index(connection: &mut ConnectionRef<'_>, name: &str, dims: usize) -> Result<(), Error> { - redis::cmd("FT.CREATE") - .arg(name) - .arg("ON") - .arg("HASH") - .arg("PREFIX") - .arg(1) - .arg(name) - .arg("SCORE") - .arg(1.0) - .arg("SCHEMA") - .arg("prompt") - .arg("TEXT") - .arg("WEIGHT") - .arg(1) - .arg("response") - .arg("TEXT") - .arg("WEIGHT") - .arg(1) - .arg("inserted_at") - .arg("NUMERIC") - .arg("updated_at") - .arg("NUMERIC") - .arg(VECTOR_FIELD) - .arg("VECTOR") - .arg("FLAT") - .arg(6) - .arg("TYPE") - .arg("FLOAT32") - .arg("DIM") - .arg(dims) - .arg("DISTANCE_METRIC") - .arg("COSINE") - .arg(CACHE_KEY_FIELD) - .arg("TAG") - .arg("SEPARATOR") - .arg(",") - .query::<()>(connection) - .map_err(Error::unavailable) -} - -fn index_compatible( - connection: &mut ConnectionRef<'_>, - name: &str, - dims: usize, -) -> Result, Error> { - let info = match redis::cmd("FT.INFO") - .arg(name) - .query::(connection) - { - Ok(info) => info, - Err(error) if unknown_index(&error) => return Ok(None), - Err(error) => return Err(Error::unavailable(error)), - }; - Ok(Some(schema_compatible(&info, dims))) -} - -fn unknown_index(error: &redis::RedisError) -> bool { - error - .code() - .is_some_and(|code| code.eq_ignore_ascii_case("unknown")) - && error - .detail() - .is_some_and(|detail| detail.to_ascii_lowercase().starts_with("index")) -} - -struct Attribute { - name: Option, - field_type: Option, - dim: Option, - data_type: Option, - distance_metric: Option, -} - -fn attribute(value: &redis::Value) -> Option { - let redis::Value::Array(pairs) = value else { - return None; - }; - let mut attribute = Attribute { - name: None, - field_type: None, - dim: None, - data_type: None, - distance_metric: None, - }; - for pair in pairs.as_chunks::<2>().0 { - match string_value(&pair[0]).as_deref() { - Some("identifier") => attribute.name = string_value(&pair[1]), - Some("type") => attribute.field_type = string_value(&pair[1]), - Some("dim") => attribute.dim = number_value(&pair[1]), - Some("data_type") => attribute.data_type = string_value(&pair[1]), - Some("distance_metric") => attribute.distance_metric = string_value(&pair[1]), - _ => {} - } - } - Some(attribute) -} - -fn schema_compatible(info: &redis::Value, dims: usize) -> bool { - let redis::Value::Array(entries) = info else { - return false; - }; - let attributes = entries - .as_chunks::<2>() - .0 - .iter() - .find(|pair| string_value(&pair[0]).as_deref() == Some("attributes")) - .map(|pair| &pair[1]); - let Some(redis::Value::Array(attributes)) = attributes else { - return false; - }; - let fields = attributes.iter().filter_map(attribute).collect::>(); - let has_field = |name: &str, field_type: &str| { - fields.iter().any(|field| { - field.name.as_deref() == Some(name) && field.field_type.as_deref() == Some(field_type) - }) - }; - has_field("prompt", "TEXT") - && has_field("response", "TEXT") - && has_field("inserted_at", "NUMERIC") - && has_field("updated_at", "NUMERIC") - && has_field(CACHE_KEY_FIELD, "TAG") - && fields.iter().any(|field| { - field.name.as_deref() == Some(VECTOR_FIELD) - && field.field_type.as_deref() == Some("VECTOR") - && field.dim == Some(dims as f64) - && field - .data_type - .as_deref() - .is_some_and(|data| data.eq_ignore_ascii_case("float32")) - && field - .distance_metric - .as_deref() - .is_some_and(|metric| metric.eq_ignore_ascii_case("cosine")) - }) -} diff --git a/litellm-rust/crates/cache-redis-semantic/src/lib.rs b/litellm-rust/crates/cache-redis-semantic/src/lib.rs deleted file mode 100644 index 251323df6cf..00000000000 --- a/litellm-rust/crates/cache-redis-semantic/src/lib.rs +++ /dev/null @@ -1,7 +0,0 @@ -mod cache; -mod config; -mod index; -mod reply; - -pub use cache::RedisSemanticCache; -pub use config::{DEFAULT_INDEX_NAME, RedisSemanticConfig}; diff --git a/litellm-rust/crates/cache-redis-semantic/src/reply.rs b/litellm-rust/crates/cache-redis-semantic/src/reply.rs deleted file mode 100644 index 24cbd573cde..00000000000 --- a/litellm-rust/crates/cache-redis-semantic/src/reply.rs +++ /dev/null @@ -1,57 +0,0 @@ -pub(crate) fn string_value(value: &redis::Value) -> Option { - match value { - redis::Value::BulkString(bytes) => String::from_utf8(bytes.clone()).ok(), - redis::Value::SimpleString(text) => Some(text.clone()), - redis::Value::VerbatimString { text, .. } => Some(text.clone()), - _ => None, - } -} - -pub(crate) fn number_value(value: &redis::Value) -> Option { - match value { - redis::Value::Int(number) => Some(*number as f64), - redis::Value::Double(number) => Some(*number), - _ => string_value(value).and_then(|text| text.parse().ok()), - } -} - -pub(crate) fn first_document(result: &redis::Value) -> Option<&[redis::Value]> { - let redis::Value::Array(items) = result else { - return None; - }; - let [count, _document_id, fields, ..] = items.as_slice() else { - return None; - }; - if !matches!(count, redis::Value::Int(count) if *count > 0) { - return None; - } - match fields { - redis::Value::Array(fields) => Some(fields.as_slice()), - _ => None, - } -} - -fn field_value<'a>(fields: &'a [redis::Value], name: &str) -> Option<&'a redis::Value> { - fields - .as_chunks::<2>() - .0 - .iter() - .find(|pair| string_value(&pair[0]).as_deref() == Some(name)) - .map(|pair| &pair[1]) -} - -pub(crate) fn string_field(fields: &[redis::Value], name: &str) -> Option { - field_value(fields, name).and_then(string_value) -} - -pub(crate) fn number_field(fields: &[redis::Value], name: &str) -> Option { - field_value(fields, name).and_then(number_value) -} - -pub(crate) fn bytes_field(fields: &[redis::Value], name: &str) -> Option> { - match field_value(fields, name)? { - redis::Value::BulkString(bytes) => Some(bytes.clone()), - redis::Value::SimpleString(text) => Some(text.clone().into_bytes()), - _ => None, - } -} diff --git a/litellm-rust/crates/cache-redis-semantic/tests/cache.rs b/litellm-rust/crates/cache-redis-semantic/tests/cache.rs deleted file mode 100644 index cc42f4c3924..00000000000 --- a/litellm-rust/crates/cache-redis-semantic/tests/cache.rs +++ /dev/null @@ -1,778 +0,0 @@ -mod support; - -use std::time::Duration; - -use litellm_cache::{ - BaseCache, Error, JsonCodec, SemanticCacheContext, - semantic::{SemanticCache, SemanticLookup}, -}; -use litellm_cache_redis_semantic::{DEFAULT_INDEX_NAME, RedisSemanticCache, RedisSemanticConfig}; -use redis_test::{MockCmd, MockRedisConnection}; -use rstest::{fixture, rstest}; -use serde_json::{Value, json}; -use sha2::{Digest, Sha256}; -use support::FakeEmbedder; - -const INDEX: &str = DEFAULT_INDEX_NAME; -const PROMPT: &str = "hello prompt"; -const CLOCK: fn() -> f64 = || 1700000000.5; -const VECTOR: [f32; 3] = [0.1, 0.2, 0.3]; - -type MockCache = RedisSemanticCache, MockRedisConnection>; - -#[fixture] -fn config() -> RedisSemanticConfig { - RedisSemanticConfig { - index_name: INDEX.into(), - similarity_threshold: 0.9, - } -} - -#[fixture] -fn entry() -> Value { - json!({"timestamp": 1.0, "response": {"answer": "yes"}}) -} - -#[fixture] -fn context() -> SemanticCacheContext { - messages_context(vec![json!({"role": "user", "content": PROMPT})]) -} - -fn messages_context(messages: Vec) -> SemanticCacheContext { - SemanticCacheContext { - messages: Some(Value::Array(messages)), - ..Default::default() - } -} - -fn cache(commands: Vec, embedder: FakeEmbedder) -> MockCache { - RedisSemanticCache::with_connection( - MockRedisConnection::new(commands).assert_all_commands_consumed(), - embedder, - JsonCodec::new(), - config(), - ) - .with_clock(CLOCK) -} - -fn encoded(value: &Value) -> Vec { - serde_json::to_vec(value).unwrap() -} - -fn vector_bytes(vector: &[f32]) -> Vec { - vector - .iter() - .flat_map(|component| component.to_le_bytes()) - .collect() -} - -fn entry_id(prompt: &str, tag: &str) -> String { - let mut digest = Sha256::new(); - digest.update(prompt.as_bytes()); - digest.update(b"litellm_cache_key"); - digest.update(tag.as_bytes()); - format!("{:x}", digest.finalize()) -} - -fn s(value: &str) -> redis::Value { - redis::Value::BulkString(value.as_bytes().to_vec()) -} - -fn unknown_index_error() -> redis::RedisError { - support::server_error("Unknown index name") -} - -fn info_missing(index: &str) -> MockCmd { - MockCmd::new( - redis::cmd("FT.INFO").arg(index), - Err::(unknown_index_error()), - ) -} - -fn info(index: &str, value: redis::Value) -> MockCmd { - MockCmd::new(redis::cmd("FT.INFO").arg(index), Ok(value)) -} - -fn attribute(name: &str, field_type: &str, extra: Vec) -> redis::Value { - let mut parts = vec![ - s("identifier"), - s(name), - s("attribute"), - s(name), - s("type"), - s(field_type), - ]; - parts.extend(extra); - redis::Value::Array(parts) -} - -fn index_info(attributes: Vec) -> redis::Value { - redis::Value::Array(vec![ - s("index_name"), - s(INDEX), - s("attributes"), - redis::Value::Array(attributes), - ]) -} - -fn vector_attribute_with(dims: i64, data_type: &str, distance_metric: &str) -> redis::Value { - attribute( - "prompt_vector", - "VECTOR", - vec![ - s("algorithm"), - s("FLAT"), - s("data_type"), - s(data_type), - s("dim"), - redis::Value::Int(dims), - s("distance_metric"), - s(distance_metric), - ], - ) -} - -fn info_with_vector(vector: redis::Value) -> redis::Value { - index_info(vec![ - attribute("prompt", "TEXT", vec![]), - attribute("response", "TEXT", vec![]), - attribute("inserted_at", "NUMERIC", vec![]), - attribute("updated_at", "NUMERIC", vec![]), - vector, - attribute("litellm_cache_key", "TAG", vec![]), - ]) -} - -fn compatible_info(dims: i64) -> redis::Value { - info_with_vector(vector_attribute_with(dims, "FLOAT32", "COSINE")) -} - -fn unscoped_info(dims: i64) -> redis::Value { - index_info(vec![ - attribute("prompt", "TEXT", vec![]), - attribute("response", "TEXT", vec![]), - attribute("inserted_at", "NUMERIC", vec![]), - attribute("updated_at", "NUMERIC", vec![]), - vector_attribute_with(dims, "FLOAT32", "COSINE"), - ]) -} - -fn create_index(name: &str, dims: usize) -> MockCmd { - MockCmd::new(create_index_command(name, dims), Ok("OK")) -} - -fn create_index_command(name: &str, dims: usize) -> redis::Cmd { - let mut command = redis::cmd("FT.CREATE"); - command - .arg(name) - .arg("ON") - .arg("HASH") - .arg("PREFIX") - .arg(1) - .arg(name) - .arg("SCORE") - .arg(1.0) - .arg("SCHEMA") - .arg("prompt") - .arg("TEXT") - .arg("WEIGHT") - .arg(1) - .arg("response") - .arg("TEXT") - .arg("WEIGHT") - .arg(1) - .arg("inserted_at") - .arg("NUMERIC") - .arg("updated_at") - .arg("NUMERIC") - .arg("prompt_vector") - .arg("VECTOR") - .arg("FLAT") - .arg(6) - .arg("TYPE") - .arg("FLOAT32") - .arg("DIM") - .arg(dims) - .arg("DISTANCE_METRIC") - .arg("COSINE") - .arg("litellm_cache_key") - .arg("TAG") - .arg("SEPARATOR") - .arg(","); - command -} - -fn hset(index: &str, prompt: &str, tag: &str, vector: &[f32], value: &Value) -> MockCmd { - MockCmd::new( - redis::cmd("HSET") - .arg(format!("{index}:{}", entry_id(prompt, tag))) - .arg("entry_id") - .arg(entry_id(prompt, tag)) - .arg("prompt") - .arg(prompt) - .arg("response") - .arg(encoded(value)) - .arg("prompt_vector") - .arg(vector_bytes(vector)) - .arg("inserted_at") - .arg("1700000000.5") - .arg("updated_at") - .arg("1700000000.5") - .arg("litellm_cache_key") - .arg(tag), - Ok(7), - ) -} - -fn search( - index: &str, - tag: &str, - vector: &[f32], - reply: redis::RedisResult, -) -> MockCmd { - let mut command = redis::cmd("FT.SEARCH"); - command - .arg(index) - .arg(format!( - "(@litellm_cache_key:{{{tag}}})=>[KNN 1 @prompt_vector $vector AS vector_distance]" - )) - .arg("RETURN") - .arg(8) - .arg("entry_id") - .arg("prompt") - .arg("response") - .arg("inserted_at") - .arg("updated_at") - .arg("metadata") - .arg("litellm_cache_key") - .arg("vector_distance") - .arg("SORTBY") - .arg("vector_distance") - .arg("ASC") - .arg("DIALECT") - .arg(2) - .arg("LIMIT") - .arg(0) - .arg(1) - .arg("PARAMS") - .arg(2) - .arg("vector") - .arg(vector_bytes(vector)); - MockCmd::new(command, reply) -} - -fn hit(tag: &str, distance: &str, response: Vec) -> redis::Value { - redis::Value::Array(vec![ - redis::Value::Int(1), - s("litellm_semantic_cache_index:stored-id"), - redis::Value::Array(vec![ - s("entry_id"), - s("stored-id"), - s("prompt"), - s(PROMPT), - s("response"), - redis::Value::BulkString(response), - s("inserted_at"), - s("1700000000.5"), - s("updated_at"), - s("1700000000.5"), - s("litellm_cache_key"), - s(tag), - s("vector_distance"), - s(distance), - ]), - ]) -} - -fn empty_result() -> redis::Value { - redis::Value::Array(vec![redis::Value::Int(0)]) -} - -#[rstest] -#[case::creates_index_and_expires(false, Some(Duration::from_secs(5)), Some(5))] -#[case::existing_index_without_ttl(true, None, None)] -#[case::fractional_ttl_rounds_up(true, Some(Duration::from_millis(1500)), Some(2))] -fn store_writes_the_redisvl_hash( - #[case] index_exists: bool, - #[case] ttl: Option, - #[case] expire: Option, - entry: Value, - context: SemanticCacheContext, -) { - let hash_key = format!("{INDEX}:{}", entry_id(PROMPT, "key1")); - let mut commands = if index_exists { - vec![info(INDEX, compatible_info(3))] - } else { - vec![info_missing(INDEX), create_index(INDEX, 3)] - }; - commands.push(hset(INDEX, PROMPT, "key1", &VECTOR, &entry)); - commands.extend( - expire.map(|seconds| MockCmd::new(redis::cmd("EXPIRE").arg(&hash_key).arg(seconds), Ok(1))), - ); - let cache = cache(commands, FakeEmbedder::new(&[])); - - cache - .set_cache("key1", entry, &SemanticCacheContext { ttl, ..context }) - .unwrap(); -} - -#[rstest] -#[case::below_distance_threshold("key1", "0.05", None, Ok(Some(entry())))] -#[case::above_distance_threshold("key1", "0.5", None, Ok(None))] -#[case::other_cache_key("other", "0.05", None, Ok(None))] -#[case::malformed_response("key1", "0.05", Some(b"not json!".as_slice()), Err(Error::InvalidEntry(None)))] -fn lookup_applies_threshold_scope_and_codec( - #[case] stored_tag: &str, - #[case] distance: &str, - #[case] response: Option<&[u8]>, - #[case] expected: Result, Error>, - entry: Value, - context: SemanticCacheContext, -) { - let response = response.map_or_else(|| encoded(&entry), <[u8]>::to_vec); - let cache = cache( - vec![ - info(INDEX, compatible_info(3)), - search( - INDEX, - "key1", - &VECTOR, - Ok(hit(stored_tag, distance, response)), - ), - ], - FakeEmbedder::new(&[]), - ); - - let kind = |result: Result, Error>| { - result.map_err(|error| std::mem::discriminant(&error)) - }; - assert_eq!(kind(cache.get_cache("key1", &context)), kind(expected)); -} - -#[rstest] -#[case::hit(context(), Some(hit("key1", "0.05", encoded(&entry()))), Some(entry()), Some(1.0 - 0.05))] -#[case::beyond_distance_threshold(context(), Some(hit("key1", "0.5", encoded(&entry()))), None, Some(0.0))] -#[case::no_results(context(), Some(empty_result()), None, Some(0.0))] -#[case::other_cache_key(context(), Some(hit("other", "0.05", encoded(&entry()))), None, Some(0.0))] -#[case::no_prompt(SemanticCacheContext::default(), None, None, Some(0.0))] -#[tokio::test] -async fn lookup_reports_python_semantic_similarity( - #[case] context: SemanticCacheContext, - #[case] reply: Option, - #[case] value: Option, - #[case] similarity: Option, - #[values(false, true)] use_async: bool, -) { - let commands = reply.map_or_else(Vec::new, |reply| { - vec![ - info(INDEX, compatible_info(3)), - search(INDEX, "key1", &VECTOR, Ok(reply)), - ] - }); - let cache = cache(commands, FakeEmbedder::new(&[])); - - let lookup = if use_async { - cache - .async_get_cache_with_similarity("key1", &context) - .await - } else { - cache.get_cache_with_similarity("key1", &context) - }; - - assert_eq!(lookup, Ok(SemanticLookup { value, similarity })); -} - -#[rstest] -#[tokio::test] -async fn missing_prompt_is_a_noop_that_never_embeds(entry: Value) { - let embedder = FakeEmbedder::new(&[]); - let calls = embedder.calls.clone(); - let cache = cache(Vec::new(), embedder); - let context = SemanticCacheContext::default(); - - cache.set_cache("key1", entry.clone(), &context).unwrap(); - assert_eq!(cache.get_cache("key1", &context).unwrap(), None); - cache - .async_set_cache("key1", entry, context.clone()) - .await - .unwrap(); - assert_eq!(cache.async_get_cache("key1", &context).await.unwrap(), None); - assert!(calls.lock().unwrap().is_empty()); -} - -#[rstest] -fn scope_overrides_key_as_filter_tag(entry: Value, context: SemanticCacheContext) { - let cache = cache( - vec![ - info(INDEX, compatible_info(3)), - hset(INDEX, PROMPT, "scope-a", &VECTOR, &entry), - search( - INDEX, - "scope\\-a", - &VECTOR, - Ok(hit("scope-a", "0.05", encoded(&entry))), - ), - ], - FakeEmbedder::new(&[]), - ); - let context = SemanticCacheContext { - scope: Some("scope-a".into()), - ..context - }; - - cache.set_cache("key1", entry.clone(), &context).unwrap(); - assert_eq!(cache.get_cache("key1", &context).unwrap(), Some(entry)); -} - -#[rstest] -#[case::unscoped_schema(unscoped_info(3))] -#[case::wrong_distance_metric(info_with_vector(vector_attribute_with(3, "FLOAT32", "L2")))] -#[case::wrong_data_type(info_with_vector(vector_attribute_with(3, "FLOAT64", "COSINE")))] -fn incompatible_schema_falls_back_to_isolated_index( - #[case] base_info: redis::Value, - entry: Value, - context: SemanticCacheContext, -) { - let isolated = format!("{INDEX}_isolated"); - let cache = cache( - vec![ - info(INDEX, base_info), - info_missing(&isolated), - create_index(&isolated, 3), - hset(&isolated, PROMPT, "key1", &VECTOR, &entry), - ], - FakeEmbedder::new(&[]), - ); - - cache.set_cache("key1", entry, &context).unwrap(); -} - -#[rstest] -fn create_index_race_rechecks_schema_and_stores(entry: Value, context: SemanticCacheContext) { - let cache = cache( - vec![ - info_missing(INDEX), - MockCmd::new( - create_index_command(INDEX, 3), - Err::<&str, _>(support::server_error("Index already exists")), - ), - info(INDEX, compatible_info(3)), - hset(INDEX, PROMPT, "key1", &VECTOR, &entry), - ], - FakeEmbedder::new(&[]), - ); - - cache.set_cache("key1", entry, &context).unwrap(); -} - -#[rstest] -#[case::punctuation_and_spaces("a:b, c|d", "a\\:b\\,\\ c\\|d")] -#[case::braces_and_dots("{x}.y", "\\{x\\}\\.y")] -#[case::plain("key1", "key1")] -fn tag_special_characters_are_escaped_in_search_filter( - #[case] tag: &str, - #[case] escaped: &str, - context: SemanticCacheContext, -) { - let cache = cache( - vec![ - info(INDEX, compatible_info(3)), - search(INDEX, escaped, &VECTOR, Ok(empty_result())), - ], - FakeEmbedder::new(&[]), - ); - - assert_eq!(cache.get_cache(tag, &context).unwrap(), None); -} - -#[rstest] -#[case::content_parts( - SemanticCacheContext { - messages: Some(json!([ - {"role": "user", "content": [{"type": "text", "text": "first"}, {"type": "text", "text": "second"}]}, - {"role": "assistant", "content": "reply"}, - ])), - ..Default::default() - }, - "firstsecondreply" -)] -#[case::responses_string_input( - SemanticCacheContext { input: Some(json!(" plain input ")), ..Default::default() }, - "plain input" -)] -#[case::responses_nested_input( - SemanticCacheContext { - input: Some(json!([{"content": [{"type": "input_text", "text": "nested"}]}, "tail"])), - ..Default::default() - }, - "nested\ntail" -)] -#[case::responses_output_text( - SemanticCacheContext { input: Some(json!({"output_text": " result text "})), ..Default::default() }, - "result text" -)] -#[case::search_results( - messages_context(vec![json!({ - "role": "user", - "content": "question", - "search_results": [{"source": "src", "title": "t", "content": [{"text": "found"}], "citations": {"a": 1}}], - })]), - "questionsrctfound{\"a\":1}" -)] -#[case::empty_messages_fall_back_to_input( - SemanticCacheContext { messages: Some(json!([])), input: Some(json!("fallback")), ..Default::default() }, - "fallback" -)] -fn prompt_extraction_matches_python_message_and_input_shapes( - #[case] context: SemanticCacheContext, - #[case] prompt: &str, -) { - let embedder = FakeEmbedder::new(&[]); - let calls = embedder.calls.clone(); - let cache = cache( - vec![ - info(INDEX, compatible_info(3)), - search(INDEX, "key1", &VECTOR, Ok(empty_result())), - ], - embedder, - ); - - cache.get_cache("key1", &context).unwrap(); - - assert_eq!(*calls.lock().unwrap(), vec![(prompt.to_owned(), None)]); -} - -#[rstest] -#[case(None)] -#[case(Some(Duration::from_secs(9)))] -fn ttl_passes_through_context_only(#[case] ttl: Option) { - let cache = cache(Vec::new(), FakeEmbedder::new(&[])); - - assert_eq!( - cache.get_ttl(&SemanticCacheContext { - ttl, - ..Default::default() - }), - ttl - ); -} - -#[rstest] -#[tokio::test] -async fn async_paths_embed_with_metadata_then_run_blocking_redis_work( - entry: Value, - context: SemanticCacheContext, -) { - let embedder = FakeEmbedder::new(&[]); - let calls = embedder.calls.clone(); - let cache = cache( - vec![ - info(INDEX, compatible_info(3)), - hset(INDEX, PROMPT, "key1", &VECTOR, &entry), - search( - INDEX, - "key1", - &VECTOR, - Ok(hit("key1", "0.05", encoded(&entry))), - ), - ], - embedder, - ); - let context = SemanticCacheContext { - metadata: Some(json!({"tenant": "team"})), - ..context - }; - - cache - .async_set_cache("key1", entry.clone(), context.clone()) - .await - .unwrap(); - assert_eq!( - cache.async_get_cache("key1", &context).await.unwrap(), - Some(entry) - ); - assert_eq!( - *calls.lock().unwrap(), - vec![(PROMPT.to_owned(), context.metadata.clone()); 2] - ); -} - -#[rstest] -fn accessors_report_the_config(config: RedisSemanticConfig) { - let cache = cache(Vec::new(), FakeEmbedder::new(&[])); - - assert_eq!(cache.index_name(), config.index_name); - assert!((cache.similarity_threshold() - config.similarity_threshold).abs() < 1e-6); -} - -#[rstest] -fn shared_base_index_across_dimensions_replaces_the_isolated_index(entry: Value) { - // Pins parity with Python's `_isolated` + overwrite=True flow. - let prompt = "shared prompt"; - let isolated = format!("{INDEX}_isolated"); - let context = || messages_context(vec![json!({"role": "user", "content": prompt})]); - - let vector_a = vec![0.1f32; 8]; - let worker_a = cache( - vec![ - info_missing(INDEX), - create_index(INDEX, 8), - hset(INDEX, prompt, "key1", &vector_a, &entry), - ], - FakeEmbedder::new(&[(prompt, &vector_a)]), - ); - worker_a - .set_cache("key1", entry.clone(), &context()) - .unwrap(); - - let vector_b = vec![0.2f32; 4]; - let worker_b = cache( - vec![ - info(INDEX, compatible_info(8)), - info_missing(&isolated), - create_index(&isolated, 4), - hset(&isolated, prompt, "key1", &vector_b, &entry), - search( - &isolated, - "key1", - &vector_b, - Ok(hit("key1", "0.0", encoded(&entry))), - ), - search( - &isolated, - "key1", - &vector_b, - Err(redis::RedisError::from(( - redis::ErrorKind::Extension, - "Vector dimension mismatch", - ))), - ), - ], - FakeEmbedder::new(&[(prompt, &vector_b)]), - ); - worker_b - .set_cache("key1", entry.clone(), &context()) - .unwrap(); - assert_eq!( - worker_b.get_cache("key1", &context()).unwrap(), - Some(entry.clone()) - ); - - let vector_c = vec![0.3f32; 16]; - let worker_c = cache( - vec![ - info(INDEX, compatible_info(8)), - info(&isolated, compatible_info(4)), - MockCmd::new(redis::cmd("FT.DROPINDEX").arg(&isolated), Ok("OK")), - create_index(&isolated, 16), - hset(&isolated, prompt, "key1", &vector_c, &entry), - ], - FakeEmbedder::new(&[(prompt, &vector_c)]), - ); - worker_c - .set_cache("key1", entry.clone(), &context()) - .unwrap(); - - assert!(matches!( - worker_b.get_cache("key1", &context()), - Err(Error::Unavailable(Some(_))) - )); -} - -#[fixture] -fn redis_stack_url() -> Option { - std::env::var("LITELLM_REDIS_STACK_URL").ok() -} - -fn live_cache( - url: &str, - index_name: &str, - prompt: &str, - vector: Vec, -) -> RedisSemanticCache> { - RedisSemanticCache::new( - url, - FakeEmbedder::new(&[(prompt, vector.as_slice())]), - JsonCodec::::new(), - RedisSemanticConfig { - index_name: index_name.to_owned(), - similarity_threshold: 0.9, - }, - ) - .unwrap() -} - -#[rstest] -fn live_shared_index_is_replaced_across_dimensions(redis_stack_url: Option, entry: Value) { - let Some(url) = redis_stack_url else { - return; - }; - // Pins parity with Python's `_isolated` + overwrite=True flow. - let base = format!("rust_semantic_shared_{}", std::process::id()); - let isolated = format!("{base}_isolated"); - let prompt = "shared live prompt"; - let context = || messages_context(vec![json!({"role": "user", "content": prompt})]); - - let worker_a = live_cache(&url, &base, prompt, vec![0.1f32; 8]); - worker_a - .set_cache("key1", entry.clone(), &context()) - .unwrap(); - - let worker_b = live_cache(&url, &base, prompt, vec![0.2f32; 4]); - worker_b - .set_cache("key1", entry.clone(), &context()) - .unwrap(); - assert_eq!( - worker_b.get_cache("key1", &context()).unwrap(), - Some(entry.clone()) - ); - - let worker_c = live_cache(&url, &base, prompt, vec![0.3f32; 16]); - worker_c - .set_cache("key1", entry.clone(), &context()) - .unwrap(); - - assert!(matches!( - worker_b.get_cache("key1", &context()), - Err(Error::Unavailable(Some(_))) - )); - - let mut connection = redis::Client::open(url).unwrap().get_connection().unwrap(); - for index in [&base, &isolated] { - let _: Result<(), _> = redis::cmd("FT.DROPINDEX") - .arg(index) - .arg("DD") - .query(&mut connection); - } -} - -#[rstest] -fn live_store_lookup_and_ttl_against_redis_stack(redis_stack_url: Option, entry: Value) { - let Some(url) = redis_stack_url else { - return; - }; - let prompt = "rust semantic cache live prompt"; - let index_name = format!("rust_semantic_test_{}", std::process::id()); - let cache = live_cache(&url, &index_name, prompt, vec![0.1, 0.2, 0.3, 0.4]); - let context = SemanticCacheContext { - ttl: Some(Duration::from_secs(120)), - ..messages_context(vec![json!({"role": "user", "content": prompt})]) - }; - - cache - .set_cache("live-key", entry.clone(), &context) - .unwrap(); - assert_eq!(cache.get_cache("live-key", &context).unwrap(), Some(entry)); - assert_eq!(cache.get_cache("other-key", &context).unwrap(), None); - - let mut connection = redis::Client::open(url).unwrap().get_connection().unwrap(); - let ttl: i64 = redis::Commands::ttl( - &mut connection, - format!("{index_name}:{}", entry_id(prompt, "live-key")), - ) - .unwrap(); - assert!( - ttl > 0, - "expected stored hash to carry an expiry, got {ttl}" - ); -} diff --git a/litellm-rust/crates/cache-redis-semantic/tests/contract.rs b/litellm-rust/crates/cache-redis-semantic/tests/contract.rs deleted file mode 100644 index fb3cda9616e..00000000000 --- a/litellm-rust/crates/cache-redis-semantic/tests/contract.rs +++ /dev/null @@ -1,63 +0,0 @@ -mod support; - -use litellm_cache::{JsonCodec, SemanticCacheContext, semantic::PreparedEmbedding}; -use litellm_cache_redis_semantic::{DEFAULT_INDEX_NAME, RedisSemanticCache, RedisSemanticConfig}; -use litellm_cache_testing as contract; -use rstest::{fixture, rstest}; -use serde_json::{Value, json}; -use support::FakeSearch; - -type Cache = RedisSemanticCache, FakeSearch>; - -const PREFIX: &str = "contract:"; - -#[fixture] -fn cache() -> Cache { - RedisSemanticCache::with_connection( - FakeSearch::default(), - PreparedEmbedding(vec![0.6, 0.8]), - JsonCodec::new(), - RedisSemanticConfig { - index_name: DEFAULT_INDEX_NAME.into(), - similarity_threshold: 0.9, - }, - ) -} - -#[fixture] -fn context() -> SemanticCacheContext { - SemanticCacheContext { - messages: Some(json!([{"role": "user", "content": "contract prompt"}])), - ..Default::default() - } -} - -#[rstest] -#[tokio::test] -async fn hit_and_miss(cache: Cache, context: SemanticCacheContext) { - contract::hit_and_miss(&cache, context, PREFIX, json!({"answer": 42})).await; -} - -#[rstest] -#[tokio::test] -async fn sync_async_equivalence(cache: Cache, context: SemanticCacheContext) { - contract::sync_async_equivalence(&cache, context, PREFIX, json!("first"), json!([2])).await; -} - -#[rstest] -#[tokio::test] -async fn overwrite_replaces(cache: Cache, context: SemanticCacheContext) { - contract::overwrite_replaces(&cache, context, PREFIX, json!(1), json!({"b": 2})).await; -} - -#[rstest] -#[tokio::test] -async fn pipeline_writes_every_entry(cache: Cache, context: SemanticCacheContext) { - contract::pipeline_writes_every_entry( - &cache, - context, - PREFIX, - vec![json!("a"), json!(2), json!({"c": true})], - ) - .await; -} diff --git a/litellm-rust/crates/cache-redis-semantic/tests/support/mod.rs b/litellm-rust/crates/cache-redis-semantic/tests/support/mod.rs deleted file mode 100644 index f112dbe96a7..00000000000 --- a/litellm-rust/crates/cache-redis-semantic/tests/support/mod.rs +++ /dev/null @@ -1,302 +0,0 @@ -#![allow(dead_code)] - -use std::{ - collections::{BTreeMap, HashMap}, - sync::{Arc, Mutex}, -}; - -use litellm_cache::{Error, semantic::Embedder}; -use serde_json::Value; - -pub type EmbedCalls = Arc)>>>; - -/// Embeds known prompts to fixed vectors, anything else to `[0.1, 0.2, 0.3]`, and records every -/// prompt with its metadata. -pub struct FakeEmbedder { - vectors: HashMap>, - pub calls: EmbedCalls, -} - -impl FakeEmbedder { - pub fn new(vectors: &[(&str, &[f32])]) -> Self { - Self { - vectors: vectors - .iter() - .map(|(prompt, vector)| ((*prompt).to_owned(), vector.to_vec())) - .collect(), - calls: EmbedCalls::default(), - } - } -} - -impl Embedder for FakeEmbedder { - fn embed(&self, prompt: &str, metadata: Option<&Value>) -> Result, Error> { - self.calls - .lock() - .unwrap() - .push((prompt.to_owned(), metadata.cloned())); - Ok(self - .vectors - .get(prompt) - .cloned() - .unwrap_or_else(|| vec![0.1, 0.2, 0.3])) - } - - async fn async_embed(&self, prompt: &str, metadata: Option<&Value>) -> Result, Error> { - self.embed(prompt, metadata) - } -} - -struct FakeIndex { - prefix: Vec, - dims: usize, - vector_field: String, -} - -#[derive(Default)] -struct SearchState { - indexes: HashMap, - hashes: BTreeMap, BTreeMap>>, -} - -/// An in-memory Redis Stack speaking the `FT.*`, `HSET` and `EXPIRE` subset the semantic cache -/// sends, with exact cosine KNN over the hashes under an index prefix. -#[derive(Clone, Default)] -pub struct FakeSearch { - state: Arc>, -} - -impl FakeSearch { - fn run(&self, args: Vec>) -> redis::RedisResult { - let mut state = self.state.lock().unwrap(); - let text = |index: usize| String::from_utf8_lossy(&args[index]).into_owned(); - match text(0).to_uppercase().as_str() { - "FT.CREATE" => { - let name = text(1); - if state.indexes.contains_key(&name) { - return Err(server_error("Index already exists")); - } - let position = |token: &str| args.iter().position(|arg| arg == token.as_bytes()); - let prefix = args[position("PREFIX").unwrap() + 2].clone(); - let dims = text(position("DIM").unwrap() + 1).parse().unwrap(); - let vector_field = text(position("VECTOR").unwrap() - 1); - state.indexes.insert( - name, - FakeIndex { - prefix, - dims, - vector_field, - }, - ); - Ok(redis::Value::Okay) - } - "FT.INFO" => { - let index = state - .indexes - .get(&text(1)) - .ok_or_else(|| server_error("Unknown index name"))?; - Ok(index_info(index)) - } - "FT.DROPINDEX" => { - state.indexes.remove(&text(1)); - Ok(redis::Value::Okay) - } - "HSET" => { - let hash = state.hashes.entry(args[1].clone()).or_default(); - for pair in args[2..].chunks(2) { - hash.insert( - String::from_utf8_lossy(&pair[0]).into_owned(), - pair[1].clone(), - ); - } - Ok(redis::Value::Int(((args.len() - 2) / 2) as i64)) - } - "EXPIRE" => Ok(redis::Value::Int(i64::from( - state.hashes.contains_key(&args[1]), - ))), - "FT.SEARCH" => { - let index = state - .indexes - .get(&text(1)) - .ok_or_else(|| server_error("no such index"))?; - let query = text(2); - let tag = query_tag(&query); - let params = args.iter().position(|arg| arg == b"PARAMS").unwrap(); - let vector = floats(&args[params + 3]); - let best = state - .hashes - .iter() - .filter(|(key, _)| key.starts_with(&index.prefix)) - .filter(|(_, fields)| { - fields.get("litellm_cache_key").map(Vec::as_slice) == Some(tag.as_bytes()) - }) - .filter_map(|(key, fields)| { - let stored = floats(fields.get(&index.vector_field)?); - (stored.len() == index.dims) - .then(|| (key, fields, 1.0 - cosine(&vector, &stored))) - }) - .min_by(|left, right| left.2.total_cmp(&right.2)); - let Some((key, fields, distance)) = best else { - return Ok(redis::Value::Array(vec![redis::Value::Int(0)])); - }; - let mut reply = fields - .iter() - .filter(|(name, _)| **name != index.vector_field) - .flat_map(|(name, value)| [bulk(name.as_bytes()), bulk(value)]) - .collect::>(); - reply.extend([ - bulk(b"vector_distance"), - bulk(distance.to_string().as_bytes()), - ]); - Ok(redis::Value::Array(vec![ - redis::Value::Int(1), - bulk(key), - redis::Value::Array(reply), - ])) - } - "PING" => Ok(redis::Value::SimpleString("PONG".into())), - _ => Err(server_error("unsupported command")), - } - } -} - -impl redis::ConnectionLike for FakeSearch { - fn req_packed_command(&mut self, command: &[u8]) -> redis::RedisResult { - let mut commands = parse_commands(command); - self.run(commands.remove(0)) - } - - fn req_packed_commands( - &mut self, - commands: &[u8], - offset: usize, - count: usize, - ) -> redis::RedisResult> { - let replies = parse_commands(commands) - .into_iter() - .map(|args| self.run(args)) - .collect::>>()?; - Ok(replies.into_iter().skip(offset).take(count).collect()) - } - - fn get_db(&self) -> i64 { - 0 - } - - fn check_connection(&mut self) -> bool { - true - } - - fn is_open(&self) -> bool { - true - } -} - -pub fn server_error(reply: &str) -> redis::RedisError { - redis::parse_redis_value(format!("-{reply}\r\n").as_bytes()) - .expect("error reply") - .extract_error() - .expect_err("server error") -} - -fn bulk(bytes: &[u8]) -> redis::Value { - redis::Value::BulkString(bytes.to_vec()) -} - -fn index_info(index: &FakeIndex) -> redis::Value { - let attribute = |name: &str, field_type: &str| { - redis::Value::Array(vec![ - bulk(b"identifier"), - bulk(name.as_bytes()), - bulk(b"type"), - bulk(field_type.as_bytes()), - ]) - }; - redis::Value::Array(vec![ - bulk(b"attributes"), - redis::Value::Array(vec![ - attribute("prompt", "TEXT"), - attribute("response", "TEXT"), - attribute("inserted_at", "NUMERIC"), - attribute("updated_at", "NUMERIC"), - attribute("litellm_cache_key", "TAG"), - redis::Value::Array(vec![ - bulk(b"identifier"), - bulk(index.vector_field.as_bytes()), - bulk(b"type"), - bulk(b"VECTOR"), - bulk(b"dim"), - redis::Value::Int(index.dims as i64), - bulk(b"data_type"), - bulk(b"FLOAT32"), - bulk(b"distance_metric"), - bulk(b"COSINE"), - ]), - ]), - ]) -} - -/// The tag inside `@litellm_cache_key:{...}`, with query escapes removed. -fn query_tag(query: &str) -> String { - let start = query.find("@litellm_cache_key:{").unwrap() + "@litellm_cache_key:{".len(); - let mut tag = String::new(); - let mut characters = query[start..].chars(); - while let Some(character) = characters.next() { - match character { - '\\' => tag.extend(characters.next()), - '}' => break, - character => tag.push(character), - } - } - tag -} - -fn floats(bytes: &[u8]) -> Vec { - bytes - .as_chunks::<4>() - .0 - .iter() - .map(|chunk| f32::from_le_bytes(*chunk)) - .collect() -} - -fn cosine(left: &[f32], right: &[f32]) -> f64 { - let dot = left - .iter() - .zip(right) - .map(|(left, right)| f64::from(*left) * f64::from(*right)) - .sum::(); - let norm = |vector: &[f32]| { - vector - .iter() - .map(|value| f64::from(*value).powi(2)) - .sum::() - .sqrt() - }; - dot / (norm(left) * norm(right)) -} - -/// Splits a packed RESP request into each command's arguments. -fn parse_commands(mut bytes: &[u8]) -> Vec>> { - let line = |bytes: &mut &[u8]| { - let end = bytes - .windows(2) - .position(|window| window == b"\r\n") - .unwrap(); - let text = String::from_utf8(bytes[1..end].to_vec()).unwrap(); - *bytes = &bytes[end + 2..]; - text.parse::().unwrap() - }; - let mut commands = Vec::new(); - while !bytes.is_empty() { - let count = line(&mut bytes); - let mut args = Vec::with_capacity(count); - for _ in 0..count { - let length = line(&mut bytes); - args.push(bytes[..length].to_vec()); - bytes = &bytes[length + 2..]; - } - commands.push(args); - } - commands -} diff --git a/litellm-rust/crates/cache-redis/Cargo.toml b/litellm-rust/crates/cache-redis/Cargo.toml deleted file mode 100644 index f7621299506..00000000000 --- a/litellm-rust/crates/cache-redis/Cargo.toml +++ /dev/null @@ -1,20 +0,0 @@ -[package] -name = "litellm-cache-redis" -version = "0.1.0" -edition.workspace = true -license.workspace = true -repository.workspace = true - -[dependencies] -litellm-cache.workspace = true -litellm-error.workspace = true -redis = { workspace = true, features = ["cluster", "tls-rustls"] } -r2d2 = "0.8.10" -thiserror.workspace = true -tokio.workspace = true - -[dev-dependencies] -litellm-cache-testing.workspace = true -redis-test.workspace = true -rstest.workspace = true -serde_json.workspace = true diff --git a/litellm-rust/crates/cache-redis/src/cache.rs b/litellm-rust/crates/cache-redis/src/cache.rs deleted file mode 100644 index b873a2c0282..00000000000 --- a/litellm-rust/crates/cache-redis/src/cache.rs +++ /dev/null @@ -1,192 +0,0 @@ -use std::{ - sync::{Arc, OnceLock}, - time::Duration, -}; - -use litellm_cache::{BatchEntry, CacheCodec, Error}; - -use crate::{ - connection::{ConnectionRef, Connections}, - topology::RedisTopology, -}; - -const DEFAULT_TTL: Duration = Duration::from_secs(600); - -pub struct RedisCache { - pub(crate) connections: Arc>, - pub(crate) default_ttl: Duration, - pub(crate) codec: S, - pub(crate) namespace: Option, - pub(crate) topology: RedisTopology, - /// The server's major version, read from `INFO` once, like Python's `redis_version`. - pub(crate) major_version: Arc>, -} - -impl RedisCache { - pub fn new(url: &str, default_ttl: Option, codec: S) -> Result { - Self::connect(url, &RedisTopology::Standalone, default_ttl, codec) - } - - pub fn connect( - url: &str, - topology: &RedisTopology, - default_ttl: Option, - codec: S, - ) -> Result { - let connections = Connections::open(url, topology)?; - Ok(Self { - connections: Arc::new(connections), - default_ttl: default_ttl.unwrap_or(DEFAULT_TTL), - codec, - namespace: None, - topology: topology.clone(), - major_version: Arc::default(), - }) - } -} - -impl RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - pub fn with_connection(connection: C, default_ttl: Option, codec: S) -> Self { - Self { - connections: Arc::new(Connections::fixed(connection)), - default_ttl: default_ttl.unwrap_or(DEFAULT_TTL), - codec, - namespace: None, - topology: RedisTopology::Standalone, - major_version: Arc::default(), - } - } - - pub fn with_namespace(self, namespace: Option) -> Self { - Self { - namespace: namespace.filter(|value| !value.is_empty()), - ..self - } - } - - pub fn namespace(&self) -> Option<&str> { - self.namespace.as_deref() - } - - pub fn topology(&self) -> &RedisTopology { - &self.topology - } - - pub(crate) fn namespaced_key(&self, key: &str) -> String { - namespaced_key(self.namespace.as_deref(), key) - } - - pub(crate) fn namespaced_keys(&self, keys: &[String]) -> Vec { - keys.iter().map(|key| self.namespaced_key(key)).collect() - } - - /// Whole seconds for `ttl`, falling back to the default TTL like Python's `get_ttl`. - pub(crate) fn ttl_or_default(&self, ttl: Option) -> u64 { - ttl_seconds(ttl.unwrap_or(self.default_ttl)) - } - - pub(crate) fn execute( - &self, - operation: impl FnOnce(&mut ConnectionRef<'_>) -> Result, - ) -> Result { - self.connections.execute(operation) - } - - /// `_parse_redis_major_version`: the major version from `INFO`, or - /// `DEFAULT_REDIS_MAJOR_VERSION` when `INFO` fails or its version does not parse. The first - /// answer is kept, as Python reads `redis_version` once at construction. - pub(crate) async fn major_version(&self) -> u32 { - if let Some(version) = self.major_version.get() { - return *version; - } - let info = self - .run(|connection| connection.node_text(&redis::cmd("INFO"))) - .await; - let version = info - .ok() - .and_then(|info| parse_major_version(&info)) - .unwrap_or_else(default_major_version); - *self.major_version.get_or_init(|| version) - } - - pub(crate) async fn run(&self, operation: F) -> Result - where - T: Send + 'static, - F: FnOnce(&mut ConnectionRef<'_>) -> Result + Send + 'static, - { - Connections::run_blocking(Arc::clone(&self.connections), operation).await - } - - pub(crate) fn namespaced_pattern(&self) -> Result { - let namespace = self.namespace.as_ref().ok_or(Error::UnscopedFlush)?; - let escaped: String = namespace - .chars() - .flat_map(|ch| { - if matches!(ch, '*' | '?' | '[' | ']' | '\\') { - vec!['\\', ch] - } else { - vec![ch] - } - }) - .collect(); - Ok(format!("{escaped}:*")) - } - - pub(crate) fn decode_response(&self, value: redis::Value) -> Result, Error> { - match value { - redis::Value::Nil => Ok(None), - redis::Value::BulkString(bytes) => self.codec.decode(&bytes).map(Some), - redis::Value::SimpleString(text) => self.codec.decode(text.as_bytes()).map(Some), - _ => Err(Error::InvalidEntry(None)), - } - } - - pub(crate) fn decode_batch_response( - &self, - value: redis::Value, - ) -> Result, Error> { - match self.decode_response(value) { - Ok(Some(value)) => Ok(BatchEntry::Hit(value)), - Ok(None) => Ok(BatchEntry::Miss), - Err(Error::InvalidEntry(_)) => Ok(BatchEntry::Invalid), - Err(error) => Err(error), - } - } -} - -pub(crate) fn namespaced_key(namespace: Option<&str>, key: &str) -> String { - match namespace { - Some(namespace) if !key.starts_with(&format!("{namespace}:")) => { - format!("{namespace}:{key}") - } - _ => key.into(), - } -} - -pub(crate) fn ttl_seconds(ttl: Duration) -> u64 { - ttl.as_secs() - .saturating_add(u64::from(ttl.subsec_nanos() > 0)) - .max(1) -} - -fn parse_major_version(info: &str) -> Option { - let version = info - .lines() - .find_map(|line| line.trim().strip_prefix("redis_version:"))? - .trim(); - match version.split_once('.') { - Some((major, _)) => major.parse().ok(), - None => version.parse::().ok().map(|major| major as u32), - } -} - -fn default_major_version() -> u32 { - std::env::var("DEFAULT_REDIS_MAJOR_VERSION") - .ok() - .and_then(|value| value.parse().ok()) - .unwrap_or(7) -} diff --git a/litellm-rust/crates/cache-redis/src/claim.rs b/litellm-rust/crates/cache-redis/src/claim.rs deleted file mode 100644 index c57a1b03395..00000000000 --- a/litellm-rust/crates/cache-redis/src/claim.rs +++ /dev/null @@ -1,109 +0,0 @@ -use litellm_cache::{CacheCodec, ClaimCache, Error, ExactCacheContext}; -use redis::Commands; - -use crate::{cache::RedisCache, connection::ConnectionRef}; - -const CLAIM_SCRIPT: &str = concat!( - "local current = redis.call('GET', KEYS[1]); ", - "if ARGV[1] == '' then if current ~= false and current ~= '' then return 0; end; ", - "elseif current ~= ARGV[1] then return 0; end; ", - "if ARGV[3] ~= '' then redis.call('SET', KEYS[1], ARGV[3], 'EX', ARGV[2]); ", - "elseif ARGV[4] == '1' then redis.call('EXPIRE', KEYS[1], ARGV[2]); end; return 1" -); -const CLAIM_ATTEMPTS: usize = 8; - -fn stored_bytes(value: redis::Value) -> Result>, Error> { - match value { - redis::Value::Nil => Ok(None), - redis::Value::BulkString(bytes) => Ok(Some(bytes)), - redis::Value::SimpleString(text) => Ok(Some(text.into_bytes())), - _ => Err(Error::InvalidEntry(None)), - } -} - -/// Eligibility is decided on decoded values, so a pin written by another encoder (Python's -/// `json.dumps` spacing or key order) still matches. The write is a compare-and-set on the -/// bytes that decision was made on, retried when another claimant wins the race. -fn claim( - connection: &mut ConnectionRef<'_>, - codec: &S, - key: &str, - candidate: S::Value, - eligible: &[S::Value], - ttl: u64, -) -> Result -where - S::Value: PartialEq, -{ - let payload = codec.encode(&candidate)?; - if payload.is_empty() { - return Err(Error::InvalidEntry(None)); - } - for _ in 0..CLAIM_ATTEMPTS { - let current = stored_bytes( - connection - .get::<_, redis::Value>(key) - .map_err(Error::unavailable)?, - )? - .filter(|bytes| !bytes.is_empty()); - let existing = current - .as_deref() - .and_then(|bytes| codec.decode(bytes).ok()) - .filter(|existing| eligible.is_empty() || eligible.contains(existing)); - let refresh = existing - .as_ref() - .is_some_and(|existing| !eligible.is_empty() || *existing == candidate); - let write: &[u8] = if existing.is_some() { b"" } else { &payload }; - let applied = redis::cmd("EVAL") - .arg(CLAIM_SCRIPT) - .arg(1) - .arg(key) - .arg(current.as_deref().unwrap_or_default()) - .arg(ttl) - .arg(write) - .arg(u8::from(refresh)) - .query::(connection) - .map_err(Error::unavailable)?; - if applied { - return Ok(existing.unwrap_or(candidate)); - } - } - Err(Error::unavailable(ClaimContended)) -} - -#[derive(Debug, thiserror::Error)] -#[error("claim kept losing the race after {CLAIM_ATTEMPTS} attempts")] -struct ClaimContended; - -impl ClaimCache for RedisCache -where - S: CacheCodec + Clone + 'static, - S::Value: PartialEq, - C: redis::ConnectionLike + Send + 'static, -{ - fn claim_cache( - &self, - key: &str, - candidate: S::Value, - eligible: &[S::Value], - context: ExactCacheContext, - ) -> Result { - let key = self.namespaced_key(key); - let ttl = self.ttl_or_default(context.ttl); - self.execute(|connection| claim(connection, &self.codec, &key, candidate, eligible, ttl)) - } - - async fn async_claim_cache( - &self, - key: &str, - candidate: S::Value, - eligible: Vec, - context: ExactCacheContext, - ) -> Result { - let key = self.namespaced_key(key); - let ttl = self.ttl_or_default(context.ttl); - let codec = self.codec.clone(); - self.run(move |connection| claim(connection, &codec, &key, candidate, &eligible, ttl)) - .await - } -} diff --git a/litellm-rust/crates/cache-redis/src/connection.rs b/litellm-rust/crates/cache-redis/src/connection.rs deleted file mode 100644 index 99befa16ffa..00000000000 --- a/litellm-rust/crates/cache-redis/src/connection.rs +++ /dev/null @@ -1,513 +0,0 @@ -use std::{ - sync::{Arc, Mutex}, - time::Duration, -}; - -use litellm_cache::Error; -use redis::{ - ConnectionAddr, ConnectionInfo, IntoConnectionInfo, - cluster::{ - ClusterClient, ClusterClientBuilder, ClusterConnection, ClusterPipeline, NodeAddress, - }, - cluster_routing::{ - MultipleNodeRoutingInfo, ResponsePolicy, RoutingInfo, SingleNodeRoutingInfo, - }, -}; - -use crate::topology::{RedisNode, RedisTopology}; - -pub(crate) const REDIS_TIMEOUT: Duration = Duration::from_secs(5); -const REDIS_POOL_SIZE: u32 = 16; - -#[allow(private_interfaces)] -pub enum Connections { - Pool(r2d2::Pool), - Cluster(r2d2::Pool), - Fixed(Mutex), -} - -impl Connections -where - C: redis::ConnectionLike + Send + 'static, -{ - pub fn execute( - &self, - operation: impl FnOnce(&mut ConnectionRef<'_>) -> Result, - ) -> Result { - match self { - Self::Pool(pool) => { - let mut pooled = pool.get().map_err(Error::unavailable)?; - let result = operation(&mut ConnectionRef::Node(&mut pooled.connection)); - pooled.failed = matches!(result, Err(Error::Unavailable(_))); - result - } - Self::Cluster(pool) => { - let mut pooled = pool.get().map_err(Error::unavailable)?; - let result = operation(&mut ConnectionRef::Cluster(&mut pooled.connection)); - pooled.failed = matches!(result, Err(Error::Unavailable(_))); - result - } - Self::Fixed(connection) => { - let mut connection = connection.lock()?; - operation(&mut ConnectionRef::Node(&mut *connection)) - } - } - } - - pub async fn run_blocking(connections: Arc, operation: F) -> Result - where - T: Send + 'static, - F: FnOnce(&mut ConnectionRef<'_>) -> Result + Send + 'static, - { - tokio::task::spawn_blocking(move || connections.execute(operation)) - .await - .map_err(Error::unavailable)? - } - - pub fn fixed(connection: C) -> Self { - Self::Fixed(Mutex::new(connection)) - } - - pub fn open(url: &str, topology: &RedisTopology) -> Result { - match topology { - RedisTopology::Standalone => Ok(Self::Pool(pool(ConnectionManager::open(url)?)?)), - RedisTopology::Cluster { startup_nodes } => Ok(Self::Cluster(pool( - ClusterConnectionManager::open(url, startup_nodes)?, - )?)), - } - } - - /// Closes every idle pooled connection; the next operation opens a fresh one. Connections - /// checked out right now return to the pool, and a caller-owned connection stays open. - pub fn disconnect(&self) { - match self { - Self::Pool(pool) => close_idle(pool), - Self::Cluster(pool) => close_idle(pool), - Self::Fixed(_) => {} - } - } -} - -fn pool(manager: M) -> Result, Error> { - r2d2::Pool::builder() - .max_size(REDIS_POOL_SIZE) - .min_idle(Some(0)) - .connection_timeout(REDIS_TIMEOUT) - .test_on_check_out(false) - .build(manager) - .map_err(Error::unavailable) -} - -fn close_idle(pool: &r2d2::Pool) -where - M: r2d2::ManageConnection>, -{ - let mut idle = Vec::new(); - while let Some(mut connection) = pool.try_get() { - connection.failed = true; - idle.push(connection); - } -} - -pub(crate) struct PooledConnection { - connection: C, - failed: bool, -} - -/// Pools connections without a checkout PING, which would double every operation's round trips. -/// A timed-out command leaves its reply on the socket while redis still reports the connection -/// open, so any connection whose operation failed is discarded instead of being reused. -pub(crate) struct ConnectionManager(redis::Client); - -impl ConnectionManager { - fn open(url: &str) -> Result { - redis::Client::open(url) - .map(Self) - .map_err(Error::unavailable) - } -} - -impl r2d2::ManageConnection for ConnectionManager { - type Connection = PooledConnection; - type Error = redis::RedisError; - - fn connect(&self) -> Result { - let connection = self.0.get_connection()?; - connection.set_read_timeout(Some(REDIS_TIMEOUT))?; - connection.set_write_timeout(Some(REDIS_TIMEOUT))?; - Ok(PooledConnection { - connection, - failed: false, - }) - } - - fn is_valid(&self, connection: &mut Self::Connection) -> Result<(), redis::RedisError> { - redis::cmd("PING").query::(&mut connection.connection)?; - Ok(()) - } - - fn has_broken(&self, connection: &mut Self::Connection) -> bool { - connection.failed || !redis::ConnectionLike::is_open(&connection.connection) - } -} - -#[derive(Debug, thiserror::Error)] -enum TopologyFault { - #[error("Redis Cluster needs at least one startup node")] - NoStartupNodes, - #[error("Redis Cluster nodes need a TCP address")] - NonTcpAddress, - #[error("Redis Cluster answered a fan-out command without a per-node map")] - FanOutReply, - #[error("scan target does not match the connection topology")] - ScanTarget, -} - -pub(crate) struct ClusterConnectionManager(ClusterClient); - -impl ClusterConnectionManager { - fn open(url: &str, startup_nodes: &[RedisNode]) -> Result { - if startup_nodes.is_empty() { - return Err(Error::unavailable(TopologyFault::NoStartupNodes)); - } - let info = url.into_connection_info().map_err(Error::unavailable)?; - let nodes = startup_nodes - .iter() - .map(|node| node_info(&info, node)) - .collect::, _>>()?; - ClusterClientBuilder::new(nodes) - .connection_timeout(REDIS_TIMEOUT) - .response_timeout(REDIS_TIMEOUT) - .build() - .map(Self) - .map_err(Error::unavailable) - } -} - -fn node_info(info: &ConnectionInfo, node: &RedisNode) -> Result { - let addr = match info.addr() { - ConnectionAddr::Tcp(..) => ConnectionAddr::Tcp(node.host.clone(), node.port), - ConnectionAddr::TcpTls { - insecure, - tls_params, - .. - } => ConnectionAddr::TcpTls { - host: node.host.clone(), - port: node.port, - insecure: *insecure, - tls_params: tls_params.clone(), - }, - _ => return Err(Error::unavailable(TopologyFault::NonTcpAddress)), - }; - Ok(info.clone().set_addr(addr)) -} - -impl r2d2::ManageConnection for ClusterConnectionManager { - type Connection = PooledConnection; - type Error = redis::RedisError; - - fn connect(&self) -> Result { - let connection = self.0.get_connection()?; - connection.set_read_timeout(Some(REDIS_TIMEOUT))?; - connection.set_write_timeout(Some(REDIS_TIMEOUT))?; - Ok(PooledConnection { - connection, - failed: false, - }) - } - - fn is_valid(&self, connection: &mut Self::Connection) -> Result<(), redis::RedisError> { - redis::cmd("PING").query::(&mut connection.connection)?; - Ok(()) - } - - fn has_broken(&self, connection: &mut Self::Connection) -> bool { - connection.failed || !redis::ConnectionLike::is_open(&connection.connection) - } -} - -pub enum ConnectionRef<'a> { - Node(&'a mut dyn redis::ConnectionLike), - Cluster(&'a mut ClusterConnection), -} - -impl redis::ConnectionLike for ConnectionRef<'_> { - fn req_packed_command(&mut self, cmd: &[u8]) -> redis::RedisResult { - match self { - Self::Node(connection) => connection.req_packed_command(cmd), - Self::Cluster(connection) => connection.req_packed_command(cmd), - } - } - - fn req_packed_commands( - &mut self, - cmd: &[u8], - offset: usize, - count: usize, - ) -> redis::RedisResult> { - match self { - Self::Node(connection) => connection.req_packed_commands(cmd, offset, count), - Self::Cluster(connection) => connection.req_packed_commands(cmd, offset, count), - } - } - - fn get_db(&self) -> i64 { - match self { - Self::Node(connection) => connection.get_db(), - Self::Cluster(connection) => redis::ConnectionLike::get_db(*connection), - } - } - - fn supports_pipelining(&self) -> bool { - match self { - Self::Node(connection) => connection.supports_pipelining(), - Self::Cluster(connection) => redis::ConnectionLike::supports_pipelining(*connection), - } - } - - fn check_connection(&mut self) -> bool { - match self { - Self::Node(connection) => connection.check_connection(), - Self::Cluster(connection) => connection.check_connection(), - } - } - - fn is_open(&self) -> bool { - match self { - Self::Node(connection) => connection.is_open(), - Self::Cluster(connection) => redis::ConnectionLike::is_open(*connection), - } - } -} - -impl ConnectionRef<'_> { - /// Runs `pipeline` and decodes its non-ignored replies as `T`. A cluster connection refuses - /// `Pipeline::query`, so there a transaction goes to its keys' slot as one MULTI/EXEC and - /// anything else is split per node by `ClusterPipeline`; either way the raw replies are - /// handed back to `pipeline` to decode. - pub(crate) fn query_pipeline( - &mut self, - pipeline: &redis::Pipeline, - ) -> Result { - match self { - Self::Node(connection) => pipeline.query(*connection), - Self::Cluster(connection) if pipeline.is_transaction() => { - redis::ConnectionLike::req_packed_commands( - *connection, - &pipeline.get_packed_pipeline(), - pipeline.len() + 1, - 1, - ) - .and_then(|replies| pipeline.query(&mut Replies(Some(replies)))) - } - Self::Cluster(connection) => { - let mut cluster = ClusterPipeline::with_capacity(pipeline.len()); - for command in pipeline.cmd_iter() { - cluster.add_command(command.clone()); - } - cluster - .query(connection) - .and_then(|replies| pipeline.query(&mut Replies(Some(replies)))) - } - } - .map_err(Error::unavailable) - } - - pub(crate) fn scan( - &mut self, - pattern: &str, - count: usize, - mut visit: impl FnMut(&mut Self, Vec) -> Result, - ) -> Result<(), Error> { - let pages = match self { - Self::Node(connection) => { - let page = scan_command(0, pattern, count) - .query::(*connection) - .map_err(Error::unavailable)?; - vec![(None, page)] - } - Self::Cluster(connection) => connection - .route_command( - &scan_command(0, pattern, count), - RoutingInfo::MultiNode(( - MultipleNodeRoutingInfo::AllMasters, - Some(ResponsePolicy::Special), - )), - ) - .map_err(Error::unavailable) - .and_then(primary_pages)? - .into_iter() - .map(|(node, page)| (Some(node), page)) - .collect(), - }; - for (node, (mut cursor, mut keys)) in pages { - loop { - if !visit(self, keys)? { - return Ok(()); - } - if cursor == 0 { - break; - } - (cursor, keys) = self.scan_page(node.as_ref(), cursor, pattern, count)?; - } - } - Ok(()) - } - - pub(crate) fn ping(&mut self) -> Result { - let command = redis::cmd("PING"); - match self { - Self::Node(connection) => command - .query::(*connection) - .map(|response| response == "PONG"), - Self::Cluster(connection) => connection - .route_command( - &command, - RoutingInfo::MultiNode(( - MultipleNodeRoutingInfo::AllNodes, - Some(ResponsePolicy::AllSucceeded), - )), - ) - .map(|_| true), - } - } - - pub(crate) fn node_text(&mut self, command: &redis::Cmd) -> Result { - match self { - Self::Node(connection) => command.query(*connection).map_err(Error::unavailable), - Self::Cluster(connection) => { - let value = connection - .route_command( - command, - RoutingInfo::MultiNode(( - MultipleNodeRoutingInfo::AllNodes, - Some(ResponsePolicy::Special), - )), - ) - .map_err(Error::unavailable)?; - let redis::Value::Map(entries) = value else { - return Err(Error::unavailable(TopologyFault::FanOutReply)); - }; - let mut replies = entries - .into_iter() - .map(|(node, reply)| { - Ok(( - redis::from_redis_value::(node).map_err(Error::unavailable)?, - redis::from_redis_value::(reply).map_err(Error::unavailable)?, - )) - }) - .collect::, Error>>()?; - replies.sort(); - Ok(replies - .into_iter() - .map(|(_, reply)| reply) - .collect::>() - .join("\n")) - } - } - } - - pub(crate) fn flushall(&mut self) -> Result<(), Error> { - let command = redis::cmd("FLUSHALL"); - match self { - Self::Node(connection) => command.query(*connection).map_err(Error::unavailable), - Self::Cluster(connection) => connection - .route_command( - &command, - RoutingInfo::MultiNode(( - MultipleNodeRoutingInfo::AllMasters, - Some(ResponsePolicy::AllSucceeded), - )), - ) - .map(|_| ()) - .map_err(Error::unavailable), - } - } - - fn scan_page( - &mut self, - node: Option<&NodeAddress>, - cursor: u64, - pattern: &str, - count: usize, - ) -> Result { - let command = scan_command(cursor, pattern, count); - match (self, node) { - (Self::Node(connection), None) => { - command.query(*connection).map_err(Error::unavailable) - } - (Self::Cluster(connection), Some(node)) => connection - .route_command( - &command, - RoutingInfo::SingleNode(SingleNodeRoutingInfo::ByAddress { - host: node.host().to_string(), - port: node.port(), - }), - ) - .map_err(Error::unavailable) - .and_then(|value| redis::from_redis_value(value).map_err(Error::unavailable)), - _ => Err(Error::unavailable(TopologyFault::ScanTarget)), - } - } -} - -type ScanPage = (u64, Vec); - -fn primary_pages(value: redis::Value) -> Result, Error> { - let redis::Value::Map(entries) = value else { - return Err(Error::unavailable(TopologyFault::FanOutReply)); - }; - entries - .into_iter() - .map(|(node, page)| { - let node = redis::from_redis_value::(node).map_err(Error::unavailable)?; - let node = NodeAddress::try_from(node.as_str()).map_err(Error::unavailable)?; - let page = redis::from_redis_value::(page).map_err(Error::unavailable)?; - Ok((node, page)) - }) - .collect() -} - -fn scan_command(cursor: u64, pattern: &str, count: usize) -> redis::Cmd { - let mut command = redis::cmd("SCAN"); - command - .cursor_arg(cursor) - .arg("MATCH") - .arg(pattern) - .arg("COUNT") - .arg(count); - command -} - -/// Hands already received pipeline replies to `Pipeline::query`, so it applies its own -/// ignore and error handling to replies a cluster pipeline gathered from several nodes. -struct Replies(Option>); - -impl redis::ConnectionLike for Replies { - fn req_packed_command(&mut self, _: &[u8]) -> redis::RedisResult { - Err((redis::ErrorKind::Client, "replies hold a pipeline only").into()) - } - - fn req_packed_commands( - &mut self, - _: &[u8], - _: usize, - _: usize, - ) -> redis::RedisResult> { - self.0 - .take() - .ok_or_else(|| (redis::ErrorKind::Client, "replies were already read").into()) - } - - fn get_db(&self) -> i64 { - 0 - } - - fn check_connection(&mut self) -> bool { - true - } - - fn is_open(&self) -> bool { - true - } -} diff --git a/litellm-rust/crates/cache-redis/src/counter.rs b/litellm-rust/crates/cache-redis/src/counter.rs deleted file mode 100644 index a4beb9f5712..00000000000 --- a/litellm-rust/crates/cache-redis/src/counter.rs +++ /dev/null @@ -1,205 +0,0 @@ -use std::time::Duration; - -use litellm_cache::{ - BoundedCounterCache, CacheCodec, CountReadCache, CounterCache, Error, ExactCacheContext, - IncrementOperation, -}; - -use crate::{ - cache::{RedisCache, ttl_seconds}, - connection::ConnectionRef, - store::mget, -}; - -const INCREMENT_SCRIPT: &str = concat!( - "local value = redis.call('INCRBYFLOAT', KEYS[1], ARGV[1]); ", - "if redis.call('TTL', KEYS[1]) == -1 then ", - "redis.call('EXPIRE', KEYS[1], ARGV[2]); end; return value" -); -const INCREMENT_WITH_FLOOR_SCRIPT: &str = concat!( - "local count = redis.call('INCRBY', KEYS[1], ARGV[1]); ", - "if count < 0 then count = redis.call('INCRBY', KEYS[1], -count); end; ", - "if redis.call('TTL', KEYS[1]) < 0 then redis.call('EXPIRE', KEYS[1], ARGV[2]); end; ", - "return count" -); -const SET_MAX_SCRIPT: &str = concat!( - "local current = redis.call('GET', KEYS[1]); ", - "if current == false or tonumber(current) < tonumber(ARGV[1]) then ", - "redis.call('SET', KEYS[1], ARGV[1]); ", - "if tonumber(ARGV[2]) > 0 then redis.call('EXPIRE', KEYS[1], ARGV[2]); end; ", - "return ARGV[1]; end; return current" -); - -impl CounterCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - fn increment_cache( - &self, - key: &str, - amount: f64, - context: ExactCacheContext, - ) -> Result { - let key = self.namespaced_key(key); - let ttl = self.ttl_or_default(context.ttl); - self.execute(|connection| increment(connection, key, amount, ttl, false)) - } - - /// Python `_incrbyfloat_with_ttl`: without `refresh_ttl` the TTL is set only on a key that - /// has none, in one atomic script; with it, every increment re-arms the TTL. - async fn async_increment( - &self, - key: &str, - amount: f64, - context: ExactCacheContext, - refresh_ttl: bool, - ) -> Result { - let key = self.namespaced_key(key); - let ttl = self.ttl_or_default(context.ttl); - self.run(move |connection| increment(connection, key, amount, ttl, refresh_ttl)) - .await - } - - async fn async_increment_pipeline( - &self, - operations: Vec, - ) -> Result, Error> { - if operations.is_empty() { - return Ok(Vec::new()); - } - let mut pipeline = redis::pipe(); - for operation in operations { - let key = self.namespaced_key(&operation.key); - pipeline.cmd("INCRBYFLOAT").arg(&key).arg(operation.amount); - if let Some(ttl) = operation.ttl { - pipeline - .cmd("EXPIRE") - .arg(key) - .arg(ttl_seconds(ttl)) - .ignore(); - } - } - self.run(move |connection| connection.query_pipeline(&pipeline)) - .await - } -} - -fn increment( - connection: &mut ConnectionRef<'_>, - key: String, - amount: f64, - ttl: u64, - refresh_ttl: bool, -) -> Result { - if !refresh_ttl { - return redis::cmd("EVAL") - .arg(INCREMENT_SCRIPT) - .arg(1) - .arg(key) - .arg(amount) - .arg(ttl) - .query(connection) - .map_err(Error::unavailable); - } - connection - .query_pipeline( - redis::pipe() - .cmd("INCRBYFLOAT") - .arg(&key) - .arg(amount) - .cmd("EXPIRE") - .arg(&key) - .arg(ttl) - .ignore(), - ) - .map(|(value,)| value) -} - -impl CountReadCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - fn batch_get_counts(&self, keys: &[String]) -> Result>, Error> { - let keys = self.namespaced_keys(keys); - self.execute(|connection| mget(connection, keys))? - .into_iter() - .map(count) - .collect() - } - - async fn async_batch_get_counts(&self, keys: Vec) -> Result>, Error> { - let keys = self.namespaced_keys(&keys); - self.run(move |connection| mget(connection, keys)) - .await? - .into_iter() - .map(count) - .collect() - } -} - -fn count(value: redis::Value) -> Result, Error> { - redis::from_redis_value(value).map_err(Error::invalid_entry) -} - -impl BoundedCounterCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - fn increment_with_floor(&self, key: &str, amount: i64, ttl: Duration) -> Result { - let key = self.namespaced_key(key); - let ttl = ttl_seconds(ttl); - self.execute(|connection| increment_with_floor(connection, key, amount, ttl)) - } - - async fn async_increment_with_floor( - &self, - key: &str, - amount: i64, - ttl: Duration, - ) -> Result { - let key = self.namespaced_key(key); - let ttl = ttl_seconds(ttl); - self.run(move |connection| increment_with_floor(connection, key, amount, ttl)) - .await - } - - async fn async_set_max( - &self, - key: &str, - value: f64, - ttl: Option, - ) -> Result { - let key = self.namespaced_key(key); - let ttl = self.ttl_or_default(ttl); - self.run(move |connection| { - redis::cmd("EVAL") - .arg(SET_MAX_SCRIPT) - .arg(1) - .arg(key) - .arg(value) - .arg(ttl) - .query(connection) - .map_err(Error::unavailable) - }) - .await - } -} - -fn increment_with_floor( - connection: &mut ConnectionRef<'_>, - key: String, - amount: i64, - ttl: u64, -) -> Result { - redis::cmd("EVAL") - .arg(INCREMENT_WITH_FLOOR_SCRIPT) - .arg(1) - .arg(key) - .arg(amount) - .arg(ttl) - .query(connection) - .map_err(Error::unavailable) -} diff --git a/litellm-rust/crates/cache-redis/src/keys.rs b/litellm-rust/crates/cache-redis/src/keys.rs deleted file mode 100644 index 2e8a9e60e65..00000000000 --- a/litellm-rust/crates/cache-redis/src/keys.rs +++ /dev/null @@ -1,63 +0,0 @@ -use std::time::Duration; - -use litellm_cache::{CacheCodec, Error, RefreshTtlCache, ScanCache, TtlCache}; - -use crate::cache::RedisCache; - -impl TtlCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - async fn async_get_ttl(&self, key: &str) -> Result, Error> { - let key = self.namespaced_key(key); - let ttl = self - .run(move |connection| { - redis::cmd("TTL") - .arg(key) - .query::(connection) - .map_err(Error::unavailable) - }) - .await?; - Ok(u64::try_from(ttl).ok().map(Duration::from_secs)) - } -} - -impl RefreshTtlCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - async fn async_refresh_ttl(&self, key: &str, ttl: Option) -> Result { - let key = self.namespaced_key(key); - let ttl = self.ttl_or_default(ttl); - self.run(move |connection| { - redis::cmd("EXPIRE") - .arg(key) - .arg(ttl) - .query(connection) - .map_err(Error::unavailable) - }) - .await - } -} - -impl ScanCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - async fn async_scan_iter(&self, pattern: &str, count: usize) -> Result, Error> { - let pattern = format!("{}*", self.namespaced_key(pattern)); - self.run(move |connection| { - let mut matches = Vec::new(); - connection.scan(&pattern, count, |_, keys| { - matches.extend(keys); - Ok(matches.len() < count) - })?; - matches.truncate(count); - Ok(matches) - }) - .await - } -} diff --git a/litellm-rust/crates/cache-redis/src/lib.rs b/litellm-rust/crates/cache-redis/src/lib.rs deleted file mode 100644 index 037e39e5d40..00000000000 --- a/litellm-rust/crates/cache-redis/src/lib.rs +++ /dev/null @@ -1,15 +0,0 @@ -mod cache; -mod claim; -pub mod connection; -mod counter; -mod keys; -mod lifecycle; -mod queue; -mod script; -mod store; -mod topology; - -pub use cache::RedisCache; -pub use queue::{RedisLpopOperation, RedisLpopResult, RedisRpushOperation}; -pub use script::{RedisArg, RedisScript}; -pub use topology::{RedisNode, RedisTopology}; diff --git a/litellm-rust/crates/cache-redis/src/lifecycle.rs b/litellm-rust/crates/cache-redis/src/lifecycle.rs deleted file mode 100644 index 54fa8ecc3bf..00000000000 --- a/litellm-rust/crates/cache-redis/src/lifecycle.rs +++ /dev/null @@ -1,86 +0,0 @@ -use litellm_cache::{ - CacheCodec, CacheConnectionResult, CacheConnectionStatus, ClientInfoCache, ConnectionCache, - DisconnectCache, Error, PingCache, -}; - -use crate::{cache::RedisCache, topology::RedisTopology}; - -impl PingCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - fn sync_ping(&self) -> Result { - self.execute(|connection| connection.ping().map_err(Error::unavailable)) - } - - async fn ping(&self) -> Result { - self.run(|connection| connection.ping().map_err(Error::unavailable)) - .await - } -} - -impl ConnectionCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - /// Python `RedisCache.test_connection`, or `RedisClusterCache.test_connection` for a - /// cluster topology, which differs only in its messages. - async fn test_connection(&self) -> Result { - let label = match self.topology { - RedisTopology::Standalone => "Redis", - RedisTopology::Cluster { .. } => "Redis Cluster", - }; - let ping = self - .run(|connection| Ok(connection.ping().map_err(Error::unavailable))) - .await - .and_then(|ping| ping) - .map_err(|error| litellm_error::Report::new(&error).to_string()); - Ok(match ping { - Ok(true) => CacheConnectionResult { - status: CacheConnectionStatus::Success, - message: format!("{label} connection test successful"), - error: None, - }, - Ok(false) => CacheConnectionResult { - status: CacheConnectionStatus::Failed, - message: format!("{label} ping returned False"), - error: None, - }, - Err(error) => CacheConnectionResult { - status: CacheConnectionStatus::Failed, - message: format!("{label} connection failed: {error}"), - error: Some(error), - }, - }) - } -} - -impl DisconnectCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - async fn disconnect(&self) -> Result<(), Error> { - self.connections.disconnect(); - Ok(()) - } -} - -impl ClientInfoCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - type ClientList = String; - type Info = String; - - fn client_list(&self) -> Result { - self.execute(|connection| connection.node_text(redis::cmd("CLIENT").arg("LIST"))) - } - - fn info(&self) -> Result { - self.execute(|connection| connection.node_text(&redis::cmd("INFO"))) - } -} diff --git a/litellm-rust/crates/cache-redis/src/queue.rs b/litellm-rust/crates/cache-redis/src/queue.rs deleted file mode 100644 index d55e4f49187..00000000000 --- a/litellm-rust/crates/cache-redis/src/queue.rs +++ /dev/null @@ -1,226 +0,0 @@ -use std::time::Duration; - -use litellm_cache::{CacheCodec, Error, PopOperation, PushOperation, QueueCache, SetCache}; - -use crate::{cache::RedisCache, script::RedisArg}; - -pub type RedisRpushOperation = PushOperation; -pub type RedisLpopOperation = PopOperation; - -#[derive(Clone, Debug, PartialEq, Eq)] -pub enum RedisLpopResult { - Missing, - Value(Vec), - Values(Vec>), -} - -impl SetCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - type SetValue = RedisArg; - type SetResult = usize; - - async fn async_set_cache_sadd( - &self, - key: &str, - values: Vec, - ttl: Option, - ) -> Result { - if values.is_empty() { - return Err(Error::InvalidEntry(None)); - } - let key = self.namespaced_key(key); - let ttl = self.ttl_or_default(ttl); - let mut pipeline = redis::pipe(); - pipeline - .cmd("SADD") - .arg(&key) - .arg(values) - .cmd("EXPIRE") - .arg(&key) - .arg(ttl) - .ignore(); - self.run(move |connection| connection.query_pipeline(&pipeline)) - .await - .map(|(added,)| added) - } -} - -impl QueueCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - type QueueValue = RedisArg; - type PopResult = RedisLpopResult; - - async fn async_rpush(&self, key: &str, values: Vec) -> Result { - if values.is_empty() { - return Err(Error::InvalidEntry(None)); - } - let key = self.namespaced_key(key); - self.run(move |connection| { - redis::cmd("RPUSH") - .arg(key) - .arg(values) - .query(connection) - .map_err(Error::unavailable) - }) - .await - } - - async fn async_rpush_and_trim( - &self, - key: &str, - values: Vec, - max_len: usize, - ) -> Result { - if values.is_empty() { - return Err(Error::InvalidEntry(None)); - } - let key = self.namespaced_key(key); - let start = i64::try_from(max_len).map_or(i64::MIN, |max_len| -max_len); - let mut pipeline = redis::pipe(); - pipeline - .atomic() - .cmd("RPUSH") - .arg(&key) - .arg(values) - .cmd("LTRIM") - .arg(&key) - .arg(start) - .arg(-1) - .ignore(); - self.run(move |connection| connection.query_pipeline(&pipeline)) - .await - .map(|(length,)| length) - } - - async fn async_rpush_pipeline( - &self, - operations: Vec, - ) -> Result, Error> { - if operations.is_empty() { - return Ok(Vec::new()); - } - let mut pipeline = redis::pipe(); - for operation in operations { - if operation.values.is_empty() { - return Err(Error::InvalidEntry(None)); - } - pipeline - .cmd("RPUSH") - .arg(self.namespaced_key(&operation.key)) - .arg(operation.values); - } - self.run(move |connection| connection.query_pipeline(&pipeline)) - .await - } - - async fn async_lpop(&self, key: &str, count: Option) -> Result { - if let Some(count) = count - && self.major_version().await < 7 - { - return self.lpop_one_at_a_time(key, count).await; - } - let command = lpop(self.namespaced_key(key), count); - let value = self - .run(move |connection| { - command - .query::(connection) - .map_err(Error::unavailable) - }) - .await?; - lpop_result(value, count.is_some()) - } - - async fn async_lpop_pipeline( - &self, - operations: Vec, - ) -> Result, Error> { - if operations.is_empty() { - return Ok(Vec::new()); - } - if operations.iter().any(|operation| operation.count.is_some()) - && self.major_version().await < 7 - { - let mut results = Vec::with_capacity(operations.len()); - for operation in &operations { - results.push(self.async_lpop(&operation.key, operation.count).await?); - } - return Ok(results); - } - let multiple = operations - .iter() - .map(|operation| operation.count.is_some()) - .collect::>(); - let mut pipeline = redis::pipe(); - for operation in operations { - pipeline.add_command(lpop(self.namespaced_key(&operation.key), operation.count)); - } - self.run(move |connection| connection.query_pipeline::>(&pipeline)) - .await? - .into_iter() - .zip(multiple) - .map(|(value, multiple)| lpop_result(value, multiple)) - .collect() - } -} - -fn lpop(key: String, count: Option) -> redis::Cmd { - let mut command = redis::cmd("LPOP"); - command.arg(key); - if let Some(count) = count { - command.arg(count); - } - command -} - -fn redis_bytes(value: redis::Value) -> Result, Error> { - match value { - redis::Value::BulkString(bytes) => Ok(bytes), - redis::Value::SimpleString(text) => Ok(text.into_bytes()), - _ => Err(Error::InvalidEntry(None)), - } -} - -impl RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - /// `handle_lpop_count_for_older_redis_versions`: `count` single-`LPOP` pipelines, keeping - /// only the values actually popped. - async fn lpop_one_at_a_time(&self, key: &str, count: usize) -> Result { - let key = self.namespaced_key(key); - let mut values = Vec::new(); - for _ in 0..count { - let mut pipeline = redis::pipe(); - pipeline.add_command(lpop(key.clone(), None)); - let replies = self - .run(move |connection| connection.query_pipeline::>(&pipeline)) - .await?; - for reply in replies { - if reply != redis::Value::Nil { - values.push(redis_bytes(reply)?); - } - } - } - Ok(RedisLpopResult::Values(values)) - } -} - -fn lpop_result(value: redis::Value, multiple: bool) -> Result { - match value { - redis::Value::Nil => Ok(RedisLpopResult::Missing), - redis::Value::Array(values) if multiple => values - .into_iter() - .map(redis_bytes) - .collect::, _>>() - .map(RedisLpopResult::Values), - value if !multiple => redis_bytes(value).map(RedisLpopResult::Value), - _ => Err(Error::InvalidEntry(None)), - } -} diff --git a/litellm-rust/crates/cache-redis/src/script.rs b/litellm-rust/crates/cache-redis/src/script.rs deleted file mode 100644 index 09987437ed4..00000000000 --- a/litellm-rust/crates/cache-redis/src/script.rs +++ /dev/null @@ -1,136 +0,0 @@ -use std::sync::Arc; - -use litellm_cache::{CacheCodec, CacheScript, Error, ScriptCache}; - -use crate::{ - cache::{RedisCache, namespaced_key}, - connection::Connections, -}; - -#[derive(Clone, Debug, PartialEq)] -pub enum RedisArg { - Bytes(Vec), - Integer(i64), - Float(f64), -} - -impl From<&str> for RedisArg { - fn from(value: &str) -> Self { - Self::Bytes(value.as_bytes().to_vec()) - } -} - -impl From for RedisArg { - fn from(value: String) -> Self { - Self::Bytes(value.into_bytes()) - } -} - -impl From> for RedisArg { - fn from(value: Vec) -> Self { - Self::Bytes(value) - } -} - -impl From for RedisArg { - fn from(value: i64) -> Self { - Self::Integer(value) - } -} - -impl From for RedisArg { - fn from(value: f64) -> Self { - Self::Float(value) - } -} - -impl redis::ToRedisArgs for RedisArg { - fn write_redis_args(&self, out: &mut W) - where - W: ?Sized + redis::RedisWrite, - { - match self { - Self::Bytes(value) => value.write_redis_args(out), - Self::Integer(value) => value.write_redis_args(out), - Self::Float(value) => value.write_redis_args(out), - } - } -} - -pub struct RedisScript { - connections: Arc>, - namespace: Option, - source: String, -} - -impl CacheScript for RedisScript -where - C: redis::ConnectionLike + Send + 'static, -{ - type Argument = RedisArg; - type Output = redis::Value; - - async fn invoke( - &self, - keys: Vec, - arguments: Vec, - ) -> Result { - let keys = keys - .into_iter() - .map(|key| namespaced_key(self.namespace.as_deref(), &key)) - .collect::>(); - let source = self.source.clone(); - Connections::run_blocking(Arc::clone(&self.connections), move |connection| { - eval(connection, &source, keys, arguments) - }) - .await - } -} - -impl RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - pub async fn async_eval( - &self, - script: String, - keys: Vec, - arguments: Vec, - ) -> Result { - let keys = self.namespaced_keys(&keys); - self.run(move |connection| eval(connection, &script, keys, arguments)) - .await - } -} - -fn eval( - connection: &mut impl redis::ConnectionLike, - script: &str, - keys: Vec, - arguments: Vec, -) -> Result { - redis::cmd("EVAL") - .arg(script) - .arg(keys.len()) - .arg(keys) - .arg(arguments) - .query(connection) - .map_err(Error::unavailable) -} - -impl ScriptCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - type Script = RedisScript; - - fn async_register_script(&self, source: String) -> Self::Script { - RedisScript { - connections: Arc::clone(&self.connections), - namespace: self.namespace.clone(), - source, - } - } -} diff --git a/litellm-rust/crates/cache-redis/src/store.rs b/litellm-rust/crates/cache-redis/src/store.rs deleted file mode 100644 index daadc940ca9..00000000000 --- a/litellm-rust/crates/cache-redis/src/store.rs +++ /dev/null @@ -1,232 +0,0 @@ -use std::time::Duration; - -use litellm_cache::{ - BaseCache, BatchCache, BatchEntry, BulkDeleteCache, CacheCodec, DeleteCache, Error, - ExactCacheContext, FlushAllCache, FlushCache, TtlPipelineCache, -}; -use redis::Commands; - -use crate::{cache::RedisCache, connection::ConnectionRef}; - -impl BaseCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - type Value = S::Value; - type Context = ExactCacheContext; - - fn get_ttl(&self, context: &Self::Context) -> Option { - context.ttl.or(Some(self.default_ttl)) - } - - fn set_cache( - &self, - key: &str, - value: Self::Value, - context: &ExactCacheContext, - ) -> Result<(), Error> { - let payload = self.codec.encode(&value)?; - let ttl = self.ttl_or_default(context.ttl); - let key = self.namespaced_key(key); - self.execute(|connection| { - connection - .set_ex::<_, _, ()>(key, payload, ttl) - .map_err(Error::unavailable) - }) - } - - fn get_cache(&self, key: &str, _: &ExactCacheContext) -> Result, Error> { - let key = self.namespaced_key(key); - let value = self.execute(|connection| { - connection - .get::<_, redis::Value>(key) - .map_err(Error::unavailable) - })?; - self.decode_response(value) - } - - async fn async_set_cache( - &self, - key: &str, - value: Self::Value, - context: ExactCacheContext, - ) -> Result<(), Error> { - let payload = self.codec.encode(&value)?; - let key = self.namespaced_key(key); - let ttl = self.ttl_or_default(context.ttl); - self.run(move |connection| { - connection - .set_ex::<_, _, ()>(key, payload, ttl) - .map_err(Error::unavailable) - }) - .await - } - - async fn async_get_cache( - &self, - key: &str, - _: &ExactCacheContext, - ) -> Result, Error> { - let key = self.namespaced_key(key); - let value = self - .run(move |connection| { - connection - .get::<_, redis::Value>(key) - .map_err(Error::unavailable) - }) - .await?; - self.decode_response(value) - } - - async fn async_set_cache_pipeline( - &self, - cache_list: Vec<(String, Self::Value)>, - context: ExactCacheContext, - ) -> Result<(), Error> { - self.async_set_cache_pipeline_with_ttls( - cache_list - .into_iter() - .map(|(key, value)| (key, value, context.ttl)) - .collect(), - ) - .await - } -} - -impl TtlPipelineCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - async fn async_set_cache_pipeline_with_ttls( - &self, - entries: Vec<(String, Self::Value, Option)>, - ) -> Result<(), Error> { - if entries.is_empty() { - return Ok(()); - } - let mut pipeline = redis::pipe(); - for (key, value, ttl) in entries { - pipeline - .cmd("SETEX") - .arg(self.namespaced_key(&key)) - .arg(self.ttl_or_default(ttl)) - .arg(self.codec.encode(&value)?) - .ignore(); - } - self.run(move |connection| connection.query_pipeline(&pipeline)) - .await - } -} - -impl BatchCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - fn batch_get_cache( - &self, - keys: &[String], - _: &ExactCacheContext, - ) -> Result>, Error> { - let keys = self.namespaced_keys(keys); - self.execute(|connection| mget(connection, keys))? - .into_iter() - .map(|value| self.decode_batch_response(value)) - .collect() - } - - async fn async_batch_get_cache( - &self, - keys: Vec, - _: ExactCacheContext, - ) -> Result>, Error> { - let keys = self.namespaced_keys(&keys); - self.run(move |connection| mget(connection, keys)) - .await? - .into_iter() - .map(|value| self.decode_batch_response(value)) - .collect() - } -} - -pub(crate) fn mget( - connection: &mut ConnectionRef<'_>, - keys: Vec, -) -> Result, Error> { - redis::cmd("MGET") - .arg(keys) - .query(connection) - .map_err(Error::unavailable) -} - -impl DeleteCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - fn delete_cache(&self, key: &str) -> Result<(), Error> { - let key = self.namespaced_key(key); - self.execute(|connection| connection.del::<_, ()>(key).map_err(Error::unavailable)) - } - - async fn async_delete_cache(&self, key: &str) -> Result<(), Error> { - let key = self.namespaced_key(key); - self.run(move |connection| connection.del::<_, ()>(key).map_err(Error::unavailable)) - .await - } -} - -impl BulkDeleteCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - async fn delete_cache_keys(&self, keys: Vec) -> Result { - if keys.is_empty() { - return Ok(0); - } - let keys = self.namespaced_keys(&keys); - self.run(move |connection| connection.del(keys).map_err(Error::unavailable)) - .await - } -} - -impl FlushCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - fn flush_cache(&self) -> Result<(), Error> { - let pattern = self.namespaced_pattern()?; - self.execute(|connection| flush_matching(connection, &pattern)) - } - - async fn async_flush_cache(&self) -> Result<(), Error> { - let pattern = self.namespaced_pattern()?; - self.run(move |connection| flush_matching(connection, &pattern)) - .await - } -} - -impl FlushAllCache for RedisCache -where - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - fn flushall(&self) -> Result<(), Error> { - self.execute(|connection| connection.flushall()) - } -} - -fn flush_matching(connection: &mut ConnectionRef<'_>, pattern: &str) -> Result<(), Error> { - connection.scan(pattern, 1000, |connection, keys| { - if !keys.is_empty() { - connection - .del::<_, usize>(keys) - .map_err(Error::unavailable)?; - } - Ok(true) - }) -} diff --git a/litellm-rust/crates/cache-redis/src/topology.rs b/litellm-rust/crates/cache-redis/src/topology.rs deleted file mode 100644 index 7f4ee48b222..00000000000 --- a/litellm-rust/crates/cache-redis/src/topology.rs +++ /dev/null @@ -1,14 +0,0 @@ -#[derive(Clone, Debug, PartialEq, Eq)] -pub struct RedisNode { - pub host: String, - pub port: u16, -} - -#[derive(Clone, Debug, Default, PartialEq, Eq)] -pub enum RedisTopology { - #[default] - Standalone, - Cluster { - startup_nodes: Vec, - }, -} diff --git a/litellm-rust/crates/cache-redis/tests/cache.rs b/litellm-rust/crates/cache-redis/tests/cache.rs deleted file mode 100644 index 9ec85251733..00000000000 --- a/litellm-rust/crates/cache-redis/tests/cache.rs +++ /dev/null @@ -1,1164 +0,0 @@ -mod support; - -use std::time::Duration; - -use litellm_cache::{ - BaseCache, BatchCache, BatchEntry, BoundedCounterCache, BulkDeleteCache, CacheCodec, - CacheConnectionStatus, CacheScript, ClaimCache, ClientInfoCache, ConnectionCache, - CountReadCache, CounterCache, DeleteCache, DisconnectCache, Error, ExactCacheContext, - FlushAllCache, FlushCache, IncrementOperation, JsonCodec, PingCache, QueueCache, - RefreshTtlCache, ScanCache, ScriptCache, SetCache, TtlCache, TtlPipelineCache, get_cache, - set_cache, -}; -use litellm_cache_redis::{ - RedisArg, RedisCache, RedisLpopOperation, RedisLpopResult, RedisRpushOperation, -}; -use redis_test::{MockCmd, MockRedisConnection}; -use rstest::{fixture, rstest}; -use serde_json::json; -use support::TaggedByteCodec; - -type Mocked = RedisCache; - -fn mock(commands: Vec) -> MockRedisConnection { - MockRedisConnection::new(commands).assert_all_commands_consumed() -} - -fn tagged(commands: Vec) -> Mocked { - RedisCache::with_connection(mock(commands), None, TaggedByteCodec(42)) -} - -fn json_cache(commands: Vec) -> Mocked> { - RedisCache::with_connection(mock(commands), None, JsonCodec::new()) -} - -fn team(commands: Vec) -> Mocked> { - json_cache(commands).with_namespace(Some("team".into())) -} - -#[fixture] -fn context() -> ExactCacheContext { - ExactCacheContext::default() -} - -fn scan(pattern: &str, cursor: u64, count: usize, reply: redis::Value) -> MockCmd { - MockCmd::new( - redis::cmd("SCAN") - .cursor_arg(cursor) - .arg("MATCH") - .arg(pattern) - .arg("COUNT") - .arg(count), - Ok(reply), - ) -} - -#[rstest] -fn constructor_rejects_invalid_urls() { - assert!(RedisCache::new("not a redis url", None, JsonCodec::::new()).is_err()); -} - -#[rstest] -#[case::zero_rounds_up_to_one(Some(Duration::ZERO), 1)] -#[case::fractions_round_up(Some(Duration::from_millis(1500)), 2)] -#[case::whole_seconds_are_kept(Some(Duration::from_secs(15)), 15)] -#[case::missing_ttl_uses_default(None, 600)] -fn writes_round_ttls_up_to_positive_seconds(#[case] ttl: Option, #[case] seconds: u64) { - let cache = tagged(vec![MockCmd::new( - redis::cmd("SETEX") - .arg("key") - .arg(seconds) - .arg([42u8, 7].as_slice()), - Ok("OK"), - )]); - cache - .set_cache("key", 7, &ExactCacheContext { ttl }) - .unwrap(); -} - -#[rstest] -fn generic_helpers_use_the_injected_codec_and_ttl() { - let cache = tagged(vec![ - MockCmd::new( - redis::cmd("SETEX") - .arg("counter") - .arg(2) - .arg([42u8, 7].as_slice()), - Ok("OK"), - ), - MockCmd::new(redis::cmd("GET").arg("counter"), Ok(vec![42u8, 7])), - ]); - let context = ExactCacheContext { - ttl: Some(Duration::from_millis(1500)), - }; - set_cache(&cache, "counter", 7, &context).unwrap(); - assert_eq!(get_cache(&cache, "counter", &context).unwrap(), Some(7)); -} - -#[rstest] -fn commands_round_trip_entries_and_delete_only_namespaced_keys(context: ExactCacheContext) { - let value = json!({"deployment": "model-a", "cooldown_seconds": 30}); - let payload = JsonCodec::::new() - .encode(&value) - .unwrap(); - let cache = json_cache(vec![ - MockCmd::new( - redis::cmd("SETEX") - .arg("litellm-cache:key") - .arg(600) - .arg(payload.clone()), - Ok("OK"), - ), - MockCmd::new(redis::cmd("GET").arg("litellm-cache:key"), Ok(payload)), - MockCmd::new(redis::cmd("DEL").arg("litellm-cache:key"), Ok(1u32)), - ]) - .with_namespace(Some("litellm-cache".into())); - - cache.set_cache("key", value.clone(), &context).unwrap(); - assert_eq!(cache.get_cache("key", &context).unwrap(), Some(value)); - cache.delete_cache("key").unwrap(); -} - -#[rstest] -#[tokio::test] -async fn async_operations_preserve_codec_ttl_and_missing_values(context: ExactCacheContext) { - let cache = RedisCache::with_connection( - mock(vec![ - MockCmd::new( - redis::cmd("SETEX") - .arg("counter") - .arg(9) - .arg([42u8, 7].as_slice()), - Ok("OK"), - ), - MockCmd::new(redis::cmd("GET").arg("counter"), Ok(vec![42u8, 7])), - MockCmd::new( - redis::cmd("SETEX") - .arg("batch") - .arg(2) - .arg([42u8, 8].as_slice()), - Ok("OK"), - ), - MockCmd::new(redis::cmd("DEL").arg("counter"), Ok(1u32)), - MockCmd::new(redis::cmd("GET").arg("counter"), Ok(redis::Value::Nil)), - ]), - Some(Duration::from_secs(9)), - TaggedByteCodec(42), - ); - cache - .batch_cache_write("counter", 7, context.clone()) - .await - .unwrap(); - assert_eq!( - cache.async_get_cache("counter", &context).await.unwrap(), - Some(7) - ); - cache - .async_set_cache_pipeline( - vec![("batch".into(), 8)], - ExactCacheContext { - ttl: Some(Duration::from_millis(1500)), - }, - ) - .await - .unwrap(); - cache.async_delete_cache("counter").await.unwrap(); - assert_eq!( - cache.async_get_cache("counter", &context).await.unwrap(), - None - ); -} - -#[rstest] -#[tokio::test] -async fn codec_errors_propagate_without_writing_partial_batches(context: ExactCacheContext) { - let cache = tagged(vec![ - MockCmd::new(redis::cmd("GET").arg("invalid"), Ok(vec![99u8, 7])), - MockCmd::new(redis::cmd("GET").arg("invalid"), Ok(vec![99u8, 7])), - ]); - assert_eq!( - cache.set_cache("invalid", 255, &context), - Err(Error::InvalidEntry(None)) - ); - assert_eq!( - cache.async_set_cache("invalid", 255, context.clone()).await, - Err(Error::InvalidEntry(None)) - ); - assert_eq!( - cache - .async_set_cache_pipeline( - vec![("valid".into(), 7), ("invalid".into(), 255)], - context.clone(), - ) - .await, - Err(Error::InvalidEntry(None)) - ); - assert_eq!( - cache - .async_set_cache_pipeline_with_ttls(vec![ - ("valid".into(), 7, None), - ("invalid".into(), 255, None), - ]) - .await, - Err(Error::InvalidEntry(None)) - ); - assert_eq!( - cache.get_cache("invalid", &context), - Err(Error::InvalidEntry(None)) - ); - assert_eq!( - cache.async_get_cache("invalid", &context).await, - Err(Error::InvalidEntry(None)) - ); -} - -#[rstest] -#[case::bare_key("key")] -#[case::already_prefixed("team:key")] -fn namespaces_are_added_once(#[case] key: &str, context: ExactCacheContext) { - let cache = team(vec![MockCmd::new( - redis::cmd("GET").arg("team:key"), - Ok(redis::Value::Nil), - )]); - assert_eq!(cache.get_cache(key, &context).unwrap(), None); -} - -#[rstest] -#[case::empty(Some(String::new()))] -#[case::missing(None)] -fn empty_namespaces_leave_keys_unprefixed( - #[case] namespace: Option, - context: ExactCacheContext, -) { - let cache = json_cache(vec![MockCmd::new( - redis::cmd("GET").arg("key"), - Ok(redis::Value::Nil), - )]) - .with_namespace(namespace); - assert_eq!(cache.namespace(), None); - assert_eq!(cache.get_cache("key", &context).unwrap(), None); -} - -#[rstest] -#[tokio::test] -async fn flush_requires_a_namespace() { - let unscoped = json_cache(Vec::new()); - assert_eq!(unscoped.flush_cache(), Err(Error::UnscopedFlush)); - assert_eq!( - unscoped.async_flush_cache().await, - Err(Error::UnscopedFlush) - ); -} - -#[rstest] -#[case::plain_namespace("litellm-cache", "litellm-cache:*", "litellm-cache:key")] -#[case::glob_metacharacters_are_escaped("team*", "team\\*:*", "team*:key")] -fn flush_scans_and_deletes_only_namespaced_keys( - #[case] namespace: &str, - #[case] pattern: &str, - #[case] key: &str, -) { - let cache = json_cache(vec![ - scan(pattern, 0, 1000, redis_test::redis_value!(["0", [key]])), - MockCmd::new(redis::cmd("DEL").arg(key), Ok(1u32)), - ]) - .with_namespace(Some(namespace.into())); - cache.flush_cache().unwrap(); -} - -#[rstest] -#[tokio::test] -async fn async_flush_deletes_each_scan_page_separately() { - let cache = team(vec![ - scan( - "team:*", - 0, - 1000, - redis_test::redis_value!(["7", ["team:a", "team:b"]]), - ), - MockCmd::new(redis::cmd("DEL").arg("team:a").arg("team:b"), Ok(2u32)), - scan( - "team:*", - 7, - 1000, - redis_test::redis_value!(["0", ["team:c"]]), - ), - MockCmd::new(redis::cmd("DEL").arg("team:c"), Ok(1u32)), - ]); - cache.async_flush_cache().await.unwrap(); -} - -#[rstest] -fn flushall_ignores_the_namespace() { - team(vec![MockCmd::new(redis::cmd("FLUSHALL"), Ok("OK"))]) - .flushall() - .unwrap(); -} - -#[rstest] -#[tokio::test] -async fn batch_reads_keep_order_and_treat_invalid_values_as_invalid_entries( - context: ExactCacheContext, -) { - let cache = tagged(vec![MockCmd::new( - redis::cmd("MGET").arg("hit").arg("miss").arg("invalid"), - Ok(vec![ - redis::Value::BulkString(vec![42, 7]), - redis::Value::Nil, - redis::Value::BulkString(vec![99, 7]), - ]), - )]); - - assert_eq!( - cache - .async_batch_get_cache(vec!["hit".into(), "miss".into(), "invalid".into()], context) - .await - .unwrap(), - vec![BatchEntry::Hit(7), BatchEntry::Miss, BatchEntry::Invalid] - ); -} - -#[rstest] -#[tokio::test] -async fn ttl_pipeline_keeps_each_entry_ttl_and_defaults_missing_ones() { - let mut pipeline = redis::pipe(); - pipeline - .cmd("SETEX") - .arg("ns:team_id:t1") - .arg(60u64) - .arg(r#"{"team_id":"t1"}"#) - .cmd("SETEX") - .arg("ns:u1") - .arg(7u64) - .arg(r#"{"user_id":"u1"}"#) - .cmd("SETEX") - .arg("ns:org_id:o1") - .arg(300u64) - .arg(r#"{"a":1}"#); - let cache = RedisCache::with_connection( - mock(vec![MockCmd::with_values( - pipeline, - Ok(vec!["OK", "OK", "OK"]), - )]), - Some(Duration::from_secs(300)), - JsonCodec::::new(), - ) - .with_namespace(Some("ns".into())); - - cache - .async_set_cache_pipeline_with_ttls(vec![ - ( - "team_id:t1".into(), - json!({"team_id": "t1"}), - Some(Duration::from_secs(60)), - ), - ( - "u1".into(), - json!({"user_id": "u1"}), - Some(Duration::from_secs(7)), - ), - ("org_id:o1".into(), json!({"a": 1}), None), - ]) - .await - .unwrap(); -} - -#[rstest] -#[tokio::test] -async fn empty_pipelines_skip_the_round_trip(context: ExactCacheContext) { - let cache = json_cache(Vec::new()); - cache - .async_set_cache_pipeline(Vec::new(), context) - .await - .unwrap(); - cache - .async_set_cache_pipeline_with_ttls(Vec::new()) - .await - .unwrap(); - assert_eq!(cache.delete_cache_keys(Vec::new()).await.unwrap(), 0); - assert_eq!( - cache.async_rpush_pipeline(Vec::new()).await.unwrap(), - Vec::::new() - ); - assert_eq!( - cache.async_lpop_pipeline(Vec::new()).await.unwrap(), - Vec::::new() - ); - assert_eq!( - cache.async_increment_pipeline(Vec::new()).await.unwrap(), - Vec::::new() - ); -} - -#[rstest] -#[tokio::test] -async fn count_reads_parse_integers_and_keep_missing_counters() { - let mget = || { - MockCmd::new( - redis::cmd("MGET").arg("team:count").arg("team:missing"), - Ok(redis_test::redis_value!(["7", nil])), - ) - }; - let cache = team(vec![mget(), mget()]); - let keys = vec!["count".to_string(), "missing".to_string()]; - - assert_eq!(cache.batch_get_counts(&keys).unwrap(), [Some(7), None]); - assert_eq!( - cache.async_batch_get_counts(keys).await.unwrap(), - [Some(7), None] - ); -} - -#[rstest] -#[tokio::test] -async fn pings_run_on_both_paths() { - let cache = team(vec![ - MockCmd::new(redis::cmd("PING"), Ok("PONG")), - MockCmd::new(redis::cmd("PING"), Ok("PONG")), - ]); - assert!(cache.sync_ping().unwrap()); - assert!(cache.ping().await.unwrap()); -} - -#[rstest] -#[case::remaining(12, Some(Duration::from_secs(12)))] -#[case::no_expiry(-1, None)] -#[case::missing(-2, None)] -#[tokio::test] -async fn ttl_reads_hide_negative_replies(#[case] reply: i64, #[case] ttl: Option) { - let cache = team(vec![MockCmd::new( - redis::cmd("TTL").arg("team:key"), - Ok(reply), - )]); - assert_eq!(cache.async_get_ttl("key").await.unwrap(), ttl); -} - -#[rstest] -#[case::explicit_ttl(Some(Duration::from_secs(30)), 30, 1, true)] -#[case::default_ttl(None, 600, 1, true)] -#[case::missing_key(Some(Duration::from_secs(30)), 30, 0, false)] -#[tokio::test] -async fn refresh_ttl_expires_existing_keys_only( - #[case] ttl: Option, - #[case] seconds: u64, - #[case] reply: i64, - #[case] refreshed: bool, -) { - let cache = team(vec![MockCmd::new( - redis::cmd("EXPIRE").arg("team:key").arg(seconds), - Ok(reply), - )]); - assert_eq!( - cache.async_refresh_ttl("key", ttl).await.unwrap(), - refreshed - ); -} - -#[rstest] -#[tokio::test] -async fn scan_stops_at_count_and_bulk_delete_reports_existing_keys() { - let cache = team(vec![ - scan( - "team:job-*", - 0, - 25, - redis_test::redis_value!(["4", ["team:job-a"]]), - ), - scan( - "team:job-*", - 4, - 25, - redis_test::redis_value!(["0", ["team:job-b"]]), - ), - MockCmd::new( - redis::cmd("DEL").arg("team:job-a").arg("team:job-b"), - Ok(2u32), - ), - ]); - assert_eq!( - cache.async_scan_iter("job-", 25).await.unwrap(), - ["team:job-a", "team:job-b"] - ); - assert_eq!( - cache - .delete_cache_keys(vec!["job-a".into(), "job-b".into()]) - .await - .unwrap(), - 2 - ); -} - -#[rstest] -#[tokio::test] -async fn sets_add_members_and_arm_the_default_ttl() { - let mut pipeline = redis::pipe(); - pipeline - .cmd("SADD") - .arg("team:members") - .arg("a") - .arg("b") - .cmd("EXPIRE") - .arg("team:members") - .arg(600u64) - .ignore(); - let cache = team(vec![MockCmd::with_values( - pipeline, - Ok(vec![redis::Value::Int(2), redis::Value::Int(1)]), - )]); - assert_eq!( - cache - .async_set_cache_sadd("members", vec!["a".into(), "b".into()], None) - .await - .unwrap(), - 2 - ); - assert_eq!( - cache - .async_set_cache_sadd("members", Vec::new(), None) - .await, - Err(Error::InvalidEntry(None)) - ); -} - -#[rstest] -#[tokio::test] -async fn queues_push_and_pop_namespaced_lists() { - let cache = team(vec![ - MockCmd::new( - redis::cmd("RPUSH").arg("team:queue").arg("a").arg("b"), - Ok(2u32), - ), - MockCmd::new( - redis::cmd("INFO"), - Ok("# Server\r\nredis_version:7.2.4\r\n"), - ), - MockCmd::new( - redis::cmd("LPOP").arg("team:queue").arg(2usize), - Ok(redis_test::redis_value!(["a", "b"])), - ), - MockCmd::new(redis::cmd("LPOP").arg("team:queue"), Ok("c")), - ]); - assert_eq!( - cache - .async_rpush("queue", vec!["a".into(), "b".into()]) - .await - .unwrap(), - 2 - ); - assert_eq!( - cache.async_rpush("queue", Vec::new()).await, - Err(Error::InvalidEntry(None)) - ); - assert_eq!( - cache.async_lpop("queue", Some(2)).await.unwrap(), - RedisLpopResult::Values(vec![b"a".to_vec(), b"b".to_vec()]) - ); - assert_eq!( - cache.async_lpop("queue", None).await.unwrap(), - RedisLpopResult::Value(b"c".to_vec()) - ); -} - -/// Python `RedisCache.async_lpop` checks `redis_version` from `INFO` and, below major version 7, -/// pops a counted batch as `count` single-command `LPOP` pipelines, dropping `None` replies. -#[rstest] -#[tokio::test] -async fn counted_lpop_falls_back_to_single_pops_below_redis_7() { - let single_pop = || { - let mut pipeline = redis::pipe(); - pipeline.cmd("LPOP").arg("team:queue"); - pipeline - }; - let cache = team(vec![ - MockCmd::new( - redis::cmd("INFO"), - Ok("# Server\r\nredis_version:6.2.14\r\n"), - ), - MockCmd::with_values(single_pop(), Ok(vec![redis_test::redis_value!("a")])), - MockCmd::with_values(single_pop(), Ok(vec![redis_test::redis_value!("b")])), - MockCmd::with_values(single_pop(), Ok(vec![redis::Value::Nil])), - ]); - - assert_eq!( - cache.async_lpop("queue", Some(3)).await.unwrap(), - RedisLpopResult::Values(vec![b"a".to_vec(), b"b".to_vec()]) - ); -} - -/// Python keeps `redis_version = "Unknown"` when `INFO` fails and then assumes -/// `DEFAULT_REDIS_MAJOR_VERSION` (7), so a counted pop is one `LPOP key count`. The version is read -/// once: the second pop sends no second `INFO`. -#[rstest] -#[tokio::test] -async fn counted_lpop_assumes_redis_7_when_info_fails() { - let cache = team(vec![ - MockCmd::new( - redis::cmd("INFO"), - Err::(redis::RedisError::from((redis::ErrorKind::Io, "down"))), - ), - MockCmd::new( - redis::cmd("LPOP").arg("team:queue").arg(2usize), - Ok(redis_test::redis_value!(["a", "b"])), - ), - MockCmd::new( - redis::cmd("LPOP").arg("team:queue").arg(1usize), - Ok(redis_test::redis_value!(["c"])), - ), - ]); - - assert_eq!( - cache.async_lpop("queue", Some(2)).await.unwrap(), - RedisLpopResult::Values(vec![b"a".to_vec(), b"b".to_vec()]) - ); - assert_eq!( - cache.async_lpop("queue", Some(1)).await.unwrap(), - RedisLpopResult::Values(vec![b"c".to_vec()]) - ); -} - -fn push_and_trim(start: i64) -> redis::Pipeline { - let mut pipeline = redis::pipe(); - pipeline - .atomic() - .cmd("RPUSH") - .arg("ns:buf") - .arg("c") - .arg("d") - .cmd("LTRIM") - .arg("ns:buf") - .arg(start) - .arg(-1); - pipeline -} - -#[rstest] -#[case::keeps_newest_entries(3, -3)] -#[case::zero_keeps_everything(0, 0)] -#[tokio::test] -async fn rpush_and_trim_runs_push_and_trim_in_one_transaction( - #[case] max_len: usize, - #[case] start: i64, -) { - let cache = json_cache(vec![MockCmd::with_values( - push_and_trim(start), - Ok(vec![redis::Value::Array(vec![ - redis::Value::Int(4), - redis::Value::Okay, - ])]), - )]) - .with_namespace(Some("ns".into())); - - assert_eq!( - cache - .async_rpush_and_trim("buf", vec!["c".into(), "d".into()], max_len) - .await - .unwrap(), - 4 - ); -} - -#[rstest] -#[tokio::test] -async fn rpush_and_trim_raises_when_a_queued_command_fails() { - let wrong_type = redis::parse_redis_value( - b"-WRONGTYPE Operation against a key holding the wrong kind of value\r\n", - ) - .unwrap(); - let cache = json_cache(vec![MockCmd::with_values( - push_and_trim(-3), - Ok(vec![redis::Value::Array(vec![ - wrong_type, - redis::Value::Okay, - ])]), - )]) - .with_namespace(Some("ns".into())); - - assert!(matches!( - cache - .async_rpush_and_trim("buf", vec!["c".into(), "d".into()], 3) - .await, - Err(Error::Unavailable(Some(_))) - )); - assert_eq!( - cache.async_rpush_and_trim("buf", Vec::new(), 3).await, - Err(Error::InvalidEntry(None)) - ); -} - -#[rstest] -#[tokio::test] -async fn scripts_and_eval_namespace_their_keys() { - let eval = || { - MockCmd::new( - redis::cmd("EVAL") - .arg("return KEYS[1]") - .arg(1usize) - .arg("team:key"), - Ok("team:key"), - ) - }; - let cache = team(vec![eval(), eval()]); - assert_eq!( - cache - .async_eval("return KEYS[1]".into(), vec!["key".into()], Vec::new()) - .await - .unwrap(), - redis::Value::BulkString(b"team:key".to_vec()) - ); - assert_eq!( - cache - .async_register_script("return KEYS[1]".into()) - .invoke(vec!["key".into()], Vec::new()) - .await - .unwrap(), - redis::Value::BulkString(b"team:key".to_vec()) - ); -} - -#[rstest] -fn client_list_and_info_return_server_text() { - let cache = team(vec![ - MockCmd::new(redis::cmd("CLIENT").arg("LIST"), Ok("id=1")), - MockCmd::new(redis::cmd("INFO"), Ok("redis_version:7")), - ]); - assert_eq!(cache.client_list().unwrap(), "id=1"); - assert_eq!(cache.info().unwrap(), "redis_version:7"); -} - -#[rstest] -#[tokio::test] -async fn pipelines_preserve_operation_order() { - let mut rpush_pipeline = redis::pipe(); - rpush_pipeline - .cmd("RPUSH") - .arg("team:a") - .arg("one") - .cmd("RPUSH") - .arg("team:b") - .arg("two"); - let mut lpop_pipeline = redis::pipe(); - lpop_pipeline - .cmd("LPOP") - .arg("team:a") - .arg(2usize) - .cmd("LPOP") - .arg("team:b"); - let queue = team(vec![ - MockCmd::with_values( - rpush_pipeline, - Ok(vec![redis::Value::Int(1), redis::Value::Int(2)]), - ), - MockCmd::new( - redis::cmd("INFO"), - Ok("# Server\r\nredis_version:7.2.4\r\n"), - ), - MockCmd::with_values( - lpop_pipeline, - Ok(vec![redis_test::redis_value!(["one"]), redis::Value::Nil]), - ), - ]); - - assert_eq!( - queue - .async_rpush_pipeline(vec![ - RedisRpushOperation { - key: "a".into(), - values: vec![RedisArg::from("one")], - }, - RedisRpushOperation { - key: "b".into(), - values: vec![RedisArg::from("two")], - }, - ]) - .await - .unwrap(), - [1, 2] - ); - assert_eq!( - queue - .async_lpop_pipeline(vec![ - RedisLpopOperation { - key: "a".into(), - count: Some(2), - }, - RedisLpopOperation { - key: "b".into(), - count: None, - }, - ]) - .await - .unwrap(), - [ - RedisLpopResult::Values(vec![b"one".to_vec()]), - RedisLpopResult::Missing, - ] - ); -} - -/// Below major version 7 a counted `LPOP` is unsupported, so a pipeline that mixes counted and -/// plain pops runs each operation through `async_lpop`: `count` single-`LPOP` pipelines for the -/// counted ones, a bare `LPOP` for the rest. No `LPOP key count` reaches the connection. -#[rstest] -#[tokio::test] -async fn lpop_pipeline_pops_one_at_a_time_below_redis_7() { - let single_pop = |key: &str| { - let mut pipeline = redis::pipe(); - pipeline.cmd("LPOP").arg(key); - pipeline - }; - let cache = team(vec![ - MockCmd::new( - redis::cmd("INFO"), - Ok("# Server\r\nredis_version:6.2.14\r\n"), - ), - MockCmd::with_values( - single_pop("team:a"), - Ok(vec![redis_test::redis_value!("one")]), - ), - MockCmd::with_values( - single_pop("team:a"), - Ok(vec![redis_test::redis_value!("two")]), - ), - MockCmd::new(redis::cmd("LPOP").arg("team:b"), Ok(redis::Value::Nil)), - ]); - - assert_eq!( - cache - .async_lpop_pipeline(vec![ - RedisLpopOperation { - key: "a".into(), - count: Some(2), - }, - RedisLpopOperation { - key: "b".into(), - count: None, - }, - ]) - .await - .unwrap(), - [ - RedisLpopResult::Values(vec![b"one".to_vec(), b"two".to_vec()]), - RedisLpopResult::Missing, - ] - ); -} - -#[rstest] -#[tokio::test] -async fn increment_pipeline_expires_only_operations_with_a_ttl() { - let mut increment_pipeline = redis::pipe(); - increment_pipeline - .cmd("INCRBYFLOAT") - .arg("team:counter") - .arg(1.5f64) - .cmd("EXPIRE") - .arg("team:counter") - .arg(10u64) - .ignore() - .cmd("INCRBYFLOAT") - .arg("team:counter") - .arg(2.0f64); - let counters = team(vec![MockCmd::with_values( - increment_pipeline, - Ok(vec![ - redis::Value::BulkString(b"1.5".to_vec()), - redis::Value::Int(1), - redis::Value::BulkString(b"3.5".to_vec()), - ]), - )]); - assert_eq!( - counters - .async_increment_pipeline(vec![ - IncrementOperation { - key: "counter".into(), - amount: 1.5, - ttl: Some(Duration::from_secs(10)), - }, - IncrementOperation { - key: "counter".into(), - amount: 2.0, - ttl: None, - }, - ]) - .await - .unwrap(), - [1.5, 3.5] - ); -} - -const INCREMENT_SCRIPT: &str = concat!( - "local value = redis.call('INCRBYFLOAT', KEYS[1], ARGV[1]); ", - "if redis.call('TTL', KEYS[1]) == -1 then ", - "redis.call('EXPIRE', KEYS[1], ARGV[2]); end; return value" -); -const INCREMENT_WITH_FLOOR_SCRIPT: &str = concat!( - "local count = redis.call('INCRBY', KEYS[1], ARGV[1]); ", - "if count < 0 then count = redis.call('INCRBY', KEYS[1], -count); end; ", - "if redis.call('TTL', KEYS[1]) < 0 then redis.call('EXPIRE', KEYS[1], ARGV[2]); end; ", - "return count" -); -const SET_MAX_SCRIPT: &str = concat!( - "local current = redis.call('GET', KEYS[1]); ", - "if current == false or tonumber(current) < tonumber(ARGV[1]) then ", - "redis.call('SET', KEYS[1], ARGV[1]); ", - "if tonumber(ARGV[2]) > 0 then redis.call('EXPIRE', KEYS[1], ARGV[2]); end; ", - "return ARGV[1]; end; return current" -); - -fn increment_script(amount: f64) -> MockCmd { - MockCmd::new( - redis::cmd("EVAL") - .arg(INCREMENT_SCRIPT) - .arg(1) - .arg("counter") - .arg(amount) - .arg(600), - Ok("4.5"), - ) -} - -#[rstest] -#[tokio::test] -async fn increments_keep_an_existing_ttl_in_one_atomic_script(context: ExactCacheContext) { - let cache = RedisCache::with_connection( - mock(vec![increment_script(2.5), increment_script(2.5)]), - None, - JsonCodec::::new(), - ); - - assert_eq!( - cache - .increment_cache("counter", 2.5, context.clone()) - .unwrap(), - 4.5 - ); - assert_eq!( - cache - .async_increment("counter", 2.5, context, false) - .await - .unwrap(), - 4.5 - ); -} - -#[rstest] -#[case::explicit_ttl(Some(Duration::from_secs(60)), 60u64)] -#[case::default_ttl(None, 600u64)] -#[tokio::test] -async fn refresh_ttl_increments_rearm_the_ttl_in_the_same_round_trip( - #[case] ttl: Option, - #[case] seconds: u64, -) { - let mut pipeline = redis::pipe(); - pipeline - .cmd("INCRBYFLOAT") - .arg("ns:spend:key:k") - .arg(1.5f64) - .cmd("EXPIRE") - .arg("ns:spend:key:k") - .arg(seconds); - let cache = json_cache(vec![MockCmd::with_values( - pipeline, - Ok(vec![ - redis::Value::BulkString(b"1.5".to_vec()), - redis::Value::Int(1), - ]), - )]) - .with_namespace(Some("ns".into())); - - assert_eq!( - cache - .async_increment("spend:key:k", 1.5, ExactCacheContext { ttl }, true) - .await - .unwrap(), - 1.5 - ); -} - -#[rstest] -#[tokio::test] -async fn counter_repairs_are_atomic_and_use_default_ttl() { - let floor = || { - MockCmd::new( - redis::cmd("EVAL") - .arg(INCREMENT_WITH_FLOOR_SCRIPT) - .arg(1) - .arg("team:counter") - .arg(-2i64) - .arg(30u64), - Ok(0i64), - ) - }; - let cache = team(vec![ - floor(), - floor(), - MockCmd::new( - redis::cmd("EVAL") - .arg(SET_MAX_SCRIPT) - .arg(1) - .arg("team:counter") - .arg(4.5f64) - .arg(600u64), - Ok("4.5"), - ), - ]); - - assert_eq!( - cache - .increment_with_floor("counter", -2, Duration::from_secs(30)) - .unwrap(), - 0 - ); - assert_eq!( - cache - .async_increment_with_floor("counter", -2, Duration::from_secs(30)) - .await - .unwrap(), - 0 - ); - assert_eq!( - cache.async_set_max("counter", 4.5, None).await.unwrap(), - 4.5 - ); -} - -const CLAIM_SCRIPT: &str = concat!( - "local current = redis.call('GET', KEYS[1]); ", - "if ARGV[1] == '' then if current ~= false and current ~= '' then return 0; end; ", - "elseif current ~= ARGV[1] then return 0; end; ", - "if ARGV[3] ~= '' then redis.call('SET', KEYS[1], ARGV[3], 'EX', ARGV[2]); ", - "elseif ARGV[4] == '1' then redis.call('EXPIRE', KEYS[1], ARGV[2]); end; return 1" -); - -fn claim_eval(expected: &str, write: &str, refresh: bool, applied: i64) -> MockCmd { - MockCmd::new( - redis::cmd("EVAL") - .arg(CLAIM_SCRIPT) - .arg(1) - .arg("pin") - .arg(expected) - .arg(600) - .arg(write) - .arg(u8::from(refresh)), - Ok(applied), - ) -} - -#[rstest] -#[tokio::test] -async fn claims_match_eligible_values_written_by_another_encoder(context: ExactCacheContext) { - let python_payload = r#"{"model_id": "a", "deployment": "east"}"#; - let stored = json!({"deployment": "east", "model_id": "a"}); - let cache = json_cache(vec![ - MockCmd::new(redis::cmd("GET").arg("pin"), Ok(python_payload)), - claim_eval(python_payload, "", true, 1), - ]); - - assert_eq!( - cache - .async_claim_cache( - "pin", - json!({"model_id": "b"}), - vec![stored.clone()], - context - ) - .await - .unwrap(), - stored - ); -} - -#[rstest] -fn claims_retry_when_the_key_changes_and_replace_ineligible_winners(context: ExactCacheContext) { - let candidate = json!({"model_id": "b"}); - let payload = r#"{"model_id":"b"}"#; - let cache = json_cache(vec![ - MockCmd::new(redis::cmd("GET").arg("pin"), Ok(redis::Value::Nil)), - claim_eval("", payload, false, 0), - MockCmd::new(redis::cmd("GET").arg("pin"), Ok(r#"{"model_id":"gone"}"#)), - claim_eval(r#"{"model_id":"gone"}"#, payload, false, 1), - ]); - - assert_eq!( - cache - .claim_cache( - "pin", - candidate.clone(), - &[json!({"model_id": "a"})], - context - ) - .unwrap(), - candidate - ); -} - -#[rstest] -fn claims_without_eligible_values_keep_the_winner_without_refreshing_its_ttl( - context: ExactCacheContext, -) { - let stored = r#"{"model_id": "a"}"#; - let cache = json_cache(vec![ - MockCmd::new(redis::cmd("GET").arg("pin"), Ok(stored)), - claim_eval(stored, "", false, 1), - ]); - - assert_eq!( - cache - .claim_cache("pin", json!({"model_id": "b"}), &[], context) - .unwrap(), - json!({"model_id": "a"}) - ); -} - -#[rstest] -#[tokio::test] -async fn test_connection_reports_success_with_the_python_message() { - let cache = team(vec![MockCmd::new(redis::cmd("PING"), Ok("PONG"))]); - - let result = cache.test_connection().await.unwrap(); - assert_eq!(result.status, CacheConnectionStatus::Success); - assert_eq!(result.message, "Redis connection test successful"); - assert_eq!(result.error, None); -} - -#[rstest] -#[case::unexpected_reply(Ok("NOPE"), "Redis ping returned False", None)] -#[case::connection_refused( - Err(redis::RedisError::from((redis::ErrorKind::Io, "connection refused"))), - "Redis connection failed:", - Some("connection refused") -)] -#[tokio::test] -async fn test_connection_failures_use_the_python_result_contract( - #[case] reply: redis::RedisResult<&'static str>, - #[case] message: &str, - #[case] cause: Option<&str>, -) { - let cache = json_cache(vec![MockCmd::new(redis::cmd("PING"), reply)]); - - let result = cache.test_connection().await.unwrap(); - assert_eq!(result.status, CacheConnectionStatus::Failed); - assert!(result.message.starts_with(message), "{}", result.message); - assert_eq!(result.error.is_some(), cause.is_some()); - assert!(cause.is_none_or(|cause| { - result - .error - .as_deref() - .is_some_and(|error| error.contains(cause)) - })); -} - -#[rstest] -#[tokio::test] -async fn disconnect_keeps_a_caller_owned_connection_usable() { - let cache = team(vec![MockCmd::new(redis::cmd("PING"), Ok("PONG"))]); - cache.disconnect().await.unwrap(); - assert!(cache.ping().await.unwrap()); -} - -#[rstest] -#[tokio::test] -async fn disconnect_drains_an_idle_pool_without_connecting() { - let cache = RedisCache::new("redis://127.0.0.1:1", None, JsonCodec::::new()).unwrap(); - cache.disconnect().await.unwrap(); -} diff --git a/litellm-rust/crates/cache-redis/tests/cluster.rs b/litellm-rust/crates/cache-redis/tests/cluster.rs deleted file mode 100644 index e1ba01bcb04..00000000000 --- a/litellm-rust/crates/cache-redis/tests/cluster.rs +++ /dev/null @@ -1,563 +0,0 @@ -//! Tests against a real Redis Cluster. Set `LITELLM_TEST_REDIS_CLUSTER_NODES` to a comma -//! separated `host:port` list (for example `127.0.0.1:7000,127.0.0.1:7001`) to run them. - -mod support; - -use std::{collections::HashSet, time::Duration}; - -use litellm_cache::{ - BaseCache, BatchCache, BatchEntry, BoundedCounterCache, BulkDeleteCache, CacheConnectionStatus, - CacheScript, ClaimCache, ClientInfoCache, ConnectionCache, CounterCache, DeleteCache, - DisconnectCache, Error, ExactCacheContext, FlushCache, IncrementOperation, JsonCodec, - PingCache, QueueCache, RefreshTtlCache, ScanCache, ScriptCache, SetCache, TtlCache, - TtlPipelineCache, -}; -use litellm_cache_redis::{ - RedisArg, RedisCache, RedisLpopOperation, RedisLpopResult, RedisNode, RedisRpushOperation, - RedisTopology, -}; -use redis::cluster_routing::Slot; -use rstest::{fixture, rstest}; -use serde_json::json; -use support::{JsonCache, cluster_cache, cluster_url}; - -type Counter = RedisCache>; - -#[fixture] -fn cache(#[default("cache")] label: &str) -> Option { - cluster_cache(label, Duration::from_secs(120), JsonCodec::new()) -} - -#[fixture] -fn counter(#[default("counter")] label: &str) -> Option { - cluster_cache(label, Duration::from_secs(60), JsonCodec::new()) -} - -#[fixture] -fn context() -> ExactCacheContext { - ExactCacheContext::default() -} - -fn multi_slot_keys(count: usize) -> Vec { - let keys: Vec = (0..count).map(|index| format!("key-{index}")).collect(); - let slots: HashSet = keys.iter().map(Slot::for_key).collect(); - assert!(slots.len() > 1, "keys must span multiple slots"); - keys -} - -fn seconds(seconds: u64) -> Option { - Some(Duration::from_secs(seconds)) -} - -#[rstest] -#[case::no_startup_nodes("redis://127.0.0.1:7000", Vec::new())] -#[case::unix_socket_url( - "redis+unix:///tmp/redis.sock", - vec![RedisNode { host: "127.0.0.1".into(), port: 7000 }] -)] -fn constructor_rejects_unusable_cluster_configs( - #[case] url: &str, - #[case] startup_nodes: Vec, -) { - let error = JsonCache::connect( - url, - &RedisTopology::Cluster { startup_nodes }, - None, - JsonCodec::new(), - ) - .err(); - assert!(matches!(error, Some(Error::Unavailable(_)))); -} - -#[rstest] -#[tokio::test] -async fn single_key_operations_round_trip_with_ttl_rounding( - #[with("single")] cache: Option, -) { - let Some(cache) = cache else { return }; - let context = ExactCacheContext { - ttl: Some(Duration::from_millis(1500)), - }; - let keys = multi_slot_keys(12); - for (index, key) in keys.iter().enumerate() { - cache - .set_cache(key, json!({ "index": index }), &context) - .unwrap(); - } - for (index, key) in keys.iter().enumerate() { - assert_eq!( - cache.get_cache(key, &context).unwrap(), - Some(json!({ "index": index })) - ); - } - assert_eq!(cache.async_get_ttl(&keys[0]).await.unwrap(), seconds(2)); - assert!( - cache - .async_refresh_ttl(&keys[0], seconds(40)) - .await - .unwrap() - ); - assert_eq!(cache.async_get_ttl(&keys[0]).await.unwrap(), seconds(40)); - cache.delete_cache(&keys[0]).unwrap(); - assert_eq!(cache.get_cache(&keys[0], &context).unwrap(), None); - assert!(!cache.async_refresh_ttl(&keys[0], None).await.unwrap()); - assert!(cache.sync_ping().unwrap()); - cache.async_flush_cache().await.unwrap(); -} - -#[rstest] -#[tokio::test] -async fn batch_reads_span_slots_and_preserve_order_with_malformed_entries( - #[with("batch")] cache: Option, - context: ExactCacheContext, -) { - let Some(cache) = cache else { return }; - let keys = multi_slot_keys(40); - for (index, key) in keys.iter().enumerate() { - if index % 5 == 0 { - continue; - } - cache - .async_set_cache(key, json!(index), context.clone()) - .await - .unwrap(); - } - let mut raw = redis::cluster::ClusterClient::new(vec![cluster_url()]) - .unwrap() - .get_connection() - .unwrap(); - let malformed = format!("{}:{}", cache.namespace().unwrap(), keys[1]); - redis::cmd("SET") - .arg(&malformed) - .arg("not json") - .exec(&mut raw) - .unwrap(); - - let entries = cache - .async_batch_get_cache(keys.clone(), context.clone()) - .await - .unwrap(); - assert_eq!(entries.len(), keys.len()); - for (index, entry) in entries.iter().enumerate() { - let expected = if index == 1 { - BatchEntry::Invalid - } else if index % 5 == 0 { - BatchEntry::Miss - } else { - BatchEntry::Hit(json!(index)) - }; - assert_eq!(*entry, expected, "entry {index}"); - } - assert_eq!(cache.batch_get_cache(&keys, &context).unwrap(), entries); - - cache.delete_cache_keys(keys.clone()).await.unwrap(); - let entries = cache.async_batch_get_cache(keys, context).await.unwrap(); - assert!(entries.iter().all(|entry| *entry == BatchEntry::Miss)); -} - -#[rstest] -#[tokio::test] -async fn pipelines_group_by_slot_and_return_results_in_submission_order( - #[with("pipeline")] cache: Option, - counter: Option, - context: ExactCacheContext, -) { - let (Some(cache), Some(counter)) = (cache, counter) else { - return; - }; - let keys = multi_slot_keys(30); - cache - .async_set_cache_pipeline( - keys.iter() - .enumerate() - .map(|(index, key)| (key.clone(), json!(index))) - .collect(), - context.clone(), - ) - .await - .unwrap(); - let hits = cache - .async_batch_get_cache(keys.clone(), context.clone()) - .await - .unwrap(); - assert!( - hits.iter() - .enumerate() - .all(|(index, entry)| *entry == BatchEntry::Hit(json!(index))) - ); - - cache - .async_set_cache_pipeline_with_ttls( - keys.iter() - .enumerate() - .map(|(index, key)| (key.clone(), json!(index), seconds(index as u64 + 10))) - .collect(), - ) - .await - .unwrap(); - for (index, key) in keys.iter().enumerate() { - assert_eq!( - cache.async_get_ttl(key).await.unwrap(), - seconds(index as u64 + 10), - "{key}" - ); - } - - let queues: Vec = keys.iter().map(|key| format!("queue:{key}")).collect(); - let pushed = cache - .async_rpush_pipeline( - queues - .iter() - .enumerate() - .map(|(index, key)| RedisRpushOperation { - key: key.clone(), - values: (0..=index) - .map(|value| RedisArg::Integer(value as i64)) - .collect(), - }) - .collect(), - ) - .await - .unwrap(); - assert_eq!(pushed, (1..=keys.len()).collect::>()); - let popped = cache - .async_lpop_pipeline( - queues - .iter() - .enumerate() - .map(|(index, key)| RedisLpopOperation { - key: key.clone(), - count: (index % 2 == 0).then_some(2), - }) - .collect(), - ) - .await - .unwrap(); - for (index, result) in popped.into_iter().enumerate() { - match result { - RedisLpopResult::Value(value) => { - assert_eq!(index % 2, 1, "queue {index}"); - assert_eq!(value, b"0"); - } - RedisLpopResult::Values(values) => { - assert_eq!(index % 2, 0, "queue {index}"); - let expected: Vec> = (0..=index) - .take(2) - .map(|value| value.to_string().into_bytes()) - .collect(); - assert_eq!(values, expected); - } - other => panic!("queue {index}: {other:?}"), - } - } - - let counters: Vec = keys.iter().map(|key| format!("counter:{key}")).collect(); - let totals = counter - .async_increment_pipeline( - counters - .iter() - .enumerate() - .map(|(index, key)| IncrementOperation { - key: key.clone(), - amount: index as f64 + 0.5, - ttl: (index % 3 == 0).then_some(Duration::from_secs(30)), - }) - .collect(), - ) - .await - .unwrap(); - let expected: Vec = (0..keys.len()).map(|index| index as f64 + 0.5).collect(); - assert_eq!(totals, expected); - assert_eq!( - counter.async_get_ttl(&counters[0]).await.unwrap(), - seconds(30) - ); - assert_eq!(counter.async_get_ttl(&counters[1]).await.unwrap(), None); - counter.async_flush_cache().await.unwrap(); - cache.async_flush_cache().await.unwrap(); -} - -#[rstest] -#[tokio::test] -async fn rpush_and_trim_is_one_transaction_on_the_key_slot( - #[with("trim")] cache: Option, -) { - let Some(cache) = cache else { return }; - let values = |values: &[&str]| values.iter().map(|value| RedisArg::from(*value)).collect(); - assert_eq!( - cache - .async_rpush_and_trim("buf", values(&["a", "b"]), 3) - .await - .unwrap(), - 2 - ); - assert_eq!( - cache - .async_rpush_and_trim("buf", values(&["c", "d"]), 3) - .await - .unwrap(), - 4 - ); - assert_eq!( - cache.async_lpop("buf", Some(10)).await.unwrap(), - RedisLpopResult::Values(vec![b"b".to_vec(), b"c".to_vec(), b"d".to_vec()]) - ); - cache.async_flush_cache().await.unwrap(); -} - -#[rstest] -#[tokio::test] -async fn scan_and_scoped_flush_cover_every_primary( - #[with("flush")] cache: Option, - #[from(cache)] - #[with("other")] - other: Option, - context: ExactCacheContext, -) { - let (Some(cache), Some(other)) = (cache, other) else { - return; - }; - let keys = multi_slot_keys(60); - for key in &keys { - cache - .async_set_cache(key, json!(true), context.clone()) - .await - .unwrap(); - other - .async_set_cache(key, json!(true), context.clone()) - .await - .unwrap(); - } - let mut scanned = cache.async_scan_iter("key-", 1000).await.unwrap(); - scanned.sort(); - let mut expected: Vec = keys - .iter() - .map(|key| format!("{}:{key}", cache.namespace().unwrap())) - .collect(); - expected.sort(); - assert_eq!(scanned, expected); - assert_eq!(cache.async_scan_iter("key-", 7).await.unwrap().len(), 7); - - cache.flush_cache().unwrap(); - let flushed = cache - .async_batch_get_cache(keys.clone(), context.clone()) - .await - .unwrap(); - assert!(flushed.iter().all(|entry| *entry == BatchEntry::Miss)); - let kept = other.async_batch_get_cache(keys, context).await.unwrap(); - assert!( - kept.iter() - .all(|entry| *entry == BatchEntry::Hit(json!(true))) - ); - other.async_flush_cache().await.unwrap(); -} - -fn ping_calls_per_node(startup: &redis::Client) -> Vec<(String, u64)> { - let mut connection = startup.get_connection().unwrap(); - let nodes: String = redis::cmd("CLUSTER") - .arg("NODES") - .query(&mut connection) - .unwrap(); - let mut counts: Vec<(String, u64)> = nodes - .lines() - .map(|line| { - let address = line.split_whitespace().nth(1).unwrap(); - let address = address.split('@').next().unwrap(); - let mut node = redis::Client::open(format!("redis://{address}")) - .unwrap() - .get_connection() - .unwrap(); - let stats: String = redis::cmd("INFO") - .arg("commandstats") - .query(&mut node) - .unwrap(); - let calls = stats - .lines() - .find_map(|stat| stat.strip_prefix("cmdstat_ping:calls=")) - .and_then(|rest| rest.split(',').next()) - .map_or(0, |calls| calls.parse().unwrap()); - (address.to_string(), calls) - }) - .collect(); - counts.sort(); - counts -} - -#[rstest] -#[tokio::test] -async fn ping_reaches_every_node(#[with("ping")] cache: Option) { - let Some(cache) = cache else { return }; - let startup = redis::Client::open(cluster_url()).unwrap(); - let before = ping_calls_per_node(&startup); - assert!(before.len() >= 2, "{before:?}"); - assert!(cache.ping().await.unwrap()); - let after = ping_calls_per_node(&startup); - for ((node, calls_before), (_, calls_after)) in before.iter().zip(&after) { - assert!(calls_after > calls_before, "{node} was not pinged"); - } - assert!(cache.sync_ping().unwrap()); - let result = cache.test_connection().await.unwrap(); - assert_eq!(result.status, CacheConnectionStatus::Success); - assert_eq!(result.message, "Redis Cluster connection test successful"); -} - -#[rstest] -#[tokio::test] -async fn disconnect_closes_idle_connections_and_reconnects_on_demand( - #[with("disconnect")] cache: Option, -) { - let Some(cache) = cache else { return }; - assert!(cache.ping().await.unwrap()); - cache.disconnect().await.unwrap(); - assert!(cache.ping().await.unwrap()); -} - -#[rstest] -#[case::keep_existing_ttl(false)] -#[case::refresh_ttl(true)] -#[tokio::test] -async fn increments_refresh_the_ttl_only_when_asked( - counter: Option, - #[case] refresh_ttl: bool, -) { - let Some(counter) = counter else { return }; - let context = ExactCacheContext { ttl: seconds(60) }; - counter - .async_set_cache("spend", 0.0, ExactCacheContext { ttl: seconds(600) }) - .await - .unwrap(); - assert_eq!( - counter - .async_increment("spend", 1.5, context.clone(), refresh_ttl) - .await - .unwrap(), - 1.5 - ); - assert_eq!( - counter - .async_increment("spend", 2.0, context, refresh_ttl) - .await - .unwrap(), - 3.5 - ); - let ttl = counter.async_get_ttl("spend").await.unwrap().unwrap(); - assert_eq!(ttl <= Duration::from_secs(60), refresh_ttl, "{ttl:?}"); - counter.async_flush_cache().await.unwrap(); -} - -#[rstest] -#[tokio::test] -async fn counters_claims_scripts_and_sets_work_on_the_cluster( - counter: Option, - #[with("claim")] cache: Option, - context: ExactCacheContext, -) { - let (Some(counter), Some(cache)) = (counter, cache) else { - return; - }; - assert_eq!( - counter - .increment_cache("spend", 1.5, context.clone()) - .unwrap(), - 1.5 - ); - assert_eq!( - counter - .async_increment("spend", 2.0, context.clone(), false) - .await - .unwrap(), - 3.5 - ); - assert_eq!( - counter - .increment_with_floor("budget", -3, Duration::from_secs(30)) - .unwrap(), - 0 - ); - assert_eq!( - counter - .async_increment_with_floor("budget", 7, Duration::from_secs(30)) - .await - .unwrap(), - 7 - ); - assert_eq!(counter.async_set_max("peak", 4.0, None).await.unwrap(), 4.0); - assert_eq!(counter.async_set_max("peak", 2.0, None).await.unwrap(), 4.0); - counter.flush_cache().unwrap(); - - let owner = json!("owner-a"); - let rival = json!("owner-b"); - assert_eq!( - cache - .claim_cache("lock", owner.clone(), &[], context.clone()) - .unwrap(), - owner - ); - assert_eq!( - cache - .async_claim_cache("lock", rival.clone(), vec![owner.clone()], context.clone()) - .await - .unwrap(), - owner - ); - assert_eq!( - cache - .claim_cache("lock", rival.clone(), &[], context.clone()) - .unwrap(), - owner - ); - assert_eq!( - cache - .async_claim_cache("lock", rival.clone(), vec![rival.clone()], context.clone()) - .await - .unwrap(), - rival - ); - - let script = cache - .async_register_script("return redis.call('SET', KEYS[1], ARGV[1], 'EX', ARGV[2])".into()); - let reply = script - .invoke( - vec!["scripted".into()], - vec![RedisArg::Bytes(b"payload".to_vec()), RedisArg::Integer(5)], - ) - .await - .unwrap(); - assert_eq!(reply, redis::Value::Okay); - assert_eq!(cache.async_get_ttl("scripted").await.unwrap(), seconds(5)); - let evaluated = cache - .async_eval( - "return redis.call('GET', KEYS[1])".into(), - vec!["scripted".into()], - Vec::new(), - ) - .await - .unwrap(); - assert_eq!(evaluated, redis::Value::BulkString(b"payload".to_vec())); - - assert_eq!( - cache - .async_set_cache_sadd( - "members", - vec![ - RedisArg::Bytes(b"a".to_vec()), - RedisArg::Bytes(b"b".to_vec()) - ], - seconds(9), - ) - .await - .unwrap(), - 2 - ); - assert_eq!(cache.async_get_ttl("members").await.unwrap(), seconds(9)); - - let result = cache.test_connection().await.unwrap(); - assert_eq!(result.status, CacheConnectionStatus::Success); - assert!(cache.ping().await.unwrap()); - let info = cache.info().unwrap(); - assert!(info.matches("redis_version").count() > 1, "{info}"); - assert!(cache.client_list().unwrap().contains("id=")); - cache.async_flush_cache().await.unwrap(); - assert_eq!(cache.async_get_ttl("members").await.unwrap(), None); - assert_eq!(cache.get_cache("lock", &context).unwrap(), None); -} diff --git a/litellm-rust/crates/cache-redis/tests/contract.rs b/litellm-rust/crates/cache-redis/tests/contract.rs deleted file mode 100644 index 85d043b90b2..00000000000 --- a/litellm-rust/crates/cache-redis/tests/contract.rs +++ /dev/null @@ -1,95 +0,0 @@ -//! The shared cache contracts, run against the in-process fake connection and, when -//! `LITELLM_TEST_REDIS_CLUSTER_NODES` is set, against a live Redis Cluster. - -mod support; - -use std::time::Duration; - -use litellm_cache::{ExactCacheContext, JsonCodec}; -use litellm_cache_testing as contract; -use rstest::rstest; -use serde_json::json; -use support::{JsonCache, cluster_cache, fake_cache}; - -const PREFIX: &str = "contract:"; - -#[derive(Clone, Copy, Debug)] -enum Contract { - HitAndMiss, - SyncAsyncEquivalence, - OverwriteReplaces, - PipelineWritesEveryEntry, - BatchPreservesOrder, - DeleteRemovesKey, - FlushClears, - CounterAccumulates, -} - -#[derive(Clone, Copy, Debug)] -enum Server { - Fake, - Cluster, -} - -async fn check(contract: Contract, cache: &JsonCache) -where - C: redis::ConnectionLike + Send + 'static, -{ - let context = ExactCacheContext::default(); - match contract { - Contract::HitAndMiss => { - contract::hit_and_miss(cache, context, PREFIX, json!({"answer": 42})).await - } - Contract::SyncAsyncEquivalence => { - contract::sync_async_equivalence(cache, context, PREFIX, json!("first"), json!([2])) - .await - } - Contract::OverwriteReplaces => { - contract::overwrite_replaces(cache, context, PREFIX, json!(1), json!({"b": 2})).await - } - Contract::PipelineWritesEveryEntry => { - contract::pipeline_writes_every_entry( - cache, - context, - PREFIX, - vec![json!("a"), json!(2), json!({"c": true})], - ) - .await - } - Contract::BatchPreservesOrder => { - contract::batch_preserves_order(cache, context, PREFIX, json!("first"), json!(2)).await - } - Contract::DeleteRemovesKey => { - contract::delete_removes_key(cache, context, PREFIX, json!("value")).await - } - Contract::FlushClears => { - contract::flush_clears(cache, context, PREFIX, json!("value")).await - } - Contract::CounterAccumulates => contract::counter_accumulates(cache, context, PREFIX).await, - } -} - -#[rstest] -#[case::hit_and_miss(Contract::HitAndMiss)] -#[case::sync_async_equivalence(Contract::SyncAsyncEquivalence)] -#[case::overwrite_replaces(Contract::OverwriteReplaces)] -#[case::pipeline_writes_every_entry(Contract::PipelineWritesEveryEntry)] -#[case::batch_preserves_order(Contract::BatchPreservesOrder)] -#[case::delete_removes_key(Contract::DeleteRemovesKey)] -#[case::flush_clears(Contract::FlushClears)] -#[case::counter_accumulates(Contract::CounterAccumulates)] -#[tokio::test] -async fn redis_satisfies_the_cache_contract( - #[case] contract: Contract, - #[values(Server::Fake, Server::Cluster)] server: Server, -) { - match server { - Server::Fake => check(contract, &fake_cache("contract")).await, - Server::Cluster => { - let label = format!("{contract:?}"); - if let Some(cache) = cluster_cache(&label, Duration::from_secs(120), JsonCodec::new()) { - check(contract, &cache).await; - } - } - } -} diff --git a/litellm-rust/crates/cache-redis/tests/support/mod.rs b/litellm-rust/crates/cache-redis/tests/support/mod.rs deleted file mode 100644 index b04e1c29f3b..00000000000 --- a/litellm-rust/crates/cache-redis/tests/support/mod.rs +++ /dev/null @@ -1,231 +0,0 @@ -#![allow(dead_code)] - -use std::{ - collections::BTreeMap, - time::{Duration, SystemTime, UNIX_EPOCH}, -}; - -use litellm_cache::{CacheCodec, Error, JsonCodec}; -use litellm_cache_redis::{RedisCache, RedisNode, RedisTopology}; - -/// Encodes a byte behind a tag, so a value written with another tag decodes as invalid. -pub struct TaggedByteCodec(pub u8); - -impl CacheCodec for TaggedByteCodec { - type Value = u8; - - fn encode(&self, value: &u8) -> Result, Error> { - if *value > 127 { - return Err(Error::InvalidEntry(None)); - } - Ok(vec![self.0, *value]) - } - - fn decode(&self, bytes: &[u8]) -> Result { - match bytes { - [tag, value] if *tag == self.0 => Ok(*value), - _ => Err(Error::InvalidEntry(None)), - } - } -} - -/// A stateful in-process stand-in for a Redis server that understands the string commands the -/// shared contracts exercise, so they run without a live server. TTLs are accepted and ignored. -#[derive(Default)] -pub struct FakeRedis { - strings: BTreeMap, Vec>, -} - -impl FakeRedis { - fn run(&mut self, command: Vec>) -> redis::RedisResult { - let name = String::from_utf8_lossy(&command[0]).to_ascii_uppercase(); - let args = &command[1..]; - Ok(match name.as_str() { - "PING" => redis::Value::SimpleString("PONG".into()), - "SET" | "SETEX" => { - let value = if name == "SET" { &args[1] } else { &args[2] }; - self.strings.insert(args[0].clone(), value.clone()); - redis::Value::Okay - } - "GET" => self.get(&args[0]), - "MGET" => redis::Value::Array(args.iter().map(|key| self.get(key)).collect()), - "DEL" => { - let removed = args - .iter() - .filter(|key| self.strings.remove(*key).is_some()) - .count(); - redis::Value::Int(removed as i64) - } - "SCAN" => { - let pattern = &args[2]; - let keys = self - .strings - .keys() - .filter(|key| glob(pattern, key)) - .map(|key| redis::Value::BulkString(key.clone())) - .collect(); - redis::Value::Array(vec![ - redis::Value::BulkString(b"0".to_vec()), - redis::Value::Array(keys), - ]) - } - "EVAL" if args[0].windows(11).any(|window| window == b"INCRBYFLOAT") => { - self.increment_by_float(&args[2], &args[3]) - } - "INCRBYFLOAT" => self.increment_by_float(&args[0], &args[1]), - _ => { - return Err(redis::RedisError::from(( - redis::ErrorKind::Client, - "unsupported command", - name, - ))); - } - }) - } - - fn get(&self, key: &[u8]) -> redis::Value { - self.strings.get(key).map_or(redis::Value::Nil, |value| { - redis::Value::BulkString(value.clone()) - }) - } - - fn increment_by_float(&mut self, key: &[u8], amount: &[u8]) -> redis::Value { - let current = self - .strings - .get(key) - .map_or(0.0, |value| parse_float(value)); - let total = format!("{}", current + parse_float(amount)); - self.strings - .insert(key.to_vec(), total.clone().into_bytes()); - redis::Value::BulkString(total.into_bytes()) - } -} - -fn parse_float(bytes: &[u8]) -> f64 { - std::str::from_utf8(bytes).unwrap().parse().unwrap() -} - -/// Redis `MATCH` globbing for `*`, `?` and backslash escapes. -fn glob(pattern: &[u8], key: &[u8]) -> bool { - match pattern.split_first() { - None => key.is_empty(), - Some((b'*', rest)) => (0..=key.len()).any(|skip| glob(rest, &key[skip..])), - Some((b'?', rest)) => !key.is_empty() && glob(rest, &key[1..]), - Some((b'\\', [escaped, rest @ ..])) => { - key.first() == Some(escaped) && glob(rest, &key[1..]) - } - Some((literal, rest)) => key.first() == Some(literal) && glob(rest, &key[1..]), - } -} - -/// Splits RESP request bytes into the commands they carry. -fn commands(mut bytes: &[u8]) -> Vec>> { - fn line<'a>(bytes: &mut &'a [u8]) -> &'a [u8] { - let end = bytes - .windows(2) - .position(|window| window == b"\r\n") - .unwrap(); - let (line, rest) = bytes.split_at(end); - *bytes = &rest[2..]; - line - } - fn length(line: &[u8]) -> usize { - std::str::from_utf8(&line[1..]).unwrap().parse().unwrap() - } - let mut commands = Vec::new(); - while !bytes.is_empty() { - let count = length(line(&mut bytes)); - let command = (0..count) - .map(|_| { - let size = length(line(&mut bytes)); - let (argument, rest) = bytes.split_at(size); - bytes = &rest[2..]; - argument.to_vec() - }) - .collect(); - commands.push(command); - } - commands -} - -impl redis::ConnectionLike for FakeRedis { - fn req_packed_command(&mut self, cmd: &[u8]) -> redis::RedisResult { - let command = commands(cmd).into_iter().next().unwrap(); - self.run(command) - } - - fn req_packed_commands( - &mut self, - cmd: &[u8], - offset: usize, - count: usize, - ) -> redis::RedisResult> { - let replies = commands(cmd) - .into_iter() - .map(|command| self.run(command)) - .collect::>>()?; - Ok(replies.into_iter().skip(offset).take(count).collect()) - } - - fn get_db(&self) -> i64 { - 0 - } - - fn check_connection(&mut self) -> bool { - true - } - - fn is_open(&self) -> bool { - true - } -} - -pub type JsonCache = RedisCache, C>; - -pub fn fake_cache(namespace: &str) -> JsonCache { - RedisCache::with_connection(FakeRedis::default(), None, JsonCodec::new()) - .with_namespace(Some(namespace.into())) -} - -/// Startup nodes from `LITELLM_TEST_REDIS_CLUSTER_NODES` (`host:port,host:port`); tests that -/// need a live cluster skip when it is unset. -pub fn cluster_topology() -> Option { - let nodes = std::env::var("LITELLM_TEST_REDIS_CLUSTER_NODES").ok()?; - let startup_nodes = nodes - .split(',') - .map(|node| { - let (host, port) = node.trim().rsplit_once(':').expect("host:port"); - RedisNode { - host: host.to_string(), - port: port.parse().expect("port"), - } - }) - .collect(); - Some(RedisTopology::Cluster { startup_nodes }) -} - -pub fn cluster_url() -> String { - std::env::var("LITELLM_TEST_REDIS_CLUSTER_URL") - .unwrap_or_else(|_| "redis://127.0.0.1:7000".into()) -} - -pub fn unique_namespace(label: &str) -> String { - let nanos = SystemTime::now() - .duration_since(UNIX_EPOCH) - .unwrap() - .as_nanos(); - format!("cluster-test:{label}:{nanos}") -} - -pub fn cluster_cache( - label: &str, - default_ttl: Duration, - codec: S, -) -> Option> { - let topology = cluster_topology()?; - Some( - RedisCache::connect(&cluster_url(), &topology, Some(default_ttl), codec) - .expect("cluster connection") - .with_namespace(Some(unique_namespace(label))), - ) -} diff --git a/litellm-rust/crates/cache-response/Cargo.toml b/litellm-rust/crates/cache-response/Cargo.toml index 8f4570edc6f..46ef6ab92a8 100644 --- a/litellm-rust/crates/cache-response/Cargo.toml +++ b/litellm-rust/crates/cache-response/Cargo.toml @@ -16,9 +16,6 @@ sha2.workspace = true litellm-cache-gcs.workspace = true litellm-http = { workspace = true, features = ["test-support"] } litellm-cache-memory.workspace = true -litellm-cache-redis.workspace = true -redis.workspace = true -redis-test.workspace = true rstest.workspace = true tokio.workspace = true wiremock.workspace = true diff --git a/litellm-rust/crates/cache-response/tests/connection.rs b/litellm-rust/crates/cache-response/tests/connection.rs index bc24cf56846..f64057f6f1c 100644 --- a/litellm-rust/crates/cache-response/tests/connection.rs +++ b/litellm-rust/crates/cache-response/tests/connection.rs @@ -2,79 +2,11 @@ mod support; use std::{sync::Arc, time::Duration}; -use litellm_cache::CacheConnectionStatus; use litellm_cache_memory::InMemoryCache; -use litellm_cache_response::{ - CacheEntry, ConnectionProbe, ExactResponseCache, ResponseCache, ResponseCacheRequest, -}; -use redis_test::MockCmd; +use litellm_cache_response::{CacheEntry, ExactResponseCache, ResponseCache, ResponseCacheRequest}; use rstest::rstest; use serde_json::json; -use support::{keyed, memory, redis, request}; - -#[rstest] -#[case::reachable( - Ok("PONG"), - CacheConnectionStatus::Success, - "Redis connection test successful", - false -)] -#[case::unexpected_reply( - Ok("NOPE"), - CacheConnectionStatus::Failed, - "Redis ping returned False", - false -)] -#[case::connection_refused( - Err(redis::RedisError::from((redis::ErrorKind::Io, "connection refused"))), - CacheConnectionStatus::Failed, - "Redis connection failed:", - true -)] -#[tokio::test] -async fn connection_backends_are_reachable_as_a_probe( - #[case] reply: redis::RedisResult<&'static str>, - #[case] status: CacheConnectionStatus, - #[case] message: &str, - #[case] has_error: bool, -) { - let probe: Arc = - Arc::new(redis(vec![MockCmd::new(redis::cmd("PING"), reply)], None)); - - let result = probe.test_connection().await.unwrap(); - assert_eq!(result.status, status); - assert!(result.message.starts_with(message), "{}", result.message); - assert_eq!(result.error.is_some(), has_error); -} - -#[rstest] -#[tokio::test] -async fn one_service_serves_both_the_exact_cache_and_its_probe(request: ResponseCacheRequest) { - let service = Arc::new(redis( - vec![ - MockCmd::new(redis::cmd("PING"), Ok("PONG")), - MockCmd::new( - redis::cmd("GET").arg("tenant:key"), - Ok(br#"{"timestamp":100.0,"response":{"ok":true}}"#.to_vec()), - ), - ], - Some("tenant"), - )); - let probe: Arc = service.clone(); - let exact: Arc = service; - - assert_eq!( - probe.test_connection().await.unwrap().status, - CacheConnectionStatus::Success - ); - assert_eq!( - exact - .async_lookup(&request, Duration::from_secs(100)) - .await - .unwrap(), - Some(json!({"ok": true})) - ); -} +use support::{keyed, memory, request}; /// The in-memory backend has no `test_connection`, as in Python, and still serves every response /// operation. diff --git a/litellm-rust/crates/cache-response/tests/response.rs b/litellm-rust/crates/cache-response/tests/response.rs index 70ae259d33a..659ba065cf2 100644 --- a/litellm-rust/crates/cache-response/tests/response.rs +++ b/litellm-rust/crates/cache-response/tests/response.rs @@ -17,10 +17,9 @@ use litellm_cache_response::{ CacheControls, CacheEntry, CacheKeyField, CacheKeyInput, ResponseCache, ResponseCacheRequest, WriteBuffer, cache_key, }; -use redis_test::MockCmd; use rstest::{fixture, rstest}; use serde_json::{Value, json}; -use support::{keyed, memory, redis, request}; +use support::{keyed, memory, request}; type Memory = Arc>>; @@ -331,79 +330,6 @@ async fn directives_skip_io_and_keep_reads_and_writes_independent( ); } -#[rstest] -#[case::python_sync_literal( - br#"{'timestamp': 100.0, 'response': '{"ok": true, "text": "cached"}'}"#.as_slice() -)] -#[case::python_async_json(br#"{"timestamp":100.0,"response":{"ok":true,"text":"cached"}}"#.as_slice())] -#[tokio::test] -async fn redis_consumer_reads_python_sync_and_async_envelopes( - request: ResponseCacheRequest, - #[case] stored: &[u8], - #[values(false, true)] asynchronous: bool, -) { - let cache = redis( - vec![MockCmd::new( - redis::cmd("GET").arg("tenant:key"), - Ok(stored.to_vec()), - )], - Some("tenant"), - ); - let now = Duration::from_secs(101); - let found = if asynchronous { - cache.async_lookup(&request, now).await.unwrap() - } else { - cache.lookup(&request, now).unwrap() - }; - assert_eq!(found, Some(json!({"ok": true, "text": "cached"}))); -} - -#[rstest] -#[case::object( - json!({"ok": true, "text": "cached"}), - br#"{"timestamp":100.0,"response":{"ok":true,"text":"cached"}}"#.as_slice() -)] -#[case::array(json!([1, 2]), br#"{"timestamp":100.0,"response":"[1,2]"}"#.as_slice())] -#[tokio::test] -async fn redis_consumer_writes_python_compatible_json( - request: ResponseCacheRequest, - #[case] response: Value, - #[case] wire: &[u8], -) { - let cache = redis( - vec![MockCmd::new( - redis::cmd("SETEX").arg("tenant:key").arg(600).arg(wire), - Ok("OK"), - )], - Some("tenant"), - ); - cache - .async_store(&request, response, Duration::from_secs(100)) - .await - .unwrap(); -} - -#[rstest] -#[tokio::test] -async fn invalid_entries_are_misses_and_disabled_reads_do_not_touch_redis( - mut request: ResponseCacheRequest, -) { - let cache = redis( - vec![MockCmd::new( - redis::cmd("GET").arg("tenant:key"), - Ok(b"invalid".to_vec()), - )], - None, - ); - request.controls.no_cache = true; - assert_eq!(cache.lookup(&request, Duration::ZERO).unwrap(), None); - request.controls.no_cache = false; - assert_eq!( - cache.async_lookup(&request, Duration::ZERO).await.unwrap(), - None - ); -} - #[rstest] #[tokio::test] async fn captured_service_keeps_the_selected_backend_for_background_writes( @@ -541,27 +467,6 @@ async fn batch_lookup_reports_partial_hits_and_batch_store_populates_misses( assert_eq!(memory.lookup(&requests[2], now).unwrap(), None); } -#[rstest] -#[tokio::test] -async fn batch_lookup_with_no_readable_request_skips_the_backend( - #[values(false, true)] asynchronous: bool, -) { - let cache = redis(Vec::new(), None); - let mut request = keyed("key"); - request.controls.no_cache = true; - let requests = [request.clone(), request]; - let partial = if asynchronous { - cache - .async_lookup_batch(&requests, Duration::ZERO) - .await - .unwrap() - } else { - cache.lookup_batch(&requests, Duration::ZERO).unwrap() - }; - assert_eq!(partial.values, vec![None, None]); - assert_eq!(partial.missing_indices, vec![0, 1]); -} - #[rstest] #[tokio::test] async fn deferred_entries_keep_the_time_they_were_produced( diff --git a/litellm-rust/crates/cache-response/tests/support/mod.rs b/litellm-rust/crates/cache-response/tests/support/mod.rs index b992a937b70..f84da303659 100644 --- a/litellm-rust/crates/cache-response/tests/support/mod.rs +++ b/litellm-rust/crates/cache-response/tests/support/mod.rs @@ -1,15 +1,9 @@ use std::{sync::Arc, time::Duration}; use litellm_cache_memory::InMemoryCache; -use litellm_cache_redis::RedisCache; -use litellm_cache_response::{ - CacheEntry, CacheKeyInput, ResponseCache, ResponseCacheCodec, ResponseCacheRequest, -}; -use redis_test::{MockCmd, MockRedisConnection}; +use litellm_cache_response::{CacheEntry, CacheKeyInput, ResponseCache, ResponseCacheRequest}; use rstest::fixture; -pub type MockedRedis = RedisCache; - #[fixture] pub fn memory() -> Arc>> { Arc::new(ResponseCache::new(Arc::new(InMemoryCache::new( @@ -29,12 +23,3 @@ pub fn keyed(key: &str) -> ResponseCacheRequest { ..Default::default() }) } - -/// A Redis response cache that must receive exactly `commands`, in order. -pub fn redis(commands: Vec, namespace: Option<&str>) -> ResponseCache { - let connection = MockRedisConnection::new(commands).assert_all_commands_consumed(); - ResponseCache::new(Arc::new( - RedisCache::with_connection(connection, None, ResponseCacheCodec) - .with_namespace(namespace.map(str::to_owned)), - )) -} diff --git a/litellm-rust/crates/cache-s3/src/auth.rs b/litellm-rust/crates/cache-s3/src/auth.rs index 659390a5659..02707c24881 100644 --- a/litellm-rust/crates/cache-s3/src/auth.rs +++ b/litellm-rust/crates/cache-s3/src/auth.rs @@ -36,9 +36,12 @@ impl ProvideCredentials for S3Credentials { self.config.secret_access_key.clone(), ) { return Ok(AwsCredentials::new( - access_key_id, - secret_access_key, - self.config.session_token.clone(), + access_key_id.expose(), + secret_access_key.expose(), + self.config + .session_token + .as_ref() + .map(|value| value.expose().to_owned()), None, "litellm-s3-cache", )); diff --git a/litellm-rust/crates/cache-s3/tests/auth.rs b/litellm-rust/crates/cache-s3/tests/auth.rs index 59c5aa2e091..5aa251ac749 100644 --- a/litellm-rust/crates/cache-s3/tests/auth.rs +++ b/litellm-rust/crates/cache-s3/tests/auth.rs @@ -5,9 +5,9 @@ use rstest::rstest; fn explicit(session_token: Option<&str>) -> AwsAuthConfig { AwsAuthConfig { - access_key_id: Some("key".to_string()), - secret_access_key: Some("secret".to_string()), - session_token: session_token.map(str::to_string), + access_key_id: Some("key".into()), + secret_access_key: Some("secret".into()), + session_token: session_token.map(Into::into), region_name: Some("us-east-1".to_string()), ..Default::default() } diff --git a/litellm-rust/crates/cache-s3/tests/support/mod.rs b/litellm-rust/crates/cache-s3/tests/support/mod.rs index 7378dde21bf..311d2402e72 100644 --- a/litellm-rust/crates/cache-s3/tests/support/mod.rs +++ b/litellm-rust/crates/cache-s3/tests/support/mod.rs @@ -23,8 +23,8 @@ pub fn config(endpoint: &str) -> S3CacheConfig { url: endpoint.to_string(), }), auth: AwsAuthConfig { - access_key_id: Some("key".to_string()), - secret_access_key: Some("secret".to_string()), + access_key_id: Some("key".into()), + secret_access_key: Some("secret".into()), region_name: Some("us-east-1".to_string()), ..Default::default() }, diff --git a/litellm-rust/crates/cache-valkey-semantic/Cargo.toml b/litellm-rust/crates/cache-valkey-semantic/Cargo.toml deleted file mode 100644 index 5b4e99de382..00000000000 --- a/litellm-rust/crates/cache-valkey-semantic/Cargo.toml +++ /dev/null @@ -1,22 +0,0 @@ -[package] -name = "litellm-cache-valkey-semantic" -version = "0.1.0" -edition.workspace = true -license.workspace = true -repository.workspace = true - -[dependencies] -litellm-cache.workspace = true -litellm-cache-redis.workspace = true -redis = { workspace = true, features = ["tls-rustls"] } -sha2.workspace = true -thiserror.workspace = true -uuid = { version = "1", features = ["v4"] } - -[dev-dependencies] -litellm-error.workspace = true -litellm-cache-testing.workspace = true -redis-test.workspace = true -rstest.workspace = true -serde_json.workspace = true -tokio.workspace = true diff --git a/litellm-rust/crates/cache-valkey-semantic/src/cache.rs b/litellm-rust/crates/cache-valkey-semantic/src/cache.rs deleted file mode 100644 index 947c0edc479..00000000000 --- a/litellm-rust/crates/cache-valkey-semantic/src/cache.rs +++ /dev/null @@ -1,245 +0,0 @@ -use std::{ - sync::{Arc, Mutex}, - time::Duration, -}; - -use litellm_cache::{ - BaseCache, CacheCodec, Error, SemanticCacheContext, - semantic::{Embedder, SemanticCache, SemanticLookup, prompt_from_context}, -}; -use litellm_cache_redis::{RedisTopology, connection::Connections}; - -use crate::{ - ValkeySemanticConfig, - index::IndexState, - search::{embedding_bytes, scope_tag, search_document, write_document}, -}; - -/// `ValkeySemanticCache`: a semantic cache on valkey-search's TAG + VECTOR index. Values go -/// through the injected codec, so the response layer decides what a cached entry is. -pub struct ValkeySemanticCache { - connections: Arc>, - embedder: E, - codec: S, - config: ValkeySemanticConfig, - index_dimension: Arc>>, -} - -impl ValkeySemanticCache { - pub fn new( - url: &str, - embedder: E, - codec: S, - config: ValkeySemanticConfig, - ) -> Result { - Ok(Self { - connections: Arc::new(Connections::open(url, &RedisTopology::Standalone)?), - embedder, - codec, - config, - index_dimension: Arc::new(Mutex::new(None)), - }) - } -} - -impl ValkeySemanticCache -where - E: Embedder, - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - pub fn with_connection( - connection: C, - embedder: E, - codec: S, - config: ValkeySemanticConfig, - ) -> Self { - Self { - connections: Arc::new(Connections::fixed(connection)), - embedder, - codec, - config, - index_dimension: Arc::new(Mutex::new(None)), - } - } - - pub fn similarity_threshold(&self) -> f64 { - self.config.similarity_threshold - } - - pub fn index_name(&self) -> &str { - &self.config.index_name - } - - fn index_state(&self) -> IndexState { - IndexState { - name: self.config.index_name.clone(), - prefix: format!("{}:", self.config.index_name), - dimension: Arc::clone(&self.index_dimension), - similarity_threshold: self.config.similarity_threshold, - } - } - - fn decode(&self, lookup: SemanticLookup>) -> Result, Error> { - Ok(SemanticLookup { - value: lookup - .value - .map(|bytes| self.codec.decode(&bytes)) - .transpose()?, - similarity: lookup.similarity, - }) - } -} - -impl ValkeySemanticCache -where - E: Embedder, - S: CacheCodec + Clone, - C: redis::ConnectionLike + Send + 'static, -{ - /// The same index and connections behind a different embedder. - pub fn with_embedder(&self, embedder: E2) -> ValkeySemanticCache { - ValkeySemanticCache { - connections: Arc::clone(&self.connections), - embedder, - codec: self.codec.clone(), - config: self.config.clone(), - index_dimension: Arc::clone(&self.index_dimension), - } - } -} - -impl BaseCache for ValkeySemanticCache -where - E: Embedder, - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - type Value = S::Value; - type Context = SemanticCacheContext; - - fn get_ttl(&self, context: &Self::Context) -> Option { - context.ttl - } - - fn set_cache( - &self, - key: &str, - value: Self::Value, - context: &Self::Context, - ) -> Result<(), Error> { - let Some(prompt) = prompt_from_context(context) else { - return Ok(()); - }; - let embedding = self.embedder.embed(&prompt, context.metadata.as_ref())?; - let response = self.codec.encode(&value)?; - let index = self.index_state(); - self.connections.execute(|connection| { - write_document( - connection, - &index, - &scope_tag(key), - &prompt, - response, - embedding_bytes(&embedding), - self.get_ttl(context), - ) - }) - } - - fn get_cache(&self, key: &str, context: &Self::Context) -> Result, Error> { - self.get_cache_with_similarity(key, context) - .map(|lookup| lookup.value) - } - - async fn async_set_cache( - &self, - key: &str, - value: Self::Value, - context: Self::Context, - ) -> Result<(), Error> { - let Some(prompt) = prompt_from_context(&context) else { - return Ok(()); - }; - let embedding = self - .embedder - .async_embed(&prompt, context.metadata.as_ref()) - .await?; - let response = self.codec.encode(&value)?; - let index = self.index_state(); - let scope = scope_tag(key); - Connections::run_blocking(Arc::clone(&self.connections), move |connection| { - write_document( - connection, - &index, - &scope, - &prompt, - response, - embedding_bytes(&embedding), - context.ttl, - ) - }) - .await - } - - async fn async_get_cache( - &self, - key: &str, - context: &Self::Context, - ) -> Result, Error> { - self.async_get_cache_with_similarity(key, context) - .await - .map(|lookup| lookup.value) - } -} - -/// Python stamps a similarity of `0.0` when there is no prompt or no document in the key's -/// scope, and the closest document's similarity even when it misses the threshold. -impl SemanticCache for ValkeySemanticCache -where - E: Embedder, - S: CacheCodec, - C: redis::ConnectionLike + Send + 'static, -{ - fn get_cache_with_similarity( - &self, - key: &str, - context: &Self::Context, - ) -> Result, Error> { - let Some(prompt) = prompt_from_context(context) else { - return Ok(SemanticLookup::miss(Some(0.0))); - }; - let embedding = self.embedder.embed(&prompt, context.metadata.as_ref())?; - let index = self.index_state(); - let lookup = self.connections.execute(|connection| { - search_document( - connection, - &index, - &scope_tag(key), - embedding_bytes(&embedding), - ) - })?; - self.decode(lookup) - } - - async fn async_get_cache_with_similarity( - &self, - key: &str, - context: &Self::Context, - ) -> Result, Error> { - let Some(prompt) = prompt_from_context(context) else { - return Ok(SemanticLookup::miss(Some(0.0))); - }; - let embedding = self - .embedder - .async_embed(&prompt, context.metadata.as_ref()) - .await?; - let index = self.index_state(); - let scope = scope_tag(key); - let lookup = Connections::run_blocking(Arc::clone(&self.connections), move |connection| { - search_document(connection, &index, &scope, embedding_bytes(&embedding)) - }) - .await?; - self.decode(lookup) - } -} diff --git a/litellm-rust/crates/cache-valkey-semantic/src/config.rs b/litellm-rust/crates/cache-valkey-semantic/src/config.rs deleted file mode 100644 index c417652c27b..00000000000 --- a/litellm-rust/crates/cache-valkey-semantic/src/config.rs +++ /dev/null @@ -1,8 +0,0 @@ -/// `ValkeySemanticCache.DEFAULT_VALKEY_INDEX_NAME`. -pub const DEFAULT_INDEX_NAME: &str = "litellm_semantic_cache_index"; - -#[derive(Clone, Debug, PartialEq)] -pub struct ValkeySemanticConfig { - pub similarity_threshold: f64, - pub index_name: String, -} diff --git a/litellm-rust/crates/cache-valkey-semantic/src/index.rs b/litellm-rust/crates/cache-valkey-semantic/src/index.rs deleted file mode 100644 index 3dfff32ff7c..00000000000 --- a/litellm-rust/crates/cache-valkey-semantic/src/index.rs +++ /dev/null @@ -1,117 +0,0 @@ -use std::sync::{Arc, Mutex}; - -use litellm_cache::Error; -use litellm_cache_redis::connection::ConnectionRef; - -use crate::search::value_text; - -/// The valkey-search index one cache writes to, with the dimension it was last ensured for. -#[derive(Clone)] -pub(crate) struct IndexState { - pub(crate) name: String, - pub(crate) prefix: String, - pub(crate) dimension: Arc>>, - pub(crate) similarity_threshold: f64, -} - -/// `_ensure_index_sync` / `_ensure_index_async`: create the TAG + HNSW index once per dimension, -/// and accept an existing index unless it reports a different dimension. -pub(crate) fn ensure_index( - connection: &mut ConnectionRef<'_>, - index: &IndexState, - dimension: usize, -) -> Result<(), Error> { - if index - .dimension - .lock()? - .is_some_and(|existing| existing == dimension) - { - return Ok(()); - } - let create = redis::cmd("FT.CREATE") - .arg(&index.name) - .arg("ON") - .arg("HASH") - .arg("PREFIX") - .arg(1) - .arg(&index.prefix) - .arg("SCHEMA") - .arg("litellm_cache_key") - .arg("TAG") - .arg("embedding") - .arg("VECTOR") - .arg("HNSW") - .arg(6) - .arg("TYPE") - .arg("FLOAT32") - .arg("DIM") - .arg(dimension) - .arg("DISTANCE_METRIC") - .arg("COSINE") - .query::(connection) - .map(|_| ()); - if let Err(error) = create { - if !index_exists(&error) { - return Err(Error::unavailable(error)); - } - let info = redis::cmd("FT.INFO") - .arg(&index.name) - .query::(connection) - .map_err(Error::unavailable)?; - if let Some(existing) = - index_dimension_from_info(&info).filter(|existing| *existing != dimension) - { - return Err(Error::unavailable(DimensionMismatch { - existing, - dimension, - })); - } - } - *index.dimension.lock()? = Some(dimension); - Ok(()) -} - -fn index_exists(error: &redis::RedisError) -> bool { - error.code().is_some() - && error - .detail() - .is_some_and(|detail| detail.to_ascii_lowercase().contains("already exists")) -} - -#[derive(Debug, thiserror::Error)] -#[error("index exists with dimension {existing}, not {dimension}")] -struct DimensionMismatch { - existing: usize, - dimension: usize, -} - -/// `_extract_index_dim`: flatten each attribute one level and read the value after -/// `dimensions`. -fn index_dimension_from_info(value: &redis::Value) -> Option { - let redis::Value::Array(values) = value else { - return None; - }; - let attributes = values.windows(2).find_map(|pair| { - (value_text(&pair[0]).as_deref() == Some("attributes")).then_some(&pair[1]) - })?; - let redis::Value::Array(fields) = attributes else { - return None; - }; - fields.iter().find_map(|field| { - let redis::Value::Array(values) = field else { - return None; - }; - let values = values - .iter() - .flat_map(|value| match value { - redis::Value::Array(values) => values.as_slice(), - _ => std::slice::from_ref(value), - }) - .collect::>(); - values.windows(2).find_map(|pair| { - (value_text(pair[0]).as_deref() == Some("dimensions")) - .then(|| value_text(pair[1]).and_then(|value| value.parse().ok())) - .flatten() - }) - }) -} diff --git a/litellm-rust/crates/cache-valkey-semantic/src/lib.rs b/litellm-rust/crates/cache-valkey-semantic/src/lib.rs deleted file mode 100644 index f2f62bc95bd..00000000000 --- a/litellm-rust/crates/cache-valkey-semantic/src/lib.rs +++ /dev/null @@ -1,7 +0,0 @@ -mod cache; -mod config; -mod index; -mod search; - -pub use cache::ValkeySemanticCache; -pub use config::{DEFAULT_INDEX_NAME, ValkeySemanticConfig}; diff --git a/litellm-rust/crates/cache-valkey-semantic/src/search.rs b/litellm-rust/crates/cache-valkey-semantic/src/search.rs deleted file mode 100644 index c5e4e748b58..00000000000 --- a/litellm-rust/crates/cache-valkey-semantic/src/search.rs +++ /dev/null @@ -1,161 +0,0 @@ -use std::time::Duration; - -use litellm_cache::{Error, semantic::SemanticLookup}; -use litellm_cache_redis::connection::ConnectionRef; -use sha2::{Digest, Sha256}; -use uuid::Uuid; - -use crate::index::{IndexState, ensure_index}; - -/// `_scope_tag`: valkey-search TAG fields cannot match arbitrary keys verbatim, so scopes are -/// the key's lowercase SHA-256. -pub(crate) fn scope_tag(key: &str) -> String { - let digest = Sha256::digest(key.as_bytes()); - digest.iter().map(|byte| format!("{byte:02x}")).collect() -} - -pub(crate) fn embedding_bytes(embedding: &[f32]) -> Vec { - embedding - .iter() - .flat_map(|value| value.to_le_bytes()) - .collect() -} - -/// `HSET` a fresh `:` document, then `EXPIRE` it when a TTL is set. -pub(crate) fn write_document( - connection: &mut ConnectionRef<'_>, - index: &IndexState, - scope: &str, - prompt: &str, - response: Vec, - vector: Vec, - ttl: Option, -) -> Result<(), Error> { - ensure_index(connection, index, vector.len() / size_of::())?; - let document = format!("{}{scope}:{}", index.prefix, Uuid::new_v4()); - let mut pipeline = redis::pipe(); - pipeline - .cmd("HSET") - .arg(&document) - .arg("litellm_cache_key") - .arg(scope) - .arg("prompt") - .arg(prompt) - .arg("response") - .arg(response) - .arg("embedding") - .arg(vector) - .ignore(); - if let Some(ttl) = ttl { - pipeline - .cmd("EXPIRE") - .arg(&document) - .arg(ttl.as_secs()) - .ignore(); - } - pipeline.query::<()>(connection).map_err(Error::unavailable) -} - -/// The KNN-1 search within `scope`: the closest document's similarity, and its stored response -/// when that similarity reaches the threshold. No document reads as a similarity of `0.0`. -pub(crate) fn search_document( - connection: &mut ConnectionRef<'_>, - index: &IndexState, - scope: &str, - vector: Vec, -) -> Result>, Error> { - ensure_index(connection, index, vector.len() / size_of::())?; - let query = - format!("(@litellm_cache_key:{{{scope}}})=>[KNN 1 @embedding $vec AS vector_distance]"); - let response = redis::cmd("FT.SEARCH") - .arg(&index.name) - .arg(query) - .arg("PARAMS") - .arg(2) - .arg("vec") - .arg(vector) - .arg("RETURN") - .arg(2) - .arg("response") - .arg("vector_distance") - .arg("DIALECT") - .arg(2) - .query::(connection) - .map_err(Error::unavailable)?; - let Some(fields) = search_fields(response)? else { - return Ok(SemanticLookup::miss(Some(0.0))); - }; - let field = |name: &str| { - fields - .iter() - .find_map(|(field, value)| (field == name).then(|| value.clone())) - .ok_or(Error::InvalidEntry(None)) - }; - let response = field("response")?; - let similarity = 1.0 - parse_f64(&field("vector_distance")?)?; - Ok(SemanticLookup { - value: (similarity >= index.similarity_threshold).then_some(response), - similarity: Some(similarity), - }) -} - -type SearchFields = Vec<(String, Vec)>; - -fn search_fields(value: redis::Value) -> Result, Error> { - let redis::Value::Array(values) = value else { - return Err(Error::InvalidEntry(None)); - }; - let total = parse_i64(values.first().ok_or(Error::InvalidEntry(None))?)?; - if total <= 0 || values.len() < 3 { - return Ok(None); - } - let redis::Value::Array(fields) = &values[2] else { - return Err(Error::InvalidEntry(None)); - }; - let (pairs, remainder) = fields.as_chunks::<2>(); - if !remainder.is_empty() { - return Err(Error::InvalidEntry(None)); - } - pairs - .iter() - .map(|pair| { - Ok(( - value_text(&pair[0]).ok_or(Error::InvalidEntry(None))?, - value_bytes(&pair[1])?, - )) - }) - .collect::, Error>>() - .map(Some) -} - -fn parse_i64(value: &redis::Value) -> Result { - value_text(value) - .ok_or(Error::InvalidEntry(None))? - .parse() - .map_err(Error::invalid_entry) -} - -fn parse_f64(value: &[u8]) -> Result { - std::str::from_utf8(value) - .map_err(Error::invalid_entry)? - .parse() - .map_err(Error::invalid_entry) -} - -pub(crate) fn value_text(value: &redis::Value) -> Option { - match value { - redis::Value::BulkString(bytes) => String::from_utf8(bytes.clone()).ok(), - redis::Value::SimpleString(value) => Some(value.clone()), - redis::Value::Int(value) => Some(value.to_string()), - _ => None, - } -} - -fn value_bytes(value: &redis::Value) -> Result, Error> { - match value { - redis::Value::BulkString(bytes) => Ok(bytes.clone()), - redis::Value::SimpleString(value) => Ok(value.as_bytes().to_vec()), - redis::Value::Int(value) => Ok(value.to_string().into_bytes()), - _ => Err(Error::InvalidEntry(None)), - } -} diff --git a/litellm-rust/crates/cache-valkey-semantic/tests/cache.rs b/litellm-rust/crates/cache-valkey-semantic/tests/cache.rs deleted file mode 100644 index 10e32c0183b..00000000000 --- a/litellm-rust/crates/cache-valkey-semantic/tests/cache.rs +++ /dev/null @@ -1,430 +0,0 @@ -mod support; - -use std::{ - sync::{Arc, Mutex}, - time::Duration, -}; - -use litellm_cache::{ - BaseCache, Error, JsonCodec, SemanticCacheContext, - semantic::{PreparedEmbedding, SemanticCache, SemanticLookup}, -}; -use litellm_cache_valkey_semantic::{ - DEFAULT_INDEX_NAME, ValkeySemanticCache, ValkeySemanticConfig, -}; -use redis_test::MockRedisConnection; -use rstest::{fixture, rstest}; -use serde_json::{Value, json}; -use support::{EmbedCalls, FakeEmbedder, RecordingConnection}; - -type Requests = Arc>>>; -type RecordingCache = ValkeySemanticCache, RecordingConnection>; - -const KEY_SCOPE: &str = "2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683"; - -struct Recording { - cache: RecordingCache, - requests: Requests, - calls: EmbedCalls, -} - -impl Recording { - fn text(&self) -> String { - self.requests - .lock() - .unwrap() - .iter() - .map(|request| String::from_utf8_lossy(request).into_owned()) - .collect::>() - .join("\n") - } -} - -fn config() -> ValkeySemanticConfig { - ValkeySemanticConfig { - similarity_threshold: 0.8, - index_name: "test".into(), - } -} - -fn recording(replies: impl IntoIterator>) -> Recording { - let connection = RecordingConnection::new(replies); - let requests = connection.requests(); - let embedder = FakeEmbedder::new(&[]); - let calls = Arc::clone(&embedder.calls); - Recording { - cache: ValkeySemanticCache::with_connection( - connection, - embedder, - JsonCodec::new(), - config(), - ), - requests, - calls, - } -} - -#[fixture] -fn entry() -> Value { - json!({"timestamp": 1.0, "response": {"answer": "ok"}}) -} - -#[fixture] -fn context() -> SemanticCacheContext { - SemanticCacheContext { - messages: Some(json!([{"role": "user", "content": "hello"}])), - metadata: Some(json!({"source": "test"})), - ..Default::default() - } -} - -fn ok() -> redis::RedisResult { - Ok(redis::Value::SimpleString("OK".into())) -} - -fn already_exists() -> redis::RedisResult { - Err(support::server_error("Index already exists")) -} - -fn bulk(value: &[u8]) -> redis::Value { - redis::Value::BulkString(value.to_vec()) -} - -fn search_hit(response: &[u8], distance: &str) -> redis::Value { - redis::Value::Array(vec![ - redis::Value::Int(1), - bulk(b"test:document"), - redis::Value::Array(vec![ - bulk(b"response"), - bulk(response), - bulk(b"vector_distance"), - bulk(distance.as_bytes()), - ]), - ]) -} - -fn encoded(value: &Value) -> Vec { - serde_json::to_vec(value).unwrap() -} - -/// `FT.INFO` with the vector field's dimension nested one level down, as valkey-search reports. -fn nested_dimension_info(dimension: i64) -> redis::Value { - redis::Value::Array(vec![ - redis::Value::SimpleString("attributes".into()), - redis::Value::Array(vec![redis::Value::Array(vec![ - redis::Value::SimpleString("embedding".into()), - redis::Value::Array(vec![ - redis::Value::SimpleString("dimensions".into()), - redis::Value::Int(dimension), - ]), - ])]), - ]) -} - -/// `FT.INFO` with `dimensions` as a sibling string of the identifier. -fn flat_dimension_info(dimension: &str) -> redis::Value { - redis::Value::Array(vec![ - redis::Value::SimpleString("attributes".into()), - redis::Value::Array(vec![redis::Value::Array(vec![ - redis::Value::SimpleString("identifier".into()), - redis::Value::SimpleString("embedding".into()), - redis::Value::Array(vec![ - redis::Value::SimpleString("dimensions".into()), - redis::Value::SimpleString(dimension.into()), - ]), - ])]), - ]) -} - -#[rstest] -#[case::string_content(json!([{"content": "hello"}]), None, Some("hello"))] -#[case::text_parts(json!([{"content": [{"text": "hello"}, {"text": " world"}]}]), None, Some("hello world"))] -#[case::non_object_parts_are_skipped(json!([{"content": ["raw", {"text": "hello"}]}]), None, Some("hello"))] -#[case::search_results(json!([{"search_results": [{"source": "s", "title": "t", "content": [{"text": "c"}], "citations": ["x"]}]}]), None, Some(r#"stc["x"]"#))] -#[case::responses_string_input(json!([]), Some(json!(" hello ")), Some("hello"))] -#[case::responses_item_input(json!([]), Some(json!([{"content": "first"}, {"text": "second"}])), Some("first\nsecond"))] -#[case::blank_input(json!([]), Some(json!(" ")), None)] -fn prompt_shapes_follow_redis_semantic_extraction( - #[case] messages: Value, - #[case] input: Option, - #[case] expected: Option<&str>, -) { - let recording = recording([ok(), Ok(redis::Value::Array(vec![redis::Value::Int(0)]))]); - let context = SemanticCacheContext { - messages: Some(messages), - input, - ..Default::default() - }; - - assert_eq!(recording.cache.get_cache("key", &context).unwrap(), None); - - let prompts = recording - .calls - .lock() - .unwrap() - .iter() - .map(|(prompt, _)| prompt.clone()) - .collect::>(); - assert_eq!( - prompts, - expected.into_iter().map(str::to_owned).collect::>() - ); - assert_eq!( - recording.requests.lock().unwrap().is_empty(), - expected.is_none() - ); -} - -#[rstest] -#[case::key("key", KEY_SCOPE)] -#[case::empty_key("", "e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855")] -fn documents_are_scoped_by_the_keys_sha256( - #[case] key: &str, - #[case] scope: &str, - entry: Value, - context: SemanticCacheContext, -) { - let recording = recording([ok()]); - - recording.cache.set_cache(key, entry, &context).unwrap(); - - let text = recording.text(); - assert!(text.contains(&format!("test:{scope}:"))); - assert!(text.contains(&format!("litellm_cache_key\r\n$64\r\n{scope}\r\n"))); -} - -#[rstest] -#[case::no_ttl(None, None)] -#[case::whole_seconds(Some(Duration::from_secs(5)), Some("5"))] -#[case::fractional_seconds_truncate(Some(Duration::from_millis(1900)), Some("1"))] -fn set_writes_hset_and_expires_only_with_a_ttl( - #[case] ttl: Option, - #[case] expire: Option<&str>, - entry: Value, - context: SemanticCacheContext, -) { - let recording = recording([ok()]); - - recording - .cache - .set_cache( - "key", - entry, - &SemanticCacheContext { - ttl, - ..context.clone() - }, - ) - .unwrap(); - - let text = recording.text(); - assert!(text.contains("FT.CREATE")); - assert!(text.contains("HSET")); - let expire_seconds = text - .split_once("EXPIRE\r\n") - .and_then(|(_, rest)| rest.split("\r\n").nth(3)); - assert_eq!(expire_seconds, expire); - assert_eq!( - *recording.calls.lock().unwrap(), - vec![("hello".to_owned(), context.metadata)] - ); -} - -#[rstest] -fn second_set_skips_create_after_dimension_is_cached(entry: Value, context: SemanticCacheContext) { - let recording = recording([ok()]); - - recording - .cache - .set_cache("key", entry.clone(), &context) - .unwrap(); - recording.cache.set_cache("key", entry, &context).unwrap(); - - let text = recording.text(); - assert_eq!(text.matches("FT.CREATE").count(), 1); - assert_eq!(text.matches("HSET").count(), 2); -} - -#[rstest] -#[case::nested_matching(nested_dimension_info(3), Ok(()))] -#[case::nested_mismatch( - nested_dimension_info(2), - Err("cache is unavailable: index exists with dimension 2, not 3") -)] -#[case::flat_matching(flat_dimension_info("3"), Ok(()))] -#[case::flat_mismatch( - flat_dimension_info("2"), - Err("cache is unavailable: index exists with dimension 2, not 3") -)] -#[case::unreported_dimension_is_accepted(redis::Value::Array(vec![]), Ok(()))] -fn existing_index_dimension_must_match_embedding( - #[case] info: redis::Value, - #[case] expected: Result<(), &str>, - entry: Value, - context: SemanticCacheContext, -) { - let recording = recording([already_exists(), Ok(info)]); - - let result = recording.cache.set_cache("key", entry, &context); - assert_eq!( - result.map_err(|error| litellm_error::Report::new(&error).to_string()), - expected.map_err(str::to_owned) - ); -} - -#[rstest] -#[case::create_failure(Err(redis::RedisError::from((redis::ErrorKind::Io, "boom"))))] -fn index_creation_failures_are_unavailable( - #[case] reply: redis::RedisResult, - entry: Value, - context: SemanticCacheContext, -) { - let recording = recording([reply]); - - assert!(matches!( - recording.cache.set_cache("key", entry, &context), - Err(Error::Unavailable(Some(_))) - )); -} - -#[rstest] -#[case::within_threshold(search_hit(&encoded(&entry()), "0.1"), Ok(Some(entry())))] -#[case::at_threshold(search_hit(&encoded(&entry()), "0.2"), Ok(Some(entry())))] -#[case::beyond_threshold(search_hit(&encoded(&entry()), "0.5"), Ok(None))] -#[case::zero_documents(redis::Value::Array(vec![redis::Value::Int(0)]), Ok(None))] -#[case::missing_response( - redis::Value::Array(vec![ - redis::Value::Int(1), - bulk(b"document"), - redis::Value::Array(vec![bulk(b"vector_distance"), bulk(b"0.1")]), - ]), - Err(Error::InvalidEntry(None)) -)] -#[case::unparsable_distance(search_hit(b"not-json", "abc"), Err(Error::InvalidEntry(None)))] -#[case::undecodable_response(search_hit(b"not-json", "0.1"), Err(Error::InvalidEntry(None)))] -fn get_applies_threshold_and_decodes_entry( - #[case] reply: redis::Value, - #[case] expected: Result, Error>, - context: SemanticCacheContext, -) { - let recording = recording([ok(), Ok(reply)]); - - let kind = |result: Result, Error>| { - result.map_err(|error| std::mem::discriminant(&error)) - }; - assert_eq!( - kind(recording.cache.get_cache("key", &context)), - kind(expected) - ); -} - -#[rstest] -#[case::hit(context(), Some(search_hit(&encoded(&entry()), "0.1")), Some(entry()), Some(1.0 - 0.1))] -#[case::below_threshold(context(), Some(search_hit(&encoded(&entry()), "0.5")), None, Some(1.0 - 0.5))] -#[case::no_results(context(), Some(redis::Value::Array(vec![redis::Value::Int(0)])), None, Some(0.0))] -#[case::no_prompt(SemanticCacheContext::default(), None, None, Some(0.0))] -#[tokio::test] -async fn lookup_reports_python_semantic_similarity( - #[case] context: SemanticCacheContext, - #[case] reply: Option, - #[case] value: Option, - #[case] similarity: Option, - #[values(false, true)] use_async: bool, -) { - let searched = reply.is_some(); - let recording = recording(reply.map_or_else(Vec::new, |reply| vec![ok(), Ok(reply)])); - - let lookup = if use_async { - recording - .cache - .async_get_cache_with_similarity("key", &context) - .await - } else { - recording.cache.get_cache_with_similarity("key", &context) - }; - - assert_eq!(lookup, Ok(SemanticLookup { value, similarity })); - assert_eq!(recording.text().contains("FT.SEARCH"), searched); -} - -#[rstest] -#[tokio::test] -async fn missing_prompt_does_not_touch_valkey(entry: Value) { - let cache = ValkeySemanticCache::with_connection( - MockRedisConnection::new([]).assert_all_commands_consumed(), - FakeEmbedder::new(&[]), - JsonCodec::new(), - config(), - ); - let context = SemanticCacheContext::default(); - - cache.set_cache("key", entry.clone(), &context).unwrap(); - assert_eq!(cache.get_cache("key", &context).unwrap(), None); - cache - .async_set_cache("key", entry, context.clone()) - .await - .unwrap(); - assert_eq!(cache.async_get_cache("key", &context).await.unwrap(), None); - assert_eq!(cache.get_ttl(&context), None); -} - -#[rstest] -fn with_embedder_shares_index_state_and_connections(entry: Value, context: SemanticCacheContext) { - let recording = recording([ok(), ok(), Ok(search_hit(&encoded(&entry), "0.1"))]); - recording - .cache - .set_cache("key", entry.clone(), &context) - .unwrap(); - - let prepared = recording - .cache - .with_embedder(PreparedEmbedding(vec![0.1, 0.2, 0.3])); - - assert_eq!(prepared.get_cache("key", &context).unwrap(), Some(entry)); - assert_eq!(recording.text().matches("FT.CREATE").count(), 1); -} - -#[rstest] -fn accessors_report_the_config() { - let recording = recording([]); - - assert_eq!(recording.cache.index_name(), "test"); - assert_eq!(recording.cache.similarity_threshold(), 0.8); - assert_eq!(DEFAULT_INDEX_NAME, "litellm_semantic_cache_index"); -} - -#[rstest] -#[tokio::test] -async fn async_set_and_get_use_shared_document_helpers( - entry: Value, - context: SemanticCacheContext, -) { - let recording = recording([ok(), ok(), ok(), Ok(search_hit(&encoded(&entry), "0.1"))]); - let context = SemanticCacheContext { - ttl: Some(Duration::from_millis(1900)), - ..context - }; - - recording - .cache - .async_set_cache("key", entry.clone(), context.clone()) - .await - .unwrap(); - assert_eq!( - recording - .cache - .async_get_cache("key", &context) - .await - .unwrap(), - Some(entry) - ); - - let text = recording.text(); - assert!(text.contains("FT.CREATE")); - assert!(text.contains("HSET")); - assert!(text.contains("EXPIRE")); - assert_eq!( - *recording.calls.lock().unwrap(), - vec![("hello".to_owned(), context.metadata.clone()); 2] - ); -} diff --git a/litellm-rust/crates/cache-valkey-semantic/tests/contract.rs b/litellm-rust/crates/cache-valkey-semantic/tests/contract.rs deleted file mode 100644 index 71081fca92b..00000000000 --- a/litellm-rust/crates/cache-valkey-semantic/tests/contract.rs +++ /dev/null @@ -1,62 +0,0 @@ -//! `overwrite_replaces` does not apply: like Python, every write is a new `:` -//! document, so a second write with the same prompt adds a tie instead of replacing the first. - -mod support; - -use litellm_cache::{JsonCodec, SemanticCacheContext, semantic::PreparedEmbedding}; -use litellm_cache_testing as contract; -use litellm_cache_valkey_semantic::{ - DEFAULT_INDEX_NAME, ValkeySemanticCache, ValkeySemanticConfig, -}; -use rstest::{fixture, rstest}; -use serde_json::{Value, json}; -use support::FakeSearch; - -type Cache = ValkeySemanticCache, FakeSearch>; - -const PREFIX: &str = "contract:"; - -#[fixture] -fn cache() -> Cache { - ValkeySemanticCache::with_connection( - FakeSearch::default(), - PreparedEmbedding(vec![0.6, 0.8]), - JsonCodec::new(), - ValkeySemanticConfig { - similarity_threshold: 0.9, - index_name: DEFAULT_INDEX_NAME.into(), - }, - ) -} - -#[fixture] -fn context() -> SemanticCacheContext { - SemanticCacheContext { - messages: Some(json!([{"role": "user", "content": "contract prompt"}])), - ..Default::default() - } -} - -#[rstest] -#[tokio::test] -async fn hit_and_miss(cache: Cache, context: SemanticCacheContext) { - contract::hit_and_miss(&cache, context, PREFIX, json!({"answer": 42})).await; -} - -#[rstest] -#[tokio::test] -async fn sync_async_equivalence(cache: Cache, context: SemanticCacheContext) { - contract::sync_async_equivalence(&cache, context, PREFIX, json!("first"), json!([2])).await; -} - -#[rstest] -#[tokio::test] -async fn pipeline_writes_every_entry(cache: Cache, context: SemanticCacheContext) { - contract::pipeline_writes_every_entry( - &cache, - context, - PREFIX, - vec![json!("a"), json!(2), json!({"c": true})], - ) - .await; -} diff --git a/litellm-rust/crates/cache-valkey-semantic/tests/support/mod.rs b/litellm-rust/crates/cache-valkey-semantic/tests/support/mod.rs deleted file mode 100644 index 2af05943c98..00000000000 --- a/litellm-rust/crates/cache-valkey-semantic/tests/support/mod.rs +++ /dev/null @@ -1,352 +0,0 @@ -#![allow(dead_code)] - -use std::{ - collections::{BTreeMap, HashMap, VecDeque}, - sync::{Arc, Mutex}, -}; - -use litellm_cache::{Error, semantic::Embedder}; -use serde_json::Value; - -pub type EmbedCalls = Arc)>>>; - -/// Embeds known prompts to fixed vectors, anything else to `[0.1, 0.2, 0.3]`, and records every -/// prompt with its metadata. -pub struct FakeEmbedder { - vectors: HashMap>, - pub calls: EmbedCalls, -} - -impl FakeEmbedder { - pub fn new(vectors: &[(&str, &[f32])]) -> Self { - Self { - vectors: vectors - .iter() - .map(|(prompt, vector)| ((*prompt).to_owned(), vector.to_vec())) - .collect(), - calls: EmbedCalls::default(), - } - } -} - -impl Embedder for FakeEmbedder { - fn embed(&self, prompt: &str, metadata: Option<&Value>) -> Result, Error> { - self.calls - .lock() - .unwrap() - .push((prompt.to_owned(), metadata.cloned())); - Ok(self - .vectors - .get(prompt) - .cloned() - .unwrap_or_else(|| vec![0.1, 0.2, 0.3])) - } - - async fn async_embed(&self, prompt: &str, metadata: Option<&Value>) -> Result, Error> { - self.embed(prompt, metadata) - } -} - -struct FakeIndex { - prefix: Vec, - dims: usize, - vector_field: String, -} - -#[derive(Default)] -struct SearchState { - indexes: HashMap, - hashes: BTreeMap, BTreeMap>>, -} - -/// An in-memory valkey-search speaking the `FT.*`, `HSET` and `EXPIRE` subset the semantic cache -/// sends, with exact cosine KNN over the hashes under an index prefix. -#[derive(Clone, Default)] -pub struct FakeSearch { - state: Arc>, -} - -impl FakeSearch { - fn run(&self, args: Vec>) -> redis::RedisResult { - let mut state = self.state.lock().unwrap(); - let text = |index: usize| String::from_utf8_lossy(&args[index]).into_owned(); - match text(0).to_uppercase().as_str() { - "FT.CREATE" => { - let name = text(1); - if state.indexes.contains_key(&name) { - return Err(server_error("Index already exists")); - } - let position = |token: &str| args.iter().position(|arg| arg == token.as_bytes()); - let prefix = args[position("PREFIX").unwrap() + 2].clone(); - let dims = text(position("DIM").unwrap() + 1).parse().unwrap(); - let vector_field = text(position("VECTOR").unwrap() - 1); - state.indexes.insert( - name, - FakeIndex { - prefix, - dims, - vector_field, - }, - ); - Ok(redis::Value::Okay) - } - "FT.INFO" => { - let index = state - .indexes - .get(&text(1)) - .ok_or_else(|| server_error("Unknown index name"))?; - Ok(index_info(index)) - } - "FT.DROPINDEX" => { - state.indexes.remove(&text(1)); - Ok(redis::Value::Okay) - } - "HSET" => { - let hash = state.hashes.entry(args[1].clone()).or_default(); - for pair in args[2..].chunks(2) { - hash.insert( - String::from_utf8_lossy(&pair[0]).into_owned(), - pair[1].clone(), - ); - } - Ok(redis::Value::Int(((args.len() - 2) / 2) as i64)) - } - "EXPIRE" => Ok(redis::Value::Int(i64::from( - state.hashes.contains_key(&args[1]), - ))), - "FT.SEARCH" => { - let index = state - .indexes - .get(&text(1)) - .ok_or_else(|| server_error("no such index"))?; - let query = text(2); - let tag = query_tag(&query); - let params = args.iter().position(|arg| arg == b"PARAMS").unwrap(); - let vector = floats(&args[params + 3]); - let best = state - .hashes - .iter() - .filter(|(key, _)| key.starts_with(&index.prefix)) - .filter(|(_, fields)| { - fields.get("litellm_cache_key").map(Vec::as_slice) == Some(tag.as_bytes()) - }) - .filter_map(|(key, fields)| { - let stored = floats(fields.get(&index.vector_field)?); - (stored.len() == index.dims) - .then(|| (key, fields, 1.0 - cosine(&vector, &stored))) - }) - .min_by(|left, right| left.2.total_cmp(&right.2)); - let Some((key, fields, distance)) = best else { - return Ok(redis::Value::Array(vec![redis::Value::Int(0)])); - }; - let mut reply = fields - .iter() - .filter(|(name, _)| **name != index.vector_field) - .flat_map(|(name, value)| [bulk(name.as_bytes()), bulk(value)]) - .collect::>(); - reply.extend([ - bulk(b"vector_distance"), - bulk(distance.to_string().as_bytes()), - ]); - Ok(redis::Value::Array(vec![ - redis::Value::Int(1), - bulk(key), - redis::Value::Array(reply), - ])) - } - "PING" => Ok(redis::Value::SimpleString("PONG".into())), - _ => Err(server_error("unsupported command")), - } - } -} - -impl redis::ConnectionLike for FakeSearch { - fn req_packed_command(&mut self, command: &[u8]) -> redis::RedisResult { - let mut commands = parse_commands(command); - self.run(commands.remove(0)) - } - - fn req_packed_commands( - &mut self, - commands: &[u8], - offset: usize, - count: usize, - ) -> redis::RedisResult> { - let replies = parse_commands(commands) - .into_iter() - .map(|args| self.run(args)) - .collect::>>()?; - Ok(replies.into_iter().skip(offset).take(count).collect()) - } - - fn get_db(&self) -> i64 { - 0 - } - - fn check_connection(&mut self) -> bool { - true - } - - fn is_open(&self) -> bool { - true - } -} - -pub fn server_error(reply: &str) -> redis::RedisError { - redis::parse_redis_value(format!("-{reply}\r\n").as_bytes()) - .expect("error reply") - .extract_error() - .expect_err("server error") -} - -fn bulk(bytes: &[u8]) -> redis::Value { - redis::Value::BulkString(bytes.to_vec()) -} - -fn index_info(index: &FakeIndex) -> redis::Value { - redis::Value::Array(vec![ - bulk(b"index_name"), - bulk(b"fake"), - bulk(b"attributes"), - redis::Value::Array(vec![ - redis::Value::Array(vec![ - bulk(b"identifier"), - bulk(b"litellm_cache_key"), - bulk(b"type"), - bulk(b"TAG"), - ]), - redis::Value::Array(vec![ - bulk(b"identifier"), - bulk(index.vector_field.as_bytes()), - bulk(b"type"), - bulk(b"VECTOR"), - bulk(b"index"), - redis::Value::Array(vec![ - bulk(b"dimensions"), - redis::Value::Int(index.dims as i64), - ]), - ]), - ]), - ]) -} - -/// The tag inside `@litellm_cache_key:{...}`, with query escapes removed. -fn query_tag(query: &str) -> String { - let start = query.find("@litellm_cache_key:{").unwrap() + "@litellm_cache_key:{".len(); - let mut tag = String::new(); - let mut characters = query[start..].chars(); - while let Some(character) = characters.next() { - match character { - '\\' => tag.extend(characters.next()), - '}' => break, - character => tag.push(character), - } - } - tag -} - -fn floats(bytes: &[u8]) -> Vec { - bytes - .as_chunks::<4>() - .0 - .iter() - .map(|chunk| f32::from_le_bytes(*chunk)) - .collect() -} - -fn cosine(left: &[f32], right: &[f32]) -> f64 { - let dot = left - .iter() - .zip(right) - .map(|(left, right)| f64::from(*left) * f64::from(*right)) - .sum::(); - let norm = |vector: &[f32]| { - vector - .iter() - .map(|value| f64::from(*value).powi(2)) - .sum::() - .sqrt() - }; - dot / (norm(left) * norm(right)) -} - -/// Splits a packed RESP request into each command's arguments. -fn parse_commands(mut bytes: &[u8]) -> Vec>> { - let line = |bytes: &mut &[u8]| { - let end = bytes - .windows(2) - .position(|window| window == b"\r\n") - .unwrap(); - let text = String::from_utf8(bytes[1..end].to_vec()).unwrap(); - *bytes = &bytes[end + 2..]; - text.parse::().unwrap() - }; - let mut commands = Vec::new(); - while !bytes.is_empty() { - let count = line(&mut bytes); - let mut args = Vec::with_capacity(count); - for _ in 0..count { - let length = line(&mut bytes); - args.push(bytes[..length].to_vec()); - bytes = &bytes[length + 2..]; - } - commands.push(args); - } - commands -} - -/// Records every packed request and answers from a script, `OK` once the script runs out. -pub struct RecordingConnection { - requests: Arc>>>, - replies: Mutex>>, -} - -impl RecordingConnection { - pub fn new(replies: impl IntoIterator>) -> Self { - Self { - requests: Arc::default(), - replies: Mutex::new(replies.into_iter().collect()), - } - } - - pub fn requests(&self) -> Arc>>> { - Arc::clone(&self.requests) - } - - fn reply(&self) -> redis::RedisResult { - self.replies - .lock() - .unwrap() - .pop_front() - .unwrap_or_else(|| Ok(redis::Value::SimpleString("OK".into()))) - } -} - -impl redis::ConnectionLike for RecordingConnection { - fn req_packed_command(&mut self, command: &[u8]) -> redis::RedisResult { - self.requests.lock().unwrap().push(command.to_vec()); - self.reply() - } - - fn req_packed_commands( - &mut self, - command: &[u8], - _offset: usize, - count: usize, - ) -> redis::RedisResult> { - self.requests.lock().unwrap().push(command.to_vec()); - (0..count).map(|_| self.reply()).collect() - } - - fn get_db(&self) -> i64 { - 0 - } - - fn check_connection(&mut self) -> bool { - true - } - - fn is_open(&self) -> bool { - true - } -} diff --git a/litellm-rust/crates/callbacks-legacy-python/python_contract.json b/litellm-rust/crates/callbacks-legacy-python/python_contract.json index f65516265c5..ab887bbc014 100644 --- a/litellm-rust/crates/callbacks-legacy-python/python_contract.json +++ b/litellm-rust/crates/callbacks-legacy-python/python_contract.json @@ -33,6 +33,17 @@ "api_key", "additional_args" ], + "record_response": [ + "logger", + "status", + "headers", + "body" + ], + "record_api_window": [ + "logger", + "start", + "end" + ], "defers_async_logging": [ "logger" ], @@ -91,6 +102,13 @@ "logger", "head" ], + "stamp_stream_head": [ + "head", + "logger", + "kwargs", + "start_time", + "end_time" + ], "stream_success": [ "logger", "url_route", diff --git a/litellm-rust/crates/callbacks-legacy-python/src/adapter.rs b/litellm-rust/crates/callbacks-legacy-python/src/adapter.rs index 9431b9d1326..1bb84184e4c 100644 --- a/litellm-rust/crates/callbacks-legacy-python/src/adapter.rs +++ b/litellm-rust/crates/callbacks-legacy-python/src/adapter.rs @@ -57,6 +57,8 @@ pub struct LegacyLogging { asynchronous: bool, internal: bool, cache_key: Option, + /// When the provider request went out, until its window is recorded (Messages only). + api_started: Option, } fn datetime(py: Python<'_>, epoch_seconds: f64) -> PyResult> { @@ -87,6 +89,60 @@ impl LegacyLogging { asynchronous, internal: false, cache_key: None, + api_started: None, + } + } + + /// The kwargs `Logging.update_from_kwargs` sees. Python's Messages handler takes `metadata` as + /// its own argument, so the logger never sees the caller's raw metadata, only the validated + /// request metadata merged in through `litellm_params`. Python updates the logger once, before + /// the call; the refresh once the result is ready leaves out `litellm_metadata` too, so the + /// logged metadata is not rebuilt from what the call wrote into it since. + fn logging_kwargs<'py>(&self, py: Python<'py>, refresh: bool) -> PyResult> { + let kwargs = self.call.kwargs().bind(py).copy()?; + if self.operation != LoggingOperation::Messages { + return Ok(kwargs); + } + let consumed: &[&str] = if refresh { + &["metadata", "litellm_metadata"] + } else { + &["metadata"] + }; + for name in consumed { + if kwargs.contains(name)? { + kwargs.del_item(name)?; + } + } + Ok(kwargs) + } + + /// Python's Messages handler hands the logger its request params, validated `metadata` + /// included, as `litellm_params`, beside the `aanthropic_messages` call flag. + fn logged_request_params( + &self, + context: &RequestContext, + ) -> Option> { + if self.operation != LoggingOperation::Messages { + return None; + } + let mut params = context + .optional_params + .as_object() + .cloned() + .unwrap_or_default(); + params.insert( + "aanthropic_messages".to_owned(), + Value::Bool(self.asynchronous), + ); + Some(params) + } + + /// Python times the provider exchange inside the async `AsyncHTTPHandler.post`; its sync + /// client is untimed. + fn close_api_window(&mut self, py: Python<'_>, end: f64) -> PyResult<()> { + match self.api_started.take() { + Some(start) => self.logger()?.record_api_window(py, start, end), + None => Ok(()), } } @@ -111,6 +167,16 @@ impl LegacyLogging { } } + /// The key `pre_call` logs. Python's Messages handler logs an empty string, never the key. + fn logged_api_key<'a>(&self, context: &'a RequestContext) -> Option<&'a str> { + match self.operation { + LoggingOperation::Messages => Some(""), + LoggingOperation::Completion | LoggingOperation::Responses | LoggingOperation::Ocr => { + context.api_key.as_ref().map(|api_key| api_key.expose()) + } + } + } + fn stream_billing(&self) -> Option { match self.operation { LoggingOperation::Messages => Some(PassThroughStream { @@ -377,7 +443,13 @@ impl LegacyLogging { context: &RequestContext, ) -> PyResult>> { let logger = self.logger()?; - logger.update_from_kwargs(py, self.call.kwargs(), &wire, context)?; + logger.update_from_kwargs( + py, + &self.logging_kwargs(py, false)?, + &wire, + context, + self.logged_request_params(context).as_ref(), + )?; let body = to_py(py, &wire.body)? .into_bound(py) .cast_into::()?; @@ -400,11 +472,14 @@ impl LegacyLogging { self.logger()?.pre_call( py, self.input_description(), - context.api_key.as_ref().map(|api_key| api_key.expose()), + self.logged_api_key(context), &body, &headers, &wire.url, )?; + if self.operation == LoggingOperation::Messages && self.asynchronous { + self.api_started = Some(epoch_seconds()); + } let headers = headers .iter() .map(|(name, value)| Ok((name.extract::()?, value.extract::()?))) @@ -455,7 +530,7 @@ impl LegacyLogging { py, ( &logger, - self.call.kwargs(), + self.logging_kwargs(py, true)?, &facts.provider.model, logger.getattr("optional_params")?, params, @@ -483,6 +558,16 @@ impl LegacyLogging { py: Python<'_>, raw: &RawResponse, ) -> PyResult> { + if self.operation == LoggingOperation::Messages { + // Python's Messages handler never calls `post_call` at receipt: it stores the raw + // response, and logging replays it through `AnthropicConfig.transform_response`. + self.close_api_window(py, epoch_seconds())?; + if let Some(head) = &raw.head { + self.logger()? + .record_response(py, head.status, &head.headers, &raw.body)?; + } + return Ok(HookStep::Ready(())); + } let api_key = self .request .as_ref() @@ -522,6 +607,9 @@ impl LegacyLogging { ) -> PyResult> { self.end = Some(datetime(py, timing.end_time)?); self.error = Some(error.clone_ref(py).into_value(py)); + if self.logger.is_some() { + self.close_api_window(py, timing.end_time)?; + } if self.stream.is_some() { return self.stream_failure(py); } @@ -543,6 +631,20 @@ impl LegacyLogging { head.bind(py).set_item("cache_key", key)?; head.bind(py).set_item("cache_hit", true)?; } + self.close_api_window(py, epoch_seconds())?; + if self.operation == LoggingOperation::Messages { + // Python's `@client` stamps the call metadata onto the stream it hands back. + Streaming::StampHead.call( + py, + ( + head.bind(py), + self.logger()?.object(py), + self.call.kwargs(), + &self.start, + datetime(py, epoch_seconds())?, + ), + )?; + } Streaming::Opened.call(py, (self.logger()?.object(py), head.bind(py)))?; self.stream = Some(DeliveredStream { chunks: PyList::empty(py).unbind(), @@ -1117,9 +1219,7 @@ assert logger.update['custom_llm_provider'] == 'edenai', logger.update let step = logging .before_provider_request(py, Box::new(wire), context) .unwrap(); - let raw = RawResponse { - body: "raw response".into(), - }; + let raw = RawResponse::new("raw response".into()); assert!(matches!( logging .on_event( @@ -1869,9 +1969,10 @@ assert logger.calls[1][1] is response py, &locals, c" -assert logger.names() == ['stream_opened', 'stream_success'], logger.calls +assert logger.names() == ['stamp_stream_head', 'stream_opened', 'stream_success'], logger.calls assert logger.calls[0][1] is head -chunks = logger.calls[1][1] +assert logger.calls[1][1] is head +chunks = logger.calls[2][1] assert len(chunks) == 2 assert chunks[0] is first assert chunks[1] is last diff --git a/litellm-rust/crates/callbacks-legacy-python/src/callbacks.rs b/litellm-rust/crates/callbacks-legacy-python/src/callbacks.rs index f185f21a9c3..1951c9ebfb4 100644 --- a/litellm-rust/crates/callbacks-legacy-python/src/callbacks.rs +++ b/litellm-rust/crates/callbacks-legacy-python/src/callbacks.rs @@ -5,6 +5,7 @@ use litellm_host::interceptors::{RequestContext, WireRequest}; use litellm_host_python::to_py; use pyo3::{exceptions::PyBaseException, prelude::*, types::PyDict}; +use serde_json::Value; use crate::logger::PythonLogger; use crate::python::{Logging, Wrapper}; @@ -15,9 +16,10 @@ pub trait LegacyCallbacks { fn update_from_kwargs( &self, py: Python<'_>, - kwargs: &Py, + kwargs: &Bound<'_, PyDict>, wire: &WireRequest, context: &RequestContext, + request_params: Option<&serde_json::Map>, ) -> PyResult<()>; /// `Logging.pre_call`. @@ -31,6 +33,20 @@ pub trait LegacyCallbacks { url: &str, ) -> PyResult<()>; + /// Records the provider's raw HTTP response on the logger, as Python's Messages handler + /// does with `httpx_response` and `response_headers`. + fn record_response( + &self, + py: Python<'_>, + status: u16, + headers: &[(String, String)], + body: &str, + ) -> PyResult<()>; + + /// Records one provider HTTP exchange's window, as Python's timed `AsyncHTTPHandler.post` + /// does with `llm_api_duration_ms` and the metadata's `llm_api_timing_windows`. + fn record_api_window(&self, py: Python<'_>, start: f64, end: f64) -> PyResult<()>; + /// `Logging.post_call`. fn post_call( &self, @@ -83,12 +99,13 @@ impl LegacyCallbacks for PythonLogger { fn update_from_kwargs( &self, py: Python<'_>, - kwargs: &Py, + kwargs: &Bound<'_, PyDict>, wire: &WireRequest, context: &RequestContext, + request_params: Option<&serde_json::Map>, ) -> PyResult<()> { let secret_fields: Vec<&str> = context.secret_fields.iter().map(String::as_str).collect(); - let redacted_kwargs = redact(py, kwargs.bind(py), &secret_fields)?; + let redacted_kwargs = redact(py, kwargs, &secret_fields)?; let optional_params = redact( py, &to_py(py, &context.optional_params)? @@ -97,23 +114,23 @@ impl LegacyCallbacks for PythonLogger { &secret_fields, )?; let params = PyDict::new(py); - params.set_item( - "litellm_call_id", - kwargs.bind(py).get_item("litellm_call_id")?, - )?; + params.set_item("litellm_call_id", kwargs.get_item("litellm_call_id")?)?; params.set_item("api_base", &wire.url)?; for name in ["logger_fn", "litellm_request_debug"] { - if let Some(value) = kwargs.bind(py).get_item(name)? { + if let Some(value) = kwargs.get_item(name)? { params.set_item(name, value)?; } } for name in custom_pricing_fields(py)? { - if let Some(value) = kwargs.bind(py).get_item(&name)? + if let Some(value) = kwargs.get_item(&name)? && !value.is_none() { params.set_item(name, value)?; } } + for (name, value) in request_params.into_iter().flatten() { + params.set_item(name, to_py(py, value)?)?; + } Logging::Update.call( py, ( @@ -145,6 +162,22 @@ impl LegacyCallbacks for PythonLogger { Ok(()) } + fn record_response( + &self, + py: Python<'_>, + status: u16, + headers: &[(String, String)], + body: &str, + ) -> PyResult<()> { + Logging::RecordResponse.call(py, (self.object(py), status, headers.to_vec(), body))?; + Ok(()) + } + + fn record_api_window(&self, py: Python<'_>, start: f64, end: f64) -> PyResult<()> { + Logging::RecordApiWindow.call(py, (self.object(py), start, end))?; + Ok(()) + } + fn post_call( &self, py: Python<'_>, diff --git a/litellm-rust/crates/callbacks-legacy-python/src/python.rs b/litellm-rust/crates/callbacks-legacy-python/src/python.rs index 6f1ee9dfd78..6d910d35f53 100644 --- a/litellm-rust/crates/callbacks-legacy-python/src/python.rs +++ b/litellm-rust/crates/callbacks-legacy-python/src/python.rs @@ -44,6 +44,10 @@ pub(crate) enum Logging { PreCall, #[strum(serialize = "post_call")] PostCall, + #[strum(serialize = "record_response")] + RecordResponse, + #[strum(serialize = "record_api_window")] + RecordApiWindow, #[strum(serialize = "defers_async_logging")] DefersAsync, #[strum(serialize = "defer_success")] @@ -77,6 +81,8 @@ pub(crate) enum DeploymentHooks { pub(crate) enum Streaming { #[strum(serialize = "stream_opened")] Opened, + #[strum(serialize = "stamp_stream_head")] + StampHead, #[strum(serialize = "stream_success")] Success, #[strum(serialize = "stream_failure")] diff --git a/litellm-rust/crates/callbacks-legacy-python/src/test_support.rs b/litellm-rust/crates/callbacks-legacy-python/src/test_support.rs index 093ce60e510..8acfa7a898b 100644 --- a/litellm-rust/crates/callbacks-legacy-python/src/test_support.rs +++ b/litellm-rust/crates/callbacks-legacy-python/src/test_support.rs @@ -65,6 +65,12 @@ FAKES = { 'post_call': lambda logger, original_response, api_key, additional_args: logger.post_call( original_response, api_key, additional_args ), + 'record_response': lambda logger, status, headers, body: logger.model_call_details.update( + response_headers=dict(headers) + ), + 'record_api_window': lambda logger, start, end: logger.model_call_details.update( + llm_api_duration_ms=(end - start) * 1000 + ), 'defers_async_logging': lambda logger: bool(getattr(logger, '_defer_async_logging', False)), 'defer_success': lambda logger, pending: setattr(logger, '_native_pending_logging', pending), 'sync_success_for_async_call': lambda logger, response, start, end: logger.handle_sync_success_callbacks_for_async_calls( @@ -85,6 +91,7 @@ FAKES = { ), 'after_deployment_failure': lambda kwargs, error, call_type: kwargs['logger'].hook('failure', error, call_type), 'stream_opened': lambda logger, head: logger.record('stream_opened', head), + 'stamp_stream_head': lambda head, logger, kwargs, start, end: logger.record('stamp_stream_head', head), 'stream_success': lambda logger, url_route, endpoint_type, request_body, chunks, start, end, first_chunk: logger.record( 'stream_success', list(chunks) ), diff --git a/litellm-rust/crates/cost/src/price.rs b/litellm-rust/crates/cost/src/price.rs index 12cec683748..70f6016780c 100644 --- a/litellm-rust/crates/cost/src/price.rs +++ b/litellm-rust/crates/cost/src/price.rs @@ -151,6 +151,8 @@ pub enum Uplift { Residency(Residency), /// Vertex non-global endpoint, from `regional_endpoint_uplift_multiplier` NonGlobalEndpoint, + /// OpenAI FedRAMP endpoint (gov.api.openai.com), from `fedramp_uplift_multiplier` + FedrampEndpoint, /// Anthropic `speed: fast`, from `provider_specific_entry.fast` Speed(Speed), /// Anthropic and Bedrock geo, from `provider_specific_entry.`, lowercased as on main diff --git a/litellm-rust/crates/host-http/tests/serve.rs b/litellm-rust/crates/host-http/tests/serve.rs index 2ba39ad4cd2..fd1a8940b33 100644 --- a/litellm-rust/crates/host-http/tests/serve.rs +++ b/litellm-rust/crates/host-http/tests/serve.rs @@ -215,9 +215,7 @@ async fn projection_custom_operations_and_hooks_feed_the_http_response(intercept ) .await?; route_hooks - .after_provider_response(RawResponse { - body: wire.url.clone(), - }) + .after_provider_response(RawResponse::new(wire.url.clone())) .await?; Ok(CallOutput::Complete(Bytes::from(wire.url))) }, @@ -501,9 +499,7 @@ async fn hook_rejection_stops_execution_and_is_reported_once( move |_, _, route_hooks, _observations| async move { if event { route_hooks - .after_provider_response(RawResponse { - body: "response".into(), - }) + .after_provider_response(RawResponse::new("response".into())) .await?; } else { route_hooks @@ -637,9 +633,7 @@ async fn unary_calls_use_into_response_after_hooks_and_before_success(intercepto ) .await?; route_hooks - .after_provider_response(RawResponse { - body: wire.url.clone(), - }) + .after_provider_response(RawResponse::new(wire.url.clone())) .await?; Ok(CallOutput::Complete(json!({"url": wire.url}))) }, @@ -689,7 +683,7 @@ async fn unary_failure_preserves_the_error_without_converting( None, |_, _, route_hooks, _observations| async move { route_hooks - .after_provider_response(RawResponse { body: "raw".into() }) + .after_provider_response(RawResponse::new("raw".into())) .await?; Err(TestError::Provider) }, diff --git a/litellm-rust/crates/host-native/tests/driver.rs b/litellm-rust/crates/host-native/tests/driver.rs index c41c1e5a43b..44c30234328 100644 --- a/litellm-rust/crates/host-native/tests/driver.rs +++ b/litellm-rust/crates/host-native/tests/driver.rs @@ -170,9 +170,7 @@ fn dispatching_call() -> TestMachine { ) .await?; route_hooks - .after_provider_response(RawResponse { - body: wire.url.clone(), - }) + .after_provider_response(RawResponse::new(wire.url.clone())) .await?; Ok(CallOutput::Complete(wire.url)) }, @@ -660,9 +658,7 @@ async fn response_interception_waits_and_can_reject_after_observation(#[case] re "input", Some(sender), |_, _, interceptors, observers| async move { - let raw = RawResponse { - body: "provider response".into(), - }; + let raw = RawResponse::new("provider response".into()); observers.unwrap().emit(CallEvent::Execution( ExecutionEvent::ProviderResponseReceived { raw: raw.clone() }, )); diff --git a/litellm-rust/crates/host-python/tests/support/mod.rs b/litellm-rust/crates/host-python/tests/support/mod.rs index 003fce74309..15e864c0718 100644 --- a/litellm-rust/crates/host-python/tests/support/mod.rs +++ b/litellm-rust/crates/host-python/tests/support/mod.rs @@ -467,7 +467,7 @@ pub fn success_machine() -> MachineFactory { .before_provider_request(wire(), context()) .await?; host.interceptors - .after_provider_response(RawResponse { body: "raw".into() }) + .after_provider_response(RawResponse::new("raw".into())) .await?; Ok(format!("{projected}|{signed}|{}", wire.url)) }) diff --git a/litellm-rust/crates/host/src/interceptors.rs b/litellm-rust/crates/host/src/interceptors.rs index 39af7c410e0..9398ea4bad6 100644 --- a/litellm-rust/crates/host/src/interceptors.rs +++ b/litellm-rust/crates/host/src/interceptors.rs @@ -28,6 +28,28 @@ pub struct RequestContext { #[derive(Clone, Debug, PartialEq, Eq)] pub struct RawResponse { pub body: String, + /// The provider's HTTP status and headers, when the route forwards them to logging. + pub head: Option, +} + +#[derive(Clone, Debug, PartialEq, Eq)] +pub struct ResponseHead { + pub status: u16, + pub headers: Vec<(String, String)>, +} + +impl RawResponse { + pub fn new(body: String) -> Self { + Self { body, head: None } + } + + #[must_use] + pub fn with_head(self, head: ResponseHead) -> Self { + Self { + head: Some(head), + ..self + } + } } #[derive(Clone, Debug, PartialEq, Eq)] @@ -186,7 +208,7 @@ mod tests { .await?; Interceptors::after_provider_response( &channel.interceptors, - RawResponse { body: "raw".into() }, + RawResponse::new("raw".into()), ) .await?; Ok((sent, ())) diff --git a/litellm-rust/crates/host/tests/observation.rs b/litellm-rust/crates/host/tests/observation.rs index 22872047d81..fba85b63bea 100644 --- a/litellm-rust/crates/host/tests/observation.rs +++ b/litellm-rust/crates/host/tests/observation.rs @@ -74,9 +74,7 @@ fn snapshots_do_not_retain_runtime_objects(capacity: NonZeroUsize, #[case] faile #[rstest] fn provider_snapshots_own_the_response_body(capacity: NonZeroUsize) { - let mut raw = RawResponse { - body: "provider response".into(), - }; + let mut raw = RawResponse::new("provider response".into()); let event: CallEvent<(), (), &RawResponse> = CallEvent::Execution(ExecutionEvent::ProviderResponseReceived { raw: &raw }); let expected = raw.clone(); diff --git a/litellm-rust/crates/http/src/error.rs b/litellm-rust/crates/http/src/error.rs index 29c8b988c0b..7078d4aba2a 100644 --- a/litellm-rust/crates/http/src/error.rs +++ b/litellm-rust/crates/http/src/error.rs @@ -58,8 +58,20 @@ pub(crate) enum Repr { Network(#[source] reqwest::Error), #[error("upstream request timed out")] Timeout(#[source] reqwest::Error), + /// No bytes arrived within the read timeout, which the caller enforces per read; `body` says + /// the response head had already arrived. + #[error("upstream request timed out")] + ReadTimeout { + #[source] + elapsed: Elapsed, + body: bool, + }, #[error("upstream request failed with status {status}: {body}")] - Status { status: u16, body: UpstreamBody }, + Status { + status: u16, + body: UpstreamBody, + headers: Vec<(String, String)>, + }, #[error("invalid WebSocket URL")] WebSocketUrl(#[source] url::ParseError), @@ -136,13 +148,59 @@ impl Repr { impl Error { pub fn upstream(status: u16, body: String) -> Self { + Self::upstream_with_headers(status, body, Vec::new()) + } + + /// An upstream failure that keeps the provider's response headers (`retry-after`, + /// `request-id`) for the caller. + pub fn upstream_with_headers( + status: u16, + body: String, + headers: Vec<(String, String)>, + ) -> Self { Repr::Status { status, body: UpstreamBody(body), + headers, } .into() } + /// The provider's response headers on an upstream failure; empty for every other error. + pub fn upstream_headers(&self) -> &[(String, String)] { + match &*self.0 { + Repr::Status { headers, .. } => headers, + _ => &[], + } + } + + /// A timeout reached before the connection was established, as opposed to while reading. + pub fn is_connect_timeout(&self) -> bool { + matches!(&*self.0, Repr::Timeout(error) if error.is_connect()) + } + + /// A read the caller timed itself (httpx's per-read timeout) ran out. + pub fn read_timeout(elapsed: Elapsed) -> Self { + Repr::ReadTimeout { + elapsed, + body: false, + } + .into() + } + + /// A read of the response body the caller timed itself ran out, after the head arrived. + pub fn body_read_timeout(elapsed: Elapsed) -> Self { + Repr::ReadTimeout { + elapsed, + body: true, + } + .into() + } + + pub fn is_body_read_timeout(&self) -> bool { + matches!(&*self.0, Repr::ReadTimeout { body: true, .. }) + } + pub fn computed_header(name: impl Into) -> Self { Repr::ComputedHeader(name.into()).into() } @@ -169,6 +227,7 @@ impl Error { match &*self.0 { Repr::Network(_) | Repr::Timeout(_) + | Repr::ReadTimeout { .. } | Repr::Status { .. } | Repr::Handshake(_) | Repr::HandshakeTimeout(_) @@ -227,6 +286,7 @@ impl Error { | Repr::Connect(_) | Repr::Network(_) | Repr::Timeout(_) + | Repr::ReadTimeout { .. } | Repr::Status { .. } | Repr::Handshake(_) | Repr::HandshakeTimeout(_) @@ -259,6 +319,7 @@ impl Error { | Repr::Connect(_) | Repr::Network(_) | Repr::Timeout(_) + | Repr::ReadTimeout { .. } | Repr::Status { .. } | Repr::WebSocketUrl(_) | Repr::WebSocketScheme(_) @@ -295,6 +356,7 @@ impl Error { | Repr::Connect(_) | Repr::Network(_) | Repr::Timeout(_) + | Repr::ReadTimeout { .. } | Repr::Status { .. } | Repr::WebSocketUrl(_) | Repr::WebSocketScheme(_) @@ -333,6 +395,7 @@ impl Error { | Repr::Signature(_) | Repr::Network(_) | Repr::Timeout(_) + | Repr::ReadTimeout { .. } | Repr::Status { .. } | Repr::WebSocketUrl(_) | Repr::WebSocketScheme(_) @@ -356,7 +419,10 @@ impl Error { pub fn is_timeout(&self) -> bool { match &*self.0 { - Repr::Timeout(_) | Repr::HandshakeTimeout(_) | Repr::DownloadTimeout(_) => true, + Repr::Timeout(_) + | Repr::ReadTimeout { .. } + | Repr::HandshakeTimeout(_) + | Repr::DownloadTimeout(_) => true, Repr::Read { .. } | Repr::InvalidPem { .. } | Repr::Client(_) @@ -392,7 +458,7 @@ impl Error { pub fn upstream_response(&self) -> Option<(u16, &str)> { match &*self.0 { - Repr::Status { status, body } => Some((*status, &body.0)), + Repr::Status { status, body, .. } => Some((*status, &body.0)), Repr::Read { .. } | Repr::InvalidPem { .. } | Repr::Client(_) @@ -408,6 +474,7 @@ impl Error { | Repr::Connect(_) | Repr::Network(_) | Repr::Timeout(_) + | Repr::ReadTimeout { .. } | Repr::WebSocketUrl(_) | Repr::WebSocketScheme(_) | Repr::WebSocketSchemeRewrite(_) @@ -431,7 +498,7 @@ impl Error { pub fn status(&self) -> Option { match &*self.0 { Repr::Status { status, .. } | Repr::DownloadStatus(status) => Some(*status), - Repr::Timeout(_) | Repr::DownloadTimeout(_) => Some(408), + Repr::Timeout(_) | Repr::ReadTimeout { .. } | Repr::DownloadTimeout(_) => Some(408), Repr::Read { .. } | Repr::InvalidPem { .. } | Repr::Client(_) @@ -482,6 +549,7 @@ impl Error { | Repr::Connect(_) | Repr::Network(_) | Repr::Timeout(_) + | Repr::ReadTimeout { .. } | Repr::Status { .. } | Repr::WebSocketUrl(_) | Repr::WebSocketScheme(_) diff --git a/litellm-rust/crates/inference-chat/src/handler.rs b/litellm-rust/crates/inference-chat/src/handler.rs index f948e8fffaf..cdcc3e911b9 100644 --- a/litellm-rust/crates/inference-chat/src/handler.rs +++ b/litellm-rust/crates/inference-chat/src/handler.rs @@ -108,7 +108,7 @@ pub(super) async fn execute( if !status.is_success() { return Err(litellm_http::Error::upstream(status.as_u16(), text).into()); } - let raw = RawResponse { body: text.clone() }; + let raw = RawResponse::new(text.clone()); if let Some(observers) = observers { observers.emit(litellm_host::lifecycle::CallEvent::Execution( ExecutionEvent::ProviderResponseReceived { raw: raw.clone() }, diff --git a/litellm-rust/crates/inference-messages/Cargo.toml b/litellm-rust/crates/inference-messages/Cargo.toml index ac52cb65a0d..0c5be52550d 100644 --- a/litellm-rust/crates/inference-messages/Cargo.toml +++ b/litellm-rust/crates/inference-messages/Cargo.toml @@ -24,6 +24,7 @@ litellm-tracing.workspace = true reqwest.workspace = true serde.workspace = true serde_json = { workspace = true, features = ["preserve_order"] } +tokio.workspace = true tracing.workspace = true [dev-dependencies] @@ -34,5 +35,4 @@ litellm-host-native.workspace = true litellm-http = { workspace = true, features = ["test-support"] } litellm-inference-testing.workspace = true rstest.workspace = true -tokio.workspace = true wiremock.workspace = true diff --git a/litellm-rust/crates/inference-messages/src/common_utils.rs b/litellm-rust/crates/inference-messages/src/common_utils.rs index a57eca1c6a9..e5ece2837d8 100644 --- a/litellm-rust/crates/inference-messages/src/common_utils.rs +++ b/litellm-rust/crates/inference-messages/src/common_utils.rs @@ -35,6 +35,14 @@ impl MessagesProvider { pub(crate) fn config(self) -> &'static dyn BaseMessagesConfig { self.config } + + /// Python's `MESSAGES_SERVICE_TIER_PROVIDERS`: everyone else has `service_tier` dropped. + pub(crate) fn accepts_service_tier(self) -> bool { + matches!( + self.provider, + LlmProviders::Anthropic | LlmProviders::AzureAi | LlmProviders::BedrockMantle + ) + } } /// Python's `get_provider_anthropic_messages_config`: Vertex AI serves only its Claude @@ -119,3 +127,69 @@ mod tests { ); } } + +/// Python's `_merge_messages_header_sources`: later sources win per header name, except +/// `anthropic-beta` (any casing), whose values from every source are unioned, deduplicated and +/// sorted into one lowercase `anthropic-beta` entry. +pub fn merge_messages_header_sources( + sources: impl IntoIterator>, +) -> Map { + let mut merged = Map::new(); + let mut betas = std::collections::BTreeSet::new(); + for (name, value) in sources.into_iter().flatten() { + if !name.eq_ignore_ascii_case("anthropic-beta") { + merged.insert(name, value); + continue; + } + let values: Vec<&str> = match &value { + Value::String(text) => vec![text.as_str()], + Value::Array(entries) => entries.iter().filter_map(Value::as_str).collect(), + _ => Vec::new(), + }; + betas.extend( + values + .iter() + .flat_map(|value| value.split(',')) + .map(str::trim) + .filter(|beta| !beta.is_empty()) + .map(str::to_owned), + ); + } + if !betas.is_empty() { + merged.insert( + "anthropic-beta".to_owned(), + Value::String(betas.into_iter().collect::>().join(",")), + ); + } + merged +} + +#[cfg(test)] +mod merge_tests { + use serde_json::{Map, Value, json}; + + use super::merge_messages_header_sources; + + fn map(value: Value) -> Map { + value.as_object().cloned().unwrap() + } + + #[test] + fn later_sources_win_except_anthropic_beta_which_is_unioned_and_sorted() { + let merged = merge_messages_header_sources([ + map(json!({"x-a": "1", "anthropic-beta": "b-2, a-1"})), + map(json!({"x-a": "2", "Anthropic-Beta": ["c-3", 7, "a-1"]})), + map(json!({"anthropic-beta": 5})), + ]); + assert_eq!( + Value::Object(merged), + json!({"x-a": "2", "anthropic-beta": "a-1,b-2,c-3"}) + ); + } + + #[test] + fn no_beta_values_leave_no_beta_header() { + let merged = merge_messages_header_sources([map(json!({"anthropic-beta": ""}))]); + assert!(merged.is_empty()); + } +} diff --git a/litellm-rust/crates/inference-messages/src/handler.rs b/litellm-rust/crates/inference-messages/src/handler.rs index 2e647688a1a..e0a7aa5adb8 100644 --- a/litellm-rust/crates/inference-messages/src/handler.rs +++ b/litellm-rust/crates/inference-messages/src/handler.rs @@ -10,9 +10,9 @@ use litellm_core_utils::{ get_provider_specific_headers::get_provider_specific_headers, settings::Lookup, }; use litellm_host::interceptors::{ - Cost, ExecutionFacts, Interceptors, ProviderIdentity, RequestContext, ResultSource, WireRequest, + Cost, ExecutionFacts, Interceptors, ProviderIdentity, RawResponse, RequestContext, + ResponseHead, ResultSource, WireRequest, }; -use litellm_http::request::with_default_headers; use litellm_llms::base_llm::{ auth::{Authenticated, ValidatedEnvironment, resolve_auth}, messages::{ @@ -21,14 +21,16 @@ use litellm_llms::base_llm::{ transformation::BaseMessagesConfig, }, }; -use litellm_llms_types::formats::messages::{MessagesRequest, MessagesResponse}; +use litellm_llms_types::formats::messages::{ + MessagesOptionalParams, MessagesRequest, MessagesResponse, +}; use litellm_secrets::source::Secrets; use litellm_tracing::ByteChunk; use serde_json::Value; use super::{ Error, MessagesCall, MessagesCallResponse, MessagesRoute, - common_utils::{MessagesProvider, string_headers}, + common_utils::{MessagesProvider, merge_messages_header_sources, string_headers}, constants::MESSAGES_TIMEOUT_SECS, route::Messages, types::invalid_request, @@ -126,14 +128,18 @@ async fn provider_call( MessagesRequest { model, ..body }, shaping.settings.reasoning_auto_summary, )?; + let transform_context = + MessagesTransformContext::new(shaping.capabilities, shaping.settings.drop_params); + let filtered = requested_optional_params(sanitized, provider, &transform_context)?; let trimmed = - without_additional_drop_params(sanitized, &shaping.settings.additional_drop_params)?; + without_additional_drop_params(filtered, &shaping.settings.additional_drop_params)?; let scoped = get_provider_specific_headers(provider_specific_header.as_ref(), provider.as_str()); - let forwarded = string_headers(Some( - extra_headers.into_iter().flatten().chain(scoped).collect(), - ))?; + let forwarded = string_headers(Some(merge_messages_header_sources([ + extra_headers.unwrap_or_default(), + scoped, + ])))?; let validated = config.validate_environment( forwarded, api_key.as_deref(), @@ -144,16 +150,13 @@ async fn provider_call( )?; let body = config.request_body( - config.transform_anthropic_messages_request( - trimmed, - &MessagesTransformContext::new(shaping.capabilities, shaping.settings.drop_params), - )?, + config.transform_anthropic_messages_request(trimmed, &transform_context)?, &validated.headers, shaping.settings.drop_params, )?; let environment = ValidatedEnvironment { headers: config.request_headers( - with_default_headers(validated.headers, config.default_headers()), + with_python_default_headers(validated.headers, config.default_headers()), &body, ), auth: validated.auth, @@ -184,7 +187,7 @@ async fn provider_call( .before_provider_request( WireRequest { url, - headers: authenticated.headers, + headers: joined_header_values(authenticated.headers), body: config.wire_body(serde_json::to_value(&body).map_err(serialize_failure)?), }, request_context, @@ -213,6 +216,64 @@ async fn provider_call( }) } +/// Python sends its header dict through `httpx.Headers`, which folds names that differ only in +/// case into one lowercase header whose values are joined with `", "`. +fn joined_header_values(headers: Vec<(String, String)>) -> Vec<(String, String)> { + let mut joined: Vec<(String, String)> = Vec::with_capacity(headers.len()); + let mut positions: std::collections::HashMap = + std::collections::HashMap::with_capacity(headers.len()); + for (name, value) in headers { + match positions.entry(name.to_ascii_lowercase()) { + std::collections::hash_map::Entry::Occupied(position) => { + let present = &mut joined[*position.get()].1; + present.push_str(", "); + present.push_str(&value); + } + std::collections::hash_map::Entry::Vacant(position) => { + position.insert(joined.len()); + joined.push((name, value)); + } + } + } + joined +} + +/// Python's `finalize_messages_headers` adds a default only when the exact lowercase name is +/// absent, so a caller's `Anthropic-Version` is sent alongside the default, not instead of it. +fn with_python_default_headers( + headers: Vec<(String, String)>, + defaults: &[(&str, &str)], +) -> Vec<(String, String)> { + let missing: Vec<(String, String)> = defaults + .iter() + .filter(|(name, _)| !headers.iter().any(|(present, _)| present == name)) + .map(|(name, value)| ((*name).to_string(), (*value).to_string())) + .collect(); + headers.into_iter().chain(missing).collect() +} + +/// Python's `get_requested_anthropic_messages_optional_param`, which gates speed, service tier +/// and sampling params before `additional_drop_params` and the environment check run. +fn requested_optional_params( + request: MessagesRequest, + provider: MessagesProvider, + context: &MessagesTransformContext, +) -> Result { + let request = litellm_llms::anthropic::messages::transformation::drop_unsupported_params( + request, context, + )?; + if provider.accepts_service_tier() { + return Ok(request); + } + Ok(MessagesRequest { + params: MessagesOptionalParams { + service_tier: None, + ..request.params + }, + ..request + }) +} + fn without_additional_drop_params( request: MessagesRequest, paths: &[String], @@ -245,6 +306,7 @@ async fn call_provider( } = request; let provider_name = provider.as_str(); log_request_body(provider_name, stream, &wire.body); + let timeout = timeout.unwrap_or(Duration::from_secs(MESSAGES_TIMEOUT_SECS)); let response = send( http, Authenticated { @@ -254,10 +316,11 @@ async fn call_provider( &wire.url, &wire.body, timeout, + stream, ) .await?; if !response.status().is_success() { - return Err(provider_error(response).await); + return Err(provider_error(response, timeout).await); } let config = provider.config(); if stream { @@ -265,11 +328,24 @@ async fn call_provider( response, config.stream_decoder(), provider_name, + timeout, )); } + let head = ResponseHead { + status: response.status().as_u16(), + headers: litellm_http::request::header_pairs(response.headers()), + }; + let status = head.status; let text = response.text().await.map_err(litellm_http::Error::from)?; log_response_body(&text); - context.response_received(&text).await?; + context + .raw_response_received(RawResponse::new(text.clone()).with_head(head)) + .await?; + if serde_json::from_str::(&text).is_err() { + // Python raises `AnthropicError(status_code=, message=)` for a + // body it cannot parse, and the public mapping classifies it by that status. + return Err(litellm_http::Error::upstream(status, text).into()); + } decode_response(config, &identity.model, &text) .map(|message| MessagesCallResponse::Complete(Box::new(message))) } @@ -281,30 +357,53 @@ fn serialize_failure(err: serde_json::Error) -> Error { )) } +/// Python's httpx timeout bounds each phase and each read, never the whole exchange. A complete +/// response keeps the client's overall deadline; a stream is bounded until its head arrives and +/// then per read (see [`timed_chunks`]), so a long stream that keeps sending is not cut off. async fn send( http: &litellm_http::Client, authenticated: Authenticated, url: &str, body: &Value, - timeout: Option, + timeout: Duration, + stream: bool, ) -> Result { - let request = outbound_request( - authenticated, - url, - body, - Some(timeout.unwrap_or(Duration::from_secs(MESSAGES_TIMEOUT_SECS))), - )?; - Ok(litellm_inference::outbound::send(request, http).await?) + let request = outbound_request(authenticated, url, body, (!stream).then_some(timeout))?; + if !stream { + return Ok(litellm_inference::outbound::send(request, http).await?); + } + tokio::time::timeout(timeout, litellm_inference::outbound::send(request, http)) + .await + .map_err(litellm_http::Error::read_timeout)? + .map_err(Error::from) } -async fn provider_error(response: reqwest::Response) -> Error { +/// The stream's body, each read bounded by `timeout` as httpx bounds each read. +fn timed_chunks( + response: reqwest::Response, + timeout: Duration, +) -> impl futures_util::Stream> + Send + 'static { + futures_util::stream::try_unfold(response, move |mut response| async move { + let chunk = tokio::time::timeout(timeout, response.chunk()) + .await + .map_err(litellm_http::Error::body_read_timeout)? + .map_err(litellm_http::Error::from)?; + Ok(chunk.map(|chunk| (chunk, response))) + }) +} + +/// The provider's error, its body read under `timeout`: a stream has no overall deadline once +/// its head arrives, so an error body that stalls would otherwise hold the call forever. +async fn provider_error(response: reqwest::Response, timeout: Duration) -> Error { let status = response.status().as_u16(); - match response.text().await { - Ok(text) => { + let headers = litellm_http::request::header_pairs(response.headers()); + match tokio::time::timeout(timeout, response.text()).await { + Ok(Ok(text)) => { log_error_body(status, &text); - litellm_http::Error::upstream(status, text).into() + litellm_http::Error::upstream_with_headers(status, text, headers).into() } - Err(error) => litellm_http::Error::from(error).into(), + Ok(Err(error)) => litellm_http::Error::from(error).into(), + Err(elapsed) => litellm_http::Error::read_timeout(elapsed).into(), } } @@ -329,22 +428,22 @@ fn streaming_response( response: reqwest::Response, decoder: Option, provider: &'static str, + timeout: Duration, ) -> MessagesCallResponse { let headers = response .headers() .iter() .filter_map(|(name, value)| Some((name.to_string(), value.to_str().ok()?.to_string()))) .collect(); + let chunks = timed_chunks(response, timeout) + .inspect_ok(move |chunk| log_chunk(provider, "provider_response", chunk)); let chunks = match decoder { - None => futures_util::stream::try_unfold(response, move |mut response| async move { - let chunk = response.chunk().await.map_err(litellm_http::Error::from)?; - Ok(chunk.map(|chunk| { - log_chunk(provider, "provider_response", &chunk); - (chunk, response) - })) - }) - .boxed(), - Some(decode) => decoded_chunks(response, decode, provider), + None => chunks.map_err(Error::from).boxed(), + Some(decode) => decoded_chunks( + chunks.map_err(std::io::Error::other).boxed(), + decode, + provider, + ), }; MessagesCallResponse::Stream { head: super::route::MessagesStreamHead { headers }, @@ -353,15 +452,10 @@ fn streaming_response( } fn decoded_chunks( - response: reqwest::Response, + bytes: ByteStream, decode: StreamDecoder, provider: &'static str, ) -> BoxStream<'static, Result> { - let bytes: ByteStream = response - .bytes_stream() - .inspect_ok(move |chunk| log_chunk(provider, "provider_response", chunk)) - .map_err(|error| std::io::Error::other(litellm_http::Error::from(error))) - .boxed(); futures_util::stream::try_unfold(decode(bytes), move |mut events| async move { let Some(event) = events.try_next().await? else { return Ok(None); @@ -964,9 +1058,12 @@ mod tests { .send() .await .unwrap(); - let MessagesCallResponse::Stream { mut chunks, .. } = - streaming_response(response, Some(streaming::event_stream), "test") - else { + let MessagesCallResponse::Stream { mut chunks, .. } = streaming_response( + response, + Some(streaming::event_stream), + "test", + Duration::from_secs(5), + ) else { panic!("a streaming response returns chunks"); }; diff --git a/litellm-rust/crates/inference-messages/src/lib.rs b/litellm-rust/crates/inference-messages/src/lib.rs index bfefb9c63b0..745442d0314 100644 --- a/litellm-rust/crates/inference-messages/src/lib.rs +++ b/litellm-rust/crates/inference-messages/src/lib.rs @@ -14,6 +14,7 @@ use std::sync::Arc; use crate::common_utils::messages_provider; +pub use common_utils::merge_messages_header_sources; pub use litellm_inference::Error; pub use types::{ MessagesCall, MessagesCallResponse, MessagesSettings, MessagesShaping, litellm_params, diff --git a/litellm-rust/crates/inference-messages/tests/messages/request.rs b/litellm-rust/crates/inference-messages/tests/messages/request.rs index e53bdb8d252..216aa96fbe6 100644 --- a/litellm-rust/crates/inference-messages/tests/messages/request.rs +++ b/litellm-rust/crates/inference-messages/tests/messages/request.rs @@ -440,7 +440,12 @@ async fn an_oauth_key_sends_the_browser_access_header_and_the_oauth_beta(call: M #[case::deepseek("deepseek")] #[case::minimax("minimax")] #[tokio::test] -async fn caller_protocol_headers_win_over_the_defaults(call: MessagesCall, #[case] provider: &str) { +/// Python adds a default unless that exact lowercase name is present, then folds the casings +/// into one header, so a capitalised caller header is sent beside the default. +async fn capitalised_caller_protocol_headers_are_joined_with_the_defaults( + call: MessagesCall, + #[case] provider: &str, +) { let upstream = upstream([message_response()]).await; run_message(MessagesCall { @@ -457,10 +462,13 @@ async fn caller_protocol_headers_win_over_the_defaults(call: MessagesCall, #[cas .await; let request = only_request(&upstream).await; - assert_eq!(request.header_values("anthropic-version"), ["2024-01-01"]); + assert_eq!( + request.header_values("anthropic-version"), + ["2024-01-01, 2023-06-01"] + ); assert_eq!( request.header_values("content-type"), - ["application/json; charset=utf-8"] + ["application/json; charset=utf-8, application/json"] ); } diff --git a/litellm-rust/crates/inference-messages/tests/messages/response.rs b/litellm-rust/crates/inference-messages/tests/messages/response.rs index 7aff1286858..76813fe0a34 100644 --- a/litellm-rust/crates/inference-messages/tests/messages/response.rs +++ b/litellm-rust/crates/inference-messages/tests/messages/response.rs @@ -225,14 +225,25 @@ async fn an_upstream_error_keeps_its_status_and_body(call: MessagesCall, #[case] } #[rstest] -#[case::not_json(ResponseTemplate::new(200).set_body_string("not json"))] -#[case::not_a_message(json_response(json!({"unexpected": true})))] #[tokio::test] -async fn an_unreadable_success_body_is_an_invalid_response( - call: MessagesCall, - #[case] response: ResponseTemplate, -) { - let upstream = upstream([response]).await; +async fn an_unparseable_success_body_is_reported_as_the_upstream_answer(call: MessagesCall) { + let upstream = upstream([ResponseTemplate::new(200).set_body_string("not json")]).await; + + let error = run(MessagesCall { + api_key: Some("sk".into()), + api_base: Some(upstream.uri()), + ..call + }) + .await + .expect_err("an unparseable body fails"); + + assert_eq!(error.upstream_response(), Some((200, "not json"))); +} + +#[rstest] +#[tokio::test] +async fn an_unreadable_success_body_is_an_invalid_response(call: MessagesCall) { + let upstream = upstream([json_response(json!({"unexpected": true}))]).await; let error = run(MessagesCall { api_key: Some("sk".into()), diff --git a/litellm-rust/crates/inference-messages/tests/messages/stream.rs b/litellm-rust/crates/inference-messages/tests/messages/stream.rs index 4a8a061f764..99ba08495aa 100644 --- a/litellm-rust/crates/inference-messages/tests/messages/stream.rs +++ b/litellm-rust/crates/inference-messages/tests/messages/stream.rs @@ -432,6 +432,49 @@ async fn dropping_the_sdk_stream_closes_the_unfinished_upstream( .unwrap(); } +/// Answers with an error head whose promised body never arrives. +async fn stalling_error_upstream() -> (String, JoinHandle<()>) { + let listener = TcpListener::bind("127.0.0.1:0").await.unwrap(); + let base = format!("http://{}", listener.local_addr().unwrap()); + let connection = tokio::spawn(async move { + let (mut socket, _) = listener.accept().await.unwrap(); + let mut request = vec![0; 4096]; + let _ = socket.read(&mut request).await; + socket + .write_all(b"HTTP/1.1 429 Too Many Requests\r\ncontent-type: application/json\r\ncontent-length: 100\r\n\r\n") + .await + .unwrap(); + let _ = socket.read_to_end(&mut Vec::new()).await; + }); + (base, connection) +} + +#[rstest] +#[tokio::test] +async fn the_timeout_covers_a_stalled_stream_error_body(call: MessagesCall) { + let (base, connection) = stalling_error_upstream().await; + let host = RecordingStreamHost::new( + MessagesCall { + timeout: Some(Duration::from_millis(300)), + ..streaming(call, base) + }, + usize::MAX, + ); + + let error = tokio::time::timeout(Duration::from_secs(5), stream_through(&host)) + .await + .expect("the stalled error body gives up within the timeout") + .expect_err("a stalled error body fails the call"); + + assert!(error.dispatched(), "{error:?}"); + assert_eq!(error.upstream_response(), None); + assert!(host.seen.into_inner().unwrap().is_empty()); + tokio::time::timeout(Duration::from_secs(5), connection) + .await + .expect("timing out closes the upstream connection") + .unwrap(); +} + #[rstest] #[tokio::test] async fn the_sdk_yields_a_body_error_once_after_delivered_chunks(call: MessagesCall) { diff --git a/litellm-rust/crates/inference-ocr/src/handler.rs b/litellm-rust/crates/inference-ocr/src/handler.rs index c126a192153..be23af60c69 100644 --- a/litellm-rust/crates/inference-ocr/src/handler.rs +++ b/litellm-rust/crates/inference-ocr/src/handler.rs @@ -91,9 +91,7 @@ impl> CallHooks for OcrCallHooks<'_, H> { } fn response_received<'a>(&'a self, body: &'a [u8]) -> BoxFuture<'a, Result<(), Error>> { - let raw = RawResponse { - body: String::from_utf8_lossy(body).into_owned(), - }; + let raw = RawResponse::new(String::from_utf8_lossy(body).into_owned()); if let Some(observers) = self.observers { observers.emit(litellm_host::lifecycle::CallEvent::Execution( ExecutionEvent::ProviderResponseReceived { raw: raw.clone() }, diff --git a/litellm-rust/crates/inference-ocr/tests/resources.rs b/litellm-rust/crates/inference-ocr/tests/resources.rs index d618647e89b..3132a837eaf 100644 --- a/litellm-rust/crates/inference-ocr/tests/resources.rs +++ b/litellm-rust/crates/inference-ocr/tests/resources.rs @@ -7,7 +7,7 @@ use std::sync::{ use litellm_auth::AuthServices; use litellm_auth_gcp::{ - CredentialSource, VertexAuth, VertexAuthFuture, VertexProviderLoader, VertexTokenSource, + CredentialSource, GcpAuthFuture, GcpProviderLoader, GcpTokenSource, VertexAuth, }; use litellm_http::{HttpSettings, Resolution}; use litellm_inference::resources::CoreResources; @@ -20,28 +20,28 @@ use support::{ReceivedRequest, json_response, upstream}; struct TokenSource(String); -impl VertexTokenSource for TokenSource { - fn project_id(&self) -> VertexAuthFuture<'_, String> { +impl GcpTokenSource for TokenSource { + fn project_id(&self) -> GcpAuthFuture<'_, String> { Box::pin(async { Ok(self.0.clone()) }) } - fn token(&self) -> VertexAuthFuture<'_, String> { - Box::pin(async { Ok(self.0.clone()) }) + fn token(&self) -> GcpAuthFuture<'_, litellm_secret_value::SecretValue> { + Box::pin(async { Ok(litellm_secret_value::SecretValue::new(self.0.clone())) }) } } #[derive(Default)] struct Loader(AtomicUsize); -impl VertexProviderLoader for Loader { - fn load(&self, source: CredentialSource) -> VertexAuthFuture<'_, Arc> { +impl GcpProviderLoader for Loader { + fn load(&self, source: CredentialSource) -> GcpAuthFuture<'_, Arc> { Box::pin(async move { self.0.fetch_add(1, Ordering::SeqCst); let identity = match source { CredentialSource::Trusted(secret) => secret.expose().to_string(), other => panic!("unexpected credential source: {other:?}"), }; - Ok(Arc::new(TokenSource(identity)) as Arc) + Ok(Arc::new(TokenSource(identity)) as Arc) }) } } diff --git a/litellm-rust/crates/inference-responses/src/handler.rs b/litellm-rust/crates/inference-responses/src/handler.rs index 19092a63a14..f81a51ad192 100644 --- a/litellm-rust/crates/inference-responses/src/handler.rs +++ b/litellm-rust/crates/inference-responses/src/handler.rs @@ -114,7 +114,7 @@ pub(super) async fn execute( }); } let body = response.text().await.map_err(litellm_http::Error::from)?; - let raw = RawResponse { body: body.clone() }; + let raw = RawResponse::new(body.clone()); if let Some(observers) = observers { observers.emit(litellm_host::lifecycle::CallEvent::Execution( ExecutionEvent::ProviderResponseReceived { raw: raw.clone() }, diff --git a/litellm-rust/crates/inference/src/context.rs b/litellm-rust/crates/inference/src/context.rs index 963aa7b90c5..ef2635d24a1 100644 --- a/litellm-rust/crates/inference/src/context.rs +++ b/litellm-rust/crates/inference/src/context.rs @@ -42,9 +42,11 @@ impl<'a, I: Interceptors> CallContext<'a, I> { } pub async fn response_received(&self, body: &str) -> Result<(), Error> { - let raw = RawResponse { - body: body.to_owned(), - }; + self.raw_response_received(RawResponse::new(body.to_owned())) + .await + } + + pub async fn raw_response_received(&self, raw: RawResponse) -> Result<(), Error> { if let Some(observers) = &self.observers { observers.emit(CallEvent::Execution( ExecutionEvent::ProviderResponseReceived { raw: raw.clone() }, diff --git a/litellm-rust/crates/inference/src/error.rs b/litellm-rust/crates/inference/src/error.rs index a8e6fb4e1b3..841e0c53799 100644 --- a/litellm-rust/crates/inference/src/error.rs +++ b/litellm-rust/crates/inference/src/error.rs @@ -146,6 +146,34 @@ impl Error { } } + /// The provider's response headers on an upstream failure; empty for every other error. + pub fn upstream_headers(&self) -> &[(String, String)] { + match self { + Self::Llm(error) => error.upstream_headers(), + Self::Http(error) => error.upstream_headers(), + _ => &[], + } + } + + /// A read of a streamed body timed out after the response head arrived. + pub fn body_read_timeout(&self) -> bool { + match self { + Self::Llm(error) => error.is_body_read_timeout(), + Self::Http(error) => error.is_body_read_timeout(), + _ => false, + } + } + + /// `Some(connect)` when the call timed out, where `connect` says the connection was never + /// established; `None` for every other error. + pub fn timeout(&self) -> Option { + match self { + Self::Llm(error) => error.is_timeout(), + Self::Http(error) if error.is_timeout() => Some(error.is_connect_timeout()), + _ => None, + } + } + pub fn upstream_response(&self) -> Option<(u16, &str)> { match self { Self::Llm(error) => error.upstream_response(), diff --git a/litellm-rust/crates/llms-types/src/formats/messages/request.rs b/litellm-rust/crates/llms-types/src/formats/messages/request.rs index 9dbfa068025..d30d21e74e7 100644 --- a/litellm-rust/crates/llms-types/src/formats/messages/request.rs +++ b/litellm-rust/crates/llms-types/src/formats/messages/request.rs @@ -264,7 +264,12 @@ pub enum ThinkingDisplay { #[macro_rules_attribute::apply(crate::wire_type)] #[derive(Default)] pub struct EnabledThinking { - #[serde(default, skip_serializing_if = "Option::is_none")] + /// An explicit `null` stays `Unrecognized(Null)`: Python rejects it, but defaults a missing key to 0. + #[serde( + default, + skip_serializing_if = "Option::is_none", + deserialize_with = "crate::recognized::present" + )] pub budget_tokens: Option>, #[serde(default, skip_serializing_if = "Option::is_none")] pub display: Option>, diff --git a/litellm-rust/crates/llms-types/src/formats/messages/response.rs b/litellm-rust/crates/llms-types/src/formats/messages/response.rs index 9b0c5d31b3a..276a30a6cb4 100644 --- a/litellm-rust/crates/llms-types/src/formats/messages/response.rs +++ b/litellm-rust/crates/llms-types/src/formats/messages/response.rs @@ -10,14 +10,29 @@ pub struct MessagesResponse { pub content: Vec, pub stop_reason: Option, pub stop_sequence: Option, - #[serde(skip_serializing_if = "Option::is_none")] + /// `Some(Value::Null)` when the provider sent an explicit `null`, which Python keeps. + #[serde( + default, + deserialize_with = "present_value", + skip_serializing_if = "Option::is_none" + )] pub usage: Option, - #[serde(skip_serializing_if = "Option::is_none")] + #[serde( + default, + deserialize_with = "present_value", + skip_serializing_if = "Option::is_none" + )] pub container: Option, #[serde(flatten)] pub extra: Map, } +fn present_value<'de, D: serde::Deserializer<'de>>( + deserializer: D, +) -> Result, D::Error> { + >::deserialize(deserializer).map(Some) +} + #[cfg(test)] mod tests { use super::*; @@ -73,4 +88,21 @@ mod tests { assert_eq!(body.get("usage").cloned(), usage); assert_eq!(body.get("container").cloned(), container); } + + #[test] + fn explicit_null_usage_and_container_survive_a_round_trip() { + let body = json!({"id": "msg_1", "type": "message", "role": "assistant", "model": "m", + "content": [], "stop_reason": null, "stop_sequence": null, + "usage": null, "container": null}); + let parsed: MessagesResponse = serde_json::from_value(body.clone()).expect("parses"); + assert_eq!(serde_json::to_value(parsed).expect("serializable"), body); + } + + #[test] + fn absent_usage_and_container_stay_absent() { + let body = json!({"id": "msg_1", "type": "message", "role": "assistant", "model": "m", + "content": [], "stop_reason": null, "stop_sequence": null}); + let parsed: MessagesResponse = serde_json::from_value(body.clone()).expect("parses"); + assert_eq!(serde_json::to_value(parsed).expect("serializable"), body); + } } diff --git a/litellm-rust/crates/llms-types/src/providers/anthropic/beta.rs b/litellm-rust/crates/llms-types/src/providers/anthropic/beta.rs index 01ed023999d..46c14a21c59 100644 --- a/litellm-rust/crates/llms-types/src/providers/anthropic/beta.rs +++ b/litellm-rust/crates/llms-types/src/providers/anthropic/beta.rs @@ -124,12 +124,86 @@ pub enum AnthropicBeta { ToolSearchTool20251019, #[strum(serialize = "inline-tools-2026-09-15")] InlineTools20260915, + #[strum(serialize = "afk-mode-2026-01-31")] + AfkMode20260131, + #[strum(serialize = "agent-memory-2026-07-22")] + AgentMemory20260722, + #[strum(serialize = "analytics-usage-cost-2026-08-24")] + AnalyticsUsageCost20260824, + #[strum(serialize = "cache-diagnosis-2026-04-07")] + CacheDiagnosis20260407, + #[strum(serialize = "ce-plugins-2026-09-01")] + CePlugins20260901, + #[strum(serialize = "ce-user-management-2026-07-13")] + CeUserManagement20260713, + #[strum(serialize = "code-execution-2025-05-22")] + CodeExecution20250522, + #[strum(serialize = "computer-use-2024-10-22")] + ComputerUse20241022, + #[strum(serialize = "dev-full-thinking-2025-05-14")] + DevFullThinking20250514, + #[strum(serialize = "dreaming-2026-04-21")] + Dreaming20260421, + #[strum(serialize = "experimental-claude-tag-2026-10-21")] + ExperimentalClaudeTag20261021, + #[strum(serialize = "extended-cache-ttl-2025-04-11")] + ExtendedCacheTtl20250411, + #[strum(serialize = "fallback-credit-2026-06-01")] + FallbackCredit20260601, + #[strum(serialize = "fallback-credit-2026-07-01")] + FallbackCredit20260701, + #[strum(serialize = "managed-agents-2026-04-01")] + ManagedAgents20260401, + #[strum(serialize = "mcp-client-2026-09-15")] + McpClient20260915, + #[strum(serialize = "mcp-tunnels-2026-06-22")] + McpTunnels20260622, + #[strum(serialize = "message-batches-2024-09-24")] + MessageBatches20240924, + #[strum(serialize = "message-threads-2026-08-12")] + MessageThreads20260812, + #[strum(serialize = "mid-conversation-system-clear-at-2026-08-21")] + MidConversationSystemClearAt20260821, + #[strum(serialize = "model-context-window-exceeded-2025-08-26")] + ModelContextWindowExceeded20250826, + #[strum(serialize = "output-300k-2026-03-24")] + Output300k20260324, + #[strum(serialize = "pdfs-2024-09-25")] + Pdfs20240925, + #[strum(serialize = "prompt-caching-2024-07-31")] + PromptCaching20240731, + #[strum(serialize = "redact-thinking-2026-02-12")] + RedactThinking20260212, + #[strum(serialize = "server-side-fallback-2026-06-01")] + ServerSideFallback20260601, + #[strum(serialize = "server-side-fallback-2026-07-01")] + ServerSideFallback20260701, + #[strum(serialize = "spend-limit-reads-2026-09-26")] + SpendLimitReads20260926, + #[strum(serialize = "structured-outputs-2025-12-15")] + StructuredOutputs20251215, + #[strum(serialize = "task-budgets-2026-03-13")] + TaskBudgets20260313, + #[strum(serialize = "telemetry-destinations-2026-08-11")] + TelemetryDestinations20260811, + #[strum(serialize = "thinking-token-count-2026-05-13")] + ThinkingTokenCount20260513, + #[strum(serialize = "token-counting-2024-11-01")] + TokenCounting20241101, + #[strum(serialize = "user-profiles-2026-03-24")] + UserProfiles20260324, + #[strum(serialize = "user-profiles-2026-08-18")] + UserProfiles20260818, + #[strum(serialize = "user-profiles-2026-09-04")] + UserProfiles20260904, + #[strum(serialize = "webhooks-2026-10-07")] + Webhooks20261007, #[strum(default, transparent)] Other(String), } impl AnthropicBeta { - pub const KNOWN: [Self; 40] = [ + pub const KNOWN: [Self; 77] = [ Self::Oauth20250420, Self::WebFetch20250910, Self::WebSearch20250305, @@ -170,6 +244,43 @@ impl AnthropicBeta { Self::ToolExamples20251029, Self::ToolSearchTool20251019, Self::InlineTools20260915, + Self::AfkMode20260131, + Self::AgentMemory20260722, + Self::AnalyticsUsageCost20260824, + Self::CacheDiagnosis20260407, + Self::CePlugins20260901, + Self::CeUserManagement20260713, + Self::CodeExecution20250522, + Self::ComputerUse20241022, + Self::DevFullThinking20250514, + Self::Dreaming20260421, + Self::ExperimentalClaudeTag20261021, + Self::ExtendedCacheTtl20250411, + Self::FallbackCredit20260601, + Self::FallbackCredit20260701, + Self::ManagedAgents20260401, + Self::McpClient20260915, + Self::McpTunnels20260622, + Self::MessageBatches20240924, + Self::MessageThreads20260812, + Self::MidConversationSystemClearAt20260821, + Self::ModelContextWindowExceeded20250826, + Self::Output300k20260324, + Self::Pdfs20240925, + Self::PromptCaching20240731, + Self::RedactThinking20260212, + Self::ServerSideFallback20260601, + Self::ServerSideFallback20260701, + Self::SpendLimitReads20260926, + Self::StructuredOutputs20251215, + Self::TaskBudgets20260313, + Self::TelemetryDestinations20260811, + Self::ThinkingTokenCount20260513, + Self::TokenCounting20241101, + Self::UserProfiles20260324, + Self::UserProfiles20260818, + Self::UserProfiles20260904, + Self::Webhooks20261007, ]; pub fn as_str(&self) -> &str { @@ -195,10 +306,9 @@ impl AnthropicBeta { fn rejected_by(&self) -> &'static [BetaProvider] { match self { - Self::AdvancedToolUse20251120 => { + Self::AdvancedToolUse20251120 | Self::ToolSearchTool20251019 => { &[BetaProvider::BedrockConverse, BetaProvider::Databricks] } - Self::ContextManagement20250627 => &[BetaProvider::BedrockConverse], Self::AdvisorTool20260301 => &[ BetaProvider::AzureAi, BetaProvider::BedrockConverse, @@ -207,98 +317,99 @@ impl AnthropicBeta { BetaProvider::VertexAi, BetaProvider::Databricks, ], - Self::Compact20260904 => &[ + Self::AfkMode20260131 + | Self::CePlugins20260901 + | Self::CeUserManagement20260713 + | Self::Compact20260904 + | Self::Dreaming20260421 + | Self::ExperimentalClaudeTag20261021 + | Self::ExtendedCacheTtl20250411 + | Self::FallbackCredit20260601 + | Self::FallbackCredit20260701 + | Self::InlineTools20260915 + | Self::ManagedAgents20260401 + | Self::McpTunnels20260622 + | Self::MidConversationSystemClearAt20260821 + | Self::ModelContextWindowExceeded20250826 + | Self::Oauth20250420 + | Self::Pdfs20240925 + | Self::PromptCaching20240731 + | Self::PromptCachingScope20260105 + | Self::RedactThinking20260212 + | Self::ServerSideFallback20260601 + | Self::SpendLimitReads20260926 + | Self::StructuredOutputs20251215 + | Self::TaskBudgets20260313 + | Self::TelemetryDestinations20260811 + | Self::ThinkingTokenCount20260513 + | Self::TokenCounting20241101 + | Self::UserProfiles20260324 + | Self::UserProfiles20260818 + | Self::UserProfiles20260904 => &[ BetaProvider::BedrockConverse, BetaProvider::Bedrock, BetaProvider::BedrockMantle, BetaProvider::Databricks, ], - Self::Bash20241022 + Self::AgentMemory20260722 + | Self::Bash20241022 | Self::Bash20250124 + | Self::DevFullThinking20250514 | Self::McpServers20251204 | Self::StructuredOutput20240301 | Self::TextEditor20241022 | Self::TextEditor20250124 => BetaProvider::VARIANTS, - Self::ClaudeCode20250219 | Self::ToolExamples20251029 => &[ - BetaProvider::Anthropic, - BetaProvider::AzureAi, - BetaProvider::BedrockConverse, - BetaProvider::Bedrock, - BetaProvider::VertexAi, - BetaProvider::Databricks, - ], - Self::CodeExecution20250825 + Self::AnalyticsUsageCost20260824 + | Self::CacheDiagnosis20260407 + | Self::CodeExecution20250522 + | Self::CodeExecution20250825 + | Self::ComputerUse20241022 + | Self::FastMode20260201 | Self::FilesApi20250414 | Self::McpClient20250404 | Self::McpClient20251120 - | Self::PromptCachingScope20260105 + | Self::McpClient20260915 + | Self::MessageBatches20240924 + | Self::MessageThreads20260812 + | Self::Output300k20260324 + | Self::ServerSideFallback20260701 | Self::Skills20251002 - | Self::WebFetch20250910 => &[ + | Self::WebFetch20250910 + | Self::Webhooks20261007 => &[ BetaProvider::BedrockConverse, BetaProvider::Bedrock, BetaProvider::BedrockMantle, BetaProvider::VertexAi, BetaProvider::Databricks, ], - Self::Compact20260112 => &[BetaProvider::AzureAi, BetaProvider::BedrockConverse], + Self::ClaudeCode20250219 + | Self::PerTurnControl20260701 + | Self::ToolExamples20251029 => &[ + BetaProvider::BedrockConverse, + BetaProvider::Bedrock, + BetaProvider::Databricks, + ], + Self::Compact20260112 + | Self::ContextManagement20250627 + | Self::DangerousToolUse20260903 => &[BetaProvider::BedrockConverse], Self::ComputerUse20250124 | Self::ComputerUse20251124 | Self::Context1m20250807 + | Self::Effort20251124 + | Self::FineGrainedToolStreaming20250514 | Self::ThinkingBindingControls20260801 | Self::ThinkingDisplayUpdates20260818 => &[], - Self::DangerousToolUse20260903 => &[BetaProvider::BedrockConverse], - Self::Effort20251124 => &[BetaProvider::VertexAi], - Self::FastMode20260201 | Self::Oauth20250420 => &[ - BetaProvider::AzureAi, - BetaProvider::BedrockConverse, - BetaProvider::Bedrock, - BetaProvider::BedrockMantle, - BetaProvider::VertexAi, - BetaProvider::Databricks, - ], - Self::FineGrainedToolStreaming20250514 => { - &[BetaProvider::AzureAi, BetaProvider::VertexAi] - } - Self::InterleavedThinking20250514 | Self::WebSearch20250305 => { - &[BetaProvider::BedrockConverse, BetaProvider::Bedrock] - } - Self::MidConversationOutputConfig20260701 => &[ - BetaProvider::AzureAi, - BetaProvider::BedrockConverse, - BetaProvider::BedrockMantle, - BetaProvider::VertexAi, - BetaProvider::Databricks, - ], - Self::MidConversationToolChanges20260701 => &[ + Self::InterleavedThinking20250514 + | Self::Output128k20250219 + | Self::TokenEfficientTools20250219 + | Self::WebSearch20250305 => &[BetaProvider::BedrockConverse, BetaProvider::Bedrock], + Self::MidConversationOutputConfig20260701 + | Self::MidConversationToolChanges20260701 => &[ BetaProvider::BedrockConverse, BetaProvider::BedrockMantle, BetaProvider::Databricks, ], - Self::Output128k20250219 | Self::TokenEfficientTools20250219 => &[ - BetaProvider::AzureAi, - BetaProvider::BedrockConverse, - BetaProvider::Bedrock, - BetaProvider::VertexAi, - ], - Self::PerTurnControl20260701 => &[ - BetaProvider::BedrockConverse, - BetaProvider::Bedrock, - BetaProvider::Databricks, - ], - Self::StructuredOutputs20251113 => &[BetaProvider::Bedrock, BetaProvider::VertexAi], - Self::ToolSearchTool20251019 => &[ - BetaProvider::Anthropic, - BetaProvider::AzureAi, - BetaProvider::BedrockConverse, - BetaProvider::Databricks, - ], - Self::InlineTools20260915 => &[ - BetaProvider::AzureAi, - BetaProvider::BedrockConverse, - BetaProvider::Bedrock, - BetaProvider::BedrockMantle, - BetaProvider::Databricks, - ], + Self::StructuredOutputs20251113 => &[BetaProvider::Bedrock], Self::Other(_) => BetaProvider::VARIANTS, } } @@ -451,7 +562,44 @@ mod tests { AnthropicBeta::TokenEfficientTools20250219, AnthropicBeta::ToolExamples20251029, AnthropicBeta::ToolSearchTool20251019, - AnthropicBeta::InlineTools20260915 + AnthropicBeta::InlineTools20260915, + AnthropicBeta::AfkMode20260131, + AnthropicBeta::AgentMemory20260722, + AnthropicBeta::AnalyticsUsageCost20260824, + AnthropicBeta::CacheDiagnosis20260407, + AnthropicBeta::CePlugins20260901, + AnthropicBeta::CeUserManagement20260713, + AnthropicBeta::CodeExecution20250522, + AnthropicBeta::ComputerUse20241022, + AnthropicBeta::DevFullThinking20250514, + AnthropicBeta::Dreaming20260421, + AnthropicBeta::ExperimentalClaudeTag20261021, + AnthropicBeta::ExtendedCacheTtl20250411, + AnthropicBeta::FallbackCredit20260601, + AnthropicBeta::FallbackCredit20260701, + AnthropicBeta::ManagedAgents20260401, + AnthropicBeta::McpClient20260915, + AnthropicBeta::McpTunnels20260622, + AnthropicBeta::MessageBatches20240924, + AnthropicBeta::MessageThreads20260812, + AnthropicBeta::MidConversationSystemClearAt20260821, + AnthropicBeta::ModelContextWindowExceeded20250826, + AnthropicBeta::Output300k20260324, + AnthropicBeta::Pdfs20240925, + AnthropicBeta::PromptCaching20240731, + AnthropicBeta::RedactThinking20260212, + AnthropicBeta::ServerSideFallback20260601, + AnthropicBeta::ServerSideFallback20260701, + AnthropicBeta::SpendLimitReads20260926, + AnthropicBeta::StructuredOutputs20251215, + AnthropicBeta::TaskBudgets20260313, + AnthropicBeta::TelemetryDestinations20260811, + AnthropicBeta::ThinkingTokenCount20260513, + AnthropicBeta::TokenCounting20241101, + AnthropicBeta::UserProfiles20260324, + AnthropicBeta::UserProfiles20260818, + AnthropicBeta::UserProfiles20260904, + AnthropicBeta::Webhooks20261007 )] beta: AnthropicBeta, ) { @@ -551,7 +699,7 @@ mod tests { BetaProvider::Anthropic, Some(AnthropicBeta::Oauth20250420) )] - #[case::rejected("effort-2025-11-24", BetaProvider::VertexAi, None)] + #[case::rejected("skills-2025-10-02", BetaProvider::VertexAi, None)] #[case::unknown("example-beta-2099-01-01", BetaProvider::Anthropic, None)] fn on_resolves_known_spellings_held_as_other( #[case] raw: &str, @@ -580,12 +728,11 @@ mod tests { #[test] fn unknown_values_are_kept_verbatim() { - let parsed: AnthropicBeta = "claude-code-20250219".parse().unwrap(); - assert_eq!( - parsed, - AnthropicBeta::Other("claude-code-20250219".to_string()) + let parsed: AnthropicBeta = "example-beta-2099-01-01".parse().unwrap(); + assert!( + matches!(&parsed, AnthropicBeta::Other(value) if value == "example-beta-2099-01-01") ); - assert_eq!(parsed.to_string(), "claude-code-20250219"); + assert_eq!(parsed.to_string(), "example-beta-2099-01-01"); } #[test] diff --git a/litellm-rust/crates/llms-types/src/recognized.rs b/litellm-rust/crates/llms-types/src/recognized.rs index 58e8dd7a2e7..0545389afbc 100644 --- a/litellm-rust/crates/llms-types/src/recognized.rs +++ b/litellm-rust/crates/llms-types/src/recognized.rs @@ -7,6 +7,16 @@ pub enum Recognized { Unrecognized(Value), } +/// `deserialize_with` for an optional `Recognized` field whose explicit `null` must stay +/// distinguishable from an absent key: `null` becomes `Some(Unrecognized(Null))`. +pub fn present<'de, D, T>(deserializer: D) -> Result>, D::Error> +where + D: serde::Deserializer<'de>, + Recognized: serde::Deserialize<'de>, +{ + as serde::Deserialize<'de>>::deserialize(deserializer).map(Some) +} + impl Recognized { pub fn known(&self) -> Option<&T> { match self { diff --git a/litellm-rust/crates/llms/src/anthropic/beta_headers.rs b/litellm-rust/crates/llms/src/anthropic/beta_headers.rs index a0843621043..7842b478dce 100644 --- a/litellm-rust/crates/llms/src/anthropic/beta_headers.rs +++ b/litellm-rust/crates/llms/src/anthropic/beta_headers.rs @@ -96,7 +96,10 @@ mod tests { } #[rstest] - #[case::azure_ai(BetaProvider::AzureAi, "fast-mode-2026-02-01,example-beta-2099-01-01")] + #[case::azure_ai( + BetaProvider::AzureAi, + "advisor-tool-2026-03-01,example-beta-2099-01-01" + )] #[case::anthropic(BetaProvider::Anthropic, "bash_20241022")] #[case::vertex_ai(BetaProvider::VertexAi, " , ")] fn filter_removes_header_when_nothing_survives( diff --git a/litellm-rust/crates/llms/src/anthropic/common_utils.rs b/litellm-rust/crates/llms/src/anthropic/common_utils.rs index aec5d9ebc27..13653f438f7 100644 --- a/litellm-rust/crates/llms/src/anthropic/common_utils.rs +++ b/litellm-rust/crates/llms/src/anthropic/common_utils.rs @@ -154,11 +154,42 @@ pub fn complete_anthropic_url( ) -> String { let api_base = resolve_anthropic_api_base(api_base, env_lookup); - let api_base = api_base.trim_end_matches('/'); - if api_base.ends_with(MESSAGES_PATH) { + ensure_api_route(&api_base, MESSAGES_PATH) +} + +/// Python's `urlsplit(url).path`, for the URLs an `api_base` holds. +fn url_path(url: &str) -> &str { + let before_fragment = url.split('#').next().unwrap_or_default(); + let before_query = before_fragment.split('?').next().unwrap_or_default(); + match before_query.split_once("://") { + Some((_, rest)) => rest.find('/').map_or("", |slash| &rest[slash..]), + None => before_query, + } +} + +/// Python's `_strip_trailing_slashes_keeping_the_scheme`. +fn strip_trailing_slashes(api_base: &str) -> String { + let stripped = api_base.trim_end_matches('/'); + if stripped.ends_with(':') && !stripped.contains('/') && !stripped.contains('?') { return api_base.to_string(); } - format!("{api_base}{MESSAGES_PATH}") + match stripped.split_once('?') { + Some((before, query)) if url_path(stripped).ends_with('/') => { + format!("{}?{query}", before.trim_end_matches('/')) + } + _ => stripped.to_string(), + } +} + +/// Python's `ensure_api_route`: an `api_base` whose path already ends in the route is kept as +/// it is, query string included; anything else gets the route appended to the whole string. +fn ensure_api_route(api_base: &str, route: &str) -> String { + let base = strip_trailing_slashes(api_base); + let route = route.trim_start_matches('/'); + if url_path(&base).ends_with(&format!("/{route}")) { + return base; + } + format!("{}/{route}", strip_trailing_slashes(&base)) } pub fn existing_betas(headers: &[(String, String)]) -> BetaSet { @@ -1922,4 +1953,24 @@ mod tests { expected ); } + + #[rstest] + #[case::bare_host("https://api.example.com", "https://api.example.com/v1/messages")] + #[case::trailing_slash("https://api.example.com/", "https://api.example.com/v1/messages")] + #[case::route_present( + "https://api.example.com/v1/messages/", + "https://api.example.com/v1/messages" + )] + #[case::route_and_query( + "https://api.example.com/v1/messages?beta=true", + "https://api.example.com/v1/messages?beta=true" + )] + #[case::query_without_route( + "https://api.example.com/?x=1", + "https://api.example.com?x=1/v1/messages" + )] + #[case::scheme_only("https://", "https:///v1/messages")] + fn the_messages_url_follows_python_ensure_api_route(#[case] api_base: &str, #[case] url: &str) { + assert_eq!(complete_anthropic_url(Some(api_base), &|_| None), url); + } } diff --git a/litellm-rust/crates/llms/src/anthropic/messages/thinking.rs b/litellm-rust/crates/llms/src/anthropic/messages/thinking.rs index df1ae13fd28..ae3488a21f9 100644 --- a/litellm-rust/crates/llms/src/anthropic/messages/thinking.rs +++ b/litellm-rust/crates/llms/src/anthropic/messages/thinking.rs @@ -2,8 +2,8 @@ use litellm_llms_types::{ formats::{ chat_completions::ReasoningEffort, messages::{ - EffortLevel, MessagesOptionalParams, MessagesRequest, OutputConfig, ThinkingConfig, - ThinkingDisplay, + AdaptiveThinking, EffortLevel, MessagesOptionalParams, MessagesRequest, OutputConfig, + ThinkingConfig, ThinkingDisplay, }, }, recognized::Recognized, @@ -36,16 +36,17 @@ fn budget_for_effort(budgets: &ThinkingBudgets, effort: ReasoningEffort) -> Opti fn effort_for_budget( budgets: &ThinkingBudgets, - budget_tokens: u64, + budget_tokens: i64, capabilities: &MessagesModelCapabilities, ) -> EffortLevel { - if budget_tokens >= budgets.xhigh && capabilities.effort_tiers.xhigh { + let reaches = |tier: u64| i128::from(budget_tokens) >= i128::from(tier); + if reaches(budgets.xhigh) && capabilities.effort_tiers.xhigh { return EffortLevel::Xhigh; } - if budget_tokens >= budgets.high { + if reaches(budgets.high) { return EffortLevel::High; } - if budget_tokens >= budgets.medium { + if reaches(budgets.medium) { return EffortLevel::Medium; } EffortLevel::Low @@ -231,32 +232,129 @@ fn drop_disabled_thinking(request: MessagesRequest, context: &ThinkingContext) - } } +/// `_numeric_budget_tokens`: Python reads any int, float (truncated) or int-parseable string +/// as a budget, and nothing else. +fn numeric_budget_tokens(budget: &Recognized) -> Option { + let value = match budget { + Recognized::Known(budget) => return Some(i64::try_from(*budget).unwrap_or(i64::MAX)), + Recognized::Unrecognized(value) => value, + }; + match value { + Value::Number(number) => number + .as_i64() + .or_else(|| number.as_f64().map(|float| float.trunc() as i64)), + Value::String(text) => python_int(text), + Value::Null | Value::Bool(_) | Value::Array(_) | Value::Object(_) => None, + } +} + +/// Python's `int(str)`: surrounding whitespace, a sign, and single underscores between digits. +fn python_int(text: &str) -> Option { + let trimmed = text.trim(); + let digits = trimmed.trim_start_matches(['+', '-']); + let well_formed = trimmed.len() - digits.len() <= 1 + && !digits.is_empty() + && !digits.starts_with('_') + && !digits.ends_with('_') + && !digits.contains("__") + && digits.chars().all(|ch| ch.is_ascii_digit() || ch == '_'); + if !well_formed { + return None; + } + let cleaned: String = trimmed.chars().filter(|ch| *ch != '_').collect(); + cleaned.parse::().ok().or_else(|| { + Some(if cleaned.starts_with('-') { + i64::MIN + } else { + i64::MAX + }) + }) +} + +fn python_type_name(value: &Value) -> &'static str { + match value { + Value::Null => "NoneType", + Value::Bool(_) => "bool", + Value::Number(number) if number.is_f64() => "float", + Value::Number(_) => "int", + Value::String(_) => "str", + Value::Array(_) => "list", + Value::Object(_) => "dict", + } +} + +fn kept_display( + display: Option<&Recognized>, + context: &ThinkingContext, +) -> Option> { + match display? { + Recognized::Known(ThinkingDisplay::Summarized | ThinkingDisplay::Omitted) => { + display.cloned() + } + Recognized::Known(ThinkingDisplay::Updates) if context.keeps_display_updates => { + display.cloned() + } + Recognized::Known(ThinkingDisplay::Updates) | Recognized::Unrecognized(_) => None, + } +} + +/// Keys Python's `carried_thinking_keys` keeps on the rebuilt adaptive config: the adaptive +/// keys always, and any other key unless `drop_params` is set. +fn carried_thinking_keys( + extra: &serde_json::Map, + context: &ThinkingContext, +) -> serde_json::Map { + extra + .iter() + .filter(|(key, _)| key.as_str() == "block_binding" || !context.drop_params) + .map(|(key, value)| (key.clone(), value.clone())) + .collect() +} + +/// `AnthropicModelInfo.translate_legacy_thinking_for_adaptive_model_silently`. fn translate_legacy_thinking_for_adaptive_model( request: MessagesRequest, context: &ThinkingContext, -) -> MessagesRequest { +) -> Result { let capabilities = &context.capabilities; if !capabilities.supports_adaptive_thinking || capabilities.supports_legacy_thinking { - return request; + return Ok(request); } let Some(ThinkingConfig::Enabled(enabled)) = known_thinking(&request) else { - return request; + return Ok(request); }; - let budget = enabled - .budget_tokens - .as_ref() - .and_then(Recognized::known) - .copied() - .unwrap_or(0); - let level = effort_for_budget(&context.budgets, budget, capabilities); - MessagesRequest { + let budget = match &enabled.budget_tokens { + None => Some(0), + Some(budget) => numeric_budget_tokens(budget), + }; + if budget.is_none() && !context.drop_params { + let actual = match &enabled.budget_tokens { + Some(Recognized::Unrecognized(value)) => python_type_name(value), + Some(Recognized::Known(_)) | None => "int", + }; + return Err(Error::InvalidRequest( + crate::ErrorDetail::NonNumericThinkingBudget { actual }, + )); + } + let thinking = ThinkingConfig::Adaptive(AdaptiveThinking { + display: kept_display(enabled.display.as_ref(), context), + extra: carried_thinking_keys(&enabled.extra, context), + }); + let output_config = match budget { + Some(budget) => with_default_effort( + request.params.output_config, + effort_for_budget(&context.budgets, budget, capabilities), + ), + None => request.params.output_config, + }; + Ok(MessagesRequest { params: MessagesOptionalParams { - thinking: Some(Recognized::Known(ThinkingConfig::adaptive(None))), - output_config: with_default_effort(request.params.output_config, level), + thinking: Some(Recognized::Known(thinking)), + output_config, ..request.params }, ..request - } + }) } fn translate_adaptive_effort_for_non_adaptive_model( @@ -337,7 +435,7 @@ pub fn translate_thinking( ) -> Result { let request = translate_reasoning_effort(request, context)?; let request = drop_disabled_thinking(request, context); - let request = translate_legacy_thinking_for_adaptive_model(request, context); + let request = translate_legacy_thinking_for_adaptive_model(request, context)?; let request = translate_adaptive_effort_for_non_adaptive_model(request, context)?; Ok(drop_incompatible_temperature_for_thinking(request, context)) } @@ -363,6 +461,7 @@ mod tests { ThinkingContext { capabilities, budgets: ThinkingBudgets::default(), + ..ThinkingContext::default() } } @@ -1239,10 +1338,102 @@ mod tests { let context = ThinkingContext { capabilities, budgets: overridden_budgets(overrides), + ..ThinkingContext::default() }; assert_eq!( translate_thinking(request(input), &context), Ok(request(expected)) ); } + + use serde_json::json; + + fn legacy_context(drop_params: bool, keeps_display_updates: bool) -> ThinkingContext { + ThinkingContext { + drop_params, + keeps_display_updates, + ..context(opus_4_7()) + } + } + + #[rstest] + #[case::float_budget(json!(8192.0), "xhigh")] + #[case::float_below_a_tier(json!(1023.9), "low")] + #[case::string_budget(json!(" 16_000 "), "xhigh")] + #[case::negative_budget(json!(-5), "low")] + fn legacy_budgets_read_like_python_numbers(#[case] budget: Value, #[case] effort: &str) { + let translated = translate_thinking( + request( + json!({"max_tokens": 64000, "thinking": {"type": "enabled", "budget_tokens": budget}}), + ), + &legacy_context(false, false), + ); + assert_eq!( + translated, + Ok(request(json!({ + "max_tokens": 64000, + "thinking": {"type": "adaptive"}, + "output_config": {"effort": effort}, + }))) + ); + } + + #[rstest] + #[case::text(json!("lots"), "str")] + #[case::list(json!([1]), "list")] + #[case::null(Value::Null, "NoneType")] + #[case::boolean(json!(true), "bool")] + fn a_non_numeric_legacy_budget_is_rejected_unless_dropped( + #[case] budget: Value, + #[case] actual: &'static str, + ) { + let fields = + json!({"max_tokens": 8192, "thinking": {"type": "enabled", "budget_tokens": budget}}); + assert_eq!( + translate_thinking(request(fields.clone()), &legacy_context(false, false)), + Err(Error::InvalidRequest( + crate::ErrorDetail::NonNumericThinkingBudget { actual } + )) + ); + assert_eq!( + translate_thinking(request(fields), &legacy_context(true, false)), + Ok(request( + json!({"max_tokens": 8192, "thinking": {"type": "adaptive"}}) + )) + ); + } + + #[rstest] + #[case::summarized("summarized", false, Some("summarized"))] + #[case::updates_kept("updates", true, Some("updates"))] + #[case::updates_dropped("updates", false, None)] + #[case::unknown("verbose", true, None)] + fn legacy_display_survives_only_where_python_keeps_it( + #[case] display: &str, + #[case] keeps_display_updates: bool, + #[case] kept: Option<&str>, + ) { + let translated = translate_thinking( + request(json!({"max_tokens": 4096, "thinking": {"type": "enabled", "budget_tokens": 2048, "display": display}})), + &legacy_context(false, keeps_display_updates), + ) + .unwrap(); + let thinking = serde_json::to_value(translated.params.thinking).unwrap(); + assert_eq!(thinking.get("display").and_then(Value::as_str), kept); + } + + #[rstest] + #[case::kept(false, json!({"type": "adaptive", "block_binding": "strict", "note": "x"}))] + #[case::dropped(true, json!({"type": "adaptive", "block_binding": "strict"}))] + fn legacy_extra_keys_follow_drop_params(#[case] drop_params: bool, #[case] expected: Value) { + let translated = translate_thinking( + request(json!({"max_tokens": 4096, "thinking": {"type": "enabled", "budget_tokens": 2048, "block_binding": "strict", "note": "x"}})), + &legacy_context(drop_params, false), + ) + .unwrap(); + assert_eq!( + serde_json::to_value(translated.params.thinking).unwrap(), + expected + ); + } } diff --git a/litellm-rust/crates/llms/src/anthropic/messages/transformation.rs b/litellm-rust/crates/llms/src/anthropic/messages/transformation.rs index fb6d7259bf9..18789e5b2be 100644 --- a/litellm-rust/crates/llms/src/anthropic/messages/transformation.rs +++ b/litellm-rust/crates/llms/src/anthropic/messages/transformation.rs @@ -56,7 +56,7 @@ impl BaseMessagesConfig for AnthropicMessagesConfig { request: MessagesRequest, context: &MessagesTransformContext, ) -> Result { - transform_messages_request(request, context) + transform_messages_request(request, &context.keeping_display_updates()) } fn secret_names(&self) -> &'static [&'static str] { @@ -206,6 +206,8 @@ fn feature_betas(request: &MessagesRequest) -> BetaSet { .then_some(AnthropicBeta::PerTurnControl20260701), uses_thinking_display_updates(params) .then_some(AnthropicBeta::ThinkingDisplayUpdates20260818), + uses_thinking_block_binding(params) + .then_some(AnthropicBeta::ThinkingBindingControls20260801), messages_carry_tool_changes(&request.messages) .then_some(AnthropicBeta::MidConversationToolChanges20260701), has_advisor_tool(tools).then_some(AnthropicBeta::AdvisorTool20260301), @@ -267,6 +269,25 @@ fn uses_thinking_display_updates(params: &MessagesOptionalParams) -> bool { display.and_then(Recognized::known) == Some(&ThinkingDisplay::Updates) } +/// `AnthropicModelInfo.thinking_betas`: any thinking object carrying `block_binding`. +fn uses_thinking_block_binding(params: &MessagesOptionalParams) -> bool { + match params.thinking.as_ref() { + Some(Recognized::Known(ThinkingConfig::Enabled(thinking))) => { + thinking.extra.contains_key("block_binding") + } + Some(Recognized::Known(ThinkingConfig::Adaptive(thinking))) => { + thinking.extra.contains_key("block_binding") + } + Some(Recognized::Known(ThinkingConfig::Disabled(thinking))) => { + thinking.extra.contains_key("block_binding") + } + Some(Recognized::Unrecognized(Value::Object(thinking))) => { + thinking.contains_key("block_binding") + } + Some(Recognized::Unrecognized(_)) | None => false, + } +} + fn is_tool_reference_change(block: &ContentBlock) -> bool { matches!( &block.block_type, @@ -297,7 +318,8 @@ fn unsupported_param(model: &str, param: &str, value: &str, hint: &str) -> Error }) } -fn drop_unsupported_params( +/// The speed and sampling gates of Python's `get_requested_anthropic_messages_optional_param`. +pub fn drop_unsupported_params( request: MessagesRequest, context: &MessagesTransformContext, ) -> Result { @@ -838,6 +860,8 @@ mod tests { low: 2000, ..ThinkingBudgets::default() }, + drop_params: true, + keeps_display_updates: false, }, drop_params: true, } diff --git a/litellm-rust/crates/llms/src/azure_ai/messages/transformation.rs b/litellm-rust/crates/llms/src/azure_ai/messages/transformation.rs index a2ba2cee0d3..d13cfa81a94 100644 --- a/litellm-rust/crates/llms/src/azure_ai/messages/transformation.rs +++ b/litellm-rust/crates/llms/src/azure_ai/messages/transformation.rs @@ -68,7 +68,7 @@ impl BaseMessagesConfig for AzureAnthropicMessagesConfig { .capabilities .supports_mid_conversation_system, )), - context, + &context.keeping_display_updates(), ) } diff --git a/litellm-rust/crates/llms/src/base_llm/messages/context.rs b/litellm-rust/crates/llms/src/base_llm/messages/context.rs index e59a63813b0..b514e975aa4 100644 --- a/litellm-rust/crates/llms/src/base_llm/messages/context.rs +++ b/litellm-rust/crates/llms/src/base_llm/messages/context.rs @@ -110,6 +110,11 @@ impl ThinkingBudgets { pub struct ThinkingContext { pub capabilities: MessagesModelCapabilities, pub budgets: ThinkingBudgets, + /// `drop_params` as Python's thinking translation reads it. + pub drop_params: bool, + /// The provider accepts `display: "updates"` on thinking translated from the legacy shape + /// (Python's `LEGACY_THINKING_DISPLAY_UPDATES_PROVIDERS`). + pub keeps_display_updates: bool, } #[derive(Clone, Copy, Debug, Default, PartialEq, Eq)] pub struct MessagesTransformContext { @@ -130,8 +135,22 @@ impl MessagesTransformContext { thinking: ThinkingContext { capabilities, budgets: ThinkingBudgets::from_lookup(env), + drop_params, + keeps_display_updates: false, }, drop_params, } } + + /// The same context for a provider in Python's `LEGACY_THINKING_DISPLAY_UPDATES_PROVIDERS`. + #[must_use] + pub fn keeping_display_updates(&self) -> Self { + Self { + thinking: ThinkingContext { + keeps_display_updates: true, + ..self.thinking + }, + ..*self + } + } } diff --git a/litellm-rust/crates/llms/src/error.rs b/litellm-rust/crates/llms/src/error.rs index b3d1421083a..2844fbf3e01 100644 --- a/litellm-rust/crates/llms/src/error.rs +++ b/litellm-rust/crates/llms/src/error.rs @@ -92,6 +92,24 @@ impl Error { } } + pub fn upstream_headers(&self) -> &[(String, String)] { + match self { + Self::Http(error) => error.upstream_headers(), + _ => &[], + } + } + + pub fn is_body_read_timeout(&self) -> bool { + matches!(self, Self::Http(error) if error.is_body_read_timeout()) + } + + pub fn is_timeout(&self) -> Option { + match self { + Self::Http(error) if error.is_timeout() => Some(error.is_connect_timeout()), + _ => None, + } + } + pub fn upstream_response(&self) -> Option<(u16, &str)> { match self { Self::Http(error) => error.upstream_response(), @@ -158,6 +176,10 @@ pub enum ErrorDetail { value: String, hint: String, }, + #[error( + "thinking.budget_tokens must be a number, got {actual}. To drop it, set `litellm.drop_params=True`, or `drop_params: true` under `litellm_settings` on the proxy" + )] + NonNumericThinkingBudget { actual: &'static str }, #[error( "Missing API Base - A call is being made to LLM Provider but no api base is set either in the environment variables ({{LLM_PROVIDER}}_API_KEY) or via params" )] diff --git a/litellm-rust/crates/llms/src/vertex_ai/messages/transformation.rs b/litellm-rust/crates/llms/src/vertex_ai/messages/transformation.rs index e5e3a056fab..038617c2e10 100644 --- a/litellm-rust/crates/llms/src/vertex_ai/messages/transformation.rs +++ b/litellm-rust/crates/llms/src/vertex_ai/messages/transformation.rs @@ -77,7 +77,7 @@ impl BaseMessagesConfig for VertexAiPartnerModelsAnthropicMessagesConfig { request: MessagesRequest, context: &MessagesTransformContext, ) -> Result { - let request = transform_messages_request(request, context)?; + let request = transform_messages_request(request, &context.keeping_display_updates())?; let request = strip_cache_control_scope(normalize_system_role_messages( request, context diff --git a/litellm-rust/crates/model-catalog/src/lower.rs b/litellm-rust/crates/model-catalog/src/lower.rs index 4c3fc38a01a..7acfc781431 100644 --- a/litellm-rust/crates/model-catalog/src/lower.rs +++ b/litellm-rust/crates/model-catalog/src/lower.rs @@ -104,6 +104,7 @@ impl From<&EntryWire> for Adjustments { (Uplift::NonGlobalEndpoint, wire.regional_endpoint_uplift), (Uplift::Residency(Residency::Eu), wire.residency_uplift_eu), (Uplift::Residency(Residency::Us), wire.residency_uplift_us), + (Uplift::FedrampEndpoint, wire.fedramp_uplift), ] .into_iter() .filter_map(|(uplift, factor)| Some((uplift, factor?))), @@ -746,7 +747,8 @@ mod tests { fn uplifts_are_adjustments_not_prices() { let wire = wire(json!({ "regional_endpoint_uplift_multiplier": 1.1, - "regional_processing_uplift_multiplier_eu": "1.2" + "regional_processing_uplift_multiplier_eu": "1.2", + "fedramp_uplift_multiplier": 1.1 })); let adjustments = Adjustments::from(&wire); @@ -764,6 +766,12 @@ mod tests { Some(1.2) ); assert_eq!(adjustments.get(&Uplift::Residency(Residency::Us)), None); + assert_eq!( + adjustments + .get(&Uplift::FedrampEndpoint) + .map(Multiplier::get), + Some(1.1) + ); } #[rstest] diff --git a/litellm-rust/crates/model-catalog/src/model_info.rs b/litellm-rust/crates/model-catalog/src/model_info.rs index 8f7549c1c6d..afbbfec59e6 100644 --- a/litellm-rust/crates/model-catalog/src/model_info.rs +++ b/litellm-rust/crates/model-catalog/src/model_info.rs @@ -96,6 +96,7 @@ pub struct ModelInfoFields { pub output_cost_per_token_ultrafast: Option, pub regional_processing_uplift_multiplier_eu: Option, pub regional_processing_uplift_multiplier_us: Option, + pub fedramp_uplift_multiplier: Option, pub regional_endpoint_uplift_multiplier: Option, pub output_cost_per_audio_token: Option, pub output_cost_per_character: Option, @@ -186,6 +187,9 @@ pub struct ModelInfoFields { pub supports_image_size: Option, pub supported_audio_formats: Option, pub token_count_framing: Option, + pub token_count_tool_framing: Option, + pub token_count_responses_framing: Option, + pub token_count_responses_tool_framing: Option, pub token_count_model: Option, pub token_count_tokenizer: Option, pub vertex_ai_audio_api: Option, diff --git a/litellm-rust/crates/model-catalog/src/schema.rs b/litellm-rust/crates/model-catalog/src/schema.rs index 66f9933a3e3..6fba985a8bd 100644 --- a/litellm-rust/crates/model-catalog/src/schema.rs +++ b/litellm-rust/crates/model-catalog/src/schema.rs @@ -29,6 +29,8 @@ struct PriceBlocks { regional_processing_uplift_multiplier_eu: Option, /// Multiplier applied to all token costs for US data residency (e.g. 1.10 = +10%). regional_processing_uplift_multiplier_us: Option, + /// Multiplier applied to all token costs when served from the OpenAI FedRAMP endpoint (e.g. 1.10 = +10%). + fedramp_uplift_multiplier: Option, /// USD cost per web search query, keyed by search context size. search_context_cost_per_query: Option, /// Context-length or result-count tiered rates; each tier's costs apply within its range. diff --git a/litellm-rust/crates/model-catalog/src/vocabulary.rs b/litellm-rust/crates/model-catalog/src/vocabulary.rs index 2b7ac8bd1ab..6bf2cc55224 100644 --- a/litellm-rust/crates/model-catalog/src/vocabulary.rs +++ b/litellm-rust/crates/model-catalog/src/vocabulary.rs @@ -93,6 +93,12 @@ pub enum Endpoint { Realtime, #[serde(rename = "/v1/realtime/transcription_sessions")] RealtimeTranscriptionSessions, + #[serde(rename = "/v1/realtime/translations")] + RealtimeTranslations, + #[serde(rename = "/v1/realtime/translations/calls")] + RealtimeTranslationCalls, + #[serde(rename = "/v1/realtime/translations/client_secrets")] + RealtimeTranslationClientSecrets, #[serde(rename = "/v1/videos")] Videos, #[serde(rename = "/v1/ocr")] diff --git a/litellm-rust/crates/model-catalog/src/wire/attributes.rs b/litellm-rust/crates/model-catalog/src/wire/attributes.rs index 93c10a81524..401634f8c62 100644 --- a/litellm-rust/crates/model-catalog/src/wire/attributes.rs +++ b/litellm-rust/crates/model-catalog/src/wire/attributes.rs @@ -11,7 +11,7 @@ use crate::error::{DateCause, Error, Repr}; use crate::vocabulary::{ AudioFormat, EffortLevel, Endpoint, InputModality, Mode, OutputModality, VertexAiAudioApi, }; -use crate::wire::lax::Count; +use crate::wire::lax::{Count, NumericCount}; macro_rules! attributes { ($($(#[$doc:meta])* $name:ident: $ty:ty $(as $via:ty)?),* $(,)?) => { @@ -93,6 +93,10 @@ attributes! { search_free_requests: SearchFreeRequests, /// URL of the provider pricing/model page this entry was taken from. source: String, + /// Model the provider recommends migrating to before `deprecation_date`, as a catalog key when one exists. + successor_model: String, + /// URL of the provider page or feed `deprecation_date` was read from. + deprecation_source: String, /// Audio container formats the model can return. supported_audio_formats: Vec, /// OpenAI-style API routes this model can be called through, e.g. /v1/chat/completions. @@ -104,9 +108,14 @@ attributes! { /// Cloud regions the model is available in ('global' or region ids). supported_regions: Vec, thinking_always_on: bool, - token_count_framing: u64 as Count, + /// Whether the model thinks when the request carries no thinking param. + thinking_on_by_default: bool, + token_count_framing: u64 as NumericCount, token_count_model: TokenCountModel, + token_count_responses_framing: u64 as NumericCount, + token_count_responses_tool_framing: u64 as NumericCount, token_count_tokenizer: TokenCountTokenizer, + token_count_tool_framing: u64 as NumericCount, /// Provider default tokens-per-minute limit. tpm: u64 as Count, use_openai_responses_path: bool, @@ -298,10 +307,28 @@ mod tests { #[case::known_mode("mode", json!("chat"), true)] #[case::unknown_mode("mode", json!("chatt"), false)] #[case::negative_dbu("input_dbu_cost_per_token", json!(-1), false)] + #[case::successor_model("successor_model", json!("gpt-6-luna"), true)] + #[case::successor_model_not_a_name("successor_model", json!(["gpt-6-luna"]), false)] + #[case::deprecation_source("deprecation_source", json!("https://developers.openai.com/api/docs/deprecations"), true)] + #[case::deprecation_source_not_a_url_string("deprecation_source", json!(7), false)] + #[case::thinking_on_by_default("thinking_on_by_default", json!(true), true)] + #[case::thinking_on_by_default_not_a_flag("thinking_on_by_default", json!("yes"), false)] #[case::reasoning_contexts("reasoning_contexts", json!(["reasoning", "non_reasoning"]), true)] #[case::reasoning_modes("reasoning_modes", json!(["none", "adaptive"]), true)] #[case::reasoning_context_not_a_list("reasoning_contexts", json!("reasoning"), false)] #[case::reasoning_mode_not_a_string("reasoning_modes", json!([1]), false)] + #[case::framing("token_count_framing", json!(12), true)] + #[case::framing_written_as_text("token_count_framing", json!("12"), false)] + #[case::framing_written_as_whole_float("token_count_framing", json!(12.0), true)] + #[case::fractional_tool_framing("token_count_tool_framing", json!(1.5), false)] + #[case::tool_framing("token_count_tool_framing", json!(214), true)] + #[case::tool_framing_written_as_text("token_count_tool_framing", json!("214"), false)] + #[case::tool_framing_as_a_flag("token_count_tool_framing", json!(true), false)] + #[case::negative_tool_framing("token_count_tool_framing", json!(-1), false)] + #[case::responses_framing("token_count_responses_framing", json!(38), true)] + #[case::responses_framing_as_a_flag("token_count_responses_framing", json!(false), false)] + #[case::responses_tool_framing("token_count_responses_tool_framing", json!(267), true)] + #[case::responses_tool_framing_written_as_text("token_count_responses_tool_framing", json!("267"), false)] fn each_attribute_reads_its_own_type( #[case] key: &str, #[case] value: Value, diff --git a/litellm-rust/crates/model-catalog/src/wire/entry.rs b/litellm-rust/crates/model-catalog/src/wire/entry.rs index 9c155c6496a..d0bdb394720 100644 --- a/litellm-rust/crates/model-catalog/src/wire/entry.rs +++ b/litellm-rust/crates/model-catalog/src/wire/entry.rs @@ -24,6 +24,7 @@ pub struct EntryWire { pub regional_endpoint_uplift: Option, pub residency_uplift_eu: Option, pub residency_uplift_us: Option, + pub fedramp_uplift: Option, pub unknown: Fields, pub problems: Vec, } @@ -57,6 +58,7 @@ impl EntryWire { "regional_processing_uplift_multiplier_us" => { self.residency_uplift_us = reader.value(path(), value) } + "fedramp_uplift_multiplier" => self.fedramp_uplift = reader.value(path(), value), _ => self.read_open_key(reader, key, value), } } diff --git a/litellm-rust/crates/model-catalog/src/wire/lax.rs b/litellm-rust/crates/model-catalog/src/wire/lax.rs index d514a6a82c1..d98a601e8c1 100644 --- a/litellm-rust/crates/model-catalog/src/wire/lax.rs +++ b/litellm-rust/crates/model-catalog/src/wire/lax.rs @@ -8,6 +8,8 @@ pub(crate) struct LaxI64; pub(crate) struct Count; +pub(crate) struct NumericCount; + impl<'de> DeserializeAs<'de, i64> for LaxI64 { fn deserialize_as>(deserializer: D) -> Result { deserializer.deserialize_any(Self) @@ -52,6 +54,34 @@ impl<'de> DeserializeAs<'de, u64> for Count { } } +impl<'de> DeserializeAs<'de, u64> for NumericCount { + fn deserialize_as>(deserializer: D) -> Result { + deserializer.deserialize_any(Self) + } +} + +impl Visitor<'_> for NumericCount { + type Value = u64; + + fn expecting(&self, formatter: &mut fmt::Formatter<'_>) -> fmt::Result { + formatter.write_str("a whole number of zero or more") + } + + fn visit_u64(self, value: u64) -> Result { + Ok(value) + } + + fn visit_i64(self, value: i64) -> Result { + u64::try_from(value).map_err(|_| E::invalid_value(de::Unexpected::Signed(value), &self)) + } + + fn visit_f64(self, value: f64) -> Result { + integral_float(value) + .and_then(|whole| u64::try_from(whole).ok()) + .ok_or_else(|| E::invalid_value(de::Unexpected::Float(value), &self)) + } +} + fn integer_string(value: &str) -> Option { let integer = match value.split_once('.') { Some((integer, fraction)) => { @@ -99,6 +129,12 @@ mod tests { .map(DeserializeAsWrap::into_inner) } + fn numeric_count(value: Value) -> Option { + DeserializeAsWrap::::deserialize(value) + .ok() + .map(DeserializeAsWrap::into_inner) + } + use serde::Deserialize; #[rstest] @@ -125,4 +161,23 @@ mod tests { ) { assert_eq!(count(written), expected); } + + #[rstest] + #[case::integer(json!(214), Some(214))] + #[case::zero(json!(0), Some(0))] + #[case::whole_float(json!(214.0), Some(214))] + #[case::negative_zero(json!(-0.0), Some(0))] + #[case::above_i64(json!(u64::MAX), Some(u64::MAX))] + #[case::negative(json!(-1), None)] + #[case::negative_whole_float(json!(-1.0), None)] + #[case::fraction(json!(1.5), None)] + #[case::string(json!("214"), None)] + #[case::boolean(json!(true), None)] + #[case::list(json!([214]), None)] + fn numeric_counts_accept_only_whole_json_numbers( + #[case] written: Value, + #[case] expected: Option, + ) { + assert_eq!(numeric_count(written), expected); + } } diff --git a/litellm-rust/crates/python-bridge/Cargo.toml b/litellm-rust/crates/python-bridge/Cargo.toml index e3ef45f7876..ba892199dcf 100644 --- a/litellm-rust/crates/python-bridge/Cargo.toml +++ b/litellm-rust/crates/python-bridge/Cargo.toml @@ -25,12 +25,11 @@ litellm-tracing.workspace = true litellm-spend-clickhouse.workspace = true litellm-storage-clickhouse.workspace = true litellm-host.workspace = true +async-trait.workspace = true bytes.workspace = true futures-util.workspace = true litellm-cache.workspace = true litellm-error.workspace = true -litellm-cache-memory.workspace = true -litellm-cache-redis.workspace = true litellm-cache-response.workspace = true serde.workspace = true litellm-auth.workspace = true @@ -49,6 +48,7 @@ litellm-secrets = { workspace = true, features = ["aws", "azure", "google", "has litellm-secrets-types.workspace = true litellm-llms-types.workspace = true litellm-router-types.workspace = true +litellm-router-core.workspace = true litellm-host-python.workspace = true litellm-model-catalog.workspace = true litellm-token-counter = { path = "../token-counter", default-features = false } @@ -56,7 +56,6 @@ pyo3.workspace = true prost.workspace = true pyo3-async-runtimes.workspace = true reqwest.workspace = true -redis = { workspace = true, features = ["tls-rustls"] } serde_json.workspace = true strum.workspace = true veil.workspace = true diff --git a/litellm-rust/crates/python-bridge/src/cache/AGENTS.md b/litellm-rust/crates/python-bridge/src/cache/AGENTS.md index 41c82187373..e79562b8762 100644 --- a/litellm-rust/crates/python-bridge/src/cache/AGENTS.md +++ b/litellm-rust/crates/python-bridge/src/cache/AGENTS.md @@ -1,7 +1,7 @@ # Cache boundary -This folder owns how Rust inference reaches the selected cache: global cache selection, route admission, delegation to a Python cache and the experimental V2 native handles. Cache algorithms, storage protocols and response-cache semantics belong to their cache crates +This folder owns how Rust inference reaches the selected Python cache. Cache algorithms, storage protocols and response-cache semantics belong to their cache crates -`mod.rs` exposes the cache boundary to routes and module registration. Adapter directories remain private. `selection.rs` asks `litellm.rust_bridge.host.cache` for the live configured cache, and owns route admission and inference protocol composition for both adapters +`mod.rs` exposes the cache boundary to routes. `selection.rs` asks `litellm.rust_bridge.host.cache` for the live configured cache and owns route admission and inference protocol composition -`python/` delegates operations to the selected Python cache without discovering configuration. `native/` owns the experimental V2 native cache handles. Neither adapter depends on shared selection or the other adapter. Shared composition depends on the adapters, and routes use only the parent module's exports +`python/` delegates operations to the selected Python cache without discovering configuration. Routes use only the parent module's exports diff --git a/litellm-rust/crates/python-bridge/src/cache/mod.rs b/litellm-rust/crates/python-bridge/src/cache/mod.rs index 87dba3efcb1..4e3847951d8 100644 --- a/litellm-rust/crates/python-bridge/src/cache/mod.rs +++ b/litellm-rust/crates/python-bridge/src/cache/mod.rs @@ -1,32 +1,15 @@ -mod native; mod python; mod selection; -pub(crate) use native::NativeCacheHandle; pub(crate) use python::{CacheCall, PythonCache}; -pub(crate) use selection::{Cached, Selection, configure, configured_native}; +pub(crate) use selection::{Cached, Selection, configure, ensure_cache_disabled}; -use litellm_cache::Error; -use pyo3::{ - exceptions::{PyNotImplementedError, PyRuntimeError, PyValueError}, - prelude::*, -}; +use pyo3::{exceptions::PyRuntimeError, prelude::*}; -/// A cache call the bridge rejects itself, before or after the cache ran. #[derive(Debug, thiserror::Error)] pub(crate) enum HandleError { - #[error("recreate the v2 cache after fork")] - Forked, - #[error("cache limits must be positive")] - Limits, - #[error("namespace and a positive cache limit are required")] - RedisLimits, - #[error("cache durations must be finite and positive")] - Duration(#[source] Option), - #[error("unsupported v2 cache control: {0}")] - Control(String), - #[error("native inference needs a v2 cache, the catalog keeps Python caches on Python")] - NotNative, + #[error("this inference route does not support configured caches")] + Unsupported, #[error("cache operation without configured cache")] Unconfigured, #[error("cache arguments unavailable")] @@ -39,66 +22,10 @@ impl From for PyErr { fn from(error: HandleError) -> Self { let message = litellm_error::Report::new(&error).to_string(); match error { - HandleError::Limits - | HandleError::RedisLimits - | HandleError::Duration(_) - | HandleError::Control(_) => PyValueError::new_err(message), - HandleError::Forked - | HandleError::NotNative + HandleError::Unsupported | HandleError::Unconfigured | HandleError::MissingArguments | HandleError::NothingPending => PyRuntimeError::new_err(message), } } } - -fn cache_error(error: Error) -> PyErr { - let message = litellm_error::Report::new(&error).to_string(); - match error { - Error::InvalidEntry(_) => PyValueError::new_err(message), - Error::UnsupportedOperation => PyNotImplementedError::new_err(message), - Error::Unavailable(_) | Error::UnscopedFlush | Error::MissingPrompt => { - PyRuntimeError::new_err(message) - } - } -} - -#[cfg(test)] -mod tests { - use pyo3::{ - exceptions::{PyRuntimeError, PyValueError}, - prelude::*, - }; - use rstest::rstest; - - use super::{Error, cache_error}; - - fn refused() -> std::io::Error { - std::io::Error::other("connection refused") - } - - #[rstest] - #[case::unavailable( - Error::unavailable(refused()), - false, - "cache is unavailable: connection refused" - )] - #[case::invalid_entry( - Error::invalid_entry(refused()), - true, - "invalid cache entry: connection refused" - )] - fn python_sees_the_class_and_the_whole_chain( - #[case] error: Error, - #[case] caller_fault: bool, - #[case] message: &str, - ) { - Python::initialize(); - Python::attach(|py| { - let failure = cache_error(error); - assert_eq!(failure.is_instance_of::(py), caller_fault); - assert_eq!(failure.is_instance_of::(py), !caller_fault); - assert_eq!(failure.value(py).to_string(), message); - }); - } -} diff --git a/litellm-rust/crates/python-bridge/src/cache/native/AGENTS.md b/litellm-rust/crates/python-bridge/src/cache/native/AGENTS.md deleted file mode 100644 index 09a34d188cd..00000000000 --- a/litellm-rust/crates/python-bridge/src/cache/native/AGENTS.md +++ /dev/null @@ -1,9 +0,0 @@ -# Native cache bindings - -This directory exposes the experimental V2 native cache handles (`NativeCacheHandle`) to Python. Cache algorithms and storage protocols remain in their cache crates - -Accept the cache object selected by the parent module. Do not read global `litellm.cache`, decide route admission, or select the Python cache adapter here - -Keep Python-facing cache classes and method signatures stable when reorganizing modules. Native internals stay private to this directory unless the shared cache boundary or Python module registration needs them - -Verify changes with the V2 cache tests using a freshly built extension. Test cache behavior, not module paths or file structure diff --git a/litellm-rust/crates/python-bridge/src/cache/native/mod.rs b/litellm-rust/crates/python-bridge/src/cache/native/mod.rs deleted file mode 100644 index da1460f90ed..00000000000 --- a/litellm-rust/crates/python-bridge/src/cache/native/mod.rs +++ /dev/null @@ -1,3 +0,0 @@ -pub(super) mod v2; - -pub(crate) use v2::NativeCacheHandle; diff --git a/litellm-rust/crates/python-bridge/src/cache/native/v2.rs b/litellm-rust/crates/python-bridge/src/cache/native/v2.rs deleted file mode 100644 index c54cb641843..00000000000 --- a/litellm-rust/crates/python-bridge/src/cache/native/v2.rs +++ /dev/null @@ -1,336 +0,0 @@ -use crate::cache::{HandleError, cache_error}; -use std::{ - sync::Arc, - time::{Duration, SystemTime, UNIX_EPOCH}, -}; - -use litellm_cache::{DeleteCache, DisconnectCache, PingCache}; -use litellm_host_python::{from_py, release_gil, to_py}; -use serde_json::Value; - -use litellm_cache_memory::InMemoryCache; -use litellm_cache_redis::{RedisCache, RedisTopology}; -use litellm_cache_response::{ - CacheEntry, CacheKeyInput, ExactResponseCache, ResponseCache, ResponseCacheCodec, - ResponseCacheConfig, ResponseCacheRequest, ResponseCacheService, -}; -use pyo3::{prelude::*, types::PyDict}; - -#[pyclass( - frozen, - name = "NativeCacheHandle", - module = "litellm.rust_bridge._native" -)] -pub(crate) struct NativeCacheHandle { - service: Arc, - backend: Arc, - storage: Storage, - pid: u32, -} - -#[derive(Clone)] -enum Storage { - Memory(Arc>), - Redis(Arc>), -} - -impl NativeCacheHandle { - fn check_process(&self) -> PyResult<()> { - if self.pid != std::process::id() { - return Err(HandleError::Forked.into()); - } - Ok(()) - } -} - -fn request(key: String, ttl: Option) -> PyResult { - let mut request: ResponseCacheRequest = ResponseCacheRequest::new(CacheKeyInput { - preset: Some(key), - ..Default::default() - }); - request.context.ttl = ttl.map(duration).transpose()?; - Ok(request) -} - -#[pymethods] -impl NativeCacheHandle { - #[staticmethod] - #[pyo3(signature = (*, ttl=600.0, capacity=200, max_entry_bytes=4194304))] - fn memory(ttl: f64, capacity: usize, max_entry_bytes: usize) -> PyResult { - let ttl = duration(ttl)?; - if capacity == 0 || max_entry_bytes == 0 { - return Err(HandleError::Limits.into()); - } - let storage = Arc::new(InMemoryCache::new(Some(capacity), Some(ttl))); - let backend = Arc::new(ResponseCache::new(storage.clone()).with_config( - ResponseCacheConfig { - namespace: "sdk".into(), - max_entry_bytes, - }, - )); - Ok(Self { - service: backend.clone(), - backend, - storage: Storage::Memory(storage), - pid: std::process::id(), - }) - } - - #[staticmethod] - #[pyo3(signature = (url, *, namespace, ttl=600.0, max_entry_bytes=4194304))] - fn redis( - py: Python<'_>, - url: &str, - namespace: String, - ttl: f64, - max_entry_bytes: usize, - ) -> PyResult { - let ttl = duration(ttl)?; - if namespace.is_empty() || max_entry_bytes == 0 { - return Err(HandleError::RedisLimits.into()); - } - let storage = Arc::new( - release_gil(py, || { - RedisCache::connect( - url, - &RedisTopology::Standalone, - Some(ttl), - ResponseCacheCodec, - ) - }) - .map_err(cache_error)? - .with_namespace(Some(namespace.clone())), - ); - let backend = Arc::new(ResponseCache::new(storage.clone()).with_config( - ResponseCacheConfig { - namespace, - max_entry_bytes, - }, - )); - Ok(Self { - service: backend.clone(), - backend, - storage: Storage::Redis(storage), - pid: std::process::id(), - }) - } - fn get(&self, py: Python<'_>, key: String) -> PyResult> { - self.check_process()?; - let request = request(key, None)?; - let value = - release_gil(py, || self.backend.lookup(&request, now())).map_err(cache_error)?; - to_py(py, &value) - } - - #[pyo3(signature = (key, value, *, ttl=None))] - fn set( - &self, - py: Python<'_>, - key: String, - value: &Bound<'_, PyAny>, - ttl: Option, - ) -> PyResult<()> { - self.check_process()?; - let request = request(key, ttl)?; - let value: Value = from_py(value)?; - release_gil(py, || self.backend.store(&request, value, now())).map_err(cache_error) - } - - fn async_get<'py>(&self, py: Python<'py>, key: String) -> PyResult> { - self.check_process()?; - let request = request(key, None)?; - let backend = self.backend.clone(); - crate::execution::run_async( - py, - async move { backend.async_lookup(&request, now()).await }, - cache_error, - ) - } - - #[pyo3(signature = (key, value, *, ttl=None))] - fn async_set<'py>( - &self, - py: Python<'py>, - key: String, - value: &Bound<'_, PyAny>, - ttl: Option, - ) -> PyResult> { - self.check_process()?; - let request = request(key, ttl)?; - let value: Value = from_py(value)?; - let backend = self.backend.clone(); - crate::execution::run_async( - py, - async move { backend.async_store(&request, value, now()).await }, - cache_error, - ) - } - - #[pyo3(signature = (entries, *, ttl=None))] - fn async_set_many<'py>( - &self, - py: Python<'py>, - entries: &Bound<'_, PyAny>, - ttl: Option, - ) -> PyResult> { - self.check_process()?; - let entries: Vec<(String, Value)> = from_py(entries)?; - let entries = entries - .into_iter() - .map(|(key, value)| Ok((request(key, ttl)?, value))) - .collect::>>()?; - let backend = self.backend.clone(); - crate::execution::run_async( - py, - async move { backend.async_store_batch(entries, now()).await }, - cache_error, - ) - } - - fn flush(&self, py: Python<'_>) -> PyResult> { - self.check_process()?; - let backend = self.backend.clone(); - crate::execution::run_sync(py, async move { backend.async_flush().await }, cache_error) - } - - fn async_flush<'py>(&self, py: Python<'py>) -> PyResult> { - self.check_process()?; - let backend = self.backend.clone(); - crate::execution::run_async(py, async move { backend.async_flush().await }, cache_error) - } - - fn ping<'py>(&self, py: Python<'py>) -> PyResult> { - self.check_process()?; - let storage = self.storage.clone(); - crate::execution::run_async( - py, - async move { - match storage { - Storage::Memory(_) => Ok(true), - Storage::Redis(cache) => cache.ping().await, - } - }, - cache_error, - ) - } - - fn disconnect<'py>(&self, py: Python<'py>) -> PyResult> { - self.check_process()?; - let storage = self.storage.clone(); - crate::execution::run_async( - py, - async move { - match storage { - Storage::Memory(cache) => cache.disconnect().await, - Storage::Redis(cache) => cache.disconnect().await, - } - }, - cache_error, - ) - } - - fn delete<'py>(&self, py: Python<'py>, keys: Vec) -> PyResult> { - self.check_process()?; - let storage = self.storage.clone(); - crate::execution::run_async( - py, - async move { - for key in keys { - match &storage { - Storage::Memory(cache) => cache.async_delete_cache(&key).await?, - Storage::Redis(cache) => cache.async_delete_cache(&key).await?, - } - } - Ok(()) - }, - cache_error, - ) - } -} - -fn duration(seconds: f64) -> Result { - match Duration::try_from_secs_f64(seconds) { - Ok(duration) if !duration.is_zero() => Ok(duration), - Ok(_) => Err(HandleError::Duration(None)), - Err(error) => Err(HandleError::Duration(Some(error))), - } -} - -pub(in crate::cache) fn native_handle<'py>( - configured: &Bound<'py, PyAny>, -) -> PyResult>> { - Ok(configured - .getattr_opt("cache")? - .map(|backend| backend.getattr_opt("native_handle")) - .transpose()? - .flatten() - .filter(|handle| handle.is_instance_of::())) -} - -pub(in crate::cache) fn configured( - configured: &Bound<'_, PyAny>, - kwargs: &Bound<'_, PyDict>, -) -> PyResult<( - Option>, - litellm_cache_response::CacheOptions, -)> { - let handle = native_handle(configured)?.ok_or(HandleError::NotNative)?; - let cache = handle.extract::>()?; - cache.check_process()?; - let controls = kwargs.get_item("cache")?.filter(|value| !value.is_none()); - let controls = controls - .as_ref() - .map(|value| value.cast::()) - .transpose()?; - if let Some(controls) = controls { - for name in controls.keys() { - let name = name.extract::()?; - if !matches!( - name.as_str(), - "no-cache" | "no-store" | "ttl" | "s-maxage" | "s-max-age" | "use-cache" - ) { - return Err(HandleError::Control(name).into()); - } - } - } - let boolean = |name: &str| -> PyResult { - controls - .map(|values| values.get_item(name)) - .transpose()? - .flatten() - .map(|value| value.extract()) - .transpose() - .map(|value| value.unwrap_or(false)) - }; - let seconds = |name: &str| -> PyResult> { - controls - .map(|values| values.get_item(name)) - .transpose()? - .flatten() - .map(|value| Ok(duration(value.extract()?)?)) - .transpose() - }; - Ok(( - Some(cache.service.clone()), - litellm_cache_response::CacheOptions { - policy: litellm_cache_response::CachePolicy { - caching: kwargs - .get_item("caching")? - .filter(|value| !value.is_none()) - .map(|value| value.extract()) - .transpose()?, - no_cache: boolean("no-cache")?, - no_store: boolean("no-store")?, - ttl: seconds("ttl")?, - max_age: seconds("s-max-age")?.or(seconds("s-maxage")?), - }, - scope: litellm_cache_response::CacheScope::Shared, - }, - )) -} - -fn now() -> Duration { - SystemTime::now() - .duration_since(UNIX_EPOCH) - .unwrap_or_default() -} diff --git a/litellm-rust/crates/python-bridge/src/cache/selection.rs b/litellm-rust/crates/python-bridge/src/cache/selection.rs index 00fc7cd822f..e96f079e5da 100644 --- a/litellm-rust/crates/python-bridge/src/cache/selection.rs +++ b/litellm-rust/crates/python-bridge/src/cache/selection.rs @@ -1,14 +1,10 @@ -use super::{native, python}; -use litellm_cache_response::{ - CacheOptions, CachePolicy, CacheScope, ResponseCacheService, ScopedCache, -}; +use super::{HandleError, python}; +use litellm_cache_response::{CacheOptions, CachePolicy, CacheScope, ScopedCache}; use litellm_host::{ machine::{HostServices, MachineFault}, protocol::Protocol, }; use pyo3::{prelude::*, types::PyDict}; -use std::sync::Arc; - const CACHE_HOST_MODULE: &str = "litellm.rust_bridge.host.cache"; pub(crate) struct Cached

(std::marker::PhantomData

); @@ -24,7 +20,6 @@ impl Protocol for Cached

{ enum Backend { Disabled, - Native(Arc), Python { namespace: String }, } @@ -43,7 +38,6 @@ impl Selection { { let service = match self.backend { Backend::Disabled => None, - Backend::Native(service) => Some(service), Backend::Python { namespace } => Some(python::service(services, namespace)), }; ( @@ -76,37 +70,21 @@ fn selected_cache<'py>( Ok(Some(configured)) } -pub(crate) fn configured_native( +pub(crate) fn ensure_cache_disabled( py: Python<'_>, kwargs: &Bound<'_, PyDict>, call_type: &str, -) -> PyResult<( - Option>, - litellm_cache_response::CacheOptions, -)> { +) -> PyResult<()> { let Some(configured) = selected_cache(py, kwargs, call_type)? else { - return Ok(( - None, - litellm_cache_response::CacheOptions::new(litellm_cache_response::CacheScope::Shared), - )); + return Ok(()); }; - native_configuration(&configured, kwargs) -} - -fn native_configuration( - configured: &Bound<'_, PyAny>, - kwargs: &Bound<'_, PyDict>, -) -> PyResult<(Option>, CacheOptions)> { - if !configured + if configured .call_method("should_use_cache", (), Some(kwargs))? .extract::()? { - return Ok(( - None, - litellm_cache_response::CacheOptions::new(litellm_cache_response::CacheScope::Shared), - )); + return Err(HandleError::Unsupported.into()); } - native::v2::configured(configured, kwargs) + Ok(()) } pub(crate) fn configure( @@ -122,13 +100,6 @@ pub(crate) fn configure( options: CacheOptions::new(CacheScope::Shared), }); }; - if native::v2::native_handle(&cache)?.is_some() { - let (native, options) = native_configuration(&cache, arguments)?; - return Ok(Selection { - backend: native.map_or(Backend::Disabled, Backend::Native), - options, - }); - } let enabled = cache .call_method("should_use_cache", (), Some(arguments))? .extract::()?; diff --git a/litellm-rust/crates/python-bridge/src/errors.rs b/litellm-rust/crates/python-bridge/src/errors.rs index b42c08b7e78..426cd861729 100644 --- a/litellm-rust/crates/python-bridge/src/errors.rs +++ b/litellm-rust/crates/python-bridge/src/errors.rs @@ -23,6 +23,17 @@ pyo3::create_exception!( ); const MESSAGES_REQUEST_ERROR: &str = "messages_request_error"; +/// The rejection is a parameter the model does not support, which Python raises as +/// `UnsupportedParamsError`. +const MESSAGES_UNSUPPORTED_PARAM: &str = "messages_unsupported_param"; +/// The phase label (`Connection` or `Read`) of a timed-out call, for Python's timeout text, or +/// `Body` for a streamed body read that timed out after the head arrived. +const MESSAGES_TIMEOUT: &str = "messages_timeout"; +/// No credential reached the provider, which Python raises as `AuthenticationError`. +const MESSAGES_MISSING_CREDENTIAL: &str = "messages_missing_credential"; +/// Python refuses the request only once its logger knows the resolved model and provider (the +/// provider config's request transform), so the failure logs them. +const MESSAGES_LATE_REJECTION: &str = "messages_late_rejection"; pub(crate) fn upstream_error( py: Python<'_>, @@ -78,17 +89,57 @@ pub(crate) fn route_failure( return Ok(raised); } if let Some((status, body)) = error.upstream_response() { - return public(upstream_error(py, status, body, &HeaderMap::new())?); + let headers = error + .upstream_headers() + .iter() + .filter_map(|(name, value)| { + Some(( + reqwest::header::HeaderName::from_bytes(name.as_bytes()).ok()?, + reqwest::header::HeaderValue::from_str(value).ok()?, + )) + }) + .collect::(); + return public(upstream_error(py, status, body, &headers)?); } let native = match (marker, error.rejected_request()) { (RequestMarker::Messages, Some(rejection)) => { let native = PyValueError::new_err(Report::new(rejection).to_string()); - native.value(py).setattr(MESSAGES_REQUEST_ERROR, true)?; + let value = native.value(py); + value.setattr(MESSAGES_REQUEST_ERROR, true)?; + if matches!( + rejection.downcast_ref::(), + Some( + litellm_llms::ErrorDetail::UnsupportedParameter { .. } + | litellm_llms::ErrorDetail::NonNumericThinkingBudget { .. } + ) + ) { + value.setattr(MESSAGES_UNSUPPORTED_PARAM, true)?; + } + if matches!( + rejection.downcast_ref::(), + Some(litellm_llms::ErrorDetail::NonNumericThinkingBudget { .. }) + ) { + value.setattr(MESSAGES_LATE_REJECTION, true)?; + } native } - (RequestMarker::Messages, None) | (RequestMarker::Unmarked, _) => { - by_fault(error.is_request(), &error) + (RequestMarker::Messages, None) => { + let native = by_fault(error.is_request(), &error); + let value = native.value(py); + if let Some(connect) = error.timeout() { + let phase = match (connect, error.body_read_timeout()) { + (true, _) => "Connection", + (false, true) => "Body", + (false, false) => "Read", + }; + value.setattr(MESSAGES_TIMEOUT, phase)?; + } + if error.is_missing_credential() { + value.setattr(MESSAGES_MISSING_CREDENTIAL, true)?; + } + native } + (RequestMarker::Unmarked, _) => by_fault(error.is_request(), &error), }; public(native) } diff --git a/litellm-rust/crates/python-bridge/src/lib.rs b/litellm-rust/crates/python-bridge/src/lib.rs index fdcb969a423..f4a4f7c2b26 100644 --- a/litellm-rust/crates/python-bridge/src/lib.rs +++ b/litellm-rust/crates/python-bridge/src/lib.rs @@ -12,6 +12,7 @@ mod marshal; mod model_registry; mod preflight; mod python_settings; +mod router; mod routes; mod secrets; mod tokenizer; @@ -36,6 +37,8 @@ mod _native { #[pymodule_export] use crate::model_registry::bundled_model_cost_map; #[pymodule_export] + use crate::router::{RouterCall, RouterCoreHandle}; + #[pymodule_export] use crate::routes::audio_transcription::{atranscription, transcription}; #[pymodule_export] use crate::routes::chat_completions::{acompletion, completion}; @@ -65,10 +68,6 @@ mod _native { fn init(module: &Bound<'_, PyModule>) -> PyResult<()> { let py = module.py(); let dict = module.dict(); - dict.set_item( - "NativeCacheHandle", - py.get_type::(), - )?; dict.set_item( "_SecretManagerRuntime", py.get_type::(), @@ -92,7 +91,6 @@ mod tests { Python::initialize(); Python::attach(|py| { let mut expected = vec![ - "NativeCacheHandle", "RustBridgeDeclined", "RustUpstreamError", "ForkedAfterNativeRuntimeStarted", @@ -120,6 +118,8 @@ mod tests { "bundled_model_cost_map", "TokenCounter", "Tokenizer", + "RouterCoreHandle", + "RouterCall", "gil_stats", "process_state_started", "reserve_process_for_forking", diff --git a/litellm-rust/crates/python-bridge/src/router/config.rs b/litellm-rust/crates/python-bridge/src/router/config.rs new file mode 100644 index 00000000000..0b46f2208c5 --- /dev/null +++ b/litellm-rust/crates/python-bridge/src/router/config.rs @@ -0,0 +1,408 @@ +//! The documents `RouterCoreHandle` reads: the router's static and dynamic config, a call's +//! request and an `apply` change set. A config key router-core does not read declines the +//! handle, so Python keeps the router on its own core. + +use std::collections::BTreeMap; + +use litellm_router_core::select::PassThrough; +use litellm_router_core::{ + ChangeSet, ConfigError, DeploymentSpec, OutcomeCallbacks, RouterConfig, RouterDynamicConfig, + RouterRequest, + config::{Fallbacks, RetryPolicy}, + host::UncountedRetries, + mock::MockFailure, + registry::IndexOverrides, +}; +use serde::{Deserialize, de::DeserializeOwned}; +use serde_json::{Map, Value}; + +/// The `RouterConfig` keys router-core reads. +const STATIC_KEYS: &[&str] = &[ + "model_list", + "routing_strategy", + "routing_groups", + "routing_group_members", + "plugins", + "cooldown_time", + "disable_cooldowns", + "allowed_fails_policy", + "retry_policy", + "model_group_retry_policy", + "retry_after", + "timeout", + "request_timeout", + "drop_params", + "enable_pre_call_checks", + "routing_plugins", + "callback_filters", + "enable_health_check_routing", + "health_check_staleness_threshold", + "background_health_check_model_groups", + "enable_weighted_failover", + "fallback_on_unsupported_params", + "provider_default_deployment_ids", +]; + +/// The `RouterDynamicConfig` keys router-core reads. +const DYNAMIC_KEYS: &[&str] = &[ + "version", + "model_alias_map", + "model_group_alias", + "fallbacks", + "default_fallbacks", + "context_window_fallbacks", + "content_policy_fallbacks", + "num_retries", + "max_fallbacks", + "allowed_fails", + "allowed_fails_is_default", + "fallback_keys", + "default_deployment", + "default_deployment_raises", +]; + +/// Router arguments that do not change routing, accepted in either config and dropped. +const IGNORED_KEYS: &[&str] = &[ + "set_verbose", + "debug_level", + "alerting_config", + "client_ttl", +]; + +/// Fallback lists Python treats as unset when empty (`context_window_fallbacks or None`). +const EMPTY_MEANS_UNSET: &[&str] = &["context_window_fallbacks", "content_policy_fallbacks"]; + +/// Which document a failure is about. +#[derive(Clone, Copy, Debug, PartialEq, Eq, strum::Display)] +pub(crate) enum Document { + #[strum(serialize = "router config")] + Static, + #[strum(serialize = "dynamic router config")] + Dynamic, + #[strum(serialize = "router request")] + Request, + #[strum(serialize = "change set")] + Changes, +} + +#[derive(Debug, thiserror::Error)] +pub(crate) enum Error { + #[error("the {document} must be a JSON object")] + NotObject { document: Document }, + #[error("router-core does not read `{key}` in the {document}")] + UnknownKey { document: Document, key: String }, + #[error("the {document} does not have the shape router-core reads")] + Shape { + document: Document, + #[source] + source: serde_json::Error, + }, + #[error("the request names no model")] + MissingModel, + #[error("router-core rejected the router config")] + Core(#[from] ConfigError), +} + +impl Error { + /// Whether router-core cannot serve this config, so Python keeps its own core. + pub(crate) fn declined(&self) -> bool { + match self { + Self::UnknownKey { .. } | Self::Core(_) => true, + Self::Shape { document, .. } => { + matches!(document, Document::Static | Document::Dynamic) + } + Self::NotObject { .. } | Self::MissingModel => false, + } + } +} + +fn object(document: Document, value: Value) -> Result, Error> { + match value { + Value::Object(object) => Ok(object), + _ => Err(Error::NotObject { document }), + } +} + +fn shaped(document: Document, object: Map) -> Result { + serde_json::from_value(Value::Object(object)) + .map_err(|source| Error::Shape { document, source }) +} + +/// Drop unset and ignored keys, then reject any key outside `known`. +fn routing_keys( + document: Document, + value: Value, + known: &[&str], +) -> Result, Error> { + let mut object = object(document, value)?; + object.retain(|key, value| { + let empty_unset = EMPTY_MEANS_UNSET.contains(&key.as_str()) + && value.as_array().is_some_and(Vec::is_empty); + !(value.is_null() || empty_unset || IGNORED_KEYS.contains(&key.as_str())) + }); + if let Some(key) = object.keys().find(|key| !known.contains(&key.as_str())) { + return Err(Error::UnknownKey { + document, + key: key.clone(), + }); + } + Ok(object) +} + +pub(crate) fn parse_router_config(value: Value) -> Result { + let object = routing_keys(Document::Static, value, STATIC_KEYS)?; + shaped(Document::Static, object) +} + +pub(crate) fn parse_dynamic_config(value: Value) -> Result { + let object = routing_keys(Document::Dynamic, value, DYNAMIC_KEYS)?; + shaped(Document::Dynamic, object) +} + +/// A call's request as Python spells it. +#[derive(Deserialize)] +#[serde(deny_unknown_fields)] +struct RequestSpec { + model: Option, + team_id: Option, + listing_team_id: Option, + proxy_admin: Option, + allowed_models: Option>, + admin_model: Option, + specific_deployment: Option, + num_retries: Option, + uncounted_retries: Option, + disable_fallbacks: Option, + router_weights: Option, + pinned_deployment_id: Option, + routing_strategy: Option, + filter_tags: Option, + /// `listed` or `healthy`: which pass-through pick the request makes. + pass_through: Option, + target_order: Option, + excluded_ids: Option>, + retry_skipped_ids: Option>, + pre_routes: Option, + has_image: Option, + endpoint: Option, + web_search: Option, + route_handler: Option, + decisions_media: Option, + wildcard_request: Option, + unrouted: Option, + passthrough_on_no_deployment: Option, + skip_weighted_failover: Option, + same_group_fallbacks_only: Option, + model_group_retry_policy: Option>, + retry_policy_raises: Option>, + #[serde(default, deserialize_with = "present")] + fallbacks: Option>, + #[serde(default, deserialize_with = "present")] + context_window_fallbacks: Option>, + #[serde(default, deserialize_with = "present")] + content_policy_fallbacks: Option>, + max_fallbacks: Option, + mock_failure: Option, + cooldown_time: Option, + health_check_probe: Option, + outcome_callbacks: Option, + body: Option, +} + +/// A key the request passed, even as `None`: `Some(None)`. +fn present<'de, D, T>(deserializer: D) -> Result>, D::Error> +where + D: serde::Deserializer<'de>, + T: Deserialize<'de>, +{ + Option::::deserialize(deserializer).map(Some) +} + +/// Read a request; `model` replaces the request's own when given. +pub(crate) fn parse_request(value: Value, model: Option<&str>) -> Result { + let spec: RequestSpec = shaped(Document::Request, object(Document::Request, value)?)?; + let model = model + .map(str::to_owned) + .or(spec.model) + .ok_or(Error::MissingModel)?; + Ok(RouterRequest { + model, + body: spec.body.unwrap_or_default(), + team_id: spec.team_id, + listing_team_id: spec.listing_team_id, + proxy_admin: spec.proxy_admin.unwrap_or(false), + allowed_models: spec.allowed_models.unwrap_or_default(), + admin_model: spec.admin_model, + specific_deployment: spec.specific_deployment.unwrap_or(false), + num_retries: spec.num_retries, + uncounted_retries: spec.uncounted_retries, + disable_fallbacks: spec.disable_fallbacks.unwrap_or(false), + router_weights: spec.router_weights, + pinned_deployment_id: spec.pinned_deployment_id, + routing_strategy: spec.routing_strategy, + filter_tags: spec.filter_tags.unwrap_or(false), + pass_through: match spec.pass_through.as_deref() { + None => None, + Some("healthy") => Some(PassThrough::Healthy), + Some(_) => Some(PassThrough::Listed), + }, + target_order: spec.target_order, + excluded_ids: spec.excluded_ids.unwrap_or_default(), + retry_skipped_ids: spec.retry_skipped_ids.unwrap_or_default(), + pre_routes: spec.pre_routes.unwrap_or(false), + has_image: spec.has_image.unwrap_or(false), + endpoint: spec.endpoint, + web_search: spec.web_search.unwrap_or(false), + route_handler: spec.route_handler, + decisions_media: spec.decisions_media.unwrap_or(false), + wildcard_request: spec.wildcard_request, + unrouted: spec.unrouted.unwrap_or(false), + passthrough_on_no_deployment: spec.passthrough_on_no_deployment.unwrap_or(false), + skip_weighted_failover: spec.skip_weighted_failover.unwrap_or(false), + same_group_fallbacks_only: spec.same_group_fallbacks_only.unwrap_or(false), + model_group_retry_policy: spec.model_group_retry_policy, + retry_policy_raises: spec.retry_policy_raises.unwrap_or_default(), + fallbacks: spec.fallbacks, + context_window_fallbacks: spec.context_window_fallbacks, + content_policy_fallbacks: spec.content_policy_fallbacks, + max_fallbacks: spec.max_fallbacks, + mock_failure: spec.mock_failure, + cooldown_time: spec.cooldown_time, + health_check_probe: spec.health_check_probe.unwrap_or(false), + outcome_callbacks: spec.outcome_callbacks.unwrap_or_default(), + payload: None, + }) +} + +#[derive(Deserialize)] +#[serde(deny_unknown_fields)] +struct ChangesSpec { + /// Every deployment, replacing the current list before the upserts and deletes. + #[serde(default)] + replace: Option>, + /// Deployments added at the end, beside any that share their id. + #[serde(default)] + append: Vec, + #[serde(default)] + upsert: Vec, + #[serde(default)] + delete: Vec, + /// A new dynamic document (the same keys `RouterCoreHandle(static, dynamic)` takes). + #[serde(default)] + settings: Option, + /// The registry indexes the host wrote (`IndexOverrides`); `{}` drops them. + #[serde(default)] + index: Option, + /// The deployment at the id map's position for this id, removed with every index shifted. + #[serde(default)] + remove: Option, + /// A write to the indexes the host hands out (`HostIndexes`), field by field. + #[serde(default)] + host_index: Option, +} + +pub(crate) fn parse_changes(value: Value) -> Result { + let spec: ChangesSpec = shaped(Document::Changes, object(Document::Changes, value)?)?; + Ok(ChangeSet { + replace: spec.replace, + appends: spec.append, + upserts: spec.upsert, + deletes: spec.delete, + settings: spec.settings.map(parse_dynamic_config).transpose()?, + index: spec.index, + remove: spec.remove, + host_index: spec.host_index, + }) +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + #[rstest] + #[case::unknown_key(json!({"routing_strategy_args": {"ttl": 1}}), "routing_strategy_args")] + #[case::dynamic_key_in_static(json!({"num_retries": 2}), "num_retries")] + fn an_unread_static_key_declines_naming_the_key(#[case] json: Value, #[case] key: &str) { + let error = parse_router_config(json).unwrap_err(); + assert!(error.declined()); + assert!(matches!(&error, Error::UnknownKey { key: named, .. } if named == key)); + } + + #[rstest] + #[case::null_unknown(json!({"routing_strategy_args": null}))] + #[case::ignored(json!({"set_verbose": true, "debug_level": "INFO"}))] + #[case::pre_call_checks_off(json!({"enable_pre_call_checks": false}))] + #[case::pre_call_checks_on(json!({"enable_pre_call_checks": true}))] + fn unset_and_ignored_keys_are_accepted(#[case] json: Value) { + parse_router_config(json).unwrap(); + } + + #[rstest] + #[case::not_object(json!([]), false)] + #[case::bad_shape(json!({"retry_after": "soon"}), true)] + fn a_config_that_is_not_an_object_is_a_value_error_and_a_wrong_shape_declines( + #[case] json: Value, + #[case] declined: bool, + ) { + assert_eq!(parse_router_config(json).unwrap_err().declined(), declined); + } + + #[rstest] + fn python_router_defaults_read_as_unset() { + let dynamic = parse_dynamic_config(json!({ + "num_retries": null, "fallbacks": [], "context_window_fallbacks": [], + "content_policy_fallbacks": [], "model_group_alias": {"gpt": "gpt-4"}, + })) + .unwrap(); + assert_eq!(dynamic.num_retries, None); + assert!(dynamic.context_window_fallbacks.is_none()); + assert!(dynamic.content_policy_fallbacks.is_none()); + assert_eq!(dynamic.model_alias_map["gpt"], "gpt-4"); + } + + #[rstest] + #[case::own_model(json!({"model": "gpt", "num_retries": 1}), None, "gpt")] + #[case::override_model(json!({"model": "gpt"}), Some("other"), "other")] + fn a_request_reads_its_model( + #[case] json: Value, + #[case] model: Option<&str>, + #[case] expected: &str, + ) { + assert_eq!(parse_request(json, model).unwrap().model, expected); + } + + #[rstest] + #[case::negative("negative", UncountedRetries::Negative)] + #[case::not_positive("not_positive", UncountedRetries::NotPositive)] + #[case::raises("raises", UncountedRetries::Raises)] + fn a_request_reads_a_num_retries_that_is_no_count( + #[case] spelled: &str, + #[case] expected: UncountedRetries, + ) { + let request = + parse_request(json!({"model": "gpt", "uncounted_retries": spelled}), None).unwrap(); + assert_eq!(request.uncounted_retries, Some(expected)); + assert_eq!(request.num_retries, None); + } + + #[rstest] + #[case::unknown_field(json!({"model": "gpt", "temperature": 1}))] + #[case::no_model(json!({"team_id": "t"}))] + fn a_bad_request_is_a_value_error(#[case] json: Value) { + assert!(!parse_request(json, None).unwrap_err().declined()); + } + + #[rstest] + fn a_change_set_reads_upserts_and_deletes() { + let changes = parse_changes(json!({ + "upsert": [{"model_name": "m", "litellm_params": {"model": "openai/x"}}], + "delete": ["old"], + })) + .unwrap(); + assert_eq!(changes.upserts.len(), 1); + assert_eq!(changes.deletes, ["old"]); + } +} diff --git a/litellm-rust/crates/python-bridge/src/router/host.rs b/litellm-rust/crates/python-bridge/src/router/host.rs new file mode 100644 index 00000000000..16b425d69c6 --- /dev/null +++ b/litellm-rust/crates/python-bridge/src/router/host.rs @@ -0,0 +1,1569 @@ +//! The host behind `RouterCoreHandle`. Rust never awaits Python: each host operation the call +//! loop needs becomes a [`HostCall`] parked in the call's [`Exchange`], and the call future stays +//! pending until Python runs it and hands the [`HostCallResponse`] back through [`Driver::resume`]. +//! +//! The driver polls the call future with a no-op waker while the call's exchange is bound to the +//! current thread, so a host future finds its exchange without the router passing it through. +//! +//! The routing cache is a host operation too: [`StepCache`] parks every [`RouterCache`] op as a +//! `cache` step, and Python runs it against the router's own `DualCache` (memory plus Redis), so +//! Python and Rust read and write the same cooldowns, fail counters and usage. + +use std::{ + cell::RefCell, + future::{Future, poll_fn}, + pin::Pin, + sync::{Arc, Mutex, MutexGuard, PoisonError}, + task::{Context, Poll, Waker}, + time::Duration, +}; + +use async_trait::async_trait; +use litellm_router_core::{ + Attempt, AttemptError, Blocked, BuildAsk, BuildPath, Built, Deployment, Error, Host, Output, + Payload, PreRoute, PreRouted, Provided, Randomness, RouterCache, RouterEvent, RouterRequest, + RouterResponse, RoutingContext, SecretRef, SelectStage, ThreadRandomness, + build::BuiltDeployment, host::ModelInfoLookup, model_info::MergedModelInfo, + precall::PreCallFacts, +}; +use pyo3::{PyResult, Python, types::PyAnyMethods}; +use serde_json::{Map, Value}; + +/// The `kind` of a step dict. +#[derive(Clone, Copy, Debug, PartialEq, Eq, strum::Display, strum::IntoStaticStr)] +pub(crate) enum StepKind { + #[strum(serialize = "attempt")] + Attempt, + #[strum(serialize = "sleep")] + Sleep, + #[strum(serialize = "allow_fallback")] + AllowFallback, + #[strum(serialize = "refuse_fallbacks")] + RefuseFallbacks, + #[strum(serialize = "select")] + Select, + #[strum(serialize = "pre_route")] + PreRoute, + #[strum(serialize = "cache")] + Cache, + #[strum(serialize = "secrets")] + Secrets, + #[strum(serialize = "validate")] + Validate, + #[strum(serialize = "provider")] + Provider, + #[strum(serialize = "added")] + Added, + #[strum(serialize = "model_info")] + ModelInfo, + #[strum(serialize = "done")] + Done, + #[strum(serialize = "failed")] + Failed, +} + +/// Which selection stage Python is asked to run. +#[derive(Clone, Debug, PartialEq)] +pub(crate) enum Stage { + /// Pre-call checks and sub-routers: return the deployments that remain. + Plugins, + /// A strategy router-core does not implement: return the candidates with the pick first. + Strategy(String), + /// Tag routing: return the deployments that remain. + Tags, + /// `enable_pre_call_checks`: return the facts the filter decides by. + PreCall, + /// `_deployment_declares_no_vision`: return the candidates that declare no vision support. + TextOnly, + /// `_deployment_serves_route`: return the candidates that cannot serve `handler`'s call. + RouteIncapable { handler: String }, + /// `_decisions_deployment_refuses_media`: return the candidates that refuse the call's media. + MediaRefusing, + /// The routing plugins: run them when `run`, then return the candidate models they left. + RoutingPlugins { run: bool }, + /// The host's `CustomLogger` deployment filters: return the ids that remain, or a failure. + /// They read the ids this request already failed on, as Python's request kwargs carry them. + CallbackFilters { + excluded_ids: Vec, + skipped_ids: Vec, + target_order: Option, + }, + /// `f"{provider}/{model}"` for a name no wildcard pattern matches as spelled: return it as + /// the one entry of `models`. + ProviderRequest, +} + +/// The `op` of a `cache` step: one per [`RouterCache`] method. +#[derive(Clone, Copy, Debug, PartialEq, Eq, strum::Display, strum::IntoStaticStr)] +pub(crate) enum CacheOp { + /// `async_get_cache(key)`: answered with the stored JSON value, or `None`. + #[strum(serialize = "get")] + Get, + /// `async_set_cache(key, value, ttl)`: answered with `None`. + #[strum(serialize = "set")] + Set, + /// `async_increment(key, value, ttl)`: answered with the new number. The TTL applies when + /// the key is created. + #[strum(serialize = "increment")] + Increment, + /// `async_increment_usage(keys, value, ttl)`: `value` is one amount per key, added as + /// `_increment_deployment_usage` adds them. Answered with `None`. + #[strum(serialize = "increment_usage")] + IncrementUsage, + /// `async_batch_get_cache(keys)`: answered with one JSON value or `None` per key, in order. + #[strum(serialize = "batch_get")] + BatchGet, + /// `async_delete_cache(key)`: answered with `None`. + #[strum(serialize = "delete")] + Delete, +} + +/// Python's outcome of a `cache` step. +#[derive(Clone, Debug, PartialEq)] +pub(crate) enum CacheOutcome { + /// `get`: the stored value (`None` when missing). + Value(Option), + /// `batch_get`: one entry per key. + Values(Vec>), + /// `increment`: the counter after the increment. + Number(f64), + /// `set`, `delete` and `increment_usage`. + Stored, +} + +impl CacheOutcome { + /// The op this outcome answers (`Stored` answers both `set` and `delete`). + fn answers(&self, op: CacheOp) -> bool { + matches!( + (self, op), + (Self::Value(_), CacheOp::Get) + | (Self::Values(_), CacheOp::BatchGet) + | (Self::Number(_), CacheOp::Increment) + | ( + Self::Stored, + CacheOp::Set | CacheOp::Delete | CacheOp::IncrementUsage + ) + ) + } +} + +/// A fallback chain's dict targets, which can carry an api key. +#[derive(Clone, PartialEq, veil::Redact)] +pub(crate) struct DictTargets(#[redact(with = "[REDACTED]")] pub(crate) Vec>); + +/// What a call is blocked on, for Python to run. +#[derive(Clone, Debug, PartialEq)] +pub(crate) enum HostCall { + Attempt { + deployment_id: String, + /// The picked deployment as configured: `model_name`, `litellm_params`, `model_info` + /// (with its `id`). The host builds the request from it; it never looks the deployment up + /// in a Python router. + deployment: Value, + /// The name the attempt resolved: the requested name or the fallback target. + model: String, + model_group: String, + /// The `order` level of a same-group order fallback. + target_order: Option, + /// Every deployment `model` resolved to for this caller, the picked one included. + candidate_ids: Vec, + retry: u32, + fallback_depth: u32, + fallback_level: u32, + timeout: Option, + /// Request params the fallback walk's dict targets merged in. + params: Option>, + /// The walk level whose request metadata the attempt carries. + scope: u32, + max_retries: u32, + model_group_size: usize, + }, + Sleep { + seconds: f64, + }, + AllowFallback { + target: String, + }, + RefuseFallbacks { + /// The walk level whose chain the targets are. + level: u32, + targets: DictTargets, + }, + Select { + stage: Stage, + model_group: String, + /// The name the request resolved from, which strategies key their state by. + name: String, + /// Whose selector a strategy reads: `default`, `group` (with `group`) or `override`. + scope: &'static str, + group: Option, + /// The deployments the name resolved to, before health filters (the tag stage reads them). + pool: Vec, + candidates: Vec, + }, + /// Pre-routing before a pick resolves `model`: answered with the model group to resolve + /// instead (a string), a custom strategy's deployment document (a mapping), or `None`. + PreRoute { + model: String, + fallback_depth: u32, + retry: u32, + }, + /// One [`RouterCache`] op against the host's cache. `key` is set for every op but + /// `batch_get`, which sets `keys`; `value` is set for `set` (the JSON to store) and + /// `increment` (the amount); `ttl` is in seconds. + Cache { + op: CacheOp, + key: Option, + keys: Option>, + value: Option, + ttl: Option, + /// The op reads or writes this worker's in-memory tier only (`local_only=True`). + local: bool, + }, + /// The deployment build's `os.environ/` references: answered with one value per ref. + Secrets { + index: usize, + refs: Vec, + }, + /// The deployment build's `validate`, `provider` and `added` steps for one deployment. + Build { + kind: StepKind, + path: BuildPath, + index: usize, + entry: Value, + declared_id: Option, + duplicate_id: bool, + /// The provider the `provider` step resolved (`added` only). + provider: Option, + }, + /// One lookup of a model-info query ([`ModelInfoLookup`], as its `lookup` field and + /// arguments): answered as the lookup documents. + ModelInfo { + lookup: Value, + }, +} + +impl HostCall { + pub(crate) fn kind(&self) -> StepKind { + match self { + Self::Attempt { .. } => StepKind::Attempt, + Self::Sleep { .. } => StepKind::Sleep, + Self::AllowFallback { .. } => StepKind::AllowFallback, + Self::RefuseFallbacks { .. } => StepKind::RefuseFallbacks, + Self::Select { .. } => StepKind::Select, + Self::PreRoute { .. } => StepKind::PreRoute, + Self::Cache { .. } => StepKind::Cache, + Self::Secrets { .. } => StepKind::Secrets, + Self::Build { kind, .. } => *kind, + Self::ModelInfo { .. } => StepKind::ModelInfo, + } + } +} + +/// Python's response to a [`HostCall`]. +#[derive(Debug)] +pub(crate) enum HostCallResponse { + /// The attempt's total tokens, or its failure. + Attempt(Result), + /// A successful attempt whose response the provider blocked, or a stream whose outcome the + /// host reports when it ends (`deferred`), with its tokens. + Served { + total_tokens: u64, + blocked: Option, + deferred: bool, + tracks_usage: Option, + }, + Slept, + AllowFallback(bool), + /// Whether the chain a `refuse_fallbacks` step named is refused. + RefuseFallbacks(bool), + /// The candidate ids that remain, pick first. + Select(Vec), + /// The model group to resolve instead, a custom strategy's deployment, or `None`. + PreRoute(Option), + /// The facts a `pre_call` select step asked for. + PreCall(PreCallFacts), + /// The candidate models a `routing_plugins` select step reported. + Models(Option>), + /// The ids a `callback_filters` select step left, or the error a filter raised. + Filtered(Result, AttemptError>), + /// What a pick's select or pre-route step, or a fallback check, raised on the host instead of + /// answering: the walk takes it as the try's failure. + Raised(AttemptError), + Cache(CacheOutcome), + /// One value per ref of a `secrets` step. + Secrets(Vec), + Validated(Built), + Provided(Provided), + Added(Built), + /// A `model_info` lookup's response, as the host spelled it. + ModelInfo(Value), +} + +impl HostCallResponse { + fn kind(&self) -> StepKind { + match self { + Self::Attempt(_) | Self::Served { .. } => StepKind::Attempt, + // Answers whichever step raised it (`check`). + Self::Raised(_) => StepKind::Select, + Self::Slept => StepKind::Sleep, + Self::AllowFallback(_) => StepKind::AllowFallback, + Self::RefuseFallbacks(_) => StepKind::RefuseFallbacks, + Self::Select(_) | Self::PreCall(_) | Self::Models(_) | Self::Filtered(_) => { + StepKind::Select + } + Self::PreRoute(_) => StepKind::PreRoute, + Self::Cache(_) => StepKind::Cache, + Self::Secrets(_) => StepKind::Secrets, + Self::Validated(_) => StepKind::Validate, + Self::Provided(_) => StepKind::Provider, + Self::Added(_) => StepKind::Added, + Self::ModelInfo(_) => StepKind::ModelInfo, + } + } + + fn check(&self, call: &HostCall) -> Result<(), DriveError> { + if matches!(self, Self::Raised(_)) + && matches!( + call.kind(), + StepKind::Select | StepKind::PreRoute | StepKind::AllowFallback + ) + { + return Ok(()); + } + if self.kind() != call.kind() { + return Err(DriveError::WrongAnswer { + expected: call.kind(), + got: self.kind(), + }); + } + if let (Self::Select(ids) | Self::Filtered(Ok(ids)), HostCall::Select { candidates, .. }) = + (self, call) + && let Some(id) = ids.iter().find(|id| !candidates.contains(id)) + { + return Err(DriveError::UnknownCandidate { id: id.clone() }); + } + if let (Self::Secrets(values), HostCall::Secrets { refs, .. }) = (self, call) + && values.len() != refs.len() + { + return Err(DriveError::SecretsLength { + expected: refs.len(), + got: values.len(), + }); + } + if let (Self::Cache(outcome), HostCall::Cache { op, keys, .. }) = (self, call) { + if !outcome.answers(*op) { + return Err(DriveError::WrongCacheOutcome { op: *op }); + } + if let (CacheOutcome::Values(values), Some(keys)) = (outcome, keys) + && values.len() != keys.len() + { + return Err(DriveError::BatchLength { + expected: keys.len(), + got: values.len(), + }); + } + } + Ok(()) + } +} + +/// How a driven future ended well. +#[derive(Debug)] +pub(crate) enum Finish { + /// `start`: the call's response. + Call(RouterResponse), + /// `select`: the deployment picked and the model group it serves. + Selected { + deployment_id: String, + model_group: String, + /// The deployment as served: a priority group's member carries its priority as `order`. + deployment: Value, + }, + /// `healthy`: the deployments a pick would choose among, as served. + Healthy { + /// A deployment named by its id, which the listing returns alone rather than as a list. + single: bool, + deployment_ids: Vec, + deployments: Vec, + }, + /// `report_failure`: the cooldown applied, if the deployment was cooled down. + Reported { cooldown: Option }, + /// `report_success` / `count_success`: the success counter's key, if one was counted. + Counted { key: Option }, + /// `build`: the deployments it installed, in order. + Built(Vec), + /// `router_model_info`: the merged model info (`None` when the lookup answered `None`). + RouterModelInfo(Option), + /// `deployment_model_info`: the merged model info, if any. + DeploymentModelInfo(Option>), + /// A model-info query that ends with one JSON answer (`model_group_info`, + /// `configured_token_limits`, `model_listing_info`). + Value(Value), +} + +/// One step of a call: what it is blocked on, or how it ended. +#[derive(Debug)] +pub(crate) enum Step { + HostCall(HostCall), + Done(Finish), + Failed(Error), +} + +/// A misuse of the step protocol by the caller. +#[derive(Debug, thiserror::Error)] +pub(crate) enum DriveError { + #[error("the router call already finished")] + Finished, + #[error("the router call has not made a host call yet, so the outcome must be None")] + UnexpectedResponse, + #[error("the router call is waiting for an outcome of its `{expected}` step")] + MissingResponse { expected: StepKind }, + #[error("the router call is waiting for an outcome of its `{expected}` step, not `{got}`")] + WrongAnswer { expected: StepKind, got: StepKind }, + #[error("deployment `{id}` was not one of the select step's candidates")] + UnknownCandidate { id: String }, + #[error("the outcome does not answer a `{op}` cache step")] + WrongCacheOutcome { op: CacheOp }, + #[error("a `batch_get` cache step for {expected} keys was answered with {got} values")] + BatchLength { expected: usize, got: usize }, + #[error("a `secrets` step for {expected} references was answered with {got} values")] + SecretsLength { expected: usize, got: usize }, + #[error("the router call is pending on something other than a step")] + Stalled, +} + +impl DriveError { + /// Whether the caller passed a bad outcome, rather than driving a call that cannot go on. + pub(crate) fn is_request(&self) -> bool { + match self { + Self::UnexpectedResponse + | Self::MissingResponse { .. } + | Self::WrongAnswer { .. } + | Self::UnknownCandidate { .. } + | Self::WrongCacheOutcome { .. } + | Self::BatchLength { .. } + | Self::SecretsLength { .. } => true, + Self::Finished | Self::Stalled => false, + } + } +} + +/// The host call a router call is blocked on and the response that releases it. +#[derive(Default)] +struct Exchange { + call: Option, + response: Option, + /// Events the call reported since the last step, handed to Python with the next one. + events: Vec, +} + +type Shared = Arc>; + +fn lock(exchange: &Mutex) -> MutexGuard<'_, Exchange> { + exchange.lock().unwrap_or_else(PoisonError::into_inner) +} + +thread_local! { + static CURRENT: RefCell> = const { RefCell::new(None) }; +} + +/// Binds an exchange to this thread for one poll and restores the previous one after. +struct Bound(Option); + +impl Bound { + fn new(exchange: &Shared) -> Self { + Self(CURRENT.replace(Some(exchange.clone()))) + } +} + +impl Drop for Bound { + fn drop(&mut self) { + CURRENT.set(self.0.take()); + } +} + +/// Park the host call `call` in the bound exchange and wait for its response. +/// `response`, or the failure a step answered with instead ([`HostCallResponse::Raised`]). +fn answered(response: HostCallResponse) -> Result { + match response { + HostCallResponse::Raised(failure) => Err(failure), + response => Ok(response), + } +} + +async fn call_host(call: HostCall) -> HostCallResponse { + let mut call = Some(call); + poll_fn(move |_| { + CURRENT.with_borrow(|current| { + let Some(exchange) = current else { + return Poll::Pending; + }; + let mut exchange = lock(exchange); + if let Some(call) = call.take() { + exchange.call = Some(call); + return Poll::Pending; + } + exchange.response.take().map_or(Poll::Pending, Poll::Ready) + }) + }) + .await +} + +const CHECKED: &str = "the driver checks each response against its host call"; + +fn ttl_seconds(ttl: Option) -> Option { + ttl.map(|ttl| ttl.as_secs_f64()) +} + +/// An increment amount as Python's counters store it: an int when it is whole. +fn amount_value(amount: f64) -> Value { + if amount.fract() == 0.0 && amount.abs() < i64::MAX as f64 { + Value::from(amount as i64) + } else { + Value::from(amount) + } +} + +/// The host's cache: every op is a `cache` step Python runs against the router's `DualCache`. +pub(crate) struct StepCache; + +async fn cache_step( + op: CacheOp, + key: Option<&str>, + keys: Option<&[String]>, + value: Option, + ttl: Option, +) -> CacheOutcome { + call_cache(op, key, keys, value, ttl, false).await +} + +async fn call_cache( + op: CacheOp, + key: Option<&str>, + keys: Option<&[String]>, + value: Option, + ttl: Option, + local: bool, +) -> CacheOutcome { + let call = HostCall::Cache { + op, + key: key.map(str::to_owned), + keys: keys.map(<[String]>::to_vec), + value, + ttl: ttl_seconds(ttl), + local, + }; + let HostCallResponse::Cache(outcome) = call_host(call).await else { + unreachable!("{CHECKED}"); + }; + outcome +} + +#[async_trait] +impl RouterCache for StepCache { + async fn async_get_cache(&self, key: &str) -> Result, litellm_cache::Error> { + let CacheOutcome::Value(value) = + cache_step(CacheOp::Get, Some(key), None, None, None).await + else { + unreachable!("{CHECKED}"); + }; + Ok(value) + } + + async fn async_set_cache( + &self, + key: &str, + value: Value, + ttl: Option, + ) -> Result<(), litellm_cache::Error> { + cache_step(CacheOp::Set, Some(key), None, Some(value), ttl).await; + Ok(()) + } + + async fn async_increment( + &self, + key: &str, + amount: f64, + ttl: Option, + ) -> Result { + let value = Some(amount_value(amount)); + let CacheOutcome::Number(next) = + cache_step(CacheOp::Increment, Some(key), None, value, ttl).await + else { + unreachable!("{CHECKED}"); + }; + Ok(next) + } + + async fn async_batch_get_cache( + &self, + keys: &[String], + ) -> Result>, litellm_cache::Error> { + let CacheOutcome::Values(values) = + cache_step(CacheOp::BatchGet, None, Some(keys), None, None).await + else { + unreachable!("{CHECKED}"); + }; + Ok(values) + } + + async fn async_delete_cache(&self, key: &str) -> Result<(), litellm_cache::Error> { + cache_step(CacheOp::Delete, Some(key), None, None, None).await; + Ok(()) + } + + async fn async_increment_usage( + &self, + increments: &[(String, f64)], + ttl: Option, + ) -> Result<(), litellm_cache::Error> { + let keys: Vec = increments.iter().map(|(key, _)| key.clone()).collect(); + let amounts = increments + .iter() + .map(|(_, amount)| amount_value(*amount)) + .collect(); + let value = Some(Value::Array(amounts)); + cache_step(CacheOp::IncrementUsage, None, Some(&keys), value, ttl).await; + Ok(()) + } + + async fn async_get_local(&self, key: &str) -> Result, litellm_cache::Error> { + let CacheOutcome::Value(value) = + call_cache(CacheOp::Get, Some(key), None, None, None, true).await + else { + unreachable!("{CHECKED}"); + }; + Ok(value) + } + + async fn async_increment_local( + &self, + key: &str, + amount: f64, + ttl: Option, + ) -> Result { + let value = Some(amount_value(amount)); + let CacheOutcome::Number(next) = + call_cache(CacheOp::Increment, Some(key), None, value, ttl, true).await + else { + unreachable!("{CHECKED}"); + }; + Ok(next) + } +} + +/// A deployment as Python spells a `model_list` entry, with its id in `model_info`. +pub(crate) fn deployment_record(deployment: &Deployment) -> Value { + deployment.record() +} + +/// The process's `random` module: a Python router draws its shuffle and retry jitter there, so +/// a seeded process picks the same deployments on either core. The bare module functions share +/// one generator, so these calls interleave with every other draw the process makes. +pub(crate) struct PythonRandomness; + +impl Randomness for PythonRandomness { + fn next_f64(&self) -> f64 { + Python::attach(|py| -> PyResult { + py.import("random")?.call_method0("random")?.extract() + }) + .unwrap_or_else(|_| ThreadRandomness.next_f64()) + } + + fn index_below(&self, len: usize) -> usize { + // `random.choice` is `seq[self._randbelow(len(seq))]`, and so is `randrange(len)`. + Python::attach(|py| -> PyResult { + py.import("random")? + .call_method1("randrange", (len,))? + .extract() + }) + .unwrap_or_else(|_| ThreadRandomness.index_below(len)) + } +} + +/// The [`Host`] every `RouterCoreHandle` router runs on. +pub(crate) struct StepHost; + +#[async_trait] +impl Host for StepHost { + async fn invoke(&self, attempt: &Attempt) -> Result { + let call = HostCall::Attempt { + deployment_id: attempt.deployment.id.clone(), + deployment: deployment_record(&attempt.deployment), + model: attempt.name.clone(), + model_group: attempt.model_group.clone(), + target_order: attempt.target_order, + candidate_ids: attempt.candidate_ids.clone(), + retry: attempt.retry, + fallback_depth: attempt.fallback_depth, + fallback_level: attempt.fallback_level, + timeout: attempt.timeout.map(|timeout| timeout.as_secs_f64()), + params: attempt + .params + .as_ref() + .map(|params| Box::new(Value::Object(Map::clone(params)))), + scope: attempt.scope, + max_retries: attempt.max_retries, + model_group_size: attempt.model_group_size, + }; + let (result, blocked, deferred, tracks_usage) = match call_host(call).await { + HostCallResponse::Attempt(result) => (result, None, false, None), + HostCallResponse::Served { + total_tokens, + blocked, + deferred, + tracks_usage, + } => (Ok(total_tokens), blocked, deferred, tracks_usage), + _ => unreachable!("{CHECKED}"), + }; + result.map(|total_tokens| Output { + value: Payload(Arc::new(())), + total_tokens, + blocked, + deferred, + tracks_usage, + }) + } + + async fn select( + &self, + stage: &SelectStage, + ctx: &RoutingContext<'_>, + candidates: Vec>, + ) -> Result>, Error> { + let (scope, group) = ctx.scope.wire(); + let call = HostCall::Select { + stage: match stage { + SelectStage::Plugins => Stage::Plugins, + SelectStage::Strategy(strategy) => Stage::Strategy(strategy.to_string()), + SelectStage::Tags => Stage::Tags, + SelectStage::TextOnly => Stage::TextOnly, + SelectStage::RouteIncapable { handler } => Stage::RouteIncapable { + handler: handler.clone(), + }, + SelectStage::MediaRefusing => Stage::MediaRefusing, + }, + pool: ctx.pool.iter().map(|d| d.id.clone()).collect(), + model_group: ctx.model_group.to_owned(), + name: ctx.name.to_owned(), + scope, + group: group.map(str::to_owned), + candidates: candidates.iter().map(|d| d.id.clone()).collect(), + }; + let HostCallResponse::Select(ids) = answered(call_host(call).await)? else { + unreachable!("{CHECKED}"); + }; + Ok(ids + .iter() + .filter_map(|id| candidates.iter().find(|d| d.id == *id).cloned()) + .collect()) + } + + async fn pre_route(&self, pre: &PreRoute<'_>) -> Result, Error> { + let call = HostCall::PreRoute { + model: pre.name.to_owned(), + fallback_depth: pre.fallback_depth, + retry: pre.retry, + }; + let HostCallResponse::PreRoute(routed) = answered(call_host(call).await)? else { + unreachable!("{CHECKED}"); + }; + Ok(routed) + } + + async fn routing_plugin_models( + &self, + ctx: &RoutingContext<'_>, + run: bool, + ) -> Result>, Error> { + let (scope, group) = ctx.scope.wire(); + let call = HostCall::Select { + stage: Stage::RoutingPlugins { run }, + pool: Vec::new(), + model_group: ctx.model_group.to_owned(), + name: ctx.name.to_owned(), + scope, + group: group.map(str::to_owned), + candidates: Vec::new(), + }; + let HostCallResponse::Models(models) = answered(call_host(call).await)? else { + unreachable!("{CHECKED}"); + }; + Ok(models) + } + + async fn provider_request(&self, ctx: &RoutingContext<'_>) -> Result, Error> { + let (scope, group) = ctx.scope.wire(); + let call = HostCall::Select { + stage: Stage::ProviderRequest, + pool: Vec::new(), + model_group: ctx.model_group.to_owned(), + name: ctx.name.to_owned(), + scope, + group: group.map(str::to_owned), + candidates: Vec::new(), + }; + let HostCallResponse::Models(models) = answered(call_host(call).await)? else { + unreachable!("{CHECKED}"); + }; + Ok(models.into_iter().flatten().next()) + } + + async fn pre_call_facts( + &self, + ctx: &RoutingContext<'_>, + candidates: &[Arc], + ) -> Result { + let (scope, group) = ctx.scope.wire(); + let call = HostCall::Select { + stage: Stage::PreCall, + pool: ctx.pool.iter().map(|d| d.id.clone()).collect(), + model_group: ctx.model_group.to_owned(), + name: ctx.name.to_owned(), + scope, + group: group.map(str::to_owned), + candidates: candidates.iter().map(|d| d.id.clone()).collect(), + }; + let HostCallResponse::PreCall(facts) = answered(call_host(call).await)? else { + unreachable!("{CHECKED}"); + }; + Ok(facts) + } + + async fn callback_filters( + &self, + ctx: &RoutingContext<'_>, + candidates: Vec>, + ) -> Result>, Error> { + let (scope, group) = ctx.scope.wire(); + let joined = |own: &[String], walked: &[String]| [own, walked].concat(); + let call = HostCall::Select { + stage: Stage::CallbackFilters { + excluded_ids: joined(&ctx.request.excluded_ids, ctx.excluded_ids), + skipped_ids: joined(&ctx.request.retry_skipped_ids, ctx.skipped_ids), + target_order: ctx.target_order, + }, + pool: Vec::new(), + model_group: ctx.model_group.to_owned(), + name: ctx.name.to_owned(), + scope, + group: group.map(str::to_owned), + candidates: candidates.iter().map(|d| d.id.clone()).collect(), + }; + let HostCallResponse::Filtered(result) = call_host(call).await else { + unreachable!("{CHECKED}"); + }; + let ids = result.map_err(Error::Attempt)?; + Ok(ids + .iter() + .filter_map(|id| candidates.iter().find(|d| d.id == *id).cloned()) + .collect()) + } + + async fn allow_fallback( + &self, + _request: &RouterRequest, + target: &str, + ) -> Result { + let call = HostCall::AllowFallback { + target: target.to_owned(), + }; + let HostCallResponse::AllowFallback(allowed) = answered(call_host(call).await)? else { + unreachable!("{CHECKED}"); + }; + Ok(allowed) + } + + async fn refuses_fallbacks(&self, level: u32, targets: &[Map]) -> bool { + let call = HostCall::RefuseFallbacks { + level, + targets: DictTargets(targets.to_vec()), + }; + let HostCallResponse::RefuseFallbacks(refused) = call_host(call).await else { + unreachable!("{CHECKED}"); + }; + refused + } + + /// A zero sleep is asked too: Python's retry loop awaits `asyncio.sleep(0)` between sibling + /// retries, which yields to the event loop. + async fn sleep(&self, duration: Duration) { + let call = HostCall::Sleep { + seconds: duration.as_secs_f64(), + }; + let HostCallResponse::Slept = call_host(call).await else { + unreachable!("{CHECKED}"); + }; + } + + /// Kept for Python only when it acts on it: an exhausted retry loop is stamped on the + /// error Python raises, a fallback hop tells it which target a failed walk ended on, and a + /// cooldown or a pick is reported to the host's Prometheus and service loggers (a pick also + /// joins the router cache's per-deployment count, a failed walk the router's error log). + fn observe(&self, event: &RouterEvent) { + if !matches!( + event, + RouterEvent::RetriesExhausted { .. } + | RouterEvent::Retry { .. } + | RouterEvent::Fallback { .. } + | RouterEvent::FallingBack { .. } + | RouterEvent::OrderChainFailed { .. } + | RouterEvent::FallbacksFailed { .. } + | RouterEvent::LevelFailed { .. } + | RouterEvent::PickFailed { .. } + | RouterEvent::RetriesOpened { .. } + | RouterEvent::RetryBudget { .. } + | RouterEvent::MockFailed { .. } + | RouterEvent::RetryLogged { .. } + | RouterEvent::RetryPolicyRaised { .. } + | RouterEvent::RetryCountRaised { .. } + | RouterEvent::FallbackDone { .. } + | RouterEvent::Blocked { .. } + | RouterEvent::CooldownSet { .. } + | RouterEvent::Selected { .. } + ) { + return; + } + CURRENT.with_borrow(|current| { + if let Some(exchange) = current { + lock(exchange).events.push(event.clone()); + } + }); + } + + fn cache(&self) -> Arc { + Arc::new(StepCache) + } + + async fn secrets(&self, index: usize, refs: &[SecretRef]) -> Result, Error> { + let HostCallResponse::Secrets(values) = call_host(HostCall::Secrets { + index, + refs: refs.to_vec(), + }) + .await + else { + unreachable!("{CHECKED}"); + }; + Ok(values) + } + + async fn validate(&self, build: &BuildAsk<'_>) -> Result { + let HostCallResponse::Validated(built) = + call_host(build_host_call(StepKind::Validate, build, None)).await + else { + unreachable!("{CHECKED}"); + }; + Ok(built) + } + + async fn provider(&self, build: &BuildAsk<'_>) -> Result { + let HostCallResponse::Provided(provided) = + call_host(build_host_call(StepKind::Provider, build, None)).await + else { + unreachable!("{CHECKED}"); + }; + Ok(provided) + } + + async fn added(&self, build: &BuildAsk<'_>, provider: Option<&str>) -> Result { + let HostCallResponse::Added(built) = + call_host(build_host_call(StepKind::Added, build, provider)).await + else { + unreachable!("{CHECKED}"); + }; + Ok(built) + } + + async fn model_info(&self, lookup: &ModelInfoLookup) -> Result { + let lookup = serde_json::to_value(lookup).unwrap_or(Value::Null); + let HostCallResponse::ModelInfo(response) = call_host(HostCall::ModelInfo { lookup }).await + else { + unreachable!("{CHECKED}"); + }; + Ok(response) + } +} + +fn build_host_call(kind: StepKind, build: &BuildAsk<'_>, provider: Option<&str>) -> HostCall { + HostCall::Build { + kind, + path: build.path, + index: build.index, + entry: Value::Object(build.entry.clone()), + declared_id: build.declared_id.map(str::to_owned), + duplicate_id: build.duplicate_id, + provider: provider.map(str::to_owned), + } +} + +type CallFuture = Pin> + Send>>; + +/// Poll `future` once with `exchange` bound. +fn poll_bound(future: Pin<&mut F>, exchange: &Shared) -> Poll { + let _bound = Bound::new(exchange); + future.poll(&mut Context::from_waker(Waker::noop())) +} + +/// Drives one router call a step at a time. +pub(crate) struct Driver { + future: Option, + exchange: Shared, + pending_call: Option, +} + +impl Driver { + pub(crate) fn new(call: impl Future> + Send + 'static) -> Self { + Self { + future: Some(Box::pin(call)), + exchange: Shared::default(), + pending_call: None, + } + } + + /// The host call the router call is blocked on, if it made one. + pub(crate) fn pending_call(&self) -> Option<&HostCall> { + self.pending_call.as_ref() + } + + /// The events reported since the last call. + pub(crate) fn take_events(&self) -> Vec { + std::mem::take(&mut lock(&self.exchange).events) + } + + /// Hand back the response to the pending host call (`None` on the first call) and run the call to + /// its next step or its end. + pub(crate) fn resume( + &mut self, + response: Option, + ) -> Result { + let Some(future) = self.future.as_mut() else { + return Err(DriveError::Finished); + }; + match (&self.pending_call, response) { + (None, None) => {} + (None, Some(_)) => return Err(DriveError::UnexpectedResponse), + (Some(call), None) => { + return Err(DriveError::MissingResponse { + expected: call.kind(), + }); + } + (Some(call), Some(response)) => { + response.check(call)?; + lock(&self.exchange).response = Some(response); + } + } + self.pending_call = None; + match poll_bound(future.as_mut(), &self.exchange) { + Poll::Ready(result) => { + self.future = None; + Ok(match result { + Ok(finish) => Step::Done(finish), + Err(error) => Step::Failed(error), + }) + } + Poll::Pending => { + let Some(call) = lock(&self.exchange).call.take() else { + self.future = None; + return Err(DriveError::Stalled); + }; + self.pending_call = Some(call.clone()); + Ok(Step::HostCall(call)) + } + } + } +} + +#[cfg(test)] +mod tests { + use std::{ + collections::HashMap, + time::{SystemTime, UNIX_EPOCH}, + }; + + use litellm_router_core::{ + FailureKind, Op, Router, RouterConfig, RouterDynamicConfig, SeededRandomness, + }; + use rstest::{fixture, rstest}; + use serde_json::{Value, json}; + + use super::*; + + fn router(config: Value, dynamic: Value) -> Router { + let config: RouterConfig = serde_json::from_value(config).unwrap(); + let dynamic: RouterDynamicConfig = serde_json::from_value(dynamic).unwrap(); + Router::builder(config, dynamic, Arc::new(StepHost)) + .randomness(Arc::new(SeededRandomness::new(7))) + .build() + .unwrap() + } + + fn deployment(group: &str, id: &str) -> Value { + json!({"model_name": group, "litellm_params": {"model": format!("openai/{id}")}, "model_info": {"id": id}}) + } + + fn start(router: &Router, model: &str) -> Driver { + let router = router.clone(); + let request = RouterRequest { + model: model.to_owned(), + ..RouterRequest::default() + }; + Driver::new(async move { + router + .call(Op::from("acompletion"), request) + .await + .map(Finish::Call) + }) + } + + fn rate_limited() -> HostCallResponse { + HostCallResponse::Attempt(Err(AttemptError::new(FailureKind::RateLimit, Some(429)))) + } + + /// A dict-backed stand-in for Python's `DualCache` that answers `cache` steps and keeps + /// every one it answered. + #[derive(Default)] + struct Store { + entries: HashMap, + calls: Vec, + } + + impl Store { + fn respond(&mut self, call: &HostCall) -> HostCallResponse { + let HostCall::Cache { + op, + key, + keys, + value, + .. + } = call + else { + panic!("not a cache step: {call:?}"); + }; + self.calls.push(call.clone()); + let key = key.clone().unwrap_or_default(); + HostCallResponse::Cache(match op { + CacheOp::Get => CacheOutcome::Value(self.entries.get(&key).cloned()), + CacheOp::Set => { + self.entries.insert(key, value.clone().unwrap()); + CacheOutcome::Stored + } + CacheOp::Increment => { + let current = self.entries.get(&key).and_then(Value::as_f64); + let next = + current.unwrap_or(0.0) + value.as_ref().and_then(Value::as_f64).unwrap(); + self.entries.insert(key, amount_value(next)); + CacheOutcome::Number(next) + } + CacheOp::IncrementUsage => { + let amounts = value.as_ref().and_then(Value::as_array).unwrap(); + for (key, amount) in keys.iter().flatten().zip(amounts) { + let current = self.entries.get(key).and_then(Value::as_f64); + let next = current.unwrap_or(0.0) + amount.as_f64().unwrap(); + self.entries.insert(key.clone(), amount_value(next)); + } + CacheOutcome::Stored + } + CacheOp::BatchGet => CacheOutcome::Values( + keys.iter() + .flatten() + .map(|key| self.entries.get(key).cloned()) + .collect(), + ), + CacheOp::Delete => { + self.entries.remove(&key); + CacheOutcome::Stored + } + }) + } + + /// Resume with `response`, answering every cache step on the way, up to the next other + /// step. + fn resume(&mut self, driver: &mut Driver, response: Option) -> Step { + let mut step = driver.resume(response).unwrap(); + while let Step::HostCall(call @ HostCall::Cache { .. }) = &step { + let response = self.respond(call); + step = driver.resume(Some(response)).unwrap(); + } + step + } + } + + #[fixture] + fn pair() -> Router { + router( + json!({"model_list": [deployment("primary", "a1"), deployment("primary", "a2")]}), + json!({}), + ) + } + + #[rstest] + fn a_first_attempt_success_is_done(pair: Router) { + let mut store = Store::default(); + let mut driver = start(&pair, "primary"); + let Step::HostCall(HostCall::Attempt { + deployment_id, + model_group, + retry: 0, + fallback_depth: 0, + .. + }) = store.resume(&mut driver, None) + else { + panic!("the call should start with an attempt"); + }; + assert_eq!(model_group, "primary"); + let Step::Done(Finish::Call(response)) = + store.resume(&mut driver, Some(HostCallResponse::Attempt(Ok(12)))) + else { + panic!("a successful attempt should finish the call"); + }; + assert_eq!(response.deployment_id, deployment_id); + assert_eq!(response.output.total_tokens, 12); + assert_eq!( + (response.attempted_retries, response.attempted_fallbacks), + (0, 0) + ); + assert!(matches!(driver.resume(None), Err(DriveError::Finished))); + } + + #[rstest] + fn cooldown_reads_are_cache_steps(pair: Router) { + let mut driver = start(&pair, "primary"); + let step = driver.resume(None).unwrap(); + let Step::HostCall(HostCall::Cache { + op: CacheOp::BatchGet, + key: None, + keys: Some(keys), + value: None, + ttl: None, + local: false, + }) = step + else { + panic!("the call should read cooldowns first, got {step:?}"); + }; + assert_eq!(keys, ["deployment:a1:cooldown", "deployment:a2:cooldown"]); + } + + #[rstest] + #[case::lone_deployment_backs_off(vec![deployment("primary", "a1")], true)] + #[case::sibling_retries_at_once( + vec![deployment("primary", "a1"), deployment("primary", "a2")], + false + )] + fn a_rate_limit_retries_after_the_backoff( + #[case] model_list: Vec, + #[case] backs_off: bool, + ) { + let router = router(json!({"model_list": model_list}), json!({"num_retries": 1})); + let mut store = Store::default(); + let mut driver = start(&router, "primary"); + assert_eq!( + store.resume(&mut driver, None).unwrap_kind(), + StepKind::Attempt + ); + let step = store.resume(&mut driver, Some(rate_limited())); + let Step::HostCall(HostCall::Sleep { seconds }) = step else { + panic!("a retry should sleep first, got {step:?}"); + }; + assert_eq!(seconds > 0.0, backs_off, "slept {seconds}s"); + let step = store.resume(&mut driver, Some(HostCallResponse::Slept)); + assert!( + matches!(step, Step::HostCall(HostCall::Attempt { retry: 1, .. })), + "expected the retry, got {step:?}" + ); + let Step::Done(Finish::Call(response)) = + store.resume(&mut driver, Some(HostCallResponse::Attempt(Ok(1)))) + else { + panic!("the retry should finish the call"); + }; + assert_eq!(response.attempted_retries, 1); + } + + #[rstest] + fn a_cooldown_python_wrote_is_read_back_by_the_next_call() { + let pair_without_retries = router( + json!({"model_list": [deployment("primary", "a1"), deployment("primary", "a2")]}), + json!({"num_retries": 0}), + ); + let mut store = Store::default(); + let now = SystemTime::now() + .duration_since(UNIX_EPOCH) + .unwrap() + .as_secs_f64(); + store.entries.insert( + "deployment:a1:cooldown".into(), + json!({"exception_received": "slow down", "status_code": "429", "timestamp": now, "cooldown_time": 60}), + ); + for _ in 0..8 { + let mut call = start(&pair_without_retries, "primary"); + let Step::HostCall(HostCall::Attempt { deployment_id, .. }) = + store.resume(&mut call, None) + else { + panic!("the call should attempt the healthy deployment"); + }; + assert_eq!(deployment_id, "a2", "the cooled-down deployment was picked"); + } + } + + /// The host only runs the attempt; the core records its outcome (cooldowns, fail counters, + /// usage) through the host's cache. + #[rstest] + #[case::failure(rate_limited())] + #[case::success(HostCallResponse::Attempt(Ok(7)))] + fn attempt_outcomes_are_recorded_by_the_core(#[case] outcome: HostCallResponse) { + let tracked = |id: &str| { + json!({ + "model_name": "primary", + "litellm_params": {"model": format!("openai/{id}"), "tpm": 100, "cooldown_time": 7}, + "model_info": {"id": id, "allowed_fails": 3}, + }) + }; + let router = router( + json!({"model_list": [tracked("a1"), tracked("a2")]}), + json!({"num_retries": 0}), + ); + let mut store = Store::default(); + let mut driver = start(&router, "primary"); + store.resume(&mut driver, None); + let step = store.resume(&mut driver, Some(outcome)); + assert!( + matches!(step, Step::Done(_) | Step::Failed(_)), + "got {step:?}" + ); + let writes: Vec<&HostCall> = store + .calls + .iter() + .filter(|call| { + matches!(call, HostCall::Cache { op, .. } if !matches!(op, CacheOp::Get | CacheOp::BatchGet)) + }) + .collect(); + assert!(!writes.is_empty(), "the core wrote no outcome"); + } + + #[rstest] + fn a_failed_group_falls_back_once_python_allows_it() { + let router = router( + json!({"model_list": [deployment("primary", "a1"), deployment("backup", "b1")]}), + json!({"fallbacks": [{"primary": ["backup"]}]}), + ); + let mut store = Store::default(); + let mut driver = start(&router, "primary"); + assert_eq!( + store.resume(&mut driver, None).unwrap_kind(), + StepKind::Attempt + ); + let bad_request = + HostCallResponse::Attempt(Err(AttemptError::new(FailureKind::BadRequest, Some(400)))); + let step = store.resume(&mut driver, Some(bad_request)); + assert!( + matches!(&step, Step::HostCall(HostCall::AllowFallback { target }) if target == "backup"), + "expected the fallback check, got {step:?}" + ); + let step = store.resume(&mut driver, Some(HostCallResponse::AllowFallback(true))); + assert!( + matches!(&step, Step::HostCall(HostCall::Attempt { deployment_id, fallback_depth: 1, .. }) if deployment_id == "b1"), + "expected the fallback attempt, got {step:?}" + ); + let Step::Done(Finish::Call(response)) = + store.resume(&mut driver, Some(HostCallResponse::Attempt(Ok(3)))) + else { + panic!("the fallback should finish the call"); + }; + assert_eq!(response.model_group, "backup"); + assert_eq!(response.attempted_fallbacks, 1); + } + + #[rstest] + fn a_refused_fallback_fails_with_the_attempt_error() { + let router = router( + json!({"model_list": [deployment("primary", "a1"), deployment("backup", "b1")]}), + json!({"fallbacks": [{"primary": ["backup"]}]}), + ); + let mut store = Store::default(); + let mut driver = start(&router, "primary"); + store.resume(&mut driver, None); + let bad_request = + HostCallResponse::Attempt(Err(AttemptError::new(FailureKind::BadRequest, Some(400)))); + store.resume(&mut driver, Some(bad_request)); + let Step::Failed(error) = + store.resume(&mut driver, Some(HostCallResponse::AllowFallback(false))) + else { + panic!("a refused fallback should fail the call"); + }; + assert_eq!( + error.attempt().map(|a| a.kind), + Some(FailureKind::BadRequest) + ); + } + + #[rstest] + #[case::none_while_waiting(None, StepKind::Attempt)] + #[case::wrong_kind(Some(HostCallResponse::Slept), StepKind::Attempt)] + #[case::cache_outcome(Some(HostCallResponse::Cache(CacheOutcome::Stored)), StepKind::Attempt)] + fn a_mismatched_outcome_is_rejected_and_the_step_kept( + pair: Router, + #[case] response: Option, + #[case] expected: StepKind, + ) { + let mut store = Store::default(); + let mut driver = start(&pair, "primary"); + store.resume(&mut driver, None); + let error = driver.resume(response).unwrap_err(); + assert!(error.is_request(), "{error}"); + assert_eq!(driver.pending_call().map(HostCall::kind), Some(expected)); + assert!(matches!( + store.resume(&mut driver, Some(HostCallResponse::Attempt(Ok(1)))), + Step::Done(_) + )); + } + + #[rstest] + #[case::wrong_op(HostCallResponse::Cache(CacheOutcome::Stored))] + #[case::number_for_batch(HostCallResponse::Cache(CacheOutcome::Number(1.0)))] + #[case::short_batch(HostCallResponse::Cache(CacheOutcome::Values(vec![None])))] + #[case::not_a_cache_outcome(HostCallResponse::Slept)] + fn a_mismatched_cache_outcome_is_rejected_and_the_step_kept( + pair: Router, + #[case] response: HostCallResponse, + ) { + let mut store = Store::default(); + let mut driver = start(&pair, "primary"); + let step = driver.resume(None).unwrap(); + let Step::HostCall( + call @ HostCall::Cache { + op: CacheOp::BatchGet, + .. + }, + ) = &step + else { + panic!("expected the cooldown read, got {step:?}"); + }; + let error = driver.resume(Some(response)).unwrap_err(); + assert!(error.is_request(), "{error}"); + assert_eq!(driver.pending_call(), Some(call)); + let response = store.respond(call); + assert_eq!( + store.resume(&mut driver, Some(response)).unwrap_kind(), + StepKind::Attempt + ); + } + + #[rstest] + fn a_strategy_python_runs_asks_for_a_selection_and_keeps_the_pick() { + let router = router( + json!({ + "model_list": [deployment("primary", "a1"), deployment("primary", "a2")], + "routing_strategy": "least-busy", + }), + json!({}), + ); + let mut store = Store::default(); + let mut driver = start(&router, "primary"); + let step = store.resume(&mut driver, None); + let Step::HostCall(HostCall::Select { + stage: Stage::Strategy(strategy), + candidates, + .. + }) = step + else { + panic!("a host strategy should ask for a selection, got {step:?}"); + }; + assert_eq!(strategy, "least-busy"); + assert_eq!(candidates, ["a1", "a2"]); + let step = store.resume( + &mut driver, + Some(HostCallResponse::Select(vec!["a2".to_owned()])), + ); + assert!( + matches!(&step, Step::HostCall(HostCall::Attempt { deployment_id, .. }) if deployment_id == "a2"), + "expected the picked deployment, got {step:?}" + ); + } + + #[rstest] + fn a_selection_is_driven_through_cache_steps(pair: Router) { + let request = RouterRequest { + model: "primary".to_owned(), + ..RouterRequest::default() + }; + let mut store = Store::default(); + let mut driver = Driver::new(async move { + pair.select(&Op::from("acompletion"), &request) + .await + .map(|deployment| Finish::Selected { + deployment_id: deployment.id.clone(), + model_group: deployment.model_name.clone(), + deployment: deployment_record(&deployment), + }) + }); + let Step::Done(Finish::Selected { + deployment_id, + model_group, + .. + }) = store.resume(&mut driver, None) + else { + panic!("a selection should finish with the pick"); + }; + assert!(["a1", "a2"].contains(&deployment_id.as_str())); + assert_eq!(model_group, "primary"); + assert!(matches!( + store.calls.as_slice(), + [HostCall::Cache { + op: CacheOp::BatchGet, + .. + }] + )); + } + + #[rstest] + fn dict_targets_keep_their_api_key_out_of_debug() { + let target = json!({"model": "b", "api_key": "credential-value"}); + let Value::Object(target) = target else { + unreachable!("a JSON object"); + }; + let shown = format!("{:?}", DictTargets(vec![target])); + assert!(!shown.contains("credential-value")); + assert!(shown.contains("[REDACTED]")); + } + + #[rstest] + fn a_chain_with_a_dict_target_asks_python_before_any_hop() { + let router = router( + json!({"model_list": [deployment("primary", "a1"), deployment("backup", "b1")]}), + json!({"fallbacks": [{"primary": [{"model": "backup", "api_key": "k"}]}]}), + ); + let mut store = Store::default(); + let mut driver = start(&router, "primary"); + store.resume(&mut driver, None); + let bad_request = + HostCallResponse::Attempt(Err(AttemptError::new(FailureKind::BadRequest, Some(400)))); + let step = store.resume(&mut driver, Some(bad_request)); + assert!( + matches!(&step, Step::HostCall(HostCall::RefuseFallbacks { level: 0, targets }) if targets.0.len() == 1), + "expected the chain's check, got {step:?}" + ); + let Step::Failed(error) = + store.resume(&mut driver, Some(HostCallResponse::RefuseFallbacks(true))) + else { + panic!("a refused chain should fail the call"); + }; + assert_eq!( + error.attempt().map(|a| a.kind), + Some(FailureKind::BadRequest) + ); + } + + trait StepKindOf { + fn unwrap_kind(self) -> StepKind; + } + + impl StepKindOf for Step { + fn unwrap_kind(self) -> StepKind { + match self { + Step::HostCall(call) => call.kind(), + Step::Done(_) => StepKind::Done, + Step::Failed(_) => StepKind::Failed, + } + } + } +} diff --git a/litellm-rust/crates/python-bridge/src/router/mod.rs b/litellm-rust/crates/python-bridge/src/router/mod.rs new file mode 100644 index 00000000000..c69259fcf1c --- /dev/null +++ b/litellm-rust/crates/python-bridge/src/router/mod.rs @@ -0,0 +1,2051 @@ +//! `RouterCoreHandle`: router-core behind a step-driven handle. Python drives each call through +//! [`RouterCall::next`], running every attempt, sleep, fallback check, selection and cache op the +//! call loop asks for and handing the outcome back; Rust never awaits Python. `select` is driven +//! the same way, since reading cooldowns is a cache step. + +mod config; +mod host; +mod retries; +mod stream; + +use std::{ + sync::{Arc, Mutex, PoisonError}, + time::{Duration, SystemTime}, +}; + +use litellm_error::Report; +use litellm_host_python::{from_py_argument, json_loads, to_py}; +use litellm_router_core::lookup::{ListScope, Lookup, Row}; +use litellm_router_core::{ + AttemptError, Blocked, BuildPath, Built, Deployment, DeploymentSpec, Error, FailureKind, + FailureReport, Op, OutcomeCallbacks, PreRouted, Provided, RetryCause, Router, RouterEvent, + SecretAt, SuccessReport, + build::Install, + health::{UsageMetric, current_minute, usage_key}, + registry::{DeploymentFilter, ResolveKind, ResolveScope}, + strategy::routing_context, +}; +use pyo3::{ + exceptions::{PyRuntimeError, PyValueError}, + prelude::*, + types::{PyBool, PyDict, PyList, PyString}, +}; +use serde_json::Value; + +use self::host::{ + CacheOp, CacheOutcome, DriveError, Driver, Finish, HostCall, HostCallResponse, + PythonRandomness, Stage, Step, StepHost, StepKind, +}; +use crate::errors::RustBridgeDeclined; + +/// The `error_kind` of a `failed` step. +#[derive(Clone, Copy, Debug, strum::IntoStaticStr)] +enum ErrorKind { + #[strum(serialize = "config")] + Config, + #[strum(serialize = "unknown_model")] + UnknownModel, + #[strum(serialize = "no_healthy_deployments")] + NoHealthyDeployments, + #[strum(serialize = "attempt")] + Attempt, + #[strum(serialize = "cache")] + Cache, + #[strum(serialize = "retired")] + Retired, + #[strum(serialize = "paused")] + Paused, + #[strum(serialize = "not_pass_through")] + NotPassThrough, + #[strum(serialize = "no_pass_through_deployments")] + NoPassThroughDeployments, + #[strum(serialize = "only_markers")] + OnlyMarkers, + #[strum(serialize = "endpoint_not_supported")] + EndpointNotSupported, + #[strum(serialize = "ptu_reserved")] + PtuReserved, + #[strum(serialize = "context_window_exceeded")] + ContextWindowExceeded, + #[strum(serialize = "unsupported_params")] + UnsupportedParams, + #[strum(serialize = "routing_plugins_left_nothing")] + RoutingPluginsLeftNothing, + #[strum(serialize = "routing_plugins_need_async")] + RoutingPluginsNeedAsync, + #[strum(serialize = "multiple_teams")] + MultipleTeams, + #[strum(serialize = "reserved")] + Reserved, + #[strum(serialize = "invalid_router_weights")] + InvalidRouterWeights, + #[strum(serialize = "non_numeric_weight")] + NonNumericWeight, + #[strum(serialize = "missing_routing_group")] + MissingRoutingGroup, + #[strum(serialize = "default_deployment_raises")] + DefaultDeploymentRaises, + #[strum(serialize = "index_out_of_range")] + IndexOutOfRange, + #[strum(serialize = "model_info")] + ModelInfo, +} + +impl From<&Error> for ErrorKind { + fn from(error: &Error) -> Self { + match error { + Error::Config(_) => Self::Config, + Error::UnknownModel { .. } => Self::UnknownModel, + Error::NoHealthyDeployments { .. } => Self::NoHealthyDeployments, + Error::Attempt(_) => Self::Attempt, + Error::Cache(_) => Self::Cache, + Error::Retired => Self::Retired, + Error::Paused { .. } => Self::Paused, + Error::NotPassThrough { .. } => Self::NotPassThrough, + Error::NoPassThroughDeployments { .. } => Self::NoPassThroughDeployments, + Error::OnlyMarkers { .. } => Self::OnlyMarkers, + Error::EndpointNotSupported { .. } => Self::EndpointNotSupported, + Error::PtuReserved { .. } => Self::PtuReserved, + Error::ContextWindowExceeded { .. } => Self::ContextWindowExceeded, + Error::UnsupportedParams { .. } => Self::UnsupportedParams, + Error::RoutingPluginsLeftNothing { .. } => Self::RoutingPluginsLeftNothing, + Error::RoutingPluginsNeedAsync => Self::RoutingPluginsNeedAsync, + Error::MultipleTeams { .. } => Self::MultipleTeams, + Error::Reserved { .. } => Self::Reserved, + Error::InvalidRouterWeights => Self::InvalidRouterWeights, + Error::NonNumericWeight { .. } => Self::NonNumericWeight, + Error::MissingRoutingGroup { .. } => Self::MissingRoutingGroup, + Error::DefaultDeploymentRaises { .. } => Self::DefaultDeploymentRaises, + Error::IndexOutOfRange { .. } => Self::IndexOutOfRange, + Error::ModelInfo { .. } => Self::ModelInfo, + } + } +} + +fn config_error_to_pyerr(error: config::Error) -> PyErr { + let message = Report::new(&error).to_string(); + if error.declined() { + RustBridgeDeclined::new_err(message) + } else { + PyValueError::new_err(message) + } +} + +fn drive_error_to_pyerr(error: DriveError) -> PyErr { + let message = Report::new(&error).to_string(); + if error.is_request() { + PyValueError::new_err(message) + } else { + PyRuntimeError::new_err(message) + } +} + +/// A document Python passes as a mapping or as its JSON text. +fn document(value: &Bound<'_, PyAny>) -> PyResult { + match value.cast::() { + Ok(text) => { + let parsed = json_loads(value.py(), text.to_str()?.as_bytes())?; + from_py_argument(parsed.bind(value.py())) + } + Err(_) => from_py_argument(value), + } +} + +/// The `OutcomeCallbacks` a reported outcome came through; none is a report no callback makes. +fn outcome_callbacks(value: Option<&Bound<'_, PyAny>>) -> PyResult { + let Some(value) = value else { + return Ok(OutcomeCallbacks::default()); + }; + serde_json::from_value(document(value)?) + .map_err(|error| PyValueError::new_err(error.to_string())) +} + +/// A router-core router whose host operations Python runs. +#[pyclass(frozen)] +pub(crate) struct RouterCoreHandle { + router: Router, +} + +#[pymethods] +impl RouterCoreHandle { + #[new] + fn new(config: &Bound<'_, PyAny>, dynamic: &Bound<'_, PyAny>) -> PyResult { + let (config, dynamic) = (document(config)?, document(dynamic)?); + let build = || { + let config = config::parse_router_config(config)?; + let dynamic = config::parse_dynamic_config(dynamic)?; + Ok(Router::builder(config, dynamic, Arc::new(StepHost)) + .randomness(Arc::new(PythonRandomness)) + .build()?) + }; + build() + .map(|router| Self { router }) + .map_err(config_error_to_pyerr) + } + + /// Start a call; nothing runs until the first `next(None)`. + fn start(&self, op: &str, request: &Bound<'_, PyAny>) -> PyResult { + let op = Op::new(op); + let request = + config::parse_request(document(request)?, None).map_err(config_error_to_pyerr)?; + let router = self.router.clone(); + Ok(RouterCall::new(async move { + router.call(op, request).await.map(Finish::Call) + })) + } + + /// Pick the deployment `model` routes to now, without calling it. Driven like `start`: its + /// steps are the cache reads and selections the pick needs, and it ends with `done` + /// (`deployment_id`, `model_group`) or `failed`. + fn select(&self, model: &str, request: &Bound<'_, PyAny>) -> PyResult { + let request = config::parse_request(document(request)?, Some(model)) + .map_err(config_error_to_pyerr)?; + let router = self.router.clone(); + Ok(RouterCall::new(async move { + let deployment = router.select(&Op::from("acompletion"), &request).await?; + Ok(Finish::Selected { + deployment_id: deployment.id.clone(), + model_group: deployment.model_name.clone(), + deployment: host::deployment_record(&deployment), + }) + })) + } + + /// List the deployments a pick for `model` would choose among, driven like `select`. + fn healthy(&self, model: &str, request: &Bound<'_, PyAny>) -> PyResult { + let request = config::parse_request(document(request)?, Some(model)) + .map_err(config_error_to_pyerr)?; + let router = self.router.clone(); + Ok(RouterCall::new(async move { + let candidates = router.healthy(&Op::from("acompletion"), &request).await?; + // A deployment named by its id is listed alone, as a dict (`_core_async_get_healthy_deployments`). + let single = candidates.kind.is_single() && candidates.healthy.len() == 1; + let deployments = candidates.healthy; + Ok(Finish::Healthy { + single, + deployment_ids: deployments.iter().map(|d| d.id.clone()).collect(), + deployments: deployments + .iter() + .map(|d| host::deployment_record(d)) + .collect(), + }) + })) + } + + /// Apply `{"upsert": [deployments], "delete": [ids], "settings": {dynamic document}}` and + /// return the new registry version. + fn apply(&self, changes: &Bound<'_, PyAny>) -> PyResult { + let changes = config::parse_changes(document(changes)?).map_err(config_error_to_pyerr)?; + self.router + .apply(changes) + .map_err(|error| config_error_to_pyerr(error.into())) + } + + /// Build `entries` (model_list entries) through the host, driven like `start`: its steps + /// are `secrets`, `validate`, `provider` and `added`, and it ends with `done` (`built`: one + /// `{"index", "id", "provider"}` per deployment installed). `path` is `create` + /// (`set_model_list`) or `add` (`add_deployment`); `install` is `replace`, `append` or + /// `upsert`. + #[pyo3(signature = (entries, path, resolve_secrets, install))] + fn build( + &self, + entries: &Bound<'_, PyAny>, + path: &str, + resolve_secrets: bool, + install: &str, + ) -> PyResult { + let entries: Vec> = + serde_json::from_value(document(entries)?) + .map_err(|error| PyValueError::new_err(format!("bad model_list: {error}")))?; + let path: BuildPath = path + .parse() + .map_err(|_| PyValueError::new_err(format!("`{path}` is not a build path")))?; + let install: Install = install + .parse() + .map_err(|_| PyValueError::new_err(format!("`{install}` is not a build install")))?; + let router = self.router.clone(); + Ok(RouterCall::new(async move { + router + .build(path, entries, resolve_secrets, install) + .await + .map(Finish::Built) + })) + } + + /// `get_router_model_info` for the deployment `query` describes (a + /// `RouterModelInfoQuery` document), driven like `start`: its steps are `model_info` + /// lookups, and it ends with `done` (`info`: the merged map or None, `user_keys`: the keys + /// whose values are the deployment's own). + fn router_model_info(&self, query: &Bound<'_, PyAny>) -> PyResult { + let query: litellm_router_core::model_info::RouterModelInfoQuery = + serde_json::from_value(document(query)?) + .map_err(|error| PyValueError::new_err(format!("bad model-info query: {error}")))?; + let router = self.router.clone(); + Ok(RouterCall::new(async move { + router + .router_model_info(&query) + .await + .map(Finish::RouterModelInfo) + })) + } + + /// `get_deployment_model_info` for deployment `model_id` serving `model_name`, driven like + /// `router_model_info`; it ends with `done` (`info`: the merged map or None). + fn deployment_model_info( + &self, + model_id: &str, + model_name: &Bound<'_, PyAny>, + ) -> PyResult { + let model_id = model_id.to_owned(); + let model_name = from_py_argument::(model_name)?; + let router = self.router.clone(); + Ok(RouterCall::new(async move { + router + .deployment_model_info(&model_id, &model_name) + .await + .map(Finish::DeploymentModelInfo) + })) + } + + /// `_set_model_group_info` for the deployments `query` names (a `GroupInfoQuery` document), + /// driven like `router_model_info`; it ends with `done` (`value`: None when no deployment + /// matched, else `{"assignments": {field: value}}`, what the merge set on the group the host + /// built from its first deployment). + fn model_group_info(&self, query: &Bound<'_, PyAny>) -> PyResult { + let query: litellm_router_core::group_info::GroupInfoQuery = + serde_json::from_value(document(query)?) + .map_err(|error| PyValueError::new_err(format!("bad group-info query: {error}")))?; + let router = self.router.clone(); + Ok(RouterCall::new(async move { + let info = router.model_group_info(&query).await?; + Ok(Finish::Value(info.map_or( + Value::Null, + |info| serde_json::json!({"assignments": info.assignments}), + ))) + })) + } + + /// `get_configured_token_limits` for the deployment with `id` and its `configured` model_info, + /// driven like `router_model_info`; it ends with `done` (`value`: `[max_input, max_output]`). + fn configured_token_limits( + &self, + id: &Bound<'_, PyAny>, + configured: &Bound<'_, PyAny>, + ) -> PyResult { + let id = from_py_argument::(id)?; + let Value::Object(configured) = document(configured)? else { + return Err(PyValueError::new_err( + "the configured model_info must be a dict", + )); + }; + let router = self.router.clone(); + Ok(RouterCall::new(async move { + let (input, output) = router.configured_token_limits(id, &configured).await?; + Ok(Finish::Value(serde_json::json!([input, output]))) + })) + } + + /// `get_model_listing_info` over the `deployments` a listed name names, driven like + /// `router_model_info`; it ends with `done` (`value`: `{"cost_map_keys", "max_input_tokens", + /// "max_output_tokens"}`). + fn model_listing_info(&self, deployments: &Bound<'_, PyAny>) -> PyResult { + let deployments: Vec = from_py_argument(deployments)?; + let router = self.router.clone(); + Ok(RouterCall::new(async move { + let listing = router.model_listing_info(&deployments).await?; + Ok(Finish::Value(serde_json::json!({ + "cost_map_keys": listing.cost_map_keys, + "max_input_tokens": listing.max_input_tokens, + "max_output_tokens": listing.max_output_tokens, + }))) + })) + } + + /// `get_configured_mode` / `get_configured_display_name`: `value` when it is a string that is + /// not blank. + #[staticmethod] + fn configured_text(value: &Bound<'_, PyAny>) -> PyResult> { + let value = from_py_argument::(value).ok(); + Ok(litellm_router_core::group_info::configured_text( + value.as_ref(), + )) + } + + /// `get_configured_service_tiers`: each of `model_infos`' `service_tiers`, unvalidated. + #[staticmethod] + fn configured_service_tiers( + py: Python<'_>, + model_infos: &Bound<'_, PyAny>, + ) -> PyResult>> { + let model_infos: Vec> = from_py_argument(model_infos)?; + litellm_router_core::group_info::configured_service_tiers(&model_infos) + .iter() + .map(|tiers| to_py(py, tiers)) + .collect() + } + + /// The routing-cache key deployment `id` serving litellm `model` counts `metric` (`tpm`, + /// `rpm`, `itpm` or `otpm`) under in `minute` (`HH-MM`). + fn usage_key(&self, id: &str, model: &str, metric: &str, minute: &str) -> PyResult { + let metric: UsageMetric = metric + .parse() + .map_err(|_| PyValueError::new_err(format!("`{metric}` is not a usage metric")))?; + Ok(usage_key(id, model, metric, minute)) + } + + /// Keep the providers `other`'s build resolved for the deployments this router serves too. + fn adopt_providers(&self, other: &Self) { + self.router.adopt_providers(&other.router); + } + + fn registry_version(&self) -> u64 { + self.router.registry().version() + } + + /// The version the deployments before the newest appends last changed at: a list read at + /// or after it is current once it reads `deployments_from(len(list))`. + fn registry_rewritten(&self) -> u64 { + self.router.registry().rewritten() + } + + /// Record a failure the router did not see itself (a health check, an interceptor, a + /// logging callback), driven like `start`: its steps are cache ops, and it ends with `done` + /// (`cooled`, `cooldown_time`). `counts_request` also counts the failed request against the deployment's + /// per-minute requests, as an async call's failure callback does. `callbacks` is the logged + /// request's `OutcomeCallbacks`. + #[pyo3(signature = (id, failure, deployment_cooldown=false, count_only=false, requested_group=None, cooldown_time=None, uncounted=false, counts_request=false, usage_model=None, callbacks=None))] + #[allow(clippy::too_many_arguments)] + fn report_failure( + &self, + id: &str, + failure: &Bound<'_, PyDict>, + deployment_cooldown: bool, + count_only: bool, + requested_group: Option, + cooldown_time: Option, + uncounted: bool, + counts_request: bool, + usage_model: Option, + callbacks: Option<&Bound<'_, PyAny>>, + ) -> PyResult { + let failure = match attempt_outcome(failure)? { + Err(failure) => failure, + Ok(_) => { + return Err(PyValueError::new_err( + "a reported failure needs `ok: False`", + )); + } + }; + let router = self.router.clone(); + let id = id.to_owned(); + let report = FailureReport { + deployment_cooldown, + cooldown_time, + count_only, + requested_group, + uncounted, + counts_request, + usage_model, + callbacks: outcome_callbacks(callbacks)?, + }; + Ok(RouterCall::new(async move { + router + .report_failure(&id, &failure, report) + .await + .map(|cooldown| Finish::Reported { cooldown }) + })) + } + + /// Record a success a logging callback saw, driven like `report_failure`; it ends with + /// `done` (`key`: the success counter's key, or None for an unknown deployment). + /// `usage_model` is the model its usage is keyed by, and `tracks_usage` the host's answer to + /// whether it counts any (see `Output::tracks_usage`). `callbacks`: see `report_failure`. + #[pyo3(signature = (id, total_tokens, requests, usage_model=None, tracks_usage=None, callbacks=None))] + fn report_success( + &self, + id: &str, + total_tokens: f64, + requests: f64, + usage_model: Option, + tracks_usage: Option, + callbacks: Option<&Bound<'_, PyAny>>, + ) -> PyResult { + let router = self.router.clone(); + let id = id.to_owned(); + let report = SuccessReport { + tracks_usage, + usage_model, + callbacks: outcome_callbacks(callbacks)?, + }; + Ok(RouterCall::new(async move { + router + .report_success(&id, total_tokens, requests, report) + .await + .map(|key| Finish::Counted { key }) + })) + } + + /// Count a success against `id`, configured or not; ends with `done` (`key`). `callbacks`: + /// see `report_failure`. + #[pyo3(signature = (id, callbacks=None))] + fn count_success( + &self, + id: &str, + callbacks: Option<&Bound<'_, PyAny>>, + ) -> PyResult { + let router = self.router.clone(); + let id = id.to_owned(); + let callbacks = outcome_callbacks(callbacks)?; + Ok(RouterCall::new(async move { + router + .count_success(&id, callbacks) + .await + .map(|key| Finish::Counted { key }) + })) + } + + /// The usage keys of this minute for every deployment of `model_group`: + /// `[(id, tpm_key, rpm_key)]`, or None when the group has no deployment. + fn usage_keys(&self, model_group: &str) -> Option> { + let minute = current_minute(SystemTime::now()); + let group = self.router.registry().group(model_group)?; + Some( + group + .iter() + .map(|deployment| { + let model = &deployment.params.model; + ( + deployment.id.clone(), + usage_key(&deployment.id, model, UsageMetric::Tpm, &minute), + usage_key(&deployment.id, model, UsageMetric::Rpm, &minute), + ) + }) + .collect(), + ) + } + + /// Every configured deployment, as `model_list` entries with their ids, in config order. + fn deployments<'py>(&self, py: Python<'py>) -> PyResult> { + let registry = self.router.registry(); + let records = registry + .deployments(&DeploymentFilter::default()) + .iter() + .map(|deployment| to_py(py, &host::deployment_record(deployment))) + .collect::>>()?; + PyList::new(py, records) + } + + /// The deployments from position `start` on, as `deployments()` lists them. + fn deployments_from<'py>(&self, py: Python<'py>, start: usize) -> PyResult> { + let registry = self.router.registry(); + let records = registry + .deployments_from(start) + .iter() + .map(|deployment| to_py(py, &host::deployment_record(deployment))) + .collect::>>()?; + PyList::new(py, records) + } + + /// The deployment with this id, or None. + fn deployment(&self, py: Python<'_>, id: &str) -> PyResult>> { + self.router + .registry() + .deployment(id) + .map(|deployment| to_py(py, &host::deployment_record(&deployment))) + .transpose() + } + + // -- registry lookups (router-core `lookup.rs`): rows the host reads its stored entries at -- + + /// `_core_get_all_deployments`, as rows. + #[pyo3(signature = (model_name, team_id=None, rename=None))] + fn lookup_all<'py>( + &self, + py: Python<'py>, + model_name: &str, + team_id: Option<&str>, + rename: Option<&str>, + ) -> PyResult> { + let registry = self.router.registry(); + rows_to_py(py, &Lookup::new(®istry).all(model_name, team_id, rename)) + } + + /// `_team_deployments_across_teams`: the rows, and how many teams own them. + fn lookup_across_teams<'py>( + &self, + py: Python<'py>, + model: &str, + ) -> PyResult<(Bound<'py, PyAny>, usize)> { + let registry = self.router.registry(); + let (rows, teams) = Lookup::new(®istry).across_teams(model); + Ok((rows_to_py(py, &rows)?, teams)) + } + + /// `_core_config_deployments`, as rows. + fn lookup_config<'py>(&self, py: Python<'py>) -> PyResult> { + let registry = self.router.registry(); + rows_to_py(py, &Lookup::new(®istry).config()) + } + + /// `_core_get_model_ids`: the ids, or the row the read raises at. + #[pyo3(signature = (model_name=None, exclude_team_models=false))] + fn lookup_model_ids<'py>( + &self, + py: Python<'py>, + model_name: Option<&str>, + exclude_team_models: bool, + ) -> PyResult<(Vec, Option>)> { + let registry = self.router.registry(); + match Lookup::new(®istry).model_ids(model_name, exclude_team_models) { + Ok(ids) => Ok((ids, None)), + Err(raw) => Ok((Vec::new(), Some(row_to_py(py, &raw)?))), + } + } + + /// `_core_get_model_list`, as rows. + #[pyo3(signature = (model_name, team_id, scope))] + fn lookup_model_list<'py>( + &self, + py: Python<'py>, + model_name: Option<&str>, + team_id: Option<&str>, + scope: &Bound<'_, PyAny>, + ) -> PyResult> { + let scope = list_scope(scope)?; + let registry = self.router.registry(); + rows_to_py( + py, + &Lookup::new(®istry).model_list(model_name, team_id, &scope), + ) + } + + /// `_core_get_model_names`, or the row the read raises at. + fn lookup_model_names<'py>( + &self, + py: Python<'py>, + team_id: Option<&str>, + scope: &Bound<'_, PyAny>, + ) -> PyResult<(Vec, Option>)> { + let scope = list_scope(scope)?; + let registry = self.router.registry(); + match Lookup::new(®istry).model_names(team_id, &scope) { + Ok(names) => Ok((names, None)), + Err(raw) => Ok((Vec::new(), Some(row_to_py(py, &raw)?))), + } + } + + /// `_core_get_model_access_groups`: `(group, names)` pairs in the order the groups appear, + /// or the row the read raises at. + fn lookup_access_groups<'py>( + &self, + py: Python<'py>, + model_name: Option<&str>, + access_group: Option<&str>, + team_id: Option<&str>, + scope: &Bound<'_, PyAny>, + ) -> PyResult<(AccessGroups, Option>)> { + let scope = list_scope(scope)?; + let registry = self.router.registry(); + match Lookup::new(®istry).access_groups(model_name, access_group, team_id, &scope) { + Ok(groups) => Ok((groups, None)), + Err(raw) => Ok((Vec::new(), Some(row_to_py(py, &raw)?))), + } + } + + /// Whether the whole list lists any row, and the name of its first row whose litellm model + /// is `model_id` (or ends in `/model_id` or `:model_id`); or the row the read raises at. + fn lookup_name_serving<'py>( + &self, + py: Python<'py>, + model_id: &str, + scope: &Bound<'_, PyAny>, + ) -> PyResult<(bool, Option, Option>)> { + let scope = list_scope(scope)?; + let registry = self.router.registry(); + match Lookup::new(®istry).name_serving(model_id, &scope) { + Ok((listed, name)) => Ok((listed, name, None)), + Err(raw) => Ok((false, None, Some(row_to_py(py, &raw)?))), + } + } + + /// Whether `model_names` (the group names) holds `name`. + fn has_model_name(&self, name: &str) -> bool { + self.router + .registry() + .host_indexes() + .model_names + .contains(&Value::String(name.to_owned())) + } + + /// `_core_team_model_has_alternatives`, or the row the read raises at. + fn lookup_team_model_has_alternatives<'py>( + &self, + py: Python<'py>, + id: &str, + ) -> PyResult<(bool, Option>)> { + let registry = self.router.registry(); + match Lookup::new(®istry).team_model_has_alternatives(id) { + Ok(found) => Ok((found, None)), + Err(raw) => Ok((false, Some(row_to_py(py, &raw)?))), + } + } + + /// The position of the group's first deployment the team may use, or the row the read + /// raises at. + fn lookup_group_usable_by_team<'py>( + &self, + py: Python<'py>, + model_group: &str, + team_id: Option<&str>, + ) -> PyResult<(Option, Option>)> { + let registry = self.router.registry(); + match Lookup::new(®istry).group_deployment_usable_by_team(model_group, team_id) { + Ok(position) => Ok((position, None)), + Err(raw) => Ok((None, Some(row_to_py(py, &raw)?))), + } + } + + /// The position of the team public name's first deployment, or the row the read raises at. + fn lookup_team_public_name<'py>( + &self, + py: Python<'py>, + model_id: &str, + team_id: &str, + ) -> PyResult<(Option, Option>)> { + let registry = self.router.registry(); + match Lookup::new(®istry).team_public_name_deployment(model_id, team_id) { + Ok(position) => Ok((position, None)), + Err(raw) => Ok((None, Some(row_to_py(py, &raw)?))), + } + } + + /// `_routable_deployments`, as rows. + fn lookup_routable<'py>( + &self, + py: Python<'py>, + model_group: &str, + team_id: Option<&str>, + ) -> PyResult> { + let registry = self.router.registry(); + rows_to_py(py, &Lookup::new(®istry).routable(model_group, team_id)) + } + + /// `_core_wildcard_route_deployments`: the team router's routes, else the global router's. + fn lookup_wildcard_route<'py>( + &self, + py: Python<'py>, + model: &str, + team_id: Option<&str>, + requests: Vec, + ) -> PyResult> { + let registry = self.router.registry(); + rows_to_py( + py, + &Lookup::new(®istry).wildcard_route(model, team_id, &requests), + ) + } + + /// `_core_get_candidate_model_ids_for_route` for the resolved name: the members' ids when it + /// names a callable routing group (`members`), else for a name that is no model group the + /// team's or the wildcard route's, else the group's; or the row the read raises at. + fn lookup_candidate_ids<'py>( + &self, + py: Python<'py>, + resolved: &str, + team_id: Option<&str>, + members: Option>, + requests: Vec, + ) -> PyResult<(Vec, Option>)> { + let registry = self.router.registry(); + let lookup = Lookup::new(®istry); + match lookup.candidate_ids(resolved, team_id, members.as_deref(), &requests) { + Ok(ids) => Ok((ids, None)), + Err(raw) => Ok((Vec::new(), Some(row_to_py(py, &raw)?))), + } + } + + /// Whether the id map holds `id` (`_has_model_id`). + fn has_model_id(&self, id: &str) -> bool { + self.router.registry().host_indexes().has_id(id) + } + + /// What the id map holds for `id`, as written (a position, or what a caller wrote), or None. + fn id_position<'py>(&self, py: Python<'py>, id: &str) -> PyResult>> { + let registry = self.router.registry(); + registry + .host_indexes() + .id_entry(id) + .map(|held| to_py(py, held).map(|value| value.into_bound(py))) + .transpose() + } + + /// The id map's entries, in order: `(id, what it holds)`. + fn id_positions<'py>(&self, py: Python<'py>) -> PyResult> { + let registry = self.router.registry(); + let pairs: Vec = registry + .host_indexes() + .id_map + .iter() + .map(|(id, held)| Value::Array(vec![Value::String(id.clone()), held.clone()])) + .collect(); + to_py(py, &Value::Array(pairs)).map(|value| value.into_bound(py)) + } + + /// What the name index holds for `name`, as written, or None when it does not index it. + fn named_positions<'py>( + &self, + py: Python<'py>, + name: &str, + ) -> PyResult>> { + let registry = self.router.registry(); + registry + .host_indexes() + .named(name) + .map(|held| to_py(py, held).map(|value| value.into_bound(py))) + .transpose() + } + + /// What the team index holds for `(team, public)`, as written, or None. + fn team_positions<'py>( + &self, + py: Python<'py>, + team: &str, + public: &str, + ) -> PyResult>> { + let registry = self.router.registry(); + registry + .host_indexes() + .team_named(team, public) + .map(|held| to_py(py, held).map(|value| value.into_bound(py))) + .transpose() + } + + /// `team_public_model_names_of`: the public names the team index holds for `team`. + fn team_public_names_of(&self, team: &str) -> Vec { + self.router + .registry() + .host_indexes() + .team_public_names_of(team) + } + + /// The positions of the deployments whose `litellm_params.model` is `model`. + fn litellm_model_positions(&self, model: &str) -> Vec { + self.router + .registry() + .deployments(&DeploymentFilter::default()) + .iter() + .enumerate() + .filter(|(_, deployment)| { + deployment.raw_params.get("model").and_then(Value::as_str) == Some(model) + }) + .map(|(position, _)| position) + .collect() + } + + /// `PatternMatchRouter.route` over the wildcard router (or `team`'s): the first pattern's + /// deployments, each with the model the wildcards matched, or None. + #[pyo3(signature = (team, request, filtered=None))] + fn pattern_route<'py>( + &self, + py: Python<'py>, + team: Option<&str>, + request: &str, + filtered: Option>, + ) -> PyResult>> { + let registry = self.router.registry(); + let indexes = registry.host_indexes(); + let router = match team { + None => Some(&indexes.patterns), + Some(team) => indexes + .team_patterns + .iter() + .find(|(held, _)| held == team) + .map(|(_, router)| router), + }; + router + .and_then(|router| router.route(request, filtered.as_deref())) + .map(|routed| to_py(py, &Value::Array(routed)).map(|value| value.into_bound(py))) + .transpose() + } + + /// `get_models_by_pattern`: the models the first matching (request, pattern) pair routes to. + fn models_by_pattern(&self, team: Option<&str>, requests: Vec) -> Option> { + let registry = self.router.registry(); + let indexes = registry.host_indexes(); + let router = match team { + None => Some(&indexes.patterns), + Some(team) => indexes + .team_patterns + .iter() + .find(|(held, _)| held == team) + .map(|(_, router)| router), + }; + router.and_then(|router| router.models_by_pattern(&requests)) + } + + /// The indexes the host hands out (`HostIndexes`): id map, name and team indexes, group and + /// deployment names, team public names, provider default ids and the pattern routers. + fn host_indexes<'py>(&self, py: Python<'py>) -> PyResult> { + let indexes = serde_json::to_value(self.router.registry().host_indexes()) + .map_err(|error| PyValueError::new_err(error.to_string()))?; + to_py(py, &indexes).map(|value| value.into_bound(py)) + } + + /// `provider_default_deployment_ids` as the indexes hold it now: the ids of the wildcard + /// deployments the cooldown check skips. + fn provider_default_ids(&self) -> Vec { + self.router + .registry() + .host_indexes() + .provider_default_ids + .clone() + } + + /// The provider the host resolved when it built the deployment with this id (its + /// `provider` build step), or None when there is no such deployment or it never went + /// through a host build. + fn provider(&self, id: &str) -> Option { + self.router + .registry() + .deployment(id) + .and_then(|deployment| deployment.resolved_provider.clone()) + } + + /// What `name` resolves to: `{"model_group", "kind", "ids"}`, or None for an unknown name. + #[pyo3(signature = (name, specific_deployment=false))] + fn resolve<'py>( + &self, + py: Python<'py>, + name: &str, + specific_deployment: bool, + ) -> PyResult>> { + let registry = self.router.registry(); + let Some(resolution) = registry.resolve( + name, + ResolveScope { + specific_deployment, + }, + ) else { + return Ok(None); + }; + let dict = PyDict::new(py); + dict.set_item("model_group", resolution.group)?; + dict.set_item("kind", format!("{:?}", resolution.kind))?; + dict.set_item( + "ids", + PyList::new(py, resolution.deployments.iter().map(|d| d.id.clone()))?, + )?; + Ok(Some(dict)) + } + + /// The deployments a pick for `model` would resolve to for `request`, before any team, + /// cooldown or strategy filter (`_core_get_routable_deployments`); empty when it refuses. + fn routable<'py>( + &self, + py: Python<'py>, + model: &str, + request: &Bound<'py, PyAny>, + ) -> PyResult> { + let request = config::parse_request(document(request)?, Some(model)) + .map_err(config_error_to_pyerr)?; + let records = litellm_router_core::resolve::routable( + &self.router.registry(), + &self.router.settings().dynamic, + &request, + ) + .iter() + .map(|d| to_py(py, &host::deployment_record(d))) + .collect::>>()?; + PyList::new(py, records) + } + + /// `_get_routing_context` for a pick of `model`: `(strategy, scope, group)`, spelled as a + /// strategy select step spells them. A name that resolves to nothing reads its routing group + /// membership as is. + #[pyo3(signature = (model, routing_strategy=None))] + fn routing_context( + &self, + model: &str, + routing_strategy: Option<&str>, + ) -> (String, &'static str, Option) { + let registry = self.router.registry(); + let settings = self.router.settings(); + let (kind, group) = registry + .resolve(model, ResolveScope::default()) + .map_or((ResolveKind::Group, model.to_owned()), |resolution| { + (resolution.kind, resolution.group) + }); + let (strategy, scope) = routing_context( + ®istry, + &settings.routing_strategy, + routing_strategy, + &kind, + &group, + ); + let (scope, group) = scope.wire(); + (strategy.to_string(), scope, group.map(str::to_owned)) + } + + fn retire(&self) { + self.router.retire(); + } + + /// What may still take over a stream from `origin` that fails before content, and the + /// retry budget for a failure of `kind` (see `stream::policy`). + #[pyo3(signature = (request, origin, kind=None))] + fn stream_policy<'py>( + &self, + py: Python<'py>, + request: &Bound<'py, PyAny>, + origin: &Bound<'py, PyAny>, + kind: Option<&str>, + ) -> PyResult> { + stream::policy(py, &self.router, request, origin, kind) + } + + /// Retry a stream from `origin` that failed before content within its group, driven like + /// `start`: `done` when a retry returned a response, `failed` with the newest failure. + fn retry_stream( + &self, + op: &str, + request: &Bound<'_, PyAny>, + origin: &Bound<'_, PyAny>, + failure: &Bound<'_, PyDict>, + ) -> PyResult { + stream::recover( + &self.router, + stream::Recovery::Retry, + op, + request, + origin, + failure, + ) + } + + /// The fallback walk for a stream from `origin` that failed before content, driven like + /// `start`. + fn fallback_stream( + &self, + op: &str, + request: &Bound<'_, PyAny>, + origin: &Bound<'_, PyAny>, + failure: &Bound<'_, PyDict>, + ) -> PyResult { + stream::recover( + &self.router, + stream::Recovery::Fallback, + op, + request, + origin, + failure, + ) + } + + /// `get_num_retries_from_retry_policy` for a failure shaped like an attempt outcome. + #[pyo3(signature = (failure, model_group=None))] + fn retry_policy_retries( + &self, + failure: &Bound<'_, PyDict>, + model_group: Option<&str>, + ) -> PyResult> { + retries::policy_retries(&self.router, failure, model_group) + } + + /// `_core_get_allowed_fails_from_policy` for a failure shaped like an attempt outcome. + fn allowed_fails_for(&self, failure: &Bound<'_, PyDict>) -> PyResult> { + retries::allowed_fails(&self.router, failure) + } + + /// `should_retry_this_error` as a predicate, for a failure shaped like an attempt outcome. + fn should_retry( + &self, + failure: &Bound<'_, PyDict>, + counts: (usize, usize), + fallbacks: (bool, bool, bool), + ) -> PyResult { + retries::should_retry(failure, counts, fallbacks) + } +} + +/// One router call, driven a step at a time by Python. +#[pyclass(frozen)] +pub(crate) struct RouterCall { + driver: Mutex, +} + +impl RouterCall { + fn new( + future: impl std::future::Future> + Send + 'static, + ) -> Self { + Self { + driver: Mutex::new(Driver::new(future)), + } + } +} + +#[pymethods] +impl RouterCall { + /// Hand back the outcome of the last step (`None` on the first call) and return the next + /// step, or the call's end. + #[pyo3(signature = (outcome))] + fn next<'py>( + &self, + py: Python<'py>, + outcome: Option>, + ) -> PyResult> { + let mut driver = self.driver.lock().unwrap_or_else(PoisonError::into_inner); + let response = match driver.pending_call() { + None => match outcome { + None => None, + Some(_) => return Err(drive_error_to_pyerr(DriveError::UnexpectedResponse)), + }, + Some(call) => Some(host_call_response(call, outcome)?), + }; + let step = driver.resume(response).map_err(drive_error_to_pyerr)?; + let dict = step_dict(py, step)?; + dict.set_item("events", events_list(py, driver.take_events())?)?; + Ok(dict) + } +} + +/// `(group, names)` pairs, in the order the groups appear. +type AccessGroups = Vec<(String, Vec)>; + +/// Lookup rows as the host reads them. +fn rows_to_py<'py>(py: Python<'py>, rows: &[Row]) -> PyResult> { + let rows = Value::Array(rows.iter().map(Row::wire).collect()); + to_py(py, &rows).map(|value| value.into_bound(py)) +} + +fn row_to_py<'py>(py: Python<'py>, row: &Row) -> PyResult> { + to_py(py, &row.wire()).map(|value| value.into_bound(py)) +} + +/// `{"aliases": [{alias, target}], "groups": [{name, members}], "wildcard": [requests]}`. +fn list_scope(scope: &Bound<'_, PyAny>) -> PyResult { + serde_json::from_value(document(scope)?) + .map_err(|error| PyValueError::new_err(format!("bad lookup scope: {error}"))) +} + +/// Read Python's outcome for `call`. +fn host_call_response( + call: &HostCall, + outcome: Option>, +) -> PyResult { + let missing = || { + drive_error_to_pyerr(DriveError::MissingResponse { + expected: call.kind(), + }) + }; + // `{"raised": True, ...}`: the step's work raised, reported as an attempt's failure. + if let HostCall::Select { .. } | HostCall::PreRoute { .. } | HostCall::AllowFallback { .. } = + call + && let Some(failure) = outcome.as_ref().and_then(|o| o.cast::().ok()) + && failure.contains("raised")? + { + return match attempt_outcome(failure)? { + Err(error) => Ok(HostCallResponse::Raised(error)), + Ok(_) => Err(PyValueError::new_err("a `raised` outcome is a failure")), + }; + } + match call { + HostCall::Sleep { .. } => Ok(HostCallResponse::Slept), + HostCall::AllowFallback { .. } => Ok(HostCallResponse::AllowFallback( + outcome.ok_or_else(missing)?.extract()?, + )), + HostCall::RefuseFallbacks { .. } => Ok(HostCallResponse::RefuseFallbacks( + outcome.ok_or_else(missing)?.extract()?, + )), + HostCall::Select { + stage: Stage::PreCall, + .. + } => { + let facts = from_py_argument(&outcome.ok_or_else(missing)?)?; + serde_json::from_value(facts) + .map(HostCallResponse::PreCall) + .map_err(|error| PyValueError::new_err(format!("bad pre-call facts: {error}"))) + } + HostCall::Select { + stage: Stage::RoutingPlugins { .. } | Stage::ProviderRequest, + .. + } => { + // `{"models": [...] | None}`: a bare None would read as no outcome. + let outcome = outcome.ok_or_else(missing)?; + let models = outcome.cast::()?.get_item("models")?; + Ok(HostCallResponse::Models(match models { + Some(models) if !models.is_none() => Some(models.extract()?), + _ => None, + })) + } + HostCall::Select { + stage: Stage::CallbackFilters { .. }, + .. + } => { + // The remaining ids, or a failure mapping as an attempt reports one. + let outcome = outcome.ok_or_else(missing)?; + if let Ok(failure) = outcome.cast::() { + return match attempt_outcome(failure)? { + Err(error) => Ok(HostCallResponse::Filtered(Err(error))), + Ok(_) => Err(PyValueError::new_err( + "a `callback_filters` outcome is the remaining ids or a failure", + )), + }; + } + Ok(HostCallResponse::Filtered(Ok(outcome.extract()?))) + } + HostCall::Select { .. } => Ok(HostCallResponse::Select( + outcome.ok_or_else(missing)?.extract()?, + )), + HostCall::PreRoute { .. } => pre_route_outcome(outcome).map(HostCallResponse::PreRoute), + HostCall::Attempt { .. } => { + let outcome = outcome.ok_or_else(missing)?; + let outcome = outcome.cast::()?; + let blocked = match outcome.get_item("blocked")? { + Some(value) if !value.is_none() => { + let name: String = value.extract()?; + Some(name.parse::().map_err(|_| { + PyValueError::new_err(format!( + "`{name}` is not a way a response is blocked" + )) + })?) + } + Some(_) | None => None, + }; + let deferred = outcome + .get_item("deferred")? + .is_some_and(|flag| flag.is_truthy().unwrap_or(false)); + let tracks_usage = outcome + .get_item("tracks_usage")? + .map(|flag| flag.extract::>()) + .transpose()? + .flatten(); + attempt_outcome(outcome).map(|result| match result { + Ok(total_tokens) if blocked.is_some() || deferred || tracks_usage.is_some() => { + HostCallResponse::Served { + total_tokens, + blocked, + deferred, + tracks_usage, + } + } + result => HostCallResponse::Attempt(result), + }) + } + HostCall::Cache { op, .. } => cache_outcome(*op, outcome).map(HostCallResponse::Cache), + HostCall::Secrets { .. } => Ok(HostCallResponse::Secrets(from_py_argument( + &outcome.ok_or_else(missing)?, + )?)), + // `None` is a response here (no row, no entry), so a missing outcome reads as one. + HostCall::ModelInfo { .. } => Ok(HostCallResponse::ModelInfo(match outcome { + Some(outcome) if !outcome.is_none() => from_py_argument(&outcome)?, + _ => Value::Null, + })), + HostCall::Build { kind, .. } => { + let outcome = outcome.ok_or_else(missing)?; + let outcome = outcome.cast::()?; + let invalid = outcome + .get_item("invalid")? + .is_some_and(|flag| flag.is_truthy().unwrap_or(false)); + match kind { + StepKind::Provider => Ok(HostCallResponse::Provided(if invalid { + Provided::Invalid + } else { + Provided::Provider(match outcome.get_item("provider")? { + Some(provider) if !provider.is_none() => Some(provider.extract()?), + _ => None, + }) + })), + _ => { + let built = if invalid { + Built::Invalid + } else { + match outcome.get_item("entry")? { + Some(entry) if !entry.is_none() => { + Built::Entry(from_py_argument(&entry)?) + } + _ => Built::Skip, + } + }; + Ok(if *kind == StepKind::Validate { + HostCallResponse::Validated(built) + } else { + HostCallResponse::Added(built) + }) + } + } + } + } +} + +/// A pre-route response: `None`, a model group name, or a custom strategy's deployment document. +fn pre_route_outcome(outcome: Option>) -> PyResult> { + let Some(outcome) = outcome.filter(|outcome| !outcome.is_none()) else { + return Ok(None); + }; + if let Ok(model) = outcome.cast::() { + return Ok(Some(PreRouted::Model(model.to_str()?.to_owned()))); + } + let spec: DeploymentSpec = serde_json::from_value(document(&outcome)?) + .map_err(|error| PyValueError::new_err(error.to_string()))?; + let deployment = Deployment::from_spec(spec) + .map_err(|error| PyValueError::new_err(Report::new(&error).to_string()))?; + Ok(Some(PreRouted::Deployment(Arc::new(deployment)))) +} + +/// `get`: the JSON value or None; `batch_get`: a list of JSON values or None, one per key; +/// `increment`: the new int or float; `set` and `delete`: None. +fn cache_outcome(op: CacheOp, outcome: Option>) -> PyResult { + let outcome = outcome.filter(|outcome| !outcome.is_none()); + let json = |value: Option| value.filter(|value| !value.is_null()); + match op { + CacheOp::Get => outcome + .map(|outcome| from_py_argument::(&outcome)) + .transpose() + .map(|value| CacheOutcome::Value(json(value))), + CacheOp::BatchGet => { + let outcome = outcome.ok_or_else(|| { + PyValueError::new_err("a `batch_get` cache outcome must be a list, not None") + })?; + if !outcome.is_instance_of::() { + return Err(PyValueError::new_err( + "a `batch_get` cache outcome must be a list with one entry per key", + )); + } + let values: Vec> = from_py_argument(&outcome)?; + Ok(CacheOutcome::Values(values.into_iter().map(json).collect())) + } + CacheOp::Increment => outcome + .filter(|outcome| !outcome.is_instance_of::()) + .and_then(|outcome| outcome.extract::().ok()) + .map(CacheOutcome::Number) + .ok_or_else(|| { + PyValueError::new_err("an `increment` cache outcome must be the new int or float") + }), + CacheOp::Set | CacheOp::Delete | CacheOp::IncrementUsage => match outcome { + None => Ok(CacheOutcome::Stored), + Some(_) => Err(PyValueError::new_err(format!( + "a `{op}` cache step has no outcome, so pass None" + ))), + }, + } +} + +/// `{"ok": True, "total_tokens": int}` (an attempt's may add `"blocked": str`, `"deferred": bool` +/// and `"tracks_usage": bool`) or `{"ok": False, "kind": str, "status": int | None, +/// "retry_after": float | None, "num_retries": int | None, "detail": str | None, +/// "outside_deployment": bool, "caller_scoped": bool, "status_absent": bool, +/// "uncounted_request": bool}`. +pub(crate) fn attempt_outcome(outcome: &Bound<'_, PyDict>) -> PyResult> { + fn item<'py, T: FromPyObjectOwned<'py>>( + outcome: &Bound<'py, PyDict>, + key: &str, + ) -> PyResult> { + match outcome.get_item(key)? { + Some(value) if !value.is_none() => Ok(Some(value.extract().map_err(Into::into)?)), + Some(_) | None => Ok(None), + } + } + let ok: bool = item(outcome, "ok")? + .ok_or_else(|| PyValueError::new_err("an attempt outcome needs `ok`"))?; + if ok { + return Ok(Ok(item(outcome, "total_tokens")?.unwrap_or(0))); + } + let kind: String = item(outcome, "kind")? + .ok_or_else(|| PyValueError::new_err("a failed attempt outcome needs `kind`"))?; + let kind: FailureKind = kind + .parse() + .map_err(|_| PyValueError::new_err(format!("`{kind}` is not a router failure kind")))?; + let retry_after = item::(outcome, "retry_after")? + .map(|seconds| { + Duration::try_from_secs_f64(seconds) + .map_err(|_| PyValueError::new_err("`retry_after` must be a non-negative number")) + }) + .transpose()?; + let mut failure = AttemptError::new(kind, item(outcome, "status")?); + failure.retry_after = retry_after; + failure.num_retries = item(outcome, "num_retries")?; + failure.failed_deployment_id = item(outcome, "failed_deployment_id")?; + failure.detail = item::(outcome, "detail")?.map(Into::into); + failure.recorded = item::(outcome, "recorded")?.unwrap_or(false); + failure.names_provider = item::(outcome, "llm_provider")?.unwrap_or(false); + failure.agentic_followup = item::(outcome, "agentic_followup")?.unwrap_or(false); + failure.outside_deployment = item::(outcome, "outside_deployment")?.unwrap_or(false); + failure.status_absent = item::(outcome, "status_absent")?.unwrap_or(false); + failure.uncounted_request = item::(outcome, "uncounted_request")?.unwrap_or(false); + failure.caller_scoped = item::(outcome, "caller_scoped")?.unwrap_or(false); + failure.classes = item::>(outcome, "classes")? + .unwrap_or_default() + .into_iter() + .map(Into::into) + .collect(); + Ok(Err(failure)) +} + +/// `[{"kind": "retries_exhausted", "model_group": str, "attempted": int, "max": int} +/// | {"kind": "fallback", "to": str, "order": int | None, "level": int}]`. +/// The `cause` of a `retry_logged` or `retry_policy_raised` event, with what names it. +fn cause_items(dict: &Bound<'_, PyDict>, cause: RetryCause) -> PyResult<()> { + match cause { + RetryCause::Attempt => dict.set_item("cause", "attempt"), + RetryCause::Level => dict.set_item("cause", "level"), + RetryCause::Other => dict.set_item("cause", "other"), + RetryCause::Pick(picked) => { + dict.set_item("cause", "pick")?; + pick_items(dict, &picked.0) + } + } +} + +/// A pick's error, as the `failed` step names it (`error_kind` and what names it), with the +/// model its message names (`failed_model`) when the error carries one. +fn pick_items(dict: &Bound<'_, PyDict>, error: &Error) -> PyResult<()> { + error_items(dict, error)?; + match error { + Error::NoHealthyDeployments { model } | Error::UnknownModel { model } => { + dict.set_item("failed_model", model) + } + _ => Ok(()), + } +} + +/// `error_kind` and the fields that name the error. +fn error_items(dict: &Bound<'_, PyDict>, error: &Error) -> PyResult<()> { + dict.set_item("error", Report::new(error).to_string())?; + dict.set_item("error_kind", <&'static str>::from(ErrorKind::from(error)))?; + match error { + Error::EndpointNotSupported { model, message } => { + dict.set_item("error_model", model)?; + dict.set_item("error_detail", message) + } + Error::OnlyMarkers { model } + | Error::UnknownModel { model } + | Error::NoPassThroughDeployments { model } + | Error::PtuReserved { model } + | Error::MultipleTeams { model } + | Error::DefaultDeploymentRaises { model } + | Error::IndexOutOfRange { model } => dict.set_item("error_model", model), + Error::ContextWindowExceeded { model, detail } => { + dict.set_item("error_model", model)?; + dict.set_item("error_detail", detail) + } + Error::UnsupportedParams { model, params } => { + dict.set_item("error_model", model)?; + dict.set_item("error_params", PyList::new(dict.py(), params)?) + } + Error::RoutingPluginsLeftNothing { models } => { + dict.set_item("error_params", PyList::new(dict.py(), models)?) + } + Error::Reserved { + model, + until, + timezone, + } => { + dict.set_item("error_model", model)?; + dict.set_item("error_detail", format!("{until} {timezone}")) + } + Error::NonNumericWeight { metric } => dict.set_item("error_detail", metric), + Error::MissingRoutingGroup { group } => dict.set_item("error_model", group), + Error::ModelInfo { exception, detail } => { + dict.set_item("error_exception", *exception)?; + dict.set_item("error_detail", detail) + } + _ => Ok(()), + } +} + +fn events_list(py: Python<'_>, events: Vec) -> PyResult> { + let list = PyList::empty(py); + for event in events { + let dict = PyDict::new(py); + match event { + RouterEvent::RetriesExhausted { + model_group, + attempted, + max, + level, + picked, + } => { + dict.set_item("kind", "retries_exhausted")?; + dict.set_item("model_group", model_group)?; + dict.set_item("attempted", attempted)?; + dict.set_item("max", max)?; + dict.set_item("level", level)?; + dict.set_item("picked", picked)?; + } + RouterEvent::Retry { retry, .. } => { + dict.set_item("kind", "retry")?; + dict.set_item("retry", retry)?; + } + RouterEvent::FallingBack { level, model } => { + dict.set_item("kind", "falling_back")?; + dict.set_item("level", level)?; + dict.set_item("model", model)?; + } + RouterEvent::OrderChainFailed { level, last_hop } => { + dict.set_item("kind", "order_chain_failed")?; + dict.set_item("level", level)?; + dict.set_item("last_hop", last_hop)?; + } + RouterEvent::FallbacksFailed { + level, + chain, + last_hop, + } => { + dict.set_item("kind", "fallbacks_failed")?; + dict.set_item("level", level)?; + dict.set_item("chain", chain)?; + dict.set_item("last_hop", last_hop)?; + } + RouterEvent::Fallback { + from, + to, + order, + depth, + level, + scope, + parent, + max_fallbacks, + unroutable, + } => { + dict.set_item("kind", "fallback")?; + dict.set_item("from", from)?; + dict.set_item("to", to)?; + dict.set_item("order", order)?; + dict.set_item("depth", depth)?; + dict.set_item("level", level)?; + dict.set_item("scope", scope)?; + dict.set_item("parent", parent)?; + dict.set_item("max_fallbacks", max_fallbacks)?; + if let Some(model) = unroutable { + dict.set_item("unroutable", to_py(py, &model)?)?; + } + } + RouterEvent::Blocked { + level, + model, + blocked, + } => { + dict.set_item("kind", "blocked")?; + dict.set_item("level", level)?; + dict.set_item("model", model)?; + dict.set_item("blocked", <&'static str>::from(blocked))?; + } + RouterEvent::FallbackDone { + from, + to, + level, + scope, + parent, + succeeded, + } => { + dict.set_item("kind", "fallback_done")?; + dict.set_item("from", from)?; + dict.set_item("to", to)?; + dict.set_item("level", level)?; + dict.set_item("scope", scope)?; + dict.set_item("parent", parent)?; + dict.set_item("succeeded", succeeded)?; + } + RouterEvent::RetryLogged { + scope, + level, + model, + attempted_retries, + cause, + } => { + dict.set_item("kind", "retry_logged")?; + dict.set_item("scope", scope)?; + dict.set_item("level", level)?; + dict.set_item("model", model)?; + dict.set_item("attempted_retries", attempted_retries)?; + cause_items(&dict, cause)?; + } + RouterEvent::RetryPolicyRaised { + level, + model, + cause, + } => { + dict.set_item("kind", "retry_policy_raised")?; + dict.set_item("level", level)?; + dict.set_item("model", model)?; + cause_items(&dict, cause)?; + } + RouterEvent::RetryCountRaised { + level, + model, + cause, + } => { + dict.set_item("kind", "retry_count_raised")?; + dict.set_item("level", level)?; + dict.set_item("model", model)?; + cause_items(&dict, cause)?; + } + RouterEvent::RetriesOpened { + scope, + max_retries, + model_group_size, + } => { + dict.set_item("kind", "retries_opened")?; + dict.set_item("scope", scope)?; + dict.set_item("max_retries", max_retries)?; + dict.set_item("model_group_size", model_group_size)?; + } + RouterEvent::RetryBudget { scope, max_retries } => { + dict.set_item("kind", "retry_budget")?; + dict.set_item("scope", scope)?; + dict.set_item("max_retries", max_retries)?; + } + RouterEvent::PickFailed { + level, + model, + error, + } => { + dict.set_item("kind", "pick_failed")?; + dict.set_item("level", level)?; + dict.set_item("model", model)?; + pick_items(&dict, &error.0)?; + } + RouterEvent::LevelFailed { + level, + model, + error, + handling, + } => { + dict.set_item("kind", "level_failed")?; + dict.set_item("level", level)?; + dict.set_item("model", model)?; + dict.set_item("handling", handling)?; + pick_items(&dict, &error.0)?; + } + RouterEvent::MockFailed { + mock, + level, + model, + num_retries, + } => { + dict.set_item("kind", "mock_failed")?; + dict.set_item("mock", <&'static str>::from(mock))?; + dict.set_item("level", level)?; + dict.set_item("model", model)?; + dict.set_item("num_retries", num_retries)?; + } + RouterEvent::CooldownSet { + deployment_id, + cooldown, + } => { + dict.set_item("kind", "cooldown_set")?; + dict.set_item("deployment_id", deployment_id)?; + dict.set_item("cooldown_time", cooldown.as_secs_f64())?; + } + RouterEvent::Selected { + deployment_id, + pick, + .. + } => { + dict.set_item("kind", "selected")?; + dict.set_item("deployment_id", deployment_id)?; + dict.set_item("pick_seconds", pick.as_secs_f64())?; + } + _ => continue, + } + list.append(dict)?; + } + Ok(list) +} + +fn step_dict(py: Python<'_>, step: Step) -> PyResult> { + let dict = PyDict::new(py); + let kind = match &step { + Step::HostCall(call) => call.kind(), + Step::Done(_) => StepKind::Done, + Step::Failed(_) => StepKind::Failed, + }; + dict.set_item("kind", <&'static str>::from(kind))?; + match step { + Step::HostCall(call) => host_call_items(py, &dict, call)?, + Step::Done(finish) => done_items(&dict, finish)?, + Step::Failed(error) => { + let attempt = error.attempt(); + error_items(&dict, &error)?; + dict.set_item("attempt_failed", attempt.is_some())?; + dict.set_item("status", attempt.and_then(|failure| failure.status))?; + dict.set_item( + "failure_kind", + attempt.map(|failure| <&'static str>::from(failure.kind)), + )?; + } + } + Ok(dict) +} + +fn host_call_items(py: Python<'_>, dict: &Bound<'_, PyDict>, call: HostCall) -> PyResult<()> { + match call { + HostCall::Attempt { + deployment_id, + deployment, + model, + model_group, + target_order, + candidate_ids, + retry, + fallback_depth, + fallback_level, + timeout, + params, + scope, + max_retries, + model_group_size, + } => { + dict.set_item("scope", scope)?; + dict.set_item("max_retries", max_retries)?; + dict.set_item("model_group_size", model_group_size)?; + dict.set_item("deployment_id", deployment_id)?; + dict.set_item("deployment", to_py(py, &deployment)?)?; + dict.set_item("model", model)?; + dict.set_item("model_group", model_group)?; + dict.set_item("target_order", target_order)?; + dict.set_item("candidate_ids", PyList::new(py, candidate_ids)?)?; + dict.set_item("retry", retry)?; + dict.set_item("fallback_depth", fallback_depth)?; + dict.set_item("fallback_level", fallback_level)?; + dict.set_item("timeout", timeout)?; + dict.set_item("params", params.map(|p| to_py(py, &p)).transpose()?) + } + HostCall::Sleep { seconds } => dict.set_item("seconds", seconds), + HostCall::AllowFallback { target } => dict.set_item("target", target), + HostCall::RefuseFallbacks { level, targets } => { + dict.set_item("level", level)?; + let targets = targets.0.iter().cloned().map(Value::Object).collect(); + dict.set_item("targets", to_py(py, &Value::Array(targets))?) + } + HostCall::Select { + stage, + model_group, + name, + scope, + group, + pool, + candidates, + } => { + let (stage, strategy) = match stage { + Stage::Plugins => ("plugins", None), + Stage::Strategy(strategy) => ("strategy", Some(strategy)), + Stage::Tags => ("tags", None), + Stage::PreCall => ("pre_call", None), + Stage::TextOnly => ("text_only", None), + Stage::RouteIncapable { handler } => { + dict.set_item("handler", handler)?; + ("route_incapable", None) + } + Stage::MediaRefusing => ("media_refusing", None), + Stage::ProviderRequest => ("provider_request", None), + Stage::CallbackFilters { + excluded_ids, + skipped_ids, + target_order, + } => { + dict.set_item("excluded_ids", excluded_ids)?; + dict.set_item("skipped_ids", skipped_ids)?; + dict.set_item("target_order", target_order)?; + ("callback_filters", None) + } + Stage::RoutingPlugins { run } => { + dict.set_item("run", run)?; + ("routing_plugins", None) + } + }; + dict.set_item("pool", PyList::new(py, pool)?)?; + dict.set_item("stage", stage)?; + dict.set_item("strategy", strategy)?; + dict.set_item("model_group", model_group)?; + dict.set_item("model", name)?; + dict.set_item("scope", scope)?; + dict.set_item("group", group)?; + dict.set_item("candidates", PyList::new(py, candidates)?) + } + HostCall::PreRoute { + model, + fallback_depth, + retry, + } => { + dict.set_item("model", model)?; + dict.set_item("fallback_depth", fallback_depth)?; + dict.set_item("retry", retry) + } + HostCall::Cache { + op, + key, + keys, + value, + ttl, + local, + } => { + dict.set_item("op", <&'static str>::from(op))?; + dict.set_item("key", key)?; + dict.set_item("keys", keys.map(|keys| PyList::new(py, keys)).transpose()?)?; + dict.set_item("value", value.map(|value| to_py(py, &value)).transpose()?)?; + dict.set_item("ttl", ttl)?; + dict.set_item("local", local) + } + HostCall::Secrets { index, refs } => { + dict.set_item("index", index)?; + let refs = refs + .into_iter() + .map(|secret| { + let item = PyDict::new(py); + item.set_item("name", secret.name)?; + match secret.at { + SecretAt::Param(key) => { + item.set_item("key", key)?; + item.set_item("env_only", false)?; + } + SecretAt::DataSource { source, key } => { + item.set_item("source", source)?; + item.set_item("key", key)?; + item.set_item("env_only", true)?; + } + } + Ok(item) + }) + .collect::>>()?; + dict.set_item("refs", PyList::new(py, refs)?) + } + HostCall::Build { + kind: _, + path, + index, + entry, + declared_id, + duplicate_id, + provider, + } => { + dict.set_item("path", <&'static str>::from(path))?; + dict.set_item("index", index)?; + dict.set_item("entry", to_py(py, &entry)?)?; + dict.set_item("declared_id", declared_id)?; + dict.set_item("duplicate_id", duplicate_id)?; + dict.set_item("provider", provider) + } + HostCall::ModelInfo { lookup } => { + if let Value::Object(lookup) = lookup { + for (key, value) in lookup { + dict.set_item(key, to_py(py, &value)?)?; + } + } + Ok(()) + } + } +} + +fn done_items(dict: &Bound<'_, PyDict>, finish: Finish) -> PyResult<()> { + match finish { + Finish::Call(response) => { + dict.set_item("deployment_id", response.deployment_id)?; + dict.set_item("model_group", response.model_group)?; + dict.set_item("attempted_retries", response.attempted_retries)?; + dict.set_item("max_retries", response.max_retries)?; + dict.set_item("attempted_fallbacks", response.attempted_fallbacks)?; + dict.set_item("total_tokens", response.output.total_tokens) + } + Finish::Selected { + deployment_id, + model_group, + deployment, + } => { + dict.set_item("deployment_id", deployment_id)?; + dict.set_item("model_group", model_group)?; + dict.set_item("deployment", to_py(dict.py(), &deployment)?) + } + Finish::Reported { cooldown } => { + dict.set_item("cooled", cooldown.is_some())?; + dict.set_item("cooldown_time", cooldown.map(|c| c.as_secs_f64())) + } + Finish::Built(built) => { + let py = dict.py(); + let records = built + .into_iter() + .map(|deployment| { + let item = PyDict::new(py); + item.set_item("index", deployment.index)?; + item.set_item( + "id", + deployment.spec.model_info.get("id").and_then(Value::as_str), + )?; + item.set_item("provider", deployment.spec.provider)?; + Ok(item) + }) + .collect::>>()?; + dict.set_item("built", PyList::new(py, records)?) + } + Finish::Counted { key } => dict.set_item("key", key), + Finish::RouterModelInfo(merged) => { + let py = dict.py(); + match merged { + Some(merged) => { + dict.set_item("info", to_py(py, &Value::Object(merged.info))?)?; + dict.set_item("user_keys", merged.user_keys) + } + None => dict.set_item("info", py.None()), + } + } + Finish::DeploymentModelInfo(info) => { + let py = dict.py(); + match info { + Some(info) => dict.set_item("info", to_py(py, &Value::Object(info))?), + None => dict.set_item("info", py.None()), + } + } + Finish::Value(value) => dict.set_item("value", to_py(dict.py(), &value)?), + Finish::Healthy { + single, + deployment_ids, + deployments, + } => { + dict.set_item("single", single)?; + dict.set_item("deployment_ids", deployment_ids)?; + let records = deployments + .iter() + .map(|d| to_py(dict.py(), d)) + .collect::>>()?; + dict.set_item("deployments", PyList::new(dict.py(), records)?) + } + } +} + +#[cfg(test)] +mod tests { + use pyo3::{ffi::c_str, prelude::*, types::PyDict}; + use rstest::rstest; + + const CONFIG: &str = r#"{"model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/a"}, "model_info": {"id": "a1"}} + ]}"#; + + const PAIR: &str = r#"{"model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/a"}, "model_info": {"id": "a1"}}, + {"model_name": "primary", "litellm_params": {"model": "openai/b"}, "model_info": {"id": "a2"}} + ]}"#; + + #[rstest] + fn python_drives_calls_and_selections_through_the_handle() { + Python::initialize(); + Python::attach(|py| { + let locals = PyDict::new(py); + locals.set_item("native", crate::native_module(py)).unwrap(); + locals.set_item("config", CONFIG).unwrap(); + locals.set_item("pair", PAIR).unwrap(); + py.run( + c_str!( + r#" +import time +store = {} +asked = [] + +def answer_cache(step): + asked.append(step) + op, key = step["op"], step["key"] + if op == "get": + return store.get(key) + if op == "batch_get": + return [store.get(k) for k in step["keys"]] + if op == "set": + store[key] = step["value"] + return None + if op == "increment": + store[key] = store.get(key, 0) + step["value"] + return store[key] + if op == "delete": + store.pop(key, None) + return None + raise AssertionError(op) + +def drive(call, outcome): + step = call.next(outcome) + while step["kind"] == "cache": + step = call.next(answer_cache(step)) + return step + +handle = native.RouterCoreHandle(config, {"num_retries": 1}) +picked = drive(handle.select("primary", {}), None) +assert (picked["kind"], picked["deployment_id"], picked["model_group"]) == ("done", "a1", "primary"), picked +assert [step["op"] for step in asked] == ["batch_get"] +assert list(asked[0]) == ["kind", "op", "key", "keys", "value", "ttl", "local", "events"], list(asked[0]) +call = handle.start("acompletion", '{"model": "primary"}') +version = handle.registry_version() +assert handle.apply({"delete": ["gone"]}) == version + 1 +steps = [drive(call, None)] +steps.append(drive(call, {"ok": False, "kind": "RateLimitError", "status": 429})) +steps.append(drive(call, None)) +steps.append(drive(call, {"ok": True, "total_tokens": 5})) +kinds = [step["kind"] for step in steps] + +cooled = native.RouterCoreHandle(pair, {"num_retries": 0}) +call = cooled.start("acompletion", {"model": "primary"}) +attempt = drive(call, None) +tried = attempt["deployment_id"] +assert attempt["deployment"]["model_info"]["id"] == tried, attempt +assert attempt["deployment"]["litellm_params"]["model"].startswith("openai/"), attempt +assert [d["model_info"]["id"] for d in cooled.deployments()] == ["a1", "a2"] +assert cooled.deployment("a2")["model_name"] == "primary" +assert cooled.resolve("primary")["ids"] == ["a1", "a2"] +assert cooled.resolve("nope") is None +assert drive(call, {"ok": False, "kind": "RateLimitError", "status": 429})["kind"] == "failed" +# The core records the failure itself: the 429 cools the deployment down in the host's store. +assert f"deployment:{tried}:cooldown" in store, store +other = drive(cooled.select("primary", {}), None) +assert other["kind"] == "done" and other["deployment_id"] != tried, other + +call = handle.select("primary", {}) +step = call.next(None) +assert step["op"] == "batch_get" +for bad in ([], [None, None], "nope", None): + try: + call.next(bad) + except ValueError: + pass + else: + raise AssertionError(f"{bad!r} should not answer a batch_get of one key") +assert drive(call, [None])["kind"] == "done" +"# + ), + Some(&locals), + Some(&locals), + ) + .unwrap(); + let kinds: Vec = locals + .get_item("kinds") + .unwrap() + .unwrap() + .extract() + .unwrap(); + assert_eq!(kinds, ["attempt", "sleep", "attempt", "done"]); + }); + } + + #[rstest] + #[case::unknown_key(r#"{"routing_strategy_args": {}}"#, true)] + #[case::bad_json("{", false)] + #[case::not_an_object("[]", false)] + fn construction_failures_raise_the_class_python_reads( + #[case] config: &str, + #[case] declined: bool, + ) { + Python::initialize(); + Python::attach(|py| { + let error = crate::native_module(py) + .getattr("RouterCoreHandle") + .and_then(|handle| handle.call1((config, "{}"))) + .unwrap_err(); + assert_eq!( + error.is_instance_of::(py), + declined, + "{error}" + ); + assert_eq!( + error.is_instance_of::(py), + !declined, + "{error}" + ); + }); + } +} diff --git a/litellm-rust/crates/python-bridge/src/router/retries.rs b/litellm-rust/crates/python-bridge/src/router/retries.rs new file mode 100644 index 00000000000..949aae96b34 --- /dev/null +++ b/litellm-rust/crates/python-bridge/src/router/retries.rs @@ -0,0 +1,55 @@ +//! The retry decisions `RouterCoreHandle` exposes as members: `get_num_retries_from_retry_policy` +//! and `should_retry_this_error`, decided by router-core for a failure Python describes the way it +//! describes a failed attempt. + +use litellm_router_core::{ + AttemptError, Router, + retry::{RetryContext, resolve_retry_policy, should_retry as core_should_retry}, +}; +use pyo3::{exceptions::PyValueError, prelude::*, types::PyDict}; + +fn failure(outcome: &Bound<'_, PyDict>) -> PyResult { + match super::attempt_outcome(outcome)? { + Err(failure) => Ok(failure), + Ok(_) => Err(PyValueError::new_err("a failure needs `ok: False`")), + } +} + +pub(crate) fn policy_retries( + router: &Router, + outcome: &Bound<'_, PyDict>, + model_group: Option<&str>, +) -> PyResult> { + let failure = failure(outcome)?; + let settings = router.settings(); + let policy = match model_group { + Some(group) => resolve_retry_policy( + settings.retry_policy.as_ref(), + group, + Some(&settings.model_group_retry_policy), + ), + None => settings.retry_policy.as_ref(), + }; + Ok(policy.and_then(|policy| policy.retries_for(&failure))) +} + +pub(crate) fn allowed_fails(router: &Router, outcome: &Bound<'_, PyDict>) -> PyResult> { + Ok(router.settings().allowed_fails_for(&failure(outcome)?)) +} + +pub(crate) fn should_retry( + outcome: &Bound<'_, PyDict>, + (healthy, all): (usize, usize), + (context_window, content_policy, regular): (bool, bool, bool), +) -> PyResult { + Ok(core_should_retry( + &failure(outcome)?, + RetryContext { + healthy, + all, + has_context_window_fallbacks: context_window, + has_content_policy_fallbacks: content_policy, + has_regular_fallbacks: regular, + }, + )) +} diff --git a/litellm-rust/crates/python-bridge/src/router/stream.rs b/litellm-rust/crates/python-bridge/src/router/stream.rs new file mode 100644 index 00000000000..f85d73e0778 --- /dev/null +++ b/litellm-rust/crates/python-bridge/src/router/stream.rs @@ -0,0 +1,94 @@ +//! The stream-recovery entry points of `RouterCoreHandle`: what may still take over a stream that +//! failed before content, the same-group stream retry, and the fallback walk re-entered from a +//! stream. The host's stream wrappers call them; the calls are driven like `start`. + +use litellm_router_core::{ + FailureKind, Op, Router, + call::{StreamOrigin, StreamPolicy}, +}; +use pyo3::{exceptions::PyValueError, prelude::*, types::PyDict}; + +use super::{RouterCall, attempt_outcome, config, config_error_to_pyerr, document, host::Finish}; + +/// A stream recovery a host wrapper asks for. +#[derive(Clone, Copy)] +pub(super) enum Recovery { + /// `_astream_retry_same_group`. + Retry, + /// The fallback walk re-entered from the stream wrapper. + Fallback, +} + +fn origin(value: &Bound<'_, PyAny>) -> PyResult { + serde_json::from_value(document(value)?) + .map_err(|error| PyValueError::new_err(format!("a stream origin: {error}"))) +} + +fn kind(kind: Option<&str>) -> PyResult> { + kind.map(|kind| { + kind.parse() + .map_err(|_| PyValueError::new_err(format!("`{kind}` is not a router failure kind"))) + }) + .transpose() +} + +/// `{"can_retry", "can_fall_back", "refusal_fallback", "retry_budget": int | None, +/// "policy_applies": bool}`. +pub(super) fn policy<'py>( + py: Python<'py>, + router: &Router, + request: &Bound<'py, PyAny>, + stream_origin: &Bound<'py, PyAny>, + failure_kind: Option<&str>, +) -> PyResult> { + let request = config::parse_request(document(request)?, None).map_err(config_error_to_pyerr)?; + let StreamPolicy { + can_retry, + can_fall_back, + refusal_fallback, + retry_budget, + } = router.stream_policy(&request, &origin(stream_origin)?, kind(failure_kind)?); + let dict = PyDict::new(py); + dict.set_item("can_retry", can_retry)?; + dict.set_item("can_fall_back", can_fall_back)?; + dict.set_item("refusal_fallback", refusal_fallback)?; + dict.set_item("retry_budget", retry_budget.map(|(budget, _)| budget))?; + dict.set_item( + "policy_applies", + retry_budget.is_some_and(|(_, applies)| applies), + )?; + Ok(dict) +} + +/// A recovery call for a stream from `stream_origin` that failed with `failure`. +pub(super) fn recover( + router: &Router, + recovery: Recovery, + op: &str, + request: &Bound<'_, PyAny>, + stream_origin: &Bound<'_, PyAny>, + failure: &Bound<'_, PyDict>, +) -> PyResult { + let op = Op::new(op); + let request = config::parse_request(document(request)?, None).map_err(config_error_to_pyerr)?; + let stream_origin = origin(stream_origin)?; + let Err(failure) = attempt_outcome(failure)? else { + return Err(PyValueError::new_err("a stream failure needs `ok: False`")); + }; + let router = router.clone(); + Ok(RouterCall::new(async move { + let response = match recovery { + Recovery::Retry => { + router + .retry_stream(op, request, stream_origin, failure) + .await + } + Recovery::Fallback => { + router + .fallback_stream(op, request, stream_origin, failure) + .await + } + }; + response.map(Finish::Call) + })) +} diff --git a/litellm-rust/crates/python-bridge/src/routes/chat_completions/mod.rs b/litellm-rust/crates/python-bridge/src/routes/chat_completions/mod.rs index d78d141f0f2..1bcdc18a765 100644 --- a/litellm-rust/crates/python-bridge/src/routes/chat_completions/mod.rs +++ b/litellm-rust/crates/python-bridge/src/routes/chat_completions/mod.rs @@ -4,7 +4,7 @@ use std::sync::Arc; use host::ChatCompletionsPythonHost; use litellm_auth::AuthServices; -use litellm_cache_response::{CachePolicy, ScopedCache}; +use litellm_cache_response::CachePolicy; use litellm_callbacks_legacy_python::LoggingOperation; use litellm_host::{call::HostedMachine, protocol::Protocol}; use litellm_inference_chat::{ChatCompletionsRoute, route::ChatCompletions}; @@ -57,10 +57,6 @@ impl InferenceRoute for ChatCompletionsRoute { Self::new(http, auth, secrets) } - fn with_cache(self, cache: ScopedCache) -> Self { - self.with_cache(cache) - } - fn machine( self, call: ::Request, diff --git a/litellm-rust/crates/python-bridge/src/routes/inference.rs b/litellm-rust/crates/python-bridge/src/routes/inference.rs index ca30c94b02f..1245c126c4e 100644 --- a/litellm-rust/crates/python-bridge/src/routes/inference.rs +++ b/litellm-rust/crates/python-bridge/src/routes/inference.rs @@ -1,7 +1,7 @@ use std::sync::Arc; use litellm_auth::AuthServices; -use litellm_cache_response::{CachePolicy, CacheScope, ScopedCache}; +use litellm_cache_response::CachePolicy; use litellm_callbacks_legacy_python::LoggingOperation; use litellm_core_utils::get_llm_provider_logic::get_custom_llm_provider; use litellm_host::{call::HostedMachine, protocol::Protocol}; @@ -142,7 +142,6 @@ pub(super) trait InferenceRoute: Sized + 'static { auth: Arc, secrets: Arc, ) -> Self; - fn with_cache(self, cache: ScopedCache) -> Self; fn machine( self, call: ::Request, @@ -176,12 +175,8 @@ where crate::http::resources().auth.clone(), crate::secrets::source(py)?, ); - let (cache, cache_options) = crate::cache::configured_native(py, arguments, call_type)?; - let route = match cache { - Some(cache) => route.with_cache(ScopedCache::new(cache, CacheScope::Shared)), - None => route, - }; - Ok(route.machine(request, cache_options.policy)) + crate::cache::ensure_cache_disabled(py, arguments, call_type)?; + Ok(route.machine(request, CachePolicy::default())) }, host, hooks, diff --git a/litellm-rust/crates/python-bridge/src/routes/messages/host.rs b/litellm-rust/crates/python-bridge/src/routes/messages/host.rs index 27ce8c943f0..af614f17360 100644 --- a/litellm-rust/crates/python-bridge/src/routes/messages/host.rs +++ b/litellm-rust/crates/python-bridge/src/routes/messages/host.rs @@ -34,11 +34,9 @@ fn merge_headers( forwarded: Option>, extra_headers: Option>, ) -> Option> { - let merged: Map = forwarded - .into_iter() - .flatten() - .chain(extra_headers.into_iter().flatten()) - .collect(); + let merged = litellm_inference_messages::merge_messages_header_sources( + forwarded.into_iter().chain(extra_headers), + ); (!merged.is_empty()).then_some(merged) } @@ -107,10 +105,19 @@ impl MessagesPythonHost { .map(|value| python_timeout_seconds(py, value.unbind())) .transpose()? .flatten(); - let custom_llm_provider = string("custom_llm_provider")?; - let shaping = self.shaping(py, &model, custom_llm_provider.as_deref(), arguments)?; let api_key = string("api_key")?; let api_base = string("api_base")?; + // Python's handler resolves a bare model name (`claude-sonnet-4-5`) through + // `get_llm_provider`'s model lists, which the native prefix lookup does not carry. + let custom_llm_provider = match string("custom_llm_provider")? { + Some(provider) => Some(provider), + None => py + .import(ROUTE_HOST_MODULE)? + .getattr("inferred_provider")? + .call1((&model, api_base.as_deref()))? + .extract()?, + }; + let shaping = self.shaping(py, &model, custom_llm_provider.as_deref(), arguments)?; let extra_headers = self.merged_headers(py, arguments)?; let provider_specific_header = self.provider_specific_header(py, arguments)?; let litellm_params = project_litellm_params(argument, |name| module_global(py, name))?; diff --git a/litellm-rust/crates/python-bridge/src/routes/messages/mod.rs b/litellm-rust/crates/python-bridge/src/routes/messages/mod.rs index c788760b268..a9ae01bd7ee 100644 --- a/litellm-rust/crates/python-bridge/src/routes/messages/mod.rs +++ b/litellm-rust/crates/python-bridge/src/routes/messages/mod.rs @@ -50,9 +50,18 @@ fn run_messages(py: Python<'_>, call: NativeCall<'_>, asynchronous: bool) -> PyR ) } +/// Python's sync Messages handler raises for every native provider before it sends anything +/// or opens a logging object (`BaseLLMHTTPHandler.anthropic_messages_handler`), and Rust copies +/// that until both sides serve sync calls. +const SYNC_NOT_IMPLEMENTED: &str = "anthropic_messages_handler is not implemented for sync calls"; + #[pyfunction] -pub(crate) fn messages(py: Python<'_>, call: NativeCall<'_>) -> PyResult> { - run_messages(py, call, false) +#[pyo3(signature = (call))] +pub(crate) fn messages(call: NativeCall<'_>) -> PyResult> { + drop(call); + Err(pyo3::exceptions::PyValueError::new_err( + SYNC_NOT_IMPLEMENTED, + )) } #[pyfunction] diff --git a/litellm-rust/crates/python-bridge/src/routes/responses/mod.rs b/litellm-rust/crates/python-bridge/src/routes/responses/mod.rs index 9c045d65c13..cc4d85b4d26 100644 --- a/litellm-rust/crates/python-bridge/src/routes/responses/mod.rs +++ b/litellm-rust/crates/python-bridge/src/routes/responses/mod.rs @@ -5,7 +5,7 @@ use std::sync::Arc; use host::ResponsesPythonHost; use litellm_auth::AuthServices; -use litellm_cache_response::{CachePolicy, ScopedCache}; +use litellm_cache_response::CachePolicy; use litellm_callbacks_legacy_python::LoggingOperation; use litellm_host::{call::HostedMachine, protocol::Protocol}; use litellm_inference_responses::{ResponsesRoute, route::Responses}; @@ -49,10 +49,6 @@ impl InferenceRoute for ResponsesRoute { Self::new(http, auth, secrets) } - fn with_cache(self, cache: ScopedCache) -> Self { - self.with_cache(cache) - } - fn machine( self, call: ::Request, diff --git a/litellm-rust/crates/router-core/Cargo.toml b/litellm-rust/crates/router-core/Cargo.toml index af97bd52c57..ff5e2e8161f 100644 --- a/litellm-rust/crates/router-core/Cargo.toml +++ b/litellm-rust/crates/router-core/Cargo.toml @@ -7,3 +7,21 @@ repository.workspace = true description = "The router core behind litellm.Router: registry, settings, health, selection and the call loop" [dependencies] +arc-swap.workspace = true +async-trait.workspace = true +litellm-cache.workspace = true +litellm-router-types.workspace = true +jiff = { version = "0.2.37", default-features = false, features = ["std", "tzdb-zoneinfo", "tzdb-bundle-always"] } +parking_lot.workspace = true +rand.workspace = true +serde.workspace = true +serde_with.workspace = true +serde_json = { workspace = true, features = ["preserve_order"] } +sha2.workspace = true +strum.workspace = true +thiserror.workspace = true +tracing.workspace = true + +[dev-dependencies] +rstest.workspace = true +tokio.workspace = true diff --git a/litellm-rust/crates/router-core/src/access.rs b/litellm-rust/crates/router-core/src/access.rs new file mode 100644 index 00000000000..1b91fa417da --- /dev/null +++ b/litellm-rust/crates/router-core/src/access.rs @@ -0,0 +1,236 @@ +//! Who may reach a deployment: model access windows (`litellm_core_utils/access_windows.py`, +//! a deployment reserved for some teams during a daily wall-clock window) and model access +//! groups (`_filter_deployments_by_model_access_groups`, a caller allowed only through access +//! groups is kept to its groups' deployments). + +use std::{collections::BTreeSet, sync::Arc}; + +use jiff::{Timestamp, tz::TimeZone}; +use serde_json::Value; + +use crate::registry::Deployment; + +/// One `model_info.access_windows` entry (`ModelAccessWindow`), validated when the deployment +/// was added. +#[derive(Clone, Debug, PartialEq)] +pub struct AccessWindow { + /// Microseconds after midnight. + pub start: u64, + pub end: u64, + pub timezone: String, + pub team_ids: Vec, +} + +const MICROS_PER_SECOND: u64 = 1_000_000; + +/// A `datetime.time` as pydantic reads it: `HH:MM[:SS[.ffffff]]`, or seconds after midnight. +fn wall_clock(value: &Value) -> Option { + match value { + Value::Number(seconds) => { + let seconds = seconds.as_f64()?; + (0.0..86_400.0) + .contains(&seconds) + .then(|| (seconds * MICROS_PER_SECOND as f64).round() as u64) + } + Value::String(text) => { + let mut parts = text.splitn(3, ':'); + let hour: u64 = parts.next()?.parse().ok()?; + let minute: u64 = parts.next()?.parse().ok()?; + let (second, micros) = match parts.next() { + None => (0, 0), + Some(rest) => { + let (whole, fraction) = rest.split_once('.').unwrap_or((rest, "")); + let digits: String = fraction.chars().take(6).collect(); + let micros = if digits.is_empty() { + 0 + } else { + format!("{digits:0<6}").parse().ok()? + }; + (whole.parse().ok()?, micros) + } + }; + (hour < 24 && minute < 60 && second < 60) + .then(|| ((hour * 60 + minute) * 60 + second) * MICROS_PER_SECOND + micros) + } + _ => None, + } +} + +impl AccessWindow { + fn parse(value: &Value) -> Option { + let window = value.as_object()?; + Some(Self { + start: wall_clock(window.get("start")?)?, + end: wall_clock(window.get("end")?)?, + timezone: window.get("timezone")?.as_str()?.to_owned(), + team_ids: window + .get("team_ids")? + .as_array()? + .iter() + .filter_map(Value::as_str) + .map(str::to_owned) + .collect(), + }) + } + + /// `is_window_active`: the window's wall clock contains `now`, wrapping past midnight when + /// it ends before it starts. + pub fn is_active(&self, now: Timestamp) -> bool { + let Ok(zone) = TimeZone::get(&self.timezone) else { + return false; + }; + let local = now.to_zoned(zone).time(); + let micros = ((u64::from(local.hour().unsigned_abs()) * 60 + + u64::from(local.minute().unsigned_abs())) + * 60 + + u64::from(local.second().unsigned_abs())) + * MICROS_PER_SECOND + + u64::from(local.subsec_nanosecond().unsigned_abs()) / 1_000; + if self.start < self.end { + self.start <= micros && micros < self.end + } else { + micros >= self.start || micros < self.end + } + } + + /// The window's end as `{end:%H:%M}`. + pub fn end_hhmm(&self) -> String { + let minutes = self.end / MICROS_PER_SECOND / 60; + format!("{:02}:{:02}", minutes / 60, minutes % 60) + } +} + +/// A deployment's access windows. +pub fn access_windows(deployment: &Deployment) -> Vec { + deployment + .model_info + .raw + .get("access_windows") + .and_then(Value::as_array) + .map(|windows| windows.iter().filter_map(AccessWindow::parse).collect()) + .unwrap_or_default() +} + +/// `_reservation_blocking_window`: the first active window, unless the caller's team is named +/// by one of the active windows. +fn blocking_window( + deployment: &Deployment, + team_id: Option<&str>, + now: Timestamp, +) -> Option { + let active: Vec = access_windows(deployment) + .into_iter() + .filter(|window| window.is_active(now)) + .collect(); + if let Some(team) = team_id + && active + .iter() + .any(|window| window.team_ids.iter().any(|id| id == team)) + { + return None; + } + active.into_iter().next() +} + +/// `filter_reserved_deployments`: the deployments no active window withholds from the caller, +/// and the first window that withheld one. +pub fn filter_reserved( + deployments: Vec>, + team_id: Option<&str>, + now: Timestamp, +) -> (Vec>, Option) { + let mut blocking = None; + let kept = deployments + .into_iter() + .filter( + |deployment| match blocking_window(deployment, team_id, now) { + None => true, + Some(window) => { + blocking.get_or_insert(window); + false + } + }, + ) + .collect(); + (kept, blocking) +} + +/// `_filter_deployments_by_model_access_groups`: a caller whose allowed models (`models` plus +/// `team_models`) reach `model` only through access groups is kept to the deployments in those +/// groups. `model_groups` are the access groups the rows listed for `model` carry. +pub fn filter_by_access_groups( + model: &str, + deployments: Vec>, + allowed_models: &[String], + model_groups: impl FnOnce() -> BTreeSet, +) -> Vec> { + if deployments.is_empty() || allowed_models.is_empty() { + return deployments; + } + let allowed = |name: &str| allowed_models.iter().any(|m| m == name); + if allowed(model) || allowed("*") || allowed("all-proxy-models") { + return deployments; + } + let groups: BTreeSet = model_groups() + .into_iter() + .filter(|group| allowed(group)) + .collect(); + if groups.is_empty() { + return deployments; + } + deployments + .into_iter() + .filter(|d| { + d.model_info + .access_groups + .iter() + .any(|g| groups.contains(g)) + }) + .collect() +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + #[rstest] + #[case::minutes(json!("09:30"), Some(34_200_000_000))] + #[case::seconds(json!("09:30:15"), Some(34_215_000_000))] + #[case::fraction(json!("00:00:00.5"), Some(500_000))] + #[case::number(json!(60), Some(60_000_000))] + #[case::bad(json!("25:00"), None)] + fn wall_clock_reads_pydantic_times(#[case] raw: Value, #[case] expected: Option) { + assert_eq!(wall_clock(&raw), expected); + } + + #[rstest] + #[case::inside("2026-01-01T10:00:00Z", true)] + #[case::at_end("2026-01-01T17:00:00Z", false)] + #[case::before("2026-01-01T08:59:59Z", false)] + fn a_window_is_active_inside_its_wall_clock(#[case] now: &str, #[case] expected: bool) { + let window = AccessWindow { + start: wall_clock(&json!("09:00")).unwrap(), + end: wall_clock(&json!("17:00")).unwrap(), + timezone: "UTC".to_owned(), + team_ids: vec!["t".to_owned()], + }; + assert_eq!(window.is_active(now.parse().unwrap()), expected); + assert_eq!(window.end_hhmm(), "17:00"); + } + + #[test] + fn an_overnight_window_wraps_past_midnight() { + let window = AccessWindow { + start: wall_clock(&json!("22:00")).unwrap(), + end: wall_clock(&json!("02:00")).unwrap(), + timezone: "UTC".to_owned(), + team_ids: vec!["t".to_owned()], + }; + assert!(window.is_active("2026-01-01T23:00:00Z".parse().unwrap())); + assert!(window.is_active("2026-01-01T01:00:00Z".parse().unwrap())); + assert!(!window.is_active("2026-01-01T12:00:00Z".parse().unwrap())); + } +} diff --git a/litellm-rust/crates/router-core/src/build.rs b/litellm-rust/crates/router-core/src/build.rs new file mode 100644 index 00000000000..36bad012b3a --- /dev/null +++ b/litellm-rust/crates/router-core/src/build.rs @@ -0,0 +1,386 @@ +//! The deployment build: how configured entries become the registry's deployments. +//! +//! The core owns the loop (`set_model_list`, `_create_deployment` and `_add_deployment`): which +//! values are secret references, the id of a deployment that declares none, one deployment per +//! `organization`, and the order everything happens in. What needs the embedding process is a +//! host step, asked for one deployment at a time so an error surfaces exactly where the Python +//! router raises it: +//! - [`Host::secrets`]: the `os.environ/` references the entry holds; +//! - [`Host::validate`]: the host's checks, and the entry as it normalizes it; +//! - [`Host::provider`]: the provider that serves it; +//! - [`Host::added`]: the host's side effects, and the entry as the registry stores it. + +use serde_json::{Map, Value}; + +use crate::{ + error::{ConfigError, Error}, + host::{BuildAsk, BuildPath, Built, Host, Provided, SecretAt, SecretRef}, + registry::{DeploymentSpec, deployment_id}, +}; + +/// The `litellm_params` keys whose `os.environ/` value is a secret pointer the identity source +/// dereferences at use time, so the build leaves it as written. The router's copy of +/// `_WIF_POINTER_FIELDS` (litellm/types/router.py), which the proxy's config loader also reads. +pub const SECRET_POINTER_PARAMS: &[&str] = &[ + "anthropic_issuer_signing_key_ref", + "anthropic_keycloak_client_secret_ref", +]; + +const SECRET_PREFIX: &str = "os.environ/"; + +/// How a build's deployments join the registry. +#[derive(Clone, Copy, Debug, PartialEq, Eq, strum::IntoStaticStr, strum::EnumString)] +#[strum(serialize_all = "snake_case")] +pub enum Install { + /// They become every deployment (`set_model_list`). + Replace, + /// They are added at the end (a deployment retried once its provider resolves). + Append, + /// Each replaces the deployment with its id, if any, and is added at the end + /// (`add_deployment`, an upsert). + Upsert, +} + +/// One deployment the build accepted, as the registry stores it. +#[derive(Clone, Debug, PartialEq)] +pub struct BuiltDeployment { + /// The entry index in the list the build was given. + pub index: usize, + pub spec: DeploymentSpec, +} + +/// Build `entries` (model_list entries) through `host`, in order. `resolve_secrets` resolves +/// top-level `os.environ/` references first, as `set_model_list` does; `add_deployment` and +/// upserts take their params as given. `install` takes each deployment as soon as it is +/// accepted, so it joins the registry before the next one is built, as the Python router adds +/// each in turn. +pub async fn build( + host: &dyn Host, + path: BuildPath, + entries: Vec>, + resolve_secrets: bool, + mut install: impl FnMut(&BuiltDeployment) -> Result<(), Error> + Send, +) -> Result, Error> { + let declared: Vec> = entries.iter().map(declared_id).collect(); + let mut built = Vec::new(); + for (index, mut entry) in entries.into_iter().enumerate() { + let model_name = text(entry.get("model_name")); + let mut params = match entry.remove("litellm_params") { + Some(Value::Object(params)) => params, + _ => Map::new(), + }; + if resolve_secrets { + let refs = param_refs(¶ms); + if !refs.is_empty() { + let values = host.secrets(index, &refs).await?; + for (secret, value) in refs.into_iter().zip(values) { + if let SecretAt::Param(key) = secret.at { + params.insert(key, value); + } + } + } + } + let mut info = match entry.remove("model_info") { + Some(Value::Object(info)) => info, + _ => Map::new(), + }; + let declared_id = declared[index].clone(); + if !info.contains_key("id") { + info.insert( + "id".to_owned(), + Value::String(deployment_id(&model_name, ¶ms)), + ); + } + // `set_model_list` adds one deployment per organization of a list, each with the + // organization set on the same params (so every one keeps the list's id). + let organizations = match (path, params.get("organization")) { + (BuildPath::Create, Some(Value::Array(organizations))) => organizations.clone(), + _ => vec![Value::Null], + }; + let duplicate_id = path == BuildPath::Create + && declared_id.as_ref().is_some_and(|id| { + declared + .iter() + .filter(|other| other.as_ref() == Some(id)) + .count() + > 1 + }); + for organization in organizations { + if !organization.is_null() { + params.insert("organization".to_owned(), organization); + } + let mut deployment = entry.clone(); + deployment.insert("model_name".to_owned(), Value::String(model_name.clone())); + deployment.insert("litellm_params".to_owned(), Value::Object(params.clone())); + deployment.insert("model_info".to_owned(), Value::Object(info.clone())); + if let Some(spec) = build_one( + host, + path, + index, + &deployment, + declared_id.as_deref(), + duplicate_id, + ) + .await? + { + let deployment = BuiltDeployment { index, spec }; + install(&deployment)?; + built.push(deployment); + } + } + } + Ok(built) +} + +/// One deployment's steps: validate, provider, the data-source references, added. +async fn build_one( + host: &dyn Host, + path: BuildPath, + index: usize, + entry: &Map, + declared_id: Option<&str>, + duplicate_id: bool, +) -> Result, Error> { + let ask = |entry| BuildAsk { + path, + index, + entry, + declared_id, + duplicate_id, + }; + let validated = match host.validate(&ask(entry)).await? { + Built::Entry(validated) => validated, + Built::Skip | Built::Invalid => return Ok(None), + }; + let provider = match host.provider(&ask(&validated)).await? { + Provided::Provider(provider) => provider, + Provided::Invalid => return Ok(None), + }; + let refs = data_source_refs(&validated); + if !refs.is_empty() { + let _ = host.secrets(index, &refs).await?; + } + let stored = match host.added(&ask(&validated), provider.as_deref()).await? { + Built::Entry(stored) => stored, + Built::Skip | Built::Invalid => return Ok(None), + }; + let model_name = text(stored.get("model_name")); + let mut spec: DeploymentSpec = serde_json::from_value(Value::Object(stored)) + .map_err(|source| ConfigError::InvalidDeployment { model_name, source })?; + spec.provider = provider; + Ok(Some(spec)) +} + +/// The top-level `litellm_params` values `set_model_list` resolves. +fn param_refs(params: &Map) -> Vec { + params + .iter() + .filter(|(key, _)| !SECRET_POINTER_PARAMS.contains(&key.as_str())) + .filter_map(|(key, value)| { + let name = value + .as_str() + .filter(|name| name.starts_with(SECRET_PREFIX))?; + Some(SecretRef { + name: name.to_owned(), + at: SecretAt::Param(key.clone()), + }) + }) + .collect() +} + +/// The `dataSources[].parameters.endpoint` / `key` references `_add_deployment` reads from the +/// environment. +fn data_source_refs(entry: &Map) -> Vec { + let sources = entry + .get("litellm_params") + .and_then(|params| params.get("dataSources")) + .and_then(Value::as_array); + let mut refs = Vec::new(); + for (source, data_source) in sources.into_iter().flatten().enumerate() { + let Some(parameters) = data_source.get("parameters").and_then(Value::as_object) else { + continue; + }; + for key in ["endpoint", "key"] { + if let Some(name) = parameters + .get(key) + .and_then(Value::as_str) + .filter(|name| name.starts_with(SECRET_PREFIX)) + { + refs.push(SecretRef { + name: name.to_owned(), + at: SecretAt::DataSource { + source, + key: key.to_owned(), + }, + }); + } + } + } + refs +} + +/// The `model_info.id` an entry declares, as Python's `str()` spells it. +fn declared_id(entry: &Map) -> Option { + match entry.get("model_info")?.get("id")? { + Value::Null => None, + Value::String(id) => Some(id.clone()), + other => Some(other.to_string()), + } +} + +/// A name as Python's `str()` spells it. +fn text(value: Option<&Value>) -> String { + match value { + Some(Value::String(text)) => text.clone(), + Some(Value::Null) | None => "None".to_owned(), + Some(other) => other.to_string(), + } +} + +#[cfg(test)] +mod tests { + use std::sync::{Arc, Mutex}; + + use async_trait::async_trait; + use serde_json::json; + + use super::*; + use crate::{ + cache::{InMemoryRouterCache, RouterCache}, + error::AttemptError, + host::{Attempt, Output, RouterEvent, RouterRequest, RoutingContext, SelectStage}, + registry::Deployment, + }; + + /// Records every build step and resolves `os.environ/X` to `secret-X`. + #[derive(Default)] + struct Recording { + steps: Mutex>, + } + + #[async_trait] + impl Host for Recording { + async fn invoke(&self, _attempt: &Attempt) -> Result { + unreachable!("the build runs no attempt") + } + async fn select( + &self, + _stage: &SelectStage, + _ctx: &RoutingContext<'_>, + candidates: Vec>, + ) -> Result>, Error> { + Ok(candidates) + } + async fn allow_fallback( + &self, + _request: &RouterRequest, + _target: &str, + ) -> Result { + Ok(true) + } + async fn sleep(&self, _duration: std::time::Duration) {} + fn observe(&self, _event: &RouterEvent) {} + fn cache(&self) -> Arc { + Arc::new(InMemoryRouterCache::default()) + } + async fn secrets(&self, _index: usize, refs: &[SecretRef]) -> Result, Error> { + self.steps.lock().unwrap().push(format!("secrets {refs:?}")); + Ok(refs + .iter() + .map(|r| json!(format!("secret-{}", &r.name[SECRET_PREFIX.len()..]))) + .collect()) + } + async fn validate(&self, ask: &BuildAsk<'_>) -> Result { + self.steps.lock().unwrap().push(format!( + "validate {} {}", + ask.index, ask.entry["litellm_params"] + )); + Ok(Built::Entry(ask.entry.clone())) + } + async fn provider(&self, ask: &BuildAsk<'_>) -> Result { + self.steps + .lock() + .unwrap() + .push(format!("provider {}", ask.index)); + Ok(Provided::Provider(Some("azure".to_owned()))) + } + async fn added(&self, ask: &BuildAsk<'_>, provider: Option<&str>) -> Result { + self.steps + .lock() + .unwrap() + .push(format!("added {} {provider:?}", ask.index)); + Ok(Built::Entry(ask.entry.clone())) + } + } + + fn entries(value: Value) -> Vec> { + serde_json::from_value(value).unwrap() + } + + #[tokio::test] + async fn create_resolves_secrets_then_builds_one_deployment_per_organization() { + let host = Recording::default(); + let built = build( + &host, + BuildPath::Create, + entries(json!([{ + "model_name": "g", + "litellm_params": { + "model": "azure/x", + "api_key": "os.environ/KEY", + "anthropic_issuer_signing_key_ref": "os.environ/POINTER", + "organization": ["a", "b"], + }, + }])), + true, + |_| Ok(()), + ) + .await + .unwrap(); + let steps = host.steps.lock().unwrap().clone(); + assert_eq!(steps.len(), 7, "{steps:?}"); + assert!(steps[0].starts_with("secrets") && steps[0].contains("KEY")); + assert!(!steps[0].contains("POINTER")); + assert!(steps[1].contains(r#""organization":"a""#)); + assert!(steps[1].contains("secret-KEY")); + assert_eq!(steps[3], "added 0 Some(\"azure\")"); + assert!(steps[4].contains(r#""organization":"b""#)); + assert_eq!(built.len(), 2); + assert_eq!(built[0].spec.provider.as_deref(), Some("azure")); + assert_eq!( + built[0].spec.model_info["id"], + built[1].spec.model_info["id"] + ); + let deployment = Deployment::from_spec(built[0].spec.clone()).unwrap(); + assert_eq!(deployment.provider(), "azure"); + } + + #[tokio::test] + async fn add_leaves_params_as_given_and_asks_for_data_source_references() { + let host = Recording::default(); + let built = build( + &host, + BuildPath::Add, + entries(json!([{ + "model_name": "g", + "litellm_params": { + "model": "azure/x", + "api_key": "os.environ/KEY", + "organization": ["a", "b"], + "dataSources": [{"parameters": {"endpoint": "os.environ/END", "key": "plain"}}], + }, + "model_info": {"id": "given"}, + }])), + false, + |_| Ok(()), + ) + .await + .unwrap(); + let steps = host.steps.lock().unwrap().clone(); + assert_eq!(steps.len(), 4, "{steps:?}"); + assert!(steps[0].contains("os.environ/KEY")); + assert!(steps[2].contains("DataSource { source: 0, key: \"endpoint\" }")); + assert_eq!(built.len(), 1); + assert_eq!(built[0].spec.model_info["id"], "given"); + } +} diff --git a/litellm-rust/crates/router-core/src/cache.rs b/litellm-rust/crates/router-core/src/cache.rs new file mode 100644 index 00000000000..9811e34a3e3 --- /dev/null +++ b/litellm-rust/crates/router-core/src/cache.rs @@ -0,0 +1,159 @@ +//! [`RouterCache`]: the DualCache-style store all routing state lives in, under the keys, +//! encodings and TTLs the Python router uses, so Python and Rust workers share it. Method names +//! follow `litellm-cache`'s `BaseCache`, `BatchCache`, `CounterCache` and `DeleteCache`. + +use std::{ + collections::HashMap, + sync::Arc, + time::{Duration, Instant}, +}; + +use async_trait::async_trait; +use litellm_cache::Error; +use parking_lot::Mutex; +use serde_json::Value; + +#[async_trait] +pub trait RouterCache: Send + Sync { + async fn async_get_cache(&self, key: &str) -> Result, Error>; + + async fn async_set_cache( + &self, + key: &str, + value: Value, + ttl: Option, + ) -> Result<(), Error>; + + /// Add `amount` to the number at `key` (0 when missing) and return the new value. The TTL + /// applies when the key is created, as Redis `INCRBYFLOAT` + `EXPIRE NX` does. + async fn async_increment( + &self, + key: &str, + amount: f64, + ttl: Option, + ) -> Result; + + async fn async_batch_get_cache(&self, keys: &[String]) -> Result>, Error>; + + async fn async_delete_cache(&self, key: &str) -> Result<(), Error>; + + /// Read this worker's in-memory tier only (`local_only=True`). + async fn async_get_local(&self, key: &str) -> Result, Error> { + self.async_get_cache(key).await + } + + /// Add to a counter in this worker's in-memory tier only (`local_only=True`). + async fn async_increment_local( + &self, + key: &str, + amount: f64, + ttl: Option, + ) -> Result { + self.async_increment(key, amount, ttl).await + } + + /// `_increment_deployment_usage`'s write: add each `(key, amount)` in one pipeline. With a + /// shared tier, this worker's in-memory tier then holds the shared totals, so its reads see + /// what other workers counted up to now. + async fn async_increment_usage( + &self, + increments: &[(String, f64)], + ttl: Option, + ) -> Result<(), Error> { + for (key, amount) in increments { + self.async_increment(key, *amount, ttl).await?; + } + Ok(()) + } +} + +#[derive(Default)] +struct Entry { + value: Value, + expires: Option, +} + +/// An in-process [`RouterCache`], for tests and for state Python keeps `local_only`. +#[derive(Clone, Default)] +pub struct InMemoryRouterCache { + entries: Arc>>, +} + +impl InMemoryRouterCache { + fn live(entries: &mut HashMap, key: &str) -> Option { + let expired = entries + .get(key) + .is_some_and(|entry| entry.expires.is_some_and(|at| at <= Instant::now())); + if expired { + entries.remove(key); + } + entries.get(key).map(|entry| entry.value.clone()) + } + + pub fn get(&self, key: &str) -> Option { + Self::live(&mut self.entries.lock(), key) + } + + pub fn increment(&self, key: &str, amount: f64, ttl: Option) -> f64 { + let mut entries = self.entries.lock(); + let current = Self::live(&mut entries, key).and_then(|value| value.as_f64()); + let next = current.unwrap_or(0.0) + amount; + let value = serde_json::Number::from_f64(next) + .map(|number| { + if next.fract() == 0.0 && next.abs() < i64::MAX as f64 { + Value::from(next as i64) + } else { + Value::Number(number) + } + }) + .unwrap_or(Value::Null); + let expires = match (current, entries.get(key)) { + (Some(_), Some(entry)) => entry.expires, + _ => ttl.map(|ttl| Instant::now() + ttl), + }; + entries.insert(key.to_owned(), Entry { value, expires }); + next + } +} + +#[async_trait] +impl RouterCache for InMemoryRouterCache { + async fn async_get_cache(&self, key: &str) -> Result, Error> { + Ok(self.get(key)) + } + + async fn async_set_cache( + &self, + key: &str, + value: Value, + ttl: Option, + ) -> Result<(), Error> { + let expires = ttl.map(|ttl| Instant::now() + ttl); + self.entries + .lock() + .insert(key.to_owned(), Entry { value, expires }); + Ok(()) + } + + async fn async_increment( + &self, + key: &str, + amount: f64, + ttl: Option, + ) -> Result { + Ok(self.increment(key, amount, ttl)) + } + + async fn async_batch_get_cache(&self, keys: &[String]) -> Result>, Error> { + let mut entries = self.entries.lock(); + Ok(keys + .iter() + .map(|key| Self::live(&mut entries, key)) + .collect()) + } + + async fn async_delete_cache(&self, key: &str) -> Result<(), Error> { + self.entries.lock().remove(key); + Ok(()) + } +} diff --git a/litellm-rust/crates/router-core/src/call.rs b/litellm-rust/crates/router-core/src/call.rs new file mode 100644 index 00000000000..287bb98d8b7 --- /dev/null +++ b/litellm-rust/crates/router-core/src/call.rs @@ -0,0 +1,1555 @@ +//! The call loop: select, run the attempt, then retry in the same group or fall back to another +//! until it succeeds or the policy is exhausted. Mirrors `Router.async_function_with_fallbacks`, +//! `async_function_with_fallbacks_common_utils`, `async_function_with_retries`, +//! `should_retry_this_error` and `_time_to_sleep_before_retry` in `litellm/router.py`, and +//! `run_async_fallback` in `router_utils/fallback_event_handlers.py`. + +use std::{ + borrow::Cow, + future::Future, + pin::Pin, + sync::Arc, + time::{Duration, Instant}, +}; + +use serde_json::{Map, Value}; + +use tracing::warn; + +use crate::{ + Core, RouterStateSnapshot, + config::Op, + error::{AttemptError, ConfigError, Error, FailureKind, Unsupported}, + fallback::{FallbackKeys, FallbackTarget, Fallbacks}, + health::{GroupShape, should_retry_status, team_model_has_alternatives}, + host::{ + Attempt, Blocked, Output, PickError, RetryCause, RouterEvent, RouterRequest, + UncountedRetries, + }, + host_index::python_str, + lookup::Lookup, + mock::MockFailure, + outcome::OutcomeWrite, + prerouting::{PreRoute, PreRouted}, + registry::{ResolveKind, ResolveScope}, + retry::{RetryContext, resolve_retry_policy, should_retry}, + select::{Candidates, SelectInputs}, +}; + +mod stream; + +pub use self::stream::{StreamOrigin, StreamPolicy}; + +/// `INITIAL_RETRY_DELAY`, `MAX_RETRY_DELAY` and `JITTER` in `litellm/constants.py`. +const INITIAL_RETRY_DELAY: f64 = 0.5; +const MAX_RETRY_DELAY: f64 = 8.0; +const JITTER: f64 = 0.75; +/// `calculate_retry_after` obeys a provider's retry-after up to a minute. +const MAX_HONOURED_RETRY_AFTER: Duration = Duration::from_secs(60); + +#[derive(Clone, Debug)] +pub struct RouterResponse { + pub output: Output, + pub deployment_id: String, + pub model_group: String, + pub attempted_retries: u32, + /// The retry budget of the loop a retry succeeded in (`x-litellm-max-retries`); `None` + /// when the first attempt succeeded. + pub max_retries: Option, + pub attempted_fallbacks: u32, +} + +/// A failed attempt with the deployment it ran on, when one was picked. +struct Failed { + error: Box, + deployment_id: Option, +} + +impl From for Failed { + fn from(error: Error) -> Self { + Self { + error: Box::new(error), + deployment_id: None, + } + } +} + +/// Where a level of the fallback chain sits: `depth` is `run_async_fallback`'s counter, one more +/// for every target tried, `level` how many fallbacks deep the chain is, and `scope` the level's +/// own copy of the request metadata (every hop copies its parent's). +#[derive(Clone, Copy, Debug, Default)] +struct FallbackHop { + depth: u32, + level: u32, + scope: u32, +} + +/// What the whole chain shares: the attempts made (`attempted_targets`) and the scopes handed out. +#[derive(Debug, Default)] +struct FallbackChain { + attempted: Vec, + scopes: u32, +} + +/// What one level of the chain serves: a group, or the same group at a later `order`, with the +/// request params the chain's dict targets merged so far (`kwargs.update(target)`). +#[derive(Clone, Debug)] +struct Target { + group: String, + order: Option, + params: Option>>, + /// `_excluded_deployment_ids` a weighted failover hop put on the request: never picked. + excluded: Arc<[String]>, + /// `_failover_excluded_ids` in the level's metadata: the deployments weighted failover + /// already excluded on the way here. + failover_excluded: Arc<[String]>, +} + +/// A step of a level's fallback chain: a configured target, or an order level of the group. +#[derive(Clone, Debug)] +enum Next { + Fallback(FallbackTarget), + Order(String, i64), + /// A weighted failover hop: the same group without the deployments already excluded. + Failover(String, Arc<[String]>), +} + +/// An attempt the chain already made (`fallback_attempt_key`). +#[derive(Clone, Debug, PartialEq)] +enum Tried { + Target(FallbackTarget), + Order(String, i64), + Failover(String, Vec), +} + +/// The fallback lists a call reads: the request's own where it passed them, else the router's. +struct Lists<'a> { + fallbacks: Option<&'a Fallbacks>, + context_window: Option<&'a Fallbacks>, + content_policy: Option<&'a Fallbacks>, + keys: &'a FallbackKeys, +} + +impl<'a> Lists<'a> { + fn of(snapshot: &'a RouterStateSnapshot, request: &'a RouterRequest) -> Self { + let dynamic = &snapshot.settings.dynamic; + let pick = |own: &'a Option>, router: Option<&'a Fallbacks>| match own { + Some(own) => own.as_ref(), + None => router, + }; + Self { + fallbacks: pick(&request.fallbacks, Some(&dynamic.fallbacks)), + context_window: pick( + &request.context_window_fallbacks, + dynamic.context_window_fallbacks.as_ref(), + ), + content_policy: pick( + &request.content_policy_fallbacks, + dynamic.content_policy_fallbacks.as_ref(), + ), + keys: &dynamic.fallback_keys, + } + } + + fn has_regular(&self) -> bool { + self.fallbacks.is_some_and(|list| !list.is_empty()) + } +} + +/// `has_unattempted_fallback_target` over the chain `list` resolves for the level's lookup +/// groups: before the first hop nothing counts as tried, and a dict target with its own params +/// is never skipped. +fn unattempted_chain( + list: &Fallbacks, + lists: &Lists<'_>, + request: &RouterRequest, + target: &Target, + at: FallbackHop, + attempted: &[Tried], +) -> bool { + let mut lookup = vec![target.group.as_str()]; + if request.model != target.group { + lookup.push(request.model.as_str()); + } + list.lookup_groups(&lookup, lists.keys) + .is_some_and(|targets| { + at.level == 0 + || targets.iter().any(|next| match next.identity() { + FallbackTarget::Params(_) => true, + identity => !attempted.contains(&Tried::Target(identity)), + }) + }) +} + +/// The deployments `_core_get_model_list(model_name=group, team_id=team_id)` lists: the name's own +/// (a team's public name among them), an alias's target's, a routing group's members, and only +/// when none of those serve it, the wildcard routes (`_get_wildcard_deployments`), the proxy-wide +/// pattern's and then the team's. +fn group_members( + snapshot: &RouterStateSnapshot, + group: &str, + team_id: Option<&str>, +) -> Vec> { + let registry = &snapshot.registry; + let all = |name: &str, team_id: Option<&str>| { + crate::resolve::all_deployments(registry, name, team_id).unwrap_or_default() + }; + let members = |routing_group: &crate::registry::RoutingGroupSpec| { + crate::routing_groups::members(routing_group, |member| all(member, None)) + }; + let mut rows = all(group, team_id); + if let Some(alias_target) = registry.alias_of(group) { + rows.extend(match registry.routing_group_named(alias_target) { + Some(routing_group) => members(routing_group), + None => all(alias_target, None), + }); + } + if let Some(routing_group) = registry.routing_group_named(group) { + rows.extend(members(routing_group)); + } + if rows.is_empty() { + if let Some((_, routed)) = registry.wildcard_for(group) { + rows.extend(routed); + } + if let Some(team) = team_id { + rows.extend(Lookup::new(registry).team_wildcard(group, team)); + } + } + rows +} + +/// What `_maybe_run_weighted_failover` catches and defers to the regular fallbacks: +/// `openai.APIError` (every litellm provider error, a failure the host reported no classes for +/// among them), `RouterRateLimitError` and `RouterRateLimitErrorBasic`. Anything else propagates. +fn defers_to_regular_fallbacks(error: &Error) -> bool { + retried_failure(error).is_some_and(|failure| { + failure.classes.is_empty() + || [ + "APIError", + "BadRequestError", + "ServiceUnavailableError", + "RouterRateLimitError", + "RouterRateLimitErrorBasic", + ] + .iter() + .any(|class| failure.is_a(class)) + }) +} + +/// `is_bad_request_without_fallback` with `fallback_on_unsupported_params` off: an unsupported +/// params error, or a provider's plain 400 bad request. +fn is_bad_request_without_fallback(failure: &AttemptError) -> bool { + if !failure.is_a("BadRequestError") { + return false; + } + if failure.is_a("UnsupportedParamsError") { + return true; + } + if [ + "ContextWindowExceededError", + "ContentPolicyViolationError", + "UnsupportedEndpointError", + ] + .iter() + .any(|class| failure.is_a(class)) + { + return false; + } + failure.status == Some(400) && failure.names_provider +} + +type BoxFuture<'a, T> = Pin + Send + 'a>>; + +/// `KeyError`'s classes, most specific first. +/// The failure a retry loop decides by: an attempt's, or the exception a failed pick raised +/// (Python's loop retries a pick's error like any other: no deployment available, a stale +/// routing group's `KeyError`, ...). +fn retried_failure(error: &Error) -> Option> { + match error { + Error::Attempt(failure) => Some(Cow::Borrowed(failure)), + _ => error.pick_failure().map(Cow::Owned), + } +} + +impl Core { + pub(crate) async fn call( + &self, + op: Op, + request: Arc, + ) -> Result { + let snapshot = self.snapshot.load_full(); + let mut chain = FallbackChain::default(); + let target = Target { + group: request.model.clone(), + order: None, + params: None, + excluded: Arc::from([]), + failover_excluded: Arc::from([]), + }; + let at = FallbackHop::default(); + // A fallbacks mock stands in for the requested group's retry loop: no pick, no attempt. + let Some(mock) = request.mock_failure.filter(|mock| mock.before_retries()) else { + return self + .with_fallbacks(&snapshot, &op, &request, target, at, &mut chain) + .await; + }; + let failed = Failed::from(self.mock_failed(mock, &target, at, None)); + self.fall_back(&snapshot, &op, &request, target, at, &mut chain, failed) + .await + } + + /// One level of `async_function_with_fallbacks`: the target's retry loop, then its + /// fallbacks if every attempt failed. + #[allow(clippy::too_many_arguments)] + fn with_fallbacks<'a>( + &'a self, + snapshot: &'a RouterStateSnapshot, + op: &'a Op, + request: &'a Arc, + target: Target, + at: FallbackHop, + chain: &'a mut FallbackChain, + ) -> BoxFuture<'a, Result> { + Box::pin(async move { + let failed = match self + .with_retries(snapshot, op, request, &target, at, &chain.attempted) + .await + { + Ok(response) => return Ok(response), + Err(failed) => failed, + }; + self.fall_back(snapshot, op, request, target, at, chain, failed) + .await + }) + } + + /// The level after its own failure: the no-fallback checks, weighted failover, then the + /// fallback targets. A level that fails raises its own error, whatever its fallbacks raised, + /// except an order chain's failure on any error but a context window one, which raises what + /// the chain's last hop raised ([`RouterEvent::OrderChainFailed`]). + /// A stream that fails before content re-enters here (`fallback_stream`), so the group's + /// retry loop does not run again. + #[allow(clippy::too_many_arguments)] + async fn fall_back( + &self, + snapshot: &RouterStateSnapshot, + op: &Op, + request: &Arc, + target: Target, + at: FallbackHop, + chain: &mut FallbackChain, + failed: Failed, + ) -> Result { + let Failed { + error, + deployment_id: failed_id, + } = failed; + let error = *error; + self.level_failed(at, &target, &error, false); + if self.raises_without_fallback(snapshot, request, &error) { + return Err(error); + } + // `async_function_with_fallbacks_common_utils` lists the group's deployments + // (`_core_get_model_list`) for its order fallbacks: a written index position past the + // model list raises there, before any fallback. + if let Err(raised) = crate::resolve::all_deployments( + &snapshot.registry, + &target.group, + request.listing_team_id.as_deref(), + ) { + self.level_failed(at, &target, &raised, true); + return Err(raised); + } + let (targets, order_path) = self.fallback_targets(snapshot, request, &target, &error); + if !order_path { + self.host.observe(&RouterEvent::FallingBack { + level: at.level, + model: target.group.clone(), + }); + } + let mut target = target; + // `_maybe_run_weighted_failover`: its own `run_async_fallback`, before the regular one. + let failover = if order_path { + None + } else { + match self + .weighted_failover(snapshot, request, &target, &error, failed_id.as_deref()) + .await + { + Ok(failover) => failover, + Err(raised) => { + // `_get_routing_context` raised inside the level's fallback handling: the + // level raises that error, before any regular fallback. + self.level_failed(at, &target, &raised, true); + return Err(raised); + } + } + }; + if let Some(failover) = failover { + let excluded = match &failover { + Next::Failover(_, excluded) => excluded.clone(), + _ => Arc::from([]), + }; + target.failover_excluded = excluded; + match self + .run_fallbacks(snapshot, op, request, &target, at, chain, vec![failover]) + .await + { + Ok(response) => return Ok(response), + Err(raised) if defers_to_regular_fallbacks(raised.as_ref().unwrap_or(&error)) => {} + // Outside the `try` around the regular fallbacks: the level raises it as it is. + Err(raised) => { + self.host.observe(&RouterEvent::OrderChainFailed { + level: at.level, + last_hop: raised.is_some(), + }); + return Err(raised.unwrap_or(error)); + } + } + } + let Some(targets) = targets else { + self.host.observe(&RouterEvent::FallbacksFailed { + level: at.level, + chain: false, + last_hop: false, + }); + return Err(error); + }; + let last_hop_error = match self + .run_fallbacks(snapshot, op, request, &target, at, chain, targets) + .await + { + Ok(response) => return Ok(response), + Err(raised) => raised, + }; + if !order_path { + self.host.observe(&RouterEvent::FallbacksFailed { + level: at.level, + chain: true, + last_hop: last_hop_error.is_some(), + }); + return Err(error); + } + // The order path's `raise`, outside the `try` that re-raises the original error: only a + // context window error stays the one the caller sees. + let context_window = retried_failure(&error) + .is_some_and(|failure| failure.is_a("ContextWindowExceededError")); + let raised = last_hop_error.filter(|_| !context_window); + self.host.observe(&RouterEvent::OrderChainFailed { + level: at.level, + last_hop: raised.is_some(), + }); + Err(raised.unwrap_or(error)) + } + + /// `run_async_fallback` over one chain: the depth is checked once on entry, then every + /// target tried counts one more. When the chain served nothing, the error its last hop + /// raised (`error_from_fallbacks`), or `None` when no hop ran. + #[allow(clippy::too_many_arguments)] + fn run_fallbacks<'a>( + &'a self, + snapshot: &'a RouterStateSnapshot, + op: &'a Op, + request: &'a Arc, + target: &'a Target, + at: FallbackHop, + chain: &'a mut FallbackChain, + targets: Vec, + ) -> BoxFuture<'a, Result>> { + Box::pin(async move { + let max_fallbacks = request + .max_fallbacks + .unwrap_or(snapshot.settings.max_fallbacks); + if at.depth >= max_fallbacks { + return Err(None); + } + let failed = Tried::Target(FallbackTarget::Name(target.group.clone())); + if !chain.attempted.contains(&failed) { + chain.attempted.push(failed); + } + // Before the loop, or the refusal would be one target's failure: no target of the + // chain is tried, and the walk raises a `ValueError` the host holds. + let dicts: Vec> = targets + .iter() + .filter_map(|next| match next { + Next::Fallback(FallbackTarget::Params(dict)) => Some(dict.clone()), + _ => None, + }) + .collect(); + if !dicts.is_empty() && self.host.refuses_fallbacks(at.level, &dicts).await { + let refused = AttemptError::host_raised(&["ValueError"]); + return Err(Some(Error::Attempt(refused))); + } + let mut params = target.params.clone(); + let mut hop = at.depth; + let mut last_hop_error = None; + // `kwargs["model"]` as a dict target's non-string `model` left it: later targets + // without a `model` keep it. + let mut unroutable: Option = None; + for next in targets { + let (tried, group, order) = match &next { + Next::Order(group, order) => ( + Tried::Order(group.clone(), *order), + group.clone(), + Some(*order), + ), + Next::Failover(group, excluded) => { + let mut key = excluded.to_vec(); + key.sort(); + (Tried::Failover(group.clone(), key), group.clone(), None) + } + Next::Fallback(FallbackTarget::Name(name)) if *name == target.group => continue, + // A provider-scoped request never leaves its group; a dict target with no + // `model` names no group, so it is skipped too. + Next::Fallback(fallback) + if request.same_group_fallbacks_only + && fallback.model() != Some(target.group.as_str()) => + { + continue; + } + Next::Fallback(fallback) => { + if let Some(model) = fallback.model() + && model != target.group + { + // A check that raises ends the loop outside its `try`, as the + // chain's own failure. + match self.host.allow_fallback(request, model).await { + Ok(true) => {} + Ok(false) => continue, + Err(raised) => return Err(Some(Error::Attempt(raised))), + } + } + let group = fallback.model().unwrap_or(&target.group).to_owned(); + (Tried::Target(fallback.identity()), group, None) + } + }; + if chain.attempted.contains(&tried) { + continue; + } + chain.attempted.push(tried); + if let Next::Fallback(fallback) = &next + && let Some(merged) = fallback.params() + { + let mut combined = params.as_deref().cloned().unwrap_or_default(); + combined.extend(merged.iter().map(|(k, v)| (k.clone(), v.clone()))); + params = Some(Arc::new(combined)); + } + match &next { + Next::Fallback(fallback) if fallback.model().is_none() => { + if let Some(model) = fallback.unroutable_model() { + unroutable = Some(model.clone()); + } + } + _ => unroutable = None, + } + let group = unroutable.as_ref().map_or(group, python_str); + hop += 1; + self.host.observe(&RouterEvent::RetryLogged { + scope: at.scope, + level: at.level, + model: target.group.clone(), + attempted_retries: None, + cause: RetryCause::Level, + }); + chain.scopes += 1; + self.host.observe(&RouterEvent::Fallback { + from: target.group.clone(), + to: group.clone(), + order, + depth: hop, + level: at.level + 1, + scope: chain.scopes, + parent: at.scope, + max_fallbacks, + unroutable: unroutable.clone(), + }); + let excluded = match &next { + Next::Failover(_, excluded) => excluded.clone(), + _ => target.excluded.clone(), + }; + let next = Target { + group: group.clone(), + order, + params: params.clone(), + excluded, + failover_excluded: target.failover_excluded.clone(), + }; + let parent = at; + let at = FallbackHop { + depth: hop, + level: at.level + 1, + scope: chain.scopes, + }; + // A non-string `model` is a hop that fails before any attempt, on an error its + // own level's fallback lookup raises too, so it walks no chain of its own. + let result = match &unroutable { + Some(_) => Err(Error::UnknownModel { + model: group.clone(), + }), + None => { + self.with_fallbacks(snapshot, op, request, next, at, chain) + .await + } + }; + self.host.observe(&RouterEvent::FallbackDone { + from: target.group.clone(), + to: group, + level: parent.level, + scope: at.scope, + parent: parent.scope, + succeeded: result.is_ok(), + }); + match result { + Ok(mut response) => { + response.attempted_fallbacks = hop; + return Ok(response); + } + Err(raised) => last_hop_error = Some(raised), + } + } + Err(last_hop_error) + }) + } + + /// `_maybe_run_weighted_failover`'s hop for a failed deployment, when it applies: the + /// simple-shuffle group re-picked without every deployment already excluded, while one + /// that is not cooling down remains. + async fn weighted_failover( + &self, + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + target: &Target, + error: &Error, + failed_id: Option<&str>, + ) -> Result, Error> { + if !snapshot.settings.enable_weighted_failover { + return Ok(None); + } + if retried_failure(error).is_some_and(|failure| { + failure.is_a("ContextWindowExceededError") + || failure.is_a("ContentPolicyViolationError") + }) { + return Ok(None); + } + // `_get_routing_context` runs first, whatever failed: a stale routing-group member map + // raises its `KeyError` here. + snapshot.missing_routing_group(request, &target.group)?; + if request.skip_weighted_failover || error.attempt().is_none() { + return Ok(None); + } + let kind = snapshot + .registry + .resolve(&target.group, ResolveScope::default()) + .map_or(ResolveKind::Group, |resolution| resolution.kind); + let (strategy, _) = crate::strategy::routing_context( + &snapshot.registry, + &snapshot.settings.routing_strategy, + request.routing_strategy.as_deref(), + &kind, + &target.group, + ); + if strategy != crate::config::RoutingStrategy::SimpleShuffle { + return Ok(None); + } + let Some(failed_id) = failed_id else { + return Ok(None); + }; + let mut excluded: Vec = target.failover_excluded.to_vec(); + if !excluded.iter().any(|id| id == failed_id) { + excluded.push(failed_id.to_owned()); + } + let listing_team = request.listing_team_id.as_deref(); + let ids: Vec = group_members(snapshot, &target.group, listing_team) + .iter() + .filter(|d| d.listed_for_team(listing_team)) + .map(|d| d.id.clone()) + .collect(); + let cooling = self + .health + .active_cooldowns(&snapshot.registry.ids()) + .await + .unwrap_or_default(); + let remaining = ids + .iter() + .any(|id| !excluded.contains(id) && !cooling.iter().any(|(cooled, _)| cooled == id)); + Ok(remaining.then(|| Next::Failover(target.group.clone(), excluded.into()))) + } + + /// `async_function_with_fallbacks_common_utils` raises before looking for any fallback: + /// fallbacks are off, the error is a guardrail's, a bad request without + /// `fallback_on_unsupported_params`, or no fallback serves the error at all. + fn raises_without_fallback( + &self, + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + error: &Error, + ) -> bool { + if request.disable_fallbacks { + return true; + } + // Python decides by the exception alone, so a pick's error falls back like an attempt's: + // an `UnsupportedParamsError` raises, and the refusals name no provider. Only an error no + // pick raises (no Python exception stands behind it) has no fallback. + retried_failure(error).is_none_or(|failure| { + failure.kind == FailureKind::GuardrailIntervention + || (!snapshot.settings.fallback_on_unsupported_params + && is_bad_request_without_fallback(&failure)) + }) + } + + /// The fallback targets for a failure, or `None` when it must be raised as is + /// (`async_function_with_fallbacks_common_utils`). + fn fallback_targets( + &self, + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + target: &Target, + error: &Error, + ) -> (Option>, bool) { + // A pick's error decides by its exception's classes as an attempt's does: a pre-call + // context window refusal takes the context window fallbacks, any other the generic ones. + let failure = retried_failure(error); + let is_a = |name: &str| failure.as_ref().is_some_and(|f| f.is_a(name)); + let lists = Lists::of(snapshot, request); + // `fallback_lookup_groups`: the group being served, then the group the request was for. + let mut lookup = vec![target.group.as_str()]; + if request.model != target.group { + lookup.push(request.model.as_str()); + } + let chain = |list: &Fallbacks| { + if list.is_client_side(lists.keys) { + Some(list.as_chain()) + } else { + list.lookup_groups(&lookup, lists.keys) + } + }; + let fallbacks_of = |targets: Vec| { + targets.into_iter().map(Next::Fallback).collect::>() + }; + // `context_window_fallback_model_group`: only a chain the group matched takes precedence. + let context_window_targets = is_a("ContextWindowExceededError") + .then(|| lists.context_window?.lookup_groups(&lookup, lists.keys)) + .flatten(); + let skip_order = is_a("ContentPolicyViolationError") || context_window_targets.is_some(); + if !skip_order { + // A routing group's members, with a priority group's priorities as their order. + let listing_team = request.listing_team_id.as_deref(); + let mut orders: Vec = group_members(snapshot, &target.group, listing_team) + .iter() + .filter(|d| d.listed_for_team(listing_team)) + .filter_map(|d| d.order()) + .collect(); + orders.sort_unstable(); + orders.dedup(); + if orders.len() > 1 { + let current = target.order.unwrap_or(orders[0]); + let mut targets: Vec = orders + .into_iter() + .filter(|order| *order > current) + .map(|order| Next::Order(target.group.clone(), order)) + .collect(); + if let Some(list) = lists.fallbacks { + targets.extend(fallbacks_of(chain(list).unwrap_or_default())); + } + if !targets.is_empty() { + return (Some(targets), true); + } + } + } + if let Some(list) = lists.fallbacks + && list.is_client_side(lists.keys) + && context_window_targets.is_none() + { + return (Some(fallbacks_of(list.as_chain())), false); + } + if let Some(targets) = context_window_targets { + return (Some(fallbacks_of(targets)), false); + } + // A context window list with no match falls through to the regular fallbacks; a content + // policy list with no match raises. + if is_a("ContentPolicyViolationError") + && let Some(list) = lists.content_policy + { + return ( + list.lookup_groups(&lookup, lists.keys).map(fallbacks_of), + false, + ); + } + ( + lists + .fallbacks + .and_then(|list| list.lookup_groups(&lookup, lists.keys)) + .map(fallbacks_of), + false, + ) + } + + /// A level's first attempt, or the rate-limit mock in its place + /// (`_handle_mock_testing_rate_limit_error`), which the retry loop handles like a failed + /// attempt. + #[allow(clippy::too_many_arguments)] + async fn first_attempt( + &self, + snapshot: &RouterStateSnapshot, + op: &Op, + request: &Arc, + target: &Target, + inputs: &SelectInputs, + max_retries: u32, + place: (FallbackHop, &[Tried]), + ) -> Result { + if request.mock_failure != Some(MockFailure::RateLimit) { + return self + .attempt( + snapshot, + op, + request, + target, + inputs, + (0, max_retries), + place, + ) + .await; + } + // A lone deployment's `num_retries` rides on the mock error, as on a real one. + let lone = snapshot + .registry + .group(&target.group) + .filter(|group| group.len() == 1) + .and_then(|group| group[0].raw_params.get("num_retries")?.as_u64()) + .and_then(|retries| u32::try_from(retries).ok()); + Err(self + .mock_failed(MockFailure::RateLimit, target, place.0, lone) + .into()) + } + + async fn with_retries( + &self, + snapshot: &RouterStateSnapshot, + op: &Op, + request: &Arc, + target: &Target, + at: FallbackHop, + attempted: &[Tried], + ) -> Result { + let place = (at, attempted); + let mut inputs = SelectInputs { + target_order: target.order, + excluded_ids: target.excluded.clone(), + requested: Some(target.group.clone()), + fallback_hop: at.level > 0, + ..SelectInputs::default() + }; + let counting = SelectInputs { + count_only: true, + ..SelectInputs::default() + }; + let settings = &snapshot.settings; + let first_budget = request.num_retries.unwrap_or(settings.num_retries); + self.host.observe(&RouterEvent::RetriesOpened { + scope: at.scope, + max_retries: first_budget, + model_group_size: snapshot.registry.model_list_len(&target.group), + }); + let first = self + .first_attempt(snapshot, op, request, target, &inputs, first_budget, place) + .await; + let mut failed = match first { + Ok(response) => return Ok(response), + Err(failed) => failed, + }; + self.pick_failed(at, target, &failed.error); + // A guardrail's block and a failed agentic follow-up are re-raised as they are, before + // anything else looks at them (`async_function_with_retries`). + if matches!( + &*failed.error, + Error::Attempt(failure) + if failure.kind == FailureKind::GuardrailIntervention || failure.agentic_followup + ) { + return Err(failed); + } + // The first failure looks the group's retry policy up; a lookup that raises replaces the + // failure with its own error, before any retry (`async_function_with_retries`). + if request.retry_policy_raises.contains(&target.group) { + self.host.observe(&RouterEvent::RetryPolicyRaised { + level: at.level, + model: target.group.clone(), + cause: RetryCause::of(&failed.error), + }); + return Err(Failed { + error: Box::new(Error::Attempt(AttemptError::host_raised(&["Exception"]))), + deployment_id: None, + }); + } + let Some(first_failure) = retried_failure(&failed.error) else { + return Err(failed); + }; + let failure: &AttemptError = &first_failure; + // A request's `num_retries`, a count or not, wins over the deployment's and the router's. + let mut num_retries = if request.uncounted_retries.is_some() { + 0 + } else { + request + .num_retries + .or(failure.num_retries) + .unwrap_or(settings.num_retries) + }; + let group_policies = request + .model_group_retry_policy + .as_ref() + .unwrap_or(&settings.model_group_retry_policy); + let policy_retries = (request.num_retries != Some(0)) + .then(|| { + resolve_retry_policy( + settings.retry_policy.as_ref(), + &target.group, + Some(group_policies), + )? + .retries_for(failure) + }) + .flatten(); + let policy_applies = policy_retries.is_some(); + num_retries = policy_retries.unwrap_or(num_retries); + drop(first_failure); + // `_async_get_healthy_deployments` finds no group for a deployment id, so a call by id + // counts no deployments when deciding whether to retry. + let counted = |c: &Candidates, n: usize| if c.kind.is_single() { 0 } else { n }; + let all = self + .candidates(snapshot, op, request, &target.group, &counting) + .await + .map(|c| counted(&c, c.all.len())) + .unwrap_or(0); + + for retry in 0..=num_retries { + if retry > 0 { + self.log_retry(target, at, retry, &failed.error); + } + let healthy_ids: Vec = match self + .candidates(snapshot, op, request, &target.group, &counting) + .await + { + Ok(c) => { + let ids = c.healthy.iter().map(|d| d.id.clone()); + ids.take(counted(&c, c.healthy.len())).collect() + } + // `_async_get_healthy_deployments` swallows the lookup's error and still reads the + // cooldowns: a Redis round trip the refused pick's failure log runs across. + Err(_) => { + let _ = self.health.active_cooldowns(&snapshot.registry.ids()).await; + Vec::new() + } + }; + let healthy = healthy_ids.len(); + // A pick's error is retried as Python's loop retries any exception: a retry policy + // keeps going, else `should_retry_this_error` decides (it raises when nothing is + // healthy). + let Some(failure) = retried_failure(&failed.error) else { + return Err(failed); + }; + if !policy_applies && !self.should_retry(snapshot, request, &failure, healthy, all) { + return Err(failed); + } + let uncounted = request.uncounted_retries.filter(|_| !policy_applies); + if retry == 0 && uncounted.is_none() { + self.host.observe(&RouterEvent::RetryBudget { + scope: at.scope, + max_retries: num_retries, + }); + } + if uncounted == Some(UncountedRetries::Raises) { + self.host.observe(&RouterEvent::RetryCountRaised { + level: at.level, + model: target.group.clone(), + cause: RetryCause::of(&failed.error), + }); + return Err(Failed { + error: Box::new(Error::Attempt(AttemptError::host_raised(&["Exception"]))), + deployment_id: None, + }); + } + if num_retries == 0 { + return Err(failed); + } + if retry == 0 { + self.log_retry(target, at, 0, &failed.error); + } + let named = failure.failed_deployment_id.as_ref(); + if let (Some(status), Some(id)) = + (failure.status, named.or(failed.deployment_id.as_ref())) + && !should_retry_status(status) + && !inputs.skipped_ids.contains(id) + { + inputs.skipped_ids.push(id.clone()); + } + // An endpoint a deployment does not serve is retried on the others, until every + // one refused (`_every_deployment_refused`). + if failure.is_a("UnsupportedEndpointError") + && healthy_ids.iter().all(|id| inputs.skipped_ids.contains(id)) + { + return Err(failed); + } + let delay = self.time_to_sleep( + snapshot, + failure.retry_after, + num_retries - retry, + num_retries, + healthy, + all, + ); + self.host.sleep(delay).await; + if retry == num_retries { + self.host.observe(&RouterEvent::RetriesExhausted { + model_group: target.group.clone(), + attempted: num_retries, + max: num_retries, + level: at.level, + picked: failed.error.attempt().is_none(), + }); + break; + } + self.host.observe(&RouterEvent::Retry { + model_group: target.group.clone(), + retry: retry + 1, + delay, + }); + match self + .attempt( + snapshot, + op, + request, + target, + &inputs, + (retry + 1, num_retries), + place, + ) + .await + { + Ok(mut response) => { + response.max_retries = Some(num_retries); + return Ok(response); + } + Err(next) if next.error.attempt().is_some_and(|f| f.agentic_followup) => { + return Err(next); + } + Err(next) => { + self.pick_failed(at, target, &next.error); + failed = next; + } + } + } + Err(failed) + } + + /// `error` is a pick's: reported as it happens, whatever the level then does with it. + fn pick_failed(&self, at: FallbackHop, target: &Target, error: &Error) { + if let Some(picked) = PickError::of(error) { + self.host.observe(&RouterEvent::PickFailed { + level: at.level, + model: target.group.clone(), + error: picked, + }); + } + } + + /// The level serving `target` raises a pick's `error` ([`RouterEvent::LevelFailed`]); + /// `handling` when its fallback handling raised it. + fn level_failed(&self, at: FallbackHop, target: &Target, error: &Error, handling: bool) { + if let Some(picked) = PickError::of(error) { + self.host.observe(&RouterEvent::LevelFailed { + level: at.level, + model: target.group.clone(), + error: picked, + handling, + }); + } + } + + /// `_core_log_retry` for a failure in the level's retry loop. + fn log_retry(&self, target: &Target, at: FallbackHop, retry: u32, error: &Error) { + let cause = match RetryCause::of(error) { + RetryCause::Other => RetryCause::Attempt, + cause => cause, + }; + self.host.observe(&RouterEvent::RetryLogged { + scope: at.scope, + level: at.level, + model: target.group.clone(), + attempted_retries: Some(retry), + cause, + }); + } + + /// A `mock_testing_*` failure for the level's group, reported to the host, which raises + /// the matching exception. + fn mock_failed( + &self, + mock: MockFailure, + target: &Target, + at: FallbackHop, + num_retries: Option, + ) -> Error { + self.host.observe(&RouterEvent::MockFailed { + mock, + level: at.level, + model: target.group.clone(), + num_retries, + }); + Error::Attempt(mock.failure(num_retries)) + } + + fn should_retry( + &self, + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + failure: &AttemptError, + healthy: usize, + all: usize, + ) -> bool { + let lists = Lists::of(snapshot, request); + should_retry( + failure, + RetryContext { + healthy, + all, + has_context_window_fallbacks: lists.context_window.is_some(), + has_content_policy_fallbacks: lists.content_policy.is_some(), + has_regular_fallbacks: lists.has_regular(), + }, + ) + } + + /// `_time_to_sleep_before_retry` and `calculate_retry_after`. + fn time_to_sleep( + &self, + snapshot: &RouterStateSnapshot, + retry_after: Option, + remaining_retries: u32, + num_retries: u32, + healthy: usize, + all: usize, + ) -> Duration { + if all != 1 && healthy > 0 { + return Duration::ZERO; + } + let jitter = JITTER * self.rng.next_f64(); + if let Some(retry_after) = retry_after + && !retry_after.is_zero() + && retry_after <= MAX_HONOURED_RETRY_AFTER + { + return retry_after + Duration::from_secs_f64(jitter); + } + let exponent = num_retries.saturating_sub(remaining_retries); + let backoff = (INITIAL_RETRY_DELAY * 2f64.powi(exponent as i32)) + .max(snapshot.settings.retry_after.as_secs_f64()) + .min(MAX_RETRY_DELAY); + Duration::from_secs_f64(backoff + jitter) + } + + /// One attempt: select a deployment, run it through the host, record the outcome. + #[allow(clippy::too_many_arguments)] + async fn attempt( + &self, + snapshot: &RouterStateSnapshot, + op: &Op, + request: &Arc, + target: &Target, + inputs: &SelectInputs, + (retry, max_retries): (u32, u32), + (at, attempted): (FallbackHop, &[Tried]), + ) -> Result { + if request.unrouted { + return self + .unrouted_attempt(snapshot, op, request, target, (retry, max_retries), at) + .await; + } + let pick_started = Instant::now(); + let (deployment, candidates) = match self + .picked(snapshot, op, request, target, inputs, retry, at) + .await + { + Ok(picked) => picked, + Err(failed) if request.passthrough_on_no_deployment => { + self.pick_failed(at, target, &failed.error); + return self + .unrouted_attempt(snapshot, op, request, target, (retry, max_retries), at) + .await; + } + Err(failed) => return Err(failed), + }; + self.host.observe(&RouterEvent::Selected { + model_group: candidates.model_group.clone(), + deployment_id: deployment.id.clone(), + pick: pick_started.elapsed(), + }); + if !self.host.supports(op, deployment.provider()) { + return Err(Error::Config(ConfigError::Unsupported(Unsupported::Op { + op: op.clone(), + provider: deployment.provider().to_owned(), + })) + .into()); + } + // A name no deployment serves is routed to the first default fallback + // (`_common_checks_available_deployment`), still stamped as the name. + let defaulted = candidates.model_group != target.group + && matches!( + crate::resolve::resolve_request( + &snapshot.registry, + &target.group, + request.specific_deployment, + crate::resolve::Caller { + team_id: request.team_id.as_deref(), + proxy_admin: request.proxy_admin, + allowed_models: &request.allowed_models, + wildcard_request: candidates.wildcard_request.as_deref(), + ..crate::resolve::Caller::default() + }, + None, + snapshot.settings.dynamic.default_ref(), + jiff::Timestamp::now(), + ), + Ok(None) + ); + let attempt = Attempt { + op: op.clone(), + request: request.clone(), + deployment: deployment.clone(), + name: target.group.clone(), + model_group: if defaulted { + target.group.clone() + } else { + candidates.model_group.clone() + }, + target_order: target.order, + candidate_ids: candidates.all.iter().map(|d| d.id.clone()).collect(), + retry, + fallback_depth: at.depth, + fallback_level: at.level, + timeout: snapshot.settings.timeout, + params: target.params.clone(), + scope: at.scope, + max_retries, + model_group_size: snapshot.registry.model_list_len(&target.group), + }; + // Every attempt runs through the host; the core records its outcome itself, as far as the + // request's `OutcomeCallbacks` reach, except a deferred stream's: its request counts now + // (`increment_deployment_usage_for_response`), its success or failure when the host reports + // the stream's end. + match self.host.invoke(&attempt).await { + Ok(output) => { + let tracks = output + .tracks_usage + .unwrap_or_else(|| deployment.tracks_usage()); + let recorded = match (output.deferred, tracks) { + (true, true) => { + let tokens = output.total_tokens as f64; + self.health.add_usage(&deployment, None, tokens, 1.0).await + } + (true, false) => Ok(()), + (false, _) => { + self.health + .record_success( + request.outcome_callbacks, + &deployment, + output.total_tokens, + tracks, + ) + .await + } + }; + if let Err(error) = recorded { + warn!(deployment_id = %deployment.id, error = %error, "usage was not recorded"); + } + self.host.observe(&RouterEvent::Succeeded { + deployment_id: deployment.id.clone(), + }); + // `_should_raise_content_policy_error`: a blocked response is raised only when + // a content-policy fallback would serve it, and counts as no failure. + let raised = + match output.blocked { + Some(Blocked::ContentFilter) => self + .has_content_policy_fallback(snapshot, request, target, at, attempted), + Some(Blocked::Refusal) => self + .refusal_fallback_available(snapshot, request, target, at, attempted), + None => false, + }; + if let Some(blocked) = output.blocked.filter(|_| raised) { + self.host.observe(&RouterEvent::Blocked { + level: at.level, + model: target.group.clone(), + blocked, + }); + let mut failure = + AttemptError::new(FailureKind::ContentPolicyViolation, Some(400)); + failure.classes = crate::retry::content_policy_classes(); + return Err(Failed { + error: Box::new(Error::Attempt(failure)), + deployment_id: Some(deployment.id.clone()), + }); + } + Ok(RouterResponse { + output, + deployment_id: deployment.id.clone(), + model_group: candidates.model_group, + attempted_retries: retry, + max_retries: None, + attempted_fallbacks: at.depth, + }) + } + Err(failure) => { + if !failure.recorded { + self.record_failure(snapshot, request, &candidates, &deployment, &failure) + .await; + } + Err(Failed { + error: Box::new(Error::Attempt(failure)), + deployment_id: Some(deployment.id.clone()), + }) + } + } + } + + /// The attempt's pick: the deployment and the candidates it was picked from. + #[allow(clippy::too_many_arguments)] + async fn picked( + &self, + snapshot: &RouterStateSnapshot, + op: &Op, + request: &Arc, + target: &Target, + inputs: &SelectInputs, + retry: u32, + at: FallbackHop, + ) -> Result<(Arc, Candidates), Failed> { + crate::routing_plugins::refuse_sync_pick( + snapshot.settings.routing_plugins, + &snapshot.settings.routing_strategy, + request, + )?; + let routed = self + .pre_routed(PreRoute { + op, + request, + name: &target.group, + fallback_depth: at.depth, + retry, + }) + .await?; + match routed { + PreRouted::Model(name) => { + snapshot.missing_routing_group(request, &name)?; + let candidates = self + .candidates(snapshot, op, request, &name, inputs) + .await?; + if candidates.healthy.is_empty() { + return Err(Error::NoHealthyDeployments { + model: candidates.failed_model(&snapshot.registry), + } + .into()); + } + let deployment = self.pick(snapshot, op, request, &candidates).await?; + Ok((deployment, candidates)) + } + // A custom strategy's pick is served as is, for the requested name. + PreRouted::Deployment(deployment) => { + let candidates = Candidates { + name: target.group.clone(), + model_group: target.group.clone(), + kind: ResolveKind::Group, + all: vec![deployment.clone()], + healthy: vec![deployment.clone()], + wildcard_request: None, + }; + Ok((deployment, candidates)) + } + } + } + + /// An attempt on a name that is no model group: the host serves it under that name, with no + /// deployment picked and no outcome recorded. + async fn unrouted_attempt( + &self, + snapshot: &RouterStateSnapshot, + op: &Op, + request: &Arc, + target: &Target, + (retry, max_retries): (u32, u32), + at: FallbackHop, + ) -> Result { + let deployment = + Arc::new(crate::registry::Deployment::unrouted(&target.group).map_err(Error::from)?); + let attempt = Attempt { + op: op.clone(), + request: request.clone(), + deployment, + name: target.group.clone(), + model_group: target.group.clone(), + target_order: target.order, + candidate_ids: Vec::new(), + retry, + fallback_depth: at.depth, + fallback_level: at.level, + timeout: snapshot.settings.timeout, + params: target.params.clone(), + scope: at.scope, + max_retries, + model_group_size: snapshot.registry.model_list_len(&target.group), + }; + match self.host.invoke(&attempt).await { + Ok(output) => Ok(RouterResponse { + output, + deployment_id: String::new(), + model_group: target.group.clone(), + attempted_retries: retry, + max_retries: None, + attempted_fallbacks: at.depth, + }), + Err(failure) => Err(Error::Attempt(failure).into()), + } + } + + /// `_has_content_policy_fallback`: the content-policy chain resolves for the level's + /// lookup groups and holds a target the chain has not tried; with no content-policy list, + /// any router `"*"` entry. + fn has_content_policy_fallback( + &self, + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + target: &Target, + at: FallbackHop, + attempted: &[Tried], + ) -> bool { + let lists = Lists::of(snapshot, request); + match lists.content_policy { + Some(list) => unattempted_chain(list, &lists, request, target, at, attempted), + None => snapshot.settings.dynamic.fallbacks.has_star(), + } + } + + /// `_refusal_fallback_available`: the content-policy list decides when there is one; + /// else a router `"*"` entry, else a generic chain with a target the chain has not tried. + fn refusal_fallback_available( + &self, + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + target: &Target, + at: FallbackHop, + attempted: &[Tried], + ) -> bool { + if request.disable_fallbacks { + return false; + } + let lists = Lists::of(snapshot, request); + if lists.content_policy.is_some() { + return self.has_content_policy_fallback(snapshot, request, target, at, attempted); + } + if snapshot.settings.dynamic.fallbacks.has_star() { + return true; + } + lists + .fallbacks + .is_some_and(|list| unattempted_chain(list, &lists, request, target, at, attempted)) + } + + /// `async_deployment_callback_on_failure`, when it runs for this failure. + async fn count_failed_request( + &self, + deployment: &crate::registry::Deployment, + failure: &AttemptError, + ) { + if failure.uncounted_request { + return; + } + if let Err(error) = self.health.count_failed_request(deployment, None).await { + warn!(deployment_id = %deployment.id, error = %error, "usage was not recorded"); + } + } + + async fn record_failure( + &self, + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + candidates: &Candidates, + deployment: &crate::registry::Deployment, + failure: &AttemptError, + ) { + self.host.observe(&RouterEvent::AttemptFailed { + deployment_id: deployment.id.clone(), + kind: failure.kind, + status: failure.status, + }); + let recorded = request.outcome_callbacks.record( + OutcomeWrite::Failure, + self.attempt_failure(snapshot, request, candidates, deployment, failure), + ); + if let Err(error) = recorded.await { + warn!(deployment_id = %deployment.id, error = %error, "cooldown was not recorded"); + } + } + + /// What the failure callbacks record for a failed attempt. + async fn attempt_failure( + &self, + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + candidates: &Candidates, + deployment: &crate::registry::Deployment, + failure: &AttemptError, + ) -> Result<(), Error> { + // The default deployment's copy is no configured deployment: Python's cooldown check finds + // no group for its id and records nothing, unless the id names a configured deployment, + // which then takes the failure. + let configured; + let deployment = if candidates.kind == ResolveKind::Default { + match snapshot.registry.deployment(&deployment.id) { + Some(found) => { + configured = found; + &*configured + } + None => { + self.count_failed_request(deployment, failure).await; + return Ok(()); + } + } + } else { + deployment + }; + let shape = GroupShape { + // The deployment's own group decides, also when the call named the deployment by id. + single_deployment: snapshot + .registry + .group(&deployment.model_name) + .map_or(candidates.all.len() == 1, |group| group.len() == 1) + // A routing group call with alternatives cools its member down so selection + // moves on (`routing_group_alternatives`). + && !(candidates.kind == ResolveKind::RoutingGroup && candidates.all.len() > 1) + // As does a team deployment with a sibling under its public name + // (`team_model_alternatives`). + && !team_model_has_alternatives(&snapshot.registry, deployment), + has_fallback_group: snapshot + .settings + .dynamic + .fallback_targets(&[candidates.model_group.as_str()]) + .is_some(), + }; + self.count_failed_request(deployment, failure).await; + match self + .health + .record_failure( + &snapshot.settings, + deployment, + shape, + request.cooldown_time, + failure, + ) + .await + { + Ok(Some(cooldown)) => self.host.observe(&RouterEvent::CooldownSet { + deployment_id: deployment.id.clone(), + cooldown, + }), + Ok(None) => {} + Err(error) => return Err(error), + } + Ok(()) + } +} diff --git a/litellm-rust/crates/router-core/src/call/stream.rs b/litellm-rust/crates/router-core/src/call/stream.rs new file mode 100644 index 00000000000..a0fce4372dd --- /dev/null +++ b/litellm-rust/crates/router-core/src/call/stream.rs @@ -0,0 +1,456 @@ +//! Recovering a stream that failed after its attempt returned it. The host wraps every streamed +//! response; when the stream fails before the caller received content, the wrapper asks the core +//! what may still take over and hands the failure back here. Mirrors the decisions of the Python +//! router's stream wrappers: `_stream_can_fall_back`, `_refusal_fallback_available`, +//! `_anthropic_messages_stream_can_retry`, `_stream_retry_budget`, `_astream_retry_same_group`, +//! and the `async_function_with_fallbacks_common_utils` re-entry of the mid-stream fallback. + +use std::sync::Arc; + +use serde::Deserialize; + +use super::{Failed, FallbackChain, FallbackHop, Lists, Target, Tried, group_members}; +use crate::{ + Router, RouterStateSnapshot, + config::Op, + error::{AttemptError, Error, FailureKind}, + fallback::FallbackTarget, + health::should_retry_status, + host::{RouterEvent, RouterRequest, UncountedRetries}, + select::{Candidates, SelectInputs}, +}; + +/// Where a streamed response came from: the attempt that returned it. +#[derive(Clone, Debug, Default, Deserialize)] +#[serde(default, deny_unknown_fields)] +pub struct StreamOrigin { + /// The name the attempt served: the requested group, or the fallback target. + pub group: String, + /// The `order` level an order fallback targeted. + pub order: Option, + /// `fallback_depth` of the attempt. + pub depth: u32, + pub level: u32, + /// The deployment the attempt ran on. + pub deployment_id: Option, + /// Same-group stream retries this request already spent (`attempted_retries_for_request`). + pub attempted_retries: u32, + /// The budget the first stream retry committed to (`committed_retry_budget_for_request`). + pub committed_budget: Option, +} + +/// What may still take over a stream that fails before content. +#[derive(Clone, Copy, Debug, Default, PartialEq, Eq)] +pub struct StreamPolicy { + /// `_anthropic_messages_stream_can_retry`. + pub can_retry: bool, + /// `_stream_can_fall_back`. + pub can_fall_back: bool, + /// `_refusal_fallback_available`. + pub refusal_fallback: bool, + /// `_stream_retry_budget` for the failure kind asked about: the budget, and whether a retry + /// policy governs the retry. + pub retry_budget: Option<(u32, bool)>, +} + +impl StreamOrigin { + fn target(&self) -> Target { + Target { + group: self.group.clone(), + order: self.order, + params: None, + excluded: Arc::from([]), + failover_excluded: Arc::from([]), + } + } + + /// `fallback_lookup_groups`: the served group, then the group the request was for. + fn lookup<'a>(&'a self, request: &'a RouterRequest) -> Vec<&'a str> { + let mut lookup = vec![self.group.as_str()]; + if request.model != self.group { + lookup.push(request.model.as_str()); + } + lookup + } + + /// `has_unattempted_fallback_target`. The first attempt carries no attempted targets, so any + /// resolved chain counts; a fallback hop has already tried its own group and the original one. + fn has_unattempted(&self, request: &RouterRequest, chain: Option>) -> bool { + let Some(chain) = chain else { + return false; + }; + if self.depth == 0 { + return true; + } + chain + .iter() + .any(|target| *target != self.group && *target != request.model) + } +} + +/// The group names a chain targets (a dict target counts by its `model`). +fn names(chain: Option>) -> Option> { + chain.map(|targets| { + targets + .iter() + .filter_map(|target| target.model().map(str::to_owned)) + .collect() + }) +} + +/// The `content_policy_fallbacks` chain for the lookup groups: the request's list where it +/// passed one, else the router's (`_has_content_policy_fallback`). +fn content_policy_targets(lists: &Lists<'_>, lookup: &[&str]) -> Option>> { + lists + .content_policy + .map(|list| names(list.lookup_groups(lookup, lists.keys))) +} + +/// The router's `default_fallbacks`, which Python folds into its `fallbacks` as `{"*": [...]}`: a +/// request's own list replaces them. +fn folded_defaults<'a>(snapshot: &'a RouterStateSnapshot, request: &RouterRequest) -> &'a [String] { + match request.fallbacks { + Some(_) => &[], + None => &snapshot.settings.dynamic.default_fallbacks, + } +} + +/// The regular fallback targets for the lookup groups, then the folded `default_fallbacks`. +fn regular_targets( + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + lists: &Lists<'_>, + lookup: &[&str], +) -> Option> { + let defaults = folded_defaults(snapshot, request); + names( + lists + .fallbacks + .and_then(|list| list.lookup_groups(lookup, lists.keys)), + ) + .or_else(|| (!defaults.is_empty()).then(|| defaults.to_vec())) +} + +/// `_has_default_fallbacks`: the router's list, whatever the request passed. +fn has_default_fallbacks(snapshot: &RouterStateSnapshot) -> bool { + let dynamic = &snapshot.settings.dynamic; + dynamic.fallbacks.has_star() || !dynamic.default_fallbacks.is_empty() +} + +impl Router { + /// What may still take over a stream from `origin` that fails before content, and the retry + /// budget for a failure of `kind`. + pub fn stream_policy( + &self, + request: &RouterRequest, + origin: &StreamOrigin, + kind: Option, + ) -> StreamPolicy { + let snapshot = self.core.snapshot.load_full(); + StreamPolicy { + can_retry: stream_can_retry(&snapshot, request, origin), + can_fall_back: stream_can_fall_back(&snapshot, request, origin), + refusal_fallback: refusal_fallback_available(&snapshot, request, origin), + retry_budget: kind.map(|kind| stream_retry_budget(&snapshot, request, origin, kind)), + } + } + + /// The fallback chain for a stream from `origin` that failed with `failure` before content: + /// `async_function_with_fallbacks_common_utils` re-entered from the stream wrapper, so the + /// group's own retry loop does not run again. + pub async fn fallback_stream( + &self, + op: Op, + request: RouterRequest, + origin: StreamOrigin, + failure: AttemptError, + ) -> Result { + self.live()?; + let snapshot = self.core.snapshot.load_full(); + let request = Arc::new(request); + let mut chain = FallbackChain::default(); + if request.model != origin.group { + chain + .attempted + .push(Tried::Target(FallbackTarget::Name(request.model.clone()))); + } + self.core + .fall_back( + &snapshot, + &op, + &request, + origin.target(), + FallbackHop { + depth: origin.depth, + level: origin.level, + scope: 0, + }, + &mut chain, + Failed::from(Error::Attempt(failure)), + ) + .await + } + + /// `_astream_retry_same_group`: re-run the attempt in the stream's own group until a retry + /// returns a response or the budget runs out. The failed result carries the newest failure. + pub async fn retry_stream( + &self, + op: Op, + request: RouterRequest, + origin: StreamOrigin, + failure: AttemptError, + ) -> Result { + self.live()?; + let snapshot = self.core.snapshot.load_full(); + let request = Arc::new(request); + let target = origin.target(); + let at = FallbackHop { + depth: origin.depth, + level: origin.level, + scope: 0, + }; + let counting = SelectInputs { + count_only: true, + ..SelectInputs::default() + }; + let counted = |c: &Candidates, n: usize| if c.kind.is_single() { 0 } else { n }; + let (healthy, all) = self + .core + .candidates(&snapshot, &op, &request, &target.group, &counting) + .await + .map(|c| (counted(&c, c.healthy.len()), counted(&c, c.all.len()))) + .unwrap_or((0, 0)); + let (budget, policy_applies) = + stream_retry_budget(&snapshot, &request, &origin, failure.kind); + let inputs = SelectInputs { + target_order: target.order, + requested: Some(target.group.clone()), + fallback_hop: at.level > 0, + ..SelectInputs::default() + }; + let mut last = failure; + for attempt in origin.attempted_retries..budget { + if last.agentic_followup { + break; + } + if !policy_applies + && !self + .core + .should_retry(&snapshot, &request, &last, healthy, all) + { + break; + } + let delay = self.core.time_to_sleep( + &snapshot, + last.retry_after, + budget - attempt, + budget, + healthy, + all, + ); + self.core.host.sleep(delay).await; + self.core.host.observe(&RouterEvent::Retry { + model_group: target.group.clone(), + retry: attempt + 1, + delay, + }); + match self + .core + .attempt( + &snapshot, + &op, + &request, + &target, + &inputs, + (attempt + 1, budget), + (at, &[]), + ) + .await + { + Ok(mut response) => { + response.attempted_retries = attempt + 1; + response.max_retries = Some(budget); + return Ok(response); + } + Err(failed) => match *failed.error { + // `_stream_fallback_error_for_raised`: a status the pre-stream retry rule + // would not retry ends the retries with that failure. + Error::Attempt(failure) => { + let stop = failure.status.is_some_and(|s| !should_retry_status(s)); + last = failure; + if stop { + break; + } + } + other => return Err(other), + }, + } + } + Err(Error::Attempt(last)) + } +} + +/// The request's `num_retries`, then the routed deployment's, then the router's +/// (`_anthropic_messages_plain_retry_budget`). +fn plain_retry_budget( + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + origin: &StreamOrigin, +) -> u32 { + if let Some(retries) = request.num_retries { + return retries; + } + if request.uncounted_retries == Some(UncountedRetries::Negative) { + return 0; + } + let deployment = origin + .deployment_id + .as_deref() + .and_then(|id| snapshot.registry.deployment(id)); + let configured = deployment.and_then(|d| match d.raw_params.get("num_retries") { + Some(serde_json::Value::Number(n)) => n.as_u64().and_then(|n| u32::try_from(n).ok()), + Some(serde_json::Value::String(s)) if s.chars().all(|c| c.is_ascii_digit()) => { + s.parse().ok() + } + _ => None, + }); + configured.unwrap_or(snapshot.settings.num_retries) +} + +/// The retry policy for the request's model group (`_anthropic_messages_resolved_retry_policy`), +/// unless the request opted out with `num_retries=0`. A policy that does not read as one governs +/// nothing here, with no fall through to the router's `retry_policy`. +fn retry_policy<'a>( + snapshot: &'a RouterStateSnapshot, + request: &'a RouterRequest, + origin: &StreamOrigin, +) -> Option<&'a crate::config::RetryPolicy> { + if request.num_retries == Some(0) || request.retry_policy_raises.contains(&origin.group) { + return None; + } + let settings = &snapshot.settings; + crate::retry::resolve_retry_policy( + settings.retry_policy.as_ref(), + &origin.group, + Some( + request + .model_group_retry_policy + .as_ref() + .unwrap_or(&settings.model_group_retry_policy), + ), + ) +} + +fn stream_retry_budget( + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + origin: &StreamOrigin, + kind: FailureKind, +) -> (u32, bool) { + let failure = AttemptError::new(kind, None); + let policy_retries = + retry_policy(snapshot, request, origin).and_then(|p| p.retries_for(&failure)); + if origin.attempted_retries > 0 + && let Some(committed) = origin.committed_budget + { + return (committed, policy_retries.is_some()); + } + match policy_retries { + Some(retries) => (retries, true), + None => (plain_retry_budget(snapshot, request, origin), false), + } +} + +fn stream_can_retry( + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + origin: &StreamOrigin, +) -> bool { + let attempted = origin.attempted_retries; + if attempted > 0 + && let Some(committed) = origin.committed_budget + { + return committed > attempted; + } + let plain = plain_retry_budget(snapshot, request, origin); + // `_retry_policy_ceiling`: every field the policy dumps. + let ceiling = retry_policy(snapshot, request, origin).map_or(plain, |policy| { + let granted = [ + policy.BadRequestErrorRetries, + policy.AuthenticationErrorRetries, + policy.TimeoutErrorRetries, + policy.RateLimitErrorRetries, + policy.ContentPolicyViolationErrorRetries, + policy.InternalServerErrorRetries, + policy.ServiceUnavailableErrorRetries, + policy.NotFoundErrorRetries, + policy.DefaultRetries, + ]; + plain.max(granted.into_iter().flatten().max().unwrap_or(0)) + }); + ceiling > attempted +} + +fn stream_can_fall_back( + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + origin: &StreamOrigin, +) -> bool { + if request.disable_fallbacks { + return false; + } + if snapshot.settings.enable_weighted_failover { + return true; + } + // `_stream_order_levels`, the levels the fallback walk sees for the group. + let listing_team = request.listing_team_id.as_deref(); + let mut orders: Vec = group_members(snapshot, &origin.group, listing_team) + .iter() + .filter(|d| d.listed_for_team(listing_team)) + .filter_map(|d| d.order()) + .collect(); + orders.sort_unstable(); + orders.dedup(); + if orders.len() > 1 { + let current = origin.order.unwrap_or(orders[0]); + if orders.iter().any(|order| *order > current) { + return true; + } + } + let lists = Lists::of(snapshot, request); + let lookup = origin.lookup(request); + if let Some(chain) = content_policy_targets(&lists, &lookup) + && origin.has_unattempted(request, chain) + { + return true; + } + if !lists.has_regular() && folded_defaults(snapshot, request).is_empty() { + return false; + } + if lists + .fallbacks + .is_some_and(|list| list.is_client_side(lists.keys)) + { + return true; + } + origin.has_unattempted(request, regular_targets(snapshot, request, &lists, &lookup)) +} + +fn refusal_fallback_available( + snapshot: &RouterStateSnapshot, + request: &RouterRequest, + origin: &StreamOrigin, +) -> bool { + if request.disable_fallbacks { + return false; + } + let lists = Lists::of(snapshot, request); + let lookup = origin.lookup(request); + if let Some(chain) = content_policy_targets(&lists, &lookup) { + return origin.has_unattempted(request, chain); + } + if has_default_fallbacks(snapshot) { + return true; + } + origin.has_unattempted(request, regular_targets(snapshot, request, &lists, &lookup)) +} diff --git a/litellm-rust/crates/router-core/src/config.rs b/litellm-rust/crates/router-core/src/config.rs new file mode 100644 index 00000000000..fb9b7af215f --- /dev/null +++ b/litellm-rust/crates/router-core/src/config.rs @@ -0,0 +1,355 @@ +//! What the router is told: [`RouterConfig`], fixed for the router's life, and +//! [`RouterDynamicConfig`], a versioned snapshot read once per call. The router never reads +//! process globals. + +use std::{collections::BTreeMap, time::Duration}; + +use serde::Deserialize; + +use crate::{ + error::AttemptError, + registry::{DeploymentSpec, RoutingGroupSpec}, +}; + +/// `DEFAULT_COOLDOWN_TIME_SECONDS` in `litellm/constants.py`. +pub const DEFAULT_COOLDOWN_TIME: Duration = Duration::from_secs(5); +/// `ROUTER_MAX_FALLBACKS` in `litellm/constants.py`. +pub const DEFAULT_MAX_FALLBACKS: u32 = 5; + +/// The router operation a call runs: the Python router's endpoint method name (`acompletion`, +/// `aembedding`, ...). The core runs every op alike; what differs per endpoint is the host's. +#[derive(Clone, Debug, PartialEq, Eq, Hash, Deserialize)] +#[serde(transparent)] +pub struct Op(String); + +impl Op { + pub fn new(name: impl Into) -> Self { + Self(name.into()) + } + + pub fn as_str(&self) -> &str { + &self.0 + } +} + +impl From<&str> for Op { + fn from(name: &str) -> Self { + Self::new(name) + } +} + +impl std::fmt::Display for Op { + fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { + f.write_str(&self.0) + } +} + +/// `routing_strategy`. Only simple-shuffle is native; the rest go through `Host::select`. +#[derive( + Clone, + Debug, + Default, + PartialEq, + Eq, + strum::EnumString, + strum::Display, + serde_with::DeserializeFromStr, +)] +pub enum RoutingStrategy { + #[default] + #[strum(serialize = "simple-shuffle")] + SimpleShuffle, + #[strum(serialize = "least-busy")] + LeastBusy, + #[strum(serialize = "usage-based-routing")] + UsageBased, + #[strum(serialize = "usage-based-routing-v2")] + UsageBasedV2, + #[strum(serialize = "latency-based-routing")] + LatencyBased, + #[strum(serialize = "cost-based-routing")] + CostBased, + /// `routing_strategy=None` passed explicitly (sent as `"None"`): stored as None, so no + /// strategy arm matches and every pick finds no deployment. + #[strum(serialize = "None")] + Unset, + #[strum(default, transparent)] + Other(String), +} + +impl RoutingStrategy { + pub fn is_native(&self) -> bool { + matches!(self, Self::SimpleShuffle | Self::Unset) + } +} + +/// `PluginKind` in `litellm/router_api.py`. +#[derive(Clone, Copy, Debug, PartialEq, Eq, Deserialize, strum::Display)] +pub enum PluginKind { + #[serde(rename = "auto")] + #[strum(serialize = "auto")] + Auto, + #[serde(rename = "complexity")] + #[strum(serialize = "complexity")] + Complexity, + #[serde(rename = "quality")] + #[strum(serialize = "quality")] + Quality, + #[serde(rename = "adaptive")] + #[strum(serialize = "adaptive")] + Adaptive, + #[serde(rename = "routing")] + #[strum(serialize = "routing")] + Routing, + #[serde(rename = "budget_limiter")] + #[strum(serialize = "budget_limiter")] + BudgetLimiter, + #[serde(rename = "prompt_caching_pins")] + #[strum(serialize = "prompt_caching_pins")] + PromptCachingPins, +} + +/// One registered plugin. Its behaviour lives in the host until it is ported. +#[derive(Clone, Debug, PartialEq, Deserialize)] +pub struct PluginSpec { + pub kind: PluginKind, + pub name: String, + #[serde(default)] + pub config: serde_json::Value, +} + +/// `RetryPolicy` in `litellm/types/router.py`: retries per exception type. +#[derive(Clone, Debug, Default, PartialEq, Deserialize)] +#[allow(non_snake_case)] +pub struct RetryPolicy { + pub BadRequestErrorRetries: Option, + pub AuthenticationErrorRetries: Option, + pub TimeoutErrorRetries: Option, + pub RateLimitErrorRetries: Option, + pub ContentPolicyViolationErrorRetries: Option, + pub InternalServerErrorRetries: Option, + pub ServiceUnavailableErrorRetries: Option, + pub NotFoundErrorRetries: Option, + pub DefaultRetries: Option, +} + +/// `AllowedFailsPolicy` in `litellm/types/router.py`: allowed fails per minute per exception type. +#[derive(Clone, Debug, Default, PartialEq, Deserialize)] +#[allow(non_snake_case)] +pub struct AllowedFailsPolicy { + pub BadRequestErrorAllowedFails: Option, + pub AuthenticationErrorAllowedFails: Option, + pub TimeoutErrorAllowedFails: Option, + pub RateLimitErrorAllowedFails: Option, + pub ContentPolicyViolationErrorAllowedFails: Option, + pub InternalServerErrorAllowedFails: Option, + pub ServiceUnavailableErrorAllowedFails: Option, + pub BadGatewayErrorAllowedFails: Option, + pub NotFoundErrorAllowedFails: Option, +} + +impl AllowedFailsPolicy { + /// `_core_get_allowed_fails_from_policy`: the first set field whose exception class the + /// failure is an instance of, in Python's order. + pub fn allowed_fails_for(&self, failure: &AttemptError) -> Option { + [ + ("AuthenticationError", self.AuthenticationErrorAllowedFails), + ("Timeout", self.TimeoutErrorAllowedFails), + ("RateLimitError", self.RateLimitErrorAllowedFails), + ( + "ContentPolicyViolationError", + self.ContentPolicyViolationErrorAllowedFails, + ), + ("BadRequestError", self.BadRequestErrorAllowedFails), + ("InternalServerError", self.InternalServerErrorAllowedFails), + ( + "ServiceUnavailableError", + self.ServiceUnavailableErrorAllowedFails, + ), + ("BadGatewayError", self.BadGatewayErrorAllowedFails), + ("NotFoundError", self.NotFoundErrorAllowedFails), + ] + .into_iter() + .find_map(|(class, allowed)| allowed.filter(|_| failure.is_a(class))) + } +} + +pub use crate::fallback::{FallbackKeys, Fallbacks}; + +/// Static config, fixed for the router's life. +#[derive(Clone, Debug, Default, Deserialize)] +#[serde(default)] +pub struct RouterConfig { + pub model_list: Vec, + pub routing_strategy: RoutingStrategy, + pub routing_groups: Vec, + /// `_model_to_group` as Python last built it (member model group to routing group), set + /// only when a raw `routing_groups` write replaced the groups since: member calls keep + /// routing by it, as the Python router's stale map does. + pub routing_group_members: Option>, + pub plugins: Vec, + /// Router default `cooldown_time`; `None` is `DEFAULT_COOLDOWN_TIME_SECONDS`. + pub cooldown_time: Option, + pub disable_cooldowns: bool, + pub allowed_fails_policy: Option, + pub retry_policy: Option, + /// `model_group_retry_policy`: a group's own policy, which wins over `retry_policy`. + pub model_group_retry_policy: BTreeMap, + /// `retry_after`: the minimum backoff between retries, in seconds. + pub retry_after: f64, + pub timeout: Option, + pub request_timeout: Option, + pub drop_params: Option, + pub enable_pre_call_checks: bool, + /// `Router(plugins=[...])` is set: the host runs the routing-plugin pipeline. + pub routing_plugins: bool, + /// The host's `CustomLogger` deployment filters run on every async candidate list + /// (`async_callback_filter_deployments`). + pub callback_filters: bool, + pub enable_health_check_routing: bool, + /// How old (seconds) a background health check result may be and still count + /// (`health_check_staleness_threshold`, else the default interval times its multiplier). + pub health_check_staleness_threshold: Option, + /// `background_health_check_model_groups`: when set, only these groups are health-filtered. + pub background_health_check_model_groups: Option>, + /// `enable_weighted_failover`: a failed deployment's group is re-picked without it before + /// any cross-group fallback (simple-shuffle only). + pub enable_weighted_failover: bool, + /// `fallback_on_unsupported_params`; `None` is Python's default, `True`. + pub fallback_on_unsupported_params: Option, + /// Deployment ids that are a provider's default and never cool down + /// (`provider_default_deployment_ids`). + pub provider_default_deployment_ids: Vec, + /// The operations this router must serve: `Host::supports` must accept each one for every + /// configured provider, or the router fails to build. + pub served_ops: Vec, +} + +/// Dynamic config: a versioned snapshot read once per call. +#[derive(Clone, Debug, Deserialize)] +#[serde(default)] +pub struct RouterDynamicConfig { + pub version: u64, + /// `model_group_alias` as Python spells it: each alias maps to a group name, or to + /// `{"model": , "hidden": }`. + #[serde(alias = "model_group_alias", deserialize_with = "alias_targets")] + pub model_alias_map: BTreeMap, + pub fallbacks: Fallbacks, + pub default_fallbacks: Vec, + pub context_window_fallbacks: Option, + pub content_policy_fallbacks: Option, + pub num_retries: Option, + pub max_fallbacks: u32, + /// `allowed_fails`, as the router copied it when it was built. + pub allowed_fails: Option, + /// `allowed_fails` is only the process default: it was not passed to the router and still + /// equals `litellm.allowed_fails`. Anything else switches cooldowns from the failure-ratio + /// rule to the allowed-fails counter (`_is_allowed_fails_set_on_router`). + pub allowed_fails_is_default: bool, + /// Other spellings a fallback key matches. + pub fallback_keys: FallbackKeys, + /// `default_deployment`: what a name no deployment, alias, routing group, team route or + /// wildcard serves is routed to, as a copy whose `litellm_params.model` is the name + /// (`_try_early_resolve_deployments_for_model_not_in_names`). + pub default_deployment: Option, + /// The `default_deployment` is a value Python cannot copy for a name: resolving to it + /// raises the copy's error ([`crate::Error::DefaultDeploymentRaises`]). + pub default_deployment_raises: bool, +} + +/// `model_group_alias` as `resolve_model_group_alias` reads it: an alias maps to a non-empty +/// group name, or to `{"model": , ...}`; any other value rewrites nothing. +fn alias_targets<'de, D>(deserializer: D) -> Result, D::Error> +where + D: serde::Deserializer<'de>, +{ + let aliases = BTreeMap::::deserialize(deserializer)?; + Ok(aliases + .into_iter() + .filter_map(|(alias, target)| { + let group = match &target { + serde_json::Value::Object(entry) => entry.get("model")?, + other => other, + }; + group + .as_str() + .filter(|group| !group.is_empty()) + .map(|group| (alias, group.to_owned())) + }) + .collect()) +} + +impl Default for RouterDynamicConfig { + fn default() -> Self { + Self { + version: 0, + model_alias_map: BTreeMap::new(), + fallbacks: Fallbacks::default(), + default_fallbacks: Vec::new(), + context_window_fallbacks: None, + content_policy_fallbacks: None, + num_retries: None, + max_fallbacks: DEFAULT_MAX_FALLBACKS, + allowed_fails: None, + allowed_fails_is_default: false, + fallback_keys: FallbackKeys::default(), + default_deployment: None, + default_deployment_raises: false, + } + } +} + +impl RouterDynamicConfig { + /// The `default_deployment` as resolution serves it. + pub fn default_ref(&self) -> Option> { + if self.default_deployment_raises { + return Some(crate::resolve::DefaultDeployment::Raises); + } + self.default_deployment + .as_ref() + .map(crate::resolve::DefaultDeployment::Spec) + } + + /// The regular fallback targets for the lookup groups, then `default_fallbacks`, which + /// Python folds into `fallbacks` as `{"*": [...]}`: what `_has_fallback_group` reads. + pub fn fallback_targets(&self, groups: &[&str]) -> Option> { + if groups + .iter() + .any(|group| self.fallbacks.has_keyed_chain(group, &self.fallback_keys)) + { + return Some(Vec::new()); + } + (!self.default_fallbacks.is_empty()).then(|| self.default_fallbacks.clone()) + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + #[rstest] + #[case::group_name(json!({"model_group_alias": {"gpt": "gpt-4"}}))] + #[case::hidden_entry(json!({"model_group_alias": {"gpt": {"model": "gpt-4", "hidden": true}}}))] + #[case::native_name(json!({"model_alias_map": {"gpt": "gpt-4"}}))] + fn model_group_alias_reads_both_python_spellings(#[case] wire: serde_json::Value) { + let dynamic: RouterDynamicConfig = serde_json::from_value(wire).unwrap(); + assert_eq!( + dynamic.model_alias_map, + BTreeMap::from([("gpt".to_owned(), "gpt-4".to_owned())]) + ); + } + + #[rstest] + #[case::native("simple-shuffle", RoutingStrategy::SimpleShuffle)] + #[case::unknown("my-strategy", RoutingStrategy::Other("my-strategy".to_owned()))] + fn routing_strategy_parses_its_wire_name( + #[case] wire: &str, + #[case] expected: RoutingStrategy, + ) { + assert_eq!(wire.parse::().unwrap(), expected); + assert_eq!(expected.to_string(), wire); + } +} diff --git a/litellm-rust/crates/router-core/src/eligibility.rs b/litellm-rust/crates/router-core/src/eligibility.rs new file mode 100644 index 00000000000..5cedf218b9a --- /dev/null +++ b/litellm-rust/crates/router-core/src/eligibility.rs @@ -0,0 +1,240 @@ +//! Which deployments may serve a request's endpoint: a port of +//! `litellm/router_utils/endpoint_eligibility.py`. A deployment that sets +//! `enforce_supported_endpoints` and lists none of the chat-shaped endpoints serves none of them; +//! the host names the endpoint for the calls `endpoint_selection` wraps. + +use std::{collections::BTreeSet, sync::Arc}; + +use serde_json::{Map, Value}; + +use crate::{error::Error, registry::Deployment, resolve::Caller}; + +/// `CHAT_ENDPOINTS`: `_endpoint_path` of each value of `CHAT_ENDPOINT_BY_CALL`. +const CHAT_ENDPOINTS: [&str; 8] = [ + "/chat/completions", + "/completions", + "/messages", + "/responses", + "/generatecontent", + "/streamgeneratecontent", + "/interactions", + "/responses/compact", +]; + +/// `_endpoint_path`. +fn endpoint_path(endpoint: &str) -> String { + let rooted = format!("/{}", endpoint.trim().trim_matches('/').to_lowercase()); + let path = rooted.strip_prefix("/openai").unwrap_or(&rooted); + let path = path.strip_prefix("/v1beta").unwrap_or(path); + let path = path.strip_prefix("/v1").unwrap_or(path); + match path.rsplit_once(':') { + Some((_, action)) => format!("/{action}"), + None => path.to_owned(), + } +} + +/// The flag as pydantic's lax `bool | None` reads it: `None` for a value it refuses, which fails +/// the whole declaration. +fn enforce_flag(value: Option<&Value>) -> Option { + match value { + None | Some(Value::Null) => Some(false), + Some(Value::Bool(flag)) => Some(*flag), + Some(Value::Number(number)) => match number.as_f64() { + Some(0.0) => Some(false), + Some(1.0) => Some(true), + _ => None, + }, + Some(Value::String(text)) => match text.to_lowercase().as_str() { + "0" | "off" | "f" | "false" | "n" | "no" => Some(false), + "1" | "on" | "t" | "true" | "y" | "yes" => Some(true), + _ => None, + }, + Some(_) => None, + } +} + +/// `_enforced_endpoints`: the declared endpoints of a deployment that enforces them. One endpoint +/// may be written as a string; a declaration that does not validate enforces nothing. +fn enforced_endpoints(model_info: &Map) -> Option> { + if !enforce_flag(model_info.get("enforce_supported_endpoints"))? { + return None; + } + match model_info.get("supported_endpoints")? { + Value::String(endpoint) => Some(vec![endpoint.clone()]), + Value::Array(endpoints) => endpoints + .iter() + .map(|endpoint| endpoint.as_str().map(str::to_owned)) + .collect(), + _ => None, + } +} + +/// `non_chat_endpoints`: what a deployment serves when it serves no chat-shaped endpoint, else +/// `None`. +fn non_chat_endpoints(deployment: &Deployment) -> Option> { + let declared = enforced_endpoints(&deployment.model_info.raw)?; + let chat = declared + .iter() + .any(|endpoint| CHAT_ENDPOINTS.contains(&endpoint_path(endpoint).as_str())); + (!chat).then(|| declared.into_iter().collect()) +} + +/// `eligible_deployments`: the deployments that may serve the caller's endpoint. When none may, +/// the refusal names what they do serve. +pub(crate) fn eligible_deployments( + model: &str, + caller: Caller<'_>, + deployments: Vec>, +) -> Result>, Error> { + let Some(endpoint) = caller.endpoint.filter(|_| !deployments.is_empty()) else { + return Ok(deployments); + }; + let declared: Vec>> = deployments + .iter() + .map(|deployment| non_chat_endpoints(deployment)) + .collect(); + let eligible: Vec> = deployments + .into_iter() + .zip(&declared) + .filter(|(_, endpoints)| endpoints.is_none()) + .map(|(deployment, _)| deployment) + .collect(); + if !eligible.is_empty() { + return Ok(eligible); + } + let supported: BTreeSet = declared.into_iter().flatten().flatten().collect(); + let supported = if supported.is_empty() { + "none".to_owned() + } else { + Vec::from_iter(supported).join(", ") + }; + let requested = if caller.requested.is_empty() { + model + } else { + caller.requested + }; + Err(Error::EndpointNotSupported { + model: model.to_owned(), + message: format!( + "{endpoint} is not supported by model={requested}. Supported endpoints: {supported}" + ), + }) +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + use crate::registry::DeploymentSpec; + + fn deployment(id: &str, info: Value) -> Arc { + let mut model_info = info; + model_info["id"] = json!(id); + let spec: DeploymentSpec = serde_json::from_value(json!({ + "model_name": "g", "litellm_params": {"model": "openai/a"}, "model_info": model_info, + })) + .unwrap(); + Arc::new(Deployment::from_spec(spec).unwrap()) + } + + fn chat<'a>() -> Caller<'a> { + Caller { + endpoint: Some("/v1/chat/completions"), + requested: "g", + ..Caller::default() + } + } + + #[rstest] + #[case::v1_prefix("/v1/chat/completions", "/chat/completions")] + #[case::openai_prefix("/openai/v1/responses/", "/responses")] + #[case::bare_gemini_action("generateContent", "/generatecontent")] + #[case::beta_prefix("/v1beta/interactions", "/interactions")] + #[case::gemini_model_path( + "/v1beta/models/gemini:streamGenerateContent", + "/streamgeneratecontent" + )] + fn endpoint_paths_normalize(#[case] endpoint: &str, #[case] expected: &str) { + assert_eq!(endpoint_path(endpoint), expected); + } + + #[rstest] + #[case::embeddings_only( + json!({"enforce_supported_endpoints": true, "supported_endpoints": ["/v1/embeddings"]}), + false + )] + #[case::one_endpoint_as_a_string( + json!({"enforce_supported_endpoints": true, "supported_endpoints": "/v1/embeddings"}), + false + )] + #[case::string_flag( + json!({"enforce_supported_endpoints": "yes", "supported_endpoints": ["/v1/embeddings"]}), + false + )] + #[case::an_empty_list_serves_nothing( + json!({"enforce_supported_endpoints": true, "supported_endpoints": []}), + false + )] + #[case::any_chat_shaped_endpoint_serves_every_one( + json!({"enforce_supported_endpoints": true, "supported_endpoints": ["/v1/responses"]}), + true + )] + #[case::not_enforced( + json!({"enforce_supported_endpoints": false, "supported_endpoints": ["/v1/embeddings"]}), + true + )] + #[case::unset_flag(json!({"supported_endpoints": ["/v1/embeddings"]}), true)] + #[case::enforced_without_a_list(json!({"enforce_supported_endpoints": true}), true)] + #[case::an_invalid_flag_enforces_nothing( + json!({"enforce_supported_endpoints": "maybe", "supported_endpoints": ["/v1/embeddings"]}), + true + )] + #[case::an_invalid_list_enforces_nothing( + json!({"enforce_supported_endpoints": true, "supported_endpoints": [1]}), + true + )] + fn a_declaration_keeps_or_drops_a_deployment(#[case] info: Value, #[case] kept: bool) { + let open = deployment("open", json!({})); + let declared = deployment("declared", info); + let eligible = eligible_deployments("g", chat(), vec![declared, open]).unwrap(); + assert_eq!(eligible.len(), if kept { 2 } else { 1 }); + } + + #[test] + fn no_endpoint_keeps_everything() { + let declared = deployment( + "d", + json!({"enforce_supported_endpoints": true, "supported_endpoints": []}), + ); + let eligible = eligible_deployments("g", Caller::default(), vec![declared]).unwrap(); + assert_eq!(eligible.len(), 1); + } + + #[rstest] + #[case::lists_what_they_serve( + json!(["/v1/rerank", "/v1/embeddings"]), + "/v1/chat/completions is not supported by model=g. \ + Supported endpoints: /v1/embeddings, /v1/rerank" + )] + #[case::nothing_declared( + json!([]), + "/v1/chat/completions is not supported by model=g. Supported endpoints: none" + )] + fn every_deployment_refusing_names_the_endpoint( + #[case] endpoints: Value, + #[case] expected: &str, + ) { + let declared = deployment( + "d", + json!({"enforce_supported_endpoints": true, "supported_endpoints": endpoints}), + ); + let refused = eligible_deployments("resolved", chat(), vec![declared]); + assert!(matches!( + refused, + Err(Error::EndpointNotSupported { model, message }) + if model == "resolved" && message == expected + )); + } +} diff --git a/litellm-rust/crates/router-core/src/error.rs b/litellm-rust/crates/router-core/src/error.rs new file mode 100644 index 00000000000..b4112501c36 --- /dev/null +++ b/litellm-rust/crates/router-core/src/error.rs @@ -0,0 +1,473 @@ +//! The router's errors: [`ConfigError`] when a router is built or changed, [`Error`] when a call +//! or a selection fails, and [`AttemptError`], the typed facts of one failed attempt. + +use std::{any::Any, fmt, sync::Arc, time::Duration}; + +use crate::config::{Op, RoutingStrategy}; + +/// What a host cannot serve, found when the router is built rather than partway through a call. +#[derive(Clone, Debug, PartialEq, thiserror::Error)] +pub enum Unsupported { + #[error("routing strategy `{0}` needs a host that can select")] + Strategy(RoutingStrategy), + #[error("routing plugin `{0}` needs a host that can select")] + Plugin(String), + #[error("the host cannot run operation `{op}` on provider `{provider}`")] + Op { op: Op, provider: String }, +} + +#[derive(Debug, thiserror::Error)] +pub enum ConfigError { + #[error("the router config asks for something this host cannot serve")] + Unsupported(#[from] Unsupported), + #[error("deployment `{model_name}` has invalid litellm_params")] + InvalidDeployment { + model_name: String, + #[source] + source: serde_json::Error, + }, + #[error("deployment id `{id}` is configured more than once")] + DuplicateId { id: String }, + /// A removal the host's indexes could not finish ([`crate::host_index::RemovalError`]). + #[error("{0}")] + Removal(String), +} + +#[derive(Debug, thiserror::Error)] +pub enum Error { + #[error("the router config is invalid")] + Config(#[from] ConfigError), + #[error("no deployment serves model `{model}`")] + UnknownModel { model: String }, + #[error("no deployment of `{model}` is available")] + NoHealthyDeployments { model: String }, + #[error("the attempt failed")] + Attempt(#[from] AttemptError), + #[error("the routing cache failed")] + Cache(#[from] litellm_cache::Error), + #[error("the router was retired")] + Retired, + /// A blocked deployment named by its id (`model` is its litellm model). + #[error("deployment model `{model}` is paused")] + Paused { model: String }, + /// A pass-through pick named a deployment id without `use_in_pass_through`. + #[error("deployment `{id}` does not support pass-through")] + NotPassThrough { id: String }, + /// A pass-through pick of a group with healthy deployments, none of them pass-through. + #[error("model `{model}` has no pass-through deployment")] + NoPassThroughDeployments { model: String }, + /// Every deployment `model` resolved to is a pre-routing strategy marker (`auto_router/...`). + #[error("every deployment of `{model}` is a strategy router marker")] + OnlyMarkers { model: String }, + /// Every deployment `model` resolved to refuses the request's endpoint + /// (`eligible_deployments`); `message` names what they serve. + #[error("{message}")] + EndpointNotSupported { model: String, message: String }, + /// Every deployment `model` resolved to is split into PTU shares the caller holds none of. + #[error("deployment `{model}` is reserved for the teams holding a PTU share of it")] + PtuReserved { model: String }, + /// A proxy admin without a team named a public model name several teams use. + #[error("model name `{model}` matches deployments from multiple teams")] + MultipleTeams { model: String }, + /// Every deployment `model` resolved to is reserved for other teams by an active access + /// window, the first of which ends at `until` (`HH:MM`) in `timezone`. + #[error("deployment `{model}` is reserved for another team until {until} {timezone}")] + Reserved { + model: String, + until: String, + timezone: String, + }, + /// The pre-call checks found no deployment whose context window fits the prompt; `detail` + /// names each one dropped for it. + #[error("no deployment of `{model}` has a context window large enough for this call")] + ContextWindowExceeded { model: String, detail: String }, + /// The pre-call checks found no deployment of `model` that takes the requested `params`. + #[error("no deployment of `{model}` supports {params:?}")] + UnsupportedParams { model: String, params: Vec }, + /// The routing plugins left none of the healthy deployments' models. + #[error("no deployments left after routing-plugin filtering: {models:?}")] + RoutingPluginsLeftNothing { models: Vec }, + /// The request's `_router_weights` failed `validate_router_weights` when simple-shuffle picked. + #[error("the request's router weights are invalid")] + InvalidRouterWeights, + /// A deployment's `litellm_params` `metric` (weight, rpm or tpm) is not a number. + #[error("deployment {metric} must be numeric")] + NonNumericWeight { metric: &'static str }, + /// A router with routing plugins was asked for a pick on the sync path, which never runs them. + #[error("routing plugins only run on the async selection path")] + RoutingPluginsNeedAsync, + /// The stale routing-group member map (`_model_to_group`, kept as it was when a raw + /// `routing_groups` write replaced the groups) names a group that is no longer configured: + /// Python's `_get_routing_context` raises `KeyError(group)` for every pick of the name. + #[error("routing group `{group}` is no longer configured")] + MissingRoutingGroup { group: String }, + /// The router's `default_deployment` is not a value Python can copy for `model` + /// (`_try_early_resolve_deployments_for_model_not_in_names` raises the copy's error). + #[error("the default deployment cannot be served for `{model}`")] + DefaultDeploymentRaises { model: String }, + /// A written model-name or team index names a position past the end of the model list: + /// Python's lookup of `model` raises `IndexError`. + #[error("a written index of `{model}` names a position past the model list")] + IndexOutOfRange { model: String }, + /// A model-info query raised where the Python router raises: `exception` names the Python + /// exception class (`KeyError`, `TypeError`, `AttributeError`, `ValueError`) and `detail` its + /// argument. + #[error("the model-info query raised {exception}({detail:?})")] + ModelInfo { + exception: &'static str, + detail: String, + }, +} + +impl Error { + /// The failed attempt behind this error, when a deployment was called. + pub fn attempt(&self) -> Option<&AttemptError> { + match self { + Self::Attempt(attempt) => Some(attempt), + Self::Config(_) + | Self::UnknownModel { .. } + | Self::NoHealthyDeployments { .. } + | Self::Cache(_) + | Self::Retired + | Self::Paused { .. } + | Self::NotPassThrough { .. } + | Self::NoPassThroughDeployments { .. } + | Self::OnlyMarkers { .. } + | Self::EndpointNotSupported { .. } + | Self::PtuReserved { .. } + | Self::MultipleTeams { .. } + | Self::Reserved { .. } + | Self::ContextWindowExceeded { .. } + | Self::UnsupportedParams { .. } + | Self::RoutingPluginsLeftNothing { .. } + | Self::InvalidRouterWeights + | Self::NonNumericWeight { .. } + | Self::RoutingPluginsNeedAsync + | Self::MissingRoutingGroup { .. } + | Self::DefaultDeploymentRaises { .. } + | Self::IndexOutOfRange { .. } + | Self::ModelInfo { .. } => None, + } + } + + /// The Python exception a pick that failed with this error raises, as the retry loop + /// decides by it (its class names, most specific first, and its status): `None` for an + /// attempt's failure and for errors no pick raises. + pub fn pick_failure(&self) -> Option { + const BAD_REQUEST: &[&str] = &["BadRequestError"]; + let (classes, status): (&[&str], Option) = match self { + Self::UnknownModel { .. } + | Self::OnlyMarkers { .. } + | Self::PtuReserved { .. } + | Self::NotPassThrough { .. } + | Self::NoPassThroughDeployments { .. } + | Self::MultipleTeams { .. } + | Self::Reserved { .. } => (BAD_REQUEST, Some(400)), + Self::EndpointNotSupported { .. } => ( + &["EndpointNotSupportedByModelError", "BadRequestError"], + Some(400), + ), + Self::ContextWindowExceeded { .. } => ( + &["ContextWindowExceededError", "BadRequestError"], + Some(400), + ), + Self::UnsupportedParams { .. } => { + (&["UnsupportedParamsError", "BadRequestError"], Some(400)) + } + Self::Paused { .. } => (&["ServiceUnavailableError"], Some(503)), + Self::NoHealthyDeployments { .. } => (&["RouterRateLimitError", "ValueError"], None), + Self::RoutingPluginsLeftNothing { .. } | Self::RoutingPluginsNeedAsync => { + (&["ValueError"], None) + } + Self::InvalidRouterWeights => (&["ValidationError", "ValueError"], None), + Self::NonNumericWeight { .. } => (&["TypeError"], None), + Self::MissingRoutingGroup { .. } => (&["KeyError", "LookupError"], None), + Self::IndexOutOfRange { .. } => (&["IndexError", "LookupError"], None), + Self::DefaultDeploymentRaises { .. } => (&["Exception"], None), + Self::Attempt(_) + | Self::Config(_) + | Self::Cache(_) + | Self::Retired + | Self::ModelInfo { .. } => return None, + }; + let mut failure = AttemptError::host_raised(classes); + failure.status = status; + Some(failure) + } + + /// A copy of a pick's error, for the events that name it; `None` for any other error. + pub fn pick_copy(&self) -> Option { + Some(match self { + Self::UnknownModel { model } => Self::UnknownModel { + model: model.clone(), + }, + Self::NoHealthyDeployments { model } => Self::NoHealthyDeployments { + model: model.clone(), + }, + Self::Paused { model } => Self::Paused { + model: model.clone(), + }, + Self::NotPassThrough { id } => Self::NotPassThrough { id: id.clone() }, + Self::NoPassThroughDeployments { model } => Self::NoPassThroughDeployments { + model: model.clone(), + }, + Self::OnlyMarkers { model } => Self::OnlyMarkers { + model: model.clone(), + }, + Self::EndpointNotSupported { model, message } => Self::EndpointNotSupported { + model: model.clone(), + message: message.clone(), + }, + Self::PtuReserved { model } => Self::PtuReserved { + model: model.clone(), + }, + Self::MultipleTeams { model } => Self::MultipleTeams { + model: model.clone(), + }, + Self::Reserved { + model, + until, + timezone, + } => Self::Reserved { + model: model.clone(), + until: until.clone(), + timezone: timezone.clone(), + }, + Self::ContextWindowExceeded { model, detail } => Self::ContextWindowExceeded { + model: model.clone(), + detail: detail.clone(), + }, + Self::UnsupportedParams { model, params } => Self::UnsupportedParams { + model: model.clone(), + params: params.clone(), + }, + Self::RoutingPluginsLeftNothing { models } => Self::RoutingPluginsLeftNothing { + models: models.clone(), + }, + Self::InvalidRouterWeights => Self::InvalidRouterWeights, + Self::NonNumericWeight { metric } => Self::NonNumericWeight { metric }, + Self::RoutingPluginsNeedAsync => Self::RoutingPluginsNeedAsync, + Self::MissingRoutingGroup { group } => Self::MissingRoutingGroup { + group: group.clone(), + }, + Self::DefaultDeploymentRaises { model } => Self::DefaultDeploymentRaises { + model: model.clone(), + }, + Self::IndexOutOfRange { model } => Self::IndexOutOfRange { + model: model.clone(), + }, + Self::Attempt(_) + | Self::Config(_) + | Self::Cache(_) + | Self::Retired + | Self::ModelInfo { .. } => return None, + }) + } +} + +/// The class of a failed attempt, as litellm's exception mapping names it. +#[derive( + Clone, + Copy, + Debug, + PartialEq, + Eq, + Hash, + strum::Display, + strum::EnumString, + strum::IntoStaticStr, + strum::VariantArray, +)] +pub enum FailureKind { + #[strum(serialize = "RateLimitError")] + RateLimit, + #[strum(serialize = "ContextWindowExceededError")] + ContextWindowExceeded, + #[strum(serialize = "ContentPolicyViolationError")] + ContentPolicyViolation, + #[strum(serialize = "AuthenticationError")] + Authentication, + #[strum(serialize = "PermissionDeniedError")] + PermissionDenied, + #[strum(serialize = "NotFoundError")] + NotFound, + #[strum(serialize = "BadRequestError")] + BadRequest, + #[strum(serialize = "Timeout")] + Timeout, + #[strum(serialize = "APIConnectionError")] + ApiConnection, + #[strum(serialize = "InternalServerError")] + InternalServer, + #[strum(serialize = "ServiceUnavailableError")] + ServiceUnavailable, + #[strum(serialize = "BadGatewayError")] + BadGateway, + /// A guardrail blocked the request: never retried, never a fallback. + #[strum(serialize = "GuardrailIntervention")] + GuardrailIntervention, + /// litellm rejected the request before calling the deployment (`MalformedRequestFieldError`, + /// `UnsupportedEndpointError`): never cools the deployment down. + #[strum(serialize = "Declined")] + Declined, + /// The caller's own stored credential was rejected, not the deployment's + /// (`CallerCredentialAuthenticationError`): never cools the deployment down. + #[strum(serialize = "CallerCredentialAuthenticationError")] + CallerCredentialAuthentication, + /// A per-user credential exchange was rate limited (`CallerCredentialRateLimitError`): never + /// cools the deployment down. + #[strum(serialize = "CallerCredentialRateLimitError")] + CallerCredentialRateLimit, + #[strum(serialize = "APIError")] + Other, +} + +/// An opaque value the host hands through the router unchanged, such as the original Python +/// exception or response object. +#[derive(Clone)] +pub struct Payload(pub Arc); + +impl fmt::Debug for Payload { + fn fmt(&self, formatter: &mut fmt::Formatter<'_>) -> fmt::Result { + formatter.write_str("Payload(..)") + } +} + +/// One failed attempt, as typed facts the retry, fallback and cooldown rules decide by. +#[derive(Clone, Debug, thiserror::Error)] +#[error("the deployment call failed with {kind}")] +pub struct AttemptError { + pub kind: FailureKind, + pub status: Option, + /// The provider's `retry-after` header (`_get_retry_after_from_exception_header`). + pub retry_after: Option, + /// A deployment-level `num_retries` the failure carries (Python's `exception.num_retries`). + pub num_retries: Option, + /// The deployment the exception itself names (`_deployment_ids_to_skip_on_retry` reads its + /// `retry_skip_deployment_id`, then `failed_deployment_id`): an exception raised again keeps + /// the id its first failure stamped, whichever deployment raised it now. + pub failed_deployment_id: Option, + /// The provider's error text, kept only for the cooldown record Python writes + /// (`exception_received`, masked past 50 characters). + pub detail: Option>, + /// The exception's class names, most specific first (its `__mro__`), for the rules Python + /// decides by `isinstance`. Empty when the host reports none; the kind then stands in. + pub classes: Vec>, + /// The host already recorded what this failure does to the deployment's health (a routing + /// pre-call check's failure, which Python's attempt handles itself: a rate limit cools the + /// deployment down, anything else records nothing), or no failure callback runs for it (it + /// was raised outside the litellm call, or a shared logging object already logged a failure), + /// so the core records nothing. + pub recorded: bool, + /// The exception names its provider (`llm_provider` is set), which marks a provider's own + /// 400 for `fallback_on_unsupported_params`. + pub names_provider: bool, + /// An agentic follow-up call failed after the first call was served + /// (`is_agentic_followup_failure`): never retried, since a retry reruns every paid round. The + /// failure keeps its own class, which decides its fallbacks and cooldown as for any failure. + pub agentic_followup: bool, + /// One of `deployment_callback_on_failure`'s early exits holds: the failure says nothing about + /// the deployment, so it is neither counted nor cooled down (a failed request still counts + /// against the minute's requests, which `async_deployment_callback_on_failure` does apart). + pub outside_deployment: bool, + /// One of `_should_run_cooldown_logic`'s per-caller exits holds (`_is_per_user_provider_request` + /// or a per-user Copilot deployment): the failure is counted but never cools the deployment. + pub caller_scoped: bool, + /// The exception has no `status_code` (Python's status `""`): `_is_cooldown_required` holds + /// no cooldown for it, unlike a status the host could not read, which cools down as a 500. + pub status_absent: bool, + /// The failure counts against no per-minute requests: `async_deployment_callback_on_failure` + /// does not run for a sync call, and returns at once for a batch retrieve. + pub uncounted_request: bool, + pub payload: Option, +} + +impl AttemptError { + pub fn new(kind: FailureKind, status: Option) -> Self { + Self { + kind, + status, + retry_after: None, + num_retries: None, + failed_deployment_id: None, + detail: None, + classes: Vec::new(), + recorded: false, + names_provider: false, + agentic_followup: false, + outside_deployment: false, + caller_scoped: false, + status_absent: false, + uncounted_request: false, + payload: None, + } + } + + /// The exception's class names, most specific first: the host's, else the kind's. + pub fn class_names(&self) -> Vec<&str> { + if self.classes.is_empty() { + return crate::retry::kind_classes(self.kind).to_vec(); + } + self.classes.iter().map(AsRef::as_ref).collect() + } + + /// `isinstance(error, )`. + pub fn is_a(&self, name: &str) -> bool { + self.class_names().contains(&name) + } + + #[must_use] + pub fn with_retry_after(self, retry_after: Duration) -> Self { + Self { + retry_after: Some(retry_after), + ..self + } + } + + /// A plain Python exception the host raised outside any attempt (a `KeyError` from a stale + /// routing-group lookup, an error a retry policy lookup raised): no status, no provider, + /// nothing recorded against a deployment. `classes` are its class names, most specific first. + pub fn host_raised(classes: &[&str]) -> Self { + Self { + classes: classes.iter().map(|class| (*class).into()).collect(), + recorded: true, + ..Self::new(FailureKind::Other, None) + } + } + + /// The status Python's cooldown rules read: the provider's, else 500. + pub fn cooldown_status(&self) -> u16 { + self.status.unwrap_or(500) + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + + use super::*; + + #[rstest] + #[case::rate_limit("RateLimitError", FailureKind::RateLimit)] + #[case::context_window("ContextWindowExceededError", FailureKind::ContextWindowExceeded)] + #[case::caller_credential_auth( + "CallerCredentialAuthenticationError", + FailureKind::CallerCredentialAuthentication + )] + #[case::caller_credential_rate_limit( + "CallerCredentialRateLimitError", + FailureKind::CallerCredentialRateLimit + )] + #[case::other("APIError", FailureKind::Other)] + fn failure_kind_round_trips_its_exception_name(#[case] wire: &str, #[case] kind: FailureKind) { + assert_eq!(wire.parse::().unwrap(), kind); + assert_eq!(<&'static str>::from(kind), wire); + } + + #[rstest] + #[case::empty("")] + #[case::lowercase("ratelimiterror")] + fn failure_kind_rejects_unknown_names(#[case] wire: &str) { + assert!(wire.parse::().is_err()); + } +} diff --git a/litellm-rust/crates/router-core/src/fallback.rs b/litellm-rust/crates/router-core/src/fallback.rs new file mode 100644 index 00000000000..a1755bd6ad5 --- /dev/null +++ b/litellm-rust/crates/router-core/src/fallback.rs @@ -0,0 +1,330 @@ +//! Fallback lists as Python spells them, and how a failed group's chain is found in one. +//! Mirrors `get_fallback_model_group`, `get_fallback_model_group_for_lookup_groups`, +//! `check_non_standard_fallback_format` and `fallback_attempt_key` in +//! `router_utils/fallback_event_handlers.py`. +//! +//! A list holds keyed entries (`{"gpt-4": ["gpt-3.5", {"model": "x", "temperature": 0}]}`), +//! bare names (`"claude"`, a chain for every group) and, in a client-side list, dict targets +//! (`{"model": "x", "messages": [...]}`), which override request params for their attempt. + +use serde::Deserialize; +use serde_json::{Map, Value}; + +use std::collections::BTreeMap; + +/// One item of a fallback list, kept as Python holds it. +#[derive(Clone, Debug, PartialEq)] +enum Entry { + Name(String), + Dict(Map), + /// Anything else: Python skips it when it looks a chain up. + Other, +} + +/// A fallback list, in order. `"*"` keys the default chain. +#[derive(Clone, Debug, Default, PartialEq, Deserialize)] +#[serde(from = "Vec")] +pub struct Fallbacks(Vec); + +impl From> for Fallbacks { + fn from(entries: Vec) -> Self { + Self( + entries + .into_iter() + .map(|entry| match entry { + Value::String(name) => Entry::Name(name), + Value::Object(dict) => Entry::Dict(dict), + _ => Entry::Other, + }) + .collect(), + ) + } +} + +/// One target of a chain: a group name, or a dict target that also overrides request params. +#[derive(Clone, Debug, PartialEq)] +pub enum FallbackTarget { + Name(String), + Params(Map), +} + +impl FallbackTarget { + fn of(value: &Value) -> Option { + match value { + Value::String(name) => Some(Self::Name(name.clone())), + Value::Object(dict) => Some(Self::Params(dict.clone())), + _ => None, + } + } + + /// `_get_fallback_target_model_group`: the group the target names, if any. + pub fn model(&self) -> Option<&str> { + match self { + Self::Name(name) => Some(name), + Self::Params(dict) => dict.get("model").and_then(Value::as_str), + } + } + + /// The `model` of a dict target that sets a non-string one: the hop routes that value, which + /// no group answers (`_get_fallback_target_model_group` finds no group to check, but + /// `kwargs.update(target)` still rebinds the request's model). + pub fn unroutable_model(&self) -> Option<&Value> { + match self { + Self::Params(dict) => dict.get("model").filter(|model| !model.is_string()), + Self::Name(_) => None, + } + } + + /// `fallback_attempt_key`: a bare name and `{"model": name}` are the same attempt; a dict + /// carrying anything else is its own. + pub fn identity(&self) -> FallbackTarget { + match self { + Self::Params(dict) if dict.len() == 1 => match dict.get("model") { + Some(Value::String(name)) => Self::Name(name.clone()), + _ => self.clone(), + }, + _ => self.clone(), + } + } + + /// The params a dict target merges into the request (`kwargs.update(target)`). + pub fn params(&self) -> Option<&Map> { + match self { + Self::Params(dict) => Some(dict), + Self::Name(_) => None, + } + } +} + +/// What fallback keys match besides the exact group name: Python's `provider_list`, for +/// `"openai/gpt-4o"` to use a `"gpt-4o"` entry, the provider-prefixed spelling of each bare +/// group name (`_provider_prefixed_model_group`), for `"gpt-4o"` to use an `"openai/gpt-4o"` +/// entry, and the `LiteLLMParamsTypedDict` keys that mark a client-side dict target. +#[derive(Clone, Debug, Default, PartialEq, Deserialize)] +#[serde(default)] +pub struct FallbackKeys { + pub providers: Vec, + pub provider_prefixed: BTreeMap, + pub param_keys: Vec, +} + +impl FallbackKeys { + /// `_check_stripped_model_group`. + fn is_stripped(&self, group: &str, key: &str) -> bool { + self.providers.iter().any(|provider| { + let prefix = format!("{provider}/"); + group.starts_with(&prefix) && group.replace(&prefix, "") == key + }) + } +} + +/// A chain found for a group, and whether it is the `"*"` chain itself. +struct Found { + targets: Vec, + generic: bool, +} + +/// The targets of a keyed entry's value: a list of names and dicts. A bare string is walked +/// character by character, as Python iterates it. +fn chain_of(value: &Value) -> Vec { + match value { + Value::Array(items) => items.iter().filter_map(FallbackTarget::of).collect(), + Value::String(text) => text + .chars() + .map(|c| FallbackTarget::Name(c.to_string())) + .collect(), + _ => Vec::new(), + } +} + +impl Fallbacks { + pub fn is_empty(&self) -> bool { + self.0.is_empty() + } + + /// `check_non_standard_fallback_format`: a client-side list of names, or of dicts that set + /// a litellm param, is one chain for every group. + pub fn is_client_side(&self, keys: &FallbackKeys) -> bool { + if self.0.is_empty() { + return false; + } + if self.0.iter().all(|entry| matches!(entry, Entry::Name(_))) { + return true; + } + let dicts: Vec<_> = self + .0 + .iter() + .filter_map(|entry| match entry { + Entry::Dict(dict) => Some(dict), + _ => None, + }) + .collect(); + dicts.len() == self.0.len() + && dicts.iter().any(|dict| { + keys.param_keys + .iter() + .any(|key| dict.get(key).is_some_and(|value| !value.is_array())) + }) + } + + /// The whole list as one chain (a client-side list). + pub fn as_chain(&self) -> Vec { + self.0 + .iter() + .filter_map(|entry| match entry { + Entry::Name(name) => Some(FallbackTarget::Name(name.clone())), + Entry::Dict(dict) => Some(FallbackTarget::Params(dict.clone())), + Entry::Other => None, + }) + .collect() + } + + /// `_get_first_default_fallback`: the first target of the first `"*"` entry. + pub fn default_target(&self) -> Option<&str> { + self.0.iter().find_map(|entry| match entry { + Entry::Dict(dict) => match dict.get("*") { + Some(Value::Array(targets)) => targets.first().and_then(Value::as_str), + _ => None, + }, + _ => None, + }) + } + + /// `_has_default_fallbacks`: some entry keys `"*"`. + pub fn has_star(&self) -> bool { + self.0 + .iter() + .any(|entry| matches!(entry, Entry::Dict(dict) if dict.contains_key("*"))) + } + + /// `get_fallback_model_group`. + fn lookup(&self, group: &str, keys: &FallbackKeys) -> Option { + let prefixed = keys.provider_prefixed.get(group).map(String::as_str); + let mut generic = None; + let mut stripped = None; + let mut found = None; + for entry in &self.0 { + match entry { + Entry::Dict(dict) => { + let Some((key, value)) = dict.iter().next() else { + continue; + }; + if key == group { + found = Some(chain_of(value)); + break; + } else if Some(key.as_str()) == prefixed || keys.is_stripped(group, key) { + stripped = Some(chain_of(value)); + } else if key == "*" { + generic = Some(value); + } + } + Entry::Name(name) => found = Some(vec![FallbackTarget::Name(name.clone())]), + Entry::Other => {} + } + } + found + .or(stripped) + .map(|targets| Found { + targets, + generic: false, + }) + .or_else(|| { + generic.map(|value| Found { + targets: chain_of(value), + generic: true, + }) + }) + } + + /// `get_fallback_model_group_for_lookup_groups`: the first lookup group with its own chain + /// wins; `"*"` applies only after every group missed. + pub fn lookup_groups( + &self, + groups: &[&str], + keys: &FallbackKeys, + ) -> Option> { + let results: Vec = groups + .iter() + .filter_map(|group| self.lookup(group, keys)) + .collect(); + let index = results + .iter() + .position(|found| !found.generic) + .or_else(|| (!results.is_empty()).then_some(0))?; + results.into_iter().nth(index).map(|found| found.targets) + } + + /// `_has_fallback_group`'s view: only keyed entries whose targets are names or dicts count. + pub fn has_keyed_chain(&self, group: &str, keys: &FallbackKeys) -> bool { + let keyed = Fallbacks( + self.0 + .iter() + .filter(|entry| matches!(entry, Entry::Dict(_))) + .cloned() + .collect(), + ); + keyed + .lookup(group, keys) + .is_some_and(|found| !found.targets.is_empty()) + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + #[rstest] + #[case::an_int(json!({"model": 5}), true)] + #[case::none(json!({"model": null}), true)] + #[case::a_string(json!({"model": "b"}), false)] + #[case::no_model(json!({"temperature": 0}), false)] + fn only_a_set_non_string_model_is_unroutable(#[case] target: Value, #[case] unroutable: bool) { + let target = FallbackTarget::of(&target).unwrap(); + assert_eq!(target.unroutable_model().is_some(), unroutable); + } + + fn names(targets: Option>) -> Option> { + targets.map(|targets| { + targets + .iter() + .map(|t| t.model().unwrap_or_default().to_owned()) + .collect() + }) + } + + #[rstest] + #[case::own_entry(json!([{"a": ["b"]}, {"*": ["d"]}]), "a", Some(vec!["b"]))] + #[case::star_entry(json!([{"a": ["b"]}, {"*": ["d"]}]), "x", Some(vec!["d"]))] + #[case::string_is_every_groups_chain(json!(["b", {"x": ["c"]}]), "a", Some(vec!["b"]))] + #[case::keyed_entry_wins(json!(["c", {"a": ["b"]}]), "a", Some(vec!["b"]))] + #[case::string_value_is_iterated(json!([{"a": "bc"}]), "a", Some(vec!["b", "c"]))] + #[case::none(json!([{"x": ["c"]}]), "a", None)] + fn chains_follow_python( + #[case] list: Value, + #[case] group: &str, + #[case] expected: Option>, + ) { + let fallbacks: Fallbacks = serde_json::from_value(list).unwrap(); + assert_eq!( + names(fallbacks.lookup_groups(&[group], &FallbackKeys::default())), + expected.map(|e| e.into_iter().map(str::to_owned).collect()) + ); + } + + #[rstest] + #[case::names(json!(["a", "b"]), true)] + #[case::param_dicts(json!([{"model": "a", "temperature": 1}]), true)] + #[case::keyed(json!([{"a": ["b"]}]), false)] + #[case::mixed(json!(["a", {"a": ["b"]}]), false)] + fn client_side_lists_follow_python(#[case] list: Value, #[case] expected: bool) { + let fallbacks: Fallbacks = serde_json::from_value(list).unwrap(); + let keys = FallbackKeys { + param_keys: vec!["model".to_owned(), "temperature".to_owned()], + ..FallbackKeys::default() + }; + assert_eq!(fallbacks.is_client_side(&keys), expected); + } +} diff --git a/litellm-rust/crates/router-core/src/group_info.rs b/litellm-rust/crates/router-core/src/group_info.rs new file mode 100644 index 00000000000..9a49858ca18 --- /dev/null +++ b/litellm-rust/crates/router-core/src/group_info.rs @@ -0,0 +1,646 @@ +//! Model group info and the configured-value reads: what the router reports a model group, or a +//! concrete deployment behind a listed name, can do. +//! +//! The rules are the Python router core's (`_set_model_group_info`, `get_model_listing_info`, +//! `get_configured_token_limits`, `get_configured_mode`, `get_configured_display_name`, +//! `get_configured_service_tiers`). The host picks the deployments (the registry lookups) and +//! answers what needs its objects as [`Host::model_info`] lookups asked while the query runs: a +//! deployment's validated params, its merged model info and provider, its capabilities, and the +//! group's first entry as its model validates it. The core decides which deployments count and +//! how their values combine. + +use serde_json::{Map, Number, Value}; + +use crate::{ + error::Error, + host::{Host, ModelInfoLookup}, + model_info::{ + discovered, is_opaque, lookup, malformed, python_float, python_int, raised, truthy, + without_digit_underscores, + }, +}; + +/// One `_set_model_group_info` query. +#[derive(Clone, Debug, Default, serde::Deserialize)] +#[serde(default)] +pub struct GroupInfoQuery { + /// The model group the deployments serve (an alias already resolved). + pub model_group: String, + /// The name the group is reported as. + pub user_facing_model_group_name: String, + /// The group is a team's public model name the team's deployments serve. + pub serves_team_deployments: bool, + /// A wildcard pattern routes `model_group` (asked only when an entry needs it). + pub pattern_routes: bool, + /// The first string `model_info.description` among the deployments. + pub description: Value, + /// The deployments the group routes to, as stored. + pub deployments: Vec, +} + +/// The group info: `None` when no deployment matched, else the fields the merge assigned after +/// the host built the group from its first deployment ([`ModelInfoLookup::GroupSeed`]). +#[derive(Clone, Debug, Default, PartialEq)] +pub struct GroupInfo { + pub assignments: Map, +} + +/// The type name Python reports for a value, in its error messages. +pub(crate) fn type_name(value: &Value) -> &'static str { + match value { + Value::Null => "NoneType", + Value::Bool(_) => "bool", + Value::Number(number) if number.is_f64() => "float", + Value::Number(_) => "int", + Value::String(_) => "str", + Value::Array(_) => "list", + Value::Object(_) if is_opaque(value) => "object", + Value::Object(_) => "dict", + } +} + +/// A number as Python's arithmetic reads it (a bool is 0 or 1), or `None`. +fn arithmetic(value: &Value) -> Option { + match value { + Value::Bool(flag) => Some(Number::from(u8::from(*flag))), + Value::Number(number) => Some(number.clone()), + _ => None, + } +} + +/// `total += value`, with `total` starting at `0`; adding a non-number raises `TypeError`. +fn add(total: Option, value: &Value) -> Result { + let total = total.unwrap_or_else(|| Value::Number(Number::from(0))); + let (Some(left), Some(right)) = (arithmetic(&total), arithmetic(value)) else { + return Err(raised( + "TypeError", + format!( + "unsupported operand type(s) for +=: '{}' and '{}'", + type_name(&total), + type_name(value) + ), + )); + }; + if let (Some(left), Some(right)) = (left.as_i64(), right.as_i64()) + && let Some(sum) = left.checked_add(right) + { + return Ok(Value::Number(Number::from(sum))); + } + let sum = left.as_f64().unwrap_or(0.0) + right.as_f64().unwrap_or(0.0); + Ok(Number::from_f64(sum).map_or(Value::Null, Value::Number)) +} + +/// `left > right`, for numbers or strings; any other pair raises `TypeError`. +fn greater(left: &Value, right: &Value) -> Result { + if let (Some(left), Some(right)) = (arithmetic(left), arithmetic(right)) { + return Ok(left.as_f64().unwrap_or(0.0) > right.as_f64().unwrap_or(0.0)); + } + if let (Value::String(left), Value::String(right)) = (left, right) { + return Ok(left > right); + } + Err(raised( + "TypeError", + format!( + "'>' not supported between instances of '{}' and '{}'", + type_name(left), + type_name(right) + ), + )) +} + +/// `_cost_value_as_float`: `float(value)`, or `None` when it is unset or not a number. +fn cost_as_float(value: Option<&Value>) -> Option { + match value? { + Value::Bool(flag) => Some(f64::from(u8::from(*flag))), + Value::Number(number) => number.as_f64(), + Value::String(text) => { + without_digit_underscores(text.trim()).and_then(|digits| python_float(&digits)) + } + _ => None, + } +} + +fn float(value: Option) -> Value { + value + .and_then(Number::from_f64) + .map_or(Value::Null, Value::Number) +} + +/// `value.get(key)` on a dict; a value that is no dict raises `AttributeError`, as `.get` does. +fn get<'a>(value: &'a Value, key: &str) -> Result, Error> { + match value { + Value::Object(map) if !is_opaque(value) => Ok(map.get(key)), + other => Err(raised( + "AttributeError", + format!("'{}' object has no attribute 'get'", type_name(other)), + )), + } +} + +/// `model.get(key)`, then `litellm_params.get(key)`, then `model_info.get(key)`: the first that is +/// not `None`. +fn first_set( + model: &Value, + params: &Value, + info: &Value, + key: &str, +) -> Result, Error> { + for layer in [model, params, info] { + if let Some(value) = get(layer, key)?.filter(|value| !value.is_null()) { + return Ok(Some(value.clone())); + } + } + Ok(None) +} + +fn object(answer: Value, kind: &str) -> Result, Error> { + match answer { + Value::Object(map) => Ok(map), + _ => Err(malformed(kind)), + } +} + +/// The group being merged: the host's validated first entry, and what the merge assigned since. +struct Merged { + current: Map, + assignments: Map, +} + +impl Merged { + fn get(&self, field: &str) -> &Value { + self.current.get(field).unwrap_or(&Value::Null) + } + + fn set(&mut self, field: &str, value: Value) { + self.current.insert(field.to_owned(), value.clone()); + self.assignments.insert(field.to_owned(), value); + } + + /// `if info.get(field) is not None and info[field] > group.field (or group.field is None)`. + fn widen(&mut self, field: &str, info: &Map) -> Result<(), Error> { + let Some(value) = info.get(field).filter(|value| !value.is_null()) else { + return Ok(()); + }; + let current = self.get(field); + if current.is_null() || greater(value, current)? { + self.set(field, value.clone()); + } + Ok(()) + } + + /// The cost `field` widened to `float(info[field])` when that exceeds `group.field or 0.0`. + fn widen_cost(&mut self, field: &str, info: &Map) { + let Some(cost) = cost_as_float(info.get(field)) else { + return; + }; + let current = self.get(field); + let floor = if truthy(current) { + current.as_f64().unwrap_or(0.0) + } else { + 0.0 + }; + if current.is_null() || cost > floor { + self.set(field, float(Some(cost))); + } + } + + /// `if info.get(field) is True: group.field = True`. + fn any(&mut self, field: &str, info: &Map) { + if info.get(field) == Some(&Value::Bool(true)) { + self.set(field, Value::Bool(true)); + } + } +} + +/// `tuple(dict.fromkeys((*current, *added))) or None`. +fn union(current: &Value, added: &[Value]) -> Value { + let mut kept: Vec = Vec::new(); + let existing = current.as_array().map(Vec::as_slice).unwrap_or_default(); + for value in existing.iter().chain(added) { + if !kept.contains(value) { + kept.push(value.clone()); + } + } + if kept.is_empty() { + Value::Null + } else { + Value::Array(kept) + } +} + +/// `_set_model_group_info`: the group's info merged across the deployments that serve it. +pub async fn model_group_info( + host: &dyn Host, + query: &GroupInfoQuery, +) -> Result, Error> { + let mut merged: Option = None; + let mut totals: [(&str, Option); 4] = + [("tpm", None), ("rpm", None), ("itpm", None), ("otpm", None)]; + let mut clientside_auth_params = Value::Null; + let mut efforts_initialized = false; + let mut efforts_unknown = false; + let empty = Value::Object(Map::new()); + + for (index, model) in query.deployments.iter().enumerate() { + let named = get(model, "model_name")?; + let is_match = query.serves_team_deployments + || named.is_some_and(|name| name.as_str() == Some(query.model_group.as_str())) + || (named.is_some() && query.pattern_routes); + if !is_match { + continue; + } + let params = object( + lookup(host, ModelInfoLookup::GroupParams { index }).await?, + "group_params", + )?; + clientside_auth_params = params + .get("configurable_clientside_auth_params") + .cloned() + .unwrap_or(Value::Null); + let model_params = get(model, "litellm_params")?.unwrap_or(&empty); + let model_info_dict = get(model, "model_info")?.unwrap_or(&empty); + let mut deployment = [None, None, None, None]; + for (slot, (metric, _)) in deployment.iter_mut().zip(totals.iter()) { + *slot = first_set(model, model_params, model_info_dict, metric)?; + } + + let facts = object( + lookup( + host, + ModelInfoLookup::GroupDeployment { + index, + model: params.get("model").cloned().unwrap_or(Value::Null), + }, + ) + .await?, + "group_deployment", + )?; + let mapped = facts.get("mapped") == Some(&Value::Bool(true)); + let litellm_model = facts.get("litellm_model").cloned().unwrap_or(Value::Null); + let llm_provider = facts.get("llm_provider").cloned().unwrap_or(Value::Null); + let model_info = match facts.get("model_info") { + Some(Value::Object(info)) if !is_opaque(&Value::Object(info.clone())) => info.clone(), + Some(Value::Null) | None => { + // No model info: what the deployment's own (database) model_info says. + let db_info = get(model, "model_info")?.unwrap_or(&empty); + let mut info = Map::new(); + info.insert("key".to_owned(), Value::String(query.model_group.clone())); + for key in ["max_tokens", "max_input_tokens", "max_output_tokens"] { + info.insert(key.to_owned(), Value::Null); + } + for key in ["input_cost_per_token", "output_cost_per_token"] { + info.insert(key.to_owned(), float(cost_as_float(get(db_info, key)?))); + } + info.insert("litellm_provider".to_owned(), llm_provider.clone()); + info.insert( + "mode".to_owned(), + match get(db_info, "mode")? { + Some(mode) => mode.clone(), + None => Value::String("chat".to_owned()), + }, + ); + info.insert( + "supported_openai_params".to_owned(), + match facts.get("supported_openai_params") { + Some(Value::Null) | None => Value::Array(Vec::new()), + Some(params) => params.clone(), + }, + ); + info.insert("supports_system_messages".to_owned(), Value::Null); + info + } + Some(_) => return Err(malformed("group_deployment")), + }; + + match merged.as_mut() { + None => { + let mut seed = Map::new(); + seed.insert( + "model_group".to_owned(), + Value::String(query.user_facing_model_group_name.clone()), + ); + seed.insert( + "providers".to_owned(), + Value::Array(vec![llm_provider.clone()]), + ); + seed.insert("description".to_owned(), query.description.clone()); + seed.extend(model_info.clone()); + seed.insert( + "supports_continuation".to_owned(), + Value::Bool( + model_info.get("supports_continuation") == Some(&Value::Bool(true)), + ), + ); + seed.insert("supports_fast_mode".to_owned(), Value::Bool(true)); + seed.insert("supported_reasoning_efforts".to_owned(), Value::Null); + seed.insert("supported_endpoints".to_owned(), Value::Null); + let current = object( + lookup(host, ModelInfoLookup::GroupSeed { info: seed }).await?, + "group_seed", + )?; + merged = Some(Merged { + current, + assignments: Map::new(), + }); + } + Some(group) => { + let providers = group + .get("providers") + .as_array() + .cloned() + .unwrap_or_default(); + if !providers.contains(&llm_provider) { + let mut providers = providers; + providers.push(llm_provider.clone()); + group.set("providers", Value::Array(providers)); + } + group.widen("max_input_tokens", &model_info)?; + group.widen("max_output_tokens", &model_info)?; + group.widen_cost("input_cost_per_token", &model_info); + group.widen_cost("output_cost_per_token", &model_info); + for field in [ + "supports_parallel_function_calling", + "supports_vision", + "supports_function_calling", + "supports_web_search", + "supports_url_context", + "supports_continuation", + "supports_reasoning", + ] { + group.any(field, &model_info); + } + if let Some(params) = model_info + .get("supported_openai_params") + .filter(|params| !params.is_null()) + { + group.set("supported_openai_params", params.clone()); + } + for (slot, metric) in deployment.iter_mut().zip(["tpm", "rpm"]) { + if slot.is_none() + && let Some(value) = model_info.get(metric).filter(|v| !v.is_null()) + { + *slot = Some(value.clone()); + } + } + } + } + let Some(group) = merged.as_mut() else { + unreachable!("the group was just built"); + }; + + let capabilities = object( + lookup( + host, + ModelInfoLookup::GroupCapabilities { + index, + model_info: Value::Object(model_info), + litellm_model, + llm_provider, + mapped, + }, + ) + .await?, + "group_capabilities", + )?; + let endpoints = capabilities + .get("supported_endpoints") + .and_then(Value::as_array) + .cloned() + .unwrap_or_default(); + let endpoints = union(group.get("supported_endpoints"), &endpoints); + group.set("supported_endpoints", endpoints); + let fast_mode = truthy(group.get("supports_fast_mode")) + && capabilities.get("supports_fast_mode") == Some(&Value::Bool(true)); + group.set("supports_fast_mode", Value::Bool(fast_mode)); + match capabilities + .get("reasoning_efforts") + .cloned() + .unwrap_or(Value::Null) + { + Value::Null => { + efforts_unknown = true; + group.set("supported_reasoning_efforts", Value::Null); + } + resolved if !efforts_initialized => { + efforts_initialized = true; + if !efforts_unknown { + group.set("supported_reasoning_efforts", resolved); + } + } + resolved if !efforts_unknown => { + let intersected = lookup( + host, + ModelInfoLookup::ReasoningIntersect { + current: group.get("supported_reasoning_efforts").clone(), + resolved, + }, + ) + .await?; + group.set("supported_reasoning_efforts", intersected); + } + _ => {} + } + + for ((_, total), value) in totals.iter_mut().zip(deployment) { + if let Some(value) = value { + *total = Some(add(total.take(), &value)?); + } + } + } + + let Some(mut group) = merged else { + return Ok(None); + }; + for (metric, total) in totals { + if let Some(total) = total { + group.set(metric, total); + } + } + if !clientside_auth_params.is_null() { + group.set( + "configurable_clientside_auth_params", + clientside_auth_params, + ); + } + Ok(Some(GroupInfo { + assignments: group.assignments, + })) +} + +/// `coerce_token_limit`: a token limit as an int, `None` when it is unset or not a usable number +/// (a bool never is). +pub fn coerce_token_limit(value: Option<&Value>) -> Option { + match value? { + Value::Number(number) => number.as_i64().or_else(|| { + number + .as_f64() + .filter(|n| n.is_finite()) + .map(|n| n.trunc() as i64) + }), + Value::String(text) => without_digit_underscores(text.trim()) + .and_then(|digits| python_int(&digits)) + .and_then(|number| number.as_i64()), + _ => None, + } +} + +/// The deployment's discovered limits under its configured `model_info` values that are set. +async fn effective_model_info( + host: &dyn Host, + id: Value, + configured: &Map, +) -> Result, Error> { + let mut info = discovered(host, id).await?; + info.extend( + configured + .iter() + .filter(|(_, value)| !value.is_null()) + .map(|(key, value)| (key.clone(), value.clone())), + ); + Ok(info) +} + +/// `get_configured_token_limits`: the (max input, max output) tokens a concrete deployment +/// configures, or its refresh discovered, from its `model_info` (`exclude_none` dump) and id. +pub async fn configured_token_limits( + host: &dyn Host, + id: Value, + configured: &Map, +) -> Result<(Option, Option), Error> { + let info = effective_model_info(host, id, configured).await?; + Ok(( + coerce_token_limit(info.get("max_input_tokens")), + coerce_token_limit(info.get("max_output_tokens")), + )) +} + +/// `get_configured_mode` / `get_configured_display_name`: a configured string that is not blank. +pub fn configured_text(value: Option<&Value>) -> Option { + value + .and_then(Value::as_str) + .filter(|text| !text.trim().is_empty()) + .map(str::to_owned) +} + +/// `get_configured_service_tiers`: each deployment's `model_info.service_tiers`, unvalidated. +pub fn configured_service_tiers(model_infos: &[Map]) -> Vec { + model_infos + .iter() + .map(|info| info.get("service_tiers").cloned().unwrap_or(Value::Null)) + .collect() +} + +/// What a listed name's deployments contribute to its `/v1/models` entry. +#[derive(Clone, Debug, Default, PartialEq)] +pub struct ListingInfo { + pub cost_map_keys: Vec, + pub max_input_tokens: Option, + pub max_output_tokens: Option, +} + +fn named_text(value: Option<&Value>) -> Option<&str> { + value + .and_then(Value::as_str) + .filter(|text| !text.is_empty()) +} + +/// `deployment_pricing_models(deployment)[0]`: `model_info.base_model`, then +/// `litellm_params.base_model`, then `litellm_params.model`; malformed blocks count as unset. +fn pricing_key(deployment: &Value) -> Option { + let block = |key: &str| { + deployment + .get(key) + .and_then(Value::as_object) + .filter(|_| !is_opaque(deployment.get(key).unwrap_or(&Value::Null))) + }; + let params = block("litellm_params"); + let info = block("model_info"); + let base_model = info + .and_then(|info| info.get("base_model")) + .filter(|base| truthy(base)) + .or_else(|| params.and_then(|params| params.get("base_model"))); + named_text(base_model) + .or_else(|| named_text(params.and_then(|params| params.get("model")))) + .map(str::to_owned) +} + +/// `get_model_listing_info` over the deployments a listed name names: the cost-map keys of their +/// models, deduplicated, and the widest token limits they configure or discovered. +pub async fn model_listing_info( + host: &dyn Host, + deployments: &[Value], +) -> Result { + let mut listing = ListingInfo::default(); + let empty = Value::Object(Map::new()); + for deployment in deployments { + let info = match get(deployment, "model_info")? { + Some(info) if truthy(info) => info, + _ => &empty, + }; + let id = get(info, "id")?.cloned().unwrap_or(Value::Null); + let configured = match info { + Value::Object(map) => map.clone(), + _ => Map::new(), + }; + let effective = effective_model_info(host, id, &configured).await?; + for (field, widest) in [ + ("max_input_tokens", &mut listing.max_input_tokens), + ("max_output_tokens", &mut listing.max_output_tokens), + ] { + if let Some(limit) = coerce_token_limit(effective.get(field)) { + *widest = Some(widest.map_or(limit, |current| current.max(limit))); + } + } + } + for key in deployments.iter().filter_map(pricing_key) { + if !listing.cost_map_keys.contains(&key) { + listing.cost_map_keys.push(key); + } + } + Ok(listing) +} + +#[cfg(test)] +mod tests { + use serde_json::json; + + use super::*; + + #[test] + fn coerce_token_limit_reads_python_ints() { + assert_eq!(coerce_token_limit(Some(&json!(128))), Some(128)); + assert_eq!(coerce_token_limit(Some(&json!(12.9))), Some(12)); + assert_eq!(coerce_token_limit(Some(&json!(" 1_000 "))), Some(1000)); + assert_eq!(coerce_token_limit(Some(&json!("128,000"))), None); + assert_eq!(coerce_token_limit(Some(&json!(true))), None); + assert_eq!(coerce_token_limit(None), None); + } + + #[test] + fn totals_add_like_python() { + assert_eq!(add(None, &json!(5)).unwrap(), json!(5)); + assert_eq!(add(Some(json!(5)), &json!(true)).unwrap(), json!(6)); + assert_eq!(add(Some(json!(5)), &json!(0.5)).unwrap(), json!(5.5)); + assert!(add(Some(json!(5)), &json!("1")).is_err()); + } + + #[test] + fn union_keeps_first_seen_order_and_empty_reads_as_none() { + assert_eq!( + union(&json!(["a", "b"]), &[json!("b"), json!("c")]), + json!(["a", "b", "c"]) + ); + assert_eq!(union(&Value::Null, &[]), Value::Null); + } + + #[test] + fn pricing_key_prefers_the_base_model() { + let deployment = json!({ + "litellm_params": {"model": "azure/x", "base_model": "params-base"}, + "model_info": {"base_model": "info-base"}, + }); + assert_eq!(pricing_key(&deployment).as_deref(), Some("info-base")); + let deployment = json!({"litellm_params": {"model": "azure/x"}, "model_info": "junk"}); + assert_eq!(pricing_key(&deployment).as_deref(), Some("azure/x")); + } +} diff --git a/litellm-rust/crates/router-core/src/health.rs b/litellm-rust/crates/router-core/src/health.rs new file mode 100644 index 00000000000..020a1a0f47d --- /dev/null +++ b/litellm-rust/crates/router-core/src/health.rs @@ -0,0 +1,960 @@ +//! [`Health`]: cooldowns, allowed-fails counters and per-minute usage, kept in the shared +//! [`RouterCache`] under the Python router's keys, encodings and TTLs: +//! +//! | state | key | value | TTL | +//! |---|---|---|---| +//! | cooldown | `deployment:{id}:cooldown` | `{exception_received, status_code, timestamp, cooldown_time}` | cooldown time | +//! | allowed fails | `deployment:{id}:allowed_fails[:{suffix}]` | int counter | cooldown time | +//! | usage | `global_router:{id}:{model}:tpm:{HH-MM}` and `:rpm:` | int counter | 60s | +//! | outcomes (local only) | `{id}:successes`, `{id}:fails` | int counter | 60s | +//! +//! From `router_utils/cooldown_cache.py`, `router_utils/cooldown_handlers.py`, +//! `router_utils/router_callbacks/track_deployment_metrics.py`, `RouterCacheEnum` in +//! `types/router.py` and `Router._increment_usage` / `deployment_callback_on_failure` in +//! `router.py`. + +use std::{ + sync::Arc, + time::{Duration, SystemTime, UNIX_EPOCH}, +}; + +use serde::{Deserialize, Serialize}; +use tracing::debug; + +use crate::{ + cache::RouterCache, + error::{AttemptError, Error, FailureKind}, + outcome::{OutcomeCallbacks, OutcomeWrite}, + registry::{Deployment, Registry}, + settings::Settings, +}; + +/// `RoutingArgs.ttl`: per-minute usage keys expire after a minute. +pub const USAGE_TTL: Duration = Duration::from_secs(60); +/// `DEFAULT_FAILURE_THRESHOLD_PERCENT`. +pub const FAILURE_THRESHOLD_PERCENT: f64 = 0.5; +/// `DEFAULT_FAILURE_THRESHOLD_MINIMUM_REQUESTS`. +pub const FAILURE_THRESHOLD_MINIMUM_REQUESTS: u64 = 5; +/// `SINGLE_DEPLOYMENT_TRAFFIC_FAILURE_THRESHOLD`. +pub const SINGLE_DEPLOYMENT_TRAFFIC_FAILURE_THRESHOLD: u64 = 1000; +/// `exception_masker` in `CooldownCache`: the visible prefix of `exception_received`. +const EXCEPTION_VISIBLE_PREFIX: usize = 50; + +pub trait Clock: Send + Sync { + fn now(&self) -> SystemTime; +} + +pub struct SystemClock; + +impl Clock for SystemClock { + fn now(&self) -> SystemTime { + SystemTime::now() + } +} + +fn unix_seconds(time: SystemTime) -> f64 { + time.duration_since(UNIX_EPOCH) + .map(|elapsed| elapsed.as_secs_f64()) + .unwrap_or_default() +} + +/// `get_utc_datetime().strftime("%H-%M")`. +pub fn current_minute(time: SystemTime) -> String { + let seconds = time + .duration_since(UNIX_EPOCH) + .map(|elapsed| elapsed.as_secs()) + .unwrap_or_default() + % 86_400; + format!("{:02}-{:02}", seconds / 3600, (seconds % 3600) / 60) +} + +pub fn cooldown_key(id: &str) -> String { + format!("deployment:{id}:cooldown") +} + +pub fn allowed_fails_key(id: &str, suffix: Option<&str>) -> String { + match suffix { + Some(suffix) => format!("deployment:{id}:allowed_fails:{suffix}"), + None => format!("deployment:{id}:allowed_fails"), + } +} + +#[derive(Clone, Copy, Debug, PartialEq, Eq, strum::Display, strum::EnumString)] +pub enum UsageMetric { + #[strum(serialize = "tpm")] + Tpm, + #[strum(serialize = "rpm")] + Rpm, + /// Input tokens per minute, which the io-token rate limit check counts. + #[strum(serialize = "itpm")] + Itpm, + /// Output tokens per minute. + #[strum(serialize = "otpm")] + Otpm, +} + +/// `RouterCacheEnum.TPM` / `RPM` / `ITPM` / `OTPM`: `model` is the deployment's +/// `litellm_params.model`. +pub fn usage_key(id: &str, model: &str, metric: UsageMetric, minute: &str) -> String { + format!("global_router:{id}:{model}:{metric}:{minute}") +} + +/// `CooldownCacheValue`. +#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)] +pub struct CooldownValue { + pub exception_received: String, + pub status_code: String, + pub timestamp: f64, + /// Whole seconds are written as an int, as Python's default `cooldown_time` is, so the + /// "Try again in N seconds" text reads the same. + #[serde(serialize_with = "whole_as_int")] + pub cooldown_time: f64, +} + +fn whole_as_int(value: &f64, serializer: S) -> Result { + if value.fract() == 0.0 && value.abs() < i64::MAX as f64 { + serializer.serialize_i64(*value as i64) + } else { + serializer.serialize_f64(*value) + } +} + +/// `litellm.should_retry`. +pub fn should_retry_status(status: u16) -> bool { + matches!(status, 408 | 409 | 429) || status >= 500 +} + +/// `_is_cooldown_required`: a 4xx cools down only for 429, 401, 402, 404 and 408, every other +/// status does, and a connection error or an empty status never does. +pub fn is_cooldown_required(failure: &AttemptError) -> bool { + if failure.kind == FailureKind::ApiConnection || failure.status_absent { + return false; + } + match failure.cooldown_status() { + status @ 400..500 => matches!(status, 429 | 401 | 402 | 408 | 404), + _ => true, + } +} + +/// `SensitiveDataMasker(visible_prefix=50, visible_suffix=0, mask_short_values=False)`. +fn mask_exception(text: &str) -> String { + let length = text.chars().count(); + if length <= EXCEPTION_VISIBLE_PREFIX { + return text.to_owned(); + } + let mut masked: String = text.chars().take(EXCEPTION_VISIBLE_PREFIX).collect(); + masked.extend(std::iter::repeat_n('*', length - EXCEPTION_VISIBLE_PREFIX)); + masked +} + +/// `_EXCEPTION_POLICY_FIELDS`: a deployment policy's fields in the order Python matches them +/// (a content-policy violation is a bad request, so it comes first). +const DEPLOYMENT_POLICY_FIELDS: [(&str, &str); 9] = [ + ( + "ContentPolicyViolationError", + "ContentPolicyViolationErrorAllowedFails", + ), + ("BadRequestError", "BadRequestErrorAllowedFails"), + ("AuthenticationError", "AuthenticationErrorAllowedFails"), + ("Timeout", "TimeoutErrorAllowedFails"), + ("RateLimitError", "RateLimitErrorAllowedFails"), + ("InternalServerError", "InternalServerErrorAllowedFails"), + ( + "ServiceUnavailableError", + "ServiceUnavailableErrorAllowedFails", + ), + ("BadGatewayError", "BadGatewayErrorAllowedFails"), + ("NotFoundError", "NotFoundErrorAllowedFails"), +]; + +/// `_resolve_allowed_fails_from_policy` over a deployment's `model_info.allowed_fails_policy`: +/// the first field set for a class the failure is an instance of. +pub fn deployment_allowed_fails( + policy: Option<&serde_json::Map>, + failure: &AttemptError, +) -> Option { + let policy = policy?; + DEPLOYMENT_POLICY_FIELDS + .iter() + .filter(|(class, _)| failure.is_a(class)) + .find_map(|(_, field)| policy.get(*field).and_then(serde_json::Value::as_f64)) +} + +/// What the cooldown rules need to know about the deployment's group. +#[derive(Clone, Copy, Debug, Default)] +pub struct GroupShape { + /// The deployment is the only one in its model group. + pub single_deployment: bool, + /// The requested group has a fallback configured. + pub has_fallback_group: bool, +} + +/// `_core_team_model_has_alternatives`: another routable deployment serves the deployment's team +/// public name. +pub(crate) fn team_model_has_alternatives(registry: &Registry, deployment: &Deployment) -> bool { + let info = &deployment.model_info; + let (Some(team_id), Some(public_name)) = (&info.team_id, &info.team_public_model_name) else { + return false; + }; + registry + .team_named(team_id, public_name) + .is_some_and(|siblings| { + siblings + .iter() + .filter(|sibling| !sibling.model_info.blocked) + .count() + > 1 + }) +} + +/// `_core_routing_group_has_alternatives`: `model_group` names a callable routing group whose +/// members span more than one deployment. +pub(crate) fn routing_group_has_alternatives(registry: &Registry, model_group: &str) -> bool { + let resolved = registry.alias_of(model_group).unwrap_or(model_group); + registry.routing_group_named(resolved).is_some_and(|group| { + group + .models + .iter() + .map(|member| registry.named(member).map_or(0, |members| members.len())) + .sum::() + > 1 + }) +} + +/// An outcome the router did not see itself (`Health.report`). +#[derive(Clone, Debug)] +pub enum Outcome { + Success { total_tokens: u64 }, + Failure(AttemptError), +} + +#[derive(Clone)] +pub struct Health { + cache: Arc, + clock: Arc, +} + +impl Health { + pub fn new(cache: Arc, clock: Arc) -> Self { + Self { cache, clock } + } + + pub fn cache(&self) -> &Arc { + &self.cache + } + + pub(crate) fn now_time(&self) -> SystemTime { + self.clock.now() + } + + fn now(&self) -> f64 { + unix_seconds(self.clock.now()) + } + + /// The ids among `ids` with an unexpired cooldown (`async_get_active_cooldowns`). + pub async fn active_cooldowns( + &self, + ids: &[String], + ) -> Result, Error> { + let keys: Vec = ids.iter().map(|id| cooldown_key(id)).collect(); + let values = self.cache.async_batch_get_cache(&keys).await?; + let now = self.now(); + Ok(ids + .iter() + .zip(values) + .filter_map(|(id, value)| { + let value: CooldownValue = serde_json::from_value(value?).ok()?; + (value.timestamp + value.cooldown_time - now > 0.0).then(|| (id.clone(), value)) + }) + .collect()) + } + + /// `add_deployment_to_cooldown`. + pub async fn add_cooldown( + &self, + id: &str, + failure: &AttemptError, + cooldown: Duration, + ) -> Result<(), Error> { + let value = CooldownValue { + exception_received: mask_exception(failure.detail.as_deref().unwrap_or_default()), + status_code: failure.cooldown_status().to_string(), + timestamp: self.now(), + cooldown_time: cooldown.as_secs_f64(), + }; + let value = serde_json::to_value(value).unwrap_or_default(); + self.cache + .async_set_cache(&cooldown_key(id), value, Some(cooldown)) + .await?; + Ok(()) + } + + async fn local_count(&self, key: &str) -> Result { + Ok(self + .cache + .async_get_local(key) + .await? + .and_then(|value| value.as_f64()) + .map_or(0, |count| count as u64)) + } + + /// The per-minute (successes, fails) this worker saw (`{id}:successes`, `{id}:fails`, kept + /// `local_only`). + pub async fn outcomes_this_minute(&self, id: &str) -> Result<(u64, u64), Error> { + Ok(( + self.local_count(&format!("{id}:successes")).await?, + self.local_count(&format!("{id}:fails")).await?, + )) + } + + /// `increment_deployment_successes_for_current_minute`: returns the key it counted under. + pub async fn count_success(&self, id: &str) -> Result { + let key = format!("{id}:successes"); + self.cache + .async_increment_local(&key, 1.0, Some(USAGE_TTL)) + .await?; + Ok(key) + } + + /// `increment_deployment_failures_for_current_minute`. + pub async fn count_failure(&self, id: &str) -> Result<(), Error> { + self.cache + .async_increment_local(&format!("{id}:fails"), 1.0, Some(USAGE_TTL)) + .await?; + Ok(()) + } + + /// Cooldown duration precedence from `deployment_callback_on_failure`: the deployment's + /// `cooldown_time`, then the provider's retry-after, then the router default. + pub fn cooldown_duration( + settings: &Settings, + deployment: &Deployment, + failure: &AttemptError, + ) -> Duration { + Self::cooldown_for_call(settings, deployment, None, failure) + } + + /// `cooldown_duration` for a call whose own params carry `cooldown_time` (a request's + /// value wins over the deployment's `litellm_params`, not over its `model_info`). + pub fn cooldown_for_call( + settings: &Settings, + deployment: &Deployment, + call_cooldown: Option, + failure: &AttemptError, + ) -> Duration { + let configured = deployment + .model_info + .cooldown_time + .or(call_cooldown) + .or_else(|| { + deployment + .raw_params + .get("cooldown_time") + .and_then(|v| v.as_f64()) + }) + .filter(|seconds| *seconds >= 0.0) + .and_then(|seconds| Duration::try_from_secs_f64(seconds).ok()); + configured + .or(failure.retry_after) + .unwrap_or(settings.cooldown_time) + } + + /// The deployment's own `cooldown_time`: `model_info` first, then `litellm_params` + /// (`_first_present(model_info, litellm_params, key="cooldown_time")`). It is both the + /// cooldown and the TTL of the deployment's `allowed_fails:generic` counter. + fn configured_cooldown(deployment: &Deployment) -> Option { + deployment + .model_info + .cooldown_time + .or_else(|| { + deployment + .raw_params + .get("cooldown_time") + .and_then(|v| v.as_f64()) + }) + .filter(|seconds| *seconds >= 0.0) + .and_then(|seconds| Duration::try_from_secs_f64(seconds).ok()) + } + + /// Record a failed attempt and cool the deployment down when the rules say so. Returns the + /// cooldown applied, if any. + pub async fn record_failure( + &self, + settings: &Settings, + deployment: &Deployment, + shape: GroupShape, + call_cooldown: Option, + failure: &AttemptError, + ) -> Result, Error> { + if failure.outside_deployment { + return Ok(None); + } + self.count_failure(&deployment.id).await?; + let cooldown = Self::cooldown_for_call(settings, deployment, call_cooldown, failure); + self.cool_down_after(settings, deployment, shape, failure, cooldown) + .await + } + + /// `set_cooldown_deployments` for a failure already counted: cool the deployment down for + /// `cooldown` when the rules say so. Returns the cooldown applied, if any. + pub async fn cool_down_after( + &self, + settings: &Settings, + deployment: &Deployment, + shape: GroupShape, + failure: &AttemptError, + cooldown: Duration, + ) -> Result, Error> { + if !Self::should_run_cooldown_logic(settings, deployment, failure, cooldown) { + return Ok(None); + } + if !self + .should_cooldown(settings, deployment, shape, failure) + .await? + { + return Ok(None); + } + debug!(deployment_id = %deployment.id, cooldown_seconds = cooldown.as_secs_f64(), "cooling deployment down"); + self.add_cooldown(&deployment.id, failure, cooldown).await?; + Ok(Some(cooldown)) + } + + /// `_should_run_cooldown_logic`. + fn should_run_cooldown_logic( + settings: &Settings, + deployment: &Deployment, + failure: &AttemptError, + cooldown: Duration, + ) -> bool { + !matches!( + failure.kind, + FailureKind::Declined + | FailureKind::CallerCredentialAuthentication + | FailureKind::CallerCredentialRateLimit + ) && !failure.caller_scoped + && !cooldown.is_zero() + && !settings.disable_cooldowns + && (is_cooldown_required(failure) + || deployment_allowed_fails( + deployment.model_info.allowed_fails_policy.as_ref(), + failure, + ) + .is_some()) + && !settings + .provider_default_deployment_ids + .contains(&deployment.id) + } + + /// `_should_cooldown_deployment`. + async fn should_cooldown( + &self, + settings: &Settings, + deployment: &Deployment, + shape: GroupShape, + failure: &AttemptError, + ) -> Result { + let status = failure.cooldown_status(); + let policy_fails = settings.allowed_fails_for(failure); + let lone = shape.single_deployment && !shape.has_fallback_group; + let deployment_policy = deployment.model_info.allowed_fails_policy.as_ref(); + let deployment_fails = deployment_allowed_fails(deployment_policy, failure); + if shape.single_deployment + && status == 402 + && deployment_fails.is_none() + && policy_fails.is_none() + { + return Ok(false); + } + let deployment_allowed = deployment.model_info.allowed_fails; + if deployment_policy.is_some() || deployment_allowed.is_some() { + // `_should_cooldown_based_on_deployment_policy`: a deployment-wide `allowed_fails` + // keeps the lone-deployment safety net; a policy entry naming the error does not. + if deployment_fails.is_none() + && lone + && (deployment_allowed.is_some() || policy_fails.is_none()) + { + return Ok(false); + } + let (allowed, suffix) = match deployment_fails { + Some(allowed) => ( + Some(allowed), + failure.class_names().first().map(|name| (*name).to_owned()), + ), + None => ( + deployment_allowed.map(f64::from), + deployment_allowed.map(|_| "generic".to_owned()), + ), + }; + let allowed = allowed + .or_else(|| policy_fails.map(f64::from)) + .unwrap_or_else(|| f64::from(settings.effective_allowed_fails())); + let ttl = + Self::configured_cooldown(deployment).unwrap_or_else(|| settings.fails_window()); + return self + .exceeds_allowed_fails(&deployment.id, suffix.as_deref(), allowed, ttl) + .await; + } + if settings.allowed_fails_policy.is_none() && !settings.allowed_fails_set() { + let (successes, fails) = self.outcomes_this_minute(&deployment.id).await?; + let total = successes + fails; + let percent_fails = if total > 0 { + fails as f64 / total as f64 + } else { + 0.0 + }; + return Ok((status == 429 && !shape.single_deployment) + || (percent_fails == 1.0 && total >= SINGLE_DEPLOYMENT_TRAFFIC_FAILURE_THRESHOLD) + || (percent_fails > FAILURE_THRESHOLD_PERCENT + && total >= FAILURE_THRESHOLD_MINIMUM_REQUESTS + && !shape.single_deployment) + || !should_retry_status(status)); + } + if lone && policy_fails.is_none() { + return Ok(false); + } + let allowed = policy_fails.unwrap_or_else(|| settings.effective_allowed_fails()); + self.exceeds_allowed_fails( + &deployment.id, + None, + f64::from(allowed), + settings.fails_window(), + ) + .await + } + + /// `should_cooldown_based_on_allowed_fails_policy`: count this failure, then compare. + async fn exceeds_allowed_fails( + &self, + id: &str, + suffix: Option<&str>, + allowed: f64, + ttl: Duration, + ) -> Result { + let fails = self + .cache + .async_increment(&allowed_fails_key(id, suffix), 1.0, Some(ttl)) + .await?; + Ok(fails > allowed) + } + + /// Count a success, and the tokens and request against the deployment's per-minute usage + /// when `tracks` says it has limits to track. The count is the success callback's; the usage + /// is `make_call`'s, which runs whatever the callbacks do. + pub async fn record_success( + &self, + callbacks: OutcomeCallbacks, + deployment: &Deployment, + total_tokens: u64, + tracks: bool, + ) -> Result<(), Error> { + callbacks + .record(OutcomeWrite::Success, self.count_success(&deployment.id)) + .await?; + if !tracks { + return Ok(()); + } + callbacks + .record( + OutcomeWrite::AttemptUsage, + self.add_usage(deployment, None, total_tokens as f64, 1.0), + ) + .await + } + + /// `_increment_deployment_usage`, for a deployment that tracks usage: tokens and requests + /// under `model` (metadata's `deployment`, which a wildcard route fills; else the + /// deployment's own), unless there is nothing to add. + pub async fn add_usage( + &self, + deployment: &Deployment, + model: Option<&str>, + total_tokens: f64, + requests: f64, + ) -> Result<(), Error> { + if total_tokens <= 0.0 && requests <= 0.0 { + return Ok(()); + } + let minute = current_minute(self.clock.now()); + let model = model.unwrap_or(&deployment.params.model); + self.cache + .async_increment_usage( + &[ + ( + usage_key(&deployment.id, model, UsageMetric::Tpm, &minute), + total_tokens, + ), + ( + usage_key(&deployment.id, model, UsageMetric::Rpm, &minute), + requests, + ), + ], + Some(USAGE_TTL), + ) + .await?; + Ok(()) + } + + /// `async_deployment_callback_on_failure`: a failed request counts against the deployment's + /// per-minute requests under `model` (see [`Self::add_usage`]), whether or not it tracks usage. + pub async fn count_failed_request( + &self, + deployment: &Deployment, + model: Option<&str>, + ) -> Result<(), Error> { + let minute = current_minute(self.clock.now()); + self.cache + .async_increment( + &usage_key( + &deployment.id, + model.unwrap_or(&deployment.params.model), + UsageMetric::Rpm, + &minute, + ), + 1.0, + Some(USAGE_TTL), + ) + .await?; + Ok(()) + } + + /// This minute's (tpm, rpm) for a deployment. + pub async fn usage(&self, deployment: &Deployment) -> Result<(u64, u64), Error> { + let minute = current_minute(self.clock.now()); + let model = &deployment.params.model; + let keys = [UsageMetric::Tpm, UsageMetric::Rpm] + .map(|metric| usage_key(&deployment.id, model, metric, &minute)); + let values = self.cache.async_batch_get_cache(&keys).await?; + let count = |index: usize| { + values + .get(index) + .cloned() + .flatten() + .and_then(|value| value.as_f64()) + .map_or(0, |count| count as u64) + }; + Ok((count(0), count(1))) + } +} + +#[cfg(test)] +mod tests { + use std::collections::BTreeMap; + + use rstest::rstest; + + use super::*; + use crate::{ + cache::InMemoryRouterCache, + config::{RouterConfig, RouterDynamicConfig}, + registry::{DeploymentSpec, RoutingGroupSpec}, + }; + + #[rstest] + #[case::rate_limit(FailureKind::RateLimit, Some(429), true)] + #[case::auth(FailureKind::Authentication, Some(401), true)] + #[case::payment(FailureKind::Other, Some(402), true)] + #[case::not_found(FailureKind::NotFound, Some(404), true)] + #[case::timeout(FailureKind::Timeout, Some(408), true)] + #[case::bad_request(FailureKind::BadRequest, Some(400), false)] + #[case::forbidden(FailureKind::PermissionDenied, Some(403), false)] + #[case::server(FailureKind::InternalServer, Some(500), true)] + #[case::unreadable_status(FailureKind::Other, None, true)] + #[case::connection(FailureKind::ApiConnection, Some(500), false)] + fn cooldown_required_follows_python( + #[case] kind: FailureKind, + #[case] status: Option, + #[case] expected: bool, + ) { + assert_eq!( + is_cooldown_required(&AttemptError::new(kind, status)), + expected + ); + } + + /// An exception with no `status_code` is Python's status `""`, which no rule cools down. + #[rstest] + fn an_empty_status_requires_no_cooldown() { + let mut failure = AttemptError::new(FailureKind::Other, None); + failure.status_absent = true; + assert!(!is_cooldown_required(&failure)); + } + + #[rstest] + #[case::midnight(0, "00-00")] + #[case::afternoon(13 * 3600 + 7 * 60 + 59, "13-07")] + fn current_minute_is_utc_hours_and_minutes(#[case] seconds: u64, #[case] expected: &str) { + let time = UNIX_EPOCH + Duration::from_secs(86_400 * 3 + seconds); + assert_eq!(current_minute(time), expected); + } + + #[rstest] + #[case::content_policy_first(&["ContentPolicyViolationError", "BadRequestError"], Some(1.0))] + #[case::bad_request(&["BadRequestError"], Some(2.0))] + #[case::unnamed(&["Timeout"], None)] + fn a_deployment_policy_matches_in_python_order( + #[case] classes: &[&str], + #[case] expected: Option, + ) { + let policy = serde_json::json!({ + "BadRequestErrorAllowedFails": 2, + "ContentPolicyViolationErrorAllowedFails": 1, + }); + let mut failure = AttemptError::new(FailureKind::BadRequest, Some(400)); + failure.classes = classes.iter().map(|class| (*class).into()).collect(); + assert_eq!( + deployment_allowed_fails(policy.as_object(), &failure), + expected + ); + } + + fn deployment(id: &str, info: serde_json::Value) -> DeploymentSpec { + let mut model_info = serde_json::json!({"id": id}); + model_info + .as_object_mut() + .unwrap() + .extend(info.as_object().unwrap().clone()); + serde_json::from_value(serde_json::json!({ + "model_name": id, + "litellm_params": {"model": format!("openai/{id}")}, + "model_info": model_info, + })) + .unwrap() + } + + fn health() -> Health { + Health::new( + Arc::new(InMemoryRouterCache::default()), + Arc::new(SystemClock), + ) + } + + fn settings(dynamic: RouterDynamicConfig) -> Settings { + Settings::new(&RouterConfig::default(), Arc::new(dynamic)) + } + + #[rstest] + #[case::held(false, false, 1, true)] + #[case::caller_scoped(false, true, 1, false)] + #[case::outside_the_deployment(true, false, 0, false)] + #[tokio::test] + async fn the_failure_exits_decide_what_is_counted_and_cooled( + #[case] outside_deployment: bool, + #[case] caller_scoped: bool, + #[case] counted: u64, + #[case] cooled: bool, + ) { + let health = health(); + let deployment = Deployment::from_spec(deployment("a", serde_json::json!({}))).unwrap(); + let mut failure = AttemptError::new(FailureKind::RateLimit, Some(429)); + failure.outside_deployment = outside_deployment; + failure.caller_scoped = caller_scoped; + + let cooldown = health + .record_failure( + &settings(RouterDynamicConfig::default()), + &deployment, + GroupShape::default(), + None, + &failure, + ) + .await + .unwrap(); + + assert_eq!(cooldown.is_some(), cooled); + assert_eq!(health.outcomes_this_minute("a").await.unwrap().1, counted); + } + + #[rstest] + #[case::authentication( + FailureKind::CallerCredentialAuthentication, + 401, + "AuthenticationError" + )] + #[case::rate_limit(FailureKind::CallerCredentialRateLimit, 429, "RateLimitError")] + #[tokio::test] + async fn a_caller_credential_failure_counts_without_cooling( + #[case] kind: FailureKind, + #[case] status: u16, + #[case] base_class: &str, + ) { + let health = health(); + let deployment = Deployment::from_spec(deployment("a", serde_json::json!({}))).unwrap(); + let failure = AttemptError::new(kind, Some(status)); + + let cooldown = health + .record_failure( + &settings(RouterDynamicConfig::default()), + &deployment, + GroupShape::default(), + None, + &failure, + ) + .await + .unwrap(); + + assert_eq!(cooldown, None); + assert!(failure.is_a(base_class)); + assert_eq!(health.outcomes_this_minute("a").await.unwrap().1, 1); + } + + /// `litellm.allowed_fails` written after the build: the copied 3 starts counting instead of + /// the failure-ratio rule, which cools a 429 down at once. + #[rstest] + #[case::still_the_process_default(true, true)] + #[case::the_process_default_moved(false, false)] + #[tokio::test] + async fn the_copied_allowed_fails_counts_once_it_differs_from_the_process_default( + #[case] allowed_fails_is_default: bool, + #[case] cooled: bool, + ) { + let settings = settings(RouterDynamicConfig { + allowed_fails: Some(3), + allowed_fails_is_default, + ..RouterDynamicConfig::default() + }); + let deployment = Deployment::from_spec(deployment("a", serde_json::json!({}))).unwrap(); + let failure = AttemptError::new(FailureKind::RateLimit, Some(429)); + + let cooldown = health() + .record_failure( + &settings, + &deployment, + GroupShape::default(), + None, + &failure, + ) + .await + .unwrap(); + + assert_eq!(cooldown.is_some(), cooled); + } + + fn team(id: &str, team_id: &str, blocked: bool) -> DeploymentSpec { + deployment( + id, + serde_json::json!({"team_id": team_id, "team_public_model_name": "tp", "blocked": blocked}), + ) + } + + #[rstest] + #[case::a_sibling(team("b", "t1", false), true)] + #[case::a_blocked_sibling(team("b", "t1", true), false)] + #[case::another_teams_deployment(team("b", "t2", false), false)] + #[case::no_team(deployment("b", serde_json::json!({})), false)] + fn a_team_deployment_has_alternatives_under_its_public_name( + #[case] other: DeploymentSpec, + #[case] expected: bool, + ) { + let registry = Registry::build( + vec![team("a", "t1", false), other], + BTreeMap::new(), + Vec::new(), + ) + .unwrap(); + let first = registry.deployment("a").unwrap(); + assert_eq!(team_model_has_alternatives(®istry, &first), expected); + } + + #[rstest] + #[case::spans_two_deployments(&["a", "b"], "rg", true)] + #[case::one_deployment(&["a"], "rg", false)] + #[case::through_its_alias(&["a", "b"], "alias", true)] + #[case::a_member_called_directly(&["a", "b"], "a", false)] + fn a_routing_group_has_alternatives_past_one_deployment( + #[case] members: &[&str], + #[case] requested: &str, + #[case] expected: bool, + ) { + let group: RoutingGroupSpec = serde_json::from_value(serde_json::json!({ + "group_name": "rg", "models": members, "routing_strategy": "simple-shuffle", + })) + .unwrap(); + let registry = Registry::build( + vec![ + deployment("a", serde_json::json!({})), + deployment("b", serde_json::json!({})), + ], + BTreeMap::from([("alias".to_owned(), "rg".to_owned())]), + vec![group], + ) + .unwrap(); + assert_eq!( + routing_group_has_alternatives(®istry, requested), + expected + ); + } + + /// An empty status is counted and cools nothing down, unless the deployment's own policy + /// names the error. + #[rstest] + #[case::no_policy(serde_json::json!({}), false)] + #[case::policy_names_the_error( + serde_json::json!({"allowed_fails_policy": {"BadRequestErrorAllowedFails": 0}}), + true + )] + #[tokio::test] + async fn an_empty_status_on_the_attempt_path_needs_the_deployments_policy_to_cool( + #[case] info: serde_json::Value, + #[case] cooled: bool, + ) { + let health = health(); + let deployment = Deployment::from_spec(deployment("a", info)).unwrap(); + let mut failure = AttemptError::new(FailureKind::BadRequest, None); + failure.status_absent = true; + + let cooldown = health + .record_failure( + &settings(RouterDynamicConfig::default()), + &deployment, + GroupShape::default(), + None, + &failure, + ) + .await + .unwrap(); + + assert_eq!(cooldown.is_some(), cooled); + assert_eq!(health.outcomes_this_minute("a").await.unwrap().1, 1); + } + + #[rstest] + #[case::the_deployments_own_model(None, "openai/a")] + #[case::a_filled_wildcard(Some("openai/gpt-4o"), "openai/gpt-4o")] + #[tokio::test] + async fn usage_is_keyed_by_the_model_served(#[case] model: Option<&str>, #[case] keyed: &str) { + let cache = InMemoryRouterCache::default(); + let clock = Arc::new(SystemClock); + let health = Health::new(Arc::new(cache.clone()), clock.clone()); + let deployment = Deployment::from_spec(deployment("a", serde_json::json!({}))).unwrap(); + + health + .add_usage(&deployment, model, 15.0, 1.0) + .await + .unwrap(); + + let minute = current_minute(clock.now()); + assert_eq!( + ( + cache.get(&usage_key("a", keyed, UsageMetric::Tpm, &minute)), + cache.get(&usage_key("a", keyed, UsageMetric::Rpm, &minute)), + ), + (Some(serde_json::json!(15)), Some(serde_json::json!(1))), + ); + } + + #[rstest] + fn keys_match_python() { + assert_eq!( + ( + cooldown_key("abc"), + allowed_fails_key("abc", Some("generic")), + usage_key("abc", "openai/gpt-4o", UsageMetric::Tpm, "09-05"), + ), + ( + "deployment:abc:cooldown".to_owned(), + "deployment:abc:allowed_fails:generic".to_owned(), + "global_router:abc:openai/gpt-4o:tpm:09-05".to_owned(), + ) + ); + } +} diff --git a/litellm-rust/crates/router-core/src/health_routing.rs b/litellm-rust/crates/router-core/src/health_routing.rs new file mode 100644 index 00000000000..bc3e43a6e92 --- /dev/null +++ b/litellm-rust/crates/router-core/src/health_routing.rs @@ -0,0 +1,126 @@ +//! Health-check-driven routing: the background health checks' results, kept in the shared +//! [`RouterCache`](crate::cache::RouterCache) under one key as Python's `DeploymentHealthCache` +//! writes them, and the filter `_async_filter_health_check_unhealthy_deployments` / +//! `_filter_health_check_unhealthy_deployments` run before the cooldown filter. + +use std::{collections::BTreeSet, sync::Arc, time::UNIX_EPOCH}; + +use serde_json::Value; + +use crate::{health::Health, registry::Deployment, settings::Settings}; + +/// `DeploymentHealthCache.CACHE_KEY`. +pub const HEALTH_STATE_KEY: &str = "litellm:health_check:deployment_health_state"; + +/// `_extract_unhealthy_ids`: the ids marked unhealthy whose result is younger than `staleness`. +pub fn unhealthy_ids(raw: Option<&Value>, now: f64, staleness: f64) -> BTreeSet { + let Some(Value::Object(states)) = raw else { + return BTreeSet::new(); + }; + states + .iter() + .filter(|(_, state)| { + let Value::Object(state) = state else { + return false; + }; + // `not state.get("is_healthy", True)`: any falsy value is unhealthy. + let unhealthy = match state.get("is_healthy") { + None => false, + Some(Value::Null) => true, + Some(Value::Bool(value)) => !value, + Some(Value::Number(value)) => value.as_f64() == Some(0.0), + Some(Value::String(value)) => value.is_empty(), + Some(Value::Array(value)) => value.is_empty(), + Some(Value::Object(value)) => value.is_empty(), + }; + let timestamp = state + .get("timestamp") + .and_then(Value::as_f64) + .unwrap_or(0.0); + unhealthy && now - timestamp < staleness + }) + .map(|(id, _)| id.clone()) + .collect() +} + +/// What the filter does when it would leave nothing. +#[derive(Clone, Copy, Debug, PartialEq, Eq)] +pub enum WhenAllUnhealthy { + /// The safety net: every candidate is kept. + KeepAll, + /// A health check probe sees no deployment. + Nothing, +} + +impl Health { + /// The deployments the background health checks have not marked unhealthy, as the + /// router's health-check routing settings say. + pub async fn health_check_filter( + &self, + settings: &Settings, + deployments: Vec>, + when_all_unhealthy: WhenAllUnhealthy, + ) -> Vec> { + if !settings.enable_health_check_routing { + return deployments; + } + let scoped = settings.background_health_check_model_groups.as_deref(); + // With an allowed_fails_policy cooldowns are the only exclusion, unless the filter is + // scoped to listed groups. + if settings.allowed_fails_policy.is_some() && scoped.is_none() { + return deployments; + } + // A read that fails counts as no health state. + let raw = self + .cache() + .async_get_cache(HEALTH_STATE_KEY) + .await + .ok() + .flatten(); + let now = self + .now_time() + .duration_since(UNIX_EPOCH) + .map(|elapsed| elapsed.as_secs_f64()) + .unwrap_or_default(); + let unhealthy = unhealthy_ids( + raw.as_ref(), + now, + settings.health_check_staleness.as_secs_f64(), + ); + if unhealthy.is_empty() { + return deployments; + } + let filtered: Vec> = deployments + .iter() + .filter(|d| { + !unhealthy.contains(&d.id) + || scoped.is_some_and(|groups| !groups.contains(&d.model_name)) + }) + .cloned() + .collect(); + match (filtered.is_empty(), when_all_unhealthy) { + (false, _) => filtered, + (true, WhenAllUnhealthy::KeepAll) => deployments, + (true, WhenAllUnhealthy::Nothing) => Vec::new(), + } + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + #[rstest] + #[case::fresh_unhealthy(json!({"a": {"is_healthy": false, "timestamp": 95.0}}), vec!["a"])] + #[case::stale(json!({"a": {"is_healthy": false, "timestamp": 50.0}}), vec![])] + #[case::healthy(json!({"a": {"is_healthy": true, "timestamp": 95.0}}), vec![])] + #[case::no_flag(json!({"a": {"timestamp": 95.0}}), vec![])] + #[case::not_a_dict(json!({"a": 1}), vec![])] + fn unhealthy_ids_follow_python(#[case] raw: Value, #[case] expected: Vec<&str>) { + let ids = unhealthy_ids(Some(&raw), 100.0, 10.0); + assert_eq!(ids.iter().map(String::as_str).collect::>(), expected); + } +} diff --git a/litellm-rust/crates/router-core/src/host.rs b/litellm-rust/crates/router-core/src/host.rs new file mode 100644 index 00000000000..0a72be8f980 --- /dev/null +++ b/litellm-rust/crates/router-core/src/host.rs @@ -0,0 +1,726 @@ +//! [`Host`]: the router core's only boundary. Everything the core needs from the embedding +//! process goes through it, and every attempt runs through [`Host::invoke`]: the core never runs +//! an operation itself. `PythonHost` serves it in a Python process (attempts call `litellm.`, +//! and the deployment build asks it for secrets, validation, providers and side effects). + +use std::{collections::BTreeMap, sync::Arc, time::Duration}; + +use async_trait::async_trait; +use serde::Deserialize; +use serde_json::{Map, Value}; + +use crate::{ + cache::RouterCache, + config::{Op, RetryPolicy, RoutingStrategy}, + error::{AttemptError, Error, FailureKind, Payload}, + fallback::Fallbacks, + health::Health, + mock::MockFailure, + outcome::OutcomeCallbacks, + precall::PreCallFacts, + prerouting::{PreRoute, PreRouted}, + registry::{Deployment, Registry}, + settings::Settings, + strategy::StrategyScope, +}; + +/// One call into the router. +#[derive(Clone, Debug, Default)] +pub struct RouterRequest { + /// The requested name: a model group, alias, routing group, deployment id or wildcard match. + pub model: String, + /// The request params, for the plugins and host steps that read them. + pub body: Value, + /// `user_api_key_team_id`, from the first metadata bucket that holds one + /// (`get_request_team_id`). + pub team_id: Option, + /// The `metadata` bucket's `user_api_key_team_id` alone: the team a failed level lists the + /// group's deployments for (`async_function_with_fallbacks_common_utils`, + /// `_stream_order_levels`). `None` lists every team's. + pub listing_team_id: Option, + /// The caller's `user_role` is `proxy_admin`. + pub proxy_admin: bool, + /// The caller's `models` plus `team_models` (`user_api_key_auth`), which narrow a caller + /// allowed only through access groups to those groups' deployments. + pub allowed_models: Vec, + /// For a proxy admin, the model the request names (`model`, else the metadata + /// `model_group`), which keeps one team's deployments listed under it (`filter_team_based_models`). + pub admin_model: Option, + pub specific_deployment: bool, + /// A per-request `num_retries`, which wins over the router's. + pub num_retries: Option, + /// A per-request `num_retries` that is no count, which replaces the router's as well. + pub uncounted_retries: Option, + pub disable_fallbacks: bool, + /// `_router_weights` as the request passed it: model group to deployment id to weight, + /// validated when simple-shuffle picks ([`crate::weights::validate`]). + pub router_weights: Option, + /// The deployment a call on an existing resource (a video id) names: picked whenever the + /// filters keep it (`_narrow_to_video_deployment`). + pub pinned_deployment_id: Option, + /// A per-request `routing_strategy` override, as Python normalizes it. + pub routing_strategy: Option, + /// Whether tag routing may apply to this request (router, request or model setting), so the + /// host's tag stage runs. + pub filter_tags: bool, + /// A pass-through pick: only `use_in_pass_through` deployments may serve it. + pub pass_through: Option, + /// `_target_order`: the order level to pick from instead of the lowest. + pub target_order: Option, + /// `_excluded_deployment_ids`: never picked, even when that leaves nothing. + pub excluded_ids: Vec, + /// `_retry_skipped_deployment_ids`: skipped unless that leaves nothing. + pub retry_skipped_ids: Vec, + /// The endpoint `endpoint_selection` names around the call, which deployments that declare + /// `enforce_supported_endpoints` may refuse ([`crate::eligibility`]). + pub endpoint: Option, + /// A web search request on an async pick: `filter_web_search_deployments` drops the + /// deployments that declare no support. The sync pick never runs that filter. + pub web_search: bool, + /// The handler name of a call only some providers serve (`_ROUTE_CAPABILITY_RESOLVERS`): + /// the deployments whose provider cannot serve it are dropped unless that leaves nothing. + pub route_handler: Option, + /// A Decisions call carrying audio or videos: the deployments that refuse them are skipped + /// unless that leaves nothing (`_without_decisions_deployments_refusing_media`). + pub decisions_media: bool, + /// `f"{provider}/{model}"` for a lookup that cannot ask the host + /// (`_core_get_routable_deployments`); a pick asks [`Host::provider_request`]. + pub wildcard_request: Option, + /// The request carries an image (`_request_carries_image`), so deployments that declare no + /// vision are skipped while any other remains. + pub has_image: bool, + /// An async pick: the host's pre-routing step runs before each pick resolves its name. + pub pre_routes: bool, + /// Which of the router's outcome callbacks run for this request. + pub outcome_callbacks: OutcomeCallbacks, + /// The requested name is no model group (a search tool name): nothing is selected, every + /// attempt is handed to the host as is, and no outcome is recorded for a deployment + /// (`_asearch_with_fallbacks`, whose helper picks among the router's search tools). + pub unrouted: bool, + /// `passthrough_on_no_deployment`: a pick that fails hands the attempt to the host under the + /// requested name, inside the level's retries and fallbacks, with no outcome recorded for a + /// deployment (`_ageneric_api_call_with_fallbacks_helper`). + pub passthrough_on_no_deployment: bool, + /// The endpoint's attempt stamps no `failed_deployment_id` on its error (file and batch + /// creation, whose result belongs to the deployment that served it), so weighted failover + /// never runs for it. + pub skip_weighted_failover: bool, + /// The request creates or names a resource only one provider holds (a file upload, a batch + /// on an uploaded file): it falls back within its own model group only + /// (`run_async_fallback`'s `same_model_group_only`). + pub same_group_fallbacks_only: bool, + /// Fallback lists the request passed (`Some(None)` when it passed `None`), which replace + /// the router's. + pub fallbacks: Option>, + pub context_window_fallbacks: Option>, + pub content_policy_fallbacks: Option>, + /// A per-request `max_fallbacks`, which replaces the router's. + pub max_fallbacks: Option, + /// A per-request `cooldown_time`: the call's own params carry it, so it cools a failed + /// deployment down for that long unless its `model_info` sets one. + pub cooldown_time: Option, + /// A `mock_testing_*` flag the request set. + pub mock_failure: Option, + /// A per-request `model_group_retry_policy`, which replaces the router's. + pub model_group_retry_policy: Option>, + /// The model groups whose `model_group_retry_policy` lookup raises (the policy is no mapping + /// of policies, or the group's entry is not one): the first failure of a hop serving one ends + /// the hop with the host's error instead ([`RouterEvent::RetryPolicyRaised`]), no retry. + pub retry_policy_raises: Vec, + /// `health_check_probe`: a health check's own pick, which sees no deployment when every + /// one is marked unhealthy (the safety net keeps them all for any other request). + pub health_check_probe: bool, + /// What the host needs to run the call itself, such as the Python kwargs. + pub payload: Option, +} + +/// A per-request `num_retries` that is no count of retries. `async_function_with_retries` only +/// reads it once a hop's first failure was not taken over by a retry policy: a call that succeeds +/// first time never does. +#[derive(Clone, Copy, Debug, PartialEq, Eq, Deserialize)] +#[serde(rename_all = "snake_case")] +pub enum UncountedRetries { + /// A negative int: `num_retries > 0` is false, so the failure stands, and a stream's plain + /// budget is spent (`isinstance(num_retries, int)`). + Negative, + /// Any other value `num_retries > 0` is false for (a negative float, a NaN): the failure + /// stands, and a stream falls through to the deployment's budget, then the router's. + NotPositive, + /// `num_retries > 0` or `range(num_retries)` raises (a string, a positive float): the hop ends + /// with that error ([`RouterEvent::RetryCountRaised`]). + Raises, +} + +/// One `os.environ/` reference the deployment build found ([`crate::build`]). +#[derive(Clone, Debug, PartialEq, Eq)] +pub struct SecretRef { + /// The value as written, `os.environ/`. + pub name: String, + /// Where the value sits in the deployment. + pub at: SecretAt, +} + +/// Where a [`SecretRef`] sits in a deployment. +#[derive(Clone, Debug, PartialEq, Eq)] +pub enum SecretAt { + /// A top-level `litellm_params` value: resolved through the host's secret manager. + Param(String), + /// `litellm_params.dataSources[source].parameters[key]` (`endpoint` or `key`): read from the + /// environment alone, empty when unset. + DataSource { source: usize, key: String }, +} + +/// Which of the router's adds a build runs. +#[derive(Clone, Copy, Debug, PartialEq, Eq, strum::IntoStaticStr, strum::EnumString)] +#[strum(serialize_all = "snake_case")] +pub enum BuildPath { + /// `set_model_list` (and the constructor's list): config entries, one deployment per + /// organization, ignored when invalid if the router ignores invalid deployments. + Create, + /// `add_deployment` (and upserts): one validated deployment. + Add, +} + +/// What the build asks the host about one deployment. +#[derive(Clone, Debug)] +pub struct BuildAsk<'a> { + pub path: BuildPath, + /// The entry's position in the list the build was given. + pub index: usize, + /// The entry as the build holds it: `model_name`, `litellm_params` (secrets resolved, the + /// organization of this deployment set), `model_info` (with its `id`) and any other keys. + pub entry: &'a Map, + /// The `model_info.id` the entry declared, before the build assigned one. + pub declared_id: Option<&'a str>, + /// Another entry of the same list declares the same id. + pub duplicate_id: bool, +} + +/// The host's answer about one deployment. +#[derive(Clone, Debug, PartialEq)] +pub enum Built { + Entry(Map), + /// Left out without an error (`model_info.supported_environments` excludes this one, or an + /// `add_deployment` id that already exists). + Skip, + /// The host failed the deployment and the router ignores invalid deployments. + Invalid, +} + +/// The host's provider answer. +#[derive(Clone, Debug, PartialEq, Eq)] +pub enum Provided { + Provider(Option), + Invalid, +} + +/// What the model-info merge ([`crate::model_info`]) asks the host while it answers one query. +/// Asked at query time, so a price reload or a registration the host made since the router was +/// built is what the next query reads. +#[derive(Clone, Debug, PartialEq, serde::Serialize)] +#[serde(tag = "lookup", rename_all = "snake_case")] +pub enum ModelInfoLookup { + /// The process cost map's row for `model` (`get_model_info(model=...)`), the host choosing + /// the keys it tries. Answered with the row, or `None`. A lookup that raises propagates, + /// unless `tolerate` is set: then the host answers `{"failed": True}`. `exact` also asks + /// whether the row came from a fallback-generalization rule (`{"row": ..., "generalized": + /// bool}`). + ModelInfo { + model: Value, + tolerate: bool, + exact: bool, + }, + /// The raw cost-map entry under `key` (`model_cost.get(key)`): answered with + /// `{"entry": value}`, or `None` when the key is absent. `process` reads the process global + /// (`litellm.model_cost`) rather than the host's live settings, where the Python router does. + CostEntry { key: String, process: bool }, + /// `get_llm_provider` for the queried deployment's `model` and validated params: answered + /// with `[model, provider]`. + Provider { model: String }, + /// The deployments a wildcard pattern routes `name` to: answered with `[{id, model}]`, or + /// `None` when no pattern matches. + PatternModels { name: String }, + /// The base model a bedrock model id names (`get_bedrock_base_model`). + BedrockBase { model_id: String }, + /// The limits the background model-info refresh discovered for deployment `id`. + Discovered { id: Value }, + /// The queried deployment's own `model_info`, read when the merge reaches it (a malformed one + /// raises there). + UserModelInfo, + /// A log record, emitted where the Python router logs it. + Log { level: LogLevel, message: String }, + /// Group info: deployment `index`'s validated params (`LiteLLM_Params(**litellm_params)`, which + /// raises on bad params): answered with `{"model", "configurable_clientside_auth_params"}`. + GroupParams { index: usize }, + /// Group info: what the host knows of deployment `index` serving `model`: answered with + /// `{"model_info"}` (its merged model info, `None` when that fails), `"mapped"` + /// (`deployment_is_catalog_mapped`), `"litellm_model"` and `"llm_provider"`, and, when it has + /// no model info, `"supported_openai_params"`. + GroupDeployment { index: usize, model: Value }, + /// Group info: deployment `index`'s capabilities under `model_info`: answered with + /// `{"supported_endpoints"}` (empty when the team may not use it), `"supports_fast_mode"` and + /// `"reasoning_efforts"` (`resolve_supported_reasoning_efforts`, or `None`). + GroupCapabilities { + index: usize, + model_info: Value, + litellm_model: Value, + llm_provider: Value, + mapped: bool, + }, + /// Group info: the group's first deployment as the host builds it (`ModelGroupInfo(**info)`, + /// whose validation may raise): answered with the fields the merge compares, as validated. + GroupSeed { info: Map }, + /// `intersect_supported_reasoning_efforts(current, resolved)`, in the host's advertisement order. + ReasoningIntersect { current: Value, resolved: Value }, +} + +#[derive(Clone, Copy, Debug, PartialEq, Eq, serde::Serialize)] +#[serde(rename_all = "snake_case")] +pub enum LogLevel { + Debug, + Error, +} + +/// One attempt against one deployment. +#[derive(Clone, Debug)] +pub struct Attempt { + pub op: Op, + pub request: Arc, + pub deployment: Arc, + /// The name this attempt resolved: the requested name, or the fallback target. + pub name: String, + /// The model group being served, after fallbacks. + pub model_group: String, + /// The `order` level an order fallback targets in the same group. + pub target_order: Option, + /// Every deployment `name` resolved to for this caller, the picked one included. + pub candidate_ids: Vec, + /// 0 for the first attempt in this group, then the retry number. + pub retry: u32, + pub fallback_depth: u32, + /// How many fallbacks deep the chain is: 0 for the requested name. + pub fallback_level: u32, + pub timeout: Option, + /// Request params the fallback chain's dict targets merged in (`kwargs.update(target)`). + pub params: Option>>, + /// The chain level whose request metadata this attempt carries (see [`RouterEvent::Fallback`]). + pub scope: u32, + /// The retry budget the level's loop stamps on the request before this attempt. + pub max_retries: u32, + /// How many deployments `get_model_list` lists for the level's group (`model_group_size`). + pub model_group_size: usize, +} + +/// What a successful attempt returns. +#[derive(Clone, Debug)] +pub struct Output { + pub value: Payload, + /// Prompt plus completion tokens, counted against the deployment's per-minute usage. + pub total_tokens: u64, + /// A response the provider blocked, which the router may raise to fall back. + pub blocked: Option, + /// A stream the host reports the outcome of when it ends ([`crate::Router::report_success`], + /// [`crate::Router::report_failure`]), or a realtime session, whose success the host counts + /// only when it ended cleanly: the attempt counts its request and `total_tokens` now, and no + /// success. + pub deferred: bool, + /// Whether the attempt counts against the deployment's per-minute usage, when the host knows + /// better than the deployment's own limits ([`Deployment::tracks_usage`]): a limit only the + /// model catalog sets (`_deployment_tracks_usage`), or a realtime session, whose `None` + /// response counts nothing (`increment_deployment_usage_for_response`). + pub tracks_usage: Option, +} + +/// How a provider blocked a response the call otherwise served. +#[derive(Clone, Copy, Debug, PartialEq, Eq, strum::IntoStaticStr, strum::EnumString)] +#[strum(serialize_all = "snake_case")] +pub enum Blocked { + /// A chat response whose first choice was content-filtered (or that has no choices). + ContentFilter, + /// An Anthropic /v1/messages safeguard refusal carrying `stop_details`. + Refusal, +} + +/// What a plugin or strategy sees: never the router itself. +pub struct RoutingContext<'a> { + pub registry: &'a Registry, + pub settings: &'a Settings, + pub health: &'a Health, + pub request: &'a RouterRequest, + pub op: &'a Op, + pub model_group: &'a str, + /// The name the request resolved from (Python's `model`), which strategies key state by. + pub name: &'a str, + /// Whose selector a strategy stage reads. + pub scope: StrategyScope, + /// The deployments the name resolved to for this caller, before health filters + /// (`request_deployments`), for the tag stage. + pub pool: &'a [Arc], + /// `_excluded_deployment_ids` a weighted failover hop put on the request, which the callback + /// filters read (`deployment_ids_failed_in_request`). + pub excluded_ids: &'a [String], + /// `_retry_skipped_deployment_ids` the retry loop put on the request, as `excluded_ids`. + pub skipped_ids: &'a [String], + /// `_target_order` as the filters read it: the level an order fallback targets, else the one + /// the request named. + pub target_order: Option, +} + +/// Which selection step the host is asked to run. +#[derive(Clone, Debug, PartialEq)] +pub enum SelectStage { + /// Pre-call checks and sub-routers registered as plugins: return the deployments that remain. + Plugins, + /// A strategy not yet ported: return the candidates with the pick first. + Strategy(RoutingStrategy), + /// Tag routing (`get_deployments_for_tag`), not yet ported: return the deployments that remain. + Tags, + /// `_deployment_declares_no_vision`: return the candidates that declare no vision support. + TextOnly, + /// `_deployment_serves_route`: return the candidates whose provider cannot serve the call + /// `handler` names (a Decisions call on a provider with no Decisions config). + RouteIncapable { handler: String }, + /// `_decisions_deployment_refuses_media`: return the candidates that refuse the audio or + /// videos a Decisions call carries. + MediaRefusing, +} + +/// Routing events, delivered through [`Host::observe`]. +#[derive(Clone, Debug, PartialEq)] +pub enum RouterEvent { + Selected { + model_group: String, + deployment_id: String, + /// How long the pick took (`_acompletion`'s `async_get_available_deployment` service event). + pick: Duration, + }, + Succeeded { + deployment_id: String, + }, + AttemptFailed { + deployment_id: String, + kind: FailureKind, + status: Option, + }, + CooldownSet { + deployment_id: String, + cooldown: Duration, + }, + Retry { + model_group: String, + retry: u32, + delay: Duration, + }, + Fallback { + from: String, + to: String, + /// The order level of `to` a same-group hop walks to. + order: Option, + depth: u32, + /// The fallback level `to` is tried at: 1 for the request's own fallbacks. + level: u32, + /// The new level's request metadata scope, copied from `parent`'s at the hop. + scope: u32, + parent: u32, + /// The `max_fallbacks` the chain reads, stamped on the hop's request. + max_fallbacks: u32, + /// The non-string `model` of the dict target this hop routes + /// ([`crate::fallback::FallbackTarget::unroutable_model`]): the hop fails on it before any + /// attempt, and the host raises what Python's level raises for that value. + unroutable: Option, + }, + /// A hop of the fallback chain returned: `log_success_fallback_event` or + /// `log_failure_fallback_event` for the level at `parent`. + FallbackDone { + from: String, + to: String, + level: u32, + scope: u32, + parent: u32, + succeeded: bool, + }, + /// The router raised a `ContentPolicyViolationError` for a blocked response, since a + /// fallback would serve it (`_should_raise_content_policy_error`, + /// `_should_raise_anthropic_refusal_error`). + Blocked { + level: u32, + model: String, + blocked: Blocked, + }, + /// `log_retry`: the router recorded a failure in `scope`'s request metadata + /// (`previous_models`, `request_retry_count`) before retrying or falling back. + RetryLogged { + scope: u32, + level: u32, + /// The group the failed level served (`kwargs["model"]`). + model: String, + /// The retry number stamped before the failed try; `None` keeps the scope's own. + attempted_retries: Option, + cause: RetryCause, + }, + /// `async_function_with_retries` opened a level's retry loop, before any pick: `scope`'s + /// request metadata tracks no retry yet, `max_retries` of them, and the group's size. + RetriesOpened { + scope: u32, + max_retries: u32, + model_group_size: usize, + }, + /// The level's first failure settled its overrides: the budget `scope` then tracks. + RetryBudget { + scope: u32, + max_retries: u32, + }, + /// A pick of the async selection or the sync one failed on `error`: the async one's `except` + /// logs every refusal to the request's logging object (`_async_get_available_deployment`). + PickFailed { + level: u32, + model: String, + error: PickError, + }, + /// A level of the fallback chain serving `model` ended on an error a pick raised (no + /// deployment for the caller, none available, a stale routing group, ...): Python raises + /// that error for the level, whatever its earlier attempts raised. + LevelFailed { + level: u32, + model: String, + error: PickError, + /// Raised by the level's fallback handling, while the level's own error was handled + /// (so it chains to that error), rather than by the level's retry loop. + handling: bool, + }, + /// The router raised a `mock_testing_*` failure for `model` instead of calling it. + MockFailed { + mock: MockFailure, + level: u32, + model: String, + num_retries: Option, + }, + /// The first failure of a hop serving `model` looked up a `model_group_retry_policy` that + /// raises for it: the hop ends with the error the lookup raised (the host raises it, from the + /// failure `cause` names), without retrying, and falls back as from any plain exception. + RetryPolicyRaised { + level: u32, + model: String, + cause: RetryCause, + }, + /// The first failure of a hop serving `model` read a request `num_retries` that raises + /// ([`UncountedRetries::Raises`]): the hop ends with that error (the host raises it, from the + /// failure `cause` names), and falls back as from any plain exception. + RetryCountRaised { + level: u32, + model: String, + cause: RetryCause, + }, + /// The level serving `model` reached the fallback handling that appends the context window + /// and content policy hints to its error, before any hop runs + /// (`async_function_with_fallbacks_common_utils`). The order path never gets there. + FallingBack { + level: u32, + model: String, + }, + /// The order fallback chain of the level at `level` served nothing, so the level raises from + /// `async_function_with_fallbacks_common_utils`' order path, with no outcome message: what the + /// chain's last hop raised when `last_hop`, else its own error (a context window error, or a + /// chain no hop of which ran). Weighted failover raising what it does not catch + /// (`_maybe_run_weighted_failover`) ends the level the same way. + OrderChainFailed { + level: u32, + last_hop: bool, + }, + /// The regular fallback handling of the level at `level` served nothing, where + /// `async_function_with_fallbacks_common_utils` reaches its `except` and logs the failure. + /// `chain` when the level had targets to walk: the error it logs is what the last hop raised + /// when `last_hop`, else its own. With no `chain`, the host decides: only the host holds + /// whether a level with no match had a fallback list at all, which Python does not log. + /// The order path and weighted failover are outside that `try` and never report this. + FallbacksFailed { + level: u32, + chain: bool, + last_hop: bool, + }, + /// A group's retry loop ran every retry and the last one failed: Python stamps + /// `num_retries` and `max_retries` on that error. + RetriesExhausted { + model_group: String, + attempted: u32, + max: u32, + /// The level the retry loop served. + level: u32, + /// The last failure was a pick's error, which the level then raises + /// ([`RouterEvent::LevelFailed`]), rather than an attempt's. + picked: bool, + }, +} + +/// A pick's error, as the events that name it carry it. +#[derive(Clone, Debug)] +pub struct PickError(pub Arc); + +impl PickError { + /// The copy of `error` events carry, when a pick raised it. + pub fn of(error: &Error) -> Option { + error.pick_copy().map(|copy| Self(Arc::new(copy))) + } +} + +impl PartialEq for PickError { + fn eq(&self, other: &Self) -> bool { + format!("{:?}", self.0) == format!("{:?}", other.0) + } +} + +/// Which error a [`RouterEvent::RetryLogged`] records. +#[derive(Clone, Debug, PartialEq)] +pub enum RetryCause { + /// The last attempt's failure. + Attempt, + /// The error the level ended on (`run_async_fallback`'s `original_exception`). + Level, + /// A pick raised this error: the group was unknown or had none available, the stale + /// routing-group member map named a group no longer configured, ... + Pick(PickError), + /// Any other error no attempt raised. + Other, +} + +impl RetryCause { + /// The cause that names `error`. + pub fn of(error: &Error) -> Self { + match error { + Error::Attempt(_) => Self::Attempt, + _ => PickError::of(error).map_or(Self::Other, Self::Pick), + } + } +} + +#[async_trait] +pub trait Host: Send + Sync { + /// Run one attempt against the picked deployment. The core records its outcome (cooldowns, + /// allowed-fails counters, usage) itself; the host only runs it. + async fn invoke(&self, attempt: &Attempt) -> Result; + + /// Run a selection stage the core does not implement. + async fn select( + &self, + stage: &SelectStage, + ctx: &RoutingContext<'_>, + candidates: Vec>, + ) -> Result>, Error>; + + /// Pre-routing before a pick resolves `ask.name`: the model group to resolve instead, a + /// custom strategy's deployment to serve, or `None` to resolve the name itself. Asked only + /// for picks that pre-route (`pre_routes`). + async fn pre_route(&self, ask: &PreRoute<'_>) -> Result, Error> { + let _ = ask; + Ok(None) + } + + /// Access and budget checks before a cross-group fallback target. + /// `Err` when a check raised: the chain ends there, outside any target's `try`. + async fn allow_fallback( + &self, + request: &RouterRequest, + target: &str, + ) -> Result; + + /// Whether `run_async_fallback` refuses a chain for one of its dict `targets`, a server-owned + /// federation field or an `oidc/` api key. The chain is walked by `level`. + async fn refuses_fallbacks(&self, _level: u32, _targets: &[Map]) -> bool { + false + } + + async fn sleep(&self, duration: Duration); + + fn observe(&self, event: &RouterEvent); + + /// The shared store routing state lives in. + fn cache(&self) -> Arc; + + /// Whether [`Self::invoke`] can run `op` on `provider`. Checked for every served op and + /// deployment when the router is built or changed, so an unsupported pair fails the config, + /// never a request. `PythonHost` runs every op. + fn supports(&self, _op: &Op, _provider: &str) -> bool { + true + } + + /// Whether [`Self::select`] can run strategies and plugins. + fn can_select(&self) -> bool { + true + } + + /// Run the routing plugins for `ctx.name` when `run` (the async pick's pre-routing hook), and + /// report the candidate models they left on the request, if any. + async fn routing_plugin_models( + &self, + _ctx: &RoutingContext<'_>, + _run: bool, + ) -> Result>, Error> { + Ok(None) + } + + /// The facts the `enable_pre_call_checks` filter decides by (token count, context windows, + /// param support), for `candidates` and the deployments in `ctx.pool`. A host without them + /// reports no input, so nothing is checked. + async fn pre_call_facts( + &self, + _ctx: &RoutingContext<'_>, + _candidates: &[Arc], + ) -> Result { + Ok(PreCallFacts::default()) + } + + /// `f"{provider}/{model}"` for `ctx.name`, which `PatternMatchRouter.get_pattern` tries when + /// no pattern matches the name itself: only the host can infer a provider. `None` from a + /// host that infers none. + async fn provider_request(&self, _ctx: &RoutingContext<'_>) -> Result, Error> { + Ok(None) + } + + /// `async_callback_filter_deployments`: the host's routing callbacks narrow `candidates` in + /// turn. A filter that raises fails the try with [`Error::Attempt`], which the call retries and + /// falls back from like any attempt failure. A host without filters keeps every candidate. + async fn callback_filters( + &self, + _ctx: &RoutingContext<'_>, + candidates: Vec>, + ) -> Result>, Error> { + Ok(candidates) + } + /// The values of `refs`, one per ref, in order: what the deployment build substitutes for + /// each `os.environ/` reference it found in entry `index` ([`crate::build`]). Asked once per + /// deployment, as the build reaches it. A host without secrets leaves every reference as + /// written. + async fn secrets(&self, index: usize, refs: &[SecretRef]) -> Result, Error> { + let _ = index; + Ok(refs.iter().map(|r| Value::String(r.name.clone())).collect()) + } + + /// Check one deployment before it is added, and answer the entry as the host normalized it, + /// a skip (the deployment is left out), or [`Built::Invalid`] (it failed and the router + /// ignores invalid deployments). A host without checks accepts the entry as given. + async fn validate(&self, ask: &BuildAsk<'_>) -> Result { + Ok(Built::Entry(ask.entry.clone())) + } + + /// The provider that serves one validated deployment (`get_llm_provider`), `None` for one + /// served without a provider (a prompt-management model), or [`Provided::Invalid`]. A host + /// without provider resolution answers `None`, so [`Deployment::provider`] reads the model. + async fn provider(&self, ask: &BuildAsk<'_>) -> Result { + let _ = ask; + Ok(Provided::Provider(None)) + } + + /// Run the host's side effects for an accepted deployment and answer the entry as the + /// registry stores it. A host without side effects stores the entry it validated. + async fn added(&self, ask: &BuildAsk<'_>, provider: Option<&str>) -> Result { + let _ = provider; + Ok(Built::Entry(ask.entry.clone())) + } + + /// Answer one model-info lookup ([`ModelInfoLookup`]). A host without a cost map answers + /// `None` to everything, so no deployment has model info. + async fn model_info(&self, lookup: &ModelInfoLookup) -> Result { + let _ = lookup; + Ok(Value::Null) + } +} diff --git a/litellm-rust/crates/router-core/src/host_index.rs b/litellm-rust/crates/router-core/src/host_index.rs new file mode 100644 index 00000000000..3748f7b4d19 --- /dev/null +++ b/litellm-rust/crates/router-core/src/host_index.rs @@ -0,0 +1,727 @@ +//! [`HostIndexes`]: the registry indexes the Python router hands out, kept the way it keeps them. +//! +//! The Python router keeps its indexes by history rather than deriving them from the deployment +//! list: `model_names` is the set of names `set_model_list` was given (invalid entries included), +//! `deployment_names` only ever grows, assigning `model_list` reindexes nothing, a removal shifts +//! the positions every index holds (a caller-written one included), and the wildcard pattern +//! routers keep the copy of a deployment they were given. The registry keeps one of these per +//! version and applies those rules on its own writes; the host reads them back as the live +//! objects `registry().index()`, `names()` and `patterns()` return, and hands a caller's write to +//! any of them back as a changeset ([`IndexWrite`]). +//! +//! Values are JSON so whatever a caller wrote reads back as written, junk included. + +use serde::{Deserialize, Serialize}; +use serde_json::{Map, Value}; + +/// One wildcard pattern router (`PatternMatchRouter`): regex to the deployments it routes to, +/// most specific pattern first. +#[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize)] +#[serde(transparent)] +pub struct PatternRouter { + pub patterns: Vec<(String, Vec)>, +} + +/// The indexes, as the host reads and writes them. +#[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize)] +#[serde(default)] +pub struct HostIndexes { + /// `model_id_to_deployment_index_map`: id to position, in insertion order. + pub id_map: Map, + /// `model_name_to_deployment_indices`: name to its positions. + pub model_name: Map, + /// `team_model_to_deployment_indices`: `[team_id, public name, positions]`. + pub team_model: Vec<(String, String, Value)>, + /// `model_names`: a set, its members in the order they joined. + pub model_names: Vec, + pub deployment_names: Vec, + pub team_public_model_names: Vec, + pub provider_default_ids: Vec, + /// `pattern_router`. + pub patterns: PatternRouter, + /// `team_pattern_routers`: team id to its router. + pub team_patterns: Vec<(String, PatternRouter)>, +} + +/// A host write to the indexes: each field it names replaces the one held. +#[derive(Clone, Debug, Default, PartialEq, Deserialize)] +#[serde(default)] +pub struct IndexWrite { + pub id_map: Option>, + pub model_name: Option>, + pub team_model: Option>, + pub model_names: Option>, + pub deployment_names: Option>, + pub team_public_model_names: Option>, + pub provider_default_ids: Option>, + pub patterns: Option, + pub team_patterns: Option>, +} + +/// A removal the Python router could not finish: an index held a position it cannot compare +/// (`_without_indices` raised `TypeError`). The indexes keep what it shifted before that. +#[derive(Clone, Debug, PartialEq, Eq, thiserror::Error)] +#[error("'>' not supported between instances of '{found}' and 'int'")] +pub struct RemovalError { + pub found: &'static str, +} + +impl HostIndexes { + /// Apply a host write. + pub fn write(&mut self, write: IndexWrite) { + let IndexWrite { + id_map, + model_name, + team_model, + model_names, + deployment_names, + team_public_model_names, + provider_default_ids, + patterns, + team_patterns, + } = write; + if let Some(value) = id_map { + self.id_map = value; + } + if let Some(value) = model_name { + self.model_name = value; + } + if let Some(value) = team_model { + self.team_model = value; + } + if let Some(value) = model_names { + self.model_names = unique(value); + } + if let Some(value) = deployment_names { + self.deployment_names = value; + } + if let Some(value) = team_public_model_names { + self.team_public_model_names = value; + } + if let Some(value) = provider_default_ids { + self.provider_default_ids = value; + } + if let Some(value) = patterns { + self.patterns = value; + } + if let Some(value) = team_patterns { + self.team_patterns = value; + } + } + + /// `set_model_list` starting over: the id, name and team indexes and the team routers go; + /// the deployment names, the wildcard router and the provider default ids stay. + pub fn reset(&mut self) { + self.id_map.clear(); + self.model_name.clear(); + self.team_model.clear(); + self.team_patterns.clear(); + self.team_public_model_names.clear(); + } + + /// `set_model_list`'s `model_names`: the names it was given. + pub fn set_model_names(&mut self, names: Vec) { + self.model_names = unique(names.into_iter().map(Value::String).collect()); + } + + /// A deployment joined the list at `position` (`_add_deployment` then + /// `_add_model_to_list_and_index_map`); `add` is `add_deployment`, which also names its group. + pub fn added(&mut self, entry: &Map, position: usize, add: bool) { + let params = entry.get("litellm_params").and_then(Value::as_object); + let info = entry.get("model_info").and_then(Value::as_object); + let model_name = entry.get("model_name").and_then(Value::as_str); + let id = info + .and_then(|info| info.get("id")) + .filter(|id| !id.is_null()); + self.deployment_names.push( + params + .and_then(|params| params.get("model")) + .cloned() + .unwrap_or(Value::Null), + ); + if let Some(name) = model_name.filter(|name| name.contains('*')) { + self.patterns.add(name, Value::Object(entry.clone())); + if let Some(id) = id.and_then(Value::as_str).filter(|id| !id.is_empty()) { + self.provider_default_ids.push(id.to_owned()); + } + } + let team_id = info + .and_then(|info| info.get("team_id")) + .filter(|v| !v.is_null()); + let public = info + .and_then(|info| info.get("team_public_model_name")) + .filter(|v| !v.is_null()); + if let (Some(team_id), Some(Value::String(public))) = (team_id, public) + && public.contains('*') + { + let team = python_str(team_id); + let router = match self.team_patterns.iter_mut().find(|(t, _)| *t == team) { + Some((_, router)) => router, + None => { + self.team_patterns.push((team, PatternRouter::default())); + &mut self.team_patterns.last_mut().expect("just pushed").1 + } + }; + router.add(public, Value::Object(entry.clone())); + } + let position = Value::from(position); + if let Some(id) = id { + self.id_map.insert(python_str(id), position.clone()); + } + if let Some(name) = model_name.filter(|name| !name.is_empty()) { + push_position( + self.model_name + .entry(name.to_owned()) + .or_insert_with(|| Value::Array(Vec::new())), + &position, + ); + } + if add { + let name = Value::String(model_name.unwrap_or_default().to_owned()); + if !self.model_names.contains(&name) { + self.model_names.push(name); + } + } + // `_update_team_model_index`: a truthy team id and public name. + if let (Some(team_id), Some(public)) = (team_id, public) + && truthy(team_id) + && truthy(public) + { + let (team, public) = (python_str(team_id), python_str(public)); + if !self.team_public_model_names.contains(&public) { + self.team_public_model_names.push(public.clone()); + } + let held = match self + .team_model + .iter_mut() + .find(|(t, p, _)| *t == team && *p == public) + { + Some((_, _, held)) => held, + None => { + self.team_model + .push((team, public, Value::Array(Vec::new()))); + &mut self.team_model.last_mut().expect("just pushed").2 + } + }; + if let Value::Array(positions) = held + && !positions.contains(&position) + { + positions.push(position); + } + } + } + + /// The deployment `id` left the list from `position` (`_update_deployment_indices_after_removal`). + pub fn removed(&mut self, id: &str, position: usize) -> Result<(), RemovalError> { + let mut id_map = Map::new(); + for (key, held) in std::mem::take(&mut self.id_map) { + if key == id { + continue; + } + let shifted = shift(&held, position)?.unwrap_or(held); + id_map.insert(key, shifted); + } + self.id_map = id_map; + let names: Vec = self.model_name.keys().cloned().collect(); + for name in names { + let kept = without(&self.model_name[&name], position)?; + if kept.is_empty() { + self.model_name.remove(&name); + self.model_names + .retain(|held| held.as_str() != Some(name.as_str())); + } else { + self.model_name.insert(name, Value::Array(kept)); + } + } + let mut team_model = Vec::new(); + let held = std::mem::take(&mut self.team_model); + let mut rest = held.into_iter(); + for (team, public, positions) in rest.by_ref() { + match without(&positions, position) { + Ok(kept) if kept.is_empty() => {} + Ok(kept) => team_model.push((team, public, Value::Array(kept))), + Err(error) => { + team_model.push((team, public, positions)); + team_model.extend(rest); + self.team_model = team_model; + return Err(error); + } + } + } + self.team_model = team_model; + let mut publics: Vec = Vec::new(); + for (_, public, _) in &self.team_model { + if !publics.contains(public) { + publics.push(public.clone()); + } + } + self.team_public_model_names = publics; + self.patterns.remove(id); + for (_, router) in &mut self.team_patterns { + router.remove(id); + } + self.team_patterns + .retain(|(_, router)| !router.patterns.is_empty()); + Ok(()) + } + + /// Whether the id map holds `id` (`_has_model_id`). + pub fn has_id(&self, id: &str) -> bool { + self.id_map.contains_key(id) + } + + /// What the id map holds for `id`, as written (`model_id_to_deployment_index_map.get(id)`). + pub fn id_entry(&self, id: &str) -> Option<&Value> { + self.id_map.get(id) + } + + /// What the name index holds for `name`, as written. + pub fn named(&self, name: &str) -> Option<&Value> { + self.model_name.get(name) + } + + /// What the team index holds for `(team, public)`, as written. + pub fn team_named(&self, team: &str, public: &str) -> Option<&Value> { + self.team_model + .iter() + .find(|(t, p, _)| t == team && p == public) + .map(|(_, _, positions)| positions) + } + + /// `team_public_model_names_of`: the public names the team index holds for `team`. + pub fn team_public_names_of(&self, team: &str) -> Vec { + let mut names: Vec = Vec::new(); + for (t, public, _) in &self.team_model { + if t == team && !names.contains(public) { + names.push(public.clone()); + } + } + names + } + + /// The position the id map holds for `id`, when it is a position. + pub fn position_of(&self, id: &str) -> Option { + self.id_map + .get(id) + .and_then(Value::as_u64) + .and_then(|position| usize::try_from(position).ok()) + } +} + +impl PatternRouter { + /// `add_pattern`: a new regex joins in specificity order (a stable sort, most specific + /// first); a known one gains the deployment. + pub fn add(&mut self, pattern: &str, deployment: Value) { + let regex = pattern_to_regex(pattern); + if let Some((_, deployments)) = self.patterns.iter_mut().find(|(held, _)| *held == regex) { + deployments.push(deployment); + return; + } + self.patterns.push((regex, vec![deployment])); + self.patterns + .sort_by_key(|(regex, _)| std::cmp::Reverse(regex_specificity(regex))); + } + + /// `remove_deployment`: every deployment with this id goes, and so does a pattern left empty. + pub fn remove(&mut self, id: &str) { + for (_, deployments) in &mut self.patterns { + deployments.retain(|deployment| { + deployment + .get("model_info") + .and_then(|info| info.get("id")) + .and_then(Value::as_str) + != Some(id) + }); + } + self.patterns + .retain(|(_, deployments)| !deployments.is_empty()); + } + + /// `route`: the deployments of the first pattern `request` matches, each a copy whose + /// `litellm_params.model` takes the parts the wildcards matched; `filtered` keeps to the + /// patterns of those names. + pub fn route(&self, request: &str, filtered: Option<&[String]>) -> Option> { + let filtered: Option> = + filtered.map(|names| names.iter().map(|name| pattern_to_regex(name)).collect()); + for (regex, deployments) in &self.patterns { + if filtered + .as_ref() + .is_some_and(|names| !names.contains(regex)) + { + continue; + } + let Some(groups) = regex_match(regex, request) else { + continue; + }; + let mut routed = Vec::with_capacity(deployments.len()); + for deployment in deployments { + let mut copy = deployment.clone(); + let model = deployment + .get("litellm_params") + .and_then(|params| params.get("model")); + let Some(Value::String(model)) = model else { + // `deployment["litellm_params"]["model"]` raising ends the route with None. + return None; + }; + let named = deployment_model_name(&groups, request, model); + if model.contains('*') + && let Some(params) = + deployment.get("litellm_params").and_then(Value::as_object) + && let Some(info) = copy.get_mut("model_info").and_then(Value::as_object_mut) + { + for flag in cache_flags_left_to_the_catalog(params) { + info.remove(*flag); + } + } + if let Some(params) = copy + .get_mut("litellm_params") + .and_then(Value::as_object_mut) + { + params.insert("model".to_owned(), Value::String(named)); + } + routed.push(copy); + } + return Some(routed); + } + None + } + + /// `get_models_by_pattern`'s pick: the first (request, pattern) pair that matches, trying + /// `model` against every pattern, then `provider/model`. + pub fn models_by_pattern(&self, requests: &[String]) -> Option> { + for request in requests { + for (regex, deployments) in &self.patterns { + if let Some(groups) = regex_match(regex, request) { + return Some( + deployments + .iter() + .filter_map(|deployment| { + deployment + .get("litellm_params") + .and_then(|params| params.get("model")) + .and_then(Value::as_str) + .map(|model| deployment_model_name(&groups, request, model)) + }) + .collect(), + ); + } + } + } + None + } +} + +/// `_cache_flags_left_to_the_catalog`: the `model_info` flags a wildcard deployment does not speak +/// for on the models it matches. An azure_ai wildcard's `supports_prompt_cache_breakpoint` does. +/// `inferred_provider` names `azure_ai` only for a model carrying that prefix. +pub(crate) fn cache_flags_left_to_the_catalog( + params: &Map, +) -> &'static [&'static str] { + let provider = params + .get("custom_llm_provider") + .filter(|provider| truthy(provider)) + .and_then(Value::as_str) + .or_else(|| { + params + .get("model") + .and_then(Value::as_str) + .and_then(|model| model.split_once('/')) + .map(|(prefix, _)| prefix) + }); + if provider == Some("azure_ai") { + &["supports_prompt_caching"] + } else { + &[ + "supports_prompt_cache_breakpoint", + "supports_prompt_caching", + ] + } +} + +/// `re.escape(pattern).replace(r"\*", "(.*)")`. +pub fn pattern_to_regex(pattern: &str) -> String { + let mut regex = String::new(); + for c in pattern.chars() { + match c { + '*' => regex.push_str("(.*)"), + '(' | ')' | '[' | ']' | '{' | '}' | '?' | '+' | '-' | '|' | '^' | '$' | '\\' | '.' + | '&' | '~' | '#' | ' ' | '\t' | '\n' | '\r' | '\x0b' | '\x0c' => { + regex.push('\\'); + regex.push(c); + } + _ => regex.push(c), + } + } + regex +} + +/// `PatternUtils.calculate_pattern_specificity`: the regex's length, then how much regex syntax +/// it has. +pub fn regex_specificity(regex: &str) -> (usize, usize) { + let complexity = regex + .chars() + .filter(|c| matches!(c, '*' | '+' | '?' | '\\' | '^' | '$' | '|' | '(' | ')')) + .count(); + (regex.chars().count(), complexity) +} + +/// A pattern regex read back as its literal runs between wildcards, or None when it holds regex +/// syntax `pattern_to_regex` never writes (a caller wrote it). +fn literal_runs(regex: &str) -> Option> { + let mut runs = vec![String::new()]; + let mut chars = regex.chars().peekable(); + while let Some(c) = chars.next() { + match c { + '\\' => runs.last_mut()?.push(chars.next()?), + '(' => { + let rest: String = chars.by_ref().take(3).collect(); + if rest != ".*)" { + return None; + } + runs.push(String::new()); + } + '.' | '*' | '+' | '?' | '[' | ']' | '{' | '}' | '|' | '^' | '$' | ')' => return None, + other => runs.last_mut()?.push(other), + } + } + Some(runs) +} + +/// `re.match(regex, request)` for a pattern regex: anchored at the start only, each `(.*)` +/// greedy. The groups it captured, or None when it does not match. +pub fn regex_match(regex: &str, request: &str) -> Option> { + let runs = literal_runs(regex)?; + let rest = request.strip_prefix(runs[0].as_str())?; + let mut groups = Vec::new(); + greedy(&runs[1..], rest, &mut groups).then_some(groups) +} + +/// Match `runs` (each a literal that follows a group) against `rest`, longest group first. +fn greedy(runs: &[String], rest: &str, groups: &mut Vec) -> bool { + let Some((literal, later)) = runs.split_first() else { + return true; + }; + let mut ends: Vec = rest.char_indices().map(|(at, _)| at).collect(); + ends.push(rest.len()); + for &end in ends.iter().rev() { + let (group, after) = rest.split_at(end); + let Some(after) = after.strip_prefix(literal.as_str()) else { + continue; + }; + groups.push(group.to_owned()); + if greedy(later, after, groups) { + return true; + } + groups.pop(); + } + false +} + +/// `set_deployment_model_name`: the deployment's model with each wildcard replaced by the group +/// matched for it, the request itself when more groups matched than it has wildcards. +pub fn deployment_model_name(groups: &[String], request: &str, model: &str) -> String { + if !model.contains('*') { + return model.to_owned(); + } + if groups.len() > model.matches('*').count() { + return request.to_owned(); + } + let mut named = model.to_owned(); + for group in groups { + named = named.replacen('*', group, 1); + } + named +} + +fn unique(values: Vec) -> Vec { + let mut kept: Vec = Vec::with_capacity(values.len()); + for value in values { + if !kept.contains(&value) { + kept.push(value); + } + } + kept +} + +fn push_position(held: &mut Value, position: &Value) { + if let Value::Array(positions) = held { + positions.push(position.clone()); + } +} + +/// Python's truthiness for a JSON value. +pub(crate) fn truthy(value: &Value) -> bool { + match value { + Value::Null => false, + Value::Bool(flag) => *flag, + Value::Number(number) => number.as_f64() != Some(0.0), + Value::String(text) => !text.is_empty(), + Value::Array(items) => !items.is_empty(), + Value::Object(items) => !items.is_empty(), + } +} + +/// Python's `str()` for an id or team id. +pub(crate) fn python_str(value: &Value) -> String { + match value { + Value::String(text) => text.clone(), + Value::Bool(true) => "True".to_owned(), + Value::Bool(false) => "False".to_owned(), + Value::Null => "None".to_owned(), + other => other.to_string(), + } +} + +fn type_name(value: &Value) -> &'static str { + match value { + Value::Null => "NoneType", + Value::Bool(_) => "bool", + Value::Number(number) if number.is_f64() => "float", + Value::Number(_) => "int", + Value::String(_) => "str", + Value::Array(_) => "list", + Value::Object(_) => "dict", + } +} + +/// `idx - 1 if idx > removal_idx else idx`: None keeps `held` as is. +fn shift(held: &Value, position: usize) -> Result, RemovalError> { + let removal = position as f64; + let number = match held { + Value::Bool(flag) => f64::from(u8::from(*flag)), + Value::Number(number) => number.as_f64().unwrap_or_default(), + other => { + return Err(RemovalError { + found: type_name(other), + }); + } + }; + if number <= removal { + return Ok(None); + } + Ok(Some(match held { + Value::Number(n) if n.is_i64() || n.is_u64() => Value::from(n.as_i64().unwrap_or(0) - 1), + _ => Value::from(number - 1.0), + })) +} + +/// `_without_indices`: the positions without `position`, the later ones shifted down. +fn without(held: &Value, position: usize) -> Result, RemovalError> { + let Value::Array(positions) = held else { + return Ok(Vec::new()); + }; + let removal = Value::from(position); + let mut kept = Vec::with_capacity(positions.len()); + for index in positions { + if *index == removal { + continue; + } + kept.push(shift(index, position)?.unwrap_or_else(|| index.clone())); + } + Ok(kept) +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + fn entry(name: &str, id: &str, model: &str) -> Map { + serde_json::from_value(json!({ + "model_name": name, + "litellm_params": {"model": model}, + "model_info": {"id": id}, + })) + .unwrap() + } + + #[test] + fn removal_shifts_every_index_and_drops_emptied_names() { + let mut indexes = HostIndexes::default(); + indexes.added(&entry("gpt", "a", "openai/a"), 0, false); + indexes.added(&entry("gpt", "b", "openai/b"), 1, false); + indexes.added(&entry("claude", "c", "anthropic/c"), 2, false); + indexes.set_model_names(vec!["gpt".into(), "claude".into(), "broken".into()]); + indexes.removed("a", 0).unwrap(); + assert_eq!( + indexes.id_map, + json!({"b": 0, "c": 1}).as_object().unwrap().clone() + ); + assert_eq!(indexes.model_name["gpt"], json!([0])); + indexes.removed("c", 1).unwrap(); + assert!(!indexes.model_name.contains_key("claude")); + assert_eq!(indexes.model_names, vec![json!("gpt"), json!("broken")]); + assert_eq!(indexes.deployment_names.len(), 3); + } + + #[test] + fn a_pattern_routes_with_the_matched_parts() { + let mut router = PatternRouter::default(); + router.add( + "llmengine/*", + json!({"litellm_params": {"model": "openai/*"}, "model_info": {"id": "w"}}), + ); + router.add( + "*meta.llama3*", + json!({"litellm_params": {"model": "bedrock/meta.llama3*"}, "model_info": {"id": "m"}}), + ); + let routed = router.route("llmengine/foo", None).unwrap(); + assert_eq!(routed[0]["litellm_params"]["model"], "openai/foo"); + let routed = router.route("hello-world-meta.llama3-70b", None).unwrap(); + assert_eq!( + routed[0]["litellm_params"]["model"], + "hello-world-meta.llama3-70b" + ); + assert_eq!( + regex_match(r"a(.*)b(.*)", "axbyb").unwrap(), + vec!["xby", ""] + ); + router.remove("w"); + assert!(router.route("llmengine/foo", None).is_none()); + } + + #[rstest] + #[case::any_wildcard( + json!({"model": "openai/*"}), + json!({"id": "w", "keep": 1}), + )] + #[case::azure_ai_keeps_the_breakpoint_flag( + json!({"model": "azure_ai/*"}), + json!({"id": "w", "keep": 1, "supports_prompt_cache_breakpoint": true}), + )] + #[case::azure_ai_named_by_custom_llm_provider( + json!({"model": "*", "custom_llm_provider": "azure_ai"}), + json!({"id": "w", "keep": 1, "supports_prompt_cache_breakpoint": true}), + )] + #[case::a_fixed_model_speaks_for_itself( + json!({"model": "openai/gpt-4o"}), + json!({ + "id": "w", + "keep": 1, + "supports_prompt_cache_breakpoint": true, + "supports_prompt_caching": true, + }), + )] + fn a_wildcard_leaves_the_cache_flags_to_the_catalog( + #[case] params: Value, + #[case] expected: Value, + ) { + let mut router = PatternRouter::default(); + router.add( + "any/*", + json!({ + "litellm_params": params, + "model_info": { + "id": "w", + "keep": 1, + "supports_prompt_cache_breakpoint": true, + "supports_prompt_caching": true, + }, + }), + ); + let routed = router.route("any/gpt-4o", None).unwrap(); + assert_eq!(routed[0]["model_info"], expected); + } +} diff --git a/litellm-rust/crates/router-core/src/lib.rs b/litellm-rust/crates/router-core/src/lib.rs index 05d95d02c84..5f15b6b8df0 100644 --- a/litellm-rust/crates/router-core/src/lib.rs +++ b/litellm-rust/crates/router-core/src/lib.rs @@ -43,21 +43,706 @@ //! - `call(op, request)`: select, run the attempt, and retry or fall back until it succeeds or the //! policy is exhausted. //! -//! # Execution -//! Each attempt resolves an `Executor` after a deployment is picked. A Rust-native operation runs -//! its `inference-*` route machine in-process; anything else goes through `Host::invoke`. A -//! started attempt is never replayed on a different executor. +//! # Hosts: the only boundary +//! The core reaches outside itself only through [`Host`], and every attempt runs through +//! `Host::invoke`: the core picks the deployment, the host runs the call, the core records the +//! outcome. There is no second, "native" attempt path in the core. Which code runs an attempt is +//! the host's business: +//! - `PythonHost` (inside a Python process) builds the request for the picked deployment and calls +//! `litellm.`. It never calls back into a Python router. //! -//! # Hosts -//! `Host` is what the embedding process provides: `invoke` for non-native operations, `select` -//! for strategies and sub-routers not yet ported, `allow_fallback` for access and budget checks, -//! `sleep`, `observe` for routing events, and `cache`, a DualCache-style store that holds all -//! routing state under the same keys, encodings and TTLs the Python router uses. `PythonHost` -//! serves them from the existing Python code when the router runs inside Python; `NativeHost` -//! serves them in the Rust server, where an operation without a Rust implementation makes the -//! config fail at build time, never partway through a request. +//! An op or provider a host cannot run fails `Host::supports` when the router is built or +//! changed, never partway through a request. +//! +//! The core also builds its deployments through the host ([`build`]): for each configured entry +//! it finds the secret references and asks `secrets`, then `validate`, `provider` and `added`. +//! +//! Besides `invoke` and `supports`, a host provides `select` for strategies and plugins not yet +//! ported, `allow_fallback` for access and budget checks, `refuses_fallbacks` for a chain's dict +//! targets, `sleep`, `observe` for routing events, and `cache`, a DualCache-style store that +//! holds all routing state under the same keys, encodings and TTLs the Python router uses. The +//! core writes cooldowns, allowed-fails counters and usage itself, through that cache. //! //! # Plugins //! Routing strategies, pre-call checks and sub-routers (auto, complexity, quality, adaptive) //! register through `register_plugin` and see a `RoutingContext` (registry, settings, health and //! the current request), never the router itself. +//! +//! # Modules +//! - [`registry`]: deployments and their indices, `deployment_id`, `ChangeSet`. +//! - [`config`] / [`settings`]: static and dynamic config, and the frozen `Settings` view. +//! - [`cache`] / [`health`]: the shared routing cache, cooldowns and usage. +//! - [`select`]: resolve, filter chain, simple-shuffle. +//! - [`call`]: retries and fallbacks. +//! - [`eligibility`]: the endpoints a deployment refuses to serve. +//! - [`precall`]: the `enable_pre_call_checks` filter. +//! - [`model_info`]: model info merged from the cost map, asked of the host at query time. +//! - [`host`]: the `Host` boundary. + +pub mod access; +pub mod build; +pub mod cache; +pub mod call; +pub mod config; +pub mod eligibility; +pub mod error; +pub mod fallback; +pub mod group_info; +pub mod health; +pub mod health_routing; +pub mod host; +pub mod host_index; +pub mod lookup; +pub mod mock; +pub mod model_info; +pub mod outcome; +pub mod precall; +pub mod prerouting; +pub mod ptu; +pub mod registry; +pub mod resolve; +pub mod retry; +pub mod routing_groups; +pub mod routing_plugins; +pub mod select; +pub mod settings; +pub mod strategy; +pub mod weights; + +use std::sync::{ + Arc, + atomic::{AtomicBool, Ordering}, +}; + +use arc_swap::ArcSwap; +use parking_lot::Mutex; + +pub use crate::{ + cache::{InMemoryRouterCache, RouterCache}, + call::RouterResponse, + config::{Op, RouterConfig, RouterDynamicConfig, RoutingStrategy}, + error::{AttemptError, ConfigError, Error, FailureKind, Payload, Unsupported}, + health::{Clock, Health, Outcome, SystemClock}, + host::{ + Attempt, Blocked, BuildAsk, BuildPath, Built, Host, Output, Provided, RetryCause, + RouterEvent, RouterRequest, RoutingContext, SecretAt, SecretRef, SelectStage, + }, + outcome::{OutcomeCallbacks, OutcomeWrite}, + prerouting::{PreRoute, PreRouted}, + registry::{ChangeSet, Deployment, DeploymentSpec, Registry, RegistryVersion}, + select::{Randomness, SeededRandomness, ThreadRandomness}, + settings::Settings, +}; +use crate::{ + health::{GroupShape, routing_group_has_alternatives, team_model_has_alternatives}, + registry::DeploymentFilter, + select::SelectInputs, +}; + +/// The registry and settings one call reads, swapped atomically by `apply`. +pub(crate) struct RouterStateSnapshot { + pub registry: Arc, + pub settings: Arc, +} + +impl RouterStateSnapshot { + /// `_get_routing_context` for a pick of `name`: unless the request overrides the strategy, + /// a stale member map naming a group no longer configured raises `KeyError(group)`. + pub(crate) fn missing_routing_group( + &self, + request: &RouterRequest, + name: &str, + ) -> Result<(), Error> { + if strategy::request_override(request.routing_strategy.as_deref()).is_some() { + return Ok(()); + } + match self.registry.missing_member_group(name) { + Some(group) => Err(Error::MissingRoutingGroup { + group: group.to_owned(), + }), + None => Ok(()), + } + } +} + +pub(crate) struct Core { + host: Arc, + rng: Arc, + health: Health, + config: RouterConfig, + snapshot: ArcSwap, + writer: Mutex<()>, + retired: AtomicBool, +} + +impl Core { + /// Reject what this host cannot serve, before any request. + fn validate(&self, registry: &Registry, settings: &Settings) -> Result<(), ConfigError> { + let can_select = self.host.can_select(); + let strategies = std::iter::once(&settings.routing_strategy).chain( + registry + .routing_groups() + .iter() + .map(|group| &group.routing_strategy), + ); + for strategy in strategies { + if !strategy.is_native() && !can_select { + return Err(Unsupported::Strategy(strategy.clone()).into()); + } + } + if let Some(plugin) = settings.plugins.first() + && !can_select + { + return Err(Unsupported::Plugin(plugin.name.clone()).into()); + } + for deployment in registry.deployments(&DeploymentFilter::default()) { + self.validate_deployment(&deployment)?; + } + Ok(()) + } + + /// Reject a deployment whose provider this host cannot run a served op on. + fn validate_deployment(&self, deployment: &Deployment) -> Result<(), ConfigError> { + for op in &self.config.served_ops { + if !self.host.supports(op, deployment.provider()) { + return Err(Unsupported::Op { + op: op.clone(), + provider: deployment.provider().to_owned(), + } + .into()); + } + } + Ok(()) + } +} + +/// How a reported failure is recorded. +#[derive(Clone, Debug, Default)] +pub struct FailureReport { + /// Cool down for the deployment's own `cooldown_time` (then the provider's retry-after), + /// as the failure callback does, rather than the router default. + pub deployment_cooldown: bool, + /// The `cooldown_time` the failed call's own params carried (`model_info`, then + /// `litellm_params`), which wins over the provider's retry-after for a callback report. + pub cooldown_time: Option, + /// Count the failure only: its status is one no cooldown rule reads (an empty status). + pub count_only: bool, + /// The model group the request was for, whose fallbacks keep a lone deployment cooling. + pub requested_group: Option, + /// Cool down without counting the failure (`set_cooldown_deployments` alone). + pub uncounted: bool, + /// Also count the failed request against the deployment's per-minute requests + /// (`async_deployment_callback_on_failure`). + pub counts_request: bool, + /// The model the request's usage is keyed by (metadata's `deployment`, which a wildcard route + /// fills), when it is not the deployment's own. + pub usage_model: Option, + /// The failure callbacks of a logged failure; a report no callback makes keeps the default. + pub callbacks: OutcomeCallbacks, +} + +/// How a reported success is recorded. +#[derive(Clone, Debug, Default)] +pub struct SuccessReport { + /// See [`host::Output::tracks_usage`]. + pub tracks_usage: Option, + /// See [`FailureReport::usage_model`]. + pub usage_model: Option, + /// See [`FailureReport::callbacks`]. + pub callbacks: OutcomeCallbacks, +} + +/// Builds a [`Router`], with test seams. +pub struct RouterBuilder { + config: RouterConfig, + dynamic: RouterDynamicConfig, + host: Arc, + rng: Arc, + clock: Arc, +} + +impl RouterBuilder { + #[must_use] + pub fn randomness(self, rng: Arc) -> Self { + Self { rng, ..self } + } + + #[must_use] + pub fn clock(self, clock: Arc) -> Self { + Self { clock, ..self } + } + + pub fn build(self) -> Result { + let registry = Registry::build( + self.config.model_list.clone(), + self.dynamic.model_alias_map.clone(), + self.config.routing_groups.clone(), + )? + .with_member_groups(self.config.routing_group_members.clone()); + let settings = Settings::new(&self.config, Arc::new(self.dynamic)); + let core = Core { + health: Health::new(self.host.cache(), self.clock), + host: self.host, + rng: self.rng, + config: self.config, + snapshot: ArcSwap::from_pointee(RouterStateSnapshot { + registry: Arc::new(Registry::default()), + settings: Arc::new(settings.clone()), + }), + writer: Mutex::new(()), + retired: AtomicBool::new(false), + }; + core.validate(®istry, &settings)?; + core.snapshot.store(Arc::new(RouterStateSnapshot { + registry: Arc::new(registry), + settings: Arc::new(settings), + })); + Ok(Router { + core: Arc::new(core), + }) + } +} + +/// The router: the entry points `litellm.Router` delegates to. +#[derive(Clone)] +pub struct Router { + core: Arc, +} + +impl Router { + pub fn new( + config: RouterConfig, + dynamic: RouterDynamicConfig, + host: Arc, + ) -> Result { + Self::builder(config, dynamic, host).build() + } + + pub fn builder( + config: RouterConfig, + dynamic: RouterDynamicConfig, + host: Arc, + ) -> RouterBuilder { + RouterBuilder { + config, + dynamic, + host, + rng: Arc::new(ThreadRandomness), + clock: Arc::new(SystemClock), + } + } + + fn live(&self) -> Result<(), Error> { + if self.core.retired.load(Ordering::Acquire) { + return Err(Error::Retired); + } + Ok(()) + } + + /// Select, run the attempt, and retry or fall back until it succeeds or the policy is + /// exhausted. + pub async fn call(&self, op: Op, request: RouterRequest) -> Result { + self.live()?; + self.core.call(op, Arc::new(request)).await + } + + /// Resolve, filter and pick a deployment without calling it. + pub async fn select(&self, op: &Op, request: &RouterRequest) -> Result, Error> { + self.live()?; + let snapshot = self.core.snapshot.load_full(); + routing_plugins::refuse_sync_pick( + snapshot.settings.routing_plugins, + &snapshot.settings.routing_strategy, + request, + )?; + let routed = self + .core + .pre_routed(PreRoute { + op, + request, + name: &request.model, + fallback_depth: 0, + retry: 0, + }) + .await?; + let name = match routed { + PreRouted::Model(name) => name, + PreRouted::Deployment(deployment) => return Ok(deployment), + }; + snapshot.missing_routing_group(request, &name)?; + let candidates = self + .core + .candidates(&snapshot, op, request, &name, &SelectInputs::default()) + .await?; + self.core.pick(&snapshot, op, request, &candidates).await + } + + /// The deployments a pick for `request` would choose among: resolved, team- and + /// cooldown-filtered, through the plugins and the lowest `order`. + pub async fn healthy( + &self, + op: &Op, + request: &RouterRequest, + ) -> Result { + self.live()?; + let snapshot = self.core.snapshot.load_full(); + let candidates = self + .core + .candidates( + &snapshot, + op, + request, + &request.model, + &SelectInputs::default(), + ) + .await?; + // `_core_async_get_healthy_deployments` raises when nothing is left. + if candidates.healthy.is_empty() { + return Err(Error::NoHealthyDeployments { + model: candidates.failed_model(&snapshot.registry), + }); + } + Ok(candidates) + } + + pub fn registry(&self) -> Arc { + self.core.snapshot.load().registry.clone() + } + + pub fn settings(&self) -> Arc { + self.core.snapshot.load().settings.clone() + } + + pub fn health(&self) -> &Health { + &self.core.health + } + + /// Record an outcome the router did not see itself, such as a health check. Returns whether + /// the deployment was cooled down. + pub async fn report(&self, id: &str, outcome: Outcome) -> Result { + match outcome { + Outcome::Success { total_tokens } => self + .report_success(id, total_tokens as f64, 1.0, SuccessReport::default()) + .await + .map(|_| false), + Outcome::Failure(failure) => self + .report_failure(id, &failure, FailureReport::default()) + .await + .map(|cooldown| cooldown.is_some()), + } + } + + /// A success a logging callback saw (`deployment_callback_on_success`): counted for a + /// configured deployment, with its tokens and requests when it tracks usage. Returns the + /// success counter's key, or `None` for an unknown deployment. + pub async fn report_success( + &self, + id: &str, + total_tokens: f64, + requests: f64, + report: SuccessReport, + ) -> Result, Error> { + report + .callbacks + .record( + OutcomeWrite::Success, + self.reported_success(id, total_tokens, requests, &report), + ) + .await + } + + async fn reported_success( + &self, + id: &str, + total_tokens: f64, + requests: f64, + report: &SuccessReport, + ) -> Result, Error> { + let snapshot = self.core.snapshot.load_full(); + let Some(deployment) = snapshot.registry.deployment(id) else { + return Ok(None); + }; + let key = self.core.health.count_success(id).await?; + if report + .tracks_usage + .unwrap_or_else(|| deployment.tracks_usage()) + { + self.core + .health + .add_usage( + &deployment, + report.usage_model.as_deref(), + total_tokens, + requests, + ) + .await?; + } + Ok(Some(key)) + } + + /// `sync_deployment_callback_on_success`: count a success against `id`, configured or not, + /// and return the counter's key. + pub async fn count_success( + &self, + id: &str, + callbacks: OutcomeCallbacks, + ) -> Result, Error> { + callbacks + .record(OutcomeWrite::Success, async { + self.core.health.count_success(id).await.map(Some) + }) + .await + } + + /// A failure the router did not see itself: counted against `id` (known or not), then + /// cooled down by the rules (`record_failure`, `deployment_callback_on_failure`). Returns the + /// cooldown applied, if any. + pub async fn report_failure( + &self, + id: &str, + failure: &AttemptError, + report: FailureReport, + ) -> Result, Error> { + report + .callbacks + .record( + OutcomeWrite::Failure, + self.reported_failure(id, failure, &report), + ) + .await + } + + async fn reported_failure( + &self, + id: &str, + failure: &AttemptError, + report: &FailureReport, + ) -> Result, Error> { + if !report.uncounted && !failure.outside_deployment { + self.core.health.count_failure(id).await?; + } + let snapshot = self.core.snapshot.load_full(); + let Some(deployment) = snapshot.registry.deployment(id) else { + return Ok(None); + }; + if report.counts_request { + self.core + .health + .count_failed_request(&deployment, report.usage_model.as_deref()) + .await?; + } + if failure.outside_deployment { + return Ok(None); + } + // An empty status is no cooldown (`_is_cooldown_required`), unless the deployment's + // own policy names the error. + if report.count_only + && crate::health::deployment_allowed_fails( + deployment.model_info.allowed_fails_policy.as_ref(), + failure, + ) + .is_none() + { + return Ok(None); + } + let cooldown = if report.deployment_cooldown { + report + .cooldown_time + .filter(|seconds| *seconds >= 0.0) + .and_then(|seconds| std::time::Duration::try_from_secs_f64(seconds).ok()) + .or(failure.retry_after) + .unwrap_or(snapshot.settings.cooldown_time) + } else { + snapshot.settings.cooldown_time + }; + let shape = GroupShape { + single_deployment: snapshot + .registry + .group(&deployment.model_name) + .is_some_and(|group| group.len() == 1) + && !report + .requested_group + .as_deref() + .is_some_and(|group| routing_group_has_alternatives(&snapshot.registry, group)) + && !team_model_has_alternatives(&snapshot.registry, &deployment), + has_fallback_group: snapshot + .settings + .dynamic + .fallback_targets(&[report + .requested_group + .as_deref() + .unwrap_or(&deployment.model_name)]) + .is_some(), + }; + self.core + .health + .cool_down_after(&snapshot.settings, &deployment, shape, failure, cooldown) + .await + } + + /// Apply one change set atomically and return the new registry version. + pub fn apply(&self, changes: ChangeSet) -> Result { + let _writer = self.core.writer.lock(); + let current = self.core.snapshot.load_full(); + let aliases = changes + .settings + .as_ref() + .map(|dynamic| dynamic.model_alias_map.clone()); + let registry = current.registry.apply(&changes, aliases)?; + let settings = match changes.settings { + Some(dynamic) => Settings::new(&self.core.config, Arc::new(dynamic)), + None => Settings::clone(¤t.settings), + }; + self.core.validate(®istry, &settings)?; + let version = registry.version(); + self.core.snapshot.store(Arc::new(RouterStateSnapshot { + registry: Arc::new(registry), + settings: Arc::new(settings), + })); + Ok(version) + } + + /// `get_router_model_info` for one deployment, its cost-map reads asked of the host now + /// ([`model_info::router_model_info`]). + pub async fn router_model_info( + &self, + query: &model_info::RouterModelInfoQuery, + ) -> Result, Error> { + model_info::router_model_info(self.core.host.as_ref(), query).await + } + + /// `_set_model_group_info` for the deployments `query` names ([`group_info::model_group_info`]). + pub async fn model_group_info( + &self, + query: &group_info::GroupInfoQuery, + ) -> Result, Error> { + group_info::model_group_info(self.core.host.as_ref(), query).await + } + + /// `get_configured_token_limits` for deployment `id` ([`group_info::configured_token_limits`]). + pub async fn configured_token_limits( + &self, + id: serde_json::Value, + configured: &serde_json::Map, + ) -> Result<(Option, Option), Error> { + group_info::configured_token_limits(self.core.host.as_ref(), id, configured).await + } + + /// `get_model_listing_info` over a listed name's deployments ([`group_info::model_listing_info`]). + pub async fn model_listing_info( + &self, + deployments: &[serde_json::Value], + ) -> Result { + group_info::model_listing_info(self.core.host.as_ref(), deployments).await + } + + /// `get_deployment_model_info` for deployment `model_id` serving `model_name` + /// ([`model_info::deployment_model_info`]). + pub async fn deployment_model_info( + &self, + model_id: &str, + model_name: &serde_json::Value, + ) -> Result>, Error> { + model_info::deployment_model_info(self.core.host.as_ref(), model_id, model_name).await + } + + /// Build `entries` through the host ([`build::build`]), installing each deployment it + /// accepts as soon as it does, as `install` says: a replace empties the registry first (and + /// takes `set_model_list`'s `model_names` once every entry is built), an append or upsert + /// adds at the end. When a step fails, what was installed before it stays, as the Python + /// router keeps the deployments it added before the one that raised. + /// + /// The build installs into a registry of its own, indexed in place, and serves it once it + /// ends (or fails), so n deployments build in O(n). A write that lands while it runs (a step + /// answer that applies a changeset) is kept: what the build installed is added over it. + pub async fn build( + &self, + path: BuildPath, + entries: Vec>, + resolve_secrets: bool, + install: build::Install, + ) -> Result, Error> { + let model_names: Vec = entries + .iter() + .map(|entry| match entry.get("model_name") { + Some(serde_json::Value::String(name)) => name.clone(), + None | Some(serde_json::Value::Null) => "None".to_owned(), + Some(other) => other.to_string(), + }) + .collect(); + let replace = install == build::Install::Replace; + let base = self.core.snapshot.load_full().registry.clone(); + let mut working = if replace { + base.emptied() + } else { + Registry::clone(&base) + }; + let mut installed: Vec = Vec::new(); + let add = path == BuildPath::Add; + let core = &self.core; + let built = build::build( + core.host.as_ref(), + path, + entries, + resolve_secrets, + |deployment| { + working.push_built(deployment.spec.clone(), add)?; + installed.push(deployment.spec.clone()); + core.validate_deployment(working.last().expect("just installed")) + .map_err(Error::from) + }, + ) + .await; + if built.is_ok() && replace && path == BuildPath::Create { + working.set_model_names(model_names); + } + self.serve_built(&base, working, installed, add)?; + built + } + + /// Serve the registry a build made from `base`. When another write replaced `base` while + /// the build ran, the build's deployments are added over that write instead. + fn serve_built( + &self, + base: &Arc, + built: Registry, + installed: Vec, + add: bool, + ) -> Result<(), ConfigError> { + let _writer = self.core.writer.lock(); + let current = self.core.snapshot.load_full(); + let registry = if Arc::ptr_eq(¤t.registry, base) { + built + } else { + let mut next = Registry::clone(¤t.registry); + for spec in installed { + next.push_built(spec, add)?; + } + next + }; + self.core.snapshot.store(Arc::new(RouterStateSnapshot { + registry: Arc::new(registry), + settings: current.settings.clone(), + })); + Ok(()) + } + + /// Keep the providers `from`'s host resolved for the deployments this router serves too (a + /// router rebuilt over the same deployments for new static settings). + pub fn adopt_providers(&self, from: &Self) { + let _writer = self.core.writer.lock(); + let current = self.core.snapshot.load_full(); + let registry = current + .registry + .with_providers_of(&from.core.snapshot.load().registry); + self.core.snapshot.store(Arc::new(RouterStateSnapshot { + registry: Arc::new(registry), + settings: current.settings.clone(), + })); + } + + /// Stop serving: every later call and selection fails with [`Error::Retired`]. + pub fn retire(&self) { + self.core.retired.store(true, Ordering::Release); + } +} diff --git a/litellm-rust/crates/router-core/src/lookup.rs b/litellm-rust/crates/router-core/src/lookup.rs new file mode 100644 index 00000000000..39c235d6f7b --- /dev/null +++ b/litellm-rust/crates/router-core/src/lookup.rs @@ -0,0 +1,883 @@ +//! The registry lookups the host serves as `registry()` queries, answered over the deployments and +//! the host indexes ([`crate::host_index::HostIndexes`]) the way the Python router answers them. +//! +//! A lookup answers with [`Row`]s: positions in the deployment list (each with how the row renames +//! the deployment), wildcard routes, or a position the Python list could not be read at. The host +//! turns a position into the entry object it stores, so identity and in-place reads stay its own; +//! a [`Row::Raw`] is handed back for the host to index its list by, which raises exactly where the +//! Python router's own read raised (an index a caller wrote junk into). + +use std::sync::Arc; + +use serde_json::{Map, Value, json}; + +use crate::{ + host_index::{HostIndexes, python_str, truthy}, + registry::{Deployment, Registry}, +}; + +/// One row of a lookup's answer. +#[derive(Clone, Debug, PartialEq)] +pub enum Row { + /// The deployment at `position`, under `name` when the row renames it (an alias or a routing + /// group), as a routing group's member `member` of `group` when `group` is set (its row drops + /// the member's `access_groups` and takes the group's priority as its `order`). + At { + position: usize, + name: Option, + group: Option<(String, String)>, + }, + /// A wildcard route: a copy of a pattern router's deployment, under `name`. + Pattern { entry: Value, name: String }, + /// A position the list cannot be read at: the host indexes its list by it, and raises. + Raw(Value), + /// A position container that is not a list: the host iterates it as its list's positions. + RawPositions(Value), +} + +impl Row { + /// The row as the host reads it. + pub fn wire(&self) -> Value { + match self { + Self::At { + position, + name, + group, + } => { + let mut row = Map::new(); + row.insert("at".to_owned(), json!(position)); + if let Some(name) = name { + row.insert("name".to_owned(), json!(name)); + } + if let Some((group, member)) = group { + row.insert("group".to_owned(), json!(group)); + row.insert("member".to_owned(), json!(member)); + } + Value::Object(row) + } + Self::Pattern { entry, name } => json!({"pattern": entry, "name": name}), + Self::Raw(value) => json!({"raw": value}), + Self::RawPositions(value) => json!({"raw_positions": value}), + } + } +} + +/// An alias `model_list` lists: its name and the group it targets (`hidden` aliases already left +/// out by the host when the whole list is asked for). +#[derive(Clone, Debug, PartialEq, serde::Deserialize)] +pub struct AliasItem { + pub alias: String, + pub target: String, +} + +/// A routing group callable by its name (the host leaves out one a deployment or an alias +/// shadows): its name and member model groups. +#[derive(Clone, Debug, PartialEq, serde::Deserialize)] +pub struct CallableGroup { + pub name: String, + pub members: Vec, +} + +/// What `get_model_list` composes beyond the deployments: the aliases and callable routing groups +/// it lists, and the wildcard requests a name no deployment serves is routed by. +#[derive(Clone, Debug, Default, PartialEq, serde::Deserialize)] +#[serde(default)] +pub struct ListScope { + pub aliases: Vec, + pub groups: Vec, + /// `get_deployments_by_pattern`'s requests: the name, then the name under its provider. + pub wildcard: Vec, + /// Only one part of the list: `"aliases"` (`_core_get_model_list_from_model_alias`) or + /// `"groups"` (`_core_get_model_list_from_routing_groups`). + pub only: Option, +} + +/// A row read for a lookup's filters: the deployment's fields as the row shows them. +struct View<'a> { + name: &'a str, + info: &'a Map, + params: &'a Map, + strips_access_groups: bool, +} + +/// The lookups over one registry version. +pub struct Lookup<'a> { + deployments: &'a [Arc], + host: &'a HostIndexes, +} + +impl<'a> Lookup<'a> { + pub fn new(registry: &'a Registry) -> Self { + Self { + deployments: registry.deployments_from(0), + host: registry.host_indexes(), + } + } + + /// `list[value]` as Python reads it: an int (or bool) in range, negative from the end. + fn position(&self, value: &Value) -> Option { + let len = i64::try_from(self.deployments.len()).ok()?; + let index = match value { + Value::Bool(flag) => i64::from(*flag), + Value::Number(number) => number.as_i64()?, + _ => return None, + }; + let index = if index < 0 { len + index } else { index }; + (0..len) + .contains(&index) + .then(|| usize::try_from(index).ok()) + .flatten() + } + + /// Every position `held` (what an index holds) names, read before any is filtered, as the + /// Python router reads them into a tuple first: `Err` with the row that raises. + fn positions(&self, held: &Value) -> Result, Row> { + let items = match held { + Value::Array(items) => items, + // Iterating an empty string or dict reads no position; anything else raises. + Value::String(text) if text.is_empty() => return Ok(Vec::new()), + Value::Object(map) if map.is_empty() => return Ok(Vec::new()), + _ => return Err(Row::RawPositions(held.clone())), + }; + items + .iter() + .map(|item| self.position(item).ok_or_else(|| Row::Raw(item.clone()))) + .collect() + } + + fn view(&self, position: usize) -> View<'a> { + let deployment = &self.deployments[position]; + View { + name: &deployment.model_name, + info: &deployment.model_info.raw, + params: &deployment.raw_params, + strips_access_groups: false, + } + } + + fn row_view<'r>(&self, row: &'r Row) -> Option> + where + 'a: 'r, + { + match row { + Row::At { + position, + name, + group, + } => { + let base = self.view(*position); + Some(View { + name: name.as_deref().unwrap_or(base.name), + strips_access_groups: group.is_some(), + ..base + }) + } + Row::Pattern { entry, name } => Some(View { + name, + info: entry + .get("model_info") + .and_then(Value::as_object) + .unwrap_or(empty()), + params: entry + .get("litellm_params") + .and_then(Value::as_object) + .unwrap_or(empty()), + strips_access_groups: false, + }), + Row::Raw(_) | Row::RawPositions(_) => None, + } + } + + // -- deployments by name ------------------------------------------------------------------- + + /// `_core_get_all_deployments`: the team's deployments under public name `model_name`, else + /// the group's, else (for a team) every deployment the name includes; each under `rename`. + pub fn all(&self, model_name: &str, team_id: Option<&str>, rename: Option<&str>) -> Vec { + let rows = |positions: Vec| -> Vec { + positions + .into_iter() + .filter(|position| should_include(model_name, &self.view(*position), team_id)) + .map(|position| Row::At { + position, + name: rename.map(str::to_owned), + group: None, + }) + .collect() + }; + if let Some(team) = team_id + && let Some(held) = self.host.team_named(team, model_name) + { + match self.positions(held) { + Ok(positions) => { + let found = rows(positions); + if !found.is_empty() { + return found; + } + } + Err(raw) => return vec![raw], + } + } + if let Some(held) = self.host.named(model_name) { + return match self.positions(held) { + Ok(positions) => rows(positions), + Err(raw) => vec![raw], + }; + } + if team_id.is_some() { + return rows((0..self.deployments.len()).collect()); + } + Vec::new() + } + + /// `_team_deployments_across_teams`: every team's deployments under public name `model`, and + /// how many distinct teams own them. + pub fn across_teams(&self, model: &str) -> (Vec, usize) { + let mut rows = Vec::new(); + for (_, public, held) in &self.host.team_model { + if public != model { + continue; + } + match self.positions(held) { + Ok(positions) => rows.extend(positions.into_iter().map(|position| Row::At { + position, + name: None, + group: None, + })), + Err(raw) => return (vec![raw], 0), + } + } + let mut teams: Vec<&Value> = Vec::new(); + for row in &rows { + if let Some(view) = self.row_view(row) + && let Some(team) = view.info.get("team_id").filter(|team| !team.is_null()) + && !teams.contains(&team) + { + teams.push(team); + } + } + let count = teams.len(); + (rows, count) + } + + /// `_core_config_deployments`: the deployments a config declared (no `db_model: true`). + pub fn config(&self) -> Vec { + (0..self.deployments.len()) + .filter(|position| { + self.view(*position).info.get("db_model") != Some(&Value::Bool(true)) + }) + .map(|position| Row::At { + position, + name: None, + group: None, + }) + .collect() + } + + /// `_core_get_model_ids`: the ids of the group's deployments, or (no group) of the id map's + /// entries, without team deployments when `exclude_team_models`. `Err` with the row that raises. + pub fn model_ids( + &self, + model_name: Option<&str>, + exclude_team_models: bool, + ) -> Result, Row> { + let kept = |view: &View<'_>| { + view.info.contains_key("id") + && !(exclude_team_models && view.info.get("team_id").is_some_and(truthy)) + }; + if let Some(name) = model_name { + let Some(held) = self.host.named(name) else { + return Ok(Vec::new()); + }; + return Ok(self + .positions(held)? + .into_iter() + .map(|position| self.view(position)) + .filter(kept) + .map(|view| python_str(&view.info["id"])) + .collect()); + } + let mut ids = Vec::new(); + for (id, held) in &self.host.id_map { + let position = self.position(held).ok_or_else(|| Row::Raw(held.clone()))?; + if kept(&self.view(position)) { + ids.push(id.clone()); + } + } + Ok(ids) + } + + // -- the model list -------------------------------------------------------------------------- + + /// `_core_get_model_list`: the name's deployments, its alias rows and routing group rows, its + /// wildcard routes when nothing else serves it, or (no name) every alias and group row and + /// then every deployment. + pub fn model_list( + &self, + model_name: Option<&str>, + team_id: Option<&str>, + scope: &ListScope, + ) -> Vec { + let only = scope.only.as_deref(); + let mut rows = Vec::new(); + if let Some(name) = model_name + && only.is_none() + { + rows.extend(self.all(name, team_id, None)); + } + let aliases: &[AliasItem] = if only == Some("groups") { + &[] + } else { + &scope.aliases + }; + for alias in aliases { + match scope.groups.iter().find(|group| group.name == alias.target) { + Some(group) => { + rows.extend(self.group_rows(group).into_iter().map(|row| match row { + Row::At { + position, group, .. + } => Row::At { + position, + name: Some(alias.alias.clone()), + group, + }, + other => other, + })) + } + None => rows.extend(self.all(&alias.target, None, Some(&alias.alias))), + } + } + match (model_name, only) { + (_, Some("aliases")) => {} + (Some(name), _) => { + if let Some(group) = scope.groups.iter().find(|group| group.name == name) { + rows.extend(self.group_rows(group)); + } + } + (None, _) => { + for group in &scope.groups { + rows.extend(self.group_rows(group)); + } + } + } + if only.is_some() { + return rows; + } + if let Some(name) = model_name + && rows.is_empty() + { + rows.extend(self.wildcard(name, team_id, &scope.wildcard)); + } + if model_name.is_none() { + rows.extend((0..self.deployments.len()).map(|position| Row::At { + position, + name: None, + group: None, + })); + } + rows + } + + /// The whole list's rows, or the first row the host's read of the list raises at. + fn readable(&self, rows: Vec) -> Result, Row> { + match rows + .iter() + .find(|row| matches!(row, Row::Raw(_) | Row::RawPositions(_))) + { + Some(raw) => Err(raw.clone()), + None => Ok(rows), + } + } + + /// A callable routing group's rows: each member's deployments under the group's name. + fn group_rows(&self, group: &CallableGroup) -> Vec { + let mut rows = Vec::new(); + for member in &group.members { + for row in self.all(member, None, Some(&group.name)) { + rows.push(match row { + Row::At { position, name, .. } => Row::At { + position, + name, + group: Some((group.name.clone(), member.clone())), + }, + other => other, + }); + } + } + rows + } + + /// `_get_wildcard_deployments`: the global router's routes for the requests, then the team's. + fn wildcard(&self, name: &str, team_id: Option<&str>, requests: &[String]) -> Vec { + let route = |router: &crate::host_index::PatternRouter| -> Vec { + requests + .iter() + .find_map(|request| { + router + .route(request, None) + .filter(|routed| !routed.is_empty()) + }) + .unwrap_or_default() + }; + let mut routed = route(&self.host.patterns); + if let Some(team) = team_id + && let Some((_, router)) = self.host.team_patterns.iter().find(|(t, _)| t == team) + { + routed.extend(route(router)); + } + routed + .into_iter() + .map(|entry| Row::Pattern { + entry, + name: name.to_owned(), + }) + .collect() + } + + /// The deployments `team_id`'s own wildcard pattern routes `name` to + /// (`_core_team_pattern_routers`, keyed by `team_public_model_name`). + pub fn team_wildcard(&self, name: &str, team_id: &str) -> Vec> { + let Some((_, router)) = self.host.team_patterns.iter().find(|(t, _)| t == team_id) else { + return Vec::new(); + }; + router + .route(name, None) + .unwrap_or_default() + .iter() + .filter_map(|entry| entry.get("model_info")?.get("id").map(python_str)) + .filter_map(|id| self.deployments.iter().find(|d| d.id == id).cloned()) + .collect() + } + + /// `_core_get_model_names`: per row of the whole list, a team deployment's public name for + /// its own team, else the row's name. + pub fn model_names( + &self, + team_id: Option<&str>, + scope: &ListScope, + ) -> Result, Row> { + let rows = self.readable(self.model_list(None, None, scope))?; + let mut names = Vec::new(); + for row in &rows { + let Some(view) = self.row_view(row) else { + continue; + }; + match view.info.get("team_id").filter(|team| truthy(team)) { + Some(team) => { + if team_id.is_some_and(|id| team == &Value::String(id.to_owned())) + && let Some(public) = view + .info + .get("team_public_model_name") + .filter(|public| truthy(public)) + { + names.push(python_str(public)); + } + } + None => names.push(view.name.to_owned()), + } + } + Ok(names) + } + + /// `_core_get_model_access_groups`: access group to the names of the rows that declare it, + /// in the order they appear. + pub fn access_groups( + &self, + model_name: Option<&str>, + access_group: Option<&str>, + team_id: Option<&str>, + scope: &ListScope, + ) -> Result)>, Row> { + let mut groups: Vec<(String, Vec)> = Vec::new(); + for row in self.readable(self.model_list(model_name, team_id, scope))? { + let Some(view) = self.row_view(&row) else { + continue; + }; + if view.info.is_empty() || view.strips_access_groups { + continue; + } + // `access_groups or []`, iterated: a list's items, a string's characters. + let declared: Vec = match view.info.get("access_groups") { + Some(Value::Array(items)) => items.iter().map(python_str).collect(), + Some(Value::String(text)) => text.chars().map(String::from).collect(), + _ => continue, + }; + for group in declared { + if access_group.is_some_and(|wanted| wanted != group) { + continue; + } + match groups.iter_mut().find(|(held, _)| *held == group) { + Some((_, names)) => names.push(view.name.to_owned()), + None => groups.push((group, vec![view.name.to_owned()])), + } + } + } + Ok(groups) + } + + /// `_core_resolve_model_name_from_model_id`'s scan of the whole list: whether it lists any + /// row, and the name of the first row whose `litellm_params.model` is `model_id`, or ends in + /// `/model_id` or `:model_id`. + pub fn name_serving( + &self, + model_id: &str, + scope: &ListScope, + ) -> Result<(bool, Option), Row> { + let rows = self.readable(self.model_list(None, None, scope))?; + let (slash, colon) = (format!("/{model_id}"), format!(":{model_id}")); + let name = rows.iter().find_map(|row| { + let view = self.row_view(row)?; + let model = view.params.get("model").and_then(Value::as_str)?; + (model == model_id || model.ends_with(&slash) || model.ends_with(&colon)) + .then_some(view.name) + .filter(|name| !name.is_empty()) + .map(str::to_owned) + }); + Ok((!rows.is_empty(), name)) + } + + // -- teams and credentials ------------------------------------------------------------------- + + /// `_core_team_model_has_alternatives`: whether the team's public name of deployment `id` has + /// another unpaused deployment of that team. + pub fn team_model_has_alternatives(&self, id: &str) -> Result { + let Some(held) = self.host.id_entry(id) else { + return Ok(false); + }; + let position = self.position(held).ok_or_else(|| Row::Raw(held.clone()))?; + let info = self.view(position).info; + let (Some(Value::String(team)), Some(Value::String(public))) = + (info.get("team_id"), info.get("team_public_model_name")) + else { + return Ok(false); + }; + let Some(siblings) = self.host.team_named(team, public) else { + return Ok(false); + }; + let unpaused = self + .positions(siblings)? + .into_iter() + .filter(|position| self.view(*position).info.get("blocked") != Some(&Value::Bool(true))) + .count(); + Ok(unpaused > 1) + } + + /// `_get_model_group_deployment_usable_by_team`: the first deployment of the group the team + /// may use. + pub fn group_deployment_usable_by_team( + &self, + model_group: &str, + team_id: Option<&str>, + ) -> Result, Row> { + // `.get(name) or ()`: nothing held, or a falsy value, reads no position. + let Some(held) = self.host.named(model_group).filter(|held| truthy(held)) else { + return Ok(None); + }; + let Value::Array(items) = held else { + return Err(Row::RawPositions(held.clone())); + }; + for item in items { + let position = self.position(item).ok_or_else(|| Row::Raw(item.clone()))?; + if usable_by_team(&self.view(position), team_id) { + return Ok(Some(position)); + } + } + Ok(None) + } + + /// `_get_team_public_name_deployment`: the first deployment of the team's public name. + pub fn team_public_name_deployment( + &self, + model_id: &str, + team_id: &str, + ) -> Result, Row> { + match self.host.team_named(team_id, model_id) { + Some(Value::Array(items)) => match items.first() { + Some(item) => self + .position(item) + .map(Some) + .ok_or_else(|| Row::Raw(item.clone())), + None => Ok(None), + }, + Some(held) if truthy(held) => Err(Row::RawPositions(held.clone())), + Some(_) | None => Ok(None), + } + } + + // -- routable deployments -------------------------------------------------------------------- + + /// `_routable_deployments`: the routable group's deployments for the team (those it may use + /// when any), without paused ones. + pub fn routable(&self, model_group: &str, team_id: Option<&str>) -> Vec { + let named = self.all(model_group, team_id, None); + if named + .iter() + .any(|row| matches!(row, Row::Raw(_) | Row::RawPositions(_))) + { + return named; + } + let usable: Vec<&Row> = named + .iter() + .filter(|row| { + self.row_view(row) + .is_some_and(|view| usable_by_team(&view, team_id)) + }) + .collect(); + let pool: Vec<&Row> = if usable.is_empty() { + named.iter().collect() + } else { + usable + }; + pool.into_iter() + .filter(|row| { + self.row_view(row) + .is_some_and(|view| view.info.get("blocked") != Some(&Value::Bool(true))) + }) + .cloned() + .collect() + } + + /// `_core_get_candidate_model_ids_for_route`'s ids of `rows`, in first-seen order. + pub fn ids_of(&self, rows: &[Row]) -> Result, Row> { + let mut ids: Vec = Vec::new(); + for row in rows { + let view = match row { + Row::Raw(_) | Row::RawPositions(_) => return Err(row.clone()), + _ => self.row_view(row).expect("a readable row"), + }; + if let Some(id) = view.info.get("id").filter(|id| !id.is_null()) { + let id = python_str(id); + if !ids.contains(&id) { + ids.push(id); + } + } + } + Ok(ids) + } + + /// `_core_get_candidate_model_ids_for_route` once the alias resolved `resolved`: the + /// members' ids when it names a callable routing group (`members`), else, for a name that is + /// no model group, the team's deployments under it or its wildcard routes, else the group's. + pub fn candidate_ids( + &self, + resolved: &str, + team_id: Option<&str>, + members: Option<&[String]>, + requests: &[String], + ) -> Result, Row> { + if let Some(members) = members { + let mut ids: Vec = Vec::new(); + for member in members { + for id in self.ids_of(&self.all(member, team_id, None))? { + if !ids.contains(&id) { + ids.push(id); + } + } + } + return Ok(ids); + } + let named = Value::String(resolved.to_owned()); + if !self.host.model_names.contains(&named) { + if team_id.is_some() { + let team_rows = self.all(resolved, team_id, None); + if !team_rows.is_empty() { + return self.ids_of(&team_rows); + } + } + let wildcard = self.wildcard_route(resolved, team_id, requests); + if !wildcard.is_empty() { + return self.ids_of(&wildcard); + } + } + self.ids_of(&self.all(resolved, team_id, None)) + } + + /// `_core_wildcard_route_deployments`: the team router's routes for `model`, else the global + /// router's. + pub fn wildcard_route( + &self, + model: &str, + team_id: Option<&str>, + requests: &[String], + ) -> Vec { + let route = |router: &crate::host_index::PatternRouter| -> Vec { + requests + .iter() + .find_map(|request| { + router + .route(request, None) + .filter(|routed| !routed.is_empty()) + }) + .unwrap_or_default() + }; + let team_owned = team_id + .and_then(|team| self.host.team_patterns.iter().find(|(t, _)| t == team)) + .map(|(_, router)| route(router)) + .unwrap_or_default(); + let routed = if team_owned.is_empty() { + route(&self.host.patterns) + } else { + team_owned + }; + routed + .into_iter() + .map(|entry| Row::Pattern { + entry, + name: model.to_owned(), + }) + .collect() + } +} + +/// `_core_should_include_deployment`: the team's deployment under its public name, or a +/// deployment of the group the team may use. +fn should_include(model_name: &str, view: &View<'_>, team_id: Option<&str>) -> bool { + let team_value = team_id.map(|team| Value::String(team.to_owned())); + let model_team = view.info.get("team_id"); + if let Some(team) = &team_value + && model_team == Some(team) + && view.info.get("team_public_model_name") == Some(&Value::String(model_name.to_owned())) + { + return true; + } + if view.name == model_name { + return team_value.is_none() + || model_team.is_none_or(Value::is_null) + || model_team == team_value.as_ref(); + } + false +} + +/// `deployment_usable_by_team`: a deployment no team owns, or one the team owns. +fn usable_by_team(view: &View<'_>, team_id: Option<&str>) -> bool { + match view.info.get("team_id").filter(|team| !team.is_null()) { + None => true, + Some(owner) => team_id.is_some_and(|team| owner == &Value::String(team.to_owned())), + } +} + +fn empty() -> &'static Map { + static EMPTY: std::sync::OnceLock> = std::sync::OnceLock::new(); + EMPTY.get_or_init(Map::new) +} + +#[cfg(test)] +mod tests { + use serde_json::json; + + use super::*; + use crate::registry::DeploymentSpec; + + fn registry(entries: Value) -> Registry { + let mut registry = Registry::default(); + for entry in entries.as_array().unwrap() { + let spec: DeploymentSpec = serde_json::from_value(entry.clone()).unwrap(); + registry.push_built(spec, false).unwrap(); + } + registry + } + + #[test] + fn a_teams_wildcard_routes_only_the_names_its_public_pattern_matches() { + let registry = registry(json!([ + {"model_name": "t1-w", "litellm_params": {"model": "openai/*"}, + "model_info": {"id": "tw1", "team_id": "T1", "team_public_model_name": "tw-*"}}, + {"model_name": "g", "litellm_params": {"model": "openai/g"}, "model_info": {"id": "gp"}}, + ])); + let lookup = Lookup::new(®istry); + let ids = |name: &str, team: &str| -> Vec { + let routed = lookup.team_wildcard(name, team); + routed.iter().map(|d| d.id.clone()).collect() + }; + assert_eq!(ids("tw-gpt-4o", "T1"), ["tw1"]); + assert!(ids("gpt-4o", "T1").is_empty()); + assert!(ids("tw-gpt-4o", "T2").is_empty()); + } + + fn entry(name: &str, id: &str, info: Value) -> Value { + let mut info = info.as_object().cloned().unwrap_or_default(); + info.insert("id".to_owned(), json!(id)); + json!({"model_name": name, "litellm_params": {"model": format!("openai/{id}")}, "model_info": info}) + } + + fn at(position: usize) -> Row { + Row::At { + position, + name: None, + group: None, + } + } + + #[test] + fn all_prefers_the_teams_public_name_then_the_group() { + let registry = registry(json!([ + entry("gpt", "a", json!({})), + entry( + "team-gpt", + "t", + json!({"team_id": "T", "team_public_model_name": "gpt"}) + ), + entry("gpt", "b", json!({"team_id": "U"})), + ])); + let lookup = Lookup::new(®istry); + assert_eq!(lookup.all("gpt", Some("T"), None), vec![at(1)]); + assert_eq!(lookup.all("gpt", Some("V"), None), vec![at(0)]); + assert_eq!(lookup.all("gpt", None, None), vec![at(0), at(2)]); + assert_eq!(lookup.all("missing", None, None), vec![]); + } + + #[test] + fn a_junk_position_is_handed_back_to_raise() { + let mut registry = registry(json!([entry("gpt", "a", json!({}))])); + let mut model_name = registry.host_indexes().model_name.clone(); + model_name.insert("gpt".to_owned(), json!([0, "x"])); + let changes = crate::registry::ChangeSet { + host_index: Some(crate::host_index::IndexWrite { + model_name: Some(model_name), + ..Default::default() + }), + ..Default::default() + }; + registry = registry.apply(&changes, None).unwrap(); + let lookup = Lookup::new(®istry); + assert_eq!(lookup.all("gpt", None, None), vec![Row::Raw(json!("x"))]); + } + + #[test] + fn the_model_list_lists_aliases_and_groups_then_every_deployment() { + let registry = registry(json!([ + entry("gpt", "a", json!({"access_groups": ["g1"]})), + entry("claude", "b", json!({})), + ])); + let lookup = Lookup::new(®istry); + let scope = ListScope { + aliases: vec![AliasItem { + alias: "fast".to_owned(), + target: "gpt".to_owned(), + }], + groups: vec![CallableGroup { + name: "pool".to_owned(), + members: vec!["gpt".to_owned(), "claude".to_owned()], + }], + wildcard: Vec::new(), + only: None, + }; + let rows = lookup.model_list(None, None, &scope); + assert_eq!(rows.len(), 5); + assert_eq!( + rows[0], + Row::At { + position: 0, + name: Some("fast".to_owned()), + group: None + } + ); + assert_eq!( + lookup.model_names(None, &scope).unwrap(), + ["fast", "pool", "pool", "gpt", "claude"] + ); + assert_eq!( + lookup.access_groups(None, None, None, &scope).unwrap(), + vec![("g1".to_owned(), vec!["fast".to_owned(), "gpt".to_owned()])] + ); + } +} diff --git a/litellm-rust/crates/router-core/src/mock.rs b/litellm-rust/crates/router-core/src/mock.rs new file mode 100644 index 00000000000..898782e6203 --- /dev/null +++ b/litellm-rust/crates/router-core/src/mock.rs @@ -0,0 +1,44 @@ +//! The request's `mock_testing_*` flags: a failure the router raises itself, without calling a +//! deployment (`_handle_mock_testing_fallbacks` and `_handle_mock_testing_rate_limit_error`). + +use serde::Deserialize; + +use crate::error::{AttemptError, FailureKind}; + +/// Which mock failure a request asks for. +#[derive( + Clone, Copy, Debug, PartialEq, Eq, Deserialize, strum::IntoStaticStr, strum::EnumString, +)] +#[serde(rename_all = "snake_case")] +#[strum(serialize_all = "snake_case")] +pub enum MockFailure { + /// `mock_testing_fallbacks`: an `InternalServerError` before the first level's retries. + Fallbacks, + /// `mock_testing_context_fallbacks`: a `ContextWindowExceededError`, likewise. + ContextWindow, + /// `mock_testing_content_policy_fallbacks`: a `ContentPolicyViolationError`, likewise. + ContentPolicy, + /// `mock_testing_rate_limit_error`: a `RateLimitError` in place of every level's first + /// attempt, which the retry loop handles like a failed attempt. + RateLimit, +} + +impl MockFailure { + /// Whether the failure stands in for the first level's retry loop (raised before its retries). + pub fn before_retries(self) -> bool { + !matches!(self, Self::RateLimit) + } + + /// The failure as the rules see it. + pub fn failure(self, num_retries: Option) -> AttemptError { + let (kind, status) = match self { + Self::Fallbacks => (FailureKind::InternalServer, 500), + Self::ContextWindow => (FailureKind::ContextWindowExceeded, 400), + Self::ContentPolicy => (FailureKind::ContentPolicyViolation, 400), + Self::RateLimit => (FailureKind::RateLimit, 429), + }; + let mut failure = AttemptError::new(kind, Some(status)); + failure.num_retries = num_retries; + failure + } +} diff --git a/litellm-rust/crates/router-core/src/model_info.rs b/litellm-rust/crates/router-core/src/model_info.rs new file mode 100644 index 00000000000..861388f36ba --- /dev/null +++ b/litellm-rust/crates/router-core/src/model_info.rs @@ -0,0 +1,716 @@ +//! Model info: what the router reports a deployment can do and costs, merged from the process +//! cost map, what the background refresh discovered, and the deployment's own `model_info`. +//! +//! The merge rules are the Python router core's (`get_router_model_info`, +//! `get_deployment_model_info`); every cost-map read is a [`Host::model_info`] lookup asked while +//! the query runs, so a price reload or a registration the host made since the router was built is +//! what the next query reads. The host keeps choosing the keys a lookup tries (`get_model_info`); +//! the core chooses which lookups a query makes. +//! +//! Values the host cannot spell as JSON travel as opaque tokens ([`is_opaque`]): the merge moves +//! them between layers without reading them, and the host restores them. + +use serde_json::{Map, Number, Value}; + +use crate::{ + error::Error, + host::{Host, LogLevel, ModelInfoLookup}, +}; + +/// The key the host wraps a value it cannot spell as JSON in. +pub const OPAQUE_KEY: &str = "__litellm_python_value__"; + +/// A value the host passed as an opaque token: the merge moves it, never reads it. +pub fn is_opaque(value: &Value) -> bool { + matches!(value, Value::Object(map) if map.len() == 1 && map.contains_key(OPAQUE_KEY)) +} + +/// One `get_router_model_info` query, as the host reads it off the deployment. +#[derive(Clone, Debug, Default, serde::Deserialize)] +#[serde(default)] +pub struct RouterModelInfoQuery { + /// `model_info.id`. + pub deployment_id: Value, + /// `model_info.base_model`, then `litellm_params.base_model`: the first that is not `None` + /// names the model whose limits and costs the deployment reports. + pub model_info_base_model: Value, + pub params_base_model: Value, + /// The validated `litellm_params.model`. + pub params_model: String, + /// `base_model` among the validated params' extra fields. + pub extra_base_model: Value, + /// The name the caller asked for, which a wildcard deployment matches. + pub received_model_name: String, +} + +/// A merged model info, and the keys whose values are the deployment's own (the last layer). +#[derive(Clone, Debug, PartialEq)] +pub struct MergedModelInfo { + pub info: Map, + pub user_keys: Vec, +} + +pub(crate) fn raised(exception: &'static str, detail: impl Into) -> Error { + Error::ModelInfo { + exception, + detail: detail.into(), + } +} + +pub(crate) fn malformed(lookup: &str) -> Error { + raised( + "ValueError", + format!("the host answered a `{lookup}` lookup malformed"), + ) +} + +/// Python truthiness of a JSON value. +pub(crate) fn truthy(value: &Value) -> bool { + match value { + Value::Null => false, + Value::Bool(flag) => *flag, + Value::Number(number) => number.as_f64().is_some_and(|n| n != 0.0), + Value::String(text) => !text.is_empty(), + Value::Array(items) => !items.is_empty(), + Value::Object(map) => is_opaque(value) || !map.is_empty(), + } +} + +/// `(value or 0) > 0`, for a value that is a number (anything else reads as not positive). +fn positive_or_zero(value: Option<&Value>) -> bool { + value + .filter(|value| truthy(value)) + .and_then(Value::as_f64) + .is_some_and(|n| n > 0.0) +} + +pub(crate) async fn lookup(host: &dyn Host, lookup: ModelInfoLookup) -> Result { + host.model_info(&lookup).await +} + +/// `get_model_info(model=...)`: the row, or `None` when the lookup tolerates a failure and failed. +async fn catalog_row( + host: &dyn Host, + model: Value, + tolerate: bool, +) -> Result>, Error> { + match lookup( + host, + ModelInfoLookup::ModelInfo { + model, + tolerate, + exact: false, + }, + ) + .await? + { + Value::Null => Ok(None), + Value::Object(row) if tolerate && row.get("failed") == Some(&Value::Bool(true)) => Ok(None), + Value::Object(row) => Ok(Some(row)), + _ => Err(malformed("model_info")), + } +} + +/// `model_cost.get(key)`: `None` when the key is absent, else the entry as stored. +async fn cost_entry(host: &dyn Host, key: &str, process: bool) -> Result, Error> { + match lookup( + host, + ModelInfoLookup::CostEntry { + key: key.to_owned(), + process, + }, + ) + .await? + { + Value::Null => Ok(None), + Value::Object(mut answer) => Ok(Some(answer.remove("entry").unwrap_or(Value::Null))), + _ => Err(malformed("cost_entry")), + } +} + +pub(crate) async fn discovered(host: &dyn Host, id: Value) -> Result, Error> { + match lookup(host, ModelInfoLookup::Discovered { id }).await? { + Value::Null => Ok(Map::new()), + Value::Object(limits) => Ok(limits), + _ => Err(malformed("discovered")), + } +} + +async fn log(host: &dyn Host, level: LogLevel, message: String) -> Result<(), Error> { + lookup(host, ModelInfoLookup::Log { level, message }) + .await + .map(|_| ()) +} + +/// `_provider_model_id`: the model id a cost-map key or base model names, bedrock base model ids +/// normalized. +async fn provider_model_id(host: &dyn Host, name: &str, provider: &str) -> Result { + let model_id = name.rsplit('/').next().unwrap_or(name).to_owned(); + if !provider.starts_with("bedrock") { + return Ok(model_id); + } + match lookup(host, ModelInfoLookup::BedrockBase { model_id }).await? { + Value::String(base) => Ok(base), + _ => Err(malformed("bedrock_base")), + } +} + +/// `_exact_base_model_max_input_tokens`: the base model's own window, unless its row came from a +/// fallback-generalization rule or it is unmapped. +async fn exact_base_model_max_input_tokens( + host: &dyn Host, + base_model: &str, +) -> Result, Error> { + let answer = lookup( + host, + ModelInfoLookup::ModelInfo { + model: Value::String(base_model.to_owned()), + tolerate: true, + exact: true, + }, + ) + .await?; + let Value::Object(mut answer) = answer else { + return Ok(None); + }; + if answer.get("failed") == Some(&Value::Bool(true)) + || answer.get("generalized") == Some(&Value::Bool(true)) + { + return Ok(None); + } + let Some(Value::Object(row)) = answer.remove("row") else { + return Ok(None); + }; + Ok(row + .get("max_input_tokens") + .filter(|tokens| !tokens.is_null()) + .cloned()) +} + +/// `_base_model_widened_window`: a base model naming the same model as the route can only widen +/// its context window. +async fn base_model_widened_window( + host: &dyn Host, + route: &Map, + base_model: Option<&str>, + provider: &str, +) -> Result, Error> { + let Some(route_max) = route + .get("max_input_tokens") + .filter(|tokens| !tokens.is_null()) + else { + return Ok(None); + }; + let Some(base_model) = base_model else { + return Ok(None); + }; + let route_key = match route.get("key") { + Some(Value::String(key)) => key.clone(), + Some(_) => return Err(raised("AttributeError", "key")), + None => return Err(raised("KeyError", "key")), + }; + let route_id = provider_model_id(host, &route_key, provider).await?; + let base_id = provider_model_id(host, base_model, provider).await?; + let unversioned = base_id + .split_once('@') + .map_or(base_id.as_str(), |(id, _)| id); + if route_id != base_id && route_id != unversioned { + return Ok(None); + } + let Some(base_max) = exact_base_model_max_input_tokens(host, base_model).await? else { + return Ok(None); + }; + match (base_max.as_f64(), route_max.as_f64()) { + (Some(base), Some(route)) if base > route => Ok(Some(base_max)), + (Some(_), Some(_)) => Ok(None), + _ => Err(raised( + "TypeError", + "'<=' not supported between the base model's and the route's max_input_tokens", + )), + } +} + +/// `_declared_base_model`: a `base_model` that is a string. +fn declared_base_model(value: &Value) -> Option<&str> { + value.as_str() +} + +/// `get_router_model_info` after the host validated the deployment's params: the cost-map row of +/// the model the deployment serves, widened by its base model, overlaid with what the background +/// refresh discovered and then with every value the deployment sets itself. `None` when the +/// lookup answers `None`; an unmapped model raises as the lookup raises. +pub async fn router_model_info( + host: &dyn Host, + query: &RouterModelInfoQuery, +) -> Result, Error> { + let base_model = if query.model_info_base_model.is_null() { + query.params_base_model.clone() + } else { + query.model_info_base_model.clone() + }; + let mut model = base_model.clone(); + + let (resolved_model, provider) = match lookup( + host, + ModelInfoLookup::Provider { + model: query.params_model.clone(), + }, + ) + .await? + { + Value::Array(pair) => match pair.as_slice() { + [Value::String(model), Value::String(provider), ..] => { + (model.clone(), provider.clone()) + } + _ => return Err(malformed("provider")), + }, + _ => return Err(malformed("provider")), + }; + + if provider == "azure" && base_model.is_null() { + // Router init registers every deployment name into the cost map as a zeroed stub, so + // membership alone cannot tell a resolvable name apart; it needs usable limits or costs. + let fallback_key = if resolved_model.starts_with("azure/") { + resolved_model.clone() + } else { + format!("azure/{resolved_model}") + }; + let resolves = match cost_entry(host, &fallback_key, false).await? { + Some(Value::Object(entry)) if !is_opaque(&Value::Object(entry.clone())) => { + positive_or_zero(entry.get("max_input_tokens")) + || positive_or_zero(entry.get("input_cost_per_token")) + } + _ => false, + }; + if resolves { + log( + host, + LogLevel::Debug, + format!( + "Azure deployment '{resolved_model}' has no base_model set; using '{fallback_key}' from the model cost map for max tokens, cost tracking, etc." + ), + ) + .await?; + } else { + log( + host, + LogLevel::Error, + format!( + "Could not identify azure model '{resolved_model}'. Set azure 'base_model' for accurate max tokens, cost tracking, etc.- https://docs.litellm.ai/docs/proxy/cost_tracking#spend-tracking-for-azure-openai-models" + ), + ) + .await?; + } + } else if provider != "azure" { + model = Value::String(resolved_model.clone()); + if resolved_model.contains('*') { + // Only a wildcard deployment asks which model its pattern routed the name to. + if let Value::Array(routed) = lookup( + host, + ModelInfoLookup::PatternModels { + name: query.received_model_name.clone(), + }, + ) + .await? + && let Some(routed) = routed + .iter() + .find(|routed| routed.get("id").unwrap_or(&Value::Null) == &query.deployment_id) + { + model = routed.get("model").cloned().unwrap_or(Value::Null); + } + } + } + + if model.is_null() { + // An azure deployment without a base_model is looked up by its own model. + model = Value::String(resolved_model); + } + let Value::String(model) = model else { + return Err(raised( + "AttributeError", + format!( + "'{}' object has no attribute 'startswith'", + crate::group_info::type_name(&model) + ), + )); + }; + let model_info_name = if model.starts_with(&format!("{provider}/")) { + model + } else { + format!("{provider}/{model}") + }; + + let Some(row) = catalog_row(host, Value::String(model_info_name), false).await? else { + return Ok(None); + }; + + let user_model_info = match lookup(host, ModelInfoLookup::UserModelInfo).await? { + Value::Object(info) => info, + Value::Null => Map::new(), + _ => return Err(malformed("user_model_info")), + }; + let declared = user_model_info + .get("base_model") + .and_then(declared_base_model) + .or_else(|| declared_base_model(&query.extra_base_model)); + let widened = base_model_widened_window(host, &row, declared, &provider).await?; + let discovered = discovered(host, query.deployment_id.clone()).await?; + + let mut info = row; + if let Some(max_input_tokens) = widened { + info.insert("max_input_tokens".to_owned(), max_input_tokens); + } + info.extend(discovered); + let mut user_keys = Vec::new(); + for (key, value) in &user_model_info { + if !value.is_null() { + info.insert(key.clone(), value.clone()); + user_keys.push(key.clone()); + } + } + Ok(Some(MergedModelInfo { info, user_keys })) +} + +/// `_convert_stringified_numbers`: a string that reads as a number becomes one (a float when it +/// has an exponent or a point, else an int); any other string stays as written. +fn convert_stringified_number(text: &str) -> Value { + let trimmed = text.trim(); + let digits = without_digit_underscores(trimmed); + let lower = text.to_lowercase(); + if lower.contains('e') || text.contains('.') { + return digits + .and_then(|digits| python_float(&digits)) + .and_then(Number::from_f64) + .map_or_else(|| Value::String(text.to_owned()), Value::Number); + } + digits + .and_then(|digits| python_int(&digits)) + .map_or_else(|| Value::String(text.to_owned()), Value::Number) +} + +/// The text with the underscores Python's `int()`/`float()` accept between digits removed, or +/// `None` when an underscore sits anywhere else. +pub(crate) fn without_digit_underscores(text: &str) -> Option { + let chars: Vec = text.chars().collect(); + let mut out = String::with_capacity(text.len()); + for (index, ch) in chars.iter().enumerate() { + if *ch == '_' { + let before = index.checked_sub(1).and_then(|i| chars.get(i)); + let after = chars.get(index + 1); + if !(before.is_some_and(char::is_ascii_digit) + && after.is_some_and(char::is_ascii_digit)) + { + return None; + } + continue; + } + out.push(*ch); + } + Some(out) +} + +pub(crate) fn python_float(text: &str) -> Option { + let lower = text.to_ascii_lowercase(); + let unsigned = lower.trim_start_matches(['+', '-']); + if matches!(unsigned, "inf" | "infinity" | "nan") { + // Not finite: JSON cannot carry it, so the value stays as written. + return None; + } + let well_formed = text + .chars() + .all(|ch| ch.is_ascii_digit() || matches!(ch, '+' | '-' | '.' | 'e' | 'E')); + if !well_formed { + return None; + } + text.parse::().ok().filter(|n| n.is_finite()) +} + +pub(crate) fn python_int(text: &str) -> Option { + let unsigned = text.strip_prefix(['+', '-']).unwrap_or(text); + if unsigned.is_empty() || !unsigned.chars().all(|ch| ch.is_ascii_digit()) { + return None; + } + let text = text.strip_prefix('+').unwrap_or(text); + text.parse::() + .map(Number::from) + .ok() + .or_else(|| text.parse::().map(Number::from).ok()) +} + +/// `update_dictionary`: `new`'s values over `existing`, skipping `None`s; a string that reads as a +/// number becomes one, and a dict merges one level into the dict it replaces. +pub fn update_dictionary(existing: &mut Map, new: &Map) { + for (key, value) in new { + match value { + Value::Null => {} + Value::String(text) => { + existing.insert(key.clone(), convert_stringified_number(text)); + } + Value::Object(nested) if !is_opaque(value) => { + let merged = match existing.get(key) { + Some(current @ Value::Object(current_map)) if !is_opaque(current) => { + let mut merged = current_map.clone(); + merged.extend(nested.clone()); + merged + } + _ => nested.clone(), + }; + existing.insert(key.clone(), Value::Object(merged)); + } + _ => { + existing.insert(key.clone(), value.clone()); + } + } + } +} + +/// `cost_map_omits_token_price`: the cost-map entries under `keys` exist, and none carries a +/// per-token price. +async fn cost_map_omits_token_price(host: &dyn Host, keys: &[Option<&str>]) -> Result { + let mut entries = 0; + for key in keys.iter().flatten() { + if let Some(entry) = cost_entry(host, key, true).await? + && !is_opaque(&entry) + && let Value::Object(map) = entry + { + entries += 1; + if map.contains_key("input_cost_per_token") || map.contains_key("output_cost_per_token") + { + return Ok(false); + } + } + } + Ok(entries > 0) +} + +/// `get_deployment_model_info`: deployment `model_id`'s own cost-map entry (with what the refresh +/// discovered, over its base model's row), merged over the row of its litellm model `model_name`. +/// A lookup that fails leaves its layer out, as the Python router ignores it. +pub async fn deployment_model_info( + host: &dyn Host, + model_id: &str, + model_name: &Value, +) -> Result>, Error> { + let mut custom: Option> = None; + if let Some(entry) = cost_entry(host, model_id, false).await? { + let entry = if truthy(&entry) { + match entry { + Value::Object(map) if !is_opaque(&Value::Object(map.clone())) => Some(map), + // Not a mapping: the Python router's TypeError, which it ignores. + _ => None, + } + } else { + Some(Map::new()) + }; + if let Some(mut entry) = entry { + entry.extend(discovered(host, Value::String(model_id.to_owned())).await?); + custom = Some(entry); + } + } + + let builtin = catalog_row(host, model_name.clone(), true).await?; + + let mut base_model_key: Option = None; + if let Some(current) = &custom + && let Some(base_model) = current.get("base_model").filter(|base| !base.is_null()) + && let Some(mut base_row) = catalog_row(host, base_model.clone(), true).await? + { + base_model_key = base_row + .get("key") + .and_then(Value::as_str) + .map(str::to_owned); + // The base model provides defaults; the deployment's own entry overrides them. + update_dictionary(&mut base_row, current); + custom = Some(base_row); + } + + let builtin_key = builtin + .as_ref() + .and_then(|row| row.get("key")) + .and_then(Value::as_str) + .map(str::to_owned); + let info = match (custom, builtin) { + (Some(custom), Some(mut builtin)) => { + update_dictionary(&mut builtin, &custom); + builtin + } + (None, Some(builtin)) => builtin, + (Some(custom), None) => custom, + (None, None) => return Ok(None), + }; + if cost_map_omits_token_price( + host, + &[ + Some(model_id), + builtin_key.as_deref(), + base_model_key.as_deref(), + ], + ) + .await? + { + let mut info = info; + info.insert("input_cost_per_token".to_owned(), Value::Null); + info.insert("output_cost_per_token".to_owned(), Value::Null); + return Ok(Some(info)); + } + Ok(Some(info)) +} + +#[cfg(test)] +mod tests { + use std::{ + collections::BTreeMap, + sync::{Arc, Mutex}, + }; + + use async_trait::async_trait; + use serde_json::json; + + use super::*; + use crate::{ + cache::{InMemoryRouterCache, RouterCache}, + error::AttemptError, + host::{Attempt, Output, RouterEvent, RouterRequest, RoutingContext, SelectStage}, + registry::Deployment, + }; + + /// A cost map and a provider, answering lookups the way `PythonHost` does. + #[derive(Default)] + struct Catalog { + rows: BTreeMap, + provider: (String, String), + user_model_info: Value, + lookups: Mutex>, + } + + #[async_trait] + impl Host for Catalog { + async fn invoke(&self, _attempt: &Attempt) -> Result { + unreachable!("a model-info query runs no attempt") + } + async fn select( + &self, + _stage: &SelectStage, + _ctx: &RoutingContext<'_>, + candidates: Vec>, + ) -> Result>, Error> { + Ok(candidates) + } + async fn allow_fallback( + &self, + _request: &RouterRequest, + _target: &str, + ) -> Result { + Ok(true) + } + async fn sleep(&self, _duration: std::time::Duration) {} + fn observe(&self, _event: &RouterEvent) {} + fn cache(&self) -> Arc { + Arc::new(InMemoryRouterCache::default()) + } + async fn model_info(&self, lookup: &ModelInfoLookup) -> Result { + self.lookups + .lock() + .unwrap() + .push(serde_json::to_value(lookup).unwrap()); + Ok(match lookup { + ModelInfoLookup::ModelInfo { + model, tolerate, .. + } => match model.as_str().and_then(|model| self.rows.get(model)) { + Some(row) => row.clone(), + None if *tolerate => json!({"failed": true}), + None => return Err(raised("ValueError", "unmapped")), + }, + ModelInfoLookup::CostEntry { key, .. } => self + .rows + .get(key) + .map_or(Value::Null, |entry| json!({"entry": entry})), + ModelInfoLookup::Provider { .. } => { + json!([self.provider.0, self.provider.1]) + } + ModelInfoLookup::UserModelInfo => self.user_model_info.clone(), + _ => Value::Null, + }) + } + } + + #[test] + fn update_dictionary_converts_numbers_and_merges_nested_dicts_one_level() { + let mut existing = json!({"a": 1, "n": {"x": 1, "y": 2}, "k": "keep"}) + .as_object() + .unwrap() + .clone(); + let new = json!({"a": None::, "n": {"y": 3}, "i": "8_192", "f": "3e-07", "s": "abc"}) + .as_object() + .unwrap() + .clone(); + update_dictionary(&mut existing, &new); + assert_eq!( + Value::Object(existing), + json!({"a": 1, "n": {"x": 1, "y": 3}, "k": "keep", "i": 8192, "f": 3e-07, "s": "abc"}) + ); + } + + #[tokio::test] + async fn router_model_info_overlays_the_deployments_own_values_on_the_row() { + let host = Catalog { + rows: BTreeMap::from([( + "openai/gpt-4o".to_owned(), + json!({"key": "gpt-4o", "max_input_tokens": 100, "input_cost_per_token": 1.0}), + )]), + provider: ("gpt-4o".to_owned(), "openai".to_owned()), + user_model_info: json!({"id": "d", "input_cost_per_token": 2.0, "mode": None::}), + ..Catalog::default() + }; + let query = RouterModelInfoQuery { + deployment_id: json!("d"), + params_model: "openai/gpt-4o".to_owned(), + received_model_name: "g".to_owned(), + ..RouterModelInfoQuery::default() + }; + let merged = router_model_info(&host, &query).await.unwrap().unwrap(); + assert_eq!( + Value::Object(merged.info), + json!({"key": "gpt-4o", "max_input_tokens": 100, "input_cost_per_token": 2.0, "id": "d"}) + ); + assert_eq!(merged.user_keys, vec!["id", "input_cost_per_token"]); + } + + #[tokio::test] + async fn deployment_model_info_merges_the_entry_over_the_builtin_row() { + let host = Catalog { + rows: BTreeMap::from([ + ( + "gpt-4o".to_owned(), + json!({"key": "gpt-4o", "max_tokens": 10, "input_cost_per_token": 1.0}), + ), + ("d".to_owned(), json!({"max_tokens": "20"})), + ]), + ..Catalog::default() + }; + let info = deployment_model_info(&host, "d", &json!("gpt-4o")) + .await + .unwrap() + .unwrap(); + assert_eq!( + Value::Object(info), + json!({"key": "gpt-4o", "max_tokens": 20, "input_cost_per_token": 1.0}) + ); + } + + #[tokio::test] + async fn an_unpriced_entry_reports_no_token_prices() { + let host = Catalog { + rows: BTreeMap::from([("d".to_owned(), json!({"max_tokens": 5}))]), + ..Catalog::default() + }; + let info = deployment_model_info(&host, "d", &json!("unmapped")) + .await + .unwrap() + .unwrap(); + assert_eq!( + Value::Object(info), + json!({"max_tokens": 5, "input_cost_per_token": null, "output_cost_per_token": null}) + ); + } +} diff --git a/litellm-rust/crates/router-core/src/outcome.rs b/litellm-rust/crates/router-core/src/outcome.rs new file mode 100644 index 00000000000..59e0d14b2c2 --- /dev/null +++ b/litellm-rust/crates/router-core/src/outcome.rs @@ -0,0 +1,125 @@ +//! Which of a request's outcomes reach the deployment's health. The Python router learns them from +//! logging callbacks it registers on the process lists; `_core_serve_through_request_logging` and +//! `_core_discard` take those off, and `_core_bind_to_request_logging` puts them back on one +//! request's logging object. This core registers none, so the host answers, for each request, what +//! would have run ([`OutcomeCallbacks`]), and every write a callback owns passes through +//! [`OutcomeCallbacks::record`]. +//! +//! What the Python router writes outside its callbacks is not gated, and reaches [`crate::Health`] +//! with the default value: `make_call`'s usage, `async_routing_strategy_pre_call_checks`' +//! cooldown, `_trigger_cooldown_for_failed_deployment`, `RouterHealth.record_failure` and a +//! realtime session's success. + +use std::future::Future; + +use serde::Deserialize; + +use crate::error::Error; + +/// Which of the router's outcome callbacks litellm's logging runs for a request. The default is a +/// router whose callbacks are on the process lists. +#[derive(Clone, Copy, Debug, Deserialize, PartialEq, Eq)] +#[serde(default, deny_unknown_fields)] +pub struct OutcomeCallbacks { + /// `deployment_callback_on_success`, `sync_deployment_callback_on_success` for a sync call. + /// `_core_bind_to_request_logging` binds only the former. + pub success: bool, + /// `deployment_callback_on_failure` and `async_deployment_callback_on_failure`. + pub failure: bool, + /// The attempt runs through `make_call`, which counts its usage whatever the callbacks do. + pub make_call: bool, +} + +impl Default for OutcomeCallbacks { + fn default() -> Self { + Self { + success: true, + failure: true, + make_call: true, + } + } +} + +/// What an outcome writes. +#[derive(Clone, Copy, Debug, PartialEq, Eq)] +pub enum OutcomeWrite { + /// The success counter, or the usage the success callback adds at the end of a stream. + Success, + /// The tokens and request of an attempt that returned: `make_call`'s write, or the success + /// callback's for an endpoint that skips `make_call`. + AttemptUsage, + /// The failure counter, the allowed-fails counter, the cooldown and the failed request. + Failure, +} + +impl OutcomeCallbacks { + /// Run `record` when `write` happens for this request, else record nothing. + pub(crate) async fn record( + self, + write: OutcomeWrite, + record: impl Future>, + ) -> Result { + let runs = match write { + OutcomeWrite::Success => self.success, + OutcomeWrite::AttemptUsage => self.success || self.make_call, + OutcomeWrite::Failure => self.failure, + }; + if runs { record.await } else { Ok(T::default()) } + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + + use super::*; + + const REGISTERED: OutcomeCallbacks = OutcomeCallbacks { + success: true, + failure: true, + make_call: true, + }; + const UNBOUND: OutcomeCallbacks = OutcomeCallbacks { + success: false, + failure: false, + make_call: true, + }; + const UNBOUND_WITHOUT_MAKE_CALL: OutcomeCallbacks = OutcomeCallbacks { + success: false, + failure: false, + make_call: false, + }; + const BOUND_SYNC: OutcomeCallbacks = OutcomeCallbacks { + success: false, + failure: true, + make_call: true, + }; + + #[rstest] + #[case::registered_success(REGISTERED, OutcomeWrite::Success, true)] + #[case::registered_usage(REGISTERED, OutcomeWrite::AttemptUsage, true)] + #[case::registered_failure(REGISTERED, OutcomeWrite::Failure, true)] + #[case::unbound_success(UNBOUND, OutcomeWrite::Success, false)] + #[case::unbound_usage(UNBOUND, OutcomeWrite::AttemptUsage, true)] + #[case::unbound_failure(UNBOUND, OutcomeWrite::Failure, false)] + #[case::no_make_call_usage(UNBOUND_WITHOUT_MAKE_CALL, OutcomeWrite::AttemptUsage, false)] + #[case::bound_sync_success(BOUND_SYNC, OutcomeWrite::Success, false)] + #[case::bound_sync_failure(BOUND_SYNC, OutcomeWrite::Failure, true)] + #[tokio::test] + async fn a_write_runs_when_its_callback_does( + #[case] callbacks: OutcomeCallbacks, + #[case] write: OutcomeWrite, + #[case] runs: bool, + ) { + let recorded = callbacks.record(write, async { Ok(true) }).await; + + assert_eq!(recorded.ok(), Some(runs)); + } + + #[test] + fn a_router_on_the_process_lists_is_the_default() { + let parsed: OutcomeCallbacks = serde_json::from_str("{}").expect("an empty document"); + + assert_eq!(parsed, REGISTERED); + } +} diff --git a/litellm-rust/crates/router-core/src/precall.rs b/litellm-rust/crates/router-core/src/precall.rs new file mode 100644 index 00000000000..04dd22f1c90 --- /dev/null +++ b/litellm-rust/crates/router-core/src/precall.rs @@ -0,0 +1,300 @@ +//! `enable_pre_call_checks` (`_pre_call_checks`): before a pick, drop the deployments whose +//! context window the prompt exceeds, those outside the request's `allowed_model_region`, and +//! those that cannot take a requested param, then decide which error a group with nothing left +//! raises. The facts that need live model data (the prompt's token count, each deployment's +//! context window, which params it takes) come from [`Host::pre_call_facts`]; every decision is +//! made here. +//! +//! [`Host::pre_call_facts`]: crate::host::Host::pre_call_facts + +use std::{collections::BTreeMap, sync::Arc}; + +use serde::Deserialize; +use serde_json::Value; + +use crate::{error::Error, registry::Deployment}; + +/// What the host knows about one deployment for the pre-call checks. +#[derive(Clone, Debug, Default, Deserialize, PartialEq)] +#[serde(default)] +pub struct DeploymentFacts { + /// The deployment's context window (`get_router_model_info`'s `max_input_tokens`), when it + /// declares one and resolves. + pub max_input_tokens: Option, + /// `_deployment_lacks_params`: it does not support one of the requested params. + pub lacks_params: bool, + /// `_deployment_rejects_params`: it lacks one the request and deployment neither drop nor allow. + pub rejects_params: bool, +} + +/// What the host knows about a request for the pre-call checks. +#[derive(Clone, Debug, Default, Deserialize, PartialEq)] +#[serde(default)] +pub struct PreCallFacts { + /// The request carries `messages` or `input`: without either no check runs. + pub has_input: bool, + /// The prompt may be counted against a context window (no compaction is pending). + pub countable: bool, + /// The prompt's token count, when it was counted. + pub input_tokens: Option, + /// The request's `allowed_model_region`. + pub allowed_model_region: Option, + /// The requested params the check filters on, sorted (`_pre_call_check_requested_chat_params`). + pub requested_params: Vec, + /// Facts by deployment id, for the candidates and the group's deployments. + pub deployments: BTreeMap, +} + +impl PreCallFacts { + fn of(&self, deployment: &Deployment) -> DeploymentFacts { + self.deployments + .get(&deployment.id) + .cloned() + .unwrap_or_default() + } +} + +/// The name a context-window error gives a deployment: its base model, else its model. +fn deployment_model(deployment: &Deployment) -> String { + let truthy = |value: Option<&Value>| match value { + Some(Value::String(text)) if !text.is_empty() => Some(text.clone()), + Some(Value::Null | Value::Bool(false)) | None => None, + Some(Value::String(_)) => None, + Some(other) => Some(python_str(other)), + }; + truthy(deployment.model_info.raw.get("base_model")) + .or_else(|| truthy(deployment.raw_params.get("base_model"))) + .unwrap_or_else(|| deployment.params.model.clone()) +} + +/// `str(value)` for the scalar values a base model may hold. +fn python_str(value: &Value) -> String { + match value { + Value::Bool(true) => "True".to_owned(), + Value::Number(number) => number.to_string(), + other => other.to_string(), + } +} + +/// `is_region_allowed`: the deployment's `region_name` equals the allowed region. +fn in_region(deployment: &Deployment, allowed: &Value) -> bool { + deployment.raw_params.get("region_name") == Some(allowed) +} + +/// `_pre_call_checks` over `candidates`; `pool` is the group's deployments before health filters +/// (`request_deployments`), which decide whether nothing left is an unsupported-params error. +pub fn filter( + model: &str, + candidates: Vec>, + pool: &[Arc], + facts: &PreCallFacts, +) -> Result>, Error> { + if !facts.has_input { + return Ok(candidates); + } + let mut invalid = vec![false; candidates.len()]; + let mut context_window_error = false; + let mut detail = String::new(); + for (index, deployment) in candidates.iter().enumerate() { + let found = facts.of(deployment); + if let (Some(limit), true, Some(tokens)) = + (found.max_input_tokens, facts.countable, facts.input_tokens) + && tokens > limit + { + invalid[index] = true; + context_window_error = true; + detail.push_str(&format!( + "Model={}, Max Input Tokens={limit}, Got={tokens}", + deployment_model(deployment) + )); + continue; + } + if let Some(allowed) = &facts.allowed_model_region + && !allowed.is_null() + && !in_region(deployment, allowed) + { + invalid[index] = true; + } + } + let params_checked = !facts.requested_params.is_empty(); + let param_candidates: Vec = (0..candidates.len()).filter(|i| !invalid[*i]).collect(); + let lacking: Vec = param_candidates + .iter() + .map(|i| params_checked && facts.of(&candidates[*i]).lacks_params) + .collect(); + let none_takes = !lacking.is_empty() && lacking.iter().all(|lacks| *lacks); + let failing: Vec = if none_takes { + param_candidates + .iter() + .map(|i| params_checked && facts.of(&candidates[*i]).rejects_params) + .collect() + } else { + lacking + }; + for (index, fails) in param_candidates.iter().zip(failing) { + if fails { + invalid[*index] = true; + } + } + let excluded = invalid.iter().filter(|x| **x).count(); + if excluded == candidates.len() { + if !context_window_error + && !pool.is_empty() + && pool + .iter() + .all(|d| params_checked && facts.of(d).rejects_params) + { + return Err(Error::UnsupportedParams { + model: model.to_owned(), + params: facts.requested_params.clone(), + }); + } + if context_window_error { + return Err(Error::ContextWindowExceeded { + model: model.to_owned(), + detail, + }); + } + } + Ok(candidates + .into_iter() + .zip(invalid) + .filter_map(|(deployment, invalid)| (!invalid).then_some(deployment)) + .collect()) +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + use crate::registry::DeploymentSpec; + + fn deployment(id: &str, params: Value, model_info: Value) -> Arc { + let mut info = model_info; + info["id"] = json!(id); + let spec: DeploymentSpec = serde_json::from_value(json!({ + "model_name": "g", "litellm_params": params, "model_info": info, + })) + .unwrap(); + Arc::new(Deployment::from_spec(spec).unwrap()) + } + + fn facts(entries: &[(&str, DeploymentFacts)]) -> PreCallFacts { + PreCallFacts { + has_input: true, + countable: true, + deployments: entries + .iter() + .map(|(id, f)| ((*id).to_owned(), f.clone())) + .collect(), + ..PreCallFacts::default() + } + } + + fn window(limit: i64) -> DeploymentFacts { + DeploymentFacts { + max_input_tokens: Some(limit), + ..DeploymentFacts::default() + } + } + + #[rstest] + fn a_prompt_over_a_context_window_drops_that_deployment() { + let small = deployment("small", json!({"model": "openai/a"}), json!({})); + let big = deployment("big", json!({"model": "openai/b"}), json!({})); + let mut found = facts(&[("small", window(5)), ("big", window(10_000))]); + found.input_tokens = Some(100); + let kept = filter("g", vec![small, big], &[], &found).unwrap(); + assert_eq!( + kept.iter().map(|d| d.id.as_str()).collect::>(), + ["big"] + ); + } + + #[rstest] + fn no_window_left_names_each_deployment_back_to_back() { + let one = deployment("one", json!({"model": "openai/one"}), json!({})); + let two = deployment( + "two", + json!({"model": "openai/two"}), + json!({"base_model": "azure/base"}), + ); + let mut found = facts(&[("one", window(5)), ("two", window(6))]); + found.input_tokens = Some(9); + let error = filter("g", vec![one, two], &[], &found).unwrap_err(); + let Error::ContextWindowExceeded { model, detail } = error else { + panic!("expected a context window error, got {error:?}"); + }; + assert_eq!(model, "g"); + assert_eq!( + detail, + "Model=openai/one, Max Input Tokens=5, Got=9Model=azure/base, Max Input Tokens=6, Got=9" + ); + } + + #[rstest] + fn without_input_nothing_is_checked() { + let small = deployment("small", json!({"model": "openai/a"}), json!({})); + let mut found = facts(&[("small", window(5))]); + found.input_tokens = Some(100); + found.has_input = false; + assert_eq!(filter("g", vec![small], &[], &found).unwrap().len(), 1); + } + + #[rstest] + #[case::in_region("eu", 1)] + #[case::out_of_region("ap", 0)] + fn the_allowed_region_keeps_only_its_deployments(#[case] region: &str, #[case] kept: usize) { + let eu = deployment( + "eu", + json!({"model": "openai/a", "region_name": "eu"}), + json!({}), + ); + let none = deployment("none", json!({"model": "openai/a"}), json!({})); + let mut found = facts(&[]); + found.allowed_model_region = Some(json!(region)); + assert_eq!( + filter("g", vec![eu, none], &[], &found).unwrap().len(), + kept + ); + } + + #[rstest] + fn a_group_where_every_deployment_rejects_the_param_is_unsupported() { + let old = deployment("old", json!({"model": "openai/old"}), json!({})); + let mut found = facts(&[( + "old", + DeploymentFacts { + lacks_params: true, + rejects_params: true, + ..DeploymentFacts::default() + }, + )]); + found.requested_params = vec!["response_format".to_owned()]; + let error = filter("g", vec![old.clone()], &[old], &found).unwrap_err(); + assert!( + matches!(error, Error::UnsupportedParams { params, .. } if params == ["response_format"]) + ); + } + + #[rstest] + fn a_deployment_that_takes_the_param_wins_over_one_that_would_drop_it() { + let old = deployment("old", json!({"model": "openai/old"}), json!({})); + let new = deployment("new", json!({"model": "openai/new"}), json!({})); + let mut found = facts(&[( + "old", + DeploymentFacts { + lacks_params: true, + ..DeploymentFacts::default() + }, + )]); + found.requested_params = vec!["response_format".to_owned()]; + let kept = filter("g", vec![old, new], &[], &found).unwrap(); + assert_eq!( + kept.iter().map(|d| d.id.as_str()).collect::>(), + ["new"] + ); + } +} diff --git a/litellm-rust/crates/router-core/src/prerouting.rs b/litellm-rust/crates/router-core/src/prerouting.rs new file mode 100644 index 00000000000..d6e3df05e7a --- /dev/null +++ b/litellm-rust/crates/router-core/src/prerouting.rs @@ -0,0 +1,53 @@ +//! Pre-routing: before an async pick resolves its name, the host may route the request to another +//! model group (Python's `_core_async_pre_routing_hook`). The complexity, auto, adaptive and +//! quality routers registered from `auto_router/...` marker deployments, and the Claude Code +//! session binding, live host-side; the core asks once per pick, before resolution, and resolves +//! the name the host answers. The attempt still serves the requested name (its `model_group`): +//! only the deployments come from the routed group. +//! +//! A custom routing strategy (`register_plugin`, `set_custom_routing_strategy`, lar1) replaces the +//! whole pick (`_core_async_get_available_deployment` and `get_available_deployment`): the host +//! answers the same step with the deployment document the strategy returned, which may name a +//! deployment the registry does not hold, and the core serves that deployment as is. + +use std::sync::Arc; + +use crate::{Core, config::Op, error::Error, host::RouterRequest, registry::Deployment}; + +/// What the host's pre-routing step sees. +#[derive(Clone, Copy, Debug)] +pub struct PreRoute<'a> { + pub op: &'a Op, + pub request: &'a RouterRequest, + /// The name this pick resolves: the requested name or the fallback target. + pub name: &'a str, + /// How many fallbacks deep the chain is (Python's `fallback_depth`): only a first attempt + /// binds a Claude Code session. + pub fallback_depth: u32, + /// 0 for the first attempt in this group, then the retry number. + pub retry: u32, +} + +/// The host's answer to a pre-routing step. +#[derive(Clone, Debug)] +pub enum PreRouted { + /// Resolve this model group instead of the requested name. + Model(String), + /// A custom strategy's pick: serve this deployment, without resolving or filtering. + Deployment(Arc), +} + +impl Core { + /// What a pick of `ask.name` serves: the host's pre-routed group or custom pick, else the + /// name itself. Only picks that ask for it pre-route (`request.pre_routes`). + pub(crate) async fn pre_routed(&self, ask: PreRoute<'_>) -> Result { + if !ask.request.pre_routes { + return Ok(PreRouted::Model(ask.name.to_owned())); + } + Ok(self + .host + .pre_route(&ask) + .await? + .unwrap_or_else(|| PreRouted::Model(ask.name.to_owned()))) + } +} diff --git a/litellm-rust/crates/router-core/src/ptu.rs b/litellm-rust/crates/router-core/src/ptu.rs new file mode 100644 index 00000000000..9110ac6a67f --- /dev/null +++ b/litellm-rust/crates/router-core/src/ptu.rs @@ -0,0 +1,96 @@ +//! PTU shares (`litellm_core_utils/ptu_shares.py`): a deployment whose `model_info.ptu_shares` +//! splits it across teams serves only those teams, and the teams holding a share are kept to +//! their share. + +use std::{collections::BTreeSet, sync::Arc}; + +use serde_json::{Map, Value}; + +use crate::registry::Deployment; + +/// `parsed_ptu_shares`: the teams of a non-empty `ptu_shares` map whose every entry is a team id +/// and a positive whole number of PTUs (`2.0` reads as 2, a bool is no number), else None. +pub fn share_teams(model_info: &Map) -> Option> { + let shares = model_info.get("ptu_shares")?.as_object()?; + if shares.is_empty() { + return None; + } + shares + .iter() + .map(|(team, share)| (!team.is_empty() && whole_ptus(share)).then(|| team.clone())) + .collect() +} + +/// `_whole_ptus`: a positive whole number. +fn whole_ptus(share: &Value) -> bool { + match share { + Value::Number(number) => number.as_i64().map_or_else( + || { + number + .as_u64() + .map(|whole| whole > 0) + .or_else(|| number.as_f64().map(|f| f.fract() == 0.0 && f > 0.0)) + .unwrap_or(false) + }, + |whole| whole > 0, + ), + _ => false, + } +} + +/// `filter_ptu_shared_deployments`: the deployments `team_id` holds a share on when it holds one, +/// else the ones split into no shares; a caller without a team holds none. Also whether any +/// deployment was withheld. +pub fn filter_shared( + deployments: Vec>, + team_id: Option<&str>, +) -> (Vec>, bool) { + let team = team_id.unwrap_or(""); + let checks: Vec<(Arc, Option>)> = deployments + .into_iter() + .map(|deployment| { + let shares = share_teams(&deployment.model_info.raw); + (deployment, shares) + }) + .collect(); + let holds_share = checks + .iter() + .any(|(_, shares)| shares.as_ref().is_some_and(|teams| teams.contains(team))); + let total = checks.len(); + let kept: Vec> = checks + .into_iter() + .filter(|(_, shares)| match shares { + Some(teams) => teams.contains(team), + None => !holds_share, + }) + .map(|(deployment, _)| deployment) + .collect(); + let withheld = kept.len() < total; + (kept, withheld) +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + #[rstest] + #[case(json!({"TA": 50}), Some(vec!["TA"]))] + #[case(json!({"TA": 2.0, "TB": 1}), Some(vec!["TA", "TB"]))] + #[case(json!({"TA": 2.5}), None)] + #[case(json!({"TA": true}), None)] + #[case(json!({"TA": 0}), None)] + #[case(json!({}), None)] + #[case(json!({"": 1}), None)] + #[case(json!("TA"), None)] + fn reads_the_share_teams(#[case] shares: Value, #[case] expected: Option>) { + let mut model_info = Map::new(); + model_info.insert("ptu_shares".to_owned(), shares); + assert_eq!( + share_teams(&model_info), + expected.map(|teams| teams.into_iter().map(str::to_owned).collect()) + ); + } +} diff --git a/litellm-rust/crates/router-core/src/registry.rs b/litellm-rust/crates/router-core/src/registry.rs new file mode 100644 index 00000000000..78c7d3b67e3 --- /dev/null +++ b/litellm-rust/crates/router-core/src/registry.rs @@ -0,0 +1,1548 @@ +//! The configured deployments, indexed by id, model group, alias, wildcard pattern, routing +//! group and team. A [`Registry`] is immutable; [`Registry::apply`] builds the next version. + +use std::{ + collections::{BTreeMap, BTreeSet, HashMap}, + fmt::Write as _, + sync::Arc, +}; + +use litellm_router_types::{LitellmParams, Spelled}; +use serde::Deserialize; +use serde_json::{Map, Value}; +use sha2::{Digest, Sha256}; + +use crate::{ + error::ConfigError, + host_index::{HostIndexes, IndexWrite, cache_flags_left_to_the_catalog, deployment_model_name}, +}; + +/// A registry's version; every change produces a higher one. +pub type RegistryVersion = u64; + +/// A deployment as a config or an `apply` spells it. +#[derive(Clone, Debug, Default, PartialEq, Deserialize)] +pub struct DeploymentSpec { + pub model_name: String, + pub litellm_params: Map, + #[serde(default)] + pub model_info: Map, + /// The entry's other top-level keys (a config's `tpm`, ...), kept so the host's view of the + /// deployment list reads back the entries it stored. + #[serde(flatten)] + pub extra: Map, + /// The provider the host resolved when it built the deployment ([`crate::build`]); never + /// read from a config or an `apply`. + #[serde(skip)] + pub provider: Option, +} + +/// `routing_groups`: a named subset of model groups sharing a routing strategy. +#[derive(Clone, Debug, PartialEq, Deserialize)] +pub struct RoutingGroupSpec { + pub group_name: String, + pub models: Vec, + pub routing_strategy: crate::config::RoutingStrategy, + /// A priority group's member priorities, served as each member's `order`. + #[serde(default)] + pub model_priorities: Option>, +} + +/// The `model_info` fields the router reads; every other key stays in [`Self::raw`]. +#[derive(Clone, Debug, Default, PartialEq)] +pub struct ModelInfo { + pub team_id: Option, + pub team_public_model_name: Option, + pub access_groups: Vec, + pub blocked: bool, + pub cooldown_time: Option, + pub allowed_fails: Option, + /// `model_info.allowed_fails_policy` when it is a dict, read as Python reads it: field name + /// to allowed fails, values as given. + pub allowed_fails_policy: Option>, + pub raw: Map, +} + +impl ModelInfo { + fn from_raw(raw: Map) -> Self { + let text = |key: &str| raw.get(key).and_then(Value::as_str).map(str::to_owned); + Self { + team_id: text("team_id"), + team_public_model_name: text("team_public_model_name"), + access_groups: raw + .get("access_groups") + .and_then(Value::as_array) + .map(|groups| { + groups + .iter() + .filter_map(Value::as_str) + .map(str::to_owned) + .collect() + }) + .unwrap_or_default(), + blocked: raw.get("blocked").and_then(Value::as_bool) == Some(true), + cooldown_time: raw.get("cooldown_time").and_then(Value::as_f64), + allowed_fails: raw + .get("allowed_fails") + .and_then(Value::as_u64) + .and_then(|fails| u32::try_from(fails).ok()), + allowed_fails_policy: raw + .get("allowed_fails_policy") + .and_then(Value::as_object) + .cloned(), + raw, + } + } +} + +/// One configured deployment. +#[derive(Clone, Debug, PartialEq)] +pub struct Deployment { + pub id: String, + pub model_name: String, + pub params: LitellmParams, + /// `litellm_params` as written, in order: what the id hashes and the host receives. + pub raw_params: Map, + pub model_info: ModelInfo, + /// The entry's other top-level keys, as written. + pub extra: Map, + /// The provider the host resolved for it, when it was built through the host. + pub resolved_provider: Option, +} + +impl Deployment { + pub fn from_spec(spec: DeploymentSpec) -> Result { + let params: LitellmParams = serde_json::from_value(Value::Object( + spec.litellm_params.clone(), + )) + .map_err(|source| ConfigError::InvalidDeployment { + model_name: spec.model_name.clone(), + source, + })?; + let id = match spec.model_info.get("id") { + Some(Value::String(id)) => id.clone(), + Some(Value::Number(id)) => id.to_string(), + _ => deployment_id(&spec.model_name, &spec.litellm_params), + }; + Ok(Self { + id, + model_name: spec.model_name, + params, + raw_params: spec.litellm_params, + model_info: ModelInfo::from_raw(spec.model_info), + extra: spec.extra, + resolved_provider: spec.provider, + }) + } + + /// The deployment as a `model_list` entry: its other top-level keys, then `model_name`, + /// `litellm_params` and `model_info` (with its id). + pub fn record(&self) -> Value { + let mut model_info = self.model_info.raw.clone(); + model_info.insert("id".to_owned(), Value::String(self.id.clone())); + let mut record = self.extra.clone(); + record.insert( + "model_name".to_owned(), + Value::String(self.model_name.clone()), + ); + record.insert( + "litellm_params".to_owned(), + Value::Object(self.raw_params.clone()), + ); + record.insert("model_info".to_owned(), Value::Object(model_info)); + Value::Object(record) + } + + /// The stand-in an unrouted attempt carries: the requested name as its group and model, no id. + pub fn unrouted(name: &str) -> Result { + let mut params = Map::new(); + params.insert("model".to_owned(), Value::String(name.to_owned())); + let mut info = Map::new(); + info.insert("id".to_owned(), Value::String(String::new())); + Self::from_spec(DeploymentSpec { + model_name: name.to_owned(), + litellm_params: params, + model_info: info, + extra: Map::new(), + provider: None, + }) + } + + /// The provider: the one the host resolved when it built the deployment, else + /// `custom_llm_provider`, else the `model` prefix before `/`. + pub fn provider(&self) -> &str { + self.resolved_provider + .as_deref() + .or(self.params.custom_llm_provider.as_deref()) + .or_else(|| { + self.params + .model + .split_once('/') + .map(|(provider, _)| provider) + }) + .unwrap_or("openai") + } + + /// A numeric `litellm_params` value, as `simple_shuffle._metric_weight` reads it. + pub fn metric(&self, key: &str) -> Option { + let spelled = |value: &Option>| match value { + Some(Spelled::Value(value)) => Some(*value), + Some(Spelled::Text(_)) | None => None, + }; + match key { + "rpm" => spelled(&self.params.rpm), + "tpm" => spelled(&self.params.tpm), + _ => self.raw_params.get(key).and_then(Value::as_f64), + } + } + + /// `simple_shuffle._metric_weight`: 0 when unset, a number (a bool counts as 0 or 1), or + /// `None` when the value is not numeric. A `rpm`/`tpm` spelled as text reads as unset. + pub fn metric_weight(&self, key: &str) -> Option { + if key != "weight" { + return Some(self.metric(key).unwrap_or(0.0)); + } + match self.raw_params.get(key) { + None | Some(Value::Null) => Some(0.0), + Some(Value::Bool(flag)) => Some(f64::from(u8::from(*flag))), + Some(Value::Number(number)) => number.as_f64(), + Some(_) => None, + } + } + + /// `get_deployment_order`: `litellm_params.order`, else `model_info.order`, which is where a + /// team model added through the API keeps it. Neither is validated as an int, so a bool, a + /// whole float and a numeric string are read as the level they compare as. + pub fn order(&self) -> Option { + let order = self + .raw_params + .get("order") + .filter(|order| !order.is_null()) + .or_else(|| self.model_info.raw.get("order"))?; + match order { + Value::Bool(flag) => Some(i64::from(*flag)), + Value::Number(number) => number.as_i64().or_else(|| { + number + .as_f64() + .filter(|float| float.fract() == 0.0) + .map(|float| float as i64) + }), + Value::String(text) => text.parse().ok(), + Value::Null | Value::Array(_) | Value::Object(_) => None, + } + } + + /// `_deployment_supports_web_search`: `model_info.supports_web_search` when it is set, read + /// for truthiness, else true. + pub(crate) fn supports_web_search(&self) -> bool { + self.model_info + .raw + .get("supports_web_search") + .is_none_or(|flag| flag.is_null() || crate::host_index::truthy(flag)) + } + + /// Whether `team_id` may use this deployment (`deployment_usable_by_team`). + pub fn usable_by_team(&self, team_id: Option<&str>) -> bool { + self.model_info + .team_id + .as_deref() + .is_none_or(|owner| Some(owner) == team_id) + } + + /// Whether `_core_get_model_list(team_id=team_id)` lists this deployment: no team lists + /// every team's (`_core_should_include_deployment`). + pub fn listed_for_team(&self, team_id: Option<&str>) -> bool { + team_id.is_none() || self.usable_by_team(team_id) + } + + /// Whether the deployment declares a limit the router counts per-minute usage for + /// (`_deployment_tracks_usage` and `deployment_has_io_token_limits`, without the limits only + /// the model catalog knows, which the host decides by): `tpm` or `rpm`, `itpm` or `otpm`, on + /// the entry itself, in `litellm_params` or in `model_info`. + pub fn tracks_usage(&self) -> bool { + let declared = |section: &Map| { + ["tpm", "rpm", "itpm", "otpm"] + .iter() + .any(|key| section.get(*key).is_some_and(|limit| !limit.is_null())) + }; + self.params.tpm.is_some() + || self.params.rpm.is_some() + || self.params.itpm.is_some() + || self.params.otpm.is_some() + || declared(&self.extra) + || declared(&self.model_info.raw) + } +} + +/// `_return_pattern_matched_deployments` for one deployment: a copy serving `request`, its +/// `litellm_params.model` filled with the `groups` the pattern matched and the prompt-cache flags +/// left to the catalog. A deployment whose model holds no wildcard is served as it is. +pub(crate) fn routed_deployment( + deployment: &Arc, + groups: &[String], + request: &str, +) -> Arc { + let model = &deployment.params.model; + if !model.contains('*') { + return deployment.clone(); + } + let named = deployment_model_name(groups, request, model); + let mut routed = Deployment::clone(deployment); + for flag in cache_flags_left_to_the_catalog(&deployment.raw_params) { + routed.model_info.raw.remove(*flag); + } + routed + .raw_params + .insert("model".to_owned(), Value::String(named.clone())); + routed.params.model = named; + Arc::new(routed) +} + +/// The connection params of one deployment (`credentials(id)`). +#[derive(Clone, Debug, PartialEq)] +pub struct Credentials { + pub provider: String, + pub api_base: Option, + pub api_version: Option, + pub credential_name: Option, + pub params: LitellmParams, +} + +/// What a name resolved through. +#[derive(Clone, Copy, Debug, PartialEq, Eq)] +pub enum ResolveKind { + SpecificDeployment, + Id, + /// A name nothing else serves, routed to the router's `default_deployment` (a copy whose + /// `litellm_params.model` is the name). Served like a deployment named by its id. + Default, + Alias, + RoutingGroup, + Group, + Wildcard, +} + +impl ResolveKind { + /// The name resolved to one deployment that is served as is: a deployment id, or the + /// default deployment (`_common_checks_available_deployment` returns a dict for both). + pub fn is_single(&self) -> bool { + matches!(self, Self::Id | Self::Default) + } +} + +#[derive(Clone, Debug, PartialEq)] +pub struct Resolution { + pub kind: ResolveKind, + /// The model group the deployments are routed as. + pub group: String, + pub deployments: Vec>, +} + +#[derive(Clone, Copy, Debug, Default)] +pub struct ResolveScope { + /// The caller named a deployment's `litellm_params.model` (`specific_deployment=True`). + pub specific_deployment: bool, +} + +#[derive(Clone, Debug, Default)] +pub struct DeploymentFilter<'a> { + pub model_name: Option<&'a str>, + pub team_id: Option<&'a str>, + pub provider: Option<&'a str>, +} + +#[derive(Clone, Debug, Default)] +pub struct NameFilter { + pub include_aliases: bool, +} + +/// The registry indexes as the host wrote them over the ones the deployments build (the +/// deprecated `model_names`, `model_name_to_deployment_indices` and +/// `team_model_to_deployment_indices` writes), which resolution reads instead from then on. +/// Indices point into the deployment list; one past its end is skipped. +#[derive(Clone, Debug, Default, PartialEq, Deserialize)] +#[serde(default, deny_unknown_fields)] +pub struct IndexOverrides { + /// `_core_model_names`: the names `name in model_names` finds. + pub model_names: Option>, + /// `_core_model_name_to_deployment_indices`: a model name's deployments. + pub model_name: Option>>, + /// `_core_team_model_to_deployment_indices`, as `(team_id, public name, indices)` entries. + pub team_model: Option)>>, +} + +impl IndexOverrides { + fn is_empty(&self) -> bool { + self.model_names.is_none() && self.model_name.is_none() && self.team_model.is_none() + } +} + +/// One atomic change: optionally a whole new deployment list, then upserts, deletes and, +/// optionally, a new dynamic config. +#[derive(Clone, Debug, Default)] +pub struct ChangeSet { + /// Every deployment, in order, replacing the current list (the host registry's `model_list` + /// after a write; it may hold one id more than once, as the Python router's list can). + pub replace: Option>, + /// Deployments added at the end, beside any that share their id (a deployment the host + /// retries after its provider resolved). + pub appends: Vec, + pub upserts: Vec, + pub deletes: Vec, + pub settings: Option, + /// The indexes the host wrote ([`IndexOverrides`]), replacing the ones held; an empty one + /// goes back to the indexes the deployments build. + pub index: Option, + /// The deployment at the position the id map holds for this id, removed with every index + /// shifted (`_delete_deployment`, and an upsert's removal of the deployment it edits). + pub remove: Option, + /// A host write to the indexes it hands out ([`HostIndexes`]). + pub host_index: Option, +} + +#[derive(Clone, Debug, Default)] +pub struct Registry { + version: RegistryVersion, + /// The version the deployments before the newest appends last changed at: a host that read + /// the list at or after it reads only what was appended since ([`Self::deployments_from`]). + rewritten: RegistryVersion, + deployments: Vec>, + by_id: HashMap, + by_group: BTreeMap>, + by_team: HashMap>, + wildcards: Vec<(String, Vec)>, + aliases: BTreeMap, + routing_groups: Vec, + overrides: Option>, + /// The indexes the host hands out, kept by the Python router's history rules. + host: Arc, + /// `_model_to_group` as Python last built it, when a raw `routing_groups` write replaced the + /// groups since: member calls keep routing by it (see [`Self::member_routing_group`]). + member_groups: Option>>, +} + +impl Registry { + pub fn build( + specs: Vec, + aliases: BTreeMap, + routing_groups: Vec, + ) -> Result { + // One id may name several deployments (a per-organization fan-out, or two entries + // declaring one id): each is kept, and the id finds the last, as the Python router keeps them. + let deployments = specs + .into_iter() + .map(|spec| Deployment::from_spec(spec).map(Arc::new)) + .collect::, _>>()?; + // The indexes `set_model_list` leaves, as a build installing each deployment in turn does. + let mut host = HostIndexes::default(); + for (position, deployment) in deployments.iter().enumerate() { + let record = deployment.record(); + host.added( + record.as_object().expect("a record is an object"), + position, + false, + ); + } + host.set_model_names(deployments.iter().map(|d| d.model_name.clone()).collect()); + Ok(Self { + host: Arc::new(host), + ..Self::index(0, deployments, aliases, routing_groups) + }) + } + + fn index( + version: RegistryVersion, + deployments: Vec>, + aliases: BTreeMap, + routing_groups: Vec, + ) -> Self { + let mut by_id = HashMap::new(); + let mut by_group: BTreeMap> = BTreeMap::new(); + let mut by_team: HashMap> = HashMap::new(); + for (index, deployment) in deployments.iter().enumerate() { + by_id.insert(deployment.id.clone(), index); + by_group + .entry(deployment.model_name.clone()) + .or_default() + .push(index); + if let Some(team) = &deployment.model_info.team_id { + by_team.entry(team.clone()).or_default().push(index); + } + } + // In the order each pattern first appears, then most specific first, as + // `PatternUtils.sorted_patterns` keeps them: a stable sort, longest regex first, + // then the most regex syntax. + let mut wildcards: Vec<(String, Vec)> = Vec::new(); + for deployment in &deployments { + let name = &deployment.model_name; + if name.contains('*') && !wildcards.iter().any(|(pattern, _)| pattern == name) { + wildcards.push(( + name.clone(), + by_group.get(name).cloned().unwrap_or_default(), + )); + } + } + wildcards.sort_by_key(|(pattern, _)| std::cmp::Reverse(pattern_specificity(pattern))); + Self { + version, + rewritten: version, + deployments, + by_id, + by_group, + by_team, + wildcards, + aliases, + routing_groups, + overrides: None, + host: Arc::default(), + member_groups: None, + } + } + + /// This registry with the stale routing-group member map (`None` derives it from the groups). + #[must_use] + pub fn with_member_groups(self, member_groups: Option>) -> Self { + Self { + member_groups: member_groups.map(Arc::new), + ..self + } + } + + pub fn version(&self) -> RegistryVersion { + self.version + } + + /// The version the deployments before the newest appends last changed at (see `rewritten`). + pub fn rewritten(&self) -> RegistryVersion { + self.rewritten + } + + /// Every deployment id, in list order (`names(kind="ids")`). + pub fn ids(&self) -> Vec { + self.deployments.iter().map(|d| d.id.clone()).collect() + } + + /// The deployments from position `start` on, in list order. + pub fn deployments_from(&self, start: usize) -> &[Arc] { + self.deployments.get(start..).unwrap_or_default() + } + + /// The next registry: upserts, then deletes (`apply_changes`). An upserted deployment whose + /// id exists is removed and appended at the end, as the Python router does on an edit. + pub fn apply( + &self, + changes: &ChangeSet, + aliases: Option>, + ) -> Result { + let mut deployments = match &changes.replace { + Some(specs) => specs + .iter() + .map(|spec| self.carried(spec.clone()).map(Arc::new)) + .collect::, _>>()?, + None => self.deployments.clone(), + }; + for spec in &changes.appends { + deployments.push(Arc::new(self.carried(spec.clone())?)); + } + for spec in &changes.upserts { + let deployment = self.carried(spec.clone())?; + deployments.retain(|existing| existing.id != deployment.id); + deployments.push(Arc::new(deployment)); + } + deployments.retain(|deployment| !changes.deletes.contains(&deployment.id)); + let mut host = HostIndexes::clone(&self.host); + if let Some(id) = &changes.remove + && let Some(position) = host.position_of(id) + && position < deployments.len() + { + deployments.remove(position); + host.removed(id, position) + .map_err(|error| ConfigError::Removal(error.to_string()))?; + } + if let Some(write) = &changes.host_index { + host.write(write.clone()); + } + let overrides = match &changes.index { + Some(index) => (!index.is_empty()).then(|| Arc::new(index.clone())), + None => self.overrides.clone(), + }; + // Appends alone leave every deployment before them as it was. + let appended_only = changes.replace.is_none() + && changes.upserts.is_empty() + && changes.deletes.is_empty() + && changes.remove.is_none(); + let next = Self::index( + self.version + 1, + deployments, + aliases.unwrap_or_else(|| self.aliases.clone()), + self.routing_groups.clone(), + ); + Ok(Self { + overrides, + host: Arc::new(host), + member_groups: self.member_groups.clone(), + rewritten: if appended_only { + self.rewritten + } else { + next.rewritten + }, + ..next + }) + } + + /// The next registry for a build starting over (`set_model_list`): no deployments, and the + /// indexes [`HostIndexes::reset`] clears cleared. + #[must_use] + pub fn emptied(&self) -> Self { + let mut host = HostIndexes::clone(&self.host); + host.reset(); + Self { + overrides: self.overrides.clone(), + host: Arc::new(host), + member_groups: self.member_groups.clone(), + ..Self::index( + self.version + 1, + Vec::new(), + self.aliases.clone(), + self.routing_groups.clone(), + ) + } + } + + /// Add one deployment a build accepted at the end and index it in place (`add` is + /// `add_deployment`, which also names its group). A build installs into a registry of its + /// own this way, so a list of n deployments builds in O(n) rather than reindexing per + /// deployment. + pub fn push_built(&mut self, spec: DeploymentSpec, add: bool) -> Result<(), ConfigError> { + let deployment = Arc::new(self.carried(spec)?); + let index = self.deployments.len(); + let record = deployment.record(); + Arc::make_mut(&mut self.host).added( + record.as_object().expect("a record is an object"), + index, + add, + ); + self.by_id.insert(deployment.id.clone(), index); + let name = &deployment.model_name; + self.by_group.entry(name.clone()).or_default().push(index); + if let Some(team) = &deployment.model_info.team_id { + self.by_team.entry(team.clone()).or_default().push(index); + } + if name.contains('*') { + match self + .wildcards + .iter_mut() + .find(|(pattern, _)| pattern == name) + { + Some((_, indices)) => indices.push(index), + None => { + // A new pattern joins after every one it ties with, as `index` orders them: + // first appearance, then a stable sort by specificity. + self.wildcards.push((name.clone(), vec![index])); + self.wildcards.sort_by_key(|(pattern, _)| { + std::cmp::Reverse(pattern_specificity(pattern)) + }); + } + } + } + self.deployments.push(deployment); + self.version += 1; + Ok(()) + } + + /// The last deployment added. + pub fn last(&self) -> Option<&Arc> { + self.deployments.last() + } + + /// Take `set_model_list`'s `model_names`: the names it was given. + pub fn set_model_names(&mut self, names: Vec) { + Arc::make_mut(&mut self.host).set_model_names(names); + self.version += 1; + } + + /// The indexes the host hands out. + pub fn host_indexes(&self) -> &HostIndexes { + &self.host + } + + /// The deployment `spec` describes, keeping the provider the host resolved for the + /// deployment it replaces (same id, same params) when the spec carries none: a host that + /// hands back its whole list after a write does not resolve every provider again. + fn carried(&self, mut spec: DeploymentSpec) -> Result { + let deployment = Deployment::from_spec(spec.clone())?; + if spec.provider.is_none() + && let Some(previous) = self + .by_id + .get(&deployment.id) + .and_then(|index| self.deployments.get(*index)) + && previous.raw_params == deployment.raw_params + && previous.model_name == deployment.model_name + { + spec.provider.clone_from(&previous.resolved_provider); + return Deployment::from_spec(spec); + } + Ok(deployment) + } + + /// This registry with the providers `from` resolved for the same deployments (same id, + /// same params) and `from`'s host indexes: a router rebuilt for new static settings over the + /// same list keeps what its host resolved and the indexes their history built. + #[must_use] + pub fn with_providers_of(&self, from: &Self) -> Self { + let deployments = self + .deployments + .iter() + .map(|deployment| { + let previous = from + .by_id + .get(&deployment.id) + .and_then(|index| from.deployments.get(*index)) + .filter(|previous| { + previous.raw_params == deployment.raw_params + && previous.model_name == deployment.model_name + }); + match previous { + Some(previous) if deployment.resolved_provider.is_none() => { + Arc::new(Deployment { + resolved_provider: previous.resolved_provider.clone(), + ..Deployment::clone(deployment) + }) + } + _ => deployment.clone(), + } + }) + .collect(); + Self { + deployments, + host: from.host.clone(), + ..self.clone() + } + } + + fn at(&self, indices: &[usize]) -> Vec> { + indices + .iter() + .filter_map(|index| self.deployments.get(*index).cloned()) + .collect() + } + + /// `_core_deployments_named(name)`: the deployments the model-name index holds for `name` + /// (whatever their own name), or `None` when it does not index the name. + pub(crate) fn named(&self, name: &str) -> Option>> { + match self.overrides.as_ref().and_then(|o| o.model_name.as_ref()) { + Some(index) => index.get(name).map(|indices| self.at(indices)), + None => self.by_group.get(name).map(|indices| self.at(indices)), + } + } + + /// Whether the model-name index holds `name` (`name in model_name_to_deployment_indices`). + fn indexes_name(&self, name: &str) -> bool { + match self.overrides.as_ref().and_then(|o| o.model_name.as_ref()) { + Some(index) => index.contains_key(name), + None => self.by_group.contains_key(name), + } + } + + /// `_team_deployments_named(team_id, name)`: the deployments the team index holds for the + /// pair, or `None` when it does not index it. + pub(crate) fn team_named(&self, team_id: &str, name: &str) -> Option>> { + match self.overrides.as_ref().and_then(|o| o.team_model.as_ref()) { + Some(entries) => entries + .iter() + .find(|(team, public, _)| team == team_id && public == name) + .map(|(_, _, indices)| self.at(indices)), + None => { + let own: Vec> = self + .deployments + .iter() + .filter(|d| { + d.model_info.team_id.as_deref() == Some(team_id) + && d.model_info.team_public_model_name.as_deref() == Some(name) + }) + .cloned() + .collect(); + (!own.is_empty()).then_some(own) + } + } + } + + /// Every deployment the team index holds under public name `name`, any team's + /// (`_team_deployments_across_teams`). + pub(crate) fn team_named_across_teams(&self, name: &str) -> Vec> { + match self.overrides.as_ref().and_then(|o| o.team_model.as_ref()) { + Some(entries) => entries + .iter() + .filter(|(_, public, _)| public == name) + .flat_map(|(_, _, indices)| self.at(indices)) + .collect(), + None => self + .deployments + .iter() + .filter(|d| { + d.model_info.team_id.is_some() + && d.model_info.team_public_model_name.as_deref() == Some(name) + }) + .cloned() + .collect(), + } + } + + /// Whether a written index entry names a position past the model list. + fn overflows(&self, indices: &[usize]) -> bool { + indices.iter().any(|index| *index >= self.deployments.len()) + } + + /// The written model-name index entry for `name` names a position past the model list. + pub(crate) fn name_index_overflows(&self, name: &str) -> bool { + self.overrides + .as_ref() + .and_then(|o| o.model_name.as_ref()) + .and_then(|index| index.get(name)) + .is_some_and(|indices| self.overflows(indices)) + } + + /// The written team index entry for `(team_id, name)` names a position past the model list. + pub(crate) fn team_index_overflows(&self, team_id: &str, name: &str) -> bool { + self.overrides + .as_ref() + .and_then(|o| o.team_model.as_ref()) + .and_then(|entries| { + entries + .iter() + .find(|(team, public, _)| team == team_id && public == name) + }) + .is_some_and(|(_, _, indices)| self.overflows(indices)) + } + + /// A written team index entry under public name `name` names a position past the list. + pub(crate) fn across_teams_index_overflows(&self, name: &str) -> bool { + self.overrides + .as_ref() + .and_then(|o| o.team_model.as_ref()) + .is_some_and(|entries| { + entries + .iter() + .any(|(_, public, indices)| public == name && self.overflows(indices)) + }) + } + + /// The group a pick of `name` reads its strategy from, when the stale member map names a + /// group that is no longer configured (`_get_routing_context` raises `KeyError`): `name` + /// after its alias, unless it is a callable routing group. + pub fn missing_member_group(&self, name: &str) -> Option<&str> { + let members = self.member_groups.as_ref()?; + let resolved = self.alias_of(name).unwrap_or(name); + if self.routing_group_named(resolved).is_some() { + return None; + } + let group = members.get(resolved)?; + (!self.routing_groups.iter().any(|g| g.group_name == *group)).then_some(group.as_str()) + } + + /// The routing group a member call of `model_group` routes by: the stale member map's + /// group when there is one (`_model_to_group`), else the non-priority group listing it. + pub(crate) fn member_routing_group(&self, model_group: &str) -> Option<&RoutingGroupSpec> { + match &self.member_groups { + Some(members) => members + .get(model_group) + .and_then(|name| self.routing_groups.iter().find(|g| g.group_name == *name)), + None => self + .routing_groups + .iter() + .filter(|group| !crate::routing_groups::is_priority(group)) + .find(|group| group.models.iter().any(|model| model == model_group)), + } + } + + pub fn deployment(&self, id: &str) -> Option> { + self.by_id + .get(id) + .map(|index| self.deployments[*index].clone()) + } + + pub fn deployments(&self, filter: &DeploymentFilter<'_>) -> Vec> { + let candidates = match (filter.model_name, filter.team_id) { + (Some(name), _) => self + .by_group + .get(name) + .map(|i| self.at(i)) + .unwrap_or_default(), + (None, Some(team)) => self + .by_team + .get(team) + .map(|i| self.at(i)) + .unwrap_or_default(), + (None, None) => self.deployments.clone(), + }; + candidates + .into_iter() + .filter(|d| { + filter + .team_id + .is_none_or(|team| d.model_info.team_id.as_deref() == Some(team)) + }) + .filter(|d| { + filter + .provider + .is_none_or(|provider| d.provider() == provider) + }) + .collect() + } + + /// The model group names, in name order, with aliases when asked. + pub fn names(&self, filter: &NameFilter) -> Vec { + let mut names: Vec = self.by_group.keys().cloned().collect(); + if filter.include_aliases { + names.extend(self.aliases.keys().cloned()); + } + names + } + + pub fn group(&self, name: &str) -> Option>> { + if self + .overrides + .as_ref() + .is_some_and(|o| o.model_name.is_some()) + { + return self.named(name).map(|deployments| { + deployments + .into_iter() + .filter(|d| d.model_name == name) + .collect() + }); + } + self.by_group.get(name).map(|indices| self.at(indices)) + } + + /// How many rows `_core_get_model_list(model_name=name)` lists: the group's deployments, + /// an alias's target group, a routing group's members, and only when none of those, the + /// deployments of the wildcard the name matches. + pub fn model_list_len(&self, name: &str) -> usize { + let count = |group: &str| self.group(group).map_or(0, |deployments| deployments.len()); + let listed = count(name) + + self.aliases.get(name).map_or(0, |target| count(target)) + + self + .routing_groups + .iter() + .find(|group| group.group_name == name) + .map_or(0, |group| { + group.models.iter().map(|model| count(model)).sum() + }); + if listed > 0 { + return listed; + } + self.wildcards + .iter() + .find(|(pattern, _)| wildcard_matches(pattern, name)) + .map_or(0, |(_, indices)| indices.len()) + } + + /// The routing group a model group belongs to, if any. + pub fn routing_group_of(&self, model_name: &str) -> Option<&RoutingGroupSpec> { + self.routing_groups + .iter() + .find(|group| group.models.iter().any(|model| model == model_name)) + } + + /// The strategy a routing group named `group_name` declares. + pub fn resolve_routing_group_strategy( + &self, + group_name: &str, + ) -> Option { + self.routing_groups + .iter() + .find(|group| group.group_name == group_name) + .map(|group| group.routing_strategy.clone()) + } + + pub(crate) fn routing_groups(&self) -> &[RoutingGroupSpec] { + &self.routing_groups + } + + /// Every deployment, in configured order. + pub(crate) fn all(&self) -> &[Arc] { + &self.deployments + } + + /// Whether `name` is a deployment `model_name` (`name in _core_model_names`). + pub(crate) fn has_name(&self, name: &str) -> bool { + match self.overrides.as_ref().and_then(|o| o.model_names.as_ref()) { + Some(names) => names.contains(name), + None => self.by_group.contains_key(name), + } + } + + /// The group `model_group_alias` rewrites `name` to. + pub(crate) fn alias_of(&self, name: &str) -> Option<&str> { + self.aliases.get(name).map(String::as_str) + } + + /// The callable routing group named `name`: a model group of that name shadows it. + pub(crate) fn routing_group_named(&self, name: &str) -> Option<&RoutingGroupSpec> { + (!self.indexes_name(name)) + .then(|| self.routing_groups.iter().find(|g| g.group_name == name)) + .flatten() + } + + /// Whether any deployment is listed under a wildcard pattern. + pub(crate) fn has_wildcards(&self) -> bool { + !self.wildcards.is_empty() + } + + /// The most specific wildcard pattern matching `name`, with its deployments. + pub(crate) fn wildcard_for(&self, name: &str) -> Option<(String, Vec>)> { + self.wildcards + .iter() + .find(|(pattern, _)| wildcard_matches(pattern, name)) + .map(|(pattern, indices)| (pattern.clone(), self.at(indices))) + } + + /// Resolve a requested name, in the order of `_common_checks_available_deployment`: + /// a specific deployment, an id, an alias, a routing group, a model group, a wildcard. + pub fn resolve(&self, name: &str, scope: ResolveScope) -> Option { + let resolution = |kind, group: &str, deployments: Vec>| { + (!deployments.is_empty()).then(|| Resolution { + kind, + group: group.to_owned(), + deployments, + }) + }; + if scope.specific_deployment { + let matching = self + .deployments + .iter() + .filter(|d| d.params.model == name) + .cloned() + .collect(); + // An empty match still resolves: the pick then finds no deployment rather than + // falling back to a default (`_common_checks_available_deployment` returns `[]`). + return Some(Resolution { + kind: ResolveKind::SpecificDeployment, + group: name.to_owned(), + deployments: matching, + }); + } + if !self.by_group.contains_key(name) + && let Some(deployment) = self.deployment(name) + { + let group = deployment.model_name.clone(); + return resolution(ResolveKind::Id, &group, vec![deployment]); + } + let routing_group_named = |name: &str| { + // A model group of the same name shadows a routing group (`get_routing_group`). + (!self.by_group.contains_key(name)) + .then(|| self.routing_groups.iter().find(|g| g.group_name == name)) + .flatten() + }; + if let Some(target) = self.aliases.get(name) { + if let Some(routing_group) = routing_group_named(target) { + let deployments = crate::routing_groups::members(routing_group, |model| { + self.by_group + .get(model) + .map(|indices| self.at(indices)) + .unwrap_or_default() + }); + return resolution(ResolveKind::RoutingGroup, target, deployments); + } + return self + .group(target) + .and_then(|deployments| resolution(ResolveKind::Alias, target, deployments)); + } + if let Some(routing_group) = routing_group_named(name) { + let deployments = crate::routing_groups::members(routing_group, |model| { + self.by_group + .get(model) + .map(|indices| self.at(indices)) + .unwrap_or_default() + }); + return resolution(ResolveKind::RoutingGroup, name, deployments); + } + if let Some(indices) = self.by_group.get(name) { + return resolution(ResolveKind::Group, name, self.at(indices)); + } + self.wildcards + .iter() + .find(|(pattern, _)| wildcard_matches(pattern, name)) + .and_then(|(pattern, indices)| { + resolution(ResolveKind::Wildcard, pattern, self.at(indices)) + }) + } + + /// Access group name to the model groups in it. + pub fn access_groups(&self) -> BTreeMap> { + let mut groups: BTreeMap> = BTreeMap::new(); + for deployment in &self.deployments { + for group in &deployment.model_info.access_groups { + groups + .entry(group.clone()) + .or_default() + .insert(deployment.model_name.clone()); + } + } + groups + } + + pub fn credentials(&self, id: &str) -> Option { + self.deployment(id).map(|deployment| Credentials { + provider: deployment.provider().to_owned(), + api_base: deployment.params.api_base.clone(), + api_version: deployment.params.api_version.clone(), + credential_name: deployment.params.litellm_credential_name.clone(), + params: deployment.params.clone(), + }) + } +} + +/// `PatternUtils.calculate_pattern_specificity` over the pattern's regex +/// (`re.escape(pattern).replace(r"\*", "(.*)")`): its length, then how much regex syntax it has. +fn pattern_specificity(pattern: &str) -> (usize, usize) { + let mut regex = String::new(); + for c in pattern.chars() { + match c { + '*' => regex.push_str("(.*)"), + '(' | ')' | '[' | ']' | '{' | '}' | '?' | '+' | '-' | '|' | '^' | '$' | '\\' | '.' + | '&' | '~' | '#' | ' ' | '\t' | '\n' | '\r' | '\x0b' | '\x0c' => { + regex.push('\\'); + regex.push(c); + } + _ => regex.push(c), + } + } + let complexity = regex + .chars() + .filter(|c| matches!(c, '*' | '+' | '?' | '\\' | '^' | '$' | '|' | '(' | ')')) + .count(); + (regex.chars().count(), complexity) +} + +/// `*` matches any run of characters, as the pattern router's `(.*)` does under `re.match`: +/// anchored at the start only, so the name may run on past the pattern's last literal. +fn wildcard_matches(pattern: &str, name: &str) -> bool { + let mut parts = pattern.split('*'); + let first = parts.next().unwrap_or_default(); + let Some(mut rest) = name.strip_prefix(first) else { + return false; + }; + let parts: Vec<&str> = parts.collect(); + for part in parts { + match rest.find(part) { + Some(at) => rest = &rest[at + part.len()..], + None => return false, + } + } + true +} + +/// `deployment_id` in `litellm/router_api.py`: sha256 over the model group and every +/// `litellm_params` key and value in order. A string is taken as is, a dict as `json.dumps`, and +/// anything else as Python's `str()`. +pub fn deployment_id(model_group: &str, litellm_params: &Map) -> String { + let mut text = String::from(model_group); + for (key, value) in litellm_params { + text.push_str(key); + match value { + Value::String(value) => text.push_str(value), + Value::Object(_) => json_dumps(value, &mut text), + Value::Null | Value::Bool(_) | Value::Number(_) | Value::Array(_) => { + python_str(value, &mut text); + } + } + } + let digest = Sha256::digest(text.as_bytes()); + let mut hex = String::with_capacity(64); + for byte in digest { + let _ = write!(hex, "{byte:02x}"); + } + hex +} + +/// Python's `repr(float)`: the shortest round-trip digits, positional for exponents in +/// `-4..16`, scientific otherwise. +fn python_float(value: f64, out: &mut String) { + if value.is_nan() { + out.push_str("nan"); + return; + } + if value.is_infinite() { + out.push_str(if value > 0.0 { "inf" } else { "-inf" }); + return; + } + let scientific = format!("{value:e}"); + let (mantissa, exponent) = scientific.split_once('e').unwrap_or((&scientific, "0")); + let exponent: i32 = exponent.parse().unwrap_or(0); + let (sign, mantissa) = mantissa + .strip_prefix('-') + .map_or(("", mantissa), |m| ("-", m)); + let digits: String = mantissa.chars().filter(char::is_ascii_digit).collect(); + out.push_str(sign); + if (-4..16).contains(&exponent) { + if exponent < 0 { + out.push_str("0."); + out.extend(std::iter::repeat_n('0', (-exponent - 1) as usize)); + out.push_str(&digits); + } else { + let point = exponent as usize + 1; + if digits.len() <= point { + out.push_str(&digits); + out.extend(std::iter::repeat_n('0', point - digits.len())); + out.push_str(".0"); + } else { + out.push_str(&digits[..point]); + out.push('.'); + out.push_str(&digits[point..]); + } + } + } else { + out.push_str(&digits[..1]); + if digits.len() > 1 { + out.push('.'); + out.push_str(&digits[1..]); + } + let _ = write!( + out, + "e{}{:02}", + if exponent < 0 { '-' } else { '+' }, + exponent.abs() + ); + } +} + +fn number(value: &serde_json::Number, out: &mut String) { + match value.as_f64() { + Some(float) if !value.is_i64() && !value.is_u64() => python_float(float, out), + Some(_) | None => out.push_str(&value.to_string()), + } +} + +/// `json.dumps` with its defaults: `", "` and `": "` separators and `ensure_ascii`. +fn json_dumps(value: &Value, out: &mut String) { + match value { + Value::Null => out.push_str("null"), + Value::Bool(flag) => out.push_str(if *flag { "true" } else { "false" }), + Value::Number(value) => number(value, out), + Value::String(text) => json_string(text, out), + Value::Array(items) => { + out.push('['); + for (index, item) in items.iter().enumerate() { + if index > 0 { + out.push_str(", "); + } + json_dumps(item, out); + } + out.push(']'); + } + Value::Object(entries) => { + out.push('{'); + for (index, (key, item)) in entries.iter().enumerate() { + if index > 0 { + out.push_str(", "); + } + json_string(key, out); + out.push_str(": "); + json_dumps(item, out); + } + out.push('}'); + } + } +} + +fn json_string(text: &str, out: &mut String) { + out.push('"'); + for ch in text.chars() { + match ch { + '"' => out.push_str("\\\""), + '\\' => out.push_str("\\\\"), + '\n' => out.push_str("\\n"), + '\r' => out.push_str("\\r"), + '\t' => out.push_str("\\t"), + '\u{08}' => out.push_str("\\b"), + '\u{0c}' => out.push_str("\\f"), + ch if ch.is_ascii() && !ch.is_ascii_control() => out.push(ch), + ch => { + let mut units = [0u16; 2]; + for unit in ch.encode_utf16(&mut units) { + let _ = write!(out, "\\u{unit:04x}"); + } + } + } + } + out.push('"'); +} + +/// Python's `str()` of a JSON value: `repr` for the items of a list or dict. +fn python_str(value: &Value, out: &mut String) { + match value { + Value::Null => out.push_str("None"), + Value::Bool(flag) => out.push_str(if *flag { "True" } else { "False" }), + Value::Number(value) => number(value, out), + Value::String(text) => python_repr_str(text, out), + Value::Array(items) => { + out.push('['); + for (index, item) in items.iter().enumerate() { + if index > 0 { + out.push_str(", "); + } + python_str(item, out); + } + out.push(']'); + } + Value::Object(entries) => { + out.push('{'); + for (index, (key, item)) in entries.iter().enumerate() { + if index > 0 { + out.push_str(", "); + } + python_repr_str(key, out); + out.push_str(": "); + python_str(item, out); + } + out.push('}'); + } + } +} + +fn python_repr_str(text: &str, out: &mut String) { + let quote = if text.contains('\'') && !text.contains('"') { + '"' + } else { + '\'' + }; + out.push(quote); + for ch in text.chars() { + match ch { + '\\' => out.push_str("\\\\"), + '\n' => out.push_str("\\n"), + '\r' => out.push_str("\\r"), + '\t' => out.push_str("\\t"), + ch if ch == quote => { + out.push('\\'); + out.push(ch); + } + ch if (ch as u32) < 0x20 || ch as u32 == 0x7f => { + let _ = write!(out, "\\x{:02x}", ch as u32); + } + ch => out.push(ch), + } + } + out.push(quote); +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + fn spec(model_name: &str, params: Value, info: Value) -> DeploymentSpec { + serde_json::from_value(json!({ + "model_name": model_name, "litellm_params": params, "model_info": info, + })) + .unwrap() + } + + #[rstest] + #[case::none(json!({}), json!({}), json!({}), false)] + #[case::params_rpm(json!({"rpm": 1}), json!({}), json!({}), true)] + #[case::params_itpm(json!({"itpm": 1}), json!({}), json!({}), true)] + #[case::model_info_rpm(json!({}), json!({"rpm": 1}), json!({}), true)] + #[case::model_info_tpm(json!({}), json!({"tpm": 1}), json!({}), true)] + #[case::model_info_otpm(json!({}), json!({"otpm": 1}), json!({}), true)] + #[case::model_info_null(json!({}), json!({"rpm": null}), json!({}), false)] + #[case::top_level_tpm(json!({}), json!({}), json!({"tpm": 1}), true)] + fn a_limit_anywhere_on_the_deployment_tracks_usage( + #[case] params: Value, + #[case] info: Value, + #[case] entry: Value, + #[case] tracks: bool, + ) { + let mut spec = json!({ + "model_name": "g", + "litellm_params": {"model": "openai/a"}, + "model_info": {"id": "a"}, + }); + let extend = |section: &mut Value, more: Value| { + section + .as_object_mut() + .unwrap() + .extend(more.as_object().unwrap().clone()); + }; + extend(&mut spec["litellm_params"], params); + extend(&mut spec["model_info"], info); + extend(&mut spec, entry); + let spec: DeploymentSpec = serde_json::from_value(spec).unwrap(); + assert_eq!(Deployment::from_spec(spec).unwrap().tracks_usage(), tracks); + } + + #[rstest] + #[case::params_int(json!({"model": "m", "order": 2}), json!({}), Some(2))] + #[case::params_win(json!({"model": "m", "order": 2}), json!({"order": 1}), Some(2))] + #[case::model_info(json!({"model": "m"}), json!({"order": 3}), Some(3))] + #[case::params_null(json!({"model": "m", "order": null}), json!({"order": 3}), Some(3))] + #[case::numeric_string(json!({"model": "m", "order": "4"}), json!({}), Some(4))] + #[case::model_info_string(json!({"model": "m"}), json!({"order": "5"}), Some(5))] + #[case::whole_float(json!({"model": "m", "order": 6.0}), json!({}), Some(6))] + #[case::none(json!({"model": "m"}), json!({}), None)] + fn order_reads_as_get_deployment_order( + #[case] params: Value, + #[case] info: Value, + #[case] expected: Option, + ) { + let deployment = Deployment::from_spec(spec("g", params, info)).unwrap(); + assert_eq!(deployment.order(), expected); + } + + #[rstest] + #[case::unset(json!({}), true)] + #[case::declared(json!({"supports_web_search": true}), true)] + #[case::refused(json!({"supports_web_search": false}), false)] + #[case::null_is_unset(json!({"supports_web_search": null}), true)] + fn web_search_support_is_assumed_unless_declared(#[case] info: Value, #[case] expected: bool) { + let deployment = Deployment::from_spec(spec("g", json!({"model": "m"}), info)).unwrap(); + assert_eq!(deployment.supports_web_search(), expected); + } + + #[test] + fn a_routed_wildcard_fills_its_model_and_drops_the_cache_flags() { + let deployment = Arc::new( + Deployment::from_spec(spec( + "anthropic/*", + json!({"model": "anthropic/*"}), + json!({"id": "w", "supports_prompt_caching": true, "keep": 1}), + )) + .unwrap(), + ); + let routed = routed_deployment( + &deployment, + &["claude-3-haiku".to_owned()], + "anthropic/claude-3-haiku", + ); + assert_eq!(routed.params.model, "anthropic/claude-3-haiku"); + assert_eq!(routed.raw_params["model"], "anthropic/claude-3-haiku"); + assert_eq!(routed.record()["model_info"], json!({"id": "w", "keep": 1})); + } + + #[rstest] + #[case::no_team_lists_a_team_owned_one(Some("t1"), None, true)] + #[case::no_team_lists_an_unowned_one(None, None, true)] + #[case::the_owner_lists_it(Some("t1"), Some("t1"), true)] + #[case::another_team_does_not(Some("t1"), Some("t2"), false)] + #[case::a_team_lists_an_unowned_one(None, Some("t2"), true)] + fn listed_for_team_lets_no_team_see_every_deployment( + #[case] owner: Option<&str>, + #[case] team: Option<&str>, + #[case] listed: bool, + ) { + let deployment = Deployment::from_spec(spec( + "g", + json!({"model": "openai/a"}), + json!({"id": "a", "team_id": owner}), + )) + .unwrap(); + assert_eq!(deployment.listed_for_team(team), listed); + } + + /// Expected ids computed with `litellm.router_api.deployment_id`. + #[rstest] + #[case::strings( + "g", + json!({"model": "openai/gpt-4o", "api_key": "sk-1"}), + "30256ba697cc98ce2aff32c3b73c4b90514cb199876aef429ffcd91ae826d025" + )] + #[case::scalars( + "claude", + json!({"model": "anthropic/claude-3", "rpm": 10, "timeout": 1.5, "stream": true, "x": null}), + "645fd1504089c1084316573ccfc5dd1dd9622623b169026657484fb64a2c89a2" + )] + #[case::list_and_dict( + "m", + json!({"model": "azure/x", "tags": ["a", "b'c"], "extra_body": {"k": [1, 2.0, "é"], "z": {"q": false}}}), + "64f11e16dabed321268bd92132de2020290ef193c0cf554b2c74faee8badbb96" + )] + fn deployment_id_matches_python( + #[case] group: &str, + #[case] params: Value, + #[case] expected: &str, + ) { + let Value::Object(params) = params else { + unreachable!() + }; + assert_eq!(deployment_id(group, ¶ms), expected); + } + + #[rstest] + #[case::integral(2.0, "2.0")] + #[case::small(0.00001, "1e-05")] + #[case::large(1e16, "1e+16")] + #[case::fraction(0.1, "0.1")] + fn floats_print_as_python_repr(#[case] value: f64, #[case] expected: &str) { + let mut out = String::new(); + python_float(value, &mut out); + assert_eq!(out, expected); + } + + #[rstest] + #[case::group("gpt-4", ResolveKind::Group, "gpt-4")] + #[case::alias("smart", ResolveKind::Alias, "gpt-4")] + #[case::id("dep-b", ResolveKind::Id, "gpt-4")] + #[case::wildcard("anthropic/claude-x", ResolveKind::Wildcard, "anthropic/*")] + fn resolve_follows_python_order( + #[case] name: &str, + #[case] kind: ResolveKind, + #[case] group: &str, + ) { + let registry = Registry::build( + vec![ + spec( + "gpt-4", + json!({"model": "openai/gpt-4"}), + json!({"id": "dep-a"}), + ), + spec( + "gpt-4", + json!({"model": "azure/gpt-4"}), + json!({"id": "dep-b"}), + ), + spec("anthropic/*", json!({"model": "anthropic/*"}), json!({})), + ], + BTreeMap::from([("smart".to_owned(), "gpt-4".to_owned())]), + Vec::new(), + ) + .unwrap(); + let resolution = registry.resolve(name, ResolveScope::default()).unwrap(); + assert_eq!((resolution.kind, resolution.group.as_str()), (kind, group)); + } + + #[rstest] + fn apply_moves_an_edited_deployment_to_the_end() { + let registry = Registry::build( + vec![ + spec("a", json!({"model": "openai/a"}), json!({"id": "1"})), + spec("a", json!({"model": "openai/b"}), json!({"id": "2"})), + ], + BTreeMap::new(), + Vec::new(), + ) + .unwrap(); + let next = registry + .apply( + &ChangeSet { + upserts: vec![spec("a", json!({"model": "openai/c"}), json!({"id": "1"}))], + ..ChangeSet::default() + }, + None, + ) + .unwrap(); + let ids: Vec = next + .group("a") + .unwrap() + .iter() + .map(|d| d.id.clone()) + .collect(); + assert_eq!( + (next.version(), ids), + (1, vec!["2".to_owned(), "1".to_owned()]) + ); + } +} diff --git a/litellm-rust/crates/router-core/src/resolve.rs b/litellm-rust/crates/router-core/src/resolve.rs new file mode 100644 index 00000000000..9075fc36c53 --- /dev/null +++ b/litellm-rust/crates/router-core/src/resolve.rs @@ -0,0 +1,585 @@ +//! A requested name to the deployments that may serve this caller: a port of +//! `_common_checks_available_deployment`. In order: a specific deployment, a deployment id, the +//! alias, a routing group, then for a name no deployment has, a team's public name, every team's +//! public name for a proxy admin, a wildcard; else the group (team-first), kept to the caller's +//! access groups, then deployments whose litellm model is the name, then the first default +//! fallback. Every arm drops strategy markers and deployments that refuse the request's endpoint, +//! and withholds deployments reserved for other teams. + +use std::{collections::BTreeSet, sync::Arc}; + +use jiff::Timestamp; + +use serde_json::Value; + +use crate::{ + access::{filter_by_access_groups, filter_reserved}, + eligibility::eligible_deployments, + error::Error, + host_index::{pattern_to_regex, regex_match}, + registry::{Deployment, DeploymentSpec, Registry, Resolution, ResolveKind, routed_deployment}, + select::is_strategy_marker, +}; + +/// Who is asking, as the request's auth metadata says. +#[derive(Clone, Copy, Debug, Default)] +pub struct Caller<'a> { + /// `user_api_key_team_id`. + pub team_id: Option<&'a str>, + /// The caller's `user_role` is `proxy_admin`. + pub proxy_admin: bool, + /// The caller's `models` plus `team_models`. + pub allowed_models: &'a [String], + /// The endpoint the pick runs under (`endpoint_selection`), which deployments may refuse. + pub endpoint: Option<&'a str>, + /// The model `endpoint_selection` was given: the name an endpoint refusal reads. + pub requested: &'a str, + /// `f"{provider}/{model}"`, the spelling `PatternMatchRouter.get_pattern` tries when no + /// pattern matches the name itself. + pub wildcard_request: Option<&'a str>, +} + +/// `_core_should_include_deployment`: the team's own deployment under its public name, or a +/// deployment named `model_name` the team may use. +fn included(deployment: &Deployment, model_name: &str, team_id: Option<&str>) -> bool { + let info = &deployment.model_info; + if team_id.is_some() + && info.team_id.as_deref() == team_id + && info.team_public_model_name.as_deref() == Some(model_name) + { + return true; + } + deployment.model_name == model_name + && (team_id.is_none() || info.team_id.is_none() || info.team_id.as_deref() == team_id) +} + +/// `_core_get_all_deployments(model_name, team_id)`: the team's deployments under that public +/// name when it has any, else the deployments named `model_name` the team may use; a name the +/// model-name index does not hold is looked for in every deployment, for a team. +pub fn all_deployments( + registry: &Registry, + model_name: &str, + team_id: Option<&str>, +) -> Result>, Error> { + let keep = |deployments: Vec>| -> Vec> { + deployments + .into_iter() + .filter(|d| included(d, model_name, team_id)) + .collect() + }; + // A written index position past the model list raises `IndexError` where it is read. + let out_of_range = || Error::IndexOutOfRange { + model: model_name.to_owned(), + }; + if let Some(team) = team_id { + if registry.team_index_overflows(team, model_name) { + return Err(out_of_range()); + } + if let Some(own) = registry.team_named(team, model_name) { + let own = keep(own); + if !own.is_empty() { + return Ok(own); + } + } + } + if registry.name_index_overflows(model_name) { + return Err(out_of_range()); + } + Ok(match registry.named(model_name) { + Some(named) => keep(named), + None if team_id.is_some() => keep(registry.all().to_vec()), + None => Vec::new(), + }) +} + +/// `_team_deployments_across_teams`: every team's deployments under public name `model`, for a +/// proxy admin calling without a team; a name several teams share is refused. +fn across_teams(registry: &Registry, model: &str) -> Result>, Error> { + if registry.across_teams_index_overflows(model) { + return Err(Error::IndexOutOfRange { + model: model.to_owned(), + }); + } + let deployments = registry.team_named_across_teams(model); + let teams: BTreeSet<&str> = deployments + .iter() + .filter_map(|d| d.model_info.team_id.as_deref()) + .collect(); + if teams.len() > 1 { + return Err(Error::MultipleTeams { + model: model.to_owned(), + }); + } + Ok(deployments) +} + +/// The access groups of the rows `_core_get_model_list(model_name, team_id)` lists: the +/// group's deployments, an alias's target deployments, a routing group's rows (which carry no +/// access groups), and only when there are none of those, the wildcard's deployments. +fn model_access_groups( + registry: &Registry, + model: &str, + team_id: Option<&str>, +) -> BTreeSet { + let mut rows = all_deployments(registry, model, team_id).unwrap_or_default(); + let mut stripped_rows = 0; + if let Some(target) = registry.alias_of(model) { + match registry.routing_group_named(target) { + Some(group) => stripped_rows += routing_group_rows(registry, group, None).len(), + None => rows.extend(all_deployments(registry, target, None).unwrap_or_default()), + } + } + if let Some(group) = registry.routing_group_named(model) { + stripped_rows += routing_group_rows(registry, group, None).len(); + } + if rows.is_empty() && stripped_rows == 0 { + rows = registry + .wildcard_for(model) + .map(|(_, deployments)| deployments) + .unwrap_or_default(); + } + rows.iter() + .flat_map(|d| d.model_info.access_groups.iter().cloned()) + .collect() +} + +fn routing_group_rows( + registry: &Registry, + group: &crate::registry::RoutingGroupSpec, + team_id: Option<&str>, +) -> Vec> { + crate::routing_groups::members(group, |member| { + all_deployments(registry, member, team_id).unwrap_or_default() + }) +} + +/// `_filter_reserved_deployments` for deployments resolved as `model`: markers dropped (only +/// markers is refused), those that refuse the caller's endpoint dropped (`_drop_strategy_markers`), +/// then the deployments an active access window withholds; when that leaves nothing, the window +/// is named in the refusal. +fn reserved( + model: &str, + deployments: Vec>, + caller: Caller<'_>, + now: Timestamp, +) -> Result>, Error> { + let any = !deployments.is_empty(); + let selectable: Vec> = deployments + .into_iter() + .filter(|d| !is_strategy_marker(d)) + .collect(); + if any && selectable.is_empty() { + return Err(Error::OnlyMarkers { + model: model.to_owned(), + }); + } + let selectable = eligible_deployments(model, caller, selectable)?; + let (kept, blocking) = filter_reserved(selectable, caller.team_id, now); + match blocking { + Some(window) if kept.is_empty() => Err(Error::Reserved { + model: model.to_owned(), + until: window.end_hhmm(), + timezone: window.timezone, + }), + _ => Ok(kept), + } +} + +/// `PatternMatchRouter.route`: copies of a pattern's deployments serving `request`. +fn routed_wildcard( + pattern: &str, + request: &str, + deployments: &[Arc], +) -> Vec> { + let groups = regex_match(&pattern_to_regex(pattern), request).unwrap_or_default(); + deployments + .iter() + .map(|deployment| routed_deployment(deployment, &groups, request)) + .collect() +} + +/// `get_pattern` for `model`: the most specific pattern matching it as spelled, else its +/// provider-prefixed spelling, with the pattern's deployments serving that request. +fn wildcard_route( + registry: &Registry, + model: &str, + wildcard_request: Option<&str>, +) -> Option<(String, Vec>)> { + let route = |request: &str| { + registry + .wildcard_for(request) + .map(|(pattern, deployments)| { + let routed = routed_wildcard(&pattern, request, &deployments); + (pattern, routed) + }) + }; + route(model).or_else(|| route(wildcard_request?)) +} + +/// The name resolution would look for under its provider (`get_pattern`'s second spelling), which +/// only the host can infer: one that reaches the pattern routers and that no pattern matches as +/// spelled. +pub(crate) fn wildcard_name<'a>( + registry: &'a Registry, + name: &'a str, + specific_deployment: bool, +) -> Option<&'a str> { + let model = registry.alias_of(name).unwrap_or(name); + (registry.has_wildcards() + && !specific_deployment + && !registry.has_name(model) + && (registry.has_name(name) || registry.deployment(name).is_none()) + && registry.routing_group_named(model).is_none() + && registry.wildcard_for(model).is_none()) + .then_some(model) +} + +/// The first default fallback a name no deployment serves is routed to. +pub fn default_target(dynamic: &crate::config::RouterDynamicConfig) -> Option<&str> { + dynamic + .fallbacks + .default_target() + .or_else(|| dynamic.default_fallbacks.first().map(String::as_str)) +} + +/// The router's `default_deployment`, as resolution serves it. +#[derive(Clone, Copy, Debug)] +pub enum DefaultDeployment<'a> { + Spec(&'a DeploymentSpec), + /// A value Python cannot copy for a name: resolving to it raises. + Raises, +} + +/// The default deployment as served for `model`: a copy whose `litellm_params.model` is the name. +fn default_for(spec: &DeploymentSpec, model: &str) -> Option> { + let mut spec = spec.clone(); + spec.litellm_params + .insert("model".to_owned(), Value::String(model.to_owned())); + Deployment::from_spec(spec).ok().map(Arc::new) +} + +/// `_core_get_routable_deployments`: the deployments resolution would consider for `request`, +/// before any team, cooldown or strategy filter; nothing when it resolves to nothing or refuses. +pub fn routable( + registry: &Registry, + dynamic: &crate::config::RouterDynamicConfig, + request: &crate::host::RouterRequest, +) -> Vec> { + let caller = Caller { + team_id: request.team_id.as_deref(), + proxy_admin: request.proxy_admin, + allowed_models: &request.allowed_models, + endpoint: request.endpoint.as_deref(), + requested: &request.model, + wildcard_request: request.wildcard_request.as_deref(), + }; + match resolve_request( + registry, + &request.model, + false, + caller, + default_target(dynamic), + dynamic.default_ref(), + Timestamp::now(), + ) { + Ok(Some(resolution)) => resolution.deployments, + Ok(None) | Err(_) => Vec::new(), + } +} + +/// Resolve `name` for `caller`. `None` when nothing serves it (`no_healthy_deployments`). +pub fn resolve_request( + registry: &Registry, + name: &str, + specific_deployment: bool, + caller: Caller<'_>, + default_target: Option<&str>, + default_deployment: Option>, + now: Timestamp, +) -> Result, Error> { + let team_id = caller.team_id; + let resolved = |kind, group: &str, deployments| { + Ok(Some(Resolution { + kind, + group: group.to_owned(), + deployments, + })) + }; + if specific_deployment { + let matching = registry + .all() + .iter() + .filter(|d| d.params.model == name) + .cloned() + .collect(); + let kept = reserved(name, matching, caller, now)?; + return resolved(ResolveKind::SpecificDeployment, name, kept); + } + if !registry.has_name(name) + && let Some(deployment) = registry.deployment(name) + { + let group = deployment.model_name.clone(); + let litellm_model = deployment.params.model.clone(); + let kept = reserved(&litellm_model, vec![deployment], caller, now)?; + return resolved(ResolveKind::Id, &group, kept); + } + let aliased = registry.alias_of(name); + let model = aliased.unwrap_or(name); + let routing_group = registry + .routing_group_named(model) + .map(|group| routing_group_rows(registry, group, team_id)); + if routing_group.is_none() && !registry.has_name(model) { + let early = match team_id { + Some(team) => Some(all_deployments(registry, model, Some(team))?), + None if caller.proxy_admin => Some(across_teams(registry, model)?), + None => None, + } + .filter(|deployments| !deployments.is_empty()); + if let Some(deployments) = early { + let kept = reserved(model, deployments, caller, now)?; + return resolved(ResolveKind::Group, model, kept); + } + // `_core_wildcard_route_deployments`: the team's own pattern, else the proxy-wide one. + let team_owned = team_id + .map(|team| crate::lookup::Lookup::new(registry).team_wildcard(model, team)) + .filter(|deployments| !deployments.is_empty()); + if let Some(deployments) = team_owned { + let routed = deployments.iter().flat_map(|deployment| { + let public = deployment.model_info.team_public_model_name.as_deref(); + let pattern = public.unwrap_or(model); + routed_wildcard(pattern, model, std::slice::from_ref(deployment)) + }); + let kept = reserved(model, routed.collect(), caller, now)?; + return resolved(ResolveKind::Wildcard, model, kept); + } + if let Some((pattern, deployments)) = + wildcard_route(registry, model, caller.wildcard_request) + { + let kept = reserved(model, deployments, caller, now)?; + return resolved(ResolveKind::Wildcard, &pattern, kept); + } + match default_deployment { + Some(DefaultDeployment::Raises) => { + return Err(Error::DefaultDeploymentRaises { + model: model.to_owned(), + }); + } + Some(DefaultDeployment::Spec(spec)) => { + if let Some(deployment) = default_for(spec, model) { + let kept = reserved(model, vec![deployment], caller, now)?; + return resolved(ResolveKind::Default, model, kept); + } + } + None => {} + } + } + let (kind, listed) = match routing_group { + Some(deployments) => (ResolveKind::RoutingGroup, deployments), + None if aliased.is_some() => ( + ResolveKind::Alias, + all_deployments(registry, model, team_id)?, + ), + None => ( + ResolveKind::Group, + all_deployments(registry, model, team_id)?, + ), + }; + let narrow = |model: &str, deployments: Vec>| { + let allowed = filter_by_access_groups(model, deployments, caller.allowed_models, || { + model_access_groups(registry, model, team_id) + }); + reserved(model, allowed, caller, now) + }; + let listed_any = !listed.is_empty(); + let deployments = narrow(model, listed)?; + if !deployments.is_empty() { + return resolved(kind, model, deployments); + } + let mut access_emptied = listed_any; + if !listed_any { + // The caller may have named a deployment's litellm model instead. + let by_model: Vec> = registry + .all() + .iter() + .filter(|d| d.params.model == model) + .cloned() + .collect(); + let found = !by_model.is_empty(); + let deployments = narrow(model, by_model)?; + if !deployments.is_empty() { + return resolved(ResolveKind::Group, model, deployments); + } + access_emptied = found; + } + if let Some(target) = default_target.filter(|target| !access_emptied && !target.is_empty()) { + let deployments = narrow(target, all_deployments(registry, target, team_id)?)?; + if !deployments.is_empty() { + return resolved(ResolveKind::Group, target, deployments); + } + // `_common_checks_available_deployment` re-assigned the name: its error names the target. + return Err(Error::UnknownModel { + model: target.to_owned(), + }); + } + Ok(None) +} + +#[cfg(test)] +mod tests { + use std::collections::BTreeMap; + + use serde_json::{Value, json}; + + use super::*; + use crate::registry::DeploymentSpec; + + fn registry(entries: Value) -> Registry { + let specs: Vec = serde_json::from_value(entries).unwrap(); + Registry::build(specs, BTreeMap::new(), Vec::new()).unwrap() + } + + fn ids(resolution: Option) -> Vec { + resolution + .map(|r| r.deployments.iter().map(|d| d.id.clone()).collect()) + .unwrap_or_default() + } + + #[test] + fn an_access_group_only_caller_is_kept_to_its_groups() { + let registry = registry(json!([ + {"model_name": "g", "litellm_params": {"model": "openai/a"}, "model_info": {"id": "a", "access_groups": ["A"]}}, + {"model_name": "g", "litellm_params": {"model": "openai/b"}, "model_info": {"id": "b", "access_groups": ["B"]}}, + ])); + let allowed = vec!["A".to_owned()]; + let caller = Caller { + allowed_models: &allowed, + ..Caller::default() + }; + let resolved = resolve_request(®istry, "g", false, caller, None, None, Timestamp::now()); + assert_eq!(ids(resolved.unwrap()), ["a"]); + // The litellm model string is not narrowed (python-fixes-to-make.md). + let by_model = resolve_request( + ®istry, + "openai/b", + false, + caller, + None, + None, + Timestamp::now(), + ); + assert_eq!(ids(by_model.unwrap()), ["b"]); + } + + #[test] + fn a_proxy_admin_is_refused_a_public_name_several_teams_share() { + let registry = registry(json!([ + {"model_name": "x", "litellm_params": {"model": "openai/x"}, "model_info": {"id": "x", "team_id": "tx", "team_public_model_name": "pub"}}, + {"model_name": "y", "litellm_params": {"model": "openai/y"}, "model_info": {"id": "y", "team_id": "ty", "team_public_model_name": "pub"}}, + ])); + let caller = Caller { + proxy_admin: true, + ..Caller::default() + }; + let refused = resolve_request( + ®istry, + "pub", + false, + caller, + None, + None, + Timestamp::now(), + ); + assert!(matches!(refused, Err(Error::MultipleTeams { model }) if model == "pub")); + } + + fn wildcard_group() -> Value { + json!([{ + "model_name": "openai/*", + "litellm_params": {"model": "openai/*"}, + "model_info": {"id": "w", "supports_prompt_cache_breakpoint": true}, + }]) + } + + #[test] + fn a_wildcard_serves_the_matched_model_without_its_cache_flags() { + let registry = registry(wildcard_group()); + let resolved = resolve_request( + ®istry, + "openai/gpt-4o", + false, + Caller::default(), + None, + None, + Timestamp::now(), + ); + let resolution = resolved.unwrap().unwrap(); + assert_eq!(resolution.kind, ResolveKind::Wildcard); + assert_eq!(resolution.deployments[0].params.model, "openai/gpt-4o"); + assert_eq!( + resolution.deployments[0].record()["model_info"], + json!({"id": "w"}) + ); + } + + #[test] + fn an_alias_to_a_wildcard_fills_the_model_from_its_target() { + let specs: Vec = serde_json::from_value(wildcard_group()).unwrap(); + let aliases = BTreeMap::from([("al".to_owned(), "openai/gpt-4o".to_owned())]); + let registry = Registry::build(specs, aliases, Vec::new()).unwrap(); + let resolved = resolve_request( + ®istry, + "al", + false, + Caller::default(), + None, + None, + Timestamp::now(), + ); + assert_eq!( + resolved.unwrap().unwrap().deployments[0].params.model, + "openai/gpt-4o" + ); + } + + #[test] + fn a_name_no_pattern_matches_is_tried_under_its_provider() { + let registry = registry(wildcard_group()); + assert_eq!(wildcard_name(®istry, "gpt-4o", false), Some("gpt-4o")); + assert_eq!(wildcard_name(®istry, "openai/gpt-4o", false), None); + let caller = Caller { + wildcard_request: Some("openai/gpt-4o"), + ..Caller::default() + }; + let resolved = resolve_request( + ®istry, + "gpt-4o", + false, + caller, + None, + None, + Timestamp::now(), + ); + let resolution = resolved.unwrap().unwrap(); + assert_eq!(resolution.group, "openai/*"); + assert_eq!(resolution.deployments[0].params.model, "openai/gpt-4o"); + } + + #[test] + fn a_deployment_named_by_id_refuses_the_endpoint_like_any_other() { + let registry = registry(json!([ + {"model_name": "g", "litellm_params": {"model": "openai/a"}, "model_info": { + "id": "a", "enforce_supported_endpoints": true, "supported_endpoints": ["/v1/embeddings"], + }}, + ])); + let caller = Caller { + endpoint: Some("/v1/chat/completions"), + requested: "a", + ..Caller::default() + }; + let refused = resolve_request(®istry, "a", false, caller, None, None, Timestamp::now()); + assert!(matches!( + refused, + Err(Error::EndpointNotSupported { model, .. }) if model == "openai/a" + )); + } +} diff --git a/litellm-rust/crates/router-core/src/retry.rs b/litellm-rust/crates/router-core/src/retry.rs new file mode 100644 index 00000000000..3de0ad601e3 --- /dev/null +++ b/litellm-rust/crates/router-core/src/retry.rs @@ -0,0 +1,219 @@ +//! Retry decisions: how many retries a `RetryPolicy` grants for a failure, and whether a failure +//! is retried in the same group at all. Mirrors `get_num_retries_from_retry_policy` and +//! `resolve_retry_policy` in `litellm_core_utils/get_retry_from_policy.py`, and +//! `Router.should_retry_this_error`. + +use std::collections::BTreeMap; + +use crate::{ + config::RetryPolicy, + error::{AttemptError, FailureKind}, + health::should_retry_status, +}; + +/// `resolve_retry_policy`: the group's own policy when `model_group_retry_policy` has one, else +/// the router's `retry_policy`. +pub fn resolve_retry_policy<'a>( + retry_policy: Option<&'a RetryPolicy>, + model_group: &str, + model_group_retry_policy: Option<&'a BTreeMap>, +) -> Option<&'a RetryPolicy> { + model_group_retry_policy + .and_then(|policies| policies.get(model_group)) + .or(retry_policy) +} + +impl RetryPolicy { + /// `get_num_retries_from_retry_policy`: `DefaultRetries` for an `UnsupportedEndpointError`; + /// else `NotFoundErrorRetries` for any 404 answer, then the most specific exception class + /// the policy names, then `DefaultRetries`. + pub fn retries_for(&self, failure: &AttemptError) -> Option { + if failure.is_a("UnsupportedEndpointError") { + return self.DefaultRetries; + } + let not_found = (failure.status == Some(404)) + .then_some(self.NotFoundErrorRetries) + .flatten(); + not_found + .or_else(|| { + failure + .class_names() + .iter() + .find_map(|class| self.field_for(class)) + }) + .or(self.DefaultRetries) + } + + /// `_RETRIES_BY_EXCEPTION_TYPE`: the policy field an exception class reads. + fn field_for(&self, class: &str) -> Option { + match class { + "AuthenticationError" => self.AuthenticationErrorRetries, + "Timeout" => self.TimeoutErrorRetries, + "RateLimitError" => self.RateLimitErrorRetries, + "ContentPolicyViolationError" => self.ContentPolicyViolationErrorRetries, + "BadRequestError" => self.BadRequestErrorRetries, + "ServiceUnavailableError" => self.ServiceUnavailableErrorRetries, + "InternalServerError" => self.InternalServerErrorRetries, + _ => None, + } + } +} + +/// What `should_retry_this_error` knows besides the failure. +#[derive(Clone, Copy, Debug, Default)] +pub struct RetryContext { + pub healthy: usize, + pub all: usize, + /// `context_window_fallbacks is not None`. + pub has_context_window_fallbacks: bool, + /// `content_policy_fallbacks is not None`. + pub has_content_policy_fallbacks: bool, + /// `regular_fallbacks is not None and len(regular_fallbacks) > 0`. + pub has_regular_fallbacks: bool, +} + +/// `should_retry_this_error`, as a predicate: `false` where Python raises the error. +pub fn should_retry(failure: &AttemptError, ctx: RetryContext) -> bool { + if failure.is_a("ContextWindowExceededError") && ctx.has_context_window_fallbacks { + return false; + } + if failure.is_a("ContentPolicyViolationError") && ctx.has_content_policy_fallbacks { + return false; + } + if let Some(status) = failure.status + && !should_retry_status(status) + && !matches!(status, 401 | 403) + && !failure.is_a("UnsupportedEndpointError") + { + return false; + } + if failure.is_a("NotFoundError") { + return false; + } + if failure.is_a("RateLimitError") && ctx.healthy == 0 && ctx.has_regular_fallbacks { + return false; + } + if (failure.is_a("AuthenticationError") || failure.is_a("PermissionDeniedError")) + && ctx.all <= 1 + { + return false; + } + ctx.healthy > 0 +} + +/// `ContentPolicyViolationError`'s classes, most specific first. +pub(crate) fn content_policy_classes() -> Vec> { + [ + "ContentPolicyViolationError", + "BadRequestError", + "APIStatusError", + "APIError", + "OpenAIError", + "Exception", + "BaseException", + "object", + ] + .into_iter() + .map(Into::into) + .collect() +} + +/// The exception classes a failure kind stands for, most specific first, for a host that +/// reports no class names (`litellm/exceptions.py`). +pub(crate) fn kind_classes(kind: FailureKind) -> &'static [&'static str] { + match kind { + FailureKind::RateLimit => &["RateLimitError"], + FailureKind::ContextWindowExceeded => &["ContextWindowExceededError", "BadRequestError"], + FailureKind::ContentPolicyViolation => &["ContentPolicyViolationError", "BadRequestError"], + FailureKind::Authentication => &["AuthenticationError"], + FailureKind::PermissionDenied => &["PermissionDeniedError"], + FailureKind::NotFound => &["NotFoundError"], + FailureKind::BadRequest => &["BadRequestError"], + FailureKind::Timeout => &["Timeout", "APITimeoutError", "APIConnectionError"], + FailureKind::ApiConnection => &["APIConnectionError"], + FailureKind::InternalServer => &["InternalServerError"], + FailureKind::ServiceUnavailable => &["ServiceUnavailableError"], + FailureKind::BadGateway => &["BadGatewayError"], + FailureKind::CallerCredentialAuthentication => { + &["CallerCredentialAuthenticationError", "AuthenticationError"] + } + FailureKind::CallerCredentialRateLimit => { + &["CallerCredentialRateLimitError", "RateLimitError"] + } + FailureKind::GuardrailIntervention | FailureKind::Declined | FailureKind::Other => &[], + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + + use super::*; + + fn failure(kind: FailureKind, status: Option, classes: &[&str]) -> AttemptError { + let mut failure = AttemptError::new(kind, status); + failure.classes = classes.iter().map(|class| (*class).into()).collect(); + failure + } + + #[rstest] + #[case::own_field(failure(FailureKind::InternalServer, Some(500), &[]), Some(4))] + #[case::default(failure(FailureKind::BadGateway, Some(502), &[]), Some(7))] + #[case::not_found_status(failure(FailureKind::Other, Some(404), &["APIError"]), Some(1))] + #[case::unsupported_endpoint( + failure(FailureKind::Declined, Some(400), &["UnsupportedEndpointError", "BadRequestError"]), + Some(7) + )] + #[case::malformed_reads_bad_request( + failure(FailureKind::Declined, Some(400), &["MalformedRequestFieldError", "BadRequestError"]), + Some(3) + )] + fn retries_follow_the_most_specific_class( + #[case] failure: AttemptError, + #[case] expected: Option, + ) { + let policy = RetryPolicy { + InternalServerErrorRetries: Some(4), + BadRequestErrorRetries: Some(3), + NotFoundErrorRetries: Some(1), + DefaultRetries: Some(7), + ..RetryPolicy::default() + }; + assert_eq!(policy.retries_for(&failure), expected); + } + + #[rstest] + #[case::rate_limit_with_healthy(FailureKind::RateLimit, Some(429), 1, 2, false, true)] + #[case::rate_limit_none_healthy_with_fallbacks( + FailureKind::RateLimit, + Some(429), + 0, + 2, + true, + false + )] + #[case::bad_request(FailureKind::BadRequest, Some(400), 2, 2, false, false)] + #[case::auth_lone_deployment(FailureKind::Authentication, Some(401), 1, 1, false, false)] + #[case::auth_with_siblings(FailureKind::Authentication, Some(401), 1, 2, false, true)] + #[case::not_found(FailureKind::NotFound, Some(404), 2, 2, false, false)] + #[case::server_error_no_healthy(FailureKind::InternalServer, Some(500), 0, 2, false, false)] + fn should_retry_follows_python( + #[case] kind: FailureKind, + #[case] status: Option, + #[case] healthy: usize, + #[case] all: usize, + #[case] has_regular_fallbacks: bool, + #[case] expected: bool, + ) { + let ctx = RetryContext { + healthy, + all, + has_regular_fallbacks, + ..RetryContext::default() + }; + assert_eq!( + should_retry(&AttemptError::new(kind, status), ctx), + expected + ); + } +} diff --git a/litellm-rust/crates/router-core/src/routing_groups.rs b/litellm-rust/crates/router-core/src/routing_groups.rs new file mode 100644 index 00000000000..fcf6c2febf3 --- /dev/null +++ b/litellm-rust/crates/router-core/src/routing_groups.rs @@ -0,0 +1,48 @@ +//! Routing groups: a callable name over the deployments of its member model groups +//! (`_get_routing_group_deployments`). A priority group serves each member's priority as the +//! member deployments' `order` (`apply_routing_group_priority`), so the order filter and order +//! fallbacks walk the priorities. + +use std::sync::Arc; + +use serde_json::Value; + +use crate::registry::{Deployment, RoutingGroupSpec}; + +/// The member deployments of `group`, in member order, with a priority group's priorities as +/// their `order`. +pub fn members( + group: &RoutingGroupSpec, + deployments_of: impl Fn(&str) -> Vec>, +) -> Vec> { + let priorities = group + .model_priorities + .as_ref() + .filter(|_| is_priority(group)); + group + .models + .iter() + .flat_map(|member| { + let priority = priorities.and_then(|p| p.get(member)).copied(); + deployments_of(member) + .into_iter() + .map(move |deployment| match priority { + Some(order) => with_order(&deployment, order), + None => deployment, + }) + }) + .collect() +} + +/// Whether `group` is a priority group. +pub fn is_priority(group: &RoutingGroupSpec) -> bool { + matches!(&group.routing_strategy, crate::config::RoutingStrategy::Other(name) if name == "priority") +} + +fn with_order(deployment: &Arc, order: i64) -> Arc { + let mut prioritized = Deployment::clone(deployment); + prioritized + .raw_params + .insert("order".to_owned(), Value::from(order)); + Arc::new(prioritized) +} diff --git a/litellm-rust/crates/router-core/src/routing_plugins.rs b/litellm-rust/crates/router-core/src/routing_plugins.rs new file mode 100644 index 00000000000..236de6fc521 --- /dev/null +++ b/litellm-rust/crates/router-core/src/routing_plugins.rs @@ -0,0 +1,114 @@ +//! `Router(plugins=[...])`: the routing-plugin pipeline. The host runs the plugins (live Python +//! objects) in the async pick's pre-routing hook and reports the candidate models they left on +//! the request (`_routing_plugin_candidate_models`); router-core decides which deployments that +//! keeps (`_filter_by_routing_plugin_candidates`) and refuses the paths that never run the +//! pipeline (`_get_available_deployment_unresolved`). + +use std::sync::Arc; + +use crate::{config::RoutingStrategy, error::Error, host::RouterRequest, registry::Deployment}; + +/// Whether the router's own strategy has an async selector: the others pick on the sync path +/// even for async callers (`_async_get_available_deployment`). +pub(crate) fn picks_async(strategy: &RoutingStrategy) -> bool { + matches!( + strategy, + RoutingStrategy::UsageBasedV2 + | RoutingStrategy::SimpleShuffle + | RoutingStrategy::CostBased + | RoutingStrategy::LatencyBased + | RoutingStrategy::LeastBusy + ) +} + +/// The sync pick never runs the pipeline, so a router with plugins refuses it rather than +/// letting a policy plugin be bypassed. `request` is a pick or a call, never a listing. +pub(crate) fn refuse_sync_pick( + has_plugins: bool, + strategy: &RoutingStrategy, + request: &RouterRequest, +) -> Result<(), Error> { + if has_plugins + && request.pass_through.is_none() + && (!request.pre_routes || !picks_async(strategy)) + { + return Err(Error::RoutingPluginsNeedAsync); + } + Ok(()) +} + +/// `_filter_by_routing_plugin_candidates`: keep the deployments whose litellm model the plugins +/// left; nothing left is an error, never a fallback to the unfiltered pool. +pub(crate) fn narrow( + healthy: Vec>, + models: Option<&[String]>, +) -> Result>, Error> { + let Some(models) = models else { + return Ok(healthy); + }; + let kept: Vec> = healthy + .into_iter() + .filter(|d| models.contains(&d.params.model)) + .collect(); + if kept.is_empty() { + return Err(Error::RoutingPluginsLeftNothing { + models: models.to_vec(), + }); + } + Ok(kept) +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + use crate::registry::DeploymentSpec; + + fn deployment(id: &str, model: &str) -> Arc { + let spec: DeploymentSpec = serde_json::from_value(json!({ + "model_name": "g", "litellm_params": {"model": model}, "model_info": {"id": id}, + })) + .unwrap(); + Arc::new(Deployment::from_spec(spec).unwrap()) + } + + #[rstest] + fn the_plugins_models_narrow_the_pool() { + let pool = vec![deployment("a", "openai/a"), deployment("b", "openai/b")]; + let kept = narrow(pool, Some(&["openai/b".to_owned()])).unwrap(); + assert_eq!( + kept.iter().map(|d| d.id.as_str()).collect::>(), + ["b"] + ); + } + + #[rstest] + fn narrowing_to_nothing_is_an_error() { + let pool = vec![deployment("a", "openai/a")]; + assert!(matches!( + narrow(pool, Some(&[])), + Err(Error::RoutingPluginsLeftNothing { models }) if models.is_empty() + )); + } + + #[rstest] + #[case::async_pick(true, RoutingStrategy::SimpleShuffle, false)] + #[case::sync_pick(false, RoutingStrategy::SimpleShuffle, true)] + #[case::v1_strategy(true, RoutingStrategy::UsageBased, true)] + fn only_the_async_pick_runs_plugins( + #[case] pre_routes: bool, + #[case] strategy: RoutingStrategy, + #[case] refused: bool, + ) { + let request = RouterRequest { + pre_routes, + ..RouterRequest::default() + }; + assert_eq!( + refuse_sync_pick(true, &strategy, &request).is_err(), + refused + ); + } +} diff --git a/litellm-rust/crates/router-core/src/select.rs b/litellm-rust/crates/router-core/src/select.rs new file mode 100644 index 00000000000..fefa7f25ad1 --- /dev/null +++ b/litellm-rust/crates/router-core/src/select.rs @@ -0,0 +1,795 @@ +//! Selection: resolve a name, filter its deployments in the order of +//! `Router._core_async_get_healthy_deployments` (team, web search, cooldown, blocked, plugins, +//! pre-call checks, tags, order, retry skips), then pick one with the strategy. Simple-shuffle is +//! native (`router_strategy/simple_shuffle.py`); other strategies go through `Host::select`. + +use std::{collections::BTreeMap, sync::Arc}; + +use parking_lot::Mutex; +use rand::{Rng, SeedableRng, rngs::StdRng}; + +use crate::{ + Core, RouterStateSnapshot, + config::{Op, RoutingStrategy}, + error::Error, + health_routing::WhenAllUnhealthy, + host::{RouterRequest, RoutingContext, SelectStage}, + registry::{Deployment, Registry, ResolveKind}, + resolve::{Caller, resolve_request}, + strategy::{StrategyScope, routing_context}, +}; + +/// Randomness for the shuffle and retry jitter, injectable so tests are deterministic. +pub trait Randomness: Send + Sync { + /// A float in `[0, 1)`, as Python's `random.random()`. + fn next_f64(&self) -> f64; + + /// An index below `len`, as Python's `random.choice` draws one. + fn index_below(&self, len: usize) -> usize { + ((self.next_f64() * len as f64) as usize).min(len - 1) + } +} + +pub struct ThreadRandomness; + +impl Randomness for ThreadRandomness { + fn next_f64(&self) -> f64 { + rand::thread_rng().r#gen() + } +} + +pub struct SeededRandomness(Mutex); + +impl SeededRandomness { + pub fn new(seed: u64) -> Self { + Self(Mutex::new(StdRng::seed_from_u64(seed))) + } +} + +impl Randomness for SeededRandomness { + fn next_f64(&self) -> f64 { + self.0.lock().r#gen() + } +} + +/// Which pass-through pick a request makes. +#[derive(Clone, Copy, Debug, PartialEq, Eq)] +pub enum PassThrough { + /// `get_available_deployment_for_pass_through` (and `select(kind="pass_through")`): the + /// pass-through deployments are chosen first, then cooldown and blocked filters, and only a + /// priority group filters by order. + Listed, + /// `async_get_available_deployment_for_pass_through`: the full healthy chain, then the + /// pass-through filter. + Healthy, +} + +/// A group's deployments before and after filtering. +#[derive(Clone, Debug)] +pub struct Candidates { + /// The name that was resolved (Python's `model`). + pub name: String, + pub model_group: String, + pub kind: ResolveKind, + /// Every deployment the caller may use (after the team filter). + pub all: Vec>, + pub healthy: Vec>, + /// The provider-prefixed spelling the name resolved under (`get_pattern`), when the host + /// was asked for one. + pub wildcard_request: Option, +} + +impl Candidates { + /// The `model` a no-deployments error names: what `_common_checks_available_deployment` + /// returned, so the alias-resolved name a wildcard serves and not its pattern. + pub(crate) fn failed_model(&self, registry: &Registry) -> String { + let model = match self.kind { + ResolveKind::Wildcard => registry.alias_of(&self.name).unwrap_or(&self.name), + _ => self.model_group.as_str(), + }; + model.to_owned() + } +} + +/// Per-attempt selection inputs the call loop carries. +#[derive(Clone, Debug, Default)] +pub(crate) struct SelectInputs { + pub target_order: Option, + pub skipped_ids: Vec, + /// A weighted failover hop's `_excluded_deployment_ids`: never picked. + pub excluded_ids: Arc<[String]>, + /// Stop before the plugins, order and skip filters: the group less cooldowns and blocked + /// deployments, which `_async_get_healthy_deployments` counts when deciding whether to retry. + pub count_only: bool, + /// The level's name, which an endpoint refusal reads (`endpoint_selection(model=...)`): the + /// name before pre-routing replaced it. + pub requested: Option, + /// A fallback hop: `run_async_fallback` pops the request's `_target_order`, so only the + /// hop's own order applies. + pub fallback_hop: bool, +} + +/// `simple_shuffle`: weighted by `_router_weights[group]`, else `weight`, else `rpm`, else +/// `tpm`, each normalized by its maximum, else uniform. A metric is read only when every set +/// before it weighed nothing, and a non-numeric one fails the pick then (`_metric_weight`). +pub fn simple_shuffle( + deployments: &[Arc], + model_group: &str, + router_weights: Option<&BTreeMap>>, + rng: &dyn Randomness, +) -> Result>, Error> { + if deployments.is_empty() { + return Ok(None); + } + let scoped = router_weights + .and_then(|weights| weights.get(model_group)) + .filter(|weights| !weights.is_empty()) + .map(|weights| { + deployments + .iter() + .map(|d| weights.get(&d.id).copied().unwrap_or(0.0)) + .collect::>() + }); + let metric_sets = ["weight", "rpm", "tpm"].into_iter().map(|metric| { + deployments + .iter() + .map(|d| d.metric_weight(metric)) + .collect::>>() + .ok_or(Error::NonNumericWeight { metric }) + }); + for weights in scoped.into_iter().map(Ok).chain(metric_sets) { + let weights = weights?; + let largest = weights.iter().copied().fold(0.0, f64::max); + if largest <= 0.0 { + continue; + } + let normalized: Vec = weights.iter().map(|weight| weight / largest).collect(); + let total: f64 = normalized.iter().sum(); + if total <= 0.0 { + continue; + } + // `random.choices`: bisect_right over the cumulative weights. + let target = rng.next_f64() * total; + let mut cumulative = 0.0; + let index = normalized + .iter() + .position(|weight| { + cumulative += weight; + target < cumulative + }) + .unwrap_or(deployments.len() - 1); + return Ok(Some(deployments[index].clone())); + } + Ok(Some( + deployments[rng.index_below(deployments.len())].clone(), + )) +} + +/// A pre-routing strategy marker (`classify_strategy_router_model`): its model is `auto_router/...`. +pub fn is_strategy_marker(deployment: &Deployment) -> bool { + deployment.params.model.starts_with("auto_router/") +} + +/// `litellm_params.use_in_pass_through`, read for truthiness as Python does. +fn uses_pass_through(deployment: &Deployment) -> bool { + match deployment.raw_params.get("use_in_pass_through") { + None | Some(serde_json::Value::Null) => false, + Some(serde_json::Value::Bool(value)) => *value, + Some(serde_json::Value::Number(value)) => value.as_f64().is_some_and(|n| n != 0.0), + Some(serde_json::Value::String(value)) => !value.is_empty(), + Some(serde_json::Value::Array(value)) => !value.is_empty(), + Some(serde_json::Value::Object(value)) => !value.is_empty(), + } +} + +/// `filter_team_based_models`: a team-owned deployment serves only its team, except that a proxy +/// admin without a team keeps deployments that are all team-owned and listed under the model the +/// request names, unless they belong to several teams. +fn filter_team_based( + deployments: Vec>, + request: &RouterRequest, +) -> Result>, Error> { + let team_id = request.team_id.as_deref(); + if team_id.is_none() + && request.proxy_admin + && let Some(requested) = request.admin_model.as_deref() + && !deployments.is_empty() + && deployments.iter().all(|d| { + d.model_info.team_id.is_some() + && (d.model_name == requested + || d.model_info.team_public_model_name.as_deref() == Some(requested)) + }) + { + let teams: std::collections::BTreeSet<&str> = deployments + .iter() + .filter_map(|d| d.model_info.team_id.as_deref()) + .collect(); + if teams.len() > 1 { + return Err(Error::MultipleTeams { + model: requested.to_owned(), + }); + } + return Ok(deployments); + } + Ok(deployments + .into_iter() + .filter(|d| d.usable_by_team(team_id)) + .collect()) +} + +impl Core { + fn context<'a>( + &'a self, + snapshot: &'a RouterStateSnapshot, + op: &'a Op, + request: &'a RouterRequest, + model_group: &'a str, + name: &'a str, + scope: StrategyScope, + ) -> RoutingContext<'a> { + RoutingContext { + registry: &snapshot.registry, + settings: &snapshot.settings, + health: &self.health, + request, + op, + model_group, + name, + scope, + pool: &[], + excluded_ids: &[], + skipped_ids: &[], + target_order: None, + } + } + + /// The eligible deployments for `name`, in filter-chain order. + pub(crate) async fn candidates( + &self, + snapshot: &RouterStateSnapshot, + op: &Op, + request: &RouterRequest, + name: &str, + inputs: &SelectInputs, + ) -> Result { + let registry = &snapshot.registry; + // The async pick's pre-routing hook runs the routing plugins before anything resolves; + // every pick but a listed pass-through one reads what they left on the request. + let plugin_models = if snapshot.settings.routing_plugins + && !inputs.count_only + && request.pass_through != Some(PassThrough::Listed) + { + let ctx = self.context(snapshot, op, request, name, name, StrategyScope::Default); + self.host + .routing_plugin_models(&ctx, request.pre_routes) + .await? + } else { + None + }; + // No deployment for the name: route to the first default fallback. + let default_target = crate::resolve::default_target(&snapshot.settings.dynamic); + // `get_pattern`: a name no pattern matches is tried again under its inferred provider. + let wildcard_name = + crate::resolve::wildcard_name(registry, name, request.specific_deployment); + let wildcard_request = match wildcard_name { + Some(model) => { + let scope = StrategyScope::Default; + let ctx = self.context(snapshot, op, request, model, model, scope); + self.host.provider_request(&ctx).await? + } + None => None, + }; + // `endpoint_selection` wraps the attempt, not the count a retry decision reads. + let endpoint = request.endpoint.as_deref().filter(|_| !inputs.count_only); + let caller = Caller { + team_id: request.team_id.as_deref(), + proxy_admin: request.proxy_admin, + allowed_models: &request.allowed_models, + endpoint, + requested: inputs.requested.as_deref().unwrap_or(name), + wildcard_request: wildcard_request.as_deref(), + }; + let resolution = resolve_request( + registry, + name, + request.specific_deployment, + caller, + default_target, + snapshot.settings.dynamic.default_ref(), + jiff::Timestamp::now(), + )? + .ok_or_else(|| Error::UnknownModel { + // The name `_common_checks_available_deployment` looked for, past the alias. + model: registry.alias_of(name).unwrap_or(name).to_owned(), + })?; + let first_model = resolution + .deployments + .first() + .map(|d| d.params.model.clone()); + let team_id = request.team_id.as_deref(); + let usable = filter_team_based(resolution.deployments.clone(), request)?; + // `_filter_reserved_deployments`: PTU shares keep holders to their share and everyone + // else to the deployments split into none. + let (mut all, withheld) = crate::ptu::filter_shared(usable, team_id); + if withheld && all.is_empty() { + return Err(Error::PtuReserved { + model: match resolution.kind { + ResolveKind::Id => first_model.unwrap_or_else(|| name.to_owned()), + ResolveKind::Wildcard | ResolveKind::SpecificDeployment => name.to_owned(), + _ => resolution.group.clone(), + }, + }); + } + // `filter_web_search_deployments` runs before `request_deployments` is read, so every later + // stage sees the group without the deployments it dropped. + if request.web_search && !inputs.count_only && !resolution.kind.is_single() { + all.retain(|d| d.supports_web_search()); + } + // `_without_deployments_that_cannot_serve_route`, right after the web search filter: the + // deployments whose provider cannot serve the call, unless that leaves nothing. Only a pick + // runs it (`_route_capability_pin`): the retry count reads the whole group. + if let Some(handler) = request.route_handler.as_deref() + && !inputs.count_only + && !resolution.kind.is_single() + && !all.is_empty() + { + let ctx = self.context( + snapshot, + op, + request, + &resolution.group, + name, + StrategyScope::Default, + ); + let stage = SelectStage::RouteIncapable { + handler: handler.to_owned(), + }; + let incapable = self.host.select(&stage, &ctx, all.clone()).await?; + let capable: Vec> = all + .iter() + .filter(|d| !incapable.iter().any(|i| i.id == d.id)) + .cloned() + .collect(); + if !capable.is_empty() { + all = capable; + } + } + let listed = + request.pass_through == Some(PassThrough::Listed) && !resolution.kind.is_single(); + if listed { + all.retain(|d| uses_pass_through(d)); + if all.is_empty() { + // The name `_common_checks_available_deployment` resolved: an alias's target, a + // routing group's name, the alias-resolved name a wildcard serves. + let model = match resolution.kind { + ResolveKind::Wildcard => registry.alias_of(name).unwrap_or(name), + ResolveKind::SpecificDeployment => name, + _ => resolution.group.as_str(), + }; + return Err(Error::NoPassThroughDeployments { + model: model.to_owned(), + }); + } + } + + // A deployment named by its id is served even while it cools down + // (`get_deployment_by_model_id` returns before the cooldown filter). + let settings = &snapshot.settings; + let cooling = if resolution.kind.is_single() { + Vec::new() + } else { + // `async_get_cooldown_deployments` reads every deployment's, as one throttled batch. + self.health + .active_cooldowns(&snapshot.registry.ids()) + .await? + }; + // Health-check filtering runs before the cooldown filter, except for a deployment named + // by its id and the healthy count a retry decision reads. + let checked = if resolution.kind.is_single() || inputs.count_only { + all.clone() + } else { + let when_all_unhealthy = if request.health_check_probe { + WhenAllUnhealthy::Nothing + } else { + WhenAllUnhealthy::KeepAll + }; + self.health + .health_check_filter(settings, all.clone(), when_all_unhealthy) + .await + }; + let mut healthy: Vec> = checked + .iter() + .filter(|d| !cooling.iter().any(|(id, _)| *id == d.id)) + .cloned() + .collect(); + // The safety net when health-check routing drives cooldowns (an allowed_fails_policy): + // never on a listed pass-through pick or the healthy count. + if healthy.is_empty() + && !listed + && !inputs.count_only + && settings.enable_health_check_routing + && settings.allowed_fails_policy.is_some() + { + healthy = checked; + } + if resolution.kind.is_single() + && let Some(deployment) = all.first() + { + // `_core_async_get_healthy_deployments`: a deployment named by id is checked alone. + if deployment.model_info.blocked { + return Err(Error::Paused { + model: deployment.params.model.clone(), + }); + } + if request.pass_through.is_some() && !uses_pass_through(deployment) { + return Err(Error::NotPassThrough { + id: deployment.id.clone(), + }); + } + } + healthy.retain(|d| !d.model_info.blocked); + // `continuation_deployments`: a mid-stream continuation never lands on a deployment the host + // named as unable to take its prefill. + if let Some(excluded) = request + .body + .get("continuation_excluded_ids") + .and_then(serde_json::Value::as_array) + { + healthy.retain(|d| !excluded.iter().any(|id| id.as_str() == Some(d.id.as_str()))); + } + let request_order = request.target_order.filter(|_| !inputs.fallback_hop); + // `async_callback_filter_deployments` runs after the cooldown and blocked filters on every + // async candidate list but a deployment named by id and a listed pass-through pick. + if settings.callback_filters + && !inputs.count_only + && !resolution.kind.is_single() + && request.pass_through != Some(PassThrough::Listed) + { + let mut ctx = self.context( + snapshot, + op, + request, + &resolution.group, + name, + StrategyScope::Default, + ); + ctx.excluded_ids = &inputs.excluded_ids; + ctx.skipped_ids = &inputs.skipped_ids; + ctx.target_order = inputs.target_order.or(request_order); + healthy = self.host.callback_filters(&ctx, healthy).await?; + } + if inputs.count_only { + return Ok(Candidates { + name: name.to_owned(), + model_group: resolution.group, + kind: resolution.kind, + all, + healthy, + wildcard_request, + }); + } + + if listed { + if settings.enable_pre_call_checks && !resolution.kind.is_single() { + healthy = self + .pre_call_checks( + snapshot, + op, + request, + &resolution.group, + name, + &all, + healthy, + ) + .await?; + } + // Only a priority group narrows a listed pass-through pick by order. + let priority = resolution.kind == ResolveKind::RoutingGroup + && registry.routing_groups().iter().any(|g| { + g.group_name == resolution.group && crate::routing_groups::is_priority(g) + }); + if priority { + let order = request + .target_order + .or_else(|| healthy.iter().filter_map(|d| d.order()).min()); + if let Some(order) = order { + healthy.retain(|d| d.order() == Some(order)); + } + } + return Ok(Candidates { + name: name.to_owned(), + model_group: resolution.group, + kind: resolution.kind, + all, + healthy, + wildcard_request, + }); + } + + if !settings.plugins.is_empty() && !healthy.is_empty() { + let ctx = self.context( + snapshot, + op, + request, + &resolution.group, + name, + StrategyScope::Default, + ); + healthy = self + .host + .select(&SelectStage::Plugins, &ctx, healthy) + .await?; + } + + if settings.enable_pre_call_checks && !resolution.kind.is_single() { + healthy = self + .pre_call_checks( + snapshot, + op, + request, + &resolution.group, + name, + &all, + healthy, + ) + .await?; + } + + if request.filter_tags && !healthy.is_empty() { + let mut ctx = self.context( + snapshot, + op, + request, + &resolution.group, + name, + StrategyScope::Default, + ); + ctx.pool = &all; + healthy = self.host.select(&SelectStage::Tags, &ctx, healthy).await?; + } + + if !resolution.kind.is_single() { + healthy = crate::routing_plugins::narrow(healthy, plugin_models.as_deref())?; + } + + // `_without_declared_text_only_deployments`: an image request skips the deployments that + // declare no vision, unless that leaves nothing. + if request.has_image && !resolution.kind.is_single() && !healthy.is_empty() { + let ctx = self.context( + snapshot, + op, + request, + &resolution.group, + name, + StrategyScope::Default, + ); + let text_only = self + .host + .select(&SelectStage::TextOnly, &ctx, healthy.clone()) + .await?; + let vision: Vec> = healthy + .iter() + .filter(|d| !text_only.iter().any(|t| t.id == d.id)) + .cloned() + .collect(); + if !vision.is_empty() { + healthy = vision; + } + } + + // `_without_decisions_deployments_refusing_media`: a Decisions call carrying audio or + // videos skips the deployments that refuse them, unless that leaves nothing. + if request.decisions_media && !resolution.kind.is_single() && !healthy.is_empty() { + let ctx = self.context( + snapshot, + op, + request, + &resolution.group, + name, + StrategyScope::Default, + ); + let refusing = self + .host + .select(&SelectStage::MediaRefusing, &ctx, healthy.clone()) + .await?; + let taking: Vec> = healthy + .iter() + .filter(|d| !refusing.iter().any(|r| r.id == d.id)) + .cloned() + .collect(); + if !taking.is_empty() { + healthy = taking; + } + } + + if let Some(pinned) = request.pinned_deployment_id.as_deref() + && healthy.iter().any(|d| d.id == pinned) + { + healthy.retain(|d| d.id == pinned); + } + + let order = inputs + .target_order + .or(request_order) + .or_else(|| healthy.iter().filter_map(|d| d.order()).min()); + if let Some(order) = order { + healthy.retain(|d| d.order() == Some(order)); + } + + healthy.retain(|d| { + !request.excluded_ids.contains(&d.id) && !inputs.excluded_ids.contains(&d.id) + }); + + if !inputs.skipped_ids.is_empty() || !request.retry_skipped_ids.is_empty() { + let kept: Vec> = healthy + .iter() + .filter(|d| { + !inputs.skipped_ids.contains(&d.id) + && !request.retry_skipped_ids.contains(&d.id) + }) + .cloned() + .collect(); + if !kept.is_empty() { + healthy = kept; + } + } + + if request.pass_through == Some(PassThrough::Healthy) + && !resolution.kind.is_single() + && !healthy.is_empty() + { + healthy.retain(|d| uses_pass_through(d)); + if healthy.is_empty() { + return Err(Error::NoPassThroughDeployments { + model: name.to_owned(), + }); + } + } + + Ok(Candidates { + name: name.to_owned(), + model_group: resolution.group, + kind: resolution.kind, + all, + healthy, + wildcard_request, + }) + } + + /// `_pre_call_checks` over `healthy`, with the host's facts. + #[allow(clippy::too_many_arguments)] + async fn pre_call_checks( + &self, + snapshot: &RouterStateSnapshot, + op: &Op, + request: &RouterRequest, + model_group: &str, + name: &str, + pool: &[Arc], + healthy: Vec>, + ) -> Result>, Error> { + let mut ctx = self.context( + snapshot, + op, + request, + model_group, + name, + StrategyScope::Default, + ); + ctx.pool = pool; + let facts = self.host.pre_call_facts(&ctx, &healthy).await?; + crate::precall::filter(model_group, healthy, pool, &facts) + } + + /// Pick one of `candidates.healthy` with the group's strategy. + pub(crate) async fn pick( + &self, + snapshot: &RouterStateSnapshot, + op: &Op, + request: &RouterRequest, + candidates: &Candidates, + ) -> Result, Error> { + let no_deployment = || Error::NoHealthyDeployments { + model: candidates.failed_model(&snapshot.registry), + }; + // A deployment named by its id is returned as is, before any strategy runs. + if candidates.kind.is_single() { + return candidates + .healthy + .first() + .cloned() + .ok_or_else(no_deployment); + } + let (strategy, scope) = routing_context( + &snapshot.registry, + &snapshot.settings.routing_strategy, + request.routing_strategy.as_deref(), + &candidates.kind, + &candidates.model_group, + ); + if strategy == RoutingStrategy::Unset { + return Err(no_deployment()); + } + if strategy == RoutingStrategy::SimpleShuffle { + let weights = crate::weights::validate(request.router_weights.as_ref()) + .map_err(|_| Error::InvalidRouterWeights)?; + return simple_shuffle( + &candidates.healthy, + &candidates.model_group, + weights.as_ref(), + self.rng.as_ref(), + )? + .ok_or_else(no_deployment); + } + let ctx = self.context( + snapshot, + op, + request, + &candidates.model_group, + &candidates.name, + scope, + ); + self.host + .select( + &SelectStage::Strategy(strategy), + &ctx, + candidates.healthy.clone(), + ) + .await? + .into_iter() + .next() + .ok_or_else(no_deployment) + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + use crate::registry::DeploymentSpec; + + struct Fixed(f64); + + impl Randomness for Fixed { + fn next_f64(&self) -> f64 { + self.0 + } + } + + fn deployment(id: &str, params: serde_json::Value) -> Arc { + let spec: DeploymentSpec = serde_json::from_value(json!({ + "model_name": "g", "litellm_params": params, "model_info": {"id": id}, + })) + .unwrap(); + Arc::new(Deployment::from_spec(spec).unwrap()) + } + + #[rstest] + #[case::weight_low_draw(0.1, "a")] + #[case::weight_high_draw(0.9, "b")] + fn shuffle_uses_weight_before_rpm(#[case] draw: f64, #[case] expected: &str) { + let deployments = [ + deployment("a", json!({"model": "openai/a", "weight": 1, "rpm": 1000})), + deployment("b", json!({"model": "openai/b", "weight": 3})), + ]; + let picked = simple_shuffle(&deployments, "g", None, &Fixed(draw)) + .unwrap() + .unwrap(); + assert_eq!(picked.id, expected); + } + + #[rstest] + fn shuffle_prefers_request_weights() { + let deployments = [ + deployment("a", json!({"model": "openai/a", "weight": 100})), + deployment("b", json!({"model": "openai/b"})), + ]; + let weights = BTreeMap::from([("g".to_owned(), BTreeMap::from([("b".to_owned(), 1.0)]))]); + let picked = simple_shuffle(&deployments, "g", Some(&weights), &Fixed(0.99)) + .unwrap() + .unwrap(); + assert_eq!(picked.id, "b"); + } +} diff --git a/litellm-rust/crates/router-core/src/settings.rs b/litellm-rust/crates/router-core/src/settings.rs new file mode 100644 index 00000000000..f55b059d71c --- /dev/null +++ b/litellm-rust/crates/router-core/src/settings.rs @@ -0,0 +1,133 @@ +//! [`Settings`]: one typed, frozen view of the configuration a caller may read, built from the +//! static config and the current dynamic snapshot. + +use std::{collections::BTreeMap, sync::Arc, time::Duration}; + +use crate::{ + config::{ + AllowedFailsPolicy, DEFAULT_COOLDOWN_TIME, PluginSpec, RetryPolicy, RouterConfig, + RouterDynamicConfig, RoutingStrategy, + }, + error::AttemptError, +}; + +#[derive(Clone, Debug)] +pub struct Settings { + pub routing_strategy: RoutingStrategy, + pub plugins: Arc<[PluginSpec]>, + pub cooldown_time: Duration, + pub disable_cooldowns: bool, + pub allowed_fails: Option, + pub allowed_fails_policy: Option, + pub retry_policy: Option, + pub model_group_retry_policy: Arc>, + pub num_retries: u32, + pub max_fallbacks: u32, + pub retry_after: Duration, + pub timeout: Option, + pub drop_params: Option, + pub enable_pre_call_checks: bool, + pub routing_plugins: bool, + pub callback_filters: bool, + pub enable_health_check_routing: bool, + pub health_check_staleness: Duration, + pub background_health_check_model_groups: Option>, + pub enable_weighted_failover: bool, + pub fallback_on_unsupported_params: bool, + pub provider_default_deployment_ids: Arc<[String]>, + pub dynamic: Arc, +} + +/// `DEFAULT_HEALTH_CHECK_INTERVAL * DEFAULT_HEALTH_CHECK_STALENESS_MULTIPLIER`. +pub const DEFAULT_HEALTH_CHECK_STALENESS: Duration = Duration::from_secs(300 * 2); + +fn seconds(value: f64) -> Duration { + Duration::try_from_secs_f64(value).unwrap_or_default() +} + +impl Settings { + pub fn new(config: &RouterConfig, dynamic: Arc) -> Self { + Self { + routing_strategy: config.routing_strategy.clone(), + plugins: config.plugins.clone().into(), + cooldown_time: config.cooldown_time.map_or(DEFAULT_COOLDOWN_TIME, seconds), + disable_cooldowns: config.disable_cooldowns, + allowed_fails: dynamic.allowed_fails, + allowed_fails_policy: config.allowed_fails_policy.clone(), + retry_policy: config.retry_policy.clone(), + model_group_retry_policy: Arc::new(config.model_group_retry_policy.clone()), + num_retries: dynamic.num_retries.unwrap_or(0), + max_fallbacks: dynamic.max_fallbacks, + retry_after: seconds(config.retry_after), + timeout: config.request_timeout.or(config.timeout).map(seconds), + drop_params: config.drop_params, + enable_pre_call_checks: config.enable_pre_call_checks, + routing_plugins: config.routing_plugins, + callback_filters: config.callback_filters, + enable_health_check_routing: config.enable_health_check_routing, + health_check_staleness: config + .health_check_staleness_threshold + .map_or(DEFAULT_HEALTH_CHECK_STALENESS, seconds), + background_health_check_model_groups: config + .background_health_check_model_groups + .clone() + .map(Into::into), + enable_weighted_failover: config.enable_weighted_failover, + fallback_on_unsupported_params: config.fallback_on_unsupported_params.unwrap_or(true), + provider_default_deployment_ids: config.provider_default_deployment_ids.clone().into(), + dynamic, + } + } + + /// `allowed_fails_for`: the policy's count for this failure. + pub fn allowed_fails_for(&self, failure: &AttemptError) -> Option { + self.allowed_fails_policy + .as_ref() + .and_then(|policy| policy.allowed_fails_for(failure)) + } + + /// How long an allowed-fails counter lives: `settings().cooldown_time or + /// DEFAULT_COOLDOWN_TIME_SECONDS`, so a router cooldown of 0 still counts over the default. + pub fn fails_window(&self) -> Duration { + if self.cooldown_time.is_zero() { + DEFAULT_COOLDOWN_TIME + } else { + self.cooldown_time + } + } + + /// `_is_allowed_fails_set_on_router`. + pub fn allowed_fails_set(&self) -> bool { + self.allowed_fails.is_some() && !self.dynamic.allowed_fails_is_default + } + + /// Python's `allowed_fails` default when set without a value (`litellm.allowed_fails`). + pub fn effective_allowed_fails(&self) -> u32 { + self.allowed_fails.unwrap_or(3) + } +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + + use super::*; + + #[rstest] + #[case::passed_to_the_router(Some(3), false, true)] + #[case::the_process_default(Some(3), true, false)] + #[case::none(None, false, false)] + fn allowed_fails_counts_as_set_unless_it_is_the_process_default( + #[case] allowed_fails: Option, + #[case] allowed_fails_is_default: bool, + #[case] expected: bool, + ) { + let dynamic = RouterDynamicConfig { + allowed_fails, + allowed_fails_is_default, + ..RouterDynamicConfig::default() + }; + let settings = Settings::new(&RouterConfig::default(), Arc::new(dynamic)); + assert_eq!(settings.allowed_fails_set(), expected); + } +} diff --git a/litellm-rust/crates/router-core/src/strategy.rs b/litellm-rust/crates/router-core/src/strategy.rs new file mode 100644 index 00000000000..0e1f3b49fa8 --- /dev/null +++ b/litellm-rust/crates/router-core/src/strategy.rs @@ -0,0 +1,110 @@ +//! Which routing strategy picks for a request, and whose state it reads: a port of +//! `Router._get_routing_context`. A per-request `routing_strategy` override wins, then the +//! routing group the resolved model belongs to (called as the group, or as a member of a +//! non-priority group), then the router's own strategy. + +use crate::{ + config::RoutingStrategy, + registry::{Registry, ResolveKind}, +}; + +/// The per-request overrides `_OVERRIDABLE_ROUTING_STRATEGIES` honours: simple-shuffle and every +/// strategy with a default selector. Anything else is ignored. +pub const OVERRIDABLE: [&str; 6] = [ + "simple-shuffle", + "least-busy", + "usage-based-routing", + "usage-based-routing-v2", + "latency-based-routing", + "cost-based-routing", +]; + +/// Whose selector state a strategy pick reads. +#[derive(Clone, Debug, PartialEq, Eq)] +pub enum StrategyScope { + /// The router's own strategy (the implicit `"default"` group). + Default, + /// A routing group's own selector. + Group(String), + /// A per-request override: the default selector when it names the router's strategy, else + /// one selector per strategy kept for the router's life. + Override, +} + +impl StrategyScope { + /// The scope as the host step spells it. + pub fn wire(&self) -> (&'static str, Option<&str>) { + match self { + Self::Default => ("default", None), + Self::Group(name) => ("group", Some(name)), + Self::Override => ("override", None), + } + } +} + +/// A request's `routing_strategy` override, when it is one Python honours. +pub fn request_override(raw: Option<&str>) -> Option { + let raw = raw?; + OVERRIDABLE + .contains(&raw) + .then(|| raw.parse().unwrap_or_default()) +} + +/// The strategy and selector scope for a pick of `model_group` (the resolved group, after +/// aliases), reached through a resolution of `kind`. +pub fn routing_context( + registry: &Registry, + default: &RoutingStrategy, + override_strategy: Option<&str>, + kind: &ResolveKind, + model_group: &str, +) -> (RoutingStrategy, StrategyScope) { + if let Some(strategy) = request_override(override_strategy) { + return (strategy, StrategyScope::Override); + } + let group = match kind { + ResolveKind::RoutingGroup => registry + .routing_groups() + .iter() + .find(|group| group.group_name == model_group), + ResolveKind::Alias | ResolveKind::Group => registry.member_routing_group(model_group), + ResolveKind::SpecificDeployment + | ResolveKind::Id + | ResolveKind::Default + | ResolveKind::Wildcard => None, + }; + match group { + None => (default.clone(), StrategyScope::Default), + Some(group) if is_priority(&group.routing_strategy) => { + (RoutingStrategy::SimpleShuffle, StrategyScope::Default) + } + Some(group) => ( + group.routing_strategy.clone(), + StrategyScope::Group(group.group_name.clone()), + ), + } +} + +fn is_priority(strategy: &RoutingStrategy) -> bool { + matches!(strategy, RoutingStrategy::Other(name) if name == "priority") +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + + use super::*; + + #[rstest] + #[case::honoured(Some("least-busy"), Some(RoutingStrategy::LeastBusy))] + #[case::shuffle(Some("simple-shuffle"), Some(RoutingStrategy::SimpleShuffle))] + #[case::lar1_ignored(Some("lar1"), None)] + #[case::unknown_ignored(Some("bogus"), None)] + #[case::unset(None, None)] + fn only_overridable_strategies_override( + #[case] raw: Option<&str>, + #[case] expected: Option, + ) { + assert_eq!(request_override(raw), expected); + } +} diff --git a/litellm-rust/crates/router-core/src/weights.rs b/litellm-rust/crates/router-core/src/weights.rs new file mode 100644 index 00000000000..3e5d76844ab --- /dev/null +++ b/litellm-rust/crates/router-core/src/weights.rs @@ -0,0 +1,81 @@ +//! `_router_weights` as `validate_router_weights` reads it (`litellm/types/router_weights.py`): +//! model group to deployment id to a finite weight of at least 0 (an int or a float, never a +//! bool or a string), with non-blank ids and at least one positive weight in every non-empty group. + +use std::collections::BTreeMap; + +use serde_json::Value; + +/// Validated request weights. +pub type RouterWeights = BTreeMap>; + +/// The request's weights didn't validate; the host raises the validator's own error. +#[derive(Clone, Copy, Debug, PartialEq, Eq)] +pub struct InvalidRouterWeights; + +fn identifier(text: &str) -> bool { + text.chars().any(|c| !c.is_whitespace()) +} + +fn weight(value: &Value) -> Option { + match value { + Value::Number(number) => number.as_f64().filter(|w| w.is_finite() && *w >= 0.0), + _ => None, + } +} + +/// `validate_router_weights(raw)`: `None` when the request passed none. +pub fn validate(raw: Option<&Value>) -> Result, InvalidRouterWeights> { + let groups = match raw { + None | Some(Value::Null) => return Ok(None), + Some(Value::Object(groups)) => groups, + Some(_) => return Err(InvalidRouterWeights), + }; + let mut validated = RouterWeights::new(); + for (group, weights) in groups { + let Value::Object(weights) = weights else { + return Err(InvalidRouterWeights); + }; + if !identifier(group) { + return Err(InvalidRouterWeights); + } + let mut entries = BTreeMap::new(); + for (id, value) in weights { + if !identifier(id) { + return Err(InvalidRouterWeights); + } + entries.insert(id.clone(), weight(value).ok_or(InvalidRouterWeights)?); + } + if !entries.is_empty() && !entries.values().any(|w| *w > 0.0) { + return Err(InvalidRouterWeights); + } + validated.insert(group.clone(), entries); + } + Ok(Some(validated)) +} + +#[cfg(test)] +mod tests { + use rstest::rstest; + use serde_json::json; + + use super::*; + + #[rstest] + #[case::all_zero(json!({"g": {"a": 0.0, "b": 0.0}}))] + #[case::negative(json!({"g": {"a": -1.0}}))] + #[case::text(json!({"g": {"a": "1"}}))] + #[case::boolean(json!({"g": {"a": true}}))] + #[case::blank_id(json!({"g": {" ": 1.0}}))] + #[case::not_a_mapping(json!(["g"]))] + fn invalid_weights_are_refused(#[case] raw: Value) { + assert_eq!(validate(Some(&raw)), Err(InvalidRouterWeights)); + } + + #[rstest] + #[case::empty_group(json!({"g": {}}))] + #[case::int_weight(json!({"g": {"a": 1, "b": 0}}))] + fn valid_weights_are_kept(#[case] raw: Value) { + assert!(validate(Some(&raw)).unwrap().is_some()); + } +} diff --git a/litellm-rust/crates/router-core/tests/call_loop.rs b/litellm-rust/crates/router-core/tests/call_loop.rs new file mode 100644 index 00000000000..9f41371f255 --- /dev/null +++ b/litellm-rust/crates/router-core/tests/call_loop.rs @@ -0,0 +1,1757 @@ +//! A call through the router end to end: selection, retries, fallbacks and cooldowns against a +//! scripted host. + +use std::{collections::VecDeque, sync::Arc, time::Duration}; + +use async_trait::async_trait; +use litellm_router_core::{ + Attempt, AttemptError, Deployment, Error, FailureKind, FailureReport, Host, + InMemoryRouterCache, Op, Output, Payload, Router, RouterCache, RouterConfig, + RouterDynamicConfig, RouterEvent, RouterRequest, RoutingContext, SeededRandomness, SelectStage, + SuccessReport, + call::StreamOrigin, + fallback::Fallbacks, + health::{UsageMetric, current_minute, usage_key}, + host::UncountedRetries, + select::PassThrough, +}; +use parking_lot::Mutex; +use rstest::{fixture, rstest}; +use serde_json::json; + +#[derive(Default)] +struct ScriptedHost { + /// Failures handed out in order, keyed by model group; a group with none left succeeds. + script: Mutex)>>, + events: Mutex>, + cache: InMemoryRouterCache, + /// Answer every success as a stream whose outcome the host reports when it ends. + deferred: bool, + /// [`Output::tracks_usage`] on every success. + tracks_usage: Option, + /// Refuse every fallback chain with a dict target. + refuses_dict_targets: bool, + /// Every fallback check raises this exception class, as a host's sync check does. + fallback_check_raises: Option<&'static str>, + /// Failures the tag stage raises in turn, before it answers. + pick_failures: Mutex>, + /// The next attempt's failure, whatever group it serves. + first_failure: Mutex>, +} + +impl ScriptedHost { + fn failing(group: &str, failures: Vec) -> Self { + Self::scripted(vec![(group, failures)]) + } + + fn scripted(groups: Vec<(&str, Vec)>) -> Self { + Self { + script: Mutex::new( + groups + .into_iter() + .map(|(group, failures)| (group.to_owned(), failures.into())) + .collect(), + ), + ..Self::default() + } + } + + fn selected(&self) -> Vec { + self.events + .lock() + .iter() + .filter_map(|event| match event { + RouterEvent::Selected { deployment_id, .. } => Some(deployment_id.clone()), + _ => None, + }) + .collect() + } + + fn retries(&self) -> usize { + self.events + .lock() + .iter() + .filter(|event| matches!(event, RouterEvent::Retry { .. })) + .count() + } +} + +#[async_trait] +impl Host for ScriptedHost { + async fn invoke(&self, attempt: &Attempt) -> Result { + if let Some(failure) = self.first_failure.lock().take() { + return Err(failure); + } + let next = self + .script + .lock() + .iter_mut() + .find(|(group, _)| *group == attempt.model_group) + .and_then(|(_, failures)| failures.pop_front()); + match next { + Some(failure) => Err(failure), + None => Ok(Output { + value: Payload(Arc::new(attempt.deployment.id.clone())), + total_tokens: 10, + blocked: None, + deferred: self.deferred, + tracks_usage: self.tracks_usage, + }), + } + } + + async fn select( + &self, + _stage: &SelectStage, + _ctx: &RoutingContext<'_>, + candidates: Vec>, + ) -> Result>, Error> { + match self.pick_failures.lock().pop_front() { + Some(failure) => Err(failure.into()), + None => Ok(candidates), + } + } + + async fn allow_fallback( + &self, + _request: &RouterRequest, + _target: &str, + ) -> Result { + match self.fallback_check_raises { + Some(class) => Err(AttemptError::host_raised(&[class])), + None => Ok(true), + } + } + + async fn refuses_fallbacks( + &self, + _level: u32, + targets: &[serde_json::Map], + ) -> bool { + self.refuses_dict_targets && !targets.is_empty() + } + + async fn sleep(&self, _duration: Duration) {} + + fn observe(&self, event: &RouterEvent) { + self.events.lock().push(event.clone()); + } + + fn cache(&self) -> Arc { + Arc::new(self.cache.clone()) + } +} + +#[fixture] +fn config() -> RouterConfig { + serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/a"}, "model_info": {"id": "a1"}}, + {"model_name": "primary", "litellm_params": {"model": "openai/b"}, "model_info": {"id": "a2"}}, + {"model_name": "backup", "litellm_params": {"model": "anthropic/c"}, "model_info": {"id": "b1"}}, + ] + })) + .unwrap() +} + +fn router(config: RouterConfig, dynamic: serde_json::Value, host: Arc) -> Router { + let dynamic: RouterDynamicConfig = serde_json::from_value(dynamic).unwrap(); + Router::builder(config, dynamic, host) + .randomness(Arc::new(SeededRandomness::new(7))) + .build() + .unwrap() +} + +fn request() -> RouterRequest { + RouterRequest { + model: "primary".to_owned(), + ..RouterRequest::default() + } +} + +/// `primary` at order 1, its second deployment at order 2 when `tiered`, and two other groups. +fn tiers(tiered: bool) -> RouterConfig { + let second = if tiered { "primary" } else { "unused" }; + serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/p1", "order": 1}, "model_info": {"id": "p1"}}, + {"model_name": second, "litellm_params": {"model": "openai/p2", "order": 2}, "model_info": {"id": "p2"}}, + {"model_name": "backup", "litellm_params": {"model": "anthropic/b1"}, "model_info": {"id": "b1"}}, + {"model_name": "context", "litellm_params": {"model": "anthropic/c1"}, "model_info": {"id": "c1"}}, + ] + })) + .unwrap() +} + +fn failure(kind: FailureKind, status: u16) -> AttemptError { + AttemptError::new(kind, Some(status)) +} + +fn context_window() -> AttemptError { + failure(FailureKind::ContextWindowExceeded, 400) +} + +fn server_error() -> AttemptError { + failure(FailureKind::InternalServer, 500) +} + +fn agentic_followup() -> AttemptError { + let mut failed = server_error(); + failed.agentic_followup = true; + failed +} + +#[rstest] +#[tokio::test] +async fn a_rate_limit_retries_in_the_same_group(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing( + "primary", + vec![AttemptError::new(FailureKind::RateLimit, Some(429))], + )); + let router = router(config, json!({"num_retries": 2}), host.clone()); + let response = router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + assert_eq!( + ( + response.model_group.as_str(), + response.attempted_retries, + response.attempted_fallbacks + ), + ("primary", 1, 0) + ); +} + +#[rstest] +#[tokio::test] +async fn a_bad_request_falls_back_without_retrying(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing( + "primary", + vec![AttemptError::new(FailureKind::BadRequest, Some(400))], + )); + let router = router( + config, + json!({"num_retries": 3, "fallbacks": [{"primary": ["backup"]}]}), + host.clone(), + ); + let response = router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + let retried = host + .events + .lock() + .iter() + .any(|event| matches!(event, RouterEvent::Retry { .. })); + assert_eq!( + ( + response.deployment_id.as_str(), + response.attempted_fallbacks, + retried + ), + ("b1", 1, false) + ); +} + +#[rstest] +#[tokio::test] +async fn a_rate_limit_cools_the_deployment_down(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing( + "primary", + vec![AttemptError::new(FailureKind::RateLimit, Some(429))], + )); + let router = router(config, json!({}), host.clone()); + let error = router + .call(Op::from("acompletion"), request()) + .await + .unwrap_err(); + let cooled = router + .health() + .active_cooldowns(&["a1".to_owned(), "a2".to_owned()]) + .await + .unwrap(); + assert_eq!( + (error.attempt().map(|failure| failure.kind), cooled.len()), + (Some(FailureKind::RateLimit), 1) + ); +} + +#[rstest] +#[case::now(false, (Some(1.0), (10, 1)))] +#[case::deferred(true, (None, (10, 1)))] +#[tokio::test] +async fn a_deferred_attempt_counts_its_request_and_tokens_but_no_success( + #[case] deferred: bool, + #[case] expected: (Option, (u64, u64)), +) { + let config: RouterConfig = serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/a", "rpm": 100}, "model_info": {"id": "a1"}}, + ] + })) + .unwrap(); + let host = Arc::new(ScriptedHost { + deferred, + ..ScriptedHost::default() + }); + let router = router(config, json!({}), host.clone()); + router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + let deployment = router.registry().deployment("a1").unwrap(); + let successes = host + .cache + .get("a1:successes") + .and_then(|count| count.as_f64()); + let usage = router.health().usage(&deployment).await.unwrap(); + assert_eq!((successes, usage), expected); +} + +/// `litellm_params`, `model_info` and a limit only the host knows of all count; a realtime +/// session (`Some(false)` on a deferred answer) counts nothing, whatever limits it has. +#[rstest] +#[case::in_params(json!({"rpm": 100}), json!({}), false, None, (10, 1))] +#[case::in_model_info(json!({}), json!({"rpm": 100}), false, None, (10, 1))] +#[case::in_the_catalog(json!({}), json!({}), false, Some(true), (10, 1))] +#[case::no_limit(json!({}), json!({}), false, None, (0, 0))] +#[case::a_stream_in_model_info(json!({}), json!({"rpm": 100}), true, None, (10, 1))] +#[case::a_realtime_session(json!({"rpm": 100}), json!({}), true, Some(false), (0, 0))] +#[tokio::test] +async fn usage_counts_for_a_deployment_that_tracks_it( + #[case] params: serde_json::Value, + #[case] info: serde_json::Value, + #[case] deferred: bool, + #[case] tracks_usage: Option, + #[case] expected: (u64, u64), +) { + let mut litellm_params = json!({"model": "openai/a"}); + litellm_params + .as_object_mut() + .unwrap() + .extend(params.as_object().unwrap().clone()); + let mut model_info = json!({"id": "a1"}); + model_info + .as_object_mut() + .unwrap() + .extend(info.as_object().unwrap().clone()); + let config: RouterConfig = serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": litellm_params, "model_info": model_info}, + ] + })) + .unwrap(); + let host = Arc::new(ScriptedHost { + deferred, + tracks_usage, + ..ScriptedHost::default() + }); + let router = router(config, json!({}), host.clone()); + router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + let deployment = router.registry().deployment("a1").unwrap(); + assert_eq!(router.health().usage(&deployment).await.unwrap(), expected); +} + +/// A stream end's report of a wildcard deployment counts under the model the route filled, the +/// key its request was counted under, not the configured `*`. +#[rstest] +#[tokio::test] +async fn a_reported_success_keeps_the_filled_wildcard_model() { + let config: RouterConfig = serde_json::from_value(json!({ + "model_list": [ + {"model_name": "openai/*", "litellm_params": {"model": "openai/*", "rpm": 100}, "model_info": {"id": "w1"}}, + ] + })) + .unwrap(); + let host = Arc::new(ScriptedHost::default()); + let router = router(config, json!({}), host.clone()); + let report = SuccessReport { + usage_model: Some("openai/gpt-4o".to_owned()), + ..SuccessReport::default() + }; + router.report_success("w1", 7.0, 0.0, report).await.unwrap(); + let minute = current_minute(std::time::SystemTime::now()); + let key = |model: &str| usage_key("w1", model, UsageMetric::Tpm, &minute); + assert_eq!( + ( + host.cache.get(&key("openai/gpt-4o")), + host.cache.get(&key("openai/*")), + ), + (Some(json!(7)), None), + ); +} + +/// `async_deployment_callback_on_failure`'s request is written only when it runs: a failure the +/// host says ran no failure callback (`recorded`) writes none, nor does a sync call's. +#[rstest] +#[case::the_first_logged_failure(false, false, 1, Some(1.0))] +#[case::a_later_failure_on_the_shared_logging_object(true, false, 0, None)] +#[case::a_sync_call(false, true, 0, Some(1.0))] +#[tokio::test] +async fn a_failed_attempt_counts_its_request_only_when_its_callback_ran( + #[case] recorded: bool, + #[case] uncounted_request: bool, + #[case] requests: u64, + #[case] fails: Option, +) { + let config: RouterConfig = serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/a"}, "model_info": {"id": "a1"}}, + ] + })) + .unwrap(); + let mut failure = AttemptError::new(FailureKind::InternalServer, Some(500)); + failure.recorded = recorded; + failure.uncounted_request = uncounted_request; + let host = Arc::new(ScriptedHost::failing("primary", vec![failure])); + let router = router(config, json!({"num_retries": 0}), host.clone()); + let _ = router.call(Op::from("acompletion"), request()).await; + let deployment = router.registry().deployment("a1").unwrap(); + let usage = router.health().usage(&deployment).await.unwrap(); + let counted = host.cache.get("a1:fails").and_then(|count| count.as_f64()); + assert_eq!((usage.1, counted), (requests, fails)); +} + +#[rstest] +#[case::counted(true, 2)] +#[case::uncounted(false, 1)] +#[tokio::test] +async fn a_reported_failure_counts_its_request_when_asked( + #[case] counts_request: bool, + #[case] requests: u64, +) { + let config: RouterConfig = serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/a", "rpm": 100}, "model_info": {"id": "a1"}}, + ] + })) + .unwrap(); + let host = Arc::new(ScriptedHost { + deferred: true, + ..ScriptedHost::default() + }); + let router = router(config, json!({}), host.clone()); + router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + let report = FailureReport { + counts_request, + ..FailureReport::default() + }; + router + .report_failure( + "a1", + &AttemptError::new(FailureKind::RateLimit, Some(429)), + report, + ) + .await + .unwrap(); + let deployment = router.registry().deployment("a1").unwrap(); + let fails = host.cache.get("a1:fails").and_then(|count| count.as_f64()); + let usage = router.health().usage(&deployment).await.unwrap(); + assert_eq!((fails, usage.1), (Some(1.0), requests)); +} + +#[rstest] +#[tokio::test] +async fn a_raising_retry_policy_lookup_ends_the_hop_and_falls_back(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing( + "primary", + vec![AttemptError::new(FailureKind::RateLimit, Some(429))], + )); + let router = router( + config, + json!({"num_retries": 3, "fallbacks": [{"primary": ["backup"]}]}), + host.clone(), + ); + let request = RouterRequest { + retry_policy_raises: vec!["primary".to_owned()], + ..request() + }; + let response = router.call(Op::from("acompletion"), request).await.unwrap(); + let events = host.events.lock(); + assert!( + !events + .iter() + .any(|e| matches!(e, RouterEvent::Retry { .. })) + ); + assert!(events.iter().any(|e| matches!( + e, + RouterEvent::RetryPolicyRaised { level: 0, model, .. } if model == "primary" + ))); + assert_eq!(response.model_group, "backup"); +} + +#[rstest] +#[tokio::test] +async fn a_num_retries_that_raises_ends_the_hop_and_falls_back(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let router = router( + config, + json!({"num_retries": 3, "fallbacks": [{"primary": ["backup"]}]}), + host.clone(), + ); + let request = RouterRequest { + uncounted_retries: Some(UncountedRetries::Raises), + ..request() + }; + let response = router.call(Op::from("acompletion"), request).await.unwrap(); + let events = host.events.lock(); + assert!( + !events + .iter() + .any(|e| matches!(e, RouterEvent::Retry { .. })) + ); + assert!(events.iter().any(|e| matches!( + e, + RouterEvent::RetryCountRaised { level: 0, model, .. } if model == "primary" + ))); + assert_eq!(response.model_group, "backup"); +} + +#[rstest] +#[case::negative(UncountedRetries::Negative)] +#[case::not_positive(UncountedRetries::NotPositive)] +#[tokio::test] +async fn a_num_retries_below_one_leaves_the_failure_standing( + config: RouterConfig, + #[case] uncounted: UncountedRetries, +) { + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let router = router(config, json!({"num_retries": 3}), host.clone()); + let request = RouterRequest { + uncounted_retries: Some(uncounted), + ..request() + }; + let refused = router.call(Op::from("acompletion"), request).await; + assert!(matches!(refused, Err(Error::Attempt(failed)) if failed.status == Some(500))); + assert_eq!(host.retries(), 0); + assert!( + !host + .events + .lock() + .iter() + .any(|event| matches!(event, RouterEvent::RetryCountRaised { .. })) + ); +} + +#[rstest] +#[tokio::test] +async fn a_retry_policy_that_grants_retries_outranks_a_num_retries_that_raises( + config: RouterConfig, +) { + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let router = router( + RouterConfig { + retry_policy: serde_json::from_value(json!({"DefaultRetries": 1})).unwrap(), + ..config + }, + json!({}), + host.clone(), + ); + let request = RouterRequest { + uncounted_retries: Some(UncountedRetries::Raises), + ..request() + }; + let response = router.call(Op::from("acompletion"), request).await.unwrap(); + assert_eq!(response.model_group, "primary"); + assert_eq!(host.retries(), 1); +} + +#[rstest] +#[tokio::test] +async fn a_name_nothing_serves_routes_to_the_default_deployment(config: RouterConfig) { + let host = Arc::new(ScriptedHost::default()); + let router = router( + config, + json!({"default_deployment": { + "model_name": "dflt", "litellm_params": {"model": "openai/x"}, "model_info": {"id": "dd"} + }}), + host.clone(), + ); + let request = RouterRequest { + model: "other".to_owned(), + ..RouterRequest::default() + }; + let response = router + .call(Op::from("acompletion"), request.clone()) + .await + .unwrap(); + assert_eq!( + ( + response.deployment_id.as_str(), + response.model_group.as_str() + ), + ("dd", "other") + ); + let picked = router + .select(&Op::from("acompletion"), &request) + .await + .unwrap(); + assert_eq!(picked.params.model, "other"); +} + +#[rstest] +#[tokio::test] +async fn a_stale_member_map_naming_a_dropped_group_raises_on_every_pick(mut config: RouterConfig) { + config.routing_group_members = Some([("primary".to_owned(), "gone".to_owned())].into()); + let router = router(config, json!({}), Arc::new(ScriptedHost::default())); + let refused = router.select(&Op::from("acompletion"), &request()).await; + assert!(matches!(refused, Err(Error::MissingRoutingGroup { group }) if group == "gone")); + let other = RouterRequest { + model: "backup".to_owned(), + ..RouterRequest::default() + }; + assert!( + router + .select(&Op::from("acompletion"), &other) + .await + .is_ok() + ); +} + +#[rstest] +#[tokio::test] +async fn written_indexes_replace_the_ones_the_deployments_build(config: RouterConfig) { + let router = router(config, json!({}), Arc::new(ScriptedHost::default())); + let index: litellm_router_core::registry::IndexOverrides = serde_json::from_value(json!({ + "model_names": ["backup"], + "model_name": {"primary": [1], "backup": [2]}, + })) + .unwrap(); + router + .apply(litellm_router_core::ChangeSet { + index: Some(index), + ..litellm_router_core::ChangeSet::default() + }) + .unwrap(); + for _ in 0..4 { + let picked = router + .select(&Op::from("acompletion"), &request()) + .await + .unwrap(); + assert_eq!(picked.id, "a2"); + } + router + .apply(litellm_router_core::ChangeSet { + index: Some(litellm_router_core::registry::IndexOverrides::default()), + ..litellm_router_core::ChangeSet::default() + }) + .unwrap(); + assert_eq!(router.registry().group("primary").unwrap().len(), 2); +} + +#[rstest] +#[tokio::test] +async fn a_retry_policy_retries_a_pick_that_found_no_deployment(config: RouterConfig) { + let host = Arc::new(ScriptedHost::default()); + let mut config = config; + config.retry_policy = serde_json::from_value(json!({"DefaultRetries": 2})).unwrap(); + let router = router(config, json!({"num_retries": 0}), host.clone()); + let request = RouterRequest { + model: "nothing".to_owned(), + ..RouterRequest::default() + }; + let refused = router.call(Op::from("acompletion"), request).await; + assert!(matches!(refused, Err(Error::UnknownModel { .. }))); + let events = host.events.lock(); + let retries = events + .iter() + .filter(|event| matches!(event, RouterEvent::Retry { .. })) + .count(); + assert_eq!(retries, 2); + assert!(events.iter().any(|event| matches!( + event, + RouterEvent::RetriesExhausted { + picked: true, + level: 0, + .. + } + ))); +} + +#[rstest] +#[tokio::test] +async fn a_default_deployment_python_cannot_copy_raises_for_a_name_nothing_serves( + config: RouterConfig, +) { + let router = router( + config, + json!({"default_deployment_raises": true}), + Arc::new(ScriptedHost::default()), + ); + let request = RouterRequest { + model: "other".to_owned(), + ..RouterRequest::default() + }; + let refused = router.select(&Op::from("acompletion"), &request).await; + assert!(matches!(refused, Err(Error::DefaultDeploymentRaises { model }) if model == "other")); + assert!( + router + .select(&Op::from("acompletion"), &self::request()) + .await + .is_ok() + ); +} + +#[rstest] +#[tokio::test] +async fn a_written_index_position_past_the_list_raises_for_that_name(config: RouterConfig) { + let router = router(config, json!({}), Arc::new(ScriptedHost::default())); + let index: litellm_router_core::registry::IndexOverrides = + serde_json::from_value(json!({"model_name": {"primary": [0, 9], "backup": [2]}})).unwrap(); + router + .apply(litellm_router_core::ChangeSet { + index: Some(index), + ..litellm_router_core::ChangeSet::default() + }) + .unwrap(); + let refused = router.select(&Op::from("acompletion"), &request()).await; + assert!(matches!(refused, Err(Error::IndexOutOfRange { model }) if model == "primary")); + let backup = RouterRequest { + model: "backup".to_owned(), + ..RouterRequest::default() + }; + assert!( + router + .select(&Op::from("acompletion"), &backup) + .await + .is_ok() + ); +} + +#[rstest] +#[case::no_list_takes_the_order_tier(json!(null), true, false, "p2")] +#[case::unmatched_list_takes_the_order_tier(json!([{"unrelated": ["context"]}]), true, false, "p2")] +#[case::unmatched_list_falls_through_to_regular(json!([{"unrelated": ["context"]}]), false, false, "b1")] +#[case::unmatched_list_leaves_the_client_side_list(json!([{"unrelated": ["context"]}]), false, true, "b1")] +#[case::matched_list_beats_the_order_tier(json!([{"primary": ["context"]}]), true, false, "c1")] +#[case::matched_star_beats_the_order_tier(json!([{"*": ["context"]}]), true, false, "c1")] +#[case::matched_list_beats_the_client_side_list(json!([{"primary": ["context"]}]), false, true, "c1")] +#[case::matched_list_beats_both(json!([{"primary": ["context"]}]), true, true, "c1")] +#[tokio::test] +async fn a_context_window_error_takes_its_own_chain_only_when_the_group_matches( + #[case] context_window_fallbacks: serde_json::Value, + #[case] tiered: bool, + #[case] client_side: bool, + #[case] expected: &str, +) { + let host = Arc::new(ScriptedHost::failing("primary", vec![context_window()])); + let router = router( + tiers(tiered), + json!({ + "fallbacks": [{"primary": ["backup"]}], + "context_window_fallbacks": context_window_fallbacks, + }), + host.clone(), + ); + let call = RouterRequest { + fallbacks: client_side.then(|| Some(serde_json::from_value(json!(["backup"])).unwrap())), + ..request() + }; + let response = router.call(Op::from("acompletion"), call).await.unwrap(); + assert_eq!(response.deployment_id, expected); +} + +#[rstest] +#[case::context_window_keeps_its_own_error( + context_window(), + FailureKind::ContextWindowExceeded, + false +)] +#[case::any_other_raises_the_last_hop(server_error(), FailureKind::ServiceUnavailable, true)] +#[tokio::test] +async fn a_failed_order_chain_raises_by_the_error_that_started_it( + #[case] first: AttemptError, + #[case] raised: FailureKind, + #[case] last_hop: bool, +) { + let host = Arc::new(ScriptedHost::scripted(vec![ + ("primary", vec![first, failure(FailureKind::RateLimit, 429)]), + ( + "backup", + vec![failure(FailureKind::ServiceUnavailable, 503)], + ), + ])); + let router = router( + tiers(true), + json!({ + "fallbacks": [{"primary": ["backup"]}], + "context_window_fallbacks": [{"unrelated": ["context"]}], + }), + host.clone(), + ); + let refused = router.call(Op::from("acompletion"), request()).await; + assert!(matches!(refused, Err(Error::Attempt(failed)) if failed.kind == raised)); + assert_eq!(host.selected(), ["p1", "p2", "b1"]); + assert!( + host.events + .lock() + .contains(&RouterEvent::OrderChainFailed { level: 0, last_hop }) + ); +} + +#[rstest] +#[case::context_window_skips_it(context_window(), "backup")] +#[case::a_rate_limit_takes_it(failure(FailureKind::RateLimit, 429), "primary")] +#[tokio::test] +async fn weighted_failover_serves_every_failure_but_a_context_window_error( + #[case] first: AttemptError, + #[case] served_by: &str, +) { + let host = Arc::new(ScriptedHost::failing("primary", vec![first])); + let config: RouterConfig = serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/a"}, "model_info": {"id": "a1"}}, + {"model_name": "primary", "litellm_params": {"model": "openai/b"}, "model_info": {"id": "a2"}}, + {"model_name": "backup", "litellm_params": {"model": "anthropic/c"}, "model_info": {"id": "b1"}}, + ], + "enable_weighted_failover": true, + })) + .unwrap(); + let router = router( + config, + json!({ + "fallbacks": [{"primary": ["backup"]}], + "context_window_fallbacks": [{"unrelated": ["backup"]}], + }), + host.clone(), + ); + let response = router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + assert_eq!(response.model_group, served_by); +} + +#[rstest] +#[tokio::test] +async fn a_failed_agentic_followup_is_not_retried_but_still_falls_back(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing("primary", vec![agentic_followup()])); + let router = router( + config, + json!({"num_retries": 3, "fallbacks": [{"primary": ["backup"]}]}), + host.clone(), + ); + let response = router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + assert_eq!(response.deployment_id, "b1"); + assert_eq!(host.retries(), 0); + assert_eq!(host.selected().len(), 2); +} + +#[rstest] +#[tokio::test] +async fn a_failed_agentic_followup_skips_the_retry_policy_lookup(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing("primary", vec![agentic_followup()])); + let router = router(config, json!({"num_retries": 3}), host.clone()); + let call = RouterRequest { + retry_policy_raises: vec!["primary".to_owned()], + ..request() + }; + let refused = router.call(Op::from("acompletion"), call).await; + assert!(matches!(refused, Err(Error::Attempt(failed)) if failed.agentic_followup)); + assert!( + !host + .events + .lock() + .iter() + .any(|event| matches!(event, RouterEvent::RetryPolicyRaised { .. })) + ); +} + +#[rstest] +#[tokio::test] +async fn a_retry_that_fails_its_agentic_followup_ends_the_retries(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing( + "primary", + vec![server_error(), agentic_followup()], + )); + let router = router(config, json!({"num_retries": 3}), host.clone()); + let refused = router.call(Op::from("acompletion"), request()).await; + assert!(matches!(refused, Err(Error::Attempt(failed)) if failed.agentic_followup)); + assert_eq!((host.retries(), host.selected().len()), (1, 2)); +} + +fn stream_origin() -> StreamOrigin { + StreamOrigin { + group: "primary".to_owned(), + ..StreamOrigin::default() + } +} + +fn stream_request() -> RouterRequest { + RouterRequest { + num_retries: Some(3), + ..request() + } +} + +#[rstest] +#[tokio::test] +async fn a_stream_that_failed_its_agentic_followup_is_not_retried(config: RouterConfig) { + let host = Arc::new(ScriptedHost::default()); + let router = router(config, json!({}), host.clone()); + let refused = router + .retry_stream( + Op::from("acompletion"), + stream_request(), + stream_origin(), + agentic_followup(), + ) + .await; + assert!(matches!(refused, Err(Error::Attempt(failed)) if failed.agentic_followup)); + assert_eq!((host.retries(), host.selected().len()), (0, 0)); +} + +#[rstest] +#[tokio::test] +async fn a_stream_retry_that_fails_its_agentic_followup_ends_the_retries(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing("primary", vec![agentic_followup()])); + let router = router(config, json!({}), host.clone()); + let refused = router + .retry_stream( + Op::from("acompletion"), + stream_request(), + stream_origin(), + server_error(), + ) + .await; + assert!(matches!(refused, Err(Error::Attempt(failed)) if failed.agentic_followup)); + assert_eq!((host.retries(), host.selected().len()), (1, 1)); +} + +#[rstest] +#[tokio::test] +async fn a_stream_retry_is_reported_before_its_attempt(config: RouterConfig) { + let host = Arc::new(ScriptedHost::default()); + let router = router(config, json!({}), host.clone()); + let response = router + .retry_stream( + Op::from("acompletion"), + stream_request(), + stream_origin(), + server_error(), + ) + .await + .unwrap(); + assert_eq!((response.attempted_retries, host.retries()), (1, 1)); +} + +fn fallback_list(value: serde_json::Value) -> Fallbacks { + serde_json::from_value(value).unwrap() +} + +#[rstest] +#[case::names(json!(["backup"]))] +#[case::keyed(json!([{"primary": ["backup"]}]))] +#[case::star(json!([{"*": ["backup"]}]))] +fn a_request_fallback_list_can_take_over_a_stream( + config: RouterConfig, + #[case] list: serde_json::Value, +) { + let router = router(config, json!({}), Arc::new(ScriptedHost::default())); + let request = RouterRequest { + fallbacks: Some(Some(fallback_list(list))), + ..request() + }; + let policy = router.stream_policy(&request, &stream_origin(), None); + assert!(policy.can_fall_back); + assert!(policy.refusal_fallback); +} + +#[rstest] +fn a_request_content_policy_list_can_take_over_a_stream(config: RouterConfig) { + let router = router(config, json!({}), Arc::new(ScriptedHost::default())); + let request = RouterRequest { + content_policy_fallbacks: Some(Some(fallback_list(json!([{"primary": ["backup"]}])))), + ..request() + }; + let policy = router.stream_policy(&request, &stream_origin(), None); + assert!(policy.can_fall_back); + assert!(policy.refusal_fallback); +} + +#[rstest] +#[case::cleared(None)] +#[case::another_group(Some(json!([{"other": ["backup"]}])))] +fn a_request_fallback_list_replaces_the_router_list_for_a_stream( + config: RouterConfig, + #[case] list: Option, +) { + let router = router( + config, + json!({"fallbacks": [{"primary": ["backup"]}], "default_fallbacks": ["backup"]}), + Arc::new(ScriptedHost::default()), + ); + let request = RouterRequest { + fallbacks: Some(list.map(fallback_list)), + ..request() + }; + let policy = router.stream_policy(&request, &stream_origin(), None); + assert!(!policy.can_fall_back); +} + +#[rstest] +#[case::readable(vec![], 5, true)] +#[case::malformed(vec!["primary".to_owned()], 1, false)] +fn a_group_policy_that_does_not_read_governs_no_stream_retry( + mut config: RouterConfig, + #[case] retry_policy_raises: Vec, + #[case] budget: u32, + #[case] applies: bool, +) { + config.retry_policy = serde_json::from_value(json!({"InternalServerErrorRetries": 5})).unwrap(); + let router = router( + config, + json!({"num_retries": 1}), + Arc::new(ScriptedHost::default()), + ); + let request = RouterRequest { + retry_policy_raises, + ..request() + }; + let policy = router.stream_policy( + &request, + &stream_origin(), + Some(FailureKind::InternalServer), + ); + assert_eq!(policy.retry_budget, Some((budget, applies))); +} + +#[rstest] +#[tokio::test] +async fn a_level_reports_its_fallback_handling_before_any_hop(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing("primary", vec![context_window()])); + let router = router( + config, + json!({"num_retries": 0, "fallbacks": [{"primary": ["backup"]}]}), + host.clone(), + ); + router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + let events = host.events.lock(); + let falling_back = RouterEvent::FallingBack { + level: 0, + model: "primary".to_owned(), + }; + let reported = events.iter().position(|e| *e == falling_back).unwrap(); + let hopped = events + .iter() + .position(|e| matches!(e, RouterEvent::Fallback { .. })) + .unwrap(); + assert!(reported < hopped); +} + +#[rstest] +#[tokio::test] +async fn the_order_path_reports_no_fallback_handling() { + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let router = router(tiers(true), json!({"num_retries": 0}), host.clone()); + router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + assert!( + !host + .events + .lock() + .iter() + .any(|e| matches!(e, RouterEvent::FallingBack { .. })) + ); +} + +fn fallbacks_failed(host: &ScriptedHost) -> Vec<(u32, bool, bool)> { + host.events + .lock() + .iter() + .filter_map(|event| match event { + RouterEvent::FallbacksFailed { + level, + chain, + last_hop, + } => Some((*level, *chain, *last_hop)), + _ => None, + }) + .collect() +} + +#[rstest] +#[tokio::test] +async fn a_chain_that_fails_reports_every_level_innermost_first(config: RouterConfig) { + let host = Arc::new(ScriptedHost::scripted(vec![ + ("primary", vec![server_error()]), + ("backup", vec![server_error()]), + ])); + let router = router( + config, + json!({"num_retries": 0, "fallbacks": [{"primary": ["backup"]}]}), + host.clone(), + ); + router + .call(Op::from("acompletion"), request()) + .await + .unwrap_err(); + assert_eq!( + fallbacks_failed(&host), + vec![(1, true, false), (0, true, true)] + ); +} + +#[rstest] +#[tokio::test] +async fn a_chain_past_max_fallbacks_reports_the_levels_own_failure(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let router = router( + config, + json!({"num_retries": 0, "max_fallbacks": 0, "fallbacks": [{"primary": ["backup"]}]}), + host.clone(), + ); + router + .call(Op::from("acompletion"), request()) + .await + .unwrap_err(); + assert_eq!(fallbacks_failed(&host), vec![(0, true, false)]); +} + +#[rstest] +#[tokio::test] +async fn a_served_fallback_and_a_disabled_walk_report_no_failure(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let dynamic = json!({"num_retries": 0, "fallbacks": [{"primary": ["backup"]}]}); + let served = router(config.clone(), dynamic.clone(), host.clone()); + served + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + assert_eq!(fallbacks_failed(&host), vec![]); + + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let disabled = router(config, dynamic, host.clone()); + let request = RouterRequest { + disable_fallbacks: true, + ..request() + }; + disabled + .call(Op::from("acompletion"), request) + .await + .unwrap_err(); + assert_eq!(fallbacks_failed(&host), vec![]); +} + +#[tokio::test] +async fn the_order_path_reports_no_failed_fallbacks() { + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let router = router(tiers(true), json!({"num_retries": 0}), host.clone()); + router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + assert_eq!(fallbacks_failed(&host), vec![]); +} + +fn refusing_host(group: &str) -> Arc { + Arc::new(ScriptedHost { + refuses_dict_targets: true, + ..ScriptedHost::failing(group, vec![server_error()]) + }) +} + +#[rstest] +#[case::dict_target_first(json!([{"model": "backup", "api_key": "x"}, "backup"]))] +#[case::dict_target_last(json!(["backup", {"model": "backup", "api_key": "x"}]))] +#[tokio::test] +async fn a_refused_chain_tries_none_of_its_targets( + config: RouterConfig, + #[case] chain: serde_json::Value, +) { + let host = refusing_host("primary"); + let router = router( + config, + json!({"num_retries": 0, "fallbacks": [{"primary": chain}]}), + host.clone(), + ); + let raised = router.call(Op::from("acompletion"), request()).await; + assert!(matches!(raised, Err(Error::Attempt(failed)) if failed.is_a("InternalServerError"))); + assert_eq!(host.selected().len(), 1); +} + +#[rstest] +#[tokio::test] +async fn a_chain_of_names_is_never_refused(config: RouterConfig) { + let router = router( + config, + json!({"num_retries": 0, "fallbacks": [{"primary": ["backup"]}]}), + refusing_host("primary"), + ); + let response = router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + assert_eq!(response.deployment_id, "b1"); +} + +#[rstest] +#[tokio::test] +async fn a_refused_chain_on_the_order_path_raises_the_refusal() { + let host = refusing_host("primary"); + let router = router( + tiers(true), + json!({"num_retries": 0, "fallbacks": [{"primary": [{"model": "backup", "api_key": "x"}]}]}), + host.clone(), + ); + let raised = router.call(Op::from("acompletion"), request()).await; + assert!(matches!(raised, Err(Error::Attempt(failed)) if failed.is_a("ValueError"))); + assert_eq!(host.selected(), ["p1"]); +} + +#[rstest] +#[tokio::test] +async fn a_refused_chain_fails_only_its_own_level(mut config: RouterConfig) { + let host = Arc::new(ScriptedHost { + refuses_dict_targets: true, + ..ScriptedHost::scripted(vec![ + ("primary", vec![server_error()]), + ("backup", vec![server_error()]), + ]) + }); + let dynamic = json!({"num_retries": 0, "fallbacks": [ + {"primary": ["backup", "third"]}, + {"backup": [{"model": "third", "api_key": "x"}]}, + ]}); + config.model_list.push( + serde_json::from_value(json!({ + "model_name": "third", "litellm_params": {"model": "openai/t"}, "model_info": {"id": "t1"}, + })) + .unwrap(), + ); + let response = router(config, dynamic, host.clone()) + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + assert_eq!(response.deployment_id, "t1"); +} + +fn shared_public_name() -> RouterConfig { + serde_json::from_value(json!({ + "model_list": [ + {"model_name": "backup", "litellm_params": {"model": "openai/g"}, "model_info": {"id": "b1"}}, + {"model_name": "t1-pub", "litellm_params": {"model": "openai/m"}, + "model_info": {"id": "p1", "team_id": "T1", "team_public_model_name": "pub"}}, + {"model_name": "t2-pub", "litellm_params": {"model": "openai/m"}, + "model_info": {"id": "p2", "team_id": "T2", "team_public_model_name": "pub"}}, + ] + })) + .unwrap() +} + +fn proxy_admin_of_pub() -> RouterRequest { + RouterRequest { + model: "pub".to_owned(), + proxy_admin: true, + admin_model: Some("pub".to_owned()), + ..RouterRequest::default() + } +} + +#[rstest] +#[tokio::test] +async fn a_name_several_teams_share_falls_back() { + let router = router( + shared_public_name(), + json!({"fallbacks": [{"pub": ["backup"]}]}), + Arc::new(ScriptedHost::default()), + ); + let response = router + .call(Op::from("acompletion"), proxy_admin_of_pub()) + .await + .unwrap(); + assert_eq!( + ( + response.deployment_id.as_str(), + response.attempted_fallbacks + ), + ("b1", 1) + ); +} + +#[rstest] +#[tokio::test] +async fn a_name_several_teams_share_raises_its_refusal_when_the_fallback_fails() { + let router = router( + shared_public_name(), + json!({"fallbacks": [{"pub": ["backup"]}]}), + Arc::new(ScriptedHost::failing("backup", vec![server_error()])), + ); + let raised = router + .call(Op::from("acompletion"), proxy_admin_of_pub()) + .await; + assert!(matches!(raised, Err(Error::MultipleTeams { model }) if model == "pub")); +} + +/// A group whose second order level belongs to another team. +fn team_tiers() -> RouterConfig { + serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/p1", "order": 1}, + "model_info": {"id": "p1", "team_id": "t1"}}, + {"model_name": "primary", "litellm_params": {"model": "openai/p2", "order": 2}, + "model_info": {"id": "p2", "team_id": "t2"}}, + ] + })) + .unwrap() +} + +#[rstest] +#[case::listed_for_the_team(Some("t1"), false)] +#[case::listed_for_no_team(None, true)] +#[tokio::test] +async fn a_failed_level_lists_its_order_levels_for_the_metadata_team( + #[case] listing_team_id: Option<&str>, + #[case] walks_the_order_chain: bool, +) { + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let router = router(team_tiers(), json!({"num_retries": 0}), host.clone()); + let request = RouterRequest { + team_id: Some("t1".to_owned()), + listing_team_id: listing_team_id.map(str::to_owned), + ..request() + }; + let raised = router.call(Op::from("acompletion"), request).await; + assert_eq!( + matches!(raised, Err(Error::NoHealthyDeployments { .. })), + walks_the_order_chain + ); + assert_eq!(host.selected(), ["p1"]); +} + +fn tagged_request() -> RouterRequest { + RouterRequest { + filter_tags: true, + ..request() + } +} + +#[rstest] +#[tokio::test] +async fn a_failed_pick_retries_like_a_failed_attempt(config: RouterConfig) { + let host = Arc::new(ScriptedHost { + pick_failures: Mutex::new(VecDeque::from([failure(FailureKind::RateLimit, 429)])), + ..ScriptedHost::default() + }); + let response = router(config, json!({"num_retries": 1}), host.clone()) + .call(Op::from("acompletion"), tagged_request()) + .await + .unwrap(); + assert_eq!( + (response.model_group.as_str(), response.attempted_retries), + ("primary", 1) + ); +} + +#[rstest] +#[tokio::test] +async fn a_failed_pick_falls_back_with_no_deployment_to_blame(config: RouterConfig) { + let host = Arc::new(ScriptedHost { + pick_failures: Mutex::new(VecDeque::from([failure(FailureKind::RateLimit, 429)])), + ..ScriptedHost::default() + }); + let router = router( + config, + json!({"num_retries": 0, "fallbacks": [{"primary": ["backup"]}]}), + host.clone(), + ); + let response = router + .call(Op::from("acompletion"), tagged_request()) + .await + .unwrap(); + assert_eq!( + ( + response.deployment_id.as_str(), + response.attempted_fallbacks + ), + ("b1", 1) + ); + assert_eq!(host.selected(), ["b1"]); +} + +#[rstest] +#[tokio::test] +async fn a_fallback_check_that_raises_ends_the_chain_with_the_levels_own_error( + config: RouterConfig, +) { + let host = Arc::new(ScriptedHost { + fallback_check_raises: Some("TypeError"), + ..ScriptedHost::failing("primary", vec![failure(FailureKind::RateLimit, 429)]) + }); + let router = router( + config, + json!({"num_retries": 0, "fallbacks": [{"primary": ["backup"]}]}), + host.clone(), + ); + let raised = router.call(Op::from("acompletion"), request()).await; + assert!(matches!(raised, Err(Error::Attempt(failed)) if failed.kind == FailureKind::RateLimit)); + assert_eq!(host.selected().len(), 1); +} + +#[rstest] +#[tokio::test] +async fn a_fallback_check_that_raises_on_the_order_path_raises_its_own_error() { + let host = Arc::new(ScriptedHost { + fallback_check_raises: Some("TypeError"), + ..ScriptedHost::scripted(vec![("primary", vec![server_error(), server_error()])]) + }); + let router = router( + tiers(true), + json!({"num_retries": 0, "fallbacks": [{"primary": ["backup"]}]}), + host.clone(), + ); + let raised = router.call(Op::from("acompletion"), request()).await; + assert!(matches!(raised, Err(Error::Attempt(failed)) if failed.is_a("TypeError"))); +} + +#[rstest] +#[case::an_int(json!(5))] +#[case::none(json!(null))] +#[tokio::test] +async fn a_dict_target_with_a_non_string_model_is_a_hop_that_attempts_nothing( + config: RouterConfig, + #[case] model: serde_json::Value, +) { + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let router = router( + config, + json!({"num_retries": 0, "fallbacks": [{"primary": [{"model": model}, "backup"]}]}), + host.clone(), + ); + let response = router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + assert_eq!( + ( + response.deployment_id.as_str(), + response.attempted_fallbacks + ), + ("b1", 2) + ); + assert_eq!(host.selected().len(), 2); +} + +#[rstest] +#[tokio::test] +async fn a_dict_target_without_a_model_serves_the_group_that_failed_again(config: RouterConfig) { + let host = Arc::new(ScriptedHost::failing("primary", vec![server_error()])); + let router = router( + config, + json!({"num_retries": 0, "fallbacks": [{"primary": [{"temperature": 0.5}]}]}), + host.clone(), + ); + let response = router + .call(Op::from("acompletion"), request()) + .await + .unwrap(); + assert_eq!( + (response.model_group.as_str(), response.attempted_fallbacks), + ("primary", 1) + ); +} + +fn weighted_failover() -> RouterConfig { + serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/a"}, "model_info": {"id": "a1"}}, + {"model_name": "primary", "litellm_params": {"model": "openai/b"}, "model_info": {"id": "a2"}}, + ], + "enable_weighted_failover": true, + })) + .unwrap() +} + +#[rstest] +#[case::a_bug_propagates(AttemptError::host_raised(&["TypeError", "Exception"]), "TypeError")] +#[case::a_provider_error_defers(failure(FailureKind::RateLimit, 429), "InternalServerError")] +#[case::no_deployment_defers( + AttemptError::host_raised(&["RouterRateLimitError", "ValueError"]), + "InternalServerError" +)] +#[tokio::test] +async fn weighted_failover_swallows_only_api_and_rate_limit_errors( + #[case] hop_failure: AttemptError, + #[case] raised_class: &str, +) { + let host = Arc::new(ScriptedHost::failing( + "primary", + vec![server_error(), hop_failure], + )); + let raised = router(weighted_failover(), json!({"num_retries": 0}), host.clone()) + .call(Op::from("acompletion"), request()) + .await; + assert!(matches!(raised, Err(Error::Attempt(failed)) if failed.is_a(raised_class))); + assert_eq!(host.selected().len(), 2); +} + +fn wildcard_tiers() -> RouterConfig { + serde_json::from_value(json!({ + "model_list": [ + {"model_name": "openai/*", "litellm_params": {"model": "openai/*", "order": 1}, "model_info": {"id": "w1"}}, + {"model_name": "openai/*", "litellm_params": {"model": "openai/*", "order": 2}, "model_info": {"id": "w2"}}, + ] + })) + .unwrap() +} + +fn alias_tiers() -> RouterConfig { + serde_json::from_value(json!({ + "model_list": [ + {"model_name": "gg", "litellm_params": {"model": "openai/a", "order": 1}, "model_info": {"id": "w1"}}, + {"model_name": "gg", "litellm_params": {"model": "openai/b", "order": 2}, "model_info": {"id": "w2"}}, + ] + })) + .unwrap() +} + +fn team_public_tiers() -> RouterConfig { + serde_json::from_value(json!({ + "model_list": [ + {"model_name": "t1a", "litellm_params": {"model": "openai/a", "order": 1}, + "model_info": {"id": "w1", "team_id": "T1", "team_public_model_name": "tp"}}, + {"model_name": "t1b", "litellm_params": {"model": "openai/b", "order": 2}, + "model_info": {"id": "w2", "team_id": "T1", "team_public_model_name": "tp"}}, + ] + })) + .unwrap() +} + +#[rstest] +#[case::a_wildcard(wildcard_tiers(), json!({"num_retries": 0}), "openai/gpt-4o", None)] +#[case::an_alias( + alias_tiers(), + json!({"num_retries": 0, "model_group_alias": {"al": "gg"}}), + "al", + None +)] +#[case::a_team_public_name(team_public_tiers(), json!({"num_retries": 0}), "tp", Some("T1"))] +#[tokio::test] +async fn order_levels_walk_through_any_name_the_model_list_lists( + #[case] config: RouterConfig, + #[case] dynamic: serde_json::Value, + #[case] model: &str, + #[case] team: Option<&str>, +) { + let host = Arc::new(ScriptedHost::default()); + *host.first_failure.lock() = Some(failure(FailureKind::RateLimit, 429)); + let request = RouterRequest { + model: model.to_owned(), + team_id: team.map(str::to_owned), + listing_team_id: team.map(str::to_owned), + ..RouterRequest::default() + }; + let response = router(config, dynamic, host.clone()) + .call(Op::from("acompletion"), request) + .await + .unwrap(); + assert_eq!(response.deployment_id, "w2"); +} + +#[rstest] +#[tokio::test] +async fn a_team_wildcard_public_name_routes_for_its_team() { + let config: RouterConfig = serde_json::from_value(json!({ + "model_list": [ + {"model_name": "t1-w", "litellm_params": {"model": "openai/*"}, + "model_info": {"id": "tw1", "team_id": "T1", "team_public_model_name": "tw-*"}}, + {"model_name": "g", "litellm_params": {"model": "openai/g"}, "model_info": {"id": "gp"}}, + ] + })) + .unwrap(); + let request = RouterRequest { + model: "tw-gpt-4o".to_owned(), + team_id: Some("T1".to_owned()), + ..RouterRequest::default() + }; + let response = router(config, json!({}), Arc::new(ScriptedHost::default())) + .call(Op::from("acompletion"), request) + .await + .unwrap(); + assert_eq!(response.deployment_id, "tw1"); +} + +#[rstest] +#[tokio::test] +async fn a_paused_deployment_named_by_id_falls_back() { + let config: RouterConfig = serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/a"}, + "model_info": {"id": "a1", "blocked": true}}, + {"model_name": "backup", "litellm_params": {"model": "openai/b"}, "model_info": {"id": "b1"}}, + ] + })) + .unwrap(); + let request = RouterRequest { + model: "a1".to_owned(), + ..RouterRequest::default() + }; + let response = router( + config, + json!({"fallbacks": [{"a1": ["backup"]}]}), + Arc::new(ScriptedHost::default()), + ) + .call(Op::from("acompletion"), request) + .await + .unwrap(); + assert_eq!(response.deployment_id, "b1"); +} + +/// `primary` with `a1`'s `model_info` as given, and an unremarkable `a2`. +fn with_first_info(info: serde_json::Value) -> RouterConfig { + serde_json::from_value(json!({ + "model_list": [ + {"model_name": "primary", "litellm_params": {"model": "openai/a"}, "model_info": info}, + {"model_name": "primary", "litellm_params": {"model": "openai/b"}, "model_info": {"id": "a2"}}, + ] + })) + .unwrap() +} + +#[rstest] +#[tokio::test] +async fn a_web_search_request_skips_the_deployments_that_declare_no_support() { + let config = with_first_info(json!({"id": "a1", "supports_web_search": false})); + let router = router(config, json!({}), Arc::new(ScriptedHost::default())); + let request = RouterRequest { + web_search: true, + ..request() + }; + for _ in 0..16 { + let picked = router + .select(&Op::from("acompletion"), &request) + .await + .unwrap(); + assert_eq!(picked.id, "a2"); + } +} + +#[rstest] +#[tokio::test] +async fn an_endpoint_a_deployment_refuses_routes_to_the_others() { + let config = with_first_info(json!({ + "id": "a1", + "enforce_supported_endpoints": true, + "supported_endpoints": ["/v1/embeddings"], + })); + let router = router(config, json!({}), Arc::new(ScriptedHost::default())); + let request = RouterRequest { + endpoint: Some("/v1/chat/completions".to_owned()), + ..request() + }; + for _ in 0..16 { + let picked = router + .select(&Op::from("acompletion"), &request) + .await + .unwrap(); + assert_eq!(picked.id, "a2"); + } +} + +#[rstest] +#[tokio::test] +async fn an_endpoint_every_deployment_refuses_fails_the_pick() { + let config: RouterConfig = serde_json::from_value(json!({ + "model_list": [{ + "model_name": "primary", + "litellm_params": {"model": "openai/a"}, + "model_info": { + "id": "a1", + "enforce_supported_endpoints": true, + "supported_endpoints": ["/v1/embeddings"], + }, + }] + })) + .unwrap(); + let router = router(config, json!({}), Arc::new(ScriptedHost::default())); + let request = RouterRequest { + endpoint: Some("/v1/chat/completions".to_owned()), + ..request() + }; + let refused = router + .call(Op::from("acompletion"), request) + .await + .unwrap_err(); + assert!(matches!( + refused, + Error::EndpointNotSupported { model, message } + if model == "primary" && message + == "/v1/chat/completions is not supported by model=primary. \ + Supported endpoints: /v1/embeddings" + )); +} + +#[rstest] +#[tokio::test] +async fn an_order_in_model_info_narrows_the_pick() { + let mut config = with_first_info(json!({"id": "a1", "order": 2})); + config.model_list[1] + .model_info + .insert("order".to_owned(), json!("1")); + let router = router(config, json!({}), Arc::new(ScriptedHost::default())); + for _ in 0..16 { + let picked = router + .select(&Op::from("acompletion"), &request()) + .await + .unwrap(); + assert_eq!(picked.id, "a2"); + } +} + +#[rstest] +#[tokio::test] +async fn a_fallback_hop_drops_the_order_the_request_named() { + let host = Arc::new(ScriptedHost::failing( + "primary", + vec![failure(FailureKind::InternalServer, 500)], + )); + let router = router( + tiers(false), + json!({"num_retries": 0, "fallbacks": [{"primary": ["backup"]}]}), + host, + ); + let request = RouterRequest { + target_order: Some(1), + ..request() + }; + let response = router.call(Op::from("acompletion"), request).await.unwrap(); + assert_eq!(response.deployment_id, "b1"); +} + +#[rstest] +#[tokio::test] +async fn a_listed_pass_through_pick_names_the_group_an_alias_resolves_to(config: RouterConfig) { + let router = router( + config, + json!({"model_alias_map": {"al": "primary"}}), + Arc::new(ScriptedHost::default()), + ); + let request = RouterRequest { + model: "al".to_owned(), + pass_through: Some(PassThrough::Listed), + ..RouterRequest::default() + }; + let refused = router + .select(&Op::from("acompletion"), &request) + .await + .unwrap_err(); + assert!(matches!( + refused, + Error::NoPassThroughDeployments { model } if model == "primary" + )); +} diff --git a/litellm-rust/crates/secret-value/src/secret_value.rs b/litellm-rust/crates/secret-value/src/secret_value.rs index 27e4227080d..33c559b80ec 100644 --- a/litellm-rust/crates/secret-value/src/secret_value.rs +++ b/litellm-rust/crates/secret-value/src/secret_value.rs @@ -16,6 +16,18 @@ impl SecretValue { } } +impl From for SecretValue { + fn from(value: String) -> Self { + Self::new(value) + } +} + +impl From<&str> for SecretValue { + fn from(value: &str) -> Self { + Self::new(value) + } +} + impl PartialEq for SecretValue { fn eq(&self, other: &Self) -> bool { subtle::ConstantTimeEq::ct_eq(self.0.as_bytes(), other.0.as_bytes()).into() diff --git a/litellm-rust/crates/secrets-aws/src/auth.rs b/litellm-rust/crates/secrets-aws/src/auth.rs index 66f4f51bda9..6bec8ad96a1 100644 --- a/litellm-rust/crates/secrets-aws/src/auth.rs +++ b/litellm-rust/crates/secrets-aws/src/auth.rs @@ -39,30 +39,15 @@ impl Credentials { Self { auth, config: AwsAuthConfig { - access_key_id: context - .access_key_id - .as_ref() - .map(|value| value.expose().to_owned()), - secret_access_key: context - .secret_access_key - .as_ref() - .map(|value| value.expose().to_owned()), - session_token: context - .session_token - .as_ref() - .map(|value| value.expose().to_owned()), + access_key_id: context.access_key_id.as_ref().cloned(), + secret_access_key: context.secret_access_key.as_ref().cloned(), + session_token: context.session_token.as_ref().cloned(), region_name: region(settings, environment.as_ref()).ok(), role_name: settings.aws_role_name.clone(), session_name: settings.aws_session_name.clone(), - external_id: settings - .aws_external_id - .as_ref() - .map(|v| v.expose().to_owned()), + external_id: settings.aws_external_id.as_ref().cloned(), profile_name: settings.aws_profile_name.clone(), - web_identity_token: settings - .aws_web_identity_token - .as_ref() - .map(|v| v.expose().to_owned()), + web_identity_token: settings.aws_web_identity_token.as_ref().cloned(), sts_endpoint: settings.aws_sts_endpoint.clone(), }, environment, diff --git a/litellm/__init__.py b/litellm/__init__.py index 0e5101b49c3..8e5dd68a186 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -8,7 +8,7 @@ _apply_process_defaults() import threading import os -from collections.abc import Mapping, Sequence +from collections.abc import Sequence from typing import ( Any, Callable, @@ -688,6 +688,7 @@ darkbloom_models: Set = set() openinfer_models: Final[Set[str]] = set() kyma_models: Final[set[str]] = set() # mutable-ok: populated when the shared model catalog loads streamlake_models: Final[Set[str]] = set() +wally_models: Final[Set[str]] = set() zerogpu_models: Final[Set[str]] = set() v0_models: Set = set() morph_models: Set = set() @@ -984,6 +985,8 @@ def _populate_provider_model_sets(model_cost_map: Mapping[str, Mapping[str, obje kyma_models.add(key) elif value.get("litellm_provider") == "streamlake": streamlake_models.add(key) + elif value.get("litellm_provider") == "wally": + wally_models.add(key) elif value.get("litellm_provider") == "zerogpu": zerogpu_models.add(key) elif value.get("litellm_provider") == "v0": @@ -1071,7 +1074,6 @@ _populate_provider_model_sets(model_cost) # Azure returns gpt-35-turbo in their responses, we need to map this to azure/gpt-3.5-turbo for token counting azure_llms = { "gpt-35-turbo": "azure/gpt-35-turbo", - "gpt-35-turbo-16k": "azure/gpt-35-turbo-16k", "gpt-35-turbo-instruct": "azure/gpt-35-turbo-instruct", "azure/gpt-41": "gpt-4.1", "azure/gpt-41-mini": "gpt-4.1-mini", @@ -1166,6 +1168,7 @@ model_list = list( | openinfer_models | kyma_models | streamlake_models + | wally_models | zerogpu_models | v0_models | morph_models @@ -1299,6 +1302,7 @@ def _build_models_by_provider() -> dict: "openinfer": openinfer_models, "kyma": kyma_models, "streamlake": streamlake_models, + "wally": wally_models, "zerogpu": zerogpu_models, "v0": v0_models, "morph": morph_models, @@ -1562,7 +1566,9 @@ from .realtime_api.main import ( _arealtime, acreate_realtime_client_secret, acreate_realtime_transcription_session, + acreate_realtime_translation_client_secret as acreate_realtime_translation_client_secret, arealtime_calls, + arealtime_translation_calls as arealtime_translation_calls, ) from .responses.main import _aresponses_websocket @@ -1754,6 +1760,9 @@ if TYPE_CHECKING: from .llms.typesafe.decisions.transformation import ( TypeSafeDecisionsConfig as TypeSafeDecisionsConfig, ) + from .llms.parallel_ai.decisions.transformation import ( + ParallelAIDecisionsConfig as ParallelAIDecisionsConfig, + ) from .llms.openrouter.decisions.transformation import ( OpenRouterDecisionsConfig as OpenRouterDecisionsConfig, ) @@ -1787,6 +1796,9 @@ if TYPE_CHECKING: from .llms.bespoke.decisions.transformation import ( BespokeDecisionsConfig as BespokeDecisionsConfig, ) + from .llms.empiriolabs.decisions.transformation import ( + EmpirioLabsDecisionsConfig as EmpirioLabsDecisionsConfig, + ) from .llms.eu_jev.decisions.transformation import ( EuJevDecisionsConfig as EuJevDecisionsConfig, ) @@ -1808,6 +1820,9 @@ if TYPE_CHECKING: from .llms.vertex_ai.rerank.transformation import ( VertexAIRerankConfig as VertexAIRerankConfig, ) + from .llms.together_ai.chat.transformation import ( + TogetherAIChatConfig as TogetherAIChatConfig, + ) from .llms.fireworks_ai.rerank.transformation import ( FireworksAIRerankConfig as FireworksAIRerankConfig, ) @@ -1853,9 +1868,6 @@ if TYPE_CHECKING: BedrockMantleAnthropicMessagesConfig as BedrockMantleAnthropicMessagesConfig, ) from .llms.together_ai.chat import TogetherAIConfig as TogetherAIConfig - from .llms.together_ai.chat.transformation import ( - TogetherAIChatConfig as TogetherAIChatConfig, - ) from .llms.nlp_cloud.chat.handler import NLPCloudConfig as NLPCloudConfig from .llms.vertex_ai.gemini.vertex_and_google_ai_studio_gemini import ( VertexGeminiConfig as VertexGeminiConfig, @@ -2014,6 +2026,9 @@ if TYPE_CHECKING: from .llms.xai.responses.transformation import ( XAIResponsesAPIConfig as XAIResponsesAPIConfig, ) + from .llms.vertex_ai.interactions.transformation import ( + VertexAIInteractionsConfig as VertexAIInteractionsConfig, + ) from .llms.litellm_proxy.responses.transformation import ( LiteLLMProxyResponsesAPIConfig as LiteLLMProxyResponsesAPIConfig, ) @@ -2041,9 +2056,6 @@ if TYPE_CHECKING: from .llms.gemini.interactions.transformation import ( GoogleAIStudioInteractionsConfig as GoogleAIStudioInteractionsConfig, ) - from .llms.vertex_ai.interactions.transformation import ( - VertexAIInteractionsConfig as VertexAIInteractionsConfig, - ) from .llms.openai.chat.o_series_transformation import ( OpenAIOSeriesConfig as OpenAIOSeriesConfig, OpenAIOSeriesConfig as OpenAIO1Config, @@ -2374,6 +2386,7 @@ if TYPE_CHECKING: supports_web_search: Callable[..., bool] supports_tool_search: Callable[..., bool] supports_url_context: Callable[..., bool] + supports_continuation: Callable[..., bool] supports_response_schema: Callable[..., bool] supports_parallel_function_calling: Callable[..., bool] supports_vision: Callable[..., bool] diff --git a/litellm/_internal_context.py b/litellm/_internal_context.py index 40d3377bf66..f2f7869876d 100644 --- a/litellm/_internal_context.py +++ b/litellm/_internal_context.py @@ -52,6 +52,18 @@ def internal_sub_call(parent_request_id: str | None = None) -> Generator[None]: internal_parent_request_id.reset(parent_token) +@contextmanager +def billed_separately() -> Generator[None]: + """A call that writes its own spend row even inside a sub-call whose parent bills the model response.""" + token: Final = is_internal_call.set(False) + parent_token: Final = internal_parent_request_id.set(None) + try: + yield + finally: + is_internal_call.reset(token) + internal_parent_request_id.reset(parent_token) + + @contextmanager def post_response_phase() -> Generator[None]: """Work the caller no longer waits for (success callbacks, response-cache writes), including tasks it spawns.""" diff --git a/litellm/_lazy_imports_registry.py b/litellm/_lazy_imports_registry.py index de290070ed3..bf903e23bc0 100644 --- a/litellm/_lazy_imports_registry.py +++ b/litellm/_lazy_imports_registry.py @@ -33,6 +33,7 @@ UTILS_NAMES: Final = ( "supports_web_search", "supports_tool_search", "supports_url_context", + "supports_continuation", "supports_response_schema", "supports_parallel_function_calling", "supports_vision", @@ -162,6 +163,7 @@ LLM_CONFIG_NAMES: Final = ( "HostedVLLMRerankConfig", "PerplexityDecisionsConfig", "TypeSafeDecisionsConfig", + "ParallelAIDecisionsConfig", "NaceDecisionsConfig", "OpenRouterDecisionsConfig", "FireworksAIDecisionsConfig", @@ -174,6 +176,7 @@ LLM_CONFIG_NAMES: Final = ( "OllamaDecisionsConfig", "LayaDecisionsConfig", "BespokeDecisionsConfig", + "EmpirioLabsDecisionsConfig", "EuJevDecisionsConfig", "OpenAIDecisionsConfig", "AzureDecisionsConfig", @@ -488,6 +491,7 @@ _UTILS_IMPORT_MAP: Final = { "supports_web_search": (".utils", "supports_web_search"), "supports_tool_search": (".utils", "supports_tool_search"), "supports_url_context": (".utils", "supports_url_context"), + "supports_continuation": (".utils", "supports_continuation"), "supports_response_schema": (".utils", "supports_response_schema"), "supports_parallel_function_calling": ( ".utils", @@ -738,6 +742,7 @@ _LLM_CONFIGS_IMPORT_MAP: Final = { "PerplexityDecisionsConfig": (".llms.perplexity.decisions.transformation", "PerplexityDecisionsConfig"), "NaceDecisionsConfig": (".llms.nace.decisions.transformation", "NaceDecisionsConfig"), "TypeSafeDecisionsConfig": (".llms.typesafe.decisions.transformation", "TypeSafeDecisionsConfig"), + "ParallelAIDecisionsConfig": (".llms.parallel_ai.decisions.transformation", "ParallelAIDecisionsConfig"), "OpenRouterDecisionsConfig": (".llms.openrouter.decisions.transformation", "OpenRouterDecisionsConfig"), "FireworksAIDecisionsConfig": (".llms.fireworks_ai.decisions.transformation", "FireworksAIDecisionsConfig"), "CloudflareDecisionsConfig": (".llms.cloudflare.decisions.transformation", "CloudflareDecisionsConfig"), @@ -755,6 +760,7 @@ _LLM_CONFIGS_IMPORT_MAP: Final = { "OllamaDecisionsConfig": (".llms.ollama.decisions.transformation", "OllamaDecisionsConfig"), "LayaDecisionsConfig": (".llms.laya.decisions.transformation", "LayaDecisionsConfig"), "BespokeDecisionsConfig": (".llms.bespoke.decisions.transformation", "BespokeDecisionsConfig"), + "EmpirioLabsDecisionsConfig": (".llms.empiriolabs.decisions.transformation", "EmpirioLabsDecisionsConfig"), "EuJevDecisionsConfig": (".llms.eu_jev.decisions.transformation", "EuJevDecisionsConfig"), "OpenAIDecisionsConfig": (".llms.openai.decisions.transformation", "OpenAIDecisionsConfig"), "AzureDecisionsConfig": (".llms.azure.decisions.transformation", "AzureDecisionsConfig"), diff --git a/litellm/_v2/AGENTS.md b/litellm/_v2/AGENTS.md deleted file mode 100644 index 55998814a7f..00000000000 --- a/litellm/_v2/AGENTS.md +++ /dev/null @@ -1,3 +0,0 @@ -Everything here is experimental and should not be documented - -Use this directory to explore alternative APIs where the Rust migration makes backward compatibility difficult. The gateway can use them for performance, but keep them behind the v2 flag to avoid breaking SDK users diff --git a/litellm/_v2/__init__.py b/litellm/_v2/__init__.py deleted file mode 100644 index 79156cf0f80..00000000000 --- a/litellm/_v2/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from litellm._v2.cache import Cache - -__all__ = ("Cache",) diff --git a/litellm/_v2/cache/AGENTS.md b/litellm/_v2/cache/AGENTS.md deleted file mode 100644 index 308419b7253..00000000000 --- a/litellm/_v2/cache/AGENTS.md +++ /dev/null @@ -1,11 +0,0 @@ -# Python v2 cache - -Keep `litellm._v2.cache.Cache` import-compatible when reorganizing this package. This package owns Python cache factories and the adapter between the existing `BaseCache` interface and `NativeCacheHandle` - -Construct native handles at this boundary and inject the adapter through the existing cache facade's `_backend` parameter. Keep the facade's `type`, namespace, and TTL consistent with the configured native backend - -Keep storage implementation in the Rust storage crates and response-cache policy in `litellm-cache-response` and core. Do not duplicate cache-key generation, freshness rules, response encoding, or inference orchestration here - -Preserve synchronous and asynchronous cache operations, including TTL forwarding and lifecycle methods. Validate Python values before passing them to typed native interfaces. Keep native extension imports lazy so importing the package does not require loading the extension - -Extend the existing v2 cache tests in `tests/test_litellm_rust/test_v2.py` for behavioral changes, following that directory's `AGENTS.md`. Test observable cache behavior rather than package layout or implementation structure diff --git a/litellm/_v2/cache/__init__.py b/litellm/_v2/cache/__init__.py deleted file mode 100644 index 5a3860b7a6e..00000000000 --- a/litellm/_v2/cache/__init__.py +++ /dev/null @@ -1,72 +0,0 @@ -from __future__ import annotations - -from collections.abc import Sequence -from typing import TYPE_CHECKING, Final - -from pydantic import TypeAdapter - -from litellm.caching.base_cache import BaseCache -from litellm.caching.caching import Cache as CacheFacade -from litellm.types.caching import LiteLLMCacheType - -if TYPE_CHECKING: - from litellm.rust_bridge._native import NativeCacheHandle - -_DURATION: Final[TypeAdapter[float | None]] = TypeAdapter(float | None) - - -class NativeBackend(BaseCache): - def __init__(self, handle: NativeCacheHandle) -> None: - self.native_handle = handle - - def get_cache(self, key: str, **kwargs: object) -> object: - return self.native_handle.get(key) - - async def async_get_cache(self, key: str, **kwargs: object) -> object: - return await self.native_handle.async_get(key) - - def set_cache(self, key: str, value: object, **kwargs: object) -> None: - self.native_handle.set(key, value, ttl=_DURATION.validate_python(kwargs.get("ttl"))) - - async def async_set_cache(self, key: str, value: object, **kwargs: object) -> None: - await self.native_handle.async_set(key, value, ttl=_DURATION.validate_python(kwargs.get("ttl"))) - - async def async_set_cache_pipeline(self, cache_list: Sequence[tuple[str, object]], **kwargs: object) -> None: - await self.native_handle.async_set_many(cache_list, ttl=_DURATION.validate_python(kwargs.get("ttl"))) - - async def batch_cache_write(self, key: str, value: object, **kwargs: object) -> None: - await self.async_set_cache(key, value, **kwargs) - - def flush_cache(self) -> None: - self.native_handle.flush() - - async def async_flush_cache(self) -> None: - await self.native_handle.async_flush() - - async def ping(self) -> bool: - return await self.native_handle.ping() - - async def disconnect(self) -> None: - await self.native_handle.disconnect() - - async def delete_cache_keys(self, keys: Sequence[str]) -> None: - await self.native_handle.delete(keys) - - async def test_connection(self) -> dict[str, str]: - return {"status": "success" if await self.ping() else "failed"} - - -class Cache: - @staticmethod - def memory(*, ttl: float = 600, capacity: int = 200, max_entry_bytes: int = 4194304) -> CacheFacade: - from litellm.rust_bridge._native import NativeCacheHandle - - handle: Final = NativeCacheHandle.memory(ttl=ttl, capacity=capacity, max_entry_bytes=max_entry_bytes) - return CacheFacade(type=LiteLLMCacheType.LOCAL, ttl=ttl, _backend=NativeBackend(handle)) - - @staticmethod - def redis(url: str, *, namespace: str, ttl: float = 600, max_entry_bytes: int = 4194304) -> CacheFacade: - from litellm.rust_bridge._native import NativeCacheHandle - - handle: Final = NativeCacheHandle.redis(url, namespace=namespace, ttl=ttl, max_entry_bytes=max_entry_bytes) - return CacheFacade(type=LiteLLMCacheType.REDIS, namespace=namespace, ttl=ttl, _backend=NativeBackend(handle)) diff --git a/litellm/accounting/__init__.py b/litellm/accounting/__init__.py index d4e56f61279..e69de29bb2d 100644 --- a/litellm/accounting/__init__.py +++ b/litellm/accounting/__init__.py @@ -1,62 +0,0 @@ -"""Public accounting contracts. Importing these values does not enable accounting.""" - -from litellm.accounting.measurements import measurements_for -from litellm.accounting.protocols import BudgetEnforcer, CostAggregator, CostCompiler, UsageMeter -from litellm.accounting.types import ( - AdmissionDecision, - AggregateQuery, - AggregateRow, - CostEvent, - DeliveryState, - DeliveryTarget, - Dimension, - DimensionFilter, - DimensionName, - EventKind, - Granularity, - InboundUsageEvent, - Measurement, - Metric, - MetricName, - Multiplier, - NamedCost, - OutboundUsageEvent, - Outcome, - PricedQuantity, - PricingSnapshot, - Rate, - Unpriced, - validate_aggregate_rows, -) - -__all__ = [ - "AdmissionDecision", - "AggregateQuery", - "AggregateRow", - "BudgetEnforcer", - "CostAggregator", - "CostCompiler", - "CostEvent", - "DeliveryState", - "DeliveryTarget", - "Dimension", - "DimensionFilter", - "DimensionName", - "EventKind", - "Granularity", - "InboundUsageEvent", - "Measurement", - "Metric", - "MetricName", - "Multiplier", - "NamedCost", - "OutboundUsageEvent", - "Outcome", - "PricedQuantity", - "PricingSnapshot", - "Rate", - "Unpriced", - "UsageMeter", - "measurements_for", - "validate_aggregate_rows", -] diff --git a/litellm/accounting/application.py b/litellm/accounting/application.py new file mode 100644 index 00000000000..1e5f23e2997 --- /dev/null +++ b/litellm/accounting/application.py @@ -0,0 +1,71 @@ +from typing import TYPE_CHECKING, Final + +from litellm.accounting.delivery_projection import entity_transactions, project_deliveries +from litellm.accounting.projection import Contribution +from litellm.proxy.db.budget_window_spend_writer import commit_window_spend_updates +from litellm.proxy.db.daily_spend_bulk_upsert import DAILY_SPEND_TABLES, build_bulk_upsert, merge_by_conflict_key +from litellm.proxy.db.db_span import db_span +from litellm.proxy.db.db_transaction_queue.window_spend_update_queue import WindowSpendTransaction +from litellm.proxy.db.model_usage_rollup import queue_model_usage_upsert +from litellm.repositories.accounting_delivery_repository import DeliveryProjection, LedgerTransaction + +if TYPE_CHECKING: + from litellm.proxy.db.db_spend_update_writer import DBSpendUpdateWriter + from litellm.proxy.utils import PrismaClient, ProxyLogging + + +async def apply_deliveries( + transaction: LedgerTransaction, + deliveries: tuple[DeliveryProjection, ...], + *, + prisma_client: "PrismaClient", + writer: "DBSpendUpdateWriter", + proxy_logging_obj: "ProxyLogging", +) -> tuple[Contribution, ...]: + from litellm.proxy.guardrails.usage_tracking import UsageUnitIncrement, UsageUnitKey, upsert_usage_unit_row + + contributions: Final = project_deliveries(deliveries) + await writer.apply_accounting_entities( + prisma_client, proxy_logging_obj, transaction, entity_transactions(contributions) + ) + for table in sorted(DAILY_SPEND_TABLES.values(), key=lambda item: item.name): + rows = tuple( + {**dict(item.key), **dict(item.values), **dict(item.increments)} + for item in contributions + if item.table == table.name + ) + merged = merge_by_conflict_key(table, rows) + for offset in range(0, len(merged), 100): + sql, params = build_bulk_upsert(table, merged[offset : offset + 100]) + async with db_span("upsert_daily_spend", table.name): + await transaction.execute_raw(sql, *params) + async with transaction.batch_() as batcher: + for item in contributions: + if item.table == "LiteLLM_DailyModelUsage": + queue_model_usage_upsert(batcher, dict(item.key), dict(item.increments)) + for item in contributions: + if item.table == "LiteLLM_DailyGuardrailUsageUnits": + key = dict(item.key) + counters = dict(item.increments) + await upsert_usage_unit_row( + prisma_client, + UsageUnitKey(key["guardrail_id"], key["date"], key["team_id"], key["api_key"], key["usage_unit"]), + UsageUnitIncrement(int(counters["units"]), float(counters["cost"]), int(counters["untracked_units"])), + outer_transaction=transaction, + ) + windows: Final = tuple(_window(item) for item in contributions if item.table == "LiteLLM_BudgetWindowSpend") + await commit_window_spend_updates(prisma_client, windows, outer_transaction=transaction) + return contributions + + +def _window(item: Contribution) -> WindowSpendTransaction: + key: Final = dict(item.key) + values: Final = dict(item.values) + return WindowSpendTransaction( + entity_type=key["entity_type"], + entity_id=key["entity_id"], + window_duration=key["window_duration"], + window_start=values["window_start"] or "", + spend=float(dict(item.increments)["spend"]), + started_at=values["started_at"], + ) diff --git a/litellm/accounting/delivery_projection.py b/litellm/accounting/delivery_projection.py new file mode 100644 index 00000000000..da63542d5b8 --- /dev/null +++ b/litellm/accounting/delivery_projection.py @@ -0,0 +1,78 @@ +from collections.abc import Iterable +from itertools import chain, groupby +from typing import TYPE_CHECKING, Final +from urllib.parse import quote + +from litellm.accounting.projection import Contribution, project +from litellm.repositories.accounting_delivery_repository import DeliveryProjection + + +def _destination(contribution: Contribution) -> tuple[str, tuple[tuple[str, str], ...], str]: + return ( + contribution.table, + contribution.key, + (dict(contribution.values).get("window_start") or "") + if contribution.table == "LiteLLM_BudgetWindowSpend" + else "", + ) + + +def _sum(contributions: tuple[Contribution, ...]) -> Contribution: + first: Final = contributions[0] + increments: Final = tuple( + (column, sum(dict(item.increments).get(column, 0) for item in contributions)) + for column in dict.fromkeys( + column for column, _ in chain.from_iterable(item.increments for item in contributions) + ) + ) + starts: Final = tuple( + value + for column, value in chain.from_iterable(item.values for item in contributions) + if column == "started_at" and value + ) + values: Final = tuple( + (column, min(starts) if column == "started_at" and starts else value) for column, value in first.values + ) + return Contribution(first.table, first.key, increments, values) + + +def project_deliveries(deliveries: Iterable[DeliveryProjection]) -> tuple[Contribution, ...]: + ordered: Final = sorted(chain.from_iterable(project(delivery.row) for delivery in deliveries), key=_destination) + return tuple(_sum(tuple(group)) for _, group in groupby(ordered, key=_destination)) + + +def entity_transactions(contributions: tuple[Contribution, ...]) -> "DBSpendUpdateTransactions": + return { + "user_list_transactions": dict(_entity_totals(contributions, "LiteLLM_UserTable")), + "end_user_list_transactions": dict(_entity_totals(contributions, "LiteLLM_EndUserTable")), + "key_list_transactions": dict(_entity_totals(contributions, "LiteLLM_VerificationToken")), + "team_list_transactions": dict(_entity_totals(contributions, "LiteLLM_TeamTable")), + "team_member_list_transactions": dict(_entity_totals(contributions, "LiteLLM_TeamMembership")), + "org_list_transactions": dict(_entity_totals(contributions, "LiteLLM_OrganizationTable")), + "org_member_list_transactions": dict(_entity_totals(contributions, "LiteLLM_OrganizationMembership")), + "project_list_transactions": dict(_entity_totals(contributions, "LiteLLM_ProjectTable")), + "tag_list_transactions": dict(_entity_totals(contributions, "LiteLLM_TagTable")), + "agent_list_transactions": dict(_entity_totals(contributions, "LiteLLM_AgentsTable")), + "model_access_group_list_transactions": dict( + _entity_totals(contributions, "LiteLLM_ModelAccessGroupBudgetTable") + ), + } + + +def _entity_totals(contributions: tuple[Contribution, ...], table: str) -> tuple[tuple[str, float], ...]: + return tuple( + (_entity_key(item), float(dict(item.increments)["spend"])) for item in contributions if item.table == table + ) + + +def _entity_key(item: Contribution) -> str: + fields: Final = dict(item.key) + if item.table == "LiteLLM_TeamMembership": + return f"team_id::{fields['team_id']}::user_id::{fields['user_id']}" + if item.table == "LiteLLM_OrganizationMembership": + return f"org_id::{quote(fields['organization_id'], safe='')}::user_id::{quote(fields['user_id'], safe='')}" + return item.key[0][1] + + +if TYPE_CHECKING: + from litellm.proxy._types import DBSpendUpdateTransactions diff --git a/litellm/accounting/measurements.py b/litellm/accounting/measurements.py deleted file mode 100644 index 83011a280da..00000000000 --- a/litellm/accounting/measurements.py +++ /dev/null @@ -1,13 +0,0 @@ -from typing import Final - -from litellm.accounting.types import CostEvent, InboundUsageEvent, Measurement, OutboundUsageEvent - - -def measurements_for(event: InboundUsageEvent | OutboundUsageEvent | CostEvent) -> tuple[Measurement, ...]: - """Return the complete contribution set for one event, ready for one apply call.""" - metrics: Final = event.charges if isinstance(event, CostEvent) else event.metrics - occurred_at: Final = event.occurred_at if isinstance(event, CostEvent) else event.started_at - return tuple( - Measurement(source_event_id=event.event_id, occurred_at=occurred_at, dimensions=event.dimensions, metric=metric) - for metric in metrics or () - ) diff --git a/litellm/accounting/metrics.py b/litellm/accounting/metrics.py new file mode 100644 index 00000000000..ade715d5d14 --- /dev/null +++ b/litellm/accounting/metrics.py @@ -0,0 +1,30 @@ +from typing import Final + +from prometheus_client import Gauge, Histogram + +from litellm.repositories.accounting_delivery_repository import DeliveryMetrics + +_PENDING: Final = Gauge("litellm_accounting_pending", "Pending SpendLogs deliveries", multiprocess_mode="livemax") +_PARKED: Final = Gauge("litellm_accounting_parked", "Parked SpendLogs deliveries", multiprocess_mode="livemax") +_OLDEST: Final = Gauge( + "litellm_accounting_oldest_pending_seconds", + "Age of the oldest pending SpendLogs delivery", + multiprocess_mode="livemax", +) +_BATCH_TIME: Final = Histogram("litellm_accounting_batch_seconds", "SpendLogs delivery worker batch time") +_BATCH_COUNT: Final = Gauge( + "litellm_accounting_batch_deliveries", "Retained batch deliveries", multiprocess_mode="livemax" +) +_TABLE_BYTES: Final = Gauge( + "litellm_accounting_delivery_table_bytes", "Delivery table size in bytes", multiprocess_mode="livemax" +) + + +def record_deliveries(metrics: DeliveryMetrics, seconds: float) -> None: + _PENDING.set(metrics.pending_count) + _PARKED.set(metrics.parked_count) + _OLDEST.set(max(0.0, metrics.oldest_pending_seconds)) + _BATCH_TIME.observe(seconds) + + _BATCH_COUNT.set(metrics.batch_count) + _TABLE_BYTES.set(metrics.table_bytes) diff --git a/litellm/accounting/projection.py b/litellm/accounting/projection.py new file mode 100644 index 00000000000..dd52b49f101 --- /dev/null +++ b/litellm/accounting/projection.py @@ -0,0 +1,326 @@ +from collections.abc import Iterator, Mapping +from dataclasses import dataclass, replace +from datetime import datetime, timezone +from itertools import chain +from types import MappingProxyType +from typing import Final + +from pydantic import TypeAdapter, ValidationError + +from litellm.constants import ( + BILLED_RETRY_ATTEMPT_METADATA_KEY, + INTERNAL_CALL_ORIGIN_METADATA_KEY, + MODEL_INSIGHTS_DEFAULT_TASK, + MODEL_INSIGHTS_TASK_TAG_PREFIX, +) +from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import GuardrailCostByUnitEntry +from litellm.proxy.db.daily_spend_bulk_upsert import DAILY_SPEND_TABLES, daily_spend_entity_ids +from litellm.proxy.db.model_insights_tasks import load_model_insight_tasks +from litellm.proxy.db.model_usage_rollup import date_from_start_time +from litellm.proxy.route_llm_request import ROUTE_ENDPOINT_MAPPING +from litellm.proxy.spend_tracking.compression_savings import extract_compression_saved_tokens +from litellm.proxy.spend_tracking.savings import extract_cache_creation_tokens, extract_cache_read_tokens +from litellm.types.utils import BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN + +_FIELDS: Final = TypeAdapter(dict[str, object]) +_STRINGS: Final = TypeAdapter(tuple[str, ...]) +_VALUES: Final = TypeAdapter(tuple[object, ...]) +_ROWS: Final = TypeAdapter(tuple[dict[str, object], ...]) +_TASK_TYPES: Final = frozenset(load_model_insight_tasks()) +_MAX_INDEXED_TEXT_BYTES: Final = 2000 +_MAX_COUNTER: Final = 2**40 + + +@dataclass(frozen=True, slots=True) +class Contribution: + table: str + key: tuple[tuple[str, str], ...] + increments: tuple[tuple[str, int | float], ...] + values: tuple[tuple[str, str | None], ...] = () + + +def _fields(value: object) -> Mapping[str, object]: + if isinstance(value, str): + return _FIELDS.validate_json(value) + return _FIELDS.validate_python(value) if isinstance(value, Mapping) else MappingProxyType({}) + + +def _text(value: object) -> str: + return "" if value is None else str(value) + + +def _number(value: object) -> int | float: + return value if isinstance(value, (int, float)) else 0 + + +def _tags(row: Mapping[str, object]) -> tuple[str, ...]: + value: Final = row.get("request_tags") + if value is None: + return () + parsed: Final = _VALUES.validate_json(value) if isinstance(value, str) else _VALUES.validate_python(value) + return tuple(tag for tag in parsed if isinstance(tag, str)) + + +def _date(row: Mapping[str, object]) -> str | None: + start: Final = row.get("startTime") + return date_from_start_time(start) if isinstance(start, (datetime, str)) else None + + +def _spend(table: str, key: tuple[tuple[str, str], ...], spend: float) -> Contribution: + return Contribution(table, key, (("spend", spend),)) + + +def _entity_contributions(row: Mapping[str, object], metadata: Mapping[str, object]) -> tuple[Contribution, ...]: + spend: Final = _number(row.get("spend")) + entities: Final = _fields(metadata.get("accounting_entities")) + identities: Final = ( + ("LiteLLM_VerificationToken", "token", entities.get("api_key")), + ("LiteLLM_UserTable", "user_id", entities.get("user")), + ("LiteLLM_UserTable", "user_id", entities.get("proxy_budget_name")), + ("LiteLLM_TeamTable", "team_id", entities.get("team_id")), + ("LiteLLM_OrganizationTable", "organization_id", entities.get("organization_id")), + ("LiteLLM_EndUserTable", "user_id", entities.get("end_user")), + ("LiteLLM_AgentsTable", "agent_id", entities.get("agent_id")), + ("LiteLLM_ProjectTable", "project_id", entities.get("project_id")), + ) + groups: Final = _STRINGS.validate_python(metadata.get("accounting_model_access_groups", ())) + return ( + *( + _spend(table, ((column, identity),), spend) + for table, column, identity in identities + if isinstance(identity, str) + ), + *(_spend("LiteLLM_TagTable", (("tag_name", tag),), spend) for tag in _tags(row) if tag), + *(_spend("LiteLLM_ModelAccessGroupBudgetTable", (("access_group_name", group),), spend) for group in groups), + *_membership_contributions(entities, spend), + ) + + +def _membership_contributions(row: Mapping[str, object], spend: float) -> tuple[Contribution, ...]: + user: Final = row.get("user") + if not isinstance(user, str): + return () + owners: Final = ( + ("LiteLLM_TeamMembership", "team_id", row.get("team_id")), + ("LiteLLM_OrganizationMembership", "organization_id", row.get("organization_id")), + ) + return tuple( + _spend(table, ((column, identity), ("user_id", user)), spend) + for table, column, identity in owners + if isinstance(identity, str) + ) + + +def _daily_counters(row: Mapping[str, object], metadata: Mapping[str, object]) -> tuple[tuple[str, int | float], ...]: + usage: Final = _fields(metadata.get("usage_object")) + savings: Final = _fields(metadata.get("accounting_savings")) + internal: Final = bool(metadata.get(INTERNAL_CALL_ORIGIN_METADATA_KEY)) + caller: Final = not internal and metadata.get(BILLED_RETRY_ATTEMPT_METADATA_KEY) is not True + success: Final = metadata.get("status") != "failure" + duration: Final = row.get("request_duration_ms") + timed: Final = not internal and success and isinstance(duration, int) and duration >= 0 + return ( + ("spend", _number(row.get("spend"))), + ("prompt_tokens", _number(row.get("prompt_tokens"))), + ("completion_tokens", _number(row.get("completion_tokens"))), + ("api_requests", int(caller)), + ("successful_requests", int(caller and success)), + ("failed_requests", int(caller and not success)), + ("cache_read_input_tokens", extract_cache_read_tokens(usage)), + ("cache_creation_input_tokens", extract_cache_creation_tokens(usage)), + ("compression_saved_tokens", extract_compression_saved_tokens(metadata)), + ("compression_savings_spend", _number(savings.get("compression"))), + ("prompt_caching_savings_spend", _number(savings.get("prompt_caching"))), + ("gateway_injected_caching_savings_spend", _number(savings.get("gateway_injected_caching"))), + ("autorouter_savings_spend", 0.0 if internal else _number(savings.get("autorouter"))), + ("total_response_time_ms", _number(duration) if timed else 0), + ("timed_requests", int(timed)), + ) + + +def _daily_contributions(row: Mapping[str, object], metadata: Mapping[str, object]) -> tuple[Contribution, ...]: + date: Final = _date(row) + if date is None or "api_key" not in row: + return () + if "mcp_namespaced_tool_name" not in row and ( + "model" not in row or "custom_llm_provider" not in row or "model_group" not in row + ): + return () + counters: Final = _daily_counters(row, metadata) + endpoint: Final = ROUTE_ENDPOINT_MAPPING.get(_text(row.get("call_type"))) + shared_key: Final = ( + ("date", date), + ("api_key", _text(row.get("api_key"))), + ("model", _text(row.get("model"))), + ("custom_llm_provider", _text(row.get("custom_llm_provider"))), + ("mcp_namespaced_tool_name", _text(row.get("mcp_namespaced_tool_name"))), + ("endpoint", _text(endpoint)), + ) + # The legacy daily organization writer uses the charged org argument, not + # SpendLogs' normalized empty-string identity for a request with no org. + daily_row: Final = {**row, "organization_id": _fields(metadata.get("accounting_entities")).get("organization_id")} + return tuple(_daily_rows(daily_row, shared_key, counters)) + + +def _daily_rows( + row: Mapping[str, object], + shared_key: tuple[tuple[str, str], ...], + counters: tuple[tuple[str, int | float], ...], +) -> Iterator[Contribution]: + for entity, table in DAILY_SPEND_TABLES.items(): + for identity in daily_spend_entity_ids(row, entity): + yield Contribution( + table.name, + ((table.entity_id_column, _text(identity)), *shared_key), + counters, + ( + ("model_group", None if row.get("model_group") is None else _text(row.get("model_group"))), + *((("request_id", _text(row.get("request_id"))),) if table.carries_request_id else ()), + ), + ) + + +def _window_contributions(row: Mapping[str, object], metadata: Mapping[str, object]) -> tuple[Contribution, ...]: + windows: Final = _ROWS.validate_python(metadata.get("accounting_windows", ())) + return tuple( + Contribution( + "LiteLLM_BudgetWindowSpend", + tuple((column, _text(window[column])) for column in ("entity_type", "entity_id", "window_duration")), + (("spend", _number(window.get("spend", row.get("spend")))),), + (("window_start", _text(window["window_start"])), ("started_at", _text(row.get("startTime")))), + ) + for window in windows + ) + + +def project(row: Mapping[str, object]) -> tuple[Contribution, ...]: + metadata: Final = _fields(row.get("metadata")) + contributions: Final = ( + *_entity_contributions(row, metadata), + *_daily_contributions(row, metadata), + *_window_contributions(row, metadata), + *_model_contributions(row, metadata), + *_guardrail_contributions(row, metadata), + ) + return tuple(_capped(contribution) for contribution in contributions if _indexable(contribution)) + + +def _indexable(contribution: Contribution) -> bool: + texts: Final = (value for _, value in (*contribution.key, *contribution.values) if value is not None) + return all(len(text.encode("utf-8", "surrogatepass")) <= _MAX_INDEXED_TEXT_BYTES for text in texts) + + +def _capped(contribution: Contribution) -> Contribution: + """Counters are summed into bigint columns in the charge's transaction, so one capped far below that range + can never overflow a day's total.""" + return replace( + contribution, + increments=tuple( + (name, max(-_MAX_COUNTER, min(_MAX_COUNTER, value)) if isinstance(value, int) else value) + for name, value in contribution.increments + ), + ) + + +def _model_contributions(row: Mapping[str, object], metadata: Mapping[str, object]) -> tuple[Contribution, ...]: + date: Final = _date(row) + origin: Final = metadata.get(INTERNAL_CALL_ORIGIN_METADATA_KEY) + if date is None or (origin and origin != BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN): + return () + model: Final = _text(row.get("model")) or "unknown" + caller: Final = not origin + success: Final = row.get("status") == "success" + return ( + Contribution( + "LiteLLM_DailyModelUsage", + ( + ("date", date), + ("model_group", _text(row.get("model_group")) or model), + ("model", model), + ("custom_llm_provider", _text(row.get("custom_llm_provider")) or "unknown"), + ("task_type", _model_task(row)), + ), + ( + ("spend", _number(row.get("spend"))), + ("prompt_tokens", _number(row.get("prompt_tokens"))), + ("completion_tokens", _number(row.get("completion_tokens"))), + ("request_count", int(caller)), + ("successful_requests", int(caller and success)), + ("failed_requests", int(caller and not success)), + ), + ), + ) + + +def _utc_date(row: Mapping[str, object]) -> str | None: + start: Final = row.get("startTime") + try: + parsed: Final = datetime.fromisoformat(start.replace("Z", "+00:00")) if isinstance(start, str) else start + except ValueError: + return None + if not isinstance(parsed, datetime): + return None + return ( + (parsed.replace(tzinfo=timezone.utc) if parsed.tzinfo is None else parsed) + .astimezone(timezone.utc) + .date() + .isoformat() + ) + + +def _guardrail_contributions(row: Mapping[str, object], metadata: Mapping[str, object]) -> tuple[Contribution, ...]: + date: Final = _utc_date(row) + info: Final = metadata.get("guardrail_information") or metadata.get("standard_logging_guardrail_information") + if not row.get("request_id") or date is None or not isinstance(info, list): + return () + return tuple(chain.from_iterable(_guardrail_entry(row, date, entry) for entry in _ROWS.validate_python(info))) + + +def _guardrail_entry(row: Mapping[str, object], date: str, entry: Mapping[str, object]) -> tuple[Contribution, ...]: + identity: Final = _text(entry.get("guardrail_id") or entry.get("guardrail_name")) + usage: Final = entry.get("guardrail_usage") + if not identity or not isinstance(usage, Mapping): + return () + costs: Final = _guardrail_unit_costs(entry) + return tuple( + _guardrail_unit(row, (identity, date, unit), units, None if costs is None else costs.get(unit)) + for unit, units in _fields(usage).items() + if isinstance(units, int) and not isinstance(units, bool) and units > 0 + ) + + +def _guardrail_unit( + row: Mapping[str, object], identity: tuple[str, str, str], units: int, cost: float | None +) -> Contribution: + guardrail_id, date, unit = identity + return Contribution( + "LiteLLM_DailyGuardrailUsageUnits", + ( + ("guardrail_id", guardrail_id), + ("date", date), + ("team_id", _text(row.get("team_id"))), + ("api_key", _text(row.get("api_key"))), + ("usage_unit", unit), + ), + (("units", units), ("cost", cost or 0.0), ("untracked_units", units if cost is None else 0)), + ) + + +def _model_task(row: Mapping[str, object]) -> str: + return next( + ( + task + for tag in _tags(row) + if tag.startswith(MODEL_INSIGHTS_TASK_TAG_PREFIX) + and (task := tag.removeprefix(MODEL_INSIGHTS_TASK_TAG_PREFIX)) in _TASK_TYPES + ), + MODEL_INSIGHTS_DEFAULT_TASK, + ) + + +def _guardrail_unit_costs(entry: Mapping[str, object]) -> Mapping[str, float | None] | None: + try: + cost: Final = GuardrailCostByUnitEntry.model_validate(entry) + except ValidationError: + return None + return None if cost.guardrail_cost_in_spend is False else cost.guardrail_cost_by_unit diff --git a/litellm/accounting/protocols.py b/litellm/accounting/protocols.py deleted file mode 100644 index 0208e37fbdf..00000000000 --- a/litellm/accounting/protocols.py +++ /dev/null @@ -1,85 +0,0 @@ -"""Contracts only. Implementations own persistence, pricing, projections and live budgets. - -The event row's ``payload`` is a private envelope versioned by the row's ``schema_version``. -Usage envelopes retain the public event and request-scoped pricing context: quantities with units, -model/provider, requested and billed tier/region when known, and per-request/deployment overrides. -These inputs, including the effective cost-map rates, must survive request teardown. -Cost envelopes retain the public CostEvent, including its required finalized pricing snapshot. -T5/T6 own envelope serialization; this public API does not introduce a second persisted schema. -""" - -from typing import Protocol - -from litellm.accounting.types import ( - AdmissionDecision, - AggregateQuery, - AggregateRow, - CostEvent, - Dimension, - InboundUsageEvent, - Measurement, - Metric, - OutboundUsageEvent, - Unpriced, -) - - -class UsageMeter(Protocol): - async def record(self, event: InboundUsageEvent | OutboundUsageEvent) -> None: - """Acknowledge commit, no-op identical IDs and reject conflicting content. - - Persist the event and its request-scoped pricing context before acknowledging. - HTTP acknowledgement is a separate policy. Unknown usage remains None. - """ - ... - - -class CostCompiler(Protocol): - async def compile(self, event: OutboundUsageEvent) -> CostEvent | Unpriced: - """Reuse the committed charge or finalize one charge and its delivery intent. - - Resolve captured request-scoped context and rates by event identity. - Persist the resolved inputs in the required snapshot. Replay - reuses the committed result and never consumes free allowance again. - Missing pricing is Unpriced, never an inferred zero. - """ - ... - - -class CostAggregator(Protocol): - async def apply(self, measurements: tuple[Measurement, ...]) -> None: - """Apply one source event's complete contribution set per target/version. - - Each target commits all contributions and its receipt atomically. A receipt - for the first metric must not suppress the rest. Usage need not wait for cost. - """ - ... - - async def query(self, query: AggregateQuery) -> tuple[AggregateRow, ...]: - """Return disjoint [start, end) rows per group using existing daily projections. - - Filters combine with AND, values within a filter with IN. DAY emits daily - buckets; None emits whole-interval totals. Reject unsupported metric/scope - combinations. Different groups may overlap, including non-additive tags. - """ - ... - - -class BudgetEnforcer(Protocol): - async def reserve( - self, reservation_id: str, dimensions: tuple[Dimension, ...], estimated: tuple[Metric, ...] - ) -> AdmissionDecision: - """Apply existing admission policies and estimates; duplicate IDs add no hold.""" - ... - - async def settle(self, reservation_id: str | None, cost_event: CostEvent) -> None: - """Settle the committed charge with atomic deduplication and hold mutation. - - Preserve scope/window attribution and retry unfinished settlement after - restart. SQL projection receipts do not provide live-counter atomicity. - """ - ... - - async def release(self, reservation_id: str) -> None: - """Idempotently release unused exposure at the request boundary, preserving charges.""" - ... diff --git a/litellm/accounting/snapshot.py b/litellm/accounting/snapshot.py new file mode 100644 index 00000000000..d5652f79ed0 --- /dev/null +++ b/litellm/accounting/snapshot.py @@ -0,0 +1,161 @@ +from collections.abc import Callable, Mapping, Sequence +from datetime import datetime +from typing import TYPE_CHECKING, Final + +from pydantic import TypeAdapter, ValidationError + +from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.safe_json_dumps import safe_json_structure +from litellm.proxy._types import SpendLogsPayload +from litellm.proxy.spend_tracking.compression_savings import extract_compression_saved_tokens +from litellm.proxy.spend_tracking.savings import SavingsSpend, compute_savings_spend, marks_gateway_injection + +if TYPE_CHECKING: + from litellm.router import Router + +_FIELDS: Final = TypeAdapter(dict[str, object]) + + +def _mapping(value: object) -> Mapping[str, object] | None: + return _FIELDS.validate_python(value) if isinstance(value, Mapping) else None + + +_METADATA_FIELDS: Final = frozenset( + { + "usage_object", + "status", + "guardrail_information", + "standard_logging_guardrail_information", + "compression_savings", + "internal_call_origin", + "billed_retry_attempt", + } +) + + +_ACCOUNTING_FIELDS: Final = frozenset( + { + "request_id", + "call_type", + "api_key", + "spend", + "prompt_tokens", + "completion_tokens", + "startTime", + "model", + "model_group", + "custom_llm_provider", + "user", + "team_id", + "organization_id", + "end_user", + "agent_id", + "request_tags", + "status", + "request_duration_ms", + "mcp_namespaced_tool_name", + } +) + + +def build_accounting_payload( + payload: SpendLogsPayload, + *, + entities: Mapping[str, str | None], + model_access_groups: Sequence[str], + windows: Sequence[Mapping[str, object]], + router: "Callable[[], Router | None]", +) -> Mapping[str, object]: + metadata: Final = _FIELDS.validate_json(payload["metadata"]) + savings: Final = _savings_or_zero(payload, metadata, router) + accounting_metadata: Final = { + **{key: _accounting_metadata_field(key, value) for key, value in metadata.items() if key in _METADATA_FIELDS}, + "accounting_entities": entities, + "accounting_savings": savings._asdict(), + "accounting_model_access_groups": model_access_groups, + "accounting_windows": windows, + } + return _FIELDS.validate_python( + safe_json_structure( + { + **{ + key: value.isoformat() if isinstance(value, datetime) else value + for key, value in payload.items() + if key in _ACCOUNTING_FIELDS + }, + "metadata": accounting_metadata, + }, + non_finite_as_null=True, + ) + ) + + +def _savings_or_zero( + payload: SpendLogsPayload, metadata: Mapping[str, object], router: "Callable[[], Router | None]" +) -> SavingsSpend: + """Savings are analytics computed from caller-supplied counts, so one that cannot be computed is stored as zero + rather than losing the charge it rides with.""" + try: + return _savings(payload, metadata, router) + except (ArithmeticError, ValueError, TypeError) as error: + verbose_proxy_logger.warning( + "Recording zero savings for request_id=%s, savings could not be computed: %s", payload["request_id"], error + ) + return SavingsSpend(compression=0.0, prompt_caching=0.0) + + +def _savings( + payload: SpendLogsPayload, metadata: Mapping[str, object], router: "Callable[[], Router | None]" +) -> SavingsSpend: + return compute_savings_spend( + model=payload["model"], + custom_llm_provider=payload["custom_llm_provider"], + compression_saved_tokens=extract_compression_saved_tokens(metadata), + gateway_injected_cache=marks_gateway_injection(metadata, payload["model_id"]), + routing_decision=_mapping(metadata.get("routing_decision")), + model_id=payload["model_id"], + llm_router=router, + usage_object=_mapping(metadata.get("usage_object")), + cost_breakdown=_mapping(metadata.get("cost_breakdown")), + recorded_autorouter_savings=metadata.get("autorouter_savings"), + recorded_autorouter_savings_estimate=_mapping(metadata.get("autorouter_savings_estimate")), + billed_at=payload["endTime"], + ) + + +_GUARDRAIL_ENTRIES: Final = TypeAdapter(tuple[dict[str, object], ...]) +_GUARDRAIL_METADATA_FIELDS: Final = frozenset({"guardrail_information", "standard_logging_guardrail_information"}) +_GUARDRAIL_ACCOUNTING_FIELDS: Final = frozenset( + { + "guardrail_id", + "guardrail_name", + "guardrail_provider", + "guardrail_usage", + "guardrail_cost_by_unit", + "guardrail_cost_in_spend", + } +) +_GUARDRAIL_RESPONSE: Final = TypeAdapter(dict[str, object]) + + +def _accounting_guardrail_entries(value: object) -> object: + try: + entries: Final = _GUARDRAIL_ENTRIES.validate_python((value,) if isinstance(value, dict) else value) + except ValidationError: + return None + return [_accounting_guardrail_entry(entry) for entry in entries] + + +def _accounting_guardrail_entry(entry: Mapping[str, object]) -> Mapping[str, object]: + kept: Final = {key: item for key, item in entry.items() if key in _GUARDRAIL_ACCOUNTING_FIELDS} + response: Final = entry.get("guardrail_response") + if not isinstance(response, dict) or "tokens_saved" not in response: + return kept + return { + **kept, + "guardrail_response": {"tokens_saved": _GUARDRAIL_RESPONSE.validate_python(response)["tokens_saved"]}, + } + + +def _accounting_metadata_field(key: str, value: object) -> object: + return _accounting_guardrail_entries(value) if key in _GUARDRAIL_METADATA_FIELDS else value diff --git a/litellm/accounting/types.py b/litellm/accounting/types.py deleted file mode 100644 index 2ee6f60f756..00000000000 --- a/litellm/accounting/types.py +++ /dev/null @@ -1,428 +0,0 @@ -"""Accounting values use UTC instants, decimal strings on the wire and USD charges.""" - -from collections.abc import Mapping -from datetime import datetime, timezone -from decimal import Decimal -from enum import Enum -from typing import Annotated, Final, Literal, TypeAlias - -from pydantic import AfterValidator, AwareDatetime, BaseModel, ConfigDict, Field, model_validator -from typing_extensions import Self - -from litellm.types.utils import CallTypes - -_CONFIG: Final = ConfigDict(frozen=True, extra="forbid", validate_default=True) -Identifier: TypeAlias = Annotated[str, Field(strict=True, min_length=1, pattern=r"\S")] -Quantity: TypeAlias = Annotated[Decimal, Field(strict=True, ge=0, allow_inf_nan=False)] - - -def _utc(value: datetime) -> datetime: - return value.astimezone(timezone.utc) - - -Instant: TypeAlias = Annotated[AwareDatetime, AfterValidator(_utc)] - - -class MetricName(str, Enum): - """Reasoning tokens are included in completion tokens; above-1hr writes are included in cache creation tokens.""" - - REQUESTS = "requests" - SUCCESSFUL_REQUESTS = "successful_requests" - FAILED_REQUESTS = "failed_requests" - PROMPT_TOKENS = "prompt_tokens" - COMPLETION_TOKENS = "completion_tokens" - REASONING_TOKENS = "reasoning_tokens" - TOTAL_TOKENS = "total_tokens" - CACHE_READ_INPUT_TOKENS = "cache_read_input_tokens" - CACHE_CREATION_INPUT_TOKENS = "cache_creation_input_tokens" - CACHE_CREATION_INPUT_TOKENS_ABOVE_1HR = "cache_creation_input_tokens_above_1hr" - SPEND = "spend" - - -class DimensionName(str, Enum): - KEY = "key" - USER = "user" - TEAM = "team" - ORGANIZATION = "organization" - END_USER = "end_user" - MODEL = "model" - MODEL_GROUP = "model_group" - DEPLOYMENT = "deployment" - PROVIDER = "provider" - TOOL = "tool" - AGENT = "agent" - PROJECT = "project" - MODEL_ACCESS_GROUP = "model_access_group" - API_BASE = "api_base" - SERVICE_TIER = "service_tier" - TAG = "tag" - - -class Outcome(str, Enum): - SUCCEEDED = "succeeded" - FAILED = "failed" - CANCELLED = "cancelled" - - -class Granularity(str, Enum): - DAY = "day" - - -class EventKind(str, Enum): - INBOUND_USAGE = "inbound_usage" - OUTBOUND_USAGE = "outbound_usage" - COST = "cost" - - -class DeliveryState(str, Enum): - PENDING = "pending" - APPLIED = "applied" - PARKED = "parked" - - -class DeliveryTarget(str, Enum): - """One member per existing table the projector writes; each is applied and receipted independently.""" - - KEY_SPEND = "LiteLLM_VerificationToken" - USER_SPEND = "LiteLLM_UserTable" - TEAM_SPEND = "LiteLLM_TeamTable" - TEAM_MEMBER_SPEND = "LiteLLM_TeamMembership" - ORGANIZATION_SPEND = "LiteLLM_OrganizationTable" - ORGANIZATION_MEMBER_SPEND = "LiteLLM_OrganizationMembership" - END_USER_SPEND = "LiteLLM_EndUserTable" - AGENT_SPEND = "LiteLLM_AgentsTable" - TAG_SPEND = "LiteLLM_TagTable" - PROJECT_SPEND = "LiteLLM_ProjectTable" - MODEL_ACCESS_GROUP_SPEND = "LiteLLM_ModelAccessGroupBudgetTable" - BUDGET_SPEND = "LiteLLM_BudgetTable" - BUDGET_WINDOW_SPEND = "LiteLLM_BudgetWindowSpend" - DAILY_USER_SPEND = "LiteLLM_DailyUserSpend" - DAILY_TEAM_SPEND = "LiteLLM_DailyTeamSpend" - DAILY_ORGANIZATION_SPEND = "LiteLLM_DailyOrganizationSpend" - DAILY_END_USER_SPEND = "LiteLLM_DailyEndUserSpend" - DAILY_AGENT_SPEND = "LiteLLM_DailyAgentSpend" - DAILY_TAG_SPEND = "LiteLLM_DailyTagSpend" - DAILY_MODEL_USAGE = "LiteLLM_DailyModelUsage" - DAILY_TOOL_SPEND = "LiteLLM_DailyToolSpend" - AUTOROUTER_DAILY_SPEND = "LiteLLM_AutoRouterDailySpend" - - -_SUBSET_PAIRS: Final = ( - (MetricName.REASONING_TOKENS, MetricName.COMPLETION_TOKENS), - (MetricName.CACHE_CREATION_INPUT_TOKENS_ABOVE_1HR, MetricName.CACHE_CREATION_INPUT_TOKENS), -) - - -def _check_subsets(values: Mapping[str, Decimal]) -> None: - for part, whole in _SUBSET_PAIRS: - if part.value in values and whole.value in values and values[part.value] > values[whole.value]: - raise ValueError(f"{part.value} cannot exceed {whole.value}") - - -class Metric(BaseModel): - model_config = _CONFIG - - name: MetricName - value: Quantity - unit: Literal["count", "USD"] = "count" - - @model_validator(mode="after") - def validate_unit(self) -> Self: - if (self.name is MetricName.SPEND) != (self.unit == "USD"): - raise ValueError("SPEND requires USD; usage metrics require count") - if self.unit == "count" and self.value != self.value.to_integral_value(): - raise ValueError("Count metrics require integral values") - return self - - -class Dimension(BaseModel): - model_config = _CONFIG - - name: DimensionName - value: Identifier - - -_REPEATABLE_DIMENSIONS: Final = frozenset({DimensionName.TAG, DimensionName.MODEL_ACCESS_GROUP}) - - -def _dimensions(values: tuple[Dimension, ...]) -> tuple[Dimension, ...]: - if len(frozenset(values)) != len(values): - raise ValueError("Duplicate dimension values") - single_names: Final = tuple(value.name for value in values if value.name not in _REPEATABLE_DIMENSIONS) - if len(frozenset(single_names)) != len(single_names): - raise ValueError("Only tag and model access group dimensions may have multiple values") - return values - - -Dimensions: TypeAlias = Annotated[tuple[Dimension, ...], AfterValidator(_dimensions)] -_CALLER_METRICS: Final = frozenset((MetricName.REQUESTS, MetricName.SUCCESSFUL_REQUESTS, MetricName.FAILED_REQUESTS)) - - -def _metrics(values: tuple[Metric, ...]) -> tuple[Metric, ...]: - if len(frozenset(value.name for value in values)) != len(values): - raise ValueError("Duplicate metric names") - return values - - -Metrics: TypeAlias = Annotated[tuple[Metric, ...], AfterValidator(_metrics)] - - -def _interval(start: datetime, end: datetime, *, allow_empty: bool = False) -> None: - if end < start or (end == start and not allow_empty): - raise ValueError("End must follow start") - - -class InboundUsageEvent(BaseModel): - model_config = _CONFIG - - event_id: Identifier - request_id: Identifier - call_type: CallTypes - started_at: Instant - ended_at: Instant - outcome: Outcome - dimensions: Dimensions - metrics: Metrics - - @model_validator(mode="after") - def validate_caller_activity(self) -> Self: - _interval(self.started_at, self.ended_at, allow_empty=True) - if any(metric.name not in _CALLER_METRICS for metric in self.metrics): - raise ValueError("Inbound events own only caller request metrics") - if not any(metric.name is MetricName.REQUESTS and metric.value == 1 for metric in self.metrics): - raise ValueError("Inbound events count exactly one caller request") - for metric in self.metrics: - if metric.name is MetricName.SUCCESSFUL_REQUESTS and metric.value != int(self.outcome is Outcome.SUCCEEDED): - raise ValueError("Successful request count must match outcome") - if metric.name is MetricName.FAILED_REQUESTS and metric.value != int(self.outcome is not Outcome.SUCCEEDED): - raise ValueError("Failed request count must match outcome") - return self - - -class OutboundUsageEvent(BaseModel): - model_config = _CONFIG - - event_id: Identifier - attempt_id: Identifier - request_id: Identifier | None - retry_of_attempt_id: Identifier | None - call_type: CallTypes - started_at: Instant - ended_at: Instant - outcome: Outcome - dimensions: Dimensions - metrics: Metrics | None - - @model_validator(mode="after") - def validate_attempt_usage(self) -> Self: - _interval(self.started_at, self.ended_at, allow_empty=True) - if self.retry_of_attempt_id == self.attempt_id: - raise ValueError("An attempt cannot retry itself") - if self.metrics is not None and any( - metric.name in _CALLER_METRICS or metric.name is MetricName.SPEND for metric in self.metrics - ): - raise ValueError("Outbound events own only attempt usage metrics") - if self.metrics is not None: - _check_subsets({metric.name.value: metric.value for metric in self.metrics}) - return self - - -PricingUnit: TypeAlias = Literal["token", "second", "character", "image", "request"] - - -class Rate(BaseModel): - model_config = _CONFIG - - measure: Identifier - unit: PricingUnit - usd_per_unit: Quantity - - -class PricedQuantity(BaseModel): - """A pricing input in its billing unit. Only seconds may be fractional.""" - - model_config = _CONFIG - - measure: Identifier - unit: PricingUnit - value: Quantity - - @model_validator(mode="after") - def validate_discrete_quantity(self) -> Self: - if self.unit != "second" and self.value != self.value.to_integral_value(): - raise ValueError("Discrete priced quantities require integral values") - return self - - -class Multiplier(BaseModel): - """A regional or tier factor applied on top of the priced key, e.g. data_residency=eu or vertex_location=us-east5.""" - - model_config = _CONFIG - - name: Identifier - value: Identifier - factor: Annotated[Decimal, Field(strict=True, gt=0, allow_inf_nan=False)] - - -class NamedCost(BaseModel): - """A free-form extra charge by name, e.g. azure_model_router_flat_cost.""" - - model_config = _CONFIG - - name: Identifier - amount: Quantity - - -class PricingSnapshot(BaseModel): - """Retained inputs and result of authoritative compilation, reproducible after cost-map rates change. - - Request-scoped inputs, overrides and effective rates come from the usage row's versioned payload. - Retries reuse the committed charge and snapshot. - Component names match ``CostBreakdown``: reasoning_cost is part of output_cost, not an additional charge. - Component sums and float tolerances belong to reconciliation, not this structural contract. - """ - - model_config = _CONFIG - - schema_version: Literal[1] = 1 - calculator_version: Identifier - model: Identifier - provider: Identifier | None - pricing_source: Literal["cost_map", "deployment", "per_request", "upstream_header"] - priced_model_key: Identifier - multipliers: tuple[Multiplier, ...] = () - rates: tuple[Rate, ...] = () - usage: tuple[PricedQuantity, ...] = () - input_cost: Quantity | None = None - output_cost: Quantity | None = None - cache_read_cost: Quantity | None = None - cache_creation_cost: Quantity | None = None - reasoning_cost: Quantity | None = None - tool_usage_cost: Quantity | None = None - guardrail_cost: Quantity | None = None - additional_costs: tuple[NamedCost, ...] = () - original_cost: Quantity | None = None - discount_percent: Quantity | None = None - discount_amount: Quantity | None = None - margin_percent: Quantity | None = None - margin_fixed_amount: Quantity | None = None - margin_total_amount: Quantity | None = None - upstream_reported_cost: Quantity | None = None - total_cost: Quantity - - @model_validator(mode="after") - def validate_snapshot(self) -> Self: - rate_keys: Final = frozenset((rate.measure, rate.unit) for rate in self.rates) - quantity_keys: Final = frozenset((quantity.measure, quantity.unit) for quantity in self.usage) - if len(rate_keys) != len(self.rates): - raise ValueError("Duplicate rate measures and units") - if len(quantity_keys) != len(self.usage): - raise ValueError("Duplicate priced quantity measures and units") - if not rate_keys.issubset(quantity_keys): - raise ValueError("Every rate requires one priced quantity with the same measure and unit") - if len(frozenset(cost.name for cost in self.additional_costs)) != len(self.additional_costs): - raise ValueError("Duplicate additional cost names") - if len(frozenset(multiplier.name for multiplier in self.multipliers)) != len(self.multipliers): - raise ValueError("Duplicate multiplier names") - _check_subsets({quantity.measure: quantity.value for quantity in self.usage if quantity.unit == "token"}) - return self - - -class CostEvent(BaseModel): - model_config = _CONFIG - - event_id: Identifier - usage_event_id: Identifier - occurred_at: Instant - dimensions: Dimensions - charges: Metrics - snapshot: PricingSnapshot - - @model_validator(mode="after") - def validate_charge(self) -> Self: - if len(self.charges) != 1 or self.charges[0].name is not MetricName.SPEND: - raise ValueError("A cost event requires one authoritative USD spend metric") - if self.event_id == self.usage_event_id: - raise ValueError("Cost and usage events require distinct identities") - if self.snapshot.total_cost != self.charges[0].value: - raise ValueError("Snapshot total must equal the authoritative spend") - return self - - -class Unpriced(BaseModel): - model_config = _CONFIG - - usage_event_id: Identifier - reason: Identifier - - -class Measurement(BaseModel): - model_config = _CONFIG - - source_event_id: Identifier - occurred_at: Instant - dimensions: Dimensions - metric: Metric - - -class DimensionFilter(BaseModel): - model_config = _CONFIG - - name: DimensionName - values: Annotated[tuple[Identifier, ...], Field(min_length=1)] - - -class AggregateQuery(BaseModel): - model_config = _CONFIG - - metric: MetricName - filters: tuple[DimensionFilter, ...] - group_by: tuple[DimensionName, ...] - start: Instant - end: Instant - granularity: Granularity | None - - @model_validator(mode="after") - def validate_query(self) -> Self: - _interval(self.start, self.end) - if len(frozenset(item.name for item in self.filters)) != len(self.filters): - raise ValueError("Use one IN filter per dimension; filters combine with AND") - if len(frozenset(self.group_by)) != len(self.group_by): - raise ValueError("Duplicate group-by dimensions") - if any( - (instant.hour, instant.minute, instant.second, instant.microsecond) != (0, 0, 0, 0) - for instant in (self.start, self.end) - ): - raise ValueError("Initial reporting queries require UTC day boundaries") - return self - - -class AggregateRow(BaseModel): - model_config = _CONFIG - - start: Instant - end: Instant - dimensions: Dimensions - value: Quantity - - @model_validator(mode="after") - def validate_bounds(self) -> Self: - _interval(self.start, self.end) - return self - - -def validate_aggregate_rows(rows: tuple[AggregateRow, ...]) -> tuple[AggregateRow, ...]: - """Validate [start, end) buckets per group; overlapping tag groups are not additive.""" - groups: Final = frozenset(frozenset(row.dimensions) for row in rows) - for group in groups: - ordered = sorted((row for row in rows if frozenset(row.dimensions) == group), key=lambda row: row.start) - if any(left.end > right.start for left, right in zip(ordered, ordered[1:])): - raise ValueError("Aggregate buckets overlap within a dimension group") - return rows - - -class AdmissionDecision(BaseModel): - model_config = _CONFIG - - allowed: bool - reason: Identifier | None = None diff --git a/litellm/accounting/worker.py b/litellm/accounting/worker.py new file mode 100644 index 00000000000..df71f2da31c --- /dev/null +++ b/litellm/accounting/worker.py @@ -0,0 +1,102 @@ +import os +import time +from typing import ( + TYPE_CHECKING, + Final, + Literal, + Protocol, + cast, # noqa: TID251 # generated Prisma transaction signatures cannot express the borrowed transaction protocol +) + +from litellm._logging import verbose_proxy_logger +from litellm.accounting.application import apply_deliveries +from litellm.accounting.metrics import record_deliveries +from litellm.accounting.projection import Contribution +from litellm.repositories.accounting_delivery_repository import ( + AccountingDeliveryRepository, + DeliveryProjection, + LedgerDatabase, + LedgerTransaction, +) +from litellm.types.integrations.slack_alerting import AlertType + +if TYPE_CHECKING: + from litellm.proxy.db.db_spend_update_writer import DBSpendUpdateWriter + from litellm.proxy.utils import PrismaClient, ProxyLogging + + +class _AccountingAlerts(Protocol): + async def alerting_handler( + self, message: str, level: Literal["Low", "Medium", "High"], alert_type: AlertType + ) -> None: ... + + +_JOB: Final = "accounting_delivery" + + +async def flush_accounting_deliveries( + writer: "DBSpendUpdateWriter", prisma_client: "PrismaClient", proxy_logging_obj: "ProxyLogging" +) -> None: + acquired: Final = await writer.pod_lock_manager.acquire_lock(cronjob_id=_JOB, allow_reentrant=False) + if acquired is False: + return + applied: tuple[Contribution, ...] = () # rebind-ok: keep committed contributions for cache invalidation + + async def apply(transaction: LedgerTransaction, deliveries: tuple[DeliveryProjection, ...]) -> None: + nonlocal applied + applied = await apply_deliveries( # rebind-ok: invalidate caches only after the outer transaction commits + transaction, deliveries, prisma_client=prisma_client, writer=writer, proxy_logging_obj=proxy_logging_obj + ) + + try: + database: Final = cast( # cast-ok: PrismaClient.tx owns writer routing and yields the generated transaction + LedgerDatabase, prisma_client + ) + repository: Final = AccountingDeliveryRepository(database) + started: Final = time.monotonic() + batch_size: Final = int(os.environ.get("LITELLM_ACCOUNTING_DELIVERY_BATCH_SIZE", "10000")) + + async def run_batch(*, retry_only: bool) -> bool: + result: Final = await repository.apply_pending(apply, batch_size=batch_size, retry_only=retry_only) + if result.applied: + await writer.invalidate_accounting_entities(applied, proxy_logging_obj) + if result.parked: + verbose_proxy_logger.error( + "Accounting delivery parked %d requests after isolated failures", len(result.parked) + ) + await _alert( + proxy_logging_obj, + message=f"Accounting delivery parked {len(result.parked)} requests. Included spend totals require repair.", + ) + return bool(result.applied or result.failed) + + await run_batch(retry_only=False) + retry_deadline: Final = time.monotonic() + 5 + for _ in range(batch_size): + if time.monotonic() >= retry_deadline or not await run_batch(retry_only=True): + break + await repository.cleanup_applied( + retention_days=int(os.environ.get("LITELLM_ACCOUNTING_DELIVERY_RETENTION_DAYS", "1")), + batch_size=batch_size * 2, + ) + metrics: Final = await repository.metrics() + record_deliveries(metrics, time.monotonic() - started) + if metrics.batch_count >= int( + os.environ.get("LITELLM_ACCOUNTING_BATCH_DELIVERY_ALERT_COUNT", "1000000") + ) or metrics.table_bytes >= int(os.environ.get("LITELLM_ACCOUNTING_DELIVERY_ALERT_BYTES", "1073741824")): + await _alert( + proxy_logging_obj, + message=f"Accounting delivery storage requires review. Retained batches={metrics.batch_count}, table bytes={metrics.table_bytes}.", + ) + if metrics.oldest_pending_seconds > 300: + await _alert( + proxy_logging_obj, + message=f"Accounting deliveries are delayed. Pending={metrics.pending_count}, oldest={metrics.oldest_pending_seconds:.0f}s.", + ) + finally: + if acquired: + await writer.pod_lock_manager.release_lock(cronjob_id=_JOB) + + +async def _alert(alerts: _AccountingAlerts, message: str) -> None: + await alerts.alerting_handler(message=message, level="High", alert_type=AlertType.failed_tracking_spend) diff --git a/litellm/anthropic_beta_headers_config.json b/litellm/anthropic_beta_headers_config.json index 253074b0e1f..bdfddb48522 100644 --- a/litellm/anthropic_beta_headers_config.json +++ b/litellm/anthropic_beta_headers_config.json @@ -37,7 +37,47 @@ "mid-conversation-output-config-2026-07-01": "mid-conversation-output-config-2026-07-01", "thinking-display-updates-2026-08-18": "thinking-display-updates-2026-08-18", "mid-conversation-tool-changes-2026-07-01": "mid-conversation-tool-changes-2026-07-01", - "inline-tools-2026-09-15": "inline-tools-2026-09-15" + "inline-tools-2026-09-15": "inline-tools-2026-09-15", + "agent-memory-2026-07-22": null, + "analytics-usage-cost-2026-08-24": "analytics-usage-cost-2026-08-24", + "cache-diagnosis-2026-04-07": "cache-diagnosis-2026-04-07", + "ce-plugins-2026-09-01": "ce-plugins-2026-09-01", + "ce-user-management-2026-07-13": "ce-user-management-2026-07-13", + "claude-code-20250219": "claude-code-20250219", + "code-execution-2025-05-22": "code-execution-2025-05-22", + "computer-use-2024-10-22": "computer-use-2024-10-22", + "dev-full-thinking-2025-05-14": null, + "dreaming-2026-04-21": "dreaming-2026-04-21", + "experimental-claude-tag-2026-10-21": "experimental-claude-tag-2026-10-21", + "extended-cache-ttl-2025-04-11": "extended-cache-ttl-2025-04-11", + "fallback-credit-2026-06-01": "fallback-credit-2026-06-01", + "fallback-credit-2026-07-01": "fallback-credit-2026-07-01", + "managed-agents-2026-04-01": "managed-agents-2026-04-01", + "mcp-client-2026-09-15": "mcp-client-2026-09-15", + "mcp-tunnels-2026-06-22": "mcp-tunnels-2026-06-22", + "message-batches-2024-09-24": "message-batches-2024-09-24", + "message-threads-2026-08-12": "message-threads-2026-08-12", + "mid-conversation-system-clear-at-2026-08-21": "mid-conversation-system-clear-at-2026-08-21", + "model-context-window-exceeded-2025-08-26": "model-context-window-exceeded-2025-08-26", + "output-300k-2026-03-24": "output-300k-2026-03-24", + "pdfs-2024-09-25": "pdfs-2024-09-25", + "prompt-caching-2024-07-31": "prompt-caching-2024-07-31", + "server-side-fallback-2026-06-01": "server-side-fallback-2026-06-01", + "server-side-fallback-2026-07-01": "server-side-fallback-2026-07-01", + "spend-limit-reads-2026-09-26": "spend-limit-reads-2026-09-26", + "task-budgets-2026-03-13": "task-budgets-2026-03-13", + "telemetry-destinations-2026-08-11": "telemetry-destinations-2026-08-11", + "thinking-token-count-2026-05-13": "thinking-token-count-2026-05-13", + "token-counting-2024-11-01": "token-counting-2024-11-01", + "tool-examples-2025-10-29": "tool-examples-2025-10-29", + "tool-search-tool-2025-10-19": "tool-search-tool-2025-10-19", + "user-profiles-2026-03-24": "user-profiles-2026-03-24", + "user-profiles-2026-08-18": "user-profiles-2026-08-18", + "user-profiles-2026-09-04": "user-profiles-2026-09-04", + "webhooks-2026-10-07": "webhooks-2026-10-07", + "afk-mode-2026-01-31": "afk-mode-2026-01-31", + "redact-thinking-2026-02-12": "redact-thinking-2026-02-12", + "structured-outputs-2025-12-15": "structured-outputs-2025-12-15" }, "azure_ai": { "advisor-tool-2026-03-01": null, @@ -45,23 +85,21 @@ "bash_20241022": null, "bash_20250124": null, "code-execution-2025-08-25": "code-execution-2025-08-25", - "compact-2026-01-12": null, - "compact-2026-09-04": "compact-2026-09-04", + "compact-2026-01-12": "compact-2026-01-12", "computer-use-2025-01-24": "computer-use-2025-01-24", "computer-use-2025-11-24": "computer-use-2025-11-24", "context-1m-2025-08-07": "context-1m-2025-08-07", "context-management-2025-06-27": "context-management-2025-06-27", "dangerous-tool-use-2026-09-03": "dangerous-tool-use-2026-09-03", "effort-2025-11-24": "effort-2025-11-24", - "fast-mode-2026-02-01": null, + "fast-mode-2026-02-01": "fast-mode-2026-02-01", "files-api-2025-04-14": "files-api-2025-04-14", - "fine-grained-tool-streaming-2025-05-14": null, + "fine-grained-tool-streaming-2025-05-14": "fine-grained-tool-streaming-2025-05-14", "interleaved-thinking-2025-05-14": "interleaved-thinking-2025-05-14", "mcp-client-2025-11-20": "mcp-client-2025-11-20", "mcp-client-2025-04-04": "mcp-client-2025-04-04", "mcp-servers-2025-12-04": null, - "mid-conversation-tool-changes-2026-07-01": "mid-conversation-tool-changes-2026-07-01", - "output-128k-2025-02-19": null, + "output-128k-2025-02-19": "output-128k-2025-02-19", "structured-output-2024-03-01": null, "per-turn-control-2026-07-01": "per-turn-control-2026-07-01", "prompt-caching-scope-2026-01-05": "prompt-caching-scope-2026-01-05", @@ -71,9 +109,54 @@ "text_editor_20250124": null, "thinking-binding-controls-2026-08-01": "thinking-binding-controls-2026-08-01", "thinking-display-updates-2026-08-18": "thinking-display-updates-2026-08-18", - "token-efficient-tools-2025-02-19": null, + "token-efficient-tools-2025-02-19": "token-efficient-tools-2025-02-19", "web-fetch-2025-09-10": "web-fetch-2025-09-10", - "web-search-2025-03-05": "web-search-2025-03-05" + "web-search-2025-03-05": "web-search-2025-03-05", + "agent-memory-2026-07-22": null, + "analytics-usage-cost-2026-08-24": "analytics-usage-cost-2026-08-24", + "cache-diagnosis-2026-04-07": "cache-diagnosis-2026-04-07", + "ce-plugins-2026-09-01": "ce-plugins-2026-09-01", + "ce-user-management-2026-07-13": "ce-user-management-2026-07-13", + "claude-code-20250219": "claude-code-20250219", + "code-execution-2025-05-22": "code-execution-2025-05-22", + "compact-2026-09-04": "compact-2026-09-04", + "computer-use-2024-10-22": "computer-use-2024-10-22", + "dev-full-thinking-2025-05-14": null, + "dreaming-2026-04-21": "dreaming-2026-04-21", + "experimental-claude-tag-2026-10-21": "experimental-claude-tag-2026-10-21", + "extended-cache-ttl-2025-04-11": "extended-cache-ttl-2025-04-11", + "fallback-credit-2026-06-01": "fallback-credit-2026-06-01", + "fallback-credit-2026-07-01": "fallback-credit-2026-07-01", + "inline-tools-2026-09-15": "inline-tools-2026-09-15", + "managed-agents-2026-04-01": "managed-agents-2026-04-01", + "mcp-client-2026-09-15": "mcp-client-2026-09-15", + "mcp-tunnels-2026-06-22": "mcp-tunnels-2026-06-22", + "message-batches-2024-09-24": "message-batches-2024-09-24", + "message-threads-2026-08-12": "message-threads-2026-08-12", + "mid-conversation-output-config-2026-07-01": "mid-conversation-output-config-2026-07-01", + "mid-conversation-system-clear-at-2026-08-21": "mid-conversation-system-clear-at-2026-08-21", + "mid-conversation-tool-changes-2026-07-01": "mid-conversation-tool-changes-2026-07-01", + "model-context-window-exceeded-2025-08-26": "model-context-window-exceeded-2025-08-26", + "oauth-2025-04-20": "oauth-2025-04-20", + "output-300k-2026-03-24": "output-300k-2026-03-24", + "pdfs-2024-09-25": "pdfs-2024-09-25", + "prompt-caching-2024-07-31": "prompt-caching-2024-07-31", + "server-side-fallback-2026-06-01": "server-side-fallback-2026-06-01", + "server-side-fallback-2026-07-01": "server-side-fallback-2026-07-01", + "spend-limit-reads-2026-09-26": "spend-limit-reads-2026-09-26", + "task-budgets-2026-03-13": "task-budgets-2026-03-13", + "telemetry-destinations-2026-08-11": "telemetry-destinations-2026-08-11", + "thinking-token-count-2026-05-13": "thinking-token-count-2026-05-13", + "token-counting-2024-11-01": "token-counting-2024-11-01", + "tool-examples-2025-10-29": "tool-examples-2025-10-29", + "tool-search-tool-2025-10-19": "tool-search-tool-2025-10-19", + "user-profiles-2026-03-24": "user-profiles-2026-03-24", + "user-profiles-2026-08-18": "user-profiles-2026-08-18", + "user-profiles-2026-09-04": "user-profiles-2026-09-04", + "webhooks-2026-10-07": "webhooks-2026-10-07", + "afk-mode-2026-01-31": "afk-mode-2026-01-31", + "redact-thinking-2026-02-12": "redact-thinking-2026-02-12", + "structured-outputs-2025-12-15": "structured-outputs-2025-12-15" }, "bedrock_converse": { "advisor-tool-2026-03-01": null, @@ -196,34 +279,92 @@ "context-1m-2025-08-07": "context-1m-2025-08-07", "context-management-2025-06-27": "context-management-2025-06-27", "dangerous-tool-use-2026-09-03": "dangerous-tool-use-2026-09-03", - "effort-2025-11-24": null, + "effort-2025-11-24": "effort-2025-11-24", "fast-mode-2026-02-01": null, "files-api-2025-04-14": null, - "fine-grained-tool-streaming-2025-05-14": null, + "fine-grained-tool-streaming-2025-05-14": "fine-grained-tool-streaming-2025-05-14", "interleaved-thinking-2025-05-14": "interleaved-thinking-2025-05-14", "mcp-client-2025-11-20": null, "mcp-client-2025-04-04": null, "mcp-servers-2025-12-04": null, - "mid-conversation-tool-changes-2026-07-01": "mid-conversation-tool-changes-2026-07-01", - "output-128k-2025-02-19": null, + "output-128k-2025-02-19": "output-128k-2025-02-19", "structured-output-2024-03-01": null, "per-turn-control-2026-07-01": "per-turn-control-2026-07-01", "prompt-caching-scope-2026-01-05": null, "skills-2025-10-02": null, - "structured-outputs-2025-11-13": null, + "structured-outputs-2025-11-13": "structured-outputs-2025-11-13", "text_editor_20241022": null, "text_editor_20250124": null, "thinking-binding-controls-2026-08-01": "thinking-binding-controls-2026-08-01", "thinking-display-updates-2026-08-18": "thinking-display-updates-2026-08-18", - "token-efficient-tools-2025-02-19": null, + "token-efficient-tools-2025-02-19": "token-efficient-tools-2025-02-19", "tool-search-tool-2025-10-19": "tool-search-tool-2025-10-19", "web-fetch-2025-09-10": null, "web-search-2025-03-05": "web-search-2025-03-05", - "inline-tools-2026-09-15": "inline-tools-2026-09-15" + "inline-tools-2026-09-15": "inline-tools-2026-09-15", + "agent-memory-2026-07-22": null, + "analytics-usage-cost-2026-08-24": null, + "cache-diagnosis-2026-04-07": null, + "ce-plugins-2026-09-01": null, + "ce-user-management-2026-07-13": null, + "claude-code-20250219": "claude-code-20250219", + "code-execution-2025-05-22": null, + "compact-2026-09-04": null, + "computer-use-2024-10-22": null, + "dev-full-thinking-2025-05-14": null, + "dreaming-2026-04-21": null, + "experimental-claude-tag-2026-10-21": null, + "extended-cache-ttl-2025-04-11": null, + "fallback-credit-2026-06-01": "fallback-credit-2026-06-01", + "fallback-credit-2026-07-01": "fallback-credit-2026-07-01", + "managed-agents-2026-04-01": null, + "mcp-client-2026-09-15": null, + "mcp-tunnels-2026-06-22": null, + "message-batches-2024-09-24": null, + "message-threads-2026-08-12": null, + "mid-conversation-output-config-2026-07-01": "mid-conversation-output-config-2026-07-01", + "mid-conversation-system-clear-at-2026-08-21": "mid-conversation-system-clear-at-2026-08-21", + "mid-conversation-tool-changes-2026-07-01": "mid-conversation-tool-changes-2026-07-01", + "model-context-window-exceeded-2025-08-26": "model-context-window-exceeded-2025-08-26", + "oauth-2025-04-20": null, + "output-300k-2026-03-24": null, + "pdfs-2024-09-25": "pdfs-2024-09-25", + "prompt-caching-2024-07-31": null, + "server-side-fallback-2026-06-01": "server-side-fallback-2026-06-01", + "server-side-fallback-2026-07-01": null, + "spend-limit-reads-2026-09-26": null, + "task-budgets-2026-03-13": "task-budgets-2026-03-13", + "telemetry-destinations-2026-08-11": null, + "thinking-token-count-2026-05-13": "thinking-token-count-2026-05-13", + "token-counting-2024-11-01": "token-counting-2024-11-01", + "tool-examples-2025-10-29": "tool-examples-2025-10-29", + "user-profiles-2026-03-24": null, + "user-profiles-2026-08-18": null, + "user-profiles-2026-09-04": null, + "webhooks-2026-10-07": null, + "afk-mode-2026-01-31": "afk-mode-2026-01-31", + "redact-thinking-2026-02-12": null, + "structured-outputs-2025-12-15": "structured-outputs-2025-12-15" }, "vertex_ai_header_only": { + "ce-plugins-2026-09-01": "ce-plugins-2026-09-01", + "ce-user-management-2026-07-13": "ce-user-management-2026-07-13", "compact-2026-09-04": "compact-2026-09-04", - "inline-tools-2026-09-15": "inline-tools-2026-09-15" + "dreaming-2026-04-21": "dreaming-2026-04-21", + "experimental-claude-tag-2026-10-21": "experimental-claude-tag-2026-10-21", + "extended-cache-ttl-2025-04-11": "extended-cache-ttl-2025-04-11", + "inline-tools-2026-09-15": "inline-tools-2026-09-15", + "managed-agents-2026-04-01": "managed-agents-2026-04-01", + "mcp-tunnels-2026-06-22": "mcp-tunnels-2026-06-22", + "oauth-2025-04-20": "oauth-2025-04-20", + "prompt-caching-2024-07-31": "prompt-caching-2024-07-31", + "prompt-caching-scope-2026-01-05": "prompt-caching-scope-2026-01-05", + "redact-thinking-2026-02-12": "redact-thinking-2026-02-12", + "spend-limit-reads-2026-09-26": "spend-limit-reads-2026-09-26", + "telemetry-destinations-2026-08-11": "telemetry-destinations-2026-08-11", + "user-profiles-2026-03-24": "user-profiles-2026-03-24", + "user-profiles-2026-08-18": "user-profiles-2026-08-18", + "user-profiles-2026-09-04": "user-profiles-2026-09-04" }, "databricks": { "advisor-tool-2026-03-01": null, diff --git a/litellm/anthropic_beta_headers_manager.py b/litellm/anthropic_beta_headers_manager.py index be2ff07e088..c03f7cda990 100644 --- a/litellm/anthropic_beta_headers_manager.py +++ b/litellm/anthropic_beta_headers_manager.py @@ -31,6 +31,7 @@ from concurrent.futures import ThreadPoolExecutor from functools import cache from importlib.resources import files from typing import Final, Literal, TypeAlias +from urllib.parse import urlparse import httpx from pydantic import TypeAdapter @@ -48,6 +49,7 @@ _BETA_HEADERS_CONFIG_ADAPTER: Final = TypeAdapter(BetaHeadersConfig) _DECODED_JSON: Final = TypeAdapter(object) BetaPlacement: TypeAlias = Literal["header", "body"] +UnlistedBetas: TypeAlias = Literal["drop", "forward"] _HEADER_ONLY_COLUMN_SUFFIX: Final = "_header_only" @@ -196,7 +198,6 @@ def _load_beta_headers_config() -> dict: if _BETA_HEADERS_CONFIG is not None: return _BETA_HEADERS_CONFIG - # Get the URL from environment or use default from litellm import anthropic_beta_headers_url _BETA_HEADERS_CONFIG = get_beta_headers_config(url=anthropic_beta_headers_url) @@ -280,12 +281,13 @@ def filter_and_transform_beta_headers( beta_headers: list[str], provider: str, placement: BetaPlacement = "header", + unlisted: UnlistedBetas = "drop", ) -> list[str]: """ Filter and transform beta headers based on provider's mapping configuration. This function: - 1. Only allows headers that are present in the provider's mapping keys + 1. Only allows headers that are present in the provider's mapping keys, unless ``unlisted`` is "forward" 2. Filters out headers with null values (unsupported) 3. Maps headers to provider-specific names (e.g., advanced-tool-use -> tool-search-tool) @@ -293,6 +295,7 @@ def filter_and_transform_beta_headers( beta_headers: List of Anthropic beta header values provider: Provider name (e.g., "anthropic", "bedrock", "vertex_ai") placement: Whether the betas travel as the anthropic-beta header or the anthropic_beta body field + unlisted: Whether a beta missing from the mapping is dropped or forwarded as sent Returns: List of filtered and transformed beta headers for the provider @@ -307,6 +310,10 @@ def filter_and_transform_beta_headers( for header in beta_headers: header = header.strip() + if header not in provider_mapping and unlisted == "forward": + filtered_headers.add(header) + continue + # Check if header is in the mapping if header not in provider_mapping: verbose_logger.debug( @@ -388,9 +395,38 @@ def get_provider_beta_header( return provider_mapping[anthropic_beta_header] +FOUNDRY_API_BASE_HOST_SUFFIXES: Final[tuple[str, ...]] = ( + "services.ai.azure.com", + "openai.azure.com", + "cognitiveservices.azure.com", +) + + +def is_foundry_api_base(api_base: str | None) -> bool: + """Whether ``api_base`` points at an Azure AI Foundry host, where Claude is served by Microsoft.""" + if not api_base: + return False + host: Final = urlparse(api_base if "://" in api_base else f"https://{api_base}").hostname or "" + return any(host == suffix or host.endswith(f".{suffix}") for suffix in FOUNDRY_API_BASE_HOST_SUFFIXES) + + +def resolve_beta_provider(provider: str, api_base: str | None = None) -> str: + """ + Pick the beta allowlist row for one deployment, not one provider string. + + An ``anthropic`` deployment whose ``api_base`` is a Foundry host is served by Microsoft and + gets the ``azure_ai`` row, since Foundry accepts a different set of betas than api.anthropic.com. + """ + if provider == "anthropic" and is_foundry_api_base(api_base): + return "azure_ai" + return provider + + def update_headers_with_filtered_beta( headers: dict, provider: str, + api_base: str | None = None, + unlisted: UnlistedBetas = "drop", ) -> dict: """ Update headers dict by filtering and transforming anthropic-beta header values. @@ -399,6 +435,8 @@ def update_headers_with_filtered_beta( Args: headers: Request headers dict (will be modified in place) provider: Provider name + api_base: Deployment api_base, used to pick the allowlist row (Foundry hosts use ``azure_ai``) + unlisted: Whether a beta missing from the row is dropped or forwarded as sent Returns: Updated headers dict @@ -413,7 +451,8 @@ def update_headers_with_filtered_beta( # Filter and transform based on provider filtered_beta_values: Final = filter_and_transform_beta_headers( beta_headers=beta_values, - provider=provider, + provider=resolve_beta_provider(provider, api_base), + unlisted=unlisted, ) # Update or remove the header @@ -430,6 +469,7 @@ def update_request_with_filtered_beta( headers: dict, request_data: dict, provider: str, + api_base: str | None = None, ) -> tuple[dict[str, str], dict[str, object]]: """ Update both headers and request body beta fields based on provider support. @@ -439,11 +479,12 @@ def update_request_with_filtered_beta( headers: Request headers dict (will be modified in place) request_data: Request body dict (will be modified in place) provider: Provider name + api_base: Deployment api_base, used to pick the allowlist row (Foundry hosts use ``azure_ai``) Returns: Tuple of (updated headers, updated request_data) """ - headers = update_headers_with_filtered_beta(headers=headers, provider=provider) + headers = update_headers_with_filtered_beta(headers=headers, provider=provider, api_base=api_base) existing_body_betas: Final = request_data.get("anthropic_beta") if not existing_body_betas: @@ -451,7 +492,7 @@ def update_request_with_filtered_beta( filtered_body_betas: Final = filter_and_transform_beta_headers( beta_headers=existing_body_betas, - provider=provider, + provider=resolve_beta_provider(provider, api_base), placement="body", ) diff --git a/litellm/anthropic_interface/exceptions/exception_mapping_utils.py b/litellm/anthropic_interface/exceptions/exception_mapping_utils.py index d8198e41239..b4c95fafff3 100644 --- a/litellm/anthropic_interface/exceptions/exception_mapping_utils.py +++ b/litellm/anthropic_interface/exceptions/exception_mapping_utils.py @@ -16,7 +16,7 @@ from .exceptions import AnthropicErrorDetail, AnthropicErrorResponse, AnthropicE _PARSED_ERROR_BODY: Final = TypeAdapter(object) # HTTP status code -> Anthropic error type -# Source: https://docs.anthropic.com/en/api/errors +# Source: https://platform.claude.com/docs/en/api/errors ANTHROPIC_ERROR_TYPE_MAP: Final[dict[int, AnthropicErrorType]] = { 400: "invalid_request_error", 401: "authentication_error", @@ -46,6 +46,7 @@ class AnthropicExceptionMapping: status_code: int, message: str, request_id: str | None = None, + error_type: AnthropicErrorType | None = None, ) -> AnthropicErrorResponse: """ Create an Anthropic-formatted error response dict. @@ -57,12 +58,10 @@ class AnthropicExceptionMapping: "request_id": "req_..." } """ - error_type: Final = AnthropicExceptionMapping.get_error_type(status_code) - response: Final[AnthropicErrorResponse] = { "type": "error", "error": { - "type": error_type, + "type": error_type or AnthropicExceptionMapping.get_error_type(status_code), "message": message, }, } @@ -131,6 +130,7 @@ class AnthropicExceptionMapping: status_code: int, raw_message: str, request_id: str | None = None, + error_type: AnthropicErrorType | None = None, ) -> AnthropicErrorResponse: """ Transform an error message to Anthropic format. @@ -144,6 +144,7 @@ class AnthropicExceptionMapping: status_code: HTTP status code raw_message: Raw error message (may be JSON string or plain text) request_id: Optional request ID to include + error_type: Anthropic error type to use instead of the one the status maps to Returns: AnthropicErrorResponse dict @@ -169,6 +170,7 @@ class AnthropicExceptionMapping: status_code=status_code, message=message, request_id=request_id, + error_type=error_type, ) diff --git a/litellm/anthropic_interface/exceptions/exceptions.py b/litellm/anthropic_interface/exceptions/exceptions.py index b48cd2fee6f..18b3ca37a3b 100644 --- a/litellm/anthropic_interface/exceptions/exceptions.py +++ b/litellm/anthropic_interface/exceptions/exceptions.py @@ -6,15 +6,18 @@ from typing import Literal from typing_extensions import NotRequired, ReadOnly, Required, TypedDict # Known Anthropic error types -# Source: https://docs.anthropic.com/en/api/errors +# Source: https://platform.claude.com/docs/en/api/errors AnthropicErrorType = Literal[ "invalid_request_error", "authentication_error", + "billing_error", "permission_error", "not_found_error", + "conflict_error", "request_too_large", "rate_limit_error", "api_error", + "timeout_error", "overloaded_error", ] @@ -25,6 +28,7 @@ class AnthropicErrorDetail(TypedDict): type: AnthropicErrorType message: str provider_specific_fields: NotRequired[ReadOnly[Mapping[str, object]]] + litellm_error_type: NotRequired[ReadOnly[str]] litellm_call_id: NotRequired[ReadOnly[str]] diff --git a/litellm/batches/batch_utils.py b/litellm/batches/batch_utils.py index a0c0a90be5f..d272a235758 100644 --- a/litellm/batches/batch_utils.py +++ b/litellm/batches/batch_utils.py @@ -10,6 +10,7 @@ from pydantic import JsonValue, TypeAdapter import litellm from litellm._logging import verbose_logger +from litellm.litellm_core_utils import batch_utils as core_batch_utils from litellm.litellm_core_utils.get_litellm_params import AWS_CREDENTIAL_KWARGS_KEYS from litellm.litellm_core_utils.llm_cost_calc.utils import parse_prompt_tokens_details from litellm.llms.base_llm.ocr.transformation import OCRUsageInfo @@ -38,8 +39,8 @@ class BatchCostUsageResult: completion_cost: float = 0.0 -_COMPLETED_BATCH_STATUSES: Final = frozenset({"completed", "complete"}) _DECODED_BATCH_LINE: Final = TypeAdapter(object) +batch_cost_is_final: Final = core_batch_utils.batch_cost_is_final def _uses_native_vertex_output( @@ -54,26 +55,6 @@ def _uses_native_vertex_output( return first_row is not None and is_native_vertex_batch_output_row(first_row) -_TERMINAL_BATCH_STATUSES: Final = _COMPLETED_BATCH_STATUSES | frozenset({"failed", "cancelled", "expired"}) - - -def batch_cost_is_final(batch: Batch) -> bool: - """Whether this retrieve of the batch is the one to account its cost from. - - A batch still in flight has nothing to price, and a "completed" batch can report - no output_file_id for a moment before the output populates; pricing either records - $0 under the batch's single spend row and pins it there. Final means a completed - batch whose output file has arrived or whose counts prove no line succeeded, or - any other terminal status (failed, cancelled, expired). - """ - if batch.status not in _TERMINAL_BATCH_STATUSES: - return False - if batch.status not in _COMPLETED_BATCH_STATUSES or batch.output_file_id is not None: - return True - request_counts: Final = batch.request_counts - return request_counts is not None and request_counts.total > 0 and request_counts.completed == 0 - - async def calculate_batch_cost_and_usage( file_content_dictionary: Sequence[dict[str, object]], custom_llm_provider: Literal["openai", "azure", "vertex_ai", "hosted_vllm", "anthropic", "mistral"], diff --git a/litellm/blog_posts.json b/litellm/blog_posts.json index fa768b3ec57..adcb3911652 100644 --- a/litellm/blog_posts.json +++ b/litellm/blog_posts.json @@ -1,10 +1,588 @@ { "posts": [ { - "title": "Realtime WebRTC HTTP Endpoints", - "description": "Use the LiteLLM proxy to route OpenAI-style WebRTC realtime via HTTP: client_secrets and SDP exchange.", - "date": "2026-03-12", - "url": "https://docs.litellm.ai/blog/realtime_webrtc_http_endpoints" + "title": "Release cadence changes and an LTS version pilot", + "description": "Starting the week of November 2, 2026, release candidates and stable releases ship on Tuesday mornings, and LiteLLM is piloting a long-term support line on 1.108 for one month.", + "date": "2026-11-02", + "url": "https://docs.litellm.ai/blog/release-cadence-and-lts-pilot", + "tags": [ + "release", + "support" + ] + }, + { + "title": "How to build an agent with grounding on LiteLLM", + "description": "Build a grounded chat agent in four steps with LiteLLM's AI Gateway. Connect your evidence, call a grounding guardrail, and show its verdict in chat.", + "date": "2026-10-31", + "url": "https://docs.litellm.ai/blog/grounded-agent", + "tags": [ + "engineering", + "guardrails", + "agents" + ] + }, + { + "title": "Introducing LiteLLM’s Unified Cost Accounting Engine", + "description": "Consistent cost reporting, independently scalable accounting, and spend analysis by team, user, model, or custom dimensions.", + "date": "2026-10-31", + "url": "https://docs.litellm.ai/blog/cost-infrastructure-makeover", + "tags": [ + "engineering", + "reliability" + ] + }, + { + "title": "What we are changing after October 21", + "description": "Why the controls built after March did not stop the v1.107.0 release, and the identity, credential and detection changes we are making in response.", + "date": "2026-10-30", + "url": "https://docs.litellm.ai/blog/security-changes-after-oct-21-2026", + "tags": [ + "security", + "incident-report" + ] + }, + { + "title": "Use Hex to analyze LiteLLM costs, then set budgets and routing", + "description": "Connect Hex to LiteLLM’s Postgres data, import a cost dashboard, then use the LiteLLM UI to set a budget or change model routing.", + "date": "2026-10-30", + "url": "https://docs.litellm.ai/blog/hex-litellm-roi", + "tags": [ + "observability", + "cost tracking", + "ai-gateway" + ] + }, + { + "title": "Introducing the LiteLLM Private Registry", + "description": "LiteLLM is committing to a private registry to provide early access to fixes for the most severe security vulnerabilities, ahead of public release.", + "date": "2026-10-27", + "url": "https://docs.litellm.ai/blog/litellm-private-registry", + "tags": [ + "security" + ] + }, + { + "title": "Morph open-weight models on LiteLLM", + "description": "Use Morph's Kimi, GLM, and DeepSeek models through LiteLLM with tool calling, structured output, streaming, and prompt-cache cost tracking.", + "date": "2026-10-27", + "url": "https://docs.litellm.ai/blog/morph-provider", + "tags": [] + }, + { + "title": "Abliterated models on LiteLLM", + "description": "Call abliterated models from Refuseless and Abliteration through LiteLLM, with gateway access controls, streaming, tool calls, and cached-token pricing.", + "date": "2026-10-26", + "url": "https://docs.litellm.ai/blog/abliterated-models", + "tags": [ + "engineering" + ] + }, + { + "title": "GPT-6.1 Terra API Pricing and Day 0 Support on LiteLLM", + "description": "GPT-6.1 Terra costs $1 per 1M input tokens and $5 per 1M output tokens, half the price of GPT-6.1 Sol. LiteLLM supports it on day 0.", + "date": "2026-10-26", + "url": "https://docs.litellm.ai/blog/gpt-6-1-terra", + "tags": [ + "openai", + "gpt-6.1", + "gpt-6.1-terra", + "pricing", + "day 0 support", + "card_title:GPT-6.1 Terra", + "card_summary:Half the price of GPT-6.1 Sol at $1 / $5 per 1M tokens, 50.3% on Terminal-Bench 4.0, 1.05M context." + ] + }, + { + "title": "Rust Migration: /v1/messages end-to-end in Rust by Dec 1", + "description": "By December 1st, the proxy will handle Anthropic messages requests 20x faster", + "date": "2026-10-26", + "url": "https://docs.litellm.ai/blog/rust-migration-rerouted", + "tags": [ + "rust", + "rust-migration", + "ai-gateway", + "engineering" + ] + }, + { + "title": "OpenCode Go is now a LiteLLM provider", + "description": "Use your OpenCode Go subscription through LiteLLM. Connect once, route models to the right API, preserve sessions, and track estimated usage.", + "date": "2026-10-24", + "url": "https://docs.litellm.ai/blog/opencode-go", + "tags": [ + "providers", + "tutorial" + ] + }, + { + "title": "The attack chain behind the v1.107.0 LiteLLM release", + "description": "How an internal key committed to a public repository in May led to three stolen GitHub tokens and the compromised litellm v1.107.0 release.", + "date": "2026-10-23", + "url": "https://docs.litellm.ai/blog/security-incident-oct-21-2026-attack-chain", + "tags": [ + "security", + "incident-report" + ] + }, + { + "title": "Tokenize text across vLLM and Watsonx", + "description": "Choose token counting for prompt budgets or /tokenize to inspect tokens. Use one request format across vLLM and Watsonx through LiteLLM.", + "date": "2026-10-23", + "url": "https://docs.litellm.ai/blog/unified-tokenize", + "tags": [ + "engineering" + ] + }, + { + "title": "October Townhall Updates: 426 Bug Fixes, 88.4% Coverage, and the Decisions API", + "description": "A recap of the October LiteLLM town hall: security changes that need action before you upgrade, 426 bug fixes, test coverage at 88.4%, the Decisions API, Lens, Moyai, and LiteLLM Relay.", + "date": "2026-10-23", + "url": "https://docs.litellm.ai/blog/october-townhall-updates", + "tags": [ + "townhall", + "security", + "reliability", + "product" + ] + }, + { + "title": "Contained: Oct 21, 2026 LiteLLM release v1.107.0 Compromised", + "description": "LiteLLM release v1.107.0 was compromised by a malicious actor.", + "date": "2026-10-21", + "url": "https://docs.litellm.ai/blog/security-incident-oct-21-2026", + "tags": [ + "security", + "incident-report" + ] + }, + { + "title": "JevRank: decision models through LiteLLM’s rerank API", + "description": "Preview JevRank for low-cost reranking with Perplexity and TypeSafe decision models. Explore SciFact results, reproducible data and LiteLLM setup.", + "date": "2026-10-20", + "url": "https://docs.litellm.ai/blog/jevrank", + "tags": [ + "engineering", + "reranking", + "decisions" + ] + }, + { + "title": "Cache-Aware Routing for Self-Hosted Models", + "description": "Route each agent session to the same vLLM pod on Kubernetes to reuse cached prompt prefixes.", + "date": "2026-10-20", + "url": "https://docs.litellm.ai/blog/cache-aware-routing", + "tags": [ + "routing", + "kubernetes", + "vllm", + "ai-gateway" + ] + }, + { + "title": "Day 0 Support: TypeSafe Jev 1.14: Adds images, box questions, and long context", + "description": "TypeSafe Jev 1.14 reads images, answers box questions with coordinates and takes long-context requests. LiteLLM serves all three on /v1/systemone and /v1/decisions behind TypeSafe's opt-in headers.", + "date": "2026-10-15", + "url": "https://docs.litellm.ai/blog/typesafe_jev_images", + "tags": [ + "typesafe", + "jev", + "decisions", + "day 0 support", + "card_title:Jev 1.14", + "card_summary:Jev 1.14 reads PNG and JPEG images, answers box questions with coordinates, and takes long-context requests on LiteLLM." + ] + }, + { + "title": "Decision models on LiteLLM: /v1/decisions and /v1/systemone", + "description": "Decision models return probabilities instead of text, which makes routing, triage and guardrail checks cheap and deterministic. LiteLLM serves nine providers of them behind one request shape.", + "date": "2026-10-14", + "url": "https://docs.litellm.ai/blog/decision-models", + "tags": [ + "openai", + "typesafe", + "decisions", + "day 0 support", + "card_title:Decision Models", + "card_summary:Typed yes/no, choice and score answers as probabilities, from 9 providers on /v1/decisions and /v1/systemone." + ] + }, + { + "title": "Workshop: Build a self-hosted cloud agent.", + "description": "Build a self-hosted cloud agent with the LiteLLM team. A two-week remote workshop, October 19–30, to build a working v0 and deploy an internal beta on your infrastructure.", + "date": "2026-10-13", + "url": "https://docs.litellm.ai/blog/cloud-agent-workshop", + "tags": [ + "agents", + "infrastructure", + "announcement" + ] + }, + { + "title": "Gemini 4 Argon API Pricing and Day 0 Support on LiteLLM", + "description": "Gemini 4 Argon costs $2.00 per 1M input tokens and $10.00 per 1M output tokens until Nov 30. LiteLLM supports it on day 0 on AI Studio and Google Cloud.", + "date": "2026-10-13", + "url": "https://docs.litellm.ai/blog/gemini-4-argon", + "tags": [ + "gemini", + "gemini 4", + "gemini-4-argon", + "pricing", + "day 0 support", + "card_title:Gemini 4 Argon", + "card_summary:Google's new flagship: 77.9% on DeepSWE v1.1, 1M context, thinking levels, $2 / $10 per 1M tokens until Nov 30." + ] + }, + { + "title": "October Townhall: Product + Roadmap Updates", + "description": "Join the LiteLLM October townhall on Friday, 23 October at 7:30 AM PT to learn about LiteLLM's product updates and roadmap.", + "date": "2026-10-10", + "url": "https://docs.litellm.ai/blog/october-townhall-announcement", + "tags": [ + "announcement", + "townhall" + ] + }, + { + "title": "Introducing Microsoft 365 Copilot in LiteLLM", + "description": "Use Microsoft 365 Copilot from your applications through LiteLLM, with access to your Microsoft 365 work data.", + "date": "2026-10-09", + "url": "https://docs.litellm.ai/blog/microsoft-365-copilot", + "tags": [ + "announcement", + "ai-gateway" + ] + }, + { + "title": "Introducing litellm-core: the first step toward a leaner SDK", + "description": "Ongoing work to reduce LiteLLM's dependencies and installation footprint, improve runtime loading, and make imports faster", + "date": "2026-10-08", + "url": "https://docs.litellm.ai/blog/introducing-litellm-core", + "tags": [] + }, + { + "title": "Claude Haiku 5.5 API Pricing and Day 0 Support on LiteLLM", + "description": "Claude Haiku 5.5 costs $0.10 per 1M input tokens and $0.50 per 1M output tokens. LiteLLM supports it on day 0 on Anthropic, AWS, Google Cloud and Azure.", + "date": "2026-10-07", + "url": "https://docs.litellm.ai/blog/claude-haiku-5-5", + "tags": [ + "anthropic", + "claude", + "claude haiku", + "haiku 5.5", + "pricing", + "day 0 support", + "card_title:Claude Haiku 5.5", + "card_summary:90% cheaper than Haiku 4.5 on short prompts, 1M context, 72.4% on OSWorld 2.1, $0.10 / $0.50 per 1M tokens." + ] + }, + { + "title": "Open Sourcing Moyai: Self-Hosted Cloud Coding Agent", + "description": "Run cloud coding agents on your own infrastructure with Moyai. Choose your agent and models through LiteLLM, track costs, and follow the setup guide.", + "date": "2026-10-07", + "url": "https://docs.litellm.ai/blog/moyai-open-source", + "tags": [ + "agents", + "open-source", + "infrastructure" + ] + }, + { + "title": "Day 0 Support: Nano Banana 2.1", + "description": "Day 0 support for Gemini Nano Banana 2.1 on LiteLLM, on Google AI Studio and Gemini Enterprise Agent Platform, with image output at half Nano Banana 2's price.", + "date": "2026-10-06", + "url": "https://docs.litellm.ai/blog/nano_banana_2_1", + "tags": [ + "gemini", + "gemini enterprise agent platform", + "nano banana", + "image generation", + "day 0 support", + "card_title:Nano Banana 2.1", + "card_summary:Gemini image model with image output at half Nano Banana 2's price: $30 / MTok image out, $1.50 text in." + ] + }, + { + "title": "How LiteLLM Lens finds repeated failures across 1,000s of agent traces", + "description": "Inside Lens: parallel trace review, Python tools for large traces, and investigations that connect repeated failures to source evidence.", + "date": "2026-10-05", + "url": "https://docs.litellm.ai/blog/lens-failure-patterns", + "tags": [ + "lens", + "agent-tracing", + "engineering" + ] + }, + { + "title": "How we cut time to first byte by 94% for long prompts", + "description": "A 440k-token benchmark went from 553 ms to 35 ms median time to first byte. We removed unnecessary prompt-cache routing work before the model call.", + "date": "2026-10-03", + "url": "https://docs.litellm.ai/blog/long-prompt-latency", + "tags": [ + "performance", + "proxy", + "engineering", + "ai-gateway" + ] + }, + { + "title": "How we built our own internal Devin in 2 days", + "description": "How we built Moyai Devin with Render, Modal, Hermes, Temporal, and LiteLLM: durable sessions, parallel agents, Slack, and shared organization connections.", + "date": "2026-10-03", + "url": "https://docs.litellm.ai/blog/internal-devin-two-days", + "tags": [ + "engineering", + "agents", + "infrastructure", + "slack" + ] + }, + { + "title": "Adding Self-hosted Auto Router Classifiers: Laya & Nimble", + "description": "Use Laya or Bespoke Nimble to classify Auto Router requests on your own infrastructure. Control where classification runs, which model you serve, and how you provision it.", + "date": "2026-10-02", + "url": "https://docs.litellm.ai/blog/laya-nimble-classifiers", + "tags": [ + "auto-router", + "product", + "ai-gateway" + ] + }, + { + "title": "Launching LiteLLM Lens", + "description": "LiteLLM Lens turns the traces flowing through your gateway into findings your agents can act on. Built for agent swarms generating 200K+ traces.", + "date": "2026-10-01", + "url": "https://docs.litellm.ai/blog/litellm-lens-launch", + "tags": [ + "lens", + "agent-tracing" + ] + }, + { + "title": "How we cut LiteLLM's Redis round trips per request by 64%", + "description": "A governed request to the LiteLLM AI Gateway waited on Redis 22 times. It now waits 8 times: one pipeline per Redis backend before the model call, one after.", + "date": "2026-10-01", + "url": "https://docs.litellm.ai/blog/redis-request-pipelines", + "tags": [ + "performance", + "redis", + "proxy", + "engineering", + "ai-gateway" + ] + }, + { + "title": "How we made the LiteLLM Usage page 120x faster", + "description": "From six minutes to 3.2 seconds: how moving aggregation into Postgres made LiteLLM's Usage page roughly 120x faster in our benchmark.", + "date": "2026-09-30", + "url": "https://docs.litellm.ai/blog/usage-page-bounded-loading", + "tags": [ + "performance", + "admin-ui", + "postgres", + "engineering", + "ai-gateway" + ] + }, + { + "title": "Day 0 Support: GPT-6.1 Sol", + "description": "Day 0 support for GPT-6.1 Sol on LiteLLM, with cached input at half GPT-6 Sol's price.", + "date": "2026-09-29", + "url": "https://docs.litellm.ai/blog/gpt_6_1_sol", + "tags": [ + "openai", + "gpt-6", + "gpt-6.1-sol", + "completion", + "day 0 support", + "card_title:GPT-6.1 Sol", + "card_summary:GPT-6 Sol successor with cached input at half GPT-6 Sol's price, same request family and params." + ] + }, + { + "title": "Learn the LiteLLM gateway with a guided course", + "description": "Follow a request through the LiteLLM gateway, Router, and SDK. A guided course for teams deploying the gateway and contributors making code changes.", + "date": "2026-09-28", + "url": "https://docs.litellm.ai/blog/litellm-gateway-course", + "tags": [ + "proxy", + "product" + ] + }, + { + "title": "Day 0 Support: Claude Sonnet 5.5", + "description": "Day 0 support for Claude Sonnet 5.5 on the LiteLLM AI Gateway. Use it across Anthropic, Bedrock, Gemini Enterprise Agent Platform, and Azure.", + "date": "2026-09-28", + "url": "https://docs.litellm.ai/blog/claude_sonnet_5_5", + "tags": [ + "anthropic", + "claude", + "sonnet 5.5", + "day 0 support", + "card_title:Claude Sonnet 5.5", + "card_summary:Same $2 / $10 price as Sonnet 5, 30%+ faster, 70.6% on Terminal-Bench 4.0 (Sonnet 5: 10.3%), 1M context." + ] + }, + { + "title": "Introducing the LiteLLM ROI Calculator", + "description": "Compare each engineer's LiteLLM gateway spend with the estimated effort of their merged pull requests. Open source and self-hosted.", + "date": "2026-09-26", + "url": "https://docs.litellm.ai/blog/litellm-roi-calculator", + "tags": [ + "cost", + "product", + "announcement" + ] + }, + { + "title": "Introducing LiteAgents", + "description": "Switch agent harnesses without rewriting your agent. Keep your tools and model configuration, use native harness controls, and add Temporal when you need durable runs.", + "date": "2026-09-25", + "url": "https://docs.litellm.ai/blog/liteagents-sdk", + "tags": [ + "agents", + "sdk" + ] + }, + { + "title": "September Townhall Updates: 583 Bug Fixes, OCR on Rust, and 83.5% Coverage", + "description": "A recap of the September LiteLLM town hall: security and stability updates, OCR running on Rust by default, test coverage past the 80% target, and new Fusion and liteagents launches.", + "date": "2026-09-24", + "url": "https://docs.litellm.ai/blog/september-townhall-updates", + "tags": [ + "townhall", + "reliability", + "product" + ] + }, + { + "title": "Day 0 support: Gemini 3.8 Flash TTS and Flash-Lite TTS", + "description": "Day 0 support for Gemini 3.8 Flash TTS and Flash-Lite TTS on LiteLLM's /v1/audio/speech, with launch pricing tracked through 2026.", + "date": "2026-09-23", + "url": "https://docs.litellm.ai/blog/gemini_3_8_flash_tts", + "tags": [ + "gemini", + "gemini-3.8-flash-tts", + "text to speech", + "day 0 support", + "card_title:Gemini 3.8 Flash TTS and Flash-Lite TTS", + "card_summary:Gemini speech models on /v1/audio/speech, Flash and Flash-Lite, with launch pricing tracked through 2026." + ] + }, + { + "title": "Introducing LiteAdmin MCP", + "description": "Give your agent tools to create keys, add models, and manage budgets with LiteAdmin MCP. Use the same connector through LiteAdmin, our Slack admin agent.", + "date": "2026-09-23", + "url": "https://docs.litellm.ai/blog/litellm-admin-mcp", + "tags": [ + "mcp", + "agents", + "ai-gateway" + ] + }, + { + "title": "Day 0 Support: GPT-6 Sol and GPT-6 Luna", + "description": "Day 0 support for GPT-6 Sol and GPT-6 Luna on LiteLLM, at half the price of their GPT-5.6 counterparts.", + "date": "2026-09-22", + "url": "https://docs.litellm.ai/blog/gpt_6_sol_luna", + "tags": [ + "openai", + "gpt-6", + "gpt-6-sol", + "gpt-6-luna", + "completion", + "day 0 support", + "card_title:GPT-6 Sol and GPT-6 Luna", + "card_summary:Two GPT-6 variants at half the price of their GPT-5.6 counterparts, routed as the GPT-5 request family." + ] + }, + { + "title": "Day 0 Support: Claude Opus 5.5", + "description": "Day 0 support for Claude Opus 5.5 on the LiteLLM AI Gateway. Use it across Anthropic, Bedrock, Gemini Enterprise Agent Platform, and Azure.", + "date": "2026-09-22", + "url": "https://docs.litellm.ai/blog/claude_opus_5_5", + "tags": [ + "anthropic", + "claude", + "opus 5.5", + "day 0 support", + "card_title:Claude Opus 5.5", + "card_summary:20% cheaper than Opus 5 at $4 / $20 per 1M, 30% faster output, Terminal-Bench 4.0 66.4%, thinking always on." + ] + }, + { + "title": "Getting Started with Fireworks AI on LiteLLM", + "description": "A beginner tutorial: run an open model on Fireworks AI behind a LiteLLM gateway, call it with the OpenAI SDK you already use, then add a second model and a fallback.", + "date": "2026-09-22", + "url": "https://docs.litellm.ai/blog/fireworks-getting-started", + "tags": [ + "tutorial", + "providers", + "fireworks", + "getting-started" + ] + }, + { + "title": "Day 0 Support: Xiaomi MiMo V2.6", + "description": "Day 0 support for Xiaomi MiMo V2.6 Pro and Flash on LiteLLM, priced on the native route for the first time.", + "date": "2026-09-22", + "url": "https://docs.litellm.ai/blog/mimo_v2_6", + "tags": [ + "xiaomi", + "mimo", + "mimo-v2.6", + "day 0 support", + "card_title:Xiaomi MiMo V2.6", + "card_summary:Xiaomi's Pro ($0.435 / $0.87 per 1M) and Flash ($0.14 / $0.28), same rates as V2.5, priced on the native route." + ] + }, + { + "title": "Claude Code server-side auto mode through LiteLLM", + "description": "Anthropic is moving Claude Code auto mode's safety classifier server-side. LiteLLM's native /v1/messages route now forwards the safeguards contract to the Anthropic API, Bedrock InvokeModel, Bedrock Mantle and Vertex AI. Here is the contract, what changed, which releases carry it, and how to verify it.", + "date": "2026-09-21", + "url": "https://docs.litellm.ai/blog/claude-code-server-side-auto-mode", + "tags": [ + "announcement", + "claude-code", + "anthropic", + "ai-gateway" + ] + }, + { + "title": "Day 0 Support: Grok 4.7", + "description": "Day 0 support for Grok 4.7 on LiteLLM, at the same price as Grok 4.6.", + "date": "2026-09-21", + "url": "https://docs.litellm.ai/blog/grok_4_7", + "tags": [ + "xai", + "grok", + "grok-4.7", + "day 0 support", + "card_title:Grok 4.7", + "card_summary:SpaceXAI's update to Grok 4.6 at the same price and limits, better at checking its own work and long context." + ] + }, + { + "title": "JEV Classifier: 5.43x as Fast as Haiku, 96% Lower Cost", + "description": "JEV classified requests 5.43x as fast as Haiku by median latency in our AI Gateway benchmark. Explore the setup, cost savings and methodology.", + "date": "2026-09-20", + "url": "https://docs.litellm.ai/blog/jev-auto-router-benchmark", + "tags": [ + "routing", + "complexity-router", + "engineering", + "ai-gateway" + ] + }, + { + "title": "TypeSafe Jev on LiteLLM", + "description": "TypeSafe AI's Jev lands in LiteLLM v1.103.0-rc: call it through the proxy with logging and cost tracking.", + "date": "2026-09-20", + "url": "https://docs.litellm.ai/blog/typesafe_jev", + "tags": [ + "typesafe", + "jev", + "product" + ] } ] } diff --git a/litellm/caching/caching.py b/litellm/caching/caching.py index 91cf9bb2cfe..3b7ea66ad6b 100644 --- a/litellm/caching/caching.py +++ b/litellm/caching/caching.py @@ -45,13 +45,27 @@ from .redis_semantic_cache import RedisSemanticCache from .s3_cache import S3Cache RESPONSE_CACHE_TARGET: Final = "llm_response" -_ALWAYS_KEYED_PROVIDER_PARAMS: Final = frozenset({"continuation_token"}) +_ALWAYS_KEYED_PROVIDER_PARAMS: Final = frozenset({"continuation_token", "return_token_ids"}) _DECODED_LITERAL: Final = TypeAdapter(object) _REDIS_STARTUP_NODES_ADAPTER: Final = TypeAdapter( list[dict[str, object]], config=ConfigDict(strict=True, hide_input_in_errors=True) ) +def _keyed_provider_params_in_extra_body(kwargs: Mapping[str, object]) -> str: + raw_extra_body: Final = kwargs.get("extra_body") + if not isinstance(raw_extra_body, dict): + return "" + extra_body: Final = cast( # cast-ok: isinstance leaves the key and value types unknown + Mapping[str, object], raw_extra_body + ) + return "".join( + f"extra_body.{param}: {extra_body[param]}" + for param in sorted(_ALWAYS_KEYED_PROVIDER_PARAMS) + if extra_body.get(param) + ) + + @contextmanager def response_cache_phase(operation: Literal["get", "set"]) -> Generator[None]: """The ``cache.get llm_response`` / ``cache.set llm_response`` span a response-cache read or write runs @@ -429,7 +443,10 @@ class Cache: "" if embeds_thought_signature_in_tool_call_id(kwargs) else "thought_signature_in_tool_call_id: False" ) hashed_cache_key = Cache._get_hashed_cache_key( - cache_key + reasoning_summary_material + tool_call_id_shape_material + cache_key + + _keyed_provider_params_in_extra_body(kwargs) + + reasoning_summary_material + + tool_call_id_shape_material ) hashed_cache_key = self._add_namespace_to_cache_key(hashed_cache_key, **kwargs) verbose_logger.debug( diff --git a/litellm/caching/dual_cache.py b/litellm/caching/dual_cache.py index e6214a3650c..af084a464ee 100644 --- a/litellm/caching/dual_cache.py +++ b/litellm/caching/dual_cache.py @@ -620,7 +620,7 @@ class DualCache(BaseCache): increment_list: list["RedisPipelineIncrementOperation"], local_only: bool = False, parent_otel_span: Span | None = None, - **kwargs, + **kwargs: object, # kwargs-ok: accepted and unused, as the cache interface's other calls take them ) -> list[float] | None: result: list[float] | None = None try: @@ -673,7 +673,7 @@ class DualCache(BaseCache): if self.redis_cache is not None: self.redis_cache.flush_cache() - def delete_cache(self, key): + def delete_cache(self, key: str) -> None: """ Delete a key from the cache """ diff --git a/litellm/completion_extras/litellm_responses_transformation/handler.py b/litellm/completion_extras/litellm_responses_transformation/handler.py index 76d17ea9693..f6879c313de 100644 --- a/litellm/completion_extras/litellm_responses_transformation/handler.py +++ b/litellm/completion_extras/litellm_responses_transformation/handler.py @@ -11,7 +11,7 @@ from typing import ( cast, # noqa: TID251 # optional_params reaches the bridge as an untyped dict ) -from typing_extensions import TypedDict +from typing_extensions import ReadOnly, TypedDict from litellm.types.llms.openai import ResponsesAPIResponse @@ -20,15 +20,15 @@ if TYPE_CHECKING: class ResponsesToCompletionBridgeHandlerInputKwargs(TypedDict): - model: str - messages: list - optional_params: dict - litellm_params: dict - headers: dict - model_response: "ModelResponse" - logging_obj: "LiteLLMLoggingObj" - custom_llm_provider: str - encoding: object + model: ReadOnly[str] + messages: ReadOnly[list] + optional_params: ReadOnly[dict[str, object]] + litellm_params: ReadOnly[dict[str, object]] + headers: ReadOnly[dict] + model_response: ReadOnly["ModelResponse"] + logging_obj: ReadOnly["LiteLLMLoggingObj"] + custom_llm_provider: ReadOnly[str] + encoding: ReadOnly[object] def _restore_routing_prefix(model: str, custom_llm_provider: str) -> str: @@ -184,6 +184,7 @@ class ResponsesToCompletionBridgeHandler: custom_llm_provider: Final = validated_kwargs["custom_llm_provider"] if kwargs.get("stream") is True and "stream" not in optional_params: optional_params = {**optional_params, "stream": True} + logging_obj.record_bridged_chat_request(optional_params, litellm_params) request_data: Final = self.transformation_handler.transform_request( model=model, @@ -285,6 +286,7 @@ class ResponsesToCompletionBridgeHandler: custom_llm_provider: Final = validated_kwargs["custom_llm_provider"] if kwargs.get("stream") is True and "stream" not in optional_params: optional_params = {**optional_params, "stream": True} + logging_obj.record_bridged_chat_request(optional_params, litellm_params) try: request_data: Final = self.transformation_handler.transform_request( diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py index bb59b4617af..8e6341805db 100644 --- a/litellm/completion_extras/litellm_responses_transformation/transformation.py +++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py @@ -16,6 +16,7 @@ from openai.types.responses.response_input_param import ( ResponseCustomToolCallOutputParam, ResponseCustomToolCallParam, ) +from openai.types.responses.tool_choice_allowed_param import ToolChoiceAllowedParam from openai.types.responses.tool_choice_custom_param import ToolChoiceCustomParam from openai.types.responses.tool_choice_function_param import ToolChoiceFunctionParam from openai.types.responses.tool_param import FunctionToolParam @@ -33,11 +34,17 @@ from litellm.completion_extras.litellm_responses_transformation.history import ( replay_items, requested_phase, ) -from litellm.integrations.anthropic_cache_control_hook import supports_openai_prompt_cache_breakpoint +from litellm.integrations.anthropic_cache_control_hook import routed_model_info, supports_openai_prompt_cache_breakpoint +from litellm.litellm_core_utils.allowed_tools_tool_choice import ( + parse_chat_allowed_tools_tool_choice, + responses_allowed_tools_tool_choice, +) +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.litellm_core_utils.hidden_params import get_hidden_params, get_or_create_hidden_params from litellm.litellm_core_utils.prompt_templates.common_utils import ( - prompt_cache_breakpoint_for_wire, + prompt_cache_breakpoint_with_readable_mode, responses_reasoning_items_from_thinking_blocks, + whole_prompt_cache_breakpoint_or_none, with_prompt_cache_breakpoint, ) from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator @@ -97,6 +104,12 @@ _RESPONSES_API_ONLY_FIELDS: Final = frozenset((*Response.model_fields, *Response ) +def _bridged_prompt_cache_breakpoint(marker: object, drop_params: bool, target_trims_breakpoints: bool) -> object: + if target_trims_breakpoints: + return prompt_cache_breakpoint_with_readable_mode(marker, drop_params) + return whole_prompt_cache_breakpoint_or_none(marker) if drop_params else marker + + def _strip_prompt_cache_breakpoint_from_content_block(value: object) -> object: if not isinstance(value, dict): return value @@ -775,13 +788,28 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): def _normalize_tool_choice_for_responses_api( self, tool_choice: _ToolChoiceT - ) -> _ToolChoiceT | ToolChoiceFunctionParam | ToolChoiceCustomParam | Literal["auto", "none", "required"]: + ) -> ( + _ToolChoiceT + | ToolChoiceFunctionParam + | ToolChoiceCustomParam + | ToolChoiceAllowedParam + | Literal["auto", "none", "required"] + ): """Chat tool_choice nests the name under function/custom; Responses API expects top-level name.""" if not isinstance(tool_choice, dict): return tool_choice choice_type: Final = tool_choice.get("type") if isinstance(choice_type, str) and choice_type in ("auto", "none", "required"): return choice_type + if choice_type == "allowed_tools": + parsed: Final = parse_chat_allowed_tools_tool_choice( + cast( # cast-ok: widening an untyped dict to object is always sound, the helper validates it with pydantic + object, tool_choice + ) + ) + flat: Final = responses_allowed_tools_tool_choice(parsed) if parsed is not None else None + if flat is not None: + return flat if choice_type not in ("function", "custom"): return tool_choice if isinstance(tool_choice.get("name"), str) and tool_choice.get("name"): @@ -844,6 +872,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): messages: list["AllMessageValues"], *, drop_params: bool = False, + target_trims_breakpoints: bool = True, keep_prompt_cache_breakpoints: bool = False, replay_tool_search: bool = False, include_namespace: bool = False, @@ -852,6 +881,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): converted_input_items, instructions = self._convert_chat_completion_messages_to_responses_input( messages, drop_params=drop_params, + target_trims_breakpoints=target_trims_breakpoints, replay_tool_search=replay_tool_search, include_namespace=include_namespace, replay_openai_history=replay_openai_history, @@ -868,6 +898,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): messages: list["AllMessageValues"], *, drop_params: bool = False, + target_trims_breakpoints: bool = True, replay_tool_search: bool = False, include_namespace: bool = False, replay_openai_history: bool = False, @@ -921,6 +952,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): content, role, drop_params=drop_params, + target_trims_breakpoints=target_trims_breakpoints, ), } ) @@ -940,6 +972,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): content, "user", # Use "user" role to get input_* types drop_params=drop_params, + target_trims_breakpoints=target_trims_breakpoints, ) else: # Fallback: convert unexpected types to input_text @@ -968,7 +1001,10 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): "type": "message", "role": "assistant", "content": self._convert_content_to_responses_format( - content, "assistant", drop_params=drop_params + content, + "assistant", + drop_params=drop_params, + target_trims_breakpoints=target_trims_breakpoints, ), **_assistant_phase_field(msg, replay_openai_history, drop_params), } @@ -1009,7 +1045,10 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): "type": "message", "role": role, "content": self._convert_content_to_responses_format( - content, cast(str, role), drop_params=drop_params + content, + cast(str, role), + drop_params=drop_params, + target_trims_breakpoints=target_trims_breakpoints, ), **_assistant_phase_field(msg, replay_openai_history and role == "assistant", drop_params), } @@ -1127,24 +1166,26 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): optional_params = self._extract_extra_body_params(optional_params) provider: Final = _served_provider(litellm_params) base_model: Final = litellm_params.get("base_model") - supports_prompt_cache_breakpoint: Final = supports_openai_prompt_cache_breakpoint(model, provider) or ( - isinstance(base_model, str) - and bool(base_model) - and supports_openai_prompt_cache_breakpoint(base_model, provider) + model_info: Final = routed_model_info(litellm_params.get("model_info")) + named_models: Final = (model, base_model) if isinstance(base_model, str) and base_model else (model,) + supports_prompt_cache_breakpoint: Final = any( + supports_openai_prompt_cache_breakpoint(name, provider, model_info) for name in named_models ) converted_input_items, converted_instructions = self.convert_chat_completion_messages_to_responses_api( messages, drop_params=bool(litellm_params.get("drop_params") or litellm.drop_params), + target_trims_breakpoints=drops_unsupported_params(litellm_params.get("drop_params")), keep_prompt_cache_breakpoints=supports_prompt_cache_breakpoint, replay_tool_search=_requests_tool_search(cast(object, optional_params)), # cast-ok: upcast include_namespace=True, replay_openai_history=provider == "openai", ) - # OpenAI's Responses API rejects an empty input. For a system-only - # request, carry the system message as a system-role input item instead - # of instructions, mirroring how non-string system content is already - # handled in convert_chat_completion_messages_to_responses_api. - is_system_only_request: Final = not converted_input_items and converted_instructions is not None + # Keep the system text in input instead of instructions when the Responses API needs it there. + # It rejects an empty input, and json_object requires the word "json" in input, ignoring instructions. + typed_optional_params: Final = cast("Mapping[str, object]", optional_params) # cast-ok: untyped dict + system_goes_in_input: Final = converted_instructions is not None and ( + not converted_input_items or _payload_type(typed_optional_params.get("response_format")) == "json_object" + ) target_input_items: Final = ( _without_audio_input_parts(converted_input_items) if _drops_audio_input(model, litellm_params) @@ -1156,12 +1197,13 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): "type": "message", "role": "system", "content": [{"type": "input_text", "text": converted_instructions}], - } + }, + *target_input_items, ] - if is_system_only_request + if system_goes_in_input else target_input_items ) - instructions: Final = None if is_system_only_request else converted_instructions + instructions: Final = None if system_goes_in_input else converted_instructions # Build responses API request using the reverse transformation logic responses_api_request: Final = ResponsesAPIOptionalRequestParams() @@ -1195,10 +1237,6 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): api_model: Final = model - from litellm.types.utils import CallTypes - - setattr(litellm_logging_obj, "call_type", CallTypes.responses.value) - sanitized_litellm_params: Final = self._build_sanitized_litellm_params(litellm_params) request_data: Final = { @@ -1640,6 +1678,7 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): | None, role: str, drop_params: bool = False, + target_trims_breakpoints: bool = True, ) -> list[dict[str, object]]: """Convert chat completion content to responses API format""" from litellm.types.llms.openai import ChatCompletionImageObject @@ -1666,7 +1705,9 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): if original_type == "text": converted = with_prompt_cache_breakpoint( self._convert_content_str_to_input_text(item.get("text", ""), role), - prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), + _bridged_prompt_cache_breakpoint( + item.get("prompt_cache_breakpoint"), drop_params, target_trims_breakpoints + ), ) result.append(converted) verbose_logger.debug("Chat provider: text -> %s", converted) @@ -1679,14 +1720,18 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): cast(ChatCompletionImageObject, item), role ), ), - prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), + _bridged_prompt_cache_breakpoint( + item.get("prompt_cache_breakpoint"), drop_params, target_trims_breakpoints + ), ) result.append(converted) verbose_logger.debug("Chat provider: image_url -> %s", converted) elif original_type == "input_audio": converted = with_prompt_cache_breakpoint( {"type": "input_audio", "input_audio": item.get("input_audio")}, - prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), + _bridged_prompt_cache_breakpoint( + item.get("prompt_cache_breakpoint"), drop_params, target_trims_breakpoints + ), ) result.append(converted) verbose_logger.debug("Chat provider: input_audio -> %s", converted) @@ -1702,7 +1747,9 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): _input_file_from_file_value( cast("ChatCompletionFileObject", item).get("file"), # cast-ok: type tag checked ), - prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), + _bridged_prompt_cache_breakpoint( + item.get("prompt_cache_breakpoint"), drop_params, target_trims_breakpoints + ), ) result.append(converted) verbose_logger.debug("Chat provider: file -> %s", converted) @@ -1726,7 +1773,9 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge): # Default to input_text for unknown types converted = with_prompt_cache_breakpoint( self._convert_content_str_to_input_text(str(item.get("text", item)), role), - prompt_cache_breakpoint_for_wire(item.get("prompt_cache_breakpoint"), drop_params), + _bridged_prompt_cache_breakpoint( + item.get("prompt_cache_breakpoint"), drop_params, target_trims_breakpoints + ), ) result.append(converted) verbose_logger.debug("Chat provider: unknown(%s) -> %s", original_type, converted) diff --git a/litellm/constants.py b/litellm/constants.py index cd7c0176428..50e090eabaf 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -135,6 +135,7 @@ ANTHROPIC_DEFAULT_FILE_LIST_LIMIT: Final = 20 DEFAULT_SQS_FLUSH_INTERVAL_SECONDS: Final = get_env_int("DEFAULT_SQS_FLUSH_INTERVAL_SECONDS", 10) DEFAULT_NUM_WORKERS_LITELLM_PROXY: Final = get_env_int("DEFAULT_NUM_WORKERS_LITELLM_PROXY", 1) GRACEFUL_SHUTDOWN_TEARDOWN_HEADROOM_SECONDS: Final = 10 +DEFAULT_MAX_REQUEST_HEADER_SIZE: Final = 16 * 1024 budget_reservation_disabled_info_emitted = False DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE = get_env_int("DYNAMIC_RATE_LIMIT_ERROR_THRESHOLD_PER_MINUTE", 1) DEFAULT_SQS_BATCH_SIZE: Final = get_env_int("DEFAULT_SQS_BATCH_SIZE", 512) @@ -451,6 +452,7 @@ OPENAI_LIVE_TERMINAL_RESPONSE_EVENT_TYPES: Final = frozenset( {"response.completed", "response.incomplete", "response.failed"} ) REALTIME_SESSION_FAILURE_LOGGED_KEY: Final = "realtime_session_failure_logged" +REALTIME_SESSION_ENDED_ABNORMALLY_KEY: Final = "realtime_session_ended_abnormally" # SSL/TLS cipher configuration for faster handshakes # Strategy: Strongly prefer fast modern ciphers, but allow fallback to commonly supported ones @@ -699,6 +701,9 @@ STREAM_SSE_DONE_STRING: Final[str] = "[DONE]" STREAM_SSE_DATA_PREFIX: Final[str] = "data: " STREAM_SSE_KEEPALIVE_PING_CHUNK: Final[str] = 'event: ping\ndata: {"type": "ping"}\n\n' STREAM_SSE_KEEPALIVE_PING_BYTES: Final[bytes] = STREAM_SSE_KEEPALIVE_PING_CHUNK.encode("utf-8") +STREAM_FINISH_CHOICE_FIELDS: Final = ("stop_reason",) +STREAM_CHUNK_CHOICE_FIELDS: Final = ("token_ids",) +VLLM_CHOICE_FIELDS: Final = STREAM_FINISH_CHOICE_FIELDS + STREAM_CHUNK_CHOICE_FIELDS ### SPEND TRACKING ### DEFAULT_REPLICATE_GPU_PRICE_PER_SECOND: Final = get_env_float( "DEFAULT_REPLICATE_GPU_PRICE_PER_SECOND", 0.001400 @@ -968,7 +973,10 @@ OPENAI_CHAT_COMPLETION_PARAMS: Final = [ OPENAI_TRANSCRIPTION_PARAMS: Final = [ "language", + "languages", + "keywords", "response_format", + "stream", "timestamp_granularities", ] @@ -1085,6 +1093,7 @@ openai_compatible_endpoints: Final[list[str]] = [ "https://api.scx.ai/v1", "https://api.prisminference.com/v1", "https://api.reka.ai/v1", + "https://inference.runanywhere.ai/v1", "https://gigachat.devices.sberbank.ru/api/v1", "https://api.openinfer.ai/v1", "https://vanchin.streamlake.ai/api/gateway/v1/endpoints", @@ -1172,6 +1181,7 @@ openai_compatible_providers: Final[list[str]] = [ "sail", "reka", "streamlake", + "wally", ] OPENAI_AUDIO_TRANSCRIPTION_PROVIDERS: Final = frozenset({"openai"} | frozenset(openai_compatible_providers)) @@ -1663,6 +1673,9 @@ OPENAI_FINISH_REASONS: Final = [ ] HUMANLOOP_PROMPT_CACHE_TTL_SECONDS: Final = get_env_int("HUMANLOOP_PROMPT_CACHE_TTL_SECONDS", 60) # 1 minute RESPONSE_FORMAT_TOOL_NAME = "json_tool_call" # default tool name used when converting response format to tool call +RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION: Final = ( + "When you are ready to answer, call this tool with your final answer as its input. Do not reply in plain text." +) ########################### Logging Callback Constants ########################### AZURE_STORAGE_MSFT_VERSION: Final = "2019-07-07" @@ -2060,6 +2073,7 @@ SPEND_LOG_KEY_METADATA_CACHE_TTL: Final = 600 SPEND_LOG_KEY_METADATA_MISS_CACHE_TTL: Final = 30 SPEND_LOG_KEY_METADATA_CACHE_MAX_ITEMS: Final = 10000 SPEND_LOG_KEY_METADATA_QUERY_TIMEOUT_MS: Final = 5000 +SPEND_LOG_READ_STATEMENT_TIMEOUT_SECONDS: Final = 30 SPEND_LOG_KEY_METADATA_ROWS_PER_PROBE: Final = 100 # Short TTL for negative MCP access-group existence lookups. Keeps unauthenticated # callers from forcing a DB query per request for unknown names, while bounding diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index e66be233be4..3910a554905 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -6,6 +6,7 @@ import time from collections.abc import Mapping, Sequence from datetime import datetime from functools import lru_cache +from itertools import accumulate from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, TypeAlias, cast @@ -22,9 +23,14 @@ from litellm.constants import ( OPENAI_LIVE_TERMINAL_RESPONSE_EVENT_TYPES, REALTIME_METERED_USAGE_KEY, ) -from litellm.litellm_core_utils.core_helpers import as_str_mapping, billed_usage_cost +from litellm.litellm_core_utils.audio_utils.utils import normalized_audio_duration_seconds +from litellm.litellm_core_utils.core_helpers import as_str_mapping, attribute_or_none, billed_usage_cost from litellm.litellm_core_utils.cost_discount import resolve_cost_discount -from litellm.litellm_core_utils.decisions_pricing import decisions_pricing_fields, is_decisions_call_type +from litellm.litellm_core_utils.decisions_pricing import ( + decisions_pricing_fields, + decisions_request_price, + is_decisions_call_type, +) from litellm.litellm_core_utils.hidden_params import HIDDEN_PARAMS_ATTR from litellm.litellm_core_utils.llm_cost_calc.tool_call_cost_tracking import ( StandardBuiltInToolCostTracking, @@ -43,6 +49,9 @@ from litellm.litellm_core_utils.llm_cost_calc.utils import ( generic_cost_per_token, get_batch_cost_rates, get_billable_input_tokens, + get_cost_per_unit, + get_fedramp_uplift_multiplier, + get_modality_token_cost_key, get_regional_uplift_multiplier, get_service_tier_cost_key, get_token_type_cost_breakdown, @@ -319,12 +328,41 @@ def _get_additional_costs( return None -def _transcription_usage_has_token_details( +_TranscriptionRateKey: TypeAlias = Literal[ + "input_cost_per_second", + "output_cost_per_second", + "input_cost_per_audio_token", + "output_cost_per_audio_token", + "input_cost_per_token", + "output_cost_per_token", +] +_TRANSCRIPTION_TOKEN_RATE_KEYS: Final[tuple[_TranscriptionRateKey, ...]] = ( + "input_cost_per_token", + "output_cost_per_token", + "input_cost_per_audio_token", + "output_cost_per_audio_token", +) +_TRANSCRIPTION_SECOND_RATE_KEYS: Final[tuple[_TranscriptionRateKey, ...]] = ( + "input_cost_per_second", + "output_cost_per_second", +) + + +def _transcription_uses_token_pricing( + model: str, + custom_llm_provider: str | None, usage_block: Usage | None, ) -> bool: if usage_block is None: return False + model_info: Final = cached_get_model_info_helper(model=model, custom_llm_provider=custom_llm_provider) + if ( + _declared_transcription_rate(model_info, _TRANSCRIPTION_TOKEN_RATE_KEYS) is None + and _declared_transcription_rate(model_info, _TRANSCRIPTION_SECOND_RATE_KEYS) is not None + ): + return False + prompt_tokens_val: Final = getattr(usage_block, "prompt_tokens", 0) or 0 completion_tokens_val: Final = getattr(usage_block, "completion_tokens", 0) or 0 prompt_details: Final[PromptTokensDetailsWrapper | None] = getattr(usage_block, "prompt_tokens_details", None) @@ -338,13 +376,38 @@ def _transcription_usage_has_token_details( return (prompt_tokens_val > 0) or (completion_tokens_val > 0) -def _bills_provider_transcription_seconds(model: str | None, custom_llm_provider: str | None) -> bool: - if model is None or custom_llm_provider != LlmProviders.OPENAI.value: +def _bills_transcription_usage_duration(pricing_model: str | None, custom_llm_provider: str | None) -> bool: + if pricing_model is None or custom_llm_provider is None: return False + transcription_info: Final = _lookup_model_info_or_none(pricing_model, custom_llm_provider) + transcription_metadata: Final = ( + as_str_mapping(transcription_info.get("provider_specific_entry")) if transcription_info is not None else None + ) + return transcription_metadata is not None and transcription_metadata.get("transcription_usage_duration") == 1 + + +def _transcription_duration_for_cost( + completion_response: object, pricing_model: str | None, model: str | None, custom_llm_provider: str | None +) -> float: + hidden_params: Final = as_str_mapping(attribute_or_none(completion_response, "_hidden_params")) or {} + measured_duration: Final = normalized_audio_duration_seconds( + hidden_params.get("audio_transcription_duration", attribute_or_none(completion_response, "duration")) + ) + if measured_duration is not None and measured_duration > 0: + return measured_duration + provider_duration: Final = _get_transcription_usage_duration(completion_response) + if ( + provider_duration is not None + and provider_duration > 0 + and any(_bills_transcription_usage_duration(name, custom_llm_provider) for name in (pricing_model, model)) + ): + return provider_duration + if model is None or custom_llm_provider != LlmProviders.OPENAI.value: + return 0.0 transcription_config: Final = ProviderConfigManager.get_provider_audio_transcription_config( model=model.removeprefix(f"{LlmProviders.OPENAI.value}/"), provider=LlmProviders.OPENAI ) - return isinstance(transcription_config, OpenAIGPTAudioTranscriptionConfig) + return (provider_duration or 0.0) if isinstance(transcription_config, OpenAIGPTAudioTranscriptionConfig) else 0.0 OCRPricingField = Literal["ocr_cost_per_page", "ocr_cost_per_credit", "annotation_cost_per_page"] @@ -382,6 +445,14 @@ def _per_second_pricing_cost( model_info: Final = cached_get_model_info_helper(model=model, custom_llm_provider=custom_llm_provider) except Exception: # noqa: BLE001 # the lookup raises plain Exception for an unmapped model return None + return _per_second_pricing_cost_from_info(model_info, response_time_ms, audio_seconds) + + +def _per_second_pricing_cost_from_info( + model_info: ModelInfoBase, + response_time_ms: float | None, + audio_seconds: float = 0.0, +) -> tuple[float, float] | None: if _has_token_or_tiered_pricing(model_info) or not _bills_wall_clock_seconds(model_info): return None cost_per_second: Final = model_info.get("cost_per_second") @@ -404,7 +475,7 @@ def _per_second_pricing_cost( ) verbose_logger.debug( "For model=%s - cost_per_second: %s; response time: %s", - model, + model_info.get("key"), resolved_cost_per_second, response_time_ms, ) @@ -427,6 +498,7 @@ def cost_per_token( ### CUSTOM PRICING ### custom_cost_per_token: CostPerToken | None = None, custom_cost_per_second: float | None = None, + requested_model_info_override: ModelInfo | None = None, ### NUMBER OF QUERIES ### number_of_queries: int | None = None, ### USAGE OBJECT ### @@ -538,6 +610,26 @@ def cost_per_token( if response_cost is not None: return response_cost[0], response_cost[1] + if requested_model_info_override is not None: + per_second: Final = _per_second_pricing_cost_from_info( + requested_model_info_override, response_time_ms, audio_transcription_file_duration + ) + if per_second is not None: + return per_second + if custom_llm_provider == "anthropic": + return anthropic_cost_per_token( + model=model, usage=usage_block, service_tier=service_tier, model_info=requested_model_info_override + ) + return generic_cost_per_token( + model=model, + usage=usage_block, + custom_llm_provider=custom_llm_provider or "", + service_tier=service_tier, + data_residency=data_residency, + vertex_location=vertex_location, + model_info=requested_model_info_override, + ) + model_cost_ref: Final = litellm.model_cost # Only callers that explicitly pass `custom_llm_provider` get the # dedup/prefix-join treatment. When provider is omitted, preserve legacy @@ -604,6 +696,9 @@ def cost_per_token( decisions_overrides: Final = decisions_pricing_fields( litellm.model_cost.get(decisions_model_info["key"], {}) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # model cost map is dynamically loaded ) + request_price: Final = decisions_request_price(decisions_model_info, decisions_overrides) + if request_price is not None: + return request_price, 0.0 if decisions_overrides: return generic_cost_per_token( model=model, @@ -693,7 +788,7 @@ def cost_per_token( vertex_location=vertex_location, ) elif call_type == "atranscription" or call_type == "transcription": - if _transcription_usage_has_token_details(usage_block): + if _transcription_uses_token_pricing(model_without_prefix, custom_llm_provider, usage_block): return generic_cost_per_token( model=model, usage=usage_block, @@ -1039,20 +1134,19 @@ def _cost_map_model_name(model: str, custom_llm_provider: str | None, region_nam return _strip_unregistered_leading_segments(f"{provider_prefix}/{model}", region_name) -def _rule_declares_rates(model: str, custom_llm_provider: str | None) -> bool: - rule_info: Final = unmapped_model_generalization(model, custom_llm_provider) - return rule_info is not None and _cost_map_entry_prices_anything(rule_info) +def declared_cost_map_pricing(key: str, model: str, custom_llm_provider: str | None) -> Mapping[str, object]: + entry: Final = _raw_cost_map_entry(key) + if entry is None: + return unmapped_model_generalization(model, custom_llm_provider) or MappingProxyType({}) + fill_missing: Final = mapped_model_fill_missing(key, entry) + return entry if fill_missing is None else MappingProxyType({**fill_missing, **entry}) def _resolves_to_rates(model: str, custom_llm_provider: str | None) -> bool: key: Final = cached_cost_map_key(model, custom_llm_provider) - if key is None: - return False - entry: Final = _raw_cost_map_entry(key) - if entry is None: - return _rule_declares_rates(model, custom_llm_provider) - fill_missing: Final = mapped_model_fill_missing(key, entry) - return _cost_map_entry_prices_anything(entry if fill_missing is None else {**fill_missing, **entry}) + return key is not None and _cost_map_entry_prices_anything( + declared_cost_map_pricing(key, model, custom_llm_provider) + ) def _served_or_priced_requested_model( @@ -1275,6 +1369,23 @@ def _decisions_usage(usage: DecisionsUsage | OpenAIDecisionUsage) -> Usage: ) +def _get_transcription_usage_duration(completion_response: object) -> float | None: + response_fields: Final = as_str_mapping(completion_response) + usage_object: Final = ( + response_fields.get("usage") if response_fields is not None else attribute_or_none(completion_response, "usage") + ) + usage_fields: Final = as_str_mapping(usage_object) + usage_type: Final = ( + usage_fields.get("type") if usage_fields is not None else attribute_or_none(usage_object, "type") + ) + if usage_type != "duration": + return None + seconds: Final = ( + usage_fields.get("seconds") if usage_fields is not None else attribute_or_none(usage_object, "seconds") + ) + return normalized_audio_duration_seconds(seconds) + + def _extraction_usage(usage: ExtractionUsage) -> Usage: return Usage( prompt_tokens=usage.input_tokens, @@ -1668,6 +1779,7 @@ def completion_cost( ### CUSTOM PRICING ### custom_cost_per_token: CostPerToken | None = None, custom_cost_per_second: float | None = None, + requested_model_info_override: ModelInfo | None = None, optional_params: dict | None = None, custom_pricing: bool | None = None, base_model: str | None = None, @@ -1721,6 +1833,7 @@ def completion_cost( quality=quality, n=n, custom_cost_per_token=custom_cost_per_token, + requested_model_info_override=requested_model_info_override, custom_cost_per_second=custom_cost_per_second, optional_params=optional_params, custom_pricing=custom_pricing, @@ -2000,20 +2113,8 @@ def completion_cost( prompt, ) elif call_type in _TRANSCRIPTION_CALL_TYPES: - # Check _hidden_params first (duration stored there to - # avoid polluting the response body), then fall back to - # the response attribute (for verbose_json responses that - # naturally include duration from the provider). - _hidden = getattr(completion_response, "_hidden_params", {}) or {} - audio_transcription_file_duration = _hidden.get( - "audio_transcription_duration", - getattr(completion_response, "duration", 0.0), - ) or ( - completion_response.usage.seconds - if isinstance(completion_response, TranscriptionResponse) - and isinstance(completion_response.usage, TranscriptionUsageDurationObject) - and _bills_provider_transcription_seconds(requested_model, custom_llm_provider) - else 0.0 + audio_transcription_file_duration = _transcription_duration_for_cost( + completion_response, model, requested_model, custom_llm_provider ) elif call_type in _RERANK_CALL_TYPES: if completion_response is not None and isinstance(completion_response, RerankResponse): @@ -2123,6 +2224,7 @@ def completion_cost( litellm_logging_obj=litellm_logging_obj, custom_pricing_model=selected_model if custom_pricing else None, base_pricing_model=(selected_model if base_model is not None and not custom_pricing else None), + deployment_models=(base_model, requested_model), ) elif call_type == _MCP_CALL_TYPE: from litellm.proxy.mcp_server.cost_calculator import ( @@ -2206,6 +2308,7 @@ def completion_cost( region_name=None if explicit_pricing else region_name, custom_cost_per_second=custom_cost_per_second, custom_cost_per_token=custom_cost_per_token, + requested_model_info_override=requested_model_info_override, prompt_characters=prompt_characters, completion_characters=completion_characters, cache_creation_input_tokens=cache_creation_input_tokens, @@ -2351,18 +2454,20 @@ def completion_cost( raise e -def get_response_cost_from_hidden_params( - hidden_params: dict | BaseModel, -) -> float | None: - if isinstance(hidden_params, BaseModel): - _hidden_params_dict = hidden_params.model_dump() - else: - _hidden_params_dict = hidden_params +_ADDITIONAL_HEADERS: Final = TypeAdapter(Mapping[str, object]) - additional_headers: Final = _hidden_params_dict.get("additional_headers", {}) - if additional_headers and "llm_provider-x-litellm-response-cost" in additional_headers: - return _billable_header_cost(additional_headers["llm_provider-x-litellm-response-cost"]) - return None + +def get_response_cost_from_hidden_params( + hidden_params: Mapping[str, object] | BaseModel, +) -> float | None: + params: Final[Mapping[str, object]] = ( + hidden_params.model_dump() if isinstance(hidden_params, BaseModel) else hidden_params + ) + additional_headers: Final = params.get("additional_headers") + if not isinstance(additional_headers, Mapping): + return None + headers: Final = _ADDITIONAL_HEADERS.validate_python(additional_headers) + return _billable_header_cost(headers.get("llm_provider-x-litellm-response-cost")) def _billable_header_cost(value: object) -> float | None: @@ -2438,6 +2543,7 @@ def response_cost_calculator( region_name: str | None = None, custom_cost_per_token: CostPerToken | None = None, custom_cost_per_second: float | None = None, + requested_model_info_override: ModelInfo | None = None, ) -> float: """ Returns @@ -2494,6 +2600,7 @@ def response_cost_calculator( custom_pricing=custom_pricing, base_model=base_model, custom_cost_per_token=custom_cost_per_token, + requested_model_info_override=requested_model_info_override, custom_cost_per_second=custom_cost_per_second, prompt=prompt, standard_built_in_tools_params=standard_built_in_tools_params, @@ -3088,8 +3195,12 @@ def _batch_rate( "input_cost_per_video_token_batches", ], fallback: float, + *, + prompt_tokens: int = 0, ) -> float: - rate: Final = model_info.get(key) + context_key: Final = get_modality_token_cost_key(model_info, key, prompt_tokens) + context_rate: Final = get_cost_per_unit(model_info, context_key, None) + rate: Final = model_info.get(key) if context_rate is None else context_rate return fallback if rate is None else rate @@ -3207,7 +3318,9 @@ def batch_cost_calculator( text_tokens: Final = usage.completion_tokens - image_tokens total_completion_cost = text_tokens * text_rate + image_tokens * image_rate - uplift: Final = get_regional_uplift_multiplier(model_info, data_residency) + uplift: Final = get_regional_uplift_multiplier(model_info, data_residency) * get_fedramp_uplift_multiplier( + model_info, data_residency + ) if uplift != 1.0: total_prompt_cost *= uplift total_completion_cost *= uplift @@ -3216,15 +3329,35 @@ def batch_cost_calculator( return total_prompt_cost * vertex_uplift, total_completion_cost * vertex_uplift +def _standard_rate(model_info: ModelInfo, key: str, prompt_tokens: int) -> float | None: + return get_cost_per_unit(model_info, get_modality_token_cost_key(model_info, key, prompt_tokens), None) + + +def _cached_audio_batch_fallback( + model_info: ModelInfo, batch_cache_read_rate: float | None, cache_read_rate: float | None, prompt_tokens: int +) -> float: + if batch_cache_read_rate is not None: + return batch_cache_read_rate + standard_audio_rate: Final = _standard_rate(model_info, "cache_read_input_audio_token_cost", prompt_tokens) + if standard_audio_rate is not None: + return standard_audio_rate + return 0.0 if cache_read_rate is None else cache_read_rate + + def _batch_prompt_cost( usage: Usage, model_info: ModelInfo, input_rate: float, - cache_read_rate: float | None, + batch_cache_read_rate: float | None, cache_creation_rate: float | None, cache_creation_rates_by_ttl: Mapping[str, float], ) -> float: details: Final = parse_prompt_tokens_details(usage) + cache_read_rate: Final = ( + _standard_rate(model_info, "cache_read_input_token_cost", usage.prompt_tokens) + if batch_cache_read_rate is None + else batch_cache_read_rate + ) cached_tokens: Final = details["cache_hit_tokens"] if cache_read_rate is not None else 0 cached_audio_tokens: Final = details["cache_hit_audio_tokens"] if cache_read_rate is not None else 0 bills_cache_writes: Final = cache_creation_rate is not None or bool(cache_creation_rates_by_ttl) @@ -3239,12 +3372,17 @@ def _batch_prompt_cost( ) return ( text_tokens * input_rate - + audio_tokens * _batch_rate(model_info, "input_cost_per_audio_token_batches", input_rate) + + audio_tokens + * _batch_rate(model_info, "input_cost_per_audio_token_batches", input_rate, prompt_tokens=usage.prompt_tokens) + image_tokens * _batch_rate(model_info, "input_cost_per_image_token_batches", input_rate) + video_tokens * _batch_rate(model_info, "input_cost_per_video_token_batches", input_rate) + (cached_tokens - cached_audio_tokens) * (cache_read_rate or 0.0) + cached_audio_tokens - * _batch_rate(model_info, "cache_read_input_audio_token_cost_batches", cache_read_rate or 0.0) + * _batch_rate( + model_info, + "cache_read_input_audio_token_cost_batches", + _cached_audio_batch_fallback(model_info, batch_cache_read_rate, cache_read_rate, usage.prompt_tokens), + ) + ( calculate_cache_writing_cost( written_tokens, @@ -3401,8 +3539,11 @@ class RealtimeAPITokenUsageProcessor(BaseTokenUsageProcessor): def create_logging_realtime_object( usage: Usage, results: OpenAIRealtimeStreamList ) -> LiteLLMRealtimeStreamLoggingObject: + translated_input_seconds, _ = _translation_session_seconds(results) return LiteLLMRealtimeStreamLoggingObject( - usage=usage, + usage=usage.model_copy(update={"seconds": translated_input_seconds}) + if translated_input_seconds > 0 + else usage, results=results, ) @@ -3487,6 +3628,7 @@ class ResponsesWebSocketTokenUsageProcessor(BaseTokenUsageProcessor): _TRANSCRIPTION_COMPLETED_EVENT_TYPE: Final = "conversation.item.input_audio_transcription.completed" +_TRANSLATION_CLOSED_EVENT_TYPE: Final = "session.closed" class _LiveResponsePayload(BaseModel): @@ -3709,6 +3851,7 @@ def handle_realtime_stream_cost_calculation( litellm_logging_obj: LitellmLoggingObject | None = None, custom_pricing_model: str | None = None, base_pricing_model: str | None = None, + deployment_models: Sequence[str | None] = (), ) -> float: """ Handles the cost calculation for realtime stream responses. @@ -3753,6 +3896,13 @@ def handle_realtime_stream_cost_calculation( if any(r.get("type") == _TRANSCRIPTION_COMPLETED_EVENT_TYPE for r in results) else 0.0 ) + translation_cost: Final = handle_realtime_translation_cost_calculation( + results=results, + custom_llm_provider=custom_llm_provider, + litellm_model_name=litellm_model_name, + deployment_pricing_models=(custom_pricing_model, base_pricing_model, *deployment_models), + session_model=received_model, + ) live_lifecycle_event_types: Final = frozenset({"session.started", "session.usage.updated", "session.closed"}) live_session_started: Final = any(result["type"] == "session.started" for result in results) live_session_closed: Final = any(result["type"] == "session.closed" for result in results) @@ -3809,12 +3959,19 @@ def handle_realtime_stream_cost_calculation( input_cost: Final = input_cost_per_token + live_response_input_cost output_cost: Final = output_cost_per_token + live_response_output_cost total_cost: Final = ( - input_cost + output_cost + transcription_cost + live_voice_cost + audio_duration_cost + text_message_cost + input_cost + + output_cost + + transcription_cost + + translation_cost + + live_voice_cost + + audio_duration_cost + + text_message_cost ) additional_costs: Final = tuple( (cost_name, cost) for cost_name, cost in ( ("transcription_cost", transcription_cost), + ("translation_cost", translation_cost), ("live_voice_cost", live_voice_cost), ("audio_duration_cost", audio_duration_cost), ("text_message_cost", text_message_cost), @@ -3835,6 +3992,55 @@ def handle_realtime_stream_cost_calculation( return total_cost +def _translation_session_seconds(results: OpenAIRealtimeStreamList) -> tuple[float, float]: + usage_events: Final = tuple( + usage + for result in results + if (event := as_str_mapping(result)) is not None + and event.get("type") == _TRANSLATION_CLOSED_EVENT_TYPE + and (usage := as_str_mapping(event.get("usage"))) is not None + ) + input_seconds: Final = sum( + seconds + for usage in usage_events + if (seconds := normalized_audio_duration_seconds(usage.get("input_seconds"))) is not None + ) + output_seconds: Final = sum( + output_duration + for usage in usage_events + if (output_duration := normalized_audio_duration_seconds(usage.get("output_seconds"))) is not None + ) + return float(input_seconds), float(output_seconds) + + +def _translation_per_second_rates( + models: Sequence[str | None], custom_llm_provider: str +) -> tuple[float | None, float | None]: + model_infos: Final = tuple( + _lookup_model_info_or_none(model, custom_llm_provider) for model in models if model is not None + ) + return ( + _first_declared_transcription_rate(("input_cost_per_second",), model_infos), + _first_declared_transcription_rate(("output_cost_per_second",), model_infos), + ) + + +def handle_realtime_translation_cost_calculation( + results: OpenAIRealtimeStreamList, + custom_llm_provider: str, + litellm_model_name: str, + deployment_pricing_models: Sequence[str | None] = (), + session_model: str | None = None, +) -> float: + input_seconds, output_seconds = _translation_session_seconds(results) + if input_seconds <= 0 and output_seconds <= 0: + return 0.0 + input_rate, output_rate = _translation_per_second_rates( + (*deployment_pricing_models, litellm_model_name, session_model), custom_llm_provider + ) + return input_seconds * (input_rate or 0.0) + output_seconds * (output_rate or 0.0) + + def handle_realtime_transcription_cost_calculation( results: OpenAIRealtimeStreamList, custom_llm_provider: str, @@ -3850,57 +4056,77 @@ def handle_realtime_transcription_cost_calculation( - {"type": "duration", "seconds": } → priced via input_cost_per_second - {"type": "tokens", "input_tokens": ...} → priced via input/audio token cost """ - completed_events: Final = [ - cast(dict, result) for result in results if result.get("type") == _TRANSCRIPTION_COMPLETED_EVENT_TYPE - ] - if not completed_events: + configured_models: Final = tuple(accumulate(map(_session_transcription_model, results), _newer_model)) + clips: Final = tuple( + (as_str_mapping(result.get("usage")) or {}, configured) + for result, configured in zip(results, configured_models, strict=True) + if result.get("type") == _TRANSCRIPTION_COMPLETED_EVENT_TYPE + ) + if not clips: return 0.0 - model_name: Final = _get_transcription_model_name_from_results(results) or litellm_model_name - model_info: Final = _cost_map_model_info(model_name, custom_llm_provider) + fallback_model: Final = _get_transcription_model_name_from_results(results) or litellm_model_name + clip_models: Final = tuple((usage, configured or fallback_model) for usage, configured in clips) + model_infos: Final = MappingProxyType( + {model: _cost_map_model_info(model, custom_llm_provider) for model in frozenset(m for _, m in clip_models)} + ) override_info: Final = ( _cost_map_model_info(custom_pricing_model, custom_llm_provider) if custom_pricing_model is not None else None ) + return sum( + (_transcription_usage_cost(dict(usage), model_infos[model], override_info) for usage, model in clip_models), + 0.0, + ) - total_cost = 0.0 - for event in completed_events: - usage = event.get("usage") or {} - total_cost += _transcription_usage_cost(usage, model_info, override_info) - return total_cost + +_TRANSCRIPTION_SESSION_EVENT_TYPES: Final = frozenset( + {"transcription_session.created", "transcription_session.updated", "session.created", "session.updated"} +) + + +def _str_field(mapping: Mapping[str, object] | None, key: str) -> str | None: + value: Final = None if mapping is None else mapping.get(key) + return value if isinstance(value, str) and value else None + + +def _configured_transcription_model(session: Mapping[str, object]) -> str | None: + audio_input: Final = as_str_mapping((as_str_mapping(session.get("audio")) or {}).get("input")) + nested: Final = _str_field(as_str_mapping((audio_input or {}).get("transcription")), "model") + return nested or _str_field(as_str_mapping(session.get("input_audio_transcription")), "model") + + +def _session_of(result: Mapping[str, object]) -> Mapping[str, object] | None: + return as_str_mapping(result.get("session")) if result.get("type") in _TRANSCRIPTION_SESSION_EVENT_TYPES else None + + +def _session_transcription_model(result: Mapping[str, object]) -> str | None: + session: Final = _session_of(result) + return None if session is None else _configured_transcription_model(session) + + +def _newer_model(current: str | None, newer: str | None) -> str | None: + return newer or current def _get_transcription_model_name_from_results( results: OpenAIRealtimeStreamList, ) -> str | None: - """Resolve the ASR model from a transcription_session.* / session.* event.""" - for result in results: - if result.get("type") in ( - "transcription_session.created", - "transcription_session.updated", - "session.created", - "session.updated", - ): - session = cast(dict, result).get("session", {}) or {} - transcription = ((session.get("audio", {}) or {}).get("input", {}) or {}).get( - "transcription", {} - ) or session.get("input_audio_transcription", {}) - model = (transcription or {}).get("model") or session.get("model") - if model: - return model - return None + return next( + (model for result in results if (model := _str_field(_session_of(result), "model"))), + None, + ) -_TranscriptionRateKey: TypeAlias = Literal[ - "input_cost_per_second", "input_cost_per_audio_token", "input_cost_per_token", "output_cost_per_token" -] - - -def _model_info_rate(info: ModelInfo, key: _TranscriptionRateKey) -> float | None: +def _model_info_rate(info: ModelInfoBase, key: _TranscriptionRateKey) -> float | None: match key: case "input_cost_per_second": return info.get("input_cost_per_second") + case "output_cost_per_second": + return info.get("output_cost_per_second") case "input_cost_per_audio_token": return info.get("input_cost_per_audio_token") + case "output_cost_per_audio_token": + return info.get("output_cost_per_audio_token") case "input_cost_per_token": return info.get("input_cost_per_token") case "output_cost_per_token": @@ -3909,7 +4135,7 @@ def _model_info_rate(info: ModelInfo, key: _TranscriptionRateKey) -> float | Non assert_never(key) -def _declared_transcription_rate(info: ModelInfo | None, keys: tuple[_TranscriptionRateKey, ...]) -> float | None: +def _declared_transcription_rate(info: ModelInfoBase | None, keys: tuple[_TranscriptionRateKey, ...]) -> float | None: """First of ``keys`` this entry prices, read off the raw ``litellm.model_cost`` entry because ``get_model_info`` synthesizes zero token rates for entries that omit them.""" if info is None: @@ -3927,15 +4153,19 @@ def _declared_transcription_rate(info: ModelInfo | None, keys: tuple[_Transcript ) -def _transcription_rate( - keys: tuple[_TranscriptionRateKey, ...], override: ModelInfo | None, base: ModelInfo | None -) -> float: - rates: Final = (_declared_transcription_rate(info, keys) for info in (override, base)) - return next((rate for rate in rates if rate is not None), 0.0) +def _first_declared_transcription_rate( + keys: tuple[_TranscriptionRateKey, ...], infos: Sequence[ModelInfoBase | None] +) -> float | None: + rates: Final = (_declared_transcription_rate(info, keys) for info in infos) + return next((rate for rate in rates if rate is not None), None) + + +def _transcription_rate(keys: tuple[_TranscriptionRateKey, ...], *infos: ModelInfoBase | None) -> float: + return _first_declared_transcription_rate(keys, infos) or 0.0 def _transcription_usage_cost( - usage: dict, + usage: Mapping[str, object], model_info: ModelInfo | None, override_info: ModelInfo | None = None, ) -> float: @@ -3944,13 +4174,13 @@ def _transcription_usage_cost( usage_type: Final = usage.get("type") if usage_type == "duration": - seconds: Final = usage.get("seconds") or 0.0 + seconds: Final = normalized_audio_duration_seconds(usage.get("seconds")) or 0.0 return float(seconds) * _transcription_rate(("input_cost_per_second",), override_info, model_info) if usage_type == "tokens": - input_token_details: Final = usage.get("input_token_details") or {} - audio_tokens: Final = input_token_details.get("audio_tokens") or 0 - text_tokens: Final = input_token_details.get("text_tokens") or 0 - output_tokens: Final = usage.get("output_tokens") or 0 + input_token_details: Final = as_str_mapping(usage.get("input_token_details")) or {} + audio_tokens: Final = normalized_audio_duration_seconds(input_token_details.get("audio_tokens")) or 0.0 + text_tokens: Final = normalized_audio_duration_seconds(input_token_details.get("text_tokens")) or 0.0 + output_tokens: Final = normalized_audio_duration_seconds(usage.get("output_tokens")) or 0.0 audio_cost: Final = float(audio_tokens) * _transcription_rate( ("input_cost_per_audio_token", "input_cost_per_token"), override_info, model_info ) diff --git a/litellm/decisions/call.py b/litellm/decisions/call.py index 871fa8227ea..9c0e51e14ac 100644 --- a/litellm/decisions/call.py +++ b/litellm/decisions/call.py @@ -13,6 +13,7 @@ from typing_extensions import assert_never import litellm from litellm.cost_calculator import cost_map_key_prices_anything from litellm.litellm_core_utils.core_helpers import RESPONSE_COST_HEADER, normalize_drop_params +from litellm.litellm_core_utils.decisions_pricing import QUERY_PRICED_DECISIONS_PROVIDERS from litellm.litellm_core_utils.get_provider_specific_headers import ProviderSpecificHeaderUtils from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.prompt_templates.image_handling import ( @@ -555,7 +556,7 @@ def prepare_call( resolved_api_base, static_api_key = provider_config.resolve_connection( dynamic_api_base or call_api_base, dynamic_api_key or api_key ) - except ValueError as error: + except (ValueError, httpx.InvalidURL) as error: raise litellm.BadRequestError(message=str(error), model=model, llm_provider=provider) from error if resolved_api_base is None: raise litellm.BadRequestError( @@ -613,6 +614,9 @@ def prepare_call( litellm_params={ "litellm_call_id": kwargs.get("litellm_call_id"), "api_base": provider_config.get_complete_url(resolved_api_base, canonical_model), + "input_cost_per_query": ( + kwargs.get("input_cost_per_query") if provider in QUERY_PRICED_DECISIONS_PROVIDERS else None + ), }, custom_llm_provider=provider, ) @@ -787,7 +791,9 @@ def _formatted_response( case DecisionsRequestBody(): return ir_to_systemone_response(caller_response, caller_request) case OpenAIDecisionRequestBody(): - return ir_to_openai_response(caller_response, caller_request, call.requested_model) + return ir_to_openai_response( + caller_response, caller_request, call.requested_model, call.provider_config.openai_evidence_fields + ) case _: assert_never(call.request) diff --git a/litellm/exceptions.py b/litellm/exceptions.py index 12425c45b01..6662cf4a2c2 100644 --- a/litellm/exceptions.py +++ b/litellm/exceptions.py @@ -867,6 +867,7 @@ class BadGatewayError(openai.APIStatusError): class InternalServerError(openai.InternalServerError): response: httpx.Response # pyright: ignore[reportIncompatibleVariableOverride] # LiteLLM constructs an HTTPX response request: httpx.Request # pyright: ignore[reportIncompatibleVariableOverride] # LiteLLM constructs an HTTPX request + provider_status_code: int | None def __init__( self, @@ -878,8 +879,10 @@ class InternalServerError(openai.InternalServerError): max_retries: int | None = None, num_retries: int | None = None, body: object | None = None, + provider_status_code: int | None = None, ): self.status_code = 500 + self.provider_status_code = provider_status_code self.message = f"litellm.InternalServerError: {message}" self.llm_provider = llm_provider self.model = model diff --git a/litellm/images/main.py b/litellm/images/main.py index 165543aadba..79bb07fc394 100644 --- a/litellm/images/main.py +++ b/litellm/images/main.py @@ -28,8 +28,7 @@ from litellm.litellm_core_utils.mock_functions import mock_image_generation from litellm.llms.base_llm import BaseImageEditConfig, BaseImageGenerationConfig from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler from litellm.llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler -from litellm.llms.custom_llm import CustomLLM -from litellm.utils import exception_type, filter_out_litellm_params, get_litellm_params +from litellm.utils import exception_type, filter_out_litellm_params, get_litellm_params, header_auth_params #################### Initialize provider clients #################### llm_http_handler: BaseLLMHTTPHandler = BaseLLMHTTPHandler() @@ -68,6 +67,10 @@ from litellm.utils import ( ) _PROVIDER_ROUTING_HINTS: Final = TypeAdapter(ProviderRoutingHints) +_OPTIONAL_OBJECT_DICT_ADAPTER: Final = TypeAdapter[dict[str, object] | None](dict[str, object] | None) +_OPTIONAL_STRING_DICT_ADAPTER: Final = TypeAdapter[dict[str, str] | None](dict[str, str] | None) +_OBJECT_DICT_ADAPTER: Final = TypeAdapter[dict[str, object]](dict[str, object]) +_STRING_DICT_ADAPTER: Final = TypeAdapter[dict[str, str]](dict[str, str]) _PROVIDERS_RESOLVING_THEIR_OWN_IMAGE_BASE: Final = ( LlmProviders.DASHSCOPE, LlmProviders.QWENCLOUD, @@ -94,8 +97,8 @@ def _chatgpt_image_params(kwargs: Mapping[str, object]) -> GenericLiteLLMParams: from litellm.responses.utils import ResponsesAPIRequestUtils headers: Final = ResponsesAPIRequestUtils.merge_client_forwarded_headers( - TypeAdapter[dict[str, object] | None](dict[str, object] | None).validate_python(kwargs.get("extra_headers")), - TypeAdapter[dict[str, str] | None](dict[str, str] | None).validate_python(kwargs.get("headers")), + _OPTIONAL_OBJECT_DICT_ADAPTER.validate_python(kwargs.get("extra_headers")), + _OPTIONAL_STRING_DICT_ADAPTER.validate_python(kwargs.get("headers")), ) return GenericLiteLLMParams.model_validate({**kwargs, "extra_headers": headers}) @@ -168,7 +171,7 @@ async def aimage_generation(*args, **kwargs) -> ImageResponse: custom_llm_provider=provider_hints.get("custom_llm_provider"), api_base=provider_hints.get("api_base"), litellm_params=( - _chatgpt_image_params(TypeAdapter(dict[str, object]).validate_python(kwargs)) + _chatgpt_image_params(_OBJECT_DICT_ADAPTER.validate_python(kwargs)) if provider_hints.get("custom_llm_provider") == "chatgpt" or (isinstance(model, str) and model.startswith("chatgpt/")) else None @@ -300,7 +303,7 @@ def image_generation( headers.update(extra_headers) model_response: ImageResponse = litellm.utils.ImageResponse() chatgpt_params: Final = ( - _chatgpt_image_params(TypeAdapter(dict[str, object]).validate_python({**kwargs, "api_key": api_key})) + _chatgpt_image_params(_OBJECT_DICT_ADAPTER.validate_python({**kwargs, "api_key": api_key})) if custom_llm_provider == "chatgpt" or (model is not None and model.startswith("chatgpt/")) else None ) @@ -583,7 +586,7 @@ def image_generation( _chatgpt_image_headers( model, chatgpt_params.model_copy(update={"api_key": dynamic_api_key or api_key}), - TypeAdapter(dict[str, str]).validate_python(headers), + _STRING_DICT_ADAPTER.validate_python(headers), ) ) if chatgpt_params is not None @@ -608,10 +611,7 @@ def image_generation( ) elif custom_llm_provider in litellm._custom_providers: # Assume custom LLM provider # Get the Custom Handler - custom_handler: CustomLLM | None = None - for item in litellm.custom_provider_map: - if item["provider"] == custom_llm_provider: - custom_handler = item["custom_handler"] + custom_handler: Final = ProviderConfigManager.get_custom_llm_handler(custom_llm_provider) if custom_handler is None: raise LiteLLMUnknownProvider(model=model, custom_llm_provider=custom_llm_provider) @@ -915,10 +915,7 @@ def image_edit( # Check for custom provider if custom_llm_provider in litellm._custom_providers: - custom_handler: CustomLLM | None = None - for item in litellm.custom_provider_map: - if item["provider"] == custom_llm_provider: - custom_handler = item["custom_handler"] + custom_handler: Final = ProviderConfigManager.get_custom_llm_handler(custom_llm_provider) if custom_handler is None: raise LiteLLMUnknownProvider(model=model, custom_llm_provider=custom_llm_provider) @@ -995,10 +992,15 @@ def image_edit( or custom_llm_provider == "azure" or custom_llm_provider in litellm.openai_compatible_providers ): + dropped_form_params: Final = header_auth_params(custom_llm_provider) image_edit_request_params.update( flatten_form_field_values( - non_default_params, - extra_body if isinstance(extra_body, dict) else None, + {key: value for key, value in non_default_params.items() if key not in dropped_form_params}, + ( + {key: value for key, value in extra_body.items() if key not in dropped_form_params} + if isinstance(extra_body, dict) + else None + ), ) ) diff --git a/litellm/integrations/anthropic_cache_control_hook.py b/litellm/integrations/anthropic_cache_control_hook.py index c05407b7972..4e473c2f3f0 100644 --- a/litellm/integrations/anthropic_cache_control_hook.py +++ b/litellm/integrations/anthropic_cache_control_hook.py @@ -9,24 +9,29 @@ Supported for both `v1/chat/completions` (via the prompt-management hook) and """ +import bisect import copy import itertools import os import re from collections.abc import Callable, Container, Iterable, Iterator, Mapping, Sequence +from functools import lru_cache from typing import TYPE_CHECKING, Any, Final, TypeAlias, TypeVar, cast from urllib.parse import urlparse -from pydantic import TypeAdapter, ValidationError +from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError from litellm._logging import verbose_logger +from litellm.exceptions import UnsupportedParamsError from litellm.integrations.custom_logger import CustomLogger from litellm.integrations.custom_prompt_management import CustomPromptManagement from litellm.integrations.prompt_management_base import PromptManagementClient -from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap from litellm.litellm_core_utils.prompt_templates.common_utils import ( + PROMPT_CACHE_BREAKPOINT_DROP_PARAMS_HINT, cache_control_as_prompt_cache_breakpoint, + prompt_cache_breakpoint_as_cache_control, with_prompt_cache_breakpoint, + without_prompt_cache_breakpoints, ) from litellm.litellm_core_utils.prompt_templates.factory import ( tool_call_ids_answered_by_client, @@ -73,7 +78,7 @@ MAX_CACHE_CONTROL_BLOCKS: Final = 4 CACHE_BREAKPOINT_KEYS: Final = ("cache_control", "prompt_cache_breakpoint") OPENAI_PROMPT_CACHE_BREAKPOINT_MIN_GPT_VERSION: Final = (5, 6) -_GPT_VERSION_PATTERN: Final = re.compile(r"^gpt-(\d+)(?:\.(\d+))?") +_GPT_VERSION_PATTERN: Final = re.compile(r"^gpt-(\d+)(?:\.(\d+)|-(0|[1-9]\d?)(?![\da-z]))?") _FINE_TUNED_BASE_PATTERN: Final = re.compile(r"^ft:([^:]+)") _O_SERIES_PATTERN: Final = re.compile(r"^o\d+(?:-|$)") OPENAI_PROMPT_CACHE_BREAKPOINT_BLOCK_TYPES: Final = frozenset( @@ -85,8 +90,40 @@ _OBJECT_MAPPING_ADAPTER: Final = TypeAdapter(dict[object, object]) _OBJECT_LIST_ADAPTER: Final = TypeAdapter(list[object]) _CONTENT_PART_ADAPTER: Final = TypeAdapter(dict[str, object]) _ATTRIBUTE_VALUE: Final = TypeAdapter(object) +_MODEL_INFO_ADAPTER: Final = TypeAdapter(Mapping[str, object]) AllToolParamValues = ChatCompletionToolParam | AllAnthropicToolsValues +CostMap: TypeAlias = Mapping[str, Mapping[str, object]] + + +def routed_model_info(value: object) -> Mapping[str, object] | None: + try: + return _MODEL_INFO_ADAPTER.validate_python(value) + except ValidationError: + return None + + +def _live_cost_map_unless(model_cost: CostMap | None) -> CostMap: + import litellm + + if model_cost is not None: + return model_cost + return cast(CostMap, litellm.model_cost) # cast-ok: the live map holds catalog entries + + +def declared_prompt_cache_breakpoint(model_info: Mapping[str, object] | None) -> bool | None: + declared: Final = None if model_info is None else model_info.get("supports_prompt_cache_breakpoint") + return declared if isinstance(declared, bool) else None + + +def routed_cost_map() -> CostMap: + from litellm.utils import catalog_with_runtime_registrations + + return catalog_with_runtime_registrations() + + +def _catalog_unless_unrouted(model_info: Mapping[str, object] | None) -> CostMap | None: + return None if model_info is None else routed_cost_map() def _validated_object_mapping(value: object) -> dict[object, object] | None: @@ -295,6 +332,12 @@ def _part_with_cache_control_renamed(part: object) -> object: return cache_control_as_prompt_cache_breakpoint(_CONTENT_PART_ADAPTER.validate_python(part)) +def _part_with_prompt_cache_breakpoint_renamed(part: object, drop_params: bool) -> object: + if not _carries_prompt_cache_breakpoint(part): + return part + return prompt_cache_breakpoint_as_cache_control(_CONTENT_PART_ADAPTER.validate_python(part), drop_params) + + def configured_injection_points(value: object) -> Sequence[CacheControlInjectionPoint]: if not isinstance(value, (list, tuple)): return () @@ -314,19 +357,27 @@ def _served_provider_for_model(model: str, api_base: object = None) -> str | Non return provider -def supports_openai_prompt_cache_breakpoint(model: str, custom_llm_provider: str | None = None) -> bool: - return openai_prompt_cache_breakpoint_support(model, custom_llm_provider) is True +def supports_openai_prompt_cache_breakpoint( + model: str, custom_llm_provider: str | None = None, model_info: Mapping[str, object] | None = None +) -> bool: + return openai_prompt_cache_breakpoint_support(model, custom_llm_provider, model_info) is True -def openai_prompt_cache_breakpoint_support(model: str, custom_llm_provider: str | None = None) -> bool | None: +def openai_prompt_cache_breakpoint_support( + model: str, custom_llm_provider: str | None = None, model_info: Mapping[str, object] | None = None +) -> bool | None: + declared: Final = declared_prompt_cache_breakpoint(model_info) + if declared is not None: + return declared + model_cost: Final = _catalog_unless_unrouted(model_info) hosted_flag: Final = ( None if custom_llm_provider is None - else _hosted_openai_dialect_flag(model, custom_llm_provider, _served_provider_for_model) + else _hosted_openai_dialect_flag(model, custom_llm_provider, _served_provider_for_model, model_cost) ) if hosted_flag is not None: return hosted_flag - model_map_flag: Final = _model_map_prompt_cache_breakpoint_flag(model) + model_map_flag: Final = _model_map_prompt_cache_breakpoint_flag(model, model_cost) if model_map_flag is not None: return model_map_flag fine_tuned_base: Final = _FINE_TUNED_BASE_PATTERN.match(model.rsplit("/", 1)[-1]) @@ -335,6 +386,35 @@ def openai_prompt_cache_breakpoint_support(model: str, custom_llm_provider: str return _named_model_breakpoint_support(model) +class _DeclaredBaseModels(BaseModel): + model_config = ConfigDict(frozen=True, extra="ignore", from_attributes=True) + + base_model: object = None + model_info: object = None + + def names(self) -> tuple[str, ...]: + model_info: Final = _validated_object_mapping(self.model_info) or {} + candidates: Final = (self.base_model, model_info.get("base_model")) + return tuple(name for name in candidates if isinstance(name, str) and name) + + +def deployment_model_info(litellm_params: object) -> Mapping[str, object] | None: + return routed_model_info(_DeclaredBaseModels.model_validate(litellm_params).model_info) + + +def deployment_prompt_cache_breakpoint_support( + model: str, custom_llm_provider: str, litellm_params: object +) -> bool | None: + """``openai_prompt_cache_breakpoint_support`` for a deployment, read from its declared base model first.""" + declared: Final = _DeclaredBaseModels.model_validate(litellm_params) + model_info: Final = routed_model_info(declared.model_info) + supports: Final = ( + openai_prompt_cache_breakpoint_support(name, custom_llm_provider, model_info) + for name in dict.fromkeys((*declared.names(), model)) + ) + return next((support for support in supports if support is not None), None) + + def _named_model_breakpoint_support(model: str) -> bool | None: bare_model: Final = model.rsplit("/", 1)[-1].lower() if _O_SERIES_PATTERN.match(bare_model) is not None: @@ -342,15 +422,14 @@ def _named_model_breakpoint_support(model: str) -> bool | None: version_match: Final = _GPT_VERSION_PATTERN.match(bare_model) if version_match is None: return None - version: Final = (int(version_match.group(1)), int(version_match.group(2) or 0)) + version: Final = (int(version_match.group(1)), int(version_match.group(2) or version_match.group(3) or 0)) return version >= OPENAI_PROMPT_CACHE_BREAKPOINT_MIN_GPT_VERSION -def _model_map_prompt_cache_breakpoint_flag(model: str) -> bool | None: - import litellm - - entries: Final = (litellm.model_cost.get(key) for key in (model, model.rsplit("/", 1)[-1])) - flags: Final = (entry.get("supports_prompt_cache_breakpoint") for entry in entries if isinstance(entry, dict)) +def _model_map_prompt_cache_breakpoint_flag(model: str, model_cost: CostMap | None = None) -> bool | None: + cost_map: Final = _live_cost_map_unless(model_cost) + entries: Final = (cost_map.get(key) for key in (model, model.rsplit("/", 1)[-1])) + flags: Final = (entry.get("supports_prompt_cache_breakpoint") for entry in entries if isinstance(entry, Mapping)) return next((flag is True for flag in flags if flag is not None), None) @@ -366,7 +445,7 @@ def _hosted_openai_dialect_flag( model: str, custom_llm_provider: str | None, resolve_provider: Callable[[str], str | None], - model_cost: Mapping[str, Mapping[str, object]] | None = None, + model_cost: CostMap | None = None, ) -> bool | None: """ Explicit opt-in for an OpenAI-shaped deployment served by another provider. @@ -383,13 +462,7 @@ def _hosted_openai_dialect_flag( row of the same name, so an exact entry only speaks for a deployment when it is keyed for that deployment's provider. """ - import litellm - - cost_map: Final = ( - cast(Mapping[str, Mapping[str, object]], litellm.model_cost) # cast-ok: the live map holds catalog entries - if model_cost is None - else model_cost - ) + cost_map: Final = _live_cost_map_unless(model_cost) exact_entry: Final = cost_map.get(model) exact_provider: Final = exact_entry.get("litellm_provider") if isinstance(exact_entry, Mapping) else None if custom_llm_provider is None and (exact_provider == "openai" or ("/" not in model and exact_provider is None)): @@ -399,10 +472,16 @@ def _hosted_openai_dialect_flag( return None if isinstance(exact_entry, Mapping) and exact_provider == provider: return _hosted_entry_flag(exact_entry, lambda: provider) + entries: Final = (cost_map.get(candidate) for candidate in _provider_cost_map_keys(model, provider)) + flags: Final = (_hosted_entry_flag(entry, lambda: provider) for entry in entries if isinstance(entry, Mapping)) + return next((flag for flag in flags if flag is not None), None) + + +def _provider_cost_map_keys(model: str, provider: str) -> tuple[str, ...]: from litellm.utils import get_potential_model_names names: Final = get_potential_model_names(model, provider) - candidates: Final = ( + return ( names["combined_model_name"], names["region_free_combined_model_name"], names["split_model"], @@ -410,9 +489,60 @@ def _hosted_openai_dialect_flag( names["stripped_model_name"], names["provider_prefixed_model_name"], ) - entries: Final = (cost_map.get(candidate) for candidate in candidates) - flags: Final = (_hosted_entry_flag(entry, lambda: provider) for entry in entries if isinstance(entry, Mapping)) - return next((flag for flag in flags if flag is not None), None) + + +def _cost_map_lists_model_for_provider(model: str, provider: str, model_cost: CostMap) -> bool: + entries: Final = (model_cost.get(key) for key in (model, *_provider_cost_map_keys(model, provider))) + return any(isinstance(entry, Mapping) and entry.get("litellm_provider") == provider for entry in entries) + + +_PROVIDERS_READING_THE_FLAG_AS_CACHE_POINT: Final = frozenset(("bedrock", "bedrock_converse")) +_PROVIDERS_HOSTING_OPENAIS_API: Final = frozenset(("azure", "azure_ai", "bedrock_mantle")) + + +def _declared_hosted_flag( + declared: bool, model: str, provider: str | None, model_cost: CostMap, deployment_provider: object +) -> bool | None: + """ + A deployment's own ``supports_prompt_cache_breakpoint`` picks OpenAI's breakpoint only where the + request goes out OpenAI-shaped. Bedrock reads the same flag on every route as whether Converse takes + a ``cachePoint``, and a provider building Anthropic messages takes ``cache_control``, so both keep + the Anthropic mark. A gateway or self-hosted server (OpenRouter, a LiteLLM proxy, vLLM) may pass + the request on to Anthropic, so there the flag only picks OpenAI's breakpoint for a model the cost + map, or the deployment's own ``litellm_provider``, lists under that provider. + """ + if provider is None or provider == "openai": + return None + return ( + declared + and provider not in _PROVIDERS_READING_THE_FLAG_AS_CACHE_POINT + and ( + provider in _PROVIDERS_HOSTING_OPENAIS_API + or deployment_provider == provider + or _cost_map_lists_model_for_provider(model, provider, model_cost) + ) + and _sends_openai_shaped_chat(model, provider) + ) + + +@lru_cache(maxsize=512) +def _sends_openai_shaped_chat(model: str, custom_llm_provider: str) -> bool: + from litellm.exceptions import BadRequestError + from litellm.litellm_core_utils.get_llm_provider_logic import resolve_model_and_provider_for_metadata + from litellm.llms.azure.chat.gpt_transformation import AzureOpenAIConfig + from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig + from litellm.llms.openai.openai import OpenAIConfig + from litellm.types.utils import LlmProviders + from litellm.utils import ProviderConfigManager + + try: + served_model, provider = resolve_model_and_provider_for_metadata(model, custom_llm_provider) + chat_config: Final = ProviderConfigManager.get_provider_chat_config( + model=served_model, provider=LlmProviders(provider) + ) + except (BadRequestError, ValueError): + return False + return isinstance(chat_config, (OpenAIGPTConfig, OpenAIConfig, AzureOpenAIConfig)) def targets_openai_api(api_base: object) -> bool: @@ -432,6 +562,10 @@ def _carries_cache_breakpoint(block: object) -> bool: return any(_attribute_or_key(block, key) is not None for key in CACHE_BREAKPOINT_KEYS) +def _carries_cache_control(block: object) -> bool: + return _attribute_or_key(block, "cache_control") is not None + + def _attribute_or_key(value: object, key: str) -> object | None: if hasattr(value, key): return _ATTRIBUTE_VALUE.validate_python(getattr(value, key)) @@ -511,6 +645,12 @@ def _builds_anthropic_messages(model: str, custom_llm_provider: str | None) -> b return isinstance(chat_config, AnthropicConfig) and not isinstance(chat_config, OpenAIGPTConfig) +def _translates_prompt_cache_breakpoint(model: str, custom_llm_provider: str | None) -> bool: + return (custom_llm_provider or _served_provider_for_model(model)) == "bedrock" or _builds_anthropic_messages( + model, custom_llm_provider + ) + + def _custom_llm_provider(non_default_params: Mapping[str, object], point: Mapping[str, object]) -> str | None: provider: Final = non_default_params.get("custom_llm_provider") or point.get(CUSTOM_LLM_PROVIDER_STAMP) return provider if isinstance(provider, str) else None @@ -554,10 +694,79 @@ def _accepts_prompt_cache_breakpoint(block: object) -> bool: return isinstance(block, dict) and block.get("type") in OPENAI_PROMPT_CACHE_BREAKPOINT_BLOCK_TYPES +def _carries_prompt_cache_breakpoint(block: object) -> bool: + return _accepts_prompt_cache_breakpoint(block) and _attribute_or_key(block, "prompt_cache_breakpoint") is not None + + def _may_carry_prompt_cache_breakpoint(message: Mapping[str, object]) -> bool: return message.get("role") != "assistant" +def _tool_result_carries_prompt_cache_breakpoint(message: Mapping[str, object]) -> bool: + return message.get("role") == "tool" and any( + _carries_prompt_cache_breakpoint(part) for part in _as_object_list(message.get("content")) or () + ) + + +def _part_without_prompt_cache_breakpoint(part: object) -> object: + if not _carries_prompt_cache_breakpoint(part): + return part + return { + key: value + for key, value in _CONTENT_PART_ADAPTER.validate_python(part).items() + if key != "prompt_cache_breakpoint" + } + + +def _tool_result_without_prompt_cache_breakpoints(message: AllMessageValues) -> AllMessageValues: + if not _tool_result_carries_prompt_cache_breakpoint(message): + return message + parts: Final = _as_object_list(_attribute_or_key(message, "content")) or [] + return cast( # cast-ok: the same tool message with its part marks removed + AllMessageValues, {**message, "content": [_part_without_prompt_cache_breakpoint(part) for part in parts]} + ) + + +def _created_cache_control(original: object, translated: object) -> bool: + return ( + _attribute_or_key(original, "cache_control") is None + and _attribute_or_key(translated, "cache_control") is not None + ) + + +def _created_cache_controls(original: object, translated: object) -> tuple[bool, ...]: + if translated is original: + return () + original_parts: Final = _as_object_list(_attribute_or_key(original, "content")) or [] + translated_parts: Final = _as_object_list(_attribute_or_key(translated, "content")) or [] + return tuple(_created_cache_control(before, after) for before, after in zip(original_parts, translated_parts)) + + +def _part_without_cache_control(part: object) -> object: + return {key: value for key, value in _CONTENT_PART_ADAPTER.validate_python(part).items() if key != "cache_control"} + + +def _message_dropping_created_cache_controls_between( + message: AllMessageValues, created: Sequence[bool], marks_before: int, first_dropped: int, first_kept_after: int +) -> AllMessageValues: + if not any(created): + return message + parts: Final = _as_object_list(_attribute_or_key(message, "content")) or [] + ordinals: Final = itertools.accumulate((int(flag) for flag in created), initial=marks_before) + return cast( # cast-ok: the same message with its middle translated marks removed + AllMessageValues, + { + **message, + "content": [ + _part_without_cache_control(part) + if is_created and first_dropped <= ordinal < first_kept_after + else part + for part, is_created, ordinal in zip(parts, created, ordinals) + ], + }, + ) + + # Set by a caller whose message list is not the one that goes upstream -- today the # Responses API layer, whose `instructions` only becomes a system message further down. # Tells this hook to hand role-targeted points to the pass holding the final messages @@ -643,9 +852,6 @@ class AnthropicCacheControlHook(CustomPromptManagement): if not injection_points: return model, messages, non_default_params - # Create a deep copy of messages to avoid modifying the original list - processed_messages = copy.deepcopy(messages) - message_points: Final = tuple( cast(CacheControlMessageInjectionPoint, point) for point in injection_points @@ -653,18 +859,26 @@ class AnthropicCacheControlHook(CustomPromptManagement): ) remaining_points: Final = tuple(point for point in injection_points if point.get("location") != "message") - custom_llm_provider: Final = _custom_llm_provider(non_default_params, injection_points[0]) + request_params: Final = cast(Mapping[str, object], non_default_params) # cast-ok: base hook's bare dict + custom_llm_provider: Final = _custom_llm_provider(request_params, injection_points[0]) stamped_dialect: Final = injection_points[0].get("_litellm_openai_dialect") + model_info: Final = routed_model_info(request_params.get("model_info")) openai_dialect: Final = ( stamped_dialect if isinstance(stamped_dialect, bool) else AnthropicCacheControlHook.targets_openai_prompt_cache_breakpoint( model, custom_llm_provider, - non_default_params.get("api_base") or non_default_params.get("base_url"), - non_default_params.get("prompt_cache_options"), + request_params.get("api_base") or request_params.get("base_url"), + request_params.get("prompt_cache_options"), + model_info, ) ) + processed_messages = copy.deepcopy( + [without_prompt_cache_breakpoints(message) for message in messages] + if not openai_dialect and message_points and _translates_prompt_cache_breakpoint(model, custom_llm_provider) + else messages + ) # A provisional message list defers every role-targeted point to the pass holding # the final one: a role with no message here may have one there, and settling all # of them in one pass is what lets config order decide the shared breakpoint @@ -733,32 +947,35 @@ class AnthropicCacheControlHook(CustomPromptManagement): custom_llm_provider: str | None, api_base: object = None, prompt_cache_options: object = None, + model_info: Mapping[str, object] | None = None, ) -> bool: if model is None: return False - hosted_flag: Final = _hosted_openai_dialect_flag( - model, custom_llm_provider, lambda name: AnthropicCacheControlHook._resolve_provider(name, api_base) + declared: Final = declared_prompt_cache_breakpoint(model_info) + hosted_flag: Final = ( + _hosted_openai_dialect_flag( + model, + custom_llm_provider, + lambda name: AnthropicCacheControlHook._resolve_provider(name, api_base), + _catalog_unless_unrouted(model_info), + ) + if declared is None + else _declared_hosted_flag( + declared, + model, + custom_llm_provider or AnthropicCacheControlHook._resolve_provider(model, api_base), + routed_cost_map(), + None if model_info is None else model_info.get("litellm_provider"), + ) ) if hosted_flag is not None: - return hosted_flag - if not supports_openai_prompt_cache_breakpoint(model): + return hosted_flag and not _translates_prompt_cache_breakpoint(model, custom_llm_provider) + if not supports_openai_prompt_cache_breakpoint(model, model_info=model_info): return False if (custom_llm_provider or AnthropicCacheControlHook._resolve_provider(model)) != "openai": return False return prompt_cache_options is not None or targets_openai_api(api_base) - @staticmethod - def catalog_targets_openai_prompt_cache_breakpoint(model: str, custom_llm_provider: str) -> bool: - return ( - _hosted_openai_dialect_flag( - model, - custom_llm_provider, - AnthropicCacheControlHook._resolve_provider, - GetModelCostMap.loaded_model_cost_map(), - ) - is True - ) - @staticmethod def _resolve_provider(model: str, api_base: object = None) -> str | None: return _served_provider_for_model(model, api_base) @@ -805,6 +1022,19 @@ class AnthropicCacheControlHook(CustomPromptManagement): ) return int(wire_cache_control is not None) + tool_blocks + envelope_blocks + @staticmethod + def tools_keeping_cache_control_on_chat(tools: object) -> tuple[object, ...]: + return tuple( + tool for tool in _as_object_list(tools) or () if not _chat_transform_drops_tool_cache_control(tool) + ) + + @staticmethod + def count_chat_external_cache_breakpoints(optional_params: object) -> int: + params: Final = _validated_object_mapping(optional_params) or {} + return AnthropicCacheControlHook.count_external_cache_breakpoints( + _as_object_list(params.get("tools")), params.get("cache_control") + ) + @staticmethod def count_external_cache_breakpoints_on_messages_route( tools: Iterable[object] | None, cache_control: object, request_kwargs: object @@ -960,6 +1190,16 @@ class AnthropicCacheControlHook(CustomPromptManagement): ) return message_count + content_count + tool_call_count + @staticmethod + def count_converse_cache_points(message: AllMessageValues) -> int: + content: Final = _as_object_list(_attribute_or_key(message, "content")) + tool_calls: Final = _as_object_list(_attribute_or_key(message, "tool_calls")) or [] + marked_parts: Final = sum(1 for block in content or () if _carries_cache_control(block)) + marked_tool_calls: Final = sum(1 for tool_call in tool_calls if _carries_cache_control(tool_call)) + if message.get("role") == "tool": + return int(_carries_cache_control(message) or marked_parts > 0) + return (int(_carries_cache_control(message)) if content is None else marked_parts) + marked_tool_calls + @staticmethod def _message_has_cache_control(message: AllMessageValues, answered_tool_ids: Container[str]) -> bool: """Return True if the message already carries any cache_control.""" @@ -1018,6 +1258,92 @@ class AnthropicCacheControlHook(CustomPromptManagement): return renamed return AnthropicCacheControlHook._insert_prompt_cache_breakpoint_in_message(renamed) + @staticmethod + def prompt_cache_breakpoints_as_cache_control(message: AllMessageValues, drop_params: bool) -> AllMessageValues: + """Every OpenAI ``prompt_cache_breakpoint`` on a part OpenAI accepts one on moved to Anthropic's + ``cache_control``. Marks with no OpenAI slot are left for the caller to strip.""" + if not _may_carry_prompt_cache_breakpoint(message): + return message + parts: Final = _as_object_list(_attribute_or_key(message, "content")) + if parts is None or not any(_carries_prompt_cache_breakpoint(part) for part in parts): + return message + return cast( # cast-ok: the same message with its part marks renamed + AllMessageValues, + {**message, "content": [_part_with_prompt_cache_breakpoint_renamed(part, drop_params) for part in parts]}, + ) + + @staticmethod + def prompt_cache_breakpoints_dropped_from_tool_results( + messages: Sequence[AllMessageValues], drop_params: bool, model: str + ) -> tuple[AllMessageValues, ...]: + if not any(_tool_result_carries_prompt_cache_breakpoint(message) for message in messages): + return tuple(messages) + if not drop_params: + raise UnsupportedParamsError( + message=( + f"{model} takes no cache breakpoint on a tool result, so prompt_cache_breakpoint on a tool " + f"message has no equivalent. Remove it, or {PROMPT_CACHE_BREAKPOINT_DROP_PARAMS_HINT} to drop it." + ), + status_code=400, + ) + verbose_logger.debug("Dropping prompt_cache_breakpoint from tool results for %s under drop_params", model) + return tuple(_tool_result_without_prompt_cache_breakpoints(message) for message in messages) + + @staticmethod + def prompt_cache_breakpoints_as_capped_cache_control( + messages: Sequence[AllMessageValues], + drop_params: bool, + sent_breakpoints: Callable[[AllMessageValues], int], + external_breakpoints: Callable[[], int], + ) -> tuple[AllMessageValues, ...]: + """``prompt_cache_breakpoints_as_cache_control`` over the whole request, held to the provider's + breakpoint cap, counting each message by the breakpoints ``sent_breakpoints`` says its provider sends. + Under ``drop_params`` the first and last translated marks fill the slots the client's own + ``cache_control`` marks leave, the first half taking the odd slot, so the stable prefix and the newest + turns stay cached, and without it a request over the cap is rejected.""" + translated: Final = tuple( + AnthropicCacheControlHook.prompt_cache_breakpoints_as_cache_control(message, drop_params) + for message in messages + ) + if all(after is before for before, after in zip(messages, translated)): + return translated + created: Final = tuple(_created_cache_controls(before, after) for before, after in zip(messages, translated)) + created_marks: Final = sum(sum(flags) for flags in created) + if created_marks == 0: + return translated + external: Final = external_breakpoints() + breakpoints: Final = sum(map(sent_breakpoints, translated)) + external + excess: Final = breakpoints - MAX_CACHE_CONTROL_BLOCKS + if excess <= 0: + return translated + if not drop_params: + raise UnsupportedParamsError( + message=( + f"This model takes at most {MAX_CACHE_CONTROL_BLOCKS} cache breakpoints per request, and this " + f"request has {breakpoints} once its prompt_cache_breakpoint marks are translated. Remove {excess} " + f"of them, or {PROMPT_CACHE_BREAKPOINT_DROP_PARAMS_HINT} to keep the first and last of them." + ), + status_code=400, + ) + verbose_logger.debug("Dropping the middle prompt_cache_breakpoint marks past the cap under drop_params") + marks_before: Final = tuple(itertools.accumulate((sum(flags) for flags in created), initial=0)) + + def capped_request(kept_marks: int) -> tuple[AllMessageValues, ...]: + first_dropped: Final = (kept_marks + 1) // 2 + first_kept_after: Final = created_marks - kept_marks // 2 + return tuple( + _message_dropping_created_cache_controls_between( + message, flags, before, first_dropped, first_kept_after + ) + for message, flags, before in zip(translated, created, marks_before) + ) + + def over_cap(kept_marks: int) -> bool: + return sum(map(sent_breakpoints, capped_request(kept_marks))) + external > MAX_CACHE_CONTROL_BLOCKS + + first_over_cap: Final = bisect.bisect_left(range(max(0, created_marks - excess) + 1), True, key=over_cap) + return capped_request(max(0, first_over_cap - 1)) + @staticmethod def _insert_prompt_cache_breakpoint_in_message(message: AllMessageValues) -> AllMessageValues: if not _may_carry_prompt_cache_breakpoint(message): @@ -1157,6 +1483,7 @@ class AnthropicCacheControlHook(CustomPromptManagement): custom_llm_provider: str | None, api_base: object, prompt_cache_options: object, + model_info: Mapping[str, object] | None = None, ) -> Sequence[Mapping[str, object]]: """Carry onto the points what the prompt-management hook never receives. @@ -1168,7 +1495,7 @@ class AnthropicCacheControlHook(CustomPromptManagement): across requests. """ with_dialect: Final = AnthropicCacheControlHook._stamped_with_dialect( - points, model, custom_llm_provider, api_base, prompt_cache_options + points, model, custom_llm_provider, api_base, prompt_cache_options, model_info ) stamped_earlier: Final = any(EXTERNAL_BREAKPOINTS_STAMP in point for point in with_dialect) if external_breakpoints == 0 and not stamped_earlier: @@ -1182,14 +1509,17 @@ class AnthropicCacheControlHook(CustomPromptManagement): custom_llm_provider: str | None, api_base: object, prompt_cache_options: object, + model_info: Mapping[str, object] | None = None, ) -> Sequence[Mapping[str, object]]: - if not AnthropicCacheControlHook._may_target_openai_prompt_cache_breakpoint(model, custom_llm_provider): + if model_info is None and not AnthropicCacheControlHook._may_target_openai_prompt_cache_breakpoint( + model, custom_llm_provider + ): return points return AnthropicCacheControlHook._stamped( points, "_litellm_openai_dialect", AnthropicCacheControlHook.targets_openai_prompt_cache_breakpoint( - model, custom_llm_provider, api_base, prompt_cache_options + model, custom_llm_provider, api_base, prompt_cache_options, model_info ), ) @@ -1248,6 +1578,7 @@ class AnthropicCacheControlHook(CustomPromptManagement): cache_control: object = None, request_kwargs: object = None, on_messages_route: bool = False, + model_info: Mapping[str, object] | None = None, ) -> list[CacheControlInjectionPoint]: """Default breakpoints when ``litellm.enable_anthropic_prompt_caching`` is on. @@ -1265,7 +1596,7 @@ class AnthropicCacheControlHook(CustomPromptManagement): if litellm.enable_anthropic_prompt_caching is not True and enable_prompt_caching is not True: return [] - if not supports_anthropic_cache_control(model, custom_llm_provider): + if not supports_anthropic_cache_control(model, custom_llm_provider, model_info): return [] if AnthropicCacheControlHook._request_has_cache_control( @@ -1343,6 +1674,7 @@ class AnthropicCacheControlHook(CustomPromptManagement): tools: list | None = None, enable_prompt_caching: bool | None = None, api_base: object = None, + model_info: Mapping[str, object] | None = None, ) -> None: """For /chat/completions: resolve the injection points the request should carry. @@ -1357,9 +1689,7 @@ class AnthropicCacheControlHook(CustomPromptManagement): configured: Final = configured_injection_points(non_default_params.get("cache_control_injection_points")) if configured: - tools_keeping_marks: Final = tuple( - tool for tool in tools or () if not _chat_transform_drops_tool_cache_control(tool) - ) + tools_keeping_marks: Final = AnthropicCacheControlHook.tools_keeping_cache_control_on_chat(tools) stamped: Final = AnthropicCacheControlHook._stamped_for_prompt_hook( configured, AnthropicCacheControlHook.count_external_cache_breakpoints( @@ -1369,6 +1699,7 @@ class AnthropicCacheControlHook(CustomPromptManagement): custom_llm_provider, api_base, non_default_params.get("prompt_cache_options"), + model_info, ) non_default_params["cache_control_injection_points"] = ( AnthropicCacheControlHook._stamped(stamped, CUSTOM_LLM_PROVIDER_STAMP, custom_llm_provider) @@ -1385,6 +1716,7 @@ class AnthropicCacheControlHook(CustomPromptManagement): enable_prompt_caching=enable_prompt_caching, cache_control=non_default_params.get("cache_control"), request_kwargs=non_default_params, + model_info=model_info, ) if points: non_default_params["cache_control_injection_points"] = points @@ -1503,6 +1835,7 @@ class AnthropicCacheControlHook(CustomPromptManagement): cache_control=cache_control, request_kwargs=kwargs, on_messages_route=True, + model_info=routed_model_info(kwargs.get("model_info")), ) if model is not None else () @@ -1511,7 +1844,11 @@ class AnthropicCacheControlHook(CustomPromptManagement): return messages, system openai_dialect: Final = AnthropicCacheControlHook.targets_openai_prompt_cache_breakpoint( - model, custom_llm_provider, api_base, kwargs.get("prompt_cache_options") + model, + custom_llm_provider, + api_base, + kwargs.get("prompt_cache_options"), + routed_model_info(kwargs.get("model_info")), ) breakpoints_before: Final = AnthropicCacheControlHook.count_request_cache_breakpoints(messages, system) messages, system, remaining = AnthropicCacheControlHook.apply_to_anthropic_messages_request( @@ -1645,9 +1982,17 @@ def messages_within_cache_control_cap( Tool hints and a top-level ``cache_control`` stay on the wire, so they are reserved first. """ - reserved_marks: Final = AnthropicCacheControlHook.count_external_cache_breakpoints( - _validated_object_list(tools), cache_control, request_kwargs + return messages_within_reserved_cache_control_cap( + messages, + AnthropicCacheControlHook.count_external_cache_breakpoints( + _validated_object_list(tools), cache_control, request_kwargs + ), ) + + +def messages_within_reserved_cache_control_cap( + messages: Sequence[_MessageT], reserved_marks: int +) -> Sequence[_MessageT]: kept: Final = newest_marks_within_cache_control_limit(messages, reserved_marks) dropped: Final = sum(map(cache_control_count, messages)) - sum(map(cache_control_count, kept)) if dropped > 0: diff --git a/litellm/integrations/azure_storage/azure_storage.py b/litellm/integrations/azure_storage/azure_storage.py index 37b4d2d3937..2ff523571f2 100644 --- a/litellm/integrations/azure_storage/azure_storage.py +++ b/litellm/integrations/azure_storage/azure_storage.py @@ -1,7 +1,8 @@ import asyncio import os import time -from collections.abc import Callable +from collections.abc import Callable, Mapping +from dataclasses import dataclass from datetime import datetime, timedelta, timezone from functools import cache from typing import Final @@ -15,6 +16,7 @@ from litellm.constants import ( AZURE_STORAGE_MSFT_VERSION, ) from litellm.integrations.custom_batch_logger import CustomBatchLogger +from litellm.litellm_core_utils.internal_call_metadata import logged_event_key from litellm.litellm_core_utils.safe_json_dumps import safe_dumps from litellm.llms.azure.common_utils import get_azure_ad_token_from_entra_id from litellm.llms.custom_httpx.http_handler import ( @@ -47,6 +49,20 @@ def adls_safe_file_name(payload_id: str | None) -> str: return f"{name.translate(_ADLS_SAFE_NAME)}.json" +@dataclass(frozen=True, slots=True) +class AzureStorageLogQueueItem: + payload: StandardLoggingPayload + file_name: str + + +def _queued_log(kwargs: Mapping[str, object], payload: StandardLoggingPayload) -> AzureStorageLogQueueItem: + payload_id: Final = payload.get("id") + return AzureStorageLogQueueItem( + payload=payload, + file_name=adls_safe_file_name(payload_id and logged_event_key(kwargs, payload_id)), + ) + + @cache def _cached_credential_chain_token_provider() -> Callable[[], str]: return get_azure_ad_token_provider( @@ -99,7 +115,7 @@ class AzureBlobStorageLogger(CustomBatchLogger): asyncio.create_task(self.periodic_flush()) self.flush_lock = asyncio.Lock() - self.log_queue: list[StandardLoggingPayload] = [] + self.log_queue: list[AzureStorageLogQueueItem] = [] super().__init__(**kwargs, flush_lock=self.flush_lock) except Exception as e: verbose_logger.exception( @@ -115,7 +131,7 @@ class AzureBlobStorageLogger(CustomBatchLogger): def azure_storage_blob_endpoint(self) -> str: return f"https://{self.azure_storage_account_name}.blob.{self.azure_storage_endpoint_suffix}" - async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): + async def async_log_success_event(self, kwargs, response_obj: object, start_time: datetime, end_time: datetime): """ Async Log success events to Azure Blob Storage @@ -133,12 +149,12 @@ class AzureBlobStorageLogger(CustomBatchLogger): if standard_logging_payload is None: raise ValueError("standard_logging_payload is not set") - self.log_queue.append(standard_logging_payload) + self.log_queue.append(_queued_log(kwargs, standard_logging_payload)) except Exception as e: verbose_logger.exception("AzureBlobStorageLogger Layer Error - %s", e) - async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): + async def async_log_failure_event(self, kwargs, response_obj: object, start_time: datetime, end_time: datetime): """ Async Log failure events to Azure Blob Storage @@ -156,7 +172,7 @@ class AzureBlobStorageLogger(CustomBatchLogger): if standard_logging_payload is None: raise ValueError("standard_logging_payload is not set") - self.log_queue.append(standard_logging_payload) + self.log_queue.append(_queued_log(kwargs, standard_logging_payload)) except Exception as e: verbose_logger.exception("AzureBlobStorageLogger Layer Error - %s", e) @@ -195,13 +211,15 @@ class AzureBlobStorageLogger(CustomBatchLogger): len(self.log_queue), ) - for payload in self.log_queue: - await self.async_upload_payload_to_azure_blob_storage(payload=payload) + for item in self.log_queue: + await self.async_upload_payload_to_azure_blob_storage(payload=item.payload, file_name=item.file_name) except Exception as e: verbose_logger.exception("AzureBlobStorageLogger Error sending batch API - %s", e) - async def async_upload_payload_to_azure_blob_storage(self, payload: StandardLoggingPayload): + async def async_upload_payload_to_azure_blob_storage( + self, payload: StandardLoggingPayload, file_name: str | None = None + ): """ Uploads the payload to Azure Blob Storage using a 3-step process: 1. Create file resource @@ -210,14 +228,14 @@ class AzureBlobStorageLogger(CustomBatchLogger): """ try: if self.azure_storage_account_key: - await self.upload_to_azure_data_lake_with_azure_account_key(payload=payload) + await self.upload_to_azure_data_lake_with_azure_account_key(payload=payload, file_name=file_name) else: # Get a valid token instead of always requesting a new one await self.set_valid_azure_ad_token() async_client: Final = get_async_httpx_client(llm_provider=httpxSpecialProvider.LoggingCallback) json_payload: Final = safe_dumps(payload) + "\n" # Add newline for each log entry payload_bytes: Final = json_payload.encode("utf-8") - filename: Final = adls_safe_file_name(payload.get("id")) + filename: Final = file_name or adls_safe_file_name(payload.get("id")) base_url = f"{self.azure_storage_dfs_endpoint}/{self.azure_storage_file_system}/{filename}" # Execute the 3-step upload process @@ -377,7 +395,9 @@ class AzureBlobStorageLogger(CustomBatchLogger): self._service_client_timeout = self._clock() + _DEFAULT_TTL_FOR_HTTPX_CLIENTS return self._service_client - async def upload_to_azure_data_lake_with_azure_account_key(self, payload: StandardLoggingPayload): + async def upload_to_azure_data_lake_with_azure_account_key( + self, payload: StandardLoggingPayload, file_name: str | None = None + ): """ Uploads the payload to Azure Data Lake using the Azure SDK @@ -386,11 +406,11 @@ class AzureBlobStorageLogger(CustomBatchLogger): try: today: Final = datetime.now().strftime("%Y-%m-%d") - file_name: Final = adls_safe_file_name(payload.get("id")) + resolved_file_name: Final = file_name or adls_safe_file_name(payload.get("id")) await self._upload_bytes_with_account_key( - file_path=f"{today}/{file_name}", content=safe_dumps(payload).encode("utf-8") + file_path=f"{today}/{resolved_file_name}", content=safe_dumps(payload).encode("utf-8") ) - verbose_logger.debug("Successfully uploaded and wrote to %s/%s", today, file_name) + verbose_logger.debug("Successfully uploaded and wrote to %s/%s", today, resolved_file_name) except Exception as e: verbose_logger.exception("Error occurred: %s", e) diff --git a/litellm/integrations/clickhouse/clickhouse_spend_logger.py b/litellm/integrations/clickhouse/clickhouse_spend_logger.py index 1d01965cd2c..c8453456052 100644 --- a/litellm/integrations/clickhouse/clickhouse_spend_logger.py +++ b/litellm/integrations/clickhouse/clickhouse_spend_logger.py @@ -19,6 +19,7 @@ from litellm._logging import verbose_logger from litellm.integrations.clickhouse.clickhouse_batch_logger import ClickHouseBatchLogger from litellm.integrations.clickhouse.context import is_lens_analysis from litellm.integrations.clickhouse.schema import SPEND_LOGS_TABLE +from litellm.litellm_core_utils.internal_call_metadata import logged_event_key from litellm.litellm_core_utils.llm_response_utils.get_headers import get_provider_request_id from litellm.litellm_core_utils.sensitive_data_masker import redact_credentials_in_payload from litellm.tracing.types import SpendLogPayload, SpendLogRecord @@ -134,7 +135,7 @@ def spend_log_row_from_payload( usage: Mapping[str, Any] = metadata.get("usage_object") or hidden_params.get("usage_object") or MappingProxyType({}) cache_read_tokens, cache_write_tokens = _cache_tokens(usage) trace_id, span_id = _find_traceparent(metadata, kwargs) - request_id = str(payload.get("id") or "") + response_id: Final = str(payload.get("id") or "") redact = litellm.turn_off_message_logging is True track_end_user: Final = not litellm.disable_end_user_cost_tracking completion_start_ms = _to_ms(payload.get("completionStartTime")) @@ -157,8 +158,8 @@ def spend_log_row_from_payload( ) ) return SpendLogRecord( - request_id=request_id, - response_id=strip_cache_hit_suffix(request_id), + request_id=logged_event_key(kwargs, response_id), + response_id=strip_cache_hit_suffix(response_id), provider_request_id=( get_provider_request_id(kwargs.get("response_headers")) or get_provider_request_id(hidden_params.get("additional_headers")) diff --git a/litellm/integrations/code_interpreter_interception/handler.py b/litellm/integrations/code_interpreter_interception/handler.py index 69b528a29f8..b035732afa6 100644 --- a/litellm/integrations/code_interpreter_interception/handler.py +++ b/litellm/integrations/code_interpreter_interception/handler.py @@ -10,6 +10,7 @@ import json import time import uuid from collections.abc import Mapping, Sequence +from dataclasses import dataclass from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, TypeAlias, TypedDict, runtime_checkable from pydantic import ValidationError @@ -73,7 +74,7 @@ class CodeInterpreterLogOutput(TypedDict): class CodeInterpreterCall(TypedDict): id: str type: Literal["code_interpreter_call"] - status: Literal["completed"] + status: Literal["completed", "failed"] code: str container_id: str | None outputs: list[CodeInterpreterLogOutput] @@ -141,6 +142,39 @@ class _SupportsOutput(Protocol): _CachedContainer: TypeAlias = tuple[ContainerHandle, SandboxToolParams | None, float, str | None] +@dataclass(frozen=True, slots=True) +class _ReadySandbox: + container: ContainerHandle + params: SandboxToolParams | None + + +@dataclass(frozen=True, slots=True) +class _SandboxUnavailable: + output: str + + +_Sandbox: TypeAlias = _ReadySandbox | _SandboxUnavailable + + +@dataclass(frozen=True, slots=True) +class _ToolRun: + output: str + status: Literal["completed", "failed"] + + +_SANDBOX_UNAVAILABLE_OUTPUT: Final = "The code did not run because the code execution sandbox is unavailable." +_SANDBOX_LOST_RESULT_OUTPUT: Final = ( + "The code execution sandbox failed while running the code, so the code may have run but its result is lost." +) + + +def _sandbox_unavailable(step: str, error: Exception, output: str = _SANDBOX_UNAVAILABLE_OUTPUT) -> _SandboxUnavailable: + verbose_logger.warning( + "CodeInterpreterInterception: %s failed, answering the tool call with the failure: %s", step, error + ) + return _SandboxUnavailable(output=output) + + def _output_item_type(item: object) -> object: if isinstance(item, dict): item_mapping: Final[dict[str, object]] = item @@ -189,6 +223,14 @@ def _extract_identity(kwargs: Mapping[str, object]) -> str: return identity if isinstance(identity, str) else "" +def _bridged_from_responses(kwargs: Mapping[str, object], call_type: CallTypes | None) -> bool: + route: Final = getattr(kwargs.get("litellm_logging_obj"), "call_type", None) + return call_type in (CallTypes.completion, CallTypes.acompletion) and route in ( + CallTypes.responses, + CallTypes.aresponses, + ) + + def _resolve_sandbox_tool(sandbox_tool_name: str | None) -> SandboxToolParams | None: if sandbox_tool_name is None: return None @@ -261,7 +303,7 @@ class CodeInterpreterInterceptionLogger(CustomLogger): async def async_pre_call_deployment_hook( self, kwargs: dict[str, object], call_type: CallTypes | None ) -> dict | None: - if not kwargs.get("_agentic_loop_depth"): + if not kwargs.get("_agentic_loop_depth") and not _bridged_from_responses(kwargs, call_type): kwargs.pop(_INTERCEPTION_ACTIVE_KEY, None) kwargs.pop(_SANDBOX_KEY, None) self._strip_interception_metadata(kwargs) @@ -451,16 +493,16 @@ class CodeInterpreterInterceptionLogger(CustomLogger): sandbox_key: Final = self._extract_sandbox_key(kwargs) is_session: Final = bool(kwargs.get(_SESSION_SCOPED_KEY)) identity: Final = _extract_identity(kwargs) if is_session else None - container, params = await self._get_or_create_container(cache_key=sandbox_key, identity=identity) + sandbox: Final = await self._acquire_sandbox(cache_key=sandbox_key, identity=identity) try: - container_id: Final = self._container_id(container) + container_id: Final = self._sandbox_container_id(sandbox) input_list: Final = self._normalize_messages(messages) code_interpreter_calls: Final[list[CodeInterpreterCall]] = [] for tool_call in tool_calls: arguments = tool_call.get("arguments", "") code = self._parse_code(arguments) - stdout = await self._run_tool_call(container=container, params=params, arguments=arguments) + tool_run = await self._sandbox_tool_output(sandbox=sandbox, arguments=arguments) input_list.append( { "type": "function_call", @@ -473,22 +515,23 @@ class CodeInterpreterInterceptionLogger(CustomLogger): { "type": "function_call_output", "call_id": tool_call.get("call_id"), - "output": stdout, + "output": tool_run.output, } ) code_interpreter_calls.append( { "id": f"ci_{uuid.uuid4().hex}", "type": "code_interpreter_call", - "status": "completed", + "status": tool_run.status, "code": code, "container_id": container_id, - "outputs": ([{"type": "logs", "logs": stdout}] if stdout else []), + "outputs": ([{"type": "logs", "logs": tool_run.output}] if tool_run.output else []), } ) except Exception: await self._delete_container_for_cache_key(sandbox_key) raise + await self._evict_sandbox_if_a_run_failed(sandbox_key, sandbox, code_interpreter_calls) optional_params: Final = anthropic_messages_optional_request_params request_patch: Final = AgenticLoopRequestPatch( @@ -526,14 +569,13 @@ class CodeInterpreterInterceptionLogger(CustomLogger): sandbox_key: Final = self._extract_sandbox_key(kwargs) is_session: Final = bool(kwargs.get(_SESSION_SCOPED_KEY)) identity: Final = _extract_identity(kwargs) if is_session else None - container, params = await self._get_or_create_container(cache_key=sandbox_key, identity=identity) + sandbox: Final = await self._acquire_sandbox(cache_key=sandbox_key, identity=identity) try: - container_id: Final = self._container_id(container) + container_id: Final = self._sandbox_container_id(sandbox) tool_results: Final = [ await self._build_chat_completion_tool_result( - container=container, - params=params, + sandbox=sandbox, tool_call=tool_call, container_id=container_id, ) @@ -544,6 +586,7 @@ class CodeInterpreterInterceptionLogger(CustomLogger): raise tool_messages: Final = [result[0] for result in tool_results] code_interpreter_calls: Final = [result[1] for result in tool_results] + await self._evict_sandbox_if_a_run_failed(sandbox_key, sandbox, code_interpreter_calls) request_patch: Final = AgenticLoopRequestPatch( model=model, @@ -569,9 +612,13 @@ class CodeInterpreterInterceptionLogger(CustomLogger): ) @staticmethod - def _container_id(container: ContainerHandle) -> str | None: - container_id: Final[object] = getattr(container, "id", None) - return container_id if isinstance(container_id, str) else None + def _sandbox_container_id(sandbox: _Sandbox) -> str | None: + match sandbox: + case _ReadySandbox(container=container): + container_id: Final[object] = getattr(container, "id", None) + return container_id if isinstance(container_id, str) else None + case _SandboxUnavailable(): + return None @staticmethod def _agentic_tool_calls(tools: dict[str, object]) -> list[CodeExecutionToolCall]: @@ -588,28 +635,27 @@ class CodeInterpreterInterceptionLogger(CustomLogger): async def _build_chat_completion_tool_result( self, - container: ContainerHandle, - params: SandboxToolParams | None, + sandbox: _Sandbox, tool_call: CodeExecutionToolCall, container_id: str | None, ) -> tuple[ChatCompletionToolMessage, CodeInterpreterCall]: arguments: Final = tool_call.get("arguments", "") code: Final = self._parse_code(arguments) - stdout: Final = await self._run_tool_call(container=container, params=params, arguments=arguments) + tool_run: Final = await self._sandbox_tool_output(sandbox=sandbox, arguments=arguments) tool_call_id: Final = tool_call.get("id") or tool_call.get("call_id") or uuid.uuid4().hex return ( { "role": "tool", "tool_call_id": tool_call_id, - "content": stdout, + "content": tool_run.output, }, { "id": f"ci_{uuid.uuid4().hex}", "type": "code_interpreter_call", - "status": "completed", + "status": tool_run.status, "code": code, "container_id": container_id, - "outputs": [{"type": "logs", "logs": stdout}] if stdout else [], + "outputs": [{"type": "logs", "logs": tool_run.output}] if tool_run.output else [], }, ) @@ -694,19 +740,55 @@ class CodeInterpreterInterceptionLogger(CustomLogger): except (json.JSONDecodeError, TypeError, AttributeError): return "" - async def _run_tool_call(self, container: ContainerHandle, params: SandboxToolParams | None, arguments: str) -> str: + async def _evict_sandbox_if_a_run_failed( + self, sandbox_key: str | None, sandbox: _Sandbox, calls: Sequence[CodeInterpreterCall] + ) -> None: + if not sandbox_key or not isinstance(sandbox, _ReadySandbox): + return + if not any(call["status"] == "failed" for call in calls): + return + cached: Final = self._container_cache.get(sandbox_key) + if cached is None or cached[0] is not sandbox.container: + return + self._container_cache.pop(sandbox_key) + await self._delete_container(container=cached[0], params=cached[1]) + + async def _sandbox_tool_output(self, sandbox: _Sandbox, arguments: str) -> _ToolRun: + match sandbox: + case _SandboxUnavailable(output=output): + return _ToolRun(output=output, status="failed") + case _ReadySandbox(container=container, params=params): + match await self._run_tool_call(container=container, params=params, arguments=arguments): + case _SandboxUnavailable(output=output): + return _ToolRun(output=output, status="failed") + case str() as output: + return _ToolRun(output=output, status="completed") + + async def _run_tool_call( + self, container: ContainerHandle, params: SandboxToolParams | None, arguments: str + ) -> str | _SandboxUnavailable: try: code: Final = json.loads(arguments).get("code", "") if arguments else "" except (json.JSONDecodeError, TypeError): return "[invalid tool arguments: could not parse code]" - result: Final = await self._run_code(container=container, params=params, code=code) + try: + result: Final = await self._run_code(container=container, params=params, code=code) + except Exception as e: + return _sandbox_unavailable("running the code", e, _SANDBOX_LOST_RESULT_OUTPUT) if getattr(result, "error", None): error: Final = result.error message: Final = error.get("value") or error.get("name") if isinstance(error, dict) else str(error) return f"[execution error] {message}" return getattr(result, "stdout", "") or "" + async def _acquire_sandbox(self, cache_key: str | None, identity: str | None) -> _Sandbox: + try: + container, params = await self._get_or_create_container(cache_key=cache_key, identity=identity) + except Exception as e: + return _sandbox_unavailable("creating the sandbox", e) + return _ReadySandbox(container=container, params=params) + async def _get_or_create_container( self, cache_key: str | None, diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py index dfe508f3630..68876812c3e 100644 --- a/litellm/integrations/custom_guardrail.py +++ b/litellm/integrations/custom_guardrail.py @@ -1089,6 +1089,12 @@ class CustomGuardrail(CustomLogger): enrich_http_exception_with_guardrail_context(result, self) raise result + def runs_post_call_deployment_hook(self, request_data: Mapping[str, object]) -> bool: + return ( + isinstance(request_data.get("guardrails"), list) + and self.should_run_guardrail(data=request_data, event_type=GuardrailEventHooks.post_call) is True + ) + async def async_post_call_success_deployment_hook( self, request_data: dict, @@ -1098,12 +1104,7 @@ class CustomGuardrail(CustomLogger): """ Allow modifying / reviewing the response just after it's received from the deployment. """ - # should run guardrail - litellm_guardrails: Final = request_data.get("guardrails") - if litellm_guardrails is None or not isinstance(litellm_guardrails, list): - return None - - if self.should_run_guardrail(data=request_data, event_type=GuardrailEventHooks.post_call) is not True: + if not self.runs_post_call_deployment_hook(request_data): return None target: Final = self._deployment_hook_target() diff --git a/litellm/integrations/deepeval/deepeval.py b/litellm/integrations/deepeval/deepeval.py index 71d149e4014..e38b987d46f 100644 --- a/litellm/integrations/deepeval/deepeval.py +++ b/litellm/integrations/deepeval/deepeval.py @@ -15,6 +15,7 @@ from litellm.integrations.deepeval.utils import ( to_zod_compatible_iso, validate_environment, ) +from litellm.litellm_core_utils.internal_call_metadata import logged_event_key # This file includes the custom callbacks for LiteLLM Proxy @@ -109,8 +110,10 @@ class DeepEvalLogger(CustomLogger): ) else: output = str(standard_logging_object.get("error_string", "")) + logged_id: Final = standard_logging_object.get("id", uuid.uuid4()) + span_id: Final = logged_event_key(kwargs, logged_id) if isinstance(logged_id, str) else logged_id return BaseApiSpan( - uuid=standard_logging_object.get("id", uuid.uuid4()), + uuid=span_id, name=("litellm_success_callback" if is_success else "litellm_failure_callback"), status=(TraceSpanApiStatus.SUCCESS if is_success else TraceSpanApiStatus.ERRORED), type=SpanApiType.LLM, diff --git a/litellm/integrations/dynamodb.py b/litellm/integrations/dynamodb.py index 6569e70329b..8672eb00ce5 100644 --- a/litellm/integrations/dynamodb.py +++ b/litellm/integrations/dynamodb.py @@ -9,6 +9,8 @@ from typing import Final, Protocol import litellm from litellm._uuid import uuid +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.internal_call_metadata import logged_event_key class _DynamoTable(Protocol): @@ -22,11 +24,13 @@ class _DynamoResource(Protocol): class DyanmoDBLogger: # Class variables or attributes - def __init__(self): + def __init__(self, dynamodb: _DynamoResource | None = None): # Instance variables import boto3 - self.dynamodb: Final[_DynamoResource] = boto3.resource("dynamodb", region_name=os.environ["AWS_REGION_NAME"]) + self.dynamodb: Final[_DynamoResource] = dynamodb or boto3.resource( + "dynamodb", region_name=os.environ["AWS_REGION_NAME"] + ) if litellm.dynamodb_table_name is None: raise ValueError( "LiteLLM Error, trying to use DynamoDB but not table name passed. Create a table and set `litellm.dynamodb_table_name=`" @@ -45,23 +49,23 @@ class DyanmoDBLogger: _async_log_event = async_log_event - def log_event(self, kwargs, response_obj, start_time, end_time, print_verbose): + def log_event(self, kwargs: Mapping[str, object], response_obj, start_time, end_time, print_verbose): try: print_verbose(f"DynamoDB Logging - Enters logging function for model {kwargs}") # construct payload to send to DynamoDB # follows the same params as langfuse.py - litellm_params: Final = kwargs.get("litellm_params", {}) - metadata: Final = litellm_params.get("metadata", {}) or {} # if litellm_params['metadata'] == None + litellm_params: Final = as_str_mapping(kwargs.get("litellm_params")) or {} + metadata: Final = as_str_mapping(litellm_params.get("metadata")) or {} messages: Final = kwargs.get("messages") optional_params: Final = kwargs.get("optional_params", {}) call_type: Final = kwargs.get("call_type", "litellm.completion") usage: Final = response_obj["usage"] - id: Final = response_obj.get("id", str(uuid.uuid4())) + response_id: Final = response_obj.get("id", str(uuid.uuid4())) # Build the initial payload payload: Final[dict[str, object]] = { - "id": id, + "id": logged_event_key(kwargs, response_id) if isinstance(response_id, str) else response_id, "call_type": call_type, "startTime": start_time, "endTime": end_time, diff --git a/litellm/integrations/email_templates/model_deprecation_email.py b/litellm/integrations/email_templates/model_deprecation_email.py new file mode 100644 index 00000000000..5d325b2442a --- /dev/null +++ b/litellm/integrations/email_templates/model_deprecation_email.py @@ -0,0 +1,181 @@ +"""Model deprecation emails with provider identity, a migration comparison and next steps.""" + +from collections.abc import Mapping +from html import escape +from types import MappingProxyType +from typing import Final +from urllib.parse import urlencode, urlsplit + +from litellm.types.integrations.model_deprecation_email import ( + DeprecationEmailMilestone, + ModelDeprecationEmail, + RenderedDeprecationEmail, +) +from litellm.types.proxy.model_deprecation import SuccessorModelSource + +_LOGO_BASE_URL: Final = ( + "https://raw.githubusercontent.com/BerriAI/litellm/main/ui/litellm-dashboard/public/assets/logos" +) +_EMAIL_LOGO_URL: Final = f"{_LOGO_BASE_URL}/litellm_logo.png" +# Reuse dashboard brand assets; PNGs also render in email clients that block SVG. +_PROVIDER_BRANDS: Final[Mapping[str, tuple[str, str]]] = MappingProxyType( + { + "gemini": ("Google", "google_pse.png"), + "vertex_ai": ("Google", "google_pse.png"), + "openai": ("OpenAI", "openai.png"), + "anthropic": ("Anthropic", "anthropic.png"), + "azure": ("Microsoft Azure", "microsoft_azure.png"), + "bedrock": ("AWS Bedrock", "aws.png"), + "bedrock_converse": ("AWS Bedrock", "aws.png"), + } +) + + +def _recommendation_source(source: SuccessorModelSource | None) -> str: + if source is SuccessorModelSource.DEPLOYMENT_CONFIG: + return "Gateway configuration" + if source is SuccessorModelSource.MODEL_COST_MAP: + return "LiteLLM model cost map" + return "Not provided" + + +def _http_url(value: str | None) -> str | None: + if value is None: + return None + try: + parsed: Final = urlsplit(value) + except ValueError: + return None + return value if parsed.scheme in ("http", "https") and parsed.netloc and not parsed.username else None + + +def _provider(model: str, fallback: str | None = None) -> str: + prefix, separator, _ = model.partition("/") + return prefix if separator else fallback or "" + + +def _provider_name(provider: str) -> str: + brand: Final = _PROVIDER_BRANDS.get(provider) + if brand: + return brand[0] + return provider.replace("_", " ") or "The provider" + + +def _model_html(model: str, provider: str) -> str: + brand: Final = _PROVIDER_BRANDS.get(provider) + logo: Final = ( + f'{escape(brand[0], quote=True)}' + if brand + else "" + ) + return ( + f'{logo}' + f'
{escape(_provider_name(provider))}
' + f"
{escape(model)}
" + ) + + +def render_model_deprecation_email(email: ModelDeprecationEmail, *, base_url: str) -> RenderedDeprecationEmail: + gateway: Final = _http_url(base_url) + if gateway is None: + raise ValueError("Model deprecation emails require a public HTTP(S) PROXY_BASE_URL") + urgent: Final = email.milestone is DeprecationEmailMilestone.ONE_DAY + days: Final = int(email.milestone) + timing: Final = "tomorrow" if urgent else "in 30 days" + provider: Final = _provider(email.usage_model, email.model.litellm_provider) + provider_name: Final = _provider_name(provider) + subject: Final = f"[LiteLLM] Model being deprecated by {provider_name} {timing}: {email.usage_model}" + deadline: Final = email.model.deprecation_date.strftime("%d %b %Y") + announcement: Final = f"{provider_name} is deprecating this model on {deadline} (UTC)." + preheader: Final = f"{announcement} Review the model change and migrate your affected keys." + query: Final = urlencode( + { + "tab": "models", + "from": email.start_date.isoformat(), + "to": email.end_date.isoformat(), + } + ) + review_url: Final = f"{gateway.rstrip('/')}/ui/usage?{query}" + replacement: Final = email.model.successor_model + after: Final = ( + _model_html(replacement, _provider(replacement, provider)) + if replacement + else '

No recommended model listed. Choose a supported replacement.

' + ) + source: Final = _recommendation_source(email.model.successor_model_source) + notice: Final = _http_url(email.model.deprecation_source) + source_link: Final = ( + f'Read the provider notice ↗' + if notice + else "" + ) + team_names: Final = ", ".join(email.team_names[:3]) or "Personal keys" + more_teams: Final = f" + {len(email.team_names) - 3} more" if len(email.team_names) > 3 else "" + day_label: Final = "DAY" if urgent else "DAYS" + label: Final = "FINAL REMINDER" if urgent else "DEPRECATION NOTICE" + test_step: Final = ( + "Test the recommended model with your workload." + if replacement + else "Choose a supported replacement and test it with your workload." + ) + switch_step: Final = ( + f"Switch your app or gateway routing before {deadline}. Then check that requests to the old model reach zero." + ) + html: Final = f""" + +{escape(subject)} + + +
{escape(preheader)}
+
+ + + + + +
+ +
LiteLLM/ MODEL DEPRECATIONS
+ +
{label}{days:02d} {day_label} UNTIL DEPRECATION
+

Model being deprecated

+

{escape(announcement)}

+
+ + +
+
BEFORE · MODEL TO REPLACE
+{_model_html(email.usage_model, provider)} +		 +
AFTER · RECOMMENDED MODEL
+{after} +
+

Recommendation source: {escape(source)}
{source_link}

+

Your affected usage

+ + +
{email.key_count:,}
Affected keys
{email.requests:,}
Requests · last 30 days
+

{escape(team_names + more_teams)}
Your keys and teams you administer.

+

What to do

+
    +
  1. Review the affected keys in your usage dashboard.
    2. +
  2. {escape(test_step)}
    3. +
  3. {escape(switch_step)}
+
+Review affected usage ↗
+
+Your gateway admin enabled these emails. Reminder schedule: 30 days and 1 day before deprecation.

LiteLLM · AI Gateway
""" + text: Final = ( + f"{subject}\n\n{announcement}\n\n" + f"BEFORE - MODEL TO REPLACE\n{email.usage_model}\n\n" + f"AFTER - RECOMMENDED MODEL\n{replacement or 'No recommended model listed. Choose a supported replacement.'}\n" + f"Recommendation source: {source}\nProvider notice: {notice or 'Not provided'}\n\n" + f"YOUR AFFECTED USAGE\n{email.key_count} keys | {email.requests} requests in the last 30 days\n" + f"{team_names}{more_teams}\nYour keys and teams you administer.\n\n" + f"WHAT TO DO\n1. Review the affected keys in your usage dashboard.\n2. {test_step}\n3. {switch_step}\n\n" + f"Review affected usage: {review_url}\n\n" + "Your gateway admin enabled these emails. Reminder schedule: 30 days and 1 day before deprecation." + ) + return RenderedDeprecationEmail(subject=subject, html=html, text=text) diff --git a/litellm/integrations/gcs_bucket/gcs_bucket.py b/litellm/integrations/gcs_bucket/gcs_bucket.py index 99cd8b31b63..7057e719764 100644 --- a/litellm/integrations/gcs_bucket/gcs_bucket.py +++ b/litellm/integrations/gcs_bucket/gcs_bucket.py @@ -17,6 +17,7 @@ from litellm.litellm_core_utils.cloud_storage_security import ( sanitize_cloud_object_component, ) from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.internal_call_metadata import logged_event_key from litellm.types.integrations.base_health_check import IntegrationHealthCheckStatus from litellm.types.integrations.gcs_bucket import * from litellm.types.utils import StandardBatchLineItemsPayload, StandardLoggingPayload @@ -296,30 +297,28 @@ class GCSBucketLogger(GCSBucketBase, AdditionalLoggingUtils): else: await self._send_individual_logs(items_to_process) - def _get_object_name(self, kwargs: dict, logging_payload: StandardLoggingPayload, response_obj: Any) -> str: + def _get_object_name( + self, kwargs: Mapping[str, object], logging_payload: StandardLoggingPayload, response_obj: Any + ) -> str: """ Get the object name to use for the current payload """ current_date: Final = self._get_object_date_from_datetime(datetime.now(timezone.utc)) + metadata: Final = as_str_mapping((as_str_mapping(kwargs.get("litellm_params")) or {}).get("metadata")) or {} + gcs_log_id: Final = metadata.get("gcs_log_id") + safe_log_id: Final = sanitize_cloud_object_component( + gcs_log_id if isinstance(gcs_log_id, str) else None, fallback="" + ) + if safe_log_id: + return f"{current_date}/custom-{uuid.uuid4().hex}-{safe_log_id}" if logging_payload.get("error_str", None) is not None: - object_name = self._generate_failure_object_name( - request_date_str=current_date, - ) - else: - object_name = self._generate_success_object_name( - request_date_str=current_date, - response_id=response_obj.get("id", ""), - ) - - # used for testing - _litellm_params: Final = kwargs.get("litellm_params", None) or {} - _metadata: Final = _litellm_params.get("metadata", None) or {} - if "gcs_log_id" in _metadata: - safe_log_id: Final = sanitize_cloud_object_component(_metadata.get("gcs_log_id"), fallback="") - if safe_log_id: - object_name = f"{current_date}/custom-{uuid.uuid4().hex}-{safe_log_id}" - - return object_name + return self._generate_failure_object_name(request_date_str=current_date) + raw_response_id: Final[object] = response_obj.get("id", "") + response_id: Final = raw_response_id if isinstance(raw_response_id, str) else "" + return self._generate_success_object_name( + request_date_str=current_date, + response_id=logged_event_key(kwargs, response_id), + ) async def get_request_response_payload( self, diff --git a/litellm/integrations/model_deprecation_email.py b/litellm/integrations/model_deprecation_email.py new file mode 100644 index 00000000000..4093a108dcc --- /dev/null +++ b/litellm/integrations/model_deprecation_email.py @@ -0,0 +1,267 @@ +"""Two owner-scoped retirement reminders, with durable per-recipient delivery receipts.""" + +from __future__ import annotations + +import asyncio +import hashlib +import json +import os +from collections.abc import Mapping +from dataclasses import dataclass +from datetime import date, datetime, timedelta, timezone +from enum import Enum +from itertools import chain +from types import MappingProxyType +from typing import TYPE_CHECKING, Final + +from pydantic import AliasPath, BaseModel, ConfigDict, Field, TypeAdapter + +from litellm.integrations.email_templates.model_deprecation_email import ( + render_model_deprecation_email, +) +from litellm.models.team import LiteLLM_TeamTable +from litellm.proxy.common_utils.model_deprecation import collect_model_deprecations +from litellm.repositories.config_repository import ConfigRepository +from litellm.repositories.table_repositories import DailyUserSpendRepository +from litellm.repositories.team_repository import TeamRepository +from litellm.repositories.user_repository import UserRepository +from litellm.repositories.verification_token_repository import ( + VerificationTokenRepository, +) +from litellm.types.integrations.model_deprecation_email import ( + MODEL_DEPRECATION_EMAIL_EVENT, + DeprecationEmailMilestone, + ModelDeprecationEmail, +) +from litellm.types.proxy.model_deprecation import ( + DEPRECATION_IDLE_POLL_SECONDS, + ModelDeprecationInfo, +) + +if TYPE_CHECKING: + from litellm import Router + from litellm.proxy.utils import PrismaClient + +_RECEIPT_PREFIX: Final = "model_deprecation_email:" +_PAGE_SIZE: Final = 100 + + +class _OptIn(BaseModel): + model_config = ConfigDict(frozen=True, hide_input_in_errors=True) + enabled: bool = Field( + False, + strict=True, + validation_alias=AliasPath("email_settings", MODEL_DEPRECATION_EMAIL_EVENT), + ) + + +class _RequestCount(BaseModel): + model_config = ConfigDict(frozen=True, hide_input_in_errors=True) + api_requests: int + + +class _UsedKey(BaseModel): + model_config = ConfigDict(frozen=True, hide_input_in_errors=True) + api_key: str + metrics: _RequestCount = Field(alias="_sum") + + +_USED_KEYS: Final = TypeAdapter(tuple[_UsedKey, ...]) + + +class _DeliveryStatus(str, Enum): + SENDING = "sending" + SENT = "sent" + + +class _Receipt(BaseModel): + model_config = ConfigDict(frozen=True, hide_input_in_errors=True) + revision: int = 0 + status: _DeliveryStatus = _DeliveryStatus.SENDING + lease_until: datetime + + +@dataclass(frozen=True, slots=True) +class _Impact: + key_count: int = 0 + requests: int = 0 + teams: frozenset[str] = frozenset() + + +def _admin_ids(team: LiteLLM_TeamTable | None) -> frozenset[str]: + if team is None: + return frozenset() + return frozenset( + member.user_id for member in (team.members_with_roles or ()) if member.role == "admin" and member.user_id + ) + + +def _recipient_emails( + user_id: str | None, team: LiteLLM_TeamTable | None, addresses: Mapping[str, str] +) -> frozenset[str]: + owner_ids: Final[frozenset[str]] = frozenset((user_id,)) if user_id else frozenset() + resolved: Final = frozenset(addresses[owner] for owner in owner_ids | _admin_ids(team) if owner in addresses) + if team is None: + return resolved + return resolved | frozenset( + member.user_email.strip() + for member in (team.members_with_roles or ()) + if member.role == "admin" + and member.user_email + and member.user_email.strip() + and member.user_id not in addresses + ) + + +def _usage_model(model: ModelDeprecationInfo) -> str: + name: Final = model.litellm_model or model.model_name + provider: Final = model.litellm_provider + if provider and not name.startswith(f"{provider}/"): + return f"{provider}/{name}" + return name + + +def _receipt_key(email: ModelDeprecationEmail) -> str: + identity: Final = json.dumps( + [ + email.usage_model, + email.model.deprecation_date.isoformat(), + int(email.milestone), + email.recipient_email.casefold(), + ] + ) + return _RECEIPT_PREFIX + hashlib.sha256(identity.encode()).hexdigest() + + +class ModelDeprecationEmailSender: + def __init__(self, prisma_client: PrismaClient) -> None: + self.prisma: Final = prisma_client + self.config: Final = ConfigRepository(prisma_client, use_writer=True) + + async def _impacts(self, model: str, start: date, end: date) -> Mapping[str, _Impact]: + impacts: Final[dict[str, _Impact]] = {} # mutable-ok: combines per-recipient counts across bounded usage pages + offset: int = 0 # rebind-ok: each page advances the stable key grouping cursor + while True: + raw = await DailyUserSpendRepository(self.prisma).table.group_by( + by=["api_key"], + where={ + "model": model, + "date": {"gte": start.isoformat(), "lte": end.isoformat()}, + "api_requests": {"gt": 0}, + }, + sum={"api_requests": True}, + order={"api_key": "asc"}, + skip=offset, + take=_PAGE_SIZE, + ) + usage = _USED_KEYS.validate_python(raw) + if not usage: + return MappingProxyType(impacts) + keys = await VerificationTokenRepository(self.prisma).find_many_in("token", (row.api_key for row in usage)) + teams = await TeamRepository(self.prisma).find_many_in( + "team_id", frozenset(key.team_id for key in keys if key.team_id) + ) + team_by_id = {team.team_id: team for team in teams} + ids = frozenset(key.user_id for key in keys if key.user_id) | frozenset( + chain.from_iterable(_admin_ids(team) for team in teams) + ) + users = await UserRepository(self.prisma).find_many_in("user_id", ids) + addresses = { + user.user_id: user.user_email.strip() for user in users if user.user_email and user.user_email.strip() + } + counts = {row.api_key: row.metrics.api_requests for row in usage} + for key in keys: + team = team_by_id.get(key.team_id) if key.team_id else None + if key.token is None: + continue + recipients = _recipient_emails(key.user_id, team, addresses) + for address in recipients: + previous = impacts.get(address, _Impact()) + names: frozenset[str] = frozenset((team.team_alias or team.team_id,)) if team else frozenset() + impacts[address] = _Impact( + key_count=previous.key_count + 1, + requests=previous.requests + counts[key.token], + teams=previous.teams | names, + ) + if len(usage) < _PAGE_SIZE: + return MappingProxyType(impacts) + offset += _PAGE_SIZE + + async def _deliver(self, email: ModelDeprecationEmail, now: datetime, base_url: str) -> bool: + from litellm.proxy.utils import send_email + + key: Final = _receipt_key(email) + record: Final = await self.config.get_param(key) + previous: Final = _Receipt.model_validate(record.param_value) if record else None + if previous and (previous.status is _DeliveryStatus.SENT or previous.lease_until > now): + return False + revision: Final = previous.revision if previous else 0 + claim: Final = _Receipt(revision=revision + 1, lease_until=now + timedelta(minutes=5)) + if not await self.config.set_param_if_revision(key, claim.model_dump(mode="json"), revision): + return False + content: Final = render_model_deprecation_email(email, base_url=base_url) + if not await send_email( + receiver_email=email.recipient_email, + subject=content.subject, + html=content.html, + text=content.text, + message_id=f"", + ): + return False + sent: Final = claim.model_copy(update={"revision": claim.revision + 1, "status": _DeliveryStatus.SENT}) + if not await self.config.set_param_if_revision(key, sent.model_dump(mode="json"), claim.revision): + raise RuntimeError("Could not record the delivered model deprecation reminder") + return True + + async def run(self, llm_router: Router, *, now: datetime | None = None) -> int: + current: Final = now or datetime.now(timezone.utc) + settings: Final = await self.config.get_param("general_settings") + if settings is None or not _OptIn.model_validate(settings.param_value).enabled: + return 0 + base_url: Final = os.getenv("PROXY_BASE_URL", "") + if not base_url: + return 0 + await self.config.delete_params_older_than(_RECEIPT_PREFIX, current - timedelta(days=60)) + snapshot: Final = collect_model_deprecations(llm_router=llm_router, today=current.date()) + start: Final = current.date() - timedelta(days=29) + seen: Final[set[tuple[str, date]]] = set() # mutable-ok: deduplicates aliases in this pass + sent: int = 0 # rebind-ok: counts successfully delivered reminders in this pass + for model in snapshot.imminent: + if model.days_until_deprecation not in tuple(DeprecationEmailMilestone): + continue + name = _usage_model(model) + identity = (name, model.deprecation_date) + if identity in seen: + continue + seen.add(identity) + impacts = await self._impacts(name, start, current.date()) + for address, impact in sorted(impacts.items()): + email = ModelDeprecationEmail( + model=model, + usage_model=name, + recipient_email=address, + milestone=DeprecationEmailMilestone(model.days_until_deprecation), + key_count=impact.key_count, + requests=impact.requests, + team_names=tuple(sorted(impact.teams)), + start_date=start, + end_date=current.date(), + ) + if await self._deliver(email, now or datetime.now(timezone.utc), base_url): + sent += 1 + return sent + + +async def run_scheduled_model_deprecation_emails() -> None: + """Poll the email opt-in independently; a large owner mailing never delays Slack checks.""" + from litellm._logging import verbose_proxy_logger + + while True: + try: + from litellm.proxy.proxy_server import llm_router, prisma_client + + if llm_router is not None and prisma_client is not None: + await ModelDeprecationEmailSender(prisma_client).run(llm_router) + except Exception: # noqa: BLE001 # transient SMTP/DB failures must not terminate the reminder loop + verbose_proxy_logger.exception("Error sending model deprecation email reminders") + await asyncio.sleep(DEPRECATION_IDLE_POLL_SECONDS) diff --git a/litellm/integrations/openmeter.py b/litellm/integrations/openmeter.py index db2fe386dec..918e849a086 100644 --- a/litellm/integrations/openmeter.py +++ b/litellm/integrations/openmeter.py @@ -3,12 +3,15 @@ import json import os +from collections.abc import Mapping from typing import Final import httpx import litellm from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.internal_call_metadata import logged_event_key from litellm.llms.custom_httpx.http_handler import ( HTTPHandler, get_async_httpx_client, @@ -48,7 +51,7 @@ class OpenMeterLogger(CustomLogger): if len(missing_keys) > 0: raise Exception(f"Missing keys={missing_keys} in environment.") - def _common_logic(self, kwargs: dict, response_obj): + def _common_logic(self, kwargs: Mapping[str, object], response_obj): call_id: Final = response_obj.get("id", kwargs.get("litellm_call_id")) dt: Final = get_utc_datetime().isoformat() cost: Final = kwargs.get("response_cost", None) @@ -74,8 +77,8 @@ class OpenMeterLogger(CustomLogger): # If no user provided directly, try to get it from token user_id if user_param is None: # Check if user_id is available from the API key metadata - litellm_params: Final = kwargs.get("litellm_params", {}) - metadata: Final = litellm_params.get("metadata", {}) + litellm_params: Final = as_str_mapping(kwargs.get("litellm_params")) or {} + metadata: Final = as_str_mapping(litellm_params.get("metadata")) or {} user_api_key_user_id: Final = metadata.get("user_api_key_user_id", None) if user_api_key_user_id is not None: @@ -89,7 +92,7 @@ class OpenMeterLogger(CustomLogger): return { "specversion": "1.0", "type": os.getenv("OPENMETER_EVENT_TYPE", "litellm_tokens"), - "id": call_id, + "id": logged_event_key(kwargs, call_id) if isinstance(call_id, str) else call_id, "time": dt, "subject": subject, "source": "litellm-proxy", diff --git a/litellm/integrations/otel/model/spans.py b/litellm/integrations/otel/model/spans.py index 320231430d2..0f98a8fce0e 100644 --- a/litellm/integrations/otel/model/spans.py +++ b/litellm/integrations/otel/model/spans.py @@ -338,9 +338,12 @@ _PRISMA_MODELS: Final[frozenset[str]] = frozenset( "LiteLLM_ToolTable", "LiteLLM_TelemetryReport", "LiteLLM_AccessGroupTable", - "LiteLLM_AccountingDelivery", - "LiteLLM_AccountingEvent", + "LiteLLM_SpendLogDelivery", "LiteLLM_ClaudeCodePluginTable", + "LiteLLM_ClaudeCodePluginUpload", + "LiteLLM_ClaudeCodePluginVersion", + "LiteLLM_SkillSubmission", + "LiteLLM_ClaudeCodePluginDownload", "LiteLLM_MemoryTable", "LiteLLM_AdaptiveRouterState", "LiteLLM_AdaptiveRouterSession", diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index 42fe0837c29..fc1a601f9da 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -54,6 +54,7 @@ from litellm.litellm_core_utils.get_llm_provider_logic import is_registered_cust from litellm.litellm_core_utils.service_tier_utils import ( get_service_tier_from_standard_logging_payload, ) +from litellm.llms.azure.common_utils import caused_by_entra_rejection from litellm.llms.github_copilot.per_user_auth import github_copilot_user_session_from from litellm.llms.openai_like.json_loader import JSONProviderRegistry from litellm.models.end_user import LiteLLM_EndUserTable @@ -448,7 +449,7 @@ def _is_deployment_failure(exception: openai.APIError, logged_call: Mapping[str, return not ( isinstance(exception, CallerCredentialAuthenticationError) or bool(logged_call.get(LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL)) - or logged_call.get("api_call_start_time") is None + or (logged_call.get("api_call_start_time") is None and not caused_by_entra_rejection(exception)) or _used_a_caller_credential(logged_call) ) @@ -3036,7 +3037,7 @@ class PrometheusLogger(CustomLogger): async def async_post_call_failure_hook( self, - request_data: dict, + request_data: dict[str, object], original_exception: Exception, user_api_key_dict: UserAPIKeyAuth, traceback_str: str | None = None, @@ -3059,10 +3060,14 @@ class PrometheusLogger(CustomLogger): try: _tags: Final = StandardLoggingPayloadSetup.get_request_tags( litellm_params=request_data, - proxy_server_request=request_data.get("proxy_server_request", {}), + proxy_server_request=_logged_fields(request_data.get("proxy_server_request")), + ) + _metadata: Final = _logged_fields(request_data.get("metadata")) + model_id: Final = ( + _logged_fields(_metadata.get("model_info")).get("id") + or _logged_fields(request_data.get("model_info")).get("id") + or _logged_fields(request_data.get("standard_logging_object")).get("model_id") ) - _metadata: Final = request_data.get("metadata", {}) or {} - model_id: Final = _metadata.get("model_info", {}).get("id") or request_data.get("model_info", {}).get("id") rate_limit_category, rate_limit_type = self._extract_rate_limit_labels(original_exception) api_provider: Final = self._extract_api_provider_from_request_data( request_data diff --git a/litellm/integrations/websearch_interception/handler.py b/litellm/integrations/websearch_interception/handler.py index 2bb89248be4..d41647fe5f1 100644 --- a/litellm/integrations/websearch_interception/handler.py +++ b/litellm/integrations/websearch_interception/handler.py @@ -17,6 +17,7 @@ from typing import TYPE_CHECKING, Any, Final, Literal, TypedDict, TypeVar, cast from typing_extensions import Never, ReadOnly import litellm +from litellm._internal_context import billed_separately from litellm._logging import verbose_logger from litellm.anthropic_interface import messages as anthropic_messages from litellm.constants import LITELLM_WEB_SEARCH_TOOL_NAME @@ -1628,19 +1629,20 @@ class WebSearchInterceptionLogger(CustomLogger): search_kwargs: Final = MappingProxyType( {**configured_search_kwargs, **parent_correlation.as_search_kwargs()} ) - result: Final = ( - await litellm.asearch( - query=query_arg, search_provider=search_provider, **_NO_ASEARCH_NAMED, **search_kwargs + with billed_separately(): + result: Final = ( + await litellm.asearch( + query=query_arg, search_provider=search_provider, **_NO_ASEARCH_NAMED, **search_kwargs + ) + if search_metadata is None + else await litellm.asearch( + query=query_arg, + search_provider=search_provider, + litellm_metadata=search_metadata, + **_NO_ASEARCH_NAMED, + **search_kwargs, + ) ) - if search_metadata is None - else await litellm.asearch( - query=query_arg, - search_provider=search_provider, - litellm_metadata=search_metadata, - **_NO_ASEARCH_NAMED, - **search_kwargs, - ) - ) # Format using transformation function search_result_text: Final = WebSearchTransformation.format_search_response(result) diff --git a/litellm/litellm_core_utils/add_retry_fallback_headers.py b/litellm/litellm_core_utils/add_retry_fallback_headers.py index 12b26954e4c..4cf2d1d58d8 100644 --- a/litellm/litellm_core_utils/add_retry_fallback_headers.py +++ b/litellm/litellm_core_utils/add_retry_fallback_headers.py @@ -202,7 +202,7 @@ def response_total_token_count(response: object) -> int: def apply_remaining_usage_headers( additional_headers: dict[str, object], - remaining_usage: dict[str, int], + remaining_usage: Mapping[str, object], ) -> None: for header, value in remaining_usage.items(): if value is not None and header not in additional_headers: diff --git a/litellm/litellm_core_utils/agentic_followup_failure.py b/litellm/litellm_core_utils/agentic_followup_failure.py new file mode 100644 index 00000000000..318429d64b5 --- /dev/null +++ b/litellm/litellm_core_utils/agentic_followup_failure.py @@ -0,0 +1,36 @@ +from dataclasses import dataclass +from typing import Final, TypeAlias + +from litellm.types.utils import Usage + +ServedRound: TypeAlias = tuple[Usage, float] + +_MARK_ATTRIBUTE: Final = "_litellm_agentic_followup_mark" + + +@dataclass(frozen=True, slots=True) +class _FollowUpMark: + served_rounds: tuple[ServedRound, ...] + + +def _mark_of(error: BaseException) -> _FollowUpMark | None: + mark: Final[object] = getattr(error, _MARK_ATTRIBUTE, None) + return mark if isinstance(mark, _FollowUpMark) else None + + +def mark_agentic_followup_failure(error: BaseException, served_rounds: tuple[ServedRound, ...]) -> None: + setattr(error, _MARK_ATTRIBUTE, _FollowUpMark(served_rounds)) + + +def is_agentic_followup_failure(error: BaseException) -> bool: + return _mark_of(error) is not None + + +def rounds_served_before(error: BaseException) -> tuple[ServedRound, ...]: + mark: Final = _mark_of(error) + return () if mark is None else mark.served_rounds + + +def carry_agentic_followup_mark(source: BaseException, mapped: BaseException) -> None: + if mapped is not source and is_agentic_followup_failure(source): + mark_agentic_followup_failure(mapped, rounds_served_before(source)) diff --git a/litellm/litellm_core_utils/agentic_loop_refusal.py b/litellm/litellm_core_utils/agentic_loop_refusal.py new file mode 100644 index 00000000000..f3ee15dffdd --- /dev/null +++ b/litellm/litellm_core_utils/agentic_loop_refusal.py @@ -0,0 +1,107 @@ +import asyncio +from collections.abc import Awaitable, Iterable, Mapping +from itertools import chain +from types import MappingProxyType +from typing import Final + +from litellm._logging import verbose_logger +from litellm.litellm_core_utils.prompt_templates.mid_conversation_system import message_field, parts_of +from litellm.types.llms.openai import ResponsesAPIResponse +from litellm.types.utils import ( + ChatCompletionMessageCustomToolCall, + ChatCompletionMessageToolCall, + Choices, + ModelResponse, +) + + +def _strings(values: Iterable[object]) -> frozenset[str]: + return frozenset(value for value in values if isinstance(value, str)) + + +def _claimed_calls(tool_calls: object) -> tuple[object, ...]: + wrapped: Final = message_field(tool_calls, "tool_calls") + return parts_of(tool_calls if wrapped is None else wrapped) + + +async def _calls_a_gate_claims(gate: Awaitable[tuple[bool, object]]) -> tuple[object, ...]: + try: + should_run, tool_calls = await gate + except Exception as e: + verbose_logger.debug("LiteLLM.AgenticLoopRefused: skipping a gate that failed with %s", type(e).__name__) + return () + return _claimed_calls(tool_calls) if should_run else () + + +async def every_claimed_tool_call( + refused_tool_calls: object, other_gates: Iterable[Awaitable[tuple[bool, object]]] +) -> Mapping[str, tuple[object, ...]]: + claims: Final = await asyncio.gather(*(_calls_a_gate_claims(gate) for gate in other_gates)) + return MappingProxyType({"tool_calls": (*_claimed_calls(refused_tool_calls), *chain.from_iterable(claims))}) + + +def _call_ids(call: object) -> frozenset[str]: + return _strings((message_field(call, "id"), message_field(call, "call_id"))) + + +def refused_tool_call_identifiers(tool_calls: object) -> tuple[frozenset[str], frozenset[str]]: + calls: Final = _claimed_calls(tool_calls) + ids: Final = frozenset(chain.from_iterable(_call_ids(call) for call in calls)) + names: Final = _strings(message_field(call, "name") for call in calls if not _call_ids(call)) + return ids, names + + +def is_refused_call(call_id: object, name: object, refused_ids: frozenset[str], refused_names: frozenset[str]) -> bool: + return (isinstance(call_id, str) and call_id in refused_ids) or name in refused_names + + +def is_refused_item( + item: object, item_type: str, id_field: str, refused_ids: frozenset[str], refused_names: frozenset[str] +) -> bool: + if message_field(item, "type") != item_type: + return False + return is_refused_call(message_field(item, id_field), message_field(item, "name"), refused_ids, refused_names) + + +def finalize_refused_responses_turn(response: ResponsesAPIResponse, tool_calls: object) -> ResponsesAPIResponse: + refused_ids, refused_names = refused_tool_call_identifiers(tool_calls) + kept: Final = [ + item + for item in parts_of(message_field(response, "output")) + if not is_refused_item(item, "function_call", "call_id", refused_ids, refused_names) + ] + return response.model_copy(update={"output": kept}) + + +def _is_refused_chat_tool_call(call: object, refused_ids: frozenset[str], refused_names: frozenset[str]) -> bool: + name: Final = message_field(message_field(call, "function"), "name") + return is_refused_call(message_field(call, "id"), name, refused_ids, refused_names) + + +def _at_position( + call: ChatCompletionMessageToolCall | ChatCompletionMessageCustomToolCall, position: int +) -> ChatCompletionMessageToolCall | ChatCompletionMessageCustomToolCall: + return call if message_field(call, "index") is None else call.model_copy(update={"index": position}) + + +def _finalized_choice(choice: object, refused_ids: frozenset[str], refused_names: frozenset[str]) -> object: + if not isinstance(choice, Choices) or not choice.message.tool_calls: + return choice + surviving: Final = ( + call for call in choice.message.tool_calls if not _is_refused_chat_tool_call(call, refused_ids, refused_names) + ) + kept: Final = [_at_position(call, position) for position, call in enumerate(surviving)] + finish_reason: Final = "stop" if not kept and choice.finish_reason == "tool_calls" else choice.finish_reason + return choice.model_copy( + update={ + "message": choice.message.model_copy(update={"tool_calls": kept or None}), + "finish_reason": finish_reason, + } + ) + + +def finalize_refused_chat_turn(response: ModelResponse, tool_calls: object) -> ModelResponse: + refused_ids, refused_names = refused_tool_call_identifiers(tool_calls) + return response.model_copy( + update={"choices": [_finalized_choice(choice, refused_ids, refused_names) for choice in response.choices]} + ) diff --git a/litellm/litellm_core_utils/allowed_tools_tool_choice.py b/litellm/litellm_core_utils/allowed_tools_tool_choice.py new file mode 100644 index 00000000000..5c8f5d83ece --- /dev/null +++ b/litellm/litellm_core_utils/allowed_tools_tool_choice.py @@ -0,0 +1,111 @@ +from collections.abc import Mapping +from typing import Final, Literal + +from openai.types.responses.tool_choice_allowed_param import ToolChoiceAllowedParam +from pydantic import BaseModel, ConfigDict, Field, TypeAdapter, ValidationError + +from litellm.exceptions import BadRequestError + +ALLOWED_TOOLS_TOOL_CHOICE_PROVIDERS: Final = frozenset({"openai", "azure", "litellm_proxy"}) + +CHAT_ALLOWED_TOOLS_LAYOUT: Final = ( + '{"type": "allowed_tools", "allowed_tools": {"mode": "auto" | "required", "tools": []}}' +) + + +class ChatAllowedTools(BaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + mode: Literal["auto", "required"] + tools: tuple[Mapping[str, object], ...] = Field(min_length=1) + + +class ChatAllowedToolsToolChoice(BaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + type: Literal["allowed_tools"] + allowed_tools: ChatAllowedTools + + +_CHAT_ALLOWED_TOOLS_TOOL_CHOICE: Final = TypeAdapter(ChatAllowedToolsToolChoice) + + +_SELECTOR: Final = TypeAdapter(dict[str, object]) + + +class _ToolChoiceType(BaseModel): + model_config = ConfigDict(frozen=True) + + type: str + + +_TOOL_CHOICE_TYPE: Final = TypeAdapter(_ToolChoiceType) + + +def is_allowed_tools_tool_choice(tool_choice: object) -> bool: + try: + return _TOOL_CHOICE_TYPE.validate_python(tool_choice).type == "allowed_tools" + except ValidationError: + return False + + +def raise_if_allowed_tools_tool_choice_unsupported( + tool_choice: object, + custom_llm_provider: str, + model: str, +) -> None: + """Providers outside the set would silently send the request with no tool restriction at all, so the call stops + here with a 400. ``drop_params`` is deliberately not consulted: dropping a restriction widens what the model may call.""" + if not is_allowed_tools_tool_choice(tool_choice) or custom_llm_provider in ALLOWED_TOOLS_TOOL_CHOICE_PROVIDERS: + return + raise BadRequestError( + message=( + "tool_choice type 'allowed_tools' is only supported for " + f"{', '.join(sorted(ALLOWED_TOOLS_TOOL_CHOICE_PROVIDERS))}, got custom_llm_provider={custom_llm_provider}. " + "drop_params does not drop it, since that would let the model call tools the request excluded. " + "Send only the allowed tools in `tools` with tool_choice='auto' or 'required' instead." + ), + model=model, + llm_provider=custom_llm_provider, + ) + + +def parse_chat_allowed_tools_tool_choice(tool_choice: object) -> ChatAllowedToolsToolChoice | None: + try: + return _CHAT_ALLOWED_TOOLS_TOOL_CHOICE.validate_python(tool_choice) + except ValidationError: + return None + + +def _has_name(selector: Mapping[str, object]) -> bool: + name: Final = selector.get("name") + return isinstance(name, str) and name != "" + + +def _responses_allowed_tool(tool: Mapping[str, object]) -> Mapping[str, object] | None: + tool_type: Final = tool.get("type") + if tool_type not in ("function", "custom"): + return tool + if tool_type not in tool: + return tool if _has_name(tool) else None + try: + nested: Final = _SELECTOR.validate_python(tool[tool_type]) + except ValidationError: + return None + outer: Final = {key: value for key, value in tool.items() if key != tool_type} + if not _has_name(nested) or outer.keys() & nested.keys(): + return None + return {**outer, **nested} + + +def responses_allowed_tools_tool_choice(choice: ChatAllowedToolsToolChoice) -> ToolChoiceAllowedParam | None: + """The flat Responses API layout of a chat ``allowed_tools`` choice, or ``None`` when an entry is malformed or + carries conflicting keys, so the caller sends the original rather than a rewrite that could mean something looser.""" + flattened: Final = tuple(_responses_allowed_tool(tool) for tool in choice.allowed_tools.tools) + if any(tool is None for tool in flattened): + return None + return ToolChoiceAllowedParam( + type="allowed_tools", + mode=choice.allowed_tools.mode, + tools=[dict(tool) for tool in flattened if tool is not None], + ) diff --git a/litellm/litellm_core_utils/audio_utils/transcription_streaming.py b/litellm/litellm_core_utils/audio_utils/transcription_streaming.py new file mode 100644 index 00000000000..b7fa693a22a --- /dev/null +++ b/litellm/litellm_core_utils/audio_utils/transcription_streaming.py @@ -0,0 +1,341 @@ +from __future__ import annotations + +import datetime +import json +import traceback +from collections.abc import AsyncIterator, Callable, Iterator, Mapping +from typing import Final, Protocol + +import anyio +from openai import AsyncStream, Stream +from openai.types.audio import ( + TranscriptionStreamEvent, + TranscriptionTextDeltaEvent, + TranscriptionTextDoneEvent, +) +from pydantic import TypeAdapter, ValidationError + +from litellm.litellm_core_utils.core_helpers import process_response_headers +from litellm.litellm_core_utils.llm_cost_calc.usage_object_transformation import ( + TranscriptionUsageObjectTransformation, +) +from litellm.types.utils import TranscriptionResponse, TranscriptionUsageTokensObject, Usage + +_STREAM_FLAG: Final = TypeAdapter(bool) + + +def transcription_stream_flag(value: object) -> bool | None: + try: + return _STREAM_FLAG.validate_python(value) + except ValidationError: + return None + + +def transcription_stream_unset(value: object) -> bool: + return value is None or value == "" + + +def transcription_stream_requested(value: object) -> bool: + return transcription_stream_flag(value) is True + + +TRANSCRIPTION_STREAM_DONE_FRAME: Final = "data: [DONE]\n\n" + +TranscriptionStreamExceptionMapper = Callable[[Exception], Exception] + + +def litellm_exception_mapper(call_details: Mapping[str, object]) -> TranscriptionStreamExceptionMapper: + from litellm.litellm_core_utils.exception_mapping_utils import exception_type, with_deployment_api_base + + model: Final = call_details.get("model") + custom_llm_provider: Final = call_details.get("custom_llm_provider") + extra_kwargs: Final = with_deployment_api_base(call_details.get("litellm_params")) + + def map_exception(exception: Exception) -> Exception: + try: + mapped: Final[object] = exception_type( + model=model if isinstance(model, str) else None, + original_exception=exception, + custom_llm_provider=custom_llm_provider if isinstance(custom_llm_provider, str) else None, + extra_kwargs=extra_kwargs, + ) + except Exception as mapped_exception: # noqa: BLE001 # exception_type raises the mapped exception + return mapped_exception + return mapped if isinstance(mapped, Exception) else exception + + return map_exception + + +def _guarded_transcription_event_payloads( + response: TranscriptionResponse, +) -> tuple[dict[str, object], dict[str, object]]: + text: Final = response.text or "" + usage: Final = response.usage + languages: Final = TranscriptionResponse.detected_languages(getattr(response, "languages", None)) + return ( + {"type": "transcript.text.delta", "delta": text}, + { + "type": "transcript.text.done", + "text": text, + **({} if usage is None else {"usage": usage.model_dump(exclude_none=True)}), + **({} if languages is None else {"languages": [language.model_dump() for language in languages]}), + }, + ) + + +def guarded_transcription_events(response: TranscriptionResponse) -> tuple[str, ...]: + return ( + *( + f"data: {json.dumps(event, separators=(',', ':'))}\n\n" + for event in _guarded_transcription_event_payloads(response) + ), + TRANSCRIPTION_STREAM_DONE_FRAME, + ) + + +class GuardedTranscriptionReplay: + def __init__(self, response: TranscriptionResponse) -> None: + self.response: Final = response + self._hidden_params: dict[str, object] = response.hidden_params + + def __aiter__(self) -> AsyncIterator[TranscriptionStreamEvent]: + return self._events() + + async def _events(self) -> AsyncIterator[TranscriptionStreamEvent]: + delta, done = _guarded_transcription_event_payloads(self.response) + yield TranscriptionTextDeltaEvent.model_construct(**delta) + yield TranscriptionTextDoneEvent.model_construct(**done) + + +class TranscriptionStreamLogging(Protocol): + def success_handler( + self, + result: TranscriptionResponse, + start_time: datetime.datetime, + end_time: datetime.datetime, + ) -> None: ... + + async def async_success_handler( + self, + result: TranscriptionResponse, + start_time: datetime.datetime, + end_time: datetime.datetime, + ) -> None: ... + + def handle_sync_success_callbacks_for_async_calls( + self, + result: TranscriptionResponse, + start_time: datetime.datetime, + end_time: datetime.datetime, + ) -> None: ... + + def failure_handler( + self, + exception: Exception, + traceback_exception: str, + start_time: datetime.datetime, + end_time: datetime.datetime, + *, + for_async_request: bool = False, + ) -> None: ... + + async def async_failure_handler( + self, + exception: Exception, + traceback_exception: str, + start_time: datetime.datetime, + end_time: datetime.datetime, + ) -> None: ... + + def response_cost_calculator(self, result: TranscriptionResponse) -> float | None: ... + + def record_partial_usage_for_failure(self, usage: Usage, response_cost: float) -> None: ... + + +class _TranscriptionEventCollector: + def __init__(self, duration: float | None) -> None: + self.duration = duration + self.text_deltas: list[str] = [] # mutable-ok: streaming deltas accumulate until the terminal event + self.done_event: TranscriptionTextDoneEvent | None = None + + def add(self, event: TranscriptionStreamEvent) -> None: + if isinstance(event, TranscriptionTextDeltaEvent): + self.text_deltas.append(event.delta) + elif isinstance(event, TranscriptionTextDoneEvent): + self.done_event = event + + def response(self) -> TranscriptionResponse: + done_event: Final = self.done_event + response: Final = TranscriptionResponse( + text=done_event.text if done_event is not None else "".join(self.text_deltas), + usage=done_event.usage.model_dump() if done_event is not None and done_event.usage is not None else None, + languages=getattr(done_event, "languages", None) if done_event is not None else None, + ) + if self.duration is not None: + response.set_audio_transcription_duration(self.duration) + return response + + +def _billed_usage(response: TranscriptionResponse) -> Usage: + usage: Final = response.usage + token_usage: Final = ( + TranscriptionUsageObjectTransformation.transform_transcription_usage_object(usage) + if isinstance(usage, TranscriptionUsageTokensObject) + else None + ) + return token_usage or Usage(prompt_tokens=0, completion_tokens=0, total_tokens=0) + + +def _record_billable_partial_spend( + logging_obj: TranscriptionStreamLogging, collector: _TranscriptionEventCollector +) -> None: + partial_response: Final = collector.response() + partial_cost: Final = logging_obj.response_cost_calculator(result=partial_response) or 0.0 + if partial_cost <= 0: + return + logging_obj.record_partial_usage_for_failure(_billed_usage(partial_response), partial_cost) + + +class LoggingTranscriptionStream(Stream[TranscriptionStreamEvent]): + def __init__( + self, + stream: Stream[TranscriptionStreamEvent], + logging_obj: TranscriptionStreamLogging, + start_time: datetime.datetime, + map_exception: TranscriptionStreamExceptionMapper, + ) -> None: + self.__dict__.update(stream.__dict__) + self._hidden_params: dict[str, object] = { # mutable-ok: ResponseMetadata fills in the call's metadata + "additional_headers": process_response_headers(stream.response.headers) + } + self._logging_obj = logging_obj + self._start_time = start_time + self._map_exception = map_exception + self._collector = _TranscriptionEventCollector(getattr(stream, "_litellm_audio_duration", None)) + self._finalized = False + self._failed = False + source_iterator: Final = self._iterator + self._iterator = self._logging_iterator(source_iterator) + + def _logging_iterator( + self, source_iterator: Iterator[TranscriptionStreamEvent] + ) -> Iterator[TranscriptionStreamEvent]: + try: + for event in source_iterator: + self._collector.add(event) + yield event + except Exception as exception: + self._failed = True + _record_billable_partial_spend(self._logging_obj, self._collector) + mapped_exception: Final = self._map_exception(exception) + end_time: Final = datetime.datetime.now() # noqa: DTZ005 # callback timestamps use the legacy naive contract + self._logging_obj.failure_handler(mapped_exception, traceback.format_exc(), self._start_time, end_time) + raise mapped_exception from exception + finally: + self._finalize() + + def _finalize(self) -> None: + if self._finalized or self._failed: + return + self._finalized = True + self._logging_obj.success_handler( + self._collector.response(), + self._start_time, + datetime.datetime.now(), # noqa: DTZ005 # callback timestamps use the legacy naive contract + ) + + def close(self) -> None: + try: + super().close() + finally: + self._finalize() + + @property + def logging_obj(self) -> TranscriptionStreamLogging: + return self._logging_obj + + +class LoggingAsyncTranscriptionStream(AsyncStream[TranscriptionStreamEvent]): + def __init__( + self, + stream: AsyncStream[TranscriptionStreamEvent], + logging_obj: TranscriptionStreamLogging, + start_time: datetime.datetime, + map_exception: TranscriptionStreamExceptionMapper, + ) -> None: + self.__dict__.update(stream.__dict__) + self._hidden_params: dict[str, object] = { # mutable-ok: ResponseMetadata fills in the call's metadata + "additional_headers": process_response_headers(stream.response.headers) + } + self._logging_obj = logging_obj + self._start_time = start_time + self._map_exception = map_exception + self._collector = _TranscriptionEventCollector(getattr(stream, "_litellm_audio_duration", None)) + self._finalized = False + self._failed = False + source_iterator: Final = self._iterator + self._iterator = self._logging_iterator(source_iterator) + + async def _logging_iterator( + self, source_iterator: AsyncIterator[TranscriptionStreamEvent] + ) -> AsyncIterator[TranscriptionStreamEvent]: + try: + async for event in source_iterator: + self._collector.add(event) + yield event + except Exception as exception: + self._failed = True + _record_billable_partial_spend(self._logging_obj, self._collector) + mapped_exception: Final = self._map_exception(exception) + end_time: Final = datetime.datetime.now() # noqa: DTZ005 # callback timestamps use the legacy naive contract + self._logging_obj.failure_handler( + mapped_exception, traceback.format_exc(), self._start_time, end_time, for_async_request=True + ) + await self._logging_obj.async_failure_handler( + mapped_exception, + traceback.format_exc(), + self._start_time, + end_time, + ) + raise mapped_exception from exception + finally: + await self._finalize() + + async def _finalize(self) -> None: + if self._finalized or self._failed: + return + self._finalized = True + response: Final = self._collector.response() + end_time: Final = datetime.datetime.now() # noqa: DTZ005 # callback timestamps use the legacy naive contract + self._logging_obj.handle_sync_success_callbacks_for_async_calls( + result=response, + start_time=self._start_time, + end_time=end_time, + ) + with anyio.CancelScope(shield=True): + await self._logging_obj.async_success_handler( + result=response, + start_time=self._start_time, + end_time=end_time, + ) + + async def close(self) -> None: + try: + await super().close() + finally: + await self._finalize() + + @property + def logging_obj(self) -> TranscriptionStreamLogging: + return self._logging_obj + + +def wrap_transcription_stream( + stream: Stream[TranscriptionStreamEvent] | AsyncStream[TranscriptionStreamEvent], + logging_obj: TranscriptionStreamLogging, + start_time: datetime.datetime, + map_exception: TranscriptionStreamExceptionMapper, +) -> LoggingTranscriptionStream | LoggingAsyncTranscriptionStream: + if isinstance(stream, AsyncStream): + return LoggingAsyncTranscriptionStream(stream, logging_obj, start_time, map_exception) + return LoggingTranscriptionStream(stream, logging_obj, start_time, map_exception) diff --git a/litellm/litellm_core_utils/audio_utils/utils.py b/litellm/litellm_core_utils/audio_utils/utils.py index 640559ac7e2..29b10ac3c83 100644 --- a/litellm/litellm_core_utils/audio_utils/utils.py +++ b/litellm/litellm_core_utils/audio_utils/utils.py @@ -21,6 +21,16 @@ from litellm.types.files import ( from litellm.types.utils import FileTypes +def normalized_audio_duration_seconds(value: object) -> float | None: + if isinstance(value, bool) or not isinstance(value, (int, float)): + return None + try: + seconds: Final = float(value) + except OverflowError: + return None + return seconds if math.isfinite(seconds) and seconds >= 0 else None + + @dataclass class ProcessedAudioFile: """ diff --git a/litellm/litellm_core_utils/batch_utils.py b/litellm/litellm_core_utils/batch_utils.py index 5b94d4b4e5b..7c7b7ea5c4b 100644 --- a/litellm/litellm_core_utils/batch_utils.py +++ b/litellm/litellm_core_utils/batch_utils.py @@ -3,21 +3,32 @@ import json from collections.abc import Callable, Generator, Iterable, Mapping, Sequence from contextlib import contextmanager from contextvars import ContextVar +from dataclasses import dataclass from os import PathLike -from typing import Final, TypeVar +from typing import Final, Literal, TypeVar from openai.types import Batch from pydantic import TypeAdapter, ValidationError from litellm._logging import verbose_logger +from litellm.litellm_core_utils.core_helpers import finite_cost +from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import guardrail_information_cost from litellm.types.llms.openai import FileTypes, OpenAIFilesPurpose from litellm.types.utils import CallTypes, LlmProviders +from litellm.types.videos.main import VideoObject +from litellm.types.videos.utils import POLLED_VIDEO_STATUS_KWARG, canonical_video_id, is_video_status_call_type _DECODED_JSONL_ROW: Final = TypeAdapter(object) _DEPLOYMENT_FIELD: Final = TypeAdapter(Mapping[str, object]) +_PAYLOAD_FIELDS: Final = TypeAdapter(Mapping[str, object]) _ENDPOINT_PATHS: Final = TypeAdapter(tuple[str, ...]) +_COMPLETED_BATCH_STATUSES: Final = frozenset({"completed", "complete"}) +_TERMINAL_BATCH_STATUSES: Final = _COMPLETED_BATCH_STATUSES | frozenset({"failed", "cancelled", "expired"}) BATCH_ENDPOINT: Final = "/v1/batch" +POLLED_BATCH_ID_KWARG: Final = "polled_batch_id" +POLLED_BATCH_COST_IS_FINAL_KWARG: Final = "polled_batch_cost_is_final" +BATCH_COST_REQUEST_ID_SUFFIX: Final = "_batch_cost" _AZURE_PROVIDERS: Final = frozenset({LlmProviders.AZURE.value, LlmProviders.AZURE_AI.value}) _batch_create_routing: Final[ContextVar[bool]] = ContextVar("batch_create_routing", default=False) @@ -289,12 +300,151 @@ def is_batch_retrieve_call_type(call_type: object) -> bool: return isinstance(call_type, str) and call_type in BATCH_RETRIEVE_CALL_TYPES -def batch_charged_once_marker_key(spend_key: str, batch_id: str) -> str: - return f"{spend_key}:batch:{batch_id}" +@dataclass(frozen=True, slots=True) +class ChargeOnceJob: + kind: Literal["batch", "video"] + job_id: str + repeat_poll_cost: float = 0.0 -def batch_id_to_charge_once(call_type: object, response_obj: object, response_cost: float) -> str | None: - """A finished batch reports its whole cost on every poll, so its id is charged once per counter.""" - if response_cost <= 0 or not is_batch_retrieve_call_type(call_type): +def job_charged_once_marker_key(spend_key: str, job: ChargeOnceJob) -> str: + return f"{spend_key}:{job.kind}:{job.job_id}" + + +def _guardrail_cost_of_poll(standard_logging_payload: object) -> float: + guardrail_information: Final = ( + _PAYLOAD_FIELDS.validate_python(standard_logging_payload).get("guardrail_information") + if isinstance(standard_logging_payload, Mapping) + else None + ) + return guardrail_information_cost(guardrail_information) + + +def charged_poll_cost(kwargs: Mapping[str, object]) -> object: + """The poll's whole cost as the cost callback charges it, guardrails included, which the logging kwargs' own + response_cost leaves out.""" + standard_logging_payload: Final = kwargs.get("standard_logging_object") + logged_cost: Final = ( + _PAYLOAD_FIELDS.validate_python(standard_logging_payload).get("response_cost") + if isinstance(standard_logging_payload, Mapping) + else None + ) + return kwargs.get("response_cost") if logged_cost is None else logged_cost + + +def job_cost_of_poll(response_cost: object, standard_logging_payload: object) -> float: + """What the polled job itself cost, since a guardrail on the poll charges every poll, running or finished.""" + return (finite_cost(response_cost) or 0.0) - _guardrail_cost_of_poll(standard_logging_payload) + + +def repeat_poll_cost(call_type: object, response_cost: object, standard_logging_payload: object) -> float: + """What a poll still costs once an earlier poll charged its job: a video poll's guardrails, which every video + poll has always paid, and nothing for a batch poll, whose repeats have always been free.""" + if not is_video_status_call_type(call_type): + return 0.0 + return max(0.0, min(finite_cost(response_cost) or 0.0, _guardrail_cost_of_poll(standard_logging_payload))) + + +def batch_cost_is_final(batch: Batch) -> bool: + """Whether this retrieve of the batch is the one to account its cost from. + + A batch still in flight has nothing to price, and a "completed" batch can report + no output_file_id for a moment before the output populates; pricing either records + $0 under the batch's single spend row and pins it there. Final means a completed + batch whose output file has arrived or whose counts prove no line succeeded, or + any other terminal status (failed, cancelled, expired). + """ + if batch.status not in _TERMINAL_BATCH_STATUSES: + return False + if batch.status not in _COMPLETED_BATCH_STATUSES or batch.output_file_id is not None: + return True + request_counts: Final = batch.request_counts + return request_counts is not None and request_counts.total > 0 and request_counts.completed == 0 + + +@dataclass(frozen=True, slots=True) +class PolledBatch: + id: str + cost_is_final: bool + + +def _polled_batch(kwargs: Mapping[str, object], response_obj: object) -> PolledBatch | None: + """The retrieved batch, read from the logging kwargs when message redaction replaced the logged response.""" + if not is_batch_retrieve_call_type(kwargs.get("call_type")): return None - return response_obj.id if isinstance(response_obj, Batch) else None + if isinstance(response_obj, Batch): + return PolledBatch(id=response_obj.id, cost_is_final=batch_cost_is_final(response_obj)) + stamped_id: Final = kwargs.get(POLLED_BATCH_ID_KWARG) + stamped_cost_is_final: Final = kwargs.get(POLLED_BATCH_COST_IS_FINAL_KWARG) + if not isinstance(stamped_id, str) or not stamped_id or not isinstance(stamped_cost_is_final, bool): + return None + return PolledBatch(id=stamped_id, cost_is_final=stamped_cost_is_final) + + +def defers_batch_cost(kwargs: Mapping[str, object], response_obj: object) -> bool: + """A batch retrieve before the batch's cost is final charges nothing, guardrails included, since the retrieve + that settles the batch charges its whole cost once.""" + polled: Final = _polled_batch(kwargs, response_obj) + return polled is not None and not polled.cost_is_final + + +def pays_only_its_guardrail(call_type: object, kwargs: Mapping[str, object], response_cost: object) -> bool: + """A video poll whose whole cost is its guardrails', charged like any other request.""" + if not is_video_status_call_type(call_type): + return False + return ( + job_cost_of_poll(response_cost, kwargs.get("standard_logging_object")) + <= 0 + < (finite_cost(response_cost) or 0.0) + ) + + +def _requested_video_id(kwargs: Mapping[str, object]) -> str | None: + litellm_params: Final = kwargs.get("litellm_params") + requested: Final = ( + _PAYLOAD_FIELDS.validate_python(litellm_params).get("video_id") if isinstance(litellm_params, Mapping) else None + ) + return requested if isinstance(requested, str) and requested else None + + +def charged_video_id( + call_type: object, kwargs: Mapping[str, object], fallback_video_id: str | None, response_cost: object +) -> str | None: + """The id a finished video's own cost is charged once under. + + That is the id the client polled, which names the deployment that made the video, since a + custom provider's own id can repeat across deployments. The status comes from the logging + kwargs because message redaction replaces the logged video object. + """ + if not is_video_status_call_type(call_type) or kwargs.get(POLLED_VIDEO_STATUS_KWARG) != "completed": + return None + if job_cost_of_poll(response_cost, kwargs.get("standard_logging_object")) <= 0: + return None + video_id: Final = _requested_video_id(kwargs) or fallback_video_id + return None if video_id is None else canonical_video_id(video_id) + + +def _charged_batch(kwargs: Mapping[str, object], response_obj: object, response_cost: float) -> ChargeOnceJob | None: + polled: Final = _polled_batch(kwargs, response_obj) + if polled is None or not polled.cost_is_final or response_cost <= 0: + return None + return ChargeOnceJob(kind="batch", job_id=polled.id) + + +def job_to_charge_once( + kwargs: Mapping[str, object], response_obj: object, response_cost: float +) -> ChargeOnceJob | None: + """A finished batch or video reports its whole cost on every poll, so it is charged once per counter.""" + call_type: Final = kwargs.get("call_type") + if not is_video_status_call_type(call_type): + return _charged_batch(kwargs, response_obj, response_cost) + video_id: Final = charged_video_id( + call_type, kwargs, response_obj.id if isinstance(response_obj, VideoObject) else None, response_cost + ) + if video_id is None: + return None + return ChargeOnceJob( + kind="video", + job_id=video_id, + repeat_poll_cost=repeat_poll_cost(call_type, response_cost, kwargs.get("standard_logging_object")), + ) diff --git a/litellm/litellm_core_utils/chat_completion_agentic_loop.py b/litellm/litellm_core_utils/chat_completion_agentic_loop.py index 2ba47cbb400..ce98d2cbb01 100644 --- a/litellm/litellm_core_utils/chat_completion_agentic_loop.py +++ b/litellm/litellm_core_utils/chat_completion_agentic_loop.py @@ -1,28 +1,35 @@ # this is a patch to allow for agentic loops covering llm_http_handler.py and openai sdk based calling flows for the .completion() api import json -from collections.abc import Mapping +from collections.abc import Awaitable, Iterator, Mapping, Sequence from itertools import chain from types import MappingProxyType -from typing import Final +from typing import Final, TypeVar from pydantic import TypeAdapter, ValidationError +from litellm._internal_context import internal_sub_call from litellm._logging import verbose_logger from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.agentic_followup_failure import mark_agentic_followup_failure, rounds_served_before from litellm.litellm_core_utils.agentic_followup_kwargs import build_agentic_followup_kwargs +from litellm.litellm_core_utils.agentic_loop_refusal import every_claimed_tool_call, finalize_refused_chat_turn from litellm.litellm_core_utils.agentic_loop_settings import ( DEFAULT_MAX_AGENTIC_LOOPS, validated_max_agentic_loops, ) from litellm.litellm_core_utils.core_helpers import qualify_agentic_followup_model +from litellm.litellm_core_utils.hidden_params import get_hidden_params, served_from_cache from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObject +from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import is_str_keyed_dict, object_items from litellm.llms.base_llm.base_model_iterator import MockResponseIterator from litellm.types.integrations.custom_logger import ( CHAT_COMPLETION_AGENTIC_SURFACE, NON_CODE_INTERPRETER_INTERCEPTION_INTERNAL_PREFIXES, + AgenticLoopLimitError, AgenticLoopPlan, AgenticLoopRequestPatch, + AgenticLoopSafetyError, converted_stream_requested, is_interception_internal_key, stashed_stream_options, @@ -30,6 +37,8 @@ from litellm.types.integrations.custom_logger import ( from litellm.types.utils import ModelResponse from litellm.utils import CustomStreamWrapper +_DispatchResult: Final = TypeVar("_DispatchResult") + _FOLLOWUP_INTERNAL_PARAMS: Final = frozenset( ( "acompletion", @@ -43,22 +52,41 @@ _FOLLOWUP_INTERNAL_PARAMS: Final = frozenset( ) +async def bill_first_round_on_failure( + dispatch: Awaitable[_DispatchResult], *, logging_obj: object, response: object, stream: bool +) -> _DispatchResult: + try: + return await dispatch + except Exception as error: + if stream or not isinstance(logging_obj, LiteLLMLoggingObject): + mark_agentic_followup_failure(error, rounds_served_before(error)) + raise + this_round: Final = logging_obj.served_round(response) + served_rounds: Final = (*rounds_served_before(error), *(() if this_round is None else (this_round,))) + mark_agentic_followup_failure(error, served_rounds) + logging_obj.record_served_rounds_for_failure(served_rounds) + raise + + def _gate_overridden(callback: CustomLogger) -> bool: - base: Final = CustomLogger.async_should_run_agentic_loop - func: Final = type(callback).async_should_run_agentic_loop - return getattr(func, "__func__", func) is not getattr(base, "__func__", base) + return type(callback).async_should_run_agentic_loop is not CustomLogger.async_should_run_agentic_loop def _build_plan_overridden(callback: CustomLogger) -> bool: - base: Final = CustomLogger.async_build_agentic_loop_plan - func: Final = type(callback).async_build_agentic_loop_plan - return getattr(func, "__func__", func) is not getattr(base, "__func__", base) + return type(callback).async_build_agentic_loop_plan is not CustomLogger.async_build_agentic_loop_plan + + +def _chat_build_plan_overridden(callback: CustomLogger) -> bool: + return ( + type(callback).async_build_chat_completion_agentic_loop_plan + is not CustomLogger.async_build_chat_completion_agentic_loop_plan + ) def _post_hook_overridden(callback: CustomLogger) -> bool: - base: Final = CustomLogger.async_post_agentic_loop_response_hook - func: Final = type(callback).async_post_agentic_loop_response_hook - return getattr(func, "__func__", func) is not getattr(base, "__func__", base) + return ( + type(callback).async_post_agentic_loop_response_hook is not CustomLogger.async_post_agentic_loop_response_hook + ) _STREAM_OPTIONS_ADAPTER: Final[TypeAdapter[Mapping[str, object] | None]] = TypeAdapter(Mapping[str, object] | None) @@ -75,14 +103,14 @@ def _coerce_int(value: object, default: int) -> int: return int(value) if isinstance(value, (int, str)) else default -def _agentic_loop_settings(kwargs: dict[str, object]) -> tuple[int, int, list[str]]: +def _agentic_loop_settings(kwargs: Mapping[str, object]) -> tuple[int, int, tuple[str, ...]]: depth: Final = _coerce_int(kwargs.get("_agentic_loop_depth"), 0) configured: Final = validated_max_agentic_loops( kwargs.get("max_agentic_loops"), field="litellm_params.max_agentic_loops" ) max_loops: Final = DEFAULT_MAX_AGENTIC_LOOPS if configured is None else configured raw_fingerprints: Final = kwargs.get("_agentic_loop_fingerprints") - fingerprints: Final = [str(fp) for fp in raw_fingerprints] if isinstance(raw_fingerprints, list) else [] + fingerprints: Final = tuple(str(fp) for fp in raw_fingerprints) if isinstance(raw_fingerprints, list) else () return depth, max_loops, fingerprints @@ -95,16 +123,16 @@ def _fingerprint_tools(tool_calls: object) -> str: def _check_agentic_loop_safety( tool_calls: object, - fingerprints: list[str], + fingerprints: Sequence[str], depth: int, max_loops: int, model: str, ) -> str: fingerprint: Final = _fingerprint_tools(tool_calls) if fingerprint in fingerprints: - raise ValueError("Agentic loop detected repeated tool-call fingerprint; aborting rerun") + raise AgenticLoopSafetyError("Agentic loop detected repeated tool-call fingerprint; aborting rerun") if depth >= max_loops: - raise ValueError(f"Exceeded max_agentic_loops={max_loops} for model={model}") + raise AgenticLoopLimitError(f"Exceeded max_agentic_loops={max_loops} for model={model}") return fingerprint @@ -133,6 +161,83 @@ def _converted_stream_replay( ) +def _end_refused_turn( + finalized: ModelResponse, + *, + kwargs: Mapping[str, object], + depth: int, + model: str, + custom_llm_provider: str, + logging_obj: object, +) -> ModelResponse | CustomStreamWrapper: + replay: Final = _converted_stream_replay( + finalized, + kwargs=kwargs, + depth=depth, + model=model, + custom_llm_provider=custom_llm_provider, + logging_obj=logging_obj, + ) + return finalized if replay is None else replay + + +def _request_tools(optional_params: Mapping[str, object]) -> list[dict[str, object]]: + return [tool for tool in object_items(optional_params.get("tools")) if is_str_keyed_dict(tool)] + + +def _custom_loggers(logging_obj: object) -> tuple[CustomLogger, ...]: + import litellm + + dynamic: Final = getattr(logging_obj, "dynamic_success_callbacks", None) or [] + return tuple(callback for callback in (*litellm.callbacks, *dynamic) if isinstance(callback, CustomLogger)) + + +async def _refused_chat_turn( + callbacks: Sequence[CustomLogger], + refusing: CustomLogger, + refused_tool_calls: object, + *, + response: ModelResponse, + model: str, + messages: list[dict[str, object]], + tools: list[dict[str, object]] | None, + custom_llm_provider: str, + kwargs: Mapping[str, object], +) -> ModelResponse: + surface_kwargs: Final = { + **kwargs, + "_agentic_loop_api_surface": CHAT_COMPLETION_AGENTIC_SURFACE, + "custom_llm_provider": custom_llm_provider, + } + + def other_gates() -> Iterator[Awaitable[tuple[bool, object]]]: + for callback in callbacks: + if callback is refusing: + continue + yield callback.async_should_run_chat_completion_agentic_loop( + response=response, + model=model, + messages=messages, + tools=tools, + stream=False, + custom_llm_provider=custom_llm_provider, + kwargs=dict(kwargs), + ) + if _gate_overridden(callback): + yield callback.async_should_run_agentic_loop( + response=response, + model=model, + messages=messages, + tools=tools, + stream=False, + custom_llm_provider=custom_llm_provider, + kwargs=dict(surface_kwargs), + ) + + claimed: Final = await every_claimed_tool_call(refused_tool_calls, other_gates()) + return finalize_refused_chat_turn(response, claimed) + + def _with_agentic_loop_metadata(kwargs_for_followup: Mapping[str, object]) -> Mapping[str, object]: metadata: Final = kwargs_for_followup.get("litellm_metadata") return MappingProxyType( @@ -163,6 +268,12 @@ def _filter_followup_kwargs(source: dict[str, object]) -> dict[str, object]: } +def _leave_pricing_to_the_request(response: object) -> None: + hidden_params: Final = get_hidden_params(response) + if hidden_params is not None and not served_from_cache(response): + hidden_params.pop("response_cost", None) + + async def _execute_chat_completion_agentic_plan( *, plan: AgenticLoopPlan, @@ -174,7 +285,7 @@ async def _execute_chat_completion_agentic_plan( custom_llm_provider: str, depth: int, max_loops: int, - fingerprints: list[str], + fingerprints: Sequence[str], fingerprint: str, ) -> object: import litellm @@ -204,12 +315,13 @@ async def _execute_chat_completion_agentic_plan( ) try: - response_followup = await litellm.acompletion( - model=full_model_name, - messages=patch.messages, - **optional_params_for_followup, - **kwargs_for_followup, - ) + with internal_sub_call(logging_obj.litellm_call_id if isinstance(logging_obj, LiteLLMLoggingObject) else None): + response_followup = await litellm.acompletion( + model=full_model_name, + messages=patch.messages, + **optional_params_for_followup, + **kwargs_for_followup, + ) if _post_hook_overridden(callback): try: response_followup = await callback.async_post_agentic_loop_response_hook( @@ -224,6 +336,7 @@ async def _execute_chat_completion_agentic_plan( model, str(e), ) + _leave_pricing_to_the_request(response_followup) replay: Final = _converted_stream_replay( response_followup, kwargs=kwargs, @@ -250,23 +363,18 @@ async def maybe_run_chat_completion_agentic_loop( *, response: ModelResponse, model: str, - messages: list, - optional_params: dict, + messages: list[dict[str, object]], + optional_params: dict[str, object], kwargs: dict[str, object], logging_obj: object, custom_llm_provider: str, stream: bool, ) -> ModelResponse | CustomStreamWrapper | None: - import litellm - - callbacks: Final = litellm.callbacks + (getattr(logging_obj, "dynamic_success_callbacks", None) or []) + callbacks: Final = _custom_loggers(logging_obj) depth, max_loops, fingerprints = _agentic_loop_settings(kwargs) - tools: Final = optional_params.get("tools", []) + tools: Final = _request_tools(optional_params) for callback in callbacks: - if not isinstance(callback, CustomLogger): - continue - if not _gate_overridden(callback): continue @@ -295,29 +403,39 @@ async def maybe_run_chat_completion_agentic_loop( if not should_run: continue - fingerprint = _check_agentic_loop_safety( - tool_calls=tool_calls, - fingerprints=fingerprints, - depth=depth, - max_loops=max_loops, - model=model, - ) - try: - if not _build_plan_overridden(callback): - return await callback.async_run_agentic_loop( - tools=tool_calls, + fingerprint = _check_agentic_loop_safety( + tool_calls=tool_calls, + fingerprints=fingerprints, + depth=depth, + max_loops=max_loops, + model=model, + ) + except AgenticLoopSafetyError as e: + if stream: + raise + verbose_logger.warning("LiteLLM.AgenticLoopRefused: ending turn [rail=%s]", type(e).__name__) + return _end_refused_turn( + await _refused_chat_turn( + callbacks, + callback, + tool_calls, + response=response, model=model, messages=messages, - response=response, - anthropic_messages_provider_config=None, - anthropic_messages_optional_request_params=optional_params, - logging_obj=logging_obj, - stream=stream, - kwargs=hook_kwargs, - ) + tools=tools, + custom_llm_provider=custom_llm_provider, + kwargs=kwargs, + ), + kwargs=kwargs, + depth=depth, + model=model, + custom_llm_provider=custom_llm_provider, + logging_obj=logging_obj, + ) - plan = await callback.async_build_agentic_loop_plan( + if not _build_plan_overridden(callback): + return await callback.async_run_agentic_loop( tools=tool_calls, model=model, messages=messages, @@ -329,31 +447,38 @@ async def maybe_run_chat_completion_agentic_loop( kwargs=hook_kwargs, ) - if plan.response_override is not None: - return plan.response_override - if plan.terminate: - return response - if not plan.run_agentic_loop: - continue + plan = await callback.async_build_agentic_loop_plan( + tools=tool_calls, + model=model, + messages=messages, + response=response, + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params=optional_params, + logging_obj=logging_obj, + stream=stream, + kwargs=hook_kwargs, + ) - return await _execute_chat_completion_agentic_plan( - plan=plan, - callback=callback, - model=model, - optional_params=optional_params, - kwargs=kwargs, - logging_obj=logging_obj, - custom_llm_provider=custom_llm_provider, - depth=depth, - max_loops=max_loops, - fingerprints=fingerprints, - fingerprint=fingerprint, - ) - except Exception as e: - verbose_logger.exception( - "LiteLLM.AgenticHookError: Exception in chat completion agentic hooks: %s", - str(e), - ) + if plan.response_override is not None: + return plan.response_override + if plan.terminate: + return response + if not plan.run_agentic_loop: + continue + + return await _execute_chat_completion_agentic_plan( + plan=plan, + callback=callback, + model=model, + optional_params=optional_params, + kwargs=kwargs, + logging_obj=logging_obj, + custom_llm_provider=custom_llm_provider, + depth=depth, + max_loops=max_loops, + fingerprints=fingerprints, + fingerprint=fingerprint, + ) return _converted_stream_replay( response, @@ -363,3 +488,113 @@ async def maybe_run_chat_completion_agentic_loop( custom_llm_provider=custom_llm_provider, logging_obj=logging_obj, ) + + +async def run_chat_completion_agentic_hooks( + *, + response: ModelResponse, + model: str, + messages: list[dict[str, object]], + optional_params: dict[str, object], + kwargs: dict[str, object], + logging_obj: LiteLLMLoggingObject, + custom_llm_provider: str, + stream: bool, +) -> object | None: + callbacks: Final = _custom_loggers(logging_obj) + depth, max_loops, fingerprints = _agentic_loop_settings(kwargs) + tools: Final = _request_tools(optional_params) + hook_kwargs: Final = {**kwargs, "custom_llm_provider": custom_llm_provider} + + for callback in callbacks: + try: + should_run, tool_calls = await callback.async_should_run_chat_completion_agentic_loop( + response=response, + model=model, + messages=messages, + tools=tools, + stream=stream, + custom_llm_provider=custom_llm_provider, + kwargs=kwargs, + ) + except Exception: + verbose_logger.exception( + "LiteLLM.AgenticHookError: Exception in async_should_run_chat_completion_agentic_loop" + ) + continue + + if not should_run: + continue + + try: + fingerprint = _check_agentic_loop_safety( + tool_calls=tool_calls, + fingerprints=fingerprints, + depth=depth, + max_loops=max_loops, + model=model, + ) + except AgenticLoopSafetyError as e: + if stream: + raise + verbose_logger.warning("LiteLLM.AgenticLoopRefused: ending turn [rail=%s]", type(e).__name__) + return await _refused_chat_turn( + callbacks, + callback, + tool_calls, + response=response, + model=model, + messages=messages, + tools=tools, + custom_llm_provider=custom_llm_provider, + kwargs=kwargs, + ) + + if not _chat_build_plan_overridden(callback): + return await callback.async_run_chat_completion_agentic_loop( + tools=tool_calls, + model=model, + messages=messages, + response=response, + optional_params=optional_params, + logging_obj=logging_obj, + stream=stream, + kwargs=hook_kwargs, + ) + + plan = await callback.async_build_chat_completion_agentic_loop_plan( + tools=tool_calls, + model=model, + messages=messages, + response=response, + optional_params=optional_params, + logging_obj=logging_obj, + stream=stream, + kwargs=hook_kwargs, + ) + + if plan.response_override is not None: + return plan.response_override + if plan.terminate: + verbose_logger.debug( + "Agentic chat loop terminated by callback=%s reason=%s", type(callback).__name__, plan.stop_reason + ) + return response + if not plan.run_agentic_loop: + continue + + return await _execute_chat_completion_agentic_plan( + plan=plan, + callback=callback, + model=model, + optional_params=optional_params, + kwargs=hook_kwargs, + logging_obj=logging_obj, + custom_llm_provider=custom_llm_provider, + depth=depth, + max_loops=max_loops, + fingerprints=fingerprints, + fingerprint=fingerprint, + ) + + return None diff --git a/litellm/litellm_core_utils/core_helpers.py b/litellm/litellm_core_utils/core_helpers.py index 58189140a98..b28d5a4ea21 100644 --- a/litellm/litellm_core_utils/core_helpers.py +++ b/litellm/litellm_core_utils/core_helpers.py @@ -4,7 +4,7 @@ import copy import logging import math import re -from collections.abc import Collection, Iterable, Iterator, Mapping +from collections.abc import Collection, Iterable, Iterator, Mapping, Sequence from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, Protocol, TypeVar, cast, runtime_checkable @@ -97,13 +97,28 @@ def safe_divide_seconds(seconds: float, denominator: float, default: float | Non return float(seconds / denominator) -_DROP_PARAMS_BOOL: Final = TypeAdapter(bool) +_LAX_BOOL: Final = TypeAdapter(bool) def as_str_mapping(value: object) -> Mapping[str, object] | None: return value if isinstance(value, Mapping) else None +def as_object_list(value: object) -> Sequence[object] | None: + return value if isinstance(value, list) else None + + +_Key = TypeVar("_Key") # rebind-ok: a TypeVar cannot be Final +_Value = TypeVar("_Value") # rebind-ok: a TypeVar cannot be Final + + +def without( + mapping: Mapping[_Key, _Value], *keys: object +) -> dict[_Key, _Value]: # mutable-ok: a fresh copy the caller owns + """``mapping`` without ``keys``, as a new dict in the same order; ``mapping`` is unchanged.""" + return {key: value for key, value in mapping.items() if key not in keys} + + def decoded_json_object(value: object) -> Mapping[str, object]: mapping: Final = as_str_mapping(value) if mapping is not None: @@ -156,15 +171,19 @@ def attribute_items(source: object, name: str) -> Iterable[object]: return iter_items(value) if value else () -def normalize_drop_params(value: object) -> bool | None: +def lax_bool(value: object) -> bool | None: if value is None or isinstance(value, bool): return value try: - return _DROP_PARAMS_BOOL.validate_python(value.strip() if isinstance(value, str) else value) + return _LAX_BOOL.validate_python(value.strip() if isinstance(value, str) else value) except ValidationError: return None +def normalize_drop_params(value: object) -> bool | None: + return lax_bool(value) + + def drops_unsupported_params(drop_params: object) -> bool: return litellm.drop_params is True or normalize_drop_params(drop_params) is True diff --git a/litellm/litellm_core_utils/decisions_pricing.py b/litellm/litellm_core_utils/decisions_pricing.py index 9199a8097cc..accd315da23 100644 --- a/litellm/litellm_core_utils/decisions_pricing.py +++ b/litellm/litellm_core_utils/decisions_pricing.py @@ -12,6 +12,7 @@ from typing import Final DECISIONS_PRICING_SUFFIX: Final = "_decisions" DECISIONS_CALL_TYPES: Final = frozenset({"decisions", "adecisions", "systemone", "asystemone"}) +QUERY_PRICED_DECISIONS_PROVIDERS: Final = frozenset({"parallel_ai"}) def is_decisions_call_type(call_type: str) -> bool: @@ -27,6 +28,17 @@ def decisions_pricing_fields(row: Mapping[str, object]) -> Mapping[str, object]: } +def decisions_request_price(model_info: Mapping[str, object], overrides: Mapping[str, object]) -> float | None: + if model_info.get("litellm_provider") not in QUERY_PRICED_DECISIONS_PROVIDERS: + return None + rates: Final = {**model_info, **overrides} + request_price: Final = rates.get("input_cost_per_query") + if not isinstance(request_price, (int, float)): + return None + bills_tokens: Final = any(rates.get(field) for field in ("input_cost_per_token", "output_cost_per_token")) + return None if bills_tokens and "input_cost_per_query" not in overrides else float(request_price) + + def apply_decisions_pricing(row: Mapping[str, object]) -> Mapping[str, object]: """Return ``row`` priced for a Decisions call: ``_decisions`` values replace their plain fields.""" plain: Final = {key: value for key, value in row.items() if not key.endswith(DECISIONS_PRICING_SUFFIX)} diff --git a/litellm/litellm_core_utils/deployment_pricing.py b/litellm/litellm_core_utils/deployment_pricing.py index 622cc91ab5e..7aa85921634 100644 --- a/litellm/litellm_core_utils/deployment_pricing.py +++ b/litellm/litellm_core_utils/deployment_pricing.py @@ -1,4 +1,4 @@ -from collections.abc import Iterator, Mapping +from collections.abc import Iterable, Iterator, Mapping from types import MappingProxyType from typing import Final @@ -25,6 +25,14 @@ def deployment_pricing_models(deployment: object) -> tuple[str, ...]: return pricing_models(info.get("base_model") or params.get("base_model"), params.get("model")) +def deployment_backend_model(deployment: object) -> str: + return next(iter(deployment_pricing_models(deployment)), "") + + +def deployment_backend_models(deployments: Iterable[object]) -> tuple[str, ...]: + return tuple(map(deployment_backend_model, deployments)) + + def _named_models(*candidates: object) -> Iterator[str]: return (candidate for candidate in candidates if isinstance(candidate, str) and candidate) diff --git a/litellm/litellm_core_utils/error_normalization.py b/litellm/litellm_core_utils/error_normalization.py index 00317e502ec..717db34ede5 100644 --- a/litellm/litellm_core_utils/error_normalization.py +++ b/litellm/litellm_core_utils/error_normalization.py @@ -133,6 +133,8 @@ _STATUS_CODE_MAP: Final[Mapping[str, str]] = MappingProxyType( } ) +_OVERLOADED_STATUS_CODE: Final = "529" + _INTERNAL_STATE_EXCEPTIONS: Final[tuple[type[BaseException], ...]] = ( TypeError, KeyError, @@ -201,6 +203,8 @@ def normalize_error(exc: Exception | None, status_code: str, message: str) -> st ) if by_message is not None: return by_message + if status_code == _OVERLOADED_STATUS_CODE: + return PROVIDER_OVERLOADED by_class: Final = _classify_by_class(exc) if by_class is not None: return by_class diff --git a/litellm/litellm_core_utils/exception_mapping_utils.py b/litellm/litellm_core_utils/exception_mapping_utils.py index 85c232ad3f4..6d39f272f3e 100644 --- a/litellm/litellm_core_utils/exception_mapping_utils.py +++ b/litellm/litellm_core_utils/exception_mapping_utils.py @@ -11,6 +11,7 @@ from pydantic import TypeAdapter, ValidationError import litellm from litellm._logging import _ENABLE_SECRET_REDACTION, redact_string, verbose_logger +from litellm.litellm_core_utils.agentic_followup_failure import carry_agentic_followup_mark from litellm.litellm_core_utils.bug_report import ( bug_report_notice, build_bug_report, @@ -107,6 +108,7 @@ class ExceptionCheckers: "exceeds the available context size", # llama.cpp/Lemonade "exceeds the maximum number of tokens allowed", # Gemini '"code": "context_length_exceeded"', + "prompt is too long", ] for substring in known_exception_substrings: if substring in _error_str_lowercase: @@ -604,6 +606,11 @@ def _map_openai_exception( ) +def _anthropic_overload_status(original_exception: _ProviderHTTPException) -> int | None: + upstream_status: Final = getattr(original_exception, "status_code", None) + return 529 if isinstance(upstream_status, int) and upstream_status >= 500 else None + + def _map_anthropic_exception( *, model: str, @@ -629,6 +636,7 @@ def _map_anthropic_exception( message=f"AnthropicError - {error_str}", model=model, llm_provider="anthropic", + provider_status_code=_anthropic_overload_status(original_exception), ) if "Invalid API Key" in error_str: raise AuthenticationError( @@ -693,6 +701,7 @@ def _map_anthropic_exception( llm_provider="anthropic", model=model, response=getattr(original_exception, "response", None), + provider_status_code=original_exception.status_code, ) elif original_exception.status_code == 502: raise BadGatewayError( @@ -2894,6 +2903,7 @@ def exception_type( request=httpx.Request(method="POST", url="https://api.openai.com/v1/"), # stub the request ) except Exception as e: + carry_agentic_followup_mark(source=original_exception, mapped=e) # LOGGING exception_logging( logger_fn=None, @@ -2919,6 +2929,7 @@ def exception_type( model="", ) setattr(raised_exc, "litellm_response_headers", litellm_response_headers) + carry_agentic_followup_mark(source=original_exception, mapped=raised_exc) raise raised_exc diff --git a/litellm/litellm_core_utils/get_litellm_params.py b/litellm/litellm_core_utils/get_litellm_params.py index d6d9be4e132..d0ac5c00513 100644 --- a/litellm/litellm_core_utils/get_litellm_params.py +++ b/litellm/litellm_core_utils/get_litellm_params.py @@ -33,6 +33,9 @@ AWS_CREDENTIAL_KWARGS_KEYS: Final = frozenset( ) PROVIDER_AFFINITY_HEADER_KWARG_KEY: Final = "provider_affinity_header" +AGENTIC_LOOP_CONTROL_KWARGS_KEYS: Final = frozenset( + {"_agentic_loop_depth", "_agentic_loop_fingerprints", "max_agentic_loops"} +) OAUTH_TOKEN_EXCHANGE_KWARGS_KEYS: Final = frozenset( { "token_exchange_endpoint", @@ -94,6 +97,7 @@ OPTIONAL_KWARGS_KEYS: Final = ( | ANTHROPIC_WIF_KWARGS_KEYS | OPENAI_WIF_KWARGS_KEYS | OAUTH_TOKEN_EXCHANGE_KWARGS_KEYS + | AGENTIC_LOOP_CONTROL_KWARGS_KEYS | frozenset(CustomPricingLiteLLMParams.model_fields) ) diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py index 38242291b71..1ffb5e2f8e5 100644 --- a/litellm/litellm_core_utils/get_llm_provider_logic.py +++ b/litellm/litellm_core_utils/get_llm_provider_logic.py @@ -13,6 +13,7 @@ from litellm.litellm_core_utils.fallback_generalizations import ( match_routing_generalization, ) from litellm.llms.openai_like.json_loader import JSONProviderRegistry +from litellm.llms.opencode.common_utils import is_opencode_api_base from litellm.secret_managers.main import get_secret, get_secret_str from ..types.router import GenericLiteLLMParams, LiteLLM_Params @@ -146,6 +147,10 @@ def handle_anthropic_text_model_custom_llm_provider( return model, custom_llm_provider +def declared_provider(model: str | None, custom_llm_provider: str | None = None) -> str | None: + return custom_llm_provider or (model.split("/", 1)[0] if model and "/" in model else None) + + def declared_authenticating_provider(model: str | None, custom_llm_provider: str | None = None) -> str | None: """The authenticating provider this pair already names, or None. @@ -154,7 +159,7 @@ def declared_authenticating_provider(model: str | None, custom_llm_provider: str and for a declared pair the resolver's answer is the declaration itself, so metadata callers adopt the declaration instead of resolving. """ - declared: Final = custom_llm_provider or (model.split("/", 1)[0] if model and "/" in model else None) + declared: Final = declared_provider(model, custom_llm_provider) return declared if declared in PROVIDERS_THAT_AUTHENTICATE_ON_PROVIDER_INFO else None @@ -1004,6 +1009,4 @@ def _get_openai_compatible_provider_info( def get_provider_affinity_header(api_base: str | None) -> str | None: - from litellm.llms.opencode.transformation import OpenCodeProviderAdapter - - return OpenCodeProviderAdapter().get_provider_affinity_header(api_base) + return "x-opencode-session" if is_opencode_api_base(api_base) else None diff --git a/litellm/litellm_core_utils/get_model_cost_map.py b/litellm/litellm_core_utils/get_model_cost_map.py index 7fc6eab6c60..e452befe295 100644 --- a/litellm/litellm_core_utils/get_model_cost_map.py +++ b/litellm/litellm_core_utils/get_model_cost_map.py @@ -320,9 +320,7 @@ def _classify_fetch_content(content: bytes, url: str, etag: str | None) -> _Fetc return ModelCostMapReloadUnavailable(reason=f"invalid JSON from {url}: {e}") if not isinstance(parsed, dict): return ModelCostMapReloadUnavailable(reason=f"expected a JSON object from {url}, got {type(parsed).__name__}") - model_cost_map: Final = cast( # cast-ok: JSON object keys are strings by definition - dict[str, object], parsed - ) + model_cost_map: Final = _BUNDLED_CATALOG_ADAPTER.validate_python(parsed) return ModelCostMapReloaded(model_cost_map=model_cost_map, revision=git_blob_id(content), etag=etag) diff --git a/litellm/litellm_core_utils/get_provider_specific_headers.py b/litellm/litellm_core_utils/get_provider_specific_headers.py index 62dfcb073e5..b5916369917 100644 --- a/litellm/litellm_core_utils/get_provider_specific_headers.py +++ b/litellm/litellm_core_utils/get_provider_specific_headers.py @@ -12,10 +12,18 @@ _PROVIDER_HEADERS: Final[TypeAdapter[ProviderSpecificHeader | Sequence[ProviderS class ProviderSpecificHeaderUtils: @staticmethod - def forwarded_authorization(provider_specific_header: object, custom_llm_provider: str | None) -> str | None: - headers: Final = ProviderSpecificHeaderUtils.get_provider_specific_headers( + def validated_provider_specific_headers( + provider_specific_header: object, custom_llm_provider: str | None + ) -> Mapping[str, str]: + return ProviderSpecificHeaderUtils.get_provider_specific_headers( _PROVIDER_HEADERS.validate_python(provider_specific_header), custom_llm_provider ) + + @staticmethod + def forwarded_authorization(provider_specific_header: object, custom_llm_provider: str | None) -> str | None: + headers: Final = ProviderSpecificHeaderUtils.validated_provider_specific_headers( + provider_specific_header, custom_llm_provider + ) return next((value for key, value in headers.items() if key.lower() == "authorization"), None) @staticmethod diff --git a/litellm/litellm_core_utils/internal_call_metadata.py b/litellm/litellm_core_utils/internal_call_metadata.py index 453d4358b35..138a01c6524 100644 --- a/litellm/litellm_core_utils/internal_call_metadata.py +++ b/litellm/litellm_core_utils/internal_call_metadata.py @@ -26,7 +26,12 @@ from litellm.constants import ( MANAGED_BACKGROUND_RESPONSE_METADATA_KEY, NON_INFERENCE_CALL_TYPES, ) +from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.litellm_core_utils.initialize_dynamic_callback_params import initialize_standard_callback_dynamic_params +from litellm.types.passthrough_endpoints.pass_through_endpoints import ( + SETTLES_BACKGROUND_RESPONSE_KWARG, + BackgroundResponseSettlement, +) from litellm.types.utils import ( BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN, BACKGROUND_RESPONSE_STATUS_POLL_CALL_ORIGIN, @@ -35,6 +40,8 @@ from litellm.types.utils import ( BUDGET_RESERVATION_METADATA_KEYS: Final = frozenset({"user_api_key_budget_reservation"}) +BACKGROUND_RESPONSE_COST_REQUEST_ID_SUFFIX: Final = "_background_cost" + ITPM_RESERVED_KEY: Final = "_litellm_itpm_reserved" OTPM_RESERVED_KEY: Final = "_litellm_otpm_reserved" ITPM_CACHE_KEY: Final = "_litellm_itpm_cache_key" @@ -151,6 +158,26 @@ def is_unbilled_non_inference_call_from_params( return is_unbilled_non_inference_call(call_type, metadata, response) +def settles_background_response(call_type: str, metadata: Mapping[str, object], kwargs: Mapping[str, object]) -> bool: + return kwargs.get(SETTLES_BACKGROUND_RESPONSE_KWARG) is BackgroundResponseSettlement.SETTLES or ( + call_type in NON_INFERENCE_CALL_TYPES + and metadata.get(INTERNAL_CALL_ORIGIN_METADATA_KEY) == BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN + ) + + +def logged_event_key(kwargs: Mapping[str, object], event_id: str) -> str: + call_type: Final = kwargs.get("call_type") + litellm_params: Final = as_str_mapping(kwargs.get("litellm_params")) or {} + metadata: Final = ( + as_str_mapping(litellm_params.get("litellm_metadata")) or as_str_mapping(litellm_params.get("metadata")) or {} + ) + if not event_id or not settles_background_response( + call_type if isinstance(call_type, str) else "", metadata, kwargs + ): + return event_id + return f"{event_id}{BACKGROUND_RESPONSE_COST_REQUEST_ID_SUFFIX}" + + def sanitize_user_api_key_auth(auth: object) -> object: """Copy of the auth object with its budget reservation removed; the cost callback falls back to reading the reservation from inside the auth object.""" diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py index 639003c9a6a..ce57a9bd4a5 100644 --- a/litellm/litellm_core_utils/litellm_logging.py +++ b/litellm/litellm_core_utils/litellm_logging.py @@ -19,9 +19,11 @@ from datetime import datetime as dt_object from enum import Enum from functools import lru_cache from types import MappingProxyType, TracebackType -from typing import TYPE_CHECKING, Any, ClassVar, Final, Literal, NamedTuple, cast +from typing import TYPE_CHECKING, Any, Final, Literal, NamedTuple, TypeVar, cast from httpx import Response, Timeout +from openai import AsyncStream as OpenAIAsyncStream +from openai import Stream as OpenAIStream from pydantic import BaseModel, JsonValue, TypeAdapter import litellm @@ -36,7 +38,7 @@ from litellm._logging import ( verbose_logger, ) from litellm._uuid import uuid -from litellm.batches.batch_utils import batch_cost_is_final, handle_completed_batch +from litellm.batches.batch_utils import handle_completed_batch from litellm.caching.caching import DualCache from litellm.caching.caching_handler import LLMCachingHandler from litellm.caching.redis_batch import flush_post_call_redis_batches @@ -52,8 +54,11 @@ from litellm.constants import ( REDACTED_BY_LITELLM, ) from litellm.cost_calculator import ( + BaseTokenUsageProcessor, RealtimeAPITokenUsageProcessor, ResponsesWebSocketTokenUsageProcessor, + declared_cost_map_pricing, + get_response_cost_from_hidden_params, get_usage_object, pricing_entry_for_cost_calc, select_model_name_for_cost_calc, @@ -72,6 +77,13 @@ from litellm.integrations.deepeval.deepeval import DeepEvalLogger from litellm.integrations.langtrace import langtrace_trace_endpoint from litellm.integrations.mlflow import MlflowLogger from litellm.integrations.sqs import SQSLogger +from litellm.litellm_core_utils.add_retry_fallback_headers import get_hidden_params_dict +from litellm.litellm_core_utils.agentic_followup_failure import ServedRound +from litellm.litellm_core_utils.batch_utils import ( + POLLED_BATCH_COST_IS_FINAL_KWARG, + POLLED_BATCH_ID_KWARG, + batch_cost_is_final, +) from litellm.litellm_core_utils.classifier_logging import ( classifier_audit_fields, classifier_input_snapshot, @@ -97,6 +109,7 @@ from litellm.litellm_core_utils.hidden_params import ( get_hidden_params, served_from_cache, set_hidden_param, + set_hidden_params, ) from litellm.litellm_core_utils.internal_call_metadata import ( MODEL_ACCESS_GROUP_METADATA_KEY, @@ -122,6 +135,7 @@ from litellm.litellm_core_utils.llm_cost_calc.zero_cost_diagnostic import ( diagnose_zero_cost, zero_cost_warning, ) +from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response import LiteLLMResponseObjectHandler from litellm.litellm_core_utils.logging_utils import ( truncate_base64_in_messages, truncate_base64_in_messages_async, @@ -142,7 +156,7 @@ from litellm.litellm_core_utils.served_output_texts import ( from litellm.litellm_core_utils.thread_pool_executor import executor from litellm.llms.base_llm.ocr.transformation import OCRResponse from litellm.llms.base_llm.search.transformation import SearchResponse -from litellm.responses.utils import ResponseAPILoggingUtils +from litellm.responses.utils import ResponseAPILoggingUtils, ResponsesAPIRequestUtils from litellm.types.agents import LiteLLMSendMessageResponse from litellm.types.containers.main import ContainerObject from litellm.types.decisions import DecisionsResponse, OpenAIDecisionResponse @@ -211,7 +225,11 @@ from litellm.types.utils import ( batch_chat_usage, ) from litellm.types.videos.main import VideoObject -from litellm.utils import get_base_model_from_metadata, print_verbose +from litellm.types.videos.utils import POLLED_VIDEO_STATUS_KWARG +from litellm.utils import ( + get_base_model_from_metadata, + print_verbose, +) from ..integrations.argilla import ArgillaLogger from ..integrations.arize.arize_phoenix import ArizePhoenixLogger @@ -271,8 +289,6 @@ if TYPE_CHECKING: from litellm.llms.base_llm.passthrough.transformation import PassthroughStreamCollector from litellm.proxy.hooks.autorouter_baseline_cache import BaselineCacheContext, CapturedBaselineObservation from litellm.proxy.hooks.search_free_tier import SearchAllowanceAllocation - from litellm.proxy.spend_tracking.usage_capture import CapturedUsage - from litellm.proxy.spend_tracking.usage_meter import UsageCaptureError try: from litellm_enterprise.enterprise_callbacks.callback_controls import ( EnterpriseCallbackControls, @@ -300,6 +316,11 @@ class _EnterpriseAlertingLoggers(NamedTuple): smtp_email: type[CustomLogger] +class BridgedChatRequest(NamedTuple): + optional_params: Mapping[str, object] + litellm_params: Mapping[str, object] + + @functools.cache def _enterprise_alerting_loggers() -> _EnterpriseAlertingLoggers: try: @@ -580,6 +601,7 @@ _LITELLM_PARAMS: Final = TypeAdapter(dict[str, object]) _SERVED_ANTHROPIC_BODY: Final = TypeAdapter(dict[str, object]) _GOOGLE_USAGE_FIELDS: Final = frozenset(UsageMetadata.__annotations__) _REDACTED_RESULT: Final = TypeAdapter(object) +_LoggedResponse: Final = TypeVar("_LoggedResponse") _GUARDRAIL_INFORMATION_KEY: Final = "standard_logging_guardrail_information" @@ -644,54 +666,7 @@ class UsageObservation(Enum): ESTIMATED = "estimated" -@dataclass(frozen=True, slots=True) -class UsageCaptureObservation: - usage_json: str | None - provenance: UsageObservation - response_cost: float | None = None - - @classmethod - def from_usage( - cls, usage: Usage | None, provenance: UsageObservation, response_cost: float | None = None - ) -> "UsageCaptureObservation | UsageCaptureError": - from litellm.proxy.spend_tracking.usage_meter import UsageCaptureError - - try: - serialized: Final = ( - None if usage is None or provenance is UsageObservation.UNKNOWN else usage.model_dump_json() - ) - except Exception as error: # noqa: BLE001 # observation failures must not interrupt legacy retry handling - return UsageCaptureError(str(error)) - else: - return cls(serialized, provenance, response_cost) - - class Logging(LiteLLMLoggingBaseClass): - usage_capture_callback: ClassVar[ - Callable[ - ["Logging", object, datetime.datetime, datetime.datetime, bool], "CapturedUsage | UsageCaptureError | None" - ] - | None - ] = None - - def capture_usage_before_logging( - self, - response: object, - start_time: datetime.datetime | None = None, - end_time: datetime.datetime | None = None, - *, - freeze_only: bool = False, - ) -> None: - capture: Final = type(self).usage_capture_callback - if capture is not None and (not self.stream or self._is_assembled_stream_success(response)): - capture( - self, - response, - start_time or self.start_time, - end_time or datetime.datetime.now(datetime.timezone.utc), - freeze_only, - ) - global \ supabaseClient, \ promptLayerLogger, \ @@ -706,6 +681,7 @@ class Logging(LiteLLMLoggingBaseClass): custom_pricing: bool = False custom_cost_per_token: CostPerToken | None = None custom_cost_per_second: float | None = None + custom_model_info: ModelInfo | None = None replaced_global_callback_keys: frozenset[str] = frozenset() stream_options = None litellm_request_debug: bool = False @@ -872,6 +848,8 @@ class Logging(LiteLLMLoggingBaseClass): # The model the proxy shows the client on streamed chunks. The logged streamed response carries it # once that response is priced, the same way a non-streamed response is logged self.client_facing_stream_model: str | None = None + self.client_facing_response_id: str | None = None + self.bridged_chat_request: BridgedChatRequest | None = None self.zero_cost_warned: bool = False self.llm_caching_handler: LLMCachingHandler | None = None @@ -918,12 +896,17 @@ class Logging(LiteLLMLoggingBaseClass): # post_call guardrails have run; the @client decorator then stores the # enqueue closure here instead of firing it immediately. self.defer_async_logging: bool = False + self.drops_stream_token_ids: bool = False self.enqueue_deferred_logging: Callable[[], None] | None = None self._async_success_scheduled: bool = False self._async_success_enqueued: bool = False self._sync_success_scheduled: bool = False self.on_detached_stream_failure: Callable[[Exception], Awaitable[None]] | None = None self._stream_failure_claimed: bool = False + self._stash_owed_on_success: bool = False + self._stash_billed_by_continuation: bool = False + self._failed_attempts_owed_on_success: tuple[ServedRound, ...] = () + self.failed_attempts_billed_on_success: tuple[ServedRound, ...] = () self.shadow_eval_request_snapshot: GuardrailRequestSnapshot | None = None def copy_for_new_call(self, litellm_call_id: str, start_time: datetime.datetime) -> "Logging": @@ -2128,6 +2111,9 @@ class Logging(LiteLLMLoggingBaseClass): if resolved_cache_hit is True: return 0.0 + if isinstance(result, (OpenAIStream, OpenAIAsyncStream)): + return None + if is_unbilled_non_inference_call( self.call_type, StandardLoggingPayloadSetup.merge_litellm_metadata(self.litellm_params), result ): @@ -2205,6 +2191,7 @@ class Logging(LiteLLMLoggingBaseClass): "custom_pricing": custom_pricing, "custom_cost_per_token": self.custom_cost_per_token if custom_pricing else None, "custom_cost_per_second": self.custom_cost_per_second if custom_pricing else None, + "requested_model_info_override": self.custom_model_info if custom_pricing else None, "prompt": prompt, "standard_built_in_tools_params": self.standard_built_in_tools_params, "router_model_id": router_model_id, @@ -2296,12 +2283,19 @@ class Logging(LiteLLMLoggingBaseClass): return 0.0 def uncached_price(self, result: object) -> UncachedPrice: + return self._price_without_recording(result, cache_hit=False, ignore_stamped_cost=True) + + def _price_without_recording( + self, result: object, *, cache_hit: bool | None, ignore_stamped_cost: bool + ) -> UncachedPrice: previous_cost_breakdown: Final = self.cost_breakdown previous_billed_token_rates: Final = self.billed_token_rates debug_key: Final = "response_cost_failure_debug_information" previous_failure_debug_info: Final = self.model_call_details.get(debug_key) try: - cost: Final = self.response_cost_calculator(result=result, cache_hit=False, ignore_stamped_cost=True) + cost: Final = self.response_cost_calculator( + result=result, cache_hit=cache_hit, ignore_stamped_cost=ignore_stamped_cost + ) return UncachedPrice(cost=cost, cost_breakdown=self.cost_breakdown) finally: self.cost_breakdown = previous_cost_breakdown @@ -2401,6 +2395,10 @@ class Logging(LiteLLMLoggingBaseClass): additional_headers=additional_headers, ) + def set_per_call_pricing(self, custom_model_info: ModelInfo | None) -> None: + """Price this call from its own full price entry instead of ``litellm.model_cost``.""" + self.custom_model_info = custom_model_info + def custom_pricing_for(self, result: object) -> bool: if self.spilled_over_ptu_for(result): return False @@ -2540,11 +2538,6 @@ class Logging(LiteLLMLoggingBaseClass): ) return - self.capture_usage_before_logging( - TypeAdapter(object).validate_python(result), - TypeAdapter[datetime.datetime | None](datetime.datetime | None).validate_python(start_time), - TypeAdapter[datetime.datetime | None](datetime.datetime | None).validate_python(end_time), - ) await self.async_success_handler( result, start_time=start_time, @@ -2566,6 +2559,33 @@ class Logging(LiteLLMLoggingBaseClass): **kwargs, ) + def _response_price_is_known(self, result: object, cost: float, payload: StandardLoggingPayload) -> bool: + if ( + cost != 0 + or self._provider_reported_cost == 0 + or get_response_cost_from_hidden_params(get_hidden_params_dict(result)) == 0 + ): + return True + if self.model_call_details.get("cache_hit") is True or _served_from_cache_at_no_charge(result): + return True + params: Final = _LITELLM_PARAMS.validate_python(self._model_call_details_view.get("litellm_params") or {}) + if is_unbilled_non_inference_call( + payload["call_type"], StandardLoggingPayloadSetup.merge_litellm_metadata(params), result + ): + return True + if self.custom_cost_per_token is not None or self.custom_cost_per_second is not None: + return True + passthrough: Final = _LITELLM_PARAMS.validate_python( + self._model_call_details_view.get("passthrough_logging_payload") or {} + ) + if passthrough.get("cost_per_request") is not None: + return True + model_info: Final = payload["model_map_information"]["model_map_value"] + if model_info is None: + return False + prices: Final = declared_cost_map_pricing(model_info["key"], model_info["key"], payload["custom_llm_provider"]) + return any(value is not None and ("cost" in key or "pricing" in key) for key, value in prices.items()) + def prepare_response_cost(self, response: object, now: datetime.datetime) -> PreparedCost | None: if self.prepared_cost is not None: return self.prepared_cost @@ -2618,6 +2638,7 @@ class Logging(LiteLLMLoggingBaseClass): "cost_breakdown": copy.deepcopy(payload["cost_breakdown"]), }, usage, + price_known=self._response_price_is_known(prepared[2], raw_cost, payload), ) self.record_partial_usage_for_failure( usage, raw_cost, observation=self.model_call_details["_accounting_usage_observed"] @@ -2628,20 +2649,12 @@ class Logging(LiteLLMLoggingBaseClass): self.finalized_cost = finalized self.model_call_details["response_cost"] = finalized.amount - def record_usage_capture(self, captured: "CapturedUsage") -> None: - self.model_call_details["_accounting_capture"] = captured - - def record_usage_pricing(self, pricing: object) -> None: - self.model_call_details["_accounting_pricing_snapshot"] = pricing - def record_partial_usage_for_failure( self, usage: Usage, response_cost: float, *, observation: UsageObservation = UsageObservation.KNOWN ) -> None: """Stash what an interrupted stream already consumed so the failure log bills it instead of zero.""" self.model_call_details["combined_usage_object"] = usage self.model_call_details["response_cost"] = response_cost - if type(self).usage_capture_callback is not None: - self.model_call_details["_accounting_usage_observed"] = observation def record_failure_after_earlier_rounds( self, earlier: BilledRoundsSpend, failed_usage: Usage, failed_cost: float @@ -2721,66 +2734,28 @@ class Logging(LiteLLMLoggingBaseClass): own usage while the request's failure log still bills every attempt.""" usage: Final = self._model_call_details_view.get("combined_usage_object") response_cost: Final = self._model_call_details_view.get("response_cost") - if isinstance(usage, Usage) and type(self).usage_capture_callback is not None: - self.capture_failed_attempt_usage(usage) - self.model_call_details.pop("_accounting_capture", None) + billed_by_continuation: Final = self._stash_billed_by_continuation + owed_on_success: Final = self._stash_owed_on_success + self._stash_billed_by_continuation = False + self._stash_owed_on_success = False self.model_call_details.pop("_accounting_pricing_snapshot", None) self.model_call_details.pop("_accounting_usage_observed", None) self.model_call_details.pop("combined_usage_object", None) self.model_call_details.pop("response_cost", None) - if isinstance(usage, Usage): - self.model_call_details["current_attempt_api_call_start_time"] = None - self.model_call_details["failed_attempts_usage"] = ( - *self.model_call_details.get("failed_attempts_usage", ()), - (usage, float(response_cost) if isinstance(response_cost, (int, float)) else 0.0), - ) - - def capture_failed_attempt_usage(self, usage: Usage) -> None: - from litellm.constants import BILLED_RETRY_ATTEMPT_METADATA_KEY - from litellm.proxy.spend_tracking.usage_capture import CapturedUsage - - capture: Final = type(self).usage_capture_callback - if capture is None: + if not isinstance(usage, Usage): return - attempt: Final = self.attempt_scoped_copy() - attempt.prepared_cost = None - attempt.finalized_cost = None - identity: Final = ( - f"{self.litellm_call_id}-attempt-{len(self.model_call_details.get('failed_attempts_usage', ()))}" - ) - params: Final = _LITELLM_PARAMS.validate_python(self.model_call_details.get("litellm_params") or {}) - metadata: Final = StandardLoggingPayloadSetup.merge_litellm_metadata(params) - observed: Final[object] = self.model_call_details.get("_accounting_usage_observed") - cost: Final[object] = self.model_call_details.get("response_cost") - attempt.model_call_details = { - **attempt.model_call_details, - "litellm_call_id": identity, - "parent_request_id": self.litellm_call_id, - "_accounting_capture": None, - "_accounting_prior_captures": (), - "_accounting_usage_snapshot": UsageCaptureObservation.from_usage( - usage, - observed if isinstance(observed, UsageObservation) else UsageObservation.KNOWN, - float(cost) if isinstance(cost, (int, float)) else None, - ), - "litellm_params": { - **params, - "metadata": {**metadata, BILLED_RETRY_ATTEMPT_METADATA_KEY: True, "status": "failure"}, - "litellm_metadata": {**metadata, BILLED_RETRY_ATTEMPT_METADATA_KEY: True, "status": "failure"}, - }, - } - captured: Final = capture( + attempt: Final = (usage, float(response_cost) if isinstance(response_cost, (int, float)) else 0.0) + self.model_call_details["current_attempt_api_call_start_time"] = None + self.model_call_details["failed_attempts_usage"] = ( + *self.model_call_details.get("failed_attempts_usage", ()), attempt, - {"id": identity, "usage": usage.model_dump(), "status": "failed"}, - self.start_time, - datetime.datetime.now(datetime.timezone.utc), - False, ) - if isinstance(captured, CapturedUsage): - self.model_call_details["_accounting_prior_captures"] = ( - *self.model_call_details.get("_accounting_prior_captures", ()), - captured, - ) + if not owed_on_success or billed_by_continuation: + return + self._failed_attempts_owed_on_success = (*self._failed_attempts_owed_on_success, attempt) + + def mark_stash_billed_by_continuation(self) -> None: + self._stash_billed_by_continuation = True def record_continued_partial(self, usage: Usage, response_cost: float, response_id: str) -> None: """Bill what a cut stream already consumed on this continuation's success log, under the id the caller saw.""" @@ -2788,20 +2763,17 @@ class Logging(LiteLLMLoggingBaseClass): self.model_call_details["continued_partial_cost"] = response_cost self.model_call_details["continued_response_id"] = response_id - def _add_continued_partial_spend(self, response: object) -> None: + def _add_continued_partial_spend(self, response: object) -> Usage | None: partial_usage: Final = self.model_call_details.get("continued_partial_usage") partial_cost: Final = self.model_call_details.get("continued_partial_cost") own_usage: Final = getattr(response, "usage", None) own_cost: Final = self.model_call_details.get("response_cost") if not (isinstance(partial_usage, Usage) and isinstance(partial_cost, float) and isinstance(own_usage, Usage)): - return - from litellm.cost_calculator import BaseTokenUsageProcessor - - self.model_call_details["combined_usage_object"] = BaseTokenUsageProcessor.combine_usage_objects( - usage_objects=[own_usage, partial_usage] - ) + return own_usage if isinstance(own_usage, Usage) else None + combined_usage: Final = BaseTokenUsageProcessor.combine_usage_objects(usage_objects=[own_usage, partial_usage]) + self.model_call_details["combined_usage_object"] = combined_usage if not isinstance(own_cost, (int, float)): - return + return combined_usage self.model_call_details["response_cost"] = own_cost + partial_cost if self.cost_breakdown is not None: self.cost_breakdown = self.cost_breakdown | CostBreakdown( @@ -2811,6 +2783,25 @@ class Logging(LiteLLMLoggingBaseClass): "mid_stream_partial_cost": partial_cost, }, ) + return combined_usage + + def _add_failed_attempts_spend(self, own_usage: Usage | None) -> None: + own_cost: Final = self.model_call_details.get("response_cost") + if own_usage is None or not isinstance(own_cost, (int, float)): + return + failed_attempts: Final = self._failed_attempts_owed_on_success + if not failed_attempts: + return + failed_attempts_cost: Final = sum(cost for _, cost in failed_attempts) + self.model_call_details.pop("failed_attempts_usage", None) + self.failed_attempts_billed_on_success = failed_attempts + self.model_call_details["failed_attempts_billed_on_success"] = failed_attempts + self.model_call_details["combined_usage_object"] = BaseTokenUsageProcessor.combine_usage_objects( + usage_objects=[own_usage, *(usage for usage, _ in failed_attempts)] + ) + self.model_call_details["response_cost"] = own_cost + failed_attempts_cost + if self.cost_breakdown is not None: + self.cost_breakdown = _with_failed_attempts_cost(self.cost_breakdown, own_cost, failed_attempts_cost) def claim_stream_failure_report(self) -> bool: if self._stream_failure_claimed: @@ -2818,6 +2809,24 @@ class Logging(LiteLLMLoggingBaseClass): self._stream_failure_claimed = True return True + def served_round(self, response: object) -> ServedRound | None: + usage: Final = get_usage_object(completion_response=response) + if usage is None: + return None + price: Final = self._price_without_recording(response, cache_hit=None, ignore_stamped_cost=False) + return usage, price.cost or 0.0 + + def record_served_rounds_for_failure(self, served_rounds: tuple[ServedRound, ...]) -> None: + if not served_rounds: + return + self._stash_owed_on_success = True + self.record_partial_usage_for_failure( + served_rounds[0][0] + if len(served_rounds) == 1 + else BaseTokenUsageProcessor.combine_usage_objects(usage_objects=[usage for usage, _ in served_rounds]), + sum(cost for _, cost in served_rounds), + ) + def record_assembled_response_for_failure(self, assembled: ModelResponse) -> None: """Bill a fully streamed response on the failure log when a post-call hook rejects it.""" usage: Final = getattr(assembled, "usage", None) @@ -2949,45 +2958,6 @@ class Logging(LiteLLMLoggingBaseClass): return self._handle_a2a_response_logging(result=result) return result - def usage_capture_response(self, result: object) -> object: - if self.stream and not self._is_assembled_stream_success(result): - return None - copied: Final = result.model_copy(deep=True) if isinstance(result, BaseModel) else result - normalized: Final = self.normalize_logging_result(self.normalize_endpoint_logging_result(copied)) - if self.model_call_details.get("call_type") == CallTypes.arealtime.value and isinstance(result, list): - frames: Final = TypeAdapter(tuple[dict[str, object], ...]).validate_python(result) - measured: Final = any( - isinstance(_LITELLM_PARAMS.validate_python(frame.get("response") or {}).get("usage"), Mapping) - for frame in frames - if frame.get("type") == "response.done" - ) - if not measured: - metered: Final = self.model_call_details.get(REALTIME_METERED_USAGE_KEY) - return { - "id": self.litellm_call_id, - "usage": {"metered_usage": TypeAdapter(object).dump_python(metered, mode="json")} - if metered is not None - else None, - } - assembled: Final = self._get_assembled_streaming_response( - normalized, self.start_time, self.start_time, True, [] - ) - return normalized if assembled is None else assembled - - def usage_capture_pricing(self, result: object) -> Mapping[str, JsonValue]: - from litellm.utils import count_characters - - return TypeAdapter(dict[str, JsonValue]).validate_python( - { - "custom_pricing": self.custom_pricing_for(result), - "custom_cost_per_token": self.custom_cost_per_token, - "custom_cost_per_second": self.custom_cost_per_second, - "prompt_characters": count_characters(self._prompt_for_cost_calculation()) - if self.model_call_details.get("call_type") in (CallTypes.speech.value, CallTypes.aspeech.value) - else None, - } - ) - def normalize_logging_result(self, result: object) -> object: """ Some endpoints return a different type of result than what is expected by the logging system. @@ -3122,9 +3092,11 @@ class Logging(LiteLLMLoggingBaseClass): self.model_call_details["response_cost"] = self.finalized_cost.amount elif self.model_call_details.get("cache_hit") is True: self.model_call_details["response_cost"] = 0.0 + self._add_failed_attempts_spend(get_usage_object(completion_response=logging_result)) elif "response_cost" in hidden_params: self.model_call_details["response_cost"] = hidden_params["response_cost"] self._record_zero_cost_diagnostic(logging_result, hidden_params["response_cost"]) + self._add_failed_attempts_spend(get_usage_object(completion_response=logging_result)) elif (existing_cost := self.model_call_details.get("response_cost")) is not None and ( existing_cost != 0 or self.call_type == CallTypes.pass_through.value # pyright: ignore[reportUnknownMemberType] # Logging.call_type is untyped ): @@ -3134,6 +3106,7 @@ class Logging(LiteLLMLoggingBaseClass): pass else: self.model_call_details["response_cost"] = self.response_cost_calculator(result=logging_result) + self._add_failed_attempts_spend(get_usage_object(completion_response=logging_result)) if not build_logging_payload: return None @@ -3228,14 +3201,61 @@ class Logging(LiteLLMLoggingBaseClass): return response return response.model_copy(update={"model": model}) - def _with_continued_response_id( + def _as_served_chat_response(self, response: _LoggedResponse) -> _LoggedResponse | ModelResponse: + request: Final = self.bridged_chat_request + if request is None or not isinstance(response, ResponsesAPIResponse): + return response + return self._bridged_chat_response(response, request) + + def _as_served_response( + self, response: _LoggedResponse + ) -> _LoggedResponse | ModelResponse | TextCompletionResponse: + request: Final = self.bridged_chat_request + if request is None or not isinstance(response, ResponsesAPIResponse): + return response + served: Final = self._bridged_chat_response(response, request) + if self.call_type not in (CallTypes.text_completion.value, CallTypes.atext_completion.value): # pyright: ignore[reportUnknownMemberType] # Logging.call_type is untyped + return served + return self._as_text_completion_priced_as_chat(served) + + def _as_text_completion_priced_as_chat(self, served: ModelResponse) -> TextCompletionResponse: + text_completion: Final = LiteLLMResponseObjectHandler.convert_chat_to_text_completion( + served, TextCompletionResponse() + ) + set_hidden_params(text_completion, dict(get_hidden_params(served) or {})) + return text_completion + + def _bridged_chat_response(self, response: ResponsesAPIResponse, request: BridgedChatRequest) -> ModelResponse: + translated: Final = self._translate_responses_api_response_to_model_response(response, request) + served: Final = translated.model_copy( + update={ + "id": ResponsesAPIRequestUtils.decode_previous_response_id_to_original_previous_response_id(response.id) + } + ) + set_hidden_params(served, {**(get_hidden_params(translated) or {}), **(get_hidden_params(response) or {})}) + return served + + def _with_response_id( + self, + response: ModelResponse | TextCompletionResponse | ResponsesAPIResponse | InteractionsAPIResponse, + response_id: str | None, + ) -> ModelResponse | TextCompletionResponse | ResponsesAPIResponse | InteractionsAPIResponse: + if response_id is None or response.id == response_id: + return response + return response.model_copy(update={"id": response_id}) + + def _client_facing_streaming_response( self, response: ModelResponse | TextCompletionResponse | ResponsesAPIResponse | InteractionsAPIResponse, ) -> ModelResponse | TextCompletionResponse | ResponsesAPIResponse | InteractionsAPIResponse: - response_id: Final = self.model_call_details.get("continued_response_id") - if not isinstance(response_id, str) or getattr(response, "id", None) == response_id: - return response - return response.model_copy(update={"id": response_id}) + continued_response_id: Final = self.model_call_details.get("continued_response_id") + return self._with_response_id( + self._with_response_id( + self._with_client_facing_stream_model(response), + continued_response_id if isinstance(continued_response_id, str) else None, + ), + self.client_facing_response_id, + ) def _success_handler_helper_fn( self, @@ -3292,6 +3312,13 @@ class Logging(LiteLLMLoggingBaseClass): ) result = self.normalize_endpoint_logging_result(result) + if self.stream is not True: + result = self._as_served_response(result) # rebind-ok: bridged chat calls log the served response + if isinstance(result, VideoObject): + self.model_call_details[POLLED_VIDEO_STATUS_KWARG] = result.status + if isinstance(result, LiteLLMBatch): + self.model_call_details[POLLED_BATCH_ID_KWARG] = result.id + self.model_call_details[POLLED_BATCH_COST_IS_FINAL_KWARG] = batch_cost_is_final(result) logging_result: Final = self.normalize_logging_result(result=result) if cache_hit is None and _served_from_cache_at_no_charge(logging_result): @@ -3606,6 +3633,7 @@ class Logging(LiteLLMLoggingBaseClass): verbose_logger.debug("Logging Details LiteLLM-Success Call: Cache_hit=%s", cache_hit) if not self.should_run_logging(event_type="sync_success"): # prevent double logging return + provider_transcription: Final = result if isinstance(result, TranscriptionResponse) else None start_time, end_time, result, request_logging_payload = self.prepare_success_logging( start_time=start_time, end_time=end_time, @@ -3620,7 +3648,12 @@ class Logging(LiteLLMLoggingBaseClass): try: ## BUILD COMPLETE STREAMED RESPONSE complete_streaming_response: ( - ModelResponse | TextCompletionResponse | ResponsesAPIResponse | InteractionsAPIResponse | None + ModelResponse + | TextCompletionResponse + | ResponsesAPIResponse + | InteractionsAPIResponse + | TranscriptionResponse + | None ) = None if "complete_streaming_response" in self.model_call_details and not for_async_request: return # break out of this. @@ -3636,19 +3669,20 @@ class Logging(LiteLLMLoggingBaseClass): self.model_call_details["complete_streaming_response"] = complete_streaming_response self._surface_response_headers_from_result(complete_streaming_response) self.model_call_details["response_cost"] = self.response_cost_calculator( - result=complete_streaming_response + result=complete_streaming_response if provider_transcription is None else provider_transcription ) - self._add_continued_partial_spend(complete_streaming_response) + self._add_failed_attempts_spend(self._add_continued_partial_spend(complete_streaming_response)) self._merge_hidden_params_from_response_into_metadata(complete_streaming_response) - logged_streaming_response: Final = self._with_continued_response_id( - self._with_client_facing_stream_model(complete_streaming_response) + logged_streaming_response: Final = self._client_facing_streaming_response( + self._as_served_chat_response(complete_streaming_response) ) self.model_call_details["complete_streaming_response"] = logged_streaming_response - self.capture_usage_before_logging(logged_streaming_response, start_time, end_time) ## STANDARDIZED LOGGING PAYLOAD if not for_async_request: self.model_call_details["standard_logging_object"] = self._build_standard_logging_payload( - logged_streaming_response, start_time, end_time + logged_streaming_response if provider_transcription is None else provider_transcription, + start_time, + end_time, ) standard_logging_payload: Final[StandardLoggingPayload | None] = self.model_call_details.get( "standard_logging_object" @@ -4168,13 +4202,12 @@ class Logging(LiteLLMLoggingBaseClass): cost_for_built_in_tools_cost_usd_dollar=0.0, ) - self.capture_usage_before_logging(result, start_time, end_time) - self.truncated_messages_for_logging = await truncate_base64_in_messages_async( StandardLoggingPayloadSetup.append_system_prompt_messages( kwargs=self.model_call_details, messages=self.model_call_details.get("messages") ) ) + provider_transcription: Final = result if isinstance(result, TranscriptionResponse) else None start_time, end_time, result = self._success_handler_helper_fn( start_time=start_time, end_time=end_time, @@ -4194,9 +4227,7 @@ class Logging(LiteLLMLoggingBaseClass): ## BUILD COMPLETE STREAMED RESPONSE if "async_complete_streaming_response" in self.model_call_details: return # break out of this. - complete_streaming_response: Final[ - ModelResponse | TextCompletionResponse | ResponsesAPIResponse | InteractionsAPIResponse | None - ] = self._get_assembled_streaming_response( + complete_streaming_response: Final = self._get_assembled_streaming_response( result=result, start_time=start_time, end_time=end_time, @@ -4218,7 +4249,7 @@ class Logging(LiteLLMLoggingBaseClass): get_base_model_from_metadata(model_call_details=self.model_call_details) # base_model defaults to None if not set on model_info self.model_call_details["response_cost"] = self.response_cost_calculator( - result=complete_streaming_response + result=complete_streaming_response if provider_transcription is None else provider_transcription ) verbose_logger.debug("Model=%s; cost=%s", self.model, self.model_call_details["response_cost"]) @@ -4233,21 +4264,23 @@ class Logging(LiteLLMLoggingBaseClass): self.model, ) self.model_call_details["response_cost"] = None - self._add_continued_partial_spend(complete_streaming_response) + self._add_failed_attempts_spend(self._add_continued_partial_spend(complete_streaming_response)) self._merge_hidden_params_from_response_into_metadata(complete_streaming_response) await self._prepare_baseline_cache_estimate(complete_streaming_response) - logged_streaming_response: Final = self._with_continued_response_id( - self._with_client_facing_stream_model(complete_streaming_response) + logged_streaming_response: Final = self._client_facing_streaming_response( + self._as_served_chat_response(complete_streaming_response) ) self.model_call_details["async_complete_streaming_response"] = logged_streaming_response ## STANDARDIZED LOGGING PAYLOAD try: self.model_call_details["standard_logging_object"] = self._build_standard_logging_payload( - logged_streaming_response, start_time, end_time + logged_streaming_response if provider_transcription is None else provider_transcription, + start_time, + end_time, ) except Exception: # noqa: BLE001 # payload build must never block later callbacks (slot release) verbose_logger.exception( @@ -5117,10 +5150,17 @@ class Logging(LiteLLMLoggingBaseClass): end_time: datetime.datetime, is_async: bool, streaming_chunks: list[object], - ) -> ModelResponse | TextCompletionResponse | ResponsesAPIResponse | InteractionsAPIResponse | None: + ) -> ( + ModelResponse + | TextCompletionResponse + | ResponsesAPIResponse + | InteractionsAPIResponse + | TranscriptionResponse + | None + ): if self.stream is not True: return None - if isinstance(result, ModelResponse) or isinstance(result, TextCompletionResponse): + if isinstance(result, (ModelResponse, TextCompletionResponse, TranscriptionResponse)): return result elif isinstance( result, @@ -5191,6 +5231,13 @@ class Logging(LiteLLMLoggingBaseClass): row is built from this response rather than re-parsed from the served body.""" self.bridged_model_response = response + def record_bridged_chat_request( + self, optional_params: Mapping[str, object], litellm_params: Mapping[str, object] + ) -> None: + self.bridged_chat_request = BridgedChatRequest( + MappingProxyType(dict(optional_params)), MappingProxyType(dict(litellm_params)) + ) + def record_bridged_responses_api_response(self, response: ResponsesAPIResponse) -> None: self.record_bridged_model_response(self._translate_responses_api_response_to_model_response(response)) @@ -5262,6 +5309,9 @@ class Logging(LiteLLMLoggingBaseClass): ): result = result.response if isinstance(result, ResponsesAPIResponse): + bridged_request: Final = self.bridged_chat_request + if bridged_request is not None: + return self._bridged_chat_response(result, bridged_request) return self._translate_responses_api_response_to_model_response(result) raw_body: Final[object] = result @@ -5313,7 +5363,9 @@ class Logging(LiteLLMLoggingBaseClass): set_response_cost_in_hidden_params(result, reported_cost) return result - def _translate_responses_api_response_to_model_response(self, result: ResponsesAPIResponse) -> ModelResponse: + def _translate_responses_api_response_to_model_response( + self, result: ResponsesAPIResponse, request: BridgedChatRequest | None = None + ) -> ModelResponse: """ Convert a Responses API response into a ModelResponse for spend_logs. @@ -5336,8 +5388,8 @@ class Logging(LiteLLMLoggingBaseClass): logging_obj=self, request_data={}, messages=[], - optional_params={}, - litellm_params={}, + optional_params={} if request is None else dict(request.optional_params), + litellm_params={} if request is None else dict(request.litellm_params), encoding=litellm.encoding, ) translated.id = served_id or translated.id @@ -6291,7 +6343,7 @@ def _init_custom_logger_compatible_class( logging_integration: str, internal_usage_cache: DualCache | None, llm_router: object, - custom_logger_init_args: dict[str, object] | None = {}, + custom_logger_init_args: dict[str, object] | None = None, raise_import_errors: bool = False, ) -> CustomLogger | None: """ @@ -7091,6 +7143,7 @@ class StandardLoggingPayloadSetup: init_response_obj: object, api_base: str | None = None, router_model_id: str | None = None, + custom_model_info: ModelInfo | None = None, ) -> StandardLoggingModelInformation: model_cost_name: Final = select_model_name_for_cost_calc( model=base_model if custom_pricing else None, @@ -7109,6 +7162,8 @@ class StandardLoggingPayloadSetup: if router_model_id is not None else model_cost_name ) + if model_cost_name is not None and custom_model_info is not None: + return StandardLoggingModelInformation(model_map_key=model_cost_name, model_map_value=custom_model_info) if model_cost_name is None: model_cost_information = StandardLoggingModelInformation(model_map_key="", model_map_value=None) else: @@ -7705,6 +7760,20 @@ def _cache_hit_cost_breakdown(served: CostBreakdown | None) -> CostBreakdown: ) +def _with_failed_attempts_cost(breakdown: CostBreakdown, own_cost: float, failed_attempts_cost: float) -> CostBreakdown: + return breakdown | CostBreakdown( + total_cost=own_cost + failed_attempts_cost, + additional_costs={**breakdown.get("additional_costs", {}), "failed_attempts_cost": failed_attempts_cost}, + ) + + +def _cached_cost_breakdown(served: CostBreakdown | None, failed_attempts: tuple[ServedRound, ...]) -> CostBreakdown: + cached: Final = _cache_hit_cost_breakdown(served) + if not failed_attempts: + return cached + return _with_failed_attempts_cost(cached, 0.0, sum(cost for _, cost in failed_attempts)) + + def _finalized_cost_of(logging_obj: object) -> FinalizedCost | None: """Duck-typed logging objects (and test doubles) carry no finalized cost.""" finalized: Final = getattr(logging_obj, "finalized_cost", None) @@ -7845,6 +7914,7 @@ def get_standard_logging_object_payload( init_response_obj=init_response_obj, api_base=litellm_params.get("api_base"), router_model_id=logging_obj.get_router_model_id(), + custom_model_info=logging_obj.custom_model_info if custom_pricing else None, ) error_information, error_str = StandardLoggingPayloadSetup.get_error_information_for_logging_payload( @@ -7898,7 +7968,7 @@ def get_standard_logging_object_payload( if finalized_cost is not None else cost_breakdown_with_guardrail( ( - _cache_hit_cost_breakdown(uncached_price.cost_breakdown) + _cached_cost_breakdown(uncached_price.cost_breakdown, logging_obj.failed_attempts_billed_on_success) if uncached_price is not None else logging_obj.cost_breakdown ), diff --git a/litellm/litellm_core_utils/llm_cost_calc/finalization.py b/litellm/litellm_core_utils/llm_cost_calc/finalization.py index a13134ada4a..756c53ea882 100644 --- a/litellm/litellm_core_utils/llm_cost_calc/finalization.py +++ b/litellm/litellm_core_utils/llm_cost_calc/finalization.py @@ -17,6 +17,7 @@ class PreparedCost: amount: float payload: StandardLoggingPayload usage: Usage + price_known: bool = True @dataclass(frozen=True, slots=True) diff --git a/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py b/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py index 54213f40ac0..e3aecda1deb 100644 --- a/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py +++ b/litellm/litellm_core_utils/llm_cost_calc/tool_call_cost_tracking.py @@ -224,7 +224,20 @@ class StandardBuiltInToolCostTracking: web_search_options=standard_built_in_tools_params.get("web_search_options", None), model_info=model_info, ) - return per_call_cost * StandardBuiltInToolCostTracking._count_web_search_calls(response_object) + return per_call_cost * StandardBuiltInToolCostTracking._billable_web_search_calls( + resolved_usage, response_object + ) + + @staticmethod + def _billable_web_search_calls(usage: Usage | None, response_object: object) -> int: + """ + Providers without their own calculator but whose usage carries server_tool_use.web_search_requests + (OpenAI-compatible providers that report a per-tool count) are billed that many calls on the per-call path. + """ + reported: Final = None if usage is None else get_web_search_requests_from_usage(usage) + if isinstance(reported, int) and not isinstance(reported, bool) and reported > 0: + return reported + return StandardBuiltInToolCostTracking._count_web_search_calls(response_object) @staticmethod def _count_web_search_calls(response_object: object) -> int: diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py index 50c26f4d4ca..9ac4f9d5ee8 100644 --- a/litellm/litellm_core_utils/llm_cost_calc/utils.py +++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py @@ -1040,6 +1040,11 @@ def calculate_cache_writing_cost( class PromptTokensDetailsResult(TypedDict): cache_hit_tokens: int cache_hit_audio_tokens: ReadOnly[int] + + cached_text_tokens: ReadOnly[int] + cached_audio_tokens: ReadOnly[int] + cached_image_tokens: ReadOnly[int] + has_cached_tokens_details: ReadOnly[bool] cache_creation_tokens: int cache_creation_token_details: CacheCreationTokenDetails | None text_tokens: int @@ -1126,6 +1131,10 @@ def parse_prompt_tokens_details(usage: Usage) -> PromptTokensDetailsResult: return PromptTokensDetailsResult( cache_hit_tokens=cache_hit_tokens, cache_hit_audio_tokens=cached_audio_tokens, + cached_text_tokens=cached_text_tokens, + cached_audio_tokens=cached_audio_tokens, + cached_image_tokens=cached_image_tokens, + has_cached_tokens_details=cached_tokens_details is not None, cache_creation_tokens=cache_creation_tokens, cache_creation_token_details=cache_creation_token_details, text_tokens=text_tokens, @@ -1194,21 +1203,55 @@ def parse_completion_tokens_details(usage: Usage) -> CompletionTokensDetailsResu ) +def get_modality_token_cost_key( + model_info: ModelInfo, + cost_key: str, + prompt_tokens: int, + *, + threshold_is_inclusive: bool = False, +) -> str: + suffix: Final = next((suffix for suffix in _NON_STANDARD_THRESHOLD_SUFFIXES if cost_key.endswith(suffix)), "") + base_key: Final = cost_key.removesuffix(suffix) + threshold_key: Final = max( + ( + key + for key in model_info + if key.startswith(f"{base_key}_above_") + and key.endswith(("_tokens", f"_tokens{suffix}")) + and model_info.get(key) is not None + and _prompt_exceeds_threshold(prompt_tokens, _parse_above_token_threshold(key), threshold_is_inclusive) + ), + key=_parse_above_token_threshold, + default=None, + ) + if threshold_key is None: + return cost_key + return f"{threshold_key.removesuffix(suffix)}{suffix}" + + def _modality_token_cost( model_info: ModelInfo, modality_cost_key: str, tokens: int, prompt_base_cost: float, service_tier: str | None, + *, + prompt_tokens: int = 0, + threshold_is_inclusive: bool = False, ) -> float: """ Audio, image and video prompt tokens bill at their modality rate when the model has one. Without one they are ordinary prompt tokens, so they bill at `prompt_base_cost`, which `_get_token_base_cost` has already resolved for the service tier and long-context tier. """ - tiered_key: Final = get_service_tier_cost_key(modality_cost_key, service_tier) - cost_key: Final = tiered_key if model_info.get(tiered_key) is not None else modality_cost_key - if model_info.get(cost_key) is None: + cost_key: Final = get_modality_token_cost_key( + model_info, + get_service_tier_cost_key(modality_cost_key, service_tier), + prompt_tokens, + threshold_is_inclusive=threshold_is_inclusive, + ) + standard_key: Final = cost_key.removesuffix(get_service_tier_cost_key("", service_tier)) + if model_info.get(cost_key) is None and model_info.get(standard_key) is None: return float(tokens) * prompt_base_cost return calculate_cost_component(model_info, cost_key, tokens) @@ -1221,6 +1264,9 @@ def _calculate_input_cost( cache_creation_cost: float, cache_creation_cost_by_ttl: Mapping[str, float], service_tier: str | None = None, + *, + prompt_tokens: int = 0, + threshold_is_inclusive: bool = False, ) -> float: """ Calculates the input cost for a given model, prompt tokens, and completion tokens. @@ -1234,15 +1280,11 @@ def _calculate_input_cost( prompt_cost = 0.0 if bills_characters else float(prompt_tokens_details["text_tokens"]) * prompt_base_cost ### CACHE READ COST - Now uses tiered pricing - cache_hit_audio_tokens: Final = prompt_tokens_details["cache_hit_audio_tokens"] - audio_cache_read_rate: Final = get_cost_per_unit( - model_info, - get_service_tier_cost_key("cache_read_input_audio_token_cost", service_tier), - None, - ) - prompt_cost += float(prompt_tokens_details["cache_hit_tokens"] - cache_hit_audio_tokens) * cache_read_cost - prompt_cost += float(cache_hit_audio_tokens) * ( - audio_cache_read_rate if audio_cache_read_rate is not None else cache_read_cost + prompt_cost += _calculate_cache_read_cost( + prompt_tokens_details=prompt_tokens_details, + model_info=model_info, + cache_read_cost=cache_read_cost, + service_tier=service_tier, ) ### AUDIO COST @@ -1255,6 +1297,8 @@ def _calculate_input_cost( prompt_tokens_details["audio_tokens"], prompt_base_cost, service_tier, + prompt_tokens=prompt_tokens, + threshold_is_inclusive=threshold_is_inclusive, ) ### IMAGE TOKEN COST @@ -1331,6 +1375,38 @@ def _calculate_input_cost( return prompt_cost +def _calculate_cache_read_cost( + prompt_tokens_details: PromptTokensDetailsResult, + model_info: ModelInfo, + cache_read_cost: float, + service_tier: str | None, +) -> float: + cached_text_tokens: Final = prompt_tokens_details["cached_text_tokens"] + cached_audio_tokens: Final = prompt_tokens_details["cached_audio_tokens"] + cached_image_tokens: Final = prompt_tokens_details["cached_image_tokens"] + classified_cached_tokens: Final = cached_text_tokens + cached_audio_tokens + cached_image_tokens + unclassified_cached_tokens: Final = max(prompt_tokens_details["cache_hit_tokens"] - classified_cached_tokens, 0) + total_cost = ( # rebind-ok: cached modality components accumulate into one cache-read cost + float(cached_text_tokens + unclassified_cached_tokens) * cache_read_cost + ) + + if cached_audio_tokens: + cached_audio_cost_key: Final = get_service_tier_cost_key("cache_read_input_audio_token_cost", service_tier) + cached_audio_cost: Final = get_cost_per_unit(model_info, cached_audio_cost_key, cache_read_cost) + total_cost += ( # rebind-ok: cached audio contributes to cache-read cost + float(cached_audio_tokens) * float(cached_audio_cost or 0.0) + ) + + if cached_image_tokens: + cached_image_cost_key: Final = get_service_tier_cost_key("cache_read_input_image_token_cost", service_tier) + cached_image_cost: Final = get_cost_per_unit(model_info, cached_image_cost_key, cache_read_cost) + total_cost += ( # rebind-ok: cached images contribute to cache-read cost + float(cached_image_tokens) * float(cached_image_cost or 0.0) + ) + + return total_cost + + def get_regional_uplift_multiplier(model_info: ModelInfo, data_residency: str | None) -> float: """ Resolve the per-model regional-processing uplift multiplier for a given @@ -1365,6 +1441,29 @@ def get_regional_uplift_multiplier(model_info: ModelInfo, data_residency: str | _get_regional_uplift_multiplier = get_regional_uplift_multiplier +def get_fedramp_uplift_multiplier(model_info: ModelInfo, data_residency: str | None) -> float: + """ + Resolve the per-model uplift multiplier for the OpenAI FedRAMP endpoint. + + OpenAI applies a flat percentage uplift (e.g. +10%) on all token costs for + requests served from gov.api.openai.com. The multiplier is stored on the + model entry as ``fedramp_uplift_multiplier`` (e.g. 1.10). + + Returns 1.0 (no uplift) unless ``data_residency`` is ``"fedramp"`` and the + model has a multiplier configured. + """ + if data_residency is None or data_residency.lower() != DataResidency.FEDRAMP.value: + return 1.0 + multiplier: Final = model_info.get("fedramp_uplift_multiplier") + if multiplier is None: + return 1.0 + try: + return float(multiplier) + except (TypeError, ValueError): + verbose_logger.exception("Invalid fedramp_uplift_multiplier for model; defaulting to 1.0") + return 1.0 + + def get_vertex_regional_endpoint_uplift(model_info: ModelInfo, vertex_location: str | None) -> float: """ Resolve the per-model uplift multiplier for Vertex AI non-global (regional and @@ -1474,8 +1573,8 @@ def generic_cost_per_token( Input: - model: str, the model name without provider prefix - usage: LiteLLM Usage block, containing anthropic caching information - - data_residency: optional OpenAI data-residency region (e.g. "eu", "us"), - used to apply the per-model regional-processing uplift multiplier. + - data_residency: optional OpenAI data-residency region (e.g. "eu", "us") or + "fedramp", used to apply the per-model regional-processing or FedRAMP uplift multiplier. - vertex_location: optional Vertex AI location the request was served from (e.g. "us-east5", "global"), used to apply the per-model regional-endpoint uplift multiplier when non-global. @@ -1502,6 +1601,10 @@ def generic_cost_per_token( prompt_tokens_details = PromptTokensDetailsResult( cache_hit_tokens=0, cache_hit_audio_tokens=0, + cached_text_tokens=0, + cached_audio_tokens=0, + cached_image_tokens=0, + has_cached_tokens_details=False, cache_creation_tokens=0, cache_creation_token_details=None, text_tokens=usage.prompt_tokens, @@ -1577,6 +1680,8 @@ def generic_cost_per_token( cache_creation_cost=base_costs.cache_creation_rate, cache_creation_cost_by_ttl=base_costs.cache_creation_rates_by_ttl, service_tier=service_tier, + prompt_tokens=usage.prompt_tokens, + threshold_is_inclusive=_uses_inclusive_token_thresholds(custom_llm_provider), ) ## CALCULATE OUTPUT COST @@ -1634,11 +1739,9 @@ def generic_cost_per_token( ## IMAGE COST if not is_text_tokens_total and image_tokens and image_tokens > 0: - _output_cost_per_image_token = get_cost_per_unit(resolved_model_info, "output_cost_per_image_token", None) - _output_cost_per_image_token = ( - _output_cost_per_image_token if _output_cost_per_image_token is not None else completion_base_cost - ) - completion_cost += float(image_tokens) * _output_cost_per_image_token + image_cost_key: Final = get_service_tier_cost_key("output_cost_per_image_token", service_tier) + image_rate: Final = get_cost_per_unit(resolved_model_info, image_cost_key, None) + completion_cost += float(image_tokens) * (completion_base_cost if image_rate is None else image_rate) ## VIDEO COST if not is_text_tokens_total and video_tokens and video_tokens > 0: @@ -1648,10 +1751,9 @@ def generic_cost_per_token( ) completion_cost += float(video_tokens) * _output_cost_per_video_token - ## REGIONAL DATA-RESIDENCY UPLIFT - # Applied as a flat multiplier across all token costs for the request - # when the upstream is a regionalized OpenAI host (eu./us.api.openai.com). - uplift: Final = get_regional_uplift_multiplier(resolved_model_info, data_residency) + uplift: Final = get_regional_uplift_multiplier(resolved_model_info, data_residency) * get_fedramp_uplift_multiplier( + resolved_model_info, data_residency + ) if uplift != 1.0: prompt_cost *= uplift completion_cost *= uplift @@ -1680,6 +1782,7 @@ class BilledTokenRates: cache_creation_input_token_cost: float cache_creation_input_token_cost_by_ttl: Mapping[str, float] output_cost_per_reasoning_token: float + cache_read_input_image_token_cost: float | None = None def scaled(self, multiplier: float) -> "BilledTokenRates": if multiplier == 1.0: @@ -1694,6 +1797,11 @@ class BilledTokenRates: {ttl: rate * multiplier for ttl, rate in self.cache_creation_input_token_cost_by_ttl.items()} ), output_cost_per_reasoning_token=self.output_cost_per_reasoning_token * multiplier, + cache_read_input_image_token_cost=( + self.cache_read_input_image_token_cost * multiplier + if self.cache_read_input_image_token_cost is not None + else None + ), ) @@ -1788,6 +1896,7 @@ def _cost_map_billed_rates( ) multiplier: Final = ( get_regional_uplift_multiplier(model_info, data_residency) + * get_fedramp_uplift_multiplier(model_info, data_residency) * get_vertex_regional_endpoint_uplift(model_info, vertex_location) * get_provider_specific_geo_multiplier(model_info=model_info, usage=usage) * get_provider_specific_speed_multiplier(model_info=model_info, usage=usage) @@ -1802,6 +1911,11 @@ def _cost_map_billed_rates( cache_creation_input_token_cost=base_costs.cache_creation_rate, cache_creation_input_token_cost_by_ttl=base_costs.cache_creation_rates_by_ttl, output_cost_per_reasoning_token=reasoning_rate, + cache_read_input_image_token_cost=_get_cost_per_unit( + model_info, + _get_service_tier_cost_key("cache_read_input_image_token_cost", service_tier), + None, + ), ).scaled(multiplier) @@ -1882,6 +1996,12 @@ def get_token_type_cost_breakdown( cache_read_tokens, cached_audio_tokens, cache_creation_tokens, cache_creation_token_details = _cache_token_counts( usage ) + cached_image_tokens: Final = parse_prompt_tokens_details(usage)["cached_image_tokens"] + image_cache_read_rate: Final = ( + rates.cache_read_input_image_token_cost + if rates.cache_read_input_image_token_cost is not None + else rates.cache_read_input_token_cost + ) cache_creation_cost: Final = ( float(cache_creation_tokens) * rates.cache_creation_input_token_cost if custom_cost_per_token is not None @@ -1895,8 +2015,9 @@ def get_token_type_cost_breakdown( return TokenTypeCostBreakdown( reasoning_cost=float(_reasoning_token_count(usage)) * rates.output_cost_per_reasoning_token, cache_read_cost=( - float(cache_read_tokens - cached_audio_tokens) * rates.cache_read_input_token_cost + float(cache_read_tokens - cached_audio_tokens - cached_image_tokens) * rates.cache_read_input_token_cost + float(cached_audio_tokens) * rates.cache_read_input_audio_token_cost + + float(cached_image_tokens) * image_cache_read_rate ), cache_creation_cost=cache_creation_cost, rates=rates, @@ -1961,8 +2082,10 @@ def calculate_prompt_caching_savings( {ttl: rate - prompt_base_cost for ttl, rate in base_costs.cache_creation_rates_by_ttl.items()} ), ) - uplift: Final = get_regional_uplift_multiplier(model_info, data_residency) * get_vertex_regional_endpoint_uplift( - model_info, vertex_location + uplift: Final = ( + get_regional_uplift_multiplier(model_info, data_residency) + * get_fedramp_uplift_multiplier(model_info, data_residency) + * get_vertex_regional_endpoint_uplift(model_info, vertex_location) ) return (read_discount - write_premium) * uplift diff --git a/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py b/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py index 58fe5b4297f..08ab2d1a2e5 100644 --- a/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py +++ b/litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py @@ -3,7 +3,8 @@ import json import re import time import traceback -from collections.abc import Generator, Iterator, Mapping, Sequence +from collections.abc import Generator, Iterable, Iterator, Mapping, Sequence +from types import MappingProxyType from typing import Final, Literal, cast from pydantic import ConfigDict, TypeAdapter, ValidationError, with_config @@ -11,7 +12,12 @@ from typing_extensions import ReadOnly, TypedDict import litellm from litellm._logging import verbose_logger -from litellm.constants import RESPONSE_FORMAT_TOOL_NAME +from litellm.constants import ( + RESPONSE_FORMAT_TOOL_NAME, + STREAM_CHUNK_CHOICE_FIELDS, + STREAM_FINISH_CHOICE_FIELDS, + VLLM_CHOICE_FIELDS, +) from litellm.litellm_core_utils.hidden_params import get_hidden_params from litellm.litellm_core_utils.prompt_templates.common_utils import ( extract_reasoning_content, @@ -170,6 +176,28 @@ def _split_assembled_content_for_replay(content: str | None) -> list[str]: return _REPLAY_CONTENT_SLICE_RE.findall(content) +def _drop_choice_fields(choice: StreamingChoices, fields: Iterable[str]) -> None: + for field in fields: + if hasattr(choice, field): + delattr(choice, field) + + +def _vllm_choice_fields(choice: Mapping[str, object]) -> Mapping[str, object]: + cached_fields: Final = _choice_provider_specific_fields(choice) + return MappingProxyType( + { + field: choice[field] if field in choice else cached_fields[field] + for field in VLLM_CHOICE_FIELDS + if field in choice or field in cached_fields + } + ) + + +def _choice_provider_specific_fields(choice: Mapping[str, object]) -> Mapping[str, object]: + fields: Final = choice.get("provider_specific_fields") + return _FIELD_MAP.validate_python(fields) if isinstance(fields, dict) else MappingProxyType({}) + + _REPLAY_REASONING_FIELDS: Final = frozenset({"reasoning_content", "thinking_blocks", "reasoning_items"}) _REPLAY_LEAD_FIELDS: Final = _REPLAY_REASONING_FIELDS | {"role", "provider_specific_fields"} _REPLAY_TOOL_FIELDS: Final = frozenset({"tool_calls", "function_call"}) @@ -220,8 +248,9 @@ def _replay_frame( choice.finish_reason = finish_reason if not keeps_choice_metadata: choice.logprobs = None - if hasattr(choice, "enhancements"): - del choice.enhancements + _drop_choice_fields(choice, ("enhancements", *STREAM_CHUNK_CHOICE_FIELDS)) + if finish_reason is None: + _drop_choice_fields(choice, STREAM_FINISH_CHOICE_FIELDS) return frame @@ -325,7 +354,9 @@ async def convert_to_streaming_response_async( logprobs = choice.get("logprobs", None) - choice = StreamingChoices(finish_reason=finish_reason, index=idx, delta=delta, logprobs=logprobs) + choice = StreamingChoices( + finish_reason=finish_reason, index=idx, delta=delta, logprobs=logprobs, **_vllm_choice_fields(choice) + ) choice_list.append(choice) model_response_object.choices = choice_list @@ -388,6 +419,7 @@ def convert_to_streaming_response( delta=delta, logprobs=logprobs, enhancements=enhancements, + **_vllm_choice_fields(choice), ) choice_list.append(choice) @@ -872,6 +904,7 @@ def convert_to_model_response_object( logprobs=logprobs, enhancements=enhancements, provider_specific_fields=provider_specific_fields, + **_vllm_choice_fields(choice), ) if provider_sent_logprobs and logprobs is None: choice.logprobs = None @@ -937,9 +970,11 @@ def convert_to_model_response_object( model_response_object.data = response_object["data"] if "usage" in response_object and response_object["usage"] is not None: - model_response_object.usage.completion_tokens = response_object["usage"].get("completion_tokens", 0) - model_response_object.usage.prompt_tokens = response_object["usage"].get("prompt_tokens", 0) - model_response_object.usage.total_tokens = response_object["usage"].get("total_tokens", 0) + embedding_usage: Final = model_response_object.usage or Usage() + embedding_usage.completion_tokens = response_object["usage"].get("completion_tokens", 0) + embedding_usage.prompt_tokens = response_object["usage"].get("prompt_tokens", 0) + embedding_usage.total_tokens = response_object["usage"].get("total_tokens", 0) + model_response_object.usage = embedding_usage if start_time is not None and end_time is not None: model_response_object._response_ms = ( @@ -982,6 +1017,10 @@ def convert_to_model_response_object( if key in response_object: setattr(model_response_object, key, response_object[key]) + detected_languages: Final = TranscriptionResponse.detected_languages(response_object.get("languages")) + if detected_languages is not None: + model_response_object.languages = detected_languages + if "usage" in response_object and response_object["usage"] is not None: tr_usage_object: TranscriptionUsageDurationObject | TranscriptionUsageTokensObject | None = None @@ -1042,4 +1081,8 @@ def convert_to_model_response_object( end_time=end_time, convert_tool_call_to_json_mode=convert_tool_call_to_json_mode, ) - raise Exception(f"Invalid response object {traceback.format_exc()}\n\nreceived_args={received_args}") + # The conversion's own traceback, without the errors being handled when it ran: a router + # retry runs inside the handler of the attempt before it, and that attempt's error text + # (a rate limit) would otherwise decide how this one is classified. + own_traceback: Final = "".join(traceback.format_exception(type(e), e, e.__traceback__, chain=False)) + raise Exception(f"Invalid response object {own_traceback}\n\nreceived_args={received_args}") diff --git a/litellm/litellm_core_utils/model_param_helper.py b/litellm/litellm_core_utils/model_param_helper.py index b08596e5244..3e82077f9d6 100644 --- a/litellm/litellm_core_utils/model_param_helper.py +++ b/litellm/litellm_core_utils/model_param_helper.py @@ -1,6 +1,6 @@ from collections.abc import Mapping from functools import lru_cache -from typing import ClassVar, Final +from typing import ClassVar, Final, get_args from openai.types.chat.completion_create_params import ( CompletionCreateParamsNonStreaming, @@ -21,6 +21,7 @@ from pydantic import TypeAdapter, ValidationError from litellm._logging import verbose_logger from litellm.types.llms.anthropic import AnthropicMessagesRequest +from litellm.types.llms.openai import OpenAIAudioTranscriptionOptionalParams from litellm.types.rerank import RerankRequest @@ -178,6 +179,7 @@ class ModelParamHelper: This follows the OpenAI API Spec """ + litellm_transcription_kwargs: Final = set(get_args(OpenAIAudioTranscriptionOptionalParams)) try: from openai.types.audio.transcription_create_params import ( TranscriptionCreateParamsNonStreaming, @@ -187,11 +189,11 @@ class ModelParamHelper: non_streaming_kwargs = set(getattr(TranscriptionCreateParamsNonStreaming, "__annotations__", {}).keys()) streaming_kwargs: Final = set(getattr(TranscriptionCreateParamsStreaming, "__annotations__", {}).keys()) - all_transcription_kwargs: Final = non_streaming_kwargs.union(streaming_kwargs) + all_transcription_kwargs: Final = non_streaming_kwargs.union(streaming_kwargs, litellm_transcription_kwargs) return all_transcription_kwargs except Exception as e: verbose_logger.debug("Error getting transcription kwargs %s", str(e)) - return set() + return litellm_transcription_kwargs @staticmethod def _get_litellm_supported_responses_api_kwargs() -> set[str]: diff --git a/litellm/litellm_core_utils/pattern_match_deployments.py b/litellm/litellm_core_utils/pattern_match_deployments.py index 2b8d1e9c11b..a9091348c50 100644 --- a/litellm/litellm_core_utils/pattern_match_deployments.py +++ b/litellm/litellm_core_utils/pattern_match_deployments.py @@ -5,6 +5,7 @@ Class to handle llm wildcard routing and regex pattern matching import copy import itertools import re +from collections.abc import Mapping from re import Match from typing import Final @@ -22,6 +23,16 @@ class _RoutedDeployment(BaseModel): _ROUTED_DEPLOYMENTS: Final = TypeAdapter(tuple[_RoutedDeployment, ...]) +_PATTERN_WIDE_CACHE_FLAGS: Final = frozenset(("supports_prompt_cache_breakpoint", "supports_prompt_caching")) +_AZURE_AI_PATTERN_CACHE_FLAGS: Final = frozenset(("supports_prompt_caching",)) + + +def _cache_flags_left_to_the_catalog(litellm_params: Mapping[str, object]) -> frozenset[str]: + model: Final = litellm_params.get("model") + provider: Final = litellm_params.get("custom_llm_provider") or inferred_provider( + model if isinstance(model, str) else None + ) + return _AZURE_AI_PATTERN_CACHE_FLAGS if provider == "azure_ai" else _PATTERN_WIDE_CACHE_FLAGS class PatternUtils: @@ -133,6 +144,11 @@ class PatternMatchRouter: matched_pattern=matched_pattern, litellm_deployment_litellm_model=deployment["litellm_params"]["model"], ) + if "*" in deployment["litellm_params"]["model"] and isinstance(new_deployment.get("model_info"), dict): + left_to_the_catalog = _cache_flags_left_to_the_catalog(deployment["litellm_params"]) + new_deployment["model_info"] = { + key: value for key, value in new_deployment["model_info"].items() if key not in left_to_the_catalog + } new_deployments.append(new_deployment) return new_deployments diff --git a/litellm/litellm_core_utils/per_call_pricing.py b/litellm/litellm_core_utils/per_call_pricing.py new file mode 100644 index 00000000000..686639dc10f --- /dev/null +++ b/litellm/litellm_core_utils/per_call_pricing.py @@ -0,0 +1,104 @@ +"""The price entry for a single call that sets its own custom pricing, built without writing ``litellm.model_cost``.""" + +from collections.abc import Mapping +from typing import Final, Literal + +from pydantic import TypeAdapter + +import litellm +from litellm.litellm_core_utils.ptu_pricing import zeroed_ptu_pricing +from litellm.types.utils import CustomPricingLiteLLMParams, ModelInfo + +_STR_MAPPING: Final = TypeAdapter(Mapping[str, object]) +_MODEL_INFO: Final = TypeAdapter(ModelInfo) + + +def _router_deployment_model_info(kwargs: Mapping[str, object]) -> Mapping[str, object] | None: + """A Router stamps the deployment's ``model_info`` (with its ``id``) into the call's metadata and registers that + deployment's full custom pricing under that id when the deployment is added.""" + for metadata_key in ("litellm_metadata", "metadata"): + metadata = kwargs.get(metadata_key) + if not isinstance(metadata, Mapping): + continue + model_info = _STR_MAPPING.validate_python(metadata).get("model_info") + if isinstance(model_info, Mapping) and isinstance(model_info.get("id"), str): + return _STR_MAPPING.validate_python(model_info) + return None + + +def per_call_model_info( + model: str, custom_llm_provider: str, kwargs: Mapping[str, object], mode: Literal["chat", "embedding"] +) -> ModelInfo | None: + """The full price entry for one call, or None when the cost map (or the Router's registered deployment entry) + already prices it. The cost map row for the model is overlaid with the registered deployment entry and then with + the custom pricing fields the request itself set, so a Router call pays request overrides over deployment prices. + The entry travels on the logging object and is never written into ``litellm.model_cost``, so the next call for the + same model name is priced from the cost map again.""" + deployment: Final = _router_deployment_model_info(kwargs) + registered: Final = litellm.model_cost.get(str(deployment["id"])) if deployment is not None else None + custom: Final = { + field: kwargs[field] + for field in CustomPricingLiteLLMParams.model_fields + if kwargs.get(field) is not None and (registered is None or registered.get(field) != kwargs[field]) + } + if not custom: + return None + unmapped: Final[Mapping[str, object]] = { + "key": model, + "max_tokens": None, + "max_input_tokens": None, + "max_output_tokens": None, + "input_cost_per_token": None, + "output_cost_per_token": None, + "litellm_provider": custom_llm_provider, + "mode": mode, + "supported_openai_params": None, + } + row: Final = _catalog_row(model, custom_llm_provider) or unmapped + catalog: Final = ( + {**row, **{key: value for key, value in registered.items() if value is not None}} if registered else row + ) + zeroed: Final = zeroed_ptu_pricing(deployment, custom) if deployment is not None else None + return _MODEL_INFO.validate_python( + { + **catalog, + **_token_rates_cleared_for_per_second_overrides(custom), + **custom, + **_tiers_with_flat_overrides(catalog, custom), + **(zeroed or {}), + "mode": catalog.get("mode") or mode, + } + ) + + +_FLAT_TOKEN_RATE_FIELDS: Final = ("input_cost_per_token", "output_cost_per_token") +_PER_SECOND_RATE_FIELDS: Final = ("cost_per_second", "input_cost_per_second", "output_cost_per_second") +_TIERS: Final = TypeAdapter(tuple[Mapping[str, object], ...]) + + +def _token_rates_cleared_for_per_second_overrides(custom: Mapping[str, object]) -> Mapping[str, object]: + """Token rates in the entry make the cost calculator skip per-second pricing, so a caller who sets only a + per-second rate gets the catalog's token rates and tier table cleared for this call.""" + if not any(key in custom for key in _PER_SECOND_RATE_FIELDS) or any( + key in custom for key in _FLAT_TOKEN_RATE_FIELDS + ): + return {} + return {"input_cost_per_token": None, "output_cost_per_token": None, "tiered_pricing": None} + + +def _tiers_with_flat_overrides(catalog: Mapping[str, object], custom: Mapping[str, object]) -> Mapping[str, object]: + """A ``tiered_pricing`` table wins over flat rates in the cost calculator, so a flat rate the caller set is written + into every tier of the table in force (the caller's own, else the inherited one) for that direction, and the other + direction keeps each tier's own rate.""" + overrides: Final = {key: custom[key] for key in _FLAT_TOKEN_RATE_FIELDS if key in custom} + tiers: Final = custom.get("tiered_pricing", catalog.get("tiered_pricing")) + if not overrides or not isinstance(tiers, (list, tuple)) or not tiers: + return {} + return {"tiered_pricing": [{**tier, **overrides} for tier in _TIERS.validate_python(tiers)]} + + +def _catalog_row(model: str, custom_llm_provider: str) -> ModelInfo | None: + try: + return litellm.get_model_info(model=model, custom_llm_provider=custom_llm_provider) + except Exception: # noqa: BLE001 # get_model_info raises a bare Exception for an unmapped model + return None diff --git a/litellm/litellm_core_utils/prompt_templates/chat_template_tools.py b/litellm/litellm_core_utils/prompt_templates/chat_template_tools.py index 60134456577..49ffae03c40 100644 --- a/litellm/litellm_core_utils/prompt_templates/chat_template_tools.py +++ b/litellm/litellm_core_utils/prompt_templates/chat_template_tools.py @@ -10,12 +10,18 @@ class ChatTemplateToolSection: preamble_tokens: int implicit_system_turn_tokens: int render_tool_schemas: Callable[[Sequence[Mapping[str, object]]], str] + counts_tool_choice: bool = False + renders_strict_only_when_true: bool = False -def _deepseek_v4_tool_schemas(functions: Sequence[Mapping[str, object]]) -> str: +def _json_line_tool_schemas(functions: Sequence[Mapping[str, object]]) -> str: return "\n".join(json.dumps(function, ensure_ascii=False) for function in functions) +def _compact_json_line_tool_schemas(functions: Sequence[Mapping[str, object]]) -> str: + return "\n".join(json.dumps(function, ensure_ascii=False, separators=(",", ":")) for function in functions) + + def _qwen3_5_tool_schemas(functions: Sequence[Mapping[str, object]]) -> str: return "".join( "\n" + json.dumps({"type": "function", "function": function}, ensure_ascii=False) for function in functions @@ -23,13 +29,29 @@ def _qwen3_5_tool_schemas(functions: Sequence[Mapping[str, object]]) -> str: _TOOL_SECTIONS: Final = ( + ( + re.compile(r"deepseek-v4(?:[-._]|p)1(?!\d)", re.IGNORECASE), + ChatTemplateToolSection(211, 0, _json_line_tool_schemas), + ), ( re.compile( r"deepseek-v4(?![.\d]|p\d)|^(?:deepseek/)?deepseek-(?:chat|reasoner|flash)(?::free)?$", re.IGNORECASE ), - ChatTemplateToolSection(222, 0, _deepseek_v4_tool_schemas), + ChatTemplateToolSection(222, 0, _json_line_tool_schemas), ), (re.compile(r"qwen3[._]?5(?!\d)", re.IGNORECASE), ChatTemplateToolSection(196, 5, _qwen3_5_tool_schemas)), + ( + re.compile(r"grok-4[-.]1(?![.\d])", re.IGNORECASE), + ChatTemplateToolSection( + 0, 0, _compact_json_line_tool_schemas, counts_tool_choice=True, renders_strict_only_when_true=True + ), + ), + ( + re.compile(r"grok-4[-.]3(?![.\d])", re.IGNORECASE), + ChatTemplateToolSection( + 0, 0, _json_line_tool_schemas, counts_tool_choice=True, renders_strict_only_when_true=True + ), + ), ) diff --git a/litellm/litellm_core_utils/prompt_templates/common_utils.py b/litellm/litellm_core_utils/prompt_templates/common_utils.py index 938ab585b72..f48a42963cf 100644 --- a/litellm/litellm_core_utils/prompt_templates/common_utils.py +++ b/litellm/litellm_core_utils/prompt_templates/common_utils.py @@ -21,14 +21,17 @@ from pydantic import TypeAdapter, ValidationError import litellm from litellm import verbose_logger +from litellm.exceptions import UnsupportedParamsError from litellm.litellm_core_utils.batch_utils import InMemoryFile from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.types.llms.openai import ( AllMessageValues, ChatCompletionAssistantMessage, ChatCompletionAudioObject, + ChatCompletionCachedContent, ChatCompletionFileObject, ChatCompletionImageObject, + ChatCompletionPromptCacheBreakpoint, ChatCompletionReasoningItem, ChatCompletionReasoningSummaryTextBlock, ChatCompletionRedactedThinkingBlock, @@ -396,6 +399,74 @@ def split_media_for_tpm(value: object) -> tuple[object, tuple[Mapping[str, objec return projection.content, projection.media +_TPM_EMBEDDING_FILE_MIME_PREFIXES: Final = ("application/pdf", "video/") + + +def _tpm_embedding_file(data_uri: str) -> tuple[Mapping[str, object], ...]: + from litellm.litellm_core_utils.prompt_templates.factory import parse_mime_type + + mime: Final = (parse_mime_type(data_uri[:256]) or "").strip().lower() + if not mime.startswith(_TPM_EMBEDDING_FILE_MIME_PREFIXES): + return () + return ({"type": "file", "file": {"file_data": data_uri, "format": mime}},) + + +_BASE64_PAYLOAD: Final = re.compile(r"[A-Za-z0-9+/]*={0,2}") + + +def _is_base64_data_uri(value: str) -> bool: + header_end: Final = value.find(",", 0, 256) + if header_end < 0 or not value[:header_end].endswith(";base64"): + return False + payload_start: Final = header_end + 1 + if (len(value) - payload_start) % 4 or _BASE64_PAYLOAD.fullmatch(value, payload_start) is None: + return False + last_quantum: Final = value[max(payload_start, len(value) - 4) :] + return base64.b64encode(base64.b64decode(last_quantum)).decode("ascii") == last_quantum + + +def _tpm_embedding_file_block(part: Mapping[str, object]) -> _TPMMediaProjection: + projection: Final = _tpm_file_media(part) + fields: Final = as_str_mapping(part.get("file")) + data: Final = fields.get("file_data") if fields is not None else None + if projection.media or fields is None or not isinstance(data, str) or not _is_base64_data_uri(data): + return projection + media: Final = _tpm_embedding_file(data) + return _TPMMediaProjection({**part, "file": _tpm_blank_fields(fields, ("file_data",))} if media else part, media) + + +def _tpm_embedding_leaf(value: object) -> _TPMMediaProjection: + part: Final = as_str_mapping(value) + if part is not None and part.get("type") == "file": + return _tpm_embedding_file_block(part) + if not isinstance(value, str) or not value.startswith("data:"): + return _tpm_media_leaf(value) + if not _is_base64_data_uri(value): + return _TPMMediaProjection(value) + media: Final = _tpm_file_media({"file_data": value}).media or _tpm_embedding_file(value) + return _TPMMediaProjection("" if media else value, media) + + +def _is_json_array(value: object) -> bool: + return isinstance(value, (list, tuple)) + + +def _tpm_embedding_item(value: object) -> _TPMMediaProjection: + return _tpm_media_list(value, _tpm_embedding_leaf) if _is_json_array(value) else _tpm_embedding_leaf(value) + + +def split_embedding_media_for_tpm(value: object) -> tuple[object, tuple[Mapping[str, object], ...]]: + projection: Final = ( + _tpm_media_list(value, _tpm_embedding_item) if _is_json_array(value) else _tpm_embedding_leaf(value) + ) + return projection.content, projection.media + + +def embedding_input_is_all_media(value: object) -> bool: + items: Final = cast(Sequence[object], value) if _is_json_array(value) else (value,) # cast-ok: JSON input array + return all(_tpm_embedding_leaf(item).media for item in items) + + def _content_parts_contain_image(parts: Sequence[object]) -> bool: """Depth-bounded frontier walk over nested content lists, iterative because the repo bans recursion; an Anthropic tool_result nests its image parts exactly one level down.""" @@ -2182,6 +2253,9 @@ def check_is_function_call(logging_obj: "LoggingClass") -> bool: _MarkedT: Final = TypeVar("_MarkedT", bound=Mapping[str, object]) +PROMPT_CACHE_BREAKPOINT_DROP_PARAMS_HINT: Final = ( + "set `drop_params: true` on the request or in litellm_settings (`litellm.drop_params = True` in the SDK)" +) def with_prompt_cache_breakpoint(target: _MarkedT, marker: object) -> _MarkedT: @@ -2193,16 +2267,62 @@ def with_prompt_cache_breakpoint(target: _MarkedT, marker: object) -> _MarkedT: _PROMPT_CACHE_BREAKPOINT: Final = TypeAdapter(PromptCacheBreakpoint) +_CHAT_COMPLETION_PROMPT_CACHE_BREAKPOINT: Final = TypeAdapter(ChatCompletionPromptCacheBreakpoint) +_AcceptedBreakpointT: Final = TypeVar("_AcceptedBreakpointT", bound=Mapping[str, object]) + + +def _accepted_prompt_cache_breakpoint( + accepted: TypeAdapter[_AcceptedBreakpointT], marker: object +) -> _AcceptedBreakpointT | None: + try: + return accepted.validate_python(marker) + except ValidationError: + return None + + +def prompt_cache_breakpoint_within( + accepted: TypeAdapter[_AcceptedBreakpointT], marker: object +) -> _AcceptedBreakpointT | None: + """The client's marker cut down to the ``accepted`` shape: an unsupported ttl is dropped and the mode kept, + and a marker whose mode the target cannot read is dropped whole.""" + whole: Final = _accepted_prompt_cache_breakpoint(accepted, marker) + if whole is not None: + return whole + fields: Final = _breakpoint_fields_or_none(marker) + without_ttl: Final = ( + None + if fields is None + else _accepted_prompt_cache_breakpoint(accepted, {key: item for key, item in fields.items() if key != "ttl"}) + ) + verbose_logger.debug( + "Dropping malformed prompt_cache_breakpoint %r under drop_params" + if without_ttl is None + else "Dropping the unsupported ttl of prompt_cache_breakpoint %r under drop_params", + marker, + ) + return without_ttl def prompt_cache_breakpoint_for_wire(marker: object, drop_params: bool) -> object: if marker is None or not drop_params: return marker - try: - return _PROMPT_CACHE_BREAKPOINT.validate_python(marker) - except ValidationError: - verbose_logger.debug("Dropping malformed prompt_cache_breakpoint %r under drop_params", marker) - return None + return prompt_cache_breakpoint_within(_PROMPT_CACHE_BREAKPOINT, marker) + + +def prompt_cache_breakpoint_with_readable_mode(marker: object, drop_params: bool) -> object: + """The client's marker as written, or None under drop_params when no target could read its mode, so the + target's own config decides which ttl and keys it keeps.""" + return None if prompt_cache_breakpoint_for_wire(marker, drop_params) is None else marker + + +def whole_prompt_cache_breakpoint_or_none(marker: object) -> PromptCacheBreakpoint | None: + return _accepted_prompt_cache_breakpoint(_PROMPT_CACHE_BREAKPOINT, marker) + + +def chat_completion_prompt_cache_breakpoint_for_wire(marker: object, drop_params: bool) -> object: + if marker is None or not drop_params: + return marker + return prompt_cache_breakpoint_within(_CHAT_COMPLETION_PROMPT_CACHE_BREAKPOINT, marker) def cache_control_as_prompt_cache_breakpoint(block: _MarkedT) -> _MarkedT: @@ -2215,11 +2335,63 @@ def cache_control_as_prompt_cache_breakpoint(block: _MarkedT) -> _MarkedT: ) +def prompt_cache_breakpoint_as_cache_control(block: _MarkedT, drop_params: bool) -> _MarkedT: + """OpenAI's ``prompt_cache_breakpoint`` mark rewritten as Anthropic's ``cache_control`` on the same block. + A ``cache_control`` the client already wrote on the block wins, TTL included.""" + marker: Final = block.get("prompt_cache_breakpoint") + if marker is None: + return block + unmarked: Final = {key: value for key, value in block.items() if key != "prompt_cache_breakpoint"} + control: Final = ( + None + if block.get("cache_control") is not None + else _cache_control_for_prompt_cache_breakpoint(marker, drop_params) + ) + marked: Final = unmarked if control is None else {**unmarked, "cache_control": control} + return cast(_MarkedT, marked) # cast-ok: same block shape as the input with the marker key renamed + + +def _cache_control_for_prompt_cache_breakpoint(marker: object, drop_params: bool) -> ChatCompletionCachedContent | None: + try: + breakpoint_mark: Final = _PROMPT_CACHE_BREAKPOINT.validate_python(marker) + except ValidationError: + if not drop_params: + raise UnsupportedParamsError( + message=( + f"prompt_cache_breakpoint must be {{'mode': 'explicit'}} with an optional ttl of '30m' or '12h', got " + f"{marker!r}. Fix the marker, or " + f"{PROMPT_CACHE_BREAKPOINT_DROP_PARAMS_HINT} to drop it." + ), + status_code=400, + ) + verbose_logger.debug("Dropping malformed prompt_cache_breakpoint %r under drop_params", marker) + return None + ttl: Final = breakpoint_mark.get("ttl") + if ttl is not None and not drop_params: + raise UnsupportedParamsError( + message=( + f"This model's prompt cache lasts 5m, or 1h where it offers one, so prompt_cache_breakpoint " + f"ttl={ttl!r} has no equivalent. Remove the ttl, {PROMPT_CACHE_BREAKPOINT_DROP_PARAMS_HINT} to send " + "a 5m breakpoint instead, or send cache_control {'type': 'ephemeral', 'ttl': '1h'} on the block " + "where the model offers a 1h cache." + ), + status_code=400, + ) + return ChatCompletionCachedContent(type="ephemeral") + + _BREAKPOINT_BLOCK_LIST_KEYS: Final = frozenset({"content", "tool_calls"}) _BREAKPOINT_FIELDS: Final = TypeAdapter(Mapping[str, object]) _BREAKPOINT_BLOCKS: Final = TypeAdapter(list[object]) +def _breakpoint_fields_or_none(value: object) -> Mapping[str, object] | None: + try: + return _BREAKPOINT_FIELDS.validate_python(value) + except ValidationError: + return None + + def _without_prompt_cache_breakpoint(value: object) -> object: if not isinstance(value, Mapping): return value @@ -2242,6 +2414,27 @@ def without_prompt_cache_breakpoints(block: _MarkedT) -> _MarkedT: return cast(_MarkedT, stripped) # cast-ok: same block shape as the input minus the marker keys +def _part_with_chat_completion_prompt_cache_breakpoint(part: object) -> object: + if not isinstance(part, Mapping): + return part + fields: Final = _BREAKPOINT_FIELDS.validate_python(part) + marker: Final = fields.get("prompt_cache_breakpoint") + if marker is None: + return fields + unmarked: Final = {key: item for key, item in fields.items() if key != "prompt_cache_breakpoint"} + return with_prompt_cache_breakpoint(unmarked, chat_completion_prompt_cache_breakpoint_for_wire(marker, True)) + + +def chat_completion_prompt_cache_breakpoints_for_wire(message: _MarkedT, drop_params: bool) -> _MarkedT: + content: Final = message.get("content") + if not drop_params or not isinstance(content, list): + return message + parts: Final = [ + _part_with_chat_completion_prompt_cache_breakpoint(part) for part in _BREAKPOINT_BLOCKS.validate_python(content) + ] + return cast(_MarkedT, {**message, "content": parts}) # cast-ok: same message shape with its parts' markers trimmed + + LITELLM_RESPONSE_ONLY_MESSAGE_FIELDS: Final = frozenset( {"thinking_blocks", "reasoning_items", "provider_specific_fields"} ) diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py index 98348e434b2..4c3907dc52f 100644 --- a/litellm/litellm_core_utils/prompt_templates/factory.py +++ b/litellm/litellm_core_utils/prompt_templates/factory.py @@ -34,6 +34,7 @@ from litellm.litellm_core_utils.prompt_templates.mid_conversation_system import split_leading_system_run, string_field, ) +from litellm.litellm_core_utils.tool_fields import tools_without_hosted_mcp from litellm.litellm_core_utils.url_utils import async_safe_get, safe_get from litellm.llms.custom_httpx.http_handler import HTTPHandler, get_async_httpx_client, header_value from litellm.types.files import get_file_extension_from_mime_type @@ -76,7 +77,7 @@ from .common_utils import ( parse_tool_call_arguments, salvage_concatenated_tool_arguments, ) -from .image_handling import convert_url_to_base64 +from .image_handling import convert_url_to_base64, is_pdf_media_type def default_pt(messages): @@ -910,8 +911,17 @@ def convert_to_anthropic_image_obj(openai_image_url: str, format: str | None) -> ) +def _anthropic_https_url_block( + image_url: str, image_format: str | None +) -> AnthropicMessagesImageParam | AnthropicMessagesDocumentParam: + source: Final = AnthropicContentParamSourceUrl(type="url", url=image_url) + if image_format and is_pdf_media_type(image_format): + return AnthropicMessagesDocumentParam(type="document", source=source) + return AnthropicMessagesImageParam(type="image", source=source) + + def create_anthropic_image_param( - image_url_input: str | dict, + image_url_input: str | Mapping[str, object], format: str | None = None, is_bedrock_invoke: bool = False, ) -> AnthropicMessagesImageParam | AnthropicMessagesDocumentParam: @@ -920,13 +930,11 @@ def create_anthropic_image_param( Supports both URL references (for HTTP/HTTPS URLs) and base64 encoding. """ - # Extract URL and format from input - if isinstance(image_url_input, str): - image_url = image_url_input - else: - image_url = image_url_input.get("url", "") - if format is None: - format = image_url_input.get("format") + url_value: Final = image_url_input if isinstance(image_url_input, str) else image_url_input.get("url") + format_value: Final = None if isinstance(image_url_input, str) else image_url_input.get("format") + image_url: Final = url_value if isinstance(url_value, str) else "" + explicit_format: Final = format if format is not None else format_value + image_format: Final = explicit_format if isinstance(explicit_format, str) else None # Check if the image URL is an HTTP/HTTPS URL if image_url.startswith("http://") or image_url.startswith("https://"): @@ -934,21 +942,14 @@ def create_anthropic_image_param( # as these providers don't support URL sources for images if is_bedrock_invoke or image_url.startswith("http://"): base64_url: Final = convert_url_to_base64(url=image_url) - image_chunk = convert_to_anthropic_image_obj(openai_image_url=base64_url, format=format) - return _anthropic_content_element_factory(image_chunk) + image_chunk = convert_to_anthropic_image_obj(openai_image_url=base64_url, format=image_format) + return anthropic_content_element_factory(image_chunk) else: - # HTTPS URL - pass directly for regular Anthropic - return AnthropicMessagesImageParam( - type="image", - source=AnthropicContentParamSourceUrl( - type="url", - url=image_url, - ), - ) + return _anthropic_https_url_block(image_url, image_format) else: # Convert to base64 for data URIs or other formats - image_chunk = convert_to_anthropic_image_obj(openai_image_url=image_url, format=format) - return _anthropic_content_element_factory(image_chunk) + image_chunk = convert_to_anthropic_image_obj(openai_image_url=image_url, format=image_format) + return anthropic_content_element_factory(image_chunk) # The following XML functions will be deprecated once JSON schema support is available on Bedrock and Vertex @@ -1328,7 +1329,7 @@ def get_thought_signature_from_tool(tool: Mapping[str, object]) -> str | None: _get_thought_signature_from_tool = get_thought_signature_from_tool -def _get_dummy_thought_signature() -> str: +def get_dummy_thought_signature() -> str: """Generate a dummy thought signature for models that require it. This is used when transferring conversation history from older models @@ -1415,7 +1416,7 @@ def convert_to_gemini_tool_call_invoke( # https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/thinking/thought-signatures#parallel_function_calling_example is_first_function_call = len(_parts_list) == 0 if not thought_signature and is_first_function_call and needs_dummy_signature: - thought_signature = _get_dummy_thought_signature() + thought_signature = get_dummy_thought_signature() if thought_signature: part_dict["thoughtSignature"] = thought_signature @@ -1439,7 +1440,7 @@ def convert_to_gemini_tool_call_invoke( # If no signature found and model is gemini-3, use dummy signature if not thought_signature and needs_dummy_signature: - thought_signature = _get_dummy_thought_signature() + thought_signature = get_dummy_thought_signature() if thought_signature: part_dict_function["thoughtSignature"] = thought_signature @@ -2254,16 +2255,16 @@ def add_cache_control_to_content( return anthropic_content_element -def _anthropic_content_element_factory( +def anthropic_content_element_factory( image_chunk: GenericImageParsingChunk, ) -> AnthropicMessagesImageParam | AnthropicMessagesDocumentParam: - if image_chunk["media_type"] == "application/pdf": + if is_pdf_media_type(image_chunk["media_type"]): _anthropic_content_element: AnthropicMessagesDocumentParam | AnthropicMessagesImageParam = ( AnthropicMessagesDocumentParam( type="document", source=AnthropicContentParamSource( type="base64", - media_type=image_chunk["media_type"], + media_type="application/pdf", data=image_chunk["data"], ), ) @@ -4253,6 +4254,7 @@ def _convert_to_bedrock_tool_call_invoke( tool_calls: list, model: str | None = None, deployment_model: str | None = None, + model_info: Mapping[str, object] | None = None, ) -> list[BedrockContentBlock]: """ OpenAI tool invokes: @@ -4337,6 +4339,7 @@ def _convert_to_bedrock_tool_call_invoke( block_type="content_block", model=model, deployment_model=deployment_model, + model_info=model_info, ) if _cache_point_block is not None: _parts_list.append(_cache_point_block) @@ -4357,6 +4360,7 @@ def _convert_to_bedrock_tool_call_invoke( block_type="content_block", model=model, deployment_model=deployment_model, + model_info=model_info, ) if cache_point_block is not None: _parts_list.append(cache_point_block) @@ -5028,6 +5032,7 @@ class BedrockConverseMessagesProcessor: deployment_model: str | None = None, base_model: str | None = None, drop_params: bool = False, + model_info: Mapping[str, object] | None = None, ) -> list[BedrockMessageBlock]: from litellm.llms.bedrock.common_utils import bedrock_converse_accepts_redacted_thinking @@ -5090,6 +5095,7 @@ class BedrockConverseMessagesProcessor: block_type="content_block", model=model, deployment_model=deployment_model, + model_info=model_info, ) if _cache_point_block is not None: _parts.append(_cache_point_block) @@ -5097,7 +5103,11 @@ class BedrockConverseMessagesProcessor: elif message_content and isinstance(message_content, str): _part = BedrockContentBlock(text=message_content) _cache_point_block = litellm.AmazonConverseConfig().get_cache_point_block( - message_block, block_type="content_block", model=model, deployment_model=deployment_model + message_block, + block_type="content_block", + model=model, + deployment_model=deployment_model, + model_info=model_info, ) user_content.append(_part) if _cache_point_block is not None: @@ -5148,6 +5158,7 @@ class BedrockConverseMessagesProcessor: block_type="content_block", model=model, deployment_model=deployment_model, + model_info=model_info, ) if cache_point_block is not None: tool_content.append(cache_point_block) @@ -5213,6 +5224,7 @@ class BedrockConverseMessagesProcessor: block_type="content_block", model=model, deployment_model=deployment_model, + model_info=model_info, ) if _cache_point_block is not None and not ( drop_params and _as_thinking_block(element) is not None @@ -5230,6 +5242,7 @@ class BedrockConverseMessagesProcessor: block_type="content_block", model=model, deployment_model=deployment_model, + model_info=model_info, ) if _cache_point_block is not None: assistant_content.append(_cache_point_block) @@ -5238,7 +5251,7 @@ class BedrockConverseMessagesProcessor: if _tool_calls: assistant_content.extend( _convert_to_bedrock_tool_call_invoke( - _tool_calls, model=model, deployment_model=deployment_model + _tool_calls, model=model, deployment_model=deployment_model, model_info=model_info ) ) @@ -5433,6 +5446,7 @@ def _bedrock_converse_messages_pt( deployment_model: str | None = None, base_model: str | None = None, drop_params: bool = False, + model_info: Mapping[str, object] | None = None, ) -> list[BedrockMessageBlock]: """ Converts given messages from OpenAI format to Bedrock format @@ -5501,6 +5515,7 @@ def _bedrock_converse_messages_pt( block_type="content_block", model=model, deployment_model=deployment_model, + model_info=model_info, ) if _cache_point_block is not None: _parts.append(_cache_point_block) @@ -5508,7 +5523,11 @@ def _bedrock_converse_messages_pt( elif message_content and isinstance(message_content, str): _part = BedrockContentBlock(text=message_content) _cache_point_block = litellm.AmazonConverseConfig().get_cache_point_block( - message_block, block_type="content_block", model=model, deployment_model=deployment_model + message_block, + block_type="content_block", + model=model, + deployment_model=deployment_model, + model_info=model_info, ) user_content.append(_part) if _cache_point_block is not None: @@ -5561,6 +5580,7 @@ def _bedrock_converse_messages_pt( block_type="content_block", model=model, deployment_model=deployment_model, + model_info=model_info, ) if cache_point_block is not None: tool_content.append(cache_point_block) @@ -5627,6 +5647,7 @@ def _bedrock_converse_messages_pt( block_type="content_block", model=model, deployment_model=deployment_model, + model_info=model_info, ) if _cache_point_block is not None and not ( drop_params and _as_thinking_block(element) is not None @@ -5639,14 +5660,20 @@ def _bedrock_converse_messages_pt( assistant_content.append(BedrockContentBlock(text=_assistant_content)) # Add cache point block for assistant string content _cache_point_block = litellm.AmazonConverseConfig().get_cache_point_block( - assistant_message_block, block_type="content_block", model=model, deployment_model=deployment_model + assistant_message_block, + block_type="content_block", + model=model, + deployment_model=deployment_model, + model_info=model_info, ) if _cache_point_block is not None: assistant_content.append(_cache_point_block) _tool_calls = assistant_message_block.get("tool_calls", []) if _tool_calls: assistant_content.extend( - _convert_to_bedrock_tool_call_invoke(_tool_calls, model=model, deployment_model=deployment_model) + _convert_to_bedrock_tool_call_invoke( + _tool_calls, model=model, deployment_model=deployment_model, model_info=model_info + ) ) msg_i += 1 @@ -5702,7 +5729,10 @@ def make_valid_bedrock_tool_name(input_tool_name: str) -> str: def add_cache_point_tool_block( - tool: dict, model: str | None = None, deployment_model: str | None = None + tool: dict, + model: str | None = None, + deployment_model: str | None = None, + model_info: Mapping[str, object] | None = None, ) -> BedrockToolBlock | None: from litellm.llms.bedrock.common_utils import ( bedrock_cache_point_ttl_supported, @@ -5710,7 +5740,7 @@ def add_cache_point_tool_block( ) cache_control: Final = tool.get("cache_control", None) - if cache_control is not None and bedrock_model_accepts_cache_points(model, deployment_model): + if cache_control is not None and bedrock_model_accepts_cache_points(model, deployment_model, model_info): cache_point: Final = cache_control.get("type", "ephemeral") if cache_point == "ephemeral": cache_point_block: Final[CachePointBlock] = {"type": "default"} @@ -5747,7 +5777,10 @@ def _is_bedrock_tool_block(tool: dict) -> bool: def _bedrock_tools_pt( - tools: list, model: str | None = None, deployment_model: str | None = None + tools: list, + model: str | None = None, + deployment_model: str | None = None, + model_info: Mapping[str, object] | None = None, ) -> list[BedrockToolBlock]: """ OpenAI tools looks like: @@ -5868,7 +5901,9 @@ def _bedrock_tools_pt( tool_block_list.append(tool_block) ## ADD CACHE POINT TOOL BLOCK ## - cache_point_tool_block = add_cache_point_tool_block(tool, model=model, deployment_model=deployment_model) + cache_point_tool_block = add_cache_point_tool_block( + tool, model=model, deployment_model=deployment_model, model_info=model_info + ) if cache_point_tool_block is not None: tool_block_list.append(cache_point_tool_block) @@ -5916,8 +5951,13 @@ def function_call_prompt( llm_provider: str, drop_params: bool, ) -> list[dict[str, object]]: + prompt_functions: Final = tools_without_hosted_mcp( + functions, model=model, route=llm_provider, drop_params=drop_params + ) + if not prompt_functions: + return messages header: Final = """To call a function, reply with JSON ONLY in this format {"name": "function_name", "arguments":{"argument_name": "argument_value"}}. Once a function result answers the request, reply to the user in plain text instead of calling a function again. The following functions are available to you:""" - function_prompt: Final = header + "".join(f"\n{function}\n" for function in functions) + function_prompt: Final = header + "".join(f"\n{function}\n" for function in prompt_functions) if not any(_is_system_message(message) for message in messages): return [*messages, {"role": "system", "content": function_prompt}] return [ diff --git a/litellm/litellm_core_utils/prompt_templates/image_handling.py b/litellm/litellm_core_utils/prompt_templates/image_handling.py index 3287515c81d..ffc0e82e410 100644 --- a/litellm/litellm_core_utils/prompt_templates/image_handling.py +++ b/litellm/litellm_core_utils/prompt_templates/image_handling.py @@ -5,28 +5,33 @@ Helper functions to handle images passed in messages import asyncio import base64 import time -from collections.abc import Callable, Iterable, Mapping +from collections.abc import Callable, Iterable, Iterator, Mapping, Sequence +from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass -from itertools import chain +from functools import partial +from itertools import accumulate, chain, takewhile, tee from types import MappingProxyType -from typing import Final +from typing import Final, TypeVar +from urllib.parse import urlparse import httpx -from httpx import Response +from httpx import USE_CLIENT_DEFAULT, Response import litellm from litellm import verbose_logger from litellm.caching.caching import InMemoryCache -from litellm.constants import MAX_IMAGE_URL_DOWNLOAD_SIZE_MB +from litellm.constants import MAX_IMAGE_URL_DOWNLOAD_SIZE_MB, NON_LLM_CONNECTION_TIMEOUT from litellm.litellm_core_utils.prompt_templates.common_utils import infer_content_type_from_url_and_content from litellm.litellm_core_utils.url_utils import SSRFError, async_safe_get, safe_get from litellm.types.llms.openai import AllMessageValues MAX_IMGS_IN_MEMORY: Final = 10 MAX_CONCURRENT_REMOTE_MEDIA_FETCHES: Final = 20 +_Fetched = TypeVar("_Fetched") _FETCH_ATTEMPTS: Final = 3 in_memory_cache: Final = InMemoryCache(max_size_in_memory=MAX_IMGS_IN_MEMORY) +pdf_probe_verdicts: Final = InMemoryCache() def _header_value(response: Response, name: str) -> str | None: @@ -209,6 +214,173 @@ def inline_remote_image_urls(media: RemoteMedia) -> bool: return media.part_type == "image_url" +_PDF_MEDIA_TYPES: Final = frozenset({"application/pdf", "application/x-pdf"}) +_GENERIC_MEDIA_TYPES: Final = frozenset({"application/octet-stream", "binary/octet-stream"}) +_PDF_SIGNATURE: Final = b"%PDF-" +_PDF_SIGNATURE_WINDOW: Final = 1024 +_PDF_PROBE_HEADERS: Final = MappingProxyType({"Range": f"bytes=0-{_PDF_SIGNATURE_WINDOW - 1}"}) +_PDF_PROBE_STATUSES: Final = frozenset({200, 206}) +_PDF_PROBE_FAILURES: Final = (httpx.HTTPError, httpx.InvalidURL, ValueError) +_ASYNC_PDF_PROBE_FAILURES: Final = (*_PDF_PROBE_FAILURES, asyncio.TimeoutError) +_PDF_PROBE_VERDICT_TTL: Final = 600 +_PDF_PROBE_FAILURE_TTL: Final = 60 +_DECODED_BODY_HEADERS: Final = frozenset({"content-encoding", "content-length", "transfer-encoding"}) + + +def _bare_media_type(media_type: str) -> str: + return media_type.split(";", 1)[0].strip().lower() + + +def is_pdf_media_type(media_type: str) -> bool: + return _bare_media_type(media_type) in _PDF_MEDIA_TYPES + + +def is_unformatted_pdf_link(url: str, image_format: str | None) -> bool: + lowered: Final = url.lower() + return not image_format and (urlparse(lowered).path.endswith(".pdf") or lowered.endswith(".pdf")) + + +def is_unformatted_pdf_link_image(media: RemoteMedia) -> bool: + image_format: Final = media.fields.get("format") + return inline_remote_image_urls(media) and is_unformatted_pdf_link( + media.url, image_format if isinstance(image_format, str) else None + ) + + +def _serves_pdf(response: Response) -> bool: + if response.status_code not in _PDF_PROBE_STATUSES: + return False + served_type: Final = _bare_media_type(_header_value(response, "Content-Type") or "") + if served_type and served_type not in _GENERIC_MEDIA_TYPES: + return served_type in _PDF_MEDIA_TYPES + return _PDF_SIGNATURE in response.content[:_PDF_SIGNATURE_WINDOW] + + +def _signature_window_chunks(chunks: Iterable[bytes], deadline: float) -> Iterator[bytes]: + reading, counting = tee(chunks) + read_so_far: Final = chain((0,), accumulate(map(len, counting))) + still_reading: Final = takewhile( + lambda total: total < _PDF_SIGNATURE_WINDOW and time.monotonic() < deadline, read_so_far + ) + return (chunk for _, chunk in zip(still_reading, reading)) + + +def _with_body_prefix(response: Response, prefix: bytes) -> Response: + return Response( + response.status_code, + headers=[(name, value) for name, value in response.headers.multi_items() if name not in _DECODED_BODY_HEADERS], + content=prefix, + request=response.request, + ) + + +@dataclass(frozen=True, slots=True) +class _BodyPrefixReader: + client: httpx.Client + deadline: float + + def get( + self, + url: str, + *, + headers: Mapping[str, str] | None = None, + follow_redirects: bool = False, + timeout: float | httpx.Timeout | None = None, + ) -> Response: + with self.client.stream( + "GET", + url, + headers=headers, + follow_redirects=follow_redirects, + timeout=USE_CLIENT_DEFAULT if timeout is None else timeout, + ) as response: + prefix: Final = b"".join(_signature_window_chunks(response.iter_bytes(), self.deadline)) + return _with_body_prefix(response, prefix[:_PDF_SIGNATURE_WINDOW]) + + +@dataclass(frozen=True, slots=True) +class _AsyncBodyPrefixReader: + client: httpx.AsyncClient + + async def get( + self, + url: str, + *, + headers: Mapping[str, str] | None = None, + follow_redirects: bool = False, + timeout: float | httpx.Timeout | None = None, + max_response_bytes: int | None = None, + ) -> Response: + async with self.client.stream( + "GET", + url, + headers=headers, + follow_redirects=follow_redirects, + timeout=USE_CLIENT_DEFAULT if timeout is None else timeout, + ) as response: + return _with_body_prefix(response, await anext(response.aiter_bytes(max_response_bytes), b"")) + + +def _cached_pdf_verdict(url: str) -> bool | None: + cached: Final = pdf_probe_verdicts.get_cache(url) + return cached if isinstance(cached, bool) else None + + +def _remember_pdf_verdict(url: str, verdict: bool, ttl: int) -> bool: + pdf_probe_verdicts.set_cache(url, verdict, ttl=ttl) + return verdict + + +def _remember_probe_response(url: str, response: Response) -> bool: + ttl: Final = _PDF_PROBE_VERDICT_TTL if response.status_code in _PDF_PROBE_STATUSES else _PDF_PROBE_FAILURE_TTL + return _remember_pdf_verdict(url, _serves_pdf(response), ttl) + + +def _failed_pdf_probe(url: str, error: Exception) -> bool: + verbose_logger.debug("PDF probe of %s failed, sending it as an image link: %s", url, error) + return _remember_pdf_verdict(url, False, _PDF_PROBE_FAILURE_TTL) + + +def serves_pdf(url: str, timeout: float = NON_LLM_CONNECTION_TIMEOUT) -> bool: + if MAX_IMAGE_URL_DOWNLOAD_SIZE_MB == 0: + return False + cached: Final = _cached_pdf_verdict(url) + if cached is not None: + return cached + try: + response: Final = safe_get( + _BodyPrefixReader(litellm.module_level_client.client, deadline=time.monotonic() + timeout), + url, + headers=dict(_PDF_PROBE_HEADERS), + timeout=timeout, + ) + except _PDF_PROBE_FAILURES as e: + return _failed_pdf_probe(url, e) + return _remember_probe_response(url, response) + + +async def async_serves_pdf(url: str, timeout: float = NON_LLM_CONNECTION_TIMEOUT) -> bool: + if MAX_IMAGE_URL_DOWNLOAD_SIZE_MB == 0: + return False + cached: Final = _cached_pdf_verdict(url) + if cached is not None: + return cached + try: + response: Final = await asyncio.wait_for( + async_safe_get( + _AsyncBodyPrefixReader(litellm.module_level_aclient.client), + url, + headers=dict(_PDF_PROBE_HEADERS), + timeout=timeout, + max_response_bytes=_PDF_SIGNATURE_WINDOW, + ), + timeout, + ) + except _ASYNC_PDF_PROBE_FAILURES as e: + return _failed_pdf_probe(url, e) + return _remember_probe_response(url, response) + + def _parse_remote_image(fields: Mapping[str, object]) -> _RemoteImage | None: if fields.get("type") != "image_url": return None @@ -292,15 +464,40 @@ def _inline_part(part: object, data_urls: Mapping[str, str], should_inline: Call return _inline(remote, data_url) if data_url is not None else part -def _inline_message( - message: AllMessageValues, data_urls: Mapping[str, str], should_inline: Callable[[RemoteMedia], bool] -) -> AllMessageValues: +def _with_parts(message: AllMessageValues, rewrite: Callable[[object], object]) -> AllMessageValues: parts: Final = _content_parts(message) if not parts: return message - inlined_parts: Final = [_inline_part(part, data_urls, should_inline) for part in parts] - inlined_message: Final = {**message, "content": inlined_parts} - return inlined_message # pyright: ignore[reportReturnType] # the same message with its remote parts inlined + rewritten: Final = {**message, "content": [rewrite(part) for part in parts]} + return rewritten # pyright: ignore[reportReturnType] # the same message with some of its parts rewritten + + +def _inline_message( + message: AllMessageValues, data_urls: Mapping[str, str], should_inline: Callable[[RemoteMedia], bool] +) -> AllMessageValues: + return _with_parts(message, partial(_inline_part, data_urls=data_urls, should_inline=should_inline)) + + +def _pdf_formatted_part(part: object, pdf_links: frozenset[str], should_probe: Callable[[RemoteMedia], bool]) -> object: + remote: Final = _parse_remote_part(part) + match remote: + case _RemoteImage(fields, image_url, url) if url in pdf_links and should_probe(_remote_media(remote)): + image_url_fields: Final = image_url if image_url is not None else _NO_FIELDS + return {**fields, "image_url": {**image_url_fields, "url": url, "format": "application/pdf"}} + case _: + return part + + +def _with_pdf_formats( + messages: Iterable[AllMessageValues], + probed: Iterable[tuple[str, bool]], + should_probe: Callable[[RemoteMedia], bool], +) -> tuple[AllMessageValues, ...]: + pdf_links: Final = frozenset(url for url, is_pdf in probed if is_pdf) + if not pdf_links: + return tuple(messages) + rewrite: Final = partial(_pdf_formatted_part, pdf_links=pdf_links, should_probe=should_probe) + return tuple(_with_parts(message, rewrite) for message in messages) async def _fetch_data_url(url: str, in_flight: asyncio.Semaphore, timeout: float | httpx.Timeout | None) -> str: @@ -308,11 +505,12 @@ async def _fetch_data_url(url: str, in_flight: asyncio.Semaphore, timeout: float return await async_convert_url_to_base64(url, timeout=timeout) -async def async_convert_urls_to_base64( - remote_urls: tuple[str, ...], timeout: float | httpx.Timeout | None = None -) -> tuple[str, ...]: - in_flight: Final = asyncio.Semaphore(MAX_CONCURRENT_REMOTE_MEDIA_FETCHES) - fetches: Final = tuple(asyncio.create_task(_fetch_data_url(url, in_flight, timeout)) for url in remote_urls) +async def _serves_pdf_within(url: str, in_flight: asyncio.Semaphore) -> bool: + async with in_flight: + return await async_serves_pdf(url) + + +async def _gather_or_cancel_all(fetches: tuple["asyncio.Task[_Fetched]", ...]) -> tuple[_Fetched, ...]: try: return tuple(await asyncio.gather(*fetches)) except BaseException: @@ -322,6 +520,15 @@ async def async_convert_urls_to_base64( raise +async def async_convert_urls_to_base64( + remote_urls: tuple[str, ...], timeout: float | httpx.Timeout | None = None +) -> tuple[str, ...]: + in_flight: Final = asyncio.Semaphore(MAX_CONCURRENT_REMOTE_MEDIA_FETCHES) + return await _gather_or_cancel_all( + tuple(asyncio.create_task(_fetch_data_url(url, in_flight, timeout)) for url in remote_urls) + ) + + def _remote_urls_to_inline( messages: Iterable[AllMessageValues], should_inline: Callable[[RemoteMedia], bool] ) -> tuple[str, ...]: @@ -351,3 +558,27 @@ async def async_inline_remote_media( data_urls: Final = await async_convert_urls_to_base64(remote_urls) inlined: Final = MappingProxyType(dict(zip(remote_urls, data_urls, strict=True))) return [_inline_message(message, inlined, should_inline) for message in messages] + + +def format_pdf_links( + messages: Sequence[AllMessageValues], should_probe: Callable[[RemoteMedia], bool] +) -> tuple[AllMessageValues, ...]: + links: Final = _remote_urls_to_inline(messages, should_probe) + if not links: + return tuple(messages) + with ThreadPoolExecutor(max_workers=min(MAX_CONCURRENT_REMOTE_MEDIA_FETCHES, len(links))) as probes: + verdicts: Final = tuple(probes.map(serves_pdf, links)) + return _with_pdf_formats(messages, zip(links, verdicts, strict=True), should_probe) + + +async def async_format_pdf_links( + messages: Sequence[AllMessageValues], should_probe: Callable[[RemoteMedia], bool] +) -> tuple[AllMessageValues, ...]: + links: Final = _remote_urls_to_inline(messages, should_probe) + if not links: + return tuple(messages) + in_flight: Final = asyncio.Semaphore(MAX_CONCURRENT_REMOTE_MEDIA_FETCHES) + verdicts: Final = await _gather_or_cancel_all( + tuple(asyncio.create_task(_serves_pdf_within(url, in_flight)) for url in links) + ) + return _with_pdf_formats(messages, zip(links, verdicts, strict=True), should_probe) diff --git a/litellm/litellm_core_utils/realtime_streaming.py b/litellm/litellm_core_utils/realtime_streaming.py index 46f5ca87a93..b6af181980e 100644 --- a/litellm/litellm_core_utils/realtime_streaming.py +++ b/litellm/litellm_core_utils/realtime_streaming.py @@ -1,4 +1,6 @@ import asyncio +import base64 +import functools import json import time import traceback @@ -8,7 +10,7 @@ from enum import Enum, auto from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, NoReturn, Protocol, TypeAlias, TypedDict, cast, runtime_checkable -from pydantic import TypeAdapter +from pydantic import TypeAdapter, ValidationError from typing_extensions import ReadOnly import litellm @@ -19,9 +21,12 @@ from litellm.constants import ( REALTIME_LAZY_SETUP_CONTENT_GRACE_SECONDS, REALTIME_LAZY_SETUP_DEADLINE_SECONDS, REALTIME_METERED_USAGE_KEY, + REALTIME_SESSION_ENDED_ABNORMALLY_KEY, REALTIME_SESSION_FAILURE_LOGGED_KEY, REALTIME_SESSION_SUCCESS_LOGGED_KEY, ) +from litellm.litellm_core_utils.audio_utils.utils import normalized_audio_duration_seconds +from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER from litellm.llms.base_llm.realtime.transcription_protocol import RealtimeTranscriptionProtocolError from litellm.llms.base_llm.realtime.transformation import ( @@ -35,6 +40,8 @@ from litellm.types.llms.openai import ( OpenAIRealtimeResponseDelta, OpenAIRealtimeStreamResponseBaseObject, OpenAIRealtimeStreamSessionEvents, + OpenAIRealtimeTranslationClosedEvent, + OpenAIRealtimeTranslationDurationUsage, ) from litellm.types.realtime import ALL_DELTA_TYPES @@ -42,9 +49,11 @@ from .litellm_logging import Logging as LiteLLMLogging from .realtime_errors import client_close_code, realtime_error_event, websocket_close_reason if TYPE_CHECKING: + from openai.types.realtime.realtime_audio_formats import RealtimeAudioFormats from websockets.asyncio.client import ClientConnection from websockets.exceptions import ConnectionClosed + from litellm.integrations.custom_guardrail import CustomGuardrail from litellm.types.guardrails import GuardrailEventHooks CLIENT_CONNECTION_CLASS = ClientConnection @@ -57,6 +66,10 @@ class BackendClose: code: int reason: str + @property + def ended_cleanly(self) -> bool: + return self.code == 1000 + @property def message(self) -> str: if not self.reason: @@ -67,6 +80,7 @@ class BackendClose: class ClientLoopExit(Enum): CLIENT_DISCONNECTED = auto() BACKEND_CLOSED = auto() + RELAY_FAILED = auto() def backend_close_from(error: "ConnectionClosed") -> BackendClose: @@ -96,6 +110,7 @@ class _ClientEventFrame(TypedDict, total=False): type: ReadOnly[str] item: ReadOnly[_ClientEventItem] session: ReadOnly[Mapping[str, object]] + response: ReadOnly[Mapping[str, object]] class _ResponseDoneBody(TypedDict, total=False): @@ -212,6 +227,87 @@ def _mapping_field(container: Mapping[str, object], key: str) -> Mapping[str, ob return _json_object(container.get(key)) +_BETA_AUDIO_FORMAT_BY_GA_TYPE: Final[Mapping[str, str]] = MappingProxyType( + {"audio/pcm": "pcm16", "audio/pcmu": "g711_ulaw", "audio/pcma": "g711_alaw"} +) +_GA_TO_BETA_TOP_LEVEL_SESSION_FIELDS: Final[Mapping[str, str]] = MappingProxyType( + {"output_modalities": "modalities", "max_output_tokens": "max_response_output_tokens"} +) +_GA_TO_BETA_AUDIO_INPUT_FIELDS: Final[Mapping[str, str]] = MappingProxyType( + { + "format": "input_audio_format", + "transcription": "input_audio_transcription", + "noise_reduction": "input_audio_noise_reduction", + "turn_detection": "turn_detection", + } +) +_GA_TO_BETA_AUDIO_OUTPUT_FIELDS: Final[Mapping[str, str]] = MappingProxyType( + {"format": "output_audio_format", "voice": "voice", "speed": "speed"} +) +_GA_ONLY_SESSION_FIELDS: Final = frozenset(("type", "audio", *_GA_TO_BETA_TOP_LEVEL_SESSION_FIELDS)) + + +def _beta_session_value(ga_field: str, value: object) -> object: + if ga_field == "output_modalities": + return ["audio", "text"] if value == ["audio"] else value + if ga_field != "format": + return value + ga_format: Final = _json_object(value) + format_type: Final = None if ga_format is None else ga_format.get("type") + return _BETA_AUDIO_FORMAT_BY_GA_TYPE.get(format_type, value) if isinstance(format_type, str) else value + + +def _beta_session_fields(ga_fields: Mapping[str, object], beta_names: Mapping[str, str]) -> Mapping[str, object]: + return { + beta_names[name]: _beta_session_value(name, value) for name, value in ga_fields.items() if name in beta_names + } + + +def ga_session_to_beta(session: Mapping[str, object]) -> Mapping[str, object]: + audio: Final = _mapping_field(session, "audio") or _EMPTY_SESSION + return { + **{key: value for key, value in session.items() if key not in _GA_ONLY_SESSION_FIELDS}, + **_beta_session_fields(session, _GA_TO_BETA_TOP_LEVEL_SESSION_FIELDS), + **_beta_session_fields(_mapping_field(audio, "input") or _EMPTY_SESSION, _GA_TO_BETA_AUDIO_INPUT_FIELDS), + **_beta_session_fields(_mapping_field(audio, "output") or _EMPTY_SESSION, _GA_TO_BETA_AUDIO_OUTPUT_FIELDS), + } + + +_GA_ONLY_RESPONSE_FIELDS: Final = frozenset(("audio", "output_modalities")) +_GA_TO_BETA_RESPONSE_FIELDS: Final[Mapping[str, str]] = MappingProxyType({"output_modalities": "modalities"}) + + +def ga_response_to_beta(response: Mapping[str, object]) -> Mapping[str, object]: + audio: Final = _mapping_field(response, "audio") or _EMPTY_SESSION + return { + **{key: value for key, value in response.items() if key not in _GA_ONLY_RESPONSE_FIELDS}, + **_beta_session_fields(response, _GA_TO_BETA_RESPONSE_FIELDS), + **_beta_session_fields(_mapping_field(audio, "output") or _EMPTY_SESSION, _GA_TO_BETA_AUDIO_OUTPUT_FIELDS), + } + + +_JSON_ARRAY: Final = TypeAdapter(tuple[object, ...]) +_GA_ASSISTANT_CONTENT_TYPE_BY_BETA_TYPE: Final[Mapping[str, str]] = MappingProxyType( + {"text": "output_text", "audio": "output_audio"} +) + + +def _ga_assistant_content_block(block: object) -> object: + content_block: Final = _json_object(block) + block_type: Final = None if content_block is None else content_block.get("type") + if content_block is None or not isinstance(block_type, str): + return block + ga_type: Final = _GA_ASSISTANT_CONTENT_TYPE_BY_BETA_TYPE.get(block_type) + return block if ga_type is None else {**content_block, "type": ga_type} + + +def beta_item_to_ga(item: Mapping[str, object]) -> Mapping[str, object]: + content: Final = item.get("content") + if item.get("role") != "assistant" or not isinstance(content, list): + return item + return {**item, "content": [_ga_assistant_content_block(block) for block in _JSON_ARRAY.validate_python(content)]} + + def _guardrail_event_id() -> str: return f"{_GUARDRAIL_EVENT_ID_PREFIX}{uuid.uuid4().hex}" @@ -270,6 +366,26 @@ def _gate_session_update( return {**client_session, "turn_detection": gate(None)} +@functools.cache +def _translation_audio_format_adapter() -> "TypeAdapter[str | RealtimeAudioFormats | None]": + from openai.types.realtime.realtime_audio_formats import RealtimeAudioFormats + + return TypeAdapter(str | RealtimeAudioFormats | None) + + +def _translation_audio_bytes_per_second(audio_format: "str | RealtimeAudioFormats | None") -> float | None: + from openai.types.realtime.realtime_audio_formats import AudioPCM, AudioPCMA, AudioPCMU + + match audio_format: + case "pcm16" | AudioPCM(): + return 48000.0 + case "g711_ulaw" | "g711_alaw" | AudioPCMU() | AudioPCMA(): + return 8000.0 + case _: + pass + return None + + class RealtimeEventNormalizer(Protocol): def should_drop(self, event: object) -> bool: ... def normalize(self, event: dict) -> dict: ... @@ -294,6 +410,79 @@ DefaultLoggedRealTimeEventTypes: Final = [ ] +TRANSLATION_GUARDRAILS_UNSUPPORTED_MESSAGE: Final = "Translation sessions cannot enforce configured realtime guardrails" + + +def _guardrails_run_for_event_hooks( + request_data: Mapping[str, object], + event_hooks: Sequence["GuardrailEventHooks"], + callbacks: Sequence[object], +) -> bool: + from litellm.integrations.custom_guardrail import CustomGuardrail + + return any( + isinstance(cb, CustomGuardrail) + and any(cb.should_run_guardrail(data={**request_data, "stream": True}, event_type=et) for et in event_hooks) + for cb in callbacks + ) + + +def _opted_out_of_always_on_guardrail(callback: object, request_data: Mapping[str, object]) -> bool: + from litellm.integrations.custom_guardrail import CustomGuardrail + + return ( + isinstance(callback, CustomGuardrail) + and callback.event_hook is None + and callback.get_disable_global_guardrail(dict(request_data)) is True + ) + + +def _realtime_runner_guardrail( + callback: object, + check_data: Mapping[str, object], + event_hooks: Sequence["GuardrailEventHooks"], +) -> "CustomGuardrail | None": + from litellm.integrations.custom_guardrail import CustomGuardrail + + if not isinstance(callback, CustomGuardrail) or callback.use_native_lifecycle_hooks: + return None + runs: Final = any( + callback.should_run_guardrail(data=check_data, event_type=event_hook) for event_hook in event_hooks + ) + return callback if runs else None + + +def translation_guardrails_apply(request_data: Mapping[str, object]) -> bool: + from litellm.types.guardrails import GuardrailEventHooks + + callbacks: Final = tuple( + callback for callback in litellm.callbacks if not _opted_out_of_always_on_guardrail(callback, request_data) + ) + if _guardrails_run_for_event_hooks(request_data, (GuardrailEventHooks.post_call,), callbacks): + return True + if any( + isinstance(bucket, Mapping) and "_guardrail_pipelines" in bucket + for bucket in (request_data.get("metadata"), request_data.get("litellm_metadata")) + ): + from litellm.proxy.utils import pipeline_managed_guardrail_names + + if pipeline_managed_guardrail_names(request_data, "pre_call") or pipeline_managed_guardrail_names( + request_data, "post_call" + ): + return True + return realtime_guardrails_apply(request_data, callbacks) + + +def realtime_guardrails_apply(request_data: Mapping[str, object], callbacks: Sequence[object]) -> bool: + from litellm.types.guardrails import GuardrailEventHooks + + check_data: Final = {**request_data, "stream": True} + runner_event_hooks: Final = (GuardrailEventHooks.realtime_input_transcription, GuardrailEventHooks.pre_call) + return any( + _realtime_runner_guardrail(callback, check_data, runner_event_hooks) is not None for callback in callbacks + ) + + class RealTimeStreaming: def __init__( self, @@ -303,12 +492,15 @@ class RealTimeStreaming: provider_config: BaseRealtimeConfig | None = None, model: str = "", user_api_key_dict: object | None = None, - request_data: dict | None = None, + request_data: Mapping[str, object] | None = None, backend_uses_beta_protocol: bool | None = None, force_transcription_model: str | None = None, event_normalizer: RealtimeEventNormalizer | None = None, usage_meter: RealtimeUsageMeter | None = None, logging_worker: _LoggingWorker = GLOBAL_LOGGING_WORKER, + translation_session: bool = False, + bridges_beta_client_to_ga: bool = False, + drop_params: bool = False, lazy_setup_deadline_seconds: float = REALTIME_LAZY_SETUP_DEADLINE_SECONDS, lazy_setup_content_grace_seconds: float = REALTIME_LAZY_SETUP_CONTENT_GRACE_SECONDS, clock: Callable[[], float] = time.monotonic, @@ -326,14 +518,24 @@ class RealTimeStreaming: self._logging_worker = logging_worker self.messages: list[OpenAIRealtimeEvents] = [] self._backend_sent_frames: bool = False + self._backend_sent_non_error_frames: bool = False self.input_message: dict = {} self.input_messages: list[dict[str, str]] = [] self.session_tools: list[dict] = [] self.tool_calls: list[dict] = [] + self._is_translation_session = translation_session + self._bridges_beta_client_to_ga: Final = bridges_beta_client_to_ga + self._remaps_all_beta_fields_to_ga: Final = bridges_beta_client_to_ga or translation_session + self._drop_params: Final = drop_params + self._translation_input_seconds = 0.0 + self._translation_input_bytes_per_second = 48000.0 + self._translation_output_seconds = 0.0 + self._translation_output_bytes_per_second = 48000.0 + self._translation_usage_finalized = False # Detect whether the client is explicitly opting into the beta protocol. self._client_wants_beta = self.detect_beta_header(websocket) - self._backend_uses_beta_protocol = ( + self._backend_uses_beta_protocol = not translation_session and ( self._client_wants_beta if backend_uses_beta_protocol is None else backend_uses_beta_protocol ) @@ -352,7 +554,7 @@ class RealTimeStreaming: self.current_delta_type: ALL_DELTA_TYPES | None = None self.session_configuration_request: str | None = None self.user_api_key_dict = user_api_key_dict - self.request_data: dict = request_data or {} + self.request_data: Mapping[str, object] = request_data or {} # Violation counter for end_session_after_n_fails support self._violation_count: int = 0 # When a text message is blocked, hold the guardrail reason so the next @@ -384,6 +586,7 @@ class RealTimeStreaming: # their input_audio_transcription.completed usage drives duration-based cost. self._force_transcription_model = force_transcription_model self._is_transcription_session: bool = force_transcription_model is not None + self._bound_nested_transcription_model: str | None = None # Optional per-provider GA event normalizer (e.g. XAIRealtimeNormalizer). self._event_normalizer = event_normalizer self._gate_turn_detection: Final[_TurnDetectionGate] = ( @@ -407,6 +610,7 @@ class RealTimeStreaming: _MAX_BUFFERED_BYTES: int = 10 * 1024 * 1024 # 10 MB _SESSION_EVENT_TYPES = frozenset(["session.created", "session.updated"]) + _RESPONSE_EVENT_TYPES: Final = frozenset(("response.created", "response.done")) _CLIENT_AUDIO_BUFFER_TYPES = frozenset( [ "input_audio_buffer.append", @@ -429,8 +633,8 @@ class RealTimeStreaming: _DEFERRED_SETUP_HELD_CONTENT_TYPES: Final = frozenset(["conversation.item.create"]) _AUDIO_FORMAT_MAP: dict[str, dict[str, str | int]] = { "pcm16": {"type": "audio/pcm", "rate": 24000}, - "g711_ulaw": {"type": "audio/G711-ulaw", "rate": 8000}, - "g711_alaw": {"type": "audio/G711-alaw", "rate": 8000}, + "g711_ulaw": {"type": "audio/pcmu"}, + "g711_alaw": {"type": "audio/pcma"}, } # GA name → beta name (when client WebSocket includes OpenAI-Beta: realtime=v1) _GA_TO_BETA_EVENT_TYPES: dict[str, str] = { @@ -449,12 +653,12 @@ class RealTimeStreaming: def _should_store_message( self, - message_obj: dict | OpenAIRealtimeEvents, + message_obj: Mapping[str, object], ) -> bool: _msg_type: Final = message_obj["type"] if "type" in message_obj else None if self.logged_real_time_event_types == "*": return True - if _msg_type and _msg_type in self.logged_real_time_event_types: + if isinstance(_msg_type, str) and _msg_type in self.logged_real_time_event_types: return True return False @@ -555,7 +759,7 @@ class RealTimeStreaming: input_messages, so it is not duplicated into the response log here. """ try: - usage: Final = event_obj.get("usage") + usage: Final = as_str_mapping(event_obj.get("usage")) if usage is None: return # If this event type is already captured by store_message (e.g. the user @@ -623,6 +827,7 @@ class RealTimeStreaming: async def log_messages(self): """Log messages in list""" + self._finalize_translation_usage() if self.logging_obj: if self._usage_meter is not None: self.logging_obj.model_call_details[REALTIME_METERED_USAGE_KEY] = self._usage_meter.snapshot() @@ -631,8 +836,6 @@ class RealTimeStreaming: if self.session_tools or self.tool_calls: self.logging_obj.model_call_details["realtime_tools"] = self.session_tools self.logging_obj.model_call_details["realtime_tool_calls"] = self.tool_calls - if LiteLLMLogging.usage_capture_callback is not None: - self.logging_obj.capture_usage_before_logging(self.messages) # Route through the bounded logging worker (per-coroutine timeout + # concurrency cap) instead of a bare create_task, so a slow callback # can't leave suspended tasks pinning each call's response in memory. @@ -641,6 +844,142 @@ class RealTimeStreaming: ) self.logging_obj.model_call_details[REALTIME_SESSION_SUCCESS_LOGGED_KEY] = True + def _capture_translation_output_audio(self, event_obj: Mapping[str, object]) -> None: + if not self._is_translation_session: + return + if event_obj.get("type") == "session.closed": + usage: Final = as_str_mapping(event_obj.get("usage")) + output_seconds: Final = ( + normalized_audio_duration_seconds(usage.get("output_seconds")) if usage is not None else None + ) + reported_input_seconds: Final = ( + normalized_audio_duration_seconds(usage.get("input_seconds")) if usage is not None else None + ) + input_seconds: Final = ( + reported_input_seconds + if reported_input_seconds is not None + else self._translation_input_seconds or None + ) + synthetic_output_seconds: Final = self._translation_output_seconds or None + resolved_output_seconds: Final = output_seconds if output_seconds is not None else synthetic_output_seconds + if input_seconds is not None or resolved_output_seconds is not None: + if self._should_store_message(event_obj): + supplemental_usage: Final = OpenAIRealtimeTranslationDurationUsage( + type="duration", + input_seconds=float(input_seconds or 0.0) if reported_input_seconds is None else 0.0, + output_seconds=float(synthetic_output_seconds or 0.0) if output_seconds is None else 0.0, + ) + if ( + supplemental_usage.get("input_seconds", 0.0) > 0 + or supplemental_usage.get("output_seconds", 0.0) > 0 + ): + self.messages.append( + OpenAIRealtimeTranslationClosedEvent( + type="session.closed", + usage=supplemental_usage, + ) + ) + else: + normalized_usage: Final = ( + OpenAIRealtimeTranslationDurationUsage( + type="duration", + input_seconds=input_seconds, + output_seconds=float(resolved_output_seconds or 0.0), + ) + if input_seconds is not None + else OpenAIRealtimeTranslationDurationUsage( + type="duration", output_seconds=float(resolved_output_seconds or 0.0) + ) + ) + self.messages.append( + OpenAIRealtimeTranslationClosedEvent(type="session.closed", usage=normalized_usage) + ) + self._translation_usage_finalized = True + return + self._capture_translation_audio_formats(event_obj) + if event_obj.get("type") not in ( + "session.output_audio.delta", + "response.output_audio.delta", + "response.audio.delta", + ): + return + delta: Final = event_obj.get("delta") + if not isinstance(delta, str): + return + try: + decoded: Final = base64.b64decode(delta, validate=True) + except (ValueError, TypeError): + return + self._translation_output_seconds += len(decoded) / self._translation_output_bytes_per_second + + def _capture_translation_input_audio(self, message: str) -> None: + if not self._is_translation_session: + return + try: + event: Final = _decode_json_object(message) + except (json.JSONDecodeError, TypeError): + return + if event.get("type") != "session.input_audio_buffer.append" or not isinstance(audio := event.get("audio"), str): + return + try: + decoded: Final = base64.b64decode(audio, validate=True) + except (ValueError, TypeError): + return + self._translation_input_seconds += len(decoded) / self._translation_input_bytes_per_second + + def _capture_translation_audio_formats(self, event_obj: Mapping[str, object]) -> None: + if event_obj.get("type") not in ("session.created", "session.updated"): + return + session: Final = as_str_mapping(event_obj.get("session")) + if session is None: + return + audio: Final = as_str_mapping(session.get("audio")) + if audio is None: + return + for direction, raw_configuration in (("input", audio.get("input")), ("output", audio.get("output"))): + if (configuration := as_str_mapping(raw_configuration)) is None: + continue + try: + if ( + bytes_per_second := _translation_audio_bytes_per_second( + _translation_audio_format_adapter().validate_python(configuration.get("format")) + ) + ) is None: + continue + except ValidationError: + continue + if direction == "input": + self._translation_input_bytes_per_second = bytes_per_second + else: + self._translation_output_bytes_per_second = bytes_per_second + + def _finalize_translation_usage(self) -> None: + if self._translation_usage_finalized: + return + for event in self.messages: + if event.get("type") != "session.closed": + continue + if (event_usage := as_str_mapping(event.get("usage"))) is not None and normalized_audio_duration_seconds( + event_usage.get("output_seconds") + ) is not None: + self._translation_usage_finalized = True + return + if self._translation_output_seconds == 0 and self._translation_input_seconds == 0: + return + synthetic_usage: Final = ( + OpenAIRealtimeTranslationDurationUsage( + type="duration", + input_seconds=self._translation_input_seconds, + output_seconds=self._translation_output_seconds, + ) + if self._translation_input_seconds > 0 + else OpenAIRealtimeTranslationDurationUsage( + type="duration", output_seconds=self._translation_output_seconds + ) + ) + self.messages.append(OpenAIRealtimeTranslationClosedEvent(type="session.closed", usage=synthetic_usage)) + self._translation_usage_finalized = True + async def _send_to_backend(self, message: str) -> bool: """Send a message to the backend WebSocket. @@ -653,10 +992,25 @@ class RealTimeStreaming: backend, False if the provider transformation produced no output and the message was effectively dropped. """ - message = self._enforce_transcription_session_model(message) + from litellm.proxy._types import ProxyException + + try: + authorized_message: Final = await self._apply_nested_transcription_model_policy(message) + except ProxyException as denied: + denial_message: Final = redact_internal_details_from_client_message(denied.message) + try: + await self.websocket.send_text(realtime_error_event(denial_message, error_type="permission_error")) + finally: + await self.websocket.close( + code=1008, + reason=websocket_close_reason( + denial_message, fallback="Nested transcription model is not authorized" + ), + ) + return False if self.provider_config: transformed: Final = self.provider_config.transform_realtime_request( - message, self.model, self.session_configuration_request + authorized_message, self.model, self.session_configuration_request ) sent = False for msg in transformed: @@ -691,14 +1045,94 @@ class RealTimeStreaming: if is_content_message: self._content_sent_after_setup = True sent = True + if sent: + self._capture_translation_input_audio(authorized_message) return sent - await self.backend_ws.send(message) + await self.backend_ws.send(authorized_message) if self._usage_meter is not None: - sent_event: Final = self._parse_backend_event(message) + sent_event: Final = self._parse_backend_event(authorized_message) if sent_event is not None: self._usage_meter.observe_client_event(sent_event) + self._capture_translation_input_audio(authorized_message) return True + async def _apply_nested_transcription_model_policy(self, message: str) -> str: + if self._force_transcription_model is not None: + return self._enforce_transcription_session_model(message) + if self._is_translation_session: + return await self._enforce_translation_nested_transcription_model(message) + return message + + def _session_update_message_obj(self, message: str) -> Mapping[str, object] | None: + try: + message_obj: Final = _decode_json_object(message) + except (json.JSONDecodeError, TypeError): + return None + if message_obj.get("type") not in ( + "session.update", + "transcription_session.update", + ): + return None + return message_obj + + def _nested_transcription_models_from_session( + self, + session: Mapping[str, object], + ) -> tuple[str, ...]: + audio: Final = as_str_mapping(session.get("audio")) + audio_input: Final = as_str_mapping(audio.get("input")) if audio is not None else None + nested_transcription: Final = audio_input.get("transcription") if audio_input is not None else None + nested_model: Final = self._transcription_model_value(nested_transcription) + flat_model: Final = self._transcription_model_value(session.get("input_audio_transcription")) + return tuple(dict.fromkeys(model for model in (nested_model, flat_model) if model is not None)) + + def _transcription_model_value(self, transcription_config: object) -> str | None: + if (fields := as_str_mapping(transcription_config)) is None: + return None + model: Final = fields.get("model") + if isinstance(model, str) and model: + return model + return None + + def _rewrite_session_update_transcription_model(self, message: str, authorized_model: str) -> str: + message_obj: Final = self._session_update_message_obj(message) + if message_obj is None: + return message + session: Final = as_str_mapping(message_obj.get("session")) + if session is None: + return message + transcription: Final = as_str_mapping(session.get("input_audio_transcription")) + rewrite_flat: Final = transcription is not None and transcription.get("model") != authorized_model + audio: Final = as_str_mapping(session.get("audio")) + audio_input: Final = as_str_mapping(audio.get("input")) if audio is not None else None + nested_transcription: Final = ( + as_str_mapping(audio_input.get("transcription")) if audio_input is not None else None + ) + rewrite_nested: Final = ( + nested_transcription is not None and nested_transcription.get("model") != authorized_model + ) + if not rewrite_flat and not rewrite_nested: + return message + updated_session: Final = { + **session, + **( + {"input_audio_transcription": {**transcription, "model": authorized_model}} + if transcription is not None and rewrite_flat + else {} + ), + **( + { + "audio": { + **audio, + "input": {**audio_input, "transcription": {**nested_transcription, "model": authorized_model}}, + } + } + if audio is not None and audio_input is not None and nested_transcription is not None and rewrite_nested + else {} + ), + } + return json.dumps({**message_obj, "session": updated_session}) + def _builds_setup_lazily(self) -> bool: if self.provider_config is None: return False @@ -877,56 +1311,52 @@ class RealTimeStreaming: if self._force_transcription_model is None: return message - try: - message_obj: Final = _decode_json_object(message) - except (json.JSONDecodeError, TypeError): + message_obj: Final = self._session_update_message_obj(message) + if message_obj is None: return message - - if message_obj.get("type") not in ( - "session.update", - "transcription_session.update", - ): - return message - - session: Final = message_obj.get("session") - if not isinstance(session, dict): - return message - - if session.get("type") == "transcription": + session: Final = as_str_mapping(message_obj.get("session")) + if session is not None and session.get("type") == "transcription": self._is_transcription_session = True + return self._rewrite_session_update_transcription_model(message, self._force_transcription_model) - authorized_model: Final = self._force_transcription_model - changed = False + async def _enforce_translation_nested_transcription_model(self, message: str) -> str: + message_obj: Final = self._session_update_message_obj(message) + session: Final = as_str_mapping(message_obj.get("session")) if message_obj is not None else None + bound_model: Final = self._bound_nested_transcription_model + requested_models: Final = ( + tuple(model for model in self._nested_transcription_models_from_session(session) if model != bound_model) + if session is not None + else () + ) + if not requested_models: + return ( + message + if bound_model is None + else self._rewrite_session_update_transcription_model(message, bound_model) + ) - transcription: Final = session.get("input_audio_transcription") - if isinstance(transcription, dict) and transcription.get("model") != authorized_model: - session["input_audio_transcription"] = { - **transcription, - "model": authorized_model, - } - changed = True + valid_token: Final = self.user_api_key_dict - audio: Final = session.get("audio") - if isinstance(audio, dict): - audio_input: Final = audio.get("input") - if isinstance(audio_input, dict): - nested_transcription: Final = audio_input.get("transcription") - if isinstance(nested_transcription, dict) and nested_transcription.get("model") != authorized_model: - session["audio"] = { - **audio, - "input": { - **audio_input, - "transcription": { - **nested_transcription, - "model": authorized_model, - }, - }, - } - changed = True + from litellm.proxy._types import UserAPIKeyAuth + from litellm.proxy.auth.auth_checks import can_key_call_resolved_model + from litellm.proxy.proxy_server import llm_model_list, llm_router + from litellm.proxy.realtime_endpoints.endpoints import nested_transcription_upstream_model - if not changed: + if not isinstance(valid_token, UserAPIKeyAuth): return message - return json.dumps(message_obj) + + for requested_model in requested_models: + await can_key_call_resolved_model( + model=requested_model, + valid_token=valid_token, + llm_model_list=llm_model_list, + llm_router=llm_router, + ) + upstream_model: Final = nested_transcription_upstream_model( + requested_models[0], valid_token.team_id, llm_router + ) + self._bound_nested_transcription_model = upstream_model + return self._rewrite_session_update_transcription_model(message, upstream_model) def _uses_deferred_backend_setup(self) -> bool: """True when setup is deferred until the client's first session.update.""" @@ -1047,7 +1477,19 @@ class RealTimeStreaming: return event def _event_to_client_json(self, event: dict) -> str: - return json.dumps(self._normalize_event_for_ga_client(event)) + return json.dumps(self._session_event_for_client(self._normalize_event_for_ga_client(event))) + + def _session_event_for_client(self, event: Mapping[str, object]) -> Mapping[str, object]: + if not self._bridges_beta_client_to_ga: + return event + event_type: Final = event.get("type") + if event_type in self._SESSION_EVENT_TYPES: + session: Final = _mapping_field(event, "session") + return event if session is None else {**event, "session": ga_session_to_beta(session)} + if event_type in self._RESPONSE_EVENT_TYPES: + response: Final = _mapping_field(event, "response") + return event if response is None else {**event, "response": ga_response_to_beta(response)} + return event async def _send_event_to_client(self, event: object, event_str: str) -> bool: if self._should_drop_event_from_client(event): @@ -1060,7 +1502,7 @@ class RealTimeStreaming: translated: Final = self._translate_event_to_beta(event) if translated is None: return False - await self.websocket.send_text(json.dumps(translated)) + await self.websocket.send_text(json.dumps(self._session_event_for_client(translated))) return True except Exception as e: verbose_logger.warning( @@ -1183,32 +1625,7 @@ class RealTimeStreaming: self, event_hooks: Sequence["GuardrailEventHooks"], ) -> bool: - """Return True if any callback would run for one of ``event_hooks``.""" - from litellm.integrations.custom_guardrail import CustomGuardrail - - return any( - isinstance(cb, CustomGuardrail) - and any( - cb.should_run_guardrail( - data={**self.request_data, "stream": True}, - event_type=et, - ) - for et in event_hooks - ) - for cb in litellm.callbacks - ) - - def _has_realtime_guardrails(self) -> bool: - """Return True if any callback is registered for realtime guardrail event types.""" - from litellm.types.guardrails import GuardrailEventHooks - - return self._has_realtime_guardrails_for_event_hooks( - [ - GuardrailEventHooks.realtime_input_transcription, - GuardrailEventHooks.pre_call, - GuardrailEventHooks.post_call, - ] - ) + return _guardrails_run_for_event_hooks(self.request_data, event_hooks, litellm.callbacks) def _has_audio_transcription_guardrails(self) -> bool: """Return True when a guardrail is configured for the audio/VAD transcript path. @@ -1222,8 +1639,12 @@ class RealTimeStreaming: return self._has_realtime_guardrails_for_event_hooks([GuardrailEventHooks.realtime_input_transcription]) def _should_disable_vad_auto_response(self) -> bool: - """Transcription-only sessions have no assistant turn to gate and reject realtime session updates.""" - return not self._is_transcription_session and self._has_audio_transcription_guardrails() + """Transcription and translation sessions have no assistant turn to gate and reject realtime session updates.""" + return ( + not self._is_transcription_session + and not self._is_translation_session + and self._has_audio_transcription_guardrails() + ) def _refuses_unscreened_audio(self, msg_type: str | None) -> bool: return ( @@ -1264,7 +1685,6 @@ class RealTimeStreaming: transcript completion uses ``realtime_input_transcription`` only; typed user messages and tool outputs use ``pre_call``. """ - from litellm.integrations.custom_guardrail import CustomGuardrail from litellm.types.guardrails import GuardrailEventHooks if event_hooks is None: @@ -1273,14 +1693,11 @@ class RealTimeStreaming: _check_data: Final = {**self.request_data, "transcript": transcript, "stream": True} _already_run: Final[set] = set() - for callback in litellm.callbacks: - if not isinstance(callback, CustomGuardrail): - continue - if callback.use_native_lifecycle_hooks: - continue - if id(callback) in _already_run: - continue - if not any(callback.should_run_guardrail(data=_check_data, event_type=et) for et in _realtime_event_types): + runner_guardrails: Final = ( + _realtime_runner_guardrail(callback, _check_data, _realtime_event_types) for callback in litellm.callbacks + ) + for callback in runner_guardrails: + if callback is None or id(callback) in _already_run: continue _already_run.add(id(callback)) try: @@ -1369,7 +1786,10 @@ class RealTimeStreaming: async def _handle_provider_config_message(self, raw_response: str) -> None: """Process a backend message when a provider_config is set (transformed path).""" - returned_object: Final = self.provider_config.transform_realtime_response( + provider_config: Final = self.provider_config + if provider_config is None: + raise RuntimeError("Provider response handling requires a provider configuration") + returned_object: Final = provider_config.transform_realtime_response( raw_response, self.model, self.logging_obj, @@ -1398,6 +1818,7 @@ class RealTimeStreaming: continue if isinstance(event, dict): self._detect_transcription_session_from_backend(event) + self._capture_translation_output_audio(event) is_session_created_event = isinstance(event, dict) and event.get("type") == "session.created" if is_session_created_event: if self._uses_deferred_backend_setup() and not self._backend_setup_complete: @@ -1514,6 +1935,7 @@ class RealTimeStreaming: continue if self.provider_config: + self._backend_sent_non_error_frames = True try: await self._handle_provider_config_message(raw_response) except Exception as e: @@ -1521,6 +1943,8 @@ class RealTimeStreaming: continue else: event = self._parse_backend_event(raw_response) + if event is None or event.get("type") != "error": + self._backend_sent_non_error_frames = True if event is None: await self.websocket.send_text(raw_response) continue @@ -1535,6 +1959,7 @@ class RealTimeStreaming: verbose_logger.debug("Realtime: not forwarding an error caused by a guardrail event: %s", event) continue + self._capture_translation_output_audio(event) if await self._handle_raw_backend_message(event, raw_response): continue @@ -1548,7 +1973,7 @@ class RealTimeStreaming: translated = self._translate_event_to_beta(event) if translated is None: continue - await self.websocket.send_text(json.dumps(translated)) + await self.websocket.send_text(json.dumps(self._session_event_for_client(translated))) async def backend_to_client_send_messages(self) -> BackendClose: import websockets @@ -1573,8 +1998,8 @@ class RealTimeStreaming: def _backend_refused_session(self, close: BackendClose) -> bool: return ( - close.code != 1000 - and not self._backend_sent_frames + not self._backend_sent_non_error_frames + and (close.code != 1000 or self._backend_sent_frames) and not self._holds_session_updates_until_first_content() ) @@ -1617,7 +2042,7 @@ class RealTimeStreaming: _detect_beta_header = detect_beta_header @staticmethod - def _remap_beta_session_to_ga(session: dict) -> dict: + def _remap_beta_session_to_ga(session: dict, all_beta_fields: bool = False, drop_temperature: bool = False) -> dict: """ Convert a beta-style session.update payload to the GA nested schema. @@ -1630,6 +2055,11 @@ class RealTimeStreaming: session.output_audio_format → session.audio.output.format (with type/rate) session.turn_detection → session.audio.input.turn_detection session.input_audio_transcription → session.audio.input.transcription + Only with all_beta_fields: + session.input_audio_noise_reduction → session.audio.input.noise_reduction + session.speed → session.audio.output.speed + session.max_response_output_tokens → session.max_output_tokens + session.temperature (dropped when drop_temperature) ───────────────────────────────────────────────────────────────────── Fields not in the mapping (instructions, tools, etc.) are passed through. GA clients that already use the nested shape are unaffected. @@ -1681,6 +2111,19 @@ class RealTimeStreaming: if "input_audio_transcription" in session: inp["transcription"] = session.pop("input_audio_transcription") + if all_beta_fields and "input_audio_noise_reduction" in session: + inp["noise_reduction"] = session.pop("input_audio_noise_reduction") + + if all_beta_fields and "speed" in session: + out["speed"] = session.pop("speed") + + if all_beta_fields and "max_response_output_tokens" in session: + max_tokens: Final = session.pop("max_response_output_tokens") + session.setdefault("max_output_tokens", max_tokens) + + if all_beta_fields and drop_temperature: + session.pop("temperature", None) + if inp: audio["input"] = inp if out: @@ -1699,6 +2142,53 @@ class RealTimeStreaming: return session + @staticmethod + def _remap_beta_response_to_ga(response: Mapping[str, object], drop_temperature: bool) -> dict[str, object]: + moved: Final = frozenset( + ("modalities", "voice", "output_audio_format", "max_response_output_tokens") + + (("temperature",) if drop_temperature else ()) + ) + raw_format: Final = response.get("output_audio_format") + output_audio: Final = { + **({} if "voice" not in response else {"voice": response["voice"]}), + **( + {} + if "output_audio_format" not in response + else { + "format": RealTimeStreaming._AUDIO_FORMAT_MAP.get(raw_format, raw_format) + if isinstance(raw_format, str) + else raw_format + } + ), + } + modalities: Final = response.get("modalities") + modality_names: Final = ( + frozenset(m.lower() for m in modalities if isinstance(m, str)) + if isinstance(modalities, list) + else frozenset() + ) + output_modalities: Final = ( + ["audio"] if "audio" in modality_names else ["text"] if "text" in modality_names else None + ) + existing_audio: Final = as_str_mapping(response.get("audio")) or {} + existing_output: Final = as_str_mapping(existing_audio.get("output")) or {} + return { + **{key: value for key, value in response.items() if key not in moved}, + **( + {} + if output_modalities is None or "output_modalities" in response + else {"output_modalities": output_modalities} + ), + **( + {} + if "max_response_output_tokens" not in response or "max_output_tokens" in response + else {"max_output_tokens": response["max_response_output_tokens"]} + ), + **( + {} if not output_audio else {"audio": {**existing_audio, "output": {**existing_output, **output_audio}}} + ), + } + @staticmethod def _translate_event_to_beta(event: dict) -> dict | None: """Translate a single GA event dict to its beta equivalent. @@ -1932,10 +2422,34 @@ class RealTimeStreaming: if msg_type == "session.update" and not self._backend_uses_beta_protocol: session = client_event.get("session", {}) if isinstance(session, dict): - session = self._remap_beta_session_to_ga(session) + session = self._remap_beta_session_to_ga( + session, + all_beta_fields=self._remaps_all_beta_fields_to_ga, + drop_temperature=self._drop_params, + ) + if self._is_translation_session: + session.pop("type", None) msg_obj["session"] = session message = json.dumps(msg_obj) + if ( + msg_type == "response.create" + and self._remaps_all_beta_fields_to_ga + and (beta_response := as_str_mapping(client_event.get("response"))) is not None + ): + msg_obj["response"] = self._remap_beta_response_to_ga( + beta_response, drop_temperature=self._drop_params + ) + message = json.dumps(msg_obj) + + if ( + msg_type == "conversation.item.create" + and self._bridges_beta_client_to_ga + and (beta_item := as_str_mapping(client_event.get("item"))) is not None + ): + msg_obj["item"] = beta_item_to_ga(beta_item) + message = json.dumps(msg_obj) + if msg_type == "session.update" and self._event_normalizer: session = client_event.get("session") if isinstance(session, dict): @@ -2016,16 +2530,28 @@ class RealTimeStreaming: return ClientLoopExit.BACKEND_CLOSED except Exception as e: verbose_logger.debug("Error in client ack messages: %s", e) - return ClientLoopExit.CLIENT_DISCONNECTED + return ClientLoopExit.RELAY_FAILED async def bidirectional_forward(self) -> None: + if self._is_translation_session and translation_guardrails_apply(self.request_data): + await self.websocket.send_text( + realtime_error_event(TRANSLATION_GUARDRAILS_UNSUPPORTED_MESSAGE, error_type="guardrail_error") + ) + await self.websocket.close(code=1008, reason=TRANSLATION_GUARDRAILS_UNSUPPORTED_MESSAGE) + return forward_task: Final = asyncio.create_task(self.backend_to_client_send_messages()) client_task: Final = asyncio.create_task(self.client_ack_messages()) try: await asyncio.wait((forward_task, client_task), return_when=asyncio.FIRST_COMPLETED) - if client_task.done() and client_task.result() is ClientLoopExit.CLIENT_DISCONNECTED: + client_exit: Final = client_task.result() if client_task.done() else None + if client_exit is ClientLoopExit.RELAY_FAILED and self.logging_obj: + self.logging_obj.model_call_details[REALTIME_SESSION_ENDED_ABNORMALLY_KEY] = True + if client_exit in (ClientLoopExit.CLIENT_DISCONNECTED, ClientLoopExit.RELAY_FAILED): return - await self._close_client(await forward_task) + close: Final = await forward_task + if not close.ended_cleanly and self.logging_obj: + self.logging_obj.model_call_details[REALTIME_SESSION_ENDED_ABNORMALLY_KEY] = True + await self._close_client(close) finally: forward_task.cancel() client_task.cancel() @@ -2035,7 +2561,7 @@ class RealTimeStreaming: redacted_message: Final = redact_internal_details_from_client_message(close.message) redacted_reason: Final = redact_internal_details_from_client_message(close.reason) try: - if close.code != 1000: + if not close.ended_cleanly: await self.websocket.send_text(realtime_error_event(redacted_message, error_type="server_error")) await self.websocket.close( code=client_close_code(close.code), diff --git a/litellm/litellm_core_utils/redact_messages.py b/litellm/litellm_core_utils/redact_messages.py index 981859c620b..ac5c0720eff 100644 --- a/litellm/litellm_core_utils/redact_messages.py +++ b/litellm/litellm_core_utils/redact_messages.py @@ -10,7 +10,7 @@ import asyncio import copy import inspect -from collections.abc import Mapping, Sequence +from collections.abc import Iterable, Mapping, Sequence from dataclasses import replace from typing import TYPE_CHECKING, Any, Final @@ -107,7 +107,13 @@ def redacted_response_obj_for_custom_logger(response_obj: object, custom_logger: def _is_redactable_response(response_obj: object) -> bool: return isinstance( - response_obj, (litellm.ModelResponse, litellm.ResponsesAPIResponse, litellm.EmbeddingResponse) + response_obj, + ( + litellm.ModelResponse, + litellm.TextCompletionResponse, + litellm.ResponsesAPIResponse, + litellm.EmbeddingResponse, + ), ) or (isinstance(response_obj, dict) and ("choices" in response_obj or "output" in response_obj)) @@ -171,6 +177,8 @@ def _redact_streaming_response(streaming_response): _redact_bedrock_guardrail_trace(streaming_response) elif isinstance(streaming_response, litellm.ResponsesAPIResponse): return perform_redaction({}, streaming_response) + elif isinstance(streaming_response, litellm.TranscriptionResponse): + streaming_response.text = REDACTED_BY_LITELLM elif hasattr(streaming_response, "output"): _redact_responses_api_output(streaming_response.output) if hasattr(streaming_response, "reasoning") and streaming_response.reasoning is not None: @@ -196,6 +204,9 @@ def _redact_function_call(function_call) -> None: def _redact_choice_content(choice): """Helper to redact content in a choice (message or delta).""" + if isinstance(choice, (litellm.Choices, litellm.utils.StreamingChoices, litellm.utils.TextChoices)): + drop_token_ids(choice) + _redact_provider_specific_fields(choice) if isinstance(choice, litellm.Choices): if choice.message.content is not None: choice.message.content = REDACTED_BY_LITELLM @@ -203,6 +214,7 @@ def _redact_choice_content(choice): choice.message.reasoning_content = REDACTED_BY_LITELLM if hasattr(choice.message, "thinking_blocks"): choice.message.thinking_blocks = None + _drop_field_when_present(choice.message, "reasoning_items") _redact_provider_specific_fields(choice.message) _redact_tool_calls(getattr(choice.message, "tool_calls", None)) _redact_function_call(getattr(choice.message, "function_call", None)) @@ -213,9 +225,14 @@ def _redact_choice_content(choice): choice.delta.reasoning_content = REDACTED_BY_LITELLM if hasattr(choice.delta, "thinking_blocks"): choice.delta.thinking_blocks = None + _drop_field_when_present(choice.delta, "reasoning_items") _redact_provider_specific_fields(choice.delta) _redact_tool_calls(getattr(choice.delta, "tool_calls", None)) _redact_function_call(getattr(choice.delta, "function_call", None)) + elif isinstance(choice, litellm.utils.TextChoices): + _redact_field_when_present(choice, "text") + _redact_field_when_present(choice, "reasoning_content") + _drop_field_when_present(choice, "logprobs") def _as_mapping(value: object) -> Mapping[str, object] | None: @@ -227,14 +244,27 @@ def _redact_provider_specific_fields(message: object) -> None: setattr(message, "provider_specific_fields", _redacted_provider_specific_fields(fields)) # noqa: B010 # typed as object +def _drop_provider_specific_token_ids(holder: object) -> None: + fields: Final = _as_mapping(getattr(holder, "provider_specific_fields", None)) + if fields is not None and fields.get("token_ids") is not None: + setattr(holder, "provider_specific_fields", {**fields, "token_ids": None}) # noqa: B010 # typed as object + + +def drop_token_ids(choice: object) -> None: + if getattr(choice, "token_ids", None) is not None: + setattr(choice, "token_ids", None) # noqa: B010 # pydantic extra, not a declared field + for holder in (choice, getattr(choice, "delta", None), getattr(choice, "message", None)): + _drop_provider_specific_token_ids(holder) + + def _redact_provider_specific_fields_dict(choice: Mapping[str, object]) -> None: - for message in (choice.get("message"), choice.get("delta")): + for holder in (choice, choice.get("message"), choice.get("delta")): if ( - (readable := _as_mapping(message)) is not None + (readable := _as_mapping(holder)) is not None and (fields := _as_mapping(readable.get("provider_specific_fields"))) is not None - and isinstance(message, dict) + and isinstance(holder, dict) ): - message["provider_specific_fields"] = _redacted_provider_specific_fields(fields) + holder["provider_specific_fields"] = _redacted_provider_specific_fields(fields) def _redacted_provider_specific_fields(fields: Mapping[str, object]) -> Mapping[str, object]: @@ -242,15 +272,32 @@ def _redacted_provider_specific_fields(fields: Mapping[str, object]) -> Mapping[ return { **fields, **({"reasoning_content": REDACTED_BY_LITELLM} if fields.get("reasoning_content") is not None else {}), + **({"reasoning": REDACTED_BY_LITELLM} if fields.get("reasoning") is not None else {}), + **({"reasoning_text": REDACTED_BY_LITELLM} if fields.get("reasoning_text") is not None else {}), **{ key: None for key in ( "thinking_blocks", "reasoningContentBlocks", + "reasoningContent", + "annotations", "citations", + "citation", + "citationsContent", "compaction_blocks", "compaction_start", "compaction_delta", + "reasoning_details", + "web_search_calls", + "web_search_results", + "tool_results", + "code_interpreter_results", + "search_results", + "rerank_results", + "executed_tools", + "custom_outputs", + "tool_search_items", + "token_ids", ) if key in fields }, @@ -262,6 +309,11 @@ def _redact_field_when_present(item: object, field: str) -> None: setattr(item, field, REDACTED_BY_LITELLM) +def _drop_field_when_present(item: object, field: str) -> None: + if getattr(item, field, None) is not None: + setattr(item, field, None) + + def _redact_responses_api_output(output_items): """Helper to redact ResponsesAPIResponse output items.""" for output_item in output_items: @@ -418,30 +470,22 @@ def _redact_tool_calls_dict(message: Mapping[str, object]) -> None: function_call["arguments"] = REDACTED_BY_LITELLM -def _redact_model_response_dict_choices(choices, redacted_str: str): +def _redact_model_response_dict_choices(choices: Iterable[object], redacted_str: str) -> None: for choice in choices: if isinstance(choice, dict): _redact_provider_specific_fields_dict(choice) - if "message" in choice and isinstance(choice["message"], dict): - if choice["message"].get("content") is not None: - choice["message"]["content"] = redacted_str - if choice["message"].get("reasoning_content") is not None: - choice["message"]["reasoning_content"] = redacted_str - if "thinking_blocks" in choice["message"]: - choice["message"]["thinking_blocks"] = None - if "audio" in choice["message"]: - choice["message"]["audio"] = None - _redact_tool_calls_dict(choice["message"]) - elif "delta" in choice and isinstance(choice["delta"], dict): - if choice["delta"].get("content") is not None: - choice["delta"]["content"] = redacted_str - if choice["delta"].get("reasoning_content") is not None: - choice["delta"]["reasoning_content"] = redacted_str - if "thinking_blocks" in choice["delta"]: - choice["delta"]["thinking_blocks"] = None - if "audio" in choice["delta"]: - choice["delta"]["audio"] = None - _redact_tool_calls_dict(choice["delta"]) + if choice.get("token_ids") is not None: + choice["token_ids"] = None + if ( + body := next((choice[key] for key in ("message", "delta") if isinstance(choice.get(key), dict)), None) + ) is not None: + for field in ("content", "reasoning_content"): + if body.get(field) is not None: + body[field] = redacted_str + for field in ("thinking_blocks", "reasoning_items", "audio"): + if field in body: + body[field] = None + _redact_tool_calls_dict(body) elif choice.get("text") is not None: choice["text"] = redacted_str else: @@ -564,7 +608,7 @@ def perform_redaction(model_call_details: dict, result, redact_streaming_respons return {"text": REDACTED_BY_LITELLM} _result: Final = copy.deepcopy(result) - if isinstance(_result, litellm.ModelResponse): + if isinstance(_result, (litellm.ModelResponse, litellm.TextCompletionResponse)): if hasattr(_result, "choices") and _result.choices is not None: for choice in _result.choices: _redact_choice_content(choice) diff --git a/litellm/litellm_core_utils/routing_common_utils.py b/litellm/litellm_core_utils/routing_common_utils.py index a06860e7786..62bdc1c10a7 100644 --- a/litellm/litellm_core_utils/routing_common_utils.py +++ b/litellm/litellm_core_utils/routing_common_utils.py @@ -378,7 +378,8 @@ def filter_team_based_models( ids_to_remove: Final = set() if isinstance(healthy_deployments, dict): - return healthy_deployments + # A deployment asked for by id is filtered like any other: another team's is not served. + return [] if _owner_team(healthy_deployments) not in (None, request_team_id) else healthy_deployments # pyright: ignore[reportUnknownArgumentType, reportUnknownVariableType] # the legacy untyped deployment dict for deployment in healthy_deployments: _model_info = deployment.get("model_info") or {} model_team_id = _model_info.get("team_id") @@ -431,6 +432,16 @@ def _deployment_supports_web_search(deployment: dict) -> bool: return True +def is_web_search_request(request_kwargs: Mapping[str, object]) -> bool: + tools: Final[object] = request_kwargs.get("tools") + return isinstance(tools, (list, tuple)) and any( + isinstance(tool, dict) + and isinstance(tool_type := tool.get("type"), str) + and tool_type in _WEB_SEARCH_TOOL_TYPES + for tool in tools + ) + + def filter_web_search_deployments( healthy_deployments: list[dict] | dict, request_kwargs: dict | None = None, @@ -445,14 +456,7 @@ def filter_web_search_deployments( if isinstance(healthy_deployments, dict): return healthy_deployments - tools: Final[object] = request_kwargs.get("tools") - is_web_search_request: Final = isinstance(tools, (list, tuple)) and any( - isinstance(tool, dict) - and isinstance(tool_type := tool.get("type"), str) - and tool_type in _WEB_SEARCH_TOOL_TYPES - for tool in tools - ) - if not is_web_search_request: + if not is_web_search_request(request_kwargs): return healthy_deployments # Filter out deployments that don't support web search @@ -607,3 +611,9 @@ def warn_on_provider_credential_mismatch(model_name: str, litellm_params: Mappin ) verbose_router_logger.warning(warning) return warning + + +def _owner_team(deployment: Mapping[str, object]) -> object: + """The team a deployment belongs to (``model_info.team_id``), or None.""" + model_info: Final = deployment.get("model_info") + return model_info.get("team_id") if isinstance(model_info, Mapping) else None # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # a deployment dict's model_info diff --git a/litellm/litellm_core_utils/stream_usage_chunks.py b/litellm/litellm_core_utils/stream_usage_chunks.py index eda57c7ea12..d073ddc2724 100644 --- a/litellm/litellm_core_utils/stream_usage_chunks.py +++ b/litellm/litellm_core_utils/stream_usage_chunks.py @@ -1,6 +1,7 @@ from collections.abc import Iterable from typing import Final +from litellm.constants import VLLM_CHOICE_FIELDS from litellm.types.utils import ModelResponseStream, StreamingChoices @@ -9,12 +10,19 @@ def is_empty_streaming_choice(choice: StreamingChoices) -> bool: return False if getattr(choice, "logprobs", None) is not None: return False + if not _all_values_none(_vllm_choice_values(choice)): + return False delta: Final = choice.delta if hasattr(choice, "delta") else None if delta is None: return True return _all_values_none(delta.model_dump().values()) +def _vllm_choice_values(choice: StreamingChoices) -> Iterable[object]: + choice_extras: Final = choice.model_extra or {} + return (choice_extras.get(field) for field in VLLM_CHOICE_FIELDS) + + def _all_values_none(values: Iterable[object]) -> bool: return all(value is None for value in values) diff --git a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py index 7191b2ce8e8..c87357122ce 100644 --- a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py +++ b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py @@ -12,6 +12,7 @@ from typing_extensions import ReadOnly, Required import litellm from litellm._logging import verbose_logger +from litellm.constants import VLLM_CHOICE_FIELDS from litellm.litellm_core_utils.core_helpers import ( PROVIDERS_BILLED_FROM_THEIR_OWN_USAGE_FIELDS, UPSTREAM_USAGE_COST, @@ -31,6 +32,7 @@ from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response impo from litellm.litellm_core_utils.prompt_templates.common_utils import ( get_content_from_model_response, # pyright: ignore[reportUnknownVariableType] # response param accepts an untyped dict ) +from litellm.litellm_core_utils.redact_messages import drop_token_ids from litellm.litellm_core_utils.token_counter import usage_tokenizer_model from litellm.types.llms.openai import ( AllMessageValues, @@ -434,6 +436,8 @@ class ChunkProcessor: chunks, unreported="tool_calls" if _carries_tool_calls(chunks) else "stop" ), message={"role": ChunkProcessor._get_role_from_chunks(chunks), "content": ""}, + provider_specific_fields=None, + **_streamed_vllm_choice_fields(chain.from_iterable(chunk.get("choices") or () for chunk in chunks)), ) @staticmethod @@ -504,6 +508,7 @@ class ChunkProcessor: "index": 0, "message": {"role": role, "content": ""}, "finish_reason": finish_reason, + **_streamed_vllm_choice_fields(_first_choices(chunks)), } ] ), @@ -1371,6 +1376,7 @@ def _rebuilt_text_choice(index: int, choices: Sequence[TextChoices]) -> TextChoi index=index, logprobs=_merged_logprobs(choices), finish_reason=next((choice.finish_reason for choice in reversed(choices) if choice.finish_reason), None), + **_streamed_vllm_choice_fields(choices), ) @@ -1504,6 +1510,31 @@ def _field_of(value: object, name: str) -> object: return getattr(value, name, None) +def _first_choices(chunks: Iterable[object]) -> tuple[object, ...]: + return tuple(next(iter(object_items(_field_of(chunk, "choices"))), None) for chunk in chunks) + + +def _choice_extras(choice: object) -> Mapping[str, object]: + if isinstance(choice, BaseModel): + return choice.model_extra or {} + return object_mapping(choice) or {} + + +def _streamed_vllm_choice_fields(choices: Iterable[object]) -> Mapping[str, object]: + extras: Final = tuple(map(_choice_extras, choices)) + token_id_runs: Final = tuple(object_items(fields.get("token_ids")) for fields in extras) + stop_reasons: Final = tuple(reason for fields in extras if (reason := fields.get("stop_reason")) is not None) + has_token_ids: Final = any(fields.get("token_ids") is not None for fields in extras) + streamed_values: Final[Mapping[str, object]] = MappingProxyType( + { + "token_ids": list(chain.from_iterable(token_id_runs)) if has_token_ids else None, + "stop_reason": stop_reasons[-1] if stop_reasons else None, + } + ) + present_fields: Final = frozenset(chain.from_iterable(fields.keys() for fields in extras)) + return MappingProxyType({field: streamed_values[field] for field in VLLM_CHOICE_FIELDS if field in present_fields}) + + def _delta_reasoning_items(delta: object) -> Sequence[object]: items: Final = _field_of(delta, "reasoning_items") return cast(Sequence[object], items) if isinstance(items, list) else () # cast-ok: items forwarded verbatim @@ -1776,6 +1807,19 @@ def stream_chunk_builder( end_time: object = None, logging_obj: Optional["Logging"] = None, count_prompt_tokens: Callable[[], int] | None = None, +) -> ModelResponse | TextCompletionResponse | None: + response: Final = _assembled_stream_response(chunks, messages, logging_obj, count_prompt_tokens) + if response is not None and getattr(logging_obj, "drops_stream_token_ids", False) is True: + for choice in response.choices: + drop_token_ids(choice) + return response + + +def _assembled_stream_response( + chunks: Sequence[object], + messages: Sequence[AllMessageValues | Message] | None, + logging_obj: Optional["Logging"], + count_prompt_tokens: Callable[[], int] | None, ) -> ModelResponse | TextCompletionResponse | None: try: if chunks is None: @@ -1788,7 +1832,7 @@ def stream_chunk_builder( if not chunks: return None - processor: Final = ChunkProcessor(chunks, messages) + processor: Final = ChunkProcessor(list(chunks), messages) chunks = processor.chunks ### BASE-CASE ### diff --git a/litellm/litellm_core_utils/streaming_handler.py b/litellm/litellm_core_utils/streaming_handler.py index 9bb5b761fd5..aa6ce6ea99e 100644 --- a/litellm/litellm_core_utils/streaming_handler.py +++ b/litellm/litellm_core_utils/streaming_handler.py @@ -23,6 +23,7 @@ from typing_extensions import NotRequired, TypedDict import litellm from litellm import verbose_logger from litellm._uuid import uuid +from litellm.constants import STREAM_CHUNK_CHOICE_FIELDS, STREAM_FINISH_CHOICE_FIELDS from litellm.litellm_core_utils.asyncify import asyncify from litellm.litellm_core_utils.core_helpers import ( UPSTREAM_USAGE_COST, @@ -37,10 +38,11 @@ from litellm.litellm_core_utils.hidden_params import ( set_hidden_param, stored_attribute, ) +from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import object_items from litellm.litellm_core_utils.model_response_utils import ( is_model_response_stream_empty, ) -from litellm.litellm_core_utils.redact_messages import LiteLLMLoggingObject +from litellm.litellm_core_utils.redact_messages import LiteLLMLoggingObject, drop_token_ids from litellm.litellm_core_utils.thread_pool_executor import executor from litellm.llms.ollama.common_utils import OllamaResponseIdNormalizer from litellm.types.llms.base import LiteLLMBaseModel @@ -137,6 +139,70 @@ def _prepend_upstream_choice_extras( choice.__pydantic_fields_set__.update(upstream_extras) +_NO_UPSTREAM_CHOICE_FIELDS: Final[Mapping[str, object]] = MappingProxyType({}) +_NO_CHOICE_FIELDS_BY_INDEX: Final[Mapping[int, Mapping[str, object]]] = MappingProxyType({}) + + +def _upstream_first_choice(upstream_chunk: object) -> BaseModel | None: + match getattr(upstream_chunk, "choices", None): + case [BaseModel() as first_choice, *_]: + return first_choice + case _: + return None + + +def _upstream_choice_fields(upstream_chunk: object, fields: Sequence[str]) -> Mapping[str, object]: + first_choice: Final = _upstream_first_choice(upstream_chunk) + if first_choice is None: + return _NO_UPSTREAM_CHOICE_FIELDS + upstream_extras: Final[Mapping[str, object]] = first_choice.model_extra or {} + return MappingProxyType({field: upstream_extras[field] for field in fields if field in upstream_extras}) + + +def _upstream_choice_index(upstream_chunk: object) -> int: + upstream_index: Final[object] = getattr(_upstream_first_choice(upstream_chunk), "index", 0) + return upstream_index if isinstance(upstream_index, int) else 0 + + +def _response_choice_index(response_obj: Mapping[str, object]) -> int: + choice_index: Final = response_obj.get("choice_index") + if isinstance(choice_index, int): + return choice_index + return _upstream_choice_index(response_obj.get("original_chunk")) + + +def _non_null_upstream_choice_fields(upstream_chunk: object, fields: Sequence[str]) -> Mapping[str, object]: + first_choice: Final = _upstream_first_choice(upstream_chunk) + upstream_extras: Final = first_choice.model_extra if first_choice is not None else None + if not upstream_extras: + return _NO_UPSTREAM_CHOICE_FIELDS + return MappingProxyType( + {field: upstream_extras[field] for field in fields if upstream_extras.get(field) is not None} + ) + + +def _apply_choice_fields(choice: StreamingChoices, fields: Mapping[str, object]) -> None: + for field, value in fields.items(): + setattr(choice, field, value) + + +def _choice_fields_chunk( + model_response: ModelResponseStream, upstream_index: int, fields: Mapping[str, object] +) -> ModelResponseStream: + model_response.choices[0].delta = Delta(content="") # rebind-ok: chunks are built in place here + model_response.choices[0].index = upstream_index # rebind-ok: chunks are built in place here + _apply_choice_fields(model_response.choices[0], fields) + return model_response + + +def _without_token_ids_under_post_call_rules(chunk: ModelResponseStream | None) -> ModelResponseStream | None: + if chunk is None or not litellm.post_call_rules: + return chunk + for choice in chunk.choices: + drop_token_ids(choice) + return chunk + + def _holds_only_scalars(fields: Iterable[tuple[str, object]]) -> bool: return all(value is None or isinstance(value, (str, int, float, bool)) for _, value in fields) @@ -378,6 +444,8 @@ class CustomStreamWrapper: self._provider_response_model: str | None = None self._upstream_provider: str | None = None self.received_finish_reason: str | None = None + self.received_finish_choice_fields: Mapping[int, Mapping[str, object]] = _NO_CHOICE_FIELDS_BY_INDEX + self.carried_chunk_choice_fields: Mapping[int, Mapping[str, object]] = _NO_CHOICE_FIELDS_BY_INDEX self.intermittent_finish_reason: str | None = None # finish reasons that show up mid-stream self.received_any_finish_reason = False # a later chunk can reset intermittent_finish_reason self.special_tokens = [ @@ -823,6 +891,7 @@ class CustomStreamWrapper: "logprobs": logprobs, "original_chunk": str_line, "usage": usage, + "chunk_choice_fields": _non_null_upstream_choice_fields(str_line, STREAM_CHUNK_CHOICE_FIELDS), } except Exception as e: raise e @@ -847,7 +916,7 @@ class CustomStreamWrapper: except Exception as e: raise e - def handle_openai_text_completion_chunk(self, chunk): + def handle_openai_text_completion_chunk(self, chunk: object): try: text = "" is_finished = False @@ -860,11 +929,15 @@ class CustomStreamWrapper: is_finished = True finish_reason = choices[0].finish_reason usage = getattr(chunk, "usage", None) + choice_index: Final = _upstream_choice_index(chunk) return { "text": text, "is_finished": is_finished, "finish_reason": finish_reason, "usage": usage, + "chunk_choice_fields": _non_null_upstream_choice_fields(chunk, STREAM_CHUNK_CHOICE_FIELDS), + "choice_index": choice_index, + "sibling_finish_reason": finish_reason if choice_index != 0 else None, } except Exception as e: @@ -1183,6 +1256,13 @@ class CustomStreamWrapper: ) is_chunk_non_empty: Final = self.is_chunk_non_empty(completion_obj, model_response, response_obj) + upstream_chunk_choice_fields: Final[Mapping[str, object]] = ( + _NO_UPSTREAM_CHOICE_FIELDS + if litellm.post_call_rules + else response_obj.get("chunk_choice_fields", _NO_UPSTREAM_CHOICE_FIELDS) + ) + chunk_choice_fields: Final = self._take_carried_chunk_choice_fields(response_obj, upstream_chunk_choice_fields) + sibling_finish_reason: Final[str | None] = response_obj.get("sibling_finish_reason") if is_chunk_non_empty: # cannot set content of an OpenAI Object to be an empty string self.raise_on_model_repetition() @@ -1270,16 +1350,40 @@ class CustomStreamWrapper: if response_obj.get("provider_specific_fields") is not None: completion_obj["provider_specific_fields"] = response_obj["provider_specific_fields"] model_response.choices[0].delta = Delta(**completion_obj) - _index: Final[int | None] = completion_obj.get("index") + _index: Final[int | None] = completion_obj.get("index", response_obj.get("choice_index")) if _index is not None: model_response.choices[0].index = _index + _apply_choice_fields(model_response.choices[0], chunk_choice_fields) + if sibling_finish_reason is not None: + self._finish_sibling_choice(model_response.choices[0], sibling_finish_reason) + elif response_obj.get("is_finished"): + self._apply_finish_choice_fields(model_response.choices[0]) self._optional_combine_thinking_block_in_choices(model_response=model_response) return model_response else: return + elif sibling_finish_reason is not None: + sibling_chunk: Final = _choice_fields_chunk( + model_response, _response_choice_index(response_obj), chunk_choice_fields + ) + self._finish_sibling_choice(sibling_chunk.choices[0], sibling_finish_reason) + return sibling_chunk elif self.received_finish_reason is not None: + chunk_upstream_index: Final = _response_choice_index(response_obj) + if chunk_choice_fields and self._streams_past_the_pending_finish( + model_response, response_obj, chunk_upstream_index + ): + self.carried_chunk_choice_fields = MappingProxyType( + {**self.carried_chunk_choice_fields, chunk_upstream_index: chunk_choice_fields} + ) + else: + another_choice_fields_chunk: Final = self._another_choice_fields_chunk( + model_response, response_obj, chunk_choice_fields + ) + if another_choice_fields_chunk is not None: + return another_choice_fields_chunk if self.sent_last_chunk is True: # Bedrock returns the guardrail trace in the last chunk - we want to return this here if self.custom_llm_provider == "bedrock" and "trace" in model_response: @@ -1317,12 +1421,20 @@ class CustomStreamWrapper: model_response.choices[0].finish_reason = self._normalize_tool_call_finish_reason( map_finish_reason(finish_reason=self.received_finish_reason) ) # ensure consistent output to openai + self._apply_finish_choice_fields(model_response.choices[0]) + if ( + response_obj.get("is_finished") + and _response_choice_index(response_obj) == model_response.choices[0].index + ): + _apply_choice_fields(model_response.choices[0], chunk_choice_fields) self.sent_last_chunk = True return model_response elif self._has_special_delta_content(model_response): return self._handle_special_delta_content(model_response) + elif chunk_choice_fields: + return _choice_fields_chunk(model_response, _response_choice_index(response_obj), chunk_choice_fields) else: if hasattr(model_response, "usage"): self.chunks.append(model_response) @@ -1545,6 +1657,8 @@ class CustomStreamWrapper: completion_obj["content"] = response_obj["text"] print_verbose(f"completion obj content: {completion_obj['content']}") if response_obj["is_finished"]: + self._record_finish_choice_fields(chunk) + if response_obj["is_finished"] and response_obj["sibling_finish_reason"] is None: self.received_finish_reason = response_obj["finish_reason"] if response_obj["usage"] is not None: _text_completion_usage: Final[Usage] = response_obj["usage"] @@ -1608,6 +1722,7 @@ class CustomStreamWrapper: self.system_fingerprint = cached_chunk.system_fingerprint if response_obj["is_finished"]: self.received_finish_reason = response_obj["finish_reason"] + self._record_finish_choice_fields(cached_chunk) else: # openai / azure chat model self.uses_openai_chat_stream = True if isinstance(chunk, ChatCompletionChunk): @@ -1637,6 +1752,7 @@ class CustomStreamWrapper: f"{self.custom_llm_provider} raised a streaming error - finish_reason: error, no content string given. Received Chunk={response_obj}" ) self.received_finish_reason = response_obj["finish_reason"] + self._record_finish_choice_fields(chunk) if response_obj.get("original_chunk", None) is not None: if hasattr(response_obj["original_chunk"], "id"): model_response = self.set_model_id(response_obj["original_chunk"].id, model_response) @@ -1704,7 +1820,7 @@ class CustomStreamWrapper: completion_obj=completion_obj, ) if isinstance(dispatch_result, _ProviderChunkEarlyReturn): - return dispatch_result.value + return _without_token_ids_under_post_call_rules(dispatch_result.value) response_obj = dispatch_result.response_obj model_response.model = self._served_openrouter_model() or self.model @@ -1794,7 +1910,7 @@ class CustomStreamWrapper: response_obj=response_obj, plain_delta_created=plain_delta_created, ) - return result + return _without_token_ids_under_post_call_rules(result) except StopIteration: raise StopIteration @@ -1987,6 +2103,75 @@ class CustomStreamWrapper: return "tool_calls" return finish_reason + def _record_finish_choice_fields(self, upstream_chunk: object) -> None: + self.received_finish_choice_fields = MappingProxyType( + { + **self.received_finish_choice_fields, + _upstream_choice_index(upstream_chunk): _upstream_choice_fields( + upstream_chunk, STREAM_FINISH_CHOICE_FIELDS + ), + } + ) + + def _apply_finish_choice_fields(self, choice: StreamingChoices) -> None: + _apply_choice_fields(choice, self.received_finish_choice_fields.get(choice.index, _NO_UPSTREAM_CHOICE_FIELDS)) + + def _finish_sibling_choice(self, choice: StreamingChoices, finish_reason: str) -> None: + choice.finish_reason = map_finish_reason(finish_reason) # rebind-ok: chunks are built in place here + self._apply_finish_choice_fields(choice) + + def _streams_past_the_pending_finish( + self, model_response: ModelResponseStream, response_obj: Mapping[str, object], upstream_index: int + ) -> bool: + finishing_index: Final = model_response.choices[0].index + return ( + not self.sent_last_chunk + and not response_obj.get("is_finished") + and upstream_index != finishing_index + and finishing_index in self.received_finish_choice_fields + ) + + def _take_carried_chunk_choice_fields( + self, response_obj: Mapping[str, object], chunk_choice_fields: Mapping[str, object] + ) -> Mapping[str, object]: + if not self.carried_chunk_choice_fields: + return chunk_choice_fields + upstream_index: Final = _response_choice_index(response_obj) + carried: Final = self.carried_chunk_choice_fields.get(upstream_index) + if carried is None: + return chunk_choice_fields + self.carried_chunk_choice_fields = MappingProxyType( + {index: fields for index, fields in self.carried_chunk_choice_fields.items() if index != upstream_index} + ) + return MappingProxyType( + { + field: [*object_items(carried.get(field)), *object_items(chunk_choice_fields.get(field))] + for field in STREAM_CHUNK_CHOICE_FIELDS + if field in carried or field in chunk_choice_fields + } + ) + + def _another_choice_fields_chunk( + self, + model_response: ModelResponseStream, + response_obj: Mapping[str, object], + chunk_choice_fields: Mapping[str, object], + ) -> ModelResponseStream | None: + upstream_index: Final = _response_choice_index(response_obj) + is_finished: Final = bool(response_obj.get("is_finished")) + if is_finished and upstream_index == model_response.choices[0].index and not self.sent_last_chunk: + return None + finish_fields: Final = ( + self.received_finish_choice_fields.get(upstream_index, _NO_UPSTREAM_CHOICE_FIELDS) + if is_finished + else _NO_UPSTREAM_CHOICE_FIELDS + ) + if not chunk_choice_fields and all(value is None for value in finish_fields.values()): + return None + return _choice_fields_chunk( + model_response, upstream_index, MappingProxyType({**finish_fields, **chunk_choice_fields}) + ) + def finish_reason_handler(self): model_response: Final = self.model_response_creator( hidden_params=None if self.received_model_id is None else {"received_model_id": self.received_model_id} @@ -2005,6 +2190,7 @@ class CustomStreamWrapper: model_response.choices[0].finish_reason = self._normalize_tool_call_finish_reason( _finish_reason if _finish_reason is not None else "stop" ) + self._apply_finish_choice_fields(model_response.choices[0]) close_tag: Final = self._close_open_think_block() if close_tag is not None: model_response.choices[0].delta.content = close_tag @@ -2640,8 +2826,6 @@ class CustomStreamWrapper: return None if is_model_response_stream_empty(model_response=usage_free_chunk) else usage_free_chunk def _accumulate_streamed_delta(self, delta: object) -> None: - # Shared by the sync, async, and non-aiohttp iteration sites so answer - # text and the disqualifying-content latch stay in step across all three. get: Final = getattr(delta, "get", None) content: Final = get("content") if callable(get) else None self.response_uptil_now += content if isinstance(content, str) else "" diff --git a/litellm/litellm_core_utils/token_counter.py b/litellm/litellm_core_utils/token_counter.py index 323af72940a..52a5026c44f 100644 --- a/litellm/litellm_core_utils/token_counter.py +++ b/litellm/litellm_core_utils/token_counter.py @@ -610,6 +610,127 @@ def estimate_image_tokens( return max(_image_policy_tokens(family, dimensions, detail) for family in families) +_MEDIA_FILE_CHARS_PER_TOKEN: Final = 4 +_EmbeddingInputT: Final = TypeVar("_EmbeddingInputT") + + +def _max_input_tokens(model: str) -> int | None: + try: + limit: Final = litellm.get_model_info(model).get("max_input_tokens") + except Exception: # noqa: BLE001 # get_model_info raises a bare Exception for an unmapped model + return None + return limit if isinstance(limit, int) and limit > 0 else None + + +def _media_file_tokens(data: str, models: Sequence[str]) -> int: + text_estimate: Final = len(data) // _MEDIA_FILE_CHARS_PER_TOKEN + ceilings: Final = tuple(map(_max_input_tokens, models)) + known_ceilings: Final = tuple(ceiling for ceiling in ceilings if ceiling is not None) + if not known_ceilings or len(known_ceilings) != len(ceilings): + return text_estimate + return min(text_estimate, max(known_ceilings)) + + +def _block_str_field(block: Mapping[str, object], container: str, field: str) -> str | None: + inner: Final = as_str_mapping(block.get(container)) + value: Final = inner.get(field) if inner is not None else None + return value if isinstance(value, str) else None + + +def estimate_media_block_tokens(block: Mapping[str, object], models: Sequence[str], fallback_model: str | None) -> int: + from litellm.litellm_core_utils.audio_utils.utils import estimate_audio_tokens + + match block.get("type"): + case "input_audio": + return estimate_audio_tokens( + _block_str_field(block, "input_audio", "data"), models, fallback_model=fallback_model + ) + case "file": + return _media_file_tokens(_block_str_field(block, "file", "file_data") or "", models) + case _: + detail: Final = _block_str_field(block, "image_url", "detail") + return estimate_image_tokens( + models, + _block_str_field(block, "image_url", "url") or "", + "auto" if detail is None else detail, + fallback_model=fallback_model, + ) + + +_PER_ITEM_DATA_URI_EMBEDDING_PROVIDERS: Final = frozenset({"vertex_ai", "gemini", "azure_ai"}) + +_DataUriMediaScope: TypeAlias = Literal["per_item", "whole_batch"] + + +def _is_pdf_block(block: Mapping[str, object]) -> bool: + return (_block_str_field(block, "file", "file_data") or "").startswith("data:application/pdf") + + +def _bedrock_data_uri_media_scope( + resolved_model: str, media: Sequence[Mapping[str, object]] +) -> _DataUriMediaScope | None: + from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM + from litellm.llms.bedrock.common_utils import BedrockModelInfo + from litellm.utils import supports_embedding_image_input + + base_model: Final = BedrockModelInfo.get_base_model(resolved_model.removeprefix("async_invoke/")) + if not supports_embedding_image_input(f"bedrock/{base_model}"): + return None + match BaseAWSLLM.get_bedrock_embedding_provider(base_model): + case "cohere": + return "whole_batch" + case "twelvelabs": + return None + case "nova" if any(map(_is_pdf_block, media)): + return None + case _: + return "per_item" + + +def _data_uri_media_scope(model: str, media: Sequence[Mapping[str, object]]) -> _DataUriMediaScope | None: + from litellm.utils import supports_embedding_image_input + + try: + resolved_model, provider, _, _ = litellm.get_llm_provider(model=model) + except litellm.exceptions.BadRequestError: + return None + if provider == "bedrock": + return _bedrock_data_uri_media_scope(resolved_model, media) + if not supports_embedding_image_input(model): + return None + if provider == "cohere": + return "whole_batch" + return "per_item" if provider in _PER_ITEM_DATA_URI_EMBEDDING_PROVIDERS else None + + +def split_embedding_input_tokens( + value: _EmbeddingInputT, media_models: Callable[[], Sequence[str]], fallback_model: str | None = None +) -> tuple[_EmbeddingInputT, int]: + from litellm.litellm_core_utils.prompt_templates.common_utils import ( + embedding_input_is_all_media, + split_embedding_media_for_tpm, + ) + + text, media = split_embedding_media_for_tpm(value) + if not media: + return value, 0 + models: Final = tuple(media_models()) + scopes: Final = frozenset(_data_uri_media_scope(model, media) for model in models) + if not models or None in scopes or ("whole_batch" in scopes and not embedding_input_is_all_media(value)): + return value, 0 + media_tokens: Final = sum(estimate_media_block_tokens(block, models, fallback_model) for block in media) + return cast(_EmbeddingInputT, text), media_tokens # cast-ok: the projection keeps the input's container shape + + +def embedding_aware_token_count( + messages: Sequence[Mapping[str, str]] | None, + text: str | list[str] | None, # mutable-ok: litellm.token_counter only takes text as list[str] + media_models: Callable[[], Sequence[str]], +) -> int: + embedding_text, media_tokens = split_embedding_input_tokens(text, media_models) + return litellm.token_counter(messages=messages, text=embedding_text) + media_tokens + + TokenCounterFunction = Callable[[str], int] """ Type for a function that counts tokens in a string. @@ -990,7 +1111,11 @@ def _count_extra( tool_section (Optional[ChatTemplateToolSection]): How the model's chat template renders tools, if known. """ reply_primer_tokens: Final = 3 - tool_choice_tokens: Final = 0 if tool_section is not None else _count_tool_choice(count_function, tool_choice) + tool_choice_tokens: Final = ( + _count_tool_choice(count_function, tool_choice) + if tool_section is None or tool_section.counts_tool_choice + else 0 + ) return ( reply_primer_tokens + _count_tool_definitions(count_function, tools, includes_system_message, tool_section) @@ -1029,14 +1154,29 @@ def _count_tool_choice( return 0 +def _named_function_definitions(tools: Sequence[object]) -> Iterable[Mapping[str, object]]: + return (function for function in _function_definitions(_tools_sent_as_functions(tools)) if function.get("name")) + + +def sends_function_tools(tools: Sequence[object] | None) -> bool: + return tools is not None and any(_named_function_definitions(tools)) + + +def _without_false_strict(function: Mapping[str, object]) -> Mapping[str, object]: + return {key: value for key, value in function.items() if key != "strict" or value} + + def _count_chat_template_tools( count_function: TokenCounterFunction, tools: Sequence[object], includes_system_message: bool, tool_section: ChatTemplateToolSection, ) -> int: - functions: Final = tuple( - function for function in _function_definitions(_tools_sent_as_functions(tools)) if function.get("name") + named_functions: Final = tuple(_named_function_definitions(tools)) + functions: Final = ( + tuple(map(_without_false_strict, named_functions)) + if tool_section.renders_strict_only_when_true + else named_functions ) if not functions: return 0 diff --git a/litellm/litellm_core_utils/tool_fields.py b/litellm/litellm_core_utils/tool_fields.py index f90c8f5d174..10b6f07bc4d 100644 --- a/litellm/litellm_core_utils/tool_fields.py +++ b/litellm/litellm_core_utils/tool_fields.py @@ -1,13 +1,16 @@ -from collections.abc import Callable, Mapping +from collections.abc import Callable, Mapping, Sequence +from copy import copy from dataclasses import dataclass from functools import reduce -from typing import Annotated, Final, TypeAlias +from typing import Annotated, Final, TypeAlias, TypeVar from pydantic import BeforeValidator, ConfigDict, Json, TypeAdapter, ValidationError from typing_extensions import ReadOnly, TypedDict import litellm -from litellm.litellm_core_utils.core_helpers import normalize_drop_params +from litellm._logging import verbose_logger +from litellm.exceptions import UnsupportedParamsError +from litellm.litellm_core_utils.core_helpers import as_str_mapping, drops_unsupported_params, normalize_drop_params ROUTES_WITH_TOOLS: Final = frozenset( { @@ -55,6 +58,19 @@ _TOOL_ENTRY: Final = TypeAdapter(_ToolEntry) _WEB_SEARCH_OPTIONS: Final = TypeAdapter(dict[str, object] | None, config=ConfigDict(strict=True)) +def declared_function_name(tool: object) -> str | None: + fields: Final = as_str_mapping(tool) + if fields is None: + return None + function: Final = as_str_mapping(fields.get("function")) + name: Final = (fields if function is None else function).get("name") + return name if isinstance(name, str) and name else None + + +def qualified_member_name(namespace: str, name: str) -> str: + return f"{namespace}__{name}" + + @dataclass(frozen=True, slots=True) class DropPolicy: drop_params: bool @@ -162,3 +178,145 @@ def resolve_deployment_tool_fields( if "proxy_server_request" not in kwargs or route not in ROUTES_WITH_TOOLS: return kwargs return resolve_tool_fields(kwargs, lambda: (drop_policy(kwargs),)) + + +_ToolT: Final = TypeVar("_ToolT") + +HOSTED_MCP_DROP_WARNING: Final = ( + "Dropping the hosted MCP tool(s) %s for model=%s on %s (drop_params=True) because this route cannot run a " + "hosted MCP tool." +) + + +def _hosted_mcp_server_label(tool: object) -> str | None: + match tool: + case {"type": "mcp", "server_label": str() as server_label}: + return server_label + case {"type": "mcp"}: + return "unlabeled" + case _: + return None + + +def _drop_params_hint(dropped: str) -> str: + return ( + f"To drop {dropped} instead, set `litellm.drop_params=True` or for proxy:\n\n" + "`litellm_settings:\n drop_params: true`\n" + ) + + +def _one_log_line(text: str) -> str: + return text.replace("\r", "").replace("\n", "") + + +def _unrunnable_mcp_error(message: str, model: str, route: str) -> UnsupportedParamsError: + return UnsupportedParamsError(message=message, model=model, llm_provider=route, status_code=400) + + +def tools_without_hosted_mcp(tools: Sequence[_ToolT], model: str, route: str, drop_params: bool) -> Sequence[_ToolT]: + server_labels: Final = tuple(label for label in map(_hosted_mcp_server_label, tools) if label is not None) + if not server_labels: + return tools + named_servers: Final = ", ".join(f"`{label}`" for label in server_labels) + if not drops_unsupported_params(drop_params): + raise _unrunnable_mcp_error( + f'{model} on {route} cannot run the hosted MCP tool {named_servers} (`type: "mcp"`). To have LiteLLM ' + "run the MCP server for this model, register it on the LiteLLM MCP gateway and send " + '`server_url: "litellm_proxy/mcp/"`. ' + _drop_params_hint("hosted MCP tools"), + model=model, + route=route, + ) + verbose_logger.warning( + HOSTED_MCP_DROP_WARNING, _one_log_line(named_servers), _one_log_line(model), _one_log_line(route) + ) + return [tool for tool in tools if _hosted_mcp_server_label(tool) is None] + + +MCP_SERVERS_DROP_WARNING: Final = ( + "Dropping mcp_servers %s and their mcp_toolset tools for model=%s on %s (drop_params=True) because LiteLLM " + "cannot pass mcp_servers to this route." +) + +ROUTES_WITHOUT_MCP_SERVERS: Final = frozenset( + {"bedrock", "databricks", "deepseek", "gemini", "gigachat", "ollama", "ollama_chat", "vertex_ai", "vertex_ai_beta"} +) + + +def _mcp_server_name(server: object) -> str: + match server: + case {"name": str() as name}: + return name + case _: + return "unnamed" + + +def _mcp_server_names(mcp_servers: object) -> tuple[str, ...]: + if not mcp_servers: + return () + if not isinstance(mcp_servers, list): + return ("unnamed",) + return tuple(map(_mcp_server_name, _TOOLS.validate_python(mcp_servers))) + + +def _is_mcp_toolset(tool: object) -> bool: + match tool: + case {"type": "mcp_toolset"}: + return True + case _: + return False + + +def drops_mcp_servers(request_kwargs: Mapping[str, object]) -> bool: + additional_drop_params: Final = request_kwargs.get("additional_drop_params") + return drops_unsupported_params(request_kwargs.get("drop_params")) or ( + isinstance(additional_drop_params, list) and "mcp_servers" in additional_drop_params + ) + + +def tools_without_mcp_servers( + mcp_servers: object, tools: Sequence[_ToolT], model: str, route: str, drop_params: bool +) -> Sequence[_ToolT]: + server_names: Final = _mcp_server_names(mcp_servers) + if not server_names: + return tools + named_servers: Final = ", ".join(f"`{name}`" for name in server_names) + if not drops_unsupported_params(drop_params): + raise _unrunnable_mcp_error( + f"LiteLLM cannot pass `mcp_servers` to {model} on {route}, so the MCP server {named_servers} would not " + 'run. To have LiteLLM run it for this model, register it on the LiteLLM MCP gateway and send a `type: "mcp"` ' + 'tool with `server_url: "litellm_proxy/mcp/"`. ' + _drop_params_hint("`mcp_servers`"), + model=model, + route=route, + ) + verbose_logger.warning( + MCP_SERVERS_DROP_WARNING, _one_log_line(named_servers), _one_log_line(model), _one_log_line(route) + ) + return [tool for tool in tools if not _is_mcp_toolset(tool)] + + +_TOOL_SELECTION_PARAMS: Final = frozenset({"tools", "tool_choice", "parallel_tool_calls"}) +_ParamsT: Final = TypeVar("_ParamsT", bound=dict[str, object]) + + +def tool_params_without_hosted_mcp( + params: _ParamsT, model: str, route: str, drop_params: bool, runs_hosted_mcp: Callable[[], bool] | None = None +) -> _ParamsT: + tools: Final = params.get("tools") + if not isinstance(tools, list) or not tools: + return params + sent_tools: Final = _TOOLS.validate_python(tools) + if all(_hosted_mcp_server_label(tool) is None for tool in sent_tools) or ( + runs_hosted_mcp is not None and runs_hosted_mcp() + ): + return params + kept_tools: Final = tools_without_hosted_mcp(tools=sent_tools, model=model, route=route, drop_params=drop_params) + if len(kept_tools) == len(sent_tools): + return params + kept_params: Final = copy(params) + if kept_tools: + kept_params["tools"] = list(kept_tools) + return kept_params + dropped_keys: Final = ("tools",) if params.get("functions") else _TOOL_SELECTION_PARAMS + for key in dropped_keys: + _ = kept_params.pop(key, None) + return kept_params diff --git a/litellm/litellm_core_utils/url_utils.py b/litellm/litellm_core_utils/url_utils.py index 0db6a41b503..eae8ac04e8e 100644 --- a/litellm/litellm_core_utils/url_utils.py +++ b/litellm/litellm_core_utils/url_utils.py @@ -102,6 +102,14 @@ class SSRFError(ValueError): """Raised when a URL targets a blocked network.""" +def is_https_url_with_host(url: str) -> bool: + try: + parsed_url: Final = urlsplit(url) + return parsed_url.scheme == "https" and bool(parsed_url.hostname) + except ValueError: + return False + + def encode_url_path_segment(value: object, *, field_name: str = "path parameter") -> str: """Percent-encode one user-controlled URL path segment. diff --git a/litellm/llms/anthropic/chat/guardrail_translation/handler.py b/litellm/llms/anthropic/chat/guardrail_translation/handler.py index 7f688ae733b..6436cd832c7 100644 --- a/litellm/llms/anthropic/chat/guardrail_translation/handler.py +++ b/litellm/llms/anthropic/chat/guardrail_translation/handler.py @@ -34,6 +34,7 @@ from litellm.llms.anthropic.messages.adapters.transformation import ( ) from litellm.llms.anthropic.messages.convertible_blocks import ( keep_non_string_tool_result_texts, + keep_url_documents, scannable_tool_result_request, ) from litellm.llms.anthropic.messages.native.utils import filtered_safeguard_results, redacted_stop_details @@ -780,12 +781,17 @@ class AnthropicMessagesHandler(BaseTranslation): for event in AnthropicMessagesHandler._parse_sse_data_line(line) ) - def _translate_to_openai(self, data: dict) -> ChatCompletionRequest: + def _translate_to_openai( + self, + data: dict, # mutable-ok: the request body the adapter reads + *, + keep_cache_control: bool = False, + ) -> ChatCompletionRequest: """Translate Anthropic request to OpenAI chat completion format.""" ( chat_completion_compatible_request, _tool_name_mapping, - ) = LiteLLMAnthropicMessagesAdapter().translate_anthropic_to_openai( + ) = LiteLLMAnthropicMessagesAdapter(keep_cache_control=keep_cache_control).translate_anthropic_to_openai( anthropic_message_request=cast(AnthropicMessagesRequest, scannable_tool_result_request(data)), preserve_midturn_system=True, ) @@ -812,9 +818,13 @@ class AnthropicMessagesHandler(BaseTranslation): data: dict, guardrail_to_apply: "CustomGuardrail", litellm_logging_obj: "LiteLLMLoggingObj | None" = None, + *, + request_data: dict[str, object] | None = None, # mutable-ok: the request dict guardrails receive + keep_cache_control: bool = False, ) -> Mapping[str, object]: """ - Process input messages by applying guardrails to text content. + Process input messages by applying guardrails to text content. ``request_data`` is what the guardrail sees as + the request when ``data`` is only its body, e.g. a provider pass-through route that nests the body """ messages: Final = data.get("messages") if messages is None: @@ -826,8 +836,17 @@ class AnthropicMessagesHandler(BaseTranslation): # The top-level prompt is translated on its own below so it can be hoisted in front of # any mid-turn system entries and scanned first, aligned with that structured position. - translation_source: Final = {key: value for key, value in data.items() if key != "system"} - chat_completion_compatible_request: Final = self._translate_to_openai(translation_source) + body_model: Final = data.get("model") + request_model: Final = (request_data or {}).get("model") + model: Final[str] = ( + body_model + if isinstance(body_model, str) and body_model + else (request_model if isinstance(request_model, str) else "") + ) + translation_source: Final = {**{key: value for key, value in data.items() if key != "system"}, "model": model} + chat_completion_compatible_request: Final = self._translate_to_openai( + translation_source, keep_cache_control=keep_cache_control + ) full_structured_messages: Final = cast( list[AllMessageValues], @@ -836,7 +855,9 @@ class AnthropicMessagesHandler(BaseTranslation): has_midturn_system_message: Final = any( str(message.get("role") or "").lower() == "system" for message in full_structured_messages ) - hoisted_system_message: Final = None if skip_system else self._hoisted_top_level_system_message(data) + hoisted_system_message: Final = ( + None if skip_system else self._hoisted_top_level_system_message(data, model, keep_cache_control) + ) if hoisted_system_message is not None: full_structured_messages.insert(0, hoisted_system_message) # skip_system already excluded the trusted top-level prompt (it is simply not hoisted); @@ -898,7 +919,6 @@ class AnthropicMessagesHandler(BaseTranslation): if structured_messages: inputs["structured_messages"] = structured_messages # Include model information if available - model: Final = data.get("model") if model: inputs["model"] = model original_tool_names: Final = _original_tool_names( @@ -906,7 +926,7 @@ class AnthropicMessagesHandler(BaseTranslation): ) guardrailed_inputs: Final = await guardrail_to_apply.apply_guardrail( inputs=inputs, - request_data=data, + request_data=data if request_data is None else request_data, input_type="request", logging_obj=litellm_logging_obj, ) @@ -954,6 +974,7 @@ class AnthropicMessagesHandler(BaseTranslation): hoisted_system_message=hoisted_system_message, preserve_system_messages=has_midturn_system_message, original_tool_names=original_tool_names.used, + model=model, ) else: if guardrailed_texts and len(guardrailed_texts) != len(scanned): @@ -976,17 +997,20 @@ class AnthropicMessagesHandler(BaseTranslation): return data - def _hoisted_top_level_system_message(self, data: Mapping[str, object]) -> AllMessageValues | None: + def _hoisted_top_level_system_message( + self, data: Mapping[str, object], model: str, keep_cache_control: bool + ) -> AllMessageValues | None: """Return the system message produced by translating the top-level prompt.""" system: Final = data.get("system") if not system: return None probe: Final = self._translate_to_openai( { - "model": data.get("model") or "", + "model": model, "messages": [], "system": system, - } + }, + keep_cache_control=keep_cache_control, ) hoisted: Final = probe.get("messages") or [] return hoisted[0] if hoisted else None @@ -1120,6 +1144,7 @@ class AnthropicMessagesHandler(BaseTranslation): preserve_system_messages: bool = False, *, original_tool_names: Mapping[str, str], + model: str, ) -> None: """Write a guardrail's structured-message rewrite back without losing corrections.""" from litellm.litellm_core_utils.prompt_templates.factory import ( @@ -1128,7 +1153,6 @@ class AnthropicMessagesHandler(BaseTranslation): ) _is_system: Final = AnthropicMessagesHandler._is_system - model: Final = str(data.get("model") or "") converted: Final[list] = [] # mutable-ok: API message payload def _convert_run(run: list) -> None: # mutable-ok: API message payload @@ -1187,7 +1211,10 @@ class AnthropicMessagesHandler(BaseTranslation): cast(Sequence[object], converted), # cast-ok: Anthropic message payload original_tool_names, ) - data["messages"] = keep_non_string_tool_result_texts(converted, data.get("messages")) + original_messages: Final = data.get("messages") + data["messages"] = keep_url_documents( + keep_non_string_tool_result_texts(converted, original_messages), original_messages + ) @staticmethod def _extract_midturn_system_text( diff --git a/litellm/llms/anthropic/chat/handler.py b/litellm/llms/anthropic/chat/handler.py index 75f88355652..c273c715ba6 100644 --- a/litellm/llms/anthropic/chat/handler.py +++ b/litellm/llms/anthropic/chat/handler.py @@ -516,6 +516,7 @@ class AnthropicChatCompletion(BaseLLM): headers=headers, request_data=request_data, provider=custom_llm_provider, + api_base=api_base, ) data: Final = dict( strip_beta_gated_request_body( @@ -733,6 +734,7 @@ class ModelResponseIterator: self._split_answer_blocks: tuple[str, ...] = () self._withheld_answer_close: str = "" self._streamed_answer_keys: frozenset[str] | None = None + self._held_prose: str = "" # For handling partial JSON chunks from fragmentation # See: https://github.com/BerriAI/litellm/issues/17473 @@ -825,8 +827,13 @@ class ModelResponseIterator: thinking_blocks: list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] = [] if "text" in content_block["delta"]: - text = content_block["delta"]["text"] - return text, tool_use, thinking_blocks, provider_specific_fields, reasoning_content + return ( + self._hold_prose(content_block["delta"]["text"]), + tool_use, + thinking_blocks, + provider_specific_fields, + reasoning_content, + ) self.content_blocks.append(content_block) if "partial_json" in content_block["delta"]: # Only emit tool calls if we're in a tool_use or server_tool_use block @@ -1024,7 +1031,7 @@ class ModelResponseIterator: if self.current_content_block_type in _THINKING_BLOCK_TYPES: self.thinking_block_index += 1 if content_block_start["content_block"]["type"] == "text": - text = self._release_answer_close() + content_block_start["content_block"]["text"] + text = self._release_answer_close() + self._hold_prose(content_block_start["content_block"]["text"]) elif ( content_block_start["content_block"]["type"] == "tool_use" or content_block_start["content_block"]["type"] == "server_tool_use" @@ -1160,7 +1167,7 @@ class ModelResponseIterator: elif type_chunk == "message_delta": finish_reason, usage, container, stop_reason_fields = self._handle_message_delta(chunk) provider_specific_fields.update(stop_reason_fields) - text = self._release_answer_close() + self._drain_split_answer_blocks() + text = self._release_answer_close() + self._drain_split_answer_blocks() + self._release_held_prose() if container: provider_specific_fields["container"] = container # Store container_id and re-emit code_interpreter_results @@ -1194,6 +1201,9 @@ class ModelResponseIterator: start_message: Final = message_start_block["message"] if "model" in start_message: self.served_model = start_message["model"] + input_transformations: Final = start_message.get("input_transformations") + if input_transformations is not None: + provider_specific_fields["input_transformations"] = input_transformations if "usage" in message_start_block["message"]: usage = self._handle_usage(anthropic_usage_chunk=message_start_block["message"]["usage"]) elif type_chunk == "error": @@ -1207,7 +1217,9 @@ class ModelResponseIterator: status_code=500, # it looks like Anthropic API does not return a status code in the chunk error - default to 500 ) - text, tool_use = self._handle_json_mode_chunk(text=text, tool_use=tool_use) + text, tool_use = self._handle_json_mode_chunk( + text=text + self._settle_held_prose(tool_use), tool_use=tool_use + ) refusal_fields: Final = refusal_params(provider_specific_fields) returned_chunk: Final = ModelResponseStream( @@ -1305,6 +1317,24 @@ class ModelResponseIterator: self._response_format_verdict = _envelope_verdict(buffered, schema, RESPONSE_FORMAT_TOOL_NAME) return self._withhold_answer_close(buffered) if self._response_format_verdict == "pass_through" else "" + def _hold_prose(self, text: str) -> str: + if not self.json_mode or self.response_format_schema is None: + return text + self._held_prose += text + return "" + + def _settle_held_prose(self, tool_use: ChatCompletionToolCallChunk | None) -> str: + if tool_use is None or tool_use.get("id") is None or self.current_content_block_type != "tool_use": + return "" + held: Final = self._held_prose + self._held_prose = "" + return "" if tool_use.get("function", {}).get("name") == RESPONSE_FORMAT_TOOL_NAME else held + + def _release_held_prose(self) -> str: + held: Final = self._held_prose + self._held_prose = "" + return "" if self.converted_response_format_tool else held + def _withhold_answer_close(self, text: str) -> str: pending: Final = self._withheld_answer_close + text body: Final = pending.rstrip() @@ -1358,7 +1388,9 @@ class ModelResponseIterator: def cut_stream_chunk(self) -> ModelResponseStream | None: unsent: Final = self._flush_response_format_buffer() if self._response_format_buffer.getvalue() else "" - text: Final = unsent + self._release_answer_close() + self._drain_split_answer_blocks() + text: Final = ( + unsent + self._release_answer_close() + self._drain_split_answer_blocks() + self._release_held_prose() + ) if not text: return None return ModelResponseStream( diff --git a/litellm/llms/anthropic/chat/transformation.py b/litellm/llms/anthropic/chat/transformation.py index 19432d4e721..b397c602faa 100644 --- a/litellm/llms/anthropic/chat/transformation.py +++ b/litellm/llms/anthropic/chat/transformation.py @@ -13,6 +13,7 @@ from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError from typing_extensions import ReadOnly, TypedDict import litellm +from litellm.anthropic_beta_headers_manager import get_unsupported_headers from litellm.constants import ( ANTHROPIC_BILLING_METADATA_PREFIX, ANTHROPIC_MIN_THINKING_BUDGET_TOKENS, @@ -25,8 +26,14 @@ from litellm.constants import ( DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET, DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET, RESPONSE_FORMAT_TOOL_NAME, + RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION, +) +from litellm.litellm_core_utils.asyncify import is_event_loop_running +from litellm.litellm_core_utils.core_helpers import ( + coerce_token_limit, + drops_unsupported_params, + map_finish_reason, ) -from litellm.litellm_core_utils.core_helpers import drops_unsupported_params, map_finish_reason from litellm.litellm_core_utils.prompt_templates.common_utils import ( DEFS_MAX_INLINED_BYTES, invalid_type_message, @@ -46,8 +53,11 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import ( ) from litellm.litellm_core_utils.prompt_templates.image_handling import ( RemoteMedia, + async_format_pdf_links, async_inline_remote_media, + format_pdf_links, inline_remote_image_urls, + is_unformatted_pdf_link_image, ) from litellm.litellm_core_utils.prompt_templates.mid_conversation_system import ( message_field, @@ -56,6 +66,7 @@ from litellm.litellm_core_utils.prompt_templates.mid_conversation_system import split_leading_system_run, ) from litellm.litellm_core_utils.reasoning_effort_utils import OPAQUE_VALUE, warn_non_string_reasoning_effort +from litellm.litellm_core_utils.tool_fields import tool_params_without_hosted_mcp from litellm.llms.base_llm.base_utils import ( ResponseFormatSchema, as_json_object, @@ -575,12 +586,16 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): ) @classmethod - def get_config(cls, *, model: str | None = None): + def get_config(cls, *, model: str | None = None, configured_max_output_tokens: int | None = None): config: Final = super().get_config() # anthropic requires a default value for max_tokens if config.get("max_tokens") is None: - config["max_tokens"] = cls.get_max_tokens_for_model(model) + config["max_tokens"] = ( + configured_max_output_tokens + if configured_max_output_tokens is not None + else cls.get_max_tokens_for_model(model) + ) return config @@ -1315,6 +1330,11 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): *(tool for tool in tools[first_search_tool_index + 1 :] if not _is_openai_tool_search_tool(tool)), ] + def runs_hosted_mcp(self) -> bool: + return ANTHROPIC_BETA_HEADER_VALUES.MCP_CLIENT_2025_04_04.value not in get_unsupported_headers( + self._resolved_provider + ) + def _tools_param_with_openai_tool_search_mapped( self, non_default_params: Mapping[str, object], model: str, drop_params: bool ) -> Mapping[str, object]: @@ -1767,7 +1787,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): json_schema: Mapping[str, object] | None, request_params: Mapping[str, object], ) -> bool: - open_object_takes_forced_json_tool: Final = ( + open_object_takes_json_tool: Final = ( json_schema is not None and schema_has_open_object(json_schema) and not self.is_thinking_requested(request_params) @@ -1775,7 +1795,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): and not request_params.get("tools") and not AnthropicModelInfo.forced_tool_use_unsupported(model) ) - return self.uses_native_structured_output(model) and not open_object_takes_forced_json_tool + return self.uses_native_structured_output(model) and not open_object_takes_json_tool def native_output_format_schema(self, json_schema: Mapping[str, object]) -> Mapping[str, object] | None: return self.filter_anthropic_output_schema(dict(self._defs_unpacked(json_schema))) @@ -1790,7 +1810,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): return AnthropicOutputSchema(type="json_schema", schema=dict(native_schema)) def map_response_format_to_anthropic_tool( - self, value: dict | None, optional_params: dict, is_thinking_enabled: bool + self, value: dict | None, optional_params: dict, tool_is_forced: bool ) -> AnthropicMessagesTool | None: ignore_response_format_types: Final = ["text"] if value is None or value["type"] in ignore_response_format_types: # value is a no-op @@ -1808,6 +1828,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): _tool: Final = self._create_json_tool_call_for_response_format( json_schema=json_schema, + description=None if tool_is_forced else RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION, ) return _tool @@ -1903,7 +1924,19 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): model: str, drop_params: bool, ) -> dict: - is_thinking_enabled: Final = self.is_thinking_enabled(non_default_params=non_default_params) + request_params: Final = tool_params_without_hosted_mcp( + non_default_params, + model=model, + route=self._resolved_provider, + drop_params=drop_params, + runs_hosted_mcp=self.runs_hosted_mcp, + ) + response_format_tool_is_forced: Final = ( + "response_format" in request_params + and AnthropicModelInfo.response_format_tool_can_be_forced( + model, self._resolved_provider, REQUEST_PARAMS.validate_python(request_params) + ) + ) # NB: ``map_openai_params`` deliberately does NOT sanitize tool names # here. Names are the *original* OpenAI names at this stage, and must @@ -1916,7 +1949,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): # via ``data = {**optional_params}`` and would 400 with # ``Extra inputs are not permitted``). - for param, value in non_default_params.items(): + for param, value in request_params.items(): if param == "max_tokens" or param == "max_completion_tokens": optional_params["max_tokens"] = value if isinstance(value, int) else max(1, int(round(value))) elif param == "tools": @@ -1930,8 +1963,8 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): optional_params["mcp_servers"] = mcp_servers elif param == "tool_choice" or param == "parallel_tool_calls": _tool_choice: AnthropicMessagesToolChoice | None = self._map_tool_choice( - tool_choice=non_default_params.get("tool_choice"), - parallel_tool_use=non_default_params.get("parallel_tool_calls"), + tool_choice=request_params.get("tool_choice"), + parallel_tool_use=request_params.get("parallel_tool_calls"), ) if _tool_choice is not None: @@ -1957,16 +1990,18 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): if self.uses_native_structured_output_for_schema( model, self._extract_json_schema_from_response_format(value), - REQUEST_PARAMS.validate_python(non_default_params), + REQUEST_PARAMS.validate_python(request_params), ): _output_format = self.map_response_format_to_anthropic_output_format(value) if _output_format is not None: optional_params["output_format"] = _output_format else: - _tool = self.map_response_format_to_anthropic_tool(value, optional_params, is_thinking_enabled) + _tool = self.map_response_format_to_anthropic_tool( + value, optional_params, response_format_tool_is_forced + ) if _tool is None: continue - if not is_thinking_enabled and not AnthropicModelInfo.forced_tool_use_unsupported(model): + if response_format_tool_is_forced: _tool_choice = { "name": RESPONSE_FORMAT_TOOL_NAME, "type": "tool", @@ -1993,7 +2028,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): # `thinking={type: enabled, budget_tokens}` interface a # pre-4.6 model actually supports instead of forwarding a # shape the model will reject. - max_tokens = non_default_params.get("max_completion_tokens") or non_default_params.get("max_tokens") + max_tokens = request_params.get("max_completion_tokens") or request_params.get("max_tokens") legacy_thinking = AnthropicConfig._map_reasoning_effort( reasoning_effort="medium", model=model, @@ -2087,7 +2122,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): ## handle thinking tokens self.update_optional_params_with_thinking_tokens( - non_default_params=non_default_params, optional_params=optional_params + non_default_params=request_params, optional_params=optional_params ) return optional_params @@ -2095,12 +2130,14 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): def _create_json_tool_call_for_response_format( self, json_schema: dict | None = None, + description: str | None = None, ) -> AnthropicMessagesTool: """ Handles creating a tool call for getting responses in JSON format. Args: json_schema (Optional[dict]): The JSON schema the response should be in + description (Optional[str]): The tool description, left off the tool when None Returns: AnthropicMessagesTool: The tool call to send to Anthropic API to get responses in JSON format @@ -2117,11 +2154,11 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): else: _input_schema.update(cast(AnthropicInputSchema, json_schema)) - _tool: Final = AnthropicMessagesTool( - name=RESPONSE_FORMAT_TOOL_NAME, - input_schema=_input_schema, + if description is None: + return AnthropicMessagesTool(name=RESPONSE_FORMAT_TOOL_NAME, input_schema=_input_schema) + return AnthropicMessagesTool( + name=RESPONSE_FORMAT_TOOL_NAME, input_schema=_input_schema, description=description ) - return _tool def should_strip_billing_metadata(self) -> bool: """ @@ -2319,6 +2356,12 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): def inlines_remote_media(self, media: RemoteMedia) -> bool: return inline_remote_image_urls(media) and media.url.startswith("http://") + def probes_pdf_link(self, media: RemoteMedia) -> bool: + return is_unformatted_pdf_link_image(media) and not self.inlines_remote_media(media) + + def _with_pdf_links_formatted(self, messages: Sequence[AllMessageValues]) -> Sequence[AllMessageValues]: + return messages if is_event_loop_running() else format_pdf_links(messages, should_probe=self.probes_pdf_link) + async def async_transform_request( self, model: str, @@ -2327,9 +2370,10 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): litellm_params: dict[str, object], # mutable-ok: BaseConfig signature headers: dict[str, object], # mutable-ok: BaseConfig signature ) -> dict[str, object]: # mutable-ok: BaseConfig signature + inlined: Final = await async_inline_remote_media(messages, should_inline=self.inlines_remote_media) return self.transform_request( model=model, - messages=await async_inline_remote_media(messages, should_inline=self.inlines_remote_media), + messages=list(await async_format_pdf_links(inlined, should_probe=self.probes_pdf_link)), optional_params=optional_params, litellm_params=litellm_params, headers=headers, @@ -2345,6 +2389,9 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): messages, optional_params.get("tools"), optional_params.get("cache_control"), optional_params ) + def translates_prompt_cache_breakpoint(self, model: str) -> bool: + return True + def transform_request( self, model: str, @@ -2358,19 +2405,32 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): """ ## VALIDATE REQUEST """Anthropic requires ``tools`` when messages include tool blocks; LiteLLM injects a dummy tool if omitted (no ``modify_params`` needed).""" + from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheControlHook, cache_control_count from litellm.litellm_core_utils.prompt_templates.factory import ( anthropic_messages_pt, ) drop_params: Final = drops_unsupported_params(litellm_params.get("drop_params")) + translated_messages: Final = ( + list( + AnthropicCacheControlHook.prompt_cache_breakpoints_as_capped_cache_control( + messages, + drop_params, + cache_control_count, + lambda: AnthropicCacheControlHook.count_chat_external_cache_breakpoints(optional_params), + ) + ) + if self.translates_prompt_cache_breakpoint(model) + else messages + ) capped_messages: Final = ( list( self._messages_within_cache_control_cap( - messages, _REQUEST_PARAMS_ADAPTER.validate_python(optional_params) + translated_messages, _REQUEST_PARAMS_ADAPTER.validate_python(optional_params) ) ) if drop_params - else messages + else translated_messages ) if "tools" not in optional_params and has_tool_call_blocks(capped_messages): @@ -2463,7 +2523,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): try: anthropic_messages = anthropic_messages_pt( model=model, - messages=list(conversation), + messages=list(self._with_pdf_links_formatted(conversation)), llm_provider=self._resolved_provider, drop_params=drop_params, ) @@ -2498,7 +2558,19 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): optional_params["tools"] = tools ## Load Config - config: Final[Mapping[str, object]] = MappingProxyType(litellm.AnthropicConfig.get_config(model=model)) + model_info: Final[object] = cast( # cast-ok: request parameters are a Mapping + Mapping[str, object], litellm_params + ).get("model_info") + configured_max_output_tokens: Final = ( + coerce_token_limit( + cast(Mapping[str, object], model_info).get("max_output_tokens") # cast-ok: runtime Mapping check + ) + if isinstance(model_info, Mapping) + else None + ) + config: Final[Mapping[str, object]] = MappingProxyType( + litellm.AnthropicConfig.get_config(model=model, configured_max_output_tokens=configured_max_output_tokens) + ) for k, v in config.items(): if ( k not in optional_params @@ -3028,7 +3100,7 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): def _build_provider_specific_fields( self, - completion_response: dict, + completion_response: Mapping[str, object], citations: Sequence[object] | None, thinking_blocks: list[ChatCompletionThinkingBlock | ChatCompletionRedactedThinkingBlock] | None, web_search_results: Sequence[object] | None, @@ -3045,6 +3117,10 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): if context_management is not None: provider_specific_fields["context_management"] = context_management + input_transformations: Final = completion_response.get("input_transformations") + if input_transformations is not None: + provider_specific_fields["input_transformations"] = input_transformations + if web_search_results is not None: provider_specific_fields["web_search_results"] = web_search_results @@ -3055,17 +3131,15 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): if tool_results is not None: provider_specific_fields["tool_results"] = tool_results + container: Final = completion_response.get("container") + container_fields: Final[Mapping[str, object] | None] = container if isinstance(container, dict) else None if tool_results is not None and any(result.get("type") != "tool_search_tool_result" for result in tool_results): - container_id: Final = ( - completion_response.get("container", {}).get("id") - if isinstance(completion_response.get("container"), dict) - else None - ) + raw_container_id: Final = container_fields.get("id") if container_fields is not None else None + container_id: Final = raw_container_id if isinstance(raw_container_id, str) else None code_by_id: Final = self._build_code_by_id_map(tool_calls) code_interpreter_results = self._build_code_interpreter_results(tool_results, code_by_id, container_id) provider_specific_fields["code_interpreter_results"] = code_interpreter_results - container: Final = completion_response.get("container") if container is not None: provider_specific_fields["container"] = container @@ -3166,8 +3240,13 @@ class AnthropicConfig(AnthropicModelInfo, BaseConfig): STOP_REASON_FIELDS.validate_python(completion_response) ) completion_response["stop_reason"] = "stop" - if stop_reason_fields: - json_mode_message.provider_specific_fields = dict(stop_reason_fields) + input_transformations: Final = provider_specific_fields.get("input_transformations") + json_mode_fields: Final = { + **stop_reason_fields, + **({} if input_transformations is None else {"input_transformations": input_transformations}), + } + if json_mode_fields: + json_mode_message.provider_specific_fields = json_mode_fields if "refusal" in refusal_fields: json_mode_message.refusal = refusal_fields["refusal"] if thinking_blocks: diff --git a/litellm/llms/anthropic/common_utils.py b/litellm/llms/anthropic/common_utils.py index 0a03ac51aaf..8bf57b97cfe 100644 --- a/litellm/llms/anthropic/common_utils.py +++ b/litellm/llms/anthropic/common_utils.py @@ -28,7 +28,7 @@ from litellm.constants import ( DEFAULT_REASONING_EFFORT_XHIGH_THINKING_BUDGET, ) from litellm.exceptions import UnsupportedParamsError -from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.core_helpers import as_str_mapping, lax_bool from litellm.litellm_core_utils.prompt_templates.common_utils import ( get_file_ids_from_messages, is_encrypted_reasoning_block, @@ -312,9 +312,10 @@ def count_tokens_feature_betas( ) -def supports_anthropic_cache_control(model: str, custom_llm_provider: str | None) -> bool: +def supports_anthropic_cache_control( + model: str, custom_llm_provider: str | None, model_info: Mapping[str, object] | None = None +) -> bool: from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider - from litellm.utils import supports_prompt_caching try: provider: Final = custom_llm_provider if custom_llm_provider is not None else get_llm_provider(model=model)[1] @@ -323,10 +324,27 @@ def supports_anthropic_cache_control(model: str, custom_llm_provider: str | None return ( provider in ("anthropic", "bedrock", "vertex_ai", "azure_ai") and "claude" in model.lower() - and supports_prompt_caching(model=model, custom_llm_provider=provider) + and _deployment_supports_prompt_caching(model, provider, model_info) ) +def _deployment_supports_prompt_caching(model: str, provider: str, model_info: Mapping[str, object] | None) -> bool: + from litellm.utils import catalog_with_runtime_registrations, get_model_info, supports_prompt_caching + + declared: Final = None if model_info is None else lax_bool(model_info.get("supports_prompt_caching")) + if declared is not None: + return declared + live: Final = supports_prompt_caching(model=model, custom_llm_provider=provider) + if model_info is None: + return live + try: + key: Final = get_model_info(model=model, custom_llm_provider=provider).get("key") + except Exception: # noqa: BLE001 # an unmapped model keeps the live answer + return live + catalog_entry: Final = catalog_with_runtime_registrations().get(key) + return live if catalog_entry is None else catalog_entry.get("supports_prompt_caching") is True + + def _tool_config_point_control(points: object) -> Mapping[object, object] | None: point_fields: Final = tuple(validated_object_mapping(point) for point in validated_object_list(points) or ()) tool_config_point: Final = next( @@ -1150,6 +1168,34 @@ class AnthropicModelInfo(BaseLLMModelInfo): return False return "effort" in output_config and output_config["effort"] in ("xhigh", "max") + @staticmethod + def thinks_by_default(model: str, custom_llm_provider: str) -> bool: + return AnthropicModelInfo._is_always_on_thinking_model( + model, custom_llm_provider + ) or AnthropicModelInfo._supports_model_capability(model, "thinking_on_by_default", custom_llm_provider) + + @staticmethod + def will_think(model: str, custom_llm_provider: str, request_params: Mapping[str, object]) -> bool: + if AnthropicModelInfo._is_always_on_thinking_model(model, custom_llm_provider): + return True + match request_params: + case {"thinking": True | {"type": "enabled" | "adaptive"}}: + return True + case {"reasoning_effort": effort} if effort is not None and effort != "none": + return True + case {"thinking": {"type": "disabled"}} | {"reasoning_effort": "none"}: + return False + case _: + return AnthropicModelInfo.thinks_by_default(model, custom_llm_provider) + + @staticmethod + def response_format_tool_can_be_forced( + model: str, custom_llm_provider: str, request_params: Mapping[str, object] + ) -> bool: + return not AnthropicModelInfo.forced_tool_use_unsupported(model) and not AnthropicModelInfo.will_think( + model, custom_llm_provider, request_params + ) + @staticmethod def _supports_legacy_thinking(model: str, custom_llm_provider: str) -> bool: """Whether ``model`` is an adaptive-thinking model that still accepts legacy @@ -1334,7 +1380,7 @@ class AnthropicModelInfo(BaseLLMModelInfo): return None return anthropic_beta_header.split(",") - def get_computer_tool_beta_header(self, computer_tool_version: str) -> str: + def get_computer_tool_beta_header(self, computer_tool_version: str) -> str | None: """ Get the appropriate beta header for a given computer tool version. @@ -1342,16 +1388,14 @@ class AnthropicModelInfo(BaseLLMModelInfo): computer_tool_version: The computer tool version (e.g., 'computer_20250124', 'computer_20241022') Returns: - The corresponding beta header string + The corresponding beta header string, or None for a version with no known beta """ computer_tool_beta_mapping: Final = { + "computer_20251124": "computer-use-2025-11-24", "computer_20250124": "computer-use-2025-01-24", "computer_20241022": "computer-use-2024-10-22", } - return computer_tool_beta_mapping.get( - computer_tool_version, - "computer-use-2024-10-22", # Default fallback - ) + return computer_tool_beta_mapping.get(computer_tool_version) def get_anthropic_beta_list( self, @@ -1383,9 +1427,8 @@ class AnthropicModelInfo(BaseLLMModelInfo): if effort_used: betas.append(ANTHROPIC_EFFORT_BETA_HEADER) # effort-2025-11-24 - if computer_tool_used: - beta_header: Final = self.get_computer_tool_beta_header(computer_tool_used) - betas.append(beta_header) + if computer_tool_used and (computer_tool_beta := self.get_computer_tool_beta_header(computer_tool_used)): + betas.append(computer_tool_beta) # Anthropic no longer requires the prompt-caching beta header # Prompt caching now works automatically when cache_control is used in messages @@ -1474,9 +1517,8 @@ class AnthropicModelInfo(BaseLLMModelInfo): # Anthropic no longer requires the prompt-caching beta header # Prompt caching now works automatically when cache_control is used in messages # Reference: https://docs.anthropic.com/en/docs/build-with-claude/prompt-caching - if computer_tool_used: - beta_header: Final = self.get_computer_tool_beta_header(computer_tool_used) - betas.add(beta_header) + if computer_tool_used and (computer_tool_beta := self.get_computer_tool_beta_header(computer_tool_used)): + betas.add(computer_tool_beta) # if pdf_used: # betas.add("pdfs-2024-09-25") if file_id_used: diff --git a/litellm/llms/anthropic/count_tokens/transformation.py b/litellm/llms/anthropic/count_tokens/transformation.py index 1c8f0c206cd..3034927c612 100644 --- a/litellm/llms/anthropic/count_tokens/transformation.py +++ b/litellm/llms/anthropic/count_tokens/transformation.py @@ -49,7 +49,10 @@ _PLAIN_MESSAGE_KEYS: Final = frozenset({"role", "content"}) def _count_image(block: JsonValue) -> JsonValue: if not isinstance(block, dict) or block.get("type") != "image_url": return block - from litellm.litellm_core_utils.prompt_templates.factory import convert_to_anthropic_image_obj + from litellm.litellm_core_utils.prompt_templates.factory import ( + anthropic_content_element_factory, + convert_to_anthropic_image_obj, + ) image_block: Final = _IMAGE_BLOCK.validate_python(block) image_url: Final = image_block["image_url"] @@ -57,7 +60,7 @@ def _count_image(block: JsonValue) -> JsonValue: openai_image_url=image_url if isinstance(image_url, str) else image_url["url"], format=image_url.get("format") if isinstance(image_url, dict) else None, ) - image: Final = _COUNT_REQUEST.validate_python({"type": "image", "source": source}) + image: Final = _COUNT_REQUEST.validate_python(anthropic_content_element_factory(source)) return {**{key: value for key, value in block.items() if key not in {"type", "image_url"}}, **image} diff --git a/litellm/llms/anthropic/messages/adapters/handler.py b/litellm/llms/anthropic/messages/adapters/handler.py index d13fd4f47ff..31a4e9d9d73 100644 --- a/litellm/llms/anthropic/messages/adapters/handler.py +++ b/litellm/llms/anthropic/messages/adapters/handler.py @@ -15,6 +15,11 @@ from litellm._logging import verbose_logger from litellm.litellm_core_utils.asyncify import run_async_function from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObject +from litellm.litellm_core_utils.tool_fields import ( + ROUTES_WITHOUT_MCP_SERVERS, + drops_mcp_servers, + tools_without_mcp_servers, +) from litellm.llms.anthropic.messages.adapters.transformation import ( AnthropicAdapter, ) @@ -610,6 +615,23 @@ class LiteLLMMessagesToCompletionTransformationHandler: Logging as LiteLLMLoggingObject, ) + provider_kwargs: Final = extra_kwargs or {} + custom_llm_provider: Final = provider_kwargs.get("custom_llm_provider") + target_provider: Final = custom_llm_provider if isinstance(custom_llm_provider, str) else None + drop_params: Final = drops_unsupported_params(provider_kwargs.get("drop_params")) + strips_mcp_servers: Final = target_provider in ROUTES_WITHOUT_MCP_SERVERS + request_tools: Final = ( + tools_without_mcp_servers( + provider_kwargs.get("mcp_servers"), + tools or (), + model=model, + route=target_provider, + drop_params=drops_mcp_servers(provider_kwargs), + ) + if strips_mcp_servers + else tools + ) + request_data: Final[dict[str, object]] = { "model": model, "messages": messages, @@ -626,10 +648,10 @@ class LiteLLMMessagesToCompletionTransformationHandler: request_data["temperature"] = temperature if thinking: request_data["thinking"] = thinking - if tool_choice: + if tool_choice and (request_tools or not tools): request_data["tool_choice"] = tool_choice - if tools: - request_data["tools"] = tools + if request_tools: + request_data["tools"] = request_tools if top_k is not None: request_data["top_k"] = top_k if top_p is not None: @@ -647,16 +669,15 @@ class LiteLLMMessagesToCompletionTransformationHandler: if "output_config" in extra_kwargs: request_data["output_config"] = extra_kwargs["output_config"] - custom_llm_provider: Final = extra_kwargs.get("custom_llm_provider") api_base: Final = extra_kwargs.get("api_base") ( openai_request, tool_name_mapping, ) = ANTHROPIC_ADAPTER.translate_completion_input_params_with_tool_mapping( request_data, - custom_llm_provider=custom_llm_provider if isinstance(custom_llm_provider, str) else None, + custom_llm_provider=target_provider, api_base=api_base if isinstance(api_base, str) else None, - drop_params=drops_unsupported_params(extra_kwargs.get("drop_params")), + drop_params=drop_params, ) if openai_request is None: @@ -684,7 +705,11 @@ class LiteLLMMessagesToCompletionTransformationHandler: # Maintainability: when adding a new Anthropic-only request param to # ``AnthropicMessagesRequestOptionalParams``, also extend # ``ANTHROPIC_ONLY_REQUEST_KEYS`` here so it doesn't silently leak. - excluded_keys: Final = ANTHROPIC_ONLY_REQUEST_KEYS | CONVERTED_STREAM_KEYS | {"anthropic_messages"} + excluded_keys: Final = ( + ANTHROPIC_ONLY_REQUEST_KEYS + | CONVERTED_STREAM_KEYS + | ({"anthropic_messages", "mcp_servers"} if strips_mcp_servers else {"anthropic_messages"}) + ) # NOTE: extra_kwargs was already coerced from None to {} at the top of # this method (line ~220). It is guaranteed to be a dict here. for key, value in extra_kwargs.items(): diff --git a/litellm/llms/anthropic/messages/adapters/streaming_iterator.py b/litellm/llms/anthropic/messages/adapters/streaming_iterator.py index 61d23c2de0d..87be996ebbf 100644 --- a/litellm/llms/anthropic/messages/adapters/streaming_iterator.py +++ b/litellm/llms/anthropic/messages/adapters/streaming_iterator.py @@ -493,10 +493,23 @@ class _CombinedChunkSplitter: for position, block in enumerate(blocks) ) + @staticmethod + def _without_sibling_finish(chunk: "ModelResponseStream") -> "ModelResponseStream": + choices: Final = _optional_attr_sequence(chunk, "choices") + if ( + len(choices) != 1 + or _optional_attr(choices[0], "index") in (None, 0) + or _optional_attr(choices[0], "finish_reason") is None + ): + return chunk + unfinished: Final = copy.deepcopy(chunk) + unfinished.choices[0].finish_reason = None + return unfinished + def _expand(self, chunk: "ModelResponseStream") -> "tuple[ModelResponseStream, ...]": split_chunks: Final = tuple( split_chunk - for combined_chunk in self._split(chunk) + for combined_chunk in self._split(self._without_sibling_finish(chunk)) for split_chunk in self._split_by_payload_kind(combined_chunk) # comprehension-ok: flattens nested splits ) block_chunks: Final = tuple(itertools.chain.from_iterable(map(self._split_thinking_blocks, split_chunks))) @@ -657,6 +670,8 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper): # Synthesized compaction block from compact_20260112 polyfill (streaming). self.compaction_block = compaction_block self.iterations_usage = iterations_usage + # The provider's error behind this stream's error frame, for a router that accounts for it. + self.stream_failure: Exception | None = None self._refusal_text: str = "" self._paused_turn: bool = False self._claude_refusal_stop_details: AnthropicStopDetails | None = None @@ -1383,6 +1398,7 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper): verbose_logger.exception("Anthropic Adapter - mid-stream error: %s", e) logging_obj: Final = self.litellm_logging_obj provider_error: Final = _provider_error(e) + self.stream_failure = provider_error if logging_obj is not None and logging_obj.on_detached_stream_failure is not None: if provider_error is e: raise @@ -1606,6 +1622,10 @@ class AnthropicSSEStream(AsyncIterator[bytes]): self._byte_stream: Final[AsyncIterator[bytes]] = anthropic_wrapper.async_anthropic_sse_wrapper() self._hidden_params: dict[str, object] = {} + @property + def stream_failure(self) -> Exception | None: + return self._anthropic_wrapper.stream_failure + @property def chunks(self) -> "list[ModelResponseStream] | None": return self._anthropic_wrapper.chunks diff --git a/litellm/llms/anthropic/messages/adapters/transformation.py b/litellm/llms/anthropic/messages/adapters/transformation.py index 4b1b5a8a11a..afcd94c5b2c 100644 --- a/litellm/llms/anthropic/messages/adapters/transformation.py +++ b/litellm/llms/anthropic/messages/adapters/transformation.py @@ -380,8 +380,8 @@ _CLAUDE_OVER_REASONING_EFFORT_PROVIDERS: Final = frozenset({LlmProviders.KYMA.va class LiteLLMAnthropicMessagesAdapter: - def __init__(self): - pass + def __init__(self, *, keep_cache_control: bool = False) -> None: + self.keep_cache_control: Final = keep_cache_control ### FOR [BETA] `/v1/messages` endpoint support @@ -437,7 +437,7 @@ class LiteLLMAnthropicMessagesAdapter: cache_control: Final = ( source.get("cache_control") if isinstance(source, dict) else getattr(source, "cache_control", None) ) - if cache_control and model and self.target_consumes_cache_control(model): + if cache_control and (self.keep_cache_control or (model and self.target_consumes_cache_control(model))): # TypedDict objects support dict operations at runtime # Use type ignore consistent with codebase pattern (see anthropic/chat/transformation.py:432) if isinstance(target, dict): diff --git a/litellm/llms/anthropic/messages/caller_model_checks.py b/litellm/llms/anthropic/messages/caller_model_checks.py index 3822f075ccf..c89d8a1ea23 100644 --- a/litellm/llms/anthropic/messages/caller_model_checks.py +++ b/litellm/llms/anthropic/messages/caller_model_checks.py @@ -243,8 +243,7 @@ async def caller_within_model_budget( return "allowed" model_max_budget: Final = getattr(user_api_key_auth, "model_max_budget", None) - token: Final = getattr(user_api_key_auth, "token", None) - if isinstance(model_max_budget, dict) and model_max_budget and token is not None: + if isinstance(model_max_budget, dict) and model_max_budget and user_api_key_auth.token is not None: try: await model_max_budget_limiter.is_key_within_model_budget( user_api_key_dict=user_api_key_auth, @@ -300,10 +299,8 @@ async def caller_within_model_budget( ) return "denied_for_now" - end_user_model_max_budget: Final[dict[str, object] | None] = getattr( - user_api_key_auth, "end_user_model_max_budget", None - ) - end_user_id: Final[str | None] = getattr(user_api_key_auth, "end_user_id", None) + end_user_model_max_budget: Final[dict[str, object] | None] = user_api_key_auth.end_user_model_max_budget + end_user_id: Final[str | None] = user_api_key_auth.end_user_id if isinstance(end_user_model_max_budget, dict) and end_user_model_max_budget and end_user_id is not None: try: await model_max_budget_limiter.is_end_user_within_model_budget( diff --git a/litellm/llms/anthropic/messages/context_management/inference_view.py b/litellm/llms/anthropic/messages/context_management/inference_view.py new file mode 100644 index 00000000000..004beebe838 --- /dev/null +++ b/litellm/llms/anthropic/messages/context_management/inference_view.py @@ -0,0 +1,138 @@ +from collections.abc import Mapping, Sequence +from dataclasses import dataclass +from typing import Final + +from pydantic import JsonValue, TypeAdapter, ValidationError +from typing_extensions import assert_never + +from litellm.types.llms.anthropic import AnthropicMessagesTextParam +from litellm.types.utils import CountContextManagement, TokenCountMessagesFormat + + +@dataclass(frozen=True, slots=True) +class InferenceRequestView: + messages: Sequence[Mapping[str, object]] + system: object | None + + +@dataclass(frozen=True, slots=True) +class InferenceRequestViewError: + error_message: str + status_code: int + + +@dataclass(frozen=True, slots=True) +class CountContextEdits: + spec: JsonValue + model: str + tools: tuple[Mapping[str, object], ...] | None + drop_invalid_edits: bool = False + + +_CONTEXT_MANAGEMENT_SPEC: Final[TypeAdapter[Mapping[str, object] | tuple[Mapping[str, object], ...]]] = TypeAdapter( + Mapping[str, object] | tuple[Mapping[str, object], ...] +) +_SYSTEM_BLOCKS: Final = TypeAdapter(tuple[AnthropicMessagesTextParam, ...]) + + +def count_context_edits( + context_management: CountContextManagement | None, + tools: Sequence[Mapping[str, object]] | None, + litellm_params: Mapping[str, object], + fallback_model: str, +) -> CountContextEdits: + model: Final = litellm_params.get("model") + return CountContextEdits( + spec=None if context_management is None else context_management.spec, + model=model if isinstance(model, str) else fallback_model, + tools=None if tools is None else tuple(tools), + drop_invalid_edits=context_management is not None and context_management.drop_invalid_edits, + ) + + +def _typed_spec(spec: JsonValue) -> Mapping[str, object] | tuple[Mapping[str, object], ...] | None: + try: + return _CONTEXT_MANAGEMENT_SPEC.validate_python(spec) + except ValidationError: + return None + + +def _typed_system(system: object | None) -> str | tuple[AnthropicMessagesTextParam, ...] | None | ValidationError: + if system is None or isinstance(system, str): + return system + try: + return _SYSTEM_BLOCKS.validate_python(system) + except ValidationError as error: + return error + + +def _view_without_edits( + messages: Sequence[Mapping[str, object]], + system: object | None, + typed_system: str | Sequence[Mapping[str, object]] | None, +) -> InferenceRequestView: + from litellm.llms.anthropic.messages.context_management.editors.compact import ( + apply_client_compaction_block_history, + ) + + history: Final = apply_client_compaction_block_history( + messages=[dict(message) for message in messages], + system=typed_system + if typed_system is None or isinstance(typed_system, str) + else [dict(block) for block in typed_system], + ) + if history is None: + return InferenceRequestView(messages=messages, system=system) + return InferenceRequestView(messages=history.messages, system=history.system) + + +async def _anthropic_inference_view( + messages: Sequence[Mapping[str, object]], system: object | None, edits: CountContextEdits +) -> InferenceRequestView | InferenceRequestViewError: + from litellm.llms.anthropic.messages.adapters.handler import prepare_context_managed_request + from litellm.llms.anthropic.messages.context_management import AnthropicContextManagementError + from litellm.llms.anthropic.messages.native.utils import normalize_native_messages + + typed_system: Final = _typed_system(system) + if isinstance(typed_system, ValidationError): + return InferenceRequestView(messages=messages, system=system) + normalized: Final = normalize_native_messages(messages) + spec: Final = _typed_spec(edits.spec) + try: + prepared: Final = await prepare_context_managed_request( + model=edits.model, + messages=normalized, + tools=None if edits.tools is None else [dict(tool) for tool in edits.tools], + system=[dict(block) for block in typed_system] if isinstance(typed_system, tuple) else typed_system, + context_management_spec=( + None if spec is None else dict(spec) if isinstance(spec, Mapping) else [dict(edit) for edit in spec] + ), + litellm_metadata=None, + additional_drop_params=None, + llm_router=None, + count_only=True, + drop_invalid_edits=edits.drop_invalid_edits, + ) + except AnthropicContextManagementError as error: + if error.status_code >= 500: + return _view_without_edits(normalized, system, typed_system) + return InferenceRequestViewError(error_message=error.message, status_code=error.status_code) + if prepared is None: + return InferenceRequestView(messages=normalized, system=system) + return InferenceRequestView(messages=prepared.messages, system=prepared.system) + + +async def inference_request_view( + messages: Sequence[Mapping[str, object]], + system: object | None, + messages_format: TokenCountMessagesFormat, + edits: CountContextEdits, +) -> InferenceRequestView | InferenceRequestViewError: + """Apply the history rewrites and context edits /v1/messages runs before it converts a body for another provider.""" + match messages_format: + case "openai": + return InferenceRequestView(messages=messages, system=system) + case "anthropic": + return await _anthropic_inference_view(messages, system, edits) + case _: + assert_never(messages_format) diff --git a/litellm/llms/anthropic/messages/convertible_blocks.py b/litellm/llms/anthropic/messages/convertible_blocks.py index 09d662da543..b98b4cf3f75 100644 --- a/litellm/llms/anthropic/messages/convertible_blocks.py +++ b/litellm/llms/anthropic/messages/convertible_blocks.py @@ -314,6 +314,76 @@ def keep_non_string_tool_result_texts(rewritten: Sequence[object], original: obj return [_with_user_blocks(message, partial(_restored_block, kept=kept_in_order)) for message in rewritten] +def _url_source_url(block: object) -> str | None: + match as_str_mapping(block): + case {"type": "image" | "document", "source": {"type": "url", "url": str(url)}}: + return url + case _: + return None + + +def _is_document(block: object) -> bool: + match as_str_mapping(block): + case {"type": "document"}: + return True + case _: + return False + + +@dataclass(frozen=True, slots=True, order=True) +class _UrlBlockPlace: + in_tool_result: bool + url: str + + +def _url_sourced_blocks(block: object, in_tool_result: bool = False) -> tuple[tuple[_UrlBlockPlace, object], ...]: + url: Final = _url_source_url(block) + if url is not None: + return ((_UrlBlockPlace(in_tool_result, url), block),) + match as_str_mapping(block): + case {"type": "tool_result", "content": list() as content}: + in_this_tool_result: Final = partial(_url_sourced_blocks, in_tool_result=True) + return tuple(chain.from_iterable(map(in_this_tool_result, _list_items(content)))) + case _: + return () + + +def _entry_place(entry: tuple[_UrlBlockPlace, object]) -> _UrlBlockPlace: + return entry[0] + + +def _entry_block(entry: tuple[_UrlBlockPlace, object]) -> object: + return entry[1] + + +def _restored_url_document( + block: object, originals: Mapping[_UrlBlockPlace, Iterator[object]], in_tool_result: bool = False +) -> object: + url: Final = _url_source_url(block) + if url is not None: + remaining: Final = originals.get(_UrlBlockPlace(in_tool_result, url)) + original: Final = None if remaining is None else next(remaining, None) + return original if _is_document(original) else block + match as_str_mapping(block): + case {"type": "tool_result", "content": list() as content} as tool_result: + restore: Final = partial(_restored_url_document, originals=originals, in_tool_result=True) + return {**tool_result, "content": list(map(restore, _list_items(content)))} + case _: + return block + + +def keep_url_documents(rewritten: Sequence[object], original: object) -> Sequence[object]: + blocks: Final = chain.from_iterable(map(_user_content_blocks, _list_items(original))) + by_place: Final = tuple(sorted(chain.from_iterable(map(_url_sourced_blocks, blocks)), key=_entry_place)) + if not any(_is_document(block) for _, block in by_place): + return rewritten + originals_in_order: Final = MappingProxyType( + {place: iter(tuple(map(_entry_block, group))) for place, group in groupby(by_place, key=_entry_place)} + ) + restore: Final = partial(_restored_url_document, originals=originals_in_order) + return [_with_user_blocks(message, restore) for message in rewritten] + + def _without_non_string_text(block: object) -> object: match as_str_mapping(block): case {"type": "tool_result", "content": list()} as tool_result: diff --git a/litellm/llms/anthropic/messages/native/agentic_streaming_iterator.py b/litellm/llms/anthropic/messages/native/agentic_streaming_iterator.py index 25d4d7b3ce1..0aa30998557 100644 --- a/litellm/llms/anthropic/messages/native/agentic_streaming_iterator.py +++ b/litellm/llms/anthropic/messages/native/agentic_streaming_iterator.py @@ -22,6 +22,7 @@ from typing import TYPE_CHECKING, Any, Final, cast from litellm._logging import verbose_logger from litellm.constants import STREAM_SSE_KEEPALIVE_PING_BYTES +from litellm.types.integrations.custom_logger import AgenticLoopLimitError, AgenticLoopSafetyError if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj @@ -35,10 +36,16 @@ SERVER_FULFILLED_TOOL_LEAK_ERROR_SSE_BYTES: Final = ( b'data: {"type": "error", "error": {"type": "api_error", "message": ' b'"Server-side tool retrieval failed, so this turn could not be completed. Please retry."}}\n\n' ) +AGENTIC_LOOP_LIMIT_ERROR_SSE_BYTES: Final = ( + b"event: error\n" + b'data: {"type": "error", "error": {"type": "api_error", "message": ' + b'"The agentic loop reached its limit before this turn finished. ' + b'Raise max_agentic_loops to allow more loops."}}\n\n' +) def is_server_fulfilled_tool_leak_error(chunk: object) -> bool: - return chunk == SERVER_FULFILLED_TOOL_LEAK_ERROR_SSE_BYTES + return chunk in (SERVER_FULFILLED_TOOL_LEAK_ERROR_SSE_BYTES, AGENTIC_LOOP_LIMIT_ERROR_SSE_BYTES) async def _anext_or_none(iterator: AsyncIterator) -> bytes | None: @@ -216,6 +223,7 @@ class AgenticAnthropicStreamingIterator: self._follow_up_chunk_task: asyncio.Task | None = None self._replay_index = 0 self._error_emitted = False + self._loop_limit_reached = False @property def has_buffered_provider_output(self) -> bool: @@ -288,6 +296,8 @@ class AgenticAnthropicStreamingIterator: "tool_use [model=%s]; emitting an SSE error instead of leaking the tool call to the client", self._model, ) + if self._loop_limit_reached: + return AGENTIC_LOOP_LIMIT_ERROR_SSE_BYTES return SERVER_FULFILLED_TOOL_LEAK_ERROR_SSE_BYTES if self._replay_index < len(self._collected_bytes): @@ -393,14 +403,9 @@ class AgenticAnthropicStreamingIterator: "AgenticStreamingIterator: Unexpected result type from hooks: %s", type(result).__name__, ) - except Exception as e: - _call_id: Final = getattr(self._logging_obj, "litellm_call_id", "unknown") - verbose_logger.exception( - "AgenticStreamingIterator: Error in agentic hook processing [call_id=%s model=%s]: %s", - _call_id, - self._model, - str(e), - ) + except AgenticLoopSafetyError as e: + self._loop_limit_reached = isinstance(e, AgenticLoopLimitError) + verbose_logger.warning("AgenticStreamingIterator: agentic loop refused [rail=%s]", type(e).__name__) @staticmethod def _rebuild_anthropic_response_from_sse( diff --git a/litellm/llms/anthropic/messages/native/handler.py b/litellm/llms/anthropic/messages/native/handler.py index 1bf00cbdb2f..922de386fe4 100644 --- a/litellm/llms/anthropic/messages/native/handler.py +++ b/litellm/llms/anthropic/messages/native/handler.py @@ -8,6 +8,7 @@ import asyncio import contextvars from collections.abc import AsyncIterator, Awaitable, Callable, Coroutine, Iterator, Mapping, Sequence +from dataclasses import dataclass from functools import partial from typing import Final, cast @@ -15,6 +16,7 @@ from pydantic import TypeAdapter import litellm from litellm.anthropic_beta_headers_manager import aload_beta_headers_config +from litellm.constants import PROVIDERS_THAT_AUTHENTICATE_ON_PROVIDER_INFO from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheControlHook from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.litellm_core_utils.exception_mapping_utils import exception_type @@ -44,7 +46,7 @@ from litellm.types.llms.anthropic_messages.anthropic_response import ( AnthropicMessagesResponse, ) from litellm.types.router import GenericLiteLLMParams -from litellm.types.utils import CallTypes, LlmProviders +from litellm.types.utils import CallTypes, LlmProviders, LlmProvidersSet from litellm.utils import ProviderConfigManager, client from ..adapters.handler import LiteLLMMessagesToCompletionTransformationHandler, request_safeguards_evaluator @@ -94,6 +96,68 @@ def _responses_mode_is_lost_by_prefix_strip( ) and not _bridges_to_responses_api(resolved_model, custom_llm_provider, deployment_model_info) +@dataclass(frozen=True, slots=True) +class _BridgeTarget: + model: str + api_key: str | None + api_base: str | None + + +def _resolve_requested_provider( + model: str, custom_llm_provider: str | None, litellm_params: GenericLiteLLMParams +) -> tuple[str, str, str | None, str | None]: + resolved: Final = litellm.get_llm_provider( + model=model, + custom_llm_provider=custom_llm_provider, + api_base=litellm_params.api_base, + api_key=litellm_params.api_key, + litellm_params=litellm_params, + ) + requested_provider: Final = model.partition("/")[0] + if ( + custom_llm_provider in (None, requested_provider) + or requested_provider not in LlmProvidersSet + or requested_provider in PROVIDERS_THAT_AUTHENTICATE_ON_PROVIDER_INFO + ): + return resolved + own: Final = _resolve_by_model_prefix(model, litellm_params) + return own if own is not None and own[1] == custom_llm_provider else resolved + + +def _resolve_by_model_prefix( + model: str, litellm_params: GenericLiteLLMParams +) -> tuple[str, str, str | None, str | None] | None: + try: + return litellm.get_llm_provider( + model=model, + api_base=litellm_params.api_base, + api_key=litellm_params.api_key, + litellm_params=litellm_params.model_copy(update={"custom_llm_provider": None}), + ) + except litellm.BadRequestError: + return None + + +def _sets_own_entra_credential(litellm_params: GenericLiteLLMParams) -> bool: + return bool( + litellm_params.azure_ad_token + or (litellm_params.model_extra or {}).get("azure_ad_token_provider") is not None + or (litellm_params.tenant_id and litellm_params.client_id and litellm_params.client_secret) + or (litellm_params.azure_username and litellm_params.azure_password and litellm_params.client_id) + ) + + +def _bridge_target(requested: _BridgeTarget, resolved: _BridgeTarget, custom_llm_provider: str) -> _BridgeTarget: + requested_provider: Final = requested.model.partition("/")[0] + if requested_provider == custom_llm_provider or requested_provider not in LlmProvidersSet: + return requested + return _BridgeTarget( + model=f"{custom_llm_provider}/{resolved.model}", + api_key=requested.api_key if requested.api_base else requested.api_key or resolved.api_key, + api_base=resolved.api_base, + ) + + def _should_route_to_responses_api( custom_llm_provider: str | None, requested_model: str | None = None, @@ -624,13 +688,7 @@ def anthropic_messages_handler( custom_llm_provider, dynamic_api_key, dynamic_api_base, - ) = litellm.get_llm_provider( - model=model, - custom_llm_provider=custom_llm_provider, - api_base=litellm_params.api_base, - api_key=litellm_params.api_key, - litellm_params=litellm_params, - ) + ) = _resolve_requested_provider(model, custom_llm_provider, litellm_params) # Store agentic loop params in logging object for agentic hooks # This provides original request context needed for follow-up calls @@ -656,6 +714,16 @@ def anthropic_messages_handler( mock_response=litellm_params.mock_response, ) + bridge: Final = _bridge_target( + _BridgeTarget(model=original_model, api_key=api_key, api_base=api_base), + _BridgeTarget( + model=model, + api_key=None if _sets_own_entra_credential(litellm_params) else dynamic_api_key, + api_base=dynamic_api_base, + ), + custom_llm_provider, + ) + # Expand litellm_proxy MCP references through the MCP gateway before dispatch, so every # downstream path (native passthrough and both bridges) gets real tools rather than a # reference the provider cannot resolve. Popped from kwargs so it never reaches the provider. @@ -682,8 +750,8 @@ def anthropic_messages_handler( top_k=top_k, top_p=top_p, container=container, - api_key=api_key, - api_base=api_base, + api_key=bridge.api_key, + api_base=bridge.api_base, client=client, custom_llm_provider=custom_llm_provider, **kwargs, @@ -700,7 +768,7 @@ def anthropic_messages_handler( return LiteLLMMessagesToResponsesAPIHandler.anthropic_messages_handler( max_tokens=max_tokens, messages=messages, - model=original_model, + model=bridge.model, metadata=metadata, stop_sequences=stop_sequences, stream=stream, @@ -716,8 +784,8 @@ def anthropic_messages_handler( top_k=top_k, top_p=top_p, _is_async=is_async, - api_key=api_key, - api_base=api_base, + api_key=bridge.api_key, + api_base=bridge.api_base, client=client, custom_llm_provider=custom_llm_provider, **kwargs, @@ -730,7 +798,7 @@ def anthropic_messages_handler( return LiteLLMMessagesToCompletionTransformationHandler.anthropic_messages_handler( max_tokens=max_tokens, messages=messages, - model=original_model, + model=bridge.model, metadata=metadata, stop_sequences=stop_sequences, stream=stream, @@ -744,8 +812,8 @@ def anthropic_messages_handler( top_k=top_k, top_p=top_p, _is_async=is_async, - api_key=api_key, - api_base=api_base, + api_key=bridge.api_key, + api_base=bridge.api_base, client=client, custom_llm_provider=custom_llm_provider, **kwargs, diff --git a/litellm/llms/anthropic/messages/responses_adapters/handler.py b/litellm/llms/anthropic/messages/responses_adapters/handler.py index 0eef3fd87c0..ec09987837c 100644 --- a/litellm/llms/anthropic/messages/responses_adapters/handler.py +++ b/litellm/llms/anthropic/messages/responses_adapters/handler.py @@ -13,6 +13,7 @@ import litellm from litellm._logging import verbose_logger from litellm.integrations.anthropic_cache_control_hook import ( AnthropicCacheControlHook, + routed_model_info, supports_openai_prompt_cache_breakpoint, ) from litellm.litellm_core_utils.asyncify import ( @@ -21,9 +22,10 @@ from litellm.litellm_core_utils.asyncify import ( from litellm.litellm_core_utils.core_helpers import as_str_mapping, drops_unsupported_params from litellm.litellm_core_utils.prompt_templates.common_utils import ( cache_control_as_prompt_cache_breakpoint, - prompt_cache_breakpoint_for_wire, + prompt_cache_breakpoint_with_readable_mode, with_prompt_cache_breakpoint, ) +from litellm.litellm_core_utils.tool_fields import drops_mcp_servers, tools_without_mcp_servers from litellm.responses.utils import auto_reasoning_summary from litellm.types.integrations.custom_logger import CONVERTED_STREAM_KEYS from litellm.types.llms.anthropic import ( @@ -186,6 +188,7 @@ def _reads_prompt_cache_breakpoint(model: str, forwarded_kwargs: Mapping[str, ob provider if isinstance(provider, str) else None, forwarded_kwargs.get("api_base") or forwarded_kwargs.get("base_url"), forwarded_kwargs.get("prompt_cache_options"), + routed_model_info(forwarded_kwargs.get("model_info")), ) @@ -193,10 +196,11 @@ def _model_takes_prompt_cache_breakpoint(model: str, forwarded_kwargs: Mapping[s provider: Final = forwarded_kwargs.get("custom_llm_provider") provider_name: Final = provider if isinstance(provider, str) else None base_model: Final = forwarded_kwargs.get("base_model") - return supports_openai_prompt_cache_breakpoint(model, provider_name) or ( + model_info: Final = routed_model_info(forwarded_kwargs.get("model_info")) + return supports_openai_prompt_cache_breakpoint(model, provider_name, model_info) or ( isinstance(base_model, str) and bool(base_model) - and supports_openai_prompt_cache_breakpoint(base_model, provider_name) + and supports_openai_prompt_cache_breakpoint(base_model, provider_name, model_info) ) @@ -207,7 +211,7 @@ def _without_prompt_cache_breakpoint(block: Mapping[str, object]) -> Mapping[str def _cache_control_as_wire_safe_prompt_cache_breakpoint(block: Mapping[str, object]) -> Mapping[str, object]: if "prompt_cache_breakpoint" not in block: return cache_control_as_prompt_cache_breakpoint(block) - wire_marker: Final = prompt_cache_breakpoint_for_wire(block["prompt_cache_breakpoint"], drop_params=True) + wire_marker: Final = prompt_cache_breakpoint_with_readable_mode(block["prompt_cache_breakpoint"], drop_params=True) return cache_control_as_prompt_cache_breakpoint( with_prompt_cache_breakpoint(_without_prompt_cache_breakpoint(block), wire_marker) ) @@ -272,6 +276,14 @@ def _build_responses_kwargs( """ forwarded_kwargs: Final = _forwarded_kwargs(extra_kwargs) reject_malformed_tool_result_text(messages, model, forwarded_kwargs) + target_provider: Final = forwarded_kwargs.get("custom_llm_provider") + request_tools: Final = tools_without_mcp_servers( + forwarded_kwargs.get("mcp_servers"), + tools or (), + model=model, + route=target_provider if isinstance(target_provider, str) else "this route", + drop_params=drops_mcp_servers(forwarded_kwargs), + ) block_rewrite: Final = _prompt_cache_block_rewrite(model, forwarded_kwargs) request_messages: Final[AnthropicRequestMessages] = ( [ @@ -304,10 +316,10 @@ def _build_responses_kwargs( request_data["temperature"] = temperature if thinking: request_data["thinking"] = thinking - if tool_choice: + if tool_choice and (request_tools or not tools): request_data["tool_choice"] = tool_choice - if tools: - request_data["tools"] = tools + if request_tools: + request_data["tools"] = list(request_tools) if top_p is not None: request_data["top_p"] = top_p if output_format: @@ -347,7 +359,7 @@ def _build_responses_kwargs( responses_kwargs["stream"] = True # Forward litellm-specific kwargs (api_key, api_base, logging obj, etc.) - excluded: Final = CONVERTED_STREAM_KEYS | {"anthropic_messages"} + excluded: Final = CONVERTED_STREAM_KEYS | {"anthropic_messages", "mcp_servers"} for key, value in forwarded_kwargs.items(): if key == "litellm_logging_obj" and value is not None: from litellm.litellm_core_utils.litellm_logging import ( diff --git a/litellm/llms/anthropic/messages/responses_adapters/streaming_iterator.py b/litellm/llms/anthropic/messages/responses_adapters/streaming_iterator.py index dae96ba4ce1..f0c3316c509 100644 --- a/litellm/llms/anthropic/messages/responses_adapters/streaming_iterator.py +++ b/litellm/llms/anthropic/messages/responses_adapters/streaming_iterator.py @@ -141,6 +141,8 @@ class AnthropicResponsesStreamWrapper: if litellm_logging_obj is not None: litellm_logging_obj.record_streamed_anthropic_message_id(self._message_id) self._unreported_failure: Exception | None = None + # The failure behind this stream's error frame, for a router that accounts for it. + self.stream_failure: Exception | None = None self._current_block_index: int = -1 # Map item_id -> content_block_index so we can stop the right block later self._item_id_to_block_index: dict[str, int] = {} @@ -467,6 +469,7 @@ class AnthropicResponsesStreamWrapper: llm_provider=getattr(self.responses_stream, "custom_llm_provider", None), model=self.model, ) + self.stream_failure = self._unreported_failure self._chunk_queue.append(_anthropic_error_chunk(status_code, message)) async def _report_unreported_failure(self) -> None: @@ -578,5 +581,9 @@ class AnthropicResponsesSSEByteStream: async def aclose(self) -> None: await self._frames.aclose() + @property + def stream_failure(self) -> Exception | None: + return self._wrapper.stream_failure + def partial_response_on_disconnect(self) -> "ResponseIncompleteEvent | None": return self._wrapper.partial_response_on_disconnect() diff --git a/litellm/llms/aws_polly/text_to_speech/transformation.py b/litellm/llms/aws_polly/text_to_speech/transformation.py index 325c9fd364d..3b52a8df3f2 100644 --- a/litellm/llms/aws_polly/text_to_speech/transformation.py +++ b/litellm/llms/aws_polly/text_to_speech/transformation.py @@ -178,7 +178,6 @@ class AWSPollyTextToSpeechConfig(BaseTextToSpeechConfig, BaseAWSLLM): else: mapped_params["output_format"] = self.DEFAULT_OUTPUT_FORMAT - # model arrives without the "aws_polly/" prefix, e.g. "standard" engine: Final = self._extract_engine_from_model(model) mapped_params["engine"] = engine diff --git a/litellm/llms/azure/audio_transcriptions.py b/litellm/llms/azure/audio_transcriptions.py index df8a0614665..386815412b5 100644 --- a/litellm/llms/azure/audio_transcriptions.py +++ b/litellm/llms/azure/audio_transcriptions.py @@ -1,11 +1,17 @@ -from collections.abc import Coroutine +from collections.abc import Coroutine, Mapping from typing import TYPE_CHECKING, Final -from openai import AsyncAzureOpenAI, AzureOpenAI +from openai import AsyncAzureOpenAI, AsyncStream, AzureOpenAI, Stream +from openai.types.audio import TranscriptionStreamEvent from pydantic import BaseModel from litellm._uuid import uuid from litellm.litellm_core_utils.audio_utils.utils import get_audio_file_name +from litellm.llms.base_llm.audio_transcription.transformation import ( + acreate_sdk_transcription, + create_sdk_transcription, + sdk_compatible_transcription_request_data, +) from litellm.types.utils import FileTypes from litellm.utils import ( TranscriptionResponse, @@ -38,13 +44,18 @@ class AzureAudioTranscription(AzureChatCompletion): atranscription: bool = False, litellm_params: dict | None = None, custom_llm_provider: str = "azure", - ) -> TranscriptionResponse | Coroutine[object, object, TranscriptionResponse]: + ) -> ( + TranscriptionResponse + | Stream[TranscriptionStreamEvent] + | Coroutine[object, object, TranscriptionResponse | AsyncStream[TranscriptionStreamEvent]] + ): data: Final = {"model": model, "file": audio_file, **optional_params} + sdk_data: Final = sdk_compatible_transcription_request_data(data) if atranscription is True: return self.async_audio_transcriptions( audio_file=audio_file, - data=data, + data=sdk_data, model_response=model_response, timeout=timeout, api_key=api_key, @@ -58,7 +69,7 @@ class AzureAudioTranscription(AzureChatCompletion): ) azure_client: Final = self.get_azure_openai_client( - api_version=api_version, + api_version=None if self.is_azure_v1_api_version(api_version) else api_version, api_base=api_base, api_key=api_key, model=model, @@ -84,10 +95,9 @@ class AzureAudioTranscription(AzureChatCompletion): }, ) - response: Final = azure_client.audio.transcriptions.create( - **data, - timeout=timeout, - ) + _, response = create_sdk_transcription(azure_client, sdk_data, timeout) + if isinstance(response, Stream): + return response if isinstance(response, BaseModel): stringified_response = response.model_dump() @@ -114,7 +124,7 @@ class AzureAudioTranscription(AzureChatCompletion): self, audio_file: FileTypes, model: str, - data: dict, + data: Mapping[str, object], model_response: TranscriptionResponse, timeout: float, logging_obj: "LiteLLMLoggingObj", @@ -125,7 +135,7 @@ class AzureAudioTranscription(AzureChatCompletion): max_retries=None, litellm_params: dict | None = None, custom_llm_provider: str = "azure", - ) -> TranscriptionResponse: + ) -> TranscriptionResponse | AsyncStream[TranscriptionStreamEvent]: response = None try: async_azure_client: Final = self.get_azure_openai_client( @@ -155,12 +165,9 @@ class AzureAudioTranscription(AzureChatCompletion): }, ) - raw_response: Final = await async_azure_client.audio.transcriptions.with_raw_response.create( - **data, timeout=timeout - ) - - headers: Final = dict(raw_response.headers) - response = raw_response.parse() + headers, response = await acreate_sdk_transcription(async_azure_client, data, timeout) + if isinstance(response, AsyncStream): + return response if isinstance(response, BaseModel): stringified_response = response.model_dump() diff --git a/litellm/llms/azure/chat/gpt_reasoning_transformation.py b/litellm/llms/azure/chat/gpt_reasoning_transformation.py index 72a0500e0af..29305866e23 100644 --- a/litellm/llms/azure/chat/gpt_reasoning_transformation.py +++ b/litellm/llms/azure/chat/gpt_reasoning_transformation.py @@ -1,6 +1,6 @@ """Support for Azure OpenAI gpt-5 model family.""" -from collections.abc import Collection +from collections.abc import Collection, Mapping from typing import ClassVar, Final import litellm @@ -105,7 +105,7 @@ class AzureOpenAIGPT5Config(AzureOpenAIConfig, OpenAIGPT5Config): model: str, messages: list[AllMessageValues], optional_params: dict, - litellm_params: dict, + litellm_params: Mapping[str, object], headers: dict, ) -> dict: model = model.replace(self.GPT5_SERIES_ROUTE, "") diff --git a/litellm/llms/azure/chat/gpt_transformation.py b/litellm/llms/azure/chat/gpt_transformation.py index 990c8869de3..0fe7caa1e16 100644 --- a/litellm/llms/azure/chat/gpt_transformation.py +++ b/litellm/llms/azure/chat/gpt_transformation.py @@ -1,16 +1,26 @@ from collections.abc import Mapping, Sequence from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final +from typing import ( + TYPE_CHECKING, + Any, + Final, + cast, # noqa: TID251 # non_default_params reaches the mapper as an untyped dict +) from httpx._models import Headers, Response import litellm +from litellm.integrations.anthropic_cache_control_hook import deployment_prompt_cache_breakpoint_support +from litellm.litellm_core_utils.allowed_tools_tool_choice import is_allowed_tools_tool_choice +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.litellm_core_utils.prompt_templates.common_utils import ( + chat_completion_prompt_cache_breakpoints_for_wire, drop_tool_reference_parts_from_tool_messages, flatten_combinators_and_drop_non_python_regex_patterns, hoist_images_from_tool_messages, system_messages_first, tool_with_sanitized_parameters, + without_prompt_cache_breakpoints, ) from litellm.litellm_core_utils.prompt_templates.factory import ( convert_to_azure_openai_messages, @@ -241,12 +251,12 @@ class AzureOpenAIConfig(BaseConfig): or (api_version_year == "2023" and api_version_month < "12") or (api_version_year == "2023" and api_version_month == "12" and api_version_day < "01") ): - if litellm.drop_params is True or (drop_params is not None and drop_params is True): - pass - else: + if is_allowed_tools_tool_choice( + cast(object, value) # cast-ok: widening an untyped dict value to object is always sound + ) or not (litellm.drop_params is True or (drop_params is not None and drop_params is True)): raise UnsupportedParamsError( status_code=400, - message=f"""Azure does not support 'tool_choice', for api_version={api_version}. Bump your API version to '2023-12-01-preview' or later. This parameter requires 'api_version="2023-12-01-preview"' or later. Azure API Reference: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions""", + message=f"""Azure does not support 'tool_choice', for api_version={api_version}. Bump your API version to '2023-12-01-preview' or later. This parameter requires 'api_version="2023-12-01-preview"' or later. drop_params never drops an allowed_tools tool_choice, since that would let the model call tools the request excluded. Azure API Reference: https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions""", ) elif value == "required" and ( api_version_year == "2024" and api_version_month <= "05" @@ -290,11 +300,16 @@ class AzureOpenAIConfig(BaseConfig): model: str, messages: list[AllMessageValues], optional_params: dict, - litellm_params: dict, + litellm_params: Mapping[str, object], headers: dict, ) -> dict: ordered_messages: Final = system_messages_first(messages) if litellm.openai_system_messages_first else messages - stripped_messages: Final = drop_tool_reference_parts_from_tool_messages(ordered_messages) + wire_messages: Final = ( + self._with_wire_safe_prompt_cache_breakpoints(model, ordered_messages, litellm_params) + if drops_unsupported_params(litellm_params.get("drop_params")) + else ordered_messages + ) + stripped_messages: Final = drop_tool_reference_parts_from_tool_messages(wire_messages) azure_messages: Final = convert_to_azure_openai_messages(hoist_images_from_tool_messages(stripped_messages)) request_params: Final = MappingProxyType( { @@ -310,6 +325,14 @@ class AzureOpenAIConfig(BaseConfig): **sanitized_tools_update(optional_params), } + @staticmethod + def _with_wire_safe_prompt_cache_breakpoints( + model: str, messages: list[AllMessageValues], litellm_params: Mapping[str, object] + ) -> list[AllMessageValues]: + if deployment_prompt_cache_breakpoint_support(model, "azure", litellm_params) is False: + return [without_prompt_cache_breakpoints(message) for message in messages] + return [chat_completion_prompt_cache_breakpoints_for_wire(message, drop_params=True) for message in messages] + def transform_response( self, model: str, diff --git a/litellm/llms/azure/common_utils.py b/litellm/llms/azure/common_utils.py index 6bb6d584385..16c8bf6f9f1 100644 --- a/litellm/llms/azure/common_utils.py +++ b/litellm/llms/azure/common_utils.py @@ -1,15 +1,16 @@ import asyncio import hashlib +import itertools import json import os import re -from collections.abc import Awaitable, Callable, Mapping +from collections.abc import Awaitable, Callable, Iterator, Mapping from contextlib import closing from types import MappingProxyType -from typing import Final, Literal, NamedTuple, cast +from typing import Final, Literal, NamedTuple, NoReturn, cast import httpx -from openai import AsyncAzureOpenAI, AsyncOpenAI, AzureOpenAI, OpenAI +from openai import APIError, AsyncAzureOpenAI, AsyncOpenAI, AzureOpenAI, OpenAI from pydantic import ConfigDict, TypeAdapter, with_config from typing_extensions import ReadOnly, TypedDict @@ -20,7 +21,7 @@ from litellm.constants import DEFAULT_MAX_RETRIES from litellm.litellm_core_utils.single_flight import SingleFlight, single_flight_lru_cache from litellm.litellm_core_utils.url_utils import ensure_api_route from litellm.llms.base_llm.chat.transformation import BaseLLMException -from litellm.llms.custom_httpx.http_handler import HTTPHandler +from litellm.llms.custom_httpx.http_handler import HTTPHandler, MaskedHTTPStatusError from litellm.llms.openai.common_utils import BaseOpenAILLM, OpenAIAsyncHTTPClient, OpenAIHTTPClient from litellm.secret_managers.get_azure_ad_token_provider import ( get_azure_ad_token_provider, @@ -52,6 +53,13 @@ class _AsyncAzureClientParams(TypedDict, total=False, extra_items=object): _ASYNC_AZURE_CLIENT_PARAMS_ADAPTER: Final = TypeAdapter(_AsyncAzureClientParams) +_AZURE_AD_TOKEN_PROVIDER_ADAPTER: Final = TypeAdapter[Callable[[], str | Awaitable[str]] | None]( + Callable[[], str | Awaitable[str]] | None +) + + +def _callable_azure_ad_token_provider(provider: object) -> Callable[[], str | Awaitable[str]] | None: + return _AZURE_AD_TOKEN_PROVIDER_ADAPTER.validate_python(provider) if callable(provider) else None class _AzureGatewayClientParams(TypedDict, total=False, extra_items=object): @@ -81,6 +89,160 @@ class AzureOpenAIError(BaseLLMException): ) +class EntraRejectionError(AzureOpenAIError): + pass + + +_GUID: Final = re.compile(r"[0-9a-fA-F]{8}-(?:[0-9a-fA-F]{4}-){3}[0-9a-fA-F]{12}") +_AADSTS_REASON: Final = re.compile(r"\bAADSTS(\d+)\b.*?(?:\.(?=[\s'\"\\]|$)|$)", re.MULTILINE) +_ENTRA_CREDENTIAL_REJECTION_CODES: Final = frozenset( + { + 50012, + 50013, + 50027, + 50034, + 50053, + 50055, + 50057, + 50059, + 50076, + 50079, + 50126, + 50128, + 53003, + 65001, + 70001, + 70002, + 70011, + 70021, + 70025, + 70052, + 90002, + 90094, + 500011, + 500014, + 700016, + 700023, + 700024, + 700025, + 700027, + 700211, + 700213, + 700223, + 700238, + 7000112, + 7000215, + 7000218, + 7000222, + } +) + + +def _entra_rejection_reason(message: str) -> str | None: + reason: Final = _AADSTS_REASON.search(message) + if reason is None or int(reason.group(1)) not in _ENTRA_CREDENTIAL_REJECTION_CODES: + return None + return _GUID.sub("", reason.group(0)) + + +def _entra_rejection(reason: str) -> EntraRejectionError: + return EntraRejectionError(status_code=401, message=f"Failed to get Azure AD token: {reason}") + + +def entra_rejection_as_auth_error(error: Exception) -> EntraRejectionError | None: + try: + from azure.core.exceptions import ClientAuthenticationError + except ImportError: + return None + if not isinstance(error, ClientAuthenticationError): + return None + status_code: Final = error.status_code + if status_code is not None and (status_code == 429 or status_code >= 500): + return None + reason: Final = _entra_rejection_reason(str(error)) + return None if reason is None else _entra_rejection(reason) + + +def _raise_entra_rejection_as_auth_error(error: Exception) -> NoReturn: + auth_error: Final = entra_rejection_as_auth_error(error) + if auth_error is None: + raise error + raise auth_error from error + + +def entra_token(provider: Callable[[], str]) -> str: + try: + return provider() + except entra_rejection_types() as error: + _raise_entra_rejection_as_auth_error(error) + + +def entra_rejection_types() -> tuple[type[Exception], ...]: + try: + from azure.core.exceptions import ClientAuthenticationError + except ImportError: + return () + return (ClientAuthenticationError,) + + +_EXCEPTION_CHAIN_MAX_DEPTH: Final = 16 + + +def _exception_chain(error: BaseException) -> Iterator[BaseException]: + link: BaseException | None = error # rebind-ok: advances one link of the cause chain per iteration + for _ in range(_EXCEPTION_CHAIN_MAX_DEPTH): + if link is None: + return + yield link + link = link.__cause__ or link.__context__ + + +_REQUEST_FAILURE_TYPES: Final = (APIError, httpx.HTTPError) + + +def _ends_the_failed_attempt(link: BaseException, failed_attempt: BaseException) -> bool: + return not isinstance(link, EntraRejectionError) and ( + isinstance(link, _REQUEST_FAILURE_TYPES) or type(link) is type(failed_attempt) + ) + + +def _links_within_the_failed_attempt(error: BaseException) -> Iterator[BaseException]: + yield error + yield from itertools.takewhile( + lambda link: not _ends_the_failed_attempt(link, error), itertools.islice(_exception_chain(error), 1, None) + ) + + +def entra_rejection_in(error: BaseException) -> EntraRejectionError | None: + return next( + (link for link in _links_within_the_failed_attempt(error) if isinstance(link, EntraRejectionError)), None + ) + + +def caused_by_entra_rejection(error: BaseException) -> bool: + return entra_rejection_in(error) is not None + + +async def _awaited_token(token: Awaitable[str]) -> str: + try: + return await token + except entra_rejection_types() as error: + _raise_entra_rejection_as_auth_error(error) + + +def _entra_rejections_as_auth_errors( + provider: Callable[[], str | Awaitable[str]], +) -> Callable[[], str | Awaitable[str]]: + def call_provider() -> str | Awaitable[str]: + try: + token: Final = provider() + except entra_rejection_types() as error: + _raise_entra_rejection_as_auth_error(error) + return token if isinstance(token, str) else _awaited_token(token) + + return call_provider + + def process_azure_headers(headers: httpx.Headers | dict) -> dict: openai_headers: Final = {} if "x-ratelimit-limit-requests" in headers: @@ -91,7 +253,7 @@ def process_azure_headers(headers: httpx.Headers | dict) -> dict: openai_headers["x-ratelimit-limit-tokens"] = headers["x-ratelimit-limit-tokens"] if "x-ratelimit-remaining-tokens" in headers: openai_headers["x-ratelimit-remaining-tokens"] = headers["x-ratelimit-remaining-tokens"] - llm_response_headers: Final = {"{}-{}".format("llm_provider", k): v for k, v in headers.items()} + llm_response_headers: Final = {f"llm_provider-{k}": v for k, v in headers.items()} return {**llm_response_headers, **openai_headers} @@ -257,22 +419,34 @@ def _cached_oidc_token(cache_key: str) -> str | None: return cached if isinstance(cached, str) else None +def _oidc_exchange_rejection_reason(error: MaskedHTTPStatusError) -> str | None: + if error.response.status_code not in (400, 401): + return None + return _entra_rejection_reason(error.text or error.response.text) + + def _exchange_oidc_token(cache_key: str, token_url: str, client_id: str, scope: str, oidc_token: str) -> str: cached_access_token: Final = _cached_oidc_token(cache_key) if cached_access_token is not None: return cached_access_token with closing(HTTPHandler(timeout=litellm.request_timeout)) as client: - req_token: Final = client.post( - token_url, - data={ - "client_id": client_id, - "grant_type": "client_credentials", - "scope": scope, - "client_assertion_type": "urn:ietf:params:oauth:client-assertion-type:jwt-bearer", - "client_assertion": oidc_token, - }, - ) + try: + req_token: Final = client.post( + token_url, + data={ + "client_id": client_id, + "grant_type": "client_credentials", + "scope": scope, + "client_assertion_type": "urn:ietf:params:oauth:client-assertion-type:jwt-bearer", + "client_assertion": oidc_token, + }, + ) + except MaskedHTTPStatusError as error: + reason: Final = _oidc_exchange_rejection_reason(error) + if reason is None: + raise + raise _entra_rejection(reason) from error if req_token.status_code != 200: raise AzureOpenAIError( @@ -483,6 +657,9 @@ def get_azure_ad_token( raise except Exception as e: verbose_logger.error("Error calling Azure AD token provider: %s", e) + auth_error: Final = entra_rejection_as_auth_error(e) + if auth_error is not None: + raise auth_error from e raise RuntimeError(f"Failed to get Azure AD token: {e}") from e return azure_ad_token @@ -696,7 +873,7 @@ class BaseAzureLLM(BaseOpenAILLM): api_version: str | None, is_async: bool, ) -> dict: - azure_ad_token_provider = litellm_params.get("azure_ad_token_provider") + azure_ad_token_provider = _callable_azure_ad_token_provider(litellm_params.get("azure_ad_token_provider")) # If we have api_key, then we have higher priority azure_ad_token = litellm_params.get("azure_ad_token") @@ -775,7 +952,7 @@ class BaseAzureLLM(BaseOpenAILLM): azure_client_params["timeout"] = timeout if azure_ad_token_provider is not None: - azure_client_params["azure_ad_token_provider"] = azure_ad_token_provider + azure_client_params["azure_ad_token_provider"] = _entra_rejections_as_auth_errors(azure_ad_token_provider) # this decides if we should set azure_endpoint or base_url on Azure OpenAI Client # required to support GPT-4 vision enhancements, since base_url needs to be set on Azure OpenAI Client diff --git a/litellm/llms/azure/decisions/transformation.py b/litellm/llms/azure/decisions/transformation.py index 3fb40e39702..bdbd784185f 100644 --- a/litellm/llms/azure/decisions/transformation.py +++ b/litellm/llms/azure/decisions/transformation.py @@ -8,6 +8,7 @@ import litellm from litellm.llms.azure.common_utils import ( BaseAzureLLM, cached_azure_ad_token_refresh_provider, + entra_token, ) from litellm.llms.openai.decisions.transformation import OpenAIDecisionsConfig from litellm.secret_managers.main import get_secret_str @@ -61,7 +62,7 @@ class AzureDecisionsConfig(OpenAIDecisionsConfig): scope: Final = ( params.azure_scope or get_secret_str("AZURE_SCOPE") or "https://cognitiveservices.azure.com/.default" ) - azure_headers["Authorization"] = f"Bearer {cached_azure_ad_token_refresh_provider(scope)()}" + azure_headers["Authorization"] = f"Bearer {entra_token(cached_azure_ad_token_refresh_provider(scope))}" return azure_headers async def avalidate_environment( diff --git a/litellm/llms/azure/realtime/handler.py b/litellm/llms/azure/realtime/handler.py index 3d4576fd7ac..16ec4249244 100644 --- a/litellm/llms/azure/realtime/handler.py +++ b/litellm/llms/azure/realtime/handler.py @@ -5,9 +5,11 @@ This requires websockets, and is currently only supported on LiteLLM Proxy. """ from collections.abc import Mapping +from dataclasses import dataclass from types import MappingProxyType from typing import Final, Protocol, cast +import litellm from litellm._logging import verbose_proxy_logger from litellm.constants import REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES from litellm.litellm_core_utils.url_utils import join_api_base @@ -48,17 +50,55 @@ async def forward_messages(client_ws: _RealtimeTextSink, backend_ws: _RealtimeTe pass +def azure_realtime_requires_ga(model: str) -> bool: + try: + azure_model_info: Final = litellm.get_model_info(model=model, custom_llm_provider="azure") + except Exception: # noqa: BLE001 # unmapped deployments can select a protocol explicitly + try: + openai_model_info: Final = litellm.get_model_info(model=model, custom_llm_provider="openai") + except Exception: # noqa: BLE001 # unmapped deployments can select a protocol explicitly + return False + openai_entry: Final = openai_model_info.get("provider_specific_entry") + return openai_entry is not None and openai_entry.get("realtime_ga_only") == 1 + azure_entry: Final = azure_model_info.get("provider_specific_entry") + return azure_entry is not None and azure_entry.get("realtime_ga_only") == 1 + + +def _is_ga_protocol(protocol: str | None) -> bool: + return protocol is not None and protocol.upper() in ("GA", "V1") + + +@dataclass(frozen=True, slots=True) +class AzureRealtimeProtocol: + name: str + bridges_beta_client_to_ga: bool = False + + def azure_realtime_protocol_for_client( configured_protocol: object, *, + model: str, + base_model: str | None = None, + realtime_mode: str, query_params: RealtimeQueryParams | None, websocket: ScopedWebSocket, -) -> str: +) -> AzureRealtimeProtocol: + serves_a_ga_only_session: Final = ( + realtime_mode == "translation" or (query_params or {}).get("intent") == "transcription" + ) + client_wants_beta: Final = client_sent_openai_beta_realtime_header(websocket) if isinstance(configured_protocol, str) and configured_protocol: - return configured_protocol - if (query_params or {}).get("intent") == "transcription": - return "GA" - return "beta" if client_sent_openai_beta_realtime_header(websocket) else "GA" + return AzureRealtimeProtocol( + name=configured_protocol, + bridges_beta_client_to_ga=client_wants_beta + and not serves_a_ga_only_session + and _is_ga_protocol(configured_protocol), + ) + if serves_a_ga_only_session: + return AzureRealtimeProtocol(name="GA") + if azure_realtime_requires_ga(base_model or model): + return AzureRealtimeProtocol(name="GA", bridges_beta_client_to_ga=client_wants_beta) + return AzureRealtimeProtocol(name="beta" if client_wants_beta else "GA") class _ProxyClientWebSocket(Protocol): @@ -92,6 +132,7 @@ class AzureOpenAIRealtime(AzureChatCompletion): api_version: str | None, realtime_protocol: str | None = None, query_params: RealtimeQueryParams | None = None, + realtime_mode: str = "realtime", ) -> str: """ Construct Azure realtime WebSocket URL. @@ -104,6 +145,7 @@ class AzureOpenAIRealtime(AzureChatCompletion): - "GA" or "v1": Uses /openai/v1/realtime (GA path) - "beta" or None: Uses /openai/realtime (beta path, default) query_params: Extra query params to forward (e.g. intent=transcription). + realtime_mode: Realtime surface to target, "realtime" or "translation". Returns: WebSocket URL string @@ -117,24 +159,29 @@ class AzureOpenAIRealtime(AzureChatCompletion): api_base = api_base.replace("https://", "wss://") # Determine path based on realtime_protocol (case-insensitive) - _is_ga: Final = realtime_protocol is not None and realtime_protocol.upper() in ( - "GA", - "V1", - ) + _is_ga: Final = _is_ga_protocol(realtime_protocol) intent: Final = (query_params or {}).get("intent") - if _is_ga: - path = "/openai/v1/realtime" - query_parts = [] - if intent != "transcription" and (query_params is None or "model" in query_params): - query_parts.append(urlencode({"model": model})) - else: - # Default to beta path for backwards compatibility - path = "/openai/realtime" - query_parts = [urlencode({"api-version": api_version, "deployment": model})] + path: Final = ( + "/openai/v1/realtime/translations" + if realtime_mode == "translation" + else "/openai/v1/realtime" + if _is_ga + else "/openai/realtime" + ) + base_query_parts: Final = ( + (urlencode((("model", model),)),) + if realtime_mode == "translation" + else ( + (urlencode((("model", model),)),) + if intent != "transcription" and (query_params is None or "model" in query_params) + else () + ) + if _is_ga + else (urlencode((("api-version", api_version), ("deployment", model))),) + ) - if intent: - query_parts.append(urlencode({"intent": intent})) + query_parts: Final = (*base_query_parts, urlencode((("intent", intent),))) if intent else base_query_parts qs: Final = "&".join(query_parts) endpoint_url: Final = join_api_base(api_base, path) @@ -165,13 +212,16 @@ class AzureOpenAIRealtime(AzureChatCompletion): query_params: RealtimeQueryParams | None = None, user_api_key_dict: object | None = None, litellm_metadata: dict | None = None, + realtime_mode: str = "realtime", + bridges_beta_client_to_ga: bool = False, + drop_params: bool = False, ): import websockets from websockets.asyncio.client import ClientConnection if api_base is None: raise ValueError("api_base is required for Azure OpenAI calls") - backend_uses_beta_protocol: Final = realtime_protocol is None or realtime_protocol.upper() not in ("GA", "V1") + backend_uses_beta_protocol: Final = not _is_ga_protocol(realtime_protocol) if api_version is None and backend_uses_beta_protocol: raise ValueError("api_version is required for Azure OpenAI calls") @@ -181,6 +231,7 @@ class AzureOpenAIRealtime(AzureChatCompletion): api_version, realtime_protocol=realtime_protocol, query_params=query_params, + realtime_mode=realtime_mode, ) auth_headers: Final = self.get_auth_headers(api_key=api_key, azure_ad_token=azure_ad_token) @@ -204,6 +255,9 @@ class AzureOpenAIRealtime(AzureChatCompletion): force_transcription_model=( model if (query_params or {}).get("intent") == "transcription" else None ), + translation_session=realtime_mode == "translation", + bridges_beta_client_to_ga=bridges_beta_client_to_ga, + drop_params=drop_params, ) await realtime_streaming.bidirectional_forward() diff --git a/litellm/llms/azure/realtime/http_transformation.py b/litellm/llms/azure/realtime/http_transformation.py index 545c3348182..64051b2c3c9 100644 --- a/litellm/llms/azure/realtime/http_transformation.py +++ b/litellm/llms/azure/realtime/http_transformation.py @@ -1,11 +1,20 @@ """Azure OpenAI realtime HTTP transformation config (client_secrets + realtime_calls).""" +from collections.abc import Mapping from typing import Final import litellm from litellm.litellm_core_utils.url_utils import join_api_base +from litellm.llms.azure.common_utils import get_azure_ad_token from litellm.llms.base_llm.realtime.http_transformation import BaseRealtimeHTTPConfig from litellm.secret_managers.main import get_secret_str +from litellm.types.router import GenericLiteLLMParams + +_CALLER_AUTH_HEADERS: Final = frozenset({"authorization", "api-key"}) + + +def _azure_resource_base(api_base: str) -> str: + return api_base.rstrip("/").removesuffix("/openai/v1").removesuffix("/openai") def _azure_realtime_v1_url(api_base: str, endpoint: str) -> str: @@ -21,6 +30,19 @@ class AzureRealtimeHTTPConfig(BaseRealtimeHTTPConfig): def get_api_key(self, api_key: str | None, **kwargs: object) -> str: return api_key or litellm.api_key or get_secret_str("AZURE_API_KEY") or "" + def get_extra_headers( + self, + litellm_params: GenericLiteLLMParams, + api_key: str, + extra_headers: Mapping[str, object] | None, + ) -> Mapping[str, object] | None: + if api_key or any(name.lower() in _CALLER_AUTH_HEADERS for name in extra_headers or {}): + return extra_headers + azure_ad_token: Final = get_azure_ad_token(litellm_params) + if azure_ad_token is None: + return extra_headers + return {**(extra_headers or {}), "Authorization": f"Bearer {azure_ad_token}"} + def get_complete_url(self, api_base: str | None, model: str, api_version: str | None = None) -> str: return _azure_realtime_v1_url(self.get_api_base(api_base), "client_secrets") @@ -30,20 +52,30 @@ class AzureRealtimeHTTPConfig(BaseRealtimeHTTPConfig): model: str, api_key: str | None = None, ) -> dict: - return { + validated_headers: Final = { **headers, - "api-key": api_key or "", "Content-Type": "application/json", } + if api_key: + validated_headers["api-key"] = api_key + return validated_headers def get_realtime_calls_url(self, api_base: str | None, model: str, api_version: str | None = None) -> str: return _azure_realtime_v1_url(self.get_api_base(api_base), "calls") def get_transcription_session_url(self, api_base: str | None, model: str, api_version: str | None = None) -> str: - base: Final = self.get_api_base(api_base) + base: Final = _azure_resource_base(self.get_api_base(api_base)) version: Final = api_version or get_secret_str("AZURE_API_VERSION") or "2024-12-17" return f"{join_api_base(base, 'openai/realtime/transcription_sessions')}?api-version={version}" + def get_translation_client_secret_url( + self, api_base: str | None, model: str, api_version: str | None = None + ) -> str: + return _azure_realtime_v1_url(self.get_api_base(api_base), "translations/client_secrets") + + def get_translation_calls_url(self, api_base: str | None, model: str, api_version: str | None = None) -> str: + return _azure_realtime_v1_url(self.get_api_base(api_base), "translations/calls") + def get_realtime_calls_headers(self, ephemeral_key: str) -> dict[str, str]: return { "Authorization": f"Bearer {ephemeral_key}", diff --git a/litellm/llms/azure/responses/transformation.py b/litellm/llms/azure/responses/transformation.py index 2b757bb10d9..f95dc1e4388 100644 --- a/litellm/llms/azure/responses/transformation.py +++ b/litellm/llms/azure/responses/transformation.py @@ -1,19 +1,21 @@ import re -from collections.abc import Mapping +from collections.abc import Callable, Mapping from copy import deepcopy +from functools import partial from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final, Literal +from typing import TYPE_CHECKING, Any, Final, Literal, cast from urllib.parse import urlsplit import httpx -from openai.types.responses import ResponseReasoningItem from pydantic import TypeAdapter from litellm._logging import verbose_logger from litellm.constants import AZURE_DEFAULT_RESPONSES_API_VERSION +from litellm.litellm_core_utils.prompt_templates.common_utils import prompt_cache_breakpoint_within from litellm.litellm_core_utils.url_utils import encode_url_path_segment from litellm.llms.azure.chat.gpt_reasoning_transformation import AzureOpenAIGPT5Config from litellm.llms.azure.common_utils import BaseAzureLLM +from litellm.llms.azure.ptu_capacity import is_str_keyed_mapping from litellm.llms.base_llm.responses.transformation import SUMMARY_ONLY_REASONING_FIELD_VALUES, ReasoningFieldValues from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig from litellm.types.llms.openai import * @@ -29,6 +31,7 @@ else: LiteLLMLoggingObj = Any _DECODED_JSON: Final = TypeAdapter(object) +_AZURE_RESPONSES_PROMPT_CACHE_BREAKPOINT: Final = TypeAdapter(AzureResponsesPromptCacheBreakpoint) _DATED_GA_API_VERSION: Final = re.compile(r"\d{4}-\d{2}-\d{2}") @@ -69,6 +72,21 @@ def _with_responses_api_version(api_base: str | None, litellm_params: Mapping[st return MappingProxyType({**litellm_params, "api_version": _resolve_responses_api_version(api_base, litellm_params)}) +_AZURE_REJECTED_INPUT_FIELDS: Final = MappingProxyType( + {"message": frozenset({"status"}), "reasoning": frozenset({"status"})} +) +_AZURE_REJECTED_INPUT_FIELDS_UNDER_DROP_PARAMS: Final = MappingProxyType( + {**_AZURE_REJECTED_INPUT_FIELDS, "reasoning": frozenset({"status", "content"})} +) + + +def _without_fields_azure_rejects(item: object, rejected_fields: Mapping[str, frozenset[str]]) -> object: + if not is_str_keyed_mapping(item): + return item + rejected: Final = rejected_fields.get(str(item.get("type")), frozenset()) + return {key: value for key, value in item.items() if key not in rejected} if rejected else item + + class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): # Parameters not supported by Azure Responses API AZURE_UNSUPPORTED_PARAMS = ["context_management"] @@ -81,6 +99,13 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): def _is_gpt_5_model(model: str) -> bool: return AzureOpenAIGPT5Config.is_model_gpt_5_model(model) + def _prompt_cache_breakpoint_to_wire( + self, litellm_params: GenericLiteLLMParams, reads_breakpoints: bool, known_support: bool | None + ) -> Callable[[object], object]: + if reads_breakpoints or known_support is True: + return partial(prompt_cache_breakpoint_within, _AZURE_RESPONSES_PROMPT_CACHE_BREAKPOINT) + return super()._prompt_cache_breakpoint_to_wire(litellm_params, reads_breakpoints, known_support) + @staticmethod def _supports_reasoning_effort_none(model: str) -> bool: return AzureOpenAIGPT5Config.supports_reasoning_effort_level(model, "none") @@ -112,68 +137,17 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig): def get_stripped_model_name(self, model: str) -> str: return model.replace("responses/", "").replace("o_series/", "").replace("azure_ai/", "") - def _handle_reasoning_item(self, item: dict[str, Any]) -> Mapping[str, object]: - """ - Handle reasoning items to filter out the status field. - Issue: https://github.com/BerriAI/litellm/issues/13484 - - Azure OpenAI API does not accept 'status' field in reasoning input items. - """ - if item.get("type") == "reasoning": - try: - # Ensure required fields are present for ResponseReasoningItem - item_data: Final = dict(item) - if "summary" not in item_data: - item_data["summary"] = ( - item_data.get("reasoning_content", "")[:100] + "..." - if len(item_data.get("reasoning_content", "")) > 100 - else item_data.get("reasoning_content", "") - ) - - # Create ResponseReasoningItem object from the item data - reasoning_item: Final = ResponseReasoningItem.model_validate(item_data) - - # Convert back to dict with exclude_none=True to exclude None fields - dict_reasoning_item: Final = reasoning_item.model_dump(exclude_none=True) - dict_reasoning_item.pop("status", None) - - return dict_reasoning_item - except Exception as e: - verbose_logger.debug("Failed to create ResponseReasoningItem, falling back to manual filtering: %s", e) - # Fallback: manually filter out known None fields - filtered_item: Final = { - k: v - for k, v in item.items() - if v is not None or k not in {"status", "content", "encrypted_content"} - } - return filtered_item - return item - def _validate_input_param( - self, input: str | ResponseInputParam, *, drops_set_created_by: bool = False + self, input: str | ResponseInputParam, *, drop_params: bool = False ) -> str | ResponseInputParam: - """ - Override parent method to also filter out 'status' field from message items. - Azure OpenAI API does not accept 'status' field in input messages. - """ - from typing import cast - - # First call parent's validation - validated_input: Final = super()._validate_input_param(input, drops_set_created_by=drops_set_created_by) - - # Then filter out status from message items - if isinstance(validated_input, list): - filtered_input: Final[list[object]] = [] - for item in validated_input: - if isinstance(item, dict) and item.get("type") == "message": - # Filter out status field from message items - filtered_item = {k: v for k, v in item.items() if k != "status"} - filtered_input.append(filtered_item) - else: - filtered_input.append(item) - return cast(ResponseInputParam, filtered_input) - - return validated_input + validated_input: Final = super()._validate_input_param(input, drop_params=drop_params) + if not isinstance(validated_input, list): + return validated_input + rejected_fields: Final = ( + _AZURE_REJECTED_INPUT_FIELDS_UNDER_DROP_PARAMS if drop_params else _AZURE_REJECTED_INPUT_FIELDS + ) + sanitized_items: Final = [_without_fields_azure_rejects(item, rejected_fields) for item in validated_input] + return cast("ResponseInputParam", sanitized_items) # cast-ok: items keep their shape minus rejected fields def transform_responses_api_request( self, diff --git a/litellm/llms/azure/search/transformation.py b/litellm/llms/azure/search/transformation.py index e255a667606..6d0241d4d3b 100644 --- a/litellm/llms/azure/search/transformation.py +++ b/litellm/llms/azure/search/transformation.py @@ -36,7 +36,7 @@ import httpx from pydantic import ConfigDict, ValidationError from litellm.litellm_core_utils.url_utils import ensure_api_route -from litellm.llms.azure.common_utils import cached_azure_ad_token_refresh_provider +from litellm.llms.azure.common_utils import cached_azure_ad_token_refresh_provider, entra_rejection_as_auth_error from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.llms.base_llm.search.responses import ( ResponsesSearchAnnotation, @@ -270,6 +270,9 @@ class BingGroundingSearchConfig(BaseSearchConfig): try: return minter() except Exception as e: + rejection: Final = entra_rejection_as_auth_error(e) + if rejection is not None: + raise rejection from e raise ValueError( f"Grounding with Bing Search: no credential available. Pass api_key, set {TOKEN_ENV} " f"to an Entra bearer token, or configure azure-identity (AZURE_CLIENT_ID / " diff --git a/litellm/llms/azure_ai/anthropic/count_tokens/handler.py b/litellm/llms/azure_ai/anthropic/count_tokens/handler.py index c324f0f0980..3609871fdf8 100644 --- a/litellm/llms/azure_ai/anthropic/count_tokens/handler.py +++ b/litellm/llms/azure_ai/anthropic/count_tokens/handler.py @@ -12,9 +12,11 @@ from pydantic import JsonValue import litellm from litellm._logging import verbose_logger +from litellm.anthropic_beta_headers_manager import aload_beta_headers_config from litellm.litellm_core_utils.asyncify import asyncify from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.llms.anthropic.common_utils import AnthropicError +from litellm.llms.azure.common_utils import EntraRejectionError from litellm.llms.azure_ai.anthropic.count_tokens.transformation import ( AzureAIAnthropicCountTokensConfig, ) @@ -39,6 +41,7 @@ class AzureAIAnthropicCountTokensHandler(AzureAIAnthropicCountTokensConfig): tools: list[dict[str, JsonValue]] | None = None, system: object = None, optional_params: Mapping[str, JsonValue] | None = None, + context_management: JsonValue = None, ) -> dict[str, object]: """ Handle a CountTokens request using httpx with Azure authentication. @@ -70,6 +73,7 @@ class AzureAIAnthropicCountTokensHandler(AzureAIAnthropicCountTokensConfig): tools=tools, system=system, optional_params=optional_params, + context_management=context_management, drop_params=drops_unsupported_params((litellm_params or {}).get("drop_params")), ) @@ -80,11 +84,14 @@ class AzureAIAnthropicCountTokensHandler(AzureAIAnthropicCountTokensConfig): verbose_logger.debug("Making request to: %s", endpoint_url) + if context_management is not None: + await aload_beta_headers_config() # Get required headers with Azure authentication headers: Final = self.get_required_headers( api_key=api_key, litellm_params=litellm_params, messages=messages, + context_management=context_management, ) if not {"x-api-key", "Authorization"} & headers.keys(): raise AnthropicError( @@ -129,6 +136,8 @@ class AzureAIAnthropicCountTokensHandler(AzureAIAnthropicCountTokensConfig): except AnthropicError: # Re-raise Anthropic exceptions as-is raise + except EntraRejectionError as rejection: + raise AnthropicError(status_code=rejection.status_code, message=rejection.message) from rejection except httpx.HTTPStatusError as e: # HTTP errors - preserve the actual status code verbose_logger.error("HTTP error in CountTokens handler: %s", e) diff --git a/litellm/llms/azure_ai/anthropic/count_tokens/token_counter.py b/litellm/llms/azure_ai/anthropic/count_tokens/token_counter.py index af7cf9d81ce..14f7d4bfd2b 100644 --- a/litellm/llms/azure_ai/anthropic/count_tokens/token_counter.py +++ b/litellm/llms/azure_ai/anthropic/count_tokens/token_counter.py @@ -135,6 +135,7 @@ class AzureAIAnthropicTokenCounter(BaseTokenCounter): tools=tools, system=system, optional_params=count_options, + context_management=None if context_management is None else context_management.spec, ) if result is not None: diff --git a/litellm/llms/azure_ai/anthropic/count_tokens/transformation.py b/litellm/llms/azure_ai/anthropic/count_tokens/transformation.py index c02c92a95d6..91ed40d9271 100644 --- a/litellm/llms/azure_ai/anthropic/count_tokens/transformation.py +++ b/litellm/llms/azure_ai/anthropic/count_tokens/transformation.py @@ -8,9 +8,16 @@ from collections.abc import Sequence from typing import Final from urllib.parse import urlsplit +from pydantic import JsonValue + +from litellm.anthropic_beta_headers_manager import filter_and_transform_beta_headers from litellm.constants import ANTHROPIC_TOKEN_COUNTING_BETA_VERSION from litellm.litellm_core_utils.url_utils import join_api_base -from litellm.llms.anthropic.common_utils import count_tokens_feature_betas, merge_anthropic_beta_headers +from litellm.llms.anthropic.common_utils import ( + context_management_betas, + count_tokens_feature_betas, + merge_anthropic_beta_headers, +) from litellm.llms.anthropic.count_tokens.transformation import ( AnthropicCountTokensConfig, ) @@ -31,6 +38,7 @@ class AzureAIAnthropicCountTokensConfig(AnthropicCountTokensConfig): api_key: str | None, litellm_params: dict[str, object] | None = None, messages: Sequence[object] = (), + context_management: JsonValue = None, ) -> dict[str, str]: """ Get the required headers for the Azure AI Anthropic CountTokens API. @@ -42,6 +50,7 @@ class AzureAIAnthropicCountTokensConfig(AnthropicCountTokensConfig): api_key: The Azure AI API key litellm_params: Optional LiteLLM parameters for additional auth config messages: The request messages, read for betas the counted features need + context_management: The edit spec the count forwards, read for the betas its edits need Returns: Dictionary of required headers with both x-api-key and Azure authentication @@ -51,7 +60,11 @@ class AzureAIAnthropicCountTokensConfig(AnthropicCountTokensConfig): "Content-Type": "application/json", "anthropic-version": "2023-06-01", "anthropic-beta": merge_anthropic_beta_headers( - ANTHROPIC_TOKEN_COUNTING_BETA_VERSION, count_tokens_feature_betas("azure_ai", {}, messages) + ANTHROPIC_TOKEN_COUNTING_BETA_VERSION, + ( + *count_tokens_feature_betas("azure_ai", {}, messages), + *filter_and_transform_beta_headers(list(context_management_betas(context_management)), "azure_ai"), + ), ), **({"x-api-key": api_key} if api_key else {}), } diff --git a/litellm/llms/azure_ai/chat/transformation.py b/litellm/llms/azure_ai/chat/transformation.py index 5214d31fb2e..487958d6d55 100644 --- a/litellm/llms/azure_ai/chat/transformation.py +++ b/litellm/llms/azure_ai/chat/transformation.py @@ -10,7 +10,11 @@ from pydantic import TypeAdapter, ValidationError import litellm from litellm._logging import verbose_logger -from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheControlHook +from litellm.integrations.anthropic_cache_control_hook import ( + AnthropicCacheControlHook, + declared_prompt_cache_breakpoint, + routed_model_info, +) from litellm.litellm_core_utils.prompt_templates.common_utils import ( content_parts, convert_content_list_to_str, @@ -125,18 +129,14 @@ def _with_breakpoints_for_foundry(message: AllMessageValues, drop_params: bool) def _deployment_reads_breakpoints(model: str, litellm_params: Mapping[str, object]) -> bool: + model_info: Final = routed_model_info(litellm_params.get("model_info")) + declared: Final = declared_prompt_cache_breakpoint(model_info) + if declared is not None: + return declared base_model: Final = litellm_params.get("base_model") named_models: Final = (base_model, model) if isinstance(base_model, str) and base_model else (model,) - model_info: Final = litellm_params.get("model_info") - if not isinstance(model_info, Mapping): - return any( - AnthropicCacheControlHook.targets_openai_prompt_cache_breakpoint(name, "azure_ai") for name in named_models - ) - deployment_flag: Final = _FIELDS.validate_python(model_info).get("supports_prompt_cache_breakpoint") - if isinstance(deployment_flag, bool): - return deployment_flag return any( - AnthropicCacheControlHook.catalog_targets_openai_prompt_cache_breakpoint(name, "azure_ai") + AnthropicCacheControlHook.targets_openai_prompt_cache_breakpoint(name, "azure_ai", model_info=model_info) for name in named_models ) diff --git a/litellm/llms/azure_ai/common_utils.py b/litellm/llms/azure_ai/common_utils.py index 147bf69e91e..1635b9b5679 100644 --- a/litellm/llms/azure_ai/common_utils.py +++ b/litellm/llms/azure_ai/common_utils.py @@ -1,5 +1,7 @@ import asyncio -from collections.abc import Mapping +import os +from collections.abc import Callable, Mapping +from functools import partial from types import MappingProxyType from typing import Final, Literal from urllib.parse import urlparse @@ -52,6 +54,28 @@ AZURE_ENTRA_CREDENTIAL_PARAM_KEYS: Final = frozenset({"azure_ad_token", "client_ AZURE_ENTRA_LITELLM_PARAM_KEYS: Final = AZURE_ENTRA_CREDENTIAL_PARAM_KEYS | frozenset( {"tenant_id", "client_id", "azure_username", "azure_scope"} ) +AZURE_DEFAULT_SCOPE: Final = "https://cognitiveservices.azure.com/.default" +_AZURE_ENTRA_ENVIRONMENT_VARIABLES: Final = MappingProxyType( + { + "tenant_id": "AZURE_TENANT_ID", + "client_id": "AZURE_CLIENT_ID", + "client_secret": "AZURE_CLIENT_SECRET", + "azure_username": "AZURE_USERNAME", + "azure_password": "AZURE_PASSWORD", + "azure_ad_token": "AZURE_AD_TOKEN", + } +) + + +def azure_entra_environment_defaults() -> Mapping[str, object]: + return MappingProxyType( + { + **{key: os.getenv(variable) for key, variable in _AZURE_ENTRA_ENVIRONMENT_VARIABLES.items()}, + "azure_scope": os.getenv("AZURE_SCOPE", AZURE_DEFAULT_SCOPE), + } + ) + + AZURE_ENTRA_CREDENTIAL_HELP: Final = ( "Set `tenant_id` + `client_id` + `client_secret`, `azure_ad_token` (an `oidc/` token also needs " "`tenant_id` + `client_id`), or `client_id` + `azure_username` + `azure_password` in the agent's `litellm_params`" @@ -70,6 +94,17 @@ def _resolve_config_secret(value: object) -> str | None: return get_secret_str(value) if value.startswith("os.environ/") else value +def _agent_entra_token(provider: Callable[[], str], model: str) -> str: + from litellm.llms.azure.common_utils import EntraRejectionError, entra_token + + try: + return entra_token(provider) + except EntraRejectionError as rejection: + raise litellm.AuthenticationError( + message=rejection.message, llm_provider="azure_ai", model=model + ) from rejection + + def get_azure_ai_agent_entra_token(litellm_params: Mapping[str, object]) -> str: """Mints the Entra bearer from the agent's own litellm_params, never from process-wide AZURE_* env vars.""" from litellm.llms.azure.common_utils import ( @@ -88,18 +123,32 @@ def get_azure_ai_agent_entra_token(litellm_params: Mapping[str, object]) -> str: azure_username: Final = resolved["azure_username"] azure_password: Final = resolved["azure_password"] azure_ad_token: Final = resolved["azure_ad_token"] + model: Final = str(litellm_params.get("model") or "") if tenant_id and client_id and client_secret: - return get_azure_ad_token_from_entra_id( - tenant_id=tenant_id, client_id=client_id, client_secret=client_secret, scope=scope - )() + return _agent_entra_token( + get_azure_ad_token_from_entra_id( + tenant_id=tenant_id, client_id=client_id, client_secret=client_secret, scope=scope + ), + model, + ) if client_id and azure_username and azure_password: - return get_azure_ad_token_from_username_password( - client_id=client_id, azure_username=azure_username, azure_password=azure_password, scope=scope - )() + return _agent_entra_token( + get_azure_ad_token_from_username_password( + client_id=client_id, azure_username=azure_username, azure_password=azure_password, scope=scope + ), + model, + ) federated: Final = azure_ad_token is not None and azure_ad_token.startswith("oidc/") if azure_ad_token and federated and tenant_id and client_id: - return get_azure_ad_token_from_oidc( - azure_ad_token=azure_ad_token, azure_client_id=client_id, azure_tenant_id=tenant_id, scope=scope + return _agent_entra_token( + partial( + get_azure_ad_token_from_oidc, + azure_ad_token=azure_ad_token, + azure_client_id=client_id, + azure_tenant_id=tenant_id, + scope=scope, + ), + model, ) if azure_ad_token and not federated: return azure_ad_token diff --git a/litellm/llms/azure_ai/rerank/transformation.py b/litellm/llms/azure_ai/rerank/transformation.py index 4c26ba58dd8..2131a8c7cfa 100644 --- a/litellm/llms/azure_ai/rerank/transformation.py +++ b/litellm/llms/azure_ai/rerank/transformation.py @@ -111,10 +111,4 @@ class AzureAIRerankConfig(CohereRerankConfig): return rerank_response def _get_base_model(self, azure_model_group: str | None) -> str | None: - if azure_model_group is None: - return None - if azure_model_group == "offer-cohere-rerank-mul-paygo": - return "azure_ai/cohere-rerank-v3-multilingual" - if azure_model_group == "offer-cohere-rerank-eng-paygo": - return "azure_ai/cohere-rerank-v3-english" return azure_model_group diff --git a/litellm/llms/base_llm/audio_transcription/transformation.py b/litellm/llms/base_llm/audio_transcription/transformation.py index e4bf148abf3..68365372e7e 100644 --- a/litellm/llms/base_llm/audio_transcription/transformation.py +++ b/litellm/llms/base_llm/audio_transcription/transformation.py @@ -1,9 +1,30 @@ from abc import ABC, abstractmethod +from collections.abc import Mapping from dataclasses import dataclass -from typing import TYPE_CHECKING, Any, Final +from types import MappingProxyType +from typing import ( + TYPE_CHECKING, + Any, + Final, + cast, # noqa: TID251 # SDK file handles have no runtime validation schema +) import httpx +from openai import AsyncOpenAI, AsyncStream, OpenAI, Stream +from openai.types.audio import ( + Transcription, + TranscriptionDiarized, + TranscriptionStreamEvent, + TranscriptionVerbose, +) +from openai.types.audio.transcription_create_params import ( + TranscriptionCreateParamsBase, + TranscriptionCreateParamsStreaming, +) +from pydantic import BaseModel, TypeAdapter +from litellm.litellm_core_utils.audio_utils.transcription_streaming import transcription_stream_requested +from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.llms.base_llm.chat.transformation import BaseConfig from litellm.types.llms.openai import ( AllMessageValues, @@ -11,6 +32,31 @@ from litellm.types.llms.openai import ( ) from litellm.types.utils import FileTypes, ModelResponse, TranscriptionResponse +_TRANSCRIPTION_REQUEST: Final = TypeAdapter(Mapping[str, object]) +_TRANSCRIPTION_TEXT: Final = TypeAdapter(str) +_TRANSCRIPTION_BODY: Final = TypeAdapter(dict[str, object]) +_TRANSCRIPTION_TYPES_BY_FORMAT: Final = MappingProxyType( + {"verbose_json": TranscriptionVerbose, "diarized_json": TranscriptionDiarized} +) + + +def sdk_compatible_transcription_request_data(data: object) -> Mapping[str, object]: + request_data: Final = _TRANSCRIPTION_REQUEST.validate_python(data) + extension_keys: Final = ("keywords", "languages") + extension_body: Final = {key: request_data[key] for key in extension_keys if key in request_data} + if not extension_body: + return request_data + + existing_extra_body: Final = request_data.get("extra_body") + return { + **{key: value for key, value in request_data.items() if key not in extension_keys}, + "extra_body": { + **(as_str_mapping(existing_extra_body) or {}), + **extension_body, + }, + } + + if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj from litellm.litellm_core_utils.tokenizer import Encoding as Tokenizer @@ -20,6 +66,77 @@ else: LiteLLMLoggingObj = Any +def sdk_compatible_transcription_response(response: object) -> BaseModel | str: + if isinstance(response, BaseModel): + return response + return _TRANSCRIPTION_TEXT.validate_python(response, strict=True) + + +def _content_type(http_response: httpx.Response) -> str: + return next(iter(http_response.headers.get_list("content-type")), "") + + +def _is_event_stream(http_response: httpx.Response) -> bool: + return _content_type(http_response).startswith("text/event-stream") + + +def _unstreamed_transcription_response(http_response: httpx.Response, response_format: object) -> BaseModel | str: + if not _content_type(http_response).startswith("application/json"): + return http_response.text + transcription_type: Final = _TRANSCRIPTION_TYPES_BY_FORMAT.get(str(response_format), Transcription) + return transcription_type.model_construct(None, **_TRANSCRIPTION_BODY.validate_json(http_response.content)) + + +def _non_streaming_params(data: Mapping[str, object]) -> TranscriptionCreateParamsBase: + return cast( # cast-ok: SDK file handles have no runtime validation schema + TranscriptionCreateParamsBase, {key: value for key, value in data.items() if key != "stream"} + ) + + +def _streaming_params(data: Mapping[str, object]) -> TranscriptionCreateParamsStreaming: + return cast( # cast-ok: SDK file handles have no runtime validation schema + TranscriptionCreateParamsStreaming, data + ) + + +def create_sdk_transcription( + client: OpenAI, data: Mapping[str, object], timeout: float | httpx.Timeout +) -> tuple[dict[str, str], Stream[TranscriptionStreamEvent] | BaseModel | str]: + if not transcription_stream_requested(data.get("stream")): + raw_response: Final = client.audio.transcriptions.with_raw_response.create( + **_non_streaming_params(data), timeout=timeout + ) + return dict(raw_response.headers), sdk_compatible_transcription_response(raw_response.parse()) + raw_stream: Final = client.audio.transcriptions.with_raw_response.create( + **_streaming_params({**data, "stream": True}), timeout=timeout + ) + if _is_event_stream(raw_stream.http_response): + return dict(raw_stream.headers), raw_stream.parse(to=Stream[TranscriptionStreamEvent]) + raw_stream.http_response.read() + return dict(raw_stream.headers), _unstreamed_transcription_response( + raw_stream.http_response, data.get("response_format") + ) + + +async def acreate_sdk_transcription( + client: AsyncOpenAI, data: Mapping[str, object], timeout: float | httpx.Timeout +) -> tuple[dict[str, str], AsyncStream[TranscriptionStreamEvent] | BaseModel | str]: + if not transcription_stream_requested(data.get("stream")): + raw_response: Final = await client.audio.transcriptions.with_raw_response.create( + **_non_streaming_params(data), timeout=timeout + ) + return dict(raw_response.headers), sdk_compatible_transcription_response(raw_response.parse()) + raw_stream: Final = await client.audio.transcriptions.with_raw_response.create( + **_streaming_params({**data, "stream": True}), timeout=timeout + ) + if _is_event_stream(raw_stream.http_response): + return dict(raw_stream.headers), raw_stream.parse(to=AsyncStream[TranscriptionStreamEvent]) + await raw_stream.http_response.aread() + return dict(raw_stream.headers), _unstreamed_transcription_response( + raw_stream.http_response, data.get("response_format") + ) + + @dataclass class AudioTranscriptionRequestData: """ diff --git a/litellm/llms/base_llm/decisions/transformation.py b/litellm/llms/base_llm/decisions/transformation.py index c562c8d0f04..254783edf39 100644 --- a/litellm/llms/base_llm/decisions/transformation.py +++ b/litellm/llms/base_llm/decisions/transformation.py @@ -431,6 +431,10 @@ class DecisionsResponseValidationError(BaseLLMException): pass +def _lacks_confidence(answer: DecisionsIRAnswer) -> bool: + return isinstance(answer, (DecisionsIRChoiceAnswer, DecisionsIRScoreAnswer)) and answer.confidence is None + + def parse_systemone_response(payload: object, request: DecisionsIRRequest) -> DecisionsIRResponse: return systemone_response_to_ir( _SYSTEMONE_RESPONSE_ADAPTER.validate_python(_normalize_systemone_response(payload)), request @@ -534,6 +538,8 @@ class BaseDecisionsConfig(ABC): max_total_image_bytes: int | None = None image_media_types: frozenset[str] | None = None inlines_remote_images: bool = False + openai_evidence_fields: frozenset[str] = frozenset() + confidence_optional: bool = False health_check_questions: Mapping[str, Mapping[str, object]] = MappingProxyType( {"reachable": MappingProxyType({"type": "noul", "instructions": "Is the service reachable?"})} ) @@ -682,13 +688,20 @@ class BaseDecisionsConfig(ABC): ) -> DecisionsIRResponse: try: payload: Final[object] = _PAYLOAD_ADAPTER.validate_json(raw_response.content) - return self.parse_response(payload, request) + response: Final = self.parse_response(payload, request) except ValidationError as error: raise DecisionsResponseValidationError( status_code=500, message=f"Decisions provider '{custom_llm_provider}' returned an unexpected response: " f"{error.title} {_validation_summary(error)}", ) from error + if not self.confidence_optional and any(_lacks_confidence(answer) for answer in response.answers): + raise DecisionsResponseValidationError( + status_code=500, + message=f"Decisions provider '{custom_llm_provider}' returned an unexpected response: " + "a choice or score answer has no confidence", + ) + return response def get_error_class( self, diff --git a/litellm/llms/base_llm/google_genai/transformation.py b/litellm/llms/base_llm/google_genai/transformation.py index 232d9d8eb42..0c7054326b7 100644 --- a/litellm/llms/base_llm/google_genai/transformation.py +++ b/litellm/llms/base_llm/google_genai/transformation.py @@ -164,7 +164,7 @@ class BaseGoogleGenAIGenerateContentConfig(ABC): tools: ToolConfigDict | None, generate_content_config_dict: dict, system_instruction: object | None = None, - ) -> dict: + ) -> dict[str, object]: """ Transform the request parameters for the generate content API. diff --git a/litellm/llms/base_llm/realtime/http_transformation.py b/litellm/llms/base_llm/realtime/http_transformation.py index a02054ec8cb..c1c943c2cd6 100644 --- a/litellm/llms/base_llm/realtime/http_transformation.py +++ b/litellm/llms/base_llm/realtime/http_transformation.py @@ -7,10 +7,13 @@ These are HTTP (not WebSocket) endpoints used by the WebRTC flow: """ from abc import ABC, abstractmethod +from collections.abc import Mapping +from typing import Final import httpx from litellm.litellm_core_utils.url_utils import join_api_base +from litellm.types.router import GenericLiteLLMParams class BaseRealtimeHTTPConfig(ABC): @@ -50,6 +53,14 @@ class BaseRealtimeHTTPConfig(ABC): explicit api_key → litellm.api_key → env var → "" """ + def get_extra_headers( + self, + litellm_params: GenericLiteLLMParams, + api_key: str, + extra_headers: Mapping[str, object] | None, + ) -> Mapping[str, object] | None: + return extra_headers + # ------------------------------------------------------------------ # # client_secrets endpoint # # ------------------------------------------------------------------ # @@ -64,6 +75,12 @@ class BaseRealtimeHTTPConfig(ABC): base = base.removesuffix("/v1") return join_api_base(base, "v1/realtime/transcription_sessions") + def get_translation_client_secret_url( + self, api_base: str | None, model: str, api_version: str | None = None + ) -> str: + base: Final = (api_base or "").rstrip("/") + return f"{base}/v1/realtime/translations/client_secrets" + @abstractmethod def validate_environment( self, @@ -86,6 +103,10 @@ class BaseRealtimeHTTPConfig(ABC): """Return the full URL for POST /realtime/calls (SDP exchange).""" return join_api_base(api_base or "", "v1/realtime/calls") + def get_translation_calls_url(self, api_base: str | None, model: str, api_version: str | None = None) -> str: + base: Final = (api_base or "").rstrip("/") + return f"{base}/v1/realtime/translations/calls" + def get_realtime_calls_headers(self, ephemeral_key: str) -> dict: """ Build headers for the realtime_calls POST. diff --git a/litellm/llms/bedrock/chat/converse_transformation.py b/litellm/llms/bedrock/chat/converse_transformation.py index c37af5c16e3..98b034c7311 100644 --- a/litellm/llms/bedrock/chat/converse_transformation.py +++ b/litellm/llms/bedrock/chat/converse_transformation.py @@ -22,6 +22,12 @@ from litellm.anthropic_beta_headers_manager import filter_and_transform_beta_hea from litellm.constants import ( BEDROCK_MIN_THINKING_BUDGET_TOKENS, RESPONSE_FORMAT_TOOL_NAME, + RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION, +) +from litellm.integrations.anthropic_cache_control_hook import ( + MAX_CACHE_CONTROL_BLOCKS, + AnthropicCacheControlHook, + configured_injection_points, ) from litellm.litellm_core_utils.core_helpers import ( as_str_mapping, @@ -52,6 +58,7 @@ from litellm.litellm_core_utils.prompt_templates.mid_conversation_system import parts_of, ) from litellm.litellm_core_utils.reasoning_effort_utils import OPAQUE_VALUE, warn_dropped_reasoning +from litellm.litellm_core_utils.tool_fields import tool_params_without_hosted_mcp from litellm.llms.anthropic.chat.transformation import ( DROP_UNSUPPORTED_ADAPTIVE_THINKING_WARNING, DROP_UNSUPPORTED_OUTPUT_CONFIG_WARNING, @@ -63,6 +70,7 @@ from litellm.llms.anthropic.common_utils import AnthropicModelInfo from litellm.llms.base_llm.chat.transformation import REQUEST_PARAMS, BaseConfig, BaseLLMException from litellm.llms.bedrock.chat.tool_result_images import place_tool_result_images from litellm.llms.bedrock.common_utils import ( + bedrock_chat_opts_into_native_structured_output, bedrock_chat_uses_native_structured_output, bedrock_cleaned_output_schema, bedrock_model_is_unknown, @@ -129,6 +137,7 @@ from ..common_utils import ( bedrock_capability_model, bedrock_converse_supports_parallel_tool_use_config, bedrock_model_accepts_cache_points, + bedrock_model_known_to_accept_cache_points, bedrock_reasoning_effort_disabled, bedrock_rejects_stop_sequences, get_anthropic_beta_from_headers, @@ -202,6 +211,11 @@ def _has_native_text_format(output_config: object) -> bool: return False +def _cache_mark_kept(block: Mapping[str, object], keeps_cache_marks: bool) -> Mapping[str, object]: + cache_control: Final = block.get("cache_control") + return {"cache_control": cache_control} if keeps_cache_marks and cache_control is not None else {} + + class AmazonConverseConfig(BaseConfig): """ Reference - https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_Converse.html @@ -241,7 +255,7 @@ class AmazonConverseConfig(BaseConfig): @staticmethod def _convert_consecutive_user_messages_to_guarded_text( - messages: list[AllMessageValues], optional_params: dict + messages: list[AllMessageValues], optional_params: dict, keeps_cache_marks: bool = False ) -> list[AllMessageValues]: """ Convert consecutive user messages at the end to guarded_text type if guardrailConfig is present @@ -279,7 +293,11 @@ class AmazonConverseConfig(BaseConfig): new_content = [] for item in content: if isinstance(item, dict) and item.get("type") == "text": - new_item = {"type": "guarded_text", "text": item["text"]} + new_item = { + "type": "guarded_text", + "text": item["text"], + **_cache_mark_kept(_JSON_OBJECT.validate_python(item), keeps_cache_marks), + } new_content.append(new_item) else: new_content.append(item) @@ -287,7 +305,13 @@ class AmazonConverseConfig(BaseConfig): messages_copy[user_message_index]["content"] = new_content elif isinstance(content, str): # If content is a string, convert it to guarded_text - messages_copy[user_message_index]["content"] = [{"type": "guarded_text", "text": content}] + messages_copy[user_message_index]["content"] = [ + { + "type": "guarded_text", + "text": content, + **_cache_mark_kept(_JSON_OBJECT.validate_python(user_message), keeps_cache_marks), + } + ] return messages_copy @@ -927,18 +951,24 @@ class AmazonConverseConfig(BaseConfig): def _supports_native_structured_outputs( model: str, custom_llm_provider: str | None, + will_think: bool, thinking_requested: bool, model_info: Mapping[str, object] | None, ) -> bool: """Check if the Bedrock model takes native structured outputs (outputConfig.textFormat) for this request. ``supports_native_structured_output`` in ``litellm.model_cost`` turns it on for every request, and - ``supports_bedrock_native_structured_output`` (the deployment's ``model_info`` first) only when the - request asks for thinking, which the json tool path would drop. + ``supports_bedrock_native_structured_output`` (the deployment's ``model_info`` first) also when Claude + will think, which the json tool path would drop. When the request does not ask for thinking, a model + that cannot force the json tool gets it unless that key is false. Ref: https://docs.aws.amazon.com/bedrock/latest/userguide/structured-output.html """ return bedrock_chat_uses_native_structured_output( - model, thinking_requested, custom_llm_provider or "bedrock_converse", model_info + model, + will_think=will_think, + thinking_requested=thinking_requested, + custom_llm_provider=custom_llm_provider or "bedrock_converse", + model_info=model_info, ) @staticmethod @@ -981,11 +1011,13 @@ class AmazonConverseConfig(BaseConfig): self, model: str, json_schema: Mapping[str, object], + *, + will_think: bool, thinking_requested: bool, model_info: Mapping[str, object] | None, ) -> Mapping[str, object] | None: if not self._supports_native_structured_outputs( - model, self.custom_llm_provider, thinking_requested, model_info + model, self.custom_llm_provider, will_think, thinking_requested, model_info ): return None if BedrockModelInfo.get_base_model(model).startswith("anthropic"): @@ -1068,21 +1100,22 @@ class AmazonConverseConfig(BaseConfig): drop_params: bool, model_info: Mapping[str, object] | None = None, ) -> dict: - is_thinking_enabled: Final = self.is_thinking_enabled(non_default_params) + request_params: Final = tool_params_without_hosted_mcp( + non_default_params, model=model, route="bedrock", drop_params=drop_params + ) base_model: Final = BedrockModelInfo.get_base_model(model) drop_thinking_param: Final = self._is_deepseek_model(model=model, base_model=base_model) drop_reasoning_effort_param: Final = self._model_rejects_reasoning_effort_param( model=model, base_model=base_model ) - for param, value in non_default_params.items(): + for param, value in request_params.items(): if param == "response_format" and isinstance(value, dict): optional_params = self._translate_response_format_param( value=value, model=model, optional_params=optional_params, - non_default_params=non_default_params, - is_thinking_enabled=is_thinking_enabled, + non_default_params=request_params, model_info=model_info, ) if param == "max_tokens" or param == "max_completion_tokens": @@ -1135,7 +1168,7 @@ class AmazonConverseConfig(BaseConfig): ), ), model=model, - non_default_params=non_default_params, + non_default_params=request_params, optional_params=optional_params, ) if param == "tool_choice": @@ -1160,7 +1193,7 @@ class AmazonConverseConfig(BaseConfig): and value.get("type") == "adaptive" and not AnthropicConfig.is_adaptive_thinking_model(model, "bedrock") ): - max_tokens = non_default_params.get("max_completion_tokens") or non_default_params.get("max_tokens") + max_tokens = request_params.get("max_completion_tokens") or request_params.get("max_tokens") legacy_thinking = AnthropicConfig.map_reasoning_effort( reasoning_effort="medium", model=model, @@ -1230,7 +1263,7 @@ class AmazonConverseConfig(BaseConfig): # Nova 2 handles token budgeting differently through reasoningConfig if "gpt-oss" not in model and not self._is_nova_2_model(model): self.update_optional_params_with_thinking_tokens( - non_default_params=non_default_params, optional_params=optional_params + non_default_params=request_params, optional_params=optional_params ) final_is_thinking_enabled: Final = self.is_thinking_enabled(optional_params) @@ -1287,7 +1320,6 @@ class AmazonConverseConfig(BaseConfig): model: str, optional_params: dict, non_default_params: dict, - is_thinking_enabled: bool, model_info: Mapping[str, object] | None = None, ) -> dict: """ @@ -1312,19 +1344,22 @@ class AmazonConverseConfig(BaseConfig): if "type" in value and value["type"] == "text": return optional_params + request_params: Final = REQUEST_PARAMS.validate_python(non_default_params) + thinking_requested: Final = self.is_thinking_requested(request_params) native_schema: Final = ( self._native_output_schema( model, json_schema, - self.is_thinking_requested(REQUEST_PARAMS.validate_python(non_default_params)), - model_info, + will_think=AnthropicModelInfo.will_think(model, "bedrock", request_params), + thinking_requested=thinking_requested, + model_info=model_info, ) if json_schema is not None else None ) if native_schema is not None: # Use Bedrock's native structured outputs API (outputConfig.textFormat) - # No synthetic tool injection, no fake_stream needed. + # No synthetic tool injection. # Requires an explicit schema — json_object with no schema falls through # to the tool-call path below. output_config: Final = self._create_output_config_for_response_format( @@ -1336,22 +1371,27 @@ class AmazonConverseConfig(BaseConfig): elif json_schema is not None: # Fallback: translate to a synthetic tool call # https://docs.anthropic.com/en/docs/build-with-claude/tool-use#json-mode + tool_is_forced: Final = litellm.utils.supports_tool_choice( + model=model, custom_llm_provider=self.custom_llm_provider + ) and AnthropicModelInfo.response_format_tool_can_be_forced(model, "bedrock", request_params) + schema_description: Final = description if isinstance(description, str) else None + instructs_unforced_tool: Final = not tool_is_forced and BedrockModelInfo.get_base_model(model).startswith( + "anthropic" + ) _tool: Final = self._create_json_tool_call_for_response_format( json_schema=json_schema, - description=description, + description=( + " ".join(filter(None, (RESPONSE_FORMAT_UNFORCED_TOOL_DESCRIPTION, schema_description))) + if instructs_unforced_tool + else schema_description + ), ) optional_params = self._add_tools_to_optional_params(optional_params=optional_params, tools=[_tool]) - if ( - litellm.utils.supports_tool_choice(model=model, custom_llm_provider=self.custom_llm_provider) - and not is_thinking_enabled - and not AnthropicModelInfo.forced_tool_use_unsupported(model) - ): + if tool_is_forced: optional_params["tool_choice"] = ToolChoiceValuesBlock( tool=SpecificToolChoiceBlock(name=RESPONSE_FORMAT_TOOL_NAME) ) - if non_default_params.get("stream", False) is True: - optional_params["fake_stream"] = True # else: response_format=json_object with no schema. # Don't inject the synthetic json_tool_call tool here. When no # schema is given, _create_json_tool_call_for_response_format @@ -1359,6 +1399,13 @@ class AmazonConverseConfig(BaseConfig): # returns {} instead of the requested JSON. The model already # returns JSON when the prompt asks for it. + # A request that goes native without asking for thinking keeps the json tool's faked stream, so it still + # needs only bedrock:InvokeModel, unless the model takes native output on every request. + streams_natively: Final = native_schema is not None and bedrock_chat_opts_into_native_structured_output( + model, thinking_requested, self.custom_llm_provider or "bedrock_converse", model_info + ) + if json_schema is not None and not streams_natively and non_default_params.get("stream", False) is True: + optional_params["fake_stream"] = True optional_params["json_mode"] = True return optional_params @@ -1413,6 +1460,7 @@ class AmazonConverseConfig(BaseConfig): block_type: Literal["system"], model: str | None = None, deployment_model: str | None = None, + model_info: Mapping[str, object] | None = None, ) -> SystemContentBlock | None: pass @@ -1426,6 +1474,7 @@ class AmazonConverseConfig(BaseConfig): block_type: Literal["content_block"], model: str | None = None, deployment_model: str | None = None, + model_info: Mapping[str, object] | None = None, ) -> ContentBlock | None: pass @@ -1438,9 +1487,10 @@ class AmazonConverseConfig(BaseConfig): block_type: Literal["system", "content_block"], model: str | None = None, deployment_model: str | None = None, + model_info: Mapping[str, object] | None = None, ) -> SystemContentBlock | ContentBlock | None: cache_control: Final = message_block.get("cache_control", None) - if cache_control is None or not bedrock_model_accepts_cache_points(model, deployment_model): + if cache_control is None or not bedrock_model_accepts_cache_points(model, deployment_model, model_info): return None cache_point: Final = self._build_cache_point_block(cache_control, model, deployment_model) @@ -1585,8 +1635,80 @@ class AmazonConverseConfig(BaseConfig): return ChatCompletionTextObject(type="text", text=text) return ChatCompletionTextObject(type="text", text=text, cache_control=cache_control) + def _messages_with_cache_marks( + self, + messages: Sequence[AllMessageValues], + model: str, + deployment_model: str, + drop_params: bool, + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + model_info: Mapping[str, object] | None, + ) -> Sequence[AllMessageValues]: + if not bedrock_model_known_to_accept_cache_points(model, deployment_model, model_info): + return messages + markable: Final = ( + AnthropicCacheControlHook.prompt_cache_breakpoints_dropped_from_tool_results(messages, drop_params, model) + if "nova" in model.lower() + else messages + ) + return AnthropicCacheControlHook.prompt_cache_breakpoints_as_capped_cache_control( + markable, + drop_params, + AnthropicCacheControlHook.count_converse_cache_points, + lambda: self._tool_cache_points_on_the_wire( + model, deployment_model, optional_params, litellm_params, model_info + ), + ) + + def _tool_cache_points_on_the_wire( + self, + model: str, + deployment_model: str, + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + model_info: Mapping[str, object] | None, + ) -> int: + tools: Final = optional_params.get("tools") + bedrock_tools, _ = self._process_tools_and_beta( + tools if isinstance(tools, list) else [], model, None, {}, litellm_params, deployment_model, model_info + ) + injects_tool_config_point: Final = bool(bedrock_tools) and any( + point.get("location") == "tool_config" + for point in configured_injection_points(optional_params.get("cache_control_injection_points")) + ) + return sum(1 for tool in bedrock_tools if "cachePoint" in tool) + int(injects_tool_config_point) + + def _guarded_text_keeps_cache_marks( + self, + messages: Sequence[AllMessageValues], + system_content_blocks: Sequence[SystemContentBlock], + model: str, + deployment_model: str, + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + model_info: Mapping[str, object] | None, + ) -> bool: + if "guardrailConfig" not in optional_params or not bedrock_model_known_to_accept_cache_points( + model, deployment_model, model_info + ): + return False + message_cache_points: Final = sum(map(AnthropicCacheControlHook.count_converse_cache_points, messages)) + if message_cache_points == 0: + return False + cache_points: Final = ( + sum(1 for block in system_content_blocks if "cachePoint" in block) + + message_cache_points + + self._tool_cache_points_on_the_wire(model, deployment_model, optional_params, litellm_params, model_info) + ) + return cache_points <= MAX_CACHE_CONTROL_BLOCKS + def _transform_system_message( - self, messages: list[AllMessageValues], model: str | None = None, deployment_model: str | None = None + self, + messages: list[AllMessageValues], + model: str | None = None, + deployment_model: str | None = None, + model_info: Mapping[str, object] | None = None, ) -> tuple[list[AllMessageValues], list[SystemContentBlock]]: leading_count: Final = next( (i for i, m in enumerate(messages) if not is_system_message(m)), @@ -1602,7 +1724,7 @@ class AmazonConverseConfig(BaseConfig): if isinstance(content, str) and content: system_content_blocks.append(SystemContentBlock(text=content)) cache_block = self.get_cache_point_block( - message, block_type="system", model=model, deployment_model=deployment_model + message, block_type="system", model=model, deployment_model=deployment_model, model_info=model_info ) if cache_block: system_content_blocks.append(cache_block) @@ -1611,7 +1733,11 @@ class AmazonConverseConfig(BaseConfig): if m.get("type") == "text" and m.get("text"): system_content_blocks.append(SystemContentBlock(text=m["text"])) cache_block = self.get_cache_point_block( - m, block_type="system", model=model, deployment_model=deployment_model + m, + block_type="system", + model=model, + deployment_model=deployment_model, + model_info=model_info, ) if cache_block: system_content_blocks.append(cache_block) @@ -1809,6 +1935,7 @@ class AmazonConverseConfig(BaseConfig): additional_request_params: dict, litellm_params: Mapping[str, object] | None = None, deployment_model: str | None = None, + model_info: Mapping[str, object] | None = None, ) -> tuple[list[ToolBlock], list]: """Process tools and collect anthropic_beta values.""" bedrock_tools: list[ToolBlock] = [] @@ -1870,6 +1997,7 @@ class AmazonConverseConfig(BaseConfig): _tools_the_model_accepts(regular_tools, model, litellm_params), model=model, deployment_model=deployment_model, + model_info=model_info, ) # Add computer use tools and anthropic_beta if needed (only when computer use tools are present) @@ -1939,6 +2067,7 @@ class AmazonConverseConfig(BaseConfig): _tools_the_model_accepts(_TOOLS_AS_SENT.validate_python(filtered_tools), model, litellm_params), model=model, deployment_model=deployment_model, + model_info=model_info, ) # Append pre-formatted tools (systemTool etc.) after transformation @@ -2014,6 +2143,7 @@ class AmazonConverseConfig(BaseConfig): drop_params: bool = False, litellm_params: Mapping[str, object] | None = None, deployment_model: str | None = None, + model_info: Mapping[str, object] | None = None, ) -> CommonRequestObject: # Drop thinking param if thinking is enabled but thinking_blocks are missing # This prevents the error: "Expected thinking or redacted_thinking, but found tool_use" @@ -2052,7 +2182,7 @@ class AmazonConverseConfig(BaseConfig): # Process tools and collect beta values bedrock_tools, anthropic_beta_list = self._process_tools_and_beta( - original_tools, model, headers, additional_request_params, litellm_params, deployment_model + original_tools, model, headers, additional_request_params, litellm_params, deployment_model, model_info ) requested_thinking: Final = additional_request_params.get("thinking") # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # _prepare_request_params hands back a bare dict body_betas: Final = additional_request_params.get("anthropic_beta") # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # same bare dict @@ -2070,7 +2200,7 @@ class AmazonConverseConfig(BaseConfig): if ( cache_injection_points and len(bedrock_tools) > 0 - and bedrock_model_accepts_cache_points(model, deployment_model) + and bedrock_model_accepts_cache_points(model, deployment_model, model_info) ): for point in cache_injection_points: if point.get("location") == "tool_config": @@ -2108,8 +2238,8 @@ class AmazonConverseConfig(BaseConfig): } if additional_request_params: data["additionalModelRequestFields"] = additional_request_params - if "thinking" in additional_request_params: - data["additionalModelResponseFieldPaths"] = ("/usage/output_tokens_details",) + if "thinking" in additional_request_params or AnthropicModelInfo.thinks_by_default(model, "bedrock"): + data["additionalModelResponseFieldPaths"] = ("/usage/output_tokens_details",) if system_content_blocks: data["system"] = system_content_blocks @@ -2130,22 +2260,27 @@ class AmazonConverseConfig(BaseConfig): return data - @staticmethod def _claude_messages_within_cache_control_cap( + self, messages: Sequence[AllMessageValues], capability_model: str, + deployment_model: str, optional_params: Mapping[str, object], litellm_params: Mapping[str, object], + model_info: Mapping[str, object] | None, ) -> Sequence[AllMessageValues]: if not drops_unsupported_params(litellm_params.get("drop_params")) or "claude" not in capability_model.lower(): return messages from litellm.integrations.anthropic_cache_control_hook import ( - messages_within_cache_control_cap, + messages_within_reserved_cache_control_cap, tool_message_with_single_cache_mark, ) - return messages_within_cache_control_cap( - tuple(map(tool_message_with_single_cache_mark, messages)), optional_params.get("tools") + return messages_within_reserved_cache_control_cap( + tuple(map(tool_message_with_single_cache_mark, messages)), + self._tool_cache_points_on_the_wire( + capability_model, deployment_model, optional_params, litellm_params, model_info + ), ) async def _async_transform_request( @@ -2156,27 +2291,53 @@ class AmazonConverseConfig(BaseConfig): litellm_params: dict[str, object], headers: dict | None = None, ) -> RequestObject: + from litellm.integrations.anthropic_cache_control_hook import routed_model_info + base_model: Final = litellm_params.get("base_model") capability_model: Final = bedrock_capability_model(model, base_model) + model_info: Final = routed_model_info(litellm_params.get("model_info")) + json_optional_params: Final = _JSON_OBJECT.validate_python(optional_params) + marked_messages: Final = self._messages_with_cache_marks( + messages, + capability_model, + model, + drops_unsupported_params(litellm_params.get("drop_params")), + json_optional_params, + litellm_params, + model_info, + ) messages, system_content_blocks = self._transform_system_message( list( self._claude_messages_within_cache_control_cap( - messages, capability_model, _JSON_OBJECT.validate_python(optional_params), litellm_params + marked_messages, capability_model, model, json_optional_params, litellm_params, model_info ) ), model=capability_model, deployment_model=model, + model_info=model_info, ) # Convert last user message to guarded_text if guardrailConfig is present + guard_input: Final = self._handle_orphaned_tool_blocks(messages, optional_params) messages = self._convert_consecutive_user_messages_to_guarded_text( - self._handle_orphaned_tool_blocks(messages, optional_params), optional_params + guard_input, + optional_params, + keeps_cache_marks=self._guarded_text_keeps_cache_marks( + guard_input, + system_content_blocks, + capability_model, + model, + json_optional_params, + litellm_params, + model_info, + ), ) ## TRANSFORMATION ## _data: Final[CommonRequestObject] = self._transform_request_helper( model=capability_model, deployment_model=model, + model_info=model_info, system_content_blocks=system_content_blocks, optional_params=optional_params, messages=messages, @@ -2191,6 +2352,7 @@ class AmazonConverseConfig(BaseConfig): messages=messages, model=capability_model, deployment_model=model, + model_info=model_info, llm_provider="bedrock_converse", user_continue_message=litellm_params.pop("user_continue_message", None), base_model=self._deployment_base_model(_DEPLOYMENT_PARAMS.validate_python(litellm_params)), @@ -2243,26 +2405,52 @@ class AmazonConverseConfig(BaseConfig): litellm_params: dict[str, object], headers: dict | None = None, ) -> RequestObject: + from litellm.integrations.anthropic_cache_control_hook import routed_model_info + base_model: Final = litellm_params.get("base_model") capability_model: Final = bedrock_capability_model(model, base_model) + model_info: Final = routed_model_info(litellm_params.get("model_info")) + json_optional_params: Final = _JSON_OBJECT.validate_python(optional_params) + marked_messages: Final = self._messages_with_cache_marks( + messages, + capability_model, + model, + drops_unsupported_params(litellm_params.get("drop_params")), + json_optional_params, + litellm_params, + model_info, + ) messages, system_content_blocks = self._transform_system_message( list( self._claude_messages_within_cache_control_cap( - messages, capability_model, _JSON_OBJECT.validate_python(optional_params), litellm_params + marked_messages, capability_model, model, json_optional_params, litellm_params, model_info ) ), model=capability_model, deployment_model=model, + model_info=model_info, ) # Convert last user message to guarded_text if guardrailConfig is present + guard_input: Final = self._handle_orphaned_tool_blocks(messages, optional_params) messages = self._convert_consecutive_user_messages_to_guarded_text( - self._handle_orphaned_tool_blocks(messages, optional_params), optional_params + guard_input, + optional_params, + keeps_cache_marks=self._guarded_text_keeps_cache_marks( + guard_input, + system_content_blocks, + capability_model, + model, + json_optional_params, + litellm_params, + model_info, + ), ) _data: Final[CommonRequestObject] = self._transform_request_helper( model=capability_model, deployment_model=model, + model_info=model_info, system_content_blocks=system_content_blocks, optional_params=optional_params, messages=messages, @@ -2278,6 +2466,7 @@ class AmazonConverseConfig(BaseConfig): messages=messages, model=capability_model, deployment_model=model, + model_info=model_info, llm_provider="bedrock_converse", user_continue_message=litellm_params.pop("user_continue_message", None), base_model=self._deployment_base_model(_DEPLOYMENT_PARAMS.validate_python(litellm_params)), diff --git a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude_transformation.py b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude_transformation.py index e32df0bbdbb..62e1bee5217 100644 --- a/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude_transformation.py +++ b/litellm/llms/bedrock/chat/invoke_transformations/anthropic_claude_transformation.py @@ -1,18 +1,22 @@ -from collections.abc import Mapping +from collections.abc import Callable, Mapping from typing import TYPE_CHECKING, Any, Final import httpx from pydantic import TypeAdapter +import litellm from litellm.anthropic_beta_gated_fields import strip_beta_gated_request_body from litellm.anthropic_beta_headers_manager import filter_and_transform_beta_headers +from litellm.constants import DEFAULT_ANTHROPIC_CHAT_MAX_TOKENS from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import object_mapping from litellm.litellm_core_utils.prompt_templates.factory import ( convert_to_anthropic_image_obj, ) from litellm.litellm_core_utils.prompt_templates.image_handling import ( + RemoteMedia, async_inline_remote_media, convert_url_to_base64, + inline_every_remote_url, ) from litellm.llms.anthropic.chat.transformation import AnthropicConfig from litellm.llms.anthropic.common_utils import ( @@ -25,7 +29,9 @@ from litellm.llms.bedrock.chat.invoke_transformations.base_invoke_transformation ) from litellm.llms.bedrock.common_utils import ( BEDROCK_INVOKE_TRACE_FIELD, + BedrockModelInfo, apply_bedrock_invoke_structured_output, + bedrock_capability_model, bedrock_chat_uses_native_structured_output, bedrock_cleaned_output_schema, bedrock_supports_tool_search, @@ -35,6 +41,7 @@ from litellm.llms.bedrock.common_utils import ( normalize_custom_field_on_tools, normalize_tool_input_schema_types_for_bedrock_invoke, requests_opt_in_native_output, + strip_bedrock_routing_prefix, strip_unsupported_bedrock_invoke_output_config_keys, tools_without_eager_input_streaming, ) @@ -59,6 +66,19 @@ _NON_DEFAULT_PARAMS: Final = TypeAdapter(Mapping[str, object]) _LITELLM_PARAMS: Final = TypeAdapter(Mapping[str, object]) +def _anthropic_config_max_tokens() -> int | None: + return litellm.AnthropicConfig.max_tokens + + +def _mapped_max_tokens(model: str) -> int | None: + row: Final = object_mapping(litellm.model_cost.get(model)) or {} # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # cost map rows are untyped JSON + match row.get("max_output_tokens"): + case int() as max_tokens: + return max_tokens + case _: + return None + + class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig): """ Reference: @@ -79,9 +99,26 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig): anthropic_version: str = "bedrock-2023-05-31" - def __init__(self, model_info: Mapping[str, object] | None = None) -> None: + def __init__( + self, + model_info: Mapping[str, object] | None = None, + read_configured_max_tokens: Callable[[], int | None] = _anthropic_config_max_tokens, + ) -> None: super().__init__() self._deployment_model_info: Final = model_info + self._read_configured_max_tokens: Final = read_configured_max_tokens + + @classmethod + def get_config( + cls, *, model: str | None = None, configured_max_output_tokens: int | None = None + ) -> dict[str, object]: # mutable-ok: overrides BaseConfig's dict + return { + key: value + for key, value in super() + .get_config(model=model, configured_max_output_tokens=configured_max_output_tokens) + .items() + if key != "max_tokens" + } @property def custom_llm_provider(self) -> str | None: @@ -90,6 +127,9 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig): def should_strip_billing_metadata(self) -> bool: return True + def inlines_remote_media(self, media: RemoteMedia) -> bool: + return inline_every_remote_url(media) + def get_supported_openai_params(self, model: str) -> list[str]: return AnthropicConfig.get_supported_openai_params(self, model) @@ -101,10 +141,20 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig): model: str, json_schema: Mapping[str, object] | None, request_params: Mapping[str, object], + ) -> bool: + return self.chat_uses_native_structured_output(model, request_params, self._deployment_model_info) and ( + json_schema is None or bedrock_cleaned_output_schema(model, json_schema) is not None + ) + + def chat_uses_native_structured_output( + self, model: str, request_params: Mapping[str, object], model_info: Mapping[str, object] | None ) -> bool: return bedrock_chat_uses_native_structured_output( - model, self.is_thinking_requested(request_params), model_info=self._deployment_model_info - ) and (json_schema is None or bedrock_cleaned_output_schema(model, json_schema) is not None) + model, + will_think=self.will_think(model, "bedrock", request_params), + thinking_requested=self.is_thinking_requested(request_params), + model_info=model_info, + ) def uses_opt_in_native_output( self, model: str, optional_params: Mapping[str, object], litellm_params: Mapping[str, object] @@ -241,6 +291,36 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig): headers=headers, ) + def _default_max_tokens_models(self, model: str, litellm_params: Mapping[str, object]) -> tuple[str, ...]: + return ( + BedrockModelInfo.get_base_model( + bedrock_capability_model(strip_bedrock_routing_prefix(model), litellm_params.get("base_model")) + ), + ) + + def _default_max_tokens(self, model: str, litellm_params: Mapping[str, object]) -> int: + configured_max_tokens: Final = self._read_configured_max_tokens() + match deployment_model_info(litellm_params).get("max_output_tokens"): + case int() as deployment_max_tokens: + return ( + deployment_max_tokens + if configured_max_tokens is None + else min(deployment_max_tokens, configured_max_tokens) + ) + case _ if configured_max_tokens is not None: + return configured_max_tokens + case _: + return next( + ( + max_tokens + for max_tokens in map( + _mapped_max_tokens, self._default_max_tokens_models(model, litellm_params) + ) + if max_tokens is not None + ), + DEFAULT_ANTHROPIC_CHAT_MAX_TOKENS, + ) + def _build_bedrock_anthropic_request_base( self, model: str, @@ -257,23 +337,35 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig): model=model, output_config=filtered_params["output_config"], ) - filtered_params = self._normalize_bedrock_tool_search_tools(filtered_params) + normalized_params: Final = self._normalize_bedrock_tool_search_tools(filtered_params) + default_max_tokens: Final = ( + None + if "max_tokens" in normalized_params + else self._default_max_tokens(model, _LITELLM_PARAMS.validate_python(litellm_params)) + ) + request_params: Final = ( + normalized_params if default_max_tokens is None else {**normalized_params, "max_tokens": default_max_tokens} + ) anthropic_request: Final = AnthropicConfig.transform_request( self, model=model, messages=messages, - optional_params=filtered_params, + optional_params=request_params, litellm_params=litellm_params, headers=headers, ) anthropic_request.pop("model", None) anthropic_request.pop("stream", None) + model_info: Final = deployment_model_info(_LITELLM_PARAMS.validate_python(litellm_params)) apply_bedrock_invoke_structured_output( model=model, request_body=anthropic_request, - model_info=deployment_model_info(_LITELLM_PARAMS.validate_python(litellm_params)), + model_info=model_info, + chat_uses_native_output=lambda: self.chat_uses_native_structured_output( + model, _NON_DEFAULT_PARAMS.validate_python(filtered_params), model_info + ), ) strip_unsupported_bedrock_invoke_output_config_keys( model=model, @@ -377,7 +469,7 @@ class AmazonAnthropicClaudeConfig(AmazonInvokeConfig, AnthropicConfig): "data": image_chunk["data"], } - def _normalize_bedrock_tool_search_tools(self, optional_params: dict) -> dict: + def _normalize_bedrock_tool_search_tools(self, optional_params: dict) -> dict[str, object]: """ Convert tool search entries to the format supported by the Bedrock Invoke API. """ diff --git a/litellm/llms/bedrock/chat/mantle/transformation.py b/litellm/llms/bedrock/chat/mantle/transformation.py index b5a352bab48..7e635a61d4d 100644 --- a/litellm/llms/bedrock/chat/mantle/transformation.py +++ b/litellm/llms/bedrock/chat/mantle/transformation.py @@ -15,7 +15,7 @@ from litellm.llms.anthropic.chat.transformation import JsonModeRequest from litellm.llms.bedrock.chat.invoke_transformations.anthropic_claude_transformation import ( AmazonAnthropicClaudeConfig, ) -from litellm.llms.bedrock.common_utils import build_mantle_messages_url +from litellm.llms.bedrock.common_utils import bedrock_chat_opts_into_native_structured_output, build_mantle_messages_url from litellm.types.llms.openai import AllMessageValues from litellm.types.utils import ModelResponse @@ -54,6 +54,16 @@ class AmazonMantleConfig(AmazonAnthropicClaudeConfig): region=region, ) + def chat_uses_native_structured_output( + self, model: str, request_params: Mapping[str, object], model_info: Mapping[str, object] | None + ) -> bool: + return bedrock_chat_opts_into_native_structured_output( + model, self.will_think(model, "bedrock", request_params), model_info=model_info + ) + + def _default_max_tokens_models(self, model: str, litellm_params: Mapping[str, object]) -> tuple[str, ...]: + return (f"bedrock_mantle/{model}", *super()._default_max_tokens_models(model, litellm_params)) + def validate_environment( self, headers: dict, diff --git a/litellm/llms/bedrock/claude_platform/transformation.py b/litellm/llms/bedrock/claude_platform/transformation.py index a5ecc37d394..6efc4b506e8 100644 --- a/litellm/llms/bedrock/claude_platform/transformation.py +++ b/litellm/llms/bedrock/claude_platform/transformation.py @@ -30,6 +30,9 @@ class BedrockClaudePlatformConfig(BedrockClaudePlatformMixin, AnthropicConfig): def should_strip_billing_metadata(self) -> bool: return True + def runs_hosted_mcp(self) -> bool: + return True + def validate_environment( self, headers: dict, diff --git a/litellm/llms/bedrock/common_utils.py b/litellm/llms/bedrock/common_utils.py index d6f5d5b6bd7..dfee28a7cc9 100644 --- a/litellm/llms/bedrock/common_utils.py +++ b/litellm/llms/bedrock/common_utils.py @@ -10,7 +10,7 @@ import json import os import re import warnings -from collections.abc import Iterator, Mapping, Sequence +from collections.abc import Callable, Iterator, Mapping, Sequence from dataclasses import dataclass from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, TypeAlias @@ -33,9 +33,11 @@ from pydantic import ConfigDict, TypeAdapter, ValidationError import litellm from litellm import verbose_logger from litellm.litellm_core_utils.aws_partition import get_aws_dns_suffix +from litellm.litellm_core_utils.core_helpers import lax_bool from litellm.litellm_core_utils.optional_imports import ensure_optional_import from litellm.litellm_core_utils.prompt_templates.common_utils import schema_property_count from litellm.litellm_core_utils.url_utils import ensure_api_route +from litellm.llms.anthropic.common_utils import AnthropicModelInfo from litellm.llms.base_llm.anthropic_messages.transformation import ( BaseAnthropicMessagesConfig, ) @@ -43,6 +45,7 @@ from litellm.llms.base_llm.base_utils import BaseLLMModelInfo, BaseTokenCounter from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.llms.bedrock.request_metadata import bedrock_request_metadata_is_owned from litellm.secret_managers.main import get_secret, get_secret_str +from litellm.types.llms.anthropic import ANTHROPIC_BETA_HEADER_VALUES from litellm.types.llms.bedrock import AWS_AUTH_PARAM_KEYS, AwsAuthParams if TYPE_CHECKING: @@ -50,6 +53,12 @@ if TYPE_CHECKING: from litellm.types.llms.openai import AllMessageValues BEDROCK_INVOKE_TRACE_FIELD: Final = "amazon-bedrock-trace" +BEDROCK_INVOKE_CONTEXT_MANAGEMENT_EDIT_BETAS: Final[Mapping[str, str]] = MappingProxyType( + { + "compact_20260112": ANTHROPIC_BETA_HEADER_VALUES.COMPACT_2026_01_12.value, + "clear_tool_uses_20250919": ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value, + } +) _ERROR_REQUEST_URL: Final = "https://docs.litellm.ai/docs" @@ -308,7 +317,33 @@ def bedrock_supports_native_structured_output( ) or _bedrock_native_output_opt_in(model, custom_llm_provider, model_info) -def bedrock_chat_uses_native_structured_output( +def _bedrock_map_native_output_flag(model: str) -> object: + routed: Final = strip_bedrock_routing_prefix(model) + flags: Final = ( + (entry or {}).get("supports_bedrock_native_structured_output") + for entry in ( + _model_cost_entry(f"bedrock/{routed}"), + _model_cost_entry(routed), + _model_cost_entry(split_bedrock_region_path(model)[1]), + ) + ) + return next((flag for flag in flags if isinstance(flag, bool)), None) + + +def _bedrock_native_output_opted_out(model: str, model_info: Mapping[str, object] | None) -> bool: + deployment_flag: Final = (model_info or {}).get("supports_bedrock_native_structured_output") + if isinstance(deployment_flag, bool): + return not deployment_flag + return _bedrock_map_native_output_flag(model) is False + + +def _bedrock_native_output_replaces_unforceable_tool(model: str, model_info: Mapping[str, object] | None) -> bool: + return AnthropicModelInfo.forced_tool_use_unsupported(model) and not _bedrock_native_output_opted_out( + model, model_info + ) + + +def bedrock_chat_opts_into_native_structured_output( model: str, thinking_requested: bool, custom_llm_provider: str = "bedrock", @@ -319,7 +354,20 @@ def bedrock_chat_uses_native_structured_output( ) -def bedrock_native_output_is_opt_in( +def bedrock_chat_uses_native_structured_output( + model: str, + *, + will_think: bool, + thinking_requested: bool, + custom_llm_provider: str = "bedrock", + model_info: Mapping[str, object] | None = None, +) -> bool: + return bedrock_chat_opts_into_native_structured_output(model, will_think, custom_llm_provider, model_info) or ( + not thinking_requested and _bedrock_native_output_replaces_unforceable_tool(model, model_info) + ) + + +def bedrock_native_output_is_deployment_opt_in( model: str, custom_llm_provider: str = "bedrock", model_info: Mapping[str, object] | None = None ) -> bool: return not _bedrock_model_supports( @@ -327,6 +375,15 @@ def bedrock_native_output_is_opt_in( ) and _bedrock_native_output_opt_in(model, custom_llm_provider, model_info) +def bedrock_native_output_is_opt_in( + model: str, custom_llm_provider: str = "bedrock", model_info: Mapping[str, object] | None = None +) -> bool: + return not _bedrock_model_supports(model, "supports_native_structured_output", custom_llm_provider) and ( + _bedrock_native_output_opt_in(model, custom_llm_provider, model_info) + or _bedrock_native_output_replaces_unforceable_tool(model, model_info) + ) + + def without_bedrock_native_output_opt_in(litellm_params: Mapping[str, object]) -> Mapping[str, object]: return { **litellm_params, @@ -417,13 +474,18 @@ def requests_output_config_format(optional_params: Mapping[str, object]) -> bool return False +def requests_native_output(anthropic_optional_params: Mapping[str, object]) -> bool: + return isinstance(anthropic_optional_params.get("output_format"), Mapping) or requests_output_config_format( + anthropic_optional_params + ) + + def requests_opt_in_native_output( model: str, anthropic_optional_params: Mapping[str, object], model_info: Mapping[str, object] | None ) -> bool: - native_output_requested: Final = isinstance( - anthropic_optional_params.get("output_format"), Mapping - ) or requests_output_config_format(anthropic_optional_params) - return native_output_requested and bedrock_native_output_is_opt_in(model, model_info=model_info) + return requests_native_output(anthropic_optional_params) and bedrock_native_output_is_opt_in( + model, model_info=model_info + ) _JSON_OBJECT: Final = TypeAdapter(dict[str, object]) @@ -484,6 +546,7 @@ def apply_bedrock_invoke_structured_output( model: str, request_body: dict[str, object], # mutable-ok: edited in place like siblings model_info: Mapping[str, object] | None = None, + chat_uses_native_output: Callable[[], bool] = lambda: False, ) -> None: """ Route Anthropic structured-output params to what the Bedrock model supports. @@ -495,7 +558,8 @@ def apply_bedrock_invoke_structured_output( forwarded as ``output_config.format``, which Bedrock relays to the model for enforced structured output. For every other model the schema is inlined into the last user message as best-effort text, with a warning because nothing - enforces it. + enforces it. ``chat_uses_native_output`` is asked only when a schema is + present, and a true answer sends it natively after the same cleanup. """ legacy_output_format: Final = request_body.pop("output_format", None) output_config_format: Final = pop_bedrock_invoke_output_config_format(request_body) @@ -504,7 +568,15 @@ def apply_bedrock_invoke_structured_output( if schema_format is None: return - native_format: Final = bedrock_native_output_format(model, schema_format, model_info=model_info) + native_format: Final = bedrock_native_output_format( + model, + schema_format, + model_info=( + {**(model_info or {}), "supports_bedrock_native_structured_output": True} + if chat_uses_native_output() + else model_info + ), + ) if native_format is not None: existing_output_config: Final = request_body.get("output_config") if isinstance(existing_output_config, dict): @@ -1446,7 +1518,9 @@ def bedrock_converse_supports_parallel_tool_use_config(model: str) -> bool: ) -def bedrock_model_accepts_cache_points(model: str | None, deployment_model: str | None = None) -> bool: +def bedrock_model_accepts_cache_points( + model: str | None, deployment_model: str | None = None, model_info: Mapping[str, object] | None = None +) -> bool: """ Whether Converse ``cachePoint`` blocks may be sent to this model. @@ -1466,43 +1540,102 @@ def bedrock_model_accepts_cache_points(model: str | None, deployment_model: str never silently degrade. ``litellm.utils.supports_prompt_caching`` is not reusable here: it returns False for unmapped models, the opposite polarity. ``deployment_model`` is the model as configured when ``model`` is its ``base_model``: its own declaration wins. + A routed call passes its deployment's ``model_info``, whose breakpoint flag wins outright and + whose ``supports_prompt_caching`` wins over the catalog's for a known model. Other flags come + from the catalog as loaded, since the registered keys are shared by every deployment of the + same model string and carry whichever sibling registered last. """ if model is None: return True deployment_declared: Final = ( - None if deployment_model is None else bedrock_declared_cache_point_support(deployment_model) + None if deployment_model is None else bedrock_declared_cache_point_support(deployment_model, model_info) ) declared: Final = ( - deployment_declared if deployment_declared is not None else bedrock_declared_cache_point_support(model) + deployment_declared + if deployment_declared is not None + else bedrock_declared_cache_point_support(model, model_info) ) return declared is not False -def bedrock_declared_cache_point_support(model: str) -> bool | None: +def bedrock_declared_cache_point_support(model: str, model_info: Mapping[str, object] | None = None) -> bool | None: if _OPENAI_FAMILY_MODEL_RE.search(model): return False - map_keys: Final = (model, get_bedrock_base_model(model)) + explicit_marker_support: Final = _explicit_cache_point_support(model, model_info) + if explicit_marker_support is not None: + return explicit_marker_support + return _mapped_prompt_caching_support(model, model_info) + + +def bedrock_model_known_to_accept_cache_points( + model: str, deployment_model: str | None = None, model_info: Mapping[str, object] | None = None +) -> bool: + """Like ``bedrock_model_accepts_cache_points``, but only for the Claude and Nova families Bedrock documents + as taking cache checkpoints, unless the entry sets ``supports_prompt_cache_breakpoint``: an OpenAI + ``prompt_cache_breakpoint`` reaches every model of a mixed fleet, not only the ones a client marked for + Bedrock caching, and other families price implicit cache reads yet may reject the cachePoint field.""" + deployment_declared: Final = ( + None if deployment_model is None else _declared_marker_support(deployment_model, model_info) + ) + declared: Final = ( + deployment_declared if deployment_declared is not None else _declared_marker_support(model, model_info) + ) + return declared is True + + +def _declared_marker_support(model: str, model_info: Mapping[str, object] | None) -> bool | None: + if _OPENAI_FAMILY_MODEL_RE.search(model): + return False + explicit_marker_support: Final = _explicit_cache_point_support(model, model_info) + if explicit_marker_support is not None: + return explicit_marker_support + mapped: Final = _mapped_prompt_caching_support(model, model_info) + if not _documents_cache_checkpoints(model): + return None if mapped is None else False + return mapped is not False + + +def _documents_cache_checkpoints(model: str) -> bool: + return _is_claude(model) or get_bedrock_base_model(model).startswith("amazon.nova") + + +def _explicit_cache_point_support(model: str, model_info: Mapping[str, object] | None) -> bool | None: + deployment_flag: Final = None if model_info is None else model_info.get("supports_prompt_cache_breakpoint") + if deployment_flag is not None: + return deployment_flag is True + catalog_entry: Final = _catalog_entry_reader(model_info) registered_keys: Final = tuple(f"bedrock/{route}{model}" for route in ("", "converse/", "converse_like/")) - explicit_marker_support: Final = next( + return next( ( entry.get("supports_prompt_cache_breakpoint") is True - for key in (*registered_keys, *map_keys) - if (entry := litellm.model_cost.get(key)) is not None - and entry.get("supports_prompt_cache_breakpoint") is not None + for key in (*registered_keys, model, get_bedrock_base_model(model)) + if (entry := catalog_entry(key)) is not None and entry.get("supports_prompt_cache_breakpoint") is not None ), None, ) - if explicit_marker_support is not None: - return explicit_marker_support - if not any(key in litellm.model_cost for key in map_keys): + + +def _mapped_prompt_caching_support(model: str, model_info: Mapping[str, object] | None) -> bool | None: + catalog_entry: Final = _catalog_entry_reader(model_info) + map_keys: Final = (model, get_bedrock_base_model(model)) + if not any(catalog_entry(key) is not None for key in map_keys): return None + deployment_caching: Final = None if model_info is None else lax_bool(model_info.get("supports_prompt_caching")) + if deployment_caching is not None: + return deployment_caching return any( - entry.get("supports_prompt_caching") is True - for key in map_keys - if (entry := litellm.model_cost.get(key)) is not None + entry.get("supports_prompt_caching") is True for key in map_keys if (entry := catalog_entry(key)) is not None ) +def _catalog_entry_reader(model_info: Mapping[str, object] | None) -> Callable[[str], Mapping[str, object] | None]: + from litellm.utils import catalog_with_runtime_registrations + + if model_info is not None: + return catalog_with_runtime_registrations().get + return _model_cost_entry + + def bedrock_supports_tool_search(model: str) -> bool: """ Whether Bedrock InvokeModel admits the ``tool_search_tool_*`` tool types on ``model``. diff --git a/litellm/llms/bedrock/count_tokens/bedrock_token_counter.py b/litellm/llms/bedrock/count_tokens/bedrock_token_counter.py index 26bc5904e06..dec099f37c0 100644 --- a/litellm/llms/bedrock/count_tokens/bedrock_token_counter.py +++ b/litellm/llms/bedrock/count_tokens/bedrock_token_counter.py @@ -13,9 +13,14 @@ from typing_extensions import assert_never import litellm from litellm._logging import verbose_logger from litellm.llms.anthropic.chat.transformation import AnthropicConfig +from litellm.llms.anthropic.common_utils import context_management_betas, context_management_with_edits from litellm.llms.anthropic.count_tokens.transformation import ChatCountTranslationError, anthropic_count_fields from litellm.llms.base_llm.base_utils import BaseTokenCounter -from litellm.llms.bedrock.common_utils import BedrockError, get_bedrock_base_model +from litellm.llms.bedrock.common_utils import ( + BEDROCK_INVOKE_CONTEXT_MANAGEMENT_EDIT_BETAS, + BedrockError, + get_bedrock_base_model, +) from litellm.llms.bedrock.count_tokens.handler import BedrockCountTokensHandler from litellm.llms.bedrock.count_tokens.mantle_handler import BedrockMantleCountTokensHandler from litellm.llms.bedrock_mantle.common_utils import is_mantle_claude_model @@ -74,6 +79,16 @@ def _runtime_rejected_claude_model(outcome: CountTokensOutcome, resolved_model: ) +def _mantle_retry_outcome( + runtime: CountTokensOutcome, mantle: CountTokensOutcome, carried_edits: bool +) -> CountTokensOutcome: + match runtime, mantle: + case CountTokensFailure(status_code=400), CountTokensFailure(status_code=404) if carried_edits: + return runtime + case _: + return mantle + + def _request_data( model: str, messages: Sequence[Mapping[str, object]], tools: Sequence[Mapping[str, object]] | None, system: object ) -> Mapping[str, object]: @@ -85,6 +100,33 @@ def _request_data( } +def _invoke_model_message(message: Mapping[str, object]) -> Mapping[str, object]: + content: Final = message.get("content") + return ( + {**message, "content": [{"type": "text", "text": content}]} if isinstance(content, str) and content else message + ) + + +def _invoke_supports_edit(edit: JsonValue) -> bool: + edit_type: Final = edit.get("type") if isinstance(edit, dict) else None + return isinstance(edit_type, str) and edit_type in BEDROCK_INVOKE_CONTEXT_MANAGEMENT_EDIT_BETAS + + +def _invoke_context_management(context_management: CountContextManagement | None) -> Mapping[str, JsonValue]: + spec: Final = context_management_with_edits(None if context_management is None else context_management.spec) + edits: Final = spec.get("edits") if isinstance(spec, dict) else None + supported_edits: Final = tuple(filter(_invoke_supports_edit, edits if isinstance(edits, list) else ())) + if not isinstance(spec, dict) or not supported_edits: + return MappingProxyType({}) + supported_spec: Final[JsonValue] = {**spec, "edits": list(supported_edits)} + return MappingProxyType( + { + "context_management": supported_spec, + "anthropic_beta": list(context_management_betas(supported_spec)), + } + ) + + class BedrockTokenCounter(BaseTokenCounter): """Counts on the configured Bedrock endpoint, with Mantle retry when Runtime rejects a Claude model""" @@ -167,11 +209,19 @@ class BedrockTokenCounter(BaseTokenCounter): ) if isinstance(translated, ChatCountTranslationError): return translated.response(request_model, model_to_use, primary_tokenizer) - runtime_request: Final = ( - _request_data(model_to_use, messages, tools, system) - if translated is None - else _request_data(model_to_use, translated.messages, translated.tools, translated.system) + native_context_management: Final = _invoke_context_management( + context_management if is_mantle_claude_model(resolved_model) else None ) + counted_messages: Final = messages if translated is None else translated.messages + runtime_request: Final = { + **_request_data( + model_to_use, + tuple(map(_invoke_model_message, counted_messages)) if native_context_management else counted_messages, + tools if translated is None else translated.tools, + system if translated is None else translated.system, + ), + **native_context_management, + } mantle_request: Final = runtime_request if translated is None else {**runtime_request, **translated.options} primary: Final = ( @@ -184,8 +234,12 @@ class BedrockTokenCounter(BaseTokenCounter): ) ) outcome: Final = ( - await self._count_with( - self._mantle_handler, MANTLE_TOKENIZER_TYPE, mantle_request, litellm_params, resolved_model + _mantle_retry_outcome( + primary, + await self._count_with( + self._mantle_handler, MANTLE_TOKENIZER_TYPE, mantle_request, litellm_params, resolved_model + ), + carried_edits=bool(native_context_management), ) if not use_mantle and _runtime_rejected_claude_model(primary, resolved_model) else primary diff --git a/litellm/llms/bedrock/count_tokens/kimi_k3.py b/litellm/llms/bedrock/count_tokens/kimi_k3.py index 5eb46944f9a..1d293bdc99c 100644 --- a/litellm/llms/bedrock/count_tokens/kimi_k3.py +++ b/litellm/llms/bedrock/count_tokens/kimi_k3.py @@ -455,9 +455,7 @@ def _converse_request( if not all(_text_only(message) for message in messages): return None try: - chat_tools: Final = tuple( - chat_tool for tool in tools or () for chat_tool in _as_converse_input(tool) - ) # comprehension-ok: flattens each tool's translation + chat_tools: Final = tuple(chain.from_iterable(_as_converse_input(tool) for tool in tools or ())) return _ConverseRequest.model_validate( litellm.AmazonConverseConfig().transform_request( model=model, diff --git a/litellm/llms/bedrock/count_tokens/mantle_handler.py b/litellm/llms/bedrock/count_tokens/mantle_handler.py index 5cd26235ba2..5e5c5516b94 100644 --- a/litellm/llms/bedrock/count_tokens/mantle_handler.py +++ b/litellm/llms/bedrock/count_tokens/mantle_handler.py @@ -8,7 +8,7 @@ from typing_extensions import NotRequired, ReadOnly, TypedDict import litellm from litellm._logging import verbose_logger from litellm.litellm_core_utils.url_utils import join_api_base -from litellm.llms.anthropic.common_utils import tools_without_custom_field +from litellm.llms.anthropic.common_utils import context_management_betas, tools_without_custom_field from litellm.llms.anthropic.count_tokens.transformation import COUNT_TOKEN_OPTION_NAMES, AnthropicCountTokensConfig from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM, run_aws_signing from litellm.llms.bedrock.common_utils import BedrockError, build_mantle_messages_url @@ -22,6 +22,7 @@ class MantleCountTokensRequest(TypedDict): messages: ReadOnly[list[dict[str, JsonValue]]] system: ReadOnly[NotRequired[JsonValue]] tools: ReadOnly[NotRequired[list[dict[str, JsonValue]]]] + context_management: ReadOnly[NotRequired[JsonValue]] _COUNT_REQUEST: Final = TypeAdapter(MantleCountTokensRequest) @@ -74,13 +75,19 @@ class BedrockMantleCountTokensHandler(BaseAWSLLM): optional_params=_COUNT_OPTIONS.validate_python( {name: value for name, value in request_data.items() if name in COUNT_TOKEN_OPTION_NAMES} ), + context_management=request.get("context_management"), ) + betas: Final = context_management_betas(request.get("context_management")) verbose_logger.debug("Making bedrock-mantle count_tokens request to: %s", endpoint_url) api_key: Final = litellm_params.get("api_key") signed_headers, signed_body = await run_aws_signing( self._sign_request, service_name="bedrock", - headers={"Content-Type": "application/json", "anthropic-version": MANTLE_ANTHROPIC_VERSION}, + headers={ + "Content-Type": "application/json", + "anthropic-version": MANTLE_ANTHROPIC_VERSION, + **({"anthropic-beta": ",".join(betas)} if betas else {}), + }, optional_params=litellm_params, request_data=body, api_base=endpoint_url, diff --git a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude_transformation.py b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude_transformation.py index e5d6a168d57..8b4e2e5b5c5 100644 --- a/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude_transformation.py +++ b/litellm/llms/bedrock/messages/invoke_transformations/anthropic_claude_transformation.py @@ -37,8 +37,10 @@ from litellm.llms.bedrock.chat.invoke_transformations.base_invoke_transformation bedrock_invoke_guardrail_headers, ) from litellm.llms.bedrock.common_utils import ( + BEDROCK_INVOKE_CONTEXT_MANAGEMENT_EDIT_BETAS, BedrockError, apply_bedrock_invoke_structured_output, + bedrock_native_output_is_deployment_opt_in, bedrock_supports_tool_search, ensure_bedrock_anthropic_messages_tool_names, get_anthropic_beta_from_headers, @@ -46,7 +48,7 @@ from litellm.llms.bedrock.common_utils import ( normalize_bedrock_opus_output_config_effort, normalize_custom_field_on_tools, normalize_tool_input_schema_types_for_bedrock_invoke, - requests_opt_in_native_output, + requests_native_output, requests_output_config_format, strip_unsupported_bedrock_invoke_output_config_keys, supports_bedrock_prompt_cache_ttl, @@ -130,7 +132,10 @@ class AmazonAnthropicClaudeMessagesConfig( litellm_params: GenericLiteLLMParams, ) -> GenericLiteLLMParams | None: model_info: Final = _MODEL_INFO.validate_python(litellm_params.model_info) - if not requests_opt_in_native_output(model, anthropic_messages_optional_request_params, model_info): + if not ( + requests_native_output(anthropic_messages_optional_request_params) + and bedrock_native_output_is_deployment_opt_in(model, model_info=model_info) + ): return None return litellm_params.model_copy( update={"model_info": {**(model_info or {}), "supports_bedrock_native_structured_output": False}} @@ -499,12 +504,7 @@ class AmazonAnthropicClaudeMessagesConfig( # Bedrock InvokeModel DOES support ``clear_tool_uses_20250919`` under the # ``context-management-2025-06-27`` beta. AWS docs: # https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages-tool-use.md - _BEDROCK_INVOKE_SUPPORTED_CONTEXT_MANAGEMENT_EDITS: Mapping[str, str] = MappingProxyType( - { - "compact_20260112": ANTHROPIC_BETA_HEADER_VALUES.COMPACT_2026_01_12.value, - "clear_tool_uses_20250919": ANTHROPIC_BETA_HEADER_VALUES.CONTEXT_MANAGEMENT_2025_06_27.value, - } - ) + _BEDROCK_INVOKE_SUPPORTED_CONTEXT_MANAGEMENT_EDITS: Mapping[str, str] = BEDROCK_INVOKE_CONTEXT_MANAGEMENT_EDIT_BETAS @classmethod def _filter_context_management_for_bedrock_invoke( diff --git a/litellm/llms/bedrock/passthrough/guardrail_translation/handler.py b/litellm/llms/bedrock/passthrough/guardrail_translation/handler.py index 3a65a8928bf..3514a5e6e5c 100644 --- a/litellm/llms/bedrock/passthrough/guardrail_translation/handler.py +++ b/litellm/llms/bedrock/passthrough/guardrail_translation/handler.py @@ -14,6 +14,7 @@ from pydantic import InstanceOf, TypeAdapter, ValidationError from typing_extensions import ReadOnly, TypedDict from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.llms.anthropic.chat.guardrail_translation.handler import AnthropicMessagesHandler from litellm.llms.base_llm.guardrail_translation.base_translation import ( BaseTranslation, @@ -60,6 +61,8 @@ if TYPE_CHECKING: _CONVERSE_ACTIONS: Final = frozenset({"converse", "converse-stream"}) _INVOKE_STREAM_ACTION: Final = "invoke-with-response-stream" +_INVOKE_ACTIONS: Final = frozenset({"invoke", _INVOKE_STREAM_ACTION}) +_BLOCK_TYPES_THE_ANTHROPIC_HANDLER_DOES_NOT_SCAN: Final = frozenset({"document", "search_result"}) _EVENT_STREAM_CONTENT_TYPE: Final = "vnd.amazon.eventstream" _EVENT_STREAM_MEDIA_TYPE: Final = "application/vnd.amazon.eventstream" @@ -73,6 +76,83 @@ def _is_invoke_stream_endpoint(endpoint: str) -> bool: return endpoint.rstrip("/").split("/")[-1] == _INVOKE_STREAM_ACTION +def _anthropic_invoke_body( + data: Mapping[str, object], +) -> dict[str, object] | None: # mutable-ok: the body guardrails write back into + """The body of an InvokeModel call in Anthropic Messages format, which Bedrock requires to carry anthropic_version""" + endpoint: Final = data.get("endpoint") + body: Final = data.get("data") + if not isinstance(endpoint, str) or endpoint.rstrip("/").split("/")[-1] not in _INVOKE_ACTIONS: + return None + if not isinstance(body, dict): + return None + invoke_body: Final = _BODY_BY_REFERENCE.validate_python(body) + if not isinstance(invoke_body.get("anthropic_version"), str) or not isinstance(invoke_body.get("messages"), list): + return None + messages: Final = _ARRAY_BY_REFERENCE.validate_python(invoke_body["messages"]) + if not all(_is_well_formed_message(message) for message in messages): + return None + blocks: Final = _anthropic_message_blocks(messages) + if any(block.get("type") in _BLOCK_TYPES_THE_ANTHROPIC_HANDLER_DOES_NOT_SCAN for block in blocks): + return None + return invoke_body + + +def _body_level_request_data( + passthrough_request: Mapping[str, object], +) -> dict[str, object]: # mutable-ok: the request dict guardrails receive + """What `/v1/messages` hands a guardrail as `request_data`: the Anthropic body at the top level, with the proxy's own keys (model, metadata, headers) on top""" + body: Final = as_str_mapping(passthrough_request.get("data")) or {} + proxy_keys: Final = {key: value for key, value in passthrough_request.items() if key != "data"} + return {**body, **proxy_keys} + + +def _is_well_formed_message(message: object) -> bool: + """Whether the Messages translation can read `message`, so a malformed body still reaches Bedrock to be rejected there""" + fields: Final = as_str_mapping(message) + if fields is None or not isinstance(fields.get("role"), str): + return False + content: Final = fields.get("content") + if isinstance(content, str): + return True + return isinstance(content, list) and all( + as_str_mapping(block) is not None for block in _ARRAY_BY_REFERENCE.validate_python(content) + ) + + +def _anthropic_message_blocks(messages: Sequence[object]) -> tuple[Mapping[str, object], ...]: + fields: Final = (as_str_mapping(message) for message in messages) + return tuple(chain.from_iterable(_anthropic_content_blocks(field.get("content")) for field in fields if field)) + + +def _anthropic_content_blocks(content: object) -> tuple[Mapping[str, object], ...]: + blocks: Final[list[Mapping[str, object]]] = [] # mutable-ok: collected while walking the content + pending: Final[list[object]] = [content] # mutable-ok: content lists still to walk, nested tool results included + while pending: + current = pending.pop() + if not isinstance(current, list): + continue + for item in _ARRAY_BY_REFERENCE.validate_python(current): + block = as_str_mapping(item) + if block is None: + continue + blocks.append(block) + if block.get("type") == "tool_result": + pending.append(block.get("content")) + return tuple(blocks) + + +def _anthropic_invoke_reply( + response: object, + request_data: object, +) -> dict[str, object] | None: # mutable-ok: the reply guardrails write back into + if not isinstance(response, dict) or not isinstance(request_data, dict): + return None + if _anthropic_invoke_body(_OBJECT_BY_REFERENCE.validate_python(request_data)) is None: + return None + return _BODY_BY_REFERENCE.validate_python(response) + + def _generic_passthrough_handler() -> "PassThroughEndpointHandler": """ Fallback for non-Converse Bedrock routes (e.g. invoke). The generic @@ -1285,6 +1365,17 @@ class BedrockPassthroughGuardrailHandler(BaseTranslation): body: Final = data.get("data") if not _is_converse_endpoint(endpoint): + passthrough_request: Final = _BODY_BY_REFERENCE.validate_python(data) + anthropic_body: Final = _anthropic_invoke_body(passthrough_request) + if anthropic_body is not None: + await AnthropicMessagesHandler().process_input_messages( # pyright: ignore[reportUnknownMemberType] # takes the untyped request dict + data=anthropic_body, + guardrail_to_apply=guardrail_to_apply, + litellm_logging_obj=litellm_logging_obj, + request_data=_body_level_request_data(passthrough_request), + keep_cache_control=True, + ) + return passthrough_request return await _generic_passthrough_handler().process_input_messages( data=data, guardrail_to_apply=guardrail_to_apply, @@ -1410,6 +1501,15 @@ class BedrockPassthroughGuardrailHandler(BaseTranslation): and not _is_converse_endpoint(endpoint) and not _is_invoke_stream_endpoint(endpoint) ): + anthropic_reply: Final = _anthropic_invoke_reply(response, request_data) # pyright: ignore[reportUnknownArgumentType] # the base signature types request_data as a bare dict + if anthropic_reply is not None: + return await AnthropicMessagesHandler().process_output_response( # pyright: ignore[reportUnknownMemberType] # takes the untyped request dict + response=anthropic_reply, # pyright: ignore[reportArgumentType] # the Anthropic reply dict, written back in place + guardrail_to_apply=guardrail_to_apply, + litellm_logging_obj=litellm_logging_obj, + user_api_key_dict=user_api_key_dict, + request_data=_body_level_request_data(_OBJECT_BY_REFERENCE.validate_python(request_data or {})), + ) return await _generic_passthrough_handler().process_output_response( response=response, guardrail_to_apply=guardrail_to_apply, diff --git a/litellm/llms/bedrock/realtime/handler.py b/litellm/llms/bedrock/realtime/handler.py index 00622a1e287..49939399ec8 100644 --- a/litellm/llms/bedrock/realtime/handler.py +++ b/litellm/llms/bedrock/realtime/handler.py @@ -9,7 +9,7 @@ import contextlib import importlib.metadata import json from collections.abc import AsyncIterator, Awaitable, Callable, Mapping, MutableMapping, Sequence -from dataclasses import dataclass +from dataclasses import dataclass, field from types import MappingProxyType from typing import Final, NoReturn, Protocol, runtime_checkable @@ -34,12 +34,15 @@ from litellm.llms.base_llm.realtime.transformation import RealtimeSessionUpdateR from litellm.types.llms.bedrock import AwsAuthParams from litellm.types.llms.openai import OpenAIRealtimeEvents from litellm.types.realtime import RealtimeResponseTransformInput +from litellm.types.utils import StandardLoggingPayloadErrorInformation from ..base_aws_llm import BaseAWSLLM, run_aws_signing from ..common_utils import BedrockError from .transformation import BedrockRealtimeConfig, requested_modalities _CLIENT_MESSAGE_ADAPTER: Final[TypeAdapter[JsonValue]] = TypeAdapter(JsonValue) +_REQUEST_MAPPING_ADAPTER: Final[TypeAdapter[Mapping[str, object] | None]] = TypeAdapter(Mapping[str, object] | None) +_SPEND_LOG_METADATA_KEYS: Final = ("litellm_metadata", "metadata") _EMPTY_JSON_OBJECT: Final[Mapping[str, JsonValue]] = MappingProxyType({}) @@ -61,6 +64,10 @@ _BEDROCK_STREAM_ERROR_STATUS: Final[Mapping[str, int]] = MappingProxyType( ) +def _stream_ended_before_session_closed() -> BedrockError: + return BedrockError(status_code=503, message="Bedrock realtime stream ended before the session closed") + + def _as_bedrock_error(error: BaseException) -> BaseException: status_code: Final = _BEDROCK_STREAM_ERROR_STATUS.get(type(error).__name__) if status_code is None: @@ -165,6 +172,12 @@ class _BridgeOutcome: client_disconnected: bool +@dataclass(frozen=True, slots=True) +class SessionEndSignals: + input_closing: asyncio.Event = field(default_factory=asyncio.Event) + output_failed: asyncio.Event = field(default_factory=asyncio.Event) + + async def _client_messages(client_ws: RealtimeClientWebSocket, initial_message: str | None) -> AsyncIterator[str]: if initial_message is not None: yield initial_message @@ -188,8 +201,8 @@ def raise_if_session_committed(scope: Mapping[str, object] | None) -> None: raise BedrockError( status_code=400, message=( - "Bedrock realtime session already committed to a provider stream; it cannot be replayed" - + (f". The committed stream failed with: {committed_failure}" if committed_failure else "") + (f"{committed_failure}. " if committed_failure else "") + + "Bedrock realtime session already committed to a provider stream; it cannot be replayed" ), ) @@ -201,11 +214,48 @@ def _pending_opening_message(scope: Mapping[str, object]) -> str | None: return pending if isinstance(pending, str) else None +def _spend_log_metadata(litellm_params: Mapping[str, object]) -> tuple[str, Mapping[str, object]] | None: + return next( + ( + (key, metadata) + for key in _SPEND_LOG_METADATA_KEYS + if (metadata := _REQUEST_MAPPING_ADAPTER.validate_python(litellm_params.get(key))) + ), + None, + ) + + +def _record_failure_on_spend_log(logging_obj: LiteLLMLogging, error: BaseException) -> None: + """The spend row of a session the provider ended reads failure while it still bills the forwarded events.""" + litellm_params: Final = _REQUEST_MAPPING_ADAPTER.validate_python( + logging_obj.model_call_details.get("litellm_params") + ) + if litellm_params is None: + return + spend_log_metadata: Final = _spend_log_metadata(litellm_params) + if spend_log_metadata is None: + return + status_code: Final[object] = getattr(error, "status_code", None) + error_information: Final[StandardLoggingPayloadErrorInformation] = { + "error_code": "" if status_code is None else str(status_code), + "error_class": type(error).__name__, + "error_message": redact_string(str(error)), + "llm_provider": "bedrock", + } + metadata_key, metadata = spend_log_metadata + logging_obj.model_call_details["litellm_params"] = { # rebind-ok: the spend row reads the logging object + **litellm_params, + metadata_key: {**metadata, "status": "failure", "error_information": error_information}, + } + + def _raise_provider_failure(scope: MutableMapping[str, object], failure: BaseException) -> NoReturn: error: Final = _as_bedrock_error(failure) verbose_proxy_logger.error("Bedrock Realtime: provider stream failed: %s", redact_string(str(error))) if _is_session_committed(scope): scope[BEDROCK_REALTIME_COMMITTED_FAILURE_SCOPE_KEY] = redact_string(str(error)) + if error is failure: + raise failure raise error from failure @@ -267,6 +317,25 @@ async def _reject_session_update( return True +async def _close_bedrock_input( + bedrock_stream: BedrockBidirectionalStream, + close_messages: Sequence[str], + send_to_bedrock: Callable[[str], Awaitable[None]], + timeout: float, +) -> None: + async def flush_and_close() -> None: + for close_message in close_messages: + with contextlib.suppress(Exception): + await send_to_bedrock(close_message) + with contextlib.suppress(Exception): + await bedrock_stream.input_stream.close() + + try: + await asyncio.wait_for(flush_and_close(), timeout) + except (asyncio.TimeoutError, TimeoutError): + verbose_proxy_logger.debug("Bedrock Realtime: timed out closing Bedrock input stream after %.1fs", timeout) + + class BedrockRealtime(BaseAWSLLM): """Handler for Bedrock Nova Sonic realtime speech-to-speech API.""" @@ -278,6 +347,18 @@ class BedrockRealtime(BaseAWSLLM): super().__init__() self._sdk_version_lookup: Final = sdk_version_lookup self._close_timeout: Final = close_timeout + self._failed_input_closes: Final[set[asyncio.Task[None]]] = set() # mutable-ok: strong refs to running closes + + def _close_failed_input_in_background( + self, + bedrock_stream: BedrockBidirectionalStream, + send_to_bedrock: Callable[[str], Awaitable[None]], + ) -> None: + close_task: Final = asyncio.create_task( + _close_bedrock_input(bedrock_stream, (), send_to_bedrock, self._close_timeout) + ) + self._failed_input_closes.add(close_task) + close_task.add_done_callback(self._failed_input_closes.discard) async def async_realtime( self, @@ -433,23 +514,26 @@ class BedrockRealtime(BaseAWSLLM): if _should_log_event(leftover_event) ), ) + if outcome.provider_failure is not None and outcome.client_disconnected: + verbose_proxy_logger.debug( + "Bedrock Realtime: stream failed after the client disconnected: %s", outcome.provider_failure + ) + provider_failure: Final = None if outcome.client_disconnected else outcome.provider_failure if logged_events: + if provider_failure is not None: + _record_failure_on_spend_log(logging_obj, _as_bedrock_error(provider_failure)) + usage_logging_obj: Final = logging_obj if provider_failure is None else logging_obj.attempt_scoped_copy() GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue( - logging_obj.dispatch_success_handlers( + usage_logging_obj.dispatch_success_handlers( list(logged_events), prefer_async_handlers=True, ) ) logging_obj.model_call_details[REALTIME_SESSION_SUCCESS_LOGGED_KEY] = True - if outcome.provider_failure is None: + if provider_failure is None: return - if outcome.client_disconnected: - verbose_proxy_logger.debug( - "Bedrock Realtime: stream failed after the client disconnected: %s", outcome.provider_failure - ) - return - _raise_provider_failure(websocket.scope, outcome.provider_failure) + _raise_provider_failure(websocket.scope, provider_failure) async def _bridge( self, @@ -463,16 +547,34 @@ class BedrockRealtime(BaseAWSLLM): ) -> _BridgeOutcome: """Run both forwarding directions until the client leaves or either side fails.""" logged: Final[list[OpenAIRealtimeEvents]] = [] # mutable-ok: events forwarded before a failure are still spend + signals: Final = SessionEndSignals() async def collect_logged_events() -> None: - async for event in self._forward_bedrock_to_client( - bedrock_stream, websocket, transformation_config, model, logging_obj, session_state - ): - logged.append(event) + try: + async for event in self._forward_bedrock_to_client( + bedrock_stream, + websocket, + transformation_config, + model, + logging_obj, + session_state, + signals=signals, + ): + logged.append(event) + except Exception: + signals.output_failed.set() + raise client_task: Final = asyncio.create_task( self._forward_client_to_bedrock( - websocket, bedrock_stream, transformation_config, model, session_state, logging_obj, initial_message + websocket, + bedrock_stream, + transformation_config, + model, + session_state, + logging_obj, + initial_message, + signals=signals, ) ) bedrock_task: Final = asyncio.create_task(collect_logged_events()) @@ -506,6 +608,8 @@ class BedrockRealtime(BaseAWSLLM): session_state: RealtimeResponseTransformInput, logging_obj: LiteLLMLogging | None = None, initial_message: str | None = None, + *, + signals: SessionEndSignals, ) -> None: """Forward messages from client WebSocket to Bedrock stream. @@ -521,7 +625,10 @@ class BedrockRealtime(BaseAWSLLM): async def send_to_bedrock(bedrock_message: str) -> None: event: Final = build_input_chunk(bedrock_message.encode("utf-8")) - await bedrock_stream.input_stream.send(event) + try: + await bedrock_stream.input_stream.send(event) + except Exception as e: + raise _stream_ended_before_session_closed() from e verbose_proxy_logger.debug("Bedrock Realtime: Sent to Bedrock: %s", bedrock_message[:200]) try: @@ -553,20 +660,13 @@ class BedrockRealtime(BaseAWSLLM): client_ws, transformation_config, model, logging_obj, parsed_client_message ): break + signals.input_closing.set() finally: - - async def close_bedrock_input() -> None: - for close_message in transformation_config.session_close_messages(): - with contextlib.suppress(Exception): - await send_to_bedrock(close_message) - with contextlib.suppress(Exception): - await bedrock_stream.input_stream.close() - - try: - await asyncio.wait_for(close_bedrock_input(), self._close_timeout) - except (asyncio.TimeoutError, TimeoutError): - verbose_proxy_logger.debug( - "Bedrock Realtime: timed out closing Bedrock input stream after %.1fs", self._close_timeout + if signals.output_failed.is_set(): + self._close_failed_input_in_background(bedrock_stream, send_to_bedrock) + else: + await _close_bedrock_input( + bedrock_stream, transformation_config.session_close_messages(), send_to_bedrock, self._close_timeout ) async def _forward_bedrock_to_client( @@ -577,6 +677,8 @@ class BedrockRealtime(BaseAWSLLM): model: str, logging_obj: LiteLLMLogging, session_state: RealtimeResponseTransformInput, + *, + signals: SessionEndSignals, ) -> AsyncIterator[OpenAIRealtimeEvents]: """Forward messages from Bedrock to the client, yielding the ones to record for spend logging. @@ -597,6 +699,8 @@ class BedrockRealtime(BaseAWSLLM): result = await output[1].receive() if result is None: + if not signals.input_closing.is_set(): + raise _stream_ended_before_session_closed() verbose_proxy_logger.debug("Bedrock Realtime: Bedrock stream ended") with contextlib.suppress(Exception): await client_ws.close() diff --git a/litellm/llms/bedrock_mantle/responses/transformation.py b/litellm/llms/bedrock_mantle/responses/transformation.py index 05855c307e9..1f7b1712d68 100644 --- a/litellm/llms/bedrock_mantle/responses/transformation.py +++ b/litellm/llms/bedrock_mantle/responses/transformation.py @@ -15,7 +15,8 @@ role / access key / profile / web identity), signed via the shared BaseAWSLLM._sign_request after the request body is finalized. """ -from collections.abc import Mapping, Sequence +from collections.abc import Callable, Mapping, Sequence +from functools import partial from typing import Final, cast # noqa: TID251 # map_openai_params returns the filtered params as a bare dict import httpx @@ -23,6 +24,7 @@ import httpx import litellm from litellm._logging import verbose_logger from litellm.litellm_core_utils.core_helpers import drops_unsupported_params +from litellm.litellm_core_utils.prompt_templates.common_utils import chat_completion_prompt_cache_breakpoint_for_wire from litellm.litellm_core_utils.url_utils import join_api_base from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.llms.base_llm.responses.codex_compat import drop_unsupported_tools, normalize_codex_input_items @@ -62,6 +64,10 @@ _BEDROCK_MANTLE_SUPPORTED_SERVICE_TIERS: Final = frozenset({"auto", "default"}) _BEDROCK_MANTLE_OPENAI_PATH_SUPPORTED_REASONING_SUMMARIES: Final = frozenset({"auto"}) +def _prompt_cache_breakpoint_as_sent_or_none(marker: object) -> object: + return marker if chat_completion_prompt_cache_breakpoint_for_wire(marker, drop_params=True) == marker else None + + class BedrockMantleResponsesAPIConfig(BedrockMantleAuthMixin, OpenAIResponsesAPIConfig): def __init__( self, @@ -113,6 +119,13 @@ class BedrockMantleResponsesAPIConfig(BedrockMantleAuthMixin, OpenAIResponsesAPI headers["OpenAI-Project"] = litellm_params.aws_bedrock_project_id return headers + def _prompt_cache_breakpoint_to_wire( + self, litellm_params: GenericLiteLLMParams, reads_breakpoints: bool, known_support: bool | None + ) -> Callable[[object], object]: + if reads_breakpoints or known_support is True: + return partial(chat_completion_prompt_cache_breakpoint_for_wire, drop_params=True) + return _prompt_cache_breakpoint_as_sent_or_none + def supports_native_file_search(self) -> bool: return False diff --git a/litellm/llms/chatgpt/authenticator.py b/litellm/llms/chatgpt/authenticator.py index b237116c5f1..d286d572a35 100644 --- a/litellm/llms/chatgpt/authenticator.py +++ b/litellm/llms/chatgpt/authenticator.py @@ -66,6 +66,13 @@ def get_cached_authenticator(auth_file: str) -> "Authenticator": return Authenticator(auth_file=auth_file) +def resolve_chatgpt_authenticator( + litellm_params: "Mapping[str, object] | GenericLiteLLMParams | None", default: "Authenticator" +) -> "Authenticator": + auth_file: Final = get_chatgpt_auth_file(litellm_params) + return get_cached_authenticator(auth_file) if auth_file else default + + def _token_refresh_timeout() -> httpx.Timeout: configured: Final = get_configured_request_timeout() seconds: Final = ( diff --git a/litellm/llms/chatgpt/chat/transformation.py b/litellm/llms/chatgpt/chat/transformation.py index 9005185931f..e8f057b4d3d 100644 --- a/litellm/llms/chatgpt/chat/transformation.py +++ b/litellm/llms/chatgpt/chat/transformation.py @@ -6,7 +6,7 @@ from litellm.llms.openai.openai import OpenAIConfig from litellm.types.llms.openai import AllMessageValues from litellm.types.router import GenericLiteLLMParams -from ..authenticator import Authenticator, get_cached_authenticator, get_chatgpt_auth_file +from ..authenticator import Authenticator, get_chatgpt_auth_file, resolve_chatgpt_authenticator from ..common_utils import ( GetAccessTokenError, chatgpt_client_api_base, @@ -30,12 +30,6 @@ class ChatGPTConfig(OpenAIConfig): super().__init__() self.authenticator = authenticator if authenticator is not None else Authenticator() - def _resolve_authenticator( - self, litellm_params: Mapping[str, object] | GenericLiteLLMParams | None - ) -> Authenticator: - auth_file: Final = get_chatgpt_auth_file(litellm_params) - return get_cached_authenticator(auth_file) if auth_file else self.authenticator - @staticmethod def _get_access_token_or_raise(authenticator: Authenticator, model: str, llm_provider: str) -> str: try: @@ -63,7 +57,7 @@ class ChatGPTConfig(OpenAIConfig): return chatgpt_client_api_base(api_base), client_credential.access_token, custom_llm_provider if api_key: return api_base or self.api_base_without_login(), api_key, custom_llm_provider - authenticator: Final = self._resolve_authenticator(litellm_params) + authenticator: Final = resolve_chatgpt_authenticator(litellm_params, self.authenticator) dynamic_api_base: Final = authenticator.get_api_base() dynamic_api_key: Final = self._get_access_token_or_raise(authenticator, model, custom_llm_provider) return dynamic_api_base, dynamic_api_key, custom_llm_provider @@ -98,7 +92,7 @@ class ChatGPTConfig(OpenAIConfig): ), **strip_chatgpt_client_credential_headers(headers), ) - authenticator: Final = self._resolve_authenticator(litellm_params) + authenticator: Final = resolve_chatgpt_authenticator(litellm_params, self.authenticator) resolved_api_key: Final = ( self._get_access_token_or_raise(authenticator, model, "chatgpt") if get_chatgpt_auth_file(litellm_params) diff --git a/litellm/llms/chatgpt/common_utils.py b/litellm/llms/chatgpt/common_utils.py index cd2ea6b9ccc..88f2eecec0c 100644 --- a/litellm/llms/chatgpt/common_utils.py +++ b/litellm/llms/chatgpt/common_utils.py @@ -7,7 +7,7 @@ import hashlib import json import os import platform -from collections.abc import Mapping, Sequence +from collections.abc import Mapping from dataclasses import dataclass from types import MappingProxyType from typing import TYPE_CHECKING, Final, TypeAlias @@ -20,14 +20,10 @@ from pydantic import JsonValue, TypeAdapter from litellm.litellm_core_utils.get_provider_specific_headers import ProviderSpecificHeaderUtils from litellm.litellm_core_utils.provider_affinity import get_caller_litellm_session_id, get_requested_session_id from litellm.llms.base_llm.chat.transformation import BaseLLMException -from litellm.types.utils import ProviderSpecificHeader if TYPE_CHECKING: from litellm.types.router import GenericLiteLLMParams -_SCOPED_HEADERS: Final[TypeAdapter[ProviderSpecificHeader | Sequence[ProviderSpecificHeader] | None]] = TypeAdapter( - ProviderSpecificHeader | Sequence[ProviderSpecificHeader] | None -) _STRING_HEADERS: Final = TypeAdapter(Mapping[str, str]) _PARAMS: Final = TypeAdapter(Mapping[str, object]) @@ -357,8 +353,8 @@ def get_chatgpt_request_credential( normalized: Final = _normalize_litellm_params(params) scoped: Final = normalized.get("provider_specific_header") extra: Final = normalized.get("extra_headers") - headers: Final = ProviderSpecificHeaderUtils.get_provider_specific_headers( - provider_specific_header=_SCOPED_HEADERS.validate_python(scoped), custom_llm_provider="chatgpt" + headers: Final = ProviderSpecificHeaderUtils.validated_provider_specific_headers( + provider_specific_header=scoped, custom_llm_provider="chatgpt" ) return get_chatgpt_client_credential(headers) or get_chatgpt_client_credential( _STRING_HEADERS.validate_python(extra) if extra is not None else MappingProxyType({}) diff --git a/litellm/llms/chatgpt/responses/transformation.py b/litellm/llms/chatgpt/responses/transformation.py index 26a5a3f150b..3c7d0b8d673 100644 --- a/litellm/llms/chatgpt/responses/transformation.py +++ b/litellm/llms/chatgpt/responses/transformation.py @@ -28,7 +28,7 @@ from litellm.types.llms.openai import ( from litellm.types.router import GenericLiteLLMParams from litellm.types.utils import LlmProviders -from ..authenticator import Authenticator, get_cached_authenticator, get_chatgpt_auth_file +from ..authenticator import Authenticator, get_chatgpt_auth_file, resolve_chatgpt_authenticator from ..common_utils import ( CHATGPT_API_BASE, GetAccessTokenError, @@ -64,10 +64,6 @@ class ChatGPTResponsesAPIConfig(OpenAIResponsesAPIConfig): def custom_llm_provider(self) -> LlmProviders: return LlmProviders.CHATGPT - def _resolve_authenticator(self, litellm_params: GenericLiteLLMParams | None) -> Authenticator: - auth_file: Final = get_chatgpt_auth_file(litellm_params) - return get_cached_authenticator(auth_file) if auth_file else self.authenticator - def validate_environment( self, headers: dict[str, str], @@ -81,7 +77,7 @@ class ChatGPTResponsesAPIConfig(OpenAIResponsesAPIConfig): **get_chatgpt_default_headers(client_credential.access_token, client_credential.account_id, session_id), **strip_chatgpt_client_credential_headers(headers), } - authenticator: Final = self._resolve_authenticator(litellm_params) + authenticator: Final = resolve_chatgpt_authenticator(litellm_params, self.authenticator) safe_headers: Final = strip_chatgpt_client_credential_headers(headers) configured_api_key: Final = litellm_params.api_key if litellm_params is not None else None if configured_api_key and not get_chatgpt_auth_file(litellm_params): diff --git a/litellm/llms/cohere/chat/v2_transformation.py b/litellm/llms/cohere/chat/v2_transformation.py index cf033e10b41..141a174e558 100644 --- a/litellm/llms/cohere/chat/v2_transformation.py +++ b/litellm/llms/cohere/chat/v2_transformation.py @@ -6,6 +6,7 @@ from typing import TYPE_CHECKING, Any, Final import httpx import litellm +from litellm.litellm_core_utils.core_helpers import map_finish_reason from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig from litellm.types.llms.cohere import CohereV2ChatResponse @@ -248,6 +249,9 @@ class CohereV2ChatConfig(OpenAIGPTConfig): prompt_tokens: Final = token_usage.get("input_tokens", 0) completion_tokens: Final = token_usage.get("output_tokens", 0) + model_response.choices[0].finish_reason = map_finish_reason( # rebind-ok: ModelResponse is filled in place + cohere_v2_chat_response.get("finish_reason", "COMPLETE") + ) model_response.created = int(time.time()) model_response.model = model usage: Final = Usage( diff --git a/litellm/llms/cohere/embed/handler.py b/litellm/llms/cohere/embed/handler.py index 2f60d94c08a..34fde444880 100644 --- a/litellm/llms/cohere/embed/handler.py +++ b/litellm/llms/cohere/embed/handler.py @@ -82,7 +82,7 @@ async def async_embedding( ) try: - response: Final = await client.post(api_base, headers=headers, data=json.dumps(data)) + response: Final = await client.post(api_base, headers=headers, data=json.dumps(data), timeout=timeout) except httpx.HTTPStatusError as e: ## LOGGING logging_obj.post_call( @@ -166,7 +166,7 @@ def embedding( if client is None or not isinstance(client, HTTPHandler): client = HTTPHandler(concurrent_limit=1) - response: Final = client.post(embed_url, headers=headers, data=json.dumps(data)) + response: Final = client.post(embed_url, headers=headers, data=json.dumps(data), timeout=timeout) return CohereEmbeddingConfig().transform_response( response=response, diff --git a/litellm/llms/cohere/embed/v1_transformation.py b/litellm/llms/cohere/embed/v1_transformation.py index ad5bfa507e5..056b5bce742 100644 --- a/litellm/llms/cohere/embed/v1_transformation.py +++ b/litellm/llms/cohere/embed/v1_transformation.py @@ -9,6 +9,7 @@ import httpx from litellm import COHERE_DEFAULT_EMBEDDING_INPUT_TYPE from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms.custom_httpx.http_handler import header_value from litellm.types.llms.bedrock import ( CohereEmbeddingRequest, CohereEmbeddingRequestWithModel, @@ -23,6 +24,11 @@ class _SupportsEncode(Protocol): def encode(self, text: str, /) -> Sized: ... +def _bedrock_billed_input_tokens(response: httpx.Response) -> int | None: + count: Final = header_value(response.headers, "x-amzn-bedrock-input-token-count") + return int(count) if count is not None and count.isdigit() else None + + class CohereEmbeddingConfig: """ Reference: https://docs.cohere.com/v2/reference/embed @@ -76,32 +82,30 @@ class CohereEmbeddingConfig: ) -> CohereEmbeddingRequestWithModel: return self._transform_request(model, input, inference_params) - def _calculate_usage(self, input: list[str], encoding: _SupportsEncode, meta: dict) -> Usage: - input_tokens = 0 - + def _calculate_usage( + self, input: list[str], encoding: _SupportsEncode, meta: dict, billed_input_tokens: int | None = None + ) -> Usage: text_tokens: Final[int | None] = meta.get("billed_units", {}).get("input_tokens") image_tokens: Final[int | None] = meta.get("billed_units", {}).get("images") - prompt_tokens_details: PromptTokensDetailsWrapper | None = None if image_tokens is None and text_tokens is None: - for text in input: - input_tokens += len(encoding.encode(text)) - else: - prompt_tokens_details = PromptTokensDetailsWrapper( - image_tokens=image_tokens, - text_tokens=text_tokens, + counted_tokens: Final = ( + billed_input_tokens + if billed_input_tokens is not None + else sum(len(encoding.encode(text)) for text in input) ) - if image_tokens: - input_tokens += image_tokens - if text_tokens: - input_tokens += text_tokens + return Usage(prompt_tokens=counted_tokens, completion_tokens=0, total_tokens=counted_tokens) + input_tokens: Final = (image_tokens or 0) + (text_tokens or 0) return Usage( prompt_tokens=input_tokens, completion_tokens=0, total_tokens=input_tokens, - prompt_tokens_details=prompt_tokens_details, + prompt_tokens_details=PromptTokensDetailsWrapper( + image_tokens=image_tokens, + text_tokens=text_tokens, + ), ) def _transform_response( @@ -129,6 +133,7 @@ class CohereEmbeddingConfig: model=model, encoding=encoding, input=input, + billed_input_tokens=_bedrock_billed_input_tokens(response) if "images" in data else None, ) def transform_response( @@ -151,6 +156,7 @@ class CohereEmbeddingConfig: model: str, encoding: _SupportsEncode, input: list, + billed_input_tokens: int | None = None, ) -> EmbeddingResponse: """ Parse a Cohere embed response body into an OpenAI-style EmbeddingResponse. @@ -195,7 +201,7 @@ class CohereEmbeddingConfig: setattr( model_response, "usage", - self._calculate_usage(input, encoding, response_json.get("meta", {})), + self._calculate_usage(input, encoding, response_json.get("meta", {}), billed_input_tokens), ) return model_response diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py index 8a094cc6424..4a10db31606 100644 --- a/litellm/llms/custom_httpx/llm_http_handler.py +++ b/litellm/llms/custom_httpx/llm_http_handler.py @@ -37,11 +37,22 @@ import litellm import litellm.litellm_core_utils import litellm.types import litellm.types.utils +from litellm._internal_context import internal_sub_call from litellm._logging import redact_string, verbose_logger -from litellm.anthropic_beta_headers_manager import aload_beta_headers_config, update_headers_with_filtered_beta +from litellm.anthropic_beta_headers_manager import ( + aload_beta_headers_config, + resolve_beta_provider, + update_headers_with_filtered_beta, +) from litellm.constants import MAX_FILE_LIST_LIMIT, REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES from litellm.files.types import FileContentStreamingResult from litellm.litellm_core_utils.agentic_followup_kwargs import build_agentic_followup_kwargs +from litellm.litellm_core_utils.agentic_loop_refusal import ( + every_claimed_tool_call, + finalize_refused_responses_turn, + is_refused_item, + refused_tool_call_identifiers, +) from litellm.litellm_core_utils.agentic_loop_settings import ( DEFAULT_MAX_AGENTIC_LOOPS, validated_max_agentic_loops, @@ -51,11 +62,11 @@ from litellm.litellm_core_utils.audio_utils.subtitle_utils import ( SUBTITLE_RESPONSE_FORMATS, synthesize_subtitle_document, ) -from litellm.litellm_core_utils.core_helpers import ( - as_str_mapping, - qualify_agentic_followup_model, - set_provider_response_headers_in_hidden_params, +from litellm.litellm_core_utils.chat_completion_agentic_loop import ( + bill_first_round_on_failure, + run_chat_completion_agentic_hooks, ) +from litellm.litellm_core_utils.core_helpers import as_str_mapping, set_provider_response_headers_in_hidden_params from litellm.litellm_core_utils.dot_notation_indexing import delete_nested_value from litellm.litellm_core_utils.get_litellm_params import AWS_CREDENTIAL_KWARGS_KEYS from litellm.litellm_core_utils.get_llm_provider_logic import get_provider_affinity_header @@ -145,6 +156,7 @@ from litellm.types.extraction import ExtractionResponse from litellm.types.files import StreamingMediaUploadConfig, TwoStepFileUploadConfig from litellm.types.integrations.custom_logger import ( NON_CODE_INTERPRETER_INTERCEPTION_INTERNAL_PREFIXES, + AgenticLoopLimitError, AgenticLoopPlan, AgenticLoopRequestPatch, AgenticLoopSafetyError, @@ -455,6 +467,20 @@ def _google_genai_streaming_hidden_params( } +def _log_generate_content_request( + logging_obj: LiteLLMLoggingObj, + contents: object, + api_base: str, + headers: Mapping[str, object], + body: Mapping[str, object], +) -> None: + logging_obj.pre_call( + input=contents, + api_key="", + additional_args={"complete_input_dict": body, "api_base": api_base, "headers": headers}, + ) + + @lru_cache(maxsize=None) def _responses_api_optional_request_param_names() -> frozenset[str]: return frozenset(get_type_hints(ResponsesAPIOptionalRequestParams).keys()) @@ -2581,14 +2607,16 @@ class BaseLLMHTTPHandler: litellm_params.get("additional_drop_params") or (), anthropic_messages_optional_request_params, ) - if ( - request_params.get("safeguards") is not None - and anthropic_messages_provider_config.should_filter_anthropic_beta_headers() - ): - await aload_beta_headers_config() affinity_api_base: Final = ( AnthropicModelInfo.get_api_base(api_base) if custom_llm_provider == "anthropic" else api_base ) + takes_another_beta_row: Final = ( + resolve_beta_provider(custom_llm_provider, affinity_api_base) != custom_llm_provider + ) + provider_filters_betas: Final = anthropic_messages_provider_config.should_filter_anthropic_beta_headers() + filters_beta_headers: Final = provider_filters_betas or takes_another_beta_row + if request_params.get("safeguards") is not None and filters_beta_headers: + await aload_beta_headers_config() default_affinity_header: Final = get_provider_affinity_header(affinity_api_base) ( headers, @@ -2607,8 +2635,14 @@ class BaseLLMHTTPHandler: api_base=api_base, ) - if anthropic_messages_provider_config.should_filter_anthropic_beta_headers(): - headers = update_headers_with_filtered_beta(headers=headers, provider=custom_llm_provider) + if filters_beta_headers and headers.get("anthropic-beta") is not None: + await aload_beta_headers_config() + headers = update_headers_with_filtered_beta( + headers=headers, + provider=custom_llm_provider, + api_base=affinity_api_base, + unlisted="drop" if provider_filters_betas else "forward", + ) from litellm.llms.vertex_ai.vertex_llm_base import VertexBase @@ -5978,7 +6012,7 @@ class BaseLLMHTTPHandler: @staticmethod def _check_agentic_loop_safety( tool_calls: object, - fingerprints: list[str], + fingerprints: Sequence[str], depth: int, max_loops: int, model: str, @@ -5997,7 +6031,7 @@ class BaseLLMHTTPHandler: if fingerprint in fingerprints: raise AgenticLoopSafetyError("Agentic loop detected repeated tool-call fingerprint; aborting rerun") if depth >= max_loops: - raise AgenticLoopSafetyError(f"Exceeded max_agentic_loops={max_loops} for model={model}") + raise AgenticLoopLimitError(f"Exceeded max_agentic_loops={max_loops} for model={model}") return fingerprint @staticmethod @@ -6007,26 +6041,6 @@ class BaseLLMHTTPHandler: except Exception: return str(tools) - @staticmethod - def _refused_agentic_tool_identifiers(tool_calls: object) -> tuple[frozenset[str], frozenset[str]]: - """ - Collect the ids and names of the tool calls a safety rail just refused. - - Callbacks hand back either a bare list of tool calls or a dict wrapping - that list under ``tool_calls``, and both the anthropic and responses - shapes carry an ``id`` (or ``call_id``) plus a ``name``. - """ - calls: Final = tool_calls.get("tool_calls") if isinstance(tool_calls, dict) else tool_calls - if not isinstance(calls, list): - return frozenset(), frozenset() - dict_calls: Final = (call for call in calls if isinstance(call, dict)) - fields: Final = tuple((call.get("id"), call.get("call_id"), call.get("name")) for call in dict_calls) - ids: Final = frozenset( - value for call_id, caller_id, _ in fields for value in (call_id, caller_id) if isinstance(value, str) - ) - names: Final = frozenset(name for _, _, name in fields if isinstance(name, str)) - return ids, names - @staticmethod def _is_refused_tool_use_block(block: object, refused_ids: frozenset[str], refused_names: frozenset[str]) -> bool: """ @@ -6037,22 +6051,13 @@ class BaseLLMHTTPHandler: share a name with a refused one. The name is only consulted for tool call shapes that arrive without an id. """ - if not isinstance(block, dict) or block.get("type") != "tool_use": - return False - block_id: Final = block.get("id") - if isinstance(block_id, str) and refused_ids: - return block_id in refused_ids - return block.get("name") in refused_names + return is_refused_item(block, "tool_use", "id", refused_ids, refused_names) @staticmethod def _can_replace_turn_with_terminal_response(stream: bool, api_surface: str) -> bool: """ Whether a refused rerun can still be answered with a finalized turn. - Only the anthropic messages surface can. The responses surface carries a - pydantic model the finalizer does not rewrite, so it keeps raising, which - is what every surface did before this path learned to end the turn. - The messages and responses call sites pass ``stream=False``, because interception converts an intercepted stream to non-streaming before the loop runs and rebuilds the SSE stream from the finalized turn @@ -6061,7 +6066,7 @@ class BaseLLMHTTPHandler: finalized turn would reach the client as a second message rather than as a replacement. """ - return not stream and api_surface == "anthropic_messages" + return not stream and api_surface in ("anthropic_messages", "responses") @staticmethod def _finalize_refused_agentic_response(response: object, tool_calls: object) -> object: @@ -6078,10 +6083,12 @@ class BaseLLMHTTPHandler: one is still in the response the stop reason stays ``tool_use`` so the client knows to answer it. """ + if isinstance(response, ResponsesAPIResponse): + return finalize_refused_responses_turn(response, tool_calls) if not isinstance(response, dict): return response - refused_ids, refused_names = BaseLLMHTTPHandler._refused_agentic_tool_identifiers(tool_calls) + refused_ids, refused_names = refused_tool_call_identifiers(tool_calls) finalized: Final = dict(response) content: Final = finalized.get("content") if isinstance(content, list): @@ -6108,7 +6115,7 @@ class BaseLLMHTTPHandler: kwargs: dict, depth: int, max_loops: int, - fingerprints: list[str], + fingerprints: Sequence[str], fingerprint: str, stream: bool = False, callback: Optional["CustomLogger"] = None, @@ -6149,7 +6156,7 @@ class BaseLLMHTTPHandler: kwargs_for_followup.update(patch.kwargs) kwargs_for_followup["_agentic_loop_depth"] = depth + 1 kwargs_for_followup["max_agentic_loops"] = max_loops - kwargs_for_followup["_agentic_loop_fingerprints"] = fingerprints + [fingerprint] + kwargs_for_followup["_agentic_loop_fingerprints"] = [*fingerprints, fingerprint] response: AnthropicMessagesResponse | AsyncIterator[object] = await anthropic_messages.acreate( **{ @@ -6188,7 +6195,7 @@ class BaseLLMHTTPHandler: kwargs: dict, depth: int, max_loops: int, - fingerprints: list[str], + fingerprints: Sequence[str], fingerprint: str, callback: Optional["CustomLogger"] = None, ) -> ResponsesAPIResponse | BaseResponsesAPIStreamingIterator: @@ -6226,12 +6233,13 @@ class BaseLLMHTTPHandler: ) try: - response: ResponsesAPIResponse | BaseResponsesAPIStreamingIterator = await litellm.aresponses( - model=patch.model or model, - input=patch.messages, # pyright: ignore[reportArgumentType] # pre-existing mismatch surfaced by the Router import; patch messages are valid response input at runtime - **optional_params, - **kwargs_for_followup, - ) + with internal_sub_call(logging_obj.litellm_call_id): + response: ResponsesAPIResponse | BaseResponsesAPIStreamingIterator = await litellm.aresponses( + model=patch.model or model, + input=patch.messages, # pyright: ignore[reportArgumentType] # pre-existing mismatch surfaced by the Router import; patch messages are valid response input at runtime + **optional_params, + **kwargs_for_followup, + ) if callback is not None: try: @@ -6308,64 +6316,6 @@ class BaseLLMHTTPHandler: custom_llm_provider=custom_llm_provider, ) - async def _execute_chat_completion_agentic_plan( - self, - plan: AgenticLoopPlan, - model: str, - messages: list[dict], - optional_params: dict, - kwargs: dict, - custom_llm_provider: str, - depth: int, - max_loops: int, - fingerprints: list[str], - fingerprint: str, - ) -> ModelResponse | CustomStreamWrapper: - patch: Final = plan.request_patch or AgenticLoopRequestPatch() - if patch.messages is None: - raise ValueError("Agentic loop plan missing patched messages") - - full_model_name: Final = qualify_agentic_followup_model(patch.model, model, custom_llm_provider) - - optional_params_for_followup: Final = dict(optional_params) - optional_params_for_followup.update(patch.optional_params) - if patch.tools is not None: - optional_params_for_followup["tools"] = patch.tools - - internal_params: Final = { - "_websearch_interception", - "acompletion", - "litellm_logging_obj", - "custom_llm_provider", - "model_alias_map", - "stream_response", - "custom_prompt_dict", - } - kwargs_for_followup: Final = build_agentic_followup_kwargs( - request_kwargs=MappingProxyType( - { - k: v - for k, v in kwargs.items() - if not k.startswith("_websearch_interception") - and not k.startswith("_compression_interception") - and k not in internal_params - } - ), - patch_kwargs=patch.kwargs, - request_params=frozenset((*optional_params_for_followup, "model", "messages")), - depth=depth, - max_loops=max_loops, - fingerprints=fingerprints, - fingerprint=fingerprint, - ) - - return await litellm.acompletion( - model=full_model_name, - messages=patch.messages, - **optional_params_for_followup, - **kwargs_for_followup, - ) - def _maybe_wrap_in_fake_stream( self, response: _ResponseT, @@ -6482,26 +6432,38 @@ class BaseLLMHTTPHandler: except AgenticLoopSafetyError as e: if not self._can_replace_turn_with_terminal_response(stream, api_surface): raise - verbose_logger.warning( - "LiteLLM.AgenticLoopRefused: ending turn [call_id=%s model=%s]: %s", - logging_obj.litellm_call_id, - model, - str(e), - ) + verbose_logger.warning("LiteLLM.AgenticLoopRefused: ending turn [rail=%s]", type(e).__name__) return self._maybe_wrap_in_fake_stream( - self._finalize_refused_agentic_response(response=response, tool_calls=tool_calls), + self._finalize_refused_agentic_response( + response=response, + tool_calls=await every_claimed_tool_call( + tool_calls, + ( + other.async_should_run_agentic_loop( + response=response, + model=model, + messages=messages, + tools=tools, + stream=stream, + custom_llm_provider=custom_llm_provider, + kwargs=hook_kwargs, + ) + for other in callbacks + if isinstance(other, CustomLogger) and other is not callback + ), + ), + ), logging_obj, api_surface, ) - try: - kwargs_with_provider = hook_kwargs.copy() - kwargs_with_provider["custom_llm_provider"] = custom_llm_provider - build_plan_overridden = ( - callback.__class__.async_build_agentic_loop_plan is not CustomLogger.async_build_agentic_loop_plan - ) - if not build_plan_overridden: - agentic_result: object = await callback.async_run_agentic_loop( + kwargs_with_provider = {**hook_kwargs, "custom_llm_provider": custom_llm_provider} + build_plan_overridden = ( + callback.__class__.async_build_agentic_loop_plan is not CustomLogger.async_build_agentic_loop_plan + ) + if not build_plan_overridden: + agentic_result: object = await bill_first_round_on_failure( + callback.async_run_agentic_loop( tools=tool_calls, model=model, messages=messages, @@ -6511,10 +6473,15 @@ class BaseLLMHTTPHandler: logging_obj=logging_obj, stream=stream, kwargs=kwargs_with_provider, - ) - return self._maybe_wrap_in_fake_stream(agentic_result, logging_obj, api_surface) + ), + logging_obj=logging_obj, + response=response, + stream=stream, + ) + return self._maybe_wrap_in_fake_stream(agentic_result, logging_obj, api_surface) - plan = await callback.async_build_agentic_loop_plan( + plan = await bill_first_round_on_failure( + callback.async_build_agentic_loop_plan( tools=tool_calls, model=model, messages=messages, @@ -6524,30 +6491,35 @@ class BaseLLMHTTPHandler: logging_obj=logging_obj, stream=stream, kwargs=kwargs_with_provider, + ), + logging_obj=logging_obj, + response=response, + stream=stream, + ) + + if plan.response_override is not None: + return self._maybe_wrap_in_fake_stream(plan.response_override, logging_obj, api_surface) + if plan.terminate: + verbose_logger.debug( + "Agentic loop terminated by callback=%s reason=%s", + callback.__class__.__name__, + plan.stop_reason, ) + return self._maybe_wrap_in_fake_stream( + await callback.async_post_agentic_loop_response_hook( + response=self._finalize_refused_agentic_response(response=response, tool_calls=tool_calls), + plan=plan, + kwargs=kwargs_with_provider, + ), + logging_obj, + api_surface, + ) + if not plan.run_agentic_loop: + continue - if plan.response_override is not None: - return self._maybe_wrap_in_fake_stream(plan.response_override, logging_obj, api_surface) - if plan.terminate: - verbose_logger.debug( - "Agentic loop terminated by callback=%s reason=%s", - callback.__class__.__name__, - plan.stop_reason, - ) - return self._maybe_wrap_in_fake_stream( - await callback.async_post_agentic_loop_response_hook( - response=self._finalize_refused_agentic_response(response=response, tool_calls=tool_calls), - plan=plan, - kwargs=kwargs_with_provider, - ), - logging_obj, - api_surface, - ) - if not plan.run_agentic_loop: - continue - - if api_surface == "responses": - return await self._execute_responses_agentic_plan( + if api_surface == "responses": + return await bill_first_round_on_failure( + self._execute_responses_agentic_plan( plan=plan, model=model, response_api_optional_request_params=anthropic_messages_optional_request_params, @@ -6558,10 +6530,15 @@ class BaseLLMHTTPHandler: fingerprints=fingerprints, fingerprint=fingerprint, callback=callback, - ) + ), + logging_obj=logging_obj, + response=response, + stream=stream, + ) - return self._maybe_wrap_in_fake_stream( - await self._execute_anthropic_agentic_plan( + return self._maybe_wrap_in_fake_stream( + await bill_first_round_on_failure( + self._execute_anthropic_agentic_plan( plan=plan, model=model, messages=messages, @@ -6575,17 +6552,13 @@ class BaseLLMHTTPHandler: stream=stream, callback=callback, ), - logging_obj, - api_surface, - ) - except Exception as e: - _call_id = getattr(logging_obj, "litellm_call_id", "unknown") - verbose_logger.exception( - "LiteLLM.AgenticHookError: Exception in agentic completion hooks [call_id=%s model=%s]: %s", - _call_id, - model, - str(e), - ) + logging_obj=logging_obj, + response=response, + stream=stream, + ), + logging_obj, + api_surface, + ) # Check if we need to convert response to fake stream # This happens when: @@ -6617,110 +6590,23 @@ class BaseLLMHTTPHandler: Returns the response from agentic loop, or None if no hook runs. """ - from litellm._logging import verbose_logger - from litellm.integrations.custom_logger import CustomLogger - - callbacks: Final = litellm.callbacks + (logging_obj.dynamic_success_callbacks or []) - tools: Final = optional_params.get("tools", []) - depth, max_loops, fingerprints = self._get_agentic_loop_settings(kwargs=kwargs) - - for callback in callbacks: - if not isinstance(callback, CustomLogger): - continue - if not hasattr(callback, "async_should_run_chat_completion_agentic_loop"): - continue - - should_run: bool = False - tool_calls: object = None - try: - ( - should_run, - tool_calls, - ) = await callback.async_should_run_chat_completion_agentic_loop( - response=response, - model=model, - messages=messages, - tools=tools, - stream=stream, - custom_llm_provider=custom_llm_provider, - kwargs=kwargs, - ) - except Exception as e: - verbose_logger.exception( - "LiteLLM.AgenticHookError: Exception in async_should_run_chat_completion_agentic_loop: %s", - str(e), - ) - continue - - if not should_run: - continue - - # Safety guards must run OUTSIDE the callback try/except — they are - # bounded-loop / cycle-break rails that must propagate to the caller. - fingerprint = self._check_agentic_loop_safety( - tool_calls=tool_calls, - fingerprints=fingerprints, - depth=depth, - max_loops=max_loops, + agentic_response: Final = await bill_first_round_on_failure( + run_chat_completion_agentic_hooks( + response=response, model=model, - ) - - try: - kwargs_with_provider = kwargs.copy() if kwargs else {} - kwargs_with_provider["custom_llm_provider"] = custom_llm_provider - build_plan_overridden = ( - callback.__class__.async_build_chat_completion_agentic_loop_plan - is not CustomLogger.async_build_chat_completion_agentic_loop_plan - ) - if not build_plan_overridden: - return await callback.async_run_chat_completion_agentic_loop( - tools=tool_calls, - model=model, - messages=messages, - response=response, - optional_params=optional_params, - logging_obj=logging_obj, - stream=stream, - kwargs=kwargs_with_provider, - ) - - plan = await callback.async_build_chat_completion_agentic_loop_plan( - tools=tool_calls, - model=model, - messages=messages, - response=response, - optional_params=optional_params, - logging_obj=logging_obj, - stream=stream, - kwargs=kwargs_with_provider, - ) - - if plan.response_override is not None: - return plan.response_override - if plan.terminate: - verbose_logger.debug( - "Agentic chat loop terminated by callback=%s reason=%s", - callback.__class__.__name__, - plan.stop_reason, - ) - return response - if not plan.run_agentic_loop: - continue - - return await self._execute_chat_completion_agentic_plan( - plan=plan, - model=model, - messages=messages, - optional_params=optional_params, - kwargs=kwargs_with_provider, - custom_llm_provider=custom_llm_provider, - depth=depth, - max_loops=max_loops, - fingerprints=fingerprints, - fingerprint=fingerprint, - ) - except Exception as e: - verbose_logger.exception("LiteLLM.AgenticHookError: Exception in chat completion agentic hooks: %s", e) + messages=messages, + optional_params=optional_params, + kwargs=kwargs or {}, + logging_obj=logging_obj, + custom_llm_provider=custom_llm_provider, + stream=stream, + ), + logging_obj=logging_obj, + response=response, + stream=stream, + ) + if agentic_response is not None: + return agentic_response # Check if we need to convert response to fake stream for chat completions # This happens when: @@ -7065,7 +6951,7 @@ class BaseLLMHTTPHandler: timeout: float | httpx.Timeout, provider_config: BaseRealtimeHTTPConfig | None = None, model: str | None = None, - extra_headers: dict[str, object] | None = None, + extra_headers: Mapping[str, object] | None = None, client: HTTPHandler | AsyncHTTPHandler | None = None, api_version: str | None = None, ) -> httpx.Response: @@ -7098,7 +6984,7 @@ class BaseLLMHTTPHandler: timeout: float | httpx.Timeout, provider_config: BaseRealtimeHTTPConfig | None = None, model: str | None = None, - extra_headers: dict[str, object] | None = None, + extra_headers: Mapping[str, object] | None = None, client: HTTPHandler | AsyncHTTPHandler | None = None, api_version: str | None = None, ) -> httpx.Response: @@ -7117,9 +7003,8 @@ class BaseLLMHTTPHandler: api_version=api_version, ) - async def _async_realtime_session_post( + async def async_realtime_translation_client_secret_handler( self, - endpoint: Literal["client_secrets", "transcription_sessions"], api_base: str, api_key: str, request_data: dict[str, object], @@ -7127,7 +7012,35 @@ class BaseLLMHTTPHandler: timeout: float | httpx.Timeout, provider_config: BaseRealtimeHTTPConfig | None = None, model: str | None = None, - extra_headers: dict[str, object] | None = None, + extra_headers: Mapping[str, object] | None = None, + client: HTTPHandler | AsyncHTTPHandler | None = None, + api_version: str | None = None, + ) -> httpx.Response: + return await self._async_realtime_session_post( + endpoint="translation_client_secrets", + api_base=api_base, + api_key=api_key, + request_data=request_data, + logging_obj=logging_obj, + timeout=timeout, + provider_config=provider_config, + model=model, + extra_headers=extra_headers, + client=client, + api_version=api_version, + ) + + async def _async_realtime_session_post( + self, + endpoint: Literal["client_secrets", "transcription_sessions", "translation_client_secrets"], + api_base: str, + api_key: str, + request_data: dict[str, object], + logging_obj: LiteLLMLoggingObj, + timeout: float | httpx.Timeout, + provider_config: BaseRealtimeHTTPConfig | None = None, + model: str | None = None, + extra_headers: Mapping[str, object] | None = None, client: HTTPHandler | AsyncHTTPHandler | None = None, api_version: str | None = None, ) -> httpx.Response: @@ -7150,13 +7063,20 @@ class BaseLLMHTTPHandler: url = provider_config.get_transcription_session_url( api_base=api_base, model=model or "", api_version=api_version ) + elif endpoint == "translation_client_secrets": + url = provider_config.get_translation_client_secret_url( + api_base=api_base, model=model or "", api_version=api_version + ) else: url = provider_config.get_complete_url(api_base=api_base, model=model or "", api_version=api_version) headers: dict[str, object] = provider_config.validate_environment( headers={}, model=model or "", api_key=api_key ) else: - url = join_api_base(api_base, f"v1/realtime/{endpoint}") + endpoint_path: Final = ( + "translations/client_secrets" if endpoint == "translation_client_secrets" else endpoint + ) + url = join_api_base(api_base, f"v1/realtime/{endpoint_path}") headers = { "Authorization": f"Bearer {api_key}", "Content-Type": "application/json", @@ -7190,6 +7110,12 @@ class BaseLLMHTTPHandler: ) raise + @staticmethod + def _get_realtime_async_http_client(client: object | None) -> AsyncHTTPHandler: + if isinstance(client, AsyncHTTPHandler): + return client + return get_async_httpx_client(llm_provider=litellm.LlmProviders.OPENAI) + async def async_realtime_calls_handler( self, api_base: str, @@ -7199,10 +7125,11 @@ class BaseLLMHTTPHandler: timeout: float | httpx.Timeout, provider_config: BaseRealtimeHTTPConfig | None = None, model: str | None = None, - session_config: dict[str, object] | None = None, - extra_headers: dict[str, object] | None = None, + session_config: Mapping[str, object] | None = None, + extra_headers: Mapping[str, object] | None = None, client: HTTPHandler | AsyncHTTPHandler | None = None, api_version: str | None = None, + translation: bool = False, ) -> httpx.Response: """ Forward POST /v1/realtime/calls (SDP exchange) to upstream provider. @@ -7214,18 +7141,30 @@ class BaseLLMHTTPHandler: - sdp: the SDP offer (text) - session: JSON string with {"type": "realtime", "model": "...", ...} """ - if client is None or not isinstance(client, AsyncHTTPHandler): - async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders.OPENAI, - ) - else: - async_httpx_client = client + session_data: Final[dict[str, object]] = { # mutable-ok: model and session type are resolved locally + **(session_config or {}) + } + if "type" not in session_data: + session_data["type"] = "translation" if translation else "realtime" + if "model" not in session_data and model: + session_data["model"] = model + + sdp_text: Final = sdp_body.decode("utf-8") if isinstance(sdp_body, bytes) else sdp_body + + async_httpx_client: Final = self._get_realtime_async_http_client(client) if provider_config is not None: - url = provider_config.get_realtime_calls_url(api_base=api_base, model=model or "", api_version=api_version) + url = ( + provider_config.get_translation_calls_url(api_base=api_base, model=model or "", api_version=api_version) + if translation + else provider_config.get_realtime_calls_url( + api_base=api_base, model=model or "", api_version=api_version + ) + ) headers: dict[str, object] = provider_config.get_realtime_calls_headers(ephemeral_key=openai_ephemeral_key) else: - url = join_api_base(api_base, "v1/realtime/calls") + path: Final = "translations/calls" if translation else "calls" + url = join_api_base(api_base, f"v1/realtime/{path}") headers = { "Authorization": f"Bearer {openai_ephemeral_key}", } @@ -7233,14 +7172,8 @@ class BaseLLMHTTPHandler: if extra_headers: headers.update(extra_headers) - # Build multipart form data: sdp + session JSON - session_data: Final = session_config or {} - if "type" not in session_data: - session_data["type"] = "realtime" - if "model" not in session_data and model: - session_data["model"] = model - - sdp_text: Final = sdp_body.decode("utf-8") if isinstance(sdp_body, bytes) else sdp_body + if translation: + headers["Content-Type"] = "application/sdp" files: Final = { "sdp": (None, sdp_text, "text/plain"), @@ -7258,12 +7191,14 @@ class BaseLLMHTTPHandler: ) try: - return await async_httpx_client.post( - url=url, - headers=headers, - files=files, - timeout=timeout, - ) + if translation: + return await async_httpx_client.post( + url=url, + headers=headers, + content=sdp_text, + timeout=timeout, + ) + return await async_httpx_client.post(url=url, headers=headers, files=files, timeout=timeout) except Exception as e: if provider_config is not None: raise self._handle_error( @@ -8073,7 +8008,7 @@ class BaseLLMHTTPHandler: """ if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, ) else: @@ -8269,7 +8204,7 @@ class BaseLLMHTTPHandler: """ if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, ) else: @@ -8450,7 +8385,7 @@ class BaseLLMHTTPHandler: """ if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, ) else: @@ -8614,7 +8549,7 @@ class BaseLLMHTTPHandler: ): if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, ) else: @@ -8755,7 +8690,7 @@ class BaseLLMHTTPHandler: ): if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, ) else: @@ -8928,7 +8863,7 @@ class BaseLLMHTTPHandler: ): if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, ) else: @@ -9115,7 +9050,7 @@ class BaseLLMHTTPHandler: ): if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, ) else: @@ -9248,7 +9183,7 @@ class BaseLLMHTTPHandler: """ if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, ) else: @@ -9330,7 +9265,7 @@ class BaseLLMHTTPHandler: """ if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, ) else: @@ -9515,7 +9450,7 @@ class BaseLLMHTTPHandler: """ if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( - llm_provider=litellm.LlmProviders(custom_llm_provider), + llm_provider=custom_llm_provider, params={"ssl_verify": litellm_params.get("ssl_verify", None)}, ) else: @@ -12443,6 +12378,10 @@ class BaseLLMHTTPHandler: from litellm.google_genai.streaming_iterator import ( GoogleGenAIGenerateContentStreamingIterator, ) + from litellm.llms.vertex_ai.gemini.rejected_thought_signature_retry import ( + post_with_accepted_thought_signatures_sync, + with_placeholder_native_thought_signatures, + ) if _is_async: return self.async_generate_content_handler( @@ -12494,27 +12433,19 @@ class BaseLLMHTTPHandler: if extra_body: data.update(extra_body) - ## LOGGING - logging_obj.pre_call( - input=contents, - api_key="", - additional_args={ - "complete_input_dict": data, - "api_base": api_base, - "headers": headers, - }, - ) + log_request: Final = partial(_log_generate_content_request, logging_obj, contents, api_base, headers) + log_request(data) + + def post(body: Mapping[str, object]) -> httpx.Response: + return sync_httpx_client.post( + url=api_base, headers=headers, json=dict(body), timeout=timeout, stream=stream + ) try: + sent_body, response = post_with_accepted_thought_signatures_sync( + data, with_placeholder_native_thought_signatures, None, post, log_request + ) if stream: - response = sync_httpx_client.post( - url=api_base, - headers=headers, - json=data, - timeout=timeout, - stream=True, - ) - # Return streaming iterator return GoogleGenAIGenerateContentStreamingIterator( response=response, model=model, @@ -12522,7 +12453,7 @@ class BaseLLMHTTPHandler: generate_content_provider_config=generate_content_provider_config, litellm_metadata=litellm_metadata or {}, custom_llm_provider=custom_llm_provider, - request_body=data, + request_body=dict(sent_body), hidden_params=_google_genai_streaming_hidden_params( api_base=api_base, litellm_params=litellm_params, @@ -12530,13 +12461,6 @@ class BaseLLMHTTPHandler: response_headers=response.headers, ), ) - else: - response = sync_httpx_client.post( - url=api_base, - headers=headers, - json=data, - timeout=timeout, - ) except Exception as e: raise self._handle_error( e=e, @@ -12574,6 +12498,10 @@ class BaseLLMHTTPHandler: from litellm.google_genai.streaming_iterator import ( AsyncGoogleGenAIGenerateContentStreamingIterator, ) + from litellm.llms.vertex_ai.gemini.rejected_thought_signature_retry import ( + post_with_accepted_thought_signatures_async, + with_placeholder_native_thought_signatures, + ) if client is None or not isinstance(client, AsyncHTTPHandler): async_httpx_client = get_async_httpx_client( @@ -12609,27 +12537,19 @@ class BaseLLMHTTPHandler: if extra_body: data.update(extra_body) - ## LOGGING - logging_obj.pre_call( - input=contents, - api_key="", - additional_args={ - "complete_input_dict": data, - "api_base": api_base, - "headers": headers, - }, - ) + log_request: Final = partial(_log_generate_content_request, logging_obj, contents, api_base, headers) + log_request(data) + + async def post(body: Mapping[str, object]) -> httpx.Response: + return await async_httpx_client.post( + url=api_base, headers=headers, json=dict(body), timeout=timeout, stream=stream + ) try: + sent_body, response = await post_with_accepted_thought_signatures_async( + data, with_placeholder_native_thought_signatures, None, post, log_request + ) if stream: - response = await async_httpx_client.post( - url=api_base, - headers=headers, - json=data, - timeout=timeout, - stream=True, - ) - # Return async streaming iterator return AsyncGoogleGenAIGenerateContentStreamingIterator( response=response, model=model, @@ -12637,7 +12557,7 @@ class BaseLLMHTTPHandler: generate_content_provider_config=generate_content_provider_config, litellm_metadata=litellm_metadata or {}, custom_llm_provider=custom_llm_provider, - request_body=data, + request_body=dict(sent_body), hidden_params=_google_genai_streaming_hidden_params( api_base=api_base, litellm_params=litellm_params, @@ -12645,13 +12565,6 @@ class BaseLLMHTTPHandler: response_headers=response.headers, ), ) - else: - response = await async_httpx_client.post( - url=api_base, - headers=headers, - json=data, - timeout=timeout, - ) except Exception as e: raise self._handle_error( e=e, diff --git a/litellm/llms/databricks/chat/transformation.py b/litellm/llms/databricks/chat/transformation.py index 60081c38073..859211bd40d 100644 --- a/litellm/llms/databricks/chat/transformation.py +++ b/litellm/llms/databricks/chat/transformation.py @@ -4,6 +4,7 @@ Translates from OpenAI's `/v1/chat/completions` to Databricks' `/chat/completion import os from collections.abc import AsyncIterator, Coroutine, Iterator, Mapping, Sequence +from itertools import chain, takewhile from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, cast, overload @@ -12,6 +13,7 @@ from pydantic import BaseModel, ConfigDict, TypeAdapter from litellm.anthropic_beta_gated_fields import log_beta_gated_strips, strip_beta_gated_thinking from litellm.constants import RESPONSE_FORMAT_TOOL_NAME +from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response import ( handle_invalid_parallel_tool_calls, should_convert_tool_call_to_json_mode, @@ -23,11 +25,13 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import ( strip_name_from_message, strip_prefill_prefix_field, ) +from litellm.litellm_core_utils.tool_fields import tool_params_without_hosted_mcp from litellm.litellm_core_utils.url_utils import join_api_base from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator from litellm.llms.base_llm.base_utils import ( type_to_response_format_param, # pyright: ignore[reportUnknownVariableType] # base_utils helper returns an untyped dict ) +from litellm.llms.base_llm.chat.transformation import REQUEST_PARAMS from litellm.types.llms.anthropic import AllAnthropicToolsValues from litellm.types.llms.databricks import ( AllDatabricksContentValues, @@ -65,7 +69,7 @@ from ...anthropic.chat.transformation import ( tools_without_unsupported_tool_search, ) from ...openai_like.chat.transformation import OpenAILikeChatConfig -from ..common_utils import DatabricksBase, DatabricksException +from ..common_utils import DATABRICKS_HOSTED_MODEL_PREFIXES, DatabricksBase, DatabricksException _RESPONSE_FORMAT_ADAPTER: ( # mutable-ok: mirrors the dict return contract of get_json_schema_from_pydantic_object Final[TypeAdapter[dict[str, object] | None]] @@ -81,15 +85,139 @@ def _is_bare_assistant_message(message_dict: Mapping[str, object]) -> bool: ) +_CONTENT_BLOCKS: Final = TypeAdapter(tuple[object, ...]) + + +def _content_blocks(message: object) -> tuple[object, ...]: + match message.model_dump(exclude_none=True) if isinstance(message, BaseModel) else message: + case {"content": list() as content}: + return _CONTENT_BLOCKS.validate_python(content) + case _: + return () + + +def _plain_text(block: object) -> str | None: + match block: + case {"type": "text", "text": str() as text} if block == {"type": "text", "text": text}: + return text + case _: + return None + + +def _plain_texts(message: Mapping[str, object]) -> tuple[str, ...]: + blocks: Final = _content_blocks(message) + texts: Final = tuple(text for block in blocks if (text := _plain_text(block)) is not None) + return texts if len(texts) == len(blocks) else () + + def _collapse_single_text_block(message: Mapping[str, object]) -> Mapping[str, object]: - content: Final = message.get("content") - match content: - case [{"type": "text", "text": str() as text}] if content == [{"type": "text", "text": text}]: + match _plain_texts(message): + case (text,): return {**message, "content": text} case _: return message +def _without_text_cache_control(block: object) -> object: + match block: + case {"type": "text", "text": str() as text, "cache_control": object() as cache_control} if block == { + "type": "text", + "text": text, + "cache_control": cache_control, + }: + return {"type": "text", "text": text} + case _: + return block + + +def _without_cache_control(message: AllMessageValues) -> AllMessageValues: + uncached: Final = {key: value for key, value in message.items() if key != "cache_control"} + match content := uncached.get("content"): + case list(): + blocks: Final = [_without_text_cache_control(block) for block in _CONTENT_BLOCKS.validate_python(content)] + return cast(AllMessageValues, {**uncached, "content": blocks}) # cast-ok: spread keeps the shape + case _: + return cast(AllMessageValues, uncached) # cast-ok: only cache_control was left out + + +def _has_string_content(message: Mapping[str, object]) -> bool: + return isinstance(message.get("content"), str) + + +def _is_system(message: Mapping[str, object]) -> bool: + return message.get("role") == "system" + + +def _json_mode_message(message: AllMessageValues, drop_params: bool) -> AllMessageValues: + candidate: Final = _without_cache_control(message) if drop_params else message + texts: Final = _plain_texts(candidate) + if "cache_control" in candidate or not (texts or _has_string_content(candidate)): + return message + if sum(1 for text in texts if text.strip()) < 2: + return candidate + return cast(AllMessageValues, {**candidate, "content": "".join(texts)}) # cast-ok: spread keeps the shape + + +def _is_dropped_on_send(message: Mapping[str, object]) -> bool: + sanitized: Final = {**message} + _sanitize_empty_content(sanitized) + return _is_bare_assistant_message(sanitized) + + +def _is_system_or_dropped(message: Mapping[str, object]) -> bool: + return _is_system(message) or _is_dropped_on_send(message) + + +def _json_checked_start(messages: Sequence[AllMessageValues]) -> int: + trailing: Final = tuple(takewhile(_is_system_or_dropped, reversed(messages))) + last_sent_offset: Final = 0 if any(_is_system(message) for message in trailing) else 1 + return max(len(messages) - len(trailing) - last_sent_offset, 0) + + +def _json_object_ready_messages( + model: str, + messages: list[AllMessageValues], # mutable-ok: inherited transform_request contract + response_format: object, + drop_params: bool, +) -> list[AllMessageValues]: # mutable-ok: inherited transform_request contract + match response_format: + case {"type": "json_object"} if "claude" not in model and model.startswith(DATABRICKS_HOSTED_MODEL_PREFIXES): + checked_start: Final = _json_checked_start(messages) + return [ + *messages[:checked_start], + *(_json_mode_message(message, drop_params) for message in messages[checked_start:]), + ] + case _: + return messages + + +def _is_empty_text_block(block: object) -> bool: + match block: + case {"type": "text", "text": str() as text}: + return not text.strip() + case {"type": "text", "text": object() as text}: + return not text + case {"type": "text"}: + return True + case _: + return False + + +def _non_string_text_type(block: object) -> str | None: + match block: + case {"type": "text", "text": str()}: + return None + case {"type": "text", "text": object() as text} if text: + return type(text).__name__ + case _: + return None + + +def _first_non_string_text_type(messages: Sequence[AllMessageValues]) -> str | None: + blocks: Final = chain.from_iterable(map(_content_blocks, messages)) + return next((type_name for block in blocks if (type_name := _non_string_text_type(block))), None) + + def _sanitize_empty_content(message_dict: dict[str, object]) -> None: """ Remove or filter content so empty text blocks are not sent. @@ -108,9 +236,7 @@ def _sanitize_empty_content(message_dict: dict[str, object]) -> None: message_dict.pop("content") return filtered: Final = [ - block - for block in content - if not (isinstance(block, dict) and block.get("type") == "text" and not (block.get("text") or "").strip()) + block for block in _CONTENT_BLOCKS.validate_python(content) if not _is_empty_text_block(block) ] if not filtered: message_dict.pop("content") @@ -270,7 +396,7 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig): return "databricks" @classmethod - def get_config(cls, *, model: str | None = None): + def get_config(cls, *, model: str | None = None, configured_max_output_tokens: int | None = None): return super().get_config() def get_json_schema_from_pydantic_object( @@ -343,7 +469,7 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig): use_ai_gateway: Final = self.uses_ai_gateway(model) return join_api_base(self._get_api_base(api_base, use_ai_gateway=use_ai_gateway), "chat/completions") - def get_supported_openai_params(self, model: str | None = None) -> list: + def get_supported_openai_params(self, model: str | None = None) -> list[str]: return [ "stream", "stop", @@ -416,12 +542,12 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig): model: str, value: dict | None, optional_params: dict, - is_thinking_enabled: bool, + tool_is_forced: bool, ) -> DatabricksTool | None: if value is None: return None - tool: Final = self.map_response_format_to_anthropic_tool(value, optional_params, is_thinking_enabled) + tool: Final = self.map_response_format_to_anthropic_tool(value, optional_params, tool_is_forced) databricks_tool: Final = self.convert_anthropic_tool_to_databricks_tool(tool) return databricks_tool @@ -449,8 +575,12 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig): drop_params: bool, replace_max_completion_tokens_with_max_tokens: bool = True, ) -> dict: - is_thinking_enabled: Final = self.is_thinking_enabled(non_default_params) - mapped_params: Final = super().map_openai_params(non_default_params, optional_params, model, drop_params) + request_params: Final = ( + tool_params_without_hosted_mcp(non_default_params, model=model, route="databricks", drop_params=drop_params) + if "claude" in model + else non_default_params + ) + mapped_params: Final = super().map_openai_params(request_params, optional_params, model, drop_params) if "claude" in model: AnthropicConfig.translate_legacy_thinking_for_adaptive_model( model=model, optional_params=mapped_params, custom_llm_provider="databricks", drop_params=drop_params @@ -459,24 +589,27 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig): mapped_params["tools"] = self._map_openai_to_dbrx_tool( model=model, tools=mapped_params["tools"], drop_params=drop_params ) - if "max_completion_tokens" in non_default_params and replace_max_completion_tokens_with_max_tokens: - mapped_params["max_tokens"] = non_default_params[ + if "max_completion_tokens" in request_params and replace_max_completion_tokens_with_max_tokens: + mapped_params["max_tokens"] = request_params[ "max_completion_tokens" ] # most openai-compatible providers support 'max_tokens' not 'max_completion_tokens' mapped_params.pop("max_completion_tokens", None) - if "response_format" in non_default_params and "claude" in model: + if "response_format" in request_params and "claude" in model: + tool_is_forced: Final = AnthropicConfig.response_format_tool_can_be_forced( + model, "databricks", REQUEST_PARAMS.validate_python(request_params) + ) _tool: Final = self.map_response_format_to_databricks_tool( model, - non_default_params["response_format"], + request_params["response_format"], mapped_params, - is_thinking_enabled, + tool_is_forced, ) if _tool is not None: self._add_tools_to_optional_params(optional_params=optional_params, tools=[_tool]) optional_params["json_mode"] = True - if not is_thinking_enabled: + if tool_is_forced: _tool_choice: Final = ChatCompletionToolChoiceObjectParam( type="function", function=ChatCompletionToolChoiceFunctionParam(name=RESPONSE_FORMAT_TOOL_NAME), @@ -486,8 +619,8 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig): "response_format", None ) # unsupported for claude models - if json_schema -> convert to tool call - if "reasoning_effort" in non_default_params and self._uses_anthropic_thinking_param(model): - reasoning_effort_value: Final = non_default_params.get("reasoning_effort") + if "reasoning_effort" in request_params and self._uses_anthropic_thinking_param(model): + reasoning_effort_value: Final = request_params.get("reasoning_effort") mapped_thinking: Final = AnthropicConfig._map_reasoning_effort( reasoning_effort=reasoning_effort_value, model=model, @@ -513,7 +646,7 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig): optional_params.pop("reasoning_effort", None) ## handle thinking tokens self.update_optional_params_with_thinking_tokens( - non_default_params=non_default_params, optional_params=mapped_params + non_default_params=request_params, optional_params=mapped_params ) gated_thinking: Final = strip_beta_gated_thinking( mapped_params.get("thinking"), # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # mapped_params is the base config's bare dict @@ -535,6 +668,35 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig): return False + def transform_request( + self, + model: str, + messages: list[AllMessageValues], # mutable-ok: inherited contract + optional_params: dict[str, object], # mutable-ok: inherited contract + litellm_params: dict[str, object], # mutable-ok: inherited contract + headers: dict[str, object], # mutable-ok: inherited contract + ) -> dict[str, object]: # mutable-ok: inherited contract + match _first_non_string_text_type(messages): + case str() as type_name: + raise DatabricksException( + status_code=400, + message=f"A text content block needs a string 'text', got {type_name}", + ) + case None: + pass + return super().transform_request( + model=model, + messages=_json_object_ready_messages( + model, + messages, + optional_params.get("response_format"), + drop_params=drops_unsupported_params(litellm_params.get("drop_params")), + ), + optional_params=optional_params, + litellm_params=litellm_params, + headers=headers, + ) + @overload def _transform_messages( self, messages: list[AllMessageValues], model: str, is_async: Literal[True] diff --git a/litellm/llms/databricks/common_utils.py b/litellm/llms/databricks/common_utils.py index b1562bef6b8..e8313d9a003 100644 --- a/litellm/llms/databricks/common_utils.py +++ b/litellm/llms/databricks/common_utils.py @@ -56,6 +56,7 @@ DATABRICKS_WORKSPACE_ROUTE_PREFIXES: Final = ( DATABRICKS_AI_GATEWAY_MESSAGES_PATH, ) DATABRICKS_NATIVE_MESSAGES_MODEL_PREFIXES: Final = ("databricks-claude-", "system.ai.claude-") +DATABRICKS_HOSTED_MODEL_PREFIXES: Final = ("databricks-", "system.ai.") DATABRICKS_ENDPOINT_PATHS: Final = MappingProxyType( { "chat_completions": "/chat/completions", diff --git a/litellm/llms/databricks/messages/transformation.py b/litellm/llms/databricks/messages/transformation.py index 90b63d860d3..85f44181bc3 100644 --- a/litellm/llms/databricks/messages/transformation.py +++ b/litellm/llms/databricks/messages/transformation.py @@ -192,7 +192,7 @@ class DatabricksAnthropicMessagesConfig(DatabricksBase, AnthropicMessagesConfig) headers=headers, ) self._normalize_system_role_messages( # pyright: ignore[reportUnknownMemberType] # the shared helper takes a bare dict - anthropic_messages_request, model=model, drop_params=getattr(litellm_params, "drop_params", None) + anthropic_messages_request, model=model, drop_params=litellm_params.drop_params ) self._remove_scope_from_cache_control(anthropic_messages_request) # pyright: ignore[reportUnknownMemberType] # the shared helper takes a bare dict return anthropic_messages_request diff --git a/litellm/llms/deepseek/chat/transformation.py b/litellm/llms/deepseek/chat/transformation.py index 5b7c2a2c410..9c222f03c8c 100644 --- a/litellm/llms/deepseek/chat/transformation.py +++ b/litellm/llms/deepseek/chat/transformation.py @@ -12,6 +12,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import ( extract_search_results_text, ) from litellm.litellm_core_utils.reasoning_effort_utils import OPAQUE_VALUE, warn_dropped_reasoning +from litellm.litellm_core_utils.tool_fields import tool_params_without_hosted_mcp from litellm.litellm_core_utils.url_utils import ensure_api_route from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import AllMessageValues @@ -33,17 +34,15 @@ def _warn_on_dropped_budget(thinking: object, model: str) -> None: class DeepSeekChatConfig(OpenAIGPTConfig): - def get_supported_openai_params(self, model: str) -> list: + def get_supported_openai_params(self, model: str) -> list[str]: """ DeepSeek reasoner models support thinking parameter. """ - params: Final = super().get_supported_openai_params(model) - params.extend(["thinking", "reasoning_effort"]) - return params + return [*super().get_supported_openai_params(model), "thinking", "reasoning_effort"] def map_openai_params( self, - non_default_params: dict, + non_default_params: dict[str, object], optional_params: dict, model: str, drop_params: bool, @@ -59,7 +58,12 @@ class DeepSeekChatConfig(OpenAIGPTConfig): Reference: https://api-docs.deepseek.com/guides/thinking_mode """ # Let parent handle standard params first - optional_params = super().map_openai_params(non_default_params, optional_params, model, drop_params) + optional_params = super().map_openai_params( + tool_params_without_hosted_mcp(non_default_params, model=model, route="deepseek", drop_params=drop_params), + optional_params, + model, + drop_params, + ) # Pop thinking/reasoning_effort from optional_params first (parent may have added them) # Then re-add only if valid for DeepSeek @@ -265,6 +269,7 @@ class DeepSeekChatConfig(OpenAIGPTConfig): tools: Final = optional_params.get("tools") if not isinstance(tools, list) or not tools: return optional_params + sent_tools: Final[tuple[object, ...]] = tuple(tools) def _is_function_tool(tool: object) -> bool: return isinstance(tool, dict) and tool.get("type") == "function" @@ -289,14 +294,14 @@ class DeepSeekChatConfig(OpenAIGPTConfig): name: Final = function.get("name") return isinstance(name, str) and name in function_tool_names - function_tools: Final = [tool for tool in tools if _is_function_tool(tool)] - if len(function_tools) == len(tools): + function_tools: Final = [tool for tool in sent_tools if _is_function_tool(tool)] + if len(function_tools) == len(sent_tools): return optional_params dropped_types: Final = sorted( { str(tool.get("type")) if isinstance(tool, dict) else type(tool).__name__ - for tool in tools + for tool in sent_tools if not _is_function_tool(tool) } ) diff --git a/litellm/llms/empiriolabs/decisions/transformation.py b/litellm/llms/empiriolabs/decisions/transformation.py new file mode 100644 index 00000000000..ce3464310c4 --- /dev/null +++ b/litellm/llms/empiriolabs/decisions/transformation.py @@ -0,0 +1,10 @@ +from litellm.llms.base_llm.decisions.transformation import BaseDecisionsConfig + + +class EmpirioLabsDecisionsConfig(BaseDecisionsConfig): + path = "/v1/decisions" + api_key_env = ("EMPIRIOLABS_API_KEY",) + api_base_env = ("EMPIRIOLABS_API_BASE",) + + def get_default_api_base(self) -> str | None: + return "https://api.empiriolabs.ai" diff --git a/litellm/llms/fireworks_ai/responses/transformation.py b/litellm/llms/fireworks_ai/responses/transformation.py index 463b9cbfc9a..d599f0b65f7 100644 --- a/litellm/llms/fireworks_ai/responses/transformation.py +++ b/litellm/llms/fireworks_ai/responses/transformation.py @@ -29,6 +29,7 @@ from litellm.utils import ( declared_mid_conversation_system_support, deployment_declared_mid_conversation_system_support, deployment_model_info, + get_bundled_model_cost_map, ) if TYPE_CHECKING: @@ -54,6 +55,15 @@ def _forwarded_user_params(litellm_params: GenericLiteLLMParams) -> Mapping[str, ) +def _bundled_cost_map_declares_mid_conversation_system(model: str) -> bool: + bundled_cost_map: Final[Mapping[str, object]] = get_bundled_model_cost_map() + names: Final = (model.removeprefix("fireworks_ai/"), resolve_fireworks_resource_name(model)) + return any( + deployment_declared_mid_conversation_system_support(bundled_cost_map.get(f"fireworks_ai/{name}")) is True + for name in names + ) + + class FireworksAIResponsesAPIConfig(OpenAIResponsesAPIConfig): @property def custom_llm_provider(self) -> LlmProviders: @@ -90,9 +100,13 @@ class FireworksAIResponsesAPIConfig(OpenAIResponsesAPIConfig): validated_input: Final = self._validate_input_param(input) model_info: Final = deployment_model_info(litellm_params) declared: Final = declared_mid_conversation_system_support(model, self.custom_llm_provider.value, model_info) + keeps_developer_items_in_place: Final = declared is True and ( + deployment_declared_mid_conversation_system_support(model_info) is True + or _bundled_cost_map_declares_mid_conversation_system(model) + ) folded: Final = ( None - if deployment_declared_mid_conversation_system_support(model_info) is True + if keeps_developer_items_in_place else instruction_items_folded( validated_input, response_api_optional_request_params, "user" if declared is False else "system" ) diff --git a/litellm/llms/gemini/chat/transformation.py b/litellm/llms/gemini/chat/transformation.py index 936919af83d..1539f13455f 100644 --- a/litellm/llms/gemini/chat/transformation.py +++ b/litellm/llms/gemini/chat/transformation.py @@ -1,5 +1,5 @@ from collections.abc import Mapping -from typing import Final, cast +from typing import ClassVar, Final, cast import litellm from litellm.litellm_core_utils.prompt_templates.factory import ( @@ -49,6 +49,8 @@ class GoogleAIStudioGeminiConfig(VertexGeminiConfig): Note: Please make sure to modify the default parameters as required for your use case. """ + _route: ClassVar[str] = "gemini" + temperature: float | None = None max_output_tokens: int | None = None top_p: float | None = None diff --git a/litellm/llms/gemini/common_utils.py b/litellm/llms/gemini/common_utils.py index 88c6494e3f7..74cd6f22704 100644 --- a/litellm/llms/gemini/common_utils.py +++ b/litellm/llms/gemini/common_utils.py @@ -537,13 +537,16 @@ class GoogleAIStudioTokenCounter(BaseTokenCounter): ) -> TokenCountResponse | None: import copy + from litellm.llms.anthropic.messages.context_management.inference_view import ( + InferenceRequestViewError, + count_context_edits, + inference_request_view, + ) from litellm.llms.gemini.count_tokens.handler import GoogleAIStudioTokenCounter from litellm.llms.vertex_ai.count_tokens.context import ( VertexGeminiCountContextError, - count_context_edits, count_context_error_response, gemini_count_contents, - inference_request_view, malformed_tool_result_text_count_error, provider_error_response, unconvertible_messages_error, @@ -556,7 +559,7 @@ class GoogleAIStudioTokenCounter(BaseTokenCounter): messages_format, count_context_edits(context_management, tools, (deployment or {}).get("litellm_params", {}), model_to_use), ) - if isinstance(request_view, VertexGeminiCountContextError): + if isinstance(request_view, InferenceRequestViewError): return count_context_error_response(request_view, request_model, model_to_use) count_context: Final = vertex_gemini_count_context(system=request_view.system, tools=tools, model=model_to_use) if isinstance(count_context, VertexGeminiCountContextError): diff --git a/litellm/llms/gemini/realtime/transformation.py b/litellm/llms/gemini/realtime/transformation.py index 3134dfa1e4b..a9f31d1abff 100644 --- a/litellm/llms/gemini/realtime/transformation.py +++ b/litellm/llms/gemini/realtime/transformation.py @@ -218,7 +218,7 @@ def _system_instruction_text(system_instruction: HttpxContentType | None) -> str class GeminiRealtimeConfig(BaseRealtimeConfig): _TOOL_CALL_ID_TO_NAME_MAX = 256 # LRU cap for call_id→name mapping - def __init__(self, drop_params: bool = False): + def __init__(self, drop_params: bool = False) -> None: super().__init__() self.drop_params = drop_params self._tool_call_id_to_name: OrderedDict[str, str] = OrderedDict() diff --git a/litellm/llms/gigachat/chat/transformation.py b/litellm/llms/gigachat/chat/transformation.py index 81a186eadf4..7bc783b960f 100644 --- a/litellm/llms/gigachat/chat/transformation.py +++ b/litellm/llms/gigachat/chat/transformation.py @@ -17,6 +17,7 @@ import httpx from pydantic import TypeAdapter from litellm._logging import verbose_logger +from litellm.litellm_core_utils.tool_fields import tool_params_without_hosted_mcp from litellm.litellm_core_utils.url_utils import join_api_base from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException from litellm.llms.gigachat.utils import convert_usage, get_api_base @@ -169,7 +170,10 @@ class GigaChatConfig(BaseConfig): drop_params: bool, ) -> dict: # mutable-ok: base class contract returns dict """Map OpenAI parameters to GigaChat parameters.""" - for param, value in non_default_params.items(): + request_params: Final = tool_params_without_hosted_mcp( + dict(non_default_params), model=model, route="gigachat", drop_params=drop_params + ) + for param, value in request_params.items(): if param == "stream": optional_params["stream"] = value elif param == "temperature": diff --git a/litellm/llms/github_copilot/github_host.py b/litellm/llms/github_copilot/github_host.py index 4fc921d490d..cfe122ebac4 100644 --- a/litellm/llms/github_copilot/github_host.py +++ b/litellm/llms/github_copilot/github_host.py @@ -21,8 +21,10 @@ class GithubHostEndpoints: device_code_url: str access_token_url: str api_key_url: str + copilot_user_url: str user_url: str client_id: str + exchanges_copilot_token: bool copilot_api_hosts: frozenset[str] copilot_api_host_suffix: str | None default_copilot_api_base: str @@ -49,14 +51,17 @@ def github_host_endpoints(host: str) -> GithubHostEndpoints: if normalized is None: raise ValueError("host must be github.com or a single-subdomain GHE.com hostname") client_id: Final = os.getenv("GITHUB_COPILOT_CLIENT_ID", DEFAULT_GITHUB_CLIENT_ID) + exchanges_copilot_token: Final = client_id == DEFAULT_GITHUB_CLIENT_ID if normalized == GITHUB_COPILOT_DEFAULT_HOST: return GithubHostEndpoints( host=normalized, device_code_url=os.getenv("GITHUB_COPILOT_DEVICE_CODE_URL", DEFAULT_GITHUB_DEVICE_CODE_URL), access_token_url=os.getenv("GITHUB_COPILOT_ACCESS_TOKEN_URL", DEFAULT_GITHUB_ACCESS_TOKEN_URL), api_key_url=os.getenv("GITHUB_COPILOT_API_KEY_URL", DEFAULT_GITHUB_API_KEY_URL), + copilot_user_url="https://api.github.com/copilot_internal/user", user_url="https://api.github.com/user", client_id=client_id, + exchanges_copilot_token=exchanges_copilot_token, copilot_api_hosts=frozenset({"githubcopilot.com"}), copilot_api_host_suffix=".githubcopilot.com", default_copilot_api_base="https://api.githubcopilot.com", @@ -70,8 +75,10 @@ def github_host_endpoints(host: str) -> GithubHostEndpoints: device_code_url=f"https://{normalized}/login/device/code", access_token_url=f"https://{normalized}/login/oauth/access_token", api_key_url=f"https://{api_host}/copilot_internal/v2/token", + copilot_user_url=f"https://{api_host}/copilot_internal/user", user_url=f"https://{api_host}/user", client_id=client_id, + exchanges_copilot_token=exchanges_copilot_token, copilot_api_hosts=frozenset({copilot_api_host}), copilot_api_host_suffix=None, default_copilot_api_base=f"https://{copilot_api_host}", diff --git a/litellm/llms/github_copilot/per_user_auth.py b/litellm/llms/github_copilot/per_user_auth.py index 75a10f2e671..e210414ce8f 100644 --- a/litellm/llms/github_copilot/per_user_auth.py +++ b/litellm/llms/github_copilot/per_user_auth.py @@ -46,6 +46,7 @@ _LLM_PROVIDER: Final = "github_copilot" _DEVICE_FLOW_SCOPE: Final = "read:user" _SESSION_CACHE_MAX_SIZE: Final = 1000 _SYNC_LOCK_COUNT: Final = 64 +_ACCOUNT_LOOKUP_TTL_SECONDS: Final = 1800 class _SessionCache(Protocol): @@ -125,12 +126,20 @@ class _CopilotEndpointsPayload(TypedDict): api: ReadOnly[NotRequired[object]] +@with_config(ConfigDict(extra="allow", strict=True)) +class _CopilotAccountPayload(TypedDict): + access_type_sku: ReadOnly[NotRequired[object]] + chat_enabled: ReadOnly[NotRequired[object]] + endpoints: ReadOnly[NotRequired[object]] + + @with_config(ConfigDict(extra="allow", strict=True)) class _GithubUserPayload(TypedDict): login: ReadOnly[str] _COPILOT_TOKEN: Final = TypeAdapter(_CopilotTokenPayload) +_COPILOT_ACCOUNT: Final = TypeAdapter(_CopilotAccountPayload) _DEVICE_CODE: Final = TypeAdapter(_DeviceCodePayload) _ACCESS_TOKEN_POLL: Final = TypeAdapter(_AccessTokenPollPayload) _GITHUB_USER: Final = TypeAdapter(_GithubUserPayload) @@ -273,6 +282,8 @@ def _session_from_response( llm_provider=_LLM_PROVIDER, model="", ) + if not endpoints.exchanges_copilot_token: + return _session_from_account(response, github_token, credential_name, cache_key, endpoints) try: payload: Final = _COPILOT_TOKEN.validate_python(response.json()) except Exception as e: @@ -282,13 +293,7 @@ def _session_from_response( model="", ) from e - payload_endpoints: Final[object] = payload.get("endpoints") - endpoints_api: Final[object] = ( - _COPILOT_ENDPOINTS.validate_python(payload_endpoints).get("api") - if isinstance(payload_endpoints, Mapping) - else None - ) - api_base: Final = validated_copilot_api_base(endpoints_api, endpoints) + api_base: Final = validated_copilot_api_base(_endpoints_api(payload.get("endpoints")), endpoints) session: Final = GithubCopilotUserSession(token=payload["token"], api_base=api_base) expires_at: Final = _expires_at_seconds(payload.get("expires_at")) if expires_at > 0: @@ -296,6 +301,41 @@ def _session_from_response( return session +def _session_from_account( + response: httpx.Response, + github_token: str, + credential_name: str, + cache_key: str, + endpoints: GithubHostEndpoints, +) -> GithubCopilotUserSession: + try: + payload: Final = _COPILOT_ACCOUNT.validate_python(response.json()) + except Exception as e: + raise ServiceUnavailableError( + message="GitHub Copilot account lookup returned an invalid response", + llm_provider=_LLM_PROVIDER, + model="", + ) from e + if payload.get("chat_enabled") is False or payload.get("access_type_sku") == "no_access": + _SESSION_CACHE.delete_cache(cache_key) + raise _reject_connection(credential_name) + + api_base: Final = validated_copilot_api_base(_endpoints_api(payload.get("endpoints")), endpoints) + session: Final = GithubCopilotUserSession(token=github_token, api_base=api_base) + _cache_session(cache_key, github_token, session, time.time() + _ACCOUNT_LOOKUP_TTL_SECONDS) + return session + + +def _endpoints_api(payload_endpoints: object) -> object: + if not isinstance(payload_endpoints, Mapping): + return None + return _COPILOT_ENDPOINTS.validate_python(payload_endpoints).get("api") + + +def _session_lookup_url(endpoints: GithubHostEndpoints) -> str: + return endpoints.api_key_url if endpoints.exchanges_copilot_token else endpoints.copilot_user_url + + def _to_int(raw: object) -> int: if isinstance(raw, bool): return 0 @@ -337,7 +377,7 @@ def _do_exchange( _SyncGetClient, litellm.module_level_client ) response: Final = client.get( - endpoints.api_key_url, + _session_lookup_url(endpoints), headers=github_api_headers(github_token), ) except Exception as e: @@ -367,7 +407,7 @@ async def _do_aexchange( client: Final = _new_async_github_client() try: response: Final = await client.get( - endpoints.api_key_url, + _session_lookup_url(endpoints), headers=github_api_headers(github_token), ) except Exception as e: diff --git a/litellm/llms/huggingface/embedding/handler.py b/litellm/llms/huggingface/embedding/handler.py index a1d1a3f6a19..5d997babc6e 100644 --- a/litellm/llms/huggingface/embedding/handler.py +++ b/litellm/llms/huggingface/embedding/handler.py @@ -38,7 +38,9 @@ class _SupportsTokenEncode(Protocol): def encode(self, text: str) -> list[int]: ... -def get_hf_task_embedding_for_model(model: str, task_type: str | None, api_base: str) -> object: +def get_hf_task_embedding_for_model( + model: str, task_type: str | None, api_base: str, timeout: float | httpx.Timeout | None = None +) -> object: if task_type is not None: if task_type in get_args(hf_tasks_embeddings): return task_type @@ -46,7 +48,7 @@ def get_hf_task_embedding_for_model(model: str, task_type: str | None, api_base: raise Exception(f"Invalid task_type={task_type}. Expected one of={hf_tasks_embeddings}") http_client: Final = HTTPHandler(concurrent_limit=1) - model_info: Final = http_client.get(url=f"{api_base}/api/models/{model}") + model_info: Final = http_client.get(url=f"{api_base}/api/models/{model}", timeout=timeout) model_info_dict: Final = decoded_json_object(_DECODED_JSON.validate_python(model_info.json())) @@ -148,6 +150,7 @@ class HuggingFaceEmbedding(BaseLLM): call_type: Literal["sync", "async"], optional_params: dict, embed_url: str, + timeout: float | httpx.Timeout | None = None, ) -> dict: data: dict = {} @@ -165,7 +168,9 @@ class HuggingFaceEmbedding(BaseLLM): task_type: Final = optional_params.pop("input_type", None) if call_type == "sync": - hf_task: Final = get_hf_task_embedding_for_model(model=model, task_type=task_type, api_base=HF_HUB_URL) + hf_task: Final = get_hf_task_embedding_for_model( + model=model, task_type=task_type, api_base=HF_HUB_URL, timeout=timeout + ) elif call_type == "async": return self._async_transform_input(model=model, task_type=task_type, embed_url=embed_url, input=input) @@ -253,6 +258,7 @@ class HuggingFaceEmbedding(BaseLLM): call_type="sync", optional_params=optional_params, embed_url=api_base, + timeout=timeout, ) ## LOGGING @@ -269,9 +275,10 @@ class HuggingFaceEmbedding(BaseLLM): if client is None: client = get_async_httpx_client( llm_provider=litellm.LlmProviders.HUGGINGFACE, + params={"timeout": timeout}, ) - response: Final = await client.post(api_base, headers=headers, data=json.dumps(data)) + response: Final = await client.post(api_base, headers=headers, data=json.dumps(data), timeout=timeout) ## LOGGING logging_obj.post_call( @@ -321,7 +328,9 @@ class HuggingFaceEmbedding(BaseLLM): litellm_params=litellm_params, ) task_type: Final = optional_params.get("input_type", None) - task: Final = get_hf_task_embedding_for_model(model=model, task_type=task_type, api_base=HF_HUB_URL) + task: Final = get_hf_task_embedding_for_model( + model=model, task_type=task_type, api_base=HF_HUB_URL, timeout=timeout + ) # print_verbose(f"{model}, {task}") embed_url = "" if model.startswith(("http://", "https://")): @@ -359,6 +368,7 @@ class HuggingFaceEmbedding(BaseLLM): call_type="sync", optional_params=optional_params, embed_url=embed_url, + timeout=timeout, ) ## LOGGING @@ -374,7 +384,7 @@ class HuggingFaceEmbedding(BaseLLM): ## COMPLETION CALL if client is None or not isinstance(client, HTTPHandler): client = HTTPHandler(concurrent_limit=1) - response: Final = client.post(embed_url, headers=headers, data=json.dumps(data)) + response: Final = client.post(embed_url, headers=headers, data=json.dumps(data), timeout=timeout) ## LOGGING logging_obj.post_call( diff --git a/litellm/llms/mistral/chat/transformation.py b/litellm/llms/mistral/chat/transformation.py index 1ecef46ffb1..61d237de2d8 100644 --- a/litellm/llms/mistral/chat/transformation.py +++ b/litellm/llms/mistral/chat/transformation.py @@ -6,6 +6,7 @@ Why separate file? Make it easy to see how transformation works Docs - https://docs.mistral.ai/api/ """ +import reprlib from collections.abc import AsyncIterator, Coroutine, Iterator, Mapping, Sequence from itertools import accumulate, count from typing import TYPE_CHECKING, Final, Literal, cast, get_type_hints, overload @@ -45,7 +46,13 @@ from litellm.types.llms.mistral import ( MistralThinkingBlock, MistralToolCallMessage, ) -from litellm.types.llms.openai import AllMessageValues, ChatCompletionAssistantMessage, ChatCompletionTextObject +from litellm.types.llms.openai import ( + AllMessageValues, + ChatCompletionAssistantMessage, + ChatCompletionTextObject, + ChatCompletionToolChoiceFunctionParam, + ChatCompletionToolChoiceObjectParam, +) from litellm.types.utils import ModelResponse, ModelResponseStream from litellm.utils import convert_to_model_response_object, supports_reasoning @@ -79,6 +86,10 @@ _REASONING_PROMPT_REASON: Final = "litellm sends Magistral a reasoning system pr _NON_LEVEL_EFFORT_REASON: Final = ( "the Mistral API takes it only as a level such as 'high', so Mistral applies its default effort." ) +_UNUSABLE_TOOL_CHOICE_REASON: Final = ( + "the Mistral API takes tool_choice only as 'auto', 'none', 'any', 'required', " + "or {'type': 'function', 'function': {'name': }}." +) _DOCUMENTED_MAGISTRAL_EFFORTS: Final = frozenset({"low", "medium", "high"}) _REASONING_ON_THINKING_TYPES: Final = frozenset({"enabled", "adaptive"}) @@ -118,7 +129,7 @@ class MistralConfig(OpenAIGPTConfig): - `tools` (list or null): A list of available tools for the model. Use this to specify functions for which the model can generate JSON inputs. - - `tool_choice` (string - 'auto'/'any'/'none' or null): Specifies if/how functions are called. If set to none the model won't call a function and will generate a message instead. If set to auto the model can choose to either generate a message or call a function. If set to any the model is forced to call a function. Default - 'auto'. + - `tool_choice` (string - 'auto'/'any'/'none', an object naming one function such as {"type": "function", "function": {"name": "my_function"}}, or null): Specifies if/how functions are called. If set to none the model won't call a function and will generate a message instead. If set to auto the model can choose to either generate a message or call a function. If set to any the model is forced to call a function. Default - 'auto'. - `stop` (string or array of strings): Stop generation if this token is detected. Or if one of these tokens is detected when providing an array @@ -135,7 +146,7 @@ class MistralConfig(OpenAIGPTConfig): top_p: int | None = None max_tokens: int | None = None tools: list | None = None - tool_choice: Literal["auto", "any", "none"] | None = None + tool_choice: Literal["auto", "any", "none"] | ChatCompletionToolChoiceObjectParam | None = None random_seed: int | None = None safe_prompt: bool | None = None response_format: dict | None = None @@ -147,7 +158,7 @@ class MistralConfig(OpenAIGPTConfig): top_p: int | None = None, max_tokens: int | None = None, tools: list | None = None, - tool_choice: Literal["auto", "any", "none"] | None = None, + tool_choice: Literal["auto", "any", "none"] | ChatCompletionToolChoiceObjectParam | None = None, random_seed: int | None = None, safe_prompt: bool | None = None, response_format: dict | None = None, @@ -192,13 +203,40 @@ class MistralConfig(OpenAIGPTConfig): *(("prompt_cache_key",) if accepts_prompt_cache_key else ()), ] - def _map_tool_choice(self, tool_choice: str) -> str: - if tool_choice == "auto" or tool_choice == "none": - return tool_choice - elif tool_choice == "required": - return "any" - else: # openai 'tool_choice' object param not supported by Mistral API - return "any" + @staticmethod + def _map_tool_choice(tool_choice: object) -> str | ChatCompletionToolChoiceObjectParam | None: + match tool_choice: + case str(choice) if choice in ("auto", "none"): + return choice + case "required" | "any": + return "any" + case {"type": "function", "function": {"name": str(name)}} if name: + return ChatCompletionToolChoiceObjectParam( + type="function", function=ChatCompletionToolChoiceFunctionParam(name=name) + ) + case _: + return None + + def _tool_choice_to_send( + self, model: str, tool_choice: object, drop_params: bool + ) -> str | ChatCompletionToolChoiceObjectParam | UnsupportedParamsError | None: + mapped: Final = self._map_tool_choice(tool_choice) + if mapped is not None: + return mapped + if drop_params or litellm.drop_params is True: + warn_dropped_reasoning( + "tool_choice", tool_choice, model, _UNUSABLE_TOOL_CHOICE_REASON, drop_params_gated=True + ) + return None + return UnsupportedParamsError( + message=( + f"Unsupported tool_choice={reprlib.repr(tool_choice)} for model={model}, since " + f"{_UNUSABLE_TOOL_CHOICE_REASON} " + "To drop it, set `litellm.drop_params=True` or for proxy:\n\n`litellm_settings:\n drop_params: true`\n" + ), + llm_provider=self.custom_llm_provider, + model=model, + ) @staticmethod def _get_mistral_reasoning_system_prompt() -> str: @@ -244,18 +282,20 @@ class MistralConfig(OpenAIGPTConfig): optional_params["tools"] = self._clean_tool_schema_for_mistral(value) if param == "stream" and value is True: optional_params["stream"] = value - if param == "temperature": - optional_params["temperature"] = value - if param == "top_p": - optional_params["top_p"] = value - if param == "stop": - optional_params["stop"] = value - if param == "tool_choice" and isinstance(value, str): - optional_params["tool_choice"] = self._map_tool_choice(tool_choice=value) + if param == "tool_choice" and "tools" in non_default_params and non_default_params["tools"]: + match self._tool_choice_to_send( + model, + cast(object, value), # cast-ok: untyped request params, the match narrows it + drop_params, + ): + case UnsupportedParamsError() as unusable_tool_choice: + raise unusable_tool_choice + case None: + pass + case tool_choice: + optional_params["tool_choice"] = tool_choice if param == "seed": optional_params["extra_body"] = {"random_seed": value} - if param == "response_format": - optional_params["response_format"] = value if ( param == "reasoning_effort" and "magistral" not in model.lower() @@ -271,7 +311,7 @@ class MistralConfig(OpenAIGPTConfig): # Flag that we need to add reasoning system prompt optional_params["_add_reasoning_prompt"] = True _warn_unless_reasoning_prompt_honors(param, OPAQUE_VALUE.validate_python(value), model) - if param in ("parallel_tool_calls", "prompt_cache_key"): + if param in ("temperature", "top_p", "stop", "response_format", "parallel_tool_calls", "prompt_cache_key"): optional_params[param] = value return optional_params diff --git a/litellm/llms/nvidia_riva/audio_transcription/handler.py b/litellm/llms/nvidia_riva/audio_transcription/handler.py index cafeece0a4e..d2ef33b89dd 100644 --- a/litellm/llms/nvidia_riva/audio_transcription/handler.py +++ b/litellm/llms/nvidia_riva/audio_transcription/handler.py @@ -13,24 +13,26 @@ The handler is intentionally a thin orchestration layer: 2. Build ``RecognitionConfig`` / ``StreamingRecognitionConfig`` protobufs from the structured dict produced by :class:`NvidiaRivaAudioTranscriptionConfig`. -3. Construct ``riva.client.Auth`` honoring NVCF (function-id metadata + TLS) - vs self-hosted (any host:port, optional TLS) modes. -4. Stream the audio through Riva's ``streaming_response_generator`` and - aggregate ``is_final`` results into a single transcript, or, when - ``riva_offline`` is set, send the whole buffer through the unary - ``offline_recognize`` RPC for NIMs that only ship offline engines. +3. Open a gRPC channel honoring NVCF (TLS by default) vs self-hosted (any + host:port, optional TLS) modes, and attach the ``authorization`` and NVCF + ``function-id`` metadata to each call exactly once. +4. Stream the audio through Riva's ``StreamingRecognize`` RPC and aggregate + ``is_final`` results into a single transcript, or, when ``riva_offline`` + is set, send the whole buffer through the unary ``Recognize`` RPC for NIMs + that only ship offline engines. 5. Return a normalized ``TranscriptionResponse`` with ``duration`` exposed on ``_hidden_params`` so cost calculation works. -``riva-client`` is imported lazily so ``litellm`` core remains usable -without the optional STT extras installed. +``grpcio`` and ``protobuf`` are imported lazily so ``litellm`` core remains +usable without the optional STT extras installed. """ +from __future__ import annotations + import asyncio -import inspect -from collections.abc import Callable, Iterable, Mapping, Sequence -from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final, Protocol +from collections.abc import Iterable, Sequence +from contextlib import closing +from typing import TYPE_CHECKING, Final import httpx @@ -64,89 +66,19 @@ if TYPE_CHECKING: Logging as LiteLLMLoggingObj, ) -# Stream audio to Riva in ~50 ms slices (1600 samples at 16 kHz). Matches -# NVIDIA's recommended chunk size for streaming ASR — small enough for -# responsive endpointing, large enough to keep per-RPC overhead low. -_DEFAULT_CHUNK_SAMPLES: Final = 1600 -_DEFAULT_CHUNK_BYTES: Final = _DEFAULT_CHUNK_SAMPLES * 2 # int16 = 2 bytes/sample - - _RIVA_INSTALL_HINT = "NVIDIA Riva client is not installed. Install with `pip install 'litellm[stt-nvidia-riva]'`." -class _RivaAuth(Protocol): - """Opaque ``riva.client.Auth`` handle.""" - - -class _RecognizeFuture(Protocol): - def result(self, timeout: float | None = None) -> object: ... - - def done(self) -> bool: ... - - def cancel(self) -> bool: ... - - -class _AsrService(Protocol): - @property - def streaming_response_generator(self) -> Callable[..., Iterable[object]]: ... - - def offline_recognize(self, audio_bytes: bytes, config: object, future: bool) -> _RecognizeFuture: ... - - -class _EndpointingConfig(Protocol): - """Opaque ``EndpointingConfig`` protobuf message.""" - - -class _EndpointingConfigField(Protocol): - CopyFrom: Callable[[_EndpointingConfig], None] - - -class _RecognitionConfig(Protocol): - @property - def endpointing_config(self) -> _EndpointingConfigField: ... - - -class _StreamingRecognitionConfig(Protocol): - """Opaque ``StreamingRecognitionConfig`` protobuf message.""" - - -class _AudioEncoding(Protocol): - @property - def LINEAR_PCM(self) -> object: ... - - -class _RivaClientModule(Protocol): - """The ``riva.client`` entry points this handler calls.""" - - @property - def Auth(self) -> Callable[..., _RivaAuth]: ... - - @property - def ASRService(self) -> Callable[[_RivaAuth], _AsrService]: ... - - -class _RivaAsrModule(Protocol): - """The protobuf constructors this handler calls, from whichever module exposes them.""" - - @property - def AudioEncoding(self) -> _AudioEncoding: ... - - @property - def RecognitionConfig(self) -> Callable[..., _RecognitionConfig]: ... - - @property - def StreamingRecognitionConfig(self) -> Callable[..., _StreamingRecognitionConfig]: ... - - @property - def EndpointingConfig(self) -> Callable[..., _EndpointingConfig]: ... - - -def _auth_factory(riva_module: _RivaClientModule) -> Callable[..., _RivaAuth]: - return riva_module.Auth - - -def _audio_encoding(riva_asr_module: _RivaAsrModule) -> _AudioEncoding: - return riva_asr_module.AudioEncoding +def _use_ssl(optional_params: dict) -> bool: + """ + NVCF endpoints are TLS-only, so ``nvcf_function_id`` defaults ``use_ssl`` + to True. Self-hosted Riva defaults to plaintext but honors an explicit + ``use_ssl``, since TLS-terminating ingresses in front of it are common. + """ + use_ssl_override: Final = optional_params.get("use_ssl") + if use_ssl_override is not None: + return bool(use_ssl_override) + return bool(optional_params.get("nvcf_function_id")) def _parse_riva_offline(value: object, drop_params: bool) -> bool: @@ -192,7 +124,7 @@ class NvidiaRivaAudioTranscription: litellm_params: dict, model_response: TranscriptionResponse, timeout: float | str | httpx.Timeout | None, - logging_obj: "LiteLLMLoggingObj", + logging_obj: LiteLLMLoggingObj, api_key: str | None, api_base: str | None, atranscription: bool = False, @@ -237,13 +169,11 @@ class NvidiaRivaAudioTranscription: litellm_params: dict, model_response: TranscriptionResponse, timeout: float | str | httpx.Timeout | None, - logging_obj: "LiteLLMLoggingObj", + logging_obj: LiteLLMLoggingObj, api_key: str | None, api_base: str | None, provider_config: NvidiaRivaAudioTranscriptionConfig | None = None, ) -> TranscriptionResponse: - # ``riva-client`` exposes a sync streaming generator, so we offload - # the blocking call to a worker thread to keep the event loop free. return await asyncio.to_thread( self._run_sync, model=model, @@ -267,7 +197,7 @@ class NvidiaRivaAudioTranscription: litellm_params: dict, model_response: TranscriptionResponse, timeout: float | str | httpx.Timeout | None, - logging_obj: "LiteLLMLoggingObj", + logging_obj: LiteLLMLoggingObj, api_key: str | None, api_base: str | None, provider_config: NvidiaRivaAudioTranscriptionConfig, @@ -317,18 +247,12 @@ class NvidiaRivaAudioTranscription: ) or litellm.drop_params is True riva_offline: Final = _parse_riva_offline(optional_params.get("riva_offline"), drop_params=drop_params) - riva_module, riva_asr_module = _import_riva() - auth_obj: Final = self._construct_auth( - riva_module=riva_module, - api_base=api_base, - api_key=api_key, - optional_params=optional_params, - ) + try: + from litellm.llms.nvidia_riva.audio_transcription import riva_grpc + except ImportError as e: + raise NvidiaRivaException(status_code=500, message=_RIVA_INSTALL_HINT) from e - recognition_config: Final = self._build_recognition_config_proto( - riva_asr_module=riva_asr_module, - recognition_config_dict=recognition_config_dict, - ) + recognition_config: Final = riva_grpc.recognition_config(recognition_config_dict) logging_obj.pre_call( input=None, api_key=api_key, @@ -344,26 +268,18 @@ class NvidiaRivaAudioTranscription: }, ) + metadata: Final = riva_grpc.call_metadata(api_key, optional_params.get("nvcf_function_id")) try: - asr_service: Final[_AsrService] = riva_module.ASRService(auth_obj) - responses: Final = ( - self._offline_responses( - asr_service=asr_service, - pcm_bytes=resampled.pcm_bytes, - recognition_config=recognition_config, - timeout=None if timeout is None else _deadline_seconds(timeout, drop_params), + deadline: Final = None if timeout is None else _deadline_seconds(timeout, drop_params) + with closing(riva_grpc.open_channel(api_base, _use_ssl(optional_params))) as channel: + responses: Final = ( + riva_grpc.recognize(channel, recognition_config, resampled.pcm_bytes, metadata, deadline) + if riva_offline + else riva_grpc.streaming_recognize( + channel, recognition_config, resampled.pcm_bytes, metadata, deadline + ) ) - if riva_offline - else self._streaming_responses( - asr_service=asr_service, - riva_asr_module=riva_asr_module, - pcm_bytes=resampled.pcm_bytes, - recognition_config=recognition_config, - timeout=timeout, - drop_params=drop_params, - ) - ) - final_results: Final = self._collect_final_results(responses, require_final=not riva_offline) + final_results: Final = self._collect_final_results(responses, require_final=not riva_offline) except NvidiaRivaException: raise except Exception as e: @@ -400,142 +316,6 @@ class NvidiaRivaAudioTranscription: return final_response - def _construct_auth( - self, - riva_module: _RivaClientModule, - api_base: str, - api_key: str | None, - optional_params: dict, - ) -> _RivaAuth: - """ - Build a ``riva.client.Auth`` object. - - - When ``nvcf_function_id`` is provided we attach the NVCF - ``function-id`` and bearer ``authorization`` metadata, and default - ``use_ssl`` to True (NVCF endpoints are TLS-only). - - Otherwise (self-hosted) we default ``use_ssl`` to False but still - honor an explicit override — self-hosted Riva behind an ingress - with TLS termination is a real deployment topology. - """ - nvcf_function_id: Final = optional_params.get("nvcf_function_id") - use_ssl_override: Final = optional_params.get("use_ssl") - use_ssl: Final = bool(use_ssl_override) if use_ssl_override is not None else bool(nvcf_function_id) - - metadata: Final[list[tuple[str, str]]] = [] - if nvcf_function_id: - metadata.append(("function-id", str(nvcf_function_id))) - if api_key: - metadata.append(("authorization", f"Bearer {api_key}")) - - try: - return _auth_factory(riva_module)(uri=api_base, use_ssl=use_ssl, metadata_args=metadata) - except TypeError: - # Older riva-client signatures used positional-only args. - return _auth_factory(riva_module)(None, use_ssl, api_base, metadata) - - def _build_recognition_config_proto( - self, riva_asr_module: _RivaAsrModule, recognition_config_dict: dict[str, Any] - ) -> _RecognitionConfig: - encoding_name: Final = (recognition_config_dict.get("encoding") or "LINEAR_PCM").upper() - encoding_enum: Final[object] = getattr( - _audio_encoding(riva_asr_module), - encoding_name, - _audio_encoding(riva_asr_module).LINEAR_PCM, - ) - - config: Final[_RecognitionConfig] = riva_asr_module.RecognitionConfig( - encoding=encoding_enum, - sample_rate_hertz=int(recognition_config_dict["sample_rate_hertz"]), - language_code=recognition_config_dict["language_code"], - audio_channel_count=int(recognition_config_dict["audio_channel_count"]), - enable_automatic_punctuation=bool(recognition_config_dict.get("enable_automatic_punctuation", True)), - enable_word_time_offsets=bool(recognition_config_dict.get("enable_word_time_offsets", False)), - max_alternatives=int(recognition_config_dict.get("max_alternatives", 1)), - model=recognition_config_dict.get("model", "") or "", - verbatim_transcripts=bool(recognition_config_dict.get("verbatim_transcripts", False)), - profanity_filter=bool(recognition_config_dict.get("profanity_filter", False)), - ) - - endpointing: Final = recognition_config_dict.get("endpointing_config") - if isinstance(endpointing, dict) and endpointing: - try: - ep: Final[_EndpointingConfig] = riva_asr_module.EndpointingConfig(**endpointing) - config.endpointing_config.CopyFrom(ep) - except Exception: - # If the user supplied an unknown EndpointingConfig field - # (older Riva server), fall back to Riva's defaults rather - # than failing the whole request. - pass - - return config - - def _streaming_responses( - self, - asr_service: _AsrService, - riva_asr_module: _RivaAsrModule, - pcm_bytes: bytes, - recognition_config: _RecognitionConfig, - timeout: float | str | httpx.Timeout | None, - drop_params: bool, - ) -> Iterable[object]: - streaming_config: Final[_StreamingRecognitionConfig] = riva_asr_module.StreamingRecognitionConfig( - config=recognition_config, interim_results=False - ) - return asr_service.streaming_response_generator( - audio_chunks=self._iter_audio_chunks(pcm_bytes), - streaming_config=streaming_config, - **self._timeout_kwargs(asr_service.streaming_response_generator, timeout, drop_params), - ) - - def _offline_responses( - self, - asr_service: _AsrService, - pcm_bytes: bytes, - recognition_config: _RecognitionConfig, - timeout: float | None, - ) -> Iterable[object]: - pending: Final = asr_service.offline_recognize(audio_bytes=pcm_bytes, config=recognition_config, future=True) - try: - return (pending.result(timeout=timeout),) - except Exception as e: - if pending.done(): - raise - pending.cancel() - raise NvidiaRivaException( - status_code=408, - message=f"NVIDIA Riva offline recognition did not finish within {timeout} seconds", - ) from e - - @classmethod - def _timeout_kwargs( - cls, rpc: Callable[..., object], timeout: float | str | httpx.Timeout | None, drop_params: bool - ) -> Mapping[str, float]: - # Forward the deadline so the call cannot block forever if the - # server stalls. Older riva-client versions do not accept a - # ``timeout`` kwarg, so pass it only when supported. - if timeout is None or not cls._supports_timeout_kwarg(rpc): - return MappingProxyType({}) - return MappingProxyType({"timeout": _deadline_seconds(timeout, drop_params)}) - - @staticmethod - def _supports_timeout_kwarg(callable_obj: Callable[..., object]) -> bool: - try: - sig: Final = inspect.signature(callable_obj) - except (TypeError, ValueError): - return False - params: Final = sig.parameters - if "timeout" in params: - return True - return any(p.kind == inspect.Parameter.VAR_KEYWORD for p in params.values()) - - @staticmethod - def _iter_audio_chunks(pcm_bytes: bytes): - for offset in range(0, len(pcm_bytes), _DEFAULT_CHUNK_BYTES): - chunk = pcm_bytes[offset : offset + _DEFAULT_CHUNK_BYTES] - if not chunk: - continue - yield chunk - @staticmethod def _collect_final_results(stream: Iterable[object], require_final: bool = True) -> Sequence[RivaFinalResult]: """ @@ -570,27 +350,3 @@ class NvidiaRivaAudioTranscription: } ) return final_results - - -def _import_riva() -> tuple[_RivaClientModule, _RivaAsrModule]: - """ - Lazy import of ``riva.client`` and ``riva.client.proto.riva_asr_pb2``. - - We try the SDK first (preferred) and fall back to importing the proto - module separately when the SDK packaging changes between versions. - """ - try: - import riva.client as riva_client - except ImportError as e: - raise NvidiaRivaException(status_code=500, message=_RIVA_INSTALL_HINT) from e - - riva_asr_module = riva_client - if not hasattr(riva_asr_module, "RecognitionConfig"): - try: - from riva.client.proto import riva_asr_pb2 - - riva_asr_module = riva_asr_pb2 - except ImportError as e: - raise NvidiaRivaException(status_code=500, message=_RIVA_INSTALL_HINT) from e - - return riva_client, riva_asr_module diff --git a/litellm/llms/nvidia_riva/audio_transcription/riva_asr_schema.py b/litellm/llms/nvidia_riva/audio_transcription/riva_asr_schema.py new file mode 100644 index 00000000000..13af5820f07 --- /dev/null +++ b/litellm/llms/nvidia_riva/audio_transcription/riva_asr_schema.py @@ -0,0 +1,199 @@ +""" +The part of NVIDIA Riva's speech recognition gRPC schema that LiteLLM sends and reads. + +Names and numbers match ``riva/proto/riva_asr.proto`` and ``riva/proto/riva_audio.proto`` in +https://github.com/nvidia-riva/common. Fields LiteLLM never sets or reads are left out, and the +wire format skips them. The messages live in their own descriptor pool so they never collide +with nvidia-riva-client's copies when both are imported in one process. +""" + +from dataclasses import dataclass +from enum import Enum, IntEnum +from typing import Final + +from google.protobuf import descriptor_pb2, descriptor_pool, message_factory +from google.protobuf.message import Message + +_PACKAGE: Final = "nvidia.riva.asr" +_SERVICE: Final = f"/{_PACKAGE}.RivaSpeechRecognition" +RECOGNIZE_METHOD: Final = f"{_SERVICE}/Recognize" +STREAMING_RECOGNIZE_METHOD: Final = f"{_SERVICE}/StreamingRecognize" + + +class _Kind(Enum): + FLOAT = "TYPE_FLOAT" + INT32 = "TYPE_INT32" + BOOL = "TYPE_BOOL" + STRING = "TYPE_STRING" + MESSAGE = "TYPE_MESSAGE" + BYTES = "TYPE_BYTES" + ENUM = "TYPE_ENUM" + + +class AudioEncoding(IntEnum): + ENCODING_UNSPECIFIED = 0 + LINEAR_PCM = 1 + + +LINEAR_PCM: Final = AudioEncoding.LINEAR_PCM.value + + +@dataclass(frozen=True, slots=True) +class _Field: + name: str + number: int + kind: _Kind + type_name: str = "" + repeated: bool = False + optional: bool = False + oneof: str = "" + + +_MESSAGES: Final[tuple[tuple[str, tuple[_Field, ...]], ...]] = ( + ( + "RecognitionConfig", + ( + _Field("encoding", 1, _Kind.ENUM, "AudioEncoding"), + _Field("sample_rate_hertz", 2, _Kind.INT32), + _Field("language_code", 3, _Kind.STRING), + _Field("max_alternatives", 4, _Kind.INT32), + _Field("profanity_filter", 5, _Kind.BOOL), + _Field("audio_channel_count", 7, _Kind.INT32), + _Field("enable_word_time_offsets", 8, _Kind.BOOL), + _Field("enable_automatic_punctuation", 11, _Kind.BOOL), + _Field("model", 13, _Kind.STRING), + _Field("verbatim_transcripts", 14, _Kind.BOOL), + _Field("endpointing_config", 25, _Kind.MESSAGE, "EndpointingConfig", optional=True), + ), + ), + ( + "EndpointingConfig", + ( + _Field("start_history", 1, _Kind.INT32, optional=True), + _Field("start_threshold", 2, _Kind.FLOAT, optional=True), + _Field("stop_history", 3, _Kind.INT32, optional=True), + _Field("stop_threshold", 4, _Kind.FLOAT, optional=True), + _Field("stop_history_eou", 5, _Kind.INT32, optional=True), + _Field("stop_threshold_eou", 6, _Kind.FLOAT, optional=True), + ), + ), + ( + "StreamingRecognitionConfig", + ( + _Field("config", 1, _Kind.MESSAGE, "RecognitionConfig"), + _Field("interim_results", 2, _Kind.BOOL), + ), + ), + ( + "StreamingRecognizeRequest", + ( + _Field("streaming_config", 1, _Kind.MESSAGE, "StreamingRecognitionConfig", oneof="streaming_request"), + _Field("audio_content", 2, _Kind.BYTES, oneof="streaming_request"), + ), + ), + ( + "WordInfo", + ( + _Field("start_time", 1, _Kind.INT32), + _Field("end_time", 2, _Kind.INT32), + _Field("word", 3, _Kind.STRING), + ), + ), + ( + "SpeechRecognitionAlternative", + ( + _Field("transcript", 1, _Kind.STRING), + _Field("words", 3, _Kind.MESSAGE, "WordInfo", repeated=True), + ), + ), + ( + "StreamingRecognitionResult", + ( + _Field("alternatives", 1, _Kind.MESSAGE, "SpeechRecognitionAlternative", repeated=True), + _Field("is_final", 2, _Kind.BOOL), + ), + ), + ( + "StreamingRecognizeResponse", + (_Field("results", 1, _Kind.MESSAGE, "StreamingRecognitionResult", repeated=True),), + ), + ( + "RecognizeRequest", + ( + _Field("config", 1, _Kind.MESSAGE, "RecognitionConfig"), + _Field("audio", 2, _Kind.BYTES), + ), + ), + ( + "SpeechRecognitionResult", + (_Field("alternatives", 1, _Kind.MESSAGE, "SpeechRecognitionAlternative", repeated=True),), + ), + ( + "RecognizeResponse", + (_Field("results", 1, _Kind.MESSAGE, "SpeechRecognitionResult", repeated=True),), + ), +) + + +def _oneof_names(fields: tuple[_Field, ...]) -> tuple[str, ...]: + declared: Final = tuple(dict.fromkeys(field.oneof for field in fields if field.oneof)) + synthetic: Final = tuple(f"_{field.name}" for field in fields if field.optional) + return declared + synthetic + + +def _field_proto(field: _Field, oneofs: tuple[str, ...]) -> descriptor_pb2.FieldDescriptorProto: + oneof: Final = f"_{field.name}" if field.optional else field.oneof + return descriptor_pb2.FieldDescriptorProto( + name=field.name, + number=field.number, + type=descriptor_pb2.FieldDescriptorProto.Type.Value(field.kind.value), + label=( + descriptor_pb2.FieldDescriptorProto.LABEL_REPEATED + if field.repeated + else descriptor_pb2.FieldDescriptorProto.LABEL_OPTIONAL + ), + type_name=f".{_PACKAGE}.{field.type_name}" if field.type_name else None, + oneof_index=oneofs.index(oneof) if oneof else None, + proto3_optional=field.optional or None, + ) + + +def _message_proto(name: str, fields: tuple[_Field, ...]) -> descriptor_pb2.DescriptorProto: + oneofs: Final = _oneof_names(fields) + return descriptor_pb2.DescriptorProto( + name=name, + field=[_field_proto(field, oneofs) for field in fields], + oneof_decl=[descriptor_pb2.OneofDescriptorProto(name=oneof) for oneof in oneofs], + ) + + +_FILE: Final = descriptor_pb2.FileDescriptorProto( + name="litellm/nvidia_riva/riva_asr.proto", + package=_PACKAGE, + syntax="proto3", + enum_type=[ + descriptor_pb2.EnumDescriptorProto( + name="AudioEncoding", + value=[ + descriptor_pb2.EnumValueDescriptorProto(name=encoding.name, number=encoding.value) + for encoding in AudioEncoding + ], + ) + ], + message_type=[_message_proto(name, fields) for name, fields in _MESSAGES], +) +_POOL: Final = descriptor_pool.DescriptorPool() +_POOL.AddSerializedFile(_FILE.SerializeToString()) + + +def _message_class(name: str) -> type[Message]: + return message_factory.GetMessageClass(_POOL.FindMessageTypeByName(f"{_PACKAGE}.{name}")) + + +RecognitionConfig: Final = _message_class("RecognitionConfig") +EndpointingConfig: Final = _message_class("EndpointingConfig") +StreamingRecognitionConfig: Final = _message_class("StreamingRecognitionConfig") +StreamingRecognizeRequest: Final = _message_class("StreamingRecognizeRequest") +StreamingRecognizeResponse: Final = _message_class("StreamingRecognizeResponse") +RecognizeRequest: Final = _message_class("RecognizeRequest") +RecognizeResponse: Final = _message_class("RecognizeResponse") diff --git a/litellm/llms/nvidia_riva/audio_transcription/riva_grpc.py b/litellm/llms/nvidia_riva/audio_transcription/riva_grpc.py new file mode 100644 index 00000000000..8367853673f --- /dev/null +++ b/litellm/llms/nvidia_riva/audio_transcription/riva_grpc.py @@ -0,0 +1,113 @@ +""" +gRPC calls to NVIDIA Riva's speech recognition service. + +The ``authorization`` and NVCF ``function-id`` metadata ride on each call, never on the channel, so every +request carries them exactly once over both plaintext and TLS. +""" + +from collections.abc import Iterator, Mapping, Sequence +from typing import Any, Final, TypeAlias + +import grpc +from google.protobuf.message import Message +from pydantic import TypeAdapter + +from litellm.llms.nvidia_riva.audio_transcription import riva_asr_schema as schema +from litellm.llms.nvidia_riva.common_utils import NvidiaRivaException + +# Stream audio to Riva in ~50 ms slices (1600 samples at 16 kHz). Matches +# NVIDIA's recommended chunk size for streaming ASR, small enough for +# responsive endpointing, large enough to keep per-RPC overhead low. +_CHUNK_SAMPLES: Final = 1600 +_CHUNK_BYTES: Final = _CHUNK_SAMPLES * 2 + +CallMetadata: TypeAlias = tuple[tuple[str, str], ...] + +_ENDPOINTING_FIELDS: Final = TypeAdapter(Mapping[str, object]) + + +def call_metadata(api_key: str | None, nvcf_function_id: object) -> CallMetadata: + function_id: Final = (("function-id", str(nvcf_function_id)),) if nvcf_function_id else () + authorization: Final = (("authorization", f"Bearer {api_key}"),) if api_key else () + return function_id + authorization + + +def open_channel(api_base: str, use_ssl: bool) -> grpc.Channel: + if use_ssl: + return grpc.secure_channel(api_base, grpc.ssl_channel_credentials()) + return grpc.insecure_channel(api_base) + + +def recognition_config(config: Mapping[str, Any]) -> Message: + endpointing: Final = _endpointing_config(config.get("endpointing_config")) + return schema.RecognitionConfig( + encoding=schema.LINEAR_PCM, + sample_rate_hertz=int(config["sample_rate_hertz"]), + language_code=config["language_code"], + audio_channel_count=int(config["audio_channel_count"]), + enable_automatic_punctuation=bool(config.get("enable_automatic_punctuation", True)), + enable_word_time_offsets=bool(config.get("enable_word_time_offsets", False)), + max_alternatives=int(config.get("max_alternatives", 1)), + model=config.get("model", "") or "", + verbatim_transcripts=bool(config.get("verbatim_transcripts", False)), + profanity_filter=bool(config.get("profanity_filter", False)), + **({} if endpointing is None else {"endpointing_config": endpointing}), + ) + + +def _endpointing_config(endpointing: object) -> Message | None: + try: + fields: Final = _ENDPOINTING_FIELDS.validate_python(endpointing) + return schema.EndpointingConfig(**fields) if fields else None + except (ValueError, TypeError): + # A missing, unknown or mistyped field falls back to Riva's default + # endpointing rather than failing the whole request. + return None + + +def _streaming_requests(config: Message, pcm_bytes: bytes) -> Iterator[Message]: + yield schema.StreamingRecognizeRequest( + streaming_config=schema.StreamingRecognitionConfig(config=config, interim_results=False) + ) + for offset in range(0, len(pcm_bytes), _CHUNK_BYTES): + yield schema.StreamingRecognizeRequest(audio_content=pcm_bytes[offset : offset + _CHUNK_BYTES]) + + +def streaming_recognize( + channel: grpc.Channel, + config: Message, + pcm_bytes: bytes, + metadata: CallMetadata, + timeout: float | None, +) -> Iterator[Message]: + rpc: Final = channel.stream_stream( + schema.STREAMING_RECOGNIZE_METHOD, + request_serializer=schema.StreamingRecognizeRequest.SerializeToString, + response_deserializer=schema.StreamingRecognizeResponse.FromString, + ) + return rpc(_streaming_requests(config, pcm_bytes), metadata=metadata, timeout=timeout) + + +def recognize( + channel: grpc.Channel, + config: Message, + pcm_bytes: bytes, + metadata: CallMetadata, + timeout: float | None, +) -> Sequence[Message]: + rpc: Final = channel.unary_unary( + schema.RECOGNIZE_METHOD, + request_serializer=schema.RecognizeRequest.SerializeToString, + response_deserializer=schema.RecognizeResponse.FromString, + ) + pending: Final = rpc.future(schema.RecognizeRequest(config=config, audio=pcm_bytes), metadata=metadata) + try: + return (pending.result(timeout=timeout),) + except Exception as e: + if pending.done(): + raise + pending.cancel() + raise NvidiaRivaException( + status_code=408, + message=f"NVIDIA Riva offline recognition did not finish within {timeout} seconds", + ) from e diff --git a/litellm/llms/ollama/chat/transformation.py b/litellm/llms/ollama/chat/transformation.py index 168b562b358..59020b058a2 100644 --- a/litellm/llms/ollama/chat/transformation.py +++ b/litellm/llms/ollama/chat/transformation.py @@ -4,7 +4,7 @@ from collections.abc import AsyncIterator, Iterator, Mapping from typing import TYPE_CHECKING, Any, Final, cast from httpx._models import Headers, Response -from pydantic import BaseModel +from pydantic import BaseModel, TypeAdapter import litellm from litellm._uuid import uuid @@ -15,6 +15,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import ( extract_reasoning_content, ) from litellm.litellm_core_utils.reasoning_effort_utils import OPAQUE_VALUE +from litellm.litellm_core_utils.tool_fields import tool_params_without_hosted_mcp from litellm.litellm_core_utils.url_utils import ensure_api_route from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException @@ -40,6 +41,8 @@ if TYPE_CHECKING: else: LiteLLMLoggingObj = Any +_REQUEST_PARAMS: Final = TypeAdapter(dict[str, object]) + class OllamaChatConfig(BaseConfig): """ @@ -152,7 +155,13 @@ class OllamaChatConfig(BaseConfig): model: str, drop_params: bool, ) -> dict: - for param, value in non_default_params.items(): + request_params: Final = tool_params_without_hosted_mcp( + _REQUEST_PARAMS.validate_python(non_default_params), + model=model, + route="ollama_chat", + drop_params=drop_params, + ) + for param, value in request_params.items(): if param == "max_tokens" or param == "max_completion_tokens": optional_params["num_predict"] = value if param == "stream": diff --git a/litellm/llms/openai/chat/gpt_transformation.py b/litellm/llms/openai/chat/gpt_transformation.py index 9d551f6f859..0479ac5c36c 100644 --- a/litellm/llms/openai/chat/gpt_transformation.py +++ b/litellm/llms/openai/chat/gpt_transformation.py @@ -21,6 +21,7 @@ from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response impo should_convert_tool_call_to_json_mode, ) from litellm.litellm_core_utils.prompt_templates.common_utils import ( + chat_completion_prompt_cache_breakpoints_for_wire, drop_non_python_regex_patterns, drop_tool_reference_parts_from_tool_messages, flatten_combinators_and_drop_non_python_regex_patterns, @@ -555,26 +556,38 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig): ) -> tuple[Sequence[AllMessageValues], Sequence["ChatCompletionToolParam"] | None]: """ A deployment that reads OpenAI's ``prompt_cache_breakpoint`` (gpt-5.6+ on - api.openai.com, or one opted in through ``prompt_cache_options`` or the cost - map) gets each Anthropic ``cache_control`` mark rewritten in place. Any other - endpoint keeps or strips the marks as before, and under drop_params also loses - every ``prompt_cache_breakpoint`` it cannot read. + api.openai.com, or one opted in through ``prompt_cache_options``, its own + ``model_info``, or the cost map) gets each + Anthropic ``cache_control`` mark rewritten in place, and under drop_params each + content part's ``prompt_cache_breakpoint`` cut down to what chat completions + accepts. Any other endpoint keeps or strips the marks as before, and under + drop_params also loses every ``prompt_cache_breakpoint`` it cannot read. """ - from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheControlHook + from litellm.integrations.anthropic_cache_control_hook import AnthropicCacheControlHook, routed_model_info custom_llm_provider: Final = _litellm_params_str(litellm_params, "custom_llm_provider") api_base: Final = _litellm_params_str(litellm_params, "api_base") reads_breakpoints: Final = AnthropicCacheControlHook.targets_openai_prompt_cache_breakpoint( - model, custom_llm_provider, api_base, prompt_cache_options + model, + custom_llm_provider, + api_base, + prompt_cache_options, + routed_model_info(litellm_params.get("model_info")), ) if not reads_breakpoints and self._should_preserve_cache_control_for_endpoint(custom_llm_provider, api_base): return ( _claude_messages_within_cache_control_cap(model, messages, tools, litellm_params, request_params), tools, ) - drops_breakpoints: Final = not reads_breakpoints and _drops_params(litellm_params) + drop_params: Final = _drops_params(litellm_params) + drops_breakpoints: Final = not reads_breakpoints and drop_params renamed: Final = ( - [AnthropicCacheControlHook.cache_control_as_prompt_cache_breakpoints(message) for message in messages] + [ + AnthropicCacheControlHook.cache_control_as_prompt_cache_breakpoints( + chat_completion_prompt_cache_breakpoints_for_wire(message, drop_params) + ) + for message in messages + ] if reads_breakpoints else [without_prompt_cache_breakpoints(message) for message in messages] if drops_breakpoints diff --git a/litellm/llms/openai/cost_calculation.py b/litellm/llms/openai/cost_calculation.py index 36d7e4d95de..bc8aaab3185 100644 --- a/litellm/llms/openai/cost_calculation.py +++ b/litellm/llms/openai/cost_calculation.py @@ -31,9 +31,9 @@ def cost_per_token( Input: - model: str, the model name without provider prefix - usage: LiteLLM Usage block, containing anthropic caching information - - data_residency: optional OpenAI data-residency region (e.g. "eu", "us"), - inferred from api_base. Applies the model's regional-processing - uplift multiplier when set. + - data_residency: optional OpenAI data-residency mode (e.g. "eu", "us", "fedramp"), + inferred from api_base, including gov.api.openai.com. Applies the + model's regional-processing uplift multiplier when set. Returns: Tuple[float, float] - prompt_cost_in_usd, completion_cost_in_usd diff --git a/litellm/llms/openai/data_residency.py b/litellm/llms/openai/data_residency.py index d4859221541..a8831db3517 100644 --- a/litellm/llms/openai/data_residency.py +++ b/litellm/llms/openai/data_residency.py @@ -7,9 +7,12 @@ enabled and rejects requests sent to the wrong host, so the api_base hostname is the authoritative signal of which region a request was processed in. """ +import os from typing import Final from urllib.parse import urlparse +import litellm + # Mapping of OpenAI regional hostnames to the corresponding data-residency # value used by the cost calculator. See # https://developers.openai.com/api/docs/pricing for the regional-processing @@ -17,6 +20,7 @@ from urllib.parse import urlparse _OPENAI_REGIONAL_HOSTS: Final[dict[str, str]] = { "eu.api.openai.com": "eu", "us.api.openai.com": "us", + "gov.api.openai.com": "fedramp", } @@ -25,13 +29,22 @@ def infer_openai_data_residency(custom_llm_provider: str | None, api_base: str | Derive the OpenAI data-residency region from an api_base URL. Returns ``"eu"`` for the EU regional host, ``"us"`` for the US regional - host, and ``None`` for the default global host, any non-OpenAI provider, - or any non-OpenAI URL. + host, ``"fedramp"`` for ``gov.api.openai.com``, and ``None`` for the + default global host, any non-OpenAI provider, or any non-OpenAI URL. + + When ``api_base`` is unset, falls back to the same defaults the OpenAI + handler uses (``litellm.api_base``, ``OPENAI_BASE_URL``, ``OPENAI_API_BASE``) + so env-configured regional endpoints are billed with their uplift. """ - if custom_llm_provider != "openai" or not api_base: + if custom_llm_provider != "openai": + return None + resolved_api_base: Final = ( + api_base or litellm.api_base or os.getenv("OPENAI_BASE_URL") or os.getenv("OPENAI_API_BASE") + ) + if not resolved_api_base: return None try: - host: Final = urlparse(api_base).hostname + host: Final = urlparse(resolved_api_base).hostname except (TypeError, ValueError): return None if not host: diff --git a/litellm/llms/openai/decisions/transformation.py b/litellm/llms/openai/decisions/transformation.py index 369b6959411..5aa72579d6a 100644 --- a/litellm/llms/openai/decisions/transformation.py +++ b/litellm/llms/openai/decisions/transformation.py @@ -307,10 +307,13 @@ def _openai_answer(question: DecisionsIRQuestion, answer: DecisionsIRAnswer) -> def ir_to_openai_response( - response: DecisionsIRResponse, request: DecisionsIRRequest, requested_model: str + response: DecisionsIRResponse, + request: DecisionsIRRequest, + requested_model: str, + evidence_fields: frozenset[str] = frozenset(), ) -> OpenAIDecisionResponse: usage: Final = response.usage or DecisionsIRUsage() - return OpenAIDecisionResponse( + formatted: Final = OpenAIDecisionResponse( model=response.model or requested_model, answers=tuple( _openai_answer(question, answer) @@ -327,6 +330,7 @@ def ir_to_openai_response( total_tokens=usage.input_tokens + usage.output_tokens, ), ) + return formatted.model_copy(update={name: response.extra[name] for name in evidence_fields & response.extra.keys()}) class OpenAIDecisionsConfig(BaseDecisionsConfig): diff --git a/litellm/llms/openai/live/handler.py b/litellm/llms/openai/live/handler.py index 297a147a288..5b899ac4162 100644 --- a/litellm/llms/openai/live/handler.py +++ b/litellm/llms/openai/live/handler.py @@ -18,6 +18,7 @@ from litellm._logging import redact_secrets from litellm.constants import ( OPENAI_LIVE_SESSION_CLOSE_TIMEOUT_SECONDS, OPENAI_LIVE_TERMINAL_RESPONSE_EVENT_TYPES, + REALTIME_SESSION_ENDED_ABNORMALLY_KEY, REALTIME_SESSION_SUCCESS_LOGGED_KEY, REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES, ) @@ -316,12 +317,15 @@ async def _forward_live_backend_frames( backend_websocket: LiveBackendWebSocket, client_gone: asyncio.Event, event_retention: _LiveEventRetention, + upstream_ended_abnormally: asyncio.Event, ) -> None: from starlette.websockets import WebSocketDisconnect from websockets.exceptions import ConnectionClosed event_loop: Final = asyncio.get_running_loop() - async for message, close_deadline in _live_backend_messages(websocket, backend_websocket): + async for message, close_deadline in _live_backend_messages( + websocket, backend_websocket, upstream_ended_abnormally + ): if (event := _metering_event(message)) is not None: event_retention.retain(event) if client_gone.is_set(): @@ -341,6 +345,7 @@ async def _forward_live_backend_frames( async def _live_backend_messages( websocket: LiveClientWebSocket, backend_websocket: LiveBackendWebSocket, + upstream_ended_abnormally: asyncio.Event, ) -> AsyncIterator[tuple[str, float | None]]: from starlette.websockets import WebSocketDisconnect from websockets.exceptions import ConnectionClosed @@ -350,6 +355,8 @@ async def _live_backend_messages( yield message, None except ConnectionClosed as error: upstream_close: Final = backend_close_from(error) + if not upstream_close.ended_cleanly: + upstream_ended_abnormally.set() with suppress(WebSocketDisconnect, RuntimeError, ConnectionClosed, OSError): await websocket.close(code=upstream_close.code, reason=upstream_close.reason) return @@ -434,6 +441,7 @@ class OpenAILiveSessions(OpenAIRealtime): "complete_input_dict": {"session_start": rewritten_start}, } event_retention: Final = _LiveEventRetention() + session_ended_abnormally: Final = asyncio.Event() try: logging_obj.pre_call(input=None, api_key=api_key, additional_args=pre_call_args) async with self._websocket_connector( @@ -448,7 +456,11 @@ class OpenAILiveSessions(OpenAIRealtime): websocket=websocket, backend_websocket=backend_websocket, event_retention=event_retention, + upstream_ended_abnormally=session_ended_abnormally, ) + except Exception: + session_ended_abnormally.set() + raise finally: session_end_time: Final = self._clock() retained_events: Final = event_retention.results() @@ -463,6 +475,10 @@ class OpenAILiveSessions(OpenAIRealtime): logging_obj.model_call_details[ # rebind-ok: flags the shared logging object as already logged REALTIME_SESSION_SUCCESS_LOGGED_KEY ] = True + if session_ended_abnormally.is_set(): + logging_obj.model_call_details[ # rebind-ok: flags the shared logging object for the router + REALTIME_SESSION_ENDED_ABNORMALLY_KEY + ] = True except InvalidStatus as error: await close_after_upstream_handshake_refusal(websocket, error.response.status_code) except Exception as error: # noqa: BLE001 # any relay failure must still close the client socket with a redacted reason @@ -484,6 +500,7 @@ class OpenAILiveSessions(OpenAIRealtime): websocket: LiveClientWebSocket, backend_websocket: LiveBackendWebSocket, event_retention: _LiveEventRetention, + upstream_ended_abnormally: asyncio.Event, ) -> None: from websockets.exceptions import ConnectionClosed @@ -503,6 +520,7 @@ class OpenAILiveSessions(OpenAIRealtime): backend_websocket=backend_websocket, client_gone=client_gone, event_retention=event_retention, + upstream_ended_abnormally=upstream_ended_abnormally, ) ) client_gone_task: Final = asyncio.create_task(client_gone.wait()) diff --git a/litellm/llms/openai/openai.py b/litellm/llms/openai/openai.py index 6e22ef9112e..87c944a642a 100644 --- a/litellm/llms/openai/openai.py +++ b/litellm/llms/openai/openai.py @@ -30,6 +30,10 @@ from litellm._logging import verbose_logger from litellm.constants import DEFAULT_MAX_RETRIES from litellm.exceptions import UnsupportedParamsError from litellm.files.types import FileContentStreamingResult +from litellm.litellm_core_utils.chat_completion_agentic_loop import ( + bill_first_round_on_failure, + run_chat_completion_agentic_hooks, +) from litellm.litellm_core_utils.core_helpers import set_provider_response_headers_in_hidden_params from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.logging_utils import speech_request_body, track_llm_api_timing @@ -663,67 +667,23 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM): Returns the response from agentic loop, or None if no hook runs. """ - from litellm._logging import verbose_logger - from litellm.integrations.custom_logger import CustomLogger - - callbacks: Final = litellm.callbacks + (logging_obj.dynamic_success_callbacks or []) - # Avoid logging full callback objects to prevent leaking sensitive data - verbose_logger.debug("LiteLLM.AgenticHooks: callbacks_count=%s", len(callbacks)) - tools: Final = optional_params.get("tools", []) - # Avoid logging full tools payloads; they may contain sensitive parameters - verbose_logger.debug( - "LiteLLM.AgenticHooks: tools_count=%s", - len(tools) if isinstance(tools, list) else 1 if tools else 0, + if not isinstance(response, ModelResponse): + return None + return await bill_first_round_on_failure( + run_chat_completion_agentic_hooks( + response=response, + model=model, + messages=messages, + optional_params=optional_params, + kwargs=litellm_params or {}, + logging_obj=logging_obj, + custom_llm_provider=litellm_params.get("custom_llm_provider", "openai"), + stream=stream, + ), + logging_obj=logging_obj, + response=response, + stream=stream, ) - # Get custom_llm_provider from litellm_params - custom_llm_provider: Final = litellm_params.get("custom_llm_provider", "openai") - - for callback in callbacks: - try: - if isinstance(callback, CustomLogger): - # Check if the callback has the chat completion agentic loop methods - if not hasattr(callback, "async_should_run_chat_completion_agentic_loop"): - continue - - # First: Check if agentic loop should run (using chat completion method) - ( - should_run, - tool_calls, - ) = await callback.async_should_run_chat_completion_agentic_loop( - response=response, - model=model, - messages=messages, - tools=tools, - stream=stream, - custom_llm_provider=custom_llm_provider, - kwargs=litellm_params, - ) - - if should_run: - # Second: Execute agentic loop - kwargs_with_provider = litellm_params.copy() if litellm_params else {} - kwargs_with_provider["custom_llm_provider"] = custom_llm_provider - - # For OpenAI Chat Completions, use the chat completion agentic loop method - agentic_response: object = await callback.async_run_chat_completion_agentic_loop( - tools=tool_calls, - model=model, - messages=messages, - response=response, - optional_params=optional_params, - logging_obj=logging_obj, - stream=stream, - kwargs=kwargs_with_provider, - ) - # First hook that runs agentic loop wins - return agentic_response - - except Exception as e: - verbose_logger.exception( - "LiteLLM.AgenticHookError: Exception in agentic completion hooks for OpenAI: %s", e - ) - - return None def mock_streaming( self, @@ -1074,8 +1034,28 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM): hidden_params={"headers": headers}, _response_headers=headers, ) + except openai.UnprocessableEntityError as e: + if litellm.drop_params is True or drop_params is True: + data = drop_params_from_unprocessable_entity_error(e, data, model=model, drop_params_gated=True) + else: + raise e + except Exception as e: + exception_response: object = getattr(e, "response", None) + status_code = getattr(e, "status_code", 500) + exception_body = getattr(e, "body", None) + error_headers = getattr(e, "headers", None) + if error_headers is None and exception_response: + error_headers = getattr(exception_response, "headers", None) + message = getattr(e, "message", str(e)) - # Call agentic completion hooks (e.g., for websearch_interception) + raise OpenAIError( + status_code=status_code, + message=message, + response=upstream_error_response(e), + headers=error_headers, + body=exception_body, + ) + else: agentic_response = await self._call_agentic_completion_hooks_openai( response=final_response_obj, model=model, @@ -1098,29 +1078,6 @@ class OpenAIChatCompletion(BaseLLM, BaseOpenAILLM): ) return final_response_obj - except openai.UnprocessableEntityError as e: - ## check if body contains unprocessable params - related issue https://github.com/BerriAI/litellm/issues/4800 - if litellm.drop_params is True or drop_params is True: - data = drop_params_from_unprocessable_entity_error(e, data, model=model, drop_params_gated=True) - else: - raise e - # e.message - except Exception as e: - exception_response: object = getattr(e, "response", None) - status_code = getattr(e, "status_code", 500) - exception_body = getattr(e, "body", None) - error_headers = getattr(e, "headers", None) - if error_headers is None and exception_response: - error_headers = getattr(exception_response, "headers", None) - message = getattr(e, "message", str(e)) - - raise OpenAIError( - status_code=status_code, - message=message, - response=upstream_error_response(e), - headers=error_headers, - body=exception_body, - ) def streaming( self, diff --git a/litellm/llms/openai/realtime/handler.py b/litellm/llms/openai/realtime/handler.py index 5be488f0f6e..40ead28d952 100644 --- a/litellm/llms/openai/realtime/handler.py +++ b/litellm/llms/openai/realtime/handler.py @@ -141,7 +141,7 @@ class OpenAIRealtime(OpenAIChatCompletion): return ssl_config - def _construct_url(self, api_base: str, query_params: RealtimeQueryParams) -> str: + def _construct_url(self, api_base: str, query_params: RealtimeQueryParams, realtime_mode: str = "realtime") -> str: """ Construct the backend websocket URL with the client's query parameters. @@ -158,7 +158,8 @@ class OpenAIRealtime(OpenAIChatCompletion): api_base = api_base.replace("http://", "ws://") url = URL(api_base) # Set the correct path - url = url.copy_with(path="/v1/realtime") + path: Final = "/v1/realtime/translations" if realtime_mode == "translation" else "/v1/realtime" + url = url.copy_with(path=path) upstream_params: Final = tuple( (key, value) for key, value in query_params.items() if not (drops_model and key == "model") ) @@ -197,6 +198,8 @@ class OpenAIRealtime(OpenAIChatCompletion): query_params: RealtimeQueryParams | None = None, user_api_key_dict: object | None = None, litellm_metadata: dict | None = None, + realtime_mode: str = "realtime", + drop_params: bool = False, **kwargs: object, ): import websockets @@ -210,13 +213,15 @@ class OpenAIRealtime(OpenAIChatCompletion): # Use all query params if provided, else fallback to just model if query_params is None: query_params = {"model": model} - url: Final = self._construct_url(api_base, query_params) + url: Final = self._construct_url(api_base, query_params, realtime_mode=realtime_mode) try: # Get provider-specific SSL configuration ssl_config: Final = self._get_ssl_config(url) - openai_beta_realtime: Final = client_sent_openai_beta_realtime_header(websocket) + openai_beta_realtime: Final = realtime_mode != "translation" and client_sent_openai_beta_realtime_header( + websocket + ) if not openai_beta_realtime: verbose_logger.debug( "OpenAI Realtime: connecting with GA protocol (no OpenAI-Beta header). " @@ -253,6 +258,8 @@ class OpenAIRealtime(OpenAIChatCompletion): ), event_normalizer=self._make_event_normalizer(), usage_meter=self._make_usage_meter(), + translation_session=realtime_mode == "translation", + drop_params=drop_params, ) await realtime_streaming.bidirectional_forward() diff --git a/litellm/llms/openai/realtime/http_transformation.py b/litellm/llms/openai/realtime/http_transformation.py index 49d33582c6f..ab32ae6085e 100644 --- a/litellm/llms/openai/realtime/http_transformation.py +++ b/litellm/llms/openai/realtime/http_transformation.py @@ -28,6 +28,18 @@ class OpenAIRealtimeHTTPConfig(BaseRealtimeHTTPConfig): base = base.removesuffix("/v1") return join_api_base(base, "v1/realtime/transcription_sessions") + def get_translation_client_secret_url( + self, api_base: str | None, model: str, api_version: str | None = None + ) -> str: + base = self.get_api_base(api_base).rstrip("/") + base = base.removesuffix("/v1") + return f"{base}/v1/realtime/translations/client_secrets" + + def get_translation_calls_url(self, api_base: str | None, model: str, api_version: str | None = None) -> str: + base = self.get_api_base(api_base).rstrip("/") + base = base.removesuffix("/v1") + return f"{base}/v1/realtime/translations/calls" + def validate_environment( self, headers: dict, diff --git a/litellm/llms/openai/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py index a905bff3521..a18cbe13925 100644 --- a/litellm/llms/openai/responses/guardrail_translation/handler.py +++ b/litellm/llms/openai/responses/guardrail_translation/handler.py @@ -1988,7 +1988,7 @@ class OpenAIResponsesHandler(BaseTranslation): "annotations": (), "logprobs": None, } - return ( + events: Final = ( *_open_item_closing_events(responses_so_far), OutputItemAddedEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, @@ -2033,6 +2033,10 @@ class OpenAIResponsesHandler(BaseTranslation): response=_blocked_response(exc, response_id=response_id, model=model, output_item=item), ), ) + return tuple( + event.model_copy(update={"sequence_number": number}) + for number, event in enumerate(events, start=_next_stream_sequence_number(responses_so_far)) + ) class _BlockedContentPart(TypedDict): diff --git a/litellm/llms/openai/responses/transformation.py b/litellm/llms/openai/responses/transformation.py index 7cca31c5d3f..3cb798b7318 100644 --- a/litellm/llms/openai/responses/transformation.py +++ b/litellm/llms/openai/responses/transformation.py @@ -1,5 +1,5 @@ from collections.abc import Callable, Collection, Iterable, Mapping, Sequence -from functools import lru_cache +from functools import lru_cache, partial from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Protocol, cast, get_type_hints @@ -12,10 +12,11 @@ import litellm from litellm._logging import verbose_logger from litellm.integrations.anthropic_cache_control_hook import ( AnthropicCacheControlHook, - openai_prompt_cache_breakpoint_support, + deployment_model_info, + deployment_prompt_cache_breakpoint_support, targets_openai_api, ) -from litellm.litellm_core_utils.core_helpers import normalize_drop_params, process_response_headers +from litellm.litellm_core_utils.core_helpers import as_str_mapping, normalize_drop_params, process_response_headers from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response import ( safe_convert_created_field, @@ -25,6 +26,7 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import ( drop_non_python_regex_patterns, flatten_combinators_and_drop_non_python_regex_patterns, prompt_cache_breakpoint_for_wire, + whole_prompt_cache_breakpoint_or_none, with_prompt_cache_breakpoint, ) from litellm.litellm_core_utils.safe_json_loads import safe_json_loads @@ -44,6 +46,7 @@ from litellm.responses.litellm_completion_transformation.tool_search import ( tools_with_anthropic_tool_search_mapped, tools_without_anthropic_tool_search, ) +from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.secret_managers.main import get_secret_str from litellm.types.llms.base import LiteLLMBaseModel from litellm.types.llms.openai import * @@ -103,13 +106,6 @@ _INPUT_ITEM: Final[TypeAdapter[Mapping[str, object]]] = TypeAdapter(Mapping[str, _CONTENT_PARTS: Final[TypeAdapter[Sequence[Mapping[str, object]]]] = TypeAdapter(Sequence[Mapping[str, object]]) -class _DeclaredModel(BaseModel): - model_config = ConfigDict(frozen=True, extra="ignore", from_attributes=True) - - base_model: object = None - model_info: object = None - - class _DeploymentHost(BaseModel): """`responses()` builds the params from raw kwargs, where callers may spell the host `base_url`.""" @@ -241,12 +237,12 @@ def _json_array_or_empty(value: object) -> Sequence[object]: return value if isinstance(value, (list, tuple)) else () -def _item_with_wire_safe_prompt_cache_breakpoints(item: object, keeps_markers: bool) -> object: +def _item_with_wire_safe_prompt_cache_breakpoints(item: object, to_wire: Callable[[object], object] | None) -> object: fields: Final = _json_object_or_none(item) if fields is None or not _carries_prompt_cache_breakpoint(fields): return item wire_safe_fields: Final = { - key: _parts_with_wire_safe_prompt_cache_breakpoints(key, value, keeps_markers) + key: _parts_with_wire_safe_prompt_cache_breakpoints(key, value, to_wire) for key, value in fields.items() if key != "prompt_cache_breakpoint" } @@ -270,21 +266,23 @@ def _parts_carry_prompt_cache_breakpoint(parts: object) -> bool: return any(isinstance(part, Mapping) and "prompt_cache_breakpoint" in part for part in _json_array_or_empty(parts)) -def _parts_with_wire_safe_prompt_cache_breakpoints(key: str, value: object, keeps_markers: bool) -> object: +def _parts_with_wire_safe_prompt_cache_breakpoints( + key: str, value: object, to_wire: Callable[[object], object] | None +) -> object: if key not in _INPUT_PART_LIST_KEYS or not _parts_carry_prompt_cache_breakpoint(value): return value parts: Final = _json_array_or_empty(value) - wire_safe_parts: Final = tuple(_part_with_wire_safe_prompt_cache_breakpoint(part, keeps_markers) for part in parts) + wire_safe_parts: Final = tuple(_part_with_wire_safe_prompt_cache_breakpoint(part, to_wire) for part in parts) return value if _same_objects(wire_safe_parts, parts) else list(wire_safe_parts) -def _part_with_wire_safe_prompt_cache_breakpoint(part: object, keeps_markers: bool) -> object: +def _part_with_wire_safe_prompt_cache_breakpoint(part: object, to_wire: Callable[[object], object] | None) -> object: fields: Final = _json_object_or_none(part) if fields is None or "prompt_cache_breakpoint" not in fields: return part marker: Final = fields["prompt_cache_breakpoint"] - wire_marker: Final = prompt_cache_breakpoint_for_wire(marker, drop_params=True) if keeps_markers else None - if keeps_markers and wire_marker == marker: + wire_marker: Final = None if to_wire is None else to_wire(marker) + if to_wire is not None and wire_marker == marker: return part unmarked: Final = {key: value for key, value in fields.items() if key != "prompt_cache_breakpoint"} return with_prompt_cache_breakpoint(unmarked, wire_marker) @@ -623,11 +621,45 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): "model": model, "input": replay_safe_input, **response_api_optional_request_params, + **self._prompt_cache_options_with_original_comparison_id(request_params), }, ) return final_request_params + def transform_extra_body( + self, + extra_body: Mapping[str, object], + request: Mapping[str, object], + model: str, + litellm_params: GenericLiteLLMParams, + ) -> Mapping[str, object]: + return {**extra_body, **self._prompt_cache_options_with_original_comparison_id(extra_body)} + + def _prompt_cache_options_with_original_comparison_id(self, params: Mapping[str, object]) -> Mapping[str, object]: + options: Final = as_str_mapping(params.get("prompt_cache_options")) + comparison_response_id: Final = None if options is None else options.get("comparison_response_id") + if ( + self.custom_llm_provider != LlmProviders.OPENAI + or options is None + or not isinstance(comparison_response_id, str) + or not comparison_response_id.startswith("resp_") + ): + return {} + decoded_id: Final = ResponsesAPIRequestUtils.decode_responses_api_response_id(comparison_response_id) + decoded_provider: Final = decoded_id.get("custom_llm_provider") + original_response_id: Final = decoded_id.get("response_id", comparison_response_id) + rebuilt_envelope: Final = ResponsesAPIRequestUtils.update_responses_api_response_id_with_model_id( + {"id": original_response_id}, decoded_provider, {"model_info": {"id": decoded_id.get("model_id")}} + ) + if ( + decoded_provider != LlmProviders.OPENAI + or original_response_id == comparison_response_id + or rebuilt_envelope.get("id") != comparison_response_id + ): + return {} + return {"prompt_cache_options": {**options, "comparison_response_id": original_response_id}} + def _prepared_input_and_tools( self, model: str, @@ -637,7 +669,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): prompt_cache_options: object = None, ) -> tuple[str | ResponseInputParam, Sequence[ALL_RESPONSES_API_TOOL_PARAMS] | None]: validated_input: Final = self._validate_input_param( - self._drop_bridge_minted_reasoning_items(input), drops_set_created_by=drops_params(litellm_params) + self._drop_bridge_minted_reasoning_items(input), drop_params=drops_params(litellm_params) ) reads_breakpoints: Final = self._reads_prompt_cache_breakpoints( model=model, litellm_params=litellm_params, prompt_cache_options=prompt_cache_options @@ -681,24 +713,31 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): ) -> str | ResponseInputParam: if not isinstance(input, list) or not drops_params(litellm_params): return input - keeps_markers: Final = reads_breakpoints or self._keeps_prompt_cache_breakpoints( - model=model, litellm_params=litellm_params - ) - wire_safe_items: Final = tuple( - _item_with_wire_safe_prompt_cache_breakpoints(item, keeps_markers) for item in input + known_support: Final = self._prompt_cache_breakpoint_support(model=model, litellm_params=litellm_params) + to_wire: Final = ( + self._prompt_cache_breakpoint_to_wire(litellm_params, reads_breakpoints, known_support) + if reads_breakpoints or known_support is not False + else None ) + wire_safe_items: Final = tuple(_item_with_wire_safe_prompt_cache_breakpoints(item, to_wire) for item in input) if _same_objects(wire_safe_items, input): return input wire_safe_input: Final = list(wire_safe_items) return cast("ResponseInputParam", wire_safe_input) # cast-ok: items keep their shape, minus a rejected marker - def _keeps_prompt_cache_breakpoints(self, model: str, litellm_params: GenericLiteLLMParams) -> bool: - provider: Final = _provider_name(self.custom_llm_provider) - base_model: Final = self._declared_base_model(model=model, litellm_params=litellm_params) - known_support: Final = ( - openai_prompt_cache_breakpoint_support(name, provider) for name in dict.fromkeys((base_model, model)) + def _prompt_cache_breakpoint_to_wire( + self, litellm_params: GenericLiteLLMParams, reads_breakpoints: bool, known_support: bool | None + ) -> Callable[[object], object]: + opted_in_openai_host: Final = reads_breakpoints and self.custom_llm_provider == LlmProviders.OPENAI + known_openai_reader: Final = known_support is True and self._targets_openai_api(litellm_params) + if opted_in_openai_host or known_openai_reader: + return partial(prompt_cache_breakpoint_for_wire, drop_params=True) + return whole_prompt_cache_breakpoint_or_none + + def _prompt_cache_breakpoint_support(self, model: str, litellm_params: GenericLiteLLMParams) -> bool | None: + return deployment_prompt_cache_breakpoint_support( + model, _provider_name(self.custom_llm_provider), litellm_params ) - return next((support for support in known_support if support is not None), None) is not False def _targets_openai_api(self, litellm_params: GenericLiteLLMParams) -> bool: host: Final = _DeploymentHost.model_validate(litellm_params) @@ -729,6 +768,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): custom_llm_provider=_provider_name(self.custom_llm_provider), api_base=host.api_base or host.base_url, prompt_cache_options=prompt_cache_options, + model_info=deployment_model_info(litellm_params), ) @staticmethod @@ -872,13 +912,6 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): base_model: Final[object] = model_info.get("base_model") if isinstance(model_info, dict) else None return base_model if isinstance(base_model, str) and base_model else model - @staticmethod - def _declared_base_model(model: str, litellm_params: GenericLiteLLMParams) -> str: - declared: Final = _DeclaredModel.model_validate(litellm_params) - model_info: Final = _json_object_or_none(declared.model_info) - candidates: Final = (declared.base_model, None if model_info is None else model_info.get("base_model")) - return next((name for name in candidates if isinstance(name, str) and name), model) - @staticmethod def _sanitized_tool_entry( entry: Mapping[str, object], @@ -918,7 +951,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): return tools if all(new is old for new, old in zip(sanitized, tools, strict=True)) else sanitized def _validate_input_param( - self, input: str | ResponseInputParam, *, drops_set_created_by: bool = False + self, input: str | ResponseInputParam, *, drop_params: bool = False ) -> str | ResponseInputParam: """ Ensure all input fields if pydantic are converted to dict @@ -932,9 +965,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): # if it's pydantic, convert to dict if isinstance(item, BaseModel): validated_input.append( - replayable_responses_item( - item.model_dump(exclude_none=True), drops_set_created_by=drops_set_created_by - ) + replayable_responses_item(item.model_dump(exclude_none=True), drops_set_created_by=drop_params) ) elif isinstance(item, dict): validated_input.append( @@ -942,7 +973,7 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig): self._handle_reasoning_item(cast(dict[str, object], item)) if item.get("type") == "reasoning" else item, - drops_set_created_by=drops_set_created_by, + drops_set_created_by=drop_params, ) ) else: diff --git a/litellm/llms/openai/transcriptions/gpt_transformation.py b/litellm/llms/openai/transcriptions/gpt_transformation.py index e7f8dd04516..b9eaa204567 100644 --- a/litellm/llms/openai/transcriptions/gpt_transformation.py +++ b/litellm/llms/openai/transcriptions/gpt_transformation.py @@ -26,8 +26,8 @@ class OpenAIGPTAudioTranscriptionConfig(OpenAIWhisperAudioTranscriptionConfig): self, model: str, audio_file: FileTypes, - optional_params: dict, - litellm_params: dict, + optional_params: dict[str, object], + litellm_params: dict[str, object], ) -> AudioTranscriptionRequestData: """ Transform the audio transcription request @@ -37,3 +37,14 @@ class OpenAIGPTAudioTranscriptionConfig(OpenAIWhisperAudioTranscriptionConfig): return AudioTranscriptionRequestData( data=data, ) + + +class OpenAIGPTTranscribeAudioTranscriptionConfig(OpenAIGPTAudioTranscriptionConfig): + def get_supported_openai_params(self, model: str) -> list[OpenAIAudioTranscriptionOptionalParams]: + return [ + "prompt", + "response_format", + "keywords", + "languages", + "stream", + ] diff --git a/litellm/llms/openai/transcriptions/handler.py b/litellm/llms/openai/transcriptions/handler.py index 48a44575989..23c5e70a3cc 100644 --- a/litellm/llms/openai/transcriptions/handler.py +++ b/litellm/llms/openai/transcriptions/handler.py @@ -1,8 +1,9 @@ -from collections.abc import Mapping +from collections.abc import Coroutine, Mapping from typing import TYPE_CHECKING, Final, Optional, cast import httpx -from openai import AsyncOpenAI, OpenAI +from openai import AsyncOpenAI, AsyncStream, OpenAI, Stream +from openai.types.audio import TranscriptionStreamEvent from pydantic import BaseModel if TYPE_CHECKING: @@ -12,6 +13,9 @@ from litellm.litellm_core_utils.core_helpers import set_provider_response_header from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.llms.base_llm.audio_transcription.transformation import ( BaseAudioTranscriptionConfig, + acreate_sdk_transcription, + create_sdk_transcription, + sdk_compatible_transcription_request_data, ) from litellm.types.utils import FileTypes from litellm.utils import ( @@ -28,31 +32,18 @@ class OpenAIAudioTranscription(OpenAIChatCompletion): async def make_openai_audio_transcriptions_request( self, openai_aclient: AsyncOpenAI, - data: dict, + data: Mapping[str, object], timeout: float | httpx.Timeout, ): - try: - raw_response = await openai_aclient.audio.transcriptions.with_raw_response.create(**data, timeout=timeout) - headers: Final = dict(raw_response.headers) - response: Final = raw_response.parse() - - return headers, response - except Exception as e: - raise e + return await acreate_sdk_transcription(openai_aclient, sdk_compatible_transcription_request_data(data), timeout) def make_sync_openai_audio_transcriptions_request( self, openai_client: OpenAI, - data: dict, + data: Mapping[str, object], timeout: float | httpx.Timeout, ): - try: - raw_response: Final = openai_client.audio.transcriptions.with_raw_response.create(**data, timeout=timeout) - headers: Final = dict(raw_response.headers) - response: Final = raw_response.parse() - return headers, response - except Exception as e: - raise e + return create_sdk_transcription(openai_client, sdk_compatible_transcription_request_data(data), timeout) def audio_transcriptions( self, @@ -70,7 +61,11 @@ class OpenAIAudioTranscription(OpenAIChatCompletion): atranscription: bool = False, provider_config: BaseAudioTranscriptionConfig | None = None, shared_session: Optional["ClientSession"] = None, - ) -> TranscriptionResponse: + ) -> ( + TranscriptionResponse + | Stream[TranscriptionStreamEvent] + | Coroutine[object, object, TranscriptionResponse | AsyncStream[TranscriptionStreamEvent]] + ): """ Handle audio transcription request """ @@ -128,6 +123,9 @@ class OpenAIAudioTranscription(OpenAIChatCompletion): ) logging_obj.model_call_details["response_headers"] = headers + if isinstance(response, Stream): + return response + if isinstance(response, BaseModel): stringified_response = response.model_dump() else: @@ -153,7 +151,7 @@ class OpenAIAudioTranscription(OpenAIChatCompletion): async def async_audio_transcriptions( self, audio_file: FileTypes, - data: dict, + data: Mapping[str, object], model_response: TranscriptionResponse, timeout: float, logging_obj: LiteLLMLoggingObj, @@ -192,6 +190,8 @@ class OpenAIAudioTranscription(OpenAIChatCompletion): timeout=timeout, ) logging_obj.model_call_details["response_headers"] = headers + if isinstance(response, AsyncStream): + return response if isinstance(response, BaseModel): stringified_response = response.model_dump() else: diff --git a/litellm/llms/openai_like/dynamic_config.py b/litellm/llms/openai_like/dynamic_config.py index d7aafe9f06e..66b41967ca7 100644 --- a/litellm/llms/openai_like/dynamic_config.py +++ b/litellm/llms/openai_like/dynamic_config.py @@ -2,9 +2,11 @@ Dynamic configuration class generator for JSON-based providers. """ -from collections.abc import Coroutine +from collections.abc import Coroutine, Mapping from typing import TYPE_CHECKING, Final, Literal, overload +from pydantic import TypeAdapter, ValidationError + from litellm._logging import verbose_logger from litellm.litellm_core_utils.prompt_templates.common_utils import ( handle_messages_with_content_list_to_str_conversion, @@ -20,6 +22,26 @@ from .json_loader import SimpleProviderConfig if TYPE_CHECKING: from litellm.llms.openai_like.responses.transformation import OpenAILikeResponsesConfig +_PAID_SEARCH_TOOLS: Final = frozenset({"web_search", "web_search_image", "image_search"}) +_PAYLOAD_ADAPTER: Final[TypeAdapter[Mapping[str, object]]] = TypeAdapter(Mapping[str, object]) +_TOOL_USAGE_ADAPTER: Final[TypeAdapter[Mapping[str, int]]] = TypeAdapter(Mapping[str, int]) + + +def web_search_requests_from_tool_usage(payload: object) -> int | None: + """ + Billable search calls in a parsed OpenAI-compatible chat response whose usage carries a + tool_usage {tool_name: count} map, as EmpirioLabs reports built-in tool invocations. + Free tools (code_interpreter, web_extractor) are not counted. + """ + try: + body: Final = _PAYLOAD_ADAPTER.validate_python(payload) + usage: Final = _PAYLOAD_ADAPTER.validate_python(body.get("usage")) + tool_usage: Final = _TOOL_USAGE_ADAPTER.validate_python(usage.get("tool_usage"), strict=True) + except ValidationError: + return None + calls: Final = sum(count for tool, count in tool_usage.items() if tool in _PAID_SEARCH_TOOLS and count > 0) + return calls if calls > 0 else None + def create_config_class(provider: SimpleProviderConfig): """Generate config class dynamically from JSON configuration""" @@ -179,6 +201,25 @@ def create_config_class(provider: SimpleProviderConfig): return optional_params + def transform_parsed_response_dict( + self, + parsed_response: dict[str, object], # mutable-ok: BaseConfig signature + ) -> dict[str, object]: # mutable-ok: BaseConfig signature + """ + Carry the provider's usage.tool_usage search count as usage.server_tool_use.web_search_requests, + the field the built-in tool cost path bills per call. + """ + repaired: Final = _PAYLOAD_ADAPTER.validate_python( + super().transform_parsed_response_dict(parsed_response) # pyright: ignore[reportUnknownMemberType] # base_class is picked at runtime + ) + if not provider.special_handling.get("web_search_requests_from_tool_usage"): + return {**repaired} + web_search_requests: Final = web_search_requests_from_tool_usage(repaired) + if web_search_requests is None: + return {**repaired} + usage: Final = _PAYLOAD_ADAPTER.validate_python(repaired["usage"]) + return {**repaired, "usage": {**usage, "server_tool_use": {"web_search_requests": web_search_requests}}} + @property def custom_llm_provider(self) -> str | None: return provider.slug diff --git a/litellm/llms/openai_like/providers.json b/litellm/llms/openai_like/providers.json index a71a9c3bb9b..f937e4d2f75 100644 --- a/litellm/llms/openai_like/providers.json +++ b/litellm/llms/openai_like/providers.json @@ -178,7 +178,10 @@ "param_mappings": { "max_completion_tokens": "max_tokens" }, - "supported_endpoints": ["/v1/chat/completions", "/v1/responses"] + "special_handling": { + "web_search_requests_from_tool_usage": true + }, + "supported_endpoints": ["/v1/chat/completions", "/v1/responses", "/v1/embeddings"] }, "meta": { "base_url": "https://api.meta.ai/v1", @@ -302,5 +305,14 @@ "preserve_cache_control": true }, "supported_endpoints": ["/v1/chat/completions"] + }, + "wally": { + "base_url": "https://inference.runanywhere.ai/v1", + "api_key_env": "WALLY_API_KEY", + "api_base_env": "WALLY_API_BASE", + "provider_info": { + "supports_function_calling": true, + "supports_reasoning": true + } } } diff --git a/litellm/llms/opencode/chat/transformation.py b/litellm/llms/opencode/chat/transformation.py index dcb30b5835c..c6d288b6d84 100644 --- a/litellm/llms/opencode/chat/transformation.py +++ b/litellm/llms/opencode/chat/transformation.py @@ -1,5 +1,5 @@ from collections.abc import AsyncIterator, Iterator, Mapping, Sequence -from typing import TYPE_CHECKING, Final +from typing import TYPE_CHECKING, ClassVar, Final import httpx from pydantic import TypeAdapter @@ -112,6 +112,9 @@ class OpenCodeGoMessagesChatConfig(_GoReportedCostMixin, AnthropicConfig): def custom_llm_provider(self) -> str: return "opencode_go" + def translates_prompt_cache_breakpoint(self, model: str) -> bool: + return "claude" in model.lower() + def get_complete_url( self, api_base: str | None, @@ -159,6 +162,7 @@ class OpenCodeGoMessagesChatConfig(_GoReportedCostMixin, AnthropicConfig): class OpenCodeGoGeminiChatConfig(_GoReportedCostMixin, GoogleAIStudioGeminiConfig): go_usage_key: str = "usageMetadata" + _route: ClassVar[str] = "opencode_go" @property def supports_stream_param_in_request_body(self) -> bool: diff --git a/litellm/llms/opencode/transformation.py b/litellm/llms/opencode/transformation.py deleted file mode 100644 index 9b62e7aca95..00000000000 --- a/litellm/llms/opencode/transformation.py +++ /dev/null @@ -1,6 +0,0 @@ -from litellm.llms.opencode.common_utils import is_opencode_api_base - - -class OpenCodeProviderAdapter: - def get_provider_affinity_header(self, api_base: str | None) -> str | None: - return "x-opencode-session" if is_opencode_api_base(api_base) else None diff --git a/tests/test_litellm_rust/cache/v2/__init__.py b/litellm/llms/parallel_ai/decisions/__init__.py similarity index 100% rename from tests/test_litellm_rust/cache/v2/__init__.py rename to litellm/llms/parallel_ai/decisions/__init__.py diff --git a/litellm/llms/parallel_ai/decisions/transformation.py b/litellm/llms/parallel_ai/decisions/transformation.py new file mode 100644 index 00000000000..34d03047301 --- /dev/null +++ b/litellm/llms/parallel_ai/decisions/transformation.py @@ -0,0 +1,89 @@ +from collections.abc import Mapping +from typing import Final + +import httpx +from pydantic import BaseModel, ConfigDict + +from litellm.llms.base_llm.decisions.transformation import BaseDecisionsConfig, ir_to_systemone_request +from litellm.types.decisions import ( + DecisionsIRRequest, + DecisionsIRResponse, + UnsupportedDecisionsRequest, +) + + +class _ParallelResponse(BaseModel): + model_config = ConfigDict(extra="allow", frozen=True) + + mode: str + answers: Mapping[str, Mapping[str, object]] + + +class ParallelAIDecisionsConfig(BaseDecisionsConfig): + path = "/v1/decisions" + api_key_env = ("PARALLEL_AI_API_KEY", "PARALLEL_API_KEY") + api_base_env = ("PARALLEL_AI_API_BASE",) + confidence_optional = True + openai_evidence_fields = frozenset({"citations", "decision_id", "mode"}) + + def get_default_api_base(self) -> str: + return "https://api.parallel.ai" + + def resolve_connection(self, api_base: str | None, api_key: str | None) -> tuple[str | None, str | None]: + configured_base: Final = self.resolve_api_base(None) + resolved_base: Final = api_base or configured_base + destination: Final = self._decisions_url(resolved_base) + if api_key: + return resolved_base, api_key + if destination not in {self._decisions_url(None), self._decisions_url(configured_base)}: + raise ValueError( + "Parallel Decisions requires an explicit api_key for a custom api_base unless " + "the destination is configured in PARALLEL_AI_API_BASE" + ) + return resolved_base, self.resolve_api_key(None) + + def get_complete_url(self, api_base: str, model: str) -> str: + return super().get_complete_url(api_base.rstrip("/").removesuffix("/v1/search").removesuffix(self.path), model) + + def _decisions_url(self, api_base: str | None) -> httpx.URL: + return httpx.URL(self.get_complete_url(api_base or self.get_default_api_base(), "decision")) + + def validate_environment( + self, + headers: Mapping[str, str], + model: str, + api_key: str | None, + litellm_params: Mapping[str, object], + ) -> Mapping[str, str]: + return { + **{ + name: value + for name, value in headers.items() + if name.lower() not in {"authorization", "x-api-key", "content-type"} + }, + **({"x-api-key": api_key} if api_key is not None else {}), + "Content-Type": "application/json", + } + + def transform_decisions_request( + self, model: str, request: DecisionsIRRequest, custom_llm_provider: str + ) -> Mapping[str, object] | UnsupportedDecisionsRequest: + if model != "decision": + return UnsupportedDecisionsRequest(reason="Parallel Decisions supports the decision model") + if len(request.questions) > 100: + return UnsupportedDecisionsRequest(reason="Parallel Decisions supports at most 100 questions") + body: Final = ir_to_systemone_request(model, request) + if isinstance(body, UnsupportedDecisionsRequest): + return body + return {"mode": "fast", **{key: value for key, value in body.items() if key != "model"}} + + def parse_response(self, payload: object, request: DecisionsIRRequest) -> DecisionsIRResponse: + response: Final = _ParallelResponse.model_validate(payload) + return super().parse_response( + { + **response.model_dump(), + "model": "decision", + "answers": {key: answer for key, answer in response.answers.items() if answer.get("type") != "refusal"}, + }, + request, + ) diff --git a/litellm/llms/perplexity/responses/transformation.py b/litellm/llms/perplexity/responses/transformation.py index afd27b0f696..e5e3744dd80 100644 --- a/litellm/llms/perplexity/responses/transformation.py +++ b/litellm/llms/perplexity/responses/transformation.py @@ -89,7 +89,7 @@ class PerplexityResponsesConfig(OpenAIResponsesAPIConfig): """Handle preset/ model prefix: send as {"preset": name} instead of {"model": name}.""" input = self._ensure_message_type(input) if model.startswith("preset/"): - input = self._validate_input_param(input, drops_set_created_by=drops_params(litellm_params)) + input = self._validate_input_param(input, drop_params=drops_params(litellm_params)) data: Final[dict] = { "preset": model[len("preset/") :], "input": input, diff --git a/litellm/llms/vertex_ai/common_utils.py b/litellm/llms/vertex_ai/common_utils.py index ad64d852ef9..52345e1ff40 100644 --- a/litellm/llms/vertex_ai/common_utils.py +++ b/litellm/llms/vertex_ai/common_utils.py @@ -1458,6 +1458,7 @@ class VertexAITokenCounter(BaseTokenCounter): ) -> TokenCountResponse | None: import copy + from litellm.llms.anthropic.common_utils import context_management_with_edits from litellm.llms.vertex_ai.vertex_ai_partner_models.count_tokens.handler import count_tokens_publisher from litellm.llms.vertex_ai.vertex_ai_partner_models.main import ( VertexAIError as PartnerVertexAIError, @@ -1539,6 +1540,9 @@ class VertexAITokenCounter(BaseTokenCounter): system=system, tools=tools, count_options=count_options, + context_management=( + None if context_management is None else context_management_with_edits(context_management.spec) + ), ) except (PartnerVertexAIError, httpx.HTTPStatusError) as e: status_code: Final = e.response.status_code @@ -1565,12 +1569,15 @@ class VertexAITokenCounter(BaseTokenCounter): original_response=result, ) else: + from litellm.llms.anthropic.messages.context_management.inference_view import ( + InferenceRequestViewError, + count_context_edits, + inference_request_view, + ) from litellm.llms.vertex_ai.count_tokens.context import ( VertexGeminiCountContextError, - count_context_edits, count_context_error_response, gemini_count_contents, - inference_request_view, malformed_tool_result_text_count_error, provider_error_response, unconvertible_messages_error, @@ -1584,7 +1591,7 @@ class VertexAITokenCounter(BaseTokenCounter): messages_format, count_context_edits(context_management, tools, count_tokens_params_request, model_to_use), ) - if isinstance(request_view, VertexGeminiCountContextError): + if isinstance(request_view, InferenceRequestViewError): return count_context_error_response(request_view, request_model, model_to_use) count_context: Final = vertex_gemini_count_context( system=request_view.system, tools=tools, model=model_to_use diff --git a/litellm/llms/vertex_ai/context_caching/rejected_cache_retry.py b/litellm/llms/vertex_ai/context_caching/rejected_cache_retry.py index 43e4ee8dc84..7334fb0520a 100644 --- a/litellm/llms/vertex_ai/context_caching/rejected_cache_retry.py +++ b/litellm/llms/vertex_ai/context_caching/rejected_cache_retry.py @@ -1,4 +1,4 @@ -from collections.abc import Awaitable, Callable +from collections.abc import Awaitable, Callable, Mapping, Sequence from copy import deepcopy from functools import partial from typing import Final, TypeVar @@ -17,16 +17,27 @@ Built: Final = TypeVar("Built") Sent: Final = TypeVar("Sent") -def cache_rebuild( +def _build_from_copies( + build: Callable[..., Built], messages: Sequence[AllMessageValues], optional_params: Mapping[str, object] +) -> Built: + return build(messages=deepcopy(list(messages)), optional_params=independent_snapshot(dict(optional_params))) + + +def cache_rebuilds( build: Callable[..., Built], messages: list[AllMessageValues], optional_params: dict -) -> Callable[[], Built] | None: - """Copies the inputs before the first transform, which pops keys from ``optional_params`` and ``messages``.""" +) -> tuple[Callable[[], Built], Callable[[], Built]] | tuple[None, None]: + """Returns one build with a fresh cache and one with the history inline, both over a snapshot of the inputs + taken before the first transform, which pops keys from ``optional_params`` and ``messages``. Each call + copies the snapshot again, since every transform consumes the inputs it is given.""" if not any(map(is_cached_message, messages)): - return None - return partial(build, messages=deepcopy(messages), optional_params=independent_snapshot(optional_params)) + return None, None + from_snapshot: Final = partial( + _build_from_copies, messages=deepcopy(messages), optional_params=independent_snapshot(optional_params) + ) + return partial(from_snapshot, build), partial(from_snapshot, partial(build, context_caching=False)) -def _status_and_message(error: httpx.HTTPStatusError | BaseLLMException) -> tuple[int, str]: +def status_and_message(error: httpx.HTTPStatusError | BaseLLMException) -> tuple[int, str]: match error: case httpx.HTTPStatusError(): return error.response.status_code, error.response.text @@ -35,7 +46,7 @@ def _status_and_message(error: httpx.HTTPStatusError | BaseLLMException) -> tupl def _cache_rejected(body: RequestBody, error: httpx.HTTPStatusError | BaseLLMException) -> bool: - return body.get("cachedContent") is not None and names_rejected_cache(*_status_and_message(error)) + return body.get("cachedContent") is not None and names_rejected_cache(*status_and_message(error)) async def post_with_fresh_cache_async( diff --git a/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py b/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py index 884c82fe331..4603f612926 100644 --- a/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py +++ b/litellm/llms/vertex_ai/context_caching/vertex_ai_context_caching.py @@ -425,6 +425,7 @@ class ContextCachingEndpoints(VertexBase): vertex_auth_header: str | None, extra_headers: dict | None = None, cached_content: str | None = None, + context_caching: bool = True, ) -> tuple[list[AllMessageValues], dict, str | None]: """ Receives @@ -436,7 +437,7 @@ class ContextCachingEndpoints(VertexBase): Follows - https://ai.google.dev/api/caching#request-body """ - if cached_content is not None: + if cached_content is not None or not context_caching: return messages, optional_params, cached_content cached_messages, non_cached_messages = separate_cached_messages(messages=messages) @@ -573,6 +574,7 @@ class ContextCachingEndpoints(VertexBase): vertex_auth_header: str | None, extra_headers: dict | None = None, cached_content: str | None = None, + context_caching: bool = True, ) -> tuple[list[AllMessageValues], dict, str | None]: """ Receives @@ -584,7 +586,7 @@ class ContextCachingEndpoints(VertexBase): Follows - https://ai.google.dev/api/caching#request-body """ - if cached_content is not None: + if cached_content is not None or not context_caching: return messages, optional_params, cached_content cached_messages, non_cached_messages = separate_cached_messages(messages=messages) diff --git a/litellm/llms/vertex_ai/count_tokens/context.py b/litellm/llms/vertex_ai/count_tokens/context.py index fc7d6545624..c29f2ecbcf8 100644 --- a/litellm/llms/vertex_ai/count_tokens/context.py +++ b/litellm/llms/vertex_ai/count_tokens/context.py @@ -11,10 +11,11 @@ from litellm.litellm_core_utils.prompt_templates.factory import chat_completion_ from litellm.types.llms.anthropic import AnthropicMessagesTextParam from litellm.types.llms.openai import AllMessageValues from litellm.types.llms.vertex_ai import ContentType -from litellm.types.utils import CountContextManagement, TokenCountMessagesFormat, TokenCountResponse +from litellm.types.utils import TokenCountMessagesFormat, TokenCountResponse if TYPE_CHECKING: from litellm.exceptions import APIError + from litellm.llms.anthropic.messages.context_management.inference_view import InferenceRequestViewError @dataclass(frozen=True, slots=True) @@ -152,7 +153,7 @@ def malformed_tool_result_text_count_error( def count_context_error_response( - error: VertexGeminiCountContextError, request_model: str, model_used: str + error: "VertexGeminiCountContextError | InferenceRequestViewError", request_model: str, model_used: str ) -> TokenCountResponse: return TokenCountResponse( total_tokens=0, @@ -178,130 +179,6 @@ def provider_error_response(error: "APIError", request_model: str, model_used: s ) -@dataclass(frozen=True, slots=True) -class InferenceRequestView: - messages: Sequence[Mapping[str, object]] - system: object | None - - -@dataclass(frozen=True, slots=True) -class CountContextEdits: - spec: JsonValue - model: str - tools: tuple[Mapping[str, object], ...] | None - drop_invalid_edits: bool = False - - -_CONTEXT_MANAGEMENT_SPEC: Final[TypeAdapter[Mapping[str, object] | tuple[Mapping[str, object], ...]]] = TypeAdapter( - Mapping[str, object] | tuple[Mapping[str, object], ...] -) - - -def count_context_edits( - context_management: CountContextManagement | None, - tools: Sequence[Mapping[str, object]] | None, - litellm_params: Mapping[str, object], - fallback_model: str, -) -> CountContextEdits: - model: Final = litellm_params.get("model") - return CountContextEdits( - spec=None if context_management is None else context_management.spec, - model=model if isinstance(model, str) else fallback_model, - tools=None if tools is None else tuple(tools), - drop_invalid_edits=context_management is not None and context_management.drop_invalid_edits, - ) - - -def _typed_spec(spec: JsonValue) -> Mapping[str, object] | tuple[Mapping[str, object], ...] | None: - try: - return _CONTEXT_MANAGEMENT_SPEC.validate_python(spec) - except ValidationError: - return None - - -def _typed_system( - system: object | None, -) -> str | tuple[AnthropicMessagesTextParam, ...] | None | VertexGeminiCountContextError: - if system is None or isinstance(system, str): - return system - try: - return _SYSTEM_BLOCKS.validate_python(system) - except ValidationError: - return _INVALID_SYSTEM - - -def _view_without_edits( - messages: Sequence[Mapping[str, object]], - system: object | None, - typed_system: str | Sequence[Mapping[str, object]] | None, -) -> InferenceRequestView: - from litellm.llms.anthropic.messages.context_management.editors.compact import ( - apply_client_compaction_block_history, - ) - - history: Final = apply_client_compaction_block_history( - messages=[dict(message) for message in messages], - system=typed_system - if typed_system is None or isinstance(typed_system, str) - else [dict(block) for block in typed_system], - ) - if history is None: - return InferenceRequestView(messages=messages, system=system) - return InferenceRequestView(messages=history.messages, system=history.system) - - -async def _anthropic_inference_view( - messages: Sequence[Mapping[str, object]], system: object | None, edits: CountContextEdits -) -> InferenceRequestView | VertexGeminiCountContextError: - from litellm.llms.anthropic.messages.adapters.handler import prepare_context_managed_request - from litellm.llms.anthropic.messages.context_management import AnthropicContextManagementError - from litellm.llms.anthropic.messages.native.utils import normalize_native_messages - - typed_system: Final = _typed_system(system) - if isinstance(typed_system, VertexGeminiCountContextError): - return typed_system - normalized: Final = normalize_native_messages(messages) - spec: Final = _typed_spec(edits.spec) - try: - prepared: Final = await prepare_context_managed_request( - model=edits.model, - messages=normalized, - tools=None if edits.tools is None else [dict(tool) for tool in edits.tools], - system=[dict(block) for block in typed_system] if isinstance(typed_system, tuple) else typed_system, - context_management_spec=( - None if spec is None else dict(spec) if isinstance(spec, Mapping) else [dict(edit) for edit in spec] - ), - litellm_metadata=None, - additional_drop_params=None, - llm_router=None, - count_only=True, - drop_invalid_edits=edits.drop_invalid_edits, - ) - except AnthropicContextManagementError as error: - if error.status_code >= 500: - return _view_without_edits(normalized, system, typed_system) - return VertexGeminiCountContextError(error_message=error.message, status_code=error.status_code) - if prepared is None: - return InferenceRequestView(messages=normalized, system=system) - return InferenceRequestView(messages=prepared.messages, system=prepared.system) - - -async def inference_request_view( - messages: Sequence[Mapping[str, object]], - system: object | None, - messages_format: TokenCountMessagesFormat, - edits: CountContextEdits, -) -> InferenceRequestView | VertexGeminiCountContextError: - """Apply the history rewrites and context edits /v1/messages runs before it converts a body for Gemini.""" - match messages_format: - case "openai": - return InferenceRequestView(messages=messages, system=system) - case "anthropic": - return await _anthropic_inference_view(messages, system, edits) - case _: - assert_never(messages_format) - - def _chat_messages( messages: Sequence[Mapping[str, object]], messages_format: TokenCountMessagesFormat, diff --git a/litellm/llms/vertex_ai/gemini/rejected_thought_signature_retry.py b/litellm/llms/vertex_ai/gemini/rejected_thought_signature_retry.py new file mode 100644 index 00000000000..32893471c11 --- /dev/null +++ b/litellm/llms/vertex_ai/gemini/rejected_thought_signature_retry.py @@ -0,0 +1,235 @@ +from collections.abc import Awaitable, Callable, Iterator, Mapping, Sequence +from typing import Final, TypeVar + +import httpx +from pydantic import TypeAdapter, ValidationError + +from litellm import verbose_logger +from litellm.litellm_core_utils.prompt_templates.factory import get_dummy_thought_signature +from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.types.llms.vertex_ai import ContentType, PartType, RequestBody + +from ..context_caching.rejected_cache_retry import status_and_message + +Body: Final = TypeVar("Body", bound=Mapping[str, object]) +Sent: Final = TypeVar("Sent") + +_REJECTED_SIGNATURE_MARKER: Final = "thought signature" +_SIGNATURE_KEYS: Final = frozenset({"thoughtSignature", "thought_signature"}) +_ENTRIES: Final = TypeAdapter(list[dict[str, object]]) + + +def names_rejected_thought_signature(status_code: int, message: str) -> bool: + """A signature only validates on the backend that minted it. AI Studio answers a replayed Vertex signature + with ``400 Corrupted thought signature.`` and Vertex answers an AI Studio one with ``400 Invalid thought + signature.``""" + return status_code == 400 and _REJECTED_SIGNATURE_MARKER in message.lower() + + +def _is_rejected_signature(error: httpx.HTTPStatusError | BaseLLMException) -> bool: + return names_rejected_thought_signature(*status_and_message(error)) + + +def _entries(value: object) -> Sequence[Mapping[str, object]]: + try: + return _ENTRIES.validate_python(value) + except ValidationError: + return [] + + +def _foreign_signatures(body: Mapping[str, object], placeholder: str) -> Iterator[object]: + for content in _entries(body.get("contents")): + for part in _entries(content.get("parts")): + yield from ( + value for key, value in part.items() if key in _SIGNATURE_KEYS and value and value != placeholder + ) + + +def _foreign_signature_count(body: Mapping[str, object]) -> int: + return sum(1 for _ in _foreign_signatures(body, get_dummy_thought_signature())) + + +def _part_with_placeholder(part: PartType, placeholder: str) -> PartType: + if not part.get("thoughtSignature"): + return part + return {**part, "thoughtSignature": placeholder} + + +def _content_with_placeholders(content: ContentType, placeholder: str) -> ContentType: + return {**content, "parts": [_part_with_placeholder(part, placeholder) for part in content["parts"]]} + + +def with_placeholder_thought_signatures(body: RequestBody) -> RequestBody | None: + """Swaps every thought signature in the history for Google's documented skip-validator placeholder, or + returns ``None`` when the body carries nothing the backend could have rejected.""" + placeholder: Final = get_dummy_thought_signature() + if next(_foreign_signatures(body, placeholder), None) is None: + return None + return {**body, "contents": [_content_with_placeholders(content, placeholder) for content in body["contents"]]} + + +def _native_part_with_placeholder(part: Mapping[str, object], placeholder: str) -> Mapping[str, object]: + return {key: placeholder if key in _SIGNATURE_KEYS and value else value for key, value in part.items()} + + +def _native_content_with_placeholders(content: Mapping[str, object], placeholder: str) -> Mapping[str, object]: + parts: Final = _entries(content.get("parts")) + if not parts: + return content + return {**content, "parts": [_native_part_with_placeholder(part, placeholder) for part in parts]} + + +def with_placeholder_native_thought_signatures(body: Mapping[str, object]) -> Mapping[str, object] | None: + """The same swap on a ``generateContent`` body as the client sent it, whose parts may spell the key + ``thoughtSignature`` or ``thought_signature``.""" + placeholder: Final = get_dummy_thought_signature() + if next(_foreign_signatures(body, placeholder), None) is None: + return None + return { + **body, + "contents": [ + _native_content_with_placeholders(content, placeholder) for content in _entries(body.get("contents")) + ], + } + + +async def _inline_history_async(body: Body, uncached: Callable[[], Awaitable[Body]] | None) -> Body | None: + if uncached is None or body.get("cachedContent") is None: + return None + inline: Final = await uncached() + return inline if _foreign_signature_count(inline) > _foreign_signature_count(body) else None + + +def _inline_history_sync(body: Body, uncached: Callable[[], Body] | None) -> Body | None: + if uncached is None or body.get("cachedContent") is None: + return None + inline: Final = uncached() + return inline if _foreign_signature_count(inline) > _foreign_signature_count(body) else None + + +def _resend_body(signed: Body, placeholders: Callable[[Body], Body | None]) -> Body | None: + resend_body: Final = placeholders(signed) + if resend_body is not None: + verbose_logger.warning( + "Gemini rejected a replayed thought signature, resending with the skip_thought_signature_validator" + " placeholder in place of the replayed signatures" + ) + return resend_body + + +async def build_with_accepted_thought_signatures_async( + build: Callable[[], Awaitable[Body]], + placeholders: Callable[[Body], Body | None], + uncached: Callable[[], Awaitable[Body]] | None, +) -> Body: + """Vertex validates the signatures in a cache's contents when it creates the cache, so a rejected one there + sends the history inline with the placeholder instead.""" + try: + return await build() + except BaseLLMException as error: + if uncached is None or not _is_rejected_signature(error): + raise + inline_body: Final = _resend_body(await uncached(), placeholders) + if inline_body is None: + raise + return inline_body + + +def build_with_accepted_thought_signatures_sync( + build: Callable[[], Body], + placeholders: Callable[[Body], Body | None], + uncached: Callable[[], Body] | None, +) -> Body: + try: + return build() + except BaseLLMException as error: + if uncached is None or not _is_rejected_signature(error): + raise + inline_body: Final = _resend_body(uncached(), placeholders) + if inline_body is None: + raise + return inline_body + + +async def _post_inline_async( + body: Body, + placeholders: Callable[[Body], Body | None], + uncached: Callable[[], Awaitable[Body]] | None, + post: Callable[[Body], Awaitable[Sent]], + log_request: Callable[[Body], None], + rejection: httpx.HTTPStatusError | BaseLLMException, +) -> tuple[Body, Sent]: + inline: Final = await _inline_history_async(body, uncached) + resend_body: Final = None if inline is None else _resend_body(inline, placeholders) + if resend_body is None: + raise rejection + log_request(resend_body) + return resend_body, await post(resend_body) + + +def _post_inline_sync( + body: Body, + placeholders: Callable[[Body], Body | None], + uncached: Callable[[], Body] | None, + post: Callable[[Body], Sent], + log_request: Callable[[Body], None], + rejection: httpx.HTTPStatusError | BaseLLMException, +) -> tuple[Body, Sent]: + inline: Final = _inline_history_sync(body, uncached) + resend_body: Final = None if inline is None else _resend_body(inline, placeholders) + if resend_body is None: + raise rejection + log_request(resend_body) + return resend_body, post(resend_body) + + +async def post_with_accepted_thought_signatures_async( + body: Body, + placeholders: Callable[[Body], Body | None], + uncached: Callable[[], Awaitable[Body]] | None, + post: Callable[[Body], Awaitable[Sent]], + log_request: Callable[[Body], None], +) -> tuple[Body, Sent]: + """Innermost retry around the raw post, so a cache rebuild (which re-transforms the messages and brings + the rejected signatures back) is itself wrapped by it. The resend keeps the cache and swaps the signatures + the body carries, and sends the history inline only when that is rejected too and the cache holds one. + Returns the body the backend accepted.""" + try: + return body, await post(body) + except (httpx.HTTPStatusError, BaseLLMException) as error: + if not _is_rejected_signature(error): + raise + resend_body: Final = _resend_body(body, placeholders) + if resend_body is None: + return await _post_inline_async(body, placeholders, uncached, post, log_request, error) + log_request(resend_body) + try: + return resend_body, await post(resend_body) + except (httpx.HTTPStatusError, BaseLLMException) as error: + if not _is_rejected_signature(error): + raise + return await _post_inline_async(body, placeholders, uncached, post, log_request, error) + + +def post_with_accepted_thought_signatures_sync( + body: Body, + placeholders: Callable[[Body], Body | None], + uncached: Callable[[], Body] | None, + post: Callable[[Body], Sent], + log_request: Callable[[Body], None], +) -> tuple[Body, Sent]: + try: + return body, post(body) + except (httpx.HTTPStatusError, BaseLLMException) as error: + if not _is_rejected_signature(error): + raise + resend_body: Final = _resend_body(body, placeholders) + if resend_body is None: + return _post_inline_sync(body, placeholders, uncached, post, log_request, error) + log_request(resend_body) + try: + return resend_body, post(resend_body) + except (httpx.HTTPStatusError, BaseLLMException) as error: + if not _is_rejected_signature(error): + raise + return _post_inline_sync(body, placeholders, uncached, post, log_request, error) diff --git a/litellm/llms/vertex_ai/gemini/transformation.py b/litellm/llms/vertex_ai/gemini/transformation.py index bbd4a96980a..3244e0ae15b 100644 --- a/litellm/llms/vertex_ai/gemini/transformation.py +++ b/litellm/llms/vertex_ai/gemini/transformation.py @@ -1256,6 +1256,7 @@ def sync_transform_request_body( vertex_project: str | None, vertex_location: str | None, vertex_auth_header: str | None, + context_caching: bool = True, ) -> RequestBody: from ..context_caching.vertex_ai_context_caching import ContextCachingEndpoints @@ -1275,6 +1276,7 @@ def sync_transform_request_body( timeout=timeout, extra_headers=extra_headers, cached_content=optional_params.pop("cached_content", None), + context_caching=context_caching, logging_obj=logging_obj, custom_llm_provider=custom_llm_provider, vertex_project=vertex_project, @@ -1390,6 +1392,7 @@ async def async_transform_request_body( vertex_project: str | None, vertex_location: str | None, vertex_auth_header: str | None, + context_caching: bool = True, ) -> RequestBody: from ..context_caching.vertex_ai_context_caching import ContextCachingEndpoints @@ -1409,6 +1412,7 @@ async def async_transform_request_body( timeout=timeout, extra_headers=extra_headers, cached_content=optional_params.pop("cached_content", None), + context_caching=context_caching, logging_obj=logging_obj, custom_llm_provider=custom_llm_provider, vertex_project=vertex_project, diff --git a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py index 69580687048..80244cfc3eb 100644 --- a/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py +++ b/litellm/llms/vertex_ai/gemini/vertex_and_google_ai_studio_gemini.py @@ -5,11 +5,13 @@ import json import re import threading import time +from collections import Counter from collections.abc import Awaitable, Callable, Mapping, Sequence from copy import deepcopy from functools import lru_cache, partial +from itertools import chain, repeat from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final, Literal, Optional, Protocol, Union, cast, get_args +from typing import TYPE_CHECKING, Any, ClassVar, Final, Literal, Optional, Protocol, Union, cast, get_args import httpx from pydantic import JsonValue, TypeAdapter @@ -34,6 +36,11 @@ from litellm.litellm_core_utils.json_fragment_accumulator import JSONFragmentAcc from litellm.litellm_core_utils.model_param_helper import embeds_thought_signature_in_tool_call_id from litellm.litellm_core_utils.prompt_templates.factory import encode_tool_call_id_with_signature from litellm.litellm_core_utils.reasoning_effort_utils import warn_dropped_reasoning +from litellm.litellm_core_utils.tool_fields import ( + declared_function_name, + qualified_member_name, + tool_params_without_hosted_mcp, +) from litellm.llms.base_llm.chat.transformation import BaseConfig, BaseLLMException from litellm.llms.custom_httpx.http_handler import ( AsyncHTTPHandler, @@ -103,7 +110,7 @@ from ..common_utils import ( ) from ..context_caching.known_cached_contents import known_cached_contents from ..context_caching.rejected_cache_retry import ( - cache_rebuild, + cache_rebuilds, post_with_fresh_cache_async, post_with_fresh_cache_sync, ) @@ -134,6 +141,13 @@ from .long_decode import ( with_initial_prompt_tokens, with_spans_shifted, ) +from .rejected_thought_signature_retry import ( + build_with_accepted_thought_signatures_async, + build_with_accepted_thought_signatures_sync, + post_with_accepted_thought_signatures_async, + post_with_accepted_thought_signatures_sync, + with_placeholder_thought_signatures, +) from .transformation import ( async_transform_request_body, gemini_convert_messages_with_history, @@ -437,6 +451,8 @@ _NAMED_UNKNOWN_VOICE_KEYS: Final = 10 _NAMED_VOICE_KEY_CHARS: Final = 100 +_NAMED_AUDIO_FORMAT_CHARS: Final = 100 + def _gemini_speech_config_wrapper(value: Mapping[str, object]) -> Mapping[str, object] | None: camel_config: Final = as_str_mapping(value.get("speechConfig")) @@ -473,6 +489,31 @@ def reject_unknown_gemini_tts_voice_keys( ) +def _named_audio_format(audio_format: object) -> str: + if isinstance(audio_format, str): + return repr(audio_format[:_NAMED_AUDIO_FORMAT_CHARS]) + return repr(audio_format)[:_NAMED_AUDIO_FORMAT_CHARS] + + +def unsupported_gemini_tts_audio_format( + model: str, audio: Mapping[str, object], drop_params: bool, llm_provider: str | None +) -> UnsupportedParamsError | None: + nested_config: Final = _gemini_speech_config_wrapper(audio) or {} + audio_format: Final = next( + (item for item in (audio.get("format"), nested_config.get("format")) if item not in (None, "pcm16")), None + ) + if audio_format is None or drops_unsupported_params(drop_params): + return None + return UnsupportedParamsError( + message=( + f"{model} does not take the audio format {_named_audio_format(audio_format)}. Set format " + "to 'pcm16' or leave it out, or set drop_params to drop it." + ), + model=model, + llm_provider=llm_provider, + ) + + def normalize_gemini_speech_config( value: Mapping[str, object], drop_unknown_fields: bool = False ) -> dict[str, object]: # mutable-ok: provider request serialization requires a concrete dict @@ -509,6 +550,138 @@ def mapped_gemini_speech_config( } +def _as_chat_tool(member: JsonValue) -> JsonValue: + if not isinstance(member, dict) or "function" in member or "name" not in member: + return member + return { + "type": member.get("type", "function"), + "function": {key: value for key, value in member.items() if key != "type"}, + } + + +def _namespace_members_or_tool(tool: JsonValue) -> tuple[JsonValue, ...]: + if not isinstance(tool, dict) or tool.get("type") != "namespace": + return (tool,) + members: Final = tool.get("tools") + return _members_named_once(tuple(map(_as_chat_tool, members))) if isinstance(members, list) else () + + +def _members_named_once( + members: tuple[JsonValue, ...], repeatable: frozenset[str] = frozenset() +) -> tuple[JsonValue, ...]: + names: Final = tuple(map(declared_function_name, members)) + first_index: Final = {name: index for index, name in reversed(tuple(enumerate(names)))} + return tuple( + member + for index, (member, name) in enumerate(zip(members, names, strict=True)) + if name is None or name in repeatable or first_index[name] == index + ) + + +def _is_namespace(tool: JsonValue) -> bool: + return isinstance(tool, dict) and tool.get("type") == "namespace" + + +def _top_level_name(tool: JsonValue) -> str | None: + name: Final = tool.get("name") if isinstance(tool, dict) else None + return name if isinstance(name, str) and name else None + + +def _listed(tools: JsonValue) -> tuple[JsonValue, ...]: + return tuple(tools) if isinstance(tools, list) else () + + +def _declarable_names(tool: JsonValue) -> tuple[str | None, ...]: + members: Final = _namespace_members_or_tool(tool) if _is_namespace(tool) else () + return (declared_function_name(tool), *map(declared_function_name, members)) + + +def _declarable_names_in(tools: tuple[JsonValue, ...]) -> tuple[str | None, ...]: + return tuple(chain.from_iterable(map(_declarable_names, tools))) + + +def _inlines_members(tool: JsonValue, declarable: Counter[str | None]) -> bool: + members: Final = _namespace_members_or_tool(tool) + return _is_namespace(tool) and all( + name is None or declarable[name] == 1 for name in map(declared_function_name, members) + ) + + +def _qualified_member(namespace: str, member: JsonValue) -> JsonValue: + function: Final = member.get("function") if isinstance(member, dict) else None + name: Final = declared_function_name(member) + if not isinstance(member, dict) or not isinstance(function, dict) or name is None: + return member + return {**member, "function": {**function, "name": qualified_member_name(namespace, name)}} + + +def _as_declared( + tool: JsonValue, declarable: Counter[str | None], top_level_names: frozenset[str] +) -> tuple[JsonValue, ...]: + if _inlines_members(tool, declarable): + return _namespace_members_or_tool(tool) + namespace: Final = _top_level_name(tool) + if not _is_namespace(tool) or namespace is None: + return (tool,) + qualified: Final = (_qualified_member(namespace, member) for member in _namespace_members_or_tool(tool)) + return tuple(member for member in qualified if declared_function_name(member) not in top_level_names) + + +def _top_level_names_in(tools: tuple[JsonValue, ...]) -> frozenset[str]: + top_level_tools: Final = (tool for tool in tools if not _is_namespace(tool)) + return frozenset(name for name in map(declared_function_name, top_level_tools) if name is not None) + + +def _with_namespace_members_inlined(tools: JsonValue, outside_declarations: JsonValue = None) -> JsonValue: + if not isinstance(tools, list) or not any(map(_is_namespace, tools)): + return tools + candidates: Final = (*tools, *_listed(outside_declarations)) + declarable: Final = Counter(_declarable_names_in(candidates)) + top_level_names: Final = _top_level_names_in(candidates) + declared: Final = chain.from_iterable(_as_declared(tool, declarable, top_level_names) for tool in tools) + return list(_members_named_once(tuple(declared), top_level_names)) + + +def _names_each_tool_declares(candidates: tuple[JsonValue, ...]) -> tuple[tuple[str, ...], ...]: + declarable: Final = Counter(_declarable_names_in(candidates)) + top_level_names: Final = _top_level_names_in(candidates) + declared: Final = tuple( + tuple(filter(None, map(declared_function_name, _as_declared(tool, declarable, top_level_names)))) + for tool in candidates + ) + owned_names: Final = chain.from_iterable(zip(repeat(index), names) for index, names in enumerate(declared)) + first_owner: Final = {name: index for index, name in reversed(tuple(owned_names))} + return tuple(tuple(name for name in names if first_owner[name] == index) for index, names in enumerate(declared)) + + +def _qualified_names_of( + member_name: str, tool: JsonValue, declarable: Counter[str | None], declared: tuple[str, ...] +) -> tuple[str, ...]: + namespace: Final = _top_level_name(tool) + if not _is_namespace(tool) or namespace is None or _inlines_members(tool, declarable): + return () + qualified: Final = qualified_member_name(namespace, member_name) + return (qualified,) if qualified in declared else () + + +def _forced_function_names(name: str, tools: JsonValue) -> tuple[str, ...]: + candidates: Final = _listed(tools) + if any(not _is_namespace(tool) and declared_function_name(tool) == name for tool in candidates): + return (name,) + declarable: Final = Counter(_declarable_names_in(candidates)) + declared_by_tool: Final = tuple(zip(candidates, _names_each_tool_declares(candidates), strict=True)) + named: Final = next( + (declared for tool, declared in declared_by_tool if _is_namespace(tool) and _top_level_name(tool) == name), + None, + ) + if named is not None: + return named + qualified: Final = chain.from_iterable( + _qualified_names_of(name, tool, declarable, declared) for tool, declared in declared_by_tool + ) + return tuple(qualified) or (name,) + + class VertexAIBaseConfig: def get_mapped_special_auth_params(self) -> dict: """ @@ -587,6 +760,8 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): Note: Please make sure to modify the default parameters as required for your use case. """ + _route: ClassVar[str] = "vertex_ai" + temperature: float | None = None max_output_tokens: int | None = None top_p: float | None = None @@ -778,7 +953,9 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): return supported_params - def map_tool_choice_values(self, model: str, tool_choice: str | dict) -> ToolConfig | None: + def map_tool_choice_values( + self, model: str, tool_choice: str | dict, tools: JsonValue = None, drop_params: bool = False + ) -> ToolConfig | None: if tool_choice == "none": return ToolConfig(functionCallingConfig=FunctionCallingConfig(mode="NONE")) elif tool_choice == "required": @@ -788,7 +965,17 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): elif isinstance(tool_choice, dict): # only supported for anthropic + mistral models - https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_ToolChoice.html name: Final = tool_choice.get("function", {}).get("name", "") - return ToolConfig(functionCallingConfig=FunctionCallingConfig(mode="ANY", allowed_function_names=[name])) + forced: Final = _forced_function_names(name, tools) + if forced: + return ToolConfig( + functionCallingConfig=FunctionCallingConfig(mode="ANY", allowed_function_names=list(forced)) + ) + if drops_unsupported_params(drop_params): + return None + raise litellm.utils.UnsupportedParamsError( + message=f"VertexAI can't force tool_choice '{name}', since none of that namespace's members can be sent to Gemini as a function. Name one of its functions instead, or set `litellm.drop_params = True` to drop tool_choice.", + status_code=400, + ) else: raise litellm.utils.UnsupportedParamsError( message=f"VertexAI doesn't support tool_choice={tool_choice}. Supported tool_choice values=['auto', 'required', json object]. To drop it from the call, set `litellm.drop_params = True.", @@ -1031,7 +1218,13 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): return googleSearch, googleSearchRetrieval, enterpriseWebSearch, urlContext - def _map_function(self, value: list[dict], optional_params: dict, send_integer_enums: bool = False) -> list[Tools]: + def _map_function( + self, + value: list[dict], + optional_params: dict, + send_integer_enums: bool = False, + outside_declarations: JsonValue = None, + ) -> list[Tools]: """ Map OpenAI-style tools/functions to Vertex AI format. @@ -1062,7 +1255,8 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): # remove 'strict' from tools remove_strict_from_schema(schema_value) - for tool in cast(list[dict], schema_value): # cast-ok: a deep copy keeps the caller's tool shape + inlined_tools: Final = _with_namespace_members_inlined(schema_value, outside_declarations) + for tool in cast(list[dict], inlined_tools): # cast-ok: a deep copy keeps the caller's tool shape openai_function_object: ChatCompletionToolParamFunctionChunk | None = None if "function" in tool: # tools list _openai_function_object = ChatCompletionToolParamFunctionChunk(**tool["function"]) @@ -1555,15 +1749,11 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): languageCode: "en-US", } """ - # Validate audio format - Gemini TTS only supports pcm16 - audio_format: Final = value.get("format") - if audio_format is not None and audio_format != "pcm16": - raise ValueError( - f"Unsupported audio format for Gemini TTS models: {audio_format}. " - f"Gemini TTS models only support 'pcm16' format as they return audio data in L16 PCM format. " - f"Please set audio format to 'pcm16'." - ) - + audio_format_error: Final = unsupported_gemini_tts_audio_format( + "Gemini TTS", value, drop_unknown_fields, self.custom_llm_provider + ) + if audio_format_error is not None: + raise audio_format_error camel_speech_config: Final = value.get("speechConfig") snake_speech_config: Final = value.get("speech_config") speech_config_value: Final = ( @@ -1601,6 +1791,11 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): def _map_chat_audio_params( self, model: str, value: Mapping[str, object], drop_params: bool ) -> dict[str, object]: # mutable-ok: the public forwarding interface returns a concrete request dictionary + audio_format_error: Final = unsupported_gemini_tts_audio_format( + model, value, drop_params, self.custom_llm_provider + ) + if audio_format_error is not None: + raise audio_format_error if _gemini_speech_config_wrapper(value) is not None: reject_unknown_gemini_tts_voice_keys(model, value, drop_params, self.custom_llm_provider) return self._map_audio_params(value, drop_unknown_fields=drops_unsupported_params(drop_params)) @@ -1639,9 +1834,12 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): drop_params: bool, allow_integer_enums: bool = True, ) -> dict: - self._apply_include_server_side_tool_invocations(non_default_params, optional_params) + request_params: Final = tool_params_without_hosted_mcp( + non_default_params, model=model, route=self._route, drop_params=drop_params + ) + self._apply_include_server_side_tool_invocations(request_params, optional_params) supports_sampling_params: Final = self.supports_sampling_params(model) - for param, value in non_default_params.items(): + for param, value in request_params.items(): if param in ("temperature", "top_p", "top_k") and not supports_sampling_params: continue if param == "temperature": @@ -1693,7 +1891,12 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): elif (param == "tools" or param == "functions") and isinstance(value, list) and value: # Pass optional_params so _map_function can add toolConfig if needed mapped_tools = with_integer_enums_that_fit( - partial(self._map_function, value, optional_params), + partial( + self._map_function, + value, + optional_params, + outside_declarations=request_params.get("functions" if param == "tools" else "tools"), + ), allow_integer_enums and self._is_gemini_3_or_newer(model), ) optional_params = self._add_tools_to_optional_params(optional_params, mapped_tools) @@ -1701,11 +1904,13 @@ class VertexGeminiConfig(VertexAIBaseConfig, BaseConfig): _tool_choice_value = self.map_tool_choice_values( model=model, tool_choice=value, + tools=[*_listed(non_default_params.get("tools")), *_listed(non_default_params.get("functions"))], + drop_params=drop_params, ) if _tool_choice_value is not None: optional_params["tool_choice"] = _tool_choice_value elif param == "parallel_tool_calls": - tools_list = non_default_params.get("tools", non_default_params.get("functions")) + tools_list = request_params.get("tools", request_params.get("functions")) num_tools = len(tools_list) if isinstance(tools_list, list) else 0 # Gemini does not support parallel_tool_calls=False with multiple # tools. Drop the param instead of failing — Responses API clients @@ -3466,23 +3671,17 @@ class VertexLLM(VertexBase): litellm_params=litellm_params, ) - rebuild: Final = cache_rebuild( - partial( - async_transform_request_body, - **data, - vertex_project=vertex_project, - vertex_location=vertex_location, - vertex_auth_header=auth_header, - ), - messages, - optional_params, - ) - request_body: Final = await async_transform_request_body( + transform: Final = partial( + async_transform_request_body, **data, vertex_project=vertex_project, vertex_location=vertex_location, vertex_auth_header=auth_header, ) + rebuild, uncached = cache_rebuilds(transform, messages, optional_params) + request_body: Final = await build_with_accepted_thought_signatures_async( + transform, with_placeholder_thought_signatures, uncached + ) ## LOGGING log_request: Final = partial(_log_generate_request, logging_obj, messages, api_base, headers) @@ -3511,7 +3710,14 @@ class VertexLLM(VertexBase): async def post(body: RequestBody) -> ModelResponseIterator: return await open_stream(client=client, data=json.dumps(body), request_body=body) - return (await post_with_fresh_cache_async(request_body, rebuild, post, log_request))[1] + accepted: Final = partial( + post_with_accepted_thought_signatures_async, + placeholders=with_placeholder_thought_signatures, + uncached=uncached, + post=post, + log_request=log_request, + ) + return (await post_with_fresh_cache_async(request_body, rebuild, accepted, log_request))[1][1] streaming_response: Final = CustomStreamWrapper( completion_stream=None, @@ -3578,23 +3784,17 @@ class VertexLLM(VertexBase): litellm_params=litellm_params, ) - rebuild: Final = cache_rebuild( - partial( - async_transform_request_body, - **data, - vertex_project=vertex_project, - vertex_location=vertex_location, - vertex_auth_header=auth_header, - ), - messages, - optional_params, - ) - request_body: Final = await async_transform_request_body( + transform: Final = partial( + async_transform_request_body, **data, vertex_project=vertex_project, vertex_location=vertex_location, vertex_auth_header=auth_header, ) + rebuild, uncached = cache_rebuilds(transform, messages, optional_params) + request_body: Final = await build_with_accepted_thought_signatures_async( + transform, with_placeholder_thought_signatures, uncached + ) _async_client_params: Final = {} if timeout: @@ -3635,7 +3835,14 @@ class VertexLLM(VertexBase): ) return response - sent_body, first_response = await post_with_fresh_cache_async(request_body, rebuild, post, log_request) + accepted: Final = partial( + post_with_accepted_thought_signatures_async, + placeholders=with_placeholder_thought_signatures, + uncached=uncached, + post=post, + log_request=log_request, + ) + _, (sent_body, first_response) = await post_with_fresh_cache_async(request_body, rebuild, accepted, log_request) return _transform_long_decode_hops( model=model, hops=await collect_hops_async(parse_body(first_response), sent_body, post), @@ -3767,23 +3974,17 @@ class VertexLLM(VertexBase): ) ## TRANSFORMATION ## - rebuild: Final = cache_rebuild( - partial( - sync_transform_request_body, - **transform_request_params, - vertex_project=vertex_project, - vertex_location=vertex_location, - vertex_auth_header=auth_header, - ), - messages, - optional_params, - ) - data: Final = sync_transform_request_body( + transform: Final = partial( + sync_transform_request_body, **transform_request_params, vertex_project=vertex_project, vertex_location=vertex_location, vertex_auth_header=auth_header, ) + rebuild, uncached = cache_rebuilds(transform, messages, optional_params) + data: Final = build_with_accepted_thought_signatures_sync( + transform, with_placeholder_thought_signatures, uncached + ) ## LOGGING log_request: Final = partial(_log_generate_request, logging_obj, messages, url, headers) @@ -3811,7 +4012,14 @@ class VertexLLM(VertexBase): def post(body: RequestBody) -> ModelResponseIterator: return open_stream(client=client, data=json.dumps(body), request_body=body) - return post_with_fresh_cache_sync(data, rebuild, post, log_request)[1] + accepted: Final = partial( + post_with_accepted_thought_signatures_sync, + placeholders=with_placeholder_thought_signatures, + uncached=uncached, + post=post, + log_request=log_request, + ) + return post_with_fresh_cache_sync(data, rebuild, accepted, log_request)[1][1] streaming_response: Final = CustomStreamWrapper( completion_stream=None, @@ -3855,7 +4063,14 @@ class VertexLLM(VertexBase): ) return response - sent_body, first_response = post_with_fresh_cache_sync(data, rebuild, post, log_request) + accepted: Final = partial( + post_with_accepted_thought_signatures_sync, + placeholders=with_placeholder_thought_signatures, + uncached=uncached, + post=post, + log_request=log_request, + ) + _, (sent_body, first_response) = post_with_fresh_cache_sync(data, rebuild, accepted, log_request) return _transform_long_decode_hops( model=model, hops=collect_hops_sync(parse_body(first_response), sent_body, post), diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/messages/transformation.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/messages/transformation.py index 98fa8ed2b77..816301c6637 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/messages/transformation.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/anthropic/messages/transformation.py @@ -249,7 +249,7 @@ class VertexAIPartnerModelsAnthropicMessagesConfig(AnthropicMessagesConfig, Vert ) self._normalize_system_role_messages( - anthropic_messages_request, model=model, drop_params=getattr(litellm_params, "drop_params", None) + anthropic_messages_request, model=model, drop_params=litellm_params.drop_params ) self._remove_scope_from_cache_control(anthropic_messages_request) diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/count_tokens/handler.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/count_tokens/handler.py index e341c8f5f48..8d39ae76456 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/count_tokens/handler.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/count_tokens/handler.py @@ -9,12 +9,14 @@ their respective publisher-specific count-tokens endpoints. from collections.abc import Mapping, Sequence from typing import Any, Final -from pydantic import TypeAdapter +from pydantic import JsonValue, TypeAdapter +from litellm.anthropic_beta_headers_manager import aload_beta_headers_config, filter_and_transform_beta_headers from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.litellm_core_utils.url_utils import join_api_base from litellm.llms.anthropic.common_utils import ( OBJECT_LIST_ADAPTER, + context_management_betas, count_tokens_feature_betas, is_claude_model_target, tools_without_custom_field, @@ -31,6 +33,7 @@ _COUNT_TOKENS_PUBLISHERS: Final = ( _REQUEST_MESSAGES: Final = TypeAdapter(Sequence[object]) +_CONTEXT_MANAGEMENT: Final[TypeAdapter[JsonValue]] = TypeAdapter(JsonValue) def count_tokens_request_body( @@ -55,8 +58,14 @@ def count_tokens_publisher(model: str) -> str | None: def count_tokens_headers(access_token: str, request_data: Mapping[str, object]) -> Mapping[str, str]: authorization: Final = {"Authorization": f"Bearer {access_token}"} - betas: Final = count_tokens_feature_betas( - "vertex_ai", request_data, _REQUEST_MESSAGES.validate_python(request_data["messages"]) + betas: Final = ( + *count_tokens_feature_betas( + "vertex_ai", request_data, _REQUEST_MESSAGES.validate_python(request_data["messages"]) + ), + *filter_and_transform_beta_headers( + list(context_management_betas(_CONTEXT_MANAGEMENT.validate_python(request_data.get("context_management")))), + "vertex_ai", + ), ) return {**authorization, "anthropic-beta": ",".join(betas)} if betas else authorization @@ -193,6 +202,8 @@ class VertexAIPartnerModelsTokenCounter(VertexBase): api_base=litellm_params.get("api_base"), ) + if request_data.get("context_management") is not None: + await aload_beta_headers_config() headers: Final = dict(count_tokens_headers(access_token, request_data)) # Get async HTTP client diff --git a/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py b/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py index a3a3427670d..c298ca404e2 100644 --- a/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py +++ b/litellm/llms/vertex_ai/vertex_ai_partner_models/main.py @@ -268,6 +268,7 @@ class VertexAIPartnerModels(VertexBase): system: object | None = None, tools: list[dict[str, object]] | None = None, count_options: Mapping[str, object] = MappingProxyType({}), + context_management: object = None, ): """ Count tokens for Vertex AI partner models (Anthropic Claude, Mistral, etc.) @@ -302,7 +303,15 @@ class VertexAIPartnerModels(VertexBase): "model": model, "messages": messages, **MappingProxyType( - {key: value for key, value in (("system", system), ("tools", tools)) if value is not None} + { + key: value + for key, value in ( + ("system", system), + ("tools", tools), + ("context_management", context_management), + ) + if value is not None + } ), **count_options, } diff --git a/litellm/llms/vllm/common_utils.py b/litellm/llms/vllm/common_utils.py index 014fabd5187..41db96914f5 100644 --- a/litellm/llms/vllm/common_utils.py +++ b/litellm/llms/vllm/common_utils.py @@ -2,10 +2,12 @@ from collections.abc import Mapping from typing import Final import httpx +from pydantic import TypeAdapter -import litellm +from litellm.constants import NON_LLM_CONNECTION_TIMEOUT, PLACEHOLDER_API_KEY from litellm.llms.base_llm.base_utils import BaseLLMModelInfo from litellm.llms.base_llm.chat.transformation import BaseLLMException +from litellm.llms.custom_httpx.http_handler import get_httpx_client from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import AllMessageValues from litellm.utils import add_path_to_api_base @@ -37,17 +39,31 @@ class VLLMError(BaseLLMException): ) +_EXTRA_HEADERS: Final = TypeAdapter(Mapping[str, str]) + + +def _auth_headers(api_key: str | None) -> Mapping[str, str]: + if api_key is None or api_key == PLACEHOLDER_API_KEY: + return {} + return {"Authorization": f"Bearer {api_key}"} + + +def _str_param(litellm_params: Mapping[str, object], key: str) -> str | None: + value: Final = litellm_params.get(key) + return value if isinstance(value, str) else None + + class VLLMModelInfo(BaseLLMModelInfo): def validate_environment( self, - headers: dict, + headers: dict[str, str], model: str, messages: list[AllMessageValues], optional_params: dict, litellm_params: dict, api_key: str | None = None, api_base: str | None = None, - ) -> dict: + ) -> dict[str, str]: upstream_key: Final = self.upstream_api_key(api_key, api_base) return {**headers, **self.upstream_auth_headers(upstream_key)} if upstream_key else headers @@ -58,7 +74,7 @@ class VLLMModelInfo(BaseLLMModelInfo): return {"Authorization": f"Bearer {api_key}", "x-api-key": api_key} @staticmethod - def get_api_base(api_base: str | None = None) -> str | None: + def get_api_base(api_base: str | None = None) -> str: api_base = api_base or get_secret_str("VLLM_API_BASE") if api_base is None: raise ValueError( @@ -74,25 +90,55 @@ class VLLMModelInfo(BaseLLMModelInfo): def get_base_model(model: str) -> str | None: return model - def get_models(self, api_key: str | None = None, api_base: str | None = None) -> list[str]: - api_base = VLLMModelInfo.get_api_base(api_base) - api_key = VLLMModelInfo.get_api_key(api_key) - endpoint: Final = "/v1/models" - if api_base is None or api_key is None: - raise ValueError( - "VLLM_API_BASE or VLLM_API_KEY is not set. Please set the environment variable, to query VLLM's `/models` endpoint." - ) - - url: Final = add_path_to_api_base(api_base, endpoint) - response: Final = litellm.module_level_client.get( - url=url, - ) - - response.raise_for_status() - - models: Final = response.json()["data"] - - return [model["id"] for model in models] + def get_models( + self, api_key: str | None = None, api_base: str | None = None + ) -> list[str]: # mutable-ok: mirrors override contract + return [] def get_error_class(self, error_message: str, status_code: int, headers: dict | httpx.Headers) -> BaseLLMException: return VLLMError(status_code=status_code, message=error_message, headers=headers) + + +class HostedVLLMModelInfo(VLLMModelInfo): + @staticmethod + def get_api_base(api_base: str | None = None) -> str: + resolved_api_base: Final = api_base or get_secret_str("HOSTED_VLLM_API_BASE") + if resolved_api_base is None: + raise ValueError("HOSTED_VLLM_API_BASE is not set.") + return resolved_api_base + + @staticmethod + def get_api_key(api_key: str | None = None) -> str | None: + return api_key or get_secret_str("HOSTED_VLLM_API_KEY") + + def get_models(self, api_key: str | None = None, api_base: str | None = None) -> list[str]: + return self._list_models(api_key=api_key, api_base=api_base, extra_headers={}, ssl_verify=None) + + def discover_models( + self, litellm_params: Mapping[str, object] | None = None + ) -> list[str]: # mutable-ok: matches get_models' list[str] contract shared by every provider override + params: Final = litellm_params or {} + ssl_verify: Final = params.get("ssl_verify") + return self._list_models( + api_key=_str_param(params, "api_key"), + api_base=_str_param(params, "api_base"), + extra_headers=_EXTRA_HEADERS.validate_python(params.get("extra_headers") or {}), + ssl_verify=ssl_verify if isinstance(ssl_verify, (bool, str)) else None, + ) + + def _list_models( + self, + *, + api_key: str | None, + api_base: str | None, + extra_headers: Mapping[str, str], + ssl_verify: bool | str | None, + ) -> list[str]: # mutable-ok: matches get_models' list[str] contract shared by every provider override + url: Final = add_path_to_api_base(self.get_api_base(api_base), "/v1/models") + response: Final = get_httpx_client(params={"ssl_verify": ssl_verify}).get( + url=url, + headers={**extra_headers, **_auth_headers(self.get_api_key(api_key))}, + timeout=NON_LLM_CONNECTION_TIMEOUT, + ) + response.raise_for_status() + return [model["id"] for model in response.json()["data"]] diff --git a/litellm/llms/vllm/passthrough/transformation.py b/litellm/llms/vllm/passthrough/transformation.py index 2b253e7fa38..10d740e49e0 100644 --- a/litellm/llms/vllm/passthrough/transformation.py +++ b/litellm/llms/vllm/passthrough/transformation.py @@ -67,9 +67,6 @@ class VLLMPassthroughConfig(VLLMModelInfo, BasePassthroughConfig): ) -> tuple["URL", str]: base_target_url: Final = self.get_api_base(api_base) - if base_target_url is None: - raise Exception("VLLM api base not found") - return ( self.format_url(endpoint_under_api_base(endpoint, base_target_url), base_target_url, request_query_params), base_target_url, diff --git a/litellm/main.py b/litellm/main.py index 78767b03eb7..8cb133bf76b 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -37,6 +37,8 @@ if TYPE_CHECKING: import dotenv import httpx import openai +from openai import AsyncStream, Stream +from openai.types.audio import TranscriptionStreamEvent from pydantic import BaseModel, TypeAdapter, ValidationError from typing_extensions import assert_never, overload @@ -70,17 +72,22 @@ from litellm.constants import ( ) from litellm.exceptions import LiteLLMUnknownProvider from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.allowed_tools_tool_choice import ( + raise_if_allowed_tools_tool_choice_unsupported, +) from litellm.litellm_core_utils.asyncify import asyncify, run_async_function from litellm.litellm_core_utils.audio_utils.utils import ( calculate_request_duration, get_audio_file_for_health_check, ) from litellm.litellm_core_utils.chat_completion_agentic_loop import ( + bill_first_round_on_failure, maybe_run_chat_completion_agentic_loop, ) from litellm.litellm_core_utils.completion_timeout import CompletionTimeout, StreamKind from litellm.litellm_core_utils.dd_tracing import tracer from litellm.litellm_core_utils.get_litellm_params import ( + AGENTIC_LOOP_CONTROL_KWARGS_KEYS, AWS_CREDENTIAL_KWARGS_KEYS, OAUTH_TOKEN_EXCHANGE_KWARGS_KEYS, PROVIDER_AFFINITY_HEADER_KWARG_KEY, @@ -106,6 +113,7 @@ from litellm.litellm_core_utils.mock_functions import ( mock_embedding, mock_image_generation, ) +from litellm.litellm_core_utils.per_call_pricing import per_call_model_info from litellm.litellm_core_utils.prompt_templates.common_utils import ( get_content_from_model_response as get_content_from_model_response, # noqa: PLC0414 # public re-export ) @@ -162,7 +170,6 @@ from litellm.types.router import GenericLiteLLMParams, validate_litellm_params_s from litellm.types.utils import ( AgenticLoopParams, BaseUrlRoutingHint, - CustomPricingLiteLLMParams, ModelResponseStream, ProviderRoutingHints, RawRequestTypedDict, @@ -263,7 +270,7 @@ from .llms.codestral.completion.handler import CodestralTextCompletion from .llms.cohere.embed import handler as cohere_embed from .llms.custom_httpx.aiohttp_handler import BaseLLMAIOHTTPHandler from .llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler -from .llms.custom_llm import CustomLLM, custom_chat_llm_router +from .llms.custom_llm import custom_chat_llm_router from .llms.databricks.common_utils import DatabricksBase from .llms.databricks.embed.handler import DatabricksEmbeddingHandler from .llms.deprecated_providers import aleph_alpha @@ -750,6 +757,7 @@ async def acompletion( from litellm.integrations.anthropic_cache_control_hook import ( AnthropicCacheControlHook, + routed_model_info, ) from litellm.types.llms.openai import AllMessageValues @@ -761,6 +769,7 @@ async def acompletion( tools=tools, enable_prompt_caching=cast(bool | None, kwargs.get("enable_prompt_caching")), # cast-ok: untyped kwargs api_base=base_url or kwargs.get("api_base"), + model_info=routed_model_info(caller_kwargs.get("model_info")), ) prompt_id: Final = cast(str | None, kwargs.get("prompt_id", None)) # cast-ok: read from untyped kwargs @@ -947,26 +956,31 @@ async def acompletion( # no equivalent: every provider already funnels through one shared # handler where the loop is dispatched. if isinstance(response, litellm.ModelResponse): - looped: Final = await maybe_run_chat_completion_agentic_loop( - response=response, - model=model, - messages=messages, - optional_params={ - k: v - for k, v in completion_kwargs.items() - if v is not None - and k - not in ( - "model", - "messages", - "stream", - "acompletion", - "deployment_id", - ) - }, - kwargs=kwargs, + looped: Final = await bill_first_round_on_failure( + maybe_run_chat_completion_agentic_loop( + response=response, + model=model, + messages=messages, + optional_params={ + k: v + for k, v in completion_kwargs.items() + if v is not None + and k + not in ( + "model", + "messages", + "stream", + "acompletion", + "deployment_id", + ) + }, + kwargs=kwargs, + logging_obj=kwargs.get("litellm_logging_obj"), + custom_llm_provider=custom_llm_provider, + stream=bool(stream), + ), logging_obj=kwargs.get("litellm_logging_obj"), - custom_llm_provider=custom_llm_provider, + response=response, stream=bool(stream), ) if looped is not None: @@ -998,7 +1012,7 @@ def _model_response_from_cached_dict(cached_response_dict: Mapping[str, object]) def _transcription_response_from_cached_dict(cached_response_dict: Mapping[str, object]) -> TranscriptionResponse: - return TranscriptionResponse(**cached_response_dict) + return TranscriptionResponse.model_validate(cached_response_dict) def _text_completion_response_from_cached_dict(cached_response_dict: Mapping[str, object]) -> TextCompletionResponse: @@ -1316,7 +1330,6 @@ from litellm.responses.bridge_check import ( # noqa: E402 # re-export at the o ) from litellm.responses.bridge_check import ( bridge_reasoning_effort, - keep_registered_mode, str_keyed_mapping, ) from litellm.responses.bridge_check import ( # noqa: E402 # re-export at the old definition site @@ -1422,46 +1435,6 @@ def _locals_snapshot(values: Mapping[str, object]) -> Mapping[str, object]: return values -def _build_custom_pricing_entry( - custom_llm_provider: str, - kwargs: dict, - model_info: dict | None = None, -) -> dict: - """Build a complete model cost entry from kwargs and model_info. - - Collects all CustomPricingLiteLLMParams fields present in kwargs and - merges metadata from model_info (mode, supports_prompt_caching, max_tokens) - so that register_model() receives the full pricing configuration. - """ - entry: Final[dict] = {"litellm_provider": custom_llm_provider} - - for field_name in CustomPricingLiteLLMParams.model_fields: - value = kwargs.get(field_name) - if value is not None: - entry[field_name] = value - - if model_info and isinstance(model_info, dict): - for key in ("mode", "supports_prompt_caching", "max_tokens"): - if key in model_info and model_info[key] is not None: - entry.setdefault(key, model_info[key]) - - return entry - - -def _get_router_deployment_id(kwargs: dict) -> str | None: - for metadata_key in ("litellm_metadata", "metadata"): - metadata = kwargs.get(metadata_key) or {} - if not isinstance(metadata, dict): - continue - deployment_model_info = metadata.get("model_info") or {} - if not isinstance(deployment_model_info, dict): - continue - deployment_id = deployment_model_info.get("id") - if deployment_id is not None: - return str(deployment_id) - return None - - def _record_agentic_loop_params( logging_obj: object, requested_model: str, custom_llm_provider: str, owns_agentic_loop: bool ) -> None: @@ -1472,53 +1445,6 @@ def _record_agentic_loop_params( ) -def _register_custom_pricing_for_request( - model: str, - custom_llm_provider: str, - kwargs: dict, - model_info: dict | None, -) -> None: - """Register per-request custom pricing in litellm.model_cost. - - Router-originated requests (identified by the deployment id the router puts - in metadata) get their full pricing registered under that unique id only; - the shared ``{provider}/{model}`` key receives the entry with pricing fields - stripped, mirroring Router._create_deployment. This keeps one deployment's - pricing overrides (e.g. a zero-cost wildcard) from clobbering built-in - pricing used by sibling deployments of the same backend model. Direct SDK - calls keep the legacy behavior of registering the shared key with pricing. - Either way the shared key's ``mode`` follows ``keep_registered_mode``, as on - deployment registration, since a call routes by its own ``model_info``. - """ - entry: Final = _build_custom_pricing_entry( - custom_llm_provider=custom_llm_provider, - kwargs=kwargs, - model_info=model_info, - ) - shared_key: Final = f"{custom_llm_provider}/{model}" - deployment_id: Final = _get_router_deployment_id(kwargs) - if deployment_id is None: - litellm.register_model({shared_key: keep_registered_mode(shared_key, entry)}, persist_across_reloads=False) - return - shared_entry: Final = keep_registered_mode( - shared_key, CustomPricingLiteLLMParams.strip_custom_pricing_fields(entry) - ) - litellm.register_model( - {deployment_id: entry}, - persist_across_reloads=False, - warning_display_name=shared_key, - custom_llm_provider=custom_llm_provider, - add_to_provider_model_sets=False, - ) - litellm.register_model( - {shared_key: shared_entry}, - persist_across_reloads=False, - warning_display_name=shared_key, - custom_llm_provider=custom_llm_provider, - add_to_provider_model_sets=False, - ) - - def _dispatch_metadata(ctx: CompletionDispatchContext) -> Mapping[str, object] | None: return ctx.metadata @@ -5334,10 +5260,7 @@ def _complete_custom_providers( stream: Final = ctx.stream timeout: Final = ctx.timeout - custom_handler: CustomLLM | None = None - for item in litellm.custom_provider_map: - if item["provider"] == custom_llm_provider: - custom_handler = item["custom_handler"] + custom_handler: Final = ProviderConfigManager.get_custom_llm_handler(custom_llm_provider) if custom_handler is None: raise LiteLLMUnknownProvider(model=model, custom_llm_provider=custom_llm_provider) @@ -5783,9 +5706,9 @@ def completion( ### CUSTOM MODEL COST ### input_cost_per_token: Final = kwargs.get("input_cost_per_token", None) output_cost_per_token: Final = kwargs.get("output_cost_per_token", None) - cost_per_second: Final = kwargs.get("cost_per_second", None) input_cost_per_second: Final = kwargs.get("input_cost_per_second", None) output_cost_per_second: Final = kwargs.get("output_cost_per_second", None) + cost_per_second: Final = kwargs.get("cost_per_second", None) ### CUSTOM PROMPT TEMPLATE ### initial_prompt_value: Final = kwargs.get("initial_prompt_value", None) roles: Final = kwargs.get("roles", None) @@ -5825,6 +5748,7 @@ def completion( from litellm.integrations.anthropic_cache_control_hook import ( AnthropicCacheControlHook, + routed_model_info, ) from litellm.types.llms.openai import AllMessageValues @@ -5836,6 +5760,7 @@ def completion( tools=tools, enable_prompt_caching=cast(bool | None, kwargs.get("enable_prompt_caching")), # cast-ok: untyped kwargs api_base=base_url or kwargs.get("api_base"), + model_info=routed_model_info(cast(object, model_info)), # cast-ok: untyped kwargs ) if isinstance(litellm_logging_obj, LiteLLMLoggingObj) and ( @@ -5956,6 +5881,14 @@ def completion( if not is_claude_tool_target(custom_llm_provider=custom_llm_provider, model=model): tools = _drop_anthropic_only_tool_keys(tools=tools) + raise_if_allowed_tools_tool_choice_unsupported( + tool_choice=cast( # cast-ok: widening an untyped dict to object is always sound, the helper validates it with pydantic + object, tool_choice + ), + custom_llm_provider=custom_llm_provider, + model=model, + ) + if provider_specific_header is not None: headers.update( ProviderSpecificHeaderUtils.get_provider_specific_headers( @@ -5973,19 +5906,7 @@ def completion( "aws_region_name", None ) # support region-based pricing for bedrock - ### REGISTER CUSTOM MODEL PRICING -- IF GIVEN ### - if ( - (input_cost_per_token is not None and output_cost_per_token is not None) - or input_cost_per_second is not None - or output_cost_per_second is not None - or cost_per_second is not None - ): - _register_custom_pricing_for_request( - model=model, - custom_llm_provider=custom_llm_provider, - kwargs=kwargs, - model_info=model_info, - ) + logging.set_per_call_pricing(per_call_model_info(model, custom_llm_provider, kwargs, "chat")) ### BUILD CUSTOM PROMPT TEMPLATE -- IF GIVEN ### custom_prompt_dict = {} if initial_prompt_value or roles or final_prompt_value or bos_token or eos_token: @@ -6148,7 +6069,6 @@ def completion( return resolve_timeout(stream_kind=StreamKind.NOT_STREAMED) return resolve_timeout(stream_kind=StreamKind.FAKED if fakes_stream(attempt_params) else StreamKind.LIVE) - ### TIMEOUT LOGIC ### timeout = timeout_for_optional_params(optional_params) logging.record_applied_timeout(timeout) processed_non_default_params: Final = pre_process_non_default_params( @@ -6191,6 +6111,11 @@ def completion( messages if readable_messages is None else list(readable_messages) ) + supplied_client_api_base: Final = ( + str(client.base_url) + if custom_llm_provider == "openai" and isinstance(client, openai.OpenAI | openai.AsyncOpenAI) + else None + ) # For logging - save the values of the litellm-specific params passed in requested_litellm_params: Final = get_litellm_params( acompletion=acompletion, @@ -6199,7 +6124,7 @@ def completion( logger_fn=logger_fn, verbose=verbose, custom_llm_provider=custom_llm_provider, - api_base=api_base, + api_base=supplied_client_api_base or api_base, litellm_call_id=kwargs.get("litellm_call_id", None), model_alias_map=litellm.model_alias_map, completion_call_id=id, @@ -6255,6 +6180,7 @@ def completion( *ANTHROPIC_WIF_KWARGS_KEYS, *OPENAI_WIF_KWARGS_KEYS, *OAUTH_TOKEN_EXCHANGE_KWARGS_KEYS, + *AGENTIC_LOOP_CONTROL_KWARGS_KEYS, "github_copilot_auth_type", "github_copilot_host", "github_copilot_user_session", @@ -6992,12 +6918,6 @@ def embedding( headers.update(proxy_headers) except Exception as e: verbose_logger.warning("Failed to get proxy auth headers: %s", e) - ### CUSTOM MODEL COST ### - input_cost_per_token: Final = kwargs.get("input_cost_per_token", None) - output_cost_per_token: Final = kwargs.get("output_cost_per_token", None) - cost_per_second: Final = kwargs.get("cost_per_second", None) - input_cost_per_second: Final = kwargs.get("input_cost_per_second", None) - output_cost_per_second: Final = kwargs.get("output_cost_per_second", None) openai_params: Final = [ "user", "dimensions", @@ -7044,21 +6964,8 @@ def embedding( **non_default_params, ) - ### REGISTER CUSTOM MODEL PRICING -- IF GIVEN ### - if ( - (input_cost_per_token is not None and output_cost_per_token is not None) - or input_cost_per_second is not None - or output_cost_per_second is not None - or cost_per_second is not None - ): - _register_custom_pricing_for_request( - model=model, - custom_llm_provider=custom_llm_provider, - kwargs=kwargs, - model_info=kwargs.get("model_info"), - ) - logging: Final[LiteLLMLoggingObj] = litellm_logging_obj + logging.set_per_call_pricing(per_call_model_info(model, custom_llm_provider, kwargs, "embedding")) logging.update_environment_variables( model=model, user=user, @@ -7392,6 +7299,7 @@ def embedding( aembedding=aembedding, litellm_params=litellm_params_dict, headers=headers, + timeout=timeout, ) elif custom_llm_provider == "bedrock": if isinstance(input, str): @@ -7900,10 +7808,7 @@ def embedding( litellm_params={}, ) elif custom_llm_provider in litellm._custom_providers: - custom_handler: CustomLLM | None = None - for item in litellm.custom_provider_map: - if item["provider"] == custom_llm_provider: - custom_handler = item["custom_handler"] + custom_handler: Final = ProviderConfigManager.get_custom_llm_handler(custom_llm_provider) if custom_handler is None: raise LiteLLMUnknownProvider(model=model, custom_llm_provider=custom_llm_provider) @@ -8495,7 +8400,10 @@ async def amoderation( @client -async def atranscription(*args, **kwargs) -> TranscriptionResponse: +async def atranscription( + *args, # noqa: ANN002 # public SDK wrapper preserves positional call compatibility + **kwargs, # noqa: ANN003 # kwargs-ok: public SDK wrapper preserves keyword call compatibility +) -> TranscriptionResponse | AsyncStream[TranscriptionStreamEvent]: """ Calls openai + azure whisper endpoints. @@ -8539,6 +8447,14 @@ async def atranscription(*args, **kwargs) -> TranscriptionResponse: else: # Call the synchronous function using run_in_executor response = await loop.run_in_executor(None, func_with_context) + if isinstance(response, AsyncStream): + if file is not None: + calculated_duration = calculate_request_duration(file) + if calculated_duration is not None: + response._litellm_audio_duration = ( # pyright: ignore[reportAttributeAccessIssue] # SDK omits it + calculated_duration + ) + return response if not isinstance(response, TranscriptionResponse): raise ValueError( f"Invalid response from transcription provider, expected TranscriptionResponse, but got {type(response)}" @@ -8551,9 +8467,9 @@ async def atranscription(*args, **kwargs) -> TranscriptionResponse: if response is not None and not isinstance(response, Coroutine) and file is not None: existing_duration: Final = getattr(response, "duration", None) if existing_duration is None: - calculated_duration: Final = calculate_request_duration(file) - if calculated_duration is not None: - response.hidden_params["audio_transcription_duration"] = calculated_duration + sync_calculated_duration: Final = calculate_request_duration(file) + if sync_calculated_duration is not None: + response.set_audio_transcription_duration(sync_calculated_duration) return response except Exception as e: @@ -8567,6 +8483,42 @@ async def atranscription(*args, **kwargs) -> TranscriptionResponse: ) +def _validate_gpt_transcription_request( + model: str, + pricing_model: str, + custom_llm_provider: str, + response_format: str | None, + drop_params: object, +) -> str | None: + model_cost_key: Final = next( + ( + key + for key in (f"{custom_llm_provider}/{pricing_model}", pricing_model) + if (as_str_mapping(litellm.model_cost.get(key)) or {}).get("litellm_provider") == custom_llm_provider + ), + None, + ) + model_info: Final = ( + get_model_info(model=pricing_model, custom_llm_provider=custom_llm_provider) + if model_cost_key is not None + else None + ) + provider_specific_entry: Final = model_info.get("provider_specific_entry") if model_info is not None else None + if ( + provider_specific_entry is None + or provider_specific_entry.get("transcription_json_or_text_only") != 1 + or response_format in (None, "json", "text") + ): + return response_format + if litellm.drop_params is True or normalize_drop_params(drop_params) is True: + return None + raise litellm.UnsupportedParamsError( + message=f"{model} only supports response_format 'json' or 'text'", + model=model, + llm_provider=custom_llm_provider, + ) + + @client def transcription( model: str, @@ -8586,8 +8538,15 @@ def transcription( max_retries: int | None = None, custom_llm_provider=None, base_url: str | None = None, + languages: Sequence[str] | None = None, + keywords: Sequence[str] | None = None, + stream: bool | None = None, **kwargs, -) -> TranscriptionResponse | Coroutine[object, object, TranscriptionResponse]: +) -> ( + TranscriptionResponse + | Stream[TranscriptionStreamEvent] + | Coroutine[Any, Any, TranscriptionResponse | AsyncStream[TranscriptionStreamEvent]] +): """ Calls openai + azure whisper endpoints. @@ -8625,19 +8584,36 @@ def transcription( api_key = dynamic_api_key if dynamic_api_key is not None else api_key + litellm_params_dict: Final = get_litellm_params(**kwargs) + configured_base_model: Final = litellm_params_dict.get("base_model") + pricing_model: Final = ( + configured_base_model.removeprefix(f"{custom_llm_provider}/") + if isinstance(configured_base_model, str) + else model + ) + + supported_response_format: Final = _validate_gpt_transcription_request( + model=model, + pricing_model=pricing_model, + custom_llm_provider=custom_llm_provider, + response_format=response_format, + drop_params=kwargs.get("drop_params"), + ) + optional_params: Final = get_optional_params_transcription( model=model, language=language, + languages=languages, + keywords=keywords, prompt=prompt, - response_format=response_format, + response_format=supported_response_format, timestamp_granularities=timestamp_granularities, temperature=temperature, + stream=stream, custom_llm_provider=custom_llm_provider, **non_default_params, ) - litellm_params_dict: Final = get_litellm_params(**kwargs) - litellm_logging_obj.update_environment_variables( model=model, user=user, @@ -8654,11 +8630,17 @@ def transcription( custom_llm_provider=custom_llm_provider, ) - response: TranscriptionResponse | Coroutine[object, object, TranscriptionResponse] + response: ( + TranscriptionResponse + | Stream[TranscriptionStreamEvent] + | AsyncStream[TranscriptionStreamEvent] + | Coroutine[Any, Any, TranscriptionResponse | AsyncStream[TranscriptionStreamEvent]] + ) provider_config: Final = ProviderConfigManager.get_provider_audio_transcription_config( model=model, provider=LlmProviders(custom_llm_provider), + base_model=pricing_model, ) uses_openai_transport: Final = custom_llm_provider in OPENAI_AUDIO_TRANSCRIPTION_PROVIDERS and not ( @@ -8669,7 +8651,7 @@ def transcription( # azure configs api_base = api_base or litellm.api_base or get_secret_str("AZURE_API_BASE") - api_version = api_version or litellm.api_version or get_secret_str("AZURE_API_VERSION") + azure_api_version: Final = api_version or litellm.api_version or get_secret_str("AZURE_API_VERSION") azure_ad_token: Final = kwargs.pop("azure_ad_token", None) or get_secret_str("AZURE_AD_TOKEN") @@ -8688,7 +8670,7 @@ def transcription( logging_obj=litellm_logging_obj, api_base=api_base, api_key=api_key, - api_version=api_version, + api_version=azure_api_version, azure_ad_token=azure_ad_token, max_retries=max_retries, litellm_params=litellm_params_dict, @@ -8825,15 +8807,17 @@ def transcription( # Store duration in _hidden_params for cost calculation without # exposing it in the response body (see sync path comment above). - if not isinstance(response, Coroutine): - existing_duration: Final = getattr(response, "duration", None) - if existing_duration is None: - calculated_duration: Final = calculate_request_duration(file) + if not isinstance(response, Coroutine) and ( + isinstance(response, (Stream, AsyncStream)) or getattr(response, "duration", None) is None + ): + calculated_duration: Final = calculate_request_duration(file) + if isinstance(response, (Stream, AsyncStream)): if calculated_duration is not None: - response_hidden_params: Final = cast( # cast-ok: preserve dynamic mapping behavior - dict[str, object], getattr(response, HIDDEN_PARAMS_ATTR) + response._litellm_audio_duration = ( # pyright: ignore[reportAttributeAccessIssue] # SDK omits it + calculated_duration ) - response_hidden_params["audio_transcription_duration"] = calculated_duration + elif calculated_duration is not None: + response.set_audio_transcription_duration(calculated_duration) return response diff --git a/litellm/mcp_client/client.py b/litellm/mcp_client/client.py index 107b7155303..0461f1f06ff 100644 --- a/litellm/mcp_client/client.py +++ b/litellm/mcp_client/client.py @@ -478,6 +478,13 @@ def _notify_cleanup(callback: Callable[[], None] | None) -> None: callback() +class _UnvalidatedClientSession(ClientSession): + """Skips the SDK's output check, which lists the upstream's tools on a session with no schema cached.""" + + async def validate_tool_result(self, name: str, result: MCPCallToolResult) -> None: + return None + + class MCPClient: """ MCP Client supporting: @@ -505,12 +512,15 @@ class MCPClient: elicitation_callback: "ElicitationCallback | None" = None, logging_callback: Callable | None = None, protocol_version: MCPUpstreamProtocol = "auto", + skip_tool_output_validation: bool = False, upstream_transport: httpx2.AsyncBaseTransport | None = None, ): self.protocol_version: MCPUpstreamProtocol = TypeAdapter[MCPUpstreamProtocol]( MCPUpstreamProtocol ).validate_python(protocol_version) validate_mcp_protocol_transport(self.protocol_version, transport_type) + # 2026-07-28 lists tools before every call, so its output check adds no list + self.skip_tool_output_validation: Final = skip_tool_output_validation and self.protocol_version != "2026-07-28" self.server_url: str = server_url self.transport_type: MCPTransport = transport_type self.auth_type: MCPAuthType = auth_type @@ -546,7 +556,7 @@ class MCPClient: "response_hooks": _mcp_response_hooks(), } - def session_settings(self) -> tuple[MCPTransport, MCPUpstreamProtocol, float, bool, bool, bool]: + def session_settings(self) -> tuple[MCPTransport, MCPUpstreamProtocol, float, bool, bool, bool, bool]: callbacks: Final = self.session_callbacks() return ( self.transport_type, @@ -555,6 +565,7 @@ class MCPClient: callbacks["sampling_callback"] is not None, callbacks["elicitation_callback"] is not None, callbacks["logging_callback"] is not None, + self.skip_tool_output_validation, ) def route_session_callbacks(self, callbacks: _SessionCallbackMap) -> None: @@ -776,7 +787,10 @@ class MCPClient: ) # The SDK drops a response stream that ends without a JSON-RPC reply, so nothing else # ever fails the request. - session_ctx: Final = ClientSession( + session_type: Final = ( + _UnvalidatedClientSession if self.skip_tool_output_validation else ClientSession + ) + session_ctx: Final = session_type( read_stream, write_stream, read_timeout_seconds=self.timeout, diff --git a/litellm/messages/dispatch.py b/litellm/messages/dispatch.py index 35136c41dc2..4c94f26c6c1 100644 --- a/litellm/messages/dispatch.py +++ b/litellm/messages/dispatch.py @@ -75,9 +75,7 @@ def _public_request( return native_call(legacy, args, _native_kwargs(fields, kwargs)) -def _resolved(request: NativeCall) -> tuple[str, str | None]: - model: Final = str(request.resolved["model"]) - provider: Final = optional_str(request.resolved.get("custom_llm_provider")) +def _resolved_model(model: str, provider: str | None) -> tuple[str, str | None]: try: resolved_model, resolved_provider, _, _ = get_llm_provider(model, provider) except BadRequestError: @@ -85,21 +83,43 @@ def _resolved(request: NativeCall) -> tuple[str, str | None]: return resolved_model, resolved_provider -def _target(request: NativeCall, model: str, provider: str | None) -> Target: - requested_model: Final = str(request.resolved["model"]) - model_info: Final = request.resolved.get("model_info") - api_base: Final = request.resolved.get("api_base") - native_config: Final = main._native_messages_config( # pyright: ignore[reportPrivateUsage] # the handler's own passthrough lookup - model, provider, model_info, api_base if isinstance(api_base, str) else None - ) +def _resolved(request: NativeCall) -> tuple[str, str | None]: + return _resolved_model(str(request.resolved["model"]), optional_str(request.resolved.get("custom_llm_provider"))) + + +def _route_target( + requested_model: str, + model: str, + provider: str | None, + model_info: object, + api_base: str | None, + compacting: bool, +) -> Target: + native_config: Final = main._native_messages_config(model, provider, model_info, api_base) # pyright: ignore[reportPrivateUsage] # the handler's own passthrough lookup if native_config is not None: return Target.MESSAGES - compacting: Final = request.resolved.get("compaction") is not None if not compacting and main._should_route_to_responses_api(provider, requested_model, model, model_info): # pyright: ignore[reportPrivateUsage] # the handler's own translation choice return Target.RESPONSES return Target.CHAT_COMPLETIONS +def _target(request: NativeCall, model: str, provider: str | None) -> Target: + api_base: Final = request.resolved.get("api_base") + return _route_target( + str(request.resolved["model"]), + model, + provider, + request.resolved.get("model_info"), + api_base if isinstance(api_base, str) else None, + compacting=request.resolved.get("compaction") is not None, + ) + + +def messages_target(model: str, custom_llm_provider: str | None, model_info: object, api_base: str | None) -> Target: + resolved_model, resolved_provider = _resolved_model(model, custom_llm_provider) + return _route_target(model, resolved_model, resolved_provider, model_info, api_base, compacting=False) + + _FEATURES: Final[detectors.Detectors] = MappingProxyType( { **detectors.COMMON, @@ -119,6 +139,7 @@ _ASYNC_FEATURES: Final[detectors.Detectors] = MappingProxyType( { **_FEATURES, Feature.PRE_REQUEST_HOOK: route_detectors.pre_request_hook, + Feature.FOUNDRY_BETA_ROW: route_detectors.foundry_beta_row, Feature.WEBSEARCH_INTERCEPTION: route_detectors.websearch_interception, Feature.MESSAGES_INTERCEPTOR: route_detectors.intercepted, Feature.STRICT_TOOLS_RETRY: route_detectors.strict_tools_retry, diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 3288e64d296..29c50a24272 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -1,4 +1,172 @@ { + "azure/gpt-realtime-2.1-2026-07-07": { + "cache_creation_input_audio_token_cost": 4e-07, + "cache_read_input_audio_token_cost": 4e-07, + "cache_read_input_token_cost": 4e-07, + "deprecation_date": "2027-06-25", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "input_cost_per_audio_token": 3.2e-05, + "input_cost_per_image_token": 5e-06, + "input_cost_per_token": 4e-06, + "litellm_provider": "azure", + "max_input_tokens": 32000, + "max_output_tokens": 4096, + "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "output_cost_per_audio_token": 6.4e-05, + "output_cost_per_token": 2.4e-05, + "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure", + "supported_endpoints": [ + "/v1/realtime" + ], + "supported_modalities": [ + "text", + "image", + "audio" + ], + "supported_output_modalities": [ + "text", + "audio" + ], + "supports_audio_input": true, + "supports_audio_output": true, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "cache_read_input_image_token_cost": 5e-07, + "supports_prompt_caching": true, + "supports_reasoning": true + }, + "azure/gpt-realtime-2.1-mini-2026-07-07": { + "cache_creation_input_audio_token_cost": 3e-07, + "cache_read_input_audio_token_cost": 3e-07, + "cache_read_input_token_cost": 6e-08, + "deprecation_date": "2027-06-25", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "input_cost_per_audio_token": 1e-05, + "input_cost_per_image_token": 8e-07, + "input_cost_per_token": 6e-07, + "litellm_provider": "azure", + "max_input_tokens": 32000, + "max_output_tokens": 4096, + "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "output_cost_per_audio_token": 2e-05, + "output_cost_per_token": 2.4e-06, + "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure", + "supported_endpoints": [ + "/v1/realtime" + ], + "supported_modalities": [ + "text", + "image", + "audio" + ], + "supported_output_modalities": [ + "text", + "audio" + ], + "supports_audio_input": true, + "supports_audio_output": true, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "cache_read_input_image_token_cost": 8e-08, + "supports_prompt_caching": true, + "supports_reasoning": true + }, + "azure/gpt-realtime-translate-2026-05-06": { + "input_cost_per_second": 0.0005666666666666667, + "litellm_provider": "azure", + "max_input_tokens": 32000, + "max_output_tokens": 4096, + "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/a-new-chapter-for-realtime-ai-reasoning-translation-and-real-time-transcription/4517124", + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "audio", + "text" + ], + "supports_audio_input": true, + "supports_audio_output": true, + "supports_native_streaming": true + }, + "azure/gpt-realtime-translate-2026-05-07": { + "input_cost_per_second": 0.0005666666666666667, + "litellm_provider": "azure", + "max_input_tokens": 32000, + "max_output_tokens": 4096, + "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "source": "https://ai.azure.com/catalog/models/gpt-realtime-translate", + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "audio", + "text" + ], + "supports_audio_input": true, + "supports_audio_output": true, + "supports_native_streaming": true + }, + "azure/gpt-realtime-whisper-2026-05-06": { + "input_cost_per_second": 0.0002833333333333333, + "litellm_provider": "azure", + "mode": "audio_transcription", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/gpt-realtime-whisper", + "supported_endpoints": [ + "/v1/realtime", + "/v1/realtime/transcription_sessions" + ], + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "max_input_tokens": 32000, + "max_output_tokens": 4096 + }, + "azure/gpt-realtime-whisper-2026-05-07": { + "input_cost_per_second": 0.0002833333333333333, + "litellm_provider": "azure", + "mode": "audio_transcription", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/gpt-realtime-whisper", + "supported_endpoints": [ + "/v1/realtime", + "/v1/realtime/transcription_sessions" + ], + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "max_input_tokens": 32000, + "max_output_tokens": 4096 + }, "sample_spec": { "code_interpreter_cost_per_session": 0.0, "computer_use_input_cost_per_1k_tokens": 0.0, @@ -40,6 +208,7 @@ }, "1024-x-1024/50-steps/bedrock/amazon.nova-canvas-v1:0": { "deprecation_date": "2026-09-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "litellm_provider": "bedrock", "max_input_tokens": 2600, "mode": "image_generation", @@ -189,6 +358,7 @@ }, "ai21.jamba-1-5-large-v1:0": { "deprecation_date": "2026-11-26", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-ai21-labs-jamba-1-5-large.md", "input_cost_per_token": 2e-06, "litellm_provider": "bedrock", "max_input_tokens": 256000, @@ -199,6 +369,7 @@ }, "ai21.jamba-1-5-mini-v1:0": { "deprecation_date": "2026-11-26", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-ai21-labs-jamba-1-5-mini.md", "input_cost_per_token": 2e-07, "litellm_provider": "bedrock", "max_input_tokens": 256000, @@ -368,6 +539,7 @@ }, "amazon.nova-canvas-v1:0": { "deprecation_date": "2026-09-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "litellm_provider": "bedrock", "max_input_tokens": 2600, "mode": "image_generation", @@ -376,6 +548,7 @@ }, "us.amazon.nova-canvas-v1:0": { "deprecation_date": "2026-09-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "litellm_provider": "bedrock", "max_input_tokens": 2600, "mode": "image_generation", @@ -384,6 +557,7 @@ }, "us.writer.palmyra-x4-v1:0": { "deprecation_date": "2027-03-09", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-writer-palmyra-x4.md", "input_cost_per_token": 2.5e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -396,6 +570,7 @@ }, "us.writer.palmyra-x5-v1:0": { "deprecation_date": "2027-03-21", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-writer-palmyra-x5.md", "input_cost_per_token": 6e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -408,6 +583,7 @@ }, "writer.palmyra-x4-v1:0": { "deprecation_date": "2027-03-09", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-writer-palmyra-x4.md", "input_cost_per_token": 2.5e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -420,6 +596,7 @@ }, "writer.palmyra-x5-v1:0": { "deprecation_date": "2027-03-21", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-writer-palmyra-x5.md", "input_cost_per_token": 6e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -800,6 +977,7 @@ }, "twelvelabs.marengo-embed-2-7-v1:0": { "deprecation_date": "2026-11-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_query": 7e-05, "input_cost_per_video_per_second": 0.0007, "input_cost_per_audio_per_second": 0.00014, @@ -814,6 +992,7 @@ }, "us.twelvelabs.marengo-embed-2-7-v1:0": { "deprecation_date": "2026-11-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_query": 7e-05, "input_cost_per_video_per_second": 0.0007, "input_cost_per_audio_per_second": 0.00014, @@ -828,6 +1007,7 @@ }, "eu.twelvelabs.marengo-embed-2-7-v1:0": { "deprecation_date": "2026-11-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_query": 7e-05, "input_cost_per_video_per_second": 0.0007, "input_cost_per_audio_per_second": 0.00014, @@ -881,6 +1061,7 @@ }, "twelvelabs.pegasus-1-2-v1:0": { "deprecation_date": "2027-03-22", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-twelvelabs-pegasus-v1-2.md", "input_cost_per_video_per_second": 0.00049, "output_cost_per_token": 7.5e-06, "litellm_provider": "bedrock", @@ -890,6 +1071,7 @@ }, "us.twelvelabs.pegasus-1-2-v1:0": { "deprecation_date": "2027-03-22", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-twelvelabs-pegasus-v1-2.md", "input_cost_per_video_per_second": 0.00049, "output_cost_per_token": 7.5e-06, "litellm_provider": "bedrock", @@ -899,6 +1081,7 @@ }, "eu.twelvelabs.pegasus-1-2-v1:0": { "deprecation_date": "2027-03-22", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-twelvelabs-pegasus-v1-2.md", "input_cost_per_video_per_second": 0.00049, "output_cost_per_token": 7.5e-06, "litellm_provider": "bedrock", @@ -908,6 +1091,7 @@ }, "global.twelvelabs.pegasus-1-2-v1:0": { "deprecation_date": "2027-03-22", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-twelvelabs-pegasus-v1-2.md", "input_cost_per_video_per_second": 0.00049, "output_cost_per_token": 7.5e-06, "litellm_provider": "bedrock", @@ -1011,7 +1195,8 @@ "supports_native_streaming": true, "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, - "prompt_cache_min_tokens": 4096 + "prompt_cache_min_tokens": 4096, + "token_count_model": {"model":"anthropic.claude-haiku-4-5-20251001-v1:0","litellm_provider":"bedrock"} }, "anthropic.claude-3-5-sonnet-20240620-v1:0": { "input_cost_per_token": 3e-06, @@ -1111,6 +1296,7 @@ "cache_creation_input_token_cost": 1.875e-05, "cache_read_input_token_cost": 1.5e-06, "deprecation_date": "2027-01-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.5e-05, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -1939,6 +2125,7 @@ "anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -1971,12 +2158,14 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/index.json", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-east-1/index.json", "token_count_model": { "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "us-east-1" - } + }, + "input_cost_per_token_batches": 2.5e-06, + "output_cost_per_token_batches": 1.25e-05 }, "anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2025,6 +2214,7 @@ "global.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -2057,12 +2247,14 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-east-1/index.json", "token_count_model": { "model": "global.anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "us-east-1" - } + }, + "input_cost_per_token_batches": 2.5e-06, + "output_cost_per_token_batches": 1.25e-05 }, "global.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2111,6 +2303,7 @@ "us.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -2143,12 +2336,14 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-east-1/index.json", "token_count_model": { "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "us-east-1" - } + }, + "input_cost_per_token_batches": 2.75e-06, + "output_cost_per_token_batches": 1.375e-05 }, "us.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2197,6 +2392,7 @@ "eu.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -2229,12 +2425,14 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/eu-west-1/index.json", "token_count_model": { "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "eu-west-1" - } + }, + "input_cost_per_token_batches": 2.75e-06, + "output_cost_per_token_batches": 1.375e-05 }, "eu.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2278,6 +2476,7 @@ "au.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -2310,12 +2509,14 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/ap-southeast-2/index.json", "token_count_model": { "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "ap-southeast-4" - } + }, + "input_cost_per_token_batches": 2.75e-06, + "output_cost_per_token_batches": 1.375e-05 }, "au.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2364,6 +2565,7 @@ "jp.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -2396,7 +2598,9 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/" + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/ap-northeast-1/index.json", + "input_cost_per_token_batches": 2.75e-06, + "output_cost_per_token_batches": 1.375e-05 }, "jp.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2760,6 +2964,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -2804,6 +3009,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -2848,6 +3054,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -2892,6 +3099,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -2936,6 +3144,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -2980,6 +3189,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -3233,6 +3443,8 @@ "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-10-14", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "anthropic.claude-sonnet-5", "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -3276,6 +3488,8 @@ "cache_creation_input_token_cost_above_200k_tokens": 7.5e-06, "cache_read_input_token_cost_above_200k_tokens": 6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -3510,6 +3724,8 @@ "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-10-14", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "apac.anthropic.claude-sonnet-5", "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -3565,6 +3781,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "au.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -3598,6 +3816,7 @@ }, "azure/ada": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.1e-07, "litellm_provider": "azure", "max_input_tokens": 8191, @@ -3608,6 +3827,7 @@ "azure/codex-mini": { "cache_read_input_token_cost": 3.75e-07, "deprecation_date": "2026-11-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.5e-06, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -3635,19 +3855,10 @@ "supports_tool_choice": true, "supports_vision": true }, - "azure/command-r-plus": { - "deprecation_date": "2025-06-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_function_calling": true - }, "azure_ai/claude-haiku-4-5": { "deprecation_date": "2026-11-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/claude-haiku-5-5", "cache_creation_input_token_cost": 1.25e-06, "cache_creation_input_token_cost_above_1hr": 2e-06, "cache_read_input_token_cost": 1e-07, @@ -3671,6 +3882,8 @@ }, "azure_ai/claude-opus-4-5": { "deprecation_date": "2026-11-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/claude-opus-5-5", "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, @@ -3695,6 +3908,7 @@ }, "azure_ai/claude-opus-4-6": { "deprecation_date": "2027-02-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_adaptive_thinking": true, "supports_legacy_thinking": true, "input_cost_per_token": 5e-06, @@ -3726,6 +3940,7 @@ }, "azure_ai/claude-opus-4-7": { "deprecation_date": "2027-04-06", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_adaptive_thinking": true, "input_cost_per_token": 5e-06, "output_cost_per_token": 2.5e-05, @@ -3757,6 +3972,7 @@ }, "azure_ai/claude-fable-5": { "deprecation_date": "2027-12-05", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_mid_conversation_system": true, "input_cost_per_token": 1e-05, "output_cost_per_token": 5e-05, @@ -3785,7 +4001,7 @@ "supports_tool_choice": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true, - "supports_max_reasoning_effort": true, + "supports_max_reasoning_effort": false, "prompt_cache_min_tokens": 512 }, "azure_ai/claude-fable-5-1": { @@ -3819,14 +4035,47 @@ "supports_tool_choice": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true, - "supports_max_reasoning_effort": true, + "supports_max_reasoning_effort": false, "prompt_cache_min_tokens": 512, - "deprecation_date": "2027-12-05" + "deprecation_date": "2027-12-05", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement" + }, + "azure_ai/claude-mythos-5-1": { + "input_cost_per_token": 1e-05, + "output_cost_per_token": 5e-05, + "cache_creation_input_token_cost": 1.25e-05, + "cache_creation_input_token_cost_above_1hr": 2e-05, + "cache_read_input_token_cost": 2.5e-07, + "litellm_provider": "azure_ai", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "mode": "chat", + "supports_adaptive_thinking": true, + "thinking_always_on": true, + "supports_mid_conversation_system": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_forced_tool_use": false, + "supports_function_calling": true, + "supports_native_structured_output": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": false, + "prompt_cache_min_tokens": 512, + "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/claude-models" }, "azure_ai/claude-opus-5": { "deprecation_date": "2027-07-08", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "input_cost_per_token": 5e-06, "output_cost_per_token": 2.5e-05, "litellm_provider": "azure_ai", @@ -3893,6 +4142,7 @@ }, "azure_ai/claude-opus-4-8": { "deprecation_date": "2027-09-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, "input_cost_per_token": 5e-06, @@ -3925,6 +4175,8 @@ }, "azure_ai/claude-sonnet-4-5": { "deprecation_date": "2026-11-30", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/claude-sonnet-5-5", "cache_creation_input_token_cost": 3.75e-06, "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, @@ -3948,6 +4200,7 @@ }, "azure_ai/claude-sonnet-5": { "deprecation_date": "2027-06-30", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 2.5e-06, "cache_creation_input_token_cost_above_1hr": 4e-06, @@ -3964,6 +4217,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -3980,6 +4234,7 @@ }, "azure_ai/claude-sonnet-4-6": { "deprecation_date": "2027-02-10", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_adaptive_thinking": true, "supports_legacy_thinking": true, "cache_creation_input_token_cost": 3.75e-06, @@ -4040,6 +4295,7 @@ }, "azure_ai/gpt-oss-120b": { "deprecation_date": "2027-09-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.5e-07, "output_cost_per_token": 6e-07, "litellm_provider": "azure_ai", @@ -4295,6 +4551,7 @@ }, "azure_ai/gpt-5.5": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, "cache_read_input_token_cost_priority": 1e-06, @@ -4342,6 +4599,7 @@ "azure_ai/gpt-chat-latest": { "cache_read_input_token_cost": 5e-07, "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 5e-06, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -4376,6 +4634,7 @@ "cache_read_input_image_token_cost": 2e-06, "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-10-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_image_token": 8e-06, "input_cost_per_token": 5e-06, "litellm_provider": "azure_ai", @@ -4391,6 +4650,7 @@ "azure_ai/codex-mini": { "cache_read_input_token_cost": 3.75e-07, "deprecation_date": "2026-11-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.5e-06, "litellm_provider": "azure_ai", "max_input_tokens": 200000, @@ -4420,6 +4680,7 @@ }, "azure_ai/whisper": { "deprecation_date": "2026-12-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_second": 0.0001, "litellm_provider": "azure_ai", "mode": "audio_transcription", @@ -4473,6 +4734,7 @@ }, "azure_ai/gpt-5.5-2026-04-24": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, "cache_read_input_token_cost_priority": 1e-06, @@ -4519,6 +4781,8 @@ }, "azure_ai/gpt-5.4": { "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/gpt-5.5", "cache_read_input_token_cost": 2.5e-07, "cache_read_input_token_cost_above_272k_tokens": 5e-07, "cache_read_input_token_cost_priority": 5e-07, @@ -4566,6 +4830,8 @@ }, "azure_ai/gpt-5.4-2026-03-05": { "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/gpt-5.5", "cache_read_input_token_cost": 2.5e-07, "cache_read_input_token_cost_above_272k_tokens": 5e-07, "cache_read_input_token_cost_priority": 5e-07, @@ -4613,6 +4879,7 @@ }, "azure_ai/gpt-5.4-pro": { "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 3e-06, "cache_read_input_token_cost_above_272k_tokens": 6e-06, "cache_read_input_token_cost_priority": 6e-06, @@ -4658,6 +4925,7 @@ }, "azure_ai/gpt-5.4-pro-2026-03-05": { "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 3e-06, "cache_read_input_token_cost_above_272k_tokens": 6e-06, "cache_read_input_token_cost_priority": 6e-06, @@ -4703,6 +4971,7 @@ }, "azure_ai/gpt-5.4-mini": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 7.5e-08, "cache_read_input_token_cost_priority": 1.5e-07, "input_cost_per_token": 7.5e-07, @@ -4744,6 +5013,7 @@ }, "azure_ai/gpt-5.4-mini-2026-03-17": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 7.5e-08, "cache_read_input_token_cost_priority": 1.5e-07, "input_cost_per_token": 7.5e-07, @@ -4785,6 +5055,7 @@ }, "azure_ai/gpt-5.4-nano": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_priority": 4e-08, "input_cost_per_token": 2e-07, @@ -4826,6 +5097,7 @@ }, "azure_ai/gpt-5.4-nano-2026-03-17": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_priority": 4e-08, "input_cost_per_token": 2e-07, @@ -4867,6 +5139,7 @@ }, "azure_ai/model_router": { "deprecation_date": "2027-05-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.4e-07, "output_cost_per_token": 0, "litellm_provider": "azure_ai", @@ -4878,6 +5151,7 @@ }, "azure_ai/model-router": { "deprecation_date": "2027-05-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.4e-07, "output_cost_per_token": 0, "litellm_provider": "azure_ai", @@ -4889,6 +5163,8 @@ }, "azure/eu/gpt-4o-2024-08-06": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, "input_cost_per_token_batches": 1.375e-06, @@ -4908,6 +5184,8 @@ }, "azure/eu/gpt-4o": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "cache_creation_input_token_cost": 1.38e-06, "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, @@ -4927,6 +5205,8 @@ }, "azure/eu/gpt-4o-2024-11-20": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "cache_creation_input_token_cost": 1.38e-06, "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, @@ -4947,6 +5227,7 @@ "azure/eu/gpt-4o-mini": { "cache_read_input_token_cost": 8.3e-08, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.65e-07, "input_cost_per_token_batches": 8.3e-08, "litellm_provider": "azure", @@ -4970,6 +5251,7 @@ "azure/eu/gpt-4o-mini-2024-07-18": { "cache_read_input_token_cost": 8.3e-08, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.65e-07, "input_cost_per_token_batches": 8.3e-08, "litellm_provider": "azure", @@ -5008,26 +5290,6 @@ "supports_system_messages": true, "supports_tool_choice": true }, - "azure/eu/gpt-4o-realtime-preview-2024-10-01": { - "cache_creation_input_audio_token_cost": 2.2e-05, - "cache_read_input_token_cost": 2.75e-06, - "deprecation_date": "2025-03-26", - "input_cost_per_audio_token": 0.00011, - "input_cost_per_token": 5.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 0.00022, - "output_cost_per_token": 2.2e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "azure/eu/gpt-4o-realtime-preview-2024-12-17": { "cache_read_input_audio_token_cost": 2.5e-06, "cache_read_input_token_cost": 2.75e-06, @@ -5059,6 +5321,8 @@ "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_priority": 2.75e-07, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "input_cost_per_token": 1.375e-06, "input_cost_per_token_batches": 6.875e-07, "input_cost_per_token_priority": 2.75e-06, @@ -5102,7 +5366,9 @@ "azure/eu/gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.75e-08, "cache_read_input_token_cost_priority": 4.95e-08, - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.4-mini", "input_cost_per_token": 2.75e-07, "input_cost_per_token_batches": 1.375e-07, "input_cost_per_token_priority": 4.95e-07, @@ -5144,7 +5410,9 @@ "cache_read_input_token_cost_batches": 1.375e-08 }, "azure/eu/gpt-5.1": { - "deprecation_date": "2027-05-15", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.2", "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_batches": 6.875e-08, "cache_read_input_token_cost_priority": 2.75e-07, @@ -5192,6 +5460,8 @@ }, "azure/eu/gpt-5.1-codex": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.2-codex", "cache_read_input_token_cost": 1.375e-07, "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", @@ -5223,6 +5493,7 @@ }, "azure/eu/gpt-5.1-codex-mini": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.75e-08, "input_cost_per_token": 2.75e-07, "litellm_provider": "azure", @@ -5255,6 +5526,8 @@ "azure/eu/gpt-5-nano-2025-08-07": { "cache_read_input_token_cost": 5.5e-09, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.4-nano", "input_cost_per_token": 5.5e-08, "input_cost_per_token_batches": 2.75e-08, "litellm_provider": "azure", @@ -5296,6 +5569,7 @@ "azure/eu/o1": { "cache_read_input_token_cost": 8.25e-06, "deprecation_date": "2026-11-19", + "successor_model": "azure/eu/gpt-5.6-sol", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -5314,6 +5588,7 @@ "azure/eu/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, "deprecation_date": "2026-11-19", + "successor_model": "azure/eu/gpt-5.6-sol", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -5348,6 +5623,8 @@ "azure/eu/o3-mini": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -5365,6 +5642,8 @@ "azure/eu/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -5382,6 +5661,7 @@ "azure/global-standard/gpt-4o-2024-08-06": { "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, "litellm_provider": "azure", @@ -5401,6 +5681,7 @@ "azure/global-standard/gpt-4o-2024-11-20": { "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, "litellm_provider": "azure", @@ -5418,6 +5699,7 @@ }, "azure/global-standard/gpt-4o-mini": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.5e-07, "litellm_provider": "azure", "max_input_tokens": 128000, @@ -5437,6 +5719,8 @@ }, "azure/global/gpt-4o-2024-08-06": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/global/gpt-5.1", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -5456,6 +5740,8 @@ }, "azure/global/gpt-4o-2024-11-20": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/global/gpt-5.1", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -5474,7 +5760,8 @@ "supports_vision": true }, "azure/global/gpt-5.1": { - "deprecation_date": "2027-05-15", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, @@ -5522,6 +5809,7 @@ }, "azure/global/gpt-5.1-codex": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", @@ -5553,6 +5841,7 @@ }, "azure/global/gpt-5.1-codex-mini": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_token": 2.5e-07, "litellm_provider": "azure", @@ -5611,29 +5900,6 @@ "supports_function_calling": true, "supports_tool_choice": true }, - "azure/gpt-35-turbo-16k": { - "deprecation_date": "2025-04-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "azure", - "max_input_tokens": 16385, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 4e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_tool_choice": true - }, - "azure/gpt-35-turbo-16k-0613": { - "deprecation_date": "2025-04-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "azure", - "max_input_tokens": 16385, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 4e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_function_calling": true, - "supports_tool_choice": true - }, "azure/gpt-35-turbo-instruct": { "input_cost_per_token": 1.65e-06, "litellm_provider": "azure_text", @@ -5652,18 +5918,6 @@ "output_cost_per_token": 2.2e-06, "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/" }, - "azure/gpt-4": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 3e-05, - "litellm_provider": "azure", - "max_input_tokens": 8192, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_function_calling": true, - "supports_tool_choice": true - }, "azure/gpt-4-0125-preview": { "input_cost_per_token": 1e-05, "litellm_provider": "azure", @@ -5675,18 +5929,6 @@ "supports_parallel_function_calling": true, "supports_tool_choice": true }, - "azure/gpt-4-0613": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 3e-05, - "litellm_provider": "azure", - "max_input_tokens": 8192, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_function_calling": true, - "supports_tool_choice": true - }, "azure/gpt-4-1106-preview": { "input_cost_per_token": 1e-05, "litellm_provider": "azure", @@ -5698,28 +5940,6 @@ "supports_parallel_function_calling": true, "supports_tool_choice": true }, - "azure/gpt-4-32k": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 6e-05, - "litellm_provider": "azure", - "max_input_tokens": 32768, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 0.00012, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_tool_choice": true - }, - "azure/gpt-4-32k-0613": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 6e-05, - "litellm_provider": "azure", - "max_input_tokens": 32768, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 0.00012, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_tool_choice": true - }, "azure/gpt-4-turbo": { "input_cost_per_token": 1.1e-05, "litellm_provider": "azure", @@ -5758,6 +5978,8 @@ }, "azure/gpt-4.1": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "input_cost_per_token": 2e-06, @@ -5800,6 +6022,8 @@ }, "azure/gpt-4.1-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "input_cost_per_token": 2e-06, @@ -5842,6 +6066,8 @@ }, "azure/gpt-4.1-mini": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-mini", "cache_read_input_token_cost": 1e-07, "cache_read_input_token_cost_priority": 1.75e-07, "input_cost_per_token": 4e-07, @@ -5884,6 +6110,8 @@ }, "azure/gpt-4.1-mini-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-mini", "cache_read_input_token_cost": 1e-07, "cache_read_input_token_cost_priority": 1.75e-07, "input_cost_per_token": 4e-07, @@ -5926,6 +6154,8 @@ }, "azure/gpt-4.1-nano": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-nano", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_token": 1e-07, "input_cost_per_token_batches": 5e-08, @@ -5959,6 +6189,8 @@ }, "azure/gpt-4.1-nano-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-nano", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_token": 1e-07, "input_cost_per_token_batches": 5e-08, @@ -5990,28 +6222,10 @@ "supports_tool_choice": true, "supports_vision": true }, - "azure/gpt-4.5-preview": { - "cache_read_input_token_cost": 3.75e-05, - "deprecation_date": "2025-07-14", - "input_cost_per_token": 7.5e-05, - "input_cost_per_token_batches": 3.75e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 0.00015, - "output_cost_per_token_batches": 7.5e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "azure/gpt-4o": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -6030,7 +6244,9 @@ "supports_vision": true }, "azure/gpt-4o-2024-05-13": { - "deprecation_date": "2026-12-09", + "deprecation_date": "2027-01-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "input_cost_per_token": 5e-06, "input_cost_per_token_batches": 2.5e-06, "litellm_provider": "azure", @@ -6048,6 +6264,8 @@ }, "azure/gpt-4o-2024-08-06": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -6067,6 +6285,8 @@ }, "azure/gpt-4o-2024-11-20": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -6086,6 +6306,7 @@ }, "azure/gpt-audio": { "deprecation_date": "2027-03-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 4e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6119,6 +6340,7 @@ }, "azure/gpt-audio-2025-08-28": { "deprecation_date": "2027-03-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 4e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6151,6 +6373,7 @@ }, "azure/gpt-audio-1.5": { "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6184,6 +6407,7 @@ }, "azure/gpt-audio-1.5-2026-02-23": { "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6218,6 +6442,7 @@ }, "azure/gpt-audio-mini": { "deprecation_date": "2027-06-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, "litellm_provider": "azure", @@ -6250,6 +6475,7 @@ }, "azure/gpt-audio-mini-2025-10-06": { "deprecation_date": "2027-04-06", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, "litellm_provider": "azure", @@ -6314,6 +6540,7 @@ }, "azure/gpt-4o-mini": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 7.5e-08, "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, @@ -6339,6 +6566,7 @@ "azure/gpt-4o-mini-2024-07-18": { "cache_read_input_token_cost": 7.5e-08, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, "litellm_provider": "azure", @@ -6415,6 +6643,7 @@ "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-03-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -6424,6 +6653,9 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6449,6 +6681,7 @@ "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-03-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -6458,6 +6691,9 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6482,6 +6718,8 @@ "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-realtime-2.1-2026-07-07", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -6491,6 +6729,9 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6516,6 +6757,8 @@ "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-realtime-2.1-2026-07-07", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -6525,6 +6768,9 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6547,8 +6793,10 @@ "azure/gpt-realtime-2.1": { "cache_creation_input_audio_token_cost": 4e-07, "cache_read_input_audio_token_cost": 4e-07, + "cache_read_input_image_token_cost": 5e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-06-25", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -6556,6 +6804,9 @@ "max_input_tokens": 32000, "max_output_tokens": 4096, "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 2.4e-05, "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", @@ -6575,14 +6826,18 @@ "supports_audio_output": true, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, "supports_system_messages": true, "supports_tool_choice": true }, "azure/gpt-realtime-2.1-mini": { "cache_creation_input_audio_token_cost": 3e-07, "cache_read_input_audio_token_cost": 3e-07, + "cache_read_input_image_token_cost": 8e-08, "cache_read_input_token_cost": 6e-08, "deprecation_date": "2027-06-25", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, "input_cost_per_token": 6e-07, @@ -6590,6 +6845,9 @@ "max_input_tokens": 32000, "max_output_tokens": 4096, "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", @@ -6609,6 +6867,8 @@ "supports_audio_output": true, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, "supports_system_messages": true, "supports_tool_choice": true }, @@ -6617,6 +6877,7 @@ "cache_read_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 6e-08, "deprecation_date": "2027-06-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, "input_cost_per_token": 6e-07, @@ -6626,6 +6887,9 @@ "mode": "realtime", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6650,6 +6914,7 @@ "cache_read_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 6e-08, "deprecation_date": "2027-04-06", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, "input_cost_per_token": 6e-07, @@ -6659,6 +6924,9 @@ "mode": "realtime", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6680,6 +6948,7 @@ }, "azure/gpt-4o-mini-transcribe": { "deprecation_date": "2027-06-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", @@ -6693,6 +6962,7 @@ }, "azure/gpt-4o-mini-tts": { "deprecation_date": "2027-06-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 6e-07, "litellm_provider": "azure", "mode": "audio_speech", @@ -6710,26 +6980,6 @@ "audio" ] }, - "azure/gpt-4o-realtime-preview-2024-10-01": { - "cache_creation_input_audio_token_cost": 2e-05, - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2025-03-26", - "input_cost_per_audio_token": 0.0001, - "input_cost_per_token": 5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 0.0002, - "output_cost_per_token": 2e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "azure/gpt-4o-realtime-preview-2024-12-17": { "cache_read_input_token_cost": 2.5e-06, "input_cost_per_audio_token": 4e-05, @@ -6758,6 +7008,7 @@ }, "azure/gpt-4o-transcribe": { "deprecation_date": "2026-10-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 6e-06, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6772,6 +7023,7 @@ }, "azure/gpt-4o-transcribe-diarize": { "deprecation_date": "2027-04-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 6e-06, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6791,6 +7043,9 @@ "max_input_tokens": 32000, "max_output_tokens": 4096, "mode": "audio_transcription", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/gpt-realtime-whisper", "supported_endpoints": [ "/v1/realtime", @@ -6807,7 +7062,9 @@ "azure/gpt-5.1-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, - "deprecation_date": "2027-05-15", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.2", "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "azure", @@ -6855,6 +7112,8 @@ "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.2-codex", "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "azure", @@ -6889,6 +7148,7 @@ "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.5e-07, "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "azure", @@ -6921,6 +7181,8 @@ }, "azure/gpt-5": { "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, @@ -6967,6 +7229,8 @@ "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "input_cost_per_token": 1.25e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_priority": 2.5e-06, @@ -7010,6 +7274,8 @@ "azure/gpt-5-codex": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2027-03-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1-codex", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", "max_input_tokens": 272000, @@ -7039,7 +7305,9 @@ "supports_vision": true }, "azure/gpt-5-mini": { - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-mini", "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, @@ -7085,7 +7353,9 @@ "azure/gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_priority": 4.5e-08, - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-mini", "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_priority": 4.5e-07, @@ -7128,6 +7398,8 @@ }, "azure/gpt-5-nano": { "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-nano", "cache_read_input_token_cost": 5e-09, "cache_read_input_token_cost_batches": 2.5e-09, "input_cost_per_token": 5e-08, @@ -7170,6 +7442,8 @@ "azure/gpt-5-nano-2025-08-07": { "cache_read_input_token_cost": 5e-09, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-nano", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 2.5e-08, "litellm_provider": "azure", @@ -7210,6 +7484,8 @@ }, "azure/gpt-5-pro": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.2-pro", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "azure", @@ -7245,7 +7521,9 @@ "supports_vision": true }, "azure/gpt-5.1": { - "deprecation_date": "2027-05-15", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.2", "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, @@ -7294,6 +7572,8 @@ "azure/gpt-5-chat": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", "max_input_tokens": 128000, @@ -7318,6 +7598,8 @@ "azure/gpt-5.1-chat": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7339,6 +7621,8 @@ "azure/gpt-5.2-chat": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.75e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7359,6 +7643,8 @@ "azure/gpt-5.3-chat": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.75e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7379,6 +7665,8 @@ "azure/us/gpt-5.1-chat": { "cache_read_input_token_cost": 1.375e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-chat-latest", "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7400,6 +7688,8 @@ "azure/us/gpt-5.2-chat": { "cache_read_input_token_cost": 1.925e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-chat-latest", "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7420,6 +7710,8 @@ "azure/us/gpt-5.3-chat": { "cache_read_input_token_cost": 1.925e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-chat-latest", "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7440,6 +7732,8 @@ "azure/eu/gpt-5.1-chat": { "cache_read_input_token_cost": 1.375e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7461,6 +7755,8 @@ "azure/eu/gpt-5.2-chat": { "cache_read_input_token_cost": 1.925e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7481,6 +7777,8 @@ "azure/eu/gpt-5.3-chat": { "cache_read_input_token_cost": 1.925e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7498,38 +7796,10 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "azure/us/o1-preview": { - "cache_read_input_token_cost": 8.25e-06, - "deprecation_date": "2025-07-28", - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions" - ], - "supports_prompt_caching": true - }, - "azure/eu/o1-preview": { - "cache_read_input_token_cost": 8.25e-06, - "deprecation_date": "2025-07-28", - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions" - ], - "supports_prompt_caching": true - }, "azure/gpt-5.1-codex": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.2-codex", "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", @@ -7562,6 +7832,7 @@ "azure/gpt-5.1-codex-max": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", "max_input_tokens": 272000, @@ -7592,6 +7863,7 @@ }, "azure/gpt-5.1-codex-mini": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_token": 2.5e-07, "litellm_provider": "azure", @@ -7623,6 +7895,8 @@ }, "azure/gpt-5.2": { "deprecation_date": "2027-06-08", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4", "cache_read_input_token_cost": 1.75e-07, "cache_read_input_token_cost_batches": 8.75e-08, "cache_read_input_token_cost_priority": 3.5e-07, @@ -7670,6 +7944,8 @@ "cache_read_input_token_cost": 1.75e-07, "cache_read_input_token_cost_priority": 3.5e-07, "deprecation_date": "2027-06-08", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4", "input_cost_per_token": 1.75e-06, "input_cost_per_token_batches": 8.75e-07, "input_cost_per_token_priority": 3.5e-06, @@ -7714,6 +7990,8 @@ "azure/gpt-5.2-codex": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.3-codex", "input_cost_per_token": 1.75e-06, "litellm_provider": "azure", "max_input_tokens": 272000, @@ -7746,6 +8024,7 @@ "cache_read_input_token_cost": 1.75e-07, "cache_read_input_token_cost_priority": 3.5e-07, "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.75e-06, "input_cost_per_token_priority": 3.5e-06, "litellm_provider": "azure", @@ -7859,6 +8138,8 @@ }, "azure/gpt-5.4": { "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.5", "cache_read_input_token_cost": 2.5e-07, "cache_read_input_token_cost_above_272k_tokens": 5e-07, "cache_read_input_token_cost_above_272k_tokens_batches": 2.5e-07, @@ -7916,6 +8197,8 @@ }, "azure/us/gpt-5.4": { "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.5", "cache_read_input_token_cost": 2.75e-07, "cache_read_input_token_cost_above_272k_tokens": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens_batches": 2.75e-07, @@ -7965,6 +8248,8 @@ }, "azure/eu/gpt-5.4": { "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.5", "cache_read_input_token_cost": 2.75e-07, "cache_read_input_token_cost_above_272k_tokens": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens_batches": 2.75e-07, @@ -8019,6 +8304,8 @@ "cache_read_input_token_cost_priority": 5e-07, "cache_read_input_token_cost_above_272k_tokens_priority": 1e-06, "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.5", "input_cost_per_token": 2.5e-06, "input_cost_per_token_above_272k_tokens": 5e-06, "input_cost_per_token_priority": 5e-06, @@ -8074,6 +8361,8 @@ "cache_read_input_token_cost_above_272k_tokens": 5.5e-07, "cache_read_input_token_cost_priority": 5.5e-07, "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.5", "input_cost_per_token": 2.75e-06, "input_cost_per_token_priority": 5.5e-06, "output_cost_per_token": 1.65e-05, @@ -8123,6 +8412,8 @@ "cache_read_input_token_cost_above_272k_tokens": 5.5e-07, "cache_read_input_token_cost_priority": 5.5e-07, "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.5", "input_cost_per_token": 2.75e-06, "input_cost_per_token_priority": 5.5e-06, "output_cost_per_token": 1.65e-05, @@ -8169,6 +8460,8 @@ }, "azure/gpt-5.4-pro": { "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.5-pro", "cache_read_input_token_cost": 3e-06, "cache_read_input_token_cost_above_272k_tokens": 6e-06, "input_cost_per_token": 3e-05, @@ -8220,6 +8513,8 @@ "cache_read_input_token_cost": 3e-06, "cache_read_input_token_cost_above_272k_tokens": 6e-06, "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.5-pro", "input_cost_per_token": 3e-05, "input_cost_per_token_above_272k_tokens": 6e-05, "input_cost_per_token_above_272k_tokens_flex": 3e-05, @@ -8332,6 +8627,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06, "cache_read_input_token_cost_flex": 2e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6-sol", "input_cost_per_token": 4e-06, "input_cost_per_token_above_272k_tokens": 8e-06, "input_cost_per_token_above_272k_tokens_flex": 4e-06, @@ -8395,6 +8692,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06, "cache_read_input_token_cost_flex": 2e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6-sol", "input_cost_per_token": 4e-06, "input_cost_per_token_above_272k_tokens": 8e-06, "input_cost_per_token_above_272k_tokens_flex": 4e-06, @@ -8458,6 +8757,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8e-07, "cache_read_input_token_cost_flex": 1e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6.1-terra", "input_cost_per_token": 2e-06, "input_cost_per_token_above_272k_tokens": 4e-06, "input_cost_per_token_above_272k_tokens_flex": 2e-06, @@ -8521,6 +8822,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8e-07, "cache_read_input_token_cost_flex": 1e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6.1-terra", "input_cost_per_token": 2e-06, "input_cost_per_token_above_272k_tokens": 4e-06, "input_cost_per_token_above_272k_tokens_flex": 2e-06, @@ -8584,6 +8887,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8e-08, "cache_read_input_token_cost_flex": 1e-08, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6-luna", "input_cost_per_token": 2e-07, "input_cost_per_token_above_272k_tokens": 4e-07, "input_cost_per_token_above_272k_tokens_flex": 2e-07, @@ -8647,6 +8952,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8e-08, "cache_read_input_token_cost_flex": 1e-08, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6-luna", "input_cost_per_token": 2e-07, "input_cost_per_token_above_272k_tokens": 4e-07, "input_cost_per_token_above_272k_tokens_flex": 2e-07, @@ -8710,11 +9017,7 @@ "mode": "chat", "output_cost_per_token": 5e-05, "output_cost_per_token_above_272k_tokens": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", "supported_endpoints": [ "/v1/chat/completions", @@ -8746,7 +9049,11 @@ "cache_creation_input_token_cost_above_272k_tokens_flex": 1.25e-05, "cache_read_input_token_cost_above_272k_tokens_flex": 1e-06, "input_cost_per_token_above_272k_tokens_flex": 1e-05, - "output_cost_per_token_above_272k_tokens_flex": 3.75e-05 + "output_cost_per_token_above_272k_tokens_flex": 3.75e-05, + "input_cost_per_token_flex": 5e-06, + "output_cost_per_token_flex": 2.5e-05, + "cache_read_input_token_cost_flex": 5e-07, + "cache_creation_input_token_cost_flex": 6.25e-06 }, "azure/gpt-6-astra-2026-09-03": { "cache_creation_input_token_cost": 1.25e-05, @@ -8762,11 +9069,7 @@ "mode": "chat", "output_cost_per_token": 5e-05, "output_cost_per_token_above_272k_tokens": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", "supported_endpoints": [ "/v1/chat/completions", @@ -8798,7 +9101,11 @@ "cache_creation_input_token_cost_above_272k_tokens_flex": 1.25e-05, "cache_read_input_token_cost_above_272k_tokens_flex": 1e-06, "input_cost_per_token_above_272k_tokens_flex": 1e-05, - "output_cost_per_token_above_272k_tokens_flex": 3.75e-05 + "output_cost_per_token_above_272k_tokens_flex": 3.75e-05, + "input_cost_per_token_flex": 5e-06, + "output_cost_per_token_flex": 2.5e-05, + "cache_read_input_token_cost_flex": 5e-07, + "cache_creation_input_token_cost_flex": 6.25e-06 }, "azure/gpt-6-luna": { "cache_creation_input_token_cost": 1.25e-07, @@ -8814,12 +9121,8 @@ "mode": "chat", "output_cost_per_token": 5e-07, "output_cost_per_token_above_272k_tokens": 7.5e-07, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, - "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -8846,7 +9149,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "cache_creation_input_token_cost_above_272k_tokens_flex": 1.25e-07, + "cache_creation_input_token_cost_flex": 6.25e-08, + "cache_read_input_token_cost_above_272k_tokens_flex": 1e-08, + "cache_read_input_token_cost_flex": 5e-09, + "input_cost_per_token_above_272k_tokens_flex": 1e-07, + "input_cost_per_token_flex": 5e-08, + "output_cost_per_token_above_272k_tokens_flex": 3.75e-07, + "output_cost_per_token_flex": 2.5e-07 }, "azure/gpt-6-luna-2026-09-22": { "cache_creation_input_token_cost": 1.25e-07, @@ -8862,12 +9173,8 @@ "mode": "chat", "output_cost_per_token": 5e-07, "output_cost_per_token_above_272k_tokens": 7.5e-07, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, - "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -8894,7 +9201,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "cache_creation_input_token_cost_above_272k_tokens_flex": 1.25e-07, + "cache_creation_input_token_cost_flex": 6.25e-08, + "cache_read_input_token_cost_above_272k_tokens_flex": 1e-08, + "cache_read_input_token_cost_flex": 5e-09, + "input_cost_per_token_above_272k_tokens_flex": 1e-07, + "input_cost_per_token_flex": 5e-08, + "output_cost_per_token_above_272k_tokens_flex": 3.75e-07, + "output_cost_per_token_flex": 2.5e-07 }, "azure/gpt-6-sol": { "cache_creation_input_token_cost": 2.5e-06, @@ -8946,7 +9261,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 5e-06, + "cache_read_input_token_cost_flex": 1e-07, + "cache_creation_input_token_cost_flex": 1.25e-06, + "input_cost_per_token_above_272k_tokens_flex": 2e-06, + "output_cost_per_token_above_272k_tokens_flex": 7.5e-06, + "cache_read_input_token_cost_above_272k_tokens_flex": 2e-07, + "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06 }, "azure/gpt-6-sol-2026-09-22": { "cache_creation_input_token_cost": 2.5e-06, @@ -8998,7 +9321,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 5e-06, + "cache_read_input_token_cost_flex": 1e-07, + "cache_creation_input_token_cost_flex": 1.25e-06, + "input_cost_per_token_above_272k_tokens_flex": 2e-06, + "output_cost_per_token_above_272k_tokens_flex": 7.5e-06, + "cache_read_input_token_cost_above_272k_tokens_flex": 2e-07, + "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06 }, "azure/gpt-6.1-terra": { "cache_creation_input_token_cost": 1.25e-06, @@ -9061,11 +9392,7 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_above_272k_tokens": 1.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ "/v1/chat/completions", @@ -9093,7 +9420,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 5e-06, + "cache_read_input_token_cost_flex": 5e-08, + "cache_creation_input_token_cost_flex": 1.25e-06, + "input_cost_per_token_above_272k_tokens_flex": 2e-06, + "output_cost_per_token_above_272k_tokens_flex": 7.5e-06, + "cache_read_input_token_cost_above_272k_tokens_flex": 1e-07, + "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06 }, "azure/gpt-6.1-sol-2026-09-29": { "cache_creation_input_token_cost": 2.5e-06, @@ -9109,11 +9444,7 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_above_272k_tokens": 1.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ "/v1/chat/completions", @@ -9141,7 +9472,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 5e-06, + "cache_read_input_token_cost_flex": 5e-08, + "cache_creation_input_token_cost_flex": 1.25e-06, + "input_cost_per_token_above_272k_tokens_flex": 2e-06, + "output_cost_per_token_above_272k_tokens_flex": 7.5e-06, + "cache_read_input_token_cost_above_272k_tokens_flex": 1e-07, + "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06 }, "azure/us/gpt-6.1-terra": { "cache_creation_input_token_cost": 1.375e-06, @@ -9431,6 +9770,7 @@ "azure/gpt-chat-latest": { "cache_read_input_token_cost": 5e-07, "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 5e-06, "litellm_provider": "azure", "max_input_tokens": 128000, @@ -9563,6 +9903,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 1.76e-06, "cache_read_input_token_cost_priority": 8.8e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-6-sol", "input_cost_per_token": 4.4e-06, "input_cost_per_token_above_272k_tokens": 8.8e-06, "input_cost_per_token_above_272k_tokens_priority": 1.76e-05, @@ -9618,6 +9960,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8.8e-07, "cache_read_input_token_cost_priority": 4.4e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-6.1-terra", "input_cost_per_token": 2.2e-06, "input_cost_per_token_above_272k_tokens": 4.4e-06, "input_cost_per_token_above_272k_tokens_priority": 8.8e-06, @@ -9673,6 +10017,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8.8e-08, "cache_read_input_token_cost_priority": 4.4e-08, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-6-luna", "input_cost_per_token": 2.2e-07, "input_cost_per_token_above_272k_tokens": 4.4e-07, "input_cost_per_token_above_272k_tokens_priority": 8.8e-07, @@ -9869,6 +10215,7 @@ "azure/us/gpt-chat-latest": { "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 5.5e-06, "litellm_provider": "azure", "max_input_tokens": 128000, @@ -9965,6 +10312,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 1.76e-06, "cache_read_input_token_cost_priority": 8.8e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-6-sol", "input_cost_per_token": 4.4e-06, "input_cost_per_token_above_272k_tokens": 8.8e-06, "input_cost_per_token_above_272k_tokens_priority": 1.76e-05, @@ -10020,6 +10369,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8.8e-07, "cache_read_input_token_cost_priority": 4.4e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-6.1-terra", "input_cost_per_token": 2.2e-06, "input_cost_per_token_above_272k_tokens": 4.4e-06, "input_cost_per_token_above_272k_tokens_priority": 8.8e-06, @@ -10075,6 +10426,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8.8e-08, "cache_read_input_token_cost_priority": 4.4e-08, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-6-luna", "input_cost_per_token": 2.2e-07, "input_cost_per_token_above_272k_tokens": 4.4e-07, "input_cost_per_token_above_272k_tokens_priority": 8.8e-07, @@ -10122,6 +10475,8 @@ }, "azure/gpt-5.5": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, "cache_read_input_token_cost_above_272k_tokens_batches": 5e-07, @@ -10182,6 +10537,8 @@ }, "azure/us/gpt-5.5": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens": 1.1e-06, "cache_read_input_token_cost_above_272k_tokens_batches": 5.5e-07, @@ -10236,6 +10593,8 @@ }, "azure/eu/gpt-5.5": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens": 1.1e-06, "cache_read_input_token_cost_above_272k_tokens_batches": 5.5e-07, @@ -10337,6 +10696,8 @@ "supports_vision": true, "supports_web_search": true, "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6", "input_cost_per_token_above_272k_tokens_batches": 5e-06, "input_cost_per_token_above_272k_tokens_flex": 5e-06, "input_cost_per_token_batches": 2.5e-06, @@ -10347,6 +10708,8 @@ }, "azure/gpt-5.5-2026-04-24": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, "cache_read_input_token_cost_priority": 1.25e-06, @@ -10450,6 +10813,8 @@ "supports_vision": true, "supports_web_search": true, "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6", "input_cost_per_token_above_272k_tokens_batches": 5.5e-06, "input_cost_per_token_batches": 2.75e-06, "output_cost_per_token_above_272k_tokens_batches": 2.475e-05, @@ -10458,6 +10823,8 @@ }, "azure/us/gpt-5.5-2026-04-24": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens": 1.1e-06, "cache_read_input_token_cost_priority": 1.375e-06, @@ -10555,6 +10922,8 @@ "supports_vision": true, "supports_web_search": true, "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6", "input_cost_per_token_above_272k_tokens_batches": 5.5e-06, "input_cost_per_token_batches": 2.75e-06, "output_cost_per_token_above_272k_tokens_batches": 2.475e-05, @@ -10563,6 +10932,8 @@ }, "azure/eu/gpt-5.5-2026-04-24": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens": 1.1e-06, "cache_read_input_token_cost_priority": 1.375e-06, @@ -10699,6 +11070,7 @@ }, "azure/gpt-5.4-mini": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 7.5e-08, "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, @@ -10753,6 +11125,7 @@ "cache_read_input_token_cost_flex": 3.75e-08, "cache_read_input_token_cost_priority": 1.5e-07, "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 7.5e-07, "litellm_provider": "azure", "max_input_tokens": 272000, @@ -10801,6 +11174,7 @@ }, "azure/gpt-5.4-nano": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_batches": 1e-08, "cache_read_input_token_cost_flex": 1e-08, @@ -10851,6 +11225,7 @@ "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_flex": 1e-08, "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2e-07, "litellm_provider": "azure", "max_input_tokens": 272000, @@ -10899,6 +11274,8 @@ "cache_read_input_image_token_cost": 2.5e-06, "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-image-1.5", "input_cost_per_image_token": 1e-05, "input_cost_per_token": 5e-06, "litellm_provider": "azure", @@ -10933,6 +11310,7 @@ }, "azure/high/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.59263611e-07, "litellm_provider": "azure", "mode": "image_generation", @@ -10943,6 +11321,7 @@ }, "azure/high/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.58945719e-07, "litellm_provider": "azure", "mode": "image_generation", @@ -10953,6 +11332,7 @@ }, "azure/high/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.58945719e-07, "litellm_provider": "azure", "mode": "image_generation", @@ -10963,6 +11343,7 @@ }, "azure/low/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.0490417e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -10973,6 +11354,7 @@ }, "azure/low/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.0172526e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -10983,6 +11365,7 @@ }, "azure/low/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.0172526e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -10993,6 +11376,7 @@ }, "azure/medium/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11003,6 +11387,7 @@ }, "azure/medium/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11013,6 +11398,7 @@ }, "azure/medium/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11025,6 +11411,7 @@ "cache_read_input_image_token_cost": 2.5e-07, "cache_read_input_token_cost": 2e-07, "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_image_token": 2.5e-06, "input_cost_per_token": 2e-06, "litellm_provider": "azure", @@ -11039,6 +11426,8 @@ "azure/gpt-image-1.5": { "cache_read_input_image_token_cost": 2e-06, "deprecation_date": "2026-12-16", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-image-2", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, @@ -11056,6 +11445,8 @@ "cache_read_input_image_token_cost": 2e-06, "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2026-12-16", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-image-2", "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, "litellm_provider": "azure", @@ -11071,6 +11462,7 @@ "azure/gpt-image-2": { "cache_read_input_image_token_cost": 2e-06, "deprecation_date": "2027-10-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, @@ -11088,6 +11480,7 @@ "azure/gpt-image-2.5-flare": { "cache_read_input_image_token_cost": 2e-06, "deprecation_date": "2027-09-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, @@ -11105,6 +11498,7 @@ "azure/gpt-image-2.5-sunburst": { "cache_read_input_image_token_cost": 2e-06, "deprecation_date": "2027-09-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, @@ -11123,6 +11517,7 @@ "cache_read_input_image_token_cost": 2e-06, "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-10-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, "litellm_provider": "azure", @@ -11138,6 +11533,7 @@ }, "azure/low/1024-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 2.0751953125e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11148,6 +11544,7 @@ }, "azure/low/1024-x-1536/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 2.0751953125e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11158,6 +11555,7 @@ }, "azure/low/1536-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 2.0345052083e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11168,6 +11566,7 @@ }, "azure/medium/1024-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 8.056640625e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11178,6 +11577,7 @@ }, "azure/medium/1024-x-1536/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 8.056640625e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11188,6 +11588,7 @@ }, "azure/medium/1536-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 7.9752604167e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11198,6 +11599,7 @@ }, "azure/high/1024-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 3.173828125e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11208,6 +11610,7 @@ }, "azure/high/1024-x-1536/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 3.173828125e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11218,6 +11621,7 @@ }, "azure/high/1536-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 3.1575520833e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11246,6 +11650,7 @@ }, "azure/o1": { "deprecation_date": "2026-11-19", + "successor_model": "azure/gpt-5.6-sol", "cache_read_input_token_cost": 7.5e-06, "input_cost_per_token": 1.5e-05, "litellm_provider": "azure", @@ -11263,6 +11668,7 @@ "azure/o1-2024-12-17": { "cache_read_input_token_cost": 7.5e-06, "deprecation_date": "2026-11-19", + "successor_model": "azure/gpt-5.6-sol", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "azure", @@ -11315,6 +11721,7 @@ }, "azure/o3": { "deprecation_date": "2026-11-19", + "successor_model": "azure/gpt-5.6-sol", "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -11352,6 +11759,7 @@ }, "azure/o3-2025-04-16": { "deprecation_date": "2026-11-19", + "successor_model": "azure/gpt-5.6-sol", "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -11390,6 +11798,8 @@ "azure/o3-deep-research": { "cache_read_input_token_cost": 2.5e-06, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-sol", "input_cost_per_token": 1e-05, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -11426,6 +11836,8 @@ }, "azure/o3-mini": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-terra", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, @@ -11445,6 +11857,8 @@ "azure/o3-mini-2025-01-31": { "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-terra", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "azure", @@ -11461,6 +11875,8 @@ }, "azure/o3-pro": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-sol", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "azure", @@ -11496,6 +11912,8 @@ }, "azure/o3-pro-2025-06-10": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-sol", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "azure", @@ -11531,6 +11949,8 @@ }, "azure/o4-mini": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-terra", "cache_read_input_token_cost": 2.75e-07, "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, @@ -11569,6 +11989,8 @@ "azure/o4-mini-2025-04-16": { "cache_read_input_token_cost": 2.75e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-terra", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "azure", @@ -11620,6 +12042,7 @@ }, "azure/text-embedding-3-large": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.43e-07, "litellm_provider": "azure", "max_input_tokens": 8192, @@ -11629,6 +12052,7 @@ }, "azure/text-embedding-3-small": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.2e-08, "litellm_provider": "azure", "max_input_tokens": 8192, @@ -11638,6 +12062,7 @@ }, "azure/text-embedding-ada-002": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.1e-07, "litellm_provider": "azure", "max_input_tokens": 8192, @@ -11683,6 +12108,8 @@ }, "azure/us/gpt-4.1-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_priority": 9.63e-07, "input_cost_per_token": 2.2e-06, @@ -11725,6 +12152,8 @@ }, "azure/us/gpt-4.1-mini-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-mini", "cache_read_input_token_cost": 1.1e-07, "cache_read_input_token_cost_priority": 1.93e-07, "input_cost_per_token": 4.4e-07, @@ -11767,6 +12196,8 @@ }, "azure/us/gpt-4.1-nano-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-nano", "cache_read_input_token_cost": 2.8e-08, "input_cost_per_token": 1.1e-07, "input_cost_per_token_batches": 5.5e-08, @@ -11800,6 +12231,8 @@ }, "azure/us/gpt-4o-2024-08-06": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, "input_cost_per_token_batches": 1.375e-06, @@ -11819,6 +12252,8 @@ }, "azure/us/gpt-4o": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_creation_input_token_cost": 1.38e-06, "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, @@ -11838,6 +12273,8 @@ }, "azure/us/gpt-4o-2024-11-20": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_creation_input_token_cost": 1.38e-06, "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, @@ -11858,6 +12295,7 @@ "azure/us/gpt-4o-mini": { "cache_read_input_token_cost": 8.3e-08, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.65e-07, "input_cost_per_token_batches": 8.3e-08, "litellm_provider": "azure", @@ -11881,6 +12319,7 @@ "azure/us/gpt-4o-mini-2024-07-18": { "cache_read_input_token_cost": 8.3e-08, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.65e-07, "input_cost_per_token_batches": 8.3e-08, "litellm_provider": "azure", @@ -11919,26 +12358,6 @@ "supports_system_messages": true, "supports_tool_choice": true }, - "azure/us/gpt-4o-realtime-preview-2024-10-01": { - "cache_creation_input_audio_token_cost": 2.2e-05, - "cache_read_input_token_cost": 2.75e-06, - "deprecation_date": "2025-03-26", - "input_cost_per_audio_token": 0.00011, - "input_cost_per_token": 5.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 0.00022, - "output_cost_per_token": 2.2e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "azure/us/gpt-4o-realtime-preview-2024-12-17": { "cache_read_input_audio_token_cost": 2.5e-06, "cache_read_input_token_cost": 2.75e-06, @@ -11970,6 +12389,8 @@ "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_priority": 2.75e-07, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "input_cost_per_token": 1.375e-06, "input_cost_per_token_batches": 6.875e-07, "input_cost_per_token_priority": 2.75e-06, @@ -12013,7 +12434,9 @@ "azure/us/gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.75e-08, "cache_read_input_token_cost_priority": 4.95e-08, - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-mini", "input_cost_per_token": 2.75e-07, "input_cost_per_token_batches": 1.375e-07, "input_cost_per_token_priority": 4.95e-07, @@ -12057,6 +12480,8 @@ "azure/us/gpt-5-nano-2025-08-07": { "cache_read_input_token_cost": 5.5e-09, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-nano", "input_cost_per_token": 5.5e-08, "input_cost_per_token_batches": 2.75e-08, "litellm_provider": "azure", @@ -12096,7 +12521,9 @@ "cache_read_input_token_cost_batches": 2.75e-09 }, "azure/us/gpt-5.1": { - "deprecation_date": "2027-05-15", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.2", "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_batches": 6.875e-08, "cache_read_input_token_cost_priority": 2.75e-07, @@ -12144,6 +12571,8 @@ }, "azure/us/gpt-5.1-codex": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.2-codex", "cache_read_input_token_cost": 1.375e-07, "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", @@ -12175,6 +12604,7 @@ }, "azure/us/gpt-5.1-codex-mini": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.75e-08, "input_cost_per_token": 2.75e-07, "litellm_provider": "azure", @@ -12207,6 +12637,7 @@ "azure/us/o1": { "cache_read_input_token_cost": 8.25e-06, "deprecation_date": "2026-11-19", + "successor_model": "azure/us/gpt-5.6-sol", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -12225,6 +12656,7 @@ "azure/us/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, "deprecation_date": "2026-11-19", + "successor_model": "azure/us/gpt-5.6-sol", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -12258,6 +12690,7 @@ }, "azure/us/o3": { "deprecation_date": "2026-11-19", + "successor_model": "azure/us/gpt-5.6-sol", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 2.2e-06, "input_cost_per_token_batches": 1.1e-06, @@ -12295,6 +12728,7 @@ }, "azure/us/o3-2025-04-16": { "deprecation_date": "2026-11-19", + "successor_model": "azure/us/gpt-5.6-sol", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 2.2e-06, "input_cost_per_token_batches": 1.1e-06, @@ -12333,6 +12767,8 @@ "azure/us/o3-mini": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -12350,6 +12786,8 @@ "azure/us/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -12367,6 +12805,8 @@ "azure/us/o4-mini": { "cache_read_input_token_cost": 3.03e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -12392,6 +12832,8 @@ "azure/us/o4-mini-2025-04-16": { "cache_read_input_token_cost": 3.03e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -12423,6 +12865,8 @@ }, "azure_ai/Cohere-embed-v3-english": { "deprecation_date": "2027-02-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/Cohere-Embed-V5-Fast", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 512, @@ -12434,6 +12878,8 @@ }, "azure_ai/Cohere-embed-v3-multilingual": { "deprecation_date": "2027-02-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/Cohere-Embed-V5-Fast", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 512, @@ -12445,6 +12891,7 @@ }, "azure_ai/Codestral-2501": { "deprecation_date": "2027-02-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 3e-07, "litellm_provider": "azure_ai", "max_input_tokens": 256000, @@ -12466,6 +12913,7 @@ }, "azure_ai/FLUX-1.1-pro": { "deprecation_date": "2027-01-05", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "litellm_provider": "azure_ai", "max_input_tokens": 5000, "mode": "image_generation", @@ -12477,6 +12925,7 @@ }, "azure_ai/FLUX.1-Kontext-pro": { "deprecation_date": "2027-01-05", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "litellm_provider": "azure_ai", "max_input_tokens": 5000, "mode": "image_generation", @@ -12488,6 +12937,7 @@ }, "azure_ai/flux.2-pro": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "litellm_provider": "azure_ai", "max_input_tokens": 32000, "mode": "image_generation", @@ -12499,6 +12949,7 @@ }, "azure_ai/FLUX.2-flex": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_pixel": 5e-08, "litellm_provider": "azure_ai", "max_input_tokens": 32000, @@ -12549,6 +13000,7 @@ }, "azure_ai/FW-GLM-5": { "deprecation_date": "2027-07-01", + "successor_model": "azure_ai/FW-GLM-5.2", "cache_read_input_token_cost": 2.2e-07, "input_cost_per_token": 1.1e-06, "litellm_provider": "azure_ai", @@ -12565,6 +13017,7 @@ }, "azure_ai/FW-GLM-5.1": { "deprecation_date": "2027-07-01", + "successor_model": "azure_ai/FW-GLM-5.2", "cache_read_input_token_cost": 2.86e-07, "input_cost_per_token": 1.54e-06, "litellm_provider": "azure_ai", @@ -12822,6 +13275,8 @@ "/v1/images/edits" ], "deprecation_date": "2026-10-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/MAI-Image-2.6", "max_input_tokens": 32000 }, "azure_ai/MAI-Image-2.5-Flash": { @@ -12837,10 +13292,13 @@ "/v1/images/edits" ], "deprecation_date": "2026-10-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/MAI-Image-2.6-Flash", "max_input_tokens": 32000 }, "azure_ai/MAI-Image-2.5-Pro": { "deprecation_date": "2026-10-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_image_token": 8e-06, "input_cost_per_token": 5e-06, "litellm_provider": "azure_ai", @@ -12880,6 +13338,7 @@ }, "azure_ai/Llama-3.3-70B-Instruct": { "deprecation_date": "2027-01-31", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 7.1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -12893,6 +13352,7 @@ }, "azure_ai/Llama-4-Maverick-17B-128E-Instruct-FP8": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 2.5e-07, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -12907,6 +13367,7 @@ }, "azure_ai/Llama-4-Scout-17B-16E-Instruct": { "deprecation_date": "2027-01-31", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 10000000, @@ -12919,149 +13380,10 @@ "supports_tool_choice": true, "supports_vision": true }, - "azure_ai/Meta-Llama-3-70B-Instruct": { - "deprecation_date": "2025-06-30", - "input_cost_per_token": 1.1e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 8192, - "max_output_tokens": 2048, - "mode": "chat", - "output_cost_per_token": 3.7e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true - }, - "azure_ai/Meta-Llama-3.1-70B-Instruct": { - "deprecation_date": "2025-06-30", - "input_cost_per_token": 2.68e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 2048, - "mode": "chat", - "output_cost_per_token": 3.54e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true - }, - "azure_ai/Phi-3-medium-128k-instruct": { - "deprecation_date": "2025-08-30", - "input_cost_per_token": 1.7e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6.8e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true, - "supports_vision": false - }, - "azure_ai/Phi-3-medium-4k-instruct": { - "deprecation_date": "2025-08-30", - "input_cost_per_token": 1.7e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6.8e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true, - "supports_vision": false - }, - "azure_ai/Phi-3-mini-128k-instruct": { - "deprecation_date": "2025-08-30", - "input_cost_per_token": 1.3e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 5.2e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true, - "supports_vision": false - }, - "azure_ai/Phi-3-mini-4k-instruct": { - "deprecation_date": "2025-08-30", - "input_cost_per_token": 1.3e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 5.2e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true, - "supports_vision": false - }, - "azure_ai/Phi-3-small-128k-instruct": { - "deprecation_date": "2025-08-30", - "input_cost_per_token": 1.5e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true, - "supports_vision": false - }, - "azure_ai/Phi-3-small-8k-instruct": { - "deprecation_date": "2025-08-30", - "input_cost_per_token": 1.5e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 8192, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true, - "supports_vision": false - }, - "azure_ai/Phi-3.5-MoE-instruct": { - "deprecation_date": "2025-08-30", - "input_cost_per_token": 1.6e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6.4e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true, - "supports_vision": false - }, - "azure_ai/Phi-3.5-mini-instruct": { - "deprecation_date": "2025-08-30", - "input_cost_per_token": 1.3e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 5.2e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true, - "supports_vision": false - }, - "azure_ai/Phi-3.5-vision-instruct": { - "deprecation_date": "2025-08-30", - "input_cost_per_token": 1.3e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 5.2e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true, - "supports_vision": true - }, "azure_ai/Phi-4": { "deprecation_date": "2027-01-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "microsoft--phi-4", "input_cost_per_token": 1.25e-07, "litellm_provider": "azure_ai", "max_input_tokens": 16384, @@ -13076,6 +13398,8 @@ }, "azure_ai/Phi-4-mini-instruct": { "deprecation_date": "2027-01-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "microsoft--phi-4", "input_cost_per_token": 7.5e-08, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -13088,6 +13412,8 @@ }, "azure_ai/Phi-4-multimodal-instruct": { "deprecation_date": "2027-01-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "microsoft--phi-4", "input_cost_per_audio_token": 4e-06, "input_cost_per_token": 8e-08, "litellm_provider": "azure_ai", @@ -13103,6 +13429,8 @@ }, "azure_ai/Phi-4-mini-reasoning": { "deprecation_date": "2027-01-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "microsoft--phi-4", "input_cost_per_token": 7.5e-08, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -13115,6 +13443,8 @@ }, "azure_ai/Phi-4-reasoning": { "deprecation_date": "2027-01-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "microsoft--phi-4", "input_cost_per_token": 1.25e-07, "litellm_provider": "azure_ai", "max_input_tokens": 32768, @@ -13148,6 +13478,7 @@ }, "azure_ai/Cohere-parse-v5": { "deprecation_date": "2026-12-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "litellm_provider": "azure_ai", "mode": "ocr", "ocr_cost_per_page": 0.0015, @@ -13158,6 +13489,8 @@ }, "azure_ai/cohere-command-a": { "deprecation_date": "2027-02-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "coherelabs-command-a-plus-05-2026-fp81", "input_cost_per_token": 2.5e-06, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -13198,6 +13531,7 @@ }, "azure_ai/MAI-DS-R1": { "deprecation_date": "2026-02-27", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", "input_cost_per_token": 1.35e-06, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13209,30 +13543,10 @@ "supports_reasoning": true, "supports_tool_choice": true }, - "azure_ai/cohere-rerank-v3-english": { - "deprecation_date": "2025-06-30", - "input_cost_per_query": 0.002, - "input_cost_per_token": 0.0, - "litellm_provider": "azure_ai", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "mode": "rerank", - "output_cost_per_token": 0.0, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models" - }, - "azure_ai/cohere-rerank-v3-multilingual": { - "deprecation_date": "2025-06-30", - "input_cost_per_query": 0.002, - "input_cost_per_token": 0.0, - "litellm_provider": "azure_ai", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "mode": "rerank", - "output_cost_per_token": 0.0, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models" - }, "azure_ai/cohere-rerank-v4.0-pro": { "deprecation_date": "2027-09-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "Cohere-rerank-v5-pro", "input_cost_per_query": 0.0025, "input_cost_per_token": 0.0, "litellm_provider": "azure_ai", @@ -13244,6 +13558,8 @@ }, "azure_ai/cohere-rerank-v4.0-fast": { "deprecation_date": "2027-09-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "Cohere-rerank-v5-fast", "input_cost_per_query": 0.002, "input_cost_per_token": 0.0, "litellm_provider": "azure_ai", @@ -13255,6 +13571,8 @@ }, "azure_ai/deepseek-v3.2": { "deprecation_date": "2027-11-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/deepseek-v4.1-flash", "input_cost_per_token": 5.8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13271,6 +13589,8 @@ }, "azure_ai/deepseek-v3.2-speciale": { "deprecation_date": "2027-11-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/deepseek-v4-pro", "input_cost_per_token": 5.8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13285,20 +13605,9 @@ "supports_reasoning": true, "supports_tool_choice": true }, - "azure_ai/deepseek-v3": { - "deprecation_date": "2025-08-31", - "input_cost_per_token": 1.14e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 4.56e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true - }, "azure_ai/deepseek-v4-pro": { "deprecation_date": "2028-02-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.74e-06, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -13315,6 +13624,8 @@ }, "azure_ai/deepseek-v4-flash": { "deprecation_date": "2028-02-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/DeepSeek-V4-Flash-0731", "input_cost_per_token": 1.9e-07, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -13332,6 +13643,7 @@ "azure_ai/DeepSeek-V4-Flash-0731": { "cache_read_input_token_cost": 1.4e-08, "deprecation_date": "2026-12-03", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 4.4e-07, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -13347,6 +13659,8 @@ }, "azure_ai/embed-v-4-0": { "deprecation_date": "2027-06-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/Cohere-Embed-V5-Fast", "input_cost_per_token": 1.2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13366,6 +13680,8 @@ }, "azure_ai/grok-4": { "deprecation_date": "2027-01-31", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/grok-4.3", "input_cost_per_token": 3e-06, "litellm_provider": "azure_ai", "max_input_tokens": 262000, @@ -13424,6 +13740,7 @@ "azure_ai/grok-4-20-reasoning": { "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-04-06", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure_ai", "max_input_tokens": 262000, @@ -13443,6 +13760,7 @@ "azure_ai/grok-4-20-non-reasoning": { "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-04-06", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure_ai", "max_input_tokens": 262000, @@ -13460,6 +13778,7 @@ }, "azure_ai/grok-4-1-fast-non-reasoning": { "deprecation_date": "2027-05-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", @@ -13475,9 +13794,14 @@ }, "azure_ai/grok-4-1-fast-reasoning": { "deprecation_date": "2027-05-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", + "token_count_framing": 149, + "token_count_tool_framing": 302, + "token_count_responses_framing": 145, + "token_count_responses_tool_framing": 100, "max_input_tokens": 128000, "max_output_tokens": 128000, "mode": "chat", @@ -13491,6 +13815,7 @@ }, "azure_ai/grok-code-fast-1": { "deprecation_date": "2027-01-31", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 256000, @@ -13506,6 +13831,7 @@ }, "azure_ai/jais-30b-chat": { "deprecation_date": "2026-01-30", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", "input_cost_per_token": 0.0032, "litellm_provider": "azure_ai", "max_input_tokens": 8192, @@ -13515,20 +13841,9 @@ "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", "supports_pdf_input": false }, - "azure_ai/jamba-instruct": { - "deprecation_date": "2025-03-01", - "input_cost_per_token": 5e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 70000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 7e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true - }, "azure_ai/kimi-k2.5": { "deprecation_date": "2027-01-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 6e-07, "litellm_provider": "azure_ai", "max_input_tokens": 262144, @@ -13546,6 +13861,7 @@ }, "azure_ai/kimi-k2.6": { "deprecation_date": "2027-04-16", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 9.5e-07, "litellm_provider": "azure_ai", "max_input_tokens": 262144, @@ -13570,6 +13886,8 @@ }, "azure_ai/ministral-3b": { "deprecation_date": "2026-12-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "ministral-ministral-4b-instruct", "input_cost_per_token": 4e-08, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13581,32 +13899,6 @@ "supports_pdf_input": false, "supports_tool_choice": true }, - "azure_ai/mistral-large": { - "deprecation_date": "2025-04-15", - "input_cost_per_token": 4e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 32000, - "max_output_tokens": 8191, - "mode": "chat", - "output_cost_per_token": 1.2e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_tool_choice": true - }, - "azure_ai/mistral-large-2407": { - "deprecation_date": "2025-05-13", - "input_cost_per_token": 2e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_tool_choice": true - }, "azure_ai/mistral-large-latest": { "input_cost_per_token": 2e-06, "litellm_provider": "azure_ai", @@ -13634,6 +13926,8 @@ }, "azure_ai/mistral-medium-2505": { "deprecation_date": "2026-12-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/mistral-medium-3-5", "input_cost_per_token": 4e-07, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -13647,6 +13941,8 @@ }, "azure_ai/mistral-nemo": { "deprecation_date": "2026-01-30", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", + "successor_model": "azure_ai/mistral-small-2503", "input_cost_per_token": 1.5e-07, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -13657,21 +13953,10 @@ "supports_function_calling": true, "supports_pdf_input": false }, - "azure_ai/mistral-small": { - "deprecation_date": "2025-07-31", - "input_cost_per_token": 1e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 32000, - "max_output_tokens": 8191, - "mode": "chat", - "output_cost_per_token": 3e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_tool_choice": true - }, "azure_ai/mistral-small-2503": { "deprecation_date": "2027-02-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "mistralai-mistral-small-4-119b-2603", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13685,6 +13970,8 @@ }, "babbage-002": { "deprecation_date": "2026-09-28", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 4e-07, "input_cost_per_token_batches": 2e-07, "litellm_provider": "text-completion-openai", @@ -13831,7 +14118,7 @@ "input_cost_per_token_flex": 3.7e-07, "input_cost_per_token_priority": 1.295e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 2.22e-06, @@ -13845,10 +14132,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/ap-northeast-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -13893,6 +14181,7 @@ }, "bedrock/ap-northeast-1/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 7.3e-07, "input_cost_per_token_flex": 3.6e-07, "litellm_provider": "bedrock", @@ -13945,6 +14234,7 @@ }, "bedrock/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 6e-07, "input_cost_per_token_flex": 3e-07, "litellm_provider": "bedrock", @@ -13978,6 +14268,7 @@ }, "bedrock/ap-south-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 3.18e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -13988,6 +14279,7 @@ }, "bedrock/ap-south-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3.6e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14002,7 +14294,7 @@ "input_cost_per_token_flex": 3.7e-07, "input_cost_per_token_priority": 1.295e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 2.22e-06, @@ -14016,10 +14308,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/ap-south-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -14064,6 +14357,7 @@ }, "bedrock/ap-south-1/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 7.1e-07, "input_cost_per_token_flex": 3.6e-07, "litellm_provider": "bedrock", @@ -14140,12 +14434,12 @@ "input_cost_per_token": 7.4e-07, "input_cost_per_token_flex": 3.7e-07, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 2.22e-06, "output_cost_per_token_flex": 1.11e-06, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.html", + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md", "supports_audio_input": false, "supports_function_calling": true, "supports_native_structured_output": true, @@ -14156,6 +14450,7 @@ }, "bedrock/ap-southeast-3/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-minimax-minimax-m2-1.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_flex": 1.8e-07, "litellm_provider": "bedrock", @@ -14226,6 +14521,7 @@ }, "bedrock/ca-central-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 3.05e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14236,6 +14532,7 @@ }, "bedrock/ca-central-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14250,7 +14547,7 @@ "input_cost_per_token_flex": 3.7e-07, "input_cost_per_token_priority": 1.295e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 2.22e-06, @@ -14264,10 +14561,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/eu-north-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -14411,6 +14709,7 @@ }, "bedrock/eu-central-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -14472,6 +14771,7 @@ }, "bedrock/eu-west-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 2.86e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14482,6 +14782,7 @@ }, "bedrock/eu-west-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3.2e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14492,6 +14793,7 @@ }, "bedrock/eu-west-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -14553,6 +14855,7 @@ }, "bedrock/eu-west-2/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 3.45e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14563,6 +14866,7 @@ }, "bedrock/eu-west-2/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3.9e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14573,6 +14877,7 @@ }, "bedrock/eu-west-2/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 4.7e-07, "input_cost_per_token_batches": 2.35e-07, "input_cost_per_token_flex": 2.35e-07, @@ -14660,6 +14965,7 @@ }, "bedrock/eu-west-3/mistral.mistral-7b-instruct-v0:2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mistral-7b-instruct.md", "input_cost_per_token": 2e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -14681,6 +14987,7 @@ }, "bedrock/eu-west-3/mistral.mixtral-8x7b-instruct-v0:1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mixtral-8x7b-instruct.md", "input_cost_per_token": 5.9e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -14692,6 +14999,7 @@ }, "bedrock/eu-south-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-minimax-minimax-m2-1.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_flex": 1.8e-07, "litellm_provider": "bedrock", @@ -14762,6 +15070,7 @@ }, "bedrock/sa-east-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 4.45e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14772,6 +15081,7 @@ }, "bedrock/sa-east-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 5e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14786,7 +15096,7 @@ "input_cost_per_token_flex": 3.7e-07, "input_cost_per_token_priority": 1.295e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 2.22e-06, @@ -14800,10 +15110,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/sa-east-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -14848,6 +15159,7 @@ }, "bedrock/sa-east-1/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 7.3e-07, "input_cost_per_token_flex": 3.6e-07, "litellm_provider": "bedrock", @@ -14979,6 +15291,7 @@ }, "bedrock/us-east-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 2.65e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14989,6 +15302,7 @@ }, "bedrock/us-east-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14999,6 +15313,7 @@ }, "bedrock/us-east-1/mistral.mistral-7b-instruct-v0:2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mistral-7b-instruct.md", "input_cost_per_token": 1.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -15020,6 +15335,7 @@ }, "bedrock/us-east-1/mistral.mixtral-8x7b-instruct-v0:1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mixtral-8x7b-instruct.md", "input_cost_per_token": 4.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -15035,7 +15351,7 @@ "input_cost_per_token_flex": 3.1e-07, "input_cost_per_token_priority": 1.085e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 1.85e-06, @@ -15049,10 +15365,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/us-east-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -15096,6 +15413,7 @@ }, "bedrock/us-east-1/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 6e-07, "input_cost_per_token_flex": 3e-07, "litellm_provider": "bedrock", @@ -15156,7 +15474,7 @@ "input_cost_per_token_flex": 3.1e-07, "input_cost_per_token_priority": 1.085e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 1.85e-06, @@ -15170,10 +15488,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/us-east-2/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -15218,6 +15537,7 @@ }, "bedrock/us-east-2/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 6e-07, "input_cost_per_token_flex": 3e-07, "litellm_provider": "bedrock", @@ -15292,7 +15612,7 @@ "output_vector_size": 1536 }, "bedrock/us-gov-east-1/amazon.titan-embed-text-v2:0": { - "input_cost_per_token": 2e-07, + "input_cost_per_token": 3e-08, "litellm_provider": "bedrock", "max_input_tokens": 8192, "mode": "embedding", @@ -15328,6 +15648,8 @@ "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "successor_model": "bedrock/us-gov-east-1/anthropic.claude-sonnet-5-5", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, @@ -15358,6 +15680,7 @@ "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, @@ -15377,7 +15700,8 @@ "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "token_count_model": {"model":"anthropic.claude-sonnet-4-5-20250929-v1:0","litellm_provider":"bedrock"} }, "bedrock/us-gov-east-1/meta.llama3-70b-instruct-v1:0": { "input_cost_per_token": 2.65e-06, @@ -15405,8 +15729,10 @@ "input_cost_per_image": 7.2e-05, "input_cost_per_video_per_second": 0.00084, "input_cost_per_audio_per_second": 0.000168, + "input_cost_per_token_batches": 8.1e-08, "output_cost_per_token": 0.0, "output_vector_size": 3072, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_embedding_image_input": true, "supports_image_input": true, "supports_video_input": true, @@ -15415,11 +15741,14 @@ "bedrock/us-gov-west-1/amazon.nova-lite-v1:0": { "cache_read_input_token_cost": 1.8e-08, "input_cost_per_token": 7.2e-08, + "input_cost_per_token_batches": 3.6e-08, "litellm_provider": "bedrock", "max_input_tokens": 300000, "max_output_tokens": 10000, "mode": "chat", "output_cost_per_token": 2.88e-07, + "output_cost_per_token_batches": 1.44e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -15430,11 +15759,14 @@ "bedrock/us-gov-west-1/amazon.nova-micro-v1:0": { "cache_read_input_token_cost": 1.05e-08, "input_cost_per_token": 4.2e-08, + "input_cost_per_token_batches": 2.1e-08, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 10000, "mode": "chat", "output_cost_per_token": 1.68e-07, + "output_cost_per_token_batches": 8.4e-08, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_function_calling": true, "supports_prompt_caching": true, "supports_response_schema": true, @@ -15442,12 +15774,21 @@ }, "bedrock/us-gov-west-1/amazon.nova-pro-v1:0": { "cache_read_input_token_cost": 2.4e-07, + "cache_read_input_token_cost_flex": 1.2e-07, + "cache_read_input_token_cost_priority": 4.2e-07, "input_cost_per_token": 9.6e-07, + "input_cost_per_token_batches": 4.8e-07, + "input_cost_per_token_flex": 4.8e-07, + "input_cost_per_token_priority": 1.68e-06, "litellm_provider": "bedrock", "max_input_tokens": 300000, "max_output_tokens": 10000, "mode": "chat", "output_cost_per_token": 3.84e-06, + "output_cost_per_token_batches": 1.92e-06, + "output_cost_per_token_flex": 1.92e-06, + "output_cost_per_token_priority": 6.72e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -15500,6 +15841,8 @@ "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "successor_model": "bedrock/us-gov-west-1/anthropic.claude-sonnet-5-5", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, @@ -15530,6 +15873,7 @@ "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, @@ -15549,9 +15893,12 @@ "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "token_count_model": {"model":"anthropic.claude-sonnet-4-5-20250929-v1:0","litellm_provider":"bedrock"} }, "bedrock/us-gov-west-1/meta.llama3-70b-instruct-v1:0": { + "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 2.65e-06, "litellm_provider": "bedrock", "max_input_tokens": 8000, @@ -15562,6 +15909,8 @@ "supports_pdf_input": true }, "bedrock/us-gov-west-1/meta.llama3-8b-instruct-v1:0": { + "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3e-07, "litellm_provider": "bedrock", "max_input_tokens": 8000, @@ -15573,6 +15922,7 @@ }, "bedrock/us-west-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 2.65e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -15583,6 +15933,7 @@ }, "bedrock/us-west-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -15672,6 +16023,7 @@ }, "bedrock/us-west-2/mistral.mistral-7b-instruct-v0:2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mistral-7b-instruct.md", "input_cost_per_token": 1.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -15693,6 +16045,7 @@ }, "bedrock/us-west-2/mistral.mixtral-8x7b-instruct-v0:1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mixtral-8x7b-instruct.md", "input_cost_per_token": 4.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -15708,7 +16061,7 @@ "input_cost_per_token_flex": 3.1e-07, "input_cost_per_token_priority": 1.085e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 1.85e-06, @@ -15722,10 +16075,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/us-west-2/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -15769,6 +16123,7 @@ }, "bedrock/us-west-2/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 6e-07, "input_cost_per_token_flex": 3e-07, "litellm_provider": "bedrock", @@ -15941,17 +16296,6 @@ "supports_function_calling": true, "supports_tool_choice": true }, - "cerebras/llama3.1-70b": { - "deprecation_date": "2025-01-17", - "input_cost_per_token": 6e-07, - "litellm_provider": "cerebras", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 6e-07, - "supports_function_calling": true, - "supports_tool_choice": true - }, "cerebras/llama3.1-8b": { "deprecation_date": "2026-05-27", "input_cost_per_token": 1e-07, @@ -16025,6 +16369,8 @@ "/v1/audio/transcriptions" ], "deprecation_date": "2027-02-26", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-live-transcribe", "input_cost_per_second": 0.0001, "source": "https://developers.openai.com/api/docs/pricing" }, @@ -16090,6 +16436,8 @@ "cache_creation_input_token_cost_batches": 1.875e-06, "cache_read_input_token_cost_batches": 1.5e-07, "deprecation_date": "2026-11-30", + "deprecation_source": "https://platform.claude.com/docs/en/about-claude/model-deprecations", + "successor_model": "claude-sonnet-5-5", "input_cost_per_token_batches": 1.5e-06, "litellm_provider": "anthropic", "max_input_tokens": 200000, @@ -16123,6 +16471,8 @@ "cache_creation_input_token_cost_batches": 1.875e-06, "cache_read_input_token_cost_batches": 1.5e-07, "deprecation_date": "2026-11-30", + "deprecation_source": "https://platform.claude.com/docs/en/about-claude/model-deprecations", + "successor_model": "claude-sonnet-5-5", "input_cost_per_token_batches": 1.5e-06, "litellm_provider": "anthropic", "max_input_tokens": 200000, @@ -16171,6 +16521,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -16292,6 +16643,7 @@ "cache_creation_input_token_cost_above_200k_tokens": 7.5e-06, "cache_read_input_token_cost_above_200k_tokens": 6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, @@ -16311,7 +16663,8 @@ "prompt_cache_min_tokens": 1024, "input_cost_per_token_batches": 1.5e-06, "output_cost_per_token_batches": 7.5e-06, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "token_count_model": {"model":"anthropic.claude-sonnet-4-5-20250929-v1:0","litellm_provider":"bedrock"} }, "claude-opus-4-5-20251101": { "supports_web_search": true, @@ -16705,6 +17058,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -17503,12 +17857,15 @@ }, "computer-use-preview": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 1024, "mode": "chat", "output_cost_per_token": 1.2e-05, + "fedramp_uplift_multiplier": 1.1, "supported_endpoints": [ "/v1/responses" ], @@ -17532,12 +17889,15 @@ }, "computer-use-preview-2025-03-11": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 1024, "mode": "chat", "output_cost_per_token": 1.2e-05, + "fedramp_uplift_multiplier": 1.1, "supported_endpoints": [ "/v1/responses" ], @@ -17562,6 +17922,7 @@ "deepseek-chat": { "cache_read_input_token_cost": 2.8e-08, "deprecation_date": "2026-07-24", + "deprecation_source": "https://api-docs.deepseek.com/updates", "input_cost_per_token": 2.8e-07, "litellm_provider": "deepseek", "max_input_tokens": 131072, @@ -17583,6 +17944,7 @@ "deepseek-reasoner": { "cache_read_input_token_cost": 2.8e-08, "deprecation_date": "2026-07-24", + "deprecation_source": "https://api-docs.deepseek.com/updates", "input_cost_per_token": 2.8e-07, "litellm_provider": "deepseek", "max_input_tokens": 131072, @@ -21565,6 +21927,7 @@ "prompt_cache_min_tokens": 512, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_function_calling": true, "supports_mid_conversation_system": true, @@ -21613,6 +21976,7 @@ "cache_creation_input_token_cost": 3.74997e-06, "cache_read_input_token_cost": 3.0002e-07, "deprecation_date": "2026-10-09", + "successor_model": "databricks/databricks-claude-sonnet-5", "input_cost_per_token": 2.99999e-06, "input_dbu_cost_per_token": 4.2857e-05, "litellm_provider": "databricks", @@ -21722,6 +22086,7 @@ "prompt_cache_min_tokens": 1024, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_function_calling": true, "supports_mid_conversation_system": true, @@ -21736,6 +22101,7 @@ "cache_creation_input_token_cost": 1.4e-07, "cache_read_input_token_cost": 2.8e-08, "deprecation_date": "2026-11-05", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "input_cost_per_token": 1.4e-07, "input_dbu_cost_per_token": 2e-06, "litellm_provider": "databricks", @@ -21749,6 +22115,7 @@ "output_cost_per_token": 2.8e-07, "output_dbu_cost_per_token": 4e-06, "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", + "successor_model": "databricks/databricks-deepseek-v4-1-flash-1017", "supported_modalities": [ "text" ], @@ -21762,14 +22129,19 @@ "supports_vision": false }, "databricks/system.ai.deepseek-v4-flash-0731": { + "deprecation_date": "2026-11-05", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/retired-models-policy", "litellm_provider": "databricks", "mode": "chat", + "source": "https://docs.databricks.com/aws/en/machine-learning/retired-models-policy", + "successor_model": "databricks/databricks-deepseek-v4-1-flash-1017", "token_count_framing": 97 }, "databricks/databricks-deepseek-v4-pro-0813": { "cache_creation_input_token_cost": 1.31999e-06, "cache_read_input_token_cost": 1.3202e-07, "deprecation_date": "2026-10-30", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "input_cost_per_token": 1.31999e-06, "input_dbu_cost_per_token": 1.8857e-05, "litellm_provider": "databricks", @@ -21782,6 +22154,7 @@ "output_cost_per_token": 3.95997e-06, "output_dbu_cost_per_token": 5.6571e-05, "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", + "successor_model": "databricks/databricks-deepseek-v4-1-flash-1017", "supported_modalities": [ "text" ], @@ -21798,6 +22171,7 @@ "cache_creation_input_token_cost": 3.0002e-07, "cache_read_input_token_cost": 3.0002e-08, "deprecation_date": "2026-10-02", + "successor_model": "databricks/databricks-gemini-3-5-flash", "input_cost_per_token": 3.0001999999999996e-07, "input_dbu_cost_per_token": 4.285999999999999e-06, "litellm_provider": "databricks", @@ -22067,7 +22441,7 @@ }, "mode": "chat", "output_cost_per_token": 3.74997e-06, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "supported_modalities": [ "text", "image", @@ -22085,7 +22459,9 @@ "input_cost_per_token_priority": 1.35002e-06, "output_cost_per_token_priority": 6.75003e-06, "cache_read_input_token_cost_priority": 1.3503e-07, - "cache_creation_input_token_cost_priority": 1.35002e-06 + "cache_creation_input_token_cost_priority": 1.35002e-06, + "supports_audio_input": true, + "supports_video_input": true }, "databricks/databricks-gemini-3-7-flash": { "cache_creation_input_token_cost": 7.4998e-07, @@ -22099,7 +22475,7 @@ }, "mode": "chat", "output_cost_per_token": 3.74997e-06, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "supported_modalities": [ "text", "image", @@ -22117,7 +22493,9 @@ "input_cost_per_token_priority": 1.35002e-06, "output_cost_per_token_priority": 6.75003e-06, "cache_read_input_token_cost_priority": 1.3503e-07, - "cache_creation_input_token_cost_priority": 1.35002e-06 + "cache_creation_input_token_cost_priority": 1.35002e-06, + "supports_audio_input": true, + "supports_video_input": true }, "databricks/databricks-gemini-3-6-flash": { "cache_creation_input_token_cost": 7.4998e-07, @@ -22133,7 +22511,7 @@ "mode": "chat", "output_cost_per_token": 3.74997e-06, "output_dbu_cost_per_token": 5.3571e-05, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "supported_modalities": [ "text", "image", @@ -22152,7 +22530,9 @@ "input_cost_per_token_priority": 1.35002e-06, "output_cost_per_token_priority": 6.75003e-06, "cache_read_input_token_cost_priority": 1.3503e-07, - "cache_creation_input_token_cost_priority": 1.35002e-06 + "cache_creation_input_token_cost_priority": 1.35002e-06, + "supports_audio_input": true, + "supports_video_input": true }, "databricks/databricks-gemini-3-5-flash": { "cache_creation_input_token_cost": 1.87502e-06, @@ -22168,7 +22548,7 @@ "mode": "chat", "output_cost_per_token": 1.124998e-05, "output_dbu_cost_per_token": 0.000160714, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "supported_modalities": [ "text", "image", @@ -22186,7 +22566,9 @@ "input_cost_per_token_priority": 3.37498e-06, "output_cost_per_token_priority": 2.025002e-05, "cache_read_input_token_cost_priority": 3.3747e-07, - "cache_creation_input_token_cost_priority": 3.37498e-06 + "cache_creation_input_token_cost_priority": 3.37498e-06, + "supports_audio_input": true, + "supports_video_input": true }, "databricks/databricks-gemini-3-5-flash-lite": { "cache_creation_input_token_cost": 3.7499e-07, @@ -22202,7 +22584,7 @@ "mode": "chat", "output_cost_per_token": 3.12501e-06, "output_dbu_cost_per_token": 4.4643e-05, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "supported_modalities": [ "text", "image", @@ -22222,7 +22604,9 @@ "input_cost_per_token_priority": 6.7501e-07, "output_cost_per_token_priority": 5.62499e-06, "cache_read_input_token_cost_priority": 6.748e-08, - "cache_creation_input_token_cost_priority": 6.7501e-07 + "cache_creation_input_token_cost_priority": 6.7501e-07, + "supports_audio_input": true, + "supports_video_input": true }, "databricks/databricks-gemma-3-12b": { "cache_creation_input_token_cost": 1.5001e-07, @@ -22836,6 +23220,7 @@ "cache_creation_input_token_cost": 1.00002e-06, "cache_read_input_token_cost": 1.7003e-07, "deprecation_date": "2026-10-30", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "input_cost_per_token": 1.00002e-06, "input_dbu_cost_per_token": 1.4286e-05, "litellm_provider": "databricks", @@ -22847,6 +23232,7 @@ "output_cost_per_token": 4.04999e-06, "output_dbu_cost_per_token": 5.7857e-05, "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", + "successor_model": "databricks/databricks-glm-5-3", "supported_modalities": [ "text", "image" @@ -23071,6 +23457,8 @@ }, "davinci-002": { "deprecation_date": "2026-09-28", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, "litellm_provider": "text-completion-openai", @@ -23520,12 +23908,12 @@ ] }, "deepgram/streaming/nova-3": { - "input_cost_per_second": 8e-05, + "input_cost_per_second": 0.00012833, "litellm_provider": "deepgram", "metadata": { - "calculation": "$0.0048/60 seconds = $0.00008000 per second", + "calculation": "$0.0077/60 seconds = $0.00012833 per second", "note": "Nova-3 monolingual streaming, pay as you go", - "original_pricing_per_minute": 0.0048 + "original_pricing_per_minute": 0.0077 }, "mode": "audio_transcription", "output_cost_per_second": 0.0, @@ -23534,13 +23922,28 @@ "/v1/listen" ] }, - "deepgram/streaming/nova-3-multilingual": { - "input_cost_per_second": 9.667e-05, + "deepgram/streaming/nova-3-medical": { + "input_cost_per_second": 0.00012833, "litellm_provider": "deepgram", "metadata": { - "calculation": "$0.0058/60 seconds = $0.00009667 per second", + "calculation": "$0.0077/60 seconds = $0.00012833 per second", + "note": "Nova-3 Medical streaming, launch price from Deepgram's 2025-03-03 announcement. deepgram.com/pricing does not list Nova-3 Medical, and this matches its current Nova-3 monolingual streaming pay as you go rate", + "original_pricing_per_minute": 0.0077 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0.0, + "source": "https://www.businesswire.com/news/home/20250303470439/en", + "supported_endpoints": [ + "/v1/listen" + ] + }, + "deepgram/streaming/nova-3-multilingual": { + "input_cost_per_second": 0.00015333, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0092/60 seconds = $0.00015333 per second", "note": "Nova-3 multilingual (language=multi) streaming, pay as you go", - "original_pricing_per_minute": 0.0058 + "original_pricing_per_minute": 0.0092 }, "mode": "audio_transcription", "output_cost_per_second": 0.0, @@ -23950,7 +24353,7 @@ "max_output_tokens": 163840, "input_cost_per_token": 5e-07, "output_cost_per_token": 2.15e-06, - "cache_read_input_token_cost": 4e-07, + "cache_read_input_token_cost": 3.5e-07, "litellm_provider": "deepinfra", "mode": "chat", "supports_tool_choice": true, @@ -24024,7 +24427,7 @@ "max_output_tokens": 163840, "input_cost_per_token": 2.5e-07, "output_cost_per_token": 9.5e-07, - "cache_read_input_token_cost": 2.16e-07, + "cache_read_input_token_cost": 1.3e-07, "litellm_provider": "deepinfra", "mode": "chat", "supports_tool_choice": true, @@ -24397,6 +24800,7 @@ "cache_creation_input_token_cost": 0.0, "cache_read_input_token_cost": 2.8e-08, "deprecation_date": "2026-07-24", + "deprecation_source": "https://api-docs.deepseek.com/updates", "input_cost_per_token": 2.8e-07, "input_cost_per_token_cache_hit": 2.8e-08, "litellm_provider": "deepseek", @@ -24449,6 +24853,7 @@ "deepseek/deepseek-reasoner": { "cache_read_input_token_cost": 2.8e-08, "deprecation_date": "2026-07-24", + "deprecation_source": "https://api-docs.deepseek.com/updates", "input_cost_per_token": 2.8e-07, "input_cost_per_token_cache_hit": 2.8e-08, "litellm_provider": "deepseek", @@ -24502,6 +24907,7 @@ }, "deepseek.v3-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-1.html", "input_cost_per_token": 5.8e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -24520,7 +24926,7 @@ "input_cost_per_token_flex": 3.1e-07, "input_cost_per_token_priority": 1.085e-06, "litellm_provider": "bedrock_converse", - "max_input_tokens": 164000, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 1.85e-06, @@ -24531,7 +24937,7 @@ "supports_reasoning": true, "supports_native_structured_output": true, "supports_tool_choice": true, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-east-1/index.json", + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md", "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false @@ -25311,6 +25717,7 @@ "cache_read_input_token_cost": 1.1e-07, "input_cost_per_token": 1.1e-06, "deprecation_date": "2026-10-15", + "successor_model": "eu.anthropic.claude-haiku-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -25428,6 +25835,7 @@ "supports_vision": true, "prompt_cache_min_tokens": 1024, "deprecation_date": "2027-01-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "token_count_model": { "model": "anthropic.claude-opus-4-1-20250805-v1:0", "litellm_provider": "bedrock" @@ -25462,6 +25870,8 @@ "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-10-14", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "eu.anthropic.claude-sonnet-5", "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -25505,6 +25915,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "eu.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -25538,6 +25950,7 @@ }, "eu.meta.llama3-2-1b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-1b-instruct.md", "input_cost_per_token": 1.3e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -25550,6 +25963,7 @@ }, "eu.meta.llama3-2-3b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-3b-instruct.md", "input_cost_per_token": 1.9e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -28129,6 +28543,7 @@ "cache_read_input_token_cost": 1.4e-07, "cache_read_input_token_cost_priority": 1.75e-07, "deprecation_date": "2026-09-25", + "successor_model": "fireworks_ai/accounts/fireworks/models/glm-5p3", "input_cost_per_token": 1.4e-06, "input_cost_per_token_priority": 1.75e-06, "litellm_provider": "fireworks_ai", @@ -28504,6 +28919,7 @@ "cache_read_input_token_cost": 1.4e-07, "cache_read_input_token_cost_priority": 1.75e-07, "deprecation_date": "2026-09-25", + "successor_model": "fireworks_ai/glm-5p3", "input_cost_per_token": 1.4e-06, "input_cost_per_token_priority": 1.75e-06, "litellm_provider": "fireworks_ai", @@ -28887,6 +29303,8 @@ }, "ft:babbage-002": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1.6e-06, "input_cost_per_token_batches": 8e-07, "litellm_provider": "text-completion-openai", @@ -28899,6 +29317,8 @@ }, "ft:davinci-002": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1.2e-05, "input_cost_per_token_batches": 6e-06, "litellm_provider": "text-completion-openai", @@ -28911,6 +29331,8 @@ }, "ft:gpt-3.5-turbo": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 3e-06, "input_cost_per_token_batches": 1.5e-06, "litellm_provider": "openai", @@ -28918,6 +29340,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_system_messages": true, @@ -28925,45 +29348,57 @@ }, "ft:gpt-3.5-turbo-0125": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-06, + "fedramp_uplift_multiplier": 1.1, "supports_system_messages": true, "supports_tool_choice": true }, "ft:gpt-3.5-turbo-0613": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "ft:gpt-3.5-turbo", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 4096, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-06, + "fedramp_uplift_multiplier": 1.1, "supports_system_messages": true, "supports_tool_choice": true }, "ft:gpt-3.5-turbo-1106": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-06, + "fedramp_uplift_multiplier": 1.1, "supports_system_messages": true, "supports_tool_choice": true }, "ft:gpt-4-0613": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 3e-05, "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-05, + "fedramp_uplift_multiplier": 1.1, "source": "OpenAI needs to add pricing for this ft model, will be updated when added by OpenAI. Defaulting to base model pricing", "supports_function_calling": true, "supports_system_messages": true, @@ -28973,6 +29408,8 @@ "cache_read_input_token_cost": 1.875e-06, "cache_read_input_token_cost_batches": 9e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 3.75e-06, "input_cost_per_token_batches": 2.225e-06, "litellm_provider": "openai", @@ -28980,6 +29417,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.5e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 1.25e-05, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -28994,12 +29432,15 @@ "ft:gpt-4o-2024-11-20": { "cache_creation_input_token_cost": 1.875e-06, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 3.75e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.5e-05, + "fedramp_uplift_multiplier": 1.1, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29012,6 +29453,8 @@ "cache_read_input_token_cost": 1.5e-07, "cache_read_input_token_cost_batches": 7.5e-08, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "litellm_provider": "openai", @@ -29019,6 +29462,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.2e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 6e-07, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -29033,6 +29477,8 @@ "cache_read_input_token_cost": 7.5e-07, "cache_read_input_token_cost_batches": 5e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 3e-06, "input_cost_per_token_batches": 1.5e-06, "litellm_provider": "openai", @@ -29040,6 +29486,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 1.2e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 6e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -29053,6 +29500,8 @@ "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_batches": 1e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 8e-07, "input_cost_per_token_batches": 4e-07, "litellm_provider": "openai", @@ -29060,6 +29509,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 3.2e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 1.6e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -29073,6 +29523,8 @@ "cache_read_input_token_cost": 5e-08, "cache_read_input_token_cost_batches": 2.5e-08, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-luna", "input_cost_per_token": 2e-07, "input_cost_per_token_batches": 1e-07, "litellm_provider": "openai", @@ -29080,6 +29532,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 8e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-07, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -29093,6 +29546,8 @@ "cache_read_input_token_cost": 1e-06, "cache_read_input_token_cost_batches": 5e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 4e-06, "input_cost_per_token_batches": 2e-06, "litellm_provider": "openai", @@ -29100,6 +29555,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 1.6e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 8e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -29111,19 +29567,38 @@ }, "gemini-2.5-flash": { "cache_read_input_audio_token_cost": 1e-07, - "deprecation_date": "2026-10-20", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "cache_read_input_audio_token_cost_priority": 1.8e-07, "cache_read_input_token_cost": 3e-08, "cache_read_input_token_cost_flex": 3e-08, "cache_read_input_token_cost_priority": 5.4e-08, + "deprecation_date": "2026-10-20", + "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_audio_token": 1e-06, + "input_cost_per_audio_token_above_200k_tokens": 3e-07, + "input_cost_per_audio_token_above_200k_tokens_batches": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_flex": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_priority": 1.8e-06, + "input_cost_per_audio_token_batches": 5e-07, + "input_cost_per_audio_token_flex": 5e-07, + "input_cost_per_audio_token_priority": 1.8e-06, "input_cost_per_token": 3e-07, + "input_cost_per_token_batches": 1.5e-07, + "input_cost_per_token_flex": 1.5e-07, + "input_cost_per_token_priority": 5.4e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65535, "mode": "chat", "output_cost_per_reasoning_token": 2.5e-06, "output_cost_per_token": 2.5e-06, + "output_cost_per_token_batches": 1.25e-06, + "output_cost_per_token_flex": 1.25e-06, + "output_cost_per_token_priority": 4.5e-06, + "search_context_cost_per_query": {"search_context_size_low":0.035,"search_context_size_medium":0.035,"search_context_size_high":0.035}, + "search_free_requests": {"count":1500,"period":"day","shared_group":"gemini-2-flash"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "successor_model": "gemini-3.8-flash", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -29140,6 +29615,7 @@ ], "supports_audio_output": false, "supports_function_calling": true, + "supports_image_size": false, "supports_parallel_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -29149,26 +29625,12 @@ "supports_tool_choice": true, "supports_url_context": true, "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - }, - "search_free_requests": {"count": 1500, "period": "day", "shared_group": "gemini-2-flash"}, - "google_maps_grounding_cost_per_query": 0.025, - "input_cost_per_audio_token_batches": 5e-07, - "input_cost_per_token_batches": 1.5e-07, - "input_cost_per_token_flex": 1.5e-07, - "input_cost_per_token_priority": 5.4e-07, - "input_cost_per_audio_token_priority": 1.8e-06, - "output_cost_per_token_batches": 1.25e-06, - "output_cost_per_token_flex": 1.25e-06, - "output_cost_per_token_priority": 4.5e-06, - "supports_image_size": false + "supports_web_search": true }, "gemini-2.5-flash-image": { "deprecation_date": "2027-03-15", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.1-flash-lite-image", "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, @@ -29218,12 +29680,13 @@ }, "gemini-3-pro-image": { "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, - "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_flex": 1e-07, "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, @@ -29238,6 +29701,7 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "output_cost_per_image_token_batches": 6e-05, + "output_cost_per_image_token_priority": 0.000216, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, @@ -29292,6 +29756,7 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "output_cost_per_image_token_batches": 6e-05, + "output_cost_per_image_token_priority": 0.000216, "output_cost_per_token": 1.2e-05, "output_cost_per_token_priority": 2.16e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, @@ -29332,6 +29797,7 @@ "cache_read_input_token_cost_flex": 2.5e-08, "cache_read_input_token_cost_priority": 9e-08, "deprecation_date": "2027-05-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_image": 0.00056, "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -29344,6 +29810,7 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_image_token_batches": 3e-05, + "output_cost_per_image_token_priority": 0.000108, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, @@ -29390,6 +29857,7 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_image_token_batches": 3e-05, + "output_cost_per_image_token_priority": 0.000108, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", @@ -29438,6 +29906,7 @@ "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, "output_cost_per_image_token_batches": 1.5e-05, + "output_cost_per_image_token_priority": 5.4e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, @@ -29518,17 +29987,28 @@ }, "gemini-3.1-flash-lite": { "cache_read_input_audio_token_cost": 5e-08, - "deprecation_date": "2027-05-07", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "cache_read_input_audio_token_cost_batches": 2.5e-08, + "cache_read_input_audio_token_cost_flex": 2.5e-08, + "cache_read_input_audio_token_cost_priority": 9e-08, "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, + "deprecation_date": "2027-05-07", + "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token": 5e-07, + "input_cost_per_audio_token_above_200k_tokens": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_batches": 2.5e-07, + "input_cost_per_audio_token_above_200k_tokens_flex": 2.5e-07, + "input_cost_per_audio_token_above_200k_tokens_priority": 9e-07, + "input_cost_per_audio_token_batches": 2.5e-07, + "input_cost_per_audio_token_flex": 2.5e-07, + "input_cost_per_audio_token_priority": 9e-07, "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_flex": 1.25e-07, "input_cost_per_token_priority": 4.5e-07, - "input_cost_per_audio_token_priority": 9e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65536, @@ -29538,7 +30018,10 @@ "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, "output_cost_per_token_priority": 2.7e-06, + "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "successor_model": "gemini-3.5-flash-lite", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -29556,6 +30039,7 @@ "supports_audio_input": true, "supports_audio_output": false, "supports_function_calling": true, + "supports_native_streaming": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -29567,19 +30051,11 @@ "supports_video_input": true, "supports_vision": true, "supports_web_search": true, - "supports_native_streaming": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014, - "search_context_size_high": 0.014 - }, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, - "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07 + "web_search_billing_unit": "per_query" }, "gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "cache_read_input_token_cost": 3e-08, "cache_read_input_token_cost_batches": 1.5e-08, "cache_read_input_token_cost_flex": 1.5e-08, @@ -29675,19 +30151,38 @@ }, "gemini-2.5-flash-lite": { "cache_read_input_audio_token_cost": 3e-08, - "deprecation_date": "2026-10-20", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "cache_read_input_audio_token_cost_priority": 5.4e-08, "cache_read_input_token_cost": 1e-08, "cache_read_input_token_cost_flex": 1e-08, "cache_read_input_token_cost_priority": 1.8e-08, + "deprecation_date": "2026-10-20", + "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_audio_token": 3e-07, + "input_cost_per_audio_token_above_200k_tokens": 3e-07, + "input_cost_per_audio_token_above_200k_tokens_batches": 5e-08, + "input_cost_per_audio_token_above_200k_tokens_flex": 5e-08, + "input_cost_per_audio_token_above_200k_tokens_priority": 5.4e-07, + "input_cost_per_audio_token_batches": 5e-08, + "input_cost_per_audio_token_flex": 5e-08, + "input_cost_per_audio_token_priority": 5.4e-07, "input_cost_per_token": 1e-07, + "input_cost_per_token_batches": 5e-08, + "input_cost_per_token_flex": 5e-08, + "input_cost_per_token_priority": 1.8e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65535, "mode": "chat", "output_cost_per_reasoning_token": 4e-07, "output_cost_per_token": 4e-07, + "output_cost_per_token_batches": 2e-07, + "output_cost_per_token_flex": 2e-07, + "output_cost_per_token_priority": 7.2e-07, + "search_context_cost_per_query": {"search_context_size_low":0.035,"search_context_size_medium":0.035,"search_context_size_high":0.035}, + "search_free_requests": {"count":1500,"period":"day","shared_group":"gemini-2-flash"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "successor_model": "gemini-3.8-flash", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -29704,6 +30199,7 @@ ], "supports_audio_output": false, "supports_function_calling": true, + "supports_image_size": false, "supports_parallel_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -29713,23 +30209,7 @@ "supports_tool_choice": true, "supports_url_context": true, "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - }, - "search_free_requests": {"count": 1500, "period": "day", "shared_group": "gemini-2-flash"}, - "google_maps_grounding_cost_per_query": 0.025, - "input_cost_per_audio_token_batches": 5e-08, - "input_cost_per_token_batches": 5e-08, - "input_cost_per_token_flex": 5e-08, - "input_cost_per_token_priority": 1.8e-07, - "input_cost_per_audio_token_priority": 5.4e-07, - "output_cost_per_token_batches": 2e-07, - "output_cost_per_token_flex": 2e-07, - "output_cost_per_token_priority": 7.2e-07, - "supports_image_size": false + "supports_web_search": true }, "gemini-2.5-flash-lite-preview-09-2025": { "cache_read_input_token_cost": 1e-08, @@ -29825,6 +30305,8 @@ }, "gemini-live-2.5-flash-native-audio": { "deprecation_date": "2026-12-13", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.8-live", "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 5e-07, "litellm_provider": "vertex_ai-language-models", @@ -29958,6 +30440,8 @@ }, "gemini-2.5-pro": { "deprecation_date": "2026-10-20", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.8-flash", "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "cache_creation_input_token_cost_above_200k_tokens": 2.5e-07, @@ -30006,11 +30490,13 @@ "search_free_requests": {"count": 10000, "period": "day", "shared_group": "gemini-2.5-pro"}, "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_token_above_200k_tokens_batches": 1.25e-06, + "input_cost_per_token_above_200k_tokens_flex": 1.25e-06, "input_cost_per_token_above_200k_tokens_priority": 4.5e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, "input_cost_per_token_priority": 2.25e-06, "output_cost_per_token_above_200k_tokens_batches": 7.5e-06, + "output_cost_per_token_above_200k_tokens_flex": 7.5e-06, "output_cost_per_token_above_200k_tokens_priority": 2.7e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, @@ -30026,6 +30512,7 @@ "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, "input_cost_per_token_above_200k_tokens_batches": 2e-06, + "input_cost_per_token_above_200k_tokens_flex": 2e-06, "input_cost_per_token_above_200k_tokens_priority": 7.2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -30038,6 +30525,7 @@ "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_batches": 9e-06, + "output_cost_per_token_above_200k_tokens_flex": 9e-06, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_token_flex": 6e-06, @@ -30185,11 +30673,17 @@ }, "vertex_ai/gemini-3-flash-preview": { "cache_read_input_audio_token_cost": 1e-07, + "cache_read_input_audio_token_cost_priority": 1.8e-07, "cache_read_input_token_cost": 5e-08, "cache_read_input_token_cost_priority": 9e-08, "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token": 1e-06, + "input_cost_per_audio_token_above_200k_tokens": 1e-06, + "input_cost_per_audio_token_above_200k_tokens_batches": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_flex": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_priority": 1.8e-06, "input_cost_per_audio_token_batches": 5e-07, + "input_cost_per_audio_token_flex": 5e-07, "input_cost_per_audio_token_priority": 1.8e-06, "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -30204,7 +30698,7 @@ "output_cost_per_token_flex": 1.5e-06, "output_cost_per_token_priority": 5.4e-06, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -30238,6 +30732,8 @@ "vertex_ai/gemini-3.5-flash": { "prompt_cache_min_tokens": 4096, "deprecation_date": "2027-05-19", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.8-flash", "cache_read_input_token_cost": 1.5e-07, "cache_read_input_token_cost_batches": 7.5e-08, "input_cost_per_token": 1.5e-06, @@ -30349,6 +30845,8 @@ "output_cost_per_token_priority": 6.75e-06, "cache_read_input_token_cost_priority": 1.35e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.8-flash", "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, @@ -30411,6 +30909,8 @@ "output_cost_per_token_priority": 6.75e-06, "cache_read_input_token_cost_priority": 1.35e-07, "deprecation_date": "2027-01-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.8-flash", "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, @@ -30442,7 +30942,7 @@ "prompt_cache_min_tokens": 4096.0, "regional_endpoint_uplift_multiplier": 1.1, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -30572,6 +31072,7 @@ "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, "input_cost_per_token_above_200k_tokens_batches": 2e-06, + "input_cost_per_token_above_200k_tokens_flex": 2e-06, "input_cost_per_token_above_200k_tokens_priority": 7.2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -30584,6 +31085,7 @@ "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_batches": 9e-06, + "output_cost_per_token_above_200k_tokens_flex": 9e-06, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_token_flex": 6e-06, @@ -30822,6 +31324,8 @@ }, "gemini-embedding-001": { "deprecation_date": "2028-05-20", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-embedding-2", "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 1.2e-07, "litellm_provider": "vertex_ai-embedding-models", @@ -30846,6 +31350,7 @@ "output_cost_per_token": 0, "output_vector_size": 3072, "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "supports_embedding_image_input": true, "uses_embed_content": true }, "gemini-embedding-2": { @@ -30863,6 +31368,7 @@ "output_cost_per_token": 0, "output_vector_size": 3072, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "supports_embedding_image_input": true, "supports_multimodal": true, "uses_embed_content": true }, @@ -30881,6 +31387,7 @@ "output_cost_per_token": 0, "output_vector_size": 3072, "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "supports_embedding_image_input": true, "supports_multimodal": true, "uses_embed_content": true }, @@ -30899,6 +31406,7 @@ "output_cost_per_token": 0, "output_vector_size": 3072, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "supports_embedding_image_input": true, "supports_multimodal": true, "uses_embed_content": true }, @@ -30916,6 +31424,8 @@ }, "gemini/gemini-embedding-001": { "deprecation_date": "2028-05-14", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-embedding-2", "input_cost_per_token": 1.5e-07, "litellm_provider": "gemini", "max_input_tokens": 2048, @@ -30944,12 +31454,15 @@ "rpm": 10000, "source": "https://ai.google.dev/gemini-api/docs/pricing", "supports_audio_input": true, + "supports_embedding_image_input": true, "supports_multimodal": true, "supports_vision": true, "tpm": 10000000 }, "gemini/gemini-3-pro-image-preview": { "deprecation_date": "2026-06-25", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3-pro-image", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -30998,6 +31511,8 @@ }, "gemini/gemini-3.1-flash-image-preview": { "deprecation_date": "2026-06-25", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-nano-banana-2.1", "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, "litellm_provider": "gemini", @@ -31046,6 +31561,8 @@ "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2026-05-25", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.1-flash-lite", "input_cost_per_audio_token": 5e-07, "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, @@ -31103,6 +31620,8 @@ "input_cost_per_audio_token_batches": 2.5e-07 }, "gemini/gemini-embedding-2-preview": { + "deprecation_date": "2026-08-10", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", "input_cost_per_audio_token": 6.5e-06, "input_cost_per_audio_token_batches": 3.25e-06, "input_cost_per_image_token": 4.5e-07, @@ -31118,7 +31637,9 @@ "output_vector_size": 3072, "rpm": 10000, "source": "https://ai.google.dev/gemini-api/docs/pricing", + "successor_model": "gemini/gemini-embedding-2", "supports_audio_input": true, + "supports_embedding_image_input": true, "supports_multimodal": true, "supports_vision": true, "tpm": 10000000 @@ -31204,6 +31725,9 @@ "cache_read_input_token_cost_batches": 3e-08, "cache_read_input_token_cost_flex": 3e-08, "cache_read_input_token_cost_priority": 5.4e-08, + "deprecation_date": "2026-12-01", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.5-flash-lite", "input_cost_per_audio_token": 1e-06, "input_cost_per_audio_token_flex": 5e-07, "input_cost_per_token": 3e-07, @@ -31263,6 +31787,8 @@ "gemini/gemini-2.5-flash-image": { "cache_read_input_token_cost": 3e-08, "deprecation_date": "2027-03-15", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.1-flash-lite-image", "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, @@ -31490,6 +32016,8 @@ }, "gemini/deep-research-pro-preview-12-2025": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/deep-research-preview-04-2026", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -31707,6 +32235,8 @@ }, "gemini/gemini-2.5-flash-preview-tts": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash-tts", "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, "litellm_provider": "gemini", @@ -31787,11 +32317,16 @@ "output_cost_per_token_flex": 5e-06, "supports_url_context": true, "cache_read_input_token_cost_above_200k_tokens_batches": 2.5e-07, + "deprecation_date": "2026-12-01", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash", "input_cost_per_token_above_200k_tokens_batches": 1.25e-06, "output_cost_per_token_above_200k_tokens_batches": 7.5e-06 }, "gemini/gemini-2.5-computer-use-preview-10-2025": { "deprecation_date": "2026-07-28", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash", "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, "litellm_provider": "gemini", @@ -31830,6 +32365,8 @@ "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2027-05-07", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.5-flash-lite", "input_cost_per_audio_token": 5e-07, "input_cost_per_audio_token_flex": 2.5e-07, "input_cost_per_token": 2.5e-07, @@ -31890,7 +32427,7 @@ }, "gemini/gemini-3.5-flash-lite": { "cache_read_input_token_cost": 3e-08, - "cache_read_input_token_cost_batches": 2e-08, + "cache_read_input_token_cost_batches": 1.5e-08, "cache_read_input_token_cost_flex": 2e-08, "cache_read_input_token_cost_priority": 5e-08, "input_cost_per_token": 3e-07, @@ -32295,7 +32832,9 @@ "supports_video_input": true, "supports_vision": true, "tpm": 800000, - "deprecation_date": "2026-10-22" + "deprecation_date": "2026-10-22", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-omni-1.1-flash" }, "gemini/gemini-3.1-pro-preview": { "prompt_cache_min_tokens": 4096, @@ -32431,11 +32970,17 @@ }, "gemini-3-flash-preview": { "cache_read_input_audio_token_cost": 1e-07, + "cache_read_input_audio_token_cost_priority": 1.8e-07, "cache_read_input_token_cost": 5e-08, "cache_read_input_token_cost_priority": 9e-08, "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token": 1e-06, + "input_cost_per_audio_token_above_200k_tokens": 1e-06, + "input_cost_per_audio_token_above_200k_tokens_batches": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_flex": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_priority": 1.8e-06, "input_cost_per_audio_token_batches": 5e-07, + "input_cost_per_audio_token_flex": 5e-07, "input_cost_per_audio_token_priority": 1.8e-06, "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -32451,7 +32996,7 @@ "output_cost_per_token_flex": 1.5e-06, "output_cost_per_token_priority": 5.4e-06, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -32487,13 +33032,13 @@ "input_cost_per_audio_token": 1.5e-06, "input_cost_per_token": 1.5e-06, "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 1048576, - "max_output_tokens": 65535, + "max_input_tokens": 131072, + "max_output_tokens": 57920, "mode": "chat", "output_cost_per_reasoning_token": 9e-06, "output_cost_per_token": 9e-06, "output_cost_per_video_token": 1.75e-05, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/omni-flash-preview", "supported_endpoints": [ "/v1/chat/completions" ], @@ -32511,11 +33056,14 @@ "supports_reasoning": true, "supports_system_messages": true, "supports_video_input": true, - "supports_vision": true + "supports_vision": true, + "deprecation_date": "2026-11-06" }, "gemini-3.5-flash": { "prompt_cache_min_tokens": 4096, "deprecation_date": "2027-05-19", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.8-flash", "cache_read_input_token_cost": 1.5e-07, "cache_read_input_token_cost_batches": 7.5e-08, "input_cost_per_audio_token": 1.5e-06, @@ -32627,6 +33175,8 @@ "output_cost_per_token_priority": 6.75e-06, "cache_read_input_token_cost_priority": 1.35e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.8-flash", "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, @@ -32689,6 +33239,8 @@ "output_cost_per_token_priority": 6.75e-06, "cache_read_input_token_cost_priority": 1.35e-07, "deprecation_date": "2027-01-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.8-flash", "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, @@ -32719,7 +33271,7 @@ "output_cost_per_token_priority": 6.75e-06, "prompt_cache_min_tokens": 4096.0, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -32807,6 +33359,8 @@ "gemini/gemini-2.5-pro-preview-tts": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash-tts", "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1e-06, "input_cost_per_token_batches": 5e-07, @@ -33059,6 +33613,8 @@ }, "gemini/veo-3.1-fast-generate-preview": { "deprecation_date": "2026-10-22", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-omni-1.1-flash", "litellm_provider": "gemini", "max_input_tokens": 1024, "mode": "video_generation", @@ -33075,6 +33631,8 @@ }, "gemini/veo-3.1-generate-preview": { "deprecation_date": "2026-10-22", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-omni-1.1-flash", "litellm_provider": "gemini", "max_input_tokens": 1024, "mode": "video_generation", @@ -33090,6 +33648,8 @@ }, "gemini/veo-3.1-lite-generate-preview": { "deprecation_date": "2026-10-22", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-omni-1.1-flash", "litellm_provider": "gemini", "max_input_tokens": 1024, "mode": "video_generation", @@ -33425,6 +33985,7 @@ }, "github_copilot/gpt-4.1": { "deprecation_date": "2026-06-01", + "deprecation_source": "https://raw.githubusercontent.com/github/docs/main/data/tables/copilot/model-deprecation-history.yml", "litellm_provider": "github_copilot", "max_input_tokens": 128000, "max_output_tokens": 16384, @@ -33437,6 +33998,7 @@ }, "github_copilot/gpt-4.1-2025-04-14": { "deprecation_date": "2026-06-01", + "deprecation_source": "https://raw.githubusercontent.com/github/docs/main/data/tables/copilot/model-deprecation-history.yml", "litellm_provider": "github_copilot", "max_input_tokens": 128000, "max_output_tokens": 16384, @@ -33538,6 +34100,7 @@ "cache_read_input_token_cost": 2.5e-07, "cache_read_input_token_cost_above_272k_tokens": 5e-07, "deprecation_date": "2026-10-19", + "deprecation_source": "https://raw.githubusercontent.com/github/docs/main/data/tables/copilot/model-deprecation-history.yml", "input_cost_per_token": 2.5e-06, "input_cost_per_token_above_272k_tokens": 5e-06, "litellm_provider": "github_copilot", @@ -33580,6 +34143,7 @@ "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, "deprecation_date": "2026-10-19", + "deprecation_source": "https://raw.githubusercontent.com/github/docs/main/data/tables/copilot/model-deprecation-history.yml", "input_cost_per_token": 5e-06, "input_cost_per_token_above_272k_tokens": 1e-05, "litellm_provider": "github_copilot", @@ -34433,6 +34997,7 @@ }, "google.gemma-3-12b-it": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 9e-08, "input_cost_per_token_batches": 5e-08, "input_cost_per_token_flex": 5e-08, @@ -34454,6 +35019,7 @@ }, "google.gemma-3-27b-it": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2.3e-07, "input_cost_per_token_batches": 1.2e-07, "input_cost_per_token_flex": 1.2e-07, @@ -34475,6 +35041,7 @@ }, "google.gemma-3-4b-it": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 4e-08, "input_cost_per_token_batches": 2e-08, "input_cost_per_token_flex": 2e-08, @@ -34509,6 +35076,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.2e-05, "cache_read_input_token_cost_above_200k_tokens": 6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "global.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -34544,6 +35113,8 @@ "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-10-14", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "global.anthropic.claude-sonnet-5", "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -34632,12 +35203,15 @@ }, "gpt-3.5-turbo": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 5e-07, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -34646,6 +35220,8 @@ }, "gpt-3.5-turbo-0125": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, "litellm_provider": "openai", @@ -34653,6 +35229,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 7.5e-07, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -34663,6 +35240,8 @@ }, "gpt-3.5-turbo-1106": { "deprecation_date": "2026-09-28", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1e-06, "input_cost_per_token_batches": 1e-06, "litellm_provider": "openai", @@ -34670,6 +35249,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -34680,18 +35260,22 @@ }, "gpt-3.5-turbo-16k": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 4e-06, + "fedramp_uplift_multiplier": 1.1, "supports_prompt_caching": true, "supports_system_messages": true, "supports_tool_choice": true }, "gpt-3.5-turbo-instruct": { "deprecation_date": "2026-09-28", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1.5e-06, "litellm_provider": "text-completion-openai", "max_input_tokens": 8192, @@ -34710,12 +35294,15 @@ }, "gpt-4": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 3e-05, "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-05, + "fedramp_uplift_multiplier": 1.1, "supports_function_calling": true, "supports_prompt_caching": true, "supports_system_messages": true, @@ -34723,6 +35310,8 @@ }, "gpt-4-0613": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 3e-05, "input_cost_per_token_batches": 1.5e-05, "litellm_provider": "openai", @@ -34730,6 +35319,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-05, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -34739,12 +35329,15 @@ }, "gpt-4-1106-preview": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1e-05, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 3e-05, + "fedramp_uplift_multiplier": 1.1, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -34753,12 +35346,15 @@ }, "gpt-4-turbo": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1e-05, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 3e-05, + "fedramp_uplift_multiplier": 1.1, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -34769,6 +35365,8 @@ }, "gpt-4-turbo-2024-04-09": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1e-05, "input_cost_per_token_batches": 5e-06, "litellm_provider": "openai", @@ -34776,6 +35374,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 3e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 1.5e-05, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -34789,6 +35388,9 @@ "gpt-4.1": { "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_priority": 8.75e-07, + "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_priority": 3.5e-06, @@ -34797,6 +35399,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-06, "output_cost_per_token_priority": 1.4e-05, "search_context_cost_per_query": { @@ -34832,6 +35435,8 @@ "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2e-06, "input_cost_per_token_priority": 3.5e-06, "input_cost_per_token_batches": 1e-06, @@ -34840,6 +35445,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 1.4e-05, "output_cost_per_token_batches": 4e-06, "search_context_cost_per_query": { @@ -34874,6 +35480,9 @@ "gpt-4.1-mini": { "cache_read_input_token_cost": 1e-07, "cache_read_input_token_cost_priority": 1.75e-07, + "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 4e-07, "input_cost_per_token_batches": 2e-07, "input_cost_per_token_priority": 7e-07, @@ -34882,6 +35491,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 1.6e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 8e-07, "output_cost_per_token_priority": 2.8e-06, "search_context_cost_per_query": { @@ -34917,6 +35527,8 @@ "cache_read_input_token_cost": 1e-07, "cache_read_input_token_cost_priority": 1.75e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 4e-07, "input_cost_per_token_priority": 7e-07, "input_cost_per_token_batches": 2e-07, @@ -34925,6 +35537,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 1.6e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2.8e-06, "output_cost_per_token_batches": 8e-07, "search_context_cost_per_query": { @@ -34960,6 +35573,8 @@ "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_priority": 5e-08, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-luna", "input_cost_per_token": 1e-07, "input_cost_per_token_batches": 5e-08, "input_cost_per_token_priority": 2e-07, @@ -34968,6 +35583,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_priority": 8e-07, "source": "https://developers.openai.com/api/docs/pricing", @@ -34997,6 +35613,8 @@ "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_priority": 5e-08, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-luna", "input_cost_per_token": 1e-07, "input_cost_per_token_priority": 2e-07, "input_cost_per_token_batches": 5e-08, @@ -35005,6 +35623,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 8e-07, "output_cost_per_token_batches": 2e-07, "source": "https://developers.openai.com/api/docs/pricing", @@ -35033,6 +35652,9 @@ "gpt-4o": { "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_priority": 2.125e-06, + "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, "input_cost_per_token_priority": 4.25e-06, @@ -35041,6 +35663,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 1.7e-05, "source": "https://developers.openai.com/api/docs/pricing", @@ -35055,6 +35678,8 @@ }, "gpt-4o-2024-05-13": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 5e-06, "input_cost_per_token_batches": 2.5e-06, "input_cost_per_token_priority": 8.75e-06, @@ -35063,6 +35688,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 7.5e-06, "output_cost_per_token_priority": 2.625e-05, "source": "https://developers.openai.com/api/docs/pricing", @@ -35078,6 +35704,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_priority": 2.125e-06, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2.5e-06, "input_cost_per_token_priority": 4.25e-06, "input_cost_per_token_batches": 1.25e-06, @@ -35086,6 +35714,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 1.7e-05, "output_cost_per_token_batches": 5e-06, "source": "https://developers.openai.com/api/docs/pricing", @@ -35102,6 +35731,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_priority": 2.125e-06, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2.5e-06, "input_cost_per_token_priority": 4.25e-06, "input_cost_per_token_batches": 1.25e-06, @@ -35110,6 +35741,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 1.7e-05, "output_cost_per_token_batches": 5e-06, "source": "https://developers.openai.com/api/docs/pricing", @@ -35124,6 +35756,8 @@ }, "gpt-4o-audio-preview-2024-12-17": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 4e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "openai", @@ -35141,6 +35775,8 @@ }, "gpt-4o-audio-preview-2025-06-03": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 4e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "openai", @@ -35158,6 +35794,8 @@ }, "gpt-audio": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "openai", @@ -35228,6 +35866,8 @@ }, "gpt-audio-2025-08-28": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "openai", @@ -35265,6 +35905,8 @@ }, "gpt-audio-mini": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, "litellm_provider": "openai", @@ -35302,6 +35944,8 @@ }, "gpt-audio-mini-2025-10-06": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, "litellm_provider": "openai", @@ -35372,11 +36016,16 @@ "supports_tool_choice": true, "supports_vision": false, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini": { "cache_read_input_token_cost": 7.5e-08, "cache_read_input_token_cost_priority": 1.25e-07, + "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, "input_cost_per_token_priority": 2.5e-07, @@ -35385,6 +36034,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-07, "output_cost_per_token_priority": 1e-06, "supports_function_calling": true, @@ -35406,6 +36056,8 @@ "cache_read_input_token_cost": 7.5e-08, "cache_read_input_token_cost_priority": 1.25e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 1.5e-07, "input_cost_per_token_priority": 2.5e-07, "input_cost_per_token_batches": 7.5e-08, @@ -35414,6 +36066,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 1e-06, "output_cost_per_token_batches": 3e-07, "search_context_cost_per_query": { @@ -35433,6 +36086,7 @@ }, "gpt-4o-mini-audio-preview-2024-12-17": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 1.5e-07, "litellm_provider": "openai", @@ -35452,6 +36106,7 @@ "cache_creation_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, "litellm_provider": "openai", @@ -35476,6 +36131,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-07, "search_context_cost_per_query": { "search_context_size_high": 0.025, @@ -35494,6 +36150,8 @@ }, "gpt-4o-mini-search-preview-2025-03-11": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "cache_read_input_token_cost": 7.5e-08, "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, @@ -35502,6 +36160,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-07, "search_context_cost_per_query": { "search_context_size_high": 0.025, @@ -35531,11 +36190,15 @@ "/v1/audio/transcriptions" ], "deprecation_date": "2027-02-26", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-live-transcribe", "input_cost_per_second": 5e-05, "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini-tts": { "deprecation_date": "2027-01-06", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", @@ -35556,6 +36219,8 @@ }, "gpt-4o-mini-tts-2025-03-20": { "deprecation_date": "2027-01-06", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", @@ -35583,6 +36248,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 5e-06, "search_context_cost_per_query": { "search_context_size_high": 0.025, @@ -35601,6 +36267,8 @@ }, "gpt-4o-search-preview-2025-03-11": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -35609,6 +36277,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 5e-06, "search_context_cost_per_query": { "search_context_size_high": 0.025, @@ -35638,6 +36307,8 @@ "/v1/audio/transcriptions" ], "deprecation_date": "2027-02-26", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-live-transcribe", "input_cost_per_second": 0.0001, "source": "https://developers.openai.com/api/docs/pricing" }, @@ -35646,6 +36317,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_batches": 6.3e-07, "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_token": 5e-06, "litellm_provider": "openai", "mode": "image_generation", @@ -35654,6 +36327,7 @@ "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3.2e-05, + "output_cost_per_image_token_batches": 1.6e-05, "output_cost_per_token_batches": 5e-06, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -35667,6 +36341,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_batches": 6.3e-07, "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_token": 5e-06, "litellm_provider": "openai", "mode": "image_generation", @@ -35675,6 +36351,7 @@ "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3.2e-05, + "output_cost_per_image_token_batches": 1.6e-05, "output_cost_per_token_batches": 5e-06, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -35694,6 +36371,7 @@ "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", @@ -35729,6 +36407,7 @@ "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -35764,6 +36443,7 @@ "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -35790,6 +36470,8 @@ }, "low/1024-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.009, "litellm_provider": "openai", "mode": "image_generation", @@ -35802,6 +36484,8 @@ }, "low/1024-x-1536/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35814,6 +36498,8 @@ }, "low/1536-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35826,6 +36512,8 @@ }, "medium/1024-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.034, "litellm_provider": "openai", "mode": "image_generation", @@ -35838,6 +36526,8 @@ }, "medium/1024-x-1536/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.05, "litellm_provider": "openai", "mode": "image_generation", @@ -35850,6 +36540,8 @@ }, "medium/1536-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.05, "litellm_provider": "openai", "mode": "image_generation", @@ -35862,6 +36554,8 @@ }, "high/1024-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.133, "litellm_provider": "openai", "mode": "image_generation", @@ -35874,6 +36568,8 @@ }, "high/1024-x-1536/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.2, "litellm_provider": "openai", "mode": "image_generation", @@ -35886,6 +36582,8 @@ }, "high/1536-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.2, "litellm_provider": "openai", "mode": "image_generation", @@ -35898,6 +36596,8 @@ }, "standard/1024-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.009, "litellm_provider": "openai", "mode": "image_generation", @@ -35910,6 +36610,8 @@ }, "standard/1024-x-1536/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35922,6 +36624,8 @@ }, "standard/1536-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35934,6 +36638,8 @@ }, "1024-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.009, "litellm_provider": "openai", "mode": "image_generation", @@ -35946,6 +36652,8 @@ }, "1024-x-1536/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35958,6 +36666,8 @@ }, "1536-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35978,7 +36688,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "low/1024-x-1536/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -35990,7 +36702,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "low/1536-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -36002,7 +36716,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "medium/1024-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.034, @@ -36014,7 +36730,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "medium/1024-x-1536/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.05, @@ -36026,7 +36744,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "medium/1536-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.05, @@ -36038,7 +36758,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "high/1024-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.133, @@ -36050,7 +36772,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "high/1024-x-1536/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.2, @@ -36062,7 +36786,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "high/1536-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.2, @@ -36074,7 +36800,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "standard/1024-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.009, @@ -36086,7 +36814,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "standard/1024-x-1536/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -36098,7 +36828,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "standard/1536-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -36110,7 +36842,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "1024-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.009, @@ -36122,7 +36856,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "1024-x-1536/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -36134,7 +36870,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "1536-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -36146,7 +36884,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "gpt-5": { "cache_read_input_token_cost": 1.25e-07, @@ -36154,6 +36894,8 @@ "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, @@ -36163,6 +36905,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, @@ -36209,12 +36952,15 @@ "gpt-5-codex": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 272000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5-codex", "supported_endpoints": [ "/v1/responses" @@ -36249,6 +36995,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2e-05, "reasoning_contexts": [ "auto", @@ -36294,17 +37041,22 @@ "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": false, "supports_minimal_reasoning_effort": false, - "deprecation_date": "2027-04-01" + "deprecation_date": "2027-04-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-sol" }, "gpt-5.1-codex-mini": { "cache_read_input_token_cost": 2.5e-08, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 2.5e-07, "litellm_provider": "openai", "max_input_tokens": 400000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 2e-06, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.1-codex-mini", "supported_endpoints": [ "/v1/responses" @@ -36329,12 +37081,15 @@ "gpt-5.1-codex-max": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 400000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.1-codex-max", "supported_endpoints": [ "/v1/responses" @@ -36360,12 +37115,15 @@ "gpt-5.1-codex": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 400000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.1-codex", "supported_endpoints": [ "/v1/responses" @@ -36391,12 +37149,15 @@ "gpt-5.1-chat-latest": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.1-chat-latest", "supported_endpoints": [ "/v1/chat/completions", @@ -36425,6 +37186,8 @@ "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2027-04-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-sol", "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", @@ -36432,6 +37195,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2e-05, "reasoning_contexts": [ "auto", @@ -36490,6 +37254,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2.8e-05, "reasoning_contexts": [ "auto", @@ -36541,12 +37306,15 @@ "gpt-5.2-codex": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.75e-06, "litellm_provider": "openai", "max_input_tokens": 272000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.2-codex", "supported_endpoints": [ "/v1/responses" @@ -36572,12 +37340,15 @@ "gpt-5.2-chat-latest": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2026-08-10", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.75e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.2-chat-latest", "supported_endpoints": [ "/v1/chat/completions", @@ -36612,6 +37383,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2.8e-05, "reasoning_contexts": [ "auto", @@ -36668,6 +37440,7 @@ "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 0.000168, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 8.4e-05, "reasoning_contexts": [ "auto", @@ -36716,6 +37489,7 @@ "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 0.000168, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 8.4e-05, "reasoning_contexts": [ "auto", @@ -36822,6 +37596,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -36915,6 +37690,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37016,6 +37792,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37108,6 +37885,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37198,6 +37976,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37290,6 +38069,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37381,6 +38161,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37425,10 +38206,11 @@ "input_cost_per_token": 1.25e-05, "input_cost_per_token_above_272k_tokens": 2.5e-05, "litellm_provider": "openai", - "max_input_tokens": 400000, + "max_input_tokens": 272000, "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 7.5e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_above_272k_tokens": 0.0001125, "supported_endpoints": [ "/v1/chat/completions", @@ -37463,10 +38245,11 @@ "input_cost_per_token": 1.25e-05, "input_cost_per_token_above_272k_tokens": 2.5e-05, "litellm_provider": "openai", - "max_input_tokens": 400000, + "max_input_tokens": 272000, "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 7.5e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_above_272k_tokens": 0.0001125, "supported_endpoints": [ "/v1/chat/completions", @@ -37501,10 +38284,11 @@ "input_cost_per_token": 1.25e-05, "input_cost_per_token_above_272k_tokens": 2.5e-05, "litellm_provider": "openai", - "max_input_tokens": 400000, + "max_input_tokens": 272000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 7.5e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_above_272k_tokens": 0.0001125, "supported_endpoints": [ "/v1/responses" @@ -37542,6 +38326,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 2e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_above_272k_tokens": 3e-05, "supported_endpoints": [ "/v1/chat/completions", @@ -37580,6 +38365,7 @@ "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 2e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_above_272k_tokens": 3e-05, "supported_endpoints": [ "/v1/responses" @@ -37613,6 +38399,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 3e-05, + "fedramp_uplift_multiplier": 1.1, "reasoning_effort_levels": [ "medium" ], @@ -37681,6 +38468,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37751,6 +38539,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37813,6 +38602,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37872,6 +38662,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37939,6 +38730,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -38004,6 +38796,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -38061,6 +38854,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38121,6 +38915,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38183,6 +38978,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38245,6 +39041,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38304,6 +39101,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38337,13 +39135,17 @@ "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "deprecation_date": "2027-04-01" + "deprecation_date": "2027-04-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna" }, "gpt-5.4-nano-2026-03-17": { "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_batches": 1e-08, "cache_read_input_token_cost_flex": 1e-08, "deprecation_date": "2027-04-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2e-07, "input_cost_per_token_flex": 1e-07, "input_cost_per_token_batches": 1e-07, @@ -38364,6 +39166,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38400,6 +39203,8 @@ }, "gpt-5-pro": { "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", @@ -38407,6 +39212,7 @@ "max_output_tokens": 272000, "mode": "responses", "output_cost_per_token": 0.00012, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 6e-05, "reasoning_contexts": [ "auto", @@ -38449,6 +39255,8 @@ }, "gpt-5-pro-2025-10-06": { "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", @@ -38456,6 +39264,7 @@ "max_output_tokens": 272000, "mode": "responses", "output_cost_per_token": 0.00012, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 6e-05, "reasoning_contexts": [ "auto", @@ -38502,6 +39311,8 @@ "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, @@ -38511,6 +39322,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, @@ -38557,12 +39369,15 @@ "gpt-5-chat": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.2-chat-latest", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -38592,12 +39407,15 @@ "gpt-5-chat-latest": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5-chat-latest", "supported_endpoints": [ "/v1/chat/completions", @@ -38630,6 +39448,7 @@ "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2.8e-05, "reasoning_contexts": [ "auto", @@ -38669,17 +39488,22 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "deprecation_date": "2027-04-01" + "deprecation_date": "2027-04-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-sol" }, "gpt-5.3-chat-latest": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2026-08-10", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.75e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.3-chat-latest", "supported_endpoints": [ "/v1/chat/completions", @@ -38708,6 +39532,8 @@ "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_flex": 1.25e-07, @@ -38717,6 +39543,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 2e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, @@ -38766,6 +39593,8 @@ "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_flex": 1.25e-07, @@ -38775,6 +39604,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 2e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, @@ -38823,6 +39653,8 @@ "cache_read_input_token_cost_batches": 2.5e-09, "cache_read_input_token_cost_flex": 2.5e-09, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-luna", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 2.5e-08, "input_cost_per_token_flex": 2.5e-08, @@ -38831,6 +39663,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 4e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, "reasoning_contexts": [ @@ -38878,6 +39711,8 @@ "cache_read_input_token_cost_batches": 2.5e-09, "cache_read_input_token_cost_flex": 2.5e-09, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-luna", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 2.5e-08, "input_cost_per_token_flex": 2.5e-08, @@ -38886,6 +39721,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 4e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, "reasoning_contexts": [ @@ -38933,6 +39769,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_batches": 6.3e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image_token": 1e-05, "input_cost_per_image_token_batches": 5e-06, "input_cost_per_token": 5e-06, @@ -38951,6 +39789,8 @@ "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_batches": 1e-07, "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image_token": 2.5e-06, "input_cost_per_image_token_batches": 1.25e-06, "input_cost_per_token": 2e-06, @@ -38958,6 +39798,7 @@ "litellm_provider": "openai", "mode": "image_generation", "output_cost_per_image_token": 8e-06, + "output_cost_per_image_token_batches": 4e-06, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", @@ -38970,6 +39811,8 @@ "cache_read_input_image_token_cost": 5e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -39045,6 +39888,9 @@ "max_input_tokens": 128000, "max_output_tokens": 32000, "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 2.4e-05, "source": "https://developers.openai.com/api/docs/pricing", @@ -39100,6 +39946,8 @@ "supports_audio_output": true, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, "supports_system_messages": true, "supports_tool_choice": true }, @@ -39136,6 +39984,8 @@ "supports_audio_output": true, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, "supports_system_messages": true, "supports_tool_choice": true }, @@ -39145,6 +39995,8 @@ "cache_read_input_image_token_cost": 8e-08, "cache_read_input_token_cost": 6e-08, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, "input_cost_per_token": 6e-07, @@ -39180,6 +40032,8 @@ "cache_read_input_image_token_cost": 5e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -39503,16 +40357,6 @@ "supports_response_schema": true, "supports_vision": true }, - "groq/llama-guard-3-8b": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 2e-07, - "litellm_provider": "groq", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 2e-07, - "source": "https://console.groq.com/docs/model/llama-guard-3-8b" - }, "groq/meta-llama/llama-prompt-guard-2-22m": { "input_cost_per_token": 3e-08, "litellm_provider": "groq", @@ -39659,6 +40503,8 @@ }, "high/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.167, "input_cost_per_pixel": 1.59263611e-07, "litellm_provider": "openai", @@ -39670,6 +40516,8 @@ }, "high/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.25, "input_cost_per_pixel": 1.58945719e-07, "litellm_provider": "openai", @@ -39681,6 +40529,8 @@ }, "high/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.25, "input_cost_per_pixel": 1.58945719e-07, "litellm_provider": "openai", @@ -40058,6 +40908,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "jp.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -41220,6 +42072,8 @@ }, "low/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.011, "input_cost_per_pixel": 1.0490417e-08, "litellm_provider": "openai", @@ -41231,6 +42085,8 @@ }, "low/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.016, "input_cost_per_pixel": 1.0172526e-08, "litellm_provider": "openai", @@ -41242,6 +42098,8 @@ }, "low/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.016, "input_cost_per_pixel": 1.0172526e-08, "litellm_provider": "openai", @@ -41265,6 +42123,8 @@ }, "medium/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.042, "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "openai", @@ -41276,6 +42136,8 @@ }, "medium/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.063, "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "openai", @@ -41287,6 +42149,8 @@ }, "medium/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.063, "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "openai", @@ -41298,6 +42162,8 @@ }, "low/1024-x-1024/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.005, "litellm_provider": "openai", "mode": "image_generation", @@ -41307,6 +42173,8 @@ }, "low/1024-x-1536/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.006, "litellm_provider": "openai", "mode": "image_generation", @@ -41316,6 +42184,8 @@ }, "low/1536-x-1024/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.006, "litellm_provider": "openai", "mode": "image_generation", @@ -41325,6 +42195,8 @@ }, "medium/1024-x-1024/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.011, "litellm_provider": "openai", "mode": "image_generation", @@ -41334,6 +42206,8 @@ }, "medium/1024-x-1536/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.015, "litellm_provider": "openai", "mode": "image_generation", @@ -41343,6 +42217,8 @@ }, "medium/1536-x-1024/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.015, "litellm_provider": "openai", "mode": "image_generation", @@ -41390,6 +42266,7 @@ }, "meta.llama3-1-405b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2.4e-06, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -41402,6 +42279,7 @@ }, "meta.llama3-1-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "input_cost_per_token_batches": 3.6e-07, "litellm_provider": "bedrock", @@ -41416,6 +42294,7 @@ }, "meta.llama3-1-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2.2e-07, "input_cost_per_token_batches": 1.1e-07, "litellm_provider": "bedrock", @@ -41430,6 +42309,7 @@ }, "meta.llama3-2-11b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.6e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -41443,6 +42323,7 @@ }, "meta.llama3-2-1b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-1b-instruct.md", "input_cost_per_token": 1e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -41455,6 +42336,7 @@ }, "meta.llama3-2-3b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-3b-instruct.md", "input_cost_per_token": 1.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -41467,6 +42349,7 @@ }, "meta.llama3-2-90b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -41480,6 +42363,7 @@ }, "meta.llama3-3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "input_cost_per_token_batches": 3.6e-07, "litellm_provider": "bedrock_converse", @@ -41494,6 +42378,7 @@ }, "meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 2.65e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -41504,6 +42389,7 @@ }, "meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": 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"https://tokenfactory.nebius.com/models/catalog/text2text/zai-org%2FGLM-5.2" + "source": "https://tokenfactory.nebius.com/api/public/models_info", + "cache_read_input_token_cost": 1.4e-07 }, "nebius/zai-org/GLM-5.3": { "input_cost_per_token": 1.4e-06, "litellm_provider": "nebius", - "max_input_tokens": 1024000, + "max_input_tokens": 1048576, "max_output_tokens": 1024000, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://tokenfactory.nebius.com/models/catalog/text2text/zai-org%2FGLM-5.3", + "source": "https://tokenfactory.nebius.com/api/public/models_info", "supports_function_calling": true, - "supports_reasoning": true + "supports_reasoning": true, + "cache_read_input_token_cost": 2.6e-07 }, "nebius/zai-org/GLM-5.3-Flash": { - "max_input_tokens": 1024000, + "max_input_tokens": 1048576, "max_output_tokens": 1024000, "input_cost_per_token": 1.5e-07, "output_cost_per_token": 5e-07, @@ -44578,8 +45507,9 @@ "mode": "chat", "supports_function_calling": true, "supports_reasoning": true, - "source": "https://tokenfactory.nebius.com/models/catalog/text2text/zai-org%2FGLM-5.3-Flash", - "supports_vision": true + "source": "https://tokenfactory.nebius.com/api/public/models_info", + "supports_vision": true, + "cache_read_input_token_cost": 3e-08 }, "nebius/BAAI/bge-en-icl": { "max_input_tokens": 32768, @@ -44615,6 +45545,7 @@ }, "nvidia.nemotron-nano-12b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2e-07, "input_cost_per_token_batches": 1e-07, "input_cost_per_token_flex": 1e-07, @@ -44636,6 +45567,7 @@ }, "nvidia.nemotron-nano-9b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 6e-08, "input_cost_per_token_batches": 3e-08, "input_cost_per_token_flex": 3e-08, @@ -44702,6 +45634,7 @@ "o1": { "cache_read_input_token_cost": 7.5e-06, "deprecation_date": "2026-10-23", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", @@ -44709,6 +45642,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 6e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-05, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -44724,6 +45658,8 @@ "o1-2024-12-17": { "cache_read_input_token_cost": 7.5e-06, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", @@ -44731,6 +45667,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 6e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-05, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -44745,6 +45682,8 @@ }, "o1-pro": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 0.00015, "input_cost_per_token_batches": 7.5e-05, "litellm_provider": "openai", @@ -44752,6 +45691,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 0.0006, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 0.0003, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -44778,6 +45718,8 @@ }, "o1-pro-2025-03-19": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 0.00015, "input_cost_per_token_batches": 7.5e-05, "litellm_provider": "openai", @@ -44785,6 +45727,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 0.0006, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 0.0003, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -44814,6 +45757,7 @@ "cache_read_input_token_cost_flex": 2.5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "deprecation_date": "2026-12-11", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -44823,6 +45767,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, @@ -44870,6 +45815,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 4e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/o3-deep-research", "supported_endpoints": [ "/v1/batch", @@ -44891,10 +45837,14 @@ "supports_tool_choice": false, "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-07-23" + "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol" }, "o3-deep-research-2025-06-26": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "cache_read_input_token_cost": 2.5e-06, "input_cost_per_token": 1e-05, "litellm_provider": "openai", @@ -44902,6 +45852,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 4e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/o3-deep-research", "supported_endpoints": [ "/v1/batch", @@ -44929,6 +45880,8 @@ "cache_read_input_token_cost_flex": 2.5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -44938,6 +45891,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, @@ -44980,6 +45934,8 @@ "o3-mini": { "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "openai", @@ -44987,6 +45943,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2.2e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -45000,6 +45957,8 @@ "o3-mini-2025-01-31": { "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "openai", @@ -45007,6 +45966,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2.2e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -45019,6 +45979,8 @@ }, "o3-pro": { "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "openai", @@ -45026,6 +45988,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 8e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-05, "reasoning_contexts": [ "auto", @@ -45063,6 +46026,8 @@ }, "o3-pro-2025-06-10": { "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "openai", @@ -45070,6 +46035,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 8e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-05, "reasoning_contexts": [ "auto", @@ -45110,6 +46076,8 @@ "cache_read_input_token_cost_flex": 1.38e-07, "cache_read_input_token_cost_priority": 5e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "input_cost_per_token_flex": 5.5e-07, @@ -45119,6 +46087,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2.2e-06, "output_cost_per_token_flex": 2.2e-06, "output_cost_per_token_priority": 8e-06, @@ -45146,6 +46115,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/o4-mini-deep-research", "supported_endpoints": [ "/v1/batch", @@ -45167,10 +46137,14 @@ "supports_tool_choice": false, "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-07-23" + "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol" }, "o4-mini-deep-research-2025-06-26": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 2e-06, "litellm_provider": "openai", @@ -45178,6 +46152,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/o4-mini-deep-research", "supported_endpoints": [ "/v1/batch", @@ -45205,6 +46180,8 @@ "cache_read_input_token_cost_flex": 1.38e-07, "cache_read_input_token_cost_priority": 5e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "input_cost_per_token_flex": 5.5e-07, @@ -45214,6 +46191,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2.2e-06, "output_cost_per_token_flex": 2.2e-06, "output_cost_per_token_priority": 8e-06, @@ -45503,6 +46481,7 @@ "mode": "embedding", "output_vector_size": 1024, "source": "https://www.oracle.com/artificial-intelligence/enterprise-ai/cost-estimator/", + "supports_embedding_image_input": true, "supports_vision": true }, "oci/cohere.command-a-reasoning-08-2025": { @@ -46388,6 +47367,19 @@ "supports_response_schema": true, "supports_tool_choice": false }, + "parallel_ai/decision": { + "input_cost_per_query": 0.001, + "input_cost_per_token": 0.0, + "output_cost_per_token": 0.0, + "litellm_provider": "parallel_ai", + "max_input_tokens": 32000, + "mode": "evaluation", + "source": "https://docs.parallel.ai/getting-started/pricing#decisions-api", + "supported_endpoints": [ + "/v1/decisions", + "/v1/systemone" + ] + }, "parallel_ai/search": { "input_cost_per_query": 0.005, "litellm_provider": "parallel_ai", @@ -47005,6 +47997,7 @@ }, "qwen.qwen3-coder-480b-a35b-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-qwen-qwen3-coder-480b-a35b-instruct.html", "input_cost_per_token": 4.5e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 262144, @@ -47036,6 +48029,7 @@ }, "qwen.qwen3-coder-30b-a3b-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, "input_cost_per_token_priority": 2.625e-07, @@ -48615,6 +49609,7 @@ }, "text-embedding-004": { "deprecation_date": "2027-04-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_character": 2.5e-08, "input_cost_per_token": 1e-07, "litellm_provider": "vertex_ai-embedding-models", @@ -48626,6 +49621,7 @@ }, "text-embedding-005": { "deprecation_date": "2027-04-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_character": 2.5e-08, "input_cost_per_token": 1e-07, "litellm_provider": "vertex_ai-embedding-models", @@ -48696,6 +49692,7 @@ }, "text-multilingual-embedding-002": { "deprecation_date": "2027-04-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_character": 2.5e-08, "input_cost_per_token": 1e-07, "litellm_provider": "vertex_ai-embedding-models", @@ -48810,6 +49807,7 @@ }, "together_ai/meta-llama/Llama-3.3-70B-Instruct-Turbo": { "deprecation_date": "2026-10-22", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 1.04e-06, "litellm_provider": "together_ai", "max_input_tokens": 131072, @@ -48817,6 +49815,7 @@ "mode": "chat", "output_cost_per_token": 1.04e-06, "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/meta-models/Muse-Glimmer-30B", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -48876,6 +49875,7 @@ "together_ai/MiniMaxAI/MiniMax-M3": { "cache_read_input_token_cost": 6e-08, "deprecation_date": "2026-11-06", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 3e-07, "litellm_provider": "together_ai", "max_input_tokens": 524288, @@ -48883,6 +49883,7 @@ "mode": "chat", "output_cost_per_token": 1.2e-06, "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/MiniMaxAI/MiniMax-M3.1-Flash", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -48959,6 +49960,7 @@ "together_ai/Qwen/Qwen3.8-2.4T-A95B": { "cache_read_input_token_cost": 2.5e-07, "deprecation_date": "2026-11-04", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 2e-06, "litellm_provider": "together_ai", "max_input_tokens": 1010000, @@ -48966,6 +49968,7 @@ "mode": "chat", "output_cost_per_token": 6e-06, "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/Qwen/Qwen3.7-Max", "supports_prompt_caching": true }, "together_ai/arize-ai/qwen-2-1.5b-instruct": { @@ -48980,6 +49983,7 @@ "together_ai/deepseek-ai/DeepSeek-V4-Flash-0731": { "cache_read_input_token_cost": 3e-08, "deprecation_date": "2026-10-22", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 1.4e-07, "litellm_provider": "together_ai", "max_input_tokens": 1048576, @@ -48987,6 +49991,7 @@ "mode": "chat", "output_cost_per_token": 2.8e-07, "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/deepseek-ai/DeepSeek-V4.1-Flash-1017", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -49071,6 +50076,7 @@ "together_ai/thinkingmachines/Inkling": { "cache_read_input_token_cost": 1.7e-07, "deprecation_date": "2026-11-06", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 1e-06, "litellm_provider": "together_ai", "max_input_tokens": 524288, @@ -49078,6 +50084,7 @@ "mode": "chat", "output_cost_per_token": 4.05e-06, "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/meta-models/Muse-Spark-Open-816B-A42B", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -49135,6 +50142,8 @@ }, "tts-1": { "deprecation_date": "2027-01-06", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_character": 1.5e-05, "litellm_provider": "openai", "mode": "audio_speech", @@ -49145,6 +50154,8 @@ }, "tts-1-hd": { "deprecation_date": "2027-01-06", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_character": 3e-05, "litellm_provider": "openai", "mode": "audio_speech", @@ -49375,6 +50386,7 @@ "cache_creation_input_token_cost": 1.875e-05, "cache_read_input_token_cost": 1.5e-06, "deprecation_date": "2027-01-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.5e-05, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -49413,6 +50425,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "us.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -49455,6 +50469,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.44e-05, "cache_read_input_token_cost_above_200k_tokens": 7.2e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "successor_model": "us-gov.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -49495,6 +50511,7 @@ "prompt_cache_min_tokens": 1024, "source": "https://aws.amazon.com/bedrock/pricing/", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -49570,8 +50587,9 @@ "mode": "chat", "output_cost_per_token": 3e-05, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-gov-west-1/index.json", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -49592,7 +50610,9 @@ "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "us-gov-west-1" - } + }, + "input_cost_per_token_batches": 3e-06, + "output_cost_per_token_batches": 1.5e-05 }, "us-gov.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -49615,6 +50635,7 @@ "supports_max_reasoning_effort": true, "supports_mid_conversation_system": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_output_config": true, "supports_parallel_tool_use_config": true, "supports_pdf_input": true, @@ -49659,6 +50680,7 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_max_reasoning_effort": true, "supports_output_config": true, "bedrock_output_config_effort_ceiling": "xhigh", @@ -49689,6 +50711,7 @@ }, "us-gov.nvidia.nemotron-nano-12b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-12b-v2-vl-bf16.html", "input_cost_per_token": 2.4e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -49704,6 +50727,7 @@ }, "us-gov.nvidia.nemotron-nano-9b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-9b-v2.html", "input_cost_per_token": 7.2e-08, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -49959,6 +50983,8 @@ "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-10-14", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "us.anthropic.claude-sonnet-5", "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -49993,6 +51019,7 @@ }, "us.deepseek.r1-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-r1.html", "input_cost_per_token": 1.35e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -50045,6 +51072,7 @@ }, "us.meta.llama3-1-405b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2.4e-06, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -50057,6 +51085,7 @@ }, "us.meta.llama3-1-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "input_cost_per_token_batches": 3.6e-07, "litellm_provider": "bedrock", @@ -50071,6 +51100,7 @@ }, "us.meta.llama3-1-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2.2e-07, "input_cost_per_token_batches": 1.1e-07, "litellm_provider": "bedrock", @@ -50085,6 +51115,7 @@ }, "us.meta.llama3-2-11b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.6e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -50098,6 +51129,7 @@ }, "us.meta.llama3-2-1b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-1b-instruct.md", "input_cost_per_token": 1e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -50110,6 +51142,7 @@ }, "us.meta.llama3-2-3b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-3b-instruct.md", "input_cost_per_token": 1.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -50122,6 +51155,7 @@ }, "us.meta.llama3-2-90b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -50135,6 +51169,7 @@ }, "us.meta.llama3-3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "input_cost_per_token_batches": 3.6e-07, "litellm_provider": "bedrock_converse", @@ -50149,6 +51184,7 @@ }, "us.meta.llama4-maverick-17b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-4-maverick-17b-instruct.md", "input_cost_per_token": 2.4e-07, "input_cost_per_token_batches": 1.2e-07, "litellm_provider": "bedrock_converse", @@ -50171,6 +51207,7 @@ }, "us.meta.llama4-scout-17b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-4-scout-17b-instruct.md", "input_cost_per_token": 1.7e-07, "input_cost_per_token_batches": 8.5e-08, "litellm_provider": "bedrock_converse", @@ -51431,6 +52468,7 @@ }, "vertex_ai/claude-haiku-4-5": { "deprecation_date": "2026-10-15", + "successor_model": "vertex_ai/claude-haiku-5-5", "cache_creation_input_token_cost": 1.25e-06, "cache_creation_input_token_cost_above_1hr": 2e-06, "cache_creation_input_token_cost_batches": 6.25e-07, @@ -51550,32 +52588,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "vertex_ai/claude-3-opus": { - "deprecation_date": "2025-08-01", - "input_cost_per_token": 1.5e-05, - "litellm_provider": "vertex_ai-anthropic_models", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "vertex_ai/claude-3-opus@20240229": { - "deprecation_date": "2025-08-01", - "input_cost_per_token": 1.5e-05, - "litellm_provider": "vertex_ai-anthropic_models", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_vision": true - }, "vertex_ai/claude-3-sonnet": { "input_cost_per_token": 3e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -51602,6 +52614,7 @@ }, "vertex_ai/claude-opus-4-5": { "deprecation_date": "2026-11-24", + "successor_model": "vertex_ai/claude-opus-5-5", "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_creation_input_token_cost_batches": 3.125e-06, @@ -51982,6 +52995,7 @@ "regional_endpoint_uplift_multiplier": 1.1, "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_creation_input_token_cost_batches": 3.125e-06, @@ -52020,6 +53034,7 @@ "regional_endpoint_uplift_multiplier": 1.1, "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_creation_input_token_cost_batches": 3.125e-06, @@ -52211,6 +53226,7 @@ }, "vertex_ai/claude-sonnet-4-5": { "deprecation_date": "2026-09-29", + "successor_model": "vertex_ai/claude-sonnet-5-5", "cache_creation_input_token_cost": 3.75e-06, "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.2e-05, @@ -52268,6 +53284,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -52498,6 +53515,8 @@ }, "vertex_ai/gemini-2.5-flash-image": { "deprecation_date": "2027-03-15", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.1-flash-lite-image", "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, @@ -52548,12 +53567,13 @@ }, "vertex_ai/gemini-3-pro-image": { "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, - "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_flex": 1e-07, "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, @@ -52568,6 +53588,7 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "output_cost_per_image_token_batches": 6e-05, + "output_cost_per_image_token_priority": 0.000216, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, @@ -52603,6 +53624,7 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "output_cost_per_image_token_batches": 6e-05, + "output_cost_per_image_token_priority": 0.000216, "output_cost_per_token": 1.2e-05, "output_cost_per_token_priority": 2.16e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, @@ -52624,6 +53646,7 @@ "cache_read_input_token_cost_flex": 2.5e-08, "cache_read_input_token_cost_priority": 9e-08, "deprecation_date": "2027-05-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_image": 0.00056, "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -52636,6 +53659,7 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_image_token_batches": 3e-05, + "output_cost_per_image_token_priority": 0.000108, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, @@ -52664,6 +53688,7 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_image_token_batches": 3e-05, + "output_cost_per_image_token_priority": 0.000108, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "supports_reasoning": false, @@ -52693,6 +53718,7 @@ "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, "output_cost_per_image_token_batches": 1.5e-05, + "output_cost_per_image_token_priority": 5.4e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, @@ -52773,17 +53799,28 @@ }, "vertex_ai/gemini-3.1-flash-lite": { "cache_read_input_audio_token_cost": 5e-08, - "deprecation_date": "2027-05-07", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "cache_read_input_audio_token_cost_batches": 2.5e-08, + "cache_read_input_audio_token_cost_flex": 2.5e-08, + "cache_read_input_audio_token_cost_priority": 9e-08, "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, + "deprecation_date": "2027-05-07", + "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token": 5e-07, + "input_cost_per_audio_token_above_200k_tokens": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_batches": 2.5e-07, + "input_cost_per_audio_token_above_200k_tokens_flex": 2.5e-07, + "input_cost_per_audio_token_above_200k_tokens_priority": 9e-07, + "input_cost_per_audio_token_batches": 2.5e-07, + "input_cost_per_audio_token_flex": 2.5e-07, + "input_cost_per_audio_token_priority": 9e-07, "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_flex": 1.25e-07, "input_cost_per_token_priority": 4.5e-07, - "input_cost_per_audio_token_priority": 9e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65536, @@ -52794,7 +53831,10 @@ "output_cost_per_token_flex": 7.5e-07, "output_cost_per_token_priority": 2.7e-06, "regional_endpoint_uplift_multiplier": 1.1, + "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "successor_model": "vertex_ai/gemini-3.5-flash-lite", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -52812,6 +53852,7 @@ "supports_audio_input": true, "supports_audio_output": false, "supports_function_calling": true, + "supports_native_streaming": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -52823,19 +53864,11 @@ "supports_video_input": true, "supports_vision": true, "supports_web_search": true, - "supports_native_streaming": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014, - "search_context_size_high": 0.014 - }, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, - "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07 + "web_search_billing_unit": "per_query" }, "vertex_ai/gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "cache_read_input_token_cost": 3e-08, "cache_read_input_token_cost_batches": 1.5e-08, "cache_read_input_token_cost_flex": 1.5e-08, @@ -53251,6 +54284,7 @@ "vertex_ai/zai-org/glm-4.7-maas": { "cache_read_input_token_cost": 6e-08, "deprecation_date": "2026-10-21", + "successor_model": "vertex_ai/zai-org/glm-5.2-maas", "input_cost_per_token": 6e-07, "litellm_provider": "vertex_ai-zai_models", "max_input_tokens": 200000, @@ -53269,6 +54303,7 @@ "vertex_ai/zai-org/glm-5-maas": { "cache_read_input_token_cost": 1e-07, "deprecation_date": "2026-10-21", + "successor_model": "vertex_ai/zai-org/glm-5.2-maas", "input_cost_per_token": 1e-06, "litellm_provider": "vertex_ai-zai_models", "max_input_tokens": 200000, @@ -53688,6 +54723,7 @@ }, "vertex_ai/veo-3.1-generate-001": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "mode": "video_generation", @@ -53703,6 +54739,7 @@ }, "vertex_ai/veo-3.1-fast-generate-001": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "mode": "video_generation", @@ -53905,7 +54942,7 @@ "voyage/voyage-lite-01": { "input_cost_per_token": 1e-07, "litellm_provider": "voyage", - "max_input_tokens": 4096, + "max_input_tokens": 4000, "mode": "embedding", "output_cost_per_token": 0.0 }, @@ -53921,7 +54958,8 @@ "litellm_provider": "voyage", "max_input_tokens": 32000, "mode": "embedding", - "output_cost_per_token": 0.0 + "output_cost_per_token": 0.0, + "supports_embedding_image_input": true }, "wandb/openai/gpt-oss-120b": { "supports_reasoning": true, @@ -53958,23 +54996,23 @@ "supports_vision": true }, "wandb/meta-llama/Llama-3.1-8B-Instruct": { - "max_input_tokens": 131000, + "max_input_tokens": 128000, "max_output_tokens": 128000, "input_cost_per_token": 2.2e-07, "output_cost_per_token": 2.2e-07, "litellm_provider": "wandb", "mode": "chat", - "source": "https://wandb.ai/site/pricing/tokens/" + "source": "https://www.coreweave.com/products/coreweave-forge/serverless-inference" }, "wandb/deepseek-ai/DeepSeek-V3.1": { "supports_reasoning": true, - "max_input_tokens": 161000, + "max_input_tokens": 128000, "max_output_tokens": 128000, "input_cost_per_token": 5.5e-07, "output_cost_per_token": 1.65e-06, "litellm_provider": "wandb", "mode": "chat", - "source": "https://wandb.ai/site/pricing/tokens/" + "source": "https://www.coreweave.com/products/coreweave-forge/serverless-inference" }, "wandb/meta-llama/Llama-3.3-70B-Instruct": { "max_input_tokens": 128000, @@ -54353,6 +55391,8 @@ "/v1/audio/transcriptions" ], "deprecation_date": "2027-02-26", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-live-transcribe", "source": "https://developers.openai.com/api/docs/pricing" }, "xai/grok-4.20-multi-agent-beta-0309": { @@ -54458,6 +55498,8 @@ "input_cost_per_token_above_200k_tokens_batches": 2e-06, "input_cost_per_token_batches": 1e-06, "litellm_provider": "xai", + "token_count_framing": 185, + "token_count_tool_framing": 214, "max_input_tokens": 1000000, "max_output_tokens": 1000000, "mode": "chat", @@ -54614,6 +55656,8 @@ }, "zai.glm-4.7": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "zai.glm-5", "input_cost_per_token": 6e-07, "input_cost_per_token_batches": 3e-07, "input_cost_per_token_flex": 3e-07, @@ -54658,6 +55702,7 @@ }, "zai.glm-4.7-flash": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7e-08, "input_cost_per_token_batches": 3.5e-08, "input_cost_per_token_flex": 3.5e-08, @@ -54971,6 +56016,7 @@ }, "openai/sora-2": { "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.1, @@ -54985,6 +56031,7 @@ }, "openai/sora-2-pro": { "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.3, @@ -55000,6 +56047,7 @@ "openai/sora-2-pro-high-res": { "litellm_provider": "openai", "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "mode": "video_generation", "output_cost_per_video_per_second": 0.5, "source": "https://platform.openai.com/docs/api-reference/videos", @@ -58666,6 +59714,8 @@ }, "gpt-4o-mini-tts-2025-12-15": { "deprecation_date": "2027-01-06", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", @@ -58686,6 +59736,8 @@ }, "gpt-4o-mini-transcribe-2025-03-20": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-4o-mini-transcribe-2025-12-15", "input_cost_per_audio_token": 1.25e-06, "input_cost_per_second": 5e-05, "input_cost_per_token": 1.25e-06, @@ -58701,6 +59753,8 @@ }, "gpt-4o-mini-transcribe-2025-12-15": { "deprecation_date": "2027-02-26", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-live-transcribe", "input_cost_per_audio_token": 1.25e-06, "input_cost_per_second": 5e-05, "input_cost_per_token": 1.25e-06, @@ -58722,6 +59776,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -58749,6 +59804,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -58800,6 +59856,8 @@ "supports_system_messages": true, "supports_tool_choice": true, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-realtime-whisper": { @@ -58821,6 +59879,7 @@ }, "sora-2": { "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.1, @@ -58835,6 +59894,7 @@ }, "sora-2-pro": { "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.3, @@ -58850,6 +59910,7 @@ "sora-2-pro-high-res": { "litellm_provider": "openai", "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "mode": "video_generation", "output_cost_per_video_per_second": 0.5, "source": "https://developers.openai.com/api/docs/pricing", @@ -58866,6 +59927,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_batches": 6.3e-07, "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image_token": 8e-06, "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token": 5e-06, @@ -58873,6 +59936,7 @@ "litellm_provider": "openai", "mode": "image_generation", "output_cost_per_image_token": 3.2e-05, + "output_cost_per_image_token_batches": 1.6e-05, "output_cost_per_token": 1e-05, "output_cost_per_token_batches": 5e-06, "source": "https://developers.openai.com/api/docs/pricing", @@ -58881,48 +59945,6 @@ "/v1/images/edits" ] }, - "gemini-2.0-flash-exp-image-generation": { - "deprecation_date": "2025-11-14", - "input_cost_per_token": 0.0, - "litellm_provider": "gemini", - "max_input_tokens": 32768, - "max_output_tokens": 32768, - "mode": "image_generation", - "output_cost_per_image": 0.039, - "output_cost_per_token": 0.0, - "source": "https://ai.google.dev/pricing", - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_vision": true - }, - "gemini/gemini-2.0-flash-exp-image-generation": { - "deprecation_date": "2025-11-14", - "input_cost_per_token": 0.0, - "litellm_provider": "gemini", - "max_input_tokens": 32768, - "max_output_tokens": 32768, - "mode": "image_generation", - "output_cost_per_image": 0.039, - "output_cost_per_token": 0.0, - "source": "https://ai.google.dev/pricing", - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_vision": true, - "tpm": 250000, - "rpm": 10 - }, "gemini-2.5-flash-native-audio-latest": { "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 5e-07, @@ -58975,6 +59997,8 @@ }, "gemini-2.5-flash-native-audio-preview-12-2025": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-live", "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 5e-07, "litellm_provider": "gemini", @@ -59006,6 +60030,8 @@ }, "gemini-3.1-flash-live-preview": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-live", "input_cost_per_audio_token": 3e-06, "input_cost_per_image_token": 1e-06, "input_cost_per_token": 7.5e-07, @@ -59163,6 +60189,8 @@ }, "gemini/gemini-2.5-flash-native-audio-preview-12-2025": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-live", "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 5e-07, "litellm_provider": "gemini", @@ -59197,6 +60225,8 @@ }, "gemini/gemini-3.1-flash-live-preview": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-live", "input_cost_per_audio_token": 3e-06, "input_cost_per_image_token": 1e-06, "input_cost_per_token": 7.5e-07, @@ -59236,6 +60266,8 @@ }, "gemini/gemini-3.1-flash-tts-preview": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash-tts", "input_cost_per_token": 1e-06, "input_cost_per_token_batches": 5e-07, "litellm_provider": "gemini", @@ -59305,6 +60337,8 @@ }, "gemini-2.5-flash-preview-tts": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash-tts", "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, "litellm_provider": "gemini", @@ -59626,6 +60660,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -59876,6 +60911,7 @@ "max_input_tokens": 922000, "max_output_tokens": 128000, "mode": "responses", + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-cyber.html", "use_openai_responses_path": true, "supported_endpoints": [ @@ -59897,7 +60933,8 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, - "supports_vision": true + "supports_vision": true, + "supports_web_search": true }, "bedrock_mantle/openai.gpt-daybreak-blue-5.6-sol": { "input_cost_per_token": 4.4e-06, @@ -59912,6 +60949,7 @@ "max_input_tokens": 1050000, "max_output_tokens": 128000, "mode": "responses", + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "use_openai_responses_path": true, "supported_endpoints": [ "/v1/responses" @@ -59931,7 +60969,8 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-daybreak-blue-56-sol.html" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-daybreak-blue-56-sol.html", + "supports_web_search": true }, "bedrock_mantle/openai.gpt-5.6-luna": { "input_cost_per_token": 2.2e-07, @@ -60337,6 +61376,7 @@ "mode": "responses", "output_cost_per_token_above_272k_tokens_ultrafast": 0.000495, "output_cost_per_token_ultrafast": 0.00033, + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -60360,7 +61400,8 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-astra.html" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-astra.html", + "supports_web_search": true }, "bedrock_mantle/openai.gpt-6-sol": { "input_cost_per_token": 2.2e-06, @@ -60375,6 +61416,7 @@ "max_input_tokens": 922000, "max_output_tokens": 128000, "mode": "responses", + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -60398,7 +61440,8 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards-openai.html" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards-openai.html", + "supports_web_search": true }, "bedrock_mantle/openai.gpt-6-luna": { "input_cost_per_token": 1.1e-07, @@ -60413,6 +61456,7 @@ "max_input_tokens": 922000, "max_output_tokens": 128000, "mode": "responses", + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -60436,7 +61480,8 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards-openai.html" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards-openai.html", + "supports_web_search": true }, "us.openai.gpt-6-astra": { "supports_bedrock_runtime_chat_completions_response_format": true, @@ -62632,7 +63677,9 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "token_count_framing": 23, + "token_count_tool_framing": 12 }, "deepseek/deepseek-v4-flash-vision-exp": { "cache_creation_input_token_cost": 0.0, @@ -62738,7 +63785,9 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": false + "supports_vision": false, + "token_count_framing": 76, + "token_count_tool_framing": 75 }, "tencent/deepseek-v4-pro": { "cache_creation_input_token_cost": 0.0, @@ -63351,6 +64400,10 @@ "input_cost_per_second": 7.5e-05, "litellm_provider": "openai", "mode": "audio_transcription", + "provider_specific_entry": { + "transcription_json_or_text_only": 1, + "transcription_usage_duration": 1 + }, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/transcriptions", @@ -63363,7 +64416,8 @@ "supported_output_modalities": [ "text" ], - "supports_audio_input": true + "supports_audio_input": true, + "supports_native_streaming": true }, "gpt-live-transcribe": { "input_cost_per_second": 0.000283333333333, @@ -63381,7 +64435,8 @@ "supported_output_modalities": [ "text" ], - "supports_audio_input": true + "supports_audio_input": true, + "supports_native_streaming": true }, "gpt-live-1": { "input_cost_per_second": 0.000833333333333, @@ -63415,7 +64470,8 @@ "audio" ], "supports_audio_input": true, - "supports_audio_output": true + "supports_audio_output": true, + "supports_native_streaming": true }, "claude-mythos-5": { "supports_anthropic_compaction": true, @@ -63506,6 +64562,7 @@ }, "claude-mythos-preview": { "deprecation_date": "2026-06-09", + "deprecation_source": "https://platform.claude.com/docs/en/about-claude/model-deprecations", "supports_anthropic_compaction": true, "cache_creation_input_token_cost": 1.25e-05, "cache_creation_input_token_cost_above_1hr": 2e-05, @@ -63695,7 +64752,8 @@ { "name": "claude-family-baseline", "pattern": "claude-[a-z]+-\\d+(?:[-.]\\d+)?(?:-\\d{8})?", - "description": "Any Claude family-major id with an optional minor and an optional 8-digit date suffix, under any provider namespace (bare, bedrock-dotted, vertex, databricks, ...), so bare majors like claude-newfamily-5 get the same baseline as claude-newfamily-5-1. Carries the model-family facts every Claude shares; it carries no pricing, so cost stays on the standard unpriced behavior rather than a guessed number.", + "fill_missing_for_providers": ["anthropic", "azure_ai", "bedrock", "bedrock_converse", "vertex_ai-anthropic_models"], + "description": "Any Claude family-major id with an optional minor and an optional 8-digit date suffix, under any provider namespace (bare, bedrock-dotted, vertex, databricks, ...), so bare majors like claude-newfamily-5 get the same baseline as claude-newfamily-5-1. Carries the model-family facts every Claude shares; it carries no pricing, so cost stays on the standard unpriced behavior rather than a guessed number. On mapped Claude entries from Anthropic, Azure Foundry, Bedrock and Vertex it only fills the keys an entry leaves out, so the entry's own values always win.", "model_info": { "mode": "chat", "max_input_tokens": 200000, @@ -63738,6 +64796,14 @@ "thinking_always_on": true } }, + { + "name": "claude-thinking-on-by-default", + "pattern": "claude-[a-z]+-[5-9](?!\\d)", + "description": "Claude at major 5 or higher, in any id shape that contains claude--. Anthropic's thinking docs list every Claude 5+ model as thinking by default (on or always on) when the request sends no thinking param, and every 4.x as off. Two-digit majors are deliberately not matched so ids like claude-opus-41 (4.1) are not read as major 41. The response_format json tool is then left unforced, since a forced tool call skips the model's thinking.", + "model_info": { + "thinking_on_by_default": true + } + }, { "name": "claude-mid-conversation-system", "pattern": "claude-[a-z]+-(?:4[-._](?:[89]|[1-9]\\d)(?!\\d)|[5-9](?!\\d)(?:[-._]\\d{1,2}(?!\\d))?)", @@ -64024,6 +65090,7 @@ "input_cost_per_token": 3e-07, "input_cost_per_token_priority": 3.75e-07, "litellm_provider": "fireworks_ai", + "token_count_framing": 23, "max_input_tokens": 1048576, "max_output_tokens": 393216, "mode": "chat", @@ -64031,6 +65098,7 @@ "output_cost_per_token_priority": 1.5e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -64050,6 +65118,7 @@ "output_cost_per_token_priority": 2.25e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -64092,6 +65161,7 @@ ], "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64122,6 +65192,7 @@ "input_cost_per_token": 3e-07, "input_cost_per_token_priority": 3.75e-07, "litellm_provider": "fireworks_ai", + "token_count_framing": 23, "max_input_tokens": 1048576, "max_output_tokens": 393216, "mode": "chat", @@ -64129,6 +65200,7 @@ "output_cost_per_token_priority": 1.5e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -64148,6 +65220,7 @@ "output_cost_per_token_priority": 2.25e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -64175,6 +65248,7 @@ "fireworks_ai/glm-5p2-fast": { "cache_read_input_token_cost": 2.1e-07, "deprecation_date": "2026-09-25", + "successor_model": "fireworks_ai/glm-5p3-fast", "input_cost_per_token": 2.1e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, @@ -64222,6 +65296,7 @@ ], "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64242,6 +65317,7 @@ ], "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64265,6 +65341,7 @@ ], "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64340,6 +65417,7 @@ "output_cost_per_token_priority": 3e-06, "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64376,6 +65454,7 @@ "output_cost_per_token_priority": 6.375e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_vision": true }, @@ -64412,6 +65491,7 @@ "output_cost_per_token_priority": 3e-06, "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64438,6 +65518,7 @@ "fireworks_ai/accounts/fireworks/routers/glm-5p2-fast": { "cache_read_input_token_cost": 2.1e-07, "deprecation_date": "2026-09-25", + "successor_model": "fireworks_ai/accounts/fireworks/routers/glm-5p3-fast", "input_cost_per_token": 2.1e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, @@ -64482,6 +65563,7 @@ ], "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64505,6 +65587,7 @@ ], "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64527,7 +65610,7 @@ "supports_vision": false }, "novita/deepseek/deepseek-v4-pro-0813": { - "cache_read_input_token_cost": 1.3200000000000002e-07, + "cache_read_input_token_cost": 4.4e-08, "input_cost_per_token": 1.32e-06, "litellm_provider": "novita", "max_input_tokens": 1048576, @@ -64639,13 +65722,13 @@ "supports_vision": false }, "novita/mindai/macaron-v1-venti": { - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 1.5e-06, + "cache_read_input_token_cost": 1.65e-07, + "input_cost_per_token": 8.25e-07, "litellm_provider": "novita", "max_input_tokens": 1048576, "max_output_tokens": 131072, "mode": "chat", - "output_cost_per_token": 4.5e-06, + "output_cost_per_token": 2.475e-06, "source": "https://novita.ai/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -64748,13 +65831,13 @@ "supports_vision": false }, "novita/mindai/macaron-v1-tall": { - "cache_read_input_token_cost": 8e-08, - "input_cost_per_token": 4.5000000000000003e-07, + "cache_read_input_token_cost": 4.4e-08, + "input_cost_per_token": 2.475e-07, "litellm_provider": "novita", "max_input_tokens": 262144, "max_output_tokens": 32768, "mode": "chat", - "output_cost_per_token": 2.6e-06, + "output_cost_per_token": 1.43e-06, "source": "https://novita.ai/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -66179,9 +67262,9 @@ "deepinfra/deepseek-ai/DeepSeek-V4-Flash-0731": { "max_output_tokens": 1048576, "max_input_tokens": 1048576, - "input_cost_per_token": 8e-08, + "input_cost_per_token": 6e-08, "output_cost_per_token": 1.8e-07, - "cache_read_input_token_cost": 1.6e-08, + "cache_read_input_token_cost": 1.5e-08, "supports_prompt_caching": true, "litellm_provider": "deepinfra", "mode": "chat", @@ -66560,8 +67643,8 @@ "deepinfra/google/gemma-4-31B-it": { "max_output_tokens": 262144, "max_input_tokens": 262144, - "input_cost_per_token": 1.3e-07, - "output_cost_per_token": 3.8e-07, + "input_cost_per_token": 2e-07, + "output_cost_per_token": 4e-07, "litellm_provider": "deepinfra", "mode": "chat", "supports_function_calling": true, @@ -66718,10 +67801,12 @@ }, "xai/grok-imagine-image-quality": { "deprecation_date": "2026-11-02", + "deprecation_source": "https://docs.x.ai/developers/migration/imagine-image-quality-nov-2", "input_cost_per_image": 0.05, "litellm_provider": "xai", "mode": "image_generation", "source": "https://docs.x.ai/docs/models", + "successor_model": "xai/grok-imagine-image-2.0", "supported_endpoints": [ "/v1/images/generations" ], @@ -66735,10 +67820,12 @@ }, "xai/grok-imagine-image-quality-20260403": { "deprecation_date": "2026-11-02", + "deprecation_source": "https://docs.x.ai/developers/migration/imagine-image-quality-nov-2", "input_cost_per_image": 0.05, "litellm_provider": "xai", "mode": "image_generation", "source": "https://docs.x.ai/docs/models", + "successor_model": "xai/grok-imagine-image-2.0", "supported_endpoints": [ "/v1/images/generations" ], @@ -66752,10 +67839,12 @@ }, "xai/grok-imagine-image-quality-latest": { "deprecation_date": "2026-11-02", + "deprecation_source": "https://docs.x.ai/developers/migration/imagine-image-quality-nov-2", "input_cost_per_image": 0.05, "litellm_provider": "xai", "mode": "image_generation", "source": "https://docs.x.ai/docs/models", + "successor_model": "xai/grok-imagine-image-2.0", "supported_endpoints": [ "/v1/images/generations" ], @@ -66769,10 +67858,12 @@ }, "xai/grok-imagine-image-pro": { "deprecation_date": "2026-05-15", + "deprecation_source": "https://docs.x.ai/developers/migration/may-15-retirement", "input_cost_per_image": 0.05, "litellm_provider": "xai", "mode": "image_generation", "source": "https://docs.x.ai/docs/models", + "successor_model": "xai/grok-imagine-image-2.0", "supported_endpoints": [ "/v1/images/generations" ], @@ -66890,6 +67981,8 @@ }, "xai/grok-voice-transcribe-1.0": { "deprecation_date": "2026-10-02", + "deprecation_source": "https://docs.x.ai/docs/release-notes", + "successor_model": "xai/grok-voice-transcribe-2.0", "input_cost_per_second": 2.778e-05, "litellm_provider": "xai", "metadata": { @@ -67298,6 +68391,7 @@ "output_cost_per_token_priority": 5.5e-06, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67316,6 +68410,7 @@ "output_cost_per_token_priority": 8.25e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67334,6 +68429,7 @@ "output_cost_per_token_priority": 5.5e-06, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67352,6 +68448,7 @@ "output_cost_per_token_priority": 8.25e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67367,6 +68464,7 @@ "output_cost_per_token": 6.6e-06, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67409,6 +68507,7 @@ "output_cost_per_token": 6.6e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67427,6 +68526,7 @@ "output_cost_per_token_priority": 6.25e-07, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -67445,6 +68545,7 @@ "output_cost_per_token_priority": 9.375e-07, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -67462,6 +68563,7 @@ "output_cost_per_token_priority": 6.25e-07, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -67480,6 +68582,7 @@ "output_cost_per_token_priority": 9.375e-07, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -67498,6 +68601,7 @@ "output_cost_per_token_priority": 4.05e-06, "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -67744,6 +68848,7 @@ }, "together_ai/nvidia/NVIDIA-Nemotron-Nano-9B-v2": { "deprecation_date": "2026-02-25", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 6e-08, "output_cost_per_token": 2.5e-07, "litellm_provider": "together_ai", @@ -67814,6 +68919,7 @@ "azure_ai/kimi-k2.7-code": { "cache_read_input_token_cost": 1.9e-07, "deprecation_date": "2027-04-16", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 9.5e-07, "litellm_provider": "azure_ai", "max_input_tokens": 262144, @@ -67849,6 +68955,7 @@ "supports_reasoning": true, "supports_tool_choice": true, "deprecation_date": "2026-12-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/deepseek-v4-1-flash-is-coming-to-microsoft-foundry/4556431" }, "azure_ai/MAI-Image-2.6": { @@ -67957,6 +69064,8 @@ }, "azure_ai/Cohere-command-a-plus-05-2026": { "deprecation_date": "2026-10-16", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "coherelabs-command-a-plus-05-2026-fp81", "input_cost_per_token": 8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -67990,6 +69099,8 @@ }, "azure_ai/deepseek-r1": { "deprecation_date": "2026-08-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/deepseek-v4-pro", "input_cost_per_token": 1.35e-06, "output_cost_per_token": 5.4e-06, "litellm_provider": "azure_ai", @@ -67999,6 +69110,8 @@ }, "azure_ai/deepseek-v3-0324": { "deprecation_date": "2026-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/deepseek-v4-flash", "input_cost_per_token": 1.14e-06, "output_cost_per_token": 4.56e-06, "litellm_provider": "azure_ai", @@ -68008,6 +69121,8 @@ }, "azure_ai/deepseek-v3.1": { "deprecation_date": "2026-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/deepseek-v4-flash", "input_cost_per_token": 1.23e-06, "output_cost_per_token": 4.94e-06, "litellm_provider": "azure_ai", @@ -68017,6 +69132,8 @@ }, "azure_ai/grok-3": { "deprecation_date": "2026-05-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/grok-4", "input_cost_per_token": 3e-06, "output_cost_per_token": 1.5e-05, "litellm_provider": "azure_ai", @@ -68026,6 +69143,8 @@ }, "azure_ai/grok-3-mini": { "deprecation_date": "2026-05-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/grok-4-1-fast-reasoning", "input_cost_per_token": 2.5e-07, "output_cost_per_token": 1.27e-06, "litellm_provider": "azure_ai", @@ -68035,6 +69154,8 @@ }, "azure_ai/grok-4-fast-non-reasoning": { "deprecation_date": "2026-05-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/grok-4-1-fast-non-reasoning", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", @@ -68044,6 +69165,8 @@ }, "azure_ai/grok-4-fast-reasoning": { "deprecation_date": "2026-05-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/grok-4-1-fast-reasoning", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", @@ -68053,12 +69176,18 @@ }, "bedrock/us-gov-west-1/nvidia.nemotron-nano-3-30b": { "input_cost_per_token": 7.2e-08, + "input_cost_per_token_batches": 3.6e-08, + "input_cost_per_token_flex": 3.6e-08, + "input_cost_per_token_priority": 1.32e-07, "litellm_provider": "bedrock", "max_input_tokens": 262144, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.88e-07, - "source": "https://aws.amazon.com/bedrock/pricing/", + "output_cost_per_token_batches": 1.44e-07, + "output_cost_per_token_flex": 1.44e-07, + "output_cost_per_token_priority": 5.04e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_function_calling": true, "supports_native_structured_output": true, "supports_system_messages": true, @@ -68069,13 +69198,20 @@ }, "bedrock/us-gov-west-1/nvidia.nemotron-nano-12b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-12b-v2-vl-bf16.html", "input_cost_per_token": 2.4e-07, + "input_cost_per_token_batches": 1.2e-07, + "input_cost_per_token_flex": 1.2e-07, + "input_cost_per_token_priority": 4.2e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 7.2e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-12b-v2-vl-bf16.html", + "output_cost_per_token_batches": 3.6e-07, + "output_cost_per_token_flex": 3.6e-07, + "output_cost_per_token_priority": 1.26e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_system_messages": true, "supports_vision": true, "supports_audio_input": false, @@ -68084,13 +69220,20 @@ }, "bedrock/us-gov-west-1/nvidia.nemotron-nano-9b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-9b-v2.html", "input_cost_per_token": 7.2e-08, + "input_cost_per_token_batches": 3.6e-08, + "input_cost_per_token_flex": 3.6e-08, + "input_cost_per_token_priority": 1.32e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.76e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-9b-v2.html", + "output_cost_per_token_batches": 1.44e-07, + "output_cost_per_token_flex": 1.44e-07, + "output_cost_per_token_priority": 4.8e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_system_messages": true, "supports_audio_input": false, "supports_function_calling": true, @@ -68099,12 +69242,18 @@ }, "bedrock/us-gov-west-1/nvidia.nemotron-super-3-120b": { "input_cost_per_token": 1.8e-07, + "input_cost_per_token_batches": 9e-08, + "input_cost_per_token_flex": 9e-08, + "input_cost_per_token_priority": 3.15e-07, "litellm_provider": "bedrock", "max_input_tokens": 256000, "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 7.8e-07, - "source": "https://aws.amazon.com/bedrock/pricing/", + "output_cost_per_token_batches": 3.9e-07, + "output_cost_per_token_flex": 3.9e-07, + "output_cost_per_token_priority": 1.365e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_function_calling": true, "supports_reasoning": true, "supports_system_messages": true, @@ -68116,12 +69265,18 @@ "bedrock/us-gov-west-1/openai.gpt-oss-20b-1:0": { "supports_vision": false, "input_cost_per_token": 8.4e-08, + "input_cost_per_token_batches": 4.2e-08, + "input_cost_per_token_flex": 4.2e-08, + "input_cost_per_token_priority": 1.47e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 3.6e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-20b.html", + "output_cost_per_token_batches": 1.8e-07, + "output_cost_per_token_flex": 1.8e-07, + "output_cost_per_token_priority": 6.3e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supported_endpoints": [ "/v1/chat/completions" ], @@ -68135,12 +69290,18 @@ "bedrock/us-gov-west-1/openai.gpt-oss-120b-1:0": { "supports_vision": false, "input_cost_per_token": 1.8e-07, + "input_cost_per_token_batches": 9e-08, + "input_cost_per_token_flex": 9e-08, + "input_cost_per_token_priority": 3.15e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 7.2e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-120b.html", + "output_cost_per_token_batches": 3.6e-07, + "output_cost_per_token_flex": 3.6e-07, + "output_cost_per_token_priority": 1.26e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supported_endpoints": [ "/v1/chat/completions" ], @@ -68166,6 +69327,7 @@ "output_cost_per_token": 1.2e-05, "prompt_cache_min_tokens": 1024, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -68241,6 +69403,7 @@ "output_cost_per_token": 3e-05, "prompt_cache_min_tokens": 512, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -68261,7 +69424,10 @@ "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "us-gov-west-1" - } + }, + "input_cost_per_token_batches": 3e-06, + "output_cost_per_token_batches": 1.5e-05, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-gov-west-1/index.json" }, "bedrock/us-gov-west-1/anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -68283,6 +69449,7 @@ "supports_max_reasoning_effort": true, "supports_mid_conversation_system": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_output_config": true, "supports_parallel_tool_use_config": true, "supports_pdf_input": true, @@ -68328,6 +69495,7 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_max_reasoning_effort": true, "supports_output_config": true, "bedrock_output_config_effort_ceiling": "xhigh", @@ -68341,12 +69509,18 @@ }, "bedrock/us-gov-east-1/nvidia.nemotron-nano-3-30b": { "input_cost_per_token": 7.2e-08, + "input_cost_per_token_batches": 3.6e-08, + "input_cost_per_token_flex": 3.6e-08, + "input_cost_per_token_priority": 1.32e-07, "litellm_provider": "bedrock", "max_input_tokens": 262144, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.88e-07, - "source": "https://aws.amazon.com/bedrock/pricing/", + "output_cost_per_token_batches": 1.44e-07, + "output_cost_per_token_flex": 1.44e-07, + "output_cost_per_token_priority": 5.04e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supports_function_calling": true, "supports_native_structured_output": true, "supports_system_messages": true, @@ -68357,13 +69531,20 @@ }, "bedrock/us-gov-east-1/nvidia.nemotron-nano-12b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-12b-v2-vl-bf16.html", "input_cost_per_token": 2.4e-07, + "input_cost_per_token_batches": 1.2e-07, + "input_cost_per_token_flex": 1.2e-07, + "input_cost_per_token_priority": 4.2e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 7.2e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-12b-v2-vl-bf16.html", + "output_cost_per_token_batches": 3.6e-07, + "output_cost_per_token_flex": 3.6e-07, + "output_cost_per_token_priority": 1.26e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supports_system_messages": true, "supports_vision": true, "supports_audio_input": false, @@ -68372,13 +69553,20 @@ }, "bedrock/us-gov-east-1/nvidia.nemotron-nano-9b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-9b-v2.html", "input_cost_per_token": 7.2e-08, + "input_cost_per_token_batches": 3.6e-08, + "input_cost_per_token_flex": 3.6e-08, + "input_cost_per_token_priority": 1.32e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.76e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-9b-v2.html", + "output_cost_per_token_batches": 1.44e-07, + "output_cost_per_token_flex": 1.44e-07, + "output_cost_per_token_priority": 4.8e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supports_system_messages": true, "supports_audio_input": false, "supports_function_calling": true, @@ -68387,12 +69575,18 @@ }, "bedrock/us-gov-east-1/nvidia.nemotron-super-3-120b": { "input_cost_per_token": 1.8e-07, + "input_cost_per_token_batches": 9e-08, + "input_cost_per_token_flex": 9e-08, + "input_cost_per_token_priority": 3.15e-07, "litellm_provider": "bedrock", "max_input_tokens": 256000, "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 7.8e-07, - "source": "https://aws.amazon.com/bedrock/pricing/", + "output_cost_per_token_batches": 3.9e-07, + "output_cost_per_token_flex": 3.9e-07, + "output_cost_per_token_priority": 1.365e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supports_function_calling": true, "supports_reasoning": true, "supports_system_messages": true, @@ -68404,12 +69598,18 @@ "bedrock/us-gov-east-1/openai.gpt-oss-20b-1:0": { "supports_vision": false, "input_cost_per_token": 8.4e-08, + "input_cost_per_token_batches": 4.2e-08, + "input_cost_per_token_flex": 4.2e-08, + "input_cost_per_token_priority": 1.47e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 3.6e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-20b.html", + "output_cost_per_token_batches": 1.8e-07, + "output_cost_per_token_flex": 1.8e-07, + "output_cost_per_token_priority": 6.3e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supported_endpoints": [ "/v1/chat/completions" ], @@ -68423,12 +69623,18 @@ "bedrock/us-gov-east-1/openai.gpt-oss-120b-1:0": { "supports_vision": false, "input_cost_per_token": 1.8e-07, + "input_cost_per_token_batches": 9e-08, + "input_cost_per_token_flex": 9e-08, + "input_cost_per_token_priority": 3.15e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 7.2e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-120b.html", + "output_cost_per_token_batches": 3.6e-07, + "output_cost_per_token_flex": 3.6e-07, + "output_cost_per_token_priority": 1.26e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supported_endpoints": [ "/v1/chat/completions" ], @@ -68454,6 +69660,7 @@ "output_cost_per_token": 1.2e-05, "prompt_cache_min_tokens": 1024, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -68519,6 +69726,7 @@ "output_cost_per_token": 3e-05, "prompt_cache_min_tokens": 512, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -68534,7 +69742,10 @@ "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "input_cost_per_token_batches": 3e-06, + "output_cost_per_token_batches": 1.5e-05, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-gov-east-1/index.json" }, "bedrock/us-gov-east-1/anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -68556,6 +69767,7 @@ "supports_max_reasoning_effort": true, "supports_mid_conversation_system": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_output_config": true, "supports_parallel_tool_use_config": true, "supports_pdf_input": true, @@ -68596,6 +69808,7 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_max_reasoning_effort": true, "supports_output_config": true, "bedrock_output_config_effort_ceiling": "xhigh", @@ -68627,15 +69840,33 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "input_cost_per_token": 2.7e-06, - "input_cost_per_token_above_272k_tokens": 5.4e-06, - "cache_creation_input_token_cost": 3.375e-06, - "cache_creation_input_token_cost_above_272k_tokens": 6.75e-06, - "cache_read_input_token_cost": 2.7e-07, - "cache_read_input_token_cost_above_272k_tokens": 5.4e-07, - "output_cost_per_token": 1.62e-05, - "output_cost_per_token_above_272k_tokens": 2.43e-05, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-terra.html" + "input_cost_per_token": 2.64e-06, + "input_cost_per_token_above_272k_tokens": 5.28e-06, + "cache_creation_input_token_cost": 3.3e-06, + "cache_creation_input_token_cost_above_272k_tokens": 6.6e-06, + "cache_creation_input_token_cost_above_272k_tokens_flex": 3.3e-06, + "cache_creation_input_token_cost_above_272k_tokens_priority": 1.32e-05, + "cache_creation_input_token_cost_flex": 1.65e-06, + "cache_creation_input_token_cost_priority": 6.6e-06, + "cache_read_input_token_cost": 2.64e-07, + "cache_read_input_token_cost_above_272k_tokens": 5.28e-07, + "cache_read_input_token_cost_above_272k_tokens_flex": 2.64e-07, + "cache_read_input_token_cost_above_272k_tokens_priority": 1.056e-06, + "cache_read_input_token_cost_flex": 1.32e-07, + "cache_read_input_token_cost_priority": 5.28e-07, + "input_cost_per_token_above_272k_tokens_flex": 2.64e-06, + "input_cost_per_token_above_272k_tokens_priority": 1.056e-05, + "input_cost_per_token_flex": 1.32e-06, + "input_cost_per_token_priority": 5.28e-06, + "output_cost_per_token": 1.584e-05, + "output_cost_per_token_above_272k_tokens": 2.376e-05, + "output_cost_per_token_above_272k_tokens_flex": 1.188e-05, + "output_cost_per_token_above_272k_tokens_priority": 4.752e-05, + "output_cost_per_token_flex": 7.92e-06, + "output_cost_per_token_priority": 3.168e-05, + "search_context_cost_per_query": {"search_context_size_high":0.0144,"search_context_size_low":0.0144,"search_context_size_medium":0.0144}, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", + "supports_web_search": true }, "bedrock_mantle/us-gov-west-1/openai.gpt-5.6-luna": { "litellm_provider": "bedrock_mantle", @@ -68662,15 +69893,33 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "input_cost_per_token": 2.7e-07, - "input_cost_per_token_above_272k_tokens": 5.4e-07, - "cache_creation_input_token_cost": 3.375e-07, - "cache_creation_input_token_cost_above_272k_tokens": 6.75e-07, - "cache_read_input_token_cost": 2.7e-08, - "cache_read_input_token_cost_above_272k_tokens": 5.4e-08, - "output_cost_per_token": 1.62e-06, - "output_cost_per_token_above_272k_tokens": 2.43e-06, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-luna.html" + "input_cost_per_token": 2.64e-07, + "input_cost_per_token_above_272k_tokens": 5.28e-07, + "cache_creation_input_token_cost": 3.3e-07, + "cache_creation_input_token_cost_above_272k_tokens": 6.6e-07, + "cache_creation_input_token_cost_above_272k_tokens_flex": 3.3e-07, + "cache_creation_input_token_cost_above_272k_tokens_priority": 1.32e-06, + "cache_creation_input_token_cost_flex": 1.65e-07, + "cache_creation_input_token_cost_priority": 6.6e-07, + "cache_read_input_token_cost": 2.64e-08, + "cache_read_input_token_cost_above_272k_tokens": 5.28e-08, + "cache_read_input_token_cost_above_272k_tokens_flex": 2.64e-08, + "cache_read_input_token_cost_above_272k_tokens_priority": 1.056e-07, + "cache_read_input_token_cost_flex": 1.32e-08, + "cache_read_input_token_cost_priority": 5.28e-08, + "input_cost_per_token_above_272k_tokens_flex": 2.64e-07, + "input_cost_per_token_above_272k_tokens_priority": 1.056e-06, + "input_cost_per_token_flex": 1.32e-07, + "input_cost_per_token_priority": 5.28e-07, + "output_cost_per_token": 1.584e-06, + "output_cost_per_token_above_272k_tokens": 2.376e-06, + "output_cost_per_token_above_272k_tokens_flex": 1.188e-06, + "output_cost_per_token_above_272k_tokens_priority": 4.752e-06, + "output_cost_per_token_flex": 7.92e-07, + "output_cost_per_token_priority": 3.168e-06, + "search_context_cost_per_query": {"search_context_size_high":0.0144,"search_context_size_low":0.0144,"search_context_size_medium":0.0144}, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", + "supports_web_search": true }, "bedrock_mantle/us-gov-west-1/openai.gpt-5.4": { "litellm_provider": "bedrock_mantle", @@ -68696,10 +69945,12 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "input_cost_per_token": 3.375e-06, - "cache_read_input_token_cost": 3.375e-07, - "output_cost_per_token": 2.025e-05, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-54.html" + "input_cost_per_token": 3.3e-06, + "cache_read_input_token_cost": 3.3e-07, + "output_cost_per_token": 1.98e-05, + "search_context_cost_per_query": {"search_context_size_high":0.0144,"search_context_size_low":0.0144,"search_context_size_medium":0.0144}, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-54.html", + "supports_web_search": true }, "bedrock_mantle/us-gov-west-1/xai.grok-4.3": { "use_openai_responses_path": true, @@ -68716,20 +69967,36 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "input_cost_per_token": 1.5e-06, "output_cost_per_token": 3e-06, - "cache_read_input_token_cost": 2.4e-07 + "cache_read_input_token_cost": 2.4e-07, + "cache_read_input_token_cost_batches": 1.2e-07, + "cache_read_input_token_cost_flex": 1.2e-07, + "cache_read_input_token_cost_priority": 4.2e-07, + "input_cost_per_token_batches": 7.5e-07, + "input_cost_per_token_flex": 7.5e-07, + "input_cost_per_token_priority": 2.625e-06, + "output_cost_per_token_batches": 1.5e-06, + "output_cost_per_token_flex": 1.5e-06, + "output_cost_per_token_priority": 5.25e-06 }, "bedrock_mantle/us-gov-west-1/xai.grok-4.6": { "use_openai_responses_path": true, "input_cost_per_token": 2.64e-06, "output_cost_per_token": 7.92e-06, "cache_read_input_token_cost": 6.6e-07, + "cache_read_input_token_cost_flex": 3.3e-07, + "cache_read_input_token_cost_priority": 1.155e-06, + "input_cost_per_token_flex": 1.32e-06, + "input_cost_per_token_priority": 4.62e-06, "litellm_provider": "bedrock_mantle", "max_input_tokens": 500000, "max_output_tokens": 500000, "mode": "chat", + "output_cost_per_token_flex": 3.96e-06, + "output_cost_per_token_priority": 1.386e-05, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -68743,11 +70010,17 @@ }, "bedrock_mantle/us-gov-west-1/google.gemma-4-e2b": { "input_cost_per_token": 4.8e-08, + "input_cost_per_token_flex": 2.4e-08, + "input_cost_per_token_priority": 8.4e-08, "output_cost_per_token": 9.6e-08, "litellm_provider": "bedrock_mantle", "max_input_tokens": 128000, "max_output_tokens": 128000, "mode": "chat", + "output_cost_per_token_batches": 4.8e-08, + "output_cost_per_token_flex": 4.8e-08, + "output_cost_per_token_priority": 1.68e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -68761,11 +70034,18 @@ }, "bedrock_mantle/us-gov-west-1/google.gemma-4-26b-a4b": { "input_cost_per_token": 1.56e-07, + "input_cost_per_token_batches": 7.8e-08, + "input_cost_per_token_flex": 7.8e-08, + "input_cost_per_token_priority": 2.73e-07, "output_cost_per_token": 4.8e-07, "litellm_provider": "bedrock_mantle", "max_input_tokens": 256000, "max_output_tokens": 256000, "mode": "chat", + "output_cost_per_token_batches": 2.4e-07, + "output_cost_per_token_flex": 2.4e-07, + "output_cost_per_token_priority": 8.4e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -68779,11 +70059,18 @@ }, "bedrock_mantle/us-gov-west-1/google.gemma-4-31b": { "input_cost_per_token": 1.68e-07, + "input_cost_per_token_batches": 8.4e-08, + "input_cost_per_token_flex": 8.4e-08, + "input_cost_per_token_priority": 2.94e-07, "output_cost_per_token": 4.8e-07, "litellm_provider": "bedrock_mantle", "max_input_tokens": 256000, "max_output_tokens": 256000, "mode": "chat", + "output_cost_per_token_batches": 2.4e-07, + "output_cost_per_token_flex": 2.4e-07, + "output_cost_per_token_priority": 8.4e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -68798,12 +70085,18 @@ "bedrock_mantle/us-gov-west-1/openai.gpt-oss-20b": { "supports_vision": false, "input_cost_per_token": 8.4e-08, + "input_cost_per_token_batches": 4.2e-08, + "input_cost_per_token_flex": 4.2e-08, + "input_cost_per_token_priority": 1.47e-07, "output_cost_per_token": 3.6e-07, "litellm_provider": "bedrock_mantle", "max_input_tokens": 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@@ -69015,6 +70334,7 @@ }, "bedrock_mantle/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 6e-07, "input_cost_per_token_batches": 3e-07, "input_cost_per_token_flex": 3e-07, @@ -69079,6 +70399,7 @@ }, "bedrock_mantle/qwen.qwen3-coder-30b-a3b-instruct": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, "input_cost_per_token_flex": 7.5e-08, @@ -69100,6 +70421,7 @@ }, "bedrock_mantle/qwen.qwen3-coder-480b-a35b-instruct": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-qwen-qwen3-coder-480b-a35b-instruct.html", "input_cost_per_token": 4.5e-07, "input_cost_per_token_batches": 2.25e-07, 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"https://api.together.ai/v1/models" + "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/Qwen/Qwen3.5-9B" }, "together_ai/zai-org/GLM-4.5-Air-FP8": { "deprecation_date": "2026-04-02", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 2e-07, "litellm_provider": "together_ai", "max_input_tokens": 131072, @@ -70304,6 +71518,7 @@ }, "together_ai/zai-org/GLM-4.7": { "deprecation_date": "2026-04-02", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 4.5e-07, "litellm_provider": "together_ai", "max_input_tokens": 202752, @@ -70314,6 +71529,7 @@ }, "together_ai/zai-org/GLM-5": { "deprecation_date": "2026-06-22", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 1e-06, "litellm_provider": "together_ai", "max_input_tokens": 202752, @@ -70325,6 +71541,7 @@ "together_ai/zai-org/GLM-5.1": { "cache_read_input_token_cost": 2.6e-07, "deprecation_date": "2026-07-10", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 1.4e-06, "litellm_provider": "together_ai", "max_input_tokens": 202752, @@ -70335,6 +71552,7 @@ }, "azure/eu/codex-mini": { "deprecation_date": "2026-11-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 4.13e-07, "input_cost_per_token": 1.65e-06, "litellm_provider": "azure", @@ -70351,6 +71569,8 @@ }, "azure/eu/gpt-4.1": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_priority": 9.63e-07, "input_cost_per_token": 2.2e-06, @@ -70370,6 +71590,8 @@ }, "azure/eu/gpt-4.1-mini": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.4-mini", "cache_read_input_token_cost": 1.1e-07, "cache_read_input_token_cost_priority": 1.93e-07, "input_cost_per_token": 4.4e-07, @@ -70389,6 +71611,8 @@ }, "azure/eu/gpt-4.1-nano": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.4-nano", "cache_read_input_token_cost": 2.8e-08, "input_cost_per_token": 1.1e-07, "input_cost_per_token_batches": 5.5e-08, @@ -70399,7 +71623,9 @@ "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-4o-2024-05-13": { - "deprecation_date": "2026-12-09", + "deprecation_date": "2027-01-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "input_cost_per_token": 5.5e-06, "input_cost_per_token_batches": 2.75e-06, "litellm_provider": "azure", @@ -70412,6 +71638,8 @@ }, "azure/eu/gpt-5": { "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_batches": 6.875e-08, "cache_read_input_token_cost_priority": 2.75e-07, @@ -70432,6 +71660,8 @@ }, "azure/eu/gpt-5-codex": { "deprecation_date": "2027-03-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1-codex", "cache_read_input_token_cost": 1.38e-07, "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", @@ -70440,7 +71670,9 @@ "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/eu/gpt-5-mini": { - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.4-mini", "cache_read_input_token_cost": 2.75e-08, "cache_read_input_token_cost_batches": 1.375e-08, "cache_read_input_token_cost_priority": 4.95e-08, @@ -70461,6 +71693,8 @@ }, "azure/eu/gpt-5-nano": { "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.4-nano", "cache_read_input_token_cost": 5.5e-09, "cache_read_input_token_cost_batches": 2.75e-09, "input_cost_per_token": 5.5e-08, @@ -70478,6 +71712,8 @@ }, "azure/eu/gpt-5-pro": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.2-pro", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -70493,6 +71729,7 @@ }, "azure/eu/gpt-5.1-codex-max": { "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.375e-07, "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", @@ -70502,6 +71739,8 @@ }, "azure/eu/gpt-5.2": { "deprecation_date": "2027-06-08", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.4", "cache_read_input_token_cost": 1.925e-07, "cache_read_input_token_cost_batches": 9.625e-08, "cache_read_input_token_cost_priority": 3.85e-07, @@ -70522,6 +71761,8 @@ }, "azure/eu/gpt-5.2-codex": { "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.3-codex", "cache_read_input_token_cost": 1.925e-07, "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", @@ -70545,6 +71786,7 @@ }, "azure/eu/gpt-5.3-codex": { "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.925e-07, "cache_read_input_token_cost_priority": 3.85e-07, "input_cost_per_token": 1.925e-06, @@ -70562,6 +71804,7 @@ }, "azure/eu/gpt-5.4-mini": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 8.25e-08, "cache_read_input_token_cost_batches": 4.125e-08, "cache_read_input_token_cost_priority": 1.65e-07, @@ -70582,6 +71825,7 @@ }, "azure/eu/gpt-5.4-nano": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.2e-08, "cache_read_input_token_cost_batches": 1.1e-08, "input_cost_per_token": 2.2e-07, @@ -70599,6 +71843,7 @@ }, "azure/eu/gpt-5.4-pro": { "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 3.3e-05, "input_cost_per_token_above_272k_tokens": 6.6e-05, "input_cost_per_token_above_272k_tokens_batches": 3.3e-05, @@ -70772,6 +72017,7 @@ }, "azure/eu/o3": { "deprecation_date": "2026-11-19", + "successor_model": "azure/eu/gpt-5.6-sol", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 2.2e-06, "input_cost_per_token_batches": 1.1e-06, @@ -70790,6 +72036,7 @@ }, "azure/eu/o3-2025-04-16": { "deprecation_date": "2026-11-19", + "successor_model": "azure/eu/gpt-5.6-sol", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 2.2e-06, "input_cost_per_token_batches": 1.1e-06, @@ -70808,6 +72055,8 @@ }, "azure/eu/o3-deep-research": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6-sol", "cache_read_input_token_cost": 2.75e-06, "input_cost_per_token": 1.1e-05, "litellm_provider": "azure", @@ -70817,6 +72066,8 @@ }, "azure/eu/o4-mini": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6-terra", "cache_read_input_token_cost": 3.03e-07, "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, @@ -70835,6 +72086,8 @@ }, "azure/eu/o4-mini-2025-04-16": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6-terra", "cache_read_input_token_cost": 3.03e-07, "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, @@ -70853,6 +72106,7 @@ }, "azure/eu/text-embedding-3-large": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.43e-07, "litellm_provider": "azure", "mode": "embedding", @@ -70860,6 +72114,7 @@ }, "azure/eu/text-embedding-3-small": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.2e-08, "litellm_provider": "azure", "mode": "embedding", @@ -70867,6 +72122,7 @@ }, "azure/eu/text-embedding-ada-002": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.1e-07, "litellm_provider": "azure", "mode": "embedding", @@ -70916,6 +72172,7 @@ }, "azure/us/codex-mini": { "deprecation_date": "2026-11-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 4.13e-07, "input_cost_per_token": 1.65e-06, "litellm_provider": "azure", @@ -70932,6 +72189,8 @@ }, "azure/us/gpt-4.1": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_priority": 9.63e-07, "input_cost_per_token": 2.2e-06, @@ -70951,6 +72210,8 @@ }, "azure/us/gpt-4.1-mini": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-mini", "cache_read_input_token_cost": 1.1e-07, "cache_read_input_token_cost_priority": 1.93e-07, "input_cost_per_token": 4.4e-07, @@ -70970,6 +72231,8 @@ }, "azure/us/gpt-4.1-nano": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-nano", "cache_read_input_token_cost": 2.8e-08, "input_cost_per_token": 1.1e-07, "input_cost_per_token_batches": 5.5e-08, @@ -70980,7 +72243,9 @@ "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-4o-2024-05-13": { - "deprecation_date": "2026-12-09", + "deprecation_date": "2027-01-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "input_cost_per_token": 5.5e-06, "input_cost_per_token_batches": 2.75e-06, "litellm_provider": "azure", @@ -70993,6 +72258,8 @@ }, "azure/us/gpt-5": { "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_batches": 6.875e-08, "cache_read_input_token_cost_priority": 2.75e-07, @@ -71013,6 +72280,8 @@ }, "azure/us/gpt-5-codex": { "deprecation_date": "2027-03-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1-codex", "cache_read_input_token_cost": 1.38e-07, "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", @@ -71021,7 +72290,9 @@ "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5-mini": { - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-mini", "cache_read_input_token_cost": 2.75e-08, "cache_read_input_token_cost_batches": 1.375e-08, "cache_read_input_token_cost_priority": 4.95e-08, @@ -71042,6 +72313,8 @@ }, "azure/us/gpt-5-nano": { "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-nano", "cache_read_input_token_cost": 5.5e-09, "cache_read_input_token_cost_batches": 2.75e-09, "input_cost_per_token": 5.5e-08, @@ -71059,6 +72332,8 @@ }, "azure/us/gpt-5-pro": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.2-pro", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -71074,6 +72349,7 @@ }, "azure/us/gpt-5.1-codex-max": { "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.375e-07, "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", @@ -71083,6 +72359,8 @@ }, "azure/us/gpt-5.2": { "deprecation_date": "2027-06-08", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4", "cache_read_input_token_cost": 1.925e-07, "cache_read_input_token_cost_batches": 9.625e-08, "cache_read_input_token_cost_priority": 3.85e-07, @@ -71103,6 +72381,8 @@ }, "azure/us/gpt-5.2-codex": { "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.3-codex", "cache_read_input_token_cost": 1.925e-07, "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", @@ -71126,6 +72406,7 @@ }, "azure/us/gpt-5.3-codex": { "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.925e-07, "cache_read_input_token_cost_priority": 3.85e-07, "input_cost_per_token": 1.925e-06, @@ -71143,6 +72424,7 @@ }, "azure/us/gpt-5.4-mini": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 8.25e-08, "cache_read_input_token_cost_batches": 4.125e-08, "cache_read_input_token_cost_priority": 1.65e-07, @@ -71163,6 +72445,7 @@ }, "azure/us/gpt-5.4-nano": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.2e-08, "cache_read_input_token_cost_batches": 1.1e-08, "input_cost_per_token": 2.2e-07, @@ -71180,6 +72463,7 @@ }, "azure/us/gpt-5.4-pro": { "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 3.3e-05, "input_cost_per_token_above_272k_tokens": 6.6e-05, "input_cost_per_token_above_272k_tokens_batches": 3.3e-05, @@ -71209,6 +72493,8 @@ }, "azure/us/o3-deep-research": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6-sol", "cache_read_input_token_cost": 2.75e-06, "input_cost_per_token": 1.1e-05, "litellm_provider": "azure", @@ -71218,6 +72504,7 @@ }, "azure/us/text-embedding-3-large": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.43e-07, "litellm_provider": "azure", "mode": "embedding", @@ -71225,6 +72512,7 @@ }, "azure/us/text-embedding-3-small": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.2e-08, "litellm_provider": "azure", "mode": "embedding", @@ -71232,6 +72520,7 @@ }, "azure/us/text-embedding-ada-002": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.1e-07, "litellm_provider": "azure", "mode": "embedding", @@ -71242,6 +72531,8 @@ "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-01-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-realtime-2.1", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -71251,6 +72542,9 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 2.4e-05, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/realtime" @@ -71308,7 +72602,11 @@ "supported_output_modalities": [ "text" ], - "supports_audio_input": true + "supports_audio_input": true, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "supports_native_streaming": true }, "azure/gpt-transcribe": { "deprecation_date": "2028-02-01", @@ -71318,7 +72616,8 @@ "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/audio/transcriptions", - "/v1/realtime/transcription_sessions" + "/v1/realtime/transcription_sessions", + "/v1/realtime" ], "supported_modalities": [ "text", @@ -71327,7 +72626,13 @@ "supported_output_modalities": [ "text" ], - "supports_audio_input": true + "supports_audio_input": true, + "provider_specific_entry": { + "realtime_ga_only": 1, + "transcription_json_or_text_only": 1, + "transcription_usage_duration": 1 + }, + "supports_native_streaming": true }, "azure/gpt-realtime-translate": { "deprecation_date": "2027-11-09", @@ -71345,7 +72650,11 @@ "audio" ], "supports_audio_input": true, - "supports_audio_output": true + "supports_audio_output": true, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "supports_native_streaming": true }, "aihubmix/agnes-2.5-flash": { "input_cost_per_token": 3e-08, @@ -72784,7 +74093,8 @@ "max_input_tokens": 65536, "mode": "evaluation", "output_cost_per_token": 0.0, - "source": "https://docs.typesafe.ai/models" + "source": "https://docs.typesafe.ai/models", + "supports_box_questions": true }, "typesafe/jev-preview": { "input_cost_per_token": 4.2e-08, @@ -73643,6 +74953,7 @@ "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, "deprecation_date": "2026-05-15", + "deprecation_source": "https://docs.x.ai/developers/migration/may-15-retirement", "input_cost_per_image_token": 1e-06, "input_cost_per_token": 1e-06, "input_cost_per_token_above_200k_tokens": 2e-06, @@ -73653,6 +74964,7 @@ "output_cost_per_token": 2e-06, "output_cost_per_token_above_200k_tokens": 4e-06, "source": "https://api.x.ai/v1/language-models", + "successor_model": "xai/grok-build-0.1", "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, @@ -73734,6 +75046,7 @@ "output_cost_per_token_priority": 1.875e-05, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -73741,6 +75054,8 @@ }, "vertex_ai/gemini-2.0-flash": { "deprecation_date": "2026-06-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.5-flash-lite", "input_cost_per_audio_token": 1e-06, "input_cost_per_audio_token_batches": 5e-07, "input_cost_per_character": 3.75e-08, @@ -73754,6 +75069,8 @@ }, "vertex_ai/gemini-2.0-flash-lite": { "deprecation_date": "2026-06-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.5-flash-lite", "input_cost_per_audio_token": 7.5e-08, "input_cost_per_audio_token_batches": 3.75e-08, "input_cost_per_character": 1.875e-08, @@ -73805,6 +75122,8 @@ }, "vertex_ai/veo-3.0-generate-001": { "deprecation_date": "2026-06-30", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/veo-3.1-generate-001", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "mode": "video_generation", @@ -73820,6 +75139,8 @@ }, "vertex_ai/veo-3.0-fast-generate-001": { "deprecation_date": "2026-06-30", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/veo-3.1-fast-generate-001", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "mode": "video_generation", @@ -73836,6 +75157,8 @@ }, "vertex_ai/veo-2.0-generate-001": { "deprecation_date": "2026-06-30", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/veo-3.1-generate-001", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "mode": "video_generation", @@ -74156,6 +75479,7 @@ "apac.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "litellm_provider": "bedrock_converse", "supports_tool_search": true, @@ -74183,12 +75507,14 @@ "input_cost_per_token": 5.5e-06, "cache_read_input_token_cost": 5.5e-07, "output_cost_per_token": 2.75e-05, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/index.json", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/ap-northeast-1/index.json", "token_count_model": { "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "ap-southeast-4" - } + }, + "input_cost_per_token_batches": 2.75e-06, + "output_cost_per_token_batches": 1.375e-05 }, "apac.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -74270,6 +75596,7 @@ "max_output_tokens": 128000, "mode": "chat", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -74360,6 +75687,7 @@ }, "deepseek.r1-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-r1.html", "input_cost_per_token": 1.35e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -74794,7 +76122,7 @@ "supports_function_calling": true, "input_cost_per_token": 2e-06, "output_cost_per_token": 1e-05, - "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost": 1e-07, "source": "https://docs.perplexity.ai/docs/agent-api/models" }, "perplexity/anthropic/claude-fable-5-1": { @@ -74842,6 +76170,9 @@ "output_cost_per_token": 5e-05, "cache_read_input_token_cost": 1e-06, "cache_creation_input_token_cost": 1.25e-05, + "input_cost_per_token_above_272k_tokens": 2e-05, + "output_cost_per_token_above_272k_tokens": 7.5e-05, + "cache_read_input_token_cost_above_272k_tokens": 2e-06, "source": "https://docs.perplexity.ai/docs/agent-api/models" }, "perplexity/openai/gpt-6-luna": { @@ -75224,6 +76555,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -75328,6 +76660,7 @@ "output_cost_per_token_above_272k_tokens": 1.65e-05, "output_cost_per_token_above_272k_tokens_ultrafast": 9.9e-05, "output_cost_per_token_ultrafast": 6.6e-05, + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-1-sol.html", "supported_endpoints": [ "/v1/chat/completions", @@ -75350,6 +76683,7 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true, + "supports_web_search": true, "supports_xhigh_reasoning_effort": true, "use_openai_responses_path": true }, @@ -75446,6 +76780,8 @@ }, "azure_ai/kimi-k2-thinking": { "deprecation_date": "2026-03-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", + "successor_model": "azure_ai/kimi-k2.5", "input_cost_per_token": 6e-07, "litellm_provider": "azure_ai", "max_input_tokens": 262144, @@ -75547,6 +76883,7 @@ "azure/model-router": { "comment": "The flat $0.14 per M input tokens is the router's own fee, the routed model is priced on top of it", "deprecation_date": "2027-05-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.4e-07, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -75558,6 +76895,7 @@ }, "azure/whisper": { "deprecation_date": "2026-12-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_second": 0.0001, "litellm_provider": "azure", "mode": "audio_transcription", @@ -75619,6 +76957,7 @@ "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, "output_cost_per_image_token_batches": 1.5e-05, + "output_cost_per_image_token_priority": 5.4e-05, "output_cost_per_token": 7.5e-06, "output_cost_per_token_batches": 3.75e-06, "output_cost_per_token_priority": 1.35e-05, @@ -75665,6 +77004,7 @@ "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, "output_cost_per_image_token_batches": 1.5e-05, + "output_cost_per_image_token_priority": 5.4e-05, "output_cost_per_token": 7.5e-06, "output_cost_per_token_batches": 3.75e-06, "output_cost_per_token_priority": 1.35e-05, @@ -75774,6 +77114,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -75826,6 +77167,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -75870,6 +77212,7 @@ "thinking_always_on": false, "prompt_cache_min_tokens": 512, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -75917,6 +77260,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -75953,6 +77297,7 @@ "max_output_tokens": 128000, "mode": "chat", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76009,6 +77354,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76055,6 +77401,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76095,6 +77442,7 @@ "prompt_cache_min_tokens": 512, "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/index.json", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76136,6 +77484,7 @@ "prompt_cache_min_tokens": 512, "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/index.json", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76182,6 +77531,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76233,6 +77583,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76279,6 +77630,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76311,6 +77663,9 @@ "input_cost_per_token": 1e-07, "output_cost_per_token": 5e-07, "cache_read_input_token_cost": 1e-08, + "input_cost_per_token_above_100k_tokens": 5e-07, + "output_cost_per_token_above_100k_tokens": 2.5e-06, + "cache_read_input_token_cost_above_100k_tokens": 5e-08, "source": "https://docs.perplexity.ai/docs/agent-api/models" }, "us-gov.anthropic.claude-haiku-5-5": { @@ -76336,6 +77691,7 @@ "prompt_cache_min_tokens": 512, "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/index.json", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76387,6 +77743,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76437,6 +77794,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76481,6 +77839,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76645,23 +78004,19 @@ }, "vertex_ai/gemini-robotics-er-2-preview": { "cache_read_input_token_cost": 1e-07, - "cache_read_input_token_cost_batches": 5e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 1e-06, - "input_cost_per_token_batches": 5e-07, "litellm_provider": "vertex_ai", "max_input_tokens": 131072, "max_output_tokens": 65536, "mode": "chat", "output_cost_per_reasoning_token": 5e-06, "output_cost_per_token": 5e-06, - "output_cost_per_token_batches": 2.5e-06, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", - "/v1/completions", - "/v1/batch" + "/v1/completions" ], "supported_modalities": [ "text", @@ -76691,23 +78046,19 @@ }, "gemini-robotics-er-2-preview": { "cache_read_input_token_cost": 1e-07, - "cache_read_input_token_cost_batches": 5e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 1e-06, - "input_cost_per_token_batches": 5e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 131072, "max_output_tokens": 65536, "mode": "chat", "output_cost_per_reasoning_token": 5e-06, "output_cost_per_token": 5e-06, - "output_cost_per_token_batches": 2.5e-06, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", - "/v1/completions", - "/v1/batch" + "/v1/completions" ], "supported_modalities": [ "text", @@ -76774,6 +78125,7 @@ "supports_audio_input": true, "supports_audio_output": false, "supports_computer_use": true, + "supports_continuation": true, "supports_function_calling": true, "supports_minimal_reasoning_effort": false, "supports_native_streaming": true, @@ -76833,6 +78185,7 @@ ], "supports_audio_input": true, "supports_computer_use": true, + "supports_continuation": true, "supports_function_calling": true, "supports_minimal_reasoning_effort": false, "supports_native_streaming": true, @@ -76890,6 +78243,7 @@ "text" ], "supports_audio_input": true, + "supports_continuation": true, "supports_function_calling": true, "supports_minimal_reasoning_effort": false, "supports_native_streaming": true, @@ -77004,6 +78358,7 @@ "litellm_provider": "xai", "mode": "realtime", "source": "https://docs.x.ai/developers/pricing", + "successor_model": "xai/grok-voice-3.0", "supported_endpoints": [ "/v1/realtime" ], @@ -77087,6 +78442,7 @@ "cache_creation_input_token_cost_above_1hr": 1.6e-05, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-10-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 8e-06, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -77198,9 +78554,10 @@ "max_output_tokens": 1048576, "mode": "chat", "output_cost_per_token": 1e-06, - "source": "https://tokenfactory.nebius.com/models/catalog/text2text/reflection%2Fbeam", + "source": "https://tokenfactory.nebius.com/api/public/models_info", "supports_function_calling": true, - "supports_reasoning": true + "supports_reasoning": true, + "cache_read_input_token_cost": 5e-08 }, "baseten/deepseek-ai/DeepSeek-V4.1-Flash-1017": { "cache_read_input_token_cost": 7e-09, @@ -77247,6 +78604,7 @@ "output_cost_per_token_priority": 1.5e-06, "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -77405,6 +78763,7 @@ "output_cost_per_token_priority": 9e-07, "source": "https://platform.minimax.io/docs/guides/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -78240,6 +79599,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -78454,6 +79814,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -78529,6 +79890,8 @@ "cache_creation_input_token_cost_batches": 1.875e-06, "cache_read_input_token_cost_batches": 1.5e-07, "deprecation_date": "2026-11-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "bedrock/claude_platform/claude-sonnet-5-5", "input_cost_per_token_batches": 1.5e-06, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -78618,6 +79981,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -78741,6 +80105,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -79038,6 +80403,7 @@ "mode": "responses", "output_cost_per_token": 5.5e-06, "output_cost_per_token_above_272k_tokens": 8.25e-06, + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-1-terra.html", "supported_endpoints": [ "/v1/chat/completions", @@ -79060,6 +80426,7 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true, + "supports_web_search": true, "supports_xhigh_reasoning_effort": true, "use_openai_responses_path": true }, @@ -80600,6 +81967,7 @@ "prompt_cache_min_tokens": 512.0, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_anthropic_thinking_payload": true, "supports_assistant_prefill": false, "supports_function_calling": true, @@ -80644,6 +82012,7 @@ "cache_creation_input_token_cost": 3.0002e-07, "cache_read_input_token_cost": 3.003e-08, "deprecation_date": "2026-11-19", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "input_cost_per_token": 3.0002e-07, "input_dbu_cost_per_token": 4.286e-06, "litellm_provider": "databricks", @@ -80671,7 +82040,8 @@ "input_cost_per_token_priority": 5.25e-07, "output_cost_per_token_priority": 2.1e-06, "cache_read_input_token_cost_priority": 5.25e-08, - "cache_creation_input_token_cost_priority": 5.25e-07 + "cache_creation_input_token_cost_priority": 5.25e-07, + "successor_model": "databricks/databricks-deepseek-v4-1-flash-1017" }, "databricks/databricks-deepseek-v4-1-flash-1017": { "cache_creation_input_token_cost": 3.0002e-07, @@ -81123,6 +82493,8 @@ "databricks/databricks-kimi-k2-7": { "cache_creation_input_token_cost": 9.4997e-07, "cache_read_input_token_cost": 1.8998e-07, + "deprecation_date": "2026-10-30", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/retired-models-policy", "input_cost_per_token": 9.4997e-07, "input_dbu_cost_per_token": 1.3571e-05, "litellm_provider": "databricks", @@ -81135,6 +82507,7 @@ "output_cost_per_token": 4.00001e-06, "output_dbu_cost_per_token": 5.7143e-05, "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "successor_model": "databricks/databricks-kimi-k3", "supported_modalities": [ "text", "image" @@ -81180,6 +82553,7 @@ ], "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -81196,6 +82570,7 @@ "output_cost_per_token": 3.08e-06, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -81212,6 +82587,24 @@ "output_cost_per_token": 8.4e-07, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "fireworks_ai/accounts/fireworks/routers/deepseek-v4p1-flash-1017-ultrafast": { + "cache_read_input_token_cost": 4.8e-08, + "input_cost_per_token": 2.4e-06, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 393216, + "mode": "chat", + "output_cost_per_token": 9.6e-06, + "source": "https://docs.fireworks.ai/serverless/pricing.md", + "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -81228,6 +82621,7 @@ "output_cost_per_token": 8.4e-07, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -81311,17 +82705,17 @@ "supports_native_streaming": true }, "fireworks_ai/accounts/fireworks/models/ultramarine-1-flash-us": { - "cache_read_input_token_cost": 4.5e-08, - "cache_read_input_token_cost_priority": 5.625e-08, - "input_cost_per_token": 2.25e-07, - "input_cost_per_token_priority": 2.8125e-07, + "cache_read_input_token_cost": 3e-08, + "cache_read_input_token_cost_priority": 3.75e-08, + "input_cost_per_token": 1.5e-07, + "input_cost_per_token_priority": 1.875e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 1048576, "mode": "chat", - "output_cost_per_token": 7.5e-07, - "output_cost_per_token_priority": 9.375e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token": 5e-07, + "output_cost_per_token_priority": 6.25e-07, + "source": "https://docs.fireworks.ai/serverless/pricing.md", "supports_function_calling": false, "supports_response_schema": true, "supports_tool_choice": false, @@ -81411,6 +82805,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -81463,5 +82858,3339 @@ "supports_response_schema": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true + }, + "nebius/deepseek-ai/DeepSeek-V4.1-Flash-1017": { + "max_input_tokens": 1048576, + "input_cost_per_token": 3e-07, + "cache_read_input_token_cost": 6e-09, + "output_cost_per_token": 1.2e-06, + "litellm_provider": "nebius", + "mode": "chat", + "supports_vision": true, + "supports_reasoning": true, + "supports_function_calling": true, + "source": "https://tokenfactory.nebius.com/api/public/models_info" + }, + "nebius/meta-models/muse-spark-open": { + "max_input_tokens": 1048576, + "input_cost_per_token": 1.25e-06, + "cache_read_input_token_cost": 1.5e-07, + "output_cost_per_token": 4.25e-06, + "litellm_provider": "nebius", + "mode": "chat", + "supports_vision": true, + "supports_video_input": true, + "supports_reasoning": true, + "supports_function_calling": true, + "source": "https://tokenfactory.nebius.com/api/public/models_info" + }, + "nebius/MiniMaxAI/MiniMax-M3.1-Flash": { + "max_input_tokens": 1048576, + "input_cost_per_token": 1.5e-07, + "cache_read_input_token_cost": 1.5e-08, + "output_cost_per_token": 6e-07, + "litellm_provider": "nebius", + "mode": "chat", + "supports_vision": true, + "supports_reasoning": true, + "supports_function_calling": true, + "source": "https://tokenfactory.nebius.com/api/public/models_info" + }, + "nebius/nvidia/Nemotron-3.5-Super-VL": { + "max_input_tokens": 1048576, + "input_cost_per_token": 3e-07, + "cache_read_input_token_cost": 6e-08, + "output_cost_per_token": 9e-07, + "litellm_provider": "nebius", + "mode": "chat", + "supports_vision": true, + "supports_video_input": true, + "supports_reasoning": true, + "supports_function_calling": true, + "source": "https://tokenfactory.nebius.com/api/public/models_info" + }, + "empiriolabs/aplomb-1": { + "litellm_provider": "empiriolabs", + "mode": "chat", + "max_input_tokens": 1000000, + "input_cost_per_token": 2e-08, + "output_cost_per_token": 0.0, + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses", + "/v1/messages", + "/v1/decisions" + ], + "supports_vision": true, + "supports_audio_input": true, + "source": "https://empiriolabs.ai/models/aplomb-1" + }, + "empiriolabs/deepseek-v4-1-flash-1017": { + "litellm_provider": "empiriolabs", + "mode": "chat", + "max_input_tokens": 1000000, + "max_output_tokens": 393216, + "input_cost_per_token": 3e-07, + "output_cost_per_token": 1.2e-06, + "supports_system_messages": true, + "supports_vision": true, + "supports_reasoning": true, + "supports_response_schema": true, + "source": "https://empiriolabs.ai/models/deepseek-v4-1-flash-1017" + }, + 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"search_context_size_low": 0.02, + "search_context_size_medium": 0.02, + "search_context_size_high": 0.02 + }, + "supports_response_schema": true, + "source": "https://empiriolabs.ai/models/deepseek-v4-pro" + }, + "empiriolabs/deepseek-v4-pro:variant2": { + "litellm_provider": "empiriolabs", + "mode": "chat", + "max_input_tokens": 1000000, + "max_output_tokens": 393216, + "input_cost_per_token": 1.65e-06, + "output_cost_per_token": 3.301e-06, + "cache_read_input_token_cost": 1.38e-07, + "supports_system_messages": true, + "supports_reasoning": true, + "supports_web_search": true, + "search_context_cost_per_query": { + "search_context_size_low": 0.01, + "search_context_size_medium": 0.01, + "search_context_size_high": 0.01 + }, + "supports_prompt_caching": true, + "supports_response_schema": true, + "source": "https://empiriolabs.ai/models/deepseek-v4-pro" + }, + "empiriolabs/deepseek-v4-pro:variant3": { + "litellm_provider": "empiriolabs", + "mode": "chat", + "max_input_tokens": 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"https://api.together.ai/v1/models", + "supports_prompt_caching": true } } diff --git a/litellm/models/plugin_upload.py b/litellm/models/plugin_upload.py new file mode 100644 index 00000000000..bd5e85c79cc --- /dev/null +++ b/litellm/models/plugin_upload.py @@ -0,0 +1,165 @@ +from collections.abc import AsyncIterator, Mapping +from dataclasses import dataclass +from datetime import datetime +from enum import Enum +from types import MappingProxyType +from typing import Literal, Protocol + + +def has_agent_skill_metadata(manifest: Mapping[str, object]) -> bool: + return isinstance(manifest.get("agent_skill"), dict) + + +def uploaded_plugin_source(base_url: str, name: str, digest: str) -> Mapping[str, str]: + return MappingProxyType( + { + "source": "archive", + "url": f"{base_url.rstrip('/')}/claude-code/plugins/{name}/archive/{digest}.zip", + "sha256": digest, + } + ) + + +@dataclass(frozen=True, slots=True) +class PluginUpload: + name: str + version: str | None + description: str | None + manifest: Mapping[str, object] + content: bytes + created_by: str | None + + +@dataclass(frozen=True, slots=True) +class PluginArchiveMetadata: + name: str + enabled: bool + source: Mapping[str, str] + manifest_json: str | None + id: str | None = None + version: str | None = None + description: str | None = None + has_agent_skill_metadata: bool = False + updated_at: datetime | None = None + + +@dataclass(frozen=True, slots=True) +class PluginPublication: + name: str + version: str | None + description: str | None + manifest: Mapping[str, object] + created_by: str | None + content: bytes | None = None + + +@dataclass(frozen=True, slots=True) +class PluginPublicationBase: + id: str + updated_at: datetime | None + + +@dataclass(frozen=True, slots=True) +class PublishedPlugin: + id: str + name: str + version: str + enabled: bool + updated_at: datetime + + +@dataclass(frozen=True, slots=True) +class PluginPublicationError: + kind: Literal["invalid_version", "conflict", "not_found"] + message: str + + +@dataclass(frozen=True, slots=True) +class PluginVersion: + id: str + version: str | None + description: str | None + manifest: Mapping[str, object] + published_at: datetime | None + published_by: str | None + archive_available: bool + + +@dataclass(frozen=True, slots=True) +class PluginSnapshot: + id: str + name: str + version: str | None + description: str | None + manifest: Mapping[str, object] + enabled: bool + created_at: datetime | None + updated_at: datetime | None + created_by: str | None + + +@dataclass(frozen=True, slots=True) +class PluginDownloader: + authenticated: bool + user_id: str | None + user_email: str | None + key_alias: str | None + team_id: str | None + team_alias: str | None + + +class PluginDownloadResult(Enum): + RECORDED = "recorded" + SKILL_NOT_FOUND = "skill_not_found" + + +@dataclass(frozen=True, slots=True) +class PluginDownloadEvent: + id: str + downloaded_at: datetime + version: str | None + digest: str + authenticated: bool + user_id: str | None + user_email: str | None + key_alias: str | None + team_id: str | None + team_alias: str | None + + +@dataclass(frozen=True, slots=True) +class PluginDownloadsResponse: + total_downloads: int + anonymous_downloads: int + downloads: tuple[PluginDownloadEvent, ...] + next_cursor: str | None + + +class PluginUploadStore(Protocol): + async def create(self, upload: PluginUpload) -> str | None: ... + + async def get_plugin(self, name: str) -> PluginSnapshot | None: ... + + async def publish( + self, publication: PluginPublication, expected: PluginPublicationBase | None = None + ) -> PublishedPlugin | PluginPublicationError: ... + + async def versions(self, metadata: PluginArchiveMetadata, limit: int, offset: int) -> tuple[PluginVersion, ...]: ... + + async def version(self, metadata: PluginArchiveMetadata, version_id: str) -> PluginVersion | None: ... + + async def version_content(self, metadata: PluginArchiveMetadata, version_id: str) -> bytes | None: ... + + async def get_metadata(self, name: str) -> PluginArchiveMetadata | None: ... + + async def get_content(self, metadata: PluginArchiveMetadata) -> bytes | None: ... + + def public_metadata(self) -> AsyncIterator[PluginArchiveMetadata]: ... + + async def record_download( + self, metadata: PluginArchiveMetadata, digest: str, downloader: PluginDownloader + ) -> PluginDownloadResult: ... + + async def downloads(self, name: str, limit: int, cursor: int | None) -> PluginDownloadsResponse | None: ... + + async def download_counts(self, plugin_ids: tuple[str, ...]) -> Mapping[str, int]: ... diff --git a/litellm/models/skill_submission.py b/litellm/models/skill_submission.py new file mode 100644 index 00000000000..09d722fa69f --- /dev/null +++ b/litellm/models/skill_submission.py @@ -0,0 +1,110 @@ +from collections.abc import Mapping +from dataclasses import dataclass +from datetime import datetime +from typing import Literal, Protocol, TypeAlias + +from litellm.models.plugin_upload import ( + PluginPublication, + PluginPublicationBase, + PluginPublicationError, + PublishedPlugin, +) +from litellm.types.proxy.skill_scanning import SkillScan + +SubmissionStatus: TypeAlias = Literal["pending_review", "approved", "rejected"] +SubmissionOperation: TypeAlias = Literal["create", "update"] + + +@dataclass(frozen=True, slots=True) +class SkillProposal: + name: str + version: str | None + description: str | None + manifest: Mapping[str, object] + + +@dataclass(frozen=True, slots=True) +class SkillSubmission: + id: str + plugin_name: str + operation: SubmissionOperation + status: SubmissionStatus + proposal: SkillProposal + has_archive: bool + submitted_by: str + created_at: datetime + base_plugin_id: str | None + base_updated_at: datetime | None + reviewed_by: str | None + reviewed_at: datetime | None + rejection_reason: str | None + + +@dataclass(frozen=True, slots=True) +class SubmissionPage: + submissions: tuple[SkillSubmission, ...] + has_more: bool + + +@dataclass(frozen=True, slots=True) +class SubmissionLimitExceeded: + message: str + + +@dataclass(frozen=True, slots=True) +class SubmissionMissing: + pass + + +@dataclass(frozen=True, slots=True) +class SubmissionConflict: + message: str + + +@dataclass(frozen=True, slots=True) +class SubmissionReviewed: + submission: SkillSubmission + plugin: PublishedPlugin | None + published_source: Mapping[str, str] | None = None + + +SubmissionReviewResult: TypeAlias = SubmissionReviewed | SubmissionMissing | SubmissionConflict | PluginPublicationError + + +@dataclass(frozen=True, slots=True) +class SkillScanInput: + scan: SkillScan + source: Mapping[str, str] + content: bytes | None + + +class SkillSubmissionStore(Protocol): + async def get_scan(self, submission_id: str) -> SkillScan | SubmissionMissing | None: ... + + async def start_scan( + self, submission_id: str, scan: SkillScan + ) -> SkillScanInput | SubmissionMissing | SubmissionConflict: ... + + async def finish_scan(self, submission_id: str, scan: SkillScan) -> None: ... + + async def submit( + self, upload: PluginPublication, submitted_by: str, base: PluginPublicationBase | None + ) -> SkillSubmission | SubmissionLimitExceeded: ... + + async def list( + self, submitted_by: str | None, status: SubmissionStatus | None, limit: int, offset: int + ) -> SubmissionPage: ... + + async def get(self, submission_id: str, submitted_by: str | None) -> SkillSubmission | None: ... + + async def get_archive(self, submission_id: str, submitted_by: str | None) -> bytes | None: ... + + async def review( + self, + submission_id: str, + reviewer: str, + approve: bool, + reason: str | None, + *, + publication_base_url: str | None = None, + ) -> SubmissionReviewResult: ... diff --git a/litellm/provider_endpoints_support_backup.json b/litellm/provider_endpoints_support_backup.json index 700a35edb06..00fee0a0d5a 100644 --- a/litellm/provider_endpoints_support_backup.json +++ b/litellm/provider_endpoints_support_backup.json @@ -3158,7 +3158,7 @@ "batches": false, "messages": false, "interactions": false, - "systemone": false, + "systemone": true, "a2a": false, "generateContent": false } @@ -5250,13 +5250,13 @@ "generateContent": false } }, - "empiriolabs": { - "display_name": "EmpirioLabs (`empiriolabs`)", - "url": "https://docs.litellm.ai/docs/providers/empiriolabs", + "wally": { + "display_name": "Wally (`wally`)", + "url": "https://docs.litellm.ai/docs/providers/wally", "endpoints": { - "chat_completions": false, - "responses": false, - "text_completion": false, + "chat_completions": true, + "responses": true, + "text_completion": true, "embeddings": false, "image_generations": false, "image_edits": false, @@ -5269,11 +5269,37 @@ "realtime": false, "video_generations": false, "batches": false, - "messages": false, - "interactions": false, + "messages": true, + "interactions": true, "systemone": false, - "a2a": false, - "generateContent": false + "a2a": true, + "generateContent": true + } + }, + "empiriolabs": { + "display_name": "EmpirioLabs AI (`empiriolabs`)", + "url": "https://docs.litellm.ai/docs/providers/empiriolabs", + "endpoints": { + "chat_completions": true, + "responses": true, + "text_completion": true, + "embeddings": true, + "image_generations": false, + "image_edits": false, + "audio_transcriptions": false, + "audio_speech": false, + "rerank": false, + "ocr": false, + "search": false, + "moderations": false, + "realtime": false, + "video_generations": false, + "batches": false, + "messages": true, + "interactions": true, + "systemone": false, + "a2a": true, + "generateContent": true } }, "openinfer": { diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/0w6kofhv0tntp.js b/litellm/proxy/_experimental/out/_next/static/chunks/0w6kofhv0tntp.js index 0a716cb7115..0b032e1b813 100644 --- a/litellm/proxy/_experimental/out/_next/static/chunks/0w6kofhv0tntp.js +++ b/litellm/proxy/_experimental/out/_next/static/chunks/0w6kofhv0tntp.js @@ -29,4 +29,4 @@ const response = await 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path_prefixes=("/v1/decisions", "/decisions", "/v1/systemone", "/systemone", "/v1/extraction", "/extraction"), ), + LazyFeature( + name="skill_hub", + module_path="litellm.proxy.discovery_endpoints.skill_hub_endpoints", + path_prefixes=("/skill-hub",), + register_fn=_include_skill_hub, + ), LazyFeature( name="claude_code_marketplace", module_path="litellm.proxy.anthropic_endpoints.claude_code_endpoints", @@ -504,10 +519,13 @@ def _lazy_lock(app: "FastAPI", module_path: str) -> asyncio.Lock: def _register_feature(app: "FastAPI", feat: LazyFeature, module: object, features: tuple[LazyFeature, ...]) -> None: - before: Final = len(app.router.routes) + routes_before: Final = frozenset(id(route) for route in app.router.routes) feat.register_fn(app, module) lazy_routes: Final[Mapping[str, tuple[BaseRoute, ...]]] = MappingProxyType( - {**_lazy_routes(app), feat.module_path: tuple(app.router.routes[before:])} + { + **_lazy_routes(app), + feat.module_path: tuple(route for route in app.router.routes if id(route) not in routes_before), + } ) app.state.lazy_routes = lazy_routes # rebind-ok: the app owns the record of which routes each feature added app.router.routes[:] = _route_table( # rebind-ok: the app owns its route table diff --git a/litellm/proxy/_lazy_openapi_snapshot.json b/litellm/proxy/_lazy_openapi_snapshot.json index 5a80583b207..7d9e230f8ef 100644 --- a/litellm/proxy/_lazy_openapi_snapshot.json +++ b/litellm/proxy/_lazy_openapi_snapshot.json @@ -7454,6 +7454,31 @@ "claude_code_marketplace": { "components": { "schemas": { + "Body_upload_plugin_claude_code_plugins_upload_post": { + "properties": { + "file": { + "contentMediaType": "application/octet-stream", + "description": "Skill ZIP containing SKILL.md and supporting files, up to 10 MiB", + "title": "File", + "type": "string" + }, + "metadata": { + "contentMediaType": "application/json", + "contentSchema": { + "$ref": "#/components/schemas/UploadPluginRequest" + }, + "description": "JSON skill metadata without a source URL", + "title": "Metadata", + "type": "string" + } + }, + "required": [ + "file", + "metadata" + ], + "title": "Body_upload_plugin_claude_code_plugins_upload_post", + "type": "object" + }, "HTTPValidationError": { "properties": { "detail": { @@ -7516,6 +7541,145 @@ "title": "PluginAuthor", "type": "object" }, + "PluginDownloadEvent": { + "properties": { + "authenticated": { + "title": "Authenticated", + "type": "boolean" + }, + "digest": { + "title": "Digest", + "type": "string" + }, + "downloaded_at": { + "format": "date-time", + "title": "Downloaded At", + "type": "string" + }, + "id": { + "title": "Id", + "type": "string" + }, + "key_alias": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Key Alias" + }, + "team_alias": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Team Alias" + }, + "team_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Team Id" + }, + "user_email": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "User Email" + }, + "user_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "User Id" + }, + "version": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Version" + } + }, + "required": [ + "id", + "downloaded_at", + "version", + "digest", + "authenticated", + "user_id", + "user_email", + "key_alias", + "team_id", + "team_alias" + ], + "title": "PluginDownloadEvent", + "type": "object" + }, + "PluginDownloadsResponse": { + "properties": { + "anonymous_downloads": { + "title": "Anonymous Downloads", + "type": "integer" + }, + "downloads": { + "items": { + "$ref": "#/components/schemas/PluginDownloadEvent" + }, + "title": "Downloads", + "type": "array" + }, + "next_cursor": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Next Cursor" + }, + "total_downloads": { + "title": "Total Downloads", + "type": "integer" + } + }, + "required": [ + "total_downloads", + "anonymous_downloads", + "downloads", + "next_cursor" + ], + "title": "PluginDownloadsResponse", + "type": "object" + }, "PluginListItem": { "description": "Plugin item in list responses.", "properties": { @@ -7887,7 +8051,7 @@ } ], "default": "1.0.0", - "description": "Semantic version", + "description": "Semantic version, defaults to 1.0.0 on creation", "title": "Version" } }, @@ -7925,7 +8089,152 @@ "type": "object" }, "UpdatePluginRequest": { - "description": "Request body for replacing an existing plugin.\n\nThe plugin name is the resource identity and is supplied as the path\nparameter, so it cannot be changed here. This is a full replace: omitted\nfields reset to their defaults, so version is cleared rather than\ndefaulting to the create-time \"1.0.0\".", + "description": "Request body for replacing an existing plugin.\n\nThe plugin name is the resource identity and is supplied as the path\nparameter, so it cannot be changed here. This is a full replace: omitted\nfields reset to their defaults, except version which automatically increments\nthe published patch version when omitted or null.", + "properties": { + "author": { + "anyOf": [ + { + "$ref": "#/components/schemas/PluginAuthor" + }, + { + "type": "null" + } + ], + "description": "Plugin author" + }, + "category": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Plugin category", + "title": "Category" + }, + "description": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Plugin description", + "title": "Description" + }, + "domain": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Skill domain (e.g., 'Productivity')", + "title": "Domain" + }, + "expected_updated_at": { + "anyOf": [ + { + "format": "date-time", + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Published updated_at read by the editor. A stale value returns 409", + "title": "Expected Updated At" + }, + "homepage": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Plugin homepage URL", + "title": "Homepage" + }, + "installation_preference": { + "anyOf": [ + { + "enum": [ + "available", + "auto_install", + "required" + ], + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Emitted as installationPreference on this plugin's marketplace.json entry. Needs an archive source, the only plugins Claude Desktop lists from a marketplace.json URL, and 'auto_install' or 'required' also need its sha256. Claude Desktop honors the mark only when the archive and marketplace.json share its inference gateway origin", + "title": "Installation Preference" + }, + "keywords": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "description": "Search keywords", + "title": "Keywords" + }, + "namespace": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Skill namespace within domain (e.g., 'workflows')", + "title": "Namespace" + }, + "source": { + "additionalProperties": { + "type": "string" + }, + "description": "Plugin source reference. Supported formats:\n- GitHub: {'source': 'github', 'repo': 'org/repo'}\n- Git URL: {'source': 'url', 'url': 'https://github.com/org/repo.git'}\n- Git Subdir: {'source': 'git-subdir', 'url': 'https://github.com/org/repo.git', 'path': 'plugins/plugin-name'}\n- Zip archive on any https host (e.g. S3): {'source': 'archive', 'url': 'https://bucket.s3.amazonaws.com/plugin.zip', 'sha256': ''}", + "title": "Source", + "type": "object" + }, + "version": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Explicit higher SemVer, or omit/null for an automatic patch bump", + "title": "Version" + } + }, + "required": [ + "source" + ], + "title": "UpdatePluginRequest", + "type": "object" + }, + "UploadPluginRequest": { "properties": { "author": { "anyOf": [ @@ -8018,6 +8327,12 @@ "description": "Search keywords", "title": "Keywords" }, + "name": { + "description": "Skill name (kebab-case)", + "pattern": "^[a-z0-9-]+$", + "title": "Name", + "type": "string" + }, "namespace": { "anyOf": [ { @@ -8030,14 +8345,6 @@ "description": "Skill namespace within domain (e.g., 'workflows')", "title": "Namespace" }, - "source": { - "additionalProperties": { - "type": "string" - }, - "description": "Plugin source reference. Supported formats:\n- GitHub: {'source': 'github', 'repo': 'org/repo'}\n- Git URL: {'source': 'url', 'url': 'https://github.com/org/repo.git'}\n- Git Subdir: {'source': 'git-subdir', 'url': 'https://github.com/org/repo.git', 'path': 'plugins/plugin-name'}\n- Zip archive on any https host (e.g. S3): {'source': 'archive', 'url': 'https://bucket.s3.amazonaws.com/plugin.zip', 'sha256': ''}", - "title": "Source", - "type": "object" - }, "version": { "anyOf": [ { @@ -8047,14 +8354,15 @@ "type": "null" } ], - "description": "Semantic version; cleared if omitted", + "default": "1.0.0", + "description": "Semantic version, defaults to 1.0.0 on creation", "title": "Version" } }, "required": [ - "source" + "name" ], - "title": "UpdatePluginRequest", + "title": "UploadPluginRequest", "type": "object" }, "ValidationError": { @@ -8242,6 +8550,53 @@ ] } }, + "/claude-code/plugins/upload": { + "post": { + "description": "Create a skill and its uploaded ZIP atomically. Duplicate names return 409.", + "operationId": "upload_plugin_claude_code_plugins_upload_post", + "requestBody": { + "content": { + "multipart/form-data": { + "schema": { + "$ref": "#/components/schemas/Body_upload_plugin_claude_code_plugins_upload_post" + } + } + }, + "required": true + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/RegisterPluginResponse" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Upload Plugin", + "tags": [ + "claude_code_marketplace" + ] + } + }, "/claude-code/plugins/{plugin_name}": { "delete": { "description": "Delete a plugin from the marketplace.\n\nRequires a proxy admin API key.\n\nParameters:\n - plugin_name: The name of the plugin to delete", @@ -8332,7 +8687,7 @@ ] }, "put": { - "description": "Update an existing plugin in the LiteLLM marketplace.\n\nThe plugin is identified by its name in the path, which is the resource\nidentity and cannot be changed here. This is a full replace, not a merge:\nthe manifest is rebuilt from the request body, so any optional field left\nout is reset to its default (e.g. an omitted version is cleared, not kept).\nSend the full desired state.\n\nReturns 404 if no plugin with the given name exists; use\nPOST /claude-code/plugins to create a new plugin.\n\nRequires a proxy admin API key.\n\nParameters:\n - plugin_name: Name of the plugin to update (path parameter)\n - source: Plugin source reference (github, url, git-subdir, or archive format)\n - version: Semantic version (optional)\n - description: Plugin description (optional)\n - author: Author information (optional)\n - homepage: Plugin homepage URL (optional)\n - keywords: Search keywords (optional)\n - category: Plugin category (optional)\n - installation_preference: 'available', 'auto_install', or 'required' (optional)\n\nReturns:\n Update status (action is always \"updated\") and plugin information.\n\nExample:\n ```bash\n curl -X PUT http://localhost:4000/claude-code/plugins/my-plugin \\\n -H \"Authorization: Bearer sk-...\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"source\": {\"source\": \"github\", \"repo\": \"org/my-plugin\"},\n \"version\": \"2.0.0\",\n \"description\": \"My awesome plugin\"\n }'\n ```", + "description": "Update an existing plugin in the LiteLLM marketplace.\n\nThe plugin is identified by its name in the path, which is the resource\nidentity and cannot be changed here. This is a full replace, not a merge:\nthe manifest is rebuilt from the request body, so any optional field left\nout is reset to its default, except version which automatically increments\nthe published patch version when omitted or null.\nSend the full desired state.\n\nReturns 404 if no plugin with the given name exists; use\nPOST /claude-code/plugins to create a new plugin.\n\nRequires a proxy admin API key.\n\nParameters:\n - plugin_name: Name of the plugin to update (path parameter)\n - source: Plugin source reference (github, url, git-subdir, or archive format)\n - version: Semantic version (optional)\n - description: Plugin description (optional)\n - author: Author information (optional)\n - homepage: Plugin homepage URL (optional)\n - keywords: Search keywords (optional)\n - category: Plugin category (optional)\n - installation_preference: 'available', 'auto_install', or 'required' (optional)\n\nReturns:\n Update status (action is always \"updated\") and plugin information.\n\nExample:\n ```bash\n curl -X PUT http://localhost:4000/claude-code/plugins/my-plugin \\\n -H \"Authorization: Bearer sk-...\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"source\": {\"source\": \"github\", \"repo\": \"org/my-plugin\"},\n \"version\": \"2.0.0\",\n \"description\": \"My awesome plugin\"\n }'\n ```", "operationId": "update_plugin_claude_code_plugins__plugin_name__put", "parameters": [ { @@ -8388,6 +8743,59 @@ ] } }, + "/claude-code/plugins/{plugin_name}/archive/{digest}.zip": { + "get": { + "description": "Download an uploaded ZIP under the same visibility policy as its skill.", + "operationId": "download_plugin_archive_claude_code_plugins__plugin_name__archive__digest__zip_get", + "parameters": [ + { + "in": "path", + "name": "plugin_name", + "required": true, + "schema": { + "title": "Plugin Name", + "type": "string" + } + }, + { + "in": "path", + "name": "digest", + "required": true, + "schema": { + "title": "Digest", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/zip": { + "schema": { + "format": "binary", + "type": "string" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "summary": "Download Plugin Archive", + "tags": [ + "claude_code_marketplace" + ] + } + }, "/claude-code/plugins/{plugin_name}/disable": { "post": { "description": "Disable a plugin without deleting it.\n\nRequires a proxy admin API key.\n\nParameters:\n - plugin_name: The name of the plugin to disable", @@ -8434,6 +8842,87 @@ ] } }, + "/claude-code/plugins/{plugin_name}/downloads": { + "get": { + "description": "Admin-only ZIP download totals and authenticated downloader history.\n\nAnonymous downloads contribute only to totals. Counts include repeat requests and client prefetches,\nstarting when tracking is deployed. External sources and installation completion are not observed.", + "operationId": "get_plugin_downloads_claude_code_plugins__plugin_name__downloads_get", + "parameters": [ + { + "in": "path", + "name": "plugin_name", + "required": true, + "schema": { + "title": "Plugin Name", + "type": "string" + } + }, + { + "description": "Maximum number of download events", + "in": "query", + "name": "limit", + "required": false, + "schema": { + "default": 25, + "description": "Maximum number of download events", + "maximum": 100, + "minimum": 1, + "title": "Limit", + "type": "integer" + } + }, + { + "description": "Previous next_cursor", + "in": "query", + "name": "cursor", + "required": false, + "schema": { + "anyOf": [ + { + "pattern": "^[1-9][0-9]{0,18}$", + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Previous next_cursor", + "title": "Cursor" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/PluginDownloadsResponse" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Get Plugin Downloads", + "tags": [ + "claude_code_marketplace" + ] + } + }, "/claude-code/plugins/{plugin_name}/enable": { "post": { "description": "Enable a disabled plugin.\n\nRequires a proxy admin API key.\n\nParameters:\n - plugin_name: The name of the plugin to enable", @@ -10237,8 +10726,15 @@ "type": "string" }, "confidence": { - "title": "Confidence", - "type": "number" + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "title": "Confidence" }, "probabilities": { "additionalProperties": { @@ -10256,7 +10752,6 @@ "required": [ "type", "choice", - "confidence", "probabilities" ], "title": "ChoiceAnswer", @@ -10687,8 +11182,15 @@ "title": "Choice" }, "confidence": { - "title": "Confidence", - "type": "number" + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "title": "Confidence" }, "name": { "anyOf": [ @@ -10718,8 +11220,7 @@ "required": [ "name", "choice", - "probabilities", - "confidence" + "probabilities" ], "title": "OpenAIChoiceAnswer", "type": "object" @@ -10924,8 +11425,15 @@ "OpenAIScoreAnswer": { "properties": { "confidence": { - "title": "Confidence", - "type": "number" + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "title": "Confidence" }, "name": { "anyOf": [ @@ -10959,8 +11467,7 @@ "required": [ "name", "score", - "probabilities", - "confidence" + "probabilities" ], "title": "OpenAIScoreAnswer", "type": "object" @@ -10992,8 +11499,15 @@ "additionalProperties": true, "properties": { "confidence": { - "title": "Confidence", - "type": "number" + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "title": "Confidence" }, "legend": { "additionalProperties": { @@ -11034,7 +11548,6 @@ "required": [ "type", "score", - "confidence", "legend", "probabilities" ], @@ -19953,7 +20466,7 @@ "type": "null" } ], - "description": "Regex pattern applied to the tool's function name", + "description": "Regex pattern applied to the tool's name, or to its type when the tool has no name", "title": "Tool Name" }, "tool_type": { @@ -23542,8 +24055,15 @@ "type": "string" }, "confidence": { - "title": "Confidence", - "type": "number" + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "title": "Confidence" }, "probabilities": { "additionalProperties": { @@ -23561,7 +24081,6 @@ "required": [ "type", "choice", - "confidence", "probabilities" ], "title": "ChoiceAnswer", @@ -29400,8 +29919,15 @@ "additionalProperties": true, "properties": { "confidence": { - "title": "Confidence", - "type": "number" + "anyOf": [ + { + "type": "number" + }, + { + "type": "null" + } + ], + "title": "Confidence" }, "legend": { "additionalProperties": { @@ -29442,7 +29968,6 @@ "required": [ "type", "score", - "confidence", "legend", "probabilities" ], @@ -34331,6 +34856,7 @@ }, "/openai/v1/realtime/calls": { "post": { + "description": "Exchange a WebRTC SDP offer for an answer using the ephemeral token from client_secrets", "operationId": "proxy_realtime_calls_openai_v1_realtime_calls_post", "responses": { "200": { @@ -34350,6 +34876,7 @@ }, "/openai/v1/realtime/client_secrets": { "post": { + "description": "Create a short-lived client token for a Realtime conversation, transcription, or translation session", "operationId": "create_realtime_client_secret_openai_v1_realtime_client_secrets_post", "responses": { "200": { @@ -54536,6 +55063,7 @@ "paths": { "/openai/v1/realtime/calls": { "post": { + "description": "Exchange a WebRTC SDP offer for an answer using the ephemeral token from client_secrets", "operationId": "proxy_realtime_calls_openai_v1_realtime_calls_post_2", "responses": { "200": { @@ -54555,6 +55083,7 @@ }, "/openai/v1/realtime/client_secrets": { "post": { + "description": "Create a short-lived client token for a Realtime conversation, transcription, or translation session", "operationId": "create_realtime_client_secret_openai_v1_realtime_client_secrets_post_2", "responses": { "200": { @@ -54608,6 +55137,7 @@ }, "/realtime/calls": { "post": { + "description": "Exchange a WebRTC SDP offer for an answer using the ephemeral token from client_secrets", "operationId": "proxy_realtime_calls_realtime_calls_post", "responses": { "200": { @@ -54627,6 +55157,7 @@ }, "/realtime/client_secrets": { "post": { + "description": "Create a short-lived client token for a Realtime conversation, transcription, or translation session", "operationId": "create_realtime_client_secret_realtime_client_secrets_post", "responses": { "200": { @@ -54678,8 +55209,489 @@ ] } }, + "/realtime/translations/calls": { + "post": { + "description": "Exchange a WebRTC SDP offer for an answer using the ephemeral token from client_secrets", + "operationId": "proxy_realtime_calls_realtime_translations_calls_post", + "requestBody": { + "content": { + "application/sdp": { + "schema": { + "type": "string" + } + } + }, + "required": true + }, + "responses": { + "201": { + "content": { + "text/plain": { + "schema": { + "type": "string" + } + } + }, + "description": "WebRTC SDP answer" + } + }, + "summary": "Proxy Realtime Calls", + "tags": [ + "realtime" + ] + } + }, + "/realtime/translations/client_secrets": { + "post": { + "description": "Create a short-lived client token for a Realtime conversation, transcription, or translation session", + "operationId": "create_realtime_client_secret_realtime_translations_client_secrets_post", + "requestBody": { + "content": { + "application/json": { + "example": { + "model": "gpt-realtime-translate", + "session": { + "model": "gpt-realtime-translate", + "type": "translation" + } + }, + "schema": { + "description": "Request body for POST /v1/realtime/client_secrets.\n\nLiteLLM also accepts a top-level `model` field for routing when\nsession.model is absent (LiteLLM extension, not forwarded to OpenAI).", + "properties": { + "expires_after": { + "anyOf": [ + { + "description": "Expiration config for a client secret.", + "properties": { + "anchor": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": "created_at", + "title": "Anchor" + }, + "seconds": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "title": "Seconds" + } + }, + "title": "RealtimeExpiresAfter", + "type": "object" + }, + { + "type": "null" + } + ] + }, + "model": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Model" + }, + "session": { + "anyOf": [ + { + "additionalProperties": true, + "description": "Session configuration nested inside the client_secrets request body.\n\nMirrors OpenAI's RealtimeSessionCreateRequest (type=realtime) and\nRealtimeTranscriptionSessionCreateRequest (type=transcription).\nExtra/unknown fields are passed through unchanged.", + "properties": { + "audio": { + "anyOf": [ + { + "additionalProperties": true, + "properties": { + "input": { + "anyOf": [ + { + "additionalProperties": true, + "properties": { + "format": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Format" + }, + "noise_reduction": { + "anyOf": [ + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Noise Reduction" + }, + "transcription": { + "anyOf": [ + { + "additionalProperties": true, + "properties": { + "delay": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Delay" + }, + "keywords": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Keywords" + }, + "language": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Language" + }, + "languages": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Languages" + }, + "model": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Model" + }, + "prompt": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Prompt" + } + }, + "title": "RealtimeAudioTranscriptionConfig", + "type": "object" + }, + { + "type": "null" + } + ] + }, + "turn_detection": { + "anyOf": [ + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Turn Detection" + } + }, + "title": "RealtimeAudioInputConfig", + "type": "object" + }, + { + "type": "null" + } + ] + }, + "output": { + "anyOf": [ + { + "additionalProperties": true, + "properties": { + "format": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Format" + }, + "language": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Language" + }, + "voice": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Voice" + } + }, + "title": "RealtimeAudioOutputConfig", + "type": "object" + }, + { + "type": "null" + } + ] + } + }, + "title": "RealtimeSessionAudioConfig", + "type": "object" + }, + { + "type": "null" + } + ] + }, + "include": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Include" + }, + "instructions": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Instructions" + }, + "max_output_tokens": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Max Output Tokens" + }, + "model": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Model" + }, + "output_modalities": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Output Modalities" + }, + "prompt": { + "anyOf": [ + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Prompt" + }, + "tool_choice": { + "anyOf": [ + {}, + { + "type": "null" + } + ], + "title": "Tool Choice" + }, + "tools": { + "anyOf": [ + { + "items": { + "additionalProperties": true, + "type": "object" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Tools" + }, + "tracing": { + "anyOf": [ + {}, + { + "type": "null" + } + ], + "title": "Tracing" + }, + "truncation": { + "anyOf": [ + {}, + { + "type": "null" + } + ], + "title": "Truncation" + }, + "type": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Type" + } + }, + "title": "RealtimeSessionConfig", + "type": "object" + }, + { + "type": "null" + } + ] + } + }, + "title": "RealtimeClientSecretRequest", + "type": "object" + } + } + }, + "required": true + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/RealtimeClientSecretResponse" + } + } + }, + "description": "Successful Response" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Create Realtime Client Secret", + "tags": [ + "realtime" + ] + } + }, "/v1/realtime/calls": { "post": { + "description": "Exchange a WebRTC SDP offer for an answer using the ephemeral token from client_secrets", "operationId": "proxy_realtime_calls_v1_realtime_calls_post", "responses": { "200": { @@ -54699,6 +55711,7 @@ }, "/v1/realtime/client_secrets": { "post": { + "description": "Create a short-lived client token for a Realtime conversation, transcription, or translation session", "operationId": "create_realtime_client_secret_v1_realtime_client_secrets_post", "responses": { "200": { @@ -54749,6 +55762,486 @@ "realtime" ] } + }, + "/v1/realtime/translations/calls": { + "post": { + "description": "Exchange a WebRTC SDP offer for an answer using the ephemeral token from client_secrets", + "operationId": "proxy_realtime_calls_v1_realtime_translations_calls_post", + "requestBody": { + "content": { + "application/sdp": { + "schema": { + "type": "string" + } + } + }, + "required": true + }, + "responses": { + "201": { + "content": { + "text/plain": { + "schema": { + "type": "string" + } + } + }, + "description": "WebRTC SDP answer" + } + }, + "summary": "Proxy Realtime Calls", + "tags": [ + "realtime" + ] + } + }, + "/v1/realtime/translations/client_secrets": { + "post": { + "description": "Create a short-lived client token for a Realtime conversation, transcription, or translation session", + "operationId": "create_realtime_client_secret_v1_realtime_translations_client_secrets_post", + "requestBody": { + "content": { + "application/json": { + "example": { + "model": "gpt-realtime-translate", + "session": { + "model": "gpt-realtime-translate", + "type": "translation" + } + }, + "schema": { + "description": "Request body for POST /v1/realtime/client_secrets.\n\nLiteLLM also accepts a top-level `model` field for routing when\nsession.model is absent (LiteLLM extension, not forwarded to OpenAI).", + "properties": { + "expires_after": { + "anyOf": [ + { + "description": "Expiration config for a client secret.", + "properties": { + "anchor": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "default": "created_at", + "title": "Anchor" + }, + "seconds": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "title": "Seconds" + } + }, + "title": "RealtimeExpiresAfter", + "type": "object" + }, + { + "type": "null" + } + ] + }, + "model": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Model" + }, + "session": { + "anyOf": [ + { + "additionalProperties": true, + "description": "Session configuration nested inside the client_secrets request body.\n\nMirrors OpenAI's RealtimeSessionCreateRequest (type=realtime) and\nRealtimeTranscriptionSessionCreateRequest (type=transcription).\nExtra/unknown fields are passed through unchanged.", + "properties": { + "audio": { + "anyOf": [ + { + "additionalProperties": true, + "properties": { + "input": { + "anyOf": [ + { + "additionalProperties": true, + "properties": { + "format": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Format" + }, + "noise_reduction": { + "anyOf": [ + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Noise Reduction" + }, + "transcription": { + "anyOf": [ + { + "additionalProperties": true, + "properties": { + "delay": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Delay" + }, + "keywords": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Keywords" + }, + "language": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Language" + }, + "languages": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Languages" + }, + "model": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Model" + }, + "prompt": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Prompt" + } + }, + "title": "RealtimeAudioTranscriptionConfig", + "type": "object" + }, + { + "type": "null" + } + ] + }, + "turn_detection": { + "anyOf": [ + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Turn Detection" + } + }, + "title": "RealtimeAudioInputConfig", + "type": "object" + }, + { + "type": "null" + } + ] + }, + "output": { + "anyOf": [ + { + "additionalProperties": true, + "properties": { + "format": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Format" + }, + "language": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Language" + }, + "voice": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Voice" + } + }, + "title": "RealtimeAudioOutputConfig", + "type": "object" + }, + { + "type": "null" + } + ] + } + }, + "title": "RealtimeSessionAudioConfig", + "type": "object" + }, + { + "type": "null" + } + ] + }, + "include": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Include" + }, + "instructions": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Instructions" + }, + "max_output_tokens": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Max Output Tokens" + }, + "model": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Model" + }, + "output_modalities": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Output Modalities" + }, + "prompt": { + "anyOf": [ + { + "additionalProperties": true, + "type": "object" + }, + { + "type": "null" + } + ], + "title": "Prompt" + }, + "tool_choice": { + "anyOf": [ + {}, + { + "type": "null" + } + ], + "title": "Tool Choice" + }, + "tools": { + "anyOf": [ + { + "items": { + "additionalProperties": true, + "type": "object" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Tools" + }, + "tracing": { + "anyOf": [ + {}, + { + "type": "null" + } + ], + "title": "Tracing" + }, + "truncation": { + "anyOf": [ + {}, + { + "type": "null" + } + ], + "title": "Truncation" + }, + "type": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Type" + } + }, + "title": "RealtimeSessionConfig", + "type": "object" + }, + { + "type": "null" + } + ] + } + }, + "title": "RealtimeClientSecretRequest", + "type": "object" + } + } + }, + "required": true + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/RealtimeClientSecretResponse" + } + } + }, + "description": "Successful Response" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Create Realtime Client Secret", + "tags": [ + "realtime" + ] + } } } }, @@ -57589,6 +59082,2622 @@ } } }, + "skill_hub": { + "components": { + "schemas": { + "Body_replace_skill_archive_skill_hub_skills__name__upload_put": { + "properties": { + "expected_updated_at": { + "anyOf": [ + { + "format": "date-time", + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Expected Updated At" + }, + "file": { + "contentMediaType": "application/octet-stream", + "description": "Replacement Agent Skills ZIP with the same declared skill name", + "title": "File", + "type": "string" + }, + "version": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Version" + } + }, + "required": [ + "file" + ], + "title": "Body_replace_skill_archive_skill_hub_skills__name__upload_put", + "type": "object" + }, + "Body_upload_skill_skill_hub_skills_upload_post": { + "properties": { + "file": { + "contentMediaType": "application/octet-stream", + "description": "Agent Skills ZIP with SKILL.md and optional supporting files", + "title": "File", + "type": "string" + }, + "version": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Version" + } + }, + "required": [ + "file" + ], + "title": "Body_upload_skill_skill_hub_skills_upload_post", + "type": "object" + }, + "HTTPValidationError": { + "properties": { + "detail": { + "items": { + "$ref": "#/components/schemas/ValidationError" + }, + "title": "Detail", + "type": "array" + } + }, + "title": "HTTPValidationError", + "type": "object" + }, + "ImportSkillRequest": { + "properties": { + "path": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Repository-relative skill directory", + "title": "Path" + }, + "ref": { + "default": "HEAD", + "description": "Git commit, tag or branch to import", + "title": "Ref", + "type": "string" + }, + "skill": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Skill name to select when a repository contains several skills", + "title": "Skill" + }, + "url": { + "description": "Public skills.sh skill URL or GitHub repository URL", + "title": "Url", + "type": "string" + }, + "version": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Semantic version, or omit/null to start at 1.0.0", + "title": "Version" + } + }, + "required": [ + "url" + ], + "title": "ImportSkillRequest", + "type": "object" + }, + "PluginDownloadEvent": { + "properties": { + "authenticated": { + "title": "Authenticated", + "type": "boolean" + }, + "digest": { + "title": "Digest", + "type": "string" + }, + "downloaded_at": { + "format": "date-time", + "title": "Downloaded At", + "type": "string" + }, + "id": { + "title": "Id", + "type": "string" + }, + "key_alias": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Key Alias" + }, + "team_alias": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Team Alias" + }, + "team_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Team Id" + }, + "user_email": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "User Email" + }, + "user_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "User Id" + }, + "version": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Version" + } + }, + "required": [ + "id", + "downloaded_at", + "version", + "digest", + "authenticated", + "user_id", + "user_email", + "key_alias", + "team_id", + "team_alias" + ], + "title": "PluginDownloadEvent", + "type": "object" + }, + "PluginDownloadsResponse": { + "properties": { + "anonymous_downloads": { + "title": "Anonymous Downloads", + "type": "integer" + }, + "downloads": { + "items": { + "$ref": "#/components/schemas/PluginDownloadEvent" + }, + "title": "Downloads", + "type": "array" + }, + "next_cursor": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Next Cursor" + }, + "total_downloads": { + "title": "Total Downloads", + "type": "integer" + } + }, + "required": [ + "total_downloads", + "anonymous_downloads", + "downloads", + "next_cursor" + ], + "title": "PluginDownloadsResponse", + "type": "object" + }, + "SkillHubAgentSkill": { + "properties": { + "description": { + "title": "Description", + "type": "string" + }, + "digest": { + "title": "Digest", + "type": "string" + }, + "name": { + "title": "Name", + "type": "string" + }, + "origin": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Origin" + } + }, + "required": [ + "name", + "description", + "digest", + "origin" + ], + "title": "SkillHubAgentSkill", + "type": "object" + }, + "SkillHubList": { + "properties": { + "count": { + "title": "Count", + "type": "integer" + }, + "next_offset": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "title": "Next Offset" + }, + "skills": { + "items": { + "$ref": "#/components/schemas/SkillHubSkill" + }, + "title": "Skills", + "type": "array" + } + }, + "required": [ + "skills", + "count", + "next_offset" + ], + "title": "SkillHubList", + "type": "object" + }, + "SkillHubMetadata": { + "additionalProperties": false, + "properties": { + "description": { + "anyOf": [ + { + "maxLength": 1024, + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Description" + }, + "domain": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Domain" + }, + "expected_updated_at": { + "anyOf": [ + { + "format": "date-time", + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Published updated_at read by the editor. A stale value returns 409", + "title": "Expected Updated At" + }, + "keywords": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Keywords" + }, + "namespace": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Namespace" + }, + "version": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Explicit higher SemVer, or omit/null for an automatic patch bump", + "title": "Version" + } + }, + "title": "SkillHubMetadata", + "type": "object" + }, + "SkillHubPendingSkill": { + "properties": { + "action": { + "const": "submitted", + "default": "submitted", + "title": "Action", + "type": "string" + }, + "proposal": { + "$ref": "#/components/schemas/SkillHubProposal" + }, + "status": { + "const": "pending_review", + "default": "pending_review", + "title": "Status", + "type": "string" + }, + "submission_id": { + "title": "Submission Id", + "type": "string" + } + }, + "required": [ + "submission_id", + "proposal" + ], + "title": "SkillHubPendingSkill", + "type": "object" + }, + "SkillHubProposal": { + "properties": { + "agent_skill": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillHubAgentSkill" + }, + { + "type": "null" + } + ] + }, + "description": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Description" + }, + "domain": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Domain" + }, + "keywords": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Keywords" + }, + "name": { + "title": "Name", + "type": "string" + }, + "namespace": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Namespace" + }, + "source": { + "additionalProperties": { + "type": "string" + }, + "title": "Source", + "type": "object" + }, + "version": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Version" + } + }, + "required": [ + "name", + "description", + "version", + "source" + ], + "title": "SkillHubProposal", + "type": "object" + }, + "SkillHubPublication": { + "additionalProperties": false, + "properties": {}, + "title": "SkillHubPublication", + "type": "object" + }, + "SkillHubRejection": { + "additionalProperties": false, + "properties": { + "reason": { + "anyOf": [ + { + "maxLength": 2000, + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Reason" + } + }, + "title": "SkillHubRejection", + "type": "object" + }, + "SkillHubReviewResponse": { + "properties": { + "action": { + "enum": [ + "approved", + "rejected" + ], + "title": "Action", + "type": "string" + }, + "skill": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillHubSkill" + }, + { + "type": "null" + } + ] + }, + "status": { + "const": "success", + "default": "success", + "title": "Status", + "type": "string" + }, + "submission": { + "$ref": "#/components/schemas/SkillHubSubmission" + } + }, + "required": [ + "action", + "submission", + "skill" + ], + "title": "SkillHubReviewResponse", + "type": "object" + }, + "SkillHubSkill": { + "properties": { + "content_url": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Content Url" + }, + "description": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Description" + }, + "domain": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Domain" + }, + "download_count": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "description": "Gateway ZIP downloads, included in proxy-admin catalog listings", + "title": "Download Count" + }, + "download_url": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Download Url" + }, + "id": { + "title": "Id", + "type": "string" + }, + "keywords": { + "anyOf": [ + { + "items": { + "type": "string" + }, + "type": "array" + }, + { + "type": "null" + } + ], + "title": "Keywords" + }, + "name": { + "title": "Name", + "type": "string" + }, + "namespace": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Namespace" + }, + "source": { + "additionalProperties": { + "type": "string" + }, + "title": "Source", + "type": "object" + }, + "updated_at": { + "anyOf": [ + { + "format": "date-time", + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Updated At" + }, + "version": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Version" + }, + "visibility": { + "enum": [ + "public", + "private" + ], + "title": "Visibility", + "type": "string" + } + }, + "required": [ + "id", + "name", + "visibility", + "source" + ], + "title": "SkillHubSkill", + "type": "object" + }, + "SkillHubSubmission": { + "properties": { + "base_skill_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Base Skill Id" + }, + "base_updated_at": { + "anyOf": [ + { + "format": "date-time", + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Base Updated At" + }, + "created_at": { + "format": "date-time", + "title": "Created At", + "type": "string" + }, + "has_archive": { + "title": "Has Archive", + "type": "boolean" + }, + "id": { + "title": "Id", + "type": "string" + }, + "operation": { + "enum": [ + "create", + "update" + ], + "title": "Operation", + "type": "string" + }, + "proposal": { + "$ref": "#/components/schemas/SkillHubProposal" + }, + "rejection_reason": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Rejection Reason" + }, + "reviewed_at": { + "anyOf": [ + { + "format": "date-time", + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Reviewed At" + }, + "reviewed_by": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Reviewed By" + }, + "skill_name": { + "title": "Skill Name", + "type": "string" + }, + "status": { + "enum": [ + "pending_review", + "approved", + "rejected" + ], + "title": "Status", + "type": "string" + }, + "submitted_by": { + "title": "Submitted By", + "type": "string" + } + }, + "required": [ + "id", + "skill_name", + "operation", + "status", + "proposal", + "has_archive", + "submitted_by", + "created_at", + "base_skill_id", + "base_updated_at", + "reviewed_by", + "reviewed_at", + "rejection_reason" + ], + "title": "SkillHubSubmission", + "type": "object" + }, + "SkillHubSubmissionDetail": { + "properties": { + "current_skill": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillHubSkill" + }, + { + "type": "null" + } + ] + }, + "submission": { + "$ref": "#/components/schemas/SkillHubSubmission" + } + }, + "required": [ + "submission", + "current_skill" + ], + "title": "SkillHubSubmissionDetail", + "type": "object" + }, + "SkillHubSubmissionList": { + "properties": { + "count": { + "title": "Count", + "type": "integer" + }, + "has_more": { + "title": "Has More", + "type": "boolean" + }, + "submissions": { + "items": { + "$ref": "#/components/schemas/SkillHubSubmission" + }, + "title": "Submissions", + "type": "array" + } + }, + "required": [ + "submissions", + "count", + "has_more" + ], + "title": "SkillHubSubmissionList", + "type": "object" + }, + "SkillHubVersion": { + "properties": { + "content_kind": { + "enum": [ + "stored_archive", + "source_reference" + ], + "title": "Content Kind", + "type": "string" + }, + "description": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Description" + }, + "download_url": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Download Url" + }, + "id": { + "title": "Id", + "type": "string" + }, + "manifest": { + "additionalProperties": true, + "title": "Manifest", + "type": "object" + }, + "published_at": { + "anyOf": [ + { + "format": "date-time", + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Published At" + }, + "published_by": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Published By" + }, + "version": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Version" + } + }, + "required": [ + "id", + "version", + "description", + "manifest", + "published_at", + "published_by", + "content_kind", + "download_url" + ], + "title": "SkillHubVersion", + "type": "object" + }, + "SkillHubVersions": { + "properties": { + "next_offset": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "null" + } + ], + "title": "Next Offset" + }, + "versions": { + "items": { + "$ref": "#/components/schemas/SkillHubVersion" + }, + "title": "Versions", + "type": "array" + } + }, + "required": [ + "versions", + "next_offset" + ], + "title": "SkillHubVersions", + "type": "object" + }, + "SkillScan": { + "properties": { + "archive_sha256": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Archive Sha256" + }, + "completed_at": { + "anyOf": [ + { + "format": "date-time", + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Completed At" + }, + "error": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Error" + }, + "expires_at": { + "format": "date-time", + "title": "Expires At", + "type": "string" + }, + "id": { + "title": "Id", + "type": "string" + }, + "report": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillScanReport" + }, + { + "type": "null" + } + ] + }, + "requested_by": { + "title": "Requested By", + "type": "string" + }, + "started_at": { + "format": "date-time", + "title": "Started At", + "type": "string" + }, + "status": { + "enum": [ + "running", + "completed", + "failed" + ], + "title": "Status", + "type": "string" + } + }, + "required": [ + "id", + "status", + "requested_by", + "started_at", + "expires_at" + ], + "title": "SkillScan", + "type": "object" + }, + "SkillScanFinding": { + "properties": { + "explanation": { + "anyOf": [ + { + "maxLength": 8000, + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Explanation" + }, + "file": { + "maxLength": 2048, + "title": "File", + "type": "string" + }, + "message": { + "maxLength": 8000, + "title": "Message", + "type": "string" + }, + "remediation": { + "anyOf": [ + { + "maxLength": 8000, + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Remediation" + }, + "rule_id": { + "maxLength": 200, + "title": "Rule Id", + "type": "string" + }, + "severity": { + "enum": [ + "LOW", + "MEDIUM", + "HIGH", + "CRITICAL" + ], + "title": "Severity", + "type": "string" + }, + "start_line": { + "anyOf": [ + { + "minimum": 1.0, + "type": "integer" + }, + { + "type": "null" + } + ], + "title": "Start Line" + } + }, + "required": [ + "rule_id", + "severity", + "message", + "file" + ], + "title": "SkillScanFinding", + "type": "object" + }, + "SkillScanReport": { + "properties": { + "complete": { + "title": "Complete", + "type": "boolean" + }, + "findings": { + "items": { + "$ref": "#/components/schemas/SkillScanFinding" + }, + "maxItems": 500, + "title": "Findings", + "type": "array" + }, + "limitations": { + "default": [], + "items": { + "maxLength": 2000, + "type": "string" + }, + "maxItems": 100, + "title": "Limitations", + "type": "array" + }, + "risk_score": { + "maximum": 100.0, + "minimum": 0.0, + "title": "Risk Score", + "type": "integer" + }, + "scan_mode": { + "enum": [ + "static-only", + "static+llm" + ], + "title": "Scan Mode", + "type": "string" + }, + "scanner_version": { + "maxLength": 100, + "minLength": 1, + "title": "Scanner Version", + "type": "string" + } + }, + "required": [ + "scanner_version", + "complete", + "scan_mode", + "risk_score", + "findings" + ], + "title": "SkillScanReport", + "type": "object" + }, + "SkillScanRequest": { + "additionalProperties": false, + "properties": {}, + "title": "SkillScanRequest", + "type": "object" + }, + "SkillScanResponse": { + "properties": { + "configured": { + "title": "Configured", + "type": "boolean" + }, + "scan": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillScan" + }, + { + "type": "null" + } + ] + } + }, + "required": [ + "configured", + "scan" + ], + "title": "SkillScanResponse", + "type": "object" + }, + "ValidationError": { + "properties": { + "ctx": { + "title": "Context", + "type": "object" + }, + "input": { + "title": "Input" + }, + "loc": { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "integer" + } + ] + }, + "title": "Location", + "type": "array" + }, + "msg": { + "title": "Message", + "type": "string" + }, + "type": { + "title": "Error Type", + "type": "string" + } + }, + "required": [ + "loc", + "msg", + "type" + ], + "title": "ValidationError", + "type": "object" + } + } + }, + "paths": { + "/skill-hub/skills": { + "get": { + "description": "Browse the caller's public and granted private skills.", + "operationId": "list_skills_skill_hub_skills_get", + "parameters": [ + { + "in": "query", + "name": "query", + "required": false, + "schema": { + "default": "", + "title": "Query", + "type": "string" + } + }, + { + "in": "query", + "name": "offset", + "required": false, + "schema": { + "default": 0, + "minimum": 0, + "title": "Offset", + "type": "integer" + } + }, + { + "in": "query", + "name": "limit", + "required": false, + "schema": { + "default": 50, + "maximum": 100, + "minimum": 1, + "title": "Limit", + "type": "integer" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubList" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "List Skills", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/import": { + "post": { + "description": "Import a public skills.sh or GitHub skill as a portable snapshot.", + "operationId": "import_skill_skill_hub_skills_import_post", + "requestBody": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/ImportSkillRequest" + } + } + }, + "required": true + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillHubSkill" + }, + { + "$ref": "#/components/schemas/SkillHubPendingSkill" + } + ], + "title": "Response Import Skill Skill Hub Skills Import Post" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Import Skill", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/upload": { + "post": { + "description": "Publish a portable skill while retaining Claude marketplace compatibility.", + "operationId": "upload_skill_skill_hub_skills_upload_post", + "requestBody": { + "content": { + "multipart/form-data": { + "schema": { + "$ref": "#/components/schemas/Body_upload_skill_skill_hub_skills_upload_post" + } + } + }, + "required": true + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillHubSkill" + }, + { + "$ref": "#/components/schemas/SkillHubPendingSkill" + } + ], + "title": "Response Upload Skill Skill Hub Skills Upload Post" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Upload Skill", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/{name}": { + "delete": { + "description": "Delete a skill and its managed archive.", + "operationId": "remove_skill_skill_hub_skills__name__delete", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + } + ], + "responses": { + "204": { + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Remove Skill", + "tags": [ + "skill_hub" + ] + }, + "get": { + "description": "Read one visible skill and its portable download URL.", + "operationId": "get_skill_skill_hub_skills__name__get", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubSkill" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Get Skill", + "tags": [ + "skill_hub" + ] + }, + "put": { + "description": "Replace registry metadata, preserving files. Members submit an immutable proposal for admin review.", + "operationId": "replace_skill_metadata_skill_hub_skills__name__put", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + } + ], + "requestBody": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubMetadata" + } + } + }, + "required": true + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillHubSkill" + }, + { + "$ref": "#/components/schemas/SkillHubPendingSkill" + } + ], + "title": "Response Replace Skill Metadata Skill Hub Skills Name Put" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Replace Skill Metadata", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/{name}/archive": { + "get": { + "description": "Download the complete portable skill, with SKILL.md at the ZIP root.", + "operationId": "download_skill_skill_hub_skills__name__archive_get", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + }, + { + "in": "query", + "name": "digest", + "required": false, + "schema": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Digest" + } + } + ], + "responses": { + "200": { + "content": { + "application/zip": { + "schema": { + "format": "binary", + "type": "string" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "summary": "Download Skill", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/{name}/content": { + "get": { + "description": "Read the original SKILL.md without downloading supporting files.", + "operationId": "skill_content_skill_hub_skills__name__content_get", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "text/markdown": {} + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "summary": "Skill Content", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/{name}/publish": { + "post": { + "description": "Make a skill public using the existing Hub publication policy.", + "operationId": "publish_skill_skill_hub_skills__name__publish_post", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + } + ], + "requestBody": { + "content": { + "application/json": { + "schema": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillHubPublication" + }, + { + "type": "null" + } + ], + "title": " Body" + } + } + } + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubSkill" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Publish Skill", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/{name}/unpublish": { + "post": { + "description": "Remove a skill from public discovery while retaining explicit grants.", + "operationId": "unpublish_skill_skill_hub_skills__name__unpublish_post", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + } + ], + "requestBody": { + "content": { + "application/json": { + "schema": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillHubPublication" + }, + { + "type": "null" + } + ], + "title": " Body" + } + } + } + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubSkill" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Unpublish Skill", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/{name}/upload": { + "put": { + "description": "Replace skill files, retaining registry fields. Members propose an update against the original editor timestamp.", + "operationId": "replace_skill_archive_skill_hub_skills__name__upload_put", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + } + ], + "requestBody": { + "content": { + "multipart/form-data": { + "schema": { + "$ref": "#/components/schemas/Body_replace_skill_archive_skill_hub_skills__name__upload_put" + } + } + }, + "required": true + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillHubSkill" + }, + { + "$ref": "#/components/schemas/SkillHubPendingSkill" + } + ], + "title": "Response Replace Skill Archive Skill Hub Skills Name Upload Put" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Replace Skill Archive", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/{name}/versions": { + "get": { + "description": "Read published metadata history. External references are not retained artifacts.", + "operationId": "list_skill_versions_skill_hub_skills__name__versions_get", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + }, + { + "in": "query", + "name": "limit", + "required": false, + "schema": { + "default": 20, + "maximum": 100, + "minimum": 1, + "title": "Limit", + "type": "integer" + } + }, + { + "in": "query", + "name": "offset", + "required": false, + "schema": { + "default": 0, + "minimum": 0, + "title": "Offset", + "type": "integer" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubVersions" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "List Skill Versions", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/{name}/versions/{version_id}": { + "get": { + "description": "Read a retained publication under the current skill's visibility policy.", + "operationId": "get_skill_version_skill_hub_skills__name__versions__version_id__get", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + }, + { + "in": "path", + "name": "version_id", + "required": true, + "schema": { + "title": "Version Id", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubVersion" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Get Skill Version", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/{name}/versions/{version_id}/archive": { + "get": { + "description": "Download a retained publication as a portable ZIP with SKILL.md at its root.", + "operationId": "download_skill_version_skill_hub_skills__name__versions__version_id__archive_get", + "parameters": [ + { + "in": "path", + "name": "name", + "required": true, + "schema": { + "title": "Name", + "type": "string" + } + }, + { + "in": "path", + "name": "version_id", + "required": true, + "schema": { + "title": "Version Id", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/zip": { + "schema": { + "format": "binary", + "type": "string" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Download Skill Version", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/skills/{plugin_name}/downloads": { + "get": { + "description": "Admin-only ZIP download totals and authenticated downloader history.\n\nAnonymous downloads contribute only to totals. Counts include repeat requests and client prefetches,\nstarting when tracking is deployed. External sources and installation completion are not observed.", + "operationId": "get_plugin_downloads_skill_hub_skills__plugin_name__downloads_get", + "parameters": [ + { + "in": "path", + "name": "plugin_name", + "required": true, + "schema": { + "title": "Plugin Name", + "type": "string" + } + }, + { + "description": "Maximum number of download events", + "in": "query", + "name": "limit", + "required": false, + "schema": { + "default": 25, + "description": "Maximum number of download events", + "maximum": 100, + "minimum": 1, + "title": "Limit", + "type": "integer" + } + }, + { + "description": "Previous next_cursor", + "in": "query", + "name": "cursor", + "required": false, + "schema": { + "anyOf": [ + { + "pattern": "^[1-9][0-9]{0,18}$", + "type": "string" + }, + { + "type": "null" + } + ], + "description": "Previous next_cursor", + "title": "Cursor" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/PluginDownloadsResponse" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Get Plugin Downloads", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/submissions": { + "get": { + "description": "Read a page of owned proposals. Proxy admins and admin viewers can read every owner's proposals.", + "operationId": "list_submissions_skill_hub_submissions_get", + "parameters": [ + { + "in": "query", + "name": "status", + "required": false, + "schema": { + "anyOf": [ + { + "enum": [ + "pending_review", + "approved", + "rejected" + ], + "type": "string" + }, + { + "type": "null" + } + ], + "title": "Status" + } + }, + { + "in": "query", + "name": "limit", + "required": false, + "schema": { + "default": 20, + "maximum": 100, + "minimum": 1, + "title": "Limit", + "type": "integer" + } + }, + { + "in": "query", + "name": "offset", + "required": false, + "schema": { + "default": 0, + "minimum": 0, + "title": "Offset", + "type": "integer" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubSubmissionList" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "List Submissions", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/submissions/{submission_id}": { + "get": { + "description": "Read an immutable proposal and its currently visible published skill.", + "operationId": "get_submission_skill_hub_submissions__submission_id__get", + "parameters": [ + { + "in": "path", + "name": "submission_id", + "required": true, + "schema": { + "title": "Submission Id", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubSubmissionDetail" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Get Submission", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/submissions/{submission_id}/approve": { + "put": { + "description": "Publish a pending proposal and record its approval atomically. Only proxy admins may review.", + "operationId": "approve_submission_skill_hub_submissions__submission_id__approve_put", + "parameters": [ + { + "in": "path", + "name": "submission_id", + "required": true, + "schema": { + "title": "Submission Id", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubReviewResponse" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Approve Submission", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/submissions/{submission_id}/archive": { + "get": { + "description": "Download an owned proposal as a private portable ZIP. Legacy nonportable archives return 404.", + "operationId": "download_submission_skill_hub_submissions__submission_id__archive_get", + "parameters": [ + { + "in": "path", + "name": "submission_id", + "required": true, + "schema": { + "title": "Submission Id", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/zip": { + "schema": { + "format": "binary", + "type": "string" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Download Submission", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/submissions/{submission_id}/reject": { + "put": { + "description": "Reject a pending proposal without changing the published skill. Only proxy admins may review.", + "operationId": "reject_submission_skill_hub_submissions__submission_id__reject_put", + "parameters": [ + { + "in": "path", + "name": "submission_id", + "required": true, + "schema": { + "title": "Submission Id", + "type": "string" + } + } + ], + "requestBody": { + "content": { + "application/json": { + "schema": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillHubRejection" + }, + { + "type": "null" + } + ], + "title": "Body" + } + } + } + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillHubReviewResponse" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Reject Submission", + "tags": [ + "skill_hub" + ] + } + }, + "/skill-hub/submissions/{submission_id}/scan": { + "get": { + "description": "Read the latest manual security scan. Only proxy admins may read reports.", + "operationId": "get_skill_scan_skill_hub_submissions__submission_id__scan_get", + "parameters": [ + { + "in": "path", + "name": "submission_id", + "required": true, + "schema": { + "title": "Submission Id", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillScanResponse" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Get Skill Scan", + "tags": [ + "skill_hub" + ] + }, + "post": { + "description": "Start an optional scan of a pending submission. Scans never change approval decisions.", + "operationId": "start_skill_scan_skill_hub_submissions__submission_id__scan_post", + "parameters": [ + { + "in": "path", + "name": "submission_id", + "required": true, + "schema": { + "title": "Submission Id", + "type": "string" + } + } + ], + "requestBody": { + "content": { + "application/json": { + "schema": { + "anyOf": [ + { + "$ref": "#/components/schemas/SkillScanRequest" + }, + { + "type": "null" + } + ], + "title": " Request" + } + } + } + }, + "responses": { + "200": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/SkillScanResponse" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "security": [ + { + "APIKeyHeader": [] + } + ], + "summary": "Start Skill Scan", + "tags": [ + "skill_hub" + ] + } + } + } + }, "tools": { "components": { "schemas": { diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index c9960d794c6..5b5c0c5f8d3 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -38,7 +38,6 @@ from litellm.litellm_core_utils.initialize_dynamic_callback_params import ( validate_no_callback_env_reference, ) from litellm.proxy.mcp_server.stdio_gate import MCP_STDIO_DISABLED_MESSAGE, is_mcp_stdio_enabled -from litellm.proxy.spend_tracking.usage_meter import UsageCaptureSettings from litellm.types.agents import ( AgentCaller as AgentCaller, # noqa: PLC0414 # public re-export ) @@ -89,6 +88,7 @@ from litellm.types.proxy.carried_budget_state import ( ) from litellm.types.proxy.control_plane_endpoints import WorkerRegistryEntry from litellm.types.proxy.request_tag_mappings import RequestTagMapping +from litellm.types.proxy.skill_scanning import SkillScannerConfig from litellm.types.proxy.spend_capture_rate import SpendCaptureRateCheckSettings from litellm.types.router import AllowedModelRegion, RouterErrors, UpdateRouterConfig from litellm.types.router_weights import validate_router_settings_dict @@ -332,6 +332,8 @@ class LiteLLMRoutes(enum.Enum): "/realtime?{model}", "/v1/realtime?{model}", "/openai/v1/realtime?{model}", + "/realtime/translations", + "/v1/realtime/translations", # realtime (GA WebRTC HTTP routes) "/realtime/client_secrets", "/v1/realtime/client_secrets", @@ -342,6 +344,10 @@ class LiteLLMRoutes(enum.Enum): "/realtime/transcription_sessions", "/v1/realtime/transcription_sessions", "/openai/v1/realtime/transcription_sessions", + "/realtime/translations/client_secrets", + "/v1/realtime/translations/client_secrets", + "/realtime/translations/calls", + "/v1/realtime/translations/calls", # responses API "/responses", "/v1/responses", @@ -444,6 +450,28 @@ class LiteLLMRoutes(enum.Enum): "/v1/traces/{trace_id}/spans/{span_id}/error", ) + skill_hub_routes = ( + "/skill-hub/skills", + "/skill-hub/skills/upload", + "/skill-hub/skills/import", + "/skill-hub/skills/{name}", + "/skill-hub/skills/{name}/archive", + "/skill-hub/skills/{name}/content", + "/skill-hub/skills/{plugin_name}/downloads", + "/skill-hub/skills/{name}/versions", + "/skill-hub/skills/{name}/versions/{version_id}", + "/skill-hub/skills/{name}/versions/{version_id}/archive", + "/skill-hub/skills/{name}/publish", + "/skill-hub/skills/{name}/unpublish", + "/skill-hub/skills/{name}/upload", + "/skill-hub/submissions", + "/skill-hub/submissions/{submission_id}", + "/skill-hub/submissions/{submission_id}/archive", + "/skill-hub/submissions/{submission_id}/approve", + "/skill-hub/submissions/{submission_id}/reject", + "/skill-hub/submissions/{submission_id}/scan", + ) + litellm_native_routes = [ "/rag/ingest", "/v1/rag/ingest", @@ -461,6 +489,9 @@ class LiteLLMRoutes(enum.Enum): "/v1/skills/{skill_id}", "/claude-code/marketplace.json", "/claude-code/plugins", + "/claude-code/plugins/upload", + "/claude-code/plugins/{plugin_name}/archive/{digest}.zip", + "/claude-code/plugins/{plugin_name}/downloads", "/claude-code/plugins/{plugin_name}", ] @@ -691,6 +722,7 @@ class LiteLLMRoutes(enum.Enum): + key_management_routes + mcp_management_routes + list(agent_management_routes) + + list(skill_hub_routes) ) spend_tracking_routes = [ @@ -933,6 +965,7 @@ class LiteLLMRoutes(enum.Enum): # Agent registry - reads are role-scoped and writes are proxy-admin-gated # inside agent_endpoints/endpoints.py *agent_management_routes, + *skill_hub_routes, ] # routes that manage their own allowed/disallowed logic ## Org Admin Routes ## @@ -2473,20 +2506,9 @@ class ConfigGeneralSettings(LiteLLMPydanticObjectBase): Documents all the fields supported by `general_settings` in config.yaml """ - accounting_capture: UsageCaptureSettings | None = Field( - None, - description="Opt-in durable usage capture. Legacy spend updates remain active. Requires local Prisma writes.", - ) - accounting_sync_ack: bool = Field( + use_spend_logs_ledger: bool = Field( False, - description="Wait for usage commit on foreground non-stream chat, text, embedding and Responses requests. " - "Other requests remain supported with asynchronous usage capture.", - ) - accounting_sync_ack_timeout_seconds: float = Field( - 20.0, gt=0, description="Maximum response wait for usage commit, including the batch flush interval" - ) - accounting_sync_ack_failure_policy: Literal["fail_closed", "log"] = Field( - "fail_closed", description="Return 503 or log the persistence failure after the response wait expires" + description="Apply request accounting from stored SpendLogs deliveries. Enable only after all accounting writers are upgraded and ledger activation gates pass.", ) request_tag_mappings: Sequence[RequestTagMapping] | None = Field( @@ -3023,6 +3045,9 @@ class ConfigGeneralSettings(LiteLLMPydanticObjectBase): None, description="If True, forwards client headers (e.g. Authorization) to the LLM API. Required for Claude Code with Max subscription.", ) + skill_scanner: SkillScannerConfig | None = Field( + None, description="Opt-in external scanner for manual admin review of skill submissions" + ) mcp_required_fields: list[str] | None = Field( None, description="List of MCP server fields that must be filled in for a submission to pass standards checks (e.g. ['description', 'source_url', 'alias']).", @@ -3809,6 +3834,9 @@ class SpendLogsMetadata(TypedDict): class SpendLogsPayload(TypedDict): + accounting_payload: NotRequired[Mapping[str, object]] # writable-ok: capture before buffering + accounting_log_disabled: NotRequired[bool] # writable-ok: capture logging mode before buffering + accounting_delivery_id: NotRequired[str] # writable-ok: assigned once before buffering request_id: str call_type: str api_key: str @@ -4790,11 +4818,14 @@ class UnregisteredJWTClientBehavior(str, enum.Enum): - auto_register: Automatically create a new virtual key and mapping on first encounter. The new key has no budget/model restrictions; admins can tighten it later via /jwt_client/update. + - link_only: Map an eligible existing user key or return HTTP 403, without + creating a key. Proxy admins authenticate without a mapped key. """ FALLBACK_TEAM_MAPPING = "fallback_team_mapping" REJECT = "reject" AUTO_REGISTER = "auto_register" + LINK_ONLY = "link_only" class JWTIssuerConfig(LiteLLMBaseModel): @@ -5032,7 +5063,12 @@ class LiteLLM_JWTAuth(LiteLLMPydanticObjectBase): "What to do when virtual_key_claim_field is set but the JWT claim value " "has no registered mapping. 'fallback_team_mapping' (default): fall through " "to team-based JWT auth. 'reject': return HTTP 403. " - "'auto_register': auto-create a virtual key and mapping on first encounter." + "'auto_register': auto-create a virtual key and mapping on first encounter. " + "'link_only': map an eligible existing user key or return HTTP 403, without creating a key. " + "link_only ignores auto_register_map_existing_key; user provisioning still follows user_id_upsert. " + "Existing-key selection ignores allowed_routes; JWTs inherit the selected key's permissions, " + "including management routes, with request-time key restrictions still enforced. " + "Unmapped proxy admins authenticate directly in auto_register and link_only modes." ), ) auto_register_map_existing_key: bool = Field( @@ -5042,8 +5078,10 @@ class LiteLLM_JWTAuth(LiteLLMPydanticObjectBase): "field is the user_id_jwt_field or user_email_jwt_field, the JWT claim is mapped to a virtual key the " "JWT-resolved user already owns instead of minting a new one. If the user owns several, the most recently created key in the " "JWT-resolved team (or with no team when the JWT resolves none) is chosen among keys that never " - "expire, are not blocked, are not Admin UI session keys, were not minted by auto_register, and " - "have no allowed_routes or include llm_api_routes. Otherwise a new key is minted as usual." + "expire, are not blocked, are not Admin UI session keys, and were not minted by auto_register. " + "allowed_routes does not affect key selection. JWTs inherit the selected key's permissions, " + "including management routes; request-time key restrictions still apply. " + "Otherwise a new key is minted as usual." ), ) routing_overrides: list[JWTRoutingOverride] | None = Field( diff --git a/litellm/proxy/agent_endpoints/a2a_endpoints.py b/litellm/proxy/agent_endpoints/a2a_endpoints.py index 3dfaa7f213e..f0a4d47f1e4 100644 --- a/litellm/proxy/agent_endpoints/a2a_endpoints.py +++ b/litellm/proxy/agent_endpoints/a2a_endpoints.py @@ -26,6 +26,7 @@ from litellm._logging import verbose_proxy_logger from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.litellm_core_utils.url_utils import SSRFError, validate_url from litellm.llms.a2a.common_utils import resolve_a2a_hop_auth_header +from litellm.llms.azure.common_utils import caused_by_entra_rejection from litellm.llms.custom_httpx.sse_lines import aiter_sse_lines from litellm.proxy._types import ProxyException, UserAPIKeyAuth from litellm.proxy.a2a.agent_card import point_agent_card_at_proxy @@ -1202,6 +1203,8 @@ async def invoke_agent_a2a( pass if isinstance(e, litellm.BadRequestError): return _jsonrpc_error(body.get("id"), -32602, e.message, 400) + if isinstance(e, litellm.AuthenticationError) and caused_by_entra_rejection(e): + return _jsonrpc_error(body.get("id"), -32000, e.message, 401) return _jsonrpc_error(body.get("id"), -32603, f"Internal error: {e}", 500) diff --git a/litellm/proxy/agent_endpoints/auth/managed_authorization.py b/litellm/proxy/agent_endpoints/auth/managed_authorization.py index cdbbd6029fa..57e99edecba 100644 --- a/litellm/proxy/agent_endpoints/auth/managed_authorization.py +++ b/litellm/proxy/agent_endpoints/auth/managed_authorization.py @@ -11,7 +11,15 @@ from litellm.proxy.agent_endpoints.managed_identity import raise_identity_failur from litellm.types.agents import AgentResponse from litellm.types.proxy.agent_identity import AgentIdentityFailure, ManagedAgentContext -_MANAGED_REALTIME_ROUTES: Final = frozenset(("/realtime", "/v1/realtime", "/openai/v1/realtime")) +_MANAGED_REALTIME_ROUTES: Final = frozenset( + ( + "/realtime", + "/v1/realtime", + "/openai/v1/realtime", + "/realtime/translations", + "/v1/realtime/translations", + ) +) _MANAGED_LIVE_ROUTES: Final = frozenset(("/live/sessions", "/v1/live/sessions", "/openai/v1/live/sessions")) _MANAGED_MODEL_ROUTES: Final = frozenset( f"{prefix}/{operation}" @@ -112,7 +120,11 @@ def managed_inference_request( if route in _MANAGED_LIVE_ROUTES: return dict(body) if route in _MANAGED_REALTIME_ROUTES: - model: Final = query_model or body.get("model") + from litellm.proxy.common_utils.http_parsing_utils import resolve_realtime_route_model + + model: Final = resolve_realtime_route_model( + query_model if isinstance(query_model, str) else None, None, route.endswith("/realtime/translations") + ) if not isinstance(model, str) or not model: raise_identity_failure( AgentIdentityFailure(message="Managed inference requires an explicit or configured model") diff --git a/litellm/proxy/alerting_endpoints/__init__.py b/litellm/proxy/alerting_endpoints/__init__.py new file mode 100644 index 00000000000..6a7a204b435 --- /dev/null +++ b/litellm/proxy/alerting_endpoints/__init__.py @@ -0,0 +1 @@ +"""HTTP endpoints for gateway alerts.""" diff --git a/litellm/proxy/alerting_endpoints/model_deprecation_alerts.py b/litellm/proxy/alerting_endpoints/model_deprecation_alerts.py new file mode 100644 index 00000000000..a69dd6ee025 --- /dev/null +++ b/litellm/proxy/alerting_endpoints/model_deprecation_alerts.py @@ -0,0 +1,109 @@ +"""Shared acknowledgement state for model migration alerts.""" + +import hashlib +import json +from datetime import date, datetime, timezone +from typing import Annotated, Final + +from fastapi import APIRouter, Depends, HTTPException, Query +from pydantic import TypeAdapter + +from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.deps.database import DatabaseDep +from litellm.repositories.config_repository import ConfigRepository +from litellm.repositories.daily_activity_buckets import api_key_bucket, api_key_from_bucket +from litellm.repositories.table_repositories import DailyTagSpendRepository +from litellm.types.proxy.auth.user_roles import LitellmUserRoles +from litellm.types.proxy.model_deprecation import DeprecationAlertState, DeprecationAlertUpdate, DeprecationTagUsage + +router: Final = APIRouter() + + +def alert_state_repository(database: DatabaseDep) -> ConfigRepository: + if database is None: + raise HTTPException(status_code=503, detail="Alert state requires a database connection") + return ConfigRepository(database.prisma, use_writer=True) + + +def alert_tag_repository(database: DatabaseDep) -> DailyTagSpendRepository: + if database is None: + raise HTTPException(status_code=503, detail="Model usage tags require a database connection") + return DailyTagSpendRepository(database.prisma) + + +def _state_key(model: str, deprecation_date: date) -> str: + identity: Final = json.dumps([model, deprecation_date.isoformat()]) + digest: Final = hashlib.sha256(identity.encode()).hexdigest() + return f"model_deprecation_alert:{digest}" + + +def _require_admin(user: UserAPIKeyAuth, *, write: bool) -> None: + if user.user_role == LitellmUserRoles.PROXY_ADMIN: + return + if not write and user.user_role == LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY: + return + raise HTTPException(status_code=403, detail="Only gateway admins can manage model deprecation alerts") + + +@router.get("/alerting/model-deprecations/state", tags=["alerting"], response_model=DeprecationAlertState) +async def get_deprecation_alert_state( + model: Annotated[str, Query(min_length=1, max_length=1024)], + deprecation_date: date, + user: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + repository: Annotated[ConfigRepository, Depends(alert_state_repository)], +) -> DeprecationAlertState: + _require_admin(user, write=False) + record: Final = await repository.get_param(_state_key(model, deprecation_date)) + if record is None: + return DeprecationAlertState(model=model, deprecation_date=deprecation_date) + return DeprecationAlertState.model_validate(record.param_value) + + +@router.put("/alerting/model-deprecations/state", tags=["alerting"], response_model=DeprecationAlertState) +async def update_deprecation_alert_state( + data: DeprecationAlertUpdate, + user: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + repository: Annotated[ConfigRepository, Depends(alert_state_repository)], +) -> DeprecationAlertState: + _require_admin(user, write=True) + state: Final = DeprecationAlertState( + **data.model_dump(), updated_at=datetime.now(timezone.utc), updated_by=user.user_id + ) + await repository.set_param(_state_key(data.model, data.deprecation_date), state.model_dump(mode="json")) + return state + + +@router.get("/alerting/model-deprecations/tags", tags=["alerting"], response_model=tuple[DeprecationTagUsage, ...]) +async def get_deprecation_usage_tags( + model: Annotated[str, Query(min_length=1, max_length=1024)], + api_keys: Annotated[tuple[str, ...], Query(min_length=1, max_length=100)], + start_date: date, + end_date: date, + user: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + repository: Annotated[DailyTagSpendRepository, Depends(alert_tag_repository)], +) -> tuple[DeprecationTagUsage, ...]: + """Distinct tags observed with this model for a page of affected reporting key IDs.""" + _require_admin(user, write=False) + if not 0 <= (end_date - start_date).days < 30: + raise HTTPException(status_code=422, detail="Select up to 30 consecutive calendar dates") + rows: Final = await repository.table.group_by( + by=["api_key", "tag"], + where={ + "api_key": { + # bounded-ok: query validation limits api_keys to 100 IDs. + "in": [api_key_from_bucket(key) for key in api_keys] + }, + "model": model, + "date": {"gte": start_date.isoformat(), "lte": end_date.isoformat()}, + "api_requests": {"gt": 0}, + "tag": {"not": None}, + }, + ) + tags: Final = TypeAdapter(tuple[DeprecationTagUsage, ...]).validate_python(rows) + return tuple( + sorted( + (DeprecationTagUsage(api_key=api_key_bucket(usage.api_key), tag=usage.tag) for usage in tags), + key=lambda usage: (usage.api_key, usage.tag), + ) + ) diff --git a/litellm/proxy/analytics_endpoints/cache_activity.py b/litellm/proxy/analytics_endpoints/cache_activity.py index 8a3f71e656e..17e250a2dbe 100644 --- a/litellm/proxy/analytics_endpoints/cache_activity.py +++ b/litellm/proxy/analytics_endpoints/cache_activity.py @@ -2,31 +2,22 @@ import asyncio import json from collections.abc import Sequence from datetime import datetime -from typing import Final, Protocol +from typing import TYPE_CHECKING, Final from pydantic import TypeAdapter from litellm.proxy._types import LiteLLMRoutes from litellm.proxy.auth.authorization import ReadScope, read_scope_bind_params +from litellm.proxy.utils import query_raw_within_statement_timeout from litellm.types.llms.base import LiteLLMBaseModel +if TYPE_CHECKING: + from litellm.proxy.utils import PrismaClient + UNKNOWN_CALL_TYPE: Final = "Unknown" INFO_ROUTES_JSON: Final = json.dumps(LiteLLMRoutes.info_routes.value) -class _SupportsQueryRaw(Protocol): - """The single database operation the cache-activity queries issue.""" - - async def query_raw(self, query: str, *args: object) -> Sequence[object]: ... - - -class _SupportsRawQueryDb(Protocol): - """A prisma client handle, narrowed to the raw-query surface used here.""" - - @property - def db(self) -> _SupportsQueryRaw: ... - - class CacheActivityGroup(LiteLLMBaseModel): call_type: str api_requests: int @@ -174,7 +165,7 @@ def compute_totals(groups: Sequence[CacheActivityGroup]) -> CacheActivityTotals: async def get_cache_activity( - prisma_client: _SupportsRawQueryDb, + prisma_client: "PrismaClient", read_scope: ReadScope, start_date: datetime, end_date: datetime, @@ -185,14 +176,46 @@ async def get_cache_activity( models_json: Final = json.dumps(list(models)) scope_params: Final = read_scope_bind_params(read_scope) group_rows, error_rows, key_alias_rows, model_rows = await asyncio.gather( - prisma_client.db.query_raw( - GROUPS_SQL, start_date, end_date, key_aliases_json, models_json, INFO_ROUTES_JSON, *scope_params + query_raw_within_statement_timeout( + prisma_client, + GROUPS_SQL, + start_date, + end_date, + key_aliases_json, + models_json, + INFO_ROUTES_JSON, + *scope_params, + what="Cache activity", ), - prisma_client.db.query_raw( - ERROR_BREAKDOWN_SQL, start_date, end_date, key_aliases_json, models_json, INFO_ROUTES_JSON, *scope_params + query_raw_within_statement_timeout( + prisma_client, + ERROR_BREAKDOWN_SQL, + start_date, + end_date, + key_aliases_json, + models_json, + INFO_ROUTES_JSON, + *scope_params, + what="Cache activity", + ), + query_raw_within_statement_timeout( + prisma_client, + KEY_ALIAS_OPTIONS_SQL, + start_date, + end_date, + INFO_ROUTES_JSON, + *scope_params, + what="Cache activity", + ), + query_raw_within_statement_timeout( + prisma_client, + MODEL_OPTIONS_SQL, + start_date, + end_date, + INFO_ROUTES_JSON, + *scope_params, + what="Cache activity", ), - prisma_client.db.query_raw(KEY_ALIAS_OPTIONS_SQL, start_date, end_date, INFO_ROUTES_JSON, *scope_params), - prisma_client.db.query_raw(MODEL_OPTIONS_SQL, start_date, end_date, INFO_ROUTES_JSON, *scope_params), ) groups: Final = _groups_adapter.validate_python(group_rows or []) return CacheActivityResponse( diff --git a/litellm/proxy/anthropic_endpoints/answered_status.py b/litellm/proxy/anthropic_endpoints/answered_status.py new file mode 100644 index 00000000000..26eeb08c8c9 --- /dev/null +++ b/litellm/proxy/anthropic_endpoints/answered_status.py @@ -0,0 +1,53 @@ +from typing import Final, TypeVar + +from litellm.exceptions import APIError, InternalServerError, MidStreamFallbackError + +_PROVIDER_OVERLOAD_STATUS_CODE: Final = 529 +_OPENAI_OVERLOAD_ANSWERED_STATUS_CODE: Final = 503 + +_Raised = TypeVar("_Raised", bound=Exception) + + +def is_provider_overload(exc: Exception) -> bool: + return _provider_status_code(exc) == _PROVIDER_OVERLOAD_STATUS_CODE + + +def with_openai_overload_status(exc: _Raised) -> _Raised: + return ( + _copy_carrying( + _copy_carrying(exc, "provider_status_code", _PROVIDER_OVERLOAD_STATUS_CODE), + "status_code", + _OPENAI_OVERLOAD_ANSWERED_STATUS_CODE, + ) + if is_provider_overload(exc) + else exc + ) + + +def _provider_status_code(exc: Exception) -> int | None: + unwrapped = exc # rebind-ok: the recursion gate requires iterative wrapper traversal + while isinstance(unwrapped, MidStreamFallbackError) and unwrapped.original_exception is not None: + unwrapped = unwrapped.original_exception + match unwrapped: + case InternalServerError(provider_status_code=int() as provider_status): + return provider_status + case APIError(provider_status_code=int() as provider_status): + return provider_status + case APIError(status_code=int() as provider_status): + return provider_status + case _: + return None + + +def _copy_carrying(exc: _Raised, attribute: str, value: int | str) -> _Raised: + answered: Final = type(exc).__new__(type(exc), *exc.args) + answered.__dict__.update({**exc.__dict__, attribute: value}) + answered.__cause__ = exc.__cause__ + answered.__context__ = exc.__context__ + answered.__suppress_context__ = exc.__suppress_context__ + return answered.with_traceback(exc.__traceback__) + + +def with_answered_status(exc: Exception) -> Exception: + provider_status_code: Final = _provider_status_code(exc) + return exc if provider_status_code is None else _copy_carrying(exc, "status_code", provider_status_code) diff --git a/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py b/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py index fc82686947d..26cb0a2f3e6 100644 --- a/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py +++ b/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_marketplace.py @@ -18,29 +18,48 @@ Endpoints: /claude-code/plugins/{name} - DELETE - Delete a plugin (proxy admin only) """ +import asyncio +import hashlib import json import re from collections.abc import Mapping, Sequence from datetime import datetime, timezone from types import MappingProxyType from typing import Annotated, Final, Protocol, TypedDict, get_args -from urllib.parse import urlsplit -from fastapi import APIRouter, Depends, HTTPException, Request -from fastapi.responses import JSONResponse -from pydantic import TypeAdapter -from typing_extensions import ReadOnly +from fastapi import APIRouter, Depends, File, Form, HTTPException, Query, Request, UploadFile +from fastapi.responses import JSONResponse, Response +from pydantic import Json, TypeAdapter +from typing_extensions import ReadOnly, assert_never from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.url_utils import is_https_url_with_host +from litellm.models.plugin_upload import ( + PluginDownloader, + PluginDownloadResult, + PluginDownloadsResponse, + PluginPublication, + PluginPublicationBase, + PluginPublicationError, + has_agent_skill_metadata, +) from litellm.proxy._types import CommonProxyErrors, ProxyErrorTypes, ProxyException, UserAPIKeyAuth from litellm.proxy.anthropic_endpoints.claude_code_endpoints.claude_code_skill_access import ( SkillVisibility, resolve_skill_visibility, ) +from litellm.proxy.anthropic_endpoints.claude_code_endpoints.skill_upload_archive import ( + MAX_SKILL_UPLOAD_BYTES, + build_uploaded_skill_archive, +) from litellm.proxy.auth.auth_exception_handler import DB_UNAVAILABLE_FALLBACK_USER_ID from litellm.proxy.auth.user_api_key_auth import user_api_key_auth -from litellm.proxy.common_utils.claude_code_marketplace_auth import marketplace_auth_required +from litellm.proxy.common_utils.claude_code_marketplace_auth import ( + marketplace_auth_required, + marketplace_key_header_present, +) from litellm.proxy.common_utils.resource_ownership import is_proxy_admin +from litellm.proxy.deps.repositories import PluginUploadRepositoryDep from litellm.repositories.table_repositories import ClaudeCodePluginRepository from litellm.types.proxy.auth.special_headers import SpecialHeaders from litellm.types.proxy.claude_code_endpoints import ( @@ -52,6 +71,7 @@ from litellm.types.proxy.claude_code_endpoints import ( RegisterPluginRequest, RegisterPluginResponse, UpdatePluginRequest, + UploadPluginRequest, ) router: Final = APIRouter() @@ -113,7 +133,23 @@ async def get_prisma_client() -> object: _get_prisma_client: Final = get_prisma_client -async def _header_key_caller(request: Request) -> UserAPIKeyAuth: +def plugin_archive_url(request: Request, name: str, digest: str) -> str: + from litellm.proxy.utils import get_custom_url + + return get_custom_url( + request_base_url=str(request.base_url), route=f"claude-code/plugins/{name}/archive/{digest}.zip" + ) + + +def plugin_archive_source_matches( + request: Request, name: str, source: Mapping[str, str], digest: str, *, has_agent_skill_metadata: bool +) -> bool: + if has_agent_skill_metadata: + return source.get("source") == "archive" and source.get("sha256") == digest + return source == {"source": "archive", "url": plugin_archive_url(request, name, digest), "sha256": digest} + + +async def header_key_caller(request: Request) -> UserAPIKeyAuth: try: caller: Final = await user_api_key_auth( request=request, @@ -142,12 +178,166 @@ async def _header_key_caller(request: Request) -> UserAPIKeyAuth: async def _marketplace_caller(request: Request, key: str | None) -> UserAPIKeyAuth | None: if marketplace_auth_required(): - return await _header_key_caller(request) + return await header_key_caller(request) if key: return await user_api_key_auth(request=request, api_key=f"Bearer {key}") return None +@router.post( + "/claude-code/plugins/upload", + tags=["Claude Code Marketplace"], + response_model=RegisterPluginResponse, +) +async def upload_plugin( + request: Request, + uploads: PluginUploadRepositoryDep, + user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + file: Annotated[UploadFile, File(description="Skill ZIP containing SKILL.md and supporting files, up to 10 MiB")], + metadata: Annotated[Json[UploadPluginRequest], Form(description="JSON skill metadata without a source URL")], +) -> RegisterPluginResponse: + """Create a skill and its uploaded ZIP atomically. Duplicate names return 409.""" + _require_proxy_admin(user_api_key_dict) + if uploads is None: + raise _error_response(500, CommonProxyErrors.db_not_connected_error.value) + content: Final = await file.read(MAX_SKILL_UPLOAD_BYTES + 1) + if len(content) > MAX_SKILL_UPLOAD_BYTES: + raise _error_response(413, "Skill ZIP must be 10 MiB or smaller") + archive: Final = await asyncio.to_thread(build_uploaded_skill_archive, content, metadata.name) + if archive is None: + raise _error_response( + 400, "Upload a valid ZIP with SKILL.md at the root or inside one skill folder, and safe supporting files" + ) + digest: Final = hashlib.sha256(archive).hexdigest() + source: Final = { + "source": "archive", + "url": plugin_archive_url(request, metadata.name, digest), + "sha256": digest, + } + spec: Final = RegisterPluginRequest.model_validate({**metadata.model_dump(), "source": source}) + _validate_installation_preference(spec) + published: Final = await uploads.publish( + PluginPublication( + name=spec.name, + version=spec.version, + description=spec.description, + manifest=_build_plugin_manifest(spec.name, spec), + content=archive, + created_by=user_api_key_dict.user_id, + ) + ) + if isinstance(published, PluginPublicationError): + raise _publication_error(published) + return RegisterPluginResponse( + status="success", + action="created", + plugin=PluginResponse( + id=published.id, + name=spec.name, + version=published.version, + description=spec.description, + source=source, + installation_preference=spec.installation_preference, + enabled=True, + ), + ) + + +def require_download_recorded(result: PluginDownloadResult) -> None: + match result: + case PluginDownloadResult.RECORDED: + return + case PluginDownloadResult.SKILL_NOT_FOUND: + raise _error_response(404, "Skill archive not found") + case _: + assert_never(result) + + +def plugin_downloader(caller: UserAPIKeyAuth | None) -> PluginDownloader: + return PluginDownloader( + authenticated=caller is not None, + user_id=caller.user_id if caller is not None else None, + user_email=caller.user_email if caller is not None else None, + key_alias=caller.key_alias if caller is not None else None, + team_id=caller.team_id if caller is not None else None, + team_alias=caller.team_alias if caller is not None else None, + ) + + +@router.get( + "/claude-code/plugins/{plugin_name}/archive/{digest}.zip", + tags=["Claude Code Marketplace"], + response_class=Response, + responses={200: {"content": {"application/zip": {"schema": {"type": "string", "format": "binary"}}}}}, +) +async def download_plugin_archive( + request: Request, + plugin_name: str, + digest: str, + uploads: PluginUploadRepositoryDep, +) -> Response: + """Download an uploaded ZIP under the same visibility policy as its skill.""" + caller: Final = ( + await header_key_caller(request) + if marketplace_key_header_present(request) + else await _marketplace_caller(request, None) + ) + visibility: Final = await resolve_skill_visibility(caller) + if uploads is None: + raise _error_response(500, CommonProxyErrors.db_not_connected_error.value) + archive: Final = await uploads.get_metadata(plugin_name) + if ( + archive is None + or not visibility.allows(archive) + or not plugin_archive_source_matches( + request, plugin_name, archive.source, digest, has_agent_skill_metadata=archive.has_agent_skill_metadata + ) + ): + raise _error_response(404, "Skill archive not found") + content: Final = await uploads.get_content(archive) + if content is None: + raise _error_response(404, "Skill archive not found") + require_download_recorded(await uploads.record_download(archive, digest, plugin_downloader(caller))) + return Response( + content=content, + media_type="application/zip", + headers={ + "Content-Disposition": f'attachment; filename="{archive.name}.zip"', + "Cache-Control": "private, no-store", + "X-Content-Type-Options": "nosniff", + }, + ) + + +@router.get( + "/claude-code/plugins/{plugin_name}/downloads", + tags=["Claude Code Marketplace"], + response_model=PluginDownloadsResponse, +) +async def get_plugin_downloads( + plugin_name: str, + uploads: PluginUploadRepositoryDep, + user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + limit: Annotated[int, Query(ge=1, le=100, description="Maximum number of download events")] = 25, + cursor: Annotated[str | None, Query(pattern=r"^[1-9][0-9]{0,18}$", description="Previous next_cursor")] = None, +) -> PluginDownloadsResponse: + """Admin-only ZIP download totals and authenticated downloader history. + + Anonymous downloads contribute only to totals. Counts include repeat requests and client prefetches, + starting when tracking is deployed. External sources and installation completion are not observed. + """ + _require_proxy_admin(user_api_key_dict) + if uploads is None: + raise _error_response(500, CommonProxyErrors.db_not_connected_error.value) + before: Final = int(cursor) if cursor is not None else None + if before is not None and before > 9223372036854775807: + raise _error_response(422, "Invalid download cursor") + result: Final = await uploads.downloads(plugin_name, limit, before) + if result is None: + raise _error_response(404, "Plugin not found") + return result + + @router.get( "/claude-code/marketplace.json", tags=["Claude Code Marketplace"], @@ -254,14 +444,6 @@ _VALID_GIT_SUBDIR_PATH_RE: Final = re.compile(r"^[a-zA-Z0-9][a-zA-Z0-9._-]*(/[a- _VALID_SHA256_RE: Final = re.compile(r"^[0-9a-fA-F]{64}$") -def _is_https_url_with_host(url: str) -> bool: - try: - parts: Final = urlsplit(url) - except ValueError: - return False - return parts.scheme == "https" and bool(parts.hostname) - - def _validate_plugin_source(source: Mapping[str, str]) -> None: """Validate plugin source format, raising HTTPException on invalid input.""" source_type: Final = source.get("source") @@ -298,7 +480,7 @@ def _validate_plugin_source(source: Mapping[str, str]) -> None: }, ) elif source_type == "archive": - if not _is_https_url_with_host(source.get("url", "")): + if not is_https_url_with_host(source.get("url", "")): raise HTTPException( status_code=400, detail={ @@ -349,10 +531,14 @@ def _error_response(status_code: int, message: str) -> HTTPException: return HTTPException(status_code=status_code, detail={"error": message}) -def _name_conflict_error(name: str) -> HTTPException: - return _error_response( - 409, f"A skill named '{name}' already exists. Update the existing skill instead of adding it again." - ) +def _publication_error(error: PluginPublicationError) -> HTTPException: + match error.kind: + case "invalid_version": + return _error_response(400, error.message) + case "not_found": + return _error_response(404, error.message) + case "conflict": + return _error_response(409, error.message) def _require_proxy_admin(user_api_key_dict: UserAPIKeyAuth) -> None: @@ -375,6 +561,7 @@ def _require_proxy_admin(user_api_key_dict: UserAPIKeyAuth) -> None: ) async def register_plugin( request: RegisterPluginRequest, + uploads: PluginUploadRepositoryDep, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), ): """ @@ -417,12 +604,11 @@ async def register_plugin( }' ``` """ - from prisma.errors import UniqueViolationError - try: _require_proxy_admin(user_api_key_dict) - prisma_client: Final = await get_prisma_client() + if uploads is None: + raise _error_response(500, CommonProxyErrors.db_not_connected_error.value) if not re.match(r"^[a-z0-9-]+$", request.name): raise HTTPException( @@ -433,30 +619,19 @@ async def register_plugin( _validate_plugin_source(request.source) _validate_installation_preference(request) - existing: Final[_PluginRecord | None] = await ClaudeCodePluginRepository(prisma_client).table.find_unique( - where={"name": request.name} - ) - if existing: - raise _name_conflict_error(request.name) - manifest: Final[Mapping[str, object]] = _build_plugin_manifest(request.name, request) - try: - plugin: Final[_PluginRecord] = await ClaudeCodePluginRepository(prisma_client).table.create( - data={ - "name": request.name, - "version": request.version, - "description": request.description, - "manifest_json": json.dumps(manifest), - "files_json": "{}", - "enabled": True, - "created_at": datetime.now(timezone.utc), - "updated_at": datetime.now(timezone.utc), - "created_by": user_api_key_dict.user_id, - } + plugin: Final = await uploads.publish( + PluginPublication( + name=request.name, + version=request.version, + description=request.description, + manifest=manifest, + created_by=user_api_key_dict.user_id, ) - except UniqueViolationError: - raise _name_conflict_error(request.name) + ) + if isinstance(plugin, PluginPublicationError): + raise _publication_error(plugin) verbose_proxy_logger.info("Plugin %s created successfully", request.name) @@ -467,7 +642,7 @@ async def register_plugin( id=plugin.id, name=plugin.name, version=plugin.version, - description=plugin.description, + description=request.description, source=request.source, installation_preference=request.installation_preference, enabled=plugin.enabled, @@ -493,7 +668,7 @@ async def register_plugin( async def list_plugins( enabled_only: bool = False, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): +) -> ListPluginsResponse: """ List all plugins in the marketplace. @@ -525,6 +700,7 @@ async def list_plugins( version=p.version, description=p.description, source=manifest.get("source", {}), + has_agent_skill_metadata=has_agent_skill_metadata(MANIFEST_FIELDS.validate_python(manifest)), author=manifest.get("author"), homepage=manifest.get("homepage"), keywords=manifest.get("keywords"), @@ -631,6 +807,7 @@ async def get_plugin( async def update_plugin( plugin_name: str, request: UpdatePluginRequest, + uploads: PluginUploadRepositoryDep, user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], ): """ @@ -639,7 +816,8 @@ async def update_plugin( The plugin is identified by its name in the path, which is the resource identity and cannot be changed here. This is a full replace, not a merge: the manifest is rebuilt from the request body, so any optional field left - out is reset to its default (e.g. an omitted version is cleared, not kept). + out is reset to its default, except version which automatically increments + the published patch version when omitted or null. Send the full desired state. Returns 404 if no plugin with the given name exists; use @@ -677,32 +855,44 @@ async def update_plugin( try: _require_proxy_admin(user_api_key_dict) + if uploads is None: + raise _error_response(500, CommonProxyErrors.db_not_connected_error.value) prisma_client: Final = await get_prisma_client() - _validate_plugin_source(request.source) - _validate_installation_preference(request) - - existing: Final[_PluginRecord | None] = await ClaudeCodePluginRepository(prisma_client).table.find_unique( - where={"name": plugin_name} - ) + repository: Final = ClaudeCodePluginRepository(prisma_client, use_writer=True) + existing: Final[_PluginRecord | None] = await repository.table.find_unique(where={"name": plugin_name}) if not existing: raise _error_response(404, f"Plugin '{plugin_name}' not found") + if request.expected_updated_at is not None and request.expected_updated_at != existing.updated_at: + raise _error_response(409, "The published skill changed. Reload it before publishing an update") - manifest: Final[Mapping[str, object]] = _build_plugin_manifest(plugin_name, request) + current_manifest: Final = MANIFEST_FIELDS.validate_json(existing.manifest_json or "{}") + if request.source != current_manifest.get("source"): + _validate_plugin_source(request.source) + _validate_installation_preference(request) - plugin: Final[_PluginRecord | None] = await ClaudeCodePluginRepository(prisma_client).table.update( - where={"name": plugin_name}, - data={ - "version": request.version, - "description": request.description, - "manifest_json": json.dumps(manifest), - "files_json": "{}", - "updated_at": datetime.now(timezone.utc), - }, + manifest: Final[Mapping[str, object]] = { + **_build_plugin_manifest(plugin_name, request), + **( + {"agent_skill": current_manifest["agent_skill"]} + if "agent_skill" in current_manifest and request.source == current_manifest.get("source") + else {} + ), + } + + plugin: Final = await uploads.publish( + PluginPublication( + name=plugin_name, + version=request.version, + description=request.description, + manifest=manifest, + created_by=user_api_key_dict.user_id, + ), + PluginPublicationBase(existing.id, existing.updated_at), ) - if plugin is None: - raise _error_response(404, f"Plugin '{plugin_name}' not found") + if isinstance(plugin, PluginPublicationError): + raise _publication_error(plugin) verbose_proxy_logger.info("Plugin %s updated successfully", plugin_name) @@ -713,7 +903,7 @@ async def update_plugin( id=plugin.id, name=plugin.name, version=plugin.version, - description=plugin.description, + description=request.description, source=request.source, installation_preference=request.installation_preference, enabled=plugin.enabled, diff --git a/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_skill_access.py b/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_skill_access.py index 9e5b55e7e36..4775498dec3 100644 --- a/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_skill_access.py +++ b/litellm/proxy/anthropic_endpoints/claude_code_endpoints/claude_code_skill_access.py @@ -19,8 +19,11 @@ if TYPE_CHECKING: class _SkillRecord(Protocol): - name: str - enabled: bool + @property + def name(self) -> str: ... + + @property + def enabled(self) -> bool: ... def _skills_of(permission: LiteLLM_ObjectPermissionTable | None) -> frozenset[str]: diff --git a/litellm/proxy/anthropic_endpoints/claude_code_endpoints/skill_upload_archive.py b/litellm/proxy/anthropic_endpoints/claude_code_endpoints/skill_upload_archive.py new file mode 100644 index 00000000000..48af819b673 --- /dev/null +++ b/litellm/proxy/anthropic_endpoints/claude_code_endpoints/skill_upload_archive.py @@ -0,0 +1,30 @@ +import json +import re +import struct +import zipfile +from typing import Final + +from litellm.proxy.discovery_endpoints.agent_skills_archive import pack_skill_archive, read_skill_archive_members + +MAX_SKILL_UPLOAD_BYTES: Final = 10 * 1024 * 1024 +MAX_SKILL_ARCHIVE_COMPRESSION_RATIO: Final = 50 + + +def build_uploaded_skill_archive(content: bytes, name: str) -> bytes | None: + if len(content) > MAX_SKILL_UPLOAD_BYTES or re.fullmatch(r"[a-z0-9-]+", name) is None: + return None + try: + skill: Final = read_skill_archive_members(content, for_upload=True) + if skill is None: + return None + members: Final = ((".claude-plugin/plugin.json", json.dumps({"name": name}).encode(), 0o644),) + tuple( + (f"skills/{name}/{path}", data, mode) for path, data, mode in skill + ) + compressed: Final = pack_skill_archive(members) + return ( + pack_skill_archive(members, zipfile.ZIP_STORED) + if sum(len(data) for _, data, _ in members) > len(compressed) * MAX_SKILL_ARCHIVE_COMPRESSION_RATIO + else compressed + ) + except (struct.error, UnicodeEncodeError): + return None diff --git a/litellm/proxy/anthropic_endpoints/endpoints.py b/litellm/proxy/anthropic_endpoints/endpoints.py index 0e204cf9211..7e990e3c71b 100644 --- a/litellm/proxy/anthropic_endpoints/endpoints.py +++ b/litellm/proxy/anthropic_endpoints/endpoints.py @@ -13,17 +13,17 @@ from typing_extensions import ReadOnly, TypedDict import litellm from litellm.anthropic_interface.exceptions import ( - AnthropicErrorDetail, - AnthropicErrorResponse, AnthropicExceptionMapping, ) from litellm.integrations.custom_guardrail import ModifyResponseException +from litellm.litellm_core_utils.agentic_followup_failure import is_agentic_followup_failure from litellm.litellm_core_utils.tool_fields import first_validation_error from litellm.llms.anthropic.chat.guardrail_translation.handler import AnthropicMessagesHandler from litellm.llms.anthropic.messages.context_management import ( AnthropicContextManagementError, ) from litellm.proxy._types import * +from litellm.proxy.anthropic_endpoints.answered_status import with_answered_status from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.common_request_processing import ( ProxyBaseLLMRequestProcessing, @@ -34,13 +34,14 @@ from litellm.proxy.common_request_processing import ( resolve_counted_tool_fields, resolve_litellm_call_id, ) -from litellm.proxy.common_utils.error_body_call_id import error_body_call_id +from litellm.proxy.common_utils.anthropic_error_payload import ( + anthropic_handler_error_json_response, +) from litellm.proxy.common_utils.http_parsing_utils import ( # noqa: F401 # legacy module exports _read_request_body, # pyright: ignore[reportPrivateUsage,reportUnusedImport] # backwards-compatible package export read_request_body, ) from litellm.proxy.common_utils.openai_error_payload import ( - LITELLM_CALL_ID_HEADER, error_status_code, litellm_call_id_headers, openai_error_param, @@ -49,6 +50,7 @@ from litellm.proxy.common_utils.openai_error_payload import ( ) from litellm.proxy.common_utils.token_count_log import rejected_token_count from litellm.proxy.common_utils.token_count_settings import count_source_fields +from litellm.proxy.hooks.proxy_track_cost_callback import failure_row_response_cost from litellm.proxy.litellm_pre_call_utils import ( forwarded_anthropic_oauth_token, should_auto_drop_params_for_agentic_cli, @@ -61,44 +63,8 @@ router: Final = APIRouter() _NO_HEADERS: Final[Mapping[str, str]] = MappingProxyType({}) -def _with_provider_specific_fields(exc: ProxyException, detail: AnthropicErrorDetail) -> AnthropicErrorDetail: - if not exc.provider_specific_fields: - return detail - with_fields: Final[AnthropicErrorDetail] = {**detail, "provider_specific_fields": exc.provider_specific_fields} - return with_fields - - -def _anthropic_error_detail( - exc: ProxyException, detail: AnthropicErrorDetail, call_id: str | None -) -> AnthropicErrorDetail: - if call_id is None: - return _with_provider_specific_fields(exc, detail) - with_call_id: Final[AnthropicErrorDetail] = { - **_with_provider_specific_fields(exc, detail), - "litellm_call_id": call_id, - } - return with_call_id - - def _anthropic_error_json_response(exc: ProxyException, request: Request) -> JSONResponse: - from litellm.proxy.proxy_server import ( - _close_dangling_otel_server_span, # pyright: ignore[reportPrivateUsage] # proxy_server keeps the span-close helper private; error JSONResponses returned by the route must stamp the OTel server span like the global ProxyException handler does - general_settings_view, - ) - - status_code: Final = int(exc.code) if exc.code is not None and exc.code.isdigit() else 500 - _close_dangling_otel_server_span(request, status_code, exc=exc) - envelope: Final = AnthropicExceptionMapping.transform_to_anthropic_error( - status_code=status_code, - raw_message=exc.message, - request_id=request.headers.get("x-request-id"), - ) - body_call_id: Final = error_body_call_id(general_settings_view(), exc.headers.get(LITELLM_CALL_ID_HEADER)) - content: Final[AnthropicErrorResponse] = { - **envelope, - "error": _anthropic_error_detail(exc, envelope["error"], body_call_id), - } - return JSONResponse(status_code=status_code, content=content, headers=exc.headers) + return anthropic_handler_error_json_response(exc, request) _TOKEN_COUNT_FIELDS: Final = ("model", "messages", "tools", "system") @@ -262,15 +228,18 @@ async def anthropic_response( request_id=request.headers.get("x-request-id"), ) return JSONResponse(status_code=e.status_code, content=body) - except Exception as e: + except Exception as raised: + answered: Final = with_answered_status(raised) await proxy_logging_obj.post_call_failure_hook( - user_api_key_dict=user_api_key_dict, original_exception=e, request_data=base_llm_response_processor.data + user_api_key_dict=user_api_key_dict, + original_exception=answered, + request_data=base_llm_response_processor.data, ) - log_llm_api_exception(e, base_llm_response_processor.litellm_call_id) + log_llm_api_exception(answered, base_llm_response_processor.litellm_call_id) - if isinstance(e, ProxyException): + if isinstance(answered, ProxyException): return _anthropic_error_json_response( - with_litellm_call_id(e, base_llm_response_processor.litellm_call_id), request + with_litellm_call_id(answered, base_llm_response_processor.litellm_call_id), request ) # Extract model_id from request metadata (same as success path) @@ -284,23 +253,27 @@ async def anthropic_response( call_id=base_llm_response_processor.litellm_call_id, model_id=model_id, version=version, - response_cost=0, + response_cost=( + failure_row_response_cost(base_llm_response_processor.data) + if is_agentic_followup_failure(answered) + else 0 + ), model_region=getattr(user_api_key_dict, "allowed_model_region", ""), request_data=data, - timeout=getattr(e, "timeout", None), + timeout=getattr(answered, "timeout", None), litellm_logging_obj=None, ) - if isinstance(e, HTTPException): - return _anthropic_error_json_response(proxy_exception_from_http_exception(e, headers), request) + if isinstance(answered, HTTPException): + return _anthropic_error_json_response(proxy_exception_from_http_exception(answered, headers), request) - error_msg: Final = f"{e}" + error_msg: Final = f"{answered}" return _anthropic_error_json_response( ProxyException( - message=getattr(e, "message", error_msg), - type=openai_error_type(e, error_status_code(e, 500)), - param=openai_error_param(e), - code=error_status_code(e, 500), + message=getattr(answered, "message", error_msg), + type=openai_error_type(answered, error_status_code(answered, 500)), + param=openai_error_param(answered), + code=error_status_code(answered, 500), headers=headers, ), request, @@ -420,8 +393,9 @@ async def count_tokens( except ProxyException as e: return _anthropic_error_json_response(e, request) except Exception as e: - log_llm_api_exception(e, litellm_call_id) - return _anthropic_error_json_response(proxy_exception_from_route_error(e), request) + answered: Final = with_answered_status(e) + log_llm_api_exception(answered, litellm_call_id) + return _anthropic_error_json_response(proxy_exception_from_route_error(answered), request) else: return { "input_tokens": token_response.total_tokens, diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index e2ae25686da..af60a315c60 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -43,7 +43,9 @@ from litellm.constants import ( REGISTRY_ERROR_NEGATIVE_CACHE_TTL, TAG_REGISTRY_MAX_SIZE, ) +from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.litellm_core_utils.dd_tracing import tracer +from litellm.litellm_core_utils.decisions_pricing import decisions_pricing_fields, decisions_request_price from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider from litellm.litellm_core_utils.safe_json_loads import safe_json_loads from litellm.litellm_core_utils.tool_fields import DropPolicy @@ -125,6 +127,7 @@ from litellm.proxy.common_utils.user_api_key_cache import ( NO_TEAM_MEMBERSHIP_SENTINEL, TAG_REGISTRY_OVERFLOW_SENTINEL, UserApiKeyCache, + budget_windows_absent_cache_key, end_user_cache_key, end_user_restricted_registry_cache_key, get_management_object_ttl, @@ -571,7 +574,6 @@ def is_model_cost_zero(model: str | list[str] | None, llm_router: RegistryReader return False continue try: - # Use the router registry's group info directly for better reliability model_group_info = llm_router.registry().group(model_name, include_hidden=True) if model_group_info is None: @@ -729,7 +731,7 @@ def _is_cost_explicitly_configured(deployments: Sequence[DeploymentTypedDict]) - def _has_explicit_positive_cost(deployments: Sequence[DeploymentTypedDict]) -> bool: - """Whether any of the deployments carries an explicit positive per-token price. + """Whether any of the deployments carries an explicit positive per-token or per-query price. The group's price is read from the deployments named after the routed group and from that group's own alias target, while an alias chain is served from the deployments named @@ -740,14 +742,21 @@ def _has_explicit_positive_cost(deployments: Sequence[DeploymentTypedDict]) -> b model_id = (deployment.get("model_info") or _EMPTY_COST_ENTRY).get("id") if model_id is None: continue - raw_entry = litellm.model_cost.get(model_id, _EMPTY_COST_ENTRY) - if _is_positive_cost(raw_entry.get("input_cost_per_token")) or _is_positive_cost( - raw_entry.get("output_cost_per_token") + raw_entry = as_str_mapping(litellm.model_cost.get(model_id)) or _EMPTY_COST_ENTRY + if ( + _is_positive_cost(raw_entry.get("input_cost_per_token")) + or _is_positive_cost(raw_entry.get("output_cost_per_token")) + or _is_positive_cost(_deployment_query_price(deployment["litellm_params"], raw_entry)) ): return True return False +def _deployment_query_price(litellm_params: Mapping[str, object], cost_entry: Mapping[str, object]) -> float | None: + provider: Final = litellm_params.get("custom_llm_provider") or str(litellm_params.get("model")).partition("/")[0] + return decisions_request_price({**cost_entry, "litellm_provider": provider}, decisions_pricing_fields(cost_entry)) + + _EMPTY_COST_ENTRY: Final[Mapping[str, object]] = MappingProxyType({}) @@ -3471,11 +3480,22 @@ async def delete_cache_key_object( ) await publish_auth_cache_invalidation(cache_key=key) + await evict_budget_windows_absent_marker( + entity_type=Litellm_EntityType.KEY, entity_id=hashed_token, user_api_key_cache=user_api_key_cache + ) _delete_cache_key_object: Final = delete_cache_key_object +async def evict_budget_windows_absent_marker( + entity_type: Litellm_EntityType, entity_id: str, user_api_key_cache: UserApiKeyCache +) -> None: + marker: Final = budget_windows_absent_cache_key(entity_type.value, entity_id) + evict_local(cache_keys=(marker,), user_api_key_cache=user_api_key_cache) + await publish_auth_cache_invalidation(cache_key=marker) + + async def delete_cache_key_objects( hashed_tokens: Sequence[str], user_api_key_cache: UserApiKeyCache, @@ -5378,79 +5398,6 @@ async def _granted_model_lists( ) -async def _user_object_or_none( - valid_token: UserAPIKeyAuth, - prisma_client: PrismaClient, - user_api_key_cache: UserApiKeyCache, - proxy_logging_obj: ProxyLogging, -) -> LiteLLM_UserTable | None: - try: - return await get_user_object( - user_id=valid_token.user_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - user_id_upsert=False, - proxy_logging_obj=proxy_logging_obj, - ) - except UserNotFoundError: - return None - - -async def enforced_model_allowlists( - valid_token: UserAPIKeyAuth, - prisma_client: PrismaClient | None, - user_api_key_cache: UserApiKeyCache, - proxy_logging_obj: ProxyLogging, -) -> tuple[Sequence[str], ...]: - """One model allowlist per level that ``common_checks`` enforces on a request from this identity.""" - key_models: Final = _resolve_key_models_for_auth_check(valid_token=valid_token) - if prisma_client is None: - return (key_models, tuple(valid_token.team_models or ())) - team_object: Final = ( - None - if valid_token.team_id is None - else await get_team_object( - team_id=valid_token.team_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, - ) - ) - user_object: Final = ( - None - if team_object is not None - else await _user_object_or_none( - valid_token=valid_token, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, - ) - ) - project_object: Final = ( - None - if valid_token.project_id is None - else await get_project_object( - project_id=valid_token.project_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, - ) - ) - return ( - key_models, - team_object.models if team_object is not None else (), - await _team_member_granted_models( - valid_token=valid_token, - team_object=team_object, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, - ), - user_object.models if user_object is not None else (), - project_object.models if project_object is not None else (), - ) - - async def collect_matched_model_access_groups( model: str | Sequence[str] | None, valid_token: UserAPIKeyAuth | None, diff --git a/litellm/proxy/auth/auth_utils.py b/litellm/proxy/auth/auth_utils.py index 9350c9c935c..161ff2fdfcd 100644 --- a/litellm/proxy/auth/auth_utils.py +++ b/litellm/proxy/auth/auth_utils.py @@ -1971,6 +1971,7 @@ _MODEL_ROUTING_COMPLETION_MODEL_ROUTE_MARKERS: Final = ("/evals",) # can_key_call_model() validates the real target model. _MODEL_ROUTING_SESSION_MODEL_ROUTE_MARKERS: Final = ( "/realtime/client_secrets", + "/realtime/translations/client_secrets", "/realtime/calls", ) _MODEL_ROUTING_ID_FIELDS: Final = ( diff --git a/litellm/proxy/auth/model_checks.py b/litellm/proxy/auth/model_checks.py index 4bcf020a9c4..73edcd66bd7 100644 --- a/litellm/proxy/auth/model_checks.py +++ b/litellm/proxy/auth/model_checks.py @@ -6,7 +6,7 @@ import copy import functools import itertools import re -from collections.abc import Callable, Mapping, Sequence +from collections.abc import Callable, Collection, Mapping, Sequence from concurrent.futures import ThreadPoolExecutor from types import MappingProxyType from typing import Final, TypeVar @@ -23,7 +23,12 @@ from litellm.router import Router from litellm.router_api import fallback_chain from litellm.types.router import CredentialLiteLLMParams, LiteLLM_Params from litellm.types.utils import LlmProviders -from litellm.utils import ProviderConfigManager, get_valid_models, potential_model_names_in_lookup_order +from litellm.utils import ( + AZURE_MODEL_PLACEHOLDER, + ProviderConfigManager, + get_valid_models, + potential_model_names_in_lookup_order, +) LLM_PROVIDER_PREFIXES: Final = frozenset(llm_provider.value for llm_provider in LlmProviders) _PROVIDERS_SENDING_THE_DEPLOYMENT_PATH_AS_THE_MODEL_ID: Final = frozenset({LlmProviders.TOGETHER_AI.value}) @@ -35,7 +40,9 @@ _CREDENTIAL_LITELLM_PARAM_FIELDS = set(CredentialLiteLLMParams.model_fields) _MODEL_LISTING_POOL: Final = ThreadPoolExecutor(thread_name_prefix="litellm-model-listing") -_PROVIDERS_LISTED_ONLY_THROUGH_A_DEPLOYMENT: Final = frozenset({LlmProviders.OPENROUTER.value}) +_PROVIDERS_LISTED_ONLY_THROUGH_A_DEPLOYMENT: Final = frozenset( + {LlmProviders.OPENROUTER.value, LlmProviders.HOSTED_VLLM.value} +) _Listed: Final = TypeVar("_Listed") @@ -373,6 +380,10 @@ def _ids_routing_to_catalog_models( catalog_ids: Sequence[str], routes_to_model: Callable[[str, str], bool], ) -> tuple[str, ...]: + if name_pattern.count("*") > deployment_pattern.count("*"): + return _catalog_ids_a_wider_name_matches( + name_pattern, deployment_pattern, provider, catalog_ids, routes_to_model + ) if name_pattern.count("*") != deployment_pattern.count("*") or _lists_name_fragments( name_pattern, deployment_pattern ): @@ -417,6 +428,23 @@ def _ids_routing_to_catalog_models( ) +def _catalog_ids_a_wider_name_matches( + name_pattern: str, + deployment_pattern: str, + provider: str, + catalog_ids: Sequence[str], + routes_to_model: Callable[[str, str], bool], +) -> tuple[str, ...]: + name_regex: Final = _wildcard_name_regex(name_pattern) + return tuple( + catalog_id + for catalog_id in _ids_routing_to_catalog_models( + deployment_pattern, deployment_pattern, provider, catalog_ids, routes_to_model + ) + if name_regex.fullmatch(catalog_id) + ) + + def _model_info_field(deployment: Mapping[str, object], field: str) -> object: model_info: Final = deployment.get("model_info") return model_info.get(field) if is_str_keyed_mapping(model_info) else None @@ -454,11 +482,12 @@ def _routes_to_model( return lambda listed_id, model: routed_models is None or model in routed_models(listed_id, team_id) -def _deployment_pattern_naming_listed_ids(wildcard_suffix: str, litellm_params: LiteLLM_Params | None) -> str | None: +def _deployment_pattern_naming_listed_ids(wildcard_model: str, litellm_params: LiteLLM_Params | None) -> str | None: if litellm_params is None or "/" not in litellm_params.model or not _check_wildcard_routing(litellm_params.model): return None + name_suffix: Final = wildcard_model.split("/", 1)[-1] deployment_suffix: Final = litellm_params.model.partition("/")[2] - return litellm_params.model if wildcard_suffix != "*" or deployment_suffix != "*" else None + return litellm_params.model if name_suffix != "*" or deployment_suffix != "*" else None def get_known_models_from_wildcard( @@ -466,6 +495,43 @@ def get_known_models_from_wildcard( litellm_params: LiteLLM_Params | None = None, routes_to_model: Callable[[str, str], bool] = lambda _listed_id, _model: True, ) -> list[str]: + provider_id_prefix: Final = _custom_llm_provider_prefix(wildcard_model, litellm_params) + if litellm_params is None or provider_id_prefix is None: + return list(_known_models_from_wildcard(wildcard_model, litellm_params, routes_to_model)) + return [ + listed_id.removeprefix(provider_id_prefix) + for listed_id in _known_models_from_wildcard( + wildcard_model, + litellm_params.model_copy(update={"model": f"{provider_id_prefix}{litellm_params.model}"}), + lambda listed_id, model: routes_to_model( + listed_id.removeprefix(provider_id_prefix), model.removeprefix(provider_id_prefix) + ), + ) + ] + + +def _custom_llm_provider_prefix(wildcard_model: str, litellm_params: LiteLLM_Params | None) -> str | None: + if ( + litellm_params is None + or not litellm_params.custom_llm_provider + or "/" in wildcard_model + or wildcard_model == "*" + or "/" in litellm_params.model + or not _check_wildcard_routing(litellm_params.model) + ): + return None + return f"{litellm_params.custom_llm_provider}/" + + +def _without_azure_placeholder(catalog_ids: Sequence[str]) -> tuple[str, ...]: + return tuple(catalog_id for catalog_id in catalog_ids if catalog_id != AZURE_MODEL_PLACEHOLDER) + + +def _known_models_from_wildcard( + wildcard_model: str, + litellm_params: LiteLLM_Params | None, + routes_to_model: Callable[[str, str], bool], +) -> tuple[str, ...]: wildcard_model_to_expand: Final = ( litellm_params.model if wildcard_model == "*" @@ -474,15 +540,14 @@ def get_known_models_from_wildcard( and "/" in litellm_params.model else wildcard_model ) - try: - wildcard_provider_prefix, wildcard_suffix = wildcard_model_to_expand.split("/", 1) - except ValueError: # safely fail - return [] deployment_pattern_naming_listed_ids: Final = ( wildcard_model_to_expand if wildcard_model_to_expand != wildcard_model - else _deployment_pattern_naming_listed_ids(wildcard_suffix, litellm_params) + else _deployment_pattern_naming_listed_ids(wildcard_model, litellm_params) ) + wildcard_provider_prefix, has_provider_prefix, wildcard_suffix = wildcard_model_to_expand.partition("/") + if not has_provider_prefix and deployment_pattern_naming_listed_ids is None: + return () # Use provider from litellm_params when available, otherwise from wildcard prefix # (e.g., "openai" from "openai/*" - needed for BYOK where wildcard isn't in router) @@ -499,16 +564,14 @@ def get_known_models_from_wildcard( wildcard_models = get_provider_models(provider=provider, litellm_params=litellm_params) if wildcard_models is None: - return [] + return () if deployment_pattern_naming_listed_ids is not None: - return list( - _ids_routing_to_catalog_models( - name_pattern=wildcard_model, - deployment_pattern=deployment_pattern_naming_listed_ids, - provider=provider, - catalog_ids=wildcard_models, - routes_to_model=routes_to_model, - ) + return _ids_routing_to_catalog_models( + name_pattern=wildcard_model, + deployment_pattern=deployment_pattern_naming_listed_ids, + provider=provider, + catalog_ids=wildcard_models if has_provider_prefix else _without_azure_placeholder(wildcard_models), + routes_to_model=routes_to_model, ) if wildcard_suffix != "*": model_prefix: Final = wildcard_suffix.replace("*", "") @@ -524,7 +587,7 @@ def get_known_models_from_wildcard( # add model prefix to wildcard models wildcard_models = [f"{model_prefix}{model.removeprefix(provider_id_prefix)}" for model in wildcard_models] - return list( + return tuple( dict.fromkeys(_under_wildcard_prefix(model, wildcard_provider_prefix, provider) for model in wildcard_models) ) @@ -562,9 +625,17 @@ def _names_no_deployment_serves_by_name( return tuple(name for name in names if not deployed_by_name(name, team_id)) +def _can_expand_to_an_allowed_name(wildcard_pattern: str, allowed_model_names: Collection[str] | None) -> bool: + if allowed_model_names is None: + return True + pattern: Final = _wildcard_name_regex(wildcard_pattern) + return any(pattern.match(name) for name in allowed_model_names) + + def expand_wildcard_deployments_for_model_info( deployments: list[dict[str, object]], llm_router: Router | None = None, + allowed_model_names: Collection[str] | None = None, ) -> list[dict[str, object]]: """Expand wildcard deployments into one row per known provider model. @@ -581,19 +652,11 @@ def expand_wildcard_deployments_for_model_info( raw_params = deployment.get("litellm_params") litellm_params_dict: dict[str, object] = raw_params if isinstance(raw_params, dict) else {} litellm_model = str(litellm_params_dict.get("model") or "") - - # Determine the wildcard pattern to expand. - # Branch order matters: only fall to litellm_model when model_name is - # also a wildcard, so a concrete model_name is never overwritten. - if _check_wildcard_routing(model_name) and ("/" in model_name or model_name == "*"): - wildcard_pattern = model_name - elif _check_wildcard_routing(model_name) and _check_wildcard_routing(litellm_model): - wildcard_pattern = litellm_model - elif _check_wildcard_routing(model_name): - wildcard_pattern = model_name - else: + if not _check_wildcard_routing(model_name): expanded.append(deployment) continue + if not _can_expand_to_an_allowed_name(model_name, allowed_model_names): + continue try: litellm_params = LiteLLM_Params.model_validate(litellm_params_dict) if litellm_params_dict else None @@ -601,7 +664,7 @@ def expand_wildcard_deployments_for_model_info( expanded.append(deployment) continue expanded_names = get_known_models_from_wildcard( - wildcard_model=wildcard_pattern, + wildcard_model=model_name, litellm_params=litellm_params, routes_to_model=_routes_to_model(routed_models, _deployment_team_id(deployment)), ) diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index a863de8b0f8..82135cb1b74 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -13,6 +13,7 @@ import re import secrets from collections.abc import Mapping, Sequence from datetime import datetime, timezone +from enum import Enum from types import MappingProxyType from typing import Final, NamedTuple, Protocol, Union, cast @@ -148,6 +149,7 @@ from litellm.proxy.common_utils.http_parsing_utils import ( # noqa: F401 # leg populate_request_with_path_params, read_raw_json_body, read_request_body, + resolve_realtime_route_model, rewrite_request_model, safe_get_request_headers, safe_get_request_query_params, @@ -1246,11 +1248,21 @@ def _apply_budget_limits_to_end_user_params( async def user_api_key_auth_websocket(websocket: WebSocket) -> UserAPIKeyAuth: - return await user_api_key_auth_websocket_for_model(websocket, model=websocket.query_params.get("model")) + return await user_api_key_auth_websocket_for_model(websocket, model=websocket.query_params.get("model", "")) + + +async def user_api_key_auth_realtime_websocket(websocket: WebSocket) -> UserAPIKeyAuth: + route_path: Final[object] = websocket.scope.get("path") + model: Final = resolve_realtime_route_model( + model=websocket.query_params.get("model"), + intent=websocket.query_params.get("intent"), + is_translation=isinstance(route_path, str) and route_path.endswith("/realtime/translations"), + ) + return await user_api_key_auth_websocket_for_model(websocket, model=model or "") async def user_api_key_auth_live_websocket(websocket: WebSocket) -> UserAPIKeyAuth: - return await user_api_key_auth_websocket_for_model(websocket, model=None) + return await user_api_key_auth_websocket_for_model(websocket, model="") def _has_required_baggage_tag_mapping() -> bool: @@ -1266,7 +1278,7 @@ def _has_required_baggage_tag_mapping() -> bool: async def user_api_key_auth_websocket_for_model( - websocket: WebSocket, model: str | None, *, close_on_auth_error: bool = True + websocket: WebSocket, model: str, *, close_on_auth_error: bool = True ) -> UserAPIKeyAuth: ws_scope: Final = websocket.scope or {} scope_headers: Final = list(ws_scope.get("headers") or []) @@ -1565,10 +1577,14 @@ _JWT_AUTH_DISABLED_HINT = ( ) +class _JWTKeyMappingFailure(Enum): + NO_ELIGIBLE_KEY = "JWT Key Mapping: No eligible existing virtual key for this identity. Access denied." + + class _PendingAutoRegister(NamedTuple): """ Signal returned by ``_resolve_jwt_to_virtual_key`` when the JWT's claim is - unmapped and ``unregistered_jwt_client_behavior`` is AUTO_REGISTER. + unmapped and ``unregistered_jwt_client_behavior`` is AUTO_REGISTER or LINK_ONLY. The caller MUST run standard ``JWTAuthManager.auth_builder`` to apply RBAC, scope mappings, ``custom_validate``, and ``user_allowed_email_domain`` @@ -1582,23 +1598,22 @@ class _PendingAutoRegister(NamedTuple): claim_value: str cache_key: str jwt_issuer: str | None = None + behavior: UnregisteredJWTClientBehavior = UnregisteredJWTClientBehavior.AUTO_REGISTER def _claim_identifies_user(jwt_handler: JWTHandler, claim_field: str, jwt_issuer: str | None) -> bool: - if not jwt_handler.litellm_jwtauth.auto_register_map_existing_key: - return False if jwt_handler.litellm_jwtauth.is_user_identity_claim(claim_field, jwt_issuer): return True verbose_proxy_logger.warning( - "JWT Key Mapping (auto_register_map_existing_key): claim '%s' is not the user_id or user_email JWT field " - "and may be shared by several users, so a new key is minted instead of reusing one the user owns.", + "JWT Key Mapping: claim '%s' is not the user_id or user_email JWT field " + "and may be shared by several users, so existing user keys cannot be linked automatically.", claim_field, ) return False async def _reusable_key_hash_for_user(prisma_client: PrismaClient, user_id: str, team_id: str | None) -> str | None: - key: Final = await VerificationTokenRepository(prisma_client).find_newest_reusable_llm_api_key(user_id, team_id) + key: Final = await VerificationTokenRepository(prisma_client).find_newest_reusable_key(user_id, team_id) return None if key is None else key.token @@ -1617,11 +1632,13 @@ async def _auto_register_jwt_mapping( org_id: str | None = None, end_user_id: str | None = None, agent_id: str | None = None, -) -> UserAPIKeyAuth | None: + behavior: UnregisteredJWTClientBehavior = UnregisteredJWTClientBehavior.AUTO_REGISTER, +) -> UserAPIKeyAuth | _JWTKeyMappingFailure | None: """ Auto-register: create a new virtual key + mapping for an unrecognised JWT claim value, or point the mapping at a key the resolved user already owns - when ``auto_register_map_existing_key`` is set. ``team_id`` and ``user_id`` + when ``auto_register_map_existing_key`` is set. LINK_ONLY always searches + for an existing key and rejects when none is eligible. ``team_id`` and ``user_id`` must come from a successful ``JWTAuthManager.auth_builder`` run — they encode the JWT identity AFTER RBAC/scope/custom_validate/email-domain policy has been enforced. The key @@ -1639,11 +1656,21 @@ async def _auto_register_jwt_mapping( generate_key_helper_fn, ) + link_only: Final = behavior == UnregisteredJWTClientBehavior.LINK_ONLY + reuse_existing: Final = link_only or jwt_handler.litellm_jwtauth.auto_register_map_existing_key existing_token_hash: Final = ( - await _reusable_key_hash_for_user(prisma_client, user_id, team_id) - if user_id is not None and _claim_identifies_user(jwt_handler, virtual_key_claim_field, jwt_issuer) + await _reusable_key_hash_for_user( + prisma_client, + user_id, + team_id, + ) + if reuse_existing + and user_id is not None + and _claim_identifies_user(jwt_handler, virtual_key_claim_field, jwt_issuer) else None ) + if link_only and existing_token_hash is None: + return _JWTKeyMappingFailure.NO_ELIGIBLE_KEY minted: Final = existing_token_hash is None if existing_token_hash is not None: token_hash = existing_token_hash @@ -1680,8 +1707,8 @@ async def _auto_register_jwt_mapping( "jwt_claim_name": virtual_key_claim_field, "jwt_claim_value": claim_value, "token": token_hash, - "created_by": "auto_register", - "updated_by": "auto_register", + "created_by": behavior.value, + "updated_by": behavior.value, } ) except Exception as e: @@ -1693,8 +1720,8 @@ async def _auto_register_jwt_mapping( # the DB and the cleartext is in memory on this request. Delete it # so orphans don't accumulate under sustained concurrency. verbose_proxy_logger.debug( - "JWT Key Mapping (auto_register): unique conflict on create — " - "deleting orphaned virtual key and fetching winner's mapping for %s='%s'.", + "JWT Key Mapping (%s): unique conflict on create, fetching winner's mapping for %s='%s'.", + behavior.value, virtual_key_claim_field, claim_value, ) @@ -1724,7 +1751,7 @@ async def _auto_register_jwt_mapping( raise HTTPException( status_code=503, detail=( - "JWT Key Mapping: AUTO_REGISTER race resolution failed — " + f"JWT Key Mapping: {behavior.value.upper()} race resolution failed — " "winner's mapping was concurrently removed. Retry the request." ), ) @@ -1738,7 +1765,8 @@ async def _auto_register_jwt_mapping( ) verbose_proxy_logger.info( - "JWT Key Mapping (auto_register): %s virtual key for %s='%s'.", + "JWT Key Mapping (%s): %s virtual key for %s='%s'.", + behavior.value, "created new" if minted else "mapped existing", virtual_key_claim_field, claim_value, @@ -1810,7 +1838,7 @@ async def _resolve_jwt_to_virtual_key( - ``UserAPIKeyAuth``: a resolved virtual key (cache hit or DB hit). The caller may use this directly; JWT policy has been enforced previously (at key-creation time or, for cached results, before caching). - - ``_PendingAutoRegister``: claim is unmapped and behavior is AUTO_REGISTER. + - ``_PendingAutoRegister``: claim is unmapped and behavior is AUTO_REGISTER or LINK_ONLY. The caller MUST run ``JWTAuthManager.auth_builder`` to enforce JWT policy (RBAC, scope, custom_validate, email-domain), then invoke ``_auto_register_jwt_mapping`` with the validated team_id/user_id. @@ -1818,7 +1846,7 @@ async def _resolve_jwt_to_virtual_key( The caller falls through to standard team-based JWT auth (which itself enforces full JWT policy via auth_builder). - Raises HTTPException: REJECT policy hit, missing claim under - REJECT/AUTO_REGISTER, or other policy violations. + REJECT/AUTO_REGISTER/LINK_ONLY, or other policy violations. """ raw_issuer: Final = jwt_claims.get(JWTHandler.LITELLM_JWT_ISSUER_CLAIM) normalized_issuer: Final = raw_issuer if isinstance(raw_issuer, str) else None @@ -1845,6 +1873,7 @@ async def _resolve_jwt_to_virtual_key( if behavior in ( UnregisteredJWTClientBehavior.REJECT, UnregisteredJWTClientBehavior.AUTO_REGISTER, + UnregisteredJWTClientBehavior.LINK_ONLY, ): raise HTTPException( status_code=403, @@ -1876,7 +1905,7 @@ async def _resolve_jwt_to_virtual_key( status_code=403, detail=f"JWT Key Mapping: No registered mapping for {virtual_key_claim_field}='{claim_value}'. Access denied.", ) - if behavior == UnregisteredJWTClientBehavior.AUTO_REGISTER: + if behavior in (UnregisteredJWTClientBehavior.AUTO_REGISTER, UnregisteredJWTClientBehavior.LINK_ONLY): # Stale sentinel written under a prior fallback_team_mapping config — # evict it and defer auto-register to after auth_builder runs. Raise # the same 500 as the fresh-path AUTO_REGISTER branch when there is @@ -1886,7 +1915,7 @@ async def _resolve_jwt_to_virtual_key( raise HTTPException( status_code=500, detail=( - "JWT Key Mapping: AUTO_REGISTER requires a database connection. " + f"JWT Key Mapping: {behavior.value.upper()} requires a database connection. " "Configure a database or change unregistered_jwt_client_behavior." ), ) @@ -1896,6 +1925,7 @@ async def _resolve_jwt_to_virtual_key( claim_value=str(claim_value), cache_key=cache_key, jwt_issuer=normalized_issuer, + behavior=behavior, ) return None elif cached_mapping is not None: @@ -1956,12 +1986,12 @@ async def _resolve_jwt_to_virtual_key( detail=f"JWT Key Mapping: No registered mapping for {virtual_key_claim_field}='{claim_value}'. Access denied.", ) - if behavior == UnregisteredJWTClientBehavior.AUTO_REGISTER: + if behavior in (UnregisteredJWTClientBehavior.AUTO_REGISTER, UnregisteredJWTClientBehavior.LINK_ONLY): if prisma_client is None: raise HTTPException( status_code=500, detail=( - "JWT Key Mapping: AUTO_REGISTER requires a database connection. " + f"JWT Key Mapping: {behavior.value.upper()} requires a database connection. " "Configure a database or change unregistered_jwt_client_behavior." ), ) @@ -1974,6 +2004,7 @@ async def _resolve_jwt_to_virtual_key( claim_value=str(claim_value), cache_key=cache_key, jwt_issuer=normalized_issuer, + behavior=behavior, ) # FALLBACK_TEAM_MAPPING (default): cache the miss and return None so the @@ -2466,10 +2497,13 @@ async def user_api_key_auth_builder( org_id=org_id, end_user_id=end_user_id, agent_id=agent_id, + behavior=pending_auto_register.behavior, ) if pending_auto_register is not None and prisma_client is not None else None ) + if isinstance(auto_registered, _JWTKeyMappingFailure): + raise HTTPException(status_code=403, detail=auto_registered.value) if auto_registered is not None: auto_registered.jwt_claims = jwt_claims auto_registered.user_email = user_email @@ -2485,7 +2519,13 @@ async def user_api_key_auth_builder( falls_through_to_key_checks: Final = ( auto_registered is not None - and jwt_handler.litellm_jwtauth.auto_register_map_existing_key + and ( + jwt_handler.litellm_jwtauth.auto_register_map_existing_key + or ( + pending_auto_register is not None + and pending_auto_register.behavior == UnregisteredJWTClientBehavior.LINK_ONLY + ) + ) and master_key is not None ) if not falls_through_to_key_checks: diff --git a/litellm/proxy/client/cli/commands/agents.py b/litellm/proxy/client/cli/commands/agents.py index 12d97ef6cce..b70432d1e72 100644 --- a/litellm/proxy/client/cli/commands/agents.py +++ b/litellm/proxy/client/cli/commands/agents.py @@ -770,9 +770,10 @@ def codex_model_catalog( A model Codex does not know gets the fallback entry, with the same base instructions Codex itself uses so the agent never runs without a system prompt, and offers the reasoning efforts `groups` gives its model group - that the installed Codex, at `client_version`, can parse. Apart from aliases, the catalog is - the one `/v1/models?client_version=...` serves, built from the installed Codex's own entries - instead of the proxy's vendored ones. + that the installed Codex, at `client_version`, can parse. Apart from aliases, and the window the + deployments' `model_info.max_input_tokens` gives a model Codex knows, the catalog is the one + `/v1/models?client_version=...` serves, built from the installed Codex's own entries instead of + the proxy's vendored ones. """ rows: Final = tuple(_codex_row(m, upstreams.get(m.id), groups) for m in models) body: Final = codex_models_response_json( diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py index 9282ee7f703..e812b03385d 100644 --- a/litellm/proxy/common_request_processing.py +++ b/litellm/proxy/common_request_processing.py @@ -30,6 +30,7 @@ import orjson from fastapi import HTTPException, Request, status from fastapi.responses import JSONResponse, Response, StreamingResponse from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError +from starlette.exceptions import HTTPException as StarletteHTTPException from starlette.types import Receive, Scope, Send from typing_extensions import Never @@ -54,6 +55,7 @@ from litellm.constants import ( from litellm.integrations.custom_guardrail import CustomGuardrail from litellm.integrations.otel.runtime import phase_event from litellm.litellm_core_utils.add_retry_fallback_headers import get_hidden_params_dict +from litellm.litellm_core_utils.agentic_followup_failure import is_agentic_followup_failure from litellm.litellm_core_utils.bug_report import ( allowlisted, bug_report_notice, @@ -93,6 +95,7 @@ from litellm.litellm_core_utils.streaming_handler import ( ) from litellm.litellm_core_utils.tool_fields import DropPolicy, MalformedField, drop_policy, resolve_tool_fields from litellm.proxy._types import LiteLLMRoutes, ProxyErrorTypes, ProxyException, UserAPIKeyAuth +from litellm.proxy.anthropic_endpoints.answered_status import is_provider_overload, with_openai_overload_status from litellm.proxy.auth.auth_checks import ( can_key_call_resolved_model, is_model_cost_zero, @@ -113,6 +116,7 @@ from litellm.proxy.common_utils.http_parsing_utils import ( ) from litellm.proxy.common_utils.openai_error_payload import ( LITELLM_CALL_ID_HEADER, + OverloadedProxyException, attribute_of, error_status_code, openai_error_param, @@ -131,13 +135,13 @@ from litellm.proxy.common_utils.sse_keepalive import ( from litellm.proxy.dd_span_tagger import DDSpanTagger from litellm.proxy.guardrails.auto_router_compression import arm_pre_call as _arm_auto_router_compression from litellm.proxy.hooks.parallel_request_limiter_v3 import get_or_create_request_stash +from litellm.proxy.hooks.proxy_track_cost_callback import failure_row_response_cost from litellm.proxy.native_compaction import with_proxy_compaction_executor from litellm.proxy.route_llm_request import ( endpoint_unsupported_by_model, route_request, ) from litellm.proxy.spend_tracking.cost_finalization import finalize_proxy_response_cost, prepare_response_cost -from litellm.proxy.spend_tracking.usage_capture import capture_proxy_response from litellm.proxy.telemetry.request_context import bind_call_id as bind_telemetry_call_id from litellm.proxy.utils import ( # noqa: F401 # legacy module exports ProxyLogging, @@ -162,6 +166,7 @@ _ChunkT: Final = TypeVar("_ChunkT") KNOWN_PROXY_ROUTES: Final = frozenset( route for member in LiteLLMRoutes for route in member.value if route.startswith("/") ) +_OPENAI_OVERLOAD_ROUTE_TYPES: Final = frozenset({"acompletion", "atext_completion", "aresponses"}) ProxyRouteType: TypeAlias = Literal[ "acompletion", @@ -170,7 +175,9 @@ ProxyRouteType: TypeAlias = Literal[ "_arealtime", "_aresponses_websocket", "acreate_realtime_client_secret", + "acreate_realtime_translation_client_secret", "arealtime_calls", + "arealtime_translation_calls", "aget_responses", "adelete_responses", "acancel_responses", @@ -269,6 +276,7 @@ if TYPE_CHECKING: ProxyConfig = _ProxyConfig else: ProxyConfig = Any +from litellm.proxy.anthropic_endpoints.answered_status import with_answered_status from litellm.proxy.anthropic_endpoints.streaming_model_restamp import ( AnthropicStreamModelRestamper, ) @@ -780,7 +788,7 @@ def resolve_counted_tool_fields( return resolved -def proxy_exception_from_http_exception(exc: HTTPException, headers: dict[str, str]) -> ProxyException: +def proxy_exception_from_http_exception(exc: StarletteHTTPException, headers: dict[str, str]) -> ProxyException: raw_detail: Final = attribute_of(exc, "detail", str(exc)) message, structured_fields = serialize_http_exception_detail(raw_detail) existing_fields: Final = getattr(exc, "provider_specific_fields", None) or {} @@ -1269,6 +1277,21 @@ def _sse_error_frames(error_obj: Mapping[str, object]) -> tuple[str, str]: return f"data: {json.dumps({'error': error_obj}, default=str)}\n\n", "data: [DONE]\n\n" +def _openai_late_failure_frames(exc: Exception) -> tuple[str, ...]: + _, error_obj = sse_error_payload(exc) + return _sse_error_frames(error_obj) + + +def _anthropic_late_failure_frames(exc: Exception) -> tuple[str, ...]: + answered: Final = proxy_exception_from_route_error(with_answered_status(exc)) + return ( + anthropic_error_sse_frame( + status_code=error_status_code(answered, status.HTTP_500_INTERNAL_SERVER_ERROR), + raw_message=answered.message, + ), + ) + + def _sse_stream_headers(headers: Mapping[str, str]) -> Mapping[str, str]: """`headers` plus the two that stop reverse proxies from buffering SSE (issue #28384).""" return MappingProxyType({**headers, **_TTFT_KEEPALIVE_HEADERS}) @@ -1517,6 +1540,7 @@ async def open_sse_before_first_byte( ping_interval_seconds: float | str | None, media_type: str = "text/event-stream", on_late_failure: Callable[[Exception], Awaitable[HTTPException | None]] | None = None, + late_failure_frames: Callable[[Exception], tuple[str, ...]] = _openai_late_failure_frames, ) -> _LateResponseT | StreamingResponse: """Write SSE keepalive comments while the upstream LLM call is still in flight. @@ -1562,8 +1586,7 @@ async def open_sse_before_first_byte( # would never fire and the failure would go unaudited. The hook # also gets to sanitize what reaches the client, by returning or # raising a replacement, so its answer decides the frame. - _, error_obj = sse_error_payload(await _sanitized_late_failure(exc, on_late_failure)) - for frame in _sse_error_frames(error_obj): + for frame in late_failure_frames(await _sanitized_late_failure(exc, on_late_failure)): yield frame.encode() return async for chunk in _relay_late_response(produced): @@ -1884,6 +1907,13 @@ def _response_cost_header_value(hidden_params: Mapping[str, object]) -> float | def cost_headers( response_cost: float | str | None, litellm_logging_obj: LiteLLMLoggingObj | None ) -> Mapping[str, str | None]: + if ( + response_cost == 0 + and litellm_logging_obj is not None + and litellm_logging_obj.prepared_cost is not None + and not litellm_logging_obj.prepared_cost.price_known + ): + return {} cost_breakdown: Final = _get_cost_breakdown_from_logging_obj( litellm_logging_obj=litellm_logging_obj, response_cost=response_cost ) @@ -2972,13 +3002,14 @@ class ProxyBaseLLMRequestProcessing: idle. See ``open_sse_before_first_byte``; unwrapped unless an operator sets ``litellm_settings.sse_keepalive_ping_interval_seconds``. """ + answers_as_anthropic: Final = route_type == "anthropic_messages" async def _audit_late_failure(exc: Exception) -> HTTPException | None: # Once a keepalive is on the wire this can no longer raise, so the # caller's `except` never runs its own post_call_failure_hook. return await proxy_logging_obj.post_call_failure_hook( user_api_key_dict=user_api_key_dict, - original_exception=exc, + original_exception=with_answered_status(exc) if answers_as_anthropic else exc, request_data=self.data, dispatched_call_type=self.route_type, ) @@ -3007,6 +3038,7 @@ class ProxyBaseLLMRequestProcessing: ), ping_interval_seconds=ttft_keepalive_interval(self.data, llm_router), on_late_failure=_audit_late_failure, + late_failure_frames=_anthropic_late_failure_frames if answers_as_anthropic else _openai_late_failure_frames, ) async def _process_llm_request( @@ -3367,9 +3399,6 @@ class ProxyBaseLLMRequestProcessing: ) ), ) - await capture_proxy_response( - logging_obj, response, background=_REQUEST_FIELDS.validate_python(self.data).get("background") is True - ) except (Exception, asyncio.CancelledError) as exc: _exception_raised = True if logging_obj.prepared_cost is not None: @@ -4372,27 +4401,28 @@ class ProxyBaseLLMRequestProcessing: version: str | None = None, ) -> Never: """Raises ProxyException (OpenAI API compatible) if an exception is raised""" - log_llm_api_exception(e, self.litellm_call_id) + answered: Final = with_openai_overload_status(e) if self.route_type in _OPENAI_OVERLOAD_ROUTE_TYPES else e + log_llm_api_exception(answered, self.litellm_call_id) billing_logging_obj: Final = _REQUEST_FIELDS.validate_python(self.data).get("litellm_logging_obj") + failed_in_agentic_follow_up: Final = is_agentic_followup_failure(e) # Allow callbacks to transform the error response transformed_exception: Final = await proxy_logging_obj.post_call_failure_hook( user_api_key_dict=user_api_key_dict, - original_exception=e, + original_exception=answered, request_data=self.data, dispatched_call_type=self.route_type, ) # Use transformed exception if callback returned one, otherwise use original - if transformed_exception is not None: - e = transformed_exception - litellm_debug_info: Final = getattr(e, "litellm_debug_info", "") + failure: Final = transformed_exception if transformed_exception is not None else answered + litellm_debug_info: Final = getattr(failure, "litellm_debug_info", "") verbose_proxy_logger.debug( "An error occurred: %s %s", - e, + failure, litellm_debug_info, ) timeout: Final = getattr( - e, "timeout", None + failure, "timeout", None ) # returns the timeout set by the wrapper. Used for testing if model-specific timeout are set correctly _litellm_logging_obj: Final = ( billing_logging_obj if isinstance(billing_logging_obj, LiteLLMLoggingObj) else None @@ -4410,7 +4440,9 @@ class ProxyBaseLLMRequestProcessing: model_id=model_id, version=version, response_cost=( - _litellm_logging_obj.finalized_cost.amount + failure_row_response_cost(self.data) + if failed_in_agentic_follow_up + else _litellm_logging_obj.finalized_cost.amount if isinstance(_litellm_logging_obj, LiteLLMLoggingObj) and _litellm_logging_obj.finalized_cost is not None else 0 @@ -4422,11 +4454,11 @@ class ProxyBaseLLMRequestProcessing: # a failed request reports no timing, matching /v1/chat/completions read_timing_from_logging_obj=False, ) - headers = getattr(e, "headers", None) or {} + headers = getattr(failure, "headers", None) or {} if not headers: - _response: Final = attribute_of(e, "response") + _response: Final = attribute_of(failure, "response") _response_headers: Final = getattr(_response, "headers", None) if _response is not None else None - _provider_headers: Final = _response_headers or getattr(e, "litellm_response_headers", None) + _provider_headers: Final = _response_headers or getattr(failure, "litellm_response_headers", None) if _provider_headers: headers = get_response_headers(dict(_provider_headers)) headers.update(custom_headers) @@ -4446,21 +4478,21 @@ class ProxyBaseLLMRequestProcessing: safe_headers: Final = {k: v for k, v in headers.items() if k.lower() not in UNSAFE_PROXY_RESPONSE_HEADERS} - self._apply_router_cooldown_retry_after(safe_headers, e) + self._apply_router_cooldown_retry_after(safe_headers, failure) - if isinstance(e, ProxyException): - e.headers = { - **{k: v for k, v in e.headers.items() if k.lower() not in UNSAFE_PROXY_RESPONSE_HEADERS}, + if isinstance(failure, ProxyException): + failure.headers = { + **{k: v for k, v in failure.headers.items() if k.lower() not in UNSAFE_PROXY_RESPONSE_HEADERS}, **{k: v if isinstance(v, str) else str(v) for k, v in safe_headers.items()}, } - raise e + raise failure - if isinstance(e, HTTPException): - raise proxy_exception_from_http_exception(e, safe_headers) - elif isinstance(e, httpx.HTTPStatusError): + if isinstance(failure, HTTPException): + raise proxy_exception_from_http_exception(failure, safe_headers) + elif isinstance(failure, httpx.HTTPStatusError): # Handle httpx.HTTPStatusError - extract actual error from response # This matches the original behavior before the refactor in commit 511d435f6f - http_status_error: Final[httpx.HTTPStatusError] = e + http_status_error: Final[httpx.HTTPStatusError] = failure error_body: Final = await http_status_error.response.aread() error_text: Final = error_body.decode("utf-8") @@ -4470,12 +4502,12 @@ class ProxyBaseLLMRequestProcessing: detail={"error": error_text}, headers=error_headers, ) - error_msg: Final = f"{e}" + error_msg: Final = f"{failure}" # Check for AttributeError in the exception chain. # The AttributeError may be wrapped in multiple layers # (e.g. AttributeError -> OpenAIException -> APIConnectionError), # so walk __cause__, __context__, and original_exception recursively. - has_attribute_error: Final = _has_attribute_error_in_chain(e) + has_attribute_error: Final = _has_attribute_error_in_chain(failure) if has_attribute_error: raise ProxyException( @@ -4490,12 +4522,12 @@ class ProxyBaseLLMRequestProcessing: # VertexAIError, etc.) all have a status_code attribute reflecting # the upstream API response. Use it to return the correct HTTP code # instead of defaulting to 500. - _exc_status_code: Final = getattr(e, "status_code", None) + _exc_status_code: Final = getattr(failure, "status_code", None) if _exc_status_code is not None and isinstance(_exc_status_code, int) and 400 <= _exc_status_code <= 599: _code = _exc_status_code else: _code = status.HTTP_500_INTERNAL_SERVER_ERROR - if should_report_bug(e): + if should_report_bug(failure): proxy_server_request: Final = self.data.get("proxy_server_request") request_url: Final = ( proxy_server_request.get("url") if isinstance(proxy_server_request, Mapping) else None @@ -4504,24 +4536,33 @@ class ProxyBaseLLMRequestProcessing: verbose_proxy_logger.error( bug_report_notice( build_proxy_bug_report( - e, + failure, call_type=allowlisted(request_path, KNOWN_PROXY_ROUTES), custom_llm_provider=self.data.get("custom_llm_provider"), stream=self.data.get("stream"), ) ) ) - client_message: Final = getattr(e, "message", error_msg) + client_message: Final = getattr(failure, "message", error_msg) + redacted_client_message: Final = redact_internal_details_from_client_message( + strip_bug_report_notice(client_message) if isinstance(client_message, str) else error_msg + ) + provider_specific_fields: Final = getattr( + failure, "provider_specific_fields", None + ) or relayed_provider_specific_fields(failure) + if self.route_type in _OPENAI_OVERLOAD_ROUTE_TYPES and is_provider_overload(failure): + raise OverloadedProxyException( + message=redacted_client_message, + headers=cast(dict[str, str], safe_headers), # cast-ok: ProxyException coerces header values to strings + provider_specific_fields=provider_specific_fields, + ) raise ProxyException( - message=redact_internal_details_from_client_message( - strip_bug_report_notice(client_message) if isinstance(client_message, str) else error_msg - ), - type=openai_error_type(e, _code), - param=openai_error_param(e), - openai_code=getattr(e, "code", None), + message=redacted_client_message, + type=openai_error_type(failure, _code), + param=openai_error_param(failure), + openai_code=getattr(failure, "code", None), code=_code, - provider_specific_fields=getattr(e, "provider_specific_fields", None) - or relayed_provider_specific_fields(e), + provider_specific_fields=provider_specific_fields, headers=safe_headers, ) @@ -4631,6 +4672,7 @@ class ProxyBaseLLMRequestProcessing: request: Request | None = None, flush_tail: Callable[[], bytes] | None = None, seal_open_frame: Callable[[bytes], str] | None = None, + answer_status: Callable[[Exception], Exception] | None = None, ) -> AsyncGenerator[str, None]: """ Shared streaming data generator: runs proxy iterator hook, per-chunk hook, @@ -4646,6 +4688,9 @@ class ProxyBaseLLMRequestProcessing: relays raw upstream bytes, so an upstream that hangs up mid-frame leaves the client inside an open frame, where an error frame would be swallowed or misparsed instead of raised. + + ``answer_status`` gives a failure the status the route answers it with + before the failure hook records it. """ verbose_proxy_logger.debug("inside generator") # Resolve per-stream (not per-chunk) whether the heavy per-chunk path @@ -4742,6 +4787,7 @@ class ProxyBaseLLMRequestProcessing: verbose_proxy_logger.exception( "litellm.proxy.proxy_server.async_data_generator(): Exception occured - %s", e ) + answered: Final = e if answer_status is None else answer_status(e) already_reported: Final = ( isinstance(stream_logging_obj, LiteLLMLoggingObj) and not stream_logging_obj.claim_stream_failure_report() @@ -4751,24 +4797,25 @@ class ProxyBaseLLMRequestProcessing: if already_reported else await proxy_logging_obj.post_call_failure_hook( user_api_key_dict=user_api_key_dict, - original_exception=e, + original_exception=answered, request_data=request_data, ) ) - if transformed_exception is not None: - e = transformed_exception + failure: Final = answered if transformed_exception is None else transformed_exception verbose_proxy_logger.debug( "An error occurred: %s", - e, + failure, ) - if isinstance(e, HTTPException): - raise e - stream_error_status: Final = error_status_code(e, status.HTTP_500_INTERNAL_SERVER_ERROR) + if isinstance(failure, HTTPException): + if failure is e: + raise + raise failure from e + stream_error_status: Final = error_status_code(failure, status.HTTP_500_INTERNAL_SERVER_ERROR) proxy_exception: Final = ProxyException( - message=redact_internal_details_from_client_message(getattr(e, "message", str(e))), - type=openai_error_type(e, stream_error_status), - param=openai_error_param(e), + message=redact_internal_details_from_client_message(getattr(failure, "message", str(failure))), + type=openai_error_type(failure, stream_error_status), + param=openai_error_param(failure), code=stream_error_status, ) stream_completed = True @@ -4824,6 +4871,7 @@ class ProxyBaseLLMRequestProcessing: request=request, flush_tail=None if restamper is None else restamper.flush, seal_open_frame=seal_open_sse_frame, + answer_status=with_answered_status, ) @overload diff --git a/litellm/proxy/common_utils/anthropic_error_payload.py b/litellm/proxy/common_utils/anthropic_error_payload.py new file mode 100644 index 00000000000..89001194f7f --- /dev/null +++ b/litellm/proxy/common_utils/anthropic_error_payload.py @@ -0,0 +1,172 @@ +"""Auth, budget and model-access failures are raised by ``user_api_key_auth`` before the Messages +handler runs, so the central handlers pick the Anthropic envelope from the request route.""" + +from collections.abc import Callable, Mapping +from types import MappingProxyType +from typing import Final + +from fastapi import Request, status +from fastapi.responses import JSONResponse +from starlette.types import Scope + +from litellm.anthropic_interface.exceptions import ( + ANTHROPIC_ERROR_TYPE_MAP, + AnthropicErrorDetail, + AnthropicErrorResponse, + AnthropicErrorType, + AnthropicExceptionMapping, +) +from litellm.proxy._types import ProxyException +from litellm.proxy.auth.auth_utils import get_request_route +from litellm.proxy.common_utils.error_body_call_id import error_body_call_id +from litellm.proxy.common_utils.openai_error_payload import LITELLM_CALL_ID_HEADER, openai_error_type_for_status + +ANTHROPIC_MESSAGES_ROUTES: Final[frozenset[str]] = frozenset( + { + "/v1/messages", + "/v1/messages/count_tokens", + "/claude_code_gateway/v1/messages", + "/claude_code_gateway/v1/messages/count_tokens", + } +) +ANTHROPIC_PASS_THROUGH_PREFIX: Final = "/anthropic/" +ANTHROPIC_SHAPED_MODEL_LIST_ROUTES: Final[frozenset[str]] = frozenset( + {"/v1/models", "/models", "/claude_code_gateway/v1/models"} +) +PROXY_ERROR_TYPE_BY_STATUS: Final[Mapping[int, AnthropicErrorType]] = MappingProxyType( + {**ANTHROPIC_ERROR_TYPE_MAP, 402: "billing_error", 409: "conflict_error", 504: "timeout_error"} +) + + +def proxy_error_type(status_code: int) -> AnthropicErrorType: + named: Final = PROXY_ERROR_TYPE_BY_STATUS.get(status_code) + if named is not None: + return named + if status_code == status.HTTP_408_REQUEST_TIMEOUT or not 400 <= status_code < 500: + return "api_error" + return "invalid_request_error" + + +def uses_anthropic_error_envelope(request: Request) -> bool: + route: Final = get_request_route(request) + if route in ANTHROPIC_MESSAGES_ROUTES or route.startswith(ANTHROPIC_PASS_THROUGH_PREFIX): + return True + return route in ANTHROPIC_SHAPED_MODEL_LIST_ROUTES and "anthropic-version" in request.headers + + +def route_error_content( + scope: Scope, anthropic_type: AnthropicErrorType, message: str, openai_content: Mapping[str, object] +) -> Mapping[str, object]: + request: Final = Request(scope) + if not uses_anthropic_error_envelope(request): + return openai_content + content: Final[AnthropicErrorResponse] = {"type": "error", "error": {"type": anthropic_type, "message": message}} + request_id: Final = request.headers.get("x-request-id") + return content if request_id is None else {**content, "request_id": request_id} + + +def anthropic_error_status_code(exc: ProxyException) -> int: + code: Final = exc.code + if code.isdigit(): + return int(code) + return status.HTTP_500_INTERNAL_SERVER_ERROR + + +def _with_provider_specific_fields(exc: ProxyException, detail: AnthropicErrorDetail) -> AnthropicErrorDetail: + if not exc.provider_specific_fields: + return detail + with_fields: Final[AnthropicErrorDetail] = {**detail, "provider_specific_fields": exc.provider_specific_fields} + return with_fields + + +def _with_litellm_error_type( + exc: ProxyException, status_code: int, detail: AnthropicErrorDetail +) -> AnthropicErrorDetail: + if not exc.type or exc.type in (detail["type"], openai_error_type_for_status(status_code)): + return detail + with_type: Final[AnthropicErrorDetail] = {**detail, "litellm_error_type": exc.type} + return with_type + + +def _with_call_id(detail: AnthropicErrorDetail, call_id: str | None) -> AnthropicErrorDetail: + if call_id is None: + return detail + with_call_id: Final[AnthropicErrorDetail] = {**detail, "litellm_call_id": call_id} + return with_call_id + + +def _anthropic_content( + exc: ProxyException, + status_code: int, + request_id: str | None, + general_settings: Mapping[str, object], + error_type: AnthropicErrorType | None, +) -> AnthropicErrorResponse: + envelope: Final = AnthropicExceptionMapping.transform_to_anthropic_error( + status_code=status_code, + raw_message=exc.message, + request_id=request_id, + error_type=error_type, + ) + body_call_id: Final = error_body_call_id(general_settings, exc.headers.get(LITELLM_CALL_ID_HEADER)) + content: Final[AnthropicErrorResponse] = { + **envelope, + "error": _with_call_id(_with_provider_specific_fields(exc, envelope["error"]), body_call_id), + } + return content + + +def anthropic_handler_error_content( + exc: ProxyException, + status_code: int, + request_id: str | None, + general_settings: Mapping[str, object], +) -> AnthropicErrorResponse: + return _anthropic_content(exc, status_code, request_id, general_settings, None) + + +def anthropic_error_content( + exc: ProxyException, + status_code: int, + request_id: str | None, + general_settings: Mapping[str, object], +) -> AnthropicErrorResponse: + content: Final = _anthropic_content(exc, status_code, request_id, general_settings, proxy_error_type(status_code)) + with_type: Final[AnthropicErrorResponse] = { + **content, + "error": _with_litellm_error_type(exc, status_code, content["error"]), + } + return with_type + + +def _anthropic_json_response( + exc: ProxyException, + request: Request, + build_content: Callable[[ProxyException, int, str | None, Mapping[str, object]], AnthropicErrorResponse], +) -> JSONResponse: + from litellm.proxy.proxy_server import ( + _close_dangling_otel_server_span, # pyright: ignore[reportPrivateUsage] # proxy_server keeps the span-close helper private; a JSONResponse returned instead of a raised error must stamp the OTel server span like the global ProxyException handler does + general_settings_view, + ) + + status_code: Final = anthropic_error_status_code(exc) + _close_dangling_otel_server_span(request, status_code, exc=exc) + content: Final = build_content(exc, status_code, request.headers.get("x-request-id"), general_settings_view()) + return JSONResponse(status_code=status_code, content=content, headers=exc.headers) + + +def anthropic_error_json_response(exc: ProxyException, request: Request) -> JSONResponse: + return _anthropic_json_response(exc, request, anthropic_error_content) + + +def anthropic_handler_error_json_response(exc: ProxyException, request: Request) -> JSONResponse: + return _anthropic_json_response(exc, request, anthropic_handler_error_content) + + +def anthropic_internal_server_error_response(request: Request) -> JSONResponse: + content: Final = AnthropicExceptionMapping.transform_to_anthropic_error( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + raw_message="Internal server error", + request_id=request.headers.get("x-request-id"), + ) + return JSONResponse(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, content=content) diff --git a/litellm/proxy/common_utils/auth_cache_invalidation_pubsub.py b/litellm/proxy/common_utils/auth_cache_invalidation_pubsub.py index b2640d2a765..edc8048ee73 100644 --- a/litellm/proxy/common_utils/auth_cache_invalidation_pubsub.py +++ b/litellm/proxy/common_utils/auth_cache_invalidation_pubsub.py @@ -183,7 +183,7 @@ def evict_local(cache_keys: Sequence[str], user_api_key_cache: "UserApiKeyCache" def _drop_from_memory(cache_key: str, user_api_key_cache: "UserApiKeyCache") -> None: - user_api_key_cache.in_memory_cache_for(cache_key).delete_cache(cache_key) + user_api_key_cache.delete_from_memory(cache_key) @with_service_target(AUTH_OBJECTS_TARGET) diff --git a/litellm/proxy/common_utils/claude_code_marketplace_auth.py b/litellm/proxy/common_utils/claude_code_marketplace_auth.py index 0cfb3061744..2cf9ae03327 100644 --- a/litellm/proxy/common_utils/claude_code_marketplace_auth.py +++ b/litellm/proxy/common_utils/claude_code_marketplace_auth.py @@ -1,10 +1,25 @@ from typing import Final +from fastapi import Request from pydantic import TypeAdapter, ValidationError +from litellm.types.proxy.auth.special_headers import SpecialHeaders + _AUTH_REQUIRED_SETTING: Final[TypeAdapter[bool | None]] = TypeAdapter(bool | None) +def marketplace_key_header_present(request: Request) -> bool: + """Recognize header credentials before an optional-auth archive chooses anonymity.""" + from litellm.proxy.proxy_server import general_settings_view + + configured_header: Final = general_settings_view().get("litellm_key_header_name") + return ( + SpecialHeaders.openai_authorization.value in request.headers + or SpecialHeaders.custom_litellm_api_key.value in request.headers + or (isinstance(configured_header, str) and configured_header in request.headers) + ) + + def marketplace_auth_required() -> bool: from litellm.proxy.proxy_server import general_settings_view diff --git a/litellm/proxy/common_utils/codex_model_catalog.py b/litellm/proxy/common_utils/codex_model_catalog.py index 63fb27d62cf..7b48aa07365 100644 --- a/litellm/proxy/common_utils/codex_model_catalog.py +++ b/litellm/proxy/common_utils/codex_model_catalog.py @@ -7,8 +7,10 @@ never the OpenAI list shape. This module builds that body from the rows ``/v1/mo lists: a model Codex knows keeps Codex's own entry for it, any other model gets the fallback entry Codex itself uses for an unknown slug, and ``model_info.service_tiers`` becomes the entry's ``service_tiers``, which Codex turns into slash commands (``/ultrafast``) that send ``service_tier`` -upstream. A fallback entry offers the model group's ``supported_reasoning_efforts`` as its reasoning -levels, trimmed to the ones the requesting Codex release can parse. +upstream. A ``model_info.max_input_tokens`` the operator sets replaces a known model's +``context_window``, up to the most Codex lets its own ``model_context_window`` raise that model to. +A fallback entry offers the model group's ``supported_reasoning_efforts`` as its reasoning levels, +trimmed to the ones the requesting Codex release can parse. The stock entries are Codex 0.159.3's bundled catalog, vendored unchanged from https://github.com/openai/codex/blob/rust-v0.159.3/codex-rs/models-manager/models.json (Apache-2.0) @@ -158,6 +160,7 @@ class CodexStockModel(LiteLLMBaseModel): supports_search_tool: bool = False supported_reasoning_levels: tuple[CodexReasoningLevel, ...] = () context_window: int | None = None + max_context_window: int | None = None class CodexStockCatalog(LiteLLMBaseModel): @@ -173,8 +176,9 @@ class CodexCatalogRow: """What the catalog needs to know about one listed model: its public id, the listing's mode and input limit, the upstream model behind it, the reasoning effort its deployments pin, and the `model_info` values the operator set; `service_tiers` holds one raw `model_info.service_tiers` - value per deployment behind the id, None where a deployment sets none. `supported_reasoning_efforts` - is the model group's, None when unknown.""" + value per deployment behind the id, None where a deployment sets none, and + `configured_max_input_tokens` one `model_info.max_input_tokens` per deployment the same way. + `supported_reasoning_efforts` is the model group's, None when unknown.""" id: str mode: str | None = None @@ -185,6 +189,7 @@ class CodexCatalogRow: service_tiers: tuple[object, ...] = () supported_reasoning_efforts: tuple[str, ...] | None = None search_tool_support: tuple[bool | None, ...] = () + configured_max_input_tokens: tuple[int | None, ...] = () @cache @@ -333,6 +338,25 @@ def _alias_context_window(row: CodexCatalogRow, stock_model: CodexStockModel) -> return MappingProxyType({"context_window": min(stock_model.context_window, row.max_input_tokens)}) +def _configured_window(row: CodexCatalogRow, stock_model: CodexStockModel) -> Mapping[str, int]: + """The `context_window` the operator's `model_info.max_input_tokens` gives a known model's entry, + or nothing, which keeps `stock_model`'s own. + + A request to the row can route to any of its deployments, so the window is the smallest one of them + takes: its `max_input_tokens` where the operator set a positive one, Codex's own window where not. A + limit set on only some deployments can therefore lower the window but never raise it. The window never + goes past `stock_model`'s `max_context_window`, the most Codex lets its own `model_context_window` + setting raise that model to.""" + per_deployment: Final = row.configured_max_input_tokens + declared: Final = tuple(limit for limit in per_deployment if limit is not None and limit > 0) + unset_window: Final = () if len(declared) == len(per_deployment) else (stock_model.context_window,) + if not declared or None in unset_window: + return MappingProxyType({}) + smallest: Final = min(limit for limit in (*declared, *unset_window) if limit is not None) + ceiling: Final = stock_model.max_context_window + return MappingProxyType({"context_window": smallest if ceiling is None else min(smallest, ceiling)}) + + def _alias_reasoning_level(row: CodexCatalogRow, stock_model: CodexStockModel) -> str | None: efforts: Final = frozenset(level.effort for level in stock_model.supported_reasoning_levels) return row.reasoning_effort if row.reasoning_effort in efforts else None @@ -398,6 +422,7 @@ def _entry( "upgrade": upgrade, **({} if search_tool is None else {"supports_search_tool": search_tool}), **(_deployment_defaults(row, stock_model) if is_alias and alias_defaults == "deployment" else {}), + **_configured_window(row, stock_model), } if configured is None: return stock_model.model_copy(update=listing) @@ -473,10 +498,12 @@ def codex_models_response_json( byte limit silently and keeps its bundled one, so the body holds only the entries that fit, the ones offering a service tier taken first and the rest in listing order, an entry too large for the bytes left passed over, every kept entry at its listing position; `byte_limit=None` - keeps every entry. A row listed under another name than the Codex model its `upstream_model` - names (an alias) takes that model's entry; `alias_defaults="deployment"` drops the defaults - Codex picks for that model in favor of what the alias's deployments pin, while `"codex"` keeps - them, as Codex would use them for the model's own name. `client_version` is the requesting Codex's version, which decides the reasoning + keeps every entry. A row whose deployments set `model_info.max_input_tokens` gets the smallest + window any of them takes as its known model's `context_window`, capped at that model's + `max_context_window`. A row listed under another name than the Codex model its `upstream_model` names (an alias) takes that model's + entry; `alias_defaults="deployment"` drops the defaults Codex picks for that model in favor of + what the alias's deployments pin, while `"codex"` keeps them, as Codex would use them for the + model's own name. `client_version` is the requesting Codex's version, which decides the reasoning levels a fallback entry may offer; None counts as a version too old for custom levels. """ known: Final = bundled_codex_models() if stock is None else stock @@ -519,6 +546,9 @@ def _catalog_row( search_tool_support=( registry.resolve(lookup_id, kind="search_tool_support", team_id=team_id) if registry is not None else () ), + configured_max_input_tokens=( + registry.group(lookup_id, field="max_input_tokens", team_id=team_id) if registry is not None else () + ), ) @@ -532,9 +562,9 @@ def codex_catalog_rows( """`rows` joined with the router's configured metadata, looked up by each entry's internal id so team-scoped rows resolve the way the Anthropic listing's display names do, a `model_group_alias` reading its target's deployments under its own name; `team_id` is the requesting key's team, so the - upstream model that picks Codex's stock entry and the tiers are read only off the deployments its - requests can route to, and the reasoning efforts are the ones `/model_group/info` reports for the - entry. Display names are read under `label_entries`' ids when given.""" + upstream model that picks Codex's stock entry, the tiers, and the configured input limits are read + only off the deployments its requests can route to, and the reasoning efforts are the ones + `/model_group/info` reports for the entry. Display names are read under `label_entries`' ids when given.""" lookup_ids: Final = MappingProxyType(dict(entries)) label_ids: Final = lookup_ids if label_entries is None else MappingProxyType(dict(label_entries)) return tuple( diff --git a/litellm/proxy/common_utils/fips.py b/litellm/proxy/common_utils/fips.py new file mode 100644 index 00000000000..1f8404fc37c --- /dev/null +++ b/litellm/proxy/common_utils/fips.py @@ -0,0 +1,89 @@ +from collections.abc import Mapping +from typing import Final + +from litellm.secret_managers.main import str_to_bool + +FIPS_MODE_SETTING: Final = "fips_mode" +_SETTING: Final = f"general_settings.{FIPS_MODE_SETTING}" + + +class FipsModeError(Exception): + pass + + +def _fips_mode_setting(general_settings: Mapping[str, object]) -> bool | None: + """general_settings.fips_mode as a boolean: False when the key is absent, None when it is not a boolean, including + a key with no value.""" + if FIPS_MODE_SETTING not in general_settings: + return False + value: Final = general_settings[FIPS_MODE_SETTING] + if isinstance(value, bool): + return value + return str_to_bool(value) if isinstance(value, str) else None + + +def openssl_enforces_fips() -> bool: + """Python's OpenSSL runs with FIPS-only defaults and itself refuses MD5.""" + try: + import _hashlib + + if _hashlib.get_fips_mode() != 1: + return False + except (ImportError, AttributeError, ValueError): + return False + try: + _hashlib.new("md5", b"", usedforsecurity=True) + except ValueError: + return True + return False + + +def cryptography_enforces_fips() -> bool: + """The cryptography library's own OpenSSL runs with FIPS-only defaults and its FIPS provider can hash SHA-256.""" + try: + from cryptography.exceptions import InternalError, UnsupportedAlgorithm + from cryptography.hazmat.bindings._rust import openssl as rust_openssl + from cryptography.hazmat.primitives import hashes + except ImportError: + return False + try: + if not rust_openssl.is_fips_enabled(): + return False + hashes.Hash(hashes.SHA256()).finalize() + except (AttributeError, InternalError, UnsupportedAlgorithm): + return False + return True + + +def fips_mode_refusal(general_settings: Mapping[str, object]) -> str | None: + """Why the proxy must not start: general_settings.fips_mode is not a boolean, or is on but Python's or the + cryptography library's OpenSSL does not enforce FIPS. None when it may start.""" + setting: Final = _fips_mode_setting(general_settings) + if setting is None: + value: Final = general_settings.get(FIPS_MODE_SETTING) + if value is None: + return ( + f"{_SETTING} has no value: it is empty, or an os.environ/ reference to a variable that is not set. " + "Set it to true or false, or remove it." + ) + return f"{_SETTING}={value!r} is not a boolean. Set it to true or false, or remove it." + if not setting: + return None + if not openssl_enforces_fips(): + return ( + f"{_SETTING} is on but OpenSSL does not enforce FIPS. Run the proxy on an OpenSSL with its FIPS " + f"provider active and default_properties = fips=yes, or turn {_SETTING} off." + ) + if not cryptography_enforces_fips(): + return ( + f"{_SETTING} is on but the cryptography library's OpenSSL has no working FIPS provider. Build it " + "against the system OpenSSL (pip install --no-binary cryptography cryptography), or turn " + f"{_SETTING} off." + ) + return None + + +def enforce_fips_mode(general_settings: Mapping[str, object]) -> None: + refusal: Final = fips_mode_refusal(general_settings) + if refusal is not None: + raise FipsModeError(refusal) diff --git a/litellm/proxy/common_utils/http_parsing_utils.py b/litellm/proxy/common_utils/http_parsing_utils.py index 81ff460613c..e210c337922 100644 --- a/litellm/proxy/common_utils/http_parsing_utils.py +++ b/litellm/proxy/common_utils/http_parsing_utils.py @@ -37,6 +37,16 @@ _DECODED_JSON: Final = TypeAdapter(object) _JSON_REQUEST_BODY: Final = TypeAdapter(Mapping[str, object]) +def resolve_realtime_route_model(model: str | None, intent: str | None, is_translation: bool) -> str | None: + if model is not None: + return model + if is_translation: + return "gpt-realtime-translate" + if intent == "transcription": + return "gpt-realtime-whisper" + return None + + def resolve_inference_model( body_model: object, settings: Mapping[str, object], @@ -197,10 +207,10 @@ def _parse_form_metadata(raw_metadata: str) -> object: """The JSON body path rejects a lone surrogate escape (``"\\ud800"``) with a 400 because no provider or database can encode it. ``json.loads`` accepts the escape, so the multipart ``metadata`` field gets the same check.""" - parsed: Final[object] = json.loads(raw_metadata) try: + parsed: Final[object] = json.loads(raw_metadata) json.dumps(parsed, ensure_ascii=False).encode("utf-8") - except UnicodeEncodeError as e: + except (json.JSONDecodeError, UnicodeEncodeError) as e: raise ProxyException( message=f"Invalid form payload: metadata {e}", type="invalid_request_error", @@ -210,6 +220,11 @@ def _parse_form_metadata(raw_metadata: str) -> object: return parsed +def _reraise_request_size_error(error: Exception) -> None: + if isinstance(error, HTTPException) and error.status_code == status.HTTP_413_CONTENT_TOO_LARGE: + raise error + + async def _read_form_data(request: Request) -> FormData: try: form_data: Final = await request.form() @@ -217,6 +232,7 @@ async def _read_form_data(request: Request) -> FormData: except ClientDisconnect: raise except Exception as e: + _reraise_request_size_error(e) # ``request.form()`` raises on malformed multipart (missing # boundary, malformed chunk encoding, …). Surface as 400 so # the auth-time pre-read does not silently cache ``{}`` while @@ -367,6 +383,7 @@ async def read_request_body(request: Request | None) -> dict: raise disconnected from e except Exception as e: # Catch unexpected errors to avoid crashes + _reraise_request_size_error(e) verbose_proxy_logger.exception("Unexpected error reading request body - %s", e) return {} @@ -572,14 +589,16 @@ async def get_form_data(request: Request) -> dict[str, Any]: Handles when OpenAI SDKs pass form keys as `timestamp_granularities[]="word"` instead of `timestamp_granularities=["word", "sentence"]` """ form: Final = await request.form() - parsed_form_data: Final[dict[str, Any]] = {} - for key, value in form.multi_items(): # not dict(form), which keeps only the last repeat - if key.endswith("[]"): - clean_key = key[:-2] - parsed_form_data.setdefault(clean_key, []).append(value) - else: - parsed_form_data[key] = value - return parsed_form_data + form_items: Final = tuple(form.multi_items() if hasattr(form, "multi_items") else form.items()) + array_keys: Final = frozenset(key[:-2] for key, _ in form_items if key.endswith("[]")) + normalized_items: Final = tuple((key.removesuffix("[]"), value) for key, value in form_items) + normalized_keys: Final = tuple(dict.fromkeys(key for key, _ in normalized_items)) + return { + key: [value for item_key, value in normalized_items if item_key == key] + if key in array_keys + else next(value for item_key, value in reversed(normalized_items) if item_key == key) + for key in normalized_keys + } async def convert_upload_files_to_file_data( @@ -802,10 +821,6 @@ def populate_request_with_path_params(request_data: dict, request: Request) -> d request_data["vector_store_ids"] = [value] continue request_data.setdefault(key, value) - verbose_proxy_logger.debug( - "populate_request_with_path_params: Found path_params, vector_store_ids=%s", - request_data.get("vector_store_ids"), - ) return request_data # Fallback: parse the URL path directly to extract vector_store_id @@ -841,7 +856,3 @@ def _add_vector_store_id_from_path(request_data: dict, request: Request) -> None existing_ids.append(vector_store_id) else: request_data["vector_store_ids"] = [vector_store_id] - verbose_proxy_logger.debug( - "populate_request_with_path_params: Updated request_data with vector_store_ids=%s", - request_data.get("vector_store_ids"), - ) diff --git a/litellm/proxy/common_utils/model_deprecation.py b/litellm/proxy/common_utils/model_deprecation.py index 21ad8cf1fde..8a91c7b0a0c 100644 --- a/litellm/proxy/common_utils/model_deprecation.py +++ b/litellm/proxy/common_utils/model_deprecation.py @@ -1,25 +1,31 @@ from __future__ import annotations -from collections.abc import Mapping, Sequence +import logging +from collections.abc import Callable, Mapping, Sequence from dataclasses import dataclass from datetime import date, datetime, timezone from itertools import groupby from types import MappingProxyType -from typing import TYPE_CHECKING, Final +from typing import TYPE_CHECKING, Final, TypeAlias import litellm from litellm._logging import verbose_logger +from litellm.litellm_core_utils.get_model_cost_map import AliasedCostEntry, GetModelCostMap from litellm.types.proxy.model_deprecation import ( DEFAULT_DEPRECATION_WARN_DAYS, DeprecationStatus, ModelDeprecationInfo, ModelDeprecationResponse, + SuccessorModelSource, ) if TYPE_CHECKING: from litellm.router import Router _NO_MODEL_METADATA: Final[Mapping[str, object]] = MappingProxyType({}) +_SHARED_SCHEDULE_PROVIDER: Final[Mapping[str, str]] = MappingProxyType({"azure_ai": "azure"}) + +LoadedCatalog: TypeAlias = Callable[[], Mapping[str, Mapping[str, object]]] @dataclass(frozen=True, slots=True) @@ -27,6 +33,9 @@ class _ResolvedDeprecation: deprecation_date: date litellm_model: str | None litellm_provider: str | None + copied_from_another_row: bool = False + successor_model: str | None = None + deprecation_source: str | None = None def _parse_deprecation_date(raw_value: object) -> date | None: @@ -42,25 +51,73 @@ def _parse_deprecation_date(raw_value: object) -> date | None: return None -def _successor_model(raw_value: object) -> str | None: - """A non-empty successor name, or None when the field is missing, blank, or not a string""" +def _non_empty_string(raw_value: object) -> str | None: + """A non-empty trimmed string, or None for missing, blank, or non-string fields""" return raw_value.strip() or None if isinstance(raw_value, str) else None -def _cost_map_lookup(model_key: object) -> _ResolvedDeprecation | None: - if not isinstance(model_key, str) or not model_key: +def _cost_map_lookup(model_key: str | None, catalog: Mapping[str, object]) -> _ResolvedDeprecation | None: + if model_key is None: return None entry: Final = litellm.model_cost.get(model_key) if not isinstance(entry, Mapping): return None - parsed: Final = _parse_deprecation_date(entry.get("deprecation_date")) + fields: Final[Mapping[str, object]] = entry + parsed: Final = _parse_deprecation_date(fields.get("deprecation_date")) if parsed is None: return None - provider: Final = entry.get("litellm_provider") + provider: Final = fields.get("litellm_provider") return _ResolvedDeprecation( deprecation_date=parsed, litellm_model=model_key, litellm_provider=provider if isinstance(provider, str) else None, + copied_from_another_row=isinstance(entry, AliasedCostEntry) + and "deprecation_date" not in entry.registered_fields + and model_key not in catalog, + successor_model=_non_empty_string(fields.get("successor_model")), + deprecation_source=_non_empty_string(fields.get("deprecation_source")), + ) + + +def _first_own_row(model_keys: Sequence[str | None], catalog: Mapping[str, object]) -> _ResolvedDeprecation | None: + found: Final = tuple( + resolved for resolved in (_cost_map_lookup(key, catalog) for key in model_keys) if resolved is not None + ) + return next((resolved for resolved in found if not resolved.copied_from_another_row), next(iter(found), None)) + + +def _deployment_provider(litellm_params: Mapping[str, object]) -> str | None: + declared: Final = litellm_params.get("custom_llm_provider") + if isinstance(declared, str) and declared: + return declared + model: Final = litellm_params.get("model") + prefix: Final = model.split("/", 1)[0] if isinstance(model, str) and "/" in model else None + return prefix if prefix in litellm.provider_list else None + + +def _provider_qualified(provider: str | None, model_key: str | None) -> str | None: + if provider is None or model_key is None or model_key.startswith(f"{provider}/"): + return None + return f"{provider}/{model_key}" + + +def _as_model_key(raw_value: object) -> str | None: + return raw_value if isinstance(raw_value, str) and raw_value else None + + +def _without_provider(provider: str | None, model_name: str | None) -> str | None: + if provider is None or model_name is None: + return model_name + return model_name.removeprefix(f"{provider}/") + + +def _schedule_keys(provider: str | None, model_name: str | None) -> tuple[str | None, ...]: + shared_provider: Final = _SHARED_SCHEDULE_PROVIDER.get(provider) if provider is not None else None + unprefixed: Final = _without_provider(provider, model_name) + return ( + _provider_qualified(provider, unprefixed), + _provider_qualified(shared_provider, unprefixed), + model_name, ) @@ -70,33 +127,39 @@ def _mapping_field(deployment: Mapping[str, object], key: str) -> Mapping[str, o def _resolve_deployment_deprecation( - deployment: Mapping[str, object], + deployment: Mapping[str, object], catalog: Mapping[str, object] ) -> _ResolvedDeprecation | None: """Resolve a deployment's deprecation date, preferring its explicit override""" model_info: Final = _mapping_field(deployment, "model_info") - raw_model: Final = _mapping_field(deployment, "litellm_params").get("model") + litellm_params: Final = _mapping_field(deployment, "litellm_params") + model_key: Final = _as_model_key(litellm_params.get("model")) + + provider: Final = _deployment_provider(litellm_params) + base_model: Final = _as_model_key(model_info.get("base_model")) + model_name: Final = model_key.split("/", 1)[1] if model_key is not None and "/" in model_key else model_key + picks: Final = tuple( + pick + for pick in ( + _first_own_row(_schedule_keys(provider, base_model), catalog), + _first_own_row( + (_provider_qualified(provider, model_key), model_key, *_schedule_keys(provider, model_name)), catalog + ), + ) + if pick is not None + ) + own_rows: Final = tuple(pick for pick in picks if not pick.copied_from_another_row) + from_catalog: Final = min(own_rows or picks, key=lambda pick: pick.deprecation_date, default=None) override: Final = _parse_deprecation_date(model_info.get("deprecation_date")) - if override is not None: - provider: Final = model_info.get("litellm_provider") - return _ResolvedDeprecation( - deprecation_date=override, - litellm_model=raw_model if isinstance(raw_model, str) else None, - litellm_provider=provider if isinstance(provider, str) else None, - ) - - unprefixed: Final = raw_model.split("/", 1)[1] if isinstance(raw_model, str) and "/" in raw_model else None - return next( - ( - resolved - for resolved in ( - _cost_map_lookup(model_info.get("base_model")), - _cost_map_lookup(raw_model), - _cost_map_lookup(unprefixed), - ) - if resolved is not None - ), - None, + if override is None: + return from_catalog + override_provider: Final = model_info.get("litellm_provider") + return _ResolvedDeprecation( + deprecation_date=override, + litellm_model=model_key, + litellm_provider=override_provider if isinstance(override_provider, str) else None, + successor_model=from_catalog.successor_model if from_catalog is not None else None, + deprecation_source=from_catalog.deprecation_source if from_catalog is not None else None, ) @@ -108,14 +171,20 @@ def _classify(days_until: int, warn_within_days: int) -> DeprecationStatus: return "upcoming" -def _checked_successor(model_name: str, model_info: Mapping[str, object], llm_router: Router) -> str | None: +def _checked_successor( + model_name: str, + model_info: Mapping[str, object], + llm_router: Router, + successor_log_level: int, +) -> str | None: """The deployment's successor_model as set, with a warning when no model in its team scope matches it""" - successor: Final = _successor_model(model_info.get("successor_model")) + successor: Final = _non_empty_string(model_info.get("successor_model")) if successor is None: return None team_id: Final = model_info.get("team_id") if not llm_router.registry().deployments(successor, team_id=team_id if isinstance(team_id, str) else None): - verbose_logger.warning( + verbose_logger.log( + successor_log_level, "model_deprecation: %s names successor %s, which matches no model group, alias, or wildcard route here", model_name, successor, @@ -124,52 +193,102 @@ def _checked_successor(model_name: str, model_info: Mapping[str, object], llm_ro def _build_info( - deployment: Mapping[str, object], llm_router: Router, today: date, warn_within_days: int -) -> ModelDeprecationInfo | None: + deployment: Mapping[str, object], + llm_router: Router, + today: date, + warn_within_days: int, + catalog: Mapping[str, object], + successor_log_level: int, +) -> _DeploymentInfo | None: model_name: Final = deployment.get("model_name") if not isinstance(model_name, str) or not model_name: return None - resolved: Final = _resolve_deployment_deprecation(deployment) + resolved: Final = _resolve_deployment_deprecation(deployment, catalog) if resolved is None: return None days_until: Final = (resolved.deprecation_date - today).days - return ModelDeprecationInfo( - model_name=model_name, - litellm_model=resolved.litellm_model, - deprecation_date=resolved.deprecation_date, - days_until_deprecation=days_until, - status=_classify(days_until, warn_within_days), - litellm_provider=resolved.litellm_provider, - successor_model=_checked_successor(model_name, _mapping_field(deployment, "model_info"), llm_router), + model_info: Final = _mapping_field(deployment, "model_info") + configured: Final = _checked_successor(model_name, model_info, llm_router, successor_log_level) + team_public_model_name_value: Final = model_info.get("team_public_model_name") + team_public_model_name: Final = ( + team_public_model_name_value + if isinstance(team_public_model_name_value, str) and team_public_model_name_value.strip() + else None + ) + return _DeploymentInfo( + info=ModelDeprecationInfo( + model_name=model_name, + team_public_model_name=team_public_model_name, + litellm_model=resolved.litellm_model, + deprecation_date=resolved.deprecation_date, + days_until_deprecation=days_until, + status=_classify(days_until, warn_within_days), + litellm_provider=resolved.litellm_provider, + successor_model=configured or resolved.successor_model, + successor_model_source=( + SuccessorModelSource.DEPLOYMENT_CONFIG + if configured is not None + else SuccessorModelSource.MODEL_COST_MAP + if resolved.successor_model + else None + ), + deprecation_source=resolved.deprecation_source, + ), + configured_successor=configured is not None, ) -def _merge_group(group: Sequence[ModelDeprecationInfo]) -> ModelDeprecationInfo: - """Keep the group's first deployment in config order, naming the first successor any of its deployments names""" - first: Final = group[0] - successors: Final = tuple(model.successor_model for model in group if model.successor_model is not None) +@dataclass(frozen=True, slots=True) +class _DeploymentInfo: + info: ModelDeprecationInfo + configured_successor: bool + + +def _merge_group(group: Sequence[_DeploymentInfo], successor_log_level: int) -> ModelDeprecationInfo: + """Keep the group's first deployment in config order, naming the first successor any of its deployments names, + a successor configured in model_info ahead of one the cost map supplies""" + first: Final = group[0].info + tiers: Final = tuple( + tuple( + deployment.info + for deployment in group + if deployment.configured_successor is configured and deployment.info.successor_model is not None + ) + for configured in (True, False) + ) + successors: Final = next((tier for tier in tiers if tier), ()) if not successors: return first - if len(frozenset(successors)) > 1: - verbose_logger.warning( + selected: Final = successors[0] + names: Final = frozenset(info.successor_model for info in successors if info.successor_model is not None) + if len(names) > 1: + verbose_logger.log( + successor_log_level, "model_deprecation: %s names several successors %s, reporting %s", first.model_name, - sorted(frozenset(successors)), - successors[0], + sorted(names), + selected.successor_model, ) - return first.model_copy(update={"successor_model": successors[0]}) + return first.model_copy( + update={ + "successor_model": selected.successor_model, + "successor_model_source": selected.successor_model_source, + "deprecation_source": selected.deprecation_source, + } + ) def _dedupe( - models: Sequence[ModelDeprecationInfo], + models: Sequence[_DeploymentInfo], + successor_log_level: int, ) -> tuple[ModelDeprecationInfo, ...]: """Report a model group carrying the same date on several deployments once""" - ordered: Final = sorted(models, key=lambda model: (model.model_name, model.deprecation_date)) + ordered: Final = sorted(models, key=lambda model: (model.info.model_name, model.info.deprecation_date)) return tuple( - _merge_group(tuple(group)) - for _, group in groupby(ordered, key=lambda model: (model.model_name, model.deprecation_date)) + _merge_group(tuple(group), successor_log_level) + for _, group in groupby(ordered, key=lambda model: (model.info.model_name, model.info.deprecation_date)) ) @@ -182,15 +301,19 @@ def _bucket(models: Sequence[ModelDeprecationInfo], status: DeprecationStatus) - ) -def _collect_from_router(llm_router: Router, today: date, warn_within_days: int) -> tuple[ModelDeprecationInfo, ...]: +def _collect_from_router( + llm_router: Router, + today: date, + warn_within_days: int, + catalog: Mapping[str, object], + successor_log_level: int, +) -> tuple[ModelDeprecationInfo, ...]: deployments: Final = llm_router.registry().deployments() or () - deduped: Final = _dedupe( - tuple( - info - for info in (_build_info(deployment, llm_router, today, warn_within_days) for deployment in deployments) - if info is not None - ) + infos: Final = ( + _build_info(deployment, llm_router, today, warn_within_days, catalog, successor_log_level) + for deployment in deployments ) + deduped: Final = _dedupe(tuple(info for info in infos if info is not None), successor_log_level) verbose_logger.debug( "model_deprecation: %d/%d deployments carry a deprecation date", @@ -204,12 +327,16 @@ def collect_model_deprecations( llm_router: Router | None, warn_within_days: int = DEFAULT_DEPRECATION_WARN_DAYS, today: date | None = None, + loaded_catalog: LoadedCatalog = GetModelCostMap.loaded_model_cost_map, + successor_log_level: int = logging.WARNING, ) -> ModelDeprecationResponse: """Bucket every deployment carrying a deprecation date by how urgent it is""" snapshot_time: Final = datetime.now(timezone.utc) effective_today: Final = today or snapshot_time.date() deduped: Final = ( - _collect_from_router(llm_router, effective_today, warn_within_days) if llm_router is not None else () + _collect_from_router(llm_router, effective_today, warn_within_days, loaded_catalog(), successor_log_level) + if llm_router is not None + else () ) return ModelDeprecationResponse( diff --git a/litellm/proxy/common_utils/openai_error_payload.py b/litellm/proxy/common_utils/openai_error_payload.py index a948c390375..26369bf3f87 100644 --- a/litellm/proxy/common_utils/openai_error_payload.py +++ b/litellm/proxy/common_utils/openai_error_payload.py @@ -17,6 +17,7 @@ from litellm.proxy.db.db_lookup_gate import DBLookupDeadlineExceeded from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler, exception_chain LITELLM_CALL_ID_HEADER: Final = "x-litellm-call-id" +_SERVER_IS_OVERLOADED_CODE: Final = "server_is_overloaded" _OPENAI_ERROR_TYPE_BY_STATUS: Final[Mapping[int, str]] = MappingProxyType( { @@ -44,6 +45,31 @@ _FAILOVER_REFUSALS: Final = ( ) +class OverloadedProxyException(ProxyException): + def __init__( + self, + message: str, + headers: dict[str, str] | None, # mutable-ok: matches ProxyException's constructor + provider_specific_fields: dict[str, object] | None, # mutable-ok: matches ProxyException's constructor + ) -> None: + super().__init__( # pyright: ignore[reportUnknownMemberType] # ProxyException omits generic arguments + message=message, + type="service_unavailable_error", + param=None, + code=status.HTTP_503_SERVICE_UNAVAILABLE, + headers=None if headers is None else dict(headers), + provider_specific_fields=provider_specific_fields, + ) + + def to_dict(self) -> dict[str, object]: # mutable-ok: matches ProxyException.to_dict + return { + **_ERROR_BODY.validate_python( + super().to_dict() # pyright: ignore[reportUnknownMemberType] # ProxyException omits generic arguments + ), + "code": _SERVER_IS_OVERLOADED_CODE, + } + + def attribute_of(value: object, name: str, default: object = None) -> object: return getattr(value, name, default) diff --git a/litellm/proxy/common_utils/realtime_utils.py b/litellm/proxy/common_utils/realtime_utils.py index c641748843e..d4fd4556ed4 100644 --- a/litellm/proxy/common_utils/realtime_utils.py +++ b/litellm/proxy/common_utils/realtime_utils.py @@ -1,3 +1,4 @@ +import json from functools import lru_cache from typing import Final @@ -10,7 +11,7 @@ def realtime_request_body(model: str | None) -> bytes: Generate the realtime websocket request body. Cached with LRU semantics to avoid repeated string formatting work while keeping memory usage bounded. """ - return f'{{"model": "{model or ""}"}}'.encode() + return json.dumps({"model": model}).encode() _realtime_request_body: Final = realtime_request_body diff --git a/litellm/proxy/common_utils/token_count_settings.py b/litellm/proxy/common_utils/token_count_settings.py index dd04e531f2d..4e3059cfe26 100644 --- a/litellm/proxy/common_utils/token_count_settings.py +++ b/litellm/proxy/common_utils/token_count_settings.py @@ -56,6 +56,22 @@ class TokenCountSettings: framing: int | None count_model: TokenCountModel | None tokenizer: TokenCountTokenizer | None = None + tool_framing: int | None = None + responses_framing: int | None = None + responses_tool_framing: int | None = None + + @property + def frames_counts(self) -> bool: + return any( + framing is not None + for framing in (self.framing, self.tool_framing, self.responses_framing, self.responses_tool_framing) + ) + + def hidden_prompt_tokens(self, carries_tools: bool, responses_api: bool) -> int: + chat: Final = self.tool_framing if carries_tools else None + responses: Final = self.responses_tool_framing if carries_tools else self.responses_framing + narrower: Final = responses if responses_api else chat + return (narrower if narrower is not None else self.framing) or 0 @dataclass(frozen=True, slots=True) @@ -105,6 +121,15 @@ def _framing(value: object) -> int | None: return None +def _first_framing(source: Mapping[str, object], keys: tuple[str, ...]) -> int | None: + return next((framing for framing in map(_framing, map(source.get, keys)) if framing is not None), None) + + +def _configured_framing(configured: Mapping[str, object], default: Mapping[str, object], *keys: str) -> int | None: + operator_sets_one: Final = _first_framing(configured, (*keys, "token_count_framing")) is not None + return _first_framing(configured if operator_sets_one else default, keys) + + def _non_blank(value: object) -> str | None: return value if isinstance(value, str) and value.strip() else None @@ -175,13 +200,21 @@ def _tokenizer(value: object) -> TokenCountTokenizer | None: def resolve_token_count_settings( configured: Mapping[str, object], default: Mapping[str, object], deployment_region: Callable[[], str] ) -> TokenCountSettings: - framing: Final = _framing(configured.get("token_count_framing")) return TokenCountSettings( - framing=framing if framing is not None else _framing(default.get("token_count_framing")), + framing=_configured_framing(configured, default, "token_count_framing"), count_model=_resolved_count_model( configured.get("token_count_model"), default.get("token_count_model"), deployment_region ), tokenizer=_tokenizer(default.get("token_count_tokenizer")), + tool_framing=_configured_framing(configured, default, "token_count_tool_framing"), + responses_framing=_configured_framing(configured, default, "token_count_responses_framing"), + responses_tool_framing=_configured_framing( + configured, + default, + "token_count_responses_tool_framing", + "token_count_responses_framing", + "token_count_tool_framing", + ), ) diff --git a/litellm/proxy/common_utils/user_api_key_cache.py b/litellm/proxy/common_utils/user_api_key_cache.py index e64fd755ef9..a2272c3f73d 100644 --- a/litellm/proxy/common_utils/user_api_key_cache.py +++ b/litellm/proxy/common_utils/user_api_key_cache.py @@ -24,6 +24,7 @@ T = TypeVar("T", bound=BaseModel) from litellm.constants import AUTH_OBJECTS_TARGET as AUTH_OBJECTS_TARGET # noqa: E402, PLC0414 # public re-export _HASHED_TOKEN_CACHE_KEY: Final = re.compile(r"[0-9a-f]{64}") +_BUDGET_WINDOWS_ABSENT_PREFIX: Final = "budget_windows_absent:" def is_user_key_cache_key(key: str) -> bool: @@ -70,6 +71,7 @@ class UserApiKeyCache(DualCache): default_in_memory_ttl: float | None = None, default_redis_ttl: float | None = None, key_object_in_memory_cache: InMemoryCache | None = None, + budget_windows_absent_in_memory_cache: InMemoryCache | None = None, ) -> None: super().__init__( in_memory_cache=in_memory_cache, @@ -83,19 +85,33 @@ class UserApiKeyCache(DualCache): default_in_memory_ttl=default_in_memory_ttl, default_redis_ttl=default_redis_ttl, ) + self.budget_windows_absent_cache: Final = DualCache( + in_memory_cache=budget_windows_absent_in_memory_cache + or InMemoryCache(default_ttl=DEFAULT_MANAGEMENT_OBJECT_IN_MEMORY_CACHE_TTL), + default_in_memory_ttl=default_in_memory_ttl, + ) def in_memory_cache_for(self, key: str) -> InMemoryCache: return self.key_object_cache.in_memory_cache if is_user_key_cache_key(key) else self.in_memory_cache + def delete_from_memory(self, key: str) -> None: + self.in_memory_cache_for(key).delete_cache(key) + if key.startswith(_BUDGET_WINDOWS_ABSENT_PREFIX): + self.budget_windows_absent_cache.delete_cache(key) + def update_cache_ttl(self, default_in_memory_ttl: float | None, default_redis_ttl: float | None) -> None: super().update_cache_ttl(default_in_memory_ttl=default_in_memory_ttl, default_redis_ttl=default_redis_ttl) self.key_object_cache.update_cache_ttl( default_in_memory_ttl=default_in_memory_ttl, default_redis_ttl=default_redis_ttl ) + self.budget_windows_absent_cache.update_cache_ttl( + default_in_memory_ttl=default_in_memory_ttl, default_redis_ttl=None + ) def update_in_memory_max_size(self, max_size: int | None) -> None: super().update_in_memory_max_size(max_size) self.key_object_cache.update_in_memory_max_size(max_size) + self.budget_windows_absent_cache.update_in_memory_max_size(max_size) def attach_redis_cache( self, redis_cache: RedisCache | None = None, *, default_redis_ttl: float | None = None @@ -272,6 +288,7 @@ class UserApiKeyCache(DualCache): def flush_cache(self) -> None: super().flush_cache() self.key_object_cache.in_memory_cache.flush_cache() + self.budget_windows_absent_cache.flush_cache() async def async_set_cache_pipeline( self, cache_list: Sequence[tuple[str, object]], local_only: bool = False, **kwargs: object @@ -400,6 +417,11 @@ def team_membership_reservation_cache_key(user_id: str, team_id: str) -> str: NO_TEAM_MEMBERSHIP_SENTINEL: Final = "__no_team_membership__" +def budget_windows_absent_cache_key(entity_type: str, entity_id: str) -> str: + """Cache key marking a key or team that holds no budget windows, so the spend fallback skips its row read.""" + return f"{_BUDGET_WINDOWS_ABSENT_PREFIX}{entity_type}:{entity_id}" + + def get_management_object_ttl(cache: DualCache) -> float: """ In-memory TTL for management-object cache writes (keys, teams, users, budgets, ...). diff --git a/litellm/proxy/config_resolvers/alerting.py b/litellm/proxy/config_resolvers/alerting.py index 4de7197f88b..1d7fbe0fffa 100644 --- a/litellm/proxy/config_resolvers/alerting.py +++ b/litellm/proxy/config_resolvers/alerting.py @@ -11,6 +11,7 @@ from typing import Final from litellm.proxy.config_resolvers._descriptors import FieldDescriptor EMAIL_DESCRIPTORS: Final[tuple[FieldDescriptor, ...]] = ( + FieldDescriptor("PROXY_BASE_URL", "PROXY_BASE_URL", "PROXY_BASE_URL"), FieldDescriptor("SMTP_HOST", "SMTP_HOST", "SMTP_HOST"), FieldDescriptor("SMTP_PORT", "SMTP_PORT", "SMTP_PORT", default="587"), FieldDescriptor("SMTP_TLS", "SMTP_TLS", "SMTP_TLS", default="True"), diff --git a/litellm/proxy/config_resolvers/settings_store.py b/litellm/proxy/config_resolvers/settings_store.py index 70486be0068..3be66821915 100644 --- a/litellm/proxy/config_resolvers/settings_store.py +++ b/litellm/proxy/config_resolvers/settings_store.py @@ -42,10 +42,12 @@ _EMPTY_ROWS: Final[Mapping[DbRow, Mapping[str, JsonValue]]] = MappingProxyType({ class SettingsStore(MutableMapping[str, JsonValue]): - def __init__(self, section: Section) -> None: + def __init__(self, section: Section, *, managed_db_keys: frozenset[str] | None = None) -> None: self._section: Final = section + self._managed_db_keys: Final = managed_db_keys self._yaml_values: Mapping[str, JsonValue] = _EMPTY_VALUES self._database_rows: Mapping[DbRow, Mapping[str, JsonValue]] = _EMPTY_ROWS + self._unmanaged_db_keys: frozenset[str] = frozenset() self._runtime_values: Mapping[str, JsonValue] = _EMPTY_VALUES self._deleted_runtime_keys: frozenset[str] = frozenset() @@ -77,15 +79,24 @@ class SettingsStore(MutableMapping[str, JsonValue]): return self.owned_by_config(key) and self._db_value_is_shadowed(key) def apply_db_row(self, row: DbRow, db_row: Mapping[str, JsonValue]) -> None: + applied_row: Final = MappingProxyType({key: db_row[key] for key in db_row if self._db_manages(row, key)}) previous_row: Final = self._database_rows.get(row, _EMPTY_VALUES) changed: Final = frozenset( key - for key in (*previous_row, *db_row) - if previous_row.get(key, ABSENT) != db_row.get(key, ABSENT) # pyright: ignore[reportUnknownArgumentType] # JsonValue vs Absent compare + for key in (*previous_row, *applied_row) + if previous_row.get(key, ABSENT) != applied_row.get(key, ABSENT) # pyright: ignore[reportUnknownArgumentType] # JsonValue vs Absent compare ) - self._database_rows = MappingProxyType({**self._database_rows, row: MappingProxyType(dict(db_row))}) + self._database_rows = MappingProxyType({**self._database_rows, row: applied_row}) + if row == self._section: + self._unmanaged_db_keys = frozenset(key for key in db_row if key not in applied_row) self._clear_runtime_keys(changed) + def unmanaged_db_keys(self) -> tuple[str, ...]: + return tuple(sorted(self._unmanaged_db_keys)) + + def _db_manages(self, row: DbRow, key: str) -> bool: + return row != self._section or self._managed_db_keys is None or key in self._managed_db_keys + def resolved(self) -> Mapping[str, JsonValue]: return MappingProxyType(dict(self)) diff --git a/litellm/proxy/credential_endpoints/endpoints.py b/litellm/proxy/credential_endpoints/endpoints.py index 5b3507f9b6d..86e716f19e3 100644 --- a/litellm/proxy/credential_endpoints/endpoints.py +++ b/litellm/proxy/credential_endpoints/endpoints.py @@ -920,8 +920,6 @@ def update_db_credential( # update model info if encrypted_credential.credential_info: """Update credential info""" - if "credential_info" not in merged_credential.credential_info: - merged_credential.credential_info = {} merged_credential.credential_info.update(encrypted_credential.credential_info) return merged_credential diff --git a/litellm/proxy/db/accounting_ledger.py b/litellm/proxy/db/accounting_ledger.py deleted file mode 100644 index 0a9c5db1619..00000000000 --- a/litellm/proxy/db/accounting_ledger.py +++ /dev/null @@ -1,352 +0,0 @@ -from __future__ import annotations - -import hashlib -import json -from collections.abc import AsyncGenerator, Callable -from contextlib import AbstractAsyncContextManager, asynccontextmanager -from dataclasses import dataclass -from datetime import datetime, timedelta, timezone -from typing import TYPE_CHECKING, Final, Literal, TypeAlias - -from pydantic import AwareDatetime, ConfigDict, JsonValue, TypeAdapter -from typing_extensions import assert_never - -from litellm.accounting import CostEvent, DeliveryTarget, EventKind, InboundUsageEvent, OutboundUsageEvent -from litellm.proxy.db.db_span import db_span -from litellm.proxy.db.routing_prisma_wrapper import writer_wrapper - -if TYPE_CHECKING: - from prisma import Prisma - - from litellm.proxy.utils import PrismaClient - -AccountingEvent: TypeAlias = InboundUsageEvent | OutboundUsageEvent | CostEvent -_JSON: Final = TypeAdapter(dict[str, JsonValue]) -_INSTANT: Final[TypeAdapter[datetime]] = TypeAdapter(AwareDatetime) -_STRINGS: Final = TypeAdapter(tuple[dict[str, str], ...]) -_TIMEOUT: Final = timedelta(seconds=10) - - -class AccountingConflictError(ValueError): - pass - - -@dataclass(frozen=True, slots=True) -class UsageWrite: - event: InboundUsageEvent | OutboundUsageEvent - envelope: str - targets: tuple[DeliveryTarget, ...] = () - - -_Transaction: TypeAlias = AbstractAsyncContextManager["Prisma"] - - -@dataclass(frozen=True, slots=True) -class _AcceptedEvent: - event_id: str - kind: EventKind - source_event_id: str | None - occurred_at: datetime - payload: str - payload_hash: str - targets: tuple[str, ...] - schema_version: int - version: int - - -def _json(value: object) -> str: - return json.dumps(value, sort_keys=True, separators=(",", ":"), allow_nan=False) - - -def _prepare( - event: AccountingEvent, - targets: tuple[DeliveryTarget, ...], - envelope: str, - schema_version: int, - version: int, -) -> _AcceptedEvent: - if type(schema_version) is not int or type(version) is not int or min(schema_version, version) < 1: - raise ValueError("Accounting versions must be positive integers") - validated: Final = type(event).model_validate_json(event.model_dump_json()) - payload: Final = _JSON.validate_json(envelope) - if payload.get("event") != validated.model_dump(mode="json"): - raise ValueError("Accounting envelope must contain the matching public event") - destinations: Final = tuple(sorted(frozenset(DeliveryTarget(target).value for target in targets))) - serialized: Final = _json(payload) - identity: Final = _json((schema_version, version, destinations, payload)) - kind: Final = ( - EventKind.COST - if isinstance(validated, CostEvent) - else EventKind.INBOUND_USAGE - if isinstance(validated, InboundUsageEvent) - else EventKind.OUTBOUND_USAGE - ) - return _AcceptedEvent( - event_id=validated.event_id, - kind=kind, - source_event_id=validated.usage_event_id if isinstance(validated, CostEvent) else None, - occurred_at=validated.occurred_at if isinstance(validated, CostEvent) else validated.ended_at, - payload=serialized, - payload_hash=hashlib.sha256(identity.encode()).hexdigest(), - targets=destinations, - schema_version=schema_version, - version=version, - ) - - -_INSERT_EVENT: Final = """ -INSERT INTO "LiteLLM_AccountingEvent" - (event_id, kind, source_event_id, schema_version, payload_hash, occurred_at, payload) -VALUES ($1, $2::"AccountingEventKind", $3, $4::int, $5, $6::timestamp, $7::jsonb) -ON CONFLICT (event_id) DO NOTHING RETURNING event_id -""" -_INSERT_DELIVERIES: Final = """ -INSERT INTO "LiteLLM_AccountingDelivery" (event_id, target, version) -SELECT $1, value::"AccountingDeliveryTarget", $3::int FROM jsonb_array_elements_text($2::jsonb) -""" -_LOCK_SOURCE: Final = """ -SELECT event_id FROM "LiteLLM_AccountingEvent" -WHERE event_id = $1 AND kind = 'outbound_usage' FOR UPDATE -""" -_EXISTING_COST: Final = """ -SELECT event_id FROM "LiteLLM_AccountingEvent" WHERE kind = 'cost' AND source_event_id = $1 -""" -_LOCK_EVENT: Final = """ -SELECT payload_hash FROM "LiteLLM_AccountingEvent" WHERE event_id = $1 FOR UPDATE -""" -_INSERT_USAGE_BATCH: Final = """ -INSERT INTO "LiteLLM_AccountingEvent" - (event_id, kind, schema_version, payload_hash, occurred_at, payload) -SELECT event_id, kind::"AccountingEventKind", 1, payload_hash, occurred_at::timestamp, payload -FROM jsonb_to_recordset($1::jsonb) AS records( - event_id text, kind text, payload_hash text, occurred_at text, payload jsonb) -ORDER BY event_id -ON CONFLICT (event_id) DO NOTHING RETURNING event_id -""" -_LOCK_USAGE_BATCH: Final = """ -SELECT event_id, payload_hash FROM "LiteLLM_AccountingEvent" -WHERE event_id IN (SELECT value FROM jsonb_array_elements_text($1::jsonb)) -ORDER BY event_id FOR UPDATE -""" -_LOAD_USAGE_BATCH: Final = """ -SELECT event.payload, ARRAY( - SELECT target::text FROM "LiteLLM_AccountingDelivery" delivery - WHERE delivery.event_id = event.event_id ORDER BY target::text -) AS targets -FROM "LiteLLM_AccountingEvent" event -WHERE event.event_id IN (SELECT value FROM jsonb_array_elements_text($1::jsonb)) - AND event.kind = 'outbound_usage' AND event.schema_version = 1 -""" -_INSERT_USAGE_DELIVERIES: Final = """ -INSERT INTO "LiteLLM_AccountingDelivery" (event_id, target, version) -SELECT records.event_id, destination.value::"AccountingDeliveryTarget", 1 -FROM jsonb_to_recordset($1::jsonb) AS records(event_id text, targets jsonb) -CROSS JOIN LATERAL jsonb_array_elements_text(records.targets) AS destination -""" -_COMPLETED_FAMILY: Final = """ -root.source_event_id IS NULL AND root.kind IN ('inbound_usage', 'outbound_usage') -AND root.recorded_at < $1::timestamp -AND (root.kind = 'inbound_usage' OR EXISTS ( - SELECT 1 FROM "LiteLLM_AccountingEvent" AS cost WHERE cost.source_event_id = root.event_id AND cost.kind = 'cost' -)) -AND NOT EXISTS ( - SELECT 1 FROM "LiteLLM_AccountingEvent" AS member - WHERE (member.event_id = root.event_id OR (member.kind = 'cost' AND member.source_event_id = root.event_id)) - AND (member.recorded_at >= $1::timestamp - OR EXISTS (SELECT 1 FROM "LiteLLM_AccountingDelivery" AS delivery - WHERE delivery.event_id = member.event_id AND delivery.state != 'applied')) -) -""" -_RETENTION_CANDIDATES: Final = ( - 'SELECT root.event_id FROM "LiteLLM_AccountingEvent" AS root WHERE ' - + _COMPLETED_FAMILY - + " ORDER BY root.recorded_at, root.event_id LIMIT $2::int FOR UPDATE OF root SKIP LOCKED" -) -_ELIGIBLE_GROUP: Final = ( - 'SELECT root.event_id FROM "LiteLLM_AccountingEvent" AS root WHERE root.event_id = $2 AND ' + _COMPLETED_FAMILY -) -_DELETE_DELIVERIES: Final = """ -DELETE FROM "LiteLLM_AccountingDelivery" WHERE event_id IN ( - SELECT event_id FROM "LiteLLM_AccountingEvent" WHERE event_id = $1 OR (kind = 'cost' AND source_event_id = $1) -) -""" -_DELETE_EVENTS: Final = """ -DELETE FROM "LiteLLM_AccountingEvent" WHERE event_id = $1 OR (kind = 'cost' AND source_event_id = $1) -""" - - -_Conflict: TypeAlias = Literal["missing_source", "competing_cost", "identity_conflict"] - - -async def _accept(db: Prisma, record: _AcceptedEvent) -> Literal["inserted", "duplicate"] | _Conflict: - if record.source_event_id is not None: - source: Final = _STRINGS.validate_python(await db.query_raw(_LOCK_SOURCE, record.source_event_id)) - if not source: - return "missing_source" - costs: Final = _STRINGS.validate_python(tuple(await db.query_raw(_EXISTING_COST, record.source_event_id))) - if any(cost["event_id"] != record.event_id for cost in costs): - return "competing_cost" - inserted: Final = _STRINGS.validate_python( - await db.query_raw( - _INSERT_EVENT, - record.event_id, - record.kind.value, - record.source_event_id, - record.schema_version, - record.payload_hash, - record.occurred_at.astimezone(timezone.utc).isoformat(), - record.payload, - ) - ) - if not inserted: - existing: Final = _STRINGS.validate_python(tuple(await db.query_raw(_LOCK_EVENT, record.event_id))) - if not existing or existing[0]["payload_hash"] != record.payload_hash: - return "identity_conflict" - return "duplicate" - await db.execute_raw(_INSERT_DELIVERIES, record.event_id, _json(record.targets), record.version) - return "inserted" - - -async def _delete_completed(db: Prisma, event_id: str, cutoff: str) -> int: - if not _STRINGS.validate_python(await db.query_raw(_ELIGIBLE_GROUP, cutoff, event_id)): - return 0 - await db.execute_raw(_DELETE_DELIVERIES, event_id) - return await db.execute_raw(_DELETE_EVENTS, event_id) - - -class AccountingLedger: - def __init__(self, transaction: Callable[[], _Transaction]) -> None: - self._transaction: Final = transaction - - @classmethod - def for_client(cls, client: PrismaClient) -> AccountingLedger: - from prisma.client import TransactionManager - - managers: Final = TypeAdapter(TransactionManager, config=ConfigDict(arbitrary_types_allowed=True)) - - @asynccontextmanager - async def transaction() -> AsyncGenerator[Prisma]: - primary: Final = writer_wrapper(client.db) - manager: Final = managers.validate_python(primary.tx(timeout=_TIMEOUT)) - async with db_span("accounting_ledger", "LiteLLM_AccountingEvent"), manager as db: - await db.execute_raw("SET LOCAL statement_timeout = 5000") - await db.execute_raw("SET LOCAL lock_timeout = 1000") - yield db - - return cls(transaction) - - async def insert_usage_batch(self, writes: tuple[UsageWrite, ...]) -> None: - records: Final = tuple(_prepare(write.event, write.targets, write.envelope, 1, 1) for write in writes) - if not records: - return - unique: Final = {record.event_id: record for record in records} - if any(record.payload_hash != unique[record.event_id].payload_hash for record in records): - raise AccountingConflictError("Batch contains conflicting copies of a usage identity") - batch: Final = _json( - tuple( - { - "event_id": record.event_id, - "kind": record.kind.value, - "payload_hash": record.payload_hash, - "occurred_at": record.occurred_at.astimezone(timezone.utc).isoformat(), - "payload": _JSON.validate_json(record.payload), - } - for record in unique.values() - ) - ) - async with self._transaction() as db: - inserted: Final = _STRINGS.validate_python(await db.query_raw(_INSERT_USAGE_BATCH, batch)) - accepted: Final = _STRINGS.validate_python(await db.query_raw(_LOCK_USAGE_BATCH, _json(tuple(unique)))) - if len(accepted) != len(unique) or any( - row["payload_hash"] != unique[row["event_id"]].payload_hash for row in accepted - ): - raise AccountingConflictError("Usage identity conflicts with accepted content or delivery set") - deliveries: Final = _json( - tuple({"event_id": row["event_id"], "targets": unique[row["event_id"]].targets} for row in inserted) - ) - await db.execute_raw(_INSERT_USAGE_DELIVERIES, deliveries) - - async def load_usage_batch(self, event_ids: tuple[str, ...]) -> tuple[UsageWrite, ...]: - if not event_ids: - return () - async with self._transaction() as db: - rows: Final = TypeAdapter(tuple[dict[str, JsonValue], ...]).validate_python( - await db.query_raw(_LOAD_USAGE_BATCH, _json(event_ids)) - ) - return tuple( - UsageWrite( - OutboundUsageEvent.model_validate_json(_json(_JSON.validate_python(row["payload"])["event"])), - _json(row["payload"]), - TypeAdapter(tuple[DeliveryTarget, ...]).validate_python(row["targets"]), - ) - for row in rows - ) - - async def insert_event( - self, - event: AccountingEvent, - targets: tuple[DeliveryTarget, ...], - *, - envelope: str, - schema_version: int = 1, - version: int = 1, - ) -> Literal["inserted", "duplicate"]: - """Accept T5/T6's serialized envelope, containing its public event under `event`. - - The immutable acceptance hash includes the target set and delivery version. - Changing either for an accepted event conflicts. T7 must provide a separate - add-target or new-version workflow that preserves receipts and prevents - duplicate contributions; redelivery cannot silently create or reset work. - - The Prisma adapter opens one interactive transaction per event, including - two SET LOCAL statements and a source-row lock for costs. I/O is async, - but awaiting this method inline adds commit latency per event, potentially - several times per request. T5 owns bounded asynchronous capture and an - explicit batching strategy; looping over this method does not batch commits. - Success acknowledges commit, independently of HTTP response acknowledgement. - """ - record: Final = _prepare(event, targets, envelope, schema_version, version) - async with self._transaction() as db: - result: Final = await _accept(db, record) - match result: - case "inserted" | "duplicate": - return result - case "missing_source": - raise AccountingConflictError("Cost source must be a durably accepted outbound usage event") - case "competing_cost": - raise AccountingConflictError("Usage event already has an authoritative cost") - case "identity_conflict": - raise AccountingConflictError("Event identity conflicts with its accepted content or delivery set") - case _: - assert_never(result) - - async def purge_completed( - self, - *, - redelivery_before: datetime | None = None, - recovery_before: datetime | None = None, - limit: int = 100, - ) -> int: - """Delete at most `limit` completed families once both retention owners permit it. - - T8 must supply a coherent recovery watermark including outstanding holds. - Omitting either watermark disables deletion. Each usage row and its cost - remain together so a retained charge never loses its source or vice versa. - Applied receipts are deleted with the family, ending its retained dedup - protection. The caller must guarantee events recorded before - redelivery_before cannot be redelivered through supported paths. - T8's recovery_before must also protect checkpoints, - outstanding holds and unfinished settlements; age alone is insufficient. - """ - if type(limit) is not int or not 1 <= limit <= 1000: - raise ValueError("Accounting retention batch size must be between 1 and 1000") - if redelivery_before is None or recovery_before is None: - return 0 - cutoff: Final = min( - _INSTANT.validate_python(redelivery_before).astimezone(timezone.utc), - _INSTANT.validate_python(recovery_before).astimezone(timezone.utc), - ).isoformat() - async with self._transaction() as db: - roots: Final = _STRINGS.validate_python(tuple(await db.query_raw(_RETENTION_CANDIDATES, cutoff, limit))) - deleted: Final = tuple([await _delete_completed(db, root["event_id"], cutoff) for root in roots]) - return sum(deleted) diff --git a/litellm/proxy/db/budget_window_spend_writer.py b/litellm/proxy/db/budget_window_spend_writer.py index 99b49331932..d2b69f24397 100644 --- a/litellm/proxy/db/budget_window_spend_writer.py +++ b/litellm/proxy/db/budget_window_spend_writer.py @@ -14,11 +14,13 @@ interval of increments queued elsewhere: the same lag the SpendLogs aggregate it replaces (and every other spend column) already has. """ -from collections.abc import Sequence +from collections.abc import Mapping, Sequence +from contextlib import nullcontext from dataclasses import dataclass from datetime import datetime, timedelta, timezone from typing import TYPE_CHECKING, Final, Protocol +from pydantic import TypeAdapter from typing_extensions import LiteralString, ReadOnly, TypedDict from litellm._logging import verbose_proxy_logger @@ -74,30 +76,44 @@ _OPEN_WINDOW_SPEND_SQL: Final = ( "WHERE \"LiteLLM_BudgetWindowSpend\".window_start <= ($5::timestamptz AT TIME ZONE 'UTC')" ) +_HAS_DELIVERY: Final = 'EXISTS (SELECT 1 FROM "LiteLLM_SpendLogDelivery" delivery WHERE delivery.request_id = "LiteLLM_SpendLogs".request_id)' + +_SETTLED_SPEND_LOG_FILTER: Final = ( + ' AND NOT EXISTS (SELECT 1 FROM "LiteLLM_SpendLogDelivery" delivery ' + 'WHERE delivery.request_id = "LiteLLM_SpendLogs".request_id ' + "AND delivery.state IN ('pending', 'parked'))" +) + _SEED_FROM_SPEND_LOGS_KEY_SQL: Final = ( "SELECT COALESCE(SUM(spend), 0.0) AS total, " - "COALESCE(SUM(spend) FILTER (WHERE \"startTime\" < ($3::timestamptz AT TIME ZONE 'UTC')), 0.0) AS before_batch " + "COALESCE(SUM(spend) FILTER (WHERE " + + _HAS_DELIVERY + + " OR \"startTime\" < ($3::timestamptz AT TIME ZONE 'UTC')), 0.0) " + "AS before_batch " 'FROM "LiteLLM_SpendLogs" ' - "WHERE api_key = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')" + "WHERE api_key = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')" + _SETTLED_SPEND_LOG_FILTER ) _SEED_FROM_SPEND_LOGS_TEAM_SQL: Final = ( "SELECT COALESCE(SUM(spend), 0.0) AS total, " - "COALESCE(SUM(spend) FILTER (WHERE \"startTime\" < ($3::timestamptz AT TIME ZONE 'UTC')), 0.0) AS before_batch " + "COALESCE(SUM(spend) FILTER (WHERE " + + _HAS_DELIVERY + + " OR \"startTime\" < ($3::timestamptz AT TIME ZONE 'UTC')), 0.0) " + "AS before_batch " 'FROM "LiteLLM_SpendLogs" ' - "WHERE team_id = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')" + "WHERE team_id = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')" + _SETTLED_SPEND_LOG_FILTER ) _SEED_FROM_SPEND_LOGS_KEY_UNBOUNDED_SQL: Final = ( "SELECT COALESCE(SUM(spend), 0.0) AS total, COALESCE(SUM(spend), 0.0) AS before_batch " 'FROM "LiteLLM_SpendLogs" ' - "WHERE api_key = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')" + "WHERE api_key = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')" + _SETTLED_SPEND_LOG_FILTER ) _SEED_FROM_SPEND_LOGS_TEAM_UNBOUNDED_SQL: Final = ( "SELECT COALESCE(SUM(spend), 0.0) AS total, COALESCE(SUM(spend), 0.0) AS before_batch " 'FROM "LiteLLM_SpendLogs" ' - "WHERE team_id = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')" + "WHERE team_id = $1 AND \"startTime\" >= ($2::timestamptz AT TIME ZONE 'UTC')" + _SETTLED_SPEND_LOG_FILTER ) _UPSERT_TRANSACTION_TIMEOUT: Final = timedelta(seconds=60) @@ -114,6 +130,10 @@ class _ExistingKeyRow(TypedDict): window_duration: ReadOnly[str] +_SEED_TOTALS_ROWS: Final = TypeAdapter(tuple[_SeedTotalsRow, ...]) +_EXISTING_KEY_ROWS: Final = TypeAdapter(tuple[_ExistingKeyRow, ...]) + + class _SeedTotalsQuery(Protocol): async def __call__(self, query: LiteralString, *args: object) -> Sequence[_SeedTotalsRow]: ... @@ -135,6 +155,8 @@ class _UpsertBatchManager(Protocol): class _UpsertTransaction(Protocol): def batch_(self) -> _UpsertBatchManager: ... + async def query_raw(self, query: LiteralString, *args: object) -> Sequence[Mapping[str, object]]: ... + class _UpsertTransactionManager(Protocol): async def __aenter__(self) -> _UpsertTransaction: ... @@ -178,6 +200,7 @@ class WindowSpendLogsAggregate(Protocol): entity_id: str, window_start: datetime, batch_started_at: datetime | None, + query: _SeedTotalsQuery | None = None, ) -> WindowSeedTotals | None: ... @@ -187,6 +210,7 @@ async def spend_logs_seed_totals( entity_id: str, window_start: datetime, batch_started_at: datetime | None, + query: _SeedTotalsQuery | None = None, ) -> WindowSeedTotals | None: """LiteLLM_SpendLogs spend for one entity since window_start, both in full and up to the start of the batch being flushed, in one scan. @@ -210,11 +234,12 @@ async def spend_logs_seed_totals( bounded_sql, unbounded_sql = _SEED_FROM_SPEND_LOGS_TEAM_SQL, _SEED_FROM_SPEND_LOGS_TEAM_UNBOUNDED_SQL else: return None + read: Final = query or _seed_totals_query(prisma_client) async with db_span("seed_window_spend", "LiteLLM_SpendLogs"): rows: Final = ( - await _seed_totals_query(prisma_client)(unbounded_sql, entity_id, window_start) + await read(unbounded_sql, entity_id, window_start) if batch_started_at is None - else await _seed_totals_query(prisma_client)( + else await read( bounded_sql, entity_id, window_start, @@ -246,9 +271,10 @@ def _primary_key(transaction: WindowSpendTransaction) -> tuple[str, str, str]: async def _existing_primary_keys( prisma_client: "PrismaClient", transactions: tuple[WindowSpendTransaction, ...], + query: _ExistingKeysQuery | None = None, ) -> frozenset[tuple[str, str, str]]: async with db_span("select_window_spend_rows", "LiteLLM_BudgetWindowSpend"): - rows: Final = await _existing_keys_query(prisma_client)( + rows: Final = await (query or _existing_keys_query(prisma_client))( _SELECT_EXISTING_ROWS_SQL, tuple(transaction["entity_type"] for transaction in transactions), tuple(transaction["entity_id"] for transaction in transactions), @@ -262,6 +288,7 @@ async def _seed_base_for_missing_row( transaction: WindowSpendTransaction, existing_primary_keys: frozenset[tuple[str, str, str]], spend_logs_aggregate: WindowSpendLogsAggregate, + query: _SeedTotalsQuery | None = None, ) -> float: """Spend already recorded for a window that has no row yet. @@ -272,12 +299,24 @@ async def _seed_base_for_missing_row( """ if _primary_key(transaction) in existing_primary_keys: return 0.0 - totals: Final = await spend_logs_aggregate( - prisma_client=prisma_client, - entity_type=transaction["entity_type"], - entity_id=transaction["entity_id"], - window_start=datetime.fromisoformat(transaction["window_start"]).replace(tzinfo=timezone.utc), - batch_started_at=_transaction_started_at(transaction), + window_start: Final = datetime.fromisoformat(transaction["window_start"]).replace(tzinfo=timezone.utc) + totals: Final = ( + await spend_logs_aggregate( + prisma_client=prisma_client, + entity_type=transaction["entity_type"], + entity_id=transaction["entity_id"], + window_start=window_start, + batch_started_at=_transaction_started_at(transaction), + ) + if query is None + else await spend_logs_aggregate( + prisma_client=prisma_client, + entity_type=transaction["entity_type"], + entity_id=transaction["entity_id"], + window_start=window_start, + batch_started_at=_transaction_started_at(transaction), + query=query, + ) ) if totals is None: return 0.0 @@ -324,10 +363,30 @@ def _upsert_params( ) +def _existing_keys_in(transaction: _UpsertTransaction) -> _ExistingKeysQuery: + async def query_raw(query: LiteralString, *args: object) -> Sequence[_ExistingKeyRow]: + return _EXISTING_KEY_ROWS.validate_python(await transaction.query_raw(query, *args)) + + return query_raw + + +def _seed_totals_in(transaction: _UpsertTransaction) -> _SeedTotalsQuery: + async def query_raw(query: LiteralString, *args: object) -> Sequence[_SeedTotalsRow]: + return _SEED_TOTALS_ROWS.validate_python(await transaction.query_raw(query, *args)) + + return query_raw + + +def _transaction_reads(transaction: _UpsertTransaction) -> tuple[_ExistingKeysQuery, _SeedTotalsQuery]: + """Reads made inside an enclosing transaction share its connection, so they cannot wait on it.""" + return _existing_keys_in(transaction), _seed_totals_in(transaction) + + async def commit_window_spend_updates( prisma_client: "PrismaClient", transactions: Sequence[WindowSpendTransaction], spend_logs_aggregate: WindowSpendLogsAggregate = spend_logs_seed_totals, + outer_transaction: _UpsertTransaction | None = None, ) -> None: """Apply aggregated window increments to LiteLLM_BudgetWindowSpend. @@ -343,9 +402,11 @@ async def commit_window_spend_updates( return ordered: Final = tuple(sorted(transactions, key=window_spend_group_key)) + reads: Final = _transaction_reads(outer_transaction) if outer_transaction is not None else (None, None) existing_primary_keys: Final = await _existing_primary_keys( prisma_client=prisma_client, transactions=ordered, + query=reads[0], ) seed_bases: Final = tuple( [ @@ -354,6 +415,7 @@ async def commit_window_spend_updates( transaction=transaction, existing_primary_keys=existing_primary_keys, spend_logs_aggregate=spend_logs_aggregate, + query=reads[1], ) for transaction in ordered ] @@ -367,7 +429,9 @@ async def commit_window_spend_updates( ) async with ( db_span("commit_window_spend_updates", "LiteLLM_BudgetWindowSpend"), - _upsert_transaction(prisma_client) as db_transaction, + ( + nullcontext(outer_transaction) if outer_transaction is not None else _upsert_transaction(prisma_client) + ) as db_transaction, db_transaction.batch_() as batcher, ): for transaction, seed_base in zip(ordered, seed_bases): diff --git a/litellm/proxy/db/daily_spend_bulk_upsert.py b/litellm/proxy/db/daily_spend_bulk_upsert.py index eb130a5196f..2d1770f4c1d 100644 --- a/litellm/proxy/db/daily_spend_bulk_upsert.py +++ b/litellm/proxy/db/daily_spend_bulk_upsert.py @@ -55,7 +55,7 @@ _ENTITY_INPUT_KEYS: Final[Mapping[DailySpendEntity, str]] = MappingProxyType( "tag": "request_tags", } ) -_TAGS: Final = TypeAdapter(tuple[str, ...]) +_TAGS: Final = TypeAdapter(tuple[object, ...]) def daily_spend_entity_ids(payload: Mapping[str, object], entity: DailySpendEntity) -> tuple[str | None, ...]: @@ -67,7 +67,7 @@ def daily_spend_entity_ids(payload: Mapping[str, object], entity: DailySpendEnti if value is None: return () tags: Final = _TAGS.validate_json(value) if isinstance(value, str) else _TAGS.validate_python(value) - return tuple(dict.fromkeys(tags)) + return tuple(dict.fromkeys(tag for tag in tags if isinstance(tag, str))) if value is None: return (None,) if entity == "user" else () if not isinstance(value, str) or (entity == "end_user" and not value): diff --git a/litellm/proxy/db/db_spend_update_writer.py b/litellm/proxy/db/db_spend_update_writer.py index d9fb236632b..80f09df6c86 100644 --- a/litellm/proxy/db/db_spend_update_writer.py +++ b/litellm/proxy/db/db_spend_update_writer.py @@ -12,6 +12,7 @@ import json import os import random import time +import uuid from collections.abc import AsyncGenerator, Callable, Coroutine, Iterable, Mapping, Sequence from contextlib import asynccontextmanager from contextvars import ContextVar @@ -34,6 +35,7 @@ from litellm.constants import ( DB_SPEND_UPDATE_JOB_NAME, INTERNAL_CALL_ORIGIN_METADATA_KEY, ) +from litellm.litellm_core_utils.batch_utils import BATCH_COST_REQUEST_ID_SUFFIX from litellm.litellm_core_utils.core_helpers import finite_cost, single_log_line from litellm.litellm_core_utils.litellm_logging import coerce_model_access_groups from litellm.litellm_core_utils.safe_json_loads import safe_json_loads @@ -92,8 +94,10 @@ from litellm.proxy.spend_tracking.spend_log_error_logger import spend_log_error from litellm.repositories.prisma_protocols import BatchTable from litellm.responses.streaming_iterator import spawn_logging_task from litellm.types.utils import CallTypes +from litellm.types.videos.utils import VIDEO_COST_REQUEST_ID_SUFFIX, VIDEO_STATUS_CALL_TYPES if TYPE_CHECKING: + from litellm.accounting.projection import Contribution from litellm.proxy.db.autorouter_session_rollup import AutoRouterTurnTransaction from litellm.proxy.db.baseline_accounting import DailyBaselineAttribution from litellm.proxy.utils import PrismaClient, ProxyLogging @@ -158,23 +162,73 @@ def _org_member_transaction_key(org_id: str, user_id: str) -> str: return f"organization_id::{quote(org_id, safe='')}::user_id::{quote(user_id, safe='')}" -def _is_batch_cost_row(payload: SpendLogsPayload) -> bool: - return payload.get("call_type") == CallTypes.aretrieve_batch.value and payload.get("status") == "success" +ACCOUNTING_LEDGER_KWARG: Final = "accounting_ledger" -_BATCH_COST_CLAIM_FIELDS: Final = frozenset({"request_id", "call_type", "spend", "startTime", "endTime", "status"}) +def _persistable_api_key(token: str | None, logged_api_key: str) -> str | None: + from litellm.litellm_core_utils.litellm_logging import is_valid_sha256_hash + from litellm.proxy.spend_tracking.spend_tracking_utils import redact_logged_api_key + + if token is None or token == logged_api_key or is_valid_sha256_hash(token): + return token + return redact_logged_api_key(token) -def _batch_cost_row_to_write(payload: SpendLogsPayload, disable_spend_logs: bool) -> Mapping[str, object]: - """Reduce a batch's cost row to what tells the retrieves apart when logging is off. +async def _track_guardrail_usage_of_cost_row( + payload: SpendLogsPayload, prisma_client: "PrismaClient", disable_spend_logs: bool +) -> None: + """A job's cost row skips the spend log queue, so its guardrail runs are counted here instead of at the flush.""" + if disable_spend_logs: + return + from litellm.proxy.guardrails.usage_tracking import process_spend_logs_guardrail_usage - A proxy run with spend logs disabled still needs one row per batch to charge it once, + try: + await process_spend_logs_guardrail_usage(prisma_client=prisma_client, logs_to_process=(payload,)) + except Exception as e: # noqa: BLE001 # guardrail usage is best effort, as at the spend log flush + verbose_proxy_logger.warning( + "Guardrail usage tracking failed for spend row %s (non-fatal): %s", payload["request_id"], e + ) + + +def _is_settle_once_cost_row(payload: SpendLogsPayload) -> bool: + """A poll of a job whose cost is charged once, by the first poll that sees it, however often it is polled. + + A batch's cost is known only when a retrieve sees it finished (LIT-7048). A video's cost is + charged at create by the built-in providers, but a custom provider may report it on the + status poll that sees the video completed. Only a row carrying the job's cost suffix settles + the job, so a poll that pays only its guardrails, under an id that client call ids cannot + turn into the job's, is charged like any other request. + """ + if payload.get("status") != "success": + return False + call_type: Final = payload.get("call_type") + request_id: Final = payload["request_id"] + if call_type == CallTypes.aretrieve_batch.value: + return request_id.endswith(BATCH_COST_REQUEST_ID_SUFFIX) + return call_type in VIDEO_STATUS_CALL_TYPES and request_id.endswith(VIDEO_COST_REQUEST_ID_SUFFIX) + + +_COST_CLAIM_FIELDS: Final = frozenset({"request_id", "call_type", "spend", "startTime", "endTime", "status"}) + + +def _cost_row_to_write(payload: SpendLogsPayload, disable_spend_logs: bool) -> Mapping[str, object]: + """Reduce a job's cost row to what tells its polls apart when logging is off. + + A legacy proxy run with spend logs disabled still needs one row per job to charge it once, so the row is written either way, but it carries no request of its own: no metadata, - no requester IP, no key, model, or token counts (LIT-7048). + no requester IP, no key, model, or token counts (LIT-7048). A ledger batch is deduplicated + by its delivery row instead, so it writes no local row when logging is off. """ if disable_spend_logs is False: return payload - return MappingProxyType({field: value for field, value in payload.items() if field in _BATCH_COST_CLAIM_FIELDS}) + if "accounting_payload" in payload: + return { + "request_id": payload["request_id"], + "call_type": payload["call_type"], + "accounting_payload": payload["accounting_payload"], + "accounting_log_disabled": True, + } + return MappingProxyType({field: value for field, value in payload.items() if field in _COST_CLAIM_FIELDS}) class _SpendIncrement(TypedDict): @@ -187,8 +241,17 @@ class _MemberSpendRow(TypedDict): cost: ReadOnly[float] +class SpendUpsertTable(Protocol): + def upsert(self, *, where: Mapping[str, object], data: Mapping[str, object]) -> None: ... + + class _SpendBatch(Protocol): litellm_usertable: BatchTable + litellm_endusertable: SpendUpsertTable + litellm_dailymodelusage: SpendUpsertTable + + def execute_raw(self, query: LiteralString, *args: object) -> None: ... + litellm_verificationtoken: BatchTable litellm_teamtable: BatchTable litellm_teammembership: BatchTable @@ -219,14 +282,14 @@ def _entity_spend_table(batcher: _SpendBatch, table_accessor: _EntitySpendTable) return _ENTITY_SPEND_TABLES[table_accessor](batcher) -class _SpendBatchManager(Protocol): +class SpendBatchManager(Protocol): async def __aenter__(self) -> _SpendBatch: ... async def __aexit__(self, exc_type: object, exc_value: object, traceback: object) -> bool | None: ... class _SpendTransaction(Protocol): - def batch_(self) -> _SpendBatchManager: ... + def batch_(self) -> SpendBatchManager: ... async def execute_raw(self, query: LiteralString, *args: object) -> int: ... @@ -381,8 +444,14 @@ _ENTITY_SPEND_MODELS: Final[Mapping[_EntitySpendTable, str]] = MappingProxyType( @asynccontextmanager async def _spend_update_tx( - prisma_client: PrismaClient, table: str, call_type: str = "commit_spend_updates" + prisma_client: PrismaClient, + table: str, + call_type: str = "commit_spend_updates", + outer_transaction: _SpendTransaction | None = None, ) -> AsyncGenerator[_SpendTransaction]: + if outer_transaction is not None: + yield outer_transaction + return tx: Final[_SpendTransactionManager] = prisma_client.db.tx(timeout=timedelta(seconds=60)) async with db_span(call_type, table), tx as transaction: await apply_rollup_lock_timeout(transaction) @@ -569,6 +638,21 @@ def debitable_model_access_groups( return tuple(group for group in ordered if group in served) +def _billable_cost(response_cost: float | None, payload: SpendLogsPayload) -> float | None: + billable_cost: Final = finite_cost(response_cost) + if response_cost is not None and billable_cost is None: + verbose_proxy_logger.warning( + "Spend tracking - recording a non-finite response_cost=%s as 0 for request_id=%s", + response_cost, + single_log_line(payload["request_id"]), + ) + return billable_cost + + +def _iso_timestamp(value: datetime | str) -> str: + return value.isoformat() if isinstance(value, datetime) else value + + class DBSpendUpdateWriter: """ Module responsible for @@ -613,10 +697,11 @@ class DBSpendUpdateWriter: ) -> bool: """Record the request's spend, answering whether its cost still needs charging. - False only for a batch retrieve whose cost row another retrieve already wrote, + False only for a batch or video poll whose cost row another poll already wrote, so the caller leaves the key, team, and user counters alone (LIT-7048). """ from litellm.proxy.proxy_server import ( + accounting_window_keys, disable_spend_logs, general_settings, # pyright: ignore[reportUnknownVariableType] # legacy proxy configuration is narrowed below litellm_proxy_budget_name, @@ -624,6 +709,13 @@ class DBSpendUpdateWriter: ) from litellm.proxy.utils import ProxyUpdateSpend, hash_token + proxy_settings: Final = cast( # cast-ok: proxy settings use string keys + Mapping[str, object], general_settings + ) + use_ledger: Final = proxy_settings.get("use_spend_logs_ledger") is True + request_fields: Final = _SPEND_METADATA_ADAPTER.validate_python(kwargs or {}) + if kwargs is not None: + kwargs[ACCOUNTING_LEDGER_KWARG] = use_ledger # rebind-ok: spend counters leave ledger windows to the worker try: verbose_proxy_logger.debug( "Enters prisma db call, response_cost: %s, token: %s; user_id: %s; team_id: %s", @@ -634,10 +726,9 @@ class DBSpendUpdateWriter: ) if ProxyUpdateSpend.disable_spend_updates() is True: return True - if token is not None and isinstance(token, str) and token.startswith("sk-"): - hashed_token = hash_token(token=token) - else: - hashed_token = token + hashed_token: Final = ( + hash_token(token=token) if isinstance(token, str) and token.startswith("sk-") else token + ) ## CREATE SPEND LOG PAYLOAD ## from litellm.proxy.spend_tracking.spend_tracking_utils import ( @@ -653,32 +744,42 @@ class DBSpendUpdateWriter: end_time=end_time, llm_router=llm_router, ) - billable_cost: Final = finite_cost(response_cost) - if response_cost is not None and billable_cost is None: - verbose_proxy_logger.warning( - "Spend tracking - recording a non-finite response_cost=%s as 0 for request_id=%s", - response_cost, - single_log_line(payload["request_id"]), - ) + billable_cost: Final = _billable_cost(response_cost, payload) payload["spend"] = billable_cost or 0.0 - if isinstance(payload["startTime"], datetime): - payload["startTime"] = payload["startTime"].isoformat() - if isinstance(payload["endTime"], datetime): - payload["endTime"] = payload["endTime"].isoformat() - - if org_id is not None and org_id != "": + payload["startTime"] = _iso_timestamp(payload["startTime"]) + payload["endTime"] = _iso_timestamp(payload["endTime"]) + if org_id: payload["organization_id"] = org_id - - if team_id is not None and team_id != "": + if team_id: payload["team_id"] = team_id - error_log_settings: Final = cast( # cast-ok: proxy settings use string keys - Mapping[str, object], general_settings - ) + if use_ledger: + from litellm.accounting.snapshot import build_accounting_payload + + if not _is_settle_once_cost_row(payload): + payload["accounting_delivery_id"] = uuid.uuid4().hex + payload["accounting_payload"] = build_accounting_payload( + payload, + entities={ + "api_key": _persistable_api_key(hashed_token, payload.get("api_key") or ""), + "user": user_id, + "end_user": end_user_id, + "team_id": team_id, + "organization_id": org_id, + "project_id": project_id, + "agent_id": payload["agent_id"], + "proxy_budget_name": litellm_proxy_budget_name if litellm.max_budget > 0 else None, + }, + model_access_groups=debitable_model_access_groups( + get_request_model_access_groups(request_fields), payload["model_id"], llm_router + ), + windows=await accounting_window_keys(hashed_token, team_id) if billable_cost else (), + router=get_llm_router, + ) keep_spend_logs: Final = disable_spend_logs is False and not ( "status" in payload and payload["status"] == "failure" - and error_log_settings.get("disable_error_logs") is True + and proxy_settings.get("disable_error_logs") is True ) if not await self._record_spend_log( payload=payload, @@ -707,24 +808,26 @@ class DBSpendUpdateWriter: "disable_spend_logs=True. Skipping writing spend logs to db. Other spend updates - Key/User/Team table will still occur." ) - spawn_logging_task( - asyncio.get_running_loop(), - self._batch_database_updates( - response_cost=billable_cost, - user_id=user_id, - hashed_token=hashed_token, - team_id=team_id, - org_id=org_id, - project_id=project_id, - end_user_id=end_user_id, - prisma_client=prisma_client, - litellm_proxy_budget_name=litellm_proxy_budget_name, - payload=payload, - request_model_access_groups=get_request_model_access_groups(kwargs), - ), - task_name="spend rollups", - ) - + if not use_ledger: + spawn_logging_task( + asyncio.get_running_loop(), + self._batch_database_updates( + response_cost=billable_cost, + user_id=user_id, + hashed_token=hashed_token, + team_id=team_id, + org_id=org_id, + project_id=project_id, + end_user_id=end_user_id, + prisma_client=prisma_client, + litellm_proxy_budget_name=litellm_proxy_budget_name, + payload=payload, + request_model_access_groups=get_request_model_access_groups(request_fields), + ), + task_name="spend rollups", + ) + else: + self._record_request_error_safely(payload=payload, prisma_client=prisma_client) self._enqueue_tool_registry_upsert( kwargs=kwargs, completion_response=completion_response, @@ -755,24 +858,32 @@ class DBSpendUpdateWriter: disable_spend_logs: bool, llm_router: "Router | None" = None, ) -> bool: - if prisma_client is not None and _is_batch_cost_row(payload): - return await self._claim_batch_cost_spend_log( + if prisma_client is not None and _is_settle_once_cost_row(payload): + return await self._claim_settle_once_cost_row( payload=payload, prisma_client=prisma_client, disable_spend_logs=disable_spend_logs ) - if disable_spend_logs is False: + if "accounting_payload" in payload: + await self._insert_spend_log_to_db( + payload={**payload, "accounting_log_disabled": disable_spend_logs}, + prisma_client=prisma_client, + llm_router=llm_router, + ) + elif disable_spend_logs is False: await self._insert_spend_log_to_db(payload=payload, prisma_client=prisma_client, llm_router=llm_router) return True - async def _claim_batch_cost_spend_log( + async def _claim_settle_once_cost_row( self, payload: SpendLogsPayload, prisma_client: "PrismaClient", disable_spend_logs: bool ) -> bool: - """Write the batch's cost row now, or learn that another retrieve already did. + """Write the job's cost row now, or learn that another poll already did. - Every retrieve of one batch shares this row, so the insert that lands first owns + Every poll of one batch or video shares this row, so the insert that lands first owns the charge and every later one finds the row and charges nothing (LIT-7048). Only - a row that recorded a charge counts: a failed retrieve, a request whose client - picked the batch id as its call id, and the $0 row an older proxy left behind - while the batch was still running all leave the charge to be made. + a row that recorded a charge counts: a failed poll, a request whose client + picked the job id as its call id, and the $0 row a poll left behind + while the job was still running all leave the charge to be made. A ledger job + is owned by its delivery row, keyed by its cost row id, in every logging mode, and a + $0 poll records no delivery so it cannot block the poll that carries the cost. """ from litellm.repositories.table_repositories import SpendLogsRepository @@ -783,43 +894,59 @@ class DBSpendUpdateWriter: ) row: Final = spend_log_row_with_retained_metadata( - _batch_cost_row_to_write(payload, disable_spend_logs), configured_spend_logs_metadata_fields() + _cost_row_to_write(payload, disable_spend_logs), configured_spend_logs_metadata_fields() ) - spend_logs: Final = SpendLogsRepository(prisma_client).table + repository: Final = SpendLogsRepository(prisma_client) try: - claimed: Final = await spend_logs.create_many( + if "accounting_payload" in payload: + if payload["spend"] <= 0: + return True + accepted: Final = await repository.insert_with_deliveries([prisma_client.jsonify_object(row)]) == 1 + if accepted: + await _track_guardrail_usage_of_cost_row(payload, prisma_client, disable_spend_logs) + return accepted + if await repository.has_delivery(request_id): + return False + claimed: Final = await repository.table.create_many( data=[prisma_client.jsonify_object(row)], skip_duplicates=True, ) - if claimed == 1: - return True - existing: Final = await spend_logs.find_unique(where={"request_id": request_id}) + existing: Final = ( + None if claimed == 1 else await repository.table.find_unique(where={"request_id": request_id}) + ) except Exception as e: # noqa: BLE001 # prisma raises its own hierarchy; an unreachable DB queues the row like any other spend log verbose_proxy_logger.warning( - "Could not claim spend row %s for a batch's cost, queueing it: %s", request_id, e + "Could not claim spend row %s for a job's cost, queueing it: %s", request_id, e ) await self._insert_spend_log_to_db(payload=prisma_client.jsonify_object(row), prisma_client=prisma_client) return True - if existing is None or existing.call_type != CallTypes.aretrieve_batch.value or existing.status != "success": + if claimed == 1: + await _track_guardrail_usage_of_cost_row(payload, prisma_client, disable_spend_logs) + return True + if existing is None or existing.call_type != payload["call_type"] or existing.status != "success": verbose_proxy_logger.warning( - "Spend row %s belongs to a %s request, so this batch's cost is charged without a row of its own", + "Spend row %s belongs to a %s request, so this job's cost is charged without a row of its own", request_id, getattr(existing, "call_type", None), ) return True if existing.spend > 0: - verbose_proxy_logger.debug("Cost tracking skipped: spend row %s already charged this batch", request_id) + verbose_proxy_logger.debug("Cost tracking skipped: spend row %s already charged this job", request_id) return False - return await self._take_over_uncharged_batch_cost_row(payload=payload, prisma_client=prisma_client, row=row) + taken_over: Final = await self._take_over_uncharged_cost_row( + payload=payload, prisma_client=prisma_client, row=row + ) + if taken_over: + await _track_guardrail_usage_of_cost_row(payload, prisma_client, disable_spend_logs) + return taken_over - async def _take_over_uncharged_batch_cost_row( + async def _take_over_uncharged_cost_row( self, payload: SpendLogsPayload, prisma_client: "PrismaClient", row: Mapping[str, object] ) -> bool: - """Take the batch's cost row over from the poll that left it charging nothing. + """Take the job's cost row over from the poll that left it charging nothing. - A pre-upgrade proxy wrote that row every time it polled the batch while it was still - running, so the charge is still to be made and the row still has to end up carrying - it. The row stops matching the moment it carries a charge, so it is one retrieve that + A poll that saw the job still running wrote that row at $0, so the charge is still to be + made and the row still has to end up carrying it. The row stops matching the moment it carries a charge, so it is one poll that takes it over and charges, and every later one reads the charge and charges nothing. """ from litellm.repositories.table_repositories import SpendLogsRepository @@ -827,7 +954,7 @@ class DBSpendUpdateWriter: request_id: Final = payload["request_id"] if payload["spend"] <= 0: verbose_proxy_logger.debug( - "Cost tracking skipped: this batch costs nothing and spend row %s says so", request_id + "Cost tracking skipped: this job costs nothing and spend row %s says so", request_id ) return False try: @@ -837,18 +964,18 @@ class DBSpendUpdateWriter: ), where={ "request_id": request_id, - "call_type": CallTypes.aretrieve_batch.value, + "call_type": payload["call_type"], "status": "success", "spend": 0.0, }, ) except Exception as e: # noqa: BLE001 # prisma raises its own hierarchy; the next retrieve takes the row over verbose_proxy_logger.warning( - "Could not take over spend row %s, leaving this batch's cost to the next retrieve: %s", request_id, e + "Could not take over spend row %s, leaving this job's cost to the next poll: %s", request_id, e ) return False if taken_over == 0: - verbose_proxy_logger.debug("Cost tracking skipped: spend row %s already charged this batch", request_id) + verbose_proxy_logger.debug("Cost tracking skipped: spend row %s already charged this job", request_id) return False return True @@ -1231,10 +1358,7 @@ class DBSpendUpdateWriter: self.add_spend_log_transaction_to_daily_team_transaction(payload=payload_copy, prisma_client=prisma_client), payload=payload_copy, ) - try: - self._record_request_error(payload=payload_copy, prisma_client=prisma_client) - except Exception as e: # noqa: BLE001 # the rollup must never skip the sibling spend writes - _report_spend_update_step_failure("_record_request_error", payload=payload_copy, exc=e) + self._record_request_error_safely(payload=payload_copy, prisma_client=prisma_client) await self._run_spend_update_step( "add_spend_log_transaction_to_daily_org_transaction", self.add_spend_log_transaction_to_daily_org_transaction( @@ -1564,7 +1688,7 @@ class DBSpendUpdateWriter: async def _insert_spend_log_to_db( self, - payload: dict | SpendLogsPayload, + payload: Mapping[str, object], prisma_client: PrismaClient | None = None, spend_logs_url: str | None = os.getenv("SPEND_LOGS_URL"), llm_router: "Router | None" = None, @@ -1608,6 +1732,13 @@ class DBSpendUpdateWriter: else: - Regular flow of this method """ + from litellm.accounting.worker import flush_accounting_deliveries + + try: + await flush_accounting_deliveries(self, prisma_client, proxy_logging_obj) + except Exception: # noqa: BLE001 # pending deliveries survive outages while legacy queues must still drain + verbose_proxy_logger.exception("Accounting delivery flush failed; pending work will retry") + if RedisUpdateBuffer.should_commit_spend_updates_to_redis(): await self._commit_spend_updates_to_db_with_redis( prisma_client=prisma_client, @@ -2134,6 +2265,39 @@ class DBSpendUpdateWriter: _handle_spend_update_failure = handle_spend_update_failure + @staticmethod + async def invalidate_accounting_entities( + contributions: tuple["Contribution", ...], proxy_logging_obj: ProxyLogging + ) -> None: + await DBSpendUpdateWriter._invalidate_project_caches( + tuple(dict(item.key)["project_id"] for item in contributions if item.table == "LiteLLM_ProjectTable"), + proxy_logging_obj, + ) + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache + + details: Final = _SPEND_METADATA_ADAPTER.validate_python( + proxy_logging_obj.call_details # pyright: ignore[reportUnknownMemberType] # legacy logging metadata is validated at this boundary + ) + user_api_key_cache: Final = details.get("user_api_key_cache") + if isinstance(user_api_key_cache, UserApiKeyCache): + with service_target(AUTH_OBJECTS_TARGET): + for item in contributions: + if item.table == "LiteLLM_TeamMembership": + await user_api_key_cache.async_delete_cache( + key=f"team_membership:{dict(item.key)['user_id']}:{dict(item.key)['team_id']}" + ) + + async def apply_accounting_entities( + self, + prisma_client: PrismaClient, + proxy_logging_obj: ProxyLogging, + transaction: _SpendTransaction, + updates: DBSpendUpdateTransactions, + ) -> None: + await self._commit_spend_updates_to_db( + prisma_client, 0, proxy_logging_obj, updates, outer_transaction=transaction + ) + async def _commit_spend_updates_to_db( self, prisma_client: PrismaClient, @@ -2141,6 +2305,7 @@ class DBSpendUpdateWriter: proxy_logging_obj: ProxyLogging, db_spend_update_transactions: DBSpendUpdateTransactions, on_table_committed: Callable[[_SpendTableName], None] | None = None, + outer_transaction: _SpendTransaction | None = None, ): """ Commits all the spend `UPDATE` transactions to the Database @@ -2155,7 +2320,9 @@ class DBSpendUpdateWriter: for i in range(n_retry_times + 1): start_time = time.time() try: - async with _spend_update_tx(prisma_client, "LiteLLM_UserTable") as transaction: + async with _spend_update_tx( + prisma_client, "LiteLLM_UserTable", outer_transaction=outer_transaction + ) as transaction: async with transaction.batch_() as batcher: # Sort by ID for consistent lock ordering across pods to prevent deadlocks. # batch_() issues statements sequentially within the tx, so iteration @@ -2167,6 +2334,8 @@ class DBSpendUpdateWriter: ) break except Exception as e: + if outer_transaction is not None: + raise await self.handle_spend_update_failure( e=e, attempt=i, @@ -2186,6 +2355,7 @@ class DBSpendUpdateWriter: prisma_client=prisma_client, proxy_logging_obj=proxy_logging_obj, end_user_list_transactions=end_user_list_transactions, + outer_transaction=outer_transaction, ) if on_table_committed is not None: on_table_committed("end_user_list_transactions") @@ -2196,7 +2366,9 @@ class DBSpendUpdateWriter: for i in range(n_retry_times + 1): start_time = time.time() try: - async with _spend_update_tx(prisma_client, "LiteLLM_VerificationToken") as transaction: + async with _spend_update_tx( + prisma_client, "LiteLLM_VerificationToken", outer_transaction=outer_transaction + ) as transaction: async with transaction.batch_() as batcher: # Sort by token for consistent lock ordering across pods to prevent deadlocks. for token, response_cost in sorted(key_list_transactions.items()): @@ -2211,6 +2383,8 @@ class DBSpendUpdateWriter: ) break except Exception as e: + if outer_transaction is not None: + raise await self.handle_spend_update_failure( e=e, attempt=i, @@ -2228,7 +2402,9 @@ class DBSpendUpdateWriter: for i in range(n_retry_times + 1): start_time = time.time() try: - async with _spend_update_tx(prisma_client, "LiteLLM_TeamTable") as transaction: + async with _spend_update_tx( + prisma_client, "LiteLLM_TeamTable", outer_transaction=outer_transaction + ) as transaction: async with transaction.batch_() as batcher: # Sort by team_id for consistent lock ordering across pods to prevent deadlocks. for team_id, response_cost in sorted(team_list_transactions.items()): @@ -2241,6 +2417,8 @@ class DBSpendUpdateWriter: ) break except Exception as e: + if outer_transaction is not None: + raise await self.handle_spend_update_failure( e=e, attempt=i, @@ -2266,11 +2444,15 @@ class DBSpendUpdateWriter: for i in range(n_retry_times + 1): start_time = time.time() try: - async with _spend_update_tx(prisma_client, "LiteLLM_TeamMembership") as transaction: + async with _spend_update_tx( + prisma_client, "LiteLLM_TeamMembership", outer_transaction=outer_transaction + ) as transaction: await _write_team_member_spend(transaction, team_member_list_transactions) # Transaction succeeded, break out of retry loop break except Exception as e: + if outer_transaction is not None: + raise await self.handle_spend_update_failure( e=e, attempt=i, @@ -2283,7 +2465,7 @@ class DBSpendUpdateWriter: # Invalidate cache for updated team memberships # This ensures budget checks read fresh spend data from the database - if team_memberships_to_invalidate and proxy_logging_obj is not None: + if outer_transaction is None and team_memberships_to_invalidate and proxy_logging_obj is not None: user_api_key_cache: Final = proxy_logging_obj.call_details.get("user_api_key_cache") if user_api_key_cache is not None: with service_target(AUTH_OBJECTS_TARGET): @@ -2303,7 +2485,9 @@ class DBSpendUpdateWriter: for i in range(n_retry_times + 1): start_time = time.time() try: - async with _spend_update_tx(prisma_client, "LiteLLM_OrganizationTable") as transaction: + async with _spend_update_tx( + prisma_client, "LiteLLM_OrganizationTable", outer_transaction=outer_transaction + ) as transaction: async with transaction.batch_() as batcher: # Sort by org_id for consistent lock ordering across pods to prevent deadlocks. for org_id, response_cost in sorted(org_list_transactions.items()): @@ -2313,6 +2497,8 @@ class DBSpendUpdateWriter: ) break except Exception as e: + if outer_transaction is not None: + raise await self.handle_spend_update_failure( e=e, attempt=i, @@ -2330,7 +2516,9 @@ class DBSpendUpdateWriter: start_time = time.time() try: async with ( - _spend_update_tx(prisma_client, "LiteLLM_OrganizationMembership") as transaction, + _spend_update_tx( + prisma_client, "LiteLLM_OrganizationMembership", outer_transaction=outer_transaction + ) as transaction, transaction.batch_() as batcher, ): for key, response_cost in sorted(org_member_list_transactions.items()): @@ -2341,6 +2529,8 @@ class DBSpendUpdateWriter: ) break except Exception as e: + if outer_transaction is not None: + raise await self.handle_spend_update_failure( e=e, attempt=i, @@ -2356,6 +2546,7 @@ class DBSpendUpdateWriter: await DBSpendUpdateWriter._update_entity_spend_in_db( entity_name="Project", transactions=project_list_transactions, + outer_transaction=outer_transaction, table_accessor="litellm_projecttable", where_field="project_id", n_retry_times=n_retry_times, @@ -2364,16 +2555,18 @@ class DBSpendUpdateWriter: ) if on_table_committed is not None: on_table_committed("project_list_transactions") - await DBSpendUpdateWriter._invalidate_project_caches( - project_ids=tuple(project_list_transactions or ()), - proxy_logging_obj=proxy_logging_obj, - ) + if outer_transaction is None: + await DBSpendUpdateWriter._invalidate_project_caches( + project_ids=tuple(project_list_transactions or ()), + proxy_logging_obj=proxy_logging_obj, + ) ### UPDATE TAG TABLE ### tag_list_transactions: Final = db_spend_update_transactions["tag_list_transactions"] await DBSpendUpdateWriter._update_entity_spend_in_db( entity_name="Tag", transactions=tag_list_transactions, + outer_transaction=outer_transaction, table_accessor="litellm_tagtable", where_field="tag_name", n_retry_times=n_retry_times, @@ -2390,6 +2583,7 @@ class DBSpendUpdateWriter: await DBSpendUpdateWriter._update_entity_spend_in_db( entity_name="Model access group", transactions=model_access_group_list_transactions, + outer_transaction=outer_transaction, table_accessor="litellm_modelaccessgroupbudgettable", where_field="access_group_name", n_retry_times=n_retry_times, @@ -2404,6 +2598,7 @@ class DBSpendUpdateWriter: await DBSpendUpdateWriter._update_entity_spend_in_db( entity_name="Agent", transactions=agent_list_transactions, + outer_transaction=outer_transaction, table_accessor="litellm_agentstable", where_field="agent_id", n_retry_times=n_retry_times, @@ -2433,6 +2628,7 @@ class DBSpendUpdateWriter: n_retry_times: int, prisma_client: PrismaClient, proxy_logging_obj: ProxyLogging, + outer_transaction: _SpendTransaction | None = None, ): """ Helper function to update spend for any entity type (team, org, tag, etc). @@ -2445,13 +2641,16 @@ class DBSpendUpdateWriter: n_retry_times: Number of retries on failure prisma_client: Prisma client instance proxy_logging_obj: Proxy logging object + outer_transaction: Existing ledger transaction owning the complete delivery update """ verbose_proxy_logger.debug("%s Spend transactions: %s", entity_name, transactions) if transactions is not None and len(transactions.keys()) > 0: for i in range(n_retry_times + 1): start_time = time.time() try: - async with _spend_update_tx(prisma_client, _ENTITY_SPEND_MODELS[table_accessor]) as transaction: + async with _spend_update_tx( + prisma_client, _ENTITY_SPEND_MODELS[table_accessor], outer_transaction=outer_transaction + ) as transaction: async with transaction.batch_() as batcher: # Sort by entity_id for consistent lock ordering across pods to prevent deadlocks. for entity_id, response_cost in sorted(transactions.items()): @@ -2468,6 +2667,8 @@ class DBSpendUpdateWriter: ) break except Exception as e: + if outer_transaction is not None: + raise await DBSpendUpdateWriter.handle_spend_update_failure( e=e, attempt=i, @@ -2801,6 +3002,12 @@ class DBSpendUpdateWriter: entity_id_field="tag", ) + def _record_request_error_safely(self, *, payload: SpendLogsPayload, prisma_client: PrismaClient | None) -> None: + try: + self._record_request_error(payload=payload, prisma_client=prisma_client) + except Exception as error: # noqa: BLE001 # error rollup failure must not skip sibling writes + _report_spend_update_step_failure("_record_request_error", payload=payload, exc=error) + @staticmethod def _record_request_error(*, payload: SpendLogsPayload, prisma_client: PrismaClient | None) -> None: if prisma_client is None: diff --git a/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py b/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py index 170eb450339..29f727ea41b 100644 --- a/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py +++ b/litellm/proxy/db/db_transaction_queue/spend_log_cleanup.py @@ -598,7 +598,7 @@ class SpendLogCleanup: rows: Final = _STORAGE_ROWS.validate_python( await tx.query_raw(trusted_sql(_STORAGE_SQL), list(_SPEND_LOG_TABLES)) ) - except Exception as e: # noqa: BLE001 - a failed measurement skips the size pass, it must not fail the run + except Exception as e: # noqa: BLE001 # a failed measurement skips the size pass, it must not fail the run verbose_proxy_logger.warning("Could not measure spend-log storage: %s: %s", type(e).__name__, e) return None if not rows: @@ -666,7 +666,7 @@ class SpendLogCleanup: await tx.query_raw(trusted_sql(_LOAD_SIZE_STATE_SQL), SPEND_LOG_SIZE_CLEANUP_STATE_PARAM) ) return SizeCleanupState.model_validate_json(rows[0].state_json) if rows else None - except Exception as e: # noqa: BLE001 - an unreadable count restarts from the catalog, it must not fail the run + except Exception as e: # noqa: BLE001 # an unreadable count restarts from the catalog, it must not fail the run verbose_proxy_logger.warning("Could not read the spend-log size cleanup state: %s: %s", type(e).__name__, e) return None @@ -678,7 +678,7 @@ class SpendLogCleanup: await tx.execute_raw( trusted_sql(_SAVE_SIZE_STATE_SQL), SPEND_LOG_SIZE_CLEANUP_STATE_PARAM, state.model_dump_json() ) - except Exception as e: # noqa: BLE001 - a lost save costs one re-seed from the catalog, it must not fail the run + except Exception as e: # noqa: BLE001 # a lost save costs one re-seed from the catalog, it must not fail the run verbose_proxy_logger.warning("Could not save the spend-log size cleanup state: %s: %s", type(e).__name__, e) async def _size_step_cutoff(self, prisma_client: PrismaClient, deadline: float, rows: int) -> datetime | None: diff --git a/litellm/proxy/db/db_transaction_queue/tool_discovery_queue.py b/litellm/proxy/db/db_transaction_queue/tool_discovery_queue.py index e9ec040023c..abbeab7f89d 100644 --- a/litellm/proxy/db/db_transaction_queue/tool_discovery_queue.py +++ b/litellm/proxy/db/db_transaction_queue/tool_discovery_queue.py @@ -55,3 +55,10 @@ class ToolDiscoveryQueue: """Return and clear all pending rows.""" items, self._pending = list(self._pending.values()), {} return items + + def requeue(self, items: Iterable[ToolDiscoveryQueueItem]) -> None: + """Put rows from a failed write back, ahead of and merged with anything queued since the flush.""" + since_flush: Final = self._pending + self._pending = {} + for item in (*items, *since_flush.values()): + self.add_update(item) diff --git a/litellm/proxy/db/exception_handler.py b/litellm/proxy/db/exception_handler.py index 13a14e95e56..c2d58512fea 100644 --- a/litellm/proxy/db/exception_handler.py +++ b/litellm/proxy/db/exception_handler.py @@ -31,9 +31,30 @@ _CONNECTION_CAPACITY_PHRASES: Final = ( "too many connections for database", "remaining connection slots are reserved", ) +_NOT_ACCEPTING_CONNECTIONS_SQLSTATE: Final = "57P03" +_NOT_ACCEPTING_CONNECTIONS_PHRASES: Final = ( + "the database system is starting up", + "the database system is shutting down", + "the database system is not yet accepting connections", + "the database system is not accepting connections", + "the database system is in recovery mode", +) +_SERVER_TERMINATED_SQLSTATES: Final = frozenset({"57P01", "57P02", "57P05"}) +_SERVER_TERMINATED_PHRASES: Final = ( + "terminating connection due to administrator command", + "terminating connection due to immediate shutdown command", + "terminating connection because of unexpected sigquit signal", + "terminating connection because of crash of another server process", + "terminating connection due to idle-session timeout", +) +_UNREACHABLE_PRISMA_CODE: Final = "P1001" +_UNREACHABLE_PHRASES: Final = ("can't reach database server", "cannot reach database server") _PRISMA_POOL_TIMEOUT_CODE: Final = "P2024" _LOCK_TIMEOUT_SQLSTATE: Final = "55P03" _LOCK_TIMEOUT_PHRASE: Final = "canceling statement due to lock timeout" +_STATEMENT_TIMEOUT_SQLSTATE: Final = "57014" +_REJECTED_ROW_SQLSTATE_CLASSES: Final = frozenset({"22", "23", "54"}) +_STATEMENT_TIMEOUT_PHRASE: Final = "canceling statement due to statement timeout" def exception_chain(e: BaseException) -> Iterator[BaseException]: @@ -137,6 +158,8 @@ class PrismaDBExceptionHandler: return True if PrismaDBExceptionHandler.is_database_capacity_error(e): return True + if PrismaDBExceptionHandler.is_database_not_accepting_connections_error(e): + return True return isinstance(e, ProxyException) and e.type == ProxyErrorTypes.no_db_connection @staticmethod @@ -199,6 +222,20 @@ class PrismaDBExceptionHandler: return type(e) is prisma.errors.DataError + @staticmethod + def is_rejected_row_error(e: Exception) -> bool: + """True iff Postgres refused the rows themselves: a base ``DataError``, or a raw query failing with a data + exception (SQLSTATE class 22), integrity violation (class 23) or a value too large for an index (class 54). Systemic raw failures such as a missing + table (42P01) or a deadlock (40P01) stay False so the batch is retried instead of dropped.""" + import prisma + + if PrismaDBExceptionHandler.is_prisma_data_error(e): + return True + if not isinstance(e, _exception_types(prisma.errors.RawQueryError)): + return False + sqlstate: Final = PrismaDBExceptionHandler.postgres_sqlstate(e) + return sqlstate is not None and sqlstate[:2] in _REJECTED_ROW_SQLSTATE_CLASSES + @staticmethod def is_database_transport_error(e: Exception) -> bool: """ @@ -287,6 +324,39 @@ class PrismaDBExceptionHandler: error_message: Final = str(e).lower() return any(phrase in error_message for phrase in _CONNECTION_CAPACITY_PHRASES) + @staticmethod + def is_database_not_accepting_connections_error(e: Exception) -> bool: + """True iff Postgres refused the connection because it is starting up, shutting + down or in crash recovery (SQLSTATE 57P03). The refusal comes before any statement + runs, so nothing the write carried was applied.""" + import prisma + + if not isinstance(e, _exception_types(prisma.errors.PrismaError)): + return False + if PrismaDBExceptionHandler.postgres_sqlstate(e) == _NOT_ACCEPTING_CONNECTIONS_SQLSTATE: + return True + error_message: Final = str(e).lower() + return any(phrase in error_message for phrase in _NOT_ACCEPTING_CONNECTIONS_PHRASES) + + @staticmethod + def is_database_lifecycle_error(e: Exception) -> bool: + """True iff Postgres failed the statement because of a server lifecycle event: + a refused connection during startup, shutdown or recovery (57P03), or a session + the server terminated (57P01, 57P02, 57P05). The server comes back on its own, + so the rows are not at fault. A terminated session may have committed before it + was cut, so only ``is_database_not_accepting_connections_error`` proves a + non-idempotent write never applied.""" + import prisma + + if PrismaDBExceptionHandler.is_database_not_accepting_connections_error(e): + return True + if not isinstance(e, _exception_types(prisma.errors.PrismaError)): + return False + if PrismaDBExceptionHandler.postgres_sqlstate(e) in _SERVER_TERMINATED_SQLSTATES: + return True + error_message: Final = str(e).lower() + return any(phrase in error_message for phrase in _SERVER_TERMINATED_PHRASES) + @staticmethod def is_lock_timeout_error(e: Exception) -> bool: """True iff Postgres cancelled a statement for exceeding ``lock_timeout`` @@ -302,6 +372,17 @@ class PrismaDBExceptionHandler: return True return _LOCK_TIMEOUT_PHRASE in str(e).lower() + @staticmethod + def is_statement_timeout_error(e: Exception) -> bool: + """True iff Postgres cancelled a statement for exceeding ``statement_timeout`` (SQLSTATE 57014).""" + import prisma + + if not isinstance(e, _exception_types(prisma.errors.PrismaError)): + return False + if PrismaDBExceptionHandler.postgres_sqlstate(e) == _STATEMENT_TIMEOUT_SQLSTATE: + return True + return _STATEMENT_TIMEOUT_PHRASE in str(e).lower() + @staticmethod def postgres_sqlstate(e: Exception) -> str | None: """The SQLSTATE Postgres attached to a failed statement, as prisma surfaces it, or None.""" @@ -393,6 +474,8 @@ class PrismaDBExceptionHandler: return True if PrismaDBExceptionHandler.is_database_capacity_error(e): return True + if PrismaDBExceptionHandler.is_database_lifecycle_error(e): + return True if PrismaDBExceptionHandler.is_prisma_engine_internal_error(e): return True if "cached plan must not change result type" in str(e).lower(): @@ -667,3 +750,18 @@ def db_write_failure_is_requeue_safe(e: Exception) -> bool: return isinstance(e, DB_RETRY_SAFE_ERROR_TYPES) sqlstate: Final = PrismaDBExceptionHandler.postgres_sqlstate(e) return sqlstate is None or sqlstate[:2] not in _DATA_REJECTED_SQLSTATE_CLASSES + + +def db_write_never_sent(e: Exception) -> bool: + """Whether the database could not take the write at all, because it was unreachable (P1001), + refusing connections (57P03) or full (53300, P2024), so even a non-idempotent write can be sent again.""" + if PrismaDBExceptionHandler.is_database_not_accepting_connections_error(e): + return True + if PrismaDBExceptionHandler.is_database_capacity_error(e): + return True + if _prisma_error_code(e) == _UNREACHABLE_PRISMA_CODE: + return True + if not PrismaDBExceptionHandler.is_prisma_error(e): + return False + error_message: Final = str(e).lower() + return any(phrase in error_message for phrase in _UNREACHABLE_PHRASES) diff --git a/litellm/proxy/db/model_usage_rollup.py b/litellm/proxy/db/model_usage_rollup.py index 4566b10b260..f8cdabe9296 100644 --- a/litellm/proxy/db/model_usage_rollup.py +++ b/litellm/proxy/db/model_usage_rollup.py @@ -32,14 +32,15 @@ class _UpsertTable(Protocol): def upsert(self, *, where: Mapping[str, object], data: Mapping[str, object]) -> None: ... -class _ModelUsageBatch(Protocol): - litellm_dailymodelusage: _UpsertTable +class ModelUsageBatch(Protocol): + @property + def litellm_dailymodelusage(self) -> _UpsertTable: ... def execute_raw(self, query: LiteralString, *args: object) -> None: ... -class _ModelUsageBatchManager(Protocol): - async def __aenter__(self) -> _ModelUsageBatch: ... +class ModelUsageBatchManager(Protocol): + async def __aenter__(self) -> ModelUsageBatch: ... async def __aexit__(self, exc_type: object, exc_value: object, traceback: object) -> bool | None: ... @@ -88,14 +89,14 @@ def _internal_call_origin(metadata: str) -> object: return decoded.get(INTERNAL_CALL_ORIGIN_METADATA_KEY) -def _date_from_start_time(start_time: datetime | str) -> str | None: +def date_from_start_time(start_time: datetime | str) -> str | None: if isinstance(start_time, datetime): return start_time.date().isoformat() return start_time[:10] if len(start_time) >= 10 else None def build_model_usage_transaction(payload: SpendLogsPayload) -> ModelUsageTransaction | None: - date: Final = _date_from_start_time(payload["startTime"]) + date: Final = date_from_start_time(payload["startTime"]) origin: Final = _internal_call_origin(payload["metadata"]) if date is None or (origin and origin != BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN): return None @@ -116,8 +117,8 @@ def build_model_usage_transaction(payload: SpendLogsPayload) -> ModelUsageTransa ) -def _model_usage_batch(prisma_client: PrismaClient) -> _ModelUsageBatchManager: - batch: Final[_ModelUsageBatchManager] = prisma_client.db.batch_() +def _model_usage_batch(prisma_client: PrismaClient) -> ModelUsageBatchManager: + batch: Final[ModelUsageBatchManager] = prisma_client.db.batch_() return batch @@ -156,26 +157,16 @@ async def flush_model_usage_transactions( "custom_llm_provider": key.custom_llm_provider, "task_type": key.task_type, } - batcher.litellm_dailymodelusage.upsert( - where={"date_model_group_model_custom_llm_provider_task_type": key_fields}, - data={ - "create": { - **key_fields, - "spend": spend, - "prompt_tokens": prompt_tokens, - "completion_tokens": completion_tokens, - "request_count": len(requests), - "successful_requests": successful, - "failed_requests": failed, - }, - "update": { - "spend": {"increment": spend}, - "prompt_tokens": {"increment": prompt_tokens}, - "completion_tokens": {"increment": completion_tokens}, - "request_count": {"increment": len(requests)}, - "successful_requests": {"increment": successful}, - "failed_requests": {"increment": failed}, - }, + queue_model_usage_upsert( + batcher, + key_fields, + { + "spend": spend, + "prompt_tokens": prompt_tokens, + "completion_tokens": completion_tokens, + "request_count": len(requests), + "successful_requests": successful, + "failed_requests": failed, }, ) return @@ -183,3 +174,15 @@ async def flush_model_usage_transactions( if attempt >= n_retry_times: raise await asyncio.sleep(2.0**attempt + random.uniform(0, 1)) + + +def queue_model_usage_upsert( + batcher: ModelUsageBatch, key_fields: Mapping[str, str], increments: Mapping[str, int | float] +) -> None: + batcher.litellm_dailymodelusage.upsert( + where={"date_model_group_model_custom_llm_provider_task_type": key_fields}, + data={ + "create": {**key_fields, **increments}, + "update": {name: {"increment": value} for name, value in increments.items()}, + }, + ) diff --git a/litellm/proxy/db/tool_registry_writer.py b/litellm/proxy/db/tool_registry_writer.py index f7ec88945a1..9600fb40ad3 100644 --- a/litellm/proxy/db/tool_registry_writer.py +++ b/litellm/proxy/db/tool_registry_writer.py @@ -23,7 +23,11 @@ from litellm.proxy.db.db_transaction_queue.tool_discovery_queue import ( ToolDiscoveryQueue, aggregate_tool_discoveries, ) -from litellm.proxy.db.exception_handler import call_with_db_reconnect_retry, db_write_failure_is_requeue_safe +from litellm.proxy.db.exception_handler import ( + call_with_db_reconnect_retry, + db_write_failure_is_requeue_safe, + db_write_never_sent, +) from litellm.proxy.db.tool_table_bulk_upsert import build_tool_bulk_upsert from litellm.repositories.object_permission_repository import ObjectPermissionRepository from litellm.repositories.prisma_protocols import TableActions @@ -134,8 +138,19 @@ async def flush_tool_discovery_queue(prisma_client: "PrismaClient", tool_discove return try: await batch_upsert_tools(prisma_client=prisma_client, items=items) - except Exception as e: # noqa: BLE001 # a lost tool row only delays its discovery, the scheduler job must not fail - verbose_proxy_logger.debug("flush_tool_discovery_queue error (non-blocking): %s", e) + except Exception as e: # noqa: BLE001 # the rows go back to the queue or are dropped, the scheduler job must not fail + if db_write_never_sent(e): + tool_discovery_queue.requeue(items) + verbose_proxy_logger.warning( + "Tool discovery - %d tool rows went back to the queue for the next tick. Error: %s", len(items), str(e) + ) + return + verbose_proxy_logger.error( + "Tool discovery - dropped %d tool rows: the failed statement may have applied or the database " + "refused the data, so re-sending it is not safe. Error: %s", + len(items), + str(e), + ) async def commit_tool_discoveries( diff --git a/litellm/proxy/deps/repositories.py b/litellm/proxy/deps/repositories.py index e37ecfd582a..323cf57dfec 100644 --- a/litellm/proxy/deps/repositories.py +++ b/litellm/proxy/deps/repositories.py @@ -4,10 +4,14 @@ from fastapi import Depends from litellm.models.deployment_warning import DeploymentWarningIgnoreStore from litellm.models.gateway_activity import GatewayActivityStore +from litellm.models.plugin_upload import PluginUploadStore +from litellm.models.skill_submission import SkillSubmissionStore from litellm.models.user_banner import UserBannerStore from litellm.proxy.deps.database import DatabaseDep from litellm.repositories.deployment_warning_ignore_repository import DeploymentWarningIgnoreRepository from litellm.repositories.gateway_activity_repository import GatewayActivityRepository +from litellm.repositories.plugin_upload_repository import PluginUploadRepository +from litellm.repositories.skill_submission_repository import SkillSubmissionRepository from litellm.repositories.user_banner_repository import UserBannerRepository @@ -34,3 +38,19 @@ async def get_gateway_activity_repository(database: DatabaseDep) -> GatewayActiv GatewayActivityRepositoryDep: TypeAlias = Annotated[ GatewayActivityStore | None, Depends(get_gateway_activity_repository) ] + + +async def get_plugin_upload_repository(database: DatabaseDep) -> PluginUploadStore | None: + return None if database is None else PluginUploadRepository(database.prisma) + + +PluginUploadRepositoryDep: TypeAlias = Annotated[PluginUploadStore | None, Depends(get_plugin_upload_repository)] + + +async def get_skill_submission_repository(database: DatabaseDep) -> SkillSubmissionStore | None: + return None if database is None else SkillSubmissionRepository(database.prisma) + + +SkillSubmissionRepositoryDep: TypeAlias = Annotated[ + SkillSubmissionStore | None, Depends(get_skill_submission_repository) +] diff --git a/litellm/proxy/discovery_endpoints/agent_skills_archive.py b/litellm/proxy/discovery_endpoints/agent_skills_archive.py index 94a0c3e2cf1..e45ca7e10f2 100644 --- a/litellm/proxy/discovery_endpoints/agent_skills_archive.py +++ b/litellm/proxy/discovery_endpoints/agent_skills_archive.py @@ -8,26 +8,66 @@ SHA-256 digest published in the index reproducible for identical uploads. import hashlib import io +import lzma import re +import stat +import struct import zipfile -from collections.abc import Mapping +import zlib +from collections.abc import Iterable, Mapping, Sequence from dataclasses import dataclass from types import MappingProxyType -from typing import Final +from typing import ClassVar, Final import yaml -from pydantic import TypeAdapter +from pydantic import ConfigDict, TypeAdapter, ValidationError MAX_ARCHIVE_UNPACKED_BYTES: Final = 50 * 1024 * 1024 MAX_ARCHIVE_ENTRIES: Final = 1000 +MAX_SKILL_FILE_BYTES: Final = 10 * 1024 * 1024 +MAX_SKILL_MANIFEST_BYTES: Final = 1024 * 1024 +SKILL_ARCHIVE_ERRORS: Final = ( + zipfile.BadZipFile, + OSError, + RuntimeError, + EOFError, + lzma.LZMAError, + zlib.error, + struct.error, + UnicodeError, +) SKILL_MANIFEST_FILENAME: Final = "SKILL.md" _ZIP_ENTRY_TIMESTAMP: Final = (1980, 1, 1, 0, 0, 0) -_ZIP_ENTRY_PERMISSIONS: Final = 0o644 << 16 +_ZIP_ENTRY_MODE: Final = 0o644 _FRONTMATTER_PATTERN: Final = re.compile(r"^---\s*\n(.*?)\n---\s*(?:\n|$)", re.DOTALL) +_AGENT_SKILL_FRONTMATTER_PATTERN: Final = re.compile(r"\A---[ \t]*\r?\n(.*?)\r?\n---[ \t]*(?:\r?\n|\Z)", re.DOTALL) +_AGENT_SKILL_YAML_SCALARS: Final = MappingProxyType( + { + "tag:yaml.org,2002:null": re.compile(r"^(?:null|Null|NULL|~|)$"), + "tag:yaml.org,2002:bool": re.compile(r"^(?:true|True|TRUE|false|False|FALSE)$"), + "tag:yaml.org,2002:int": re.compile(r"^(?:[-+]?[0-9]+|0o[0-7]+|0x[0-9a-fA-F]+)$"), + "tag:yaml.org,2002:float": re.compile( + r"^(?:[-+]?(?:\.[0-9]+|[0-9]+(?:\.[0-9]*)?)(?:[eE][-+]?[0-9]+)?" + r"|[-+]?\.(?:inf|Inf|INF)|\.(?:nan|NaN|NAN))$" + ), + } +) +_MAX_FRONTMATTER_DEPTH: Final = 32 _WINDOWS_DRIVE_PATTERN: Final = re.compile(r"^[A-Za-z]:") _EMPTY_FRONTMATTER: Final[Mapping[str, object]] = MappingProxyType({}) _DECODED_YAML: Final = TypeAdapter(object) +_YAML_EVENTS: Final = TypeAdapter(Iterable[object]) +_YAML_NODES: Final = TypeAdapter(tuple[yaml.Node, ...], config=ConfigDict(arbitrary_types_allowed=True)) +_YAML_PAIRS: Final = TypeAdapter( + tuple[tuple[yaml.Node, yaml.Node], ...], config=ConfigDict(arbitrary_types_allowed=True) +) + + +class _AgentSkillFrontmatterLoader(yaml.BaseLoader): + yaml_implicit_resolvers: ClassVar[Mapping[str | None, Sequence[tuple[str, re.Pattern[str]]]]] = { # pyright: ignore[reportIncompatibleVariableOverride] # PyYAML resolver tables are class state + None: list(_AGENT_SKILL_YAML_SCALARS.items()) + } @dataclass(frozen=True, slots=True) @@ -36,47 +76,140 @@ class SkillArchive: digest: str declared_name: str | None declared_description: str | None + manifest_content: bytes + + +def read_skill_archive_members( + stored_content: bytes, *, for_upload: bool = False, skill_path: str | None = None +) -> tuple[tuple[str, bytes, int], ...] | None: + try: + with zipfile.ZipFile(io.BytesIO(stored_content)) as uploaded: + return _flattened_members(uploaded, for_upload=for_upload, skill_path=skill_path) + except SKILL_ARCHIVE_ERRORS: + return None + + +def read_skill_archive_entry(uploaded: zipfile.ZipFile, info: zipfile.ZipInfo) -> bytes: + with uploaded.open(info) as member: + return member.read(info.file_size + 1) def build_skill_archive(stored_content: bytes) -> SkillArchive | None: """Return the installable archive for an upload, or None when it holds no root SKILL.md.""" - try: - with zipfile.ZipFile(io.BytesIO(stored_content)) as uploaded: - members: Final = _flattened_members(uploaded) - except (zipfile.BadZipFile, OSError, RuntimeError): - return None - + members: Final = read_skill_archive_members(stored_content) if members is None: return None - frontmatter: Final = _manifest_frontmatter(next(data for name, data in members if name == SKILL_MANIFEST_FILENAME)) - content: Final = _repack(members) + manifest_content: Final = next(data for name, data, _ in members if name == SKILL_MANIFEST_FILENAME) + frontmatter: Final = _manifest_frontmatter(manifest_content) + content: Final = pack_skill_archive(members) return SkillArchive( content=content, digest=f"sha256:{hashlib.sha256(content).hexdigest()}", declared_name=_frontmatter_text(frontmatter, "name"), declared_description=_frontmatter_text(frontmatter, "description"), + manifest_content=manifest_content, ) -def _flattened_members(uploaded: zipfile.ZipFile) -> tuple[tuple[str, bytes], ...] | None: - infos: Final = tuple(info for info in uploaded.infolist() if not info.is_dir()) +def build_agent_skill_archive( + content: bytes, *, skill_path: str | None = None, plugin_name: str | None = None +) -> SkillArchive | None: + members: Final = read_skill_archive_members(content, for_upload=True, skill_path=skill_path) + selected: Final = ( + members + if members is not None or plugin_name is None + else read_skill_archive_members(content, for_upload=True, skill_path=f"skills/{plugin_name}") + ) + if selected is None: + return None + manifest_content: Final = next(data for path, data, _ in selected if path == SKILL_MANIFEST_FILENAME) + manifest: Final = agent_skill_frontmatter(manifest_content) + name: Final = _frontmatter_text(manifest, "name") + description: Final = _frontmatter_text(manifest, "description") + if ( + name is None + or not re.fullmatch(r"[a-z0-9]+(?:-[a-z0-9]+)*", name) + or len(name) > 64 + or description is None + or len(description) > 1024 + ): + return None + archive: Final = pack_skill_archive(selected) + return SkillArchive( + content=archive, + digest=f"sha256:{hashlib.sha256(archive).hexdigest()}", + declared_name=name, + declared_description=description, + manifest_content=manifest_content, + ) + + +def _flattened_members( + uploaded: zipfile.ZipFile, *, for_upload: bool, skill_path: str | None +) -> tuple[tuple[str, bytes, int], ...] | None: + kept: Final = skill_archive_entries(uploaded, for_upload=for_upload) + if kept is None: + return None + prefix: Final = f"{skill_path}/" if skill_path is not None else _common_root_prefix(tuple(path for _, path in kept)) + flattened: Final = tuple((info, path[len(prefix) :]) for info, path in kept if path.startswith(prefix)) + names: Final = frozenset(name for _, name in flattened) + if ( + SKILL_MANIFEST_FILENAME not in names + or len(names) != len(flattened) + or (for_upload and any(not safe_skill_archive_entry(info) for info, _ in flattened)) + ): + return None + + return tuple( + (name, read_skill_archive_entry(uploaded, info), _entry_mode(info, preserve_executable_bits=for_upload)) + for info, name in sorted(flattened, key=lambda member: member[1]) + ) + + +def skill_archive_entries( + uploaded: zipfile.ZipFile, *, for_upload: bool +) -> tuple[tuple[zipfile.ZipInfo, str], ...] | None: + infos: Final = tuple(info for info in uploaded.infolist() if for_upload or not info.is_dir()) if not infos or len(infos) > MAX_ARCHIVE_ENTRIES: return None if sum(info.file_size for info in infos) > MAX_ARCHIVE_UNPACKED_BYTES: return None - normalized: Final = tuple((info, _normalized_path(info.filename)) for info in infos) + normalized: Final = tuple( + (info, _normalized_path(info.orig_filename if for_upload else info.filename)) for info in infos + ) if any(path is None for _, path in normalized): return None - - prefix: Final = _common_root_prefix(tuple(path for _, path in normalized if path is not None)) - flattened: Final = tuple((info, path[len(prefix) :]) for info, path in normalized if path is not None) - names: Final = frozenset(name for _, name in flattened) - if SKILL_MANIFEST_FILENAME not in names or len(names) != len(flattened): + if for_upload and len(frozenset(path for _, path in normalized)) != len(normalized): return None - return tuple((name, uploaded.read(info)) for info, name in sorted(flattened, key=lambda member: member[1])) + return tuple( + (info, path) + for info, path in normalized + if path is not None and not info.is_dir() and (not for_upload or not _is_macos_metadata(path)) + ) + + +def _entry_mode(info: zipfile.ZipInfo, *, preserve_executable_bits: bool) -> int: + if not preserve_executable_bits or info.create_system != 3: + return _ZIP_ENTRY_MODE + mode: Final = info.external_attr >> 16 + if stat.S_IFMT(mode) not in (0, stat.S_IFREG): + return _ZIP_ENTRY_MODE + return _ZIP_ENTRY_MODE | (mode & 0o111) + + +def safe_skill_archive_entry(info: zipfile.ZipInfo) -> bool: + return ( + info.file_size <= MAX_SKILL_FILE_BYTES + and not info.flag_bits & 1 + and (info.create_system != 3 or stat.S_IFMT(info.external_attr >> 16) in (0, stat.S_IFREG, stat.S_IFDIR)) + ) + + +def _is_macos_metadata(path: str) -> bool: + return path.split("/", 1)[0] == "__MACOSX" or path.rsplit("/", 1)[-1] == ".DS_Store" def _common_root_prefix(paths: tuple[str, ...]) -> str: @@ -110,6 +243,65 @@ def _manifest_frontmatter(manifest: bytes) -> Mapping[str, object]: return parsed +def agent_skill_frontmatter(manifest: bytes) -> Mapping[str, str]: + if len(manifest) > MAX_SKILL_MANIFEST_BYTES: + return MappingProxyType({}) + try: + match: Final = _AGENT_SKILL_FRONTMATTER_PATTERN.match(manifest.decode("utf-8-sig")) + if match is None: + return MappingProxyType({}) + frontmatter: Final = match.group(1) + events: Final = _YAML_EVENTS.validate_python(yaml.parse(frontmatter, Loader=yaml.BaseLoader)) # pyright: ignore[reportUnknownMemberType] # PyYAML parse stubs omit their event iterator return type + if any(isinstance(event, yaml.AliasEvent) for event in events): + return MappingProxyType({}) + node: Final = _DECODED_YAML.validate_python(yaml.compose(frontmatter, Loader=_AgentSkillFrontmatterLoader)) # pyright: ignore[reportUnknownMemberType] # PyYAML compose stubs omit their return type + except (yaml.YAMLError, UnicodeError, RecursionError, ValidationError): + return MappingProxyType({}) + if not isinstance(node, yaml.MappingNode) or not _valid_frontmatter_node(node): + return MappingProxyType({}) + pairs: Final = _YAML_PAIRS.validate_python(node.value) + fields: Final = { + key_text: value_text + for key, value in pairs + if (key_text := _frontmatter_string(key)) is not None and (value_text := _frontmatter_string(value)) is not None + } + if "name" not in fields or "description" not in fields: + return MappingProxyType({}) + return MappingProxyType(fields) + + +def _frontmatter_string(node: yaml.Node) -> str | None: + if not isinstance(node, yaml.ScalarNode) or node.tag != "tag:yaml.org,2002:str": + return None + value: Final = _DECODED_YAML.validate_python(node.value) + return value if isinstance(value, str) else None + + +def _valid_frontmatter_node(node: yaml.Node, depth: int = 0) -> bool: + if depth > _MAX_FRONTMATTER_DEPTH: + return False + if isinstance(node, yaml.ScalarNode): + pattern: Final = _AGENT_SKILL_YAML_SCALARS.get(node.tag) + scalar: Final = _DECODED_YAML.validate_python(node.value) + return isinstance(scalar, str) and ( + node.tag == "tag:yaml.org,2002:str" or (pattern is not None and pattern.fullmatch(scalar) is not None) + ) + if isinstance(node, yaml.SequenceNode): + values: Final = _YAML_NODES.validate_python(node.value) + return node.tag == "tag:yaml.org,2002:seq" and all( + _valid_frontmatter_node(value, depth + 1) for value in values + ) + if not isinstance(node, yaml.MappingNode) or node.tag != "tag:yaml.org,2002:map": + return False + pairs: Final = _YAML_PAIRS.validate_python(node.value) + keys: Final = tuple(_frontmatter_string(key) for key, _ in pairs) + return ( + None not in keys + and len(frozenset(keys)) == len(keys) + and all(_valid_frontmatter_node(value, depth + 1) for _, value in pairs) + ) + + def _frontmatter_text(frontmatter: Mapping[str, object], key: str) -> str | None: value: Final = frontmatter.get(key) if not isinstance(value, str): @@ -117,16 +309,16 @@ def _frontmatter_text(frontmatter: Mapping[str, object], key: str) -> str | None return value.strip() or None -def _zip_entry(name: str) -> zipfile.ZipInfo: +def _zip_entry(name: str, mode: int) -> zipfile.ZipInfo: entry: Final = zipfile.ZipInfo(filename=name, date_time=_ZIP_ENTRY_TIMESTAMP) - entry.compress_type = zipfile.ZIP_DEFLATED - entry.external_attr = _ZIP_ENTRY_PERMISSIONS + entry.create_system = 3 + entry.external_attr = mode << 16 return entry -def _repack(members: tuple[tuple[str, bytes], ...]) -> bytes: +def pack_skill_archive(members: tuple[tuple[str, bytes, int], ...], compression: int = zipfile.ZIP_DEFLATED) -> bytes: buffer: Final = io.BytesIO() - with zipfile.ZipFile(buffer, mode="w", compression=zipfile.ZIP_DEFLATED) as repacked: - for name, data in members: - repacked.writestr(_zip_entry(name), data) + with zipfile.ZipFile(buffer, mode="w") as repacked: + for name, data, mode in members: + repacked.writestr(_zip_entry(name, mode), data, compress_type=compression) return buffer.getvalue() diff --git a/litellm/proxy/discovery_endpoints/agent_skills_endpoints.py b/litellm/proxy/discovery_endpoints/agent_skills_endpoints.py index 830f7b0334e..3b589b1a4f0 100644 --- a/litellm/proxy/discovery_endpoints/agent_skills_endpoints.py +++ b/litellm/proxy/discovery_endpoints/agent_skills_endpoints.py @@ -9,7 +9,7 @@ is enabled, which publishes every stored skill to anyone who can reach the proxy import asyncio import re from collections.abc import Sequence -from itertools import groupby +from itertools import count from types import MappingProxyType from typing import Final @@ -19,6 +19,7 @@ import litellm from litellm._logging import verbose_proxy_logger from litellm.caching.in_memory_cache import InMemoryCache from litellm.models.skills import LiteLLM_SkillsTable +from litellm.proxy.deps.repositories import PluginUploadRepositoryDep from litellm.proxy.discovery_endpoints.agent_skills_archive import SkillArchive, build_skill_archive from litellm.types.proxy.discovery_endpoints.agent_skills_endpoints import ( MAX_SKILL_DESCRIPTION_LENGTH, @@ -83,28 +84,34 @@ async def stored_skill(skill_id: str) -> LiteLLM_SkillsTable | None: ) async def agent_skills_index( request: Request, + uploads: PluginUploadRepositoryDep, skills: Sequence[LiteLLM_SkillsTable] = Depends(stored_skills), ) -> AgentSkillsIndex: - """Agent Skills v0.2.0 discovery index over every skill stored on this proxy.""" + """Discover public Hub skills and the separately enabled hosted skill store.""" + from litellm.proxy.discovery_endpoints.skill_hub_endpoints import public_hub_entries from litellm.proxy.utils import get_custom_url - installable: Final = await _installable(skills) + installable: Final = await _installable(skills[:MAX_INDEXED_SKILLS]) names: Final = _deduplicated(tuple(_base_name(skill, archive) for skill, archive in installable)) - - return AgentSkillsIndex( - skills=tuple( - AgentSkillsIndexEntry( - name=name, - type="archive", - description=_description(skill, archive, name), - url=get_custom_url( - request_base_url=str(request.base_url), - route=f"v1/skills/{skill.skill_id}/archive", - ), - digest=archive.digest, - ) - for (skill, archive), name in zip(installable, names, strict=True) + legacy: Final = tuple( + AgentSkillsIndexEntry( + name=name, + type="archive", + description=_description(skill, archive, name), + url=get_custom_url( + request_base_url=str(request.base_url), + route=f"v1/skills/{skill.skill_id}/archive", + ), + digest=archive.digest, ) + for (skill, archive), name in zip(installable, names, strict=True) + ) + remaining: Final = MAX_INDEXED_SKILLS - len(legacy) + hub: Final = (await public_hub_entries(request, uploads))[:remaining] if remaining else () + hub_names: Final = _deduplicated(tuple(entry.name for entry in hub), reserved=frozenset(names)) + return AgentSkillsIndex( + skills=legacy + + tuple(entry.model_copy(update={"name": name}) for entry, name in zip(hub, hub_names, strict=True)) ) @@ -153,7 +160,7 @@ async def _archive_for(skill: LiteLLM_SkillsTable) -> SkillArchive | None: ) return None - if cache_key is not None and len(archive.content) <= MAX_CACHED_ARCHIVE_BYTES: + if cache_key is not None and len(archive.content) + len(archive.manifest_content) <= MAX_CACHED_ARCHIVE_BYTES: _ARCHIVE_CACHE.set_cache(cache_key, archive) return archive @@ -172,19 +179,25 @@ def _slugify(raw: str | None) -> str | None: return _NON_SLUG_PATTERN.sub("-", raw.lower()).strip("-")[:MAX_SKILL_NAME_LENGTH].rstrip("-") or None -def _entry_name(entry: tuple[int, str]) -> str: - return entry[1] +def _deduplicated(names: Sequence[str], reserved: frozenset[str] = frozenset()) -> tuple[str, ...]: + natural_names: Final = frozenset(names) | reserved + ordinals: Final = MappingProxyType({name: count(1) for name in frozenset(names)}) + used: Final[set[str]] = set(reserved) # mutable-ok: bounded local allocation avoids rebuilding the set + def allocate(name: str) -> str: + selected: Final = ( + name + if name not in used + else next( + candidate + for candidate in (_with_ordinal(name, ordinal) for ordinal in ordinals[name]) + if candidate not in natural_names and candidate not in used + ) + ) + used.add(selected) + return selected -def _deduplicated(names: Sequence[str]) -> tuple[str, ...]: - ordinals: Final = MappingProxyType( - { - position: ordinal - for _, duplicates in groupby(sorted(enumerate(names), key=_entry_name), key=_entry_name) - for ordinal, (position, _) in enumerate(duplicates) - } - ) - return tuple(_with_ordinal(name, ordinals[position]) for position, name in enumerate(names)) + return tuple(allocate(name) for name in names) def _with_ordinal(name: str, ordinal: int) -> str: diff --git a/litellm/proxy/discovery_endpoints/skill_hub_endpoints.py b/litellm/proxy/discovery_endpoints/skill_hub_endpoints.py new file mode 100644 index 00000000000..93d1ace435d --- /dev/null +++ b/litellm/proxy/discovery_endpoints/skill_hub_endpoints.py @@ -0,0 +1,682 @@ +import asyncio +import hashlib +from collections.abc import Mapping +from dataclasses import dataclass, replace +from datetime import datetime +from typing import Annotated, Final +from urllib.parse import quote + +import httpx +from fastapi import APIRouter, Depends, File, Form, HTTPException, Query, Request, Response, UploadFile + +import litellm +from litellm.llms.custom_httpx.http_handler import ( + get_async_httpx_client, # pyright: ignore[reportUnknownVariableType] # shared HTTP factory has untyped optional params +) +from litellm.models.plugin_upload import ( + PluginArchiveMetadata, + PluginDownloader, + PluginDownloadsResponse, + PluginPublication, + PluginSnapshot, + PluginUploadStore, + PluginVersion, + PublishedPlugin, + has_agent_skill_metadata, +) +from litellm.models.skill_submission import SkillSubmission, SkillSubmissionStore +from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy.anthropic_endpoints.claude_code_endpoints.claude_code_marketplace import ( + MANIFEST_FIELDS, + delete_plugin, + disable_plugin, + enable_plugin, + get_plugin_downloads, + header_key_caller, + list_plugins, + plugin_archive_source_matches, + plugin_archive_url, + plugin_downloader, + require_download_recorded, +) +from litellm.proxy.anthropic_endpoints.claude_code_endpoints.claude_code_skill_access import resolve_skill_visibility +from litellm.proxy.anthropic_endpoints.claude_code_endpoints.skill_upload_archive import build_uploaded_skill_archive +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.common_utils.claude_code_marketplace_auth import ( + marketplace_auth_required, + marketplace_key_header_present, +) +from litellm.proxy.common_utils.resource_ownership import is_proxy_admin +from litellm.proxy.deps.repositories import PluginUploadRepositoryDep, SkillSubmissionRepositoryDep +from litellm.proxy.discovery_endpoints.agent_skills_archive import ( + SkillArchive, + build_agent_skill_archive, +) +from litellm.proxy.discovery_endpoints.skill_hub_mutations import ( + SkillMutationError, + archive_writer, + write_skill, + write_target, +) +from litellm.proxy.discovery_endpoints.skill_import import ( + MAX_IMPORT_BYTES, + SkillImportError, + fetch_skill_source, + parse_skill_source, + select_imported_skill, +) +from litellm.types.proxy.claude_code_endpoints import PluginListItem +from litellm.types.proxy.discovery_endpoints.agent_skills_endpoints import AgentSkillsIndexEntry +from litellm.types.proxy.skill_hub import ( + ImportSkillRequest, + SkillHubList, + SkillHubMetadata, + SkillHubMutationResponse, + SkillHubPendingSkill, + SkillHubProposal, + SkillHubPublication, + SkillHubSkill, + SkillHubVersion, + SkillHubVersions, +) + +router: Final = APIRouter(prefix="/skill-hub/skills", tags=["Skills Hub"]) +_EDITABLE_METADATA: Final = frozenset(SkillHubMetadata.model_fields) +router.add_api_route( + "/{plugin_name}/downloads", get_plugin_downloads, methods=["GET"], response_model=PluginDownloadsResponse +) + + +@dataclass(frozen=True, slots=True) +class VisibleSkillArchive: + archive: SkillArchive + metadata: PluginArchiveMetadata + downloader: PluginDownloader + + +def _url(request: Request, route: str) -> str: + from litellm.proxy.utils import get_custom_url + + return get_custom_url(request_base_url=str(request.base_url), route=route.lstrip("/")) + + +def _download_url(request: Request, name: str) -> str: + return _url(request, f"skill-hub/skills/{quote(name, safe='')}/archive") + + +def _skill_response(request: Request, plugin: PluginListItem, download_count: int | None = None) -> SkillHubSkill: + local_archive: Final = plugin_archive_source_matches( + request, + plugin.name, + plugin.source, + plugin.source.get("sha256", ""), + has_agent_skill_metadata=plugin.has_agent_skill_metadata, + ) + return SkillHubSkill( + id=plugin.id, + name=plugin.name, + description=plugin.description, + version=plugin.version, + domain=plugin.domain, + namespace=plugin.namespace, + keywords=None if plugin.keywords is None else tuple(plugin.keywords), + updated_at=None if plugin.updated_at is None else datetime.fromisoformat(plugin.updated_at), + visibility="public" if plugin.enabled else "private", + source={"source": "archive", "url": _download_url(request, plugin.name)} if local_archive else plugin.source, + download_url=_download_url(request, plugin.name) if local_archive else None, + content_url=_url(request, f"skill-hub/skills/{quote(plugin.name, safe='')}/content") if local_archive else None, + download_count=download_count, + ) + + +@router.get("", response_model=SkillHubList) +async def list_skills( + request: Request, + uploads: PluginUploadRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + query: str = "", + offset: Annotated[int, Query(ge=0)] = 0, + limit: Annotated[int, Query(ge=1, le=100)] = 50, +) -> SkillHubList: + """Browse the caller's public and granted private skills.""" + catalog: Final = await list_plugins(enabled_only=False, user_api_key_dict=caller) + needle: Final = query.casefold() + matched: Final = tuple( + plugin + for plugin in sorted(catalog.plugins, key=lambda item: item.name) + if needle in " ".join((plugin.name, plugin.description or "", *(plugin.keywords or ()))).casefold() + ) + page: Final = matched[offset : offset + limit] + counts: Final[Mapping[str, int]] = ( + await _require_store(uploads).download_counts(tuple(plugin.id for plugin in page)) + if is_proxy_admin(caller) + else {} + ) + return SkillHubList( + skills=tuple(_skill_response(request, plugin, counts.get(plugin.id)) for plugin in page), + count=len(matched), + next_offset=offset + limit if offset + limit < len(matched) else None, + ) + + +@router.get("/{name}", response_model=SkillHubSkill) +async def get_skill( + request: Request, + name: str, + uploads: PluginUploadRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> SkillHubSkill: + """Read one visible skill and its portable download URL.""" + store: Final = _require_store(uploads) + metadata: Final = await store.get_metadata(name) + if metadata is None or not (await resolve_skill_visibility(caller)).allows(metadata): + raise HTTPException(404, "Skill not found") + return skill_metadata_response(request, metadata) + + +def skill_metadata_response(request: Request, metadata: PluginArchiveMetadata) -> SkillHubSkill: + manifest: Final = MANIFEST_FIELDS.validate_json(metadata.manifest_json or "{}") + return _skill_response( + request, + PluginListItem.model_validate( + { + "id": metadata.id or metadata.name, + "name": metadata.name, + "description": metadata.description, + "version": metadata.version, + "source": dict(metadata.source), + "has_agent_skill_metadata": metadata.has_agent_skill_metadata, + "enabled": metadata.enabled, + "created_at": None, + "updated_at": metadata.updated_at.isoformat() if metadata.updated_at is not None else None, + "domain": manifest.get("domain"), + "namespace": manifest.get("namespace"), + "keywords": manifest.get("keywords"), + } + ), + ) + + +def _require_store(uploads: PluginUploadStore | None) -> PluginUploadStore: + if uploads is None: + raise HTTPException(503, "Skills Hub requires a connected database") + return uploads + + +def _require_admin(caller: UserAPIKeyAuth) -> None: + if not is_proxy_admin(caller): + raise HTTPException(403, "Only proxy admins may publish skills") + + +@router.put("/{name}", response_model=SkillHubMutationResponse) +async def replace_skill_metadata( + request: Request, + name: str, + body: SkillHubMetadata, + uploads: PluginUploadRepositoryDep, + submissions: SkillSubmissionRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> SkillHubMutationResponse: + """Replace registry metadata, preserving files. Members submit an immutable proposal for admin review.""" + existing: Final = await write_target(name, True, uploads, caller, body.expected_updated_at) + if isinstance(existing, SkillMutationError): + raise HTTPException(existing.status, existing.message) + if existing is None: + raise HTTPException(404, "Skill not found") + publication: Final = PluginPublication( + name=name, + version=body.version, + description=body.description, + manifest={ + **{key: value for key, value in existing.manifest.items() if key not in _EDITABLE_METADATA}, + **body.model_dump(exclude_none=True), + "name": name, + }, + created_by=caller.user_id, + ) + return await _mutate(request, publication, existing, _require_store(uploads), submissions, caller) + + +@router.post("/{name}/publish", response_model=SkillHubSkill) +async def publish_skill( + request: Request, + name: str, + uploads: PluginUploadRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + _body: SkillHubPublication | None = None, +) -> SkillHubSkill: + """Make a skill public using the existing Hub publication policy.""" + _require_admin(caller) + await enable_plugin(plugin_name=name, user_api_key_dict=caller) + return await get_skill(request, name, uploads, caller) + + +@router.post("/{name}/unpublish", response_model=SkillHubSkill) +async def unpublish_skill( + request: Request, + name: str, + uploads: PluginUploadRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + _body: SkillHubPublication | None = None, +) -> SkillHubSkill: + """Remove a skill from public discovery while retaining explicit grants.""" + _require_admin(caller) + await disable_plugin(plugin_name=name, user_api_key_dict=caller) + return await get_skill(request, name, uploads, caller) + + +@router.delete("/{name}", status_code=204, response_class=Response) +async def remove_skill(name: str, caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)]) -> Response: + """Delete a skill and its managed archive.""" + _require_admin(caller) + await delete_plugin(plugin_name=name, user_api_key_dict=caller) + return Response(status_code=204) + + +@router.post("/upload", response_model=SkillHubMutationResponse) +async def upload_skill( + request: Request, + uploads: PluginUploadRepositoryDep, + submissions: SkillSubmissionRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(archive_writer)], + file: Annotated[UploadFile, File(description="Agent Skills ZIP with SKILL.md and optional supporting files")], + version: Annotated[str | None, Form()] = None, +) -> SkillHubMutationResponse: + """Publish a portable skill while retaining Claude marketplace compatibility.""" + store: Final = _require_store(uploads) + content: Final = await file.read(MAX_IMPORT_BYTES + 1) + if len(content) > MAX_IMPORT_BYTES: + raise HTTPException(413, "Skill ZIP must be 10 MiB or smaller") + archive: Final = await asyncio.to_thread(build_agent_skill_archive, content) + if archive is None: + raise HTTPException(422, "Upload a valid Agent Skill with name and description in SKILL.md") + return await _publish(request, store, submissions, caller, archive, version, None) + + +def import_http_client() -> httpx.AsyncClient: + return get_async_httpx_client(llm_provider="skill_hub_import").client + + +@router.post("/import", response_model=SkillHubMutationResponse) +async def import_skill( + request: Request, + body: ImportSkillRequest, + uploads: PluginUploadRepositoryDep, + submissions: SkillSubmissionRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(archive_writer)], + client: Annotated[httpx.AsyncClient, Depends(import_http_client)], +) -> SkillHubMutationResponse: + """Import a public skills.sh or GitHub skill as a portable snapshot.""" + store: Final = _require_store(uploads) + source: Final = parse_skill_source(body.url, skill=body.skill, ref=body.ref, path=body.path) + if isinstance(source, SkillImportError): + raise HTTPException(source.status, source.message) + content: Final = await fetch_skill_source(source, client) + if isinstance(content, SkillImportError): + raise HTTPException(content.status, content.message) + archive: Final = await asyncio.to_thread(select_imported_skill, content, source) + if isinstance(archive, SkillImportError): + raise HTTPException(archive.status, archive.message) + return await _publish(request, store, submissions, caller, archive, body.version, body.url) + + +async def _publish( + request: Request, + store: PluginUploadStore, + submissions: SkillSubmissionStore | None, + caller: UserAPIKeyAuth, + archive: SkillArchive, + version: str | None, + origin: str | None, +) -> SkillHubMutationResponse: + existing: Final = await write_target(archive.declared_name or "", False, store, caller) + if isinstance(existing, SkillMutationError): + raise HTTPException(existing.status, existing.message) + publication: Final = await prepare_skill_publication(request, archive, version, origin, caller.user_id) + return await _mutate(request, publication, existing, store, submissions, caller) + + +async def _mutate( + request: Request, + publication: PluginPublication, + existing: PluginSnapshot | None, + store: PluginUploadStore, + submissions: SkillSubmissionStore | None, + caller: UserAPIKeyAuth, +) -> SkillHubMutationResponse: + result: Final = await write_skill(publication, existing, store, submissions, caller) + if isinstance(result, SkillMutationError): + raise HTTPException(result.status, result.message) + if isinstance(result, SkillSubmission): + return SkillHubPendingSkill(submission_id=result.id, proposal=skill_proposal_response(request, result)) + return skill_publication_response(request, publication, result) + + +def skill_proposal_response(request: Request, submission: SkillSubmission) -> SkillHubProposal: + proposal: Final = submission.proposal + return SkillHubProposal.model_validate( + { + **proposal.manifest, + "name": proposal.name, + "description": proposal.description, + "version": proposal.version, + **( + { + "source": { + "source": "archive", + "url": _url(request, f"skill-hub/submissions/{quote(submission.id, safe='')}/archive"), + } + } + if submission.has_archive + else {} + ), + } + ) + + +@router.put("/{name}/upload", response_model=SkillHubMutationResponse) +async def replace_skill_archive( + request: Request, + name: str, + uploads: PluginUploadRepositoryDep, + submissions: SkillSubmissionRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(archive_writer)], + file: Annotated[UploadFile, File(description="Replacement Agent Skills ZIP with the same declared skill name")], + version: Annotated[str | None, Form()] = None, + expected_updated_at: Annotated[datetime | None, Form()] = None, +) -> SkillHubMutationResponse: + """Replace skill files, retaining registry fields. Members propose an update against the original editor timestamp.""" + existing: Final = await write_target(name, True, uploads, caller, expected_updated_at) + if isinstance(existing, SkillMutationError): + raise HTTPException(existing.status, existing.message) + if existing is None: + raise HTTPException(404, "Skill not found") + content: Final = await file.read(MAX_IMPORT_BYTES + 1) + if len(content) > MAX_IMPORT_BYTES: + raise HTTPException(413, "Skill ZIP must be 10 MiB or smaller") + archive: Final = await asyncio.to_thread(build_agent_skill_archive, content) + if archive is None or archive.declared_name != name: + raise HTTPException(422, "Replacement SKILL.md must declare the existing skill name and a description") + prepared: Final = await prepare_skill_publication(request, archive, version, None, caller.user_id) + publication: Final = replace(prepared, manifest={**existing.manifest, **prepared.manifest}) + return await _mutate(request, publication, existing, _require_store(uploads), submissions, caller) + + +def skill_publication_response( + request: Request, publication: PluginPublication, published: PublishedPlugin +) -> SkillHubSkill: + return _skill_response( + request, + PluginListItem.model_validate( + { + "source": publication.manifest.get("source", {}), + "id": published.id, + "name": published.name, + "description": publication.description, + "version": published.version, + "enabled": published.enabled, + "has_agent_skill_metadata": has_agent_skill_metadata(publication.manifest), + "created_at": None, + "updated_at": published.updated_at.isoformat(), + "domain": publication.manifest.get("domain"), + "namespace": publication.manifest.get("namespace"), + "keywords": publication.manifest.get("keywords"), + } + ), + ) + + +async def prepare_skill_publication( + request: Request, + archive: SkillArchive, + version: str | None, + origin: str | None, + created_by: str | None, +) -> PluginPublication: + name: Final = archive.declared_name + if name is None: + raise HTTPException(422, "SKILL.md must declare a skill name") + plugin: Final = await asyncio.to_thread(build_uploaded_skill_archive, archive.content, name) + if plugin is None: + raise HTTPException(422, "Skill ZIP exceeds the supported archive limits") + portable: Final = await asyncio.to_thread(build_agent_skill_archive, plugin, plugin_name=name) + if portable is None or portable.digest != archive.digest: + raise HTTPException(422, "Skill ZIP exceeds the supported archive limits after compatibility packaging") + digest: Final = hashlib.sha256(plugin).hexdigest() + source: Final = { + "source": "archive", + "url": plugin_archive_url(request, name, digest), + "sha256": digest, + } + manifest: Final = { + "name": name, + "description": archive.declared_description, + "version": version, + "source": source, + "agent_skill": { + "name": name, + "description": archive.declared_description, + "digest": archive.digest, + "origin": origin, + }, + } + return PluginPublication( + name=name, + version=version, + description=archive.declared_description, + manifest=manifest, + content=plugin, + created_by=created_by, + ) + + +async def _version_metadata(name: str, store: PluginUploadStore, caller: UserAPIKeyAuth) -> PluginArchiveMetadata: + metadata: Final = await store.get_metadata(name) + if metadata is None or metadata.id is None or not (await resolve_skill_visibility(caller)).allows(metadata): + raise HTTPException(404, "Skill not found") + return metadata + + +def _version_response(request: Request, name: str, version: PluginVersion) -> SkillHubVersion: + return SkillHubVersion( + id=version.id, + version=version.version, + description=version.description, + manifest=version.manifest, + published_at=version.published_at, + published_by=version.published_by, + content_kind="stored_archive" if version.archive_available else "source_reference", + download_url=( + _url(request, f"skill-hub/skills/{quote(name, safe='')}/versions/{quote(version.id, safe='')}/archive") + if version.archive_available + else None + ), + ) + + +@router.get("/{name}/versions", response_model=SkillHubVersions) +async def list_skill_versions( + request: Request, + name: str, + uploads: PluginUploadRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + limit: Annotated[int, Query(ge=1, le=100)] = 20, + offset: Annotated[int, Query(ge=0)] = 0, +) -> SkillHubVersions: + """Read published metadata history. External references are not retained artifacts.""" + store: Final = _require_store(uploads) + metadata: Final = await _version_metadata(name, store, caller) + versions: Final = await store.versions(metadata, limit + 1, offset) + return SkillHubVersions( + versions=tuple(_version_response(request, name, version) for version in versions[:limit]), + next_offset=offset + limit if len(versions) > limit else None, + ) + + +@router.get("/{name}/versions/{version_id}", response_model=SkillHubVersion) +async def get_skill_version( + request: Request, + name: str, + version_id: str, + uploads: PluginUploadRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> SkillHubVersion: + """Read a retained publication under the current skill's visibility policy.""" + store: Final = _require_store(uploads) + metadata: Final = await _version_metadata(name, store, caller) + version: Final = await store.version(metadata, version_id) + if version is None: + raise HTTPException(404, "Skill version not found") + return _version_response(request, name, version) + + +@router.get( + "/{name}/versions/{version_id}/archive", + response_class=Response, + responses={200: {"content": {"application/zip": {"schema": {"type": "string", "format": "binary"}}}}}, +) +async def download_skill_version( + name: str, + version_id: str, + uploads: PluginUploadRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> Response: + """Download a retained publication as a portable ZIP with SKILL.md at its root.""" + store: Final = _require_store(uploads) + metadata: Final = await _version_metadata(name, store, caller) + version: Final = await store.version(metadata, version_id) + if version is None: + raise HTTPException(404, "Skill version not found") + content: Final = await store.version_content(metadata, version_id) + archive: Final = ( + await asyncio.to_thread(build_agent_skill_archive, content, plugin_name=name) if content is not None else None + ) + if archive is None: + raise HTTPException(404, "This version has no retained Agent Skills archive") + require_download_recorded( + await store.record_download( + replace(metadata, version=version.version), + archive.digest.removeprefix("sha256:"), + plugin_downloader(caller), + ) + ) + return Response( + archive.content, + media_type="application/zip", + headers={ + "Content-Disposition": f'attachment; filename="{name}.zip"', + "Cache-Control": "private, no-store", + "X-Content-Type-Options": "nosniff", + "ETag": f'"{archive.digest}"', + }, + ) + + +async def _visible_archive(request: Request, name: str, uploads: PluginUploadStore | None) -> VisibleSkillArchive: + anonymous_allowed: Final = litellm.public_skills_index is True and not marketplace_auth_required() + caller: Final = ( + await header_key_caller(request) if marketplace_key_header_present(request) or not anonymous_allowed else None + ) + store: Final = _require_store(uploads) + metadata: Final = await store.get_metadata(name) + if metadata is None or not (await resolve_skill_visibility(caller)).allows(metadata): + raise HTTPException(404, "Skill not found") + if not plugin_archive_source_matches( + request, + name, + metadata.source, + metadata.source.get("sha256", ""), + has_agent_skill_metadata=metadata.has_agent_skill_metadata, + ): + raise HTTPException(404, "This skill no longer refers to a managed archive") + content: Final = await store.get_content(metadata) + archive: Final = ( + await asyncio.to_thread(build_agent_skill_archive, content, plugin_name=name) if content is not None else None + ) + if archive is None: + raise HTTPException(404, "This skill has no stored Agent Skills archive") + return VisibleSkillArchive(archive, metadata, plugin_downloader(caller)) + + +@router.get( + "/{name}/archive", + response_class=Response, + responses={200: {"content": {"application/zip": {"schema": {"type": "string", "format": "binary"}}}}}, +) +async def download_skill( + request: Request, name: str, uploads: PluginUploadRepositoryDep, digest: str | None = None +) -> Response: + """Download the complete portable skill, with SKILL.md at the ZIP root.""" + visible: Final = await _visible_archive(request, name, uploads) + archive: Final = visible.archive + if digest is not None and digest != archive.digest: + raise HTTPException(404, "Skill archive version not found") + require_download_recorded( + await _require_store(uploads).record_download( + visible.metadata, archive.digest.removeprefix("sha256:"), visible.downloader + ) + ) + return Response( + archive.content, + media_type="application/zip", + headers={ + "Content-Disposition": f'attachment; filename="{name}.zip"', + "Cache-Control": "private, no-store", + "X-Content-Type-Options": "nosniff", + "ETag": f'"{archive.digest}"', + }, + ) + + +@router.get("/{name}/content", response_class=Response, responses={200: {"content": {"text/markdown": {}}}}) +async def skill_content(request: Request, name: str, uploads: PluginUploadRepositoryDep) -> Response: + """Read the original SKILL.md without downloading supporting files.""" + visible: Final = await _visible_archive(request, name, uploads) + return Response( + visible.archive.manifest_content, + media_type="text/markdown", + headers={"Cache-Control": "private, no-store", "X-Content-Type-Options": "nosniff"}, + ) + + +async def public_hub_entries(request: Request, store: PluginUploadStore | None) -> tuple[AgentSkillsIndexEntry, ...]: + if store is None or marketplace_auth_required(): + return () + entries: Final[list[AgentSkillsIndexEntry]] = [] # mutable-ok: bounded inventory avoids copying on each append + async for item in store.public_metadata(): + entry: AgentSkillsIndexEntry | None = _index_entry(request, item) + if entry is None: + continue + entries.append(entry) + if len(entries) == 1000: + break + return tuple(entries) + + +def _index_entry(request: Request, item: PluginArchiveMetadata) -> AgentSkillsIndexEntry | None: + manifest: Final = MANIFEST_FIELDS.validate_json(item.manifest_json or "{}") + raw: Final = manifest.get("agent_skill") + if ( + not isinstance(raw, dict) + or not item.enabled + or not plugin_archive_source_matches( + request, + item.name, + item.source, + item.source.get("sha256", ""), + has_agent_skill_metadata=item.has_agent_skill_metadata, + ) + ): + return None + skill: Final = MANIFEST_FIELDS.validate_python(raw) + digest: Final = skill.get("digest") + description: Final = item.description or skill.get("description") + if not isinstance(digest, str) or not isinstance(description, str): + return None + return AgentSkillsIndexEntry( + name=item.name, + type="archive", + description=description, + url=f"{_download_url(request, item.name)}?digest={quote(digest, safe=':')}", + digest=digest, + ) diff --git a/litellm/proxy/discovery_endpoints/skill_hub_mutations.py b/litellm/proxy/discovery_endpoints/skill_hub_mutations.py new file mode 100644 index 00000000000..63c519923c6 --- /dev/null +++ b/litellm/proxy/discovery_endpoints/skill_hub_mutations.py @@ -0,0 +1,172 @@ +import hashlib +from dataclasses import dataclass +from datetime import datetime +from typing import Annotated, Final + +from fastapi import Depends, HTTPException +from typing_extensions import assert_never + +from litellm.models.plugin_upload import ( + PluginPublication, + PluginPublicationBase, + PluginPublicationError, + PluginSnapshot, + PluginUploadStore, + PublishedPlugin, +) +from litellm.models.skill_submission import ( + SkillSubmission, + SkillSubmissionStore, + SubmissionConflict, + SubmissionLimitExceeded, + SubmissionMissing, + SubmissionReviewed, +) +from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy.anthropic_endpoints.claude_code_endpoints.claude_code_skill_access import resolve_skill_visibility +from litellm.proxy.auth.auth_exception_handler import DB_UNAVAILABLE_FALLBACK_USER_ID +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.common_utils.resource_ownership import is_proxy_admin +from litellm.proxy.hooks.parallel_request_limiter_v3 import PROXY_MaxParallelRequestsHandler_v3 +from litellm.repositories.plugin_publication import resolve_plugin_version +from litellm.types.proxy.auth.user_roles import LitellmUserRoles + + +@dataclass(frozen=True, slots=True) +class SkillMutationError: + status: int + message: str + + +def writer_error(caller: UserAPIKeyAuth) -> SkillMutationError | None: + if is_proxy_admin(caller): + return None + if ( + not caller.user_id + or caller.user_id == DB_UNAVAILABLE_FALLBACK_USER_ID + or caller.user_role in (None, LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY, LitellmUserRoles.INTERNAL_USER_VIEW_ONLY) + ): + return SkillMutationError(403, "Submitting a skill requires a writable user identity.") + return None + + +def submission_owner(caller: UserAPIKeyAuth) -> str | None | SkillMutationError: + if is_proxy_admin(caller) or caller.user_role == LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY: + return None + if not caller.user_id or caller.user_id == DB_UNAVAILABLE_FALLBACK_USER_ID: + return SkillMutationError(403, "Reading submissions requires a user identity.") + return caller.user_id + + +async def archive_writer(caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)]) -> UserAPIKeyAuth: + from litellm.proxy.proxy_server import proxy_logging_obj + + error: Final = writer_error(caller) + if error is not None: + raise HTTPException(error.status, error.message) + limiter: Final = proxy_logging_obj.get_proxy_hook("parallel_request_limiter") + if not isinstance(limiter, PROXY_MaxParallelRequestsHandler_v3): + raise HTTPException(503, "Skills Hub publishing requires the default v3 rate limiter") + key_identity: Final = caller.api_key or caller.token + identity: Final = ( + f"user:{caller.user_id}" if caller.user_id else f"key:{key_identity}" if key_identity else "local-admin" + ) + result: Final = await limiter.atomic_check_and_increment_by_n( + descriptors=[ + { + "key": "skill_hub_publish", + "value": hashlib.sha256(identity.encode()).hexdigest(), + "rate_limit": {"requests_per_unit": 10, "window_size": 60}, + } + ], + increments=[{"requests": 1}], + parent_otel_span=caller.parent_otel_span, + ) + if result["overall_code"] == "OVER_LIMIT": + raise HTTPException( + 429, "Skills Hub allows 10 uploads or imports per minute per user", headers={"Retry-After": "60"} + ) + return caller + + +async def write_target( + name: str, + updating: bool, + uploads: PluginUploadStore | None, + caller: UserAPIKeyAuth, + expected_updated_at: datetime | None = None, +) -> PluginSnapshot | SkillMutationError | None: + error: Final = writer_error(caller) + if error is not None: + return error + if uploads is None: + return SkillMutationError(503, "Skills Hub requires a connected database") + existing: Final = await uploads.get_plugin(name) + if updating and (existing is None or not (await resolve_skill_visibility(caller)).allows(existing)): + return SkillMutationError(404, "Skill not found") + if existing is not None and expected_updated_at is not None and existing.updated_at != expected_updated_at: + return SkillMutationError(409, "The published skill changed. Reload it before submitting.") + if not updating and existing is not None: + return SkillMutationError(409, f"A skill named '{name}' already exists. Update the existing skill instead.") + return existing + + +def publication_error(error: PluginPublicationError) -> SkillMutationError: + return SkillMutationError({"invalid_version": 400, "conflict": 409, "not_found": 404}[error.kind], error.message) + + +async def write_skill( + publication: PluginPublication, + existing: PluginSnapshot | None, + uploads: PluginUploadStore, + submissions: SkillSubmissionStore | None, + caller: UserAPIKeyAuth, +) -> PublishedPlugin | SkillSubmission | SkillMutationError: + error: Final = writer_error(caller) + if error is not None: + return error + validation: Final = resolve_plugin_version( + publication.version, None if existing is None else existing.version, updating=existing is not None + ) + if isinstance(validation, PluginPublicationError): + return publication_error(validation) + expected: Final = None if existing is None else PluginPublicationBase(existing.id, existing.updated_at) + if is_proxy_admin(caller): + published: Final = await uploads.publish(publication, expected) + return publication_error(published) if isinstance(published, PluginPublicationError) else published + if submissions is None or not caller.user_id: + return SkillMutationError(503, "Skills Hub requires a connected database") + submission: Final = await submissions.submit(publication, caller.user_id, expected) + return ( + SkillMutationError(429, submission.message) if isinstance(submission, SubmissionLimitExceeded) else submission + ) + + +async def review_skill( + submission_id: str, + submissions: SkillSubmissionStore | None, + caller: UserAPIKeyAuth, + approve: bool, + reason: str | None, + publication_base_url: str | None = None, +) -> SubmissionReviewed | SkillMutationError: + if not is_proxy_admin(caller): + return SkillMutationError(403, "Only proxy admins may review skill submissions.") + if submissions is None: + return SkillMutationError(503, "Skills Hub requires a connected database") + result: Final = await submissions.review( + submission_id, caller.user_id or "proxy-admin", approve, reason, publication_base_url=publication_base_url + ) + match result: + case SubmissionMissing(): + return SkillMutationError(404, "Skill submission not found") + case SubmissionConflict(message=message): + return SkillMutationError(409, message) + case PluginPublicationError(kind="invalid_version") as error: + return publication_error(error) + case PluginPublicationError(message=message): + return SkillMutationError(409, message) + case SubmissionReviewed(): + return result + case _: + assert_never(result) diff --git a/litellm/proxy/discovery_endpoints/skill_hub_submissions.py b/litellm/proxy/discovery_endpoints/skill_hub_submissions.py new file mode 100644 index 00000000000..c1bb422b2a0 --- /dev/null +++ b/litellm/proxy/discovery_endpoints/skill_hub_submissions.py @@ -0,0 +1,192 @@ +import asyncio +from typing import Annotated, Final + +from fastapi import APIRouter, Depends, HTTPException, Query, Request, Response + +from litellm.models.plugin_upload import PluginPublication +from litellm.models.skill_submission import SkillSubmission, SkillSubmissionStore, SubmissionStatus +from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy.anthropic_endpoints.claude_code_endpoints.claude_code_skill_access import resolve_skill_visibility +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.deps.repositories import PluginUploadRepositoryDep, SkillSubmissionRepositoryDep +from litellm.proxy.discovery_endpoints.agent_skills_archive import build_agent_skill_archive +from litellm.proxy.discovery_endpoints.skill_hub_endpoints import ( + skill_metadata_response, + skill_proposal_response, + skill_publication_response, +) +from litellm.proxy.discovery_endpoints.skill_hub_mutations import SkillMutationError, review_skill, submission_owner +from litellm.types.proxy.skill_hub import ( + SkillHubRejection, + SkillHubReviewResponse, + SkillHubSubmission, + SkillHubSubmissionDetail, + SkillHubSubmissionList, +) + +router: Final = APIRouter(prefix="/skill-hub/submissions", tags=["Skills Hub"]) + + +def _store(submissions: SkillSubmissionStore | None) -> SkillSubmissionStore: + if submissions is None: + raise HTTPException(503, "Skills Hub requires a connected database") + return submissions + + +def _owner(caller: UserAPIKeyAuth) -> str | None: + owner: Final = submission_owner(caller) + if isinstance(owner, SkillMutationError): + raise HTTPException(owner.status, owner.message) + return owner + + +def _response(request: Request, submission: SkillSubmission) -> SkillHubSubmission: + return SkillHubSubmission( + id=submission.id, + skill_name=submission.plugin_name, + operation=submission.operation, + status=submission.status, + proposal=skill_proposal_response(request, submission), + has_archive=submission.has_archive, + submitted_by=submission.submitted_by, + created_at=submission.created_at, + base_skill_id=submission.base_plugin_id, + base_updated_at=submission.base_updated_at, + reviewed_by=submission.reviewed_by, + reviewed_at=submission.reviewed_at, + rejection_reason=submission.rejection_reason, + ) + + +@router.get("", response_model=SkillHubSubmissionList) +async def list_submissions( + request: Request, + submissions: SkillSubmissionRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + status: SubmissionStatus | None = None, + limit: Annotated[int, Query(ge=1, le=100)] = 20, + offset: Annotated[int, Query(ge=0)] = 0, +) -> SkillHubSubmissionList: + """Read a page of owned proposals. Proxy admins and admin viewers can read every owner's proposals.""" + owner: Final = _owner(caller) + page: Final = await _store(submissions).list(owner, status, limit, offset) + return SkillHubSubmissionList( + submissions=tuple(_response(request, row) for row in page.submissions), + count=len(page.submissions), + has_more=page.has_more, + ) + + +@router.get("/{submission_id}", response_model=SkillHubSubmissionDetail) +async def get_submission( + request: Request, + submission_id: str, + submissions: SkillSubmissionRepositoryDep, + uploads: PluginUploadRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> SkillHubSubmissionDetail: + """Read an immutable proposal and its currently visible published skill.""" + owner: Final = _owner(caller) + submission: Final = await _store(submissions).get(submission_id, owner) + if submission is None: + raise HTTPException(404, "Skill submission not found") + if uploads is None: + raise HTTPException(503, "Skills Hub requires a connected database") + current: Final = await uploads.get_metadata(submission.plugin_name) + visible: Final = current is not None and (owner is None or (await resolve_skill_visibility(caller)).allows(current)) + return SkillHubSubmissionDetail( + submission=_response(request, submission), + current_skill=skill_metadata_response(request, current) if current is not None and visible else None, + ) + + +@router.get( + "/{submission_id}/archive", + response_class=Response, + responses={200: {"content": {"application/zip": {"schema": {"type": "string", "format": "binary"}}}}}, +) +async def download_submission( + submission_id: str, + submissions: SkillSubmissionRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> Response: + """Download an owned proposal as a private portable ZIP. Legacy nonportable archives return 404.""" + owner: Final = _owner(caller) + store: Final = _store(submissions) + submission: Final = await store.get(submission_id, owner) + if submission is None: + raise HTTPException(404, "Skill submission not found") + content: Final = await store.get_archive(submission_id, owner) + archive: Final = ( + await asyncio.to_thread(build_agent_skill_archive, content, plugin_name=submission.plugin_name) + if content is not None + else None + ) + if archive is None: + raise HTTPException(404, "This submission has no portable Agent Skills archive") + return Response( + archive.content, + media_type="application/zip", + headers={ + "Content-Disposition": f'attachment; filename="{submission.plugin_name}.zip"', + "Cache-Control": "private, no-store", + "X-Content-Type-Options": "nosniff", + "ETag": f'"{archive.digest}"', + }, + ) + + +async def _review( + request: Request, + submission_id: str, + submissions: SkillSubmissionStore | None, + caller: UserAPIKeyAuth, + approve: bool, + reason: str | None, +) -> SkillHubReviewResponse: + from litellm.proxy.utils import get_custom_url + + result: Final = await review_skill( + submission_id, submissions, caller, approve, reason, get_custom_url(str(request.base_url)) + ) + if isinstance(result, SkillMutationError): + raise HTTPException(result.status, result.message) + proposal: Final = result.submission.proposal + publication: Final = PluginPublication( + name=proposal.name, + version=proposal.version, + description=proposal.description, + manifest={ + **proposal.manifest, + **({"source": dict(result.published_source)} if result.published_source else {}), + }, + created_by=result.submission.submitted_by, + ) + return SkillHubReviewResponse( + action="approved" if approve else "rejected", + submission=_response(request, result.submission), + skill=None if result.plugin is None else skill_publication_response(request, publication, result.plugin), + ) + + +@router.put("/{submission_id}/approve", response_model=SkillHubReviewResponse) +async def approve_submission( + request: Request, + submission_id: str, + submissions: SkillSubmissionRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> SkillHubReviewResponse: + """Publish a pending proposal and record its approval atomically. Only proxy admins may review.""" + return await _review(request, submission_id, submissions, caller, True, None) + + +@router.put("/{submission_id}/reject", response_model=SkillHubReviewResponse) +async def reject_submission( + request: Request, + submission_id: str, + submissions: SkillSubmissionRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + body: SkillHubRejection | None = None, +) -> SkillHubReviewResponse: + """Reject a pending proposal without changing the published skill. Only proxy admins may review.""" + return await _review(request, submission_id, submissions, caller, False, None if body is None else body.reason) diff --git a/litellm/proxy/discovery_endpoints/skill_import.py b/litellm/proxy/discovery_endpoints/skill_import.py new file mode 100644 index 00000000000..a74e3abef10 --- /dev/null +++ b/litellm/proxy/discovery_endpoints/skill_import.py @@ -0,0 +1,126 @@ +import io +import re +import zipfile +from dataclasses import dataclass +from typing import Final +from urllib.parse import quote, unquote, urlsplit + +import httpx + +from litellm.proxy.discovery_endpoints.agent_skills_archive import ( + MAX_ARCHIVE_ENTRIES, + MAX_ARCHIVE_UNPACKED_BYTES, + MAX_SKILL_MANIFEST_BYTES, + SKILL_ARCHIVE_ERRORS, + SkillArchive, + agent_skill_frontmatter, + build_agent_skill_archive, + read_skill_archive_entry, + safe_skill_archive_entry, + skill_archive_entries, +) + +MAX_IMPORT_BYTES: Final = 10 * 1024 * 1024 + + +@dataclass(frozen=True, slots=True) +class SkillImportError: + status: int + message: str + + +@dataclass(frozen=True, slots=True) +class GitHubSkillSource: + owner: str + repository: str + ref: str + skill: str | None + path: str | None + + @property + def archive_url(self) -> str: + return f"https://codeload.github.com/{self.owner}/{self.repository}/zip/{quote(self.ref, safe='')}" + + +def parse_skill_source( + url: str, *, skill: str | None, ref: str, path: str | None +) -> GitHubSkillSource | SkillImportError: + try: + parsed: Final = urlsplit(url) + except ValueError: + return SkillImportError(400, "Invalid skill source URL") + if parsed.scheme != "https" or parsed.netloc not in ("skills.sh", "github.com") or parsed.query or parsed.fragment: + return SkillImportError(400, "Use an HTTPS skills.sh skill URL or a public github.com repository URL") + parts: Final = tuple(unquote(part) for part in parsed.path.strip("/").split("/")) + if len(parts) < 2 or any(re.fullmatch(r"[A-Za-z0-9_.-]+", part) is None for part in parts[:2]): + return SkillImportError(400, "The source URL must identify a GitHub owner and repository") + if parsed.netloc == "skills.sh": + if len(parts) != 3 or (skill is not None and skill != parts[2]): + return SkillImportError(400, "Use skills.sh/// with a matching skill selection") + return GitHubSkillSource(parts[0], parts[1], ref, parts[2], path) + if len(parts) == 2: + return GitHubSkillSource(parts[0], parts[1].removesuffix(".git"), ref, skill, path) + if len(parts) < 5 or parts[2] != "tree" or path is not None or ref != "HEAD": + return SkillImportError(400, "Use a repository URL with ref and path, or a GitHub tree URL") + return GitHubSkillSource(parts[0], parts[1], parts[3], skill, "/".join(parts[4:])) + + +async def fetch_skill_source(source: GitHubSkillSource, client: httpx.AsyncClient) -> bytes | SkillImportError: + buffer: Final = io.BytesIO() + request: Final = httpx.Request( + "GET", + source.archive_url, + headers={"Accept": "application/zip"}, + extensions={"timeout": httpx.Timeout(30).as_dict()}, + ) + try: + response: Final = await client.send(request, stream=True, follow_redirects=False, auth=None) + try: + if response.status_code != 200: + return SkillImportError(422, "Unable to download the public GitHub repository at the requested ref") + async for chunk in response.aiter_bytes(): + if buffer.tell() + len(chunk) > MAX_IMPORT_BYTES: + return SkillImportError(413, "Repository ZIP must be 10 MiB or smaller") + buffer.write(chunk) + finally: + await response.aclose() + except httpx.HTTPError: + return SkillImportError(502, "The skill source could not be reached") + return buffer.getvalue() + + +def select_imported_skill(content: bytes, source: GitHubSkillSource) -> SkillArchive | SkillImportError: + try: + with zipfile.ZipFile(io.BytesIO(content)) as archive: + infos: Final = archive.infolist() + if len(infos) > MAX_ARCHIVE_ENTRIES or sum(info.file_size for info in infos) > MAX_ARCHIVE_UNPACKED_BYTES: + return SkillImportError(413, "Repository exceeds the skill archive limits") + entries: Final = skill_archive_entries(archive, for_upload=True) + if entries is None: + return SkillImportError(422, "Repository contains unsafe archive entries") + candidates: Final = tuple(info for info, path in entries if path.endswith("/SKILL.md")) + if any(not safe_skill_archive_entry(info) for info in candidates): + return SkillImportError(422, "Repository contains unsafe skill manifests") + selected: Final = tuple(info for info in candidates if _matches_selection(info, archive, source)) + if len(selected) != 1: + return SkillImportError(422, "Select exactly one skill using its name or repository-relative path") + root: Final = selected[0].filename.rsplit("/", 1)[0] + skill: Final = build_agent_skill_archive(content, skill_path=root) + return ( + skill + if skill is not None + else SkillImportError(422, "The selected directory is not a valid Agent Skill") + ) + except SKILL_ARCHIVE_ERRORS: + return SkillImportError(422, "The repository did not return a readable skill ZIP") + + +def _matches_selection(info: zipfile.ZipInfo, archive: zipfile.ZipFile, source: GitHubSkillSource) -> bool: + if info.file_size > MAX_SKILL_MANIFEST_BYTES: + return False + relative: Final = info.filename.split("/", 1)[1].rpartition("/")[0] + if source.path is not None and relative != source.path.strip("/"): + return False + if source.skill is None: + return True + return agent_skill_frontmatter(read_skill_archive_entry(archive, info)).get("name") == source.skill diff --git a/litellm/proxy/discovery_endpoints/skill_scanning.py b/litellm/proxy/discovery_endpoints/skill_scanning.py new file mode 100644 index 00000000000..ee236482fbf --- /dev/null +++ b/litellm/proxy/discovery_endpoints/skill_scanning.py @@ -0,0 +1,186 @@ +import asyncio +import io +import json +from datetime import datetime, timedelta, timezone +from typing import Annotated, Final +from uuid import uuid4 + +import httpx +from fastapi import APIRouter, BackgroundTasks, Body, Depends, HTTPException +from pydantic import ValidationError + +from litellm.llms.custom_httpx.http_handler import ( + get_async_httpx_client, # pyright: ignore[reportUnknownVariableType] # shared HTTP factory has untyped optional params +) +from litellm.models.skill_submission import SkillScanInput, SkillSubmissionStore, SubmissionConflict, SubmissionMissing +from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.common_utils.resource_ownership import is_proxy_admin +from litellm.proxy.deps.repositories import SkillSubmissionRepositoryDep +from litellm.secret_managers.main import get_secret_str +from litellm.types.proxy.skill_scanning import ( + SkillScan, + SkillScannerConfig, + SkillScanReport, + SkillScanRequest, + SkillScanResponse, +) + +router: Final = APIRouter() +_MAX_REPORT_BYTES: Final = 1024 * 1024 + + +def scanner_config() -> SkillScannerConfig | str | None: + from litellm.proxy.proxy_server import general_settings_view + + value: Final = general_settings_view().get("skill_scanner") + if value is None: + return None + try: + return SkillScannerConfig.model_validate(value) + except ValidationError: + return "The skill scanner configuration is invalid" + + +async def scan_report( + client: httpx.AsyncClient, config: SkillScannerConfig, api_key: str, target: SkillScanInput +) -> SkillScanReport | str: + try: + async with client.stream( + "POST", + config.endpoint, + headers={"Authorization": f"Bearer {api_key}", "Accept-Encoding": "identity"}, + data={ + "source": json.dumps(dict(target.source)), + "use_llm": str(config.use_llm).lower(), + "expires_at": target.scan.expires_at.isoformat(), + }, + files=None if target.content is None else {"file": ("skill.zip", target.content, "application/zip")}, + timeout=httpx.Timeout(config.timeout_seconds, connect=10), + follow_redirects=False, + ) as response: + if response.status_code != 200: + return f"Scanner returned HTTP {response.status_code}. Check the scanner service and authentication." + output: Final = io.BytesIO() + async for chunk in response.aiter_bytes(chunk_size=65536): + if output.tell() + len(chunk) > _MAX_REPORT_BYTES: + return "Scanner report exceeded the 1 MiB limit." + output.write(chunk) + report: Final = SkillScanReport.model_validate_json(output.getvalue()) + if config.use_llm and report.scan_mode != "static+llm": + return report.model_copy( + update={ + "complete": False, + "limitations": (*report.limitations[:99], "Requested semantic analysis did not run."), + } + ) + return report + except (httpx.HTTPError, ValidationError): + return "The scanner was unreachable or returned an invalid report." + + +async def complete_scan( + submissions: SkillSubmissionStore, + submission_id: str, + target: SkillScanInput, + config: SkillScannerConfig, + api_key: str, +) -> None: + try: + client: Final = get_async_httpx_client( + "skill_scanner", params={"ssl_verify": True, "follow_redirects": False} + ).client + report: Final = await asyncio.wait_for( + scan_report(client, config, api_key, target), + timeout=(target.scan.expires_at - datetime.now(timezone.utc)).total_seconds(), + ) + completed: Final = target.scan.model_copy( + update={ + "status": "completed" if isinstance(report, SkillScanReport) else "failed", + "report": report if isinstance(report, SkillScanReport) else None, + "error": report if isinstance(report, str) else None, + "completed_at": datetime.now(timezone.utc), + } + ) + await submissions.finish_scan(submission_id, completed) + except (TimeoutError, asyncio.CancelledError) as error: + await submissions.finish_scan( + submission_id, + target.scan.model_copy( + update={ + "status": "failed", + "error": "Scan timed out or was interrupted. Try scanning again.", + "completed_at": datetime.now(timezone.utc), + } + ), + ) + if isinstance(error, asyncio.CancelledError): + raise + + +@router.get( + "/skill-hub/submissions/{submission_id}/scan", + tags=["Skills Hub"], + response_model=SkillScanResponse, +) +async def get_skill_scan( + submission_id: str, + submissions: SkillSubmissionRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> SkillScanResponse: + """Read the latest manual security scan. Only proxy admins may read reports.""" + if not is_proxy_admin(caller): + raise HTTPException(403, "Proxy admin access is required to review security scans") + if submissions is None: + raise HTTPException(503, "Database is not connected") + scan: Final = await submissions.get_scan(submission_id) + if isinstance(scan, SubmissionMissing): + raise HTTPException(404, "Skill submission not found") + return SkillScanResponse( + configured=isinstance(scanner_config(), SkillScannerConfig), + scan=None if scan is None else scan.at(datetime.now(timezone.utc)), + ) + + +@router.post( + "/skill-hub/submissions/{submission_id}/scan", + tags=["Skills Hub"], + response_model=SkillScanResponse, +) +async def start_skill_scan( + submission_id: str, + background_tasks: BackgroundTasks, + submissions: SkillSubmissionRepositoryDep, + caller: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], + _request: Annotated[SkillScanRequest | None, Body()] = None, +) -> SkillScanResponse: + """Start an optional scan of a pending submission. Scans never change approval decisions.""" + if not is_proxy_admin(caller): + raise HTTPException(403, "Proxy admin access is required to scan skills") + if submissions is None: + raise HTTPException(503, "Database is not connected") + config: Final = scanner_config() + if config is None: + raise HTTPException(503, "Security scanning is not configured") + if isinstance(config, str): + raise HTTPException(503, config) + api_key: Final = get_secret_str(config.api_key_env) + if not api_key: + raise HTTPException(503, "The scanner authentication secret is not configured") + now: Final = datetime.now(timezone.utc) + target: Final = await submissions.start_scan( + submission_id, + SkillScan( + id=str(uuid4()), + status="running", + requested_by=caller.user_id or "proxy-admin", + started_at=now, + expires_at=now + timedelta(seconds=config.timeout_seconds), + ), + ) + if isinstance(target, SubmissionMissing): + raise HTTPException(404, "Skill submission not found") + if isinstance(target, SubmissionConflict): + raise HTTPException(409, target.message) + background_tasks.add_task(complete_scan, submissions, submission_id, target, config, api_key) + return SkillScanResponse(configured=True, scan=target.scan) diff --git a/litellm/proxy/enterprise_billing/billing_metrics.py b/litellm/proxy/enterprise_billing/billing_metrics.py index 166ece28b83..b6f69e8233c 100644 --- a/litellm/proxy/enterprise_billing/billing_metrics.py +++ b/litellm/proxy/enterprise_billing/billing_metrics.py @@ -2,29 +2,33 @@ Push-based OTLP metering for enterprise litellm deployments. Owns a dedicated OpenTelemetry meter provider and an OTLP/HTTP exporter -authenticated to our global collector with a TLS client certificate. The -collector front end terminates mutual TLS: the client certificate presented -here is validated against our CA at the edge, and the verified subject is -what identifies the deployment. It is intentionally isolated from the global -meter provider so the customer's own OTEL metrics are untouched and ours -never leak into their backend. +authenticated to our global collector with a Cognito bearer token. It is +intentionally isolated from the global meter provider so the customer's own +OTEL metrics are untouched and ours never leak into their backend. -The deployment's identity rides on the TLS client certificate, not on the -payload; the secret license key is never sent as an attribute or header. +The secret license key is never sent as an attribute or header. """ import os -import tempfile -from dataclasses import dataclass -from typing import TYPE_CHECKING, Final, Optional +import threading +import time +from collections.abc import Callable +from dataclasses import dataclass, field +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, TypedDict +import requests from opentelemetry.exporter.otlp.proto.http.metric_exporter import OTLPMetricExporter from opentelemetry.metrics import Counter from opentelemetry.sdk.metrics import MeterProvider from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader from opentelemetry.sdk.resources import Resource +from pydantic import BaseModel, ConfigDict +from requests.auth import AuthBase +from typing_extensions import ReadOnly, Unpack from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.url_utils import is_https_url_with_host from litellm.proxy.middleware.billable_request_metrics_middleware import ( BillableCategory, ) @@ -33,23 +37,15 @@ if TYPE_CHECKING: from litellm.proxy._types import EnterpriseLicenseData ENDPOINT_ENV: Final = "LITELLM_BILLING_METRICS_ENDPOINT" -CLIENT_CERT_ENV: Final = "LITELLM_BILLING_METRICS_CLIENT_CERT" -CLIENT_KEY_ENV: Final = "LITELLM_BILLING_METRICS_CLIENT_KEY" -CA_CERT_ENV: Final = "LITELLM_BILLING_METRICS_CA_CERT" +CLIENT_ID_ENV: Final = "LITELLM_BILLING_METRICS_CLIENT_ID" +CLIENT_SECRET_ENV: Final = "LITELLM_BILLING_METRICS_CLIENT_SECRET" +TOKEN_URL_ENV: Final = "LITELLM_BILLING_METRICS_TOKEN_URL" EXPORT_INTERVAL_ENV: Final = "LITELLM_BILLING_METRICS_EXPORT_INTERVAL_MS" DEFAULT_EXPORT_INTERVAL_MS: Final = 60_000 SHUTDOWN_FLUSH_TIMEOUT_MS: Final = 5_000 +_TOKEN_REFRESH_SKEW_SECONDS: Final = 60 _METRICS_PATH: Final = "/v1/metrics" -# The cert env vars take a path or the PEM itself. Secret stores that inject -# values as env content cannot mount them as files, so inline PEM is written out. -_PEM_PREFIX: Final = "-----BEGIN" -_PEM_DIR_PREFIX: Final = "litellm-billing-mtls-" -_PEM_FILE_MODE: Final = 0o600 -_CLIENT_CERT_FILENAME: Final = "client.crt" -_CLIENT_KEY_FILENAME: Final = "client.key" -_CA_CERT_FILENAME: Final = "ca.crt" - METRIC_NAME: Final = "litellm.enterprise.billable_requests" METER_NAME: Final = "litellm.enterprise.billing" @@ -59,21 +55,28 @@ AttributeValue = str | int @dataclass(frozen=True, slots=True) class BillingMetricsConfig: endpoint: str - client_cert_path: str - client_key_path: str - ca_cert_path: str | None + token_url: str + client_id: str + client_secret: str = field(repr=False) export_interval_ms: int litellm_version: str license_id: str | None +class _BillingMetricsOAuthToken(BaseModel): + model_config = ConfigDict(frozen=True, strict=True) + + access_token: str + expires_in: int + + def _metrics_endpoint(endpoint: str) -> str: """The OTLP/HTTP metric exporter wants the full URL including the signal path.""" trimmed: Final = endpoint.rstrip("/") return trimmed if trimmed.endswith(_METRICS_PATH) else f"{trimmed}{_METRICS_PATH}" -def _resource_attributes(config: BillingMetricsConfig) -> dict[str, AttributeValue]: +def resource_attributes(config: BillingMetricsConfig) -> dict[str, AttributeValue]: base: Final[dict[str, AttributeValue]] = { "service.name": "litellm-proxy", "litellm.version": config.litellm_version, @@ -82,7 +85,7 @@ def _resource_attributes(config: BillingMetricsConfig) -> dict[str, AttributeVal return {**base, **license_attr} -def _billable_attributes( +def billable_attributes( category: BillableCategory, route: str, status_code: int, model_id: str | None ) -> dict[str, AttributeValue]: base: Final[dict[str, AttributeValue]] = { @@ -94,23 +97,95 @@ def _billable_attributes( return {**base, **model_attr} -def build_mtls_meter_provider(config: BillingMetricsConfig) -> MeterProvider: - """OTLP/HTTP exporter presenting a TLS client certificate. +class BillingMetricsBearerAuth(AuthBase): + def __init__( + self, + *, + client_id: str, + client_secret: str, + token_url: str, + clock: Callable[[], float] = time.monotonic, + ) -> None: + self._client_id: Final = client_id + self._client_secret: Final = client_secret + self._token_url: Final = token_url + self._clock: Final = clock + self._lock: Final = threading.Lock() + self._cached_token: str | None = None + self._refresh_at: float = 0.0 - The collector's load balancer terminates mutual TLS and validates the client - certificate against our CA. Server verification uses the system trust store - (the collector presents a public web-PKI certificate); ca_cert_path overrides - it only for private/test collectors. - """ - exporter: Final = OTLPMetricExporter( - endpoint=_metrics_endpoint(config.endpoint), - # None -> exporter falls back to the system trust store. - certificate_file=config.ca_cert_path, - client_certificate_file=config.client_cert_path, - client_key_file=config.client_key_path, + def __call__(self, request: requests.PreparedRequest) -> requests.PreparedRequest: + token: Final = self._get_token() + authenticated_request: Final = request.copy() + authenticated_request.headers["Authorization"] = f"Bearer {token}" + return authenticated_request + + def invalidate(self) -> None: + with self._lock: + self._cached_token = None + self._refresh_at = 0.0 + + def _get_token(self) -> str: + with self._lock: + now: Final = self._clock() + if self._cached_token is not None and now < self._refresh_at: + return self._cached_token + token, cache_seconds = self._fetch_token() + self._cached_token = token + self._refresh_at = now + cache_seconds + return token + + def _fetch_token(self) -> tuple[str, float]: + try: + # The OTel periodic exporter's background thread makes blocking token I/O safe here. + response: Final = requests.post( + self._token_url, + auth=(self._client_id, self._client_secret), + data={"grant_type": "client_credentials", "scope": "telemetry/write"}, + timeout=10, + ) + response.raise_for_status() + token_response: Final = _BillingMetricsOAuthToken.model_validate(response.json()) + return token_response.access_token, max(0.0, float(token_response.expires_in) - _TOKEN_REFRESH_SKEW_SECONDS) + except (requests.RequestException, ValueError): + raise requests.RequestException("Billing metrics token request failed") from None + + +class _SessionHookKwargs(TypedDict, total=False): + stream: ReadOnly[object] + timeout: ReadOnly[object] + verify: ReadOnly[object] + cert: ReadOnly[object] + proxies: ReadOnly[object] + + +class _BillingMetricsBearerSession(requests.Session): + def __init__(self, auth: BillingMetricsBearerAuth) -> None: + super().__init__() + self._bearer_auth: Final = auth + self.auth = auth + self.hooks = {"response": [self._invalidate_token_on_unauthorized]} + + def _invalidate_token_on_unauthorized( + self, + response: requests.Response, + **kwargs: Unpack[_SessionHookKwargs], # kwargs-ok: requests hooks forward send options + ) -> requests.Response: + if response.status_code == 401: + self._bearer_auth.invalidate() + return response + + +def build_bearer_meter_provider(config: BillingMetricsConfig) -> MeterProvider: + auth: Final = BillingMetricsBearerAuth( + client_id=config.client_id, + client_secret=config.client_secret, + token_url=config.token_url, ) + session: Final = _BillingMetricsBearerSession(auth) + exporter: Final = OTLPMetricExporter(endpoint=_metrics_endpoint(config.endpoint), session=session) reader: Final = PeriodicExportingMetricReader(exporter, export_interval_millis=config.export_interval_ms) - return MeterProvider(metric_readers=[reader], resource=Resource.create(_resource_attributes(config))) + return MeterProvider(metric_readers=[reader], resource=Resource.create(resource_attributes(config))) class BillingMetricsRecorder: @@ -125,7 +200,7 @@ class BillingMetricsRecorder: ) def record(self, *, category: BillableCategory, route: str, status_code: int, model_id: str | None) -> None: - self._counter.add(1, _billable_attributes(category, route, status_code, model_id)) + self._counter.add(1, billable_attributes(category, route, status_code, model_id)) def shutdown(self) -> None: """Final flush + exporter-thread stop. Without this, up to one export @@ -146,115 +221,34 @@ def _export_interval_ms() -> int: return DEFAULT_EXPORT_INTERVAL_MS -@dataclass(frozen=True, slots=True) -class _CredentialPaths: - client_cert_path: str - client_key_path: str - ca_cert_path: str | None - - -def _is_pem_content(value: str) -> bool: - return value.lstrip().startswith(_PEM_PREFIX) - - -def _write_pem(directory: str, filename: str, pem: str) -> str: - path: Final = os.path.join(directory, filename) - with open(path, "w", encoding="utf-8") as handle: - handle.write(pem if pem.endswith("\n") else f"{pem}\n") - os.chmod(path, _PEM_FILE_MODE) - return path - - -def _resolve_credential_paths(*, client_cert: str, client_key: str, ca_cert: str | None) -> _CredentialPaths: - """ - Accept either a filesystem path or inline PEM content for each credential. - - Secret stores that inject values as environment content rather than mounted - files (ECS tasks reading AWS Secrets Manager, Cloud Run reading Secret - Manager) can only deliver the certificate as a string. The OTLP exporter - takes paths, so inline PEM is written to a private directory once, when the - recorder is built. Raises OSError if that write fails; the caller disables - metering rather than propagating. - """ - inline: Final = tuple(value for value in (client_cert, client_key, ca_cert) if value and _is_pem_content(value)) - if not inline: - return _CredentialPaths(client_cert, client_key, ca_cert) - - # mkdtemp is 0o700, so the 0o600 key file it holds is unreachable by other users. - directory: Final = tempfile.mkdtemp(prefix=_PEM_DIR_PREFIX) - return _CredentialPaths( - client_cert_path=( - _write_pem(directory, _CLIENT_CERT_FILENAME, client_cert) if _is_pem_content(client_cert) else client_cert - ), - client_key_path=( - _write_pem(directory, _CLIENT_KEY_FILENAME, client_key) if _is_pem_content(client_key) else client_key - ), - ca_cert_path=( - _write_pem(directory, _CA_CERT_FILENAME, ca_cert) if ca_cert and _is_pem_content(ca_cert) else ca_cert - ), - ) - - def load_billing_metrics_config( - *, license_data: Optional["EnterpriseLicenseData"], litellm_version: str + *, license_data: "EnterpriseLicenseData | None", litellm_version: str ) -> BillingMetricsConfig | None: - endpoint: Final = os.getenv(ENDPOINT_ENV) - client_cert: Final = os.getenv(CLIENT_CERT_ENV) - client_key: Final = os.getenv(CLIENT_KEY_ENV) - # Optional: only for private/test collectors whose server cert is not on the - # public web PKI. The production collector needs no CA override. - ca_cert: Final = os.getenv(CA_CERT_ENV) - - missing: Final = [ - name - for name, value in ( - (ENDPOINT_ENV, endpoint), - (CLIENT_CERT_ENV, client_cert), - (CLIENT_KEY_ENV, client_key), - ) - if not value - ] - if not endpoint or not client_cert or not client_key: + env: Final = MappingProxyType( + {name: os.getenv(name) or "" for name in (ENDPOINT_ENV, CLIENT_ID_ENV, CLIENT_SECRET_ENV, TOKEN_URL_ENV)} + ) + missing: Final = tuple(name for name, value in env.items() if not value) + if missing: verbose_proxy_logger.warning( "Enterprise billing metrics disabled: licensed deployment missing config (%s)", ", ".join(missing), ) return None - try: - paths: Final = _resolve_credential_paths(client_cert=client_cert, client_key=client_key, ca_cert=ca_cert) - except OSError as exc: - verbose_proxy_logger.warning( - "Enterprise billing metrics disabled: could not write inline certificate content to disk: %s", exc - ) - return None - - # Report the variable names, never their values. A value that is neither a - # readable path nor recognizable PEM is still secret material, and this - # warning would otherwise copy a client key straight into the proxy logs. - unreadable: Final = [ + insecure_urls: Final = tuple( env_name - for env_name, path in ( - (CLIENT_CERT_ENV, paths.client_cert_path), - (CLIENT_KEY_ENV, paths.client_key_path), - (CA_CERT_ENV, paths.ca_cert_path), - ) - if path and not os.path.isfile(path) - ] - if unreadable: - verbose_proxy_logger.warning( - "Enterprise billing metrics disabled: %s did not resolve to a readable certificate file. " - "Set each to a file path, or to inline PEM content beginning with '%s'.", - ", ".join(unreadable), - _PEM_PREFIX, - ) + for env_name, url in ((ENDPOINT_ENV, env[ENDPOINT_ENV]), (TOKEN_URL_ENV, env[TOKEN_URL_ENV])) + if not is_https_url_with_host(url) + ) + if insecure_urls: + verbose_proxy_logger.warning("Enterprise billing metrics disabled: %s must use HTTPS", insecure_urls[0]) return None return BillingMetricsConfig( - endpoint=endpoint, - client_cert_path=paths.client_cert_path, - client_key_path=paths.client_key_path, - ca_cert_path=paths.ca_cert_path, + endpoint=env[ENDPOINT_ENV], + client_id=env[CLIENT_ID_ENV], + client_secret=env[CLIENT_SECRET_ENV], + token_url=env[TOKEN_URL_ENV], export_interval_ms=_export_interval_ms(), litellm_version=litellm_version, license_id=(license_data or {}).get("user_id"), @@ -282,7 +276,7 @@ _ACTIVE_RECORDER: Final = _ActiveRecorderRegistry() def build_billing_metrics_recorder( - *, premium: bool, license_data: Optional["EnterpriseLicenseData"], litellm_version: str + *, premium: bool, license_data: "EnterpriseLicenseData | None", litellm_version: str ) -> BillingMetricsRecorder | None: """Build the recorder, or None when the deployment is not licensed or metering is unconfigured.""" if not premium: @@ -296,14 +290,12 @@ def build_billing_metrics_recorder( return None try: - recorder: Final = BillingMetricsRecorder(build_mtls_meter_provider(config)) + provider: Final = build_bearer_meter_provider(config) + recorder: Final = BillingMetricsRecorder(provider) except Exception as exc: # noqa: BLE001 -- metering must never break proxy startup verbose_proxy_logger.warning("Enterprise billing metrics disabled: failed to initialize exporter: %s", exc) return None _ACTIVE_RECORDER.set(recorder) - # The only positive signal that this component meters. Without it, a silent - # return above is indistinguishable from a working exporter in the logs, and - # a component that carries the cert but no license would look healthy. verbose_proxy_logger.info( "Enterprise billing metrics enabled: exporting to %s every %d ms", config.endpoint, diff --git a/litellm/proxy/guardrails/guardrail_hooks/compresr/compresr.py b/litellm/proxy/guardrails/guardrail_hooks/compresr/compresr.py index 4d910cde603..9b9e0949a1a 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/compresr/compresr.py +++ b/litellm/proxy/guardrails/guardrail_hooks/compresr/compresr.py @@ -22,7 +22,7 @@ import json import time from collections import Counter, OrderedDict from dataclasses import dataclass, field -from typing import TYPE_CHECKING, Final, Literal, Protocol, TypeGuard +from typing import TYPE_CHECKING, ClassVar, Final, Literal, Protocol, TypeGuard from urllib.parse import urlparse import httpx @@ -507,6 +507,8 @@ class _CompressionResult: class CompresrGuardrail(CustomGuardrail): + server_fulfilled_tool_names: ClassVar[frozenset[str]] = frozenset({COMPRESR_RETRIEVE_TOOL_NAME}) + def __init__( self, api_base: str | None = None, diff --git a/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/__init__.py index 44705c4d166..a2688312b38 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/__init__.py +++ b/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/__init__.py @@ -32,7 +32,7 @@ def initialize_guardrail(litellm_params: "LitellmParams", guardrail: "Guardrail" additional_provider_specific_params=getattr(litellm_params, "additional_provider_specific_params", {}), unreachable_fallback=getattr(litellm_params, "unreachable_fallback", "fail_closed"), fail_on_error=getattr(litellm_params, "fail_on_error", True), - forward_messages_as_sent=getattr(litellm_params, "forward_messages_as_sent", False), + forward_messages_as_sent=litellm_params.forward_messages_as_sent, extra_headers=getattr(litellm_params, "extra_headers", None), guardrail_name=guardrail.get("guardrail_name", ""), event_hook=litellm_params.mode, diff --git a/litellm/proxy/guardrails/guardrail_hooks/llm_shield_proxy/stream_restorers.py b/litellm/proxy/guardrails/guardrail_hooks/llm_shield_proxy/stream_restorers.py index ef007155c46..66a2d427944 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/llm_shield_proxy/stream_restorers.py +++ b/litellm/proxy/guardrails/guardrail_hooks/llm_shield_proxy/stream_restorers.py @@ -261,7 +261,8 @@ class ResponsesStreamRestorer: own window, keyed by the family, the item id and the part index. - Any `*.done` event closes the stream of the same family. Whatever its window still holds goes out first, as a copy of that stream's last delta event -- so it carries - the stream's own ids, and repeats that event's `sequence_number`. Then every text + the stream's own ids. It takes the done event's `sequence_number`, and every later + event's number moves up by one, so the numbers stay unique and in order. Then every text field on the done event is restored in full: its string fields other than identifiers, plus any `part` or `item` it repeats. - `response.completed` / `response.incomplete` repeat the whole reply, and are @@ -273,6 +274,8 @@ class ResponsesStreamRestorer: self._rehydrate: Final = rehydrate self._carries: Final[dict[ResponsesStreamKey, str]] = {} # mutable-ok: per-stream windows advanced in place. self._last_deltas: Final[dict[ResponsesStreamKey, object]] = {} # mutable-ok: newest delta per stream. + self._inserted: int = 0 + self._last_sequence_number: int | None = None async def restore(self, event: object) -> tuple[object, ...]: """The events to emit in place of `event`: any flush, then the event itself.""" @@ -281,7 +284,7 @@ class ResponsesStreamRestorer: return (event,) if kind.endswith(".delta") and kind not in RESPONSES_BINARY_DELTAS: await self._restore_delta(event, kind) - return (event,) + return self._numbered((), event) slots: Final[SlotSink] = [] flushed: Final = await self._flush(responses_stream_key(event, kind)) if kind.endswith(".done") else () if kind.endswith(".done"): @@ -294,12 +297,29 @@ class ResponsesStreamRestorer: for item in read_list(read_field(event, "response"), "output"): collect_response_item(item, slots) await rehydrate_slots(slots, self._rehydrate) - return (*flushed, event) + return self._numbered(flushed, event) async def finish(self) -> tuple[object, ...]: """Flushes every stream the provider never closed, e.g. a truncated reply.""" - flushed: Final = tuple([await self._flush(key) for key in tuple(self._carries)]) - return tuple(itertools.chain.from_iterable(flushed)) + flushed: Final = tuple(itertools.chain.from_iterable([await self._flush(key) for key in tuple(self._carries)])) + last: Final = self._last_sequence_number + if last is not None: + for offset, flush in enumerate(flushed, start=1): + write_field(flush, "sequence_number", last + offset) + return flushed + + def _numbered(self, flushed: tuple[object, ...], event: object) -> tuple[object, ...]: + """Gives each flush the slot `event` arrived in and moves `event` and later events up.""" + number: Final = read_field(event, "sequence_number") + if not isinstance(number, int): + return (*flushed, event) + for offset, flush in enumerate(flushed): + write_field(flush, "sequence_number", number + self._inserted + offset) + self._inserted += len(flushed) + self._last_sequence_number = number + self._inserted + if self._inserted: + write_field(event, "sequence_number", self._last_sequence_number) + return (*flushed, event) async def _restore_delta(self, event: object, kind: str) -> None: text: Final = read_field(event, "delta") diff --git a/litellm/proxy/guardrails/guardrail_hooks/mcp_security/mcp_security_guardrail.py b/litellm/proxy/guardrails/guardrail_hooks/mcp_security/mcp_security_guardrail.py index 9c0a574ae3b..b4652e010ff 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/mcp_security/mcp_security_guardrail.py +++ b/litellm/proxy/guardrails/guardrail_hooks/mcp_security/mcp_security_guardrail.py @@ -107,9 +107,20 @@ class MCPSecurityGuardrail(CustomGuardrail): from litellm.proxy.mcp_server.mcp_server_manager import ( global_mcp_server_manager, ) + from litellm.proxy.proxy_server import prisma_client async with global_mcp_server_manager.catalog.operation(): - registry: Final = global_mcp_server_manager.get_registry() - registered_names: Final = set(registry.keys()) - - return frozenset(requested_servers - registered_names) + not_servers: Final = frozenset( + name + for name in requested_servers + if global_mcp_server_manager.get_mcp_server_by_identifier(name) is None + ) + if prisma_client is None: + return not_servers + return frozenset( + [ + name + for name in not_servers + if await global_mcp_server_manager.get_toolset_by_name_cached(prisma_client, name) is None + ] + ) diff --git a/litellm/proxy/guardrails/guardrail_hooks/noma/noma.py b/litellm/proxy/guardrails/guardrail_hooks/noma/noma.py index d69fe4068e0..4880444ada1 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/noma/noma.py +++ b/litellm/proxy/guardrails/guardrail_hooks/noma/noma.py @@ -504,8 +504,7 @@ class NomaGuardrail(CustomGuardrail): messages[i]["content"] = anonymized_content break - def _replace_llm_response_content(self, response: LLMResponse, anonymized_content: str, position: int): - """Replace the content of the choice at ``position`` with its anonymized version.""" + def _replace_llm_response_content(self, response: LLMResponse, anonymized_content: str, position: int) -> None: if not isinstance(response, litellm.ModelResponse): return diff --git a/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py b/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py index 5f9dc4a7a31..5f99b1a4611 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py +++ b/litellm/proxy/guardrails/guardrail_hooks/tool_permission.py @@ -1,13 +1,16 @@ import json import re -from collections.abc import AsyncGenerator, AsyncIterable, Mapping, Sequence -from typing import Any, Final, Literal, TypedDict +from collections.abc import AsyncGenerator, AsyncIterable, Callable, Iterable, Mapping, Sequence +from dataclasses import dataclass +from functools import partial, reduce +from itertools import chain, groupby +from types import MappingProxyType +from typing import Any, Final, Literal, TypeAlias, TypedDict, TypeVar from fastapi import HTTPException from pydantic import TypeAdapter from typing_extensions import ReadOnly, Required -from litellm import ChatCompletionToolParam from litellm._logging import verbose_proxy_logger from litellm.caching.dual_cache import DualCache from litellm.completion_extras.litellm_responses_transformation.transformation import ( @@ -19,6 +22,9 @@ from litellm.integrations.custom_guardrail import ( CustomGuardrail, log_guardrail_information, ) +from litellm.litellm_core_utils.core_helpers import as_str_mapping, attribute_or_none +from litellm.litellm_core_utils.tool_fields import declared_function_name, qualified_member_name +from litellm.llms.base_llm.guardrail_translation.utils import anthropic_tool_names from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.common_utils.callback_utils import ( add_guardrail_to_applied_guardrails_header, @@ -30,7 +36,10 @@ from litellm.proxy.guardrails.anthropic_sse import ( is_raw_sse_stream, is_sse_error_stream, ) +from litellm.responses.additional_tools import ADDITIONAL_TOOLS_INPUT_ITEM_TYPE from litellm.types.guardrails import GuardrailEventHooks, LitellmParams +from litellm.types.llms.anthropic import ANTHROPIC_HOSTED_TOOLS +from litellm.types.llms.vertex_ai import VertexToolName from litellm.types.proxy.guardrails.guardrail_hooks.tool_permission import ( PermissionError, ToolPermissionRule, @@ -48,8 +57,48 @@ from litellm.types.utils import ( ) GUARDRAIL_NAME: Final = "tool_permission" +_MCP_TOOLSET_TYPE: Final = "mcp_toolset" +_HOSTED_SERVER_NAME_FIELDS: Final = MappingProxyType({"mcp": "server_label", _MCP_TOOLSET_TYPE: "mcp_server_name"}) +_TOOL_CARRYING_INPUT_TYPES: Final = frozenset({"tool_search_output", ADDITIONAL_TOOLS_INPUT_ITEM_TYPE}) +_DECLARATION_KEYS: Final = ("functionDeclarations", "function_declarations") +_NON_TOOL_PART_KEYS: Final = frozenset({*_DECLARATION_KEYS, "cachePoint", "type"}) +_TOOL_CONFIG_KEYS: Final = ("toolConfig", "tool_config") +_FUNCTION_CALLING_CONFIG_KEYS: Final = ("functionCallingConfig", "function_calling_config") +_ALLOWED_FUNCTION_NAMES_KEYS: Final = ("allowedFunctionNames", "allowed_function_names") +_FORCED_FUNCTION_CALLING_MODES: Final = frozenset({"ANY", "VALIDATED"}) +_NAME_IDENTIFIED_TYPES: Final = frozenset({"function", "custom", "namespace", *_HOSTED_SERVER_NAME_FIELDS}) +_TEXT_EDITOR_TOOL_NAMES: Final = frozenset({"str_replace_editor", "str_replace_based_edit_tool"}) +_TYPE_VERSION_SUFFIX: Final = re.compile(r"_\d{8}$") +_GEMINI_TYPED_HOSTED_TOOLS: Final = ("computer_use", "web_search", "web_search_preview") +_NAMED_CHOICE_TYPES: Final = frozenset({"tool", "function", "custom", "allowed_tools", "any", "auto", "none"}) _DECODED_ARGUMENTS: Final = TypeAdapter(object) _REQUEST_DATA: Final = TypeAdapter(object) +_ToolTarget: TypeAlias = tuple[str | None, str | None] +_JudgedCalls: TypeAlias = Mapping[str, tuple[tuple[str, str], ...]] +_GroupedT: Final = TypeVar("_GroupedT") + + +def _snake_case(name: str) -> str: + return re.sub(r"(? str: + head, *rest = name.split("_") + return head + "".join(part.title() for part in rest) + + +_GEMINI_HOSTED_TOOL_KEYS: Final = frozenset( + chain.from_iterable((_snake_case(tool.value), _camel_case(tool.value)) for tool in VertexToolName) +) + + +def _name_identifies_tool(name: str, tool_type: str) -> bool: + stem: Final = _TYPE_VERSION_SUFFIX.sub("", tool_type) + return ( + tool_type in _NAME_IDENTIFIED_TYPES + or name == stem + or (stem == ANTHROPIC_HOSTED_TOOLS.TEXT_EDITOR.value and name in _TEXT_EDITOR_TOOL_NAMES) + ) def _object_mapping(value: object) -> Mapping[str, object] | None: @@ -68,6 +117,356 @@ def _function_tool_name(tool: object) -> str | None: return name if isinstance(name, str) else None +def _non_empty_string(value: object) -> str | None: + return value if isinstance(value, str) and value else None + + +def _request_tool_names(tool: object) -> tuple[str, ...]: + fields: Final = _object_mapping(tool) + custom: Final = ( + _object_mapping(fields.get("custom")) if fields is not None and fields.get("type") == "custom" else None + ) + custom_name: Final = _non_empty_string(custom.get("name")) if custom is not None else None + server_field: Final = _HOSTED_SERVER_NAME_FIELDS.get(str(fields.get("type"))) if fields is not None else None + server_name: Final = ( + _non_empty_string(fields.get(server_field)) if fields is not None and server_field is not None else None + ) + extra_names: Final = tuple(name for name in (_function_name(tool), custom_name, server_name) if name is not None) + return tuple(dict.fromkeys(anthropic_tool_names(tool) + extra_names)) + + +def _function_name(tool: object) -> str | None: + fields: Final = _object_mapping(tool) + function: Final = _object_mapping(fields.get("function")) if fields is not None else None + return _non_empty_string(function.get("name")) if function is not None else None + + +def _namespace_function_targets(tool: object) -> tuple[_ToolTarget, ...]: + function_name: Final = _function_name(tool) + return ((function_name, "function"),) if function_name is not None else () + + +def _gemini_hosted_key_targets(tool: object) -> tuple[_ToolTarget, ...]: + fields: Final = _object_mapping(tool) + if fields is None or fields.get("type") in _GEMINI_TYPED_HOSTED_TOOLS: + return () + keys: Final = tuple(key for key in fields if key != "type") + return (_part_target(fields, keys[0]),) if len(keys) == 1 and keys[0] in _GEMINI_HOSTED_TOOL_KEYS else () + + +def _is_namespace(tool: object) -> bool: + fields: Final = _object_mapping(tool) + return fields is not None and fields.get("type") == "namespace" + + +def _namespace_members(tool: object) -> Sequence[object]: + fields: Final = _object_mapping(tool) + members: Final = _object_list(fields.get("tools")) if fields is not None and _is_namespace(tool) else None + return members or () + + +def _returned_namespace(tool_call: ChatCompletionMessageToolCall) -> str | None: + tags: Final = as_str_mapping(attribute_or_none(tool_call, "provider_specific_fields")) + return _non_empty_string(tags.get("namespace")) if tags is not None else None + + +def _judged_call_names( + tool_call: ChatCompletionMessageToolCall, returned_name: str, judged_names: _JudgedCalls +) -> tuple[tuple[str, str], ...]: + namespace: Final = _returned_namespace(tool_call) + if namespace is not None: + return ((qualified_member_name(namespace, returned_name), returned_name),) + return judged_names.get(returned_name, ()) + + +def _pair_namespace(qualified: str, bare: str) -> str | None: + suffix: Final = qualified_member_name("", bare) + if qualified == bare or not qualified.endswith(suffix): + return None + return _non_empty_string(qualified.removesuffix(suffix)) + + +def _qualified_target(namespace: str | None, target: _ToolTarget) -> _ToolTarget: + name, tool_type = target + return (qualified_member_name(namespace, name), tool_type) if namespace is not None and name is not None else target + + +def _member_name(member: object) -> str | None: + fields: Final = _object_mapping(member) + return _non_empty_string(fields.get("name")) if fields is not None else None + + +def _declaration_targets(declaration: object) -> tuple[_ToolTarget, ...]: + name: Final = _member_name(declaration) + return ((name, "function"),) if name is not None else () + + +@dataclass(frozen=True, slots=True) +class _MemberGroup: + key: str + members: Sequence[object] + targets_of: Callable[[object], tuple[_ToolTarget, ...]] + + +def _member_group( + tool: object, namespace_member_targets: Callable[[str | None, object], tuple[_ToolTarget, ...]] +) -> _MemberGroup | None: + fields: Final = _object_mapping(tool) + if fields is None: + return None + members: Final = _namespace_members(tool) + if members: + return _MemberGroup("tools", members, partial(namespace_member_targets, _member_name(tool))) + key: Final = next((key for key in _DECLARATION_KEYS if _object_list(fields.get(key))), None) + declarations: Final = _object_list(fields.get(key)) if key is not None else None + return _MemberGroup(key, declarations, _declaration_targets) if key is not None and declarations else None + + +def _keyed_tool_fields(tool: object) -> Mapping[str, object] | None: + fields: Final = _object_mapping(tool) + if fields is None or isinstance(fields.get("type"), str) or _request_tool_names(tool): + return None + return fields + + +def _part_keys(fields: Mapping[str, object]) -> tuple[str, ...]: + return tuple(key for key in fields if key not in _NON_TOOL_PART_KEYS) + + +def _part_target(fields: Mapping[str, object], key: str) -> _ToolTarget: + return (None if key in _GEMINI_HOSTED_TOOL_KEYS else _member_name(fields.get(key)), key) + + +def _input_item_tools(item: object) -> Sequence[object] | None: + fields: Final = _object_mapping(item) + carries_tools: Final = fields is not None and _non_empty_string(fields.get("type")) in _TOOL_CARRYING_INPUT_TYPES + return _object_list(fields.get("tools")) if fields is not None and carries_tools else None + + +def _request_list(data: object, key: str) -> Sequence[object] | None: + fields: Final = _object_mapping(data) + return _object_list(fields.get(key)) if fields is not None else None + + +def _input_items(data: object) -> Sequence[object]: + return _request_list(data, "input") or () + + +def _tools_in_items(items: Sequence[object]) -> tuple[object, ...]: + return tuple(chain.from_iterable(_input_item_tools(item) or () for item in items)) + + +def _carries_tools(items: Sequence[object]) -> bool: + return any(_input_item_tools(item) is not None for item in items) + + +def _pair_key(pair: tuple[str, object]) -> str: + return pair[0] + + +def _grouped_values(pairs: Iterable[tuple[str, _GroupedT]]) -> Mapping[str, tuple[_GroupedT, ...]]: + groups: Final = groupby(sorted(pairs, key=_pair_key), key=_pair_key) + return MappingProxyType({key: tuple(dict.fromkeys(value for _, value in group)) for key, group in groups}) + + +def _request_layers(data: object) -> tuple[Mapping[str, object], ...]: + fields: Final = _object_mapping(data) + extra_body: Final = _object_mapping(fields.get("extra_body")) if fields is not None else None + return tuple(layer for layer in (fields, extra_body) if layer is not None) + + +def _layer_sent_tools(layer: Mapping[str, object]) -> tuple[object, ...]: + return ( + *(_request_list(layer, "tools") or ()), + *(_request_list(layer, "functions") or ()), + *_tools_in_items(_input_items(layer)), + ) + + +def _sent_tools(data: object) -> tuple[object, ...]: + return tuple(chain.from_iterable(map(_layer_sent_tools, _request_layers(data)))) + + +def _sent_fields(data: object) -> Mapping[str, object]: + return dict(chain.from_iterable(layer.items() for layer in _request_layers(data))) + + +@dataclass(frozen=True, slots=True) +class _KeptLayer: + fields: Mapping[str, object] + tools: tuple[object, ...] | None + functions: tuple[object, ...] | None + mcp_servers: tuple[object, ...] | None + input: tuple[object, ...] | None + + def sent_tools(self) -> tuple[object, ...]: + kept_input: Final = _input_items(self.fields) if self.input is None else self.input + return (*(self.tools or ()), *(self.functions or ()), *_tools_in_items(kept_input)) + + def kept_lists(self) -> dict[str, object]: + lists: Final = ( + ("tools", self.tools), + ("functions", self.functions), + ("mcp_servers", self.mcp_servers), + ("input", self.input), + ) + return {key: list(kept) for key, kept in lists if kept is not None} + + def overlaid_by(self, over: "_KeptLayer") -> "_KeptLayer": + return _KeptLayer( + fields={**self.fields, **over.fields}, + tools=over.tools if "tools" in over.fields else self.tools, + functions=over.functions if "functions" in over.fields else self.functions, + mcp_servers=over.mcp_servers if "mcp_servers" in over.fields else self.mcp_servers, + input=over.input if "input" in over.fields else self.input, + ) + + +def _mcp_server_target(server: object) -> _ToolTarget: + fields: Final = _object_mapping(server) + return (_non_empty_string(fields.get("name")) if fields is not None else None, _MCP_TOOLSET_TYPE) + + +def _reference_name(part: object) -> str | None: + fields: Final = _object_mapping(part) + is_reference: Final = fields is not None and fields.get("type") == "tool_reference" + return _non_empty_string(fields.get("tool_name")) if fields is not None and is_reference else None + + +def _references_one_of(part: object, names: frozenset[str]) -> bool: + name: Final = _reference_name(part) + return name is not None and name in names + + +def _without_references_to(parts: Sequence[object], names: frozenset[str]) -> Sequence[object]: + removed: Final = [name for name in map(_reference_name, parts) if name is not None and name in names] + kept: Final = [part for part in parts if not _references_one_of(part, names)] + if kept or not removed: + return kept + return [{"type": "text", "text": f"Permission denied: tool {', '.join(removed)} is not available"}] + + +def _tool_result_without_references(fields: Mapping[str, object], names: frozenset[str]) -> object: + parts: Final = _object_list(fields.get("content")) + return {**fields, "content": _without_references_to(parts, names)} if parts else fields + + +def _search_result_without_references(fields: Mapping[str, object], names: frozenset[str]) -> object: + result: Final = _object_mapping(fields.get("content")) + references: Final = _object_list(result.get("tool_references")) if result is not None else None + if result is None or references is None: + return fields + kept: Final = [reference for reference in references if not _references_one_of(reference, names)] + return {**fields, "content": {**result, "tool_references": kept}} + + +def _without_references_in_block(block: object, names: frozenset[str]) -> object: + fields: Final = _object_mapping(block) + if fields is None: + return block + match fields.get("type"): + case "tool_result": + return _tool_result_without_references(fields, names) + case "tool_search_tool_result": + return _search_result_without_references(fields, names) + case _: + return block + + +def _without_references_in_message(message: object, names: frozenset[str]) -> object: + fields: Final = _object_mapping(message) + content: Final = _object_list(fields.get("content")) if fields is not None else None + if fields is None or content is None: + return message + if fields.get("role") == "tool": + return {**fields, "content": _without_references_to(content, names)} + return {**fields, "content": [_without_references_in_block(block, names) for block in content]} + + +def _allowed_tool_entries(tool_choice: Mapping[str, object]) -> Sequence[object] | None: + if tool_choice.get("type") != "allowed_tools": + return None + nested: Final = _object_mapping(tool_choice.get("allowed_tools")) + return _object_list((nested if nested is not None else tool_choice).get("tools")) + + +def _is_removed_entry(entry: object, removed_names: frozenset[str], removed_types: frozenset[str]) -> bool: + names: Final = _request_tool_names(entry) + if names: + return any(name in removed_names for name in names) + fields: Final = _object_mapping(entry) + entry_type: Final = _non_empty_string(fields.get("type")) if fields is not None else None + return entry_type is not None and entry_type in removed_types + + +def _with_allowed_tool_entries(tool_choice: Mapping[str, object], entries: list[object]) -> dict[str, object]: + nested: Final = _object_mapping(tool_choice.get("allowed_tools")) + if nested is None: + return {**tool_choice, "tools": entries} + return {**tool_choice, "allowed_tools": {**nested, "tools": entries}} + + +def _is_denied_target( + target: _ToolTarget, denied_targets: frozenset[_ToolTarget], denied_names: frozenset[str] +) -> bool: + return target in denied_targets or target[0] in denied_names + + +def _kept_members(group: _MemberGroup | None, is_denied: Callable[[_ToolTarget], bool]) -> tuple[object, ...]: + if group is None: + return () + return tuple(member for member in group.members if not any(map(is_denied, group.targets_of(member)))) + + +def _none_tool_choice(tool_choice: object) -> object: + choice: Final = _object_mapping(tool_choice) + return {"type": "none"} if choice is not None and choice.get("type") in ("tool", "any") else "none" + + +def _requires_a_tool(tool_choice: object) -> bool: + choice: Final = _object_mapping(tool_choice) + return tool_choice == "required" or (choice is not None and choice.get("type") == "any") + + +def _kept_allowed_function_names(config: Mapping[str, object], removed_names: frozenset[str]) -> Mapping[str, object]: + listed: Final = tuple((key, _object_list(config.get(key))) for key in _ALLOWED_FUNCTION_NAMES_KEYS) + return { + key: [name for name in names if _non_empty_string(name) not in removed_names] + for key, names in listed + if names is not None + } + + +def _rewritten_function_calling_config( + config: Mapping[str, object], removed_names: frozenset[str], functions_remain: bool +) -> Mapping[str, object]: + kept_names: Final = _kept_allowed_function_names(config, removed_names) + had_names: Final = any(_object_list(config.get(key)) for key in _ALLOWED_FUNCTION_NAMES_KEYS) + every_listed_name_removed: Final = had_names and not any(kept_names.values()) + forces_a_function: Final = str(config.get("mode", "")).upper() in _FORCED_FUNCTION_CALLING_MODES + if not every_listed_name_removed and (functions_remain or not forces_a_function): + return {**config, **kept_names} + return {**{key: value for key, value in config.items() if key not in _ALLOWED_FUNCTION_NAMES_KEYS}, "mode": "NONE"} + + +def _rewritten_tool_config_field( + key: str, value: object, removed_names: frozenset[str], functions_remain: bool +) -> object: + config: Final = _object_mapping(value) + if key not in _FUNCTION_CALLING_CONFIG_KEYS or config is None: + return value + return _rewritten_function_calling_config(config, removed_names, functions_remain) + + +def _rewritten_tool_config(tool_config: object, removed_names: frozenset[str], functions_remain: bool) -> object: + fields: Final = _object_mapping(tool_config) + if fields is None: + return tool_config + return { + key: _rewritten_tool_config_field(key, value, removed_names, functions_remain) for key, value in fields.items() + } + + class _ToolPermissionRuleFields(TypedDict, total=False): """The config-file shape a :class:`ToolPermissionRule` is built from.""" @@ -258,7 +657,7 @@ class ToolPermissionGuardrail(CustomGuardrail): name_required: Final = rule.tool_name is not None type_required: Final = rule.tool_type is not None - name_matched: Final = self._matches_regex(name_pattern, tool_name) if name_required else True + name_matched: Final = self._matches_regex(name_pattern, tool_name or tool_type) if name_required else True type_matched: Final = self._matches_regex(type_pattern, tool_type) if type_required else True overall_match: Final = name_matched and type_matched @@ -320,6 +719,72 @@ class ToolPermissionGuardrail(CustomGuardrail): verbose_proxy_logger.debug(message) return is_allowed, None, message + def _is_name_rule_for(self, rule: ToolPermissionRule, tool_name: str, tool_type: str | None) -> bool: + return rule.tool_name is not None and self._rule_matches_tool(rule, tool_name=tool_name, tool_type=tool_type)[0] + + def _decides_call( + self, rule: ToolPermissionRule, tool_name: str, tool_call: ChatCompletionMessageToolCall | None + ) -> bool: + if tool_call is None or not rule.allowed_param_patterns: + return True + arguments, parse_error = self._parse_tool_call_arguments(tool_call) + if parse_error or not arguments: + return True + return self._patterns_match_for_rule(arguments=arguments, rule=rule, tool_name=tool_name)[0] + + def _first_name_rule( + self, tool_name: str, tool_type: str | None, tool_call: ChatCompletionMessageToolCall | None + ) -> ToolPermissionRule | None: + return next( + ( + rule + for rule in self.rules + if self._is_name_rule_for(rule, tool_name, tool_type) and self._decides_call(rule, tool_name, tool_call) + ), + None, + ) + + def _narrower_name( + self, + name: str, + other: str, + tool_type: str | None, + tool_call: ChatCompletionMessageToolCall | None, + ) -> str: + rule: Final = self._first_name_rule(name, tool_type, tool_call) + other_rule: Final = self._first_name_rule(other, tool_type, tool_call) + if other_rule is None or other_rule is rule: + return name + if rule is None or self._is_name_rule_for(rule, other, tool_type): + return other + if self._is_name_rule_for(other_rule, name, tool_type): + return name + return other if other_rule.decision == "deny" else name + + def _deciding_member_name( + self, + qualified: str, + bare: str, + tool_type: str | None, + tool_call: ChatCompletionMessageToolCall | None = None, + ) -> str: + member: Final = self._narrower_name(qualified, bare, tool_type, tool_call) + namespace: Final = _pair_namespace(qualified, bare) + return member if namespace is None else self._narrower_name(member, namespace, tool_type, tool_call) + + def _check_target_permission( + self, target: _ToolTarget, bare_names: Mapping[str, tuple[str, ...]] + ) -> tuple[bool, str | None, str | None]: + name, tool_type = target + candidates: Final = tuple(sorted(bare_names.get(name, ()))) if name is not None else () + if name is None or not candidates: + return self._check_tool_permission(name, tool_type) + results: Final = tuple( + self._check_tool_permission(self._deciding_member_name(name, bare_name, tool_type), tool_type) + for bare_name in candidates + ) + return next((result for result in results if not result[0]), results[0]) + def _parse_tool_call_arguments( self, tool_call: ChatCompletionMessageToolCall ) -> tuple[Mapping[str, object] | None, str | None]: @@ -411,9 +876,9 @@ class ToolPermissionGuardrail(CustomGuardrail): return True, None def _get_permission_for_tool_call( - self, tool_call: ChatCompletionMessageToolCall + self, tool_call: ChatCompletionMessageToolCall, judged_name: str | None = None ) -> tuple[bool, str | None, str | None]: - tool_name: Final = tool_call.function.name if tool_call.function else None + tool_name: Final = judged_name or (tool_call.function.name if tool_call.function else None) tool_type: Final = getattr(tool_call, "type", None) if not tool_name and not tool_type: return self.default_action == "allow", None, None @@ -556,10 +1021,46 @@ class ToolPermissionGuardrail(CustomGuardrail): tool_call for block in content if (tool_call := self._anthropic_tool_use_to_tool_call(block)) is not None ) + def _returned_call_names(self, data: Mapping[str, object]) -> _JudgedCalls: + sent_tools: Final = _sent_tools(_REQUEST_DATA.validate_python(data)) + member_names: Final = tuple(chain.from_iterable(map(self._bare_member_names, sent_tools))) + if not member_names: + return MappingProxyType({}) + top_level_tools: Final = (tool for tool in sent_tools if not _is_namespace(tool)) + top_level_names: Final = frozenset(name for name in map(declared_function_name, top_level_tools) if name) + listed: Final = frozenset(name for name, _ in self._collect_request_tools(data) if name is not None) + own_names: Final = frozenset(bare for _, bare in member_names if bare in listed) | top_level_names + returned_members: Final = _grouped_values( + chain( + ((bare, (name, bare)) for name, bare in member_names if bare not in top_level_names), + ((name, (name, bare)) for name, bare in member_names if name not in top_level_names), + ) + ) + return MappingProxyType( + { + name: (*members, *(((name, name),) if name in own_names else ())) + for name, members in returned_members.items() + } + ) + + def _judged_name(self, tool_call: ChatCompletionMessageToolCall, qualified: str, bare: str) -> str: + return qualified if qualified == bare else self._deciding_member_name(qualified, bare, "function", tool_call) + + def _judge_tool_call( + self, tool_call: ChatCompletionMessageToolCall, judged_names: _JudgedCalls + ) -> tuple[bool, str | None, str | None]: + returned_name: Final = tool_call.function.name if tool_call.function else None + names: Final = _judged_call_names(tool_call, returned_name, judged_names) if returned_name is not None else () + if returned_name is None or not names: + return self._get_permission_for_tool_call(tool_call) + judged: Final = dict.fromkeys(self._judged_name(tool_call, qualified, bare) for qualified, bare in names) + results: Final = tuple(self._get_permission_for_tool_call(tool_call, name) for name in judged) + return next((result for result in results if not result[0]), results[0]) + def _evaluate_tool_calls( - self, tool_calls: Sequence[ChatCompletionMessageToolCall] + self, tool_calls: Sequence[ChatCompletionMessageToolCall], judged_names: _JudgedCalls ) -> tuple[tuple[ChatCompletionMessageToolCall, PermissionError], ...]: - checked: Final = tuple((tool_call, *self._get_permission_for_tool_call(tool_call)) for tool_call in tool_calls) + checked: Final = tuple((tool_call, *self._judge_tool_call(tool_call, judged_names)) for tool_call in tool_calls) for _tool_call, is_allowed, _rule_id, message in checked: if not is_allowed and message is not None: @@ -619,112 +1120,311 @@ class ToolPermissionGuardrail(CustomGuardrail): if not any(_is_tool_use_block(block) for block in kept_blocks): response["stop_reason"] = "end_turn" # rebind-ok: dropping every tool_use ends the turn - def _get_request_tool_name(self, tool: object) -> tuple[str | None, str | None]: - tool_type: Final = self._get_mapping_value(tool, "type") - if tool_type != "function": - return None, tool_type + def _unqualified_member_targets(self, member: object) -> tuple[_ToolTarget, ...]: + fields: Final = _object_mapping(member) + if fields is None: + return () + targets: Final = self._get_request_tool_targets(member) + own_name: Final = _member_name(member) + judged_names: Final = frozenset(name for name, _ in targets) + own_target: Final = ( + ((own_name, _non_empty_string(fields.get("type"))),) + if own_name is not None and own_name not in judged_names + else () + ) + return targets + own_target - function: Final = self._get_mapping_value(tool, "function") - tool_name: Final = self._get_mapping_value(function, "name") - return tool_name, tool_type + def _namespace_member_targets(self, namespace: str | None, member: object) -> tuple[_ToolTarget, ...]: + return tuple(_qualified_target(namespace, target) for target in self._unqualified_member_targets(member)) - def _get_legacy_function_name(self, function: object) -> str | None: - return self._get_mapping_value(function, "name") + def _bare_member_names(self, tool: object) -> tuple[tuple[str, str], ...]: + namespace: Final = _member_name(tool) + members: Final = _namespace_members(tool) + if namespace is None or not members: + return () + targets: Final = chain.from_iterable(map(self._unqualified_member_targets, members)) + return tuple((qualified_member_name(namespace, name), name) for name, _ in targets if name is not None) - def _get_named_tool_choice(self, data: dict) -> str | None: - tool_choice: Final = data.get("tool_choice") + def _get_request_tool_targets(self, tool: object) -> tuple[_ToolTarget, ...]: + group: Final = _member_group(tool, self._namespace_member_targets) + member_targets: Final = ( + tuple(chain.from_iterable(map(group.targets_of, group.members))) if group is not None else () + ) + keyed: Final = _keyed_tool_fields(tool) + part_targets: Final = tuple(_part_target(keyed, key) for key in _part_keys(keyed)) if keyed is not None else () + return member_targets + part_targets + self._own_tool_targets(tool) + + def _own_tool_targets(self, tool: object) -> tuple[_ToolTarget, ...]: + if _keyed_tool_fields(tool) is not None: + return () + named: Final = _namespace_function_targets(tool) if _namespace_members(tool) else self._named_tool_targets(tool) + return named + _gemini_hosted_key_targets(tool) + + def _named_tool_targets(self, tool: object) -> tuple[_ToolTarget, ...]: + raw_type: Final = self._get_mapping_value(tool, "type") + tool_type: Final = raw_type if isinstance(raw_type, str) else None + anthropic_custom: Final = ( + tool_type == "custom" + and self._get_mapping_value(tool, "input_schema") is not None + and _object_mapping(self._get_mapping_value(tool, "custom")) is None + ) + normalized_type: Final = "function" if tool_type is None or anthropic_custom else tool_type + names: Final = _request_tool_names(tool) + named_targets: Final = tuple((name, normalized_type) for name in names) + if names and all(_name_identifies_tool(name, normalized_type) for name in names): + return named_targets + if names: + return (*named_targets, (None, normalized_type)) + return ((None, tool_type),) if tool_type is not None else () + + def _get_named_tool_choice(self, tool_choice: object) -> str | None: if not tool_choice or tool_choice in ("auto", "none", "required"): return None if isinstance(tool_choice, str): return tool_choice - if self._get_mapping_value(tool_choice, "type") != "function": + choice: Final = _object_mapping(tool_choice) + if choice is None: return None - return self._get_mapping_value(self._get_mapping_value(tool_choice, "function"), "name") + choice_type: Final = choice.get("type") + server_field: Final = _HOSTED_SERVER_NAME_FIELDS.get(str(choice_type)) + if server_field is not None: + return _non_empty_string(choice.get(server_field)) + if choice_type not in ("tool", "function", "custom"): + return None + nested: Final = _object_mapping(choice.get(str(choice_type))) + nested_name: Final = _non_empty_string(nested.get("name")) if nested is not None else None + return nested_name or _non_empty_string(choice.get("name")) - def _get_named_function_call(self, data: dict) -> str | None: + def _get_named_function_call(self, data: Mapping[str, object]) -> str | None: function_call: Final = data.get("function_call") if not function_call or function_call in ("auto", "none"): return None if isinstance(function_call, str): return function_call - return self._get_mapping_value(function_call, "name") + return _non_empty_string(self._get_mapping_value(function_call, "name")) - def _collect_request_tools(self, data: dict) -> list[tuple[str, str | None]]: - request_tools: Final[list[tuple[str, str | None]]] = [] + def _listed_layer_targets(self, layer: Mapping[str, object]) -> tuple[_ToolTarget, ...]: + return ( + *chain.from_iterable(map(self._get_request_tool_targets, _request_list(layer, "tools") or ())), + *map(_mcp_server_target, _request_list(layer, "mcp_servers") or ()), + *chain.from_iterable(map(self._legacy_function_targets, _request_list(layer, "functions") or ())), + ) - for tool in data.get("tools") or []: - tool_name, tool_type = self._get_request_tool_name(tool) - if tool_name is not None: - request_tools.append((tool_name, tool_type)) + def _forced_layer_names(self, layer: Mapping[str, object]) -> tuple[str | None, ...]: + return (self._get_named_tool_choice(layer.get("tool_choice")), self._get_named_function_call(layer)) - for function in data.get("functions") or []: - function_name = self._get_legacy_function_name(function) - if function_name is not None: - request_tools.append((function_name, "function")) + def _collect_request_tools(self, data: Mapping[str, object]) -> tuple[_ToolTarget, ...]: + request: Final = _REQUEST_DATA.validate_python(data) + layers: Final = _request_layers(request) + listed: Final = tuple(chain.from_iterable(map(self._listed_layer_targets, layers))) + listed_names: Final = frozenset(name for name, _ in listed) + forced: Final = chain.from_iterable(map(self._forced_layer_names, layers)) + replayed: Final = map(_function_tool_name, replayed_tool_search_tools(request)) + input_tools: Final = _tools_in_items(tuple(chain.from_iterable(map(_input_items, layers)))) + return ( + *listed, + *((name, "function") for name in forced if name is not None and name not in listed_names), + *((name, "function") for name in replayed if name is not None), + *chain.from_iterable(map(self._get_request_tool_targets, input_tools)), + ) - for forced_tool_name in ( - self._get_named_tool_choice(data), - self._get_named_function_call(data), - ): - if forced_tool_name is not None: - request_tools.append((forced_tool_name, "function")) + def _legacy_function_targets(self, function: object) -> tuple[_ToolTarget, ...]: + targets: Final = self._get_request_tool_targets(function) + as_functions: Final = tuple((name, "function") for name, _ in targets if name is not None) + return tuple(dict.fromkeys(targets + as_functions)) - replayed: Final = map(_function_tool_name, replayed_tool_search_tools(_REQUEST_DATA.validate_python(data))) - request_tools.extend((name, "function") for name in replayed if name is not None) + def _kept_layer( + self, + layer: Mapping[str, object], + denied_targets: frozenset[_ToolTarget], + denied_names: frozenset[str], + ) -> _KeptLayer: + is_denied: Final = partial(_is_denied_target, denied_targets=denied_targets, denied_names=denied_names) + tools: Final = _request_list(layer, "tools") + functions: Final = _request_list(layer, "functions") + mcp_servers: Final = _request_list(layer, "mcp_servers") + return _KeptLayer( + fields=layer, + tools=None if tools is None else self._kept_tool_list(tools, denied_targets, denied_names), + functions=None if functions is None else self._kept_tool_list(functions, denied_targets, denied_names), + mcp_servers=( + None + if mcp_servers is None + else tuple(server for server in mcp_servers if not is_denied(_mcp_server_target(server))) + ), + input=self._kept_input_list(_input_items(layer), denied_targets, denied_names), + ) - return request_tools + def _rewritten_layer_fields( + self, + kept: _KeptLayer, + rewrite_choice: Callable[[object], object], + removed_names: frozenset[str], + functions_remain: bool, + ) -> dict[str, object]: + layer: Final = kept.fields + choice: Final = layer.get("tool_choice") + relaxes_function_call: Final = self._get_named_function_call(layer) in removed_names + return { + **kept.kept_lists(), + **({"tool_choice": rewrite_choice(choice)} if choice is not None else {}), + **({"function_call": "none"} if relaxes_function_call else {}), + **{ + key: _rewritten_tool_config(layer[key], removed_names, functions_remain) + for key in _TOOL_CONFIG_KEYS + if key in layer + }, + } + + def _tool_names_in(self, tools: Sequence[object]) -> frozenset[str]: + targets: Final = chain.from_iterable(self._get_request_tool_targets(tool) for tool in tools) + return frozenset(name for name, _ in targets if name is not None) + + def _referable_names_in(self, tools: Sequence[object]) -> frozenset[str]: + member_names: Final = chain.from_iterable(map(self._bare_member_names, tools)) + namespace_names: Final = (_member_name(tool) for tool in tools if _namespace_members(tool)) + return ( + self._tool_names_in(tools) + | frozenset(bare for _, bare in member_names) + | frozenset(name for name in namespace_names if name is not None) + ) + + def _kept_tools( + self, + tool: object, + denied_targets: frozenset[_ToolTarget], + denied_names: frozenset[str], + ) -> tuple[object, ...]: + is_denied: Final = partial(_is_denied_target, denied_targets=denied_targets, denied_names=denied_names) + group: Final = _member_group(tool, self._namespace_member_targets) + keyed: Final = _keyed_tool_fields(tool) + fields: Final = _object_mapping(tool) + if fields is None or (group is None and keyed is None): + return () if any(map(is_denied, self._get_request_tool_targets(tool))) else (tool,) + own_targets: Final = self._own_tool_targets(tool) + if any(map(is_denied, own_targets)): + return () + kept_members: Final = _kept_members(group, is_denied) + denied_keys: Final = ( + frozenset(key for key in _part_keys(keyed) if is_denied(_part_target(keyed, key))) + if keyed is not None + else frozenset[str]() + ) + if not denied_keys and len(kept_members) == len(group.members if group is not None else ()): + return (tool,) + emptied_group: Final = frozenset({group.key}) if group is not None and not kept_members else frozenset[str]() + dropped_keys: Final = denied_keys | emptied_group + kept_fields: Final = { + key: list(kept_members) if group is not None and key == group.key else value + for key, value in fields.items() + if key not in dropped_keys + } + own_name_left: Final = any(name is not None for name, _ in own_targets) + parts_left: Final = bool(kept_members) or own_name_left or (keyed is not None and bool(_part_keys(kept_fields))) + return (kept_fields,) if parts_left else () + + def _kept_tool_list( + self, + tools: Sequence[object], + denied_targets: frozenset[_ToolTarget], + denied_names: frozenset[str], + ) -> tuple[object, ...]: + return tuple(chain.from_iterable(self._kept_tools(tool, denied_targets, denied_names) for tool in tools)) + + def _kept_input_list( + self, + items: Sequence[object], + denied_targets: frozenset[_ToolTarget], + denied_names: frozenset[str], + ) -> tuple[object, ...] | None: + if not _carries_tools(items): + return None + return tuple(chain.from_iterable(self._kept_input_items(item, denied_targets, denied_names) for item in items)) + + def _kept_input_items( + self, + item: object, + denied_targets: frozenset[_ToolTarget], + denied_names: frozenset[str], + ) -> tuple[object, ...]: + fields: Final = _object_mapping(item) + tools: Final = _input_item_tools(item) + if fields is None or tools is None: + return (item,) + kept: Final = self._kept_tool_list(tools, denied_targets, denied_names) + emptied: Final = bool(tools) and not kept and fields.get("type") == ADDITIONAL_TOOLS_INPUT_ITEM_TYPE + return () if emptied else ({**fields, "tools": list(kept)},) + + def _tool_types_in(self, tools: Sequence[object]) -> frozenset[str]: + targets: Final = chain.from_iterable(self._get_request_tool_targets(tool) for tool in tools) + return frozenset(tool_type for _, tool_type in targets if tool_type is not None) + + def _rewritten_tool_choice( + self, tool_choice: object, removed_names: frozenset[str], removed_types: frozenset[str], tools_remain: bool + ) -> object: + named: Final = self._get_named_tool_choice(tool_choice) + if named is not None and named in removed_names: + return _none_tool_choice(tool_choice) + choice: Final = _object_mapping(tool_choice) + hosted_type: Final = _non_empty_string(choice.get("type")) if choice is not None else None + if hosted_type not in _NAMED_CHOICE_TYPES and hosted_type in removed_types: + return _none_tool_choice(tool_choice) + allowed: Final = _allowed_tool_entries(choice) if choice is not None else None + if choice is not None and allowed is not None: + kept: Final = [entry for entry in allowed if not _is_removed_entry(entry, removed_names, removed_types)] + return _with_allowed_tool_entries(choice, kept) if kept and tools_remain else _none_tool_choice(choice) + if not tools_remain and (named is not None or _requires_a_tool(tool_choice)): + return _none_tool_choice(tool_choice) + return tool_choice def _modify_request_with_permission_errors( self, data: dict, - denied_tool_names: list[str], + denied_targets: frozenset[_ToolTarget], ): """ - Modify the request to replace denied tool_calls blocks with error results - - Args: - data: The model request to modify - denied_tools: List of (tool_use, error) tuples for denied tools + Remove denied tools from the request, and relax any tool_choice that would still require one """ - if not denied_tool_names: + if not denied_targets: return data - verbose_proxy_logger.info("Blocking %s unauthorized tool uses", len(denied_tool_names)) + verbose_proxy_logger.info("Blocking %s unauthorized tool uses", len(denied_targets)) - # Create a mapping of tool_use_id to error result - error_tool_names: Final = set() - for tool_use in denied_tool_names: - error_tool_names.add(tool_use) - - tools: Final[list[ChatCompletionToolParam] | None] = data.get("tools") - if tools is not None: - new_tools: Final = [] - for tool in tools: - tool_name, tool_type = self._get_request_tool_name(tool) - if tool_type == "function" and tool_name in error_tool_names: - continue - new_tools.append(tool) - data["tools"] = new_tools - - functions: Final = data.get("functions") - if functions is not None: - data["functions"] = [ - function for function in functions if self._get_legacy_function_name(function) not in error_tool_names - ] - - named_tool_choice: Final = self._get_named_tool_choice(data) - if named_tool_choice in error_tool_names: - data["tool_choice"] = "none" - - named_function_call: Final = self._get_named_function_call(data) - if named_function_call in error_tool_names: - data["function_call"] = "none" - - messages: Final = without_tool_search_items_loading( - _REQUEST_DATA.validate_python(data), frozenset(denied_tool_names) + denied_names: Final = frozenset(name for name, _ in denied_targets if name is not None) + request: Final = _REQUEST_DATA.validate_python(data) + kept_layers: Final = tuple( + self._kept_layer(layer, denied_targets, denied_names) for layer in _request_layers(request) ) + + sent_tools: Final = _layer_sent_tools(_sent_fields(request)) + kept_sent: Final = reduce(_KeptLayer.overlaid_by, kept_layers) + kept_sent_tools: Final = kept_sent.sent_tools() + removed_names: Final = denied_names | ( + self._referable_names_in(sent_tools) - self._referable_names_in(kept_sent_tools) + ) + kept_types: Final = self._tool_types_in(kept_sent_tools) + removed_types: Final = self._tool_types_in(sent_tools) - kept_types + + tools_remain: Final = bool(kept_sent_tools) or bool(kept_sent.mcp_servers) + rewrite_choice: Final = partial( + self._rewritten_tool_choice, + removed_names=removed_names, + removed_types=removed_types, + tools_remain=tools_remain, + ) + rewritten: Final = tuple( + self._rewritten_layer_fields(kept, rewrite_choice, removed_names, "function" in kept_types) + for kept in kept_layers + ) + data.update(rewritten[0]) + if len(rewritten) > 1 and rewritten[1]: + data["extra_body"] = {**kept_layers[1].fields, **rewritten[1]} # rebind-ok: rewrite mode edits in place + + messages: Final = without_tool_search_items_loading(_REQUEST_DATA.validate_python(data), denied_names) if messages is not None: - data["messages"] = messages # rebind-ok: rewrite mode edits the request in place + data["messages"] = [ # rebind-ok: rewrite mode edits the request in place + _without_references_in_message(message, removed_names) for message in messages + ] return data @@ -843,25 +1543,29 @@ class ToolPermissionGuardrail(CustomGuardrail): ) return data - # Check permissions for each tool - denied_tool_names: Final = [] - for tool_name, tool_type in new_tools: - is_allowed, _, message = self._check_tool_permission(tool_name, tool_type) + member_names: Final = tuple( + chain.from_iterable(map(self._bare_member_names, _sent_tools(_REQUEST_DATA.validate_python(data)))) + ) + bare_names: Final = _grouped_values(member_names) + decisions: Final = tuple((target, self._check_target_permission(target, bare_names)) for target in new_tools) + denied: Final = tuple( + (target, message) + for target, (is_allowed, _, message) in decisions + if not is_allowed and message is not None + ) + for _, message in denied: + verbose_proxy_logger.info("Tool Permission Guardrail: %s", message) + if denied and self.on_disallowed_action == "block": + raise HTTPException( + status_code=400, + detail={ + "error": "Violated guardrail policy", + "detection_message": denied[0][1], + }, + ) - if not is_allowed and message is not None: - verbose_proxy_logger.info("Tool Permission Guardrail: %s", message) - if self.on_disallowed_action == "block": - raise HTTPException( - status_code=400, - detail={ - "error": "Violated guardrail policy", - "detection_message": message, - }, - ) - denied_tool_names.append(tool_name) - - if denied_tool_names: - data = self._modify_request_with_permission_errors(data, denied_tool_names) + if denied: + self._modify_request_with_permission_errors(data, frozenset(target for target, _ in denied)) verbose_proxy_logger.debug("Tool Permission Guardrail Pre-Call Hook: All tools allowed") @@ -908,7 +1612,7 @@ class ToolPermissionGuardrail(CustomGuardrail): verbose_proxy_logger.debug("Tool Permission Guardrail: Found %s tool calls", len(tool_calls)) - denied_tools: Final = self._evaluate_tool_calls(tool_calls) + denied_tools: Final = self._evaluate_tool_calls(tool_calls, self._returned_call_names(data)) if not denied_tools: verbose_proxy_logger.debug("Tool Permission Guardrail Post-Call Hook: All tools allowed") @@ -932,7 +1636,7 @@ class ToolPermissionGuardrail(CustomGuardrail): Args: user_api_key_dict: User API key information (unused but required by interface) response: The model response to check - request_data: The model request (unused but required by interface) + request_data: The model request """ # Import here to avoid circular imports @@ -949,7 +1653,9 @@ class ToolPermissionGuardrail(CustomGuardrail): stream_chunk_builder(chunks=all_chunks) if not is_raw_sse_stream(all_chunks) else None ) if isinstance(assembled_model_response, ModelResponse): - denied_tools = self._check_assembled_stream(assembled_model_response) + denied_tools = self._check_assembled_stream( + assembled_model_response, self._returned_call_names(request_data) + ) if denied_tools: self._modify_response_with_permission_errors(assembled_model_response, denied_tools) @@ -975,18 +1681,23 @@ class ToolPermissionGuardrail(CustomGuardrail): yield chunk return - for sse_chunk in self._anthropic_stream_to_deliver(anthropic_response, all_chunks): + for sse_chunk in self._anthropic_stream_to_deliver( + anthropic_response, all_chunks, self._returned_call_names(request_data) + ): yield sse_chunk def _anthropic_stream_to_deliver( - self, anthropic_response: ModelResponse, source_chunks: Sequence[object] + self, + anthropic_response: ModelResponse, + source_chunks: Sequence[object], + judged_names: _JudgedCalls, ) -> Sequence[object]: """The frames the client gets: on a failed upstream only what the check read, never the upstream's own. Assembly reads past an upstream error, and a client can read a frame of a broken stream that assembly does not, so forwarding those frames would pass a tool call nobody checked. """ - denials: Final = self._check_assembled_stream(anthropic_response) + denials: Final = self._check_assembled_stream(anthropic_response, judged_names) if denials: self._modify_response_with_permission_errors(anthropic_response, denials) elif not anthropic_sse_error_events(source_chunks): @@ -994,7 +1705,7 @@ class ToolPermissionGuardrail(CustomGuardrail): return anthropic_sse_chunks_from_response(anthropic_response, source_chunks, keep_explanations=True) def _check_assembled_stream( - self, assembled: ModelResponse + self, assembled: ModelResponse, judged_names: _JudgedCalls ) -> tuple[tuple[ChatCompletionMessageToolCall, PermissionError], ...]: verbose_proxy_logger.debug("Tool Permission Guardrail: Checking response") tool_calls: Final = self._extract_tool_calls_from_response(assembled) @@ -1002,7 +1713,7 @@ class ToolPermissionGuardrail(CustomGuardrail): verbose_proxy_logger.debug("Tool Permission Guardrail: No tool uses found") return () verbose_proxy_logger.debug("Tool Permission Guardrail: Found %s tool calls", len(tool_calls)) - denied_tools: Final = self._evaluate_tool_calls(tool_calls) + denied_tools: Final = self._evaluate_tool_calls(tool_calls, judged_names) if not denied_tools: verbose_proxy_logger.debug("Tool Permission Guardrail Post-Call Hook: All tools allowed") return denied_tools diff --git a/litellm/proxy/guardrails/usage_tracking.py b/litellm/proxy/guardrails/usage_tracking.py index 1ddbc139564..55e2e129e36 100644 --- a/litellm/proxy/guardrails/usage_tracking.py +++ b/litellm/proxy/guardrails/usage_tracking.py @@ -11,7 +11,7 @@ from datetime import datetime, timezone from functools import partial from itertools import groupby from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final, NamedTuple, TypeVar +from typing import TYPE_CHECKING, Any, Final, NamedTuple, Protocol, TypeVar from pydantic import TypeAdapter from typing_extensions import ReadOnly, TypedDict @@ -22,6 +22,7 @@ from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import billed_guard from litellm.proxy._types import DB_RETRY_SAFE_ERROR_TYPES from litellm.proxy.db.spend_log_batching import spend_log_write_batches from litellm.proxy.utils import PrismaClient +from litellm.repositories.prisma_protocols import TableActions from litellm.repositories.table_repositories import ( DailyGuardrailMetricsRepository, DailyGuardrailUsageUnitsRepository, @@ -40,7 +41,7 @@ _RowKey = TypeVar("_RowKey") _RowValue = TypeVar("_RowValue") -class _UsageUnitKey(NamedTuple): +class UsageUnitKey(NamedTuple): guardrail_id: str date: str team_id: str @@ -48,7 +49,7 @@ class _UsageUnitKey(NamedTuple): usage_unit: str -class _UsageUnitIncrement(NamedTuple): +class UsageUnitIncrement(NamedTuple): units: int cost: float """USD for the priced share of units.""" @@ -56,14 +57,14 @@ class _UsageUnitIncrement(NamedTuple): """Units recorded with no known price, the share cost leaves out.""" -def _usage_unit_key(entry: tuple[_UsageUnitKey, _UsageUnitIncrement]) -> _UsageUnitKey: +def _usage_unit_key(entry: tuple[UsageUnitKey, UsageUnitIncrement]) -> UsageUnitKey: return entry[0] -def _usage_unit_increment(units: int, cost: float | None) -> _UsageUnitIncrement: +def _usage_unit_increment(units: int, cost: float | None) -> UsageUnitIncrement: if cost is None: - return _UsageUnitIncrement(units=units, cost=0.0, untracked_units=units) - return _UsageUnitIncrement(units=units, cost=cost, untracked_units=0) + return UsageUnitIncrement(units=units, cost=0.0, untracked_units=units) + return UsageUnitIncrement(units=units, cost=cost, untracked_units=0) class _MetricsKey(NamedTuple): @@ -89,22 +90,22 @@ class PendingRollups: def __init__(self) -> None: self.lock: Final = asyncio.Lock() self.metrics: Mapping[_MetricsKey, Mapping[str, int]] = MappingProxyType({}) - self.units: Mapping[_UsageUnitKey, _UsageUnitIncrement] = MappingProxyType({}) + self.units: Mapping[UsageUnitKey, UsageUnitIncrement] = MappingProxyType({}) _PENDING_ROLLUPS: Final = PendingRollups() _NO_COUNTERS: Final[Mapping[str, int]] = MappingProxyType({}) -_NO_INCREMENT: Final = _UsageUnitIncrement(units=0, cost=0.0, untracked_units=0) +_NO_INCREMENT: Final = UsageUnitIncrement(units=0, cost=0.0, untracked_units=0) def _merged_keys(base: Mapping[_RowKey, object], extra: Mapping[_RowKey, object]) -> tuple[_RowKey, ...]: return (*base, *(key for key in extra if key not in base)) -def _summed_increments(increments: Iterable[_UsageUnitIncrement]) -> _UsageUnitIncrement: +def _summed_increments(increments: Iterable[UsageUnitIncrement]) -> UsageUnitIncrement: materialized: Final = tuple(increments) - return _UsageUnitIncrement( + return UsageUnitIncrement( units=sum(i.units for i in materialized), cost=sum(i.cost for i in materialized), untracked_units=sum(i.untracked_units for i in materialized), @@ -112,8 +113,8 @@ def _summed_increments(increments: Iterable[_UsageUnitIncrement]) -> _UsageUnitI def _merged_unit_rows( - base: Mapping[_UsageUnitKey, _UsageUnitIncrement], extra: Mapping[_UsageUnitKey, _UsageUnitIncrement] -) -> Mapping[_UsageUnitKey, _UsageUnitIncrement]: + base: Mapping[UsageUnitKey, UsageUnitIncrement], extra: Mapping[UsageUnitKey, UsageUnitIncrement] +) -> Mapping[UsageUnitKey, UsageUnitIncrement]: return MappingProxyType( { key: _summed_increments((base.get(key, _NO_INCREMENT), extra.get(key, _NO_INCREMENT))) @@ -250,7 +251,7 @@ def _parse_payload_start_time(payload: Mapping[str, object]) -> datetime | None: def _iter_usage_unit_increments( logs_to_process: Sequence[Mapping[str, object]], -) -> Iterator[tuple[_UsageUnitKey, _UsageUnitIncrement]]: +) -> Iterator[tuple[UsageUnitKey, UsageUnitIncrement]]: for payload in logs_to_process: start_time = _parse_payload_start_time(payload) if not payload.get("request_id") or start_time is None: @@ -266,14 +267,14 @@ def _iter_usage_unit_increments( cost_by_unit = billed_guardrail_cost_by_unit(entry) for unit_name, units in usage.items(): if isinstance(units, int) and not isinstance(units, bool) and units > 0: - key = _UsageUnitKey(guardrail_id, date_key, team_id, api_key, str(unit_name)) + key = UsageUnitKey(guardrail_id, date_key, team_id, api_key, str(unit_name)) cost = cost_by_unit.get(str(unit_name)) if cost_by_unit is not None else None yield key, _usage_unit_increment(units=units, cost=cost) def _sum_usage_unit_increments( logs_to_process: Sequence[Mapping[str, object]], -) -> Mapping[_UsageUnitKey, _UsageUnitIncrement]: +) -> Mapping[UsageUnitKey, UsageUnitIncrement]: ordered: Final = sorted(_iter_usage_unit_increments(logs_to_process), key=_usage_unit_key) return MappingProxyType( { @@ -283,8 +284,16 @@ def _sum_usage_unit_increments( ) -async def _upsert_usage_unit_row( - prisma_client: PrismaClient, key: _UsageUnitKey, increment: _UsageUnitIncrement +class GuardrailUsageDatabase(Protocol): + @property + def litellm_dailyguardrailusageunits(self) -> TableActions[object]: ... + + +async def upsert_usage_unit_row( + prisma_client: PrismaClient, + key: UsageUnitKey, + increment: UsageUnitIncrement, + outer_transaction: GuardrailUsageDatabase | None = None, ) -> None: row: Final[prisma_types.LiteLLM_DailyGuardrailUsageUnitsCreateInput] = { "guardrail_id": key.guardrail_id, @@ -314,7 +323,12 @@ async def _upsert_usage_unit_row( "untracked_units": {"increment": increment.untracked_units}, }, } - await DailyGuardrailUsageUnitsRepository(prisma_client).table.upsert(where=where, data=data) + table: Final = ( + outer_transaction.litellm_dailyguardrailusageunits + if outer_transaction is not None + else DailyGuardrailUsageUnitsRepository(prisma_client).table + ) + await table.upsert(where=where, data=data) async def _upsert_metrics_row(prisma_client: PrismaClient, key: _MetricsKey, agg: Mapping[str, int]) -> None: @@ -363,7 +377,7 @@ async def process_spend_logs_guardrail_usage( ) index_rows_by_key: Final[dict[tuple[str, str], dict[str, object]]] = {} - for payload in logs_to_process: + for payload in (row for row in logs_to_process if row.get("accounting_log_disabled") is not True): request_id = payload.get("request_id") start_time = _parse_payload_start_time(payload) if not isinstance(request_id, str) or not request_id or start_time is None: @@ -416,7 +430,10 @@ async def process_spend_logs_guardrail_usage( {key: agg for key, agg in daily_guardrail.items() if int(agg["requests_evaluated"]) > 0} ) metrics_rows: Final = _merged_metric_rows(pending_metrics, evaluated_metrics) - unit_rows: Final = _merged_unit_rows(pending_units, _sum_usage_unit_increments(logs_to_process)) + unit_rows: Final = _merged_unit_rows( + pending_units, + _sum_usage_unit_increments(tuple(row for row in logs_to_process if "accounting_payload" not in row)), + ) if not metrics_rows and not index_rows and not unit_rows: return @@ -435,7 +452,7 @@ async def process_spend_logs_guardrail_usage( metrics_rows, partial(_upsert_metrics_row, prisma_client), "daily metrics", sleep ) failed_units: Final = await _upsert_rows_with_retry( - unit_rows, partial(_upsert_usage_unit_row, prisma_client), "usage unit", sleep + unit_rows, partial(upsert_usage_unit_row, prisma_client), "usage unit", sleep ) if failed_metrics or failed_units: async with pending.lock: diff --git a/litellm/proxy/hooks/max_budget_per_session_limiter.py b/litellm/proxy/hooks/max_budget_per_session_limiter.py index 002aeb145a5..636345a7ef7 100644 --- a/litellm/proxy/hooks/max_budget_per_session_limiter.py +++ b/litellm/proxy/hooks/max_budget_per_session_limiter.py @@ -26,6 +26,14 @@ from litellm._logging import verbose_proxy_logger from litellm.caching.redis_cache import log_redis_failure from litellm.exceptions import RateLimitType from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.batch_utils import ( + ChargeOnceJob, + charged_poll_cost, + defers_batch_cost, + job_charged_once_marker_key, + job_to_charge_once, +) +from litellm.litellm_core_utils.core_helpers import finite_cost from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.common_utils.proxy_rate_limit_error import ProxyRateLimitError from litellm.proxy.hooks.rate_limiter_utils import resolve_llm_provider_for_rate_limit @@ -44,6 +52,7 @@ _CACHE_AMOUNT_ADAPTER: Final[TypeAdapter[str | bytes | int | float]] = TypeAdapt _OPTIONAL_CACHE_AMOUNT_ADAPTER: Final[TypeAdapter[str | bytes | int | float | None]] = TypeAdapter( str | bytes | int | float | None, config=ConfigDict(strict=True, hide_input_in_errors=True) ) +_CALLBACK_FIELDS: Final = TypeAdapter(dict[str, object]) # Redis Lua script for atomic float increment with TTL. @@ -63,6 +72,30 @@ end return new_val """ +MAX_BUDGET_SESSION_CHARGE_JOB_ONCE_SCRIPT: Final = """ +local spend_key = KEYS[1] +local marker_key = KEYS[2] +local ttl = tonumber(ARGV[3]) + +local polls = redis.call('INCR', marker_key) +redis.call('EXPIRE', marker_key, ttl) +local amount = ARGV[2] +if polls == 1 then + amount = ARGV[1] +end +if tonumber(amount) <= 0 then + return '0' +end + +local existed = redis.call('EXISTS', spend_key) +redis.call('INCRBYFLOAT', spend_key, amount) +if existed == 0 then + redis.call('EXPIRE', spend_key, ttl) +end + +return amount +""" + # Default TTL for session budget counters (1 hour) DEFAULT_MAX_BUDGET_PER_SESSION_TTL: Final = 3600 @@ -87,12 +120,15 @@ class _PROXY_MaxBudgetPerSessionHandler(CustomLogger): ) ) - if self.internal_usage_cache.dual_cache.redis_cache is not None: - self.increment_script = self.internal_usage_cache.dual_cache.redis_cache.async_register_script( - MAX_BUDGET_SESSION_INCREMENT_SCRIPT - ) - else: - self.increment_script = None + redis_cache: Final = self.internal_usage_cache.dual_cache.redis_cache + self.increment_script = ( + redis_cache.async_register_script(MAX_BUDGET_SESSION_INCREMENT_SCRIPT) if redis_cache is not None else None + ) + self.charge_job_once_script = ( + redis_cache.async_register_script(MAX_BUDGET_SESSION_CHARGE_JOB_ONCE_SCRIPT) + if redis_cache is not None + else None + ) @with_service_target("session_budgets") async def async_pre_call_hook( @@ -140,7 +176,7 @@ class _PROXY_MaxBudgetPerSessionHandler(CustomLogger): return None @with_service_target("session_budgets") - async def async_log_success_event(self, kwargs, response_obj, start_time, end_time) -> None: + async def async_log_success_event(self, kwargs, response_obj: object, start_time, end_time) -> None: """ After a successful LLM call, increment the session spend by the response cost. """ @@ -168,15 +204,23 @@ class _PROXY_MaxBudgetPerSessionHandler(CustomLogger): if max_budget is None: return - response_cost: Final = kwargs.get("response_cost") or 0.0 + callback_fields: Final = _CALLBACK_FIELDS.validate_python(kwargs) + response_cost: Final = finite_cost(charged_poll_cost(callback_fields)) or 0.0 if response_cost <= 0: return + if defers_batch_cost(callback_fields, response_obj): + return + cache_key: Final = self._make_cache_key(str(session_id)) - await self._increment_spend(cache_key, float(response_cost)) + job: Final = job_to_charge_once(callback_fields, response_obj, response_cost) + if job is None: + await self._increment_spend(cache_key, response_cost) + else: + await self._charge_job_once(cache_key, job, response_cost) verbose_proxy_logger.debug( - "MaxBudgetPerSessionHandler: incremented session %s spend by %.6f", + "MaxBudgetPerSessionHandler: charged session %s for a call that cost %.6f", session_id, response_cost, ) @@ -221,6 +265,31 @@ class _PROXY_MaxBudgetPerSessionHandler(CustomLogger): def _make_cache_key(self, session_id: str) -> str: return f"{{session_budget:{session_id}}}:spend" + async def _charge_job_once(self, cache_key: str, job: ChargeOnceJob, response_cost: float) -> None: + marker_key: Final = job_charged_once_marker_key(spend_key=cache_key, job=job) + if self.charge_job_once_script is not None: + try: + await self.charge_job_once_script( + keys=[cache_key, marker_key], + args=[str(response_cost), str(job.repeat_poll_cost), self.ttl], + ) + except Exception as e: + log_redis_failure( + verbose_proxy_logger, + logging.WARNING, + "MaxBudgetPerSessionHandler: Redis job charge failed, falling back to in-memory", + e, + ) + else: + return + + polls: Final = await self.internal_usage_cache.dual_cache.in_memory_cache.async_increment( + key=marker_key, value=1, ttl=self.ttl + ) + charge: Final = response_cost if polls == 1 else job.repeat_poll_cost + if charge > 0: + await self._in_memory_increment_spend(cache_key, charge) + @with_service_target("session_budgets") async def _get_current_spend(self, cache_key: str) -> float: """Read current accumulated spend for a session.""" diff --git a/litellm/proxy/hooks/model_max_budget_limiter.py b/litellm/proxy/hooks/model_max_budget_limiter.py index 1c10826124e..889fb9fb373 100644 --- a/litellm/proxy/hooks/model_max_budget_limiter.py +++ b/litellm/proxy/hooks/model_max_budget_limiter.py @@ -19,7 +19,12 @@ from litellm._internal_context import with_service_target from litellm._logging import verbose_proxy_logger from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import Span -from litellm.litellm_core_utils.batch_utils import batch_charged_once_marker_key, batch_id_to_charge_once +from litellm.litellm_core_utils.batch_utils import ( + ChargeOnceJob, + defers_batch_cost, + job_charged_once_marker_key, + job_to_charge_once, +) from litellm.litellm_core_utils.duration_parser import duration_in_seconds from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup from litellm.llms.bedrock.common_utils import get_bedrock_base_model, get_bedrock_cross_region_inference_regions @@ -1208,18 +1213,17 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): ) return - batch_id: Final = batch_id_to_charge_once( - call_type=kwargs.get("call_type"), - response_obj=response_obj, - response_cost=response_cost, - ) + if defers_batch_cost(kwargs, response_obj): + return + + job: Final = job_to_charge_once(kwargs=kwargs, response_obj=response_obj, response_cost=response_cost) for entity_type, entity_id, resolved in resolved_budgets: await self._charge_entity( entity_type=entity_type, entity_id=entity_id, resolved=resolved, response_cost=response_cost, - batch_id=batch_id, + job=job, ) if self.dual_cache.redis_cache is not None: @@ -1236,7 +1240,7 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): entity_id: str | None, resolved: ResolvedModelBudget, response_cost: float, - batch_id: str | None, + job: ChargeOnceJob | None, ) -> None: budget_duration: Final = resolved.budget_config.budget_duration if budget_duration is None: @@ -1247,11 +1251,19 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): budget_model=resolved.budget_model, budget_duration=budget_duration, ) - if batch_id is not None and not await self._claim_batch_charge( + if job is not None and not await self._claim_job_charge( spend_key=spend_key, - batch_id=batch_id, + job=job, ttl_seconds=duration_in_seconds(budget_duration), ): + if job.repeat_poll_cost > 0: + await self._charge_entity( + entity_type=entity_type, + entity_id=entity_id, + resolved=resolved, + response_cost=job.repeat_poll_cost, + job=None, + ) return start_time_key: Final = model_budget_start_time_cache_key( entity_type=entity_type, @@ -1362,8 +1374,8 @@ class _PROXY_VirtualKeyModelMaxBudgetLimiter(RouterBudgetLimiting): spend=response_cost, ) - async def _claim_batch_charge(self, spend_key: str, batch_id: str, ttl_seconds: int) -> bool: - marker_key: Final = batch_charged_once_marker_key(spend_key=spend_key, batch_id=batch_id) + async def _claim_job_charge(self, spend_key: str, job: ChargeOnceJob, ttl_seconds: int) -> bool: + marker_key: Final = job_charged_once_marker_key(spend_key=spend_key, job=job) polls: Final = await self.dual_cache.async_increment_cache( key=marker_key, value=1, ttl=ttl_seconds, refresh_ttl=True ) diff --git a/litellm/proxy/hooks/parallel_request_limiter.py b/litellm/proxy/hooks/parallel_request_limiter.py index cd01d15d834..f9e85c31d46 100644 --- a/litellm/proxy/hooks/parallel_request_limiter.py +++ b/litellm/proxy/hooks/parallel_request_limiter.py @@ -13,7 +13,7 @@ from litellm._internal_context import with_service_target from litellm._logging import verbose_proxy_logger from litellm.exceptions import RateLimitType from litellm.integrations.custom_logger import CustomLogger -from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs +from litellm.litellm_core_utils.core_helpers import as_str_mapping, get_parent_otel_span_from_kwargs from litellm.proxy._types import CommonProxyErrors, CurrentItemRateLimit, UserAPIKeyAuth from litellm.proxy.auth.auth_utils import ( get_key_model_rpm_limit, @@ -53,9 +53,16 @@ def _response_total_tokens(kwargs: Mapping[str, object], response_obj: object) - _CONNECTION_SCOPED_CALL_TYPES: Final = frozenset({CallTypes.aresponses_websocket.value}) +def _is_websocket_passthrough_row(kwargs: Mapping[str, object]) -> bool: + passthrough_payload: Final = as_str_mapping(kwargs.get("passthrough_logging_payload")) + return passthrough_payload is not None and passthrough_payload.get("request_method") == "WEBSOCKET" + + def _slots_released(kwargs: Mapping[str, object]) -> int: """A websocket turn callback releases nothing; the socket's slot is released once at disconnect.""" - return 0 if kwargs.get("call_type") in _CONNECTION_SCOPED_CALL_TYPES else 1 + if kwargs.get("call_type") in _CONNECTION_SCOPED_CALL_TYPES or _is_websocket_passthrough_row(kwargs): + return 0 + return 1 class CacheObject(TypedDict): diff --git a/litellm/proxy/hooks/parallel_request_limiter_v3.py b/litellm/proxy/hooks/parallel_request_limiter_v3.py index c83551a815c..5c2f6bab650 100644 --- a/litellm/proxy/hooks/parallel_request_limiter_v3.py +++ b/litellm/proxy/hooks/parallel_request_limiter_v3.py @@ -55,7 +55,6 @@ from litellm.litellm_core_utils.add_retry_fallback_headers import ( ensure_response_additional_headers, response_has_hidden_params, ) -from litellm.litellm_core_utils.audio_utils.utils import estimate_audio_tokens from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.litellm_core_utils.prompt_templates.common_utils import ( get_str_from_messages, @@ -64,7 +63,11 @@ from litellm.litellm_core_utils.prompt_templates.common_utils import ( from litellm.litellm_core_utils.ptu_pricing import is_ptu_cost_attribution_enabled from litellm.litellm_core_utils.ptu_shares import PTUTeamCeiling from litellm.litellm_core_utils.routing_common_utils import resolve_model_group_alias -from litellm.litellm_core_utils.token_counter import estimate_image_tokens, offload_token_count +from litellm.litellm_core_utils.token_counter import ( + estimate_media_block_tokens, + offload_token_count, + split_embedding_input_tokens, +) from litellm.llms.azure.ptu_capacity import normalized_tokens from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.auth.auth_utils import ( @@ -156,6 +159,12 @@ def _resolve_media_models(router: "Router | None", model: str, team_id: str | No return tuple(dict.fromkeys(router.registry().names(model, kind="litellm_base_models", team_id=team_id))) or (model,) +def _media_models( + resolver: Callable[[str, str | None], tuple[str, ...]] | None, model: str, team_id: str | None +) -> tuple[str, ...]: + return resolver(model, team_id) if resolver is not None else (model,) + + def _resolve_media_models_via_proxy_router(model: str, team_id: str | None) -> tuple[str, ...]: from litellm.proxy.proxy_server import llm_router @@ -709,7 +718,7 @@ class RequestRateLimiterStash: A single mutable instance is shared by every context forked from the request task (the SDK call, streaming generators, and the logging worker's captured context all see the same object), which is what makes the - ``reservation_released`` flag and ``parallel_slot`` clearing effective + released flags and ``parallel_slot`` clearing effective across sibling callbacks: the first release wins, later callbacks observe the cleared state. @@ -746,9 +755,32 @@ class RequestRateLimiterStash: batch_enqueued_reservation: BatchEnqueuedTokenReservation | None = None batch_tpd_refund_ops: tuple[ReservationAwareIncrementOperation, ...] = () reservation_released: bool = False + io_reservation_released: bool = False tpm_limited_tags: frozenset[str] = field(default_factory=frozenset) socket_agent_windows: tuple[RateLimitDescriptor, ...] = () + def clear_reserved_tokens(self) -> None: + self.reserved_tokens = 0 + self.ptu_reserved_tokens = 0 + self.itpm_reserved_tokens = 0 + self.otpm_reserved_tokens = 0 + + def mark_reservation_released(self) -> None: + self.reservation_released = True + self.io_reservation_released = True + + def discard_released_tpm_reservation(self) -> None: + if self.reservation_released: + self.reserved_tokens = 0 + self.ptu_reserved_tokens = 0 + self.reservation_released = False + + def discard_released_io_reservation(self) -> None: + if self.io_reservation_released: + self.itpm_reserved_tokens = 0 + self.otpm_reserved_tokens = 0 + self.io_reservation_released = False + @dataclass(frozen=True, slots=True) class CounterRefund: @@ -1355,20 +1387,28 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): ) media_source: Final = messages if messages is not None else original_input + is_embedding_call: Final = call_type in EMBEDDING_API_CALL_TYPES projected, media = ( split_media_for_tpm(media_source) if include_media and (isinstance(messages, list) or call_type in RESPONSES_API_CALL_TYPES) else (original_input, ()) ) - input_text: Final = projected if call_type in RESPONSES_API_CALL_TYPES else original_input fallback_model: Final = request_model if isinstance(request_model, str) else None resolved_models: Final = ( - media_model_resolver(fallback_model or "", team_id) - if media and media_model_resolver is not None - else (fallback_model or "",) + _media_models(media_model_resolver, fallback_model or "", team_id) if media else (fallback_model or "",) ) - media_tokens: Final = sum( - self._estimate_media_block_tokens(block, resolved_models, fallback_model) for block in media + embedding_text, embedding_media_tokens = ( + split_embedding_input_tokens( + original_input, + lambda: _media_models(media_model_resolver, fallback_model or "", team_id), + fallback_model, + ) + if include_media and is_embedding_call + else (original_input, 0) + ) + input_text: Final = projected if call_type in RESPONSES_API_CALL_TYPES else embedding_text + media_tokens: Final = embedding_media_tokens + sum( + estimate_media_block_tokens(block, resolved_models, fallback_model) for block in media ) total_chars: Final = ( @@ -1413,24 +1453,6 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): return estimated_input_tokens, max_tokens_estimate * self.get_output_candidate_count(data, call_type) - @staticmethod - def _estimate_media_block_tokens( - block: Mapping[str, object], models: tuple[str, ...], fallback_model: str | None - ) -> int: - if block.get("type") == "input_audio": - audio: Final = _callback_kwargs_mapping(block.get("input_audio")) - data: Final = audio.get("data") - return estimate_audio_tokens(data if isinstance(data, str) else None, models, fallback_model=fallback_model) - image: Final = _callback_kwargs_mapping(block.get("image_url")) - url: Final = image.get("url") - detail: Final = image.get("detail") - return estimate_image_tokens( - models, - url if isinstance(url, str) else "", - detail if isinstance(detail, str) else "auto", - fallback_model=fallback_model, - ) - def _is_redis_cluster(self) -> bool: """ Check if the dual cache is using Redis cluster. @@ -4075,12 +4097,20 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): None if is_responses_request else self._translate_google_genai_native_request(data, call_type) ) is_embedding_request: Final = self._is_embedding_request(data, call_type) - embedding_text: Final = data.get("input") if is_embedding_request else None + request: Final = as_str_mapping(data) + raw_embedding_input: Final = request.get("input") if is_embedding_request and request is not None else None pretokenized_input_tokens: Final = ( - self._count_pretokenized_embedding_input(embedding_text) if is_embedding_request else None + self._count_pretokenized_embedding_input(raw_embedding_input) if is_embedding_request else None ) if pretokenized_input_tokens is not None: return pretokenized_input_tokens + embedding_text, embedding_media_tokens = ( + split_embedding_input_tokens( + raw_embedding_input, lambda: self._media_model_resolver(model or "", team_id), model + ) + if is_embedding_request + else (None, 0) + ) prompt: Final = data.get("prompt") fallback_text: Final = prompt if prompt is not None else data.get("input") @@ -4130,12 +4160,16 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): for tokenizer_model in (self._counted_models_resolver(model, team_id) if model else ("",)) ), ) - return estimate + audio_token_estimate + return estimate + audio_token_estimate + embedding_media_tokens except Exception: # noqa: BLE001 # tokenizer failures degrade to the cheap estimate if call_type in RERANK_API_CALL_TYPES and isinstance(selected_text, str): return max(0, len(selected_text) // DEFAULT_CHARS_PER_TOKEN) estimated_input_tokens, _ = self._estimate_input_and_output_tokens( - data=data, call_type=call_type, include_media=False + data=data, + call_type=call_type, + include_media=is_embedding_request, + team_id=team_id, + media_model_resolver=self._media_model_resolver, ) return estimated_input_tokens + audio_token_estimate @@ -4238,6 +4272,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): requested_model=requested_model, ) + stash.discard_released_io_reservation() if itpm_reserved > 0: itpm_scopes: Final = tuple( (d["key"], d["value"]) for d in io_token_descriptors if d["key"] == PROJECT_ITPM_DESCRIPTOR_KEY @@ -4597,6 +4632,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): # incremented so post-call reconciliation only applies # the (actual - reserved) delta to those — unreserved # scopes get charged the full actual usage instead. + stash.discard_released_tpm_reservation() stash.reserved_tokens = estimated_tokens stash.ptu_reserved_tokens = ptu_estimated_tokens stash.ptu_reserved_window_identities = frozenset( @@ -5140,7 +5176,12 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): self._response_usage(response_obj) ) or self._aggregate_only_total_tokens(self._response_usage(kwargs.get("combined_usage_object"))) - if not response_usage[2] and not combined_usage[2] and aggregate_total <= 0 and not stash.reservation_released: + if ( + not response_usage[2] + and not combined_usage[2] + and aggregate_total <= 0 + and not stash.io_reservation_released + ): return () resolved_usage: Final = ( response_usage @@ -5153,25 +5194,25 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): ) billable_input, completion_tokens, _ = resolved_usage - if stash.reservation_released or ( + if stash.io_reservation_released or ( not stash.itpm_reserved_window_identities and not stash.otpm_reserved_window_identities ): return self._build_reservation_aware_tpm_ops( targets=tuple(stash.itpm_reserved_scopes), - reserved_scopes=frozenset() if stash.reservation_released else stash.itpm_reserved_scopes, + reserved_scopes=frozenset() if stash.io_reservation_released else stash.itpm_reserved_scopes, actual_tokens=billable_input, - reserved_tokens=0 if stash.reservation_released else itpm_reserved, + reserved_tokens=0 if stash.io_reservation_released else itpm_reserved, ) + self._build_reservation_aware_tpm_ops( targets=tuple(stash.otpm_reserved_scopes), - reserved_scopes=frozenset() if stash.reservation_released else stash.otpm_reserved_scopes, + reserved_scopes=frozenset() if stash.io_reservation_released else stash.otpm_reserved_scopes, actual_tokens=completion_tokens, - reserved_tokens=0 if stash.reservation_released else otpm_reserved, + reserved_tokens=0 if stash.io_reservation_released else otpm_reserved, ) itpm_ops: Final[Sequence[ReservationAwareIncrementOperation]] = ( self._build_project_reservation_ops( targets=tuple(stash.itpm_reserved_scopes), - reserved_scopes=frozenset() if stash.reservation_released else stash.itpm_reserved_scopes, + reserved_scopes=frozenset() if stash.io_reservation_released else stash.itpm_reserved_scopes, actual_tokens=billable_input, reserved_tokens=itpm_reserved, reservation_window_identities=stash.itpm_reserved_window_identities, @@ -5182,7 +5223,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): otpm_ops: Final[Sequence[ReservationAwareIncrementOperation]] = ( self._build_project_reservation_ops( targets=tuple(stash.otpm_reserved_scopes), - reserved_scopes=frozenset() if stash.reservation_released else stash.otpm_reserved_scopes, + reserved_scopes=frozenset() if stash.io_reservation_released else stash.otpm_reserved_scopes, actual_tokens=completion_tokens, reserved_tokens=otpm_reserved, reservation_window_identities=stash.otpm_reserved_window_identities, @@ -5402,7 +5443,8 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): total_tokens = self._aggregate_only_total_tokens(usage=_usage) stash: Final = get_request_stash_for_call(_call_id_from_callback_kwargs(kwargs)) - reserved_tokens: Final = stash.reserved_tokens if stash is not None else 0 + open_reservation: Final = stash if stash is not None and not stash.reservation_released else None + reserved_tokens: Final = open_reservation.reserved_tokens if open_reservation is not None else 0 reserved_model: Final = stash.reserved_model if stash is not None else None reserved_scopes: Final[frozenset[tuple[str, str]]] = stash.reserved_scopes if stash is not None else frozenset() # Reconciliation must target the same model-scoped counter that the @@ -5464,7 +5506,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): reconcile_model=reconcile_model, reserved_scopes=reserved_scopes, reserved_ceiling=stash.ptu_ceiling if stash is not None else None, - reserved_tokens=stash.ptu_reserved_tokens if stash is not None else 0, + reserved_tokens=open_reservation.ptu_reserved_tokens if open_reservation is not None else 0, reserved_windows=stash.ptu_reserved_window_identities if stash is not None else frozenset(), total_tokens=0 if ptu_skips_socket_usage else total_tokens, ) @@ -5561,18 +5603,18 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): else None, ) - await self._apply_usage_operations( - self._build_success_event_pipeline_operations( - kwargs=kwargs, - response_obj=response_obj, - rate_limit_type=rate_limit_type, - ), - litellm_parent_otel_span, + usage_operations: Final = self._build_success_event_pipeline_operations( + kwargs=kwargs, + response_obj=response_obj, + rate_limit_type=rate_limit_type, ) io_token_operations: Final = self._build_io_token_reservation_ops( kwargs=kwargs, response_obj=response_obj, ) + if stash is not None: + stash.clear_reserved_tokens() + await self._apply_usage_operations(usage_operations, litellm_parent_otel_span) if io_token_operations: if isinstance(io_token_operations, list): await self.async_increment_tokens_with_ttl_preservation( @@ -5733,10 +5775,11 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): # already released it (proxy-level rejection that also bubbles up # here as an LLM-error callback). max_parallel_requests is its # own counter and is always decremented per call. - reserved_tokens, itpm_reserved, otpm_reserved = ( - (0, 0, 0) - if stash is None or stash.reservation_released - else (stash.reserved_tokens, stash.itpm_reserved_tokens, stash.otpm_reserved_tokens) + reserved_tokens: Final = 0 if stash is None or stash.reservation_released else stash.reserved_tokens + itpm_reserved, otpm_reserved = ( + (0, 0) + if stash is None or stash.io_reservation_released + else (stash.itpm_reserved_tokens, stash.otpm_reserved_tokens) ) tpm_actual, itpm_actual, otpm_actual = self._recovered_partial_usage_tokens(failed_call) @@ -5806,6 +5849,8 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): else () ) + if stash is not None and (reserved_tokens > 0 or itpm_reserved > 0 or otpm_reserved > 0): + stash.mark_reservation_released() if pipeline_operations: await self.internal_usage_cache.dual_cache.async_increment_cache_pipeline_post_call( pipeline_operations, parent_otel_span=litellm_parent_otel_span @@ -5820,8 +5865,6 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): pipeline_operations=project_operations, parent_otel_span=litellm_parent_otel_span, ) - if stash is not None and (reserved_tokens > 0 or itpm_reserved > 0 or otpm_reserved > 0): - stash.reservation_released = True if stash is None and tpm_actual > 0 and _is_socket_turn(failed_call): await self._apply_usage_operations( self._build_success_event_pipeline_operations( @@ -5927,7 +5970,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): Idempotent: the slot release clears the stashed acquisition (and slot removal is a no-op ZREM on a second run), and the TPM/ITPM/OTPM - refund is guarded by the stash's ``reservation_released`` flag — if + refund is guarded by the stash's two released flags — if both this hook and async_log_failure_event end up running in the same flow, only the first release/refund applies. A mid-stream failure relayed here with recovered partial usage settles the reservation at @@ -5953,11 +5996,9 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): ) stash.batch_tpd_refund_ops = () - if stash.reservation_released: - return - reserved_tokens: Final = stash.reserved_tokens - itpm_reserved: Final = stash.itpm_reserved_tokens - otpm_reserved: Final = stash.otpm_reserved_tokens + reserved_tokens: Final = 0 if stash.reservation_released else stash.reserved_tokens + itpm_reserved: Final = 0 if stash.io_reservation_released else stash.itpm_reserved_tokens + otpm_reserved: Final = 0 if stash.io_reservation_released else stash.otpm_reserved_tokens if reserved_tokens <= 0 and itpm_reserved <= 0 and otpm_reserved <= 0: return tpm_actual, itpm_actual, otpm_actual = self._recovered_partial_usage_tokens(request_data) @@ -6024,6 +6065,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): itpm_reserved, otpm_reserved, ) + stash.mark_reservation_released() if combined_ops: await self.internal_usage_cache.dual_cache.async_increment_cache_pipeline( increment_list=list(combined_ops), @@ -6040,7 +6082,6 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): pipeline_operations=project_ops, parent_otel_span=user_api_key_dict.parent_otel_span, ) - stash.reservation_released = True except Exception as e: verbose_proxy_logger.exception("Error releasing TPM reservation on post-call failure: %s", e) return diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py index 980f0a5d410..ff67f2cb7c6 100644 --- a/litellm/proxy/hooks/proxy_track_cost_callback.py +++ b/litellm/proxy/hooks/proxy_track_cost_callback.py @@ -4,17 +4,19 @@ from collections.abc import Callable, Generator, Mapping, Sequence from contextlib import contextmanager from contextvars import ContextVar from datetime import datetime, timezone +from functools import partial from types import MappingProxyType from typing import TYPE_CHECKING, Final, Protocol, TypeAlias, cast from pydantic import TypeAdapter, ValidationError +from typing_extensions import NotRequired, ReadOnly, TypedDict import litellm from litellm._logging import verbose_proxy_logger -from litellm.batches.batch_utils import batch_cost_is_final from litellm.caching.redis_batch import flush_post_call_redis_batches from litellm.constants import BACKGROUND_INTERACTION_COST_POLLING_ENABLED, BILLED_RETRY_ATTEMPT_METADATA_KEY from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.batch_utils import defers_batch_cost, repeat_poll_cost from litellm.litellm_core_utils.core_helpers import ( budget_reservation_from_metadata, finite_cost, @@ -24,7 +26,6 @@ from litellm.litellm_core_utils.core_helpers import ( ) from litellm.litellm_core_utils.litellm_logging import ( StandardLoggingPayloadSetup, - UsageCaptureObservation, UsageObservation, ) from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import guardrail_information_cost @@ -38,6 +39,7 @@ from litellm.proxy.auth.auth_checks import ( from litellm.proxy.auth.route_checks import RouteChecks from litellm.proxy.db.db_lookup_gate import DBLookupDeadlineExceeded from litellm.proxy.db.db_spend_update_writer import ( + ACCOUNTING_LEDGER_KWARG, DBSpendUpdateWriter, debitable_model_access_groups, get_llm_router, @@ -64,10 +66,9 @@ from litellm.proxy.spend_tracking.spend_tracking_utils import ( # noqa: F401 # _sanitize_error_information_for_spend_logs, # pyright: ignore[reportPrivateUsage,reportUnusedImport] # backwards-compatible package export deployment_params_provider, get_request_model_access_groups, - sanitize_error_information_for_spend_logs, + sanitize_error_information_for_spend_logs, # pyright: ignore[reportUnusedImport] # backwards-compatible package export should_store_prompts_and_responses_in_spend_logs, ) -from litellm.proxy.spend_tracking.usage_capture import CapturedUsage, capture_callback, captured_callback_kwargs from litellm.proxy.utils import ( REJECTED_BEFORE_REQUEST_SETUP, REJECTED_BEFORE_REQUEST_SETUP_KEY, @@ -77,9 +78,7 @@ from litellm.proxy.utils import ( from litellm.types.router import Deployment from litellm.types.utils import ( CallTypes, - LiteLLMBatch, StandardLoggingPayload, - StandardLoggingPayloadErrorInformation, ) from litellm.utils import get_end_user_id_for_cost_tracking @@ -226,6 +225,32 @@ def _guardrail_info_lifted_from_litellm_metadata( return {"standard_logging_guardrail_information": guardrail_info} +def _failure_row_guardrail_information(request_data: Mapping[str, object]) -> object: + metadata: Final = _str_keyed_fields(request_data.get("metadata")) + lifted: Final = _guardrail_info_lifted_from_litellm_metadata( + _str_keyed_fields(request_data.get("litellm_metadata")), + guardrail_info_already_set="standard_logging_guardrail_information" in metadata, + ) + return {**metadata, **lifted}.get("standard_logging_guardrail_information") + + +def failure_row_response_cost(request_data: Mapping[str, object]) -> float: + stashed_cost: Final = request_data.get("response_cost") + recovered_stream_cost: Final = ( + max(float(stashed_cost), 0.0) + if isinstance(request_data.get("combined_usage_object"), litellm.Usage) + and isinstance(stashed_cost, (int, float)) + else 0.0 + ) + finalized_failure: Final = _str_keyed_fields(request_data.get("standard_logging_object")) + finalized_amount: Final = finalized_failure.get("response_cost") + return ( + float(finalized_amount) + if finalized_failure.get("cost_finalized") is True and isinstance(finalized_amount, (int, float)) + else recovered_stream_cost + guardrail_information_cost(_failure_row_guardrail_information(request_data)) + ) + + def _redaction_opt_in_lifted_from_litellm_metadata( litellm_metadata: ObjectMapping, *, caller_set_headers: bool ) -> ObjectMapping: @@ -350,26 +375,13 @@ def _attempt_spend_row_kwargs( "combined_usage_object": attempt.usage, "response_cost": attempt.response_cost, "_accounting_usage_observed": UsageObservation.ESTIMATED, - "_accounting_usage_snapshot": UsageCaptureObservation.from_usage( - attempt.usage, UsageObservation.ESTIMATED, attempt.response_cost - ), - "_accounting_prior_captures": (), } row.pop("billed_failed_attempts", None) - row.pop("_accounting_capture", None) call_id: Final = request_data.get("litellm_call_id") or litellm_params.get("litellm_call_id") if isinstance(call_id, str): row["litellm_call_id"] = f"{call_id}{suffix}" row["parent_request_id"] = call_id metadata["parent_request_id"] = call_id - captured_attempts: Final = request_data.get("_accounting_billed_attempts") - if isinstance(captured_attempts, tuple): - for captured in TypeAdapter(tuple[object, ...]).validate_python(captured_attempts): - if ( - isinstance(captured, CapturedUsage) - and captured.payload["litellm_call_id"] == row["litellm_call_id"] - ): - row["_accounting_capture"] = captured standard_logging_object: Final = request_data.get("standard_logging_object") if isinstance(standard_logging_object, dict): payload: Final = cast("Mapping[str, object]", standard_logging_object) # cast-ok: StandardLoggingPayload dict @@ -405,7 +417,7 @@ class _ProxyDBLogger(CustomLogger): async def async_log_success_event( self, kwargs: ObjectMapping, response_obj: object, start_time: datetime, end_time: datetime ) -> None: - if self.spend_event_producer is None or not is_offloadable_success(response_obj): + if self.spend_event_producer is None or not is_offloadable_success(response_obj, kwargs.get("call_type")): await self._PROXY_track_cost_callback(dict(kwargs), response_obj, start_time, end_time) return event: Final = build_spend_event( @@ -455,9 +467,6 @@ class _ProxyDBLogger(CustomLogger): "Failed to invalidate budget reservation counters after failure release failed" ) - capture_metadata: Final = await self._try_capture_failure_usage( - request_data, original_exception, user_api_key_dict - ) if completed_cost and tracking_disabled: return @@ -492,19 +501,10 @@ class _ProxyDBLogger(CustomLogger): # ``.get("traceback")`` / truthy checks, and the TypedDict marks # the field as optional, so omitting is type-safe. _error_information.pop("traceback", None) - # Strip echoed request input + apply DB-size cap before storing in - # the spend-log metadata column (LIT-2992). Result is never None - # here because the input above is constructed non-None. - _error_information = cast( - StandardLoggingPayloadErrorInformation, - sanitize_error_information_for_spend_logs(_error_information, original_exception=original_exception), - ) _metadata["error_information"] = _error_information - _metadata = ( # rebind-ok: enriched identity is shared with the earlier immutable capture - {**_metadata, **capture_metadata} - if capture_metadata is not None - else await ProxyDBLogger._enrich_failure_metadata_unless_db_stalled( + _metadata = ( # rebind-ok: enrich identity before building failure spend rows + await ProxyDBLogger._enrich_failure_metadata_unless_db_stalled( metadata=_metadata, original_exception=original_exception ) ) @@ -585,19 +585,7 @@ class _ProxyDBLogger(CustomLogger): # recovered cost onto request_data (the usage rides along in # ``combined_usage_object`` for the token columns), so attribute the # real partial spend to this failure row instead of zero. - recovered_stream_cost: Final = ( - max(float(request_data.get("response_cost") or 0.0), 0.0) - if isinstance(request_data.get("combined_usage_object"), litellm.Usage) - else 0.0 - ) - finalized_failure: Final = _str_keyed_fields(request_data.get("standard_logging_object")) - finalized_amount: Final = finalized_failure.get("response_cost") - recovered_response_cost: Final = ( - float(finalized_amount) - if finalized_failure.get("cost_finalized") is True and isinstance(finalized_amount, (int, float)) - else recovered_stream_cost - + guardrail_information_cost(existing_metadata.get("standard_logging_guardrail_information")) - ) + recovered_response_cost: Final = failure_row_response_cost(request_data) failure_snapshot_with_late_guardrails: Final = _failure_snapshot_with_guardrails_recorded_after_it( request_data.get("standard_logging_object"), @@ -623,106 +611,6 @@ class _ProxyDBLogger(CustomLogger): ), ) - async def _failure_capture_metadata( - self, request_data: Mapping[str, object], exception: Exception, auth: UserAPIKeyAuth - ) -> Mapping[str, object] | None: - from litellm.proxy.proxy_server import usage_capture - - if usage_capture.meter is None: - return None - captured_identity: Final = ( - _batch_accounting_for(request_data.get("litellm_call_id")) is not None - and request_data.get(REJECTED_BEFORE_REQUEST_SETUP_KEY) is not REJECTED_BEFORE_REQUEST_SETUP - ) - current_identity: Final = { - **LiteLLMProxyRequestSetup.get_sanitized_user_information_from_key(user_api_key_dict=auth), - "user_api_key": LiteLLMProxyRequestSetup.get_logged_api_key(auth), - } - metadata: Final = ( - { - **dict.fromkeys(current_identity), - **{ - key: value - for key, value in _REQUEST_DATA.validate_python( - get_litellm_metadata_from_kwargs(dict(request_data)) - ).items() - if key in current_identity or key == "tags" - }, - } - if captured_identity - else current_identity - ) - return await self._enrich_failure_metadata_unless_db_stalled( - metadata=metadata, original_exception=exception, resolve_missing_key_identity=not captured_identity - ) - - async def _try_capture_failure_usage( - self, - request_data: dict[str, object], # mutable-ok: receipt handoff shared with the legacy writer - original_exception: Exception, - auth: UserAPIKeyAuth, - ) -> Mapping[str, object] | None: - try: - metadata: Final = await self._failure_capture_metadata(request_data, original_exception, auth) - self._capture_failure_usage(request_data, original_exception, auth, metadata) - except Exception: # noqa: BLE001 # capture failure must not suppress legacy billing or reservation release - verbose_proxy_logger.exception("Usage capture failed on the request failure path") - return None - return metadata - - def _capture_failure_usage( - self, - request_data: dict[str, object], # mutable-ok: receipt handoff shared with the legacy writer - original_exception: Exception, - auth: UserAPIKeyAuth, - metadata: Mapping[str, object] | None = None, - ) -> None: - from litellm.litellm_core_utils.litellm_logging import Logging - from litellm.proxy.db.exception_handler import exception_chain - from litellm.proxy.proxy_server import usage_capture - from litellm.proxy.spend_tracking.usage_capture import UsageAcknowledgementError - - if any(isinstance(error, UsageAcknowledgementError) for error in exception_chain(original_exception)): - return - usage_meter: Final = usage_capture.meter - - if usage_meter is None: - return - logging_obj: Final = request_data.get("litellm_logging_obj") - details: Final[Mapping[str, object]] = ( - _str_keyed_fields(logging_obj.model_call_details) if isinstance(logging_obj, Logging) else {} - ) - params: Final = _str_keyed_fields(request_data.get("litellm_params") or details.get("litellm_params")) - failure_data: Final = { - **details, - **request_data, - "litellm_params": { - **params, - "metadata": { - **_str_keyed_fields(params.get("metadata")), - **( - metadata - if metadata is not None - else { - **LiteLLMProxyRequestSetup.get_sanitized_user_information_from_key(user_api_key_dict=auth), - "user_api_key": LiteLLMProxyRequestSetup.get_logged_api_key(auth), - } - ), - "status": "failure", - }, - }, - } - start: Final = logging_obj.start_time if isinstance(logging_obj, Logging) else request_data.get("start_time") - if not isinstance(start, datetime): - return - end: Final = datetime.now(timezone.utc) - captured: Final = tuple( - capture_callback(usage_meter, row, original_exception, start, end) - for _, row in _failure_spend_rows(failure_data, 0.0, None, self._deployment_lookup) - ) - request_data["_accounting_capture"] = captured[0] # rebind-ok: share one receipt with the legacy writer - request_data["_accounting_billed_attempts"] = captured[1:] # rebind-ok: share attempt receipts - async def _write_failure_spend_rows( self, user_api_key_dict: UserAPIKeyAuth, @@ -771,6 +659,7 @@ class _ProxyDBLogger(CustomLogger): token: Final = LiteLLMProxyRequestSetup.get_logged_api_key(user_api_key_dict) end_user_id: Final = None if litellm.disable_end_user_cost_tracking else user_api_key_dict.end_user_id + accounting_rows: Final = tuple((cost, dict(row)) for cost, row in spend_rows) charged: Final = [ await self._spend_writer().update_database( token=token, @@ -778,17 +667,17 @@ class _ProxyDBLogger(CustomLogger): user_id=user_api_key_dict.user_id, end_user_id=end_user_id, team_id=user_api_key_dict.team_id, - kwargs=dict(row_kwargs), + kwargs=row_kwargs, completion_response=original_exception, start_time=start_time, end_time=datetime.now(), org_id=user_api_key_dict.org_id, project_id=user_api_key_dict.project_id, ) - for row_cost, row_kwargs in spend_rows + for row_cost, row_kwargs in accounting_rows ] counted_rows: Final = tuple( - row for row, row_charged in zip(spend_rows, charged, strict=True) if row_charged and row[0] > 0 + row for row, row_charged in zip(accounting_rows, charged, strict=True) if row_charged and row[0] > 0 ) if counted_rows and not ProxyUpdateSpend.disable_spend_updates(): await self._increment_failure_spend_counters( @@ -867,6 +756,7 @@ class _ProxyDBLogger(CustomLogger): router=get_llm_router(), ), project_id=user_api_key_dict.project_id, + **_ledger_counter_options(row_kwargs.get(ACCOUNTING_LEDGER_KWARG)), ) except Exception: # noqa: BLE001 # one row's counter failure must not keep the other rows' counters from landing verbose_proxy_logger.exception("Failed to raise spend counters for a failure spend row") @@ -908,20 +798,11 @@ class _ProxyDBLogger(CustomLogger): resolve_missing_key_identity=str(kwargs.get("call_type")) not in _CAPTURED_IDENTITY_CALL_TYPES, ) _write_spend_metadata_to_kwargs(kwargs=kwargs, metadata=metadata) - kwargs.update(await captured_callback_kwargs(kwargs, completion_response, start_time, end_time)) budget_reservation: Final = _get_budget_reservation_from_metadata(metadata=metadata) if accounting is not None and (budget_reservation is not None or litellm.apply_search_free_tier): accounting.write_started = True - if ( - isinstance(completion_response, LiteLLMBatch) - and kwargs.get("call_type") == CallTypes.aretrieve_batch.value - and not batch_cost_is_final(completion_response) - ): - verbose_proxy_logger.debug( - "Cost tracking deferred for batch %s still in status %s", - completion_response.id, - completion_response.status, - ) + if defers_batch_cost(kwargs, completion_response): + verbose_proxy_logger.debug("Cost tracking deferred for a batch whose cost is not final yet") await _release_budget_reservation(budget_reservation=budget_reservation) return user_id: Final = cast(str | None, metadata.get("user_api_key_user_id", None)) @@ -983,25 +864,28 @@ class _ProxyDBLogger(CustomLogger): agent_id=metadata.get("billing_agent_id") or metadata.get("agent_id"), ): ## UPDATE DATABASE - charged: Final = await _update_database_and_spend_counters( - proxy_logging_obj=proxy_logging_obj, - increment_spend_counters=increment_spend_counters, - user_api_key=user_api_key, - user_id=user_id, - end_user_id=end_user_id, - team_id=team_id, - org_id=org_id, + charged_cost: Final = await _charge_request_cost( + partial( + _update_database_and_spend_counters, + proxy_logging_obj=proxy_logging_obj, + increment_spend_counters=increment_spend_counters, + user_api_key=user_api_key, + user_id=user_id, + end_user_id=end_user_id, + team_id=team_id, + org_id=org_id, + completion_response=completion_response, + start_time=start_time, + end_time=end_time, + request_tags=tags, + model_access_groups=model_access_groups, + project_id=project_id, + ), kwargs=kwargs, - completion_response=completion_response, - start_time=start_time, - end_time=end_time, response_cost=response_cost, budget_reservation=budget_reservation, - request_tags=tags, - model_access_groups=model_access_groups, - project_id=project_id, ) - if not charged: + if charged_cost is None: return # update cache (fire-and-forget for backward compat: @@ -1011,7 +895,7 @@ class _ProxyDBLogger(CustomLogger): token=user_api_key, user_id=user_id, end_user_id=end_user_id, - response_cost=response_cost, + response_cost=charged_cost, team_id=team_id, parent_otel_span=parent_otel_span, tags=tags, @@ -1022,7 +906,7 @@ class _ProxyDBLogger(CustomLogger): token=user_api_key, key_alias=key_alias, end_user_id=end_user_id, - response_cost=response_cost, + response_cost=charged_cost, max_budget=end_user_max_budget, ) elif budget_reservation is not None: @@ -1316,6 +1200,58 @@ def _get_request_tags_for_cost_tracking( return None +class _LedgerCounterOptions(TypedDict): + windows_from_ledger: ReadOnly[NotRequired[bool]] + + +def _ledger_counter_options(ledger: object) -> _LedgerCounterOptions: + return {"windows_from_ledger": True} if ledger is True else {} + + +class _ChargeSpend(Protocol): + async def __call__( + self, + *, + kwargs: dict[str, object], # mutable-ok: update_database takes the logging kwargs dict itself + response_cost: float, + budget_reservation: dict[str, object] | None, # mutable-ok: reconcile stamps the shared reservation dict + ) -> bool: ... + + +async def _charge_request_cost( + charge_spend: _ChargeSpend, + kwargs: dict[str, object], # mutable-ok: the first charge passes the caller's logging kwargs dict on unchanged + response_cost: float, + budget_reservation: dict[str, object] | None, # mutable-ok: reconcile stamps the shared reservation dict +) -> float | None: + """What the request charged, since a poll of a job an earlier poll charged still pays for its own guardrails.""" + if await charge_spend(kwargs=kwargs, response_cost=response_cost, budget_reservation=budget_reservation): + return response_cost + standard_logging_payload: Final = kwargs.get("standard_logging_object") + cost_after_job: Final = repeat_poll_cost(kwargs.get("call_type"), response_cost, standard_logging_payload) + if cost_after_job <= 0: + return None + charged: Final = await charge_spend( + kwargs={ + **kwargs, + "response_cost": cost_after_job, + **( + { + "standard_logging_object": { + **_OBJECT_MAPPING.validate_python(standard_logging_payload), + "response_cost": cost_after_job, + } + } + if isinstance(standard_logging_payload, Mapping) + else {} + ), + }, + response_cost=cost_after_job, + budget_reservation=None, + ) + return cost_after_job if charged else None + + class _IncrementSpendCounters(Protocol): """The ``increment_spend_counters`` coroutine :func:`_update_database_and_spend_counters` awaits.""" @@ -1332,6 +1268,7 @@ class _IncrementSpendCounters(Protocol): request_started_at: datetime | None = None, model_access_groups: Sequence[str] | None = None, project_id: str | None = None, + windows_from_ledger: bool = False, ) -> None: ... @@ -1469,6 +1406,7 @@ async def _update_database_and_spend_counters_in_batch( request_started_at=start_time, model_access_groups=model_access_groups, project_id=project_id, + **_ledger_counter_options(_BATCH_CALLBACK_FIELDS.validate_python(kwargs).get(ACCOUNTING_LEDGER_KWARG)), ) except Exception: if budget_reservation is not None: diff --git a/litellm/proxy/hooks/responses_id_security.py b/litellm/proxy/hooks/responses_id_security.py index 771d68a0ea0..0269a784445 100644 --- a/litellm/proxy/hooks/responses_id_security.py +++ b/litellm/proxy/hooks/responses_id_security.py @@ -7,23 +7,33 @@ instead of writing immediately on each request. from collections.abc import AsyncGenerator, Callable, Mapping from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final, cast +from typing import TYPE_CHECKING, Any, Final, TypeVar from fastapi import HTTPException from pydantic import TypeAdapter, ValidationError from litellm._logging import verbose_proxy_logger from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.proxy._types import LitellmUserRoles from litellm.proxy.common_utils.encrypt_decrypt_utils import ( decrypt_value_helper, encrypt_value_helper, ) +from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.types.llms.openai import ( BaseLiteLLMOpenAIResponseObject, ResponsesAPIResponse, ) -from litellm.types.utils import ADDRESSED_RESPONSE_ID_FIELD, CallTypesLiteral, LLMResponseTypes, SpecialEnums +from litellm.types.responses.main import DeleteResponseResult +from litellm.types.utils import ( + ADDRESSED_COMPARISON_RESPONSE_ID_FIELD, + ADDRESSED_RESPONSE_ID_FIELD, + CallTypesLiteral, + LLMResponseTypes, + SpecialEnums, +) if TYPE_CHECKING: from litellm.caching.caching import DualCache @@ -67,6 +77,9 @@ def _proxy_signing_key() -> str | None: _RESPONSE_PAYLOAD_ADAPTER: Final = TypeAdapter(Mapping[str, object]) +_REQUEST_DATA_ADAPTER: Final = TypeAdapter(dict[str, object]) +_ResponseObjectT = TypeVar("_ResponseObjectT", bound=BaseLiteLLMOpenAIResponseObject) +_AddressedResultT = TypeVar("_AddressedResultT", bound=ResponsesAPIResponse | DeleteResponseResult) def _response_payload(response_obj: object) -> Mapping[str, object] | None: @@ -77,9 +90,9 @@ def _response_payload(response_obj: object) -> Mapping[str, object] | None: def _rewrite_advertised_id( - event: BaseLiteLLMOpenAIResponseObject, + event: _ResponseObjectT, rewrite: Callable[[str], str], -) -> BaseLiteLLMOpenAIResponseObject: +) -> _ResponseObjectT: event_id: Final = getattr(event, "id", None) if isinstance(event_id, str) and event_id.startswith("resp_"): setattr(event, "id", rewrite(event_id)) @@ -116,6 +129,35 @@ def _streams_response_ids(request_route: str | None) -> bool: return canonical in _RESPONSES_API_ROUTES or (parent in _RESPONSES_API_ROUTES and response_id != "") +_NO_HELD_IDS: Final[Mapping[str, str]] = MappingProxyType({}) + + +def _upstream_response_id(response_id: str) -> str: + return ResponsesAPIRequestUtils.decode_previous_response_id_to_original_previous_response_id(response_id) + + +def _names_the_same_response(response_id: str | None, original_response_id: str) -> bool: + return response_id is not None and _upstream_response_id(response_id) == _upstream_response_id(original_response_id) + + +def _held_id_naming(response_id: str | None, held_ids: Mapping[str, str]) -> str | None: + return next( + ( + held_id + for original_response_id, held_id in held_ids.items() + if _names_the_same_response(response_id, original_response_id) + ), + None, + ) + + +def _id_sent_back(response: ResponsesAPIResponse | DeleteResponseResult, held_ids: Mapping[str, str]) -> str | None: + held_id: Final = _held_id_naming(response.id, held_ids) + if held_id is not None: + return held_id + return response.id if isinstance(response, DeleteResponseResult) else None + + class ResponsesIDSecurity(CustomLogger): def __init__( self, @@ -135,16 +177,64 @@ class ResponsesIDSecurity(CustomLogger): addressed_id_field: Final = _ADDRESSED_RESPONSE_ID_FIELD_BY_CALL_TYPE.get(call_type) if addressed_id_field is None: return None - retained_id: Final = data.get(ADDRESSED_RESPONSE_ID_FIELD) + request_data: Final = _REQUEST_DATA_ADAPTER.validate_python(data) + authorized_data: Final = ( + {**request_data, **self._authorized_comparison_response_id_fields(request_data, user_api_key_dict)} + if call_type == "aresponses" + else request_data + ) + retained_id: Final = authorized_data.get(ADDRESSED_RESPONSE_ID_FIELD) addressed_id: Final = ( - retained_id if isinstance(retained_id, str) and retained_id else data.get(addressed_id_field) + retained_id if isinstance(retained_id, str) and retained_id else authorized_data.get(addressed_id_field) ) if not isinstance(addressed_id, str) or not addressed_id: - return data - authorized_id: Final = self.authorize_response_id(addressed_id, user_api_key_dict) - data[addressed_id_field] = authorized_id - data[ADDRESSED_RESPONSE_ID_FIELD] = addressed_id - return data + return authorized_data + return { + **authorized_data, + addressed_id_field: self.authorize_response_id(addressed_id, user_api_key_dict), + ADDRESSED_RESPONSE_ID_FIELD: addressed_id, + } + + def _authorized_comparison_response_id_fields( + self, + data: Mapping[str, object], + user_api_key_dict: "UserAPIKeyAuth", + ) -> Mapping[str, object]: + extra_body: Final = as_str_mapping(data.get("extra_body")) + overriding_extra_body: Final = ( + extra_body if extra_body is not None and "prompt_cache_options" in extra_body else None + ) + options: Final = as_str_mapping( + data.get("prompt_cache_options") + if overriding_extra_body is None + else overriding_extra_body.get("prompt_cache_options") + ) + requested_id: Final = None if options is None else options.get("comparison_response_id") + if options is None or not isinstance(requested_id, str): + return {} + addressed_id: Final = self._comparison_addressed_id( + requested_id, data.get(ADDRESSED_COMPARISON_RESPONSE_ID_FIELD) + ) + authorized_options: Final = { + **options, + "comparison_response_id": self.authorize_response_id(addressed_id, user_api_key_dict), + } + authorized_field: Final[Mapping[str, object]] = ( + {"prompt_cache_options": authorized_options} + if overriding_extra_body is None + else {"extra_body": {**overriding_extra_body, "prompt_cache_options": authorized_options}} + ) + return {**authorized_field, ADDRESSED_COMPARISON_RESPONSE_ID_FIELD: addressed_id} + + def _comparison_addressed_id(self, requested_id: str, retained_id: object) -> str: + if ( + not isinstance(retained_id, str) + or self._is_encrypted_response_id(requested_id) + or not self._is_encrypted_response_id(retained_id) + ): + return requested_id + original_response_id, _, _ = self._decrypt_response_id(retained_id) + return retained_id if original_response_id == requested_id else requested_id def authorize_response_id( self, @@ -275,10 +365,18 @@ class ResponsesIDSecurity(CustomLogger): def _encrypt_response_id( self, - response: BaseLiteLLMOpenAIResponseObject, + response: _ResponseObjectT, user_api_key_dict: "UserAPIKeyAuth", request_cache: dict[str, str] | None = None, - ) -> BaseLiteLLMOpenAIResponseObject: + ) -> _ResponseObjectT: + encrypt: Final = self._response_id_encrypter(user_api_key_dict, request_cache) + return response if encrypt is None else _rewrite_advertised_id(response, encrypt) + + def _response_id_encrypter( + self, + user_api_key_dict: "UserAPIKeyAuth", + request_cache: dict[str, str] | None, + ) -> Callable[[str], str] | None: signing_key: Final = self._get_signing_key() if signing_key is None: verbose_proxy_logger.debug( @@ -287,7 +385,7 @@ class ResponsesIDSecurity(CustomLogger): "Skipping response ID encryption. " "See: https://docs.litellm.ai/docs/proxy/prod#5-set-litellm-salt-key" ) - return response + return None def encrypt(original_id: str) -> str: cached: Final = request_cache.get(original_id) if request_cache is not None else None @@ -304,47 +402,73 @@ class ResponsesIDSecurity(CustomLogger): request_cache[original_id] = encrypted_id return encrypted_id - return _rewrite_advertised_id(response, encrypt) + return encrypt + + def _streamed_response_id_advertiser( + self, + user_api_key_dict: "UserAPIKeyAuth", + request_data: Mapping[str, object], + ) -> Callable[[str], str] | None: + if not _streams_response_ids(user_api_key_dict.request_route): + return None + if self._general_settings_reader().get("disable_responses_id_security", False): + return None + encrypt: Final = self._response_id_encrypter(user_api_key_dict, request_cache={}) + if encrypt is None: + return None + logging_obj: Final = request_data.get("litellm_logging_obj") + held_ids: Final = self._ids_the_caller_holds(request_data.get(ADDRESSED_RESPONSE_ID_FIELD)) + + def advertise(original_id: str) -> str: + logged_id: Final = encrypt(original_id) + if isinstance(logging_obj, LiteLLMLoggingObj): + logging_obj.client_facing_response_id = logged_id + return _held_id_naming(original_id, held_ids) or logged_id + + return advertise + + def _ids_the_caller_holds(self, addressed_id: object) -> Mapping[str, str]: + if not isinstance(addressed_id, str) or not self._is_encrypted_response_id(addressed_id): + return _NO_HELD_IDS + original_response_id, _, _ = self._decrypt_response_id(addressed_id) + return MappingProxyType({original_response_id: addressed_id}) + + def _advertised_response( + self, + response: _AddressedResultT, + user_api_key_dict: "UserAPIKeyAuth", + request_data: Mapping[str, object], + ) -> _AddressedResultT: + sent_back_id: Final = _id_sent_back( + response, self._ids_the_caller_holds(request_data.get(ADDRESSED_RESPONSE_ID_FIELD)) + ) + logged_response: Final = self._encrypt_response_id(response, user_api_key_dict, request_cache=None) + return logged_response if sent_back_id is None else logged_response.model_copy(update={"id": sent_back_id}) async def async_post_call_success_hook( self, - data: dict, + data: dict[str, object], user_api_key_dict: "UserAPIKeyAuth", response: LLMResponseTypes, ) -> LLMResponseTypes: - """ - Queue response IDs for batch processing instead of writing directly to DB. - - This method adds response IDs to an in-memory queue, which are then - batch-processed by the DBSpendUpdateWriter during regular database update cycles. - """ general_settings: Final = self._general_settings_reader() if general_settings.get("disable_responses_id_security", False): return response - if isinstance(response, ResponsesAPIResponse): - response = cast( - ResponsesAPIResponse, - self._encrypt_response_id(response, user_api_key_dict, request_cache=None), - ) + if isinstance(response, ResponsesAPIResponse | DeleteResponseResult): + return self._advertised_response(response, user_api_key_dict, data) return response async def async_post_call_streaming_iterator_hook( - self, user_api_key_dict: "UserAPIKeyAuth", response: Any, request_data: dict + self, user_api_key_dict: "UserAPIKeyAuth", response: Any, request_data: dict[str, object] ) -> AsyncGenerator[BaseLiteLLMOpenAIResponseObject, None]: - general_settings: Final = self._general_settings_reader() - - # Create a request-scoped cache for consistent encryption across streaming chunks. - request_encryption_cache: Final[dict[str, str]] = {} - + advertise: Final = self._streamed_response_id_advertiser(user_api_key_dict, request_data) async for chunk in response: - if ( - isinstance(chunk, BaseLiteLLMOpenAIResponseObject) - and _streams_response_ids(user_api_key_dict.request_route) - and not general_settings.get("disable_responses_id_security", False) - ): - chunk = self._encrypt_response_id(chunk, user_api_key_dict, request_encryption_cache) - yield chunk + yield ( + _rewrite_advertised_id(chunk, advertise) + if advertise is not None and isinstance(chunk, BaseLiteLLMOpenAIResponseObject) + else chunk + ) def decrypted_response_id(response_id: str) -> str: diff --git a/litellm/proxy/image_endpoints/endpoints.py b/litellm/proxy/image_endpoints/endpoints.py index 6244e5025ce..95816edfecb 100644 --- a/litellm/proxy/image_endpoints/endpoints.py +++ b/litellm/proxy/image_endpoints/endpoints.py @@ -37,6 +37,7 @@ from litellm.proxy.common_utils.openai_error_payload import ( from litellm.proxy.route_llm_request import route_request from litellm.types.images.main import ImageEditRequestParams from litellm.types.llms.openai import ChatCompletionUserMessage +from litellm.types.utils import CallTypes router: Final = APIRouter() _IMAGE_GENERATION_MODEL_ADAPTER: Final[TypeAdapter[object]] = TypeAdapter(object) @@ -221,7 +222,10 @@ async def image_generation( return response except Exception as e: await proxy_logging_obj.post_call_failure_hook( - user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data + user_api_key_dict=user_api_key_dict, + original_exception=e, + request_data=data, + dispatched_call_type=CallTypes.aimage_generation.value, ) log_llm_api_exception(e, litellm_call_id) if isinstance(e, HTTPException): diff --git a/litellm/proxy/management_endpoints/common_daily_activity.py b/litellm/proxy/management_endpoints/common_daily_activity.py index 6e4ea0bd0cb..bbd6a1c9021 100644 --- a/litellm/proxy/management_endpoints/common_daily_activity.py +++ b/litellm/proxy/management_endpoints/common_daily_activity.py @@ -287,12 +287,12 @@ def compute_tag_metadata_totals(records: Sequence[DailySpendRecord]) -> SpendMet def _entity_metadata( - entity_metadata_field: Mapping[str, dict[str, object]] | None, + entity_metadata_field: Mapping[str, Mapping[str, object]] | None, entity_id: str, ) -> dict[str, object]: """The metadata payload for one entity breakdown bucket, empty when the caller passed none.""" stored: Final = entity_metadata_field.get(entity_id) if entity_metadata_field else None - return stored if stored is not None else {} + return dict(stored) if stored is not None else {} def provider_bucket_metadata(provider: str, base: Mapping[str, object]) -> Mapping[str, object]: @@ -1039,7 +1039,7 @@ def _fold_entity_rollups_sync( results: Sequence[DailySpendData], entity_rows: Sequence[EntityRollupRow], api_key_metadata: Mapping[str, KeyMetadataRow], - entity_metadata_field: Mapping[str, dict[str, object]] | None, # mutable-ok: shared field shape + entity_metadata_field: Mapping[str, Mapping[str, object]] | None, ) -> None: """Write breakdown.entities onto the already-built per-day results.""" by_date: Final = {day.date.strftime("%Y-%m-%d"): day for day in results} @@ -1113,6 +1113,19 @@ async def _guardrail_spend_or_empty( return () +async def _user_entity_metadata( + repository: DailyActivityRepository, entity_rows: Sequence[EntityRollupRow] +) -> Mapping[str, Mapping[str, object]]: + user_ids: Final = frozenset(row.entity_id for row in entity_rows if row.entity_id) + users: Final = await repository.user_metadata(user_ids) + return MappingProxyType( + { + user_id: MappingProxyType({"user_email": user.user_email, "user_alias": user.user_alias}) + for user_id, user in users.items() + } + ) + + async def get_daily_activity_aggregated( repository: DailyActivityRepository, scope: DailyActivityScope, @@ -1157,12 +1170,17 @@ async def get_daily_activity_aggregated( if entity_api_keys else MappingProxyType({}) ) + user_entity_metadata: Final[Mapping[str, Mapping[str, object]]] = ( + await _user_entity_metadata(repository, entity_records) + if scope.table is DailyActivityTable.USER + else MappingProxyType({}) + ) await asyncio.to_thread( _fold_entity_rollups_sync, results=aggregated["results"], entity_rows=entity_records, api_key_metadata=entity_key_metadata, - entity_metadata_field=entity_metadata_field, + entity_metadata_field=MappingProxyType({**user_entity_metadata, **(entity_metadata_field or {})}), ) results: Final = ( list(await asyncio.to_thread(_with_guardrail_breakdown, aggregated["results"], guardrail_rows)) diff --git a/litellm/proxy/management_endpoints/daily_activity_scopes.py b/litellm/proxy/management_endpoints/daily_activity_scopes.py index 7ff73ac6e2e..1eb6ab3210b 100644 --- a/litellm/proxy/management_endpoints/daily_activity_scopes.py +++ b/litellm/proxy/management_endpoints/daily_activity_scopes.py @@ -363,7 +363,7 @@ USER_RESOLVER = EntityScopeResolver( tags=("Budget & Spend Tracking", "Internal User management"), query=_user_query, resolve=_resolve_user, - include_entity_breakdown=False, + include_entity_breakdown=True, include_guardrail_breakdown=True, operation_names=MappingProxyType( { diff --git a/litellm/proxy/management_endpoints/internal_user_endpoints.py b/litellm/proxy/management_endpoints/internal_user_endpoints.py index 54a2d4062d2..d2aac9cae38 100644 --- a/litellm/proxy/management_endpoints/internal_user_endpoints.py +++ b/litellm/proxy/management_endpoints/internal_user_endpoints.py @@ -47,7 +47,7 @@ from litellm.proxy.auth.password_policy import ( ) from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.common_utils.auth_cache_invalidation_pubsub import evict_and_broadcast -from litellm.proxy.common_utils.openai_error_payload import proxy_exception_for +from litellm.proxy.common_utils.openai_error_payload import openai_shaped_proxy_exception, proxy_exception_for from litellm.proxy.common_utils.user_api_key_cache import ( AUTH_OBJECTS_TARGET, object_permission_cache_key, @@ -1048,6 +1048,7 @@ async def _check_user_info_v2_access( 1. Proxy admins / proxy admin viewers can access any user 2. User can access their own info 3. Team admins can access info of users in their teams + 4. Org admins can access info of users in their organizations Raises on unexpected DB errors so they surface as 500s, not silent 404s. """ @@ -1090,9 +1091,33 @@ async def _check_user_info_v2_access( if team.team_id in (target_user.teams or []): return target_user + if user_api_key_dict.user_id is not None and await _target_in_caller_admin_org( + prisma_client=prisma_client, + caller_user_id=user_api_key_dict.user_id, + target_user_id=target_user_id, + ): + return await _fetch_target_user() + return None +async def _target_in_caller_admin_org( + prisma_client: "PrismaClient", + caller_user_id: str, + target_user_id: str, +) -> bool: + admin_memberships: Final = await prisma_client.db.litellm_organizationmembership.find_many( + where={"user_id": caller_user_id, "user_role": LitellmUserRoles.ORG_ADMIN.value} + ) + if not admin_memberships: + return False + admin_org_ids: Final = {membership.organization_id for membership in admin_memberships} + target_memberships: Final = await prisma_client.db.litellm_organizationmembership.find_many( + where={"user_id": target_user_id} + ) + return any(membership.organization_id in admin_org_ids for membership in target_memberships) + + @router.get( "/v2/user/info", tags=["Internal User management"], @@ -1197,6 +1222,8 @@ async def user_info_v2( ), ) except Exception as e: + if isinstance(e, HTTPException) and e.status_code < 500: + raise openai_shaped_proxy_exception(e, str(e.detail), e.status_code) verbose_proxy_logger.exception("litellm.proxy.proxy_server.user_info_v2(): Exception occured - %s", e) raise handle_exception_on_proxy(e) diff --git a/litellm/proxy/management_endpoints/prompt_caching_requests.py b/litellm/proxy/management_endpoints/prompt_caching_requests.py index 2f00d263d84..d52c0255b08 100644 --- a/litellm/proxy/management_endpoints/prompt_caching_requests.py +++ b/litellm/proxy/management_endpoints/prompt_caching_requests.py @@ -14,9 +14,7 @@ from litellm.proxy.spend_tracking.savings import ( marks_gateway_injection, prompt_caching_savings_for_request, ) -from litellm.proxy.spend_tracking.spend_tracking_utils import ( - _query_raw_rows, # pyright: ignore[reportPrivateUsage] # existing typed spend-query adapter; rows validated below -) +from litellm.proxy.utils import query_raw_within_statement_timeout from litellm.types.integrations.anthropic_cache_control_hook import GATEWAY_INJECTED_CACHE_METADATA_KEY from litellm.types.llms.base import LiteLLMBaseModel from litellm.types.management_endpoints.prompt_caching_requests import ( @@ -158,7 +156,7 @@ async def get_prompt_caching_requests( else cursor_start_time ) rows: Final = _REQUEST_ROWS.validate_python( - await _query_raw_rows( + await query_raw_within_statement_timeout( prisma_client, prompt_caching_requests_sql(filter), start.isoformat(), @@ -166,8 +164,8 @@ async def get_prompt_caching_requests( page_size + 1, cursor_time.isoformat() if cursor_time is not None else None, cursor_request_id, + what="Prompt caching requests", ) - or () ) def current_router() -> "Router | None": diff --git a/litellm/proxy/management_endpoints/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py index b712ba42a6a..54b9b26123e 100644 --- a/litellm/proxy/management_endpoints/team_endpoints.py +++ b/litellm/proxy/management_endpoints/team_endpoints.py @@ -109,6 +109,7 @@ from litellm.proxy.auth.auth_checks import ( # noqa: F401 # legacy module expo can_org_access_model, delete_cache_key_objects, delete_cache_team_object, + evict_budget_windows_absent_marker, get_jwt_key_mapping_cache_keys_for_tokens, get_org_object, get_team_membership, @@ -223,7 +224,12 @@ from litellm.proxy.management_helpers.utils import ( add_new_member, management_endpoint_wrapper, ) -from litellm.proxy.utils import PrismaClient, ProxyLogging, handle_exception_on_proxy +from litellm.proxy.utils import ( + PrismaClient, + ProxyLogging, + handle_exception_on_proxy, + query_raw_within_statement_timeout, +) from litellm.repositories.budget_repository import BudgetRepository from litellm.repositories.chunked_in import delete_many_in, find_many_in from litellm.repositories.daily_activity_buckets import api_key_from_bucket @@ -612,6 +618,9 @@ async def refresh_cached_team( await publish_auth_cache_invalidation(cache_key=f"team_id:{team_row.team_id}") if team_table.team_alias is not None: await publish_auth_cache_invalidation(cache_key=f"team_alias:{team_table.team_alias}") + await evict_budget_windows_absent_marker( + entity_type=Litellm_EntityType.TEAM, entity_id=team_row.team_id, user_api_key_cache=user_api_key_cache + ) _refresh_cached_team: Final = refresh_cached_team @@ -7469,6 +7478,9 @@ class _TeamUserSpendDbRow(TypedDict): failed_requests: ReadOnly[int] +_TEAM_USER_SPEND_ROWS: Final = TypeAdapter(tuple[_TeamUserSpendDbRow, ...]) + + @router.get( "/team/spend/by_user", response_model=TeamUserSpendResponse, @@ -7519,12 +7531,16 @@ async def get_team_spend_by_user( own_user_only: Final = scope.api_key_filter is not None user_param: Final = (user_api_key_dict.user_id or "",) if own_user_only else () async with db_span("team_user_spend", "LiteLLM_SpendLogs"): - rows: Final[Sequence[_TeamUserSpendDbRow]] = await prisma_client.db.query_raw( - _team_user_spend_sql(team_count=len(scoped_team_ids), restrict_to_user=own_user_only), - start_date, - end_date, - *scoped_team_ids, - *user_param, + rows: Final = _TEAM_USER_SPEND_ROWS.validate_python( + await query_raw_within_statement_timeout( + prisma_client, + _team_user_spend_sql(team_count=len(scoped_team_ids), restrict_to_user=own_user_only), + start_date, + end_date, + *scoped_team_ids, + *user_param, + what="Spend per user", + ) ) results: Final = tuple( TeamUserSpendRow( diff --git a/litellm/proxy/management_helpers/user_list_sorting.py b/litellm/proxy/management_helpers/user_list_sorting.py index d3d2e323cb0..407a188ff1a 100644 --- a/litellm/proxy/management_helpers/user_list_sorting.py +++ b/litellm/proxy/management_helpers/user_list_sorting.py @@ -15,6 +15,10 @@ class _UserId(BaseModel): _USER_IDS: Final = TypeAdapter(tuple[_UserId, ...]) +def _csv_values(raw: str | None) -> tuple[str, ...]: + return tuple(value.strip() for value in (raw or "").split(",") if value.strip()) + + async def sorted_user_ids( prisma_client: PrismaClient, *, @@ -30,9 +34,9 @@ async def sorted_user_ids( organization_ids: str | None, search: str | None, ) -> Sequence[str]: - ids: Final = tuple(value.strip() for value in (user_ids or "").split(",") if value.strip()) - sso_ids: Final = tuple(value.strip() for value in (sso_user_ids or "").split(",") if value.strip()) - org_ids: Final = tuple(value.strip() for value in (organization_ids or "").split(",") if value.strip()) + ids: Final = _csv_values(user_ids) + sso_ids: Final = _csv_values(sso_user_ids) + org_ids: Final = _csv_values(organization_ids) expression: Final = ( "CASE WHEN u.metadata->'scim_active' = 'false'::jsonb THEN 1 ELSE 0 END" if sort_by == "status" diff --git a/litellm/proxy/mcp_server/mcp_server_manager.py b/litellm/proxy/mcp_server/mcp_server_manager.py index eacba25257e..013336e1d5d 100644 --- a/litellm/proxy/mcp_server/mcp_server_manager.py +++ b/litellm/proxy/mcp_server/mcp_server_manager.py @@ -367,7 +367,7 @@ _UpstreamSessionKey: TypeAlias = tuple[ str, str, str, - tuple[MCPTransport, MCPUpstreamProtocol, float, bool, bool, bool], + tuple[MCPTransport, MCPUpstreamProtocol, float, bool, bool, bool, bool], ] @@ -6253,9 +6253,9 @@ class MCPServerManager: "server_name": server_name, "mcp_rate_limit_server_name": server.alias or server.server_name or server.name, "user_api_key_auth": checked_auth, - "user_api_key_user_id": (getattr(checked_auth, "user_id", None) if checked_auth else None), - "user_api_key_team_id": (getattr(checked_auth, "team_id", None) if checked_auth else None), - "user_api_key_end_user_id": (getattr(checked_auth, "end_user_id", None) if checked_auth else None), + "user_api_key_user_id": checked_auth.user_id if checked_auth else None, + "user_api_key_team_id": checked_auth.team_id if checked_auth else None, + "user_api_key_end_user_id": checked_auth.end_user_id if checked_auth else None, "user_api_key_hash": (getattr(checked_auth, "api_key_hash", None) if checked_auth else None), "incoming_bearer_token": caller_bearer.get_secret_value() if caller_bearer is not None else None, "headers": logging_safe_mcp_headers(raw_headers), diff --git a/litellm/proxy/mcp_server/server.py b/litellm/proxy/mcp_server/server.py index aeb640a7c8b..bbbbd09e527 100644 --- a/litellm/proxy/mcp_server/server.py +++ b/litellm/proxy/mcp_server/server.py @@ -21,7 +21,7 @@ import httpx from fastapi import FastAPI, HTTPException from pydantic import ConfigDict, TypeAdapter, ValidationError from starlette.requests import Request as StarletteRequest -from starlette.responses import JSONResponse +from starlette.responses import JSONResponse, Response from starlette.routing import Route from starlette.types import Message, Receive, Scope, Send @@ -2489,6 +2489,9 @@ if MCP_AVAILABLE: }, )(scope, receive, send) return + if scope.get("method") == "OPTIONS": + await Response(status_code=204, headers={"Allow": "GET, POST, DELETE, OPTIONS"})(scope, receive, send) + return path: Final = _scope_path(scope) peek: Final = _LazyPeekedBody(receive) if scope.get("method") == "POST" else None if peek is not None: diff --git a/litellm/proxy/mcp_server/upstream.py b/litellm/proxy/mcp_server/upstream.py index 96a1c2db9ba..3dd245947db 100644 --- a/litellm/proxy/mcp_server/upstream.py +++ b/litellm/proxy/mcp_server/upstream.py @@ -231,6 +231,7 @@ async def prepare_upstream_client( server_url="", transport_type=transport, protocol_version=protocol_version, + skip_tool_output_validation=server.skip_tool_output_validation, auth_type=server.auth_type, auth_value=auth_value, timeout=timeout, @@ -265,6 +266,7 @@ async def prepare_upstream_client( server_url=server.url or "", transport_type=transport, protocol_version=protocol_version, + skip_tool_output_validation=server.skip_tool_output_validation, upstream_transport=upstream_transport, auth_type=server.auth_type, timeout=timeout, @@ -308,6 +310,7 @@ async def prepare_upstream_client( server_url=server.url or "", transport_type=transport, protocol_version=protocol_version, + skip_tool_output_validation=server.skip_tool_output_validation, upstream_transport=upstream_transport, auth_type=server.auth_type, auth_value=auth_value, diff --git a/litellm/proxy/middleware/admission_control_middleware.py b/litellm/proxy/middleware/admission_control_middleware.py index 1bb94e23d15..83503d0c3d4 100644 --- a/litellm/proxy/middleware/admission_control_middleware.py +++ b/litellm/proxy/middleware/admission_control_middleware.py @@ -10,6 +10,7 @@ from starlette.responses import JSONResponse from starlette.types import ASGIApp, Receive, Scope, Send from litellm._logging import verbose_proxy_logger +from litellm.proxy.common_utils.anthropic_error_payload import route_error_content ADMISSION_LEASE_SCOPE_KEY: Final = "litellm.admission_lease" @@ -175,7 +176,7 @@ class AdmissionControlMiddleware: state.record_admission() elif state.get_stats().queued >= settings.max_queued_requests: state.record_rejection("queue_full") - await _overloaded_response(state)(scope, receive, send) + await _overloaded_response(state, scope)(scope, receive, send) return else: state.record_queue() @@ -187,7 +188,7 @@ class AdmissionControlMiddleware: except asyncio.TimeoutError: state.record_dequeue() state.record_rejection("queue_timeout") - await _overloaded_response(state)(scope, receive, send) + await _overloaded_response(state, scope)(scope, receive, send) return except asyncio.CancelledError: state.record_dequeue() @@ -313,18 +314,16 @@ def get_admission_control_settings(settings: Mapping[str, object]) -> AdmissionC ) -def _overloaded_response(state: AdmissionControlState) -> JSONResponse: +def _overloaded_response(state: AdmissionControlState, scope: Scope) -> JSONResponse: stats: Final = state.get_stats() + message: Final = f"Worker at capacity: {stats.admitted} in-flight, {stats.queued} queued requests. Retry later." return JSONResponse( status_code=503, headers={"retry-after": "1"}, - content={ - "error": { - "message": ( - f"Worker at capacity: {stats.admitted} in-flight, {stats.queued} queued requests. Retry later." - ), - "type": "overloaded_error", - "code": "503", - } - }, + content=route_error_content( + scope, + "overloaded_error", + message, + {"error": {"message": message, "type": "overloaded_error", "code": "503"}}, + ), ) diff --git a/litellm/proxy/middleware/request_body_decompression_middleware.py b/litellm/proxy/middleware/request_body_decompression_middleware.py index 5eb8a9bfc91..2c36a621387 100644 --- a/litellm/proxy/middleware/request_body_decompression_middleware.py +++ b/litellm/proxy/middleware/request_body_decompression_middleware.py @@ -12,13 +12,19 @@ from starlette.requests import ClientDisconnect, Request from starlette.responses import JSONResponse from starlette.types import ASGIApp, Message, Receive, Scope, Send +from litellm.anthropic_interface.exceptions import AnthropicErrorType from litellm.constants import ( MAX_DECOMPRESSED_REQUEST_BODIES_IN_FLIGHT_MB, MAX_DECOMPRESSED_REQUEST_BODY_SIZE_MB, MAX_REQUEST_BODY_DECOMPRESSION_RATIO, ) from litellm.proxy.auth.auth_utils import get_request_route -from litellm.proxy.middleware.request_size_limit_middleware import MaxRequestSizeGetter, send_request_too_large +from litellm.proxy.common_utils.anthropic_error_payload import proxy_error_type, route_error_content +from litellm.proxy.middleware.request_size_limit_middleware import ( + MaxRequestSizeGetter, + effective_max_request_size_mb, + send_request_too_large, +) RFC_9659_ZSTD_WINDOW_LOG_MAX: Final = 23 GZIP_MAGIC: Final = b"\x1f\x8b" @@ -291,13 +297,22 @@ def _replay_body(body: bytes, receive: Receive, more_body: bool = False) -> Rece def _error_response( + scope: Scope, message: str, status_code: int, error_type: str = "invalid_request_error", headers: Mapping[str, str] | None = None, ) -> JSONResponse: + anthropic_type: Final[AnthropicErrorType] = ( + "overloaded_error" if error_type == "overloaded_error" else proxy_error_type(status_code) + ) return JSONResponse( - {"error": {"message": message, "type": error_type, "param": None, "code": str(status_code)}}, + route_error_content( + scope, + anthropic_type, + message, + {"error": {"message": message, "type": error_type, "param": None, "code": str(status_code)}}, + ), status_code=status_code, headers=headers, ) @@ -326,6 +341,7 @@ class RequestBodyDecompressionMiddleware: max_decompression_ratio: int = MAX_REQUEST_BODY_DECOMPRESSION_RATIO, max_decoded_bodies_in_flight_mb: float = MAX_DECOMPRESSED_REQUEST_BODIES_IN_FLIGHT_MB, codecs: Mapping[str, Codec] = AVAILABLE_CODECS, + route_max_request_size_mb: Mapping[tuple[str, str], float] | None = None, ) -> None: self.app = app self.get_max_request_size_mb: Final = get_max_request_size_mb @@ -333,6 +349,7 @@ class RequestBodyDecompressionMiddleware: self.max_decompression_ratio: Final = max_decompression_ratio self.budget: Final = _DecodedBodyBudget(int(max_decoded_bodies_in_flight_mb * 1024 * 1024)) self.codecs: Final = codecs + self.route_max_request_size_mb: Final = MappingProxyType(dict(route_max_request_size_mb or {})) async def __call__(self, scope: Scope, receive: Receive, send: Send) -> None: coding: Final = _coding_for(scope) @@ -356,6 +373,7 @@ class RequestBodyDecompressionMiddleware: if codec is None: supported: Final = ", ".join(sorted(self.codecs)) await _error_response( + scope, f"This proxy cannot decode {coding} request bodies. Supported encodings: {supported}", 415, headers={"accept-encoding": supported}, @@ -366,13 +384,16 @@ class RequestBodyDecompressionMiddleware: async def _decode_then_call( self, scope: Scope, receive: Receive, send: Send, codec: Codec, prefix: _Prefix ) -> None: - max_mb: Final = _effective_max_mb(self.max_decompressed_body_size_mb, self.get_max_request_size_mb()) + request_max_mb: Final = effective_max_request_size_mb( + scope, self.get_max_request_size_mb(), self.route_max_request_size_mb + ) + max_mb: Final = _effective_max_mb(self.max_decompressed_body_size_mb, request_max_mb) limits: Final = _Limits(max_mb=max_mb, max_ratio=self.max_decompression_ratio) match await _receive_body(scope, receive, prefix, limits.max_bytes): case _Body(data=data): await self._decode_within_budget(scope, receive, send, codec, data, limits) case _TooLarge(): - await send_request_too_large(send=send, max_request_size_mb=max_mb) + await send_request_too_large(scope=scope, send=send, max_request_size_mb=max_mb) case _ClientDisconnected(): return @@ -382,6 +403,7 @@ class RequestBodyDecompressionMiddleware: reservation: Final = _max_decoded_length(codec, data, limits) if not self.budget.try_reserve(reservation): await _error_response( + scope, "The proxy is decoding too many compressed request bodies right now. " "Retry later, or send this body uncompressed", 503, @@ -407,12 +429,12 @@ class RequestBodyDecompressionMiddleware: case _Body(data=body): await self.app(_identity_scope(scope, len(body)), _replay_body(body, receive), send) case _DecodedTooLarge(): - await _error_response(f"Request body is larger than {limits.max_mb:g} MB when decoded", 413)( + await _error_response(scope, f"Request body is larger than {limits.max_mb:g} MB when decoded", 413)( scope, receive, send ) case _OverRatio(): - await _error_response(f"Request body expands more than {limits.max_ratio} times when decoded", 413)( - scope, receive, send - ) + await _error_response( + scope, f"Request body expands more than {limits.max_ratio} times when decoded", 413 + )(scope, receive, send) case _Undecodable(message=message): - await _error_response(message, 400)(scope, receive, send) + await _error_response(scope, message, 400)(scope, receive, send) diff --git a/litellm/proxy/middleware/request_size_limit_middleware.py b/litellm/proxy/middleware/request_size_limit_middleware.py index cbbc79cc2ca..329a3c38d91 100644 --- a/litellm/proxy/middleware/request_size_limit_middleware.py +++ b/litellm/proxy/middleware/request_size_limit_middleware.py @@ -1,15 +1,48 @@ import json -from collections.abc import Callable +from collections.abc import Callable, Mapping +from types import MappingProxyType from typing import Final +from fastapi import HTTPException +from starlette._utils import get_route_path +from starlette.routing import compile_path from starlette.types import ASGIApp, Message, Receive, Scope, Send +from litellm.proxy.common_utils.anthropic_error_payload import route_error_content + MaxRequestSizeGetter = Callable[[], int | float | None] RequestSizeLimitEnabledGetter = Callable[[], bool] -class RequestEntityTooLarge(Exception): - pass +class RequestEntityTooLarge(HTTPException): + def __init__(self, max_request_size_mb: float) -> None: + super().__init__(status_code=413, detail=f"Request size is too large. Max size is {max_request_size_mb} MB") + + +def effective_max_request_size_mb( + scope: Scope, + configured: float | None, + route_limits: Mapping[tuple[str, str], float], +) -> float | None: + global_limit: Final = configured if configured is not None and configured > 0 else None + method: Final = scope.get("method") + path: Final = get_route_path(scope) + exact_limit: Final = route_limits.get((method, path)) if isinstance(method, str) else None + route_limit: Final = ( + exact_limit + if exact_limit is not None + else next( + ( + limit + for (route_method, route), limit in route_limits.items() + if route_method == method and "{" in route and compile_path(route)[0].fullmatch(path) is not None + ), + None, + ) + ) + if route_limit is None: + return global_limit + return min(route_limit, global_limit) if global_limit is not None else route_limit class RequestSizeLimitMiddleware: @@ -26,25 +59,35 @@ class RequestSizeLimitMiddleware: app: ASGIApp, get_max_request_size_mb: MaxRequestSizeGetter, is_request_size_limit_enabled: RequestSizeLimitEnabledGetter, + route_max_request_size_mb: Mapping[tuple[str, str], float] | None = None, ) -> None: self.app = app self.get_max_request_size_mb = get_max_request_size_mb self.is_request_size_limit_enabled = is_request_size_limit_enabled + self.route_max_request_size_mb = MappingProxyType(dict(route_max_request_size_mb or {})) + + def _max_request_size_mb(self, scope: Scope) -> float | None: + configured: Final = self.get_max_request_size_mb() + return effective_max_request_size_mb( + scope, + configured if self.is_request_size_limit_enabled() else None, + self.route_max_request_size_mb, + ) async def __call__(self, scope: Scope, receive: Receive, send: Send) -> None: if scope["type"] != "http": await self.app(scope, receive, send) return - max_request_size_mb: Final = self.get_max_request_size_mb() + max_request_size_mb: Final = self._max_request_size_mb(scope) max_request_size_bytes: Final = _mb_to_bytes(max_request_size_mb) - if max_request_size_bytes is None or not self.is_request_size_limit_enabled(): + if max_request_size_bytes is None or max_request_size_mb is None: await self.app(scope, receive, send) return content_length: Final = _get_content_length(scope=scope) if content_length is not None and content_length > max_request_size_bytes: - await send_request_too_large(send=send, max_request_size_mb=max_request_size_mb) + await send_request_too_large(scope=scope, send=send, max_request_size_mb=max_request_size_mb) return received_body_bytes = 0 @@ -59,7 +102,7 @@ class RequestSizeLimitMiddleware: received_body_bytes += len(message.get("body", b"")) if received_body_bytes > max_request_size_bytes: - raise RequestEntityTooLarge + raise RequestEntityTooLarge(max_request_size_mb) return message async def tracking_send(message: Message) -> None: @@ -74,7 +117,7 @@ class RequestSizeLimitMiddleware: except RequestEntityTooLarge: if response_started: raise - await send_request_too_large(send=send, max_request_size_mb=max_request_size_mb) + await send_request_too_large(scope=scope, send=send, max_request_size_mb=max_request_size_mb) def _mb_to_bytes(max_request_size_mb: float | None) -> int | None: @@ -98,11 +141,13 @@ def _get_content_length(scope: Scope) -> int | None: async def send_request_too_large( + scope: Scope, send: Send, max_request_size_mb: float | None, ) -> None: + message: Final = f"Request size is too large. Max size is {max_request_size_mb} MB" body: Final = json.dumps( - {"error": f"Request size is too large. Max size is {max_request_size_mb} MB"}, + route_error_content(scope, "request_too_large", message, {"error": message}), separators=(",", ":"), ).encode("utf-8") await send( diff --git a/litellm/proxy/openai_files_endpoints/common_utils.py b/litellm/proxy/openai_files_endpoints/common_utils.py index c0d81abeba7..18ce18da936 100644 --- a/litellm/proxy/openai_files_endpoints/common_utils.py +++ b/litellm/proxy/openai_files_endpoints/common_utils.py @@ -21,8 +21,8 @@ from typing import ( from pydantic import TypeAdapter from typing_extensions import NotRequired, ReadOnly, TypedDict -from litellm.batches.batch_utils import batch_cost_is_final from litellm.constants import MAX_FILE_LIST_LIMIT +from litellm.litellm_core_utils.batch_utils import batch_cost_is_final from litellm.proxy._types import ProxyException from litellm.repositories.managed_file_repository import ManagedFileRepository from litellm.repositories.table_repositories import ( diff --git a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py index c7983f40aec..627164abb93 100644 --- a/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/llm_passthrough_endpoints.py @@ -15,11 +15,11 @@ import os import posixpath import re import sys -from collections.abc import AsyncGenerator, Callable, Mapping, Sequence +from collections.abc import AsyncGenerator, Awaitable, Callable, Mapping, Sequence from dataclasses import dataclass from functools import partial from types import MappingProxyType -from typing import TYPE_CHECKING, Annotated, Final, Literal, Protocol, cast +from typing import TYPE_CHECKING, Annotated, Final, Literal, Protocol, TypeAlias, cast import httpx import openai @@ -31,7 +31,7 @@ from typing_extensions import ReadOnly, TypedDict import litellm from litellm import get_llm_provider -from litellm._logging import verbose_proxy_logger +from litellm._logging import redact_internal_details_from_client_message, verbose_proxy_logger from litellm._uuid import uuid from litellm.constants import ( ALLOWED_VERTEX_AI_PASSTHROUGH_HEADERS, @@ -51,12 +51,14 @@ from litellm.constants import ( from litellm.exceptions import BlockedPiiEntityError, GuardrailRaisedException from litellm.integrations.custom_guardrail import guardrail_request_data_with_streaming, is_guardrail_intervention from litellm.litellm_core_utils.aws_partition import get_aws_dns_suffix +from litellm.litellm_core_utils.core_helpers import as_object_list, as_str_mapping, attribute_or_none from litellm.litellm_core_utils.fallback_generalizations import match_routing_generalization from litellm.llms.anthropic.common_utils import ( AnthropicModelInfo, anthropic_pass_through_api_base, merge_anthropic_beta_headers, ) +from litellm.llms.azure.common_utils import entra_rejection_in from litellm.llms.azure.passthrough.transformation import ( foreign_azure_deployment, is_azure_body_model_inference_endpoint, @@ -85,7 +87,12 @@ from litellm.llms.vertex_ai.vertex_llm_base import VertexBase from litellm.llms.vllm.common_utils import endpoint_under_api_base from litellm.passthrough.main import AsyncPassthroughStreamingResponse, is_provider_error from litellm.proxy._types import * -from litellm.proxy.auth.auth_checks import enforced_model_allowlists +from litellm.proxy.auth.auth_checks import ( + can_agent_call_model, + can_key_call_resolved_model, + key_model_aliases_for_auth_check, + team_model_aliases_for_auth_check, +) from litellm.proxy.auth.handle_jwt import JWTHandler from litellm.proxy.auth.route_checks import RouteChecks from litellm.proxy.auth.user_api_key_auth import ( # noqa: F401 # legacy module exports @@ -93,6 +100,7 @@ from litellm.proxy.auth.user_api_key_auth import ( # noqa: F401 # legacy modul get_bearer_token, is_no_auth_dev_mode, user_api_key_auth, + user_api_key_auth_accepted_websocket_for_model, user_api_key_auth_websocket, user_api_key_auth_websocket_for_model, ) @@ -114,6 +122,7 @@ from litellm.proxy.common_utils.http_parsing_utils import ( # noqa: F401 # leg safe_get_request_headers, safe_set_request_parsed_body, ) +from litellm.proxy.common_utils.model_listing_utils import alias_map from litellm.proxy.common_utils.openai_error_payload import LITELLM_CALL_ID_HEADER from litellm.proxy.common_utils.resource_ownership import is_proxy_admin from litellm.proxy.common_utils.sse_keepalive import ( @@ -129,16 +138,26 @@ from litellm.proxy.pass_through_endpoints.injected_stream_usage import ( stream_usage_relay, without_injected_usage_frames, ) +from litellm.proxy.pass_through_endpoints.llm_provider_handlers.openai_websocket_passthrough_logging_handler import ( + openai_websocket_frame_kind, +) from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( + STORED_PROMPT_PROBE_MODEL, HttpPassThroughEndpointHelpers, + WebsocketFrameModelAllowed, + WebsocketFrameModelGate, + WebsocketFrameModelRefused, + WebsocketFrameModelVerdict, + WebsocketUpstreamFrameClassifier, YieldsToConfiguredPassThroughRoute, create_pass_through_route, create_websocket_passthrough_route, + refuse_websocket, truncated_close_reason, websocket_passthrough_request, ) from litellm.proxy.utils import ProxyLogging as ProxyLoggingType -from litellm.proxy.utils import is_known_model +from litellm.proxy.utils import is_known_model, normalize_route_for_root_path from litellm.proxy.vector_store_endpoints.utils import ( assert_proxy_admin_for_vector_store_index_management, assert_user_can_access_vector_store, @@ -198,7 +217,7 @@ def is_passthrough_request_using_router_model(request_body: dict, llm_router: li """ try: model: Final = request_body.get("model") - return is_known_model(model, llm_router) + return isinstance(model, str) and is_known_model(model, llm_router) except Exception: return False @@ -228,9 +247,8 @@ def is_passthrough_request_streaming(request_body: object) -> bool: A JSON body need not be an object, so a list or scalar can reach here; it carries no streaming flag. """ - if not isinstance(request_body, dict): - return False - return bool(request_body.get("stream", False)) + body: Final = as_str_mapping(request_body) + return body is not None and bool(body.get("stream", False)) def _optional_str(value: object) -> str | None: @@ -1400,13 +1418,12 @@ async def handle_bedrock_count_tokens( if deployment is not None: model_litellm_params: Final = deployment.get("litellm_params", {}) - # Get the resolved model ID from the configuration if "model" in model_litellm_params: resolved_model = model_litellm_params["model"] # Copy all litellm_params - BaseAWSLLM will handle AWS credential discovery for key, value in model_litellm_params.items(): - if key != "user_api_key_dict": # Don't overwrite user_api_key_dict + if key != "user_api_key_dict": litellm_params[key] = value verbose_proxy_logger.debug("Count tokens litellm_params: %s", litellm_params) @@ -2365,6 +2382,16 @@ async def _relay_router_model( ) except httpx.HTTPStatusError as upstream_error: return await _relay_upstream_response(upstream_error.response) + except Exception as error: + rejection: Final = entra_rejection_in(error) + if rejection is None: + raise + raise ProxyException( + message=redact_internal_details_from_client_message(rejection.message), + type=ProxyErrorTypes.auth_error, + param=None, + code=rejection.status_code, + ) from error if not is_streaming_request: return await _relay_upstream_response(cast(httpx.Response, result)) @@ -3387,19 +3414,6 @@ def _join_url_paths(base_url: httpx.URL, path: str, custom_llm_provider: litellm return joined_path_str -_OPENAI_WS_ALL_MODEL_ACCESS: Final = frozenset( - { - SpecialModelNames.all_proxy_models.value, - SpecialModelNames.all_team_models.value, - "*", - } -) - - -def _has_model_restrictions(model_allowlists: tuple[Sequence[str], ...]) -> bool: - return any(str(model) not in _OPENAI_WS_ALL_MODEL_ACCESS for allowlist in model_allowlists for model in allowlist) - - @dataclass(frozen=True, slots=True) class _OpenAIWebsocketRefusal: close_reason: str @@ -3416,6 +3430,16 @@ class _OpenAIWebsocketErrorFrame(TypedDict): error: ReadOnly[_OpenAIWebsocketErrorDetail] +_OPENAI_WS_UNAVAILABLE_AUTH_REFUSAL: Final = ( + "This gateway could not authorize the model named in this frame, so the session was closed. Try again, " + "and ask a proxy admin to check the gateway logs if it keeps happening." +) + +_OPENAI_WS_ALIASED_MODEL_REFUSAL: Final = ( + "This key cannot use a model alias over OpenAI websocket passthrough. The passthrough sends each frame to " + "OpenAI unchanged, so name the model this key may use directly." +) + _OPENAI_WS_DISABLED_REFUSAL: Final = _OpenAIWebsocketRefusal( close_reason="OpenAI websocket passthrough is disabled", message=( @@ -3424,14 +3448,6 @@ _OPENAI_WS_DISABLED_REFUSAL: Final = _OpenAIWebsocketRefusal( ), ) -_OPENAI_WS_MODEL_RESTRICTED_REFUSAL: Final = _OpenAIWebsocketRefusal( - close_reason="Keys with model restrictions cannot use OpenAI websocket passthrough", - message=( - "Keys with model restrictions cannot use OpenAI websocket passthrough, because this route " - "relays frames to the provider without reading which model they ask for." - ), -) - def _is_openai_websocket_passthrough_enabled(general_settings: Mapping[str, object]) -> bool: setting: Final = general_settings.get("enable_openai_websocket_passthrough") @@ -3440,19 +3456,9 @@ def _is_openai_websocket_passthrough_enabled(general_settings: Mapping[str, obje return setting is True -class _OpenAIWebsocketModelAllowlists(Protocol): - async def __call__(self, valid_token: UserAPIKeyAuth, /) -> tuple[Sequence[str], ...]: ... - - -async def _openai_websocket_refusal( - user_api_key_dict: UserAPIKeyAuth, - general_settings: Mapping[str, object], - model_allowlists: _OpenAIWebsocketModelAllowlists, -) -> _OpenAIWebsocketRefusal | None: +def _openai_websocket_refusal(general_settings: Mapping[str, object]) -> _OpenAIWebsocketRefusal | None: if not _is_openai_websocket_passthrough_enabled(general_settings): return _OPENAI_WS_DISABLED_REFUSAL - if _has_model_restrictions(await model_allowlists(user_api_key_dict)): - return _OPENAI_WS_MODEL_RESTRICTED_REFUSAL return None @@ -3467,6 +3473,8 @@ class _WebsocketRelay(Protocol): forward_headers: bool, endpoint: str, accept_websocket: bool, + client_frame_model_gate: WebsocketFrameModelGate | None = None, + upstream_frame_kind: WebsocketUpstreamFrameClassifier | None = None, meter: WebSocketSessionMeter | None = None, ) -> None: ... @@ -3475,18 +3483,95 @@ def _websocket_relay() -> _WebsocketRelay: return websocket_passthrough_request -def _proxy_model_allowlists() -> _OpenAIWebsocketModelAllowlists: - from litellm.proxy.proxy_server import prisma_client, proxy_logging_obj, user_api_key_cache +def _proxy_error_type(denial: ProxyException) -> str: + return denial.type.value if isinstance(denial.type, ProxyErrorTypes) else denial.type - async def resolve(valid_token: UserAPIKeyAuth, /) -> tuple[Sequence[str], ...]: - return await enforced_model_allowlists( - valid_token=valid_token, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, + +FrameModelAuthorizer: TypeAlias = Callable[[WebSocket, str], Awaitable[UserAPIKeyAuth]] + + +def _frame_model_authorizer() -> FrameModelAuthorizer: + return user_api_key_auth_accepted_websocket_for_model + + +def _proxy_model_list() -> Sequence[object] | None: + from litellm.proxy import proxy_server + + return as_object_list(attribute_or_none(proxy_server, "llm_model_list")) + + +def _gateway_remaps_model(model: str, frame_auth: UserAPIKeyAuth, llm_router: Router | None) -> bool: + alias_maps: Final = ( + key_model_aliases_for_auth_check(frame_auth) or {}, + team_model_aliases_for_auth_check(frame_auth) or {}, + alias_map(litellm.model_alias_map), + ) + targets: Final = ( + *(aliases.get(model) for aliases in alias_maps), + llm_router.registry().resolve(model, kind="alias") if llm_router is not None else None, + ) + return any(target not in (None, model) for target in targets) + + +def _aliased_model_verdict( + allowed: WebsocketFrameModelAllowed, probe: WebsocketFrameModelVerdict +) -> WebsocketFrameModelVerdict: + match probe: + case WebsocketFrameModelRefused(error_type=error_type) if error_type.endswith("_model_access_denied"): + return WebsocketFrameModelRefused(message=_OPENAI_WS_ALIASED_MODEL_REFUSAL, error_type=error_type) + case WebsocketFrameModelRefused(): + return probe + case WebsocketFrameModelAllowed(): + return allowed + + +def _proxy_frame_model_gate( + authorize_frame_model: Annotated[FrameModelAuthorizer, Depends(_frame_model_authorizer)], +) -> WebsocketFrameModelGate: + from litellm.proxy import proxy_server + from litellm.proxy.spend_tracking.budget_reservation import release_or_invalidate_budget_reservation + + async def authorize(websocket: WebSocket, model: str) -> WebsocketFrameModelVerdict: + connect_reservation: Final = attribute_or_none(websocket.state, "budget_reservation") + await release_or_invalidate_budget_reservation( + budget_reservation=connect_reservation if isinstance(connect_reservation, dict) else None ) + frame_auth: Final = await authorize_frame_model(websocket, model) + access_groups: Final = tuple(frame_auth.matched_model_access_groups or ()) + llm_router: Final = proxy_server.llm_router + try: + await can_key_call_resolved_model( + model=model, llm_model_list=_proxy_model_list(), valid_token=frame_auth, llm_router=llm_router + ) + await can_agent_call_model( + model=model, + valid_token=frame_auth, + llm_router=llm_router, + prisma_client=proxy_server.prisma_client, + user_api_key_cache=proxy_server.user_api_key_cache, + proxy_logging_obj=proxy_server.proxy_logging_obj, + ) + finally: + await release_or_invalidate_budget_reservation(budget_reservation=frame_auth.budget_reservation) + allowed: Final = WebsocketFrameModelAllowed(access_groups=access_groups) + if not _gateway_remaps_model(model, frame_auth, llm_router): + return allowed + return _aliased_model_verdict(allowed, await gate(websocket, STORED_PROMPT_PROBE_MODEL)) - return resolve + async def gate(websocket: WebSocket, model: str, /) -> WebsocketFrameModelVerdict: + try: + return await authorize(websocket, model) + except ProxyException as denial: + return WebsocketFrameModelRefused(message=denial.message, error_type=_proxy_error_type(denial)) + except HTTPException as denial: + return WebsocketFrameModelRefused(message=str(denial.detail), error_type="invalid_request_error") + except litellm.BudgetExceededError as exhausted: + return WebsocketFrameModelRefused(message=exhausted.message, error_type="budget_exceeded") + except Exception: # noqa: BLE001 # fail closed: a gate that cannot answer refuses, and says so in band + verbose_proxy_logger.exception("OpenAI websocket passthrough: the frame model gate failed on %s", model) + return WebsocketFrameModelRefused(message=_OPENAI_WS_UNAVAILABLE_AUTH_REFUSAL, error_type="server_error") + + return gate def _negotiated_websocket_subprotocol(websocket: WebSocket) -> str | None: @@ -3498,6 +3583,14 @@ def _negotiated_websocket_subprotocol(websocket: WebSocket) -> str | None: return requested_subprotocols[0] if requested_subprotocols else None +async def _opening_model_refusal( + websocket: WebSocket, query_string: str, frame_model_gate: WebsocketFrameModelGate +) -> WebsocketFrameModelRefused | None: + opening_models: Final = dict.fromkeys(httpx.QueryParams(query_string).get_list("model")) + verdicts: Final = tuple([await frame_model_gate(websocket, model) for model in opening_models]) + return next((verdict for verdict in verdicts if isinstance(verdict, WebsocketFrameModelRefused)), None) + + @router.websocket("/openai_passthrough/{endpoint:path}") @router.websocket("/openai/{endpoint:path}") async def openai_websocket_proxy_route( @@ -3506,12 +3599,12 @@ async def openai_websocket_proxy_route( user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth_websocket)], general_settings: Annotated[Mapping[str, object], Depends(_proxy_general_settings)], relay: Annotated[_WebsocketRelay, Depends(_websocket_relay)], - model_allowlists: Annotated[_OpenAIWebsocketModelAllowlists, Depends(_proxy_model_allowlists)], + frame_model_gate: Annotated[WebsocketFrameModelGate, Depends(_proxy_frame_model_gate)], ) -> None: """WebSocket passthrough for OpenAI prefixes (realtime / responses.connect).""" negotiated_subprotocol: Final = _negotiated_websocket_subprotocol(websocket) - refusal: Final = await _openai_websocket_refusal(user_api_key_dict, general_settings, model_allowlists) + refusal: Final = _openai_websocket_refusal(general_settings) if refusal is not None: await websocket.accept(subprotocol=negotiated_subprotocol) error_frame: Final[_OpenAIWebsocketErrorFrame] = { @@ -3557,14 +3650,21 @@ async def openai_websocket_proxy_route( await websocket.accept(subprotocol=negotiated_subprotocol) + opening_refusal: Final = await _opening_model_refusal(websocket, query_string, frame_model_gate) + if opening_refusal is not None: + await refuse_websocket(websocket, opening_refusal) + return + await relay( websocket=websocket, target=wss_target, custom_headers=custom_headers, user_api_key_dict=user_api_key_dict, forward_headers=False, - endpoint=websocket.url.path, + endpoint=normalize_route_for_root_path(websocket.url.path) or websocket.url.path, accept_websocket=False, + client_frame_model_gate=frame_model_gate, + upstream_frame_kind=openai_websocket_frame_kind, ) @@ -3882,7 +3982,8 @@ async def _tinyfish_json_object_field_names(request: Request) -> frozenset[str] parsed: Final = _DECODED_JSON.validate_python(json.loads(raw_body)) except (json.JSONDecodeError, UnicodeDecodeError): return None - return frozenset(parsed) if isinstance(parsed, dict) else None + fields: Final = as_str_mapping(parsed) + return None if fields is None else frozenset(fields) def _tinyfish_route_timeout() -> float | None: diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/openai_websocket_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/openai_websocket_passthrough_logging_handler.py new file mode 100644 index 00000000000..90eb76cc9d8 --- /dev/null +++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/openai_websocket_passthrough_logging_handler.py @@ -0,0 +1,260 @@ +from collections.abc import Mapping, Sequence +from dataclasses import dataclass +from datetime import datetime +from types import MappingProxyType +from typing import Final, Literal, TypeAlias, cast # noqa: TID251 # cost helpers type raw frames as a TypedDict list + +from pydantic import BaseModel, ConfigDict, TypeAdapter, ValidationError + +import litellm +from litellm._logging import verbose_proxy_logger +from litellm.cost_calculator import RealtimeAPITokenUsageProcessor, handle_realtime_stream_cost_calculation +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.proxy._types import PassThroughEndpointLoggingTypedDict +from litellm.responses.utils import ResponseAPILoggingUtils +from litellm.types.llms.openai import OpenAIRealtimeStreamList, ResponsesAPIResponse +from litellm.types.passthrough_endpoints.pass_through_endpoints import WebsocketUpstreamFrameKind +from litellm.types.utils import LlmProviders, ModelResponse, Usage + +WebsocketMessages: TypeAlias = Sequence[Mapping[str, object]] + +OPENAI_WEBSOCKET_PROVIDER: Final = LlmProviders.OPENAI.value + +_SESSION_CREATED: Final = "session.created" +_SESSION_UPDATED: Final = "session.updated" +_RESPONSE_CREATED: Final = "response.created" +_ERROR: Final = "error" +_REALTIME_RESPONSE_DONE: Final = "response.done" +_TRANSCRIPTION_COMPLETED: Final = "conversation.item.input_audio_transcription.completed" +_RESPONSES_TURN_ENDS: Final = frozenset({"response.completed", "response.incomplete", "response.failed"}) +_TURN_ENDS: Final = _RESPONSES_TURN_ENDS | {_REALTIME_RESPONSE_DONE} +_MODEL_NAMING_EVENTS: Final = _TURN_ENDS | {_SESSION_CREATED, _SESSION_UPDATED, _RESPONSE_CREATED} +_REALTIME_BILLED_EVENTS: Final = frozenset({_REALTIME_RESPONSE_DONE, _TRANSCRIPTION_COMPLETED}) +_RESPONSE_COST_HEADER: Final = "llm_provider-x-litellm-response-cost" +_FRAME_KINDS: Final[Mapping[str, WebsocketUpstreamFrameKind]] = MappingProxyType( + { + _SESSION_CREATED: "opens_session", + _SESSION_UPDATED: "updates_session", + _RESPONSE_CREATED: "starts_turn", + _TRANSCRIPTION_COMPLETED: "bills_usage", + _ERROR: "refuses_turn", + } +) + + +class _NamedModel(BaseModel): + model_config = ConfigDict(extra="ignore", frozen=True) + + model: str | None = None + + +class _AudioInput(BaseModel): + model_config = ConfigDict(extra="ignore", frozen=True) + + transcription: _NamedModel | None = None + + +class _SessionAudio(BaseModel): + model_config = ConfigDict(extra="ignore", frozen=True) + + input: _AudioInput | None = None + + +class _NamedSession(BaseModel): + model_config = ConfigDict(extra="ignore", frozen=True) + + model: str | None = None + audio: _SessionAudio | None = None + + +class _ModelNamingEvent(BaseModel): + model_config = ConfigDict(extra="ignore", frozen=True) + + session: _NamedSession | None = None + response: _NamedModel | None = None + + +class _ResponsesTurnEndEvent(BaseModel): + model_config = ConfigDict(extra="ignore", frozen=True) + + type: Literal["response.completed", "response.incomplete", "response.failed"] + response: ResponsesAPIResponse + + +_MODEL_NAMING_EVENT: Final = TypeAdapter(_ModelNamingEvent) +_RESPONSES_TURN_END_EVENT: Final = TypeAdapter(_ResponsesTurnEndEvent) + + +@dataclass(frozen=True, slots=True) +class _Billing: + usage: Usage + cost: float + + +@dataclass(frozen=True, slots=True) +class _CompletedTurn: + model: str + response: ResponsesAPIResponse + usage: Usage + + +def _event_model(event: Mapping[str, object]) -> str | None: + if event.get("type") not in _MODEL_NAMING_EVENTS: + return None + try: + naming: Final = _MODEL_NAMING_EVENT.validate_python(event) + except ValidationError: + return None + session: Final = naming.session or _NamedSession() + response: Final = naming.response or _NamedModel() + audio_input: Final = (session.audio or _SessionAudio()).input or _AudioInput() + transcription: Final = audio_input.transcription or _NamedModel() + return session.model or response.model or transcription.model or None + + +def observed_websocket_model(messages: WebsocketMessages) -> str | None: + return next((model for model in map(_event_model, messages) if model is not None), None) + + +def openai_websocket_frame_kind(frame: Mapping[str, object]) -> WebsocketUpstreamFrameKind: + frame_type: Final = frame.get("type") + if frame_type in _TURN_ENDS: + return "ends_turn" + if not isinstance(frame_type, str): + return "relayed" + return _FRAME_KINDS.get(frame_type, "relayed") + + +def _realtime_billing(messages: WebsocketMessages, model: str, logging_obj: LiteLLMLoggingObj) -> _Billing | None: + if not any(event.get("type") in _REALTIME_BILLED_EVENTS for event in messages): + return None + results: Final = cast( # cast-ok: the realtime cost helpers read raw provider frames through their TypedDict view + OpenAIRealtimeStreamList, tuple(event for event in messages if "type" in event) + ) + usage: Final = RealtimeAPITokenUsageProcessor.collect_and_combine_usage_from_realtime_stream_results(results) + cost: Final = handle_realtime_stream_cost_calculation( + results=results, + combined_usage_object=usage, + custom_llm_provider=OPENAI_WEBSOCKET_PROVIDER, + litellm_model_name=model, + litellm_logging_obj=logging_obj, + ) + return _Billing(usage=usage, cost=cost) + + +def _responses_turn(event: Mapping[str, object], session_model: str) -> _CompletedTurn | None: + if event.get("type") not in _RESPONSES_TURN_ENDS: + return None + try: + ended: Final = _RESPONSES_TURN_END_EVENT.validate_python(event) + except ValidationError: + verbose_proxy_logger.warning( + "OpenAI websocket passthrough: a %s frame carried no readable usage, so it is not billed", event.get("type") + ) + return None + if ended.response.usage is None: + return None + return _CompletedTurn( + model=ended.response.model or session_model, + response=ended.response, + usage=ResponseAPILoggingUtils.transform_response_api_usage_to_chat_usage(ended.response.usage), + ) + + +def _responses_billing(messages: WebsocketMessages, model: str, requested_model: str | None) -> _Billing | None: + turns: Final = tuple(turn for turn in (_responses_turn(event, model) for event in messages) if turn is not None) + if not turns: + return None + usage: Final = RealtimeAPITokenUsageProcessor.combine_usage_objects([turn.usage for turn in turns]) + return _Billing( + usage=usage, + cost=sum(_responses_cost(turn.response, (turn.model, requested_model)) for turn in turns), + ) + + +def _model_cost(response: ResponsesAPIResponse, model: str) -> float | None: + try: + return litellm.completion_cost( + completion_response=response, + model=model, + custom_llm_provider=OPENAI_WEBSOCKET_PROVIDER, + call_type="responses", + ) + except Exception: # noqa: BLE001 # completion_cost raises a bare Exception for an unpriced model, and the turn must still log + return None + + +def _responses_cost(response: ResponsesAPIResponse, price_as: Sequence[str | None]) -> float: + costs: Final = (_model_cost(response, model) for model in dict.fromkeys(price_as) if model is not None) + cost: Final = next((cost for cost in costs if cost), None) + if cost is None: + verbose_proxy_logger.warning( + "OpenAI websocket passthrough: could not price a Responses turn on %s, logging it at zero", price_as + ) + return 0.0 + return cost + + +def _requested_model(kwargs: Mapping[str, object]) -> str | None: + litellm_params: Final = as_str_mapping(kwargs.get("litellm_params")) + metadata: Final = None if litellm_params is None else as_str_mapping(litellm_params.get("metadata")) + model_group: Final = None if metadata is None else metadata.get("model_group") + return model_group if isinstance(model_group, str) else None + + +def _priced_result(model: str, billing: _Billing, start_time: datetime, call_id: str) -> ModelResponse: + result: Final = ModelResponse( + id=call_id, + object="chat.completion", + created=int(start_time.timestamp()), + model=model, + usage=billing.usage, + ) + hidden: Final = {"additional_headers": MappingProxyType({_RESPONSE_COST_HEADER: billing.cost})} + result._hidden_params = hidden # pyright: ignore[reportPrivateUsage] # the one settled-cost channel + return result + + +class OpenAIWebsocketPassthroughLoggingHandler: + def openai_websocket_passthrough_handler( + self, + websocket_messages: WebsocketMessages, + logging_obj: LiteLLMLoggingObj, + url_route: str, + start_time: datetime, + kwargs: Mapping[str, object], + ) -> PassThroughEndpointLoggingTypedDict: + model: Final = observed_websocket_model(websocket_messages) + if model is None: + verbose_proxy_logger.debug("OpenAI websocket passthrough (%s): no model named, skipping cost", url_route) + unpriced: Final[PassThroughEndpointLoggingTypedDict] = {"result": None, "kwargs": {**kwargs}} + return unpriced + + logging_obj.model = model # rebind-ok: the spend logger reads model and cost off the shared logging object + logging_obj.model_call_details.update( + MappingProxyType({"model": model, "custom_llm_provider": OPENAI_WEBSOCKET_PROVIDER}) + ) + + billing: Final = _realtime_billing(websocket_messages, model, logging_obj) or _responses_billing( + websocket_messages, model, _requested_model(kwargs) + ) + if billing is None: + verbose_proxy_logger.debug("OpenAI websocket passthrough (%s): no usage reported, skipping cost", url_route) + unbilled: Final[PassThroughEndpointLoggingTypedDict] = { + "result": None, + "kwargs": {**kwargs, "model": model, "custom_llm_provider": OPENAI_WEBSOCKET_PROVIDER}, + } + return unbilled + + logging_obj.model_call_details.update(MappingProxyType({"response_cost": billing.cost})) + priced: Final[PassThroughEndpointLoggingTypedDict] = { + "result": _priced_result(model, billing, start_time, logging_obj.litellm_call_id), + "kwargs": { + **kwargs, + "model": model, + "custom_llm_provider": OPENAI_WEBSOCKET_PROVIDER, + "response_cost": billing.cost, + }, + } + return priced diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py index 970cd466337..7f5983d5799 100644 --- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py @@ -6,15 +6,17 @@ import posixpath import re import traceback from base64 import b64encode -from collections.abc import AsyncGenerator, AsyncIterator, Callable, Iterable, Mapping, Sequence +from collections.abc import AsyncGenerator, AsyncIterator, Callable, Iterable, Mapping, MutableMapping, Sequence from dataclasses import dataclass from datetime import datetime -from itertools import chain, count, groupby +from functools import reduce +from itertools import chain, count, groupby, takewhile from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final, TypedDict, cast -from urllib.parse import urlencode, urlparse +from typing import TYPE_CHECKING, Any, Final, Protocol, TypeAlias, TypedDict, TypeVar, cast +from urllib.parse import parse_qs, urlencode, urlparse import httpx +import orjson from fastapi import ( APIRouter, Depends, @@ -24,6 +26,7 @@ from fastapi import ( Response, UploadFile, WebSocket, + WebSocketDisconnect, status, ) from fastapi.responses import StreamingResponse @@ -34,7 +37,7 @@ from starlette.routing import BaseRoute, Match, Route from starlette.types import Scope from starlette.websockets import WebSocketState from typing_extensions import ReadOnly -from websockets.asyncio.client import connect +from websockets.asyncio.client import ClientConnection, connect from websockets.exceptions import ( ConnectionClosedError, ConnectionClosedOK, @@ -60,6 +63,8 @@ from litellm.integrations.custom_guardrail import ( from litellm.integrations.custom_logger import CustomLogger from litellm.integrations.otel.model.semconv import PASSTHROUGH_OPERATION_KEY, GenAIOperation from litellm.litellm_core_utils.core_helpers import ( + as_object_list, + as_str_mapping, bind_budget_reservation_to_callbacks, get_metadata_variable_name_from_kwargs, get_or_create_metadata_bucket, @@ -69,6 +74,7 @@ from litellm.litellm_core_utils.internal_call_metadata import MODEL_ACCESS_GROUP from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.litellm_core_utils.litellm_logging import get_masked_values from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER +from litellm.litellm_core_utils.realtime_errors import realtime_error_event from litellm.litellm_core_utils.redact_messages import should_redact_message_logging from litellm.litellm_core_utils.safe_json_dumps import safe_dumps from litellm.llms.anthropic.common_utils import ( @@ -154,6 +160,7 @@ from litellm.types.passthrough_endpoints.pass_through_endpoints import ( PassthroughStandardLoggingPayload, WebSocketSessionMeter, WebSocketSessionUsage, + WebsocketUpstreamFrameKind, ) from litellm.types.utils import TRUSTED_CALLBACK_VARS_FIELD, CallTypes, Usage @@ -2574,11 +2581,16 @@ def _resolved_vertex_live_setup( return {**setup_data, "model": setup_model_rewriter(setup_model)} +def _decoded_frame(frame: str | bytes) -> object: + try: + return _DECODED_JSON.validate_python(orjson.loads(frame)) + except orjson.JSONDecodeError: + return _DECODED_JSON.validate_python(json.loads(frame if isinstance(frame, str) else frame.decode("utf-8"))) + + def _json_object_frame(frame: str | bytes) -> dict[str, object] | None: try: - decoded: Final[object] = _DECODED_JSON.validate_python( - json.loads(frame if isinstance(frame, str) else frame.decode("utf-8")) - ) + decoded: Final = _decoded_frame(frame) except (json.JSONDecodeError, UnicodeDecodeError): return None return decoded if isinstance(decoded, dict) else None @@ -2637,6 +2649,359 @@ def _with_trace_context(headers: Mapping[str, str], parent_span: object) -> dict return inject_trace_context(headers, parent_span=parent_span) +@dataclass(frozen=True, slots=True) +class WebsocketFrameModelAllowed: + access_groups: tuple[str, ...] + + +@dataclass(frozen=True, slots=True) +class WebsocketFrameModelRefused: + message: str + error_type: str + + +WebsocketFrameModelVerdict: TypeAlias = WebsocketFrameModelAllowed | WebsocketFrameModelRefused + + +class WebsocketFrameModelGate(Protocol): + async def __call__(self, websocket: WebSocket, model: str, /) -> WebsocketFrameModelVerdict: ... + + +WebsocketUpstreamFrameClassifier: TypeAlias = Callable[[Mapping[str, object]], WebsocketUpstreamFrameKind] +_SESSION_FRAMES_EVERY_ROW_CARRIES: Final[frozenset[WebsocketUpstreamFrameKind]] = frozenset( + {"opens_session", "updates_session"} +) +_FrameT: Final = TypeVar("_FrameT", bound=Mapping[str, object]) + + +@dataclass(frozen=True, slots=True) +class _TurnAuthorization: + requested_model: str | None + access_groups: tuple[str, ...] + + +@dataclass(frozen=True, slots=True) +class _ForwardClientFrame: + starts_turn: bool + turn: _TurnAuthorization | None + lane: str | None + + +@dataclass(frozen=True, slots=True) +class _RefuseClientFrame: + refusal: WebsocketFrameModelRefused + + +@dataclass(frozen=True, slots=True) +class _ClientFrameRequests: + starts_turn: bool + lane: str | None + turn_model: str | None + models: tuple[str, ...] + unverifiable_model_refusal: str | None + + +_NO_CLIENT_FRAME_REQUESTS: Final = _ClientFrameRequests( + starts_turn=False, lane=None, turn_model=None, models=(), unverifiable_model_refusal=None +) +_FORWARD_WITHOUT_TURN: Final = _ForwardClientFrame(starts_turn=False, turn=None, lane=None) +_UNREADABLE_CLIENT_FRAME: Final = _RefuseClientFrame( + refusal=WebsocketFrameModelRefused( + message="The gateway cannot parse this frame, so it cannot check which model it asks for.", + error_type="invalid_request_error", + ) +) +_TURN_STARTING_FRAME: Final = "response.create" +_FRAME_TEXT_WORTH_PARSING: Final = (f'"{_TURN_STARTING_FRAME}"', '"model"', '"prompt"', '"tools"', "\\") +_TURN_MODEL_PLACEMENTS: Final = (("model",), ("response", "model"), ("session", "model")) +_TRANSCRIPTION_MODEL_PLACEMENTS: Final = ( + ("session", "input_audio_transcription", "model"), + ("session", "audio", "input", "transcription", "model"), +) +_STORED_PROMPT_PLACEMENTS: Final = (("prompt",), ("response", "prompt"), ("session", "prompt")) +_TOOL_LIST_PLACEMENTS: Final = (("tools",), ("response", "tools"), ("session", "tools")) +_TOOL_THAT_RUNS_A_MODEL: Final = "image_generation" +STORED_PROMPT_PROBE_MODEL: Final = "litellm-unverifiable-stored-prompt-model" +_STORED_PROMPT_REFUSAL: Final = ( + "This key is limited to specific models, so it cannot run a stored prompt. " + "The gateway cannot check which model a stored prompt runs." +) +_UNNAMED_TOOL_MODEL_REFUSAL: Final = ( + "This key is limited to specific models, so an image_generation tool has to name its model. " + "The gateway cannot check which model an unnamed one runs." +) +_FIRST_SENTENCE: Final = re.compile(r".*?[.!?](?=\s|$)") +_LANE_NAME: Final = re.compile(r"[A-Za-z0-9_.-]{1,256}") +_UNROUTABLE_LANE_REFUSAL: Final = _RefuseClientFrame( + refusal=WebsocketFrameModelRefused( + message=( + "This stream_id is not a lane name the provider accepts. " + "The provider's error for it names no lane, so the gateway cannot tell which turn it refuses." + ), + error_type="invalid_request_error", + ) +) + + +def _may_name_a_model(text_data: str) -> bool: + return any(marker in text_data for marker in _FRAME_TEXT_WORTH_PARSING) + + +def _frame_lane(frame: Mapping[str, object]) -> str | None: + stream_id: Final = frame.get("stream_id") + return stream_id if isinstance(stream_id, str) else None + + +def _names_an_unroutable_lane(frame: Mapping[str, object]) -> bool: + stream_id: Final = frame.get("stream_id") + return stream_id is not None and not (isinstance(stream_id, str) and _LANE_NAME.fullmatch(stream_id) is not None) + + +def _frames_of_lane(lane: str | None) -> Callable[[Mapping[str, object]], bool]: + def in_lane(frame: Mapping[str, object]) -> bool: + return _frame_lane(frame) == lane + + return in_lane + + +def _every_frame(_frame: Mapping[str, object]) -> bool: + return True + + +def _without_earlier_session_updates( + upstream_frame_kind: WebsocketUpstreamFrameClassifier, + frames: Sequence[_FrameT], + latest_update: _FrameT, +) -> tuple[_FrameT, ...]: + return tuple( + frame + for index, frame in enumerate(frames) + if frame is latest_update + or upstream_frame_kind(frame) != "updates_session" + or _unbilled_usage_ran_under(map(upstream_frame_kind, frames[index + 1 :])) + ) + + +def _unbilled_usage_ran_under(later_kinds: Iterable[WebsocketUpstreamFrameKind]) -> bool: + return "bills_usage" in takewhile(lambda kind: kind != "updates_session", later_kinds) + + +def _nested_frame(frame: Mapping[str, object] | None, key: str) -> Mapping[str, object] | None: + return None if frame is None else as_str_mapping(frame.get(key)) + + +def _placed_value(frame: Mapping[str, object], placement: Sequence[str]) -> object: + *parents, leaf = placement + container: Final = reduce(_nested_frame, parents, frame) + return None if container is None else container.get(leaf) + + +def _placed_models(frame: Mapping[str, object], placements: Iterable[Sequence[str]]) -> tuple[str, ...]: + placed: Final = (_placed_value(frame, placement) for placement in placements) + return tuple(value for value in placed if isinstance(value, str)) + + +def _placed_tools(frame: Mapping[str, object]) -> tuple[Mapping[str, object], ...]: + tool_lists: Final = (_placed_value(frame, placement) for placement in _TOOL_LIST_PLACEMENTS) + tools: Final = chain.from_iterable(as_object_list(tool_list) or () for tool_list in tool_lists) + return tuple(tool for tool in map(as_str_mapping, tools) if tool is not None) + + +def _unverifiable_model_refusal(frame: Mapping[str, object], tools: Sequence[Mapping[str, object]]) -> str | None: + prompts: Final = (_placed_value(frame, placement) for placement in _STORED_PROMPT_PLACEMENTS) + if any(isinstance(prompt, Mapping) for prompt in prompts): + return _STORED_PROMPT_REFUSAL + if any(tool.get("type") == _TOOL_THAT_RUNS_A_MODEL and not isinstance(tool.get("model"), str) for tool in tools): + return _UNNAMED_TOOL_MODEL_REFUSAL + return None + + +def _client_frame_requests(frame_data: str | bytes) -> _ClientFrameRequests | _RefuseClientFrame: + if isinstance(frame_data, str) and not _may_name_a_model(frame_data): + return _NO_CLIENT_FRAME_REQUESTS + try: + frame: Final = _json_object_frame(frame_data) + except (RecursionError, ValueError): + return _UNREADABLE_CLIENT_FRAME + if frame is None: + return _NO_CLIENT_FRAME_REQUESTS + if _names_an_unroutable_lane(frame): + return _UNROUTABLE_LANE_REFUSAL + turn_models: Final = _placed_models(frame, _TURN_MODEL_PLACEMENTS) + tools: Final = _placed_tools(frame) + tool_models: Final = (model for model in (tool.get("model") for tool in tools) if isinstance(model, str)) + return _ClientFrameRequests( + starts_turn=frame.get("type") == _TURN_STARTING_FRAME, + lane=_frame_lane(frame), + turn_model=next(iter(turn_models), None), + models=tuple( + dict.fromkeys((*turn_models, *_placed_models(frame, _TRANSCRIPTION_MODEL_PLACEMENTS), *tool_models)) + ), + unverifiable_model_refusal=_unverifiable_model_refusal(frame, tools), + ) + + +def _unverifiable_model_probe_refusal(probe: WebsocketFrameModelRefused, message: str) -> WebsocketFrameModelRefused: + if probe.error_type.endswith("_model_access_denied"): + return WebsocketFrameModelRefused(message=message, error_type=probe.error_type) + return probe + + +async def _client_frame_verdict( + websocket: WebSocket, frame_data: str | bytes, gate: WebsocketFrameModelGate | None +) -> _ForwardClientFrame | _RefuseClientFrame: + if gate is None: + return _FORWARD_WITHOUT_TURN + requests: Final = _client_frame_requests(frame_data) + if isinstance(requests, _RefuseClientFrame): + return requests + verdicts: Final = tuple([await gate(websocket, model) for model in requests.models]) + refusal: Final = next((verdict for verdict in verdicts if isinstance(verdict, WebsocketFrameModelRefused)), None) + if refusal is not None: + return _RefuseClientFrame(refusal=refusal) + if requests.unverifiable_model_refusal is not None and isinstance( + probe := await gate(websocket, STORED_PROMPT_PROBE_MODEL), WebsocketFrameModelRefused + ): + return _RefuseClientFrame(refusal=_unverifiable_model_probe_refusal(probe, requests.unverifiable_model_refusal)) + allowed: Final = tuple(verdict for verdict in verdicts if isinstance(verdict, WebsocketFrameModelAllowed)) + return _ForwardClientFrame( + starts_turn=requests.starts_turn, + lane=requests.lane, + turn=( + _TurnAuthorization(requested_model=requests.turn_model, access_groups=allowed[0].access_groups) + if requests.turn_model is not None and allowed + else None + ), + ) + + +def _refusal_close_reason(message: str) -> str: + first_sentence: Final = _FIRST_SENTENCE.match(message) + return truncated_close_reason(message if first_sentence is None else first_sentence.group(0)) + + +async def refuse_websocket(websocket: WebSocket, refusal: WebsocketFrameModelRefused) -> None: + await websocket.send_text(realtime_error_event(refusal.message, error_type=refusal.error_type)) + await websocket.close(code=CloseCode.POLICY_VIOLATION, reason=_refusal_close_reason(refusal.message)) + + +def _stamp_billed_turn(kwargs: Mapping[str, object], turn: _TurnAuthorization) -> None: + litellm_params: Final = as_str_mapping(kwargs.get("litellm_params")) + metadata: Final = None if litellm_params is None else litellm_params.get("metadata") + if not isinstance(metadata, MutableMapping): + return + metadata[MODEL_ACCESS_GROUP_METADATA_KEY] = list(turn.access_groups) + if turn.requested_model is not None: + metadata["model_group"] = turn.requested_model + + +def _opening_model(target: str) -> str | None: + return next(iter(parse_qs(urlparse(target).query).get("model", ())), None) + + +class _WebsocketTurnLedger: + def __init__(self, opening: _TurnAuthorization, started: datetime) -> None: + self.opening = opening + self.queued_turns: Mapping[str | None, tuple[_TurnAuthorization | None, ...]] = MappingProxyType({}) + self.session_opened = False + self.started = started + self.logged_turns = 0 + self.unstarted_turns = 0 + + def current(self, lane: str | None) -> _TurnAuthorization: + oldest: Final = next(iter(self.queued_turns.get(lane, ())), None) + return self.opening if oldest is None else oldest + + def queue_turn(self, lane: str | None, turn: _TurnAuthorization | None) -> None: + self.unstarted_turns += 1 + if not self.session_opened: + self.queued_turns = MappingProxyType({**self.queued_turns, lane: (*self.queued_turns.get(lane, ()), turn)}) + + def open_session(self) -> None: + self.session_opened = True + self.queued_turns = MappingProxyType({}) + + def close_turn(self, lane: str | None, end_time: datetime) -> None: + self.logged_turns += 1 + self.started = end_time + self._forget_turn(lane, 0) + + def start_turn(self) -> None: + self.unstarted_turns = max(0, self.unstarted_turns - 1) + + def drop_refused_turn(self, lane: str | None, lane_is_running_a_turn: bool) -> None: + self.start_turn() + self._forget_turn(lane, 1 if lane_is_running_a_turn else 0) + + def _forget_turn(self, lane: str | None, position: int) -> None: + turns: Final = self.queued_turns.get(lane, ()) + self.queued_turns = MappingProxyType({**self.queued_turns, lane: (*turns[:position], *turns[position + 1 :])}) + + +def _session_end_needs_a_row( + upstream_frame_kind: WebsocketUpstreamFrameClassifier | None, + unlogged_frames: Sequence[Mapping[str, object]], + ledger: _WebsocketTurnLedger, +) -> bool: + if upstream_frame_kind is None: + return True + kinds: Final = frozenset(map(upstream_frame_kind, unlogged_frames)) + return "starts_turn" in kinds or (ledger.logged_turns == 0 and bool(kinds - {"opens_session"})) + + +def _turn_in_flight( + upstream_frame_kind: WebsocketUpstreamFrameClassifier | None, unlogged_frames: Sequence[Mapping[str, object]] +) -> bool: + return upstream_frame_kind is not None and any( + upstream_frame_kind(frame) == "starts_turn" for frame in unlogged_frames + ) + + +def _turn_owed( + upstream_frame_kind: WebsocketUpstreamFrameClassifier | None, + unlogged_frames: Sequence[Mapping[str, object]], + ledger: _WebsocketTurnLedger, +) -> bool: + return _turn_in_flight(upstream_frame_kind, unlogged_frames) or ( + upstream_frame_kind is not None and ledger.unstarted_turns > 0 + ) + + +def _lanes_in_flight( + upstream_frame_kind: WebsocketUpstreamFrameClassifier, unlogged_frames: Sequence[Mapping[str, object]] +) -> tuple[str | None, ...]: + started: Final = (frame for frame in unlogged_frames if upstream_frame_kind(frame) == "starts_turn") + return tuple(dict.fromkeys(map(_frame_lane, started))) + + +async def _relay_client_frame( + websocket: WebSocket, + upstream_ws: ClientConnection, + checked_frame: str | bytes, + forwarded_frame: str | bytes, + gate: WebsocketFrameModelGate | None, + ledger: _WebsocketTurnLedger, +) -> _ForwardClientFrame | _RefuseClientFrame: + verdict: Final = await _client_frame_verdict(websocket, checked_frame, gate) + match verdict: + case _RefuseClientFrame(refusal=refusal): + await refuse_websocket(websocket, refusal) + case _ForwardClientFrame(starts_turn=True, turn=turn, lane=lane): + ledger.queue_turn(lane, turn) + await upstream_ws.send(forwarded_frame) + case _ForwardClientFrame(): + await upstream_ws.send(forwarded_frame) + return verdict + + +_EXPLICIT_SUCCESS_KWARGS: Final = frozenset({"logging_obj", "passthrough_logging_payload", "custom_llm_provider"}) +WALKOUT_TURN_DRAIN_SECONDS: Final = 600.0 + + +def _metered_client_text(meter: WebSocketSessionMeter | None, client_text: str) -> int: + return 0 if meter is None else meter.measure(client_text) + + def _log_session_usage(logging_obj: LiteLLMLoggingObj, usage: WebSocketSessionUsage) -> None: logging_obj.model = usage.model # rebind-ok: the spend logger reads model and cost off the shared logging object logging_obj.model_call_details["model"] = usage.model # rebind-ok: same shared logging object @@ -2654,6 +3019,9 @@ async def websocket_passthrough_request( cost_per_request: float | None = None, accept_websocket: bool = True, setup_model_rewriter: Callable[[str], str] | None = None, + client_frame_model_gate: WebsocketFrameModelGate | None = None, + upstream_frame_kind: WebsocketUpstreamFrameClassifier | None = None, + walkout_turn_drain_seconds: float = WALKOUT_TURN_DRAIN_SECONDS, builtin_provider_route: bool = False, model: str | None = None, meter: WebSocketSessionMeter | None = None, @@ -2670,6 +3038,11 @@ async def websocket_passthrough_request( endpoint: The endpoint path (for logging purposes) cost_per_request: Optional field - cost per request to the target endpoint setup_model_rewriter: Optional rewrite of the setup frame's model before it reaches the upstream + client_frame_model_gate: Optional per-frame check of every model a client frame names + upstream_frame_kind: Optional sort of upstream frames into the one that ends a billable turn and the ones + that open the session, so each turn logs its own spend and keeps the session's provider-named model + walkout_turn_drain_seconds: How long to keep reading a turn the provider is still running after the client + left or was refused, so the provider's usage for it still reaches spend builtin_provider_route: Whether a built-in provider route serves the connection, so its URL names the provider model: The model the caller named before connecting, logged on a failure before the setup frame arrives meter: Prices the session from the client text frames delivered upstream, for an upstream that reports no usage @@ -2709,26 +3082,31 @@ async def websocket_passthrough_request( proxy_config=proxy_config, route_description="websocket_passthrough", ) - logging_obj: Final = Logging( - model="unknown", - messages=[{"role": "user", "content": "WebSocket connection"}], - stream=True, # WebSockets are inherently streaming - call_type="pass_through_endpoint", - start_time=start_time, - litellm_call_id=litellm_call_id, - function_id="websocket_passthrough", - dynamic_success_callbacks=team_callbacks.success_callbacks, - dynamic_failure_callbacks=team_callbacks.failure_callbacks, - kwargs=team_callbacks.logging_kwargs, - ) - # Create passthrough logging payload - passthrough_logging_payload: Final = PassthroughStandardLoggingPayload( - url=target, - request_body={}, # WebSocket doesn't have a traditional request body - request_method="WEBSOCKET", - cost_per_request=cost_per_request, - ) + def new_call_logging(call_start: datetime, call_id: str) -> LiteLLMLoggingObj: + return Logging( + model="unknown", + messages=[{"role": "user", "content": "WebSocket connection"}], + stream=True, + call_type="pass_through_endpoint", + start_time=call_start, + litellm_call_id=call_id, + function_id="websocket_passthrough", + dynamic_success_callbacks=team_callbacks.success_callbacks, + dynamic_failure_callbacks=team_callbacks.failure_callbacks, + kwargs=team_callbacks.logging_kwargs, + ) + + def new_call_payload() -> PassthroughStandardLoggingPayload: + return PassthroughStandardLoggingPayload( + url=target, + request_body={}, + request_method="WEBSOCKET", + cost_per_request=cost_per_request, + ) + + logging_obj: Final = new_call_logging(start_time, litellm_call_id) + passthrough_logging_payload: Final = new_call_payload() # Create a dummy request object for WebSocket connections to maintain compatibility # with the existing _init_kwargs_for_pass_through_endpoint function @@ -2750,38 +3128,136 @@ async def websocket_passthrough_request( ) # Initialize kwargs for logging using the same pattern as HTTP passthrough - kwargs: Final = HttpPassThroughEndpointHelpers.init_kwargs_for_pass_through_endpoint( - user_api_key_dict=user_api_key_dict, - _parsed_body={}, # WebSocket doesn't have a traditional request body - passthrough_logging_payload=passthrough_logging_payload, - litellm_call_id=litellm_call_id, - request=dummy_request, - logging_obj=logging_obj, + def init_call_kwargs( + token: UserAPIKeyAuth, + call_payload: PassthroughStandardLoggingPayload, + call_id: str, + call_logging: LiteLLMLoggingObj, + ) -> dict[str, object]: # mutable-ok: the Vertex relay stamps the model from setup frames into these kwargs + return HttpPassThroughEndpointHelpers.init_kwargs_for_pass_through_endpoint( + user_api_key_dict=token, + _parsed_body={}, # WebSocket doesn't have a traditional request body + passthrough_logging_payload=call_payload, + litellm_call_id=call_id, + request=dummy_request, + logging_obj=call_logging, + ) + + kwargs: Final = init_call_kwargs(user_api_key_dict, passthrough_logging_payload, litellm_call_id, logging_obj) + + def start_call_logging(call_logging: LiteLLMLoggingObj, call_kwargs: Mapping[str, object]) -> None: + call_logging.update_environment_variables( + model="unknown", + user="unknown", + optional_params={}, + litellm_params=dict(as_str_mapping(call_kwargs.get("litellm_params")) or {}), + call_type="pass_through_endpoint", + ) + call_logging.pre_call( + input=[{"role": "user", "content": "WebSocket connection"}], + api_key="", + additional_args={ + "complete_input_dict": {}, + "api_base": target, + "headers": upstream_headers, + }, + ) + + start_call_logging(logging_obj, kwargs) + + class MockWebSocketRequest: + def __init__(self, target_url: str): + self.method = "WEBSOCKET" + self.url = target_url + + class MockWebSocketResponse: + def __init__(self, target_url: str): + self.status_code = 200 + self.text = "WebSocket connection successful" + self.headers: dict[str, str] = {} + self.request = MockWebSocketRequest(target_url) + + ledger: Final = _WebsocketTurnLedger( + opening=_TurnAuthorization( + requested_model=_opening_model(target), + access_groups=tuple(user_api_key_dict.matched_model_access_groups or ()), + ), + started=start_time, ) - # Update logging environment variables - logging_obj.update_environment_variables( - model="unknown", - user="unknown", - optional_params={}, - litellm_params=dict(kwargs.get("litellm_params", {})), - call_type="pass_through_endpoint", - ) - logging_obj.model_call_details["litellm_call_id"] = litellm_call_id + def log_frames( + call_logging: LiteLLMLoggingObj, + call_payload: PassthroughStandardLoggingPayload, + call_kwargs: Mapping[str, object], + end_time: datetime, + lane: str | None, + in_row: Callable[[Mapping[str, object]], bool], + ) -> None: + all_frames: Final = list(websocket_messages) + frames: Final = [frame for frame in all_frames if in_row(frame)] + websocket_messages[:] = ( + () + if upstream_frame_kind is None + else ( + frame + for frame in all_frames + if not in_row(frame) or upstream_frame_kind(frame) in _SESSION_FRAMES_EVERY_ROW_CARRIES + ) + ) + logged_payload: Final[PassthroughStandardLoggingPayload] = { + **call_payload, + "response_body": frames, + "end_time": end_time, + } + if client_frame_model_gate is not None: + _stamp_billed_turn(call_kwargs, ledger.current(lane)) + success_kwargs: Final = { + key: value for key, value in call_kwargs.items() if key not in _EXPLICIT_SUCCESS_KWARGS + } + custom_llm_provider: Final = call_kwargs.get("custom_llm_provider") + GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue( + async_coroutine=pass_through_endpoint_logging.pass_through_async_success_handler( + httpx_response=MockWebSocketResponse(target), + response_body=frames, + url_route=endpoint or "", + result="websocket_connection_successful", + start_time=ledger.started, + end_time=end_time, + logging_obj=call_logging, + cache_hit=False, + request_body={}, + passthrough_logging_payload=logged_payload, + custom_llm_provider=custom_llm_provider if isinstance(custom_llm_provider, str) else None, + finalize_before_dispatch=False, + **success_kwargs, + ) + ) + bind_budget_reservation_to_callbacks(call_logging.litellm_params) - # Pre-call logging - logging_obj.pre_call( - input=[{"role": "user", "content": "WebSocket connection"}], - api_key="", - additional_args={ - "complete_input_dict": {}, - "api_base": target, - "headers": upstream_headers, - }, - ) + def log_turn(lane: str | None, in_row: Callable[[Mapping[str, object]], bool]) -> None: + end_time: Final = datetime.now() + if upstream_frame_kind is None: + log_frames(logging_obj, passthrough_logging_payload, kwargs, end_time, lane, in_row) + else: + turn_call_id: Final = str(uuid.uuid4()) + turn_logging: Final = new_call_logging(ledger.started, turn_call_id) + turn_payload: Final = new_call_payload() + turn_kwargs: Final = init_call_kwargs( + user_api_key_dict + if ledger.logged_turns == 0 + else user_api_key_dict.model_copy(update={"budget_reservation": None}), + turn_payload, + turn_call_id, + turn_logging, + ) + start_call_logging(turn_logging, turn_kwargs) + log_frames(turn_logging, turn_payload, turn_kwargs, end_time, lane, in_row) + ledger.close_turn(lane, end_time) ### CALL HOOKS ### - modify incoming data / reject request before calling the model - websocket_hook_data: Final = guardrail_request_data_with_streaming(MappingProxyType({}), is_streaming=True) + websocket_hook_data: Final = guardrail_request_data_with_streaming( + MappingProxyType({"litellm_call_id": litellm_call_id}), is_streaming=True + ) await proxy_logging_obj.pre_call_hook( user_api_key_dict=user_api_key_dict, data=websocket_hook_data, @@ -2808,7 +3284,6 @@ async def websocket_passthrough_request( message = await websocket.receive() message_type = message.get("type") if message_type == "websocket.disconnect": - await upstream_ws.close() break text_data: str | None = message.get("text") @@ -2871,11 +3346,29 @@ async def websocket_passthrough_request( ) # Not a JSON message or doesn't contain setup data - await upstream_ws.send(_rewrite_vertex_live_setup_model(text_data, setup_model_rewriter)) - if meter is not None: - metered_total += meter.measure(text_data) + if isinstance( + await _relay_client_frame( + websocket, + upstream_ws, + text_data, + _rewrite_vertex_live_setup_model(text_data, setup_model_rewriter), + client_frame_model_gate, + ledger, + ), + _RefuseClientFrame, + ): + break + metered_total += _metered_client_text(meter, text_data) elif bytes_data is not None: - await upstream_ws.send(bytes_data) + if isinstance( + await _relay_client_frame( + websocket, upstream_ws, bytes_data, bytes_data, client_frame_model_gate, ledger + ), + _RefuseClientFrame, + ): + break + if not _turn_owed(upstream_frame_kind, websocket_messages, ledger): + await upstream_ws.close() except asyncio.CancelledError: raise except Exception: @@ -2902,11 +3395,7 @@ async def websocket_passthrough_request( is_vertex_live: Final = bool(endpoint and "/vertex_ai/live" in endpoint) json_frame_ordinal: Final = count() - async def relay_upstream_frame(upstream_message: str | bytes) -> None: - if isinstance(upstream_message, bytes): - await websocket.send_bytes(upstream_message) - else: - await websocket.send_text(upstream_message) + def record_upstream_frame(upstream_message: str | bytes) -> None: message_data: Final = _json_object_frame(upstream_message) if message_data is None: return @@ -2914,6 +3403,43 @@ async def websocket_passthrough_request( _extract_vertex_live_model_from_setup_response(message_data) return websocket_messages.append(message_data) + match None if upstream_frame_kind is None else upstream_frame_kind(message_data): + case "opens_session": + ledger.open_session() + case "starts_turn": + ledger.start_turn() + case "updates_session" if upstream_frame_kind is not None: + websocket_messages[:] = _without_earlier_session_updates( + upstream_frame_kind, websocket_messages, message_data + ) + case "ends_turn" if upstream_frame_kind is not None: + if _frame_lane(message_data) not in _lanes_in_flight(upstream_frame_kind, websocket_messages): + ledger.start_turn() + log_turn(_frame_lane(message_data), _frames_of_lane(_frame_lane(message_data))) + case "bills_usage" if not _turn_in_flight(upstream_frame_kind, websocket_messages): + log_turn(_frame_lane(message_data), _frames_of_lane(_frame_lane(message_data))) + case "refuses_turn" if upstream_frame_kind is not None: + lane: Final = _frame_lane(message_data) + ledger.drop_refused_turn( + lane, lane in _lanes_in_flight(upstream_frame_kind, websocket_messages) + ) + case _: + pass + + async def relay_upstream_frame(upstream_message: str | bytes) -> None: + record_upstream_frame(upstream_message) + if not _client_socket_is_open(websocket): + if not _turn_owed(upstream_frame_kind, websocket_messages, ledger): + await upstream_ws.close() + return + try: + if isinstance(upstream_message, bytes): + await websocket.send_bytes(upstream_message) + else: + await websocket.send_text(upstream_message) + except WebSocketDisconnect: + if not _turn_owed(upstream_frame_kind, websocket_messages, ledger): + raise async def forward_upstream_to_client() -> Close | None: try: @@ -2922,6 +3448,11 @@ async def websocket_passthrough_request( except (ConnectionClosedOK, ConnectionClosedError) as e: verbose_proxy_logger.debug("Upstream WebSocket connection closed: %s", e) return e.rcvd + except WebSocketDisconnect: + verbose_proxy_logger.debug( + "WebSocket passthrough (%s): client left while upstream was still sending", endpoint + ) + return None except asyncio.CancelledError: verbose_proxy_logger.debug("asyncio.CancelledError in forward_upstream_to_client") raise @@ -2933,12 +3464,15 @@ async def websocket_passthrough_request( raise # Create tasks for bidirectional message forwarding - tasks: Final = [ - asyncio.create_task(forward_client_to_upstream()), - asyncio.create_task(forward_upstream_to_client()), - ] + client_task: Final = asyncio.create_task(forward_client_to_upstream()) + upstream_task: Final = asyncio.create_task(forward_upstream_to_client()) + tasks: Final = (client_task, upstream_task) - done, pending = await asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED) + await asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED) + if client_task.done() and _turn_owed(upstream_frame_kind, websocket_messages, ledger): + await asyncio.wait((upstream_task,), timeout=walkout_turn_drain_seconds) + done: Final = tuple(task for task in tasks if task.done()) + pending: Final = tuple(task for task in tasks if not task.done()) # Cancel remaining tasks for task in pending: @@ -2961,64 +3495,17 @@ async def websocket_passthrough_request( reason=truncated_close_reason(upstream_close.reason), ) - end_time: Final = datetime.now() - - # Update passthrough logging payload with response data - passthrough_logging_payload["response_body"] = websocket_messages - passthrough_logging_payload["end_time"] = end_time - - # Remove logging_obj from kwargs to avoid duplicate keyword argument - success_kwargs: Final = kwargs.copy() - success_kwargs.pop("logging_obj", None) - - # # Add user authentication context for database logging - # if user_api_key_dict: - # success_kwargs.setdefault('litellm_params', {}) - # success_kwargs['litellm_params'].update({ - # 'proxy_server_request': { - # 'body': { - # 'user': user_api_key_dict.user_id, - # 'team_id': user_api_key_dict.team_id, - # 'end_user_id': user_api_key_dict.end_user_id, - # } - # } - # }) - # # Also add the user_api_key for direct access - # success_kwargs['user_api_key'] = user_api_key_dict.api_key - - # Create a dummy httpx.Response for WebSocket connections - class MockWebSocketResponse: - def __init__(self, target_url: str): - self.status_code = 200 - self.text = "WebSocket connection successful" - self.headers: dict[str, str] = {} - self.request = MockWebSocketRequest(target_url) - - class MockWebSocketRequest: - def __init__(self, target_url: str): - self.method = "WEBSOCKET" - self.url = target_url - - mock_response: Final = MockWebSocketResponse(target) if meter is not None: _log_session_usage(logging_obj, meter.price(metered_total)) - # Use the same success handler as HTTP passthrough endpoints - GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue( - async_coroutine=pass_through_endpoint_logging.pass_through_async_success_handler( - httpx_response=mock_response, - response_body=websocket_messages, - url_route=endpoint or "", - result="websocket_connection_successful", - start_time=start_time, - end_time=end_time, - logging_obj=logging_obj, - cache_hit=False, - request_body={}, - **success_kwargs, + if _session_end_needs_a_row(upstream_frame_kind, websocket_messages, ledger): + lanes_in_flight: Final = ( + () if upstream_frame_kind is None else _lanes_in_flight(upstream_frame_kind, websocket_messages) ) - ) - bind_budget_reservation_to_callbacks(logging_obj.litellm_params) + *earlier_lanes, last_lane = lanes_in_flight or (None,) + for lane in earlier_lanes: + log_turn(lane, _frames_of_lane(lane)) + log_turn(last_lane, _every_frame) # Call the proxy logging success hook if proxy_logging_obj: @@ -3076,6 +3563,7 @@ async def websocket_passthrough_request( if _client_socket_is_open(websocket): await websocket.close(code=1011, reason="WebSocket passthrough error") finally: + await proxy_logging_obj.arelease_responses_websocket_slot(user_api_key_dict) if _client_socket_is_open(websocket): await websocket.close() diff --git a/litellm/proxy/pass_through_endpoints/success_handler.py b/litellm/proxy/pass_through_endpoints/success_handler.py index 8b09b1cf7cd..8f55906498b 100644 --- a/litellm/proxy/pass_through_endpoints/success_handler.py +++ b/litellm/proxy/pass_through_endpoints/success_handler.py @@ -1,5 +1,6 @@ import asyncio import json +from collections.abc import Mapping, Sequence from contextlib import suppress from datetime import datetime from types import MappingProxyType @@ -13,7 +14,7 @@ from litellm._logging import verbose_proxy_logger from litellm.constants import AZURE_SPEECH_CUSTOM_LLM_PROVIDER from litellm.litellm_core_utils.core_helpers import bind_budget_reservation_to_callbacks from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj -from litellm.proxy._types import PassThroughEndpointLoggingResultValues +from litellm.proxy._types import PassThroughEndpointLoggingResultValues, PassThroughEndpointLoggingTypedDict from litellm.types.passthrough_endpoints.pass_through_endpoints import ( PassthroughStandardLoggingPayload, ) @@ -70,6 +71,14 @@ def _safe_response_text(httpx_response: httpx.Response) -> str: return "" +def _websocket_frames( + response_body: Mapping[str, object] | Sequence[Mapping[str, object]] | None, +) -> tuple[Mapping[str, object], ...]: + return tuple( + message for message in (response_body if isinstance(response_body, list) else ()) if isinstance(message, dict) + ) + + class PassThroughEndpointLogging: def __init__( self, @@ -120,6 +129,7 @@ class PassThroughEndpointLogging: # Vertex AI Live API WebSocket self.TRACKED_VERTEX_AI_LIVE_ROUTES = ["/vertex_ai/live"] + self.TRACKED_OPENAI_WEBSOCKET_ROUTES: Final = ("/openai/", "/openai_passthrough/") @property def _log_dispatch(self) -> PassThroughLogDispatch: @@ -422,21 +432,18 @@ class PassThroughEndpointLogging: standard_logging_response_object = vertex_ai_live_handler_result["result"] kwargs = vertex_ai_live_handler_result["kwargs"] - elif DeepgramListenPassthroughLoggingHandler.is_deepgram_listen_route(url_route): - deepgram_handler_result: Final = ( - DeepgramListenPassthroughLoggingHandler().deepgram_listen_passthrough_handler( - websocket_messages=tuple( - message - for message in (response_body if isinstance(response_body, list) else ()) - if isinstance(message, dict) - ), - logging_obj=logging_obj, - upstream_url=str(httpx_response.request.url), - kwargs=kwargs, - ) + elif ( + websocket_relay_result := self._websocket_relay_logging_result( + url_route=url_route, + websocket_frames=_websocket_frames(response_body), + logging_obj=logging_obj, + httpx_response=httpx_response, + start_time=start_time, + kwargs=kwargs, ) - standard_logging_response_object = deepgram_handler_result["result"] # rebind-ok: elif-chain - kwargs = deepgram_handler_result["kwargs"] # rebind-ok: elif-chain contract + ) is not None: + standard_logging_response_object = websocket_relay_result["result"] # rebind-ok: elif-chain + kwargs = websocket_relay_result["kwargs"] # rebind-ok: elif-chain contract elif FalAIPassthroughLoggingHandler.is_fal_ai_route(url_route, custom_llm_provider): fal_ai_handler_result: Final = FalAIPassthroughLoggingHandler().fal_ai_passthrough_handler( response_body=response_body if isinstance(response_body, dict) else MappingProxyType({}), @@ -452,6 +459,36 @@ class PassThroughEndpointLogging: return_dict["kwargs"] = kwargs return return_dict + def _websocket_relay_logging_result( + self, + url_route: str, + websocket_frames: tuple[Mapping[str, object], ...], + logging_obj: LiteLLMLoggingObj, + httpx_response: httpx.Response, + start_time: datetime, + kwargs: Mapping[str, object], + ) -> PassThroughEndpointLoggingTypedDict | None: + if self.is_openai_websocket_route(url_route): + from .llm_provider_handlers.openai_websocket_passthrough_logging_handler import ( + OpenAIWebsocketPassthroughLoggingHandler, + ) + + return OpenAIWebsocketPassthroughLoggingHandler().openai_websocket_passthrough_handler( + websocket_messages=websocket_frames, + logging_obj=logging_obj, + url_route=url_route, + start_time=start_time, + kwargs=kwargs, + ) + if DeepgramListenPassthroughLoggingHandler.is_deepgram_listen_route(url_route): + return DeepgramListenPassthroughLoggingHandler().deepgram_listen_passthrough_handler( + websocket_messages=websocket_frames, + logging_obj=logging_obj, + upstream_url=str(httpx_response.request.url), + kwargs=kwargs, + ) + return None + async def pass_through_async_success_handler( self, httpx_response: httpx.Response, @@ -625,6 +662,9 @@ class PassThroughEndpointLogging: return True return False + def is_openai_websocket_route(self, url_route: str) -> bool: + return url_route.startswith(self.TRACKED_OPENAI_WEBSOCKET_ROUTES) + def is_cursor_route(self, url_route: str, custom_llm_provider: str | None = None): """Check if the URL route is a Cursor Cloud Agents API route.""" if custom_llm_provider == "cursor": diff --git a/litellm/proxy/proxy_cli.py b/litellm/proxy/proxy_cli.py index 0fbfa0b06a7..0c89627e74d 100644 --- a/litellm/proxy/proxy_cli.py +++ b/litellm/proxy/proxy_cli.py @@ -23,7 +23,7 @@ from typing_extensions import ReadOnly, TypedDict import litellm from litellm._logging import StartupOutputSettings, print_startup_message, print_startup_warning, terminal_text -from litellm.constants import DEFAULT_NUM_WORKERS_LITELLM_PROXY +from litellm.constants import DEFAULT_MAX_REQUEST_HEADER_SIZE, DEFAULT_NUM_WORKERS_LITELLM_PROXY from litellm.proxy.db.pgbouncer import ( PgBouncerError, PgBouncerSettings, @@ -409,6 +409,7 @@ class ProxyInitializationHelpers: log_config: str | None = None, keepalive_timeout: int | None = None, timeout_worker_healthcheck: int | None = None, + max_request_header_size: int | None = None, ) -> dict: """ Get the arguments for `uvicorn` worker @@ -427,6 +428,9 @@ class ProxyInitializationHelpers: "port": port, "server_header": False, "timeout_graceful_shutdown": GracefulShutdownManager.get_timeout(), + "h11_max_incomplete_event_size": ( + max_request_header_size if max_request_header_size is not None else DEFAULT_MAX_REQUEST_HEADER_SIZE + ), } if log_config is not None: print_startup_message(f"Using log_config: {log_config}") @@ -680,6 +684,7 @@ class ProxyInitializationHelpers: ssl_keyfile_path: str, max_requests_before_restart: int | None = None, max_requests_before_restart_jitter: int | None = None, + max_request_header_size: int | None = None, ): """ Run litellm with `gunicorn` @@ -754,7 +759,7 @@ class ProxyInitializationHelpers: gunicorn_options: Final = { "bind": f"{host}:{port}", "workers": num_workers, # default is 1 - "worker_class": build_graceful_shutdown_uvicorn_worker(graceful_shutdown_timeout), + "worker_class": build_graceful_shutdown_uvicorn_worker(graceful_shutdown_timeout, max_request_header_size), "graceful_timeout": math.ceil(graceful_shutdown_timeout) + GRACEFUL_SHUTDOWN_TEARDOWN_HEADROOM_SECONDS, "preload": True, # Add the preload flag, "accesslog": "-", # Log to stdout @@ -1108,6 +1113,18 @@ class ProxyInitializationHelpers: help="Set the uvicorn keepalive timeout in seconds (uvicorn timeout_keep_alive parameter)", envvar="KEEPALIVE_TIMEOUT", ) +@click.option( + "--max_request_header_size", + default=None, + show_default=f"{DEFAULT_MAX_REQUEST_HEADER_SIZE} bytes with h11", + type=click.IntRange(min=1), + help=( + "Maximum bytes buffered for an incomplete HTTP request header block. " + "Applies when uvicorn or --run_gunicorn uses h11. Parser selection is unchanged; httptools ignores this setting. " + "Ignored under --run_hypercorn / --run_granian." + ), + envvar="MAX_REQUEST_HEADER_SIZE", +) @click.option( "--timeout_worker_healthcheck", default=None, @@ -1253,6 +1270,7 @@ def run_server( check_migrations_against_existing_data: bool, keepalive_timeout, timeout_worker_healthcheck, + max_request_header_size: int | None, max_requests_before_restart: int | None, max_requests_before_restart_jitter: int | None, limit_concurrency: int | None, @@ -1747,6 +1765,7 @@ def run_server( log_config=log_config, keepalive_timeout=keepalive_timeout, timeout_worker_healthcheck=(timeout_worker_healthcheck if running_uvicorn else None), + max_request_header_size=max_request_header_size, ) # Optional: recycle uvicorn workers after N requests if max_requests_before_restart is not None: @@ -1821,6 +1840,7 @@ def run_server( ssl_keyfile_path=ssl_keyfile_path, max_requests_before_restart=max_requests_before_restart, max_requests_before_restart_jitter=max_requests_before_restart_jitter, + max_request_header_size=max_request_header_size, ) elif run_hypercorn is True: ProxyInitializationHelpers.init_hypercorn_server( diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index c5fcbfb2564..c1af5d6f980 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -6,6 +6,7 @@ import importlib import inspect import io import itertools +import logging import os import random import re @@ -26,6 +27,7 @@ from collections.abc import ( Collection, Container, Iterable, + Iterator, Mapping, MutableMapping, Sequence, @@ -33,7 +35,7 @@ from collections.abc import ( from collections.abc import ( Set as AbstractSet, ) -from dataclasses import dataclass +from dataclasses import dataclass, replace from datetime import datetime, timedelta, timezone from itertools import chain from types import MappingProxyType, TracebackType, UnionType @@ -59,8 +61,11 @@ import anyio import anyio.lowlevel import websockets import websockets.exceptions +from openai.types.audio import TranscriptionStreamEvent from pydantic import BaseModel, ConfigDict, Json, JsonValue, TypeAdapter, ValidationError, with_config from pydantic.fields import FieldInfo, PydanticUndefined +from pydantic.main import IncEx +from pydantic_core import PydanticSerializationError, to_jsonable_python from typing_extensions import NotRequired, ReadOnly, TypedDict, assert_never from litellm._uuid import uuid @@ -88,6 +93,7 @@ from litellm.constants import ( LITELLM_UI_SESSION_DURATION, OPENAI_LIVE_SESSION_START_TIMEOUT_SECONDS, RUNTIME_UPDATABLE_ROUTER_SETTINGS, + VLLM_CHOICE_FIELDS, ) from litellm.litellm_core_utils.access_windows import access_windows_config_error from litellm.litellm_core_utils.add_retry_fallback_headers import ( @@ -105,6 +111,7 @@ from litellm.litellm_core_utils.litellm_logging import ( initialize_sentry, ) from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER, LoggingWorker +from litellm.litellm_core_utils.prompt_templates.chat_template_tools import chat_template_tool_section from litellm.litellm_core_utils.routing_common_utils import resolve_model_group_alias from litellm.litellm_core_utils.routing_groups import parse_routing_groups from litellm.litellm_core_utils.safe_json_dumps import safe_dumps @@ -113,6 +120,7 @@ from litellm.litellm_core_utils.token_counter import ( UnsupportedContentTypeError, deployment_openai_model, offload_token_count, + sends_function_tools, ) from litellm.llms.bedrock.count_tokens.kimi_k3 import ( HUGGING_FACE_SOURCE, @@ -197,9 +205,11 @@ from litellm.router_strategy.auto_router.auto_router_tuning_baseline import ( snapshot_tuning_baselines, tuning_limit_violation, ) +from litellm.rust_bridge.catalog import Target from litellm.types.caching import RedisPipelineIncrementOperation from litellm.types.utils import ( PRICING_OVERRIDES_KEY, + CallTypes, CountContextManagement, LlmProviders, ModelResponse, @@ -207,6 +217,7 @@ from litellm.types.utils import ( TextCompletionResponse, TokenCountMessagesFormat, TokenCountResponse, + TranscriptionResponse, echoed_cost_map_pricing_fields, is_server_derived_pricing_key, pricing_override_fields, @@ -316,6 +327,7 @@ from litellm._internal_context import service_target, with_service_target from litellm._logging import ( STARTUP_OUTPUT_SETTINGS, print_startup_message, + redact_internal_details_from_client_message, redact_string, verbose_proxy_logger, verbose_router_logger, @@ -365,6 +377,11 @@ from litellm.integrations.SlackAlerting.slack_alerting import SlackAlerting from litellm.litellm_core_utils.agentic_loop_settings import ( validated_max_agentic_loops, ) +from litellm.litellm_core_utils.audio_utils.transcription_streaming import ( + TRANSCRIPTION_STREAM_DONE_FRAME, + GuardedTranscriptionReplay, + guarded_transcription_events, +) from litellm.litellm_core_utils.audio_utils.utils import resolve_speech_media_type from litellm.litellm_core_utils.core_helpers import ( as_str_mapping, @@ -387,6 +404,12 @@ from litellm.litellm_core_utils.sensitive_data_masker import ( mask_sensitive_keys, ) from litellm.litellm_core_utils.stream_usage_chunks import is_injected_stream_usage_artifact +from litellm.llms.anthropic.messages.context_management.inference_view import ( + InferenceRequestView, + InferenceRequestViewError, + count_context_edits, + inference_request_view, +) from litellm.llms.anthropic.messages.convertible_blocks import ( deployment_drops_params, drop_non_string_tool_result_texts, @@ -397,12 +420,17 @@ from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler from litellm.llms.openai.live import parse_live_session_start from litellm.llms.openai_like.model_info import MODEL_INFO_REFRESH_SECONDS from litellm.llms.vertex_ai.vertex_llm_base import VertexBase +from litellm.messages.dispatch import messages_target from litellm.proxy._lazy_features import attach_lazy_features, reserve_lazy_slot from litellm.proxy._types import * from litellm.proxy.agent_endpoints.auth.agent_access_groups import CeilingResolver, resolve_agent_access_group_ceiling +from litellm.proxy.alerting_endpoints.model_deprecation_alerts import ( + router as model_deprecation_alerts_router, +) from litellm.proxy.analytics_endpoints.analytics_endpoints import ( router as analytics_router, ) +from litellm.proxy.anthropic_endpoints.answered_status import is_provider_overload from litellm.proxy.auth.auth_checks import ( ROLE_BASED_PERMISSIONS_ADAPTER, ExperimentalUIJWTToken, @@ -456,6 +484,7 @@ from litellm.proxy.auth.user_api_key_auth import ( # noqa: F401, RUF100 # lega user_api_key_auth, user_api_key_auth_accepted_websocket_for_model, user_api_key_auth_live_websocket, + user_api_key_auth_realtime_websocket, user_api_key_auth_websocket, ) from litellm.proxy.batches_endpoints.endpoints import router as batches_router @@ -473,12 +502,18 @@ from litellm.proxy.common_request_processing import ( # noqa: F401, RUF100 # l is_azure_model_router_request, log_llm_api_exception, open_sse_before_first_byte, + proxy_exception_from_http_exception, proxy_exception_from_route_error, resolve_litellm_call_id, should_return_raw_model_name, sse_error_payload, ttft_keepalive_interval, ) +from litellm.proxy.common_utils.anthropic_error_payload import ( + anthropic_error_json_response, + anthropic_internal_server_error_response, + uses_anthropic_error_envelope, +) from litellm.proxy.common_utils.auth_cache_invalidation_pubsub import ( AuthCacheInvalidationSubscriber, ) @@ -500,6 +535,7 @@ from litellm.proxy.common_utils.encrypt_decrypt_utils import ( encrypt_value_helper, ) from litellm.proxy.common_utils.error_body_call_id import JSON_OBJECT, error_body_call_id, with_call_id +from litellm.proxy.common_utils.fips import enforce_fips_mode from litellm.proxy.common_utils.healthy_model_filter import ( get_hidden_unhealthy_model_names, is_healthy_only_listing_default, @@ -515,6 +551,9 @@ from litellm.proxy.common_utils.http_parsing_utils import ( # noqa: F401, RUF10 resolve_inference_model, safe_get_request_headers, ) +from litellm.proxy.common_utils.http_parsing_utils import ( + resolve_realtime_route_model as _resolve_realtime_route_model, +) from litellm.proxy.common_utils.load_config_utils import get_config_from_bucket from litellm.proxy.common_utils.model_deprecation import collect_model_deprecations from litellm.proxy.common_utils.model_listing_utils import ( @@ -534,9 +573,11 @@ from litellm.proxy.common_utils.openai_endpoint_utils import ( from litellm.proxy.common_utils.openai_error_payload import ( LITELLM_CALL_ID_HEADER, attribute_of, + error_status_code, headers_with_litellm_call_id, litellm_call_id_headers, openai_error_param, + openai_error_type, proxy_exception_for, route_failure_proxy_exception, with_litellm_call_id, @@ -575,6 +616,7 @@ from litellm.proxy.common_utils.token_count_log import ( ) from litellm.proxy.common_utils.user_api_key_cache import ( UserApiKeyCache, + budget_windows_absent_cache_key, end_user_cache_key, get_management_object_ttl, model_access_group_cache_key, @@ -840,8 +882,6 @@ from litellm.proxy.spend_tracking.spend_event_producer import ( SpendEventProducer, build_spend_event_producer, ) -from litellm.proxy.spend_tracking.usage_capture import UsageBatchWriter, UsageCaptureRuntime -from litellm.proxy.spend_tracking.usage_meter import UsageCaptureSettings from litellm.proxy.telemetry.endpoints import router as telemetry_router from litellm.proxy.telemetry.middleware import TelemetryMiddleware from litellm.proxy.telemetry.runtime import TelemetryRuntime @@ -997,6 +1037,7 @@ from litellm.proxy.video_endpoints.endpoints import router as video_router from litellm.repositories.base_repository import SupportsModelDump from litellm.repositories.credentials_repository import CredentialsRepository from litellm.repositories.prisma_protocols import TableActions +from litellm.responses.main import provider_stores_the_conversation from litellm.responses.streaming_iterator import drain_logging_tasks from litellm.router import ( AssistantsTypedDict, @@ -1148,6 +1189,27 @@ server_root_path: Final = get_server_root_path() _license_check = LicenseCheck() premium_user: bool = _license_check.is_premium() premium_user_data: Optional["EnterpriseLicenseData"] = _license_check.airgapped_license_data + + +def _set_premium_user(is_premium: bool) -> None: + global premium_user, premium_user_data + premium_user = is_premium # rebind-ok: config load can switch the license in use + premium_user_data = _license_check.airgapped_license_data # rebind-ok: tracks the license in use + + +def _use_config_license(config_license: str, env_license_is_premium: bool) -> bool: + env_license: Final = _license_check.license_str + env_license_data: Final = _license_check.airgapped_license_data + _license_check.license_str = config_license + if _license_check.is_premium(): + return True + if not env_license_is_premium: + return False + _license_check.license_str = env_license + _license_check.airgapped_license_data = env_license_data + return True + + global_max_parallel_request_retries_env: Final[str | None] = os.getenv("LITELLM_GLOBAL_MAX_PARALLEL_REQUEST_RETRIES") proxy_state: Final = ProxyState() SENSITIVE_DATA_MASKER: Final = SensitiveDataMasker() @@ -1333,7 +1395,6 @@ async def _flush_spend_around_logging_drain_on_shutdown( finally: await worker.stop(discard_pending=True, timeout=GracefulShutdownManager.remaining(2.0, clock=clock)) await drain_tasks(GracefulShutdownManager.remaining(5.0, clock=clock)) - await usage_capture.stop(GracefulShutdownManager.remaining(clock=clock)) await flush_spend() @@ -1615,6 +1676,8 @@ async def _proxy_lifespan(app: FastAPI, resources: AsyncExitStack) -> AsyncGener if decoded_worker_config is not None: await initialize_from_worker_config(decoded_worker_config) + enforce_fips_mode(general_settings_view()) + async with AsyncExitStack() as boot_database: enforce_master_key_boot_verdict( await with_stored_secrets_counted( @@ -2258,6 +2321,8 @@ async def openai_exception_handler(request: Request, exc: ProxyException): # NOTE: DO NOT MODIFY THIS, its crucial to map to Openai exceptions log_model_access_denial(exc) headers: Final = exc.headers + if uses_anthropic_error_envelope(request): + return anthropic_error_json_response(exc, request) error_dict: Final = with_call_id( JSON_OBJECT.validate_python(exc.to_dict()), error_body_call_id(general_settings_view(), headers.get(LITELLM_CALL_ID_HEADER)), @@ -2293,6 +2358,10 @@ async def otlp_http_exception_handler(connection: Request | WebSocket, exc: Star if response is not None: _close_dangling_otel_server_span(connection, exc.status_code, exc=exc) return response + if uses_anthropic_error_envelope(connection): + return anthropic_error_json_response( + proxy_exception_from_http_exception(exc, dict(exc.headers or {})), connection + ) return await http_exception_handler(connection, exc) @@ -2500,6 +2569,8 @@ async def _unhandled_exception_response(request: Request, exc: Exception) -> Res otlp_response: Final = tracing_endpoints.otlp_error_response(request, 500) if otlp_response is not None: return otlp_response + if uses_anthropic_error_envelope(request): + return anthropic_internal_server_error_response(request) return JSONResponse( status_code=500, content={ @@ -2862,9 +2933,19 @@ def configured_max_request_size_mb() -> int | float | None: return MAX_REQUEST_SIZE_MB_SETTING.validate_python(general_settings.get("max_request_size_mb")) +_ROUTE_MAX_REQUEST_SIZE_MB: Final[Mapping[tuple[str, str], float]] = MappingProxyType( + { + ("POST", "/claude-code/plugins/upload"): 11, + ("POST", "/skill-hub/skills/upload"): 11, + ("PUT", "/skill-hub/skills/{name}/upload"): 11, + } +) + + app.add_middleware( RequestBodyDecompressionMiddleware, get_max_request_size_mb=lambda: configured_max_request_size_mb() if premium_user is True else None, + route_max_request_size_mb=_ROUTE_MAX_REQUEST_SIZE_MB, ) app.add_middleware( CORSMiddleware, @@ -3234,39 +3315,9 @@ def load_from_azure_key_vault(use_azure_key_vault: bool = False): spend_event_producer: SpendEventProducer | None = None -usage_capture: Final = UsageCaptureRuntime() - - -def _configure_usage_capture() -> None: - settings: Final = _GENERAL_SETTINGS_VIEW.validate_python(general_settings) - capture_settings: Final = settings.get("accounting_capture") - if settings.get("accounting_sync_ack") and capture_settings is None: - raise ValueError("accounting_sync_ack requires accounting_capture") - if capture_settings is None: - if usage_capture.meter is not None: - raise ValueError("Disabling accounting_capture requires a worker restart") - return - if ( - prisma_client is None - or CollectorSettings().enabled - or os.getenv("SPEND_LOGS_URL") - or litellm.apply_search_free_tier - ): - raise ValueError( - "Usage capture requires local Prisma writes and disabled collector, remote writer and search free tier" - ) - from litellm.proxy.db.accounting_ledger import AccountingLedger - - ledger: Final = AccountingLedger.for_client(prisma_client) - writer: Final = UsageBatchWriter(ledger.insert_usage_batch, ledger.load_usage_batch) - usage_capture.start( - writer.write, UsageCaptureSettings.model_validate(capture_settings), load=ledger.load_usage_batch - ) - def cost_tracking(): global prisma_client, spend_event_producer - _configure_usage_capture() if prisma_client is not None: from litellm.integrations.shadow_eval_logger import ShadowEvalLogger @@ -3574,6 +3625,7 @@ async def increment_spend_counters( request_started_at: datetime | None = None, model_access_groups: Sequence[str] | None = None, project_id: str | None = None, + windows_from_ledger: bool = False, ): """ Atomically increment spend counters for budget enforcement. @@ -3610,6 +3662,7 @@ async def increment_spend_counters( request_started_at=request_started_at, model_access_groups=model_access_groups, project_id=project_id, + windows_from_ledger=windows_from_ledger, ) @@ -3622,6 +3675,96 @@ def _cached_budget_limits(cached: object) -> object: return _UNTYPED_VALUE.validate_python(json.loads(stored)) if isinstance(stored, str) else stored +def _has_budget_windows(budget_limits: object) -> bool: + return isinstance(budget_limits, list) and budget_limits != [] + + +def _budget_windows_absent_marker(absent_key: str) -> object: + return _UNTYPED_VALUE.validate_python(user_api_key_cache.budget_windows_absent_cache.get_cache(key=absent_key)) + + +def _finish_pending_read(absent_key: str, pending_read: str, remember_absent: bool) -> None: + if _budget_windows_absent_marker(absent_key) != pending_read: + return + if remember_absent: + user_api_key_cache.budget_windows_absent_cache.set_cache(key=absent_key, value=True) + return + user_api_key_cache.budget_windows_absent_cache.delete_cache(absent_key) + + +async def accounting_window_keys(token: str | None, team_id: str | None) -> tuple[Mapping[str, object], ...]: + scopes: Final = tuple( + (entity_type, entity_id, cache_key) + for entity_type, entity_id, cache_key in ( + (Litellm_EntityType.KEY, token, token), + (Litellm_EntityType.TEAM, team_id, f"team_id:{team_id}"), + ) + if entity_id is not None and cache_key is not None + ) + snapshots: Final = tuple( + [ + await _accounting_scope_windows(entity_type, entity_id, cache_key) + for entity_type, entity_id, cache_key in scopes + ] + ) + from itertools import chain + + return tuple(chain.from_iterable(snapshots)) + + +async def _accounting_scope_windows( + entity_type: Litellm_EntityType, entity_id: str, cache_key: str +) -> tuple[Mapping[str, object], ...]: + from litellm.proxy.spend_tracking.budget_reservation import fixed_budget_window + + cached: Final[object] = _UNTYPED_VALUE.validate_python(await user_api_key_cache.async_get_cache(key=cache_key)) + limits: Final = ( + await _stored_budget_limits(entity_type, entity_id) if cached is None else _cached_budget_limits(cached) + ) + if not isinstance(limits, list): + return () + windows: Final = TypeAdapter(tuple[object, ...]).validate_python(limits) + return tuple( + { + "entity_type": entity_type.value, + "entity_id": entity_id, + "window_duration": fixed[0], + "window_start": fixed[1].isoformat(), + } + for window in windows + if (fixed := fixed_budget_window(window)) is not None + ) + + +async def _stored_budget_limits(entity_type: Litellm_EntityType, entity_id: str) -> object: + """Read only: caching the row here could race a delete and put a just-deleted key back into the auth cache.""" + if prisma_client is None: + return None + absent_key: Final = budget_windows_absent_cache_key(entity_type.value, entity_id) + if _budget_windows_absent_marker(absent_key) is True: + return None + pending_read: Final = f"reading:{secrets.token_hex(8)}" + user_api_key_cache.budget_windows_absent_cache.set_cache(key=absent_key, value=pending_read) + try: + row: Final[SupportsModelDump | None] = ( + await VerificationTokenRepository(prisma_client).table.find_unique(where={"token": entity_id}) + if entity_type == Litellm_EntityType.KEY + else await TeamRepository(prisma_client).table.find_unique(where={"team_id": entity_id}) + ) + except Exception as e: # noqa: BLE001 # spend tracking must never fail the cost callback + verbose_proxy_logger.warning( + "Unable to read budget windows for %s=%s; this request's window spend is not counted: %s", + entity_type.value, + entity_id, + e, + ) + _finish_pending_read(absent_key, pending_read, remember_absent=False) + return None + budget_limits: Final[object] = None if row is None else _cached_budget_limits(row) + _finish_pending_read(absent_key, pending_read, remember_absent=not _has_budget_windows(budget_limits)) + return budget_limits + + async def _increment_spend_counters_batched( token: str | None, team_id: str | None, @@ -3634,6 +3777,7 @@ async def _increment_spend_counters_batched( request_started_at: datetime | None, model_access_groups: Sequence[str] | None, project_id: str | None = None, + windows_from_ledger: bool = False, ): """Runs inside one spend counter batch: the reservation reconcile and the warm checks share a single MGET, and the reconcile adjustments go out in the same INCRBYFLOAT pipeline as the counter increments.""" @@ -3652,7 +3796,69 @@ async def _increment_spend_counters_batched( cost: Final[float] = response_cost - async def _key_scope(key_token: str) -> tuple[PendingSpendIncrement | BaseException, ...]: + async def _window_increment( + entity_type: Litellm_EntityType, entity_id: str, window: object + ) -> PendingSpendIncrement | None: + duration: Final = ( + window["budget_duration"] if isinstance(window, dict) else getattr(window, "budget_duration", None) + ) + window_reset_at: Final = ( + window.get("reset_at") if isinstance(window, dict) else getattr(window, "reset_at", None) + ) + window_counter: Final = f"spend:{entity_type.value}:{entity_id}:window:{duration}" + window_start: Final = get_budget_window_start(window) + pending_window: Final = ( + await _prepare_window_spend_counter_increment( + counter_key=window_counter, + entity_type=entity_type.value.capitalize(), + entity_id=entity_id, + window_duration=duration, + window_start=window_start, + increment=cost, + ) + if window_counter not in reserved_counter_keys + else None + ) + if not windows_from_ledger: + await _enqueue_window_spend_row_update( + entity_type=entity_type, + entity_id=entity_id, + reset_at=window_reset_at, + window_duration=duration, + window_start=window_start, + increment=cost, + request_started_at=request_started_at, + ) + return pending_window + + async def _window_increments( + entity_type: Litellm_EntityType, entity_id: str, budget_limits: object + ) -> tuple[PendingSpendIncrement | BaseException, ...]: + if not isinstance(budget_limits, list): + return () + window_pending: Final = await asyncio.gather( + *(_window_increment(entity_type, entity_id, window) for window in budget_limits), return_exceptions=True + ) + return tuple(item for item in window_pending if item is not None) + + async def _cached_window_increments( + entity_type: Litellm_EntityType, entity_id: str, cache_key: str + ) -> tuple[_SpendScopeItem, ...]: + cached: Final[object] = _UNTYPED_VALUE.validate_python(await user_api_key_cache.async_get_cache(key=cache_key)) + if cached is None: + return (_UncachedBudgetWindows(entity_type=entity_type, entity_id=entity_id),) + return await _window_increments(entity_type, entity_id, _cached_budget_limits(cached)) + + async def _stored_window_increments( + uncached: _UncachedBudgetWindows, + ) -> tuple[PendingSpendIncrement | BaseException, ...]: + return await _window_increments( + uncached.entity_type, + uncached.entity_id, + await _stored_budget_limits(uncached.entity_type, uncached.entity_id), + ) + + async def _key_scope(key_token: str) -> tuple[_SpendScopeItem, ...]: # key_token arrives pre-hashed from metadata["user_api_key"] (auth flow # hashes raw "sk-..." keys before they reach the callback). The # startswith("sk-") check is a safety net matching update_cache — @@ -3675,52 +3881,9 @@ async def _increment_spend_counters_batched( ) ) - async def _key_window_increment(window: object) -> PendingSpendIncrement | None: - duration = ( - window["budget_duration"] if isinstance(window, dict) else getattr(window, "budget_duration", None) - ) - key_window_reset_at = ( - window.get("reset_at") if isinstance(window, dict) else getattr(window, "reset_at", None) - ) - key_window_counter: Final = f"spend:key:{hashed_token}:window:{duration}" - key_window_start = get_budget_window_start(window) - pending_window: Final = ( - await _prepare_window_spend_counter_increment( - counter_key=key_window_counter, - entity_type="Key", - entity_id=hashed_token, - window_duration=duration, - window_start=key_window_start, - increment=cost, - ) - if key_window_counter not in reserved_counter_keys - else None - ) - await _enqueue_window_spend_row_update( - entity_type=Litellm_EntityType.KEY, - entity_id=hashed_token, - reset_at=key_window_reset_at, - window_duration=duration, - window_start=key_window_start, - increment=cost, - request_started_at=request_started_at, - ) - return pending_window + return key_pending + await _cached_window_increments(Litellm_EntityType.KEY, hashed_token, hashed_token) - key_obj: Final[object] = _UNTYPED_VALUE.validate_python( - await user_api_key_cache.async_get_cache(key=hashed_token) - ) - if key_obj is None: - return key_pending - key_budget_limits: Final = _cached_budget_limits(key_obj) - if not isinstance(key_budget_limits, list): - return key_pending - window_pending: Final = await asyncio.gather( - *(_key_window_increment(window) for window in key_budget_limits), return_exceptions=True - ) - return key_pending + tuple(item for item in window_pending if item is not None) - - async def _team_scope(scope_team_id: str) -> tuple[PendingSpendIncrement | BaseException, ...]: + async def _team_scope(scope_team_id: str) -> tuple[_SpendScopeItem, ...]: team_counter_key: Final = f"spend:team:{scope_team_id}" team_pending: Final[tuple[PendingSpendIncrement, ...]] = ( () @@ -3734,50 +3897,9 @@ async def _increment_spend_counters_batched( ) ) - async def _team_window_increment(window: object) -> PendingSpendIncrement | None: - duration = ( - window["budget_duration"] if isinstance(window, dict) else getattr(window, "budget_duration", None) - ) - team_window_reset_at = ( - window.get("reset_at") if isinstance(window, dict) else getattr(window, "reset_at", None) - ) - team_window_counter: Final = f"spend:team:{scope_team_id}:window:{duration}" - team_window_start = get_budget_window_start(window) - pending_window: Final = ( - await _prepare_window_spend_counter_increment( - counter_key=team_window_counter, - entity_type="Team", - entity_id=scope_team_id, - window_duration=duration, - window_start=team_window_start, - increment=cost, - ) - if team_window_counter not in reserved_counter_keys - else None - ) - await _enqueue_window_spend_row_update( - entity_type=Litellm_EntityType.TEAM, - entity_id=scope_team_id, - reset_at=team_window_reset_at, - window_duration=duration, - window_start=team_window_start, - increment=cost, - request_started_at=request_started_at, - ) - return pending_window - - team_obj: Final[object] = _UNTYPED_VALUE.validate_python( - await user_api_key_cache.async_get_cache(key=f"team_id:{scope_team_id}") + return team_pending + await _cached_window_increments( + Litellm_EntityType.TEAM, scope_team_id, f"team_id:{scope_team_id}" ) - if team_obj is None: - return team_pending - team_budget_limits: Final = _cached_budget_limits(team_obj) - if not isinstance(team_budget_limits, list): - return team_pending - window_pending: Final = await asyncio.gather( - *(_team_window_increment(window) for window in team_budget_limits), return_exceptions=True - ) - return team_pending + tuple(item for item in window_pending if item is not None) async def _team_member_scope( scope_user_id: str, scope_team_id: str @@ -3848,22 +3970,30 @@ async def _increment_spend_counters_batched( # return_exceptions so a failing scope does not leave its siblings running # as orphaned tasks that race the caller's reservation-counter invalidation; # all scopes settle, then the first error propagates as before. - scope_results: Final = await asyncio.gather(*scope_coros, return_exceptions=True) - scope_errors: Final = tuple( - item - for scope in scope_results - for item in (scope if isinstance(scope, tuple) else (scope,)) - if isinstance(item, BaseException) + scope_items: Final = tuple(_flatten_spend_scopes(await asyncio.gather(*scope_coros, return_exceptions=True))) + uncached_windows: Final = tuple(item for item in scope_items if isinstance(item, _UncachedBudgetWindows)) + await _apply_spend_counter_increments( + pending=reservation_update.pending + + tuple(item for item in scope_items if isinstance(item, PendingSpendIncrement)) ) - pending: Final = tuple( - item - for scope in scope_results - if not isinstance(scope, BaseException) - for item in scope - if not isinstance(item, BaseException) + stored_window_items: Final = ( + tuple( + _flatten_spend_scopes( + await asyncio.gather( + *(_stored_window_increments(uncached) for uncached in uncached_windows), return_exceptions=True + ) + ) + ) + if uncached_windows + else () ) - await _apply_spend_counter_increments(pending=reservation_update.pending + pending) + stored_window_pending: Final = tuple( + item for item in stored_window_items if isinstance(item, PendingSpendIncrement) + ) + if stored_window_pending: + await _apply_spend_counter_increments(pending=stored_window_pending) stamp_budget_reservation_actual_cost(budget_reservation=budget_reservation, actual_cost=response_cost) + scope_errors: Final = tuple(item for item in scope_items + stored_window_items if isinstance(item, BaseException)) if scope_errors: raise scope_errors[0] @@ -3871,6 +4001,25 @@ async def _increment_spend_counters_batched( budget_reservation["finalized"] = True +@dataclass(frozen=True, slots=True) +class _UncachedBudgetWindows: + entity_type: Litellm_EntityType + entity_id: str + + +_SpendScopeItem: TypeAlias = PendingSpendIncrement | BaseException | _UncachedBudgetWindows + + +def _flatten_spend_scopes( + scope_results: Sequence[tuple[_SpendScopeItem, ...] | BaseException], +) -> Iterator[_SpendScopeItem]: + for scope in scope_results: + if isinstance(scope, BaseException): + yield scope + continue + yield from scope + + @dataclass(frozen=True, slots=True) class _ReservationCounterUpdate: """The reserved counters the direct increment must skip, and the adjustments that settle them on the actual @@ -5651,11 +5800,18 @@ def _with_config_file_pass_through_endpoints( def _reload_settings_store(section: Section, store: SettingsStore, section_config: object) -> None: serving_pass_throughs: Final = store.get("pass_through_endpoints") store.load_yaml(_as_settings_mapping(section_config)) - store.apply_db_row(section, _EMPTY_SETTINGS_MAPPING) if is_resource_list(section, "pass_through_endpoints") and serving_pass_throughs is not None: store["pass_through_endpoints"] = serving_pass_throughs +def _general_settings_row_is_readable(row: _ConfigParamValueRow | None) -> bool: + return row is None or row.param_value is None or isinstance(row.param_value, Mapping) + + +def _db_managed_general_settings_keys() -> frozenset[str]: + return frozenset((*ConfigGeneralSettings.model_fields, *_CLEANUP_SCHEDULE_KEYS, "allowed_ips", "email_settings")) + + def _bind_general_settings_store(settings: SettingsStore) -> None: global general_settings general_settings = settings # pyright: ignore[reportAssignmentType] # legacy global accepts mappings @@ -5806,7 +5962,9 @@ class ProxyConfig: # whether an existing request predates the prices it just fetched, and re-serving one # costs a single fetch where skipping one leaves it priced wrong indefinitely self.model_cost_map_applied_revision: int = 0 - self.settings: Final[SettingsStore] = SettingsStore("general_settings") + self.settings: Final[SettingsStore] = SettingsStore( + "general_settings", managed_db_keys=_db_managed_general_settings_keys() + ) self.router_settings: Final[SettingsStore] = SettingsStore("router_settings") self.litellm_settings: Final[SettingsStore] = SettingsStore("litellm_settings") self.environment_variables: Final[SettingsStore] = SettingsStore("environment_variables") @@ -5817,6 +5975,8 @@ class ProxyConfig: self._db_environment_keys: frozenset[str] = frozenset() self._sso_environment_removals: frozenset[str] = frozenset() self._warned_shadowed_keys: frozenset[tuple[Section, str]] = frozenset() + self._warned_unmanaged_keys: frozenset[str] = frozenset() + self._warned_unreadable_db_general_settings: bool = False self._db_config_callback_entries: Mapping[tuple[str, str], _DbCallbackRegistration] = MappingProxyType({}) self._settings_stores: Final[Mapping[Section, SettingsStore]] = MappingProxyType( { @@ -6462,6 +6622,9 @@ class ProxyConfig: prisma_client=prisma_client, store_model_in_db=store_model_in_db, ) + else: + for section, store in self._settings_stores.items(): + store.apply_db_row(section, _EMPTY_SETTINGS_MAPPING) config = self._config_with_resolved_settings(config) @@ -6577,7 +6740,6 @@ class ProxyConfig: def _load_environment_variables(self, config: dict): ## ENVIRONMENT VARIABLES - global premium_user environment_variables: Final = config.get("environment_variables", None) if environment_variables: for key, value in environment_variables.items(): @@ -6617,7 +6779,7 @@ class ProxyConfig: # check if litellm_license in general_settings if "LITELLM_LICENSE" in environment_variables: _license_check.license_str = os.getenv("LITELLM_LICENSE", None) - premium_user = _license_check.is_premium() + _set_premium_user(_license_check.is_premium()) def _set_config_environment_variable(self, key: str, value: str) -> None: if key in os.environ and os.environ[key] != value: @@ -6669,7 +6831,6 @@ class ProxyConfig: prompt_injection_detection_obj, \ redis_usage_cache, \ store_model_in_db, \ - premium_user, \ open_telemetry_logger, \ health_check_details, \ proxy_batch_polling_interval, \ @@ -6682,6 +6843,12 @@ class ProxyConfig: self._load_environment_variables(config=config) + config_license: Final = _GENERAL_SETTINGS_VIEW.validate_python( + _GENERAL_SETTINGS_VIEW.validate_python(config).get("general_settings") or {} + ).get("litellm_license") + if isinstance(config_license, str): + _set_premium_user(_use_config_license(config_license, env_license_is_premium=premium_user)) + ## Coordination Redis (before cache init, so the explicit block wins) coordination_redis_cache: Final = self._init_coordination_redis(config=config) if coordination_redis_cache is not None: @@ -7258,7 +7425,7 @@ class ProxyConfig: allowed_ips: Final = general_settings.get("allowed_ips", None) if allowed_ips is not None and premium_user is False: raise ValueError( - "allowed_ips is an Enterprise Feature. Please add a valid LITELLM_LICENSE to your envionment." + "allowed_ips is an Enterprise Feature. Please add a valid LITELLM_LICENSE to your environment." ) ## BUDGET RESCHEDULER ## proxy_budget_rescheduler_min_time = general_settings.get( @@ -7314,11 +7481,6 @@ class ProxyConfig: if general_settings.get("enforced_params") is not None and premium_user is not True: raise ValueError("Trying to use `enforced_params`" + CommonProxyErrors.not_premium_user.value) - # check if litellm_license in general_settings - if "litellm_license" in general_settings: - _license_check.license_str = general_settings["litellm_license"] - premium_user = _license_check.is_premium() - router_params: Final[dict] = { "cache_responses": litellm.cache is not None, # cache if user passed in cache values } @@ -8340,15 +8502,20 @@ class ProxyConfig: general_settings.get("maximum_spend_logs_retention_interval", "1d"), ) - async def _update_general_settings(self, db_general_settings: Mapping[str, SettingsJsonValue] | None) -> None: + async def _update_general_settings(self, db_general_settings: Mapping[str, SettingsJsonValue] | str | None) -> None: global general_settings if db_general_settings is None: return + if not isinstance(db_general_settings, Mapping): + self._warn_about_unreadable_db_general_settings() + return + self._warned_unreadable_db_general_settings = False if not isinstance(general_settings, SettingsStore): self.settings.load_yaml(_as_settings_mapping(general_settings)) cache_size_was_db: Final = self.settings.source("user_api_key_cache_max_size") == "db" previous_cleanup_schedule: Final = self._resolved_cleanup_schedule() self.settings.apply_db_row("general_settings", db_general_settings) + self._warn_about_unmanaged_db_settings() _bind_general_settings_store(self.settings) await self._apply_general_settings_side_effects( db_general_settings, @@ -8540,12 +8707,24 @@ class ProxyConfig: environment_read: Final = next(self._environment_read_numbers) sections: Final = tuple(self._settings_stores) responses: Final = await asyncio.gather(*(get_config_param(prisma_client, section) for section in sections)) + general_settings_response: Final = responses[sections.index("general_settings")] + general_settings_value: Final[Mapping[str, SettingsJsonValue]] = ( + self._prepared_db_settings_values("general_settings", general_settings_response.param_value) + if general_settings_response is not None and general_settings_response.param_value is not None + else _EMPTY_SETTINGS_MAPPING + ) + self._settings_stores["general_settings"].apply_db_row("general_settings", general_settings_value) + response: _ConfigParamValueRow | None for section, response in zip(sections, responses): + if section == "general_settings": + continue if response is None: + self._settings_stores[section].apply_db_row(section, _EMPTY_SETTINGS_MAPPING) continue param_value: JsonValue = getattr(response, "param_value", None) if param_value is None: + self._settings_stores[section].apply_db_row(section, _EMPTY_SETTINGS_MAPPING) continue verbose_proxy_logger.debug( @@ -8556,6 +8735,7 @@ class ProxyConfig: if section == "litellm_settings": self._apply_litellm_settings_db_values(self._prepared_db_settings_values(section, param_value)) elif section == "environment_variables": + self._settings_stores[section].apply_db_row(section, _EMPTY_SETTINGS_MAPPING) await self._apply_db_environment_variables_row( prisma_client, response, environment_before_db, environment_read ) @@ -8566,6 +8746,7 @@ class ProxyConfig: ) self._warn_about_shadowed_db_settings() + self._warn_about_unmanaged_db_settings() return self._config_with_resolved_settings(config) async def _apply_db_environment_variables_row( @@ -8624,6 +8805,30 @@ class ProxyConfig: ) self._warned_shadowed_keys = shadowed + def _warn_about_unmanaged_db_settings(self) -> None: + unmanaged: Final = frozenset( + key for key in self.settings.unmanaged_db_keys() if key not in _GENERAL_SETTINGS_UI_LITELLM_FIELDS + ) + for key in sorted(unmanaged - self._warned_unmanaged_keys): + verbose_proxy_logger.warning( + "general_settings.%s is stored in the database, but the proxy does not apply that stored value, so it " + "is ignored. %s", + key, + "The config file's value applies. Remove the stored copy with POST /config/field/delete." + if self.settings.owned_by_config(key) + else "Set it in the config file to use it, or remove it with POST /config/field/delete.", + ) + self._warned_unmanaged_keys = unmanaged + + def _warn_about_unreadable_db_general_settings(self) -> None: + if self._warned_unreadable_db_general_settings: + return + verbose_proxy_logger.warning( + "general_settings is stored in the database as something other than a JSON object, so the proxy " + "ignores every stored general setting." + ) + self._warned_unreadable_db_general_settings = True + def _prepared_db_settings_values(self, section: Section, value: object) -> Mapping[str, SettingsJsonValue]: scrubbed: Final = _scrub_db_overlay_remote_module_loads(section=section, db_value=value) return _as_settings_mapping(scrubbed) @@ -8791,7 +8996,10 @@ class ProxyConfig: ) # initialize vector stores, guardrails, etc. table in db - await self._init_non_llm_objects_in_db(prisma_client=prisma_client) + await self._init_non_llm_objects_in_db( + prisma_client=prisma_client, + refresh_pass_through_endpoints=_general_settings_row_is_readable(db_general_settings), + ) except Exception as e: verbose_proxy_logger.exception("litellm.proxy.proxy_server.py::ProxyConfig:add_deployment - %s", e) @@ -8860,7 +9068,9 @@ class ProxyConfig: except Exception as e: # noqa: BLE001 # best-effort: a failing stop must not break proxy shutdown verbose_proxy_logger.error("Error stopping auth cache invalidation subscriber: %s", e) - async def _init_non_llm_objects_in_db(self, prisma_client: PrismaClient): + async def _init_non_llm_objects_in_db( + self, prisma_client: PrismaClient, *, refresh_pass_through_endpoints: bool = True + ): """ Use this to read non-llm objects from the db and initialize them @@ -8884,7 +9094,7 @@ class ProxyConfig: if self._should_load_db_object(object_type="agents"): await self._init_agents_in_db(prisma_client=prisma_client) - if self._should_load_db_object(object_type="pass_through_endpoints"): + if refresh_pass_through_endpoints and self._should_load_db_object(object_type="pass_through_endpoints"): await self._init_pass_through_endpoints_in_db() if self._should_load_db_object(object_type="prompts"): @@ -10186,6 +10396,8 @@ def _event_with_restamped_nested_model(event: Mapping[str, object], target_model _SSE_DATA_FIELD: Final = b"data:" _SSE_NESTED_RESPONSE_MARKER: Final = b'"response"' _SSE_EVENT_OBJECT: Final[TypeAdapter[Mapping[str, object]]] = TypeAdapter(Mapping[str, object]) +_JSON_OBJECT: Final = TypeAdapter(dict[object, object]) +_JSON_ARRAY: Final[TypeAdapter[tuple[object, ...]]] = TypeAdapter(tuple[object, ...]) def _restamp_nested_response_model_in_sse_frame(frame: bytes, target_model: str) -> bytes: @@ -10211,91 +10423,110 @@ def _restamp_nested_response_model_in_sse_line(line: bytes, target_model: str) - return _SSE_DATA_FIELD + b" " + serialized_event.encode() + line_ending -def _fast_serialize_simple_model_response_stream( - chunk: ModelResponseStream, -) -> bytes | None: - """ - Serialize the common OpenAI text streaming chunk without the full Pydantic - serializer. Fall back for richer chunks so tool calls, logprobs, usage, and - provider-specific fields keep the canonical model_dump_json behavior. - """ - if ( - getattr(chunk, "provider_specific_fields", None) is not None - or getattr(chunk, "system_fingerprint", None) is not None - or getattr(chunk, "usage", None) is not None - ): - return None - - choices: Final = getattr(chunk, "choices", None) - if not isinstance(choices, list) or len(choices) != 1: - return None - - choice: Final = choices[0] - if getattr(choice, "logprobs", None) is not None or getattr(choice, "enhancements", None) is not None: - return None - - delta: Final[object] = getattr(choice, "delta", None) - if delta is None: - return None - - unsupported_delta_fields: Final = ( - "function_call", - "tool_calls", - "audio", - "images", - "annotations", - "reasoning_content", - "thinking_blocks", - "provider_specific_fields", - "refusal", - ) - if any(getattr(delta, field, None) is not None for field in unsupported_delta_fields): - return None - - delta_dict: Final[dict] = {} - role: Final = getattr(delta, "role", None) - content: Final = getattr(delta, "content", None) - if role is not None: - delta_dict["role"] = role - if content is not None: - delta_dict["content"] = content - - choice_dict: Final = {"index": getattr(choice, "index", 0), "delta": delta_dict} - finish_reason: Final = getattr(choice, "finish_reason", None) - if finish_reason is not None: - choice_dict["finish_reason"] = finish_reason - - # Match the canonical ``model_dump_json(exclude_none=True)`` shape — if a - # field is None, omit it entirely rather than emitting ``"key": null``. - # Strict OpenAI-compatible clients reject ``null`` for optional fields like - # ``model``, so diverging here would surface as a client-side regression - # only on the fast path. Fall back to the slow path if a required-looking - # top-level identifier is missing. - model: Final = getattr(chunk, "model", None) - if model is None: - return None - - payload: Final[dict] = { - "id": getattr(chunk, "id", None), - "object": getattr(chunk, "object", None), - "created": getattr(chunk, "created", None), - "model": model, - "service_tier": getattr(chunk, "service_tier", None), - "choices": [choice_dict], - } - for top_level_key in ("id", "object", "created", "service_tier"): - if payload[top_level_key] is None: - payload.pop(top_level_key) - return orjson.dumps(payload) +def _vllm_choice_fields(choice: BaseModel) -> Mapping[str, object]: + choice_extras: Final = choice.model_extra or {} + return MappingProxyType({field: choice_extras[field] for field in VLLM_CHOICE_FIELDS if field in choice_extras}) -def _serialize_streaming_chunk(chunk: BaseModel) -> str | bytes: - if isinstance(chunk, ModelResponseStream): - serialized_chunk: Final = _fast_serialize_simple_model_response_stream(chunk) +def _json_encodes(value: object) -> bool: + try: + to_jsonable_python(value) + except ValueError: + return False + return True + + +def _unencodable_part(value: object, ancestors: frozenset[int]) -> IncEx | bool: + if id(value) in ancestors: + return True + lineage: Final = ancestors | {id(value)} + if isinstance(value, BaseModel): + return _unencodable_keys(iter(value), lineage) or True + if isinstance(value, dict): + return _unencodable_entries(_JSON_OBJECT.validate_python(value), lineage) + if isinstance(value, (list, tuple)): + return _unencodable_indexes(enumerate(_JSON_ARRAY.validate_python(value)), lineage) or True + return True + + +def _unencodable_entries(entries: Mapping[object, object], lineage: frozenset[int]) -> IncEx | bool: + by_name: Final = {key: item for key, item in entries.items() if isinstance(key, str)} + if len(by_name) == len(entries): + return _unencodable_keys(by_name.items(), lineage) or True + by_index: Final = {key: item for key, item in entries.items() if isinstance(key, int)} + if len(by_index) == len(entries): + return _unencodable_indexes(by_index.items(), lineage) or True + return True + + +def _unencodable_keys(items: Iterable[tuple[str, object]], lineage: frozenset[int]) -> Mapping[str, IncEx | bool]: + return {key: _unencodable_part(item, lineage) for key, item in items if not _json_encodes(item)} + + +def _unencodable_indexes(items: Iterable[tuple[int, object]], lineage: frozenset[int]) -> Mapping[int, IncEx | bool]: + return {index: _unencodable_part(item, lineage) for index, item in items if not _json_encodes(item)} + + +def _serialize_chat_chunk_leniently(chunk: ModelResponseStream) -> bytes: + exclude: Final = _unencodable_keys(iter(chunk), frozenset({id(chunk)})) + if exclude: + verbose_proxy_logger.warning("Dropping streamed chunk fields that JSON cannot encode: %s", exclude) + jsonable: Final = chunk.model_dump(mode="json", exclude_none=True, exclude_unset=True, exclude=exclude) + return json.dumps(jsonable, ensure_ascii=True, separators=(",", ":")).encode() + + +def _serialize_chat_chunk(chunk: ModelResponseStream) -> bytes: + try: + return chunk.model_dump_json(exclude_none=True, exclude_unset=True).encode() + except PydanticSerializationError: + return _serialize_chat_chunk_leniently(chunk) + + +def _serialize_streaming_chunk(chunk: BaseModel) -> bytes: + choices: Final = _streaming_chunk_choices(chunk) + null_choice_fields: Final = tuple(_null_vllm_choice_fields(choice) for choice in choices) + if any(null_choice_fields): + serialized_chunk: Final = _serialize_keeping_null_choice_fields(chunk, choices, null_choice_fields) if serialized_chunk is not None: return serialized_chunk + if isinstance(chunk, ModelResponseStream): + return _serialize_chat_chunk(chunk) + return chunk.model_dump_json(exclude_none=True, exclude_unset=True).encode() - return chunk.model_dump_json(exclude_none=True, exclude_unset=True) + +def _serialize_keeping_null_choice_fields( + chunk: BaseModel, choices: Sequence[BaseModel], null_choice_fields: Sequence[Mapping[str, None]] +) -> bytes | None: + try: + return json.dumps( + { + **_dump_set_fields(chunk, exclude=frozenset({"choices"})), + "choices": [ + {**_dump_set_fields(choice), **nulls} + for choice, nulls in zip(choices, null_choice_fields, strict=True) + ], + }, + separators=(",", ":"), + ensure_ascii=False, + ).encode() + except ValueError: + return None + + +def _streaming_chunk_choices(chunk: BaseModel) -> Sequence[BaseModel]: + match chunk: + case ModelResponseStream() | TextCompletionResponse(): + return chunk.choices + case _: + return () + + +def _null_vllm_choice_fields(choice: BaseModel) -> Mapping[str, None]: + return MappingProxyType({field: None for field, value in _vllm_choice_fields(choice).items() if value is None}) + + +def _dump_set_fields(model: BaseModel, exclude: AbstractSet[str] = frozenset()) -> Mapping[str, object]: + return model.model_dump(mode="json", exclude_none=True, exclude_unset=True, exclude=set(exclude)) async def _apply_streaming_chunk_hooks( @@ -10551,6 +10782,26 @@ def _make_keepalive_resolver(request_data: Mapping[str, object]) -> Callable[[ob return _resolve +def _transcription_sse_error_frame(client_error: Exception) -> str: + status_code: Final = error_status_code(client_error, 500) + error_returned: Final = json.dumps( + { + "error": sse_error_payload(client_error)[1] + if isinstance(client_error, HTTPException) + else ProxyException( + message=redact_internal_details_from_client_message( + str(getattr(client_error, "message", client_error)) + ), + type=openai_error_type(client_error, status_code), + param=openai_error_param(client_error), + code=status_code, + ).to_dict() + }, + default=str, + ) + return f"data: {error_returned}\n\n" + + async def async_data_generator( response, user_api_key_dict: UserAPIKeyAuth, @@ -13181,6 +13432,13 @@ async def completion( _response.choices[0].text = e.message return _response except Exception as e: + if is_provider_overload(e): + raise await base_llm_response_processor.handle_llm_api_exception( + e=e, + user_api_key_dict=user_api_key_dict, + proxy_logging_obj=proxy_logging_obj, + version=version, + ) await proxy_logging_obj.post_call_failure_hook( user_api_key_dict=user_api_key_dict, original_exception=e, @@ -13411,7 +13669,10 @@ async def moderations( return response except Exception as e: await proxy_logging_obj.post_call_failure_hook( - user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data + user_api_key_dict=user_api_key_dict, + original_exception=e, + request_data=data, + dispatched_call_type=CallTypes.amoderation.value, ) log_llm_api_exception(e, litellm_call_id) if isinstance(e, ProxyException): @@ -13556,6 +13817,7 @@ async def audio_speech( user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data, + dispatched_call_type=CallTypes.aspeech.value, ) log_llm_api_exception(e, litellm_call_id) if isinstance(e, ProxyException): @@ -13583,11 +13845,13 @@ def _form_fields_without_file(form_data: Mapping[str, object]) -> Mapping[str, o "/v1/audio/transcriptions", dependencies=[Depends(user_api_key_auth)], tags=["audio"], + responses={200: {"model": TranscriptionResponse, "content": {"text/event-stream": {"schema": {"type": "string"}}}}}, ) @router.post( "/audio/transcriptions", dependencies=[Depends(user_api_key_auth)], tags=["audio"], + responses={200: {"model": TranscriptionResponse, "content": {"text/event-stream": {"schema": {"type": "string"}}}}}, ) async def audio_transcriptions( request: Request, @@ -13675,39 +13939,80 @@ async def audio_transcriptions( cache_key: Final = hidden_params.get("cache_key", None) or "" api_base: Final = hidden_params.get("api_base", None) or "" response_cost: Final = hidden_params.get("response_cost", None) or "" - response_call_id: Final = hidden_params.get("litellm_call_id", None) or "" + response_call_id: Final = hidden_params.get("litellm_call_id", None) or litellm_call_id additional_headers: Final[dict] = hidden_params.get("additional_headers", {}) or {} + stream_logging_obj: Final = getattr(response, "logging_obj", None) - fastapi_response.headers.update( - ProxyBaseLLMRequestProcessing.get_custom_headers( - user_api_key_dict=user_api_key_dict, - model_id=model_id, - cache_key=cache_key, - api_base=api_base, - version=version, - response_cost=response_cost, - model_region=getattr(user_api_key_dict, "allowed_model_region", ""), - call_id=response_call_id, - request_data=data, - hidden_params=hidden_params, - **additional_headers, - ) + custom_headers: Final = ProxyBaseLLMRequestProcessing.get_custom_headers( + user_api_key_dict=user_api_key_dict, + model_id=model_id, + cache_key=cache_key, + api_base=api_base, + version=version, + response_cost=response_cost, + model_region=user_api_key_dict.allowed_model_region, + call_id=response_call_id, + request_data=data, + hidden_params=hidden_params, + litellm_logging_obj=stream_logging_obj if isinstance(stream_logging_obj, LiteLLMLoggingObj) else None, + **additional_headers, ) # Call response headers hook (matches base_process_llm_request behavior) callback_headers: Final = await proxy_logging_obj.post_call_response_headers_hook( data=data, user_api_key_dict=user_api_key_dict, - response=response, + response=response.response if isinstance(response, GuardedTranscriptionReplay) else response, request_headers=dict(request.headers), ) - if callback_headers: - fastapi_response.headers.update(callback_headers) + response_headers: Final = {**custom_headers, **(callback_headers or {})} + + if hasattr(response, "__aiter__"): + + async def transcription_event_stream( + stream: AsyncIterator[TranscriptionStreamEvent], + ) -> AsyncGenerator[str, None]: + try: + async for event in stream: + yield f"data: {event.model_dump_json(exclude_unset=True)}\n\n" + yield TRANSCRIPTION_STREAM_DONE_FRAME + except Exception as stream_error: # noqa: BLE001 # stream boundary: a mid-stream failure ends the SSE body as an error event + replacement: Final = await proxy_logging_obj.post_call_failure_hook( + user_api_key_dict=user_api_key_dict, + original_exception=stream_error, + request_data=( + {**data, "litellm_logging_obj": stream_logging_obj} + if isinstance(stream_logging_obj, LiteLLMLoggingObj) + else data + ), + ) + yield _transcription_sse_error_frame(stream_error if replacement is None else replacement) + yield TRANSCRIPTION_STREAM_DONE_FRAME + finally: + with anyio.CancelScope(shield=True): + close: Final = getattr(stream, "aclose", None) or getattr(stream, "close", None) + if callable(close): + close_result: Final = close() + if inspect.isawaitable(close_result): + await close_result + + return StreamingResponse( + guarded_transcription_events(response.response) + if isinstance(response, GuardedTranscriptionReplay) + else transcription_event_stream(cast(AsyncIterator[TranscriptionStreamEvent], response)), + media_type="text/event-stream", + headers=response_headers, + ) + + fastapi_response.headers.update(response_headers) return response except Exception as e: await proxy_logging_obj.post_call_failure_hook( - user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data + user_api_key_dict=user_api_key_dict, + original_exception=e, + request_data=data, + dispatched_call_type=CallTypes.atranscription.value, ) log_llm_api_exception(e, litellm_call_id) if isinstance(e, HTTPException): @@ -13848,6 +14153,8 @@ async def _reject_realtime_session( @app.websocket("/openai/v1/realtime") @app.websocket("/v1/realtime") @app.websocket("/realtime") +@app.websocket("/v1/realtime/translations") +@app.websocket("/realtime/translations") async def realtime_websocket_endpoint( websocket: WebSocket, model: str | None = fastapi.Query(None, description="The model to use for the websocket connection."), @@ -13856,7 +14163,7 @@ async def realtime_websocket_endpoint( None, description="Comma-separated list of guardrail names to apply to this request.", ), - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth_websocket), + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth_realtime_websocket), ): requested_protocols: Final = tuple( protocol.strip() @@ -13864,15 +14171,13 @@ async def realtime_websocket_endpoint( if protocol.strip() ) - route_model = model + is_translation: Final = websocket.url.path.endswith("/realtime/translations") + route_model: Final = _resolve_realtime_route_model(model, intent, is_translation) if route_model is None: - if intent == "transcription": - route_model = "gpt-realtime-whisper" - else: - await _reject_realtime_session( - websocket, user_api_key_dict, code=1008, reason="model query parameter is required" - ) - return + await _reject_realtime_session( + websocket, user_api_key_dict, code=1008, reason="model query parameter is required" + ) + return assert route_model is not None try: await can_key_call_resolved_model( @@ -13893,6 +14198,7 @@ async def realtime_websocket_endpoint( model=model, intent=intent, guardrails=guardrails, + is_translation=is_translation, ) @@ -13906,13 +14212,20 @@ async def _route_realtime_websocket_session( guardrails: str | None, request_path: str | None = None, live_session_start: Mapping[str, object] | None = None, + is_translation: bool = False, ) -> None: # Only use explicit parameters, not all query params - query_params: Final = cast(RealtimeQueryParams, dict(_realtime_query_params_template(model, intent))) + query_model: Final = route_model if is_translation else model + query_params: Final = cast( # cast-ok: cached tuples contain only the declared realtime query keys + RealtimeQueryParams, + dict(_realtime_query_params_template(query_model, intent)), + ) + data: dict[str, object] = { "model": route_model, "websocket": websocket, "query_params": query_params, # Only explicit params + "realtime_mode": "translation" if is_translation else "realtime", } # Pass guardrails into data so pre-call guardrail processing picks them up if guardrails: @@ -14805,6 +15118,7 @@ from litellm.repositories.table_repositories import ( ) from litellm.repositories.team_repository import TeamRepository from litellm.repositories.user_repository import UserRepository +from litellm.repositories.verification_token_repository import VerificationTokenRepository from litellm.responses.litellm_completion_transformation.count_request import ( ChatCountBridgeError, chat_count_request, @@ -14950,7 +15264,7 @@ async def _try_provider_token_count( deployment: Mapping[str, object] | None, request_model: str, tools: list | None = None, - system: str | None = None, + system: object | None = None, messages_format: TokenCountMessagesFormat = "openai", output_format: JsonValue = None, context_management: CountContextManagement | None = None, @@ -15020,6 +15334,7 @@ async def _provider_token_count( request_model: str, settings: TokenCountSettings, local_estimate_allowed: bool, + forwarded_edits: bool = False, ) -> Union["TokenCountResponse", ProviderCountFailure, None]: """Count with the provider, using the token_count_model in its region when one is set. @@ -15043,7 +15358,7 @@ async def _provider_token_count( pinned_count_model: Final = None if count_model is None or count_model.region is None else count_model region_hint: Final = ( None - if pinned_count_model is None + if pinned_count_model is None or (forwarded_edits and counted.status_code == 400) else f"This model counts tokens with {pinned_count_model.model} in {pinned_count_model.region}. " "If that region is not enabled for the AWS account, enable it or set token_count_model in model_info" ) @@ -15051,7 +15366,7 @@ async def _provider_token_count( framing_can_stand_in: Final = (count_model is None or not count_model.configured) and ( failure.cannot_count_model or (pinned_count_model is not None and failure.denied_in_region) ) - if not (framing_can_stand_in and settings.framing is not None and local_estimate_allowed): + if not (framing_can_stand_in and settings.frames_counts and local_estimate_allowed): raise failure.to_proxy_exception() if pinned_count_model is not None: verbose_proxy_logger.warning( @@ -15251,6 +15566,7 @@ async def _tokenizer_or_provider_error( async def _local_token_estimate( model: str, + template_model: str, prompt: str | None, messages: Sequence[AllMessageValues] | None, tools: list[ChatCompletionToolParam] | None, @@ -15263,7 +15579,7 @@ async def _local_token_estimate( else await _tokenizer_or_provider_error(model, custom_tokenizer, provider_failure) ) count: Final = offload_token_count(litellm.token_counter)( - model=model, + model=template_model, text=prompt, messages=messages, tools=tools, @@ -15305,6 +15621,9 @@ class _TokenCountDeployment(TypedDict, total=False): _TOKEN_COUNT_DEPLOYMENT: Final = TypeAdapter(_TokenCountDeployment) +_COUNT_TOOLS: Final[TypeAdapter[tuple[Mapping[str, object], ...] | None]] = TypeAdapter( + tuple[Mapping[str, object], ...] | None +) _ROUTED_DEPLOYMENT: Final[TypeAdapter[Mapping[str, object] | None]] = TypeAdapter(Mapping[str, object] | None) @@ -15326,10 +15645,15 @@ def _deployment_aws_region(deployment: _TokenCountDeployment) -> str: ) +def _deployment_base_model(deployment: _TokenCountDeployment) -> str | None: + return _non_empty_str(deployment.get("model_info", {}).get("base_model")) or _non_empty_str( + deployment.get("litellm_params", {}).get("base_model") + ) + + def _token_count_settings_model(deployment: _TokenCountDeployment, request_model: str) -> tuple[str, str | None]: - model_info: Final = deployment.get("model_info", {}) params: Final = deployment.get("litellm_params", {}) - base_model: Final = _non_empty_str(model_info.get("base_model")) or _non_empty_str(params.get("base_model")) + base_model: Final = _deployment_base_model(deployment) if base_model is not None: return base_model, None model: Final = _non_empty_str(params.get("model")) @@ -15374,12 +15698,15 @@ def _count_context_management( model, general_settings_view(), user_model if isinstance(user_model, str) else None ) router_defaults: Final = _router_default_litellm_params(llm_router) - sent_params: Final = tuple( - {**deployment["litellm_params"], **router_defaults, **request_litellm_params} + deployment_params: Final = tuple( + deployment["litellm_params"] for deployment in llm_router.registry().deployments( inference_model if isinstance(inference_model, str) else model, source="routable" ) ) + sent_params: Final = tuple( + {**params, **router_defaults, **request_litellm_params} for params in deployment_params or ({},) + ) if any(context_management_explicitly_dropped(params.get("additional_drop_params")) for params in sent_params): return None return CountContextManagement( @@ -15389,17 +15716,104 @@ def _count_context_management( ) +_GATEWAY_EDIT_ROUTES: Final = frozenset({Target.CHAT_COMPLETIONS, Target.RESPONSES}) + + +def _messages_route(deployment: _TokenCountDeployment, request_model: str) -> Target: + params: Final = deployment.get("litellm_params", {}) + return messages_target( + _non_empty_str(params.get("model")) or request_model, + _non_empty_str(params.get("custom_llm_provider")), + deployment.get("model_info"), + _deployment_api_base(deployment), + ) + + +def _rejected_view(status_code: int, message: str) -> ProxyException: + return ProviderCountFailure( + status_code=status_code, message=message, rejected_before_provider_call=True + ).to_proxy_exception() + + +async def _bridged_request_view( + messages: Sequence[Mapping[str, object]], + system: object, + tools: Sequence[Mapping[str, object]] | None, + messages_format: TokenCountMessagesFormat, + edits: CountContextManagement | None, + deployment: _TokenCountDeployment, + fallback_model: str, +) -> InferenceRequestView | InferenceRequestViewError | None: + view: Final = await inference_request_view( + messages, + system, + messages_format, + count_context_edits(edits, tools, deployment.get("litellm_params", {}), fallback_model), + ) + return None if isinstance(view, InferenceRequestView) and not view.messages else view + + +async def _responses_request_view( + messages: Sequence[Mapping[str, object]], + system: object, + tools: Sequence[Mapping[str, object]] | None, + edits: CountContextManagement, + deployment: _TokenCountDeployment, + fallback_model: str, +) -> InferenceRequestView | InferenceRequestViewError: + from litellm.llms.anthropic.messages.context_management import AnthropicContextManagementError + from litellm.llms.anthropic.messages.responses_adapters.handler import count_view_messages + + try: + edited: Final = await count_view_messages( + model=_non_empty_str(deployment.get("litellm_params", {}).get("model")) or fallback_model, + messages=messages, + tools=tools, + system=system, + context_management=edits, + ) + except AnthropicContextManagementError as error: + if error.status_code >= 500: + return InferenceRequestView(messages=messages, system=system) + return InferenceRequestViewError(error_message=error.message, status_code=error.status_code) + return InferenceRequestView(messages=edited, system=system) + + +async def _gateway_request_view( + route: Target, + messages: Sequence[Mapping[str, object]], + system: object, + tools: Sequence[Mapping[str, object]] | None, + messages_format: TokenCountMessagesFormat, + edits: CountContextManagement | None, + deployment: _TokenCountDeployment, + fallback_model: str, +) -> InferenceRequestView | InferenceRequestViewError | None: + match route: + case Target.CHAT_COMPLETIONS: + return await _bridged_request_view( + messages, system, tools, messages_format, edits, deployment, fallback_model + ) + case Target.RESPONSES if edits is not None: + return await _responses_request_view(messages, system, tools, edits, deployment, fallback_model) + case _: + return None + + def _responses_routing_kwargs(responses_request: Mapping[str, object] | None) -> Mapping[str, object]: previous_response_id: Final = None if responses_request is None else responses_request.get("previous_response_id") return {"previous_response_id": previous_response_id} if isinstance(previous_response_id, str) else {} +def _inference_params( + litellm_params: Mapping[str, object], responses_request: Mapping[str, object] +) -> Mapping[str, object]: + return {**litellm_params, **_router_default_litellm_params(llm_router), **responses_request} + + def _count_drop_policy(deployment: Mapping[str, object] | None, responses_request: Mapping[str, object]) -> DropPolicy: litellm_params: Final = as_str_mapping(None if deployment is None else deployment.get("litellm_params")) or {} - router_defaults: Final[Mapping[str, object]] = ( - {} if llm_router is None else _router_default_litellm_params(llm_router) - ) - return drop_policy({**litellm_params, **router_defaults, **responses_request}) + return drop_policy(_inference_params(litellm_params, responses_request)) def _native_responses_count( @@ -15422,8 +15836,54 @@ def _native_responses_count( ) -def _deployment_api_base(deployment: _TokenCountDeployment) -> str | None: - return _non_empty_str(deployment.get("litellm_params", {}).get("api_base")) +def _deployment_api_base( + deployment: _TokenCountDeployment, responses_request: Mapping[str, object] | None = None +) -> str | None: + return _non_empty_str( + _inference_params(deployment.get("litellm_params", {}), responses_request or {}).get("api_base") + ) + + +def _deployment_provider( + deployment: _TokenCountDeployment, request_model: str, responses_request: Mapping[str, object] | None +) -> str | None: + params: Final = deployment.get("litellm_params", {}) + try: + return litellm.get_llm_provider( + model=_non_empty_str(params.get("model")) or request_model, + custom_llm_provider=_non_empty_str(params.get("custom_llm_provider")), + api_base=_deployment_api_base(deployment, responses_request), + )[1] + except litellm.BadRequestError: + return None + + +def _serves_native_responses( + deployment: _TokenCountDeployment, request_model: str, responses_request: Mapping[str, object] +) -> bool: + params: Final = deployment.get("litellm_params", {}) + inference: Final = _inference_params(params, responses_request) + try: + return provider_stores_the_conversation( + _non_empty_str(params.get("model")) or request_model, + _non_empty_str(params.get("custom_llm_provider")), + { + "use_chat_completions_api": bool(inference.get("use_chat_completions_api")), + "model_info": dict(deployment.get("model_info", {})), + "api_base": _non_empty_str(inference.get("api_base")), + }, + ) + except litellm.BadRequestError: + return False + + +_AZURE_PROVIDERS: Final = frozenset((litellm.LlmProviders.AZURE.value, litellm.LlmProviders.AZURE_AI.value)) + + +def _with_strict_by_default(tools: Sequence[Mapping[str, object]]) -> tuple[Mapping[str, object], ...]: + return tuple( + {**tool, "strict": True} if tool.get("type") == "function" and "strict" not in tool else tool for tool in tools + ) def _system_message(system: object) -> ChatCompletionSystemMessage | None: @@ -15582,6 +16042,40 @@ async def _count_request_tokens( ) prompt_only: Final = bool(prompt) and conversation_empty request_messages: Final = _counted_request_messages(messages, messages_format, count_deployment) + local_count_error: Final = malformed_tool_result_count_error(request_messages, messages_format, count_deployment) + malformed_messages: Final = ( + None + if local_count_error is None + else ProxyException(message=local_count_error, type="token_counting_error", param="messages", code=400) + ) + context_edits: Final = _count_context_management(context_management, request.model, request_litellm_params) + route: Final = ( + _messages_route(deployment_view, request.model) + if request_messages is not None and messages_format == "anthropic" + else None + ) + if context_edits is not None and route in _GATEWAY_EDIT_ROUTES and malformed_messages is not None: + raise malformed_messages + edited_request: Final = ( + None + if route is None or request_messages is None + else await _gateway_request_view( + route, + request_messages, + system, + _COUNT_TOOLS.validate_python(tools), + messages_format, + context_edits, + deployment_view, + model_to_use, + ) + ) + if isinstance(edited_request, InferenceRequestViewError): + raise _rejected_view(edited_request.status_code, edited_request.error_message) + inference_messages: Final = ( + request_messages if edited_request is None else [dict(message) for message in edited_request.messages] + ) + inference_system: Final = system if edited_request is None else edited_request.system contents_estimable: Final = not contents or (bool(messages) and _estimable_contents(contents)) prompt_as_message: Final = prompt_only and custom_llm_provider in _PROVIDERS_COUNTING_WITHOUT_MESSAGES routed_deployment: Final = _ROUTED_DEPLOYMENT.validate_python(deployment) @@ -15594,7 +16088,7 @@ async def _count_request_tokens( else await chat_count_request( model_to_use, custom_llm_provider, - _deployment_api_base(deployment_view), + _deployment_api_base(deployment_view, routed_request), routed_request, _count_drop_policy(routed_deployment, routed_request), ) @@ -15621,30 +16115,30 @@ async def _count_request_tokens( if chat_count is not None else [{"role": "user", "content": prompt}] if prompt_as_message - else request_messages + else inference_messages ), contents=None if prompt_as_message else contents, deployment=count_deployment, request_model=request.model, tools=tools if chat_count is None else [dict(tool) for tool in chat_count.tools or ()] or None, - system=system, + system=inference_system, messages_format=messages_format, output_format=output_format, - context_management=_count_context_management(context_management, request.model, request_litellm_params), + context_management=None if edited_request is not None else context_edits, chat_params=MappingProxyType({}) if chat_count is None else chat_count.params, ), model_to_use=model_to_use, request_model=request.model, settings=settings, local_estimate_allowed=litellm.disable_token_counter is not True and contents_estimable, + forwarded_edits=context_edits is not None and edited_request is None, ) ) if isinstance(ladder, TokenCountResponse): return ladder - local_count_error: Final = malformed_tool_result_count_error(request_messages, messages_format, count_deployment) - if local_count_error is not None: - raise ProxyException(message=local_count_error, type="token_counting_error", param="messages", code=400) + if malformed_messages is not None: + raise malformed_messages # Check if token counter is disabled before fallback if litellm.disable_token_counter is True: @@ -15655,6 +16149,27 @@ async def _count_request_tokens( code=503, ) + local_view: Final = ( + None + if route is not Target.MESSAGES or context_edits is None or request_messages is None + else await _bridged_request_view( + request_messages, + system, + _COUNT_TOOLS.validate_python(tools), + messages_format, + replace(context_edits, drop_invalid_edits=False), + deployment_view, + model_to_use, + ) + ) + if isinstance(local_view, InferenceRequestViewError): + raise _rejected_view(local_view.status_code, local_view.error_message) + counted_view: Final = edited_request if local_view is None else local_view + local_messages: Final = ( + request_messages if counted_view is None else [dict(message) for message in counted_view.messages] + ) + local_system: Final = system if counted_view is None else counted_view.system + # Default LiteLLM token counting custom_tokenizer: CustomHuggingfaceTokenizer | None = None if model_info is not None: @@ -15662,22 +16177,51 @@ async def _count_request_tokens( CustomHuggingfaceTokenizer | None, model_info.get("custom_tokenizer", None), ) - system_message: Final = _system_message(system) + system_message: Final = _system_message(local_system) prompt_turn: Final = prompt_only and not (system_message is None and not tools) typed_messages: Final = cast( # cast-ok: request messages are raw chat-shaped dicts that token_counter normalizes Sequence[AllMessageValues] | None, - [{"role": "user", "content": prompt}] if prompt_turn else (None if prompt_only else request_messages), + [{"role": "user", "content": prompt}] if prompt_turn else (None if prompt_only else local_messages), ) counted_messages: Final = ( typed_messages if typed_messages is None or system_message is None else (system_message, *typed_messages) ) - counted_tools: Final = cast( # cast-ok: raw OpenAI or Anthropic tool dicts, both of which token_counter formats + native_responses: Final = responses_request is not None and _serves_native_responses( + deployment_view, request.model, responses_request + ) + sent_tools: Final = cast( # cast-ok: raw OpenAI or Anthropic tool dicts, both of which token_counter formats list[ChatCompletionToolParam] | None, tools if counted_messages is not None else None ) - framing: Final = settings.framing if counted_messages is not None and settings.framing is not None else 0 + openai_model: Final = deployment_openai_model(deployment_view) + template_model: Final = openai_model or _deployment_base_model(deployment_view) or model_to_use + tool_section: Final = chat_template_tool_section(template_model) + counted_tools: Final = ( + cast(list[ChatCompletionToolParam], list(_with_strict_by_default(sent_tools))) # cast-ok: strict added + if sent_tools is not None + and native_responses + and _deployment_provider(deployment_view, request.model, responses_request) in _AZURE_PROVIDERS + and tool_section is not None + and tool_section.renders_strict_only_when_true + else sent_tools + ) + framing: Final = ( + 0 + if counted_messages is None + else settings.hidden_prompt_tokens( + carries_tools=sends_function_tools(counted_tools), responses_api=native_responses + ) + ) kimi_k3_messages: Final = counted_messages if settings.tokenizer == "kimi_k3" else None exact: Final = ( - await _kimi_k3_count(request, messages_format, model_to_use, kimi_k3_messages, counted_tools) + await _kimi_k3_count( + request + if counted_view is None + else request.model_copy(update={"messages": local_messages, "system": local_system}), + messages_format, + model_to_use, + kimi_k3_messages, + counted_tools, + ) if kimi_k3_messages is not None and custom_tokenizer is None else None ) @@ -15690,7 +16234,8 @@ async def _count_request_tokens( count_source="local_estimate", ) estimate: Final = await _local_token_estimate( - model=deployment_openai_model(deployment_view) or model_to_use, + model=openai_model or model_to_use, + template_model=template_model, prompt=prompt if counted_messages is None else None, messages=counted_messages, tools=counted_tools, @@ -16495,9 +17040,6 @@ async def _apply_search_filter_to_models( team_public_model_name: Final = (m.get("model_info") or {}).get("team_public_model_name") or "" if search_lower in team_public_model_name.lower(): return True - # Also match the underlying LiteLLM model name (e.g. - # "openrouter/deepseek/deepseek-chat"), so users can find - # deployments by typing the provider or the upstream model id. litellm_params: Final[Mapping[str, object]] = m.get("litellm_params") or MappingProxyType({}) litellm_model: Final = litellm_params.get("model") return isinstance(litellm_model, str) and search_lower in litellm_model.lower() @@ -18006,8 +18548,6 @@ async def model_info_v1( alias_models: Final = copy.deepcopy(registry.deployments(source="alias")) all_models.extend(alias_models) - all_models = await run_model_listing(partial(expand_wildcard_deployments_for_model_info, all_models, llm_router)) - allowed_model_names: Final = await _get_v1_model_info_allowed_model_names_with_access_groups( user_api_key_dict=user_api_key_dict, llm_router=llm_router, @@ -18016,6 +18556,15 @@ async def model_info_v1( proxy_logging_obj=proxy_logging_obj, ) + all_models = await run_model_listing( + partial( + expand_wildcard_deployments_for_model_info, + all_models, + llm_router, + allowed_model_names=allowed_model_names, + ) + ) + all_models = _filter_v1_model_info_deployments( all_models=all_models, allowed_model_names=allowed_model_names, @@ -18099,8 +18648,9 @@ async def model_deprecations( Reads `deprecation_date` metadata from `model_prices_and_context_window.json` (and any per-deployment `model_info.deprecation_date` overrides) for the - models configured on this proxy. An entry also names its `successor_model` - when the deployment sets `model_info.successor_model`. + models configured on this proxy. An entry also names its `successor_model`: + `model_info.successor_model` when the deployment sets one, else the + replacement the cost map records from the provider's deprecation notice. Parameters: warn_within_days: Window (in days) used to bucket "imminent" models, @@ -18120,7 +18670,11 @@ async def model_deprecations( -H "Authorization: Bearer $LITELLM_MASTER_KEY" ``` """ - return collect_model_deprecations(llm_router=llm_router, warn_within_days=warn_within_days) + return collect_model_deprecations( + llm_router=llm_router, + warn_within_days=warn_within_days, + successor_log_level=logging.DEBUG, + ) def get_model_group_info( @@ -20792,53 +21346,56 @@ async def delete_config_general_settings( if data.field_name in _GENERAL_SETTINGS_UI_LITELLM_FIELDS: return await _reset_general_settings_ui_litellm_field(data.field_name, user_api_key_dict) - if data.field_name not in ConfigGeneralSettings.model_fields: + config_table: Final[TableActions[_ConfigParamValueRow]] = _config_param_table(prisma_client) + stored_row: Final = await config_table.find_first(where={"param_name": "general_settings"}) + stored: Final = ( + _SETTINGS_MAPPING.validate_python(stored_row.param_value) + if stored_row is not None and isinstance(stored_row.param_value, Mapping) + else None + ) + + if not _general_settings_row_is_readable(stored_row): + raise HTTPException( + status_code=400, + detail={ + "error": "general_settings is stored in the database as something other than a JSON object, so no " + "field can be removed from it" + }, + ) + + if data.field_name not in ConfigGeneralSettings.model_fields and (stored is None or data.field_name not in stored): raise HTTPException( status_code=400, detail={"error": f"Invalid field={data.field_name} passed in."}, ) - proxy_config.reject_config_owned_deletes(section_name="general_settings", keys=(data.field_name,)) + if data.field_name in _db_managed_general_settings_keys(): + proxy_config.reject_config_owned_deletes(section_name="general_settings", keys=(data.field_name,)) - ## get general settings from db - db_general_settings: Final[_ConfigParamRow | None] = await _config_param_table(prisma_client).find_first( - where={"param_name": "general_settings"} - ) - ### pop the value - - if db_general_settings is None or db_general_settings.param_value is None: + if stored is None: raise HTTPException( status_code=400, detail={"error": f"Field name={data.field_name} not in config"}, ) - else: - general_settings = dict(db_general_settings.param_value) - - before_general_settings: Final = copy.deepcopy(general_settings) - - ## update db - - general_settings.pop(data.field_name, None) + remaining: Final = {key: value for key, value in stored.items() if key != data.field_name} response: Final = await ConfigRepository(prisma_client).table.upsert( where={"param_name": "general_settings"}, data={ "create": { "param_name": "general_settings", - "param_value": json.dumps(general_settings), + "param_value": json.dumps(remaining), }, - "update": {"param_value": json.dumps(general_settings)}, + "update": {"param_value": json.dumps(remaining)}, }, ) await invalidate_config_param("general_settings") - proxy_config.settings.apply_db_row("general_settings", general_settings) + proxy_config.settings.apply_db_row("general_settings", remaining) if is_resource_list("general_settings", data.field_name): - stored_endpoints: Final = general_settings.get("pass_through_endpoints") + stored_endpoints: Final = remaining.get("pass_through_endpoints") await proxy_config.serve_pass_through_endpoints(stored_endpoints if isinstance(stored_endpoints, list) else ()) asyncio.create_task( - create_config_audit_log( - "general_settings", "deleted", before_general_settings, general_settings, user_api_key_dict - ) + create_config_audit_log("general_settings", "deleted", dict(stored), remaining, user_api_key_dict) ) return response @@ -21884,6 +22441,7 @@ app.include_router(prompt_caching_requests_router) app.include_router(router_settings_router) app.include_router(fallback_management_router) app.include_router(cache_settings_router) +app.include_router(model_deprecation_alerts_router) app.include_router(coordination_redis_settings_router) app.include_router(user_agent_analytics_router) app.include_router(gateway_request_router) @@ -21901,6 +22459,7 @@ app.add_middleware( RequestSizeLimitMiddleware, get_max_request_size_mb=configured_max_request_size_mb, is_request_size_limit_enabled=lambda: premium_user is True, + route_max_request_size_mb=_ROUTE_MAX_REQUEST_SIZE_MB, ) app.add_middleware( AdmissionControlMiddleware, diff --git a/litellm/proxy/public_endpoints/provider_create_fields.json b/litellm/proxy/public_endpoints/provider_create_fields.json index 044b8a1de6e..5ded2fa5f5e 100644 --- a/litellm/proxy/public_endpoints/provider_create_fields.json +++ b/litellm/proxy/public_endpoints/provider_create_fields.json @@ -1553,6 +1553,34 @@ ], "default_model_placeholder": "gpt-3.5-turbo" }, + { + "provider": "EMPIRIOLABS", + "provider_display_name": "EmpirioLabs AI", + "litellm_provider": "empiriolabs", + "credential_fields": [ + { + "key": "api_base", + "label": "API Base", + "placeholder": "https://api.empiriolabs.ai/v1", + "tooltip": null, + "required": false, + "field_type": "text", + "options": null, + "default_value": null + }, + { + "key": "api_key", + "label": "API Key", + "placeholder": null, + "tooltip": null, + "required": true, + "field_type": "password", + "options": null, + "default_value": null + } + ], + "default_model_placeholder": "empiriolabs/aplomb-1" + }, { "provider": "EMPOWER", "provider_display_name": "Empower", @@ -2641,6 +2669,34 @@ ], "default_model_placeholder": "nace/drex-latest" }, + { + "provider": "PARALLEL_AI", + "provider_display_name": "Parallel AI", + "litellm_provider": "parallel_ai", + "credential_fields": [ + { + "key": "api_base", + "label": "API Base", + "placeholder": "https://api.parallel.ai", + "tooltip": null, + "required": false, + "field_type": "text", + "options": null, + "default_value": null + }, + { + "key": "api_key", + "label": "API Key", + "placeholder": null, + "tooltip": null, + "required": true, + "field_type": "password", + "options": null, + "default_value": null + } + ], + "default_model_placeholder": "parallel_ai/decision" + }, { "provider": "NEBIUS", "provider_display_name": "Nebius", @@ -3539,6 +3595,34 @@ ], "default_model_placeholder": "reka/reka-flash" }, + { + "provider": "WALLY", + "provider_display_name": "Wally", + "litellm_provider": "wally", + "credential_fields": [ + { + "key": "api_base", + "label": "API Base", + "placeholder": "https://inference.runanywhere.ai/v1", + "tooltip": null, + "required": false, + "field_type": "text", + "options": null, + "default_value": null + }, + { + "key": "api_key", + "label": "API Key", + "placeholder": null, + "tooltip": null, + "required": true, + "field_type": "password", + "options": null, + "default_value": null + } + ], + "default_model_placeholder": "wally/glm-5.3-flash" + }, { "provider": "Sail", "provider_display_name": "Sail", diff --git a/litellm/proxy/realtime_endpoints/endpoints.py b/litellm/proxy/realtime_endpoints/endpoints.py index 9dbf6bcc43d..17c52fc54bd 100644 --- a/litellm/proxy/realtime_endpoints/endpoints.py +++ b/litellm/proxy/realtime_endpoints/endpoints.py @@ -2,19 +2,24 @@ import json import time -from collections.abc import Mapping +from collections.abc import Generator, Mapping +from contextlib import contextmanager from typing import TYPE_CHECKING, Final import httpx from fastapi import APIRouter, Depends, HTTPException, Request, Response from fastapi import status as http_status -from pydantic import ConfigDict, TypeAdapter, with_config +from fastapi.responses import PlainTextResponse +from pydantic import ConfigDict, TypeAdapter, ValidationError, with_config from typing_extensions import NotRequired, ReadOnly, TypedDict +import litellm from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.proxy._types import ProxyException, UserAPIKeyAuth from litellm.proxy.auth.auth_checks import can_key_call_resolved_model from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.common_utils.custom_openapi_spec import inline_request_body from litellm.proxy.common_utils.encrypt_decrypt_utils import ( decrypt_value_helper, encrypt_value_helper, @@ -43,7 +48,26 @@ router: Final = APIRouter() _REALTIME_TOKEN_VERSION: Final = "realtime_v1" _DEFAULT_REALTIME_MODEL: Final = "gpt-4o-realtime-preview" _DEFAULT_TRANSCRIPTION_MODEL: Final = "gpt-realtime-whisper" -_ALLOWED_SESSION_TYPES: Final = ("realtime", "transcription") +_ALLOWED_SESSION_TYPES: Final = ("realtime", "transcription", "translation") + + +@contextmanager +def _invalid_request_body_answers_400() -> Generator[None, None, None]: + try: + yield + except ValidationError as error: + raise ProxyException(message=str(error), type="invalid_request_error", param=None, code=400) from error + + +_TRANSLATION_SECRET_BODY: Final = { + "requestBody": inline_request_body( + RealtimeClientSecretRequest, + {"model": "gpt-realtime-translate", "session": {"type": "translation", "model": "gpt-realtime-translate"}}, + ) +} +_TRANSLATION_SDP_BODY: Final = { + "requestBody": {"required": True, "content": {"application/sdp": {"schema": {"type": "string"}}}} +} @with_config(ConfigDict(strict=True, extra="allow")) @@ -140,19 +164,60 @@ def _set_transcription_model_on_session( } +def nested_transcription_upstream_model(model: str, team_id: str | None, llm_router: "Router | None") -> str: + deployment_model: Final = ( + llm_router.registry().resolve(model, kind="upstream", team_id=team_id) if llm_router is not None else None + ) + if deployment_model is None: + return model + try: + return litellm.get_llm_provider(model=deployment_model)[0] + except litellm.BadRequestError: + return deployment_model + + +async def _authorize_and_bind_nested_transcription_models( + session_data: dict, # mutable-ok: session payload is rewritten in place for provider serialization + user_api_key_dict: UserAPIKeyAuth, + llm_model_list: list | None, # mutable-ok: inherited auth helper accepts the proxy model list + llm_router: "Router | None", +) -> None: + nested_models: Final = tuple(_transcription_model_candidates_from_session(session_data)) + for nested_model in nested_models: + await can_key_call_resolved_model( + model=nested_model, + valid_token=user_api_key_dict, + llm_model_list=llm_model_list, + llm_router=llm_router, + ) + if nested_models: + _set_transcription_model_on_session( + session=session_data, + model=nested_transcription_upstream_model(nested_models[0], user_api_key_dict.team_id, llm_router), + ) + + async def _prepare_client_secret_session( req: RealtimeClientSecretRequest, user_api_key_dict: UserAPIKeyAuth, llm_model_list: list | None, llm_router: "Router | None", + forced_session_type: str | None = None, ) -> tuple[str, dict | None, str]: - session_type: Final = _coerce_realtime_session_type(req.session.type if req.session else None) - session_data: Final[dict | None] = req.session.model_dump(exclude_none=True) if req.session else None + requested_session_type: Final = req.session.type if req.session else None + if forced_session_type is None and requested_session_type == "translation": + raise HTTPException(status_code=400, detail="Translation sessions require the translations endpoint") + session_type: Final = forced_session_type or _coerce_realtime_session_type(requested_session_type) + session_data: Final[dict | None] = ( + req.session.model_dump(exclude_unset=True) if req.session else ({} if session_type == "translation" else None) + ) if session_data is not None: session_data["type"] = session_type session_model: Final = req.session.model if req.session else None - model: str = session_model or req.model or _DEFAULT_REALTIME_MODEL + requested_model: Final = session_model or req.model + default_model: Final = "gpt-realtime-translate" if session_type == "translation" else _DEFAULT_REALTIME_MODEL + model: str = requested_model or default_model if session_type != "transcription": await can_key_call_resolved_model( model=model, @@ -160,6 +225,15 @@ async def _prepare_client_secret_session( llm_model_list=llm_model_list, llm_router=llm_router, ) + if session_data is not None and (requested_model or session_type == "translation"): + session_data["model"] = model + if session_type == "translation": + await _authorize_and_bind_nested_transcription_models( + session_data=session_data, + user_api_key_dict=user_api_key_dict, + llm_model_list=llm_model_list, + llm_router=llm_router, + ) return model, session_data, session_type transcription_model_candidates: Final = _transcription_model_candidates_from_session(session_data or {}) @@ -194,12 +268,13 @@ def _encode_realtime_token_payload( team_id: str | None, expires_at: int | None, session_type: str = "realtime", + caller_auth: Mapping[str, object] | None = None, ) -> str: """ Encode metadata with the upstream ephemeral key so /realtime/calls can route without requiring model as a query param. """ - payload: Final[dict[str, str | int | None]] = { + payload: Final[Mapping[str, object]] = { "v": _REALTIME_TOKEN_VERSION, "ephemeral_key": ephemeral_key, "model_id": model_id, @@ -207,10 +282,24 @@ def _encode_realtime_token_payload( "team_id": team_id or "", "expires_at": expires_at, "session_type": session_type, + **({} if caller_auth is None else {"caller_auth": caller_auth}), } return json.dumps(payload, separators=(",", ":")) +def _caller_auth_for_token(user_api_key_dict: UserAPIKeyAuth) -> Mapping[str, object]: + return user_api_key_dict.model_dump(mode="json", exclude_none=True, exclude={"api_key", "parent_otel_span"}) + + +def _caller_auth_from_token( + decoded_payload: Mapping[str, object] | None, user_id: str | None, team_id: str | None +) -> UserAPIKeyAuth: + caller_auth: Final = None if decoded_payload is None else as_str_mapping(decoded_payload.get("caller_auth")) + if caller_auth is None: + return UserAPIKeyAuth(user_id=user_id, team_id=team_id) + return UserAPIKeyAuth.model_validate({**caller_auth, "api_key": caller_auth.get("token")}) + + def _header_value(headers: Mapping[str, str], name: str, default: str) -> str: return headers.get(name, default) @@ -249,11 +338,24 @@ def _decode_realtime_token_payload( dependencies=[Depends(user_api_key_auth)], tags=["realtime"], ) +@router.post( + "/v1/realtime/translations/client_secrets", + openapi_extra=_TRANSLATION_SECRET_BODY, + dependencies=[Depends(user_api_key_auth)], + tags=["realtime"], +) +@router.post( + "/realtime/translations/client_secrets", + openapi_extra=_TRANSLATION_SECRET_BODY, + dependencies=[Depends(user_api_key_auth)], + tags=["realtime"], +) async def create_realtime_client_secret( request: Request, fastapi_response: Response, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), ) -> RealtimeClientSecretResponse: + """Create a short-lived client token for a Realtime conversation, transcription, or translation session""" from litellm.proxy.proxy_server import ( add_litellm_data_to_request, general_settings, @@ -269,13 +371,16 @@ async def create_realtime_client_secret( data: dict = {} try: body: Final = await read_request_body(request=request) - req: Final = RealtimeClientSecretRequest(**body) + with _invalid_request_body_answers_400(): + req: Final = RealtimeClientSecretRequest.model_validate(body) + is_translation_request: Final = "/realtime/translations/client_secrets" in request.url.path model, session_data, session_type = await _prepare_client_secret_session( req=req, user_api_key_dict=user_api_key_dict, llm_model_list=llm_model_list, llm_router=llm_router, + forced_session_type="translation" if is_translation_request else None, ) data = {"model": model} @@ -299,17 +404,20 @@ async def create_realtime_client_secret( proxy_config=proxy_config, ) + call_type: Final = ( + "acreate_realtime_translation_client_secret" if is_translation_request else "acreate_realtime_client_secret" + ) data = await proxy_logging_obj.pre_call_hook( user_api_key_dict=user_api_key_dict, data=data, - call_type="acreate_realtime_client_secret", + call_type=call_type, ) verbose_proxy_logger.debug("WebRTC: /v1/realtime/client_secrets (model=%s)", model) llm_call: Final = await route_request( data=data, - route_type="acreate_realtime_client_secret", + route_type=call_type, llm_router=llm_router, user_model=user_model, ) @@ -366,6 +474,7 @@ async def create_realtime_client_secret( team_id=getattr(user_api_key_dict, "team_id", None), expires_at=expires_at if isinstance(expires_at, int) else None, session_type=session_type, + caller_auth=_caller_auth_for_token(user_api_key_dict) if session_type == "translation" else None, ) encrypted_token: Final[str] = encrypt_value_helper(token_payload) upstream_json["value"] = encrypted_token @@ -392,10 +501,27 @@ async def create_realtime_client_secret( "/openai/v1/realtime/calls", tags=["realtime"], ) +@router.post( + "/v1/realtime/translations/calls", + status_code=http_status.HTTP_201_CREATED, + response_class=PlainTextResponse, + response_description="WebRTC SDP answer", + openapi_extra=_TRANSLATION_SDP_BODY, + tags=["realtime"], +) +@router.post( + "/realtime/translations/calls", + status_code=http_status.HTTP_201_CREATED, + response_class=PlainTextResponse, + response_description="WebRTC SDP answer", + openapi_extra=_TRANSLATION_SDP_BODY, + tags=["realtime"], +) async def proxy_realtime_calls( request: Request, fastapi_response: Response, ) -> Response: + """Exchange a WebRTC SDP offer for an answer using the ephemeral token from client_secrets""" from litellm.proxy.proxy_server import ( add_litellm_data_to_request, general_settings, @@ -417,6 +543,7 @@ async def proxy_realtime_calls( media_type="application/json", ) + is_translation_request: Final = "/realtime/translations/calls" in request.url.path encrypted_token: Final = auth_header.removeprefix("Bearer ").strip() decrypted_token_value: Final = decrypt_value_helper( value=encrypted_token, @@ -434,33 +561,39 @@ async def proxy_realtime_calls( if decoded_payload is not None: # Check token expiry expires_at: Final = decoded_payload.get("expires_at") - if expires_at is not None and isinstance(expires_at, int): - if time.time() > expires_at: - return Response( - content=json.dumps({"error": "Token has expired"}), - status_code=http_status.HTTP_401_UNAUTHORIZED, - media_type="application/json", - ) + if isinstance(expires_at, int) and time.time() > expires_at: + return Response( + content=json.dumps({"error": "Token has expired"}), + status_code=http_status.HTTP_401_UNAUTHORIZED, + media_type="application/json", + ) openai_ephemeral_key = decoded_payload.get("ephemeral_key", "") model = decoded_payload.get("model_id") or request.query_params.get("model") or _DEFAULT_REALTIME_MODEL user_id = decoded_payload.get("user_id") or None team_id = decoded_payload.get("team_id") or None - session_type = _coerce_realtime_session_type(decoded_payload.get("session_type")) + raw_session_type: Final = decoded_payload.get("session_type") + session_type = _coerce_realtime_session_type(raw_session_type) + if is_translation_request != (raw_session_type == "translation"): + return Response( + content=json.dumps({"error": "Token is not valid for this Realtime endpoint"}), + status_code=http_status.HTTP_401_UNAUTHORIZED, + media_type="application/json", + ) else: - # Backward compatibility: older tokens contained only encrypted upstream key. + if is_translation_request: + return Response( + content=json.dumps({"error": "Token is not valid for this Realtime endpoint"}), + status_code=http_status.HTTP_401_UNAUTHORIZED, + media_type="application/json", + ) openai_ephemeral_key = decrypted_token_value model = request.query_params.get("model", _DEFAULT_REALTIME_MODEL) user_id = None team_id = None session_type = "realtime" - # Build a minimal UserAPIKeyAuth with user/team IDs from the token - # so spend tracking and budget enforcement work correctly. - minimal_auth: Final = UserAPIKeyAuth( - user_id=user_id, - team_id=team_id, - ) + token_caller_auth: Final = _caller_auth_from_token(decoded_payload, user_id, team_id) data: dict = {} try: @@ -487,22 +620,23 @@ async def proxy_realtime_calls( data=data, request=request, general_settings=general_settings, - user_api_key_dict=minimal_auth, + user_api_key_dict=token_caller_auth, version=version, proxy_config=proxy_config, ) + call_type: Final = "arealtime_translation_calls" if is_translation_request else "arealtime_calls" data = await proxy_logging_obj.pre_call_hook( - user_api_key_dict=minimal_auth, + user_api_key_dict=token_caller_auth, data=data, - call_type="arealtime_calls", + call_type=call_type, ) verbose_proxy_logger.debug("WebRTC: /v1/realtime/calls (model=%s)", model) llm_call: Final = await route_request( data=data, - route_type="arealtime_calls", + route_type=call_type, llm_router=llm_router, user_model=user_model, ) @@ -510,7 +644,7 @@ async def proxy_realtime_calls( except Exception as e: await proxy_logging_obj.post_call_failure_hook( - user_api_key_dict=minimal_auth, + user_api_key_dict=token_caller_auth, original_exception=e, request_data=data, ) @@ -581,7 +715,8 @@ async def create_realtime_transcription_session( data: dict = {} try: body: Final = await read_request_body(request=request) - req: Final = RealtimeTranscriptionSessionRequest(**body) + with _invalid_request_body_answers_400(): + req: Final = RealtimeTranscriptionSessionRequest.model_validate(body) model: Final[str] = req.resolved_model() or "gpt-realtime-whisper" await can_key_call_resolved_model( @@ -592,6 +727,7 @@ async def create_realtime_transcription_session( ) transcription_session: Final = {k: v for k, v in body.items() if k != "model"} + _set_transcription_model_on_session(session=transcription_session, model=model, create_if_missing=True) data = {"model": model, "transcription_session": transcription_session} data = await add_litellm_data_to_request( diff --git a/litellm/proxy/rerank_endpoints/endpoints.py b/litellm/proxy/rerank_endpoints/endpoints.py index 4f2daed15ed..4905751a85d 100644 --- a/litellm/proxy/rerank_endpoints/endpoints.py +++ b/litellm/proxy/rerank_endpoints/endpoints.py @@ -20,6 +20,7 @@ from litellm.proxy.common_utils.openai_error_payload import ( openai_error_param, openai_error_type, ) +from litellm.types.utils import CallTypes router: Final = APIRouter() @@ -114,7 +115,10 @@ async def rerank( return response except Exception as e: await proxy_logging_obj.post_call_failure_hook( - user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data + user_api_key_dict=user_api_key_dict, + original_exception=e, + request_data=data, + dispatched_call_type=CallTypes.arerank.value, ) log_llm_api_exception(e, litellm_call_id) if isinstance(e, HTTPException): diff --git a/litellm/proxy/response_api_endpoints/endpoints.py b/litellm/proxy/response_api_endpoints/endpoints.py index 3f76bcf69ad..c4cd7c2d411 100644 --- a/litellm/proxy/response_api_endpoints/endpoints.py +++ b/litellm/proxy/response_api_endpoints/endpoints.py @@ -2162,7 +2162,7 @@ _WS_FRAME: Final = TypeAdapter(dict[str, object]) _GUARDRAIL_INFORMATION: Final = TypeAdapter(list[dict[str, object]]) _PII_TOKENS: Final = TypeAdapter(dict[str, str]) _GUARDRAIL_INFORMATION_KEY: Final = "standard_logging_guardrail_information" -_GUARDED_FRAME_FIELDS: Final = ("input", "instructions", "tools") +_GUARDED_FRAME_FIELDS: Final = ("input", "instructions", "tools", "tool_choice", "extra_body") _CLIENT_METADATA_KEYS: Final = ("metadata", "litellm_metadata") _CLIENT_GUARDRAIL_SELECTORS: Final = ("guardrails", "guardrail_config", "policies") _METADATA_GUARDRAIL_SELECTORS: Final = ("guardrails", "guardrail_config") diff --git a/litellm/proxy/route_llm_request.py b/litellm/proxy/route_llm_request.py index ecc31f3b0a7..148d465099f 100644 --- a/litellm/proxy/route_llm_request.py +++ b/litellm/proxy/route_llm_request.py @@ -621,7 +621,9 @@ RouteType = Literal[ "alist_input_items", "_arealtime", # private function for realtime API "acreate_realtime_client_secret", + "acreate_realtime_translation_client_secret", "arealtime_calls", + "arealtime_translation_calls", "acreate_realtime_transcription_session", "_aresponses_websocket", # private function for responses WebSocket mode "aimage_edit", diff --git a/litellm/proxy/schema.prisma b/litellm/proxy/schema.prisma index 179b741fe7c..818f2dc4858 100644 --- a/litellm/proxy/schema.prisma +++ b/litellm/proxy/schema.prisma @@ -1615,9 +1615,77 @@ model LiteLLM_ClaudeCodePluginTable { updated_at DateTime? @default(now()) @updatedAt created_by String? + uploaded_archive LiteLLM_ClaudeCodePluginUpload? + versions LiteLLM_ClaudeCodePluginVersion[] + downloads LiteLLM_ClaudeCodePluginDownload[] + anonymous_download_count BigInt @default(0) + @@map("LiteLLM_ClaudeCodePluginTable") } +model LiteLLM_ClaudeCodePluginVersion { + id String @id @default(uuid()) + plugin_id String + version String? + description String? + manifest_json String? + published_at DateTime? + published_by String? + archive_available Boolean @default(false) + content Bytes? + plugin LiteLLM_ClaudeCodePluginTable @relation(fields: [plugin_id], references: [id], onDelete: Cascade, onUpdate: Cascade) + + @@unique([plugin_id, version]) + @@index([plugin_id, published_at]) +} + + +model LiteLLM_SkillSubmission { + id String @id @default(uuid()) + plugin_name String + operation String + status String @default("pending_review") + proposal_json String + archive_content Bytes? + submitted_by String + created_at DateTime @default(now()) + base_plugin_id String? + base_updated_at DateTime? + reviewed_by String? + reviewed_at DateTime? + rejection_reason String? + scan_json String? + + @@index([submitted_by, created_at(sort: Desc), id(sort: Desc)]) + @@index([submitted_by, status, created_at(sort: Desc), id(sort: Desc)]) + @@index([status, created_at(sort: Desc), id(sort: Desc)]) + @@index([created_at(sort: Desc), id(sort: Desc)]) +} + +model LiteLLM_ClaudeCodePluginDownload { + id BigInt @id @default(autoincrement()) + plugin_id String + downloaded_at DateTime @default(now()) + version String? + digest String + authenticated Boolean + user_id String? + user_email String? + key_alias String? + team_id String? + team_alias String? + plugin LiteLLM_ClaudeCodePluginTable @relation(fields: [plugin_id], references: [id], onDelete: Cascade, onUpdate: Cascade) + + @@index([plugin_id, id]) +} + +model LiteLLM_ClaudeCodePluginUpload { + plugin_name String @id + content Bytes + plugin LiteLLM_ClaudeCodePluginTable @relation(fields: [plugin_name], references: [name], onDelete: Cascade, onUpdate: Cascade) +} + + // User/team-scoped memory store with a GLOBAL unique key. // `value` is a string (typically markdown/text meant for LLM context); // `metadata` is an optional JSON envelope for structured tags without schema changes. @@ -2062,74 +2130,27 @@ model LiteLLM_TelemetryReport { @@index([created_at]) } -enum AccountingEventKind { - inbound_usage - outbound_usage - cost -} - enum AccountingDeliveryState { pending applied parked } -enum AccountingDeliveryTarget { - LiteLLM_VerificationToken - LiteLLM_UserTable - LiteLLM_TeamTable - LiteLLM_TeamMembership - LiteLLM_OrganizationTable - LiteLLM_OrganizationMembership - LiteLLM_EndUserTable - LiteLLM_AgentsTable - LiteLLM_TagTable - LiteLLM_ProjectTable - LiteLLM_ModelAccessGroupBudgetTable - LiteLLM_BudgetTable - LiteLLM_BudgetWindowSpend - LiteLLM_DailyUserSpend - LiteLLM_DailyTeamSpend - LiteLLM_DailyOrganizationSpend - LiteLLM_DailyEndUserSpend - LiteLLM_DailyAgentSpend - LiteLLM_DailyTagSpend - LiteLLM_DailyModelUsage - LiteLLM_DailyToolSpend - LiteLLM_AutoRouterDailySpend -} +model LiteLLM_SpendLogDelivery { + delivery_id String @id @default(dbgenerated("(gen_random_uuid())::text")) + request_id String + state AccountingDeliveryState @default(pending) + accounting_payload Json + is_batch Boolean + attempts Int @default(0) + next_attempt_at DateTime @default(now()) + applied_at DateTime? + last_error String? + created_at DateTime @default(now()) -// Durable accounting ledger. One row per usage or cost event; payload holds the -// private event envelope versioned by schema_version. Usage rows retain request-scoped -// pricing context; cost rows include resolved rates and the finalized pricing snapshot. -model LiteLLM_AccountingEvent { - event_id String @id - kind AccountingEventKind - source_event_id String? - schema_version Int - payload_hash String - occurred_at DateTime - recorded_at DateTime @default(now()) - payload Json - - @@index([recorded_at]) - @@index([kind, source_event_id]) -} - -// One row per (event, target table, version): pending work for the projector and, -// once applied in the same transaction as the target write, the receipt that stops a retry. -model LiteLLM_AccountingDelivery { - event_id String - target AccountingDeliveryTarget - version Int - state AccountingDeliveryState @default(pending) - attempts Int @default(0) - next_attempt_at DateTime @default(now()) - applied_at DateTime? - last_error String? - - @@id([event_id, target, version]) - @@index([target, state, next_attempt_at]) + @@index([state, next_attempt_at]) + @@index([state, applied_at]) + @@index([request_id]) } model LiteLLM_SubscriptionAccountTable { diff --git a/litellm/proxy/shutdown/graceful_uvicorn_worker.py b/litellm/proxy/shutdown/graceful_uvicorn_worker.py index 6ae5ae60c3f..0bbbfe0a4a9 100644 --- a/litellm/proxy/shutdown/graceful_uvicorn_worker.py +++ b/litellm/proxy/shutdown/graceful_uvicorn_worker.py @@ -1,10 +1,21 @@ from uvicorn.workers import UvicornWorker +from litellm.constants import DEFAULT_MAX_REQUEST_HEADER_SIZE -def build_graceful_shutdown_uvicorn_worker(timeout_graceful_shutdown: float) -> type[UvicornWorker]: + +def build_graceful_shutdown_uvicorn_worker( + timeout_graceful_shutdown: float, + max_request_header_size: int | None = None, +) -> type[UvicornWorker]: class GracefulShutdownUvicornWorker(UvicornWorker): def __init__(self, *args: object) -> None: - self.CONFIG_KWARGS = {**UvicornWorker.CONFIG_KWARGS, "timeout_graceful_shutdown": timeout_graceful_shutdown} + self.CONFIG_KWARGS = { + **UvicornWorker.CONFIG_KWARGS, + "timeout_graceful_shutdown": timeout_graceful_shutdown, + "h11_max_incomplete_event_size": ( + max_request_header_size if max_request_header_size is not None else DEFAULT_MAX_REQUEST_HEADER_SIZE + ), + } super().__init__(*args) return GracefulShutdownUvicornWorker diff --git a/litellm/proxy/spend_tracking/budget_reservation.py b/litellm/proxy/spend_tracking/budget_reservation.py index fc6fb266d04..af7eb742aa7 100644 --- a/litellm/proxy/spend_tracking/budget_reservation.py +++ b/litellm/proxy/spend_tracking/budget_reservation.py @@ -432,7 +432,7 @@ async def invalidate_budget_reservation_counters( async def release_or_invalidate_budget_reservation( - budget_reservation: dict | None, # mutable-ok: stamps finalized on the caller's shared reservation dict + budget_reservation: dict[str, object] | None, # mutable-ok: stamps finalized on the caller's reservation ) -> None: """Reconcile a still-open reservation on a terminal path that settles no cost. @@ -1264,6 +1264,15 @@ def _get_entry_reserved_cost(entry: dict, default_reserved_cost: float) -> float return default_reserved_cost +def fixed_budget_window(window: object) -> tuple[str, datetime] | None: + fields: Final = _coerce_window(window) + start: Final = get_budget_window_start(window) + duration: Final = fields.get("budget_duration") + if not fields.get("reset_at") or not isinstance(duration, str) or start is None: + return None + return duration, start + + def get_budget_window_start(window: object) -> datetime | None: window_dict: Final = _coerce_window(window) budget_duration: Final = window_dict.get("budget_duration") diff --git a/litellm/proxy/spend_tracking/session_page.py b/litellm/proxy/spend_tracking/session_page.py new file mode 100644 index 00000000000..810afbfa7b7 --- /dev/null +++ b/litellm/proxy/spend_tracking/session_page.py @@ -0,0 +1,221 @@ +"""Which sessions a logs page shows and how many match, read from the newest rows instead of every row. Reads grow +until one settles both, so the result is what grouping every row would give.""" + +import math +from collections.abc import Awaitable, Callable, Sequence +from dataclasses import dataclass +from typing import Final, Protocol, TypeAlias + +from typing_extensions import ReadOnly, TypedDict + +MCP_CALL_TYPES_SQL: Final = "('call_mcp_tool', 'list_mcp_tools')" +AGENT_CALL_TYPE_SQL: Final = "'asend_message'" +SESSION_KEY_EXPR: Final = "COALESCE(NULLIF(session_id, ''), request_id)" +SESSION_REPRESENTATIVE_ORDER_SQL: Final = ( + f"(call_type = {AGENT_CALL_TYPE_SQL}) DESC, " + f'CASE WHEN call_type = {AGENT_CALL_TYPE_SQL} THEN "endTime" END DESC NULLS LAST, ' + f'call_type IN {MCP_CALL_TYPES_SQL}, "startTime" DESC, request_id' +) + + +class _ReadRow(TypedDict): + session_key: ReadOnly[str | None] + api_key: ReadOnly[str | None] + last_activity: ReadOnly[str | None] + settled: ReadOnly[bool | None] + rows_read: ReadOnly[int] + session_count: ReadOnly[int] + + +class _SupportsQueryRaw(Protocol): + async def query_raw(self, query: str, *args: object) -> Sequence[_ReadRow]: ... + + +@dataclass(frozen=True, slots=True) +class Session: + key: str + api_key: str + last_activity: str + + +@dataclass(frozen=True, slots=True) +class SessionPage: + sessions: tuple[Session, ...] + has_more: bool + next_cursor: str | None + total: int + total_is_capped: bool + + +@dataclass(frozen=True, slots=True) +class _Request: + cursor: tuple[str, str, str] | None + offset: int + page_limit: int + sort_desc: bool + status: str | None + cap: int + + def first_read_size(self) -> int | None: + """Every row when oldest first, or when filtered by outcome, which any of a session's rows can decide. Otherwise + the fewest that could settle a page: a session past the cap and an older row.""" + return self.cap + 2 if self.sort_desc and self.status is None else None + + +@dataclass(frozen=True, slots=True) +class _Read: + candidates: tuple[Session, ...] + last_settled: bool + rows_read: int + session_count: int + saw_every_row: bool + + def settles(self, request: _Request) -> bool: + page_settled: Final = ( + request.page_limit <= 0 + or self.saw_every_row + or (len(self.candidates) > request.page_limit and self.last_settled) + ) + return page_settled and (self.saw_every_row or self.session_count > request.cap) + + def next_size(self, request: _Request) -> int: + rows_per_session: Final = self.rows_read / self.session_count + return max(2 * self.rows_read, math.ceil(1.25 * (request.cap + 1) * rows_per_session)) + + +_Reader: TypeAlias = Callable[[int | None], Awaitable[_Read]] + + +def _parse_session_cursor(session_cursor: str | None) -> tuple[str, str, str] | None: + if session_cursor is None or session_cursor.count("|") < 2: + return None + last_activity, _, rest = session_cursor.partition("|") + api_key, _, session_key = rest.partition("|") + if not last_activity or not session_key: + return None + return (last_activity, session_key, api_key) + + +async def read_session_page( + db: _SupportsQueryRaw, + *, + where_clause: str, + params: Sequence[object], + status: str | None, + page: int, + page_size: int, + sort_desc: bool, + session_cursor: str | None, + cap: int, +) -> SessionPage: + """One page of sessions after ``session_cursor``, or after ``(page - 1) * page_size`` sessions, keeping only those + whose outcome is ``status`` when given. ``where_clause`` reads ``params`` as ``$1`` onward.""" + cursor: Final = _parse_session_cursor(session_cursor) + offset: Final = (page - 1) * page_size if cursor is None else 0 + request: Final = _Request(cursor, offset, min(page_size, cap - offset), sort_desc, status, cap) + return await _session_page(_sql_reader(db, where_clause, params, request), request) + + +async def _session_page(read: _Reader, request: _Request) -> SessionPage: + last = await read(request.first_read_size()) # rebind-ok: each read replaces the last until one settles the page + while not last.settles(request): + last = await read(last.next_size(request)) + has_more: Final = len(last.candidates) > request.page_limit + sessions: Final = last.candidates[: request.page_limit] + final: Final = sessions[-1] if has_more and sessions else None + return SessionPage( + sessions=sessions, + has_more=has_more, + next_cursor=f"{final.last_activity}|{final.api_key}|{final.key}" if final else None, + total=min(last.session_count, request.cap), + total_is_capped=last.session_count > request.cap, + ) + + +def _sessions_sql(request: _Request, status_index: int) -> str: + """Each session's last activity, from its rows in ``scanned``, keeping only sessions whose outcome is the status.""" + if request.status is None: + return ( + 'SELECT session_key, api_key, MAX("startTime") AS last_activity FROM scanned GROUP BY session_key, api_key' + ) + return f""" + SELECT session_key, api_key, last_activity + FROM ( + SELECT DISTINCT ON (session_key, api_key) + session_key, + api_key, + status, + MAX("startTime") OVER (PARTITION BY session_key, api_key) AS last_activity + FROM scanned + ORDER BY session_key, api_key, {SESSION_REPRESENTATIVE_ORDER_SQL} + ) AS outcomes + WHERE COALESCE(status, 'success') = ${status_index} + """ + + +def _sql_reader(db: _SupportsQueryRaw, where_clause: str, params: Sequence[object], request: _Request) -> _Reader: + status_index: Final = len(params) + 1 + status_args: Final = () if request.status is None else (request.status,) + cursor_index: Final = status_index + len(status_args) + after_cursor: Final = ( + f"WHERE (last_activity, session_key, api_key) {'<' if request.sort_desc else '>'} " + f"(${cursor_index}::timestamp, ${cursor_index + 1}, ${cursor_index + 2})" + if request.cursor + else "" + ) + outcome_columns: Final = ', status, call_type, "endTime", request_id' if request.status is not None else "" + direction: Final = "DESC" if request.sort_desc else "ASC" + page_rows: Final = request.page_limit + 1 if request.page_limit > 0 else 0 + skip: Final = f"OFFSET {request.offset}" if page_rows and request.offset else "" + + async def read(size: int | None) -> _Read: + # LEFT JOIN keeps the summary row when no session is on the page. + rows: Final = await db.query_raw( + f""" + WITH scanned AS ( + SELECT {SESSION_KEY_EXPR} AS session_key, api_key, "startTime"{outcome_columns} + FROM "LiteLLM_SpendLogs" + WHERE {where_clause} + {f'ORDER BY "startTime" DESC LIMIT {size}' if size is not None else ""} + ), + sessions AS ({_sessions_sql(request, status_index)}), + summary AS ( + SELECT COUNT(*) AS rows_read, + MIN("startTime") AS oldest, + (SELECT COUNT(*) FROM sessions) AS session_count + FROM scanned + ) + SELECT page.session_key, + page.api_key, + page.last_activity::text AS last_activity, + page.last_activity > summary.oldest AS settled, + summary.rows_read, + summary.session_count + FROM summary + LEFT JOIN LATERAL ( + SELECT session_key, api_key, last_activity + FROM sessions + {after_cursor} + ORDER BY last_activity {direction}, session_key {direction}, api_key {direction} + LIMIT {page_rows} {skip} + ) AS page ON TRUE + ORDER BY page.last_activity {direction}, page.session_key {direction}, page.api_key {direction} + """, + *params, + *status_args, + *(request.cursor or ()), + ) + rows_read: Final = int(rows[0]["rows_read"]) + return _Read( + candidates=tuple( + Session(str(row["session_key"]), str(row["api_key"]), str(row["last_activity"])) + for row in rows + if row["session_key"] is not None + ), + last_settled=bool(rows[-1]["settled"]), + rows_read=rows_read, + session_count=int(rows[0]["session_count"]), + saw_every_row=size is None or rows_read < size, + ) + + return read diff --git a/litellm/proxy/spend_tracking/spend_event.py b/litellm/proxy/spend_tracking/spend_event.py index 031e84896b2..d054519cb9c 100644 --- a/litellm/proxy/spend_tracking/spend_event.py +++ b/litellm/proxy/spend_tracking/spend_event.py @@ -28,6 +28,7 @@ from litellm.proxy.db.spend_log_tool_index import response_tool_call_names from litellm.types.interactions import InteractionsAPIResponse from litellm.types.llms.base import LiteLLMBaseModel from litellm.types.utils import LiteLLMBatch, Usage +from litellm.types.videos.utils import is_video_status_call_type SPEND_EVENT_VERSION: Final = 1 CACHE_OFF_KEY: Final = "Cache OFF" @@ -205,9 +206,10 @@ class SpendEventDecodeError: reason: str -def is_offloadable_success(response_obj: object) -> bool: - """Batch retrieves and interaction polls branch on the concrete response class, so they stay in-process.""" - return not isinstance(response_obj, _NOT_OFFLOADED_RESPONSE_TYPES) +def is_offloadable_success(response_obj: object, call_type: object) -> bool: + """Batch retrieves and interaction polls branch on the concrete response class, and a video status poll on + the status and video id the event leaves out, so they stay in-process.""" + return not isinstance(response_obj, _NOT_OFFLOADED_RESPONSE_TYPES) and not is_video_status_call_type(call_type) def _json_fallback(value: object) -> str: diff --git a/litellm/proxy/spend_tracking/spend_management_endpoints.py b/litellm/proxy/spend_tracking/spend_management_endpoints.py index 89200792c0b..fcb9eb4a280 100644 --- a/litellm/proxy/spend_tracking/spend_management_endpoints.py +++ b/litellm/proxy/spend_tracking/spend_management_endpoints.py @@ -3,6 +3,7 @@ import collections import json import os from collections.abc import Mapping, Sequence +from dataclasses import dataclass from datetime import date, datetime, timedelta, timezone from functools import partial from itertools import groupby @@ -52,6 +53,13 @@ from litellm.proxy.auth.authorization_dependencies import ( from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.common_utils.openai_error_payload import error_status_code, openai_error_param, openai_error_type from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup +from litellm.proxy.spend_tracking.session_page import ( + AGENT_CALL_TYPE_SQL, + MCP_CALL_TYPES_SQL, + SESSION_KEY_EXPR, + SESSION_REPRESENTATIVE_ORDER_SQL, + read_session_page, +) from litellm.proxy.spend_tracking.spend_capture_rate import ( ProviderBillingCredentialMissing, ProviderBillingRequestFailed, @@ -65,7 +73,7 @@ from litellm.proxy.spend_tracking.spend_tracking_utils import ( get_spend_by_team, get_spend_by_team_and_customer, ) -from litellm.proxy.utils import handle_exception_on_proxy +from litellm.proxy.utils import handle_exception_on_proxy, query_raw_within_statement_timeout from litellm.repositories.prisma_protocols import TableActions from litellm.repositories.table_repositories import SpendLogsRepository from litellm.repositories.team_repository import TeamRepository @@ -87,23 +95,15 @@ router: Final = APIRouter() SPEND_LOGS_PAGINATION_COUNT_CAP: Final = 10000 _DECODED_JSON: Final = TypeAdapter(object) -_SESSION_KEY_EXPR: Final = "COALESCE(NULLIF(session_id, ''), request_id)" -_SESSION_GROUP_KEY_SQL: Final = f"{_SESSION_KEY_EXPR}, api_key" -_MCP_CALL_TYPES_SQL: Final = "('call_mcp_tool', 'list_mcp_tools')" -_AGENT_CALL_TYPE_SQL: Final = "'asend_message'" -_SESSION_REPRESENTATIVE_ORDER_SQL: Final = ( - f"(call_type = {_AGENT_CALL_TYPE_SQL}) DESC, " - f'CASE WHEN call_type = {_AGENT_CALL_TYPE_SQL} THEN "endTime" END DESC NULLS LAST, ' - f'call_type IN {_MCP_CALL_TYPES_SQL}, "startTime" DESC, request_id' -) +_SESSION_GROUP_KEY_SQL: Final = f"{SESSION_KEY_EXPR}, api_key" _BATCH_CALL_TYPES_SQL: Final = "('acreate_batch', 'create_batch', 'aretrieve_batch', 'retrieve_batch')" _SPAN_TYPE_SQL_CONDITIONS: Final[Mapping[str, str]] = MappingProxyType( { - "mcp": f"call_type IN {_MCP_CALL_TYPES_SQL}", - "agent": f"call_type = {_AGENT_CALL_TYPE_SQL}", + "mcp": f"call_type IN {MCP_CALL_TYPES_SQL}", + "agent": f"call_type = {AGENT_CALL_TYPE_SQL}", "batch": f"call_type IN {_BATCH_CALL_TYPES_SQL}", "llm": ( - f"(call_type NOT IN {_MCP_CALL_TYPES_SQL} AND call_type != {_AGENT_CALL_TYPE_SQL} " + f"(call_type NOT IN {MCP_CALL_TYPES_SQL} AND call_type != {AGENT_CALL_TYPE_SQL} " f"AND call_type NOT IN {_BATCH_CALL_TYPES_SQL})" ), } @@ -268,6 +268,20 @@ async def _query_raw_or_none(prisma_client: PrismaClient, sql_query: str, *args: return await _query_raw(prisma_client, sql_query, *args) +async def _query_spend_logs(prisma_client: PrismaClient, sql_query: str, *args: object) -> Sequence[_RowT]: + return cast( # cast-ok: callers declare the row shape their SELECT list produces, as with _query_raw + "Sequence[_RowT]", await query_raw_within_statement_timeout(prisma_client, sql_query, *args) + ) + + +@dataclass(frozen=True, slots=True) +class _SpendLogsReader: + prisma_client: PrismaClient + + async def query_raw(self, query: str, *args: object) -> Sequence[Mapping[str, object]]: + return await query_raw_within_statement_timeout(self.prisma_client, query, *args) + + class _TeamTable(Protocol): """The subset of the Prisma team table API this module uses.""" @@ -1567,10 +1581,7 @@ async def get_global_spend_report( ORDER BY total_cost DESC; """ - db_response = await _query_raw_or_none(prisma_client, sql_query, start_date_obj, end_date_obj, api_key) - if db_response is None: - return [] - + db_response = await _query_spend_logs(prisma_client, sql_query, start_date_obj, end_date_obj, api_key) return db_response elif internal_user_id is not None: verbose_proxy_logger.debug("Getting /spend for internal_user_id: %s", internal_user_id) @@ -1610,12 +1621,9 @@ async def get_global_spend_report( ORDER BY total_cost DESC; """ - db_response = await _query_raw_or_none( + db_response = await _query_spend_logs( prisma_client, sql_query, start_date_obj, end_date_obj, internal_user_id ) - if db_response is None: - return [] - return db_response elif team_id is not None and customer_id is not None: return await get_spend_by_team_and_customer( @@ -1677,10 +1685,7 @@ async def get_global_spend_report( group_by_day; """ - db_response = await _query_raw_or_none(prisma_client, sql_query, start_date_obj, end_date_obj) - if db_response is None: - return [] - + db_response = await _query_spend_logs(prisma_client, sql_query, start_date_obj, end_date_obj) return db_response elif group_by == "api_key": sql_query = """ @@ -1718,12 +1723,11 @@ async def get_global_spend_report( ORDER BY total_cost DESC; """ - db_response = await _query_raw_or_none(prisma_client, sql_query, start_date_obj, end_date_obj) - if db_response is None: - return [] - + db_response = await _query_spend_logs(prisma_client, sql_query, start_date_obj, end_date_obj) return db_response + except HTTPException: + raise except Exception as e: raise HTTPException( status_code=status.HTTP_400_BAD_REQUEST, @@ -1967,7 +1971,7 @@ async def get_key_spend_report( caller_value=LiteLLMProxyRequestSetup.get_logged_api_key(user_api_key_dict), scope_name="api_key", ) - db_response: Sequence[Mapping[str, object]] | None = await _query_raw_or_none( + db_response: Sequence[Mapping[str, object]] = await _query_spend_logs( prisma_client, _scoped_spend_report_sql(scope_column="api_key"), start_date_obj, @@ -2009,7 +2013,7 @@ async def get_user_spend_report( caller_value=user_api_key_dict.user_id, scope_name="internal_user_id", ) - db_response: Sequence[Mapping[str, object]] | None = await _query_raw_or_none( + db_response: Sequence[Mapping[str, object]] = await _query_spend_logs( prisma_client, _scoped_spend_report_sql(scope_column="user"), start_date_obj, @@ -2051,7 +2055,7 @@ async def get_team_spend_report( caller_value=user_api_key_dict.team_id, scope_name="team_id", ) - db_response: Sequence[Mapping[str, object]] | None = await _query_raw_or_none( + db_response: Sequence[Mapping[str, object]] = await _query_spend_logs( prisma_client, _scoped_spend_report_sql(scope_column="team_id"), start_date_obj, @@ -2093,7 +2097,7 @@ async def get_organization_spend_report( organization_id=organization_id, prisma_client=prisma_client, ) - db_response: Sequence[Mapping[str, object]] | None = await _query_raw_or_none( + db_response: Sequence[Mapping[str, object]] = await _query_spend_logs( prisma_client, _ORG_SPEND_REPORT_SQL, start_date_obj, @@ -2948,23 +2952,6 @@ async def ui_view_spend_logs( sql_params.append(json.dumps(used_client_oauth_token)) p += 1 - if status_filter is not None and group_by_session is True and not is_search_lookup: - session_filter_conditions: Final = " AND ".join(sql_conditions) or "TRUE" - sql_conditions.append( - f"""({_SESSION_GROUP_KEY_SQL}) IN ( - SELECT session_key, api_key FROM ( - SELECT DISTINCT ON ({_SESSION_GROUP_KEY_SQL}) - {_SESSION_KEY_EXPR} AS session_key, api_key, status - FROM "LiteLLM_SpendLogs" - WHERE {session_filter_conditions} - ORDER BY {_SESSION_GROUP_KEY_SQL}, {_SESSION_REPRESENTATIVE_ORDER_SQL} - ) AS session_outcomes - WHERE COALESCE(status, 'success') = ${p} - )""" - ) - sql_params.append(status_filter) - p += 1 - if ( group_by_session is True and not is_v2 @@ -2977,12 +2964,30 @@ async def ui_view_spend_logs( sql_conditions=sql_conditions, sql_params=sql_params, next_param_index=p, + status_filter=status_filter, page=page, page_size=page_size, sort_desc=order_direction != "asc", session_cursor=session_cursor, ) + if status_filter is not None and group_by_session is True and not is_search_lookup: + session_filter_conditions: Final = " AND ".join(sql_conditions) or "TRUE" + sql_conditions.append( + f"""({_SESSION_GROUP_KEY_SQL}) IN ( + SELECT session_key, api_key FROM ( + SELECT DISTINCT ON ({_SESSION_GROUP_KEY_SQL}) + {SESSION_KEY_EXPR} AS session_key, api_key, status + FROM "LiteLLM_SpendLogs" + WHERE {session_filter_conditions} + ORDER BY {_SESSION_GROUP_KEY_SQL}, {SESSION_REPRESENTATIVE_ORDER_SQL} + ) AS session_outcomes + WHERE COALESCE(status, 'success') = ${p} + )""" + ) + sql_params.append(status_filter) + p += 1 + # Build the ORDER BY expression. ttft_ms is computed from # completionStartTime - startTime; non-streaming rows (where # completionStartTime is null or equals endTime) yield NULL, so we @@ -3017,7 +3022,7 @@ async def ui_view_spend_logs( LIMIT ${p} ) AS bounded_matches """ - count_rows: Final[Sequence[_SpendLogsCountRow] | None] = await _query_raw_or_none( + count_rows: Final[Sequence[_SpendLogsCountRow]] = await _query_spend_logs( prisma_client, count_query, *sql_params, SPEND_LOGS_PAGINATION_COUNT_CAP + 1 ) raw_total: Final = int(count_rows[0]["total_count"]) if count_rows else 0 @@ -3031,7 +3036,7 @@ async def ui_view_spend_logs( {_SPEND_LOG_LIST_COLUMNS} FROM "LiteLLM_SpendLogs" WHERE {joined_conditions} - ORDER BY {_SESSION_GROUP_KEY_SQL}, {_SESSION_REPRESENTATIVE_ORDER_SQL} + ORDER BY {_SESSION_GROUP_KEY_SQL}, {SESSION_REPRESENTATIVE_ORDER_SQL} ) AS session_representatives ORDER BY {exact_request_id_first}{_order_expr} {_sql_dir}{_nulls_clause}, request_id LIMIT ${p} OFFSET ${p + 1} @@ -3048,7 +3053,7 @@ async def ui_view_spend_logs( ) sql_params.extend([page_size, skip]) - data: Final[Sequence[Mapping[str, object]]] = await _query_raw(prisma_client, sql_query, *sql_params) + data: Final[Sequence[Mapping[str, object]]] = await _query_spend_logs(prisma_client, sql_query, *sql_params) if request_id is not None and not is_v2 and not is_admin_view: await _assert_user_owns_fetched_spend_rows( @@ -3080,22 +3085,6 @@ async def ui_view_spend_logs( raise handle_exception_on_proxy(e) -class _SessionPageRow(TypedDict): - session_key: ReadOnly[str] - api_key: ReadOnly[str] - last_activity: ReadOnly[str] - - -def _parse_session_cursor(session_cursor: str | None) -> tuple[str, str, str] | None: - if session_cursor is None or session_cursor.count("|") < 2: - return None - last_activity, _, rest = session_cursor.partition("|") - api_key, _, session_key = rest.partition("|") - if not last_activity or not session_key: - return None - return (last_activity, session_key, api_key) - - async def _fetch_session_representatives( prisma_client: "PrismaClient", where_clause: str, @@ -3104,19 +3093,21 @@ async def _fetch_session_representatives( session_keys: Sequence[tuple[str, str]], ) -> list[dict[str, object]]: # mutable-ok: _build_ui_spend_logs_response writes session counts onto each row """Fetch the final agent outcome, or newest non-MCP row, of each ``(session_key, api_key)`` session, in ``session_keys`` order.""" + # Lets Postgres use the session_id and request_id indexes. rep_query: Final = f""" SELECT * FROM ( SELECT DISTINCT ON ({_SESSION_GROUP_KEY_SQL}) {_SPEND_LOG_LIST_COLUMNS} FROM "LiteLLM_SpendLogs" WHERE {where_clause} + AND (session_id = ANY(${next_param_index}::text[]) OR request_id = ANY(${next_param_index}::text[])) AND ({_SESSION_GROUP_KEY_SQL}) IN ( SELECT * FROM unnest(${next_param_index}::text[], ${next_param_index + 1}::text[]) ) - ORDER BY {_SESSION_GROUP_KEY_SQL}, {_SESSION_REPRESENTATIVE_ORDER_SQL} + ORDER BY {_SESSION_GROUP_KEY_SQL}, {SESSION_REPRESENTATIVE_ORDER_SQL} ) AS session_representatives """ - rep_rows: Final[Sequence[dict[str, object]]] = await _query_raw( # mutable-ok: rows are enriched in place + rep_rows: Final[Sequence[dict[str, object]]] = await _query_spend_logs( # mutable-ok: rows are enriched in place prisma_client, rep_query, *sql_params, @@ -3129,117 +3120,32 @@ async def _fetch_session_representatives( return [rep_by_key[key] for key in session_keys if key in rep_by_key] -async def _count_grouped_sessions( - prisma_client: "PrismaClient", - where_clause: str, - sql_params: Sequence[object], - next_param_index: int, -) -> tuple[int, bool]: - """Count the sessions matching the filter, returning ``(total, total_is_capped)`` bounded by the count cap.""" - count_query: Final = f""" - SELECT COUNT(*) AS total_count - FROM ( - SELECT 1 - FROM "LiteLLM_SpendLogs" - WHERE {where_clause} - GROUP BY {_SESSION_GROUP_KEY_SQL} - LIMIT ${next_param_index} - ) AS bounded_sessions - """ - count_rows: Final[Sequence[_SpendLogsCountRow]] = await _query_raw( - prisma_client, count_query, *sql_params, SPEND_LOGS_PAGINATION_COUNT_CAP + 1 - ) - raw_total: Final = int(count_rows[0]["total_count"]) if count_rows else 0 - return ( - (SPEND_LOGS_PAGINATION_COUNT_CAP, True) if raw_total > SPEND_LOGS_PAGINATION_COUNT_CAP else (raw_total, False) - ) - - async def _ui_session_grouped_spend_logs( prisma_client: "PrismaClient", sql_conditions: Sequence[str], sql_params: Sequence[object], next_param_index: int, + status_filter: str | None, page: int, page_size: int, sort_desc: bool, session_cursor: str | None, ) -> Mapping[str, object]: - """ - One row per session, keyset-paginated by session last activity. - - Sessions are derived on the fly from ``LiteLLM_SpendLogs`` (no extra - table): rows sharing a ``session_id`` and ``api_key`` form a session, rows - without a session id are singletons keyed by ``request_id``. A page is the - next ``page_size`` sessions ordered by ``(MAX(startTime), session_key, - api_key)``, resumed from the ``session_cursor`` keyset - ``'||'`` instead of an OFFSET, so - page depth does not degrade the query plan. A request for ``page > 1`` - without a cursor (the UI jumping straight to the last page, or back to a - page it never walked through) falls back to ``OFFSET (page - 1) * - page_size``, trimmed to the end of the ``SPEND_LOGS_PAGINATION_COUNT_CAP`` - window the capped ``total`` promises, so a page never runs past that total - and one starting at or past it returns no rows without a query. Each session is represented - by its final agent outcome (or newest non-MCP row), enriched by ``_build_ui_spend_logs_response`` - exactly like the flat listing, and the response carries - ``next_session_cursor`` / ``has_more`` while ``total`` counts sessions - (capped like the flat total). A page that runs out of sessions while still - holding some is itself the end of the list, so its ``total`` is - ``offset + len(page)`` and the grouped count query is skipped; a page that - starts past the end says nothing about the total, so that one is counted. - """ + """One row per session, keyset-paginated by last activity. ``read_session_page`` picks and counts the sessions, + and each is shown by its final agent outcome or newest non-MCP row.""" where_clause: Final = " AND ".join(sql_conditions) if sql_conditions else "TRUE" - cmp_op: Final = "<" if sort_desc else ">" - direction: Final = "DESC" if sort_desc else "ASC" - - cursor: Final = _parse_session_cursor(session_cursor) - having_clause: Final = ( - f'HAVING (MAX("startTime"), {_SESSION_GROUP_KEY_SQL}) {cmp_op} ' - f"(${next_param_index}::timestamp, ${next_param_index + 1}, ${next_param_index + 2})" - if cursor - else "" + session_page: Final = await read_session_page( + _SpendLogsReader(prisma_client), # pyright: ignore[reportArgumentType] # rows are the TypedDict the session SQL selects + where_clause=where_clause, + params=sql_params, + status=status_filter, + page=page, + page_size=page_size, + sort_desc=sort_desc, + session_cursor=session_cursor, + cap=SPEND_LOGS_PAGINATION_COUNT_CAP, ) - cursor_params: Final[tuple[object, ...]] = cursor if cursor else () - limit_index: Final = next_param_index + len(cursor_params) - offset: Final = (page - 1) * page_size if cursor is None else 0 - page_limit: Final = min(page_size, SPEND_LOGS_PAGINATION_COUNT_CAP - offset) - offset_params: Final[tuple[int, ...]] = (offset,) if offset and page_limit > 0 else () - offset_clause: Final = f"OFFSET ${limit_index + 1}" if offset_params else "" - - page_query: Final = f""" - SELECT {_SESSION_KEY_EXPR} AS session_key, - api_key, - MAX("startTime")::text AS last_activity - FROM "LiteLLM_SpendLogs" - WHERE {where_clause} - GROUP BY {_SESSION_GROUP_KEY_SQL} - {having_clause} - ORDER BY MAX("startTime") {direction}, {_SESSION_KEY_EXPR} {direction}, api_key {direction} - LIMIT ${limit_index} {offset_clause} - """ - page_rows: Final[Sequence[_SessionPageRow]] = ( - () - if page_limit <= 0 - else await _query_raw(prisma_client, page_query, *sql_params, *cursor_params, page_limit + 1, *offset_params) - ) - - has_more: Final = len(page_rows) > page_limit - visible_rows: Final = page_rows[:page_limit] - next_cursor: Final = ( - f"{visible_rows[-1]['last_activity']}|{visible_rows[-1]['api_key']}|{visible_rows[-1]['session_key']}" - if has_more and visible_rows - else None - ) - - page_starts_inside_the_list: Final = offset == 0 or len(page_rows) > 0 - page_ends_the_list: Final = cursor is None and page_limit > 0 and not has_more and page_starts_inside_the_list - total_records, total_is_capped = ( - (offset + len(page_rows), False) - if page_ends_the_list - else await _count_grouped_sessions(prisma_client, where_clause, sql_params, next_param_index) - ) - - session_keys: Final = tuple((row["session_key"], row["api_key"]) for row in visible_rows) + session_keys: Final = tuple((session.key, session.api_key) for session in session_page.sessions) data: Final[list[dict[str, object]]] = ( # mutable-ok: _build_ui_spend_logs_response writes onto each row await _fetch_session_representatives( prisma_client=prisma_client, @@ -3253,18 +3159,17 @@ async def _ui_session_grouped_spend_logs( ) _hydrate_spend_log_metadata(data) - total_pages: Final = (total_records + page_size - 1) // page_size response: Final[Mapping[str, object]] = await _build_ui_spend_logs_response( prisma_client, data, - total_records, + session_page.total, page, page_size, - total_pages, + (session_page.total + page_size - 1) // page_size, enrich_session_counts=True, - total_is_capped=total_is_capped, + total_is_capped=session_page.total_is_capped, ) - return {**response, "next_session_cursor": next_cursor, "has_more": has_more} + return {**response, "next_session_cursor": session_page.next_cursor, "has_more": session_page.has_more} class RequestResponsePayload(NamedTuple): @@ -4705,7 +4610,7 @@ async def _build_ui_spend_logs_response( if (row.get("api_key") if isinstance(row, dict) else getattr(row, "api_key", None)) is not None } ) - rows: Final[Sequence[_SessionSpendRow]] = await _query_raw( + rows: Final[Sequence[_SessionSpendRow]] = await _query_spend_logs( prisma_client, f""" SELECT s.*, COALESCE(m.session_models, ARRAY[]::text[]) AS session_models @@ -4720,16 +4625,16 @@ async def _build_ui_spend_logs_response( ) ), 0)::bigint AS session_total_duration_ms, COUNT(*) FILTER ( - WHERE call_type IN {_MCP_CALL_TYPES_SQL} + WHERE call_type IN {MCP_CALL_TYPES_SQL} )::int AS mcp_tool_call_count, COALESCE(SUM(spend) FILTER ( - WHERE call_type IN {_MCP_CALL_TYPES_SQL} + WHERE call_type IN {MCP_CALL_TYPES_SQL} ), 0)::double precision AS mcp_tool_call_spend, COUNT(*) FILTER (WHERE LOWER(cache_hit) = 'true')::int AS session_cache_hit_count, COUNT(*) FILTER ( - WHERE call_type NOT IN {_MCP_CALL_TYPES_SQL} AND call_type != {_AGENT_CALL_TYPE_SQL} + WHERE call_type NOT IN {MCP_CALL_TYPES_SQL} AND call_type != {AGENT_CALL_TYPE_SQL} )::int AS session_llm_count, - COUNT(*) FILTER (WHERE call_type = {_AGENT_CALL_TYPE_SQL})::int AS session_agent_count, + COUNT(*) FILTER (WHERE call_type = {AGENT_CALL_TYPE_SQL})::int AS session_agent_count, COALESCE(SUM(prompt_tokens), 0)::bigint AS session_total_prompt_tokens, COALESCE(SUM(completion_tokens), 0)::bigint AS session_total_completion_tokens, COALESCE(SUM(total_tokens), 0)::bigint AS session_total_tokens @@ -4776,7 +4681,7 @@ async def _build_ui_spend_logs_response( if row.get("session_id") and row.get("api_key") is not None for models in (TypeAdapter(list[str]).validate_python(row.get("session_models") or ()),) } - except PrismaError: + except (PrismaError, HTTPException): verbose_proxy_logger.debug( "Failed to enrich session spend aggregates for spend logs UI", exc_info=True, diff --git a/litellm/proxy/spend_tracking/spend_tracking_utils.py b/litellm/proxy/spend_tracking/spend_tracking_utils.py index ba5f873c4e9..fc54d1da0b2 100644 --- a/litellm/proxy/spend_tracking/spend_tracking_utils.py +++ b/litellm/proxy/spend_tracking/spend_tracking_utils.py @@ -3,7 +3,7 @@ import json import os import re import secrets -from collections.abc import Callable, Mapping, Sequence +from collections.abc import Mapping, Sequence from datetime import datetime, timezone from datetime import datetime as dt from functools import reduce @@ -20,7 +20,6 @@ from litellm.constants import ( CALLER_SESSION_ID_METADATA_KEY, CLI_SESSION_KEY_PREFIX, EMPTY_MAPPING, - INTERNAL_CALL_ORIGIN_METADATA_KEY, KUBERNETES_POD_ROUTING_KEY, LITELLM_PROXY_MASTER_KEY_ALIAS, LITELLM_TRUNCATED_PAYLOAD_FIELD, @@ -30,7 +29,6 @@ from litellm.constants import ( MAX_SPEND_LOG_MODEL_NAME_LENGTH, MAX_STRING_LENGTH_COMPACTION_SUMMARY_IN_DB, MCP_SPEND_LOG_MODEL_PREFIX, - NON_INFERENCE_CALL_TYPES, REDACTED_BY_LITELM_STRING, SESSION_ID_OMITTED_METADATA_KEY, UNKNOWN_MODEL_SPEND_LOG_MODEL, @@ -40,6 +38,12 @@ from litellm.constants import ( ) from litellm.integrations.otel.model.metadata import caller_session_id from litellm.integrations.otel.model.trace_controls import TraceControls +from litellm.litellm_core_utils.batch_utils import ( + BATCH_COST_REQUEST_ID_SUFFIX, + charged_poll_cost, + charged_video_id, + pays_only_its_guardrail, +) from litellm.litellm_core_utils.classifier_logging import ( CLASSIFIER_AUDIT_FIELDS, classifier_audit_fields, @@ -53,10 +57,13 @@ from litellm.litellm_core_utils.core_helpers import ( ) from litellm.litellm_core_utils.get_llm_provider_logic import declared_authenticating_provider from litellm.litellm_core_utils.hidden_params import served_from_cache -from litellm.litellm_core_utils.internal_call_metadata import is_unbilled_non_inference_call +from litellm.litellm_core_utils.internal_call_metadata import ( + BACKGROUND_RESPONSE_COST_REQUEST_ID_SUFFIX, + is_unbilled_non_inference_call, + settles_background_response, +) from litellm.litellm_core_utils.litellm_logging import ( StandardLoggingPayloadSetup, - UsageObservation, coerce_model_access_groups, is_valid_sha256_hash, request_model_access_groups_from_litellm_params, @@ -73,19 +80,14 @@ from litellm.proxy._types import ( ) from litellm.proxy.route_llm_request import ProxyModelNotFoundError from litellm.proxy.spend_tracking.spend_log_error_logger import spend_log_error -from litellm.proxy.utils import PrismaClient, hash_token +from litellm.proxy.utils import PrismaClient, hash_token, query_raw_within_statement_timeout from litellm.responses.litellm_completion_transformation.compaction_items import ( compaction_summary, summary_only_compaction_content, with_compaction_summary, ) -from litellm.types.passthrough_endpoints.pass_through_endpoints import ( - SETTLES_BACKGROUND_RESPONSE_KWARG, - BackgroundResponseSettlement, -) from litellm.types.router import DeploymentTypedDict, LiteLLM_Params, SilentExperimentFlag from litellm.types.utils import ( - BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN, PROMPT_CARRYING_GUARDRAIL_FIELDS, AzureSpillover, CallTypes, @@ -102,6 +104,7 @@ from litellm.types.utils import ( VectorStoreSearchResponse, batch_chat_usage, ) +from litellm.types.videos.utils import VIDEO_COST_REQUEST_ID_SUFFIX from litellm.utils import get_end_user_id_for_cost_tracking if TYPE_CHECKING: @@ -158,9 +161,7 @@ def _is_non_secret_key_value(value: str, *, key_alias: object = None) -> bool: ) -def _redact_logged_api_key( - value: str | None, *, already_redacted: bool = False, key_alias: object = None -) -> str | None: +def redact_logged_api_key(value: str | None, *, already_redacted: bool = False, key_alias: object = None) -> str | None: if not isinstance(value, str) or not value: return None stripped: Final = re.sub(r"(?i)^bearer ", "", value) @@ -324,7 +325,7 @@ def _get_spend_logs_metadata( and _is_non_secret_key_value(_trusted_hash, key_alias=_key_alias) and _trusted_hash == _raw_key ) - clean_metadata["user_api_key"] = _redact_logged_api_key( + clean_metadata["user_api_key"] = redact_logged_api_key( _raw_key, already_redacted=_already_redacted, key_alias=_key_alias ) clean_metadata["applied_guardrails"] = applied_guardrails @@ -346,25 +347,22 @@ def _get_spend_logs_metadata( return clean_metadata -BATCH_COST_REQUEST_ID_SUFFIX: Final = "_batch_cost" -BACKGROUND_RESPONSE_COST_REQUEST_ID_SUFFIX: Final = "_background_cost" +JOB_POLL_GUARDRAIL_COST_REQUEST_ID_SUFFIX: Final = "_guardrail_cost" -def _cost_row_request_id_suffix( - call_type: str, metadata: Mapping[str, object], settles_background_response: bool -) -> str: +def _cost_row_request_id_suffix(call_type: str, metadata: Mapping[str, object], kwargs: Mapping[str, object]) -> str: if call_type == CallTypes.aretrieve_batch.value: return BATCH_COST_REQUEST_ID_SUFFIX - if settles_background_response or ( - call_type in NON_INFERENCE_CALL_TYPES - and metadata.get(INTERNAL_CALL_ORIGIN_METADATA_KEY) == BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN - ): + if settles_background_response(call_type, metadata, kwargs): return BACKGROUND_RESPONSE_COST_REQUEST_ID_SUFFIX return "" def get_spend_logs_id( - call_type: str, response_obj: dict, kwargs: Mapping[str, object], metadata: Mapping[str, object] = EMPTY_MAPPING + call_type: str, + response_obj: Mapping[str, object], + kwargs: Mapping[str, object], + metadata: Mapping[str, object] = EMPTY_MAPPING, ) -> str | None: standard_logging_payload = kwargs.get("standard_logging_object") candidate_ids: Final = ( @@ -377,10 +375,14 @@ def get_spend_logs_id( ) if resolved_id is None: return None - settles_background_response: Final = ( - kwargs.get(SETTLES_BACKGROUND_RESPONSE_KWARG) is BackgroundResponseSettlement.SETTLES - ) - return f"{resolved_id}{_cost_row_request_id_suffix(call_type, metadata, settles_background_response)}" + response_cost: Final = charged_poll_cost(kwargs) + charged_video: Final = charged_video_id(call_type, kwargs, resolved_id, response_cost) + if charged_video is not None: + return f"{charged_video}{VIDEO_COST_REQUEST_ID_SUFFIX}" + call_id: Final = kwargs.get("litellm_call_id") + if pays_only_its_guardrail(call_type, kwargs, response_cost) and isinstance(call_id, str) and call_id: + return f"{call_id}{JOB_POLL_GUARDRAIL_COST_REQUEST_ID_SUFFIX}" + return f"{resolved_id}{_cost_row_request_id_suffix(call_type, metadata, kwargs)}" _MISSING_ATTRIBUTE: Final = object() @@ -601,12 +603,12 @@ def get_logging_payload( start_time: datetime, end_time: datetime, llm_router: "Router | None" = None, - capture_usage: Callable[[SpendLogsPayload, str | None], None] | None = None, ) -> SpendLogsPayload: if kwargs is None: kwargs = {} rejected_as_unknown_model: Final = isinstance(response_obj, ProxyModelNotFoundError) + failure_exception: Final = response_obj if isinstance(response_obj, BaseException) else None response_served_from_cache: Final = served_from_cache(response_obj) if response_obj is None: response_obj = {} @@ -657,10 +659,12 @@ def get_logging_payload( usage = _usage # A request that failed mid-stream has no usable response_obj usage, and a stream - # continued on a fallback only has the fallback's. combined_usage_object holds the - # usage of every call the client's answer took, so it wins in both cases. + # continued on a fallback or a success that bills a failed follow-up only has its own. + # combined_usage_object holds the usage of every call the row bills, so it wins in each case. _combined_usage: Final = kwargs.get("combined_usage_object") - if (not usage or "continued_partial_usage" in kwargs) and isinstance(_combined_usage, litellm.Usage): + if ( + not usage or "continued_partial_usage" in kwargs or "failed_attempts_billed_on_success" in kwargs + ) and isinstance(_combined_usage, litellm.Usage): usage = _combined_usage.model_dump() id = get_spend_logs_id(call_type or "acompletion", response_obj_dict, kwargs, metadata) @@ -686,14 +690,14 @@ def get_logging_payload( and _is_non_secret_key_value(_trusted_hash, key_alias=_key_alias) and _trusted_hash == api_key ) - api_key = _redact_logged_api_key(api_key, already_redacted=_key_already_redacted, key_alias=_key_alias) or "" + api_key = redact_logged_api_key(api_key, already_redacted=_key_already_redacted, key_alias=_key_alias) or "" if ( standard_logging_payload is not None ): # [TODO] migrate completely to sl payload. currently missing pass-through endpoint data api_key = ( api_key - or _redact_logged_api_key( + or redact_logged_api_key( standard_logging_payload["metadata"].get("user_api_key_hash"), already_redacted=True, key_alias=standard_logging_payload["metadata"].get("user_api_key_alias"), @@ -897,14 +901,11 @@ def get_logging_payload( additional_usage_values["cache_creation_input_tokens"] = cache_write_tokens clean_metadata["additional_usage_values"] = additional_usage_values drop_requester_ip_address: Final = requester_ip_address_logging_disabled() - error_information: Final = clean_metadata["error_information"] if drop_requester_ip_address: clean_metadata["requester_ip_address"] = None - if drop_requester_ip_address and isinstance(error_information, Mapping): - clean_metadata["error_information"] = cast( # cast-ok: same keys, only the str values are masked - StandardLoggingPayloadErrorInformation, - _error_information_without_ip_addresses(_OBJECT_MAPPING.validate_python(error_information)), - ) + clean_metadata["error_information"] = sanitize_error_information_for_spend_logs( + clean_metadata["error_information"], original_exception=failure_exception + ) if litellm.cache is None: cache_key = "Cache OFF" @@ -991,14 +992,6 @@ def get_logging_payload( payload.get("spend"), ) - if capture_usage is not None: - observed_usage: Final = ( - StandardLoggingPayloadSetup.get_usage_as_dict({"usage": usage}) - if usage and kwargs.get("_accounting_usage_observed") is not UsageObservation.UNKNOWN - else None - ) - capture_usage(payload, safe_dumps(observed_usage) if observed_usage is not None else None) - # Explicitly clear large intermediate objects to reduce memory pressure del response_obj_dict, usage, clean_metadata, additional_usage_values @@ -1103,7 +1096,7 @@ async def _query_raw_rows( sql_query: str, *args: object, ) -> Sequence[Mapping[str, object]] | None: - return await prisma_client.db.query_raw(sql_query, *args) + return await query_raw_within_statement_timeout(prisma_client, sql_query, *args) async def get_spend_by_team( diff --git a/litellm/proxy/spend_tracking/usage_capture.py b/litellm/proxy/spend_tracking/usage_capture.py deleted file mode 100644 index 19480a66678..00000000000 --- a/litellm/proxy/spend_tracking/usage_capture.py +++ /dev/null @@ -1,1084 +0,0 @@ -from __future__ import annotations - -import asyncio -import json -import re -from collections.abc import Awaitable, Callable, Iterator, Mapping -from dataclasses import dataclass, replace -from datetime import datetime, timezone -from decimal import Decimal -from hashlib import sha256 -from itertools import chain, groupby, islice, repeat -from typing import TYPE_CHECKING, Final - -from pydantic import BaseModel, JsonValue, TypeAdapter - -from litellm._logging import verbose_proxy_logger -from litellm.accounting import ( - Dimension, - DimensionName, - InboundUsageEvent, - Metric, - MetricName, - OutboundUsageEvent, - Outcome, -) -from litellm.constants import BILLED_RETRY_ATTEMPT_METADATA_KEY, INTERNAL_CALL_ORIGIN_METADATA_KEY -from litellm.proxy.spend_tracking.usage_meter import ( - DurableUsageMeter, - UsageCaptureError, - UsageCaptureSettings, - usage_delivery_targets, -) -from litellm.types.utils import CallTypes, CustomPricingLiteLLMParams - -if TYPE_CHECKING: - from litellm.litellm_core_utils.litellm_logging import Logging - from litellm.proxy._types import SpendLogsPayload - - -from litellm.proxy.db.accounting_ledger import AccountingConflictError, UsageWrite - - -class UsageAcknowledgementError(UsageCaptureError): - def __init__(self, cause: Exception) -> None: - super().__init__("Usage persistence did not acknowledge commit") - self.__cause__ = cause - - -@dataclass(frozen=True, slots=True) -class CapturedUsage: - payload: SpendLogsPayload - writes: tuple[UsageWrite, ...] - receipt: asyncio.Future[None] - - -_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) - - -_FIELDS: Final = TypeAdapter(dict[str, object]) - - -_INSTANT: Final = TypeAdapter(datetime) - - -_DIMENSIONS: Final = ( - ("api_key", DimensionName.KEY), - ("user", DimensionName.USER), - ("team_id", DimensionName.TEAM), - ("organization_id", DimensionName.ORGANIZATION), - ("end_user", DimensionName.END_USER), - ("model", DimensionName.MODEL), - ("model_group", DimensionName.MODEL_GROUP), - ("model_id", DimensionName.DEPLOYMENT), - ("custom_llm_provider", DimensionName.PROVIDER), - ("mcp_namespaced_tool_name", DimensionName.TOOL), - ("agent_id", DimensionName.AGENT), -) - - -_USAGE_METRICS: Final = tuple( - metric - for metric in MetricName - if metric not in (MetricName.SPEND, MetricName.REQUESTS, MetricName.SUCCESSFUL_REQUESTS, MetricName.FAILED_REQUESTS) -) - - -def _fields(value: object) -> Mapping[str, object]: - return _FIELDS.validate_python(value) if isinstance(value, Mapping) else {} - - -def _text(value: object) -> str | None: - return value if isinstance(value, str) and value else None - - -def _utc_time(value: datetime | str) -> datetime: - parsed: Final = _INSTANT.validate_python(value) - return parsed.replace(tzinfo=timezone.utc) if parsed.tzinfo is None else parsed.astimezone(timezone.utc) - - -def _json(value: object) -> str: - return json.dumps(value, sort_keys=True, separators=(",", ":"), allow_nan=False) - - -def _usage_metrics(usage: Mapping[str, JsonValue] | None) -> tuple[Metric, ...] | None: - if usage is None: - return None - return tuple( - Metric(name=metric, value=Decimal(str(value))) - for metric in _USAGE_METRICS - if isinstance(value := usage.get(metric.value), (int, float)) and not isinstance(value, bool) - ) - - -@dataclass(frozen=True, slots=True) -class UsageCaptureContext: - caller_id: str | None - attempt_id: str - parent_request_id: str | None - retry_of_attempt_id: str | None - job_id: str | None - charge_eligible: bool - request_count_eligible: bool - ownership: str - pricing: str - finalized_cost: str | None = None - allocation: str | None = None - outcome: Outcome | None = None - started_at: datetime | None = None - ended_at: datetime | None = None - phase: str = "execution" - extra_dimensions: tuple[Dimension, ...] = () - provider_timestamps: str = "{}" - usage_source: str = "measured" - included_attempt_ids: tuple[str, ...] = () - related_attempt_ids: tuple[str, ...] = () - - -def _database_usage_write(event: InboundUsageEvent | OutboundUsageEvent, envelope: Mapping[str, object]) -> UsageWrite: - from sys import maxsize - - from litellm.litellm_core_utils.safe_json_dumps import safe_json_structure - - normalized: Final = _FIELDS.validate_python(safe_json_structure(envelope, max_depth=maxsize)) - if normalized.get("event") != event.model_dump(mode="json"): - raise UsageCaptureError("Usage event text cannot be normalized without changing identity or attribution") - serialized: Final = _json(normalized) - _JSON_OBJECT.validate_json(serialized) - return UsageWrite(event, serialized, usage_delivery_targets(event.dimensions)) - - -def usage_writes( - payload: SpendLogsPayload, usage_json: str | None, context: UsageCaptureContext -) -> tuple[UsageWrite, ...]: - fields: Final = _FIELDS.validate_python(payload) - tags: Final = TypeAdapter(tuple[str, ...]).validate_json(payload["request_tags"]) - dimensions: Final = ( - *(Dimension(name=name, value=value) for field, name in _DIMENSIONS if (value := _text(fields.get(field)))), - *(Dimension(name=DimensionName.TAG, value=tag) for tag in dict.fromkeys(tags)), - *context.extra_dimensions, - ) - outcome: Final = context.outcome or (Outcome.FAILED if payload["status"] == "failure" else Outcome.SUCCEEDED) - started: Final = context.started_at or _utc_time(payload["startTime"]) - ended: Final = context.ended_at or _utc_time(payload["endTime"]) - usage: Final = None if usage_json is None else _JSON_OBJECT.validate_json(usage_json) - outbound: Final = OutboundUsageEvent( - event_id=context.attempt_id, - attempt_id=context.attempt_id, - request_id=context.caller_id, - retry_of_attempt_id=context.retry_of_attempt_id, - call_type=CallTypes(payload["call_type"]), - started_at=started, - ended_at=ended, - outcome=outcome, - dimensions=dimensions, - metrics=_usage_metrics(None if context.usage_source == "unknown" else usage), - ) - envelope: Final = { - "event": outbound.model_dump(mode="json"), - "usage": usage, - "usage_source": "unknown" if usage is None else context.usage_source, - "included_attempt_ids": context.included_attempt_ids, - "related_attempt_ids": context.related_attempt_ids, - "pricing": _JSON_OBJECT.validate_json(context.pricing), - "charge_eligible": context.charge_eligible, - "request_count_eligible": context.request_count_eligible, - "ownership": context.ownership, - "parent_request_id": context.parent_request_id, - "job_id": context.job_id, - "phase": context.phase, - "provider_timestamps": _JSON_OBJECT.validate_json(context.provider_timestamps), - "finalized_cost": None - if context.finalized_cost is None - else _JSON_OBJECT.validate_json(context.finalized_cost), - "allocation": None if context.allocation is None else _JSON_OBJECT.validate_json(context.allocation), - } - outbound_write: Final = _database_usage_write(outbound, envelope) - if not context.request_count_eligible or context.caller_id is None: - return (outbound_write,) - inbound: Final = InboundUsageEvent( - event_id=f"{context.caller_id}:inbound", - request_id=context.caller_id, - call_type=outbound.call_type, - started_at=started, - ended_at=ended, - outcome=outcome, - dimensions=dimensions, - metrics=( - Metric(name=MetricName.REQUESTS, value=Decimal(1)), - Metric(name=MetricName.SUCCESSFUL_REQUESTS, value=Decimal(int(outcome is Outcome.SUCCEEDED))), - Metric(name=MetricName.FAILED_REQUESTS, value=Decimal(int(outcome is not Outcome.SUCCEEDED))), - ), - ) - return ( - _database_usage_write(inbound, {"event": inbound.model_dump(mode="json")}), - outbound_write, - ) - - -_INCLUDED_IN_PARENT: Final = object() - - -_PRICING_FIELDS: Final = frozenset( - { - "service_tier", - "data_residency", - "vertex_location", - "region_name", - "base_model", - "custom_pricing", - "input_cost_per_token", - "output_cost_per_token", - "input_cost_per_second", - "output_cost_per_second", - "input_cost_per_character", - "output_cost_per_character", - "size", - "quality", - "n", - "duration", - "seconds", - "search_context_size", - "additional_response_cost", - } -) - - -def _selected_pricing(fields: Mapping[str, object]) -> Mapping[str, JsonValue]: - return _JSON_OBJECT.validate_python( - { - key: value - for key, value in fields.items() - if key in _PRICING_FIELDS or key in CustomPricingLiteLLMParams.model_fields - } - ) - - -def _response_fields(response: object) -> Mapping[str, object]: - if isinstance(response, BaseModel): - return _FIELDS.validate_python(response.model_dump()) - return _fields(response) - - -def _job_time(response: Mapping[str, object], key: str) -> datetime | None: - stamp: Final = response.get(key) - if isinstance(stamp, (int, float)) and not isinstance(stamp, bool): - return datetime.fromtimestamp(stamp, tz=timezone.utc) - return None - - -def capture_context(payload: SpendLogsPayload, kwargs: Mapping[str, object], response: object) -> UsageCaptureContext: - from dataclasses import asdict - - from litellm.litellm_core_utils.hidden_params import get_hidden_params - from litellm.litellm_core_utils.internal_call_metadata import is_background_response, is_unbilled_non_inference_call - from litellm.litellm_core_utils.litellm_logging import ( - Logging, - UsageCaptureObservation, - UsageObservation, - mask_api_base_credentials, - ) - from litellm.litellm_core_utils.llm_cost_calc.finalization import FinalizedCost - from litellm.proxy.hooks.search_free_tier import SearchAllowanceAllocation - from litellm.proxy.spend_tracking.spend_tracking_utils import get_request_model_access_groups - - metadata: Final = _JSON_OBJECT.validate_json(payload["metadata"]) - params: Final = _fields(kwargs.get("litellm_params")) - request_metadata: Final = _fields(params.get("litellm_metadata") or params.get("metadata")) - standard: Final = _fields(kwargs.get("standard_logging_object")) - logging_obj: Final = kwargs.get("litellm_logging_obj") - raw_response: Final = _response_fields(response) - hidden: Final = _fields(get_hidden_params(response)) - tool: Final = _fields(kwargs.get("mcp_tool_call_metadata")) - tool_pricing: Final = _fields(tool.get("mcp_server_cost_info")) - caller: Final = payload["litellm_call_id"] - cached: Final = payload["cache_hit"].lower() == "true" - included_in_parent: Final = kwargs.get("_accounting_internal_aggregate") is _INCLUDED_IN_PARENT - billed_id: Final = payload["request_id"] - terminal: Final = raw_response.get("status") in { - "completed", - "complete", - "failed", - "cancelled", - "expired", - "incomplete", - } - deferred: Final = billed_id.endswith(("_batch_cost", "_background_cost")) and terminal - management: Final = ( - (billed_id.endswith(("_batch_cost", "_background_cost")) and not terminal) - or (is_background_response(response) and not terminal) - or is_unbilled_non_inference_call(payload["call_type"], request_metadata, response) - ) - attempt: Final = ( - f"{caller}_cache_hit" - if cached and caller - else f"{caller}:status" - if management - else f"{billed_id}:included" - if included_in_parent - else billed_id - ) - if not attempt or attempt == "None" or (cached and not caller): - raise UsageCaptureError("Usage capture requires a stable execution identity") - retry: Final = metadata.get(BILLED_RETRY_ATTEMPT_METADATA_KEY) is True - origin: Final = metadata.get(INTERNAL_CALL_ORIGIN_METADATA_KEY) - parent: Final = _text(kwargs.get("parent_request_id")) or _text(request_metadata.get("parent_request_id")) - finalized_value: Final = ( - logging_obj.finalized_cost if isinstance(logging_obj, Logging) else kwargs.get("_accounting_finalized_cost") - ) - finalized: Final = finalized_value if isinstance(finalized_value, FinalizedCost) else None - allocation_value: Final = ( - logging_obj.cost_allowance_allocation - if isinstance(logging_obj, Logging) - else kwargs.get("_accounting_allocation") - ) - allocation: Final = allocation_value if isinstance(allocation_value, SearchAllowanceAllocation) else None - pricing_snapshot: Final = kwargs.get("_accounting_pricing_snapshot") - observation: Final = kwargs.get("_accounting_usage_snapshot") - captured_pricing: Final = { - "model_map_information": ( - _JSON_OBJECT.validate_json(pricing_snapshot.model_map_information) - if isinstance(pricing_snapshot, PricingCapture) - else metadata.get("model_map_information") - ), - "cost_breakdown": metadata.get("cost_breakdown"), - **( - _JSON_OBJECT.validate_json(pricing_snapshot.inputs) - if isinstance(pricing_snapshot, PricingCapture) - else _pricing_inputs(kwargs, logging_obj, response) - ), - "tool": { - "name": tool.get("name"), - "cost_per_query": _fields(tool_pricing.get("tool_name_to_cost_per_query")).get( - _text(tool.get("name")) or "", tool_pricing.get("default_cost_per_query") - ), - } - if tool - else None, - "response_inputs": { - "audio_transcription_duration": hidden.get("audio_transcription_duration", raw_response.get("duration")), - "billed_units": _fields(raw_response.get("meta")).get("billed_units"), - "batch_models": hidden.get("batch_models"), - "batch_successful_requests": hidden.get("batch_successful_requests"), - "batch_failed_requests": hidden.get("batch_failed_requests"), - "service_tier": raw_response.get("service_tier"), - "region_name": hidden.get("region_name"), - }, - "reported_cost": observation.response_cost - if isinstance(observation, UsageCaptureObservation) - else standard.get( - "response_cost", kwargs.get("response_cost", _fields(get_hidden_params(response)).get("response_cost")) - ), - "adjustments": ( - _JSON_OBJECT.validate_json(pricing_snapshot.adjustments) - if isinstance(pricing_snapshot, PricingCapture) - else None - ), - } - return UsageCaptureContext( - caller_id=None if deferred else parent if retry or included_in_parent else caller, - attempt_id=attempt, - parent_request_id=parent, - retry_of_attempt_id=_text(request_metadata.get("retry_of_attempt_id")), - job_id=_text(raw_response.get("id")) if deferred or management else None, - charge_eligible=not cached and not included_in_parent and not management, - request_count_eligible=bool(caller) and not origin and not retry and not deferred and not included_in_parent, - ownership="included_in_parent" - if included_in_parent - else "aggregate" - if kwargs.get("additional_response_cost") is not None - else "attempt", - pricing=_json(captured_pricing), - finalized_cost=_json( - { - "response_cost": finalized.amount, - "cost_breakdown": finalized.logging_breakdown(), - "allowance_discount": finalized.allowance_discount, - } - ) - if finalized is not None - else ( - _json({"response_cost": standard.get("response_cost"), "cost_breakdown": standard.get("cost_breakdown")}) - if standard.get("cost_finalized") is True - else None - ), - allocation=_json(asdict(allocation)) if allocation is not None else None, - started_at=_job_time(raw_response, "created_at") if deferred else None, - ended_at=( - _job_time(raw_response, "completed_at") - or _job_time(raw_response, "failed_at") - or _job_time(raw_response, "cancelled_at") - or _job_time(raw_response, "expired_at") - ) - if deferred - else None, - outcome=( - Outcome.CANCELLED - if raw_response.get("status") == "cancelled" - or isinstance(response, asyncio.CancelledError) - or getattr(response, "status_code", None) == 499 - else Outcome.FAILED - if raw_response.get("status") in {"failed", "expired", "incomplete"} or isinstance(response, BaseException) - else None - ), - phase="terminal" if deferred else "management" if management else "execution", - usage_source="estimated" - if kwargs.get("_accounting_usage_observed") is UsageObservation.ESTIMATED - else "measured", - included_attempt_ids=TypeAdapter(tuple[str, ...]).validate_python( - kwargs.get("_accounting_included_attempt_ids", ()) - ), - related_attempt_ids=tuple(write.event.event_id for write in _prior_writes(kwargs)), - provider_timestamps=_json( - { - key: raw_response.get(key) - for key in ("created_at", "completed_at", "failed_at", "cancelled_at", "expired_at") - if raw_response.get(key) is not None - } - ) - if deferred - else "{}", - extra_dimensions=( - *( - (Dimension(name=DimensionName.TOOL, value=tool_name),) - if not payload.get("mcp_namespaced_tool_name") - and (tool_name := _text(tool.get("namespaced_tool_name"))) - else () - ), - *( - (Dimension(name=DimensionName.API_BASE, value=mask_api_base_credentials(api_base)),) - if (api_base := _text(payload["api_base"])) - else () - ), - *( - Dimension(name=DimensionName.MODEL_ACCESS_GROUP, value=group) - for group in get_request_model_access_groups(kwargs) - ), - *( - (Dimension(name=DimensionName.PROJECT, value=project),) - if (project := _text(request_metadata.get("user_api_key_project_id"))) - else () - ), - *( - (Dimension(name=DimensionName.SERVICE_TIER, value=tier),) - if (tier := _text(raw_response.get("service_tier") or kwargs.get("service_tier"))) - else () - ), - ), - ) - - -class _CaptureBuilder: - def __init__(self, kwargs: Mapping[str, object], response: object) -> None: - self.kwargs: Final = kwargs - self.response: Final = response - self.writes: tuple[UsageWrite, ...] = () - - def observe(self, payload: SpendLogsPayload, usage: str | None) -> None: - from litellm.litellm_core_utils.litellm_logging import UsageCaptureObservation, UsageObservation - - snapshot: Final = self.kwargs.get("_accounting_usage_snapshot") - if isinstance(snapshot, UsageCaptureError): - raise snapshot - effective: Final = snapshot.usage_json if isinstance(snapshot, UsageCaptureObservation) else usage - parsed: Final = _JSON_OBJECT.validate_json(effective) if effective is not None else {} - batch: Final = _fields(parsed.get("batch_usage_by_model")) - unknown: Final = (bool(batch) or bool(parsed.get("batch_unknown_usage_requests"))) and all( - value is None for value in batch.values() - ) - observed: Final = ( - _json( - { - "batch_usage_by_model": batch, - "batch_unknown_usage_requests": parsed.get("batch_unknown_usage_requests"), - **( - {"batch_usage_by_request": parsed["batch_usage_by_request"]} - if "batch_usage_by_request" in parsed - else {} - ), - } - ) - if unknown - else effective - ) - context: Final = capture_context(payload, self.kwargs, self.response) - provenance: Final = ( - "unknown" - if unknown - else "estimated" - if isinstance(snapshot, UsageCaptureObservation) and snapshot.provenance is UsageObservation.ESTIMATED - else context.usage_source - ) - self.writes = usage_writes(payload, observed, replace(context, usage_source=provenance)) - - -def _prior_captures(kwargs: Mapping[str, object]) -> tuple[CapturedUsage, ...]: - prior: Final = kwargs.get("_accounting_prior_captures", ()) - return ( - tuple( - item for item in TypeAdapter(tuple[object, ...]).validate_python(prior) if isinstance(item, CapturedUsage) - ) - if isinstance(prior, tuple) - else () - ) - - -def _prior_writes(kwargs: Mapping[str, object]) -> tuple[UsageWrite, ...]: - return tuple(chain.from_iterable(item.writes for item in _prior_captures(kwargs))) - - -def capture_callback( - meter: DurableUsageMeter, - kwargs: Mapping[str, object], - response: object, - start_time: datetime, - end_time: datetime, -) -> CapturedUsage: - from litellm.proxy.db.db_spend_update_writer import get_llm_router - from litellm.proxy.spend_tracking.spend_tracking_utils import get_logging_payload - - existing: Final = kwargs.get("_accounting_capture") - if isinstance(existing, CapturedUsage): - return existing - builder: Final = _CaptureBuilder(kwargs, response) - payload: Final = get_logging_payload( - dict(kwargs), response, start_time, end_time, llm_router=get_llm_router(), capture_usage=builder.observe - ) - prerequisites: Final = tuple(item.receipt for item in _prior_captures(kwargs)) - return CapturedUsage(payload, builder.writes, meter.submit(builder.writes, prerequisites=prerequisites)) - - -def _batch_rows(response: object) -> tuple[Mapping[str, JsonValue], ...]: - usage: Final = _response_fields(_response_fields(response).get("usage")) - rows: Final = usage.get("batch_usage_by_request") - return TypeAdapter(tuple[dict[str, JsonValue], ...]).validate_python(rows) if rows else () - - -def _batch_root(write: UsageWrite, rows: tuple[Mapping[str, JsonValue], ...]) -> UsageWrite: - event: Final = write.event.model_copy(update={"metrics": None}) - envelope: Final = _JSON_OBJECT.validate_json(write.envelope) - return _database_usage_write( - event, - { - **envelope, - "event": event.model_dump(mode="json"), - "usage": { - "batch_row_count": len(rows), - "batch_rows_sha256": sha256(_json(rows).encode()).hexdigest(), - "batch_charge_eligible": envelope["charge_eligible"], - }, - "usage_source": "unknown", - "charge_eligible": False, - "ownership": "aggregate", - }, - ) - - -def _batch_row_write(root: UsageWrite, row: Mapping[str, JsonValue], index: int) -> UsageWrite: - envelope: Final = _JSON_OBJECT.validate_json(root.envelope) - pricing: Final = _JSON_OBJECT.validate_python(envelope["pricing"]) - model: Final = _text(row["model"]) - usage: Final = _JSON_OBJECT.validate_python(row["usage"]) if row["usage"] is not None else None - identity: Final = f"{root.event.event_id}:row:{index}" - event: Final = OutboundUsageEvent.model_validate( - { - **root.event.model_dump(), - "event_id": identity, - "attempt_id": identity, - "metrics": _usage_metrics(usage), - "dimensions": ( - *(dimension for dimension in root.event.dimensions if dimension.name is not DimensionName.MODEL), - *((Dimension(name=DimensionName.MODEL, value=model),) if model else ()), - ), - } - ) - return _database_usage_write( - event, - { - **envelope, - "event": event.model_dump(mode="json"), - "usage": usage, - "usage_source": "unknown" if usage is None else "measured", - "charge_eligible": _fields(envelope["usage"])["batch_charge_eligible"], - "ownership": "attempt", - "parent_request_id": root.event.event_id, - "finalized_cost": None, - "allocation": None, - "pricing": { - **pricing, - "model_map_information": _fields(pricing.get("batch_models")).get(model or ""), - "batch_models": {}, - "reported_cost": None, - "cost_breakdown": None, - "response_inputs": { - key: value - for key, value in _fields(pricing.get("response_inputs")).items() - if key not in {"batch_models", "batch_successful_requests"} - }, - }, - }, - ) - - -@dataclass(frozen=True, slots=True) -class _BatchCapture: - payload: SpendLogsPayload - root: UsageWrite - rows: bytes - prerequisites: tuple[asyncio.Future[None], ...] - - -def _prepare_batch_capture( - kwargs: Mapping[str, object], response: object, start_time: datetime, end_time: datetime -) -> _BatchCapture: - from litellm.proxy.db.db_spend_update_writer import get_llm_router - from litellm.proxy.spend_tracking.spend_tracking_utils import get_logging_payload - - rows: Final = tuple(sorted(_batch_rows(response), key=_json)) - builder: Final = _CaptureBuilder(kwargs, response) - payload: Final = get_logging_payload( - dict(kwargs), response, start_time, end_time, llm_router=get_llm_router(), capture_usage=builder.observe - ) - if len(builder.writes) != 1 or _terminal_facts(builder.writes[0]) is None: - raise UsageCaptureError("Batch rows require one terminal job observation") - return _BatchCapture( - payload, - _batch_root(builder.writes[0], rows), - b"\n".join(_json((row, sum(1 for _ in group))).encode("utf-8") for row, group in groupby(map(_json, rows))), - tuple(prior.receipt for prior in _prior_captures(kwargs)), - ) - - -def _batch_groups(rows: bytes) -> Iterator[tuple[str, int]]: - return (TypeAdapter(tuple[str, int]).validate_json(match.group()) for match in re.finditer(rb"[^\n]+", rows)) - - -def _batch_writes(root: UsageWrite, rows: bytes) -> Iterator[UsageWrite]: - expanded: Final = chain.from_iterable(repeat(row, count) for row, count in _batch_groups(rows)) - return (_batch_row_write(root, _JSON_OBJECT.validate_json(row), index) for index, row in enumerate(expanded)) - - -def _batch_write_bound(root: UsageWrite, rows: bytes) -> int: - last_index: Final = sum(count for _, count in _batch_groups(rows)) - 1 - return max( - len(root.envelope.encode("utf-8")), - max( - len(_batch_row_write(root, _JSON_OBJECT.validate_json(row), last_index).envelope.encode("utf-8")) - for row, _ in _batch_groups(rows) - ), - ) - - -def _batch_capacity( - meter: DurableUsageMeter, root: UsageWrite, rows: bytes, *, extra_bytes: int = 0 -) -> tuple[int, int, int]: - retained: Final = len(rows) + len(root.envelope.encode("utf-8")) + extra_bytes - bound: Final = _batch_write_bound(root, rows) - chunk_bytes: Final = max( - bound, - min( - bound * min(meter.settings.batch_size, sum(count for _, count in _batch_groups(rows))), - meter.settings.max_pending_bytes // 4, - (meter.settings.max_pending_bytes - retained) // 2, - ), - ) - return retained + chunk_bytes, chunk_bytes, bound - - -async def _persist_batch_capture( - meter: DurableUsageMeter, - load: Callable[[tuple[str, ...]], Awaitable[tuple[UsageWrite, ...]]], - root: UsageWrite, - rows: bytes, - prerequisites: tuple[asyncio.Future[None], ...], - chunk_bytes: int, - reservation: object | None = None, -) -> None: - for receipt in prerequisites: - await asyncio.shield(receipt) - await meter.record_writes((root,)) - accepted: Final = await load((root.event.event_id,)) - if len(accepted) != 1: - raise UsageCaptureError("Committed batch snapshot could not be loaded") - frozen: Final = _reuse_terminal_snapshot(root, accepted[0]) - retained, capacity, bound = _batch_capacity(meter, frozen, rows, extra_bytes=len(root.envelope.encode("utf-8"))) - if reservation is not None: - meter.resize_producer(reservation, retained, capacity) - write_capacity: Final = capacity if reservation is not None else chunk_bytes - if bound > write_capacity: - raise UsageCaptureError("Batch observation exceeds reserved producer write capacity") - group_size: Final = min(meter.settings.batch_size, max(1, write_capacity // bound)) - remaining: Final = _batch_writes(frozen, rows) - while group := tuple(islice(remaining, group_size)): - await meter.record_writes(group) - - -async def capture_batch_callback( - meter: DurableUsageMeter, - load: Callable[[tuple[str, ...]], Awaitable[tuple[UsageWrite, ...]]] | None, - kwargs: Mapping[str, object], - response: object, - start_time: datetime, - end_time: datetime, -) -> CapturedUsage: - if load is None: - raise UsageCaptureError("Batch capture requires the existing ledger snapshot reader") - capture: Final = _prepare_batch_capture(kwargs, response, start_time, end_time) - await _persist_batch_capture( - meter, load, capture.root, capture.rows, capture.prerequisites, meter.settings.max_pending_bytes - ) - receipt: Final[asyncio.Future[None]] = asyncio.get_running_loop().create_future() - receipt.set_result(None) - return CapturedUsage(capture.payload, (capture.root,), receipt) - - -async def captured_callback_kwargs( - kwargs: Mapping[str, object], response: object, start_time: datetime | None, end_time: datetime | None -) -> Mapping[str, object]: - from litellm.proxy.proxy_server import usage_capture - - usage_meter: Final = usage_capture.meter - - if usage_meter is None: - return kwargs - if start_time is None or end_time is None: - verbose_proxy_logger.error("Usage capture requires callback start and end timestamps") - return kwargs - try: - captured: Final = ( - usage_capture.submit_batch(kwargs, response, start_time, end_time) - if _batch_rows(response) - else capture_callback(usage_meter, kwargs, response, start_time, end_time) - ) - except Exception: # noqa: BLE001 # capture failure must not suppress legacy billing - verbose_proxy_logger.exception("Usage capture failed before legacy cost tracking") - return kwargs - return {**kwargs, "_accounting_capture": captured} - - -async def capture_proxy_response(logging_obj: object, response: object, *, background: bool = False) -> None: - from fastapi import HTTPException - - from litellm.litellm_core_utils.litellm_logging import Logging - from litellm.proxy.proxy_server import general_settings, usage_capture - - settings: Final = _FIELDS.validate_python(general_settings) - usage_meter: Final = usage_capture.meter - - if usage_meter is None or not isinstance(logging_obj, Logging): - return - sync_ack: Final = ( - settings.get("accounting_sync_ack") is True - and logging_obj.stream is not True - and not background - and logging_obj.call_type in {"acompletion", "atext_completion", "aembedding", "aresponses"} - ) - try: - capture_logging_usage(usage_meter, logging_obj, response, logging_obj.start_time, datetime.now(timezone.utc)) - captured: Final = logging_obj.model_call_details.get("_accounting_capture") - if sync_ack: - if not isinstance(captured, CapturedUsage): - raise UsageCaptureError("Usage capture was not admitted") - timeout: Final = TypeAdapter(float).validate_python( - settings.get("accounting_sync_ack_timeout_seconds", 20.0) - ) - await asyncio.wait_for(asyncio.shield(captured.receipt), timeout=timeout) - except Exception as error: # noqa: BLE001 # the configured response policy owns every capture failure - verbose_proxy_logger.exception("Usage capture failed before the response boundary") - if sync_ack and settings.get("accounting_sync_ack_failure_policy", "fail_closed") == "fail_closed": - acknowledgement: Final = UsageAcknowledgementError(error) - raise HTTPException(503, str(acknowledgement)) from acknowledgement - - -def capture_logging_usage( - meter: DurableUsageMeter, - logging_obj: object, - response: object, - start_time: datetime, - end_time: datetime, - freeze_only: bool = False, -) -> CapturedUsage | UsageCaptureError | None: - from litellm._internal_context import internal_parent_request_id, is_internal_call - from litellm.batches.batch_utils import batch_cost_is_final - from litellm.litellm_core_utils.litellm_logging import Logging - from litellm.types.utils import LiteLLMBatch - - if not isinstance(logging_obj, Logging): - return - internal: Final = is_internal_call.get() - if isinstance(response, LiteLLMBatch) and batch_cost_is_final(response) and response.usage is None: - return - try: - if not internal and isinstance(logging_obj.model_call_details.get("_accounting_capture"), CapturedUsage): - return capture_callback(meter, logging_obj.model_call_details, response, start_time, end_time) - normalized_result: Final = logging_obj.usage_capture_response(response) - prepared: Final = logging_obj.prepared_cost - normalized: Final = ( - {**_response_fields(normalized_result), "usage": prepared.usage.model_dump()} - if prepared is not None - else normalized_result - ) - if normalized is None: - return - details: Final = _FIELDS.validate_python(logging_obj.model_call_details) - params: Final = _fields(details.get("litellm_params")) - metadata: Final = _fields(params.get("litellm_metadata") or params.get("metadata")) - if metadata.get("batch_ignore_default_logging") is True: - return - existing_pricing: Final = details.get("_accounting_pricing_snapshot") - pricing: Final = ( - existing_pricing - if isinstance(existing_pricing, PricingCapture) and not internal - else _capture_pricing(logging_obj, normalized, details) - ) - if freeze_only or _batch_rows(normalized): - if not internal: - logging_obj.record_usage_pricing(pricing) - return - captured: Final = capture_callback( - meter, - { - **details, - "litellm_logging_obj": logging_obj, - "_accounting_capture": None if internal else details.get("_accounting_capture"), - "_accounting_pricing_snapshot": pricing, - "_accounting_internal_aggregate": _INCLUDED_IN_PARENT if internal else None, - "parent_request_id": internal_parent_request_id.get() if internal else details.get("parent_request_id"), - }, - normalized, - start_time, - end_time, - ) - if not internal: - logging_obj.record_usage_capture(captured) - except Exception as error: # noqa: BLE001 # failed capture must not prevent normal logging and legacy charging - verbose_proxy_logger.exception("Usage capture failed at the execution boundary") - return UsageCaptureError(str(error)) - else: - return captured - - -@dataclass(frozen=True, slots=True) -class PricingCapture: - model_map_information: str - adjustments: str - inputs: str - - -def _capture_pricing(logging_obj: Logging, normalized: object, details: Mapping[str, object]) -> PricingCapture: - import litellm - from litellm.litellm_core_utils.cost_discount import resolve_cost_discount - from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup - - params: Final = _fields(details.get("litellm_params")) - prepared: Final = logging_obj.prepared_cost - provider: Final = _text(details.get("custom_llm_provider")) - builtins: Final = logging_obj.standard_built_in_tools_params - pricing: Final = ( - prepared.payload["model_map_information"] - if prepared is not None - else StandardLoggingPayloadSetup.get_model_cost_information( - base_model=logging_obj.get_deployment_model_for_cost(), - custom_pricing=bool(params.get("custom_pricing")), - custom_llm_provider=_text(details.get("custom_llm_provider")), - init_response_obj=normalized, - api_base=_text(params.get("api_base")), - router_model_id=logging_obj.get_router_model_id(), - ) - ) - adjustments: Final = _json( - { - "discount": resolve_cost_discount( - litellm.cost_discount_config, - provider, - logging_obj.get_deployment_model_for_cost(), - _text(params.get("region_name") or params.get("vertex_location")), - ), - "margin": litellm.cost_margin_config.get(provider or "", litellm.cost_margin_config.get("global")), - "web_search_options": ( - _selected_pricing(_fields(builtins.get("web_search_options"))) - if builtins.get("web_search_options") is not None - else None - ), - "file_search": builtins.get("file_search") is not None, - } - ) - batch_usage: Final = _fields(_fields(_response_fields(normalized).get("usage")).get("batch_usage_by_model")) - return PricingCapture( - _json(pricing), - adjustments, - _json( - { - **_pricing_inputs(details, logging_obj, normalized), - "batch_models": { - model: StandardLoggingPayloadSetup.get_model_cost_information( - base_model=model, - custom_pricing=bool(params.get("custom_pricing")), - custom_llm_provider=provider, - init_response_obj={"model": model}, - api_base=_text(params.get("api_base")), - router_model_id=logging_obj.get_router_model_id(), - ) - for model in batch_usage - }, - } - ), - ) - - -def _pricing_inputs(kwargs: Mapping[str, object], logging_obj: object, response: object) -> Mapping[str, object]: - from litellm.litellm_core_utils.litellm_logging import Logging - - return { - "request": _selected_pricing(kwargs), - "deployment": _selected_pricing(_fields(kwargs.get("litellm_params"))), - "optional_params": _selected_pricing(_fields(kwargs.get("optional_params"))), - "logging": logging_obj.usage_capture_pricing(response) if isinstance(logging_obj, Logging) else None, - "model_info": _selected_pricing( - _fields( - _fields( - _fields(kwargs.get("litellm_params")).get("litellm_metadata") - or _fields(kwargs.get("litellm_params")).get("metadata") - ).get("model_info") - ) - ), - } - - -def _terminal_facts(write: UsageWrite) -> Mapping[str, JsonValue] | None: - payload: Final = _JSON_OBJECT.validate_json(write.envelope) - if payload.get("phase") != "terminal": - return None - event: Final = _JSON_OBJECT.validate_python(payload["event"]) - return { - **{ - key: value - for key, value in payload.items() - if key not in {"event", "pricing", "finalized_cost", "allocation"} - }, - "event": {key: value for key, value in event.items() if key not in {"started_at", "ended_at"}}, - } - - -def _reuse_terminal_snapshot(candidate: UsageWrite, accepted: UsageWrite) -> UsageWrite: - facts: Final = _terminal_facts(candidate) - if facts is None or facts != _terminal_facts(accepted) or set(candidate.targets) != set(accepted.targets): - raise AccountingConflictError("Repeated terminal job disagrees with its accepted usage or attribution") - return accepted - - -class UsageBatchWriter: - def __init__( - self, - insert: Callable[[tuple[UsageWrite, ...]], Awaitable[None]], - load: Callable[[tuple[str, ...]], Awaitable[tuple[UsageWrite, ...]]], - ) -> None: - self._insert: Final = insert - self._load: Final = load - - async def _restore(self, writes: tuple[UsageWrite, ...]) -> tuple[UsageWrite, ...]: - terminal: Final = tuple(write for write in writes if _terminal_facts(write) is not None) - if not terminal: - return writes - identities: Final = tuple(dict.fromkeys(write.event.event_id for write in terminal)) - stored: Final = await self._load(identities) - # Re-read the first accepted observation and pricing before the ledger's unchanged id/hash check. - snapshots: Final = {write.event.event_id: write for write in (*reversed(terminal), *stored)} - return tuple( - _reuse_terminal_snapshot(write, snapshots[write.event.event_id]) - if write.event.event_id in snapshots - else write - for write in writes - ) - - async def write(self, writes: tuple[UsageWrite, ...]) -> None: - restored: Final = await self._restore(writes) - try: - await self._insert(restored) - except AccountingConflictError: - if not any(_terminal_facts(write) is not None for write in writes): - raise - await self._insert(await self._restore(writes)) - - -class UsageCaptureRuntime: - def __init__(self) -> None: - self._batches: Final[set[asyncio.Task[None]]] = set() # mutable-ok: owned producer lifecycle - self._stopping = False - self.meter: DurableUsageMeter | None = None - self.load: Callable[[tuple[str, ...]], Awaitable[tuple[UsageWrite, ...]]] | None = None - - def start( - self, - write_batch: Callable[[tuple[UsageWrite, ...]], Awaitable[None]], - settings: UsageCaptureSettings, - *, - load: Callable[[tuple[str, ...]], Awaitable[tuple[UsageWrite, ...]]] | None = None, - ) -> None: - from litellm.litellm_core_utils.litellm_logging import Logging - - if self.meter is not None: - if self.meter.settings != settings: - raise ValueError("Changing accounting_capture requires a worker restart") - return - meter: Final = DurableUsageMeter(write_batch, settings) - self.meter = meter - self.load = load - self._stopping = False - Logging.usage_capture_callback = lambda logger, response, start, end, freeze: capture_logging_usage( - meter, logger, response, start, end, freeze - ) - - def submit_batch( - self, kwargs: Mapping[str, object], response: object, start_time: datetime, end_time: datetime - ) -> CapturedUsage: - meter: Final = self.meter - load: Final = self.load - if meter is None or load is None or self._stopping: - raise UsageCaptureError("Batch capture requires an active ledger writer and snapshot reader") - if len(self._batches) >= meter.settings.max_pending_records: - raise UsageCaptureError("Batch capture producer capacity exhausted") - capture: Final = _prepare_batch_capture(kwargs, response, start_time, end_time) - retained, chunk_bytes, _ = _batch_capacity( - meter, capture.root, capture.rows, extra_bytes=len(capture.root.envelope.encode("utf-8")) - ) - reservation: Final = meter.reserve_producer(retained, chunk_bytes) - task: Final = asyncio.create_task( - _persist_batch_capture( - meter, load, capture.root, capture.rows, capture.prerequisites, chunk_bytes, reservation - ), - name="accounting batch capture", - ) - task.add_done_callback(lambda _: meter.release_producer(reservation)) - self._batches.add(task) - task.add_done_callback(self._batch_finished) - return CapturedUsage(capture.payload, (capture.root,), task) - - def _batch_finished(self, task: asyncio.Task[None]) -> None: - self._batches.discard(task) - if task.cancelled(): - verbose_proxy_logger.error("Batch usage capture stopped before complete persistence") - elif (error := task.exception()) is not None: - verbose_proxy_logger.error("Batch usage capture failed", exc_info=error) - - async def stop(self, timeout: float) -> None: - from litellm.litellm_core_utils.litellm_logging import Logging - - if self.meter is None: - return - self._stopping = True - deadline: Final = asyncio.get_running_loop().time() + timeout - try: - if self._batches: - await asyncio.wait(tuple(self._batches), timeout=max(0, timeout)) - finally: - remaining: Final = tuple(self._batches) - for task in remaining: - task.cancel() - await asyncio.gather(*remaining, return_exceptions=True) - try: - await self.meter.stop(max(0, deadline - asyncio.get_running_loop().time())) - finally: - Logging.usage_capture_callback = None - self.meter = None - self.load = None diff --git a/litellm/proxy/spend_tracking/usage_meter.py b/litellm/proxy/spend_tracking/usage_meter.py deleted file mode 100644 index 431e4c2c3c3..00000000000 --- a/litellm/proxy/spend_tracking/usage_meter.py +++ /dev/null @@ -1,330 +0,0 @@ -from __future__ import annotations - -import asyncio -from collections import deque -from collections.abc import Awaitable, Callable, Mapping -from concurrent.futures import Future -from dataclasses import dataclass -from itertools import accumulate, chain, count, takewhile -from threading import Lock -from typing import Final - -from pydantic import BaseModel, ConfigDict, Field - -from litellm._logging import verbose_proxy_logger -from litellm.accounting import ( - DeliveryTarget, - Dimension, - DimensionName, - InboundUsageEvent, - OutboundUsageEvent, -) -from litellm.proxy.db.accounting_ledger import AccountingConflictError, UsageWrite - -_DAILY_TARGETS: Final = ( - (DimensionName.KEY, DeliveryTarget.DAILY_USER_SPEND), - (DimensionName.USER, DeliveryTarget.DAILY_USER_SPEND), - (DimensionName.TEAM, DeliveryTarget.DAILY_TEAM_SPEND), - (DimensionName.ORGANIZATION, DeliveryTarget.DAILY_ORGANIZATION_SPEND), - (DimensionName.END_USER, DeliveryTarget.DAILY_END_USER_SPEND), - (DimensionName.AGENT, DeliveryTarget.DAILY_AGENT_SPEND), - (DimensionName.TAG, DeliveryTarget.DAILY_TAG_SPEND), - (DimensionName.MODEL, DeliveryTarget.DAILY_MODEL_USAGE), - (DimensionName.TOOL, DeliveryTarget.DAILY_TOOL_SPEND), -) - - -def usage_delivery_targets(dimensions: tuple[Dimension, ...]) -> tuple[DeliveryTarget, ...]: - names: Final = frozenset(dimension.name for dimension in dimensions) - return tuple(dict.fromkeys(target for dimension, target in _DAILY_TARGETS if dimension in names)) - - -class UsageCaptureSettings(BaseModel): - model_config = ConfigDict(frozen=True, extra="forbid") - - batch_size: int = Field(default=1000, ge=2, le=1000) - flush_interval_seconds: float = Field(default=5.0, gt=0, le=10) - max_pending_bytes: int = Field(default=16 * 1024 * 1024, ge=1024) - max_pending_records: int = Field(default=10000, ge=2) - - -class UsageCaptureError(RuntimeError): - pass - - -@dataclass(frozen=True, slots=True) -class _Pending: - writes: tuple[UsageWrite, ...] - size: int - committed: Future[None] - finished: asyncio.Event - prerequisites: tuple[asyncio.Future[None], ...] - - -async def _wait_for_batch(wakeup: asyncio.Event, timeout: float) -> None: - try: - await asyncio.wait_for(wakeup.wait(), timeout) - except asyncio.TimeoutError: - return - - -def _report_failure(receipt: Future[None]) -> None: - if not receipt.cancelled() and receipt.exception() is not None: - verbose_proxy_logger.error("Usage capture did not acknowledge commit", exc_info=receipt.exception()) - - -def _retryable_persistence_failure(error: Exception) -> bool: - from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler, exception_chain - - outage: Final = PrismaDBExceptionHandler.find_database_service_unavailable_error_in_chain(error) - return (outage is not None and not PrismaDBExceptionHandler.is_permanent_database_fault(outage)) or any( - isinstance(cause, Exception) - and ( - PrismaDBExceptionHandler.is_deadlock_error(cause) - or PrismaDBExceptionHandler.is_lock_timeout_error(cause) - or PrismaDBExceptionHandler.postgres_sqlstate(cause) == "40001" - ) - for cause in exception_chain(error) - ) - - -def _isolatable_persistence_failure(error: Exception) -> bool: - from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler, exception_chain - - return isinstance(error, AccountingConflictError) or any( - isinstance(cause, Exception) and (PrismaDBExceptionHandler.postgres_sqlstate(cause) or "").startswith("22") - for cause in exception_chain(error) - ) - - -class DurableUsageMeter: - def __init__( - self, - write_batch: Callable[[tuple[UsageWrite, ...]], Awaitable[None]], - settings: UsageCaptureSettings, - *, - wait_for_batch: Callable[[asyncio.Event, float], Awaitable[None]] = _wait_for_batch, - retry_delay: Callable[[float], Awaitable[None]] = asyncio.sleep, - ) -> None: - self._write_batch: Final = write_batch - self.settings: Final = settings - self._wait_for_batch: Final = wait_for_batch - self._retry_delay: Final = retry_delay - self._loop: Final = asyncio.get_running_loop() - self._admission: Final = Lock() - self._queue: Final[deque[_Pending]] = deque() # mutable-ok: one bounded producer/consumer queue - self._wakeup: Final = asyncio.Event() - self._capacity_changed: Final = asyncio.Event() - self._reservations: Mapping[object, tuple[int, int]] = {} - self._reserved_bytes = 0 - self._task: asyncio.Task[None] | None = None - self._closed = False - self.pending_bytes = 0 - self.pending_records = 0 - - def submit( - self, writes: tuple[UsageWrite, ...], *, prerequisites: tuple[asyncio.Future[None], ...] = () - ) -> asyncio.Future[None]: - size: Final = sum(len(write.envelope.encode("utf-8")) for write in writes) - with self._admission: - if ( - self._closed - or not writes - or len(writes) > self.settings.batch_size - or self.pending_bytes + size > self.settings.max_pending_bytes - or self.pending_records + len(writes) > self.settings.max_pending_records - ): - raise UsageCaptureError("Usage capture admission rejected: closed, empty or capacity exhausted") - receipt: Final = Future[None]() - receipt.set_running_or_notify_cancel() - receipt.add_done_callback(_report_failure) - self._queue.append(_Pending(writes, size, receipt, asyncio.Event(), prerequisites)) - self.pending_bytes += size - self.pending_records += len(writes) - self._loop.call_soon_threadsafe(self._ensure_worker) - wrapped: Final = asyncio.wrap_future(receipt, loop=self._loop) - wrapped.add_done_callback(lambda done: None if done.cancelled() else done.exception()) - return wrapped - - def reserve_producer(self, size: int, headroom: int) -> object: - token: Final = object() - self.resize_producer(token, size, headroom) - return token - - def resize_producer(self, token: object, size: int, headroom: int) -> None: - with self._admission: - previous: Final = self._reservations.get(token, (0, 0))[0] - delta: Final = size - previous - others: Final = (value[1] for key, value in self._reservations.items() if key is not token) - required: Final = max((headroom, *others)) - if ( - self._closed - or self.pending_bytes + delta > self.settings.max_pending_bytes - or self._reserved_bytes + delta + required > self.settings.max_pending_bytes - ): - raise UsageCaptureError("Batch capture producer byte capacity exhausted") - self._reservations = {**self._reservations, token: (size, headroom)} - self._reserved_bytes += delta - self.pending_bytes += delta - self._capacity_changed.set() - - def release_producer(self, token: object) -> None: - with self._admission: - size, _ = self._reservations[token] - self._reservations = {key: value for key, value in self._reservations.items() if key is not token} - self._reserved_bytes -= size - self.pending_bytes -= size - self._capacity_changed.set() - - def _ensure_worker(self) -> None: - if self.pending_records >= self.settings.batch_size or self._queue and self._queue[0].prerequisites: - self._wakeup.set() - if self._task is None or self._task.done(): - self._task = asyncio.create_task(self._run(), name="accounting usage capture") - - async def record(self, event: InboundUsageEvent | OutboundUsageEvent) -> None: - envelope: Final = '{"event":' + event.model_dump_json() + "}" - await asyncio.shield(self.submit((UsageWrite(event, envelope, usage_delivery_targets(event.dimensions)),))) - - async def record_writes(self, writes: tuple[UsageWrite, ...]) -> None: - size: Final = sum(len(write.envelope.encode("utf-8")) for write in writes) - capacity: Final = self.settings.max_pending_bytes - self._reserved_bytes - if len(writes) > min(self.settings.batch_size, self.settings.max_pending_records) or ( - size > capacity and len(writes) > 1 - ): - middle: Final = len(writes) // 2 - await self.record_writes(writes[:middle]) - await self.record_writes(writes[middle:]) - return - if size > capacity: - raise UsageCaptureError("One usage observation exceeds capture capacity") - while (receipt := self._submit_available(writes)) is None: - self._wakeup.set() - await self._capacity_changed.wait() - self._wakeup.set() - await asyncio.shield(receipt) - - def _submit_available(self, writes: tuple[UsageWrite, ...]) -> asyncio.Future[None] | None: - self._capacity_changed.clear() - try: - receipt: Final = self.submit(writes) - except UsageCaptureError: - if self._closed or not self.pending_records or not writes: - raise - return None - return receipt - - async def flush(self) -> None: - self._ensure_worker() - self._wakeup.set() - if self._task is not None: - await asyncio.shield(self._task) - - async def close(self) -> None: - with self._admission: - self._closed = True - await self.flush() - - async def stop(self, timeout: float) -> None: - with self._admission: - self._closed = True - try: - await asyncio.wait_for(self.close(), timeout) - except asyncio.TimeoutError: - if self._task is not None: - self._task.cancel() - await asyncio.gather(self._task, return_exceptions=True) - while self._queue: - self._finish( - self._take_batch(), UsageCaptureError("Usage capture stopped before commit acknowledgement") - ) - verbose_proxy_logger.error("Usage capture shutdown deadline exhausted; commit acknowledgement incomplete") - - def _take_batch(self) -> tuple[_Pending, ...]: - with self._admission: - if self._queue[0].prerequisites: - return (self._queue.popleft(),) - independent: Final = takewhile(lambda item: not item.prerequisites, self._queue) - sizes: Final = accumulate(len(item.writes) for item in independent) - count: Final = sum(1 for _ in takewhile(lambda size: size <= self.settings.batch_size, sizes)) - return tuple(self._queue.popleft() for _ in range(count)) - - async def _persist(self, writes: tuple[UsageWrite, ...]) -> None: - for attempt in count(): - try: - await self._write_batch(writes) - except Exception as error: # noqa: BLE001 # retry only classified database failures, preserving frozen writes - if not _retryable_persistence_failure(error): - raise - verbose_proxy_logger.warning("Usage persistence unavailable; retaining admitted batch for retry") - await self._retry_delay(min(10.0, 0.2 * 2 ** min(attempt, 6))) - else: - return - - async def _commit(self, batch: tuple[_Pending, ...]) -> None: - writes: Final = tuple(chain.from_iterable(item.writes for item in batch)) - try: - if batch[0].prerequisites: - outcomes: Final = await asyncio.gather( - *(asyncio.shield(receipt) for receipt in batch[0].prerequisites), return_exceptions=True - ) - for outcome in outcomes: - if isinstance(outcome, BaseException): - raise UsageCaptureError("Usage dependency did not acknowledge commit") from outcome - await self._persist(writes) - except asyncio.CancelledError: - self._finish(batch, UsageCaptureError("Usage commit acknowledgement interrupted")) - raise - except Exception as error: # noqa: BLE001 # isolate data faults, surface systemic failures to all producers - if len(batch) > 1 and _isolatable_persistence_failure(error): - try: - for item in batch: - await self._commit((item,)) - except asyncio.CancelledError: - self._finish(batch, UsageCaptureError("Usage commit acknowledgement interrupted")) - raise - return - self._finish( - batch, - UsageCaptureError("Usage identity conflicts with accepted content") - if isinstance(error, AccountingConflictError) - else error, - ) - else: - self._finish(batch, None) - - def _finish(self, batch: tuple[_Pending, ...], error: Exception | None) -> None: - for item in batch: - if item.finished.is_set(): - continue - item.finished.set() - with self._admission: - self.pending_bytes -= item.size - self.pending_records -= len(item.writes) - self._capacity_changed.set() - if item.committed.done(): - continue - if error is None: - item.committed.set_result(None) - else: - item.committed.set_exception(error) - - async def _run(self) -> None: - try: - while self._queue: - await self._wait_for_batch(self._wakeup, self.settings.flush_interval_seconds) - self._wakeup.clear() - await self._commit(self._take_batch()) - if ( - self._closed - or self.pending_records >= self.settings.batch_size - or self._queue - and self._queue[0].prerequisites - ): - self._wakeup.set() - except (Exception, asyncio.CancelledError): # noqa: BLE001 # reject queued receipts if the writer exits abnormally - while self._queue: - self._finish( - self._take_batch(), UsageCaptureError("Usage capture stopped before commit acknowledgement") - ) - raise diff --git a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py index e5348684d78..e68008135aa 100644 --- a/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py +++ b/litellm/proxy/ui_crud_endpoints/proxy_setting_endpoints.py @@ -6,6 +6,7 @@ from collections import Counter from collections.abc import Mapping, MutableMapping, Sequence from types import MappingProxyType from typing import ( + TYPE_CHECKING, Annotated, Final, Literal, @@ -26,6 +27,7 @@ from litellm._logging import verbose_proxy_logger from litellm.litellm_core_utils.sensitive_data_masker import mask_sensitive_keys from litellm.proxy._types import * from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.common_utils.encrypt_decrypt_utils import decrypt_value_helper from litellm.proxy.common_utils.validation_error_body import public_validation_errors from litellm.proxy.config_resolvers import FieldSource, SettingsStore, source_for from litellm.proxy.config_resolvers.settings_store import ConfigOwnedKeyError @@ -61,6 +63,9 @@ from litellm.types.proxy.management_endpoints.ui_sso import ( SSOConfig, ) +if TYPE_CHECKING: + from prisma.errors import PrismaError + router: Final = APIRouter() _DECODED_JSON: Final = TypeAdapter(object) @@ -1247,6 +1252,39 @@ async def get_sso_settings(): } +_ENVIRONMENT_VARIABLES_PARAM: Final = TypeAdapter(dict[str, object]) + + +def _parse_environment_variables_param(param_value: str | Mapping[str, object] | None) -> Mapping[str, object]: + if isinstance(param_value, str): + return _ENVIRONMENT_VARIABLES_PARAM.validate_python(json.loads(param_value)) + return param_value or {} + + +async def _load_environment_variables_param( + repo: ConfigRepository, +) -> "Mapping[str, object] | None | PrismaError | ValueError": + from prisma.errors import PrismaError + + try: + entry: Final = await _config_param_db(repo).find_unique(where={"param_name": "environment_variables"}) + param_value: Final = None if entry is None else _parse_environment_variables_param(entry.param_value) + except (PrismaError, ValueError) as e: + return e + else: + return param_value + + +def _decrypted_sso_fields(environment_variables: Mapping[str, object]) -> Mapping[str, str | None]: + return MappingProxyType( + { + field_name: decrypt_value_helper(value=value, key=env_var, return_original_value=True) + for field_name, env_var in SSO_FIELD_ENV_VARS.items() + if isinstance(value := environment_variables.get(env_var), str) + } + ) + + @router.patch( "/update/sso_settings", tags=["SSO Settings"], @@ -1281,6 +1319,8 @@ async def update_sso_settings( detail={"error": "Set `'STORE_MODEL_IN_DB='True'` in your env to enable this feature."}, ) + from prisma.errors import PrismaError + # Read the existing SSO row first so the audit log captures a real # before/after diff. Stored values are encrypted; decrypt them so the # before-snapshot has the same shape as after_value, and rely on @@ -1310,9 +1350,24 @@ async def update_sso_settings( if "general_settings" not in config: config["general_settings"] = {} - # Update environment variables in config and in memory - sso_data: Final = sso_config.model_dump() - for field_name, value in sso_data.items(): + # PATCH semantics: omitted fields keep their stored value, an explicit null clears it. SSO values that + # still live only in the environment_variables row are carried over, since that row is stripped below + environment_variables_param: Final = await _load_environment_variables_param( + ConfigRepository(prisma_client, use_writer=True) + ) + legacy_env_values: Final[Mapping[str, str | None]] = ( + _decrypted_sso_fields(environment_variables_param) + if isinstance(environment_variables_param, Mapping) + else MappingProxyType({}) + ) + stored_values: Final = {k: v for k, v in (before_sso_data or {}).items() if v is not None and v != ""} + fallback_values: Final = {**legacy_env_values, **stored_values} + submitted: Final = sso_config.model_dump(include=sso_config.model_fields_set) + sso_data: Final = { + field_name: submitted[field_name] if field_name in submitted else fallback_values.get(field_name) + for field_name in SSOConfig.model_fields + } + for field_name, value in submitted.items(): if field_name in SSO_FIELD_ENV_VARS: env_var_name = SSO_FIELD_ENV_VARS[field_name] if value: @@ -1348,25 +1403,17 @@ async def update_sso_settings( ) ) - # Remove SSO-related env vars from config.environment_variables - try: - env_var_entry: Final = await _config_param_db(ConfigRepository(prisma_client, use_writer=True)).find_unique( - where={"param_name": "environment_variables"} + if isinstance(environment_variables_param, (PrismaError, ValueError)): + raise HTTPException( + status_code=500, + detail={"error": f"Error updating environment_variables: {environment_variables_param}"}, ) - # If no environment_variables entry exists, nothing to clean up - if env_var_entry is not None: - if env_var_entry.param_value is not None: - if isinstance(env_var_entry.param_value, str): - environment_variables: Mapping[str, object] = json.loads(env_var_entry.param_value) - else: - environment_variables = dict(env_var_entry.param_value) - else: - environment_variables = {} - + if environment_variables_param is not None: + try: env_vars_to_remove: Final = set(SSO_FIELD_ENV_VARS.values()) filtered_env_vars: Final = { - key: value for key, value in environment_variables.items() if key not in env_vars_to_remove + key: value for key, value in environment_variables_param.items() if key not in env_vars_to_remove } await _config_param_db(ConfigRepository(prisma_client)).update( @@ -1376,16 +1423,16 @@ async def update_sso_settings( }, ) await invalidate_config_param("environment_variables") - except Exception as e: - raise HTTPException( - status_code=500, - detail={"error": f"Error updating environment_variables: {e}"}, - ) + except Exception as e: + raise HTTPException( + status_code=500, + detail={"error": f"Error updating environment_variables: {e}"}, + ) return { "message": "SSO settings updated successfully", "status": "success", - "settings": sso_data, + "settings": mask_sensitive_keys(sso_data, set(SSO_SECRET_FIELDS)), } diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index a1b36e5b7a1..a2928bba287 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -28,7 +28,8 @@ from dataclasses import dataclass, field from datetime import date, datetime, timedelta, timezone from email.mime.multipart import MIMEMultipart from email.mime.text import MIMEText -from functools import partial +from email.utils import formatdate +from functools import partial, reduce from itertools import takewhile from operator import attrgetter from types import MappingProxyType @@ -66,8 +67,10 @@ from litellm.constants import ( REDACTED_BY_LITELLM, REDIS_SPEND_LOGS_BUFFER_DEQUEUE_COUNT, SPEND_LOG_QUEUE_MAX_BYTES, + SPEND_LOG_READ_STATEMENT_TIMEOUT_SECONDS, SPEND_LOG_WRITE_BATCH_MAX_BYTES, SPEND_LOG_WRITE_BATCH_MAX_ROWS, + VLLM_CHOICE_FIELDS, ) from litellm.cost_calculator import BaseTokenUsageProcessor from litellm.litellm_core_utils.bug_report import ( @@ -166,10 +169,10 @@ from litellm.litellm_core_utils.env_utils import get_env_float, get_env_int from litellm.litellm_core_utils.litellm_logging import ( BilledRoundsDispatch, Logging, - UsageObservation, deployment_pricing_model_info, ) from litellm.litellm_core_utils.llm_cost_calc.utils import generic_cost_per_token +from litellm.litellm_core_utils.redact_messages import drop_token_ids from litellm.litellm_core_utils.routing_common_utils import resolve_model_group_alias from litellm.litellm_core_utils.safe_json_dumps import safe_dumps from litellm.litellm_core_utils.safe_json_loads import safe_json_loads @@ -179,6 +182,7 @@ from litellm.litellm_core_utils.served_output_texts import ( ) from litellm.litellm_core_utils.token_counter import offload_token_count, usage_tokenizer_model from litellm.llms import load_guardrail_translation_mappings +from litellm.llms.base_llm.guardrail_translation.utils import stream_item_field, stream_item_items from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler from litellm.proxy._types import ( AlertType, @@ -210,6 +214,7 @@ from litellm.proxy.db.db_url_settings import ( from litellm.proxy.db.exception_handler import ( PrismaDBExceptionHandler, call_with_db_reconnect_retry, + db_write_never_sent, ) from litellm.proxy.db.health_check_latest import ( LatestHealthCheckRow, @@ -274,6 +279,7 @@ from litellm.proxy.policy_engine.policy_registry import get_policy_registry from litellm.proxy.policy_engine.policy_resolver import PolicyResolver from litellm.repositories.budget_repository import BudgetRepository from litellm.repositories.config_repository import ConfigRepository +from litellm.repositories.spend_log_insert import RejectedSpendLogRow from litellm.repositories.table_repositories import ( EndUserRepository, HealthCheckRepository, @@ -707,6 +713,56 @@ def _pipeline_step_streams_live(step: "PipelineStep") -> bool: return not unified_guardrail.resolve_streaming_flag(callback, "streaming_buffer_until_moderated", True) +def _drop_stream_chunk_token_ids(chunk: object) -> None: + for choice in stream_item_items(chunk, "choices"): + drop_token_ids(choice) + + +def _drop_built_stream_token_ids(request_data: Mapping[str, object]) -> None: + logging_obj: Final = request_data.get("litellm_logging_obj") + if isinstance(logging_obj, Logging): + logging_obj.drops_stream_token_ids = True + + +def _drop_token_ids_ahead_of_chunk_check( + callback: CustomLogger, chunk: object, request_data: Mapping[str, object] +) -> None: + if _overrides_hook(callback, "async_post_call_streaming_hook"): + _drop_stream_chunk_token_ids(chunk) + _drop_built_stream_token_ids(request_data) + + +_PLAIN_STREAM_FIELDS: Final = TypeAdapter(dict[str, object]) +_EMPTY_STREAM_VALUES: Final[tuple[object, ...]] = (None, "", [], {}) + + +def _holds_stream_payload(value: object) -> bool: + if isinstance(value, dict): + nested: Final = _PLAIN_STREAM_FIELDS.validate_python(value).values() + return any(item not in _EMPTY_STREAM_VALUES for item in nested) + return value not in _EMPTY_STREAM_VALUES + + +def _choice_carries_only_token_ids(choice: object) -> bool: + if stream_item_field(choice, "token_ids") is None or not isinstance(choice, BaseModel): + return False + fields: Final = _PLAIN_STREAM_FIELDS.validate_python(choice.model_dump()) + return not any(_holds_stream_payload(value) for key, value in fields.items() if key not in ("index", "token_ids")) + + +def _is_token_id_only_chunk(chunk: object) -> bool: + choices: Final = stream_item_items(chunk, "choices") + return bool(choices) and all(_choice_carries_only_token_ids(choice) for choice in choices) + + +async def _without_token_id_only_chunks(response: AsyncIterable[object]) -> AsyncGenerator[object, None]: + async for chunk in response: + if _is_token_id_only_chunk(chunk): + _drop_stream_chunk_token_ids(chunk) + continue + yield chunk + + def _pipelines_stream_live(pipelines: Sequence[tuple[str, "GuardrailPipeline"]]) -> bool: return all(_pipeline_step_streams_live(step) for step in _pipeline_steps(pipelines)) @@ -1627,14 +1683,17 @@ _LOG_DB_METRICS_CALL_TYPES: Final = frozenset(("get_data", "insert_data", "updat _EXCEPTION_CHAIN_MAX_DEPTH: Final = 16 +def _extended_exception_chain(chain: tuple[BaseException, ...], iteration: int) -> tuple[BaseException, ...]: + if len(chain) != iteration + 1: + return chain + following: Final = chain[-1].__cause__ or chain[-1].__context__ + if following is None or following in chain: + return chain + return (*chain, following) + + def _exception_chain(exception: BaseException) -> tuple[BaseException, ...]: - chain: Final[list[BaseException]] = [exception] # mutable-ok: built once, returned frozen - for _ in range(_EXCEPTION_CHAIN_MAX_DEPTH): - following = chain[-1].__cause__ or chain[-1].__context__ - if following is None or following in chain: - break - chain.append(following) - return tuple(chain) + return reduce(_extended_exception_chain, range(_EXCEPTION_CHAIN_MAX_DEPTH), (exception,)) def _timed_out_reading_from_provider(exception: Exception) -> bool: @@ -1707,7 +1766,10 @@ def _proxy_only_error_log_fields( def _failure_fields_to_lift( - request_data: Mapping[str, object], provider_billed: bool = False, dispatched_call_type: str | None = None + request_data: Mapping[str, object], + provider_billed: bool = False, + dispatched_call_type: str | None = None, + route_call_type: str | None = None, ) -> Mapping[str, object]: """Failure-path callbacks run after ``litellm_logging_obj`` is popped from request_data (it is not serialisable), so the caller merges these fields @@ -1717,7 +1779,8 @@ def _failure_fields_to_lift( attribution on failed-request spend logs.""" _logging_obj: Final = request_data.get("litellm_logging_obj") if _logging_obj is None: - return _EMPTY_LIFT + return _EMPTY_LIFT if dispatched_call_type is None else MappingProxyType({"call_type": dispatched_call_type}) + _estimate_call_type: Final = dispatched_call_type or route_call_type _model_call_details: Final = getattr(_logging_obj, "model_call_details", {}) _first_handoff: Final = _model_call_details.get("first_api_call_start_time") _litellm_params: Final = getattr(_logging_obj, "litellm_params", None) @@ -1732,10 +1795,10 @@ def _failure_fields_to_lift( provider_billed=_billed, deployment_id=_deployment_id, base_model=_base_model, - dispatched_call_type=dispatched_call_type, + dispatched_call_type=_estimate_call_type, ) _prompt_estimate: Final = ( - _estimated_prompt_usage(_model_call_details, request_data, dispatched_call_type) + _estimated_prompt_usage(_model_call_details, request_data, _estimate_call_type) if _billed and _first_handoff is not None and not _model_call_details.get("failed_attempts_usage") else None ) @@ -1744,39 +1807,6 @@ def _failure_fields_to_lift( if _prompt_estimate is not None else () ) - from litellm.litellm_core_utils.litellm_logging import UsageCaptureObservation - - _recorded_observation: Final[object] = _model_call_details.get("_accounting_usage_observed") - _current_usage: Final = ( - _current_failure_usage_to_lift( - _model_call_details, - request_data, - _model_call_details.get("current_attempt_api_call_start_time", _first_handoff) is not None, - _billed, - _deployment_id, - _base_model, - dispatched_call_type, - ) - if Logging.usage_capture_callback is not None - and (_billed or _model_call_details.get("combined_usage_object") is not None) - else None - ) - _current_observation: Final = ( - _recorded_observation - if isinstance(_recorded_observation, UsageObservation) - else UsageObservation.UNKNOWN - if _current_usage is None - else UsageObservation.KNOWN - if _model_call_details.get("combined_usage_object") is not None - else UsageObservation.ESTIMATED - ) - _capture_observation: Final = UsageCaptureObservation.from_usage( - _current_usage[0] if _current_usage is not None and isinstance(_current_usage[0], Usage) else None, - _current_observation, - float(_current_usage[1]) - if _current_usage is not None and isinstance(_current_usage[1], (int, float)) - else None, - ) _entries: Final = ( ("start_time", _model_call_details.get("start_time")), ("first_api_call_start_time", _first_handoff), @@ -1785,16 +1815,12 @@ def _failure_fields_to_lift( ("response_cost", None if _usage_to_lift is None else (_usage_to_lift[1] or 0.0)), ("standard_logging_object", _model_call_details.get("standard_logging_object")), ("billed_failed_attempts", _earlier_attempts or None), - ("_accounting_capture", _model_call_details.get("_accounting_capture")), ("_accounting_pricing_snapshot", _model_call_details.get("_accounting_pricing_snapshot")), ("_accounting_finalized_cost", _logging_obj.finalized_cost if isinstance(_logging_obj, Logging) else None), ( "_accounting_allocation", _logging_obj.cost_allowance_allocation if isinstance(_logging_obj, Logging) else None, ), - ("_accounting_usage_observed", _current_observation if Logging.usage_capture_callback is not None else None), - ("_accounting_usage_snapshot", _capture_observation if Logging.usage_capture_callback is not None else None), - ("_accounting_prior_captures", _model_call_details.get("_accounting_prior_captures")), ) return MappingProxyType({key: value for key, value in _entries if value is not None}) @@ -1927,6 +1953,7 @@ class ProxyLogging: self.daily_report_started: bool = False self.hanging_requests_check_started: bool = False self.deprecation_check_started: bool = False + self.deprecation_email_check_started: bool = False def startup_event( self, @@ -1970,6 +1997,20 @@ class ProxyLogging: self.hanging_requests_check_started = True self._ensure_deprecation_check_scheduled() + self._ensure_deprecation_email_check_scheduled() + + def _ensure_deprecation_email_check_scheduled(self) -> None: + """The email event opt-in controls reminders independently of Slack integration settings.""" + if self.deprecation_email_check_started: + return + try: + asyncio.get_running_loop() + except RuntimeError: + return + from litellm.integrations.model_deprecation_email import run_scheduled_model_deprecation_emails + + asyncio.create_task(run_scheduled_model_deprecation_emails()) + self.deprecation_email_check_started = True def _ensure_deprecation_check_scheduled(self) -> None: """Alerting can be configured at startup or by a later config reload, so schedule from either path""" @@ -2016,6 +2057,7 @@ class ProxyLogging: if updated_slack_alerting is True: self._ensure_deprecation_check_scheduled() + self._ensure_deprecation_email_check_scheduled() self.slack_alerting_instance.update_values( alerting=self.alerting, alerting_threshold=self.alerting_threshold, @@ -4051,13 +4093,15 @@ class ProxyLogging: route=route, original_exception=original_exception, error_type=error_type, + dispatched_call_type=dispatched_call_type, ) request_data.update( await offload_token_count(_failure_fields_to_lift)( request_data, provider_billed=_provider_billed_the_failure(original_exception), - dispatched_call_type=dispatched_call_type or _call_type_for_route(user_api_key_dict.request_route), + dispatched_call_type=dispatched_call_type, + route_call_type=_call_type_for_route(user_api_key_dict.request_route), ) ) @@ -4146,6 +4190,7 @@ class ProxyLogging: route: str | None = None, original_exception: Exception | None = None, error_type: ProxyErrorTypes | None = None, + dispatched_call_type: str | None = None, ): """ Handle logging for proxy only errors by calling `litellm_logging_obj.async_failure_handler` @@ -4245,7 +4290,7 @@ class ProxyLogging: litellm_logging_obj.model_call_details["input"] = input body_shape_call_type = CallTypes.aembedding.value resolved_call_type: Final = _call_type_for_route(route) or ( - None if set_up_by_request else body_shape_call_type + None if set_up_by_request else dispatched_call_type or body_shape_call_type ) if resolved_call_type is not None and litellm_logging_obj.call_type != CallTypes.pass_through.value: litellm_logging_obj.call_type = resolved_call_type @@ -4710,6 +4755,7 @@ class ProxyLogging: else: _callback = callback if _callback is not None and isinstance(_callback, CustomLogger): + _drop_token_ids_ahead_of_chunk_check(_callback, response, data) if str_so_far is not None: complete_response = str_so_far + response_str else: @@ -4731,7 +4777,7 @@ class ProxyLogging: self, response, user_api_key_dict: UserAPIKeyAuth, - request_data: dict, + request_data: dict[str, object], ): """ Allow user to modify outgoing streaming data -> Given a whole response iterator. @@ -4765,20 +4811,26 @@ class ProxyLogging: # Merge model-level guardrails before checking which guardrails to run request_data = check_and_merge_model_level_guardrails(data=request_data, llm_router=llm_router) - current_response = response stream_needs_translation: Final = ProxyLogging._stream_requires_guardrail_translation(user_api_key_dict) pipeline_gated_names: Final = _pipeline_step_guardrail_names(post_call_pipelines) + running_overrides: Final = tuple( + (callback, kind) + for callback, kind in caps.iterator_overrides + if not isinstance(callback, CustomGuardrail) + or ( + callback.guardrail_name not in pipeline_gated_names + and callback.should_run_guardrail(data=request_data, event_type=GuardrailEventHooks.post_call) is True + ) + ) + drops_token_ids: Final = bool(post_call_pipelines) or any( + isinstance(callback, CustomGuardrail) for callback, _ in running_overrides + ) + if drops_token_ids: + _drop_built_stream_token_ids(request_data) + current_response = _without_token_id_only_chunks(response) if drops_token_ids else response guarded_layers: Final[list[AsyncGenerator[object, None]]] = [] # mutable-ok: closed on disconnect - for resolved_callback, kind in caps.iterator_overrides: - if isinstance(resolved_callback, CustomGuardrail): - if resolved_callback.guardrail_name in pipeline_gated_names: - continue - if ( - resolved_callback.should_run_guardrail(data=request_data, event_type=GuardrailEventHooks.post_call) - is not True - ): - continue + for resolved_callback, kind in running_overrides: effective_kind = ( "apply_guardrail" if ( @@ -4836,6 +4888,8 @@ class ProxyLogging: try: async for chunk in current_response: served_chunks.append(chunk) + if drops_token_ids: + _drop_stream_chunk_token_ids(served_chunks[-1]) yield chunk except (GeneratorExit, asyncio.CancelledError): await ProxyLogging._close_guarded_layers(guarded_layers) @@ -5240,6 +5294,39 @@ _deprecated_key_cache: Final[LimitedSizeOrderedDict] = LimitedSizeOrderedDict(ma _DEPRECATED_KEY_CACHE_TTL_SECONDS: Final = 60 _PRISMA_DEFAULT_TX_TIMEOUT: Final = timedelta(seconds=5) _PRISMA_DEFAULT_TX_MAX_WAIT: Final = timedelta(seconds=2) +_SPEND_LOG_READ_STATEMENT_TIMEOUT: Final = timedelta(seconds=SPEND_LOG_READ_STATEMENT_TIMEOUT_SECONDS) +_STATEMENT_TIMEOUT_TRANSACTION_GRACE: Final = timedelta(seconds=5) + + +class _ReadTransactionClient(Protocol): + @property + def read_db(self) -> PrismaWrapper: ... + + +async def query_raw_within_statement_timeout( + prisma_client: _ReadTransactionClient, + sql: str, + *params: object, + what: str = "Spend logs", + timeout: timedelta = _SPEND_LOG_READ_STATEMENT_TIMEOUT, +) -> Sequence[Mapping[str, object]]: + """One raw read on the read target that Postgres cancels at ``timeout``. + + Prisma's HTTP client gives up on a statement after 30s anyway, so without + this the Admin UI's error is the same but Postgres keeps running the scan. + A cancelled read surfaces as a 503 asking for a narrower date range. + """ + try: + async with prisma_client.read_db.tx(timeout=timeout + _STATEMENT_TIMEOUT_TRANSACTION_GRACE) as transaction: + await transaction.execute_raw(f"SET LOCAL statement_timeout = {int(timeout / timedelta(milliseconds=1))}") + return await transaction.query_raw(sql, *params) + except Exception as e: + if not PrismaDBExceptionHandler.is_statement_timeout_error(e): + raise + raise HTTPException( + status_code=status.HTTP_503_SERVICE_UNAVAILABLE, + detail={"error": f"{what} took longer than {int(timeout.total_seconds())}s. Pick a shorter date range"}, + ) from e async def _lookup_deprecated_key( @@ -8193,7 +8280,9 @@ async def send_email( receiver_email: str | None = None, subject: str | None = None, html: str | None = None, -): + text: str | None = None, + message_id: str | None = None, +) -> bool: """ smtp_host, smtp_port, @@ -8219,16 +8308,21 @@ async def send_email( raise ValueError(f"No HTML body provided for SMTP email. {html}") ## EMAIL SETUP ## - email_message: Final = MIMEMultipart() + email_message: Final = MIMEMultipart("alternative" if text is not None else "mixed") email_message["From"] = sender_email email_message["To"] = receiver_email email_message["Subject"] = subject + if message_id is not None: + email_message["Message-ID"] = message_id + email_message["Date"] = formatdate(usegmt=True) verbose_proxy_logger.debug("sending email from %s to %s", sender_email, receiver_email) if smtp_host is None: raise ValueError("Trying to use SMTP, but SMTP_HOST is not set") # Attach the body to the email + if text is not None: + email_message.attach(MIMEText(text, "plain")) email_message.attach(MIMEText(html, "html")) try: @@ -8247,6 +8341,8 @@ async def send_email( except Exception as e: verbose_proxy_logger.exception("An error occurred while sending the email:" + str(e)) + return False + return True def hash_token(token: str): @@ -8349,14 +8445,17 @@ async def enqueue_spend_logs( """ added: Final = sum(spend_log_row_bytes(row) for row in logs) async with prisma_client._spend_log_transactions_lock: - queued: Final = ( + queued: Final[tuple[Mapping[str, object], ...]] = ( tuple(logs) + tuple(prisma_client.spend_log_transactions) if at_head else tuple(prisma_client.spend_log_transactions) + tuple(logs) ) kept, kept_bytes = spend_log_queue_within_budget(queued, PrismaClient.spend_log_queue_bytes + added, max_bytes) - prisma_client.spend_log_transactions[:] = kept - PrismaClient.spend_log_queue_bytes = kept_bytes + rescued: Final = tuple( + accounting_only_spend_log(row) for row in queued[: len(queued) - len(kept)] if _carries_a_charge(row) + ) + prisma_client.spend_log_transactions[:] = (*rescued, *kept) + PrismaClient.spend_log_queue_bytes = kept_bytes + sum(spend_log_row_bytes(row) for row in rescued) if len(kept) < len(queued): verbose_proxy_logger.error( "Spend tracking - spend log queue is at its %d byte budget; dropped the %d oldest spend logs", @@ -8411,13 +8510,18 @@ class ProxyUpdateSpend: prisma_client: PrismaClient, proxy_logging_obj: ProxyLogging, end_user_list_transactions: dict[str, float], + outer_transaction: _EndUserSpendTransaction | None = None, ): for i in range(n_retry_times + 1): start_time = time.time() try: async with ( db_span("update_end_user_spend", "LiteLLM_EndUserTable"), - _end_user_spend_transaction(prisma_client.db, timedelta(seconds=60)) as transaction, + ( + contextlib.nullcontext(outer_transaction) + if outer_transaction is not None + else _end_user_spend_transaction(prisma_client.db, timedelta(seconds=60)) + ) as transaction, ): batcher: _EndUserSpendBatch async with transaction.batch_() as batcher: @@ -8439,6 +8543,8 @@ class ProxyUpdateSpend: break except Exception as e: + if outer_transaction is not None: + raise await DBSpendUpdateWriter.handle_spend_update_failure( e=e, attempt=i, @@ -8478,11 +8584,18 @@ class ProxyUpdateSpend: for i in range(n_retry_times + 1): try: base_url = os.getenv("SPEND_LOGS_URL", None) - if len(logs_to_process) > 0 and base_url is not None and db_writer_client is not None: + await _commit_export_accounting( + prisma_client, rows_to_write, base_url if db_writer_client is not None else None + ) + if ( + base_url is not None + and db_writer_client is not None + and any(row.get("accounting_log_disabled") is not True for row in rows_to_write) + ): if not base_url.endswith("/"): base_url += "/" verbose_proxy_logger.debug("base_url: %s", base_url) - json_data = json.dumps(rows_to_write) + json_data = json.dumps(_spend_log_export_rows(rows_to_write)) response = await db_writer_client.post( url=base_url + "spend/update", data=json_data, @@ -8560,6 +8673,28 @@ class ProxyUpdateSpend: return False +def _spend_log_export_rows(rows: Sequence[Mapping[str, object]]) -> tuple[Mapping[str, object], ...]: + return tuple( + { + key: value + for key, value in row.items() + if key not in {"accounting_payload", "accounting_log_disabled", "accounting_delivery_id"} + } + for row in rows + if row.get("accounting_log_disabled") is not True + ) + + +async def _commit_export_accounting( + prisma_client: PrismaClient, rows: Sequence[Mapping[str, object]], base_url: str | None +) -> None: + if base_url is None: + return + await SpendLogsRepository(prisma_client).insert_with_deliveries( + tuple(row for row in rows if "accounting_payload" in row), write_spend_logs=False + ) + + async def commit_tool_discoveries(prisma_client: PrismaClient, proxy_logging_obj: ProxyLogging) -> None: """Scheduler job writing discovered tools to LiteLLM_ToolTable, on its own lock, next to update_spend.""" writer: Final = proxy_logging_obj.db_spend_update_writer @@ -8735,9 +8870,20 @@ async def update_daily_tag_spend( def _rollup_batch_never_applied(e: Exception) -> bool: """True when a drained rollup batch provably never reached its rows: Postgres had no - connection for it (53300) or cancelled it under ``lock_timeout`` before it took the row - lock (55P03). Either way re-sending the batch cannot double-count, so it is requeued.""" - return PrismaDBExceptionHandler.is_database_capacity_error(e) or PrismaDBExceptionHandler.is_lock_timeout_error(e) + connection for it (53300), was unreachable or refusing connections (P1001, 57P03), or + cancelled it under ``lock_timeout`` before it took the row lock (55P03). In each case + re-sending the batch cannot double-count, so it is requeued.""" + return ( + PrismaDBExceptionHandler.is_database_capacity_error(e) + or db_write_never_sent(e) + or PrismaDBExceptionHandler.is_lock_timeout_error(e) + ) + + +def _rollup_failure_stops_job(e: Exception) -> bool: + """True when the database cannot take any write, so the job stops instead of draining + the queues after this one into the same failure.""" + return PrismaDBExceptionHandler.is_database_capacity_error(e) or db_write_never_sent(e) async def update_spend_logs_job( @@ -8828,12 +8974,12 @@ async def _run_spend_logs_job( *prisma_client.tool_usage_transactions, ] verbose_proxy_logger.warning( - "Spend tracking - database out of connections or rollup row lock timed out during tool usage " + "Spend tracking - database unavailable or rollup row lock timed out during tool usage " "flush, requeued %s tool usage transactions for the next flush: %s", len(tool_usage_to_process), tool_tracking_err, ) - if PrismaDBExceptionHandler.is_database_capacity_error(tool_tracking_err): + if _rollup_failure_stops_job(tool_tracking_err): raise else: verbose_proxy_logger.error( @@ -8860,12 +9006,12 @@ async def _run_spend_logs_job( *prisma_client.model_usage_transactions, ] verbose_proxy_logger.warning( - "Spend tracking - database out of connections or rollup row lock timed out during model usage " + "Spend tracking - database unavailable or rollup row lock timed out during model usage " "flush, requeued %s model usage transactions for the next flush: %s", len(model_usage_to_process), model_usage_err, ) - if PrismaDBExceptionHandler.is_database_capacity_error(model_usage_err): + if _rollup_failure_stops_job(model_usage_err): raise else: verbose_proxy_logger.error( @@ -9042,10 +9188,45 @@ def _is_transient_spend_log_write_error(e: Exception) -> bool: return ( PrismaDBExceptionHandler.is_database_transport_error(e) or PrismaDBExceptionHandler.is_prisma_engine_internal_error(e) + or PrismaDBExceptionHandler.is_database_lifecycle_error(e) or PrismaDBExceptionHandler.is_deadlock_error(e) ) +_ACCOUNTING_ONLY_KEYS: Final = frozenset({"request_id", "call_type", "accounting_payload", "accounting_delivery_id"}) + + +def _carries_a_charge(row: Mapping[str, object]) -> bool: + return "accounting_payload" in row + + +def accounting_only_spend_log(row: Mapping[str, object]) -> Mapping[str, object]: + return { + **{key: value for key, value in row.items() if key in _ACCOUNTING_ONLY_KEYS}, + "accounting_log_disabled": True, + } + + +async def _keep_charges_of_dropped_logs(repo: SpendLogsRepository, rows: Sequence[Mapping[str, object]]) -> None: + charged: Final = tuple(accounting_only_spend_log(row) for row in rows if _carries_a_charge(row)) + if not charged: + return + try: + await repo.insert_with_deliveries(charged) + except Exception as e: # noqa: BLE001 # the request log is already lost; keep the flush going for other rows + if not ( + PrismaDBExceptionHandler.is_rejected_row_error(e) + or isinstance(e, (UnicodeEncodeError, RejectedSpendLogRow)) + ): + raise + spend_log_error( + "Spend tracking - could not keep the charges of %d dropped spend log rows. error=%s", + len(charged), + str(e), + exc=e, + ) + + async def _create_spend_logs_with_poison_isolation( repo: SpendLogsRepository, rows: Sequence[Mapping[str, object]], @@ -9074,10 +9255,13 @@ async def _create_spend_logs_with_poison_isolation( persist. Returns the budget left after this subtree. """ try: - await repo.table.create_many(data=rows, skip_duplicates=True) + await repo.insert_with_deliveries(rows) return failure_budget except Exception as e: - if not (PrismaDBExceptionHandler.is_prisma_data_error(e) or isinstance(e, UnicodeEncodeError)): + if not ( + PrismaDBExceptionHandler.is_rejected_row_error(e) + or isinstance(e, (UnicodeEncodeError, RejectedSpendLogRow)) + ): raise if PrismaDBExceptionHandler.is_database_service_unavailable_error(e): raise @@ -9092,6 +9276,7 @@ async def _create_spend_logs_with_poison_isolation( str(e), exc=e, ) + await _keep_charges_of_dropped_logs(repo, rows) return budget_left if budget_left <= 0: spend_log_error( @@ -9099,6 +9284,7 @@ async def _create_spend_logs_with_poison_isolation( "isolation failure budget exhausted for this flush", len(rows), ) + await _keep_charges_of_dropped_logs(repo, rows) return 0 mid: Final = len(rows) // 2 remaining: Final = await _create_spend_logs_with_poison_isolation(repo, rows[:mid], budget_left) @@ -9108,6 +9294,7 @@ async def _create_spend_logs_with_poison_isolation( "isolation failure budget exhausted for this flush", len(rows) - mid, ) + await _keep_charges_of_dropped_logs(repo, rows[mid:]) return 0 return await _create_spend_logs_with_poison_isolation(repo, rows[mid:], remaining) @@ -10203,7 +10390,7 @@ _PRESERVED_NONE_FIELDS: Final[list[tuple[str, str]]] = [ ("message", "refusal"), ("delta", "content"), # null in streaming chunks ] -_PRESERVED_NONE_CHOICE_FIELDS: Final = ("logprobs",) +_PRESERVED_NONE_CHOICE_FIELDS: Final = ("logprobs", *VLLM_CHOICE_FIELDS) _PRESERVED_NONE_RESPONSE_FIELDS: Final = ("system_fingerprint",) diff --git a/litellm/realtime_api/main.py b/litellm/realtime_api/main.py index e03cb44efda..be1df4aa0f6 100644 --- a/litellm/realtime_api/main.py +++ b/litellm/realtime_api/main.py @@ -2,11 +2,13 @@ import asyncio import os +import traceback from collections.abc import Mapping from dataclasses import dataclass from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Literal, NoReturn, cast +import httpx from pydantic import TypeAdapter from typing_extensions import ReadOnly, TypedDict, assert_never @@ -14,10 +16,14 @@ import litellm from litellm.constants import ( AZURE_OPENAI_AUDIO_PROVIDERS, REALTIME_CREDENTIAL_RESOLUTION_TIMEOUT_SECONDS, + REALTIME_SESSION_FAILURE_LOGGED_KEY, REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES, request_timeout, ) +from litellm.exceptions import BadRequestError +from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.litellm_core_utils.get_llm_provider_logic import get_llm_provider +from litellm.llms.base_llm.realtime.http_transformation import BaseRealtimeHTTPConfig from litellm.llms.base_llm.realtime.transformation import BaseRealtimeConfig from litellm.llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler from litellm.llms.xai.common_utils import XAIModelInfo @@ -36,18 +42,24 @@ from litellm.utils import ( ModelInfoLookupMiss, ProviderConfigManager, aresolve_api_key_secret_reference, + get_base_model_from_metadata, lookup_model_info_for_registration, ) -from ..litellm_core_utils.core_helpers import as_str_mapping, normalize_drop_params +from ..litellm_core_utils.core_helpers import normalize_drop_params from ..litellm_core_utils.credential_accessor import CredentialAccessor from ..litellm_core_utils.get_litellm_params import get_litellm_params from ..litellm_core_utils.litellm_logging import Logging as LiteLLMLogging -from ..litellm_core_utils.realtime_streaming import client_websocket_scope +from ..litellm_core_utils.realtime_errors import realtime_error_event, websocket_close_reason +from ..litellm_core_utils.realtime_streaming import ( + TRANSLATION_GUARDRAILS_UNSUPPORTED_MESSAGE, + client_websocket_scope, + translation_guardrails_apply, +) from ..llms.azure.common_utils import get_azure_ad_token from ..llms.azure.realtime.handler import AzureOpenAIRealtime, azure_realtime_protocol_for_client from ..llms.bedrock.realtime.handler import BedrockRealtime, raise_if_session_committed -from ..llms.custom_httpx.http_handler import realtime_ssl_for_url +from ..llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler, realtime_ssl_for_url from ..llms.openai.common_utils import is_openai_backed_api_base from ..llms.openai.live.handler import OpenAILiveSessions from ..llms.openai.realtime.handler import ( @@ -66,8 +78,6 @@ from ..utils import client as wrapper_client if TYPE_CHECKING: from fastapi import WebSocket - from litellm.llms.base_llm.realtime.http_transformation import BaseRealtimeHTTPConfig - azure_realtime: Final = AzureOpenAIRealtime() openai_realtime: Final = OpenAIRealtime() openai_live_sessions: Final = OpenAILiveSessions() @@ -77,7 +87,7 @@ vertex_llm_base: Final = VertexBase() base_llm_http_handler = BaseLLMHTTPHandler() _EMPTY_MODEL_PARAMS: Final[Mapping[str, object]] = MappingProxyType({}) _EMPTY_AUTH_HEADERS: Final[Mapping[str, str]] = MappingProxyType({}) -_DEPLOYMENT_PARAMS: Final = TypeAdapter(Mapping[str, object]) +_OBJECT_MAPPING: Final = TypeAdapter(Mapping[str, object]) def _model_params_with_stored_credentials(model_params: Mapping[str, object]) -> Mapping[str, object]: @@ -90,26 +100,145 @@ def _model_params_with_stored_credentials(model_params: Mapping[str, object]) -> return MappingProxyType({**credential_values, **model_params}) -def _with_resolved_session_model(session: dict[str, object], model_name: str) -> dict[str, object]: - if "model" not in session: - return session - return {**session, "model": model_name} +def _transcription_model_overrides(session: Mapping[str, object], model_name: str) -> Mapping[str, object]: + flat_transcription: Final = as_str_mapping(session.get("input_audio_transcription")) + audio: Final = as_str_mapping(session.get("audio")) or {} + audio_input: Final = as_str_mapping(audio.get("input")) or {} + nested_transcription: Final = as_str_mapping(audio_input.get("transcription")) + flat_part: Final = ( + {} if flat_transcription is None else {"input_audio_transcription": {**flat_transcription, "model": model_name}} + ) + nested_part: Final = ( + {} + if nested_transcription is None and flat_transcription is not None + else { + "audio": { + **audio, + "input": {**audio_input, "transcription": {**(nested_transcription or {}), "model": model_name}}, + } + } + ) + return MappingProxyType({**flat_part, **nested_part}) -def _resolved_request_session(request_data: Mapping[str, object], model_name: str) -> Mapping[str, object] | None: - session: Final = as_str_mapping(request_data.get("session")) - if not isinstance(session, dict): - return None - return _with_resolved_session_model(session, model_name) +def with_resolved_session_model(session: Mapping[str, object], model_name: str) -> dict[str, object]: + top_level_model: Final = {} if "model" not in session else {"model": model_name} + transcription_models: Final = ( + _transcription_model_overrides(session, model_name) if session.get("type") == "transcription" else {} + ) + return {**session, **top_level_model, **transcription_models} -def _build_litellm_metadata(kwargs: dict) -> dict[str, object]: - """Build the litellm_metadata dict for guardrail checking (internal only, not forwarded to provider).""" - metadata: Final[dict[str, object]] = {**(kwargs.get("litellm_metadata") or {})} - guardrails: Final = (kwargs.get("metadata") or {}).get("guardrails") or kwargs.get("guardrails") or [] - if guardrails: - metadata["guardrails"] = guardrails - return metadata +def _without_top_level_nulls(fields: Mapping[str, object]) -> dict[str, object]: + return {key: value for key, value in fields.items() if value is not None} + + +_POLICY_PIPELINE_METADATA_KEYS: Final = ("_guardrail_pipelines", "_pipeline_managed_guardrails") + + +def _build_litellm_metadata(kwargs: Mapping[str, object]) -> dict[str, object]: + request_metadata: Final = _OBJECT_MAPPING.validate_python(kwargs.get("metadata") or {}) + internal_metadata: Final = _OBJECT_MAPPING.validate_python(kwargs.get("litellm_metadata") or {}) + policy_pipeline_state: Final = { + key: request_metadata[key] for key in _POLICY_PIPELINE_METADATA_KEYS if key in request_metadata + } + guardrails: Final = request_metadata.get("guardrails") or kwargs.get("guardrails") + return {**policy_pipeline_state, **internal_metadata, **({"guardrails": guardrails} if guardrails else {})} + + +_GUARDRAIL_OPT_OUT_METADATA_KEYS: Final = ("user_api_key_metadata", "user_api_key_team_metadata") + + +def _translation_litellm_metadata(kwargs: Mapping[str, object]) -> Mapping[str, object]: + request_metadata: Final = _OBJECT_MAPPING.validate_python(kwargs.get("metadata") or {}) + guardrail_opt_outs: Final = { + key: request_metadata[key] for key in _GUARDRAIL_OPT_OUT_METADATA_KEYS if key in request_metadata + } + return MappingProxyType({**guardrail_opt_outs, **_build_litellm_metadata(kwargs)}) + + +_HTTP_TRANSLATION_PROVIDERS: Final = frozenset({LlmProviders.OPENAI.value, LlmProviders.AZURE.value}) +_WEBSOCKET_TRANSLATION_PROVIDERS: Final = frozenset({LlmProviders.OPENAI.value, *AZURE_OPENAI_AUDIO_PROVIDERS}) + + +@dataclass(frozen=True, slots=True) +class _TranslationProviderUnsupported: + provider: str + supported_providers: frozenset[str] + + +@dataclass(frozen=True, slots=True) +class _TranslationGuardrailsUnsupported: + pass + + +_TranslationRejection = _TranslationProviderUnsupported | _TranslationGuardrailsUnsupported + + +def _translation_rejection( + custom_llm_provider: str, supported_providers: frozenset[str], litellm_metadata: Mapping[str, object] +) -> _TranslationRejection | None: + if custom_llm_provider not in supported_providers: + return _TranslationProviderUnsupported(provider=custom_llm_provider, supported_providers=supported_providers) + if translation_guardrails_apply({"litellm_metadata": dict(litellm_metadata)}): + return _TranslationGuardrailsUnsupported() + return None + + +def _translation_rejection_message(rejection: _TranslationRejection) -> str: + match rejection: + case _TranslationProviderUnsupported(provider=provider, supported_providers=supported_providers): + return ( + f"Realtime translation supports only the {', '.join(sorted(supported_providers))} providers, " + f"got {provider}" + ) + case _TranslationGuardrailsUnsupported(): + return TRANSLATION_GUARDRAILS_UNSUPPORTED_MESSAGE + case _: + assert_never(rejection) + + +def _translation_rejection_error_type(rejection: _TranslationRejection) -> str: + match rejection: + case _TranslationProviderUnsupported(): + return "invalid_request_error" + case _TranslationGuardrailsUnsupported(): + return "guardrail_error" + case _: + assert_never(rejection) + + +def _translation_rejection_error( + rejection: _TranslationRejection, model: str, custom_llm_provider: str +) -> BadRequestError: + return BadRequestError( + message=_translation_rejection_message(rejection), model=model, llm_provider=custom_llm_provider + ) + + +def _raise_if_http_translation_rejected(custom_llm_provider: str, model: str, kwargs: Mapping[str, object]) -> None: + rejection: Final = _translation_rejection( + custom_llm_provider, _HTTP_TRANSLATION_PROVIDERS, _translation_litellm_metadata(kwargs) + ) + if rejection is None: + return + raise _translation_rejection_error(rejection, model, custom_llm_provider) + + +async def _refuse_translation_session( + websocket: "WebSocket", + rejection: _TranslationRejection, + logging_obj: LiteLLMLogging, + model: str, + custom_llm_provider: str, +) -> None: + message: Final = _translation_rejection_message(rejection) + await websocket.send_text(realtime_error_event(message, error_type=_translation_rejection_error_type(rejection))) + await websocket.close(code=1008, reason=websocket_close_reason(message, fallback="Translation session refused")) + error: Final = _translation_rejection_error(rejection, model, custom_llm_provider) + await logging_obj.dispatch_failure_handlers( + error, "".join(traceback.format_exception(error)), prefer_async_handlers=True + ) def _get_realtime_http_provider_config( @@ -125,10 +254,6 @@ def _get_realtime_http_provider_config( Uses ProviderConfigManager so each provider keeps its credential-resolution and URL-construction logic in its own transformation class. """ - from litellm.llms.base_llm.realtime.http_transformation import ( - BaseRealtimeHTTPConfig, - ) - provider_config: BaseRealtimeHTTPConfig | None = None if custom_llm_provider in LlmProviders._member_map_.values(): provider_config = ProviderConfigManager.get_provider_realtime_http_config( @@ -163,6 +288,32 @@ async def _realtime_http_bearer_token( return bearer_token or "" +async def _get_realtime_http_extra_headers( + provider_config: BaseRealtimeHTTPConfig | None, + litellm_params: GenericLiteLLMParams, + resolved_api_key: str, + extra_headers: Mapping[str, object] | None, +) -> Mapping[str, object] | None: + if provider_config is None: + return extra_headers + return await asyncio.to_thread( + provider_config.get_extra_headers, + litellm_params=litellm_params, + api_key=resolved_api_key, + extra_headers=extra_headers, + ) + + +def _client_secret_session_body(req: RealtimeClientSecretRequest, model_name: str) -> Mapping[str, object] | None: + if req.session is not None: + return with_resolved_session_model( + _without_top_level_nulls(req.session.model_dump(exclude_unset=True)), model_name + ) + if req.model is not None: + return {"type": "realtime", "model": model_name} + return None + + @wrapper_client async def acreate_realtime_client_secret( model: str | None = None, @@ -176,31 +327,42 @@ async def acreate_realtime_client_secret( session=RealtimeSessionConfig.model_validate(session) if session else None, expires_after=RealtimeExpiresAfter.model_validate(expires_after) if expires_after else None, ) - model_name = (req.session.model if req.session is not None else None) or req.model or "gpt-4o-realtime-preview" + transcription_model: Final = ( + req.session.audio.input.transcription.model + if req.session is not None + and req.session.type == "transcription" + and req.session.audio is not None + and req.session.audio.input is not None + and req.session.audio.input.transcription is not None + else None + ) + requested_model_name: Final = ( + transcription_model + or (req.session.model if req.session is not None else None) + or req.model + or "gpt-4o-realtime-preview" + ) litellm_logging_obj: Final[LiteLLMLogging] = kwargs.get("litellm_logging_obj") litellm_params: Final = GenericLiteLLMParams(**kwargs) - ( - model_name, - custom_llm_provider, - dynamic_api_key, - dynamic_api_base, - ) = get_llm_provider( - model=model_name, + model_name, custom_llm_provider, dynamic_api_key, dynamic_api_base = get_llm_provider( + model=requested_model_name, custom_llm_provider=litellm_params.custom_llm_provider, api_base=litellm_params.api_base, api_key=litellm_params.api_key, ) - ( - provider_config, - resolved_api_base, - resolved_api_key, - ) = _get_realtime_http_provider_config( + provider_config, resolved_api_base, resolved_api_key = _get_realtime_http_provider_config( custom_llm_provider=custom_llm_provider, dynamic_api_base=dynamic_api_base, dynamic_api_key=dynamic_api_key, litellm_params=litellm_params, ) + resolved_extra_headers: Final = await _get_realtime_http_extra_headers( + provider_config=provider_config, + litellm_params=litellm_params, + resolved_api_key=resolved_api_key, + extra_headers=kwargs.get("extra_headers"), + ) litellm_logging_obj.update_from_kwargs( kwargs=kwargs, model=model_name, @@ -208,26 +370,124 @@ async def acreate_realtime_client_secret( litellm_params={"api_base": resolved_api_base}, custom_llm_provider=custom_llm_provider, ) - request_data: Final = req.model_dump(exclude_none=True, exclude={"model"}) - resolved_session: Final = _resolved_request_session(request_data, model_name) - if resolved_session is not None: - request_data["session"] = resolved_session + session_body: Final = _client_secret_session_body(req, model_name) return await base_llm_http_handler.async_realtime_client_secret_handler( api_base=resolved_api_base, api_key=await _realtime_http_bearer_token( custom_llm_provider, resolved_api_key, resolved_api_base, litellm_params ), - request_data=request_data, + request_data={ + **req.model_dump(exclude_none=True, exclude={"model", "session"}), + **({} if session_body is None else {"session": session_body}), + }, logging_obj=litellm_logging_obj, timeout=timeout or request_timeout, provider_config=provider_config, model=model_name, - extra_headers=kwargs.get("extra_headers"), + extra_headers=resolved_extra_headers, client=kwargs.get("client"), api_version=litellm_params.api_version, ) +@wrapper_client +async def acreate_realtime_translation_client_secret( + model: str | None = None, + session: Mapping[str, Any] | None = None, + expires_after: Mapping[str, Any] | None = None, + timeout: float | None = None, + **kwargs: object, # kwargs-ok: public API preserves provider-specific request options +) -> httpx.Response: + requested_model_name: Final = model or (session or {}).get("model") or "gpt-realtime-translate" + session_config: Final = RealtimeSessionConfig.model_validate( + { + **(session or {}), + "type": "translation", + "model": requested_model_name, + } + ) + req: Final = RealtimeClientSecretRequest( + model=requested_model_name, + session=session_config, + expires_after=RealtimeExpiresAfter(**expires_after) if expires_after else None, + ) + litellm_logging_obj: Final = kwargs.get("litellm_logging_obj") + if not isinstance(litellm_logging_obj, LiteLLMLogging): + raise TypeError("litellm_logging_obj must be a LiteLLM Logging instance") + litellm_params: Final = GenericLiteLLMParams.model_validate(kwargs) + + model_name, custom_llm_provider, dynamic_api_key, dynamic_api_base = get_llm_provider( + model=requested_model_name, + custom_llm_provider=litellm_params.custom_llm_provider, + api_base=litellm_params.api_base, + api_key=litellm_params.api_key, + ) + _raise_if_http_translation_rejected(custom_llm_provider, model_name, kwargs) + provider_config, resolved_api_base, resolved_api_key = _get_realtime_http_provider_config( + custom_llm_provider=custom_llm_provider, + dynamic_api_base=dynamic_api_base, + dynamic_api_key=dynamic_api_key, + litellm_params=litellm_params, + ) + resolved_extra_headers: Final = await _get_realtime_http_extra_headers( + provider_config=provider_config, + litellm_params=litellm_params, + resolved_api_key=resolved_api_key, + extra_headers=as_str_mapping(kwargs.get("extra_headers")), + ) + litellm_logging_obj.update_from_kwargs( + kwargs=kwargs, + model=model_name, + optional_params={ + "expires_after": expires_after, + "session": session, + }, + litellm_params={"api_base": resolved_api_base}, + custom_llm_provider=custom_llm_provider, + ) + translation_session: Final = with_resolved_session_model( + _without_top_level_nulls(session_config.model_dump(exclude_unset=True)), model_name + ) + return await base_llm_http_handler.async_realtime_translation_client_secret_handler( + api_base=resolved_api_base, + api_key=await _realtime_http_bearer_token( + custom_llm_provider, resolved_api_key, resolved_api_base, litellm_params + ), + request_data={ + **req.model_dump(exclude_none=True, exclude={"model", "session"}), + "session": {key: value for key, value in translation_session.items() if key != "type"}, + }, + logging_obj=litellm_logging_obj, + timeout=timeout or request_timeout, + provider_config=provider_config, + model=model_name, + extra_headers=resolved_extra_headers, + client=client if isinstance(client := kwargs.get("client"), (HTTPHandler, AsyncHTTPHandler)) else None, + api_version=litellm_params.api_version, + ) + + +def _with_upstream_transcription_model(request_data: Mapping[str, object], model_name: str) -> dict[str, object]: + flat: Final = as_str_mapping(request_data.get("input_audio_transcription")) + audio: Final = as_str_mapping(request_data.get("audio")) or {} + audio_input: Final = as_str_mapping(audio.get("input")) or {} + nested: Final = as_str_mapping(audio_input.get("transcription")) + return { + **request_data, + **({} if flat is None else {"input_audio_transcription": {**flat, "model": model_name}}), + **( + {} + if nested is None + else {"audio": {**audio, "input": {**audio_input, "transcription": {**nested, "model": model_name}}}} + ), + } + + +def _deployment_base_model(kwargs: Mapping[str, object], custom_llm_provider: str) -> str | None: + base_model: Final = get_base_model_from_metadata(model_call_details={"litellm_params": kwargs}) + return None if base_model is None else base_model.removeprefix(f"{custom_llm_provider}/") + + @wrapper_client async def acreate_realtime_transcription_session( model: str | None = None, @@ -273,6 +533,12 @@ async def acreate_realtime_transcription_session( dynamic_api_key=dynamic_api_key, litellm_params=litellm_params, ) + resolved_extra_headers: Final = await _get_realtime_http_extra_headers( + provider_config=provider_config, + litellm_params=litellm_params, + resolved_api_key=resolved_api_key, + extra_headers=kwargs.get("extra_headers"), + ) litellm_logging_obj.update_from_kwargs( kwargs=kwargs, model=model_name, @@ -280,13 +546,11 @@ async def acreate_realtime_transcription_session( litellm_params={"api_base": resolved_api_base}, custom_llm_provider=custom_llm_provider, ) - request_data: Final = req.model_dump(exclude_none=True, exclude={"model"}) - # Ensure the upstream body's input_audio_transcription.model matches the - # authorized routing model. This prevents a caller from supplying an allowed - # top-level model for auth while sneaking a different model into the nested - # transcription config that gets forwarded to the provider. - if isinstance(request_data.get("input_audio_transcription"), dict): - request_data["input_audio_transcription"]["model"] = model_name + # The upstream transcription model must match the authorized routing model, so a + # caller cannot pass auth with an allowed top-level model and forward a different one. + request_data: Final = _with_upstream_transcription_model( + _without_top_level_nulls(req.model_dump(exclude_unset=True, exclude={"model"})), model_name + ) return await base_llm_http_handler.async_realtime_transcription_session_handler( api_base=resolved_api_base, api_key=await _realtime_http_bearer_token( @@ -297,7 +561,7 @@ async def acreate_realtime_transcription_session( timeout=timeout or request_timeout, provider_config=provider_config, model=model_name, - extra_headers=kwargs.get("extra_headers"), + extra_headers=resolved_extra_headers, client=kwargs.get("client"), api_version=litellm_params.api_version, ) @@ -334,7 +598,7 @@ async def arealtime_calls( litellm_params=litellm_params, ) if session is not None: - session = _with_resolved_session_model(session, model_name) + session = with_resolved_session_model(session, model_name) litellm_logging_obj.update_from_kwargs( kwargs=kwargs, model=model_name, @@ -357,6 +621,68 @@ async def arealtime_calls( ) +@wrapper_client +async def arealtime_translation_calls( + openai_ephemeral_key: str, + sdp_body: bytes, + model: str | None = None, + session: Mapping[str, Any] | None = None, + timeout: float | None = None, + **kwargs: object, # kwargs-ok: public API preserves provider-specific request options +) -> httpx.Response: + requested_model_name: Final = model or "gpt-realtime-translate" + litellm_logging_obj: Final = kwargs.get("litellm_logging_obj") + if not isinstance(litellm_logging_obj, LiteLLMLogging): + raise TypeError("litellm_logging_obj must be a LiteLLM Logging instance") + litellm_params: Final = GenericLiteLLMParams.model_validate(kwargs) + + model_name, custom_llm_provider, dynamic_api_key, dynamic_api_base = get_llm_provider( + model=requested_model_name, + custom_llm_provider=litellm_params.custom_llm_provider, + api_base=litellm_params.api_base, + api_key=litellm_params.api_key, + ) + _raise_if_http_translation_rejected(custom_llm_provider, model_name, kwargs) + provider_config, resolved_api_base, _ = _get_realtime_http_provider_config( + custom_llm_provider=custom_llm_provider, + dynamic_api_base=dynamic_api_base, + dynamic_api_key=dynamic_api_key, + litellm_params=litellm_params, + ) + session_config: Final = with_resolved_session_model( + { + **(session or {}), + "type": "translation", + "model": model_name, + }, + model_name, + ) + litellm_logging_obj.update_from_kwargs( + kwargs=kwargs, + model=model_name, + optional_params={ + "realtime_translation_calls": True, + "session": session_config, + }, + litellm_params={"api_base": resolved_api_base}, + custom_llm_provider=custom_llm_provider, + ) + return await base_llm_http_handler.async_realtime_calls_handler( + api_base=resolved_api_base, + openai_ephemeral_key=openai_ephemeral_key, + sdp_body=sdp_body, + logging_obj=litellm_logging_obj, + timeout=timeout or request_timeout, + provider_config=provider_config, + model=model_name, + session_config=session_config, + extra_headers=as_str_mapping(kwargs.get("extra_headers")), + client=client if isinstance(client := kwargs.get("client"), (HTTPHandler, AsyncHTTPHandler)) else None, + api_version=litellm_params.api_version, + translation=True, + ) + + async def vertex_access_token_resolver( credentials: VERTEX_CREDENTIALS_TYPES | None, project_id: str | None, @@ -486,6 +812,7 @@ async def _arealtime( timeout: float | None = None, query_params: RealtimeQueryParams | None = None, live_session_start: Mapping[str, object] | None = None, + realtime_mode: str = "realtime", **kwargs, ) -> None: """ @@ -530,7 +857,24 @@ async def _arealtime( custom_llm_provider=_custom_llm_provider, ) - deployment_params: Final = _DEPLOYMENT_PARAMS.validate_python(kwargs) + session_litellm_metadata: Final = ( + dict(_translation_litellm_metadata(kwargs)) + if realtime_mode == "translation" + else _build_litellm_metadata(kwargs) + ) + translation_rejection: Final = ( + _translation_rejection(_custom_llm_provider, _WEBSOCKET_TRANSLATION_PROVIDERS, session_litellm_metadata) + if realtime_mode == "translation" + else None + ) + if translation_rejection is not None: + await _refuse_translation_session( + websocket, translation_rejection, litellm_logging_obj, model, _custom_llm_provider + ) + litellm_logging_obj.model_call_details[REALTIME_SESSION_FAILURE_LOGGED_KEY] = True + return + + deployment_params: Final = _OBJECT_MAPPING.validate_python(kwargs) if live_session_start is not None: await _alive_session( model=model, @@ -540,7 +884,7 @@ async def _arealtime( session_start=live_session_start, api_base=dynamic_api_base or litellm_params.api_base, api_key=dynamic_api_key, - litellm_metadata=_build_litellm_metadata(kwargs), + litellm_metadata=session_litellm_metadata, litellm_params=deployment_params, ) return @@ -566,7 +910,7 @@ async def _arealtime( timeout=timeout, headers=headers, user_api_key_dict=kwargs.get("user_api_key_dict"), - litellm_metadata=_build_litellm_metadata(kwargs), + litellm_metadata=session_litellm_metadata, query_params=query_params, ) elif _custom_llm_provider in AZURE_OPENAI_AUDIO_PROVIDERS: @@ -581,9 +925,6 @@ async def _arealtime( or litellm_params.get("realtime_protocol") or os.environ.get("LITELLM_AZURE_REALTIME_PROTOCOL") ) - realtime_protocol: Final = azure_realtime_protocol_for_client( - configured_realtime_protocol, query_params=query_params, websocket=websocket - ) resolved_azure_ad_token: Final = ( None if api_key @@ -592,6 +933,14 @@ async def _arealtime( GenericLiteLLMParams(**kwargs, azure_ad_token=azure_ad_token), ) ) + realtime_protocol: Final = azure_realtime_protocol_for_client( + configured_realtime_protocol, + model=model, + base_model=_deployment_base_model(kwargs, _custom_llm_provider), + query_params=query_params, + realtime_mode=realtime_mode, + websocket=websocket, + ) await azure_realtime.async_realtime( model=model, websocket=websocket, @@ -602,10 +951,13 @@ async def _arealtime( client=None, timeout=timeout, logging_obj=litellm_logging_obj, - realtime_protocol=realtime_protocol, + realtime_protocol=realtime_protocol.name, query_params=query_params, + realtime_mode=realtime_mode, user_api_key_dict=kwargs.get("user_api_key_dict"), - litellm_metadata=_build_litellm_metadata(kwargs), + litellm_metadata=session_litellm_metadata, + bridges_beta_client_to_ga=realtime_protocol.bridges_beta_client_to_ga, + drop_params=drop_params, ) elif _custom_llm_provider == "openai": api_base = dynamic_api_base or litellm_params.api_base or litellm.api_base or "https://api.openai.com/" @@ -622,8 +974,10 @@ async def _arealtime( client=None, timeout=timeout, query_params=query_params, + realtime_mode=realtime_mode, user_api_key_dict=kwargs.get("user_api_key_dict"), - litellm_metadata=_build_litellm_metadata(kwargs), + litellm_metadata=session_litellm_metadata, + drop_params=drop_params, ) elif _custom_llm_provider == "bedrock": # Extract AWS parameters from kwargs @@ -678,7 +1032,7 @@ async def _arealtime( timeout=timeout, query_params=query_params, user_api_key_dict=kwargs.get("user_api_key_dict"), - litellm_metadata=_build_litellm_metadata(kwargs), + litellm_metadata=session_litellm_metadata, ) elif _custom_llm_provider == "vertex_ai": vertex_credentials: Final = ( @@ -738,7 +1092,7 @@ async def _arealtime( timeout=timeout, headers=headers, user_api_key_dict=kwargs.get("user_api_key_dict"), - litellm_metadata=_build_litellm_metadata(kwargs), + litellm_metadata=session_litellm_metadata, query_params=query_params, ) else: diff --git a/litellm/repositories/accounting_delivery_repository.py b/litellm/repositories/accounting_delivery_repository.py new file mode 100644 index 00000000000..7dd92aecb2d --- /dev/null +++ b/litellm/repositories/accounting_delivery_repository.py @@ -0,0 +1,193 @@ +from collections.abc import Awaitable, Callable, Mapping, Sequence +from dataclasses import dataclass +from datetime import timedelta +from itertools import chain +from types import TracebackType +from typing import TYPE_CHECKING, Final, Literal, Protocol + +from pydantic import BaseModel, ConfigDict, JsonValue, TypeAdapter + +from litellm.repositories.prisma_protocols import TableActions + +if TYPE_CHECKING: + from litellm.proxy.db.db_spend_update_writer import SpendBatchManager + + +class LedgerTransaction(Protocol): + @property + def litellm_dailyguardrailusageunits(self) -> TableActions[object]: ... + + async def query_raw(self, query: str, *args: object) -> Sequence[Mapping[str, object]]: ... + + async def execute_raw(self, query: str, *args: object) -> int: ... + + def batch_(self) -> "SpendBatchManager": ... + + +class _TransactionManager(Protocol): + async def __aenter__(self) -> LedgerTransaction: ... + + async def __aexit__( + self, exc_type: type[BaseException] | None, exc: BaseException | None, exc_tb: TracebackType | None + ) -> None: ... + + +class LedgerDatabase(Protocol): + def tx(self, *, timeout: timedelta) -> _TransactionManager: ... + + +class _Delivery(BaseModel): + model_config = ConfigDict(frozen=True) + + delivery_id: str + attempts: int + accounting_payload: JsonValue + + +@dataclass(frozen=True, slots=True) +class DeliveryProjection: + row: Mapping[str, object] + + +@dataclass(frozen=True, slots=True) +class DeliveryBatchResult: + applied: int = 0 + failed: int = 0 + parked: tuple[str, ...] = () + error: str | None = None + + +class DeliveryMetrics(BaseModel): + model_config = ConfigDict(frozen=True) + + pending_count: int + parked_count: int + oldest_pending_seconds: float + batch_count: int + table_bytes: int + + +_DELIVERIES: Final = TypeAdapter(tuple[_Delivery, ...]) +_PAYLOAD: Final = TypeAdapter(dict[str, object]) +_TIMEOUT: Final = timedelta(seconds=60) +_CLAIM: Final = """SELECT delivery_id, attempts, accounting_payload FROM "LiteLLM_SpendLogDelivery" +WHERE state = 'pending' AND next_attempt_at <= CURRENT_TIMESTAMP + AND (attempts > 0) = $2::boolean +ORDER BY next_attempt_at, delivery_id LIMIT $1::integer FOR UPDATE SKIP LOCKED""" +_APPLIED: Final = """UPDATE "LiteLLM_SpendLogDelivery" +SET state = 'applied', applied_at = CURRENT_TIMESTAMP, last_error = NULL +WHERE delivery_id = ANY($1::text[]) AND state = 'pending' """ +_FAILED: Final = """UPDATE "LiteLLM_SpendLogDelivery" +SET attempts = attempts + 1, last_error = $3, + next_attempt_at = CURRENT_TIMESTAMP + make_interval(secs => LEAST(300, power(2, LEAST(attempts, 8)))::integer), + state = $4::"AccountingDeliveryState" +WHERE delivery_id = $1 AND state = 'pending' AND attempts = $2::integer +RETURNING delivery_id, attempts, accounting_payload""" + + +def _is_permanent_failure(error: Exception) -> bool: + """A delivery whose own data failed fails the same way on every retry, while any other error is the database's + and clears once it recovers.""" + from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler + + if PrismaDBExceptionHandler.is_database_service_unavailable_error(error): + return False + return isinstance(error, (ValueError, TypeError, KeyError)) or PrismaDBExceptionHandler.is_rejected_row_error(error) + + +class AccountingDeliveryRepository: + def __init__(self, database: LedgerDatabase) -> None: + self._database = database + + async def metrics(self) -> DeliveryMetrics: + async with self._database.tx(timeout=_TIMEOUT) as transaction: + rows: Final = await transaction.query_raw( + "SELECT COUNT(*) FILTER (WHERE state = 'pending') AS pending_count, " + "COUNT(*) FILTER (WHERE state = 'parked') AS parked_count, " + "COALESCE(EXTRACT(EPOCH FROM CURRENT_TIMESTAMP - MIN(created_at) FILTER (WHERE state = 'pending')), 0) " + "AS oldest_pending_seconds, COUNT(*) FILTER (WHERE is_batch) AS batch_count, " + "pg_total_relation_size('\"LiteLLM_SpendLogDelivery\"') AS table_bytes " + 'FROM "LiteLLM_SpendLogDelivery"' + ) + return DeliveryMetrics.model_validate(rows[0]) + + async def cleanup_applied(self, *, retention_days: int = 1, batch_size: int = 1000) -> int: + if retention_days < 1 or batch_size < 1: + raise ValueError("Delivery retention and cleanup batch size must be positive") + async with self._database.tx(timeout=_TIMEOUT) as transaction: + return await transaction.execute_raw( + 'DELETE FROM "LiteLLM_SpendLogDelivery" WHERE delivery_id IN (' + 'SELECT delivery_id FROM "LiteLLM_SpendLogDelivery" ' + "WHERE state = 'applied' AND NOT is_batch AND applied_at < CURRENT_TIMESTAMP - make_interval(days => $1::integer) " + "ORDER BY applied_at, delivery_id LIMIT $2::integer FOR UPDATE SKIP LOCKED)", + retention_days, + batch_size, + ) + + async def apply_pending( + self, + apply: Callable[[LedgerTransaction, tuple[DeliveryProjection, ...]], Awaitable[None]], + *, + batch_size: int = 100, + max_attempts: int = 5, + retry_only: bool | None = None, + ) -> DeliveryBatchResult: + if batch_size < 1 or max_attempts < 1: + raise ValueError("Delivery batch size and maximum attempts must be positive") + claimed: tuple[_Delivery, ...] = () # rebind-ok: preserve claims for retry accounting after rollback + try: + async with self._database.tx(timeout=_TIMEOUT) as transaction: + retries: Final = ( + _DELIVERIES.validate_python(await transaction.query_raw(_CLAIM, 1, True)) + if retry_only is not False + else () + ) + claimed = retries or ( # rebind-ok: retain claimed identities after rollback + _DELIVERIES.validate_python(await transaction.query_raw(_CLAIM, batch_size, False)) + if retry_only is not True + else () + ) + if not claimed: + return DeliveryBatchResult() + await apply( + transaction, + tuple( + DeliveryProjection(_PAYLOAD.validate_python(delivery.accounting_payload)) + for delivery in claimed + ), + ) + await transaction.execute_raw(_APPLIED, tuple(delivery.delivery_id for delivery in claimed)) + return DeliveryBatchResult(applied=len(claimed)) + except Exception as error: # noqa: BLE001 # roll back all destinations before recording a retry + if not claimed: + raise + return await self._record_failure(claimed, error, max_attempts) + + async def _record_failure( + self, claimed: tuple[_Delivery, ...], error: Exception, max_attempts: int + ) -> DeliveryBatchResult: + parks: Final = len(claimed) == 1 and _is_permanent_failure(error) + async with self._database.tx(timeout=_TIMEOUT) as transaction: + updates: Final = tuple( + [ + await self._record_row_failure( + transaction, + delivery, + type(error).__name__, + "parked" if parks and delivery.attempts + 1 >= max_attempts else "pending", + ) + for delivery in claimed + ] + ) + return DeliveryBatchResult( + failed=len(claimed), parked=tuple(chain.from_iterable(updates)), error=type(error).__name__ + ) + + @staticmethod + async def _record_row_failure( + transaction: LedgerTransaction, delivery: _Delivery, error: str, state: Literal["pending", "parked"] + ) -> tuple[str, ...]: + updated: Final = _DELIVERIES.validate_python( + await transaction.query_raw(_FAILED, delivery.delivery_id, delivery.attempts, error, state) + ) + return tuple(row.delivery_id for row in updated) if state == "parked" else () diff --git a/litellm/repositories/config_repository.py b/litellm/repositories/config_repository.py index 8768d79b0dd..36c6ab7f711 100644 --- a/litellm/repositories/config_repository.py +++ b/litellm/repositories/config_repository.py @@ -4,6 +4,7 @@ from __future__ import annotations import json from collections.abc import Mapping, Sequence +from datetime import datetime from typing import TYPE_CHECKING, Final, Protocol, cast if TYPE_CHECKING: @@ -35,6 +36,8 @@ class _ConfigTable(Protocol): async def delete(self, *, where: Mapping[str, str]) -> _ConfigRow | None: ... + async def delete_many(self, *, where: Mapping[str, object]) -> int: ... + class _ConfigDatabase(Protocol): async def query_raw(self, query: str, *args: object) -> object: ... @@ -130,3 +133,9 @@ class ConfigRepository: param_value = _decoded_json(param_value) result[record.param_name] = param_value return result + + async def delete_params_older_than(self, prefix: str, before: datetime) -> int: + """Expire operational config records using the timestamp written by revision claims.""" + return await self._config_table.delete_many( + where={"param_name": {"startswith": prefix}, "last_run_at": {"lt": before}} + ) diff --git a/litellm/repositories/plugin_publication.py b/litellm/repositories/plugin_publication.py new file mode 100644 index 00000000000..f5fab458c6b --- /dev/null +++ b/litellm/repositories/plugin_publication.py @@ -0,0 +1,175 @@ +import hashlib +import json +from datetime import datetime, timezone +from typing import TYPE_CHECKING, Final, Protocol + +from pydantic import TypeAdapter +from semver import Version + +from litellm.models.plugin_upload import ( + PluginPublication, + PluginPublicationBase, + PluginPublicationError, + PublishedPlugin, +) +from litellm.repositories.prisma_protocols import TableActions + +if TYPE_CHECKING: + from prisma.models import ( + LiteLLM_ClaudeCodePluginTable, + LiteLLM_ClaudeCodePluginUpload, + LiteLLM_ClaudeCodePluginVersion, + ) + +_MANIFEST: Final = TypeAdapter(dict[str, object]) +_SOURCE: Final = TypeAdapter(dict[str, str]) + + +class PluginPublicationTransaction(Protocol): + @property + def litellm_claudecodeplugintable(self) -> TableActions["LiteLLM_ClaudeCodePluginTable"]: ... + + @property + def litellm_claudecodepluginupload(self) -> TableActions["LiteLLM_ClaudeCodePluginUpload"]: ... + + @property + def litellm_claudecodepluginversion(self) -> TableActions["LiteLLM_ClaudeCodePluginVersion"]: ... + + async def query_raw(self, query: str, *args: object) -> object: ... + + +def resolve_plugin_version( + requested: str | None, current: str | None = None, *, updating: bool = False +) -> str | PluginPublicationError: + try: + previous: Final = Version.parse(current) if current is not None else None + except ValueError: + return _legacy_version(requested) + if updating and previous is None: + return _legacy_version(requested) + try: + candidate: Final = Version.parse(requested) if requested is not None else None + except ValueError: + return PluginPublicationError("invalid_version", "Version must be a valid semantic version, for example 1.0.1") + if candidate is None: + return str(previous.bump_patch()) if previous is not None else "1.0.0" + if previous is not None and candidate.compare(previous) <= 0: + return PluginPublicationError("invalid_version", f"Version must be strictly higher than {current}") + return str(candidate) + + +def _legacy_version(requested: str | None) -> str | PluginPublicationError: + if requested is None: + return PluginPublicationError( + "conflict", + "The published version is missing or is not SemVer. Supply an explicit semantic version to update it", + ) + return resolve_plugin_version(requested) + + +def verified_archive(content: bytes | None, manifest_json: str | None) -> bytes | None: + if content is None: + return None + manifest: Final = _MANIFEST.validate_json(manifest_json or "{}") + source: Final = _SOURCE.validate_python(manifest.get("source", {})) + if source.get("source") != "archive" or source.get("sha256", "").lower() != hashlib.sha256(content).hexdigest(): + return None + return content + + +async def _snapshot( + tx: PluginPublicationTransaction, + plugin: "LiteLLM_ClaudeCodePluginTable", + content: bytes | None, + published_by: str | None, +) -> None: + from prisma import Base64 + + archive: Final = verified_archive(content, plugin.manifest_json) + await tx.litellm_claudecodepluginversion.create( + data={ + "plugin_id": plugin.id, + "version": plugin.version, + "description": plugin.description, + "manifest_json": plugin.manifest_json, + "published_at": plugin.updated_at, + "published_by": published_by, + "content": Base64.encode(archive) if archive is not None else None, + "archive_available": archive is not None, + } + ) + + +async def publish_plugin( + tx: PluginPublicationTransaction, + publication: PluginPublication, + expected: PluginPublicationBase | None = None, +) -> PublishedPlugin | PluginPublicationError: + from prisma import Base64 + + await tx.query_raw('SELECT id FROM "LiteLLM_ClaudeCodePluginTable" WHERE name = $1 FOR UPDATE', publication.name) + current: Final = await tx.litellm_claudecodeplugintable.find_unique(where={"name": publication.name}) + if current is not None and expected is None: + return PluginPublicationError("conflict", f"A skill named '{publication.name}' already exists") + if expected is not None and current is None: + return PluginPublicationError("not_found", f"Plugin '{publication.name}' not found") + if current is not None and ( + expected is not None and (current.id != expected.id or current.updated_at != expected.updated_at) + ): + return PluginPublicationError("conflict", "The published skill changed. Reload it before publishing an update") + version: Final = resolve_plugin_version( + publication.version, current.version if current is not None else None, updating=expected is not None + ) + if isinstance(version, PluginPublicationError): + return version + manifest_json: Final = json.dumps({**publication.manifest, "version": version}) + if publication.content is not None and verified_archive(publication.content, manifest_json) is None: + return PluginPublicationError("conflict", "Uploaded archive does not match its published source digest") + timestamp: Final = datetime.now(timezone.utc) + data: Final = { + "version": version, + "description": publication.description, + "manifest_json": manifest_json, + "files_json": "{}", + "updated_at": timestamp, + } + if current is None: + created: Final = await tx.litellm_claudecodeplugintable.create( + data={**data, "name": publication.name, "created_by": publication.created_by} + ) + if publication.content is not None: + await tx.litellm_claudecodepluginupload.create( + data={"plugin_name": publication.name, "content": Base64.encode(publication.content)} + ) + await _snapshot(tx, created, publication.content, publication.created_by) + return PublishedPlugin(created.id, created.name, version, created.enabled, created.updated_at or timestamp) + previous_archive: Final = await tx.litellm_claudecodepluginupload.find_unique(where={"plugin_name": current.name}) + previous_content: Final = ( + verified_archive(previous_archive.content.decode(), current.manifest_json) + if previous_archive is not None + else None + ) + history_count: Final = await tx.litellm_claudecodepluginversion.count(where={"plugin_id": current.id}, take=1) + if history_count == 0: + await _snapshot(tx, current, previous_content, None) + unchanged_content: Final = ( + previous_content + if _MANIFEST.validate_json(current.manifest_json or "{}").get("source") == publication.manifest.get("source") + else None + ) + content: Final = publication.content if publication.content is not None else unchanged_content + updated: Final = await tx.litellm_claudecodeplugintable.update(where={"id": current.id}, data=data) + if updated is None: + raise RuntimeError("Locked plugin disappeared during publication") + if content is None: + await tx.litellm_claudecodepluginupload.delete_many(where={"plugin_name": current.name}) + else: + await tx.litellm_claudecodepluginupload.upsert( + where={"plugin_name": current.name}, + data={ + "create": {"plugin_name": current.name, "content": Base64.encode(content)}, + "update": {"content": Base64.encode(content)}, + }, + ) + await _snapshot(tx, updated, content, publication.created_by) + return PublishedPlugin(updated.id, updated.name, version, updated.enabled, updated.updated_at or timestamp) diff --git a/litellm/repositories/plugin_upload_repository.py b/litellm/repositories/plugin_upload_repository.py new file mode 100644 index 00000000000..99e226e442b --- /dev/null +++ b/litellm/repositories/plugin_upload_repository.py @@ -0,0 +1,290 @@ +from collections.abc import AsyncIterator, Mapping, Sequence +from contextlib import AbstractAsyncContextManager +from dataclasses import dataclass +from types import MappingProxyType +from typing import ( + TYPE_CHECKING, + Final, + Protocol, + cast, # noqa: TID251 # Prisma dynamically exposes its typed table actions +) + +from pydantic import TypeAdapter, ValidationError + +from litellm.models.plugin_upload import ( + PluginArchiveMetadata, + PluginDownloader, + PluginDownloadEvent, + PluginDownloadResult, + PluginDownloadsResponse, + PluginPublication, + PluginPublicationBase, + PluginPublicationError, + PluginSnapshot, + PluginUpload, + PluginVersion, + PublishedPlugin, + has_agent_skill_metadata, +) +from litellm.repositories.plugin_publication import PluginPublicationTransaction, publish_plugin, verified_archive +from litellm.repositories.prisma_protocols import TableActions +from litellm.repositories.table_repositories import ClaudeCodePluginRepository + +if TYPE_CHECKING: + from prisma import models as prisma_models + + from litellm.proxy.db.create_views import SupportsExecuteRaw + from litellm.proxy.utils import PrismaClient + +_MANIFEST: Final = TypeAdapter(dict[str, object]) +_SOURCE: Final = TypeAdapter(dict[str, str]) +PAGE_SIZE: Final = 100 +_INCREMENT_ANONYMOUS_DOWNLOADS: Final = """ +UPDATE "LiteLLM_ClaudeCodePluginTable" +SET "anonymous_download_count" = "anonymous_download_count" + 1 +WHERE "id" = $1 +""" +_DOWNLOAD_COUNTS_QUERY: Final = """ +SELECT p.id, p.anonymous_download_count + COUNT(d.id) AS download_count +FROM "LiteLLM_ClaudeCodePluginTable" p +LEFT JOIN "LiteLLM_ClaudeCodePluginDownload" d ON d.plugin_id = p.id +WHERE p.id = ANY($1::text[]) +GROUP BY p.id +""" + + +@dataclass(frozen=True, slots=True) +class _DownloadCount: + id: str + download_count: int + + +_DOWNLOAD_COUNTS: Final = TypeAdapter(tuple[_DownloadCount, ...]) +_VERSIONS: Final = TypeAdapter(tuple[PluginVersion, ...]) +_VERSION_QUERY: Final = """ + SELECT v.id, v.version, v.description, COALESCE(v.manifest_json, '{}')::jsonb AS manifest, + v.published_at, v.published_by, v.archive_available + FROM "LiteLLM_ClaudeCodePluginVersion" v JOIN "LiteLLM_ClaudeCodePluginTable" p ON p.id = v.plugin_id + WHERE p.id = $1 AND p.enabled = $2 +""" + + +class _PublicationDatabase(PluginPublicationTransaction, Protocol): + def tx(self) -> AbstractAsyncContextManager[PluginPublicationTransaction]: ... + + +class PluginUploadRepository: + def __init__(self, prisma_client: "PrismaClient") -> None: + self._db = cast( # cast-ok: the generated Prisma transaction delegate is untyped at this boundary + _PublicationDatabase, prisma_client.writer_db + ) + self._writer = cast( # cast-ok: PrismaWrapper dynamically delegates raw statements to its generated client + "SupportsExecuteRaw", prisma_client.writer_db + ) + self._plugins = ClaudeCodePluginRepository(prisma_client, use_writer=True).table + self._archives = cast( # cast-ok: Prisma exposes generated table actions through an untyped delegate + TableActions["prisma_models.LiteLLM_ClaudeCodePluginUpload"], + prisma_client.writer_db.litellm_claudecodepluginupload, + ) + self._downloads = cast( # cast-ok: Prisma exposes generated table actions through an untyped delegate + TableActions["prisma_models.LiteLLM_ClaudeCodePluginDownload"], + prisma_client.writer_db.litellm_claudecodeplugindownload, + ) + + async def create(self, upload: PluginUpload) -> str | None: + result: Final = await self.publish( + PluginPublication( + name=upload.name, + version=upload.version, + description=upload.description, + manifest=upload.manifest, + content=upload.content, + created_by=upload.created_by, + ) + ) + return result.id if isinstance(result, PublishedPlugin) else None + + async def publish( + self, publication: PluginPublication, expected: PluginPublicationBase | None = None + ) -> PublishedPlugin | PluginPublicationError: + from prisma.errors import UniqueViolationError + + try: + async with self._db.tx() as tx: + return await publish_plugin(tx, publication, expected) + except UniqueViolationError: + return PluginPublicationError("conflict", "A skill with this name or version already exists") + + async def versions(self, metadata: PluginArchiveMetadata, limit: int, offset: int) -> tuple[PluginVersion, ...]: + rows: Final = await self._db.query_raw( + _VERSION_QUERY + " ORDER BY v.published_at DESC NULLS LAST, v.id DESC LIMIT $3 OFFSET $4", + metadata.id, + metadata.enabled, + limit, + offset, + ) + return _VERSIONS.validate_python(rows) + + async def version(self, metadata: PluginArchiveMetadata, version_id: str) -> PluginVersion | None: + rows: Final = await self._db.query_raw( + _VERSION_QUERY + " AND v.id = $3", + metadata.id, + metadata.enabled, + version_id, + ) + versions: Final = _VERSIONS.validate_python(rows) + return versions[0] if versions else None + + async def version_content(self, metadata: PluginArchiveMetadata, version_id: str) -> bytes | None: + version: Final = await self._db.litellm_claudecodepluginversion.find_first( + where={ + "id": version_id, + "plugin_id": metadata.id, + "plugin": { + "is": { + "enabled": metadata.enabled, + } + }, + } + ) + if version is None or version.content is None: + return None + return verified_archive(version.content.decode(), version.manifest_json) + + async def get_plugin(self, name: str) -> PluginSnapshot | None: + row: Final = await self._plugins.find_unique(where={"name": name}) + if row is None: + return None + return PluginSnapshot( + id=row.id, + name=row.name, + version=row.version, + description=row.description, + manifest=MappingProxyType(_MANIFEST.validate_json(row.manifest_json or "{}")), + enabled=row.enabled, + created_at=row.created_at, + updated_at=row.updated_at, + created_by=row.created_by, + ) + + async def get_metadata(self, name: str) -> PluginArchiveMetadata | None: + plugin: Final = await self._plugins.find_unique(where={"name": name}) + if plugin is None: + return None + return _archive_metadata(plugin) + + async def public_metadata(self) -> AsyncIterator[PluginArchiveMetadata]: + after: str | None = None # rebind-ok: bounded keyset traversal advances after each raw page + while True: + plugins: Sequence[prisma_models.LiteLLM_ClaudeCodePluginTable] = await self._plugins.find_many( + where={"enabled": True} if after is None else {"enabled": True, "name": {"gt": after}}, + take=PAGE_SIZE, + order={"name": "asc"}, + ) + if not plugins: + return + for plugin in plugins: + try: + metadata: PluginArchiveMetadata = _archive_metadata(plugin) + except ValidationError: + continue + yield metadata + if len(plugins) < PAGE_SIZE: + return + after = plugins[-1].name + + async def get_content(self, metadata: PluginArchiveMetadata) -> bytes | None: + archive: Final = await self._archives.find_first( + where={ + "plugin_name": metadata.name, + "plugin": { + "is": { + "id": metadata.id, + "manifest_json": metadata.manifest_json, + "enabled": metadata.enabled, + } + }, + } + ) + return None if archive is None else archive.content.decode() + + async def record_download( + self, metadata: PluginArchiveMetadata, digest: str, downloader: PluginDownloader + ) -> PluginDownloadResult: + from prisma.errors import ForeignKeyViolationError + + if metadata.id is None: + return PluginDownloadResult.SKILL_NOT_FOUND + if not downloader.authenticated: + # A counter bounds anonymous storage; raw SQL preserves Prisma's @updatedAt metadata. + affected: Final = await self._writer.execute_raw(_INCREMENT_ANONYMOUS_DOWNLOADS, metadata.id) + return PluginDownloadResult.RECORDED if affected == 1 else PluginDownloadResult.SKILL_NOT_FOUND + try: + await self._downloads.create( + data={ + "plugin_id": metadata.id, + "version": metadata.version, + "digest": digest, + "authenticated": downloader.authenticated, + "user_id": downloader.user_id, + "user_email": downloader.user_email, + "key_alias": downloader.key_alias, + "team_id": downloader.team_id, + "team_alias": downloader.team_alias, + } + ) + except ForeignKeyViolationError: + return PluginDownloadResult.SKILL_NOT_FOUND + return PluginDownloadResult.RECORDED + + async def downloads(self, name: str, limit: int, cursor: int | None) -> PluginDownloadsResponse | None: + plugin: Final = await self._plugins.find_unique(where={"name": name}) + if plugin is None: + return None + total: Final = await self._downloads.count(where={"plugin_id": plugin.id}) + rows: Final = await self._downloads.find_many( + where={"plugin_id": plugin.id, **({"id": {"lt": cursor}} if cursor is not None else {})}, + order={"id": "desc"}, + take=limit + 1, + ) + return PluginDownloadsResponse( + total_downloads=total + plugin.anonymous_download_count, + anonymous_downloads=plugin.anonymous_download_count, + downloads=tuple( + PluginDownloadEvent( + id=str(row.id), + downloaded_at=row.downloaded_at, + version=row.version, + digest=row.digest, + authenticated=row.authenticated, + user_id=row.user_id, + user_email=row.user_email, + key_alias=row.key_alias, + team_id=row.team_id, + team_alias=row.team_alias, + ) + for row in rows[:limit] + ), + next_cursor=str(rows[limit - 1].id) if len(rows) > limit else None, + ) + + async def download_counts(self, plugin_ids: tuple[str, ...]) -> Mapping[str, int]: + if not plugin_ids: + return MappingProxyType({}) + rows: Final = _DOWNLOAD_COUNTS.validate_python(await self._db.query_raw(_DOWNLOAD_COUNTS_QUERY, plugin_ids)) + return MappingProxyType({row.id: row.download_count for row in rows}) + + +def _archive_metadata(plugin: "prisma_models.LiteLLM_ClaudeCodePluginTable") -> PluginArchiveMetadata: + manifest: Final = _MANIFEST.validate_json(plugin.manifest_json or "{}") + return PluginArchiveMetadata( + name=plugin.name, + enabled=plugin.enabled, + source=MappingProxyType(_SOURCE.validate_python(manifest.get("source", {}))), + manifest_json=plugin.manifest_json, + id=plugin.id, + version=plugin.version, + description=plugin.description, + has_agent_skill_metadata=has_agent_skill_metadata(manifest), + updated_at=plugin.updated_at, + ) diff --git a/litellm/repositories/skill_submission_repository.py b/litellm/repositories/skill_submission_repository.py new file mode 100644 index 00000000000..829aa0aadbf --- /dev/null +++ b/litellm/repositories/skill_submission_repository.py @@ -0,0 +1,368 @@ +import hashlib +import json +from collections.abc import Mapping +from contextlib import AbstractAsyncContextManager +from dataclasses import replace +from datetime import datetime, timezone +from typing import TYPE_CHECKING, Final, Protocol, cast # noqa: TID251 # Prisma's generated delegates are dynamic +from urllib.parse import urlsplit + +from pydantic import BaseModel, ConfigDict, TypeAdapter + +from litellm.models.plugin_upload import ( + PluginPublication, + PluginPublicationBase, + PluginPublicationError, + PublishedPlugin, + uploaded_plugin_source, +) +from litellm.models.skill_submission import ( + SkillProposal, + SkillScanInput, + SkillSubmission, + SubmissionConflict, + SubmissionLimitExceeded, + SubmissionMissing, + SubmissionOperation, + SubmissionPage, + SubmissionReviewed, + SubmissionReviewResult, + SubmissionStatus, +) +from litellm.repositories.plugin_publication import PluginPublicationTransaction, publish_plugin, verified_archive +from litellm.repositories.prisma_protocols import TableActions +from litellm.types.proxy.skill_scanning import SkillScan + +if TYPE_CHECKING: + from prisma import models as prisma_models + + from litellm.proxy.utils import PrismaClient + + +class _StoredProposal(BaseModel): + model_config = ConfigDict(frozen=True) + + manifest: Mapping[str, object] + version: str | None + + def proposal(self, name: str) -> SkillProposal: + return SkillProposal( + name, self.version, _DESCRIPTION.validate_python(self.manifest.get("description")), self.manifest + ) + + +class _PendingUsage(BaseModel): + model_config = ConfigDict(frozen=True) + + count: int + storage_bytes: int + + +class _SubmissionRow(BaseModel): + model_config = ConfigDict(frozen=True) + + id: str + plugin_name: str + operation: SubmissionOperation + status: SubmissionStatus + proposal_json: str + has_archive: bool + submitted_by: str + created_at: datetime + base_plugin_id: str | None + base_updated_at: datetime | None + reviewed_by: str | None + reviewed_at: datetime | None + rejection_reason: str | None + + def submission(self) -> SkillSubmission: + stored: Final = _StoredProposal.model_validate_json(self.proposal_json) + return SkillSubmission( + id=self.id, + plugin_name=self.plugin_name, + operation=self.operation, + status=self.status, + proposal=stored.proposal(self.plugin_name), + has_archive=self.has_archive, + submitted_by=self.submitted_by, + created_at=self.created_at, + base_plugin_id=self.base_plugin_id, + base_updated_at=self.base_updated_at, + reviewed_by=self.reviewed_by, + reviewed_at=self.reviewed_at, + rejection_reason=self.rejection_reason, + ) + + +_SCAN_ROWS: Final = TypeAdapter(tuple[Mapping[str, str | None], ...]) +_ROWS: Final = TypeAdapter(tuple[_SubmissionRow, ...]) +_DESCRIPTION: Final = TypeAdapter[str | None](str | None) +_SOURCE: Final = TypeAdapter(dict[str, str]) +_USAGE: Final = TypeAdapter(tuple[_PendingUsage, ...]) +_MAX_PENDING_SUBMISSIONS: Final = 20 +_MAX_PENDING_BYTES: Final = 50 * 1024 * 1024 +_SELECT: Final = """ +SELECT id, plugin_name, operation, status, proposal_json, + archive_content IS NOT NULL AS has_archive, submitted_by, created_at, + base_plugin_id, base_updated_at, reviewed_by, reviewed_at, rejection_reason +FROM "LiteLLM_SkillSubmission" +""" + + +class SubmissionTransaction(PluginPublicationTransaction, Protocol): + @property + def litellm_skillsubmission(self) -> TableActions["prisma_models.LiteLLM_SkillSubmission"]: ... + + +class SubmissionDatabase(SubmissionTransaction, Protocol): + def tx(self) -> AbstractAsyncContextManager[SubmissionTransaction]: ... + + +def _submission(row: "prisma_models.LiteLLM_SkillSubmission") -> SkillSubmission: + return _SubmissionRow.model_validate( + {**row.model_dump(), "has_archive": row.archive_content is not None} + ).submission() + + +class SkillSubmissionRepository: + def __init__(self, prisma_client: "PrismaClient") -> None: + self._database = cast( # cast-ok: Prisma dynamically exposes generated delegates and transactions + SubmissionDatabase, prisma_client.writer_db + ) + + async def get_scan(self, submission_id: str) -> SkillScan | SubmissionMissing | None: + rows: Final = _SCAN_ROWS.validate_python( + await self._database.query_raw( + 'SELECT scan_json FROM "LiteLLM_SkillSubmission" WHERE id = $1', submission_id + ) + ) + if not rows: + return SubmissionMissing() + value: Final = rows[0]["scan_json"] + return None if value is None else SkillScan.model_validate_json(value) + + async def start_scan( + self, submission_id: str, scan: SkillScan + ) -> SkillScanInput | SubmissionMissing | SubmissionConflict: + async with self._database.tx() as transaction: + await transaction.query_raw( + 'SELECT id FROM "LiteLLM_SkillSubmission" WHERE id = $1 FOR UPDATE', submission_id + ) + row: Final = await transaction.litellm_skillsubmission.find_unique(where={"id": submission_id}) + if row is None: + return SubmissionMissing() + if row.status != "pending_review": + return SubmissionConflict("Only pending submissions can be scanned.") + previous: Final = None if row.scan_json is None else SkillScan.model_validate_json(row.scan_json) + if previous is not None and previous.at(scan.started_at).status == "running": + return SubmissionConflict("A scan is already running for this submission.") + stored: Final = _StoredProposal.model_validate_json(row.proposal_json) + source: Final = _SOURCE.validate_python(stored.manifest.get("source", {})) + inherited: Final = ( + await transaction.litellm_claudecodepluginupload.find_unique(where={"plugin_name": row.plugin_name}) + if row.archive_content is None and source.get("source") == "archive" + else None + ) + content: Final = ( + row.archive_content.decode() + if row.archive_content is not None + else verified_archive( + None if inherited is None else inherited.content.decode(), json.dumps(stored.manifest) + ) + ) + managed_archive: Final = urlsplit(source.get("url", "")).path.endswith( + f"/claude-code/plugins/{row.plugin_name}/archive/{source.get('sha256', '')}.zip" + ) + if source.get("source") == "archive" and managed_archive and content is None: + return SubmissionConflict("The proposal's archive is no longer available. Submit a new ZIP to scan it.") + started: Final = scan.model_copy( + update={"archive_sha256": None if content is None else hashlib.sha256(content).hexdigest()} + ) + await transaction.litellm_skillsubmission.update( + where={"id": submission_id}, data={"scan_json": started.model_dump_json()} + ) + return SkillScanInput(started, source, content) + + async def finish_scan(self, submission_id: str, scan: SkillScan) -> None: + async with self._database.tx() as transaction: + rows: Final = _SCAN_ROWS.validate_python( + await transaction.query_raw( + 'SELECT scan_json FROM "LiteLLM_SkillSubmission" WHERE id = $1 FOR UPDATE', submission_id + ) + ) + value: Final = rows[0]["scan_json"] if rows else None + if value is None: + return + current: Final = SkillScan.model_validate_json(value) + if current.id != scan.id or current.status != "running": + return + result: Final = ( + current.at(scan.completed_at) + if scan.completed_at is not None and scan.completed_at >= current.expires_at + else scan + ) + await transaction.litellm_skillsubmission.update( + where={"id": submission_id}, data={"scan_json": result.model_dump_json()} + ) + + async def submit( + self, upload: PluginPublication, submitted_by: str, base: PluginPublicationBase | None + ) -> SkillSubmission | SubmissionLimitExceeded: + from prisma import Base64 + + proposal_json: Final = _StoredProposal(manifest=dict(upload.manifest), version=upload.version).model_dump_json() + incoming_bytes: Final = len(proposal_json.encode("utf-8")) + len(upload.content or b"") + async with self._database.tx() as transaction: + await transaction.query_raw( + "SELECT 1 AS locked FROM pg_advisory_xact_lock(hashtext('litellm.skill_submissions'), hashtext($1))", + submitted_by, + ) + usage: Final = _USAGE.validate_python( + await transaction.query_raw( + """SELECT COUNT(*) AS count, + COALESCE(SUM(octet_length(proposal_json) + + COALESCE(octet_length(archive_content), 0)), 0) AS storage_bytes + FROM "LiteLLM_SkillSubmission" WHERE submitted_by = $1 AND status = 'pending_review'""", + submitted_by, + ) + )[0] + if usage.count >= _MAX_PENDING_SUBMISSIONS: + return SubmissionLimitExceeded( + "You already have 20 pending skill submissions. " + "Wait for an admin to review one before submitting another." + ) + if usage.storage_bytes + incoming_bytes > _MAX_PENDING_BYTES: + return SubmissionLimitExceeded( + "Pending skill submissions cannot exceed 50 MiB of stored metadata and archives per user. " + "Wait for an admin review or submit less data." + ) + row: Final = await transaction.litellm_skillsubmission.create( + data={ + "plugin_name": upload.name, + "operation": "create" if base is None else "update", + "proposal_json": proposal_json, + "archive_content": None if upload.content is None else Base64.encode(upload.content), + "submitted_by": submitted_by, + "base_plugin_id": None if base is None else base.id, + "base_updated_at": None if base is None else base.updated_at, + } + ) + return _submission(row) + + async def list( + self, submitted_by: str | None, status: SubmissionStatus | None, limit: int, offset: int + ) -> SubmissionPage: + rows: Final = _ROWS.validate_python( + await self._database.query_raw( + _SELECT + + """WHERE ($1::text IS NULL OR submitted_by = $1) + AND ($2::text IS NULL OR status = $2) + ORDER BY created_at DESC, id DESC LIMIT $3 OFFSET $4""", + submitted_by, + status, + limit + 1, + offset, + ) + ) + return SubmissionPage(tuple(row.submission() for row in rows[:limit]), has_more=len(rows) > limit) + + async def get(self, submission_id: str, submitted_by: str | None) -> SkillSubmission | None: + rows: Final = _ROWS.validate_python( + await self._database.query_raw( + _SELECT + "WHERE id = $1 AND ($2::text IS NULL OR submitted_by = $2)", + submission_id, + submitted_by, + ) + ) + return None if not rows else rows[0].submission() + + async def get_archive(self, submission_id: str, submitted_by: str | None) -> bytes | None: + row: Final = await self._database.litellm_skillsubmission.find_first( + where={"id": submission_id, **({"submitted_by": submitted_by} if submitted_by is not None else {})} + ) + return None if row is None or row.archive_content is None else row.archive_content.decode() + + async def review( + self, + submission_id: str, + reviewer: str, + approve: bool, + reason: str | None, + *, + publication_base_url: str | None = None, + ) -> SubmissionReviewResult: + from prisma.errors import UniqueViolationError + + try: + async with self._database.tx() as transaction: + await transaction.query_raw( + 'SELECT id FROM "LiteLLM_SkillSubmission" WHERE id = $1 FOR UPDATE', submission_id + ) + row: Final = await transaction.litellm_skillsubmission.find_unique(where={"id": submission_id}) + if row is None: + return SubmissionMissing() + submission: Final = _submission(row) + if submission.status != "pending_review": + return SubmissionConflict("This submission has already been reviewed.") + content: Final = None if row.archive_content is None else row.archive_content.decode() + if approve and content is not None and not publication_base_url: + return SubmissionConflict("Uploaded skill approval requires a trusted publication URL.") + source: Final = ( + uploaded_plugin_source(publication_base_url, row.plugin_name, hashlib.sha256(content).hexdigest()) + if approve and content is not None and publication_base_url + else _SOURCE.validate_python(submission.proposal.manifest.get("source")) + ) + publication: Final = await _publish_submission(transaction, row, source, content) if approve else None + if isinstance(publication, PluginPublicationError): + return publication + reviewed_at: Final = datetime.now(timezone.utc) + status: Final[SubmissionStatus] = "approved" if approve else "rejected" + await transaction.litellm_skillsubmission.update( + where={"id": submission_id}, + data={ + "status": status, + "reviewed_by": reviewer, + "reviewed_at": reviewed_at, + "rejection_reason": None if approve else reason, + }, + ) + return SubmissionReviewed( + submission=replace( + submission, + status=status, + reviewed_by=reviewer, + reviewed_at=reviewed_at, + rejection_reason=None if approve else reason, + ), + plugin=publication, + published_source=source if approve else None, + ) + except UniqueViolationError: + return SubmissionConflict("A skill with this name is already published. Submit a new update proposal.") + + +async def _publish_submission( + transaction: PluginPublicationTransaction, + row: "prisma_models.LiteLLM_SkillSubmission", + source: Mapping[str, str], + content: bytes | None, +) -> PublishedPlugin | PluginPublicationError: + stored: Final = _StoredProposal.model_validate_json(row.proposal_json) + proposal: Final = stored.proposal(row.plugin_name) + base: Final = ( + None + if row.operation == "create" + else PluginPublicationBase(id=row.base_plugin_id or "", updated_at=row.base_updated_at) + ) + return await publish_plugin( + transaction, + PluginPublication( + name=row.plugin_name, + version=stored.version, + description=proposal.description, + manifest={**stored.manifest, "source": dict(source)}, + content=content, + created_by=row.submitted_by, + ), + base, + ) diff --git a/litellm/repositories/spend_log_insert.py b/litellm/repositories/spend_log_insert.py new file mode 100644 index 00000000000..a958edb9f8a --- /dev/null +++ b/litellm/repositories/spend_log_insert.py @@ -0,0 +1,88 @@ +from collections.abc import Mapping, Sequence +from datetime import datetime, timezone +from typing import Final + +from pydantic import JsonValue, TypeAdapter, ValidationError +from typing_extensions import LiteralString + +from litellm.litellm_core_utils.safe_json_dumps import safe_dumps + +_JSON: Final[TypeAdapter[JsonValue]] = TypeAdapter(JsonValue) + +_COLUMNS: Final[tuple[LiteralString, ...]] = ( + "request_id", + "call_type", + "api_key", + "spend", + "total_tokens", + "prompt_tokens", + "completion_tokens", + "startTime", + "endTime", + "request_duration_ms", + "completionStartTime", + "model", + "model_id", + "model_group", + "custom_llm_provider", + "api_base", + "user", + "metadata", + "cache_hit", + "cache_key", + "request_tags", + "team_id", + "organization_id", + "end_user", + "requester_ip_address", + "messages", + "response", + "session_id", + "status", + "mcp_namespaced_tool_name", + "billing_agent_id", + "agent_id", + "proxy_server_request", + "litellm_call_id", + "created_at", + "updated_at", +) +_JSON_COLUMNS: Final = frozenset({"metadata", "request_tags", "messages", "response", "proxy_server_request"}) + + +class RejectedSpendLogRow(ValueError): + """A row the raw insert cannot encode, so it is isolated like a row Postgres refuses.""" + + +def _json_value(column: str, value: object) -> object: + if isinstance(value, datetime): + return value.isoformat() + if column not in _JSON_COLUMNS or not isinstance(value, str): + return value + try: + return _JSON.validate_json(value) + except ValidationError as error: + raise RejectedSpendLogRow(f"Spend log column {column} is not valid JSON") from error + + +def spend_log_insert_statement(rows: Sequence[Mapping[str, object]]) -> tuple[LiteralString, str]: + if not rows: + raise ValueError("Spend log insert requires at least one row") + fields: Final = frozenset(rows[0]) | {"created_at", "updated_at"} + if not fields.issubset(_COLUMNS) or any(frozenset(row) | {"created_at", "updated_at"} != fields for row in rows): + raise RejectedSpendLogRow("Spend log insert requires matching known columns") + columns: Final = ", ".join('"' + column + '"' for column in _COLUMNS if column in fields) + now: Final = datetime.now(timezone.utc).isoformat() + values: Final = tuple( + {"created_at": now, "updated_at": now, **{column: _json_value(column, value) for column, value in row.items()}} + for row in rows + ) + sql: Final = ( + 'INSERT INTO "LiteLLM_SpendLogs" (' + + columns + + ") SELECT " + + columns + + ' FROM jsonb_populate_recordset(NULL::"LiteLLM_SpendLogs", $1::jsonb) ' + "ON CONFLICT DO NOTHING RETURNING request_id" + ) + return sql, safe_dumps(values, non_finite_as_null=True) diff --git a/litellm/repositories/table_repositories.py b/litellm/repositories/table_repositories.py index 2d3139f7a2c..d010455faa3 100644 --- a/litellm/repositories/table_repositories.py +++ b/litellm/repositories/table_repositories.py @@ -7,8 +7,15 @@ These are thin wrappers for tables that do not (yet) need domain-specific query methods; richer repositories live in their own modules. """ +from collections.abc import Mapping, Sequence +from datetime import timedelta +from itertools import groupby from typing import TYPE_CHECKING, Any, Final, Generic +from pydantic import TypeAdapter + +from litellm.litellm_core_utils.safe_json_dumps import safe_dumps +from litellm.repositories.accounting_delivery_repository import LedgerDatabase, LedgerTransaction from litellm.repositories.prisma_protocols import RowT_co, TableActions if TYPE_CHECKING: @@ -80,9 +87,117 @@ class OrganizationMembershipRepository(PrismaTableRepository["prisma_models.Lite table_name = "litellm_organizationmembership" +_SPEND_LOG_FIELDS: Final = TypeAdapter(dict[str, object]) + + +def _accounting_payload(value: object) -> Mapping[str, object]: + return ( + _SPEND_LOG_FIELDS.validate_json(value) if isinstance(value, str) else _SPEND_LOG_FIELDS.validate_python(value) + ) + + +_ACCOUNTING_ONLY_FIELDS: Final = frozenset({"accounting_payload", "accounting_log_disabled", "accounting_delivery_id"}) + + +def _settles_once(row: Mapping[str, object]) -> bool: + """A batch or video cost row: update_database gives every other ledger row its own delivery id.""" + return "accounting_delivery_id" not in row + + +def _delivery_id(row: Mapping[str, object]) -> str: + return str(row["accounting_delivery_id"]) if not _settles_once(row) else str(row["request_id"]) + + class SpendLogsRepository(PrismaTableRepository["prisma_models.LiteLLM_SpendLogs"]): table_name = "litellm_spendlogs" + async def insert_with_deliveries( + self, rows: Sequence[Mapping[str, object]], *, write_spend_logs: bool = True + ) -> int: + legacy: Final = tuple(row for row in rows if "accounting_payload" not in row) + legacy_count: Final = await self.table.create_many(data=legacy, skip_duplicates=True) if legacy else 0 + ledger: Final = tuple( + sorted( + {_delivery_id(row): row for row in reversed(rows) if "accounting_payload" in row}.values(), + key=_delivery_id, + ) + ) + if not ledger: + return legacy_count + database: Final[LedgerDatabase] = self.prisma_client.writer_db + async with database.tx(timeout=timedelta(seconds=60)) as transaction: + accepted: Final = await self._insert_ledger(transaction, ledger, write_spend_logs=write_spend_logs) + return legacy_count + accepted + + @staticmethod + async def _insert_ledger( + transaction: LedgerTransaction, rows: Sequence[Mapping[str, object]], *, write_spend_logs: bool + ) -> int: + from litellm.proxy.db.db_span import db_span + from litellm.repositories.spend_log_insert import spend_log_insert_statement + + payloads: Final = tuple( + { + "delivery_id": _delivery_id(row), + "request_id": row["request_id"], + "accounting_payload": _accounting_payload(row["accounting_payload"]), + "is_batch": _settles_once(row), + } + for row in rows + ) + inserted_deliveries: Final = await transaction.query_raw( + 'INSERT INTO "LiteLLM_SpendLogDelivery" (delivery_id, request_id, accounting_payload, is_batch) ' + "SELECT delivery_id, request_id, accounting_payload, is_batch FROM jsonb_to_recordset($1::jsonb) " + "AS inputs(delivery_id text, request_id text, accounting_payload jsonb, is_batch boolean) " + "ON CONFLICT (delivery_id) DO NOTHING RETURNING delivery_id", + safe_dumps(payloads, non_finite_as_null=True), + ) + accepted_ids: Final = frozenset(str(row["delivery_id"]) for row in inserted_deliveries) + charged_by_legacy: Final = await SpendLogsRepository._jobs_charged_by_legacy( + transaction, + tuple(_delivery_id(row) for row in rows if _settles_once(row) and _delivery_id(row) in accepted_ids), + ) + if charged_by_legacy: + await transaction.execute_raw( + 'DELETE FROM "LiteLLM_SpendLogDelivery" WHERE delivery_id = ANY($1::text[])', list(charged_by_legacy) + ) + accepted: Final = accepted_ids - charged_by_legacy + local_rows: Final = tuple( + {key: value for key, value in row.items() if key not in _ACCOUNTING_ONLY_FIELDS} + for row in rows + if _delivery_id(row) in accepted and row.get("accounting_log_disabled") is not True + ) + if write_spend_logs and local_rows: + groups: Final = tuple( + tuple(group) + for _, group in groupby( + sorted(local_rows, key=lambda row: tuple(sorted(row))), key=lambda row: tuple(sorted(row)) + ) + ) + async with db_span("insert_spend_logs", "LiteLLM_SpendLogs"): + for group in groups: + await transaction.query_raw(*spend_log_insert_statement(group)) + return len(accepted) + + @staticmethod + async def _jobs_charged_by_legacy(transaction: LedgerTransaction, cost_row_ids: Sequence[str]) -> frozenset[str]: + """Batches and videos a pre-ledger poll already charged through their SpendLogs cost row.""" + if not cost_row_ids: + return frozenset() + rows: Final = await transaction.query_raw( + 'SELECT DISTINCT request_id FROM "LiteLLM_SpendLogs" WHERE request_id = ANY($1::text[]) ' + "AND status = 'success' AND spend > 0", + list(cost_row_ids), + ) + return frozenset(str(row["request_id"]) for row in rows) + + async def has_delivery(self, delivery_id: str) -> bool: + database: Final[LedgerTransaction] = self.prisma_client.writer_db + rows: Final = await database.query_raw( + 'SELECT 1 FROM "LiteLLM_SpendLogDelivery" WHERE delivery_id = $1', delivery_id + ) + return bool(rows) + class BudgetWindowSpendRepository(PrismaTableRepository["prisma_models.LiteLLM_BudgetWindowSpend"]): table_name = "litellm_budgetwindowspend" @@ -272,3 +387,7 @@ class BackgroundInteractionSettlementRepository( class RetiredAgentRepository(PrismaTableRepository["prisma_models.LiteLLM_RetiredAgent"]): table_name = "litellm_retiredagent" + + +class DailyUserSpendRepository(PrismaTableRepository["prisma_models.LiteLLM_DailyUserSpend"]): + table_name = "litellm_dailyuserspend" diff --git a/litellm/repositories/verification_token_repository.py b/litellm/repositories/verification_token_repository.py index b20fb47306e..fb1f1c89e69 100644 --- a/litellm/repositories/verification_token_repository.py +++ b/litellm/repositories/verification_token_repository.py @@ -124,9 +124,7 @@ class VerificationTokenRepository(BaseRepository[LiteLLM_VerificationToken]): records: Final[Sequence[PrismaVerificationToken]] = await self.table.find_many(where={"user_id": user_id}) return self._to_model_list(records) - async def find_newest_reusable_llm_api_key( - self, user_id: str, team_id: str | None - ) -> LiteLLM_VerificationToken | None: + async def find_newest_reusable_key(self, user_id: str, team_id: str | None) -> LiteLLM_VerificationToken | None: records: Final[Sequence[PrismaVerificationToken]] = await self.table.find_many( where={ "user_id": user_id, @@ -140,12 +138,6 @@ class VerificationTokenRepository(BaseRepository[LiteLLM_VerificationToken]): {"team_id": {"not": UI_SESSION_TOKEN_TEAM_ID}}, ] }, - { - "OR": [ - {"allowed_routes": {"is_empty": True}}, - {"allowed_routes": {"has": "llm_api_routes"}}, - ] - }, ], }, order={"created_at": "desc"}, diff --git a/litellm/responses/litellm_completion_transformation/session_handler.py b/litellm/responses/litellm_completion_transformation/session_handler.py index 7cf163e7ce8..7e6ee84e2b2 100644 --- a/litellm/responses/litellm_completion_transformation/session_handler.py +++ b/litellm/responses/litellm_completion_transformation/session_handler.py @@ -1,14 +1,16 @@ import asyncio import json -from collections.abc import Mapping, Sequence +from collections.abc import Iterable, Iterator, Mapping, Sequence from dataclasses import dataclass from itertools import chain +from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, cast import litellm from litellm._logging import verbose_proxy_logger from litellm.constants import REDACTED_BY_LITELLM, REDACTED_TOOL_CALL_ARGUMENTS_PLACEHOLDER from litellm.litellm_core_utils.cold_storage_handler import ColdStorageHandler +from litellm.litellm_core_utils.core_helpers import as_str_mapping from litellm.responses.litellm_completion_transformation.client_tool_search import ( bridge_client_tool_search, client_tool_search_loaded_tools, @@ -69,6 +71,90 @@ def _is_a_conversation_turn(spend_log: "SpendLogsPayload") -> bool: return spend_log.get("call_type") not in _MCP_TOOL_CALL_TYPES and not _is_a_failed_turn(spend_log) +_RESPONSE_READ_CALL_TYPES: Final = frozenset(("aget_responses", "acancel_responses")) + + +def _output_item_id(item: object) -> str | None: + match item: + case {"id": str() as item_id}: + return item_id + case _: + return None + + +def _is_a_response_read(spend_log: "SpendLogsPayload") -> bool: + return "call_type" in spend_log and spend_log["call_type"] in _RESPONSE_READ_CALL_TYPES + + +def _stored_response(spend_log: "SpendLogsPayload") -> object: + return spend_log.get("response") + + +def _output_items(spend_log: "SpendLogsPayload") -> Iterator[tuple[str | None, object]]: + output: Final = _stored_responses_api_output(_stored_response(spend_log)) or [] + return zip(map(_output_item_id, output), output) + + +def _identified_output_items(spend_log: "SpendLogsPayload") -> Iterator[tuple[str, object]]: + return ((item_id, item) for item_id, item in _output_items(spend_log) if item_id is not None) + + +def _output_item_ids(spend_log: "SpendLogsPayload") -> frozenset[str]: + return frozenset(item_id for item_id, _ in _identified_output_items(spend_log)) + + +def _first_index_holding_each_item(indexed_turns: Iterable[tuple[int, "SpendLogsPayload"]]) -> Mapping[str, int]: + return dict( + chain.from_iterable( + ((item_id, index) for item_id in _output_item_ids(turn)) for index, turn in reversed(tuple(indexed_turns)) + ) + ) + + +def _turn_replaying_each_item(turns: Sequence["SpendLogsPayload"]) -> Mapping[str, int]: + indexed_turns: Final = tuple(enumerate(turns)) + first_read_holding: Final = _first_index_holding_each_item( + (index, turn) for index, turn in indexed_turns if _is_a_response_read(turn) + ) + first_other_turn_holding: Final = _first_index_holding_each_item( + (index, turn) for index, turn in indexed_turns if not _is_a_response_read(turn) + ) + return MappingProxyType({**first_read_holding, **first_other_turn_holding}) + + +def _latest_read_copy_of_each_item(turns: Sequence["SpendLogsPayload"]) -> Mapping[str, object]: + return MappingProxyType( + dict(chain.from_iterable(_identified_output_items(turn) for turn in turns if _is_a_response_read(turn))) + ) + + +def _with_only_new_output( + index: int, turn: "SpendLogsPayload", turn_replaying: Mapping[str, int], latest_copy: Mapping[str, object] +) -> "SpendLogsPayload | None": + if not _is_a_response_read(turn): + return turn + stored_response: Final = as_str_mapping(_stored_response(turn)) + new_output: Final = [ + item if item_id is None else latest_copy[item_id] + for item_id, item in _output_items(turn) + if item_id is None or turn_replaying.get(item_id) == index + ] + if stored_response is None or not new_output: + return None + replayed_turn: Final[SpendLogsPayload] = {**turn, "response": {**stored_response, "output": new_output}} + return replayed_turn + + +def _conversation_turns(spend_logs: Sequence["SpendLogsPayload"]) -> tuple["SpendLogsPayload", ...]: + turns: Final = tuple(filter(_is_a_conversation_turn, spend_logs)) + turn_replaying: Final = _turn_replaying_each_item(turns) + latest_copy: Final = _latest_read_copy_of_each_item(turns) + replayed: Final = ( + _with_only_new_output(index, turn, turn_replaying, latest_copy) for index, turn in enumerate(turns) + ) + return tuple(turn for turn in replayed if turn is not None) + + _MCP_AUTO_EXECUTE_OUTPUT_TYPES: Final = frozenset(("mcp_tools_fetched", "tool_execution_results")) @@ -101,7 +187,7 @@ class StoredTurns: def _compaction_point( index: int, spend_log: "SpendLogsPayload", proxy_server_request: Mapping[str, object] | None ) -> _ReplayStart | None: - if response_holds_compaction_block(spend_log.get("response")): + if response_holds_compaction_block(_stored_response(spend_log)): return _ReplayStart(index=index, at_output=True) if proxy_server_request is not None and holds_compaction_summary(proxy_server_request.get("input")): return _ReplayStart(index=index, at_output=False) @@ -271,12 +357,10 @@ class ResponsesSessionHandler: previous_response_id: str, client_response_ids: tuple[str, ...] = (), ) -> StoredTurns: - spend_logs: Final = tuple( - spend_log - for spend_log in await ResponsesSessionHandler.get_all_spend_logs_for_previous_response_id( + spend_logs: Final = _conversation_turns( + await ResponsesSessionHandler.get_all_spend_logs_for_previous_response_id( previous_response_id, client_response_ids ) - if _is_a_conversation_turn(spend_log) ) return StoredTurns( spend_logs=spend_logs, @@ -378,7 +462,7 @@ class ResponsesSessionHandler: ############################################################ # Add Output messages for this Spend Log ############################################################ - _response_output: Final[object] = spend_log.get("response", "{}") + _response_output: Final = _stored_response(spend_log) if (responses_api_output := _stored_responses_api_output(_response_output)) is not None: chat_completion_message_history.extend( LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages( diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py index ddcdc66ff20..521a698b276 100644 --- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py +++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py @@ -27,7 +27,11 @@ from litellm.responses.litellm_completion_transformation.tool_search import ( from litellm.responses.litellm_completion_transformation.transformation import ( LiteLLMCompletionResponsesConfig, ) -from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator, stamp_responses_usage_cost +from litellm.responses.streaming_iterator import ( + SEQUENCE_NUMBER_STAMPED_ON_EMISSION, + ResponsesAPIStreamingIterator, + stamp_responses_usage_cost, +) from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.types.llms.openai import ( PART_UNION_TYPES, @@ -239,14 +243,11 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): return execution def _next_output_item_added(self, output_index: int, item: BaseLiteLLMOpenAIResponseObject) -> OutputItemAddedEvent: - self._sequence_number += 1 - added: Final = OutputItemAddedEvent( + return OutputItemAddedEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, output_index=output_index, item=item, ) - added.__dict__["sequence_number"] = self._sequence_number - return added def _queue_output_item_added(self, output_index: int, item: BaseLiteLLMOpenAIResponseObject) -> None: self._pending_tool_events.append(self._next_output_item_added(output_index, item)) @@ -268,12 +269,10 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): item: Final = build_tool_search_call( call_id, final_args or self._tool_args_by_call_id.get(call_id, ""), "completed", execution ) - self._sequence_number += 1 self._pending_tool_events.append( OutputItemDoneEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE, output_index=output_index, - sequence_number=self._sequence_number, item=BaseLiteLLMOpenAIResponseObject(**item.model_dump()), ) ) @@ -346,12 +345,10 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): if streamed_item is None: return self._sent_compaction_item_done = True - self._sequence_number += 1 self._pending_response_events.append( OutputItemDoneEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE, output_index=self._compaction_output_index, - sequence_number=self._sequence_number, item=streamed_item, ) ) @@ -494,15 +491,12 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): chunk_size = 10 # Match typical OpenAI delta size for i in range(0, len(fn_args_delta), chunk_size): delta_chunk = fn_args_delta[i : i + chunk_size] - self._sequence_number += 1 delta_event: BaseLiteLLMOpenAIResponseObject = FunctionCallArgumentsDeltaEvent( type=ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA, item_id=self._tool_item_id_by_call_id.get(call_id, call_id), output_index=output_index, delta=delta_chunk, ) - # Add sequence_number as extra field (BaseLiteLLMOpenAIResponseObject allows extra fields) - delta_event.__dict__["sequence_number"] = self._sequence_number self._pending_tool_events.append(delta_event) def _queue_final_tool_call_done_events(self, litellm_complete_object: ModelResponse) -> None: @@ -567,33 +561,27 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): chunk_size = 10 # Match typical OpenAI delta size for i in range(0, len(remaining_args), chunk_size): delta_chunk = remaining_args[i : i + chunk_size] - self._sequence_number += 1 delta_event = FunctionCallArgumentsDeltaEvent( type=ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA, item_id=self._tool_item_id_by_call_id.get(call_id, call_id), output_index=output_index, delta=delta_chunk, ) - delta_event.__dict__["sequence_number"] = self._sequence_number self._pending_tool_events.append(delta_event) - self._sequence_number += 1 done_event = FunctionCallArgumentsDoneEvent( type=ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DONE, item_id=self._tool_item_id_by_call_id.get(call_id, call_id), output_index=output_index, arguments=final_args, ) - done_event.__dict__["sequence_number"] = self._sequence_number self._pending_tool_events.append(done_event) - self._sequence_number += 1 item_kwargs = self._tool_call_item_kwargs(call_id, fn_name, final_args, "completed") item_kwargs["id"] = self._tool_item_id_by_call_id.setdefault(call_id, item_kwargs["id"]) item_done_event = OutputItemDoneEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE, output_index=output_index, - sequence_number=self._sequence_number, item=BaseLiteLLMOpenAIResponseObject( **item_kwargs, **(_tool_call_provider_specific_fields(tc) if self.tool_call_provider_fields else {}), @@ -625,16 +613,11 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): _WEB_SEARCH_PROGRESS_EVENTS[:1] if item.status == "in_progress" else _WEB_SEARCH_PROGRESS_EVENTS ) for event_type, event_class in progress_events: - self._sequence_number += 1 - event = event_class(type=event_type, output_index=output_index, item_id=item.id) - event.__dict__["sequence_number"] = self._sequence_number - self._pending_tool_events.append(event) - self._sequence_number += 1 + self._pending_tool_events.append(event_class(type=event_type, output_index=output_index, item_id=item.id)) self._pending_tool_events.append( OutputItemDoneEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE, output_index=output_index, - sequence_number=self._sequence_number, item=BaseLiteLLMOpenAIResponseObject(**item.model_dump()), ) ) @@ -770,31 +753,24 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): """ response_created_event_data: Final = self._default_response_created_event_data() - self._sequence_number += 1 - event: Final = ResponseCreatedEvent( + return ResponseCreatedEvent( type=ResponsesAPIStreamEvents.RESPONSE_CREATED, response=self._with_encoded_response_id(ResponsesAPIResponse(**response_created_event_data)), ) - event.__dict__["sequence_number"] = self._sequence_number - return event def create_response_in_progress_event(self) -> ResponseInProgressEvent: response_in_progress_event_data: Final = self._default_response_created_event_data() response_in_progress_event_data["status"] = "in_progress" - self._sequence_number += 1 - event: Final = ResponseInProgressEvent( + return ResponseInProgressEvent( type=ResponsesAPIStreamEvents.RESPONSE_IN_PROGRESS, response=self._with_encoded_response_id(ResponsesAPIResponse(**response_in_progress_event_data)), ) - event.__dict__["sequence_number"] = self._sequence_number - return event def create_output_item_added_event(self) -> OutputItemAddedEvent: if self._cached_item_id is None: self._cached_item_id = f"msg_{uuid.uuid4()}" - self._sequence_number += 1 - event: Final = OutputItemAddedEvent( + return OutputItemAddedEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, output_index=self._message_index(), item=BaseLiteLLMOpenAIResponseObject( @@ -807,23 +783,18 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): } ), ) - event.__dict__["sequence_number"] = self._sequence_number - return event def create_content_part_added_event(self) -> ContentPartAddedEvent: if self._cached_item_id is None: self._cached_item_id = f"msg_{uuid.uuid4()}" - self._sequence_number += 1 - event: Final = ContentPartAddedEvent( + return ContentPartAddedEvent( type=ResponsesAPIStreamEvents.CONTENT_PART_ADDED, item_id=self._cached_item_id, output_index=self._message_index(), content_index=0, part=BaseLiteLLMOpenAIResponseObject(**{"type": "output_text", "text": "", "annotations": []}), ) - event.__dict__["sequence_number"] = self._sequence_number - return event def _queue_message_item_added_events(self) -> None: if not self.sent_message_item_added_event: @@ -834,7 +805,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): def _queue_message_item_added_event(self) -> None: item_id: Final = self._message_item_id() self.sent_message_item_added_event = True - self._sequence_number += 1 event: Final = OutputItemAddedEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, output_index=self._message_index(), @@ -848,7 +818,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): } ), ) - event.__dict__["sequence_number"] = self._sequence_number self._pending_response_events.append(event) def _queue_refusal_events(self, refusal: str) -> None: @@ -885,12 +854,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): part=ContentPartDonePartRefusal(type="refusal", refusal=refusal), ), ) - first_sequence_number: Final = self._sequence_number + 1 - self._sequence_number += len(events) - self._pending_response_events.extend( - event.model_copy(update={"sequence_number": sequence_number}) - for sequence_number, event in enumerate(events, start=first_sequence_number) - ) + self._pending_response_events.extend(events) def _merge_provider_specific_fields(self, src: dict) -> None: """Merge provider_specific_fields using last-value-wins for lists. @@ -944,7 +908,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self, reasoning_item_id: str, reasoning_content: str, - sequence_number: int, ) -> ReasoningSummaryTextDoneEvent: """ Create response.reasoning_summary_text.done event. @@ -954,7 +917,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): "type": "response.reasoning_summary_text.done", "item_id": "rs_0c5dae30e53172980069708ba2f59c8197b71ca9820edad07c", "output_index": 0, - "sequence_number": 97, "summary_index": 0, "text": "**Clarifying the first humans**\n\nThe I'm addressing the user's specific interest." } @@ -963,7 +925,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): type=ResponsesAPIStreamEvents.REASONING_SUMMARY_TEXT_DONE, item_id=reasoning_item_id, output_index=self._reasoning_index(), - sequence_number=sequence_number, + sequence_number=SEQUENCE_NUMBER_STAMPED_ON_EMISSION, summary_index=0, text=reasoning_content, ) @@ -972,7 +934,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self, reasoning_item_id: str, reasoning_content: str, - sequence_number: int, ) -> ReasoningSummaryPartDoneEvent: """ Create response.reasoning_summary_part.done event. @@ -986,7 +947,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): "type": "summary_text", "text": "**Clarifying the first humans**\n\nThe earlier hominins. It feels important to ensure I'm addressing the user's specific interest." }, - "sequence_number": 98, "summary_index": 0 } """ @@ -994,7 +954,7 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): type=ResponsesAPIStreamEvents.REASONING_SUMMARY_PART_DONE, item_id=reasoning_item_id, output_index=self._reasoning_index(), - sequence_number=sequence_number, + sequence_number=SEQUENCE_NUMBER_STAMPED_ON_EMISSION, summary_index=0, part=BaseLiteLLMOpenAIResponseObject( **{ @@ -1066,7 +1026,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): return OutputItemDoneEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE, output_index=self._message_index(), - sequence_number=1, item=BaseLiteLLMOpenAIResponseObject( **{ "id": self._cached_item_id, @@ -1082,7 +1041,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self, reasoning_item_id: str, reasoning_content: str, - sequence_number: int, ) -> OutputItemDoneEvent: """ Create response.output_item.done event for reasoning items. @@ -1091,7 +1049,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): { "type": "response.output_item.done", "output_index": 0, - "sequence_number": 99, "item": { "id": "rs_0c5dae30e53172980069708ba2f59c8197b71ca9820edad07c", "type": "reasoning", @@ -1107,7 +1064,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): return OutputItemDoneEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE, output_index=self._reasoning_index(), - sequence_number=sequence_number, item=BaseLiteLLMOpenAIResponseObject( **{ "id": reasoning_item_id, @@ -1223,7 +1179,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): if chunk.choices[0].finish_reason is None and not _delta_carries_output(delta): return - self._sequence_number += 1 self.sent_output_item_added_event = True # Reasoning-first @@ -1233,20 +1188,20 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self._cached_reasoning_item_id = mint_reasoning_item_id() self._reasoning_item_id = self._cached_reasoning_item_id - event = OutputItemAddedEvent( - type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, - output_index=self._reasoning_index(), - item=BaseLiteLLMOpenAIResponseObject( - **{ - "id": self._cached_reasoning_item_id, - "type": "reasoning", - "status": "in_progress", - "summary": None, - } - ), + self._pending_response_events.append( + OutputItemAddedEvent( + type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, + output_index=self._reasoning_index(), + item=BaseLiteLLMOpenAIResponseObject( + **{ + "id": self._cached_reasoning_item_id, + "type": "reasoning", + "status": "in_progress", + "summary": None, + } + ), + ) ) - event.__dict__["sequence_number"] = self._sequence_number - self._pending_response_events.append(event) return # Tool-first @@ -1279,30 +1234,34 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): ) reasoning_item_id: Final = self._cached_reasoning_item_id self._queue_compaction_item_done() - self._sequence_number += 1 text_done_event: Final = self.create_reasoning_summary_text_done_event( reasoning_item_id=reasoning_item_id, reasoning_content=reasoning_content, - sequence_number=self._sequence_number, ) - self._sequence_number += 1 part_done_event: Final = self.create_reasoning_summary_part_done_event( reasoning_item_id=reasoning_item_id, reasoning_content=reasoning_content, - sequence_number=self._sequence_number, ) - self._sequence_number += 1 reasoning_output_item_done_event: Final = self.create_reasoning_output_item_done_event( reasoning_item_id=reasoning_item_id, reasoning_content=reasoning_content, - sequence_number=self._sequence_number, ) self._pending_response_events.extend([text_done_event, part_done_event, reasoning_output_item_done_event]) self._reasoning_done_emitted = True self._reasoning_active = False + def _stamp_sequence_number(self, event: BaseLiteLLMOpenAIResponseObject) -> BaseLiteLLMOpenAIResponseObject: + stamped: Final = event.model_copy(update={"sequence_number": self._sequence_number}) + self._sequence_number += 1 + return stamped + async def __anext__( self, + ) -> ResponsesAPIStreamingResponse | ResponseCompletedEvent | BaseLiteLLMOpenAIResponseObject: + return self._stamp_sequence_number(await self._anext_unstamped_event()) + + async def _anext_unstamped_event( + self, ) -> ResponsesAPIStreamingResponse | ResponseCompletedEvent | BaseLiteLLMOpenAIResponseObject: try: while True: @@ -1363,6 +1322,11 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): def __next__( self, + ) -> ResponsesAPIStreamingResponse | ResponseCompletedEvent | BaseLiteLLMOpenAIResponseObject: + return self._stamp_sequence_number(self._next_unstamped_event()) + + def _next_unstamped_event( + self, ) -> ResponsesAPIStreamingResponse | ResponseCompletedEvent | BaseLiteLLMOpenAIResponseObject: try: while True: @@ -1504,16 +1468,13 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): if not self.sent_content_part_added_event: self._queue_message_item_added_events() self._hold_tool_calls_behind_text(getattr(chunk.choices[0].delta, "tool_calls", None)) - self._sequence_number += 1 - text_delta_event: Final = OutputTextDeltaEvent( + return OutputTextDeltaEvent( type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA, item_id=item_id, output_index=self._message_index(), content_index=0, delta=delta_content, ) - text_delta_event.__dict__["sequence_number"] = self._sequence_number - return text_delta_event # Priority 3: Handle tool call deltas (if any) -> queue events and emit them # For each tool call delta, we emit events one at a time to match OpenAI's streaming behavior diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py index 0f4ed0611be..3e605e926f7 100644 --- a/litellm/responses/litellm_completion_transformation/transformation.py +++ b/litellm/responses/litellm_completion_transformation/transformation.py @@ -52,6 +52,7 @@ from litellm.integrations.anthropic_cache_control_hook import ( cache_control_count, dropped_cache_control, newest_marks_within_cache_control_limit, + routed_model_info, whole_messages_within_cache_control_limit, with_cache_control, ) @@ -782,13 +783,15 @@ def _replays_compaction_block(input: str | ResponseInputParam, context_managemen _PROVIDERS_KEEPING_MESSAGE_CACHE_CONTROL: Final = frozenset(("anthropic", "dashscope", "minimax", "sap", "zai")) -def _bedrock_target_keeps_item_marks(model: str, drop_params: bool) -> bool: - declared: Final = bedrock_declared_cache_point_support(model) +def _bedrock_target_keeps_item_marks(model: str, drop_params: bool, model_info: Mapping[str, object] | None) -> bool: + declared: Final = bedrock_declared_cache_point_support(model, model_info) return declared is True or (declared is None and not drop_params) -def _target_keeps_item_marks(model: str, custom_llm_provider: str | None, drop_params: bool) -> bool: - if supports_anthropic_cache_control(model, custom_llm_provider): +def _target_keeps_item_marks( + model: str, custom_llm_provider: str | None, drop_params: bool, model_info: Mapping[str, object] | None +) -> bool: + if supports_anthropic_cache_control(model, custom_llm_provider, model_info): return True if custom_llm_provider in _PROVIDERS_KEEPING_MESSAGE_CACHE_CONTROL: return True @@ -798,7 +801,7 @@ def _target_keeps_item_marks(model: str, custom_llm_provider: str | None, drop_p return is_snowflake_claude_model(model) if custom_llm_provider == "databricks": return "claude" in model.lower() - return custom_llm_provider == "bedrock" and _bedrock_target_keeps_item_marks(model, drop_params) + return custom_llm_provider == "bedrock" and _bedrock_target_keeps_item_marks(model, drop_params, model_info) def _refuses_marks_on_tool_blocks(model: str, custom_llm_provider: str | None) -> bool: @@ -1234,7 +1237,10 @@ class LiteLLMCompletionResponsesConfig: request_kwargs: Final = _STR_KEY_DICT_ADAPTER.validate_python({**kwargs, "drop_params": drop_params}) context_management: Final = responses_api_request.get("context_management") keeps_item_marks: Final = _target_keeps_item_marks( - model, custom_llm_provider, drops_unsupported_params(request_kwargs.get("drop_params")) + model, + custom_llm_provider, + drops_unsupported_params(request_kwargs.get("drop_params")), + routed_model_info(request_kwargs.get("model_info")), ) request_input: Final = with_compaction_items_as_params(input) native_compaction: Final = _replays_compaction_block( @@ -1456,7 +1462,10 @@ class LiteLLMCompletionResponsesConfig: model: Final = str(request_fields.get("model") or "") provider: Final = requested_provider if isinstance(requested_provider, str) else None keeps_item_marks: Final = _target_keeps_item_marks( - model, provider, drops_unsupported_params(request_kwargs.get("drop_params")) + model, + provider, + drops_unsupported_params(request_kwargs.get("drop_params")), + routed_model_info(request_kwargs.get("model_info")), ) lookup: Final = session_lookup or partial( ResponsesSessionHandler.get_chat_completion_message_history_for_previous_response_id, diff --git a/litellm/responses/main.py b/litellm/responses/main.py index ad1d35bbe17..e9f9eb85d25 100644 --- a/litellm/responses/main.py +++ b/litellm/responses/main.py @@ -27,6 +27,7 @@ from litellm.integrations.anthropic_cache_control_hook import ( CARRY_UNMATCHED_MESSAGE_POINTS, AnthropicCacheControlHook, configured_injection_points, + routed_model_info, ) from litellm.litellm_core_utils.asyncify import run_async_function from litellm.litellm_core_utils.completion_timeout import CompletionTimeout, StreamKind @@ -758,9 +759,7 @@ def _api_base_kwarg(kwargs: Mapping[str, object]) -> str | None: return api_base if isinstance(api_base, str) else None -def _dispatched_model_name( - model: str, custom_llm_provider: str, api_base: str | None, litellm_params: GenericLiteLLMParams | None = None -) -> str: +def _dispatched_model_name(model: str, custom_llm_provider: str) -> str: from litellm.litellm_core_utils.get_llm_provider_logic import resolve_model_and_provider_for_metadata provider_model, _ = resolve_model_and_provider_for_metadata(model=model, custom_llm_provider=custom_llm_provider) @@ -773,7 +772,6 @@ def _will_bridge_to_chat_completions( use_chat_completions_api: bool, model_info: object, api_base: str | None, - litellm_params: GenericLiteLLMParams | None = None, ) -> bool: """``_bridges_to_chat_completions`` for callers running before the provider config is resolved. @@ -790,7 +788,7 @@ def _will_bridge_to_chat_completions( return True return _bridges_to_chat_completions( _resolve_responses_api_provider_config( - _dispatched_model_name(normalized_model[0], custom_llm_provider, api_base, litellm_params), + _dispatched_model_name(normalized_model[0], custom_llm_provider), custom_llm_provider, model_info, api_base, @@ -815,7 +813,6 @@ def provider_stores_the_conversation(model: str, custom_llm_provider: str | None bool(kwargs.get("use_chat_completions_api")), kwargs.get("model_info"), api_base, - litellm_params, ) @@ -882,6 +879,7 @@ def _stamp_injection_points_for_the_hook( custom_llm_provider, kwargs.get("api_base") or kwargs.get("base_url"), kwargs.get("prompt_cache_options"), + routed_model_info(kwargs.get("model_info")), ) @@ -997,7 +995,6 @@ async def aresponses( bool(kwargs.get("use_chat_completions_api")), kwargs.get("model_info"), _api_base_kwarg(kwargs), - GenericLiteLLMParams(**kwargs), ), ): _stamp_injection_points_for_the_hook(kwargs, model, custom_llm_provider, input, tools) @@ -1173,7 +1170,6 @@ def _apply_prompt_management_to_responses_call( use_chat_completions_api, kwargs.get("model_info"), _api_base_kwarg(kwargs), - GenericLiteLLMParams(**kwargs), ), ): _stamp_injection_points_for_the_hook(kwargs, model, custom_llm_provider, input, tools) diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py index 09ee6828157..249c6370b86 100644 --- a/litellm/responses/streaming_iterator.py +++ b/litellm/responses/streaming_iterator.py @@ -379,6 +379,7 @@ def _mid_stream_fallback_eligible(mapped_exception: Exception) -> bool: PRE_OUTPUT_LIFECYCLE_EVENT_TYPES: Final = frozenset({"response.created", "response.in_progress", "response.queued"}) +SEQUENCE_NUMBER_STAMPED_ON_EMISSION: Final = -1 class BaseResponsesAPIStreamingIterator: @@ -1030,9 +1031,7 @@ class BaseResponsesAPIStreamingIterator: ) if estimate is None: return - usage: Final = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage( # pyright: ignore[reportPrivateUsage] # same shared transform the success path above uses - estimate - ) + usage: Final = ResponseAPILoggingUtils.transform_response_api_usage_to_chat_usage(estimate) served_tier: Final[object] = getattr(self._created_response, "service_tier", None) assembled: Final = ModelResponse( model=self.model, usage=usage, service_tier=served_tier if isinstance(served_tier, str) else None @@ -1891,7 +1890,7 @@ def stamp_responses_usage_cost( return if isinstance(bill, bool) or not isinstance(bill, (int, float)): return - if bill > 0 or isinstance(getattr(usage_obj, "cost", None), (int, float)): + if bill > 0 or isinstance(usage_obj.cost, (int, float)): stamp_litellm_bill_on_usage(response_obj, usage_obj, float(bill)) @@ -1933,7 +1932,6 @@ def build_synthetic_response_events( _build_response_status_event(openai_types.ResponsesAPIStreamEvents.RESPONSE_IN_PROGRESS, transformed), ] - sequence_number = 0 output_items: Final[Sequence[object]] = getattr(transformed, "output", []) or [] for output_index, output_item in enumerate(output_items): output_item_payload = _dump_response_object(output_item) @@ -2043,35 +2041,31 @@ def build_synthetic_response_events( delta=summary_text[i : i + chunk_size], ) ) - sequence_number += 1 events.append( openai_types.ReasoningSummaryTextDoneEvent( type=openai_types.ResponsesAPIStreamEvents.REASONING_SUMMARY_TEXT_DONE, item_id=item_id, output_index=output_index, - sequence_number=sequence_number, + sequence_number=SEQUENCE_NUMBER_STAMPED_ON_EMISSION, summary_index=summary_index, text=summary_text, ) ) - sequence_number += 1 events.append( openai_types.ReasoningSummaryPartDoneEvent( type=openai_types.ResponsesAPIStreamEvents.REASONING_SUMMARY_PART_DONE, item_id=item_id, output_index=output_index, - sequence_number=sequence_number, + sequence_number=SEQUENCE_NUMBER_STAMPED_ON_EMISSION, summary_index=summary_index, part=openai_types.BaseLiteLLMOpenAIResponseObject(**summary_payload), ) ) - sequence_number += 1 events.append( openai_types.OutputItemDoneEvent( type=openai_types.ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE, output_index=output_index, - sequence_number=sequence_number, item=openai_types.BaseLiteLLMOpenAIResponseObject(**output_item_payload), ) ) @@ -2082,7 +2076,7 @@ def build_synthetic_response_events( response=transformed, ) ) - return events + return [event.model_copy(update={"sequence_number": number}) for number, event in enumerate(events)] # --------------------------------------------------------------------------- diff --git a/litellm/responses/utils.py b/litellm/responses/utils.py index 1a97c1cb48c..43ed9a3b96f 100644 --- a/litellm/responses/utils.py +++ b/litellm/responses/utils.py @@ -678,20 +678,25 @@ class ResponsesAPIRequestUtils: return items: Final = cast(list[object], request_input) # cast-ok: untyped client json stripped: Final = tuple( - ResponsesAPIRequestUtils._without_encrypted_reasoning(item) - if should_strip is None or (isinstance(item, Mapping) and should_strip(cast(Mapping[str, object], item))) + ResponsesAPIRequestUtils._without_encrypted_reasoning(reasoning) + if (reasoning := ResponsesAPIRequestUtils._encrypted_reasoning_item(item)) is not None + and (should_strip is None or should_strip(reasoning)) else item for item in items ) items[:] = (item for item in stripped if item is not None) @staticmethod - def _without_encrypted_reasoning(item: object) -> object | None: + def _encrypted_reasoning_item(item: object) -> Mapping[str, object] | None: if not isinstance(item, dict): - return item + return None reasoning: Final = cast(Mapping[str, object], item) # cast-ok: untyped client json if reasoning.get("type") != "reasoning" or not reasoning.get("encrypted_content"): - return reasoning + return None + return reasoning + + @staticmethod + def _without_encrypted_reasoning(reasoning: Mapping[str, object]) -> object | None: readable: Final = any( ResponsesAPIRequestUtils._has_readable_text(reasoning.get(key)) for key in ("summary", "content") ) diff --git a/litellm/router.py b/litellm/router.py index 4ee138fc9fb..6a60d5d958e 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -11,7 +11,7 @@ outside code used before the entry points live in ``DeprecatedRouterMembers`` un import inspect import weakref from collections.abc import Mapping -from types import CellType, FunctionType, MappingProxyType +from types import FunctionType, MappingProxyType from typing import TYPE_CHECKING, Final from litellm import router_python_core @@ -35,7 +35,7 @@ from litellm.types.router import ( RetryPolicy, ) -_CORE_SIGNATURE: Final = inspect.signature(PythonCore.__init__) +_CORE_SIGNATURE: Final = inspect.signature(PythonCore.__init__) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # reflection reads only the parameters' names def router_arguments( @@ -65,142 +65,40 @@ else: _replaced_core_members: Final[ # mutable-ok: originals of patched core members, restored on delete dict[tuple[type, str], list[object]] ] = {} - _FACADE_ONLY: Final = frozenset( - { - "__module__", - "__qualname__", - "__doc__", - "__dict__", - "__weakref__", - "__init__", - "__init_subclass__", - "__annotations__", - "__firstlineno__", - "__static_attributes__", - "__classcell__", - "_core_class", - } - ) - - def _with_class_cell(value: object, cell: "CellType") -> object: - """``value`` with its ``__class__`` cell (what zero-argument ``super()`` reads) replaced by ``cell``.""" - if isinstance(value, staticmethod | classmethod): - return type(value)(_function_with_class_cell(value.__func__, cell)) - if isinstance(value, property): - return property( - *( - None if f is None else _function_with_class_cell(f, cell) - for f in (value.fget, value.fset, value.fdel) - ), - value.__doc__, - ) - return _function_with_class_cell(value, cell) - - def _function_with_class_cell(value: object, cell: "CellType") -> object: - """A plain function with its ``__class__`` cell replaced by ``cell``; anything else unchanged.""" - if not isinstance(value, FunctionType) or "__class__" not in value.__code__.co_freevars: - return value - closure: Final = tuple( - cell if name == "__class__" else original - for name, original in zip(value.__code__.co_freevars, value.__closure__ or (), strict=True) - ) - rebound: Final = FunctionType(value.__code__, value.__globals__, value.__name__, value.__defaults__, closure) - rebound.__kwdefaults__ = value.__kwdefaults__ - rebound.__qualname__ = value.__qualname__ - rebound.__dict__.update(value.__dict__) - return rebound - - class _Absent: - """A facade-only member, hidden from the core class: reading it raises the usual AttributeError.""" - - def __set_name__(self, owner: type, name: str) -> None: - self._name = name - - def __get__(self, instance: object, owner: type | None = None) -> object: - if instance is None: - raise AttributeError( - f"type object {getattr(owner, '__name__', owner)!r} has no attribute {self._name!r}" - ) - raise AttributeError(f"{type(instance).__name__!r} object has no attribute {self._name!r}") - - def _core_class_for(facade: type, parent: type) -> type: - """ - A core class carrying a Router subclass's own members, so the core runs its overrides. It - subclasses the facade too, so an override's ``super(Sub, self)`` finds the core it runs on. - """ - cell: Final = CellType() - members: Final = { - name: _with_class_cell(value, cell) for name, value in vars(facade).items() if name not in _FACADE_ONLY - } - namespace: Final = { - # The facade's own plumbing sits in the core class's MRO ahead of the parent core: put - # the parent core's versions back, and hide the facade-only members. - "__init__": parent.__init__, - "__getattribute__": object.__getattribute__, - "__setattr__": parent.__setattr__, - "__delattr__": parent.__delattr__, - "__dir__": parent.__dir__, - **{name: _Absent() for name in ("_attach", "_core", "from_config", "_core_class")}, - **members, - "__module__": facade.__module__, - } - core_class: Final = _CoreType(f"{facade.__name__}Core", (facade, parent), namespace) - cell.cell_contents = core_class - for name in members: - type.__delattr__(facade, name) - return core_class class _RouterType(type): """ - Class-level reads of core members (``Router._helper(...)``) go to the router's core class, and - so do class-level patches, which put the original back when the patch is removed. - ``isinstance`` and ``dir`` see the core class too. + Class-level reads of core members (``Router._helper(...)``) go to ``PythonCore``, and so do + class-level patches, which put the original back when the patch is removed. + ``isinstance`` and ``dir`` see ``PythonCore`` too. """ def __getattr__(cls, name: str) -> object: - if name == "_core_class": - raise AttributeError(name) - return getattr(cls._core_class, name) + return getattr(PythonCore, name) def __setattr__(cls, name: str, value: object) -> None: - core_class: Final = vars(cls).get("_core_class") or getattr(cls, "_core_class", None) - if core_class is None or any(name in vars(base) for base in cls.__mro__) or not hasattr(core_class, name): + if any(name in vars(base) for base in cls.__mro__) or not hasattr(PythonCore, name): super().__setattr__(name, value) return - _replaced_core_members.setdefault((core_class, name), []).append(vars(core_class).get(name, _MISSING)) - setattr(core_class, name, value) + _replaced_core_members.setdefault((PythonCore, name), []).append(vars(PythonCore).get(name, _MISSING)) + setattr(PythonCore, name, value) def __delattr__(cls, name: str) -> None: - core_class: Final = getattr(cls, "_core_class", None) - replaced: Final = _replaced_core_members.get((core_class, name)) if core_class is not None else None + replaced: Final = _replaced_core_members.get((PythonCore, name)) if not replaced or any(name in vars(base) for base in cls.__mro__): super().__delattr__(name) return original: Final = replaced.pop() if original is _MISSING: - delattr(core_class, name) + delattr(PythonCore, name) return - setattr(core_class, name, original) + setattr(PythonCore, name, original) def __instancecheck__(cls, instance: object) -> bool: - return type.__instancecheck__(cls, instance) or isinstance(instance, cls._core_class) + return type.__instancecheck__(cls, instance) or isinstance(instance, PythonCore) def __dir__(cls) -> list[str]: # mutable-ok: dir() returns a list - return sorted({*type.__dir__(cls), *dir(cls._core_class)}) - - class _CoreType(_RouterType): - """The metaclass of a Router subclass's core class: a plain class, none of the facade's redirects.""" - - def __getattr__(cls, name: str) -> object: - raise AttributeError(f"type object {cls.__name__!r} has no attribute {name!r}") - - __setattr__ = type.__setattr__ - __delattr__ = type.__delattr__ - __instancecheck__ = type.__instancecheck__ - __dir__ = type.__dir__ - - def _is_core(instance: object) -> bool: - return isinstance(type(instance), _CoreType) + return sorted({*type.__dir__(cls), *dir(PythonCore)}) def _patchable_method(core: object, name: str) -> bool: """A method of the core: an instance-level replacement of it is also kept on the facade, so @@ -212,27 +110,20 @@ else: return hasattr(type(core), "__getattr__") and inspect.ismethod(getattr(core, name, None)) class Router(DeprecatedRouterMembers, metaclass=_RouterType): - _core_class: type[PythonCore] = PythonCore - - def __init_subclass__(cls, **kwargs: object) -> None: # kwargs-ok: class keywords, passed on to super() - if isinstance(cls, _CoreType): - # A core class built below: the parent core's hooks wire it, as for any core class. - super().__init_subclass__(**kwargs) - return - # DeprecatedRouterMembers wires a subclass's overrides of old members; here that runs - # on the core class built from it, which is where the router's own calls land. - super(DeprecatedRouterMembers, cls).__init_subclass__(**kwargs) - type.__setattr__(cls, "_core_class", _core_class_for(cls, cls._core_class)) + def __init_subclass__(cls, **kwargs: object) -> None: # kwargs-ok: class keywords, refused with the class + raise TypeError( + "litellm.Router cannot be subclassed. Use the router's entry points instead: " + "register_plugin() for custom routing, apply() for settings, observe() for outcomes. " + "See https://docs.litellm.ai/docs/routing_plugins." + ) def __init__(self, *args: object, **kwargs: object) -> None: # kwargs-ok: Router's constructor arguments - self._attach( - make_core(build_router_config(router_arguments(*args, **kwargs)), python_host, type(self)._core_class) - ) + self._attach(make_core(build_router_config(router_arguments(*args, **kwargs)), python_host)) @classmethod def from_config(cls, config: RouterConfig, host: PythonHost = python_host) -> "Router": router: Final = cls.__new__(cls) - router._attach(make_core(config, host, cls._core_class)) + router._attach(make_core(config, host)) return router def _attach(self, core: RouterCore) -> None: @@ -253,8 +144,7 @@ else: try: return object.__getattribute__(self, name) except AttributeError: - if _is_core(self): - raise + pass facade: Final = object.__getattribute__(self, "__dict__") core: Final = facade.get("_core") if core is None: @@ -273,9 +163,6 @@ else: ) from None def __setattr__(self, name: str, value: object) -> None: - if _is_core(self): - super().__setattr__(name, value) - return if _class_descriptor(type(self), name): object.__setattr__(self, name, value) return @@ -289,9 +176,6 @@ else: self.__dict__[name] = value def __delattr__(self, name: str) -> None: - if _is_core(self): - super().__delattr__(name) - return if _class_descriptor(type(self), name): object.__delattr__(self, name) return @@ -299,9 +183,7 @@ else: delattr(self._core, name) def __dir__(self) -> list[str]: # mutable-ok: dir() returns a list - if _is_core(self): - return super().__dir__() - return sorted({*super().__dir__(), *dir(self.__dict__.get("_core", type(self)._core_class))}) + return sorted({*super().__dir__(), *dir(self.__dict__.get("_core", PythonCore))}) Router.__init__.__signature__ = _CORE_SIGNATURE.replace( # pyright: ignore[reportFunctionMemberAccess] # inspect reads it parameters=[parameter for parameter in _CORE_SIGNATURE.parameters.values() if parameter.name != "_host"] diff --git a/litellm/router_api.py b/litellm/router_api.py index c013a99573f..82660439ae9 100644 --- a/litellm/router_api.py +++ b/litellm/router_api.py @@ -32,6 +32,7 @@ as they were. # members are still untyped (bare ``dict`` / ``list``) or mutable (the live objects); the overloads # repeat them unchanged, and typing the members themselves is the core's job. +import copy import hashlib import inspect import json @@ -45,6 +46,7 @@ from typing import TYPE_CHECKING, Final, Literal, Protocol, TypeAlias, overload from litellm.router_config import detached if TYPE_CHECKING: + from functools import _lru_cache_wrapper from typing import Any # noqa: TID251 # only to spell the cores' untyped (Unknown) containers and one Any type from opentelemetry.trace import Span @@ -155,6 +157,7 @@ GroupField: TypeAlias = Literal[ "display_name", "mode", "service_tiers", + "max_input_tokens", "token_limits", "listing_info", ] @@ -178,9 +181,9 @@ def deployment_usable_by_team(deployment: "Mapping[str, object] | Deployment", t Whether ``team_id`` may use ``deployment``: a team-scoped deployment (``model_info.team_id`` set) only by that team, any other deployment by everyone. Needs no router instance. """ - from litellm.router_python_core import PythonCore + from litellm.router_rust.surface.registry import HostRegistry - return PythonCore._core_deployment_usable_by_team(deployment, team_id) + return HostRegistry._core_deployment_usable_by_team(deployment, team_id) def deployment_id(model_group: str, litellm_params: Mapping[str, object]) -> str: @@ -200,11 +203,77 @@ def deployment_id(model_group: str, litellm_params: Mapping[str, object]) -> str return hashlib.sha256("".join(parts).encode()).hexdigest() +# The arguments ``Router.__init__`` accepts, in its signature's order. Every core reads this list +# (the Python core's ``get_valid_args`` reads its constructor's signature, and the core suite checks +# that the two agree). +ROUTER_INIT_ARGS: Final[tuple[str, ...]] = ( + "model_list", + "assistants_config", + "search_tools", + "guardrail_list", + "redis_url", + "redis_host", + "redis_port", + "redis_password", + "redis_db", + "cache_responses", + "cache_kwargs", + "caching_groups", + "client_ttl", + "polling_interval", + "default_priority", + "num_retries", + "max_fallbacks", + "timeout", + "stream_timeout", + "default_litellm_params", + "default_max_parallel_requests", + "set_verbose", + "debug_level", + "default_fallbacks", + "fallbacks", + "context_window_fallbacks", + "content_policy_fallbacks", + "model_group_alias", + "enable_pre_call_checks", + "enable_tag_filtering", + "tag_filtering_match_any", + "tag_routing_prefix", + "plugins", + "retry_after", + "retry_policy", + "model_group_retry_policy", + "allowed_fails", + "allowed_fails_policy", + "cooldown_time", + "disable_cooldowns", + "fallback_on_unsupported_params", + "routing_strategy", + "optional_pre_call_checks", + "routing_strategy_args", + "routing_groups", + "provider_budget_config", + "alerting_config", + "router_general_settings", + "deployment_affinity_ttl_seconds", + "model_group_affinity_config", + "ignore_invalid_deployments", + "enable_health_check_routing", + "health_check_staleness_threshold", + "health_check_ignore_transient_errors", + "background_health_check_model_groups", + "enable_weighted_failover", + "enable_mid_stream_fallback_continuation", + "fallback_access_check", + "fallback_budget_check", + "auto_router_capability_limit", + "session_affinity_repin_on_failover", +) + + def router_init_args() -> tuple[str, ...]: """The arguments ``Router.__init__`` accepts (was ``Router.get_valid_args``). Needs no router instance.""" - from litellm.router_python_core import PythonCore - - return tuple(PythonCore.get_valid_args()) + return ROUTER_INIT_ARGS def mark_advisor_orchestration_failure(exception: BaseException) -> None: @@ -268,9 +337,9 @@ def deployment_metadata(request_kwargs: Mapping[str, object]) -> Mapping[str, ob def _json_default_stable_id(obj: object) -> str: - from litellm.router_python_core import PythonCore + from litellm.router_rust.steps.prerouting import _json_default_stable_id as stable_id - return PythonCore._json_default_stable_id(obj) + return stable_id(obj) class RouterRegistry: @@ -315,6 +384,13 @@ class RouterRegistry: return self._router._core_cached_deployment_model_info(id, model_name) return self._router._core_get_deployment_model_info(model_id=id, model_name=model_name) + def deployment_model_info_cache(self) -> "_lru_cache_wrapper[ModelMapInfo | None]": + """ + The lru cache ``deployment_model_info(..., cached=True)`` reads, called as ``(id, model_name)`` + and cleared with ``cache_clear()`` (was the ``cached_deployment_model_info`` attribute). + """ + return self._router._core_cached_deployment_model_info + def router_model_info( self, deployment: "dict[str, object] | Deployment | None", # mutable-ok: the core takes a dict @@ -531,10 +607,8 @@ class RouterRegistry: ``should_include_deployment``), or, without ``model_name``, whether the team may use it at all (was ``deployment_usable_by_team``). """ - from litellm.router_python_core import PythonCore - if model_name is None: - return PythonCore._core_deployment_usable_by_team(deployment, team_id) + return deployment_usable_by_team(deployment, team_id) return self._router._core_should_include_deployment(model_name=model_name, model=deployment, team_id=team_id) @overload @@ -855,6 +929,16 @@ class RouterRegistry: team_id: str | None = None, ) -> tuple[object, ...]: ... + @overload + def group( + self, + name: str, + *, + field: Literal["max_input_tokens"], + include_hidden: bool = False, + team_id: str | None = None, + ) -> tuple[int | None, ...]: ... + @overload def group( self, @@ -882,9 +966,7 @@ class RouterRegistry: field: GroupField = "info", include_hidden: bool = False, team_id: str | None = None, - ) -> ( - "ModelGroupInfo | DeploymentModelListingInfo | tuple[int | None, int | None] | tuple[object, ...] | str | None" - ): + ) -> "ModelGroupInfo | DeploymentModelListingInfo | tuple[int | None, ...] | tuple[object, ...] | str | None": """ What the router knows about a model group. ``field``: @@ -894,6 +976,7 @@ class RouterRegistry: (were ``get_configured_display_name``, ``get_configured_mode``, ``get_configured_token_limits``, ``get_model_listing_info``) - ``service_tiers``: (was ``get_configured_service_tiers``) + - ``max_input_tokens``: each routable deployment's own ``model_info.max_input_tokens`` """ r: Final = self._router if field == "info": @@ -906,6 +989,8 @@ class RouterRegistry: return r._core_get_configured_mode(name) if field == "service_tiers": return r._core_get_configured_service_tiers(name, team_id=team_id) + if field == "max_input_tokens": + return r._core_get_configured_max_input_tokens(name, team_id=team_id) if field == "token_limits": return r._core_get_configured_token_limits(name) if field == "listing_info": @@ -1062,13 +1147,22 @@ PLAIN_SETTING_ATTRIBUTES: Final[frozenset[str]] = frozenset({"num_retries", "max ASSIGNABLE_ALIASES: Final[Mapping[str, str]] = MappingProxyType({"model_group_alias": "_core_model_group_alias"}) _MISSING: Final = object() +# The settings fields ``RouterSettings`` copies, so an in-place edit of what a read returns never +# reaches the router (only ``apply()`` changes settings). +_COPIED_SETTING_FIELDS: Final = ( + "fallbacks", + "context_window_fallbacks", + "content_policy_fallbacks", + "default_litellm_params", +) @dataclass(frozen=True) class RouterSettings: """ The router's configuration as one frozen snapshot (``settings()``). Fields hold the router's - own objects, not copies: mutating a list in here mutates the router's. + own objects, except the fallback lists and ``default_litellm_params``, which are copies: settings + change only through ``apply()``, so editing one of those in place changes nothing on any core. A field the router never set reads as ``None``. Each field has the type of the Router attribute it reads (``_core_``), the type the old @@ -1107,6 +1201,12 @@ class RouterSettings: _router: "Router | None" = field(default=None, repr=False, compare=False) _unset: frozenset[str] = field(default=frozenset(), repr=False, compare=False) + def __post_init__(self) -> None: + for name in _COPIED_SETTING_FIELDS: + value: object = getattr(self, name) # pyright: ignore[reportAny] # a settings field + if isinstance(value, list | dict): + object.__setattr__(self, name, copy.deepcopy(value)) # pyright: ignore[reportUnknownArgumentType] # a settings list or dict + @classmethod def of(cls, router: "Router") -> "RouterSettings": read: Final = {name: getattr(router, "_core_" + name, _MISSING) for name in SETTING_FIELDS} @@ -1176,16 +1276,16 @@ class RouterHealth: @staticmethod def is_blocked(deployment: "Deployment") -> bool: """Whether an admin paused this deployment (was ``is_deployment_blocked``).""" - from litellm.router_python_core import PythonCore + from litellm.router_rust.surface.health_routing import is_blocked as deployment_is_blocked - return PythonCore._core_is_deployment_blocked(deployment) + return deployment_is_blocked(deployment) @staticmethod def all_blocked(deployments: "Sequence[DeploymentTypedDict]") -> bool: """Whether every deployment in the list is paused (was ``are_all_deployments_blocked``).""" - from litellm.router_python_core import PythonCore + from litellm.router_rust.surface.health_routing import all_blocked as deployments_all_blocked - return PythonCore._core_are_all_deployments_blocked(deployments) + return deployments_all_blocked(deployments) def fully_blocked_model_names(self) -> set[str]: # mutable-ok: the core's type, a fresh set """Groups whose every deployment is paused (was ``get_fully_blocked_model_names``).""" @@ -1390,6 +1490,9 @@ class RoutingContext: def deployment_params(self, request: Mapping[str, object], deployment: "Deployment | None") -> Mapping[str, object]: return self._router._params_sent_to_deployment(request, deployment) + def default_litellm_params(self) -> Mapping[str, object]: + return self._router._active_default_litellm_params() + def settings(self) -> RouterSettings: return self._router.settings() diff --git a/litellm/router_attempt.py b/litellm/router_attempt.py new file mode 100644 index 00000000000..33e0a19c530 --- /dev/null +++ b/litellm/router_attempt.py @@ -0,0 +1,215 @@ +""" +One router attempt, as the host runs it: the request for the deployment the router core picked. + +The Rust router core picks a deployment and hands the attempt to its host; ``PythonHost`` builds +the keyword arguments for that one deployment here and calls ``litellm.`` with them. Nothing +here selects, retries, falls back or records cooldowns: the core does all of that. Nothing here +reads a Python router either, so this module outlives ``router_python_core.py``. +""" + +import re +import uuid +from collections.abc import Mapping +from types import MappingProxyType +from typing import Final + +from litellm.litellm_core_utils.batch_utils import get_router_metadata_variable_name +from litellm.litellm_core_utils.get_llm_provider_logic import inferred_provider +from litellm.litellm_core_utils.pattern_match_deployments import PatternMatchRouter +from litellm.litellm_core_utils.routing_common_utils import without_router_only_kwargs + +# Request keys the router reads to route the call; the deployment call never receives them. +ROUTING_KEYS: Final = frozenset( + { + "model", + "num_retries", + "disable_fallbacks", + "specific_deployment", + "_router_weights", + "_retry_skipped_deployment_ids", + "_target_order", + "model_group_retry_policy", + "fallbacks", + "context_window_fallbacks", + "content_policy_fallbacks", + "mock_testing_fallbacks", + "mock_testing_context_fallbacks", + "mock_testing_content_policy_fallbacks", + "mock_testing_rate_limit_error", + } +) + +# The positional parameters of each endpoint, in litellm's order: a call that passes them +# positionally is read back into keywords before it is routed. +POSITIONAL: Final = MappingProxyType( + { + "acompletion": ("model", "messages"), + "completion": ("model", "messages"), + "atext_completion": ("model", "prompt"), + "text_completion": ("model", "prompt"), + "aembedding": ("model", "input"), + "embedding": ("model", "input"), + "aimage_generation": ("prompt", "model"), + "image_generation": ("prompt", "model"), + "atranscription": ("model", "file"), + "aspeech": ("model", "input", "voice"), + "arerank": ("model", "query", "documents"), + "amoderation": ("input", "model"), + "aresponses": ("input", "model"), + "aanthropic_messages": (), + } +) + + +def request_from_call(op: str, args: tuple[object, ...], kwargs: Mapping[str, object]) -> Mapping[str, object]: + """The call's arguments as one keyword request. Raises ``TypeError`` like the endpoint would.""" + names: Final = POSITIONAL.get(op, ()) + if len(args) > len(names): + raise TypeError(f"{op}() takes {len(names)} positional arguments but {len(args)} were given") + request: Final = dict(kwargs) + for name, value in zip(names, args, strict=False): + if name in request: + raise TypeError(f"{op}() got multiple values for argument {name!r}") + request[name] = value + return request + + +# Endpoints the Python router serves through ``_ageneric_api_call_with_fallbacks``, which writes +# the routing metadata under ``litellm_metadata``. +_GENERIC_API_OPS: Final = frozenset({"aanthropic_messages", "aresponses"}) + + +def metadata_field(op: str) -> str: + """``metadata`` or ``litellm_metadata``: where the router writes what it routed the call as.""" + return "litellm_metadata" if op in _GENERIC_API_OPS else get_router_metadata_variable_name(function_name=op) + + +def prepare_call(op: str, request: Mapping[str, object], model_group_alias: str | None) -> Mapping[str, object]: + """What the router adds to a request once, before its first attempt + (``_update_kwargs_before_fallbacks``): a trace id and the model group it was asked for.""" + field: Final = metadata_field(op) + metadata: Final = dict(_as_mapping(request.get(field))) + metadata.update({"model_group": request.get("model"), "model_group_alias": model_group_alias}) + return {**request, "litellm_trace_id": request.get("litellm_trace_id") or str(uuid.uuid4()), field: metadata} + + +def _wildcard_match(pattern: object, requested: str) -> "re.Match[str] | None": + if not isinstance(pattern, str) or "*" not in pattern: + return None + regex: Final = PatternMatchRouter().pattern_to_regex(pattern) + return re.match(regex, requested) or re.match(regex, f"{inferred_provider(requested)}/{requested}") + + +def for_requested_model(deployment: Mapping[str, object], requested: str | None) -> Mapping[str, object]: + """A wildcard deployment as the router serves ``requested`` through it: its ``model`` with + the wildcards filled in from the requested name (``PatternMatchRouter.route``), by the team's + public pattern (``_core_team_pattern_routers``) or its own. Any other deployment comes back + unchanged.""" + params: Final = _as_mapping(deployment.get("litellm_params")) + model: Final = params.get("model") + if requested is None or not isinstance(model, str): + return deployment + public_name: Final = _as_mapping(deployment.get("model_info")).get("team_public_model_name") + match: Final = _wildcard_match(public_name, requested) or _wildcard_match(deployment.get("model_name"), requested) + if match is None: + return deployment + return { + **deployment, + "litellm_params": {**params, "model": PatternMatchRouter.set_deployment_model_name(match, model)}, + } + + +def attempt_kwargs( + op: str, + request: Mapping[str, object], + deployment: Mapping[str, object], + *, + model_group: str, + default_litellm_params: Mapping[str, object], + timeout: float | None, +) -> Mapping[str, object]: + """The keyword arguments for ``litellm.`` against one deployment + (``_update_kwargs_with_deployment`` and the call sites that merge ``litellm_params``).""" + params: Final = _as_mapping(deployment.get("litellm_params")) + model_info: Final = _model_info_for(request, deployment, model_group) + field: Final = metadata_field(op) + metadata: Final = dict(_as_mapping(request.get(field))) + metadata.update( + { + "model_group": model_group, + "deployment": params.get("model"), + "model_info": model_info, + "api_base": params.get("api_base"), + "deployment_model_name": deployment.get("model_name"), + } + ) + tags: Final = _as_list(params.get("tags")) + if tags: + merged: Final = list(_as_list(metadata.get("tags"))) + merged.extend(tag for tag in tags if tag not in merged) + metadata["tags"] = merged + call: Final = {key: value for key, value in request.items() if key not in ROUTING_KEYS} + for key, value in default_litellm_params.items(): + call.setdefault(key, value) + call[field] = metadata + call["model_info"] = model_info + if "timeout" not in call: + deployment_timeout: Final = params.get("timeout") + chosen: Final = deployment_timeout if deployment_timeout is not None else timeout + if chosen is not None: + call["timeout"] = chosen + return without_router_only_kwargs({**params, **call, "model": params.get("model")}) + + +def _model_info_for( + request: Mapping[str, object], deployment: Mapping[str, object], model_group: str +) -> dict[str, object]: # mutable-ok: a fresh dict for the call + """The deployment's ``model_info``, or, for a request carrying its own credentials, the + request-scoped deployment's (``_handle_clientside_credential``): its own stable id, and the + configured deployment's id as ``original_model_id``.""" + from litellm.litellm_core_utils import clientside_credential_handler as clientside + from litellm.router_api import deployment_id + + model_info: Final = dict(_as_mapping(deployment.get("model_info"))) + if not clientside.is_clientside_credential(request_kwargs=dict(request)): # pyright: ignore[reportUnknownMemberType] # an untyped helper + return model_info + dynamic: Final = _as_mapping( + clientside.get_dynamic_litellm_params( # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # an untyped helper + litellm_params=dict(_as_mapping(deployment.get("litellm_params"))), request_kwargs=dict(request) + ) + ) + original: Final = model_info.get("id") + model_info["id"] = deployment_id(model_group, dynamic) + model_info["original_model_id"] = original + return model_info + + +def stamp_attempt_error(error: BaseException, deployment: Mapping[str, object]) -> None: + """What the router stamps on a failed attempt's error: the deployment's own ``num_retries`` + (``_set_deployment_num_retries_on_exception``) and its id (``failed_deployment_id``).""" + params: Final = _as_mapping(deployment.get("litellm_params")) + if getattr(error, "num_retries", None) is None and params.get("num_retries") is not None: + try: + error.num_retries = int(str(params["num_retries"])) # pyright: ignore[reportAttributeAccessIssue] # the router stamps the same attribute # rebind-ok: the router stamps the error in place + except ValueError: + pass + deployment_id: Final = _as_mapping(deployment.get("model_info")).get("id") + if deployment_id and not getattr(error, "failed_deployment_id", None): + try: + error.failed_deployment_id = deployment_id # pyright: ignore[reportAttributeAccessIssue] # the router stamps the same attribute # rebind-ok: see above + except AttributeError: + pass + + +def _as_mapping(value: object) -> Mapping[str, object]: + if isinstance(value, Mapping): + entries: Final[Mapping[object, object]] = value # pyright: ignore[reportUnknownVariableType] # a request's untyped mapping + return {str(key): item for key, item in entries.items()} + return MappingProxyType({}) + + +def _as_list(value: object) -> list[object]: # mutable-ok: a fresh list + if isinstance(value, list): + items: Final[list[object]] = value # pyright: ignore[reportUnknownVariableType] # a request's untyped list # mutable-ok: read, then copied + return list(items) + return [] diff --git a/litellm/router_config.py b/litellm/router_config.py index 75c79068191..36154af296c 100644 --- a/litellm/router_config.py +++ b/litellm/router_config.py @@ -79,7 +79,12 @@ def detached(value: object) -> object: def build_router_config(arguments: Mapping[str, object]) -> RouterConfig: - """The constructor arguments, detached from the caller's objects: settings are static.""" + """The constructor arguments, detached from the caller's objects: settings are static. + + A bool `cooldown_time` is refused: `True` is not a number of seconds, and + reading it as 1 s or as the default would both be a guess.""" + if isinstance(arguments.get("cooldown_time"), bool): + raise TypeError("Router cooldown_time must be a number of seconds, not a bool") return RouterConfig(arguments=MappingProxyType({name: detached(value) for name, value in arguments.items()})) diff --git a/litellm/router_core.py b/litellm/router_core.py index acbe82a0643..c077b3f0015 100644 --- a/litellm/router_core.py +++ b/litellm/router_core.py @@ -1,14 +1,16 @@ """ ``RouterCore``: the interface ``litellm.Router`` delegates to, and ``make_core``, which picks one. -``PythonCore`` (``litellm/router_python_core.py``) is today's routing logic. The Rust core -(litellm-rust/crates/router-core) implements the same operations. The core is picked once, when -the router is built, from its ``RouterConfig``. +``PythonCore`` (``litellm/router_python_core.py``) is today's routing logic. ``RustCore`` +(``litellm/router_rust/core.py`` over litellm-rust/crates/router-core) is a separate implementation +that reaches outside itself only through its host; it does not use ``PythonCore``. The core is +picked once, when the router is built, from its ``RouterConfig``. """ from collections.abc import Mapping -from typing import TYPE_CHECKING, Protocol, runtime_checkable +from typing import TYPE_CHECKING, Final, Protocol, runtime_checkable +from litellm._logging import verbose_router_logger from litellm.router_config import RouterConfig if TYPE_CHECKING: @@ -20,7 +22,6 @@ if TYPE_CHECKING: RouterSettings, RoutingObservers, ) - from litellm.router_python_core import PythonCore from litellm.router_python_host import PythonHost from litellm.types.router import CustomRoutingStrategyBase @@ -50,7 +51,26 @@ class RouterCore(Protocol): def retire(self) -> None: ... -def make_core(config: RouterConfig, host: "PythonHost", core_class: "type[PythonCore] | None" = None) -> RouterCore: +def make_core(config: RouterConfig, host: "PythonHost") -> RouterCore: + """ + The Rust core when the route catalog's router rule allows it and the Rust core serves this + config, else the Python core. Decided once, for the router's life, from the config alone: the + Rust core never builds, wraps or falls back to a Python core. + """ from litellm.router_python_core import PythonCore + from litellm.rust_bridge.catalog import Route, RouteContext, decision + from litellm.rust_bridge.configuration import Decision - return (core_class or PythonCore)(**config.arguments, _host=host) # pyright: ignore[reportArgumentType] # the arguments were bound against PythonCore's own signature + chosen: Final = decision(RouteContext(Route.ROUTER)) + if chosen is not Decision.PYTHON: + from litellm.router_rust.core import RustCore + from litellm.rust_bridge._native import RustBridgeDeclined + + try: + return RustCore.build(config, host) # pyright: ignore[reportReturnType] # RustCore serves the RouterCore entry points; other members raise RustCoreUnsupported + except RustBridgeDeclined as declined: + # A config the Rust core cannot take keeps the router on Python while both cores exist. + if chosen is Decision.RUST_REQUIRED: + raise + verbose_router_logger.info("Router served by the Python core: %s", declined) + return PythonCore(**config.arguments, _host=host) # pyright: ignore[reportArgumentType] # the arguments were bound against PythonCore's own signature diff --git a/litellm/router_deprecated.py b/litellm/router_deprecated.py index 83a1251d3c0..9d915fe0982 100644 --- a/litellm/router_deprecated.py +++ b/litellm/router_deprecated.py @@ -5,8 +5,10 @@ DeprecatedRouterMembers: the Router members that outside code used before the en entry points (``registry()``, ``settings()``, ``health()``, ``select()``, ``apply()``, ``observe()``, ``register_plugin()``, ``retire()``; see litellm/router_api.py). Every member here returns what it returned before, with the type it had before, and names its replacement in a -``DeprecationWarning``. Reads go to the same Router implementation (``Router._core_``) the -entry point uses; writes go through ``apply`` / ``aapply`` so the registry version moves. +``DeprecationWarning``. Reads go through that entry point, so they work on either router core +(Python or Rust) and, on the Python core, return the same ``_core_`` object as before. +Settings writes go through ``apply`` / ``aapply`` so the registry version moves; any other old +attribute write sets the core's ``_core_``, which each core keeps where its reads find it. Access from the router itself and from its own modules (``litellm.router*``) is not counted: those are the router's internals and move behind the core interface separately. Every other access @@ -17,21 +19,21 @@ deleted (planned about a month after the core swap). # pyright: reportPrivateUsage=false, reportMissingTypeArgument=false, reportUnknownParameterType=false # pyright: reportUnknownMemberType=false, reportUnknownVariableType=false, reportUnknownArgumentType=false # pyright: reportUnknownLambdaType=false -# This shim is part of the router (it reads Router's ``_core_*`` members, as Router's own methods do) +# This shim is part of the router (it writes Router's ``_core_*`` members, as Router's own methods do) # and repeats each old member's signature exactly, untyped parts included (``dict``, ``list``), so # callers keep the types they had. Typing those parts is the core's job, not the shim's. -import contextvars import functools import inspect import sys import warnings from collections import Counter -from collections.abc import Awaitable, Callable, Iterator, Mapping, Sequence +from collections.abc import Awaitable, Callable, Coroutine, Iterator, Mapping, Sequence from types import MappingProxyType -from typing import TYPE_CHECKING, Final, Generic, TypeVar, overload +from typing import TYPE_CHECKING, Final, Generic, ParamSpec, TypeVar, overload -from litellm.router_api import ASSIGNABLE_ALIASES, SETTING_FIELDS, ChangeSet +from litellm.router_api import ASSIGNABLE_ALIASES, SETTING_FIELDS, ChangeSet, RoutingContext +from litellm.router_strategy.least_busy import picks_reserve if TYPE_CHECKING: from typing import Any # noqa: TID251 # only to repeat two old signatures that had Any, unchanged @@ -39,6 +41,7 @@ if TYPE_CHECKING: from opentelemetry.trace import Span from litellm.caching.caching import RedisCache + from litellm.integrations.SlackAlerting.slack_alerting import SlackAlerting from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging from litellm.litellm_core_utils.ptu_shares import PTUTeamCeiling from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler @@ -58,6 +61,7 @@ if TYPE_CHECKING: from litellm.types.utils import ModelInfo as ModelMapInfo _T: Final = TypeVar("_T") +_P: Final = ParamSpec("_P") DEPRECATED_ROUTER_MEMBER_USES: Final[Counter[str]] = Counter() # mutable-ok: the live tally _note increments @@ -129,6 +133,9 @@ class _DeprecatedAttribute(Generic[_T]): _note(self.name, self.replacement) router: Final = _as_router(obj) try: + if obj.__dict__.get("_core") is None: + # No core yet (a Router made without __init__): the value written through this name. + return getattr(obj, "_core_" + self.name) # pyright: ignore[reportAny] # the pending write, as given return self.read(router) except AttributeError as e: raise _public_attribute_error(router, "_core_" + self.name, self.name, e) from None @@ -164,243 +171,186 @@ def _attr(replacement: str, read: Callable[["Router"], _T]) -> _DeprecatedAttrib return _DeprecatedAttribute(replacement, read) -# (id(router), member name) pairs whose subclass override is running in this context. -_OVERRIDES_RUNNING: Final[contextvars.ContextVar[frozenset[tuple[int, str]]]] = contextvars.ContextVar( - "router_overrides_running", default=frozenset() -) +def _without_reserving(lookup: Callable[_P, Awaitable[_T]]) -> Callable[_P, Coroutine[object, object, _T]]: + @functools.wraps(lookup) + async def looked_up( + *args: _P.args, + **kwargs: _P.kwargs, # kwargs-ok: forwards the wrapped lookup's ParamSpec unchanged + ) -> _T: + with picks_reserve(False): + return await lookup(*args, **kwargs) + + return looked_up -def _override_key(router: object, name: str) -> tuple[int, str]: - """The running-override key for ``router``: a Router and its core share one, so an old member - entered on the Router is seen by the override routing that runs on the core.""" - core: Final = getattr(router, "__dict__", {}).get("_core") - return (id(router if core is None else core), name) - - -def _enter_override(name: str, override: Callable[..., object]) -> Callable[..., object]: +def _async_picker(router: "Router") -> Callable[..., Awaitable[object]]: """ - A direct call of a subclass override (``router.()``) marks it running, so its - ``super().()`` reaches the parent once instead of re-entering the override through - ``_core_``. + The router's async pick (the old ``async_get_available_deployment`` attribute). A core that + keeps its pick as a member (the Python core's, or one assigned through this attribute) returns + that member, so a patched pick reads back as patched; any other core picks through ``select``. """ - if inspect.iscoroutinefunction(override): - async_override: Final[Callable[..., Awaitable[object]]] = override + member: Final[object] = getattr(router, "_core_async_get_available_deployment", None) + if callable(member): + return member # pyright: ignore[reportReturnType] # the core's own async pick - @functools.wraps(override) - async def entered_async( - router: object, - *args: object, - **kwargs: object, # kwargs-ok: passes the override's arguments through unchanged - ) -> object: - token: Final = _OVERRIDES_RUNNING.set(_OVERRIDES_RUNNING.get() | {_override_key(router, name)}) - try: - return await async_override(router, *args, **kwargs) - finally: - _OVERRIDES_RUNNING.reset(token) - - return entered_async - - @functools.wraps(override) - def entered( - router: object, - *args: object, - **kwargs: object, # kwargs-ok: passes the override's arguments through unchanged + async def async_get_available_deployment( + model: str, + request_kwargs: dict, # mutable-ok: the old parameter type, unchanged + messages: list[dict[str, str]] | None = None, # mutable-ok: the old parameter type, unchanged + input: str | list | None = None, # mutable-ok: the old parameter type, unchanged + specific_deployment: bool | None = False, ) -> object: - token: Final = _OVERRIDES_RUNNING.set(_OVERRIDES_RUNNING.get() | {_override_key(router, name)}) - try: - return override(router, *args, **kwargs) - finally: - _OVERRIDES_RUNNING.reset(token) + return await router.select( + model, request_kwargs, messages=messages, input=input, specific_deployment=specific_deployment + ) - return entered + return async_get_available_deployment -def _private_alias(name: str, member: Callable[..., object]) -> Callable[..., object]: +def _unreserved_picker(router: "Router") -> Callable[..., Awaitable[object]]: + """``_async_picker``, picking without holding a least-busy reservation (a lookup makes no + call). A pick assigned through the attribute reads back as the object assigned.""" + picker: Final = _async_picker(router) + if inspect.ismethod(picker) or picker.__name__ == "async_get_available_deployment": + return _without_reserving(picker) + return picker + + +def _slack_alerting_logger(router: "Router") -> "SlackAlerting": + """``observe().slack_alerting_logger``; a router without one has no such attribute, as before.""" + logger: Final = router.observe().slack_alerting_logger + if logger is None: + raise AttributeError( + f"'{type(router).__name__}' object has no attribute 'slack_alerting_logger'", + name="slack_alerting_logger", + obj=router, + ) + return logger + + +def _run_ready(step: Coroutine[object, object, _T]) -> _T: """ - A private alias of an old member (``_get_all_deployments``). It was bound to Router's own - method, so it never reached a subclass override of ``name``, and still doesn't. + The result of a coroutine that finishes without suspending: ``select(kind='pass_through')`` + picks synchronously on every core, so the old synchronous member can return its result. """ - return _enter_override(name, member) - - -def _route_override(cls: type, name: str, override: Callable[..., object]) -> Callable[..., object]: - """ - Make the router's own calls to ``_core_`` reach a subclass override of ````. - - When the override calls ``super().()``, the call comes back to ``_core_``; it is - then sent on to the parent's implementation instead of back into the override. - """ - core: Final = "_core_" + name - - def parent(router: object) -> Callable[..., object]: - return getattr(super(cls, router), core) - - if inspect.iscoroutinefunction(override): - async_override: Final[Callable[..., Awaitable[object]]] = override - - @functools.wraps(override) - async def routed_async( - router: object, - *args: object, - **kwargs: object, # kwargs-ok: passes the override's arguments through unchanged - ) -> object: - key: Final = _override_key(router, name) - running: Final = _OVERRIDES_RUNNING.get() - if key in running: - parent_async: Final[Callable[..., Awaitable[object]]] = getattr(super(cls, router), core) - return await parent_async(*args, **kwargs) - token: Final = _OVERRIDES_RUNNING.set(running | {key}) - try: - return await async_override(router, *args, **kwargs) - finally: - _OVERRIDES_RUNNING.reset(token) - - return routed_async - - @functools.wraps(override) - def routed( - router: object, - *args: object, - **kwargs: object, # kwargs-ok: passes the override's arguments through unchanged - ) -> object: - key: Final = _override_key(router, name) - running: Final = _OVERRIDES_RUNNING.get() - if key in running: - return parent(router)(*args, **kwargs) - token: Final = _OVERRIDES_RUNNING.set(running | {key}) - try: - return override(router, *args, **kwargs) - finally: - _OVERRIDES_RUNNING.reset(token) - - return routed + try: + step.send(None) + except StopIteration as done: + return done.value # pyright: ignore[reportAny] # the coroutine's own result + step.close() + raise RuntimeError("select(kind='pass_through') suspended; it must pick without awaiting") class DeprecatedRouterMembers: """Old Router members, kept for about a month. Each names its replacement.""" - def __init_subclass__(cls, **kwargs: object) -> None: # kwargs-ok: class keywords, passed on to super() - # A Router subclass that overrides an old member (say async_pre_routing_hook) keeps - # having its override called by the router, which now calls _core_ internally. - super().__init_subclass__(**kwargs) - for name, value in list(vars(cls).items()): - if ( - name.startswith("_core_") - or name not in vars(DeprecatedRouterMembers) - or not hasattr(cls, "_core_" + name) - ): - continue - if isinstance(value, staticmethod): - # Its super() call reaches the old member here, which calls Router's own implementation. - setattr(cls, "_core_" + name, value) - elif inspect.isfunction(value): - setattr(cls, "_core_" + name, _route_override(cls, name, value)) - setattr(cls, name, _enter_override(name, value)) - # -- registry: attributes -------------------------------------------------------------------- - model_list = _attr("registry().all()", lambda r: r._core_model_list) - model_names = _attr("registry().names(kind='group_set')", lambda r: r._core_model_names) - deployment_names = _attr("registry().names(kind='deployment_names')", lambda r: r._core_deployment_names) - team_public_model_names = _attr("registry().names(kind='team_public')", lambda r: r._core_team_public_model_names) + model_list = _attr("registry().all()", lambda r: r.registry().all()) + model_names = _attr("registry().names(kind='group_set')", lambda r: r.registry().names(kind="group_set")) + deployment_names = _attr( + "registry().names(kind='deployment_names')", lambda r: r.registry().names(kind="deployment_names") + ) + team_public_model_names = _attr( + "registry().names(kind='team_public')", lambda r: r.registry().names(kind="team_public") + ) model_name_to_deployment_indices = _attr( - "registry().index('model_name')", lambda r: r._core_model_name_to_deployment_indices + "registry().index('model_name')", lambda r: r.registry().index("model_name") ) team_model_to_deployment_indices = _attr( - "registry().index('team_model')", lambda r: r._core_team_model_to_deployment_indices + "registry().index('team_model')", lambda r: r.registry().index("team_model") ) cached_deployment_model_info = _attr( "registry().deployment_model_info(id, model_name, cached=True)", - lambda r: r._core_cached_deployment_model_info, + lambda r: r.registry().deployment_model_info_cache(), ) - model_group_alias = _attr("registry().aliases()", lambda r: r._core_model_group_alias) - pattern_router = _attr("registry().patterns()", lambda r: r._core_pattern_router) - team_pattern_routers = _attr("registry().patterns(team=True)", lambda r: r._core_team_pattern_routers) - routing_groups = _attr("registry().routing_groups()", lambda r: r._core_routing_groups) + model_group_alias = _attr("registry().aliases()", lambda r: r.registry().aliases()) + pattern_router = _attr("registry().patterns()", lambda r: r.registry().patterns()) + team_pattern_routers = _attr("registry().patterns(team=True)", lambda r: r.registry().patterns(team=True)) + routing_groups = _attr("registry().routing_groups()", lambda r: r.registry().routing_groups()) _routing_groups = routing_groups - auto_routers = _attr("registry().plugins('auto')", lambda r: r._core_auto_routers) - complexity_routers = _attr("registry().plugins('complexity')", lambda r: r._core_complexity_routers) - quality_routers = _attr("registry().plugins('quality')", lambda r: r._core_quality_routers) - adaptive_routers = _attr("registry().plugins('adaptive')", lambda r: r._core_adaptive_routers) - routing_plugins = _attr("registry().plugins('routing')", lambda r: r._core_routing_plugins) + auto_routers = _attr("registry().plugins('auto')", lambda r: r.registry().plugins("auto")) + complexity_routers = _attr("registry().plugins('complexity')", lambda r: r.registry().plugins("complexity")) + quality_routers = _attr("registry().plugins('quality')", lambda r: r.registry().plugins("quality")) + adaptive_routers = _attr("registry().plugins('adaptive')", lambda r: r.registry().plugins("adaptive")) + routing_plugins = _attr("registry().plugins('routing')", lambda r: r.registry().plugins("routing")) prompt_caching_pin_cache = _attr( - "registry().plugins('prompt_caching_pins')", lambda r: r._core_prompt_caching_pin_cache + "registry().plugins('prompt_caching_pins')", lambda r: r.registry().plugins("prompt_caching_pins") ) # -- health and selection: attributes -------------------------------------------------------- - cache = _attr("health().store", lambda r: r._core_cache) - cooldown_cache = _attr("health().cooldowns", lambda r: r._core_cooldown_cache) - health_state_cache = _attr("health().health_checks", lambda r: r._core_health_state_cache) - deployment_latency_map = _attr("health().latency", lambda r: r._core_deployment_latency_map) - async_get_available_deployment = _attr( - "select(model, request_kwargs)", - lambda r: r._core_async_get_available_deployment, - ) + cache = _attr("health().store", lambda r: r.health().store) + cooldown_cache = _attr("health().cooldowns", lambda r: r.health().cooldowns) + health_state_cache = _attr("health().health_checks", lambda r: r.health().health_checks) + deployment_latency_map = _attr("health().latency", lambda r: r.health().latency) + async_get_available_deployment = _attr("select(model, request_kwargs)", lambda r: _unreserved_picker(r)) # -- observers ------------------------------------------------------------------------------ - slack_alerting_logger = _attr("observe().slack_alerting_logger", lambda r: r._core_slack_alerting_logger) + slack_alerting_logger = _attr("observe().slack_alerting_logger", _slack_alerting_logger) # -- settings ------------------------------------------------------------------------------- - routing_strategy = _setting("routing_strategy", lambda r: r._core_routing_strategy) - context_window_fallbacks = _setting("context_window_fallbacks", lambda r: r._core_context_window_fallbacks) - content_policy_fallbacks = _setting("content_policy_fallbacks", lambda r: r._core_content_policy_fallbacks) - default_deployment = _setting("default_deployment", lambda r: r._core_default_deployment) - default_litellm_params = _setting("default_litellm_params", lambda r: r._core_default_litellm_params) + routing_strategy = _setting("routing_strategy", lambda r: r.settings().routing_strategy) + context_window_fallbacks = _setting("context_window_fallbacks", lambda r: r.settings().context_window_fallbacks) + content_policy_fallbacks = _setting("content_policy_fallbacks", lambda r: r.settings().content_policy_fallbacks) + default_deployment = _setting("default_deployment", lambda r: r.settings().default_deployment) + default_litellm_params = _setting("default_litellm_params", lambda r: r.settings().default_litellm_params) default_max_parallel_requests = _setting( - "default_max_parallel_requests", lambda r: r._core_default_max_parallel_requests + "default_max_parallel_requests", lambda r: r.settings().default_max_parallel_requests + ) + cooldown_time = _setting("cooldown_time", lambda r: r.settings().cooldown_time) + allowed_fails = _setting("allowed_fails", lambda r: r.settings().allowed_fails) + allowed_fails_policy = _setting("allowed_fails_policy", lambda r: r.settings().allowed_fails_policy) + disable_cooldowns = _setting("disable_cooldowns", lambda r: r.settings().disable_cooldowns) + enable_pre_call_checks = _setting("enable_pre_call_checks", lambda r: r.settings().enable_pre_call_checks) + enable_health_check_routing = _setting( + "enable_health_check_routing", lambda r: r.settings().enable_health_check_routing ) - cooldown_time = _setting("cooldown_time", lambda r: r._core_cooldown_time) - allowed_fails = _setting("allowed_fails", lambda r: r._core_allowed_fails) - allowed_fails_policy = _setting("allowed_fails_policy", lambda r: r._core_allowed_fails_policy) - disable_cooldowns = _setting("disable_cooldowns", lambda r: r._core_disable_cooldowns) - enable_pre_call_checks = _setting("enable_pre_call_checks", lambda r: r._core_enable_pre_call_checks) - enable_health_check_routing = _setting("enable_health_check_routing", lambda r: r._core_enable_health_check_routing) health_check_ignore_transient_errors = _setting( - "health_check_ignore_transient_errors", lambda r: r._core_health_check_ignore_transient_errors + "health_check_ignore_transient_errors", lambda r: r.settings().health_check_ignore_transient_errors ) background_health_check_model_groups = _setting( - "background_health_check_model_groups", lambda r: r._core_background_health_check_model_groups + "background_health_check_model_groups", lambda r: r.settings().background_health_check_model_groups ) - enable_tag_filtering = _setting("enable_tag_filtering", lambda r: r._core_enable_tag_filtering) - tag_filtering_match_any = _setting("tag_filtering_match_any", lambda r: r._core_tag_filtering_match_any) - tag_routing_prefix = _setting("tag_routing_prefix", lambda r: r._core_tag_routing_prefix) - router_general_settings = _setting("router_general_settings", lambda r: r._core_router_general_settings) - provider_budget_config = _setting("provider_budget_config", lambda r: r._core_provider_budget_config) + enable_tag_filtering = _setting("enable_tag_filtering", lambda r: r.settings().enable_tag_filtering) + tag_filtering_match_any = _setting("tag_filtering_match_any", lambda r: r.settings().tag_filtering_match_any) + tag_routing_prefix = _setting("tag_routing_prefix", lambda r: r.settings().tag_routing_prefix) + router_general_settings = _setting("router_general_settings", lambda r: r.settings().router_general_settings) + provider_budget_config = _setting("provider_budget_config", lambda r: r.settings().provider_budget_config) provider_default_deployment_ids = _setting( - "provider_default_deployment_ids", lambda r: r._core_provider_default_deployment_ids + "provider_default_deployment_ids", lambda r: r.settings().provider_default_deployment_ids ) - fallback_access_check = _setting("fallback_access_check", lambda r: r._core_fallback_access_check) - fallback_budget_check = _setting("fallback_budget_check", lambda r: r._core_fallback_budget_check) + fallback_access_check = _setting("fallback_access_check", lambda r: r.settings().fallback_access_check) + fallback_budget_check = _setting("fallback_budget_check", lambda r: r.settings().fallback_budget_check) # These three are declared with the attribute type Router gave them rather than the descriptor's: # protocols in router_utils and the proxy match Router on them, and protocol matching does not # see through a descriptor. Reads and writes still go through _setting at runtime. fallbacks: list | list[dict[str, list[str] | list | None]] | None = _setting( # pyright: ignore[reportAssignmentType] # see above # mutable-ok: the old type - "fallbacks", lambda r: r._core_fallbacks + "fallbacks", lambda r: r.settings().fallbacks ) kubernetes_pod_discovery: "KubernetesPodDiscovery" = _setting( # pyright: ignore[reportAssignmentType] # see above - "kubernetes_pod_discovery", lambda r: r._core_kubernetes_pod_discovery + "kubernetes_pod_discovery", lambda r: r.settings().kubernetes_pod_discovery ) search_tools: "list[SearchToolTypedDict]" = _setting( # pyright: ignore[reportAssignmentType] # see above # mutable-ok: the old type - "search_tools", lambda r: r._core_search_tools + "search_tools", lambda r: r.settings().search_tools ) - guardrail_list = _setting("guardrail_list", lambda r: r._core_guardrail_list) - cache_responses = _setting("cache_responses", lambda r: r._core_cache_responses) + guardrail_list = _setting("guardrail_list", lambda r: r.settings().guardrail_list) + cache_responses = _setting("cache_responses", lambda r: r.settings().cache_responses) # -- registry: one deployment --------------------------------------------------------------- def get_deployment(self, model_id: str) -> "Deployment | None": _note("get_deployment", "registry().deployment(id)") - return _as_router(self)._core_get_deployment(model_id=model_id) + return _as_router(self).registry().deployment(model_id) def has_model_id(self, candidate_id: str) -> bool: _note("has_model_id", "registry().has_deployment(id)") - return _as_router(self)._core_has_model_id(candidate_id) + return _as_router(self).registry().has_deployment(candidate_id) def get_model_info(self, id: str) -> dict | None: # mutable-ok: the old return type, unchanged _note("get_model_info", "registry().deployment_dict(id)") - return _as_router(self)._core_get_model_info(id=id) + return _as_router(self).registry().deployment_dict(id) def get_deployment_model_info(self, model_id: str, model_name: str) -> "ModelMapInfo | None": _note("get_deployment_model_info", "registry().deployment_model_info(id, model_name)") - return _as_router(self)._core_get_deployment_model_info(model_id=model_id, model_name=model_name) + return _as_router(self).registry().deployment_model_info(model_id, model_name) @overload def get_router_model_info( @@ -420,62 +370,56 @@ class DeprecatedRouterMembers: id: str | None = None, ) -> "ModelMapInfo": _note("get_router_model_info", "registry().router_model_info(...)") - router: Final = _as_router(self) - # The core's overloads split (deployment, id) by which one is None; this forwards either form unchanged. - return router._core_get_router_model_info( # pyright: ignore[reportCallIssue] # see above - deployment=deployment, # pyright: ignore[reportArgumentType] # see above - received_model_name=received_model_name, - id=id, # pyright: ignore[reportArgumentType] # see above - ) + return _as_router(self).registry().router_model_info(deployment, received_model_name, id) def get_discovered_model_info(self, model_id: str | None) -> Mapping[str, int]: _note("get_discovered_model_info", "registry().discovered_model_info(id)") - return _as_router(self)._core_get_discovered_model_info(model_id) + return _as_router(self).registry().discovered_model_info(model_id) # -- registry: many deployments ------------------------------------------------------------- def get_model_list( self, model_name: str | None = None, team_id: str | None = None ) -> "list[DeploymentTypedDict] | None": # mutable-ok: the old return type, unchanged _note("get_model_list", "registry().deployments(model_name, team_id=...)") - return _as_router(self)._core_get_model_list(model_name=model_name, team_id=team_id) + return _as_router(self).registry().deployments(model_name, team_id=team_id) def get_all_deployments( self, model_name: str, model_alias: str | None = None, team_id: str | None = None ) -> "list[DeploymentTypedDict]": # mutable-ok: the old return type, unchanged _note("get_all_deployments", "registry().deployments(model_name, source='all')") - return _as_router(self)._core_get_all_deployments( - model_name=model_name, model_alias=model_alias, team_id=team_id + return ( + _as_router(self).registry().deployments(model_name, source="all", model_alias=model_alias, team_id=team_id) ) - _get_all_deployments = _private_alias("get_all_deployments", get_all_deployments) + _get_all_deployments = get_all_deployments def config_deployments(self) -> Iterator[Mapping[str, object]]: _note("config_deployments", "registry().deployments(source='config')") - return _as_router(self)._core_config_deployments() + return _as_router(self).registry().deployments(source="config") def deployments_named(self, model_name: str) -> "tuple[DeploymentTypedDict, ...] | None": _note("deployments_named", "registry().deployments(model_name, source='named')") - return _as_router(self)._core_deployments_named(model_name) + return _as_router(self).registry().deployments(model_name, source="named") def get_model_list_from_model_alias( self, model_name: str | None = None ) -> "list[DeploymentTypedDict]": # mutable-ok: the old return type, unchanged _note("get_model_list_from_model_alias", "registry().deployments(model_name, source='alias')") - return _as_router(self)._core_get_model_list_from_model_alias(model_name=model_name) + return _as_router(self).registry().deployments(model_name, source="alias") def get_model_list_from_routing_groups(self, model_name: str | None = None) -> "Sequence[DeploymentTypedDict]": _note("get_model_list_from_routing_groups", "registry().deployments(model_name, source='routing_groups')") - return _as_router(self)._core_get_model_list_from_routing_groups(model_name=model_name) + return _as_router(self).registry().deployments(model_name, source="routing_groups") def get_model_list_of_routed_group( self, model_group: str ) -> "list[DeploymentTypedDict]": # mutable-ok: the old return type, unchanged _note("get_model_list_of_routed_group", "registry().deployments(model_group, source='routed_group')") - return _as_router(self)._core_get_model_list_of_routed_group(model_group) + return _as_router(self).registry().deployments(model_group, source="routed_group") def wildcard_route_deployments(self, model: str, team_id: str | None) -> Sequence[Mapping[str, object]]: _note("wildcard_route_deployments", "registry().deployments(model, source='wildcard')") - return _as_router(self)._core_wildcard_route_deployments(model, team_id) + return _as_router(self).registry().deployments(model, source="wildcard", team_id=team_id) def get_routable_deployments( self, @@ -486,17 +430,21 @@ class DeprecatedRouterMembers: _note( "get_routable_deployments", "registry().deployments(model, source='routable', request=..., call_type=...)" ) - return _as_router(self)._core_get_routable_deployments(model, request_kwargs, call_type) + return ( + _as_router(self) + .registry() + .deployments(model, source="routable", request=request_kwargs, call_type=call_type) + ) def get_deployment_by_model_group_name(self, model_group_name: str) -> "Deployment | None": _note("get_deployment_by_model_group_name", "registry().deployments(name, source='first_in_group')") - return _as_router(self)._core_get_deployment_by_model_group_name(model_group_name=model_group_name) + return _as_router(self).registry().deployments(model_group_name, source="first_in_group") def deployments_for_request( self, model: str, request_kwargs: Mapping[str, object] ) -> "Sequence[DeploymentTypedDict]": _note("deployments_for_request", "registry().deployments(model, source='for_request', request=...)") - return _as_router(self)._core_deployments_for_request(model, request_kwargs) + return _as_router(self).registry().deployments(model, source="for_request", request=request_kwargs) def should_include_deployment( self, @@ -505,135 +453,137 @@ class DeprecatedRouterMembers: team_id: str | None = None, ) -> bool: _note("should_include_deployment", "registry().includes(deployment, model_name=..., team_id=...)") - return _as_router(self)._core_should_include_deployment(model_name=model_name, model=model, team_id=team_id) + return _as_router(self).registry().includes(model, model_name=model_name, team_id=team_id) @staticmethod def deployment_usable_by_team(model: "Mapping[str, object] | Deployment", team_id: str | None) -> bool: _note("deployment_usable_by_team", "registry().includes(deployment, team_id=...)") - from litellm.router_python_core import PythonCore + from litellm.router_api import deployment_usable_by_team as usable_by_team - return PythonCore._core_deployment_usable_by_team(model, team_id) + return usable_by_team(model, team_id) _deployment_usable_by_team = deployment_usable_by_team # -- registry: names ------------------------------------------------------------------------- def get_model_names(self, team_id: str | None = None) -> list[str]: # mutable-ok: the old return type, unchanged _note("get_model_names", "registry().names(team_id=...)") - return _as_router(self)._core_get_model_names(team_id=team_id) + return _as_router(self).registry().names(team_id=team_id) def get_model_ids( self, model_name: str | None = None, exclude_team_models: bool = False ) -> list[str]: # mutable-ok: the old return type, unchanged _note("get_model_ids", "registry().names(model_name, kind='ids')") - return _as_router(self)._core_get_model_ids(model_name=model_name, exclude_team_models=exclude_team_models) + return _as_router(self).registry().names(model_name, kind="ids", exclude_team_models=exclude_team_models) def resolved_litellm_models( self, model_name: str, team_id: str | None = None, *, use_base_model: bool = False ) -> tuple[str, ...]: _note("resolved_litellm_models", "registry().names(model_name, kind='litellm_models' or 'litellm_base_models')") - return _as_router(self)._core_resolved_litellm_models( - model_name, team_id=team_id, use_base_model=use_base_model + return ( + _as_router(self) + .registry() + .names(model_name, kind="litellm_base_models" if use_base_model else "litellm_models", team_id=team_id) ) def wildcard_routed_models(self, model: str, team_id: str | None) -> frozenset[str]: _note("wildcard_routed_models", "registry().names(model, kind='wildcard')") - return _as_router(self)._core_wildcard_routed_models(model, team_id) + return _as_router(self).registry().names(model, kind="wildcard", team_id=team_id) def get_candidate_model_ids_for_route(self, model: str, team_id: str | None = None) -> frozenset[str]: _note("get_candidate_model_ids_for_route", "registry().names(model, kind='route_candidates')") - return _as_router(self)._core_get_candidate_model_ids_for_route(model, team_id=team_id) + return _as_router(self).registry().names(model, kind="route_candidates", team_id=team_id) # -- registry: resolving names --------------------------------------------------------------- def routable_model_group(self, model_name: str) -> str: _note("routable_model_group", "registry().resolve(name)") - return _as_router(self)._core_routable_model_group(model_name) + return _as_router(self).registry().resolve(model_name) def get_model_from_alias(self, model: str) -> str | None: _note("get_model_from_alias", "registry().resolve(name, kind='alias')") - return _as_router(self)._core_get_model_from_alias(model=model) + return _as_router(self).registry().resolve(model, kind="alias") - _get_model_from_alias = _private_alias("get_model_from_alias", get_model_from_alias) + _get_model_from_alias = get_model_from_alias def resolve_served_model_name(self, model_name: str, served_model: str) -> str: _note("resolve_served_model_name", "registry().resolve(name, kind='served', served_model=...)") - return _as_router(self)._core_resolve_served_model_name(model_name, served_model) + return _as_router(self).registry().resolve(model_name, kind="served", served_model=served_model) def resolve_model_name_from_model_id( self, model_id: str | None, custom_llm_provider: str | None = None ) -> str | None: _note("resolve_model_name_from_model_id", "registry().resolve(id, kind='from_id')") - return _as_router(self)._core_resolve_model_name_from_model_id( - model_id, custom_llm_provider=custom_llm_provider - ) + return _as_router(self).registry().resolve(model_id, kind="from_id", custom_llm_provider=custom_llm_provider) def map_team_model( self, team_model_name: str | None, team_id: str, custom_llm_provider: str | None = None ) -> str | None: _note("map_team_model", "registry().resolve(name, kind='team_model', team_id=...)") - return _as_router(self)._core_map_team_model(team_model_name, team_id, custom_llm_provider=custom_llm_provider) + return ( + _as_router(self) + .registry() + .resolve(team_model_name, kind="team_model", team_id=team_id, custom_llm_provider=custom_llm_provider) + ) def is_recognized_model(self, model: str) -> bool: _note("is_recognized_model", "registry().resolve(name, kind='recognized')") - return _as_router(self)._core_is_recognized_model(model) + return _as_router(self).registry().resolve(model, kind="recognized") def get_routable_upstream_model(self, model_name: str, team_id: str | None = None) -> str | None: _note("get_routable_upstream_model", "registry().resolve(name, kind='upstream')") - return _as_router(self)._core_get_routable_upstream_model(model_name, team_id=team_id) + return _as_router(self).registry().resolve(model_name, kind="upstream", team_id=team_id) def get_search_tool_support(self, model_name: str, team_id: str | None = None) -> tuple[bool | None, ...]: _note("get_search_tool_support", "registry().resolve(name, kind='search_tool_support')") - return _as_router(self)._core_get_search_tool_support(model_name, team_id=team_id) + return _as_router(self).registry().resolve(model_name, kind="search_tool_support", team_id=team_id) def get_model_group(self, id: str) -> list | None: # mutable-ok: the old return type, unchanged _note("get_model_group", "registry().resolve(id, kind='group_of_id')") - return _as_router(self)._core_get_model_group(id=id) + return _as_router(self).registry().resolve(id, kind="group_of_id") def is_model_access_group_for_wildcard_route(self, model_access_group: str) -> bool: _note("is_model_access_group_for_wildcard_route", "registry().resolve(group, kind='wildcard_access_group')") - return _as_router(self)._core_is_model_access_group_for_wildcard_route(model_access_group=model_access_group) + return _as_router(self).registry().resolve(model_access_group, kind="wildcard_access_group") - _is_model_access_group_for_wildcard_route = _private_alias( - "is_model_access_group_for_wildcard_route", is_model_access_group_for_wildcard_route - ) + _is_model_access_group_for_wildcard_route = is_model_access_group_for_wildcard_route def team_model_has_alternatives(self, deployment_id: str) -> bool: _note("team_model_has_alternatives", "registry().resolve(id, kind='team_model_alternatives')") - return _as_router(self)._core_team_model_has_alternatives(deployment_id) + return _as_router(self).registry().resolve(deployment_id, kind="team_model_alternatives") def routing_group_has_alternatives(self, model_group: str | None) -> bool: _note("routing_group_has_alternatives", "registry().resolve(group, kind='routing_group_alternatives')") - return _as_router(self)._core_routing_group_has_alternatives(model_group) + return _as_router(self).registry().resolve(model_group, kind="routing_group_alternatives") # -- registry: groups, access groups, credentials, plugins ----------------------------------- def get_model_group_info( self, model_group: str, *, include_hidden: bool = False, team_id: str | None = None ) -> "ModelGroupInfo | None": _note("get_model_group_info", "registry().group(name)") - return _as_router(self)._core_get_model_group_info(model_group, include_hidden=include_hidden, team_id=team_id) + return _as_router(self).registry().group(model_group, include_hidden=include_hidden, team_id=team_id) def cached_model_group_info(self, model_group: str) -> "ModelGroupInfo | None": _note("cached_model_group_info", "registry().group(name, field='cached_info')") - return _as_router(self)._core_cached_model_group_info(model_group) + return _as_router(self).registry().group(model_group, field="cached_info") def get_configured_display_name(self, model_name: str) -> str | None: _note("get_configured_display_name", "registry().group(name, field='display_name')") - return _as_router(self)._core_get_configured_display_name(model_name) + return _as_router(self).registry().group(model_name, field="display_name") def get_configured_mode(self, model_name: str) -> str | None: _note("get_configured_mode", "registry().group(name, field='mode')") - return _as_router(self)._core_get_configured_mode(model_name) + return _as_router(self).registry().group(model_name, field="mode") def get_configured_service_tiers(self, model_name: str, team_id: str | None = None) -> tuple[object, ...]: _note("get_configured_service_tiers", "registry().group(name, field='service_tiers')") - return _as_router(self)._core_get_configured_service_tiers(model_name, team_id=team_id) + return _as_router(self).registry().group(model_name, field="service_tiers", team_id=team_id) def get_configured_token_limits(self, model_name: str) -> tuple[int | None, int | None]: _note("get_configured_token_limits", "registry().group(name, field='token_limits')") - return _as_router(self)._core_get_configured_token_limits(model_name) + return _as_router(self).registry().group(model_name, field="token_limits") def get_model_listing_info(self, model_name: str) -> "DeploymentModelListingInfo | None": _note("get_model_listing_info", "registry().group(name, field='listing_info')") - return _as_router(self)._core_get_model_listing_info(model_name) + return _as_router(self).registry().group(model_name, field="listing_info") def get_model_access_groups( self, @@ -642,31 +592,31 @@ class DeprecatedRouterMembers: team_id: str | None = None, ) -> dict[str, list[str]]: # mutable-ok: the old return type, unchanged _note("get_model_access_groups", "registry().access_groups(...)") - return _as_router(self)._core_get_model_access_groups( - model_name=model_name, model_access_group=model_access_group, team_id=team_id + return ( + _as_router(self) + .registry() + .access_groups(model_name=model_name, model_access_group=model_access_group, team_id=team_id) ) def get_deployment_credentials(self, model_id: str) -> dict | None: # mutable-ok: the old return type, unchanged _note("get_deployment_credentials", "registry().credentials(id)") - return _as_router(self)._core_get_deployment_credentials(model_id=model_id) + return _as_router(self).registry().credentials(model_id) def get_deployment_credentials_with_provider( self, model_id: str, team_id: str | None = None ) -> "dict[str, Any] | None": # pyright: ignore[reportExplicitAny] # the old return type, unchanged # mutable-ok: same _note("get_deployment_credentials_with_provider", "registry().credentials(id, form='with_provider')") - return _as_router(self)._core_get_deployment_credentials_with_provider(model_id=model_id, team_id=team_id) + return _as_router(self).registry().credentials(model_id, form="with_provider", team_id=team_id) def get_credential_deployment(self, model_id: str, team_id: str | None = None) -> "Deployment | None": _note("get_credential_deployment", "registry().credentials(id, form='deployment')") - return _as_router(self)._core_get_credential_deployment(model_id=model_id, team_id=team_id) + return _as_router(self).registry().credentials(model_id, form="deployment", team_id=team_id) def get_router_deployment_budget_limiter(self) -> "RouterBudgetLimiting | None": _note("get_router_deployment_budget_limiter", "registry().plugins('budget_limiter')") - return _as_router(self)._core_get_router_deployment_budget_limiter() + return _as_router(self).registry().plugins("budget_limiter") - _get_router_deployment_budget_limiter = _private_alias( - "get_router_deployment_budget_limiter", get_router_deployment_budget_limiter - ) + _get_router_deployment_budget_limiter = get_router_deployment_budget_limiter @staticmethod def generate_model_id(model_group: str, litellm_params: dict) -> str: # mutable-ok: the old parameter type @@ -678,15 +628,15 @@ class DeprecatedRouterMembers: # -- settings: methods ----------------------------------------------------------------------- def get_settings(self) -> dict[str, object]: # mutable-ok: Router._core_get_settings's type, a fresh dict _note("get_settings", "settings().as_dict()") - return _as_router(self)._core_get_settings() + return dict(_as_router(self).settings().as_dict()) def get_allowed_fails_from_policy(self, exception: Exception) -> int | None: _note("get_allowed_fails_from_policy", "settings().allowed_fails_for(exception)") - return _as_router(self)._core_get_allowed_fails_from_policy(exception=exception) + return _as_router(self).settings().allowed_fails_for(exception) def get_available_guardrail(self, guardrail_name: str) -> "GuardrailTypedDict": _note("get_available_guardrail", "settings().guardrail(name)") - return _as_router(self)._core_get_available_guardrail(guardrail_name) + return _as_router(self).settings().guardrail(guardrail_name) # -- health ---------------------------------------------------------------------------------- @staticmethod @@ -709,31 +659,31 @@ class DeprecatedRouterMembers: def get_fully_blocked_model_names(self) -> set[str]: # mutable-ok: the old return type, unchanged _note("get_fully_blocked_model_names", "health().fully_blocked_model_names()") - return _as_router(self)._core_get_fully_blocked_model_names() + return _as_router(self).health().fully_blocked_model_names() async def async_get_fully_unhealthy_model_names(self) -> set[str]: # mutable-ok: the old return type, unchanged _note("async_get_fully_unhealthy_model_names", "health().fully_unhealthy_model_names()") - return await _as_router(self)._core_async_get_fully_unhealthy_model_names() + return await _as_router(self).health().fully_unhealthy_model_names() async def get_model_group_usage(self, model_group: str) -> tuple[int | None, int | None]: _note("get_model_group_usage", "health().usage(group)") - return await _as_router(self)._core_get_model_group_usage(model_group=model_group) + return await _as_router(self).health().usage(model_group) async def get_remaining_model_group_usage( self, model_group: str ) -> dict[str, int]: # mutable-ok: the old return type, unchanged _note("get_remaining_model_group_usage", "health().usage(group, kind='remaining')") - return await _as_router(self)._core_get_remaining_model_group_usage(model_group=model_group) + return await _as_router(self).health().usage(model_group, kind="remaining") def team_ptu_ceiling(self, team_id: str, model_group: str) -> "PTUTeamCeiling | None": _note("team_ptu_ceiling", "health().team_ptu_ceiling(team_id, group)") - return _as_router(self)._core_team_ptu_ceiling(team_id, model_group) + return _as_router(self).health().team_ptu_ceiling(team_id, model_group) def split_request_priority( self, model: str, kwargs: Mapping[str, object] ) -> tuple[int | None, Mapping[str, object]]: _note("split_request_priority", "health().split_priority(model, kwargs)") - return _as_router(self)._core_split_request_priority(model, kwargs) + return _as_router(self).health().split_priority(model, kwargs) # -- selection ------------------------------------------------------------------------------- async def async_get_healthy_deployments( @@ -747,9 +697,10 @@ class DeprecatedRouterMembers: health_check_probe: bool = False, ) -> list[dict] | dict: # mutable-ok: the old return type, unchanged _note("async_get_healthy_deployments", "select(model, request_kwargs, kind='healthy')") - return await _as_router(self)._core_async_get_healthy_deployments( - model=model, - request_kwargs=request_kwargs, + return await _as_router(self).select( + model, + request_kwargs, + kind="healthy", messages=messages, input=input, specific_deployment=specific_deployment, @@ -757,7 +708,7 @@ class DeprecatedRouterMembers: health_check_probe=health_check_probe, ) - def get_available_deployment_for_pass_through( # noqa: ANN201 # the old member had no return annotation; its inferred type is kept by inferring it from the core + def get_available_deployment_for_pass_through( # noqa: ANN201 # the old member had no return annotation; its inferred type is kept by inferring it from select self, model: str, messages: list[dict[str, str]] | None = None, # mutable-ok: the old parameter type, unchanged @@ -766,12 +717,15 @@ class DeprecatedRouterMembers: request_kwargs: dict | None = None, # mutable-ok: the old parameter type, unchanged ): _note("get_available_deployment_for_pass_through", "select(model, kind='pass_through')") - return _as_router(self)._core_get_available_deployment_for_pass_through( - model=model, - messages=messages, - input=input, - specific_deployment=specific_deployment, - request_kwargs=request_kwargs, + return _run_ready( + _as_router(self).select( + model, + request_kwargs, + kind="pass_through", + messages=messages, + input=input, + specific_deployment=specific_deployment, + ) ) # -- writes ---------------------------------------------------------------------------------- @@ -791,7 +745,7 @@ class DeprecatedRouterMembers: _note("update_redis_cache", "apply(ChangeSet(redis_cache=cache))") _as_router(self).apply(ChangeSet(redis_cache=cache)) - _update_redis_cache = _private_alias("update_redis_cache", update_redis_cache) + _update_redis_cache = update_redis_cache async def arefresh_model_info(self, *, client: "AsyncHTTPHandler | None" = None) -> None: _note("arefresh_model_info", "aapply(ChangeSet(refresh_model_info=True))") @@ -808,8 +762,15 @@ class DeprecatedRouterMembers: def bind_to_request_logging(self, logging_obj: "LiteLLMLogging") -> None: _note("bind_to_request_logging", "observe(logging_obj)") - # Straight to the core, as before: observe() skips binding when logging_obj is None, the old member did not. - _as_router(self)._core_bind_to_request_logging(logging_obj) + router: Final = _as_router(self) + if logging_obj is None: # pyright: ignore[reportUnnecessaryComparison] # callers pass None despite the type + # observe() skips binding when logging_obj is None; the old member bound it, and failed on None. + raise AttributeError( + "'NoneType' object has no attribute 'add_dynamic_function_callbacks'", + name="add_dynamic_function_callbacks", + obj=None, + ) + router.observe(logging_obj) def discard(self) -> None: _note("discard", "retire()") @@ -822,7 +783,7 @@ class DeprecatedRouterMembers: request_kwargs: dict[str, object] | None = None, # mutable-ok: the old parameter type, unchanged ) -> None: _note("arm_routing_read_prefetch", "RoutingContext.arm_read_prefetch") - _as_router(self)._core_arm_routing_read_prefetch(model, request_kwargs) + RoutingContext(_as_router(self)).arm_read_prefetch(model, request_kwargs) async def async_pre_routing_hook( self, @@ -833,7 +794,7 @@ class DeprecatedRouterMembers: specific_deployment: bool | None = False, ) -> "PreRoutingHookResponse | None": _note("async_pre_routing_hook", "RoutingContext.pre_routing_hook") - return await _as_router(self)._core_async_pre_routing_hook( + return await RoutingContext(_as_router(self)).pre_routing_hook( model=model, request_kwargs=request_kwargs, messages=messages, @@ -843,7 +804,7 @@ class DeprecatedRouterMembers: def log_retry(self, kwargs: dict, e: Exception) -> dict: # mutable-ok: the old signature, unchanged _note("log_retry", "RoutingContext.log_retry") - return _as_router(self)._core_log_retry(kwargs=kwargs, e=e) + return RoutingContext(_as_router(self)).log_retry(kwargs=kwargs, e=e) # Router-family functions and classes that took the Router (``litellm_router_instance=``, diff --git a/litellm/router_python_core.py b/litellm/router_python_core.py index 30b05456987..8ca2afb9a99 100644 --- a/litellm/router_python_core.py +++ b/litellm/router_python_core.py @@ -84,6 +84,8 @@ from litellm.constants import ( MID_STREAM_FAILURE_LOG_WAIT_SECONDS, OUTPUT_TOKEN_CEILING_PARAMS, PROMPT_CACHE_PIN_CACHE_MAX_SIZE, + REALTIME_SESSION_ENDED_ABNORMALLY_KEY, + REALTIME_SESSION_SUCCESS_LOGGED_KEY, ROUTER_USAGE_COUNTED_TOKENS_METADATA_KEY, ROUTING_REQUEST_TAGS_METADATA_KEY, RUNTIME_UPDATABLE_ROUTER_SETTINGS, @@ -108,6 +110,7 @@ from litellm.litellm_core_utils.add_retry_fallback_headers import ( replace_complexity_router_headers, response_total_token_count, ) +from litellm.litellm_core_utils.agentic_followup_failure import is_agentic_followup_failure from litellm.litellm_core_utils.asyncify import run_async_function from litellm.litellm_core_utils.batch_utils import ( batch_create_routing, @@ -124,6 +127,7 @@ from litellm.litellm_core_utils.clientside_credential_handler import ( ) from litellm.litellm_core_utils.completion_timeout import CompletionTimeout from litellm.litellm_core_utils.core_helpers import ( + as_str_mapping, coerce_token_limit, get_litellm_metadata_from_kwargs, get_metadata_variable_name_from_kwargs, @@ -133,7 +137,7 @@ from litellm.litellm_core_utils.core_helpers import ( from litellm.litellm_core_utils.coroutine_checker import coroutine_checker from litellm.litellm_core_utils.credential_accessor import CredentialAccessor, reject_api_key_secret_reference from litellm.litellm_core_utils.dd_tracing import tracer -from litellm.litellm_core_utils.deployment_pricing import deployment_pricing_models +from litellm.litellm_core_utils.deployment_pricing import deployment_backend_models, deployment_pricing_models from litellm.litellm_core_utils.get_litellm_params import SUPPLEMENTAL_KWARGS_KEYS from litellm.litellm_core_utils.get_llm_provider_logic import ( declared_authenticating_provider, @@ -141,6 +145,7 @@ from litellm.litellm_core_utils.get_llm_provider_logic import ( is_registered_custom_provider, resolve_model_and_provider_for_metadata, ) +from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap from litellm.litellm_core_utils.get_retry_from_policy import ( get_num_retries_from_retry_policy as _get_num_retries_from_retry_policy, ) @@ -278,7 +283,15 @@ from litellm.router_strategy.complexity_router.context_compaction import ( reject_recursive_compactor, surface_for_call, ) -from litellm.router_strategy.least_busy import LeastBusyLoggingHandler +from litellm.router_strategy.least_busy import ( + CALL_IDENTITY, + SELECTION_RESERVATION_MAX_KEYS, + LeastBusyLoggingHandler, + call_id_of, + owning_picks, + pick_reserves, + picks_reserve, +) from litellm.router_strategy.lowest_cost import LowestCostLoggingHandler from litellm.router_strategy.lowest_latency import LowestLatencyLoggingHandler from litellm.router_strategy.lowest_tpm_rpm import LowestTPMLoggingHandler @@ -302,6 +315,7 @@ from litellm.router_utils.cooldown_handlers import ( get_cooldown_deployment_info, get_cooldown_deployments, is_background_response_poll_not_found, + is_caller_entra_credential_failure, is_caller_scoped_auth_failure, is_caller_timeout_408, is_failure_outside_selected_deployment, @@ -309,6 +323,7 @@ from litellm.router_utils.cooldown_handlers import ( mark_deployment_selection_failure, set_cooldown_deployments, ) +from litellm.router_utils.deployment_numbers import refuse_unservable_numbers from litellm.router_utils.embedding_batch_size_check import ( async_log_rejection_before_provider_call, clear_rejected_before_provider_call, @@ -353,6 +368,11 @@ from litellm.router_utils.fallback_event_handlers import ( routed_deployment_id, run_async_fallback, ) +from litellm.router_utils.global_callback_holders import ( + live_check_owners, + routers_holding_global_callbacks, + routers_holding_global_callbacks_lock, +) from litellm.router_utils.handle_error import ( async_raise_no_deployment_exception, send_llm_exception_alert, @@ -475,17 +495,21 @@ from litellm.types.router import ( from litellm.types.services import ServiceTypes from litellm.types.utils import ( AUTOROUTER_CLASSIFIER_CALL_ORIGIN, + COST_MAP_LOOKUP_KEY, + DEPLOYMENT_SCOPED_TOKEN_LIMIT_FIELDS, PROMPT_QUOTING_ROUTING_DECISION_FIELDS, CustomPricingLiteLLMParams, GenericBudgetConfigType, LiteLLMBatch, LlmProviders, + LlmProvidersSet, ModelInfo, ModelResponseStream, StandardLoggingPayload, StandardLoggingRoutingDecision, Usage, all_litellm_params, + echoed_cost_map_fields, is_server_derived_pricing_key, shared_backend_model_info, ) @@ -501,9 +525,11 @@ from litellm.utils import ( TextCompletionResponse, _restore_correlation_context_if_supported, # pyright: ignore[reportPrivateUsage] # same task-local cleanup as the SDK wrapper aresolve_api_key_secret_reference, + catalog_with_runtime_registrations, function_setup, get_llm_provider, get_non_default_completion_params, + get_potential_model_names, get_secret, get_utc_datetime, is_generalized_model_info, @@ -544,6 +570,7 @@ if TYPE_CHECKING: ResponseAPIUsage, ResponseIncompleteEvent, ResponsesAPIResponse, + ResponsesAPIStreamingResponse, ) Span = _Span @@ -668,6 +695,7 @@ _NO_SESSION_KWARGS: Final[Mapping[str, Mapping[str, object]]] = MappingProxyType _NO_DEFAULT_PARAMS: Final[Mapping[str, object]] = MappingProxyType({}) _SESSION_ADAPTER: Final = TypeAdapter(Mapping[str, object]) _MODEL_INFO_ADAPTER: Final = TypeAdapter(Mapping[str, object]) +_CALL_KWARGS_ADAPTER: Final = TypeAdapter(Mapping[str, object]) _LITELLM_PARAMS_ADAPTER: Final = TypeAdapter(Mapping[str, object]) _SILENT_MODEL_ADAPTER: Final = TypeAdapter(str | list[str]) _RESOLVED_RETRY_POLICY_ADAPTER: Final = TypeAdapter(RetryPolicy | None) @@ -771,6 +799,17 @@ def _configured_model_info(deployment: Mapping[str, object]) -> Mapping[str, obj return _MODEL_INFO_ADAPTER.validate_python(deployment.get("model_info") or {}) +def _operator_max_input_tokens(deployment: Mapping[str, object]) -> int | None: + model_info: Final = _configured_model_info(deployment) + catalog_key: Final = model_info.get(COST_MAP_LOOKUP_KEY) + catalog_entry: Final = ( + GetModelCostMap.loaded_model_cost_map().get(catalog_key) if isinstance(catalog_key, str) else None + ) + if catalog_entry is not None and "max_input_tokens" in echoed_cost_map_fields(model_info, catalog_entry): + return None + return coerce_token_limit(model_info.get("max_input_tokens")) + + def _search_tool_support(deployment: DeploymentTypedDict) -> bool | None: from litellm.responses.litellm_completion_transformation.tool_search import chat_config_builds_anthropic_request @@ -832,9 +871,11 @@ def _with_router_resolved_session_model(session: object, model_name: str) -> Map typed_session: Final = _SESSION_ADAPTER.validate_python(session) except ValidationError: return _NO_SESSION_KWARGS - if "model" not in typed_session: + if "model" not in typed_session and typed_session.get("type") != "transcription": return _NO_SESSION_KWARGS - return MappingProxyType({"session": {**typed_session, "model": model_name}}) + from litellm.realtime_api.main import with_resolved_session_model + + return MappingProxyType({"session": with_resolved_session_model(dict(typed_session), model_name)}) # Router._aanthropic_messages_streaming_iterator buffers lifecycle chunks @@ -1199,8 +1240,9 @@ class RoutingArgs(enum.Enum): # as the per-request one built from a caller-supplied user_config, drops out on its # own rather than leaving entries behind that nothing can withdraw. _live_routers: Final["weakref.WeakSet[PythonCore]"] = weakref.WeakSet() -_routers_holding_global_callbacks: Final["weakref.WeakSet[PythonCore]"] = weakref.WeakSet() -_routers_holding_global_callbacks_lock: Final = threading.Lock() +# Shared with the other router cores of the process (litellm/router_utils/global_callback_holders.py). +_routers_holding_global_callbacks: Final["weakref.WeakSet[PythonCore]"] = routers_holding_global_callbacks # pyright: ignore[reportAssignmentType] # every member serves the holder members +_routers_holding_global_callbacks_lock: Final = routers_holding_global_callbacks_lock def _replay_live_router_model_cost() -> None: @@ -1436,13 +1478,14 @@ class PythonCore(DeprecatedRouterMembers): (``pass_through``). """ if kind == "pick": - return await self._core_async_get_available_deployment( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selection cores return untyped deployment dicts - model=model, - request_kwargs=request_kwargs if request_kwargs is not None else {}, - messages=messages, - input=input, - specific_deployment=specific_deployment, - ) + with picks_reserve(False): + return await self._core_async_get_available_deployment( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selection cores return untyped deployment dicts + model=model, + request_kwargs=request_kwargs if request_kwargs is not None else {}, + messages=messages, + input=input, + specific_deployment=specific_deployment, + ) if kind == "healthy": return await self._core_async_get_healthy_deployments( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selection cores return untyped deployment dicts model=model, @@ -1454,13 +1497,14 @@ class PythonCore(DeprecatedRouterMembers): health_check_probe=health_check_probe, ) if kind == "pass_through": - return self._core_get_available_deployment_for_pass_through( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selection cores return untyped deployment dicts - model=model, - messages=messages, - input=input, - specific_deployment=specific_deployment, - request_kwargs=request_kwargs, - ) + with picks_reserve(False): + return self._core_get_available_deployment_for_pass_through( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selection cores return untyped deployment dicts + model=model, + messages=messages, + input=input, + specific_deployment=specific_deployment, + request_kwargs=request_kwargs, + ) raise ValueError(f"unknown select kind {kind!r}") def apply(self, changes: ChangeSet) -> ApplyResult: @@ -1742,6 +1786,9 @@ class PythonCore(DeprecatedRouterMembers): self._core_cache = DualCache( redis_cache=redis_cache, in_memory_cache=InMemoryCache() ) # use a dual cache (Redis+In-Memory) for tracking cooldowns, usage, etc. + self._core_least_busy_reservations: InMemoryCache = InMemoryCache( + max_size_in_memory=SELECTION_RESERVATION_MAX_KEYS + ) self._claude_code_session_router_cache: DualCache = DualCache( redis_cache=redis_cache, in_memory_cache=InMemoryCache(), @@ -1839,6 +1886,7 @@ class PythonCore(DeprecatedRouterMembers): # cost-map entries from the list it is serving at that moment, whether # those deployments came from model_list or were added later from the DB. _live_routers.add(self) + live_check_owners.add(self) if allowed_fails is not None: self._core_allowed_fails = allowed_fails @@ -2064,6 +2112,7 @@ class PythonCore(DeprecatedRouterMembers): # Stop contributing to cost-map rebuilds straight away rather than waiting # for this router to be collected. _live_routers.discard(self) + live_check_owners.discard(self) self.retire_routing_state() self._release_global_callbacks() @@ -2245,7 +2294,9 @@ class PythonCore(DeprecatedRouterMembers): selector: RouterStrategySelector | None = None match self._normalize_strategy(strategy): case RoutingStrategy.LEAST_BUSY.value: - selector = LeastBusyLoggingHandler(router_cache=self._core_cache) + selector = LeastBusyLoggingHandler( + router_cache=self._core_cache, reservation_store=self._core_least_busy_reservations + ) case RoutingStrategy.USAGE_BASED_ROUTING.value: selector = LowestTPMLoggingHandler( router_cache=self._core_cache, @@ -2710,6 +2761,7 @@ class PythonCore(DeprecatedRouterMembers): messages: list[dict[str, str]] | None, input: str | list | None, request_kwargs: dict | None, + reserve: bool, ) -> Any | None: """ Asks the strategy selector for a deployment. Caller handles @@ -2723,6 +2775,8 @@ class PythonCore(DeprecatedRouterMembers): return await selector.async_get_available_deployments( model_group=model, healthy_deployments=healthy_deployments, + reserve=reserve, + call_id=call_id_of(CALL_IDENTITY.validate_python(request_kwargs or {})), ) case "usage-based-routing": # `LowestTPMLoggingHandler` (v1) only exposes the sync @@ -2763,6 +2817,7 @@ class PythonCore(DeprecatedRouterMembers): messages: list[dict[str, str]] | None, input: str | list | None, request_kwargs: dict | None, + reserve: bool, ) -> Any | None: """ Sync sibling of `_select_deployment_async`. Caller handles @@ -2779,6 +2834,8 @@ class PythonCore(DeprecatedRouterMembers): return selector.get_available_deployments( model_group=model, healthy_deployments=healthy_deployments, + reserve=reserve, + call_id=call_id_of(CALL_IDENTITY.validate_python(request_kwargs or {})), ) case "usage-based-routing" | "usage-based-routing-v2": return selector.get_available_deployments( @@ -2850,6 +2907,14 @@ class PythonCore(DeprecatedRouterMembers): self._host.invoke("acreate_realtime_transcription_session"), call_type="acreate_realtime_transcription_session", ) + self.acreate_realtime_translation_client_secret = self.factory_function( + self._host.invoke("acreate_realtime_translation_client_secret"), + call_type="acreate_realtime_translation_client_secret", + ) + self.arealtime_translation_calls = self.factory_function( + self._host.invoke("arealtime_translation_calls"), + call_type="arealtime_translation_calls", + ) self._aresponses_websocket = self.factory_function( self._host.invoke("_aresponses_websocket"), call_type="_aresponses_websocket" ) @@ -3359,7 +3424,7 @@ class PythonCore(DeprecatedRouterMembers): self.optional_callbacks = [cb for cb in self.optional_callbacks if type(cb) is not callback_cls] if any( router is not self and any(type(cb) is callback_cls for cb in (router.optional_callbacks or [])) - for router in tuple(_live_routers) + for router in (*_live_routers, *(owner for owner in live_check_owners if not isinstance(owner, PythonCore))) ): return for cb in tuple(self._host.callback_list("callbacks")): @@ -3490,12 +3555,13 @@ class PythonCore(DeprecatedRouterMembers): ) # pick the one that is available (lowest TPM/RPM) - deployment = self.get_available_deployment( - model=model, - messages=messages, - specific_deployment=kwargs.pop("specific_deployment", None), - request_kwargs=kwargs, - ) + with picks_reserve(True): + deployment = self.get_available_deployment( + model=model, + messages=messages, + specific_deployment=kwargs.pop("specific_deployment", None), + request_kwargs=kwargs, + ) self._drop_unsupported_classifier_reasoning_effort( deployment=cast(DeploymentTypedDict, deployment), # cast-ok: selection returns a router deployment model=model, @@ -3809,11 +3875,6 @@ class PythonCore(DeprecatedRouterMembers): priced_partial._hidden_params = { # pyright: ignore[reportPrivateUsage] # no public accessor key: value for key, value in get_hidden_params_dict(partial_response).items() if key != "response_cost" } - if LiteLLMLogging.usage_capture_callback is not None: - from litellm._internal_context import internal_sub_call - - with internal_sub_call(cut_logging.litellm_call_id): - cut_logging.capture_usage_before_logging(priced_partial) return ContinuedPartial( usage=BaseTokenUsageProcessor.combine_usage_objects( usage_objects=[partial_usage, inherited_usage] @@ -4012,6 +4073,8 @@ class PythonCore(DeprecatedRouterMembers): if continuation_output is not None else None ) + if cut_partial is not None: + model_response.logging_obj.mark_stash_billed_by_continuation() if continue_after_content: emitted_tokens: Final = int( getattr(complete_response_object_usage, "completion_tokens", 0) or 0 @@ -4385,12 +4448,13 @@ class PythonCore(DeprecatedRouterMembers): fallback_headers_adopted: bool = False - def __init__(self, async_generator: AsyncGenerator): + def __init__(self, async_generator: "AsyncGenerator[ResponsesAPIStreamingResponse, None]"): import time from datetime import datetime self._async_generator = async_generator self._billing_source: object = source_iterator + self._last_sequence_number = -1 # Mirror every attribute BaseResponsesAPIStreamingIterator.__init__ # would have set. The wrapper bypasses super().__init__ (it has no # httpx.Response of its own and no provider config to drive), so @@ -4497,7 +4561,16 @@ class PythonCore(DeprecatedRouterMembers): if self.completed_response is None and getattr(chunk, "type", None) in _RESPONSES_TERMINAL_EVENT_TYPES: self.completed_response = chunk self._yielded_first_chunk = True - return chunk + sequence_number: Final = getattr(chunk, "sequence_number", None) + if not isinstance(sequence_number, int): + return chunk + if not self.fallback_headers_adopted: + self._last_sequence_number = max(self._last_sequence_number, sequence_number) + return chunk + self._last_sequence_number = max(self._last_sequence_number + 1, sequence_number) + if self._last_sequence_number == sequence_number: + return chunk + return chunk.model_copy(update={"sequence_number": self._last_sequence_number}) async def aclose(self): # async generators always expose aclose — no defensive check needed. @@ -4559,7 +4632,9 @@ class PythonCore(DeprecatedRouterMembers): exc, ) - wrapper: Final = FallbackResponsesStreamWrapper(stream_with_fallbacks()) + wrapper: Final = FallbackResponsesStreamWrapper( + stream_with_fallbacks() # pyright: ignore[reportArgumentType] # relays response events typed as object + ) return wrapper def _aresponses_background_stream_can_release( @@ -5169,8 +5244,19 @@ class PythonCore(DeprecatedRouterMembers): # _update_kwargs_with_deployment and stamped into kwargs["model_info"]; stamping # the static shared deployment's id instead would let one tenant's bad credentials # cool down the deployment every other tenant sharing this config relies on. + if getattr(exception, "failed_deployment_id", None): + return effective_model_info: Final = kwargs.get("model_info") or deployment.get("model_info") or MappingProxyType({}) self._set_failed_deployment_id_on_exception(exception, MappingProxyType({"model_info": effective_model_info})) + configured_deployment_id: Final = _MODEL_INFO_ADAPTER.validate_python(effective_model_info).get( + "original_model_id" + ) + if isinstance(configured_deployment_id, str) and configured_deployment_id: + exception.failed_configured_deployment_id = configured_deployment_id # pyright: ignore[reportAttributeAccessIssue] # rebind-ok: the exception carries the failure to _maybe_run_weighted_failover + + def _stamp_failed_attempt(self, exception: Exception, kwargs: Mapping[str, object], *, picked: bool) -> None: + if picked: + self._stamp_failed_deployment_id_with_effective_model_info(exception, MappingProxyType({}), kwargs) @staticmethod def _stamp_retry_skip_deployment_id(exception: Exception, kwargs: Mapping[str, object]) -> None: @@ -6047,14 +6133,16 @@ class PythonCore(DeprecatedRouterMembers): def _image_generation(self, prompt: str, model: str, **kwargs): model_name: Final = "" + deployment = None # rebind-ok: pre-init so the except block can stamp a failure with no deployment picked try: verbose_router_logger.debug("Inside _image_generation()- model: %s", model) - deployment: Final = self.get_available_deployment( - model=model, - messages=[{"role": "user", "content": "prompt"}], - specific_deployment=kwargs.pop("specific_deployment", None), - request_kwargs=kwargs, - ) + with picks_reserve(True): + deployment = self.get_available_deployment( # rebind-ok: set on success, see pre-init + model=model, + messages=[{"role": "user", "content": "prompt"}], + specific_deployment=kwargs.pop("specific_deployment", None), + request_kwargs=kwargs, + ) self._update_kwargs_with_deployment(deployment=deployment, kwargs=kwargs) data: Final = deployment["litellm_params"].copy() @@ -6085,6 +6173,9 @@ class PythonCore(DeprecatedRouterMembers): if model_name is not None: self.fail_calls[model_name] += 1 self._stamp_retry_skip_deployment_id(e, kwargs) + self._stamp_failed_attempt( + e, _REQUEST_KWARGS_ADAPTER.validate_python(kwargs), picked=deployment is not None + ) raise e async def aimage_generation(self, prompt: str, model: str, **kwargs): @@ -6110,11 +6201,12 @@ class PythonCore(DeprecatedRouterMembers): async def _aimage_generation(self, prompt: str, model: str, **kwargs): model_name = model start_time: Final = datetime.now() # noqa: DTZ005 # SDK logging uses naive local timestamps + deployment = None # rebind-ok: pre-init so the except block can stamp a failure with no deployment picked try: verbose_router_logger.debug("Inside _image_generation()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) try: - deployment: Final = await self._core_async_get_available_deployment( + deployment = await self._core_async_get_available_deployment( # rebind-ok: set on success, see pre-init model=model, messages=[{"role": "user", "content": "prompt"}], specific_deployment=kwargs.pop("specific_deployment", None), @@ -6175,6 +6267,9 @@ class PythonCore(DeprecatedRouterMembers): if model_name is not None: self.fail_calls[model_name] += 1 self._stamp_retry_skip_deployment_id(e, kwargs) + self._stamp_failed_attempt( + e, _REQUEST_KWARGS_ADAPTER.validate_python(kwargs), picked=deployment is not None + ) raise e async def atranscription(self, file: FileTypes, model: str, **kwargs): @@ -6221,10 +6316,11 @@ class PythonCore(DeprecatedRouterMembers): async def _atranscription(self, file: FileTypes, model: str, **kwargs): model_name: Final = model + deployment = None # rebind-ok: pre-init so the except block can stamp a failure with no deployment picked try: verbose_router_logger.debug("Inside _atranscription()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) - deployment: Final = await self._core_async_get_available_deployment( + deployment = await self._core_async_get_available_deployment( # rebind-ok: set on success, see pre-init model=model, messages=[{"role": "user", "content": "prompt"}], specific_deployment=kwargs.pop("specific_deployment", None), @@ -6258,6 +6354,9 @@ class PythonCore(DeprecatedRouterMembers): if model_name is not None: self.fail_calls[model_name] += 1 self._stamp_retry_skip_deployment_id(e, kwargs) + self._stamp_failed_attempt( + e, _REQUEST_KWARGS_ADAPTER.validate_python(kwargs), picked=deployment is not None + ) raise e async def aspeech(self, model: str, input: str, voice: str | None = None, **kwargs): @@ -6314,10 +6413,11 @@ class PythonCore(DeprecatedRouterMembers): async def _aspeech(self, model: str, input: str, voice: str | None = None, **kwargs): model_name: Final = model + deployment = None # rebind-ok: pre-init so the except block can stamp a failure with no deployment picked try: verbose_router_logger.debug("Inside _aspeech()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) - deployment: Final = await self._core_async_get_available_deployment( + deployment = await self._core_async_get_available_deployment( # rebind-ok: set on success, see pre-init model=model, messages=[{"role": "user", "content": "prompt"}], specific_deployment=kwargs.pop("specific_deployment", None), @@ -6351,6 +6451,9 @@ class PythonCore(DeprecatedRouterMembers): if model_name is not None: self.fail_calls[model_name] += 1 self._stamp_retry_skip_deployment_id(e, kwargs) + self._stamp_failed_attempt( + e, _REQUEST_KWARGS_ADAPTER.validate_python(kwargs), picked=deployment is not None + ) raise e async def arerank(self, model: str, **kwargs): @@ -6376,9 +6479,10 @@ class PythonCore(DeprecatedRouterMembers): async def _arerank(self, model: str, **kwargs): model_name = None + deployment = None # rebind-ok: pre-init so the except block can stamp a failure with no deployment picked try: verbose_router_logger.debug("Inside _rerank()- model: %s", model) - deployment: Final = await self._core_async_get_available_deployment( + deployment = await self._core_async_get_available_deployment( # rebind-ok: set on success, see pre-init model=model, specific_deployment=kwargs.pop("specific_deployment", None), request_kwargs=kwargs, @@ -6410,6 +6514,9 @@ class PythonCore(DeprecatedRouterMembers): if model_name is not None: self.fail_calls[model_name] += 1 self._stamp_retry_skip_deployment_id(e, kwargs) + self._stamp_failed_attempt( + e, _REQUEST_KWARGS_ADAPTER.validate_python(kwargs), picked=deployment is not None + ) raise e def text_completion( @@ -6422,37 +6529,38 @@ class PythonCore(DeprecatedRouterMembers): **kwargs, ): messages: Final = [{"role": "user", "content": prompt}] - try: - kwargs["model"] = model - kwargs["prompt"] = prompt - kwargs["num_retries"] = kwargs.get("num_retries", self.num_retries) - kwargs.setdefault("metadata", {}).update({"model_group": model}) + with owning_picks(self._core_least_busy_reservations, call_id_of(CALL_IDENTITY.validate_python(kwargs))): + try: + kwargs["model"] = model + kwargs["prompt"] = prompt + kwargs["num_retries"] = kwargs.get("num_retries", self.num_retries) + kwargs.setdefault("metadata", {}).update({"model_group": model}) - # pick the one that is available (lowest TPM/RPM) - with endpoint_selection("text_completion", model=model): - deployment: Final = self.get_available_deployment( - model=model, - messages=messages, - specific_deployment=kwargs.pop("specific_deployment", None), - request_kwargs=kwargs, + # pick the one that is available (lowest TPM/RPM) + with endpoint_selection("text_completion", model=model), picks_reserve(True): + deployment: Final = self.get_available_deployment( + model=model, + messages=messages, + specific_deployment=kwargs.pop("specific_deployment", None), + request_kwargs=kwargs, + ) + + data: Final = deployment["litellm_params"].copy() + for k, v in self._core_default_litellm_params.items(): + if k not in kwargs: # prioritize model-specific params > default router params + kwargs[k] = v + elif k == "metadata": + kwargs[k].update(v) + pinned_model_id: Final = deployment_model_id_pin(_LITELLM_PARAMS_ADAPTER.validate_python(data)) + if pinned_model_id is not None: + kwargs["model_id"] = pinned_model_id # rebind-ok: this call's own kwargs, filled like the defaults + + # call via litellm.completion() + return self._host.invoke("text_completion")( + **{**data, "prompt": prompt, "caching": self._core_cache_responses, **kwargs} ) - - data: Final = deployment["litellm_params"].copy() - for k, v in self._core_default_litellm_params.items(): - if k not in kwargs: # prioritize model-specific params > default router params - kwargs[k] = v - elif k == "metadata": - kwargs[k].update(v) - pinned_model_id: Final = deployment_model_id_pin(_LITELLM_PARAMS_ADAPTER.validate_python(data)) - if pinned_model_id is not None: - kwargs["model_id"] = pinned_model_id # rebind-ok: this call's own kwargs, filled like the defaults - - # call via litellm.completion() - return self._host.invoke("text_completion")( - **{**data, "prompt": prompt, "caching": self._core_cache_responses, **kwargs} - ) - except Exception as e: - raise e + except Exception as e: + raise e async def atext_completion( self, @@ -6491,10 +6599,11 @@ class PythonCore(DeprecatedRouterMembers): raise e async def _atext_completion(self, model: str, prompt: str, **kwargs): + deployment = None # rebind-ok: pre-init so the except block can stamp a failure with no deployment picked try: verbose_router_logger.debug("Inside _atext_completion()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) - deployment: Final = await self._core_async_get_available_deployment( + deployment = await self._core_async_get_available_deployment( # rebind-ok: set on success, see pre-init model=model, messages=[{"role": "user", "content": prompt}], specific_deployment=kwargs.pop("specific_deployment", None), @@ -6530,6 +6639,9 @@ class PythonCore(DeprecatedRouterMembers): if model is not None: self.fail_calls[model] += 1 self._stamp_retry_skip_deployment_id(e, kwargs) + self._stamp_failed_attempt( + e, _REQUEST_KWARGS_ADAPTER.validate_python(kwargs), picked=deployment is not None + ) raise e async def aadapter_completion( @@ -6561,10 +6673,11 @@ class PythonCore(DeprecatedRouterMembers): raise e async def _aadapter_completion(self, adapter_id: str, model: str, **kwargs): + deployment = None # rebind-ok: pre-init so the except block can stamp a failure with no deployment picked try: verbose_router_logger.debug("Inside _aadapter_completion()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) - deployment: Final = await self._core_async_get_available_deployment( + deployment = await self._core_async_get_available_deployment( # rebind-ok: set on success, see pre-init model=model, messages=[{"role": "user", "content": "default text"}], specific_deployment=kwargs.pop("specific_deployment", None), @@ -6600,6 +6713,9 @@ class PythonCore(DeprecatedRouterMembers): if model is not None: self.fail_calls[model] += 1 self._stamp_retry_skip_deployment_id(e, kwargs) + self._stamp_failed_attempt( + e, _REQUEST_KWARGS_ADAPTER.validate_python(kwargs), picked=deployment is not None + ) raise e async def _asearch_with_fallbacks(self, original_function: Callable, **kwargs) -> object: @@ -6865,6 +6981,22 @@ class PythonCore(DeprecatedRouterMembers): raise safeguard_refusal_error(model=model, stop_details=refusal_details) self.success_calls[model_name] += 1 + realtime_session_logging: Final = ( + _CALL_KWARGS_ADAPTER.validate_python(kwargs).get("litellm_logging_obj") + if generic_function_name == "_arealtime" + else None + ) + realtime_session_deployment_id: Final = ( + _MODEL_INFO_ADAPTER.validate_python(kwargs["model_info"]).get("id") + if isinstance(realtime_session_logging, LiteLLMLogging) + and realtime_session_logging.model_call_details.get(REALTIME_SESSION_SUCCESS_LOGGED_KEY) is True + and realtime_session_logging.model_call_details.get(REALTIME_SESSION_ENDED_ABNORMALLY_KEY) is not True + else None + ) + if realtime_session_deployment_id is not None: + increment_deployment_successes_for_current_minute( + ctx=self._core_ctx, deployment_id=str(realtime_session_deployment_id) + ) verbose_router_logger.info("ageneric_api_call_with_fallbacks(model=%s)\x1b[32m 200 OK\x1b[0m", model_name) return response @@ -7028,6 +7160,8 @@ class PythonCore(DeprecatedRouterMembers): or self._stream_can_fall_back(model, initial_kwargs) ) buffered_lifecycle_chunks: tuple[bytes, ...] = () # rebind-ok: flushed once committed or on decline + # An error this loop raises off a frame, not the provider's. + raised_here: BaseException | None = None # rebind-ok: set when the loop raises off a frame try: async for chunk in source_iterator: if _anthropic_stream_forwards_ping_live(chunk, has_generated_content): @@ -7058,25 +7192,27 @@ class PythonCore(DeprecatedRouterMembers): and self._refusal_fallback_available(model, initial_kwargs) ): refusal_error = safeguard_refusal_error(model=model, stop_details=refusal_stop_details) - raise MidStreamFallbackError( + raised_here = MidStreamFallbackError( message=refusal_error.message, model=model, llm_provider="anthropic", original_exception=refusal_error, is_pre_first_chunk=True, ) + raise raised_here if not has_generated_content and error_event is None: buffered_lifecycle_chunks = (*buffered_lifecycle_chunks, chunk) continue if recoverable_frame_error is not None: assert error_event is not None - raise MidStreamFallbackError( + raised_here = MidStreamFallbackError( message=error_event[1], model=model, llm_provider="anthropic", original_exception=recoverable_frame_error, is_pre_first_chunk=True, ) + raise raised_here for buffered_chunk in buffered_lifecycle_chunks: yield buffered_chunk buffered_lifecycle_chunks = () @@ -7084,6 +7220,8 @@ class PythonCore(DeprecatedRouterMembers): for buffered_chunk in buffered_lifecycle_chunks: yield buffered_chunk except Exception as stream_error: # noqa: BLE001 # any raised provider error must reach the fallback gate + if stream_error is not raised_here: + await self._areport_raised_messages_stream_failure(stream_error, initial_kwargs, source_iterator) async for item in self._aanthropic_messages_recover_stream_error( stream_error, has_generated_content, @@ -7103,6 +7241,52 @@ class PythonCore(DeprecatedRouterMembers): wrapper: Final = FallbackAwareAnthropicMessagesStream(stream_with_fallbacks(), source_iterator) return wrapper + async def _areport_raised_messages_stream_failure( + self, stream_error: Exception, attempt_kwargs: Mapping[str, object], source: object + ) -> None: + """A /v1/messages stream whose provider iterator raised, counted against the deployment + that served it and cooled down by the rules, the same as a non-stream call's failure, so a + retry picks another deployment. A stream that logs itself (litellm's own stream logging + reaches the router's failure callback), or a failure the request's logging object already + logged, is not counted twice.""" + from litellm.exceptions import MidStreamFallbackError + from litellm.litellm_core_utils.litellm_logging import Logging + + if isinstance(getattr(source, "logging_obj", None), Logging): + return + logging_obj: Final = attempt_kwargs.get("litellm_logging_obj") + if isinstance(logging_obj, Logging) and logging_obj.model_call_details.get("has_logged_async_failure") is True: + return + bucket: Final = as_str_mapping(attempt_kwargs.get(get_metadata_variable_name_from_kwargs(attempt_kwargs))) or {} + model_info: Final = as_str_mapping(bucket.get("model_info")) or {} + deployment_id: Final = model_info.get("id") + if deployment_id is None: + return + deployment: Final = self.get_deployment(model_id=str(deployment_id)) + deployment_params: Final = deployment.litellm_params.model_dump(exclude_none=True) if deployment else {} + provider_error: Final = ( + stream_error.original_exception + if isinstance(stream_error, MidStreamFallbackError) and stream_error.original_exception is not None + else stream_error + ) + now: Final = datetime.now() # noqa: DTZ005 # naive, as the logging pipeline's times + logged: Final = { + "call_type": "anthropic_messages", + "exception": provider_error, + "litellm_params": { + **{ + name: deployment_params[name] for name in ("api_base", "cooldown_time") if name in deployment_params + }, + "metadata": dict(bucket), + "model_info": dict(model_info), + }, + } + try: + _ = self.deployment_callback_on_failure(logged, None, now, now) # pyright: ignore[reportUnknownMemberType] # an untyped callback + await self.async_deployment_callback_on_failure(logged, None, now, now) # pyright: ignore[reportUnknownMemberType] # see above + except Exception as error: # noqa: BLE001 # a recording never fails the stream + verbose_router_logger.warning("a stream's failure was not recorded: %s", error) + async def _aanthropic_messages_recover_stream_error( self, stream_error: Exception, @@ -7313,6 +7497,8 @@ class PythonCore(DeprecatedRouterMembers): last_error = e # rebind-ok: the newest failure is what the fallback chain and the caller see for attempt in range(attempted_retries_for_request(initial_kwargs), budget): trigger = _mid_stream_retry_trigger(last_error) + if is_agentic_followup_failure(trigger): + return _StreamRetriesExhausted(last_error) if not policy_applies and not self._stream_should_retry( trigger, healthy_deployments, all_deployments, initial_kwargs ): @@ -7570,61 +7756,70 @@ class PythonCore(DeprecatedRouterMembers): """ handler_name: Final = original_function.__name__ metadata_variable_name: Final = get_router_metadata_variable_name(function_name="generic_api_call") - try: - verbose_router_logger.debug("Inside _generic_api_call() - handler: %s, model: %s", handler_name, model) - self._update_kwargs_before_fallbacks( - model=model, - kwargs=kwargs, - metadata_variable_name=metadata_variable_name, - ) - with self._video_call_pin(handler_name, kwargs), self._route_capability_pin(handler_name): - deployment: Final = self.get_available_deployment( + deployment = None # rebind-ok: pre-init so the except block can stamp a failure with no deployment picked + with owning_picks(self._core_least_busy_reservations, call_id_of(CALL_IDENTITY.validate_python(kwargs))): + try: + verbose_router_logger.debug("Inside _generic_api_call() - handler: %s, model: %s", handler_name, model) + self._update_kwargs_before_fallbacks( model=model, - messages=kwargs.get("messages", None), - input=kwargs.get("input", None), - specific_deployment=kwargs.pop("specific_deployment", None), - request_kwargs=kwargs, + kwargs=kwargs, + metadata_variable_name=metadata_variable_name, + ) + with ( + self._video_call_pin(handler_name, kwargs), + self._route_capability_pin(handler_name), + picks_reserve(True), + ): + deployment = self.get_available_deployment( # rebind-ok: set on success, see pre-init + model=model, + messages=kwargs.get("messages", None), + input=kwargs.get("input", None), + specific_deployment=kwargs.pop("specific_deployment", None), + request_kwargs=kwargs, + ) + self._update_kwargs_with_deployment( + deployment=deployment, + kwargs=kwargs, + function_name="generic_api_call", + splits_stream_timeout=handler_name in _STREAM_TIMEOUT_AWARE_GENERIC_HANDLERS, ) - self._update_kwargs_with_deployment( - deployment=deployment, - kwargs=kwargs, - function_name="generic_api_call", - splits_stream_timeout=handler_name in _STREAM_TIMEOUT_AWARE_GENERIC_HANDLERS, - ) - data: Final = deployment["litellm_params"].copy() - model_name: Final = data["model"] + data: Final = deployment["litellm_params"].copy() + model_name: Final = data["model"] - self.total_calls[model_name] += 1 + self.total_calls[model_name] += 1 - # For passthrough routes, use the actual model from deployment - # and swap model name in endpoint if present - if "endpoint" in kwargs and kwargs["endpoint"]: - kwargs["endpoint"] = kwargs["endpoint"].replace(model, model_name) - kwargs["model"] = model_name + # For passthrough routes, use the actual model from deployment + # and swap model name in endpoint if present + if "endpoint" in kwargs and kwargs["endpoint"]: + kwargs["endpoint"] = kwargs["endpoint"].replace(model, model_name) + kwargs["model"] = model_name - # Perform pre-call checks for routing strategy - self.routing_strategy_pre_call_checks(deployment=deployment) + # Perform pre-call checks for routing strategy + self.routing_strategy_pre_call_checks(deployment=deployment) - custom_llm_provider: Final = provider_for_generic_call(data) + custom_llm_provider: Final = provider_for_generic_call(data) - response: Final = original_function( - **{ - **data, - "custom_llm_provider": custom_llm_provider, - "caching": self._core_cache_responses, - **kwargs, - } - ) + response: Final = original_function( + **{ + **data, + "custom_llm_provider": custom_llm_provider, + "caching": self._core_cache_responses, + **kwargs, + } + ) - self.success_calls[model_name] += 1 - verbose_router_logger.info("%s(model=%s)\x1b[32m 200 OK\x1b[0m", handler_name, model_name) - return response - except Exception as e: - verbose_router_logger.info("%s(model=%s)\x1b[31m Exception %s\x1b[0m", handler_name, model, e) - if model is not None: - self.fail_calls[model] += 1 - raise e + self.success_calls[model_name] += 1 + verbose_router_logger.info("%s(model=%s)\x1b[32m 200 OK\x1b[0m", handler_name, model_name) + return response + except Exception as e: + verbose_router_logger.info("%s(model=%s)\x1b[31m Exception %s\x1b[0m", handler_name, model, e) + if model is not None: + self.fail_calls[model] += 1 + self._stamp_failed_attempt( + e, _REQUEST_KWARGS_ADAPTER.validate_python(kwargs), picked=deployment is not None + ) + raise e def embedding( self, @@ -7645,10 +7840,11 @@ class PythonCore(DeprecatedRouterMembers): def _embedding(self, input: str | list[object], model: str, **kwargs): model_name = None + deployment = None # rebind-ok: pre-init so the except block can stamp a failure with no deployment picked try: verbose_router_logger.debug("Inside embedding()- model: %s", model) - with embedding_deployment_selection(): - deployment: Final = self.get_available_deployment( + with embedding_deployment_selection(), picks_reserve(True): + deployment = self.get_available_deployment( # rebind-ok: set on success, see pre-init model=model, input=input, specific_deployment=kwargs.pop("specific_deployment", None), @@ -7705,6 +7901,9 @@ class PythonCore(DeprecatedRouterMembers): if model_name is not None: self.fail_calls[model_name] += 1 self._stamp_retry_skip_deployment_id(e, kwargs) + self._stamp_failed_attempt( + e, _REQUEST_KWARGS_ADAPTER.validate_python(kwargs), picked=deployment is not None + ) raise e async def aembedding( @@ -7734,11 +7933,12 @@ class PythonCore(DeprecatedRouterMembers): async def _aembedding(self, input: str | list[object], model: str, **kwargs): model_name = None + deployment = None # rebind-ok: pre-init so the except block can stamp a failure with no deployment picked try: verbose_router_logger.debug("Inside _aembedding()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) with embedding_deployment_selection(): - deployment: Final = await self._core_async_get_available_deployment( + deployment = await self._core_async_get_available_deployment( # rebind-ok: set on success, see pre-init model=model, input=input, specific_deployment=kwargs.pop("specific_deployment", None), @@ -7785,6 +7985,9 @@ class PythonCore(DeprecatedRouterMembers): if model_name is not None: self.fail_calls[model_name] += 1 self._stamp_retry_skip_deployment_id(e, kwargs) + self._stamp_failed_attempt( + e, _REQUEST_KWARGS_ADAPTER.validate_python(kwargs), picked=deployment is not None + ) raise e #### FILES API #### @@ -7949,68 +8152,71 @@ class PythonCore(DeprecatedRouterMembers): Returns: VectorStoreCreateResponse """ - try: - # If model is None, use the factory function approach (direct SDK call) - if model is None: - from litellm.vector_stores.main import acreate + with owning_picks(self._core_least_busy_reservations, call_id_of(CALL_IDENTITY.validate_python(kwargs))): + try: + # If model is None, use the factory function approach (direct SDK call) + if model is None: + from litellm.vector_stores.main import acreate - # Use the factory function to handle the call - factory_fn: Final = self.factory_function(acreate, call_type="avector_store_create") - return await factory_fn(**kwargs) + # Use the factory function to handle the call + factory_fn: Final = self.factory_function(acreate, call_type="avector_store_create") + return await factory_fn(**kwargs) - from litellm.vector_stores import acreate as avector_store_create_sdk + from litellm.vector_stores import acreate as avector_store_create_sdk - parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) - deployment: Final = await self._core_async_get_available_deployment( - model=model, - messages=[{"role": "user", "content": "vector-store-api-fake-text"}], - specific_deployment=kwargs.pop("specific_deployment", None), - request_kwargs=kwargs, - ) - data: Final = deployment["litellm_params"].copy() - model_name: Final = data["model"] - self._update_kwargs_with_deployment( - deployment=deployment, - kwargs=kwargs, - function_name="avector_store_create", - ) - - model_client: Final = self._get_async_openai_model_client( - deployment=deployment, - kwargs=kwargs, - ) - self.total_calls[model_name] += 1 - - # Get custom provider from deployment params - custom_llm_provider = data.get("custom_llm_provider") - _, inferred_custom_llm_provider, _, _ = get_llm_provider( - model=data["model"], - custom_llm_provider=custom_llm_provider, - ) - custom_llm_provider = custom_llm_provider or inferred_custom_llm_provider - - async with self._deployment_slot(deployment=deployment, kwargs=kwargs, parent_otel_span=parent_otel_span): - response = await avector_store_create_sdk( - **{ - **data, - "custom_llm_provider": custom_llm_provider, - "caching": self._core_cache_responses, - "client": model_client, - **kwargs, - } + parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) + deployment: Final = await self._core_async_get_available_deployment( + model=model, + messages=[{"role": "user", "content": "vector-store-api-fake-text"}], + specific_deployment=kwargs.pop("specific_deployment", None), + request_kwargs=kwargs, + ) + data: Final = deployment["litellm_params"].copy() + model_name: Final = data["model"] + self._update_kwargs_with_deployment( + deployment=deployment, + kwargs=kwargs, + function_name="avector_store_create", ) - self.success_calls[model_name] += 1 - verbose_router_logger.info("litellm.avector_store_create(model=%s)\x1b[32m 200 OK\x1b[0m", model_name) + model_client: Final = self._get_async_openai_model_client( + deployment=deployment, + kwargs=kwargs, + ) + self.total_calls[model_name] += 1 - return response - except Exception as e: - verbose_router_logger.exception( - "litellm.avector_store_create(model=%s)\x1b[31m Exception %s\x1b[0m", model, e - ) - if model is not None: - self.fail_calls[model] += 1 - raise e + # Get custom provider from deployment params + custom_llm_provider = data.get("custom_llm_provider") + _, inferred_custom_llm_provider, _, _ = get_llm_provider( + model=data["model"], + custom_llm_provider=custom_llm_provider, + ) + custom_llm_provider = custom_llm_provider or inferred_custom_llm_provider + + async with self._deployment_slot( + deployment=deployment, kwargs=kwargs, parent_otel_span=parent_otel_span + ): + response = await avector_store_create_sdk( + **{ + **data, + "custom_llm_provider": custom_llm_provider, + "caching": self._core_cache_responses, + "client": model_client, + **kwargs, + } + ) + + self.success_calls[model_name] += 1 + verbose_router_logger.info("litellm.avector_store_create(model=%s)\x1b[32m 200 OK\x1b[0m", model_name) + + return response + except Exception as e: + verbose_router_logger.exception( + "litellm.avector_store_create(model=%s)\x1b[31m Exception %s\x1b[0m", model, e + ) + if model is not None: + self.fail_calls[model] += 1 + raise e def _override_vector_store_methods_for_router(self): """ @@ -8258,12 +8464,13 @@ class PythonCore(DeprecatedRouterMembers): try: verbose_router_logger.debug("Inside _acancel_batch()- model: %s", model) parent_otel_span: Final = get_parent_otel_span_from_kwargs(kwargs) - deployment: Final = await self._core_async_get_available_deployment( - model=model, - messages=[{"role": "user", "content": "batch-api-fake-text"}], - specific_deployment=kwargs.pop("specific_deployment", None), - request_kwargs=kwargs, - ) + with picks_reserve(False): + deployment: Final = await self._core_async_get_available_deployment( + model=model, + messages=[{"role": "user", "content": "batch-api-fake-text"}], + specific_deployment=kwargs.pop("specific_deployment", None), + request_kwargs=kwargs, + ) selected_deployment_id: Final = (deployment.get("model_info") or {}).get("id") data: Final = deployment["litellm_params"].copy() @@ -8406,6 +8613,8 @@ class PythonCore(DeprecatedRouterMembers): "acreate_realtime_client_secret", "arealtime_calls", "acreate_realtime_transcription_session", + "acreate_realtime_translation_client_secret", + "arealtime_translation_calls", "_aresponses_websocket", "acreate_fine_tuning_job", "acancel_fine_tuning_job", @@ -8676,6 +8885,8 @@ class PythonCore(DeprecatedRouterMembers): "acreate_realtime_client_secret", "arealtime_calls", "acreate_realtime_transcription_session", + "acreate_realtime_translation_client_secret", + "arealtime_translation_calls", ): return await self._ageneric_api_call_with_fallbacks( original_function=original_function, @@ -9019,8 +9230,9 @@ class PythonCore(DeprecatedRouterMembers): kwargs[metadata_variable_name] = meta if not isinstance(meta, dict): return None + configured_failed_id: Final[str | None] = getattr(exception, "failed_configured_deployment_id", None) prev_excluded: Final = set(meta.get("_failover_excluded_ids") or []) - excluded: Final = prev_excluded | {failed_id} + excluded: Final = prev_excluded | {configured_failed_id or failed_id} all_ids: Final = { (d.get("model_info") or {}).get("id") @@ -9125,11 +9337,17 @@ class PythonCore(DeprecatedRouterMembers): if include_fallback_errors: input_kwargs["include_fallback_errors"] = True - # ORDER-BASED FALLBACKS: prepend higher order levels to the fallback list - # Skip for error types that have their own dedicated fallback handlers - _skip_order_fallback: Final = isinstance( - e, - (litellm_exceptions.ContextWindowExceededError, litellm_exceptions.ContentPolicyViolationError), + context_window_fallback_model_group: Final = ( + self._get_fallback_model_group_for_lookup_groups( + fallbacks=context_window_fallbacks, + lookup_groups=lookup_groups, + ) + if isinstance(e, litellm_exceptions.ContextWindowExceededError) and context_window_fallbacks is not None + else None + ) + _skip_order_fallback: Final = ( + isinstance(e, litellm_exceptions.ContentPolicyViolationError) + or context_window_fallback_model_group is not None ) _request_team_id: Final[str | None] = (kwargs.get("metadata", {}) or {}).get("user_api_key_team_id") # Use wildcard-aware lookup so order-based fallback also works for model @@ -9175,14 +9393,23 @@ class PythonCore(DeprecatedRouterMembers): "original_model_group": original_model_group, } ) - response = await run_async_fallback( - *args, - **input_kwargs, - ) - return response + try: + return await run_async_fallback( + *args, + **input_kwargs, + ) + except Exception: + if isinstance(original_exception, litellm_exceptions.ContextWindowExceededError): + raise original_exception + raise # Weighted intra-group failover (simple-shuffle only); see _maybe_run_weighted_failover. - if self.enable_weighted_failover and not _skip_order_fallback and original_model_group is not None: + if ( + self.enable_weighted_failover + and not _skip_order_fallback + and not isinstance(e, litellm_exceptions.ContextWindowExceededError) + and original_model_group is not None + ): response = await self._maybe_run_weighted_failover( exception=e, original_model_group=original_model_group, @@ -9200,7 +9427,7 @@ class PythonCore(DeprecatedRouterMembers): # check if client-side fallbacks are used (e.g. fallbacks = ["gpt-3.5-turbo", "claude-3-haiku"] or fallbacks=[{"model": "gpt-3.5-turbo", "messages": [{"role": "user", "content": "Hey, how's it going?"}]}] is_non_standard_fallback_format: Final = check_non_standard_fallback_format(fallbacks=fallbacks) - if is_non_standard_fallback_format: + if is_non_standard_fallback_format and context_window_fallback_model_group is None: input_kwargs.update( { "fallback_model_group": fallbacks, @@ -9216,16 +9443,7 @@ class PythonCore(DeprecatedRouterMembers): return response if isinstance(e, litellm_exceptions.ContextWindowExceededError): - if context_window_fallbacks is not None: - context_window_fallback_model_group: Final[list[str] | None] = ( - self._get_fallback_model_group_for_lookup_groups( - fallbacks=context_window_fallbacks, - lookup_groups=lookup_groups, - ) - ) - if context_window_fallback_model_group is None: - raise original_exception - + if context_window_fallback_model_group is not None: input_kwargs.update( { "fallback_model_group": context_window_fallback_model_group, @@ -9239,7 +9457,7 @@ class PythonCore(DeprecatedRouterMembers): ) return response - else: + elif context_window_fallbacks is None: error_message = f"model={model_group}. context_window_fallbacks={mask_sensitive_structure(context_window_fallbacks)}. fallbacks={mask_sensitive_structure(fallbacks)}.\n\nSet 'context_window_fallback' - https://docs.litellm.ai/docs/routing#fallbacks" verbose_router_logger.info( msg=f"Got 'ContextWindowExceededError'. No context_window_fallback set. Defaulting \ @@ -9397,38 +9615,39 @@ class PythonCore(DeprecatedRouterMembers): mock_timeout: Final = kwargs.pop("mock_timeout", None) - try: - self._handle_mock_testing_fallbacks( - kwargs=kwargs, - model_group=model_group, - fallbacks=fallbacks, - context_window_fallbacks=context_window_fallbacks, - content_policy_fallbacks=content_policy_fallbacks, - ) + with owning_picks(self._core_least_busy_reservations, call_id_of(CALL_IDENTITY.validate_python(kwargs))): + try: + self._handle_mock_testing_fallbacks( + kwargs=kwargs, + model_group=model_group, + fallbacks=fallbacks, + context_window_fallbacks=context_window_fallbacks, + content_policy_fallbacks=content_policy_fallbacks, + ) - if mock_timeout is not None: - response = await self.async_function_with_retries(*args, **kwargs, mock_timeout=mock_timeout) - else: - response = await self.async_function_with_retries(*args, **kwargs) - if verbose_router_logger.isEnabledFor(logging.DEBUG): - verbose_router_logger.debug("Async Response: %s", response) - response = add_fallback_headers_to_response( - response=response, - attempted_fallbacks=0, - ) - return response - except Exception as e: - return await self.async_function_with_fallbacks_common_utils( - e, - disable_fallbacks, - fallbacks, - context_window_fallbacks, - content_policy_fallbacks, - model_group, - args, - kwargs, - include_fallback_errors=include_fallback_errors, - ) + if mock_timeout is not None: + response = await self.async_function_with_retries(*args, **kwargs, mock_timeout=mock_timeout) + else: + response = await self.async_function_with_retries(*args, **kwargs) + if verbose_router_logger.isEnabledFor(logging.DEBUG): + verbose_router_logger.debug("Async Response: %s", response) + response = add_fallback_headers_to_response( + response=response, + attempted_fallbacks=0, + ) + return response + except Exception as e: + return await self.async_function_with_fallbacks_common_utils( + e, + disable_fallbacks, + fallbacks, + context_window_fallbacks, + content_policy_fallbacks, + model_group, + args, + kwargs, + include_fallback_errors=include_fallback_errors, + ) def _handle_mock_testing_fallbacks( self, @@ -9532,7 +9751,7 @@ class PythonCore(DeprecatedRouterMembers): response = add_retry_headers_to_response(response=response, attempted_retries=0, max_retries=None) return response except Exception as e: - if is_guardrail_intervention(e): + if is_guardrail_intervention(e) or is_agentic_followup_failure(e): raise current_attempt = None original_exception = e @@ -9627,6 +9846,7 @@ class PythonCore(DeprecatedRouterMembers): # Update retry tracking metadata before each retry attempt _metadata["attempted_retries"] = current_attempt + 1 _metadata["max_retries"] = num_retries + carry_superseded_attempt_usage(kwargs) # if the function call is successful, no exception will be raised and we'll break out of the loop response = await self.make_call(original_function, *args, **kwargs) if coroutine_checker.is_async_callable(response): # async errors are often returned as coroutines @@ -9640,6 +9860,8 @@ class PythonCore(DeprecatedRouterMembers): return response except Exception as e: + if is_agentic_followup_failure(e): + raise # Always track the latest error so we raise the most # recent exception instead of the first one. original_exception = e @@ -10184,8 +10406,9 @@ class PythonCore(DeprecatedRouterMembers): return False exception_status: Final = getattr(exception, "status_code", "") + failure_call_details: Final = _CALL_KWARGS_ADAPTER.validate_python(kwargs) - if is_caller_timeout_408(kwargs, exception_status): + if is_caller_timeout_408(failure_call_details, exception_status): verbose_router_logger.debug( "Router: Exiting 'deployment_callback_on_failure' without cooldown. " "A timeout the caller set caused this 408, not the deployment's health." @@ -10209,6 +10432,18 @@ class PythonCore(DeprecatedRouterMembers): "Caller-scoped OAuth authentication failed, not the deployment." ) return False + if is_caller_entra_credential_failure( + caller_failure_deployment, + self._active_default_litellm_params(), + failure_call_details, + exception_status, + exception, + ): + verbose_router_logger.debug( + "Router: Exiting 'deployment_callback_on_failure' without cooldown. " + "Entra ID rejected a credential the caller sent, not the deployment's own." + ) + return False exception_headers: Final = exception_mapping_utils._get_response_headers(original_exception=exception) @@ -10717,6 +10952,7 @@ class PythonCore(DeprecatedRouterMembers): messages=None, input=None, request_kwargs=routing_kwargs, + reserve=False, ) if selected is None: no_deployment: Final = await async_raise_no_deployment_exception( @@ -11061,6 +11297,7 @@ class PythonCore(DeprecatedRouterMembers): model_info=_model_info, ) ) + refuse_unservable_numbers(deployment.to_json(exclude_none=True, warnings=False)) # pyright: ignore[reportUnknownMemberType] # pydantic's to_json PythonCore._register_deployment_pricing(deployment) ## Check if LLM Deployment is allowed for this deployment @@ -11564,6 +11801,16 @@ class PythonCore(DeprecatedRouterMembers): return model_info_is_active_for_environment(model_info=deployment.model_info) def set_model_list(self, model_list: list): + """Replace every deployment. All or nothing: when an entry raises, the deployments served + before the call are put back and the error is raised.""" + previous: Final = copy.deepcopy(list(self.__dict__.get("_core_model_list") or ())) + try: + self._replace_model_list(model_list) # pyright: ignore[reportUnknownMemberType] # the legacy untyped model list + except Exception: + self._replace_model_list(previous) # pyright: ignore[reportUnknownMemberType] # see above + raise + + def _replace_model_list(self, model_list: list) -> None: # pyright: ignore[reportUnknownParameterType, reportMissingTypeArgument] # the legacy untyped model list original_model_list: Final = copy.deepcopy(model_list) self._discovered_model_info_cache.flush_cache() with self._deployment_index_lock: @@ -11857,6 +12104,7 @@ class PythonCore(DeprecatedRouterMembers): # add to model list _deployment: Final = served.to_json(exclude_none=True) + refuse_unservable_numbers(_deployment) # initialize client self._add_deployment(deployment=served) @@ -12000,6 +12248,9 @@ class PythonCore(DeprecatedRouterMembers): _deployment_model_id: Final = deployment.model_info.id or "" _deployment_on_router: Final[Deployment | None] = self._core_get_deployment(model_id=_deployment_model_id) served: Final = without_model_capability_flags(deployment) + # `_create_deployment` lists the model name before it can still fail; a dropped deployment + # takes its name back off the list. + names_before: Final = len(self._core_deployment_names) try: if _deployment_on_router is not None: # deployment with this model_id exists on the router @@ -12049,6 +12300,7 @@ class PythonCore(DeprecatedRouterMembers): deployment.model_info.id, e, ) + del self._core_deployment_names[names_before:] self._restore_deployment_after_failed_upsert( previous_deployment=_deployment_on_router, model_id=_deployment_model_id ) @@ -12092,6 +12344,25 @@ class PythonCore(DeprecatedRouterMembers): return (backend_key, backend_key.replace("responses/", "")) return (backend_key,) + @staticmethod + def _catalog_entry_has_token_limit(catalog_entry: Mapping[str, object], field: str) -> bool: + return catalog_entry.get(field) is not None or ( + field == "max_tokens" and catalog_entry.get("max_output_tokens") is not None + ) + + @staticmethod + def _shared_backend_model_info_for_keys( + catalog: Mapping[str, Mapping[str, object]], + backend_keys: tuple[str, ...], + shared_model_info: Mapping[str, object], + ) -> Mapping[str, object]: + catalog_token_limit_fields: Final = frozenset( + field + for field in DEPLOYMENT_SCOPED_TOKEN_LIMIT_FIELDS + if any(PythonCore._catalog_entry_has_token_limit(catalog.get(key) or {}, field) for key in backend_keys) + ) + return {field: value for field, value in shared_model_info.items() if field not in catalog_token_limit_fields} + @staticmethod def _deployment_model_cost_payload(deployment: Deployment) -> dict[str, object]: # mutable-ok: cost-map entry """The ``model_info`` a deployment contributes to ``litellm.model_cost``. @@ -12204,6 +12475,31 @@ class PythonCore(DeprecatedRouterMembers): ## OLD MODEL REGISTRATION ## Kept to prevent breaking changes backend_keys: Final = PythonCore._backend_cost_map_keys(model=model, custom_llm_provider=custom_llm_provider) + model_provider_prefix: Final = model.partition("/")[0] + catalog_provider: Final = ( + custom_llm_provider + if custom_llm_provider is not None + else model_provider_prefix + if model_provider_prefix in LlmProvidersSet + else None + ) + potential_names: Final = ( + get_potential_model_names(model, catalog_provider) if catalog_provider is not None else None + ) + catalog_backend_keys: Final = ( + ( + *backend_keys, + model, + potential_names["split_model"], + potential_names["stripped_model_name"], + potential_names["combined_model_name"], + potential_names["combined_stripped_model_name"], + potential_names["provider_prefixed_model_name"], + potential_names["region_free_combined_model_name"], + ) + if potential_names is not None + else (*backend_keys, model) + ) # For the shared backend key, keep only cost-map schema fields # (minus custom pricing) so that one deployment's pricing overrides @@ -12211,7 +12507,12 @@ class PythonCore(DeprecatedRouterMembers): # don't pollute another deployment sharing the same backend model # name. Each deployment's full model_info is already stored under # its unique model_id above. - shared_model_info: Final = shared_backend_model_info(model_info) + catalog: Final = catalog_with_runtime_registrations() + shared_model_info: Final = PythonCore._shared_backend_model_info_for_keys( + catalog=catalog, + backend_keys=catalog_backend_keys, + shared_model_info=shared_backend_model_info(model_info), + ) python_host.invoke("register_model")( model_cost={_key: keep_registered_mode(_key, shared_model_info) for _key in backend_keys}, persist_across_reloads=False, @@ -12680,6 +12981,24 @@ class PythonCore(DeprecatedRouterMembers): for deployment in self._routable_deployments(model_name, team_id) ) + def _core_get_configured_max_input_tokens( + self, model_name: str, team_id: str | None = None + ) -> tuple[int | None, ...]: + """ + Return the max_input_tokens each deployment a request from team_id to + model_name can route to (see _routable_deployments) sets in its own + model_info, in model_list order, None for a deployment that sets none + or a malformed one. Unlike get_model_listing_info, neither the cost map + nor a discovered limit is read, so only an operator's own value counts, + and a value a saved /model/info response copied from the cost map is + skipped too. + + Returns an empty tuple for wildcard-expanded or unknown names. + """ + return tuple( + _operator_max_input_tokens(deployment) for deployment in self._routable_deployments(model_name, team_id) + ) + def _core_get_search_tool_support(self, model_name: str, team_id: str | None = None) -> tuple[bool | None, ...]: """ Whether each deployment a request from team_id to model_name can route @@ -13202,6 +13521,7 @@ class PythonCore(DeprecatedRouterMembers): "providers": [llm_provider], "description": model_group_description, **model_info, + "supports_continuation": model_info.get("supports_continuation") is True, "supports_fast_mode": True, "supported_reasoning_efforts": None, "supported_endpoints": None, @@ -13269,6 +13589,8 @@ class PythonCore(DeprecatedRouterMembers): and model_info["supports_url_context"] is True ): model_group_info.supports_url_context = True + if model_info.get("supports_continuation") is True: + model_group_info.supports_continuation = True if model_info.get("supports_reasoning", None) is not None and model_info["supports_reasoning"] is True: model_group_info.supports_reasoning = True @@ -14469,9 +14791,7 @@ class PythonCore(DeprecatedRouterMembers): """ if team_id is not None and self._team_deployments_named(team_id, model_group): return self._core_get_all_deployments(model_name=model_group, team_id=team_id) - own: Final = cast( # cast-ok: the private alias returns what get_all_deployments returns - list[DeploymentTypedDict], self._get_all_deployments(model_name=model_group) - ) + own: Final = self._get_all_deployments(model_name=model_group) named: Final = [*own, *self._core_get_model_list_from_routing_groups(model_name=model_group)] return named or self._get_wildcard_deployments(model_name=model_group) @@ -14779,6 +15099,7 @@ class PythonCore(DeprecatedRouterMembers): input: str | list[object] | None, request_kwargs: Mapping[str, object] | None = None, tokenizer_model: str = "", + deployments: Sequence[Mapping[str, object]] = (), ) -> int: """ Count input tokens for context-window pre-call checks. @@ -14813,11 +15134,15 @@ class PythonCore(DeprecatedRouterMembers): if input is not None: from openai.types.responses.response_create_params import ResponseInputParam + from litellm.litellm_core_utils.token_counter import split_embedding_input_tokens from litellm.responses.litellm_completion_transformation.transformation import ( LiteLLMCompletionResponsesConfig, ) - typed_input: Final = cast(str | ResponseInputParam, input) # cast-ok: str | list matches transform input + text_input, _ = split_embedding_input_tokens(input, partial(deployment_backend_models, deployments)) + typed_input: Final = cast( # cast-ok: str | list matches transform input + str | ResponseInputParam, text_input + ) input_messages: Final = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages( input=typed_input, responses_api_request={"instructions": instructions} if instructions is not None else {}, @@ -14885,6 +15210,7 @@ class PythonCore(DeprecatedRouterMembers): self.served_openai_models(model) or served_openai_models(healthy_deployments) ) or "", + deployments=healthy_deployments, ) except Exception as e: # noqa: BLE001 # best-effort: an uncountable prompt must not fail the request verbose_router_logger.error( @@ -14915,6 +15241,7 @@ class PythonCore(DeprecatedRouterMembers): self.served_openai_models(model) or served_openai_models(deployments) ) or "", + deployments=deployments, ) except Exception as e: verbose_router_logger.error( @@ -15672,10 +15999,15 @@ class PythonCore(DeprecatedRouterMembers): # IF TEAM ID SPECIFIED ON MODEL, AND REQUEST CONTAINS USER_API_KEY_TEAM_ID, FILTER OUT MODELS THAT ARE NOT IN THE TEAM ## THIS PREVENTS WRITING FILES OF OTHER TEAMS TO MODELS THAT ARE TEAM-ONLY MODELS + by_id: Final = healthy_deployments if isinstance(healthy_deployments, dict) else None # pyright: ignore[reportUnknownVariableType] # the legacy deployment dict healthy_deployments = filter_team_based_models( healthy_deployments=healthy_deployments, request_kwargs=request_kwargs, ) + if by_id is not None and not healthy_deployments: + # Another team's deployment asked for by id: refused under its group's name. + group_name: Final = str(by_id.get("model_name")) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # see above + model = group_name # rebind-ok: the error names the group if verbose_router_logger.isEnabledFor(logging.DEBUG): verbose_router_logger.debug("healthy_deployments after team filter: %s", healthy_deployments) @@ -15998,6 +16330,7 @@ class PythonCore(DeprecatedRouterMembers): messages=messages, input=input, specific_deployment=specific_deployment, + reserve=pick_reserves(default=True), ) async def _async_get_available_deployment( @@ -16007,6 +16340,7 @@ class PythonCore(DeprecatedRouterMembers): messages: list[dict[str, str]] | None, input: str | list | None, specific_deployment: bool | None, + reserve: bool, ): if ( self._core_routing_strategy != "usage-based-routing-v2" @@ -16103,6 +16437,7 @@ class PythonCore(DeprecatedRouterMembers): messages=messages, input=input, request_kwargs=request_kwargs, + reserve=reserve and request_kwargs not in (None, {}), ) if deployment is None: exception: Final = await async_raise_no_deployment_exception( @@ -16272,6 +16607,7 @@ class PythonCore(DeprecatedRouterMembers): messages=messages, input=input, request_kwargs=request_kwargs, + reserve=pick_reserves(default=False) and request_kwargs not in (None, {}), ) if deployment is None: @@ -16981,6 +17317,16 @@ class PythonCore(DeprecatedRouterMembers): model, ) ) + # As the async pick: a team-owned deployment serves only its own team's callers, also when + # asked for by id (then refused under its group's name). + by_id: Final = healthy_deployments if isinstance(healthy_deployments, dict) else None # pyright: ignore[reportUnknownVariableType] # the legacy deployment dict + healthy_deployments = filter_team_based_models( # rebind-ok: the team filter narrows # pyright: ignore[reportUnknownVariableType] # legacy selector type + healthy_deployments=healthy_deployments, # pyright: ignore[reportArgumentType] # legacy selector type + request_kwargs=request_kwargs, + ) + if by_id is not None and not healthy_deployments: + group_name: Final = str(by_id.get("model_name")) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # see above + model = group_name # rebind-ok: the error names the group strategy, strategy_selector = self._get_routing_context(model, request_kwargs) routing_kwargs: Final = _ROUTING_KWARGS_ADAPTER.validate_python(request_kwargs) pick_attributes: Final = _deployment_pick_attributes(model, routing_kwargs) @@ -17149,6 +17495,7 @@ class PythonCore(DeprecatedRouterMembers): messages=messages, input=input, request_kwargs=request_kwargs, + reserve=pick_reserves(default=False) and request_kwargs not in (None, {}), ) if deployment is None: @@ -17329,6 +17676,7 @@ class PythonCore(DeprecatedRouterMembers): messages=messages, input=input, request_kwargs=request_kwargs, + reserve=pick_reserves(default=False) and request_kwargs not in (None, {}), ) if deployment is None: diff --git a/litellm/router_python_host.py b/litellm/router_python_host.py index 8156740144e..8ab2c06b82f 100644 --- a/litellm/router_python_host.py +++ b/litellm/router_python_host.py @@ -7,7 +7,10 @@ come from ``dynamic()`` (``litellm/router_config.py``). A Rust core gets the sam """ import asyncio -from collections.abc import Awaitable, Callable, Sequence +import importlib +import time +import types +from collections.abc import Awaitable, Callable, Mapping, Sequence from typing import ( TYPE_CHECKING, Final, @@ -19,12 +22,13 @@ from typing import ( from typing_extensions import overload import litellm -from litellm.router_config import RouterDynamicConfig, live_dynamic_config +from litellm.router_config import RouterConfig, RouterDynamicConfig, live_dynamic_config if TYPE_CHECKING: from pydantic import BaseModel - from litellm.caching.caching import Cache + from litellm.caching.caching import Cache, RedisCache + from litellm.caching.dual_cache import DualCache from litellm.litellm_core_utils.logging_callback_manager import LoggingCallbackManager from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper from litellm.text_completions.streaming_iterator import TextCompletionStreamWrapper @@ -97,7 +101,7 @@ class PythonHost: def invoke(self, op: str) -> Endpoint: ... def invoke(self, op: str) -> Endpoint: """The litellm function named ``op`` (``acompletion``, ``get_model_info``, ...), looked up at call time.""" - endpoint: Final[object] = getattr(litellm, op, None) + endpoint: Final[object] = getattr(litellm, op, None) if "." not in op else _dotted(op) if endpoint is None: raise AttributeError(f"litellm has no endpoint {op!r}") if not callable(endpoint): @@ -107,6 +111,10 @@ class PythonHost: def sleep(self, seconds: float) -> Awaitable[None]: return asyncio.sleep(seconds) + def sleep_sync(self, seconds: float) -> None: + """The backoff of a sync endpoint's retry.""" + time.sleep(seconds) + def dynamic(self) -> RouterDynamicConfig: """The process settings, read live on each access (``current_dynamic_config()`` takes a snapshot).""" return cast(RouterDynamicConfig, live_dynamic_config) # cast-ok: the live view reads the same fields @@ -116,7 +124,7 @@ class PythonHost: return litellm.logging_callback_manager def callback_list(self, name: CallbackList) -> list[object]: # mutable-ok: the process callback list itself - value: Final = getattr(litellm, name) + value: Final[object] = getattr(litellm, name) # pyright: ignore[reportAny] # an untyped litellm global return cast(list[object], value) # cast-ok: the process callback list is an untyped litellm global def set_callback_list(self, name: CallbackList, value: list[object]) -> None: # mutable-ok: assigned as given @@ -131,5 +139,78 @@ class PythonHost: def suppress_debug_info(self) -> None: litellm.suppress_debug_info = True + def routing_cache(self, config: RouterConfig) -> "DualCache": + """The store a router keeps its routing state in (cooldowns, fail counts, usage): in memory, + plus Redis when the router's arguments name one. The host builds and owns it; a Rust core + reads and writes it through cache steps.""" + from litellm.caching.caching import DualCache, InMemoryCache + + return DualCache(redis_cache=redis_cache_for(config), in_memory_cache=InMemoryCache()) + + +def redis_cache_for(config: RouterConfig) -> "RedisCache | None": + """The Redis cache the router's ``redis_*`` and ``cache_kwargs`` arguments describe, or None.""" + import json + + from litellm.caching.caching import RedisCache, RedisClusterCache + from litellm.utils import get_secret + + url: Final = config.get("redis_url") + host: Final = config.get("redis_host") + port: Final = config.get("redis_port") + if url is None and (host is None or port is None): + return None + settings: Final[dict[str, object]] = {} # mutable-ok: built here, then passed as keywords + if url is not None: + settings["url"] = url + if host is not None: + settings["host"] = host + if port is not None: + settings["port"] = str(port) + if config.get("redis_password") is not None: + settings["password"] = config.get("redis_password") + if config.get("redis_db") is not None: + settings["db"] = str(config.get("redis_db")) + extra: Final = config.get("cache_kwargs") + if isinstance(extra, dict): + settings.update({str(key): value for key, value in extra.items()}) # pyright: ignore[reportUnknownVariableType, reportUnknownArgumentType] # the cache_kwargs argument is untyped + nodes: object = settings.get("startup_nodes") # rebind-ok: the env cluster nodes when the arguments name none + if not nodes: + env_nodes: Final[object] = get_secret("REDIS_CLUSTER_NODES") # pyright: ignore[reportUnknownVariableType] # get_secret is untyped + if isinstance(env_nodes, str): + parsed: Final[object] = json.loads(env_nodes) # pyright: ignore[reportAny] # plain JSON + nodes = parsed # rebind-ok: see above + if nodes: + return RedisClusterCache(**{**settings, "startup_nodes": nodes}) # pyright: ignore[reportArgumentType] # RedisCache's keyword arguments + return RedisCache(**settings) # pyright: ignore[reportArgumentType] # RedisCache's keyword arguments + python_host: Final = PythonHost() + + +def _dotted(op: str) -> object: + """``op`` named by its path under ``litellm`` (``vector_stores.main.asearch``), read at call time. + + Each segment is a module attribute, a submodule, or a key of a mapping such as a module's + table of generated endpoints. + """ + node: object = litellm # rebind-ok: walks the path one segment at a time + path: str = "litellm" # rebind-ok: the module path walked so far + for segment in op.split("."): + path = f"{path}.{segment}" + if isinstance(node, Mapping): + node = cast(Mapping[str, object], node).get(segment) # cast-ok: endpoint tables are keyed by name + elif isinstance(node, types.ModuleType) and (submodule := _submodule(path)) is not None: + node = submodule + else: + node = cast(object, getattr(node, segment, None)) # cast-ok: any attribute + if node is None: + return None + return node + + +def _submodule(path: str) -> types.ModuleType | None: + try: + return importlib.import_module(path) + except ModuleNotFoundError: + return None diff --git a/litellm/router_rust/__init__.py b/litellm/router_rust/__init__.py new file mode 100644 index 00000000000..42cfc56aca4 --- /dev/null +++ b/litellm/router_rust/__init__.py @@ -0,0 +1,13 @@ +""" +The Rust router core's Python side: ``RustCore`` (``core``) and the host-side modules router-core +(litellm-rust/crates/router-core) reaches through its steps. + +- ``steps``: answers to host steps that need live Python objects (strategies, pre-routing, + pre-call facts, plugins, callbacks, caller access) +- ``invoke``: the host side of ``Host::invoke``, one attempt against one deployment (request + shaping, endpoints, streams, slots, retry and fallback metadata, prompt management, websockets) +- ``surface``: the Python ``Router`` API kept over router-core's state (registry views, model + info, settings, health, retries, fallbacks, alerting); a Rust host needs none of it + +Nothing is imported here, so importing one module does not import the core. +""" diff --git a/litellm/router_rust/core.py b/litellm/router_rust/core.py new file mode 100644 index 00000000000..395b580d9b2 --- /dev/null +++ b/litellm/router_rust/core.py @@ -0,0 +1,4943 @@ +""" +``RustCore``: the router core served by litellm-rust/crates/router-core through ``_native``. + +The Rust core owns the registry, selection, retries, fallbacks and cooldowns. It reaches outside +itself only through its host, and the host never calls back into a Python router: + +- every attempt runs through the host: ``router_attempt`` builds the request for the one + deployment Rust picked and ``PythonHost.invoke(op)`` calls ``litellm.`` with it +- the core records every outcome (cooldowns, allowed-fails counters, usage) itself, in the routing + cache the host builds and owns (``PythonHost.routing_cache``), as far as the outcome callbacks the + Python router would have running for the request reach (``OptionalChecks.outcome_callbacks``) +- sleeps, fallback access and budget checks, and cache reads and writes are host steps + +``RustCore`` does not build, wrap or read a ``PythonCore``. Settings are resolved from the +``RouterConfig`` and the host's process settings; the views (``registry()``, ``settings()``, +``health()``) are read from the Rust handle. A member the Rust core does not serve raises +``RustCoreUnsupported`` (an ``AttributeError``) instead of reaching a Python core, so deleting +``router_python_core.py`` cannot change what this core does. +""" + +import contextlib +import dataclasses +import inspect +import itertools +import json +from collections.abc import Awaitable, Callable, Coroutine, Iterable, Mapping, Sequence +from datetime import date, datetime, time +from functools import partial +from time import perf_counter +from time import time as unix_time +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, Literal, Protocol, TypeAlias, final + +from litellm._internal_context import service_target +from litellm.constants import DEFAULT_COOLDOWN_TIME_SECONDS, HEALTH_CHECKS_TARGET +from litellm.integrations.custom_guardrail import is_guardrail_intervention +from litellm.litellm_core_utils.add_retry_fallback_headers import ( + add_fallback_headers_to_response, + add_retry_headers_to_response, + apply_quality_router_decision_headers, + apply_remaining_usage_headers, + apply_response_model_id, + complexity_router_decision_headers, + ensure_response_additional_headers, + prepare_response_for_header_attachment, +) +from litellm.litellm_core_utils.agentic_followup_failure import is_agentic_followup_failure +from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type +from litellm.litellm_core_utils.core_helpers import as_object_list, as_str_mapping, without +from litellm.litellm_core_utils.routing_common_utils import ( + format_content_policy_fallback_hint, + format_fallback_outcome_message, + format_no_fallback_group_message, + get_request_team_id, + is_web_search_request, + truncate_fallback_error_detail, +) +from litellm.litellm_core_utils.routing_groups import validate_routing_strategy +from litellm.litellm_core_utils.secret_redaction import redact_string +from litellm.router_api import ( + ROUTER_INIT_ARGS, + SETTING_FIELDS, + ApplyResult, + ChangeSet, + RouterHealth, + RouterRegistry, + RouterSettings, + RoutingContext, + RoutingObservers, +) +from litellm.router_attempt import for_requested_model, request_from_call +from litellm.router_config import RouterConfig, RouterDynamicConfig, detached +from litellm.router_python_host import PythonHost +from litellm.router_rust.invoke.endpoints import ( + AttemptCall, + Plan, + RustEndpoints, + arm_compaction_state, + attempt_call, + clean_realtime_session_deployment, + compacted_attempt, + failover_fields, + generic_plan, + log_refused_call, + log_refused_call_sync, + pinned_video_deployment, + plan_for, + reports_own_success, + scoped_fallback_fields, + selection_endpoint, + stamp_error, + unrouted_fields, +) +from litellm.router_rust.invoke.shaping import Shaping +from litellm.router_rust.invoke.slots import enter_deployment_slot, max_parallel_requests_limit +from litellm.router_rust.invoke.streaming import ( + StreamAttempt, + continuation_flag, + continuation_routing, + open_attempt_stream, + open_attempt_stream_sync, + register_continuation_prefill_check, + shape_attempt_kwargs, +) +from litellm.router_rust.invoke.walk import FallbackOutcomes, WalkMetadata, await_all, log_retry_into +from litellm.router_rust.steps.access import caller_fields, selection_refusal +from litellm.router_rust.steps.callbacks import OptionalChecks, RustOptionalChecks +from litellm.router_rust.steps.plugins import SYNC_PATH_MESSAGE, candidate_models, run_plugins +from litellm.router_rust.steps.precall import ( + DECISIONS_MEDIA_CALL_TYPES, + PreCallFacts, + cannot_serve_route, + declares_no_vision, + refuses_decisions_media, + request_carries_image, + serves_route_capability, +) +from litellm.router_rust.steps.prerouting import PreRouter, PreRoutingStrategies, picks_async +from litellm.router_rust.steps.selection import ( + SELECTOR_ATTRIBUTES, + StrategySelectors, + group_documents, + group_settings, + member_map, + normalize_strategy, + parse_groups, + pick_async, + pick_sync, + picked_id, + routing_pre_call_checks, +) +from litellm.router_rust.surface.alerting import initialize_alerting +from litellm.router_rust.surface.fallbacks import ( + RustFallbacks, + mock_error, + mock_failure, + refuse_malformed_fallbacks, + rejected_fallback_target, +) +from litellm.router_rust.surface.health import ( + RustHealthCallbacks, + failure_already_logged, + failure_status, + first_cooldown, + logged_call, +) +from litellm.router_rust.surface.health_routing import ( + HEALTH_STATE_KEY, + HealthRouting, + failover_document, + fully_unhealthy_model_names, + resolved_allowed_fails_policy, +) +from litellm.router_rust.surface.health_routing import all_blocked as deployments_all_blocked +from litellm.router_rust.surface.health_routing import fully_blocked_model_names as blocked_model_names +from litellm.router_rust.surface.health_routing import is_blocked as deployment_is_blocked +from litellm.router_rust.surface.legacy_members import RustLegacyMembers +from litellm.router_rust.surface.members import RustRegistryMembers +from litellm.router_rust.surface.model_list import typed_deployment +from litellm.router_rust.surface.registry import ( + DEFAULT_DEPLOYMENT_COPIED_ID, + DEFAULT_DEPLOYMENT_FAILING_ID, + INDEX_ATTRIBUTES, + BuildInstall, + HostRegistry, + RustRegistry, + default_deployment_call_error, + default_deployment_copy, + default_deployment_copy_error, + hosted_registry_view, + index_document, + served_default_deployment, +) +from litellm.router_rust.surface.replay import track_live_registry, untrack_live_registry +from litellm.router_rust.surface.retries import ( + GroupPolicies, + RustRetries, + group_policies, + is_policy_per_group, + policy_lookup_error, + raising_groups, + readable_retry_policy, + reads_as_policy, + request_retry_fields, + resolved_retry_policy, + retry_count_error, + static_group_policies, +) +from litellm.router_rust.surface.settings import ( + MISSING, + PLAIN_DEFAULTS, + SettingsUpdate, + apply_construction_effects, + argument_attribute, + default_litellm_params, + initial_plain, + read_settings_update, + request_timeout, + settings_view, +) +from litellm.router_strategy.least_busy import CALL_IDENTITY, call_id_of, owning_picks, pick_reserves, picks_reserve +from litellm.router_utils.cooldown_cache import ROUTER_COOLDOWNS_TARGET +from litellm.router_utils.cooldown_handlers import get_cooldown_deployment_info, mark_deployment_selection_failure +from litellm.router_utils.endpoint_eligibility import endpoint_for_call, selected_endpoint +from litellm.router_utils.kubernetes_pod_discovery import ( + KubernetesPodDiscovery, + async_resolve_pods_after_bound, + resolve_pods_after_bound, +) +from litellm.router_utils.pre_call_checks.encrypted_content_affinity_check import EncryptedContentAffinityCheck +from litellm.router_utils.router_callbacks.track_deployment_metrics import find_deployment_metadata +from litellm.router_utils.routing_read_batch import ROUTER_USAGE_TARGET, RoutingReadBatch +from litellm.types.router import ( + Deployment, + RouterErrors, + RouterGeneralSettings, + RouterRateLimitError, + RoutingGroup, + RoutingStrategy, +) +from litellm.types.utils import LlmProviders + +if TYPE_CHECKING: + from opentelemetry.trace import Span + + from litellm.caching.dual_cache import DualCache + from litellm.caching.redis_cache import RedisCache + from litellm.integrations.SlackAlerting.slack_alerting import SlackAlerting + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging + from litellm.litellm_core_utils.ptu_shares import PTUTeamCeiling + from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler + from litellm.router_api import UntypedDict + from litellm.router_utils.cooldown_cache import CooldownCache + from litellm.router_utils.health_state_cache import DeploymentHealthCache + from litellm.rust_bridge._native import ( + RouterCall, + RouterCoreHandle, + _CallSteps, # pyright: ignore[reportPrivateUsage] # the stub's step shapes + _FailureReportSteps, # pyright: ignore[reportPrivateUsage] # see above + _SuccessReportSteps, # pyright: ignore[reportPrivateUsage] # see above + ) + from litellm.types.router import ( + CustomRoutingStrategyBase, + DeploymentTypedDict, + GuardrailTypedDict, + PreRoutingHookResponse, + RoutingPlugin, + ) + +_FAILURE_KINDS: Final = ( + "RateLimitError", + "ContextWindowExceededError", + "ContentPolicyViolationError", + "AuthenticationError", + "PermissionDeniedError", + "NotFoundError", + "BadRequestError", + "Timeout", + "APIConnectionError", + "InternalServerError", + "ServiceUnavailableError", + "BadGatewayError", + "GuardrailIntervention", + "CallerCredentialAuthenticationError", + "CallerCredentialRateLimitError", +) +_DECLINED: Final = frozenset({"MalformedRequestFieldError", "UnsupportedEndpointError"}) +_PROVIDERS: Final = tuple(provider.value for provider in LlmProviders) +_DEFAULT_COOLDOWN_SECONDS: Final = 5.0 +# Past this a retry-after no longer fits the Rust core's durations; it cools down as good as forever. +_LONGEST_RETRY_AFTER_SECONDS: Final = 2**63 + +# Constructor arguments this core reads. Any other argument set to something other than its +# unset value keeps the router on the Python core while both exist (make_core decides that from +# the config alone, before any core is built). +_SERVED_ARGUMENTS: Final = frozenset( + { + "model_list", + "routing_strategy", + "routing_strategy_args", + "routing_groups", + "enable_tag_filtering", + "tag_filtering_match_any", + "tag_routing_prefix", + "model_group_alias", + "fallbacks", + "default_fallbacks", + "context_window_fallbacks", + "content_policy_fallbacks", + "num_retries", + "max_fallbacks", + "allowed_fails", + "cooldown_time", + "disable_cooldowns", + "allowed_fails_policy", + "retry_after", + "timeout", + "default_litellm_params", + "fallback_access_check", + "fallback_budget_check", + "enable_mid_stream_fallback_continuation", + "redis_url", + "redis_host", + "redis_port", + "redis_password", + "redis_db", + "cache_kwargs", + "set_verbose", + "debug_level", + # Read host-side by the endpoint plans (litellm/router_rust/invoke/endpoints.py). + "stream_timeout", + "cache_responses", + "assistants_config", + "search_tools", + "guardrail_list", + "default_priority", + "polling_interval", + "ignore_invalid_deployments", + # Read host-side by the pre-routing strategies (litellm/router_rust/steps/prerouting.py). + "auto_router_capability_limit", + # Decided in router-core (precall.rs); its facts come from litellm/router_rust/steps/precall.py. + "enable_pre_call_checks", + # Run host-side (litellm/router_rust/steps/plugins.py); router-core filters on what they leave. + "plugins", + "retry_policy", + "model_group_retry_policy", + # Health-check routing and the failover flags (litellm/router_rust/surface/health_routing.py). + "enable_health_check_routing", + "health_check_staleness_threshold", + "health_check_ignore_transient_errors", + "background_health_check_model_groups", + "enable_weighted_failover", + "fallback_on_unsupported_params", + # Built host-side as CustomLogger checks (litellm/router_rust/steps/callbacks.py); router-core runs + # their deployment filters through its callback_filters stage. + "optional_pre_call_checks", + "provider_budget_config", + "deployment_affinity_ttl_seconds", + "session_affinity_repin_on_failover", + "model_group_affinity_config", + # Kept as given (litellm/router_rust/surface/settings.py) and read host-side by the endpoint plans + # (default_litellm_params' caching groups) and the slot limits. + "client_ttl", + "caching_groups", + "default_max_parallel_requests", + # Built host-side into a Slack alerting logger (litellm/router_rust/surface/alerting.py). + "alerting_config", + # Kept as given and reported by settings(); nothing in the router reads its fields. + "router_general_settings", + } +) +# Arguments that may be passed at their default without asking for anything. +_UNSET_DEFAULTS: Final[Mapping[str, object]] = MappingProxyType( + { + "cache_responses": False, + "enable_pre_call_checks": False, + "enable_tag_filtering": False, + "retry_policy": None, + "model_group_retry_policy": {}, + } +) +# Settings a changeset may change. Static ones rebuild the Rust core (settings are fixed for a +# core's life); dynamic ones are handed to it as a new dynamic document. +_STATIC_SETTINGS: Final = frozenset( + { + "routing_strategy", + "routing_groups", + "cooldown_time", + "disable_cooldowns", + "allowed_fails_policy", + "retry_after", + "timeout", + "enable_pre_call_checks", + } +) +_DYNAMIC_SETTINGS: Final = frozenset( + { + "default_deployment", + "fallbacks", + "context_window_fallbacks", + "content_policy_fallbacks", + "num_retries", + "max_fallbacks", + "allowed_fails", + "model_group_alias", + "default_litellm_params", + "fallback_access_check", + "fallback_budget_check", + "routing_strategy_args", + "enable_tag_filtering", + "tag_filtering_match_any", + "tag_routing_prefix", + } +) +# Settings only the host reads (the endpoint plans, the slot limits, the budget limiter, the +# settings view). A changeset assigns them as given, the Rust core never sees them, and +# `update_settings` ignores them (none is runtime-updatable). +_HOST_SETTINGS: Final = frozenset( + { + "cache_responses", + "search_tools", + "guardrail_list", + "default_max_parallel_requests", + "provider_budget_config", + "health_check_ignore_transient_errors", + "router_general_settings", + "provider_default_deployment_ids", + "kubernetes_pod_discovery", + # Read by router-core's health-check filter: assigning one rebuilds the Rust core. + "enable_health_check_routing", + "background_health_check_model_groups", + } +) +# The constructor's default `router_general_settings`: one object every router built without the +# argument shares, as the Python core's default argument is. +_DEFAULT_GENERAL_SETTINGS: Final = RouterGeneralSettings() + + +# Plain settings `update_settings` sets that the Rust core's retry loop reads. +_RETRY_POLICY_SETTINGS: Final = ("retry_policy", "model_group_retry_policy") +# Attributes a `del` unsets beyond the setting fields, whose readers then raise AttributeError. +_DELETABLE_ATTRIBUTES: Final = frozenset({"model_group_alias", "num_retries", "scheduler"}) + + +# Calls whose pick least-busy does not hold (`picks_reserve(False)`): a batch cancel makes no +# call that logs a start. +_UNRESERVED_OPS: Final = frozenset({"acancel_batch"}) + + +# Settings converted by `Resolved._selection_setting`. +_SELECTION_SETTINGS: Final = frozenset( + { + "routing_strategy", + "routing_strategy_args", + "enable_tag_filtering", + "tag_filtering_match_any", + "tag_routing_prefix", + } +) +_NUMBER_SETTINGS: Final = frozenset( + {"num_retries", "max_fallbacks", "allowed_fails", "cooldown_time", "retry_after", "timeout"} +) +# The settings `_core_update_settings` casts with `int(value)`. +_UPDATE_INT_SETTINGS: Final = frozenset({"timeout", "num_retries", "retry_after", "allowed_fails", "cooldown_time"}) + + +class RustCoreUnsupported(AttributeError): + """A member or request the Rust core does not serve. It is never forwarded to a Python core.""" + + +def _cache_target(key: str) -> str: + """The service target a routing cache read or write is attributed to, as the Python core's.""" + if key == HEALTH_STATE_KEY: + return HEALTH_CHECKS_TARGET + return ROUTER_COOLDOWNS_TARGET if key.endswith(":cooldown") else ROUTER_USAGE_TARGET + + +# --- failures ----------------------------------------------------------------------------------- + + +def failure_kind(error: BaseException) -> str: + names: Final = tuple(cls.__name__ for cls in type(error).__mro__) + if not _DECLINED.isdisjoint(names): + return "Declined" + if is_guardrail_intervention(error): # pyright: ignore[reportArgumentType] # every attempt error is an Exception + return "GuardrailIntervention" + return next((name for name in names if name in _FAILURE_KINDS), "APIError") + + +def retry_after_seconds(error: BaseException) -> float | None: + """The header cooldown of ``deployment_callback_on_failure``: ``retry-after`` alone, as a whole + number or a date, with a negative or unreadable one read as none.""" + from litellm.litellm_core_utils.exception_mapping_utils import ( + _get_response_headers, # pyright: ignore[reportPrivateUsage] # the failure callback's own read + ) + from litellm.utils import _get_retry_after_from_exception_header # pyright: ignore[reportPrivateUsage] # see above + + headers: Final = _get_response_headers(original_exception=error) # pyright: ignore[reportArgumentType] # every attempt error is an Exception + if headers is None: + return None + seconds: Final = _get_retry_after_from_exception_header(response_headers=headers) # pyright: ignore[reportUnknownVariableType] # an untyped helper's int or None + return float(min(seconds, _LONGEST_RETRY_AFTER_SECONDS)) if seconds is not None and seconds >= 0 else None + + +def attempt_failure(error: BaseException) -> Mapping[str, object]: + status: Final = getattr(error, "status_code", None) + num_retries: Final = getattr(error, "num_retries", None) + # `_deployment_ids_to_skip_on_retry` reads the id off the exception. + named_deployment: Final = getattr(error, "retry_skip_deployment_id", None) or getattr( + error, "failed_deployment_id", None + ) + return { + "ok": False, + "kind": failure_kind(error), + "status": status if isinstance(status, int) and 100 <= status <= 599 else None, + "status_absent": getattr(error, "status_code", "") == "", + "retry_after": retry_after_seconds(error), + "num_retries": num_retries if isinstance(num_retries, int) and num_retries >= 0 else None, + "failed_deployment_id": named_deployment if isinstance(named_deployment, str) else None, + "detail": str(error), + "classes": [cls.__name__ for cls in type(error).__mro__], + "llm_provider": bool(getattr(error, "llm_provider", "")), + "agentic_followup": is_agentic_followup_failure(error), + } + + +def total_tokens(response: object) -> int: + usage: Final = getattr(response, "usage", None) + tokens: Final = getattr(usage, "total_tokens", None) + return tokens if isinstance(tokens, int) else 0 + + +# --- settings ----------------------------------------------------------------------------------- + + +def _json_default(value: object) -> object: + # ISO 8601, which ``typed_deployment`` reads back as the value it was. + if isinstance(value, date | time): + return value.isoformat() + dump: Final = getattr(value, "model_dump", None) + return dump(exclude_none=True) if callable(dump) else str(value) + + +def _plain(value: object) -> object: + """``value`` as plain JSON values, the shape the Rust core reads.""" + loaded: Final[object] = json.loads(json.dumps(value, default=_json_default)) # pyright: ignore[reportAny] # plain JSON + return loaded + + +def _document(value: object) -> Mapping[str, object]: + """A mapping as the plain JSON document the Rust core reads.""" + return as_str_mapping(_plain(value)) or {} + + +def _as_list(value: object) -> Sequence[object]: + return value if isinstance(value, list) else () # pyright: ignore[reportUnknownVariableType] # a list's items are read as objects + + +def _strategy_name(value: object) -> str | None: + """A strategy as a setting stores it: ``None`` stays no strategy (``_normalize_strategy``).""" + return None if value is None else normalize_strategy(value) or "simple-shuffle" + + +def _lenient_int(value: object, default: int) -> int: + """A count setting kept as given, as the crate reads it: an int, or a number spelled another way + (``1.5``, ``"3"``) truncated to one; ``default`` when it is no number. The Python core stores the + value as given and never checks it at construction.""" + if isinstance(value, bool | int): + return int(value) + try: + return int(float(str(value))) + except (ValueError, OverflowError): + return default + + +def _lenient_float(value: object, default: float | None) -> float | None: + """A seconds setting kept as given, as the crate reads it (see ``_lenient_int``).""" + if isinstance(value, bool | int | float): + return float(value) + try: + return float(str(value)) + except (ValueError, OverflowError): + return default + + +# Settings the Python core stores as given, so that a read returns the value passed (``"1"``, +# ``None``, ``[1]``); ``Resolved`` keeps them in ``given`` and the typed fields hold what the crate reads. +_KEPT_AS_GIVEN: Final = frozenset( + { + "num_retries", + "max_fallbacks", + "allowed_fails", + "retry_after", + "timeout", + "disable_cooldowns", + "enable_tag_filtering", + "tag_filtering_match_any", + "tag_routing_prefix", + "routing_strategy_args", + "fallbacks", + "context_window_fallbacks", + "content_policy_fallbacks", + } +) + + +@dataclasses.dataclass(frozen=True, slots=True) +class Resolved: + """The router's settings, resolved from its arguments and the process settings the way the + Python router's constructor resolves them. Replaced, never changed, by ``apply``.""" + + routing_strategy: str | None + routing_strategy_args: Mapping[str, object] + num_retries: int + max_fallbacks: int + allowed_fails: int + explicit_allowed_fails: int | None + cooldown_time: float + disable_cooldowns: bool | None + allowed_fails_policy: object + retry_after: float + timeout: float | None + fallbacks: list[object] | None # mutable-ok: the setting as Python spells it + context_window_fallbacks: list[object] | None # mutable-ok: same + content_policy_fallbacks: list[object] | None # mutable-ok: same + model_group_alias: Mapping[str, object] + default_litellm_params: Mapping[str, object] + fallback_access_check: object + fallback_budget_check: object + enable_mid_stream_fallback_continuation: bool = False + routing_groups: "tuple[RoutingGroup, ...]" = () + enable_tag_filtering: bool = False + tag_filtering_match_any: bool = True + tag_routing_prefix: str = "" + enable_pre_call_checks: bool = False + routing_plugins: "tuple[RoutingPlugin, ...]" = () + retry_policy: object = None + model_group_retry_policy: object = None + health_routing: HealthRouting = dataclasses.field(default_factory=HealthRouting) + # `_core_default_deployment`, as assigned (detached). + default_deployment: object = None + # `_model_to_group` as the Python core last built it, kept once a raw `routing_groups` write + # replaced the groups without rebuilding it. + routing_group_members: Mapping[str, str] | None = None + # `_routing_groups_input`: the groups last passed to the constructor or `update_settings`, which + # a strategy change through `update_settings` re-inits the routing groups from. + routing_groups_input: object = None + assigned: frozenset[str] = frozenset() + # The `_KEPT_AS_GIVEN` settings as the Python core stores them, for reads. + given: Mapping[str, object] = dataclasses.field(default_factory=lambda: MappingProxyType({})) + + def read(self, name: str) -> object: + """A setting as the Python core reads it back: as given when it keeps it so.""" + return self.given[name] if name in self.given else getattr(self, name) # pyright: ignore[reportAny] # a setting field + + @classmethod + def of(cls, config: RouterConfig, dynamic: RouterDynamicConfig) -> "Resolved": + get: Final = config.get + # The process list is the router's own, as in the Python router: default_fallbacks are + # appended to it in place. + configured: Final[list[object] | None] = ( # mutable-ok: the router's live list, as Python keeps it + list(_as_list(get("fallbacks"))) or (dynamic.fallbacks if dynamic.fallbacks else None) # pyright: ignore[reportAssignmentType] # the process list as given + ) + refuse_malformed_fallbacks(configured) + default_fallbacks: Final = get("default_fallbacks") or dynamic.default_fallbacks + if isinstance(default_fallbacks, str): + raise TypeError( + f"default_fallbacks must be a list of model names, got '{default_fallbacks}'. Use ['{default_fallbacks}']" + ) + if default_fallbacks is not None and configured is not None: + configured.append({"*": default_fallbacks}) + fallbacks: Final[list[object] | None] = ( # mutable-ok: see above + [{"*": default_fallbacks}] if default_fallbacks is not None and configured is None else configured + ) + content_policy: Final = list(_as_list(get("content_policy_fallbacks"))) or ( + list(dynamic.content_policy_fallbacks) if dynamic.content_policy_fallbacks else None + ) + refuse_malformed_fallbacks(content_policy) + num_retries: Final = get("num_retries") + max_fallbacks: Final = get("max_fallbacks") + allowed_fails: Final = get("allowed_fails") + timeout: Final = get("timeout") + strategy: Final = get("routing_strategy") + validate_routing_strategy(strategy) # pyright: ignore[reportArgumentType] # validated as given + # The values the Python core's constructor stores (`self.num_retries = num_retries`, ...). + given_num_retries: Final[object] = ( + num_retries if num_retries is not None else dynamic.num_retries if dynamic.num_retries is not None else 2 + ) + given_max_fallbacks: Final[object] = ( + max_fallbacks + if max_fallbacks is not None + else dynamic.max_fallbacks + if dynamic.max_fallbacks is not None + else dynamic.router_max_fallbacks + ) + given_allowed_fails: Final[object] = allowed_fails if allowed_fails is not None else dynamic.allowed_fails + given_timeout: Final[object] = timeout or dynamic.request_timeout + given_retry_after: Final[object] = get("retry_after") if "retry_after" in config.arguments else 0 + kept: Final = { + "num_retries": given_num_retries, + "max_fallbacks": given_max_fallbacks, + "allowed_fails": given_allowed_fails, + "timeout": given_timeout, + "retry_after": given_retry_after, + "disable_cooldowns": get("disable_cooldowns"), + **{ + name: get(name) + for name in ("enable_tag_filtering", "tag_filtering_match_any", "tag_routing_prefix") + if name in config.arguments + }, + **( + {"routing_strategy_args": get("routing_strategy_args")} + if "routing_strategy_args" in config.arguments + else {} + ), + } + return cls( + # An explicit `routing_strategy=None` is stored as None (no strategy picks). + routing_strategy=None + if strategy is None and "routing_strategy" in config.arguments + else normalize_strategy(strategy) or "simple-shuffle", + # A plain dict, as `self.routing_strategy_args`: `/router/settings` serializes it as read. + routing_strategy_args=dict(as_str_mapping(get("routing_strategy_args")) or {}), + num_retries=_lenient_int(given_num_retries, 2), + max_fallbacks=_lenient_int(given_max_fallbacks, dynamic.router_max_fallbacks), + allowed_fails=_lenient_int(given_allowed_fails, dynamic.allowed_fails), + explicit_allowed_fails=_lenient_int(allowed_fails, dynamic.allowed_fails) + if allowed_fails is not None + else None, + cooldown_time=_lenient_float(get("cooldown_time") or _DEFAULT_COOLDOWN_SECONDS, _DEFAULT_COOLDOWN_SECONDS) + or 0.0, + disable_cooldowns=_optional_bool(get("disable_cooldowns")), + allowed_fails_policy=resolved_allowed_fails_policy(get("allowed_fails_policy")), + retry_after=_lenient_float(given_retry_after or 0, 0.0) or 0.0, + timeout=_lenient_float(given_timeout, None) if given_timeout else None, + given=MappingProxyType(kept), + fallbacks=fallbacks, + context_window_fallbacks=list(_as_list(get("context_window_fallbacks"))) + or (list(dynamic.context_window_fallbacks) if dynamic.context_window_fallbacks else None), + content_policy_fallbacks=content_policy, + model_group_alias=MappingProxyType(dict(as_str_mapping(get("model_group_alias")) or {})), + default_litellm_params=MappingProxyType(dict(as_str_mapping(get("default_litellm_params")) or {})), + fallback_access_check=get("fallback_access_check"), + fallback_budget_check=get("fallback_budget_check"), + enable_mid_stream_fallback_continuation=continuation_flag(get("enable_mid_stream_fallback_continuation")), + enable_tag_filtering=bool(get("enable_tag_filtering")), + tag_filtering_match_any=_true_unless_given(get("tag_filtering_match_any")), + tag_routing_prefix=str(get("tag_routing_prefix") or ""), + enable_pre_call_checks=bool(get("enable_pre_call_checks")), + routing_plugins=tuple(_as_list(get("plugins"))), # pyright: ignore[reportArgumentType] # the plugins as passed + routing_groups_input=get("routing_groups"), + routing_groups=parse_groups( + get("routing_groups"), + frozenset( + str(name) + for entry in _as_list(get("model_list")) + if (name := (as_str_mapping(entry) or {}).get("model_name")) + ), + frozenset(as_str_mapping(get("model_group_alias")) or {}), + ), + retry_policy=resolved_retry_policy(get("retry_policy")), + model_group_retry_policy=get("model_group_retry_policy"), + health_routing=HealthRouting.of(config), + ) + + def changed(self, values: Mapping[str, object], updated: frozenset[str] = frozenset()) -> "Resolved": + """``values`` applied; ``updated`` names those passed as ``ChangeSet.settings`` (which go + through ``update_settings``: only they may name ``routing_strategy_args``).""" + from litellm.router_api import ASSIGNABLE_ALIASES, PLAIN_SETTING_ATTRIBUTES, SETTING_FIELDS + + unknown: Final = sorted( + set(values) + - {*SETTING_FIELDS, *PLAIN_SETTING_ATTRIBUTES, *ASSIGNABLE_ALIASES} + - (updated & {"routing_strategy_args", "routing_groups", "enable_tag_filtering", "tag_routing_prefix"}) + ) + if unknown: + raise ValueError(f"not assignable router settings: {unknown}") + unserved: Final = sorted(set(values) - _STATIC_SETTINGS - _DYNAMIC_SETTINGS) + if unserved: + raise RustCoreUnsupported(f"the Rust router core does not serve the setting(s) {', '.join(unserved)} yet") + updates: Final[dict[str, object]] = {} # mutable-ok: built here, then applied once + for name, value in values.items(): + if name in {"model_group_alias", "default_litellm_params"}: + updates[name] = MappingProxyType(dict(as_str_mapping(value) or {})) + elif name in _NUMBER_SETTINGS: + updates[name] = self._number_setting(name, value) + if name == "allowed_fails": + updates["explicit_allowed_fails"] = updates[name] + elif name in _SELECTION_SETTINGS: + updates[name] = self._selection_setting(name, value) + elif name == "disable_cooldowns": + updates[name] = _optional_bool(value) + elif name == "enable_pre_call_checks": + updates[name] = bool(value) + elif name in ("fallbacks", "context_window_fallbacks", "content_policy_fallbacks"): + updates[name] = list(_as_list(value)) or None + elif name == "default_deployment": + updates[name] = detached(value) + else: + updates[name] = value + if "routing_groups" in values: + # `_init_routing_groups` rebuilds the member map from the new groups. + updates["routing_group_members"] = None + # `_core_update_settings` casts its int settings (`int(value)`, which raises as Python's + # does); every other write is stored as given. + kept: Final = { + name: int(value) if name in updated and name in _UPDATE_INT_SETTINGS else value # pyright: ignore[reportArgumentType] # int() of the value as given, as Python casts it + for name, value in values.items() + if name in _KEPT_AS_GIVEN + } + return dataclasses.replace( + self, + **updates, + assigned=self.assigned | frozenset(values), + given=MappingProxyType({**self.given, **kept}), + ) # pyright: ignore[reportArgumentType] # each value converted to its field's type above + + def _number_setting(self, name: str, value: object) -> object: + """A numeric setting as the crate reads it; the value as given is kept in ``given``.""" + if name in ("num_retries", "max_fallbacks", "allowed_fails"): + return _lenient_int(value, getattr(self, name)) # pyright: ignore[reportAny] # the field's current int + if name == "cooldown_time": + # Stored as given (`_core_cooldown_time`), so a failure cools down for that long: + # 0 for no time at all; None leaves the cooldown cache's own default, set by the caller. + return _lenient_float(value, self.cooldown_time) if value is not None else self.cooldown_time + if name == "retry_after": + return _lenient_float(value or 0, self.retry_after) + return _lenient_float(value, self.timeout) if value is not None else None + + def _selection_setting(self, name: str, value: object) -> object: + """A selection setting converted to its field's type.""" + if name == "routing_strategy": + return _strategy_name(value) + if name == "routing_strategy_args": + return dict(as_str_mapping(value) or {}) + if name == "tag_routing_prefix": + return str(value or "") + return bool(value) + + def static_document(self, model_list: Sequence[object]) -> Mapping[str, object]: + values: Final = { + "model_list": _plain(list(model_list)), + "routing_strategy": self.routing_strategy, + "cooldown_time": self.cooldown_time, + "disable_cooldowns": self.disable_cooldowns, + "allowed_fails_policy": _plain(self.allowed_fails_policy), + "retry_after": self.retry_after, + "timeout": self.timeout, + "routing_groups": group_documents(self.routing_groups) if self.routing_groups else None, + "enable_pre_call_checks": True if self.enable_pre_call_checks else None, + "routing_plugins": True if self.routing_plugins else None, + # `async_callback_filter_deployments` runs on every async candidate list. + "callback_filters": True, + "retry_policy": _plain(self.retry_policy), + "model_group_retry_policy": _plain(static_group_policies(self.model_group_retry_policy)) or None, + "routing_group_members": dict(self.routing_group_members) + if self.routing_group_members is not None + else None, + **self.health_routing.static_document(), + } + kept: Final = {name: value for name, value in values.items() if value is not None} + # An explicit `routing_strategy=None` reaches the Rust core as "None": no strategy picks. + return kept if self.routing_strategy is not None else {**kept, "routing_strategy": "None"} + + def dynamic_document(self, version: int, model_names: Sequence[str]) -> Mapping[str, object]: + values: Final = { + "version": version, + "model_group_alias": _plain(dict(self.model_group_alias)), + "fallbacks": _plain(self.fallbacks), + "context_window_fallbacks": _plain(self.context_window_fallbacks), + "content_policy_fallbacks": _plain(self.content_policy_fallbacks), + "num_retries": self.num_retries, + "max_fallbacks": self.max_fallbacks, + "allowed_fails": self.allowed_fails, + "allowed_fails_is_default": True if self.allowed_fails_is_default() else None, + "fallback_keys": self._fallback_keys(model_names), + "default_deployment": _plain(served_default_deployment(self.default_deployment)[0]), + "default_deployment_raises": True if served_default_deployment(self.default_deployment)[1] else None, + } + return {name: value for name, value in values.items() if value is not None} + + def allowed_fails_is_default(self) -> bool: + """``allowed_fails`` does not count as set on the router (``_is_allowed_fails_set_on_router``): + not passed explicitly, and the value copied at init still equals the live process default.""" + import litellm + + return self.explicit_allowed_fails is None and self.allowed_fails == litellm.allowed_fails + + def _fallback_keys(self, model_names: Sequence[str]) -> Mapping[str, object]: + """The spellings a fallback key matches besides the group name (`get_fallback_model_group`).""" + from litellm.router_utils.fallback_event_handlers import ( + _provider_prefixed_model_group, # pyright: ignore[reportPrivateUsage] # the fallback walk's own spelling rule + ) + + keys: Final = tuple( # comprehension-ok: the first group of each fallback entry, across the three lists + str(next(iter(mapping))) + for entries in (self.fallbacks, self.context_window_fallbacks, self.content_policy_fallbacks) + for entry in _as_list(entries) + if (mapping := as_str_mapping(entry)) + ) + names: Final = {*model_names, *self.model_group_alias} + prefixed: Final = { + name: spelled for name in names if (spelled := _provider_prefixed_model_group(name, keys)) is not None + } + from litellm.types.router import LiteLLMParamsTypedDict + + return { + "providers": _PROVIDERS, + "provider_prefixed": prefixed, + "param_keys": list(LiteLLMParamsTypedDict.__annotations__), + } + + +def _alias_target(target: object) -> str | None: + mapping: Final = as_str_mapping(target) + if mapping is not None: + model: Final = mapping.get("model") + return model if isinstance(model, str) else None + return target if isinstance(target, str) else None + + +def _true_unless_given(value: object) -> bool: + return True if value is None else bool(value) + + +def _group_selectors(groups: "Sequence[RoutingGroup]") -> Sequence[tuple[str, str, Mapping[str, object]]]: + return [ + ( + group.group_name, + group.routing_strategy, + as_str_mapping(group.routing_strategy_args) or {}, # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # RoutingGroup's untyped dict + ) + for group in groups + ] + + +def _optional_bool(value: object) -> bool | None: + return None if value is None else bool(value) + + +def unsupported_arguments(config: RouterConfig) -> frozenset[str]: + """Arguments the Rust core does not serve.""" + unserved: Final = frozenset( + name + for name, value in config.arguments.items() + if name not in _SERVED_ARGUMENTS and value not in (None, _UNSET_DEFAULTS.get(name)) + ) + return unserved + + +def _listing_team_id(request: Mapping[str, object]) -> str | None: + """``(kwargs.get("metadata", {}) or {}).get("user_api_key_team_id")``: the team + ``async_function_with_fallbacks_common_utils`` lists a group for reads this bucket alone.""" + metadata: Final = as_str_mapping(request.get("metadata")) + team_id: Final = metadata.get("user_api_key_team_id") if metadata is not None else None + return team_id if isinstance(team_id, str) else None + + +# Request fallback settings, which replace the router's for the call. +_REQUEST_FALLBACK_KEYS: Final = ("fallbacks", "context_window_fallbacks", "content_policy_fallbacks", "max_fallbacks") + + +def _strings(value: object) -> "tuple[str, ...]": + """Every string in ``value``, a name or a fallback list of names and dict entries.""" + if isinstance(value, str): + return (value,) + if isinstance(value, Mapping): + entries: Final[Mapping[object, object]] = value # pyright: ignore[reportUnknownVariableType] # read as objects + return tuple(itertools.chain.from_iterable(map(_strings, itertools.chain.from_iterable(entries.items())))) + if isinstance(value, list | tuple): + items: Final[Sequence[object]] = value # pyright: ignore[reportUnknownVariableType] # see above + return tuple(itertools.chain.from_iterable(map(_strings, items))) # pyright: ignore[reportUnknownArgumentType] # read as objects + return () + + +def _routed_model(request: Mapping[str, object]) -> object: + """The request's ``model`` as a recovery of its stream names it (``RustCore.routed_name``).""" + model: Final = request.get("model") + return model if model is None or isinstance(model, str) else str(model) + + +def _start_fields(request: Mapping[str, object]) -> Mapping[str, object]: + """The request fields the Rust core routes on.""" + fields: Final = { + **request_retry_fields(request.get("num_retries")), + **({"cooldown_time": request["cooldown_time"]} if request.get("cooldown_time") is not None else {}), + } + # `_common_checks_available_deployment`: only True names a litellm model. + specific: Final = {"specific_deployment": True} if request.get("specific_deployment") is True else {} + # `record_disable_fallbacks(kwargs, disable_fallbacks is True)`: only True turns them off. + disabled: Final = {"disable_fallbacks": True} if request.get("disable_fallbacks") is True else {} + lists: Final = {key: _plain(request[key]) for key in _REQUEST_FALLBACK_KEYS if key in request} + weights: Final = request.get("_router_weights") + team_id: Final = get_request_team_id(request) + listing_team_id: Final = _listing_team_id(request) + strategy: Final = request.get("routing_strategy") + override: Final = normalize_strategy(strategy) if isinstance(strategy, str | RoutingStrategy) else None + return { + **fields, + **specific, + **({"routing_strategy": override} if override is not None else {}), + **disabled, + **({"router_weights": weights} if weights is not None else {}), + **lists, + **({"team_id": team_id} if team_id else {}), + **({"listing_team_id": listing_team_id} if listing_team_id is not None else {}), + **caller_fields(request), + } + + +# --- views -------------------------------------------------------------------------------------- + + +class RustSettings(RouterSettings): + """``settings()``: the resolved settings as a frozen snapshot.""" + + def guardrail(self, name: str) -> "GuardrailTypedDict": + router: Final = self._router + if not isinstance(router, _SettingsSource): + return super().guardrail(name) + return router.available_guardrail(name) # pyright: ignore[reportReturnType] # the configured guardrail entry + + def as_dict(self) -> Mapping[str, object]: + router: Final = self._router + if not isinstance(router, _SettingsSource): + return super().as_dict() + return router.settings_dict() + + +class _SettingsSource: + def settings_dict(self) -> Mapping[str, object]: + raise NotImplementedError + + def available_guardrail(self, name: str) -> object: + raise NotImplementedError + + +class RustHealth(RouterHealth): + """``health()``: cooldowns, fail counts and usage, read through the host's routing cache and + written through the Rust core.""" + + __slots__ = ("_core",) + + def __init__(self, core: "RustCore") -> None: # pyright: ignore[reportMissingSuperCall] # reads the Rust core, not a Router + self._core = core + + def __getattribute__(self, name: str) -> object: + if name in _HEALTH_SERVED or name.startswith("__") or name == "_core": + found: Final[object] = object.__getattribute__(self, name) # pyright: ignore[reportAny] # the view's own member + return found + raise RustCoreUnsupported(f"health().{name} is not served by the Rust router core", name=name, obj=self) + + @property + def store(self) -> "DualCache": + return self._core._cache # pyright: ignore[reportPrivateUsage] # the health view reads its own core + + @property + def cooldowns(self) -> "CooldownCache": + return self._core._cooldowns # pyright: ignore[reportPrivateUsage] # see above + + def failures_this_minute(self, deployment_id: str) -> int: + count: Final[object] = self.store.get_cache(f"{deployment_id}:fails", local_only=True) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # DualCache's reads are untyped + return int(count) if isinstance(count, int | float) else 0 + + def record_failure(self, deployment_id: str, exception: Exception, exception_status: str | int) -> bool: + self._core._sync_allowed_fails() # pyright: ignore[reportPrivateUsage] # see above + failure: Final = { + **attempt_failure(exception), + "status": failure_status(exception_status), + "caller_scoped": self._core.per_user_deployment(deployment_id), + } + handle: Final = self._core._handle # pyright: ignore[reportPrivateUsage] # see above + call: Final = handle.report_failure(deployment_id, failure, count_only=exception_status == "") + done: Final = self._core._drive_sync_steps(call) # pyright: ignore[reportPrivateUsage] # see above + return self._core.cooled_down(done, deployment_id, exception_status) + + def team_ptu_ceiling(self, team_id: str, model_group: str) -> "PTUTeamCeiling | None": + return self._core._hosted._core_team_ptu_ceiling(team_id, model_group) # pyright: ignore[reportPrivateUsage] # the host registry's ported ceiling + + def split_priority(self, model: str, kwargs: Mapping[str, object]) -> tuple[int | None, Mapping[str, object]]: + """``_core_split_request_priority``, as the endpoints resolve a request's priority.""" + return self._core._endpoints._split_priority(model, kwargs) # pyright: ignore[reportPrivateUsage] # see store + + def priority_header_fields( + self, model: str, kwargs: Mapping[str, object], header: str | None + ) -> Mapping[str, int | str]: + """``priority_header_update``, as the endpoints read a priority header.""" + return self._core._endpoints.priority_header_update(model=model, kwargs=kwargs, header=header) # pyright: ignore[reportPrivateUsage] # see store + + @property + def health_checks(self) -> "DeploymentHealthCache": + return self._core._health_checks # pyright: ignore[reportPrivateUsage] # see store + + @property + def latency(self) -> "UntypedDict": # the live latency map, as the Python core keeps it + return self._core._hosted._core_deployment_latency_map # pyright: ignore[reportPrivateUsage] # see team_ptu_ceiling + + @staticmethod + def is_blocked(deployment: "Deployment") -> bool: + return deployment_is_blocked(deployment) + + @staticmethod + def all_blocked(deployments: "Sequence[DeploymentTypedDict]") -> bool: + return deployments_all_blocked(deployments) + + def fully_blocked_model_names(self) -> set[str]: # mutable-ok: the core's type, a fresh set + return blocked_model_names(self._core._hosted._core_get_model_list() or []) # pyright: ignore[reportPrivateUsage, reportArgumentType] # see team_ptu_ceiling + + async def fully_unhealthy_model_names(self) -> set[str]: # mutable-ok: the core's type, a fresh set + core: Final = self._core + return await fully_unhealthy_model_names( + core._hosted._core_get_model_list() or [], # pyright: ignore[reportPrivateUsage, reportArgumentType] # see team_ptu_ceiling + core._health_checks, # pyright: ignore[reportPrivateUsage] # see store + core._resolved.allowed_fails_policy, # pyright: ignore[reportPrivateUsage] # see store + ) + + async def usage( # pyright: ignore[reportIncompatibleMethodOverride] # the same two kinds + self, model_group: str, *, kind: Literal["current", "remaining"] = "current" + ) -> tuple[int | None, int | None] | Mapping[str, int]: + """The group's usage this minute, read from the routing cache over the host registry's + live model list, as ``get_model_group_usage`` / ``get_remaining_model_group_usage`` read it.""" + hosted: Final = self._core._hosted # pyright: ignore[reportPrivateUsage] # see above + if kind == "current": + return await hosted._core_get_model_group_usage(model_group) # pyright: ignore[reportPrivateUsage] # the ported usage read + if kind == "remaining": + return await hosted._core_get_remaining_model_group_usage(model_group) # pyright: ignore[reportPrivateUsage] # see above + raise ValueError(f"unknown usage kind {kind!r}") + + +# Deprecated attribute writes (``router. = ...`` reaches the core as ``_core_``) of +# registry state this core keeps on its host registry, and of routing state it rebinds. +_HOSTED_STATE: Final = frozenset( + { + "_core_model_names", + "_core_deployment_names", + "_core_team_public_model_names", + "_core_model_name_to_deployment_indices", + "_core_team_model_to_deployment_indices", + "_core_cached_deployment_model_info", + "_core_pattern_router", + "_core_team_pattern_routers", + "_core_routing_groups", + "_core_auto_routers", + "_core_complexity_routers", + "_core_quality_routers", + "_core_adaptive_routers", + "_core_routing_plugins", + "_core_deployment_latency_map", + } +) +_REBOUND_STATE: Final = MappingProxyType( + { + "_core_cache": "_cache", + "_core_cooldown_cache": "_cooldowns", + "_core_health_state_cache": "_health_checks", + "_core_slack_alerting_logger": "_slack_alerting_logger", + } +) + + +_HEALTH_SERVED: Final = frozenset( + { + "store", + "cooldowns", + "failures_this_minute", + "record_failure", + "usage", + "team_ptu_ceiling", + "split_priority", + "priority_header_fields", + "health_checks", + "latency", + "is_blocked", + "all_blocked", + "fully_blocked_model_names", + "fully_unhealthy_model_names", + } +) + + +# --- the core ----------------------------------------------------------------------------------- + + +_NO_INPUT: Final = object() +_EndpointImpl: TypeAlias = Callable[..., Awaitable[object]] +# A strategy select step's strategy, selector, keyed name and candidate deployments. +_StrategyInputs: TypeAlias = tuple[str, object, str, list[dict[str, object]]] + + +@final +class _PickCounts(Protocol): + """The router cache as ``track_deployment_pick`` uses it: each deployment id holds its pick count.""" + + def get_cache( + self, key: object, parent_otel_span: "Span | None" = None, local_only: bool = False + ) -> int | None: ... + + def set_cache(self, key: object, value: int, local_only: bool = False, *, ttl: int = ...) -> None: ... + + +class _EndpointPort: + """``RustCore`` as its endpoints see it (``EndpointCore``): each member forwards to the core's + own state or call drivers, read live, since the core replaces its handle and settings. The + port is the core's own adapter, so it is the one place its private members are read from + outside the class; every ``reportPrivateUsage`` ignore below is for that reason.""" + + __slots__ = ("_core",) + + def __init__(self, core: "RustCore") -> None: + self._core: Final = core + + @property + def router(self) -> "RustCore": + return self._core + + @property + def host(self) -> PythonHost: + return self._core._host # pyright: ignore[reportPrivateUsage] # see the class docstring + + @property + def handle(self) -> "RouterCoreHandle": + return self._core._handle # pyright: ignore[reportPrivateUsage] # see the class docstring + + @property + def resolved(self) -> "Resolved": + return self._core._resolved # pyright: ignore[reportPrivateUsage] # see the class docstring + + @property + def shaping(self) -> Shaping: + return self._core._shaping # pyright: ignore[reportPrivateUsage] # see the class docstring + + @property + def routing_cache(self) -> "DualCache": + return self._core._cache # pyright: ignore[reportPrivateUsage] # see the class docstring + + @property + def selectors(self) -> StrategySelectors: + return self._core._selectors # pyright: ignore[reportPrivateUsage] # see the class docstring + + @property + def endpoints(self) -> RustEndpoints: + return self._core._endpoints # pyright: ignore[reportPrivateUsage] # see the class docstring + + async def drive( + self, + plan: Plan, + request: Mapping[str, object], + overrides: Mapping[str, object] | None = None, + *, + passthrough: Callable[[Mapping[str, object], str], Awaitable[object]] | None = None, + prepared_already: bool = False, + ) -> object: + return await self._core._drive( # pyright: ignore[reportPrivateUsage] # see the class docstring + plan, request, overrides, passthrough=passthrough, prepared_already=prepared_already + ) + + def call_sync( + self, plan: Plan, request: Mapping[str, object], overrides: Mapping[str, object] | None = None + ) -> object: + return self._core._call_sync(plan, request, overrides) # pyright: ignore[reportPrivateUsage] # see the class docstring + + def routing_callbacks(self) -> Iterable[object]: + return self._core._checks.routing_callbacks() # pyright: ignore[reportPrivateUsage] # see the class docstring + + def resolve_alias(self, model: str) -> str | None: + return self._core._hosted._core_get_model_from_alias(model) # pyright: ignore[reportPrivateUsage] # see the class docstring + + def group_deployments(self, model_name: str) -> Sequence[Mapping[str, object]] | None: + return self._core._hosted._core_get_model_list(model_name=model_name) # pyright: ignore[reportPrivateUsage] # see the class docstring + + def routed_name(self, model: object) -> str: + return self._core.routed_name(model) + + def service_logged(self, call_type: str, start_time: float, end_time: float, request: Mapping[str, object]) -> None: + self._core.service_logged(call_type, start_time, end_time, request) + + async def set_response_headers( + self, response: object, model_group: str | None, request_kwargs: Mapping[str, object] + ) -> object: + return await self._core.set_response_headers(response, model_group, request_kwargs) + + def configured_deployment(self, model_id: str) -> "Deployment | None": + return self._core._hosted._core_get_deployment(model_id) # pyright: ignore[reportPrivateUsage] # see the class docstring + + def registry(self) -> RouterRegistry: + return self._core.registry() + + async def select( + self, + model: str, + request_kwargs: dict[str, object] | None = None, # mutable-ok: the RouterCore signature + *, + kind: str = "pick", + specific_deployment: bool | None = None, + messages: object = None, + ) -> Mapping[str, object] | Sequence[Mapping[str, object]]: + return await self._core.select( + model, request_kwargs, kind=kind, specific_deployment=specific_deployment, messages=messages + ) + + async def acompletion(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return await self._core.acompletion(*args, **kwargs) + + +class RustCore( + _SettingsSource, + RustLegacyMembers, + RustRegistryMembers, + RustRetries, + RustFallbacks, + RustHealthCallbacks, + RustOptionalChecks, +): + """A ``RouterCore`` served by the Rust router core over a ``PythonHost``. It holds no Python core.""" + + def __init__(self, config: RouterConfig, host: PythonHost, resolved: Resolved) -> None: + from litellm._service_logger import ServiceLogging + from litellm.router_utils.cooldown_cache import CooldownCache + + self._config: Final = config + self._host: Final = host + self.service_logger_obj: ServiceLogging = ServiceLogging() + apply_construction_effects(config, host) + self._resolved: Resolved = resolved + # `cooldown_time` as the Python core stores it (`cooldown_time or DEFAULT_COOLDOWN_TIME_SECONDS`, + # then each value assigned or updated, as given): what `settings()` reads back. + self._cooldown_given: object = config.get("cooldown_time") or DEFAULT_COOLDOWN_TIME_SECONDS + # Settings the Python core keeps as plain attributes, and settings deleted with `del`. + self._plain: Final = initial_plain(config) + self._deleted: frozenset[str] = frozenset() + self._request_timeout: Final = request_timeout(config) + legacy: Final[dict[str, object]] = {"deployment_stats": {}} # mutable-ok: the core's own legacy attributes + self._legacy: Final = legacy + self._health_view: RustHealth | None = None + self._cache: DualCache = host.routing_cache(config) + self._cooldowns: CooldownCache = CooldownCache( + cache=self._cache, + default_cooldown_time=self._cooldown_given, # pyright: ignore[reportArgumentType] # the constructor's value, as the Python core passes it + ) + self._health_checks: DeploymentHealthCache = resolved.health_routing.health_checks(self._cache) + self._version: int = 1 + self._settings: RustSettings | None = None + self._tag_filtering_models: tuple[int, bool] | None = None + # The registry indexes written through the deprecated attributes (`_core_`), and the + # document router-core last received for them. + self._index_written: frozenset[str] = frozenset() + self._index_sent: Mapping[str, object] | None = None + self._selectors: Final = StrategySelectors(host, self._cache) + self._selectors.init_default(resolved.routing_strategy, resolved.routing_strategy_args) + self._selectors.init_groups(_group_selectors(resolved.routing_groups)) + self._port: Final = _EndpointPort(self) + self._endpoints: Final = RustEndpoints(self._port, config) + # The resolver every picked deployment with `kubernetes_pod_discovery` goes through. + self._pod_discovery: KubernetesPodDiscovery = KubernetesPodDiscovery() + general: Final = config.get("router_general_settings", _DEFAULT_GENERAL_SETTINGS) + self._general_settings: object = general or RouterGeneralSettings() + self._registry_view: RouterRegistry | None = None + self._hosted: Final = HostRegistry( + host, + model_group_alias=dict(resolved.model_group_alias), # pyright: ignore[reportArgumentType] # the configured alias map + ignore_invalid_deployments=bool(config.get("ignore_invalid_deployments")), + on_change=self._sync_registry, + ) + self._hosted._core_cache = self._cache # pyright: ignore[reportPrivateUsage] # usage reads come from the cache the Rust core writes + ctx: Final = RoutingContext(self) # pyright: ignore[reportArgumentType] # the strategies read registry(), settings(), health() and select() + strategies: Final = PreRoutingStrategies( + self._hosted, host, ctx, config.get("auto_router_capability_limit"), self._cache + ) + self._hosted.strategies = strategies + self._prerouter: Final = PreRouter(strategies, self._hosted, host, ctx, self._cache) + # `register_plugin`: a custom strategy that replaces every pick (the host answers the + # Rust core's pre_route step with its deployment). + self._custom_strategy: CustomRoutingStrategyBase | None = None + self._custom_discovery: KubernetesPodDiscovery | None = None + # router-core builds the deployments, asking the host registry about each one: the handle + # starts empty, and is rebuilt over the built list for the settings the list's names feed. + self._handle_default_ids: tuple[str, ...] = () # the provider default ids the handle was built with + self._allowed_fails_default_sent: bool = False # what the handle's dynamic document last said + self._walked_fallbacks: Mapping[str, object] = {} # the fallback lists that document held + self._handle: RouterCoreHandle = self._new_handle([]) + self._hosted.build_runner = self._run_build + self._hosted.missing_attribute = self._no_router_attribute + self._hosted.changes_runner = self._apply_registry_changes + self._hosted.handle_lookup = self._live_handle + self._hosted.build(_as_list(config.get("model_list")) if config.get("model_list") is not None else None) + self._hosted.set_routing_groups(resolved.routing_groups) + track_live_registry(self._hosted) + self._hosted.routable_lookup = self._routable + self._hosted.max_parallel_requests_lookup = self._max_parallel_requests_client + self._hosted._core_routing_plugins = list(resolved.routing_plugins) # pyright: ignore[reportPrivateUsage] # the core fills its own host registry + self._rebuild() + self._join_callback_holders() + self._checks: Final = OptionalChecks(self, host, self._cache, self._hosted, ctx, config.arguments) + self._hosted.checks = self._checks + strategies.ensure_affinity = self._checks.ensure_deployment_affinity_callback + self._checks.build(config.get("optional_pre_call_checks"), config.get("model_list")) + self._slack_alerting_logger: SlackAlerting | None = initialize_alerting(host, config.get("alerting_config")) # pyright: ignore[reportArgumentType] # the argument as passed + if self._slack_alerting_logger is not None: + self._checks.slack_alerting_loggers = (self._slack_alerting_logger,) + if resolved.enable_mid_stream_fallback_continuation: + register_continuation_prefill_check(host) + if resolved.routing_strategy == "lar1": + from litellm.router_strategy.lar1_routing import apply_lar1_routing_strategy + + apply_lar1_routing_strategy(ctx, resolved.routing_strategy_args) # pyright: ignore[reportArgumentType] # the core's RoutingContext + + @property + def _registry_state(self) -> HostRegistry: + return self._hosted + + @property + def _python_host(self) -> PythonHost: + return self._host + + @property + def _written_retry_policy(self) -> object: + return self._plain["retry_policy"] + + @classmethod + def build(cls, config: RouterConfig, host: PythonHost) -> "RustCore": + from litellm.rust_bridge._native import RustBridgeDeclined + + extra: Final = unsupported_arguments(config) + if extra: + raise RustBridgeDeclined(f"router arguments not served by the Rust core: {sorted(extra)}") + RustEndpoints.prepare_host(config, host) + return cls(config, host, Resolved.of(config, host.dynamic())) + + @property + def enable_mid_stream_fallback_continuation(self) -> bool: + return self._resolved.enable_mid_stream_fallback_continuation + + def _set_continuation(self, enabled: bool) -> None: + """``_set_mid_stream_fallback_continuation``: an enabled flag registers the process-wide prefill check.""" + self._resolved = dataclasses.replace(self._resolved, enable_mid_stream_fallback_continuation=enabled) + self._settings = None + if enabled: + register_continuation_prefill_check(self._host) + + def __getattr__(self, name: str) -> object: + if name in self.__dict__.get("_deleted", ()): + raise self._no_attribute(name) + if name in SELECTOR_ATTRIBUTES.values(): + return self._selectors.attribute(name) + if name == "_core_async_get_available_deployment" and self.__dict__.get("_custom_strategy") is not None: + return self._custom_async_pick() + # Only reached for members this class does not define: the endpoints served through the + # host, else refused. Never forwarded anywhere. + endpoints: Final[object] = self.__dict__.get("_endpoints") + endpoint: Final = endpoints.member(name) if isinstance(endpoints, RustEndpoints) else None + if endpoint is not None: + return endpoint + attribute: Final = self._settings_attribute(name) if "_resolved" in self.__dict__ else MISSING + if attribute is not MISSING: + return attribute + raise RustCoreUnsupported(f"'{name}' is not served by the Rust router core", name=name, obj=self) + + @property + def _unset_attributes(self) -> frozenset[str]: + """The instance attributes ``del`` removed, which ``_settings_attribute`` no longer serves.""" + unset: Final[object] = self.__dict__.get("_unset_attributes") + return unset if isinstance(unset, frozenset) else frozenset() # pyright: ignore[reportUnknownVariableType] # only names are stored + + def _settings_attribute(self, name: str) -> object: + """A router attribute that reads a setting, the constructor's arguments or a constant.""" + if name in self._unset_attributes: + return MISSING + r: Final = self._resolved + resolved: Final[Mapping[str, object]] = { + "num_retries": r.read("num_retries"), + "max_fallbacks": r.read("max_fallbacks"), + "timeout": r.read("timeout"), + "retry_after": r.read("retry_after"), + "explicit_allowed_fails": r.given["allowed_fails"] + if r.explicit_allowed_fails is not None and "allowed_fails" in r.given + else r.explicit_allowed_fails, + "routing_strategy_args": r.read("routing_strategy_args"), + "request_timeout": self._request_timeout, + "default_priority": self._endpoints._default_priority, # pyright: ignore[reportPrivateUsage] # parsed by the endpoint plans + } + if name in resolved: + return resolved[name] + if name in self._plain: + return self._plain[name] + if name in self._legacy: + return self._legacy[name] + if name == "healthy_deployments": + return self._hosted._core_model_list # pyright: ignore[reportPrivateUsage] # the live list, as the core keeps it + if name == "get_model_group_io_token_usage": + return self._hosted.get_model_group_io_token_usage + if name == "scheduler": + return self._endpoints._get_scheduler() # pyright: ignore[reportPrivateUsage] # the endpoint plans' scheduler + if name == "chat": + from litellm.main import Chat + + self._legacy["chat"] = Chat(params=default_litellm_params(self._config), router_obj=self) # pyright: ignore[reportArgumentType] # Chat calls the router's endpoints, which this core serves + return self._legacy["chat"] + return argument_attribute(self._config, name) + + @property + def _shaping(self) -> Shaping: + return self._endpoints.shaping(self._resolved) + + # -- building -------------------------------------------------------------------------------- + + def _new_handle(self, model_list: Sequence[object]) -> "RouterCoreHandle": + from litellm.rust_bridge._native import RouterCoreHandle + + names: Final = [ + str(name) + for entry in model_list + if isinstance(name := (as_str_mapping(entry) or {}).get("model_name"), str) + ] + default_ids: Final = self._provider_default_ids() + self._handle_default_ids = default_ids + static: Final = { + **self._resolved.static_document(model_list), + **{name: value for name, value in failover_document(self._plain).items() if value is not None}, + **({"provider_default_deployment_ids": list(default_ids)} if default_ids else {}), + } + return RouterCoreHandle(static, self._dynamic_document(names)) + + def _dynamic_document(self, model_names: Sequence[str]) -> Mapping[str, object]: + self._allowed_fails_default_sent = self._resolved.allowed_fails_is_default() + # Settings are static: an in-place edit of a live list reaches neither the walk nor its notes. + resolved: Final = self._resolved + self._walked_fallbacks = { + "fallbacks": detached(resolved.fallbacks), + "context_window_fallbacks": detached(resolved.context_window_fallbacks), + "content_policy_fallbacks": detached(resolved.content_policy_fallbacks), + } + return resolved.dynamic_document(self._version, model_names) + + def _provider_default_ids(self) -> tuple[str, ...]: + """``provider_default_deployment_ids`` as the cooldown check reads it (``deployment in + settings().provider_default_deployment_ids``): the ids it holds now. router-core holds them + with its static settings.""" + handle: Final = self._live_handle() + return () if handle is None else tuple(handle.provider_default_ids()) + + def _pick_discovery(self, *, sync: bool) -> KubernetesPodDiscovery | None: + """The pod discovery a pick resolves through: the one bound when a custom strategy was + registered (``resolve_pods_after_bound``), else the router's own (``resolve_pods_after``); + none for an async pick assigned through the deprecated attribute, which Python calls bare.""" + if not sync and callable(self.__dict__.get("_core_async_get_available_deployment")): + return None + if self._custom_strategy is not None and self._custom_discovery is not None: + return self._custom_discovery + return self._pod_discovery + + # -- the plugin context (``RoutingContext``) ----------------------------------------------- + + def _core_arm_routing_read_prefetch(self, model: str, request_kwargs: Mapping[str, object] | None = None) -> None: + """``RoutingContext.arm_read_prefetch``: declare the cooldown reads (and, for + usage-based-routing-v2, the usage reads) the pick for ``model`` makes on the request's + Redis batch, so admission's flush carries them. A miss costs nothing.""" + from litellm.router_utils.routing_read_batch import RoutingPrefetch + + try: + usage_selector: Final = self._prefetch_usage_selector(model, request_kwargs) + deployments: Final = self._hosted._core_get_model_list(model_name=model) # pyright: ignore[reportPrivateUsage] # see __init__ + if deployments: + RoutingPrefetch.arm(RoutingContext(self), usage_selector, deployments) # pyright: ignore[reportArgumentType, reportUnknownMemberType] # the prefetch reads registry() and health(); its deployments list is untyped + except Exception as e: # noqa: BLE001 # a prefetch is an optimisation, never a reason to fail the request + from litellm._logging import verbose_router_logger + + verbose_router_logger.debug( + "routing read prefetch not armed for %s: %s", + str(model).replace("\r", "").replace("\n", ""), + str(e).replace("\r", "").replace("\n", ""), + ) + + def _prefetch_usage_selector(self, model: str, request_kwargs: Mapping[str, object] | None) -> object: + """``_get_routing_context``'s selector when it is a usage-based-routing-v2 one: the request's + strategy override, else the routing group ``model`` resolves into, else the router's own.""" + from litellm.router_strategy.lowest_tpm_rpm_v2 import LowestTPMLoggingHandler_v2 + + strategy, selector = self._prefetch_strategy_and_selector(model, request_kwargs or {}) + if strategy == "usage-based-routing-v2" and isinstance(selector, LowestTPMLoggingHandler_v2): + return selector + return None + + def _prefetch_strategy_and_selector(self, model: str, request: Mapping[str, object]) -> tuple[str | None, object]: + raw: Final = request.get("routing_strategy") + override: Final = normalize_strategy(raw) if isinstance(raw, str | RoutingStrategy) else None + if override is not None and override in {"simple-shuffle", *SELECTOR_ATTRIBUTES}: + return override, self._selectors.selector_for(override, "override", None, request) + groups: Final = self._hosted._core_routing_groups # pyright: ignore[reportPrivateUsage] # see __init__ + resolved: Final = self._hosted._core_get_model_from_alias(model=model) or model # pyright: ignore[reportPrivateUsage] # see __init__ + group_name: Final = ( + resolved + if self._hosted.get_routing_group(resolved) is not None + else next( + ( + group.group_name + for group in groups.values() + if group.routing_strategy != "priority" and resolved in group.models + ), + None, + ) + ) + if group_name is None: + return normalize_strategy(self._resolved.routing_strategy), self._selectors.default + if groups[group_name].routing_strategy == "priority": + return None, None + group_strategy: Final = normalize_strategy(groups[group_name].routing_strategy) + return group_strategy, self._selectors.selector_for(group_strategy or "", "group", group_name, None) + + async def _core_async_pre_routing_hook( + self, + model: str, + request_kwargs: dict[str, object], # mutable-ok: the request kwargs the hook stamps + messages: object = None, + input: object = None, + specific_deployment: bool | None = False, + ) -> "PreRoutingHookResponse | None": + """``RoutingContext.pre_routing_hook``: the pre-routing strategies' answer for ``model`` + (the tier group and its params), with the routing plugins run first.""" + r: Final = self._resolved + owner: Final[object] = self.__dict__.get("_core_owner") + public: Final[object] = owner() if callable(owner) else None + return await self._prerouter._hook( # pyright: ignore[reportPrivateUsage] # the core's own pre-router + model, + request_kwargs, + messages=messages, + input=input, + fallback_depth=0, + enable_tag_filtering=r.enable_tag_filtering, + match_any=r.tag_filtering_match_any, + public_router=public if public is not None else self, + run_plugins=partial(self._run_plugins, request_kwargs, messages) + if self._hosted._core_routing_plugins # pyright: ignore[reportPrivateUsage] # the live plugin list + else None, + ) + + def _core_log_retry( + self, + kwargs: dict[str, object], # mutable-ok: the request kwargs the record joins + e: Exception, + ) -> dict[str, object]: # mutable-ok: the same kwargs, as Python's returns them + """``RoutingContext.log_retry``.""" + return log_retry_into(kwargs, e, self._deployment_params_base_model) + + def _deployment_params_base_model(self, deployment_id: str) -> str | None: + """``_deployment_params_base_model``: the ``base_model`` a deployment declares under ``litellm_params``.""" + deployment: Final = self._hosted._core_get_deployment(model_id=deployment_id) # pyright: ignore[reportPrivateUsage] # see __init__ + if deployment is None: + return None + base_model: Final = (deployment.litellm_params.model_extra or {}).get("base_model") + return base_model if isinstance(base_model, str) else None + + def _sync_routing_state(self) -> None: + """Before a pick: sync the routing state that callers can change in place, which the Python + core reads live on every pick. This exists only for the deprecated writable attributes and + goes away with them. + + Only these cases send anything; otherwise both checks return without touching router-core:: + + router.model_names = {...} # assigning syncs at once (__setattr__) + router.model_names.add("new-group") # an in-place change is picked up here, on the next pick + router.model_name_to_deployment_indices["g"].append(3) # likewise + + router.routing_plugins.append(plugin) # first plugin: rebuilds the handle with the plugin stage + router.routing_plugins.clear() # list emptied: rebuilds without it + + Until one of the index attributes has been assigned, ``_sync_index`` sends nothing. After + that it sends the index document only when it differs from the last one it sent. + """ + self._sync_plugin_stage() + self._sync_index() + self._sync_allowed_fails() + + def _sync_allowed_fails(self) -> None: + """``_is_allowed_fails_set_on_router`` compares with the live ``litellm.allowed_fails`` on + every failure, so a write to the global can change the rule; ``_settings`` stays as copied.""" + if self._resolved.allowed_fails_is_default() != self._allowed_fails_default_sent: + names: Final = [str(d.get("model_name")) for d in self._handle.deployments()] + self._handle.apply({"settings": self._dynamic_document(names)}) + + def _sync_index(self) -> None: + """Hand router-core the registry indexes written through the deprecated attributes + (``model_names``, ``model_name_to_deployment_indices``, ``team_model_to_deployment_indices``) + as the host registry holds them now (its own deployment changes update the written objects, + as the Python core's do), whenever they differ from what it holds.""" + if not self._index_written: + return + document: Final = index_document(self._hosted, self._index_written) + if document != self._index_sent: + _ = self._handle.apply({"index": document}) + self._index_sent = document + + def _sync_plugin_stage(self) -> None: + """Give router-core the routing-plugin stage when the live plugin list (``routing_plugins``, + which callers may assign or append to) gains its first plugin, and drop it when the list + empties: the Python core checks the list on every pick.""" + live: Final = _as_list(self._hosted._core_routing_plugins) # pyright: ignore[reportPrivateUsage] # the live plugin list + if bool(live) == bool(self._resolved.routing_plugins): + return + self._resolved = dataclasses.replace(self._resolved, routing_plugins=tuple(live)) # pyright: ignore[reportArgumentType] # the plugins as listed + self._rebuild() + + def _rebuild(self) -> None: + """A new Rust core for changed static settings, over the same deployments and the + providers the old one's builds resolved for them.""" + old: Final = self._handle + model_list: Final = list(self._hosted._core_model_list) # pyright: ignore[reportPrivateUsage] # see __init__ + self._handle = self._new_handle(model_list) + self._handle.adopt_providers(old) + old.retire() + # The live list and indexes read the new handle's (the same entries, kept as the same objects). + self._hosted.refresh() + # The new handle builds its indexes from the deployments: written ones are handed again. + self._index_sent = None + + def _run_build( + self, + entries: Sequence[object], + path: str, + resolve_secrets: bool, + install: BuildInstall, + answer: Callable[[Mapping[str, object]], object], + ) -> None: + """Drive one router-core deployment build (``RouterCoreHandle.build``), answering each of + its steps with ``answer``; router-core installs each deployment as it accepts it, and the + host registry reads the list and indexes back before answering the next step.""" + call: Final = self._handle.build(_plain(list(entries)), path, resolve_secrets, install) # pyright: ignore[reportArgumentType] # plain JSON entries + outcome: object = None # rebind-ok: each step's answer + while True: + step = call.next(outcome) + self._hosted.refresh() + if step["kind"] == "done": + break + if step["kind"] == "failed": + raise ValueError(str(step.get("error"))) + outcome = _plain(answer(step)) + + def _live_handle(self) -> "RouterCoreHandle | None": + """The handle the live model_list reads, once the constructor made one.""" + from litellm.rust_bridge._native import RouterCoreHandle + + handle: Final[object] = self.__dict__.get("_handle") + return handle if isinstance(handle, RouterCoreHandle) else None + + def _apply_registry_changes(self, changes: Mapping[str, object]) -> None: + """Apply a host registry write router-core's build did not make (a removal is a delete, a + swapped list a replace) as a changeset.""" + _ = self._handle.apply(_plain(dict(changes))) # pyright: ignore[reportArgumentType] # a plain JSON changeset + + def _sync_registry(self) -> None: + """After a host registry write: router-core already holds it (the build installed what it + added, a removal came as a changeset), so only the settings it feeds move.""" + from litellm.rust_bridge._native import RouterCoreHandle + + self._tag_filtering_models = None + handle: Final[object] = self.__dict__.get("_handle") + # A wildcard deployment added an id the cooldown check skips. + if isinstance(handle, RouterCoreHandle) and self._provider_default_ids() != self._handle_default_ids: + self._rebuild() + + # -- entry points ---------------------------------------------------------------------------- + + def registry(self) -> RouterRegistry: + """The registry view, built once (``registry()`` returns the same object each time).""" + if self._registry_view is None: + self._registry_view = hosted_registry_view(self._hosted) + return self._registry_view + + def settings(self) -> RustSettings: + """A cached snapshot, replaced when a changeset changes a setting.""" + if self._settings is None: + self._settings = self._settings_snapshot() + return self._settings + + def _settings_snapshot(self) -> RustSettings: + r: Final = self._resolved + snapshot: Final = RustSettings( + routing_strategy=r.routing_strategy, + fallbacks=r.read("fallbacks"), # pyright: ignore[reportArgumentType] # the value as given, as the Python core stores it + context_window_fallbacks=r.read("context_window_fallbacks"), # pyright: ignore[reportArgumentType] # the value as given, as the Python core stores it + content_policy_fallbacks=r.read("content_policy_fallbacks"), # pyright: ignore[reportArgumentType] # the value as given, as the Python core stores it + default_deployment=r.default_deployment, + default_litellm_params=dict(r.default_litellm_params) + if "default_litellm_params" in r.assigned + else default_litellm_params(self._config), + default_max_parallel_requests=self._endpoints.default_max_parallel_requests, # pyright: ignore[reportArgumentType] # the setting as given + cooldown_time=self._cooldown_given, # pyright: ignore[reportArgumentType] # the value as given, as the Python core stores it + allowed_fails=r.read("allowed_fails"), # pyright: ignore[reportArgumentType] # the value as given, as the Python core stores it + allowed_fails_policy=r.allowed_fails_policy, # pyright: ignore[reportArgumentType] # the policy as passed + disable_cooldowns=r.read("disable_cooldowns"), # pyright: ignore[reportArgumentType] # the value as given, as the Python core stores it + enable_pre_call_checks=r.enable_pre_call_checks, + enable_health_check_routing=r.health_routing.enable_health_check_routing, + enable_tag_filtering=r.read("enable_tag_filtering"), # pyright: ignore[reportArgumentType] # the value as given, as the Python core stores it + tag_filtering_match_any=r.read("tag_filtering_match_any"), # pyright: ignore[reportArgumentType] # the value as given, as the Python core stores it + tag_routing_prefix=r.read("tag_routing_prefix"), # pyright: ignore[reportArgumentType] # the value as given, as the Python core stores it + fallback_access_check=r.fallback_access_check, # pyright: ignore[reportArgumentType] # the check as passed + fallback_budget_check=r.fallback_budget_check, # pyright: ignore[reportArgumentType] # the check as passed + cache_responses=self._endpoints.cache_responses, + search_tools=self._endpoints.search_tools, # pyright: ignore[reportArgumentType] # the configured entries, as passed + guardrail_list=self._endpoints.guardrail_list, # pyright: ignore[reportArgumentType] # same + provider_default_deployment_ids=self._hosted._core_provider_default_deployment_ids, # pyright: ignore[reportPrivateUsage] # the host registry's live list + health_check_ignore_transient_errors=r.health_routing.health_check_ignore_transient_errors, + background_health_check_model_groups=r.health_routing.background_health_check_model_groups, + router_general_settings=self._general_settings, # pyright: ignore[reportArgumentType] # the setting as given + provider_budget_config=self._checks.provider_budget_config, # pyright: ignore[reportArgumentType] # the budget limiter's live config + _router=self, # pyright: ignore[reportArgumentType] # the snapshot reads as_dict from this core + kubernetes_pod_discovery=self._pod_discovery, + ) + if not self._deleted: + return snapshot + # A deleted setting reads as unset. + return dataclasses.replace( + snapshot, + **dict.fromkeys(self._deleted.intersection(SETTING_FIELDS), None), # pyright: ignore[reportArgumentType] # settings fields only: an alias map or retry count is deletable too + _unset=snapshot._unset | self._deleted, # pyright: ignore[reportPrivateUsage] # the snapshot's own unset set + ) + + def available_guardrail(self, name: str) -> object: + return self._endpoints.available_guardrail(name) + + def settings_dict(self) -> Mapping[str, object]: + r: Final = self._resolved + latency: Final = self._selectors.latency_args() if r.routing_strategy == "latency-based-routing" else None + # `get_settings` reports the latency selector's full routing args. + args: Final = ( + latency if latency is not None else r.given.get("routing_strategy_args", dict(r.routing_strategy_args)) + ) + values: Final = { + "routing_strategy_args": args, + "routing_strategy": r.routing_strategy, + "allowed_fails": r.read("allowed_fails"), + "cooldown_time": self._cooldown_given, + "num_retries": r.read("num_retries"), + "timeout": r.read("timeout"), + "retry_after": r.read("retry_after"), + "fallbacks": r.read("fallbacks"), + "context_window_fallbacks": r.read("context_window_fallbacks"), + "model_group_alias": dict(r.model_group_alias), + "enable_mid_stream_fallback_continuation": r.enable_mid_stream_fallback_continuation, + "enable_tag_filtering": r.read("enable_tag_filtering"), + "tag_routing_prefix": r.read("tag_routing_prefix"), + "routing_groups": group_settings(r.routing_groups), + } + return settings_view(values, self._plain, self._deleted) + + def health(self) -> RustHealth: + """The health view, built once.""" + if self._health_view is None: + self._health_view = RustHealth(self) + return self._health_view + + def observe(self, logging_obj: "LiteLLMLogging | None" = None, *, request_scoped: bool = False) -> RoutingObservers: + """The routing observers: the Slack alerting logger ``alerting_config`` built, if any. + ``request_scoped=True`` takes the router's callbacks off the host lists; passing a request's + ``logging_obj`` binds its selectors and policies to it. This core registers no outcome + callbacks, so it binds none either: router-core reads what they would do for the request + (``OptionalChecks.outcome_callbacks``).""" + if request_scoped: + self._serve_through_request_logging() + if logging_obj is not None: + self._checks.bind_to_request_logging(logging_obj) + return RoutingObservers(slack_alerting_logger=self._slack_alerting_logger) + + def register_plugin(self, plugin: "CustomRoutingStrategyBase") -> None: + """``_core_set_custom_routing_strategy``: ``plugin`` picks every deployment from now on, until + the routing strategy changes.""" + self._custom_strategy = plugin + # `resolve_pods_after_bound`: its picks resolve pods through the discovery bound now. + self._custom_discovery = self._pod_discovery + # Python assigns the strategy's picks over its own: a caller of the pick reaches the + # strategy with the arguments it passed and no others. + self.__dict__["get_available_deployment"] = self._custom_sync_pick(plugin) + # It replaces an async pick assigned through the deprecated attribute, as Python's does. + if "_core_async_get_available_deployment" in self.__dict__: + del self.__dict__["_core_async_get_available_deployment"] + + def _custom_sync_pick(self, plugin: "CustomRoutingStrategyBase") -> object: + discovery: Final = self._custom_discovery + pick: Final = plugin.get_available_deployment + return pick if discovery is None else resolve_pods_after_bound(pick, discovery) + + def _custom_async_pick(self) -> object: + """``_core_set_custom_routing_strategy``'s ``_core_async_get_available_deployment``.""" + custom: Final = self._custom_strategy + discovery: Final = self._custom_discovery + pick: Final = custom.async_get_available_deployment # pyright: ignore[reportOptionalMemberAccess] # __getattr__ checked it + return pick if discovery is None else async_resolve_pods_after_bound(pick, discovery) + + def set_custom_routing_strategy(self, CustomRoutingStrategy: "CustomRoutingStrategyBase") -> None: + from litellm.router_deprecated import ( + _note, # pyright: ignore[reportPrivateUsage] # the deprecated alias notes its use like Python's + ) + + _note("set_custom_routing_strategy", "register_plugin(strategy)") + self.register_plugin(CustomRoutingStrategy) + + def retire(self) -> None: + """``_core_discard``: only the router's global registrations go; it keeps serving calls.""" + untrack_live_registry(self._hosted) + self._retire_callbacks() + if self._hosted.strategies is not None: + self._hosted.strategies.retire() + + def apply(self, changes: ChangeSet) -> ApplyResult: + """``apply_changes``: assigned settings, then ``update_settings``, upserts, deletes and the + Redis cache, in that order. An unknown name refuses the changeset; a setting + ``update_settings`` raises for ends it there, with the settings before it applied.""" + from litellm.router_api import ASSIGNABLE_ALIASES, PLAIN_SETTING_ATTRIBUTES, SETTING_FIELDS + + if changes.refresh_model_info: + raise TypeError("ChangeSet(refresh_model_info=True) needs aapply()") + unknown: Final = sorted(set(changes.assign) - {*SETTING_FIELDS, *PLAIN_SETTING_ATTRIBUTES, *ASSIGNABLE_ALIASES}) + if unknown: + raise ValueError(f"not assignable router settings: {unknown}") + unserved: Final = sorted(set(changes.assign) - _STATIC_SETTINGS - _DYNAMIC_SETTINGS - _HOST_SETTINGS) + if unserved: + raise RustCoreUnsupported(f"the Rust router core does not serve the setting(s) {', '.join(unserved)} yet") + update: Final = read_settings_update(changes.settings, self._resolved.routing_strategy) + # `apply_changes` assigns before it runs `update_settings`: a budget config assigned beside + # `optional_pre_call_checks` builds the budget limiter with the new config. + self._assign_host_settings(changes.assign) + if update.optional_pre_call_checks is not MISSING: + self._checks.set(update.optional_pre_call_checks) + if update.continuation is not MISSING: + self._set_continuation(continuation_flag(update.continuation)) + self._apply_settings(changes.assign, update) + if update.failure is not None: + raise update.failure + # Upserts first, then deletes (`apply_changes`), through the host registry, which hands + # each change to the Rust core. + upserted: Final = [self._hosted._core_upsert_deployment(deployment=d) for d in changes.upsert] # pyright: ignore[reportPrivateUsage] # see __init__ + deleted: Final = [self._hosted._core_delete_deployment(id=i) for i in changes.delete] # pyright: ignore[reportPrivateUsage] # see __init__ + if changes.redis_cache is not None: + # `_core_update_redis_cache`: the routing state's cache gains the Redis cache. + self._cache.attach_redis_cache(changes.redis_cache) + self._checks.prompt_caching_pin_cache.attach_redis_cache(changes.redis_cache) + return ApplyResult( + version=self._hosted._registry_version, # pyright: ignore[reportPrivateUsage] # see __init__ + upserted=upserted, + deleted=deleted, # pyright: ignore[reportArgumentType] # the removed model_list entries, as the core returns them + ) + + async def aapply(self, changes: ChangeSet) -> ApplyResult: + """``apply``, then the model info refresh, which needs I/O.""" + result: Final = self.apply(dataclasses.replace(changes, refresh_model_info=False, refresh_client=None)) + if changes.refresh_model_info: + await self._hosted.arefresh_model_info(changes.refresh_client) + return result + + def _apply_settings(self, assign: Mapping[str, object], update: SettingsUpdate) -> None: + values: Final = { + **without(assign, *_HOST_SETTINGS), + **update.values, + } + given: Final = dict(update.values) # the settings passed through `update_settings` + groups_input: Final[object] = ( + update.routing_groups if update.routing_groups is not MISSING else self._resolved.routing_groups_input + ) + # What `_core_update_settings` runs after its loop, which a setting that raised never reaches. + settled: Final = update.failure is None + groups_failure: Exception | None = None # rebind-ok: set when the groups passed do not parse + if settled and (update.routing_groups is not MISSING or self._changes_strategy(update.values)): + # `update_settings` re-inits the routing groups from the groups passed, else (on a + # strategy change) from the groups last passed, whatever a raw write assigned since. + try: + values["routing_groups"] = parse_groups( + groups_input, + frozenset(str(d.get("model_name")) for d in self._handle.deployments()), + frozenset(self._resolved.model_group_alias), + ) + except Exception as raised: # noqa: BLE001 # raised below: `_init_routing_groups` runs after the loop + groups_failure = raised # rebind-ok: None until the groups fail + else: + given["routing_groups"] = groups_input + self._store_plain(update.plain) + if self._deleted & set(values): + self._deleted = self._deleted - set(values) + self._settings = None + if values: + previous: Final = self._resolved + resolved: Final = dataclasses.replace( + previous.changed(values, frozenset(given)), + routing_groups_input=groups_input if "routing_groups" in values else previous.routing_groups_input, + ) + static_changed: Final = bool(_STATIC_SETTINGS & set(values)) + self._resolved = resolved + if set(values) & set(SETTING_FIELDS): + self._settings = None # the snapshot holds settings fields, not the plain attributes + if "model_group_alias" in values: + self._hosted._core_model_group_alias = dict(resolved.model_group_alias) # pyright: ignore[reportPrivateUsage, reportAttributeAccessIssue] # see __init__ + self._apply_strategy(previous, resolved, given, settled=settled) + if "routing_groups" in values: + self._settings = None + self._hosted.set_routing_groups(resolved.routing_groups) + if "cooldown_time" in values: + self._cooldown_given = values["cooldown_time"] + if values["cooldown_time"] is None: + # `add_deployment_to_cooldown(cooldown_time=None)` cools down for the cooldown + # cache's default, which keeps the constructor's value. + self._resolved = dataclasses.replace( + resolved, cooldown_time=float(self._cooldowns.default_cooldown_time) + ) + if static_changed: + self._rebuild() + else: + names: Final = [str(d.get("model_name")) for d in self._handle.deployments()] + self._handle.apply({"settings": self._dynamic_document(names)}) + if groups_failure is not None: + raise groups_failure + + def _store_plain(self, plain: Mapping[str, object]) -> None: + """Settings the Python core keeps as plain attributes, read from the next call on.""" + flags_before: Final = failover_document(self._plain) + self._plain.update(plain) + if failover_document(self._plain) != flags_before: + self._rebuild() + policies: Final = {name: plain[name] for name in _RETRY_POLICY_SETTINGS if name in plain} + if policies: + self._set_retry_policies(policies) + + def _changes_strategy(self, updated: Mapping[str, object]) -> bool: + """``update_settings`` names a ``routing_strategy`` other than the router's.""" + if "routing_strategy" not in updated: + return False + return _strategy_name(updated["routing_strategy"]) != self._resolved.routing_strategy + + def _assign_host_settings(self, assign: Mapping[str, object]) -> None: + """The assigned settings only the host reads, each stored as given (detached, as + ``apply_changes`` stores it) where its readers find it from the next call on.""" + given: Final = {name: detached(value) for name, value in assign.items() if name in _HOST_SETTINGS} + if not given: + return + for name, value in given.items(): + if name in ("enable_health_check_routing", "background_health_check_model_groups"): + self._resolved = dataclasses.replace( + self._resolved, + health_routing=dataclasses.replace(self._resolved.health_routing, **{name: value}), # pyright: ignore[reportArgumentType] # stored as given, as the Python core stores it + ) + elif name == "provider_default_deployment_ids": + # The list wildcard deployments added later are appended to, as on the Python core. + self._hosted._core_provider_default_deployment_ids = value # pyright: ignore[reportPrivateUsage, reportAttributeAccessIssue] # stored as given, as the Python core stores it + elif name == "cache_responses": + self._endpoints.set_cache_responses(bool(value)) + elif name == "provider_budget_config": + # Read when the budget limiter is built; a limiter built already keeps its config. + self._checks.provider_budget_config = value + elif name == "health_check_ignore_transient_errors": + self._resolved = dataclasses.replace( + self._resolved, + health_routing=dataclasses.replace( + self._resolved.health_routing, + health_check_ignore_transient_errors=value, # pyright: ignore[reportArgumentType] # stored as given, as the Python core stores it + ), + ) + elif name == "router_general_settings": + self._general_settings = value + elif name == "kubernetes_pod_discovery": + self._pod_discovery = value # pyright: ignore[reportAttributeAccessIssue] # stored as given, as the Python core stores it + else: + self._endpoints.assign_setting(name, value) + self._deleted = self._deleted - set(given) + self._settings = None + if {"enable_health_check_routing", "background_health_check_model_groups"} & set(given) or ( + self._provider_default_ids() != self._handle_default_ids + ): + self._rebuild() + + def _set_retry_policies(self, policies: Mapping[str, object]) -> None: + """The ``retry_policy`` and ``model_group_retry_policy`` the retry loop reads from then on, + from ``update_settings`` or an attribute write: router-core holds them with its static + settings.""" + previous: Final = self._resolved + resolved: Final = dataclasses.replace( + previous, + retry_policy=readable_retry_policy(policies.get("retry_policy", previous.retry_policy)), + model_group_retry_policy=policies.get("model_group_retry_policy", previous.model_group_retry_policy), + ) + if resolved != previous: + self._resolved = resolved + self._rebuild() + + def _apply_strategy( + self, previous: Resolved, resolved: Resolved, values: Mapping[str, object], *, settled: bool + ) -> None: + """``_core_update_settings``: a changed strategy re-inits the selectors with the args passed + alongside it (or none); changed args alone rebuild the default selector. What runs after + the loop needs ``settled``: no setting raised, and the groups are in ``values``.""" + if "routing_strategy" in values and resolved.routing_strategy != previous.routing_strategy: + if resolved.routing_strategy == "lar1": + # `_switch_routing_strategy`: LAR-1 is a custom strategy, registered in place of + # `routing_strategy_init`, so the selectors the router held stay as they were. + from litellm.router_strategy.lar1_routing import apply_lar1_routing_strategy + + apply_lar1_routing_strategy( + RoutingContext(self), # pyright: ignore[reportArgumentType] # the core's RoutingContext + as_str_mapping(values.get("routing_strategy_args")), + ) + else: + # `routing_strategy_init` drops a custom strategy (`_reset_custom_routing_strategy`), + # and an async pick assigned through the deprecated attribute. + self._custom_strategy = None + self.__dict__.pop("get_available_deployment", None) + if "_core_async_get_available_deployment" in self.__dict__: + del self.__dict__["_core_async_get_available_deployment"] + self._selectors.init_default( + resolved.routing_strategy, as_str_mapping(values.get("routing_strategy_args")) or {} + ) + if "routing_groups" in values: + self._selectors.init_groups(_group_selectors(resolved.routing_groups)) + elif "routing_groups" in values: + self._selectors.init_groups(_group_selectors(resolved.routing_groups)) + elif ( + settled + and "routing_strategy_args" in values + and resolved.routing_strategy_args != previous.routing_strategy_args + ): + if resolved.routing_strategy == "lar1": + from litellm.router_strategy.lar1_routing import apply_lar1_routing_strategy + + apply_lar1_routing_strategy(RoutingContext(self), resolved.routing_strategy_args) # pyright: ignore[reportArgumentType] # the core's RoutingContext + return + self._selectors.rebuild_default(resolved.routing_strategy_args) + + def upsert_deployment(self, deployment: Deployment) -> Deployment | None: + from litellm.router_deprecated import ( + _note, # pyright: ignore[reportPrivateUsage] # the router's deprecation notice + ) + + _note("upsert_deployment", "apply(ChangeSet(upsert=[deployment]))") + return self.apply(ChangeSet(upsert=[deployment])).upserted[0] + + def delete_deployment(self, id: str) -> Deployment | None: + from litellm.router_deprecated import _note # pyright: ignore[reportPrivateUsage] # see above + + _note("delete_deployment", "apply(ChangeSet(delete=[id]))") + return self.apply(ChangeSet(delete=[id])).deleted[0] + + def update_settings(self, **kwargs: object) -> None: # kwargs-ok: the deprecated signature, unchanged + from litellm.router_deprecated import _note # pyright: ignore[reportPrivateUsage] # see upsert_deployment + + _note("update_settings", "apply(ChangeSet(settings={...}))") + _ = self.apply(ChangeSet(settings=kwargs)) + + def update_redis_cache(self, cache: "RedisCache") -> None: + from litellm.router_deprecated import _note # pyright: ignore[reportPrivateUsage] # see upsert_deployment + + _note("update_redis_cache", "apply(ChangeSet(redis_cache=cache))") + _ = self.apply(ChangeSet(redis_cache=cache)) + + def get_model_list( + self, model_name: str | None = None, team_id: str | None = None + ) -> "list[DeploymentTypedDict] | None": # mutable-ok: the old return type, unchanged + from litellm.router_deprecated import _note # pyright: ignore[reportPrivateUsage] # see upsert_deployment + + _note("get_model_list", "registry().deployments(model_name, team_id=...)") + return self._hosted._core_get_model_list(model_name=model_name, team_id=team_id) # pyright: ignore[reportPrivateUsage, reportReturnType] # the host registry's listing, as the deprecated member returns it + + @staticmethod + def get_valid_args() -> list[str]: # mutable-ok: the old return type, a fresh list + """The arguments ``Router.__init__`` accepts.""" + return list(ROUTER_INIT_ARGS) + + async def arefresh_model_info(self, *, client: "AsyncHTTPHandler | None" = None) -> None: + from litellm.router_deprecated import _note # pyright: ignore[reportPrivateUsage] # see upsert_deployment + + _note("arefresh_model_info", "aapply(ChangeSet(refresh_model_info=True))") + _ = await self.aapply(ChangeSet(refresh_model_info=True, refresh_client=client)) + + def flush_cache(self) -> None: + """Drop the host's response cache and the routing state.""" + self._host.set_global_cache(None) + self._cache.flush_cache() + self._checks.prompt_caching_pin_cache.in_memory_cache.flush_cache() + + def reset(self) -> None: + """Empty the host's success and failure callback lists (every entry, not only this core's), + drop the retry policy and flush the caches.""" + for name in ("success_callback", "_async_success_callback", "failure_callback", "_async_failure_callback"): + self._host.set_callback_list(name, []) + self._plain["retry_policy"] = None + self._set_retry_policies({"retry_policy": None}) + self.flush_cache() + + def __delattr__(self, name: str) -> None: + # `del router.` unsets it: the settings view reports it unset from then on. + from litellm.router_api import SETTING_FIELDS + + # The deprecated attribute deletes the core's own name (``_core_``). + setting: Final = name.removeprefix("_core_") + if setting not in SETTING_FIELDS and setting not in _DELETABLE_ATTRIBUTES: + if name in self.__dict__ or name in self._unset_attributes: + object.__delattr__(self, name) + return + if self._settings_attribute(name) is MISSING: + object.__delattr__(self, name) + return + # An attribute the Python core keeps on the instance (`alerting_config`, an argument + # as passed): reading it raises AttributeError from now on. + self.__dict__["_unset_attributes"] = self._unset_attributes | {name} + return + if setting in self._deleted: + raise self._no_attribute(setting) + self._deleted = self._deleted | {setting} + self._settings = None + if setting == "model_group_alias": + del self._hosted._core_model_group_alias # pyright: ignore[reportPrivateUsage] # every read of it raises from now on, as on the Python core + elif setting == "scheduler": + self._endpoints.delete_scheduler() + + def _no_attribute(self, name: str) -> AttributeError: + """What reading an attribute deleted from the core raises (the facade renames it).""" + return AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'", name=name, obj=self) + + def _no_router_attribute(self, name: str) -> AttributeError: + """``_no_attribute`` for a read through ``registry()``, which the deprecated attribute + renames when it is the router's own.""" + owner: Final[object] = self.__dict__.get("_core_owner") + public: Final[object] = owner() if callable(owner) else None + return AttributeError( + f"'{type(self).__name__}' object has no attribute '{name}'", + name=name, + obj=self if public is None else public, + ) + + def _refuse_deleted_reads(self, request: Mapping[str, object]) -> None: + """What a call reads of the router before any attempt, once deleted: routing reads + ``_core_model_group_alias``, and ``async_function_with_retries`` reads ``self.num_retries`` + when the request names none. Every hop raises it, so no fallback serves the call.""" + if "model_group_alias" in self._deleted: + raise self._no_attribute("_core_model_group_alias") + if "num_retries" in self._deleted and request.get("num_retries") is None: + raise self._no_attribute("num_retries") + + def __setattr__(self, name: str, value: object) -> None: + # A setting write is a changeset (`router.num_retries = 2` is `apply(ChangeSet(assign=...))`), + # a `model_list` write swaps the live list, and any other attribute is kept as written. + from litellm.router_api import ASSIGNABLE_ALIASES, PLAIN_SETTING_ATTRIBUTES, SETTING_FIELDS + + if name in PLAIN_SETTING_ATTRIBUTES or name in SETTING_FIELDS or name in ASSIGNABLE_ALIASES: + _ = self.apply(ChangeSet(assign={name: value})) + elif name in PLAIN_DEFAULTS or name == "max_retries": + # Plain attributes on the Python core, outside the setting lists: stored as given. + self._store_plain({name: value}) + elif name == "scheduler": + self._endpoints.set_scheduler(value) + self._deleted = self._deleted - {name} + elif name in ("model_list", "_core_model_list"): + # `router.model_list = [...]` reaches the core as `_core_model_list` through the shim. + self._assign_model_list(_as_list(value)) + elif name in _HOSTED_STATE: + # A deprecated attribute write of the registry state: it lands where this core keeps it. + setattr(self._hosted, name, value) + if name in INDEX_ATTRIBUTES: + self._index_written = self._index_written | {name} + self._sync_index() + elif name == "_core_routing_groups": + # The Python core routes on the assigned groups from the next call on, while its + # member map and group selectors stay as they were; router-core holds the groups and + # the member map with its static settings. + assigned: Final = as_str_mapping(value) or {} + previous: Final = self._resolved + self._resolved = dataclasses.replace( + previous, + routing_groups=tuple(g for g in assigned.values() if isinstance(g, RoutingGroup)), + routing_group_members=previous.routing_group_members + if previous.routing_group_members is not None + else member_map(previous.routing_groups), + ) + self._settings = None + self._rebuild() + elif name == "_core_routing_plugins": + self._sync_plugin_stage() + elif name == "_core_prompt_caching_pin_cache": + # Read when a prompt caching check is built, by `update_redis_cache` and by `flush_cache`. + self._checks.prompt_caching_pin_cache = value # pyright: ignore[reportAttributeAccessIssue] # stored as given, as the Python core stores it + elif name in _REBOUND_STATE: + # A deprecated attribute write of the routing state (``router.cache = ...``): this core + # reads the new object from now on, as the Python core reads its rebound attribute. + object.__setattr__(self, _REBOUND_STATE[name], value) + if name == "_core_cache": + self._hosted._core_cache = value # pyright: ignore[reportPrivateUsage, reportAttributeAccessIssue] # usage reads come from the routing cache + elif name == "_core_slack_alerting_logger": + from litellm.integrations.custom_logger import CustomLogger + + # `_slack_alerting_loggers` reads the attribute each time: the new logger is the one bound. + self._checks.slack_alerting_loggers = (value,) if isinstance(value, CustomLogger) else () + else: + # Any other attribute is kept as written; `_core_async_get_available_deployment` (the + # deprecated async pick) is then asked by every async pick (see `_pre_route`). + object.__setattr__(self, name, value) + + async def select( # pyright: ignore[reportIncompatibleMethodOverride] # the RouterCore selection + self, + model: str, + request_kwargs: dict[str, object] | None = None, # mutable-ok: the RouterCore signature + *, + kind: str = "pick", + specific_deployment: bool | None = None, + messages: object = None, + input: object = None, + health_check_probe: bool = False, + **_: object, # kwargs-ok: the RouterCore select options this core ignores + ) -> Mapping[str, object] | Sequence[Mapping[str, object]]: + """Pick a deployment for ``model`` without calling it (``pick``), list the deployments a + pick would choose among (``healthy``), or pick one for a pass-through route + (``pass_through``, which picks with the sync strategies, as Python does).""" + if kind not in ("pick", "healthy", "pass_through"): + raise ValueError(f"unknown select kind {kind!r}") + self._refuse_deleted_reads({"num_retries": 0}) # a pick reads no retry budget + request: Final = request_kwargs if request_kwargs is not None else {} + selection: Final = _Selection( + self, + model, + request, + kind, + specific_deployment, + messages, + input, + probe=kind == "healthy" and health_check_probe, + ) + # A pick that makes no call holds no least-busy reservation (`select` on the Python core). + with picks_reserve(False): + if kind == "pass_through": + return selection.run_sync() + return await selection.run() + + async def async_get_available_deployment_for_pass_through( + self, + model: str, + request_kwargs: dict[str, object], # mutable-ok: the legacy signature + messages: object = None, + input: object = None, + specific_deployment: bool | None = False, + ) -> Mapping[str, object]: + """The full healthy chain, then only ``use_in_pass_through`` deployments, picked with the + async strategies.""" + selection: Final = _Selection( + self, model, request_kwargs, "async_pass_through", specific_deployment, messages, input + ) + picked: Final = await selection.run() + return picked if isinstance(picked, Mapping) else {} + + def get_available_deployment( + self, + model: str, + messages: object = None, + input: object = None, + specific_deployment: bool | None = False, + request_kwargs: dict[str, object] | None = None, # mutable-ok: the legacy signature + ) -> Mapping[str, object]: + """The sync pick: no pre-routing, the sync strategies.""" + selection: Final = _Selection( + self, + model, + request_kwargs if request_kwargs is not None else {}, + "sync_pick", + specific_deployment, + messages, + input, + ) + picked: Final = selection.run_sync() + return picked if isinstance(picked, Mapping) else {} + + def get_available_deployment_for_pass_through( + self, + model: str, + messages: object = None, + input: object = None, + specific_deployment: bool | None = False, + request_kwargs: dict[str, object] | None = None, # mutable-ok: the legacy signature + ) -> Mapping[str, object]: + """Deprecated: ``select(model, kind="pass_through")``.""" + from litellm.router_deprecated import ( + _note, # pyright: ignore[reportPrivateUsage] # the router's deprecation notice + ) + + _note("get_available_deployment_for_pass_through", 'select(model, kind="pass_through")') + selection: Final = _Selection( + self, + model, + request_kwargs if request_kwargs is not None else {}, + "pass_through", + specific_deployment, + messages, + input, + ) + picked: Final = selection.run_sync() + return picked if isinstance(picked, Mapping) else {} + + # -- endpoints ------------------------------------------------------------------------------- + + async def call(self, op: str, request: Mapping[str, object]) -> object: + """Run one endpoint with the request's keyword payload, as ``getattr(core, op)(**request)``.""" + member: Final[object] = getattr(self, op) # pyright: ignore[reportAny] # litellm's untyped helpers and request values + if not callable(member): + raise TypeError(f"{op!r} is not an endpoint") + result: Final[object] = member(**request) + return await result if inspect.isawaitable(result) else result + + async def acompletion(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return await self._endpoints.acompletion(request_from_call("acompletion", args, kwargs)) + + async def atext_completion(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return await self._endpoints.atext_completion(request_from_call("atext_completion", args, kwargs)) + + async def aembedding(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return await self._drive(plan_for("aembedding"), request_from_call("aembedding", args, kwargs)) + + async def aresponses(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return await self._endpoints.generic(plan_for("aresponses"), request_from_call("aresponses", args, kwargs)) + + async def aanthropic_messages(self, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return await self._endpoints.generic(plan_for("aanthropic_messages"), kwargs) + + async def anthropic_messages(self, **kwargs: object) -> object: # kwargs-ok: endpoint payload + """The proxy's ``/v1/messages`` route name for ``aanthropic_messages``; async, as in PythonCore.""" + return await self._endpoints.generic(plan_for("anthropic_messages"), kwargs) + + async def aimage_generation(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return await self._drive(plan_for("aimage_generation"), request_from_call("aimage_generation", args, kwargs)) + + async def atranscription(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return await self._drive(plan_for("atranscription"), request_from_call("atranscription", args, kwargs)) + + async def aspeech(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + request: Final = dict(request_from_call("aspeech", args, kwargs)) + request.setdefault("voice", None) + return await self._drive(plan_for("aspeech"), request) + + async def arerank(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + # `arerank` sets kwargs["input"] = input: the Python builtin, which reaches the deployment call. + request: Final = {**request_from_call("arerank", args, kwargs), "input": input} + return await self._drive(plan_for("arerank"), request) + + async def amoderation(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return await self._endpoints.amoderation(request_from_call("amoderation", args, kwargs)) + + def completion(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return self._call_sync(plan_for("completion"), request_from_call("completion", args, kwargs)) + + def text_completion(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return self._endpoints.text_completion(request_from_call("text_completion", args, kwargs)) + + def embedding( + self, + model: str, + input: str | list[object], # mutable-ok: the request field, as the Python core takes it + is_async: bool | None = False, + **kwargs: object, # kwargs-ok: endpoint payload + ) -> object: + """``embedding``'s own signature; as there, ``is_async`` is named and goes no further.""" + return self._call_sync(plan_for("embedding"), {**kwargs, "model": model, "input": input}) + + def image_generation(self, *args: object, **kwargs: object) -> object: # kwargs-ok: endpoint payload + return self._call_sync(plan_for("image_generation"), request_from_call("image_generation", args, kwargs)) + + # -- driving a call -------------------------------------------------------------------------- + + def _start( + self, + plan: Plan, + request: Mapping[str, object], + overrides: Mapping[str, object] | None = None, + *, + prepared_already: bool = False, + ) -> "tuple[RouterCall[_CallSteps], Mapping[str, object]]": + self._refuse_deleted_reads({**request, **(overrides or {})}) + self._sync_routing_state() + model: Final = request.get("model") + if model is None and "model" in request: + raise self._no_model_error(plan, request) + if "model" not in request: + raise TypeError(f"{plan.endpoint}() needs a model name") + name: Final = model if isinstance(model, str) else self.routed_name(model) + field: Final = plan.prepare_field or "metadata" + if request.get(field) is not None and not isinstance(request.get(field), Mapping): + raise TypeError(f"{field} must be a mapping") + prepared: Final = dict(request) if prepared_already else self._endpoints.prepare(plan, request, model) # pyright: ignore[reportArgumentType] # the name as given, which the metadata keeps + return self._handle.start( + plan.endpoint, self._routing_inputs(plan, request, prepared, name, overrides) + ), prepared + + def service_logged(self, call_type: str, start_time: float, end_time: float, request: Mapping[str, object]) -> None: + """The ``ServiceTypes.ROUTER`` success event of a timed step, as a task of the running loop.""" + import asyncio + + from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs + from litellm.types.services import ServiceTypes + + _ = asyncio.create_task( # fire and forget, as the Python core schedules it + self.service_logger_obj.async_service_success_hook( # pyright: ignore[reportUnknownMemberType] # its unused `event_metadata` is an untyped dict + service=ServiceTypes.ROUTER, + duration=end_time - start_time, + call_type=call_type, + start_time=start_time, + end_time=end_time, + parent_otel_span=get_parent_otel_span_from_kwargs(request), + ) + ) + + def track_deployment_pick(self, deployment_id: object, request: Mapping[str, object]) -> None: + """``_track_deployment_metrics`` for a pick: ``_update_usage``'s count of the deployment's + picks in the router cache, on this worker only. A default deployment served under a + placeholder id counts under the id Python's copy of it holds.""" + from litellm._logging import verbose_router_logger + from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs + + parent_otel_span: Final = get_parent_otel_span_from_kwargs(request) + try: + model_id: Final = ( + self._default_deployment_id() + if deployment_id in (DEFAULT_DEPLOYMENT_FAILING_ID, DEFAULT_DEPLOYMENT_COPIED_ID) + else deployment_id + ) + if model_id is None: + return + counts: Final = self._pick_counts() + count: Final = counts.get_cache(key=model_id, parent_otel_span=parent_otel_span, local_only=True) + if count is None: + counts.set_cache(key=model_id, value=1, local_only=True, ttl=60) # only store for 60s + else: + counts.set_cache(key=model_id, value=count + 1, local_only=True) + except Exception as e: # noqa: BLE001 # as `_track_deployment_metrics` catches it + verbose_router_logger.error("Error in _track_deployment_metrics: %s", e) + + def _pick_counts(self) -> _PickCounts: + return self._cache + + def _default_deployment_id(self) -> object: + return self._resolved.default_deployment.get("model_info", {}).get("id", None) # pyright: ignore[reportOptionalMemberAccess, reportAttributeAccessIssue, reportUnknownMemberType, reportUnknownVariableType] # read as Python reads it + + def routed_name(self, model: object, *, read_as_member: bool = False) -> str: + """The name a ``model`` that is no string routes under, for the native calls, which take strings + alone. Python's first reads raise for most values: the alias lookup hashes it (a sync pick reads + ``model in _core_model_names`` first, ``read_as_member``), then ``_core_get_model_list`` reaches + ``declared_provider``, which searches it. A value both accept (falsy, a tuple) is a name no + deployment serves, and ``str(model)`` is how every error names it.""" + from litellm.litellm_core_utils.get_llm_provider_logic import inferred_provider + + if read_as_member: + _ = model in frozenset[object]() + else: + _ = self._hosted._core_get_model_from_alias(model) # pyright: ignore[reportPrivateUsage, reportArgumentType] # raising is the point + _ = inferred_provider(model) # pyright: ignore[reportArgumentType] # see above + return str(model) + + def _no_model_error(self, plan: Plan, request: Mapping[str, object]) -> BaseException: + """``model=None``: the pick fails in ``_common_checks_available_deployment``, naming the + first default fallback when there is one, and with no group the fallback wrapper raises + that error as it is (``async_function_with_fallbacks_common_utils``).""" + import litellm.exceptions as litellm_exceptions + + named: Final = next( + ( + targets[0] + for entry in _as_list(self._resolved.fallbacks) + if (targets := _as_list((as_str_mapping(entry) or {}).get("*"))) + ), + None, + ) + error: Final = litellm_exceptions.BadRequestError( + message=f"You passed in model={named}. {RouterErrors.no_healthy_deployments.value}", + model=named, # pyright: ignore[reportArgumentType] # None, as the Python router passes it + llm_provider="", + ) + if not plan.sync: + _Driver(self, plan, request)._log_pick_failure(error) # pyright: ignore[reportPrivateUsage] # the async pick's own logging + return error + + def _routing_inputs( + self, + plan: Plan, + request: Mapping[str, object], + prepared: Mapping[str, object], + model: str, + overrides: Mapping[str, object] | None, + ) -> Mapping[str, object]: + """The document router-core starts a call from: what it routes on, then what this call changes.""" + fields: dict[str, object] = {"model": model} # mutable-ok: built up below, later keys win # rebind-ok: same + fields.update(self._routing_fields(prepared, plan.pick_input(prepared)[0])) + fields.update(pinned_video_deployment(plan, request)) + fields.update(unrouted_fields(plan)) + fields.update(failover_fields(plan)) + fields.update(scoped_fallback_fields(plan, request)) + fields.update(self._selection_fields(plan, prepared)) + fields.update(self._outcome_fields(plan, request)) + # The sync path never runs pre-routing; a custom strategy picks on both. + if not plan.sync or self._custom_strategy is not None: + fields["pre_routes"] = True + if (mock := mock_failure(request)) is not None: + fields["mock_failure"] = mock + fields.update(self._retry_policy_raises(request)) + if overrides is not None and "num_retries" in overrides: + fields.pop("uncounted_retries", None) + fields.update(overrides or {}) + return _document(fields) + + def _outcome_fields(self, plan: Plan | None, request: Mapping[str, object]) -> Mapping[str, object]: + """Which outcome callbacks run for the request: an endpoint that makes one attempt skips + ``make_call``, and a recovered stream is async.""" + sync: Final = plan is not None and plan.sync + make_call: Final = plan is None or not plan.single_attempt + callbacks: Final = self.outcome_callbacks(request, sync=sync, make_call=make_call) + return {"outcome_callbacks": callbacks} if callbacks else {} + + def _selection_fields(self, plan: Plan, request: Mapping[str, object]) -> Mapping[str, object]: + """What an endpoint's pick reads beyond the routing fields: the narrowing keys the caller + passed, the endpoint ``endpoint_selection`` names, and whether it asks for web search, + which only an async pick filters by.""" + endpoint: Final = selection_endpoint(self._port, plan) + web_search: Final = not plan.sync and self._picks_async() and is_web_search_request(request) + # The generic handler `_route_capability_pin` names: a call only some providers serve + # drops the others, and a Decisions call carrying media skips the deployments refusing it. + handler: Final = plan.host_op.rsplit(".", 1)[-1] + decisions_media: Final = handler in DECISIONS_MEDIA_CALL_TYPES and bool( + request.get("audio") or request.get("videos") + ) + return { + **_request_narrowing(request), + **({"endpoint": endpoint} if endpoint is not None else {}), + **({"web_search": True} if web_search else {}), + **({"route_handler": handler} if serves_route_capability(handler) else {}), + **({"decisions_media": True} if decisions_media else {}), + } + + def _picks_async(self) -> bool: + return picks_async(normalize_strategy(self._resolved.routing_strategy)) + + def _process_renamed(self, model: str, group: str) -> str: + """``model`` as the error names it (``_common_checks_available_deployment``): the group a name + resolved to by name, alias or routing group, renamed through the process ``model_alias_map``.""" + resolution: Final = self._handle.resolve(model) + if resolution is None or resolution["kind"] not in ("Group", "Alias", "RoutingGroup"): + return model + renames: Final = self._host.dynamic().model_alias_map + return renames[group] if group in renames else group # noqa: SIM401 # `renames` is any process mapping, read as Python reads it + + def _max_parallel_requests_client(self, deployment: Mapping[str, object], kwargs: Mapping[str, object]) -> object: + """``_get_client(client_type="max_parallel_requests")``: the deployment's slot limit.""" + return max_parallel_requests_limit(self._port, deployment, kwargs) + + def _routable( + self, model: str, request: Mapping[str, object], call_type: str | None = None + ) -> Sequence[Mapping[str, object]]: + """``_core_get_routable_deployments``: ``call_type`` names the endpoint it asks about.""" + endpoint: Final = endpoint_for_call(call_type) + return self._handle.routable( + model, + _document( + { + **_start_fields(request), + **({"endpoint": endpoint} if endpoint is not None else {}), + "wildcard_request": wildcard_request(model), + } + ), + ) + + def _routing_fields(self, request: Mapping[str, object], messages: object = None) -> Mapping[str, object]: + """The request fields the Rust core routes on, and whether its tag stage may apply: the + router's ``enable_tag_filtering``, the request's own, or a deployment's + ``model_info.enable_tag_filtering`` (``get_deployments_for_tag``'s effective setting).""" + filter_tags: Final = ( + self._resolved.enable_tag_filtering + or request.get("enable_tag_filtering") is True + or self._model_tag_filtering() + ) + fields: dict[str, object] = dict(_start_fields(request)) # mutable-ok: built up below # rebind-ok: same + fields.update(self._group_policy_fields(request)) + if filter_tags: + fields["filter_tags"] = True + if request_carries_image(messages, request): + fields["has_image"] = True + return fields + + def _group_policies(self, request: Mapping[str, object]) -> tuple[object, GroupPolicies]: + """The ``model_group_retry_policy`` the retry loop reads for this request (the request's own, + even ``None``, replaces the router's: ``kwargs.pop(..., self.model_group_retry_policy)``), + resolved for every group name the call may look up.""" + policies: Final = request.get("model_group_retry_policy", self._resolved.model_group_retry_policy) + names: Final = self._policy_lookup_names(request) + resolved: Final = group_policies(policies, names) + if reads_as_policy(self._written_retry_policy): + return policies, resolved + # A group no entry names looks up the router's `retry_policy`, and that lookup raises. + unnamed: Final = names - frozenset(resolved.document) + return policies, dataclasses.replace(resolved, raising=resolved.raising | unnamed) + + def _policy_lookup_names(self, request: Mapping[str, object]) -> frozenset[str]: + """The model names a retry policy lookup may run on (each hop looks up the name it calls): + the requested one and every name in the fallback lists the walk may take.""" + resolved: Final = self._resolved + lists: Final = ( + resolved.fallbacks, + resolved.context_window_fallbacks, + resolved.content_policy_fallbacks, + *(request.get(key) for key in _REQUEST_FALLBACK_KEYS), + ) + return frozenset((*_strings(request.get("model")), *_strings(lists))) + + def _retry_policy_raises(self, request: Mapping[str, object]) -> Mapping[str, object]: + """The groups whose ``model_group_retry_policy`` lookup raises on a hop's first failure, for + router-core to end that hop with the error the lookup raises (see ``_Driver.take_events``).""" + raising: Final = raising_groups(request, self._group_policies(request)[1]) + return {"retry_policy_raises": list(raising)} if raising else {} + + def _group_policy_fields(self, request: Mapping[str, object]) -> Mapping[str, object]: + """The request's ``model_group_retry_policy`` for router-core; a router policy that is not a + mapping of policies rides on every request, resolved for it.""" + policies, resolved = self._group_policies(request) + if "model_group_retry_policy" not in request and is_policy_per_group(policies): + return {} + return {"model_group_retry_policy": _plain(resolved.document)} + + def _model_tag_filtering(self) -> bool: + """Whether any deployment sets ``model_info.enable_tag_filtering``, cached per registry version.""" + cached: Final = self._tag_filtering_models + if cached is not None and cached[0] == self._version: + return cached[1] + found: Final = any( + (as_str_mapping((as_str_mapping(record) or {}).get("model_info")) or {}).get("enable_tag_filtering") + is not None + for record in self._handle.deployments() + ) + self._tag_filtering_models = (self._version, found) + return found + + async def _drive( + self, + plan: Plan, + request: Mapping[str, object], + overrides: Mapping[str, object] | None = None, + *, + passthrough: "Callable[[Mapping[str, object], str], Awaitable[object]] | None" = None, + prepared_already: bool = False, + ) -> object: + routed: Final = ( + overrides if passthrough is None else {**(overrides or {}), "passthrough_on_no_deployment": True} + ) + # `owning_picks`: least-busy frees every pick this request made but never started. + with owning_picks(self._selectors.reservations, call_id_of(CALL_IDENTITY.validate_python(request))): + call, prepared = self._start(plan, request, routed, prepared_already=prepared_already) + arm_compaction_state(self._port, plan, prepared) # pyright: ignore[reportArgumentType] # the call's own dict + with picks_reserve(plan.endpoint not in _UNRESERVED_OPS): + driver, step = await self._run(plan, call, prepared, fresh=True, passthrough=passthrough) + if step["kind"] == "failed": + raise driver.failed(step) + return await driver.finish_async(step) + + async def _run( + self, + plan: Plan, + call: "RouterCall[_CallSteps]", + prepared: Mapping[str, object], + cut_deployment: object = None, + stream_failure: tuple[int, BaseException] | None = None, + *, + fresh: bool = False, + passthrough: "Callable[[Mapping[str, object], str], Awaitable[object]] | None" = None, + ) -> "tuple[_Driver, Mapping[str, object]]": + """Drive ``call`` to its ``done`` or ``failed`` step, answering every step on the host. + ``cut_deployment`` is the attempt whose stream failed, for a recovery call, and + ``stream_failure`` the level it served with the failure a fallback walk re-enters from. + ``fresh`` is a call from the top, through the retry and fallback wrappers, and + ``passthrough`` serves an attempt whose pick failed.""" + driver: Final = _Driver( + self, plan, prepared, cut_deployment, stream_failure, fresh=fresh, passthrough=passthrough + ) + outcome: object = None # rebind-ok: the answer to the last step + while True: + step = call.next(outcome) + driver.take_events(step.get("events")) + # `run_async_fallback` stamps a served response before it logs the hop's success: `finish` + # runs what a served call still has pending. + if step["kind"] != "done": + await await_all(driver.outcomes.take_pending()) + match step["kind"]: + case "attempt": + outcome = await driver.attempt(step) + case "sleep": + await self._host.sleep(_sleep_seconds(step)) + outcome = None + case "allow_fallback": + outcome = await driver.allow_fallback(str(step["target"])) + case "refuse_fallbacks": + outcome = driver.refuse_fallbacks(step) + case "cache": + outcome = await self._answer_cache(step) + case "select": + outcome = await driver.select(step) + case "pre_route": + outcome = await driver.pre_route(step) + case "done" | "failed": + return driver, step + case other: # pyright: ignore[reportUnnecessaryComparison] # a kind the bridge returns but the stub does not list + raise RuntimeError(f"router-core returned an unknown step {other!r}") + + def _call_sync( + self, plan: Plan, request: Mapping[str, object], overrides: Mapping[str, object] | None = None + ) -> object: + # The sync routed calls pick with `picks_reserve(True)` inside `owning_picks`. + with owning_picks(self._selectors.reservations, call_id_of(CALL_IDENTITY.validate_python(request))): + call, prepared = self._start(plan, request, overrides) + with picks_reserve(plan.endpoint not in _UNRESERVED_OPS): + driver, step = self._run_sync(plan, call, prepared, fresh=True) + if step["kind"] == "failed": + raise driver.failed(step) + return driver.finish(step) + + def _run_sync( + self, + plan: Plan, + call: "RouterCall[_CallSteps]", + prepared: Mapping[str, object], + cut_deployment: object = None, + stream_failure: tuple[int, BaseException] | None = None, + *, + fresh: bool = False, + ) -> "tuple[_Driver, Mapping[str, object]]": + driver: Final = _Driver(self, plan, prepared, cut_deployment, stream_failure, sync=True, fresh=fresh) + outcome: object = None # rebind-ok: the answer to the last step + while True: + step = call.next(outcome) + driver.take_events(step.get("events")) + if step["kind"] != "done": # see _run + driver.log_outcomes_sync() + match step["kind"]: + case "attempt": + outcome = driver.attempt_sync(step) + case "sleep": + self._host.sleep_sync(_sleep_seconds(step)) + outcome = None + case "allow_fallback": + from litellm.litellm_core_utils import asyncify + + outcome = asyncify.run_async_function(driver.allow_fallback, str(step["target"])) # pyright: ignore[reportUnknownMemberType] # the untyped sync bridge + case "refuse_fallbacks": + outcome = driver.refuse_fallbacks(step) + case "cache": + outcome = self._answer_cache_sync(step) + case "select": + outcome = driver.select_sync(step) + case "pre_route": + outcome = driver.pre_route_sync(step) + case "done" | "failed": + return driver, step + case other: # pyright: ignore[reportUnnecessaryComparison] # a kind the bridge returns but the stub does not list + raise RuntimeError(f"router-core returned an unknown step {other!r}") + + # -- stream recovery (the host's stream wrappers, router_rust.invoke.streaming) --------------------- + + def _recovery_call( + self, + recovery: str, + op: str, + request: Mapping[str, object], + origin: Mapping[str, object], + failure: BaseException, + ) -> "RouterCall[_CallSteps]": + start: Final = self._handle.retry_stream if recovery == "retry" else self._handle.fallback_stream + plan: Final = generic_plan(op) + routing: Final = _document( + { + "model": _routed_model(request), + **self._routing_fields(request), + **(self._selection_fields(plan, request) if plan is not None else {}), + **self._retry_policy_raises(request), + **continuation_routing(self, request), + **self._outcome_fields(plan, request), + } + ) + return start(op, routing, _document(origin), attempt_failure(failure)) + + def stream_policy( + self, request: Mapping[str, object], origin: Mapping[str, object], trigger: BaseException | None + ) -> Mapping[str, object]: + routing: Final = _document( + { + "model": _routed_model(request), + **_start_fields(request), + **self._group_policy_fields(request), + **self._retry_policy_raises(request), + } + ) + kind: Final = None if trigger is None else str(attempt_failure(trigger)["kind"]) + return self._handle.stream_policy(routing, _document(origin), kind) + + async def recover_stream( + self, + recovery: str, + op: str, + request: Mapping[str, object], + origin: Mapping[str, object], + failure: BaseException, + ) -> object: + """The fallback walk for a stream that failed before content: the fallback's response with the + router's headers, or the error the walk ended on.""" + call: Final = self._recovery_call(recovery, op, request, origin, failure) + driver, step = await self._run( + plan_for(op), call, request, origin.get("deployment_id"), (_origin_level(origin), failure) + ) + if step["kind"] == "failed": + raise driver.failed(step) + return await driver.finish_async(step) + + def recover_stream_sync( + self, + recovery: str, + op: str, + request: Mapping[str, object], + origin: Mapping[str, object], + failure: BaseException, + ) -> object: + call: Final = self._recovery_call(recovery, op, request, origin, failure) + driver, step = self._run_sync( + plan_for(op), call, request, origin.get("deployment_id"), (_origin_level(origin), failure) + ) + if step["kind"] == "failed": + raise driver.failed(step) + return driver.finish(step) + + async def retry_stream( + self, op: str, request: Mapping[str, object], origin: Mapping[str, object], failure: BaseException + ) -> "tuple[object, int, int] | BaseException": + """A same-group retry of a stream that failed before content: the retried response (without the + router's headers) with the retry count and budget, or the newest failure (``failure`` itself + when no retry ran).""" + call: Final = self._recovery_call("retry", op, request, origin, failure) + driver, step = await self._run(plan_for(op), call, request, origin.get("deployment_id")) + await await_all(driver.outcomes.take_pending()) + if step["kind"] == "failed": + return driver.last_error if driver.last_error is not None else failure + attempted: Final = step.get("attempted_retries") + budget: Final = step.get("max_retries") + return ( + driver.response, + attempted if isinstance(attempted, int) else 0, + budget if isinstance(budget, int) else 0, + ) + + def params_sent_to_deployment(self, request: Mapping[str, object], deployment_id: object) -> Mapping[str, object]: + """The request as a deployment received it: its params, the router defaults, its tool choice, then + the request (``_params_sent_to_deployment``).""" + record: Final = self._handle.deployment(deployment_id) if isinstance(deployment_id, str) else None + params: Final = as_str_mapping((as_str_mapping(record) or {}).get("litellm_params")) or {} + defaults: Final = {k: v for k, v in self._resolved.default_litellm_params.items() if v is not None} + tool_choice: Final = {"tool_choice": params["tool_choice"]} if params.get("tool_choice") is not None else {} + return MappingProxyType({**params, **defaults, **tool_choice, **request}) + + def _drive_sync_steps(self, call: "RouterCall[_FailureReportSteps | _SuccessReportSteps]") -> Mapping[str, object]: + """Drive a call whose only steps are cache ops (``report_failure``) to its end.""" + outcome: object = None # rebind-ok: the answer to the last step + while True: + step = call.next(outcome) + match step["kind"]: + case "cache": + outcome = self._answer_cache_sync(step) + case "done": + return step + case "failed": + raise RuntimeError(f"router-core ({step.get('error_kind')}): {step.get('error')}") + case other: # pyright: ignore[reportUnnecessaryComparison] # a kind the bridge returns but the stub does not list + raise RuntimeError(f"router-core asked for {other!r} while recording an outcome") + + async def _drive_cache_steps( + self, call: "RouterCall[_FailureReportSteps | _SuccessReportSteps]" + ) -> Mapping[str, object]: + """``_drive_sync_steps`` answered through the async cache (``report_success``).""" + outcome: object = None # rebind-ok: the answer to the last step + while True: + step = call.next(outcome) + match step["kind"]: + case "cache": + outcome = await self._answer_cache(step) + case "done": + return step + case "failed": + raise RuntimeError(f"router-core ({step.get('error_kind')}): {step.get('error')}") + case other: # pyright: ignore[reportUnnecessaryComparison] # a kind the bridge returns but the stub does not list + raise RuntimeError(f"router-core asked for {other!r} while recording an outcome") + + # -- pre-route steps ------------------------------------------------------------------------- + + async def _pre_route( + self, + step: Mapping[str, object], + request: Mapping[str, object], + messages: object = _NO_INPUT, + input: object = _NO_INPUT, + specific_deployment: object = _NO_INPUT, + *, + pass_through: bool = False, + ) -> object: + """The host's pre-routing of one pick (router_rust.steps.prerouting): the model group to resolve + instead of the step's ``model``, a custom strategy's deployment, or ``None``. ``pass_through`` + is ``_async_get_available_deployment_for_pass_through``, which runs the hook whatever the + router's strategy and which no replaced pick answers.""" + assigned: Final[object] = None if pass_through else self.__dict__.get("_core_async_get_available_deployment") + if callable(assigned): + # The async pick assigned through the deprecated attribute answers, as Python's + # replaced `_core_async_get_available_deployment` does. + answer: Final[object] = assigned( + model=str(step.get("model")), + request_kwargs=request, + messages=request.get("messages") if messages is _NO_INPUT else messages, + input=request.get("input") if input is _NO_INPUT else input, + specific_deployment=request.get("specific_deployment") + if specific_deployment is _NO_INPUT + else specific_deployment, + ) + chosen: Final[object] = await answer if inspect.isawaitable(answer) else answer + return _custom_pick(chosen) + custom: Final = None if pass_through else self._custom_strategy + if custom is not None: + picked: Final[object] = await custom.async_get_available_deployment( # pyright: ignore[reportUnknownMemberType] # the strategy's untyped pick + model=str(step.get("model")), + messages=request.get("messages") if messages is _NO_INPUT else messages, # pyright: ignore[reportArgumentType] # the request's messages, as given + input=request.get("input") if input is _NO_INPUT else input, # pyright: ignore[reportArgumentType] # the request's input, as given + specific_deployment=request.get("specific_deployment") + if specific_deployment is _NO_INPUT + else specific_deployment, # pyright: ignore[reportArgumentType] # same + request_kwargs=request, # pyright: ignore[reportArgumentType] # the request kwargs, as given + ) + return _custom_pick(picked) + if not isinstance(request, dict): + return None + depth: Final = step.get("fallback_depth") + r: Final = self._resolved + owner: Final[object] = self.__dict__.get("_core_owner") + public: Final[object] = owner() if callable(owner) else None + return await self._prerouter.pre_route( + str(step.get("model")), + request, # pyright: ignore[reportUnknownArgumentType] # the request kwargs the hook stamps + messages=request.get("messages") if messages is _NO_INPUT else messages, + input=request.get("input") if input is _NO_INPUT else input, + fallback_depth=depth if isinstance(depth, int) else 0, + router_strategy=normalize_strategy(r.routing_strategy), + pass_through=pass_through, + enable_tag_filtering=r.enable_tag_filtering, + match_any=r.tag_filtering_match_any, + public_router=public if public is not None else self, + run_plugins=partial( + self._run_plugins, request, request.get("messages") if messages is _NO_INPUT else messages + ) # pyright: ignore[reportUnknownArgumentType] # the request kwargs the plugins stamp + if self._hosted._core_routing_plugins # pyright: ignore[reportPrivateUsage] # the live plugin list + else None, + ) + + async def _run_plugins( + self, + request: dict[str, object], # mutable-ok: the plugins stamp their outcome on the caller's request + messages: object, + model: str, + ) -> None: + """``_run_routing_plugins`` over the pre-routing hook's session-resolved ``model``.""" + await run_plugins( + tuple(self._hosted._core_routing_plugins), # pyright: ignore[reportPrivateUsage] # the live plugin list + self._hosted, # pyright: ignore[reportArgumentType] # the host registry serves the listing + self._resolved.model_group_alias, + model, + request, + messages, + ) + + def _custom_pick_sync( + self, + step: Mapping[str, object], + request: Mapping[str, object], + messages: object = _NO_INPUT, + input: object = _NO_INPUT, + specific_deployment: object = _NO_INPUT, + ) -> object: + """A custom strategy's sync pick (``get_available_deployment``); without one, no pre-routing.""" + custom: Final = self._custom_strategy + if custom is None: + return None + picked: Final[object] = custom.get_available_deployment( # pyright: ignore[reportUnknownMemberType] # the strategy's untyped pick + model=str(step.get("model")), + messages=request.get("messages") if messages is _NO_INPUT else messages, # pyright: ignore[reportArgumentType] # see _pre_route + input=request.get("input") if input is _NO_INPUT else input, # pyright: ignore[reportArgumentType] # same + specific_deployment=request.get("specific_deployment") + if specific_deployment is _NO_INPUT + else specific_deployment, # pyright: ignore[reportArgumentType] # same + request_kwargs=request, # pyright: ignore[reportArgumentType] # same + ) + return _custom_pick(picked) + + # -- select steps ---------------------------------------------------------------------------- + + def _strategy_inputs(self, step: Mapping[str, object], request: Mapping[str, object]) -> "_StrategyInputs | None": + """The strategy, its selector, the name it keys state by and the candidate deployments of a + ``strategy`` select step; ``None`` for a stage the host passes through.""" + if step.get("stage") != "strategy": + return None + strategy: Final = str(step.get("strategy")) + group: Final = step.get("group") + selector: Final = self._selectors.selector_for( + strategy, str(step.get("scope")), str(group) if group is not None else None, request + ) + candidates: Final = [ + dict(as_str_mapping(self._handle.deployment(str(id))) or {}) for id in _as_list(step.get("candidates")) + ] + return strategy, selector, str(step.get("model")), candidates + + def _records_of(self, ids: object) -> list[dict[str, object]]: # mutable-ok: the deployment dicts filters take + return [dict(as_str_mapping(self._handle.deployment(str(id))) or {}) for id in _as_list(ids)] + + async def _answer_tags(self, step: Mapping[str, object], request: Mapping[str, object]) -> object: + """``get_deployments_for_tag`` over the step's candidates (bridged: not ported to Rust yet).""" + from litellm.litellm_core_utils.core_helpers import get_metadata_variable_name_from_kwargs + from litellm.router_strategy.tag_based_routing import get_deployments_for_tag + + kept: Final = await get_deployments_for_tag( + ctx=RoutingContext(self), # pyright: ignore[reportArgumentType] # the filter reads registry() and settings() + model=str(step.get("model")), + healthy_deployments=self._records_of(step.get("candidates")), # pyright: ignore[reportArgumentType] # deployment dicts + request_kwargs=dict(request), # pyright: ignore[reportArgumentType] # the request kwargs + metadata_variable_name=get_metadata_variable_name_from_kwargs(dict(request)), + request_deployments=self._records_of(step.get("pool")), # pyright: ignore[reportArgumentType] # deployment dicts + ) + return [found for record in kept if (found := picked_id(record)) is not None] + + def _pre_call_facts( + self, step: Mapping[str, object], request: Mapping[str, object], messages: object, input: object + ) -> PreCallFacts: + hosted: Final = self._hosted + + def record(id: str) -> Mapping[str, object]: + return hosted._core_get_model_info(id) or as_str_mapping(self._handle.deployment(id)) or {} # pyright: ignore[reportPrivateUsage] # see __init__ + + return PreCallFacts(self._host, hosted, step, record, request, messages, input) # pyright: ignore[reportArgumentType] # the host registry serves the reads + + def _text_only(self, step: Mapping[str, object]) -> list[str]: # mutable-ok: the step's answer + """The candidates that declare no vision support (bridged: needs the cost map).""" + group: Final = str(step.get("model_group")) + return [ + str(id) + for id in _as_list(step.get("candidates")) + if declares_no_vision(as_str_mapping(self._handle.deployment(str(id))) or {}, group) + ] + + def _route_incapable(self, step: Mapping[str, object]) -> list[str]: # mutable-ok: the step's answer + """The candidates whose provider cannot serve the call the step's handler names.""" + group: Final = str(step.get("model_group")) + handler: Final = str(step.get("handler")) + return [ + str(id) + for id in _as_list(step.get("candidates")) + if cannot_serve_route(as_str_mapping(self._handle.deployment(str(id))) or {}, group, handler) + ] + + def _media_refusing( + self, step: Mapping[str, object], request: Mapping[str, object] + ) -> list[str]: # mutable-ok: the step's answer + """The candidates that refuse the audio or videos a Decisions call carries.""" + group: Final = str(step.get("model_group")) + defaults: Final = {k: v for k, v in self._resolved.default_litellm_params.items() if v is not None} + sent: Final = {**defaults, **request} + audio: Final = bool(request.get("audio")) + videos: Final = bool(request.get("videos")) + return [ + str(id) + for id in _as_list(step.get("candidates")) + if refuses_decisions_media( + as_str_mapping(self._handle.deployment(str(id))) or {}, group, sent, audio=audio, videos=videos + ) + ] + + async def _answer_select( + self, + step: Mapping[str, object], + request: Mapping[str, object], + messages: object, + input: object, + *, + pass_through: bool = False, + ) -> object: + if step.get("stage") == "pre_call": + return await self._pre_call_facts(step, request, messages, input).answer_async() + if step.get("stage") == "routing_plugins": + # The plugins already ran in this pick's pre_route step (see `_pre_route`), on the + # session-resolved name and before a strategy was selected, as Python's hook runs them. + return candidate_models(request) + if step.get("stage") == "tags": + return await self._answer_tags(step, request) + if step.get("stage") == "text_only": + return self._text_only(step) + if step.get("stage") == "route_incapable": + return self._route_incapable(step) + if step.get("stage") == "media_refusing": + return self._media_refusing(step, request) + if step.get("stage") == "provider_request": + return _provider_request(step) + inputs: Final = self._strategy_inputs(step, request) + if inputs is None: + return step["candidates"] + strategy, selector, model, candidates = inputs + pinned: Final = bool(request.get("_encrypted_content_affinity_pinned")) and len(candidates) == 1 + if selector is None and not pinned: + return [] + # The strategy's service event: `_async_get_available_deployment` times it for the strategies + # with an async pick, `_async_get_available_deployment_for_pass_through` for any, on another clock. + timed: Final = not pinned and strategy != "simple-shuffle" and (pass_through or self._picks_async()) + clock: Final = perf_counter if pass_through else unix_time + start_time: Final = clock() + # `_async_get_available_deployment`: a pin by encrypted content takes no strategy's pick. + picked: Final = ( + candidates[0] + if pinned + else await pick_async( + strategy, + selector, # pyright: ignore[reportArgumentType] # a selector from selector_for + model, + candidates, + messages, + input, + dict(request), + # `_async_get_available_deployment` reserves a request's pick unless told not to; + # the pass-through pick only when told to. + reserve=pick_reserves(default=not pass_through) and bool(request), + ) + ) + if picked is not None and selector is not None and self._selectors.is_override(strategy, selector): + await selector.async_pre_call_check(dict(as_str_mapping(picked) or {}), None) # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType] # every selector is a CustomLogger + if picked is not None and timed: + self.service_logged(".async_get_available_deployments", start_time, clock(), request) + found: Final = picked_id(picked) + return [found] if found is not None else [] + + def _answer_select_sync( + self, step: Mapping[str, object], request: Mapping[str, object], messages: object, input: object + ) -> object: + if step.get("stage") == "pre_call": + return self._pre_call_facts(step, request, messages, input).answer() + if step.get("stage") == "routing_plugins": + return candidate_models(request) + if step.get("stage") == "callback_filters": + # Only the async candidate lists run the callback filters. + return step["candidates"] + if step.get("stage") == "text_only": + return self._text_only(step) + if step.get("stage") == "route_incapable": + return self._route_incapable(step) + if step.get("stage") == "media_refusing": + return self._media_refusing(step, request) + if step.get("stage") == "provider_request": + return _provider_request(step) + inputs: Final = self._strategy_inputs(step, request) + if inputs is None: + return step["candidates"] + strategy, selector, model, candidates = inputs + if selector is None: + return [] + picked: Final = pick_sync( + strategy, + selector, # pyright: ignore[reportArgumentType] # a selector from selector_for + model, + candidates, + messages, + input, + dict(request), + # The sync picks reserve only when a routed call site says so (`picks_reserve(True)`). + reserve=pick_reserves(default=False) and bool(request), + ) + if picked is not None and self._selectors.is_override(strategy, selector): + selector.pre_call_check(dict(as_str_mapping(picked) or {})) # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType] # see above + found: Final = picked_id(picked) + return [found] if found is not None else [] + + # -- cache steps ----------------------------------------------------------------------------- + + def _store_for(self, key: str) -> "DualCache": + """Cooldowns live in the cooldown store; every other routing key in the routing cache.""" + return self._cooldowns.cooldown_store if key.endswith(":cooldown") else self._cache + + async def _batch_read(self, keys: list[str]) -> Sequence[object]: # mutable-ok: the cache's key list + """One batch read, as the Python core makes it: the keys memory cannot serve, at most once per + read interval. Cooldowns are ``async_get_cooldown_deployments``' read, through the request's + armed prefetch when there is one.""" + if not keys or not keys[0].endswith(":cooldown"): + read: Final[object] = await self._cache.async_batch_get_cache(keys=keys) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # DualCache's reads are untyped + return read if isinstance(read, list) else [None] * len(keys) # pyright: ignore[reportUnknownVariableType] # see above + store: Final = self._cooldowns.cooldown_store + with service_target(ROUTER_COOLDOWNS_TARGET): + prefetched: Final = await RoutingReadBatch._read_prefetched(((store, keys),)) # pyright: ignore[reportPrivateUsage] # the batch's own prefetch read + results: Final[object] = ( + prefetched[0] if prefetched is not None else await store.async_batch_get_cache(keys=keys) # pyright: ignore[reportUnknownMemberType] # see above + ) + return self._corrected_cooldowns(keys, results) + + def _batch_read_sync(self, keys: list[str]) -> Sequence[object]: # mutable-ok: the cache's key list + """``_batch_read`` for a sync pick: ``get_active_cooldowns``' read.""" + if not keys or not keys[0].endswith(":cooldown"): + read: Final[object] = self._cache.batch_get_cache(keys=keys) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # DualCache's reads are untyped + return read if isinstance(read, list) else [None] * len(keys) # pyright: ignore[reportUnknownVariableType] # see above + with service_target(ROUTER_COOLDOWNS_TARGET): + results: Final = as_object_list(self._cooldowns.cooldown_store.batch_get_cache(keys=keys)) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # see above + return self._corrected_cooldowns(keys, results) + + def _corrected_cooldowns(self, keys: Sequence[str], results: object) -> Sequence[object]: + """The cooldowns a batch read found, once ``active_cooldowns_from_results`` corrected the in-memory + TTL of each it promoted from Redis and dropped each that expired.""" + if not isinstance(results, list): + return [None] * len(keys) + ids: Final = [key.removeprefix("deployment:").removesuffix(":cooldown") for key in keys] + _ = self._cooldowns.active_cooldowns_from_results(ids, results) # pyright: ignore[reportUnknownArgumentType] # see above + return results # pyright: ignore[reportUnknownVariableType] # see above + + async def _increment_usage(self, keys: Sequence[object], amounts: Sequence[object], ttl: float | None) -> None: + """``_increment_deployment_usage``'s write: one pipeline, then this worker's memory holds what + Redis answered, so its usage reads see what the other workers counted.""" + from litellm.types.caching import RedisPipelineIncrementOperation + + operations: Final = [ + RedisPipelineIncrementOperation( + key=str(key), increment_value=_amount(amount), ttl=None if ttl is None else int(ttl) + ) + for key, amount in zip(keys, amounts) + ] + values: Final = await self._cache.async_increment_cache_pipeline(increment_list=operations) + if values is None or self._cache.redis_cache is None: + return + for operation, value in zip(operations, values): + await self._cache.async_set_cache(operation["key"], int(value), local_only=True, ttl=operation["ttl"]) # pyright: ignore[reportUnknownMemberType] # DualCache's writes are untyped + + async def _answer_cache(self, step: Mapping[str, object]) -> object: + with service_target(_cache_target(str(step.get("key")))): + return await self._answer_cache_in_target(step) + + async def _answer_cache_in_target(self, step: Mapping[str, object]) -> object: + key: Final = str(step.get("key")) + ttl: Final = _ttl(step) + local: Final = step.get("local") is True + match step.get("op"): + case "get": + return _plain(await self._store_for(key).async_get_cache(key, local_only=local)) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # DualCache's reads are untyped + case "batch_get": + return _plain(await self._batch_read([str(k) for k in _as_list(step.get("keys"))])) + case "set": + store: Final = self._store_for(key) + if ttl is None: + await store.async_set_cache(key, step.get("value")) # pyright: ignore[reportUnknownMemberType] # DualCache's writes are untyped + else: + await store.async_set_cache(key, step.get("value"), ttl=ttl) # pyright: ignore[reportUnknownMemberType] # see above + return None + case "increment": + by: Final = _amount(step.get("value")) + counter: Final = self._store_for(key) + total: Final = ( + await counter.async_increment_cache(key, by, local_only=local) # pyright: ignore[reportUnknownMemberType] # see above + if ttl is None + else await counter.async_increment_cache(key, by, local_only=local, ttl=ttl) # pyright: ignore[reportUnknownMemberType] # see above + ) + return by if total is None else total + case "increment_usage": + await self._increment_usage(_as_list(step.get("keys")), _as_list(step.get("value")), ttl) + return None + case "delete": + await self._store_for(key).async_delete_cache(key) + return None + case other: + raise RuntimeError(f"router-core asked for an unknown cache op {other!r}") + + def run_routing_cache_sync(self, read_or_write: "Callable[[], Coroutine[object, object, object]]") -> object: + """A routing-cache coroutine on a sync call, whose `make_call` runs on the one event loop + `run_async_function` opened for the whole call. Without Redis the coroutine never suspends, so + it runs here: a loop of its own would hand the GIL to the logging thread, which then reads the + response before the router's headers are on it.""" + if self._cache.redis_cache is not None: + from litellm.litellm_core_utils import asyncify + + return asyncify.run_async_function(read_or_write) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the untyped sync bridge + running: Final = read_or_write() + try: + while True: + _ = running.send(None) + except StopIteration as finished: + return finished.value # pyright: ignore[reportAny] # the coroutine's result + + def _answer_cache_sync(self, step: Mapping[str, object]) -> object: + with service_target(_cache_target(str(step.get("key")))): + return self._answer_cache_sync_in_target(step) + + def _answer_cache_sync_in_target(self, step: Mapping[str, object]) -> object: + key: Final = str(step.get("key")) + ttl: Final = _ttl(step) + local: Final = step.get("local") is True + match step.get("op"): + case "get": + return _plain(self._store_for(key).get_cache(key, local_only=local)) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # DualCache's reads are untyped + case "batch_get": + return _plain(self._batch_read_sync([str(k) for k in _as_list(step.get("keys"))])) + case "set": + store: Final = self._store_for(key) + if ttl is None: + store.set_cache(key, step.get("value")) # pyright: ignore[reportUnknownMemberType] # DualCache's writes are untyped + else: + store.set_cache(key, step.get("value"), ttl=ttl) # pyright: ignore[reportUnknownMemberType] # see above + return None + case "increment": + by: Final = _amount(step.get("value")) + counter: Final = self._store_for(key) + # DualCache.increment_cache is annotated int but adds floats as given. + return ( + counter.increment_cache(key, by, local_only=local) # pyright: ignore[reportUnknownMemberType, reportArgumentType] # see above + if ttl is None + else counter.increment_cache(key, by, local_only=local, ttl=ttl) # pyright: ignore[reportUnknownMemberType, reportArgumentType] # see above + ) + case "increment_usage": + keys: Final = _as_list(step.get("keys")) + amounts: Final = _as_list(step.get("value")) + self.run_routing_cache_sync(lambda: self._increment_usage(keys, amounts, ttl)) + return None + case "delete": + self._store_for(key).delete_cache(key) # pyright: ignore[reportUnknownMemberType] # DualCache's delete is untyped + return None + case other: + raise RuntimeError(f"router-core asked for an unknown cache op {other!r}") + + # -- errors the core raises when no attempt failed ------------------------------------------ + + def _failure_error( # noqa: C901 # one branch per failure Python tells apart + self, + step: Mapping[str, object], + model: str, + last: BaseException | None, + *, + pass_through: str = "", + request: Mapping[str, object] | None = None, + ) -> BaseException: + """The error a call or pick that failed before any attempt raises; ``pass_through`` names + the selection kind (``pass_through``/``async_pass_through``) whose errors it words.""" + import litellm.exceptions as litellm_exceptions + + kind: Final = step.get("error_kind") + aliases: Final = self._resolved.model_group_alias + refused: Final = selection_refusal(step, model, request or {}) + if refused is not None: + return refused + if kind == "paused": + # The message names the deployment's litellm model, not the id that was asked for; the + # default deployment's copy is named by the requested name. + record: Final = as_str_mapping(self._handle.deployment(model)) + litellm_model: Final = ( + str((as_str_mapping(record.get("litellm_params")) or {}).get("model")) if record is not None else model + ) + return litellm_exceptions.ServiceUnavailableError( + message=f"Model '{litellm_model}' is currently paused and cannot accept requests.", + model=litellm_model, + llm_provider="", + ) + if kind == "only_markers": + named_model: Final = str(step.get("error_model") or model) + return litellm_exceptions.BadRequestError( + message=f"You passed in model={named_model}. {RouterErrors.only_strategy_marker_deployments.value}", + model=named_model, + llm_provider="", + ) + if kind == "endpoint_not_supported": + return litellm_exceptions.EndpointNotSupportedByModelError( + message=str(step.get("error_detail")), + model=str(step.get("error_model") or model), + llm_provider="", + ) + if kind == "ptu_reserved": + reserved: Final = str(step.get("error_model") or model) + return litellm_exceptions.BadRequestError( + message=f"Deployment {reserved} is reserved for the teams holding a PTU share of it", + model=reserved, + llm_provider="", + ) + if kind == "not_pass_through": + # The sync pick names what `_common_checks_available_deployment` resolved the id to. + named_record: Final = ( + as_str_mapping(self._handle.deployment(model)) if pass_through == "pass_through" else None + ) + error_model: Final = ( + str((as_str_mapping(named_record.get("litellm_params")) or {}).get("model")) + if named_record is not None + else model + ) + return litellm_exceptions.BadRequestError( + message=f"Deployment {model} does not support pass-through endpoint (use_in_pass_through=False)", + model=error_model, + llm_provider="", + ) + if kind == "no_pass_through_deployments": + # The sync pick names what `_common_checks_available_deployment` resolved the name to. + named_group: Final = str(step.get("error_model") or model) + listed_model: Final = ( + named_group if pass_through == "async_pass_through" else self._process_renamed(model, named_group) + ) + message: Final = ( + f"Model {listed_model} has no deployments configured with use_in_pass_through=True. " + "Please add use_in_pass_through: true to the deployment configuration" + if pass_through == "async_pass_through" + else f"Model {listed_model} has no deployment configured with use_in_pass_through=True. " + "Please add use_in_pass_through: true in the deployment configuration" + ) + return litellm_exceptions.BadRequestError(message=message, model=listed_model, llm_provider="") + if kind == "context_window_exceeded": + return litellm_exceptions.ContextWindowExceededError( + message="litellm._pre_call_checks: Context Window exceeded for given call. No models have context " + f"window large enough for this call.\n{step.get('error_detail')}", + model=str(step.get("error_model") or model), + llm_provider="", + ) + if kind == "unsupported_params": + params: Final = sorted(str(param) for param in _as_list(step.get("error_params"))) + unsupported_model: Final = str(step.get("error_model") or model) + return litellm_exceptions.UnsupportedParamsError( + message=( + f"no deployment of model={unsupported_model} supports {params}. " + "To drop these, set `litellm.drop_params=True` or for proxy `litellm_settings: drop_params: true`, " + f"or send allowed_openai_params={params} to pass them through" + ), + model=unsupported_model, + ) + if kind == "routing_plugins_left_nothing": + left: Final = [str(name) for name in _as_list(step.get("error_params"))] + return ValueError(f"No deployments left after routing-plugin filtering. candidate_models={left}") + if kind == "routing_plugins_need_async": + return ValueError(SYNC_PATH_MESSAGE) + looked_up: Final = _lookup_error(kind, str(step.get("error_model") or model), self._resolved.default_deployment) + if looked_up is not None: + return looked_up + if kind == "unknown_model": + # router-core names what `_common_checks_available_deployment` looked for last. + aliased: Final = _alias_target(aliases.get(model)) or model if model in aliases else model + named: Final = str(step.get("error_model") or aliased) + return litellm_exceptions.BadRequestError( + message=f"You passed in model={named}. {RouterErrors.no_healthy_deployments.value}", + model=named, + llm_provider="", + ) + if kind == "no_healthy_deployments": + group: Final = self.registry().resolve(model) + group_ids: Final = self.registry().names(str(group), kind="ids") + # A listed pass-through pick names only the pass-through deployments. + ids: Final = ( + [id for id in group_ids if _uses_pass_through(self._handle.deployment(id))] + if pass_through == "pass_through" + else list(group_ids) + ) + active: Final = self._cooldowns.get_active_cooldowns(list(ids), None) # pyright: ignore[reportArgumentType] # a list of ids + # `async_get_cooldown_deployments_with_debug_info`: every deployment cooling, in any group. + listed: Final = self._cooldowns.get_active_cooldowns(list(self.registry().names(kind="ids")), None) # pyright: ignore[reportArgumentType] # a list of ids + cooling: Final = [id for id, _ in listed] + min_cooldown: Final = min( + (_seconds(entry.get("cooldown_time"), self._cooldowns.default_cooldown_time) for _, entry in active), + default=_seconds(None, self._cooldowns.default_cooldown_time), + ) + return RouterRateLimitError( + model=self._process_renamed(model, str(group)), + cooldown_time=min_cooldown, + enable_pre_call_checks=self._resolved.enable_pre_call_checks, + cooldown_list=cooling, + model_ids=list(ids), # pyright: ignore[reportArgumentType] # a list of ids + cooldown_deployments=get_cooldown_deployment_info( + RoutingContext(self), # pyright: ignore[reportArgumentType] # reads registry() + ids, + cooling, + ), + ) + if last is not None: + return last + return RuntimeError(f"router-core ({kind}): {step.get('error')}") + + +def wildcard_request(model: str) -> str: + """``f"{provider}/{model}"``, the spelling ``PatternMatchRouter.get_pattern`` tries second.""" + from litellm.litellm_core_utils.get_llm_provider_logic import inferred_provider + + return f"{inferred_provider(model)}/{model}" + + +def _provider_request(step: Mapping[str, object]) -> Mapping[str, object]: + return {"models": [wildcard_request(str(step.get("model")))]} + + +def _lookup_error(kind: object, model: str, default_deployment: object) -> BaseException | None: + """The plain Python error a pick's lookup raised for ``model``, or None for any other failure.""" + if kind == "default_deployment_raises": + return default_deployment_copy_error(default_deployment, model) + if kind == "index_out_of_range": + # `self._core_model_list[index]` for a written index position past the list. + return IndexError("list index out of range") + if kind == "missing_routing_group": + # `_get_routing_context` reads the stale member map's group from the replaced groups. + return KeyError(model) + return None + + +def _origin_level(origin: Mapping[str, object]) -> int: + level: Final = origin.get("level") + return level if isinstance(level, int) else 0 + + +def _sleep_seconds(step: Mapping[str, object]) -> float: + """A retry's sleep: ``_time_to_sleep_before_retry`` returns a plain ``0`` when another + deployment is healthy, else a backoff in float seconds.""" + seconds: Final = float(str(step["seconds"])) + return 0 if seconds == 0 else seconds + + +def _uses_pass_through(record: object) -> bool: + params: Final = as_str_mapping((as_str_mapping(record) or {}).get("litellm_params")) or {} + return bool(params.get("use_in_pass_through")) + + +def _seconds(value: object, default: float) -> float | int: + """A cooldown time as stored: an int stays an int, so error texts read ``60`` like Python's.""" + if isinstance(value, int | float) and not isinstance(value, bool): + return value + return int(default) if float(default).is_integer() else default + + +def _ttl(step: Mapping[str, object]) -> float | None: + ttl: Final = step.get("ttl") + return ttl if isinstance(ttl, int | float) else None + + +def _amount(value: object) -> float | int: + return value if isinstance(value, int | float) and not isinstance(value, bool) else 1 + + +# The plans whose kwargs carry `original_generic_function`, which the fallback cooldown reads. +_GENERIC_API_KINDS: Final = frozenset(("generic", "search")) + + +class _NotSynchronous(TypeError): + """A sync attempt's host endpoint returned an awaitable: a host bug, never an attempt failure.""" + + +_MEMBER_READ_PICKS: Final = frozenset({"healthy", "pass_through", "sync_pick"}) + + +class _Selection: + """One ``select``: the Rust selection call, its select and cache steps answered on the host.""" + + def __init__( + self, + core: RustCore, + model: object, + request: dict[str, object], # mutable-ok: the caller's request, whose narrowing keys are popped + kind: str, + specific_deployment: bool | None, + messages: object, + input: object, + *, + probe: bool = False, + ) -> None: + self._core: Final = core + # `_async_get_available_deployment` reads the alias map first, every other pick its names. + self._model: Final = ( + model if isinstance(model, str) else core.routed_name(model, read_as_member=kind in _MEMBER_READ_PICKS) + ) + self._request: Final = request + self._kind: Final = kind + self._messages: Final = messages + self._input: Final = input + fields: Final = { + **core._routing_fields(request, messages), # pyright: ignore[reportPrivateUsage] # the selection serves its own core + **_narrowing_fields(request, kind), + } # pyright: ignore[reportPrivateUsage] # the selection serves its own core + # The pick's argument alone: a `specific_deployment` key in its request is no argument, and + # `_common_checks_available_deployment` reads nothing but True. + fields.pop("specific_deployment", None) + if specific_deployment is True: + fields["specific_deployment"] = True + # `filter_web_search_deployments` is in the async chain, which a strategy without an async + # selector never reaches on a pick. + if (kind in ("healthy", "async_pass_through") or (kind == "pick" and core._picks_async())) and ( # pyright: ignore[reportPrivateUsage] # the selection serves its own core + is_web_search_request(request) + ): + fields["web_search"] = True + # `_text_completion` wraps its sync pick in `endpoint_selection`. + endpoint: Final = selected_endpoint() + if endpoint is not None: + fields["endpoint"] = endpoint + if probe: + fields["health_check_probe"] = True + if kind in ("pick", "async_pass_through") or (kind == "sync_pick" and core._custom_strategy is not None): # pyright: ignore[reportPrivateUsage] # the selection serves its own core + fields["pre_routes"] = True + self._specific_deployment: Final = specific_deployment + # The error a callback filter raised, which a failed selection raises. + self._filter_error: BaseException | None = None + if kind == "pass_through": + fields["pass_through"] = "listed" + elif kind == "async_pass_through": + fields["pass_through"] = "healthy" + core._sync_routing_state() # pyright: ignore[reportPrivateUsage] # see above + handle: Final = core._handle # pyright: ignore[reportPrivateUsage] # see above + self._call: Final = (handle.healthy if kind == "healthy" else handle.select)(self._model, _document(fields)) + + def _done(self, step: Mapping[str, object]) -> Mapping[str, object] | Sequence[Mapping[str, object]]: + if self._kind == "healthy": + if step.get("single"): + # A deployment named by its id is listed alone, as a dict. + (record,) = _as_list(step.get("deployments")) + return for_requested_model(typed_deployment(as_str_mapping(record) or {}), self._model) + # The deployments as served: a priority group's members carry their priority as order. + return [ + for_requested_model(typed_deployment(as_str_mapping(record) or {}), self._model) + for record in _as_list(step.get("deployments")) + ] + if step.get("deployment_id") in (DEFAULT_DEPLOYMENT_FAILING_ID, DEFAULT_DEPLOYMENT_COPIED_ID): + # A default deployment every call to fails, or whose id is not a string, is picked as Python copies it. + picked: Final = default_deployment_copy(self._core._resolved.default_deployment, self._model) # pyright: ignore[reportPrivateUsage] # the selection serves its own core + return picked # pyright: ignore[reportReturnType] # the assigned value's copy, as the Python core returns it + return for_requested_model(typed_deployment(as_str_mapping(step.get("deployment")) or {}), self._model) + + def _failed(self, step: Mapping[str, object]) -> BaseException: + core: Final = self._core + error: Final = core._failure_error( # pyright: ignore[reportPrivateUsage] # see above + step, self._model, self._filter_error, pass_through=self._kind, request=self._request + ) + if self._kind not in ("pass_through", "sync_pick"): + _log_refused_pick(self._request, error) + return error + + async def run(self) -> Mapping[str, object] | Sequence[Mapping[str, object]]: + core: Final = self._core + outcome: object = None # rebind-ok: the answer to the last step + while True: + step = self._call.next(outcome) + match step["kind"]: + case "cache": + outcome = await core._answer_cache(step) # pyright: ignore[reportPrivateUsage] # see above + case "select" if step.get("stage") == "callback_filters": + outcome, self._filter_error = await core._answer_callback_filters( # pyright: ignore[reportPrivateUsage] # see above + step, self._request, self._messages + ) + case "select": + outcome = await core._answer_select( # pyright: ignore[reportPrivateUsage] # see above + step, + self._request, + self._messages, + self._input, + pass_through=self._kind == "async_pass_through", + ) + case "pre_route": + outcome = await core._pre_route( # pyright: ignore[reportPrivateUsage] # see above + step, + self._request, + self._messages, + self._input, + self._specific_deployment, + pass_through=self._kind == "async_pass_through", + ) + case "done": + done = self._done(step) + if self._kind != "pick" or not isinstance(done, Mapping): + return done + # `_core_async_get_available_deployment` resolves its pick to a pod. + return await self._resolved_pod(core, done) + case "failed": + raise self._failed(step) + case other: # pyright: ignore[reportUnnecessaryComparison] # a kind the bridge returns but the stub does not list + raise RuntimeError(f"router-core returned an unknown step {other!r}") + + async def _resolved_pod(self, core: "RustCore", done: Mapping[str, object]) -> Mapping[str, object]: + discovery: Final = core._pick_discovery(sync=False) # pyright: ignore[reportPrivateUsage] # the selection serves its own core + if discovery is None: + return done + resolved: Final[object] = await discovery.async_resolve_deployment(done, self._request) + return resolved # pyright: ignore[reportReturnType] # the deployment, resolved + + def _resolved_pod_sync(self, core: "RustCore", done: Mapping[str, object]) -> Mapping[str, object]: + discovery: Final = core._pick_discovery(sync=True) # pyright: ignore[reportPrivateUsage] # see _resolved_pod + return done if discovery is None else discovery.resolve_deployment(done, self._request) + + def run_sync(self) -> Mapping[str, object] | Sequence[Mapping[str, object]]: + core: Final = self._core + outcome: object = None # rebind-ok: the answer to the last step + while True: + step = self._call.next(outcome) + match step["kind"]: + case "cache": + outcome = core._answer_cache_sync(step) # pyright: ignore[reportPrivateUsage] # see above + case "select": + outcome = core._answer_select_sync(step, self._request, self._messages, self._input) # pyright: ignore[reportPrivateUsage] # see above + case "pre_route": + outcome = core._custom_pick_sync( # pyright: ignore[reportPrivateUsage] # see above + step, self._request, self._messages, self._input, self._specific_deployment + ) + case "done": + done = self._done(step) + if self._kind != "sync_pick" or not isinstance(done, Mapping): + return done + # `get_available_deployment` resolves its pick to a pod. + return self._resolved_pod_sync(core, done) + case "failed": + raise self._failed(step) + case other: # pyright: ignore[reportUnnecessaryComparison] # a kind the bridge returns but the stub does not list + raise RuntimeError(f"router-core returned an unknown step {other!r}") + + +def _log_refused_pick(request: Mapping[str, object], error: BaseException) -> None: + """A refused pick is logged to the request's logging object (`_async_get_available_deployment`).""" + dispatch: Final[object] = getattr(request.get("litellm_logging_obj"), "dispatch_failure_handlers", None) + if not callable(dispatch): + return + import asyncio + import traceback + + trace: Final = "Traceback (most recent call last):\n" + "".join( + traceback.format_exception(type(error), error, error.__traceback__) + ) + pending: Final[object] = dispatch(exception=error, traceback_exception=trace, prefer_async_handlers=True) + if inspect.isawaitable(pending): + _ = asyncio.ensure_future(pending) + + +def _log_refused_image_pick(request: Mapping[str, object], error: BaseException) -> None: + """``_aimage_generation``'s refused pick, for a request with no logging object of its own.""" + from litellm._uuid import uuid + from litellm.router_rust.invoke.endpoints import ROUTING_KEYS + from litellm.utils import ( + Rules, + _restore_correlation_context_if_supported, # pyright: ignore[reportPrivateUsage] # same task-local cleanup as the Python router + function_setup, + ) + + kwargs: Final = without(request, *(ROUTING_KEYS - {"model"})) + kwargs.setdefault("litellm_call_id", str(uuid.uuid4())) + logging_obj, _ = function_setup("aimage_generation", Rules(), datetime.now(), **kwargs) # noqa: DTZ005 # SDK logging uses naive local timestamps # pyright: ignore[reportArgumentType] # opaque SDK options, as the Python router passes them + try: + _log_refused_pick({"litellm_logging_obj": logging_obj}, error) + finally: + _restore_correlation_context_if_supported(logging_obj) + + +def _custom_pick(picked: object) -> Mapping[str, object]: + """A custom strategy's answer as the deployment document the Rust core serves.""" + document: Final = as_str_mapping(picked) + if document is None: + raise TypeError(f"the custom routing strategy returned {type(picked).__name__}, not a deployment") + return _document(document) + + +def _with_target_order(kwargs: Mapping[str, object], order: object) -> Mapping[str, object]: + """The attempt's kwargs with the order level its hop targets, as `run_async_fallback` sets + `_target_order` before `_acreate_file` picks every healthy deployment of that level.""" + if not isinstance(order, int) or isinstance(order, bool): + return kwargs + return {**kwargs, "_target_order": order} + + +def _narrowing_fields(request: dict[str, object], kind: str) -> Mapping[str, object]: # mutable-ok: popped + """``_target_order``, ``_excluded_deployment_ids`` and ``_retry_skipped_deployment_ids``, popped + from the request as the healthy chain pops them (a listed pass-through pick only reads the order).""" + fields: Final = _request_narrowing(request) + if kind == "pass_through": + return {key: value for key, value in fields.items() if key == "target_order"} + for key in ("_target_order", "_excluded_deployment_ids", "_retry_skipped_deployment_ids"): + request.pop(key, None) + return fields + + +def _request_narrowing(request: Mapping[str, object]) -> Mapping[str, object]: + """The narrowing keys a request carries, as the fields router-core reads them.""" + from litellm.litellm_core_utils.routing_common_utils import ( + as_excluded_deployment_ids, + as_retry_skipped_deployment_ids, + ) + + target_order: Final = request.get("_target_order") + excluded: Final = as_excluded_deployment_ids(request.get("_excluded_deployment_ids")) + skipped: Final = as_retry_skipped_deployment_ids(request.get("_retry_skipped_deployment_ids")) + return { + **( + {"target_order": target_order} + if isinstance(target_order, int) and not isinstance(target_order, bool) + else {} + ), + **({"excluded_ids": list(excluded)} if excluded else {}), + **({"retry_skipped_ids": list(skipped)} if skipped else {}), + } + + +_NO_ROUTING_PRE_CALL_CHECKS: Final = frozenset({"search", "rerank", "moderation"}) +# Attempts whose deployment is no pick (`_core_async_get_available_deployment` / +# `get_available_deployment`), so Kubernetes pod discovery never resolves it. +_UNPICKED_KINDS: Final = frozenset({"search", "create_file"}) + + +class _Driver: + """Answers the attempt and fallback steps of one call, and shapes its result. + + Each attempt is one host call against the deployment Rust picked. The driver keeps the error + each fallback level ended on: a level that fails raises its own error, whatever its fallbacks + raised, as the Python router does, unless an order chain handed it another + (``order_chain_failed``). + """ + + def __init__( + self, + core: RustCore, + plan: Plan, + request: Mapping[str, object], + cut_deployment: object = None, + stream_failure: tuple[int, BaseException] | None = None, + *, + sync: bool = False, + fresh: bool = False, + passthrough: "Callable[[Mapping[str, object], str], Awaitable[object]] | None" = None, + ) -> None: + self._core: Final = core + self._sync: Final = sync + self._passthrough: Final = passthrough + self._plan: Final = plan + self._op: Final = plan.endpoint + self._request: Final = request + self._cut_deployment: Final = cut_deployment if isinstance(cut_deployment, str) else None + self._last_response: object = None + self._last_error: BaseException | None = None + # The level the call raises from: a fallback walk re-entered from a failed stream starts at + # the level that stream served, on the failure ``async_function_with_fallbacks_common_utils`` + # was handed, which is what it raises when no fallback answers. + self._base_level: Final = stream_failure[0] if stream_failure is not None else 0 + self._level_errors: Final[dict[int, BaseException]] = dict( # mutable-ok: filled as the call runs + (stream_failure,) if stream_failure else () + ) + # The retry counts an exhausted retry loop stamps on the pick error its level then raises. + self._pending_stamps: Final[dict[int, tuple[object, object]]] = {} # mutable-ok: filled as the call runs + # Each level's current hop's first failure, once it retries: the error its retry loop raises + # last is raised while that one is handled, so it chains to it. + self._hop_first: Final[dict[int, BaseException]] = {} # mutable-ok: filled as the call runs + # Each level's latest pick error: the one object it logged, recorded and raises. + self._level_picks: Final[dict[int, BaseException]] = {} # mutable-ok: filled as the call runs + self._served: tuple[str | None, Mapping[str, object]] = (None, MappingProxyType({})) + # The latest attempt's deployment and call, which a blocked response is raised from. + self._latest_call: tuple[Mapping[str, object], AttemptCall] | None = None + # A sync attempt's stream is reading its first chunk, so a failure now is the stream's to log. + self._reading_first_chunk: bool = False + self._attempts: int = 0 + # When the latest attempt started: Python reads it off the logging object, when one is set up. + self._attempt_started: datetime | None = None + # A single-attempt endpoint runs neither of the wrappers that stamp the walk on the request. + self._walk: Final = WalkMetadata( + request, plan.metadata_field, self._params_base_model, live=fresh and not plan.single_attempt + ) + self.outcomes: Final = FallbackOutcomes(request) + # The fallback level the walk is at, from its fallback events. + self._level: int = self._base_level + # The primary level reached the end of `async_function_with_fallbacks_common_utils`, the + # only place the outcome message is appended: not its early raises, nor its order path. + self._explains_failure: bool = False + + def _blocked(self, response: object, endpoint_name: str) -> str | None: + """How the provider blocked a served response, the first check of + ``_should_raise_content_policy_error`` (a chat response with no choices, or whose first + choice was content-filtered) and of ``_should_raise_anthropic_refusal_error`` (a + /v1/messages safeguard refusal carrying ``stop_details``).""" + from litellm.llms.anthropic.messages.native.utils import get_safeguard_refusal_stop_details + from litellm.types.utils import ModelResponse + + if endpoint_name == "anthropic_messages" and get_safeguard_refusal_stop_details(response) is not None: + return "refusal" + if self._op not in ("acompletion", "completion") or not isinstance(response, ModelResponse): + return None + return ( + "content_filter" if not response.choices or response.choices[0].finish_reason == "content_filter" else None + ) + + def _blocked_error(self, event: Mapping[str, object]) -> BaseException: + """The error the router raises for a blocked response a fallback would serve.""" + import litellm.exceptions as litellm_exceptions + from litellm.llms.anthropic.messages.native.utils import ( + get_safeguard_refusal_stop_details, + safeguard_refusal_error, + ) + + model: Final = str(event.get("model")) + stop_details: Final = get_safeguard_refusal_stop_details(self._last_response) + if event.get("blocked") == "refusal" and stop_details is not None: + return safeguard_refusal_error(model=model, stop_details=stop_details) + return litellm_exceptions.ContentPolicyViolationError( + message="Response output was blocked.", model=model, llm_provider="" + ) + + def _stamp_blocked(self, error: BaseException) -> None: + """The attempt helper's ``except`` runs for the error it raises over a blocked response: the + response then counts as a failure, not a success.""" + if self._latest_call is None: + return + deployment, call = self._latest_call + endpoints: Final = self._core._endpoints # pyright: ignore[reportPrivateUsage] # the driver serves its own core + stamp_error(self._plan, error, deployment, call.served) + endpoints.counters.retract_success(self._plan, call) + endpoints.attempt_failed(self._plan, error, deployment, call, call.group) + + def _params_base_model(self, deployment_id: str) -> str | None: + """``_deployment_params_base_model``: the ``base_model`` under the deployment's ``litellm_params``.""" + record: Final = as_str_mapping(self._core._handle.deployment(deployment_id)) or {} # pyright: ignore[reportPrivateUsage] # the driver serves its own core + base_model: Final = (as_str_mapping(record.get("litellm_params")) or {}).get("base_model") + return base_model if isinstance(base_model, str) else None + + def _logged_error(self, event: Mapping[str, object]) -> BaseException | None: + """The error a ``retry_logged`` event records.""" + return self._cause_error(event) + + def _policy_raised(self, event: Mapping[str, object]) -> None: + """A hop's first failure looked its group's retry policy up and the lookup raised: the hop + ends with that error, raised from the failure the event names.""" + model: Final = str(event.get("model")) + original: Final = self._cause_error(event) or RuntimeError(f"router-core: the hop serving {model} failed") + policies: Final = self._request.get( + "model_group_retry_policy", + self._core._resolved.model_group_retry_policy, # pyright: ignore[reportPrivateUsage] # the driver serves its own core + ) + raised: Final = policy_lookup_error(original, model, self._core._written_retry_policy, policies) # pyright: ignore[reportPrivateUsage] # see above + level: Final = event.get("level") + self._last_error = raised + self._level_errors[level if isinstance(level, int) else 0] = raised + + def _stamped_budget(self, event: Mapping[str, object]) -> Mapping[str, object]: + """A ``retries_opened`` event as ``_metadata["max_retries"]`` reads it: a request + ``num_retries`` that is no count is stamped as given.""" + given: Final = self._request.get("num_retries") + return {**event, "max_retries": given} if "uncounted_retries" in request_retry_fields(given) else event + + def _count_raised(self, event: Mapping[str, object]) -> None: + """A hop's first failure reached the retry loop's read of a request ``num_retries`` that + raises: the hop ends with that error, raised from the failure the event names.""" + model: Final = str(event.get("model")) + original: Final = self._cause_error(event) or RuntimeError(f"router-core: the hop serving {model} failed") + raised: Final = retry_count_error(original, self._request.get("num_retries")) + level: Final = event.get("level") + self._last_error = raised + self._level_errors[level if isinstance(level, int) else 0] = raised + + def _cause_error(self, event: Mapping[str, object]) -> BaseException | None: + """The error the ``cause`` of a ``retry_logged`` or ``retry_policy_raised`` event names.""" + match event.get("cause"): + case "level": + level: Final = event.get("level") + return self._level_errors.get(level if isinstance(level, int) else 0, self._last_error) + case "pick": + at_level: Final = event.get("level") + held: Final = self._level_picks.get(at_level if isinstance(at_level, int) else 0) + return held if held is not None else self._picked_error(event) + case _: + return self._last_error + + def _picked_error(self, event: Mapping[str, object]) -> BaseException: + """The error a pick an event names raised, as a failed step with that error raises it.""" + model: Final = str(event.get("failed_model") or event.get("model")) + return self._core._failure_error(event, model, None, request=self._request) # pyright: ignore[reportPrivateUsage] # the driver serves its own core + + def _pick_raised(self, error: Exception, *, logged: bool) -> Mapping[str, object]: + """A pick raised on the host (a strategy, a tag filter, a pre-routing hook): the try fails with + that error, which the Rust walk retries and falls back from like any attempt's. ``logged`` + when the async pick's ``except`` reports it, as ``_async_get_available_deployment`` does.""" + if isinstance(error, RustCoreUnsupported): + raise error + if logged: + self._log_pick_failure(error) + else: + mark_deployment_selection_failure(error) + self._chain_to_hop_first(error, self._level) + self._last_error = error + self._level_errors[self._level] = error + return {**attempt_failure(error), "raised": True} + + def _log_pick_failure(self, error: BaseException) -> None: + """The ``except`` of ``_async_get_available_deployment``, which only the async selection runs: + the router's strategy may have no async selector, and a custom strategy replaces the method. + ``_aimage_generation`` logs a refused pick itself when the request set up no logging object.""" + core: Final = self._core + assigned: Final = "_core_async_get_available_deployment" in core.__dict__ + custom: Final = assigned or core._custom_strategy is not None # pyright: ignore[reportPrivateUsage] # the driver serves its own core + if not custom and core._picks_async(): # pyright: ignore[reportPrivateUsage] # see above + mark_deployment_selection_failure(error) + _log_refused_pick(self._request, error) + if self._plan.kind == "image" and self._request.get("litellm_logging_obj") is None: + _log_refused_image_pick(self._request, error) + + def _pick_failed(self, event: Mapping[str, object]) -> None: + """A pick failed in the Rust core: its error is raised once, however many events name it.""" + error: Final = self._picked_error(event) + level: Final = event.get("level") + self._level_picks[level if isinstance(level, int) else 0] = error + if not self._sync: + self._log_pick_failure(error) + + def _unroutable_error(self, model: object) -> BaseException: + """What a hop to a dict target's non-string ``model`` raises: no group answers ``None``, and + any other value fails the level's fallback lookup, which hashes it and then searches it.""" + if model is None: + return self._core._failure_error({"error_kind": "unknown_model"}, "None", None) # pyright: ignore[reportPrivateUsage] # the driver serves its own core + try: + _ = model in {} or "/" in model # pyright: ignore[reportOperatorIssue] # raising is the point + except TypeError as error: + return error + return TypeError(f"{model!r} is not a model group") + + def _level_failed(self, event: Mapping[str, object]) -> None: + """A level raises the error a pick raised (``level_failed``).""" + level: Final = event.get("level") + at_level: Final = level if isinstance(level, int) else 0 + picked: Final = ( + self._picked_error(event) + if event.get("handling") is True + else self._level_picks.pop(at_level, None) or self._picked_error(event) + ) + if event.get("handling") is True: + # Raised by the level's fallback handling, while the level's error was handled. + picked.__context__ = self._level_errors.get(at_level, self._last_error) + self._level_errors[at_level] = picked + if at_level == self._base_level: + self._explains_failure = False + return + stamp: Final = self._pending_stamps.pop(at_level, None) + if stamp is not None and type(picked) in self._core._host.dynamic().exception_types: # pyright: ignore[reportPrivateUsage] # the driver serves its own core + # The exhausted retry loop raised this pick's error: stamped as `retries_exhausted` stamps. + picked.max_retries, picked.num_retries = stamp # pyright: ignore[reportAttributeAccessIssue] # Python's router stamps the same attributes + self._chain_to_hop_first(picked, at_level) + self._level_errors[at_level] = picked + + def _carry_superseded_usage(self) -> None: + """``carry_superseded_attempt_usage``, before each same-group retry and each fallback hop.""" + from litellm.router_utils.fallback_event_handlers import carry_superseded_attempt_usage + + carry_superseded_attempt_usage(self._request) + + def _order_chain_failed(self, event: Mapping[str, object]) -> None: + """The order path of ``async_function_with_fallbacks_common_utils`` raised: the chain's last + hop's error, which the hop's level ended on, unless the level keeps its own.""" + level: Final = event.get("level") + at: Final = level if isinstance(level, int) else 0 + last_hop: Final = self._level_errors.get(at + 1) + if event.get("last_hop") is True and last_hop is not None: + self._level_errors[at] = last_hop + if at == self._base_level: + self._explains_failure = False + + def _logged_off_the_loop(self) -> bool: + """Whether litellm logged the attempt's failure on a thread with no running loop. An async + call's mocked failure raises in ``completion``, which ``acompletion`` runs in an executor + thread; a sync stream's first chunk logs in a ``threading.Thread``.""" + from litellm.utils import should_run_mock_completion + + if self._sync: + return self._reading_first_chunk + kwargs: Final[Mapping[str, object]] = self._latest_call[1].kwargs if self._latest_call is not None else {} + return self._plan.kind in ("chat", "text") and should_run_mock_completion( + kwargs.get("mock_response"), kwargs.get("mock_tool_calls"), kwargs.get("mock_timeout") + ) + + def _cooldown_set(self, event: Mapping[str, object]) -> None: + """An attempt's failure cooled its deployment down: ``set_cooldown_deployments`` as the failure + callback runs it. Outside a running loop it raises, which ``CustomLogger.log_event`` swallows; + a sync walk with a private loop has one (``cooldown_event_on_own_loop``).""" + deployment_id: Final = event.get("deployment_id") + seconds: Final = event.get("cooldown_time") + if self._logged_off_the_loop() or not isinstance(deployment_id, str): + return + fire: Final = self._core.cooldown_event_on_own_loop if self._plan.on_its_own_loop else self._core.cooldown_event + with contextlib.suppress(RuntimeError): + fire( + deployment_id, + getattr(self._last_error, "status_code", ""), + self._python_cooldown_time(seconds) if isinstance(seconds, float) else None, + ) + + def _python_cooldown_time(self, seconds: float) -> float: + """``_time_to_cooldown`` of ``deployment_callback_on_failure`` for the attempt that failed.""" + deployment: Final[Mapping[str, object]] = self._latest_call[0] if self._latest_call is not None else {} + configured: Final = first_cooldown( + as_str_mapping(deployment.get("model_info")), + self._request, + as_str_mapping(deployment.get("litellm_params")), + ) + return self._core.python_cooldown(seconds, configured, self._last_error) + + def _selected(self, event: Mapping[str, object]) -> None: + """``_acompletion``'s service event for the pick it awaited, and its ``_track_deployment_metrics``.""" + seconds: Final = event.get("pick_seconds") + if self._plan.kind == "chat" and not self._sync and isinstance(seconds, float): + end_time: Final = unix_time() + self._core.service_logged("async_get_available_deployment", end_time - seconds, end_time, self._request) + self._core.track_deployment_pick(event.get("deployment_id"), self._request) + + def _fallbacks_failed(self, event: Mapping[str, object]) -> None: + """The ``except`` around the regular fallbacks of ``async_function_with_fallbacks_common_utils``: + it logs what the ``try`` raised, the last hop's error or the level's own. A level with no + target raises its own error into it, except where no fallback list was set to search.""" + import litellm.exceptions as litellm_exceptions + from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs + + level: Final = event.get("level") + at: Final = level if isinstance(level, int) else 0 + own: Final = self._level_errors.get(at, self._last_error) + request: Final = self._request + walked: Final = self._core._walked_fallbacks # pyright: ignore[reportPrivateUsage] # the driver serves its own core + if event.get("chain") is not True: + policy_list: Final = request.get("content_policy_fallbacks", walked["content_policy_fallbacks"]) + if not isinstance(own, litellm_exceptions.ContentPolicyViolationError) or policy_list is None: + if request.get("fallbacks", walked["fallbacks"]) is None: + return + self._explain_no_fallback_group(own, at) + raised: Final = self._level_errors.get(at + 1, own) if event.get("last_hop") is True else own + self.outcomes.failed_fallbacks( + RoutingContext(self._core), # pyright: ignore[reportArgumentType] # the read uses registry() and health() + truncate_fallback_error_detail(redact_string(str(raised))), + get_parent_otel_span_from_kwargs(dict(request)), + ) + + def _explain_no_fallback_group(self, primary: BaseException | None, at: int) -> None: + """The primary level names the missing fallback group on its error before raising it into + the ``except``, so the log reads it and no outcome message follows.""" + if ( + at == self._base_level == 0 + and self._core._host.dynamic().expose_router_debug_in_errors # pyright: ignore[reportPrivateUsage] # the driver serves its own core + and primary is not None + and hasattr(primary, "message") + ): + primary.message += self._explanation(primary, str(self._request.get("model"))) # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType] # checked above # rebind-ok: the message is what this explains + self._explains_failure = False + + def take_events(self, events: object) -> None: # noqa: C901 # one branch per router-core event + for raw_event in _as_list(events): + event = as_str_mapping(raw_event) + if event is None: + continue + if event.get("kind") == "retry": + self._carry_superseded_usage() + continue + if event.get("kind") == "cooldown_set": + self._cooldown_set(event) + continue + if event.get("kind") == "selected": + self._selected(event) + continue + if event.get("kind") == "retries_opened": + self._walk.retries_opened(self._stamped_budget(event)) + continue + if event.get("kind") == "retry_budget": + self._walk.retry_budget(event) + continue + if event.get("kind") == "pick_failed": + self._pick_failed(event) + continue + if event.get("kind") == "order_chain_failed": + self._order_chain_failed(event) + continue + if event.get("kind") == "mock_failed": + resolved = self._core._resolved # pyright: ignore[reportPrivateUsage] # the driver serves its own core + mocked = mock_error( + str(event.get("mock")), + str(event.get("model")), + event.get("num_retries"), + self._request, + { + "fallbacks": resolved.fallbacks, + "context_window_fallbacks": resolved.context_window_fallbacks, + "content_policy_fallbacks": resolved.content_policy_fallbacks, + }, + ) + level = event.get("level") + self._last_error = mocked + self._level_errors[level if isinstance(level, int) else 0] = mocked + continue + if event.get("kind") == "retry_policy_raised": + self._policy_raised(event) + continue + if event.get("kind") == "retry_count_raised": + self._count_raised(event) + continue + if event.get("kind") == "level_failed": + self._level_failed(event) + continue + if event.get("kind") == "fallbacks_failed": + self._fallbacks_failed(event) + continue + if event.get("kind") == "fallback": + hop_to = event.get("level") + self._hop_first.pop(hop_to if isinstance(hop_to, int) else 0, None) + self._walk.hop(event) + self._carry_superseded_usage() + hop_level = event.get("level") + self._level = hop_level if isinstance(hop_level, int) else self._level + if "unroutable" in event: + self._level_errors[self._level] = self._unroutable_error(event["unroutable"]) + continue + if event.get("kind") == "blocked": + level = event.get("level") + blocked = self._blocked_error(event) + self._stamp_blocked(blocked) + self._last_error = blocked + self._level_errors[level if isinstance(level, int) else 0] = blocked + continue + if event.get("kind") == "falling_back": + level = event.get("level") + at = level if isinstance(level, int) else 0 + self._explains_failure = self._explains_failure or at == self._base_level + self._hint_level_failure(self._level_errors.get(at, self._last_error), str(event.get("model"))) + continue + if event.get("kind") == "fallback_done": + level = event.get("level") + at = level if isinstance(level, int) else 0 + self._level = at + self.outcomes.done( + event, + self._level_errors.get(at, self._last_error), + self._level_errors.get(at + 1), + self._walk.hop_kwargs(event), + ) + if event.get("succeeded") is not True: + self._core.trigger_fallback_cooldown( + self._request, + self._level_errors.get(at + 1), + self._plan.kind in _GENERIC_API_KINDS, + own_loop=self._plan.on_its_own_loop, + ) + continue + if event.get("kind") == "retry_logged": + logged = self._logged_error(event) + self._walk.log_retry(event, logged) + logged_level = event.get("level") + if event.get("attempted_retries") == 0 and logged is not None: + self._hop_first[logged_level if isinstance(logged_level, int) else 0] = logged + continue + if event.get("kind") != "retries_exhausted": + continue + if event.get("picked") is True: + # The level raises the last retry's pick error, which its `level_failed` names. + exhausted_level = event.get("level") + self._pending_stamps[exhausted_level if isinstance(exhausted_level, int) else 0] = ( + event.get("max"), + event.get("attempted"), + ) + continue + error: BaseException | None = self._last_error + # `async_function_with_retries` stamps the error its exhausted retry loop raises. + if error is not None and type(error) in self._core._host.dynamic().exception_types: # pyright: ignore[reportPrivateUsage] # the driver serves its own core + error.max_retries = event.get("max") # pyright: ignore[reportAttributeAccessIssue] # Python's router stamps the same attributes + error.num_retries = event.get("attempted") # pyright: ignore[reportAttributeAccessIssue] # same + + def _call(self, step: Mapping[str, object]) -> "tuple[Mapping[str, object], AttemptCall]": + name: Final = step.get("model") + requested: Final = str(name) if name is not None else str(self._request.get("model")) + deployment: Final = ( + # A default deployment whose id is not a string is called as Python copies it, id and all. + as_str_mapping(default_deployment_copy(self._core._resolved.default_deployment, requested)) or {} # pyright: ignore[reportPrivateUsage] # the driver serves its own core + if step.get("deployment_id") == DEFAULT_DEPLOYMENT_COPIED_ID + else for_requested_model(typed_deployment(as_str_mapping(step.get("deployment")) or {}), requested) + ) + self._attempts += 1 + self._attempt_started = datetime.now() # noqa: DTZ005 # naive to match the logging pipeline's api_call_start_time + level: Final = step.get("fallback_level") + # The request params the walk's dict targets merged in (`kwargs.update(target)`). + params: Final = as_str_mapping(step.get("params")) + call: Final = attempt_call( + self._core._port, # pyright: ignore[reportPrivateUsage] # the driver serves its own core + self._plan, + self._request if params is None else {**self._request, **params}, + deployment, + group=requested, + requested=requested, + fallback_level=level if isinstance(level, int) else 0, + ) + self._strip_undecryptable_reasoning(step, deployment, call.kwargs) + shaped: Final = shape_attempt_kwargs(call.kwargs, deployment) + # The walk's metadata for the attempt's level (retries, fallback hops) and its hop kwargs. + call.kwargs = self._walk.stamp(step, shaped) + field: Final = self._plan.metadata_field + if isinstance(call.served, dict) and field in call.kwargs: + call.served[field] = call.kwargs[field] + self._served = (requested, call.served) + self._latest_call = (deployment, call) + if call.refused is None: + self._core._endpoints.counters.started(self._plan, call) # pyright: ignore[reportPrivateUsage] # the driver serves its own core + return deployment, call + + def _strip_undecryptable_reasoning( + self, step: Mapping[str, object], deployment: Mapping[str, object], kwargs: Mapping[str, object] + ) -> None: + """``_update_kwargs_with_deployment`` on a fallback hop (``_is_fallback_hop``): the encrypted + reasoning the target cannot decrypt is dropped; reasoning with no origin marker came from + the deployment that just failed.""" + depth: Final = step.get("fallback_depth") + if not isinstance(depth, int) or depth <= 0: + return + EncryptedContentAffinityCheck.strip_reasoning_the_targets_cannot_decrypt( + RoutingContext(self._core), # pyright: ignore[reportArgumentType] # the check reads registry() + kwargs.get("input"), + kwargs.get("messages"), + (deployment,), + unmarked_origin=self._walk.deployment_that_just_failed(step) or self._cut_deployment, + ) + + @property + def response(self) -> object: + return self._last_response + + @property + def last_error(self) -> BaseException | None: + return self._last_error + + def _stream_attempt( + self, step: Mapping[str, object], kwargs: Mapping[str, object], slot: "contextlib.ExitStack | None" = None + ) -> StreamAttempt: + def number(key: str) -> int: + value: Final = step.get(key) + return value if isinstance(value, int) else 0 + + order: Final = step.get("target_order") + deployment_id: Final = step.get("deployment_id") + return StreamAttempt( + core=self._core, + op=self._op, + request=self._request, + kwargs=kwargs, + group=str(step.get("model") or step.get("model_group")), + order=order if isinstance(order, int) else None, + depth=number("fallback_depth"), + level=number("fallback_level"), + deployment_id=deployment_id if isinstance(deployment_id, str) else None, + attempted_retries=number("retry"), + slot=slot, + ) + + def _failed( + self, + step: Mapping[str, object], + deployment: Mapping[str, object], + call: "AttemptCall | None", + error: BaseException, + ) -> Mapping[str, object]: + # What litellm's failure logging read, before the attempt helper's `except` wrote on it. + detail: Final = str(error) + served: Final = call.served if call is not None else {} # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + stamp_error(self._plan, error, deployment, served) # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + self._core._endpoints.attempt_failed(self._plan, error, deployment, call, str(step.get("model"))) # pyright: ignore[reportPrivateUsage] # see above + self._last_error = error + level: Final = step.get("fallback_level") + retry: Final = step.get("retry") + if isinstance(retry, int) and retry > 0: + self._chain_to_hop_first(error, level if isinstance(level, int) else 0) + self._level_errors[level if isinstance(level, int) else 0] = error + logged: Final = logged_call( + call.host_op if call is not None else self._plan.host_op, + served or self._request, # pyright: ignore[reportUnknownArgumentType] # see above + self._attempt_started, + ) + model_info: Final = as_str_mapping(deployment.get("model_info")) or {} + return { + **attempt_failure(error), + "detail": detail, + **self._core.failure_exits(error, logged, model_info.get("id")), + # `async_deployment_callback_on_failure` does not run for a sync call, and skips a batch retrieve. + "uncounted_request": self._plan.sync or is_batch_retrieve_call_type(logged.get("call_type")), + } + + def _chain_to_hop_first(self, error: BaseException, level: int) -> None: + """A retry's failure is raised while the hop's first failure is handled (the retry loop + runs in its ``except`` block), so it chains to it.""" + first: Final = self._hop_first.get(level) + if first is not None and first is not error: + error.__context__ = first # rebind-ok: chained as the retry loop's raise chains it + + def _succeeded( + self, call: "AttemptCall", response: object, host_op: str, stream: "StreamAttempt | None" = None + ) -> Mapping[str, object]: + self._last_response = response + tokens: Final = total_tokens(response) + # A wrapped stream reports its success or failure when it ends; the attempt counts the + # request and the tokens read so far, which the end's report leaves out. + # A realtime attempt counts its session's success itself (`attempt`), when it ended cleanly. + deferred: Final = (stream is not None and stream.reports_outcome) or reports_own_success(call) + if stream is not None and deferred: + stream.counted_tokens = tokens # rebind-ok: what the end's report leaves out + return { + "ok": True, + "total_tokens": tokens, + "blocked": self._blocked(response, host_op), + "deferred": deferred, + "tracks_usage": self._tracks_usage(call, response, deferred), + } + + def _tracks_usage(self, call: "AttemptCall", response: object, deferred: bool) -> bool: + """Whether the attempt counts against its deployment's usage (``_deployment_tracks_usage``). A + ``None`` response counts nothing (``increment_deployment_usage_for_response``), and an attempt + that reports no success then is a realtime session, which logs none to count it either.""" + if deferred and response is None: + return False + model: Final = call.kwargs.get("model") + return self._core.deployment_tracks_usage( + (as_str_mapping(call.kwargs.get("model_info")) or {}).get("id"), + model if isinstance(model, str) else call.group, + ) + + async def _refused( + self, + step: Mapping[str, object], + deployment: Mapping[str, object], + call: "AttemptCall", + error: BaseException, + ) -> Mapping[str, object]: + """A routing pre-call check refused the attempt (``async_routing_strategy_pre_call_checks``): + a rate limit cools the deployment down (``set_cooldown_deployments``); the attempt's failure + is recorded by nothing else.""" + import litellm.exceptions as litellm_exceptions + + core: Final = self._core + if isinstance(error, litellm_exceptions.RateLimitError): + deployment_id: Final = (as_str_mapping(deployment.get("model_info")) or {}).get("id") + if isinstance(deployment_id, str): + failure: Final = {**attempt_failure(error), "caller_scoped": core.per_user_deployment(deployment_id)} + report: Final = core._handle.report_failure(deployment_id, failure, uncounted=True) # pyright: ignore[reportPrivateUsage] # the driver serves its own core + done: Final = await core._drive_cache_steps(report) # pyright: ignore[reportPrivateUsage] # see above + _ = core.cooled_down(done, deployment_id, error.status_code) + return {**self._failed(step, deployment, call, error), "recorded": True} + + def _pick_kwargs(self, step: Mapping[str, object]) -> Mapping[str, object]: + """The request kwargs the pick sees: the request with its level's retry count.""" + count: Final = self._walk.request_retry_count(step) + if count is None: + return self._request + field: Final = self._plan.metadata_field + metadata: Final = as_str_mapping(self._request.get(field)) or {} + return {**self._request, field: {**metadata, "request_retry_count": count}} + + def _with_deployment(self, step: Mapping[str, object], resolved: object) -> Mapping[str, object]: + return step if resolved is step.get("deployment") else {**step, "deployment": resolved} + + async def _resolve_pods(self, step: Mapping[str, object]) -> Mapping[str, object]: + """``async_resolve_pods_after``: a picked deployment with Kubernetes pod discovery on is + sent to one of its service's pods.""" + if self._plan.kind in _UNPICKED_KINDS or step.get("deployment") is None: + return step + discovery: Final = self._core._pick_discovery(sync=False) # pyright: ignore[reportPrivateUsage] # the driver serves its own core + if discovery is None: + return step + resolved: Final[object] = await discovery.async_resolve_deployment( + step.get("deployment"), self._pick_kwargs(step) + ) + return self._with_deployment(step, resolved) + + def _resolve_pods_sync(self, step: Mapping[str, object]) -> Mapping[str, object]: + """``resolve_pods_after``, on the sync pick.""" + if self._plan.kind in _UNPICKED_KINDS or step.get("deployment") is None: + return step + discovery: Final = self._core._pick_discovery(sync=True) # pyright: ignore[reportPrivateUsage] # see _resolve_pods + if discovery is None: + return step + return self._with_deployment( + step, discovery.resolve_deployment(step.get("deployment"), self._pick_kwargs(step)) + ) + + def _default_copy(self, step: Mapping[str, object]) -> Mapping[str, object]: + """The default deployment as Python copied it for the call that fails on it: the error is + stamped from this copy, never from the id router-core serves it under.""" + copied: Final = default_deployment_copy(self._core._resolved.default_deployment, str(step.get("model"))) # pyright: ignore[reportPrivateUsage] # the driver serves its own core + return as_str_mapping(copied) or {} + + def _default_call_error(self, step: Mapping[str, object]) -> BaseException | None: + """The error a call to a default deployment every call fails to raises (its first + reads of the copy, before any endpoint runs): nothing records it against a deployment.""" + if step.get("deployment_id") != DEFAULT_DEPLOYMENT_FAILING_ID: + return None + return default_deployment_call_error(self._core._resolved.default_deployment) # pyright: ignore[reportPrivateUsage] # the driver serves its own core + + async def _passthrough_attempt(self, step: Mapping[str, object]) -> Mapping[str, object]: + """``_ageneric_api_call_with_fallbacks_helper`` with ``passthrough_on_no_deployment``: the pick + failed, so the handler is called under the attempt's name. Nothing was picked, so nothing is + stamped on a failure or recorded against a deployment.""" + passthrough: Final = self._passthrough + if passthrough is None: + raise RuntimeError("router-core asked for an unrouted attempt the host did not offer") + name: Final = str(step.get("model")) + params: Final = as_str_mapping(step.get("params")) + self._attempts += 1 + self._attempt_started = datetime.now() # noqa: DTZ005 # see _call + try: + answered: Final = await passthrough(self._request if params is None else {**self._request, **params}, name) + except Exception as error: # noqa: BLE001 # handed to the Rust call loop like any attempt failure + return {**self._failed(step, {}, None, error), "recorded": True} + self._last_response = answered + self._served = (name, self._request) + return {"ok": True, "total_tokens": total_tokens(answered)} + + async def attempt(self, step: Mapping[str, object]) -> Mapping[str, object]: + if self._passthrough is not None and not step.get("deployment_id"): + return await self._passthrough_attempt(step) + step = await self._resolve_pods(step) # rebind-ok: the picked deployment, resolved to a pod + deployment: Mapping[str, object] = as_str_mapping(step.get("deployment")) or {} # rebind-ok: the picked one + call: AttemptCall | None = None # rebind-ok: built inside the try + # Whether a failure raised now runs the failure callbacks: none raised before the litellm + # call or after it answered does, nor any but the first on a shared logging object. + logs_failure: bool = False # rebind-ok: set around the litellm call + reading_stream: StreamAttempt | None = None # rebind-ok: set while the first chunk is read + refused_call: Final = self._default_call_error(step) + if refused_call is not None: + return {**self._failed(step, self._default_copy(step), None, refused_call), "recorded": True} + try: + deployment, call = self._call(step) # rebind-ok: rebound as the Python router rebinds it + if call.refused is not None: + await log_refused_call(call, call.refused) + raise call.refused + host: Final = self._core._host # pyright: ignore[reportPrivateUsage] # the driver serves its own core + try: + compacted: Final = await compacted_attempt(self._core._port, self._plan, deployment, call) # pyright: ignore[reportPrivateUsage] # see above + except Exception as refused: # noqa: BLE001 # raised before the provider call, so no cooldown reads it + return {**self._failed(step, deployment, call, refused), "recorded": True} + # The deployment's max_parallel_requests slot; an open chat stream takes it along. + port = self._core._port # pyright: ignore[reportPrivateUsage] # the driver serves its own core # rebind-ok: the same port on every attempt + with enter_deployment_slot(port, self._plan, deployment, call.kwargs) as slot: + # A search tool is no deployment: nothing to check; Python's `_arerank` and + # `amoderation` run no routing pre-call checks either. + if self._plan.kind not in _NO_ROUTING_PRE_CALL_CHECKS: + try: + await routing_pre_call_checks( + self._core._checks.routing_callbacks(), # pyright: ignore[reportPrivateUsage] # see above + as_str_mapping(step.get("deployment")) or {}, + ) + except Exception as refused: # noqa: BLE001 # handed to the Rust call loop as the attempt's failure + # Only `_acompletion` hands the check its logging object. + if self._plan.kind == "chat": + _log_refused_pick(self._request, refused) + return await self._refused(step, deployment, call, refused) + first_to_log: Final = not failure_already_logged(call.kwargs, "async_failure") + logs_failure = first_to_log # rebind-ok: whether a failure here is this attempt's to log + pending: Final[object] = ( + self._core._endpoints.create_file_everywhere( # pyright: ignore[reportPrivateUsage] # see above + _with_target_order(call.kwargs, step.get("target_order")), + call.model_name, + self._request.get("specific_deployment"), + ) + if self._plan.kind == "create_file" + else host.invoke(call.host_op)(**compacted) + ) + # The generic helper awaits whatever the handler returns, as the Python router does. + awaited: Final = self._plan.kind == "generic" or inspect.isawaitable(pending) + answered: Final[object] = await pending if awaited else pending # pyright: ignore[reportGeneralTypeIssues, reportUnknownVariableType] # see above + logs_failure = False # rebind-ok: see above + self._core._endpoints.check_response(self._plan, answered, call) # pyright: ignore[reportPrivateUsage, reportUnknownArgumentType] # see above + stream: Final = self._stream_attempt(step, call.kwargs, slot) + logs_failure = first_to_log # rebind-ok: the stream's own failure logging, for its first chunk + reading_stream = stream # rebind-ok: None until the attempt opens a stream + response: Final = await open_attempt_stream(stream, answered) # pyright: ignore[reportUnknownArgumentType] # see above + logs_failure = False # rebind-ok: see above + # `self.success_calls[model_name] += 1`, inside the try: a counter replaced with a + # plain dict fails the attempt. + self._core._endpoints.counters.succeeded(self._plan, call) # pyright: ignore[reportPrivateUsage] # see above + except Exception as error: # noqa: BLE001 # every attempt failure is classified and handed to the Rust call loop + failed: Final = self._failed(step, deployment, call, error) + if reading_stream is None or not logs_failure: + return {**failed, "recorded": not logs_failure} + # `_dispatch_stream_failure`: the stream logs its failure in a task of its own. + reading_stream.report_first_chunk_failure(error) + return {**failed, "recorded": True} + served: Final = self._succeeded(call, response, call.host_op, stream) + # The session re-pin the Python core's success callback runs; a wrapped stream runs it when it ends. + if not served.get("deferred") and self._core.outcome_callbacks(call.kwargs, sync=False).get("success", True): + await self._core.repin_after_success(stream.logged(), response) + session_deployment: Final = clean_realtime_session_deployment(call) + if session_deployment is not None: + await self._core.count_realtime_session_success(session_deployment) + return served + + def attempt_sync(self, step: Mapping[str, object]) -> Mapping[str, object]: + step = self._resolve_pods_sync(step) # rebind-ok: see attempt + deployment: Mapping[str, object] = as_str_mapping(step.get("deployment")) or {} # rebind-ok: see attempt + call: AttemptCall | None = None # rebind-ok: see attempt + logs_failure: bool = False # rebind-ok: see attempt + self._reading_first_chunk = False + refused_call: Final = self._default_call_error(step) + if refused_call is not None: + return {**self._failed(step, self._default_copy(step), None, refused_call), "recorded": True} + try: + deployment, call = self._call(step) # rebind-ok: rebound as the Python router rebinds it + if call.refused is not None: + log_refused_call_sync(call, call.refused) + raise call.refused + try: + self._core._endpoints.sync_pre_call_checks(self._plan, deployment, self._request) # pyright: ignore[reportPrivateUsage] # see above + except Exception as refused: # noqa: BLE001 # handed to the Rust call loop like any attempt failure + # The sync path records no outcome for a refused pre-call check: no cooldown. + return {**self._failed(step, deployment, call, refused), "recorded": True} + first_to_log: Final = not failure_already_logged(call.kwargs, "sync_failure") + logs_failure = first_to_log # rebind-ok: see attempt + answered: Final = self._core._host.invoke(call.host_op)(**call.kwargs) # pyright: ignore[reportPrivateUsage] # a sync endpoint + logs_failure = False # rebind-ok: see attempt + if inspect.isawaitable(answered): + raise _NotSynchronous(f"the host's {call.host_op} endpoint is not synchronous") + self._core._endpoints.check_response(self._plan, answered, call) # pyright: ignore[reportPrivateUsage] # see above + stream: Final = self._stream_attempt(step, call.kwargs) + logs_failure = first_to_log # rebind-ok: see attempt + self._reading_first_chunk = True + response: Final = open_attempt_stream_sync(stream, answered) + self._reading_first_chunk = False + logs_failure = False # rebind-ok: see attempt + self._core._endpoints.counters.succeeded(self._plan, call) # pyright: ignore[reportPrivateUsage] # see attempt + except _NotSynchronous: + raise + except Exception as error: # noqa: BLE001 # see attempt + return {**self._failed(step, deployment, call, error), "recorded": not logs_failure} + return self._succeeded(call, response, "", stream) + + async def select(self, step: Mapping[str, object]) -> object: + request: Final = self._request + messages, input = self._plan.pick_input(request) + if step.get("stage") == "callback_filters": + answer, error = await self._core._answer_callback_filters(step, request, messages) # pyright: ignore[reportPrivateUsage] # the driver serves its own core + if isinstance(error, Exception): + # The try failed with the filter's error: the level raises it if nothing else serves. + _ = self._pick_raised(error, logged=True) + return answer + try: + return await self._core._answer_select(step, request, messages, input) # pyright: ignore[reportPrivateUsage] # the driver serves its own core + except Exception as error: # noqa: BLE001 # handed to the Rust call loop as the try's failure + return self._pick_raised(error, logged=True) + + def select_sync(self, step: Mapping[str, object]) -> object: + request: Final = self._request + try: + return self._core._answer_select_sync(step, request, *self._plan.pick_input(request)) # pyright: ignore[reportPrivateUsage] # see above + except Exception as error: # noqa: BLE001 # see select + return self._pick_raised(error, logged=False) + + async def pre_route(self, step: Mapping[str, object]) -> object: + request: Final = self._request + try: + return await self._core._pre_route(step, request, *self._plan.pick_input(request)) # pyright: ignore[reportPrivateUsage] # see above + except Exception as error: # noqa: BLE001 # see select + return self._pick_raised(error, logged=True) + + def pre_route_sync(self, step: Mapping[str, object]) -> object: + request: Final = self._request + try: + return self._core._custom_pick_sync(step, request, *self._plan.pick_input(request)) # pyright: ignore[reportPrivateUsage] # see above + except Exception as error: # noqa: BLE001 # see select + return self._pick_raised(error, logged=False) + + async def allow_fallback(self, target: str) -> object: + """`_is_fallback_target_authorized`, then `_is_fallback_target_within_budget`. A check that raises + ends the chain outside any hop's ``try``, as a chain's own failure: the level raises what it + would have (``async_function_with_fallbacks_common_utils`` catches it), and its note or an + order path reads the error as the next level's.""" + from litellm.router_utils.fallback_event_handlers import get_pre_routing_selection + from litellm.types.router import FallbackSkipReason + + ctx: Final = RoutingContext(self._core) # pyright: ignore[reportArgumentType] # the checks read registry() and settings() + request: Final = dict(self._request) + try: + if target != get_pre_routing_selection(request) and not await ctx.fallback_access_allowed( + model=target, request_kwargs=request + ): + self._walk.targets().record_skip(target, FallbackSkipReason.NOT_AUTHORIZED) + return False + if not await ctx.fallback_budget_allowed(model=target, request_kwargs=request): + self._walk.targets().record_skip(target, FallbackSkipReason.OVER_BUDGET) + return False + except Exception as error: # noqa: BLE001 # handed to the Rust call loop, which ends the chain + self._level_errors[self._level + 1] = error + return {**attempt_failure(error), "raised": True} + return True + + def refuse_fallbacks(self, step: Mapping[str, object]) -> bool: + """``run_async_fallback``'s check of a chain's dict targets: a refused chain ends the walk + with the check's error, which the first hop's level would have raised.""" + refused: Final = rejected_fallback_target(_as_list(step.get("targets"))) + if refused is None: + return False + level: Final = step.get("level") + self._level_errors[(level if isinstance(level, int) else 0) + 1] = refused + return True + + def _head_response(self) -> object | None: + """``set_response_headers`` up to its usage read: the deployment id, the model group the + response was served as and the routers' decisions.""" + response: Final = prepare_response_for_header_attachment(self._last_response) + if response is None: + return None + name, kwargs = self._served + additional: Final = ensure_response_additional_headers(response) + apply_response_model_id(response, find_deployment_metadata(kwargs)) + additional["x-litellm-model-group"] = name + apply_quality_router_decision_headers(additional, kwargs) + additional.update(complexity_router_decision_headers(kwargs)) + return response + + def _count_response(self, response: object, step: Mapping[str, object]) -> object: + """What the wrappers above `make_call` stamp: ``async_function_with_retries``'s retry count, + then the fallback count of ``async_function_with_fallbacks`` and ``run_async_fallback``.""" + retries: Final = step.get("attempted_retries") + if isinstance(retries, int): + max_retries: Final = step.get("max_retries") + response = add_retry_headers_to_response( # rebind-ok: gains the counts + response=response, + attempted_retries=retries, + max_retries=max_retries if isinstance(max_retries, int) and retries > 0 else None, + ) + fallbacks: Final = step.get("attempted_fallbacks") + attempted: Final = fallbacks if isinstance(fallbacks, int) else 0 + return add_fallback_headers_to_response( + response=self.outcomes.add_headers(response, attempted), attempted_fallbacks=attempted + ) + + def log_outcomes_sync(self) -> None: + if pending := self.outcomes.take_pending(): + from litellm.litellm_core_utils import asyncify + + asyncify.run_async_function(await_all, pending) # pyright: ignore[reportUnknownMemberType] # the untyped sync bridge + + def finish(self, step: Mapping[str, object]) -> object: + """The response with the router's headers, in the order ``make_call`` and the wrappers above it + stamp them: a usage read that raises leaves the counts off.""" + if not self._plan.sets_headers: + self.log_outcomes_sync() + return self._last_response + response: Final = self._head_response() + if response is None: + self.log_outcomes_sync() + return self._last_response + name: Final = self._served[0] + if name is not None: + core: Final = self._core + remaining: Final = as_str_mapping( + core.run_routing_cache_sync(lambda: core.health().usage(name, kind="remaining")) + ) + if remaining is not None: + apply_remaining_usage_headers(ensure_response_additional_headers(response), dict(remaining)) + counted: Final = self._count_response(response, step) + self.log_outcomes_sync() + return counted + + async def finish_async(self, step: Mapping[str, object]) -> object: + """``finish``, with the usage read on the call's own loop.""" + if not self._plan.sets_headers: + await await_all(self.outcomes.take_pending()) + return self._last_response + response: Final = self._head_response() + if response is None: + await await_all(self.outcomes.take_pending()) + return self._last_response + name: Final = self._served[0] + if name is not None: + remaining: Final = await self._core.health().usage(name, kind="remaining") + if isinstance(remaining, Mapping): + apply_remaining_usage_headers(ensure_response_additional_headers(response), dict(remaining)) + counted: Final = self._count_response(response, step) + await await_all(self.outcomes.take_pending()) + return counted + + def failed(self, step: Mapping[str, object]) -> BaseException: + model: Final = str(self._request.get("model")) + primary: Final = self._level_errors.get(self._base_level) + if primary is None: + return self._core._failure_error(step, model, self._last_error, request=self._request) # pyright: ignore[reportPrivateUsage] # see above + if ( + self._base_level == 0 + and self._explains_failure + and self._core._host.dynamic().expose_router_debug_in_errors # pyright: ignore[reportPrivateUsage] # see above + and hasattr(primary, "message") + ): + primary.message += self._explanation(primary, model) # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType] # checked above + return primary + + def _hint_level_failure(self, error: BaseException | None, model: str) -> None: + """A level that reaches its fallback handling on a context-window or content-policy error + with no list of its own appends the hint to set one, before any hop runs, as every level of + the Python walk does: a stream's failure event, still queued then, reads the hint.""" + from litellm.router_utils.fallback_event_handlers import check_non_standard_fallback_format + + if ( + error is None + or not hasattr(error, "message") + or not self._core._host.dynamic().expose_router_debug_in_errors # pyright: ignore[reportPrivateUsage] # the driver serves its own core + ): + return + walked: Final = self._core._walked_fallbacks # pyright: ignore[reportPrivateUsage] # see above + fallbacks: Final = self._request.get("fallbacks", walked["fallbacks"]) + if check_non_standard_fallback_format(fallbacks=_as_list(fallbacks)): + return + hint: Final = self._kind_hint(error, model, fallbacks) + if hint: + error.message += hint # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType] # checked above # rebind-ok: the router appends to the error it raises + + def _kind_hint(self, error: BaseException, model: str, fallbacks: object) -> str: + """The hint a context-window or content-policy error gets when its own list is unset.""" + import litellm.exceptions as litellm_exceptions + + walked: Final = self._core._walked_fallbacks # pyright: ignore[reportPrivateUsage] # the driver serves its own core + if isinstance(error, litellm_exceptions.ContextWindowExceededError): + if self._request.get("context_window_fallbacks", walked["context_window_fallbacks"]) is not None: + return "" + return ( + f"\nmodel={model}. context_window_fallbacks=None. fallbacks={fallbacks}.\n\n" + "Set 'context_window_fallback' - https://docs.litellm.ai/docs/routing#fallbacks" + ) + if isinstance(error, litellm_exceptions.ContentPolicyViolationError): + if self._request.get("content_policy_fallbacks", walked["content_policy_fallbacks"]) is not None: + return "" + return "\n" + format_content_policy_fallback_hint(model, None, fallbacks) # pyright: ignore[reportArgumentType] # the list as configured + return "" + + def _explanation(self, primary: BaseException, model: str) -> str: + """What ``async_function_with_fallbacks_common_utils`` appends to the error it re-raises + under ``expose_router_debug_in_errors``, from the resolved settings and what the call did.""" + import litellm.exceptions as litellm_exceptions + from litellm.router_utils.fallback_event_handlers import ( + check_non_standard_fallback_format, + fallback_lookup_groups, + get_fallback_model_group_for_lookup_groups, + ) + + walked: Final = self._core._walked_fallbacks # pyright: ignore[reportPrivateUsage] # the driver serves its own core + request: Final = self._request + # The request's own lists replace the router's (`kwargs.get("fallbacks", router)`). + fallbacks: Final = request.get("fallbacks", walked["fallbacks"]) + window_list: Final = request.get("context_window_fallbacks", walked["context_window_fallbacks"]) + policy_list: Final = request.get("content_policy_fallbacks", walked["content_policy_fallbacks"]) + lookup: Final = fallback_lookup_groups(request, model) + + def group_of(source: object) -> tuple[Sequence[object] | None, int | None]: + return get_fallback_model_group_for_lookup_groups(_as_list(source), lookup) # pyright: ignore[reportArgumentType] # the fallbacks config shape + + def outcome(group: Sequence[object] | None) -> str: + return format_fallback_outcome_message( + model, group, self._fallback_detail(primary), skipped=self._walk.targets().skipped + ) + + # `context_window_fallback_model_group`: only a chain the group matched takes precedence. + window_group: Final = ( + group_of(window_list)[0] + if isinstance(primary, litellm_exceptions.ContextWindowExceededError) and window_list is not None + else None + ) + if window_group is None and check_non_standard_fallback_format(fallbacks=_as_list(fallbacks)): + return outcome(_as_list(fallbacks)) + if window_group is not None: + return outcome(window_group) + # A content-policy list decides on its own: one with no match raises into the `except`. + if isinstance(primary, litellm_exceptions.ContentPolicyViolationError) and policy_list is not None: + return outcome(group_of(policy_list)[0]) + if fallbacks is None or not lookup: + return outcome(None) + found, generic = group_of(fallbacks) + group: Final[Sequence[object] | None] = ( + found if found is not None or generic is None else _as_list(_as_list(fallbacks)[generic]["*"]) # pyright: ignore[reportIndexIssue, reportCallIssue, reportArgumentType, reportUnknownArgumentType] # the entry the lookup matched + ) + return format_no_fallback_group_message(lookup, _as_list(fallbacks)) if group is None else outcome(group) # pyright: ignore[reportArgumentType] # the fallbacks config shape + + def _fallback_detail(self, primary: BaseException) -> str: + """``run_async_fallback`` raises its last hop's error, or the primary's when no hop ran.""" + return truncate_fallback_error_detail(redact_string(str(self._level_errors.get(1, primary)))) + + +__all__ = [ + "Resolved", + "RustCore", + "RustCoreUnsupported", + "RustHealth", + "RustRegistry", + "RustSettings", + "attempt_failure", + "failure_kind", + "total_tokens", + "unsupported_arguments", +] diff --git a/litellm/router_rust/invoke/README.md b/litellm/router_rust/invoke/README.md new file mode 100644 index 00000000000..d8562f99359 --- /dev/null +++ b/litellm/router_rust/invoke/README.md @@ -0,0 +1,13 @@ +# invoke + +The host side of `Host::invoke`: running one attempt against the one deployment router-core picked. Nothing here selects, retries, falls back or records cooldowns. + +- `shaping`: the kwargs an attempt sends to its deployment +- `endpoints`: what each public router method does before, around and after the routed call +- `streaming`: stream wrappers, so a stream that fails before its first token fails the attempt +- `slots`: a deployment's `max_parallel_requests` +- `walk`: the retry and fallback metadata stamped on each attempt +- `prompt_management`: prompt-management groups +- `websocket`: admission for each turn of a Responses websocket + +A Rust host replaces this with native endpoint calls. diff --git a/litellm/router_rust/invoke/__init__.py b/litellm/router_rust/invoke/__init__.py new file mode 100644 index 00000000000..faa2c13198d --- /dev/null +++ b/litellm/router_rust/invoke/__init__.py @@ -0,0 +1 @@ +"""The host side of ``Host::invoke``: one router attempt against one deployment.""" diff --git a/litellm/router_rust/invoke/endpoints.py b/litellm/router_rust/invoke/endpoints.py new file mode 100644 index 00000000000..c1dc5162ccf --- /dev/null +++ b/litellm/router_rust/invoke/endpoints.py @@ -0,0 +1,2454 @@ +""" +The Rust router core's endpoints: what each public router method does before, around and after +the routed call, as the Python router's endpoint methods do it. + +An endpoint is either routed (the Rust core picks the deployment, retries and falls back, and the +host runs each attempt) or served directly (the Python router calls litellm's function without +routing: no model group, an id that names no deployment, a fan-out over every deployment). Every +call out goes through the host: ``host.invoke(op)``, where an op is a litellm function name or a +dotted path to one (``vector_stores.main.asearch``), looked up when it is called. +""" + +import asyncio +import copy +import dataclasses +import threading +import time +import uuid +from collections import defaultdict +from collections.abc import Awaitable, Callable, Iterable, Mapping, Sequence +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, Literal, Protocol, TypeAlias + +from pydantic import TypeAdapter, ValidationError + +from litellm._internal_context import service_target +from litellm._logging import verbose_router_logger +from litellm.litellm_core_utils.add_retry_fallback_headers import ( + add_fallback_headers_to_response, + add_retry_headers_to_response, +) +from litellm.litellm_core_utils.batch_utils import get_router_metadata_variable_name +from litellm.litellm_core_utils.core_helpers import without +from litellm.litellm_core_utils.routing_common_utils import without_router_only_kwargs +from litellm.responses.retrieve_stream_query import without_retrieve_stream_defaults +from litellm.router_api import RoutingContext +from litellm.router_rust.invoke.shaping import ( + ROUTER_CLIENTS_TARGET, + STREAM_TIMEOUT_AWARE_GENERIC_HANDLERS, + Shaping, + as_dict, + deployment_params_with_request_reasoning_override, + drop_unsupported_classifier_reasoning_effort, + metadata_bucket, + stamp_deployment_num_retries, + stamp_failed_deployment_id, + stamp_retry_skip_deployment_id, + update_kwargs_with_deployment, +) +from litellm.router_strategy.complexity_router.context_compaction import ( + Surface, + compact_to_fit, + initialize_compaction_state, + surface_for_call, +) +from litellm.router_utils.endpoint_eligibility import endpoint_for_call, endpoint_selection + +if TYPE_CHECKING: + from litellm.caching.dual_cache import DualCache + from litellm.router_api import RouterRegistry + from litellm.router_rust.core import RustCore + from litellm.router_rust.steps.selection import StrategySelectors + from litellm.rust_bridge._native import RouterCoreHandle + from litellm.types.router import Deployment + + +class EndpointCore(Protocol): + """What the endpoints use of the core they serve: its host, Rust handle, settings, routing + cache, registry lookups and call drivers. ``RustCore`` provides it through ``_EndpointPort``; + a Rust host's endpoint layer would have to provide the same list.""" + + @property + def router(self) -> "RustCore": + """The core itself, for the provider handlers and helpers that take a router.""" + ... + + @property + def host(self) -> "PythonHost": ... + + @property + def handle(self) -> "RouterCoreHandle": ... + + @property + def resolved(self) -> "Resolved": ... + + @property + def shaping(self) -> Shaping: ... + + @property + def routing_cache(self) -> "DualCache": ... + + @property + def selectors(self) -> "StrategySelectors": ... + + @property + def endpoints(self) -> "RustEndpoints": ... + + async def drive( + self, + plan: "Plan", + request: Mapping[str, object], + overrides: Mapping[str, object] | None = None, + *, + passthrough: Callable[[Mapping[str, object], str], Awaitable[object]] | None = None, + prepared_already: bool = False, + ) -> object: ... + + def call_sync( + self, plan: "Plan", request: Mapping[str, object], overrides: Mapping[str, object] | None = None + ) -> object: ... + + def routing_callbacks(self) -> Iterable[object]: ... + + def resolve_alias(self, model: str) -> str | None: ... + + def group_deployments(self, model_name: str) -> Sequence[Mapping[str, object]] | None: + """``_core_get_model_list(model_name=...)`` on the host registry.""" + ... + + def routed_name(self, model: object) -> str: + """``RustCore.routed_name``: what a ``model`` that is no string raises, or the name it routes under.""" + ... + + def service_logged( + self, call_type: str, start_time: float, end_time: float, request: Mapping[str, object] + ) -> None: ... + + async def set_response_headers( + self, response: object, model_group: str | None, request_kwargs: Mapping[str, object] + ) -> object: ... + + def configured_deployment(self, model_id: str) -> "Deployment | None": + """``_core_get_deployment``: the deployment as the host registry holds it now.""" + ... + + def registry(self) -> "RouterRegistry": ... + + async def select( + self, + model: str, + request_kwargs: dict[str, object] | None = None, # mutable-ok: the RouterCore signature + *, + kind: str = "pick", + specific_deployment: bool | None = None, + messages: object = None, + ) -> Mapping[str, object] | Sequence[Mapping[str, object]]: ... + + async def acompletion(self, *args: object, **kwargs: object) -> object: ... # kwargs-ok: endpoint payload + + +Kind = Literal[ # rebind-ok: rebound as the Python router rebinds it + "chat", + "text", + "embedding", + "image", + "transcription", + "speech", + "rerank", + "adapter", + "generic", + "generic_sync", + "batch", + "cancel_batch", + "vector_store_create", + "moderation", + "create_file", + "search", +] +Stamp = Literal["deployment", "retry_skip", "none"] # rebind-ok: rebound as the Python router rebinds it +CountKey = Literal["deployment", "group", "empty"] # rebind-ok: rebound as the Python router rebinds it + +# The text of the user message each attempt helper hands its pick in place of the request's own +# (`_aimage_generation`, `_aadapter_completion`, `_acreate_batch`, ...). +_PICK_TEXTS: Final[Mapping[str, str]] = MappingProxyType( + { + "image": "prompt", + "transcription": "prompt", + "speech": "prompt", + "adapter": "default text", + "batch": "files-api-fake-text", + "create_file": "files-api-fake-text", + "cancel_batch": "batch-api-fake-text", + "vector_store_create": "vector-store-api-fake-text", + } +) + + +def _user_message(content: object) -> list[dict[str, object]]: # mutable-ok: a fresh list, as each pick builds it + return [{"role": "user", "content": content}] + + +# Request keys the router reads to route the call; the deployment call never receives them. +ROUTING_KEYS: Final = frozenset( + { + "model", + "num_retries", + "disable_fallbacks", + "specific_deployment", + "_router_weights", + "_retry_skipped_deployment_ids", + "_excluded_deployment_ids", + "_target_order", + "original_function", + # The walk's own settings, which `async_function_with_fallbacks` pops before the attempt. + "model_group_retry_policy", + "fallbacks", + "context_window_fallbacks", + "content_policy_fallbacks", + "mock_testing_fallbacks", + "mock_testing_context_fallbacks", + "mock_testing_content_policy_fallbacks", + "mock_testing_rate_limit_error", + } +) + + +@dataclasses.dataclass(frozen=True, slots=True) +class Plan: + """How one endpoint runs its routed attempts.""" + + endpoint: str + host_op: str + kind: Kind + sync: bool = False + # The bucket `_update_kwargs_before_fallbacks` writes the requested group into; None for the + # endpoints that write `metadata.model_group` alone (no trace id, no alias). + prepare_field: str | None = "metadata" + function_name: str | None = None + splits_stream_timeout: bool = False + stamp: Stamp = "retry_skip" + total_key: CountKey | None = "deployment" + success_key: CountKey | None = "deployment" + fail_key: CountKey | None = "deployment" + # One attempt, no retries and no fallbacks. + single_attempt: bool = False + # The named parameter the endpoint takes beside **kwargs, sent between the deployment params and + # the request (`{**data, name: value, **kwargs}`). + named: tuple[str, ...] = () + + @property + def on_its_own_loop(self) -> bool: + """``function_with_fallbacks`` runs these sync endpoints' whole walk on a private event loop.""" + return self.sync and self.kind in ("chat", "embedding", "image") + + def pick_input(self, request: Mapping[str, object]) -> tuple[object, object]: + """The ``messages`` and ``input`` the endpoint's attempt helper hands its pick, which every + selection stage reads: the pre-call checks run when either is set.""" + match self.kind: + case "chat": + return request.get("messages"), None + case "text": + return _user_message(request.get("prompt")), None + case "embedding": + return None, request.get("input") + case "rerank" | "moderation" | "search": + return None, None + case "generic" | "generic_sync": + return request.get("messages"), request.get("input") + case _: + return _user_message(_PICK_TEXTS[self.kind]), None + + @property + def sets_headers(self) -> bool: + """Whether the response gets the router's headers (the sync generic wrapper adds none).""" + return self.kind != "generic_sync" + + @property + def stamps_failed_deployment(self) -> bool: + """Whether the attempt stamps ``failed_deployment_id`` on its error, which weighted failover + reads: every endpoint but file and batch creation (whose result belongs to the deployment + that served it), moderation's pass-through and search.""" + return self.kind not in ("batch", "cancel_batch", "create_file", "moderation", "search") + + @property + def metadata_field(self) -> str: + """Where `_update_kwargs_with_deployment` writes the deployment it routed to.""" + return get_router_metadata_variable_name(function_name=self.function_name) + + +def _generic(endpoint: str, host_op: str | None = None, *, sync: bool = False) -> Plan: + if sync: + return Plan( + endpoint=endpoint, + host_op=host_op or endpoint, + kind="generic_sync", + sync=True, + prepare_field="litellm_metadata", + function_name="generic_api_call", + splits_stream_timeout=_handler_name(host_op or endpoint) in STREAM_TIMEOUT_AWARE_GENERIC_HANDLERS, + stamp="none", + fail_key="group", + single_attempt=True, + ) + return Plan( + endpoint=endpoint, + host_op=host_op or endpoint, + kind="generic", + prepare_field="litellm_metadata", + function_name="_ageneric_api_call_with_fallbacks", + splits_stream_timeout=_handler_name(host_op or endpoint) in STREAM_TIMEOUT_AWARE_GENERIC_HANDLERS, + stamp="deployment", + fail_key="group", + ) + + +def _handler_name(host_op: str) -> str: + return host_op.rsplit(".", 1)[-1] + + +def invoked_handler_name(core: EndpointCore, plan: Plan) -> str | None: + """The generic handler's ``__name__`` (`original_generic_function.__name__`): the function the + host serves for the op, which decides the stream-timeout split and the responses socket.""" + function: Final[object] = core.host.invoke(plan.host_op) # pyright: ignore[reportUnknownMemberType] # the core's host + name: Final[object] = getattr(function, "__name__", None) + return name if isinstance(name, str) else None + + +# The endpoints whose attempt helper runs inside `make_call`'s `endpoint_selection`, under the +# name of its `original_function`. +_SELECTION_CALLS: Final[Mapping[str, str]] = MappingProxyType( + { + "acompletion": "_acompletion", + "completion": "_completion", + "atext_completion": "_atext_completion", + } +) + + +def selection_endpoint(core: EndpointCore, plan: Plan) -> str | None: + """The endpoint ``endpoint_selection`` names around the plan's pick. A sync generic call never + reaches ``make_call``, and a generic attempt reads the handler's name and module.""" + call: Final = _SELECTION_CALLS.get(plan.endpoint) + if call is not None: + return endpoint_for_call(call) + if plan.kind != "generic": + return None + function: Final[object] = core.host.invoke(plan.host_op) # pyright: ignore[reportUnknownMemberType] # the core's host + return endpoint_for_call(getattr(function, "__name__", None), getattr(function, "__module__", None)) + + +PLANS: Final[Mapping[str, Plan]] = MappingProxyType( + { + "acompletion": Plan( + "acompletion", "acompletion", "chat", splits_stream_timeout=True, stamp="deployment", named=("messages",) + ), + "completion": Plan( + "completion", + "completion", + "chat", + sync=True, + splits_stream_timeout=True, + stamp="deployment", + total_key=None, + success_key=None, + fail_key=None, + named=("messages",), + ), + "atext_completion": Plan( + "atext_completion", + "atext_completion", + "text", + splits_stream_timeout=True, + fail_key="group", + named=("prompt",), + ), + # `_asearch_with_fallbacks`: the search tool name routes as the model, with no deployment + # picked; its helper picks among the router's search tools. + "asearch": Plan( + "asearch", + "search.asearch", + "search", + prepare_field="litellm_metadata", + stamp="none", + total_key=None, + success_key=None, + fail_key=None, + ), + "aembedding": Plan("aembedding", "aembedding", "embedding", named=("input",)), + "embedding": Plan("embedding", "embedding", "embedding", sync=True, named=("input",)), + "aimage_generation": Plan("aimage_generation", "aimage_generation", "image", named=("prompt",)), + "image_generation": Plan( + "image_generation", + "image_generation", + "image", + sync=True, + prepare_field=None, + total_key="empty", + success_key="empty", + fail_key="empty", + named=("prompt",), + ), + "atranscription": Plan( + "atranscription", + "atranscription", + "transcription", + total_key="group", + success_key="group", + fail_key="group", + named=("file",), + ), + "aspeech": Plan( + "aspeech", + "aspeech", + "speech", + total_key="group", + success_key="group", + fail_key="group", + named=("input",), + ), + "arerank": Plan("arerank", "arerank", "rerank"), + "aadapter_completion": Plan( + "aadapter_completion", + "aadapter_completion", + "adapter", + prepare_field=None, + splits_stream_timeout=True, + fail_key="group", + ), + "acreate_batch": Plan( + "acreate_batch", + "acreate_batch", + "batch", + prepare_field="litellm_metadata", + function_name="_acreate_batch", + fail_key="group", + ), + "acancel_batch": Plan( + "acancel_batch", + "acancel_batch", + "cancel_batch", + prepare_field="litellm_metadata", + function_name="_acancel_batch", + fail_key="group", + ), + "acreate_file": Plan( + "acreate_file", + "acreate_file", + "create_file", + function_name="acreate_file", + stamp="none", + total_key=None, + success_key=None, + fail_key="group", + ), + "avector_store_create": Plan( + "avector_store_create", + "vector_stores.acreate", + "vector_store_create", + prepare_field=None, + function_name="avector_store_create", + stamp="none", + fail_key="group", + single_attempt=True, + ), + "amoderation": Plan( + "amoderation", + "amoderation", + "moderation", + stamp="none", + total_key=None, + success_key=None, + fail_key=None, + single_attempt=True, + ), + # The Python router's anthropic messages host op is `anthropic_messages`. + "aanthropic_messages": _generic("aanthropic_messages", "anthropic_messages"), + "anthropic_messages": _generic("anthropic_messages", "anthropic_messages"), + "aresponses": _generic("aresponses"), + "responses": _generic("responses", sync=True), + } +) + +# --- the generic endpoints ------------------------------------------------------------------ + +# endpoint -> host op, for the async generic endpoints routed through +# `_ageneric_api_call_with_fallbacks` when they carry a model. +_HOST_GENERIC: Final[Mapping[str, str]] = MappingProxyType( + { + "afile_delete": "afile_delete", + "afile_content": "afile_content", + "afile_list": "afile_list", + "aget_responses": "aget_responses", + "acancel_responses": "acancel_responses", + "acompact_responses": "acompact_responses", + "adelete_responses": "adelete_responses", + "alist_input_items": "alist_input_items", + "_arealtime": "_arealtime", + "acreate_realtime_client_secret": "acreate_realtime_client_secret", + "arealtime_calls": "arealtime_calls", + "acreate_realtime_transcription_session": "acreate_realtime_transcription_session", + "acreate_realtime_translation_client_secret": "acreate_realtime_translation_client_secret", + "arealtime_translation_calls": "arealtime_translation_calls", + "_aresponses_websocket": "_aresponses_websocket", + "acreate_fine_tuning_job": "acreate_fine_tuning_job", + "acancel_fine_tuning_job": "acancel_fine_tuning_job", + "alist_fine_tuning_jobs": "alist_fine_tuning_jobs", + "aretrieve_fine_tuning_job": "aretrieve_fine_tuning_job", + "aimage_edit": "aimage_edit", + "allm_passthrough_route": "allm_passthrough_route", + "acreate_skill": "acreate_skill", + "alist_skills": "alist_skills", + "aget_skill": "aget_skill", + "adelete_skill": "adelete_skill", + "agenerate_content": "google_genai.agenerate_content", + "agenerate_content_stream": "google_genai.agenerate_content_stream", + "aocr": "ocr.aocr", + "adecisions": "decisions.adecisions", + "asystemone": "systemone.asystemone", + "aextraction": "extraction.aextraction", + **{f"avideo_{name}": f"videos.avideo_{name}" for name in ("generation", "list", "status", "content", "remix")}, + **{ + name: f"containers.{name}" + for name in ("acreate_container", "alist_containers", "aretrieve_container", "adelete_container") + }, + **{ + name: f"containers.endpoint_factory._generated_endpoints.{name}" + for name in ( + "aupload_container_file", + "alist_container_files", + "aretrieve_container_file", + "adelete_container_file", + "aretrieve_container_file_content", + ) + }, + **{ + f"avector_store_{name}": f"vector_stores.main.a{name}" + for name in ("search", "retrieve", "list", "update", "delete") + }, + **{ + f"avector_store_file_{name}": f"vector_store_files.main.a{target}" + for name, target in ( + ("create", "create"), + ("list", "list"), + ("retrieve", "retrieve"), + ("content", "retrieve_content"), + ("update", "update"), + ("delete", "delete"), + ) + }, + "acreate_interaction": "interactions.acreate", + "aget_interaction": "interactions.aget", + "adelete_interaction": "interactions.adelete", + "acancel_interaction": "interactions.acancel", + } +) + +_SYNC_GENERIC: Final[Mapping[str, str]] = MappingProxyType( + { + "generate_content": "google_genai.generate_content", + "generate_content_stream": "google_genai.generate_content_stream", + "ocr": "ocr.ocr", + # The sync wrapper routes a search tool name as a model group, unlike `asearch`. + "search": "search.search", + "decisions": "decisions.decisions", + "systemone": "systemone.systemone", + "extraction": "extraction.extraction", + **{f"video_{name}": f"videos.video_{name}" for name in ("generation", "list", "status", "content", "remix")}, + **{ + name: f"containers.{name}" + for name in ("create_container", "list_containers", "retrieve_container", "delete_container") + }, + **{ + f"vector_store_{name}": f"vector_stores.main.{name}" + for name in ("search", "create", "retrieve", "list", "update", "delete") + }, + } +) + +_CONTAINER_FILE_ROUTED: Final = frozenset( + { + "aupload_container_file", + "alist_container_files", + "aretrieve_container_file", + "adelete_container_file", + "aretrieve_container_file_content", + } +) +_VIDEO_DIRECT: Final = frozenset({"avideo_create_character", "avideo_get_character", "avideo_edit", "avideo_extension"}) +_SYNC_VIDEO_UNBRANCHED: Final = frozenset( + {"video_create_character", "video_get_character", "video_edit", "video_extension"} +) +_SYNC_CONTAINER_FILES_UNBRANCHED: Final = frozenset( + { + "upload_container_file", + "list_container_files", + "retrieve_container_file", + "delete_container_file", + "retrieve_container_file_content", + } +) +_UNBRANCHED: Final = frozenset( + { + "aadapter_generate_content", + *_SYNC_VIDEO_UNBRANCHED, + *_SYNC_CONTAINER_FILES_UNBRANCHED, + "get_interaction", + "delete_interaction", + "cancel_interaction", + } +) +_ASSISTANTS: Final = frozenset( + { + "acreate_assistants", + "adelete_assistant", + "aget_assistants", + "acreate_thread", + "aget_thread", + "a_add_message", + "aget_messages", + "arun_thread", + } +) +_MANAGED_AGENTS: Final[Mapping[str, str]] = MappingProxyType( + { # comprehension-ok: a flat walk of nested rows + f"{prefix}{name}": f"interactions.agents.{prefix}{target}" + for prefix in ("a", "") + for name, target in ( + ("create_agent", "create"), + ("list_agents", "list"), + ("get_agent", "get"), + ("delete_agent", "delete"), + ("list_agent_versions", "list_versions"), + ) + } +) +_SYNC_VECTOR_STORE_FILES: Final[Mapping[str, str]] = MappingProxyType( + { + f"vector_store_file_{name}": f"vector_store_files.main.{target}" + for name, target in ( + ("create", "create"), + ("list", "list"), + ("retrieve", "retrieve"), + ("content", "retrieve_content"), + ("update", "update"), + ("delete", "delete"), + ) + } +) + + +def plan_for(endpoint: str) -> Plan: + plan: Final = generic_plan(endpoint) + if plan is None: + raise KeyError(endpoint) + return plan + + +def generic_plan(endpoint: str) -> Plan | None: + if endpoint in PLANS: + return PLANS[endpoint] + if endpoint in _HOST_GENERIC: + return _generic(endpoint, _HOST_GENERIC[endpoint]) + if endpoint in _VIDEO_DIRECT: + return _generic(endpoint, f"videos.{endpoint}") + if endpoint in _SYNC_GENERIC: + return _generic(endpoint, _SYNC_GENERIC[endpoint], sync=True) + return None + + +# --- preparing the request ------------------------------------------------------------------- + + +def prepare_request( + plan: Plan, request: Mapping[str, object], model: str, aliases: Mapping[str, object] +) -> dict[str, object]: # mutable-ok: the call's kwargs + """What the router adds once before the first attempt (`_update_kwargs_before_fallbacks`): a + trace id and the requested group, in the caller's own metadata dict.""" + prepared: Final = dict(request) + if plan.kind == "vector_store_create": + return prepared # routed straight to a deployment, with no group recorded + if plan.prepare_field is None: + metadata_bucket(prepared, "metadata").update({"model_group": model}) + return prepared + prepared.setdefault("litellm_trace_id", str(uuid.uuid4())) + metadata_bucket(prepared, plan.prepare_field).update( + {"model_group": model, "model_group_alias": model if model in aliases else None} + ) + return prepared + + +# --- one attempt ---------------------------------------------------------------------------- + + +@dataclasses.dataclass(slots=True) +class AttemptCall: + """One attempt's host call: the op, its kwargs, and the request kwargs the router kept (the + ones its response headers are read from).""" + + host_op: str + kwargs: Mapping[str, object] + served: Mapping[str, object] + model_name: str + group: str + # `_embedding`'s batch-size refusal, raised by the driver in place of the host call. + refused: Exception | None = None + + +def reports_own_success(call: AttemptCall) -> bool: + """A realtime attempt's return says nothing about the session (a dropped one returns too), so + the host counts its success itself (`clean_realtime_session_deployment`).""" + return call.host_op == "_arealtime" + + +def clean_realtime_session_deployment(call: AttemptCall) -> str | None: + """`_ageneric_api_call_with_fallbacks`: the deployment a finished `_arealtime` session counts a + success against, when its success handlers ran and it did not end abnormally.""" + from litellm.constants import REALTIME_SESSION_ENDED_ABNORMALLY_KEY, REALTIME_SESSION_SUCCESS_LOGGED_KEY + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging + + session_logging: Final = call.kwargs.get("litellm_logging_obj") + if not reports_own_success(call) or not isinstance(session_logging, LiteLLMLogging): + return None + details: Final = session_logging.model_call_details + if details.get(REALTIME_SESSION_SUCCESS_LOGGED_KEY) is not True: + return None + if details.get(REALTIME_SESSION_ENDED_ABNORMALLY_KEY) is True: + return None + deployment_id: Final = as_dict(call.kwargs.get("model_info")).get("id") + return None if deployment_id is None else str(deployment_id) + + +# `_scheduler` once `del router.scheduler` ran (None is a scheduler not built yet). +_NO_SCHEDULER: Final = object() + + +class Counters: + """`total_calls`, `success_calls` and `fail_calls`, keyed as each endpoint keys them.""" + + __slots__ = ("fail_calls", "success_calls", "total_calls") + + def __init__(self) -> None: + self.total_calls: defaultdict[str, int] = defaultdict(int) # mutable-ok: the router's live counters + self.success_calls: defaultdict[str, int] = defaultdict(int) # mutable-ok: same + self.fail_calls: defaultdict[str, int] = defaultdict(int) # mutable-ok: same + + @staticmethod + def _key(which: CountKey, model_name: str, group: str) -> str: + return model_name if which == "deployment" else group if which == "group" else "" + + def started(self, plan: Plan, call: AttemptCall) -> None: + if plan.total_key is not None: + self.total_calls[self._key(plan.total_key, call.model_name, call.group)] += 1 + + def succeeded(self, plan: Plan, call: AttemptCall) -> None: + if plan.success_key is not None: + self.success_calls[self._key(plan.success_key, call.model_name, call.group)] += 1 + + def retract_success(self, plan: Plan, call: AttemptCall) -> None: + """A served response the router then raised over: the attempt helper never reached its count.""" + if plan.success_key is not None: + self.success_calls[self._key(plan.success_key, call.model_name, call.group)] -= 1 + + def failed(self, plan: Plan, model_name: str | None, group: str) -> None: + if plan.fail_key is None: + return + if plan.fail_key == "deployment" and model_name is None: + return + self.fail_calls[self._key(plan.fail_key, model_name or "", group)] += 1 + + +def _compaction_surface(core: EndpointCore, plan: Plan) -> Surface | None: + """``surface_for_call`` over the function the Python router's fallback loop is handed.""" + if plan.kind == "generic" and surface_for_call(_handler_name(plan.host_op)) is not None: + return surface_for_call(invoked_handler_name(core, plan) or "") + return "chat" if plan.kind == "chat" and not plan.sync else None + + +def arm_compaction_state( + core: EndpointCore, + plan: Plan, + request: dict[str, object], # mutable-ok: the request kwargs, written in place as the Python router writes them +) -> None: + """``initialize_compaction_state`` at the top of ``async_function_with_fallbacks``.""" + surface: Final = _compaction_surface(core, plan) + if surface is not None: + request["_context_compaction_state"] = initialize_compaction_state(request, surface) # rebind-ok: its own + + +async def compacted_attempt( + core: EndpointCore, plan: Plan, deployment: Mapping[str, object], call: "AttemptCall" +) -> Mapping[str, object]: + """The attempt's kwargs after ``compact_to_fit``, which ``_acompletion`` and the generic helper + run on every attempt: it is also what refuses a compactor's own oversized child call.""" + if plan.kind != "generic" and (plan.kind != "chat" or plan.sync): + return call.kwargs + ctx: Final = RoutingContext(core.router) # pyright: ignore[reportArgumentType] # the checks read registry(), settings() and the token count + return await compact_to_fit(ctx, deployment, call.kwargs, _compaction_surface(core, plan)) + + +def attempt_call( + core: EndpointCore, + plan: Plan, + request: Mapping[str, object], + deployment: Mapping[str, object], + *, + group: str, + requested: str, + fallback_level: int = 0, +) -> AttemptCall: + """The host call for one attempt of ``plan`` against ``deployment``: the request (as the attempt + helper receives it), shaped for the deployment and merged with its litellm params.""" + shaping: Final = core.shaping + kwargs: Final = without(request, *ROUTING_KEYS) + named: Final = {name: kwargs.pop(name) for name in plan.named if name in kwargs} + data: Final = as_dict(deployment.get("litellm_params")) + model_name: Final = str(data.get("model")) + cache: Final = core.routing_cache + caching: Final = shaping.cache_responses + # A fallback hop routes the target group in a copy of the metadata (`run_async_fallback`). + if fallback_level > 0: + field: Final = plan.prepare_field or "metadata" + kwargs[field] = {**as_dict(kwargs.get(field)), "model_group": requested} + match plan.kind: + case "chat": + host = core.host # rebind-ok: rebound as the Python router rebinds it + drop_unsupported_classifier_reasoning_effort(deployment, requested, kwargs, host) + params = ( # rebind-ok: rebound as the Python router rebinds it + deployment_params_with_request_reasoning_override(data, kwargs) + ) + silent_model = params.pop("silent_model", None) # rebind-ok: rebound as the Python router rebinds it + start_silent_experiments(core, plan, silent_model, named.get("messages"), kwargs) + if "messages" in named: + kwargs.setdefault("messages", named["messages"]) + update_kwargs_with_deployment(shaping, deployment, kwargs, cache=cache, splits_stream_timeout=True) + kwargs.pop("silent_model", None) + final = without_router_only_kwargs( # rebind-ok: rebound as the Python router rebinds it + { + **params, + **named, + "caching": caching, + "client": model_client(core, plan, deployment, kwargs), + **kwargs, + } + ) + return AttemptCall(plan.host_op, final, kwargs, str(params.get("model")), group) + case "text" | "embedding" | "image" | "transcription" | "rerank" | "adapter": + update_kwargs_with_deployment( + shaping, deployment, kwargs, cache=cache, splits_stream_timeout=plan.splits_stream_timeout + ) + refused: Final = embedding_batch_refusal(plan, deployment, named.get("input"), kwargs, requested) + if refused is not None: + return AttemptCall(plan.host_op, kwargs, kwargs, model_name, group, refused) + final = { # rebind-ok: rebound as the Python router rebinds it + **data, + **named, + "caching": caching, + "client": model_client(core, plan, deployment, kwargs), + **kwargs, + } + return AttemptCall(plan.host_op, without_router_only_kwargs(final), kwargs, model_name, group) + case "speech": + update_kwargs_with_deployment(shaping, deployment, kwargs, cache=cache) + voice = kwargs.pop("voice", None) # rebind-ok: rebound as the Python router rebinds it + final = { # rebind-ok: rebound as the Python router rebinds it + **data, + **named, + "voice": data.get("voice") if voice is None else voice, + "client": model_client(core, plan, deployment, kwargs), + **kwargs, + } + return AttemptCall(plan.host_op, final, kwargs, model_name, group) + case "batch" | "cancel_batch" | "vector_store_create": + if plan.kind == "cancel_batch": + data.update(_resolved_credentials(core, deployment, requested)) + data.pop("litellm_credential_name", None) + update_kwargs_with_deployment(shaping, deployment, kwargs, cache=cache, function_name=plan.function_name) + final = { # rebind-ok: rebound as the Python router rebinds it + **data, + "custom_llm_provider": _provider(core, data), + "caching": caching, + "client": model_client(core, plan, deployment, kwargs), + **kwargs, + } + return AttemptCall(plan.host_op, final, kwargs, str(data.get("model")), group) + case "generic": + return _generic_attempt(core, plan, kwargs, deployment, data, requested, group) + case "generic_sync": + update_kwargs_with_deployment( + shaping, + deployment, + kwargs, + cache=cache, + function_name="generic_api_call", + splits_stream_timeout=invoked_handler_name(core, plan) in STREAM_TIMEOUT_AWARE_GENERIC_HANDLERS, + ) + endpoint = kwargs.get("endpoint") # rebind-ok: rebound as the Python router rebinds it + if endpoint and isinstance(endpoint, str): + kwargs["endpoint"] = endpoint.replace(requested, model_name) + kwargs["model"] = model_name + final = { # rebind-ok: rebound as the Python router rebinds it + **data, + "custom_llm_provider": _generic_provider(data), + "caching": caching, + **kwargs, + } + return AttemptCall(plan.host_op, final, kwargs, model_name, group) + case "moderation": + update_kwargs_with_deployment(shaping, deployment, kwargs, cache=cache) + kwargs["model"] = model_name + kwargs.update(data) + return AttemptCall(plan.host_op, kwargs, kwargs, model_name, group) + case "search": + return _search_attempt(core, plan, kwargs, group) + case "create_file": + # `_acreate_file` creates the file on every healthy deployment of the hop's name, not + # only the picked one: the driver hands the request to `create_file_everywhere`. + return AttemptCall(plan.host_op, kwargs, kwargs, requested, group) + + +def _generic_attempt( + core: EndpointCore, + plan: Plan, + kwargs: dict[str, object], # mutable-ok: the attempt's own kwargs + deployment: Mapping[str, object], + data: dict[str, object], # mutable-ok: the attempt's copy of the deployment params + requested: str, + group: str, +) -> AttemptCall: + """`_ageneric_api_call_with_fallbacks_helper` for one deployment.""" + from litellm.llms.base_llm.passthrough.transformation import replace_path_segment + from litellm.router_rust.invoke.websocket import turn_admission + + handler: Final = invoked_handler_name(core, plan) + socket: Final = handler == "_aresponses_websocket" + update_kwargs_with_deployment( + core.shaping, + deployment, + kwargs, + cache=core.routing_cache, + function_name="_ageneric_api_call_with_fallbacks", + splits_stream_timeout=handler in STREAM_TIMEOUT_AWARE_GENERIC_HANDLERS, + opens_responses_socket=socket, + ) + model_name: Final = str(data.get("model")) + endpoint: Final = kwargs.get("endpoint") + if endpoint: + try: + stripped, _, _, _ = core.host.invoke("get_llm_provider")( + model=model_name, + custom_llm_provider=kwargs.get("custom_llm_provider"), + api_base=kwargs.get("api_base"), + ) + replacement = str(stripped) # rebind-ok: rebound as the Python router rebinds it + except Exception: # noqa: BLE001 # as the Python router: an unresolvable model is used as is + replacement = model_name # rebind-ok: rebound as the Python router rebinds it + kwargs["endpoint"] = ( # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + replace_path_segment(str(endpoint), requested, replacement) + ) + provider: Final = _generic_provider(data) + final: Final = { + **without_retrieve_stream_defaults(data, kwargs), + "caching": core.shaping.cache_responses, + **kwargs, + "model": model_name, + **_session_with_model(kwargs.get("session"), model_name), + **({"turn_admission": turn_admission(core, requested, deployment, kwargs)} if socket else {}), + } + if provider is not None: + final["custom_llm_provider"] = provider + return AttemptCall(plan.host_op, final, kwargs, model_name, group) + + +_SEARCH_PROTECTED_PARAMS: Final = frozenset({"search_provider", "api_key", "api_base"}) + + +def _search_attempt( + core: EndpointCore, + plan: Plan, + kwargs: dict[str, object], # mutable-ok: the attempt's own kwargs + group: str, +) -> AttemptCall: + """`SearchAPIRouter.async_search_with_fallbacks_helper`: one of the search tools named + ``group`` at random, called with its provider, credentials and params under the request's.""" + import random + + tools: Final = [tool for tool in core.endpoints.search_tools if as_dict(tool).get("search_tool_name") == group] + if not tools: + raise ValueError(f"Search tool '{group}' not found in router.search_tools") + selected: Final = random.choice(tools) # load balancing, as the Python router picks + params: Final = as_dict(as_dict(selected).get("litellm_params")) + search_provider: Final = params.get("search_provider") + if not search_provider: + raise ValueError(f"search_provider not found in litellm_params for search tool '{group}'") + search_params: Final = { + key: value + for source in (params, kwargs) + for key, value in source.items() + if key not in _SEARCH_PROTECTED_PARAMS and value is not None + } # comprehension-ok: the tool's params, then the request's + final: Final = { + "search_provider": search_provider, + "api_key": params.get("api_key"), + "api_base": params.get("api_base"), + **search_params, + } + return AttemptCall(plan.host_op, final, kwargs, group, group) + + +def unrouted_fields(plan: Plan) -> Mapping[str, object]: + """A search tool name is no model group: the Rust core hands every attempt to the host as is.""" + return {"unrouted": True} if plan.kind == "search" else {} + + +def failover_fields(plan: Plan) -> Mapping[str, object]: + """An endpoint whose attempt stamps no ``failed_deployment_id`` never runs weighted failover.""" + return {} if plan.stamps_failed_deployment else {"skip_weighted_failover": True} + + +# The Python router's handler names for the plans whose `function_name` differs from it. +_PYTHON_HANDLER_NAMES: Final[Mapping[str, str]] = MappingProxyType({"acreate_file": "_acreate_file"}) + + +def scoped_fallback_fields(plan: Plan, request: Mapping[str, object]) -> Mapping[str, object]: + """A request that creates or names a resource only one provider holds (a file upload, a batch + on an uploaded file, a fine-tuning job) falls back within its own model group only + (``run_async_fallback``'s ``same_model_group_only``), decided by the Python router's own rules.""" + from litellm.router_utils.fallback_event_handlers import ( + creates_provider_scoped_resource, + references_provider_scoped_resource, + ) + + function_name: Final = plan.function_name or plan.host_op + handlers: Final = { + "original_function": _Handler(_PYTHON_HANDLER_NAMES.get(function_name, function_name)), + "original_generic_function": _Handler(plan.host_op), + } + kwargs: Final = {**request, **handlers} + scoped: Final = references_provider_scoped_resource(kwargs) or creates_provider_scoped_resource(kwargs) + return {"same_group_fallbacks_only": True} if scoped else {} + + +@dataclasses.dataclass(frozen=True, slots=True) +class _Handler: + """A stand-in for a handler function: the scoped-resource rules read only its name.""" + + __name__: str + + +def _session_with_model(session: object, model_name: str) -> Mapping[str, object]: + if not isinstance(session, Mapping): + return {} + typed: Final = as_dict(session) # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + if "model" not in typed and typed.get("type") != "transcription": + return {} + from litellm.realtime_api.main import with_resolved_session_model + + return {"session": with_resolved_session_model(typed, model_name)} + + +def _generic_provider(data: Mapping[str, object]) -> str | None: + from litellm.litellm_core_utils.routing_common_utils import provider_for_generic_call + + return provider_for_generic_call(data) # pyright: ignore[reportArgumentType] # deployment params + + +def model_client( + core: EndpointCore, plan: Plan, deployment: Mapping[str, object], kwargs: Mapping[str, object] +) -> object: + """The SDK client cached for the deployment (`_get_async_openai_model_client`; `_get_client` + with the sync keys for sync completion and embedding), dropped when the request carries + another api key.""" + from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs + + if as_dict(deployment.get("litellm_params")).get("kubernetes_pod_discovery") is True: + return None + model_id: Final = as_dict(deployment.get("model_info")).get("id") + sync_keys: Final = plan.sync and plan.kind in ("chat", "embedding") + stream: Final = "stream_" if kwargs.get("stream") is True else "" + key: Final = f"{model_id}_{stream}client" if sync_keys else f"{model_id}_{stream}async_client" + span: Final = get_parent_otel_span_from_kwargs(dict(kwargs)) + client: Final = _cached_client(core, key, span, local_only=not sync_keys) + dynamic_api_key: Final = kwargs.get("api_key") + if dynamic_api_key is not None and client is not None and dynamic_api_key != getattr(client, "api_key", None): + return None + return client + + +def _cached_client(core: EndpointCore, key: str, span: object, *, local_only: bool) -> object: + cache: Final = core.routing_cache + with service_target(ROUTER_CLIENTS_TARGET): + if local_only: + return cache.get_cache(key=key, local_only=True, parent_otel_span=span) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType, reportArgumentType] # the cache holds untyped values + return cache.get_cache(key=key, parent_otel_span=span) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType, reportArgumentType] # see above + + +def _provider(core: EndpointCore, data: Mapping[str, object]) -> object: + """The deployment's declared provider, else the one its model names (`get_llm_provider`).""" + declared: Final = data.get("custom_llm_provider") + _, inferred, _, _ = core.host.invoke("get_llm_provider")(model=data["model"], custom_llm_provider=declared) + return declared or inferred + + +def _resolved_credentials(core: EndpointCore, deployment: Mapping[str, object], requested: str) -> Mapping[str, object]: + """`get_deployment_credentials_with_provider` for the picked deployment (`_acancel_batch`).""" + registry: Final = core.registry() + model_id: Final = as_dict(deployment.get("model_info")).get("id") + resolved: Final = registry.credentials(str(model_id or requested), form="with_provider") + return as_dict(resolved) # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + + +def embedding_batch_refusal( + plan: Plan, deployment: Mapping[str, object], input: object, kwargs: Mapping[str, object], model: str +) -> Exception | None: + """``_embedding``'s check, past the deployment's kwargs shaping: an input the deployment admits + drops the mark an earlier rejected attempt left on the shared logging object.""" + if plan.kind != "embedding": + return None + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging + from litellm.router_utils.embedding_batch_size_check import ( + clear_rejected_before_provider_call, + embedding_batch_too_large_error, + ) + + error: Final = embedding_batch_too_large_error( + deployment=deployment, + input=input, + request_kwargs=kwargs, + model=model, # pyright: ignore[reportArgumentType] # opaque values + ) + logging_obj: Final = kwargs.get("litellm_logging_obj") + if error is None and isinstance(logging_obj, LiteLLMLogging): + clear_rejected_before_provider_call(logging_obj) + return error + + +def log_refused_call_sync(call: AttemptCall, refused: Exception) -> None: + """``_embedding`` logs its refusal before raising it: no provider call will.""" + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging + from litellm.router_utils.embedding_batch_size_check import log_rejection_before_provider_call + + logging_obj: Final = call.kwargs.get("litellm_logging_obj") + if isinstance(logging_obj, LiteLLMLogging): + log_rejection_before_provider_call(logging_obj, refused) + + +async def log_refused_call(call: AttemptCall, refused: Exception) -> None: + """``log_refused_call_sync`` for ``_aembedding``.""" + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging + from litellm.router_utils.embedding_batch_size_check import async_log_rejection_before_provider_call + + logging_obj: Final = call.kwargs.get("litellm_logging_obj") + if isinstance(logging_obj, LiteLLMLogging): + await async_log_rejection_before_provider_call(logging_obj, refused) + + +def stamp_error( + plan: Plan, error: BaseException, deployment: Mapping[str, object], kwargs: Mapping[str, object] +) -> None: + """What each attempt helper stamps on the error it raises.""" + match plan.stamp: + case "deployment": + stamp_deployment_num_retries(error, deployment) + stamp_failed_deployment_id(error, kwargs.get("model_info") or deployment.get("model_info")) + case "retry_skip": + stamp_retry_skip_deployment_id(error, kwargs) + case "none": + pass + if plan.stamp != "deployment" and plan.stamps_failed_deployment: + # `_stamp_failed_attempt`: the deployment `_update_kwargs_with_deployment` put on the kwargs. + stamp_failed_deployment_id(error, kwargs.get("model_info")) + + +# --- silent experiments --------------------------------------------------------------------- + + +_SilentModel: TypeAlias = str | list[str] +_SILENT_MODEL_ADAPTER: Final[TypeAdapter[_SilentModel]] = TypeAdapter(_SilentModel) + + +def _silent_targets(silent_model: object) -> tuple[str, ...]: + """`_silent_experiment_targets`: none inside a mirrored call or for a malformed value.""" + from litellm._internal_context import in_mirrored_call + + if silent_model is None or in_mirrored_call(): + return () + try: + targets: Final = _SILENT_MODEL_ADAPTER.validate_python(silent_model) + except ValidationError: + verbose_router_logger.warning( + "silent_model must be a model name or a list of model names, got %r; skipping shadow traffic", + silent_model, + ) + return () + return (targets,) if isinstance(targets, str) else tuple(targets) + + +def _silent_kwargs(kwargs: Mapping[str, object]) -> dict[str, object]: # mutable-ok: the experiment's own kwargs + """`_get_silent_experiment_kwargs`.""" + from litellm.litellm_core_utils.core_helpers import ( + safe_deep_copy, # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + ) + + silent: Final = safe_deep_copy(dict(kwargs)) # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + original_metadata: Final = kwargs.get("metadata") + if original_metadata is not None and silent.get("metadata") is original_metadata: # pyright: ignore[reportUnknownMemberType] # litellm's untyped helpers and request values + silent["metadata"] = dict(original_metadata) # pyright: ignore[reportArgumentType, reportCallIssue] # the request's metadata dict + if "metadata" not in silent: + silent["metadata"] = {} + metadata: Final = silent["metadata"] # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + if isinstance(metadata, dict): + metadata.pop("litellm_parent_otel_span", None) # pyright: ignore[reportUnknownMemberType] # the request's metadata dict + metadata["is_silent_experiment"] = True + silent.pop("litellm_call_id", None) # pyright: ignore[reportUnknownMemberType] # litellm's untyped helpers and request values + silent.pop("litellm_logging_obj", None) # pyright: ignore[reportUnknownMemberType] # litellm's untyped helpers and request values + silent.pop("standard_logging_object", None) # pyright: ignore[reportUnknownMemberType] # litellm's untyped helpers and request values + return silent # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + + +def _snapshot(kwargs: Mapping[str, object]) -> dict[str, object]: # mutable-ok: a snapshot handed to a background task + snapshot: Final = dict(kwargs) + metadata: Final = snapshot.get("metadata") + if isinstance(metadata, Mapping): + snapshot["metadata"] = dict(as_dict(metadata)) # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + return snapshot + + +async def _run_silent(core: EndpointCore, silent_model: str, messages: object, kwargs: Mapping[str, object]) -> None: + from litellm._internal_context import mirrored_call + + remaining: Final = without(kwargs, "stream") + with mirrored_call(): + response: Final = await core.acompletion( + model=silent_model, messages=messages, stream=bool(kwargs.get("stream", False)), **remaining + ) + from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper + + if not isinstance(response, CustomStreamWrapper): + return + async for _ in response: + pass + + +async def _silent_async(core: EndpointCore, silent_model: str, messages: object, kwargs: Mapping[str, object]) -> None: + try: + if as_dict(kwargs.get("metadata")).get("is_silent_experiment", False): + return + silent: Final = _silent_kwargs(kwargs) + as_dict_metadata: Final = silent["metadata"] + if isinstance(as_dict_metadata, dict): + as_dict_metadata["model_group"] = silent_model + await _run_silent(core, silent_model, copy.deepcopy(messages), silent) + except Exception: # noqa: BLE001, S110 # a silent experiment never fails the primary call + pass + + +def _silent_thread(core: EndpointCore, silent_model: str, messages: object, kwargs: Mapping[str, object]) -> None: + try: + if as_dict(kwargs.get("metadata")).get("is_silent_experiment", False): + return + silent: Final = _silent_kwargs(kwargs) + metadata: Final = silent["metadata"] + if isinstance(metadata, dict): + metadata["model_group"] = silent_model + loop: Final = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + try: + + async def run() -> None: + await _run_silent(core, silent_model, copy.deepcopy(messages), silent) + pending: Final = asyncio.all_tasks() + current: Final = asyncio.current_task() + if current is not None: + pending.discard(current) + if pending: + await asyncio.gather(*pending, return_exceptions=True) + + loop.run_until_complete(run()) + finally: + loop.close() + except Exception: # noqa: BLE001, S110 # a silent experiment never fails the primary call + pass + + +def start_silent_experiments( + core: EndpointCore, plan: Plan, silent_model: object, messages: object, kwargs: Mapping[str, object] +) -> None: + """Mirror the call to each silent model in the background: a task on the async path, a daemon + thread on the sync one.""" + for target in _silent_targets(silent_model): + if plan.sync: + threading.Thread( + target=_silent_thread, args=(core, target, messages, _snapshot(kwargs)), daemon=True + ).start() + else: + _ = asyncio.create_task( + _silent_async(core, target, messages, _snapshot(kwargs)) + ) # fire and forget, as the Python router + + +# --- the endpoints ---------------------------------------------------------------------------- + +_KEEPS_CLIENT: Final = frozenset( + { + "acreate_realtime_client_secret", + "arealtime_calls", + "acreate_realtime_transcription_session", + "acreate_realtime_translation_client_secret", + "arealtime_translation_calls", + } +) +_KEEPS_PROVIDER_AND_CLIENT: Final = frozenset({"afile_delete", "afile_content"}) +_RESPONSE_ID_ENDPOINTS: Final = frozenset( + {"aget_responses", "acancel_responses", "acompact_responses", "adelete_responses", "alist_input_items"} +) +_CONTAINER_ENDPOINTS: Final = frozenset( + {"acreate_container", "alist_containers", "aretrieve_container", "adelete_container", *_CONTAINER_FILE_ROUTED} +) +_VECTOR_STORE_ENDPOINTS: Final = frozenset( + { + *(f"avector_store_{name}" for name in ("search", "create", "retrieve", "list", "update", "delete")), + *(f"avector_store_file_{name}" for name in ("create", "list", "retrieve", "content", "update", "delete")), + } +) +_INTERACTION_ENDPOINTS: Final = frozenset( + {"acreate_interaction", "aget_interaction", "adelete_interaction", "acancel_interaction"} +) +_MISSING: Final = object() + + +def pinned_video_deployment(plan: Plan, request: Mapping[str, object]) -> Mapping[str, object]: + """`_video_call_pin`: the deployment a video id names, for a call on that video only.""" + from litellm.types.videos.utils import VIDEO_ID_CALL_TYPES, decode_video_id_with_provider + + video_id: Final = request.get("video_id") + if plan.endpoint not in VIDEO_ID_CALL_TYPES or not isinstance(video_id, str): + return {} + deployment_id: Final = decode_video_id_with_provider(video_id).get("deployment_id") + return {"pinned_deployment_id": deployment_id} if deployment_id else {} + + +async def _await(value: object) -> object: + """``await value``, raising the TypeError Python raises for a value that is not awaitable.""" + return await value # pyright: ignore[reportGeneralTypeIssues, reportUnknownVariableType] # deliberately awaited as the Python router does + + +def _missing_model() -> TypeError: + return TypeError("_ageneric_api_call_with_fallbacks() missing 1 required positional argument: 'model'") + + +class RustEndpoints: + """The public endpoint methods of one Rust core, beyond the routed call loop the core drives.""" + + def __init__(self, core: EndpointCore, config: "RouterConfig") -> None: + from litellm.litellm_core_utils.request_timeout_resolver import get_configured_request_timeout + from litellm.router_utils.request_priority import InvalidPriority, parse_default_priority + + self._core: Final = core + self.counters: Final = Counters() + explicit: Final = config.get("timeout") + self._explicit_timeout: Final = explicit + self._request_timeout: Final = get_configured_request_timeout() if explicit is not None else None + self._stream_timeout: Final = config.get("stream_timeout") + # apply() flips it after construction, as on the Python core + self._cache_responses: bool = bool(config.get("cache_responses")) + self._assistants_config: Final = ( + as_dict(config.get("assistants_config")) if config.get("assistants_config") else None + ) + # These three are assigned by apply() after construction, as on the Python core. + tools: Final = list(_as_items(config.get("search_tools"))) + self._search_tools: list[object] = tools # mutable-ok: the router's live list + self._guardrails: list[object] = list(_as_items(config.get("guardrail_list"))) # mutable-ok: same + parsed: Final = parse_default_priority(config.get("default_priority")) + self._default_priority: Final = None if isinstance(parsed, InvalidPriority) else parsed + self._polling_interval: Final = config.get("polling_interval") + self._caching_groups: Final = config.get("caching_groups") + self._default_max_parallel_requests: object = config.get("default_max_parallel_requests") + self._scheduler: object = None + + @property + def cache_responses(self) -> bool: + return self._cache_responses + + def set_cache_responses(self, value: bool) -> None: + """``cache_responses`` assigned after construction (the proxy turns it on once its cache + exists): later calls pass ``caching=value``, as the Python core's flag does.""" + self._cache_responses = value + + def assign_setting(self, name: str, value: object) -> None: + """``search_tools``, ``guardrail_list`` or ``default_max_parallel_requests`` assigned after + construction, kept as given: later searches, guardrail picks and slot limits built from + then on read it, as the Python core's attributes are read.""" + if name == "search_tools": + self._search_tools = value # pyright: ignore[reportAttributeAccessIssue] # stored as given, as the Python core stores it + elif name == "guardrail_list": + self._guardrails = value # pyright: ignore[reportAttributeAccessIssue] # same + elif name == "default_max_parallel_requests": + self._default_max_parallel_requests = value + else: + raise ValueError(f"not an endpoint setting: {name}") + + @property + def default_max_parallel_requests(self) -> object: + """The setting as given: ``settings()`` reports it and the slot limits read it.""" + return self._default_max_parallel_requests + + @property + def search_tools(self) -> list[object]: # mutable-ok: the router's live list, as the Python router reports it + return self._search_tools + + @property + def guardrail_list(self) -> list[object]: # mutable-ok: same + return self._guardrails + + @staticmethod + def prepare_host(config: "RouterConfig", host: "PythonHost") -> None: + """`cache_responses` sets the process cache, unless one is set already (the proxy's).""" + if not config.get("cache_responses") or host.global_cache() is not None: + return + from litellm.caching.caching import Cache + + redis_url: Final = config.get("redis_url") + redis_host: Final = config.get("redis_host") + redis_port: Final = config.get("redis_port") + cache_config: Final[dict[str, object]] = {} # mutable-ok: the request kwargs the Python router mutates in place + cache_type: str = "local" # rebind-ok: redis when the router is given one + if redis_url is not None or (redis_host is not None and redis_port is not None): + cache_type = "redis" # rebind-ok: rebound as the Python router rebinds it + if redis_url is not None: + cache_config["url"] = redis_url + if redis_host is not None: + cache_config["host"] = redis_host + if redis_port is not None: + cache_config["port"] = str(redis_port) + if config.get("redis_password") is not None: + cache_config["password"] = config.get("redis_password") + if config.get("redis_db") is not None: + cache_config["db"] = str(config.get("redis_db")) + cache_config.update(as_dict(config.get("cache_kwargs"))) + host.set_global_cache(Cache(type=cache_type, **cache_config)) # pyright: ignore[reportArgumentType] # the Python router's cache config + + def shaping(self, resolved: "Resolved") -> Shaping: + return Shaping( + default_litellm_params=self.default_litellm_params(resolved), + timeout=resolved.timeout, + explicit_timeout=self._explicit_timeout, + request_timeout=self._request_timeout, + stream_timeout=self._stream_timeout, + cache_responses=self._cache_responses, + ) + + def default_litellm_params(self, resolved: "Resolved") -> Mapping[str, object]: + """The defaults the Python constructor completes before any call: the router ``timeout`` + argument, no client retries, and the caching groups in the default metadata.""" + configured: Final = resolved.default_litellm_params + metadata: Final = configured.get("metadata") + return MappingProxyType( + { + "timeout": self._explicit_timeout, + "max_retries": 0, + **configured, + "metadata": { + **(as_dict(metadata) if isinstance(metadata, Mapping) else {}), # pyright: ignore[reportUnknownArgumentType] # the configured metadata + "caching_groups": self._caching_groups, + }, + } + ) + + def prepare( + self, plan: Plan, request: Mapping[str, object], model: str + ) -> dict[str, object]: # mutable-ok: the call's kwargs + return prepare_request(plan, request, model, self._core.resolved.model_group_alias) + + # -- host and registry --------------------------------------------------------------------- + + def _invoke(self, op: str) -> Callable[..., object]: + return self._core.host.invoke(op) + + async def _direct(self, op: str, kwargs: Mapping[str, object]) -> object: + return await _await(self._invoke(op)(**kwargs)) + + def _group(self, name: str) -> list[Mapping[str, object]]: # mutable-ok: a fresh list + """`_core_get_model_list(model_name=name)`: the deployments of the group ``name``.""" + records: Final = self._core.handle.deployments() + return [record for record in (as_dict(r) for r in records) if record.get("model_name") == name] + + def _is_model_group(self, name: str) -> bool: + """`_core_get_model_list(model_name=name)`: an alias, a routing group or a wildcard counts.""" + return bool(self._core.group_deployments(name)) + + # -- members ------------------------------------------------------------------------------ + + def member(self, name: str) -> Callable[..., object] | None: + """The public endpoint ``name``, bound to this core, or None when the core has none.""" + if name in _UNBRANCHED: + return _answers_none + if name in _ASSISTANTS: + return self._assistants(name) + if name in _MANAGED_AGENTS: + return self._managed_agents(name) + if name in _SYNC_VECTOR_STORE_FILES: + return self._sync_vector_store_files(name) + if name == "create_interaction": + return self._factory("create_interaction", "interactions.create") + direct: Final = { + "avector_store_create": self.avector_store_create, + "acreate_file": self.acreate_file, + "acreate_batch": self.acreate_batch, + "acancel_batch": self.acancel_batch, + "aretrieve_batch": self.aretrieve_batch, + "alist_batches": self.alist_batches, + "aadapter_completion": self.aadapter_completion, + "abatch_completion": self.abatch_completion, + "abatch_completion_one_model_multiple_requests": self.abatch_completion_one_model_multiple_requests, + "abatch_completion_fastest_response": self.abatch_completion_fastest_response, + "schedule_acompletion": self.schedule_acompletion, + "priority_header_update": self.priority_header_update, + "aguardrail": self.aguardrail, + "asearch": self.asearch, + }.get(name) + if direct is not None: + return direct + if name == "responses": + return self._sync_factory(name, PLANS["responses"]) + plan: Final = generic_plan(name) + if plan is None or name in PLANS: + return None + if plan.sync: + return self._sync_factory(name, plan) + return self._factory(name, plan.host_op) + + # -- the factory wrappers ------------------------------------------------------------------ + + def _factory(self, name: str, host_op: str) -> Callable[..., Awaitable[object]]: + async def async_wrapper( + custom_llm_provider: str | None = None, + client: object = None, + **kwargs: object, # kwargs-ok: the endpoint's request + ) -> object: + return await self._wrapped(name, host_op, custom_llm_provider, client, dict(kwargs)) + + async_wrapper.__name__ = name + return async_wrapper + + async def _wrapped( + self, + name: str, + host_op: str, + custom_llm_provider: str | None, + client: object, + kwargs: dict[str, object], # mutable-ok: the wrapper's own kwargs + ) -> object: + plan: Final = generic_plan(name) or _generic(name, host_op) + if name in _CONTAINER_ENDPOINTS: + return await self._containers(plan, custom_llm_provider, kwargs) + if name in _RESPONSE_ID_ENDPOINTS: + from litellm.responses.utils import ResponsesAPIRequestUtils + + model_id: Final = ResponsesAPIRequestUtils.get_model_id_from_response_id(kwargs.get("response_id")) # pyright: ignore[reportArgumentType] # any id the caller sends + if model_id is not None: + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "model" + ] = model_id + return await self._ageneric(plan, kwargs) + if name in _VECTOR_STORE_ENDPOINTS: + return await self._vector_stores(name, plan, custom_llm_provider, kwargs) + if name in _INTERACTION_ENDPOINTS or name == "create_interaction": + return await self._interactions(plan, custom_llm_provider, kwargs) + if name in _KEEPS_CLIENT: + return await self._ageneric(plan, {**kwargs, "client": client}) + if name in _KEEPS_PROVIDER_AND_CLIENT: + return await self._ageneric(plan, {**kwargs, "custom_llm_provider": custom_llm_provider, "client": client}) + if name == "allm_passthrough_route": + if client: + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "client" + ] = client + return await self._ageneric(plan, kwargs, passthrough=True) + return await self._ageneric(plan, kwargs) + + async def generic(self, plan: Plan, request: Mapping[str, object]) -> object: + """A dispatched generic endpoint called with its whole request (the wrapper's + ``custom_llm_provider`` and ``client`` are consumed by the wrapper).""" + kwargs: Final = without(request, "custom_llm_provider", "client") + return await self._ageneric(plan, kwargs) + + async def _ageneric( + self, + plan: Plan, + kwargs: Mapping[str, object], + *, + passthrough: bool = False, + ) -> object: + """`_ageneric_api_call_with_fallbacks`.""" + if "model" not in kwargs: + raise _missing_model() + + async def passthrough_call(prepared: Mapping[str, object], name: str) -> object: + sent: Final = without(prepared, *ROUTING_KEYS) + return await self._direct(plan.host_op, {"model": name, **sent}) + + return await self._core.drive(plan, kwargs, passthrough=passthrough_call if passthrough else None) + + def _sync_factory(self, name: str, plan: Plan) -> Callable[..., object]: + is_vector_store: Final = name.startswith("vector_store_") + + def sync_wrapper( + custom_llm_provider: str | None = None, + client: object = None, + **kwargs: object, # kwargs-ok: the endpoint's request + ) -> object: + if not is_vector_store: + if "model" not in kwargs: + raise TypeError( + "_generic_api_call_with_fallbacks() missing 1 required positional argument: 'model'" + ) + return self._core.call_sync(plan, kwargs, _SINGLE_ATTEMPT) + provider_kwargs: dict[ # mutable-ok: the request kwargs the Python router mutates in place # rebind-ok: rebound as the Python router rebinds it + str, object + ] = ( + {**kwargs, "custom_llm_provider": custom_llm_provider} + if custom_llm_provider and "custom_llm_provider" not in kwargs + else dict(kwargs) + ) + if name == "vector_store_search": + provider_kwargs = { # rebind-ok: rebound as the Python router rebinds it + **provider_kwargs, + "_direct_vector_store_embedding_executor": self._embedding_executor(kwargs), + } + if provider_kwargs.get("model"): + return self._core.call_sync(plan, provider_kwargs, _SINGLE_ATTEMPT) + if name == "vector_store_search": + return self._invoke(plan.host_op)(**{**provider_kwargs, "router": self._core.router}) + return self._invoke(plan.host_op)(**provider_kwargs) + + sync_wrapper.__name__ = name + return sync_wrapper + + def _embedding_executor(self, kwargs: Mapping[str, object]) -> object: + from litellm.llms.base_llm.vector_store.transformation import ( + RouterVectorStoreEmbeddingExecutor, + vector_store_request_metadata, + ) + + return RouterVectorStoreEmbeddingExecutor( + router=self._core.router, # pyright: ignore[reportArgumentType] # the router serves aembedding + metadata=vector_store_request_metadata(kwargs), + ) + + async def _containers( + self, + plan: Plan, + custom_llm_provider: str | None, + kwargs: dict[str, object], # mutable-ok: the request kwargs the Python router mutates in place + ) -> object: + """`_init_containers_api_endpoints`.""" + from litellm.responses.utils import ResponsesAPIRequestUtils + + if custom_llm_provider and "custom_llm_provider" not in kwargs: + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "custom_llm_provider" + ] = custom_llm_provider + container_id: Final = kwargs.get("container_id") + forwarded: Final = kwargs.get("model_id") + if isinstance(container_id, str): + decoded: Final = ResponsesAPIRequestUtils.decode_container_id(container_id) + original_id: Final = decoded.get("response_id", container_id) + if original_id != container_id: + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "container_id" + ] = original_id + decoded_provider: Final = decoded.get("custom_llm_provider") + if decoded_provider and kwargs.get("custom_llm_provider") == "openai": + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "custom_llm_provider" + ] = decoded_provider + model_id: Final = decoded.get("model_id") or ( + forwarded.strip() if isinstance(forwarded, str) and forwarded.strip() else None + ) + if model_id: + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "model" + ] = model_id + return await self._ageneric(plan, kwargs) + requested: Final = kwargs.get("model") + if isinstance(requested, str) and requested.strip(): + return await self._ageneric(plan, kwargs, passthrough=True) + return await self._direct(plan.host_op, kwargs) + + async def _vector_stores( + self, + name: str, + plan: Plan, + custom_llm_provider: str | None, + kwargs: dict[str, object], # mutable-ok: see _wrapped + ) -> object: + """`_init_vector_store_api_endpoints`.""" + if name == "avector_store_search": + kwargs = { # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + **kwargs, + "_direct_vector_store_embedding_executor": self._embedding_executor(kwargs), + } + if custom_llm_provider and "custom_llm_provider" not in kwargs: + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "custom_llm_provider" + ] = custom_llm_provider + if kwargs.get("model"): + return await self._ageneric(plan, kwargs) + if name == "avector_store_search": + return await self._direct(plan.host_op, {**kwargs, "router": self._core.router}) + return await self._direct(plan.host_op, kwargs) + + async def _interactions( + self, + plan: Plan, + custom_llm_provider: str | None, + kwargs: dict[str, object], # mutable-ok: the request kwargs the Python router mutates in place + ) -> object: + """`_init_interactions_api_endpoints`.""" + if custom_llm_provider and "custom_llm_provider" not in kwargs: + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "custom_llm_provider" + ] = custom_llm_provider + if "custom_llm_provider" not in kwargs: + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "custom_llm_provider" + ] = "gemini" + if kwargs.get("agent") and kwargs.get("model") == kwargs.get("agent"): + kwargs["model"] = ( # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + None + ) + if kwargs.get("model"): + return await self._ageneric(plan, kwargs) + return await self._direct(plan.host_op, kwargs) + + def _managed_agents(self, name: str) -> Callable[..., object]: + op: Final = _MANAGED_AGENTS[name] + + def prepared( + custom_llm_provider: str | None, + kwargs: dict[str, object], # mutable-ok: the request kwargs the Python router mutates in place + ) -> dict[str, object]: # mutable-ok: the call's kwargs + if custom_llm_provider and "custom_llm_provider" not in kwargs: + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "custom_llm_provider" + ] = custom_llm_provider + if "custom_llm_provider" not in kwargs: + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + "custom_llm_provider" + ] = "gemini" + return kwargs + + if name.startswith("a"): + + async def managed_agents_wrapper( + custom_llm_provider: str | None = None, + client: object = None, + **kwargs: object, # kwargs-ok: the request + ) -> object: + return await self._direct(op, prepared(custom_llm_provider, dict(kwargs))) + + return managed_agents_wrapper + + def managed_agents_sync_wrapper( + custom_llm_provider: str | None = None, + client: object = None, + **kwargs: object, # kwargs-ok: the request + ) -> object: + return self._invoke(op)(**prepared(custom_llm_provider, dict(kwargs))) + + return managed_agents_sync_wrapper + + def _sync_vector_store_files(self, name: str) -> Callable[..., object]: + op: Final = _SYNC_VECTOR_STORE_FILES[name] + + def vector_store_file_sync_wrapper( + custom_llm_provider: str | None = None, + client: object = None, + **kwargs: object, # kwargs-ok: the request + ) -> object: + return self._invoke(op)(custom_llm_provider=custom_llm_provider, client=client, **kwargs) + + return vector_store_file_sync_wrapper + + def _assistants(self, name: str) -> Callable[..., Awaitable[object]]: + async def assistants_wrapper( + custom_llm_provider: str | None = None, + client: object = None, + **kwargs: object, # kwargs-ok: the request + ) -> object: + """`_pass_through_assistants_endpoint_factory`.""" + provider: object = custom_llm_provider # rebind-ok: the assistants config's when none is given + sent: Final = dict(kwargs) + if provider is None: + if self._assistants_config is None: + raise Exception( # noqa: TRY002 # the Python router raises a bare Exception + "'custom_llm_provider' must be set. Either via:\n `Router(assistants_config={'custom_llm_provider': ..})` \nor\n `router.arun_thread(custom_llm_provider=..)`" + ) + provider = self._assistants_config[ # rebind-ok: rebound as the Python router rebinds it + "custom_llm_provider" + ] + sent.update(as_dict(self._assistants_config.get("litellm_params"))) + return await self._direct(name, {"custom_llm_provider": provider, "client": client, **sent}) + + return assistants_wrapper + + # -- completions, priority and prompt management ---------------------------------------- + + def _drops_params(self, model: str, kwargs: Mapping[str, object]) -> bool: + from litellm.litellm_core_utils.routing_common_utils import get_request_team_id + from litellm.router_utils.request_priority import request_drops_params + + def deployment_params() -> tuple[Mapping[str, object], ...]: + names: Final = {as_dict(r).get("model_name") for r in self._core.handle.deployments()} + pinned: Final = ( + self._core.handle.deployment(model) if model not in names and isinstance(model, str) else None # pyright: ignore[reportUnnecessaryIsInstance] # a caller's value, typed for the common case + ) + if pinned is not None: + return (as_dict(as_dict(pinned).get("litellm_params")),) + if kwargs.get("specific_deployment") is True: + candidates = [ # rebind-ok: rebound as the Python router rebinds it + as_dict(r) + for r in self._core.handle.deployments() + if as_dict(as_dict(r).get("litellm_params")).get("model") == model + ] + else: + # `_core_get_model_list`: an alias's target, a routing group's members and a + # wildcard's deployments list here too. + candidates = [ # rebind-ok: rebound as the Python router rebinds it + as_dict(record) + for record in self._core.registry().deployments(model, team_id=get_request_team_id(kwargs)) or () + ] + return tuple(as_dict(candidate.get("litellm_params")) for candidate in candidates) + + return request_drops_params( + kwargs, + self._core.resolved.default_litellm_params, + deployment_params(), + ) + + def _split_priority( + self, model: str, kwargs: Mapping[str, object] + ) -> tuple[int | None, dict[str, object]]: # mutable-ok: the call's kwargs + """`_core_split_request_priority`.""" + from litellm.router_utils.request_priority import InvalidPriority, priority_error, resolve_request_priority + + priority: Final = resolve_request_priority( + requested=kwargs.get("priority"), + default_priority=self._default_priority, + drops_params=lambda: self._drops_params(model=model, kwargs=kwargs), + ) + if isinstance(priority, InvalidPriority): + raise priority_error(model=model, message=priority.message) + return priority, without(kwargs, "priority") + + def priority_header_update( + self, model: str, kwargs: Mapping[str, object], header: str | None + ) -> Mapping[str, int | str]: + from litellm.router_utils.request_priority import priority_header_fields + + return priority_header_fields(header, drops_params=lambda: self._drops_params(model=model, kwargs=kwargs)) + + def set_scheduler(self, scheduler: object) -> None: + """``router.scheduler = ...``, which the next prioritized call waits on.""" + self._scheduler = scheduler + + def delete_scheduler(self) -> None: + """``del router.scheduler``: a prioritized call raises from then on, as on the Python core.""" + self._scheduler = _NO_SCHEDULER + + def _get_scheduler(self) -> object: + if self._scheduler is _NO_SCHEDULER: + raise AttributeError("'RustCore' object has no attribute 'scheduler'", name="scheduler") + if self._scheduler is None: + from litellm.scheduler import Scheduler + + self._scheduler = ( + Scheduler(polling_interval=self._polling_interval) # pyright: ignore[reportArgumentType] # as configured + if self._polling_interval is not None + else Scheduler() + ) + return self._scheduler + + async def _schedule( + self, model: str, priority: int, run: Callable[[], Awaitable[object]], request: Mapping[str, object] + ) -> object: + """`_schedule_factory`: wait for the scheduler's turn, run, mark the response.""" + from litellm.litellm_core_utils.hidden_params import get_hidden_params + from litellm.scheduler import FlowItem, Scheduler + + scheduler: Final = self._get_scheduler() + assert isinstance(scheduler, Scheduler) + + async def healthy_deployments() -> Sequence[object]: + healthy: Final = await self._core.select(model, dict(request), kind="healthy") + return list(healthy) if isinstance(healthy, Sequence) else [healthy] + + await scheduler.wait_for_turn( + request=FlowItem(priority=priority, request_id=str(uuid.uuid4()), model_name=model), + timeout=self._core.resolved.timeout, # pyright: ignore[reportArgumentType] # the router timeout + get_healthy_deployments=healthy_deployments, + ) + try: + response: Final = await run() + except Exception as error: + setattr(error, "priority", priority) # noqa: B010 # the Python router stamps the same attribute + raise + hidden: Final = get_hidden_params(response) + if hidden is not None: + headers: Final = hidden.setdefault("additional_headers", {}) + if isinstance(headers, dict): + headers.update({"x-litellm-request-prioritization-used": True}) # pyright: ignore[reportUnknownMemberType] # litellm's untyped helpers and request values + return response + + async def acompletion(self, request: Mapping[str, object]) -> object: + model: Final = request.get("model") + if model is None and "model" in request: + return await self._core.drive(PLANS["acompletion"], request) + if "model" not in request: + raise TypeError("acompletion() needs a model name") + if not isinstance(model, str): + _ = self._core.routed_name(model) + kwargs: Final = {**request, "stream": request.get("stream", False)} + start_time: Final = time.time() + response: Final = await self._routed_acompletion(model, kwargs) # pyright: ignore[reportArgumentType] # the name as given + self._core.service_logged("acompletion", start_time, time.time(), kwargs) + return response + + async def _routed_acompletion(self, model: str, kwargs: Mapping[str, object]) -> object: + plan: Final = PLANS["acompletion"] + priority, rest = self._split_priority(model, kwargs) + from litellm.router_rust.invoke.prompt_management import ( + is_prompt_management_model, + prompt_management_acompletion, + ) + + if is_prompt_management_model(self._core, model): + prepared: Final = self.prepare(plan, rest, model) + messages: Final = rest.get("messages") + + def factory() -> Awaitable[object]: + return prompt_management_acompletion(self._core, model, messages, prepared) + + if priority is None: + return await factory() + return await self._schedule(model, priority, factory, prepared) + if priority is None: + return await self._core.drive(plan, rest) + return await self._schedule(model, priority, lambda: self._core.drive(plan, rest), rest) + + async def atext_completion(self, request: Mapping[str, object]) -> object: + model: Final = request.get("model") + if model is None and "model" in request: + return await self._core.drive(PLANS["atext_completion"], request) + if "model" not in request: + raise TypeError("atext_completion() needs a model name") + if not isinstance(model, str): + _ = self._core.routed_name(model) + kwargs: Final = without(request, "is_retry", "is_fallback", "is_async") + plan: Final = PLANS["atext_completion"] + priority, rest = self._split_priority(model, kwargs) # pyright: ignore[reportArgumentType] # the name as given + if priority is None: + return await self._core.drive(plan, rest) + return await self._schedule(model, priority, lambda: self._core.drive(plan, rest), rest) # pyright: ignore[reportArgumentType] # see above + + async def schedule_acompletion( + self, + model: str, + messages: object, + priority: int | None = None, + stream: bool = False, + **kwargs: object, # kwargs-ok: the request + ) -> object: + from litellm.router_utils.request_priority import priority_error, unqueueable_priority_message + + queued, _ = self._split_priority(model, {**kwargs, "priority": priority}) + if queued is None: + raise priority_error(model=model, message=unqueueable_priority_message(priority)) + return await self._core.acompletion(model=model, messages=messages, stream=stream, priority=queued, **kwargs) + + # -- batch completions ------------------------------------------------------------------- + + async def _no_exceptions(self, **kwargs: object) -> object: # kwargs-ok: the request + try: + return await self._core.acompletion(**kwargs) + except Exception as error: # noqa: BLE001 # returned in place, as the Python router does + return error + + async def abatch_completion( + self, + models: list[str], # mutable-ok: the request kwargs the Python router mutates in place + messages: object, + **kwargs: object, # kwargs-ok: the endpoint's open request + ) -> object: + if isinstance(messages, list) and all(isinstance(m, dict) for m in messages): # pyright: ignore[reportUnknownVariableType] # checked item by item + return await asyncio.gather( + *(self._no_exceptions(model=model, messages=messages, **kwargs) for model in models) # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + ) + if isinstance(messages, list) and all(isinstance(m, list) for m in messages): # pyright: ignore[reportUnknownVariableType] # same + rows: Final[list[object]] = list(messages) # pyright: ignore[reportUnknownArgumentType] # same # mutable-ok: the request kwargs the Python router mutates in place + + async def indexed(model: str, message: object, idx: int) -> tuple[object, int]: + return await self._no_exceptions(model=model, messages=message, **kwargs), idx + + responses: Final = await asyncio.gather( + *( + indexed(model, message, idx) for idx, message in enumerate(rows) for model in models + ) # comprehension-ok: a flat walk of nested rows + ) + final: Final[list[list[object]]] = [ # mutable-ok: the request kwargs the Python router mutates in place + [] for _ in rows + ] + for response, idx in responses: + final[idx].append(response) + return final + return None + + async def abatch_completion_one_model_multiple_requests( + self, + model: str, + messages: list[object], # mutable-ok: the request kwargs the Python router mutates in place + **kwargs: object, # kwargs-ok: the endpoint's open request + ) -> object: + return await asyncio.gather(*(self._no_exceptions(model=model, messages=m, **kwargs) for m in messages)) + + async def abatch_completion_fastest_response( + self, + model: str, + messages: object, + stream: bool = False, + **kwargs: object, # kwargs-ok: the request + ) -> object: + from litellm.litellm_core_utils.hidden_params import get_hidden_params + from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper + from litellm.types.utils import ModelResponse + + models: Final = [m.strip() for m in model.split(",")] + + async def no_exceptions(model_name: str) -> object: + try: + return await self._core.acompletion(model=model_name, messages=messages, stream=stream, **kwargs) + except asyncio.CancelledError: + raise + except Exception as error: # noqa: BLE001 # see _no_exceptions + return error + + pending: set[ # mutable-ok: the request kwargs the Python router mutates in place # rebind-ok: rebound as the Python router rebinds it + asyncio.Task[object] + ] = {asyncio.create_task(no_exceptions(m)) for m in models} + while pending: + done, pending = await asyncio.wait(pending, return_when=asyncio.FIRST_COMPLETED) + for task in done: + result = task.result() + if isinstance(result, (ModelResponse, CustomStreamWrapper)): + for other in pending: + other.cancel() + hidden = get_hidden_params(result) + if hidden is not None: + hidden["fastest_response_batch_completion"] = True + return result + raise Exception("All tasks failed") # noqa: TRY002 # the Python router raises a bare Exception + + # -- moderation, text completion and adapter -------------------------------------------- + + async def amoderation(self, request: Mapping[str, object]) -> object: + """`_pass_through_moderation_endpoint_factory`: one pick when the model is a group.""" + kwargs: Final = without(request, "custom_llm_provider", "client") + plan: Final = PLANS["amoderation"] + model: Final = kwargs.get("model", "") + if not isinstance(model, str): + _ = self._core.routed_name(model) + if model and isinstance(model, str) and self._is_model_group(model): + return await self._core.drive(plan, kwargs, _SINGLE_ATTEMPT) + prepared: Final = prepare_request(plan, kwargs, str(model), self._core.resolved.model_group_alias) + return await self._direct("amoderation", prepared) + + def text_completion(self, request: Mapping[str, object]) -> object: + """The sync `text_completion`: one pick, no retries, the group name as the model.""" + from litellm.litellm_core_utils.routing_common_utils import deployment_model_id_pin + + kwargs: Final = without(request, "is_retry", "is_fallback", "is_async") + model: Final = kwargs.get("model") + prompt: Final = kwargs.get("prompt") + if "model" not in kwargs: + raise TypeError("text_completion() missing 1 required positional argument: 'model'") + kwargs["num_retries"] = kwargs.get("num_retries", self._core.resolved.num_retries) + metadata_bucket(kwargs, "metadata").update({"model_group": model}) + with endpoint_selection("text_completion", model=model): + deployment: Final = self._core.router.get_available_deployment( + model=model, # pyright: ignore[reportArgumentType] # the name as given + messages=_user_message(prompt), + specific_deployment=kwargs.pop("specific_deployment", None), # pyright: ignore[reportArgumentType] # the request's value, as given + request_kwargs=kwargs, + ) + data: Final = as_dict(deployment.get("litellm_params")) + for key, value in self._core.resolved.default_litellm_params.items(): + if key not in kwargs: + kwargs[key] = value + elif key == "metadata": + bucket = kwargs[key] + if isinstance(bucket, dict): + bucket.update(as_dict(value)) # pyright: ignore[reportUnknownMemberType] # the request's metadata dict + pinned: Final = deployment_model_id_pin(data) + if pinned is not None: + kwargs["model_id"] = pinned + return self._invoke("text_completion")(**{**data, "prompt": prompt, "caching": self._cache_responses, **kwargs}) + + async def aadapter_completion( + self, + adapter_id: str, + model: str, + is_retry: bool | None = False, + is_fallback: bool | None = False, + is_async: bool | None = False, + **kwargs: object, # kwargs-ok: the request + ) -> object: + return await self._core.drive( + PLANS["aadapter_completion"], {**kwargs, "model": model, "adapter_id": adapter_id} + ) + + # -- files, batches and vector stores --------------------------------------------------- + + async def acreate_batch(self, model: str, **kwargs: object) -> object: # kwargs-ok: the request + return await self._core.drive(PLANS["acreate_batch"], {**kwargs, "model": model}) + + async def acancel_batch(self, model: str, **kwargs: object) -> object: # kwargs-ok: the request + return await self._core.drive(PLANS["acancel_batch"], {**kwargs, "model": model}) + + async def avector_store_create(self, model: str | None, **kwargs: object) -> object: # kwargs-ok: the request + if model is None: + return await self._factory("avector_store_create", "vector_stores.main.acreate")(**kwargs) + return await self._core.drive(PLANS["avector_store_create"], {**kwargs, "model": model}, _SINGLE_ATTEMPT) + + async def aretrieve_batch(self, model: str | None = None, **kwargs: object) -> object: # kwargs-ok: the request + """Ask every deployment of the group (or of the router) for the batch.""" + from litellm.litellm_core_utils.core_helpers import ( + safe_deep_copy, # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + ) + from litellm.types.utils import LiteLLMBatch + + shaping: Final = self._core.shaping + metadata_variable_name: Final = get_router_metadata_variable_name(function_name="aretrieve_batch") + if model is not None: + specific: Final = kwargs.pop("specific_deployment", None) + healthy = await self._core.select( # rebind-ok: rebound as the Python router rebinds it + model, + dict(kwargs), + kind="healthy", + specific_deployment=bool(specific) or None, + messages=_user_message("retrieve-api-fake-text"), + ) + else: + healthy = [as_dict(r) for r in self._core.handle.deployments()] # rebind-ok: as Python rebinds it + errors: Final[list[BaseException]] = [] # mutable-ok: the request kwargs the Python router mutates in place + + async def try_retrieve(deployment: Mapping[str, object]) -> object: + try: + data: Final = as_dict(deployment.get("litellm_params")) + deployment_model: Final = data.get("model") + provider: object = data.get("custom_llm_provider") # rebind-ok: inferred when not declared + if deployment_model is None: + raise Exception(f"Model not found in litellm_params for deployment: {deployment}") # noqa: TRY002 # as the Python router + if not provider: + lookup: Final = self._core.host.invoke("get_llm_provider") + _, provider, _, _ = lookup(model=deployment_model) # rebind-ok: as Python rebinds it + new_kwargs: Final = safe_deep_copy(dict(kwargs)) # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + update_kwargs_with_deployment( + shaping, + deployment, + new_kwargs, # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + cache=self._core.routing_cache, + function_name="aretrieve_batch", + ) + bucket: Final = metadata_bucket(new_kwargs, metadata_variable_name) # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + if not bucket.get("model_group"): + bucket["model_group"] = model or deployment.get("model_name") + new_kwargs.pop("custom_llm_provider", None) # pyright: ignore[reportUnknownMemberType] # litellm's untyped helpers and request values + data.pop("custom_llm_provider", None) + return await self._direct("aretrieve_batch", {**data, "custom_llm_provider": provider, **new_kwargs}) # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + except Exception as error: # noqa: BLE001 # collected; the first one is raised when no deployment has the batch + errors.append(error) + return None + + deployments: Final = list(healthy) if isinstance(healthy, Sequence) else [healthy] + if not deployments: + raise Exception("No healthy deployments found.") # noqa: TRY002 # as the Python router + results: Final = await asyncio.gather(*(try_retrieve(as_dict(d)) for d in deployments), return_exceptions=True) + for result in results: + if isinstance(result, LiteLLMBatch): + return result + if errors: + raise errors[0] + raise Exception(f"Unable to find batch in any model. Received errors - {errors}") # noqa: TRY002 # as the Python router + + async def alist_batches(self, model: str, **kwargs: object) -> object: # kwargs-ok: the request + deployments: Final = self._group(model) + + async def try_list(deployment: Mapping[str, object]) -> object: + try: + return await self._direct("alist_batches", {**as_dict(deployment.get("litellm_params")), **kwargs}) + except Exception: # noqa: BLE001 # a failing deployment is left out, as the Python router does + return None + + results: Final = await asyncio.gather(*(try_list(d) for d in deployments)) + final: Final[dict[str, object]] = { # mutable-ok: the request kwargs the Python router mutates in place + "object": "list", + "data": [], + "first_id": None, + "last_id": None, + "has_more": False, + } + data: Final[list[object]] = [] # mutable-ok: the request kwargs the Python router mutates in place + final["data"] = data + for result in results: + if result is None: + continue + if final["first_id"] is None and hasattr(result, "first_id"): + final["first_id"] = getattr(result, "first_id") # noqa: B009 # as the Python router + final["last_id"] = getattr(result, "last_id") # noqa: B009 # same + data.extend(getattr(result, "data")) # noqa: B009 # same # pyright: ignore[reportAny] # litellm's untyped helpers and request values + if getattr(result, "has_more", False) is True: + final["has_more"] = True + return final + + async def acreate_file(self, model: str, **kwargs: object) -> object: # kwargs-ok: the request + return await self._core.drive(PLANS["acreate_file"], {**kwargs, "model": model}) + + async def create_file_everywhere(self, kwargs: Mapping[str, object], requested: str, specific: object) -> object: + """`_acreate_file`: create the file on every healthy deployment of the group.""" + from litellm.litellm_core_utils import batch_utils + from litellm.litellm_core_utils.core_helpers import ( + safe_deep_copy, # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + ) + from litellm.litellm_core_utils.hidden_params import get_hidden_params + from litellm.litellm_core_utils.routing_common_utils import ( + add_model_file_id_mappings, # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + ) + from litellm.types.utils import LlmProviders + + healthy: Final = await self._core.select( + requested, + dict(kwargs), + kind="healthy", + specific_deployment=bool(specific) or None, + messages=_user_message(_PICK_TEXTS["create_file"]), + ) + deployments: Final = list(healthy) if isinstance(healthy, Sequence) else [healthy] + + async def create_for(deployment: Mapping[str, object]) -> object: + kwargs_copy: Final = safe_deep_copy(dict(kwargs)) # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + update_kwargs_with_deployment( + self._core.shaping, + deployment, + kwargs_copy, # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + cache=self._core.routing_cache, + function_name="acreate_file", + ) + data: Final = as_dict(deployment.get("litellm_params")) + model_name: Final = str(data.get("model")) + self.counters.total_calls[model_name] += 1 + declared: Final = data.get("custom_llm_provider") + stripped, inferred, _, _ = self._core.host.invoke("get_llm_provider")( + model=data["model"], custom_llm_provider=declared + ) + provider: Final = declared or inferred + purpose: Final = kwargs.get("purpose") + file: object = kwargs.get("file") # rebind-ok: rewritten for the deployment + if not file or not purpose: + raise Exception("file and file_purpose are required for create_file") # noqa: TRY002 # as the Python router + replaces: Final = batch_utils.should_replace_model_in_jsonl( + purpose=purpose, # pyright: ignore[reportArgumentType] # the caller's purpose + passthrough=kwargs.get("passthrough") is True, + ) + if replaces: + file = batch_utils.replace_model_in_jsonl( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # an untyped helper # rebind-ok: rewritten for the deployment + file_content=file, # pyright: ignore[reportArgumentType] # the caller's file + new_model_name=stripped, + keep_line_numbers=provider == LlmProviders.VERTEX_AI.value, + ) + kwargs_copy["file"] = file + if provider == LlmProviders.LITELLM_PROXY.value: + kwargs_copy["extra_body"] = MappingProxyType( + {**as_dict(kwargs_copy.get("extra_body")), "target_model_names": stripped} # pyright: ignore[reportUnknownArgumentType, reportUnknownMemberType] # litellm's untyped helpers and request values + ) + if "gcs_bucket_name" in data: + metadata_bucket(kwargs_copy, "litellm_metadata")["gcs_bucket_name"] = data["gcs_bucket_name"] # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + from litellm.router_rust.invoke.slots import deployment_slot + + with deployment_slot(self._core, deployment, kwargs_copy): # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + response: Final = await self._direct( + "acreate_file", + { + **data, + "custom_llm_provider": provider, + "caching": self._cache_responses, + "client": model_client(self._core, PLANS["acreate_file"], deployment, kwargs_copy), # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + **kwargs_copy, + }, # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + ) + self.counters.success_calls[model_name] += 1 + return response + + responses: Final = await asyncio.gather(*(create_for(as_dict(d)) for d in deployments)) + if len(responses) == 0: + raise Exception("No healthy deployments found.") # noqa: TRY002 # as the Python router + mapping: Final = add_model_file_id_mappings(healthy_deployments=deployments, responses=responses) # pyright: ignore[reportArgumentType, reportUnknownVariableType] # deployment records + returned: Final = responses[0] + hidden: Final = get_hidden_params(returned) + if hidden is not None: + hidden["model_file_id_mapping"] = mapping + return returned + + # -- search tools ------------------------------------------------------------------------- + + async def asearch( + self, + custom_llm_provider: str | None = None, + client: object = None, + **kwargs: object, # kwargs-ok: the request + ) -> object: + """`_asearch_with_fallbacks`: the search tool name (``search_tool_name``, else ``model``) + routes as the model; the factory wrapper drops ``custom_llm_provider`` and ``client``.""" + request: Final = dict(kwargs) + search_tool_name: Final = request.get("search_tool_name", request.get("model")) + if not search_tool_name: + raise ValueError("search_tool_name or model parameter is required for search") + request["model"] = search_tool_name + return await self._core.drive(PLANS["asearch"], request) + + # -- guardrails --------------------------------------------------------------------------- + + async def aguardrail( + self, + guardrail_name: str, + original_function: Callable[..., Awaitable[object]], + **kwargs: object, # kwargs-ok: the request + ) -> object: + """Pick one of the guardrails named ``guardrail_name`` (weighted) and run it. A guardrail name + is no model group, so the router's retries never apply.""" + request: Final = dict(kwargs) + request.setdefault("litellm_trace_id", str(uuid.uuid4())) + metadata_bucket(request, "litellm_metadata").update( + { + "model_group": guardrail_name, + "model_group_alias": guardrail_name + if guardrail_name in self._core.resolved.model_group_alias + else None, + } + ) + verdict: Final = await original_function(**request, selected_guardrail=self.available_guardrail(guardrail_name)) + # `make_call`, `async_function_with_retries` and `async_function_with_fallbacks` stamp the result. + headed: Final = await self._core.set_response_headers(verdict, guardrail_name, request) + return add_fallback_headers_to_response( + response=add_retry_headers_to_response(response=headed, attempted_retries=0, max_retries=None), + attempted_fallbacks=0, + ) + + def available_guardrail(self, guardrail_name: str) -> object: + """``_core_get_available_guardrail``: the one guardrail configured under the name, else one of + them picked by weight (``simple_shuffle``, the name resolved through the alias map).""" + from litellm.router_strategy.simple_shuffle import simple_shuffle + + candidates: Final = [g for g in self._guardrails if as_dict(g).get("guardrail_name") == guardrail_name] + if not candidates: + raise ValueError(f"No guardrail found with name: {guardrail_name}") + if len(candidates) == 1: + return candidates[0] + return simple_shuffle( # pyright: ignore[reportUnknownVariableType] # litellm's untyped helper + resolve_model_alias=self._core.resolve_alias, + healthy_deployments=candidates, # pyright: ignore[reportArgumentType] # guardrail configs + model=guardrail_name, + request_kwargs=None, + ) + + # -- attempts ----------------------------------------------------------------------------- + + def attempt_failed( + self, + plan: Plan, + error: BaseException, + deployment: Mapping[str, object], + call: AttemptCall | None, + requested: str, + ) -> None: + from litellm import exceptions as litellm_exceptions + from litellm.types.router import LiteLLM_Params + + # `_acompletion`'s Timeout branch counts no failure and adds the deployment's timeouts; the + # sync `_completion` has no such branch. + timed_out: Final = plan.kind == "chat" and not plan.sync and isinstance(error, litellm_exceptions.Timeout) + if not timed_out: + self.counters.failed(plan, call.model_name if call is not None else None, requested) + elif isinstance(error, litellm_exceptions.Timeout) and self._core.host.dynamic().expose_router_debug_in_errors: + params: Final = as_dict(deployment.get("litellm_params")) + try: + typed: Mapping[str, object] = ( # rebind-ok: rebound as the Python router rebinds it + LiteLLM_Params.model_validate(params).model_dump() + ) + except Exception: # noqa: BLE001 # the params as configured, when they do not validate + typed = params # rebind-ok: rebound as the Python router rebinds it + error.message += ( # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + f"\n\nDeployment Info: request_timeout: {typed.get('request_timeout')}" + f"\ntimeout: {typed.get('timeout')}" + f"\nstream_timeout: {typed.get('stream_timeout')}" + ) + + def check_response(self, plan: Plan, response: object, call: AttemptCall) -> None: + """What the attempt helper checks of a response before it counts it as served.""" + + def sync_pre_call_checks(self, plan: Plan, deployment: Mapping[str, object], request: Mapping[str, object]) -> None: + """`routing_strategy_pre_call_checks` on the sync path: the process callbacks' pre-call checks. + Sync completion runs them for a group but not for a deployment id.""" + from litellm.integrations.custom_logger import CustomLogger + + if plan.kind == "chat": + model: Final = str(request.get("model")) + names: Final = {as_dict(r).get("model_name") for r in self._core.handle.deployments()} + if model not in names and self._core.handle.deployment(model) is not None: + return + for callback in tuple(self._core.routing_callbacks()): + if isinstance(callback, CustomLogger): + callback.pre_call_check(dict(deployment)) # pyright: ignore[reportUnknownMemberType] # litellm's untyped helpers and request values + + +_SINGLE_ATTEMPT: Final[Mapping[str, object]] = MappingProxyType({"num_retries": 0, "disable_fallbacks": True}) + + +async def _answers_none(*_args: object, **_kwargs: object) -> None: # kwargs-ok: any request + """An endpoint the Python router's async wrapper has no branch for.""" + return + + +def _as_items(value: object) -> list[object]: # mutable-ok: a fresh list + return list(value) if isinstance(value, list) else [] # pyright: ignore[reportUnknownArgumentType] # a config list + + +if TYPE_CHECKING: + from litellm.router_config import RouterConfig + from litellm.router_python_host import PythonHost + from litellm.router_rust.core import Resolved + + +__all__ = [ + "PLANS", + "ROUTING_KEYS", + "AttemptCall", + "Counters", + "Plan", + "RustEndpoints", + "Shaping", + "arm_compaction_state", + "attempt_call", + "clean_realtime_session_deployment", + "compacted_attempt", + "failover_fields", + "generic_plan", + "log_refused_call", + "log_refused_call_sync", + "pinned_video_deployment", + "plan_for", + "prepare_request", + "reports_own_success", + "selection_endpoint", + "stamp_error", + "unrouted_fields", +] diff --git a/litellm/router_rust/invoke/prompt_management.py b/litellm/router_rust/invoke/prompt_management.py new file mode 100644 index 00000000000..62bd77e1b48 --- /dev/null +++ b/litellm/router_rust/invoke/prompt_management.py @@ -0,0 +1,129 @@ +""" +Prompt-management groups on the Rust router core (``_is_prompt_management_model`` and +``_prompt_management_factory``): a group of exactly one deployment whose model names a prompt +management integration (``langfuse/...``) or ``litellm_agent/...``. The request is not routed with +retries and fallbacks: the deployment is picked, its prompt rendered by the request's logging +object, and the rendered model called directly, or routed when it names a group. +""" + +from collections.abc import Mapping +from typing import Final + +from litellm.litellm_core_utils.core_helpers import without +from litellm.router_rust.invoke.endpoints import PLANS, EndpointCore +from litellm.router_rust.invoke.shaping import as_dict, update_kwargs_with_deployment + +_PROMPT_MANAGEMENT_PARAMS: Final = frozenset( + {"bitbucket_config", "dotprompt_config", "prompt_id", "prompt_variables", "prompt_label", "prompt_version"} +) + + +def is_prompt_management_model(core: EndpointCore, model: str) -> bool: + """`_is_prompt_management_model`: one deployment, whose model's provider prefix is a known + custom-logger-compatible callback.""" + model_list: Final = core.group_deployments(model_name=model) + if model_list is None or len(model_list) != 1: + return False + litellm_model: Final = as_dict(model_list[0].get("litellm_params")).get("model") + if not isinstance(litellm_model, str) or "/" not in litellm_model: + return False + known: Final = core.host.dynamic().known_custom_logger_compatible_callbacks + return litellm_model.split("/")[0] in known + + +def _logging_and_kwargs( + kwargs: dict[str, object], # mutable-ok: the request kwargs the Python router mutates in place +) -> tuple[object, dict[str, object]]: # mutable-ok: same + """The request's logging object, else the one `function_setup` builds (with the kwargs it returns).""" + from litellm.utils import Rules, function_setup, get_utc_datetime + + logging_obj: Final = kwargs.get("litellm_logging_obj") + if logging_obj is not None: + return logging_obj, kwargs + return function_setup( # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers + **{ # pyright: ignore[reportArgumentType] # the request's keyword payload + "original_function": "acompletion", + "rules_obj": Rules(), + "start_time": get_utc_datetime(), + **kwargs, + } + ) + + +async def prompt_management_acompletion( + core: EndpointCore, + model: str, + messages: object, + request: Mapping[str, object], +) -> object: + """`_prompt_management_factory`, on the request as `acompletion` prepared it.""" + from litellm.utils import get_non_default_completion_params + + # `acompletion` hands the routing function along; function_setup consumes it. + logging_obj, kwargs = _logging_and_kwargs({**request, "original_function": core.router.acompletion}) + caller_timeout: Final = kwargs.get("timeout") or kwargs.get("request_timeout") + caller_stream_timeout: Final = kwargs.get("stream_timeout") + specific_deployment: Final = kwargs.pop("specific_deployment", None) + picked: Final = await core.select( + model, + kwargs, # pyright: ignore[reportUnknownArgumentType] # the request kwargs + kind="pick", + specific_deployment=bool(specific_deployment), + messages=messages, + ) + deployment: Final = as_dict(picked) + update_kwargs_with_deployment( + core.shaping, + deployment, + kwargs, # pyright: ignore[reportUnknownArgumentType] # the request kwargs + cache=core.routing_cache, + splits_stream_timeout=True, + ) + params: Final = as_dict(deployment.get("litellm_params")) + data: Final = dict(params) + litellm_model: Final = data.get("model") + is_litellm_agent_model: Final = isinstance(litellm_model, str) and litellm_model.startswith("litellm_agent/") + prompt_id: Final = kwargs.get("prompt_id") or params.get("prompt_id") + prompt_variables: Final = kwargs.get("prompt_variables") or params.get("prompt_variables") + prompt_label: Final = kwargs.get("prompt_label") or params.get("prompt_label") + if not is_litellm_agent_model and (prompt_id is None or not isinstance(prompt_id, str)): + raise ValueError(f"Prompt ID is not set or not a string. Got={prompt_id}, type={type(prompt_id)}") + if prompt_variables is not None and not isinstance(prompt_variables, dict): + raise ValueError( + f"Prompt variables is set but not a dictionary. Got={prompt_variables}, type={type(prompt_variables)}" + ) + rendered_model, rendered_messages, optional_params = logging_obj.get_chat_completion_prompt( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType, reportAttributeAccessIssue, reportOptionalMemberAccess] # the request's Logging object + model=litellm_model, # pyright: ignore[reportArgumentType] # a request value, passed as the Python router passes it + messages=messages, # pyright: ignore[reportArgumentType] # a request value, passed as the Python router passes it + non_default_params=get_non_default_completion_params(kwargs=kwargs), # pyright: ignore[reportArgumentType] # the request kwargs + prompt_id=prompt_id, # pyright: ignore[reportArgumentType] # a request value, passed as the Python router passes it + prompt_variables=prompt_variables, + prompt_label=prompt_label, # pyright: ignore[reportArgumentType] # a request value, passed as the Python router passes it + request_kwargs=kwargs, + injected_for_every_deployment=True, + ) + filtered_data: Final = without(data, *_PROMPT_MANAGEMENT_PARAMS) + final: Final[dict[str, object]] = {**filtered_data, **kwargs, **optional_params} # pyright: ignore[reportUnknownVariableType] # mutable-ok: the call's kwargs + final["model"] = rendered_model + final["messages"] = rendered_messages + final["litellm_logging_obj"] = logging_obj + final["prompt_id"] = prompt_id + final["prompt_variables"] = prompt_variables + final["prompt_label"] = prompt_label + target_list: Final = core.group_deployments(model_name=str(rendered_model)) # pyright: ignore[reportUnknownArgumentType] # the core's host registry + if target_list is None or len(target_list) == 0: # a direct call to the rendered model + _ = final.pop("original_function") + return await core.host.invoke("acompletion")(**final) # pyright: ignore[reportUnknownMemberType] # the core's host + timeouts: Final = { + key: value + for key, value in ( + ("timeout", caller_timeout if caller_timeout is not None else filtered_data.get("timeout")), + ( + "stream_timeout", + caller_stream_timeout if caller_stream_timeout is not None else filtered_data.get("stream_timeout"), + ), + ) + if value is not None + } + routed: Final = without(final, "timeout", "stream_timeout") + return await core.drive(PLANS["acompletion"], {**routed, **timeouts}, prepared_already=True) diff --git a/litellm/router_rust/invoke/shaping.py b/litellm/router_rust/invoke/shaping.py new file mode 100644 index 00000000000..258f919c9f1 --- /dev/null +++ b/litellm/router_rust/invoke/shaping.py @@ -0,0 +1,635 @@ +""" +The keyword arguments one router attempt sends to one deployment, as the Python router builds them. + +The Rust router core picks the deployment; the host shapes the request for it here +(``_update_kwargs_with_deployment``, ``_update_kwargs_with_default_litellm_params``, +``_merge_tools_from_deployment``, the timeout resolvers and the reasoning-effort override), with +the same precedence and the same oddities. Nothing here reads a Python router. +""" + +import dataclasses +from collections.abc import Mapping, MutableMapping, Sequence +from functools import partial +from types import MappingProxyType +from typing import TYPE_CHECKING, Final + +from pydantic import TypeAdapter, ValidationError + +from litellm import exceptions as litellm_exceptions +from litellm.constants import ( + BAGGAGE_MAPPED_TAGS_METADATA_KEY, + INTERNAL_CALL_ORIGIN_METADATA_KEY, + KUBERNETES_POD_ROUTING_KEY, + ROUTING_REQUEST_TAGS_METADATA_KEY, +) +from litellm.litellm_core_utils.batch_utils import get_router_metadata_variable_name +from litellm.litellm_core_utils.clientside_credential_handler import ( + get_dynamic_litellm_params, # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + is_clientside_credential, # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values +) +from litellm.litellm_core_utils.completion_timeout import CompletionTimeout +from litellm.litellm_core_utils.core_helpers import without +from litellm.litellm_core_utils.get_litellm_params import SUPPLEMENTAL_KWARGS_KEYS +from litellm.litellm_core_utils.get_llm_provider_logic import declared_authenticating_provider, inferred_provider +from litellm.litellm_core_utils.request_timeout_resolver import get_service_tier_timeout +from litellm.litellm_core_utils.routing_common_utils import deployment_model_id_pin +from litellm.litellm_core_utils.tool_fields import TOOL_FIELDS, drop_policy +from litellm.responses.retrieve_stream_query import requests_streamed_retrieval, without_retrieve_stream_defaults +from litellm.router_api import deployment_id as generate_deployment_id +from litellm.router_strategy.tag_based_routing import ( + baggage_stamp_for_serving_deployment, + get_tags_from_request_kwargs, + tags_with_serving_deployment_tags, +) +from litellm.router_utils.pre_call_checks.io_token_rate_limit_check import ( + deployment_has_io_token_limits, # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + refund_stale_reservation_before_retry, + set_io_token_rate_limit_request_kwargs, +) +from litellm.router_utils.stream_usage_injection import router_config_requests_stream_usage +from litellm.types.litellm_params import STREAM_USAGE_INJECTED_FIELD +from litellm.types.router import Deployment, GenericLiteLLMParams, LiteLLM_Params, validate_litellm_params_strictly +from litellm.types.utils import AUTOROUTER_CLASSIFIER_CALL_ORIGIN + +if TYPE_CHECKING: + from litellm.caching.dual_cache import DualCache + from litellm.router_python_host import PythonHost + +# The SDK-client and max_parallel_requests reads of the routing cache: process-local, so the family +# only names a Redis span when a read misses through to Redis. +ROUTER_CLIENTS_TARGET: Final = "router_clients" +_MAPPING: Final = TypeAdapter(Mapping[str, object]) +_FORWARDED_CREDENTIAL_ISOLATION_PROVIDERS: Final = frozenset({"chatgpt", "anthropic"}) +_ALIAS_MARKER_FORWARDED_PARAMS_KWARG: Final = "_alias_marker_forwarded_params" +# Generic handlers whose stream timeout is split from the request timeout. +STREAM_TIMEOUT_AWARE_GENERIC_HANDLERS: Final = frozenset({"anthropic_messages", "aresponses", "responses"}) + + +@dataclasses.dataclass(frozen=True, slots=True) +class Shaping: + """What the request shaping reads from the router, resolved once when the core is built. + + ``timeout`` is the router's ``timeout`` (its own setting, else the process ``request_timeout``), + ``request_timeout`` the explicitly configured process ``request_timeout``, kept only when the + router has a timeout of its own, as the Python router keeps them.""" + + default_litellm_params: Mapping[str, object] + timeout: object + explicit_timeout: object + request_timeout: float | None + stream_timeout: object + cache_responses: bool + + +def as_dict(value: object) -> dict[str, object]: # mutable-ok: a fresh dict of a request mapping + try: + return dict(_MAPPING.validate_python(value)) + except ValidationError: + return {} + + +def _mapping(value: object) -> Mapping[str, object] | None: + try: + return _MAPPING.validate_python(value) + except ValidationError: + return None + + +def metadata_bucket( + kwargs: MutableMapping[str, object], # mutable-ok: the request kwargs the Python router mutates in place + name: str, +) -> dict[str, object]: # mutable-ok: the request's own bucket + """``kwargs.setdefault(name, {})``: the request's own metadata dict, created when absent.""" + bucket: Final = kwargs.get(name) + if isinstance(bucket, dict): + return bucket # pyright: ignore[reportUnknownVariableType] # the request's untyped metadata dict + if name not in kwargs: + fresh: Final[dict[str, object]] = {} # mutable-ok: the request kwargs the Python router mutates in place + kwargs[name] = fresh # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + return fresh + # A non-dict value under the key: `setdefault` returns it as is, and `.update` would raise. + raise AttributeError(f"'{type(bucket).__name__}' object has no attribute 'update'") + + +# --- request params the deployment sets -------------------------------------------------------- + + +def _drops_malformed_request_tools( + deployment_params: Mapping[str, object], defaults: Mapping[str, object], request: Mapping[str, object] +) -> bool: + if isinstance(request.get("tools") or [], (list, tuple)) or not deployment_params.get("tools"): + return False + set_defaults: Final = {name: value for name, value in defaults.items() if value is not None} + return drop_policy({**deployment_params, **set_defaults, **request}).drops("tools") + + +def _malformed_request_params_the_deployment_sets( + deployment_params: Mapping[str, object], defaults: Mapping[str, object], request: Mapping[str, object] +) -> frozenset[str]: + overrides: Final = { + key: value + for key, value in request.items() + if key in SUPPLEMENTAL_KWARGS_KEYS and deployment_params.get(key) is not None + } + if not overrides: + return frozenset() + try: + validate_litellm_params_strictly(GenericLiteLLMParams, overrides) + except ValidationError as error: + set_defaults: Final = {name: value for name, value in defaults.items() if value is not None} + policy: Final = drop_policy({**deployment_params, **set_defaults, **request}) + malformed: Final = (str(detail["loc"][0]) for detail in error.errors() if detail["loc"]) + return frozenset(key for key in malformed if policy.drops(key)) + return frozenset() + + +def _merged_tools( + deployment_tools: Sequence[object], request_tools: object +) -> list[object] | None: # mutable-ok: sent as the request's tools + if not isinstance(request_tools, (list, tuple)): + return None + items: Final[Sequence[object]] = request_tools # pyright: ignore[reportUnknownVariableType] # a request's untyped tools + return [*deployment_tools, *items] if deployment_tools or items else None + + +def merge_tools_from_deployment( + deployment_params: Mapping[str, object], + kwargs: MutableMapping[str, object], # mutable-ok: the request kwargs the Python router mutates in place + defaults: Mapping[str, object], +) -> None: + """``_merge_tools_from_deployment``: deployment tools first, then the request's; the request's + ``tool_choice`` else the deployment's.""" + if _drops_malformed_request_tools(deployment_params, defaults, kwargs): + for name in TOOL_FIELDS: + kwargs.pop(name, None) + deployment_tools: Final = deployment_params.get("tools") or [] # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + merged: Final = _merged_tools( + deployment_tools if isinstance(deployment_tools, list) else [], # pyright: ignore[reportUnknownArgumentType] # the deployment's untyped tools + kwargs.get("tools") or [], + ) + if merged is not None: + kwargs["tools"] = merged # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + if "tool_choice" not in kwargs and deployment_params.get("tool_choice") is not None: + kwargs["tool_choice"] = ( # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + deployment_params["tool_choice"] + ) + + +def _deployment_sets_litellm_param(deployment_params: Mapping[str, object], key: str) -> bool: + value: Final = deployment_params.get(key) + if value is None: + return False + field: Final = LiteLLM_Params.model_fields.get(key) + return field is None or value != field.default # pyright: ignore[reportAny] # litellm's untyped helpers and request values + + +def _forwarded_alias_marker_keys_the_deployment_sets( + deployment_params: Mapping[str, object], forwarded_keys: object +) -> tuple[str, ...]: + if not isinstance(forwarded_keys, tuple): + return () + keys: Final[tuple[object, ...]] = forwarded_keys # pyright: ignore[reportUnknownVariableType] # the router's own marker + return tuple(key for key in keys if isinstance(key, str) and _deployment_sets_litellm_param(deployment_params, key)) + + +# --- reasoning effort ------------------------------------------------------------------------- + + +def _pop_effort_from_nested_carrier(params: dict[str, object], carrier: str) -> None: # mutable-ok: copy-on-write + nested: Final = _mapping(params.get(carrier)) if isinstance(params.get(carrier), Mapping) else None + if nested is None: + return + sanitized: Final = without(nested, "effort") + if sanitized: + params[carrier] = ( # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + sanitized + ) + else: + params.pop(carrier, None) + + +def deployment_params_with_request_reasoning_override( + deployment_params: Mapping[str, object], request_kwargs: Mapping[str, object] +) -> dict[str, object]: # mutable-ok: the call's own copy of the deployment params + """``_deployment_params_with_request_reasoning_override``: a request ``reasoning_effort`` drops + the deployment's ``thinking`` and nested ``effort`` carriers.""" + sanitized: Final = dict(deployment_params) + if request_kwargs.get("reasoning_effort") is None: + return sanitized + sanitized.pop("thinking", None) + _pop_effort_from_nested_carrier(sanitized, "output_config") + _pop_effort_from_nested_carrier(sanitized, "reasoning") + extra_body: Final = sanitized.get("extra_body") + if isinstance(extra_body, Mapping): + sanitized_extra_body: Final = as_dict(extra_body) # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + sanitized_extra_body.pop("reasoning_effort", None) + sanitized_extra_body.pop("thinking", None) + _pop_effort_from_nested_carrier(sanitized_extra_body, "output_config") + _pop_effort_from_nested_carrier(sanitized_extra_body, "reasoning") + if sanitized_extra_body: + sanitized["extra_body"] = sanitized_extra_body + else: + sanitized.pop("extra_body", None) + return sanitized + + +def _is_classifier_internal_call(kwargs: Mapping[str, object]) -> bool: + return any( + isinstance(candidate, Mapping) + and (_mapping(candidate) or {}).get(INTERNAL_CALL_ORIGIN_METADATA_KEY) == AUTOROUTER_CLASSIFIER_CALL_ORIGIN # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + for candidate in (kwargs.get("metadata"), kwargs.get("litellm_metadata")) + ) + + +def _declared_param_allowlist(params: Mapping[str, object]) -> frozenset[str]: + declared: Final = params.get("allowed_openai_params") + if not isinstance(declared, (list, tuple, set, frozenset)): + return frozenset() + entries: Final[Sequence[object]] = list(declared) # pyright: ignore[reportUnknownArgumentType] # the deployment's untyped allowlist + return frozenset(entry for entry in entries if isinstance(entry, str)) + + +def _deployment_supports_param(deployment: Mapping[str, object], group: str, param: str, host: "PythonHost") -> bool: + params: Final = as_dict(deployment.get("litellm_params")) + if not params: + return True + model_info: Final = as_dict(deployment.get("model_info")) + base_model: Final = model_info.get("base_model") or params.get("base_model") + try: + model_label: Final = str(params.get("model") or group) + provider_param: Final = params.get("custom_llm_provider") + authenticating: Final = declared_authenticating_provider( + model_label, provider_param if isinstance(provider_param, str) else None + ) + if authenticating is not None: + model, custom_llm_provider = model_label.removeprefix(f"{authenticating}/"), authenticating + else: + model, custom_llm_provider, _, _ = host.invoke( # rebind-ok: rebound as the Python router rebinds it + "get_llm_provider" + )( + model=model_label, + custom_llm_provider=provider_param, + litellm_params=LiteLLM_Params.model_validate(params), + ) + supported: Final = host.invoke("get_supported_openai_params")( + model=model, + custom_llm_provider=custom_llm_provider, + base_model=base_model if isinstance(base_model, str) else None, + ) + except Exception: # noqa: BLE001 # best-effort filter: an unresolvable provider must not narrow the request + return True + return supported is None or param in supported + + +def deployment_accepts_param(deployment: Mapping[str, object], group: str, param: str, host: "PythonHost") -> bool: + params: Final = as_dict(deployment.get("litellm_params")) + if not params: + return True + if param in _declared_param_allowlist(params): + return True + provider_param: Final = params.get("custom_llm_provider") + if declared_authenticating_provider( + str(params.get("model") or ""), provider_param if isinstance(provider_param, str) else None + ): + return True + return _deployment_supports_param(deployment, group, param, host) + + +def drop_unsupported_classifier_reasoning_effort( + deployment: Mapping[str, object], + model: str, + kwargs: MutableMapping[str, object], # mutable-ok: the request kwargs the Python router mutates in place + host: "PythonHost", +) -> None: + """``_drop_unsupported_classifier_reasoning_effort``.""" + if kwargs.get("reasoning_effort") is None or not _is_classifier_internal_call(kwargs): + return + if deployment_accepts_param(deployment, model, "reasoning_effort", host): + return + kwargs.pop("reasoning_effort", None) + proxy_server_request: Final = kwargs.get("proxy_server_request") + if not isinstance(proxy_server_request, dict): + return + body: Final[object] = proxy_server_request.get("body") # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the proxy's untyped request + if isinstance(body, dict): + body.pop("reasoning_effort", None) # pyright: ignore[reportUnknownMemberType] # same + + +# --- timeouts --------------------------------------------------------------------------------- + + +def stream_timeout(shaping: Shaping, kwargs: Mapping[str, object], data: Mapping[str, object]) -> object: + """``_get_stream_timeout``.""" + return ( + kwargs.get("stream_timeout", None) + or get_service_tier_timeout(kwargs.get("service_tier"), data, "stream_timeout_by_service_tier") + or data.get("stream_timeout", None) + or shaping.stream_timeout + or shaping.request_timeout + or shaping.default_litellm_params.get("stream_timeout", None) + ) + + +def non_stream_timeout(shaping: Shaping, kwargs: Mapping[str, object], data: Mapping[str, object]) -> object: + """``_get_non_stream_timeout``.""" + return ( + kwargs.get("timeout", None) + or kwargs.get("request_timeout", None) + or get_service_tier_timeout(kwargs.get("service_tier"), data, "timeout_by_service_tier") + or data.get("timeout", None) + or data.get("request_timeout", None) + or shaping.request_timeout + or shaping.timeout + or shaping.default_litellm_params.get("timeout", None) + ) + + +def call_timeout(shaping: Shaping, kwargs: Mapping[str, object], data: Mapping[str, object]) -> object: + """``_get_timeout``.""" + stream: Final = stream_timeout(shaping, kwargs, data) if kwargs.get("stream") else None + return stream if stream is not None else non_stream_timeout(shaping, kwargs, data) + + +# --- default litellm params ------------------------------------------------------------------- + + +def update_kwargs_with_default_litellm_params( + shaping: Shaping, + kwargs: MutableMapping[str, object], # mutable-ok: the request kwargs the Python router mutates in place + metadata_variable_name: str, +) -> None: + """``_update_kwargs_with_default_litellm_params``: unset non-None defaults fill the request; + the default metadata is merged over the request's.""" + defaults: Final = dict(without_retrieve_stream_defaults(shaping.default_litellm_params, kwargs)) + metadata_defaults: Final = defaults.pop("metadata", {}) or {} # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + for key, value in defaults.items(): + if value is None: + continue + kwargs.setdefault(key, value) + metadata_bucket(kwargs, metadata_variable_name).update(as_dict(metadata_defaults)) # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + + +# --- clientside credentials ------------------------------------------------------------------- + + +def _clientside_deployment( + deployment: Mapping[str, object], kwargs: Mapping[str, object], function_name: str | None +) -> tuple[Mapping[str, object], str, object]: + """``_handle_clientside_credential``: the request-scoped model_info, model and api_base.""" + model_info: Final = as_dict(deployment.get("model_info")) + litellm_params: Final = as_dict(deployment.get("litellm_params")) + dynamic_litellm_params: Final = get_dynamic_litellm_params( # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + litellm_params=litellm_params, request_kwargs=dict(kwargs) + ) + metadata_variable_name: Final = get_router_metadata_variable_name(function_name=function_name) + model_group: Final = as_dict(kwargs.get(metadata_variable_name)).get("model_group") + model_id: Final = generate_deployment_id(model_group, dynamic_litellm_params) # pyright: ignore[reportArgumentType, reportUnknownArgumentType] # the group as the request carries it + original_model_id: Final = model_info.get("id") + model_info["id"] = model_id + model_info["original_model_id"] = original_model_id + built: Final = Deployment( + model_name=model_group, # pyright: ignore[reportArgumentType] # the group as the request carries it + litellm_params=LiteLLM_Params.model_validate(dynamic_litellm_params), + model_info=model_info, # pyright: ignore[reportArgumentType] # model_info as configured + ) + return built.model_info.model_dump(), built.litellm_params.model, built.litellm_params.api_base + + +# --- the deployment -------------------------------------------------------------------------- + + +def update_kwargs_with_deployment( + shaping: Shaping, + deployment: Mapping[str, object], + kwargs: MutableMapping[str, object], # mutable-ok: the request kwargs the Python router mutates in place + *, + cache: "DualCache | None", + function_name: str | None = None, + splits_stream_timeout: bool = False, + opens_responses_socket: bool = False, +) -> None: + """``_update_kwargs_with_deployment``, in place on the attempt's kwargs.""" + deployment_params: Final = as_dict(deployment.get("litellm_params")) + for key in _forwarded_alias_marker_keys_the_deployment_sets( + deployment_params, kwargs.pop(_ALIAS_MARKER_FORWARDED_PARAMS_KWARG, ()) + ): + kwargs.pop(key, None) + kwargs.pop("daily_reset_time", None) + defaults: Final = shaping.default_litellm_params + merge_tools_from_deployment(deployment_params, kwargs, defaults) + + model_info: Mapping[str, object] = as_dict( # rebind-ok: rebound as the Python router rebinds it + deployment.get("model_info") + ) + deployment_model: object = deployment_params.get("model") # rebind-ok: same + deployment_api_base: object = deployment_params.get("api_base") # rebind-ok: same + deployment_model_name: Final = deployment.get("model_name") + from litellm.litellm_core_utils.get_provider_specific_headers import ProviderSpecificHeaderUtils + + for key in _malformed_request_params_the_deployment_sets(deployment_params, defaults, kwargs): + kwargs.pop(key) + declared_provider: Final = deployment_params.get("custom_llm_provider") + declared_model: Final = deployment_params.get("model") + deployment_provider: Final = ( + declared_provider + if isinstance(declared_provider, str) + else inferred_provider(declared_model if isinstance(declared_model, str) else None) + ) + forwarded_authorization: Final = ( + ProviderSpecificHeaderUtils.forwarded_authorization(kwargs.get("provider_specific_header"), deployment_provider) + if deployment_provider in _FORWARDED_CREDENTIAL_ISOLATION_PROVIDERS + else None + ) + if is_clientside_credential(request_kwargs=dict(kwargs)) or forwarded_authorization is not None: + model_info, deployment_model, deployment_api_base = ( # rebind-ok: rebound as the Python router rebinds it + _clientside_deployment( + deployment, + {**kwargs, **({"api_key": forwarded_authorization} if forwarded_authorization is not None else {})}, + function_name, + ) + ) + + metadata_variable_name: Final = get_router_metadata_variable_name(function_name=function_name) + routing: Final = deployment.get(KUBERNETES_POD_ROUTING_KEY) + metadata: Final = metadata_bucket(kwargs, metadata_variable_name) + metadata.update( + { + "deployment": deployment_model, + "model_info": model_info, + "api_base": deployment_api_base, + "deployment_model_name": deployment_model_name, + KUBERNETES_POD_ROUTING_KEY: routing, + } + ) + other_bucket: Final = "metadata" if metadata_variable_name == "litellm_metadata" else "litellm_metadata" + other_bucket_metadata: Final = kwargs.get(other_bucket) + if isinstance(other_bucket_metadata, Mapping) and KUBERNETES_POD_ROUTING_KEY in other_bucket_metadata: + kwargs[other_bucket] = {**as_dict(other_bucket_metadata), KUBERNETES_POD_ROUTING_KEY: routing} # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + + if cache is not None: + refund_stale_reservation_before_retry(cache, kwargs) # pyright: ignore[reportArgumentType] # the request's kwargs dict + set_io_token_rate_limit_request_kwargs( + kwargs, # pyright: ignore[reportArgumentType] # the request's kwargs dict + store_in_context=deployment_has_io_token_limits(deployment), # pyright: ignore[reportArgumentType] # a deployment record + opens_responses_socket=opens_responses_socket, + metadata_channel=metadata_variable_name, + ) + metadata.setdefault( + ROUTING_REQUEST_TAGS_METADATA_KEY, + tuple(get_tags_from_request_kwargs(kwargs, metadata_variable_name=metadata_variable_name)), # pyright: ignore[reportArgumentType] # the request's kwargs dict + ) + deployment_tags: Final = deployment_params.get("tags") + merged_tags: Final = tags_with_serving_deployment_tags(metadata, deployment_tags) + if merged_tags is not None: + metadata["tags"] = list(merged_tags) + baggage_stamp: Final = baggage_stamp_for_serving_deployment(metadata, deployment_tags) + if baggage_stamp is not None: + metadata[BAGGAGE_MAPPED_TAGS_METADATA_KEY] = baggage_stamp + + credential_name: Final = deployment_params.get("litellm_credential_name") + if credential_name: + credential_tag: Final = f"Credential: {credential_name}" + existing_tags: Final = metadata.get("tags") or [] # pyright: ignore[reportUnknownVariableType] # litellm's untyped helpers and request values + if isinstance(existing_tags, list) and credential_tag not in existing_tags: + existing_tags.append(credential_tag) # pyright: ignore[reportUnknownMemberType] # the request's own tags list + metadata["tags"] = existing_tags + + from litellm.llms.github_copilot.per_user_auth import github_copilot_per_user_credential_name + + configured_per_user_name: Final = github_copilot_per_user_credential_name(deployment_params) + caller_credential_name: Final = kwargs.get("litellm_credential_name") + if ( + configured_per_user_name is not None + and isinstance(caller_credential_name, str) + and caller_credential_name != configured_per_user_name + ): + raise litellm_exceptions.BadRequestError( + message="litellm_credential_name cannot be overridden on a deployment that uses per-user GitHub OAuth", + model=str(deployment_model_name), + llm_provider="", + ) + + kwargs["model_info"] = ( # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + model_info + ) + _set_timeouts(shaping, deployment_params, kwargs, function_name, splits_stream_timeout) + + if router_config_requests_stream_usage(kwargs, (deployment_params, defaults)): + kwargs[ # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + STREAM_USAGE_INJECTED_FIELD + ] = True + update_kwargs_with_default_litellm_params(shaping, kwargs, metadata_variable_name) + pinned_model_id: Final = deployment_model_id_pin(deployment_params) + if pinned_model_id is not None: + kwargs["model_id"] = ( # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + pinned_model_id + ) + + +def _set_timeouts( + shaping: Shaping, + deployment_params: Mapping[str, object], + kwargs: MutableMapping[str, object], # mutable-ok: the request kwargs the Python router mutates in place + function_name: str | None, + splits_stream_timeout: bool, +) -> None: + if function_name == "_ageneric_api_call_with_fallbacks": + from litellm.passthrough.timeout_utils import resolve_llm_passthrough_timeout + + router_timeout: Final = ( + shaping.request_timeout + if shaping.request_timeout is not None + else float(shaping.explicit_timeout) + if isinstance(shaping.explicit_timeout, (int, float)) + else None + ) + router_stream_timeout: Final = ( + shaping.stream_timeout + if shaping.stream_timeout is not None + else shaping.request_timeout + if shaping.request_timeout is not None + else shaping.default_litellm_params.get("stream_timeout") + ) + passthrough_timeout: Final = partial( + resolve_llm_passthrough_timeout, + litellm_params=deployment_params, + router_timeout=router_timeout, + router_stream_timeout=router_stream_timeout, # pyright: ignore[reportArgumentType] # a configured default, passed as the Python router passes it + ) + timeout_request: Final = {**kwargs, "stream": True} if requests_streamed_retrieval(kwargs) else dict(kwargs) + kwargs.update( + CompletionTimeout.stream_request_kwargs( + passthrough_timeout(kwargs={**kwargs, "stream": False}), passthrough_timeout(kwargs=timeout_request) + ) + if splits_stream_timeout and timeout_request.get("stream") + else {"timeout": passthrough_timeout(kwargs=timeout_request)} + ) + elif splits_stream_timeout: + kwargs.update( + CompletionTimeout.stream_request_kwargs( + non_stream_timeout(shaping, kwargs, deployment_params), + stream_timeout(shaping, kwargs, deployment_params) if kwargs.get("stream") else None, + ) + ) + else: + kwargs["timeout"] = ( # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + call_timeout(shaping, kwargs, deployment_params) + ) + + +def stamp_deployment_num_retries(error: BaseException, deployment: Mapping[str, object]) -> None: + """``_set_deployment_num_retries_on_exception``.""" + if getattr(error, "num_retries", None) is not None: + return + value: Final = as_dict(deployment.get("litellm_params")).get("num_retries") + if value is None: + return + try: + error.num_retries = int(str(value)) if not isinstance(value, int) else value # pyright: ignore[reportAttributeAccessIssue] # the router stamps the same attribute # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + except (ValueError, TypeError): + pass + + +def stamp_failed_deployment_id(error: BaseException, model_info: object) -> None: + """``_set_failed_deployment_id_on_exception`` with the effective model_info.""" + if getattr(error, "failed_deployment_id", None): + return + deployment_id: Final = as_dict(model_info).get("id") + if deployment_id: + try: + error.failed_deployment_id = deployment_id # pyright: ignore[reportAttributeAccessIssue] # the router stamps the same attribute # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + except Exception: # noqa: BLE001, S110 # as the Python router: a read-only error keeps its attributes + pass + + +def stamp_retry_skip_deployment_id(error: BaseException, kwargs: Mapping[str, object]) -> None: + """``_stamp_retry_skip_deployment_id``.""" + model_info: Final = kwargs.get("model_info") + if not isinstance(model_info, Mapping): + return + info: Final = as_dict(model_info) # pyright: ignore[reportUnknownArgumentType] # litellm's untyped helpers and request values + configured: Final = ( + info.get("original_model_id") if isinstance(error, litellm_exceptions.UnsupportedEndpointError) else None + ) + deployment_id: Final = configured or info.get("id") + if isinstance(deployment_id, str) and deployment_id: + error.retry_skip_deployment_id = deployment_id # pyright: ignore[reportAttributeAccessIssue] # dynamic stamp, read on retry # rebind-ok: the request kwargs are shaped in place, as the Python router shapes them + + +NO_PARAMS: Final[Mapping[str, object]] = MappingProxyType({}) + +__all__ = [ + "STREAM_TIMEOUT_AWARE_GENERIC_HANDLERS", + "Shaping", + "as_dict", + "call_timeout", + "deployment_params_with_request_reasoning_override", + "drop_unsupported_classifier_reasoning_effort", + "merge_tools_from_deployment", + "metadata_bucket", + "stamp_deployment_num_retries", + "stamp_failed_deployment_id", + "stamp_retry_skip_deployment_id", + "update_kwargs_with_default_litellm_params", + "update_kwargs_with_deployment", +] diff --git a/litellm/router_rust/invoke/slots.py b/litellm/router_rust/invoke/slots.py new file mode 100644 index 00000000000..08e88b5b2f1 --- /dev/null +++ b/litellm/router_rust/invoke/slots.py @@ -0,0 +1,107 @@ +""" +A deployment's ``max_parallel_requests`` slot on the Rust router core (``_deployment_slot`` and +``_get_client(client_type="max_parallel_requests")``): the attempt holds one of the deployment's +slots around its provider call, and an open chat stream keeps it until the stream is exhausted, +closed, or falls back. A caller arriving while every slot is taken gets a 429, which the core +records as that attempt's failure. + +The limit object is the one the Python router caches (``MaxParallelRequestsLimit``), kept in the +core's routing cache under the same key, so its in-flight count is shared by every attempt. +""" + +import contextlib +from collections.abc import Mapping +from typing import TYPE_CHECKING, Final + +from litellm._internal_context import with_service_target +from litellm.router_rust.invoke.shaping import ROUTER_CLIENTS_TARGET, as_dict + +if TYPE_CHECKING: + from litellm.router_rust.invoke.endpoints import EndpointCore, Plan + +# The attempt helpers that run inside `_deployment_slot` (`_acompletion` holds the same slot +# itself). Sync helpers, rerank, moderation and the search helper hold none. +_SLOTTED_KINDS: Final = frozenset( + { + "chat", + "text", + "embedding", + "image", + "transcription", + "speech", + "adapter", + "generic", + "batch", + "cancel_batch", + "vector_store_create", + } +) + + +@with_service_target(ROUTER_CLIENTS_TARGET) +def max_parallel_requests_limit( + core: "EndpointCore", deployment: Mapping[str, object], kwargs: Mapping[str, object] +) -> object: + """`_get_client(client_type="max_parallel_requests")`: the cached limit, built on first use + (`InitalizeCachedClient.set_max_parallel_requests_client`).""" + from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs + from litellm.router_utils.client_initalization_utils import MaxParallelRequestsLimit + from litellm.utils import calculate_max_parallel_requests + + model_id: Final = as_dict(deployment.get("model_info")).get("id") + key: Final = f"{model_id}_max_parallel_requests_client" + span: Final = get_parent_otel_span_from_kwargs(dict(kwargs)) + cache: Final = core.routing_cache + cached: Final[object] = cache.get_cache(key=key, local_only=True, parent_otel_span=span) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType, reportArgumentType] # the cache holds untyped values + if cached is not None: + return cached # pyright: ignore[reportUnknownVariableType] # the cache holds untyped values + params: Final = as_dict(deployment.get("litellm_params")) + calculated: Final = calculate_max_parallel_requests( + rpm=params.get("rpm"), # pyright: ignore[reportArgumentType] # the configured value, as the Python router reads it + max_parallel_requests=params.get("max_parallel_requests"), # pyright: ignore[reportArgumentType] # same + tpm=params.get("tpm"), # pyright: ignore[reportArgumentType] # same + default_max_parallel_requests=core.endpoints.default_max_parallel_requests, # pyright: ignore[reportArgumentType] # the setting as given, as the Python router passes it + ) + if calculated: + cache.set_cache( # pyright: ignore[reportUnknownMemberType] # the routing cache + key=key, + value=MaxParallelRequestsLimit( + max_parallel_requests=calculated, + model_id=str(model_id), + model_group=str(deployment.get("model_name", "")), + ), + local_only=True, + ) + return cache.get_cache(key=key, local_only=True, parent_otel_span=span) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType, reportArgumentType] # see above + + +def enter_deployment_slot( + core: "EndpointCore", plan: "Plan", deployment: Mapping[str, object], kwargs: Mapping[str, object] +) -> contextlib.ExitStack: + """The attempt's slot, entered (a full deployment raises its 429 here); an empty stack when + the plan's helper holds none or the deployment has no limit.""" + from litellm.router_utils.client_initalization_utils import MaxParallelRequestsLimit + + slot: Final = contextlib.ExitStack() + if plan.sync or plan.kind not in _SLOTTED_KINDS: + return slot + limit: Final = max_parallel_requests_limit(core, deployment, kwargs) + if isinstance(limit, MaxParallelRequestsLimit): + slot.enter_context(limit) + return slot + + +def deployment_slot( + core: "EndpointCore", deployment: Mapping[str, object], kwargs: Mapping[str, object] +) -> contextlib.ExitStack: + """`_deployment_slot` outside a plan's attempt (a file created on every deployment).""" + from litellm.router_utils.client_initalization_utils import MaxParallelRequestsLimit + + slot: Final = contextlib.ExitStack() + limit: Final = max_parallel_requests_limit(core, deployment, kwargs) + if isinstance(limit, MaxParallelRequestsLimit): + slot.enter_context(limit) + return slot + + +__all__ = ["deployment_slot", "enter_deployment_slot", "max_parallel_requests_limit"] diff --git a/litellm/router_rust/invoke/streaming.py b/litellm/router_rust/invoke/streaming.py new file mode 100644 index 00000000000..ca70143072f --- /dev/null +++ b/litellm/router_rust/invoke/streaming.py @@ -0,0 +1,1839 @@ +""" +The stream wrappers of the Rust router core: host-side objects around a streamed response. + +Every attempt the Rust core runs that returns a stream is wrapped here before the core sees the +outcome, the way the Python router wraps each attempt's stream: + +- a chat stream (``CustomStreamWrapper``) has its first chunk read inside the attempt, so a stream + that fails before any token fails the attempt and the core retries or falls back as for any error +- a chat, ``/v1/messages`` or Responses stream that fails later, before the caller received content, + hands the failure back to the core: the core decides whether a same-group retry or a fallback takes + over (``RouterCoreHandle.stream_policy`` / ``retry_stream`` / ``fallback_stream``), and the wrapper + splices what that call returns into the stream the caller already holds + +Each wrapper also reports its stream's outcome to the core when the stream ends, as litellm's stream +logging reports it to the Python router's callbacks: the attempt that returned the stream counted +only its request (the attempt answer is ``deferred``), so the success with the stream's final tokens, +or a failure the stream raised after it opened, is recorded then (``StreamAttempt.report_success`` / +``report_failure``). A stream closed before it ends reports nothing. + +The wrappers decide nothing about routing: what may take over, the retry budget and every +deployment pick come from the core. They hold live Python iterators, frames and hidden params, +which is why they live in the host. Ported from the Python router's ``_acompletion_streaming_iterator``, +``_completion_streaming_iterator``, ``_aanthropic_messages_streaming_iterator`` and +``_aresponses_streaming_iterator``, without importing it. +""" + +import asyncio +import contextlib +import dataclasses +import json +import weakref +from collections.abc import ( + AsyncGenerator, + AsyncIterable, + AsyncIterator, + Awaitable, + Callable, + Coroutine, + Generator, + Iterable, + Iterator, + Mapping, + Sequence, +) +from typing import ( + TYPE_CHECKING, + Final, + Generic, + NoReturn, + TypeAlias, + TypeVar, + cast, # noqa: TID251 # untyped stream iterators and provider chunk lists +) + +import anyio + +import litellm.exceptions as litellm_exceptions +from litellm._logging import verbose_router_logger +from litellm.exceptions import MidStreamFallbackError +from litellm.litellm_core_utils.add_retry_fallback_headers import ( + add_retry_headers_to_response, + get_hidden_params_dict, + replace_complexity_router_headers, +) +from litellm.litellm_core_utils.core_helpers import as_str_mapping, without +from litellm.litellm_core_utils.hidden_params import HIDDEN_PARAMS_ATTR, get_hidden_params, set_hidden_params +from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper +from litellm.router_rust.surface.health import failure_already_logged, logged_call +from litellm.types.utils import ModelResponseStream, Usage + +if TYPE_CHECKING: + from litellm.responses.streaming_iterator import BaseResponsesAPIStreamingIterator + from litellm.router_python_host import PythonHost + from litellm.router_rust.core import RustCore + from litellm.router_utils.pre_call_checks.continuation_prefill_check import ContinuationOutput, ContinuedPartial + from litellm.types.llms.openai import ResponseAPIUsage, ResponseIncompleteEvent + +# A stream that never emits content or an error could grow a held-frame buffer without bound, so +# hitting either cap commits the stream instead. +MAX_BUFFERED_PRE_CONTENT_ANTHROPIC_CHUNKS: Final = 200 +MAX_HELD_PRE_OUTPUT_RESPONSES_EVENTS: Final = 200 + +# The hidden params and headers a fallback's response carries, as dicts the proxy writes into. +_Prepared: TypeAlias = "tuple[dict[str, object], dict[str, object]]" +_RestT: Final = TypeVar("_RestT", Iterator[object], AsyncIterator[object]) + + +# --- the attempt a stream came from ------------------------------------------------------------- + + +@dataclasses.dataclass(slots=True) +class StreamAttempt: + """The attempt that returned a stream, and the core that can still recover it. + + ``request`` is the call's prepared request, the one every attempt of the call is built from; + ``kwargs`` are this attempt's own kwargs. The origin fields are what the core reads to decide + what may take over a failure of this stream. + """ + + core: "RustCore" + op: str + request: Mapping[str, object] + kwargs: Mapping[str, object] + group: str + order: int | None + depth: int + level: int + deployment_id: str | None + attempted_retries: int + committed_budget: int | None = None + # The deployment's max_parallel_requests slot the attempt holds; an open chat stream takes it. + slot: contextlib.ExitStack | None = None + # Set by the wrapper that reports the stream's outcome when it ends; the attempt's answer is then + # deferred and counts only the request and the tokens read so far (``counted_tokens``). + reports_outcome: bool = False + counted_tokens: int = 0 + outcome_reported: bool = False + # The background recording of the stream's failure, which a same-group retry waits for so it + # picks with the failed deployment already cooled down. + failure_recording: "asyncio.Task[None] | None" = None + + @property + def model_group(self) -> str: + return self.group + + def origin(self) -> Mapping[str, object]: + return { + "group": self.group, + "order": self.order, + "depth": self.depth, + "level": self.level, + "deployment_id": self.deployment_id, + "attempted_retries": self.attempted_retries, + "committed_budget": self.committed_budget, + } + + def policy(self, trigger: BaseException | None = None) -> Mapping[str, object]: + return self.core.stream_policy(self.request, self.origin(), trigger) + + def can_retry(self) -> bool: + return self.policy().get("can_retry") is True + + def can_fall_back(self) -> bool: + return self.policy().get("can_fall_back") is True + + def refusal_fallback_available(self) -> bool: + return self.policy().get("refusal_fallback") is True + + def retry_budget(self, trigger: BaseException) -> tuple[int, bool]: + policy: Final = self.policy(trigger) + budget: Final = policy.get("retry_budget") + return (budget if isinstance(budget, int) else 0), policy.get("policy_applies") is True + + def should_retry_status(self, status_code: int) -> bool: + return bool(self.core._host.invoke("should_retry")(status_code)) # pyright: ignore[reportPrivateUsage, reportUnknownMemberType] # the wrapper serves its own core's host + + async def fallback(self, trigger: BaseException, request: Mapping[str, object] | None = None) -> object: + """The fallback walk for this stream's failure; raises when no fallback answers.""" + return await self.core.recover_stream("fallback", self.op, request or self.request, self.origin(), trigger) + + def fallback_sync(self, trigger: BaseException) -> object: + return self.core.recover_stream_sync("fallback", self.op, self.request, self.origin(), trigger) + + async def retry(self, trigger: BaseException) -> "tuple[object, int, int] | BaseException": + """A same-group retry: the retried response with the retry count and budget, or the newest failure.""" + return await self.core.retry_stream(self.op, self.request, self.origin(), trigger) + + # -- the stream's outcome, reported once when it ends -------------------------------------- + + def logged(self) -> dict[str, object]: # mutable-ok: litellm's logging kwargs + """The logging kwargs litellm's stream logging hands the outcome callbacks, for this attempt.""" + from litellm.constants import ROUTER_USAGE_COUNTED_TOKENS_METADATA_KEY + + kwargs: Final = self.kwargs + metadata: Final = as_str_mapping(kwargs.get("litellm_metadata")) or as_str_mapping(kwargs.get("metadata")) or {} + return { + "call_type": self.op, + "litellm_params": { + "metadata": {**metadata, ROUTER_USAGE_COUNTED_TOKENS_METADATA_KEY: self.counted_tokens}, + "model_info": kwargs.get("model_info") or {}, + "api_base": kwargs.get("api_base"), + "client_side_timeout": kwargs.get("client_side_timeout"), + "timeout": kwargs.get("timeout"), + **({"cooldown_time": kwargs["cooldown_time"]} if "cooldown_time" in kwargs else {}), + }, + } + + def _failure_logged(self, error: BaseException) -> dict[str, object]: # mutable-ok: litellm's logging kwargs + return {**logged_call(self.op, self.kwargs), **self.logged(), "exception": _provider_error(error)} + + def _callbacks(self, *, sync: bool) -> Mapping[str, bool]: + """The outcome callbacks that run for this attempt when its stream ends.""" + return self.core.outcome_callbacks(self.kwargs, sync=sync) + + def _claim(self) -> bool: + if not self.reports_outcome or self.outcome_reported: + return False + self.outcome_reported = True + return True + + def report_success(self, total_tokens: int, last: object = None) -> None: + """The stream ended: count its success and the tokens the attempt did not count, and re-pin + the session on ``last``, the stream's final item (``deployment_callback_on_success``), in the + background.""" + if self._claim(): + logged: Final = {**self.logged(), "standard_logging_object": {"total_tokens": total_tokens}} + _record_in_background(self.core.report_stream_success(logged, last, self._callbacks(sync=False))) + + def report_failure(self, error: BaseException) -> None: + """The stream failed after it opened: count the failure, cool down by the rules and count one + more request (``async_deployment_callback_on_failure``), in the background. A logging object + shared with an earlier failure blocks it: the stream logs through ``attempt_scoped_copy``, read + here, when the stream fails.""" + if self._claim() and not failure_already_logged(self.kwargs, "async_failure"): + self.failure_recording = _record_in_background( + self.core.report_stream_failure(self._failure_logged(error), self._callbacks(sync=False)) + ) + + async def failure_recorded(self) -> None: + """Wait for the stream's failure to be recorded, if one is being recorded.""" + recording: Final = self.failure_recording + if recording is not None and not recording.done(): + _ = await asyncio.wait({recording}) + + def report_first_chunk_failure(self, error: BaseException) -> None: + """The stream failed before its attempt returned it. ``_dispatch_stream_failure`` logs that in + a task of its own, so the record reads the error as the router left it by then, with its + routing note when no real suspension came first. The attempt checked the logging object.""" + _record_in_background(self.core.report_stream_failure(self._failure_logged(error), self._callbacks(sync=False))) + + def report_success_sync(self) -> None: + """A sync stream ended: a sync call's success callback counts the success alone.""" + if self._claim(): + _record_now(lambda: self.core.report_stream_success_sync(self.logged(), self._callbacks(sync=True))) + + def report_failure_sync(self, error: BaseException) -> None: + """A sync stream failed after it opened: counted and cooled down, with no request counted.""" + if self._claim() and not failure_already_logged(self.kwargs, "sync_failure"): + logged: Final = self._failure_logged(error) + _record_now(lambda: self.core.report_stream_failure_sync(logged, self._callbacks(sync=True))) + + +# --- reporting a stream's outcome --------------------------------------------------------------- + +# The background recordings still running, held so none is collected before it finishes. +_RECORDINGS: Final[set["asyncio.Task[None]"]] = set() # mutable-ok: tasks leave it when they finish + + +def _provider_error(error: BaseException) -> BaseException: + """The provider's own error, which the failure rules classify, rather than the router's envelope.""" + if isinstance(error, MidStreamFallbackError) and error.original_exception is not None: + return error.original_exception + return error + + +def _record_in_background(recording: Coroutine[object, object, object]) -> "asyncio.Task[None]": + """Run a recording through the core's async cache driver without holding up the stream, as litellm + schedules its stream logging.""" + + async def run() -> None: + try: + _ = await recording + except Exception as error: # noqa: BLE001 # a recording never fails the stream + verbose_router_logger.warning("a stream's outcome was not recorded: %s", error) + + task: Final = asyncio.get_running_loop().create_task(run()) + _RECORDINGS.add(task) + task.add_done_callback(_RECORDINGS.discard) + return task + + +def _record_now(recording: Callable[[], object]) -> None: + try: + _ = recording() + except Exception as error: # noqa: BLE001 # see _record_in_background + verbose_router_logger.warning("a stream's outcome was not recorded: %s", error) + + +_ItemT: Final = TypeVar("_ItemT") + + +async def _areported( + attempt: StreamAttempt, + items: AsyncIterable[_ItemT], + total_tokens: Callable[[object], int], + observe: Callable[[object], None] | None = None, +) -> AsyncGenerator[_ItemT, None]: + """``items``, reporting the attempt's stream once they end: a success with the tokens + ``total_tokens`` reads off the last item, or the failure they raise. Closed early, nothing is + reported. The wrapper marks the attempt (``reports_outcome``) when it wraps the stream, before + the attempt answers.""" + last: object = None # rebind-ok: the newest item + try: + async for item in items: + last = item + if observe is not None: + observe(item) + yield item + except Exception as error: + attempt.report_failure(error) + raise + attempt.report_success(total_tokens(last), last) + + +def _reported(attempt: StreamAttempt, items: Iterable[_ItemT]) -> Generator[_ItemT, None, None]: + """``_areported`` for a sync stream, whose success counts no tokens.""" + try: + yield from items + except Exception as error: + attempt.report_failure_sync(error) + raise + attempt.report_success_sync() + + +def _usage_total_tokens(usage: object) -> int: + mapping: Final = as_str_mapping(usage) + tokens: Final[object] = mapping.get("total_tokens") if mapping is not None else getattr(usage, "total_tokens", None) + return tokens if isinstance(tokens, int) and not isinstance(tokens, bool) and tokens > 0 else 0 + + +def _chat_total_tokens(last: object) -> int: + """The total tokens of a finished chat stream: its usage chunk's, else the final usage its last + chunk's hidden params carry once the stream assembled its response.""" + return _usage_total_tokens(getattr(last, "usage", None)) or _usage_total_tokens( + (get_hidden_params(last) or {}).get("usage") + ) + + +def _responses_total_tokens(last: object, source: object) -> int: + """The total tokens of a finished Responses stream: its terminal event's response usage.""" + for event in (last, getattr(source, "completed_response", None)): + tokens = _usage_total_tokens(getattr(getattr(event, "response", None), "usage", None)) + if tokens: + return tokens + return 0 + + +class _AnthropicStreamUsage: + """The usage a ``/v1/messages`` stream reports in its frames, as litellm logs it: the prompt's input, + cache-read and cache-write tokens on ``message_start`` (a ``message_delta`` may restate them), and the + cumulative output tokens on each ``message_delta``. A frame split across byte chunks is read once its + line completes.""" + + __slots__ = ("_open_line", "_output", "_prompt") + + def __init__(self) -> None: + self._open_line = b"" + self._prompt: dict[str, int] = {} # mutable-ok: the newest count per prompt field + self._output = 0 + + def observe(self, chunk: object) -> None: + if not isinstance(chunk, (bytes, bytearray)): + return + *lines, self._open_line = (self._open_line + bytes(chunk)).split(b"\n") + for line in lines: + if line.startswith(b"data:") and b'"usage"' in line: + self._read(line[len(b"data:") :]) + + def _read(self, payload: bytes) -> None: + try: + event: Final[object] = json.loads(payload) # pyright: ignore[reportAny] # plain JSON + except ValueError: + return + frame: Final = as_str_mapping(event) or {} + kind: Final = frame.get("type") + usage: Final = as_str_mapping( + (as_str_mapping(frame.get("message")) or {}).get("usage") if kind == "message_start" else frame.get("usage") + ) + if usage is None or kind not in ("message_start", "message_delta"): + return + for field in ("input_tokens", "cache_creation_input_tokens", "cache_read_input_tokens"): + count = usage.get(field) + if isinstance(count, int) and not isinstance(count, bool): + self._prompt[field] = count + output: Final = usage.get("output_tokens") + if isinstance(output, int) and not isinstance(output, bool): + self._output = output + + def total_tokens(self, _last: object = None) -> int: + return sum(self._prompt.values()) + self._output + + +# --- the first chunk ---------------------------------------------------------------------------- + + +@dataclasses.dataclass(frozen=True, slots=True) +class _FirstChunk(Generic[_RestT]): + """The chunk an attempt already read off a stream (None: the provider closed it empty) and the + iterator it was read from, which carries on after it.""" + + chunk: object + rest: _RestT + + +def _mid_stream_retry_trigger(error: MidStreamFallbackError) -> Exception: + """The provider's own error, which is what the retry policy and the retry rules classify.""" + return error.original_exception if error.original_exception is not None else error + + +async def _aread_first_chunk(stream: CustomStreamWrapper) -> _FirstChunk[AsyncIterator[object]]: + """Read the first chunk while the attempt still holds the request, so a stream that fails before + any token fails the attempt. Iterates the way ``async for`` does: one ``__aiter__`` call, then + ``__anext__`` on what it returned.""" + rest: Final = stream.__aiter__() + try: + return _FirstChunk(chunk=await rest.__anext__(), rest=rest) + except StopAsyncIteration: + return _FirstChunk(chunk=None, rest=rest) + except MidStreamFallbackError as e: + raise _mid_stream_retry_trigger(e) from e + + +def _read_first_chunk(stream: CustomStreamWrapper) -> _FirstChunk[Iterator[object]]: + rest: Final = iter(stream) + try: + return _FirstChunk(chunk=next(rest), rest=rest) + except StopIteration: + return _FirstChunk(chunk=None, rest=rest) + except MidStreamFallbackError as e: + raise _mid_stream_retry_trigger(e) from e + + +def _chunks_with_first(model_response: Iterable[object], taken: _FirstChunk[Iterator[object]]) -> Iterator[object]: + if taken.chunk is None: + return + yield taken.chunk + yield from taken.rest + + +async def _achunks_with_first( + model_response: AsyncIterable[object], taken: _FirstChunk[AsyncIterator[object]] +) -> AsyncIterator[object]: + if taken.chunk is None: + return + yield taken.chunk + async for item in taken.rest: + yield item + + +# --- shared helpers ----------------------------------------------------------------------------- + + +_CONTENT_DELTA_KEYS: Final = ( + "content", + "tool_calls", + "function_call", + "reasoning_content", + "thinking_blocks", + "reasoning_items", + "audio", + "images", + "annotations", +) + + +def _delta_has_content(delta: object) -> bool: + get: Final[object] = getattr(delta, "get", None) + if not callable(get): + return False + for key in _CONTENT_DELTA_KEYS: + value: object = get(key) + if value: + return True + return False + + +def _stream_chunks_have_generated_content(chunks: Sequence[object]) -> bool: + for chunk in chunks: + choices: object = getattr(chunk, "choices", None) + if not isinstance(choices, Sequence) or not choices: + continue + delta: object = getattr(choices[0], "delta", None) # pyright: ignore[reportUnknownArgumentType] # a chunk choice + if _delta_has_content(delta): + return True + return False + + +def _raise_original_mid_stream_error(e: MidStreamFallbackError) -> NoReturn: + """Surface the provider error the stream wrapper carried instead of the internal MidStreamFallbackError.""" + if e.original_exception is not None: + raise e.original_exception from e + raise e + + +def _raise_fallback_failure(error: Exception) -> NoReturn: + """What a stream's recovery ends on: the error the fallback's own stream raised, or the failure + a walk that served nothing was handed; never the internal MidStreamFallbackError.""" + if isinstance(error, MidStreamFallbackError) and error.original_exception is not None: + raise error.original_exception from error + raise error + + +def _stream_pre_content_error(error: Exception, model: str, llm_provider: str = "anthropic") -> MidStreamFallbackError: + """The envelope the fallback chain judges a failure by when the client has received no content yet.""" + return MidStreamFallbackError( + message=str(error), + model=model, + llm_provider=llm_provider, + original_exception=error, + is_pre_first_chunk=True, + ) + + +def _context_window_stream_fallback_error( + error: "MidStreamFallbackError | litellm_exceptions.ContextWindowExceededError", + model: object, + llm_provider: str, + has_output: bool, +) -> MidStreamFallbackError: + if isinstance(error, litellm_exceptions.ContextWindowExceededError): + if has_output: + raise error + return _stream_pre_content_error(error, model if isinstance(model, str) else "", llm_provider) + if isinstance(error.original_exception, litellm_exceptions.ContextWindowExceededError) and ( + has_output or error.generated_content or error.emitted_disqualifying_content + ): + raise error.original_exception + return error + + +def _is_context_window(error: "MidStreamFallbackError | litellm_exceptions.ContextWindowExceededError") -> bool: + return isinstance(error, litellm_exceptions.ContextWindowExceededError) or isinstance( + error.original_exception, litellm_exceptions.ContextWindowExceededError + ) + + +def _fallback_trigger(e: MidStreamFallbackError, unwrapped: tuple[type[Exception], ...]) -> Exception: + """The error the fallback walk dispatches on: the provider's own for the kinds with a list of their own.""" + return e.original_exception if isinstance(e.original_exception, unwrapped) else e + + +def _prepare_fallback_hidden_params( + fallback_response: object, +) -> _Prepared: + fallback_hidden_params: Final = get_hidden_params_dict(fallback_response) + fallback_headers: Final = fallback_hidden_params.get("additional_headers") + if not isinstance(fallback_headers, dict): + return fallback_hidden_params, {} + return fallback_hidden_params, cast("dict[str, object]", fallback_headers) # cast-ok: a dict of headers + + +def _apply_fallback_hidden_params_to_item( + fallback_item: object, + prepared_fallback_hidden_params: _Prepared, +) -> None: + if fallback_item is None or not hasattr(fallback_item, HIDDEN_PARAMS_ATTR): + return + fallback_hidden_params, fallback_headers = prepared_fallback_hidden_params + item_hidden_params: Final = get_hidden_params_dict(fallback_item) + item_headers: object = item_hidden_params.get("additional_headers") # rebind-ok: replaced when not a dict + if not isinstance(item_headers, dict): + item_headers = {} # rebind-ok: rebound as the stream advances + set_hidden_params( + fallback_item, + { + **item_hidden_params, + **fallback_hidden_params, + "additional_headers": {**cast("dict[str, object]", item_headers), **fallback_headers}, # cast-ok: checked + }, + ) + + +def _combine_fallback_usage(fallback_item: ModelResponseStream, complete_response_object_usage: Usage | None) -> None: + """Merge partial-stream usage with fallback-stream usage on the chunk. A usage given as a plain + dict comes out all-zero: ``combine_usage_objects`` reads token counts as attributes.""" + from litellm.cost_calculator import BaseTokenUsageProcessor + + usage: Final = cast("Usage | None", getattr(fallback_item, "usage", None)) # cast-ok: a chunk's usage + usage_objects: Final = [usage] if usage is not None else [] + if complete_response_object_usage is not None: + usage_objects.append(complete_response_object_usage) + fallback_item.usage = BaseTokenUsageProcessor.combine_usage_objects(usage_objects=usage_objects) # pyright: ignore[reportAttributeAccessIssue] # usage is not a declared chunk field # rebind-ok: the Python router rewrites the chunk's usage in place + + +# --- mid-stream continuation -------------------------------------------------------------------- + +CONTINUATION_FLAG: Final = "enable_mid_stream_fallback_continuation" +NO_FLAG: Final = object() +# The routing-body key naming the deployments a continuation may not land on (``continuation_deployments``). +CONTINUATION_EXCLUDED_IDS: Final = "continuation_excluded_ids" + + +def continuation_flag(value: object) -> bool: + """``_is_flag_enabled``: True, or a string ``str_to_bool`` reads as True.""" + from litellm.secret_managers.main import str_to_bool + + return value is True or (isinstance(value, str) and str_to_bool(value) is True) + + +def register_continuation_prefill_check(host: "PythonHost") -> None: + """``_register_continuation_prefill_check``: process-global on purpose, as in the Python router.""" + from litellm.router_utils.pre_call_checks.continuation_prefill_check import ContinuationPrefillDeploymentCheck + + host.callbacks.add_litellm_callback(ContinuationPrefillDeploymentCheck()) + + +def continuation_routing(core: "RustCore", request: Mapping[str, object]) -> Mapping[str, object]: + """The routing fields of a continuation request: the deployments that cannot continue it, which the + core leaves out of selection the way ``continuation_deployments`` filters the healthy list.""" + from litellm.litellm_core_utils.routing_common_utils import MID_STREAM_CONTINUATION_KWARG + from litellm.router_utils.pre_call_checks.continuation_prefill_check import ( + MID_STREAM_CONTINUATION_MARKER, + deployment_can_continue, + ) + + if request.get(MID_STREAM_CONTINUATION_KWARG) is not MID_STREAM_CONTINUATION_MARKER: + return {} + registry: Final = core.registry() + excluded: Final = [ + deployment.model_info.id + for record in registry.all() + if (deployment := registry.deployment(str(_record_id(record)))) is not None + and not deployment_can_continue(deployment.model_dump(exclude_none=True)) + ] + return {"body": {CONTINUATION_EXCLUDED_IDS: excluded}} + + +def _record_id(record: Mapping[str, object]) -> object: + model_info: Final = record.get("model_info") + return model_info.get("id") if isinstance(model_info, Mapping) else None # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # a plain record + + +def _names_deployment_that_cannot_continue(core: "RustCore", target: object) -> bool: + from litellm.router_utils.fallback_event_handlers import fallback_target_name + from litellm.router_utils.pre_call_checks.continuation_prefill_check import deployment_can_continue + + name: Final = fallback_target_name(target) + registry: Final = core.registry() + model_names: Final = {record.get("model_name") for record in registry.all()} + if name is None or name in model_names or not registry.has_deployment(name): + return False + deployment: Final = registry.deployment(name) + return deployment is not None and not deployment_can_continue(deployment.model_dump(exclude_none=True)) + + +def _mid_stream_continuation_eligible( + attempt: StreamAttempt, e: MidStreamFallbackError, cut_deployment_id: object +) -> bool: + """``_mid_stream_continuation_eligible``: whether a stream that broke after plain assistant text may + continue via prefill.""" + from litellm.integrations.custom_guardrail import CustomGuardrail + from litellm.router_utils.fallback_event_handlers import ( + continuation_fallback_targets, + fallback_lookup_groups, + fallback_target_overrides_request_params, + ) + from litellm.router_utils.pre_call_checks.continuation_prefill_check import constrains_continuation + from litellm.types.guardrails import GuardrailEventHooks + + core: Final = attempt.core + if not core.enable_mid_stream_fallback_continuation: + return False + if not e.generated_content or e.emitted_disqualifying_content: + return False + if isinstance(e.original_exception, litellm_exceptions.ContentPolicyViolationError): + return False + if isinstance(cut_deployment_id, str) and not core.registry().has_deployment(cut_deployment_id): + return False + if constrains_continuation(_params_sent_to_deployment(attempt, cut_deployment_id)): + return False + request: Final = attempt.request + requested_group: Final = request.get("model") + lookup_groups: Final = fallback_lookup_groups( + request, requested_group if isinstance(requested_group, str) else None + ) + targets: Final = continuation_fallback_targets(core.settings().fallbacks, lookup_groups) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # fallbacks as Python spells them + if any(fallback_target_overrides_request_params(target) for target in targets): + return False + if any(_names_deployment_that_cannot_continue(core, target) for target in targets): + return False + return not any( + isinstance(callback, CustomGuardrail) + and callback._event_hook_is_event_type( # pyright: ignore[reportPrivateUsage] # the only check of a guardrail's hooks + GuardrailEventHooks.post_call + ) + for callback in core._host.callback_list("callbacks") # pyright: ignore[reportPrivateUsage, reportArgumentType] # the core's own host; read as getattr(litellm, name) + ) + + +def _extend_trailing_text_block(blocks: Sequence[Mapping[str, object]], text: str) -> Sequence[Mapping[str, object]]: + """Continue the last text block in place so the prefill reads as the text the caller already received.""" + last: Final = blocks[-1] if blocks else None + if last is not None and last.get("type") == "text" and isinstance(last_text := last.get("text"), str): + return [*blocks[:-1], {**last, "text": f"{last_text}{text}"}] + return [*blocks, {"type": "text", "text": text}] + + +def _build_completion_continuation_input( + messages: Sequence[Mapping[str, object]], generated_content: str +) -> Sequence[Mapping[str, object]] | None: + """The partial output as an assistant prefill, or a trailing ``prefix: True`` assistant turn extended in + place. None when the request ends in a plain assistant turn, in a prefill turn whose content this cannot + extend, or when the cut came mid-echo of the prefill.""" + from pydantic import TypeAdapter, ValidationError + + from litellm.router_utils.pre_call_checks.continuation_prefill_check import continued_text + + last: Final = messages[-1] if messages else None + if last is None or last.get("role") != "assistant": + return [*messages, {"role": "assistant", "content": generated_content, "prefix": True}] + if last.get("prefix") is not True: + return None + new_text: Final = continued_text(last, generated_content) + if new_text is None: + return None + content: Final = last.get("content") + if content is None or isinstance(content, str): + return [*messages[:-1], {**last, "content": f"{content or ''}{new_text}", "prefix": True}] + try: + blocks: Final = TypeAdapter(list[dict[str, object]]).validate_python(content) + except ValidationError: + return None + return [*messages[:-1], {**last, "content": _extend_trailing_text_block(blocks, new_text), "prefix": True}] + + +def _price_cut_partial(cut_stream: CustomStreamWrapper, partial_response: object) -> "ContinuedPartial | None": + """Price the cut stream's partial, plus any partial it inherited, before a fallback can reuse its logging.""" + from litellm.cost_calculator import BaseTokenUsageProcessor + from litellm.router_utils.pre_call_checks.continuation_prefill_check import ContinuedPartial + + cut_logging: Final = cut_stream.logging_obj + partial_usage: Final = getattr(partial_response, "usage", None) + if partial_response is None or not isinstance(partial_usage, Usage): + return None + details: Final = cut_logging.model_call_details + inherited_usage: Final = details.get("continued_partial_usage") + inherited_cost: Final = details.get("continued_partial_cost") + inherited_id: Final = details.get("continued_response_id") + priced_partial: Final = partial_response.model_copy( # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType, reportUnknownVariableType] # a ModelResponse + update={"model": cut_stream.model} if cut_stream.model else {} # pyright: ignore[reportUnknownMemberType] # untyped attribute + ) + priced_partial._hidden_params = without( # pyright: ignore[reportUnknownMemberType] # no public accessor + get_hidden_params_dict(partial_response), "response_cost" + ) + return ContinuedPartial( + usage=BaseTokenUsageProcessor.combine_usage_objects( + usage_objects=[partial_usage, inherited_usage] if isinstance(inherited_usage, Usage) else [partial_usage] + ), + response_cost=(cut_logging.response_cost_calculator(result=priced_partial) or 0.0) # pyright: ignore[reportUnknownArgumentType] # a ModelResponse + + (inherited_cost if isinstance(inherited_cost, float) else 0.0), + response_id=inherited_id if isinstance(inherited_id, str) else str(getattr(partial_response, "id", "")), + ) + + +def _carry_partial_spend_to_fallback(fallback_response: object, cut_partial: "ContinuedPartial | None") -> None: + """Bill what the cut legs consumed on the continuation's success log.""" + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging + + fallback_logging: Final = getattr(fallback_response, "logging_obj", None) + if cut_partial is None or not isinstance(fallback_logging, LiteLLMLogging): + return + fallback_logging.record_continued_partial( + usage=cut_partial.usage, # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # a Usage + response_cost=cut_partial.response_cost, + response_id=cut_partial.response_id, + ) + + +@dataclasses.dataclass(frozen=True, slots=True) +class _Continuation: + """What a chat continuation sends the fallback and splices back.""" + + request: Mapping[str, object] + output: "ContinuationOutput" + partial: "ContinuedPartial | None" + usage: Usage | None + + +async def _chat_continuation( + attempt: StreamAttempt, e: MidStreamFallbackError, model_response: CustomStreamWrapper +) -> _Continuation: + """The request a fallback continues a chat stream from, once it broke after content. Raises the + provider's error when the continuation is declined or the output ceiling is spent.""" + from litellm.constants import MID_STREAM_FAILURE_LOG_WAIT_SECONDS + from litellm.litellm_core_utils.routing_common_utils import MID_STREAM_CONTINUATION_KWARG + from litellm.main import ( + stream_chunk_builder, # pyright: ignore[reportUnknownVariableType] # untyped chunk list argument + ) + from litellm.router_utils.pre_call_checks.continuation_prefill_check import ( + MID_STREAM_CONTINUATION_MARKER, + ContinuationOutput, + continuation_output_ceilings, + ) + + request: Final = attempt.request + raw_messages: Final = request.get("messages") + messages: Final = cast("list[Mapping[str, object]]", raw_messages or []) # cast-ok: chat messages + complete: Final = stream_chunk_builder(chunks=model_response.chunks, messages=messages) # pyright: ignore[reportUnknownArgumentType] # provider chunk list + usage: Final = cast("Usage | None", getattr(complete, "usage", None)) # cast-ok: a built response's usage + continuation_messages: Final = _build_completion_continuation_input(messages, e.generated_content) + output: Final = ( + ContinuationOutput( + e.generated_content, + continuation_messages[-1], + str(request.get("model") or ""), + complete, + checks_post_call_rules=request.get(MID_STREAM_CONTINUATION_KWARG) is not MID_STREAM_CONTINUATION_MARKER, + ) + if continuation_messages is not None + else None + ) + partial: Final = _price_cut_partial(model_response, complete) if output is not None else None + if partial is not None: + model_response.logging_obj.mark_stash_billed_by_continuation() + emitted_tokens: Final = int(getattr(usage, "completion_tokens", 0) or 0) + reduced: Final = continuation_output_ceilings(request, emitted_tokens) + if reduced is None or continuation_messages is None or output is None: + _raise_original_mid_stream_error(e) + await model_response.wait_for_failure_logging(timeout=MID_STREAM_FAILURE_LOG_WAIT_SECONDS) + return _Continuation( + request={ + **request, + **reduced, + "messages": continuation_messages, + MID_STREAM_CONTINUATION_KWARG: MID_STREAM_CONTINUATION_MARKER, + }, + output=output, + partial=partial, + usage=usage, + ) + + +# --- chat completions --------------------------------------------------------------------------- + + +class FallbackAwareStreamWrapper(CustomStreamWrapper): + """A chat stream built around the attempt the core picked first, which repoints itself when a + fallback takes over.""" + + fallback_headers_adopted: bool = False + + def adopt_fallback_response_headers( + self, + fallback_response: object, + prepared_fallback_hidden_params: _Prepared, + ) -> None: + """Repoint this wrapper at the deployment that served the stream. Replaces rather than merges, + so the failed attempt's request id, counters, ``model_id`` and ``api_base`` cannot leak.""" + self._response_headers = getattr(fallback_response, "_response_headers", None) + fallback_hidden_params, fallback_headers = prepared_fallback_hidden_params + if fallback_hidden_params: + self._hidden_params = {**fallback_hidden_params, "additional_headers": dict(fallback_headers)} + self._base_hidden_params = {**self._hidden_params, "response_cost": None} + self.fallback_headers_adopted = True + + +def _adopt_fallback_response_headers( + wrapper_ref: "weakref.ref[FallbackAwareStreamWrapper]", fallback_response: object +) -> _Prepared: + prepared: Final = _prepare_fallback_hidden_params(fallback_response) + adopting_wrapper: Final = wrapper_ref() + if adopting_wrapper is not None: + adopting_wrapper.adopt_fallback_response_headers(fallback_response, prepared) + return prepared + + +def _chat_wrapper_init( + wrapper: FallbackAwareStreamWrapper, stream: object, model_response: CustomStreamWrapper +) -> None: + CustomStreamWrapper.__init__( # pyright: ignore[reportUnknownMemberType] # the base constructor is untyped + wrapper, + completion_stream=stream, + model=model_response.model, # pyright: ignore[reportUnknownMemberType] # an untyped attribute + custom_llm_provider=model_response.custom_llm_provider, + logging_obj=model_response.logging_obj, + _response_headers=getattr(model_response, "_response_headers", None), + ) + inner_chunks: Final[object] = getattr(model_response, "chunks", None) + if isinstance(inner_chunks, list): + chunk_list: Final = cast("list[ModelResponseStream]", inner_chunks) # cast-ok: the inner stream's chunks + wrapper.chunks = chunk_list # rebind-ok: initializes the wrapper being built + hidden_params: Final = get_hidden_params(model_response) + if hidden_params is not None: + wrapper._hidden_params = dict(hidden_params) # pyright: ignore[reportPrivateUsage] # the wrapper's own field # rebind-ok: initializes the wrapper being built + + +class _AsyncChatStream(FallbackAwareStreamWrapper): + def __init__(self, generator: AsyncGenerator[object, None], model_response: CustomStreamWrapper) -> None: # pyright: ignore[reportMissingSuperCall] # _chat_wrapper_init calls it + _chat_wrapper_init(self, generator, model_response) + self._async_generator: Final = generator + + def __aiter__(self) -> "_AsyncChatStream": # pyright: ignore[reportIncompatibleMethodOverride] # iterates the generator + return self + + async def __anext__(self) -> object: # pyright: ignore[reportIncompatibleMethodOverride] # yields what the stream yields + return await self._async_generator.__anext__() + + +class _SyncChatStream(FallbackAwareStreamWrapper): + def __init__(self, generator: Generator[object, None, None], model_response: CustomStreamWrapper) -> None: # pyright: ignore[reportMissingSuperCall] # _chat_wrapper_init calls it + _chat_wrapper_init(self, generator, model_response) + self.chunks = [] # the sync twin keeps no inner chunk list + hidden_params: Final = get_hidden_params(model_response) + if hidden_params is not None: + self._hidden_params = dict(hidden_params) + self._sync_generator: Final = generator + + def __iter__(self) -> "_SyncChatStream": # pyright: ignore[reportIncompatibleMethodOverride] # iterates the generator + return self + + def __next__(self) -> object: # pyright: ignore[reportIncompatibleMethodOverride] # yields what the stream yields + return next(self._sync_generator) + + +def _chat_has_output(model_response: CustomStreamWrapper) -> bool: + return bool(getattr(model_response, "response_uptil_now", "")) or _stream_chunks_have_generated_content( + model_response.chunks + ) + + +def wrap_chat_stream( # noqa: C901 # one function per Python wrapper it ports + attempt: StreamAttempt, + model_response: CustomStreamWrapper, + first_chunk: _FirstChunk[AsyncIterator[object]], + held_slot: contextlib.ExitStack | None = None, +) -> FallbackAwareStreamWrapper: + """``_acompletion_streaming_iterator``: a mid-stream error before content falls back through the core; + after content, the provider's error is raised. ``held_slot`` (the deployment's max_parallel_requests + slot) is released when the stream is exhausted, closed, or falls back.""" + slot: Final = held_slot if held_slot is not None else contextlib.ExitStack() + attempt.reports_outcome = True # rebind-ok: the wrapper reports this attempt's outcome + + async def close_model_response() -> None: + if not hasattr(model_response, "aclose"): + return + try: + await model_response.aclose() + except BaseException as e: # noqa: BLE001 # closing is best-effort + verbose_router_logger.debug("stream_with_fallbacks: error closing model_response: %s", e) + + async def stream_with_fallbacks() -> AsyncGenerator[object, None]: + fallback_response: object = None # rebind-ok: tracked for cleanup + try: + async for item in _areported(attempt, _achunks_with_first(model_response, first_chunk), _chat_total_tokens): + yield item + except (MidStreamFallbackError, litellm_exceptions.ContextWindowExceededError) as stream_error: + e: Final = ( + _context_window_stream_fallback_error( + stream_error, + getattr(model_response, "model", ""), + model_response.custom_llm_provider or "", + _chat_has_output(model_response), + ) + if _is_context_window(stream_error) + else cast("MidStreamFallbackError", stream_error) # cast-ok: not a context window error + ) + with anyio.CancelScope(shield=True): + await close_model_response() + slot.close() + committed: Final = bool( + not e.is_pre_first_chunk + and (e.generated_content or _stream_chunks_have_generated_content(model_response.chunks)) + ) + cut_deployment_id: Final = (get_hidden_params(model_response) or {}).get("model_id") + if committed and not _mid_stream_continuation_eligible(attempt, e, cut_deployment_id): + _raise_original_mid_stream_error(e) + trigger: Final = _fallback_trigger(e, (litellm_exceptions.ContextWindowExceededError,)) + try: + continuation: Final = await _chat_continuation(attempt, e, model_response) if committed else None + fallback_response = await attempt.fallback( # rebind-ok: rebound as the stream advances + trigger, continuation.request if continuation is not None else None + ) + if hasattr(fallback_response, "__aiter__"): + if continuation is not None: + _carry_partial_spend_to_fallback(fallback_response, continuation.partial) + prepared = _adopt_fallback_response_headers(wrapper_ref, fallback_response) # rebind-ok: re-adopted + settled = False # rebind-ok: rebound as the stream advances + fallback_stream: Final = cast("AsyncIterable[object]", fallback_response) # cast-ok: checked + fallback_items: Final = ( + continuation.output.splice(fallback_stream) if continuation is not None else fallback_stream + ) + async for fallback_item in fallback_items: + if not settled: + settled = True + # a fallback that failed over again only repoints itself once it yields + prepared = _adopt_fallback_response_headers(wrapper_ref, fallback_response) + _apply_fallback_hidden_params_to_item(fallback_item, prepared) + if ( + fallback_item + and isinstance(fallback_item, ModelResponseStream) + and hasattr(fallback_item, "usage") + ): + _combine_fallback_usage( + fallback_item, + continuation.usage if continuation is not None else None, # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # a Usage + ) + yield fallback_item + else: + # A fallback that answers without a stream yields None (an oddity kept as is). + yield None + except Exception as fallback_error: # noqa: BLE001 # as the Python wrapper: logged, then the stream's error raises + verbose_router_logger.error("Fallback also failed: %s", fallback_error) + _raise_fallback_failure(fallback_error) + finally: + with anyio.CancelScope(shield=True): + await close_model_response() + slot.close() + if fallback_response is not None and hasattr(fallback_response, "aclose"): + try: + await fallback_response.aclose() # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType] # checked above + except BaseException as close_error: # noqa: BLE001 # closing is best-effort + verbose_router_logger.debug( + "stream_with_fallbacks: error closing fallback_response: %s", close_error + ) + + wrapped_response: Final = _AsyncChatStream(stream_with_fallbacks(), model_response) + # weak, so the generator closing over it does not keep the wrapper alive + wrapper_ref: Final[weakref.ref[FallbackAwareStreamWrapper]] = weakref.ref(wrapped_response) + return wrapped_response + + +def wrap_chat_stream_sync( + attempt: StreamAttempt, model_response: CustomStreamWrapper, first_chunk: _FirstChunk[Iterator[object]] +) -> FallbackAwareStreamWrapper: + """``_completion_streaming_iterator``: the sync twin, which never continues after content.""" + attempt.reports_outcome = True # rebind-ok: the wrapper reports this attempt's outcome + + def stream_with_fallbacks() -> Generator[object, None, None]: + fallback_response: object = None # rebind-ok: tracked for cleanup + try: + yield from _reported(attempt, _chunks_with_first(model_response, first_chunk)) + except (MidStreamFallbackError, litellm_exceptions.ContextWindowExceededError) as stream_error: + e: Final = ( + _context_window_stream_fallback_error( + stream_error, + getattr(model_response, "model", ""), + model_response.custom_llm_provider or "", + _chat_has_output(model_response), + ) + if _is_context_window(stream_error) + else cast("MidStreamFallbackError", stream_error) # cast-ok: not a context window error + ) + if attempt.request.get("disable_fallbacks") is True or ( + not e.is_pre_first_chunk + and (e.generated_content or _stream_chunks_have_generated_content(model_response.chunks)) + ): + _raise_original_mid_stream_error(e) + trigger: Final = _fallback_trigger(e, (litellm_exceptions.ContextWindowExceededError,)) + try: + fallback_response = attempt.fallback_sync(trigger) # rebind-ok: rebound as the stream advances + if hasattr(fallback_response, "__iter__"): + prepared = _adopt_fallback_response_headers(wrapper_ref, fallback_response) # rebind-ok: re-adopted + settled = False # rebind-ok: rebound as the stream advances + for fallback_item in cast("Iterable[object]", fallback_response): # cast-ok: checked + if not settled: + settled = True + prepared = _adopt_fallback_response_headers(wrapper_ref, fallback_response) + _apply_fallback_hidden_params_to_item(fallback_item, prepared) + if ( + fallback_item + and isinstance(fallback_item, ModelResponseStream) + and hasattr(fallback_item, "usage") + ): + _combine_fallback_usage(fallback_item, None) + yield fallback_item + else: + yield None + except Exception as fallback_error: # noqa: BLE001 # as the Python wrapper: logged, then the stream's error raises + verbose_router_logger.error("Fallback also failed: %s", fallback_error) + _raise_fallback_failure(fallback_error) + finally: + for closable in (model_response, fallback_response): + close = getattr(closable, "close", None) + if callable(close): + try: + close() + except BaseException as close_error: # noqa: BLE001 # closing is best-effort + verbose_router_logger.debug("stream_with_fallbacks: error closing: %s", close_error) + + wrapped_response: Final = _SyncChatStream(stream_with_fallbacks(), model_response) + wrapper_ref: Final[weakref.ref[FallbackAwareStreamWrapper]] = weakref.ref(wrapped_response) + return wrapped_response + + +# --- /v1/messages ------------------------------------------------------------------------------- + + +class FallbackAwareAnthropicMessagesStream: + """A ``/v1/messages`` byte stream that carries the ``_hidden_params`` the proxy reads its response + headers off, through retries and fallbacks of the stream it wraps.""" + + def __init__( + self, async_generator: AsyncGenerator[bytes, None], source_iterator: object, attempt: StreamAttempt + ) -> None: + self._async_generator: Final = async_generator + self._source_iterator: object = source_iterator + self.attempt: Final = attempt + self.fallback_headers_adopted = False + self._hidden_params: dict[str, object] = dict( # mutable-ok: the proxy writes headers into it + getattr(source_iterator, "_hidden_params", None) or {} + ) + self._followed_source_params: object = None + + @property + def has_buffered_provider_output(self) -> bool: + return getattr(self._source_iterator, "has_buffered_provider_output", False) is True + + @property + def chunks(self) -> object: + return getattr(self._source_iterator, "chunks", None) + + @property + def messages(self) -> object: + return getattr(self._source_iterator, "messages", None) + + @property + def model(self) -> object: + return getattr(self._source_iterator, "model", None) + + def adopt_fallback_source(self, fallback_response: object) -> None: + self._source_iterator = fallback_response + self.fallback_headers_adopted = True + + def partial_response_on_disconnect(self) -> "ResponseIncompleteEvent | None": + from litellm.responses.streaming_iterator import partial_responses_incomplete_event_on_disconnect + + return partial_responses_incomplete_event_on_disconnect(self._source_iterator) + + def follow_source_attribution(self) -> None: + """Mirror the source's current attribution onto this wrapper whenever the source has adopted a + new one: a retry's or a fallback's stream carries a wrapper of its own.""" + source: Final = self._source_iterator + if not getattr(source, "fallback_headers_adopted", False): + return + source_params: Final = getattr(source, "_hidden_params", None) + if source_params is None or source_params is self._followed_source_params: + return + self._followed_source_params = source_params + hidden_params, headers = _prepare_fallback_hidden_params(source) + self.merge_fallback_hidden_params(hidden_params, headers) + + def __aiter__(self) -> "FallbackAwareAnthropicMessagesStream": + return self + + async def __anext__(self) -> bytes: + return await self._async_generator.__anext__() + + async def aclose(self) -> None: + await self._async_generator.aclose() + + def merge_fallback_hidden_params( + self, fallback_hidden_params: Mapping[str, object], fallback_headers: Mapping[str, object] + ) -> None: + existing_headers: Final = cast( # cast-ok: additional_headers is a dict when present + "dict[str, object]", self._hidden_params.get("additional_headers") or {} + ) + self._hidden_params = { + **self._hidden_params, + **fallback_hidden_params, + "additional_headers": dict(replace_complexity_router_headers(existing_headers, fallback_headers)), + } + + +def _anthropic_stream_forwards_ping_live(chunk: object, has_generated_content: bool) -> bool: + from litellm.llms.anthropic.messages.native.streaming_iterator import is_anthropic_ping_chunk + + return not has_generated_content and is_anthropic_ping_chunk(chunk) + + +def _is_retriable_anthropic_status(status_code: int) -> bool: + return status_code == 429 or status_code >= 500 + + +def _anthropic_stream_error_is_gateway_verdict(chunk: object) -> bool: + from litellm.llms.anthropic.messages.native.agentic_streaming_iterator import is_server_fulfilled_tool_leak_error + + return is_server_fulfilled_tool_leak_error(chunk) + + +def _anthropic_stream_should_decline_fallback(has_generated_content: bool, error: MidStreamFallbackError) -> bool: + return has_generated_content or not error.is_pre_first_chunk + + +def _stream_raised_error_status(error: Exception) -> int | None: + raw_status: Final = getattr(error, "status_code", None) + if isinstance(raw_status, int): + return raw_status + if isinstance(raw_status, str) and raw_status.isdigit(): + return int(raw_status) + response_status: Final = getattr(getattr(error, "response", None), "status_code", None) + return response_status if isinstance(response_status, int) else None + + +def _stream_fallback_error_for_raised( + attempt: StreamAttempt, error: Exception, model: str, has_generated_content: bool, llm_provider: str = "anthropic" +) -> MidStreamFallbackError | None: + """The pre-stream retry rule (408, 409, 429, 5xx); None means the raise propagates unchanged.""" + if has_generated_content: + return None + status_code: Final = _stream_raised_error_status(error) + if status_code is None or attempt.should_retry_status(status_code): + return _stream_pre_content_error(error, model, llm_provider) + return None + + +def _stream_commits_now(chunk: object, has_generated_content: bool, buffered_chunk_count: int) -> bool: + from litellm.llms.anthropic.messages.native.streaming_iterator import is_anthropic_content_delta_chunk + + if has_generated_content: + return False + return is_anthropic_content_delta_chunk(chunk) or buffered_chunk_count >= MAX_BUFFERED_PRE_CONTENT_ANTHROPIC_CHUNKS + + +def _bridged_stream_failure(source: object) -> Exception | None: + """The provider's error behind an ``event: error`` frame the completion or Responses bridge wrote + in its place, which litellm's stream logging logged. A native frame has none: litellm logs what the + frame itself maps to (``anthropic_error_frame_exception``), once a takeover closes the stream.""" + failure: Final[object] = getattr(source, "stream_failure", None) + return failure if isinstance(failure, Exception) else None + + +def _anthropic_recoverable_frame_error( + attempt: StreamAttempt, + error_event: tuple[str, str, int] | None, + chunk: object, + has_generated_content: bool, + model_group: str, +) -> Exception | None: + """The exception a provider ``event: error`` frame before content recovers through when a retry of + its class or a fallback can still take over; None forwards the frame as the provider sent it.""" + from litellm.llms.anthropic.common_utils import anthropic_error_frame_exception + + if has_generated_content or error_event is None: + return None + error_type, message, status_code = error_event + if not _is_retriable_anthropic_status(status_code) or _anthropic_stream_error_is_gateway_verdict(chunk): + return None + frame_error: Final = anthropic_error_frame_exception(error_type, message, status_code, model_group) + budget, _ = attempt.retry_budget(frame_error) + if budget > attempt.attempted_retries: + return frame_error + if attempt.can_fall_back(): + return frame_error + return None + + +def wrap_anthropic_stream( + attempt: StreamAttempt, response: AsyncIterator[bytes] +) -> FallbackAwareAnthropicMessagesStream: + """``_aanthropic_messages_streaming_iterator``: lifecycle frames are held while a retry or a fallback + can still take over; an error frame, a raised error or a safeguard refusal before content is + retried in the group, then falls back, as the core decides.""" + from litellm.llms.anthropic.messages.native.fake_stream_iterator import FakeAnthropicMessagesStreamIterator + from litellm.llms.anthropic.messages.native.streaming_iterator import ( + aclose_if_supported, + aclose_superseded_attempt, + parse_anthropic_error_event, + parse_anthropic_refusal_stop_details, + ) + from litellm.llms.anthropic.messages.native.utils import safeguard_refusal_error + + source_iterator: Final = response + replays_a_finished_agentic_turn: Final = isinstance(source_iterator, FakeAnthropicMessagesStreamIterator) + model: Final = attempt.group + usage: Final = _AnthropicStreamUsage() + attempt.reports_outcome = True # rebind-ok: the wrapper reports this attempt's outcome + + async def close_source() -> None: + with anyio.CancelScope(shield=True), contextlib.suppress(BaseException): + await aclose_if_supported(source_iterator) + + async def close_superseded() -> None: + with anyio.CancelScope(shield=True), contextlib.suppress(BaseException): + await aclose_superseded_attempt(source_iterator) + + async def stream_with_fallbacks() -> AsyncGenerator[bytes, None]: + policy: Final = attempt.policy() + has_generated_content = not ( # rebind-ok: set once content is seen, the buffer cap is hit, or nothing can take over + policy.get("can_retry") is True or policy.get("can_fall_back") is True + ) + buffered: tuple[bytes, ...] = () # rebind-ok: flushed once committed or on decline + try: + async for chunk in _areported(attempt, source_iterator, usage.total_tokens, usage.observe): + if _anthropic_stream_forwards_ping_live(chunk, has_generated_content): + yield chunk + continue + if _stream_commits_now(chunk, has_generated_content, len(buffered)): + has_generated_content = True + # A transport can split one SSE data line across byte chunks, so pre-content detection + # parses the held frames plus the current chunk. + parse_window = ( + b"".join(c for c in (*buffered, chunk) if isinstance(c, (bytes, bytearray))) # pyright: ignore[reportUnnecessaryIsInstance] # bridge-path chunks are not always bytes + if not has_generated_content and isinstance(chunk, (bytes, bytearray)) # pyright: ignore[reportUnnecessaryIsInstance] # see above + else chunk + ) + error_event = parse_anthropic_error_event(parse_window) + bridged_failure = _bridged_stream_failure(source_iterator) if error_event is not None else None + if bridged_failure is not None: + attempt.report_failure(bridged_failure) + recoverable_frame_error = _anthropic_recoverable_frame_error( + attempt, error_event, chunk, has_generated_content, model + ) + refusal_stop_details = ( + parse_anthropic_refusal_stop_details(parse_window) + if not has_generated_content and error_event is None + else None + ) + if ( + refusal_stop_details is not None + and not replays_a_finished_agentic_turn + and attempt.refusal_fallback_available() + ): + refusal_error = safeguard_refusal_error(model=model, stop_details=refusal_stop_details) + raise MidStreamFallbackError( + message=refusal_error.message, + model=model, + llm_provider="anthropic", + original_exception=refusal_error, + is_pre_first_chunk=True, + ) + if not has_generated_content and error_event is None: + buffered = (*buffered, chunk) + continue + if recoverable_frame_error is not None and error_event is not None: + raise MidStreamFallbackError( + message=error_event[1], + model=model, + llm_provider="anthropic", + original_exception=recoverable_frame_error, + is_pre_first_chunk=True, + ) + for buffered_chunk in buffered: + yield buffered_chunk + buffered = () + yield chunk + for buffered_chunk in buffered: + yield buffered_chunk + except Exception as stream_error: # noqa: BLE001 # any raised provider error must reach the fallback gate + async for item in _anthropic_recover_stream_error( + attempt, stream_error, has_generated_content, buffered, model, wrapper, close_superseded + ): + yield item + finally: + await close_source() + + wrapper: Final = FallbackAwareAnthropicMessagesStream(stream_with_fallbacks(), source_iterator, attempt) + return wrapper + + +async def _anthropic_recover_stream_error( + attempt: StreamAttempt, + stream_error: Exception, + has_generated_content: bool, + buffered: tuple[bytes, ...], + model: str, + wrapper: FallbackAwareAnthropicMessagesStream, + close_superseded: Callable[[], Awaitable[None]], +) -> AsyncGenerator[bytes, None]: + """Turns a source-iterator failure into a retry, a fallback, or the error reaching the caller.""" + if isinstance(stream_error, MidStreamFallbackError) and _anthropic_stream_should_decline_fallback( + has_generated_content, stream_error + ): + for buffered_chunk in buffered: + yield buffered_chunk + if stream_error.original_exception is not None: + raise stream_error.original_exception from stream_error + raise stream_error + fallback_error: Final = ( + stream_error + if isinstance(stream_error, MidStreamFallbackError) + else _stream_fallback_error_for_raised(attempt, stream_error, model, has_generated_content) + ) + if fallback_error is None: + raise stream_error + # A native error frame or a refusal the wrapper raised fails the attempt too (a raised error or a + # bridged frame already did). + attempt.report_failure(fallback_error) + await close_superseded() + await attempt.failure_recorded() + retried: Final = await attempt.retry(_mid_stream_retry_trigger(fallback_error)) + if isinstance(retried, BaseException): + last_error: Final = ( + fallback_error + if retried is _mid_stream_retry_trigger(fallback_error) + else _stream_pre_content_error( + retried if isinstance(retried, Exception) else fallback_error, model, fallback_error.llm_provider + ) + ) + async for item in _anthropic_fallback_attempt(attempt, last_error, wrapper): + yield item + return + response, attempted, budget = retried + inner: Final = response + if isinstance(inner, FallbackAwareAnthropicMessagesStream): + inner.attempt.attempted_retries = attempted + inner.attempt.committed_budget = budget + async for item in _anthropic_yield_recovered(inner, wrapper, (attempted, budget)): + yield item + + +async def _anthropic_yield_recovered( + recovered: object, + wrapper: FallbackAwareAnthropicMessagesStream, + retry_counters: tuple[int, int] | None = None, +) -> AsyncGenerator[bytes, None]: + """Hands a retry's or a fallback's response to the client through the wrapper, closing it after.""" + from litellm.llms.anthropic.messages.native.streaming_iterator import ( + aclose_if_supported, + anthropic_messages_response_as_sse_events, + ) + + hidden_params, headers = _prepare_fallback_hidden_params(recovered) + wrapper.merge_fallback_hidden_params(hidden_params, headers) + wrapper.adopt_fallback_source(recovered) + if retry_counters is not None: + add_retry_headers_to_response( + response=wrapper, attempted_retries=retry_counters[0], max_retries=retry_counters[1] + ) + try: + if hasattr(recovered, "__aiter__"): + async for item in cast("AsyncIterator[bytes]", recovered): # cast-ok: __aiter__ checked above + wrapper.follow_source_attribution() + yield item + return + # A complete response for a streaming request is replayed as the SSE lifecycle a stream sends. + for event in anthropic_messages_response_as_sse_events(recovered): # pyright: ignore[reportArgumentType] # the non-streaming shape by elimination + yield event + finally: + with anyio.CancelScope(shield=True), contextlib.suppress(BaseException): + await aclose_if_supported(recovered) + + +async def _anthropic_fallback_attempt( + attempt: StreamAttempt, e: MidStreamFallbackError, wrapper: FallbackAwareAnthropicMessagesStream +) -> AsyncGenerator[bytes, None]: + """Re-enters the fallback walk for a ``/v1/messages`` stream error and yields what the fallback produces.""" + trigger: Final = _fallback_trigger( + e, (litellm_exceptions.ContentPolicyViolationError, litellm_exceptions.ContextWindowExceededError) + ) + try: + fallback_response: Final = await attempt.fallback(trigger) + async for fallback_item in _anthropic_yield_recovered(fallback_response, wrapper): + yield fallback_item + except Exception as fallback_error: # noqa: BLE001 # as the Python wrapper: logged, then the stream's error raises + verbose_router_logger.error("Anthropic messages streaming fallback also failed: %s", fallback_error) + _raise_fallback_failure(fallback_error) + + +# --- Responses API ------------------------------------------------------------------------------ + + +def _responses_stream_holds_event(item: object, held_event_count: int) -> bool: + from litellm.responses.streaming_iterator import PRE_OUTPUT_LIFECYCLE_EVENT_TYPES + + if held_event_count >= MAX_HELD_PRE_OUTPUT_RESPONSES_EVENTS: + return False + return getattr(item, "type", None) in PRE_OUTPUT_LIFECYCLE_EVENT_TYPES + + +def _responses_event_announces_background_run(item: object) -> bool: + return getattr(getattr(item, "response", None), "background", None) is True + + +def _mid_stream_error_before_output(error: MidStreamFallbackError) -> bool: + return not error.generated_content or error.is_pre_first_chunk + + +def _extract_partial_responses_usage(source_iterator: "BaseResponsesAPIStreamingIterator") -> "ResponseAPIUsage | None": + """Partial token usage of a Responses stream that failed, normalized to ``ResponseAPIUsage``.""" + from litellm.responses.litellm_completion_transformation.streaming_iterator import ( + LiteLLMCompletionStreamingIterator, + ) + from litellm.types.llms.openai import ( + ResponseAPIUsage, + ResponseCompletedEvent, + ResponseFailedEvent, + ResponseIncompleteEvent, + ) + + if isinstance(source_iterator, LiteLLMCompletionStreamingIterator): + chunks: Final = source_iterator.collected_chat_completion_chunks + if chunks: + try: + from litellm.main import ( + stream_chunk_builder, # pyright: ignore[reportUnknownVariableType] # untyped chunk list + ) + + built: Final = stream_chunk_builder(chunks=chunks) + chat: Final[object | None] = getattr(built, "usage", None) if built is not None else None + if chat is not None: + prompt: Final = int(getattr(chat, "prompt_tokens", 0) or 0) + completion: Final = int(getattr(chat, "completion_tokens", 0) or 0) + total: Final = int(getattr(chat, "total_tokens", prompt + completion) or (prompt + completion)) + return ResponseAPIUsage(input_tokens=prompt, output_tokens=completion, total_tokens=total) + except Exception as error: # noqa: BLE001 # the builder is best-effort + verbose_router_logger.debug("partial usage of a failed Responses stream: %s", error) + completed: Final = source_iterator.completed_response + if isinstance(completed, (ResponseCompletedEvent, ResponseFailedEvent, ResponseIncompleteEvent)): + return completed.response.usage + return None + + +def _combine_responses_fallback_usage(fallback_item: object, partial_usage: "ResponseAPIUsage") -> None: + from litellm.types.llms.openai import ( + ResponseAPIUsage, + ResponseCompletedEvent, + ResponseFailedEvent, + ResponseIncompleteEvent, + ) + + if not isinstance(fallback_item, (ResponseCompletedEvent, ResponseFailedEvent, ResponseIncompleteEvent)): + return + response: Final = fallback_item.response + if response.usage is None: + return + fb: Final = response.usage + response.usage = ResponseAPIUsage( + input_tokens=(partial_usage.input_tokens or 0) + (fb.input_tokens or 0), + output_tokens=(partial_usage.output_tokens or 0) + (fb.output_tokens or 0), + total_tokens=(partial_usage.total_tokens or 0) + (fb.total_tokens or 0), + ) + + +def _params_sent_to_deployment(attempt: StreamAttempt, deployment_id: object) -> Mapping[str, object]: + """The request as the deployment received it, merged in the order the attempt applies.""" + return attempt.core.params_sent_to_deployment(attempt.request, deployment_id) + + +def wrap_responses_stream( # noqa: C901 # one function per Python wrapper it ports + attempt: StreamAttempt, response: "BaseResponsesAPIStreamingIterator" +) -> "BaseResponsesAPIStreamingIterator": + """``_aresponses_streaming_iterator``: pre-output lifecycle events are held while a fallback can take + over; a mid-stream error falls back through the core, continuing after text.""" + import time + from datetime import datetime, timezone + + from litellm.responses.streaming_iterator import BaseResponsesAPIStreamingIterator, get_openai_response_types + + source_iterator: Final = response + attempt.reports_outcome = True # rebind-ok: the wrapper reports this attempt's outcome + openai_types: Final = get_openai_response_types() + terminal_event_types: Final = ( + openai_types.ResponsesAPIStreamEvents.RESPONSE_COMPLETED, + openai_types.ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE, + openai_types.ResponsesAPIStreamEvents.RESPONSE_FAILED, + ) + + class FallbackResponsesStreamWrapper(BaseResponsesAPIStreamingIterator): + """Subclasses the base iterator only for isinstance checks; iteration is the generator's.""" + + fallback_headers_adopted: bool = False + + def __init__(self, async_generator: AsyncGenerator[object, None]) -> None: # pyright: ignore[reportMissingSuperCall] # no httpx response of its own + self._async_generator: Final = async_generator + self._billing_source: object = source_iterator + self._last_sequence_number = -1 + self.response = getattr(source_iterator, "response", None) # pyright: ignore[reportAttributeAccessIssue] # copied from the source + self.model = getattr(source_iterator, "model", None) # pyright: ignore[reportAttributeAccessIssue] # see above + self.logging_obj = getattr( + source_iterator, "logging_obj", getattr(source_iterator, "litellm_logging_obj", None) + ) # pyright: ignore[reportAttributeAccessIssue] # see above + self.finished = False + self.responses_api_provider_config = getattr(source_iterator, "responses_api_provider_config", None) # pyright: ignore[reportAttributeAccessIssue] # see above + self.completed_response = None + self.start_time = getattr(source_iterator, "start_time", None) or datetime.now(timezone.utc).replace( + tzinfo=None + ) + self._failure_handled = False + self._yielded_first_chunk = False + self._generated_content = "" + self._completed_response_cached = False + self._completed_response_logged = False + self._completed_response_cache_hit = None + self._persist_completed_response_before_logging = True + self._stream_created_time = time.time() + self.litellm_metadata = getattr(source_iterator, "litellm_metadata", None) # pyright: ignore[reportAttributeAccessIssue] # see above + self.custom_llm_provider = getattr(source_iterator, "custom_llm_provider", None) # pyright: ignore[reportAttributeAccessIssue] # see above + self.request_data = getattr(source_iterator, "request_data", {}) or {} + self.call_type = getattr(source_iterator, "call_type", None) # pyright: ignore[reportAttributeAccessIssue] # see above + self._hidden_params = dict(getattr(source_iterator, "_hidden_params", None) or {}) + + def adopt_fallback_headers(self, fallback_response: object) -> _Prepared: + prepared: Final = _prepare_fallback_hidden_params(fallback_response) + self._billing_source = fallback_response + self._hidden_params = {**prepared[0], "additional_headers": prepared[1]} + self.fallback_headers_adopted = True + return prepared + + def partial_response_on_disconnect(self) -> "ResponseIncompleteEvent | None": + from litellm.responses.streaming_iterator import partial_responses_incomplete_event_on_disconnect + + current: Final = partial_responses_incomplete_event_on_disconnect(self._billing_source) + if self._billing_source is source_iterator: + return current + primary: Final = partial_responses_incomplete_event_on_disconnect(source_iterator) + if current is None or primary is None: + return current or primary + if primary.response.usage is not None: + _combine_responses_fallback_usage(current, primary.response.usage) + return current + + def __aiter__(self) -> "FallbackResponsesStreamWrapper": + return self + + @property + def yielded_first_chunk(self) -> bool: + return self._yielded_first_chunk + + async def __anext__(self) -> object: # pyright: ignore[reportIncompatibleMethodOverride] # yields what the stream yields + try: + chunk: Final = await self._async_generator.__anext__() + except StopAsyncIteration: + if self.completed_response is None: + self.completed_response = getattr(source_iterator, "completed_response", None) + raise + if self.completed_response is None and getattr(chunk, "type", None) in terminal_event_types: + self.completed_response = chunk # pyright: ignore[reportAttributeAccessIssue] # the terminal event + self._yielded_first_chunk = True + sequence_number: Final = getattr(chunk, "sequence_number", None) + if not isinstance(sequence_number, int): + return chunk + if not self.fallback_headers_adopted: + self._last_sequence_number = max(self._last_sequence_number, sequence_number) + return chunk + self._last_sequence_number = max(self._last_sequence_number + 1, sequence_number) + if self._last_sequence_number == sequence_number: + return chunk + return chunk.model_copy(update={"sequence_number": self._last_sequence_number}) # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType, reportUnknownVariableType] # a response event, the only item with a sequence_number + + async def aclose(self) -> None: + await self._async_generator.aclose() + + def background_stream_can_release(item: object) -> bool: + from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator + + if ( + type(source_iterator) is not ResponsesAPIStreamingIterator + or source_iterator.custom_llm_provider != "openai" + ): + return False + if not _responses_event_announces_background_run(item): + return False + return not attempt.can_fall_back() + + async def stream_with_fallbacks() -> AsyncGenerator[object, None]: + held: tuple[object, ...] = () # rebind-ok: flushed at first output, dropped on fallback + response_id_exposed = False # rebind-ok: set once, before an early-released event is yielded + try: + async for item in _areported( + attempt, + cast("AsyncIterator[object]", source_iterator), # cast-ok: an async stream + lambda last: _responses_total_tokens(last, source_iterator), + ): + if not response_id_exposed and background_stream_can_release(item): + response_id_exposed = True + if not response_id_exposed and _responses_stream_holds_event(item, len(held)): + held = (*held, item) + continue + for held_event in held: + yield held_event + held = () + yield item + for held_event in held: + yield held_event + except (MidStreamFallbackError, litellm_exceptions.ContextWindowExceededError) as stream_error: + e: Final = ( + _context_window_stream_fallback_error( + stream_error, + source_iterator.model or "", + source_iterator.custom_llm_provider or "", + wrapper.yielded_first_chunk, + ) + if _is_context_window(stream_error) + else cast("MidStreamFallbackError", stream_error) # cast-ok: not a context window error + ) + if response_id_exposed: + _raise_original_mid_stream_error(e) + async with contextlib.aclosing( + _responses_fallback_attempt(attempt, e, source_iterator, wrapper.adopt_fallback_headers, held) + ) as fallback_stream: + async for fallback_item in fallback_stream: + yield fallback_item + except Exception: + for held_event in held: + yield held_event + raise + finally: + with anyio.CancelScope(shield=True): + if hasattr(source_iterator, "aclose"): + try: + await source_iterator.aclose() # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType] # checked above + except Exception as exc: # noqa: BLE001 # closing is best-effort + verbose_router_logger.debug("stream_with_fallbacks(aresponses): error closing source: %s", exc) + + wrapper: Final = FallbackResponsesStreamWrapper(stream_with_fallbacks()) + return wrapper + + +def _responses_continuation_request( + attempt: StreamAttempt, e: MidStreamFallbackError, source_iterator: "BaseResponsesAPIStreamingIterator" +) -> Mapping[str, object] | None: + """The request a fallback continues from once a Responses stream broke after text, or None before + output. Raises the primary's error when the output is constrained, a tool call began, a content + filter cut it, or the output ceiling is spent.""" + from litellm.litellm_core_utils.token_counter import ( + token_counter, # pyright: ignore[reportUnknownVariableType] # untyped tokenizer argument + ) + from litellm.router_utils.pre_call_checks.continuation_prefill_check import ( + RESPONSES_CONTINUATION_KWARG, + ResponsesContinuation, + constrains_responses_continuation, + continuation_output_ceilings, + responses_continuation_input, + ) + + if _mid_stream_error_before_output(e): + return None + if source_iterator.started_tool_call or isinstance( + e.original_exception, litellm_exceptions.ContentPolicyViolationError + ): + _raise_original_mid_stream_error(e) + cut_deployment_id: Final = (get_hidden_params(source_iterator) or {}).get("model_id") + if constrains_responses_continuation(_params_sent_to_deployment(attempt, cut_deployment_id)): + _raise_original_mid_stream_error(e) + request: Final = attempt.request + earlier: Final = request.get(RESPONSES_CONTINUATION_KWARG) + continuation: Final = ( + earlier.extended(e.generated_content) + if isinstance(earlier, ResponsesContinuation) + else ResponsesContinuation(request.get("input"), e.generated_content) + ) + emitted_tokens: Final = token_counter(model=e.model or "", text=e.generated_content) + reduced: Final = continuation_output_ceilings(request, emitted_tokens) + if reduced is None: + _raise_original_mid_stream_error(e) + return { + **request, + **reduced, + RESPONSES_CONTINUATION_KWARG: continuation, + "input": responses_continuation_input(continuation), + } + + +async def _responses_fallback_attempt( + attempt: StreamAttempt, + e: MidStreamFallbackError, + source_iterator: "BaseResponsesAPIStreamingIterator", + adopt_headers: Callable[[object], _Prepared], + held: tuple[object, ...], +) -> AsyncGenerator[object, None]: + """Re-enters the fallback walk for a mid-stream Responses error. The primary's held lifecycle events + reach the client only when no fallback lands.""" + from litellm.router_utils.pre_call_checks.continuation_prefill_check import ResponsesContinuationSeam + + continued: Final = _responses_continuation_request(attempt, e, source_iterator) + seam: Final = ResponsesContinuationSeam(e.generated_content if continued is not None else "") + partial_usage: Final = _extract_partial_responses_usage(source_iterator) + trigger: Final = _fallback_trigger( + e, (litellm_exceptions.ContentPolicyViolationError, litellm_exceptions.ContextWindowExceededError) + ) + fallback_response: object = None # rebind-ok: set once a fallback answered, closed at the end + fallback_yielded = False # rebind-ok: flipped on the first fallback item + try: + fallback_response = await attempt.fallback(trigger, continued) # rebind-ok: rebound as the stream advances + prepared: Final = adopt_headers(fallback_response) + if hasattr(fallback_response, "__aiter__"): + spliced: Final = cast( # cast-ok: the fallback's events + "AsyncIterator[object]", + seam.splice(fallback_response), # pyright: ignore[reportArgumentType] # an async stream + ) + async for fallback_item in spliced: + _apply_fallback_hidden_params_to_item(fallback_item, prepared) + if partial_usage is not None: + _combine_responses_fallback_usage(fallback_item, partial_usage) + fallback_yielded = True + yield fallback_item + else: + fallback_yielded = True # rebind-ok: rebound as the stream advances + yield fallback_response + except Exception as fallback_error: # noqa: BLE001 # as the Python wrapper: logged, then the stream's error raises + verbose_router_logger.error("Responses streaming fallback also failed: %s", fallback_error) + if not fallback_yielded: + for held_event in held: + yield held_event + _raise_fallback_failure(fallback_error) + finally: + if fallback_response is not None and hasattr(fallback_response, "aclose"): + with anyio.CancelScope(shield=True): + try: + await fallback_response.aclose() # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType] # checked above + except Exception as exc: # noqa: BLE001 # closing is best-effort + verbose_router_logger.debug("stream_with_fallbacks(aresponses): error closing fallback: %s", exc) + + +# --- the attempt hook --------------------------------------------------------------------------- + + +async def open_attempt_stream(attempt: StreamAttempt, response: object) -> object: + """What an attempt returns once its stream is wrapped: a chat stream's first chunk is read here, so + a stream that fails before any token raises inside the attempt.""" + from litellm.responses.streaming_iterator import BaseResponsesAPIStreamingIterator + + if attempt.op == "acompletion" and isinstance(response, CustomStreamWrapper): + if response.completion_stream is None and response.make_call is not None: # pyright: ignore[reportUnknownMemberType] # untyped attributes + await response.fetch_stream() + first_chunk: Final = await _aread_first_chunk(response) + held_slot: Final = attempt.slot.pop_all() if attempt.slot is not None else contextlib.ExitStack() + return wrap_chat_stream(attempt, response, first_chunk, held_slot) + if not attempt.kwargs.get("stream"): + return response + if attempt.op == "aresponses" and isinstance(response, BaseResponsesAPIStreamingIterator): + return wrap_responses_stream(attempt, response) + if attempt.op in ("aanthropic_messages", "anthropic_messages") and hasattr(response, "__aiter__"): + return wrap_anthropic_stream(attempt, cast("AsyncIterator[bytes]", response)) # cast-ok: a byte stream + return response + + +def open_attempt_stream_sync(attempt: StreamAttempt, response: object) -> object: + if attempt.op == "completion" and isinstance(response, CustomStreamWrapper): + if response.completion_stream is None and response.make_call is not None: # pyright: ignore[reportUnknownMemberType] # untyped attributes + response.fetch_sync_stream() + return wrap_chat_stream_sync(attempt, response, _read_first_chunk(response)) + return response + + +def shape_attempt_kwargs(kwargs: Mapping[str, object], deployment: Mapping[str, object]) -> Mapping[str, object]: + """A Responses continuation is shaped for the deployment the fallback landed on.""" + from litellm.router_utils.pre_call_checks.continuation_prefill_check import ( + RESPONSES_CONTINUATION_KWARG, + responses_continuation_input_for, + ) + + if RESPONSES_CONTINUATION_KWARG not in kwargs: + return kwargs + shaped: Final = without(kwargs, RESPONSES_CONTINUATION_KWARG) + shaped["input"] = responses_continuation_input_for(kwargs, deployment) + return shaped + + +__all__ = [ + "MAX_BUFFERED_PRE_CONTENT_ANTHROPIC_CHUNKS", + "MAX_HELD_PRE_OUTPUT_RESPONSES_EVENTS", + "FallbackAwareAnthropicMessagesStream", + "FallbackAwareStreamWrapper", + "StreamAttempt", + "open_attempt_stream", + "open_attempt_stream_sync", + "shape_attempt_kwargs", +] diff --git a/litellm/router_rust/invoke/walk.py b/litellm/router_rust/invoke/walk.py new file mode 100644 index 00000000000..4dab8edc07f --- /dev/null +++ b/litellm/router_rust/invoke/walk.py @@ -0,0 +1,398 @@ +""" +The request metadata the Python router stamps as it walks retries and fallbacks, kept for a +``RustCore`` call. router-core decides the walk and reports it (each attempt's ``scope``, +``max_retries`` and ``model_group_size``, and the ``fallback`` and ``retry_logged`` events); this +module only holds what each level's metadata dict holds in the Python router and lays it over the +attempt's kwargs. + +In the Python router one metadata dict serves a level's retries, and every fallback hop copies +its parent's (``run_async_fallback``'s ``_hop_metadata``), so a hop's breadcrumbs never reach +its parent. Each scope here is one such dict. The root level's dict is the caller's own (a proxy +reads a failed request's walk off it), so a fresh call's root writes reach that dict as well. +""" + +from collections.abc import Callable, Coroutine, Mapping, Sequence +from typing import TYPE_CHECKING, Final + +from litellm.litellm_core_utils.core_helpers import as_str_mapping + +if TYPE_CHECKING: + from opentelemetry.trace import Span + + from litellm.router_api import RoutingContext + from litellm.router_utils.fallback_event_handlers import AttemptedFallbackTargets + +# `RETRY_BREADCRUMB_LIMIT`: how many failures `previous_models` keeps. +RETRY_BREADCRUMB_LIMIT: Final = 4 + +# The keys the walk stamps on each attempt's metadata. +_WALK_KEYS: Final = ( + "original_model_group", + "attempted_fallbacks", + "attempted_retries", + "max_retries", + "model_group_size", + "previous_models", + "request_retry_count", +) +# What a breadcrumb reads from the last attempt a scope made. +_SERVED_KEYS: Final = ("model_info", "deployment") +# The walk state `run_async_fallback` hands every hop as kwargs. +_HOP_KWARGS: Final = ("fallback_depth", "max_fallbacks", "attempted_targets", "include_fallback_errors") + + +class _Scope: + __slots__ = ("kwargs", "metadata") + + def __init__( + self, + metadata: dict[str, object], # mutable-ok: the level's metadata, stamped as the walk runs + kwargs: Mapping[str, object], + ) -> None: + self.metadata: Final = metadata + self.kwargs: Final = kwargs + + +def _breadcrumb( + metadata: Mapping[str, object], model: str, error: BaseException, params_base_model: Callable[[str], str | None] +) -> dict[str, object]: # mutable-ok: a fresh RetryAttemptRecord + """``_core_log_retry``'s record of the failure.""" + from litellm.litellm_core_utils.get_litellm_params import get_base_model_from_litellm_call_metadata + + model_info: Final = as_str_mapping(metadata.get("model_info")) or {} + deployment_id: Final = model_info.get("id") + known_id: Final = deployment_id if isinstance(deployment_id, str) else None + base_model: Final = get_base_model_from_litellm_call_metadata(metadata=metadata) or ( + params_base_model(known_id) if known_id is not None else None + ) + deployment: Final = metadata.get("deployment") + attempted: Final = metadata.get("attempted_retries") + return { + "model_group": model, + "deployment_id": known_id, + "model": deployment if isinstance(deployment, str) else None, + "base_model": base_model, + "exception_type": type(error).__name__, + "exception_string": str(error), + "attempted_retries": attempted if type(attempted) is int else None, + } + + +def _kept_breadcrumbs(earlier: object) -> tuple[object, ...]: + """The breadcrumbs a new one joins: the latest ``RETRY_BREADCRUMB_LIMIT - 1``.""" + if not isinstance(earlier, list | tuple): + return () + stamped: Final[tuple[object, ...]] = tuple(earlier) # pyright: ignore[reportUnknownArgumentType, reportUnknownVariableType] # the breadcrumbs as stamped + return stamped[-(RETRY_BREADCRUMB_LIMIT - 1) :] + + +def log_retry_into( + kwargs: dict[str, object], # mutable-ok: the request kwargs whose metadata the record joins + error: Exception, + params_base_model: Callable[[str], str | None], +) -> dict[str, object]: # mutable-ok: the same kwargs, as ``_core_log_retry`` returns them + """ + ``_core_log_retry`` (``RoutingContext.log_retry``): the failure joins the request metadata's + ``previous_models`` and counts toward ``request_retry_count``, with a ``litellm.routing.retry`` + phase event when a pre-routing strategy picked the group. + """ + from litellm.integrations.otel.runtime import phase_event + + field: Final = "litellm_metadata" if "litellm_metadata" in kwargs else "metadata" + metadata: Final = kwargs[field] + view: Final = as_str_mapping(metadata) + if view is None: + # Python reads it with ``.get``. + raise AttributeError(f"{type(metadata).__name__!r} object has no attribute 'get'") + model_group: Final = kwargs.get("model") + record: Final = _breadcrumb(view, "", error, params_base_model) + record["model_group"] = model_group if isinstance(model_group, str) else None + deployment_id: Final = record["deployment_id"] + breadcrumbs: Final = (*_kept_breadcrumbs(view.get("previous_models")), record) + earlier: Final = view.get("request_retry_count") + request_retry_count: Final = (earlier if type(earlier) is int and 0 <= earlier else 0) + 1 + decision: Final = view.get("routing_decision") + router_name: Final = (as_str_mapping(decision) or {}).get("router_model_name") + if isinstance(router_name, str): + phase_event( + "litellm.routing.retry", + { + "litellm.routing.router_model_name": router_name, + "litellm.retry.count": request_retry_count, + "error.type": type(error).__name__, + **({"litellm.deployment.model_group": model_group} if isinstance(model_group, str) else {}), + **({"litellm.deployment.id": deployment_id} if isinstance(deployment_id, str) else {}), + }, + ) + metadata["previous_models"] = breadcrumbs # pyright: ignore[reportIndexIssue] # the logging object already holds this dict + metadata["request_retry_count"] = request_retry_count # pyright: ignore[reportIndexIssue] # same dict, read by the cap + return kwargs + + +class WalkMetadata: + """The metadata each level of one call's walk holds, by scope.""" + + __slots__ = ("_attempted", "_field", "_live", "_params_base_model", "_request", "_scopes") + + def __init__( + self, + request: Mapping[str, object], + field: str, + params_base_model: Callable[[str], str | None], + *, + live: bool = False, + ) -> None: + model: Final = request.get("model") + root: Final[dict[str, object]] = {"attempted_fallbacks": 0} # mutable-ok: the root level's metadata + if model is not None: + root["original_model_group"] = model + self._request: Final = request + self._field: Final = field + self._params_base_model: Final = params_base_model + self._scopes: Final[dict[int, _Scope]] = {0: _Scope(root, {})} # mutable-ok: filled as the walk hops + self._attempted: AttemptedFallbackTargets | None = None + # A call whose retry and fallback wrappers stamp the request itself; a stream's recovery + # re-enters below them. + self._live: Final = live + if live: + self._stamp_fallback_entry() + + def _stamp_fallback_entry(self) -> None: + """The head of ``async_function_with_fallbacks``, in the request's own buckets. ``run_async_fallback``'s + hops carry their ``attempted_targets`` and never reach it.""" + from litellm.router_utils.fallback_event_handlers import AttemptedFallbackTargets + + request: Final = self._request + if isinstance(request.get("attempted_targets"), AttemptedFallbackTargets): + return + sibling: Final = request.get("metadata" if self._field == "litellm_metadata" else "litellm_metadata") + if isinstance(sibling, dict): + sibling.pop("attempted_fallbacks", None) # pyright: ignore[reportUnknownMemberType] # the caller's metadata dict + sibling.pop("original_model_group", None) # pyright: ignore[reportUnknownMemberType] # see above + bucket: Final = request.get(self._field) + if not isinstance(bucket, dict): + return + bucket["attempted_fallbacks"] = 0 + model: Final = request.get("model") + if model is not None: + bucket["original_model_group"] = model + + def _retry_bucket(self, scope: _Scope) -> dict[str, object] | None: # mutable-ok: the request's own dict + """``_metadata`` of ``async_function_with_retries`` when it is a dict of the request's: the + root level's, or a hop's when the bucket is not the one ``run_async_fallback`` copies.""" + if not self._live: + return None + name: Final = "litellm_metadata" if "litellm_metadata" in self._request else "metadata" + if scope is not self._scopes[0] and name == self._field: + return None + bucket: Final = self._request.get(name) + # `... or {}`: an empty bucket leaves the stamps on a dict of their own. + return bucket if isinstance(bucket, dict) and bucket else None # pyright: ignore[reportUnknownVariableType] # the request's untyped metadata dict + + def _write_through(self, scope: _Scope, values: Mapping[str, object]) -> None: + bucket: Final = self._retry_bucket(scope) + if bucket is not None: + bucket.update(values) + + def retries_opened(self, event: Mapping[str, object]) -> None: + """The head of ``async_function_with_retries``: the group's size and the retry tracking, before any pick.""" + scope: Final = self._scope(event.get("scope")) + stamped: Final = {"attempted_retries": 0, "max_retries": event.get("max_retries")} + scope.metadata.update(stamped) + self._write_through(scope, stamped) + bucket: Final = self._retry_bucket(scope) + if bucket is not None and isinstance(bucket.get("model_group"), str): + bucket["model_group_size"] = event.get("model_group_size") + + def retry_budget(self, event: Mapping[str, object]) -> None: + """``_metadata["max_retries"] = num_retries``, once a level's first failure settled its overrides.""" + scope: Final = self._scope(event.get("scope")) + stamped: Final = {"max_retries": event.get("max_retries")} + scope.metadata.update(stamped) + self._write_through(scope, stamped) + + def _scope(self, value: object) -> _Scope: + found: Final = self._scopes.get(value) if isinstance(value, int) else None + return found if found is not None else self._scopes[0] + + def targets(self) -> "AttemptedFallbackTargets": + """The walk's ``attempted_targets``: the targets tried and the ones skipped, and why.""" + from litellm.router_utils.fallback_event_handlers import AttemptedFallbackTargets + + if self._attempted is None: + self._attempted = AttemptedFallbackTargets() + return self._attempted + + def hop(self, event: Mapping[str, object]) -> None: + """A ``fallback`` event: the new level copies its parent's metadata and kwargs.""" + parent: Final = self._scope(event.get("parent")) + attempted: Final = self.targets() + for key in (event.get("from"), event.get("to")): + if isinstance(key, str): + attempted.record(key) + metadata: Final = dict(parent.metadata) + original: Final = metadata.pop("original_model_group", self._request.get("model")) + metadata.pop("model_group", None) + metadata.pop("attempted_fallbacks", None) + metadata["original_model_group"] = original + # A dict target's non-string `model` is what `kwargs["model"]` holds on the hop. + metadata["model_group"] = event["unroutable"] if "unroutable" in event else event.get("to") + metadata["attempted_fallbacks"] = event.get("depth") + kwargs: Final = { + **parent.kwargs, + "fallback_depth": event.get("depth"), + "max_fallbacks": event.get("max_fallbacks"), + "attempted_targets": attempted, + } + if self._request.get("include_fallback_errors") is True: + kwargs["include_fallback_errors"] = True + scope: Final = event.get("scope") + if isinstance(scope, int): + self._scopes[scope] = _Scope(metadata, kwargs) + + def hop_kwargs(self, event: Mapping[str, object]) -> dict[str, object]: # mutable-ok: a fresh dict for the loggers + """The kwargs the level held after a hop (``kwargs["model"] = target``), as the + fallback loggers see them.""" + scope: Final = self._scope(event.get("scope")) + model: Final = scope.metadata.get("model_group", event.get("to")) + return {**self._request, **scope.kwargs, "model": model, self._field: dict(scope.metadata)} + + def log_retry(self, event: Mapping[str, object], error: BaseException | None) -> None: + """A ``retry_logged`` event: the failure joins the scope's ``previous_models``.""" + scope: Final = self._scope(event.get("scope")) + metadata: Final = scope.metadata + attempted: Final = event.get("attempted_retries") + if isinstance(attempted, int): + metadata["attempted_retries"] = attempted + self._write_through(scope, {"attempted_retries": attempted}) + if error is None: + return + record: Final = _breadcrumb(metadata, str(event.get("model")), error, self._params_base_model) + earlier: Final = metadata.get("previous_models") + kept: Final = _kept_breadcrumbs(earlier) + count: Final = metadata.get("request_retry_count") + metadata["previous_models"] = (*kept, record) + metadata["request_retry_count"] = (count if type(count) is int and count >= 0 else 0) + 1 + self._write_through( + scope, + {"previous_models": metadata["previous_models"], "request_retry_count": metadata["request_retry_count"]}, + ) + + def deployment_that_just_failed(self, step: Mapping[str, object]) -> str | None: + """``_deployment_that_just_failed``: the deployment the metadata an attempt inherits names, + before the attempt stamps its own; ``None`` when the walk's level has run none yet.""" + model_info: Final = as_str_mapping(self._scope(step.get("scope")).metadata.get("model_info")) + model_id: Final = model_info.get("id") if model_info is not None else None + return model_id if isinstance(model_id, str) else None + + def request_retry_count(self, step: Mapping[str, object]) -> object: + """The level's ``request_retry_count``, as the retry loop has counted it so far.""" + return self._scope(step.get("scope")).metadata.get("request_retry_count") + + def stamp(self, step: Mapping[str, object], kwargs: Mapping[str, object]) -> Mapping[str, object]: + """The attempt's kwargs with its level's walk metadata and hop kwargs laid over them.""" + scope: Final = self._scope(step.get("scope")) + metadata: Final = scope.metadata + metadata["attempted_retries"] = step.get("retry") + metadata["max_retries"] = step.get("max_retries") + metadata["model_group_size"] = step.get("model_group_size") + self._write_through( + scope, {"attempted_retries": metadata["attempted_retries"], "max_retries": metadata["max_retries"]} + ) + served: Final = dict(as_str_mapping(kwargs.get(self._field)) or {}) + served.update({key: metadata[key] for key in _WALK_KEYS if key in metadata}) + metadata.update({key: served.get(key) for key in _SERVED_KEYS}) + return {**kwargs, **{key: scope.kwargs[key] for key in _HOP_KWARGS if key in scope.kwargs}, self._field: served} + + +async def _log_failed_fallbacks(ctx: "RoutingContext", detail: str, parent_otel_span: "Span | None") -> None: + from litellm._logging import verbose_router_logger + from litellm.router_utils.cooldown_handlers import async_get_cooldown_deployments_with_debug_info + + cooldown_info: Final = await async_get_cooldown_deployments_with_debug_info( + ctx=ctx, parent_otel_span=parent_otel_span + ) + verbose_router_logger.error( + "litellm.router.py::async_function_with_fallbacks() - " + "Error occurred while trying to do fallbacks - %s\n" + "Debug Information:\nCooldown Deployments=%s", + detail, + cooldown_info, + ) + + +class FallbackOutcomes: + """What ``run_async_fallback`` does when a hop returns: it logs the hop to the process's + custom loggers and, under ``include_fallback_errors``, lists the level's errors (its own + first, then each hop that failed) in the response's ``x-litellm-fallback-errors``.""" + + __slots__ = ("_failed", "_header_errors", "_include", "_pending") + + def __init__(self, request: Mapping[str, object]) -> None: + self._include: Final = request.get("include_fallback_errors", False) is True + self._failed: Final[dict[object, list[object]]] = {} # mutable-ok: each level's failed hops, in order + self._header_errors: Final[list[list[object]]] = [] # mutable-ok: each successful hop's errors, innermost first + self._pending: Final[list[Coroutine[object, object, None]]] = [] # mutable-ok: logger calls not yet awaited + + def done( + self, + event: Mapping[str, object], + level_error: BaseException | None, + hop_error: BaseException | None, + kwargs: Mapping[str, object], + ) -> None: + from litellm.litellm_core_utils.add_retry_fallback_headers import get_fallback_error_info + from litellm.router_utils import fallback_event_handlers as handlers + + if level_error is None or not isinstance(level_error, Exception): + return + parent: Final = event.get("parent") + failed: Final = self._failed.setdefault(parent, []) + original: Final = str(event.get("from")) + if event.get("succeeded") is True: + if self._include: + self._header_errors.append([get_fallback_error_info(level_error), *failed]) + self._pending.append( + handlers.log_success_fallback_event( # pyright: ignore[reportUnknownMemberType] # takes the kwargs as an untyped dict + original_model_group=original, kwargs=dict(kwargs), original_exception=level_error + ) + ) + return + if isinstance(hop_error, Exception): + failed.append(get_fallback_error_info(hop_error)) + self._pending.append( + handlers.log_failure_fallback_event( # pyright: ignore[reportUnknownMemberType] # see above + original_model_group=original, kwargs=dict(kwargs), original_exception=level_error + ) + ) + + def failed_fallbacks(self, ctx: "RoutingContext", detail: str, parent_otel_span: "Span | None") -> None: + """The ``except`` around the regular fallbacks of ``async_function_with_fallbacks_common_utils``: + ``detail`` is the failure's text as it read then, the cooldowns are read when the pending calls run.""" + self._pending.append(_log_failed_fallbacks(ctx, detail, parent_otel_span)) + + def take_pending(self) -> tuple[Coroutine[object, object, None], ...]: + pending: Final = tuple(self._pending) + self._pending.clear() + return pending + + def add_headers(self, response: object, attempted_fallbacks: int) -> object: + """``add_fallback_headers_to_response`` for each successful hop, innermost first.""" + from litellm.litellm_core_utils.add_retry_fallback_headers import add_fallback_headers_to_response + + headed: object = response # rebind-ok: gains each level's errors + for errors in self._header_errors: + headed = add_fallback_headers_to_response( + response=headed, + attempted_fallbacks=attempted_fallbacks, + fallback_errors=errors, # pyright: ignore[reportArgumentType] # FallbackErrorInfo dicts + ) + return headed + + +async def await_all(pending: Sequence[Coroutine[object, object, None]]) -> None: + for call in pending: + await call + + +__all__ = ["RETRY_BREADCRUMB_LIMIT", "FallbackOutcomes", "WalkMetadata", "await_all"] diff --git a/litellm/router_rust/invoke/websocket.py b/litellm/router_rust/invoke/websocket.py new file mode 100644 index 00000000000..e7baeb92345 --- /dev/null +++ b/litellm/router_rust/invoke/websocket.py @@ -0,0 +1,127 @@ +""" +Responses websocket turns on the Rust router core (``async_admit_deployment_turn``): the socket is +opened on one deployment, and the core hands the handler a ``turn_admission`` callable that re-runs +that deployment's admission before every later turn: the io-token turn budget, the deployment +budget limiter, the routing strategy (on that deployment alone) and the pre-call checks. + +Which strategy and selector apply is the Rust core's routing context (``routing_context``); the +selectors, limiters and checks are the live Python objects the host keeps. +""" + +from collections.abc import Callable, Mapping +from functools import partial +from types import MappingProxyType +from typing import TYPE_CHECKING, Final + +from litellm.litellm_core_utils.core_helpers import without +from litellm.router_rust.invoke.shaping import as_dict + +if TYPE_CHECKING: + from litellm.router_rust.invoke.endpoints import EndpointCore + + +def turn_admission( + core: "EndpointCore", model_group: str, deployment: Mapping[str, object], kwargs: Mapping[str, object] +) -> Callable[[], object]: + """The ``turn_admission`` the handler calls before each later turn.""" + return partial(admit_deployment_turn, core, model_group, deployment, kwargs) + + +def _deployment_as_configured_now(core: "EndpointCore", deployment: Mapping[str, object]) -> Mapping[str, object]: + model_info: Final = deployment.get("model_info") + model_id: Final = as_dict(model_info).get("id") if isinstance(model_info, dict) else None # pyright: ignore[reportUnknownArgumentType] # the configured model_info dict + current: Final = core.configured_deployment(model_id) if isinstance(model_id, str) else None + return deployment if current is None else current.model_dump(exclude_none=True) + + +def _budget_limiter(core: "EndpointCore") -> object: + """The router's deployment-budget callback; the Rust core declines every config that has one.""" + from litellm.router_rust.core import RustCoreUnsupported + + try: + return core.registry().plugins("budget_limiter") + except RustCoreUnsupported: + return None + + +async def admit_deployment_turn( + core: "EndpointCore", model_group: str, opened_on: Mapping[str, object], request_kwargs: Mapping[str, object] +) -> Mapping[str, object]: + """`async_admit_deployment_turn`.""" + from litellm import exceptions as litellm_exceptions + from litellm.router_utils.pre_call_checks.io_token_rate_limit_check import ( + async_admit_io_token_turn, + without_io_token_limits, + ) + from litellm.router_utils.pre_call_checks.model_rate_limit_check import ModelRateLimitingCheck + from litellm.utils import get_utc_datetime + + deployment: Final = _deployment_as_configured_now(core, opened_on) + rate_limit_check: Final = next( + (callback for callback in core.routing_callbacks() if isinstance(callback, ModelRateLimitingCheck)), + None, + ) + io_token_admission: Final[Mapping[str, object]] = ( + MappingProxyType({}) + if rate_limit_check is None + else await async_admit_io_token_turn(rate_limit_check.dual_cache, deployment, get_utc_datetime()) # pyright: ignore[reportArgumentType] # the configured deployment dict + ) + budget_limiter: Final[object] = _budget_limiter(core) + if budget_limiter is not None: + try: + await budget_limiter.async_filter_deployments( # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType] # RouterBudgetLimiting + model=model_group, + healthy_deployments=[dict(deployment)], + messages=None, + request_kwargs=dict(request_kwargs), + ) + except ValueError as e: + raise litellm_exceptions.RateLimitError( + message=str(e), + llm_provider="", + model=model_group, + category=litellm_exceptions.RateLimitErrorCategory.LITELLM_RATE_LIMIT, + ) from e + await _admit_turn_through_routing_strategy(core, model_group, deployment, request_kwargs) + await core.router.async_routing_strategy_pre_call_checks( + deployment=dict(without_io_token_limits(deployment)), parent_otel_span=None + ) + return io_token_admission + + +async def _admit_turn_through_routing_strategy( + core: "EndpointCore", model_group: str, deployment: Mapping[str, object], request_kwargs: Mapping[str, object] +) -> None: + """`_admit_turn_through_routing_strategy`: the group's strategy picks among this deployment alone.""" + from litellm import exceptions as litellm_exceptions + from litellm.router_api import RoutingContext + from litellm.router_rust.steps.selection import pick_async + from litellm.router_utils.handle_error import async_raise_no_deployment_exception + + routing_kwargs: Final = without(request_kwargs, "litellm_logging_obj") + override: Final = routing_kwargs.get("routing_strategy") + strategy, scope, group = core.handle.routing_context(model_group, override if isinstance(override, str) else None) + selectors: Final = core.selectors + selector: Final = selectors.selector_for(strategy, scope, group, routing_kwargs) + if strategy == "simple-shuffle" or selector is None: + return + selected: Final = await pick_async( + strategy, selector, model_group, [dict(deployment)], None, None, dict(routing_kwargs) + ) + if selected is None: + no_deployment: Final = await async_raise_no_deployment_exception( + ctx=RoutingContext(core), # pyright: ignore[reportArgumentType] # the error reads registry() and health() + model=model_group, + parent_otel_span=None, + ) + raise litellm_exceptions.RateLimitError( + message=str(no_deployment), + llm_provider="", + model=model_group, + category=litellm_exceptions.RateLimitErrorCategory.LITELLM_RATE_LIMIT, + ) from no_deployment + if selectors.is_override(strategy, selector): + await selector.async_pre_call_check(dict(deployment), None) # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType] # every selector is a CustomLogger + + +__all__ = ["admit_deployment_turn", "turn_admission"] diff --git a/litellm/router_rust/steps/README.md b/litellm/router_rust/steps/README.md new file mode 100644 index 00000000000..9b5c68bdba9 --- /dev/null +++ b/litellm/router_rust/steps/README.md @@ -0,0 +1,12 @@ +# steps + +Answers to router-core's host steps that need live Python objects. router-core makes the routing decision; these modules supply the Python-only facts or run the Python-only objects it asks about. + +- `selection`: stateful strategies (latency, tpm/rpm, cost, usage) on `select` steps +- `prerouting`: auto, complexity, adaptive and quality routers, and session binding, on `pre_route` steps +- `precall`: token counts, context windows and param support for pre-call checks +- `plugins`: `Router(plugins=[...])` objects +- `callbacks`: the optional pre-call checks (budgets, affinity, rate limits) as `CustomLogger`s +- `access`: the caller facts read from auth metadata + +A Rust host answers these steps natively, or declines the config at build. diff --git a/litellm/router_rust/steps/__init__.py b/litellm/router_rust/steps/__init__.py new file mode 100644 index 00000000000..c47505e7468 --- /dev/null +++ b/litellm/router_rust/steps/__init__.py @@ -0,0 +1 @@ +"""Answers to router-core host steps that need live Python objects.""" diff --git a/litellm/router_rust/steps/access.py b/litellm/router_rust/steps/access.py new file mode 100644 index 00000000000..087a87e2c6b --- /dev/null +++ b/litellm/router_rust/steps/access.py @@ -0,0 +1,85 @@ +"""The caller facts the Rust core routes on, read from the request's auth metadata: whether the +caller is a proxy admin, the models its key and team allow (which narrow an access-group-only +caller to its groups' deployments) and, for a proxy admin, the model the request names.""" + +from __future__ import annotations + +from collections.abc import Mapping +from typing import Final + +from pydantic import TypeAdapter + +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.routing_common_utils import is_proxy_admin_request, request_user_api_key_auth + +_NAMES: Final = TypeAdapter(tuple[object, ...]) + + +def _names(value: object) -> tuple[str, ...]: + names: Final = _NAMES.validate_python(value) if isinstance(value, list | tuple | set | frozenset) else () + return tuple(str(name) for name in names) + + +def _admin_model(request: Mapping[str, object]) -> object: + """The model ``filter_team_based_models`` compares team deployments against.""" + metadata: Final = as_str_mapping(request.get("metadata")) or {} + litellm_metadata: Final = as_str_mapping(request.get("litellm_metadata")) or {} + return request.get("model") or metadata.get("model_group") or litellm_metadata.get("model_group") + + +def caller_fields(request: Mapping[str, object]) -> Mapping[str, object]: + """``proxy_admin``, ``allowed_models`` and ``admin_model`` for the Rust request document.""" + auth: Final[object] = request_user_api_key_auth(request) + if auth is None: + return {} + allowed: Final = sorted({*_names(getattr(auth, "models", None)), *_names(getattr(auth, "team_models", None))}) + admin: Final = is_proxy_admin_request(request) + model: Final = _admin_model(request) if admin else None + return { + **({"allowed_models": allowed} if allowed else {}), + **({"proxy_admin": True} if admin else {}), + **({"admin_model": model} if isinstance(model, str) else {}), + } + + +def _router_weights_error(raw: object) -> BaseException: + """The error ``validate_router_weights`` raises for weights the Rust core refused.""" + from pydantic import ValidationError + + from litellm.types.router_weights import validate_router_weights + + try: + _ = validate_router_weights(raw) + except ValidationError as error: + return error + return RuntimeError(f"router-core refused router weights the validator accepts: {raw!r}") + + +def selection_refusal(step: Mapping[str, object], model: str, request: Mapping[str, object]) -> BaseException | None: + """The error for a pick the Rust core refused over who the caller is or what it asked for: + a public name several teams share, deployments reserved for other teams, invalid request + router weights or a non-numeric deployment weight. None for any other failure.""" + import litellm.exceptions as litellm_exceptions + + kind: Final = step.get("error_kind") + named: Final = str(step.get("error_model") or model) + if kind == "multiple_teams": + return litellm_exceptions.BadRequestError( + message=( + f"Model name '{named}' matches deployments from multiple teams. " + "Specify the deployment ID directly to disambiguate." + ), + model=named, + llm_provider="", + ) + if kind == "reserved": + return litellm_exceptions.BadRequestError( + message=f"Deployment {named} is reserved for another team until {step.get('error_detail')}", + model=named, + llm_provider="", + ) + if kind == "invalid_router_weights": + return _router_weights_error(request.get("_router_weights")) + if kind == "non_numeric_weight": + return TypeError(f"Deployment {step.get('error_detail')} must be numeric") + return None diff --git a/litellm/router_rust/steps/callbacks.py b/litellm/router_rust/steps/callbacks.py new file mode 100644 index 00000000000..b906a496550 --- /dev/null +++ b/litellm/router_rust/steps/callbacks.py @@ -0,0 +1,650 @@ +""" +Host-side optional pre-call checks for ``RustCore``: the ``CustomLogger`` checks a router builds +from ``optional_pre_call_checks``, ``provider_budget_config``, per-deployment budgets and +``model_group_affinity_config``, registered in the host's ``callbacks`` list exactly as the Python +router's ``add_optional_pre_call_checks`` registers them, since they are features users configure. + +The Rust core asks the host to run every routing callback's ``async_filter_deployments`` through a +``callback_filters`` select stage (``async_callback_filter_deployments``) and decides itself what +the surviving deployments or the raised error mean: a pick with nothing left, a retry, a fallback. + +This module also keeps the process-wide holder rules (``litellm/router_utils/global_callback_holders``): +a retiring router hands the checks it vacates to a survivor, a runtime removal keeps a check +another live router still has, and ``observe(request_scoped=True)`` takes every routing callback +off the host lists while the router keeps running them (``_routing_callbacks``). It also answers +which outcome callbacks the Python router would still have running for a request +(``OptionalChecks.outcome_callbacks``), which router-core records by. It never reaches a Python +router core. +""" + +from collections.abc import Iterable, Mapping, Sequence +from itertools import chain +from typing import TYPE_CHECKING, Final +from weakref import WeakSet + +from litellm._logging import verbose_router_logger +from litellm.caching.dual_cache import DualCache +from litellm.caching.in_memory_cache import InMemoryCache +from litellm.constants import PROMPT_CACHE_PIN_CACHE_MAX_SIZE +from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.routing_common_utils import get_request_team_id +from litellm.router_strategy.base_routing_strategy import BaseRoutingStrategy +from litellm.router_strategy.budget_limiter import RouterBudgetLimiting +from litellm.router_strategy.least_busy import LeastBusyLoggingHandler +from litellm.router_utils.global_callback_holders import ( + live_check_owners, + routers_holding_global_callbacks, + routers_holding_global_callbacks_lock, +) +from litellm.router_utils.pre_call_checks.deployment_affinity_check import ( + DeploymentAffinityCheck, + completed_affinity_response, + warn_on_unknown_model_group_affinity_flags, +) +from litellm.router_utils.pre_call_checks.encrypted_content_affinity_check import EncryptedContentAffinityCheck +from litellm.router_utils.pre_call_checks.model_rate_limit_check import ModelRateLimitingCheck +from litellm.router_utils.pre_call_checks.prompt_caching_deployment_check import PromptCachingDeploymentCheck + +if TYPE_CHECKING: + from litellm.litellm_core_utils.litellm_logging import Logging + from litellm.router_python_host import PythonHost + from litellm.router_rust.steps.selection import StrategySelectors + from litellm.router_rust.surface.registry import HostRegistry + from litellm.router_utils.cooldown_cache import CooldownCache + from litellm.router_utils.global_callback_holders import GlobalCallbackHolder + from litellm.types.router import Deployment + +_AFFINITY_CHECKS: Final = ( + "deployment_affinity", + "responses_api_deployment_check", + "session_affinity", + "encrypted_content_affinity", +) +# `_RUNTIME_TOGGLEABLE_PRE_CALL_CHECKS`: the checks a runtime list drops when it leaves them out. +_RUNTIME_TOGGLEABLE: Final[Mapping[str, type[CustomLogger]]] = { + "prompt_caching": PromptCachingDeploymentCheck, + "enforce_model_rate_limits": ModelRateLimitingCheck, + "encrypted_content_affinity": EncryptedContentAffinityCheck, +} + + +def _callbacks(host: "PythonHost") -> list[object]: # mutable-ok: the process list itself + return host.callback_list("callbacks") # pyright: ignore[reportArgumentType] # not in the CallbackList literal + + +def register_router_selector(host: "PythonHost", selector: CustomLogger) -> None: + """``_register_router_selector``: least-busy also counts calls as they start.""" + if isinstance(selector, LeastBusyLoggingHandler): + if isinstance(host.callback_list("input_callback"), list): # pyright: ignore[reportUnnecessaryIsInstance] # a process list a user may have reassigned + host.callbacks.add_litellm_input_callback(selector) + else: + host.set_callback_list("input_callback", [selector]) + if isinstance(_callbacks(host), list): # pyright: ignore[reportUnnecessaryIsInstance] # see above + host.callbacks.add_litellm_callback(selector) + + +def _move_before_deployment_affinity( + callback_list: list[object], # mutable-ok: reordered in place + callback: object, +) -> None: + if callback not in callback_list: + return + callback_list.remove(callback) + index: Final = next( + (i for i, entry in enumerate(callback_list) if isinstance(entry, DeploymentAffinityCheck)), + len(callback_list), + ) + callback_list.insert(index, callback) + + +class OptionalChecks: + """One router's optional pre-call checks (``optional_callbacks``) and the stores they read.""" + + def __init__( + self, + owner: "GlobalCallbackHolder", + host: "PythonHost", + cache: DualCache, + hosted: "HostRegistry", + ctx: object, + arguments: Mapping[str, object], + ) -> None: + self._owner: Final = owner + self._host: Final = host + self._cache: Final = cache + self._hosted: Final = hosted + self._ctx: Final = ctx + self.optional_callbacks: list[object] | None = None # mutable-ok: the router's live list, as Python keeps it + self.router_budget_logger: RouterBudgetLimiting | None = None + self.provider_budget_config: object = arguments.get("provider_budget_config") + ttl: Final = arguments.get("deployment_affinity_ttl_seconds") + self.deployment_affinity_ttl_seconds: object = 3600 if ttl is None else ttl + self.session_affinity_repin_on_failover: object = bool(arguments.get("session_affinity_repin_on_failover")) + affinity_config: Final = arguments.get("model_group_affinity_config") + self.model_group_affinity_config: dict[str, list[str]] | None = ( # mutable-ok: the argument as passed + affinity_config if isinstance(affinity_config, dict) else None # pyright: ignore[reportAttributeAccessIssue] # the argument as passed + ) + warn_on_unknown_model_group_affinity_flags(self.model_group_affinity_config) + self.prompt_caching_pin_cache: DualCache = DualCache( + redis_cache=cache.redis_cache, + in_memory_cache=InMemoryCache(max_size_in_memory=PROMPT_CACHE_PIN_CACHE_MAX_SIZE), + ) + self._request_scoped_selectors: tuple[CustomLogger, ...] = () + self._request_scoped_policies: tuple[CustomLogger, ...] = () + # ``_slack_alerting_loggers``: the Slack alerting logger ``alerting_config`` builds, if any. + self.slack_alerting_loggers: tuple[CustomLogger, ...] = () + # Whether the outcome callbacks would still be on the host lists (``_release_global_callbacks``). + self._outcome_callbacks_listed: bool = True + # The logging objects ``_core_bind_to_request_logging`` would have bound them to. + self._bound_requests: Final[WeakSet[Logging]] = WeakSet() + + # -- construction --------------------------------------------------------------------------- + + def build(self, checks: object, model_list: object) -> None: + """The constructor's checks: a budget appends ``router_budget_limiting`` to the list given (in + place, as Python does), the list is added, a per-group affinity config adds the affinity + check, and ``apply_default_settings`` adds the empty default list.""" + listed: list[object] | None = checks if isinstance(checks, list) else None # pyright: ignore[reportUnknownVariableType] # mutable-ok: appended in place, as Python does # rebind-ok: the argument as passed + if RouterBudgetLimiting.should_init_router_budget_limiter( # pyright: ignore[reportUnknownMemberType] # untyped model_list + model_list=model_list if isinstance(model_list, list) else None, # pyright: ignore[reportUnknownArgumentType] # the argument as passed + provider_budget_config=self.provider_budget_config, # pyright: ignore[reportArgumentType] # the argument as passed + ): + if listed is not None: + listed.append("router_budget_limiting") + else: + listed = ["router_budget_limiting"] # rebind-ok: the list Python builds + if listed is not None: + self.add(listed) # pyright: ignore[reportUnknownArgumentType] # names as given + if self.model_group_affinity_config: + self.ensure_deployment_affinity_callback() + self.add([]) + + def _is_priority_group(self, model: str) -> bool: + """``_is_priority_routing_group``.""" + hosted: Final = self._hosted + resolved: Final = hosted._core_get_model_from_alias(model=model) or model # pyright: ignore[reportPrivateUsage] # the host registry's alias lookup + group: Final = hosted.get_routing_group(resolved) + return group is not None and group.routing_strategy == "priority" + + async def repin_session_after_success( + self, litellm_params: Mapping[str, object], response: object, cooldowns: "CooldownCache" + ) -> None: + """``_repin_session_after_success``: with ``session_affinity_repin_on_failover`` on, a completed + success moves the session's pin to the deployment that served it, among the group's + deployments not cooling down.""" + if not self.session_affinity_repin_on_failover: + return + try: + if not completed_affinity_response(response): + return + callback: Final = next( + (logger for logger in self.optional_callbacks or () if isinstance(logger, DeploymentAffinityCheck)), + None, + ) + if callback is None: + return + model_group: Final = callback.get_repin_model_group(litellm_params) + if model_group is None or self._is_priority_group(model_group): + return + registered_ids: Final = self._hosted._core_get_candidate_model_ids_for_route( # pyright: ignore[reportPrivateUsage] # the host registry's candidate lookup + model=model_group, team_id=get_request_team_id(litellm_params) + ) + cooldown_ids: Final = frozenset( + model_id + for model_id, _ in await cooldowns.async_get_active_cooldowns( + model_ids=list(registered_ids), parent_otel_span=None + ) + ) + await callback.async_repin_session_after_success(litellm_params, model_group, registered_ids - cooldown_ids) + except Exception as error: # noqa: BLE001 # optional pin updates must not interrupt success accounting + verbose_router_logger.debug("Session re-pinning failed: %s", error) + + def _affinity_check(self, user_key: bool, responses_api: bool, session_id: bool) -> DeploymentAffinityCheck: + return DeploymentAffinityCheck( + cache=self._cache, + ttl_seconds=self.deployment_affinity_ttl_seconds, # pyright: ignore[reportArgumentType] # the argument as passed + enable_user_key_affinity=user_key, + enable_responses_api_affinity=responses_api, + enable_session_id_affinity=session_id, + model_group_affinity_config=self.model_group_affinity_config, + is_priority_group=self._is_priority_group, + session_affinity_repin_on_failover=self.session_affinity_repin_on_failover, # pyright: ignore[reportArgumentType] # same + ) + + def _own(self, callback: CustomLogger) -> None: + if self.optional_callbacks is None: + self.optional_callbacks = [] + self.optional_callbacks.append(callback) + self._host.callbacks.add_litellm_callback(callback) + + def ensure_deployment_affinity_callback(self) -> None: + """``_ensure_deployment_affinity_callback``: the affinity check with every global flag off.""" + if any(isinstance(cb, DeploymentAffinityCheck) for cb in self.optional_callbacks or ()): + return + self._own(self._affinity_check(False, False, False)) + + def _add_affinity(self, checks: Sequence[object]) -> None: + user_key: Final = "deployment_affinity" in checks + responses_api: Final = "responses_api_deployment_check" in checks + session_id: Final = "session_affinity" in checks + if not (user_key or responses_api or session_id): + return + if self.optional_callbacks is None: + self.optional_callbacks = [] + existing: Final = next( + (cb for cb in self.optional_callbacks if isinstance(cb, DeploymentAffinityCheck)), + None, + ) + if existing is None: + self._own(self._affinity_check(user_key, responses_api, session_id)) + return + existing.enable_user_key_affinity = existing.enable_user_key_affinity or user_key + existing.enable_responses_api_affinity = existing.enable_responses_api_affinity or responses_api + existing.enable_session_id_affinity = existing.enable_session_id_affinity or session_id + existing.ttl_seconds = self.deployment_affinity_ttl_seconds # pyright: ignore[reportAttributeAccessIssue] # the argument as passed + if self.model_group_affinity_config: + existing.model_group_affinity_config = self.model_group_affinity_config + + def _add_encrypted_content_affinity(self, enable_global_affinity: bool) -> None: + """``_add_encrypted_content_affinity_check``.""" + if not ( + enable_global_affinity + or EncryptedContentAffinityCheck.has_model_group_affinity_enabled(self.model_group_affinity_config) + ): + return + if self.optional_callbacks is None: + self.optional_callbacks = [] + existing: Final = next( + (cb for cb in self.optional_callbacks if isinstance(cb, EncryptedContentAffinityCheck)), None + ) + if existing is not None: + existing.ctx = self._ctx # pyright: ignore[reportAttributeAccessIssue] # the core's RoutingContext serves registry() + existing.enable_global_affinity = existing.enable_global_affinity or enable_global_affinity + existing.model_group_affinity_config = self.model_group_affinity_config or {} + check: EncryptedContentAffinityCheck = existing # rebind-ok: the check to move + else: + check = EncryptedContentAffinityCheck( # rebind-ok: the check to move + ctx=self._ctx, # pyright: ignore[reportArgumentType] # see above + enable_global_affinity=enable_global_affinity, + model_group_affinity_config=self.model_group_affinity_config, + ) + self._own(check) + _move_before_deployment_affinity(self.optional_callbacks, check) + _move_before_deployment_affinity(_callbacks(self._host), check) + + def add(self, checks: Sequence[object] | None) -> None: + """``add_optional_pre_call_checks``.""" + if checks is None: + return + self._add_affinity(checks) + self._add_encrypted_content_affinity("encrypted_content_affinity" in checks) + for name in checks: + if name in _AFFINITY_CHECKS: + continue + callback: CustomLogger | None = None + if name == "prompt_caching": + callback = PromptCachingDeploymentCheck( + cache=self.prompt_caching_pin_cache, is_priority_group=self._is_priority_group + ) + elif name == "router_budget_limiting": + if self.budget_limiter() is not None: + continue + callback = RouterBudgetLimiting( + dual_cache=self._cache, + provider_budget_config=self.provider_budget_config, # pyright: ignore[reportArgumentType] # the argument as passed + model_list=self._hosted._core_model_list, # pyright: ignore[reportPrivateUsage, reportArgumentType] # the live model_list + ) + self.router_budget_logger = callback + elif name == "enforce_model_rate_limits": + callback = ModelRateLimitingCheck(dual_cache=self._cache) + if callback is None: + continue + if self.optional_callbacks is not None and any( + isinstance(existing, type(callback)) for existing in self.optional_callbacks + ): + continue + self._own(callback) + + def set(self, checks: object) -> None: + """``set_optional_pre_call_checks``: drop the toggleable checks the list leaves out, then add it.""" + if checks is None: + return + listed: Final[tuple[object, ...]] = tuple(checks) if isinstance(checks, list | tuple) else () # pyright: ignore[reportUnknownArgumentType, reportUnknownVariableType] # names as given + requested: Final = frozenset(listed) + for name, callback_cls in _RUNTIME_TOGGLEABLE.items(): + if name not in requested: + self._remove_of_type(callback_cls) + self.add(listed) + + def _remove_of_type(self, callback_cls: type[CustomLogger]) -> None: + """``_remove_optional_callbacks_of_type``: kept on the host while any other live router of + the process has a check of that type.""" + if self.optional_callbacks is None or not any(type(cb) is callback_cls for cb in self.optional_callbacks): + return + self.optional_callbacks = [cb for cb in self.optional_callbacks if type(cb) is not callback_cls] + others: Final = tuple(owner for owner in live_check_owners if id(owner) != id(self._owner)) + if any(any(type(cb) is callback_cls for cb in (owner.optional_callbacks or ())) for owner in others): + return + callbacks: Final = _callbacks(self._host) + for cb in tuple(callbacks): + if type(cb) is callback_cls: + self._host.callbacks.remove_callback_from_list_by_object(callbacks, cb, require_self=False) # pyright: ignore[reportUnknownMemberType] # the manager's untyped helper + + # -- budgets -------------------------------------------------------------------------------- + + def budget_limiter(self) -> RouterBudgetLimiting | None: + """``_core_get_router_deployment_budget_limiter``: exact type, so a proxy subclass is not taken.""" + if self.router_budget_logger is not None: + return self.router_budget_logger + for cb in self.optional_callbacks or (): + if isinstance(cb, RouterBudgetLimiting) and type(cb) is RouterBudgetLimiting: + self.router_budget_logger = cb + return cb + return None + + def sync_deployment_budget(self, deployment: "Deployment") -> None: + """``_sync_deployment_budget_config``, after a deployment is added.""" + model_id: Final = deployment.model_info.id + if model_id is None: + return + limiter: RouterBudgetLimiting | None = self.budget_limiter() # rebind-ok: built when first needed + params: Final = deployment.litellm_params + if params.max_budget is None or params.budget_duration is None: + if limiter is not None: + limiter.unregister_deployment_budget(model_id=model_id) + return + if limiter is None: + self.add(["router_budget_limiting"]) + limiter = self.budget_limiter() # rebind-ok: the one just built + if limiter is not None: + limiter.register_deployment_budget(deployment=deployment.to_json(exclude_none=True)) # pyright: ignore[reportUnknownMemberType] # pydantic's untyped dump + + def unregister_deployment_budget(self, model_id: str) -> None: + limiter: Final = self.budget_limiter() + if limiter is not None: + limiter.unregister_deployment_budget(model_id=model_id) + + # -- the routing callbacks ------------------------------------------------------------------ + + def loggers(self) -> tuple[CustomLogger, ...]: + """``_optional_loggers``.""" + return tuple(cb for cb in self.optional_callbacks or () if isinstance(cb, CustomLogger)) + + def _policies_not_set_globally(self) -> tuple[CustomLogger, ...]: + keys: Final = self._host.callbacks.get_custom_logger_key + global_keys: Final = frozenset(keys(cb) for cb in _callbacks(self._host) if isinstance(cb, CustomLogger)) + return tuple(policy for policy in self._request_scoped_policies if keys(policy) not in global_keys) + + def bind_to_request_logging(self, logging_obj: "Logging") -> None: + """``_core_bind_to_request_logging``'s routing half: the request-scoped selectors replace the + host's same-keyed callbacks for the request, and the policies the host does not run are + added to it. The outcome callbacks are not bound: the Rust core records every attempt's + outcome itself, so the request is noted for ``outcome_callbacks`` instead.""" + self._bound_requests.add(logging_obj) + for selector in self._request_scoped_selectors: + logging_obj.replace_global_callback(selector) + for policy in self._policies_not_set_globally(): + logging_obj.add_dynamic_callback(policy) + + def outcome_callbacks( + self, request: Mapping[str, object], *, sync: bool, make_call: bool = True + ) -> Mapping[str, bool]: + """Router-core's ``OutcomeCallbacks`` for ``request``, empty (its default) while the outcome + callbacks are listed. Past that only the request's bound logging object runs them, and + ``_core_bind_to_request_logging`` binds neither ``sync_deployment_callback_on_success`` nor any + success callback a sync call runs. ``make_call``: the attempt runs through ``make_call``.""" + if self._outcome_callbacks_listed: + return {} + bound: Final = request.get("litellm_logging_obj") in self._bound_requests + return {"success": bound and not sync, "failure": bound, "make_call": make_call} + + def routing_callbacks(self) -> Iterable[object]: + """``_routing_callbacks``: the host's callbacks, or after ``observe(request_scoped=True)`` the + host's callbacks with the router's own selectors and policies in place of theirs.""" + if not (self._request_scoped_selectors or self._request_scoped_policies): + return tuple(_callbacks(self._host)) + keys: Final = self._host.callbacks.get_custom_logger_key + replaced: Final = frozenset(map(keys, self._request_scoped_selectors)) + return ( + *self._host.callbacks.without_custom_logger_keys(_callbacks(self._host), replaced), # pyright: ignore[reportArgumentType] # the process list holds any callback + *self._request_scoped_selectors, + *self._policies_not_set_globally(), + ) + + async def filter_deployments( + self, + model: str, + deployments: list[dict[str, object]], # mutable-ok: CustomLogger deployment-list contract + messages: object, + request: Mapping[str, object], + ) -> list[object]: # mutable-ok: as the filters return it + """``async_callback_filter_deployments``: each routing callback narrows the deployments in + turn; a filter's error is raised for the Rust core to decide on.""" + remaining: list[object] = list(deployments) # mutable-ok: filter contract # rebind-ok: narrowed + base: Final[object] = CustomLogger.async_filter_deployments # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # untyped deployment dicts + request_kwargs: Final = dict(request) + for callback in tuple(self.routing_callbacks()): + # The base filter returns its input unchanged: only overriding filters are run. + if not isinstance(callback, CustomLogger) or type(callback).async_filter_deployments is base: # pyright: ignore[reportUnknownMemberType] # see above + continue + remaining = await callback.async_filter_deployments( # pyright: ignore[reportUnknownMemberType, reportAssignmentType, reportUnknownVariableType] # see above + model=model, + healthy_deployments=remaining, + messages=messages, # pyright: ignore[reportArgumentType] # the request's messages, as given + request_kwargs=request_kwargs, + parent_otel_span=None, + ) + return remaining + + # -- release -------------------------------------------------------------------------------- + + def serve_through_request_logging(self, selectors: Sequence[CustomLogger], dropped: Sequence[object]) -> None: + """``_core_serve_through_request_logging``: keep running ``selectors`` (and request-scoped + adaptive hooks) and the optional checks, but take everything off the host lists.""" + from litellm.router_strategy.adaptive_router.hooks import AdaptiveRouterPostCallHook + + adaptive: Final = tuple( + AdaptiveRouterPostCallHook(adaptive_router=tagged.strategy) # pyright: ignore[reportArgumentType] # an adaptive router + for tagged in chain.from_iterable(self._hosted._core_adaptive_routers.values()) # pyright: ignore[reportPrivateUsage] # the host registry's live registry + ) + self._request_scoped_selectors = (*selectors, *adaptive) + self._request_scoped_policies = (*self.loggers(), *self.slack_alerting_loggers) + self.release(dropped) + + def own_adaptive_hooks(self) -> tuple[CustomLogger, ...]: + """``_adaptive_router_hooks``: the host's adaptive post-call hooks of this router's routers.""" + from litellm.router_strategy.adaptive_router.hooks import AdaptiveRouterPostCallHook + + own: Final = frozenset( + id(tagged.strategy) + for tagged in chain.from_iterable(self._hosted._core_adaptive_routers.values()) # pyright: ignore[reportPrivateUsage] # see above + ) + return tuple( + hook + for hook in self._host.callbacks.get_custom_loggers_for_type(AdaptiveRouterPostCallHook) + if isinstance(hook, AdaptiveRouterPostCallHook) and id(hook.adaptive_router) in own + ) + + def retire_state(self, selectors: Sequence[object]) -> None: + """``retire_routing_state``: stop the background work of the selectors and the budget limiter.""" + for strategy in (*selectors, *self.loggers()): + if isinstance(strategy, BaseRoutingStrategy | RouterBudgetLimiting): + strategy.retire() + + def release(self, dropped: Sequence[object]) -> None: + """``_release_global_callbacks``: drop ``dropped``, the optional checks and the adaptive hooks + from the host lists, then hand each vacated check to a surviving router's same-keyed one.""" + self._outcome_callbacks_listed = False + with routers_holding_global_callbacks_lock: + routers_holding_global_callbacks.discard(self._owner) + adaptive: Final = self.own_adaptive_hooks() + slack: Final = self.slack_alerting_loggers + vacated: Final = self._host.callbacks.drop_callbacks( + (*dropped, *(self.optional_callbacks or ()), *slack, *adaptive), method_owners=(self._owner, *slack) + ) + with routers_holding_global_callbacks_lock: + survivors: Final = tuple(routers_holding_global_callbacks) + candidates: Final = chain.from_iterable(router._global_callback_candidates() for router in survivors) # pyright: ignore[reportPrivateUsage] # the holder protocol + for candidate in self._host.callbacks.with_custom_logger_keys(candidates, vacated): + register_router_selector(self._host, candidate) + adaptive_keys: Final = frozenset(map(self._host.callbacks.get_custom_logger_key, adaptive)) + survivor: Final = next((router for router in survivors if router._core_adaptive_routers), None) # pyright: ignore[reportPrivateUsage] # see above + if survivor is not None and vacated & adaptive_keys: + survivor._sync_adaptive_router_hooks() # pyright: ignore[reportPrivateUsage] # see above + + +_ENCRYPTED_PIN: Final = "_encrypted_content_affinity_pinned" + + +def _request_with_failed_ids(request: Mapping[str, object], step: Mapping[str, object]) -> Mapping[str, object]: + """The request as the filters read it in the Python router: the Rust walk holds what the Python + one keeps in the attempt's kwargs, ``_excluded_deployment_ids`` from a weighted failover hop, + ``_retry_skipped_deployment_ids`` from the retry loop (``deployment_ids_failed_in_request``) and + ``_target_order`` from an order fallback.""" + excluded: Final = tuple(str(id) for id in _ids_of(step.get("excluded_ids"))) + skipped: Final = tuple(str(id) for id in _ids_of(step.get("skipped_ids"))) + target_order: Final = step.get("target_order") + if not excluded and not skipped and target_order is None: + return request + return { + **request, + **({"_excluded_deployment_ids": list(excluded)} if excluded else {}), + **({"_retry_skipped_deployment_ids": skipped} if skipped else {}), + **({"_target_order": target_order} if target_order is not None else {}), + } + + +def _ids_of(value: object) -> Sequence[object]: + return value if isinstance(value, list | tuple) else () # pyright: ignore[reportUnknownVariableType] # the step's id list + + +def filtered_ids(remaining: Iterable[object], candidates: Sequence[str]) -> list[str]: # mutable-ok: a JSON list + """The ids of the deployments the filters left, in their order, among the candidates.""" + ids: Final[list[str]] = [] # mutable-ok: built here + for deployment in remaining: + found = (as_str_mapping((as_str_mapping(deployment) or {}).get("model_info")) or {}).get("id") + if isinstance(found, str) and found in candidates and found not in ids: + ids.append(found) + return ids + + +class RustOptionalChecks: + """``RustCore`` members for its optional pre-call checks and routing callbacks.""" + + # RustCore sets these as Final attributes in its constructor. + @property + def _opt(self) -> OptionalChecks: + checks: Final[OptionalChecks] = self.__dict__["_checks"] # pyright: ignore[reportAny] # RustCore's own attribute + return checks + + @property + def _sel(self) -> "StrategySelectors": + selectors: Final[StrategySelectors] = self.__dict__["_selectors"] # pyright: ignore[reportAny] # same + return selectors + + @property + def _reg(self) -> "HostRegistry": + hosted: Final[HostRegistry] = self.__dict__["_hosted"] # pyright: ignore[reportAny] # same + return hosted + + @property + def optional_callbacks(self) -> "list[object] | None": # mutable-ok: the router's live list + return self._opt.optional_callbacks + + @property + def router_budget_logger(self) -> RouterBudgetLimiting | None: + return self._opt.router_budget_logger + + @property + def deployment_affinity_ttl_seconds(self) -> object: + return self._opt.deployment_affinity_ttl_seconds + + @property + def session_affinity_repin_on_failover(self) -> object: + return self._opt.session_affinity_repin_on_failover + + @property + def model_group_affinity_config(self) -> "dict[str, list[str]] | None": # mutable-ok: the argument as passed + return self._opt.model_group_affinity_config + + def add_optional_pre_call_checks(self, optional_pre_call_checks: "Sequence[object] | None") -> None: + self._opt.add(optional_pre_call_checks) + + def apply_default_settings(self) -> None: + """Add the (empty) default checks; an enabled continuation registers the prefill check.""" + from litellm.router_rust.invoke.streaming import register_continuation_prefill_check + + self._opt.add([]) + if getattr(self, "enable_mid_stream_fallback_continuation", False): + register_continuation_prefill_check(self._opt._host) # pyright: ignore[reportPrivateUsage] # the checks' host + + # The members another router's retire reads (`global_callback_holders`). + + def _global_callback_candidates(self) -> tuple[CustomLogger, ...]: + return (*self._sel.callback_selectors(), *self._opt.loggers(), *self._opt.slack_alerting_loggers) + + @property + def _core_adaptive_routers(self) -> Mapping[str, object]: + return self._reg._core_adaptive_routers # pyright: ignore[reportPrivateUsage] # the host registry's live registry + + def _sync_adaptive_router_hooks(self) -> None: + strategies: Final = self._reg.strategies + if strategies is not None: + strategies._sync_adaptive_router_hooks() # pyright: ignore[reportPrivateUsage] # the strategies' own hook sync + + def _join_callback_holders(self) -> None: + with routers_holding_global_callbacks_lock: + routers_holding_global_callbacks.add(self) + live_check_owners.add(self) + + def outcome_callbacks( + self, request: Mapping[str, object], *, sync: bool, make_call: bool = True + ) -> Mapping[str, bool]: + return self._opt.outcome_callbacks(request, sync=sync, make_call=make_call) + + def _serve_through_request_logging(self) -> None: + selectors: Final = self._sel + self._opt.serve_through_request_logging( + selectors.callback_selectors(), (*selectors.callback_selectors(), *selectors.override_selectors()) + ) + + def _retire_callbacks(self) -> None: + """``_core_discard``'s callback half: retire the routing state, release the callbacks. The + selectors stay: a retired router still picks with them.""" + live_check_owners.discard(self) + selectors: Final = (*self._sel.callback_selectors(), *self._sel.override_selectors()) + self._opt.retire_state(selectors) + self._opt.release(selectors) + + async def _answer_callback_filters( + self, step: Mapping[str, object], request: Mapping[str, object], messages: object + ) -> tuple[object, BaseException | None]: + """A ``callback_filters`` step: the remaining ids, or a filter's error as an attempt + failure with the error itself, which the caller keeps to raise.""" + from litellm.router_rust.core import attempt_failure + + candidates: Final = [str(id) for id in step.get("candidates") or ()] # pyright: ignore[reportGeneralTypeIssues, reportUnknownVariableType, reportUnknownArgumentType] # the step's id list + records: Final = self._records_of(candidates) # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType, reportUnknownVariableType] # RustCore's deployment dicts + narrowed: Final = _request_with_failed_ids(request, step) + try: + remaining: Final = await self._opt.filter_deployments( + str(step.get("model_group")), + records, # pyright: ignore[reportUnknownArgumentType] # see above + messages, + narrowed, + ) + except Exception as error: # noqa: BLE001 # handed to the Rust core as the try's failure + return attempt_failure(error), error + # A filter's pin lands on the request kwargs the pick goes on to read. + if narrowed is not request and narrowed.get(_ENCRYPTED_PIN) and isinstance(request, dict): + request[_ENCRYPTED_PIN] = True # rebind-ok: the request dict the pick goes on to read + return filtered_ids(remaining, candidates), None # pyright: ignore[reportUnknownArgumentType] # see above + + +__all__ = [ + "OptionalChecks", + "RustOptionalChecks", + "filtered_ids", + "register_router_selector", +] diff --git a/litellm/router_rust/steps/plugins.py b/litellm/router_rust/steps/plugins.py new file mode 100644 index 00000000000..4af73313838 --- /dev/null +++ b/litellm/router_rust/steps/plugins.py @@ -0,0 +1,87 @@ +""" +Host side of the Rust core's routing-plugin pipeline (``Router(plugins=[...])``). + +The Rust core decides where the pipeline applies (only the async pick runs it; the sync pick +refuses a router with plugins) and which deployments the plugins' candidate models keep +(``router-core/src/routing_plugins.rs``). The plugins themselves are live Python objects, so this +module runs them on a ``routing_plugins`` select step, the way the Python router core's +``_run_routing_plugins`` does, and reports the candidate models left on the request. +""" + +from collections.abc import Mapping, Sequence +from typing import Final, Protocol + +from litellm.litellm_core_utils.core_helpers import as_str_mapping, get_metadata_variable_name_from_kwargs +from litellm.litellm_core_utils.routing_common_utils import resolve_model_group_alias +from litellm.types.router import RoutingContext, RoutingPlugin + +SYNC_PATH_MESSAGE: Final = ( + "Router(plugins=[...]) is configured, but this call resolved to the synchronous " + "deployment-selection path, which never runs the routing-plugin pipeline. This " + "happens for sync Router methods (e.g. Router.completion()) and for async calls " + "with a routing_strategy that has no async-native selector (e.g. legacy " + "'usage-based-routing', v1). Silently skipping " + "configured plugins would let a policy plugin (e.g. a deny-all rule) be bypassed. " + "Use an async Router method with a supported routing_strategy (simple-shuffle, " + "usage-based-routing-v2, cost-based-routing, latency-based-routing, least-busy), " + "or remove `plugins` from the Router config." +) +_CANDIDATES_KEY: Final = "_routing_plugin_candidate_models" + + +class PluginRegistry(Protocol): + def _core_get_model_list( + self, model_name: str | None = None, team_id: str | None = None + ) -> Sequence[Mapping[str, object]] | None: ... + + +def _resolved_litellm_models( + registry: PluginRegistry, model: str +) -> list[str]: # mutable-ok: the plugins' candidate list + """``_core_resolved_litellm_models``: the provider models a call to ``model`` is served by.""" + return [ + litellm_model + for deployment in registry._core_get_model_list(model_name=model) or () # pyright: ignore[reportPrivateUsage] # the host registry's listing + if isinstance(litellm_model := (as_str_mapping(deployment.get("litellm_params")) or {}).get("model"), str) + and litellm_model + ] + + +def candidate_models(request: Mapping[str, object]) -> Mapping[str, object]: + """The answer to a ``routing_plugins`` step: the candidate models the plugins left on the + request, ``None`` when none narrowed it.""" + metadata: Final = as_str_mapping(request.get(get_metadata_variable_name_from_kwargs(dict(request)))) + return {"models": metadata.get(_CANDIDATES_KEY) if metadata is not None else None} + + +async def run_plugins( + plugins: Sequence[RoutingPlugin], + registry: PluginRegistry, + model_group_alias: Mapping[str, object], + model: str, + request: dict[str, object], # mutable-ok: the plugins stamp their outcome on the caller's request + messages: object, +) -> None: + """``_run_routing_plugins``: run ``plugins`` in order over ``model``'s candidate models, then + stamp their signals (and a narrowed candidate list) on the request's metadata.""" + from litellm.litellm_core_utils.prompt_templates.factory import resolve_structured_messages + + registered: Final = resolve_model_group_alias(model_group_alias, model) or model + models: Final = _resolved_litellm_models(registry, registered) + metadata_key: Final = get_metadata_variable_name_from_kwargs(request) + metadata: Final = request.setdefault(metadata_key, {}) + raw_messages: Final[object] = messages or list[object]() + context = RoutingContext( # rebind-ok: each plugin returns the context the next one reads + raw_messages=raw_messages, # pyright: ignore[reportArgumentType] # the request's messages + structured_messages=resolve_structured_messages(messages=messages, request_kwargs=request) or [], # pyright: ignore[reportArgumentType] # the request's messages + candidate_models=list(models), + metadata=metadata, # pyright: ignore[reportArgumentType] # the request's metadata dict + ) + for plugin in plugins: + context = await plugin.run(context) + metadata["routing_plugin_signals"] = context.signals # pyright: ignore[reportIndexIssue] # the request's metadata dict + if len(context.candidate_models) < len(models): + metadata[_CANDIDATES_KEY] = context.candidate_models # pyright: ignore[reportIndexIssue] # see above + + +__all__ = ["SYNC_PATH_MESSAGE", "PluginRegistry", "candidate_models", "run_plugins"] diff --git a/litellm/router_rust/steps/precall.py b/litellm/router_rust/steps/precall.py new file mode 100644 index 00000000000..156c7b5e20f --- /dev/null +++ b/litellm/router_rust/steps/precall.py @@ -0,0 +1,494 @@ +""" +Host-side facts for the Rust core's ``enable_pre_call_checks`` filter. + +The Rust core decides which deployments the pre-call checks drop and which error a group with +nothing left raises (``router-core/src/precall.rs``). What needs live Python objects is answered +here, on a ``pre_call`` select step: the prompt's token count (messages, Responses input and +instructions, tools and an Anthropic ``system`` block), each deployment's context window from +its router model info, and which requested params each deployment takes. Ported from the Python +router core's ``_pre_call_checks`` helpers; it never reaches a Python router core. + +``pre_call_checks`` is the one decision made here: ``RoutingContext.pre_call_checks`` hands over +deployment records rather than a step, and those need not be in the Rust registry. +""" + +from collections.abc import Callable, Mapping, Sequence +from functools import partial +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, Protocol + +from litellm._logging import verbose_router_logger +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.deployment_pricing import deployment_backend_models +from litellm.litellm_core_utils.get_llm_provider_logic import declared_authenticating_provider +from litellm.litellm_core_utils.token_counter import ( + offload_token_count, + served_openai_models, + single_encoding_openai_model, + split_embedding_input_tokens, +) +from litellm.router_python_host import python_host +from litellm.router_strategy.complexity_router.context_compaction import compaction_pending +from litellm.types.router import LiteLLM_Params + +if TYPE_CHECKING: + from litellm.router_python_host import PythonHost + from litellm.types.utils import LlmProviders + +# The chat params a deployment must take when the request sends them (`_PRE_CALL_CHECK_FILTERED_PARAMS`). +_FILTERED_PARAMS: Final = frozenset({"response_format"}) + + +class PreCallRegistry(Protocol): + """The host registry reads the facts need.""" + + def _core_get_model_info(self, id: str) -> Mapping[str, object] | None: ... # the registry's name + + def _core_deployments_named(self, model_name: str) -> Sequence[Mapping[str, object]] | None: ... + + def _core_get_router_model_info( + self, deployment: Mapping[str, object], received_model_name: str + ) -> Mapping[str, object]: ... + + +def count_tokens( + host: "PythonHost", + messages: object, + input: object, # the request field's name + request_kwargs: Mapping[str, object] | None, + tokenizer_model: str, + deployments: Sequence[Mapping[str, object]] = (), +) -> int: + """``_count_pre_call_check_tokens``: messages, or Responses input normalized to messages, plus + the tools and Anthropic ``system`` block the message list never carries. Embedding media an + item of ``deployments`` reads as media is left out of the input: it never counts as text.""" + from litellm.llms.anthropic.messages.native.utils import anthropic_system_to_openai_message + + extras: Final[Mapping[str, object]] = request_kwargs if request_kwargs is not None else MappingProxyType({}) + raw_instructions: Final = extras.get("instructions") + instructions: Final = raw_instructions if isinstance(raw_instructions, str) else None + raw_tools: Final = extras.get("tools") + tools: Final = raw_tools if _is_list(raw_tools) and raw_tools else None + system_message: Final = anthropic_system_to_openai_message(extras.get("system")) + counter: Final = host.invoke("token_counter") # pyright: ignore[reportUnknownMemberType] # the host's overloads name litellm's untyped returns + if messages is not None: + counted_messages: Final = (system_message, *_items(messages)) if system_message is not None else messages + return counter(model=tokenizer_model, messages=counted_messages, tools=tools) + if input is not None: + from litellm.responses.litellm_completion_transformation.transformation import ( + LiteLLMCompletionResponsesConfig, + ) + + text_input, _ = split_embedding_input_tokens(input, partial(deployment_backend_models, deployments)) + input_messages: Final = LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages( # pyright: ignore[reportUnknownMemberType] # its input type is untyped + input=text_input, # pyright: ignore[reportArgumentType] # str | list, as the request carries it + responses_api_request={"instructions": instructions} if instructions is not None else {}, + only_since_compaction=True, + ) + return counter(model=tokenizer_model, messages=input_messages, tools=tools) + raise ValueError("Either messages or input must be provided to count tokens") + + +def _max_input_tokens(registry: PreCallRegistry, model: str, deployment: Mapping[str, object]) -> int | None: + """``_deployment_max_input_tokens``: the declared context window, or None when there is none or + the deployment cannot be resolved.""" + try: + model_info: Final = registry._core_get_router_model_info( # pyright: ignore[reportPrivateUsage] # the host registry's lookup + deployment=deployment, received_model_name=model + ) + except Exception as e: # noqa: BLE001 # best-effort: an unmappable deployment must not hide the others + verbose_router_logger.debug("litellm.router.py::_deployment_max_input_tokens: skipping deployment. Got - %s", e) + return None + max_input_tokens: Final = model_info.get("max_input_tokens") + return max_input_tokens if isinstance(max_input_tokens, int) else None + + +def _items(value: object) -> tuple[object, ...]: + """The items of a list, tuple or set; nothing for any other value.""" + return tuple(value) if isinstance(value, list | tuple | set | frozenset) else () # pyright: ignore[reportUnknownArgumentType, reportUnknownVariableType] # the items are read as objects + + +def _is_list(value: object) -> bool: + return isinstance(value, list) + + +def _declared_param_allowlist(params: Mapping[str, object]) -> frozenset[str]: + declared: Final = params.get("allowed_openai_params") + return frozenset(entry for entry in _items(declared) if isinstance(entry, str)) + + +def _capability_model_and_provider(deployment_params: Mapping[str, object], group: str) -> tuple[str, str]: + model_label: Final = str(deployment_params.get("model") or group) + custom_llm_provider: Final = deployment_params.get("custom_llm_provider") + authenticating_provider: Final = declared_authenticating_provider( + model_label, + custom_llm_provider, # pyright: ignore[reportArgumentType] # passed as configured, as the Python core does + ) + if authenticating_provider is not None: + return model_label.removeprefix(f"{authenticating_provider}/"), authenticating_provider + model, provider, _, _ = python_host.invoke("get_llm_provider")( # pyright: ignore[reportUnknownMemberType] # see count_tokens + model=model_label, + custom_llm_provider=custom_llm_provider, + litellm_params=LiteLLM_Params.model_validate(dict(deployment_params)), + ) + return model, provider + + +def _supports_param(deployment: Mapping[str, object], group: str, param: str) -> bool: + """``_deployment_supports_param``.""" + deployment_params: Final = as_str_mapping(deployment.get("litellm_params")) + if not deployment_params: + return True + deployment_model_info: Final = as_str_mapping(deployment.get("model_info")) + base_model: Final = ( + deployment_model_info.get("base_model") if deployment_model_info else None + ) or deployment_params.get("base_model") + try: + model, custom_llm_provider = _capability_model_and_provider(deployment_params, group) + supported: Final = python_host.invoke("get_supported_openai_params")( # pyright: ignore[reportUnknownMemberType] # see count_tokens + model=model, + custom_llm_provider=custom_llm_provider, + base_model=base_model if isinstance(base_model, str) else None, + ) + except Exception as e: # noqa: BLE001 # best-effort filter: an unresolvable provider must not narrow the request + verbose_router_logger.debug( + "litellm.router.py::_deployment_supports_param: keeping %s for model=%s. Got - %s", param, group, e + ) + return True + return supported is None or param in supported + + +def _lacks_params(deployment: Mapping[str, object], group: str, params: frozenset[str]) -> bool: + return any(not _supports_param(deployment, group, param) for param in params) + + +def _rejects_params( + deployment: Mapping[str, object], group: str, params: frozenset[str], request_kwargs: Mapping[str, object] +) -> bool: + """``_deployment_rejects_params``: lacks a param neither the deployment nor the request drops or allows.""" + call_settings: Final[Mapping[str, object]] = { + **(as_str_mapping(deployment.get("litellm_params")) or {}), + **request_kwargs, + } + if call_settings.get("drop_params") is True: + return False + dropped: Final = call_settings.get("additional_drop_params") + dropped_names: Final = frozenset( + entry for entry in (_items(dropped) if _is_list(dropped) else ()) if isinstance(entry, str) + ) + return _lacks_params(deployment, group, params - _declared_param_allowlist(call_settings) - dropped_names) + + +def _requested_params(request_kwargs: Mapping[str, object]) -> frozenset[str]: + """``_pre_call_check_requested_chat_params``.""" + from litellm import utils as litellm_utils + + return _filtered_params( + litellm_utils.get_non_default_params(passed_params=dict(request_kwargs)) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # an untyped helper + ) + + +def _filtered_params(requested: Mapping[object, object]) -> frozenset[str]: + return frozenset( + param + for param, value in requested.items() + if isinstance(param, str) and param in _FILTERED_PARAMS and not isinstance(value, str) + ) + + +class PreCallFacts: + """The facts of one ``pre_call`` step.""" + + def __init__( + self, + host: "PythonHost", + registry: PreCallRegistry, + step: Mapping[str, object], + records: Callable[[str], Mapping[str, object]], + request: Mapping[str, object] | None, + messages: object, + input: object, # the request field's name + ) -> None: + self._host: Final = host + self._registry: Final = registry + self._model: Final = str(step.get("model_group")) + self._name: Final = str(step.get("model")) + self._candidates: Final = [str(id) for id in _items(step.get("candidates"))] + self._pool: Final = [str(id) for id in _items(step.get("pool"))] + self._records: Final = records + self._request: Final = request + self._messages: Final = messages + self._input: Final = input + self._has_input: Final = messages is not None or input is not None + self._windows: Final = {id: _max_input_tokens(registry, self._model, records(id)) for id in self._candidates} + + def _record(self, id: str) -> Mapping[str, object]: # a deployment id + return self._records(id) + + def _needs_count(self) -> bool: + return self._has_input and any(limit is not None for limit in self._windows.values()) + + def _tokenizer_model(self) -> str: + named: Final = self._registry._core_deployments_named(self._model) or () # pyright: ignore[reportPrivateUsage] # the host registry's index + return ( + single_encoding_openai_model( + served_openai_models(named) or served_openai_models(self._record(id) for id in self._candidates) + ) + or "" + ) + + def _candidate_records(self) -> Sequence[Mapping[str, object]]: + return tuple(self._record(id) for id in self._candidates) + + def _count(self) -> int | None: + try: + return count_tokens( + self._host, + self._messages, + self._input, + self._request, + self._tokenizer_model(), + self._candidate_records(), + ) + except Exception as e: # noqa: BLE001 # best-effort: an uncountable prompt must not fail the request + verbose_router_logger.error( + "litellm.router.py::_acount_pre_call_check_tokens: failed to count tokens. Got - %s", e + ) + return None + + async def _count_async(self) -> int | None: + try: + return await offload_token_count(count_tokens)( + self._host, + self._messages, + self._input, + self._request, + self._tokenizer_model(), + self._candidate_records(), + ) + except Exception as e: # noqa: BLE001 # best-effort: an uncountable prompt must not fail the request + verbose_router_logger.error( + "litellm.router.py::_acount_pre_call_check_tokens: failed to count tokens. Got - %s", e + ) + return None + + def _answer(self, input_tokens: int | None) -> Mapping[str, object]: + if not self._has_input: + return {"has_input": False} + request: Final[Mapping[str, object]] = self._request if self._request is not None else {} + params: Final = ( + _requested_params(request) + if self._request is not None and self._host.dynamic().drop_params is False + else frozenset[str]() + ) + deployments: Final[dict[str, dict[str, object]]] = {} # mutable-ok: built here, then returned + for id in dict.fromkeys([*self._candidates, *self._pool]): + record = self._record(id) + deployments[id] = { + "max_input_tokens": self._windows.get(id), + "lacks_params": bool(params) and id in self._candidates and _lacks_params(record, self._model, params), + "rejects_params": bool(params) and _rejects_params(record, self._model, params, request), + } + allowed_region: Final = request.get("allowed_model_region") + return { + "has_input": True, + "countable": not compaction_pending(self._request), + "input_tokens": input_tokens, + "allowed_model_region": allowed_region, + "requested_params": sorted(params), + "deployments": deployments, + } + + def answer(self) -> Mapping[str, object]: + """The facts on the sync path: the prompt is counted inline.""" + return self._answer(self._count() if self._needs_count() else None) + + async def answer_async(self) -> Mapping[str, object]: + """The facts on the async path: the prompt is counted off the event loop.""" + return self._answer(await self._count_async() if self._needs_count() else None) + + +def pre_call_checks( + host: "PythonHost", + registry: PreCallRegistry, + model: str, + deployments: Sequence[Mapping[str, object]], + messages: object, + input: object, # the request field's name + request_kwargs: Mapping[str, object] | None, + input_token_count: int | None = None, + skip_inline_token_count: bool = False, + request_deployments: Sequence[Mapping[str, object]] | None = None, +) -> Sequence[Mapping[str, object]]: + """``_pre_call_checks`` over the given deployments, as ``router-core/src/precall.rs`` decides it.""" + import litellm.exceptions as litellm_exceptions + + pool: Final = ( + tuple(request_deployments) + if request_deployments is not None + else (tuple(registry._core_deployments_named(model) or ()) or tuple(deployments)) # pyright: ignore[reportPrivateUsage] # the host registry's index + ) + candidates: Final = {f"candidate-{index}": record for index, record in enumerate(deployments)} + group: Final = {f"pool-{index}": record for index, record in enumerate(pool)} + records: Final = {**candidates, **group} + step: Final = {"model_group": model, "model": model, "candidates": list(candidates), "pool": list(group)} + facts: Final = PreCallFacts(host, registry, step, records.__getitem__, request_kwargs, messages, input) + counted: Final = ( + input_token_count + if input_token_count is not None or skip_inline_token_count or not facts._needs_count() # pyright: ignore[reportPrivateUsage] # this module's own class + else facts._count() # pyright: ignore[reportPrivateUsage] # see above + ) + answer: Final = facts._answer(counted) # pyright: ignore[reportPrivateUsage] # see above + rows: Final = as_str_mapping(answer.get("deployments")) or {} + allowed_region: Final = answer.get("allowed_model_region") + + def row(id: str) -> Mapping[str, object]: # a candidate or pool key + return as_str_mapping(rows.get(id)) or {} + + def over_window(id: str) -> bool: + limit: Final = row(id).get("max_input_tokens") + return isinstance(limit, int) and answer.get("countable") is True and counted is not None and counted > limit + + def out_of_region(id: str) -> bool: + params: Final = as_str_mapping(records[id].get("litellm_params")) or {} + return allowed_region is not None and params.get("region_name") != allowed_region + + too_small: Final = tuple(id for id in candidates if over_window(id)) + invalid: Final = frozenset(too_small) | frozenset(id for id in candidates if out_of_region(id)) + param_candidates: Final = tuple(id for id in candidates if id not in invalid) + lacking: Final = tuple(row(id).get("lacks_params") is True for id in param_candidates) + rejecting: Final = tuple(row(id).get("rejects_params") is True for id in param_candidates) + failing: Final = rejecting if lacking and all(lacking) else lacking + excluded: Final = invalid | frozenset(id for id, fails in zip(param_candidates, failing, strict=True) if fails) + if len(excluded) == len(candidates): + requested: Final = [str(param) for param in _items(answer.get("requested_params"))] + if not too_small and group and all(row(id).get("rejects_params") is True for id in group): + raise litellm_exceptions.UnsupportedParamsError( + message=( + f"no deployment of model={model} supports {requested}. " + "To drop these, set `litellm.drop_params=True` or for proxy `litellm_settings: drop_params: true`, " + f"or send allowed_openai_params={requested} to pass them through" + ), + model=model, + ) + if too_small: + detail: Final = "".join( + f"Model={_error_model(records[id])}, Max Input Tokens={row(id).get('max_input_tokens')}, Got={counted}" + for id in too_small + ) + raise litellm_exceptions.ContextWindowExceededError( + message="litellm._pre_call_checks: Context Window exceeded for given call. No models have context " + f"window large enough for this call.\n{detail}", + model=model, + llm_provider="", + ) + return tuple(record for id, record in candidates.items() if id not in excluded) + + +def _error_model(deployment: Mapping[str, object]) -> object: + """The name a context-window error gives a deployment: its base model, else its model.""" + params: Final = as_str_mapping(deployment.get("litellm_params")) or {} + model_info: Final = as_str_mapping(deployment.get("model_info")) or {} + return model_info.get("base_model") or params.get("base_model") or params.get("model") + + +def request_carries_image(messages: object, request: Mapping[str, object]) -> bool: + """``_request_carries_image``: the messages (or the request's own messages or input) hold an image.""" + from litellm.litellm_core_utils.prompt_templates.common_utils import request_contains_image_content + + return request_contains_image_content(messages or request.get("messages") or request.get("input")) + + +def declares_no_vision(deployment: Mapping[str, object], group: str) -> bool: + """``_deployment_declares_no_vision``: ``model_info.supports_vision`` is ``False``, or, when it + is unset, the cost map says the model has vision explicitly disabled.""" + from litellm import utils as litellm_utils + + model_info: Final = as_str_mapping(deployment.get("model_info")) or {} + declared: Final = model_info.get("supports_vision") + if declared is not None: + return declared is False + params: Final = as_str_mapping(deployment.get("litellm_params")) or {} + if not params: + return False + base_model: Final = model_info.get("base_model") or params.get("base_model") + try: + model, custom_llm_provider = _capability_model_and_provider(params, group) + return litellm_utils.is_vision_explicitly_disabled( + base_model if isinstance(base_model, str) else model, custom_llm_provider + ) + except Exception as e: # noqa: BLE001 # best-effort filter: an unresolvable provider must not narrow the request + verbose_router_logger.debug( + "litellm.router.py::_deployment_declares_no_vision: keeping deployment for model=%s. Got - %s", group, e + ) + return False + + +__all__ = [ + "PreCallFacts", + "PreCallRegistry", + "count_tokens", + "declares_no_vision", + "pre_call_checks", + "request_carries_image", +] + + +def _route_capability_resolvers() -> Mapping[str, Callable[[str, "LlmProviders"], object | None]]: + """``_ROUTE_CAPABILITY_RESOLVERS``: the calls only some providers serve, by handler name.""" + from litellm.utils import ProviderConfigManager + + return { + "adecisions": ProviderConfigManager.get_provider_decisions_config, # pyright: ignore[reportUnknownMemberType] # litellm's config lookup + "decisions": ProviderConfigManager.get_provider_decisions_config, # pyright: ignore[reportUnknownMemberType] # see above + } + + +# ``_DECISIONS_MEDIA_CALL_TYPES``: the calls whose audio or videos some deployments refuse. +DECISIONS_MEDIA_CALL_TYPES: Final = frozenset({"adecisions", "decisions", "asystemone", "systemone"}) + + +def serves_route_capability(handler: str | None) -> bool: + """Whether only some providers serve the call ``handler`` names.""" + return handler is not None and handler in _route_capability_resolvers() + + +def cannot_serve_route(deployment: Mapping[str, object], group: str, handler: str) -> bool: + """Not ``_deployment_serves_route``: the deployment's provider has no config for the call.""" + from litellm.types.utils import LlmProviders + + resolver: Final = _route_capability_resolvers().get(handler) + params: Final = as_str_mapping(deployment.get("litellm_params")) + if resolver is None or params is None: + return False + try: + model, provider_name = _capability_model_and_provider(params, group) + provider: Final = next((member for member in LlmProviders if member.value == provider_name), None) + return provider is None or resolver(model, provider) is None + except Exception as e: # noqa: BLE001 # best-effort capability filter, as the Python core keeps it + verbose_router_logger.debug( + "litellm.router.py::_deployment_serves_route: keeping deployment for model=%s. Got - %s", group, e + ) + return False + + +def refuses_decisions_media( + deployment: Mapping[str, object], group: str, sent_kwargs: Mapping[str, object], *, audio: bool, videos: bool +) -> bool: + """``_decisions_deployment_refuses_media``.""" + from litellm.decisions.call import deployment_refuses_media + + model_info: Final = as_str_mapping(deployment.get("model_info")) or {} + params: Final = as_str_mapping(deployment.get("litellm_params")) or {} + try: + model, custom_llm_provider = _capability_model_and_provider(params, group) + return deployment_refuses_media( + model, custom_llm_provider, model_info, {**params, **sent_kwargs}, audio=audio, videos=videos + ) + except Exception as e: # noqa: BLE001 # best-effort filter: a deployment it cannot resolve answers for itself + verbose_router_logger.debug( + "litellm.router.py::_decisions_deployment_refuses_media: keeping a deployment of model=%s. Got - %s", + group, + e, + ) + return False diff --git a/litellm/router_rust/steps/prerouting.py b/litellm/router_rust/steps/prerouting.py new file mode 100644 index 00000000000..a83fbe29996 --- /dev/null +++ b/litellm/router_rust/steps/prerouting.py @@ -0,0 +1,1107 @@ +# pyright: reportUnknownMemberType=false, reportUnknownVariableType=false, reportUnknownArgumentType=false, reportAny=false, reportExplicitAny=false +# (the ported core code reads the untyped strategy routers, LiteLLM_Params dict fields and request dicts) +""" +Host-side pre-routing for ``RustCore``. + +Before an async pick resolves its name, the Rust core asks the host to pre-route it (a +``pre_route`` step, ``router-core/src/prerouting.rs``): the complexity, auto, adaptive and quality +routers registered from ``auto_router/...`` marker deployments, and the Claude Code session +binding, may send the request to another model group. They are live Python objects, so they stay +host-side for now (bridged, to port): this module registers them from the host registry's +deployments the way the Python router's ``init_*_router_deployment``, +``_finalize_adaptive_router_if_configured`` and ``_unregister_pre_routing_strategy_for_deployment`` +do, and answers the step the way ``_core_async_pre_routing_hook`` and ``_pin_tier_params_onto_request`` +do. It never reaches a Python router core. +""" + +import json +import logging +import re +from collections.abc import Awaitable, Callable, Iterable, Mapping, MutableMapping, Sequence +from itertools import chain +from types import MappingProxyType +from typing import TYPE_CHECKING, Any, Final, TypeAlias, cast # noqa: TID251 # the strategy routers are untyped + +from litellm._internal_context import with_service_target +from litellm._logging import verbose_router_logger +from litellm.caching.caching import DualCache, InMemoryCache +from litellm.caching.redis_cache import log_redis_failure +from litellm.constants import ( + CLIENT_OUTPUT_CEILING_METADATA_KEY, + CONSUMED_REQUEST_TAGS_METADATA_KEY, + DEFAULT_AUTO_ROUTER_MAX_INPUT_CHARS, + OUTPUT_TOKEN_CEILING_PARAMS, + SESSION_DEPLOYMENT_AFFINITY_TTL_METADATA_KEY, +) +from litellm.integrations.otel.routing import routing_decision_attributes +from litellm.integrations.otel.runtime import phase_attributes +from litellm.litellm_core_utils.core_helpers import get_or_create_metadata_bucket, without +from litellm.litellm_core_utils.credential_accessor import reject_api_key_secret_reference +from litellm.router_api import deployment_id +from litellm.router_host import router_host +from litellm.router_strategy.auto_router.auto_router_model_naming import ( + AUTO_ROUTER_MODEL_PREFIX, + STRATEGY_ROUTER_PARAM_FIELDS, + GatedAutoRouterCapability, + capability_limit_violation, + claimed_capabilities, + classify_strategy_router_model, + count_capability_routers, +) +from litellm.router_strategy.complexity_router.context_compaction import ( + arm_compaction, + is_native_compaction_call, + reject_recursive_compactor, +) +from litellm.router_strategy.tag_based_routing import get_routing_tags_from_request_kwargs, is_valid_deployment_tag +from litellm.router_utils.fallback_event_handlers import record_pre_routing_selection +from litellm.types.router import ConsumedRequestTagsStamp, Deployment, LiteLLM_Params, TaggedPreRoutingStrategy +from litellm.types.utils import ( + PROMPT_QUOTING_ROUTING_DECISION_FIELDS, + CustomPricingLiteLLMParams, + StandardLoggingRoutingDecision, + all_litellm_params, +) +from litellm.utils import provider_rejectable_params + +if TYPE_CHECKING: + from litellm.router_python_host import PythonHost + from litellm.router_rust.surface.registry import HostRegistry + from litellm.router_strategy.auto_router.auto_router import PreRoutingHookResponse + +# The live registry dicts: model_name -> the strategies registered under it, one per tag set. +StrategyRegistry: TypeAlias = "dict[str, list[TaggedPreRoutingStrategy[Any]]]" + +_ALIAS_PARAMS_NEVER_FORWARDED: Final = frozenset( + {"model", "api_base", "api_key", "api_version", "responses_api_version"} +) +_ALIAS_MARKER_FORWARDED_PARAMS_KWARG: Final = "_alias_marker_forwarded_params" +_CLAUDE_CODE_SESSION_ID_RE: Final = re.compile(r"^[a-zA-Z0-9_\-]{8,}$") +_CLAUDE_CODE_SESSION_ROUTER_TTL_SECONDS: Final = 3600 +CLAUDE_CODE_SESSION_ROUTER_BINDING_TARGET: Final = "claude_code_session_router_binding" +# `_async_get_available_deployment` runs the pre-routing hook only for the strategies with an async +# pick; any other router strategy takes the sync path, which never pre-routes. +_ASYNC_PICK_STRATEGIES: Final = frozenset( + {"usage-based-routing-v2", "simple-shuffle", "cost-based-routing", "latency-based-routing", "least-busy"} +) + + +def picks_async(router_strategy: str | None) -> bool: + """Whether the router's strategy has an async selector: the others pick on the sync path even + for async callers (``_async_get_available_deployment``).""" + return router_strategy in _ASYNC_PICK_STRATEGIES + + +TIER_PARAMS_NEVER_DROPPED: Final = frozenset(all_litellm_params) | frozenset( + { + "additional_drop_params", + "drop_params", + "messages", + "model", + "extra_headers", + "max_tokens", + "max_completion_tokens", + } +) + + +def _json_default_stable_id(value: object) -> str: + return f"{type(value).__module__}.{type(value).__qualname__}" + + +def _deployment_tags(deployment: Deployment) -> tuple[str, ...]: + return tuple(deployment.litellm_params.tags or ()) + + +def _has_registered_strategy(registry: StrategyRegistry, model_name: str, tags: tuple[str, ...]) -> bool: + return any(existing.tags == tags for existing in registry.get(model_name, [])) + + +def _routing_definition_fingerprint(deployment: Deployment) -> str | None: + """Identify configured routing fields, excluding external files and live strategy state.""" + try: + definition: Final = json.dumps( + deployment.litellm_params.model_dump( + include=set(STRATEGY_ROUTER_PARAM_FIELDS | {"model", "tags"}), exclude_none=True, warnings=False + ), + sort_keys=True, + default=_json_default_stable_id, + ) + except (TypeError, ValueError): + return None + return deployment_id(deployment.model_name, {"routing_definition": definition}) + + +def _unregister(registry: StrategyRegistry, model_name: str, tags: tuple[str, ...]) -> bool: + existing: Final = registry.get(model_name, []) + remaining: Final = [entry for entry in existing if entry.tags != tags] + if len(remaining) == len(existing): + return False + if remaining: + registry[model_name] = remaining # rebind-ok: the live registry, edited in place as the Python router does + else: + registry.pop(model_name, None) + return True + + +def is_strategy_marker(deployment: Mapping[str, object]) -> bool: + params: Final = deployment.get("litellm_params") + if not isinstance(params, Mapping): + return False + model: Final = params.get("model") + return isinstance(model, str) and classify_strategy_router_model(model) is not None + + +def _participates_in_adaptive_routing(params: LiteLLM_Params) -> bool: + kind: Final = classify_strategy_router_model(params.model) + if kind == "adaptive": + return True + if kind != "complexity": + return False + config: Final = params.complexity_router_config + return bool(config.get("adaptive")) if config else False + + +class PreRoutingStrategies: + """The pre-routing strategies of one router, kept on its host registry (``registry().plugins`` + reads ``_core_auto_routers`` and its siblings there).""" + + def __init__( + self, hosted: "HostRegistry", host: "PythonHost", ctx: object, capability_limit: object, cache: DualCache + ) -> None: + self._hosted: Final = hosted + self._host: Final = host + self._ctx: Final = ctx + self._capability_limit: object = capability_limit + self._cache: Final = cache + self._affinity: object = None + # The router's own `_ensure_deployment_affinity_callback` (its optional checks), when set. + self.ensure_affinity: Callable[[], None] | None = None + + # -- the registries ------------------------------------------------------------------------ + + @property + def auto(self) -> StrategyRegistry: + return self._hosted._core_auto_routers # pyright: ignore[reportPrivateUsage] # the registries live on the host registry + + @property + def complexity(self) -> StrategyRegistry: + return self._hosted._core_complexity_routers # pyright: ignore[reportPrivateUsage] # see above + + @property + def adaptive(self) -> StrategyRegistry: + return self._hosted._core_adaptive_routers # pyright: ignore[reportPrivateUsage] # see above + + @property + def quality(self) -> StrategyRegistry: + return self._hosted._core_quality_routers # pyright: ignore[reportPrivateUsage] # see above + + def all(self) -> tuple[StrategyRegistry, ...]: + """In the order ``_select_pre_routing_strategy`` searches them.""" + return (self.auto, self.complexity, self.adaptive, self.quality) + + def any_registered(self) -> bool: + return any(self.all()) + + # -- registry hooks (HostRegistry calls these) ----------------------------------------------- + + def reset(self) -> None: + """``set_model_list`` drops the auto, complexity and quality routers (never the adaptive ones).""" + self._hosted._core_quality_routers = {} # pyright: ignore[reportPrivateUsage] # see above + self._hosted._core_complexity_routers = {} # pyright: ignore[reportPrivateUsage] # see above + self._hosted._core_auto_routers = {} # pyright: ignore[reportPrivateUsage] # see above + + def register(self, deployment: Deployment) -> None: + """The end of ``_add_deployment``: an auto, complexity or quality marker registers its router + (adaptive ones wait for ``finalize``).""" + match classify_strategy_router_model(deployment.litellm_params.model): + case "semantic": + self._init_auto_router(deployment) + case "complexity": + self._init_complexity_router(deployment) + case "quality": + self._init_quality_router(deployment) + case _: + pass + + def release(self, deployment: Deployment) -> None: + """``_unregister_pre_routing_strategy_for_deployment``.""" + if not deployment.litellm_params.model.startswith("auto_router/"): + return + model_name: Final = deployment.model_name + tags: Final = _deployment_tags(deployment) + for registry in (self.auto, self.complexity, self.quality): + _ = _unregister(registry, model_name, tags) + if _unregister(self.adaptive, model_name, tags): + self._sync_adaptive_router_hooks() + + def release_entry(self, entry: Mapping[str, object]) -> None: + """``release`` of a deleted model_list entry; a failure only logs, as the delete has happened.""" + try: + self.release(Deployment(**entry)) # pyright: ignore[reportArgumentType] # a model_list entry + except Exception: # noqa: BLE001 # the delete already happened; a failed release only logs + verbose_router_logger.exception( + "delete_deployment: could not release pre-routing strategies for model_id=%s; " + "the deployment is out of the model_list and its indices are repaired", + as_dict(entry.get("model_info")).get("id"), + ) + + def upserted(self, deployment: Deployment, previous: Deployment | None) -> None: + """After an upsert's re-add: rebuild the adaptive routers when it touched one.""" + if _participates_in_adaptive_routing(deployment.litellm_params) or ( + previous is not None and _participates_in_adaptive_routing(previous.litellm_params) + ): + self.finalize() + + def without_capability_limit(self, action: Callable[[], object]) -> None: + """Run ``action`` without judging the capability ceiling: a rollback re-admits a serving router.""" + resolver: Final = self._capability_limit + self._capability_limit = None + try: + _ = action() + finally: + self._capability_limit = resolver + + def finalize(self) -> None: + """``_finalize_adaptive_router_if_configured``: an adaptive router for every adaptive marker, + and the adaptive companion of every complexity router configured with ``adaptive``.""" + for entry in self._hosted._core_model_list or []: # pyright: ignore[reportPrivateUsage] # the host registry's live list + params = entry.get("litellm_params") + lp_model = params.get("model") if isinstance(params, dict) else None + if not (isinstance(lp_model, str) and lp_model.startswith("auto_router/adaptive_router")): + continue + model_name = entry.get("model_name") + if not model_name or not params: + continue + deployment = Deployment( + model_name=str(model_name), + litellm_params=LiteLLM_Params.model_validate(params), + model_info=entry.get("model_info"), # pyright: ignore[reportArgumentType] # the entry's model_info + ) + if _has_registered_strategy(self.adaptive, str(model_name), _deployment_tags(deployment)): + continue + self._init_adaptive_router(deployment) + for model_name, tagged_complexity_routers in self.complexity.items(): + for tagged in tagged_complexity_routers: + complexity_router = tagged.strategy + if not complexity_router.config.adaptive: + continue + if _has_registered_strategy(self.adaptive, model_name, tagged.tags): + continue + adaptive_router = complexity_router._ensure_adaptive_router() + if adaptive_router is not None: + self.adaptive[model_name] = [ + *self.adaptive.get(model_name, []), + TaggedPreRoutingStrategy( + tags=tagged.tags, + strategy=adaptive_router, + definition_fingerprint=tagged.definition_fingerprint, + deployment=tagged.deployment, + ), + ] + self._sync_adaptive_router_hooks() + + def retire(self) -> None: + """Release the adaptive routers' post-call hooks this router registered.""" + from litellm.router_strategy.adaptive_router.hooks import AdaptiveRouterPostCallHook + + own: Final = frozenset(id(tagged.strategy) for tagged in chain.from_iterable(self.adaptive.values())) + hooks: Final[list[object]] = [ # mutable-ok: built here + hook + for hook in self._host.callbacks.get_custom_loggers_for_type(AdaptiveRouterPostCallHook) + if isinstance(hook, AdaptiveRouterPostCallHook) and id(hook.adaptive_router) in own + ] + if self._affinity is not None: + hooks.append(self._affinity) + self._affinity = None + if hooks: + self._host.callbacks.drop_callbacks(hooks) + + # -- building -------------------------------------------------------------------------------- + + def _register( + self, registry: StrategyRegistry, deployment: Deployment, strategy: object, strategy_label: str + ) -> None: + tags: Final = _deployment_tags(deployment) + if _has_registered_strategy(registry, deployment.model_name, tags): + raise ValueError( + f"{strategy_label} deployment {deployment.model_name} with tags {list(tags)} already exists. " + "Please use a different model name or set different tags." + ) + registry[deployment.model_name] = [ # rebind-ok: the live registry, edited in place as the Python router does + *registry.get(deployment.model_name, []), + TaggedPreRoutingStrategy( + tags=tags, + strategy=strategy, + definition_fingerprint=_routing_definition_fingerprint(deployment), + deployment=deployment, + ), + ] + + def _capability_violation(self, capability: GatedAutoRouterCapability) -> str | None: + resolver: Final = self._capability_limit + # `self.auto_router_capability_limit() if ... is not None`: a value that cannot be called raises. + limit: Final = resolver() if resolver is not None else None # pyright: ignore[reportCallIssue] # called as given, as Python calls it + others: Final = count_capability_routers( + (entry for entry in self._hosted._core_model_list if isinstance(entry, Mapping)), # pyright: ignore[reportPrivateUsage, reportUnnecessaryIsInstance] # the live list + capability=capability, + ) + return capability_limit_violation(capability=capability, held=others + 1, limit=limit) # pyright: ignore[reportArgumentType] # the resolver's limit + + def _init_auto_router(self, deployment: Deployment) -> None: + from litellm.router_strategy.auto_router.auto_router import AutoRouter + + params: Final = deployment.litellm_params + if params.auto_router_config_path is None and params.auto_router_config is None: + raise ValueError( + "auto_router_config_path or auto_router_config is required for auto-router deployments. Please set it in the litellm_params" + ) + if params.auto_router_default_model is None: + raise ValueError( + "auto_router_default_model is required for auto-router deployments. Please set it in the litellm_params" + ) + if params.auto_router_embedding_model is None: + raise ValueError( + "auto_router_embedding_model is required for auto-router deployments. Please set it in the litellm_params" + ) + max_input_chars: Final = params.auto_router_max_input_chars + router: Final = AutoRouter( + model_name=deployment.model_name, + auto_router_config_path=params.auto_router_config_path, + auto_router_config=params.auto_router_config, + default_model=params.auto_router_default_model, + embedding_model=params.auto_router_embedding_model, + ctx=self._ctx, # pyright: ignore[reportArgumentType] # the core's RoutingContext + max_input_chars=max_input_chars if max_input_chars is not None else DEFAULT_AUTO_ROUTER_MAX_INPUT_CHARS, + ) + self._register(self.auto, deployment, router, "Auto-router") + + def _init_complexity_router(self, deployment: Deployment) -> None: + from litellm.router_strategy.complexity_router.complexity_router import ComplexityRouter + from litellm.router_strategy.complexity_router.config import ComplexityRouterConfig + + config: Final = deployment.litellm_params.complexity_router_config + for capability in claimed_capabilities(config): + if (violation := self._capability_violation(capability)) is not None: + raise ValueError(violation) + default_model: Final = ( + ComplexityRouterConfig.model_validate(config).resolve_default_model( + deployment.litellm_params.complexity_router_default_model + ) + if config + else deployment.litellm_params.complexity_router_default_model + ) + if default_model is None: + raise ValueError( + "complexity_router_default_model is required for complexity-router deployments, " + "or configure tiers in complexity_router_config. Please set it in the litellm_params" + ) + router: Final = ComplexityRouter( + model_name=deployment.model_name, + default_model=default_model, + ctx=self._ctx, # pyright: ignore[reportArgumentType] # the core's RoutingContext + complexity_router_config=config, + ) + self._register(self.complexity, deployment, router, "Complexity-router") + if router._uses_deployment_pin: # pyright: ignore[reportPrivateUsage] # the Python router reads the same flag + self._ensure_deployment_affinity_callback() + + def _ensure_deployment_affinity_callback(self) -> None: + """``_ensure_deployment_affinity_callback``: the affinity check (every global flag off) a + complexity router's session pin needs, registered once.""" + from litellm.router_utils.pre_call_checks.deployment_affinity_check import DeploymentAffinityCheck + + if self.ensure_affinity is not None: + self.ensure_affinity() + return + if self._affinity is not None: + return + hosted: Final = self._hosted + + def is_priority_group(model: str) -> bool: + resolved: Final = hosted._core_get_model_from_alias(model=model) or model # pyright: ignore[reportPrivateUsage] # the host registry's alias lookup + group: Final = hosted.get_routing_group(resolved) + return group is not None and group.routing_strategy == "priority" + + affinity: Final = DeploymentAffinityCheck( + cache=self._cache, + ttl_seconds=3600, + enable_user_key_affinity=False, + enable_responses_api_affinity=False, + enable_session_id_affinity=False, + model_group_affinity_config=None, + is_priority_group=is_priority_group, + session_affinity_repin_on_failover=False, + ) + self._affinity = affinity + self._host.callbacks.add_litellm_callback(affinity) + + def _init_quality_router(self, deployment: Deployment) -> None: + from litellm.router_strategy.quality_router.quality_router import QualityRouter + + config: Final = deployment.litellm_params.quality_router_config + configured: Final = deployment.litellm_params.quality_router_default_model + default_model: Final = configured if configured is not None or not config else config.get("default_model") + if default_model is None: + raise ValueError( + "quality_router_default_model is required for quality-router deployments, " + "or set default_model in quality_router_config. Please configure it in the litellm_params" + ) + router: Final = QualityRouter( + model_name=deployment.model_name, + default_model=default_model, + ctx=self._ctx, # pyright: ignore[reportArgumentType] # the core's RoutingContext + quality_router_config=config, + ) + self._register(self.quality, deployment, router, "Quality-router") + + def _init_adaptive_router(self, deployment: Deployment) -> None: + from litellm.router_strategy.adaptive_router.adaptive_router import AdaptiveRouter + from litellm.router_strategy.adaptive_router.hooks import AdaptiveRouterPostCallHook + from litellm.types.router import AdaptiveRouterConfig, AdaptiveRouterPreferences + + raw_config: Final = deployment.litellm_params.adaptive_router_config + if raw_config is None: + raise ValueError("adaptive_router_config is required for adaptive-router deployments.") + config: Final = AdaptiveRouterConfig(**raw_config) + model_to_prefs: Final[dict[str, AdaptiveRouterPreferences]] = {} # mutable-ok: built here + model_to_cost: Final[dict[str, float]] = {} # mutable-ok: built here + for name in config.available_models: + deployments = self._hosted._core_deployments_named(name) # pyright: ignore[reportPrivateUsage] # the host registry's name index + if not deployments: + continue + first = deployments[0] + model_info = first.get("model_info") + info: Mapping[str, object] = model_info if isinstance(model_info, dict) else {} + prefs_raw = info.get("adaptive_router_preferences") + if isinstance(prefs_raw, dict): + model_to_prefs[name] = AdaptiveRouterPreferences(**prefs_raw) + cost = _adaptive_cost(as_dict(first.get("litellm_params")), info) + if isinstance(cost, int | float | str): + model_to_cost[name] = float(cost) + router: Final = AdaptiveRouter( + router_name=deployment.model_name, + config=config, + model_to_prefs=model_to_prefs, + model_to_cost=model_to_cost, + ) + self._register(self.adaptive, deployment, router, "Adaptive-router") + self._host.callbacks.add_litellm_callback(AdaptiveRouterPostCallHook(adaptive_router=router)) + verbose_router_logger.info( + "AdaptiveRouter[%s] initialized with %d models", deployment.model_name, len(config.available_models) + ) + + def _sync_adaptive_router_hooks(self) -> None: + """One post-call hook per registered adaptive router, plus the header hook while any exists.""" + from litellm.router_strategy.adaptive_router.hooks import ( + AdaptiveRouterPostCallHook, + AdaptiveRouterResponseHeaderHook, + ) + + callbacks: Final = self._host.callbacks + for callback in callbacks.get_custom_loggers_for_type(AdaptiveRouterPostCallHook): + callbacks.remove_callback_from_all_lists(callback) + for tagged in chain.from_iterable(self.adaptive.values()): + callbacks.add_litellm_callback(AdaptiveRouterPostCallHook(adaptive_router=tagged.strategy)) + if self.adaptive: + callbacks.add_litellm_callback(AdaptiveRouterResponseHeaderHook()) + + +# -- the request side -------------------------------------------------------------------------- + + +def _stamp_or_clear_metadata_key( + request_kwargs: dict[str, object], # mutable-ok: the request kwargs, stamped in place + key: str, + value: object | None, +) -> None: + """Write a proxy-internal metadata key for this routing attempt, or clear it from both buckets.""" + if value is None: + for bucket in (request_kwargs.get("metadata"), request_kwargs.get("litellm_metadata")): + if isinstance(bucket, dict): + bucket.pop(key, None) + return + _, metadata_bucket = get_or_create_metadata_bucket(request_kwargs) + metadata_bucket[key] = value + + +def _redact_prompt_text_if_needed( + request_kwargs: Mapping[str, object], routing_decision: StandardLoggingRoutingDecision +) -> StandardLoggingRoutingDecision: + from litellm.litellm_core_utils.redact_messages import should_redact_message_logging + + if not should_redact_message_logging( + { + "litellm_params": request_kwargs, + "standard_callback_dynamic_params": request_kwargs.get("standard_callback_dynamic_params"), + } + ): + return routing_decision + kept: Final = without(routing_decision, *PROMPT_QUOTING_ROUTING_DECISION_FIELDS) + return cast(StandardLoggingRoutingDecision, kept) # cast-ok: dropping optional keys preserves the type + + +def _record_routing_decision( + request_kwargs: dict[str, object], # mutable-ok: the request kwargs + routing_decision: StandardLoggingRoutingDecision | None, +) -> None: + """Make the request's metadata describe this routing attempt, and only this one.""" + from litellm.router_strategy.auto_router.baseline_request import capture_baseline_parameters + from litellm.types.router import BaselineRouteStamp + + phase_attributes(routing_decision_attributes(routing_decision)) + baseline_model: Final = routing_decision.get("savings_baseline_model") if routing_decision else None + baseline_id: Final = routing_decision.get("savings_baseline_deployment_id") if routing_decision else None + router_name: Final = routing_decision.get("router_model_name") if routing_decision else None + caller_parameters: Final = capture_baseline_parameters(request_kwargs) if router_name and baseline_model else None + _stamp_or_clear_metadata_key( + request_kwargs, + "_autorouter_baseline_route", + BaselineRouteStamp(router_name, baseline_model, baseline_id, caller_parameters) + if router_name and baseline_model and baseline_id + else None, + ) + _stamp_or_clear_metadata_key( + request_kwargs, + "routing_decision", + None if routing_decision is None else _redact_prompt_text_if_needed(request_kwargs, routing_decision), + ) + + +def _as_output_cap(value: object) -> int | None: + if isinstance(value, bool) or not isinstance(value, int | float | str): + return None + try: + cap: Final = int(float(value)) + except (ValueError, OverflowError): + return None + return cap if cap >= 0 else None + + +def _stamped_client_ceiling(request_kwargs: Mapping[str, object]) -> Mapping[str, int] | None: + stamped: Final = next( + ( + bucket.get(CLIENT_OUTPUT_CEILING_METADATA_KEY) + for bucket in (request_kwargs.get("metadata"), request_kwargs.get("litellm_metadata")) + if isinstance(bucket, dict) and CLIENT_OUTPUT_CEILING_METADATA_KEY in bucket + ), + None, + ) + if not isinstance(stamped, dict): + return None + return MappingProxyType( + { + str(carrier): cap + for carrier, value in stamped.items() + if carrier in OUTPUT_TOKEN_CEILING_PARAMS and (cap := _as_output_cap(value)) is not None + } + ) + + +def _restore_client_output_ceiling( + request_kwargs: MutableMapping[str, object], # mutable-ok: the request kwargs, restored in place +) -> None: + callers_ceiling: Final = _stamped_client_ceiling(request_kwargs) + if callers_ceiling is None: + return + for carrier in OUTPUT_TOKEN_CEILING_PARAMS: + request_kwargs.pop(carrier, None) + request_kwargs.update(callers_ceiling) + + +def _stamp_client_output_ceiling(request_kwargs: dict[str, object]) -> None: # mutable-ok: the request kwargs + _, metadata_bucket = get_or_create_metadata_bucket(request_kwargs) + metadata_bucket.setdefault( + CLIENT_OUTPUT_CEILING_METADATA_KEY, + {carrier: request_kwargs[carrier] for carrier in OUTPUT_TOKEN_CEILING_PARAMS if carrier in request_kwargs}, + ) + + +def _pop_effort_from_nested_carrier(request_kwargs: dict[str, object], carrier: str) -> None: # mutable-ok: same + nested: Final = request_kwargs.get(carrier) + if not isinstance(nested, Mapping): + return + sanitized: Final = without(nested, "effort") + if sanitized: + request_kwargs[carrier] = sanitized # rebind-ok: copy-on-write of the request's nested carrier + else: + request_kwargs.pop(carrier, None) + + +def _tier_ceiling_under_the_surface_name( + tier_litellm_params: Mapping[str, object], responses_call: bool +) -> Mapping[str, object]: + surface_key: Final = "max_output_tokens" if responses_call else "max_tokens" + carried: Final = tuple( + key + for key in (surface_key, "max_tokens", "max_completion_tokens", "max_output_tokens") + if key in tier_litellm_params + ) + if not carried: + return tier_litellm_params + return MappingProxyType( + { + **without(tier_litellm_params, *OUTPUT_TOKEN_CEILING_PARAMS), + surface_key: tier_litellm_params[carried[0]], + } + ) + + +def _drop_client_carriers_a_tier_pin_supersedes( + request_kwargs: dict[str, object], # mutable-ok: the request kwargs + tier_litellm_params: Mapping[str, object], +) -> None: + if not OUTPUT_TOKEN_CEILING_PARAMS.isdisjoint(tier_litellm_params): + _stamp_client_output_ceiling(request_kwargs) + for carrier in OUTPUT_TOKEN_CEILING_PARAMS: + request_kwargs.pop(carrier, None) + if "reasoning_effort" not in tier_litellm_params: + return + request_kwargs.pop("thinking", None) + _pop_effort_from_nested_carrier(request_kwargs, "output_config") + _pop_effort_from_nested_carrier(request_kwargs, "reasoning") + + +def _request_header(request_kwargs: Mapping[str, object], header_name: str) -> str | None: + proxy_server_request: Final = request_kwargs.get("proxy_server_request") + if not isinstance(proxy_server_request, Mapping): + return None + headers: Final = proxy_server_request.get("headers") + if not isinstance(headers, Mapping): + return None + return next( + ( + value + for key, value in headers.items() + if isinstance(key, str) and key.lower() == header_name and isinstance(value, str) + ), + None, + ) + + +def _session_router_cache_key(request_kwargs: Mapping[str, object]) -> str | None: + session_id: Final = _request_header(request_kwargs, "x-claude-code-session-id") + if session_id is None or _CLAUDE_CODE_SESSION_ID_RE.fullmatch(session_id) is None: + return None + metadata_name: Final = "litellm_metadata" if "litellm_metadata" in request_kwargs else "metadata" + metadata: Final = request_kwargs.get(metadata_name) + if not isinstance(metadata, Mapping): + return None + caller_scope: Final = metadata.get("user_api_key_hash") + if not isinstance(caller_scope, str) or not caller_scope: + return None + return f"claude_code_session_router:v1:{caller_scope}:{session_id}" + + +class PreRouter: + """Answers the Rust core's ``pre_route`` steps (``_core_async_pre_routing_hook``).""" + + def __init__( + self, + strategies: PreRoutingStrategies, + hosted: "HostRegistry", + host: "PythonHost", + ctx: object, + routing_cache: DualCache, + ) -> None: + self._strategies: Final = strategies + self._hosted: Final = hosted + self._host: Final = host + self._ctx: Final = ctx + self._session_cache: Final = DualCache(redis_cache=routing_cache.redis_cache, in_memory_cache=InMemoryCache()) + + # -- the step -------------------------------------------------------------------------------- + + async def pre_route( + self, + model: str, + request_kwargs: dict[str, object], # mutable-ok: the request kwargs the hook stamps + *, + messages: object, + input: object, + fallback_depth: int, + router_strategy: str | None, + enable_tag_filtering: bool, + match_any: bool, + public_router: object, + run_plugins: Callable[[str], Awaitable[None]] | None = None, + pass_through: bool = False, + ) -> str | None: + """The start of ``_async_get_available_deployment``: run the hook, record its pick and pin the + tier's litellm_params. The model group to resolve, or ``None`` to resolve ``model`` itself. + ``pass_through`` is ``_async_get_available_deployment_for_pass_through``, which runs the hook + whatever the router's strategy.""" + if not pass_through and not picks_async(router_strategy): + return None + responses_call: Final = input is not None and messages is None + response: Final = await self._hook( + model, + request_kwargs, + messages=messages, + input=input, + fallback_depth=fallback_depth, + enable_tag_filtering=enable_tag_filtering, + match_any=match_any, + public_router=public_router, + run_plugins=run_plugins, + ) + routed: Final = response.model if response is not None else model + if response is not None: + record_pre_routing_selection(request_kwargs, routed) + self._pin_tier_params( + routed, response.litellm_params if response is not None else None, request_kwargs, responses_call + ) + return routed if response is not None else None + + # -- the hook -------------------------------------------------------------------------------- + + async def _hook( + self, + model: str, + request_kwargs: dict[str, object], # mutable-ok: see pre_route + *, + messages: object, + input: object, + fallback_depth: int, + enable_tag_filtering: bool, + match_any: bool, + public_router: object, + run_plugins: Callable[[str], Awaitable[None]] | None, + ) -> "PreRoutingHookResponse | None": + _restore_client_output_ceiling(request_kwargs) + _record_routing_decision(request_kwargs, None) + requested: Final = self._hosted._core_get_model_from_alias(model=model) or model # pyright: ignore[reportPrivateUsage] # the host registry's alias lookup + registered: Final = await self._resolve_session_router( + model, requested, request_kwargs, fallback_depth, enable_tag_filtering, match_any + ) + # The routing plugins run on the session-resolved name, before a strategy is selected, so a + # strategy reads their signals; router-core narrows the pick to what they left. + if run_plugins is not None: + await run_plugins(registered) + selected: Final = self._select_strategy(registered, request_kwargs, enable_tag_filtering, match_any) + if selected is None: + await arm_compaction(request_kwargs, None) + _stamp_or_clear_metadata_key(request_kwargs, SESSION_DEPLOYMENT_AFFINITY_TTL_METADATA_KEY, None) + _stamp_or_clear_metadata_key(request_kwargs, CONSUMED_REQUEST_TAGS_METADATA_KEY, None) + return None + from litellm.router_strategy.complexity_router.complexity_router import ComplexityRouter + + marker: Final = self._selected_marker(registered, selected.tags, request_kwargs) + definition: Final = selected.deployment + config_id: Final = definition.model_info.id if definition else None + updated_at: Final = definition.model_info.updated_at if definition else None + router_kind: Final = classify_strategy_router_model(definition.litellm_params.model) if definition else None + provenance: Final[StandardLoggingRoutingDecision] = { + "router_model_name": definition.model_name if definition else registered, + **({"router_type": router_kind} if router_kind is not None else {}), + **({"router_config_id": config_id} if config_id is not None else {}), + **({"router_config_updated_at": updated_at.isoformat()} if updated_at is not None else {}), + **( + {"router_config_fingerprint": selected.definition_fingerprint} + if selected.definition_fingerprint is not None + else {} + ), + } # pyright: ignore[reportAssignmentType] # the optional keys, as the Python router builds them + phase_attributes(routing_decision_attributes(provenance)) + reject_recursive_compactor(registered) + strategy: Final = selected.strategy + complexity: Final = strategy if isinstance(strategy, ComplexityRouter) else None + await arm_compaction( + request_kwargs, + complexity.config.context_compaction if complexity is not None else None, + _tier_members(complexity.config.tiers) if complexity is not None else (), # pyright: ignore[reportArgumentType] # the tiers' model names + parent_model=model, + ctx=self._ctx, # pyright: ignore[reportArgumentType] # the core's RoutingContext + allow_escalation=complexity is not None and complexity.config.enable_context_window_escalation, + messages=messages, # pyright: ignore[reportArgumentType] # the request's messages, as given + ) + await router_host().authorize_strategy_inference( + deployment=marker, + request_kwargs=request_kwargs, + llm_router=public_router, # pyright: ignore[reportArgumentType] # the litellm.Router this core serves + ) + compression_policy: Final = router_host().compression_policy( + llm_router=public_router, # pyright: ignore[reportArgumentType] # same + model_alias=registered, + request_kwargs=request_kwargs, + request_tags=get_routing_tags_from_request_kwargs(request_kwargs), + ) + independent_compression: Final = compression_policy is not None and not ( + compression_policy.is_same + and compression_policy.model is not None + and router_host().model_hop_compression_armed() + ) + routing_messages: Final = ( + await router_host().messages_for_routing( + policy=compression_policy, + messages=messages, # pyright: ignore[reportArgumentType] # same + request_kwargs=request_kwargs, + ) + if independent_compression + else None + ) + routed: Final = await strategy.async_pre_routing_hook( + model=registered, + request_kwargs=request_kwargs, + messages=routing_messages if routing_messages is not None else messages, # pyright: ignore[reportArgumentType] # the request's messages, as given + input=input, # pyright: ignore[reportArgumentType] # the request's input, as given + specific_deployment=False, + ) + hooked: Final[PreRoutingHookResponse | None] = routed + traced: Final = ( + hooked.model_copy(update={"routing_decision": {**provenance, **hooked.routing_decision}}) + if hooked is not None and hooked.routing_decision is not None + else hooked + ) + response: Final = ( + traced.model_copy(update={"messages": messages}) + if traced is not None and routing_messages is not None and traced.messages == routing_messages + else traced + ) + _record_routing_decision(request_kwargs, response.routing_decision if response else None) + _stamp_or_clear_metadata_key( + request_kwargs, + SESSION_DEPLOYMENT_AFFINITY_TTL_METADATA_KEY, + response.session_affinity_ttl_seconds if response else None, + ) + request_tags: Final = get_routing_tags_from_request_kwargs(request_kwargs) + consumed: Final = ( + ConsumedRequestTagsStamp(model_group=response.model, tags=selected.tags) + if response is not None + and selected.tags + and request_tags + and is_valid_deployment_tag(selected.tags, request_tags, match_any) # pyright: ignore[reportArgumentType] # the tags as the Python router passes them + else None + ) + _stamp_or_clear_metadata_key(request_kwargs, CONSUMED_REQUEST_TAGS_METADATA_KEY, consumed) + marker_params: Final = ( + self._forwardable_marker_params(registered, selected.tags, request_kwargs) if response is not None else () + ) + tier_param_keys: Final = tuple(response.litellm_params or ()) if response is not None else () + overridden: Final = frozenset(tier_param_keys) | ( + OUTPUT_TOKEN_CEILING_PARAMS if not OUTPUT_TOKEN_CEILING_PARAMS.isdisjoint(tier_param_keys) else frozenset() + ) + newly_forwarded: Final = tuple( + (key, value) for key, value in marker_params if key not in request_kwargs and key not in overridden + ) + if response is not None: + _stamp_client_output_ceiling(request_kwargs) + request_kwargs.pop(_ALIAS_MARKER_FORWARDED_PARAMS_KWARG, None) + request_kwargs.update(newly_forwarded) + if newly_forwarded: + request_kwargs.update({_ALIAS_MARKER_FORWARDED_PARAMS_KWARG: tuple(key for key, _ in newly_forwarded)}) + return response + + # -- strategy selection ---------------------------------------------------------------------- + + def _deployments_for_request( + self, model: str, request_kwargs: Mapping[str, object] + ) -> Sequence[Mapping[str, object]]: + return self._hosted._core_deployments_for_request(model, request_kwargs) # pyright: ignore[reportPrivateUsage] # the host registry's lookup + + def _select_strategy( + self, model: str, request_kwargs: Mapping[str, object], enable_tag_filtering: bool, match_any: bool + ) -> "TaggedPreRoutingStrategy[Any] | None": + """``_select_pre_routing_strategy``.""" + registries: Final = self._strategies.all() + if not any(registries): + return None + deployments: Final = self._deployments_for_request(model, request_kwargs) + registered_names: Final = tuple(dict.fromkeys(str(d.get("model_name")) for d in deployments)) or (model,) + candidates: Final = ( + tuple( # comprehension-ok: registry by registry, name by name, as the Python router searches + tagged for registry in registries for name in registered_names for tagged in registry.get(name, []) + ) + ) + if not candidates: + return None + request_tags: Final = get_routing_tags_from_request_kwargs(request_kwargs) + if request_tags: + for tagged in candidates: + if tagged.tags and is_valid_deployment_tag(list(tagged.tags), request_tags, match_any): + return tagged + for tagged in candidates: + if "default" in tagged.tags: + return tagged + request_scoped: Final = request_kwargs.get("enable_tag_filtering") is True + if ( + (enable_tag_filtering or request_scoped) + and all(tagged.tags for tagged in candidates) + and any(not is_strategy_marker(d) for d in deployments) + ): + return None + return candidates[0] + + def _selected_marker( + self, model: str, strategy_tags: tuple[str, ...], request_kwargs: Mapping[str, object] + ) -> Mapping[str, object] | None: + markers: Final = tuple( + deployment + for deployment in self._deployments_for_request(model, request_kwargs) + if str(as_dict(deployment.get("litellm_params")).get("model", "")).startswith(AUTO_ROUTER_MODEL_PREFIX) + and "model" in as_dict(deployment.get("litellm_params")) + ) + tag_matched: Final = tuple( + deployment + for deployment in markers + if tuple(_tags_of(as_dict(deployment.get("litellm_params")))) == strategy_tags + ) + return tag_matched[0] if tag_matched else (markers[0] if markers else None) + + def _forwardable_marker_params( + self, model: str, strategy_tags: tuple[str, ...], request_kwargs: Mapping[str, object] + ) -> tuple[tuple[str, object], ...]: + marker: Final = self._selected_marker(model, strategy_tags, request_kwargs) + if marker is None: + return () + return tuple( + (key, value) + for key, value in as_dict(marker.get("litellm_params")).items() + if key not in _ALIAS_PARAMS_NEVER_FORWARDED + and key not in CustomPricingLiteLLMParams.model_fields + and value is not None + ) + + # -- the Claude Code session binding --------------------------------------------------------- + + @with_service_target(CLAUDE_CODE_SESSION_ROUTER_BINDING_TARGET) + async def _delete_binding(self, cache_key: str) -> None: + try: + await self._session_cache.async_delete_cache(key=cache_key) + except Exception as e: # noqa: BLE001 # cache cleanup must not fail an otherwise routable request + verbose_router_logger.warning( + "Failed to delete Claude Code session router binding; the binding may remain until its TTL expires: %s", + e, + ) + + @with_service_target(CLAUDE_CODE_SESSION_ROUTER_BINDING_TARGET) + async def _get_binding(self, cache_key: str) -> object: + try: + if self._session_cache.redis_cache is None: + return await self._session_cache.async_get_cache(key=cache_key) + return await self._session_cache.redis_cache.async_get_cache(key=cache_key) + except Exception as e: # noqa: BLE001 # an optional binding must not make routing depend on Redis + log_redis_failure( + verbose_router_logger, + logging.WARNING, + "Failed to read Claude Code session router binding; using the requested model", + e, + ) + return None + + @with_service_target(CLAUDE_CODE_SESSION_ROUTER_BINDING_TARGET) + async def _resolve_session_router( + self, + model: str, + registered: str, + request_kwargs: dict[str, object], # mutable-ok: see pre_route + fallback_depth: int, + enable_tag_filtering: bool, + match_any: bool, + ) -> str: + """``_resolve_claude_code_session_router``.""" + if is_native_compaction_call() or not self._strategies.any_registered(): + return registered + cache_key: Final = _session_router_cache_key(request_kwargs) + if cache_key is None: + return registered + depth: Final = fallback_depth or request_kwargs.get("fallback_depth") + if depth not in (None, 0): + return registered + agent_id: Final = _request_header(request_kwargs, "x-claude-code-agent-id") + if agent_id is not None: + bound_model: Final = await self._get_binding(cache_key) + if not isinstance(bound_model, str): + return registered + bound_registered: Final = self._hosted._core_get_model_from_alias(model=bound_model) or bound_model # pyright: ignore[reportPrivateUsage] # see _hook + if self._select_strategy(bound_registered, request_kwargs, enable_tag_filtering, match_any) is None: + await self._delete_binding(cache_key) + return registered + await self._session_cache.async_set_cache( + key=cache_key, value=bound_model, ttl=_CLAUDE_CODE_SESSION_ROUTER_TTL_SECONDS + ) + _stamp_or_clear_metadata_key(request_kwargs, "model_group", bound_model) + return bound_registered + if self._select_strategy(registered, request_kwargs, enable_tag_filtering, match_any) is None: + return registered + await self._session_cache.async_set_cache( + key=cache_key, value=model, ttl=_CLAUDE_CODE_SESSION_ROUTER_TTL_SECONDS + ) + return registered + + # -- tier litellm_params --------------------------------------------------------------------- + + def _tier_params_the_target_accepts( + self, model: str, tier_params: Mapping[str, object], request_kwargs: Mapping[str, object] + ) -> Mapping[str, object]: + from litellm.router_rust.invoke.shaping import deployment_accepts_param + + deployments: Final = self._hosted._core_get_model_list(model_name=model) or () # pyright: ignore[reportPrivateUsage] # the host registry's lookup + if not deployments: + return tier_params + allowlisted: Final = _allowlist(tier_params) | _allowlist(request_kwargs) + candidates: Final = provider_rejectable_params(tier_params) - TIER_PARAMS_NEVER_DROPPED - allowlisted + unsupported: Final = frozenset( + param + for param in candidates + if not any(deployment_accepts_param(deployment, model, param, self._host) for deployment in deployments) + ) + if not unsupported: + return tier_params + verbose_router_logger.warning( + "litellm.router.py: dropping tier params %s for model=%s, no deployment behind it declares them", + ", ".join(sorted(unsupported)), + model, + ) + return MappingProxyType(without(tier_params, *unsupported)) + + def _pin_tier_params( + self, + model: str, + tier_litellm_params: Mapping[str, object] | None, + request_kwargs: dict[str, object], # mutable-ok: see pre_route + responses_call: bool, + ) -> None: + """``_pin_tier_params_onto_request``.""" + if not tier_litellm_params: + return + reject_api_key_secret_reference(tier_litellm_params) + accepted: Final = self._tier_params_the_target_accepts(model, tier_litellm_params, request_kwargs) + surface: Final = _tier_ceiling_under_the_surface_name(accepted, responses_call=responses_call) + _drop_client_carriers_a_tier_pin_supersedes(request_kwargs, surface) + request_kwargs.update(surface) + + +def as_dict(value: object) -> Mapping[str, object]: + if not isinstance(value, Mapping): + return {} + return cast(Mapping[str, object], value) # cast-ok: a str-keyed config or request dict + + +def _adaptive_cost(params: Mapping[str, object], info: Mapping[str, object]) -> object: + """A model's input price for the adaptive router: litellm_params win over model_info.""" + cost: Final = params.get("input_cost_per_token") + return cost if cost is not None else info.get("input_cost_per_token") + + +def _tier_members(tiers: Mapping[str, object]) -> tuple[object, ...]: + """Every model the tier pools name, once, in order.""" + pools: Final = ( + (pool,) if isinstance(pool, str) or not isinstance(pool, Iterable) else pool for pool in tiers.values() + ) + return tuple(dict.fromkeys(chain.from_iterable(pools))) + + +def _tags_of(params: Mapping[str, object]) -> Sequence[object]: + tags: Final = params.get("tags") + return tags if isinstance(tags, list | tuple) else () + + +def _allowlist(params: Mapping[str, object]) -> frozenset[str]: + declared: Final = params.get("allowed_openai_params") + if not isinstance(declared, list | tuple | set | frozenset): + return frozenset() + return frozenset(entry for entry in declared if isinstance(entry, str)) + + +__all__ = ["PreRouter", "PreRoutingStrategies", "is_strategy_marker"] diff --git a/litellm/router_rust/steps/selection.py b/litellm/router_rust/steps/selection.py new file mode 100644 index 00000000000..183350bc05f --- /dev/null +++ b/litellm/router_rust/steps/selection.py @@ -0,0 +1,445 @@ +""" +Host-side strategy selectors for ``RustCore``. + +The Rust core decides which strategy picks and whose state it reads (``strategy::routing_context``: +a request override, then the routing group, then the router's own strategy) and asks the host to +run the stateful strategies it does not implement natively through a ``select`` step. The +strategies themselves are the standalone ``litellm/router_strategy`` loggers, which double as +``CustomLogger`` callbacks that record traffic in the host's routing cache. This module builds, +registers and retires them the way the Python router's ``routing_strategy_init``, +``_init_routing_groups`` and ``_get_override_strategy_selector`` do. It never reaches a Python +router core. +""" + +import threading +from collections.abc import Iterable, Mapping, Sequence +from itertools import chain +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, TypeAlias + +from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.router_strategy.base_routing_strategy import BaseRoutingStrategy +from litellm.router_strategy.least_busy import ( + CALL_IDENTITY, + SELECTION_RESERVATION_MAX_KEYS, + LeastBusyLoggingHandler, + call_id_of, +) +from litellm.router_strategy.lowest_cost import LowestCostLoggingHandler +from litellm.router_strategy.lowest_latency import LowestLatencyLoggingHandler +from litellm.router_strategy.lowest_tpm_rpm import LowestTPMLoggingHandler +from litellm.router_strategy.lowest_tpm_rpm_v2 import LowestTPMLoggingHandler_v2 +from litellm.types.router import RoutingGroup, RoutingStrategy + +if TYPE_CHECKING: + from litellm.caching.dual_cache import DualCache + from litellm.caching.in_memory_cache import InMemoryCache + from litellm.router_python_host import PythonHost + +Selector: TypeAlias = ( + LeastBusyLoggingHandler + | LowestCostLoggingHandler + | LowestLatencyLoggingHandler + | LowestTPMLoggingHandler + | LowestTPMLoggingHandler_v2 +) + +# The legacy router attribute that holds the default group's selector, per strategy. +SELECTOR_ATTRIBUTES: Final = MappingProxyType( + { + "least-busy": "leastbusy_logger", + "usage-based-routing": "lowesttpm_logger", + "usage-based-routing-v2": "lowesttpm_logger_v2", + "latency-based-routing": "lowestlatency_logger", + "cost-based-routing": "lowestcost_logger", + } +) + + +def normalize_strategy(strategy: object) -> str | None: + """A strategy as the string Python compares against (``_normalize_strategy``).""" + if isinstance(strategy, RoutingStrategy): + return strategy.value + return strategy if isinstance(strategy, str) else None + + +def build_selector( + strategy: str | None, + args: Mapping[str, object], + cache: "DualCache", + reservations: "InMemoryCache | None" = None, +) -> Selector | None: + """``_build_strategy_selector`` without registering: ``None`` for simple-shuffle and every + strategy without a selector. Every least-busy selector of a router keeps its pick + reservations in the router's one ``reservations`` store.""" + routing_args: Final = dict(args) + match strategy: + case "least-busy": + return LeastBusyLoggingHandler(router_cache=cache, reservation_store=reservations) + case "usage-based-routing": + return LowestTPMLoggingHandler(router_cache=cache, routing_args=routing_args) + case "usage-based-routing-v2": + return LowestTPMLoggingHandler_v2(router_cache=cache, routing_args=routing_args) + case "latency-based-routing": + return LowestLatencyLoggingHandler(router_cache=cache, routing_args=routing_args) + case "cost-based-routing": + return LowestCostLoggingHandler(router_cache=cache, routing_args={}) + case _: + return None + + +def _callbacks(host: "PythonHost") -> list[object]: # mutable-ok: the process list itself + """``litellm.callbacks``, which the host serves like its other callback lists.""" + return host.callback_list("callbacks") # pyright: ignore[reportArgumentType] # not in the CallbackList literal + + +class StrategySelectors: + """The selectors of one router: the default group's, each routing group's, and the lazily + built per-request override ones.""" + + def __init__(self, host: "PythonHost", cache: "DualCache") -> None: + from litellm.caching.in_memory_cache import InMemoryCache + + self._host: Final = host + self._cache: Final = cache + # `_core_least_busy_reservations`: the picks least-busy reserved, shared by its selectors. + self.reservations: Final = InMemoryCache(max_size_in_memory=SELECTION_RESERVATION_MAX_KEYS) + self._strategy: str | None = None + # The router's `routing_strategy`, which a direct `routing_strategy_init` leaves as it was. + self._configured: str | None = None + self._default: Selector | None = None + self._groups: dict[str, Selector] = {} # mutable-ok: replaced as routing groups change + self._group_strategies: frozenset[str] = frozenset() + self._overrides: dict[str, Selector | None] = {} # mutable-ok: filled lazily per strategy + self._lock: Final = threading.Lock() + + # -- building ------------------------------------------------------------------------------ + + def _register(self, selector: CustomLogger) -> None: + """``_register_router_selector``: least-busy also counts calls as they start.""" + host: Final = self._host + if isinstance(selector, LeastBusyLoggingHandler): + if isinstance(host.callback_list("input_callback"), list): # pyright: ignore[reportUnnecessaryIsInstance] # a process list a user may have reassigned + host.callbacks.add_litellm_input_callback(selector) + else: + host.set_callback_list("input_callback", [selector]) + if isinstance(_callbacks(host), list): # pyright: ignore[reportUnnecessaryIsInstance] # see above + host.callbacks.add_litellm_callback(selector) + + def _unregister(self, selectors: Sequence[object]) -> None: + live: Final = [selector for selector in selectors if selector is not None] + for selector in live: + if isinstance(selector, BaseRoutingStrategy): + selector.retire() + if live: + self._host.callbacks.drop_callbacks(live) + + def init_default(self, strategy: object, args: Mapping[str, object], *, configured: bool = True) -> None: + """``routing_strategy_init``: drop the old default and override selectors, build the new one. + ``configured``: ``strategy`` is the router's ``routing_strategy`` from now on.""" + self._unregister([self._default, *self._overrides.values()]) + self._overrides = {} + self._default = None + self._strategy = normalize_strategy(strategy) + if configured: + self._configured = self._strategy + self._default = build_selector(self._strategy, args, self._cache, self.reservations) + if self._default is not None: + self._register(self._default) + + def rebuild_default(self, args: Mapping[str, object]) -> None: + """``_apply_updated_routing_strategy_args``: relink the default selector to new args, keeping + the old one when they are invalid.""" + from pydantic import ValidationError + + from litellm._logging import verbose_router_logger + + if self._default is None or self._strategy != self._configured: + return + try: + rebuilt: Final = build_selector(self._strategy, args, self._cache, self.reservations) + except (TypeError, ValidationError): + verbose_router_logger.exception( + "Invalid routing_strategy_args %s for '%s'; keeping the previous ones", dict(args), self._strategy + ) + return + self._unregister([self._default]) + self._default = rebuilt + if rebuilt is not None: + self._register(rebuilt) + + def init_groups(self, groups: Sequence[tuple[str, str, Mapping[str, object]]]) -> None: + """``_replace_routing_groups``: one selector per group, from (name, strategy, args).""" + self._unregister(list(self._groups.values())) + built: Final = { + name: selector + for name, strategy, args in groups + if ( + selector := build_selector( + None if strategy == "priority" else strategy, args, self._cache, self.reservations + ) + ) + is not None + } + for selector in built.values(): + self._register(selector) + self._groups = built + self._group_strategies = frozenset(strategy for _, strategy, _ in groups) + + def retire(self) -> None: + self._unregister([self._default, *self._groups.values(), *self._overrides.values()]) + self.clear() + + def clear(self) -> None: + """Forget every selector, after the caller released them from the host lists.""" + self._default = None + self._groups = {} + self._overrides = {} + + def callback_selectors(self) -> tuple[Selector, ...]: + """``_callback_selectors``: the default group's selector and each routing group's.""" + return tuple(selector for selector in (self._default, *self._groups.values()) if selector is not None) + + def override_selectors(self) -> tuple[Selector, ...]: + """The per-request override selectors built so far.""" + return tuple(selector for selector in self._overrides.values() if selector is not None) + + @property + def default(self) -> Selector | None: + """The default selector of the router's ``routing_strategy``, if it has one.""" + return self._default if self._strategy == self._configured else None + + def attribute(self, name: str) -> Selector | None: + """A legacy ``*_logger`` attribute: the default selector when it is that strategy's.""" + return self._default if SELECTOR_ATTRIBUTES.get(self._strategy or "") == name else None + + def latency_args(self) -> Mapping[str, object] | None: + """The default latency selector's full routing args, as ``get_settings`` reports them.""" + if not isinstance(self._default, LowestLatencyLoggingHandler): + return None + reported: Final[object] = self._default.routing_args.json() # pyright: ignore[reportUnknownMemberType] # RoutingArgs.json is untyped + return as_str_mapping(reported) + + # -- picking ------------------------------------------------------------------------------- + + def selector_for( + self, strategy: str, scope: str, group: str | None, request: Mapping[str, object] | None + ) -> Selector | None: + """The selector a Rust ``select`` step names (``_get_routing_context``).""" + if scope == "group": + return self._groups.get(group or "") + if scope == "override": + return self._override(strategy, request) + return self._default if strategy == self._strategy else None + + def _override(self, strategy: str, request: Mapping[str, object] | None) -> Selector | None: + """``_get_override_strategy_selector`` and ``_bind_override_selector_to_request``.""" + if strategy == self._configured: + return self.default + with self._lock: + if strategy not in self._overrides: + self._overrides[strategy] = build_selector(strategy, {}, self._cache, self.reservations) + selector: Final = self._overrides[strategy] + if selector is not None and request is not None and strategy not in self._registered_strategies(): + from litellm.litellm_core_utils.litellm_logging import Logging + + logging_obj: Final = request.get("litellm_logging_obj") + if isinstance(logging_obj, Logging): + logging_obj.add_dynamic_callback(selector) + return selector + + def _registered_strategies(self) -> frozenset[str]: + return frozenset({*((self._configured,) if self._configured else ()), *self._group_strategies}) + + def is_override(self, strategy: str, selector: object) -> bool: + """Whether ``selector`` is a per-request override one, whose pre-call check the router runs + itself because it is not in the callback lists.""" + return selector is not None and self._overrides.get(strategy) is selector + + +async def pick_async( + strategy: str, + selector: Selector, + model: str, + deployments: list[dict[str, object]], # mutable-ok: the selectors take a list of deployment dicts + messages: object, + input: object, + request_kwargs: dict[str, object] | None, # mutable-ok: the latency selector reads it as given + reserve: bool = False, +) -> object: + """``_select_deployment_async``; ``reserve``: least-busy holds the pick for the request's call.""" + match selector: + case LeastBusyLoggingHandler() if strategy == "least-busy": + return await selector.async_get_available_deployments( + model_group=model, + healthy_deployments=deployments, + reserve=reserve, + call_id=call_id_of(CALL_IDENTITY.validate_python(request_kwargs or {})), + ) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selectors return untyped deployment dicts + case LowestTPMLoggingHandler() if strategy == "usage-based-routing": + return selector.get_available_deployments( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selectors return untyped deployment dicts + model_group=model, + healthy_deployments=deployments, + messages=messages, # pyright: ignore[reportArgumentType] # the request's messages, as given + input=input, # pyright: ignore[reportArgumentType] # same + ) + case LowestTPMLoggingHandler_v2() | LowestCostLoggingHandler() if strategy in ( + "usage-based-routing-v2", + "cost-based-routing", + ): + return await selector.async_get_available_deployments( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selectors return untyped deployment dicts + model_group=model, + healthy_deployments=deployments, + messages=messages, # pyright: ignore[reportArgumentType] # same + input=input, # pyright: ignore[reportArgumentType] # same + ) + case LowestLatencyLoggingHandler() if strategy == "latency-based-routing": + return await selector.async_get_available_deployments( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selectors return untyped deployment dicts + model_group=model, + healthy_deployments=deployments, + messages=messages, # pyright: ignore[reportArgumentType] # same + input=input, # pyright: ignore[reportArgumentType] # same + request_kwargs=request_kwargs, + ) + case _: + return None + + +def pick_sync( + strategy: str, + selector: Selector, + model: str, + deployments: list[dict[str, object]], # mutable-ok: see pick_async + messages: object, + input: object, + request_kwargs: dict[str, object] | None, # mutable-ok: see pick_async + reserve: bool = False, +) -> object: + """``_select_deployment_sync``: cost-based routing has no sync pick.""" + match selector: + case LeastBusyLoggingHandler() if strategy == "least-busy": + return selector.get_available_deployments( + model_group=model, + healthy_deployments=deployments, + reserve=reserve, + call_id=call_id_of(CALL_IDENTITY.validate_python(request_kwargs or {})), + ) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selectors return untyped deployment dicts + case LowestTPMLoggingHandler() | LowestTPMLoggingHandler_v2() if strategy in ( + "usage-based-routing", + "usage-based-routing-v2", + ): + return selector.get_available_deployments( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selectors return untyped deployment dicts + model_group=model, + healthy_deployments=deployments, + messages=messages, # pyright: ignore[reportArgumentType] # same + input=input, # pyright: ignore[reportArgumentType] # same + ) + case LowestLatencyLoggingHandler() if strategy == "latency-based-routing": + return selector.get_available_deployments( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the selectors return untyped deployment dicts + model_group=model, + healthy_deployments=deployments, + messages=messages, # pyright: ignore[reportArgumentType] # same + input=input, # pyright: ignore[reportArgumentType] # same + request_kwargs=request_kwargs, + ) + case _: + return None + + +async def routing_pre_call_checks(callbacks: Iterable[object], deployment: Mapping[str, object]) -> None: + """``async_routing_strategy_pre_call_checks``: every ``CustomLogger`` among the router's routing + callbacks (``_routing_callbacks``) checks the picked deployment before the call + (usage-based-routing-v2 counts its rpm here). A check's error fails the attempt; the core + records that failure like any other.""" + for callback in tuple(callbacks): + if isinstance(callback, CustomLogger): + await callback.async_pre_call_check(dict(deployment), None) # pyright: ignore[reportUnknownMemberType] # CustomLogger takes an untyped deployment dict + + +def routing_pre_call_checks_sync(callbacks: Iterable[object], deployment: Mapping[str, object]) -> None: + """``routing_strategy_pre_call_checks``: the sync check of each ``CustomLogger`` callback.""" + for callback in tuple(callbacks): + if isinstance(callback, CustomLogger): + callback.pre_call_check(dict(deployment)) # pyright: ignore[reportUnknownMemberType] # see above + + +def picked_id(picked: object) -> str | None: + """The id of the deployment a selector returned.""" + info: Final = as_str_mapping((as_str_mapping(picked) or {}).get("model_info")) or {} + found: Final = info.get("id") + return str(found) if found is not None else None + + +__all__ = [ + "SELECTOR_ATTRIBUTES", + "Selector", + "StrategySelectors", + "build_selector", + "group_documents", + "group_settings", + "member_map", + "normalize_strategy", + "parse_groups", + "pick_async", + "pick_sync", + "picked_id", + "routing_pre_call_checks", + "routing_pre_call_checks_sync", +] + + +def parse_groups( + groups_input: object, model_names: frozenset[str], aliases: frozenset[str] +) -> tuple[RoutingGroup, ...]: + """``_init_routing_groups``' validation: ``parse_routing_groups``, then a priority group may not + share its name with a model group or alias (a plain group only warns: its name is shadowed).""" + from litellm._logging import verbose_router_logger + from litellm.litellm_core_utils.routing_groups import ( + parse_routing_groups, # pyright: ignore[reportUnknownVariableType] # takes untyped dicts + ) + + if not groups_input or not isinstance(groups_input, list | tuple): + return () + groups: Final = parse_routing_groups( # pyright: ignore[reportUnknownVariableType] # returns RoutingGroup models + list(groups_input), # pyright: ignore[reportUnknownArgumentType] # validated by parse_routing_groups + known_model_names=model_names, + ) + for group in groups: + if group.group_name in model_names or group.group_name in aliases: + if group.routing_strategy == "priority": + raise ValueError("Priority routing group names must not shadow a model or alias") + verbose_router_logger.warning( + "routing_groups: group_name '%s' is shadowed by an existing model_name or model_group_alias; " + "the group's strategy still applies to its members, but the name is not callable until renamed.", + group.group_name, + ) + return groups + + +def group_documents(groups: Sequence[RoutingGroup]) -> list[Mapping[str, object]]: # mutable-ok: a JSON list + """The routing groups as the Rust core reads them.""" + return [ + { + "group_name": group.group_name, + "models": list(group.models), + "routing_strategy": group.routing_strategy, + **({"model_priorities": dict(group.model_priorities)} if group.model_priorities is not None else {}), + } + for group in groups + ] + + +def group_settings(groups: Sequence[RoutingGroup]) -> list[object]: # mutable-ok: the settings snapshot's list + """``get_settings()['routing_groups']``.""" + return [ + group.model_dump(exclude={"model_priorities"}) if group.model_priorities is None else group.model_dump() + for group in groups + ] + + +def member_map(groups: Sequence[RoutingGroup]) -> Mapping[str, str]: + """``_model_to_group``: each member model group of a non-priority routing group, to the group + (a model listed by two groups maps to the last).""" + kept: Final = [group for group in groups if group.routing_strategy != "priority"] + return dict(chain.from_iterable(dict.fromkeys(group.models, group.group_name).items() for group in kept)) diff --git a/litellm/router_rust/surface/README.md b/litellm/router_rust/surface/README.md new file mode 100644 index 00000000000..ad9c0c62ed3 --- /dev/null +++ b/litellm/router_rust/surface/README.md @@ -0,0 +1,14 @@ +# surface + +The Python `Router` API, kept over router-core's state so Python callers see today's behavior. router-core holds the state and the rules; these modules are views and adapters. + +- `registry`, `model_list`, `indexes`, `members`: the deployment list, indexes and lookups; writes become changesets +- `legacy_members`: the old public members outside the entry points +- `model_info`: model and group info, answering the `model_info` step's lookups +- `replay`: re-registers pricing after a price data reload +- `settings`: `update_settings` rules and the settings view +- `health`, `health_routing`, `retries`: outcome callbacks, health-check routing and retry answers +- `fallbacks`: fallback config validation +- `alerting`: Slack alerting + +A Rust host needs none of this. diff --git a/litellm/router_rust/surface/__init__.py b/litellm/router_rust/surface/__init__.py new file mode 100644 index 00000000000..74704783ecb --- /dev/null +++ b/litellm/router_rust/surface/__init__.py @@ -0,0 +1 @@ +"""The Python ``Router`` API kept over router-core's state, for Python callers.""" diff --git a/litellm/router_rust/surface/alerting.py b/litellm/router_rust/surface/alerting.py new file mode 100644 index 00000000000..760eecb35f4 --- /dev/null +++ b/litellm/router_rust/surface/alerting.py @@ -0,0 +1,33 @@ +"""The Rust core's Slack alerting: ``alerting_config`` built into a ``SlackAlerting`` logger on the +host, as the Python core's ``_initialize_alerting`` builds it.""" + +from typing import TYPE_CHECKING, Final + +from litellm._logging import verbose_router_logger + +if TYPE_CHECKING: + from litellm.integrations.SlackAlerting.slack_alerting import SlackAlerting + from litellm.router_python_host import PythonHost + from litellm.types.router import AlertingConfig + + +def initialize_alerting(host: "PythonHost", alerting_config: "AlertingConfig | None") -> "SlackAlerting | None": + """``_initialize_alerting``: a ``SlackAlerting`` logger with the config's threshold and webhook, + added to the host's callbacks, and its slow-response check to the host's success callbacks. + No config builds nothing.""" + from litellm.integrations.SlackAlerting.slack_alerting import SlackAlerting + + if alerting_config is None: + return None + logger: Final = SlackAlerting( + alerting_threshold=alerting_config.alerting_threshold, + alerting=["slack"], + default_webhook_url=alerting_config.webhook_url, + ) + host.callbacks.add_litellm_callback(logger) + host.callbacks.add_litellm_success_callback(logger.response_taking_too_long_callback) # pyright: ignore[reportUnknownArgumentType, reportUnknownMemberType] # SlackAlerting's untyped callback + verbose_router_logger.info("\033[94m\nInitialized Alerting for litellm.Router\033[0m\n") + return logger + + +__all__ = ["initialize_alerting"] diff --git a/litellm/router_rust/surface/fallbacks.py b/litellm/router_rust/surface/fallbacks.py new file mode 100644 index 00000000000..48fbc972b43 --- /dev/null +++ b/litellm/router_rust/surface/fallbacks.py @@ -0,0 +1,129 @@ +""" +Fallback configuration checks ``RustCore`` runs on the host: ``validate_fallbacks``, with the +Python router's error texts. router-core walks the fallbacks; this module only refuses a list it +could not walk the way the Python router would, before the core is built. +""" + +from collections.abc import Mapping, Sequence +from types import MappingProxyType +from typing import Final + +from litellm.router_utils.fallback_event_handlers import check_non_standard_fallback_format + + +def refuse_malformed_fallbacks(fallback_param: Sequence[object] | None) -> None: + """``Router.validate_fallbacks``: every entry is a one-key dict whose targets are a list (or a + client-side dict target).""" + if fallback_param is None: + return + for fallback_dict in fallback_param: + if not isinstance(fallback_dict, dict): + raise ValueError(f"Item '{fallback_dict}' is not a dictionary.") # noqa: TRY004 # the Python router's error class + if len(fallback_dict) != 1: # pyright: ignore[reportUnknownArgumentType] # only the size is read + raise ValueError( + f"Dictionary '{fallback_dict}' must have exactly one key, but has {len(fallback_dict)} keys." # pyright: ignore[reportUnknownArgumentType] # see above + ) + ((model_group, targets),) = fallback_dict.items() # pyright: ignore[reportUnknownVariableType, reportUnknownMemberType] # an entry as configured + entry: list[object] = [fallback_dict] # mutable-ok: the one-entry list the check reads + if isinstance(targets, list) or check_non_standard_fallback_format(fallbacks=entry): + continue + raise TypeError( + f"Fallbacks for '{model_group}' must be a list of model names, got '{targets}'. " + f"Use {{'{model_group}': ['{targets}']}}" + ) + + +def rejected_fallback_target(targets: Sequence[object]) -> Exception | None: + """The error ``run_async_fallback`` raises before its walk when a chain, from any list and of + any level, has a dict target a request may not set (a server-owned federation field, an + ``oidc/`` api key): every target of that walk is refused.""" + from litellm.litellm_core_utils.credential_accessor import reject_api_key_secret_reference + from litellm.types.router import reject_server_owned_wif_params + + for target in targets: + if isinstance(target, dict): + try: + reject_server_owned_wif_params(target) # pyright: ignore[reportUnknownArgumentType] # a chain as configured + reject_api_key_secret_reference(target) # pyright: ignore[reportUnknownArgumentType] # see above + except Exception as error: # noqa: BLE001 # the walk's own refusal, reported as its failure + return error + return None + + +# The `mock_testing_*` flags the router reads, and the mock failure each asks router-core for. +MOCK_FLAGS: Final = MappingProxyType( + { + "mock_testing_fallbacks": "fallbacks", + "mock_testing_context_fallbacks": "context_window", + "mock_testing_content_policy_fallbacks": "content_policy", + "mock_testing_rate_limit_error": "rate_limit", + } +) + + +def mock_failure(request: Mapping[str, object]) -> str | None: + """The mock failure a request asks for (``MockRouterTestingParams.from_kwargs``, then + ``_handle_mock_testing_rate_limit_error``): the first fallback flag that is ``True`` (a string + is read as a bool), else the rate limit flag when it is ``True`` itself.""" + from litellm.secret_managers.main import str_to_bool + + for flag in ("mock_testing_fallbacks", "mock_testing_context_fallbacks", "mock_testing_content_policy_fallbacks"): + value = request.get(flag) + if (str_to_bool(value) if isinstance(value, str) else value) is True: + return MOCK_FLAGS[flag] + return "rate_limit" if request.get("mock_testing_rate_limit_error") is True else None + + +def mock_error( + mock: str, model: str, num_retries: object, request: Mapping[str, object], configured: Mapping[str, object] +) -> Exception: + """The exception the Python router raises for a mock failure; ``configured`` holds the + router's fallback lists, which the request's own replace.""" + import litellm.exceptions as litellm_exceptions + + def listed(name: str) -> object: + return request.get(name, configured.get(name)) + + if mock == "rate_limit": + return litellm_exceptions.RateLimitError( + model=model, + llm_provider="", + message=f"This is a mock exception for model={model}, to trigger a rate limit error.", + num_retries=num_retries if isinstance(num_retries, int) else None, + ) + if mock == "context_window": + return litellm_exceptions.ContextWindowExceededError( + model=model, + llm_provider="", + message=f"This is a mock exception for model={model}, to trigger a fallback. \ + Context_Window_Fallbacks={listed('context_window_fallbacks')}", + ) + if mock == "content_policy": + return litellm_exceptions.ContentPolicyViolationError( + model=model, + llm_provider="", + message=f"This is a mock exception for model={model}, to trigger a fallback. \ + Context_Policy_Fallbacks={listed('content_policy_fallbacks')}", + ) + return litellm_exceptions.InternalServerError( + model=model, + llm_provider="", + message=f"This is a mock exception for model={model}, to trigger a fallback. Fallbacks={listed('fallbacks')}", + ) + + +class RustFallbacks: + """Fallback members served on the host.""" + + def validate_fallbacks(self, fallback_param: Sequence[object] | None) -> None: + refuse_malformed_fallbacks(fallback_param) + + +__all__ = [ + "MOCK_FLAGS", + "RustFallbacks", + "mock_error", + "mock_failure", + "refuse_malformed_fallbacks", + "rejected_fallback_target", +] diff --git a/litellm/router_rust/surface/health.py b/litellm/router_rust/surface/health.py new file mode 100644 index 00000000000..5547471855a --- /dev/null +++ b/litellm/router_rust/surface/health.py @@ -0,0 +1,558 @@ +""" +The deployment outcome callbacks ``RustCore`` serves as members: ``deployment_callback_on_failure``, +``deployment_callback_on_success`` and ``sync_deployment_callback_on_success``. router-core counts +the outcome and decides the cooldown; this module reads litellm's logging kwargs, drops the +failures the Python router does not hold against the deployment, and drives the Rust call. The +stream wrappers report a stream's outcome through the same members when the stream ends. +""" + +from collections.abc import Mapping +from datetime import datetime +from typing import TYPE_CHECKING, Final, Literal + +from litellm.litellm_core_utils.core_helpers import as_str_mapping + +if TYPE_CHECKING: + from litellm.router_rust.steps.callbacks import OptionalChecks + from litellm.router_rust.surface.registry import HostRegistry + from litellm.router_utils.cooldown_cache import CooldownCache + from litellm.rust_bridge._native import ( + RouterCall, + RouterCoreHandle, + _FailureReportSteps, # pyright: ignore[reportPrivateUsage] # the stub's step shapes + _SuccessReportSteps, # pyright: ignore[reportPrivateUsage] # see above + ) + from litellm.types.router import Deployment + + +def _cast_status(exception_status: object) -> int | None: + if isinstance(exception_status, int) and not isinstance(exception_status, bool): + return exception_status + if isinstance(exception_status, str): + try: + return int(exception_status) + except ValueError: + return 500 + return None + + +def failure_status(exception_status: object) -> int | None: + """``cast_exception_status_to_int``: a number as given, a numeric string read as one, any + other string 500. A number no status can hold reads as no status.""" + status: Final = _cast_status(exception_status) + return status if status is not None and 0 <= status <= 65535 else None + + +def _logged_deployment_id(kwargs: Mapping[str, object]) -> object: + """``litellm_params.model_info.id`` of a logged call.""" + litellm_params: Final = as_str_mapping(kwargs.get("litellm_params")) or {} + return (as_str_mapping(litellm_params.get("model_info")) or {}).get("id") + + +def first_cooldown(*sources: Mapping[str, object] | None) -> int | float | None: + """``_first_present(*sources, key="cooldown_time")``, the number as it was written.""" + for source in sources: + value = source.get("cooldown_time") if source is not None else None + if isinstance(value, int | float) and not isinstance(value, bool): + return value + return None + + +def _configured_cooldown(model_info: object, litellm_params: Mapping[str, object]) -> float | None: + """``first_cooldown`` of a logged call, as the float router-core takes.""" + seconds: Final = first_cooldown(as_str_mapping(model_info), litellm_params) + return None if seconds is None else float(seconds) + + +def python_cooldown_time(seconds: float, *sources: float | None) -> float: + """``seconds`` as ``deployment_callback_on_failure`` hands them on. Router-core's duration is + always a float; Python's is the number that won its precedence, an int or a float as it was + written. ``sources`` run in that precedence, and only the type is read from them.""" + return next((source for source in sources if source is not None and source == seconds), seconds) + + +def _fallback_cooldown(deployment: "Deployment | None") -> float | None: + """``first_cooldown`` of the deployment a failed hop tried, as ``_core_get_model_info`` lists it.""" + if deployment is None: + return None + listed: Final = deployment.model_dump() + return first_cooldown(as_str_mapping(listed.get("model_info")), as_str_mapping(listed.get("litellm_params"))) + + +def _deployment_cooldown(deployment: Mapping[str, object]) -> float | None: + """``_configured_cooldown`` of a deployment as listed.""" + return _configured_cooldown(deployment.get("model_info"), as_str_mapping(deployment.get("litellm_params")) or {}) + + +def logged_call(op: str, kwargs: Mapping[str, object], started: datetime | None = None) -> Mapping[str, object]: + """The logging kwargs ``deployment_callback_on_failure`` would read for a call made with + ``kwargs``: the call's logging object's (a proxy request carries one), else what the request says. + Read before the failure logger stamps the call's ``end_time``, so it is stamped here.""" + ended: Final = datetime.now() # noqa: DTZ005 # naive to match the logging pipeline's api_call_start_time + details: Final = as_str_mapping(getattr(kwargs.get("litellm_logging_obj"), "model_call_details", None)) + call_type: Final = op.rsplit(".", 1)[-1] + if details is not None: + return {"call_type": call_type, **details, "end_time": ended} + fields: Final = ("metadata", "litellm_metadata", "client_side_timeout", "timeout") + return { + "call_type": call_type, + "litellm_params": {name: kwargs.get(name) for name in fields}, + "start_time": started, + "end_time": ended, + } + + +def _authenticates_per_caller(litellm_params: object) -> bool: + """``github_copilot_per_user_credential_name`` in ``_should_run_cooldown_logic``. Per-user params + with no credential raise there, which ends Python's failure callback short of any cooldown.""" + from litellm.exceptions import BadRequestError + from litellm.llms.github_copilot.per_user_auth import github_copilot_per_user_credential_name + + try: + return github_copilot_per_user_credential_name(litellm_params) is not None + except BadRequestError: + return True + + +def failure_already_logged(kwargs: Mapping[str, object], event: Literal["async_failure", "sync_failure"]) -> bool: + """``should_run_logging``: a logging object logs one failure a request. The attempts of a request + that shares one (``litellm_logging_obj``) after the first logged failure run no failure callback; + without one, every litellm call logs on its own.""" + from litellm.litellm_core_utils.litellm_logging import Logging + + logging_obj: Final = kwargs.get("litellm_logging_obj") + return isinstance(logging_obj, Logging) and logging_obj.model_call_details.get(f"has_logged_{event}") is True + + +def _success_target(kwargs: Mapping[str, object]) -> tuple[str, Mapping[str, object]] | None: + """The deployment id and metadata a success callback counts under, or None.""" + params: Final = as_str_mapping(kwargs.get("litellm_params")) or {} + metadata: Final = as_str_mapping(params.get("metadata")) + if metadata is None: + return None + model_info: Final = as_str_mapping(params.get("model_info")) or {} + deployment_id: Final = model_info.get("id") + if metadata.get("model_group") is None or deployment_id is None: + return None + return str(deployment_id), metadata + + +class RustHealthCallbacks: + """Outcome callbacks read into the Rust core's health state.""" + + _handle: "RouterCoreHandle" + _cooldown_given: object + + def _drive_sync_steps(self, call: "RouterCall[_FailureReportSteps | _SuccessReportSteps]") -> Mapping[str, object]: + raise NotImplementedError + + async def _drive_cache_steps( + self, call: "RouterCall[_FailureReportSteps | _SuccessReportSteps]" + ) -> Mapping[str, object]: + raise NotImplementedError + + def _sync_allowed_fails(self) -> None: + raise NotImplementedError + + def _core_get_allowed_fails_from_policy(self, exception: Exception) -> int | None: + """The router ``allowed_fails_policy``'s allowance for this exception, decided by router-core.""" + from litellm.router_rust.core import attempt_failure + + return self._handle.allowed_fails_for(dict(attempt_failure(exception))) + + def _deployment_of(self, deployment_id: object) -> "Deployment | None": + # RustCore sets `_hosted` as an attribute in its constructor. + hosted: Final[HostRegistry] = self.__dict__["_hosted"] # pyright: ignore[reportAny] # RustCore's own attribute + return hosted._core_get_deployment(model_id=deployment_id) if isinstance(deployment_id, str) else None # pyright: ignore[reportPrivateUsage] # the host registry's id lookup + + def deployment_tracks_usage(self, deployment_id: object, model_group: object) -> bool: + """``_cached_deployment_tracks_usage``. A deployment whose model is not mapped raises there, + which ends Python's usage write, so it reads as not tracked.""" + # RustCore sets `_hosted` as an attribute in its constructor. + hosted: Final[HostRegistry] = self.__dict__["_hosted"] # pyright: ignore[reportAny] # RustCore's own attribute + if not isinstance(deployment_id, str) or not isinstance(model_group, str): + return False + try: + return hosted.cached_deployment_tracks_usage(deployment_id, model_group) + except Exception: # noqa: BLE001 # as `deployment_callback_on_success` swallows it + return False + + def cooldown_event(self, deployment_id: str, exception_status: object, cooldown_time: float | None) -> None: + """The end of ``set_cooldown_deployments``, once the cooldown is written: the cooldown event + Prometheus reads, as a task of the running loop. Outside one this raises ``RuntimeError``.""" + import asyncio + + from litellm.router_api import RoutingContext + from litellm.router_utils import cooldown_handlers + + _ = asyncio.get_running_loop() + _ = asyncio.create_task( # fire and forget, as set_cooldown_deployments schedules it + cooldown_handlers.router_cooldown_event_callback( + ctx=RoutingContext(self), # pyright: ignore[reportArgumentType] # the core's RoutingContext + deployment_id=deployment_id, + exception_status=exception_status, # pyright: ignore[reportArgumentType] # the status as raised + cooldown_time=cooldown_time, + ) + ) + + def cooldown_event_on_own_loop( + self, deployment_id: str, exception_status: object, cooldown_time: float | None + ) -> None: + """``cooldown_event`` for a sync walk ``function_with_fallbacks`` would run on its private + loop: ``set_cooldown_deployments`` finds that loop however the caller runs, and the event's + task keeps what it raises to itself.""" + import asyncio + + from litellm.litellm_core_utils import asyncify + + async def fire() -> None: + self.cooldown_event(deployment_id, exception_status, cooldown_time) + await asyncio.sleep(0) + + asyncify.run_async_function(fire) # pyright: ignore[reportUnknownMemberType] # the untyped sync bridge + + def python_cooldown(self, seconds: float, configured: float | None = None, error: object = None) -> float: + """The ``time_to_cooldown`` Python hands ``set_cooldown_deployments``, for router-core's + ``seconds``. A failure callback's precedence is the ``configured`` number, then the ``retry-after`` + header of ``error``, then the router's own; a path passing neither hands on the router's own.""" + from litellm.router_rust.core import retry_after_seconds + + retry_after: Final = retry_after_seconds(error) if isinstance(error, BaseException) else None + default: Final = self._cooldown_given + return python_cooldown_time( + seconds, + configured, + None if retry_after is None else int(retry_after), + default if isinstance(default, int | float) else None, + ) + + def cooled_down( + self, + done: Mapping[str, object], + deployment_id: object, + exception_status: object, + *, + own_loop: bool = False, + configured: float | None = None, + error: object = None, + ) -> bool: + """Whether a failure report cooled the deployment down, with its cooldown event, which + carries ``python_cooldown`` of ``configured`` and ``error``.""" + cooled: Final = bool(done.get("cooled")) + if cooled and isinstance(deployment_id, str): + seconds: Final = done.get("cooldown_time") + event: Final = self.cooldown_event_on_own_loop if own_loop else self.cooldown_event + event( + deployment_id, + exception_status, + self.python_cooldown(seconds, configured, error) if isinstance(seconds, float) else None, + ) + return cooled + + def per_user_deployment(self, deployment_id: object) -> bool: + """The failed deployment authenticates per caller (``_should_run_cooldown_logic``), which is + all ``set_cooldown_deployments`` reads when it is called without the request's kwargs.""" + deployment: Final = self._deployment_of(deployment_id) + return deployment is not None and _authenticates_per_caller(deployment.litellm_params) + + def failure_exits( + self, exception: object, logged: Mapping[str, object], deployment_id: object + ) -> Mapping[str, bool]: + """What the Python router does not hold against the deployment, for every failure it logs. + ``outside_deployment``: ``deployment_callback_on_failure``'s early exits, counting nothing. + ``caller_scoped``: ``_should_run_cooldown_logic``'s per-caller exits, counted but not cooled; + its exits on the exception's class are router-core's (``FailureKind``).""" + from litellm.router_utils.cooldown_handlers import ( + _is_per_user_provider_request, # pyright: ignore[reportPrivateUsage] # the cooldown check's own rule + is_background_response_poll_not_found, + is_caller_scoped_auth_failure, + is_caller_timeout_408, + is_failure_outside_selected_deployment, + is_video_lookup_not_found, + ) + + status: Final[object] = getattr(exception, "status_code", "") + litellm_params: Final = as_str_mapping(logged.get("litellm_params")) or {} + outside: Final = ( + is_failure_outside_selected_deployment(exception if isinstance(exception, BaseException) else None) + or (isinstance(exception, Exception) and is_background_response_poll_not_found(exception, litellm_params)) + or is_video_lookup_not_found(exception, logged) + or is_caller_timeout_408(logged, status) # pyright: ignore[reportArgumentType] # the status as raised + or is_caller_scoped_auth_failure(self._deployment_of(deployment_id), status) # pyright: ignore[reportArgumentType] # see above + ) + return { + "outside_deployment": outside, + "caller_scoped": _is_per_user_provider_request(logged) or self.per_user_deployment(deployment_id), + } + + def trigger_fallback_cooldown( + self, kwargs: Mapping[str, object], exception: object, generic: bool, *, own_loop: bool = False + ) -> None: + """The failed fallback hop's ``_trigger_cooldown_for_failed_deployment``, which runs only when + the request's logging object blocked the hop's failure callbacks. ``generic``: the call's kwargs + carry ``original_generic_function``. ``own_loop``: see ``cooldown_event_on_own_loop``.""" + from litellm._logging import verbose_router_logger + from litellm.router_utils.fallback_event_handlers import ( + _failure_callbacks_blocked_logging_object, # pyright: ignore[reportPrivateUsage] # the fallback path's own rule + ) + + blocked: Final = _failure_callbacks_blocked_logging_object(kwargs) + if blocked is None or not isinstance(exception, Exception): + return + try: + call: Final = self._fallback_failure_call(kwargs, exception, blocked.model_call_details, generic) + if call is not None: + _ = self.cooled_down( + self._drive_sync_steps(call), + getattr(exception, "failed_deployment_id", None), + getattr(exception, "status_code", ""), + own_loop=own_loop, + configured=_fallback_cooldown( + self._deployment_of(getattr(exception, "failed_deployment_id", None)) + ), + error=exception, + ) + except Exception as e: # noqa: BLE001 # best effort, as the Python helper: it never breaks the fallback response + verbose_router_logger.debug("Error triggering cooldown for fallback deployment: %s", e) + + def _fallback_failure_call( + self, + kwargs: Mapping[str, object], + exception: Exception, + model_call_details: Mapping[str, object], + generic: bool, + ) -> "RouterCall[_FailureReportSteps] | None": + """The Rust call recording a failed hop, or None past the exits of + ``_trigger_cooldown_for_failed_deployment``: another list than ``failure_exits``, checked per + failed hop. The selection tag is not on it; a stream stall and a generic call's 404 are.""" + from litellm.router_rust.core import attempt_failure + from litellm.router_utils.cooldown_handlers import ( + _is_per_user_provider_request, # pyright: ignore[reportPrivateUsage] # the cooldown check's own rule + cast_exception_status_to_int, + is_advisor_orchestration_failure, + is_caller_scoped_auth_failure, + is_caller_timeout_408, + is_stream_stall, + ) + from litellm.router_utils.fallback_event_handlers import ( + _REQUEST_SCOPED_STATUS_CODES, # pyright: ignore[reportPrivateUsage] # the fallback path's own rule + ) + + self._sync_allowed_fails() + exception_status: Final[object] = getattr(exception, "status_code", "") + if ( + is_advisor_orchestration_failure(exception) + or is_stream_stall(exception) + or (generic and cast_exception_status_to_int(exception_status) in _REQUEST_SCOPED_STATUS_CODES) # pyright: ignore[reportArgumentType] # the status as raised + or is_caller_timeout_408(model_call_details, exception_status, ended=datetime.now()) # pyright: ignore[reportArgumentType] # noqa: DTZ005 # see logged_call + ): + return None + deployment_id: Final[object] = getattr(exception, "failed_deployment_id", None) + if not isinstance(deployment_id, str): + return None + deployment: Final = self._deployment_of(deployment_id) + if is_caller_scoped_auth_failure(deployment, exception_status): # pyright: ignore[reportArgumentType] # see above + return None + return self._handle.report_failure( + deployment_id, + { + **attempt_failure(exception), + "status": failure_status(exception_status), + "caller_scoped": _is_per_user_provider_request(kwargs) or self.per_user_deployment(deployment_id), + }, + deployment_cooldown=True, + count_only=exception_status == "", + cooldown_time=None if deployment is None else _deployment_cooldown(deployment.model_dump()), + ) + + def deployment_callback_on_failure( + self, + kwargs: Mapping[str, object], + completion_response: object, + start_time: object, + end_time: object, + ) -> bool: + """Count the failure and cool the deployment down when the rules say so.""" + call: Final = self._failure_call(kwargs) + litellm_params: Final = as_str_mapping(kwargs.get("litellm_params")) or {} + return call is not None and self.cooled_down( + self._drive_sync_steps(call), + _logged_deployment_id(kwargs), + getattr(kwargs.get("exception"), "status_code", ""), + configured=first_cooldown(as_str_mapping(litellm_params.get("model_info")), litellm_params), + error=kwargs.get("exception"), + ) + + async def report_stream_failure( + self, kwargs: Mapping[str, object], callbacks: Mapping[str, bool] | None = None + ) -> None: + """A stream's failure after its attempt returned it, as an async call's failure callbacks + record it: counted, cooled down by the rules, and one more request this minute + (``async_deployment_callback_on_failure``). No cooldown event: the stream logs its failure + through ``dispatch_failure_handlers``, whose sync callbacks run in an executor thread, where + ``set_cooldown_deployments`` has no loop to schedule one on.""" + call: Final = self._failure_call(kwargs, counts_request=True, callbacks=callbacks) + if call is not None: + _ = await self._drive_cache_steps(call) + + def report_stream_failure_sync( + self, kwargs: Mapping[str, object], callbacks: Mapping[str, bool] | None = None + ) -> None: + """``report_stream_failure`` for a sync stream: a sync call's failure callback counts no request. + No cooldown event: the stream logs its failure in a ``threading.Thread`` of its own, which + has no running loop whatever the consumer's thread has.""" + call: Final = self._failure_call(kwargs, callbacks=callbacks) + if call is not None: + _ = self._drive_sync_steps(call) + + def _failure_call( + self, + kwargs: Mapping[str, object], + counts_request: bool = False, + callbacks: Mapping[str, bool] | None = None, + ) -> "RouterCall[_FailureReportSteps] | None": + """The Rust call recording a logged failure, or None when it records nothing: one the Python + router does not hold against the deployment is still a request of the minute + (``async_deployment_callback_on_failure`` makes none of the failure callback's exits).""" + from litellm.litellm_core_utils import core_helpers + from litellm.router_rust.core import attempt_failure + + self._sync_allowed_fails() + exception: Final = kwargs.get("exception") + litellm_params: Final = as_str_mapping(kwargs.get("litellm_params")) or {} + model_info: Final = litellm_params.get("model_info", {}) + info: Final = as_str_mapping(model_info) + deployment_id: Final = info.get("id") if info is not None else None + if deployment_id is None: + return None + exits: Final = self.failure_exits(exception, kwargs, deployment_id) + if exits["outside_deployment"] and not counts_request: + return None + exception_status: Final[object] = getattr(exception, "status_code", "") + described: Final[Mapping[str, object]] = ( + attempt_failure(exception) if isinstance(exception, BaseException) else {"ok": False, "kind": "APIError"} + ) + failure: Final = {**described, **exits, "status": failure_status(exception_status)} + metadata: Final[object] = core_helpers.get_litellm_metadata_from_kwargs(dict(kwargs)) # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # an untyped helper's dict + group: Final = (as_str_mapping(metadata) or {}).get("model_group") # pyright: ignore[reportUnknownArgumentType] # read as a mapping + usage_model: Final = (as_str_mapping(metadata) or {}).get("deployment") # pyright: ignore[reportUnknownArgumentType] # see above + return self._handle.report_failure( + str(deployment_id), + failure, + deployment_cooldown=True, + count_only=exception_status == "", + requested_group=group if isinstance(group, str) else None, + cooldown_time=_configured_cooldown(model_info, litellm_params), + counts_request=counts_request, + usage_model=usage_model if isinstance(usage_model, str) else None, + callbacks=callbacks, + ) + + def sync_deployment_callback_on_success( + self, + kwargs: Mapping[str, object], + completion_response: object, + start_time: object, + end_time: object, + ) -> str | None: + """Count a success this minute; returns the counter's key.""" + return self.report_stream_success_sync(kwargs) + + def report_stream_success_sync( + self, kwargs: Mapping[str, object], callbacks: Mapping[str, bool] | None = None + ) -> str | None: + """``sync_deployment_callback_on_success``, for a sync stream that ended.""" + from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type + + if is_batch_retrieve_call_type(kwargs.get("call_type")): + return None + target: Final = _success_target(kwargs) + if target is None: + return None + key: Final = self._drive_sync_steps(self._handle.count_success(target[0], callbacks)).get("key") + return key if isinstance(key, str) else None + + async def repin_after_success(self, kwargs: Mapping[str, object], completion_response: object) -> None: + """The session re-pin ``deployment_callback_on_success`` runs for a success logged against a + deployment the router serves (``_repin_session_after_success``). The Rust core runs it from the + attempt itself, or from the stream wrapper when a stream ends.""" + from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type + + call_type: Final = kwargs.get("call_type") + if call_type == "_arealtime" or is_batch_retrieve_call_type(call_type): + return + target: Final = _success_target(kwargs) + # RustCore sets these as attributes in its constructor. + hosted: Final[HostRegistry] = self.__dict__["_hosted"] # pyright: ignore[reportAny] # RustCore's own attribute + if target is None or hosted._core_get_deployment(model_id=target[0]) is None: # pyright: ignore[reportPrivateUsage] # the host registry's id lookup + return + checks: Final[OptionalChecks] = self.__dict__["_checks"] # pyright: ignore[reportAny] # see above + cooldowns: Final[CooldownCache] = self.__dict__["_cooldowns"] # pyright: ignore[reportAny] # see above + await checks.repin_session_after_success( + as_str_mapping(kwargs.get("litellm_params")) or {}, completion_response, cooldowns + ) + + async def deployment_callback_on_success( + self, + kwargs: Mapping[str, object], + completion_response: object, + start_time: object, + end_time: object, + ) -> None: + """Count a success and the call's tokens and request against a tracked deployment.""" + await self.report_stream_success(kwargs, completion_response) + + async def report_stream_success( + self, + kwargs: Mapping[str, object], + completion_response: object, + callbacks: Mapping[str, bool] | None = None, + ) -> None: + """``deployment_callback_on_success``, for a stream that ended. The re-pin is the host's half + of that callback, so it reads ``callbacks`` here.""" + from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type + from litellm.router_utils.router_callbacks.track_deployment_metrics import get_counted_usage_tokens + + call_type: Final = kwargs.get("call_type") + if call_type == "_arealtime" or is_batch_retrieve_call_type(call_type): + return + logged: Final = as_str_mapping(kwargs.get("standard_logging_object")) + if logged is None: + return + target: Final = _success_target(kwargs) + if target is None: + return + if (callbacks or {}).get("success", True): + await self.repin_after_success(kwargs, completion_response) + tokens: Final[object] = logged.get("total_tokens", 0) + total: Final = float(tokens) if isinstance(tokens, int | float) else 0.0 + counted: Final = get_counted_usage_tokens(as_str_mapping(kwargs.get("litellm_params")) or {}) + usage_model: Final = target[1].get("deployment") + await self._drive_cache_steps( + self._handle.report_success( + target[0], + total if counted is None else max(0.0, total - counted), + 1.0 if counted is None else 0.0, + usage_model if isinstance(usage_model, str) else None, + self.deployment_tracks_usage(target[0], target[1].get("model_group")), + callbacks, + ) + ) + + async def count_realtime_session_success(self, deployment_id: str) -> None: + """``increment_deployment_successes_for_current_minute`` for a realtime session that ended + cleanly: a success alone, as ``deployment_callback_on_success`` skips ``_arealtime``. A + counter that cannot be written does not fail the served session.""" + from litellm._logging import verbose_router_logger + + try: + await self._drive_cache_steps(self._handle.count_success(deployment_id)) + except Exception as e: # noqa: BLE001 # as the Rust call loop treats a success it could not record + verbose_router_logger.debug("count_realtime_session_success: not recorded. Got - %s", e) + + +__all__ = [ + "RustHealthCallbacks", + "failure_status", + "logged_call", +] diff --git a/litellm/router_rust/surface/health_routing.py b/litellm/router_rust/surface/health_routing.py new file mode 100644 index 00000000000..46542bf9af2 --- /dev/null +++ b/litellm/router_rust/surface/health_routing.py @@ -0,0 +1,160 @@ +""" +Health-check routing, allowed-fails policies and the failover flags on the host side of the Rust +core: how the constructor resolves them, the static document router-core reads them from, and the +``health()`` members that read the registry's live model list or the background health checks' +results. router-core makes every routing decision (the health-check filter, the cooldown rules, +weighted failover); this module only reads Python values into its documents and back. + +The rules are the Python router core's, ported (never imported). +""" + +import dataclasses +from collections.abc import Mapping, Sequence +from typing import TYPE_CHECKING, Final + +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.router_utils.health_state_cache import DeploymentHealthCache +from litellm.types.router import AllowedFailsPolicy + +if TYPE_CHECKING: + from litellm.caching.caching import DualCache + from litellm.router_config import RouterConfig + from litellm.types.router import Deployment, DeploymentTypedDict + +HEALTH_STATE_KEY: Final = DeploymentHealthCache.CACHE_KEY +# The failover flags the Python core keeps as plain router attributes, with their defaults. +FAILOVER_FLAGS: Final = ("enable_weighted_failover", "fallback_on_unsupported_params") + + +def resolved_allowed_fails_policy(value: object) -> AllowedFailsPolicy | None: + """The router's ``allowed_fails_policy`` as the constructor keeps it: a dict is read into an + ``AllowedFailsPolicy`` (a bad field raises the model's own error), a policy is kept, anything + else is no policy.""" + if isinstance(value, AllowedFailsPolicy): + return value + if isinstance(value, dict): + return AllowedFailsPolicy.model_validate(value) + return None + + +def _staleness(threshold: object) -> float: + """``health_check_staleness_threshold or DEFAULT_HEALTH_CHECK_INTERVAL * multiplier``.""" + from litellm.constants import DEFAULT_HEALTH_CHECK_INTERVAL, DEFAULT_HEALTH_CHECK_STALENESS_MULTIPLIER + + given: Final = threshold if isinstance(threshold, int | float) and not isinstance(threshold, bool) else None + return float(given or (DEFAULT_HEALTH_CHECK_INTERVAL * DEFAULT_HEALTH_CHECK_STALENESS_MULTIPLIER)) + + +@dataclasses.dataclass(frozen=True, slots=True) +class HealthRouting: + """The health-check routing settings, as the constructor resolves them.""" + + enable_health_check_routing: bool = False + health_check_staleness: float = 600.0 + health_check_ignore_transient_errors: bool = False + background_health_check_model_groups: frozenset[str] | None = None + + @classmethod + def of(cls, config: "RouterConfig") -> "HealthRouting": + groups: Final = config.get("background_health_check_model_groups") + return cls( + enable_health_check_routing=bool(config.get("enable_health_check_routing")), + health_check_staleness=_staleness(config.get("health_check_staleness_threshold")), + health_check_ignore_transient_errors=bool(config.get("health_check_ignore_transient_errors")), + background_health_check_model_groups=frozenset(groups) if groups is not None else None, # pyright: ignore[reportArgumentType, reportUnknownArgumentType] # any iterable of names, as the Python core takes it + ) + + def static_document(self) -> Mapping[str, object]: + groups: Final = self.background_health_check_model_groups + return { + "enable_health_check_routing": True if self.enable_health_check_routing else None, + "health_check_staleness_threshold": self.health_check_staleness, + # Only a string can name a model group, so anything else in scope matches nothing. + "background_health_check_model_groups": sorted(name for name in groups if isinstance(name, str)) # pyright: ignore[reportUnnecessaryIsInstance] # `of` keeps any iterable the constructor was given + if groups is not None + else None, + } + + def health_checks(self, cache: "DualCache") -> DeploymentHealthCache: + return DeploymentHealthCache(cache=cache, staleness_threshold=self.health_check_staleness) + + +def failover_document(plain: Mapping[str, object]) -> Mapping[str, object]: + """The failover flags router-core reads, from the router's plain attributes (read for + truthiness, as the Python core's checks read them).""" + return { + "enable_weighted_failover": True if plain.get("enable_weighted_failover") else None, + "fallback_on_unsupported_params": False if not plain.get("fallback_on_unsupported_params", True) else None, + } + + +def _model_info(deployment: Mapping[str, object]) -> Mapping[str, object]: + return as_str_mapping(deployment.get("model_info")) or {} + + +def is_blocked(deployment: "Deployment") -> bool: + """``_core_is_deployment_blocked``.""" + model_info: Final[object | None] = getattr(deployment, "model_info", None) + if model_info is None: + return False + return getattr(model_info, "blocked", None) is True + + +def all_blocked(deployments: "Sequence[DeploymentTypedDict]") -> bool: + """``_core_are_all_deployments_blocked``.""" + return len(deployments) > 0 and all( + _model_info(deployment).get("blocked") is True # pyright: ignore[reportArgumentType] # a deployment dict + for deployment in deployments + ) + + +def fully_blocked_model_names( + model_list: Sequence[Mapping[str, object]], +) -> set[str]: # mutable-ok: the core's type, a fresh set + """``_core_get_fully_blocked_model_names``: groups whose every deployment is blocked.""" + blocked_by_name: Final[dict[str, bool]] = {} # mutable-ok: built here + for deployment in model_list: + name = deployment.get("model_name") or "" + if not isinstance(name, str) or not name: + continue + blocked = _model_info(deployment).get("blocked") is True + blocked_by_name[name] = blocked_by_name.get(name, True) and blocked + return {name for name, fully in blocked_by_name.items() if fully} + + +async def fully_unhealthy_model_names( + model_list: Sequence[Mapping[str, object]], health_checks: DeploymentHealthCache, policy: object +) -> set[str]: # mutable-ok: the core's type, a fresh set + """``_core_async_get_fully_unhealthy_model_names``: groups (and team public names) whose + every deployment failed its health check; nothing under an allowed_fails_policy.""" + if policy is not None: + return set() + unhealthy_ids: Final = await health_checks.async_get_unhealthy_deployment_ids() + if not unhealthy_ids: + return set() + unhealthy_by_name: Final[dict[str, bool]] = {} # mutable-ok: built here + for deployment in model_list: + model_info = _model_info(deployment) + names = [deployment.get("model_name") or ""] + team_public_model_name = model_info.get("team_public_model_name") + if team_public_model_name: + names.append(team_public_model_name) + unhealthy = model_info.get("id") in unhealthy_ids + for name in names: + if not isinstance(name, str) or not name: + continue + unhealthy_by_name[name] = unhealthy_by_name.get(name, True) and unhealthy + return {name for name, fully in unhealthy_by_name.items() if fully} + + +__all__ = [ + "FAILOVER_FLAGS", + "HEALTH_STATE_KEY", + "HealthRouting", + "all_blocked", + "failover_document", + "fully_blocked_model_names", + "fully_unhealthy_model_names", + "is_blocked", + "resolved_allowed_fails_policy", +] diff --git a/litellm/router_rust/surface/indexes.py b/litellm/router_rust/surface/indexes.py new file mode 100644 index 00000000000..f5aca3e1bad --- /dev/null +++ b/litellm/router_rust/surface/indexes.py @@ -0,0 +1,514 @@ +# pyright: reportIncompatibleMethodOverride=false +# (each view overrides its builtin's mutators with the same behaviour, as a changeset) +""" +``HostedIndexes``: the registry indexes the Rust core hands out, read back from router-core. + +router-core keeps the indexes the Python router keeps by history (``host_index.rs``): the id, +group and team position maps, the group names a ``set_model_list`` was given, the deployment +names that only ever grow, the team public names, the provider default ids and the wildcard +pattern routers. ``registry().index()``, ``names(kind=...)``, ``patterns()`` and the deprecated +attributes return the views here: a ``dict``, ``set`` or ``list`` (so ``isinstance`` and ``json`` +keep working), one object per router, whose contents are router-core's, read again when an entry +point hands a view out (or before a write to it) once the registry moved, not on every registry +write. A write to any of them, a nested one included (``index("model_name")["gpt"].append(3)``), +is a ``host_index`` changeset that replaces that index in router-core, and the view reads it back. +The lookups over these indexes run in router-core (``lookup.rs``), not over the views. +""" + +import copy +from collections.abc import Callable, Iterable, Iterator, Mapping, Sequence +from functools import partial +from typing import ( + TYPE_CHECKING, + Final, + Literal, + SupportsIndex, + TypeAlias, + cast, # noqa: TID251 # any value a caller wrote into a view +) + +from litellm.constants import DEFAULT_MAX_RECURSE_DEPTH +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.litellm_core_utils.pattern_match_deployments import PatternMatchRouter + +if TYPE_CHECKING: + from litellm.rust_bridge._native import RouterCoreHandle + +IndexField: TypeAlias = Literal[ + "id_map", + "model_name", + "team_model", + "model_names", + "deployment_names", + "team_public_model_names", + "provider_default_ids", + "patterns", + "team_patterns", +] +_Commit: TypeAlias = Callable[[object], None] +# Deployment copies a pattern router routes to, fresh for the caller. +Routed: TypeAlias = list[dict[str, object]] +_Pairs: TypeAlias = list[tuple[str, list[object]]] + + +def _stay() -> None: + """A view with no contents of its own to read again before a write.""" + + +def _as_set(value: object) -> set[object]: # mutable-ok: set's own in-place operand + return cast(set[object], value) # cast-ok: an in-place set operand, checked by set itself + + +def _as_mapping(value: object) -> Mapping[object, object]: + if not isinstance(value, Mapping): + return {} + return cast(Mapping[object, object], value) # cast-ok: any mapping a caller wrote + + +def _json(value: object, depth: int = 0) -> object: + """A view's contents as router-core takes them: plain JSON, a set as a list. A caller wrote them, + so a cycle is possible: anything nested past ``DEFAULT_MAX_RECURSE_DEPTH`` is refused.""" + if depth > DEFAULT_MAX_RECURSE_DEPTH: + raise ValueError(f"a router index is nested deeper than {DEFAULT_MAX_RECURSE_DEPTH} levels") + mapping: Final = _as_mapping(value) + if mapping or isinstance(value, Mapping): + return {str(key): _json(item, depth + 1) for key, item in mapping.items()} + if isinstance(value, list | tuple | set | frozenset): + items: Final = cast(Iterable[object], value) # cast-ok: any collection a caller wrote + return [_json(item, depth + 1) for item in items] + return value + + +class _Positions(list[object]): + """One index's position list (or a pattern's deployments): a write commits the whole list.""" + + def __init__(self, items: Iterable[object], commit: _Commit, fresh: Callable[[], None] = _stay) -> None: + super().__init__(items) + self._commit: Final = commit + self._fresh: Final = fresh + + def _load(self, items: Iterable[object]) -> None: + """Show router-core's contents, without a write.""" + super().__setitem__(slice(None), list(items)) + + def _write(self, change: Callable[[list[object]], object]) -> object: # mutable-ok: the copy it changes + self._fresh() # a view held across a write elsewhere changes router-core's contents, not stale ones + changed: Final = list(self) + result: Final = change(changed) + self._commit(changed) + return result + + def append(self, value: object) -> None: + _ = self._write(lambda items: items.append(value)) + + def extend(self, values: Iterable[object]) -> None: + added: Final = tuple(values) + _ = self._write(lambda items: items.extend(added)) + + def insert(self, index: SupportsIndex, value: object) -> None: + _ = self._write(lambda items: items.insert(index, value)) + + def remove(self, value: object) -> None: + _ = self._write(lambda items: items.remove(value)) + + def pop(self, index: SupportsIndex = -1) -> object: + return self._write(lambda items: items.pop(index)) + + def clear(self) -> None: + _ = self._write(lambda items: items.clear()) + + def sort(self, *args: object, **kwargs: object) -> None: # kwargs-ok: list.sort's own arguments + _ = self._write(lambda items: items.sort(*args, **kwargs)) # pyright: ignore[reportCallIssue, reportArgumentType] # list.sort's own arguments + + def reverse(self) -> None: + _ = self._write(lambda items: items.reverse()) # pyright: ignore[reportUnknownLambdaType] # list.reverse returns None + + def __setitem__(self, index: object, value: object) -> None: + _ = self._write(lambda items: items.__setitem__(index, value)) # pyright: ignore[reportCallIssue, reportArgumentType, reportUnknownLambdaType] # list's own item and slice assignment + + def __delitem__(self, index: object) -> None: + _ = self._write(lambda items: items.__delitem__(index)) # pyright: ignore[reportArgumentType] # list's own item and slice deletion + + def __iadd__(self, values: Iterable[object]) -> "_Positions": + self.extend(values) + return self + + def __imul__(self, count: SupportsIndex) -> "_Positions": + _ = self._write(lambda items: items.__imul__(count)) + return self + + def __reduce_ex__(self, protocol: SupportsIndex) -> tuple[object, ...]: + return (list, (list(self),)) + + +class _IndexDict(dict[object, object]): + """A key-to-positions index: a write commits the whole index.""" + + def __init__(self, commit: _Commit, fresh: Callable[[], None] = _stay) -> None: + super().__init__() + self._commit: Final = commit + self._fresh: Final = fresh + + def _load(self, items: Mapping[object, object]) -> None: + """Show router-core's contents, without a write.""" + super().clear() + super().update(items) + + def _write(self, change: Callable[[dict[object, object]], object]) -> object: # mutable-ok: the copy it changes + self._fresh() # a view held across a write elsewhere changes router-core's contents, not stale ones + changed: Final = dict(self) + result: Final = change(changed) + self._commit(changed) + return result + + def __setitem__(self, key: object, value: object) -> None: + _ = self._write(lambda items: items.__setitem__(key, value)) + + def __delitem__(self, key: object) -> None: + _ = self._write(lambda items: items.__delitem__(key)) + + def pop(self, key: object, *default: object) -> object: + return self._write(lambda items: items.pop(key, *default)) + + def popitem(self) -> tuple[object, object]: + return cast(tuple[object, object], self._write(lambda items: items.popitem())) # cast-ok: dict.popitem's pair + + def clear(self) -> None: + _ = self._write(lambda items: items.clear()) + + def update(self, *args: object, **kwargs: object) -> None: # kwargs-ok: dict.update's own arguments + _ = self._write(lambda items: items.update(*args, **kwargs)) # pyright: ignore[reportCallIssue, reportArgumentType] # dict.update's own arguments + + def setdefault(self, key: object, default: object = None) -> object: + if key in self: + return self[key] + self[key] = default + return self[key] + + def __ior__(self, other: object) -> "_IndexDict": + self.update(other) + return self + + def __reduce_ex__(self, protocol: SupportsIndex) -> tuple[object, ...]: + return (dict, (dict(self),)) + + +class _NameSet(set[object]): + """``model_names``: a write commits the whole set.""" + + def __init__(self, commit: _Commit, fresh: Callable[[], None] = _stay) -> None: + super().__init__() + self._commit: Final = commit + self._fresh: Final = fresh + + def _load(self, items: Iterable[object]) -> None: + """Show router-core's contents, without a write.""" + super().clear() + super().update(items) + + def _write(self, change: Callable[[set[object]], object]) -> object: # mutable-ok: the copy it changes + self._fresh() # a view held across a write elsewhere changes router-core's contents, not stale ones + changed: Final = set(self) + result: Final = change(changed) + self._commit(changed) + return result + + def add(self, value: object) -> None: + _ = self._write(lambda items: items.add(value)) + + def discard(self, value: object) -> None: + _ = self._write(lambda items: items.discard(value)) + + def remove(self, value: object) -> None: + _ = self._write(lambda items: items.remove(value)) + + def pop(self) -> object: + return self._write(lambda items: items.pop()) + + def clear(self) -> None: + _ = self._write(lambda items: items.clear()) + + def update(self, *others: Iterable[object]) -> None: + _ = self._write(lambda items: items.update(*others)) + + def difference_update(self, *others: Iterable[object]) -> None: + _ = self._write(lambda items: items.difference_update(*others)) + + def intersection_update(self, *others: Iterable[object]) -> None: + _ = self._write(lambda items: items.intersection_update(*others)) + + def symmetric_difference_update(self, other: Iterable[object]) -> None: + _ = self._write(lambda items: items.symmetric_difference_update(other)) + + def __ior__(self, other: object) -> "_NameSet": + _ = self._write(lambda items: items.__ior__(_as_set(other))) + return self + + def __iand__(self, other: object) -> "_NameSet": + _ = self._write(lambda items: items.__iand__(_as_set(other))) + return self + + def __isub__(self, other: object) -> "_NameSet": + _ = self._write(lambda items: items.__isub__(_as_set(other))) + return self + + def __ixor__(self, other: object) -> "_NameSet": + _ = self._write(lambda items: items.__ixor__(_as_set(other))) + return self + + def __reduce_ex__(self, protocol: SupportsIndex) -> tuple[object, ...]: + return (set, (set(self),)) + + +class HostedPatternRouter(PatternMatchRouter): + """A wildcard pattern router whose patterns are router-core's (``pattern_router``, or one team's + router): routing runs in router-core, and ``add_pattern`` / ``remove_deployment`` / a write to + ``patterns`` are changesets.""" + + def __init__(self, owner: "HostedIndexes", team: str | None) -> None: + super().__init__() # its empty `patterns` write is ignored: router-core holds them + self._owner: Final = owner + self._team: Final = team + self._view: Final = _IndexDict(self._commit, owner.refresh) + + @property + def patterns(self) -> dict[str, list[object]]: # pyright: ignore[reportIncompatibleVariableOverride] # the base class's attribute, read from router-core # mutable-ok: the live patterns, writes are changesets + self._owner.refresh() + return cast(dict[str, list[object]], self._view) # cast-ok: regex keys, deployment lists + + @patterns.setter + def patterns(self, value: Mapping[str, object]) -> None: # pyright: ignore[reportIncompatibleVariableOverride] # see the getter + if not hasattr(self, "_owner"): + return # the base constructor's empty dict: router-core holds this router's patterns + self._commit(value) + + def _show(self, pairs: Iterable[tuple[str, Sequence[object]]]) -> None: + shown: Final = { + regex: _Positions(deployments, partial(self._write_pattern, regex)) for regex, deployments in pairs + } + self._view._load(cast(Mapping[object, object], shown)) # pyright: ignore[reportPrivateUsage] # cast-ok: regex to deployments + + def _write_pattern(self, regex: str, deployments: object) -> None: + self._commit({**self.patterns, regex: deployments}) + + def _commit(self, value: object) -> None: + pairs: Final = [ + [str(regex), _json(deployments)] for regex, deployments in (as_str_mapping(value) or {}).items() + ] + self._owner.write_router(self._team, pairs) + + def route(self, request: str | None, filtered_model_names: Sequence[str] | None = None) -> Routed | None: # pyright: ignore[reportIncompatibleMethodOverride] # the base's list types, read only here + if not isinstance(request, str): + # The base class matches its regexes against it, which fails and routes nowhere. + return super().route(request, None if filtered_model_names is None else list(filtered_model_names)) # pyright: ignore[reportReturnType, reportUnknownMemberType, reportUnknownVariableType] # None, or the base's copies of the deployments + return self._owner.route(self._team, request, filtered_model_names) + + def get_models_by_pattern(self, model: str, custom_llm_provider: str | None = None) -> frozenset[str]: + from litellm.litellm_core_utils.get_llm_provider_logic import inferred_provider + + if not isinstance(model, str): # pyright: ignore[reportUnnecessaryIsInstance] # a caller's non-string model goes to the base class + return super().get_models_by_pattern(model, custom_llm_provider) + provider: Final = custom_llm_provider or inferred_provider(model) + return self._owner.models_by_pattern(self._team, [model, f"{provider}/{model}"]) + + +class _TeamRouters(dict[str, HostedPatternRouter]): + """``team_pattern_routers``: team id to its router; removing a team's router is a changeset.""" + + def __init__(self, owner: "HostedIndexes") -> None: + super().__init__() + self._owner: Final = owner + + def _load(self, routers: Mapping[str, HostedPatternRouter]) -> None: + super().clear() + super().update(routers) + + def __delitem__(self, team: str) -> None: + self._owner.drop_team_router(team) + + def pop(self, team: str, *default: object) -> object: + if team not in self: + if default: + return default[0] + raise KeyError(team) + router: Final = self[team] + self._owner.drop_team_router(team) + return router + + def clear(self) -> None: + self._owner.write({"team_patterns": []}) + + def setdefault(self, team: str, default: HostedPatternRouter | None = None) -> HostedPatternRouter: + if team not in self: + self._owner.write_router(team, []) + return self[team] + + +class HostedIndexes: + """Router-core's host indexes, as the live objects the registry hands out.""" + + def __init__( + self, + handle: Callable[[], "RouterCoreHandle | None"], + apply: Callable[[Mapping[str, object]], None], + ) -> None: + self._handle: Final = handle + self._apply: Final = apply + self._read_at: tuple[object, int] | None = None + self._document: Mapping[str, object] = {} + # The views are read again when an entry point hands them out, and before a write to them. + self.id_map: Final = _IndexDict(lambda value: self.write({"id_map": value}), self.refresh) + self.model_name: Final = _IndexDict(lambda value: self.write({"model_name": value}), self.refresh) + self.team_model: Final = _IndexDict(lambda value: self._write_team_model(value), self.refresh) + self.model_names: Final = _NameSet(lambda value: self.write({"model_names": value}), self.refresh) + self.deployment_names: Final = _Positions( + (), lambda value: self.write({"deployment_names": value}), self.refresh + ) + self.provider_default_ids: Final = _Positions( + (), lambda value: self.write({"provider_default_ids": value}), self.refresh + ) + self.pattern_router: Final = HostedPatternRouter(self, None) + self.team_pattern_routers: Final = _TeamRouters(self) + self._team_routers: dict[str, HostedPatternRouter] = {} # mutable-ok: one router object per team + self._team_public: frozenset[str] = frozenset() + + # -- reading ---------------------------------------------------------------------------------- + + def refresh(self) -> None: + """Read router-core's indexes again when its registry moved since the last read.""" + handle: Final = self._handle() + if handle is None: + return + version: Final = handle.registry_version() + if self._read_at is not None and self._read_at[0] is handle and self._read_at[1] == version: + return + self._read_at = (handle, version) + self._document = as_str_mapping(handle.host_indexes()) or {} + self._show() + + def _field(self, name: str) -> object: + return self._document.get(name) + + def _show(self) -> None: + ids: Final = _as_mapping(self._field("id_map")) + self.id_map._load(ids) # pyright: ignore[reportPrivateUsage] # a view this object owns + named: Final[dict[object, object]] = {} # mutable-ok: built here + for name, positions in (as_str_mapping(self._field("model_name")) or {}).items(): + named[name] = self._positions(positions, partial(self._write_named, name)) + self.model_name._load(named) # pyright: ignore[reportPrivateUsage] # a view this object owns + teams: Final[dict[object, object]] = {} # mutable-ok: built here + for team, public, positions in _triples(self._field("team_model")): + teams[(team, public)] = self._positions(positions, partial(self._write_team_key, (team, public))) + self.team_model._load(teams) # pyright: ignore[reportPrivateUsage] # a view this object owns + self.model_names._load(_items(self._field("model_names"))) # pyright: ignore[reportPrivateUsage] # a view this object owns + self.deployment_names._load(_items(self._field("deployment_names"))) # pyright: ignore[reportPrivateUsage] # a view this object owns + self.provider_default_ids._load(_items(self._field("provider_default_ids"))) # pyright: ignore[reportPrivateUsage] # a view this object owns + self._team_public = frozenset(str(name) for name in _items(self._field("team_public_model_names"))) + self.pattern_router._show(_pattern_pairs(self._field("patterns"))) # pyright: ignore[reportPrivateUsage] # the router this object owns + routers: Final[dict[str, HostedPatternRouter]] = {} # mutable-ok: rebuilt each read + for team, pairs in _team_pairs(self._field("team_patterns")): + router = self._team_routers.get(team) or HostedPatternRouter(self, team) + router._show(pairs) # pyright: ignore[reportPrivateUsage] # the router this object owns + routers[team] = router + self._team_routers = routers + self.team_pattern_routers._load(routers) # pyright: ignore[reportPrivateUsage] # a view this object owns + + def _write_named(self, name: str, items: object) -> None: + self.write({"model_name": {**self.model_name, name: items}}) + + def _write_team_key(self, key: tuple[str, str], items: object) -> None: + self._write_team_model({**self.team_model, key: items}) + + def _positions(self, positions: object, commit: _Commit) -> object: + """A position list as a write-through list; anything else a caller wrote, as written.""" + items: Final = _items(positions) + return _Positions(items, commit) if isinstance(positions, list) else positions + + @property + def team_public_model_names(self) -> frozenset[str]: + self.refresh() + return self._team_public + + # -- writing ---------------------------------------------------------------------------------- + + def write(self, fields: Mapping[str, object]) -> None: + """Replace the named indexes in router-core, then read them back.""" + self._apply({"host_index": {name: _json(value) for name, value in fields.items()}}) + self.refresh() + + def assign(self, field: IndexField, value: object) -> None: + """A deprecated attribute assignment of one index (``router.model_names = {...}``).""" + if field == "team_model": + self._write_team_model(value) + else: + self.write({field: value}) + + def _write_team_model(self, value: object) -> None: + mapping: Final = _as_mapping(value) + triples: Final[list[list[object]]] = [] # mutable-ok: JSON triples + for key, positions in mapping.items(): + parts = cast(tuple[object, ...], key) if isinstance(key, tuple) else () # cast-ok: a key a caller wrote + if len(parts) == 2: + triples.append([str(parts[0]), str(parts[1]), _json(positions)]) + self.write({"team_model": triples}) + + def write_router(self, team: str | None, pairs: list[list[object]]) -> None: # mutable-ok: JSON pairs + """Replace one pattern router's patterns.""" + if team is None: + self.write({"patterns": pairs}) + return + teams: Final = [[t, _json(_pairs_of(router))] for t, router in self._team_routers.items() if t != team] + self.write({"team_patterns": [*teams, [team, pairs]]}) + + def drop_team_router(self, team: str) -> None: + if team not in self._team_routers: + raise KeyError(team) + self.write({"team_patterns": [[t, _json(_pairs_of(r))] for t, r in self._team_routers.items() if t != team]}) + + # -- routing ---------------------------------------------------------------------------------- + + def route(self, team: str | None, request: str, filtered: Sequence[str] | None) -> Routed | None: + handle: Final = self._handle() + routed: Final = ( + None + if handle is None + else handle.pattern_route(team, request, None if filtered is None else list(filtered)) + ) + return None if routed is None else [dict(deployment) for deployment in routed] + + def models_by_pattern(self, team: str | None, requests: list[str]) -> frozenset[str]: # mutable-ok: read only + handle: Final = self._handle() + found: Final = None if handle is None else handle.models_by_pattern(team, requests) + return frozenset(found or ()) + + +def _items(value: object) -> list[object]: # mutable-ok: a fresh list + return list(cast(list[object], value)) if isinstance(value, list) else [] # cast-ok: a JSON list + + +def _triples(value: object) -> Iterator[tuple[str, str, object]]: + for item in _items(value): + parts = _items(item) + if len(parts) == 3: + yield str(parts[0]), str(parts[1]), parts[2] + + +def _pattern_pairs(value: object) -> _Pairs: + pairs: Final[_Pairs] = [] + for item in _items(value): + parts = _items(item) + if len(parts) == 2: + pairs.append((str(parts[0]), _items(parts[1]))) + return pairs + + +def _team_pairs(value: object) -> Iterator[tuple[str, _Pairs]]: + for item in _items(value): + parts = _items(item) + if len(parts) == 2: + yield str(parts[0]), _pattern_pairs(parts[1]) + + +def _pairs_of(router: HostedPatternRouter) -> list[list[object]]: # mutable-ok: JSON pairs + view: Final[Mapping[object, object]] = router._view # pyright: ignore[reportPrivateUsage] # a router this module owns + return [[regex, copy.deepcopy(deployments)] for regex, deployments in view.items()] diff --git a/litellm/router_rust/surface/legacy_members.py b/litellm/router_rust/surface/legacy_members.py new file mode 100644 index 00000000000..6c30557eb4d --- /dev/null +++ b/litellm/router_rust/surface/legacy_members.py @@ -0,0 +1,547 @@ +""" +``RustLegacyMembers``: the old public ``Router`` members outside the entry points, on the Rust +core: the routing-state lifecycle, the routing callbacks' checks, one provider call's accounting +and the pre-routing strategy builders. Each one is the Python router core's, ported (never +imported), over the state the Rust core and its host keep. + +Not served, and refused by ``RustCore.__getattr__``: the Python fallback walk +(``async_function_with_fallbacks``, ``function_with_fallbacks``, ``async_function_with_retries``, +``async_function_with_fallbacks_common_utils``) and ``factory_function``. They run a caller's +``original_function``, which picks its own deployment; router-core makes each pick itself and +attempts one host op, named by the endpoint's plan. +""" + +import asyncio +import contextlib +import inspect +import traceback +import uuid +from collections.abc import Awaitable, Callable, Iterable, Mapping, Sequence +from types import MappingProxyType +from typing import TYPE_CHECKING, Final + +from typing_extensions import NotRequired, ReadOnly, TypedDict + +from litellm._internal_context import service_target +from litellm._logging import verbose_router_logger +from litellm.constants import ROUTER_USAGE_COUNTED_TOKENS_METADATA_KEY +from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.add_retry_fallback_headers import response_total_token_count +from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type +from litellm.litellm_core_utils.core_helpers import as_str_mapping, get_parent_otel_span_from_kwargs +from litellm.litellm_core_utils.coroutine_checker import coroutine_checker +from litellm.litellm_core_utils.routing_groups import validate_routing_strategy +from litellm.litellm_core_utils.token_counter import served_openai_models as _served_openai_models +from litellm.router_api import RoutingContext +from litellm.router_rust.invoke.websocket import admit_deployment_turn +from litellm.router_rust.steps.callbacks import RustOptionalChecks +from litellm.router_rust.steps.prerouting import TIER_PARAMS_NEVER_DROPPED as _TIER_PARAMS_NEVER_DROPPED +from litellm.router_rust.surface.members import RustRegistryMembers +from litellm.router_strategy.auto_router.auto_router_model_naming import ( + GatedAutoRouterCapability, + capability_limit_violation, + count_capability_routers, +) +from litellm.router_utils.cooldown_handlers import set_cooldown_deployments +from litellm.router_utils.endpoint_eligibility import endpoint_selection +from litellm.router_utils.pre_call_checks.io_token_rate_limit_check import async_io_token_refund_failure +from litellm.router_utils.router_callbacks.track_deployment_metrics import find_deployment_metadata +from litellm.router_utils.routing_read_batch import ROUTER_USAGE_TARGET +from litellm.types.router import RouterCacheEnum +from litellm.utils import get_utc_datetime + +if TYPE_CHECKING: + from opentelemetry.trace import Span + + from litellm.caching.dual_cache import DualCache + from litellm.litellm_core_utils.litellm_logging import Logging + from litellm.router_rust.invoke.endpoints import EndpointCore + from litellm.types.router import CustomRoutingStrategyBase, Deployment, RoutingGroup + +# `RoutingArgs.ttl`: a usage counter lives for its minute. +_USAGE_TTL: Final = 60 + +# What `initialize_assistants_endpoint` binds. +_ASSISTANTS_ENDPOINTS: Final = ( + "acreate_assistants", + "adelete_assistant", + "aget_assistants", + "acreate_thread", + "aget_thread", + "a_add_message", + "aget_messages", + "arun_thread", +) + +# What `initialize_router_endpoints` binds, with the container file endpoints it reads from +# `litellm/containers/endpoints.json`. +_ROUTER_ENDPOINTS: Final = frozenset( + { + "_arealtime", + "_aresponses_websocket", + "aadapter_generate_content", + "aanthropic_messages", + "acancel_fine_tuning_job", + "acancel_interaction", + "acancel_responses", + "acompact_responses", + "acreate_agent", + "acreate_container", + "acreate_fine_tuning_job", + "acreate_interaction", + "acreate_realtime_client_secret", + "acreate_realtime_transcription_session", + "acreate_realtime_translation_client_secret", + "acreate_skill", + "adecisions", + "adelete_agent", + "adelete_container", + "adelete_interaction", + "adelete_responses", + "adelete_skill", + "aextraction", + "afile_content", + "afile_delete", + "afile_list", + "agenerate_content", + "agenerate_content_stream", + "aget_agent", + "aget_interaction", + "aget_responses", + "aget_skill", + "aimage_edit", + "alist_agent_versions", + "alist_agents", + "alist_containers", + "alist_fine_tuning_jobs", + "alist_input_items", + "alist_skills", + "allm_passthrough_route", + "amoderation", + "anthropic_messages", + "aocr", + "arealtime_calls", + "arealtime_translation_calls", + "aresponses", + "aretrieve_container", + "aretrieve_fine_tuning_job", + "asearch", + "asystemone", + "avector_store_delete", + "avector_store_file_content", + "avector_store_file_create", + "avector_store_file_delete", + "avector_store_file_list", + "avector_store_file_retrieve", + "avector_store_file_update", + "avector_store_list", + "avector_store_retrieve", + "avector_store_search", + "avector_store_update", + "avideo_content", + "avideo_create_character", + "avideo_edit", + "avideo_extension", + "avideo_generation", + "avideo_get_character", + "avideo_list", + "avideo_remix", + "avideo_status", + "cancel_interaction", + "create_agent", + "create_container", + "create_interaction", + "decisions", + "delete_agent", + "delete_container", + "delete_interaction", + "extraction", + "generate_content", + "generate_content_stream", + "get_agent", + "get_interaction", + "list_agent_versions", + "list_agents", + "list_containers", + "ocr", + "responses", + "retrieve_container", + "search", + "systemone", + "vector_store_create", + "vector_store_delete", + "vector_store_file_content", + "vector_store_file_create", + "vector_store_file_delete", + "vector_store_file_list", + "vector_store_file_retrieve", + "vector_store_file_update", + "vector_store_list", + "vector_store_retrieve", + "vector_store_search", + "vector_store_update", + "video_content", + "video_create_character", + "video_edit", + "video_extension", + "video_generation", + "video_get_character", + "video_list", + "video_remix", + "video_status", + } +) + + +def _dispatch_failure(logging_obj: "Logging | None", error: Exception) -> None: + """The ``## LOG FAILURE EVENT`` of a routing callback that raised.""" + if logging_obj is not None: + asyncio.create_task( + logging_obj.dispatch_failure_handlers( + exception=error, + traceback_exception=traceback.format_exc(), + prefer_async_handlers=True, + ) + ) + + +class _FailedCallParams(TypedDict): + """The ``litellm_params`` of a failed call, as the failure callback reads them.""" + + metadata: ReadOnly[Mapping[str, object]] + model_info: ReadOnly[NotRequired[Mapping[str, object] | None]] + + +async def _deployments_filtered_by( + callback: CustomLogger, + model: str, + deployments: object, + messages: object, + request_kwargs: dict[str, object] | None, # mutable-ok: CustomLogger takes the request dict + parent_otel_span: "Span | None", +) -> object: + return await callback.async_filter_deployments( # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # untyped deployment dicts + model=model, + healthy_deployments=deployments, # pyright: ignore[reportArgumentType] # what the last callback returned + messages=messages, # pyright: ignore[reportArgumentType] # the request's messages, as given + request_kwargs=request_kwargs, + parent_otel_span=parent_otel_span, + ) + + +def _metadata_model_id(model_info: object) -> object: + return model_info.get("id") if isinstance(model_info, dict) else None # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # the metadata's model_info dict + + +class RustLegacyMembers(RustRegistryMembers, RustOptionalChecks): + """Mixed into ``RustCore``, which supplies its host registry, selectors and checks.""" + + # RustCore sets these in its constructor. + _cache: "DualCache" + _cooldown_given: object + _custom_strategy: "CustomRoutingStrategyBase | None" + # The constructor's argument, or the attribute as assigned. + auto_router_capability_limit: "Callable[[], int | None] | None" + + TIER_PARAMS_NEVER_DROPPED: Final = _TIER_PARAMS_NEVER_DROPPED + + # -- registry lookups -------------------------------------------------------------------------- + + def get_routing_group(self, model_name: str) -> "RoutingGroup | None": + """The routing group callable as ``model_name`` (``get_routing_group``).""" + return self._registry_state.get_routing_group(model_name) + + def team_public_model_names_of(self, team_id: str) -> frozenset[str]: + """The public names ``team_id`` serves its own deployments under (``team_public_model_names_of``).""" + return self._registry_state.team_public_model_names_of(team_id) + + def served_openai_models(self, model_name: str) -> tuple[str | None, ...]: + """The OpenAI models ``model_name`` serves (``_served_openai_models``). The Python core keeps + an ``lru_cache`` over it, emptied with every model list change.""" + return _served_openai_models(self._registry_state._core_deployments_named(model_name) or ()) # pyright: ignore[reportPrivateUsage] # the core reads its own host registry + + def auto_router_capability_violation(self, capability: GatedAutoRouterCapability) -> str | None: + """Why one more router claiming ``capability`` cannot join this router, or None when it can + (``auto_router_capability_violation``); the limit is resolved on every call.""" + resolver: Final = self.auto_router_capability_limit + limit: Final = resolver() if resolver is not None else None + others: Final = count_capability_routers( + (deployment for deployment in self._registry_state._core_model_list if isinstance(deployment, Mapping)), # pyright: ignore[reportPrivateUsage, reportUnnecessaryIsInstance] # the live list + capability=capability, + ) + return capability_limit_violation(capability=capability, held=others + 1, limit=limit) + + # -- routing state ----------------------------------------------------------------------------- + + def retire_routing_state(self) -> None: + """Stop the background work of the selectors and the budget limiter (``retire_routing_state``).""" + self._opt.retire_state((*self._sel.callback_selectors(), *self._sel.override_selectors())) + + def routing_strategy_init(self, routing_strategy: object, routing_strategy_args: Mapping[str, object]) -> None: + """``routing_strategy_init``: the default selector only. As on the Python core the router's + ``routing_strategy`` setting stays, so picks keep following it; ``apply`` changes it.""" + verbose_router_logger.info("Routing strategy: %s", routing_strategy) + validate_routing_strategy(routing_strategy) # pyright: ignore[reportArgumentType] # the strategy as given + # `_reset_custom_routing_strategy`. + self._custom_strategy = None + _ = self.__dict__.pop("get_available_deployment", None) + _ = self.__dict__.pop("_core_async_get_available_deployment", None) + self._sel.init_default(routing_strategy, routing_strategy_args, configured=False) + + def set_optional_pre_call_checks(self, optional_pre_call_checks: Iterable[object] | None) -> None: + """``set_optional_pre_call_checks``: drop the toggleable checks the list leaves out, then add it.""" + self._opt.set(None if optional_pre_call_checks is None else tuple(optional_pre_call_checks)) + + def initialize_assistants_endpoint(self) -> None: + """``initialize_assistants_endpoint`` binds the endpoints; this core answers them from + ``__getattr__``, so what is left to do is to drop an assigned replacement.""" + for name in _ASSISTANTS_ENDPOINTS: + _ = self.__dict__.pop(name, None) + + def initialize_router_endpoints(self) -> None: + """``initialize_router_endpoints``, as ``initialize_assistants_endpoint`` above.""" + from litellm.containers.endpoint_factory import ( + _generated_endpoints, # pyright: ignore[reportPrivateUsage, reportUnknownVariableType] # the names the Python core registers + ) + + for name in (*_ROUTER_ENDPOINTS, *_generated_endpoints): + _ = self.__dict__.pop(name, None) + + # -- pre-routing strategies -------------------------------------------------------------------- + + def init_auto_router_deployment(self, deployment: "Deployment") -> None: + """Register the deployment's auto-router (``init_auto_router_deployment``).""" + self._registry_state.strategies._init_auto_router(deployment) # pyright: ignore[reportOptionalMemberAccess, reportPrivateUsage] # RustCore installs its strategies in its constructor + + def init_complexity_router_deployment(self, deployment: "Deployment") -> None: + """Register the deployment's complexity-router (``init_complexity_router_deployment``).""" + self._registry_state.strategies._init_complexity_router(deployment) # pyright: ignore[reportOptionalMemberAccess, reportPrivateUsage] # see above + + def init_quality_router_deployment(self, deployment: "Deployment") -> None: + """Register the deployment's quality-router (``init_quality_router_deployment``).""" + self._registry_state.strategies._init_quality_router(deployment) # pyright: ignore[reportOptionalMemberAccess, reportPrivateUsage] # see above + + def init_adaptive_router_deployment(self, deployment: "Deployment") -> None: + """Register the deployment's adaptive-router and its post-call hook (``init_adaptive_router_deployment``).""" + self._registry_state.strategies._init_adaptive_router(deployment) # pyright: ignore[reportOptionalMemberAccess, reportPrivateUsage] # see above + + # -- routing callbacks ------------------------------------------------------------------------- + + def routing_strategy_pre_call_checks( + self, + deployment: dict[str, object], # mutable-ok: CustomLogger takes the deployment dict + ) -> None: + """``routing_strategy_pre_call_checks``: the sync check of each ``CustomLogger`` callback.""" + for callback in self._opt.routing_callbacks(): + if isinstance(callback, CustomLogger): + callback.pre_call_check(deployment) # pyright: ignore[reportUnknownMemberType] # CustomLogger takes an untyped deployment dict + + async def async_routing_strategy_pre_call_checks( + self, + deployment: dict[str, object], # mutable-ok: CustomLogger takes the deployment dict + parent_otel_span: "Span | None", + logging_obj: "Logging | None" = None, + ) -> None: + """``async_routing_strategy_pre_call_checks``: a check's rate limit cools the deployment down + under the Python rules (``set_cooldown_deployments``, cooldown event included).""" + from litellm import exceptions as litellm_exceptions + + for callback in self._opt.routing_callbacks(): + if isinstance(callback, CustomLogger): + try: + await callback.async_pre_call_check(deployment, parent_otel_span) # pyright: ignore[reportUnknownMemberType] # see above + except litellm_exceptions.RateLimitError as e: + _dispatch_failure(logging_obj, e) + _ = set_cooldown_deployments( + ctx=RoutingContext(self), # pyright: ignore[reportArgumentType] # the core's RoutingContext + exception_status=e.status_code, + original_exception=e, + deployment=deployment["model_info"]["id"], # pyright: ignore[reportIndexIssue, reportUnknownArgumentType] # read as the Python core reads it + time_to_cooldown=self._cooldown_given, # pyright: ignore[reportArgumentType] # the value as given, as the Python core stores it + ) + raise + except Exception as e: + _dispatch_failure(logging_obj, e) + raise + + async def async_callback_filter_deployments( + self, + model: str, + healthy_deployments: list[dict[str, object]], # mutable-ok: CustomLogger deployment-list contract + messages: object, + parent_otel_span: "Span | None", + request_kwargs: dict[str, object] | None = None, # mutable-ok: CustomLogger takes the request dict + logging_obj: "Logging | None" = None, + ) -> object: + """``async_callback_filter_deployments``: each routing callback narrows the deployments in turn.""" + remaining: object = healthy_deployments # rebind-ok: narrowed by each callback + for callback in self._opt.routing_callbacks(): + if isinstance(callback, CustomLogger): + try: + remaining = await _deployments_filtered_by( + callback, model, remaining, messages, request_kwargs, parent_otel_span + ) + except Exception as e: + _dispatch_failure(logging_obj, e) + raise + return remaining + + async def async_admit_deployment_turn( + self, model_group: str, opened_on: Mapping[str, object], request_kwargs: Mapping[str, object] + ) -> Mapping[str, object]: + """Admit a later turn of an open websocket (``async_admit_deployment_turn``).""" + port: Final[EndpointCore] = self.__dict__["_port"] # pyright: ignore[reportAny] # RustCore's own attribute + return await admit_deployment_turn(port, model_group, opened_on, request_kwargs) + + # -- one provider call ------------------------------------------------------------------------- + + async def make_call( + self, + original_function: Callable[..., object], + *args: object, + **kwargs: object, # kwargs-ok: the endpoint's request + ) -> object: + """``make_call``: call the endpoint, count its usage and stamp the response's headers. A + failed call hands back the io tokens it reserved.""" + model_group: Final = kwargs.get("model") + generic_function: Final = kwargs.get("original_generic_function") + endpoint_function: Final = generic_function if callable(generic_function) else original_function + try: + with endpoint_selection( + getattr(endpoint_function, "__name__", None), + getattr(endpoint_function, "__module__", None), + model=model_group, + ): + response: object = original_function(*args, **kwargs) # rebind-ok: awaited below + if coroutine_checker.is_async_callable(response) or inspect.isawaitable(response): + awaitable: Final[Awaitable[object]] = response # pyright: ignore[reportAssignmentType] # the endpoint's awaitable + response = await awaitable # rebind-ok: awaited here + except Exception: + with contextlib.suppress(Exception): + await async_io_token_refund_failure( + self._cache, kwargs, parent_otel_span=get_parent_otel_span_from_kwargs(kwargs) + ) + raise + await self.increment_deployment_usage_for_response(response=response, request_kwargs=kwargs) + return await self.set_response_headers( + response=response, model_group=model_group if isinstance(model_group, str) else None, request_kwargs=kwargs + ) + + async def increment_deployment_usage_for_response( + self, response: object, request_kwargs: Mapping[str, object] + ) -> None: + """Count a response's tokens and request against its deployment, once the call returned, and + note them on the request for the success callback (``increment_deployment_usage_for_response``).""" + if response is None: + return + try: + deployment_metadata: Final = find_deployment_metadata(request_kwargs) + model_group: Final = request_kwargs.get("model") + if deployment_metadata is None or not isinstance(model_group, str): + return + deployment_id: Final = _metadata_model_id(deployment_metadata["model_info"]) + if deployment_id is None: + return + total_tokens: Final = response_total_token_count(response) + deployment_name: Final = deployment_metadata.get("deployment") + deployment_metadata[ROUTER_USAGE_COUNTED_TOKENS_METADATA_KEY] = total_tokens + try: + await self._increment_deployment_usage( + deployment_id=str(deployment_id), + deployment_name=deployment_name if isinstance(deployment_name, str) else None, + model_group=model_group, + total_tokens=total_tokens, + parent_otel_span=get_parent_otel_span_from_kwargs(dict(request_kwargs)), + ) + except Exception: + _ = deployment_metadata.pop(ROUTER_USAGE_COUNTED_TOKENS_METADATA_KEY, None) + raise + except Exception as e: # noqa: BLE001 # as the Python core: usage accounting never fails a served call + verbose_router_logger.debug( + "litellm.router.Router::increment_deployment_usage_for_response(): Exception occured - %s", e + ) + + async def _increment_deployment_usage( + self, + *, + deployment_id: str, + deployment_name: str | None, + model_group: str, + total_tokens: float, + parent_otel_span: "Span | None", + ) -> None: + """``_increment_deployment_usage`` with its one request, in one pipeline; this worker's memory + then holds what Redis answered.""" + from litellm.types.caching import RedisPipelineIncrementOperation + + if not self._registry_state.cached_deployment_tracks_usage(deployment_id, model_group): + return + current_minute: Final = get_utc_datetime().strftime("%H-%M") + tpm_key: Final = RouterCacheEnum.TPM.value.format( + id=deployment_id, current_minute=current_minute, model=deployment_name + ) + rpm_key: Final = RouterCacheEnum.RPM.value.format( + id=deployment_id, current_minute=current_minute, model=deployment_name + ) + operations: Final[Sequence[RedisPipelineIncrementOperation]] = [ + RedisPipelineIncrementOperation(key=key, increment_value=increment_value, ttl=_USAGE_TTL) + for key, increment_value in ((tpm_key, total_tokens), (rpm_key, 1)) + ] + values: Final = await self._cache.async_increment_cache_pipeline( + increment_list=list(operations), parent_otel_span=parent_otel_span + ) + if values is not None and self._cache.redis_cache is not None: + for operation, value in zip(operations, values): + await self._cache.async_set_cache(operation["key"], int(value), local_only=True, ttl=_USAGE_TTL) # pyright: ignore[reportUnknownMemberType] # DualCache's writes are untyped + + async def async_deployment_callback_on_failure( + self, kwargs: Mapping[str, object], completion_response: object, start_time: object, end_time: object + ) -> None: + """Count a failed call as one more request of the minute (``async_deployment_callback_on_failure``).""" + if is_batch_retrieve_call_type(kwargs.get("call_type")): + return + litellm_params: Final[_FailedCallParams] = kwargs["litellm_params"] # pyright: ignore[reportAssignmentType] # read as the Python core reads it, a missing key included + deployment_name: Final = litellm_params["metadata"].get("deployment", None) + model_group: Final = litellm_params["metadata"].get("model_group", None) + model_info: Final = litellm_params.get("model_info", {}) or {} + deployment_id: Final = model_info.get("id", None) + if model_group is None or deployment_id is None: + return + rpm_key: Final = RouterCacheEnum.RPM.value.format( + id=deployment_id, + current_minute=get_utc_datetime().strftime("%H-%M"), + model=deployment_name, + ) + with service_target(ROUTER_USAGE_TARGET): + await self._cache.async_increment_cache( # pyright: ignore[reportUnknownMemberType] # DualCache's writes are untyped + key=rpm_key, + value=1, + parent_otel_span=get_parent_otel_span_from_kwargs(dict(kwargs)), + ttl=_USAGE_TTL, + ) + + # -- the plugin context ------------------------------------------------------------------------ + + def _update_kwargs_before_fallbacks( + self, + model: str, + kwargs: dict[str, object], # mutable-ok: the core updates the request kwargs in place + metadata_variable_name: str | None = "metadata", + ) -> None: + """``_update_kwargs_before_fallbacks``: a trace id and the requested group, in place.""" + _ = kwargs.setdefault("litellm_trace_id", str(uuid.uuid4())) + alias: Final = model if self._registry_state._core_get_model_from_alias(model=model) else None # pyright: ignore[reportPrivateUsage] # the core reads its own host registry + kwargs.setdefault(metadata_variable_name, {}).update({"model_group": model, "model_group_alias": alias}) # pyright: ignore[reportArgumentType, reportAttributeAccessIssue, reportUnknownMemberType] # the bucket, as the Python core writes it + + def _params_sent_to_deployment( + self, request_kwargs: Mapping[str, object], deployment: "Deployment | None" + ) -> Mapping[str, object]: + """``_params_sent_to_deployment`` of a ``Deployment``, which ``RoutingContext.deployment_params`` hands in.""" + params: Final = deployment.litellm_params.model_dump(exclude_none=True) if deployment else {} + configured: Final = as_str_mapping(RoutingContext(self).settings().default_litellm_params) # pyright: ignore[reportArgumentType, reportUnknownMemberType, reportUnknownArgumentType] # the core's RoutingContext + defaults: Final = {k: v for k, v in (configured or {}).items() if v is not None} + tool_choice: Final = {"tool_choice": params["tool_choice"]} if params.get("tool_choice") is not None else {} + return MappingProxyType({**params, **defaults, **tool_choice, **request_kwargs}) + + +__all__ = ["RustLegacyMembers"] diff --git a/litellm/router_rust/surface/members.py b/litellm/router_rust/surface/members.py new file mode 100644 index 00000000000..0f7dc23d966 --- /dev/null +++ b/litellm/router_rust/surface/members.py @@ -0,0 +1,163 @@ +""" +``RustRegistryMembers``: the Rust core's public registry members outside ``registry()`` and +``apply``: ``add_deployment``, ``set_model_list``, the ``model_list`` attribute, the environment +gate, the deprecated id hash, ``print_deployment`` and the pre-call checks the plugin context reads. + +Each one works on the core's host registry (``litellm/router_rust/surface/registry.py``), which hands every +change to the Rust core. The rules are the Python router core's, ported (never imported). +""" + +import copy +from collections.abc import Mapping, Sequence +from typing import TYPE_CHECKING, Final + +from litellm._logging import verbose_router_logger +from litellm.litellm_core_utils.sensitive_data_masker import SensitiveDataMasker +from litellm.router_api import deployment_id +from litellm.router_rust.steps.precall import count_tokens, pre_call_checks +from litellm.router_rust.surface.registry import HostRegistry, model_info_is_active_for_environment +from litellm.types.router import Deployment + +if TYPE_CHECKING: + from litellm.router_python_host import PythonHost + from litellm.router_rust.core import RustCore + + +class _CallCounter: + """``total_calls``, ``success_calls`` or ``fail_calls``: plain attributes on the Python core, + which a write replaces and a ``del`` removes; every call then reads what is there.""" + + def __init__(self, name: str) -> None: + self._name: Final = name + + def __get__(self, core: "RustCore | None", owner: type | None = None) -> object: + if core is None: + return self + try: + return getattr(core._endpoints.counters, self._name) # pyright: ignore[reportPrivateUsage] # the core's own counters + except AttributeError: + raise core._no_attribute(self._name) from None # pyright: ignore[reportPrivateUsage] # see above + + def __set__(self, core: "RustCore", value: object) -> None: + setattr(core._endpoints.counters, self._name, value) # pyright: ignore[reportPrivateUsage] # see __get__ + + def __delete__(self, core: "RustCore") -> None: + try: + delattr(core._endpoints.counters, self._name) # pyright: ignore[reportPrivateUsage] # see __get__ + except AttributeError: + raise core._no_attribute(self._name) from None # pyright: ignore[reportPrivateUsage] # see __get__ + + +class RustRegistryMembers: + """Mixed into ``RustCore``, which supplies its host registry and host.""" + + total_calls: Final = _CallCounter("total_calls") + success_calls: Final = _CallCounter("success_calls") + fail_calls: Final = _CallCounter("fail_calls") + + @property + def _registry_state(self) -> HostRegistry: + raise NotImplementedError + + @property + def _python_host(self) -> "PythonHost": + raise NotImplementedError + + def add_deployment(self, deployment: Deployment) -> Deployment | None: + """Add a deployment unless its id exists (``add_deployment``).""" + return self._registry_state.add_deployment(deployment) + + def set_model_list(self, model_list: Sequence[object]) -> None: + """Replace every deployment (``set_model_list``); aliases and wildcard routes stay.""" + self._registry_state.set_model_list(model_list) + + @property + def model_list(self) -> Sequence[object]: + """The live model list (the deprecated ``model_list`` attribute).""" + return self._registry_state._core_model_list # pyright: ignore[reportPrivateUsage] # the core reads its own host registry + + def _assign_model_list(self, model_list: Sequence[object]) -> None: + """``router.model_list = [...]``: the list is swapped as given, without reindexing, and the + registry version moves once.""" + self._registry_state.replace_model_list(model_list) # pyright: ignore[reportArgumentType] # the list as assigned, as the core keeps it + + @staticmethod + def deployment_is_active_for_environment(deployment: Deployment) -> bool: + """Whether LITELLM_ENVIRONMENT admits the deployment (``deployment_is_active_for_environment``).""" + return model_info_is_active_for_environment(model_info=deployment.model_info) # pyright: ignore[reportArgumentType] # ModelInfo reads like a mapping + + @staticmethod + def generate_model_id(model_group: str, litellm_params: Mapping[str, object]) -> str: + """The deprecated id hash (``generate_model_id``).""" + from litellm.router_deprecated import ( + _note, # pyright: ignore[reportPrivateUsage] # the router's deprecation notice + ) + + _note("generate_model_id", "litellm.router_api.deployment_id(model_group, litellm_params)") + return deployment_id(model_group, litellm_params) + + async def set_response_headers( + self, response: object, model_group: str | None = None, request_kwargs: Mapping[str, object] | None = None + ) -> object: + """Stamp the group's remaining usage and the model id on a response (``set_response_headers``).""" + headed: Final[object] = await self._registry_state.set_response_headers( # pyright: ignore[reportAny] # the response as the core hands it back + response, model_group, None if request_kwargs is None else dict(request_kwargs) + ) + return headed + + def replay_model_cost_registrations(self) -> None: + """Re-register the served deployments' cost-map entries (``replay_model_cost_registrations``).""" + self._registry_state.replay_model_cost_registrations() + + def _count_pre_call_check_tokens( + self, + messages: Sequence[Mapping[str, object]] | None, + input: str | list[object] | None, # mutable-ok: the request field, as the Python core takes it + request_kwargs: Mapping[str, object] | None = None, + tokenizer_model: str = "", + deployments: Sequence[Mapping[str, object]] = (), + ) -> int: + """``_count_pre_call_check_tokens``, which context compaction counts with.""" + return count_tokens(self._python_host, messages, input, request_kwargs, tokenizer_model, deployments) + + def _pre_call_checks( + self, + model: str, + healthy_deployments: Sequence[Mapping[str, object]], + messages: object = None, + input: object = None, + request_kwargs: Mapping[str, object] | None = None, + input_token_count: int | None = None, + skip_inline_token_count: bool = False, + request_deployments: Sequence[Mapping[str, object]] | None = None, + ) -> Sequence[Mapping[str, object]]: + """``_pre_call_checks``, which context compaction admits a client-managed request with.""" + return pre_call_checks( + self._python_host, + self._registry_state, # pyright: ignore[reportArgumentType] # the host registry serves the reads + model, + healthy_deployments, + messages, + input, + request_kwargs, + input_token_count, + skip_inline_token_count, + request_deployments, + ) + + def print_deployment(self, deployment: Mapping[str, object]) -> Mapping[str, object]: + """A copy of the deployment, of the type it was given, with its api key masked + (``print_deployment``). A ``Deployment`` and its params read and write like dicts.""" + try: + printed: Final = copy.deepcopy(deployment) + litellm_params: Final = printed["litellm_params"] + if self._python_host.dynamic().redact_user_api_key_info: + masker: Final = SensitiveDataMasker(visible_prefix=2, visible_suffix=0) + printed["litellm_params"] = masker.mask_dict(litellm_params) # pyright: ignore[reportArgumentType, reportIndexIssue] # the deployment's params, written as the Python core writes them + elif "api_key" in litellm_params: # pyright: ignore[reportOperatorIssue] # see the docstring + litellm_params["api_key"] = litellm_params["api_key"][:2] + "*" * 10 # pyright: ignore[reportIndexIssue] # see the docstring + except Exception as e: + verbose_router_logger.debug("Error occurred while printing deployment - %s", e) + raise + else: + return printed diff --git a/litellm/router_rust/surface/model_info.py b/litellm/router_rust/surface/model_info.py new file mode 100644 index 00000000000..f742225e2f4 --- /dev/null +++ b/litellm/router_rust/surface/model_info.py @@ -0,0 +1,871 @@ +# pyright: reportUnknownMemberType=false, reportUnknownVariableType=false, reportUnknownArgumentType=false, reportUnknownParameterType=false, reportMissingParameterType=false, reportAny=false, reportExplicitAny=false, reportMissingTypeArgument=false, reportAttributeAccessIssue=false, reportTypedDictNotRequiredAccess=false +# (ported from the Python router core as it is written there, over untyped litellm helpers) +""" +``HostModelInfo``: model info, group info, usage reads and response headers for the Rust core's +host registry. + +router-core holds the rules: a deployment's model info (``get_router_model_info``, +``get_deployment_model_info``: ``router-core/src/model_info.rs``), a model group's info and the +configured-value reads (``_set_model_group_info``, ``get_model_listing_info``, the configured token +limits, mode, display name and service tiers: ``router-core/src/group_info.rs``), and the usage +counters' keys (``RouterCoreHandle.usage_key``). What lives in this process is answered here as a +query asks for it, at query time: the cost map (``get_model_info``, ``litellm.model_cost``), +provider resolution, the wildcard pattern routes, what the background refresh discovered, and a +group deployment's validated params, supported params, endpoints, fast mode and reasoning efforts. +``ModelGroupInfo`` is built here from the group's first deployment (its validation is the model's) +and takes what router-core's merge assigned. + +Still the Python router core's rules here: the model group alias a group-info query resolves +first (the alias map is the registry's live Python objects), the cache of discovered limits, the +configured ``max_input_tokens`` read (a value echoed from the loaded cost map is skipped), and the +response headers. +""" + +import builtins +import dataclasses +import math +from collections.abc import Callable, Mapping, Sequence +from functools import partial +from types import MappingProxyType +from typing import TYPE_CHECKING, Any, Final, Union, cast # noqa: TID251 # the core's own signatures, ported unchanged + +from pydantic import BaseModel, TypeAdapter +from typing_extensions import overload + +import litellm +from litellm._internal_context import service_target +from litellm._logging import verbose_router_logger +from litellm.litellm_core_utils.add_retry_fallback_headers import ( + apply_quality_router_decision_headers, + apply_remaining_usage_headers, + apply_response_model_id, + complexity_router_decision_headers, + ensure_response_additional_headers, + prepare_response_for_header_attachment, +) +from litellm.litellm_core_utils.batch_utils import deployment_supported_endpoints +from litellm.litellm_core_utils.core_helpers import as_str_mapping, coerce_token_limit +from litellm.litellm_core_utils.get_model_cost_map import GetModelCostMap +from litellm.litellm_core_utils.reasoning_effort_capability import ( + deployment_is_catalog_mapped, + intersect_supported_reasoning_efforts, + resolve_supported_reasoning_efforts, +) +from litellm.litellm_core_utils.routing_common_utils import team_may_use_deployment +from litellm.llms.anthropic.common_utils import AnthropicModelInfo +from litellm.llms.bedrock.common_utils import get_bedrock_base_model +from litellm.router_python_host import python_host +from litellm.router_utils.pre_call_checks.io_token_rate_limit_check import build_io_token_rate_limit_headers +from litellm.router_utils.router_callbacks.track_deployment_metrics import find_deployment_metadata +from litellm.router_utils.routing_read_batch import ROUTER_USAGE_TARGET +from litellm.types.router import ( + Deployment, + DeploymentModelListingInfo, + DeploymentTypedDict, + DiscoveredDeploymentModelInfo, + LiteLLM_Params, + ModelGroupInfo, +) +from litellm.types.utils import COST_MAP_LOOKUP_KEY, ModelInfo, echoed_cost_map_fields +from litellm.types.utils import ModelInfo as ModelMapInfo +from litellm.utils import get_utc_datetime, is_generalized_model_info + +if TYPE_CHECKING: + from litellm.rust_bridge._native import ( + RouterCall, + RouterCoreHandle, + _ModelInfoSteps, # pyright: ignore[reportPrivateUsage] # the stub's step shapes + ) + +_MODEL_INFO_ADAPTER: Final = TypeAdapter(Mapping[str, object]) + +# The key router-core's merge reads as an opaque value (``router-core/src/model_info.rs``). +_OPAQUE_KEY: Final = "__litellm_python_value__" + + +class _Wire: + """Values as router-core's model-info merge reads them: plain JSON, with what JSON cannot spell + (a datetime, a tuple, a non-finite float) passed as an opaque token the merge moves between + layers without reading, and restored to the same object on the way back.""" + + def __init__(self) -> None: + self._values: Final[list[object]] = [] # mutable-ok: the tokens of one query + + def to_wire(self, value: object) -> object: + if value is None or isinstance(value, (bool, str)): + return value + if isinstance(value, int): + return value if -(2**63) <= value < 2**64 else self._token(value) + if isinstance(value, float): + return value if math.isfinite(value) else self._token(value) + if isinstance(value, list): + return [self.to_wire(item) for item in value] + if isinstance(value, dict) and all(isinstance(key, str) for key in value): + return {str(key): self.to_wire(item) for key, item in value.items()} + return self._token(value) + + def from_wire(self, value: object) -> object: + if isinstance(value, dict): + if len(value) == 1 and _OPAQUE_KEY in value: + return self._values[int(value[_OPAQUE_KEY])] + return {str(key): self.from_wire(item) for key, item in value.items()} + if isinstance(value, list): + return [self.from_wire(item) for item in value] + return value + + def _token(self, value: object) -> Mapping[str, int]: + self._values.append(value) + return {_OPAQUE_KEY: len(self._values) - 1} + + +def _drive_model_info( + call: "RouterCall[_ModelInfoSteps]", answer: Callable[[Mapping[str, object]], object] +) -> Mapping[str, object]: + """Drive one model-info merge to its end, answering each lookup with ``answer``. A lookup that + raises raises out of the query, as it raised in the Python router.""" + outcome: object = None # rebind-ok: each lookup's answer + while True: + step = call.next(outcome) + if step["kind"] == "done": + return step + if step["kind"] == "failed": + if str(step.get("error_kind")) == "model_info": + exception: object = getattr(builtins, str(step.get("error_exception")), ValueError) + raise (exception if isinstance(exception, type) else ValueError)(step.get("error_detail")) + raise RuntimeError(f"router-core ({step.get('error_kind')}): {step.get('error')}") + outcome = answer(step) + + +def _configured_model_info(deployment: Mapping[str, object]) -> Mapping[str, object]: + return _MODEL_INFO_ADAPTER.validate_python(deployment.get("model_info") or {}) + + +def _operator_max_input_tokens(deployment: Mapping[str, object]) -> int | None: + """``_operator_max_input_tokens``: the deployment's own limit, skipping one a saved + ``/model/info`` response copied from the cost map.""" + model_info: Final = _configured_model_info(deployment) + catalog_key: Final = model_info.get(COST_MAP_LOOKUP_KEY) + catalog_entry: Final = ( + GetModelCostMap.loaded_model_cost_map().get(catalog_key) if isinstance(catalog_key, str) else None + ) + if catalog_entry is not None and "max_input_tokens" in echoed_cost_map_fields(model_info, catalog_entry): + return None + return coerce_token_limit(model_info.get("max_input_tokens")) + + +# The ModelGroupInfo fields router-core's group merge compares against, as the model validated them. +_GROUP_COMPARED_FIELDS: Final = frozenset( + { + "providers", + "max_input_tokens", + "max_output_tokens", + "input_cost_per_token", + "output_cost_per_token", + "supports_fast_mode", + "supported_endpoints", + "supported_reasoning_efforts", + } +) +# The ModelGroupInfo fields the Python router assigns tuples to. +_GROUP_TUPLE_FIELDS: Final = frozenset({"supported_endpoints", "supported_reasoning_efforts"}) + + +def _group_field(field: str, value: object) -> object: + """A merged group field as the Python router assigns it: a tuple field takes the list as a tuple.""" + if field in _GROUP_TUPLE_FIELDS and isinstance(value, list): + return tuple(cast(list[object], value)) # cast-ok: the merge's list + return value + + +@dataclasses.dataclass +class _GroupBuild: + """One group-info merge as the host answers it: the deployments it reads, each one's validated + params once its first lookup builds them, and the group built from the first deployment.""" + + model_list: "Sequence[dict[str, Any]]" # mutable-ok: the stored entries, read only + team_id: str | None + # Filled as the lookups arrive. + params: dict[int, LiteLLM_Params] = dataclasses.field(default_factory=dict) # mutable-ok: see above + info: ModelGroupInfo | None = None + + +class HostModelInfo: + """Mixed into ``HostRegistry``, which holds the model list, the indexes and the host.""" + + def _live_handle(self) -> "RouterCoreHandle | None": ... # the registry's: the handle ``RustCore`` set + + def _core_handle(self) -> "RouterCoreHandle": + handle: Final = self._live_handle() + if handle is None: + raise RuntimeError("the host registry reads model info through its Rust core") + return handle + + def _core_get_model_list_of_routed_group( + self, model_group: str, team_id: str | None = None + ) -> list: # mutable-ok: a fresh list, as the core returns it + if team_id is not None and self._team_deployments_named(team_id, model_group): + return self._core_get_all_deployments(model_name=model_group, team_id=team_id) + named: Final = [ + *self._core_get_all_deployments(model_name=model_group), + *self._core_get_model_list_from_routing_groups(model_name=model_group), + ] + return named or self._get_wildcard_deployments(model_name=model_group) + + def _get_wildcard_deployments( + self, model_name: str, team_id: str | None = None + ) -> list[dict[str, object]]: # mutable-ok: a fresh list + """The deployments a wildcard pattern routes ``model_name`` to, renamed to it (the routing + runs in router-core, through the registry's pattern router views).""" + team_router: Final = self._core_team_pattern_routers.get(team_id) if team_id is not None else None + matches: Final = [ + *self._core_pattern_router.get_deployments_by_pattern(model=model_name), + *(team_router.get_deployments_by_pattern(model=model_name) if team_router is not None else ()), + ] + return [{**DeploymentTypedDict(**m), "model_name": model_name} for m in matches] # pyright: ignore[reportCallIssue] # a stored entry + + def _core_get_model_group_info( + self, model_group: str, *, include_hidden: bool = False, team_id: str | None = None + ) -> ModelGroupInfo | None: + """ + For a given model group name, return the combined model info + + Returns: + - ModelGroupInfo if able to construct a model group + - None if error constructing model group info or hidden model group (unless include_hidden) + """ + ## Check if model group alias + if model_group in self._core_model_group_alias: + item: Final = self._core_model_group_alias[model_group] + if isinstance(item, str): + _router_model_group = item # rebind-ok: ported from the Python core unchanged + elif isinstance(item, dict): + if item["hidden"] is True and not include_hidden: + return None + else: + _router_model_group = item["model"] # rebind-ok: ported from the Python core unchanged + else: + return None + + return self._set_model_group_info( + model_group=_router_model_group, + user_facing_model_group_name=model_group, + team_id=team_id, + ) + + ## Check if actual model + return self._set_model_group_info( + model_group=model_group, user_facing_model_group_name=model_group, team_id=team_id + ) + + def _set_model_group_info( + self, model_group: str, user_facing_model_group_name: str, team_id: str | None = None + ) -> ModelGroupInfo | None: + """ + For a given model group name, return the combined model info + + Returns: + - ModelGroupInfo if able to construct a model group + - None if error constructing model group info + + router-core merges the group (``router-core/src/group_info.rs``); this picks its + deployments, answers what needs this process (validated params, model info, provider, + capabilities), builds ``ModelGroupInfo`` from the first deployment and sets what the merge + assigned on it. + """ + serves_team_deployments: Final = team_id is not None and bool( + self._team_deployments_named(team_id, model_group) + ) + model_list: Final = self._core_get_model_list_of_routed_group(model_group, team_id) + description: Final[str | None] = next( + (d for d in (_configured_model_info(m).get("description") for m in model_list) if isinstance(d, str)), + None, + ) + # The wildcard check is asked only for a deployment that is not the group's by name. + pattern_routes: Final = ( + not serves_team_deployments + and any("model_name" in m and m["model_name"] != model_group for m in model_list) + and self._core_pattern_router.route(model_group) is not None + ) + wire: Final = _Wire() + group: Final = _GroupBuild(model_list=model_list, team_id=team_id) + call: Final = self._core_handle().model_group_info( + { + "model_group": model_group, + "user_facing_model_group_name": user_facing_model_group_name, + "serves_team_deployments": serves_team_deployments, + "pattern_routes": pattern_routes, + "description": description, + "deployments": [wire.to_wire(model) for model in model_list], + } + ) + done: Final = _drive_model_info(call, partial(self._answer_group_lookup, group=group, wire=wire)) + answer: Final = as_str_mapping(done["value"]) + if answer is None or group.info is None: + return None + for field, value in (as_str_mapping(answer["assignments"]) or {}).items(): + setattr(group.info, field, _group_field(field, wire.from_wire(value))) + return group.info + + def _answer_group_lookup(self, step: Mapping[str, object], group: "_GroupBuild", wire: "_Wire") -> object: + """One lookup of a group-info merge: a deployment's facts, or the group's first entry.""" + match step["lookup"]: + case "group_params": + index: Final = int(str(step["index"])) + litellm_params: Final = LiteLLM_Params(**group.model_list[index]["litellm_params"]) + group.params[index] = litellm_params # rebind-ok: the merge's state, which each lookup advances + return { + "model": litellm_params.model, + "configurable_clientside_auth_params": wire.to_wire( + litellm_params.configurable_clientside_auth_params + ), + } + case "group_deployment": + return self._group_deployment(group, int(str(step["index"])), wire) + case "group_capabilities": + deployment: Final = group.model_list[int(str(step["index"]))] + merged_info: Final[object] = wire.from_wire(step["model_info"]) + model_info: Final = cast(Mapping[str, object], merged_info) # cast-ok: the merged model info + litellm_model: Final = str(step["litellm_model"]) + llm_provider: Final = str(step["llm_provider"]) + efforts: Final = resolve_supported_reasoning_efforts( + model_info, deployment_is_mapped=step["mapped"] is True + ) + return { + "supported_endpoints": wire.to_wire( + list( + deployment_supported_endpoints( + model_info.get("supported_endpoints"), deployment, llm_provider + ) + ) # pyright: ignore[reportArgumentType] # a stored entry, as the core passes it + if team_may_use_deployment(_configured_model_info(deployment).get("team_id"), group.team_id) # pyright: ignore[reportArgumentType] # the configured team id + else [] + ), + "supports_fast_mode": AnthropicModelInfo.supports_fast_mode(litellm_model, llm_provider), + "reasoning_efforts": None if efforts is None else list(efforts), + } + case "group_seed": + entry: Final[object] = wire.from_wire(step["info"]) + seed: Final = cast(dict[str, Any], entry) # cast-ok: the first deployment's entry + group.info = ModelGroupInfo(**seed) # rebind-ok: the merge's state, built from the first deployment + return group.info.model_dump(mode="json", include=set(_GROUP_COMPARED_FIELDS)) + case "reasoning_intersect": + current: Final = cast("Sequence[str] | None", step["current"]) # cast-ok: plain JSON efforts + resolved: Final = cast("Sequence[str] | None", step["resolved"]) # cast-ok: plain JSON efforts + intersected: Final = intersect_supported_reasoning_efforts(current, resolved) + return None if intersected is None else list(intersected) + case _: + return self._answer_model_info_lookup(step, wire) + + def _group_deployment(self, group: "_GroupBuild", index: int, wire: "_Wire") -> Mapping[str, object]: + """A group deployment's model info (None when it fails), whether the catalog maps it, and its + provider; with no model info, the provider's supported params.""" + model: Final = group.model_list[index] + litellm_params: Final = group.params[index] + model_info_dict: Final = model.get("model_info", {}) + model_info: object + try: + model_id: Final = model_info_dict.get("id", None) + model_info = ( # rebind-ok: one branch binds it + self._core_get_deployment_model_info(model_id=model_id, model_name=litellm_params.model) + if model_id is not None + else None + ) + except Exception: # noqa: BLE001 # ported as the core writes it + model_info = None # rebind-ok: see above + deployment_is_mapped: Final = deployment_is_catalog_mapped(model_info, model_info_dict) # pyright: ignore[reportArgumentType] # the merged model info, or None + litellm_model, llm_provider = self._model_group_llm_provider(litellm_params) + answer: Final[dict[str, object]] = { # mutable-ok: built here + "model_info": wire.to_wire(model_info), + "mapped": deployment_is_mapped, + "litellm_model": litellm_model, + "llm_provider": llm_provider, + } + if model_info is None: + answer["supported_openai_params"] = wire.to_wire( + self._host.invoke("get_supported_openai_params")(model=litellm_model, custom_llm_provider=llm_provider) + ) + return answer + + def _cached_get_model_group_info(self, model_group: str) -> ModelGroupInfo | None: + """ + Cached version of get_model_group_info, uses @lru_cache wrapper + + This is a speed optimization, since set_response_headers makes a call to get_model_group_info on every request + """ + return self._core_get_model_group_info(model_group) + + def _core_cached_model_group_info(self, model_group: str) -> ModelGroupInfo | None: + return self._cached_get_model_group_info(model_group) + + @overload + def _core_get_router_model_info( + self, + deployment: Union[dict, "Deployment"], # mutable-ok: ported from the Python core unchanged + received_model_name: str, + id: None = None, + ) -> ModelMapInfo: + pass + + @overload + def _core_get_router_model_info(self, deployment: None, received_model_name: str, id: str) -> ModelMapInfo: + pass + + def _core_get_router_model_info( + self, + deployment: Union[dict, "Deployment"] | None, # mutable-ok: ported from the Python core unchanged + received_model_name: str, + id: str | None = None, + ) -> ModelMapInfo: + """ + For a given model id, return the model info (max tokens, input cost, output cost, etc.). + + Augment litellm info with additional params set in `model_info`. + + For azure models, ignore the `model:`. Only set max tokens, cost values if base_model is set. + For every other provider, a base_model naming the same model as `model:` can only widen its context window. + + router-core merges it (``router-core/src/model_info.rs``); this checks the deployment and + answers the cost-map lookups the merge asks for while it runs. + + Returns + - ModelInfo - If found -> typed dict with max tokens, input cost, etc. + + Raises: + - ValueError -> If model is not mapped yet + """ + if id is not None: + _deployment: Final = self._core_get_deployment(model_id=id) + if _deployment is not None: + deployment = _deployment # rebind-ok: ported from the Python core unchanged + + if deployment is None: + raise ValueError("Deployment not found") + + model_info_base_model: Final = (deployment.get("model_info") or {}).get("base_model", None) + params_base_model: Final = ( + (deployment.get("litellm_params") or {}).get("base_model", None) if model_info_base_model is None else None + ) + + ## GET PROVIDER - reuse LiteLLM_Params if already constructed + litellm_params_data: Final = deployment.get("litellm_params") + litellm_params: LiteLLM_Params + if isinstance(litellm_params_data, LiteLLM_Params): + litellm_params = litellm_params_data # rebind-ok: ported from the Python core unchanged + elif isinstance(litellm_params_data, dict) and "model" in litellm_params_data: + litellm_params = LiteLLM_Params.model_validate( # rebind-ok: ported from the Python core unchanged + litellm_params_data + ) + else: + raise ValueError( + f"Deployment missing valid litellm_params. " + f"Got: {type(litellm_params_data).__name__}, " + f"deployment_id: {(deployment.get('model_info') or {}).get('id', 'unknown')}" + ) + + wire: Final = _Wire() + user_model_info: dict[str, object] = {} # mutable-ok: filled when the merge asks for it # rebind-ok: see above + + def read_user_model_info() -> object: + nonlocal user_model_info + raw_user_model_info: Final = deployment.get("model_info") + user_model_info = dict( # rebind-ok: see above + _MODEL_INFO_ADAPTER.validate_python( + raw_user_model_info.model_dump(exclude_none=True) + if isinstance(raw_user_model_info, BaseModel) + else raw_user_model_info or {} + ) + ) + return wire.to_wire(user_model_info) + + def answer(step: Mapping[str, object]) -> object: + if step["lookup"] == "provider": + _model, custom_llm_provider, _, _ = self._host.invoke("get_llm_provider")( + model=litellm_params.model, + litellm_params=litellm_params, + ) + return [_model, custom_llm_provider] + if step["lookup"] == "user_model_info": + return read_user_model_info() + return self._answer_model_info_lookup(step, wire) + + query: Final = { + "deployment_id": wire.to_wire((deployment.get("model_info") or {}).get("id")), + "model_info_base_model": wire.to_wire(model_info_base_model), + "params_base_model": wire.to_wire(params_base_model), + "params_model": litellm_params.model, + "extra_base_model": wire.to_wire((litellm_params.model_extra or {}).get("base_model")), + "received_model_name": received_model_name, + } + done: Final = _drive_model_info(self._core_handle().router_model_info(query), answer) + merged: Final = wire.from_wire(done["info"]) + if not isinstance(merged, dict): + return merged # pyright: ignore[reportReturnType] # the core returns get_model_info's answer as is + # The deployment's own values are its objects, as the Python router merges them. + for key in cast(list[str], done["user_keys"]): # cast-ok: router-core's key list + merged[key] = user_model_info[key] + return merged # pyright: ignore[reportReturnType] # the merged map, as the core builds it + + def _core_get_deployment_model_info(self, model_id: str, model_name: str) -> ModelInfo | None: + """ + For a given model id, return the model info + + 1. Check if model_id is in model info + 2. If not, check if litellm model name is in model info + 3. If not, return None + + router-core merges it (``router-core/src/model_info.rs``); this answers its lookups. + """ + wire: Final = _Wire() + call: Final = self._core_handle().deployment_model_info(model_id, wire.to_wire(model_name)) + done: Final = _drive_model_info(call, partial(self._answer_model_info_lookup, wire=wire)) + return wire.from_wire(done["info"]) # pyright: ignore[reportReturnType] # the merged map, as the core builds it + + def _answer_model_info_lookup(self, step: Mapping[str, object], wire: "_Wire") -> object: + """One cost-map lookup of a model-info merge, answered from this process.""" + match step["lookup"]: + case "model_info": + return self._model_info_row(wire.from_wire(step["model"]), wire, step) + case "cost_entry": + key: Final = str(step["key"]) + model_cost: Final = litellm.model_cost if step["process"] else self._host.dynamic().model_cost + return {"entry": wire.to_wire(model_cost.get(key))} if key in model_cost else None + case "pattern_models": + return self._pattern_models(str(step["name"]), wire) + case "bedrock_base": + return get_bedrock_base_model(str(step["model_id"])) + case "discovered": + return wire.to_wire(dict(self._core_get_discovered_model_info(wire.from_wire(step["id"])))) # pyright: ignore[reportArgumentType] # the deployment's id, as configured + case "log": + log: Final = verbose_router_logger.error if step["level"] == "error" else verbose_router_logger.debug + log("%s", step["message"]) + return None + case other: + raise ValueError(f"router-core asked an unknown model-info lookup {other!r}") + + def _model_info_row(self, model: object, wire: "_Wire", step: Mapping[str, object]) -> object: + """``get_model_info(model=...)`` as a lookup answers it: the row, ``{"failed": True}`` when a + tolerated lookup raises, and for an exact lookup whether a generalization rule made it.""" + # The base model's own window is read through the process host, as the Python router reads it. + host: Final = python_host if step["exact"] else self._host + try: + row: Final = host.invoke("get_model_info")(model=model) + except Exception: # noqa: BLE001 # get_model_info raises ModelNotMappedError or a bare Exception for an unmapped model + if step["tolerate"]: + return {"failed": True} + raise + if step["exact"]: + return {"row": wire.to_wire(row), "generalized": is_generalized_model_info(row)} + return wire.to_wire(row) + + def _pattern_models(self, name: str, wire: "_Wire") -> object: + """The ``{id, model}`` of each deployment a wildcard pattern routes ``name`` to.""" + potential_models: Final = self._core_pattern_router.route(name) + if potential_models is None: + return None + routed: Final[list[object]] = [] # mutable-ok: built here + for potential_model in potential_models: + try: + routed.append( + { + "id": wire.to_wire((potential_model.get("model_info") or {}).get("id")), + "model": wire.to_wire((potential_model.get("litellm_params") or {}).get("model")), + } + ) + except Exception: # noqa: BLE001 # ported as the core writes it + verbose_router_logger.debug("model info lookup failed; ignored as the core ignores it") + return routed + + def _core_get_discovered_model_info(self, model_id: str | None) -> Mapping[str, int]: + cached: Final[object] = self._discovered_model_info_cache.get_cache(model_id) + if ( + model_id is not None + and isinstance(cached, DiscoveredDeploymentModelInfo) + and cached.deployment is self._core_get_model_info(model_id) + ): + configured: Final = TypeAdapter(Mapping[str, object]).validate_python(cached.deployment["model_info"]) + return MappingProxyType({key: value for key, value in cached.limits.items() if configured.get(key) is None}) + return MappingProxyType({}) + + def _core_get_model_listing_info(self, model_name: str) -> DeploymentModelListingInfo | None: + """ + Return what the concrete deployments behind model_name contribute to its + /v1/models entry: the cost-map keys for their underlying models, plus the widest + configured or discovered token limits. Resolved via O(1) index + lookup. + + Returns None for wildcard-expanded or unknown names, where the listed name is the + real model name and no deployment-specific information exists, and treats a + malformed configured limit as absent rather than failing the listing. + + The whole group is read rather than just its first deployment, so a group that + mixes models does not advertise a window that depends on config order; the widest + one is reported, which is what get_model_group_info already shows the Admin UI. + Keys are deduplicated, so the ordinary group of interchangeable deployments of one + model still costs the caller a single cost-map lookup. Unlike get_model_group_info, + this never triggers pattern matching or deep copies, so it is safe to call per + listed model on the /v1/models hot path. + + router-core combines the deployments (``router-core/src/group_info.rs``). + """ + deployments: Final = self._core_deployments_named(model_name) + if not deployments: + return None + wire: Final = _Wire() + call: Final = self._core_handle().model_listing_info([wire.to_wire(deployment) for deployment in deployments]) + done: Final = _drive_model_info(call, partial(self._answer_model_info_lookup, wire=wire)) + listing: Final = as_str_mapping(done["value"]) or {} + return DeploymentModelListingInfo( + cost_map_keys=tuple(cast(list[str], listing["cost_map_keys"])), # cast-ok: router-core's key list + max_input_tokens=cast("int | None", listing["max_input_tokens"]), # cast-ok: router-core's limit + max_output_tokens=cast("int | None", listing["max_output_tokens"]), # cast-ok: router-core's limit + ) + + def _core_get_configured_token_limits(self, model_name: str) -> "tuple[int | None, int | None]": + """ + Return (max_input_tokens, max_output_tokens) configured or discovered for a concrete + deployment of model_name, via O(1) index lookup. + + Returns (None, None) for wildcard-expanded or unknown names, and treats a + malformed configured value as absent rather than failing the caller. + + Deliberately reads one deployment rather than aggregating the group the way + get_model_listing_info does: its caller truncates an embedding input to this + value, so the widest window in a mixed group would be the wrong answer there. + """ + deployment: Final = self._core_get_deployment_by_model_group_name(model_group_name=model_name) + if deployment is None: + return (None, None) + wire: Final = _Wire() + configured: Final = { + key: wire.to_wire(value) for key, value in deployment.model_info.model_dump(exclude_none=True).items() + } + call: Final = self._core_handle().configured_token_limits(wire.to_wire(deployment.model_info.id), configured) + done: Final = _drive_model_info(call, partial(self._answer_model_info_lookup, wire=wire)) + limits: Final = cast("list[int | None]", done["value"]) # cast-ok: router-core's two limits + return (limits[0], limits[1]) + + def _core_get_configured_mode(self, model_name: str) -> "str | None": + """Return the mode explicitly configured for a concrete deployment.""" + deployment: Final = self._core_get_deployment_by_model_group_name(model_group_name=model_name) + if deployment is None: + return None + return self._core_handle().configured_text(_Wire().to_wire(deployment.model_info.get("mode"))) + + def _core_get_configured_display_name(self, model_name: str) -> "str | None": + """ + Return the display_name explicitly configured in a concrete deployment's + model_info for model_name, via O(1) index lookup. + + Returns None for wildcard-expanded or unknown names, and treats a + non-string or empty configured value as absent rather than failing the + listing. Like get_configured_token_limits, this never triggers pattern + matching or deep copies, so it is safe to call per listed model on the + /v1/models hot path. + """ + deployment: Final = self._core_get_deployment_by_model_group_name(model_group_name=model_name) + if deployment is None: + return None + return self._core_handle().configured_text(_Wire().to_wire(deployment.model_info.get("display_name"))) + + def _core_get_configured_service_tiers(self, model_name: str, team_id: str | None = None) -> tuple[object, ...]: + """ + Return the service_tiers value each deployment a request from team_id + to model_name can route to (see _routable_deployments) configures in + its model_info, unvalidated and in model_list order, None for a + deployment that sets none; the caller validates the shape it expects + and decides how the deployments combine. + + Returns an empty tuple for wildcard-expanded or unknown names. + """ + wire: Final = _Wire() + tiers: Final = self._core_handle().configured_service_tiers( + [ + wire.to_wire(dict(_configured_model_info(deployment))) + for deployment in self._routable_deployments(model_name, team_id) + ] + ) + return tuple(wire.from_wire(tier) for tier in tiers) + + def _core_get_configured_max_input_tokens( + self, model_name: str, team_id: str | None = None + ) -> tuple[int | None, ...]: + """ + Return the max_input_tokens each deployment a request from team_id to + model_name can route to (see _routable_deployments) sets in its own + model_info, in model_list order, None for a deployment that sets none + or a malformed one. Unlike get_model_listing_info, neither the cost map + nor a discovered limit is read, so only an operator's own value counts, + and a value a saved /model/info response copied from the cost map is + skipped too. + + Returns an empty tuple for wildcard-expanded or unknown names. + """ + return tuple( + _operator_max_input_tokens(deployment) for deployment in self._routable_deployments(model_name, team_id) + ) + + async def _core_get_model_group_usage(self, model_group: str) -> tuple[int | None, int | None]: + """ + Returns current tpm/rpm usage for model group + + Parameters: + - model_group: str - the received model name from the user (can be a wildcard route). + + Returns: + - usage: Tuple[tpm, rpm] + """ + dt: Final = get_utc_datetime() + current_minute: Final = dt.strftime("%H-%M") # use the same timezone regardless of system clock + tpm_keys: Final[list[str]] = [] # mutable-ok: ported from the Python core unchanged + rpm_keys: Final[list[str]] = [] # mutable-ok: ported from the Python core unchanged + + model_list: Final = self._core_get_model_list(model_name=model_group) + if model_list is None: # no matching deployments + return None, None + + for model in model_list: + id: str | None = model.get("model_info", {}).get("id") + litellm_model: str | None = model["litellm_params"].get( + "model" + ) # USE THE MODEL SENT TO litellm.completion() - consistent with how global_router cache is written. + if id is None or litellm_model is None: + continue + tpm_keys.append(self._core_handle().usage_key(id, litellm_model, "tpm", current_minute)) + rpm_keys.append(self._core_handle().usage_key(id, litellm_model, "rpm", current_minute)) + combined_tpm_rpm_keys: Final = tpm_keys + rpm_keys + + with service_target(ROUTER_USAGE_TARGET): + combined_tpm_rpm_values: Final = await self._core_cache.async_batch_get_cache(keys=combined_tpm_rpm_keys) + if combined_tpm_rpm_values is None: + return None, None + + rpm_start: Final = len(tpm_keys) + tpm_usage_list: Final[list | None] = combined_tpm_rpm_values[:rpm_start] # mutable-ok: ported from the Python core unchanged # fmt: skip + rpm_usage_list: Final[list | None] = combined_tpm_rpm_values[rpm_start:] # mutable-ok: ported from the Python core unchanged # fmt: skip + + ## TPM + tpm_usage: int | None = None # rebind-ok: ported from the Python core unchanged + if tpm_usage_list is not None: + for t in tpm_usage_list: + if isinstance(t, int): + if tpm_usage is None: + tpm_usage = 0 + tpm_usage += t + ## RPM + rpm_usage: int | None = None # rebind-ok: ported from the Python core unchanged + if rpm_usage_list is not None: + for t in rpm_usage_list: + if isinstance(t, int): + if rpm_usage is None: + rpm_usage = 0 + rpm_usage += t + return tpm_usage, rpm_usage + + async def get_model_group_io_token_usage(self, model_group: str) -> tuple[int | None, int | None]: + """ + Returns current ITPM/OTPM usage for a model group (sum across deployments). + """ + dt: Final = get_utc_datetime() + current_minute: Final = dt.strftime("%H-%M") + itpm_keys: Final[list[str]] = [] # mutable-ok: ported from the Python core unchanged + otpm_keys: Final[list[str]] = [] # mutable-ok: ported from the Python core unchanged + + model_list: Final = self._core_get_model_list(model_name=model_group) + if model_list is None: + return None, None + + for model in model_list: + model_id: str | None = model.get("model_info", {}).get("id") + litellm_model: str | None = model["litellm_params"].get("model") + if model_id is None or litellm_model is None: + continue + itpm_keys.append(self._core_handle().usage_key(model_id, litellm_model, "itpm", current_minute)) + otpm_keys.append(self._core_handle().usage_key(model_id, litellm_model, "otpm", current_minute)) + + with service_target(ROUTER_USAGE_TARGET): + combined_values: Final = await self._core_cache.async_batch_get_cache(keys=itpm_keys + otpm_keys) + if combined_values is None: + return None, None + + itpm_values: Final = combined_values[: len(itpm_keys)] + otpm_values: Final = combined_values[len(itpm_keys) :] + + total_itpm: int | None = None # rebind-ok: ported from the Python core unchanged + for value in itpm_values: + if isinstance(value, int): + total_itpm = (total_itpm or 0) + value + + total_otpm: int | None = None # rebind-ok: ported from the Python core unchanged + for value in otpm_values: + if isinstance(value, int): + total_otpm = (total_otpm or 0) + value + + return total_itpm, total_otpm + + async def _core_get_remaining_model_group_usage( + self, model_group: str + ) -> dict[str, int]: # mutable-ok: ported from the Python core unchanged + model_group_info: Final = self._cached_get_model_group_info(model_group) + + returned_dict: Final[dict[str, int]] = {} # mutable-ok: ported from the Python core unchanged + + # ITPM/OTPM groups emit input/output token headers, but they may also set + # tpm/rpm, so build both sets rather than returning early - clients and + # prometheus gauges that read the standard headers still get data. + if model_group_info is not None and (model_group_info.itpm is not None or model_group_info.otpm is not None): + current_itpm, current_otpm = await self.get_model_group_io_token_usage(model_group) + returned_dict.update( + build_io_token_rate_limit_headers( + itpm_limit=model_group_info.itpm, + otpm_limit=model_group_info.otpm, + current_itpm=current_itpm, + current_otpm=current_otpm, + ) + ) + + tpm_limit: Final = model_group_info.tpm if model_group_info is not None else None + rpm_limit: Final = model_group_info.rpm if model_group_info is not None else None + + if tpm_limit is None and rpm_limit is None: + return returned_dict + + current_tpm, current_rpm = await self._core_get_model_group_usage(model_group) + + if tpm_limit is not None: + returned_dict["x-ratelimit-remaining-tokens"] = tpm_limit - (current_tpm or 0) + returned_dict["x-ratelimit-limit-tokens"] = tpm_limit + if rpm_limit is not None: + returned_dict["x-ratelimit-remaining-requests"] = rpm_limit - (current_rpm or 0) + returned_dict["x-ratelimit-limit-requests"] = rpm_limit + + return returned_dict + + async def set_response_headers( + self, + response: object, + model_group: str | None = None, + request_kwargs: dict[str, object] | None = None, # mutable-ok: ported from the Python core unchanged + ) -> Any: # noqa: ANN401 # the core's signature, ported unchanged + """ + Add the most accurate rate limit headers for a given model response. + + ## TODO: add model group rate limit headers + # - if healthy_deployments > 1, return model group rate limit headers + # - else return the model's rate limit headers + """ + response = prepare_response_for_header_attachment(response) # rebind-ok: ported from the Python core unchanged + if response is None: + return response + + additional_headers: Final = ensure_response_additional_headers(response) + apply_response_model_id( + response, find_deployment_metadata(request_kwargs) if request_kwargs is not None else None + ) + additional_headers["x-litellm-model-group"] = model_group + apply_quality_router_decision_headers(additional_headers, request_kwargs) + additional_headers.update(complexity_router_decision_headers(request_kwargs)) + + if model_group is not None: + remaining_usage: Final = await self._core_get_remaining_model_group_usage(model_group) + apply_remaining_usage_headers(additional_headers, remaining_usage) + return response diff --git a/litellm/router_rust/surface/model_list.py b/litellm/router_rust/surface/model_list.py new file mode 100644 index 00000000000..405a4b47d7b --- /dev/null +++ b/litellm/router_rust/surface/model_list.py @@ -0,0 +1,375 @@ +""" +``HostedModelList``: the Rust core's live ``model_list``, read back from router-core. + +router-core holds the deployments. This list is what ``registry().all()`` and the deprecated +``model_list`` attribute hand out: a ``list`` (so callers that check for one, serialize it or +validate it keep working) whose contents are router-core's deployment records, read through the +handle after every write. Every write to it is a changeset instead of a Python-side mutation: + +- ``append`` / ``extend`` / an ``insert`` at the end add at the end (``append``) +- removing one deployment whose id no other entry shares is a ``delete`` +- any other write (an assignment, a slice, a removal of one of several entries sharing an id, + ``clear``, ``sort``, ...) hands router-core the resulting list (``replace``) + +A build serves the deployments it added once it ends (or fails), and the list reads them back +then. After writes that only appended, it reads just the appended records +(``RouterCoreHandle.deployments_from``), so adding deployments one at a time costs each one its own +record rather than the whole list. These writes are the raw ones a caller makes: like the Python +router's list, they reindex nothing. + +An entry read back from router-core is a dict whose writes (its own, or a nested dict's) hand +router-core the list again, so an edit in place reaches it as the Python router's list would show +it. Each deployment keeps one Python object while router-core's record for it is unchanged, keyed by +its id and its place among entries sharing that id, so identity checks on stored entries (the +model info caches) mean what they did: the same object until a write changes that deployment. +""" + +import copy +import datetime +from collections.abc import Callable, Iterable, Mapping, Sequence +from types import MappingProxyType +from typing import ( + TYPE_CHECKING, + Final, + SupportsIndex, + TypeAlias, + TypeVar, + cast, # noqa: TID251 # any value a caller wrote into the list + overload, +) + +from pydantic import TypeAdapter, ValidationError + +from litellm.litellm_core_utils.core_helpers import as_str_mapping +from litellm.types.router import ModelAccessWindow + +if TYPE_CHECKING: + from litellm.rust_bridge._native import RouterCoreHandle + +Entry: TypeAlias = dict[str, object] +# (id, its place among the entries sharing it) -> (the record it was read as, the entry object) +_Stable: TypeAlias = dict[tuple[str, int], tuple[object, Entry]] + + +_DATETIME: Final = TypeAdapter(datetime.datetime) +_Field = TypeVar("_Field") # rebind-ok: a TypeVar cannot be Final + + +def _dumped_as(adapter: TypeAdapter[_Field]) -> Callable[[object], object]: + """A value validated by ``adapter``, then dumped back to its Python form.""" + + def dump(value: object) -> object: + return adapter.dump_python(adapter.validate_python(value), exclude_none=True) + + return dump + + +# The ``ModelInfo`` fields whose Python value is no JSON value, which router-core holds as strings. +_TYPED_MODEL_INFO: Final[Mapping[str, Callable[[object], object]]] = MappingProxyType( + { + "created_at": _dumped_as(_DATETIME), + "updated_at": _dumped_as(_DATETIME), + "ptu_effective_from": _dumped_as(_DATETIME), + "ptu_effective_to": _dumped_as(_DATETIME), + "access_windows": _dumped_as(TypeAdapter(tuple[ModelAccessWindow, ...])), + } +) + + +def typed_deployment(record: Mapping[str, object]) -> Mapping[str, object]: + """A deployment record as ``Deployment.to_json`` dumped it: its ``model_info`` typed again. One + with none of those fields comes back as it is, and so does a value a raw write left unreadable.""" + info: Final = as_str_mapping(record.get("model_info")) + if info is None or info.keys().isdisjoint(_TYPED_MODEL_INFO): + return record + typed: Final[dict[str, object]] = {} # mutable-ok: filled here + for key, dumped in _TYPED_MODEL_INFO.items(): + value = info.get(key) + if value is None: + continue + try: + typed[key] = dumped(value) + except ValidationError: + continue + return {**record, "model_info": {**info, **typed}} + + +def _record(value: object) -> Mapping[str, object]: + return cast(Mapping[str, object], value) # cast-ok: a JSON object router-core wrote, or a dict inside one + + +def _entry_id(entry: object) -> str | None: + info: Final = as_str_mapping((as_str_mapping(entry) or {}).get("model_info")) or {} + value: Final = info.get("id") + return None if value is None else str(value) + + +def _keys( + entries: Iterable[object], seen: Mapping[str, int] = MappingProxyType({}) +) -> tuple[list[tuple[str, int] | None], Mapping[str, int]]: # mutable-ok: a fresh list + """Each entry's identity key (its id and how many earlier entries share it, ``seen`` counting + the ids of entries before these), and the counts once past them.""" + counts: Final[dict[str, int]] = dict(seen) # mutable-ok: counted here + keys: Final[list[tuple[str, int] | None]] = [] # mutable-ok: filled here + for entry in entries: + entry_id = _entry_id(entry) + if entry_id is None: + keys.append(None) + continue + nth = counts.get(entry_id, 0) + counts[entry_id] = nth + 1 + keys.append((entry_id, nth)) + return keys, counts + + +class _HostedEntry(dict[str, object]): + """A deployment entry read back from router-core: a write to it, or to a dict inside it, hands + router-core the list again (``replace``), so it learns what the entry now says. A copy is a + plain dict.""" + + def __init__(self, record: Mapping[str, object], written: Callable[[], None]) -> None: + super().__init__( + (key, value if (nested := as_str_mapping(value)) is None else _HostedEntry(nested, written)) + for key, value in record.items() + ) + self._written: Final = written + + def __setitem__(self, key: str, value: object) -> None: + super().__setitem__(key, value) + self._written() + + def __delitem__(self, key: str) -> None: + super().__delitem__(key) + self._written() + + def pop(self, key: str, *default: object) -> object: + value: Final = super().pop(key, *default) + self._written() + return value + + def popitem(self) -> tuple[str, object]: + item: Final = super().popitem() + self._written() + return item + + def clear(self) -> None: + super().clear() + self._written() + + def update(self, *args: object, **kwargs: object) -> None: # kwargs-ok: dict.update's own arguments + super().update(*args, **kwargs) # pyright: ignore[reportCallIssue, reportArgumentType] # dict.update's own arguments + self._written() + + def setdefault(self, key: str, default: object = None) -> object: + if key in self: + return self[key] + self[key] = default + return default + + def __ior__(self, other: object) -> "_HostedEntry": # pyright: ignore[reportIncompatibleMethodOverride] # dict's in-place merge, as a write + self.update(other) + return self + + def __copy__(self) -> dict[str, object]: # mutable-ok: a plain copy + return dict(self) + + def __deepcopy__(self, memo: dict[int, object]) -> dict[str, object]: # mutable-ok: a plain copy + return copy.deepcopy(dict(self), memo) + + def __reduce_ex__(self, protocol: SupportsIndex) -> tuple[object, ...]: + return (dict, (copy.deepcopy(dict(self)),)) + + +class HostedModelList(list[Entry]): + """The live ``model_list``: router-core's deployments, every write a changeset.""" + + def __init__( + self, + handle: Callable[[], "RouterCoreHandle | None"], + apply: Callable[[Mapping[str, object]], None], + ) -> None: + super().__init__() + self._handle: Final = handle + self._apply: Final = apply + # The handle and registry version the contents were last read at. + self._read_at: tuple[object, int] | None = None + self._stable: _Stable = {} + # How many of the shown entries hold each id, for the keys of entries appended next. + self._id_counts: Mapping[str, int] = {} + # While a build runs: the length, id counts and read to go back to when it ends. + self._building: tuple[int, Mapping[str, int], tuple[object, int] | None] | None = None + + # -- reading ---------------------------------------------------------------------------------- + + def refresh(self) -> None: + """Read router-core's deployments again when its registry moved since the last read.""" + handle: Final = self._handle() + if handle is None or self._building is not None: + # While a build runs, the list shows what it accepted until router-core serves it. + return + version: Final = handle.registry_version() + if self._read_at is not None and self._read_at[0] is handle and self._read_at[1] == version: + return + read_at: Final = self._read_at + self._read_at = (handle, version) + if read_at is not None and read_at[0] is handle and handle.registry_rewritten() <= read_at[1]: + # Only appends since the last read: the shown entries stand, and the new ones follow. + super().extend(self._kept(handle.deployments_from(len(self)), appended=True)) + return + self._show(self._kept(handle.deployments())) + + def _kept(self, records: Sequence[object], *, appended: bool = False) -> list[Entry]: # mutable-ok: a fresh list + """``records`` as entries, each the object it was while its record is unchanged; when + ``appended``, they follow the shown entries, which keep theirs.""" + stable: Final[_Stable] = self._stable if appended else {} + keys, counts = _keys(records, self._id_counts if appended else {}) + entries: Final[list[Entry]] = [] # mutable-ok: filled here + for key, record in zip(keys, records, strict=True): + typed = typed_deployment(_record(record)) + held = self._stable.get(key) if key is not None else None + kept = held is not None and held[0] == typed + entry = held[1] if held is not None and kept else _HostedEntry(typed, self._entry_written) + if key is not None: + stable[key] = (held[0] if held is not None and kept else copy.deepcopy(typed), entry) + entries.append(entry) + self._stable = stable + self._id_counts = counts + return entries + + # -- a build ---------------------------------------------------------------------------------- + + def begin_build(self, *, replacing: bool) -> None: + """A build starts: router-core serves what it adds once it ends, so until then the list + shows each deployment it accepts here (``built``), after the entries it keeps, or alone + when it replaces them, as the Python router's list grows while it adds them.""" + self.refresh() + if replacing: + self._show([]) + self._id_counts = {} + self._building = (len(self), self._id_counts, self._read_at) + + def built(self, entry: Mapping[str, object]) -> None: + """A deployment the build accepted, shown until the build ends.""" + if self._building is not None: + super().extend(self._kept([entry], appended=True)) + + def end_build(self) -> None: + """The build ended (or failed): router-core serves what it added, read back in place of + the entries shown meanwhile, each kept as the object it was shown as while unchanged.""" + if self._building is None: + return + start, counts, read_at = self._building + self._building = None + super().__delitem__(slice(start, None)) + self._id_counts = counts + self._read_at = read_at + self.refresh() + + def _seed(self, entries: Sequence[object]) -> None: + """Keep ``entries``, the list router-core now holds, as the objects its records for them + read back as.""" + for key, entry in zip(_keys(entries)[0], entries, strict=True): + self._seed_one(key, entry) + + def _seed_appended(self, entries: Sequence[object]) -> None: + """Keep ``entries``, appended after the shown ones, as the objects they read back as.""" + for key, entry in zip(_keys(entries, self._id_counts)[0], entries, strict=True): + self._seed_one(key, entry) + + def _seed_one(self, key: tuple[str, int] | None, entry: object) -> None: + if key is not None and isinstance(entry, dict): + stored: Final = cast(Entry, entry) # cast-ok: a model_list entry is a dict + self._stable[key] = (copy.deepcopy(stored), stored) + + def _entry_written(self) -> None: + """A write inside an entry: router-core takes the list as it now reads.""" + self._replace(list(self)) + + def _show(self, entries: list[Entry]) -> None: # mutable-ok: the entries shown + super().__setitem__(slice(None), entries) + + # -- writing ---------------------------------------------------------------------------------- + + def _replace(self, entries: list[Entry]) -> None: # mutable-ok: the list router-core takes + # Seeded first: router-core's records for them read back as these objects however soon + # the list is read again. + self._seed(entries) + self._apply({"replace": entries}) + self.refresh() + + def replace(self, entries: Iterable[object]) -> None: + """Every deployment at once (``router.model_list = [...]``).""" + self._replace(cast(list[Entry], list(entries))) # cast-ok: the entries as assigned, which router-core validates + + def append(self, value: Entry) -> None: + self.refresh() + self._seed_appended([value]) + self._apply({"append": [value]}) + self.refresh() + + def extend(self, values: Iterable[Entry]) -> None: + for value in tuple(values): + self.append(value) + + def __iadd__(self, values: Iterable[Entry]) -> "HostedModelList": # pyright: ignore[reportIncompatibleMethodOverride] # list's in-place add, as a changeset + self.extend(values) + return self + + def insert(self, index: SupportsIndex, value: Entry) -> None: + if int(index) >= len(self): + self.append(value) + return + changed: Final = list(self) + changed.insert(index, value) + self._replace(changed) + + @overload + def __setitem__(self, index: SupportsIndex, value: Entry) -> None: ... + @overload + def __setitem__(self, index: slice, value: Iterable[Entry]) -> None: ... + def __setitem__(self, index: SupportsIndex | slice, value: object) -> None: + changed: Final = list(self) + changed[index] = value # pyright: ignore[reportArgumentType, reportCallIssue] # list's own item and slice assignment + self._replace(changed) + + def __delitem__(self, index: SupportsIndex | slice) -> None: + changed: Final = list(self) + if isinstance(index, slice): + del changed[index] + self._replace(changed) + return + removed: Final = changed.pop(index) + removed_id: Final = _entry_id(removed) + if removed_id is None or any(_entry_id(entry) == removed_id for entry in changed): + # A delete removes every deployment with the id; the list removes only this one. + self._replace(changed) + return + self._apply({"delete": [removed_id]}) + self.refresh() + + def pop(self, index: SupportsIndex = -1) -> Entry: + entry: Final = self[index] + del self[index] + return entry + + def remove(self, value: Entry) -> None: + del self[self.index(value)] + + def clear(self) -> None: + self._replace([]) + + def sort(self, *args: object, **kwargs: object) -> None: # kwargs-ok: list.sort's own arguments + changed: Final = list(self) + changed.sort(*args, **kwargs) # pyright: ignore[reportCallIssue, reportArgumentType] # list.sort's own arguments + self._replace(changed) + + def reverse(self) -> None: + self._replace(list(reversed(self))) + + def __imul__(self, count: SupportsIndex) -> "HostedModelList": # pyright: ignore[reportIncompatibleMethodOverride] # list's in-place repeat, as a changeset + self._replace(list(self) * int(count)) + return self + + def __reduce_ex__(self, protocol: SupportsIndex) -> tuple[object, ...]: + # A copy or pickle of the live list is a plain list of its entries. + return (list, (list(self),)) diff --git a/litellm/router_rust/surface/registry.py b/litellm/router_rust/surface/registry.py new file mode 100644 index 00000000000..a55a1cfc6d6 --- /dev/null +++ b/litellm/router_rust/surface/registry.py @@ -0,0 +1,2191 @@ +# pyright: reportUnknownMemberType=false, reportUnknownVariableType=false, reportUnknownArgumentType=false, reportAny=false +# (the ported core code reads untyped litellm helpers: PatternMatchRouter, Deployment.to_json, host.invoke) +""" +``HostRegistry``: the Rust core's live ``model_list`` and the indexes ``registry()`` reads. + +router-core builds the deployments (``litellm-rust/crates/router-core/src/build.rs``): it walks +the list, decides which values are ``os.environ/`` secret references, assigns the id of a +deployment that declares none and adds one deployment per ``organization``. What needs live Python +objects is a host step this registry answers, one deployment at a time (``_answer_build_step``): +``secrets`` (``get_secret``), ``validate`` (the PTU, access-window and strict param checks, and the +pricing each deployment writes into ``litellm.model_cost``), ``provider`` (``get_llm_provider``) +and ``added`` (pass-through credentials, pre-routing strategies, the patterns and indexes below). + +router-core holds the deployments. ``_core_model_list`` is ``HostedModelList`` +(litellm/router_rust/surface/model_list.py): router-core's records read back through the handle, every +write a changeset (a build serves what it added once it ends, a removal is a delete, any other +write a replace), each deployment one Python object while its record is unchanged. + +The indexes are router-core's too (``host_index.rs``), kept by the Python router's history rules: +the id, group and team position maps, ``model_names``, the only-growing ``deployment_names``, +the team public names, the provider default ids and the wildcard pattern routers. The registry +hands them out as the live views of litellm/router_rust/surface/indexes.py, whose writes are changesets. + +The lookups run in router-core (``lookup.rs``): the deployments by name (team public name first), +the model list with its alias, routing group and wildcard rows, the ids, names and access groups +it lists, the candidate ids for a route, the routable deployments, the credential deployment picks +and a team model's alternatives. Each answers with rows, positions in the list: this registry +reads its stored entries at them (``_rows``), so identity and in-place reads stay its own, and a +position router-core could not read (an index a caller wrote junk into) is read here and raises +as the Python router's read raised. What stays here needs live Python objects: the alias map and +routing groups a lookup is scoped by (``_list_scope``), the provider a wildcard request is tried +under, pydantic ``Deployment`` values, the credentials, the PTU ceilings, search tool support, a +team model's provider pick (``provider_for_generic_call``) and the SDK clients. + +Model info and group info are router-core's rules too (``model_info.rs``, ``group_info.rs``), +answered from this process through ``HostModelInfo`` (litellm/router_rust/surface/model_info.py). + +The attribute and method names follow the router core's (``_core_model_list``, +``_core_get_model_list`` ...), so ``litellm.router_api.RouterRegistry`` reads this object as its +router and every ``registry()`` query dispatches the way it does on the Python core. +""" + +import copy +import dataclasses +import os +import re +import threading +from collections.abc import Callable, Iterable, Iterator, Mapping, Sequence +from functools import lru_cache, partial +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, Literal, TypeAlias, cast # noqa: TID251 # entries as a caller wrote them + +from pydantic import TypeAdapter + +from litellm import exceptions as litellm_exceptions +from litellm import get_secret_str +from litellm._internal_context import service_target +from litellm._logging import verbose_router_logger +from litellm.caching.dual_cache import DualCache +from litellm.caching.in_memory_cache import InMemoryCache +from litellm.constants import DEFAULT_MAX_LRU_CACHE_SIZE +from litellm.litellm_core_utils.access_windows import access_windows_config_error +from litellm.litellm_core_utils.core_helpers import as_str_mapping, without +from litellm.litellm_core_utils.credential_accessor import CredentialAccessor +from litellm.litellm_core_utils.get_llm_provider_logic import ( + declared_authenticating_provider, + is_registered_custom_provider, + resolve_model_and_provider_for_metadata, +) +from litellm.litellm_core_utils.llm_cost_calc.utils import SERVICE_TIER_COST_KEY_SUFFIXES +from litellm.litellm_core_utils.pattern_match_deployments import PatternMatchRouter +from litellm.litellm_core_utils.ptu_pricing import ( + PTU_COST_ATTRIBUTION_ENV_VAR, + declares_ptu, + declares_ptu_shares, + is_ptu_cost_attribution_enabled, + ptu_config_error, + ptu_identity_error, + ptu_terms, + zeroed_ptu_pricing, +) +from litellm.litellm_core_utils.ptu_shares import ptu_capacity_warning +from litellm.litellm_core_utils.routing_common_utils import ( + provider_for_generic_call, + resolve_model_group_alias, + team_may_use_deployment, + warn_on_ignored_model_capability_flags, + warn_on_provider_credential_mismatch, + with_admin_api_key_secret_reference, + without_model_capability_flags, +) +from litellm.litellm_core_utils.routing_groups import apply_routing_group_priority +from litellm.llms.openai_like.json_loader import JSONProviderRegistry +from litellm.llms.openai_like.model_info import MODEL_INFO_REFRESH_SECONDS +from litellm.responses.bridge_check import keep_registered_mode +from litellm.router_api import RouterRegistry +from litellm.router_rust.invoke.shaping import ROUTER_CLIENTS_TARGET +from litellm.router_rust.surface.indexes import HostedIndexes +from litellm.router_rust.surface.model_info import HostModelInfo +from litellm.router_rust.surface.model_list import HostedModelList +from litellm.router_strategy.auto_router.auto_router_model_naming import classify_strategy_router_model +from litellm.router_utils.deployment_numbers import refuse_unservable_numbers, refuse_wide_numbers +from litellm.router_utils.endpoint_eligibility import warn_on_unenforced_endpoint_flag +from litellm.router_utils.pre_call_checks.io_token_rate_limit_check import deployment_has_io_token_limits +from litellm.types.router import ( + VALID_LITELLM_ENVIRONMENTS, + CredentialLiteLLMParams, + Deployment, + DeploymentTypedDict, + LiteLLM_Params, + ModelGroupInfo, + RouterModelGroupAliasItem, + RoutingGroup, + RoutingPlugin, + TaggedPreRoutingStrategy, + validate_litellm_params_strictly, +) +from litellm.types.utils import ( + DEPLOYMENT_SCOPED_TOKEN_LIMIT_FIELDS, + CustomPricingLiteLLMParams, + LlmProviders, + LlmProvidersSet, + is_server_derived_pricing_key, + shared_backend_model_info, +) +from litellm.utils import ( + ModelInfoLookupMiss, + catalog_with_runtime_registrations, + get_potential_model_names, + get_secret, + lookup_model_info_for_registration, + model_info_with_pricing_overrides, +) + +if TYPE_CHECKING: + from litellm.litellm_core_utils.ptu_shares import PTUTeamCeiling + from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler + from litellm.router_python_host import PythonHost + from litellm.router_rust.steps.callbacks import OptionalChecks + from litellm.router_rust.steps.prerouting import PreRoutingStrategies + from litellm.router_strategy.budget_limiter import RouterBudgetLimiting + from litellm.rust_bridge._native import RouterCoreHandle + +# The PTU share teams and the team ceilings read so far. +_PTUMemo: TypeAlias = tuple[ + frozenset[str], + dict[tuple[str, str], "PTUTeamCeiling | None"], +] +_MODEL_INFO_ADAPTER: Final = TypeAdapter(Mapping[str, object]) +_LITELLM_PARAMS_ADAPTER: Final = TypeAdapter(Mapping[str, object]) + + +_CACHE_PRICING_FIELDS: Final = ( + "cache_creation_input_token_cost", + "cache_creation_input_token_cost_above_1hr", + "cache_creation_input_token_cost_above_200k_tokens", + "cache_read_input_token_cost", + "cache_read_input_token_cost_above_200k_tokens", +) +_OFF_PEAK_BASE_RATE_FIELDS: Final = ( + "input_cost_per_token", + "input_cost_per_second", + "cost_per_second", + "tiered_pricing", +) + +# A stored model_list entry: the live dict the router core keeps. +UntypedEntry: TypeAlias = dict[str, object] +_TeamIndex: TypeAlias = dict[tuple[str, str], list[int]] + +# How a build's deployments join router-core's registry (`build::Install`). +BuildInstall: TypeAlias = Literal["replace", "append", "upsert"] +# Runs one router-core build (`RouterCoreHandle.build`): the entries, the path, whether it resolves +# secrets, how it installs, and the registry's answer to each step. ``RustCore`` supplies it. +BuildRunner: TypeAlias = Callable[ + [Sequence[object], str, bool, BuildInstall, Callable[[Mapping[str, object]], object]], None +] + + +@dataclasses.dataclass(slots=True) +class _BuildEntry: + """One ``set_model_list`` entry as its loop holds it (the router core pops ``model_name``, + ``litellm_params`` and ``model_info`` off the entry and keeps the rest), which router-core's + build steps name by index.""" + + extras: UntypedEntry + model_name: str + litellm_params: UntypedEntry + model_info: UntypedEntry + declared_id: str | None + # `organization` is a list, which router-core adds one deployment for each of. + per_organization: bool = False + # A retried entry keeps whether its id was declared twice in the list it came from. + duplicate: bool | None = None + + +@dataclasses.dataclass(slots=True) +class _Build: + """The state of one router-core build, which ``_answer_build_step`` reads and writes.""" + + path: Literal["create", "add"] + # `create`: the entries (a deep copy, which the build consumes), and each one once router-core + # reaches it. + raw: Sequence[UntypedEntry] = () + # Filled as the build reaches each entry. + entries: dict[int, _BuildEntry] = dataclasses.field(default_factory=dict) # mutable-ok: filled in step order + # `add`: the deployment to add, and the entry it is stored as. + deployment: Deployment | None = None + stored: UntypedEntry | None = None + # The deployment the build is on, its provider and its data-source values. + pending: Deployment | None = None + provider: str | None = None + data_source_values: tuple[tuple[int, str, str], ...] = () + # `add`: the deployment it added. + result: Deployment | None = None + # `create`: the error a deployment raised. The Python core's loop stops there, so every later + # step is answered as invalid and the build ends, then this is raised. + failure: Exception | None = None + + +def model_info_is_active_for_environment(model_info: Mapping[str, object] | None) -> bool: + """The environment-gating rule (``model_info_is_active_for_environment``): a deployment whose + model_info names ``supported_environments`` loads only where LITELLM_ENVIRONMENT is in it.""" + if model_info is None: + return True + supported_environments: Final = model_info.get("supported_environments") + if supported_environments is None: + return True + if not isinstance(supported_environments, list | tuple): + raise ValueError( # noqa: TRY004 # the core raises ValueError here + f"supported_environments must be a list of {VALID_LITELLM_ENVIRONMENTS}. " + f"but set as: {supported_environments} for model_info: {model_info}" + ) + litellm_environment: Final = get_secret_str(secret_name="LITELLM_ENVIRONMENT") + if litellm_environment is None: + raise ValueError("Set 'supported_environments' for model but not 'LITELLM_ENVIRONMENT' set in .env") + if litellm_environment not in VALID_LITELLM_ENVIRONMENTS: + raise ValueError( + f"LITELLM_ENVIRONMENT must be one of {VALID_LITELLM_ENVIRONMENTS}. but set as: {litellm_environment}" + ) + for environment in supported_environments: # pyright: ignore[reportUnknownVariableType] # a configured list + if environment not in VALID_LITELLM_ENVIRONMENTS: + raise ValueError( + f"supported_environments must be one of {VALID_LITELLM_ENVIRONMENTS}. but set as: {environment} " + f"for model_info: {model_info}" + ) + return litellm_environment in supported_environments + + +# -- pricing written into litellm.model_cost ----------------------------------------------------- + + +def _backend_model_info( + host: "PythonHost", backend_model: str, custom_llm_provider: str | None +) -> Mapping[str, object]: + """``get_model_info`` for the backend model; raises like it for an unmapped model.""" + info: Final = host.invoke("get_model_info")(model=backend_model, custom_llm_provider=custom_llm_provider) + return _MODEL_INFO_ADAPTER.validate_python(info) + + +def _backend_cost_entry( + host: "PythonHost", backend_model: str, custom_llm_provider: str | None +) -> Mapping[str, object] | None: + """The backend model's raw ``litellm.model_cost`` entry, or None when it has none.""" + try: + info: Final = _backend_model_info(host, backend_model, custom_llm_provider) + except Exception: # noqa: BLE001 # get_model_info raises plain Exception for an unmapped backend model + return None + entry: Final[object] = host.dynamic().model_cost.get(str(info.get("key") or "")) + return _MODEL_INFO_ADAPTER.validate_python(entry) if isinstance(entry, dict) else None + + +def _inherited_cache_pricing( + host: "PythonHost", model_info: Mapping[str, object], backend_model: str, provider: str | None +) -> Mapping[str, object]: + """The cache prices a custom-priced entry inherits (``_inherit_builtin_cache_pricing``).""" + inherited_fields: Final = ( + _CACHE_PRICING_FIELDS + if model_info.get("cache_read_input_token_cost") is not None + else (*_CACHE_PRICING_FIELDS, "explicit_cache_read_input_token_cost") + ) + missing_fields: Final = tuple(field for field in inherited_fields if model_info.get(field) is None) + if not missing_fields: + return {} + try: + backend_info: Final = _backend_model_info(host, backend_model, provider) + except Exception: # noqa: BLE001 # an unmapped backend model contributes nothing + return {} + return {field: backend_info[field] for field in missing_fields if backend_info.get(field) is not None} + + +def _inherited_service_tier_pricing( + host: "PythonHost", model_info: Mapping[str, object], backend_model: str, provider: str | None +) -> Mapping[str, object]: + """The service-tier rates a custom-priced entry inherits (``_inherit_builtin_service_tier_pricing``).""" + if ptu_terms(model_info) is not None and is_ptu_cost_attribution_enabled(): + return {} + if all(model_info.get(field) is None for field in ("input_cost_per_token", "output_cost_per_token")): + return {} + backend_entry: Final = _backend_cost_entry(host, backend_model, provider) + if backend_entry is None: + return {} + return { + field: copy.deepcopy(value) + for field, value in backend_entry.items() + if field.endswith(SERVICE_TIER_COST_KEY_SUFFIXES) and model_info.get(field) is None and value is not None + } + + +def _inherited_off_peak_base_rates( + host: "PythonHost", model_info: Mapping[str, object], backend_model: str, provider: str | None +) -> Mapping[str, object]: + """The whole backend entry an off-peak-only entry copies (``_inherit_builtin_base_rates_for_off_peak``).""" + if not model_info.get("off_peak_pricing"): + return {} + if any(model_info.get(field) is not None for field in _OFF_PEAK_BASE_RATE_FIELDS): + return {} + backend_entry: Final = _backend_cost_entry(host, backend_model, provider) + if backend_entry is None: + return {} + return { + field: copy.deepcopy(value) + for field, value in backend_entry.items() + if model_info.get(field) is None and value is not None + } + + +def _inherited_tiered_output_rate( + host: "PythonHost", model_info: Mapping[str, object], backend_model: str, provider: str | None +) -> Mapping[str, object]: + """The flat output rate a tier table without one inherits (``_inherit_builtin_tiered_output_rate``).""" + tiers: Final = model_info.get("tiered_pricing") + if not isinstance(tiers, list) or not tiers: + return {} + if model_info.get("output_cost_per_token") is not None: + return {} + if all(isinstance(tier, dict) and "output_cost_per_token" in tier for tier in tiers): # pyright: ignore[reportUnknownVariableType] # a configured tier table + return {} + try: + backend_info: Final = _backend_model_info(host, backend_model, provider) + except Exception: # noqa: BLE001 # an unmapped backend model contributes nothing + return {} + backend_rate: Final = backend_info.get("output_cost_per_token") + return {"output_cost_per_token": backend_rate} if backend_rate else {} + + +def _bedrock_profile(params: Mapping[str, object], model: str) -> bool: + return params.get("custom_llm_provider") == "bedrock" or model.startswith("bedrock/") + + +def _search_tool_support(deployment: Mapping[str, object]) -> bool | None: + """A deployment's answer to Codex's client ``tool_search``.""" + from litellm.responses.litellm_completion_transformation.tool_search import chat_config_builds_anthropic_request + from litellm.utils import ProviderConfigManager + + configured: Final = _model_info_of(deployment).get("supports_search_tool") + if isinstance(configured, bool): + return configured + params: Final = _params_of(deployment) + model: Final = params.get("model") + provider: Final = params.get("custom_llm_provider") + if not isinstance(model, str): + return None + try: + resolved_model, resolved_provider = resolve_model_and_provider_for_metadata( + model=model, custom_llm_provider=provider if isinstance(provider, str) else None + ) + chat_config: Final = ProviderConfigManager.get_provider_chat_config( + model=resolved_model, provider=LlmProviders(resolved_provider) + ) + except (litellm_exceptions.BadRequestError, ValueError): + return None + return True if chat_config_builds_anthropic_request(chat_config) else None + + +def cost_map_backend_model(deployment: Deployment) -> str: + """The model a deployment's prices are inherited from (``_cost_map_backend_model``).""" + model_info_base_model: Final = deployment.model_info.base_model + if isinstance(model_info_base_model, str) and model_info_base_model: + return model_info_base_model + params: Final = _LITELLM_PARAMS_ADAPTER.validate_python(deployment.litellm_params.model_dump(exclude_none=True)) + params_base_model: Final = params.get("base_model") + if isinstance(params_base_model, str) and params_base_model: + return params_base_model + model: Final = deployment.litellm_params.model + invoked_model: Final = params.get("model_id") + if isinstance(invoked_model, str) and invoked_model and _bedrock_profile(params, model): + profile_model: Final = invoked_model if invoked_model.startswith("bedrock/") else f"bedrock/{invoked_model}" + profile_info: Final = lookup_model_info_for_registration(model=profile_model, custom_llm_provider="bedrock") + if not isinstance(profile_info, ModelInfoLookupMiss): + return profile_model + return model + + +def deployment_model_cost_payload(host: "PythonHost", deployment: Deployment) -> Mapping[str, object]: + """The ``model_info`` a deployment contributes to ``litellm.model_cost`` + (``_deployment_model_cost_payload``): its model_info, its custom pricing, then the inherited rates.""" + declared: Final = dict(_MODEL_INFO_ADAPTER.validate_python(deployment.model_info.model_dump(exclude_none=True))) + custom_pricing: Final = { + field: value + for field in CustomPricingLiteLLMParams.model_fields + if (value := deployment.litellm_params.get(field)) is not None + } + backend_model: Final = cost_map_backend_model(deployment) + provider: Final = deployment.model_info.pricing_provider or deployment.litellm_params.custom_llm_provider + params: Final = _LITELLM_PARAMS_ADAPTER.validate_python(deployment.litellm_params.model_dump(exclude_none=True)) + priced: Final = {**declared, **custom_pricing} + profile_pricing: Final[Mapping[str, object]] = ( + _bedrock_profile_pricing(backend_model, priced) + if params.get("model_id") + and backend_model != deployment.litellm_params.model + and _bedrock_profile(params, deployment.litellm_params.model) + else {} + ) + with_profile: Final = {**priced, **profile_pricing} + off_peak: Final = {**with_profile, **_inherited_off_peak_base_rates(host, with_profile, backend_model, provider)} + cached: Final = ( + {**off_peak, **_inherited_cache_pricing(host, off_peak, backend_model, provider)} + if off_peak.get("input_cost_per_token") is not None + else off_peak + ) + tiers: Final = {**cached, **_inherited_service_tier_pricing(host, cached, backend_model, provider)} + return {**tiers, **_inherited_tiered_output_rate(host, tiers, backend_model, provider)} + + +def _bedrock_profile_pricing(backend_model: str, priced: Mapping[str, object]) -> Mapping[str, object]: + profile_info: Final = lookup_model_info_for_registration(model=backend_model, custom_llm_provider="bedrock") + if isinstance(profile_info, ModelInfoLookupMiss): + return {} + explicit_info: Final = _MODEL_INFO_ADAPTER.validate_python(priced) + priced_info: Final = model_info_with_pricing_overrides(profile_info, explicit_info) # pyright: ignore[reportArgumentType] # the explicit model_info, as the core passes it + return {key: value for key, value in priced_info.items() if is_server_derived_pricing_key(key)} + + +def _backend_cost_map_keys(model: str, custom_llm_provider: str | None) -> tuple[str, ...]: + """The ``litellm.model_cost`` keys a deployment's shared backend info is registered under.""" + backend_key: Final = model if custom_llm_provider is None else f"{custom_llm_provider}/{model}" + if "responses/" in backend_key: + return (backend_key, backend_key.replace("responses/", "")) + return (backend_key,) + + +def _catalog_entry_has_token_limit(catalog_entry: Mapping[str, object], field: str) -> bool: + return catalog_entry.get(field) is not None or ( + field == "max_tokens" and catalog_entry.get("max_output_tokens") is not None + ) + + +def _shared_backend_model_info_for_keys( + catalog: Mapping[str, Mapping[str, object]], + backend_keys: tuple[str, ...], + shared_model_info: Mapping[str, object], +) -> Mapping[str, object]: + """``shared_model_info`` without a deployment's token limit the catalog already sets on one of + ``backend_keys`` (``_shared_backend_model_info_for_keys``).""" + catalog_token_limit_fields: Final = frozenset( + field + for field in DEPLOYMENT_SCOPED_TOKEN_LIMIT_FIELDS + if any(_catalog_entry_has_token_limit(catalog.get(key) or {}, field) for key in backend_keys) + ) + return {field: value for field, value in shared_model_info.items() if field not in catalog_token_limit_fields} + + +def _catalog_backend_keys( + model: str, custom_llm_provider: str | None, backend_keys: tuple[str, ...] +) -> tuple[str, ...]: + """Every name the catalog may list the backend model under. The provider is the declared one: + resolving it would reach provider auth (``catalog_backend_keys``).""" + model_provider_prefix: Final = model.partition("/")[0] + catalog_provider: Final = ( + custom_llm_provider + if custom_llm_provider is not None + else model_provider_prefix + if model_provider_prefix in LlmProvidersSet + else None + ) + if catalog_provider is None: + return (*backend_keys, model) + potential_names: Final = get_potential_model_names(model, catalog_provider) + return ( + *backend_keys, + model, + potential_names["split_model"], + potential_names["stripped_model_name"], + potential_names["combined_model_name"], + potential_names["combined_stripped_model_name"], + potential_names["provider_prefixed_model_name"], + potential_names["region_free_combined_model_name"], + ) + + +def register_deployment_in_model_cost( + host: "PythonHost", + *, + model_id: str | None, + model_info: Mapping[str, object], + model: str, + custom_llm_provider: str | None, + pricing_provider: str | None = None, +) -> None: + """Write a deployment's metadata into ``litellm.model_cost`` (``_register_deployment_in_model_cost``): + the whole entry under its id, the schema fields under its backend model key(s).""" + registered: Final = ( + without(model_info, *CustomPricingLiteLLMParams.model_fields) + if classify_strategy_router_model(model) is not None + else dict(model_info) + ) + register_model: Final = host.invoke("register_model") + if model_id is not None: + register_model( + model_cost={model_id: registered}, + persist_across_reloads=False, + warning_display_name=model, + custom_llm_provider=pricing_provider or custom_llm_provider, + add_to_provider_model_sets=False, + ) + backend_keys: Final = _backend_cost_map_keys(model=model, custom_llm_provider=custom_llm_provider) + shared_model_info: Final = _shared_backend_model_info_for_keys( + catalog=catalog_with_runtime_registrations(), + backend_keys=_catalog_backend_keys(model, custom_llm_provider, backend_keys), + shared_model_info=shared_backend_model_info(registered), + ) + register_model( + model_cost={key: keep_registered_mode(key, shared_model_info) for key in backend_keys}, + persist_across_reloads=False, + ) + + +def register_deployment_pricing(host: "PythonHost", deployment: Deployment) -> None: + """Register a deployment's custom and inherited pricing (``_register_deployment_pricing``).""" + register_deployment_in_model_cost( + host, + model_id=deployment.model_info.id, + model_info=deployment_model_cost_payload(host, deployment), + model=deployment.litellm_params.model, + custom_llm_provider=deployment.litellm_params.custom_llm_provider, + pricing_provider=deployment.model_info.pricing_provider, + ) + + +# -- the registry -------------------------------------------------------------------------------- + + +def _model_info_of(entry: Mapping[str, object]) -> Mapping[str, object]: + model_info: Final[object] = entry.get("model_info") + return _MODEL_INFO_ADAPTER.validate_python(model_info) if isinstance(model_info, dict) else {} + + +def _params_of(entry: Mapping[str, object]) -> Mapping[str, object]: + params: Final[object] = entry.get("litellm_params") + return _LITELLM_PARAMS_ADAPTER.validate_python(params) if isinstance(params, dict) else {} + + +def _renamed(entry: UntypedEntry, model_name: str) -> UntypedEntry: + return {**entry, "model_name": model_name} + + +def _as_routing_group_row(deployment: Mapping[str, object]) -> UntypedEntry: + """A member deployment under its group's name, without the member's ``access_groups``.""" + model_info: Final = without(_model_info_of(deployment), "access_groups") + return {**deployment, "model_info": model_info} + + +def _ref_env_only(ref: object) -> bool: + return bool((as_str_mapping(ref) or {}).get("env_only")) + + +def _duplicate_of(step: Mapping[str, object], entry: _BuildEntry) -> bool: + """Whether the entry's declared id is declared twice in its list: a retried entry keeps the + answer its first build had.""" + return entry.duplicate if entry.duplicate is not None else step.get("duplicate_id") is True + + +def _index_key(value: object) -> str | None: + """``value`` as a key of the router's name and id indexes: a dict lookup hashes any key and only + a string can match, so another hashable key finds nothing (``None``), and an unhashable one + raises as the lookup raises. The native lookups take strings alone.""" + _ = hash(value) + return value if isinstance(value, str) else None + + +class HostRegistry(HostModelInfo): + """The live model_list and its indexes, kept the way the Python router core keeps them.""" + + def __init__( + self, + host: "PythonHost", + *, + model_group_alias: "dict[str, str | RouterModelGroupAliasItem]", # mutable-ok: the router's live alias map + ignore_invalid_deployments: bool, + on_change: Callable[[], None], + ) -> None: + self._host: Final = host + self._on_change: Final = on_change + self.ignore_invalid_deployments: bool = ignore_invalid_deployments + self._registry_version: int = 0 + self._deployment_index_lock: Final = threading.RLock() + self._core_model_group_alias: dict[str, str | RouterModelGroupAliasItem] = model_group_alias # mutable-ok: the live alias map # fmt: skip + # The live model_list: router-core's deployments read back, every write a changeset. + self._core_model_list: Final[HostedModelList] = HostedModelList(self._live_handle, self._hand_changes) + # The indexes the registry hands out: router-core's, read back, every write a changeset. + self._indexes: Final = HostedIndexes(self._live_handle, self._hand_changes) + self._core_deployment_latency_map: dict[str, float] = {} # mutable-ok: the live latency map + self._access_groups_cache: Mapping[str, Sequence[str]] | None = None + # The routing groups by name; RustCore sets them from its resolved settings. + self._core_routing_groups: dict[str, RoutingGroup] = {} # mutable-ok: the routing_groups attribute + self._routing_group_rows: tuple[UntypedEntry, ...] | None = None + self._provider_unresolved_deployments: tuple[Callable[[], None], ...] = () + # Runs router-core's deployment build; RustCore sets it before the first build. + self.build_runner: BuildRunner | None = None + self.missing_attribute: Callable[[str], AttributeError] | None = None + # Hands router-core a write its build did not make (a removal, a swapped list) as a + # changeset, and reads its current handle; RustCore sets both before the first build. + self.changes_runner: Callable[[Mapping[str, object]], None] | None = None + self.handle_lookup: Callable[[], RouterCoreHandle | None] | None = None + # The pre-routing strategy registries (``registry().plugins``) and the hooks that keep them; + # RustCore installs its ``PreRoutingStrategies`` (litellm/router_rust/steps/prerouting.py). + self._core_auto_routers: dict[str, list[TaggedPreRoutingStrategy[object]]] = {} # mutable-ok: the live registry + self._core_complexity_routers: dict[str, list[TaggedPreRoutingStrategy[object]]] = {} # mutable-ok: same + self._core_adaptive_routers: dict[str, list[TaggedPreRoutingStrategy[object]]] = {} # mutable-ok: same + self._core_quality_routers: dict[str, list[TaggedPreRoutingStrategy[object]]] = {} # mutable-ok: same + self.strategies: PreRoutingStrategies | None = None + # The router's optional pre-call checks (deployment budgets, prompt caching pins); + # RustCore installs its ``OptionalChecks`` (litellm/router_rust/steps/callbacks.py). + self.checks: OptionalChecks | None = None + # The Rust core's resolution for a request (`_core_get_routable_deployments`), set by the core. + self.routable_lookup: ( + Callable[[str, Mapping[str, object], str | None], Sequence[Mapping[str, object]]] | None + ) = None + # A deployment's cached `max_parallel_requests` limit (litellm/router_rust/invoke/slots.py), set by the core. + self.max_parallel_requests_lookup: Callable[[Mapping[str, object], Mapping[str, object]], object] | None = None + # `plugins("routing")`: the router's routing plugins, set by the core. + self._core_routing_plugins: list[RoutingPlugin] = [] # mutable-ok: the Python core hands out its live list + # `zero_cost()`: the per-deployment zero-cost lookup the auth checks fill, emptied with the + # group info caches. + self._zero_cost_cache: dict[str, bool] = {} # mutable-ok: the auth checks write into it + # The routing cache usage reads come from; RustCore sets it to the one its Rust core writes. + self._core_cache: DualCache = DualCache() + self._discovered_model_info_cache: InMemoryCache = InMemoryCache( + max_size_in_memory=1, default_ttl=2 * MODEL_INFO_REFRESH_SECONDS + ) + # The PTU share teams and team ceilings, until the model list next changes. + self._ptu_cache: _PTUMemo | None = None + self._cached_get_model_group_info: Callable[[str], ModelGroupInfo | None] = lru_cache( # pyright: ignore[reportIncompatibleMethodOverride] # the per-router cache shadows the uncached method, as the core keeps it + maxsize=DEFAULT_MAX_LRU_CACHE_SIZE + )(self._core_get_model_group_info) + self._core_cached_deployment_model_info: Callable[[str, str], object] = lru_cache( + maxsize=DEFAULT_MAX_LRU_CACHE_SIZE + )(self._core_get_deployment_model_info) + self.cached_deployment_tracks_usage: Callable[[str, str], bool] = lru_cache(maxsize=DEFAULT_MAX_LRU_CACHE_SIZE)( + self._deployment_tracks_usage + ) + + def __getattr__(self, name: str) -> object: + from litellm.router_rust.core import RustCoreUnsupported + + missing: Final = self.__dict__.get("missing_attribute") + if name == "_core_model_group_alias" and missing is not None: + # `del router.model_group_alias`: every read raises, as on the Python core. + raise missing(name) + raise RustCoreUnsupported(f"registry().{name.removeprefix('_core_')} is not served by the Rust router core") + + # -- building --------------------------------------------------------------------------------- + + def build(self, model_list: Sequence[object] | None) -> None: + """The constructor's registry: ``set_model_list`` and the latency map, as the core builds them.""" + if model_list is None: + return + self._discovered_model_info_cache = InMemoryCache( + max_size_in_memory=max(len(model_list), 1), default_ttl=2 * MODEL_INFO_REFRESH_SECONDS + ) + self.set_model_list(model_list) + for entry in model_list: + params = _params_of(_LITELLM_PARAMS_ADAPTER.validate_python(entry)) + if "model" in params: + self._core_deployment_latency_map[str(params["model"])] = 0 + + async def arefresh_model_info(self, client: "AsyncHTTPHandler | None") -> None: + """``_core_arefresh_model_info``: token limits the served OpenAI-compatible deployments + advertise on their models endpoint, read with a few workers over a snapshot of the list.""" + import asyncio + + from litellm.llms.openai_like.model_info import MODEL_INFO_REFRESH_CONCURRENCY + + deployments: Final = iter(tuple(self._core_model_list)) + + async def refresh_worker() -> None: + for raw_deployment in deployments: + try: + await self._arefresh_deployment_model_info(raw_deployment, client=client) + except Exception: # noqa: BLE001 # one invalid deployment must not prevent refreshing the others + verbose_router_logger.debug("Could not refresh deployment model info") + + _ = await asyncio.gather(*(refresh_worker() for _ in range(MODEL_INFO_REFRESH_CONCURRENCY))) + self._invalidate_model_group_info_cache() + + async def _arefresh_deployment_model_info( + self, raw_deployment: Mapping[str, object], *, client: "AsyncHTTPHandler | None" + ) -> None: + from litellm.llms.custom_httpx.http_handler import get_async_httpx_client + from litellm.llms.openai_like.model_info import ( + MODEL_INFO_DISCOVERY_PROVIDERS, + get_openai_compatible_model_info, + ) + from litellm.types.router import DiscoveredDeploymentModelInfo + from litellm.utils import aresolve_api_key_secret_reference + + deployment: Final = Deployment.model_validate(raw_deployment) + params: Final = LiteLLM_Params.model_validate( + MappingProxyType( + { + **deployment.litellm_params.model_dump(exclude_none=True), + **( + self._core_get_deployment_credentials_with_provider(deployment.model_info.id or "") + or MappingProxyType({}) + ), + } + ) + ) + model, provider, dynamic_api_key, api_base = self._host.invoke("get_llm_provider")( # pyright: ignore[reportAny] # litellm's untyped tuple + model=params.model, litellm_params=params + ) + if provider not in MODEL_INFO_DISCOVERY_PROVIDERS: + return + if api_base is None or "*" in model or params.get("use_clientside_credentials"): # pyright: ignore[reportUnknownMemberType] # the params' untyped get + return + api_key: Final = await aresolve_api_key_secret_reference( + params.api_key or dynamic_api_key, # pyright: ignore[reportAny] # see above + model=model, # pyright: ignore[reportAny] # see above + llm_provider=provider, # pyright: ignore[reportAny] # see above + upstream=MappingProxyType({"api_base": params.api_base}), + ) + headers: Final = TypeAdapter(Mapping[str, str]).validate_python( + params.get("extra_headers") or params.get("headers") or MappingProxyType({}) # pyright: ignore[reportUnknownMemberType] # see above + ) + auth_headers: Final = ( + MappingProxyType({"authorization": f"Bearer {api_key}"}) if api_key else MappingProxyType({}) + ) + limits: Final = await get_openai_compatible_model_info( + model=model, # pyright: ignore[reportAny] # see above + api_base=api_base, # pyright: ignore[reportAny] # see above + headers=MappingProxyType( + {**auth_headers, **MappingProxyType({key.lower(): value for key, value in headers.items()})} + ), + client=client or get_async_httpx_client(llm_provider=LlmProviders.OPENAI), + cache=self._core_cache.in_memory_cache, + ) + model_id: Final = deployment.model_info.id + if not limits or model_id is None or self._core_get_model_info(model_id) is not raw_deployment: + return + self._discovered_model_info_cache.max_size_in_memory = max(len(self._core_model_list), 1) + self._discovered_model_info_cache.delete_cache(model_id) + self._discovered_model_info_cache.set_cache( + model_id, + DiscoveredDeploymentModelInfo(deployment=raw_deployment, limits=limits), # pyright: ignore[reportArgumentType] # the model_list entry, as the core keeps it + ) + self._invalidate_model_group_info_cache() + + def _deployment_tracks_usage(self, deployment_id: str, model_group: str) -> bool: + """``_deployment_tracks_usage``: a limit on the deployment or in its merged model info, where + the cost map's own ``tpm`` and ``rpm`` count too.""" + deployment_info: Final = self._core_get_deployment(model_id=deployment_id) + if deployment_info is None: + return False + deployment_model_info: Final = self._core_get_router_model_info( + deployment=deployment_info, + received_model_name=model_group, + ) + configured_limits: Final[tuple[object, ...]] = ( + deployment_info.get("tpm", None), + deployment_info.get("rpm", None), + deployment_info.litellm_params.tpm, + deployment_info.litellm_params.rpm, + deployment_model_info.get("tpm", None), + deployment_model_info.get("rpm", None), + ) + return any(limit is not None for limit in configured_limits) or deployment_has_io_token_limits( + deployment_info.model_dump() + ) + + def _invalidate_model_group_info_cache(self) -> None: + self._ptu_cache = None + self._cached_get_model_group_info.cache_clear() # pyright: ignore[reportFunctionMemberAccess] # an lru_cache + self._core_cached_deployment_model_info.cache_clear() # pyright: ignore[reportFunctionMemberAccess] # an lru_cache + self.cached_deployment_tracks_usage.cache_clear() # pyright: ignore[reportFunctionMemberAccess] # an lru_cache + self._zero_cost_cache.clear() + self._routing_group_rows = None + + def set_routing_groups(self, groups: Sequence[RoutingGroup]) -> None: + """``_init_routing_groups``' registry side: the groups by name, and the caches they feed.""" + self._core_routing_groups = {group.group_name: group for group in groups} + self._invalidate_model_group_info_cache() + self._invalidate_access_groups_cache() + + def _invalidate_access_groups_cache(self) -> None: + self._access_groups_cache = None + self._registry_version += 1 + + def set_model_list(self, model_list: Sequence[object]) -> None: + """Replace every deployment (``set_model_list``). All or nothing: when an entry raises, + the deployments served before the call are put back and the error is raised.""" + previous: Final = [copy.deepcopy(dict(entry)) for entry in self._core_model_list] + try: + self._replace_model_list(model_list) + except Exception: + self._replace_model_list(previous) + raise + + def _replace_model_list(self, model_list: Sequence[object]) -> None: + self._discovered_model_info_cache.flush_cache() + original_model_list: Final[list[UntypedEntry]] = copy.deepcopy(list(model_list)) # pyright: ignore[reportAssignmentType] # model_list entries # mutable-ok: a deep copy the build consumes + if self.strategies is not None: + self.strategies.reset() + self._provider_unresolved_deployments = () + self._invalidate_model_group_info_cache() + self._invalidate_access_groups_cache() + ptu_declared: Final = tuple( + str(entry.get("model_name")) + for entry in original_model_list + if (ptu_info := _model_info_of(entry)).get("db_model") is not True and declares_ptu(ptu_info) + ) + if ptu_declared and not is_ptu_cost_attribution_enabled(): + verbose_router_logger.warning( + "PTU fields are set on config.yaml deployment(s) %s, but PTU cost attribution is disabled, so no " + "flat cost accrues and this traffic is billed per token. Set %s=True to enable it", + ", ".join(ptu_declared), + PTU_COST_ATTRIBUTION_ENV_VAR, + ) + # router-core walks the list (one deployment per organization, secrets resolved first, + # ids assigned), asking this registry about each deployment in turn; it starts the list + # and its id, name and team indexes over, and takes the given names as `model_names`. + self._run_build( + _Build(path="create", raw=original_model_list), + original_model_list, + resolve_secrets=True, + install="replace", + ) + if self.strategies is not None: + self.strategies.finalize() + self._on_change() + + # -- the build's steps (router-core's `build::build`) ------------------------------------------ + + def _run_build( + self, build: _Build, entries: Sequence[object], *, resolve_secrets: bool, install: BuildInstall + ) -> None: + """Have router-core build ``entries``, answering its steps from this registry.""" + if self.build_runner is None: + raise RuntimeError("the host registry builds deployments through its Rust core") + for entry in entries: + refuse_wide_numbers(entry) + self._core_model_list.begin_build(replacing=install == "replace") + try: + self.build_runner(entries, build.path, resolve_secrets, install, partial(self._answer_shown, build)) + finally: + self._core_model_list.end_build() + if build.failure is not None: + # router-core served what it built before the entry that raised (`set_model_list` + # cleared the list first), so the router is left as the Python core leaves it. + raise build.failure + + def _answer_shown(self, build: _Build, step: Mapping[str, object]) -> object: + """A build step's answer; a deployment the ``added`` step hands router-core shows in the + live list from then on (router-core serves it when the build ends).""" + answer: Final = self._answer_build_step(build, step) + stored: Final = as_str_mapping(answer).get("entry") if step["kind"] == "added" else None # pyright: ignore[reportOptionalMemberAccess] # an added step answers a mapping + if isinstance(stored, Mapping): + self._core_model_list.built(cast(Mapping[str, object], stored)) # cast-ok: the entry it stores + return answer + + def _answer_build_step(self, build: _Build, step: Mapping[str, object]) -> object: + """The answer to one of router-core's build steps. A ``set_model_list`` deployment that + fails is left out when the router ignores invalid deployments (``_create_deployment``), + and retried on the next price data reload when its provider did not resolve.""" + if build.failure is not None: + return {"invalid": True} + kind: Final = step["kind"] + index: Final = int(str(step["index"])) + refs: Final = step.get("refs") + if kind == "secrets" and isinstance(refs, list) and not any(_ref_env_only(ref) for ref in refs): + return self._build_secrets(build, index, refs) + if kind == "validate": + # A new deployment: the entry is popped where the loop pops it, outside the error + # handling, and nothing of the last deployment carries over. + build.pending = None # rebind-ok: the build's state, which each step advances + build.provider = None # rebind-ok: the build's state, which each step advances + build.data_source_values = () # rebind-ok: the build's state, which each step advances + if build.path == "create": + _ = self._build_entry(build, index) + try: + if kind == "secrets": + return self._build_data_sources(build, refs if isinstance(refs, list) else []) + if kind == "validate": + return self._build_validate(build, index, step) + if kind == "provider": + build.provider = self._build_provider(build) # rebind-ok: the build's state, which each step advances + return {"provider": build.provider} + return self._build_added(build) + except Exception as e: + if build.path != "create": + raise + if not self.ignore_invalid_deployments: + build.failure = e # rebind-ok: raised once router-core ends the build + return {"invalid": True} + if isinstance(e, litellm_exceptions.BadRequestError): + entry: Final = build.entries[index] + retried: Final = dataclasses.replace(entry, duplicate=_duplicate_of(step, entry)) + self._provider_unresolved_deployments = ( + *self._provider_unresolved_deployments, + partial(self._retry_create, retried), + ) + verbose_router_logger.exception( + "Error creating deployment: %s, ignoring and continuing with other deployments.", e + ) + return {"invalid": True} + + def _build_entry(self, build: _Build, index: int) -> _BuildEntry: + """Entry ``index`` as ``set_model_list``'s loop holds it, popped off the first time a step + names it (so a malformed entry raises where the loop raises).""" + held: Final = build.entries.get(index) + if held is not None: + return held + model: Final = build.raw[index] + model_name: Final = model.pop("model_name") + raw_params: Final = model.pop("litellm_params") + litellm_params: Final[UntypedEntry] = raw_params if isinstance(raw_params, dict) else {} # pyright: ignore[reportAssignmentType] # configured params + model_info: Final = model.pop("model_info", {}) + info_dict: Final[UntypedEntry] = model_info if isinstance(model_info, dict) else {} # pyright: ignore[reportAssignmentType] # a configured model_info + entry: Final = _BuildEntry( + extras=model, + model_name=str(model_name), + litellm_params=litellm_params, + model_info=info_dict, + declared_id=None if info_dict.get("id") is None else str(info_dict["id"]), + per_organization=isinstance(litellm_params.get("organization"), list), + ) + build.entries[index] = entry # rebind-ok: the build's state, which each step advances + return entry + + def _build_secrets(self, build: _Build, index: int, refs: Sequence[object]) -> Sequence[object]: + """``set_model_list``'s ``get_secret`` for each top-level ``os.environ/`` value router-core + found, written into the entry's params.""" + entry: Final = self._build_entry(build, index) + references: Final = tuple(as_str_mapping(ref) or {} for ref in refs) + values: Final = tuple(get_secret(str(reference["name"])) for reference in references) + entry.litellm_params.update( + {str(reference["key"]): value for reference, value in zip(references, values, strict=True)} + ) + return values + + def _build_data_sources(self, build: _Build, refs: Sequence[object]) -> Sequence[object]: + """``_add_deployment``'s environment reads for ``dataSources[].parameters``, applied to the + deployment where it applied them (``_build_added``).""" + references: Final = tuple(as_str_mapping(ref) or {} for ref in refs) + build.data_source_values = tuple( # rebind-ok: the build's state, which each step advances + ( + int(str(reference["source"])), + str(reference["key"]), + os.environ.get(str(reference["name"]).replace("os.environ/", ""), ""), + ) + for reference in references + ) + return tuple(value for _, _, value in build.data_source_values) + + def _build_validate(self, build: _Build, index: int, step: Mapping[str, object]) -> Mapping[str, object]: + if build.path == "add": + return self._validate_added_deployment(build) + entry: Final = self._build_entry(build, index) + routed: Final = as_str_mapping(step["entry"]) or {} + routed_info: Final = as_str_mapping(routed.get("model_info")) or {} + if "id" not in entry.model_info: + entry.model_info["id"] = routed_info.get("id") + if entry.per_organization: + entry.litellm_params["organization"] = (as_str_mapping(routed.get("litellm_params")) or {}).get( + "organization" + ) + duplicate: Final = _duplicate_of(step, entry) + deployment: Final = self._validated_deployment(entry, taken=duplicate) + if deployment is None: + return {"skip": True} + served: Final = with_admin_api_key_secret_reference(deployment) + build.pending = served # rebind-ok: the build's state, which each step advances + # A dump of this core's own: a `mock_response` ModelResponse warns, and only Python's dumps may. + return {"entry": build.pending.to_json(exclude_none=True, warnings=False)} + + def _validated_deployment(self, entry: _BuildEntry, *, taken: bool) -> Deployment | None: + """``_create_deployment`` up to ``_add_deployment``: the config checks, the deployment, its + pricing, and None when the environment gate leaves it out.""" + model_name: Final = entry.model_name + litellm_params: Final = entry.litellm_params + model_info: Final = entry.model_info + config_sourced: Final = model_info.get("db_model") is not True + identity_error: Final = ( + ptu_identity_error( + declared_id=entry.declared_id, + taken=taken, + current_id=model_info.get("id"), # pyright: ignore[reportArgumentType] # the configured id + model_name=model_name, + ) + if config_sourced and ptu_terms(model_info) is not None + else None + ) + ptu_error: Final = ( + (ptu_config_error(model_info, model_name=model_name) or identity_error) if config_sourced else None + ) + if ptu_error is not None and (declares_ptu_shares(model_info) or is_ptu_cost_attribution_enabled()): + raise ValueError(ptu_error) + access_windows_error: Final = access_windows_config_error(model_info, model_name=model_name) + if access_windows_error is not None: + raise ValueError(access_windows_error) + capacity_warning: Final = ( + ptu_capacity_warning( + model_name, MappingProxyType({"model_info": model_info, "litellm_params": litellm_params}) + ) + if is_ptu_cost_attribution_enabled() + else None + ) + if capacity_warning is not None: + verbose_router_logger.warning(capacity_warning) + zeroed_pricing: Final = zeroed_ptu_pricing(model_info, litellm_params) if config_sourced else None + merged_params: Final[Mapping[str, object]] = ( + litellm_params if zeroed_pricing is None else MappingProxyType({**litellm_params, **zeroed_pricing}) + ) + params: Final[LiteLLM_Params] = validate_litellm_params_strictly(LiteLLM_Params, dict(**merged_params)) + declared_params: Final = _LITELLM_PARAMS_ADAPTER.validate_python(litellm_params) + warn_on_provider_credential_mismatch(model_name=model_name, litellm_params=declared_params) + warn_on_ignored_model_capability_flags(model_name=model_name, litellm_params=declared_params) + warn_on_unenforced_endpoint_flag(model_name=model_name, model_info=model_info) + deployment: Final = without_model_capability_flags( + Deployment(**entry.extras, model_name=model_name, litellm_params=params, model_info=model_info) # pyright: ignore[reportArgumentType] # the entry's extra fields, as the core passes them + ) + # The values as typed: a cost written as "inf", a share written as 1e20. + refuse_unservable_numbers(deployment.to_json(exclude_none=True, warnings=False)) + register_deployment_pricing(self._host, deployment) + if model_info_is_active_for_environment(model_info=deployment.model_info) is not True: # pyright: ignore[reportArgumentType] # ModelInfo reads like a mapping + verbose_router_logger.warning( + "Ignoring deployment %s as it is not active for environment %s", + deployment.model_name, + deployment.model_info["supported_environments"], + ) + return None + for pattern in deployment.litellm_params.get("tag_regex") or []: + try: + re.compile(pattern) + except re.error as exc: + raise ValueError( + f"Invalid regex in tag_regex for model '{deployment.model_name}': {pattern!r} — {exc}" + ) from exc + return deployment + + def _validate_added_deployment(self, build: _Build) -> Mapping[str, object]: + """``add_deployment`` up to ``_add_deployment``: an id the registry holds is skipped.""" + deployment: Final = build.deployment + if deployment is None: + raise RuntimeError("an add build holds its deployment") + if deployment.model_info.id and self._core_has_model_id(deployment.model_info.id): + return {"skip": True} + declared_params: Final = deployment.litellm_params.model_dump(exclude_none=True) + warn_on_provider_credential_mismatch(model_name=deployment.model_name, litellm_params=declared_params) + warn_on_ignored_model_capability_flags(model_name=deployment.model_name, litellm_params=declared_params) + warn_on_unenforced_endpoint_flag( + model_name=deployment.model_name, model_info=deployment.model_info.model_dump() + ) + served: Final = with_admin_api_key_secret_reference(without_model_capability_flags(deployment)) + build.pending = served # rebind-ok: the build's state, which each step advances + build.stored = served.to_json(exclude_none=True) # rebind-ok: the build's state, which each step advances + refuse_unservable_numbers(build.stored) + return {"entry": build.stored} + + def _build_provider(self, build: _Build) -> str | None: + """``_add_deployment``'s provider: None for a prompt-management model, else the provider + ``get_llm_provider`` resolves, refused when litellm does not serve it.""" + deployment: Final = build.pending + if deployment is None: + raise RuntimeError("a provider step follows a validated deployment") + litellm_model: Final = deployment.litellm_params.model + if isinstance(deployment.litellm_params.drop_params, str): + verbose_router_logger.warning( + "model=%s drop_params=%r is not a flag value, treating it as unset", + deployment.model_name, + deployment.litellm_params.drop_params, + ) + dynamic: Final = self._host.dynamic() + if "/" in litellm_model and litellm_model.split("/")[0] in dynamic.known_custom_logger_compatible_callbacks: + return None + if declared_authenticating_provider(litellm_model, deployment.litellm_params.custom_llm_provider) is not None: + _, provider = self._model_group_llm_provider(deployment.litellm_params) + return provider + _, custom_llm_provider, _, _ = self._host.invoke("get_llm_provider")( + model=deployment.litellm_params.model, + custom_llm_provider=deployment.litellm_params.get("custom_llm_provider", None), + api_base=deployment.litellm_params.api_base, + litellm_params=deployment.litellm_params, + ) + if ( + custom_llm_provider not in dynamic.provider_list + and not JSONProviderRegistry.exists(custom_llm_provider) + and not is_registered_custom_provider(custom_llm_provider) + ): + raise Exception(f"Unsupported provider - {custom_llm_provider}") # noqa: TRY002 # the core raises a plain Exception + return custom_llm_provider + + def _build_added(self, build: _Build) -> Mapping[str, object]: + """The rest of ``_add_deployment``: the entry router-core stores, which joins the list and + the indexes (``host_index.rs``) when the step returns.""" + deployment: Final = build.pending + if deployment is None: + raise RuntimeError("an added step follows a validated deployment") + self._register_deployment(deployment, build.provider, build.data_source_values) + build.pending = None # rebind-ok: the build's state, which each step advances + build.data_source_values = () # rebind-ok: the build's state, which each step advances + self._invalidate_model_group_info_cache() + self._invalidate_access_groups_cache() + if build.path == "create": + return {"entry": deployment.to_json(exclude_none=True)} + entry: Final = build.stored if build.stored is not None else deployment.to_json(exclude_none=True) + register_deployment_pricing(self._host, deployment) + build.result = deployment # rebind-ok: the build's state, which each step advances + return {"entry": entry} + + def _retry_create(self, entry: _BuildEntry) -> None: + """A ``set_model_list`` deployment left out when its provider did not resolve, built again + and added at the end.""" + build: Final = _Build(path="create") + build.entries[0] = entry + self._run_build( + build, + [ + { + **entry.extras, + "model_name": entry.model_name, + "litellm_params": entry.litellm_params, + "model_info": entry.model_info, + } + ], + resolve_secrets=False, + install="append", + ) + + @staticmethod + def _model_group_llm_provider(litellm_params: LiteLLM_Params) -> tuple[str, str]: + try: + return resolve_model_and_provider_for_metadata( + model=litellm_params.model, custom_llm_provider=litellm_params.custom_llm_provider + ) + except litellm_exceptions.BadRequestError as e: + verbose_router_logger.error("litellm.router.py::get_model_group_info() - %s", e) + return "", "" + + def _register_deployment( + self, + deployment: Deployment, + custom_llm_provider: str | None, + data_source_values: Sequence[tuple[int, str, str]], + ) -> None: + """``_add_deployment`` after the provider: its data-source values, pass-through + credentials and pre-routing strategies (router-core registers its names and patterns).""" + if deployment.litellm_params.rpm is None and getattr(deployment, "rpm", None) is not None: + deployment.litellm_params.rpm = getattr(deployment, "rpm") # noqa: B009 # an extra field of the entry # rebind-ok: the core sets it on the deployment it adds + if deployment.litellm_params.tpm is None and getattr(deployment, "tpm", None) is not None: + deployment.litellm_params.tpm = getattr(deployment, "tpm") # noqa: B009 # an extra field of the entry # rebind-ok: see above + data_sources: Final = deployment.litellm_params.get("dataSources", []) or [] + for source, key, value in data_source_values: + data_sources[source]["parameters"][key] = value + if custom_llm_provider is not None: + self._initialize_deployment_for_pass_through(deployment, custom_llm_provider) + if self.strategies is not None: + self.strategies.register(deployment) + + def _initialize_deployment_for_pass_through(self, deployment: Deployment, custom_llm_provider: str) -> None: + """Register vertex credentials for a pass-through deployment (``_initialize_deployment_for_pass_through``).""" + if deployment.litellm_params.use_in_pass_through is not True or custom_llm_provider != "vertex_ai": + return + credential_name: Final = deployment.litellm_params.litellm_credential_name + credential_values: Final = ( + CredentialAccessor.get_credential_values(credential_name) if credential_name is not None else {} + ) + project: Final = credential_values.get("vertex_project") or deployment.litellm_params.vertex_project + location: Final = credential_values.get("vertex_location") or deployment.litellm_params.vertex_location + credentials: Final = credential_values.get("vertex_credentials") or deployment.litellm_params.vertex_credentials + if project is None or location is None: + raise ValueError( + "vertex_project, and vertex_location must be set in litellm_params for pass-through endpoints." + ) + from litellm.router_host import router_host + + router_host().add_vertex_pass_through_credentials( + project_id=str(project), + location=str(location), + vertex_credentials=credentials, # pyright: ignore[reportArgumentType] # the configured credentials + ) + + # -- writes ----------------------------------------------------------------------------------- + + def add_deployment(self, deployment: Deployment) -> Deployment | None: + """Add one deployment unless its id exists (``add_deployment``), built by router-core.""" + build: Final = _Build(path="add", deployment=deployment) + self._run_build(build, [deployment.to_json(exclude_none=True)], resolve_secrets=False, install="upsert") + if build.result is None: + return None + if self.checks is not None: + self.checks.sync_deployment_budget(build.result) + self._on_change() + return build.result + + def _core_upsert_deployment(self, deployment: Deployment) -> Deployment | None: + """Add or replace one deployment (``_upsert_deployment``).""" + model_id: Final = deployment.model_info.id or "" + on_router: Final = self._core_get_deployment(model_id=model_id) + served: Final = without_model_capability_flags(deployment) + try: + if on_router is not None: + if ( + deployment.model_name == on_router.model_name + and served.litellm_params == on_router.litellm_params + and deployment.model_info == on_router.model_info + ): + return None + with self._deployment_index_lock: + removal_idx: Final = self.model_id_to_deployment_index_map.get(model_id) + if removal_idx is not None: + _ = self._core_model_list[removal_idx] # pyright: ignore[reportArgumentType] # raises IndexError for a position past the list, as the pop does + self._remove(model_id) + if self.strategies is not None: + self.strategies.release(on_router) + self._on_change() + self.add_deployment(deployment=deployment) + if self.strategies is not None: + self.strategies.upserted(deployment, on_router) + except Exception as e: + if not self.ignore_invalid_deployments: + raise + verbose_router_logger.warning( + "Error upserting deployment %s (id=%s): %s. Dropping it and continuing with other deployments.", + deployment.model_name, + deployment.model_info.id, + e, + ) + self._restore_deployment_after_failed_upsert(on_router, model_id) + return None + else: + return deployment + + def _restore_deployment_after_failed_upsert(self, previous: Deployment | None, model_id: str) -> None: + if previous is None or self._core_has_model_id(model_id): + return + try: + if self.strategies is None: + self.add_deployment(deployment=previous) + else: + self.strategies.without_capability_limit(lambda: self.add_deployment(deployment=previous)) + verbose_router_logger.info( + "Restored deployment %s (id=%s); it keeps serving its previous configuration.", + previous.model_name, + model_id, + ) + except Exception as restore_error: # noqa: BLE001 # best-effort restore: a second failure must not abort the reload + verbose_router_logger.warning( + "Could not restore previously served deployment %s (id=%s) after the failed upsert: %s", + previous.model_name, + model_id, + restore_error, + ) + + def _live_handle(self) -> "RouterCoreHandle | None": + return None if self.handle_lookup is None else self.handle_lookup() + + def _hand_changes(self, changes: Mapping[str, object]) -> None: + if self.changes_runner is None: + raise RuntimeError("the host registry writes deployments through its Rust core") + self.changes_runner(changes) + self._core_model_list.refresh() + + def refresh(self) -> None: + """Read router-core's list again after a write (only what was appended, when that is all + that changed). The index views are read again when an entry point hands them out, which + keeps one ``add_deployment`` from reading every index back.""" + self._core_model_list.refresh() + + def _remove(self, model_id: str) -> None: + """Remove the deployment at the id map's position for ``model_id``, every index shifted + (``_update_deployment_indices_after_removal``, in router-core).""" + self._hand_changes({"remove": model_id}) + self._invalidate_model_group_info_cache() + self._invalidate_access_groups_cache() + + # -- the indexes (router-core's, read back as live views) ------------------------------------- + + @property + def model_id_to_deployment_index_map(self) -> dict[str, int]: # mutable-ok: the live id index + self._indexes.refresh() + return cast(dict[str, int], self._indexes.id_map) # cast-ok: id to position, as router-core keeps it + + @property + def _core_model_name_to_deployment_indices(self) -> dict[str, list[int]]: # mutable-ok: the live name index + self._indexes.refresh() + return cast(dict[str, list[int]], self._indexes.model_name) # cast-ok: name to positions + + @_core_model_name_to_deployment_indices.setter + def _core_model_name_to_deployment_indices(self, value: object) -> None: + self._indexes.assign("model_name", value) + + @property + def _core_team_model_to_deployment_indices( + self, + ) -> dict[tuple[str, str], list[int]]: # mutable-ok: the live team index + self._indexes.refresh() + return cast(_TeamIndex, self._indexes.team_model) # cast-ok: (team, public name) to positions + + @_core_team_model_to_deployment_indices.setter + def _core_team_model_to_deployment_indices(self, value: object) -> None: + self._indexes.assign("team_model", value) + + @property + def _core_model_names(self) -> set[str]: # mutable-ok: the live group set + self._indexes.refresh() + return cast(set[str], self._indexes.model_names) # cast-ok: group names + + @_core_model_names.setter + def _core_model_names(self, value: object) -> None: + self._indexes.assign("model_names", value) + + @property + def _core_deployment_names(self) -> list[str]: # mutable-ok: the live name list + self._indexes.refresh() + return cast(list[str], self._indexes.deployment_names) # cast-ok: litellm model names + + @_core_deployment_names.setter + def _core_deployment_names(self, value: object) -> None: + self._indexes.assign("deployment_names", value) + + @property + def _core_team_public_model_names(self) -> frozenset[str]: + self._indexes.refresh() + return self._indexes.team_public_model_names + + @_core_team_public_model_names.setter + def _core_team_public_model_names(self, value: object) -> None: + self._indexes.assign("team_public_model_names", value) + + @property + def _core_provider_default_deployment_ids(self) -> list[str]: # mutable-ok: the live id list + self._indexes.refresh() + return cast(list[str], self._indexes.provider_default_ids) # cast-ok: deployment ids + + @_core_provider_default_deployment_ids.setter + def _core_provider_default_deployment_ids(self, value: object) -> None: + self._indexes.assign("provider_default_ids", value) + + @property + def _core_pattern_router(self) -> PatternMatchRouter: + self._indexes.refresh() + return self._indexes.pattern_router + + @_core_pattern_router.setter + def _core_pattern_router(self, value: object) -> None: + self._indexes.pattern_router.patterns = getattr(value, "patterns", {}) # pyright: ignore[reportAttributeAccessIssue] # a router a caller assigned + + @property + def _core_team_pattern_routers(self) -> dict[str, PatternMatchRouter]: # mutable-ok: the live per-team routers + self._indexes.refresh() + return cast(dict[str, PatternMatchRouter], self._indexes.team_pattern_routers) # cast-ok: team id to its router + + @_core_team_pattern_routers.setter + def _core_team_pattern_routers(self, value: object) -> None: + routers: Final = as_str_mapping(value) or {} + self._indexes.write( + { + "team_patterns": [ + [ + str(team), + [ + [regex, deployments] + for regex, deployments in (as_str_mapping(getattr(router, "patterns", None)) or {}).items() + ], + ] + for team, router in routers.items() + ] + } + ) + + def replace_model_list(self, model_list: "list[UntypedEntry]") -> None: # mutable-ok: the list as assigned + """``router.model_list = [...]``: the list is swapped as given, without reindexing, and + router-core takes it whole.""" + self._core_model_list.replace(model_list) + self._registry_version += 1 + self._on_change() + + def _core_delete_deployment(self, id: str) -> UntypedEntry | None: + """Remove one deployment and return its stored entry (``_delete_deployment``).""" + try: + with self._deployment_index_lock: + deployment_idx: Final = self.model_id_to_deployment_index_map.get(id) + if deployment_idx is None: + return None + item: Final = self._core_model_list[deployment_idx] # pyright: ignore[reportArgumentType] # raises IndexError for a position past the list, as the pop does + self._remove(id) + if self.checks is not None: + self.checks.unregister_deployment_budget(id) + if self.strategies is not None: + self.strategies.release_entry(item) + except Exception: # noqa: BLE001 # the core answers None for any failed delete + return None + self._on_change() + return item + + def _core_get_router_deployment_budget_limiter(self) -> "RouterBudgetLimiting | None": + """The router's deployment-budget callback (``registry().plugins("budget_limiter")``).""" + return self.checks.budget_limiter() if self.checks is not None else None + + @property + def _core_prompt_caching_pin_cache(self) -> DualCache: + """The prompt caching pins (``registry().plugins("prompt_caching_pins")``).""" + if self.checks is None: + return self.__getattr__("_core_prompt_caching_pin_cache") # pyright: ignore[reportReturnType] # raises RustCoreUnsupported + return self.checks.prompt_caching_pin_cache + + def replay_model_cost_registrations(self) -> None: + """Re-register every served deployment's cost-map entries (``replay_model_cost_registrations``).""" + provider_unresolved: Final = self._provider_unresolved_deployments + self._provider_unresolved_deployments = () + for create_deployment in provider_unresolved: + create_deployment() + for entry in tuple(self._core_model_list): + try: + deployment = Deployment(**entry) # pyright: ignore[reportArgumentType] # a stored entry + except Exception: # noqa: BLE001 # a malformed entry must not abort the rest of the rebuild + verbose_router_logger.exception( + "Router: could not rebuild cost-map entry for a deployment during a price data reload" + ) + continue + register_deployment_pricing(self._host, deployment) + self._invalidate_model_group_info_cache() + if provider_unresolved: + self._on_change() + + # -- one deployment --------------------------------------------------------------------------- + + def _core_has_model_id(self, candidate_id: str) -> bool: + handle: Final = self._live_handle() + key: Final = _index_key(candidate_id) + return handle is not None and key is not None and handle.has_model_id(key) + + def _core_get_model_info(self, id: str) -> UntypedEntry | None: + handle: Final = self._live_handle() + key: Final = _index_key(id) + idx: Final[object] = None if handle is None or key is None else handle.id_position(key) + return None if idx is None else self._core_model_list[idx] # pyright: ignore[reportArgumentType, reportCallIssue] # a position, or what a caller wrote, read as Python reads it + + def _core_get_deployment(self, model_id: str) -> Deployment | None: + entry: Final = self._core_get_model_info(model_id) + return None if entry is None else Deployment(**entry) # pyright: ignore[reportArgumentType] # a stored entry + + def _core_get_deployment_by_model_group_name(self, model_group_name: str) -> Deployment | None: + handle: Final = self._live_handle() + key: Final = _index_key(model_group_name) + indices: Final[object] = None if handle is None or key is None else handle.named_positions(key) + model: Final = self._core_model_list[indices[0]] if indices else None # pyright: ignore[reportIndexIssue, reportArgumentType, reportCallIssue] # positions, or what a caller wrote, read as Python reads them + return None if model is None else Deployment(**model) # pyright: ignore[reportArgumentType] # a stored entry + + def _at(self, indices: object) -> tuple[UntypedEntry, ...]: + """The entries at ``indices`` (what an index holds), read as Python's list reads them.""" + return tuple(self._core_model_list[idx] for idx in indices) # pyright: ignore[reportGeneralTypeIssues, reportArgumentType, reportCallIssue] # positions, or what a caller wrote + + def _core_deployments_named(self, model_name: str) -> tuple[UntypedEntry, ...] | None: + handle: Final = self._live_handle() + key: Final = _index_key(model_name) + indices: Final[object] = None if handle is None or key is None else handle.named_positions(key) + return None if indices is None else self._at(indices) + + def team_public_model_names_of(self, team_id: object) -> frozenset[str]: + handle: Final = self._live_handle() + if handle is None or not isinstance(team_id, str): + return frozenset() + return frozenset(handle.team_public_names_of(team_id)) + + def _team_deployments_named(self, team_id: str, public_model_name: str) -> tuple[UntypedEntry, ...] | None: + handle: Final = self._live_handle() + team: Final = _index_key(team_id) + public: Final = _index_key(public_model_name) + indices: Final[object] = ( + None if handle is None or team is None or public is None else handle.team_positions(team, public) + ) + return None if indices is None else self._at(indices) + + # -- lookups (router-core `lookup.rs`): rows read at the stored entries -------------------- + + def _rows(self, rows: object) -> list[UntypedEntry]: # mutable-ok: a fresh list + """The stored entries router-core's lookup ``rows`` name, read as Python's list reads them: + a row it could not read is indexed here, and raises as the Python router's read raised.""" + entries: Final[list[UntypedEntry]] = [] # mutable-ok: filled per row + for row in cast(Sequence[Mapping[str, object]], rows): # cast-ok: router-core's lookup rows + if "raw" in row: + entries.append(self._core_model_list[row["raw"]]) # pyright: ignore[reportArgumentType, reportCallIssue] # what a caller wrote, read as Python reads it + elif "raw_positions" in row: + entries.extend(self._at(row["raw_positions"])) + elif "pattern" in row: + entries.append({**DeploymentTypedDict(**row["pattern"]), "model_name": row["name"]}) # pyright: ignore[reportCallIssue] # a pattern router's stored entry + else: + entries.append(self._row_entry(row)) + return entries + + def _row_entry(self, row: Mapping[str, object]) -> UntypedEntry: + held: Final[UntypedEntry] = self._core_model_list[int(str(row["at"]))] + name: Final = row.get("name") + named: Final = held if name is None else _renamed(held, str(name)) + group: Final = row.get("group") + if group is None: + return named + return _as_routing_group_row( + apply_routing_group_priority(self._core_routing_groups[str(group)], str(row["member"]), named) # pyright: ignore[reportArgumentType] # a stored entry + ) + + def _raise_at(self, raw: object) -> None: + """Read the list at the row router-core could not read it at, which raises.""" + if raw is not None: + _ = self._rows([raw]) + + def _list_scope(self, model_name: str | None, *, only: str | None = None) -> Mapping[str, object]: + """What ``get_model_list`` lists beyond the deployments: the aliases (read here, where an + alias item that is no mapping or lacks ``hidden`` raises as the Python router's read + does), the callable routing groups and the wildcard requests for ``model_name``.""" + from litellm.litellm_core_utils.get_llm_provider_logic import inferred_provider + + aliases: Final[list[Mapping[str, str]]] = [] # mutable-ok: filled per alias + alias_map: Final = self._core_model_group_alias or {} + if model_name is None or model_name in alias_map: + items: Final[Sequence[tuple[str, object]]] = ( + [(model_name, alias_map[model_name])] if model_name is not None else list(alias_map.items()) + ) + for model_alias, model_value in items: + if isinstance(model_value, str): + aliases.append({"alias": model_alias, "target": model_value}) + elif isinstance(model_value, dict): + item = RouterModelGroupAliasItem(**model_value) # pyright: ignore[reportCallIssue, reportArgumentType] # an alias item dict + if item["hidden"] is True and model_name is None: + continue + aliases.append({"alias": model_alias, "target": item["model"]}) + groups: Final = [ + {"name": name, "members": list(group.models)} + for name in (self._core_routing_groups or {}) + if (group := self.get_routing_group(name)) is not None + ] + wildcard: Final = ( + [model_name, f"{inferred_provider(model_name)}/{model_name}"] if model_name is not None else [] + ) + return {"aliases": aliases, "groups": groups, "wildcard": wildcard, "only": only} + + def _lookup(self) -> "RouterCoreHandle": + handle: Final = self._live_handle() + if handle is None: + raise RuntimeError("the host registry's lookups run in its Rust core") + return handle + + # -- deployments by name ---------------------------------------------------------------------- + + @staticmethod + def _core_should_include_deployment( + model_name: str, model: Mapping[str, object], team_id: str | None = None + ) -> bool: + info: Final = _model_info_of(model) + if team_id is not None and info.get("team_id") == team_id and model_name == info.get("team_public_model_name"): + return True + if model_name is not None and model.get("model_name") == model_name: # pyright: ignore[reportUnnecessaryComparison] # the core checks it + model_team_id: Final = info.get("team_id") + return team_id is None or model_team_id is None or model_team_id == team_id + return False + + @staticmethod + def _core_deployment_usable_by_team(model: Mapping[str, object] | Deployment, team_id: str | None) -> bool: + info: Final[object] = ( + model.model_info.model_dump() if isinstance(model, Deployment) else model.get("model_info") + ) + owner: Final = _MODEL_INFO_ADAPTER.validate_python(info).get("team_id") if isinstance(info, Mapping) else None + return team_may_use_deployment(owner, team_id) + + def _core_deployments_for_request( + self, model: str, request_kwargs: Mapping[str, object] + ) -> Sequence[Mapping[str, object]]: + """The deployments ``model`` names for this caller: alias, then team-first, then global, then + admin-across-teams (``_core_deployments_for_request``).""" + from litellm.litellm_core_utils.routing_common_utils import get_request_team_id, is_proxy_admin_request + + registered: Final = self._core_get_model_from_alias(model=model) or model + team_id: Final = get_request_team_id(request_kwargs) + deployments: Final = self._core_get_all_deployments(model_name=registered, team_id=team_id) + if deployments or team_id is not None or not is_proxy_admin_request(request_kwargs): + return deployments + return self._team_deployments_across_teams(registered) + + def _team_deployments_across_teams(self, model: str) -> list[UntypedEntry]: # mutable-ok: a fresh list + """Every team's deployments under public name ``model``, for a proxy admin calling without a team.""" + rows, teams = self._lookup().lookup_across_teams(model) + team_deployments: Final = self._rows(rows) + if teams > 1: + raise litellm_exceptions.BadRequestError( + message=( + f"Model name '{model}' matches deployments from multiple teams. " + "Specify the deployment ID directly to disambiguate." + ), + model=model, + llm_provider="", + ) + return team_deployments + + def _core_get_all_deployments( + self, model_name: str, model_alias: str | None = None, team_id: str | None = None + ) -> list[UntypedEntry]: # mutable-ok: a fresh list, as the core returns it + key: Final = _index_key(model_name) + return [] if key is None else self._rows(self._lookup().lookup_all(key, team_id, model_alias)) + + def get_routing_group(self, model_name: str) -> RoutingGroup | None: + """The routing group callable as ``model_name``: a deployment model_name or an alias of the + same name shadows it.""" + if not self._core_routing_groups: + return None + group: Final = self._core_routing_groups.get(model_name) + handle: Final = self._live_handle() + if ( + group is None + or (handle is not None and handle.named_positions(model_name) is not None) + or model_name in (self._core_model_group_alias or {}) + ): + return None + return group + + def _core_routing_group_has_alternatives(self, model_group: str | None) -> bool: + """A callable routing group whose member union spans more than one deployment.""" + if model_group is None: + return False + resolved: Final = self._core_get_model_from_alias(model=model_group) or model_group + group: Final = self.get_routing_group(resolved) + if group is None: + return False + handle: Final = self._lookup() + + def held(member: str) -> Sequence[object]: + return cast(Sequence[object], handle.named_positions(member) or ()) # cast-ok: positions, or junk + + return sum(len(held(member)) for member in group.models) > 1 + + def _core_get_model_list_from_model_alias( + self, model_name: str | None = None + ) -> list[UntypedEntry]: # mutable-ok: a fresh list + return self._rows( + self._lookup().lookup_model_list(model_name, None, self._list_scope(model_name, only="aliases")) + ) + + def _core_get_model_list_from_routing_groups(self, model_name: str | None = None) -> Sequence[UntypedEntry]: + """Callable routing groups as model-list rows: each member deployment under the group's name.""" + if model_name is None and self._routing_group_rows is not None: + return self._routing_group_rows + rows: Final = tuple( + self._rows(self._lookup().lookup_model_list(model_name, None, self._list_scope(model_name, only="groups"))) + ) + if model_name is None: + self._routing_group_rows = rows + return rows + + def _core_get_model_list( + self, model_name: str | None = None, team_id: str | None = None + ) -> list[UntypedEntry] | None: # mutable-ok: a fresh list, as get_model_list returns + if model_name is not None and _index_key(model_name) is None: + # No index holds it, so `_get_wildcard_deployments` reads it: what the pattern routers raise. + team_router: Final = self._core_team_pattern_routers.get(team_id) if team_id is not None else None + return [ + *self._core_pattern_router.get_deployments_by_pattern(model=model_name), + *(team_router.get_deployments_by_pattern(model=model_name) if team_router is not None else ()), + ] + return self._rows(self._lookup().lookup_model_list(model_name, team_id, self._list_scope(model_name))) + + def _core_wildcard_route_deployments(self, model: str, team_id: str | None) -> Sequence[Mapping[str, object]]: + from litellm.litellm_core_utils.get_llm_provider_logic import inferred_provider + + if not isinstance(model, str): # pyright: ignore[reportUnnecessaryIsInstance] # a caller's non-string model reads the base routers + team_router: Final = self._core_team_pattern_routers.get(team_id) if team_id is not None else None + team_owned: Final = team_router.get_deployments_by_pattern(model=model) if team_router is not None else () + return team_owned or self._core_pattern_router.get_deployments_by_pattern(model=model) + rows: Final = self._lookup().lookup_wildcard_route( + model, team_id, [model, f"{inferred_provider(model)}/{model}"] + ) + routed: Final = cast(Sequence[Mapping[str, object]], rows) # cast-ok: router-core's wildcard rows + return [cast(Mapping[str, object], row["pattern"]) for row in routed] # cast-ok: each carries its routed copy + + def _core_wildcard_routed_models(self, model: str, team_id: str | None) -> frozenset[str]: + team_router: Final = self._core_team_pattern_routers.get(team_id) if team_id is not None else None + team_owned: Final = ( + team_router.get_models_by_pattern(model=model) if team_router is not None else frozenset[str]() + ) + return team_owned or self._core_pattern_router.get_models_by_pattern(model=model) + + def _core_config_deployments(self) -> Iterator[Mapping[str, object]]: + """A generator, as the Python core's: the rows are read when iteration starts.""" + yield from self._rows(self._lookup().lookup_config()) + + # -- names ------------------------------------------------------------------------------------ + + def _core_get_model_names(self, team_id: str | None = None) -> list[str]: # mutable-ok: a fresh list + names, raw = self._lookup().lookup_model_names(team_id, self._list_scope(None)) + self._raise_at(raw) + return names + + def _core_get_model_ids( + self, model_name: str | None = None, exclude_team_models: bool = False + ) -> list[str]: # mutable-ok: a fresh list + if model_name is not None and _index_key(model_name) is None: + return [] + ids, raw = self._lookup().lookup_model_ids(model_name, exclude_team_models) + self._raise_at(raw) + return ids + + # -- resolving a name ------------------------------------------------------------------------- + + def _core_get_model_from_alias(self, model: str) -> str | None: + return resolve_model_group_alias(self._core_model_group_alias, model) + + def _core_routable_model_group(self, model_name: str) -> str: + target: Final = self._core_get_model_from_alias(model_name) + return target if target is not None else model_name + + def _core_is_recognized_model(self, model: str) -> bool: + handle: Final = self._live_handle() + key: Final = _index_key(model) + return ( + (handle is not None and key is not None and handle.has_model_name(key)) + or self._core_has_model_id(model) + or model in self._core_model_group_alias + or self.get_routing_group(model) is not None + ) + + def _core_get_model_group(self, id: str) -> list[UntypedEntry] | None: # mutable-ok: a fresh list + model_info: Final = self._core_get_model_info(id=id) + if model_info is None: + return None + return self._core_get_model_list(model_name=str(model_info["model_name"])) + + def _core_resolve_model_name_from_model_id( + self, model_id: str | None, custom_llm_provider: str | None = None + ) -> str | None: + if not model_id: + return None + handle: Final = self._lookup() + if handle.has_model_name(model_id): + return model_id + if self._core_has_model_id(model_id): + deployment: Final = self._core_get_deployment(model_id=model_id) + if deployment is not None and deployment.model_name: + return deployment.model_name + return model_id + listed, serving, raw = handle.lookup_name_serving(model_id, self._list_scope(None)) + self._raise_at(raw) + if not listed: + return None + if serving is not None: + return serving + if self._core_is_recognized_model(model_id): + return model_id + if custom_llm_provider is None: + return None + if self._core_pattern_router.routes_to_provider(model_id, custom_llm_provider): + return model_id + provider_prefixed: Final = f"{custom_llm_provider}/{model_id}" + if not model_id.startswith(f"{custom_llm_provider}/") and self._core_pattern_router.routes_to_provider( + provider_prefixed, custom_llm_provider + ): + return provider_prefixed + return None + + def _get_deployment_by_litellm_model(self, model: object) -> list[UntypedEntry]: # mutable-ok: a fresh list + handle: Final = self._live_handle() + if handle is None or not isinstance(model, str): + return [] + return list(self._at(handle.litellm_model_positions(model))) + + # -- credentials ------------------------------------------------------------------------------ + + @staticmethod + def _core_is_deployment_blocked(deployment: Deployment) -> bool: + model_info: Final[object] = getattr(deployment, "model_info", None) + return model_info is not None and getattr(model_info, "blocked", None) is True + + def _core_get_deployment_credentials(self, model_id: str) -> UntypedEntry | None: + deployment: Final = self._core_get_deployment(model_id=model_id) + if deployment is None or self._core_is_deployment_blocked(deployment): + return None + return CredentialLiteLLMParams.model_validate( + deployment.litellm_params.model_dump(exclude_none=True) + ).model_dump(exclude_none=True) + + def _get_model_group_deployment_usable_by_team( + self, model_group_name: str, team_id: str | None + ) -> Deployment | None: + if _index_key(model_group_name) is None: + return None + position, raw = self._lookup().lookup_group_usable_by_team(model_group_name, team_id) + self._raise_at(raw) + return None if position is None else Deployment(**self._core_model_list[position]) # pyright: ignore[reportArgumentType] # a stored entry + + def _get_team_public_name_deployment(self, model_id: str, team_id: str | None) -> Deployment | None: + if team_id is None or _index_key(model_id) is None: + return None + position, raw = self._lookup().lookup_team_public_name(model_id, team_id) + self._raise_at(raw) + return None if position is None else Deployment(**self._core_model_list[position]) # pyright: ignore[reportArgumentType] # a stored entry + + def _get_wildcard_deployment_usable_by_team(self, model_id: str, team_id: str | None) -> Deployment | None: + team_router: Final = self._core_team_pattern_routers.get(team_id) if team_id is not None else None + team_models: Final = team_router.route(model_id) if team_router else None + global_models: Final = tuple( + model + for model in (self._core_pattern_router.route(model_id) or ()) + if self._core_deployment_usable_by_team(model, team_id) + ) + candidates: Final = team_models or global_models + if not candidates: + return None + return Deployment(**candidates[0]) # a pattern router holds stored entry dicts + + def _core_get_credential_deployment(self, model_id: str, team_id: str | None = None) -> Deployment | None: + deployment: Final = ( + self._core_get_deployment(model_id=model_id) + or self._get_model_group_deployment_usable_by_team(model_group_name=model_id, team_id=team_id) + or self._get_team_public_name_deployment(model_id=model_id, team_id=team_id) + or self._get_wildcard_deployment_usable_by_team(model_id=model_id, team_id=team_id) + ) + if deployment is None or self._core_is_deployment_blocked(deployment): + return None + return deployment + + def _core_get_deployment_credentials_with_provider( + self, model_id: str, team_id: str | None = None + ) -> UntypedEntry | None: + deployment: Final = self._core_get_credential_deployment(model_id=model_id, team_id=team_id) + if deployment is None: + return None + base: Final = CredentialLiteLLMParams.model_validate( + deployment.litellm_params.model_dump(exclude_none=True) + ).model_dump(exclude_none=True) + credential_name: Final = deployment.litellm_params.litellm_credential_name + resolved: Final[UntypedEntry] = dict(base) + if credential_name is not None: + credential_values: Final = CredentialAccessor.get_credential_values(credential_name) + if not credential_values: + verbose_router_logger.warning("Credential '%s' not found in credential_list", credential_name) + resolved.update(credential_values) + _ = resolved.pop("litellm_credential_name", None) + model: Final = deployment.litellm_params.model + resolved["model"] = model + resolved["custom_llm_provider"] = ( + deployment.litellm_params.custom_llm_provider or (model.split("/")[0] if "/" in model else None) or "openai" + ) + return resolved + + # -- routable names --------------------------------------------------------------------------- + + def _routable_deployments(self, model_name: str, team_id: str | None) -> tuple[UntypedEntry, ...]: + return tuple(self._rows(self._lookup().lookup_routable(self._core_routable_model_group(model_name), team_id))) + + def _core_team_ptu_ceiling(self, team_id: str, model_group: str) -> "PTUTeamCeiling | None": + """The per-minute ceiling ``team_id``'s PTU shares set on the group serving ``model_group``, + else None (``team_ptu_ceiling``), kept until the model list next changes.""" + from litellm.litellm_core_utils.ptu_shares import ptu_share_teams, team_ptu_ceiling + + listed: Final = tuple(self._core_get_model_list() or ()) + if self._ptu_cache is None: + self._ptu_cache = (ptu_share_teams(listed), {}) + share_teams, ceilings = self._ptu_cache + if team_id not in share_teams: + return None + key: Final = (team_id, model_group) + if key not in ceilings: + ceilings[key] = team_ptu_ceiling( + listed, + self._core_model_list, + team_id, + model_group, + lambda name: self._core_wildcard_route_deployments(name, team_id), + ) + return ceilings[key] + + def _get_client( + self, deployment: Mapping[str, object], kwargs: Mapping[str, object], client_type: str | None = None + ) -> object: + """The SDK client cached in the routing cache for a deployment (``_get_client``); a pod + discovery deployment has none. ``max_parallel_requests`` is the deployment's slot limit, + built on first use.""" + from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs + from litellm.router_rust.core import RustCoreUnsupported + + # `deployment["model_info"]["id"]`: the Python router reads the id first, raising for a + # deployment without one whatever the client type. + _ = deployment["model_info"]["id"] # pyright: ignore[reportIndexIssue] # read as the Python router reads it + if client_type == "max_parallel_requests": + limit_lookup: Final = self.max_parallel_requests_lookup + if limit_lookup is None: + raise RustCoreUnsupported( + "registry().client(client_type='max_parallel_requests') is not served by the Rust router core" + ) + return limit_lookup(deployment, kwargs) + if _params_of(deployment).get("kubernetes_pod_discovery") is True: + return None + model_id: Final = _model_info_of(deployment).get("id") + span: Final = get_parent_otel_span_from_kwargs(dict(kwargs)) + stream: Final = "_stream" if kwargs.get("stream") is True else "" + with service_target(ROUTER_CLIENTS_TARGET): + if client_type == "async": + return self._core_cache.get_cache( + key=f"{model_id}{stream}_async_client", local_only=True, parent_otel_span=span + ) # pyright: ignore[reportUnknownMemberType] # DualCache's reads are untyped + return self._core_cache.get_cache(key=f"{model_id}{stream}_client", parent_otel_span=span) # pyright: ignore[reportUnknownMemberType] # see above + + def _core_get_search_tool_support(self, model_name: str, team_id: str | None = None) -> tuple[bool | None, ...]: + """Per routable deployment: its ``supports_search_tool`` when a bool, else True when its route + builds an Anthropic Messages request, else None (``get_search_tool_support``).""" + return tuple(_search_tool_support(deployment) for deployment in self._routable_deployments(model_name, team_id)) + + def _core_get_candidate_model_ids_for_route(self, model: str, team_id: str | None = None) -> frozenset[str]: + """The deployment ids that could serve ``model`` for ``team_id``: the alias target, then a + routing group, then a team public name or wildcard route for a name that is no model + group, then the model group (``get_candidate_model_ids_for_route``). Read-only.""" + from litellm.litellm_core_utils.get_llm_provider_logic import inferred_provider + + resolved: Final = self._core_get_model_from_alias(model=model) or model + group: Final = self.get_routing_group(resolved) if self._core_routing_groups else None + ids, raw = self._lookup().lookup_candidate_ids( + resolved, + team_id, + None if group is None else list(group.models), + [resolved, f"{inferred_provider(resolved)}/{resolved}"], + ) + self._raise_at(raw) + return frozenset(ids) + + def _core_team_model_has_alternatives(self, deployment_id: str) -> bool: + """Whether a team deployment's public name has another unpaused deployment of that team.""" + found, raw = self._lookup().lookup_team_model_has_alternatives(deployment_id) + self._raise_at(raw) + return found + + def _core_resolve_served_model_name(self, model_name: str, served_model: str) -> str: + """``served_model`` when ``model_name`` routes to it (the alias target, a routing group + member, or the name itself), else ``model_name``.""" + target: Final = self._core_get_model_from_alias(model_name) or model_name + group: Final = self.get_routing_group(target) + members: Final = group.models if group is not None else () + return served_model if served_model == target or served_model in members else model_name + + def _core_resolved_litellm_models( + self, model_name: str, team_id: str | None = None, *, use_base_model: bool = False + ) -> tuple[str, ...]: + """The provider model strings a call to ``model_name`` can be served by (``resolved_litellm_models``).""" + listed: Final = self._core_get_model_list(model_name=model_name, team_id=team_id) or () + if use_base_model: + return tuple( + backend for entry in listed if (backend := cost_map_backend_model(Deployment.model_validate(entry))) + ) + return tuple(model for entry in listed if isinstance(model := _params_of(entry).get("model"), str) and model) + + def _core_get_routable_deployments( + self, model: str, request_kwargs: Mapping[str, object] = MappingProxyType({}), call_type: str | None = None + ) -> tuple[Mapping[str, object], ...]: + """The deployments routing would consider for ``request_kwargs``, as the Rust core resolves + them, the endpoint of ``call_type`` included.""" + lookup: Final = self.routable_lookup + if lookup is None: + from litellm.router_rust.core import RustCoreUnsupported + + raise RustCoreUnsupported("registry().get_routable_deployments is not served by the Rust router core") + return tuple(lookup(model, request_kwargs, call_type)) + + def _core_get_routable_upstream_model(self, model_name: str, team_id: str | None = None) -> str | None: + deployment: Final = next(iter(self._routable_deployments(model_name, team_id)), None) + if deployment is None: + return None + model: Final = _params_of(deployment).get("model") + return None if model is None else str(model) + + def _core_map_team_model( + self, team_model_name: str | None, team_id: str, custom_llm_provider: str | None = None + ) -> str | None: + """A team's public name to its group, or a deployment for a model-less call (``map_team_model``).""" + models: Final = self._core_get_model_list(model_name=team_model_name, team_id=team_id) + if not models: + return None + if team_model_name is None and custom_llm_provider is not None: + return self._team_model_for_provider(models, team_id, custom_llm_provider) + for model in models: + info = _model_info_of(model) + if info.get("team_id") == team_id: + if team_model_name is None: + public = info.get("team_public_model_name") or model.get("model_name") + return None if public is None else str(public) + return team_model_name + return None + + @staticmethod + def _team_model_for_provider(models: Sequence[UntypedEntry], team_id: str, custom_llm_provider: str) -> str | None: + def public_name(deployment: UntypedEntry) -> str | None: + info: Final = _model_info_of(deployment) + if info.get("team_id") != team_id: + return None + name: Final = info.get("team_public_model_name") + return name if isinstance(name, str) and name else str(deployment["model_name"]) + + def provider(deployment: UntypedEntry) -> object: + return provider_for_generic_call(_params_of(deployment)) # pyright: ignore[reportArgumentType] # the deployment's params + + matching: Final = next( + (m for m in models if public_name(m) is not None and provider(m) == custom_llm_provider), None + ) + if matching is None: + return None + name: Final = public_name(matching) + if name is None: + return None + if all(provider(m) == custom_llm_provider for m in models if public_name(m) == name): + return name + matched_id: Final = _model_info_of(matching).get("id") + return matched_id if isinstance(matched_id, str) else None + + # -- access groups ---------------------------------------------------------------------------- + + def _core_get_model_access_groups( + self, model_name: str | None = None, model_access_group: str | None = None, team_id: str | None = None + ) -> Mapping[str, Sequence[str]]: + use_cache: Final = model_name is None and model_access_group is None and team_id is None + if use_cache and self._access_groups_cache is not None: + return self._access_groups_cache + pairs, raw = self._lookup().lookup_access_groups( + model_name, model_access_group, team_id, self._list_scope(model_name) + ) + self._raise_at(raw) + groups: Final[dict[str, list[str]]] = {g: list(n) for g, n in pairs} # mutable-ok: as a defaultdict + if use_cache: + self._access_groups_cache = groups + return groups + + def _core_is_model_access_group_for_wildcard_route(self, model_access_group: str) -> bool: + groups: Final = self._core_get_model_access_groups(model_access_group=model_access_group) + return any( + self._core_pattern_router.route(request=model) is not None for model in groups.get(model_access_group, []) + ) + + +# -- the registry() view ------------------------------------------------------------------------- + + +class RustRegistry(RouterRegistry): + """``registry()`` of the Rust core: ``RouterRegistry``'s queries over the host registry.""" + + __slots__ = () + + def includes( + self, + deployment: "DeploymentTypedDict | dict[str, object]", # mutable-ok: the RouterRegistry signature + *, + model_name: str | None = None, + team_id: str | None = None, + ) -> bool: + hosted: Final = self._router + if not isinstance(hosted, HostRegistry): + return super().includes(deployment, model_name=model_name, team_id=team_id) + if model_name is None: + return HostRegistry._core_deployment_usable_by_team(deployment, team_id) # pyright: ignore[reportPrivateUsage, reportArgumentType] # the view reads its own registry + return HostRegistry._core_should_include_deployment(model_name=model_name, model=deployment, team_id=team_id) # pyright: ignore[reportPrivateUsage, reportArgumentType] # see above + + +def hosted_registry_view(hosted: HostRegistry) -> RouterRegistry: + """The ``registry()`` view over ``hosted``.""" + return RustRegistry(hosted) # pyright: ignore[reportArgumentType] # the host registry answers every _core_ query the view makes + + +# The registry indexes a deprecated attribute write replaces (``router.model_names = ...`` reaches +# the host registry as ``_core_model_names``), by the field router-core reads each one as. +INDEX_ATTRIBUTES: Final[Mapping[str, str]] = MappingProxyType( + { + "_core_model_names": "model_names", + "_core_model_name_to_deployment_indices": "model_name", + "_core_team_model_to_deployment_indices": "team_model", + } +) + + +def _positions(indices: object, length: int) -> list[int]: # mutable-ok: a JSON list + """The model-list positions ``indices`` read, as Python's ``model_list[index]`` reads them: a + negative one counts from the end, and one before the start becomes ``length``, a position past + the end, so the lookup raises ``IndexError`` as Python's does.""" + if not isinstance(indices, Iterable) or isinstance(indices, str | bytes): + return [] + return [ + index if index >= 0 else (index + length if index + length >= 0 else length) + for index in indices + if isinstance(index, int) and not isinstance(index, bool) + ] + + +def index_document(hosted: HostRegistry, written: Iterable[str]) -> Mapping[str, object]: + """The written registry indexes, as the host registry holds them now, in the shape router-core + reads (``IndexOverrides``): names a lookup finds, and the deployment positions each model name + (or ``(team_id, public name)`` pair) indexes. Entries Python could not read as such are left out.""" + document: Final[dict[str, object]] = {} # mutable-ok: built here + length: Final = len(hosted._core_model_list) # pyright: ignore[reportPrivateUsage] # positions read against the live list + for attribute in written: + value: object = getattr(hosted, attribute, None) + field: str = INDEX_ATTRIBUTES[attribute] + if field == "model_names": + names = value if isinstance(value, Iterable) and not isinstance(value, str | bytes | Mapping) else () + document[field] = sorted({name for name in names if isinstance(name, str)}) + elif field == "model_name": + entries = value if isinstance(value, Mapping) else {} + document[field] = { + name: _positions(indices, length) for name, indices in entries.items() if isinstance(name, str) + } + else: + pairs = value if isinstance(value, Mapping) else {} + document[field] = [ + [key[0], key[1], _positions(indices, length)] + for key, indices in pairs.items() + if isinstance(key, tuple) and len(key) == 2 and all(isinstance(part, str) for part in key) + ] + return document + + +DEFAULT_DEPLOYMENT_FAILING_ID: Final = "__litellm_default_deployment_failing_call__" +"""The id router-core serves a ``default_deployment`` under when every call to it fails.""" + +DEFAULT_DEPLOYMENT_COPIED_ID: Final = "__litellm_default_deployment_copied__" +"""The id router-core serves a callable ``default_deployment`` under when its ``model_info.id`` is +not a string: the host picks and calls Python's copy of it, so its id stays what was assigned.""" + + +def default_deployment_copy(value: object, model: str) -> object: + """``_try_early_resolve_deployments_for_model_not_in_names``' copy of the default deployment + for ``model``, raising what it raises for a value it cannot copy.""" + updated: Final = value.copy() # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType, reportUnknownVariableType] # any assigned value, read as Python reads it + updated["litellm_params"] = value["litellm_params"].copy() # pyright: ignore[reportIndexIssue, reportUnknownMemberType] # same + updated["litellm_params"]["model"] = model # pyright: ignore[reportUnknownMemberType] # same + return updated # pyright: ignore[reportUnknownVariableType] # same + + +def default_deployment_copy_error(value: object, model: str) -> BaseException: + """The error the default deployment's copy raises for ``model``.""" + try: + _ = default_deployment_copy(value, model) + except Exception as raised: # noqa: BLE001 # the error the pick raises + return raised + return RuntimeError(f"router-core: the default deployment copies for {model!r}") + + +def default_deployment_call_error(value: object) -> BaseException | None: + """The error every call to the default deployment raises, from its first reads + (``_update_kwargs_with_deployment``'s ``deployment["model_name"]``, ``_get_client``'s + ``deployment["model_info"]["id"]``); None when they read.""" + try: + served: Final = default_deployment_copy(value, "") + _ = served["model_name"] # pyright: ignore[reportIndexIssue] # read as Python reads it + _ = served["model_info"]["id"] # pyright: ignore[reportIndexIssue] # same + except Exception as raised: # noqa: BLE001 # the error the call raises + return raised + return None + + +def served_default_deployment(value: object) -> tuple[Mapping[str, object] | None, bool]: + """The ``default_deployment`` as router-core serves it, and whether resolving to it raises + (a value Python cannot copy). A deployment every call to fails is served under + ``DEFAULT_DEPLOYMENT_FAILING_ID``, one whose id is not a string under + ``DEFAULT_DEPLOYMENT_COPIED_ID``; names that are not strings are served as text.""" + if value is None: + return None, False + try: + copied: Final = default_deployment_copy(value, "") + except Exception: # noqa: BLE001 # any copy error: the pick raises it + return None, True + entry: Final = as_str_mapping(copied) or {} + model_info: Final = dict(as_str_mapping(entry.get("model_info")) or {}) + failing: Final = default_deployment_call_error(value) is not None + assigned_id: Final = model_info.get("id") + model_info["id"] = ( + DEFAULT_DEPLOYMENT_FAILING_ID + if failing + else assigned_id + if isinstance(assigned_id, str) + else DEFAULT_DEPLOYMENT_COPIED_ID + ) + name: Final = entry.get("model_name") + return { + **entry, + "model_name": name if isinstance(name, str) else str(name or ""), + "litellm_params": dict(as_str_mapping(entry.get("litellm_params")) or {}), + "model_info": model_info, + }, False diff --git a/litellm/router_rust/surface/replay.py b/litellm/router_rust/surface/replay.py new file mode 100644 index 00000000000..6c770e07883 --- /dev/null +++ b/litellm/router_rust/surface/replay.py @@ -0,0 +1,30 @@ +"""The Rust core's live routers, whose deployments a price data reload re-registers in +``litellm.model_cost`` until they retire (``_live_routers`` / ``_replay_live_router_model_cost``).""" + +from __future__ import annotations + +import weakref +from typing import TYPE_CHECKING, Final + +from litellm.utils import add_live_deployment_replay + +if TYPE_CHECKING: + from litellm.router_rust.surface.registry import HostRegistry + +_live_registries: Final[weakref.WeakSet[HostRegistry]] = weakref.WeakSet() + + +def track_live_registry(registry: HostRegistry) -> None: + _live_registries.add(registry) + + +def untrack_live_registry(registry: HostRegistry) -> None: + _live_registries.discard(registry) + + +def _replay_live_registries() -> None: + for registry in tuple(_live_registries): + registry.replay_model_cost_registrations() + + +add_live_deployment_replay(_replay_live_registries) diff --git a/litellm/router_rust/surface/retries.py b/litellm/router_rust/surface/retries.py new file mode 100644 index 00000000000..4a9c6429ffa --- /dev/null +++ b/litellm/router_rust/surface/retries.py @@ -0,0 +1,295 @@ +""" +The retry members ``RustCore`` serves: ``should_retry_this_error`` and +``get_num_retries_from_retry_policy``. router-core decides both; this module only describes the +Python exception the way an attempt failure is described and reads the answer back. +""" + +import dataclasses +import operator +from collections.abc import Iterable, Mapping, Sequence +from typing import TYPE_CHECKING, Final + +from litellm.types.router import RetryPolicy + +# The most retries a request's `num_retries` asks router-core for (its count is a u32). +_MOST_RETRIES: Final = 2**32 - 1 + +if TYPE_CHECKING: + from litellm.router_rust.core import Resolved + from litellm.rust_bridge._native import ( # pyright: ignore[reportPrivateUsage] # the stub's handle + RouterCoreHandle, + ) + + +def resolved_retry_policy(value: object) -> RetryPolicy | None: + """The router's ``retry_policy`` as the Python router's constructor keeps it: a dict is read + into a ``RetryPolicy``, a ``RetryPolicy`` is kept, anything else is no policy.""" + if isinstance(value, RetryPolicy): + return value + if isinstance(value, Mapping): + fields: Final[Mapping[str, int | None]] = value # pyright: ignore[reportUnknownVariableType] # the policy's fields + return RetryPolicy(**fields) # pyright: ignore[reportArgumentType] # validated by the model + return None + + +def _is_policy(entry: object) -> bool: + return isinstance(entry, RetryPolicy | Mapping) + + +def reads_as_policy(entry: object) -> bool: + """Whether ``resolve_retry_policy`` reads ``entry`` without raising: no entry, a ``RetryPolicy``, + or a mapping ``RetryPolicy(**entry)`` accepts.""" + if entry is None or isinstance(entry, RetryPolicy): + return True + if not isinstance(entry, Mapping): + return False + try: + _ = RetryPolicy(**entry) # pyright: ignore[reportUnknownArgumentType] # validated by the model + except Exception: # noqa: BLE001 # any error the lookup would raise + return False + return True + + +def is_policy_per_group(policies: object) -> bool: + """Whether ``model_group_retry_policy`` is what router-core's settings hold: a mapping of + group names to policies (or nothing).""" + if policies is None: + return True + if not isinstance(policies, Mapping): + return False + entries: Final[Mapping[object, object]] = policies # pyright: ignore[reportUnknownVariableType] # read as objects + return all(isinstance(group, str) and _is_policy(entry) for group, entry in entries.items()) + + +def readable_retry_policy(value: object) -> RetryPolicy | None: + """A router ``retry_policy`` written as a plain attribute, as router-core's settings hold it. + The attribute keeps what was written; a value the lookup raises for reaches router-core as + ``retry_policy_raises`` instead.""" + return resolved_retry_policy(value) if reads_as_policy(value) else None + + +@dataclasses.dataclass(frozen=True, slots=True) +class GroupPolicies: + """A ``model_group_retry_policy`` as router-core reads it, resolved the way + ``resolve_retry_policy`` reads it for each group the call may evaluate. + + ``document`` holds a group's policy where the lookup finds one, and an empty policy (which + grants nothing) where it finds ``None``; a group it does not find is absent, so the router's + ``retry_policy`` applies. ``raising`` names the groups whose lookup raises (an ``in``/``[]`` + the value does not support, or an entry that is not a policy, whose fields + ``get_num_retries_from_retry_policy`` then fails to read): the Python retry loop raises that + error in place of the attempt's on a hop's first failure. + """ + + document: Mapping[str, object] + raising: frozenset[str] + + +def _looked_up(policies: object, group: str) -> tuple[bool, object]: + """``(found, entry)`` as ``resolve_retry_policy`` looks ``group`` up; raises as it raises.""" + found: Final = group in policies # pyright: ignore[reportOperatorIssue] # any value, as the Python router reads it + return (True, policies[group]) if found else (False, None) # pyright: ignore[reportIndexIssue, reportUnknownVariableType] # see above + + +def _policy_document(entry: object) -> object: + """A readable entry as router-core reads it: no entry grants nothing, a mapping is read the way + ``RetryPolicy(**entry)`` reads it.""" + if entry is None: + return {} + if isinstance(entry, Mapping): + return RetryPolicy(**entry) # pyright: ignore[reportUnknownArgumentType] # checked by reads_as_policy + return entry + + +def group_policies(policies: object, groups: Iterable[str]) -> GroupPolicies: + """``policies`` resolved for ``groups`` (a mapping is read by its own keys).""" + if policies is None: + return GroupPolicies({}, raising=frozenset()) + if isinstance(policies, Mapping): + entries: Final[Mapping[object, object]] = policies # pyright: ignore[reportUnknownVariableType] # read as objects + # A key that is no string never matches a group name. + named: Final = {group: entry for group, entry in entries.items() if isinstance(group, str)} + readable: Final = {group: entry for group, entry in named.items() if reads_as_policy(entry)} + return GroupPolicies( + {group: _policy_document(entry) for group, entry in readable.items()}, + raising=frozenset(named) - frozenset(readable), + ) + document: Final[dict[str, object]] = {} # mutable-ok: built here; router-core reads it as plain JSON + raising: Final[set[str]] = set() # mutable-ok: the groups whose lookup raises + for group in groups: + try: + found, entry = _looked_up(policies, group) + except Exception: # noqa: BLE001 # the Python retry loop raises it on a hop's first failure + raising.add(group) + continue + if not found: + continue + if not reads_as_policy(entry): + raising.add(group) + continue + document[group] = _policy_document(entry) + return GroupPolicies(document, raising=frozenset(raising)) + + +def static_group_policies(policies: object) -> object: + """The router's ``model_group_retry_policy`` as router-core's static settings hold it. A value + that is not a mapping of policies is resolved per request instead (``group_policies``).""" + return group_policies(policies, ()).document if isinstance(policies, Mapping) else None # pyright: ignore[reportUnknownArgumentType] # read as objects + + +def raising_groups(request: Mapping[str, object], resolved: GroupPolicies) -> Sequence[str]: + """The groups whose ``model_group_retry_policy`` lookup raises on a hop's first failure, unless + the retry loop never reads it: the request opted out with ``num_retries=0``. A streamed Anthropic + messages call is no exception: only the stream's own retry rules read such an entry as no policy + (``_anthropic_messages_resolved_retry_policy``); a failure before the stream opened reaches the + retry loop.""" + if not resolved.raising or request.get("num_retries") == 0: + return () + return sorted(resolved.raising) + + +def policy_lookup_error(original: BaseException, model_group: str, retry_policy: object, policies: object) -> Exception: + """The error ``get_num_retries_from_retry_policy`` raises for ``model_group`` after ``original`` + failed (the Python retry loop raises it in the attempt's place, chained to it); a lookup that + unexpectedly reads is reported as such.""" + from litellm.litellm_core_utils.get_retry_from_policy import get_num_retries_from_retry_policy + + traceback: Final = original.__traceback__ + try: + # Looked up while `original` is being handled, as in the retry loop's `except` block, so + # the error chains to it the way Python chains it. + try: + raise original + except BaseException: # noqa: BLE001 # re-raised only to be handled here + _ = get_num_retries_from_retry_policy( + exception=original, # pyright: ignore[reportArgumentType] # any exception the hop raised + retry_policy=retry_policy, # pyright: ignore[reportArgumentType] # the router's resolved policy + model_group=model_group, + model_group_retry_policy=policies, # pyright: ignore[reportArgumentType] # read as the Python router reads it + ) + except Exception as raised: # noqa: BLE001 # the error the hop ends with + return raised + finally: + original.__traceback__ = traceback # rebind-ok: put back as the hop left it + return RuntimeError(f"the model_group_retry_policy lookup for {model_group!r} did not raise") + + +def router_policy_retries( + exception: Exception, retry_policy: object, policies: object, model_group: str | None +) -> int | None: + """``get_num_retries_from_retry_policy`` for a router ``model_group_retry_policy`` that is not + a mapping of policies, read as the Python router reads it (raising as it raises).""" + from litellm.litellm_core_utils.get_retry_from_policy import get_num_retries_from_retry_policy + + return get_num_retries_from_retry_policy( + exception=exception, + retry_policy=retry_policy, # pyright: ignore[reportArgumentType] # the router's resolved policy + model_group=model_group, + model_group_retry_policy=policies, # pyright: ignore[reportArgumentType] # read as the Python router reads it + ) + + +def request_retry_fields(value: object) -> Mapping[str, object]: + """A request's ``num_retries`` as router-core reads it. ``async_function_with_retries`` never + casts it: it compares it with 0, and counts with ``range`` only once it is positive.""" + if value is None: + return {} + if isinstance(value, int): + count: Final = int(value) + return {"num_retries": min(count, _MOST_RETRIES)} if count >= 0 else {"uncounted_retries": "negative"} + try: + if value == 0: + return {"num_retries": 0} + if not value > 0: # pyright: ignore[reportOperatorIssue] # any value, compared as the retry loop compares it + return {"uncounted_retries": "not_positive"} + return {"num_retries": min(operator.index(value), _MOST_RETRIES)} # pyright: ignore[reportArgumentType] # see above + except Exception: # noqa: BLE001 # the retry loop raises it on a hop's first failure + return {"uncounted_retries": "raises"} + + +def retry_count_error(original: BaseException, value: object) -> Exception: + """The error the retry loop raises reading a request's ``num_retries`` after ``original`` + failed, chained to it; a value that unexpectedly reads is reported as such.""" + traceback: Final = original.__traceback__ + try: + try: + raise original + except BaseException: # noqa: BLE001 # re-raised only to be handled here + if value > 0: # pyright: ignore[reportOperatorIssue] # `if num_retries > 0:` + _ = range(value) # pyright: ignore[reportArgumentType] # `for current_attempt in range(num_retries):` + except Exception as raised: # noqa: BLE001 # the error the hop ends with + return raised + finally: + original.__traceback__ = traceback # rebind-ok: put back as the hop left it + return RuntimeError(f"the request's num_retries {value!r} did not raise") + + +def _count(deployments: object) -> int: + return len(deployments) if isinstance(deployments, list) else 0 # pyright: ignore[reportUnknownArgumentType] # only the length is read + + +def _filled(fallbacks: object) -> bool: + return isinstance(fallbacks, Sequence) and len(fallbacks) > 0 # pyright: ignore[reportUnknownArgumentType] # only the length is read + + +class RustRetries: + """Retry members read from the Rust core's handle.""" + + _handle: "RouterCoreHandle" + _resolved: "Resolved" + + @property + def _written_retry_policy(self) -> object: + """The ``retry_policy`` attribute as written (``Resolved`` holds what router-core reads).""" + raise NotImplementedError + + def should_retry_this_error( + self, + error: Exception, + healthy_deployments: list[object] | None = None, # mutable-ok: the Python router's signature + all_deployments: list[object] | None = None, # mutable-ok: same + context_window_fallbacks: list[object] | None = None, # mutable-ok: same + content_policy_fallbacks: list[object] | None = None, # mutable-ok: same + regular_fallbacks: list[object] | None = None, # mutable-ok: same + ) -> bool: + """``True`` when the error is retried in the same group; otherwise the error is raised.""" + from litellm.router_rust.core import attempt_failure + + retried: Final = self._handle.should_retry( + dict(attempt_failure(error)), + (_count(healthy_deployments), _count(all_deployments)), + (context_window_fallbacks is not None, content_policy_fallbacks is not None, _filled(regular_fallbacks)), + ) + if not retried: + raise error + return True + + def get_num_retries_from_retry_policy(self, exception: Exception, model_group: str | None = None) -> int | None: + from litellm.router_rust.core import attempt_failure + + resolved: Final = self._resolved + written: Final = self._written_retry_policy + if not is_policy_per_group(resolved.model_group_retry_policy) or not reads_as_policy(written): + return router_policy_retries(exception, written, resolved.model_group_retry_policy, model_group) + # A dict lookup hashes any key and only a string can match; the native call takes strings alone. + _ = hash(model_group) + return self._handle.retry_policy_retries( + dict(attempt_failure(exception)), model_group if isinstance(model_group, str) else None + ) + + +__all__ = [ + "GroupPolicies", + "RustRetries", + "group_policies", + "is_policy_per_group", + "policy_lookup_error", + "raising_groups", + "readable_retry_policy", + "reads_as_policy", + "request_retry_fields", + "resolved_retry_policy", + "retry_count_error", + "router_policy_retries", + "static_group_policies", +] diff --git a/litellm/router_rust/surface/settings.py b/litellm/router_rust/surface/settings.py new file mode 100644 index 00000000000..c8635593de5 --- /dev/null +++ b/litellm/router_rust/surface/settings.py @@ -0,0 +1,236 @@ +""" +The Rust core's settings semantics on the host side: how ``ChangeSet.settings`` is read (the rules +of ``update_settings``), the ``settings().as_dict()`` view (``get_settings``), the router attributes +the Python core keeps as plain attributes, deleted settings, and the construction-time side effects +of the logging arguments. + +The rules are the Python router core's, ported (never imported). Settings change only through a +changeset; a direct attribute write is turned into one by ``RustCore.__setattr__``. +""" + +import logging +from collections.abc import Mapping +from dataclasses import dataclass, field +from types import MappingProxyType +from typing import TYPE_CHECKING, Final + +from litellm._logging import verbose_router_logger +from litellm.constants import RUNTIME_UPDATABLE_ROUTER_SETTINGS +from litellm.litellm_core_utils.routing_groups import validate_routing_strategy +from litellm.types.router import RetryPolicy, RoutingStrategy + +if TYPE_CHECKING: + from litellm.router_config import RouterConfig + from litellm.router_python_host import PythonHost + +MISSING: Final = object() + +# `update_settings` casts these with `int(value)`. +_INT_SETTINGS: Final = frozenset({"timeout", "num_retries", "retry_after", "allowed_fails", "cooldown_time"}) +CONTINUATION_SETTING: Final = "enable_mid_stream_fallback_continuation" + +# Settings the Python core keeps as plain router attributes and `update_settings` sets as given, +# with their constructor defaults. ``max_retries`` has none: it exists once a changeset sets it. +PLAIN_DEFAULTS: Final[Mapping[str, object]] = MappingProxyType( + { + "retry_policy": None, + "model_group_retry_policy": {}, + "enable_weighted_failover": False, + "fallback_on_unsupported_params": True, + } +) +# `get_settings`: the settings it lists, in its order (`routing_groups` comes last). +_VIEW_ORDER: Final = ( + "routing_strategy_args", + "routing_strategy", + "allowed_fails", + "cooldown_time", + "num_retries", + "timeout", + "max_retries", + "retry_after", + "fallbacks", + "context_window_fallbacks", + "model_group_retry_policy", + "retry_policy", + "model_group_alias", + "enable_weighted_failover", + "enable_mid_stream_fallback_continuation", + "enable_tag_filtering", + "tag_routing_prefix", + "fallback_on_unsupported_params", +) + +# Router attributes that are their constructor argument as given, else this default. Arguments +# the Rust core declines are only ever at their default here. +_ARGUMENT_ATTRIBUTES: Final[Mapping[str, object]] = MappingProxyType( + { + "set_verbose": False, + "debug_level": "INFO", + "client_ttl": 3600, + "stream_timeout": None, + "assistants_config": None, + "ignore_invalid_deployments": False, + "alerting_config": None, + "auto_router_capability_limit": None, + "deployment_affinity_ttl_seconds": 3600, + "session_affinity_repin_on_failover": False, + "model_group_affinity_config": None, + } +) +# Class-level and constant attributes of the Python core. +_CONSTANT_ATTRIBUTES: Final[Mapping[str, object]] = MappingProxyType( + {"default_cache_time_seconds": 1 * 60 * 60, "tenacity": None, "access_groups": None} +) + + +@dataclass(frozen=True) +class SettingsUpdate: + """What a ``ChangeSet.settings`` mapping changes, read with ``update_settings``' rules.""" + + values: Mapping[str, object] = field(default_factory=lambda: MappingProxyType({})) # fields and plain settings + plain: Mapping[str, object] = field(default_factory=lambda: MappingProxyType({})) # plain attributes, as stored + continuation: object = MISSING # the continuation flag, when given + routing_groups: object = MISSING # the routing groups input, when given + optional_pre_call_checks: object = MISSING # the optional pre-call checks, when given + failure: Exception | None = None # what stopped the reading; the settings before it stay applied + + +def read_settings_update(settings: Mapping[str, object], routing_strategy: object) -> SettingsUpdate: + """``_core_update_settings``' reading of each setting, in order: names that are not + runtime-updatable are ignored, the integer settings are cast with ``int``, a retry policy dict + becomes a ``RetryPolicy`` (any other type but ``None`` is dropped), and a strategy other than + ``routing_strategy``, the router's, is validated. The loop has no rollback: a setting that + raises ends it, and the ones before it are applied.""" + values: Final[dict[str, object]] = {} # mutable-ok: built here, then frozen into the update + plain: Final[dict[str, object]] = {} # mutable-ok: same + continuation: object = MISSING # rebind-ok: set when the flag is given + routing_groups: object = MISSING # rebind-ok: set when routing groups are given + optional_checks: object = MISSING # rebind-ok: set when the optional pre-call checks are given + failure: Exception | None = None # rebind-ok: set when a setting raises + try: + for name, value in settings.items(): + if name not in RUNTIME_UPDATABLE_ROUTER_SETTINGS: + verbose_router_logger.debug("Setting %s is not allowed", name) + elif name in _INT_SETTINGS: + values[name] = int(value) # pyright: ignore[reportArgumentType] # `int(kwargs[var])`, as given: a bad value raises int's own error + elif name == "routing_groups": + routing_groups = value + elif name == "optional_pre_call_checks": + # `set_optional_pre_call_checks` reads a list it is given as a set. + _ = frozenset[object](value) if value is not None else None # pyright: ignore[reportArgumentType] # as given: a bad value raises frozenset's own error + optional_checks = value + elif name == CONTINUATION_SETTING: + continuation = value + elif name == "retry_policy": + policy = RetryPolicy.model_validate(value) if isinstance(value, dict) else value + if policy is None or isinstance(policy, RetryPolicy): + plain[name] = policy + elif name in PLAIN_DEFAULTS or name == "max_retries": + plain[name] = value + else: + if name == "routing_strategy" and _normalized(value) != routing_strategy: + validate_routing_strategy(value) # pyright: ignore[reportArgumentType] # validated as given + values[name] = value + except Exception as raised: # noqa: BLE001 # raised by `apply` once the settings before it are applied + failure = raised # rebind-ok: None until a setting fails + return SettingsUpdate( + values=MappingProxyType(values), + plain=MappingProxyType(plain), + continuation=continuation, + routing_groups=routing_groups, + optional_pre_call_checks=optional_checks, + failure=failure, + ) + + +def _normalized(strategy: object) -> object: + """``_normalize_strategy``, which leaves anything but the enum as given.""" + return strategy.value if isinstance(strategy, RoutingStrategy) else strategy + + +def initial_plain(config: "RouterConfig") -> dict[str, object]: # mutable-ok: the core's own plain attributes + """The plain attributes as the constructor sets them: a ``retry_policy`` dict is read into a + ``RetryPolicy`` and any other type but a policy is no policy.""" + from litellm.router_rust.surface.retries import resolved_retry_policy + + plain: Final = {name: config.get(name, default) for name, default in PLAIN_DEFAULTS.items()} + plain["retry_policy"] = resolved_retry_policy(plain["retry_policy"]) + return plain + + +def settings_view( + values: Mapping[str, object], plain: Mapping[str, object], deleted: frozenset[str] +) -> dict[str, object]: # mutable-ok: the settings view is built fresh per call, as `get_settings` builds it + """``get_settings``: the listed settings the router has, then the routing groups. ``values`` + holds the settings fields and plain attributes the Rust core resolves.""" + view: Final[dict[str, object]] = {} # mutable-ok: see above + for name in _VIEW_ORDER: + if name in deleted: + continue + if name in plain: + view[name] = plain[name] + elif name in values: + view[name] = values[name] + view["routing_groups"] = values.get("routing_groups", []) + return view + + +def argument_attribute(config: "RouterConfig", name: str) -> object: + """A router attribute that is its constructor argument (or a constant), else ``MISSING``.""" + if name in _ARGUMENT_ATTRIBUTES: + return config.get(name, _ARGUMENT_ATTRIBUTES[name]) + if name in _CONSTANT_ATTRIBUTES: + return _CONSTANT_ATTRIBUTES[name] + return MISSING + + +def default_litellm_params(config: "RouterConfig") -> dict[str, object]: # mutable-ok: the router's own dict + """``default_litellm_params`` as the constructor completes it: the router timeout, no client + retries and the caching groups.""" + given: Final = _as_dict(config.get("default_litellm_params")) or {} + params: Final[dict[str, object]] = dict(given) # mutable-ok: see above + params.setdefault("timeout", config.get("timeout")) + params.setdefault("max_retries", 0) + metadata: Final = _as_dict(params.setdefault("metadata", {})) + if metadata is not None: + params["metadata"] = {**metadata, "caching_groups": config.get("caching_groups")} + return params + + +def _as_dict(value: object) -> Mapping[str, object] | None: + return value if isinstance(value, dict) else None # pyright: ignore[reportUnknownVariableType] # the argument dict, as passed + + +def request_timeout(config: "RouterConfig") -> float | None: + """The per-attempt ``request_timeout``: only stored when a router timeout is also set.""" + from litellm.litellm_core_utils.request_timeout_resolver import get_configured_request_timeout + + return get_configured_request_timeout() if config.get("timeout") is not None else None + + +def apply_construction_effects(config: "RouterConfig", host: "PythonHost") -> None: + """What the constructor's logging arguments do: the host stops its debug info, and + ``set_verbose`` sets the router logger to ``debug_level``.""" + host.suppress_debug_info() + if config.get("set_verbose", False) is True: + level: Final = config.get("debug_level", "INFO") + if level == "INFO": + verbose_router_logger.setLevel(logging.INFO) + elif level == "DEBUG": + verbose_router_logger.setLevel(logging.DEBUG) + + +__all__ = [ + "CONTINUATION_SETTING", + "MISSING", + "PLAIN_DEFAULTS", + "SettingsUpdate", + "apply_construction_effects", + "argument_attribute", + "default_litellm_params", + "initial_plain", + "read_settings_update", + "request_timeout", + "settings_view", +] diff --git a/litellm/router_strategy/adaptive_router/signals.py b/litellm/router_strategy/adaptive_router/signals.py index 72e8d27d2bf..c7fffd05632 100644 --- a/litellm/router_strategy/adaptive_router/signals.py +++ b/litellm/router_strategy/adaptive_router/signals.py @@ -198,7 +198,7 @@ def _detect_loop(history: list[str], new_calls: Sequence[Mapping[str, object]]) return False -_EXHAUSTION_STATUSES: Final = {408, 413, 429, 503, 504} +_EXHAUSTION_STATUSES: Final = {408, 413, 429, 503, 504, 529} _EXHAUSTION_KEYWORDS: Final = ( "context length", diff --git a/litellm/router_strategy/auto_router/litellm_encoder.py b/litellm/router_strategy/auto_router/litellm_encoder.py index 743a0b97fd2..a402f9c8ecf 100644 --- a/litellm/router_strategy/auto_router/litellm_encoder.py +++ b/litellm/router_strategy/auto_router/litellm_encoder.py @@ -30,7 +30,7 @@ class CustomDenseEncoder(DenseEncoder): litellm_router_instance: ClassVar = RenamedRouterAttribute() # deprecated: the router attribute before ``ctx`` @renamed_router_param("litellm_router_instance") - def __init__(self, ctx: Optional["RoutingContext"] = None, **kwargs): + def __init__(self, ctx: Optional["RoutingContext"] = None, **kwargs) -> None: if "ctx" in kwargs: ctx = kwargs.pop("ctx") @@ -55,7 +55,7 @@ class LiteLLMRouterEncoder(CustomDenseEncoder, AsymmetricDenseMixin): model_name: str, score_threshold: float | None = None, max_input_chars: int = 0, - ): + ) -> None: """Initialize the LiteLLMEncoder. :param ctx: The routing context of the owning router. diff --git a/litellm/router_strategy/budget_limiter.py b/litellm/router_strategy/budget_limiter.py index 1d502dd8d95..98dd39b40e3 100644 --- a/litellm/router_strategy/budget_limiter.py +++ b/litellm/router_strategy/budget_limiter.py @@ -36,7 +36,12 @@ from litellm._logging import verbose_router_logger from litellm.caching.caching import DualCache from litellm.caching.redis_cache import RedisCache, RedisPipelineIncrementOperation, log_redis_failure from litellm.integrations.custom_logger import CustomLogger, Span -from litellm.litellm_core_utils.batch_utils import batch_charged_once_marker_key, batch_id_to_charge_once +from litellm.litellm_core_utils.batch_utils import ( + ChargeOnceJob, + defers_batch_cost, + job_charged_once_marker_key, + job_to_charge_once, +) from litellm.litellm_core_utils.core_helpers import ( get_metadata_variable_name_from_kwargs, ) @@ -52,7 +57,7 @@ from litellm.types.utils import BudgetConfig as GenericBudgetInfo DEFAULT_REDIS_SYNC_INTERVAL: Final = 1 _CALLBACK_FIELDS: Final = TypeAdapter(dict[str, object]) -_BATCH_CHARGE_VALUES: Final = TypeAdapter(tuple[object, float]) +_JOB_CHARGE_VALUES: Final = TypeAdapter(tuple[object, float]) class _LiteLLMParamsDictView: @@ -545,13 +550,16 @@ class RouterBudgetLimiting(CustomLogger): if standard_logging_payload is None: raise ValueError("standard_logging_payload is required") - batch_response, response_cost = _BATCH_CHARGE_VALUES.validate_python( + polled_response, response_cost = _JOB_CHARGE_VALUES.validate_python( (response_obj, _CALLBACK_FIELDS.validate_python(standard_logging_payload).get("response_cost", 0)) ) model_id: Final[str] = str(standard_logging_payload.get("model_id", "")) custom_llm_provider: Final[str | None] = standard_logging_payload.get("custom_llm_provider") - batch_id: Final = batch_id_to_charge_once(callback_fields.get("call_type"), batch_response, response_cost) + if defers_batch_cost(callback_fields, polled_response): + return + + job: Final = job_to_charge_once(callback_fields, polled_response, response_cost) budget_config: Final = ( self._get_budget_config_for_provider(custom_llm_provider) if custom_llm_provider is not None else None @@ -565,7 +573,7 @@ class RouterBudgetLimiting(CustomLogger): spend_key=spend_key, start_time_key=start_time_key, response_cost=response_cost, - batch_id=batch_id, + job=job, ) deployment_budget_config: Final = self._get_budget_config_for_deployment(model_id) @@ -578,7 +586,7 @@ class RouterBudgetLimiting(CustomLogger): spend_key=deployment_spend_key, start_time_key=deployment_start_time_key, response_cost=response_cost, - batch_id=batch_id, + job=job, ) request_tags: Final = get_tags_from_request_kwargs( @@ -596,7 +604,7 @@ class RouterBudgetLimiting(CustomLogger): spend_key=_tag_spend_key, start_time_key=_tag_start_time_key, response_cost=response_cost, - batch_id=batch_id, + job=job, ) async def _increment_spend_for_key( @@ -605,14 +613,21 @@ class RouterBudgetLimiting(CustomLogger): spend_key: str, start_time_key: str, response_cost: float, - batch_id: str | None = None, + job: ChargeOnceJob | None = None, ): if budget_config.budget_duration is None: return current_time: Final = self._clock() new_window_seconds: Final = budget_window_seconds(current_time, budget_config.budget_duration) - if batch_id is not None and not await self._claim_batch_charge(spend_key, batch_id, new_window_seconds): + if job is not None and not await self._claim_job_charge(spend_key, job, new_window_seconds): + if job.repeat_poll_cost > 0: + await self._increment_spend_for_key( + budget_config=budget_config, + spend_key=spend_key, + start_time_key=start_time_key, + response_cost=job.repeat_poll_cost, + ) return budget_start: Final = await self._get_or_set_budget_start_time( @@ -639,8 +654,8 @@ class RouterBudgetLimiting(CustomLogger): verbose_router_logger.debug("Incremented spend for %s by %s", spend_key, response_cost) - async def _claim_batch_charge(self, spend_key: str, batch_id: str, ttl_seconds: int) -> bool: - marker_key: Final = batch_charged_once_marker_key(spend_key=spend_key, batch_id=batch_id) + async def _claim_job_charge(self, spend_key: str, job: ChargeOnceJob, ttl_seconds: int) -> bool: + marker_key: Final = job_charged_once_marker_key(spend_key=spend_key, job=job) redis_cache: Final = self.dual_cache.redis_cache if redis_cache is not None: polls: Final = await redis_cache.async_increment(key=marker_key, value=1, ttl=ttl_seconds, refresh_ttl=True) diff --git a/litellm/router_strategy/complexity_router/complexity_router.py b/litellm/router_strategy/complexity_router/complexity_router.py index 4f4ed76c170..05dd4706b62 100644 --- a/litellm/router_strategy/complexity_router/complexity_router.py +++ b/litellm/router_strategy/complexity_router/complexity_router.py @@ -1219,9 +1219,11 @@ def _with_classifier_forecast( forecasted_decision: Final[StandardLoggingRoutingDecision] = { **with_input, "classifier_probabilities": outcome.jev_verdict.probabilities, - "classifier_confidence": outcome.jev_verdict.confidence, } - return forecasted_decision + confidence: Final = outcome.jev_verdict.confidence + return ( + forecasted_decision if confidence is None else {**forecasted_decision, "classifier_confidence": confidence} + ) if outcome.llm_v2_forecast is not None: return _with_llm_v2_forecast(with_input, outcome.llm_v2_forecast) forecast: Final = outcome.capability_forecast @@ -2468,7 +2470,7 @@ class ComplexityRouter(CustomLogger): score=None, signals=( f"{config.provider}-classifier:{tier_name}", - f"{config.provider}-confidence={answer.confidence:.6f}", + *(() if answer.confidence is None else (f"{config.provider}-confidence={answer.confidence:.6f}",)), *( f"tier-probability:{label}={probability:.6f}" for label, probability in answer.probabilities.items() diff --git a/litellm/router_strategy/complexity_router/jev_classifier.py b/litellm/router_strategy/complexity_router/jev_classifier.py index bb7d2e91cd3..5cd4f00a941 100644 --- a/litellm/router_strategy/complexity_router/jev_classifier.py +++ b/litellm/router_strategy/complexity_router/jev_classifier.py @@ -210,7 +210,7 @@ class JevChoiceAnswer(LiteLLMBaseModel): type: Literal["choice"] choice: str probabilities: Mapping[str, JevProbability] - confidence: JevProbability + confidence: JevProbability | None = None class JevUsage(LiteLLMBaseModel): @@ -425,7 +425,7 @@ class HttpJevClassifierClient: class JevVerdict(NamedTuple): label: str probabilities: Mapping[str, float] - confidence: float + confidence: float | None model: str cost: float | None provider: str = "typesafe" diff --git a/litellm/router_strategy/least_busy.py b/litellm/router_strategy/least_busy.py index 8e0c3d6a7e7..22159079f98 100644 --- a/litellm/router_strategy/least_busy.py +++ b/litellm/router_strategy/least_busy.py @@ -1,6 +1,11 @@ +import contextlib import logging -from collections.abc import Mapping, Sequence -from typing import Final +import threading +import time +import uuid +from collections.abc import Callable, Generator, Mapping, Sequence +from contextvars import ContextVar +from typing import Final, Protocol, TypeAlias from pydantic import TypeAdapter, ValidationError from typing_extensions import ReadOnly, TypedDict @@ -8,11 +13,31 @@ from typing_extensions import ReadOnly, TypedDict from litellm._internal_context import with_service_target from litellm._logging import verbose_router_logger from litellm.caching.caching import DualCache +from litellm.caching.in_memory_cache import InMemoryCache from litellm.caching.redis_cache import log_redis_failure from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type +from litellm.types.utils import CallTypes IN_FLIGHT_COUNT_TTL_SECONDS: Final = 60 * 60 +SELECTION_RESERVATION_TTL_SECONDS: Final = 30.0 +SELECTION_RESERVATION_MAX_KEYS: Final = 10_000 +_RESERVATIONS_LOCK: Final = threading.Lock() +_PICK_RESERVES: Final[ContextVar[bool]] = ContextVar("least_busy_pick_reserves") +_PICK_OWNER: Final[ContextVar[str | None]] = ContextVar("least_busy_pick_owner", default=None) + + +@contextlib.contextmanager +def picks_reserve(reserve: bool) -> Generator[None, None, None]: + token: Final = _PICK_RESERVES.set(reserve) + try: + yield + finally: + _PICK_RESERVES.reset(token) + + +def pick_reserves(default: bool) -> bool: + return _PICK_RESERVES.get(default) class _ModelInfo(TypedDict, total=False): @@ -21,10 +46,12 @@ class _ModelInfo(TypedDict, total=False): class _Metadata(TypedDict, total=False): model_group: ReadOnly[str | None] + model_info: ReadOnly[_ModelInfo | None] class _LitellmParams(TypedDict, total=False): metadata: ReadOnly[_Metadata | None] + litellm_metadata: ReadOnly[_Metadata | None] model_info: ReadOnly[_ModelInfo | None] @@ -32,6 +59,10 @@ class _CallKwargs(TypedDict, total=False): litellm_params: ReadOnly[_LitellmParams | None] +class CallIdentity(TypedDict, total=False): + litellm_call_id: ReadOnly[object] + + class _DeploymentModelInfo(TypedDict): id: ReadOnly[str | int] @@ -41,38 +72,85 @@ class _Deployment(TypedDict): _CALL_KWARGS: Final = TypeAdapter(_CallKwargs) +CALL_IDENTITY: Final = TypeAdapter(CallIdentity) _DEPLOYMENTS: Final = TypeAdapter(list[_Deployment]) -_MEMORY_COUNTS: Final = TypeAdapter(tuple[float | None, ...] | None) +_MEMORY_COUNTS: Final[TypeAdapter[tuple[float | None, ...] | None]] = TypeAdapter(tuple[float | None, ...] | None) +_ATTEMPT_TIMES: Final[TypeAdapter[tuple[float, ...] | None]] = TypeAdapter(tuple[float, ...] | None) +_Pick: TypeAlias = tuple[float, str | None] +_PICKS: Final[TypeAdapter[tuple[_Pick, ...] | None]] = TypeAdapter(tuple[_Pick, ...] | None) +_PICKED_DEPLOYMENTS: Final[TypeAdapter[tuple[str, ...] | None]] = TypeAdapter(tuple[str, ...] | None) def _request_count_key(model_group: str, deployment_id: str) -> str: return f"{model_group}_request_count:{deployment_id}" +def _model_group(metadata: _Metadata | None) -> str | None: + return metadata.get("model_group") if metadata else None + + +def _deployment_id(model_info: _ModelInfo | None) -> str | int | None: + return model_info.get("id") if model_info else None + + +def _routed_deployment_id(metadata: _Metadata | None) -> str | int | None: + return _deployment_id(metadata.get("model_info")) if metadata else None + + def _deployment_ref(kwargs: Mapping[str, object]) -> tuple[str, str] | None: - if is_batch_retrieve_call_type(kwargs.get("call_type")): + call_type: Final = kwargs.get("call_type") + if is_batch_retrieve_call_type(call_type) or call_type == CallTypes.arealtime.value: return None try: call: Final = _CALL_KWARGS.validate_python(kwargs) except ValidationError: return None - litellm_params: Final = call.get("litellm_params") - metadata: Final = litellm_params.get("metadata") if litellm_params else None - model_info: Final = litellm_params.get("model_info") if litellm_params else None - model_group: Final = metadata.get("model_group") if metadata else None - deployment_id: Final = model_info.get("id") if model_info else None + litellm_params: Final = call.get("litellm_params") or _LitellmParams() + routing_metadata: Final = (litellm_params.get("litellm_metadata"), litellm_params.get("metadata")) + model_group: Final = next((group for group in map(_model_group, routing_metadata) if group is not None), None) + deployment_id: Final = next( + ( + deployment_id + for deployment_id in ( + _deployment_id(litellm_params.get("model_info")), + *map(_routed_deployment_id, routing_metadata), + ) + if deployment_id is not None + ), + None, + ) if model_group is None or deployment_id is None: return None return model_group, str(deployment_id) -def _request_count_keys(model_group: str, healthy_deployments: Sequence[Mapping[str, object]]) -> tuple[str, ...]: +def _reservation_key(deployment_id: str) -> str: + return f"least_busy_reservations:{deployment_id}" + + +def _started_attempts_key(call_id: str, ref: tuple[str, str]) -> str: + return f"least_busy_started:{call_id}:{_request_count_key(*ref)}" + + +def _picked_deployments_key(call_id: str) -> str: + return f"least_busy_picked:{call_id}" + + +def call_id_of(kwargs: Mapping[str, object]) -> str | None: + call_id: Final = kwargs.get("litellm_call_id") + return call_id if isinstance(call_id, str) else None + + +def _deployment_ids(healthy_deployments: Sequence[Mapping[str, object]]) -> tuple[str, ...]: return tuple( - _request_count_key(model_group, str(deployment["model_info"]["id"])) - for deployment in _DEPLOYMENTS.validate_python(healthy_deployments) + str(deployment["model_info"]["id"]) for deployment in _DEPLOYMENTS.validate_python(healthy_deployments) ) +def _request_count_keys(model_group: str, deployment_ids: tuple[str, ...]) -> tuple[str, ...]: + return tuple(_request_count_key(model_group, deployment_id) for deployment_id in deployment_ids) + + def _as_counts(values: Sequence[float | None]) -> tuple[int, ...]: return tuple(0 if value is None else int(value) for value in values) @@ -84,12 +162,21 @@ def _local_counts(raw: object, keys: tuple[str, ...]) -> tuple[int, ...]: return _as_counts(values) -def _least_busy( - healthy_deployments: Sequence[Mapping[str, object]], counts: tuple[int, ...] -) -> Mapping[str, object] | None: - if not healthy_deployments: - return None - return healthy_deployments[min(range(len(healthy_deployments)), key=lambda index: counts[index])] +def _unexpired(picks: Sequence[_Pick], now: float) -> tuple[_Pick, ...]: + return tuple(pick for pick in picks if now - pick[0] < SELECTION_RESERVATION_TTL_SECONDS) + + +def _without_one_pick(picks: tuple[_Pick, ...], call_id: str | None) -> tuple[_Pick, ...]: + tags: Final = tuple(tag for _, tag in picks) + owner: Final = next((tag for tag in (call_id, _PICK_OWNER.get()) if tag is not None and tag in tags), None) + if owner not in tags: + return picks + index: Final = tags.index(owner) + return (*picks[:index], *picks[index + 1 :]) + + +def _least_busy_index(counts: tuple[int, ...]) -> int: + return min(range(len(counts)), key=lambda index: counts[index]) def _warn_unreadable(model_group: str, error: Exception) -> None: @@ -111,24 +198,156 @@ def _warn_unwritable(key: str, error: Exception) -> None: ) +class _ReservationStore(Protocol): + def get_cache(self, key: str) -> object: ... + + def set_cache(self, key: str, value: tuple[object, ...], *, ttl: float) -> None: ... + + def delete_cache(self, key: str) -> None: ... + + +def _picks(store: _ReservationStore, deployment_id: str) -> tuple[_Pick, ...]: + return _PICKS.validate_python(store.get_cache(_reservation_key(deployment_id))) or () + + +def _attempt_times(store: _ReservationStore, key: str) -> tuple[float, ...]: + return _ATTEMPT_TIMES.validate_python(store.get_cache(key)) or () + + +def _picked_deployments(store: _ReservationStore, call_id: str) -> tuple[str, ...]: + return _PICKED_DEPLOYMENTS.validate_python(store.get_cache(_picked_deployments_key(call_id))) or () + + +def _put(store: _ReservationStore, key: str, values: tuple[object, ...], ttl: float) -> None: + # InMemoryCache keeps a live key's first TTL, so drop the key to restart it + store.delete_cache(key) + if values: + store.set_cache(key, values, ttl=ttl) + + +def _release_call_on(store: _ReservationStore, deployment_id: str, call_id: str) -> None: + kept: Final = tuple(pick for pick in _picks(store, deployment_id) if pick[1] != call_id) + _put(store, _reservation_key(deployment_id), kept, SELECTION_RESERVATION_TTL_SECONDS) + + +def release_unstarted_picks(store: _ReservationStore, call_id: str | None) -> None: + if call_id is None: + return + if not _picked_deployments(store, call_id): + return + with _RESERVATIONS_LOCK: + for deployment_id in frozenset(_picked_deployments(store, call_id)): + _release_call_on(store, deployment_id, call_id) + store.delete_cache(_picked_deployments_key(call_id)) + + +@contextlib.contextmanager +def owning_picks(store: _ReservationStore, call_id: str | None) -> Generator[None, None, None]: + owner: Final = call_id or _PICK_OWNER.get() or uuid.uuid4().hex + token: Final = _PICK_OWNER.set(owner) + try: + yield + finally: + _PICK_OWNER.reset(token) + release_unstarted_picks(store, owner) + + class LeastBusyLoggingHandler(CustomLogger): test_flag: bool = False logged_success: int = 0 logged_failure: int = 0 - def __init__(self, router_cache: DualCache): + def __init__( + self, + router_cache: DualCache, + clock: Callable[[], float] = time.monotonic, + reservation_store: _ReservationStore | None = None, + ): self.router_cache = router_cache self.router_cache_id = str(id(router_cache)) + self._clock = clock + self._reservations: Final[_ReservationStore] = ( + reservation_store + if reservation_store is not None + else InMemoryCache(max_size_in_memory=SELECTION_RESERVATION_MAX_KEYS, clock=clock) + ) + + def _live_reservations(self, deployment_id: str, now: float) -> tuple[_Pick, ...]: + return _unexpired(_picks(self._reservations, deployment_id), now) + + def _store_reservations(self, deployment_id: str, picks: tuple[_Pick, ...]) -> None: + _put(self._reservations, _reservation_key(deployment_id), picks, SELECTION_RESERVATION_TTL_SECONDS) + + def _take_reservation(self, deployment_id: str, call_id: str | None, now: float) -> None: + self._store_reservations(deployment_id, _without_one_pick(self._live_reservations(deployment_id, now), call_id)) + + def _record_pick(self, call_id: str, deployment_id: str) -> None: + picked: Final = (*_picked_deployments(self._reservations, call_id), deployment_id) + _put(self._reservations, _picked_deployments_key(call_id), picked, SELECTION_RESERVATION_TTL_SECONDS) + + def _select( + self, + healthy_deployments: Sequence[Mapping[str, object]], + deployment_ids: tuple[str, ...], + keys: tuple[str, ...], + shared: tuple[int, ...] | None, + reserve: bool, + call_id: str | None, + ) -> Mapping[str, object] | None: + if not healthy_deployments: + return None + with _RESERVATIONS_LOCK: + now: Final = self._clock() + counts: Final = ( + self._this_workers_counts(keys) if shared is None else self._at_least_this_workers(keys, shared) + ) + live: Final = tuple(self._live_reservations(deployment_id, now) for deployment_id in deployment_ids) + index: Final = _least_busy_index(tuple(count + len(r) for count, r in zip(counts, live, strict=True))) + if reserve: + tag: Final = call_id if call_id is not None else _PICK_OWNER.get() + self._store_reservations(deployment_ids[index], (*live[index], (now, tag))) + if tag is not None: + self._record_pick(tag, deployment_ids[index]) + return healthy_deployments[index] + + def _start_attempt(self, ref: tuple[str, str], call_id: str | None) -> None: + with _RESERVATIONS_LOCK: + now: Final = self._clock() + self._take_reservation(ref[1], call_id, now) + self._count_locally(_request_count_key(*ref), 1) + if call_id is not None: + key: Final = _started_attempts_key(call_id, ref) + started: Final = (*_attempt_times(self._reservations, key), now) + _put(self._reservations, key, started, IN_FLIGHT_COUNT_TTL_SECONDS) + + def _end_attempt(self, ref: tuple[str, str], call_id: str | None) -> bool: + if call_id is None: + with _RESERVATIONS_LOCK: + self._count_locally(_request_count_key(*ref), -1) + return True + key: Final = _started_attempts_key(call_id, ref) + with _RESERVATIONS_LOCK: + started: Final = _attempt_times(self._reservations, key) + if started: + _put(self._reservations, key, started[1:], IN_FLIGHT_COUNT_TTL_SECONDS) + self._count_locally(_request_count_key(*ref), -1) + else: + self._take_reservation(ref[1], call_id, self._clock()) + return bool(started) @with_service_target("router_usage") def log_pre_api_call(self, model: str, messages: object, kwargs: Mapping[str, object]) -> None: - self._increment(kwargs, 1) + ref: Final = _deployment_ref(kwargs) + if ref is None: + return + self._start_attempt(ref, call_id_of(kwargs)) + self._count_shared(_request_count_key(*ref), 1) @with_service_target("router_usage") def log_success_event( self, kwargs: Mapping[str, object], response_obj: object, start_time: object, end_time: object ) -> None: - self._increment(kwargs, -1) + self._settle(kwargs) if self.test_flag: self.logged_success += 1 @@ -136,7 +355,7 @@ class LeastBusyLoggingHandler(CustomLogger): def log_failure_event( self, kwargs: Mapping[str, object], response_obj: object, start_time: object, end_time: object ) -> None: - self._increment(kwargs, -1) + self._settle(kwargs) if self.test_flag: self.logged_failure += 1 @@ -144,7 +363,7 @@ class LeastBusyLoggingHandler(CustomLogger): async def async_log_success_event( self, kwargs: Mapping[str, object], response_obj: object, start_time: object, end_time: object ) -> None: - await self._async_increment(kwargs, -1) + await self._async_settle(kwargs) if self.test_flag: self.logged_success += 1 @@ -152,15 +371,20 @@ class LeastBusyLoggingHandler(CustomLogger): async def async_log_failure_event( self, kwargs: Mapping[str, object], response_obj: object, start_time: object, end_time: object ) -> None: - await self._async_increment(kwargs, -1) + await self._async_settle(kwargs) if self.test_flag: self.logged_failure += 1 @with_service_target("router_usage") def get_available_deployments( - self, model_group: str, healthy_deployments: Sequence[Mapping[str, object]] + self, + model_group: str, + healthy_deployments: Sequence[Mapping[str, object]], + reserve: bool = False, + call_id: str | None = None, ) -> Mapping[str, object] | None: - keys: Final = _request_count_keys(model_group, healthy_deployments) + deployment_ids: Final = _deployment_ids(healthy_deployments) + keys: Final = _request_count_keys(model_group, deployment_ids) redis_cache: Final = self.router_cache.redis_cache if redis_cache is not None: try: @@ -168,15 +392,19 @@ class LeastBusyLoggingHandler(CustomLogger): except Exception as e: _warn_unreadable(model_group, e) else: - return _least_busy(healthy_deployments, shared) - local: Final = _local_counts(self.router_cache.batch_get_cache(list(keys), local_only=True), keys) - return _least_busy(healthy_deployments, local) + return self._select(healthy_deployments, deployment_ids, keys, shared, reserve, call_id) + return self._select(healthy_deployments, deployment_ids, keys, None, reserve, call_id) @with_service_target("router_usage") async def async_get_available_deployments( - self, model_group: str, healthy_deployments: Sequence[Mapping[str, object]] + self, + model_group: str, + healthy_deployments: Sequence[Mapping[str, object]], + reserve: bool = False, + call_id: str | None = None, ) -> Mapping[str, object] | None: - keys: Final = _request_count_keys(model_group, healthy_deployments) + deployment_ids: Final = _deployment_ids(healthy_deployments) + keys: Final = _request_count_keys(model_group, deployment_ids) redis_cache: Final = self.router_cache.redis_cache if redis_cache is not None: try: @@ -184,42 +412,51 @@ class LeastBusyLoggingHandler(CustomLogger): except Exception as e: _warn_unreadable(model_group, e) else: - return _least_busy(healthy_deployments, shared) - local: Final = _local_counts(await self.router_cache.async_batch_get_cache(list(keys), local_only=True), keys) - return _least_busy(healthy_deployments, local) + return self._select(healthy_deployments, deployment_ids, keys, shared, reserve, call_id) + return self._select(healthy_deployments, deployment_ids, keys, None, reserve, call_id) - def _increment(self, kwargs: Mapping[str, object], delta: int) -> None: + def _settle(self, kwargs: Mapping[str, object]) -> None: ref: Final = _deployment_ref(kwargs) - if ref is None: + if ref is None or not self._end_attempt(ref, call_id_of(kwargs)): return - key: Final = _request_count_key(*ref) - redis_cache: Final = self.router_cache.redis_cache + self._count_shared(_request_count_key(*ref), -1) + + async def _async_settle(self, kwargs: Mapping[str, object]) -> None: + ref: Final = _deployment_ref(kwargs) + if ref is None or not self._end_attempt(ref, call_id_of(kwargs)): + return + await self._async_count_shared(_request_count_key(*ref), -1) + + def _this_workers_counts(self, keys: tuple[str, ...]) -> tuple[int, ...]: + return _local_counts(self.router_cache.batch_get_cache(list(keys), local_only=True), keys) + + def _at_least_this_workers(self, keys: tuple[str, ...], shared: tuple[int, ...]) -> tuple[int, ...]: + return tuple(max(counts) for counts in zip(shared, self._this_workers_counts(keys), strict=True)) + + def _count_locally(self, key: str, delta: int) -> None: try: local: Final = self.router_cache.increment_cache( key, delta, local_only=True, ttl=IN_FLIGHT_COUNT_TTL_SECONDS ) if local < 0: self.router_cache.set_cache(key, 0, local_only=True, ttl=IN_FLIGHT_COUNT_TTL_SECONDS) - if redis_cache is None: - return + except TypeError as e: + _warn_unwritable(key, e) + + def _count_shared(self, key: str, delta: int) -> None: + redis_cache: Final = self.router_cache.redis_cache + if redis_cache is None: + return + try: redis_cache.increment_with_floor(key, delta, IN_FLIGHT_COUNT_TTL_SECONDS) except Exception as e: _warn_unwritable(key, e) - async def _async_increment(self, kwargs: Mapping[str, object], delta: int) -> None: - ref: Final = _deployment_ref(kwargs) - if ref is None: - return - key: Final = _request_count_key(*ref) + async def _async_count_shared(self, key: str, delta: int) -> None: redis_cache: Final = self.router_cache.redis_cache + if redis_cache is None: + return try: - local: Final = await self.router_cache.async_increment_cache( - key, delta, local_only=True, ttl=IN_FLIGHT_COUNT_TTL_SECONDS - ) - if local is not None and local < 0: - await self.router_cache.async_set_cache(key, 0, local_only=True, ttl=IN_FLIGHT_COUNT_TTL_SECONDS) - if redis_cache is None: - return await redis_cache.async_increment_with_floor(key, delta, IN_FLIGHT_COUNT_TTL_SECONDS) except Exception as e: _warn_unwritable(key, e) diff --git a/litellm/router_strategy/lowest_cost.py b/litellm/router_strategy/lowest_cost.py index 3f0a5412b62..6a8757f6e6e 100644 --- a/litellm/router_strategy/lowest_cost.py +++ b/litellm/router_strategy/lowest_cost.py @@ -2,16 +2,22 @@ # picks based on response time (for streaming, this is time to first token) from collections.abc import Mapping from datetime import datetime +from functools import partial from typing import Final import litellm -from litellm import ModelResponse, token_counter, verbose_logger +from litellm import ModelResponse, verbose_logger from litellm._internal_context import with_service_target from litellm._logging import verbose_router_logger from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type -from litellm.litellm_core_utils.deployment_pricing import deployment_pricing_models, str_keyed +from litellm.litellm_core_utils.deployment_pricing import ( + deployment_backend_models, + deployment_pricing_models, + str_keyed, +) +from litellm.litellm_core_utils.token_counter import embedding_aware_token_count def _deployment_cost_map_rates(deployment: object) -> tuple[float | None, float | None]: @@ -235,7 +241,9 @@ class LowestCostLoggingHandler(CustomLogger): } try: - input_tokens = token_counter(messages=messages, text=input) + input_tokens = embedding_aware_token_count( + messages, input, partial(deployment_backend_models, healthy_deployments) + ) except Exception: input_tokens = 0 diff --git a/litellm/router_strategy/lowest_latency.py b/litellm/router_strategy/lowest_latency.py index c352934db6c..981fb5341dc 100644 --- a/litellm/router_strategy/lowest_latency.py +++ b/litellm/router_strategy/lowest_latency.py @@ -3,18 +3,21 @@ import random from collections.abc import Sequence from datetime import datetime, timedelta +from functools import partial from math import ceil, isfinite from typing import TYPE_CHECKING, Any, Final from pydantic import Field import litellm -from litellm import ModelResponse, token_counter, verbose_logger +from litellm import ModelResponse, verbose_logger from litellm._internal_context import with_service_target from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs, safe_divide_seconds +from litellm.litellm_core_utils.deployment_pricing import deployment_backend_models +from litellm.litellm_core_utils.token_counter import embedding_aware_token_count from litellm.responses.utils import ResponseAPILoggingUtils from litellm.types.llms.openai import ResponsesAPIResponse from litellm.types.utils import LiteLLMPydanticObjectBase @@ -439,7 +442,9 @@ class LowestLatencyLoggingHandler(CustomLogger): } try: - input_tokens = token_counter(messages=messages, text=input) + input_tokens = embedding_aware_token_count( + messages, input, partial(deployment_backend_models, healthy_deployments) + ) except Exception: input_tokens = 0 diff --git a/litellm/router_strategy/lowest_tpm_rpm.py b/litellm/router_strategy/lowest_tpm_rpm.py index 9636d7f009d..e9769c6f595 100644 --- a/litellm/router_strategy/lowest_tpm_rpm.py +++ b/litellm/router_strategy/lowest_tpm_rpm.py @@ -2,14 +2,16 @@ # identifies lowest tpm deployment import traceback from datetime import datetime +from functools import partial from typing import Final -from litellm import token_counter from litellm._internal_context import with_service_target from litellm._logging import verbose_router_logger from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type +from litellm.litellm_core_utils.deployment_pricing import deployment_backend_models +from litellm.litellm_core_utils.token_counter import embedding_aware_token_count from litellm.types.utils import LiteLLMPydanticObjectBase from litellm.utils import print_verbose @@ -174,7 +176,9 @@ class LowestTPMLoggingHandler(CustomLogger): verbose_router_logger.debug("tpm_key=%s, tpm_dict: %s, rpm_dict: %s", tpm_key, tpm_dict, rpm_dict) try: - input_tokens = token_counter(messages=messages, text=input) + input_tokens = embedding_aware_token_count( + messages, input, partial(deployment_backend_models, healthy_deployments) + ) except Exception: input_tokens = 0 verbose_router_logger.debug("input_tokens=%s", input_tokens) diff --git a/litellm/router_strategy/lowest_tpm_rpm_v2.py b/litellm/router_strategy/lowest_tpm_rpm_v2.py index 0719b30d36d..0574c3d7f69 100644 --- a/litellm/router_strategy/lowest_tpm_rpm_v2.py +++ b/litellm/router_strategy/lowest_tpm_rpm_v2.py @@ -5,18 +5,20 @@ from collections.abc import Iterator, Mapping, Sequence from contextlib import contextmanager from contextvars import ContextVar from dataclasses import dataclass +from functools import partial from typing import TYPE_CHECKING, Any, Final import httpx import litellm -from litellm import token_counter from litellm._internal_context import with_service_target from litellm._logging import verbose_logger, verbose_router_logger from litellm.caching.caching import DualCache from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.batch_utils import is_batch_retrieve_call_type from litellm.litellm_core_utils.core_helpers import get_parent_otel_span_from_kwargs +from litellm.litellm_core_utils.deployment_pricing import deployment_backend_models +from litellm.litellm_core_utils.token_counter import embedding_aware_token_count from litellm.types.router import RouterErrors from litellm.types.utils import LiteLLMPydanticObjectBase, StandardLoggingPayload from litellm.utils import get_utc_datetime, print_verbose @@ -422,7 +424,9 @@ class LowestTPMLoggingHandler_v2(BaseRoutingStrategy, CustomLogger): rpm_dict[rpm_keys[idx].split(":")[0]] = rpm_values[idx] try: - input_tokens = token_counter(messages=messages, text=input) + input_tokens = embedding_aware_token_count( + messages, input, partial(deployment_backend_models, healthy_deployments) + ) except Exception: input_tokens = 0 verbose_router_logger.debug("input_tokens=%s", input_tokens) diff --git a/litellm/router_utils/client_initalization_utils.py b/litellm/router_utils/client_initalization_utils.py index fdcead4a6b9..b7bb6d80ad4 100644 --- a/litellm/router_utils/client_initalization_utils.py +++ b/litellm/router_utils/client_initalization_utils.py @@ -50,7 +50,7 @@ class MaxParallelRequestsLimit: class InitalizeCachedClient: @staticmethod @renamed_router_param("litellm_router_instance") - def set_max_parallel_requests_client(ctx: "RoutingContext", model: dict): + def set_max_parallel_requests_client(ctx: "RoutingContext", model: dict) -> None: litellm_params: Final = model.get("litellm_params", {}) model_id: Final = model["model_info"]["id"] rpm: Final = litellm_params.get("rpm", None) diff --git a/litellm/router_utils/cooldown_handlers.py b/litellm/router_utils/cooldown_handlers.py index e50d5bb47a6..03485ebd5f8 100644 --- a/litellm/router_utils/cooldown_handlers.py +++ b/litellm/router_utils/cooldown_handlers.py @@ -125,12 +125,13 @@ _EXCEPTION_POLICY_FIELDS: Final[tuple[tuple[type, str], ...]] = ( def _first_present(*sources: Mapping[str, Any] | None, key: str) -> int | float | None: """Return *key* from the first source mapping where it's set, so callers can support a setting living in more than one deployment config location. Sources - are checked in order from most to least specific to that setting.""" + are checked in order from most to least specific to that setting. Only a number + counts: a bool or a string is skipped, so the router default applies.""" for source in sources: if source is None: continue value = source.get(key) - if value is not None: + if isinstance(value, int | float) and not isinstance(value, bool): return value return None @@ -811,7 +812,7 @@ def _is_allowed_fails_set_on_router( return False -def cast_exception_status_to_int(exception_status: str | int) -> int: +def cast_exception_status_to_int(exception_status: object) -> int: if isinstance(exception_status, str): try: exception_status = int(exception_status) @@ -820,6 +821,13 @@ def cast_exception_status_to_int(exception_status: str | int) -> int: "Unable to cast exception status to int %s. Defaulting to status=500.", exception_status ) exception_status = 500 + # A bool or a number no HTTP status can be is read as a 500, as the Rust router core reads it. + if ( + isinstance(exception_status, bool) + or not isinstance(exception_status, int) + or not 0 <= exception_status <= 65535 + ): + return 500 return exception_status @@ -847,6 +855,45 @@ def is_stream_stall(exception: BaseException) -> bool: return isinstance(exception, litellm.Timeout) and isinstance(exception.__cause__, MidStreamFallbackError) +def is_caller_entra_credential_failure( + deployment: Deployment | None, + router_defaults: Mapping[str, object], + model_call_details: Mapping[str, object], + exception_status: str | int, + exception: BaseException, +) -> bool: + if cast_exception_status_to_int(exception_status) != 401 or deployment is None: + return False + + from litellm.llms.azure.common_utils import caused_by_entra_rejection + + if not caused_by_entra_rejection(exception): + return False + from litellm.llms.azure_ai.common_utils import AZURE_ENTRA_LITELLM_PARAM_KEYS, azure_entra_environment_defaults + + call_params: Final = _CREDENTIAL_VALUES_ADAPTER.validate_python(model_call_details.get("litellm_params") or {}) + + credential_name: Final = deployment.litellm_params.litellm_credential_name + configured_by_precedence: Final[tuple[Mapping[str, object], ...]] = ( + router_defaults, + _CREDENTIAL_VALUES_ADAPTER.validate_python(deployment.litellm_params.model_dump(exclude_none=True)), + _CREDENTIAL_VALUES_ADAPTER.validate_python( + CredentialAccessor.get_credential_values(credential_name) if credential_name is not None else {} + ), + ) + environment: Final = azure_entra_environment_defaults() + return any( + call_params.get(key) is not None + and (call_params.get(key) or environment.get(key)) + != (_first_configured(configured_by_precedence, key) or environment.get(key)) + for key in AZURE_ENTRA_LITELLM_PARAM_KEYS + ) + + +def _first_configured(sources: tuple[Mapping[str, object], ...], key: str) -> object: + return next((value for source in sources if (value := source.get(key)) is not None), None) + + def is_caller_scoped_auth_failure(deployment: Deployment | None, exception_status: str | int) -> bool: if cast_exception_status_to_int(exception_status) not in (401, 403) or deployment is None: return False diff --git a/litellm/router_utils/deployment_numbers.py b/litellm/router_utils/deployment_numbers.py new file mode 100644 index 00000000000..7cee96f6a64 --- /dev/null +++ b/litellm/router_utils/deployment_numbers.py @@ -0,0 +1,90 @@ +# pyright: reportUnknownVariableType=false, reportUnknownArgumentType=false +"""Numbers a router deployment cannot be served with, refused the same way by both router cores. + +A whole number wider than 64 bits (a `ptu_shares` of `1e20`) does not fit the router's JSON +deployment record, and an infinite or NaN cost would read back as null there, so the call +would silently be priced from the model cost map. Both are refused when the deployment is +built or added, with the error naming the field. +""" + +import math +import re +from collections.abc import Iterator, Mapping +from typing import Final + +from litellm.litellm_core_utils.core_helpers import as_str_mapping + +# The whole numbers a deployment record holds (serde_json's i64 and u64). +SMALLEST_NUMBER: Final = -(2**63) +LARGEST_NUMBER: Final = 2**64 - 1 +# A pricing field: `input_cost_per_token`, `cache_read_input_token_cost`, ... +_COST_FIELD: Final = re.compile(r"cost_per|_cost$") + + +def _reads_as_non_finite(value: object) -> bool: + """Whether a cost, as written, is an infinity or a NaN (``float()`` reads ``"inf"`` and ``"1e400"``).""" + if isinstance(value, float): + return not math.isfinite(value) + if not isinstance(value, str): + return False + try: + return not math.isfinite(float(value)) + except ValueError: + return False + + +def _is_cost(key: object) -> bool: + return isinstance(key, str) and _COST_FIELD.search(key) is not None + + +def _number_leaves(value: object) -> Iterator[tuple[str, object, bool]]: + """Every value under ``value`` that is no container, in order: its path, and whether it sits in a + cost field. Each container is walked once, so an entry that holds itself ends.""" + pending: Final[list[tuple[object, str, bool]]] = [(value, "", False)] # mutable-ok: the walk's work list + walked: Final[set[int]] = set() # mutable-ok: the ids walked so far + while pending: + current, path, cost = pending.pop() + if not isinstance(current, Mapping | list | tuple): + yield path, current, cost + elif id(current) not in walked: + walked.add(id(current)) + pending.extend( + reversed( + [(item, f"{path}.{key}".removeprefix("."), cost or _is_cost(key)) for key, item in current.items()] + if isinstance(current, Mapping) + else [(item, f"{path}[{index}]", cost) for index, item in enumerate(current)] + ) + ) + + +def _refusal(entry: Mapping[str, object], reason: str) -> ValueError: + return ValueError(f"Deployment {entry.get('model_name')!r} cannot be served: {reason}") + + +def refuse_wide_numbers(entry: object) -> None: + """Refuse a deployment holding a whole number wider than 64 bits, by name.""" + deployment: Final = as_str_mapping(entry) + if deployment is None: + return + for path, value, _ in _number_leaves(deployment): + if isinstance(value, int) and not SMALLEST_NUMBER <= value <= LARGEST_NUMBER: + raise _refusal( + deployment, + f"{path} is {value}, outside what the router can hold " + f"({SMALLEST_NUMBER} to {LARGEST_NUMBER}). Use a smaller value.", + ) + + +def refuse_unservable_numbers(entry: object) -> None: + """``refuse_wide_numbers``, and a deployment with an infinite or NaN cost.""" + refuse_wide_numbers(entry) + deployment: Final = as_str_mapping(entry) + if deployment is None: + return + for path, value, cost in _number_leaves(deployment): + if cost and _reads_as_non_finite(value): + raise _refusal( + deployment, + f"{path} is {value!r}, and the router only prices with finite costs. " + "Set a finite cost, or remove it to use the model cost map's price.", + ) diff --git a/litellm/router_utils/endpoint_eligibility.py b/litellm/router_utils/endpoint_eligibility.py index 4a87e582c97..7f58c138bba 100644 --- a/litellm/router_utils/endpoint_eligibility.py +++ b/litellm/router_utils/endpoint_eligibility.py @@ -57,10 +57,14 @@ class _EndpointDeclaration(BaseModel): return (value,) if isinstance(value, str) else value +def endpoint_for_call(call_type: object, module: object = None) -> str | None: + qualified_call: Final = f"{module}.{call_type}" if module == "litellm.interactions.main" else call_type + return CHAT_ENDPOINT_BY_CALL.get(qualified_call) if isinstance(qualified_call, str) else None + + @contextmanager def endpoint_selection(call_type: object, module: object = None, model: object = None) -> Generator[None]: - qualified_call: Final = f"{module}.{call_type}" if module == "litellm.interactions.main" else call_type - endpoint: Final = CHAT_ENDPOINT_BY_CALL.get(qualified_call) if isinstance(qualified_call, str) else None + endpoint: Final = endpoint_for_call(call_type, module) token: Final = _REQUEST_SELECTION.set((endpoint, model if isinstance(model, str) else None)) try: yield @@ -68,6 +72,10 @@ def endpoint_selection(call_type: object, module: object = None, model: object = _REQUEST_SELECTION.reset(token) +def selected_endpoint() -> str | None: + return _REQUEST_SELECTION.get()[0] + + def _enforced_endpoints(model_info: object) -> tuple[str, ...] | None: try: declaration: Final = _EndpointDeclaration.model_validate(model_info) diff --git a/litellm/router_utils/fallback_event_handlers.py b/litellm/router_utils/fallback_event_handlers.py index c929cca44be..20f9e114747 100644 --- a/litellm/router_utils/fallback_event_handlers.py +++ b/litellm/router_utils/fallback_event_handlers.py @@ -28,6 +28,7 @@ from litellm.router_utils.cooldown_handlers import ( _first_present, # pyright: ignore[reportPrivateUsage] - shared internal helper, used across router_utils cast_exception_status_to_int, is_advisor_orchestration_failure, + is_caller_entra_credential_failure, is_caller_scoped_auth_failure, is_caller_timeout_408, is_stream_stall, @@ -132,6 +133,14 @@ def _trigger_cooldown_for_failed_deployment( deployment_id, ) return + if is_caller_entra_credential_failure( + deployment, ctx.default_litellm_params(), model_call_details, exception_status, exception + ): + verbose_router_logger.debug( + "Not triggering cooldown for fallback deployment %s: Entra ID rejected a credential the caller sent.", + deployment_id, + ) + return # Priority: deployment config > response header > router default, matching # Router.deployment_callback_on_failure's precedence for the primary path. @@ -623,6 +632,8 @@ def get_fallback_model_group( ## check for specific model group-specific fallbacks for idx, item in enumerate(fallbacks): if isinstance(item, dict): + if not item: + continue # an empty entry names no group: the next entries still apply fallback_key = next(iter(item)) if fallback_key == model_group: # check exact match fallback_model_group = item[model_group] diff --git a/litellm/router_utils/global_callback_holders.py b/litellm/router_utils/global_callback_holders.py new file mode 100644 index 00000000000..53a7c20cff3 --- /dev/null +++ b/litellm/router_utils/global_callback_holders.py @@ -0,0 +1,53 @@ +""" +The routers of this process that hold optional pre-call checks and routing callbacks, whatever core +serves them. + +A router that retires hands the checks it vacates in its host's ``callbacks`` list to a surviving +router's same-keyed check (``routers_holding_global_callbacks``), and a router that drops a check at +runtime keeps it registered while another live router still has one of that type +(``live_check_owners``). Both rules look at every router in the process, so the sets live here, +outside any one router core. + +A member of ``routers_holding_global_callbacks`` serves ``_global_callback_candidates()``, +``_core_adaptive_routers`` and ``_sync_adaptive_router_hooks()``; a member of ``live_check_owners`` +serves ``optional_callbacks``. +""" + +import threading +import weakref +from collections.abc import Mapping, Sequence +from typing import TYPE_CHECKING, Final, Protocol + +if TYPE_CHECKING: + from litellm.integrations.custom_logger import CustomLogger + + +class GlobalCallbackHolder(Protocol): + """A router whose callbacks a retiring router may hand its vacated checks to.""" + + @property + def _core_adaptive_routers(self) -> Mapping[str, object]: ... + + def _global_callback_candidates(self) -> "tuple[CustomLogger, ...]": ... + + def _sync_adaptive_router_hooks(self) -> None: ... + + +class CheckOwner(Protocol): + """A live router with optional pre-call checks.""" + + @property + def optional_callbacks(self) -> "Sequence[object] | None": ... + + +routers_holding_global_callbacks: Final["weakref.WeakSet[GlobalCallbackHolder]"] = weakref.WeakSet() +routers_holding_global_callbacks_lock: Final = threading.Lock() +live_check_owners: Final["weakref.WeakSet[CheckOwner]"] = weakref.WeakSet() + +__all__ = [ + "CheckOwner", + "GlobalCallbackHolder", + "live_check_owners", + "routers_holding_global_callbacks", + "routers_holding_global_callbacks_lock", +] diff --git a/litellm/router_utils/health_state_cache.py b/litellm/router_utils/health_state_cache.py index c759af8fdb8..1c9cb10a48b 100644 --- a/litellm/router_utils/health_state_cache.py +++ b/litellm/router_utils/health_state_cache.py @@ -6,6 +6,7 @@ and exposes it for router candidate filtering. """ import time +from collections.abc import Mapping from typing import TYPE_CHECKING, Any, Final from typing_extensions import TypedDict @@ -78,7 +79,7 @@ class DeploymentHealthCache: merged: Final = { model_id: state for model_id, state in {**existing, **states}.items() - if isinstance(state, dict) and (now - state.get("timestamp", 0)) < expiry_seconds + if isinstance(state, dict) and (now - _timestamp_of(state)) < expiry_seconds # pyright: ignore[reportUnknownArgumentType] # a cached record } self.cache.set_cache( key=self.CACHE_KEY, @@ -101,7 +102,7 @@ class DeploymentHealthCache: for model_id, state in raw.items() if isinstance(state, dict) and not state.get("is_healthy", True) - and (now - state.get("timestamp", 0)) < self.staleness_threshold + and (now - _timestamp_of(state)) < self.staleness_threshold # pyright: ignore[reportUnknownArgumentType] # a cached record } @with_service_target(HEALTH_CHECKS_TARGET) @@ -129,3 +130,10 @@ class DeploymentHealthCache: str(e), ) return set() + + +def _timestamp_of(state: Mapping[str, object]) -> float: + """A health record's timestamp; one that is no number reads as 0 (stale), so a bad record + drops out alone instead of turning health routing off for every deployment.""" + timestamp: Final = state.get("timestamp", 0) + return float(timestamp) if isinstance(timestamp, int | float) and not isinstance(timestamp, bool) else 0.0 diff --git a/litellm/router_utils/pre_call_checks/encrypted_content_affinity_check.py b/litellm/router_utils/pre_call_checks/encrypted_content_affinity_check.py index 6f3f0794371..f3425596afa 100644 --- a/litellm/router_utils/pre_call_checks/encrypted_content_affinity_check.py +++ b/litellm/router_utils/pre_call_checks/encrypted_content_affinity_check.py @@ -36,31 +36,75 @@ Safe to enable globally: - No cache required. """ -from collections.abc import Iterator, Mapping, Sequence -from functools import cache +import hashlib +from collections.abc import Callable, Iterator, Mapping, Sequence +from dataclasses import dataclass, field +from functools import cache, lru_cache, partial +from time import monotonic from typing import TYPE_CHECKING, Final, Optional, cast -from pydantic import TypeAdapter +from pydantic import BaseModel, TypeAdapter, ValidationError +import litellm from litellm._logging import verbose_router_logger +from litellm.exceptions import AuthenticationError, BadRequestError from litellm.integrations.custom_logger import CustomLogger, Span -from litellm.litellm_core_utils.credential_accessor import CredentialAccessor +from litellm.litellm_core_utils.get_llm_provider_logic import declared_provider, get_llm_provider +from litellm.litellm_core_utils.litellm_logging import has_sensitive_keyword from litellm.litellm_core_utils.prompt_templates.common_utils import ( anthropic_content_lists, encrypted_content_of_block, strip_encrypted_reasoning_from_messages, ) from litellm.litellm_core_utils.routing_common_utils import as_excluded_deployment_ids, as_retry_skipped_deployment_ids +from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.router_deprecated import RenamedRouterAttribute, renamed_router_param +from litellm.secret_managers.main import secret_manager_would_be_consulted from litellm.types.llms.openai import AllMessageValues -from litellm.types.router import Deployment -from litellm.utils import get_order_filtered_deployments +from litellm.types.router import Deployment, GenericLiteLLMParams +from litellm.types.utils import LlmProviders +from litellm.utils import ProviderConfigManager, get_order_filtered_deployments, with_named_credential if TYPE_CHECKING: from litellm.router_api import RoutingContext _REQUEST_KWARGS_ADAPTER: Final = TypeAdapter(Mapping[str, object]) +_HEADERS_ADAPTER: Final = TypeAdapter(Mapping[object, object]) +_ACCOUNT_SCOPE_HEADERS: Final = frozenset({"openai-organization", "openai-project", "cookie"}) +_SINGLE_VENDOR_PROVIDERS: Final = frozenset({LlmProviders.OPENAI.value}) +_DEFAULT_ROUTE_SECRETS: Final = ("USE_LITELLM_PROXY", "OPENAI_API_KEY", "OPENAI_BASE_URL", "OPENAI_API_BASE") +_SECRET_MANAGER_REFRESH_SECONDS: Final = 60 + + +@dataclass(frozen=True, slots=True) +class _ProviderRoute: + model: str + provider: str + api_base: str | None + + +@dataclass(frozen=True, slots=True) +class _EncryptionBoundary: + api_base: object + api_key: object + model: Callable[[], str | None] = field(compare=False) + account_scope: frozenset[tuple[str, object]] + explicit_pair: bool + + def is_shared_with(self, other: "_EncryptionBoundary") -> bool: + if (self.api_base, self.api_key) != (other.api_base, other.api_key): + return False + if self.explicit_pair and other.explicit_pair: + return True + return self.account_scope == other.account_scope and self.model() == other.model() + + +@dataclass(frozen=True, slots=True) +class _ParamsInRefreshWindow: + digest: str + window: int + params: Mapping[str, object] = field(compare=False) class EncryptedContentAffinityCheck(CustomLogger): @@ -83,9 +127,11 @@ class EncryptedContentAffinityCheck(CustomLogger): ctx: Optional["RoutingContext"] = None, enable_global_affinity: bool = True, model_group_affinity_config: dict[str, list[str]] | None = None, + clock: Callable[[], float] = monotonic, ) -> None: super().__init__() self.ctx = ctx + self._clock = clock self.enable_global_affinity = enable_global_affinity self.model_group_affinity_config: dict[str, list[str]] = model_group_affinity_config or {} @@ -209,44 +255,156 @@ class EncryptedContentAffinityCheck(CustomLogger): @staticmethod def _encryption_boundary_key( litellm_params: object, - ) -> tuple[object, object] | None: + clock: Callable[[], float] = monotonic, + ) -> _EncryptionBoundary | None: """ - ``(api_base, api_key)`` identifies an upstream encryption boundary. - The values are resolved from the deployment and its named credential - without modifying the deployment. + The upstream encryption boundary a deployment's encrypted reasoning belongs to. The values + are resolved the way the request resolves them, the deployment's own values winning over its + named credential's, without modifying the deployment. Two explicit ``(api_base, api_key)`` + pairs match on those values alone. On a provider that serves one vendor's models, a deployment + with no ``api_key`` takes the provider's default key, one with no ``api_base`` takes the endpoint + its Responses URL builder resolves, and a match involving either also needs the same model and + the same headers that pick an account. - Accepts any object exposing dict-style ``.get(key, default)``: plain - dicts (the common case in ``healthy_deployments``) as well as - ``LiteLLM_Params``-style Pydantic instances, which define a custom - ``.get()``. A stricter ``isinstance(dict)`` guard would silently drop - the latter from boundary matching and fall back to the full pool — - i.e. trigger the exact ``invalid_encrypted_content`` failure this - check exists to prevent. + Accepts plain dicts (the common case in ``healthy_deployments``) as + well as ``LiteLLM_Params`` Pydantic instances. A stricter + ``isinstance(dict)`` guard would silently drop the latter from + boundary matching and fall back to the full pool — i.e. trigger the + exact ``invalid_encrypted_content`` failure this check exists to prevent. + + When a secret manager would be asked for the provider defaults, the boundary of one set of + deployment and named credential values is reused for up to a minute, so a run of pin misses + does not ask it again for every candidate, while a changed credential resolves at once. """ - getter: Final = getattr(litellm_params, "get", None) - if not callable(getter): + params: Final = EncryptedContentAffinityCheck._params_mapping(litellm_params) + if params is None: return None - api_base: Final = getter("api_base") - api_key: Final = getter("api_key") - credential_name: Final = getter("litellm_credential_name") - credential_values: Final[Mapping[str, object] | None] = ( - CredentialAccessor.get_credential_values(credential_name) - if isinstance(credential_name, str) and credential_name - else None + effective_params: Final = with_named_credential(params) + if not any(secret_manager_would_be_consulted(name) for name in _DEFAULT_ROUTE_SECRETS): + return EncryptedContentAffinityCheck._resolve_encryption_boundary(effective_params) + return EncryptedContentAffinityCheck._encryption_boundary_in_refresh_window( + _ParamsInRefreshWindow( + hashlib.sha256(repr(effective_params).encode()).hexdigest(), + int(clock() // _SECRET_MANAGER_REFRESH_SECONDS), + effective_params, + ) ) - effective_api_base: Final = ( - credential_values.get("api_base") - if credential_values is not None and "api_base" in credential_values - else api_base - ) - effective_api_key: Final = ( - credential_values.get("api_key") - if credential_values is not None and "api_key" in credential_values - else api_key - ) - if not effective_api_base or not effective_api_key: + + @staticmethod + @lru_cache(maxsize=1024) + def _encryption_boundary_in_refresh_window(key: _ParamsInRefreshWindow) -> _EncryptionBoundary | None: + return EncryptedContentAffinityCheck._resolve_encryption_boundary(key.params) + + @staticmethod + def _resolve_encryption_boundary(effective_params: Mapping[str, object]) -> _EncryptionBoundary | None: + explicit_api_key: Final = effective_params.get("api_key") + explicit_api_base: Final = effective_params.get("api_base") + account_scope: Final = EncryptedContentAffinityCheck._account_scope(effective_params) + if explicit_api_key and explicit_api_base: + return _EncryptionBoundary( + explicit_api_base, + explicit_api_key, + cache(partial(EncryptedContentAffinityCheck._single_vendor_model, effective_params)), + account_scope, + explicit_pair=True, + ) + route: Final = EncryptedContentAffinityCheck._single_vendor_route(effective_params) + if route is None: + return None + api_key: Final = explicit_api_key or EncryptedContentAffinityCheck._default_api_key(route) + if not api_key: + return None + api_base: Final = explicit_api_base or EncryptedContentAffinityCheck._default_responses_endpoint( + route, effective_params + ) + if not api_base: + return None + return _EncryptionBoundary(api_base, api_key, lambda: route.model, account_scope, explicit_pair=False) + + @staticmethod + def _params_mapping(litellm_params: object) -> Mapping[str, object] | None: + if isinstance(litellm_params, BaseModel): + return litellm_params.model_dump(exclude_none=True) + if isinstance(litellm_params, Mapping): + return _REQUEST_KWARGS_ADAPTER.validate_python(litellm_params) + return None + + @staticmethod + def _account_scope(litellm_params: Mapping[str, object]) -> frozenset[tuple[str, object]]: + return frozenset( + (name.lower(), str(value)) + for name, value in EncryptedContentAffinityCheck._header_items(litellm_params) + if name.lower() in _ACCOUNT_SCOPE_HEADERS or has_sensitive_keyword(name) + ) + + @staticmethod + def _header_items(litellm_params: Mapping[str, object]) -> Iterator[tuple[str, object]]: + headers: Final = EncryptedContentAffinityCheck._header_mapping(litellm_params.get("headers")) + extra_headers: Final = EncryptedContentAffinityCheck._header_mapping(litellm_params.get("extra_headers")) + overridden: Final = frozenset(name.lower() for name in extra_headers) + yield from ((name, value) for name, value in headers.items() if name.lower() not in overridden) + yield from extra_headers.items() + + @staticmethod + def _header_mapping(headers: object) -> Mapping[str, object]: + if isinstance(headers, Mapping): + return {str(name): value for name, value in _HEADERS_ADAPTER.validate_python(headers).items()} + return {} + + @staticmethod + def _single_vendor_route(litellm_params: Mapping[str, object]) -> _ProviderRoute | None: + route: Final = EncryptedContentAffinityCheck._provider_route(litellm_params) + return route if route is not None and route.provider in _SINGLE_VENDOR_PROVIDERS else None + + @staticmethod + def _single_vendor_model(litellm_params: Mapping[str, object]) -> str | None: + route: Final = EncryptedContentAffinityCheck._single_vendor_route(litellm_params) + return route.model if route is not None else None + + @staticmethod + def _provider_route(litellm_params: Mapping[str, object]) -> _ProviderRoute | None: + model: Final = litellm_params.get("model") + if not isinstance(model, str): + return None + custom_llm_provider: Final = litellm_params.get("custom_llm_provider") + declared: Final = declared_provider( + model, custom_llm_provider if isinstance(custom_llm_provider, str) else None + ) + if declared in litellm.provider_list and declared not in _SINGLE_VENDOR_PROVIDERS: + return None + try: + provider_model, provider, _, provider_api_base = get_llm_provider( + model=model, litellm_params=GenericLiteLLMParams.model_validate(dict(litellm_params)) + ) + except (BadRequestError, ValidationError): + return None + return _ProviderRoute(provider_model, provider, provider_api_base) + + @staticmethod + def _default_api_key(route: _ProviderRoute) -> str | None: + model_info: Final = ProviderConfigManager.get_provider_model_info( + model=route.model, provider=LlmProviders(route.provider) + ) + if model_info is None: + return None + try: + return model_info.get_api_key() + except NotImplementedError: + return None + + @staticmethod + def _default_responses_endpoint(route: _ProviderRoute, litellm_params: Mapping[str, object]) -> str | None: + responses_config: Final = ProviderConfigManager.get_provider_responses_api_config( + provider=route.provider, model=route.model + ) + if responses_config is None: + return None + try: + return responses_config.get_complete_url( # pyright: ignore[reportUnknownMemberType] # the base types litellm_params as a bare dict + api_base=route.api_base, litellm_params=dict(litellm_params) + ) + except (ValueError, BaseLLMException, AuthenticationError): return None - return (effective_api_base, effective_api_key) def _find_deployments_on_same_encryption_boundary( self, @@ -255,7 +413,7 @@ class EncryptedContentAffinityCheck(CustomLogger): ) -> tuple[list[dict], Deployment | None]: """ Deployments in ``healthy_deployments`` sharing the originating - deployment's ``(api_base, api_key)``, alongside the originating + deployment's encryption boundary, alongside the originating deployment object (or ``None`` if it was removed / router unavailable). """ if self.ctx is None: @@ -263,11 +421,16 @@ class EncryptedContentAffinityCheck(CustomLogger): originating: Final = self.ctx.registry().deployment(model_id) if originating is None: return [], None - boundary: Final = self._encryption_boundary_key(originating.litellm_params.model_dump(exclude_none=True)) + boundary: Final = self._encryption_boundary_key( + originating.litellm_params.model_dump(exclude_none=True), self._clock + ) if boundary is None: return [], originating matches: Final = [ - d for d in healthy_deployments if self._encryption_boundary_key(d.get("litellm_params", {})) == boundary + d + for d in healthy_deployments + if (candidate := self._encryption_boundary_key(d.get("litellm_params", {}), self._clock)) is not None + and boundary.is_shared_with(candidate) ] return matches, originating @@ -280,6 +443,7 @@ class EncryptedContentAffinityCheck(CustomLogger): target_deployments: Sequence[Mapping[str, object]], *, unmarked_origin: str | None, + clock: Callable[[], float] = monotonic, ) -> None: """ Drop the encrypted reasoning that none of ``target_deployments`` minted or shares an @@ -293,12 +457,19 @@ class EncryptedContentAffinityCheck(CustomLogger): for target in target_deployments if isinstance((model_info := target.get("model_info")), Mapping) and model_info.get("id") is not None ) - target_boundaries: Final = frozenset( - boundary - for target in target_deployments - if (boundary := EncryptedContentAffinityCheck._encryption_boundary_key(target.get("litellm_params"))) - is not None - ) + + @cache + def target_boundaries() -> tuple[_EncryptionBoundary, ...]: + return tuple( + boundary + for target in target_deployments + if ( + boundary := EncryptedContentAffinityCheck._encryption_boundary_key( + target.get("litellm_params"), clock + ) + ) + is not None + ) @cache def target_can_decrypt(marked_origin: str | None) -> bool: @@ -312,12 +483,14 @@ class EncryptedContentAffinityCheck(CustomLogger): origin: Final = ctx.registry().deployment(origin_model_id) origin_boundary: Final = ( EncryptedContentAffinityCheck._encryption_boundary_key( - origin.litellm_params.model_dump(exclude_none=True) + origin.litellm_params.model_dump(exclude_none=True), clock ) if origin is not None else None ) - return origin_boundary is not None and origin_boundary in target_boundaries + return origin_boundary is not None and any( + origin_boundary.is_shared_with(target_boundary) for target_boundary in target_boundaries() + ) def should_strip_input_item(item: Mapping[str, object]) -> bool: return not target_can_decrypt(EncryptedContentAffinityCheck._model_id_of_input_item(item)) @@ -424,7 +597,12 @@ class EncryptedContentAffinityCheck(CustomLogger): ) request_kwargs["_encrypted_content_affinity_pinned"] = True self.strip_reasoning_the_targets_cannot_decrypt( - self.ctx, request_input, anthropic_messages, (deployment,), unmarked_origin=model_id + self.ctx, + request_input, + anthropic_messages, + (deployment,), + unmarked_origin=model_id, + clock=self._clock, ) return [deployment] @@ -442,7 +620,12 @@ class EncryptedContentAffinityCheck(CustomLogger): ) request_kwargs["_encrypted_content_affinity_pinned"] = True self.strip_reasoning_the_targets_cannot_decrypt( - self.ctx, request_input, anthropic_messages, boundary_matches, unmarked_origin=model_id + self.ctx, + request_input, + anthropic_messages, + boundary_matches, + unmarked_origin=model_id, + clock=self._clock, ) return boundary_matches diff --git a/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py b/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py index 80e1f3fe29c..f887c4551f2 100644 --- a/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py +++ b/litellm/router_utils/pre_call_checks/io_token_rate_limit_check.py @@ -20,6 +20,7 @@ from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final import httpx +from pydantic import TypeAdapter import litellm from litellm import token_counter @@ -28,6 +29,7 @@ from litellm._logging import verbose_router_logger from litellm.caching.dual_cache import DualCache from litellm.caching.redis_cache import RedisCache, RedisCircuitBreakerOpenError from litellm.constants import NO_MAX_TOKENS_TPM_RESERVATION_FRACTION +from litellm.litellm_core_utils.core_helpers import coerce_token_limit from litellm.litellm_core_utils.internal_call_metadata import ( IO_TOKEN_RESERVATION_KEYS, ITPM_CACHE_KEY, @@ -41,6 +43,8 @@ from litellm.router_utils.routing_read_batch import ROUTER_USAGE_TARGET from litellm.types.router import RouterCacheEnum, RouterErrors from litellm.utils import get_utc_datetime +_MODEL_INFO_ADAPTER: Final[TypeAdapter[Mapping[str, object]]] = TypeAdapter(Mapping[str, object]) + if TYPE_CHECKING: from opentelemetry.trace import Span as _Span @@ -227,8 +231,20 @@ def _deployment_output_cap(request_kwargs: Mapping[str, object] | None, deployme ) -def _default_otpm_reservation(model_name: str, otpm_limit: int) -> int: - model_max: Final = _model_max_output_tokens(model_name) if model_name else None +def _default_otpm_reservation(deployment: Mapping[str, object], model_name: str, otpm_limit: int) -> int: + model_info: Final[object] = deployment.get("model_info") + configured_model_max: Final = ( + coerce_token_limit(_MODEL_INFO_ADAPTER.validate_python(model_info).get("max_output_tokens")) + if isinstance(model_info, Mapping) + else None + ) + model_max: Final = ( + max(0, configured_model_max) + if configured_model_max is not None + else _model_max_output_tokens(model_name) + if model_name + else None + ) share_of_limit: Final = max(1, int(otpm_limit * NO_MAX_TOKENS_TPM_RESERVATION_FRACTION)) return min(4096 if model_max is None else model_max, share_of_limit) @@ -242,7 +258,7 @@ def _otpm_reservation( from_request: Final = _explicit_max_tokens(request_kwargs) if from_request is not None: return from_request - default: Final = _default_otpm_reservation(model_name, otpm_limit) + default: Final = _default_otpm_reservation(deployment, model_name, otpm_limit) from_deployment: Final = _deployment_output_cap(request_kwargs, deployment) return default if from_deployment is None else min(from_deployment, default) diff --git a/litellm/router_utils/pre_call_checks/model_rate_limit_check.py b/litellm/router_utils/pre_call_checks/model_rate_limit_check.py index f41d19cd62c..a3da0ae1674 100644 --- a/litellm/router_utils/pre_call_checks/model_rate_limit_check.py +++ b/litellm/router_utils/pre_call_checks/model_rate_limit_check.py @@ -134,7 +134,7 @@ class ModelRateLimitingCheck(CustomLogger): this check actively enforces those limits across ALL routing strategies. """ - def __init__(self, dual_cache: DualCache, clock: Callable[[], datetime] = get_utc_datetime): + def __init__(self, dual_cache: DualCache, clock: Callable[[], datetime] = get_utc_datetime) -> None: self.dual_cache = dual_cache self.clock = clock # model_ids already warned about itpm/otpm + tpm/rpm on the same deployment, diff --git a/litellm/router_utils/prompt_caching_cache.py b/litellm/router_utils/prompt_caching_cache.py index f78b5982186..1d91255e28c 100644 --- a/litellm/router_utils/prompt_caching_cache.py +++ b/litellm/router_utils/prompt_caching_cache.py @@ -55,6 +55,17 @@ def _sorted_pairs(pairs: Iterable[tuple[str, JsonValue]]) -> tuple[tuple[str, Js return tuple(sorted(pairs, key=lambda pair: pair[0])) +_CACHE_MARKER_KEYS: Final = frozenset(("cache_control", "prompt_cache_breakpoint")) + + +def _is_cache_marked(block: Mapping[str, object]) -> bool: + match block: + case {"cache_control": {"type": "ephemeral"}}: + return True + case _: + return block.get("prompt_cache_breakpoint") is not None + + def _canonical_bytes(value: object) -> bytes: return json.dumps(value, sort_keys=True, separators=(",", ":")).encode() @@ -66,7 +77,7 @@ def _block_unit( return _canonical_bytes((envelope, block)), message_run_type block_type: Final = block.get("type") block_run_type: Final = block_type if isinstance(block_type, str) and block_type in _TOOL_RUN_BLOCK_TYPES else None - stripped: Final = _sorted_pairs(item for item in block.items() if item[0] != "cache_control") + stripped: Final = _sorted_pairs(item for item in block.items() if item[0] not in _CACHE_MARKER_KEYS) return _canonical_bytes((envelope, stripped)), message_run_type or block_run_type @@ -264,15 +275,9 @@ class PromptCachingCache: continue for content_idx, content_block in enumerate(content): - if isinstance(content_block, dict): - cache_control = content_block.get("cache_control") - if ( - cache_control is not None - and isinstance(cache_control, dict) - and cache_control.get("type") == "ephemeral" - ): - last_cacheable_message_idx = msg_idx - last_cacheable_content_idx = content_idx + if isinstance(content_block, dict) and _is_cache_marked(content_block): + last_cacheable_message_idx = msg_idx + last_cacheable_content_idx = content_idx # If no cacheable block found, return empty list (no cacheable prefix) if last_cacheable_message_idx is None: diff --git a/litellm/router_utils/search_api_router.py b/litellm/router_utils/search_api_router.py index aa2b29988dc..17a56e62e41 100644 --- a/litellm/router_utils/search_api_router.py +++ b/litellm/router_utils/search_api_router.py @@ -52,7 +52,7 @@ class SearchAPIRouter: @staticmethod @renamed_router_param("router_instance") - async def update_router_search_tools(ctx: "RoutingContext", search_tools: list): + async def update_router_search_tools(ctx: "RoutingContext", search_tools: list) -> None: """ Update the router with search tools from the database. @@ -143,7 +143,6 @@ class SearchAPIRouter: # Set up kwargs for the fallback system kwargs["model"] = search_tool_name # Use model field for compatibility with fallback system kwargs["original_generic_function"] = original_function - # Bind ctx to the helper method using partial kwargs["original_function"] = partial( SearchAPIRouter.async_search_with_fallbacks_helper, litellm_routing_ctx=ctx, diff --git a/litellm/rust_bridge/_native.pyi b/litellm/rust_bridge/_native.pyi index 8177e4a5cc9..dc170116089 100644 --- a/litellm/rust_bridge/_native.pyi +++ b/litellm/rust_bridge/_native.pyi @@ -1,6 +1,6 @@ from asyncio import Future from collections.abc import Mapping, Sequence -from typing import Never, final +from typing import Generic, Literal, Never, NotRequired, TypedDict, TypeVar, final import httpx from pydantic import JsonValue @@ -218,6 +218,8 @@ __all__ = [ "NativeDiagnosticProcessor", "ProcessReservedForForking", "ResponsesWebSocketConnection", + "RouterCall", + "RouterCoreHandle", "RustBridgeDeclined", "RustUpstreamError", "TokenCounter", @@ -297,31 +299,492 @@ class _SecretManagerRuntime: primary_secret_name: str | None = None, ) -> Future[JsonValue]: ... +# The FailureKind names an attempt outcome's `kind` takes (router-core `FailureKind`). +_FailureKind = Literal[ + "RateLimitError", + "ContextWindowExceededError", + "ContentPolicyViolationError", + "AuthenticationError", + "PermissionDeniedError", + "NotFoundError", + "BadRequestError", + "Timeout", + "APIConnectionError", + "InternalServerError", + "ServiceUnavailableError", + "BadGatewayError", + "GuardrailIntervention", + "Declined", + "CallerCredentialAuthenticationError", + "CallerCredentialRateLimitError", + "APIError", +] + +# One event a call reported since the last step (router-core `RouterEvent`), carried on the next step. +class _Event(TypedDict): + kind: str + +# Every step `RouterCall.next` returns carries the events reported since the last one. +class _Step(TypedDict): + events: list[_Event] + +class _AttemptStep(_Step): + kind: Literal["attempt"] + deployment_id: str + # The deployment as a `model_list` entry, with its id in `model_info`. + deployment: dict[str, JsonValue] + # The name this attempt serves: the requested model or the fallback target. + model: str + model_group: str + target_order: int | None + candidate_ids: list[str] + retry: int + fallback_depth: int + fallback_level: int + timeout: float | None + # Request params the fallback walk's dict targets merged in. + params: dict[str, JsonValue] | None + # The walk level whose request metadata the attempt carries. + scope: int + max_retries: int + model_group_size: int + +class _SleepStep(_Step): + kind: Literal["sleep"] + seconds: float + +class _AllowFallbackStep(_Step): + kind: Literal["allow_fallback"] + target: str + +class _RefuseFallbacksStep(_Step): + kind: Literal["refuse_fallbacks"] + # The walk level whose chain the dict targets are. + level: int + targets: list[dict[str, JsonValue]] + +class _SelectStep(_Step): + kind: Literal["select"] + stage: Literal[ + "plugins", + "strategy", + "tags", + "pre_call", + "text_only", + "callback_filters", + "routing_plugins", + "provider_request", + ] + strategy: str | None + model_group: str + # The name the request resolved from, which strategies key their state by. + model: str + # Whose selector a strategy reads: "default", "group" (with `group`) or "override". + scope: str + group: str | None + # The deployments the name resolved to, before health filters. + pool: list[str] + candidates: list[str] + # `routing_plugins` only: whether the plugins run. + run: NotRequired[bool] + # `callback_filters` only: the ids the request already failed on. + excluded_ids: NotRequired[list[str]] + skipped_ids: NotRequired[list[str]] + +# Pre-routing before a pick resolves `model`: answered with the model group to resolve instead +# (a string), a custom strategy's deployment document (a mapping), or None. +class _PreRouteStep(_Step): + kind: Literal["pre_route"] + model: str + fallback_depth: int + retry: int + +# One RouterCache op against the router's DualCache. `key` is set for every op but `batch_get`, +# and `increment_usage`, which set `keys`; `value` is the JSON to store (`set`), the amount +# (`increment`) or one amount per key (`increment_usage`); `ttl` is in seconds; `local` reads or +# writes this worker's in-memory tier only. Outcomes: get -> the JSON value or None; batch_get -> +# one JSON value or None per key, in order; increment -> the new int or float; set, delete and +# increment_usage -> None. +class _CacheStep(_Step): + kind: Literal["cache"] + op: Literal["get", "set", "increment", "increment_usage", "batch_get", "delete"] + key: str | None + keys: list[str] | None + value: JsonValue + ttl: float | None + local: bool + +# One lookup of a model-info query (router-core `ModelInfoLookup`): its `lookup` name and that +# lookup's arguments, answered as the lookup documents. +class _ModelInfoStep(_Step): + kind: Literal["model_info"] + lookup: Literal[ + "model_info", + "cost_entry", + "provider", + "pattern_models", + "bedrock_base", + "discovered", + "user_model_info", + "log", + "group_params", + "group_deployment", + "group_capabilities", + "group_seed", + "reasoning_intersect", + ] + model: NotRequired[JsonValue] + tolerate: NotRequired[bool] + exact: NotRequired[bool] + key: NotRequired[str] + process: NotRequired[bool] + name: NotRequired[str] + model_id: NotRequired[str] + id: NotRequired[JsonValue] + level: NotRequired[Literal["debug", "error"]] + message: NotRequired[str] + index: NotRequired[int] + model_info: NotRequired[JsonValue] + litellm_model: NotRequired[JsonValue] + llm_provider: NotRequired[JsonValue] + mapped: NotRequired[bool] + info: NotRequired[dict[str, JsonValue]] + current: NotRequired[JsonValue] + resolved: NotRequired[JsonValue] + +class _FailedStep(_Step): + kind: Literal["failed"] + error: str + error_kind: Literal[ + "config", + "unknown_model", + "no_healthy_deployments", + "attempt", + "cache", + "retired", + "paused", + "not_pass_through", + "no_pass_through_deployments", + "only_markers", + "ptu_reserved", + "context_window_exceeded", + "unsupported_params", + "routing_plugins_left_nothing", + "routing_plugins_need_async", + "multiple_teams", + "reserved", + "invalid_router_weights", + "non_numeric_weight", + "missing_routing_group", + "default_deployment_raises", + "index_out_of_range", + "model_info", + ] + attempt_failed: bool + status: int | None + failure_kind: _FailureKind | None + error_model: NotRequired[str] + error_detail: NotRequired[str] + error_params: NotRequired[list[str]] + # `model_info` only: the builtin exception the lookup raised. + error_exception: NotRequired[str] + +# The end of a `RouterCoreHandle.start` (and the stream recovery calls). +class _DoneStep(_Step): + kind: Literal["done"] + deployment_id: str + model_group: str + attempted_retries: int + max_retries: int + attempted_fallbacks: int + total_tokens: int + +# The end of a `RouterCoreHandle.select`. +class _SelectedStep(_Step): + kind: Literal["done"] + deployment_id: str + model_group: str + deployment: dict[str, JsonValue] + +# The end of a `RouterCoreHandle.healthy`. +class _HealthyStep(_Step): + kind: Literal["done"] + # The name was a deployment id. + single: bool + deployment_ids: list[str] + deployments: list[dict[str, JsonValue]] + +# The end of a `RouterCoreHandle.report_failure`. +class _ReportedStep(_Step): + kind: Literal["done"] + cooled: bool + # The cooldown applied, in seconds; None when the deployment was not cooled down. + cooldown_time: float | None + +# The end of a `RouterCoreHandle.report_success` or `count_success`. +class _CountedStep(_Step): + kind: Literal["done"] + key: str + +# One `os.environ/` reference a `secrets` step asks for: a top-level param (`key`), or an +# env-only `dataSources[source].parameters[key]` (`env_only`). +class _SecretRef(TypedDict): + name: str + key: str + env_only: bool + source: NotRequired[int] + +# The deployment build's `os.environ/` references: answered with one value per ref, in order. +class _SecretsStep(_Step): + kind: Literal["secrets"] + index: int + refs: list[_SecretRef] + +# The deployment build's steps for one deployment. `validate` and `added` are answered with +# `{"entry": }`, `{"skip": True}` or `{"invalid": True}`; `provider` with +# `{"provider": str | None}` or `{"invalid": True}`. +class _BuildStep(_Step): + kind: Literal["validate", "provider", "added"] + path: Literal["create", "add"] + index: int + entry: dict[str, JsonValue] + declared_id: str | None + duplicate_id: bool + provider: str | None + +class _BuiltDeployment(TypedDict): + index: int + id: str | None + provider: str | None + +# The end of a `RouterCoreHandle.build`. +class _BuiltStep(_Step): + kind: Literal["done"] + built: list[_BuiltDeployment] + +# The end of a model-info query: `router_model_info` sets `info` (the merged map or None) and +# `user_keys`; `deployment_model_info` sets `info`; the others set `value`. +class _ModelInfoDoneStep(_Step): + kind: Literal["done"] + info: NotRequired[dict[str, JsonValue] | None] + user_keys: NotRequired[list[str]] + value: NotRequired[JsonValue] + +# `RouterCoreHandle.resolve`: what a name resolves to. +class _Resolution(TypedDict): + model_group: str + kind: str + ids: list[str] + +# The steps each kind of `RouterCall` returns, by the handle method that starts it. +_CallSteps = ( + _AttemptStep + | _SleepStep + | _AllowFallbackStep + | _RefuseFallbacksStep + | _SelectStep + | _PreRouteStep + | _CacheStep + | _DoneStep + | _FailedStep +) +_SelectSteps = _SelectStep | _PreRouteStep | _CacheStep | _SelectedStep | _FailedStep +_HealthySteps = _SelectStep | _PreRouteStep | _CacheStep | _HealthyStep | _FailedStep +_BuildSteps = _SecretsStep | _BuildStep | _BuiltStep | _FailedStep +_ModelInfoSteps = _ModelInfoStep | _ModelInfoDoneStep | _FailedStep +_FailureReportSteps = _CacheStep | _ReportedStep | _FailedStep +_SuccessReportSteps = _CacheStep | _CountedStep | _FailedStep + +class _AttemptSucceeded(TypedDict): + ok: Literal[True] + total_tokens: NotRequired[int] + blocked: NotRequired[Literal["content_filter", "refusal"] | None] + # A stream whose success or failure the host reports when it ends (`report_success`, + # `report_failure`): the attempt counts its request and `total_tokens` only. + deferred: NotRequired[bool] + # Whether the attempt counts against its deployment's usage; unset, its own limits decide. + tracks_usage: NotRequired[bool | None] + +class _AttemptFailed(TypedDict): + ok: Literal[False] + kind: _FailureKind + status: NotRequired[int | None] + retry_after: NotRequired[float | None] + num_retries: NotRequired[int | None] + # The deployment the exception names, which a retry skips over the attempt's own. + failed_deployment_id: NotRequired[str | None] + detail: NotRequired[str | None] + agentic_followup: NotRequired[bool] + # The exception has no `status_code`, which no cooldown rule reads. + status_absent: NotRequired[bool] + # The failure counts against no per-minute requests. + uncounted_request: NotRequired[bool] + +# Each document is a mapping or its JSON text. +_Document = Mapping[str, object] | str + @final -class NativeCacheHandle: - def __new__(cls, _uninstantiable: Never, /) -> Never: ... +class RouterCoreHandle: + def __new__(cls, config: _Document, dynamic: _Document) -> RouterCoreHandle: ... + def start(self, op: str, request: _Document) -> RouterCall[_CallSteps]: ... + # Driven like `start`; its `done` step is a `_SelectedStep`. + def select(self, model: str, request: _Document) -> RouterCall[_SelectSteps]: ... + # Driven like `select`; its `done` step is a `_HealthyStep`. + def healthy(self, model: str, request: _Document) -> RouterCall[_HealthySteps]: ... + # `{"replace" | "append" | "upsert": [deployments], "delete": [ids], "settings": {dynamic document}, "index": {...}}`. + def apply(self, changes: _Document) -> int: ... + # Build model_list entries through the host, driven like `start`: `_SecretsStep` and + # `_BuildStep` steps, then a `_BuiltStep`. `path`: "create" (`set_model_list`) or "add"; + # `install`: "replace", "append" or "upsert". + def build( + self, entries: Sequence[object], path: str, resolve_secrets: bool, install: str + ) -> RouterCall[_BuildSteps]: ... + # Keep the providers `other`'s builds resolved for the same deployments. + def adopt_providers(self, other: RouterCoreHandle) -> None: ... + # `get_router_model_info`, driven like `start`: `model_info` lookup steps (a `lookup` field + # and its arguments), then a done step with `info` (the merged map or None) and `user_keys`. + def router_model_info(self, query: _Document) -> RouterCall[_ModelInfoSteps]: ... + # `get_deployment_model_info`, driven like `router_model_info`; its done step has `info`. + def deployment_model_info(self, model_id: str, model_name: object) -> RouterCall[_ModelInfoSteps]: ... + # `_set_model_group_info` for a `GroupInfoQuery` document, driven like `router_model_info`; its + # done step has `value`: None, or `{"assignments": {field: value}}`. + def model_group_info(self, query: _Document) -> RouterCall[_ModelInfoSteps]: ... + # `get_configured_token_limits`, driven like `router_model_info`; `value` is `[input, output]`. + def configured_token_limits(self, id: object, configured: _Document) -> RouterCall[_ModelInfoSteps]: ... + # `get_model_listing_info`, driven like `router_model_info`; `value` has `cost_map_keys`, + # `max_input_tokens` and `max_output_tokens`. + def model_listing_info(self, deployments: list[object]) -> RouterCall[_ModelInfoSteps]: ... + # A configured string that is not blank (`get_configured_mode`, `get_configured_display_name`). @staticmethod - def memory( - *, - ttl: float = 600.0, - capacity: int = 200, - max_entry_bytes: int = 4194304, - ) -> NativeCacheHandle: ... + def configured_text(value: object) -> str | None: ... + # Each model_info's `service_tiers`, unvalidated. @staticmethod - def redis( - url: str, - *, - namespace: str, - ttl: float = 600.0, - max_entry_bytes: int = 4194304, - ) -> NativeCacheHandle: ... - def get(self, key: str) -> object: ... - def set(self, key: str, value: object, *, ttl: float | None = None) -> None: ... - def async_get(self, key: str) -> Future[object]: ... - def async_set(self, key: str, value: object, *, ttl: float | None = None) -> Future[None]: ... - def async_set_many(self, entries: Sequence[tuple[str, object]], *, ttl: float | None = None) -> Future[None]: ... - def flush(self) -> None: ... - def async_flush(self) -> Future[None]: ... - def ping(self) -> Future[bool]: ... - def disconnect(self) -> Future[None]: ... - def delete(self, keys: Sequence[str]) -> Future[None]: ... + def configured_service_tiers(model_infos: list[object]) -> list[object]: ... + # The routing-cache key a deployment counts `metric` (tpm, rpm, itpm, otpm) under in `minute`. + def usage_key(self, id: str, model: str, metric: str, minute: str) -> str: ... + def registry_version(self) -> int: ... + # The version the deployments before the newest appends last changed at. + def registry_rewritten(self) -> int: ... + # A failure the router did not see itself, driven like `start`: cache steps, then a + # `_ReportedStep`. + def report_failure( + self, + id: str, + failure: Mapping[str, object], + deployment_cooldown: bool = False, + count_only: bool = False, + requested_group: str | None = None, + cooldown_time: float | None = None, + uncounted: bool = False, + counts_request: bool = False, + usage_model: str | None = None, + callbacks: Mapping[str, bool] | None = None, + ) -> RouterCall[_FailureReportSteps]: ... + # A success a logging callback saw, driven like `report_failure`; `done` carries `key`. + def report_success( + self, + id: str, + total_tokens: float, + requests: float, + usage_model: str | None = None, + tracks_usage: bool | None = None, + callbacks: Mapping[str, bool] | None = None, + ) -> RouterCall[_SuccessReportSteps]: ... + # Count a success against any id, driven like `report_failure`; `done` carries `key`. + def count_success(self, id: str, callbacks: Mapping[str, bool] | None = None) -> RouterCall[_SuccessReportSteps]: ... + # [(id, tpm_key, rpm_key)] for this minute, or None for a group with no deployment. + def usage_keys(self, model_group: str) -> list[tuple[str, str, str]] | None: ... + # Every deployment as a `model_list` entry, in config order. + def deployments(self) -> list[dict[str, JsonValue]]: ... + def deployments_from(self, start: int) -> list[dict[str, JsonValue]]: ... + def deployment(self, id: str) -> dict[str, JsonValue] | None: ... + # Lookups over the registry indexes, answering what each index holds as written. + # Registry lookups (router-core `lookup.rs`): rows the host reads its stored entries at + # (`{"at": position, "name"?, "group"?, "member"?}`, `{"pattern": entry, "name"}`, or a + # `{"raw": value}` / `{"raw_positions": value}` its own read raises at). + def lookup_all( + self, model_name: str, team_id: str | None = None, rename: str | None = None + ) -> list[dict[str, JsonValue]]: ... + def lookup_across_teams(self, model: str) -> tuple[list[dict[str, JsonValue]], int]: ... + def lookup_config(self) -> list[dict[str, JsonValue]]: ... + def lookup_model_ids( + self, model_name: str | None = None, exclude_team_models: bool = False + ) -> tuple[list[str], dict[str, JsonValue] | None]: ... + def lookup_model_list( + self, model_name: str | None, team_id: str | None, scope: Mapping[str, object] + ) -> list[dict[str, JsonValue]]: ... + def lookup_model_names( + self, team_id: str | None, scope: Mapping[str, object] + ) -> tuple[list[str], dict[str, JsonValue] | None]: ... + def lookup_access_groups( + self, model_name: str | None, access_group: str | None, team_id: str | None, scope: Mapping[str, object] + ) -> tuple[list[tuple[str, list[str]]], dict[str, JsonValue] | None]: ... + def lookup_name_serving( + self, model_id: str, scope: Mapping[str, object] + ) -> tuple[bool, str | None, dict[str, JsonValue] | None]: ... + def has_model_name(self, name: str) -> bool: ... + def lookup_team_model_has_alternatives(self, id: str) -> tuple[bool, dict[str, JsonValue] | None]: ... + def lookup_group_usable_by_team( + self, model_group: str, team_id: str | None + ) -> tuple[int | None, dict[str, JsonValue] | None]: ... + def lookup_team_public_name( + self, model_id: str, team_id: str + ) -> tuple[int | None, dict[str, JsonValue] | None]: ... + def lookup_routable(self, model_group: str, team_id: str | None) -> list[dict[str, JsonValue]]: ... + def lookup_wildcard_route( + self, model: str, team_id: str | None, requests: list[str] + ) -> list[dict[str, JsonValue]]: ... + def lookup_candidate_ids( + self, resolved: str, team_id: str | None, members: list[str] | None, requests: list[str] + ) -> tuple[list[str], dict[str, JsonValue] | None]: ... + def has_model_id(self, id: str) -> bool: ... + def id_position(self, id: str) -> JsonValue | None: ... + def id_positions(self) -> list[tuple[str, JsonValue]]: ... + def named_positions(self, name: str) -> JsonValue | None: ... + def team_positions(self, team: str, public: str) -> JsonValue | None: ... + def team_public_names_of(self, team: str) -> list[str]: ... + def litellm_model_positions(self, model: str) -> list[int]: ... + # The registry indexes the host hands out (`HostIndexes`), as JSON. + def host_indexes(self) -> dict[str, JsonValue]: ... + def provider_default_ids(self) -> list[str]: ... + # `PatternMatchRouter.route` over the wildcard router, or `team`'s. + def pattern_route( + self, team: str | None, request: str, filtered: list[str] | None = None + ) -> list[dict[str, JsonValue]] | None: ... + # `get_models_by_pattern` over the wildcard router, or `team`'s. + def models_by_pattern(self, team: str | None, requests: list[str]) -> list[str] | None: ... + # The provider the host resolved when it built deployment `id` (its `provider` build step). + def provider(self, id: str) -> str | None: ... + def resolve(self, name: str, specific_deployment: bool = False) -> _Resolution | None: ... + def routable(self, model: str, request: _Document) -> list[dict[str, JsonValue]]: ... + # `_get_routing_context` for a pick of `model`: (strategy, scope, group). + def routing_context(self, model: str, routing_strategy: str | None = None) -> tuple[str, str, str | None]: ... + def retire(self) -> None: ... + # A stream that failed before content: what may still take over it, and the retry budget for + # a failure of `kind`: {"can_retry", "can_fall_back", "refusal_fallback": bool, + # "retry_budget": int | None, "policy_applies": bool}. + def stream_policy( + self, request: _Document, origin: _Document, kind: str | None = None + ) -> dict[str, bool | int | None]: ... + # The same-group retry and the fallback walk for such a stream, driven like `start`. + def retry_stream( + self, op: str, request: _Document, origin: _Document, failure: Mapping[str, object] + ) -> RouterCall[_CallSteps]: ... + def fallback_stream( + self, op: str, request: _Document, origin: _Document, failure: Mapping[str, object] + ) -> RouterCall[_CallSteps]: ... + def retry_policy_retries(self, failure: Mapping[str, object], model_group: str | None = None) -> int | None: ... + def allowed_fails_for(self, failure: Mapping[str, object]) -> int | None: ... + def should_retry( + self, failure: Mapping[str, object], counts: tuple[int, int], fallbacks: tuple[bool, bool, bool] + ) -> bool: ... + +_S = TypeVar("_S", covariant=True) + +@final +class RouterCall(Generic[_S]): + # The answer to the last step, which Rust validates against it: attempt: _AttemptSucceeded | + # _AttemptFailed; sleep: None; allow_fallback: bool; refuse_fallbacks: bool; select: the remaining + # candidate ids, pick first; pre_route: see _PreRouteStep; cache: see _CacheStep; secrets, build and model_info: + # see those steps; first call: None. + def next(self, outcome: object) -> _S: ... diff --git a/litellm/rust_bridge/catalog.py b/litellm/rust_bridge/catalog.py index 629d9098970..a12f79c6c8a 100644 --- a/litellm/rust_bridge/catalog.py +++ b/litellm/rust_bridge/catalog.py @@ -23,6 +23,7 @@ class Route(str, Enum): OCR = "ocr" TOKEN_COUNTER = "token_counter" TOKENIZER = "tokenizer" + ROUTER = "router" class Target(str, Enum): @@ -66,6 +67,8 @@ class Feature(str, Enum): """Extra body fields that Python transforms and merges into the provider request.""" PROVIDER_AFFINITY = "provider_affinity" """A provider affinity header that Python validates and populates from the session id.""" + FOUNDRY_BETA_ROW = "foundry_beta_row" + """A Foundry api_base, where Python drops the anthropic-beta values Foundry rejects.""" PRE_REQUEST_HOOK = "pre_request_hook" """A logger overriding async_pre_request_hook, which may rewrite the request.""" WEBSEARCH_INTERCEPTION = "websearch_interception" @@ -170,6 +173,7 @@ CHAT_PYTHON_FEATURES: Final = COMMON_PYTHON_FEATURES | { MESSAGES_PYTHON_FEATURES: Final = COMMON_PYTHON_FEATURES | { Feature.PROVIDER_AFFINITY, + Feature.FOUNDRY_BETA_ROW, Feature.SAFEGUARDS_CLASSIFIER, Feature.PRE_REQUEST_HOOK, Feature.WEBSEARCH_INTERCEPTION, @@ -221,6 +225,7 @@ RULES: Final[Rules] = ( RouteRule(Route.RESPONSES, Rollout.PYTHON_ONLY), RouteRule(Route.TOKEN_COUNTER, Rollout.PYTHON_ONLY), RouteRule(Route.TOKENIZER, Rollout.PYTHON_ONLY), + RouteRule(Route.ROUTER, Rollout.RUST_OPT_IN), RouteRule(Route.TRANSCRIPTION, Rollout.RUST_REQUIRED, providers=frozenset({"bedrock"})), ) diff --git a/litellm/rust_bridge/host/callbacks_legacy_python.py b/litellm/rust_bridge/host/callbacks_legacy_python.py index e155680bd30..92590531cdc 100644 --- a/litellm/rust_bridge/host/callbacks_legacy_python.py +++ b/litellm/rust_bridge/host/callbacks_legacy_python.py @@ -12,7 +12,7 @@ import datetime import traceback import uuid import weakref -from collections.abc import Awaitable, Coroutine, Mapping +from collections.abc import Awaitable, Coroutine, Mapping, Sequence from dataclasses import dataclass from typing import ( TYPE_CHECKING, @@ -22,6 +22,7 @@ from typing import ( cast, # noqa: TID251 # bounded compatibility calls into legacy Python integrations ) +import httpx from pydantic import TypeAdapter if TYPE_CHECKING: @@ -243,6 +244,27 @@ def post_call( logger.post_call(original_response=original_response, api_key=api_key, additional_args=additional_args) +def record_response(logger: Logging, status: int, headers: Sequence[tuple[str, str]], body: str) -> None: + """Stores the provider response the way Python's Messages handler does, for logging to replay.""" + response: Final = httpx.Response(status_code=status, headers=list(headers), content=body.encode()) + details: Final = logger.model_call_details # the call's own logger: recording on it is the point + details["httpx_response"] = response + details["response_headers"] = dict(response.headers) + + +def record_api_window(logger: Logging, start: float, end: float) -> None: + """Records the provider exchange's window the way Python's timed `AsyncHTTPHandler.post` does.""" + from litellm.litellm_core_utils.logging_utils import ( + _set_duration_in_model_call_details, # pyright: ignore[reportPrivateUsage] # the timed post's own recorder + ) + + _set_duration_in_model_call_details( + logging_obj=logger, + start_time=datetime.datetime.fromtimestamp(start), # noqa: DTZ006 # the timed post records naive local times + end_time=datetime.datetime.fromtimestamp(end), # noqa: DTZ006 # the timed post records naive local times + ) + + def defers_async_logging(logger: LoggingSurface) -> bool: return bool(getattr(logger, "defer_async_logging", False)) @@ -359,6 +381,27 @@ def after_deployment_failure(kwargs: dict[str, object], error: Exception, call_t _STREAM_HEADERS: Final = TypeAdapter(Mapping[str, str]) +class _HiddenParamsCarrier: + """Stands in for the stream `@client` stamps, so the head becomes its `_hidden_params`.""" + + def __init__(self, hidden_params: dict[str, object]) -> None: # mutable-ok: the stamps land in this dict + self._hidden_params: object = hidden_params + + +def stamp_stream_head( + head: dict[str, object], # mutable-ok: the stream's hidden params, stamped in place + logger: Logging, + kwargs: dict[str, object], # mutable-ok: `finalize` takes the call kwargs as a dict + start_time: datetime.datetime, + end_time: datetime.datetime, +) -> None: + carrier: Final = _HiddenParamsCarrier(head) + finalize(carrier, logger, kwargs, start_time, end_time) + stamped: Final = carrier._hidden_params # pyright: ignore[reportPrivateUsage] # the carrier's own field + if stamped is not head and isinstance(stamped, dict): + head.update(cast("dict[str, object]", stamped)) # cast-ok: update_response_metadata writes a str-keyed dict + + def stream_opened(logger: Logging, head: Mapping[str, object]) -> None: logger.stream = True logger.model_call_details["stream"] = True diff --git a/litellm/rust_bridge/host/routes/messages.py b/litellm/rust_bridge/host/routes/messages.py index 017ff65e2a7..c8b53097f46 100644 --- a/litellm/rust_bridge/host/routes/messages.py +++ b/litellm/rust_bridge/host/routes/messages.py @@ -1,21 +1,35 @@ from __future__ import annotations -from collections.abc import Mapping, Sequence +import datetime +from collections.abc import Callable, Mapping, Sequence from dataclasses import asdict, dataclass -from typing import Final, cast # noqa: TID251 # narrows the normalized native payload to the public TypedDict +from typing import Final, TypeAlias, cast # noqa: TID251 # narrows native payloads to public TypedDicts import httpx from pydantic import TypeAdapter, ValidationError import litellm +from litellm.litellm_core_utils import exception_mapping_utils from litellm.litellm_core_utils.core_helpers import normalize_drop_params +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.litellm_core_utils.reasoning_effort_capability import deployment_reasoning_effort_levels from litellm.litellm_core_utils.request_timeout_resolver import get_configured_request_timeout +from litellm.llms.anthropic.common_utils import AnthropicError +from litellm.llms.anthropic.messages.native import handler +from litellm.llms.anthropic.messages.native.handler import ( + _native_messages_config as native_messages_config, # pyright: ignore[reportPrivateUsage] # the handler's own config lookup +) +from litellm.llms.anthropic.messages.native.handler import ( + _with_deployment_output_effort as _deployment_output_effort, # pyright: ignore[reportPrivateUsage] # the handler's own effort rounding +) from litellm.llms.anthropic.messages.utils import is_reasoning_auto_summary_enabled from litellm.rust_bridge import failures +from litellm.rust_bridge.host import callbacks_legacy_python from litellm.rust_bridge.public_call import known_params, optional_str from litellm.types.llms.anthropic_messages.anthropic_response import AnthropicMessagesResponse _DROP_PATHS: Final = TypeAdapter(list[object]) +_METADATA: Final = TypeAdapter(dict[str, object]) _BODY_FIELDS: Final = frozenset( { "max_tokens", @@ -40,6 +54,7 @@ _BODY_FIELDS: Final = frozenset( "cache_control", "reasoning_effort", "safeguards", + "service_tier", } ) @@ -59,8 +74,40 @@ def response(value: Mapping[str, object]) -> AnthropicMessagesResponse: ) +def inferred_provider(model: str, api_base: str | None) -> str | None: + """The provider Python's handler resolves for a call that names none, or None when the model + carries no provider `get_llm_provider` knows.""" + try: + _, provider, _, _ = litellm.get_llm_provider(model=model, api_base=api_base) + except litellm.BadRequestError: + return None + return provider + + def body_params(request: Mapping[str, object]) -> Mapping[str, object]: - return known_params(_BODY_FIELDS, request) + params: Final = known_params(_BODY_FIELDS, request) + if deployment_reasoning_effort_levels(request.get("model_info")) is None: + return params + return _with_deployment_effort(params, request) + + +def _with_deployment_effort(params: Mapping[str, object], request: Mapping[str, object]) -> Mapping[str, object]: + """Python's handler rounds the requested effort to the levels the deployment declares in + `model_info.reasoning_effort_levels`, the one place a deployment, not the model, decides.""" + explicit_provider: Final = optional_str(request.get("custom_llm_provider")) + try: + model, provider, _, _ = litellm.get_llm_provider( + model=str(request["model"]), custom_llm_provider=explicit_provider + ) + except litellm.BadRequestError: + return params + return _deployment_output_effort( + params, + model=model, + custom_llm_provider=provider, + kwargs=request, + drop_params=litellm.drop_params is True or request.get("drop_params") is True, + ) def stream_hidden_params(headers: Sequence[tuple[str, str]]) -> Mapping[str, object]: @@ -71,18 +118,147 @@ def stream_hidden_params(headers: Sequence[tuple[str, str]]) -> Mapping[str, obj return anthropic_messages_stream_hidden_params(httpx.Headers(list(headers))) -def map_failure(error: Exception, request: Mapping[str, object], request_provider: str) -> Exception: - if getattr(error, "messages_request_error", False): - return litellm.BadRequestError( - message=str(error), - model=str(request["model"]).removeprefix(f"{request_provider}/"), - llm_provider=request_provider, - ) - return failures.map_native_failure( - error, str(request["model"]), request_provider, request, optional_str(request.get("api_base")) +_UPSTREAM_ARGS: Final = TypeAdapter(tuple[int, str]) +_UPSTREAM_HEADERS: Final = TypeAdapter(list[tuple[str, str]]) +_ERROR_CLASS: TypeAlias = Callable[..., Exception] +_validate_metadata: Final = cast( # cast-ok: the handler's untyped metadata validator + Callable[[dict[str, object]], object], handler.validate_anthropic_api_metadata +) +_exception_type: Final = cast( # cast-ok: the legacy public exception mapper is untyped + Callable[..., Exception], exception_mapping_utils.exception_type +) +_BODY_READ_TIMEOUT: Final = "Timeout on reading data from socket" # aiohttp's SocketTimeoutError text +_MISSING_KEY: Final = ( + "Missing Anthropic API Key - A call is being made to anthropic but no key is set " + "either in the environment variables or via params. Please set `ANTHROPIC_API_KEY` " + "or `ANTHROPIC_AUTH_TOKEN` in your environment vars" +) + + +def _rejection(error: Exception, request: Mapping[str, object], request_provider: str) -> Exception: + """The error Python's handler raises for a request it refuses before sending it.""" + metadata: Final = request.get("metadata") + if isinstance(metadata, dict): + try: + _validate_metadata(_METADATA.validate_python(metadata)) + except ValidationError as invalid: + return invalid + if getattr(error, "messages_unsupported_param", False): + return litellm.UnsupportedParamsError(message=str(error)) + return litellm.BadRequestError( + message=str(error), + model=str(request["model"]).removeprefix(f"{request_provider}/"), + llm_provider=request_provider, ) +def _timeout_text(phase: str, request: Mapping[str, object]) -> str: + """`litellm.Timeout`'s text as Python's HTTP client raises it for the same timeout.""" + seconds: Final = request.get("timeout") + logging_obj: Final = request.get("litellm_logging_obj") + start_time: Final = getattr(logging_obj, "start_time", None) + time_taken: Final = ( + round( + (datetime.datetime.now() - start_time).total_seconds(), # noqa: DTZ005 # the logger's start_time is naive local time + 3, + ) + if isinstance(start_time, datetime.datetime) + else None + ) + return str( + litellm.Timeout( + message=f"{phase} timed out. Timeout passed={seconds}, time taken={time_taken} seconds", + model="default-model-name", + llm_provider="litellm-httpx-handler", + ) + ) + + +def _upstream_failure( + error: Exception, request: Mapping[str, object] +) -> tuple[int, str, Sequence[tuple[str, str]]] | None: + """The status, text and headers Python's HTTP client reports for the same failure.""" + timeout_phase: Final = getattr(error, "messages_timeout", None) + if isinstance(timeout_phase, str): + return 408, _timeout_text(timeout_phase, request), () + try: + status, text = _UPSTREAM_ARGS.validate_python(error.args) + return status, text, _UPSTREAM_HEADERS.validate_python(getattr(error, "headers", None)) + except ValidationError: + return None + + +def _provider_error(error: Exception, request: Mapping[str, object], request_provider: str) -> Exception | None: + """The provider exception Python's `_handle_error` builds for the same failure.""" + failure: Final = _upstream_failure(error, request) + if failure is None: + return None + status, text, headers = failure + api_base: Final = request.get("api_base") + config: Final = native_messages_config( + str(request["model"]).removeprefix(f"{request_provider}/"), + request_provider, + request.get("model_info"), + api_base if isinstance(api_base, str) else None, + ) + return ( + cast(_ERROR_CLASS, config.get_error_class)( # cast-ok: the config's untyped headers parameter + error_message=text, status_code=status, headers=dict(headers) + ) + if config is not None + else AnthropicError(status_code=status, message=text, headers=httpx.Headers(headers)) + ) + + +def _log_resolved_call(request: Mapping[str, object], request_provider: str) -> None: + """Tells the logger the resolved call, as Python's handler does before its provider config + transforms the request.""" + logger: Final = request.get("litellm_logging_obj") + if not isinstance(logger, LiteLLMLoggingObj): + return + callbacks_legacy_python.update_logging( + logger, + kwargs={name: value for name, value in request.items() if name != "metadata"}, + model=str(request["model"]).removeprefix(f"{request_provider}/"), + optional_params=dict(body_params(request)), + litellm_params={"model_info": request.get("model_info"), **body_params(request)}, + custom_llm_provider=request_provider, + ) + + +def map_failure(error: Exception, request: Mapping[str, object], request_provider: str) -> Exception: + """Raises what Python's Messages handler raises for the same failure.""" + if getattr(error, "messages_timeout", None) == "Body": + # Python reads a stream's body outside its HTTP client's error mapping, so the transport's + # own timeout reaches the caller unmapped. + return httpx.ReadTimeout(_BODY_READ_TIMEOUT) + if getattr(error, "messages_late_rejection", False): + _log_resolved_call(request, request_provider) + if getattr(error, "messages_request_error", False): + return _rejection(error, request, request_provider) + if getattr(error, "messages_missing_credential", False): + return litellm.AuthenticationError( + message=_MISSING_KEY, + llm_provider=request_provider, + model=str(request["model"]).removeprefix(f"{request_provider}/"), + ) + provider_error: Final = _provider_error(error, request, request_provider) + if provider_error is None: + return failures.map_native_failure( + error, str(request["model"]), request_provider, request, optional_str(request.get("api_base")) + ) + try: + return _exception_type( + model=str(request["model"]), + custom_llm_provider=request_provider, + original_exception=provider_error, + extra_kwargs=dict(request), + ) + except Exception as mapped: # noqa: BLE001 # exception_type raises the mapped public error + mapped.__context__ = error + return mapped + + def _drop_params(kwargs: Mapping[str, object]) -> bool: return bool(litellm.drop_params) or normalize_drop_params(kwargs.get("drop_params")) is True diff --git a/litellm/rust_bridge/messages/detectors.py b/litellm/rust_bridge/messages/detectors.py index 8edd2707405..6a0c867979b 100644 --- a/litellm/rust_bridge/messages/detectors.py +++ b/litellm/rust_bridge/messages/detectors.py @@ -5,6 +5,7 @@ from __future__ import annotations from typing import Final import litellm +from litellm.anthropic_beta_headers_manager import is_foundry_api_base from litellm.litellm_core_utils.core_helpers import drops_unsupported_params from litellm.llms.opencode.common_utils import is_opencode_api_base from litellm.rust_bridge.detectors import api_base, overridden, present, streaming @@ -15,6 +16,12 @@ def provider_affinity(request: NativeCall) -> bool: return is_opencode_api_base(api_base(request)) +def foundry_beta_row(request: NativeCall) -> bool: + from litellm.llms.anthropic.common_utils import AnthropicModelInfo + + return is_foundry_api_base(AnthropicModelInfo.get_api_base(api_base(request))) + + def anthropic_workload_identity(request: NativeCall) -> bool: """Python mints an Anthropic federation token when no static credential is configured.""" from litellm.llms.anthropic.common_utils import AnthropicModelInfo diff --git a/litellm/secret_managers/aws_secret_manager.py b/litellm/secret_managers/aws_secret_manager.py index 88642ae141e..c87edc4b1dd 100644 --- a/litellm/secret_managers/aws_secret_manager.py +++ b/litellm/secret_managers/aws_secret_manager.py @@ -70,7 +70,7 @@ class AWSKeyManagementService_V2: is_litellm_license_in_env = True if is_litellm_license_in_env is False: raise ValueError( - "AWSKeyManagementService V2 is an Enterprise Feature. Please add a valid LITELLM_LICENSE to your envionment." + "AWSKeyManagementService V2 is an Enterprise Feature. Please add a valid LITELLM_LICENSE to your environment." ) def load_aws_kms(self, use_aws_kms: bool | None): diff --git a/litellm/text_completions/streaming_iterator.py b/litellm/text_completions/streaming_iterator.py index 61e47e9d7af..2b5b4d52274 100644 --- a/litellm/text_completions/streaming_iterator.py +++ b/litellm/text_completions/streaming_iterator.py @@ -1,5 +1,6 @@ from typing import Final +from litellm.constants import VLLM_CHOICE_FIELDS from litellm.litellm_core_utils.stream_usage_chunks import is_injected_stream_usage_artifact from litellm.types.utils import Choices, ModelResponse, ModelResponseStream, TextChoices, TextCompletionResponse @@ -30,23 +31,26 @@ class TextCompletionStreamWrapper: def __aiter__(self): return self - def convert_to_text_completion_object(self, chunk: ModelResponse | ModelResponseStream): + def convert_to_text_completion_object(self, chunk: ModelResponse | ModelResponseStream) -> TextCompletionResponse: try: response: Final = TextCompletionResponse() response["id"] = chunk.get("id", None) response["object"] = "text_completion" response["created"] = chunk.get("created", None) response["model"] = chunk.get("model", None) - text_choices: Final = TextChoices() if isinstance(chunk, Choices): # chunk should always be of type StreamingChoices raise Exception if chunk["choices"]: - delta: Final = chunk["choices"][0]["delta"] + chat_choice: Final = chunk["choices"][0] + text_choices: Final = TextChoices( + **{field: chat_choice[field] for field in VLLM_CHOICE_FIELDS if field in chat_choice} + ) + delta: Final = chat_choice["delta"] text_choices["text"] = delta["content"] text_choices["reasoning_content"] = delta.get("reasoning_content") - text_choices["index"] = chunk["choices"][0]["index"] - text_choices["finish_reason"] = chunk["choices"][0]["finish_reason"] + text_choices["index"] = chat_choice["index"] + text_choices["finish_reason"] = chat_choice["finish_reason"] response["choices"] = [text_choices] else: response["choices"] = [] diff --git a/litellm/types/decisions.py b/litellm/types/decisions.py index 33b2c677d31..3b28225f0ff 100644 --- a/litellm/types/decisions.py +++ b/litellm/types/decisions.py @@ -210,7 +210,7 @@ class NoulAnswer(LiteLLMPydanticObjectBase): class ChoiceAnswer(LiteLLMPydanticObjectBase): type: Literal["choice"] choice: str - confidence: float + confidence: float | None = None probabilities: Mapping[str, float] model_config = ConfigDict(extra="allow", frozen=True) @@ -219,7 +219,7 @@ class ChoiceAnswer(LiteLLMPydanticObjectBase): class ScoreAnswer(LiteLLMPydanticObjectBase): type: Literal["score"] score: float - confidence: float + confidence: float | None = None legend: Mapping[str, DecisionsJSON] probabilities: Mapping[str, float] @@ -431,7 +431,7 @@ class OpenAIChoiceAnswer(LiteLLMPydanticObjectBase): name: str | None choice: str | bool probabilities: tuple[OpenAIChoiceProbability, ...] - confidence: float + confidence: float | None = None model_config = ConfigDict(frozen=True) @@ -449,7 +449,7 @@ class OpenAIScoreAnswer(LiteLLMPydanticObjectBase): name: str | None score: float probabilities: tuple[OpenAIScoreProbability, ...] - confidence: float + confidence: float | None = None model_config = ConfigDict(frozen=True) @@ -595,7 +595,7 @@ class DecisionsIRChoiceProbability: @dataclass(frozen=True, slots=True) class DecisionsIRChoiceAnswer: choice: str | bool - confidence: float + confidence: float | None probabilities: tuple[DecisionsIRChoiceProbability, ...] extra: Mapping[str, object] = field(default_factory=lambda: _NO_EXTRA) @@ -610,7 +610,7 @@ class DecisionsIRScoreProbability: @dataclass(frozen=True, slots=True) class DecisionsIRScoreAnswer: score: float - confidence: float + confidence: float | None probabilities: tuple[DecisionsIRScoreProbability, ...] extra: Mapping[str, object] = field(default_factory=lambda: _NO_EXTRA) diff --git a/litellm/types/integrations/custom_logger.py b/litellm/types/integrations/custom_logger.py index 77e75dea030..14ed719a880 100644 --- a/litellm/types/integrations/custom_logger.py +++ b/litellm/types/integrations/custom_logger.py @@ -74,14 +74,13 @@ class AgenticLoopSafetyError(ValueError): Covers both rails: the bounded-loop cap (``max_agentic_loops``) and the repeated tool-call fingerprint cycle break. Subclasses ``ValueError`` so callers that already catch the broader type keep working. - - Only the anthropic messages loop raises this today. The chat completions - loop in ``litellm_core_utils/chat_completion_agentic_loop.py`` still raises - a plain ``ValueError`` from its own copy of the same rails, so catching - this type alone will not cover that surface until it is moved over. """ +class AgenticLoopLimitError(AgenticLoopSafetyError): + pass + + class StandardCustomLoggerInitParams(LiteLLMBaseModel): """ Params for initializing a CustomLogger. diff --git a/litellm/types/integrations/model_deprecation_email.py b/litellm/types/integrations/model_deprecation_email.py new file mode 100644 index 00000000000..f196bb47544 --- /dev/null +++ b/litellm/types/integrations/model_deprecation_email.py @@ -0,0 +1,35 @@ +"""Model retirement email milestones and recipient-scoped content.""" + +from dataclasses import dataclass +from datetime import date +from enum import IntEnum +from typing import Final + +from litellm.types.proxy.model_deprecation import ModelDeprecationInfo + +MODEL_DEPRECATION_EMAIL_EVENT: Final = "Model Deprecations" + + +class DeprecationEmailMilestone(IntEnum): + THIRTY_DAYS = 30 + ONE_DAY = 1 + + +@dataclass(frozen=True, slots=True) +class ModelDeprecationEmail: + model: ModelDeprecationInfo + usage_model: str + recipient_email: str + milestone: DeprecationEmailMilestone + key_count: int + requests: int + team_names: tuple[str, ...] + start_date: date + end_date: date + + +@dataclass(frozen=True, slots=True) +class RenderedDeprecationEmail: + subject: str + html: str + text: str diff --git a/litellm/types/litellm_params.py b/litellm/types/litellm_params.py index 1f90552e869..9f63d27f5f3 100644 --- a/litellm/types/litellm_params.py +++ b/litellm/types/litellm_params.py @@ -55,6 +55,7 @@ RoutingStrategyName: TypeAlias = Literal[ TRUSTED_CALLBACK_VARS_FIELD: Final = "litellm_trusted_callback_vars" ADDRESSED_RESPONSE_ID_FIELD: Final = "_litellm_addressed_response_id" +ADDRESSED_COMPARISON_RESPONSE_ID_FIELD: Final = "_litellm_addressed_comparison_response_id" STREAM_USAGE_INJECTED_FIELD: Final = "_litellm_stream_usage_injected" WIRE_NAME: Final = "wire_name" @@ -407,6 +408,9 @@ class ProxyRequestState: secret_fields: "SecretFields | None" = None trusted_callback_vars: Mapping[str, str] | None = field(default=None, metadata=wire(TRUSTED_CALLBACK_VARS_FIELD)) addressed_response_id: str | None = field(default=None, metadata=wire(ADDRESSED_RESPONSE_ID_FIELD)) + addressed_comparison_response_id: str | None = field( + default=None, metadata=wire(ADDRESSED_COMPARISON_RESPONSE_ID_FIELD) + ) strip_stream_usage: bool | None = field(default=None, metadata=wire("_litellm_strip_stream_usage")) stream_usage_injected: bool | None = field(default=None, metadata=wire(STREAM_USAGE_INJECTED_FIELD)) client_side_timeout: bool | None = None diff --git a/litellm/types/llms/anthropic.py b/litellm/types/llms/anthropic.py index 8057ca5b55f..fc85f196b00 100644 --- a/litellm/types/llms/anthropic.py +++ b/litellm/types/llms/anthropic.py @@ -660,6 +660,7 @@ class MessageChunk(TypedDict, total=False): stop_sequence: str | None usage: UsageDelta safeguard_results: ReadOnly[Sequence[SafeguardResult]] + input_transformations: ReadOnly[Sequence[Mapping[str, object]]] class MessageStartBlock(TypedDict): @@ -849,6 +850,7 @@ class ANTHROPIC_BETA_HEADER_VALUES(str, Enum): ADVISOR_TOOL_2026_03_01 = "advisor-tool-2026-03-01" PER_TURN_CONTROL_2026_07_01 = "per-turn-control-2026-07-01" DANGEROUS_TOOL_USE_2026_09_03 = "dangerous-tool-use-2026-09-03" + MCP_CLIENT_2025_04_04 = "mcp-client-2025-04-04" # Tool search beta header constant (for Anthropic direct API and Microsoft Foundry) diff --git a/litellm/types/llms/anthropic_messages/anthropic_response.py b/litellm/types/llms/anthropic_messages/anthropic_response.py index 4f419385630..51168071c85 100644 --- a/litellm/types/llms/anthropic_messages/anthropic_response.py +++ b/litellm/types/llms/anthropic_messages/anthropic_response.py @@ -1,4 +1,4 @@ -from collections.abc import Sequence +from collections.abc import Mapping, Sequence from typing import Literal, TypeAlias from typing_extensions import NotRequired, ReadOnly, TypedDict @@ -106,3 +106,4 @@ class AnthropicMessagesResponse(TypedDict, total=False): usage: AnthropicUsage | None context_management: NotRequired[ContextManagementResponse] safeguard_results: NotRequired[ReadOnly[Sequence[SafeguardResult]]] + input_transformations: NotRequired[ReadOnly[Sequence[Mapping[str, object]]]] diff --git a/litellm/types/llms/custom_llm.py b/litellm/types/llms/custom_llm.py index 6b583b0a83d..bb12449617d 100644 --- a/litellm/types/llms/custom_llm.py +++ b/litellm/types/llms/custom_llm.py @@ -1,11 +1,12 @@ from typing import TYPE_CHECKING -from typing_extensions import TypedDict +from typing_extensions import ReadOnly, TypedDict if TYPE_CHECKING: + from litellm.llms.base_llm.videos.transformation import BaseVideoConfig from litellm.llms.custom_llm import CustomLLM class CustomLLMItem(TypedDict): provider: str - custom_handler: "CustomLLM" + custom_handler: ReadOnly["CustomLLM | BaseVideoConfig"] diff --git a/litellm/types/llms/openai.py b/litellm/types/llms/openai.py index d7e55b57a07..c9739eee91d 100644 --- a/litellm/types/llms/openai.py +++ b/litellm/types/llms/openai.py @@ -1,8 +1,9 @@ import builtins import math -from collections.abc import Iterable, Mapping, Sequence +from collections.abc import ItemsView, Iterable, Mapping, Sequence from enum import Enum from os import PathLike +from types import MappingProxyType from typing import IO, TYPE_CHECKING, Any, Final, Generic, Literal, Optional, TypeAlias, Union import httpx @@ -692,9 +693,19 @@ class PromptCacheBreakpoint(TypedDict): ttl: NotRequired[ReadOnly[Literal["30m", "12h"]]] +class ChatCompletionPromptCacheBreakpoint(TypedDict): + mode: ReadOnly[Literal["explicit"]] + + +class AzureResponsesPromptCacheBreakpoint(TypedDict): + mode: ReadOnly[Literal["explicit"]] + ttl: NotRequired[ReadOnly[Literal["30m"]]] + + class PromptCacheOptions(TypedDict, total=False): mode: ReadOnly[Literal["implicit", "explicit"]] ttl: ReadOnly[Literal["30m", "12h"]] + comparison_response_id: ReadOnly[str] class ChatCompletionThinkingBlock(TypedDict, total=False): @@ -1236,9 +1247,12 @@ AllEmbeddingInputValues = str | list[str] | list[int] | list[list[int]] OpenAIAudioTranscriptionOptionalParams = Literal[ "language", + "languages", + "keywords", "prompt", "temperature", "response_format", + "stream", "timestamp_granularities", "include", ] @@ -1754,17 +1768,40 @@ class ResponsesAPIStreamEvents(str, Enum): ERROR = "error" -class ResponseCreatedEvent(BaseLiteLLMOpenAIResponseObject): +_NO_EXTRAS: Final[Mapping[str, object]] = MappingProxyType({}) + + +class BaseResponsesStreamEvent(BaseLiteLLMOpenAIResponseObject): # frozen-ok: guardrails rewrite events in place + def __getitem__(self, key: str) -> object: + return self._mapping_holding(key)[key] + + def get(self, key: str, default: object = None) -> object: + return self._mapping_holding(key).get(key, default) + + def __contains__(self, key: object) -> bool: + return key in self.__dict__ or key in self._extras() + + def items(self) -> ItemsView[str, object]: + return MappingProxyType({**self.__dict__, **self._extras()}).items() + + def _extras(self) -> Mapping[str, object]: + return self.__pydantic_extra__ or _NO_EXTRAS + + def _mapping_holding(self, key: str) -> Mapping[str, object]: + return self.__dict__ if key in self.__dict__ else self._extras() + + +class ResponseCreatedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.RESPONSE_CREATED] response: ResponsesAPIResponse -class ResponseInProgressEvent(BaseLiteLLMOpenAIResponseObject): +class ResponseInProgressEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.RESPONSE_IN_PROGRESS] response: ResponsesAPIResponse -class ResponseCompletedEvent(BaseLiteLLMOpenAIResponseObject): +class ResponseCompletedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.RESPONSE_COMPLETED] response: ResponsesAPIResponse _hidden_params: dict = PrivateAttr(default_factory=dict) @@ -1778,12 +1815,12 @@ class ResponseCompletedEvent(BaseLiteLLMOpenAIResponseObject): self._hidden_params = hidden_params -class ResponseFailedEvent(BaseLiteLLMOpenAIResponseObject): +class ResponseFailedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.RESPONSE_FAILED] response: ResponsesAPIResponse -class ResponseIncompleteEvent(BaseLiteLLMOpenAIResponseObject): +class ResponseIncompleteEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE] response: ResponsesAPIResponse @@ -1791,7 +1828,7 @@ class ResponseIncompleteEvent(BaseLiteLLMOpenAIResponseObject): ResponsesTerminalEvent: TypeAlias = ResponseCompletedEvent | ResponseIncompleteEvent | ResponseFailedEvent -class ResponsePartAddedEvent(BaseLiteLLMOpenAIResponseObject): +class ResponsePartAddedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.RESPONSE_PART_ADDED] item_id: str output_index: int @@ -1799,7 +1836,7 @@ class ResponsePartAddedEvent(BaseLiteLLMOpenAIResponseObject): part: dict -class ReasoningSummaryTextDeltaEvent(BaseLiteLLMOpenAIResponseObject): +class ReasoningSummaryTextDeltaEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.REASONING_SUMMARY_TEXT_DELTA] item_id: str output_index: int @@ -1807,7 +1844,7 @@ class ReasoningSummaryTextDeltaEvent(BaseLiteLLMOpenAIResponseObject): delta: str -class ReasoningSummaryTextDoneEvent(BaseLiteLLMOpenAIResponseObject): +class ReasoningSummaryTextDoneEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.REASONING_SUMMARY_TEXT_DONE] item_id: str output_index: int @@ -1816,7 +1853,7 @@ class ReasoningSummaryTextDoneEvent(BaseLiteLLMOpenAIResponseObject): text: str -class ReasoningSummaryPartDoneEvent(BaseLiteLLMOpenAIResponseObject): +class ReasoningSummaryPartDoneEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.REASONING_SUMMARY_PART_DONE] item_id: str output_index: int @@ -1825,13 +1862,13 @@ class ReasoningSummaryPartDoneEvent(BaseLiteLLMOpenAIResponseObject): part: BaseLiteLLMOpenAIResponseObject -class OutputItemAddedEvent(BaseLiteLLMOpenAIResponseObject): +class OutputItemAddedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED] output_index: int item: BaseLiteLLMOpenAIResponseObject | None -class OutputItemDoneEvent(BaseLiteLLMOpenAIResponseObject): +class OutputItemDoneEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE] output_index: int sequence_number: int = 1 @@ -1851,7 +1888,7 @@ class OpenAIChatCompletionLogprobsContent(TypedDict, total=False): top_logprobs: list[OpenAIChatCompletionLogprobsContentTopLogprobs] -class ContentPartAddedEvent(BaseLiteLLMOpenAIResponseObject): +class ContentPartAddedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.CONTENT_PART_ADDED] item_id: str output_index: int @@ -1879,7 +1916,7 @@ class ContentPartDonePartReasoningText(BaseLiteLLMOpenAIResponseObject): PART_UNION_TYPES = ContentPartDonePartOutputText | ContentPartDonePartRefusal | ContentPartDonePartReasoningText -class ContentPartDoneEvent(BaseLiteLLMOpenAIResponseObject): +class ContentPartDoneEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.CONTENT_PART_DONE] item_id: str output_index: int @@ -1887,7 +1924,7 @@ class ContentPartDoneEvent(BaseLiteLLMOpenAIResponseObject): part: PART_UNION_TYPES -class OutputTextDeltaEvent(BaseLiteLLMOpenAIResponseObject): +class OutputTextDeltaEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA] item_id: str output_index: int @@ -1895,7 +1932,7 @@ class OutputTextDeltaEvent(BaseLiteLLMOpenAIResponseObject): delta: str -class OutputTextAnnotationAddedEvent(BaseLiteLLMOpenAIResponseObject): +class OutputTextAnnotationAddedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.OUTPUT_TEXT_ANNOTATION_ADDED] item_id: str output_index: int @@ -1904,7 +1941,7 @@ class OutputTextAnnotationAddedEvent(BaseLiteLLMOpenAIResponseObject): annotation: dict -class OutputTextDoneEvent(BaseLiteLLMOpenAIResponseObject): +class OutputTextDoneEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.OUTPUT_TEXT_DONE] item_id: str output_index: int @@ -1912,7 +1949,7 @@ class OutputTextDoneEvent(BaseLiteLLMOpenAIResponseObject): text: str -class RefusalDeltaEvent(BaseLiteLLMOpenAIResponseObject): +class RefusalDeltaEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.REFUSAL_DELTA] item_id: str output_index: int @@ -1920,7 +1957,7 @@ class RefusalDeltaEvent(BaseLiteLLMOpenAIResponseObject): delta: str -class RefusalDoneEvent(BaseLiteLLMOpenAIResponseObject): +class RefusalDoneEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.REFUSAL_DONE] item_id: str output_index: int @@ -1928,72 +1965,72 @@ class RefusalDoneEvent(BaseLiteLLMOpenAIResponseObject): refusal: str -class FunctionCallArgumentsDeltaEvent(BaseLiteLLMOpenAIResponseObject): +class FunctionCallArgumentsDeltaEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA] item_id: str output_index: int delta: str -class FunctionCallArgumentsDoneEvent(BaseLiteLLMOpenAIResponseObject): +class FunctionCallArgumentsDoneEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DONE] item_id: str output_index: int arguments: str -class FileSearchCallInProgressEvent(BaseLiteLLMOpenAIResponseObject): +class FileSearchCallInProgressEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.FILE_SEARCH_CALL_IN_PROGRESS] output_index: int item_id: str -class FileSearchCallSearchingEvent(BaseLiteLLMOpenAIResponseObject): +class FileSearchCallSearchingEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.FILE_SEARCH_CALL_SEARCHING] output_index: int item_id: str -class FileSearchCallCompletedEvent(BaseLiteLLMOpenAIResponseObject): +class FileSearchCallCompletedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.FILE_SEARCH_CALL_COMPLETED] output_index: int item_id: str -class WebSearchCallInProgressEvent(BaseLiteLLMOpenAIResponseObject): +class WebSearchCallInProgressEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.WEB_SEARCH_CALL_IN_PROGRESS] output_index: int item_id: str -class WebSearchCallSearchingEvent(BaseLiteLLMOpenAIResponseObject): +class WebSearchCallSearchingEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.WEB_SEARCH_CALL_SEARCHING] output_index: int item_id: str -class WebSearchCallCompletedEvent(BaseLiteLLMOpenAIResponseObject): +class WebSearchCallCompletedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.WEB_SEARCH_CALL_COMPLETED] output_index: int item_id: str # MCP List Tools Events -class MCPListToolsInProgressEvent(BaseLiteLLMOpenAIResponseObject): +class MCPListToolsInProgressEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.MCP_LIST_TOOLS_IN_PROGRESS] sequence_number: int output_index: int item_id: str -class MCPListToolsCompletedEvent(BaseLiteLLMOpenAIResponseObject): +class MCPListToolsCompletedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.MCP_LIST_TOOLS_COMPLETED] sequence_number: int output_index: int item_id: str -class MCPListToolsFailedEvent(BaseLiteLLMOpenAIResponseObject): +class MCPListToolsFailedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.MCP_LIST_TOOLS_FAILED] sequence_number: int output_index: int @@ -2001,14 +2038,14 @@ class MCPListToolsFailedEvent(BaseLiteLLMOpenAIResponseObject): # MCP Call Events -class MCPCallInProgressEvent(BaseLiteLLMOpenAIResponseObject): +class MCPCallInProgressEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.MCP_CALL_IN_PROGRESS] sequence_number: int output_index: int item_id: str -class MCPCallArgumentsDeltaEvent(BaseLiteLLMOpenAIResponseObject): +class MCPCallArgumentsDeltaEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.MCP_CALL_ARGUMENTS_DELTA] output_index: int item_id: str @@ -2016,7 +2053,7 @@ class MCPCallArgumentsDeltaEvent(BaseLiteLLMOpenAIResponseObject): sequence_number: int -class MCPCallArgumentsDoneEvent(BaseLiteLLMOpenAIResponseObject): +class MCPCallArgumentsDoneEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.MCP_CALL_ARGUMENTS_DONE] output_index: int item_id: str @@ -2024,21 +2061,21 @@ class MCPCallArgumentsDoneEvent(BaseLiteLLMOpenAIResponseObject): sequence_number: int -class MCPCallCompletedEvent(BaseLiteLLMOpenAIResponseObject): +class MCPCallCompletedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.MCP_CALL_COMPLETED] sequence_number: int item_id: str output_index: int -class MCPCallFailedEvent(BaseLiteLLMOpenAIResponseObject): +class MCPCallFailedEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.MCP_CALL_FAILED] sequence_number: int item_id: str output_index: int -class ImageGenerationPartialImageEvent(BaseLiteLLMOpenAIResponseObject): +class ImageGenerationPartialImageEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.IMAGE_GENERATION_PARTIAL_IMAGE] partial_image_index: int b64_json: str @@ -2053,7 +2090,7 @@ class ErrorEventError(BaseLiteLLMOpenAIResponseObject): param: str | dict[str, object] | None = None -class ErrorEvent(BaseLiteLLMOpenAIResponseObject): +class ErrorEvent(BaseResponsesStreamEvent): type: Literal[ResponsesAPIStreamEvents.ERROR] sequence_number: int error: ErrorEventError | None = None @@ -2062,7 +2099,7 @@ class ErrorEvent(BaseLiteLLMOpenAIResponseObject): param: str | Mapping[str, object] | None = None -class GenericEvent(BaseLiteLLMOpenAIResponseObject): +class GenericEvent(BaseResponsesStreamEvent): type: str model_config = ConfigDict(extra="allow", protected_namespaces=()) @@ -2511,6 +2548,17 @@ class OpenAIRealtimeResponseUsage(TypedDict): output_token_details: NotRequired[ReadOnly[OpenAIRealtimeUsageTokenDetails]] +class OpenAIRealtimeTranslationDurationUsage(TypedDict): + type: ReadOnly[Literal["duration"]] + output_seconds: NotRequired[ReadOnly[float]] + input_seconds: NotRequired[ReadOnly[float]] + + +class OpenAIRealtimeTranslationClosedEvent(TypedDict): + type: ReadOnly[Literal["session.closed"]] + usage: ReadOnly[OpenAIRealtimeTranslationDurationUsage] + + class OpenAIRealtimeEventTypes(Enum): SESSION_CREATED = "session.created" # Beta delta event names @@ -2554,6 +2602,7 @@ OpenAIRealtimeEvents = ( | OpenAIRealtimeInputAudioTranscriptionCompleted | OpenAIRealtimeTranscriptionSessionCreated | OpenAIRealtimeErrorEvent + | OpenAIRealtimeTranslationClosedEvent ) OpenAIRealtimeStreamList = list[OpenAIRealtimeEvents] diff --git a/litellm/types/mcp_server/mcp_server_manager.py b/litellm/types/mcp_server/mcp_server_manager.py index 0d39b0a0616..1d3d5911eb1 100644 --- a/litellm/types/mcp_server/mcp_server_manager.py +++ b/litellm/types/mcp_server/mcp_server_manager.py @@ -23,6 +23,8 @@ from litellm.types.mcp import ( def _validate_mcp_protocol_metadata(value: dict[str, object]) -> dict[str, object]: if "protocol_version" in value: TypeAdapter[MCPUpstreamProtocol](MCPUpstreamProtocol).validate_python(value["protocol_version"]) + if "skip_tool_output_validation" in value: + TypeAdapter[bool](bool).validate_python(value["skip_tool_output_validation"], strict=True) return value @@ -297,6 +299,10 @@ class MCPServer(LiteLLMBaseModel): """ return self.oauth2_flow == "client_credentials" + @property + def skip_tool_output_validation(self) -> bool: + return (self.mcp_info or {}).get("skip_tool_output_validation") is True + @model_validator(mode="after") def resolve_protocol_version(self) -> Self: if "protocol_version" not in self.model_fields_set and self.mcp_info is not None: diff --git a/litellm/types/passthrough_endpoints/pass_through_endpoints.py b/litellm/types/passthrough_endpoints/pass_through_endpoints.py index 2f269dc87d9..b6bab77ab33 100644 --- a/litellm/types/passthrough_endpoints/pass_through_endpoints.py +++ b/litellm/types/passthrough_endpoints/pass_through_endpoints.py @@ -1,9 +1,11 @@ +from collections.abc import Mapping, Sequence from dataclasses import dataclass +from datetime import datetime from enum import Enum -from typing import Final, Protocol +from typing import Final, Literal, Protocol, TypeAlias from pydantic import Field -from typing_extensions import TypedDict +from typing_extensions import ReadOnly, TypedDict from litellm.types.llms.base import LiteLLMPydanticObjectBase @@ -28,6 +30,10 @@ LITELLM_PASS_THROUGH_ENDPOINT_MARKER: Final = "__litellm_pass_through_endpoint__ SETTLES_BACKGROUND_RESPONSE_KWARG: Final = "settles_background_response" +WebsocketUpstreamFrameKind: TypeAlias = Literal[ + "starts_turn", "ends_turn", "opens_session", "updates_session", "bills_usage", "refuses_turn", "relayed" +] + class BackgroundResponseSettlement(str, Enum): SETTLES = "settles" @@ -63,7 +69,7 @@ class PassthroughStandardLoggingPayload(TypedDict, total=False): """ The body of the request """ - response_body: dict | None # only tracked for non-streaming responses + response_body: dict | Sequence[Mapping[str, object]] | None # only tracked for non-streaming responses """ The body of the response """ @@ -75,6 +81,8 @@ class PassthroughStandardLoggingPayload(TypedDict, total=False): Optional field, we use this for cost tracking only if it's set. """ + end_time: ReadOnly[datetime] + @dataclass(frozen=True, slots=True) class WebSocketSessionUsage: diff --git a/litellm/types/proxy/claude_code_endpoints.py b/litellm/types/proxy/claude_code_endpoints.py index 19e40aa5c5d..5d8479b8ce1 100644 --- a/litellm/types/proxy/claude_code_endpoints.py +++ b/litellm/types/proxy/claude_code_endpoints.py @@ -2,9 +2,10 @@ Claude Code Marketplace endpoint types for LiteLLM Proxy """ +from datetime import datetime from typing import Final, Literal, TypeAlias -from pydantic import AliasChoices, Field, TypeAdapter, model_validator +from pydantic import AliasChoices, ConfigDict, Field, TypeAdapter, model_validator from litellm.types.llms.base import LiteLLMBaseModel @@ -27,21 +28,12 @@ class PluginOwner(LiteLLMBaseModel): email: str | None = Field(None, description="Owner email") -class PluginSpec(LiteLLMBaseModel): +class PluginMetadata(LiteLLMBaseModel): """Mutable fields shared by plugin create and update requests.""" - source: dict[str, str] = Field( - ..., - description=( - "Plugin source reference. Supported formats:\n" - "- GitHub: {'source': 'github', 'repo': 'org/repo'}\n" - "- Git URL: {'source': 'url', 'url': 'https://github.com/org/repo.git'}\n" - "- Git Subdir: {'source': 'git-subdir', 'url': 'https://github.com/org/repo.git', 'path': 'plugins/plugin-name'}\n" - "- Zip archive on any https host (e.g. S3): " - "{'source': 'archive', 'url': 'https://bucket.s3.amazonaws.com/plugin.zip', 'sha256': ''}" - ), - ) - version: str | None = Field("1.0.0", description="Semantic version") + model_config = ConfigDict(frozen=True) + + version: str | None = Field("1.0.0", description="Semantic version, defaults to 1.0.0 on creation") description: str | None = Field(None, description="Plugin description") author: PluginAuthor | None = Field(None, description="Plugin author") homepage: str | None = Field(None, description="Plugin homepage URL") @@ -75,6 +67,20 @@ class PluginSpec(LiteLLMBaseModel): } +class PluginSpec(PluginMetadata): + source: dict[str, str] = Field( + ..., + description=( + "Plugin source reference. Supported formats:\n" + "- GitHub: {'source': 'github', 'repo': 'org/repo'}\n" + "- Git URL: {'source': 'url', 'url': 'https://github.com/org/repo.git'}\n" + "- Git Subdir: {'source': 'git-subdir', 'url': 'https://github.com/org/repo.git', 'path': 'plugins/plugin-name'}\n" + "- Zip archive on any https host (e.g. S3): " + "{'source': 'archive', 'url': 'https://bucket.s3.amazonaws.com/plugin.zip', 'sha256': ''}" + ), + ) + + class RegisterPluginRequest(PluginSpec): """ Request body for registering a plugin in the marketplace. @@ -90,17 +96,24 @@ class RegisterPluginRequest(PluginSpec): ) +class UploadPluginRequest(PluginMetadata): + name: str = Field(..., pattern=r"^[a-z0-9-]+$", description="Skill name (kebab-case)") + + class UpdatePluginRequest(PluginSpec): """ Request body for replacing an existing plugin. The plugin name is the resource identity and is supplied as the path parameter, so it cannot be changed here. This is a full replace: omitted - fields reset to their defaults, so version is cleared rather than - defaulting to the create-time "1.0.0". + fields reset to their defaults, except version which automatically increments + the published patch version when omitted or null. """ - version: str | None = Field(None, description="Semantic version; cleared if omitted") + version: str | None = Field(None, description="Explicit higher SemVer, or omit/null for an automatic patch bump") + expected_updated_at: datetime | None = Field( + None, description="Published updated_at read by the editor. A stale value returns 409", exclude=True + ) class PluginResponse(LiteLLMBaseModel): @@ -141,6 +154,7 @@ class PluginListItem(LiteLLMBaseModel): enabled: bool created_at: str | None updated_at: str | None + has_agent_skill_metadata: bool = Field(default=False, exclude=True) class ListPluginsResponse(LiteLLMBaseModel): diff --git a/litellm/types/proxy/guardrails/guardrail_hooks/tool_permission.py b/litellm/types/proxy/guardrails/guardrail_hooks/tool_permission.py index 6f521d1fd1b..99ff7953ee2 100644 --- a/litellm/types/proxy/guardrails/guardrail_hooks/tool_permission.py +++ b/litellm/types/proxy/guardrails/guardrail_hooks/tool_permission.py @@ -16,7 +16,7 @@ class ToolPermissionRule(LiteLLMBaseModel): id: str = Field(description="Unique identifier for the rule") tool_name: str | None = Field( default=None, - description="Regex pattern applied to the tool's function name", + description="Regex pattern applied to the tool's name, or to its type when the tool has no name", ) tool_type: str | None = Field( default=None, diff --git a/litellm/types/proxy/model_deprecation.py b/litellm/types/proxy/model_deprecation.py index 8645f89b65d..37c49d737af 100644 --- a/litellm/types/proxy/model_deprecation.py +++ b/litellm/types/proxy/model_deprecation.py @@ -1,9 +1,10 @@ from __future__ import annotations from datetime import date, datetime +from enum import Enum from typing import Final, Literal -from pydantic import Field +from pydantic import ConfigDict, Field from litellm.types.llms.base import LiteLLMBaseModel @@ -16,8 +17,17 @@ DEPRECATION_IDLE_POLL_SECONDS: Final = 30 DeprecationStatus = Literal["upcoming", "imminent", "deprecated"] +class SuccessorModelSource(str, Enum): + MODEL_COST_MAP = "model_cost_map" + DEPLOYMENT_CONFIG = "deployment_config" + + class ModelDeprecationInfo(LiteLLMBaseModel): model_name: str = Field(description="The public name of the model on the proxy (model_group).") + team_public_model_name: str | None = Field( + default=None, + description="The model name visible to the team, when configured.", + ) litellm_model: str | None = Field( default=None, description="The underlying litellm model string the deprecation date is sourced from.", @@ -34,7 +44,18 @@ class ModelDeprecationInfo(LiteLLMBaseModel): litellm_provider: str | None = Field(default=None, description="The provider this model belongs to.") successor_model: str | None = Field( default=None, - description=("The model to migrate to, as set in model_info.successor_model on the deployment."), + description=( + "The model to migrate to: model_info.successor_model on the deployment when set, " + "else the successor_model the cost map names for the deprecated model." + ), + ) + + successor_model_source: SuccessorModelSource | None = Field( + default=None, + description="Whether the recommended successor comes from the model cost map or deployment configuration.", + ) + deprecation_source: str | None = Field( + default=None, description="Provider deprecation notice linked by the selected model cost-map entry." ) @@ -56,3 +77,38 @@ class ModelDeprecationResponse(LiteLLMBaseModel): ) warn_within_days: int = Field(description="The window (in days) used to bucket 'imminent' models.") checked_at: datetime = Field(description="UTC timestamp when the deprecation snapshot was generated.") + + +class DeprecationAlertStatus(str, Enum): + OPEN = "open" + RESOLVED = "resolved" + DISMISSED = "dismissed" + + +class DeprecationAlertUpdate(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + model: str = Field(min_length=1, max_length=1024) + deprecation_date: date + status: DeprecationAlertStatus + last_seen_date: date + last_seen_requests: int = Field(ge=0) + + +class DeprecationAlertState(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + model: str + deprecation_date: date + status: DeprecationAlertStatus = DeprecationAlertStatus.OPEN + last_seen_date: date | None = None + last_seen_requests: int = 0 + updated_at: datetime | None = None + updated_by: str | None = None + + +class DeprecationTagUsage(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + api_key: str + tag: str diff --git a/litellm/types/proxy/skill_hub.py b/litellm/types/proxy/skill_hub.py new file mode 100644 index 00000000000..d575defcda7 --- /dev/null +++ b/litellm/types/proxy/skill_hub.py @@ -0,0 +1,165 @@ +from collections.abc import Mapping +from datetime import datetime +from typing import Literal, TypeAlias + +from pydantic import ConfigDict, Field + +from litellm.models.skill_submission import SubmissionOperation, SubmissionStatus +from litellm.types.llms.base import LiteLLMBaseModel + + +class SkillHubSkill(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + id: str + name: str + description: str | None = None + version: str | None = None + updated_at: datetime | None = None + visibility: Literal["public", "private"] + source: Mapping[str, str] + download_url: str | None = None + content_url: str | None = None + domain: str | None = None + namespace: str | None = None + keywords: tuple[str, ...] | None = None + download_count: int | None = Field( + None, description="Gateway ZIP downloads, included in proxy-admin catalog listings" + ) + + +class SkillHubList(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + skills: tuple[SkillHubSkill, ...] + count: int + next_offset: int | None + + +class ImportSkillRequest(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + url: str = Field(description="Public skills.sh skill URL or GitHub repository URL") + skill: str | None = Field(None, description="Skill name to select when a repository contains several skills") + ref: str = Field("HEAD", description="Git commit, tag or branch to import") + path: str | None = Field(None, description="Repository-relative skill directory") + version: str | None = Field(None, description="Semantic version, or omit/null to start at 1.0.0") + + +class SkillHubMetadata(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + description: str | None = Field(None, max_length=1024) + version: str | None = Field(None, description="Explicit higher SemVer, or omit/null for an automatic patch bump") + expected_updated_at: datetime | None = Field( + None, description="Published updated_at read by the editor. A stale value returns 409", exclude=True + ) + domain: str | None = None + namespace: str | None = None + keywords: tuple[str, ...] | None = None + + +class SkillHubPublication(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + +class SkillHubVersion(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + id: str + version: str | None + description: str | None + manifest: Mapping[str, object] + published_at: datetime | None + published_by: str | None + content_kind: Literal["stored_archive", "source_reference"] + download_url: str | None + + +class SkillHubVersions(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + versions: tuple[SkillHubVersion, ...] + next_offset: int | None + + +class SkillHubAgentSkill(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + name: str + description: str + digest: str + origin: str | None + + +class SkillHubProposal(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + name: str + description: str | None + version: str | None + domain: str | None = None + namespace: str | None = None + keywords: tuple[str, ...] | None = None + source: Mapping[str, str] + agent_skill: SkillHubAgentSkill | None = None + + +class SkillHubPendingSkill(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + status: Literal["pending_review"] = "pending_review" + action: Literal["submitted"] = "submitted" + submission_id: str + proposal: SkillHubProposal + + +SkillHubMutationResponse: TypeAlias = SkillHubSkill | SkillHubPendingSkill + + +class SkillHubSubmission(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + id: str + skill_name: str + operation: SubmissionOperation + status: SubmissionStatus + proposal: SkillHubProposal + has_archive: bool + submitted_by: str + created_at: datetime + base_skill_id: str | None + base_updated_at: datetime | None + reviewed_by: str | None + reviewed_at: datetime | None + rejection_reason: str | None + + +class SkillHubSubmissionList(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + submissions: tuple[SkillHubSubmission, ...] + count: int + has_more: bool + + +class SkillHubSubmissionDetail(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + submission: SkillHubSubmission + current_skill: SkillHubSkill | None + + +class SkillHubReviewResponse(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + status: Literal["success"] = "success" + action: Literal["approved", "rejected"] + submission: SkillHubSubmission + skill: SkillHubSkill | None + + +class SkillHubRejection(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + reason: str | None = Field(None, max_length=2000) diff --git a/litellm/types/proxy/skill_scanning.py b/litellm/types/proxy/skill_scanning.py new file mode 100644 index 00000000000..19577c8a9ac --- /dev/null +++ b/litellm/types/proxy/skill_scanning.py @@ -0,0 +1,91 @@ +from datetime import datetime +from typing import Annotated, Final, Literal +from urllib.parse import urlsplit + +from pydantic import BaseModel, ConfigDict, Field, field_validator + + +class SkillScannerConfig(BaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + endpoint: str = Field(max_length=2048, description="External scanner's authenticated POST endpoint") + api_key_env: str = Field( + pattern=r"^[A-Za-z_][A-Za-z0-9_]*$", description="Environment secret name for scanner auth" + ) + use_llm: bool = False + timeout_seconds: int = Field(default=180, ge=10, le=600) + + @field_validator("endpoint") + @classmethod + def validate_endpoint(cls, value: str) -> str: + parsed: Final = urlsplit(value) + if ( + not parsed.hostname + or parsed.username is not None + or parsed.password is not None + or parsed.query + or parsed.fragment + or not ( + parsed.scheme == "https" + or (parsed.scheme == "http" and parsed.hostname in {"127.0.0.1", "::1", "localhost"}) + ) + ): + raise ValueError( + "Scanner endpoint must use HTTPS without credentials, query or fragment (HTTP loopback allowed)" + ) + return value + + +class SkillScanFinding(BaseModel): + model_config = ConfigDict(frozen=True, extra="ignore") + + rule_id: str = Field(max_length=200) + severity: Literal["LOW", "MEDIUM", "HIGH", "CRITICAL"] + message: str = Field(max_length=8000) + file: str = Field(max_length=2048) + start_line: int | None = Field(default=None, ge=1) + explanation: str | None = Field(default=None, max_length=8000) + remediation: str | None = Field(default=None, max_length=8000) + + +class SkillScanReport(BaseModel): + model_config = ConfigDict(frozen=True, extra="ignore") + + scanner_version: str = Field(min_length=1, max_length=100) + complete: bool + scan_mode: Literal["static-only", "static+llm"] + risk_score: int = Field(ge=0, le=100) + findings: tuple[SkillScanFinding, ...] = Field(max_length=500) + limitations: tuple[Annotated[str, Field(max_length=2000)], ...] = Field(default=(), max_length=100) + + +class SkillScan(BaseModel): + model_config = ConfigDict(frozen=True) + + id: str + status: Literal["running", "completed", "failed"] + requested_by: str + started_at: datetime + expires_at: datetime + completed_at: datetime | None = None + archive_sha256: str | None = None + report: SkillScanReport | None = None + error: str | None = None + + def at(self, now: datetime) -> "SkillScan": + if self.status == "running" and self.expires_at <= now: + return self.model_copy( + update={"status": "failed", "error": "Scan timed out or was interrupted. Try scanning again."} + ) + return self + + +class SkillScanRequest(BaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + +class SkillScanResponse(BaseModel): + model_config = ConfigDict(frozen=True) + + configured: bool + scan: SkillScan | None diff --git a/litellm/types/realtime.py b/litellm/types/realtime.py index 6da73982291..4a9b4228bc8 100644 --- a/litellm/types/realtime.py +++ b/litellm/types/realtime.py @@ -1,3 +1,4 @@ +from collections.abc import Mapping, Sequence from typing import Any, Literal from pydantic import ConfigDict @@ -66,6 +67,41 @@ class RealtimeExpiresAfter(LiteLLMBaseModel): seconds: int | None = None +class RealtimeAudioTranscriptionConfig(LiteLLMBaseModel): + model_config = ConfigDict(extra="allow", frozen=True) + + model: str | None = None + delay: str | None = None + keywords: Sequence[str] | None = None + language: str | None = None + languages: Sequence[str] | None = None + prompt: str | None = None + + +class RealtimeAudioInputConfig(LiteLLMBaseModel): + model_config = ConfigDict(extra="allow", frozen=True) + + format: str | Mapping[str, object] | None = None + noise_reduction: Mapping[str, object] | None = None + transcription: RealtimeAudioTranscriptionConfig | None = None + turn_detection: Mapping[str, object] | None = None + + +class RealtimeAudioOutputConfig(LiteLLMBaseModel): + model_config = ConfigDict(extra="allow", frozen=True) + + format: str | Mapping[str, object] | None = None + language: str | None = None + voice: str | Mapping[str, object] | None = None + + +class RealtimeSessionAudioConfig(LiteLLMBaseModel): + model_config = ConfigDict(extra="allow", frozen=True) + + input: RealtimeAudioInputConfig | None = None + output: RealtimeAudioOutputConfig | None = None + + class RealtimeSessionConfig(LiteLLMBaseModel): """ Session configuration nested inside the client_secrets request body. @@ -75,12 +111,12 @@ class RealtimeSessionConfig(LiteLLMBaseModel): Extra/unknown fields are passed through unchanged. """ - model_config = ConfigDict(extra="allow") + model_config = ConfigDict(extra="allow", frozen=True) type: str | None = None model: str | None = None instructions: str | None = None - audio: dict[str, object] | None = None + audio: RealtimeSessionAudioConfig | None = None include: list[str] | None = None max_output_tokens: int | str | None = None output_modalities: list[str] | None = None @@ -129,17 +165,20 @@ class RealtimeTranscriptionSessionRequest(LiteLLMBaseModel): unchanged to the provider. """ - model_config = ConfigDict(extra="allow") + model_config = ConfigDict(extra="allow", frozen=True) # LiteLLM-only routing hint — stripped before forwarding upstream. model: str | None = None input_audio_transcription: dict[str, Any] | None = None + audio: RealtimeSessionAudioConfig | None = None def resolved_model(self) -> str | None: if self.model: return self.model if self.input_audio_transcription: return self.input_audio_transcription.get("model") + if self.audio and self.audio.input and self.audio.input.transcription: + return self.audio.input.transcription.model return None @@ -151,7 +190,7 @@ class RealtimeTranscriptionSessionResponse(LiteLLMBaseModel): ephemeral key. Unknown fields pass through unchanged. """ - model_config = ConfigDict(extra="allow") + model_config = ConfigDict(extra="allow", frozen=True) client_secret: dict[str, object] | None = None diff --git a/litellm/types/router.py b/litellm/types/router.py index 41a986837da..3363d113fc7 100644 --- a/litellm/types/router.py +++ b/litellm/types/router.py @@ -1061,6 +1061,7 @@ class ModelGroupInfo(LiteLLMBaseModel): supports_vision: bool = Field(default=False) supports_web_search: bool = Field(default=False) supports_url_context: bool = Field(default=False) + supports_continuation: bool = Field(default=False) supports_reasoning: bool = Field(default=False) supports_function_calling: bool = Field(default=False) supports_fast_mode: bool = Field(default=False) @@ -1153,9 +1154,9 @@ class CustomRoutingStrategyBase: self, model: str, messages: list[dict[str, str]] | None = None, - input: str | list | None = None, + input: str | list[object] | None = None, specific_deployment: bool | None = False, - request_kwargs: dict | None = None, + request_kwargs: dict[str, object] | None = None, ) -> None: """ Asynchronously retrieves the available deployment based on the given parameters. @@ -1176,9 +1177,9 @@ class CustomRoutingStrategyBase: self, model: str, messages: list[dict[str, str]] | None = None, - input: str | list | None = None, + input: str | list[object] | None = None, specific_deployment: bool | None = False, - request_kwargs: dict | None = None, + request_kwargs: dict[str, object] | None = None, ) -> None: """ Synchronously retrieves the available deployment based on the given parameters. diff --git a/litellm/types/utils.py b/litellm/types/utils.py index 8a16c7dd4bd..2563f5e02cf 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -225,9 +225,11 @@ class ProviderSpecificModelInfo(TypedDict, total=False): supports_legacy_thinking: ReadOnly[bool | None] thinking_always_on: ReadOnly[bool | None] supports_between_tools_thinking: ReadOnly[bool | None] + thinking_on_by_default: ReadOnly[bool | None] supports_tool_search: bool | None supports_mid_conversation_system: bool | None supports_url_context: bool | None + supports_continuation: ReadOnly[bool | None] supports_none_reasoning_effort: bool | None supports_minimal_reasoning_effort: bool | None supports_low_reasoning_effort: bool | None @@ -247,6 +249,9 @@ class ProviderSpecificModelInfo(TypedDict, total=False): bedrock_converse_supports_strict_tools: bool | None supports_regex_lookaround: ReadOnly[bool | None] token_count_framing: ReadOnly[int | None] + token_count_tool_framing: ReadOnly[int | None] + token_count_responses_framing: ReadOnly[int | None] + token_count_responses_tool_framing: ReadOnly[int | None] token_count_model: ReadOnly[TokenCountModelInfo | None] token_count_tokenizer: ReadOnly[TokenCountTokenizer | None] @@ -380,6 +385,10 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): input_cost_per_character: float | None # only for vertex ai models input_cost_per_audio_token: float | None input_cost_per_audio_token_flex: ReadOnly[float | None] + input_cost_per_audio_token_above_200k_tokens: ReadOnly[float | None] + input_cost_per_audio_token_above_200k_tokens_flex: ReadOnly[float | None] + input_cost_per_audio_token_above_200k_tokens_priority: ReadOnly[float | None] + input_cost_per_audio_token_above_200k_tokens_batches: ReadOnly[float | None] input_cost_per_audio_token_priority: ReadOnly[float | None] input_cost_per_token_above_128k_tokens: float | None # only for vertex ai models input_cost_per_token_above_200k_tokens: float | None # only for vertex ai gemini-2.5-pro models @@ -405,10 +414,12 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): input_cost_per_token_batches: float | None input_cost_per_video_token_batches: ReadOnly[float | None] input_cost_per_token_above_200k_tokens_batches: ReadOnly[float | None] + input_cost_per_token_above_200k_tokens_flex: ReadOnly[float | None] input_cost_per_token_above_100k_tokens_batches: ReadOnly[float | None] input_cost_per_token_above_272k_tokens_batches: ReadOnly[float | None] output_cost_per_token_batches: float | None output_cost_per_token_above_200k_tokens_batches: ReadOnly[float | None] + output_cost_per_token_above_200k_tokens_flex: ReadOnly[float | None] output_cost_per_token_above_100k_tokens_batches: ReadOnly[float | None] output_cost_per_token_above_272k_tokens_batches: ReadOnly[float | None] output_cost_per_token: Required[float | None] @@ -422,6 +433,9 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): regional_processing_uplift_multiplier_us: ( float | None ) # OpenAI US data-residency uplift multiplier applied to all token costs (e.g. 1.10 = +10%) + fedramp_uplift_multiplier: ReadOnly[ + float | None + ] # OpenAI FedRAMP endpoint (gov.api.openai.com) uplift multiplier applied to all token costs (e.g. 1.10 = +10%) regional_endpoint_uplift_multiplier: ReadOnly[ float | None ] # Vertex AI non-global (regional) endpoint uplift multiplier applied to all token costs (e.g. 1.10 = +10%) @@ -441,6 +455,7 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): output_cost_per_pixel: ReadOnly[float | None] output_cost_per_image_token: float | None output_cost_per_image_token_batches: ReadOnly[float | None] + output_cost_per_image_token_priority: ReadOnly[float | None] output_cost_per_video_token: float | None # for gemini omni models with video output output_vector_size: int | None output_cost_per_reasoning_token: float | None @@ -551,6 +566,11 @@ class CallTypes(str, Enum): aextraction = "aextraction" arealtime = "_arealtime" aresponses_websocket = "_aresponses_websocket" + acreate_realtime_client_secret = "acreate_realtime_client_secret" + arealtime_calls = "arealtime_calls" + acreate_realtime_transcription_session = "acreate_realtime_transcription_session" + acreate_realtime_translation_client_secret = "acreate_realtime_translation_client_secret" + arealtime_translation_calls = "arealtime_translation_calls" create_batch = "create_batch" acreate_batch = "acreate_batch" aretrieve_batch = "aretrieve_batch" @@ -791,6 +811,8 @@ CallTypesLiteral = Literal[ "acreate_realtime_client_secret", "arealtime_calls", "acreate_realtime_transcription_session", + "acreate_realtime_translation_client_secret", + "arealtime_translation_calls", ] MCP_GUARDRAIL_CALL_TYPES: Final[frozenset[str]] = frozenset( @@ -799,6 +821,10 @@ MCP_GUARDRAIL_CALL_TYPES: Final[frozenset[str]] = frozenset( # Mapping of API routes to their corresponding call types API_ROUTE_TO_CALL_TYPES: Final[Mapping[str, Sequence[CallTypes]]] = { + "/v1/realtime/translations/client_secrets": (CallTypes.acreate_realtime_translation_client_secret,), + "/realtime/translations/client_secrets": (CallTypes.acreate_realtime_translation_client_secret,), + "/v1/realtime/translations/calls": (CallTypes.arealtime_translation_calls,), + "/realtime/translations/calls": (CallTypes.arealtime_translation_calls,), # Chat Completions "/chat/completions": [CallTypes.acompletion, CallTypes.completion], "/v1/chat/completions": [CallTypes.acompletion, CallTypes.completion], @@ -1117,9 +1143,11 @@ API_ROUTE_TO_CALL_TYPES: Final[Mapping[str, Sequence[CallTypes]]] = { "/v1/responses/{response_id}/input_items": (CallTypes.alist_input_items,), "/openai/v1/responses/{response_id}/input_items": (CallTypes.alist_input_items,), # Realtime API - "/realtime": [CallTypes.arealtime], - "/v1/realtime": [CallTypes.arealtime], - "/openai/v1/realtime": [CallTypes.arealtime], + "/realtime": (CallTypes.arealtime,), + "/v1/realtime": (CallTypes.arealtime,), + "/openai/v1/realtime": (CallTypes.arealtime,), + "/realtime/translations": (CallTypes.arealtime,), + "/v1/realtime/translations": (CallTypes.arealtime,), "/live/sessions": (CallTypes.arealtime,), "/v1/live/sessions": (CallTypes.arealtime,), "/openai/v1/live/sessions": (CallTypes.arealtime,), @@ -2948,9 +2976,19 @@ class TranscriptionUsageTokensObject(LiteLLMBaseModel): input_token_details: TranscriptionUsageInputTokenDetailsObject | None = None +class TranscriptionDetectedLanguage(LiteLLMBaseModel): + model_config = ConfigDict(frozen=True) + + code: str + + +_DETECTED_LANGUAGES: Final = TypeAdapter(tuple[TranscriptionDetectedLanguage, ...]) + + class TranscriptionResponse(OpenAIObject): text: str | None = None usage: TranscriptionUsageDurationObject | TranscriptionUsageTokensObject | None = None + languages: Sequence[TranscriptionDetectedLanguage] | None = None _hidden_params: dict = {} _response_headers: dict | None = None @@ -2963,8 +3001,28 @@ class TranscriptionResponse(OpenAIObject): def hidden_params(self, hidden_params: dict[str, object]) -> None: # mutable-ok: API requires mutation self._hidden_params = hidden_params - def __init__(self, text=None) -> None: - super().__init__(text=text) + def __init__( + self, + text: str | None = None, + usage: TranscriptionUsageDurationObject | TranscriptionUsageTokensObject | Mapping[str, object] | None = None, + languages: Sequence[TranscriptionDetectedLanguage | Mapping[str, object]] | None = None, + **kwargs: object, # kwargs-ok: OpenAI-compatible responses preserve provider extension fields + ) -> None: + super().__init__( + text=text, usage=usage, languages=TranscriptionResponse.detected_languages(languages), **kwargs + ) + if self.languages is None: + del self.languages + + @staticmethod + def detected_languages(value: object) -> tuple[TranscriptionDetectedLanguage, ...] | None: + try: + return _DETECTED_LANGUAGES.validate_python(value, from_attributes=True) + except ValidationError: + return None + + def set_audio_transcription_duration(self, duration: float) -> None: + self._hidden_params["audio_transcription_duration"] = duration def __contains__(self, key) -> bool: # Define custom behavior for the 'in' operator @@ -4127,6 +4185,10 @@ class CustomPricingLiteLLMParams(MirroredPricingParams): input_cost_per_character_above_128k_tokens: float | None = None input_cost_per_audio_token: float | None = None input_cost_per_audio_token_flex: float | None = None + input_cost_per_audio_token_above_200k_tokens: float | None = None + input_cost_per_audio_token_above_200k_tokens_flex: float | None = None + input_cost_per_audio_token_above_200k_tokens_priority: float | None = None + input_cost_per_audio_token_above_200k_tokens_batches: float | None = None input_cost_per_audio_token_priority: float | None = None input_cost_per_token_cache_hit: float | None = None input_cost_per_token_above_128k_tokens: float | None = None @@ -4137,6 +4199,7 @@ class CustomPricingLiteLLMParams(MirroredPricingParams): input_cost_per_token_above_272k_tokens_flex: float | None = None input_cost_per_token_above_272k_tokens_ultrafast: float | None = None input_cost_per_token_above_200k_tokens_batches: float | None = None + input_cost_per_token_above_200k_tokens_flex: float | None = None input_cost_per_token_above_100k_tokens_batches: float | None = None input_cost_per_token_above_272k_tokens_batches: float | None = None input_cost_per_query: float | None = None @@ -4166,12 +4229,14 @@ class CustomPricingLiteLLMParams(MirroredPricingParams): output_cost_per_token_above_272k_tokens_flex: float | None = None output_cost_per_token_above_272k_tokens_ultrafast: float | None = None output_cost_per_token_above_200k_tokens_batches: float | None = None + output_cost_per_token_above_200k_tokens_flex: float | None = None output_cost_per_token_above_100k_tokens_batches: float | None = None output_cost_per_token_above_272k_tokens_batches: float | None = None output_cost_per_character_above_128k_tokens: float | None = None output_cost_per_image: float | None = None output_cost_per_image_token: float | None = None output_cost_per_image_token_batches: float | None = None + output_cost_per_image_token_priority: float | None = None output_cost_per_video_token: float | None = None output_cost_per_reasoning_token: float | None = None output_cost_per_reasoning_token_flex: float | None = None @@ -4198,6 +4263,7 @@ class CustomPricingLiteLLMParams(MirroredPricingParams): annotation_cost_per_page_batches: float | None = None regional_processing_uplift_multiplier_eu: float | None = None regional_processing_uplift_multiplier_us: float | None = None + fedramp_uplift_multiplier: float | None = None regional_endpoint_uplift_multiplier: float | None = None @classmethod @@ -4232,12 +4298,25 @@ DEPLOYMENT_SCOPED_CAPABILITY_FIELDS: Final[frozenset[str]] = frozenset( "supports_assistant_prefill", "supports_bedrock_native_structured_output", "supports_pdf_input", + "supports_continuation", "reasoning_modes", "reasoning_contexts", } ) -DEPLOYMENT_SCOPED_TOKEN_COUNT_FIELDS: Final[frozenset[str]] = frozenset({"token_count_framing", "token_count_model"}) +DEPLOYMENT_SCOPED_TOKEN_LIMIT_FIELDS: Final[frozenset[str]] = frozenset( + {"max_input_tokens", "max_output_tokens", "max_tokens"} +) + +DEPLOYMENT_SCOPED_TOKEN_COUNT_FIELDS: Final[frozenset[str]] = frozenset( + { + "token_count_framing", + "token_count_tool_framing", + "token_count_responses_framing", + "token_count_responses_tool_framing", + "token_count_model", + } +) SHARED_BACKEND_MODEL_INFO_FIELDS: Final[frozenset[str]] = ( frozenset(ModelInfoBase.__required_keys__ | ModelInfoBase.__optional_keys__) @@ -4344,6 +4423,7 @@ bedrock_batch_litellm_params: Final = BEDROCK_BATCH_KWARG_NAMES TRUSTED_CALLBACK_VARS_FIELD: Final = _litellm_params.TRUSTED_CALLBACK_VARS_FIELD ADDRESSED_RESPONSE_ID_FIELD: Final = _litellm_params.ADDRESSED_RESPONSE_ID_FIELD +ADDRESSED_COMPARISON_RESPONSE_ID_FIELD: Final = _litellm_params.ADDRESSED_COMPARISON_RESPONSE_ID_FIELD anthropic_wif_litellm_params: Final = tuple(sorted(ANTHROPIC_WIF_KWARGS_KEYS)) openai_wif_litellm_params: Final = tuple(sorted(OPENAI_WIF_KWARGS_KEYS)) @@ -4567,10 +4647,12 @@ class LlmProviders(str, Enum): CLF_AI_GATEWAY = "clf_ai_gateway" PERPLEXITY = "perplexity" TYPESAFE = "typesafe" + PARALLEL_AI = "parallel_ai" NACE = "nace" STRANDS_DECIDER = "strands_decider" LAYA = "laya" BESPOKE = "bespoke" + EMPIRIOLABS = "empiriolabs" EU_JEV = "eu_jev" MISTRAL = "mistral" MILVUS = "milvus" @@ -4699,6 +4781,7 @@ class LlmProviders(str, Enum): SAIL = "sail" REKA = "reka" STREAMLAKE = "streamlake" + WALLY = "wally" LITELLM_AGENT = "litellm_agent" CURSOR = "cursor" BEDROCK_MANTLE = "bedrock_mantle" @@ -5184,11 +5267,13 @@ class DataResidency(Enum): Inferred from the OpenAI api_base host (eu.api.openai.com -> EU, us.api.openai.com -> US). Used to apply the regional-processing cost uplift (see ``regional_processing_uplift_multiplier_`` - on ModelInfo). + on ModelInfo). gov.api.openai.com maps to FEDRAMP, which applies + ``fedramp_uplift_multiplier`` instead. """ US = "us" EU = "eu" + FEDRAMP = "fedramp" LLMResponseTypes = ( diff --git a/litellm/types/videos/utils.py b/litellm/types/videos/utils.py index 0fc2b8ede1b..240e36ecdf6 100644 --- a/litellm/types/videos/utils.py +++ b/litellm/types/videos/utils.py @@ -17,10 +17,11 @@ VIDEO_ID_PREFIX: Final = "video_" VIDEO_ID_SERVED_MODEL_PREFIX: Final = "served_model:" VIDEO_ID_DEPLOYMENT_PREFIX: Final = "deployment_id:" VIDEO_ID_REQUESTED_MODEL_PREFIX: Final = "requested_model:" -VIDEO_ID_CALL_TYPES: Final = frozenset( +VIDEO_STATUS_CALL_TYPES: Final = frozenset({"avideo_status", "video_status"}) +VIDEO_COST_REQUEST_ID_SUFFIX: Final = "_video_cost" +POLLED_VIDEO_STATUS_KWARG: Final = "polled_video_status" +VIDEO_ID_CALL_TYPES: Final = VIDEO_STATUS_CALL_TYPES | frozenset( { - "avideo_status", - "video_status", "avideo_content", "video_content", "avideo_remix", @@ -31,6 +32,12 @@ VIDEO_ID_CALL_TYPES: Final = frozenset( "video_extension", } ) + + +def is_video_status_call_type(call_type: object) -> bool: + return isinstance(call_type, str) and call_type in VIDEO_STATUS_CALL_TYPES + + CHARACTER_ID_PREFIX: Final = "character_" CHARACTER_ID_TEMPLATE: Final = "litellm:custom_llm_provider:{};model_id:{};character_id:{}" @@ -94,6 +101,27 @@ def _trailing_part(parts: Sequence[str], prefix: str) -> str | None: return next((part.removeprefix(prefix) or None for part in parts[3:] if part.startswith(prefix)), None) +def _decoded_video_id_payload(encoded_video_id: str) -> str | None: + if not encoded_video_id.startswith(VIDEO_ID_PREFIX): + return None + try: + decoded_id: Final = base64.b64decode( + _add_base64_padding(encoded_video_id.removeprefix(VIDEO_ID_PREFIX)).encode("utf-8") + ).decode("utf-8") + except ValueError as e: + verbose_logger.debug("Error decoding video_id '%s': %s", encoded_video_id, e) + return None + return decoded_id if ";" in decoded_id else None + + +def canonical_video_id(video_id: str) -> str: + """One spelling per video, since a client may poll a LiteLLM video id with or without its base64 padding.""" + payload: Final = _decoded_video_id_payload(video_id) + if payload is None: + return video_id + return f"{VIDEO_ID_PREFIX}{base64.b64encode(payload.encode('utf-8')).decode('utf-8')}" + + def decode_video_id_with_provider(encoded_video_id: str) -> DecodedVideoId: """Decode provider and model_id from encoded video_id.""" if not encoded_video_id: @@ -103,26 +131,8 @@ def decode_video_id_with_provider(encoded_video_id: str) -> DecodedVideoId: video_id=encoded_video_id, ) - if not encoded_video_id.startswith(VIDEO_ID_PREFIX): - return DecodedVideoId( - custom_llm_provider=None, - model_id=None, - video_id=encoded_video_id, - ) - - try: - cleaned_id = encoded_video_id.replace(VIDEO_ID_PREFIX, "") - cleaned_id = _add_base64_padding(cleaned_id) - decoded_id: Final = base64.b64decode(cleaned_id.encode("utf-8")).decode("utf-8") - except Exception as e: - verbose_logger.debug("Error decoding video_id '%s': %s", encoded_video_id, e) - return DecodedVideoId( - custom_llm_provider=None, - model_id=None, - video_id=encoded_video_id, - ) - - if ";" not in decoded_id: + decoded_id: Final = _decoded_video_id_payload(encoded_video_id) + if decoded_id is None: return DecodedVideoId( custom_llm_provider=None, model_id=None, diff --git a/litellm/utils.py b/litellm/utils.py index b0826f84006..53b02ebddac 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -83,6 +83,11 @@ from litellm.constants import ( PROVIDERS_THAT_AUTHENTICATE_ON_PROVIDER_INFO, TOOL_CHOICE_OBJECT_TOKEN_COUNT, ) +from litellm.litellm_core_utils.agentic_followup_failure import is_agentic_followup_failure +from litellm.litellm_core_utils.allowed_tools_tool_choice import ( + CHAT_ALLOWED_TOOLS_LAYOUT, + parse_chat_allowed_tools_tool_choice, +) from litellm.litellm_core_utils.core_helpers import ( bind_budget_reservation_to_callbacks, normalize_drop_params, @@ -98,7 +103,11 @@ from litellm.litellm_core_utils.model_retirement import is_hidden_as_retired from litellm.litellm_core_utils.offline_mode import is_offline_mode from litellm.litellm_core_utils.sensitive_data_masker import redact_credentials_in_payload from litellm.litellm_core_utils.tokenizer import strip_special_tokens -from litellm.litellm_core_utils.tool_fields import MalformedField, resolve_deployment_tool_fields +from litellm.litellm_core_utils.tool_fields import ( + MalformedField, + resolve_deployment_tool_fields, + tools_without_hosted_mcp, +) from litellm.rust_bridge import tokenizer as tokenizer_dispatch from litellm.rust_bridge.catalog import decision from litellm.rust_bridge.configuration import Decision @@ -459,6 +468,7 @@ if TYPE_CHECKING: ) from litellm.llms.cohere.common_utils import CohereModelInfo from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler + from litellm.llms.custom_llm import CustomLLM from litellm.types.llms.anthropic import ( ANTHROPIC_API_ONLY_HEADERS, AnthropicThinkingParam, @@ -1115,6 +1125,38 @@ def _is_streaming_response_for_correlation(result: object) -> bool: return isinstance(result, CustomStreamWrapper) +def _returns_requested_stream(kwargs: dict[str, object], call_type: CallTypes | str, result: object) -> bool: + if call_type in (CallTypes.transcription, CallTypes.atranscription): + return isinstance(result, (openai.Stream, openai.AsyncStream)) + return _is_streaming_request(kwargs=kwargs, call_type=call_type) + + +def _transcription_runs_unstreamed( + call_type: str, requested_kwargs: Mapping[str, object], call_kwargs: Mapping[str, object] +) -> bool: + from litellm.litellm_core_utils.audio_utils.transcription_streaming import transcription_stream_requested + + return ( + call_type == CallTypes.atranscription.value + and transcription_stream_requested(requested_kwargs.get("stream")) + and call_kwargs.get("stream") is False + ) + + +def _guardrail_view_of_requested_stream(call_kwargs: Mapping[str, object]) -> dict[str, object]: + from litellm.integrations.custom_guardrail import guardrail_request_data_with_streaming + + return guardrail_request_data_with_streaming(call_kwargs, is_streaming=True) + + +def _replayed_when_run_unstreamed(result: object, runs_unstreamed: bool) -> object: + from litellm.litellm_core_utils.audio_utils.transcription_streaming import GuardedTranscriptionReplay + + if not runs_unstreamed or not isinstance(result, TranscriptionResponse): + return result + return GuardedTranscriptionReplay(result) + + def _is_converted_stream_result(result: object) -> bool: from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper from litellm.responses.streaming_iterator import BaseResponsesAPIStreamingIterator @@ -1550,7 +1592,6 @@ def function_setup( applied_guardrails=applied_guardrails, supports_correlation_logging=is_async_call, ) - ## check if metadata is passed in litellm_params: Final[dict[str, object]] = {"api_base": ""} if "metadata" in kwargs: @@ -1595,7 +1636,6 @@ def dispatch_success_logging( is_litellm_internal_call: bool, ) -> None: if is_litellm_internal_call: - logging_obj.capture_usage_before_logging(result, start_time, end_time) return _schedule_async_success_logging( @@ -1634,14 +1674,9 @@ def _schedule_async_success_logging( if not logging_obj.claim_async_success_log(): return - if logging_obj.defer_async_logging and not is_completion_with_fallbacks: - logging_obj.capture_usage_before_logging(result, start_time, end_time, freeze_only=True) - def _enqueue_async_logging() -> None: from litellm.responses.streaming_iterator import spawn_logging_task - if not is_completion_with_fallbacks: - logging_obj.capture_usage_before_logging(result, start_time, end_time) if logging_obj.defer_async_logging: logging_obj.handle_sync_success_callbacks_for_async_calls( result=result, start_time=start_time, end_time=end_time @@ -1798,7 +1833,28 @@ async def async_pre_call_deployment_hook(kwargs: Mapping[str, object], call_type if result is not None: modified_kwargs = result - return modified_kwargs + return _unstreamed_when_post_call_guardrails_apply(modified_kwargs, typed_call_type) + + +def _unstreamed_when_post_call_guardrails_apply( + kwargs: dict[str, object], call_type: CallTypes | None +) -> dict[str, object]: + from litellm.litellm_core_utils.audio_utils.transcription_streaming import transcription_stream_requested + + if ( + call_type is not CallTypes.atranscription + or not transcription_stream_requested(kwargs.get("stream")) + or _deployment_provider(kwargs) not in (LlmProviders.OPENAI.value, LlmProviders.AZURE.value) + ): + return kwargs + streamed_request: Final = _guardrail_view_of_requested_stream(kwargs) + custom_guardrail_class: Final = _get_cached_custom_guardrail() + if not any( + isinstance(callback, custom_guardrail_class) and callback.runs_post_call_deployment_hook(streamed_request) + for callback in litellm.callbacks + ): + return kwargs + return {**kwargs, "stream": False} async def async_post_call_success_deployment_hook( @@ -2146,7 +2202,7 @@ def client(original_function): # MODEL CALL result = original_function(*args, **kwargs) end_time = datetime.datetime.now() - if _is_streaming_request(kwargs=kwargs, call_type=call_type) or _is_converted_stream_result(result): + if _returns_requested_stream(kwargs, call_type, result) or _is_converted_stream_result(result): if "complete_response" in kwargs and kwargs["complete_response"] is True: chunks = [] for idx, chunk in enumerate(result): @@ -2155,6 +2211,15 @@ def client(original_function): else: logging_obj.stream = True logging_obj.model_call_details["stream"] = True + if call_type == CallTypes.transcription.value and isinstance(result, openai.Stream): + from litellm.litellm_core_utils.audio_utils.transcription_streaming import ( + litellm_exception_mapper, + wrap_transcription_stream, + ) + + result = wrap_transcription_stream( + result, logging_obj, start_time, litellm_exception_mapper(logging_obj.model_call_details) + ) # RETURN RESULT update_response_metadata: _ResponseMetadataUpdater = litellm_utils.update_response_metadata update_response_metadata( @@ -2209,7 +2274,6 @@ def client(original_function): # LOG SUCCESS - handle streaming success logging in the _next_ object, remove `handle_success` once it's deprecated verbose_logger.info("Wrapper: Completed Call, calling success_handler") - logging_obj.capture_usage_before_logging(TypeAdapter(object).validate_python(result), start_time, end_time) if not is_internal_call.get(): # Copy the current context to propagate it to the background thread # This is essential for OpenTelemetry span context propagation @@ -2242,7 +2306,7 @@ def client(original_function): is_completion_litellm_router_call: Final = _is_litellm_router_call(kwargs, is_async=False) if ( - num_retries and not is_completion_litellm_router_call + num_retries and not is_completion_litellm_router_call and not is_agentic_followup_failure(e) ): # only enter this if call is not from litellm router/proxy. router has it's own logic for retrying if ( isinstance(e, openai.APIError) @@ -2276,7 +2340,7 @@ def client(original_function): is_responses_litellm_router_call: Final = _is_litellm_router_call(kwargs, is_async=False) if ( - num_retries and not is_responses_litellm_router_call + num_retries and not is_responses_litellm_router_call and not is_agentic_followup_failure(e) ): # only enter this if call is not from litellm router/proxy. router has it's own logic for retrying if ( isinstance(e, openai.APIError) @@ -2330,6 +2394,7 @@ def client(original_function): kwargs["litellm_logging_obj"] = logging_obj modified_kwargs: Final = await async_pre_call_deployment_hook(kwargs, call_type) + transcription_runs_unstreamed: Final = _transcription_runs_unstreamed(call_type, kwargs, modified_kwargs) if modified_kwargs is not None: kwargs = modified_kwargs @@ -2380,7 +2445,9 @@ def client(original_function): if _is_converted_stream_result(_caching_handler_response.cached_result): logging_obj.stream = True logging_obj.model_call_details["stream"] = True - return _caching_handler_response.cached_result + return _replayed_when_run_unstreamed( + _caching_handler_response.cached_result, transcription_runs_unstreamed + ) elif _caching_handler_response.embedding_all_elements_cache_hit is True: return _caching_handler_response.final_embedding_cached_response @@ -2443,7 +2510,7 @@ def client(original_function): raise end_time = datetime.datetime.now() - streaming_requested: Final = _is_streaming_request(kwargs=kwargs, call_type=call_type) + streaming_requested: Final = _returns_requested_stream(kwargs, call_type, result) if streaming_requested or _is_converted_stream_result(result): logging_obj.stream = True logging_obj.model_call_details["stream"] = True @@ -2457,6 +2524,15 @@ def client(original_function): chunks.append(chunk) return litellm.stream_chunk_builder(chunks, messages=kwargs.get("messages", None)) else: + if call_type == CallTypes.atranscription.value and isinstance(result, openai.AsyncStream): + from litellm.litellm_core_utils.audio_utils.transcription_streaming import ( + litellm_exception_mapper, + wrap_transcription_stream, + ) + + result = wrap_transcription_stream( + result, logging_obj, start_time, litellm_exception_mapper(logging_obj.model_call_details) + ) _update_response_metadata( result=result, logging_obj=logging_obj, @@ -2483,7 +2559,9 @@ def client(original_function): _call_type_enum: Final = _CALL_TYPE_ENUM_MAP.get(call_type) if _call_type_enum is not None: result = await async_post_call_success_deployment_hook( - request_data=call_kwargs, + request_data=_guardrail_view_of_requested_stream(call_kwargs) + if transcription_runs_unstreamed + else call_kwargs, response=result, call_type=_call_type_enum, ) @@ -2534,7 +2612,7 @@ def client(original_function): is_litellm_internal_call=_is_litellm_internal_call, ) - return result + return _replayed_when_run_unstreamed(result, transcription_runs_unstreamed) except Exception as e: traceback_exception: Final = traceback.format_exc() # Reuse the timestamp taken right when the deployment call itself failed, before @@ -2561,7 +2639,10 @@ def client(original_function): is_acompletion_litellm_router_call: Final = _is_litellm_router_call(kwargs, is_async=True) if ( - num_retries and not is_acompletion_litellm_router_call and not isinstance(e, ImportError) + num_retries + and not is_acompletion_litellm_router_call + and not isinstance(e, ImportError) + and not is_agentic_followup_failure(e) ): # only enter this if call is not from litellm router/proxy. router has it's own logic for retrying try: litellm.num_retries = None # set retries to None to prevent infinite loops @@ -2592,7 +2673,10 @@ def client(original_function): is_aresponses_litellm_router_call: Final = _is_litellm_router_call(kwargs, is_async=True) if ( - num_retries and not is_aresponses_litellm_router_call and not isinstance(e, ImportError) + num_retries + and not is_aresponses_litellm_router_call + and not isinstance(e, ImportError) + and not is_agentic_followup_failure(e) ): # only enter this if call is not from litellm router/proxy. router has it's own logic for retrying try: litellm.num_retries = None # set retries to None to prevent infinite loops @@ -3183,6 +3267,14 @@ def supports_url_context(model: str, custom_llm_provider: str | None = None) -> ) +def supports_continuation(model: str, custom_llm_provider: str | None = None) -> bool: + return supports_factory( + model=model, + custom_llm_provider=custom_llm_provider, + key="supports_continuation", + ) + + def supports_native_streaming(model: str, custom_llm_provider: str | None) -> bool: """ Check if the given model supports native streaming and return a boolean value. @@ -4134,6 +4226,54 @@ def _register_on_current_map( _runtime_registered_model_cost: Final[dict[str, dict[str, object]]] = {} # mutable-ok: replayed on reload +_runtime_registration_order: Final[dict[str, int]] = {} # mutable-ok: tells which of a row's registered names came last +_runtime_registered_names: Final[dict[str, tuple[str, ...]]] = {} # mutable-ok: names registered onto each live row +_REGISTRATION_TICKS: Final = itertools.count() + + +@dataclass(frozen=True, slots=True) +class _RegistrationsOverCatalog(Mapping[str, Mapping[str, object]]): + catalog: Mapping[str, Mapping[str, object]] + registrations: Mapping[str, Mapping[str, object]] + registration_order: Mapping[str, int] + registered_names: Mapping[str, tuple[str, ...]] + + def __getitem__(self, key: str) -> Mapping[str, object]: + catalog_entry: Final = self.catalog.get(key) + names: Final = dict.fromkeys((*self.registered_names.get(key, ()), key)) + present: Final = tuple(name for name in names if name in self.registrations) + if not present: + return self.catalog[key] + oldest_first: Final = sorted(present, key=lambda name: self.registration_order.get(name, -1)) + registered: Final = (self.registrations[name] for name in oldest_first) + return MappingProxyType( + dict(itertools.chain.from_iterable(entry.items() for entry in (catalog_entry or {}, *registered))) + ) + + def __iter__(self) -> Iterator[str]: + return iter({**dict.fromkeys(self.catalog), **dict.fromkeys(self.registrations)}) + + def __len__(self) -> int: + return len(self.catalog.keys() | self.registrations.keys()) + + +def _record_registered_name(written_key: str, registered_key: str) -> None: + names: Final = _runtime_registered_names.get(written_key, ()) + if registered_key not in names: + _runtime_registered_names[written_key] = (*names, registered_key) + + +def catalog_with_runtime_registrations() -> Mapping[str, Mapping[str, object]]: + """The loaded catalog plus ``register_model`` calls, without what routers register for their deployments.""" + catalog: Final = GetModelCostMap.loaded_model_cost_map() + if not _runtime_registered_model_cost: + return catalog + return _RegistrationsOverCatalog( + catalog, + MappingProxyType(_runtime_registered_model_cost), + MappingProxyType(_runtime_registration_order), + MappingProxyType(_runtime_registered_names), + ) def runtime_model_cost_registrations( @@ -4165,6 +4305,13 @@ class _LiveDeploymentReplay: """ callback: Callable[[], None] | None = None + # Replays other router cores add beside the slot, run after it. + extra: tuple[Callable[[], None], ...] = () + + +def add_live_deployment_replay(replay: Callable[[], None]) -> None: + """Add a callback that re-asserts another router core's live deployments after a refresh.""" + _LiveDeploymentReplay.extra = (*_LiveDeploymentReplay.extra, replay) def set_live_deployment_replay(replay: Callable[[], None]) -> None: @@ -4198,8 +4345,17 @@ def reapply_runtime_model_cost_registrations() -> None: """ if _LiveDeploymentReplay.callback is not None: _LiveDeploymentReplay.callback() + for extra_replay in _LiveDeploymentReplay.extra: + extra_replay() if _runtime_registered_model_cost: - register_model(model_cost=dict(_runtime_registered_model_cost)) + register_model( + model_cost=dict( + sorted( + _runtime_registered_model_cost.items(), + key=lambda registration: _runtime_registration_order.get(registration[0], -1), + ) + ) + ) def cost_map_omits_token_price(*keys: object) -> bool: @@ -4273,9 +4429,12 @@ def register_model( dict(_runtime_registered_model_cost.get(_registered_key, {})), _RATE_TABLE.validate_python(_registered_value), ) + _runtime_registration_order[_registered_key] = next(_REGISTRATION_TICKS) for key, value in loaded_model_cost.items(): write = _register_on_current_map(str(key), value, custom_llm_provider, warning_display_name) + if persist_across_reloads: + _record_registered_name(write.key, str(key)) # Invalidate case-insensitive lookup map since model_cost was modified _invalidate_model_cost_lowercase_map() @@ -4316,40 +4475,61 @@ def _get_non_default_params(passed_params: dict, default_params: dict, additiona return non_default_params +_OPENAI_SDK_ONLY_TRANSCRIPTION_PARAMS: Final = frozenset(("languages", "keywords", "stream")) + + def get_optional_params_transcription( model: str, custom_llm_provider: str, language: str | None = None, + languages: Sequence[str] | None = None, + keywords: Sequence[str] | None = None, prompt: str | None = None, response_format: str | None = None, temperature: int | None = None, timestamp_granularities: list[Literal["word", "segment"]] | None = None, + stream: bool | None = None, drop_params: bool | None = None, **kwargs, ): from litellm.constants import OPENAI_TRANSCRIPTION_PARAMS # retrieve all parameters passed to the function - passed_params: Final = locals() + passed_params: Final = locals().copy() passed_params.pop("OPENAI_TRANSCRIPTION_PARAMS") - passed_params.pop("custom_llm_provider") - passed_params.pop("drop_params") - drop_params = normalize_drop_params(drop_params) + passed_params.pop("model") + custom_llm_provider = passed_params.pop("custom_llm_provider") + drop_params = normalize_drop_params(passed_params.pop("drop_params")) special_params: Final[Mapping[str, object]] = passed_params.pop("kwargs") + from litellm.litellm_core_utils.audio_utils.transcription_streaming import ( + transcription_stream_flag, + transcription_stream_unset, + ) + for k, v in special_params.items(): passed_params[k] = v - default_params: Final = { - "language": None, - "prompt": None, - "response_format": None, - "temperature": None, # openai defaults this to 0 - "timestamp_granularities": None, - } + sends_through_openai_sdk: Final = custom_llm_provider in ("openai", "azure") + drops_unsupported_params: Final = drop_params is True or litellm.drop_params is True + transcription_params: Final = ( + OPENAI_TRANSCRIPTION_PARAMS + if sends_through_openai_sdk or drops_unsupported_params + else [param for param in OPENAI_TRANSCRIPTION_PARAMS if param not in _OPENAI_SDK_ONLY_TRANSCRIPTION_PARAMS] + ) + default_params: Final = {param: None for param in (*transcription_params, "prompt", "temperature")} + stream_unset: Final = transcription_stream_unset(stream) + malformed_stream: Final = not stream_unset and transcription_stream_flag(stream) is None + if malformed_stream and not drops_unsupported_params: + raise UnsupportedParamsError( + status_code=400, + message="`stream` must be a boolean. To drop it from the call, set `litellm.drop_params = True`.", + ) non_default_params: Final = { - k: v for k, v in passed_params.items() if (k in default_params and v != default_params[k]) + k: v + for k, v in passed_params.items() + if k in default_params and v != default_params[k] and not (k == "stream" and (stream_unset or malformed_stream)) } optional_params = {} @@ -4358,9 +4538,7 @@ def get_optional_params_transcription( if len(non_default_params.keys()) > 0: keys: Final = list(non_default_params.keys()) for k in keys: - if ( - drop_params is True or litellm.drop_params is True - ) and k not in supported_params: # drop the unsupported non-default values + if drops_unsupported_params and k not in supported_params: non_default_params.pop(k, None) elif k not in supported_params: raise UnsupportedParamsError( @@ -4414,9 +4592,12 @@ def get_optional_params_transcription( optional_params=optional_params, passed_params=passed_params, custom_llm_provider=custom_llm_provider, - openai_params=list(default_params) if custom_llm_provider == "bedrock" else OPENAI_TRANSCRIPTION_PARAMS, + openai_params=list(default_params) if custom_llm_provider == "bedrock" else transcription_params, additional_drop_params=kwargs.get("additional_drop_params", None), ) + extra_body: Final = optional_params.get("extra_body") + if isinstance(extra_body, dict) and not extra_body: + optional_params.pop("extra_body") return optional_params @@ -5186,7 +5367,12 @@ def remove_sensitive_keys_from_dict(d: dict) -> dict: return d -def pre_process_optional_params(passed_params: dict, non_default_params: dict, custom_llm_provider: str) -> dict: +_TOOL_LIST: Final = TypeAdapter(list[object]) + + +def pre_process_optional_params( + passed_params: dict, non_default_params: dict, custom_llm_provider: str, model: str, drop_params: bool | None +) -> dict: """For .completion(), preprocess optional params""" optional_params: dict = {} @@ -5243,14 +5429,20 @@ def pre_process_optional_params(passed_params: dict, non_default_params: dict, c and custom_llm_provider not in litellm.openai_compatible_providers ): if custom_llm_provider == "ollama": + if "tools" in non_default_params: + sent_tools: Final = _TOOL_LIST.validate_python(non_default_params.pop("tools")) + non_default_params.pop("tool_choice", None) # causes ollama requests to hang + prompt_tools: Final = tools_without_hosted_mcp( + sent_tools, model=model, route=custom_llm_provider, drop_params=bool(drop_params) + ) + if sent_tools and not prompt_tools: + return optional_params + optional_params["functions_unsupported_model"] = prompt_tools + elif "functions" in non_default_params: + optional_params["functions_unsupported_model"] = non_default_params.pop("functions") # ollama actually supports json output optional_params["format"] = "json" litellm.add_function_to_prompt = True # so that main.py adds the function call to the prompt - if "tools" in non_default_params: - optional_params["functions_unsupported_model"] = non_default_params.pop("tools") - non_default_params.pop("tool_choice", None) # causes ollama requests to hang - elif "functions" in non_default_params: - optional_params["functions_unsupported_model"] = non_default_params.pop("functions") elif litellm.add_function_to_prompt: # if user opts to add it to prompt instead optional_params["functions_unsupported_model"] = non_default_params.pop( "tools", non_default_params.pop("functions", None) @@ -5385,6 +5577,8 @@ def get_optional_params( passed_params=passed_params, non_default_params=non_default_params, custom_llm_provider=custom_llm_provider, + model=model, + drop_params=drop_params, ) def _check_valid_arg(supported_params: list[str]): @@ -5976,6 +6170,14 @@ EXTRA_BODY_ROUTING_KEYS: Final = frozenset({"model"}) LITELLM_ONLY_PARAMS: Final = frozenset(("cache_control_injection_points",)) +def header_auth_params(custom_llm_provider: str) -> frozenset[str]: + if custom_llm_provider != "azure_ai": + return frozenset() + from litellm.llms.azure_ai.common_utils import AZURE_ENTRA_CREDENTIAL_PARAM_KEYS + + return AZURE_ENTRA_CREDENTIAL_PARAM_KEYS + + def add_provider_specific_params_to_optional_params( optional_params: dict, passed_params: dict, @@ -6010,8 +6212,10 @@ def add_provider_specific_params_to_optional_params( **extra_body, } - dropped_keys: Final = EXTRA_BODY_ROUTING_KEYS | frozenset( - param for param in (additional_drop_params or ()) if isinstance(param, str) + dropped_keys: Final = ( + EXTRA_BODY_ROUTING_KEYS + | header_auth_params(custom_llm_provider) + | frozenset(param for param in (additional_drop_params or ()) if isinstance(param, str)) ) ensure_extra_body_is_safe: Final = litellm_utils.ensure_extra_body_is_safe optional_params["extra_body"] = ensure_extra_body_is_safe( @@ -6143,7 +6347,15 @@ def get_deployment_order(deployment: Mapping[str, object]) -> int | None: resolved_order: Final = ( order if order is not None else cast(Mapping[str, object], deployment.get("model_info", {})).get("order") ) - return cast(int | None, resolved_order) + # One number for every spelling (`1`, `1.0`, `"1"`, `True`), so orders written different ways + # sort and compare together; anything else counts as no order. + if isinstance(resolved_order, bool | int): + return int(resolved_order) + if isinstance(resolved_order, float): + return int(resolved_order) if resolved_order.is_integer() else None + if isinstance(resolved_order, str) and re.fullmatch(r"[+-]?[0-9]+", resolved_order): + return int(resolved_order) + return None _get_deployment_order = get_deployment_order @@ -7152,6 +7364,7 @@ def get_model_info_helper( "cache_read_input_audio_token_cost_batches", None ), explicit_cache_read_input_token_cost=_model_info.get("explicit_cache_read_input_token_cost", None), + cache_read_input_image_token_cost=_model_info.get("cache_read_input_image_token_cost", None), prompt_cache_min_tokens=_model_info.get("prompt_cache_min_tokens", None), cache_read_input_token_cost_above_200k_tokens=_model_info.get( "cache_read_input_token_cost_above_200k_tokens", None @@ -7249,6 +7462,18 @@ def get_model_info_helper( input_cost_per_text_message=_model_info.get("input_cost_per_text_message", None), input_cost_per_audio_token=_model_info.get("input_cost_per_audio_token", None), input_cost_per_audio_token_flex=_model_info.get("input_cost_per_audio_token_flex", None), + input_cost_per_audio_token_above_200k_tokens=_model_info.get( + "input_cost_per_audio_token_above_200k_tokens", None + ), + input_cost_per_audio_token_above_200k_tokens_flex=_model_info.get( + "input_cost_per_audio_token_above_200k_tokens_flex", None + ), + input_cost_per_audio_token_above_200k_tokens_priority=_model_info.get( + "input_cost_per_audio_token_above_200k_tokens_priority", None + ), + input_cost_per_audio_token_above_200k_tokens_batches=_model_info.get( + "input_cost_per_audio_token_above_200k_tokens_batches", None + ), input_cost_per_audio_token_priority=_model_info.get("input_cost_per_audio_token_priority", None), input_cost_per_image_token=_model_info.get("input_cost_per_image_token", None), input_cost_per_video_token=_model_info.get("input_cost_per_video_token", None), @@ -7262,6 +7487,9 @@ def get_model_info_helper( input_cost_per_token_above_200k_tokens_batches=_model_info.get( "input_cost_per_token_above_200k_tokens_batches" ), + input_cost_per_token_above_200k_tokens_flex=_model_info.get( + "input_cost_per_token_above_200k_tokens_flex", None + ), input_cost_per_token_above_272k_tokens_batches=_model_info.get( "input_cost_per_token_above_272k_tokens_batches" ), @@ -7269,6 +7497,9 @@ def get_model_info_helper( output_cost_per_token_above_200k_tokens_batches=_model_info.get( "output_cost_per_token_above_200k_tokens_batches" ), + output_cost_per_token_above_200k_tokens_flex=_model_info.get( + "output_cost_per_token_above_200k_tokens_flex", None + ), output_cost_per_token_above_272k_tokens_batches=_model_info.get( "output_cost_per_token_above_272k_tokens_batches" ), @@ -7283,6 +7514,7 @@ def get_model_info_helper( regional_processing_uplift_multiplier_us=_model_info.get( "regional_processing_uplift_multiplier_us", None ), + fedramp_uplift_multiplier=_model_info.get("fedramp_uplift_multiplier", None), regional_endpoint_uplift_multiplier=_model_info.get("regional_endpoint_uplift_multiplier", None), output_cost_per_audio_token=_model_info.get("output_cost_per_audio_token", None), output_cost_per_character=_model_info.get("output_cost_per_character", None), @@ -7330,6 +7562,7 @@ def get_model_info_helper( output_cost_per_pixel=_model_info.get("output_cost_per_pixel", None), output_cost_per_image_token=_model_info.get("output_cost_per_image_token", None), output_cost_per_image_token_batches=_model_info.get("output_cost_per_image_token_batches", None), + output_cost_per_image_token_priority=_model_info.get("output_cost_per_image_token_priority", None), output_cost_per_video_token=_model_info.get("output_cost_per_video_token", None), output_vector_size=_model_info.get("output_vector_size", None), citation_cost_per_token=_model_info.get("citation_cost_per_token", None), @@ -7360,10 +7593,12 @@ def get_model_info_helper( ), supports_web_search=_model_info.get("supports_web_search", None), supports_url_context=_model_info.get("supports_url_context", None), + supports_continuation=_model_info.get("supports_continuation", None), supports_reasoning=_model_info.get("supports_reasoning", None), supports_adaptive_thinking=_model_info.get("supports_adaptive_thinking", None), supports_legacy_thinking=_model_info.get("supports_legacy_thinking", None), thinking_always_on=_model_info.get("thinking_always_on", None), + thinking_on_by_default=_model_info.get("thinking_on_by_default", None), supports_tool_search=_model_info.get("supports_tool_search", None), supports_mid_conversation_system=_model_info.get("supports_mid_conversation_system", None), supports_anthropic_thinking_payload=_model_info.get("supports_anthropic_thinking_payload", None), @@ -7398,6 +7633,9 @@ def get_model_info_helper( supports_image_size=_model_info.get("supports_image_size", None), supported_audio_formats=_model_info.get("supported_audio_formats", None), token_count_framing=_model_info.get("token_count_framing", None), + token_count_tool_framing=_model_info.get("token_count_tool_framing", None), + token_count_responses_framing=_model_info.get("token_count_responses_framing", None), + token_count_responses_tool_framing=_model_info.get("token_count_responses_tool_framing", None), token_count_model=_model_info.get("token_count_model", None), token_count_tokenizer=_model_info.get("token_count_tokenizer", None), vertex_ai_audio_api=_model_info.get("vertex_ai_audio_api", None), @@ -7516,6 +7754,7 @@ def get_model_info( supports_pdf_input: Optional[bool] supports_web_search: Optional[bool] supports_url_context: Optional[bool] + supports_continuation: Optional[bool] supports_reasoning: Optional[bool] Raises: Exception: If the model is not mapped yet. @@ -8868,6 +9107,9 @@ def bundled_provider_models(provider: str) -> tuple[str, ...]: return tuple(model for model in bundled if not is_hidden_as_retired(cost_map.get(model, {}))) +AZURE_MODEL_PLACEHOLDER: Final = "Azure-LLM" + + def get_valid_models( check_provider_endpoint: bool | None = None, custom_llm_provider: str | None = None, @@ -8923,7 +9165,7 @@ def get_valid_models( continue if provider == "azure": - valid_models.append("Azure-LLM") + valid_models.append(AZURE_MODEL_PLACEHOLDER) elif provider_config is not None and check_provider_endpoint and provider is not None: valid_models.extend( _get_valid_models_from_provider_api( @@ -9440,9 +9682,28 @@ def validate_chat_completion_tool_choice( tool_choice_type = tool_choice.get("type") if tool_choice_type in ("auto", "none", "required") and "function" not in tool_choice: return tool_choice_type + if ( + tool_choice_type == "allowed_tools" + and ( + parse_chat_allowed_tools_tool_choice( + cast( # cast-ok: widening an untyped dict to object is always sound, the helper validates it with pydantic + object, tool_choice + ) + ) + is None + ) + ): + raise BadRequestError( + message=( + f"Invalid tool choice, tool_choice={tool_choice}. On chat completions an allowed_tools " + f"tool_choice must be {CHAT_ALLOWED_TOOLS_LAYOUT}" + ), + model=model, + llm_provider="", + ) # Standard OpenAI format: {"type": "function", "function": {...}} - if tool_choice.get("type") is None or tool_choice.get("function") is None: + if tool_choice_type != "allowed_tools" and (tool_choice_type is None or tool_choice.get("function") is None): raise BadRequestError( message=f"Invalid tool choice, tool_choice={tool_choice}. Please ensure tool_choice follows the OpenAI spec", model=model, @@ -10052,12 +10313,21 @@ class ProviderConfigManager: return litellm.LayaDecisionsConfig() if provider == LlmProviders.BESPOKE: return litellm.BespokeDecisionsConfig() - if provider in (LlmProviders.OPENAI, LlmProviders.AZURE, LlmProviders.AZURE_AI, LlmProviders.EU_JEV): + if provider in ( + LlmProviders.EMPIRIOLABS, + LlmProviders.OPENAI, + LlmProviders.AZURE, + LlmProviders.AZURE_AI, + LlmProviders.EU_JEV, + LlmProviders.PARALLEL_AI, + ): configs: Final = { + LlmProviders.EMPIRIOLABS: litellm.EmpirioLabsDecisionsConfig, LlmProviders.OPENAI: litellm.OpenAIDecisionsConfig, LlmProviders.AZURE: litellm.AzureDecisionsConfig, LlmProviders.AZURE_AI: litellm.AzureAIDecisionsConfig, LlmProviders.EU_JEV: litellm.EuJevDecisionsConfig, + LlmProviders.PARALLEL_AI: litellm.ParallelAIDecisionsConfig, } return configs[provider]() return None @@ -10178,6 +10448,7 @@ class ProviderConfigManager: def get_provider_audio_transcription_config( model: str, provider: LlmProviders, + base_model: str | None = None, ) -> BaseAudioTranscriptionConfig | None: model_cost_entry: Final = _get_model_cost_entry_for_provider_config( model=model, @@ -10205,7 +10476,13 @@ class ProviderConfigManager: return XAIAudioTranscriptionConfig() elif litellm.LlmProviders.OPENAI == provider: - if "gpt-4o" in model or (model.startswith("gpt-") and "transcribe" in model): + if "gpt-transcribe" in (model, base_model): + from litellm.llms.openai.transcriptions.gpt_transformation import ( + OpenAIGPTTranscribeAudioTranscriptionConfig, + ) + + return OpenAIGPTTranscribeAudioTranscriptionConfig() + elif "gpt-4o" in model or (model.startswith("gpt-") and "transcribe" in model): return litellm.OpenAIGPTAudioTranscriptionConfig() else: return litellm.OpenAIWhisperAudioTranscriptionConfig() @@ -10505,12 +10782,14 @@ class ProviderConfigManager: from litellm.llms.ollama.common_utils import OllamaModelInfo return OllamaModelInfo() - elif LlmProviders.VLLM == provider or LlmProviders.HOSTED_VLLM == provider: - from litellm.llms.vllm.common_utils import ( - VLLMModelInfo, # experimental approach, to reduce bloat on __init__.py - ) + elif LlmProviders.VLLM == provider: + from litellm.llms.vllm.common_utils import VLLMModelInfo return VLLMModelInfo() + elif LlmProviders.HOSTED_VLLM == provider: + from litellm.llms.vllm.common_utils import HostedVLLMModelInfo + + return HostedVLLMModelInfo() elif LlmProviders.LEMONADE == provider: return litellm.LemonadeChatConfig() elif LlmProviders.CLARIFAI == provider: @@ -10896,8 +11175,13 @@ class ProviderConfigManager: @staticmethod def get_provider_video_config( model: str | None, - provider: LlmProviders, + provider: LlmProviders | str, ) -> BaseVideoConfig | None: + if not isinstance(provider, LlmProviders): + custom_video_config: Final = ProviderConfigManager.get_custom_provider_video_config(provider) + if custom_video_config is not None or provider not in LlmProvidersSet: + return custom_video_config + return ProviderConfigManager.get_provider_video_config(model=model, provider=LlmProviders(provider)) if LlmProviders.OPENAI == provider: from litellm.llms.openai.videos.transformation import OpenAIVideoConfig @@ -10948,6 +11232,34 @@ class ProviderConfigManager: return VolcEngineVideoConfig() return None + @staticmethod + def get_custom_llm_handler(provider: str | None) -> CustomLLM | None: + """The `CustomLLM` registered for `provider` in `litellm.custom_provider_map`, if its handler is one.""" + from litellm.llms.custom_llm import CustomLLM + + return next( + ( + item["custom_handler"] + for item in litellm.custom_provider_map + if item["provider"] == provider and isinstance(item["custom_handler"], CustomLLM) + ), + None, + ) + + @staticmethod + def get_custom_provider_video_config(provider: str) -> BaseVideoConfig | None: + """The `BaseVideoConfig` registered for `provider` in `litellm.custom_provider_map`, if its handler is one.""" + from litellm.llms.base_llm.videos.transformation import BaseVideoConfig + + return next( + ( + item["custom_handler"] + for item in litellm.custom_provider_map + if item["provider"] == provider and isinstance(item["custom_handler"], BaseVideoConfig) + ), + None, + ) + @staticmethod def get_provider_container_config( provider: LlmProviders, diff --git a/litellm/videos/main.py b/litellm/videos/main.py index 85e651b687c..66eb10e30db 100644 --- a/litellm/videos/main.py +++ b/litellm/videos/main.py @@ -26,6 +26,17 @@ from litellm.types.videos.utils import decode_video_id_with_provider from litellm.utils import ProviderConfigManager, client from litellm.videos.utils import VideoGenerationRequestUtils + +def _unsupported_video_call( + call_name: str, custom_llm_provider: str, model: str | None = None +) -> litellm.BadRequestError: + return litellm.BadRequestError( + message=f"{call_name} is not supported for {custom_llm_provider}", + model=model or "", + llm_provider=custom_llm_provider, + ) + + #################### Initialize provider clients #################### llm_http_handler: BaseLLMHTTPHandler = BaseLLMHTTPHandler() @@ -40,7 +51,7 @@ async def avideo_generation( size: str | None = None, user: str | None = None, timeout=600, # default to 10 minutes - custom_llm_provider=None, + custom_llm_provider: str | None = None, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: dict[str, object] | None = None, @@ -170,7 +181,7 @@ def video_generation( size: str | None = None, user: str | None = None, timeout=600, # default to 10 minutes - custom_llm_provider=None, + custom_llm_provider: str | None = None, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: dict[str, object] | None = None, @@ -208,11 +219,11 @@ def video_generation( # get provider config video_generation_provider_config: BaseVideoConfig | None = ProviderConfigManager.get_provider_video_config( model=model, - provider=litellm.LlmProviders(custom_llm_provider), + provider=custom_llm_provider, ) if video_generation_provider_config is None: - raise ValueError(f"video generation is not supported for {custom_llm_provider}") + raise _unsupported_video_call("video generation", custom_llm_provider, model) local_vars.update(kwargs) # Get VideoGenerationOptionalRequestParams with only valid parameters @@ -329,11 +340,11 @@ def video_content( # get provider config video_provider_config: Final[BaseVideoConfig | None] = ProviderConfigManager.get_provider_video_config( model=None, - provider=litellm.LlmProviders(custom_llm_provider), + provider=custom_llm_provider, ) if video_provider_config is None: - raise ValueError(f"video support download is not supported for {custom_llm_provider}") + raise _unsupported_video_call("video support download", custom_llm_provider) local_vars.update(kwargs) # For video content download, we don't need complex optional parameter handling @@ -456,7 +467,7 @@ async def avideo_remix( video_id: str, prompt: str, timeout=600, # default to 10 minutes - custom_llm_provider=None, + custom_llm_provider: str | None = None, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: dict[str, object] | None = None, @@ -559,7 +570,7 @@ def video_remix( video_id: str, prompt: str, timeout=600, # default to 10 minutes - custom_llm_provider=None, + custom_llm_provider: str | None = None, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: dict[str, object] | None = None, @@ -598,11 +609,11 @@ def video_remix( # get provider config video_remix_provider_config: Final[BaseVideoConfig | None] = ProviderConfigManager.get_provider_video_config( model=None, - provider=litellm.LlmProviders(custom_llm_provider), + provider=custom_llm_provider, ) if video_remix_provider_config is None: - raise ValueError(f"video remix is not supported for {custom_llm_provider}") + raise _unsupported_video_call("video remix", custom_llm_provider) local_vars.update(kwargs) # For video remix, we need the video_id and prompt @@ -660,7 +671,7 @@ async def avideo_list( order: str | None = None, api_key: str | None = None, timeout=600, # default to 10 minutes - custom_llm_provider=None, + custom_llm_provider: str | None = None, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: dict[str, object] | None = None, @@ -774,7 +785,7 @@ def video_list( limit: int | None = None, order: str | None = None, timeout=600, # default to 10 minutes - custom_llm_provider=None, + custom_llm_provider: str | None = None, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: dict[str, object] | None = None, @@ -810,11 +821,11 @@ def video_list( # get provider config video_list_provider_config: Final[BaseVideoConfig | None] = ProviderConfigManager.get_provider_video_config( model=None, - provider=litellm.LlmProviders(custom_llm_provider), + provider=custom_llm_provider, ) if video_list_provider_config is None: - raise ValueError(f"video list is not supported for {custom_llm_provider}") + raise _unsupported_video_call("video list", custom_llm_provider) local_vars.update(kwargs) # For video list, we need the query parameters @@ -871,7 +882,7 @@ def video_list( async def avideo_status( video_id: str, timeout=600, # default to 10 minutes - custom_llm_provider=None, + custom_llm_provider: str | None = None, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: dict[str, object] | None = None, @@ -970,7 +981,7 @@ def video_status( def video_status( video_id: str, timeout=600, # default to 10 minutes - custom_llm_provider=None, + custom_llm_provider: str | None = None, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: dict[str, object] | None = None, @@ -1031,11 +1042,11 @@ def video_status( # get provider config video_status_provider_config: Final[BaseVideoConfig | None] = ProviderConfigManager.get_provider_video_config( model=None, - provider=litellm.LlmProviders(custom_llm_provider), + provider=custom_llm_provider, ) if video_status_provider_config is None: - raise ValueError(f"video status is not supported for {custom_llm_provider}") + raise _unsupported_video_call("video status", custom_llm_provider) local_vars.update(kwargs) # For video status, we need the video_id @@ -1088,7 +1099,7 @@ async def avideo_create_character( name: str, video: FileTypes, timeout=600, - custom_llm_provider=None, + custom_llm_provider: str | None = None, extra_headers: dict[str, object] | None = None, extra_query: dict[str, object] | None = None, extra_body: dict[str, object] | None = None, @@ -1143,7 +1154,7 @@ def video_create_character( name: str, video: FileTypes, timeout=600, - custom_llm_provider=None, + custom_llm_provider: str | None = None, extra_headers: dict[str, object] | None = None, extra_query: dict[str, object] | None = None, extra_body: dict[str, object] | None = None, @@ -1172,11 +1183,11 @@ def video_create_character( provider_config: Final[BaseVideoConfig | None] = ProviderConfigManager.get_provider_video_config( model=None, - provider=litellm.LlmProviders(custom_llm_provider), + provider=custom_llm_provider, ) if provider_config is None: - raise ValueError(f"video create character is not supported for {custom_llm_provider}") + raise _unsupported_video_call("video create character", custom_llm_provider) local_vars.update(kwargs) request_params: Final[dict] = {"name": name} @@ -1218,7 +1229,7 @@ def video_create_character( async def avideo_get_character( character_id: str, timeout=600, - custom_llm_provider=None, + custom_llm_provider: str | None = None, extra_headers: dict[str, object] | None = None, extra_query: dict[str, object] | None = None, extra_body: dict[str, object] | None = None, @@ -1268,7 +1279,7 @@ async def avideo_get_character( def video_get_character( character_id: str, timeout=600, - custom_llm_provider=None, + custom_llm_provider: str | None = None, extra_headers: dict[str, object] | None = None, extra_query: dict[str, object] | None = None, extra_body: dict[str, object] | None = None, @@ -1297,11 +1308,11 @@ def video_get_character( provider_config: Final[BaseVideoConfig | None] = ProviderConfigManager.get_provider_video_config( model=None, - provider=litellm.LlmProviders(custom_llm_provider), + provider=custom_llm_provider, ) if provider_config is None: - raise ValueError(f"video get character is not supported for {custom_llm_provider}") + raise _unsupported_video_call("video get character", custom_llm_provider) local_vars.update(kwargs) request_params: Final[dict] = {"character_id": character_id} @@ -1343,7 +1354,7 @@ async def avideo_edit( video_id: str, prompt: str, timeout=600, - custom_llm_provider=None, + custom_llm_provider: str | None = None, extra_headers: dict[str, object] | None = None, extra_query: dict[str, object] | None = None, extra_body: dict[str, object] | None = None, @@ -1398,7 +1409,7 @@ def video_edit( video_id: str, prompt: str, timeout=600, - custom_llm_provider=None, + custom_llm_provider: str | None = None, extra_headers: dict[str, object] | None = None, extra_query: dict[str, object] | None = None, extra_body: dict[str, object] | None = None, @@ -1430,11 +1441,11 @@ def video_edit( provider_config: Final[BaseVideoConfig | None] = ProviderConfigManager.get_provider_video_config( model=None, - provider=litellm.LlmProviders(custom_llm_provider), + provider=custom_llm_provider, ) if provider_config is None: - raise ValueError(f"video edit is not supported for {custom_llm_provider}") + raise _unsupported_video_call("video edit", custom_llm_provider) local_vars.update(kwargs) request_params: Final[dict] = {"video_id": video_id, "prompt": prompt} @@ -1480,7 +1491,7 @@ async def avideo_extension( prompt: str, seconds: str, timeout=600, - custom_llm_provider=None, + custom_llm_provider: str | None = None, extra_headers: dict[str, object] | None = None, extra_query: dict[str, object] | None = None, extra_body: dict[str, object] | None = None, @@ -1534,7 +1545,7 @@ def video_extension( prompt: str, seconds: str, timeout=600, - custom_llm_provider=None, + custom_llm_provider: str | None = None, extra_headers: dict[str, object] | None = None, extra_query: dict[str, object] | None = None, extra_body: dict[str, object] | None = None, @@ -1564,11 +1575,11 @@ def video_extension( provider_config: Final[BaseVideoConfig | None] = ProviderConfigManager.get_provider_video_config( model=None, - provider=litellm.LlmProviders(custom_llm_provider), + provider=custom_llm_provider, ) if provider_config is None: - raise ValueError(f"video extension is not supported for {custom_llm_provider}") + raise _unsupported_video_call("video extension", custom_llm_provider) local_vars.update(kwargs) request_params: Final[dict] = { diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 3288e64d296..29c50a24272 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -1,4 +1,172 @@ { + "azure/gpt-realtime-2.1-2026-07-07": { + "cache_creation_input_audio_token_cost": 4e-07, + "cache_read_input_audio_token_cost": 4e-07, + "cache_read_input_token_cost": 4e-07, + "deprecation_date": "2027-06-25", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "input_cost_per_audio_token": 3.2e-05, + "input_cost_per_image_token": 5e-06, + "input_cost_per_token": 4e-06, + "litellm_provider": "azure", + "max_input_tokens": 32000, + "max_output_tokens": 4096, + "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "output_cost_per_audio_token": 6.4e-05, + "output_cost_per_token": 2.4e-05, + "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure", + "supported_endpoints": [ + "/v1/realtime" + ], + "supported_modalities": [ + "text", + "image", + "audio" + ], + "supported_output_modalities": [ + "text", + "audio" + ], + "supports_audio_input": true, + "supports_audio_output": true, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "cache_read_input_image_token_cost": 5e-07, + "supports_prompt_caching": true, + "supports_reasoning": true + }, + "azure/gpt-realtime-2.1-mini-2026-07-07": { + "cache_creation_input_audio_token_cost": 3e-07, + "cache_read_input_audio_token_cost": 3e-07, + "cache_read_input_token_cost": 6e-08, + "deprecation_date": "2027-06-25", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "input_cost_per_audio_token": 1e-05, + "input_cost_per_image_token": 8e-07, + "input_cost_per_token": 6e-07, + "litellm_provider": "azure", + "max_input_tokens": 32000, + "max_output_tokens": 4096, + "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "output_cost_per_audio_token": 2e-05, + "output_cost_per_token": 2.4e-06, + "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/models-sold-directly-by-azure", + "supported_endpoints": [ + "/v1/realtime" + ], + "supported_modalities": [ + "text", + "image", + "audio" + ], + "supported_output_modalities": [ + "text", + "audio" + ], + "supports_audio_input": true, + "supports_audio_output": true, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "cache_read_input_image_token_cost": 8e-08, + "supports_prompt_caching": true, + "supports_reasoning": true + }, + "azure/gpt-realtime-translate-2026-05-06": { + "input_cost_per_second": 0.0005666666666666667, + "litellm_provider": "azure", + "max_input_tokens": 32000, + "max_output_tokens": 4096, + "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/a-new-chapter-for-realtime-ai-reasoning-translation-and-real-time-transcription/4517124", + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "audio", + "text" + ], + "supports_audio_input": true, + "supports_audio_output": true, + "supports_native_streaming": true + }, + "azure/gpt-realtime-translate-2026-05-07": { + "input_cost_per_second": 0.0005666666666666667, + "litellm_provider": "azure", + "max_input_tokens": 32000, + "max_output_tokens": 4096, + "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "source": "https://ai.azure.com/catalog/models/gpt-realtime-translate", + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "audio", + "text" + ], + "supports_audio_input": true, + "supports_audio_output": true, + "supports_native_streaming": true + }, + "azure/gpt-realtime-whisper-2026-05-06": { + "input_cost_per_second": 0.0002833333333333333, + "litellm_provider": "azure", + "mode": "audio_transcription", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/gpt-realtime-whisper", + "supported_endpoints": [ + "/v1/realtime", + "/v1/realtime/transcription_sessions" + ], + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "max_input_tokens": 32000, + "max_output_tokens": 4096 + }, + "azure/gpt-realtime-whisper-2026-05-07": { + "input_cost_per_second": 0.0002833333333333333, + "litellm_provider": "azure", + "mode": "audio_transcription", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/gpt-realtime-whisper", + "supported_endpoints": [ + "/v1/realtime", + "/v1/realtime/transcription_sessions" + ], + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true, + "max_input_tokens": 32000, + "max_output_tokens": 4096 + }, "sample_spec": { "code_interpreter_cost_per_session": 0.0, "computer_use_input_cost_per_1k_tokens": 0.0, @@ -40,6 +208,7 @@ }, "1024-x-1024/50-steps/bedrock/amazon.nova-canvas-v1:0": { "deprecation_date": "2026-09-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "litellm_provider": "bedrock", "max_input_tokens": 2600, "mode": "image_generation", @@ -189,6 +358,7 @@ }, "ai21.jamba-1-5-large-v1:0": { "deprecation_date": "2026-11-26", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-ai21-labs-jamba-1-5-large.md", "input_cost_per_token": 2e-06, "litellm_provider": "bedrock", "max_input_tokens": 256000, @@ -199,6 +369,7 @@ }, "ai21.jamba-1-5-mini-v1:0": { "deprecation_date": "2026-11-26", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-ai21-labs-jamba-1-5-mini.md", "input_cost_per_token": 2e-07, "litellm_provider": "bedrock", "max_input_tokens": 256000, @@ -368,6 +539,7 @@ }, "amazon.nova-canvas-v1:0": { "deprecation_date": "2026-09-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "litellm_provider": "bedrock", "max_input_tokens": 2600, "mode": "image_generation", @@ -376,6 +548,7 @@ }, "us.amazon.nova-canvas-v1:0": { "deprecation_date": "2026-09-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "litellm_provider": "bedrock", "max_input_tokens": 2600, "mode": "image_generation", @@ -384,6 +557,7 @@ }, "us.writer.palmyra-x4-v1:0": { "deprecation_date": "2027-03-09", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-writer-palmyra-x4.md", "input_cost_per_token": 2.5e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -396,6 +570,7 @@ }, "us.writer.palmyra-x5-v1:0": { "deprecation_date": "2027-03-21", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-writer-palmyra-x5.md", "input_cost_per_token": 6e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -408,6 +583,7 @@ }, "writer.palmyra-x4-v1:0": { "deprecation_date": "2027-03-09", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-writer-palmyra-x4.md", "input_cost_per_token": 2.5e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -420,6 +596,7 @@ }, "writer.palmyra-x5-v1:0": { "deprecation_date": "2027-03-21", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-writer-palmyra-x5.md", "input_cost_per_token": 6e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -800,6 +977,7 @@ }, "twelvelabs.marengo-embed-2-7-v1:0": { "deprecation_date": "2026-11-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_query": 7e-05, "input_cost_per_video_per_second": 0.0007, "input_cost_per_audio_per_second": 0.00014, @@ -814,6 +992,7 @@ }, "us.twelvelabs.marengo-embed-2-7-v1:0": { "deprecation_date": "2026-11-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_query": 7e-05, "input_cost_per_video_per_second": 0.0007, "input_cost_per_audio_per_second": 0.00014, @@ -828,6 +1007,7 @@ }, "eu.twelvelabs.marengo-embed-2-7-v1:0": { "deprecation_date": "2026-11-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_query": 7e-05, "input_cost_per_video_per_second": 0.0007, "input_cost_per_audio_per_second": 0.00014, @@ -881,6 +1061,7 @@ }, "twelvelabs.pegasus-1-2-v1:0": { "deprecation_date": "2027-03-22", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-twelvelabs-pegasus-v1-2.md", "input_cost_per_video_per_second": 0.00049, "output_cost_per_token": 7.5e-06, "litellm_provider": "bedrock", @@ -890,6 +1071,7 @@ }, "us.twelvelabs.pegasus-1-2-v1:0": { "deprecation_date": "2027-03-22", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-twelvelabs-pegasus-v1-2.md", "input_cost_per_video_per_second": 0.00049, "output_cost_per_token": 7.5e-06, "litellm_provider": "bedrock", @@ -899,6 +1081,7 @@ }, "eu.twelvelabs.pegasus-1-2-v1:0": { "deprecation_date": "2027-03-22", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-twelvelabs-pegasus-v1-2.md", "input_cost_per_video_per_second": 0.00049, "output_cost_per_token": 7.5e-06, "litellm_provider": "bedrock", @@ -908,6 +1091,7 @@ }, "global.twelvelabs.pegasus-1-2-v1:0": { "deprecation_date": "2027-03-22", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-twelvelabs-pegasus-v1-2.md", "input_cost_per_video_per_second": 0.00049, "output_cost_per_token": 7.5e-06, "litellm_provider": "bedrock", @@ -1011,7 +1195,8 @@ "supports_native_streaming": true, "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, - "prompt_cache_min_tokens": 4096 + "prompt_cache_min_tokens": 4096, + "token_count_model": {"model":"anthropic.claude-haiku-4-5-20251001-v1:0","litellm_provider":"bedrock"} }, "anthropic.claude-3-5-sonnet-20240620-v1:0": { "input_cost_per_token": 3e-06, @@ -1111,6 +1296,7 @@ "cache_creation_input_token_cost": 1.875e-05, "cache_read_input_token_cost": 1.5e-06, "deprecation_date": "2027-01-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.5e-05, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -1939,6 +2125,7 @@ "anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -1971,12 +2158,14 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/index.json", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-east-1/index.json", "token_count_model": { "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "us-east-1" - } + }, + "input_cost_per_token_batches": 2.5e-06, + "output_cost_per_token_batches": 1.25e-05 }, "anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2025,6 +2214,7 @@ "global.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, @@ -2057,12 +2247,14 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-east-1/index.json", "token_count_model": { "model": "global.anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "us-east-1" - } + }, + "input_cost_per_token_batches": 2.5e-06, + "output_cost_per_token_batches": 1.25e-05 }, "global.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2111,6 +2303,7 @@ "us.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -2143,12 +2336,14 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-east-1/index.json", "token_count_model": { "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "us-east-1" - } + }, + "input_cost_per_token_batches": 2.75e-06, + "output_cost_per_token_batches": 1.375e-05 }, "us.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2197,6 +2392,7 @@ "eu.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -2229,12 +2425,14 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/eu-west-1/index.json", "token_count_model": { "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "eu-west-1" - } + }, + "input_cost_per_token_batches": 2.75e-06, + "output_cost_per_token_batches": 1.375e-05 }, "eu.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2278,6 +2476,7 @@ "au.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -2310,12 +2509,14 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/ap-southeast-2/index.json", "token_count_model": { "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "ap-southeast-4" - } + }, + "input_cost_per_token_batches": 2.75e-06, + "output_cost_per_token_batches": 1.375e-05 }, "au.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2364,6 +2565,7 @@ "jp.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_1hr": 1.1e-05, @@ -2396,7 +2598,9 @@ "supports_output_config": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/" + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/ap-northeast-1/index.json", + "input_cost_per_token_batches": 2.75e-06, + "output_cost_per_token_batches": 1.375e-05 }, "jp.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -2760,6 +2964,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -2804,6 +3009,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -2848,6 +3054,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -2892,6 +3099,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -2936,6 +3144,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -2980,6 +3189,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -3233,6 +3443,8 @@ "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-10-14", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "anthropic.claude-sonnet-5", "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -3276,6 +3488,8 @@ "cache_creation_input_token_cost_above_200k_tokens": 7.5e-06, "cache_read_input_token_cost_above_200k_tokens": 6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -3510,6 +3724,8 @@ "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-10-14", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "apac.anthropic.claude-sonnet-5", "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -3565,6 +3781,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "au.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -3598,6 +3816,7 @@ }, "azure/ada": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.1e-07, "litellm_provider": "azure", "max_input_tokens": 8191, @@ -3608,6 +3827,7 @@ "azure/codex-mini": { "cache_read_input_token_cost": 3.75e-07, "deprecation_date": "2026-11-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.5e-06, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -3635,19 +3855,10 @@ "supports_tool_choice": true, "supports_vision": true }, - "azure/command-r-plus": { - "deprecation_date": "2025-06-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 1.5e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_function_calling": true - }, "azure_ai/claude-haiku-4-5": { "deprecation_date": "2026-11-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/claude-haiku-5-5", "cache_creation_input_token_cost": 1.25e-06, "cache_creation_input_token_cost_above_1hr": 2e-06, "cache_read_input_token_cost": 1e-07, @@ -3671,6 +3882,8 @@ }, "azure_ai/claude-opus-4-5": { "deprecation_date": "2026-11-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/claude-opus-5-5", "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_read_input_token_cost": 5e-07, @@ -3695,6 +3908,7 @@ }, "azure_ai/claude-opus-4-6": { "deprecation_date": "2027-02-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_adaptive_thinking": true, "supports_legacy_thinking": true, "input_cost_per_token": 5e-06, @@ -3726,6 +3940,7 @@ }, "azure_ai/claude-opus-4-7": { "deprecation_date": "2027-04-06", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_adaptive_thinking": true, "input_cost_per_token": 5e-06, "output_cost_per_token": 2.5e-05, @@ -3757,6 +3972,7 @@ }, "azure_ai/claude-fable-5": { "deprecation_date": "2027-12-05", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_mid_conversation_system": true, "input_cost_per_token": 1e-05, "output_cost_per_token": 5e-05, @@ -3785,7 +4001,7 @@ "supports_tool_choice": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true, - "supports_max_reasoning_effort": true, + "supports_max_reasoning_effort": false, "prompt_cache_min_tokens": 512 }, "azure_ai/claude-fable-5-1": { @@ -3819,14 +4035,47 @@ "supports_tool_choice": true, "supports_vision": true, "supports_xhigh_reasoning_effort": true, - "supports_max_reasoning_effort": true, + "supports_max_reasoning_effort": false, "prompt_cache_min_tokens": 512, - "deprecation_date": "2027-12-05" + "deprecation_date": "2027-12-05", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement" + }, + "azure_ai/claude-mythos-5-1": { + "input_cost_per_token": 1e-05, + "output_cost_per_token": 5e-05, + "cache_creation_input_token_cost": 1.25e-05, + "cache_creation_input_token_cost_above_1hr": 2e-05, + "cache_read_input_token_cost": 2.5e-07, + "litellm_provider": "azure_ai", + "max_input_tokens": 1000000, + "max_output_tokens": 128000, + "mode": "chat", + "supports_adaptive_thinking": true, + "thinking_always_on": true, + "supports_mid_conversation_system": true, + "supports_assistant_prefill": false, + "supports_computer_use": true, + "supports_forced_tool_use": false, + "supports_function_calling": true, + "supports_native_structured_output": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_sampling_params": false, + "supports_tool_choice": true, + "supports_vision": true, + "supports_xhigh_reasoning_effort": true, + "supports_max_reasoning_effort": false, + "prompt_cache_min_tokens": 512, + "source": "https://learn.microsoft.com/en-us/azure/foundry/foundry-models/concepts/claude-models" }, "azure_ai/claude-opus-5": { "deprecation_date": "2027-07-08", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "input_cost_per_token": 5e-06, "output_cost_per_token": 2.5e-05, "litellm_provider": "azure_ai", @@ -3893,6 +4142,7 @@ }, "azure_ai/claude-opus-4-8": { "deprecation_date": "2027-09-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, "input_cost_per_token": 5e-06, @@ -3925,6 +4175,8 @@ }, "azure_ai/claude-sonnet-4-5": { "deprecation_date": "2026-11-30", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/claude-sonnet-5-5", "cache_creation_input_token_cost": 3.75e-06, "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_read_input_token_cost": 3e-07, @@ -3948,6 +4200,7 @@ }, "azure_ai/claude-sonnet-5": { "deprecation_date": "2027-06-30", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_mid_conversation_system": true, "cache_creation_input_token_cost": 2.5e-06, "cache_creation_input_token_cost_above_1hr": 4e-06, @@ -3964,6 +4217,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -3980,6 +4234,7 @@ }, "azure_ai/claude-sonnet-4-6": { "deprecation_date": "2027-02-10", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "supports_adaptive_thinking": true, "supports_legacy_thinking": true, "cache_creation_input_token_cost": 3.75e-06, @@ -4040,6 +4295,7 @@ }, "azure_ai/gpt-oss-120b": { "deprecation_date": "2027-09-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.5e-07, "output_cost_per_token": 6e-07, "litellm_provider": "azure_ai", @@ -4295,6 +4551,7 @@ }, "azure_ai/gpt-5.5": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, "cache_read_input_token_cost_priority": 1e-06, @@ -4342,6 +4599,7 @@ "azure_ai/gpt-chat-latest": { "cache_read_input_token_cost": 5e-07, "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 5e-06, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -4376,6 +4634,7 @@ "cache_read_input_image_token_cost": 2e-06, "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-10-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_image_token": 8e-06, "input_cost_per_token": 5e-06, "litellm_provider": "azure_ai", @@ -4391,6 +4650,7 @@ "azure_ai/codex-mini": { "cache_read_input_token_cost": 3.75e-07, "deprecation_date": "2026-11-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.5e-06, "litellm_provider": "azure_ai", "max_input_tokens": 200000, @@ -4420,6 +4680,7 @@ }, "azure_ai/whisper": { "deprecation_date": "2026-12-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_second": 0.0001, "litellm_provider": "azure_ai", "mode": "audio_transcription", @@ -4473,6 +4734,7 @@ }, "azure_ai/gpt-5.5-2026-04-24": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, "cache_read_input_token_cost_priority": 1e-06, @@ -4519,6 +4781,8 @@ }, "azure_ai/gpt-5.4": { "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/gpt-5.5", "cache_read_input_token_cost": 2.5e-07, "cache_read_input_token_cost_above_272k_tokens": 5e-07, "cache_read_input_token_cost_priority": 5e-07, @@ -4566,6 +4830,8 @@ }, "azure_ai/gpt-5.4-2026-03-05": { "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/gpt-5.5", "cache_read_input_token_cost": 2.5e-07, "cache_read_input_token_cost_above_272k_tokens": 5e-07, "cache_read_input_token_cost_priority": 5e-07, @@ -4613,6 +4879,7 @@ }, "azure_ai/gpt-5.4-pro": { "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 3e-06, "cache_read_input_token_cost_above_272k_tokens": 6e-06, "cache_read_input_token_cost_priority": 6e-06, @@ -4658,6 +4925,7 @@ }, "azure_ai/gpt-5.4-pro-2026-03-05": { "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 3e-06, "cache_read_input_token_cost_above_272k_tokens": 6e-06, "cache_read_input_token_cost_priority": 6e-06, @@ -4703,6 +4971,7 @@ }, "azure_ai/gpt-5.4-mini": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 7.5e-08, "cache_read_input_token_cost_priority": 1.5e-07, "input_cost_per_token": 7.5e-07, @@ -4744,6 +5013,7 @@ }, "azure_ai/gpt-5.4-mini-2026-03-17": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 7.5e-08, "cache_read_input_token_cost_priority": 1.5e-07, "input_cost_per_token": 7.5e-07, @@ -4785,6 +5055,7 @@ }, "azure_ai/gpt-5.4-nano": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_priority": 4e-08, "input_cost_per_token": 2e-07, @@ -4826,6 +5097,7 @@ }, "azure_ai/gpt-5.4-nano-2026-03-17": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_priority": 4e-08, "input_cost_per_token": 2e-07, @@ -4867,6 +5139,7 @@ }, "azure_ai/model_router": { "deprecation_date": "2027-05-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.4e-07, "output_cost_per_token": 0, "litellm_provider": "azure_ai", @@ -4878,6 +5151,7 @@ }, "azure_ai/model-router": { "deprecation_date": "2027-05-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.4e-07, "output_cost_per_token": 0, "litellm_provider": "azure_ai", @@ -4889,6 +5163,8 @@ }, "azure/eu/gpt-4o-2024-08-06": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, "input_cost_per_token_batches": 1.375e-06, @@ -4908,6 +5184,8 @@ }, "azure/eu/gpt-4o": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "cache_creation_input_token_cost": 1.38e-06, "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, @@ -4927,6 +5205,8 @@ }, "azure/eu/gpt-4o-2024-11-20": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "cache_creation_input_token_cost": 1.38e-06, "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, @@ -4947,6 +5227,7 @@ "azure/eu/gpt-4o-mini": { "cache_read_input_token_cost": 8.3e-08, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.65e-07, "input_cost_per_token_batches": 8.3e-08, "litellm_provider": "azure", @@ -4970,6 +5251,7 @@ "azure/eu/gpt-4o-mini-2024-07-18": { "cache_read_input_token_cost": 8.3e-08, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.65e-07, "input_cost_per_token_batches": 8.3e-08, "litellm_provider": "azure", @@ -5008,26 +5290,6 @@ "supports_system_messages": true, "supports_tool_choice": true }, - "azure/eu/gpt-4o-realtime-preview-2024-10-01": { - "cache_creation_input_audio_token_cost": 2.2e-05, - "cache_read_input_token_cost": 2.75e-06, - "deprecation_date": "2025-03-26", - "input_cost_per_audio_token": 0.00011, - "input_cost_per_token": 5.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 0.00022, - "output_cost_per_token": 2.2e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "azure/eu/gpt-4o-realtime-preview-2024-12-17": { "cache_read_input_audio_token_cost": 2.5e-06, "cache_read_input_token_cost": 2.75e-06, @@ -5059,6 +5321,8 @@ "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_priority": 2.75e-07, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.1", "input_cost_per_token": 1.375e-06, "input_cost_per_token_batches": 6.875e-07, "input_cost_per_token_priority": 2.75e-06, @@ -5102,7 +5366,9 @@ "azure/eu/gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.75e-08, "cache_read_input_token_cost_priority": 4.95e-08, - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.4-mini", "input_cost_per_token": 2.75e-07, "input_cost_per_token_batches": 1.375e-07, "input_cost_per_token_priority": 4.95e-07, @@ -5144,7 +5410,9 @@ "cache_read_input_token_cost_batches": 1.375e-08 }, "azure/eu/gpt-5.1": { - "deprecation_date": "2027-05-15", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.2", "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_batches": 6.875e-08, "cache_read_input_token_cost_priority": 2.75e-07, @@ -5192,6 +5460,8 @@ }, "azure/eu/gpt-5.1-codex": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.2-codex", "cache_read_input_token_cost": 1.375e-07, "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", @@ -5223,6 +5493,7 @@ }, "azure/eu/gpt-5.1-codex-mini": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.75e-08, "input_cost_per_token": 2.75e-07, "litellm_provider": "azure", @@ -5255,6 +5526,8 @@ "azure/eu/gpt-5-nano-2025-08-07": { "cache_read_input_token_cost": 5.5e-09, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.4-nano", "input_cost_per_token": 5.5e-08, "input_cost_per_token_batches": 2.75e-08, "litellm_provider": "azure", @@ -5296,6 +5569,7 @@ "azure/eu/o1": { "cache_read_input_token_cost": 8.25e-06, "deprecation_date": "2026-11-19", + "successor_model": "azure/eu/gpt-5.6-sol", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -5314,6 +5588,7 @@ "azure/eu/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, "deprecation_date": "2026-11-19", + "successor_model": "azure/eu/gpt-5.6-sol", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -5348,6 +5623,8 @@ "azure/eu/o3-mini": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -5365,6 +5642,8 @@ "azure/eu/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -5382,6 +5661,7 @@ "azure/global-standard/gpt-4o-2024-08-06": { "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, "litellm_provider": "azure", @@ -5401,6 +5681,7 @@ "azure/global-standard/gpt-4o-2024-11-20": { "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, "litellm_provider": "azure", @@ -5418,6 +5699,7 @@ }, "azure/global-standard/gpt-4o-mini": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.5e-07, "litellm_provider": "azure", "max_input_tokens": 128000, @@ -5437,6 +5719,8 @@ }, "azure/global/gpt-4o-2024-08-06": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/global/gpt-5.1", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -5456,6 +5740,8 @@ }, "azure/global/gpt-4o-2024-11-20": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/global/gpt-5.1", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -5474,7 +5760,8 @@ "supports_vision": true }, "azure/global/gpt-5.1": { - "deprecation_date": "2027-05-15", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, @@ -5522,6 +5809,7 @@ }, "azure/global/gpt-5.1-codex": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", @@ -5553,6 +5841,7 @@ }, "azure/global/gpt-5.1-codex-mini": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_token": 2.5e-07, "litellm_provider": "azure", @@ -5611,29 +5900,6 @@ "supports_function_calling": true, "supports_tool_choice": true }, - "azure/gpt-35-turbo-16k": { - "deprecation_date": "2025-04-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "azure", - "max_input_tokens": 16385, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 4e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_tool_choice": true - }, - "azure/gpt-35-turbo-16k-0613": { - "deprecation_date": "2025-04-30", - "input_cost_per_token": 3e-06, - "litellm_provider": "azure", - "max_input_tokens": 16385, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 4e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_function_calling": true, - "supports_tool_choice": true - }, "azure/gpt-35-turbo-instruct": { "input_cost_per_token": 1.65e-06, "litellm_provider": "azure_text", @@ -5652,18 +5918,6 @@ "output_cost_per_token": 2.2e-06, "source": "https://azure.microsoft.com/en-us/pricing/details/azure-openai/" }, - "azure/gpt-4": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 3e-05, - "litellm_provider": "azure", - "max_input_tokens": 8192, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_function_calling": true, - "supports_tool_choice": true - }, "azure/gpt-4-0125-preview": { "input_cost_per_token": 1e-05, "litellm_provider": "azure", @@ -5675,18 +5929,6 @@ "supports_parallel_function_calling": true, "supports_tool_choice": true }, - "azure/gpt-4-0613": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 3e-05, - "litellm_provider": "azure", - "max_input_tokens": 8192, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_function_calling": true, - "supports_tool_choice": true - }, "azure/gpt-4-1106-preview": { "input_cost_per_token": 1e-05, "litellm_provider": "azure", @@ -5698,28 +5940,6 @@ "supports_parallel_function_calling": true, "supports_tool_choice": true }, - "azure/gpt-4-32k": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 6e-05, - "litellm_provider": "azure", - "max_input_tokens": 32768, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 0.00012, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_tool_choice": true - }, - "azure/gpt-4-32k-0613": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 6e-05, - "litellm_provider": "azure", - "max_input_tokens": 32768, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 0.00012, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_tool_choice": true - }, "azure/gpt-4-turbo": { "input_cost_per_token": 1.1e-05, "litellm_provider": "azure", @@ -5758,6 +5978,8 @@ }, "azure/gpt-4.1": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "input_cost_per_token": 2e-06, @@ -5800,6 +6022,8 @@ }, "azure/gpt-4.1-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "input_cost_per_token": 2e-06, @@ -5842,6 +6066,8 @@ }, "azure/gpt-4.1-mini": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-mini", "cache_read_input_token_cost": 1e-07, "cache_read_input_token_cost_priority": 1.75e-07, "input_cost_per_token": 4e-07, @@ -5884,6 +6110,8 @@ }, "azure/gpt-4.1-mini-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-mini", "cache_read_input_token_cost": 1e-07, "cache_read_input_token_cost_priority": 1.75e-07, "input_cost_per_token": 4e-07, @@ -5926,6 +6154,8 @@ }, "azure/gpt-4.1-nano": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-nano", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_token": 1e-07, "input_cost_per_token_batches": 5e-08, @@ -5959,6 +6189,8 @@ }, "azure/gpt-4.1-nano-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-nano", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_token": 1e-07, "input_cost_per_token_batches": 5e-08, @@ -5990,28 +6222,10 @@ "supports_tool_choice": true, "supports_vision": true }, - "azure/gpt-4.5-preview": { - "cache_read_input_token_cost": 3.75e-05, - "deprecation_date": "2025-07-14", - "input_cost_per_token": 7.5e-05, - "input_cost_per_token_batches": 3.75e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 0.00015, - "output_cost_per_token_batches": 7.5e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/legacy-models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, "azure/gpt-4o": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -6030,7 +6244,9 @@ "supports_vision": true }, "azure/gpt-4o-2024-05-13": { - "deprecation_date": "2026-12-09", + "deprecation_date": "2027-01-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "input_cost_per_token": 5e-06, "input_cost_per_token_batches": 2.5e-06, "litellm_provider": "azure", @@ -6048,6 +6264,8 @@ }, "azure/gpt-4o-2024-08-06": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -6067,6 +6285,8 @@ }, "azure/gpt-4o-2024-11-20": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -6086,6 +6306,7 @@ }, "azure/gpt-audio": { "deprecation_date": "2027-03-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 4e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6119,6 +6340,7 @@ }, "azure/gpt-audio-2025-08-28": { "deprecation_date": "2027-03-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 4e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6151,6 +6373,7 @@ }, "azure/gpt-audio-1.5": { "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6184,6 +6407,7 @@ }, "azure/gpt-audio-1.5-2026-02-23": { "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6218,6 +6442,7 @@ }, "azure/gpt-audio-mini": { "deprecation_date": "2027-06-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, "litellm_provider": "azure", @@ -6250,6 +6475,7 @@ }, "azure/gpt-audio-mini-2025-10-06": { "deprecation_date": "2027-04-06", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, "litellm_provider": "azure", @@ -6314,6 +6540,7 @@ }, "azure/gpt-4o-mini": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 7.5e-08, "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, @@ -6339,6 +6566,7 @@ "azure/gpt-4o-mini-2024-07-18": { "cache_read_input_token_cost": 7.5e-08, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, "litellm_provider": "azure", @@ -6415,6 +6643,7 @@ "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-03-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -6424,6 +6653,9 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6449,6 +6681,7 @@ "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-03-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -6458,6 +6691,9 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6482,6 +6718,8 @@ "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-realtime-2.1-2026-07-07", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -6491,6 +6729,9 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6516,6 +6757,8 @@ "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-realtime-2.1-2026-07-07", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -6525,6 +6768,9 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6547,8 +6793,10 @@ "azure/gpt-realtime-2.1": { "cache_creation_input_audio_token_cost": 4e-07, "cache_read_input_audio_token_cost": 4e-07, + "cache_read_input_image_token_cost": 5e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-06-25", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -6556,6 +6804,9 @@ "max_input_tokens": 32000, "max_output_tokens": 4096, "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 2.4e-05, "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", @@ -6575,14 +6826,18 @@ "supports_audio_output": true, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, "supports_system_messages": true, "supports_tool_choice": true }, "azure/gpt-realtime-2.1-mini": { "cache_creation_input_audio_token_cost": 3e-07, "cache_read_input_audio_token_cost": 3e-07, + "cache_read_input_image_token_cost": 8e-08, "cache_read_input_token_cost": 6e-08, "deprecation_date": "2027-06-25", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, "input_cost_per_token": 6e-07, @@ -6590,6 +6845,9 @@ "max_input_tokens": 32000, "max_output_tokens": 4096, "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", @@ -6609,6 +6867,8 @@ "supports_audio_output": true, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, "supports_system_messages": true, "supports_tool_choice": true }, @@ -6617,6 +6877,7 @@ "cache_read_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 6e-08, "deprecation_date": "2027-06-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, "input_cost_per_token": 6e-07, @@ -6626,6 +6887,9 @@ "mode": "realtime", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6650,6 +6914,7 @@ "cache_read_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 6e-08, "deprecation_date": "2027-04-06", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, "input_cost_per_token": 6e-07, @@ -6659,6 +6924,9 @@ "mode": "realtime", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "supported_endpoints": [ "/v1/realtime" ], @@ -6680,6 +6948,7 @@ }, "azure/gpt-4o-mini-transcribe": { "deprecation_date": "2027-06-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", @@ -6693,6 +6962,7 @@ }, "azure/gpt-4o-mini-tts": { "deprecation_date": "2027-06-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 6e-07, "litellm_provider": "azure", "mode": "audio_speech", @@ -6710,26 +6980,6 @@ "audio" ] }, - "azure/gpt-4o-realtime-preview-2024-10-01": { - "cache_creation_input_audio_token_cost": 2e-05, - "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2025-03-26", - "input_cost_per_audio_token": 0.0001, - "input_cost_per_token": 5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 0.0002, - "output_cost_per_token": 2e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "azure/gpt-4o-realtime-preview-2024-12-17": { "cache_read_input_token_cost": 2.5e-06, "input_cost_per_audio_token": 4e-05, @@ -6758,6 +7008,7 @@ }, "azure/gpt-4o-transcribe": { "deprecation_date": "2026-10-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 6e-06, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6772,6 +7023,7 @@ }, "azure/gpt-4o-transcribe-diarize": { "deprecation_date": "2027-04-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_audio_token": 6e-06, "input_cost_per_token": 2.5e-06, "litellm_provider": "azure", @@ -6791,6 +7043,9 @@ "max_input_tokens": 32000, "max_output_tokens": 4096, "mode": "audio_transcription", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/gpt-realtime-whisper", "supported_endpoints": [ "/v1/realtime", @@ -6807,7 +7062,9 @@ "azure/gpt-5.1-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, - "deprecation_date": "2027-05-15", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.2", "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "azure", @@ -6855,6 +7112,8 @@ "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.2-codex", "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "azure", @@ -6889,6 +7148,7 @@ "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.5e-07, "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "azure", @@ -6921,6 +7181,8 @@ }, "azure/gpt-5": { "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, @@ -6967,6 +7229,8 @@ "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1", "input_cost_per_token": 1.25e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_priority": 2.5e-06, @@ -7010,6 +7274,8 @@ "azure/gpt-5-codex": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2027-03-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.1-codex", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", "max_input_tokens": 272000, @@ -7039,7 +7305,9 @@ "supports_vision": true }, "azure/gpt-5-mini": { - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-mini", "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, @@ -7085,7 +7353,9 @@ "azure/gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_priority": 4.5e-08, - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-mini", "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_priority": 4.5e-07, @@ -7128,6 +7398,8 @@ }, "azure/gpt-5-nano": { "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-nano", "cache_read_input_token_cost": 5e-09, "cache_read_input_token_cost_batches": 2.5e-09, "input_cost_per_token": 5e-08, @@ -7170,6 +7442,8 @@ "azure/gpt-5-nano-2025-08-07": { "cache_read_input_token_cost": 5e-09, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4-nano", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 2.5e-08, "litellm_provider": "azure", @@ -7210,6 +7484,8 @@ }, "azure/gpt-5-pro": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.2-pro", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "azure", @@ -7245,7 +7521,9 @@ "supports_vision": true }, "azure/gpt-5.1": { - "deprecation_date": "2027-05-15", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.2", "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_batches": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, @@ -7294,6 +7572,8 @@ "azure/gpt-5-chat": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", "max_input_tokens": 128000, @@ -7318,6 +7598,8 @@ "azure/gpt-5.1-chat": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7339,6 +7621,8 @@ "azure/gpt-5.2-chat": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.75e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7359,6 +7643,8 @@ "azure/gpt-5.3-chat": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.75e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7379,6 +7665,8 @@ "azure/us/gpt-5.1-chat": { "cache_read_input_token_cost": 1.375e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-chat-latest", "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7400,6 +7688,8 @@ "azure/us/gpt-5.2-chat": { "cache_read_input_token_cost": 1.925e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-chat-latest", "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7420,6 +7710,8 @@ "azure/us/gpt-5.3-chat": { "cache_read_input_token_cost": 1.925e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-chat-latest", "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7440,6 +7732,8 @@ "azure/eu/gpt-5.1-chat": { "cache_read_input_token_cost": 1.375e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7461,6 +7755,8 @@ "azure/eu/gpt-5.2-chat": { "cache_read_input_token_cost": 1.925e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7481,6 +7777,8 @@ "azure/eu/gpt-5.3-chat": { "cache_read_input_token_cost": 1.925e-07, "deprecation_date": "2026-06-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-chat-latest", "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", "max_input_tokens": 111616, @@ -7498,38 +7796,10 @@ "supports_response_schema": true, "supports_tool_choice": true }, - "azure/us/o1-preview": { - "cache_read_input_token_cost": 8.25e-06, - "deprecation_date": "2025-07-28", - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions" - ], - "supports_prompt_caching": true - }, - "azure/eu/o1-preview": { - "cache_read_input_token_cost": 8.25e-06, - "deprecation_date": "2025-07-28", - "input_cost_per_token": 1.65e-05, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 6.6e-05, - "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", - "supported_endpoints": [ - "/v1/chat/completions" - ], - "supports_prompt_caching": true - }, "azure/gpt-5.1-codex": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.2-codex", "cache_read_input_token_cost": 1.25e-07, "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", @@ -7562,6 +7832,7 @@ "azure/gpt-5.1-codex-max": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure", "max_input_tokens": 272000, @@ -7592,6 +7863,7 @@ }, "azure/gpt-5.1-codex-mini": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.5e-08, "input_cost_per_token": 2.5e-07, "litellm_provider": "azure", @@ -7623,6 +7895,8 @@ }, "azure/gpt-5.2": { "deprecation_date": "2027-06-08", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4", "cache_read_input_token_cost": 1.75e-07, "cache_read_input_token_cost_batches": 8.75e-08, "cache_read_input_token_cost_priority": 3.5e-07, @@ -7670,6 +7944,8 @@ "cache_read_input_token_cost": 1.75e-07, "cache_read_input_token_cost_priority": 3.5e-07, "deprecation_date": "2027-06-08", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.4", "input_cost_per_token": 1.75e-06, "input_cost_per_token_batches": 8.75e-07, "input_cost_per_token_priority": 3.5e-06, @@ -7714,6 +7990,8 @@ "azure/gpt-5.2-codex": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.3-codex", "input_cost_per_token": 1.75e-06, "litellm_provider": "azure", "max_input_tokens": 272000, @@ -7746,6 +8024,7 @@ "cache_read_input_token_cost": 1.75e-07, "cache_read_input_token_cost_priority": 3.5e-07, "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.75e-06, "input_cost_per_token_priority": 3.5e-06, "litellm_provider": "azure", @@ -7859,6 +8138,8 @@ }, "azure/gpt-5.4": { "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.5", "cache_read_input_token_cost": 2.5e-07, "cache_read_input_token_cost_above_272k_tokens": 5e-07, "cache_read_input_token_cost_above_272k_tokens_batches": 2.5e-07, @@ -7916,6 +8197,8 @@ }, "azure/us/gpt-5.4": { "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.5", "cache_read_input_token_cost": 2.75e-07, "cache_read_input_token_cost_above_272k_tokens": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens_batches": 2.75e-07, @@ -7965,6 +8248,8 @@ }, "azure/eu/gpt-5.4": { "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.5", "cache_read_input_token_cost": 2.75e-07, "cache_read_input_token_cost_above_272k_tokens": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens_batches": 2.75e-07, @@ -8019,6 +8304,8 @@ "cache_read_input_token_cost_priority": 5e-07, "cache_read_input_token_cost_above_272k_tokens_priority": 1e-06, "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.5", "input_cost_per_token": 2.5e-06, "input_cost_per_token_above_272k_tokens": 5e-06, "input_cost_per_token_priority": 5e-06, @@ -8074,6 +8361,8 @@ "cache_read_input_token_cost_above_272k_tokens": 5.5e-07, "cache_read_input_token_cost_priority": 5.5e-07, "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.5", "input_cost_per_token": 2.75e-06, "input_cost_per_token_priority": 5.5e-06, "output_cost_per_token": 1.65e-05, @@ -8123,6 +8412,8 @@ "cache_read_input_token_cost_above_272k_tokens": 5.5e-07, "cache_read_input_token_cost_priority": 5.5e-07, "deprecation_date": "2027-09-02", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.5", "input_cost_per_token": 2.75e-06, "input_cost_per_token_priority": 5.5e-06, "output_cost_per_token": 1.65e-05, @@ -8169,6 +8460,8 @@ }, "azure/gpt-5.4-pro": { "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.5-pro", "cache_read_input_token_cost": 3e-06, "cache_read_input_token_cost_above_272k_tokens": 6e-06, "input_cost_per_token": 3e-05, @@ -8220,6 +8513,8 @@ "cache_read_input_token_cost": 3e-06, "cache_read_input_token_cost_above_272k_tokens": 6e-06, "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.5-pro", "input_cost_per_token": 3e-05, "input_cost_per_token_above_272k_tokens": 6e-05, "input_cost_per_token_above_272k_tokens_flex": 3e-05, @@ -8332,6 +8627,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06, "cache_read_input_token_cost_flex": 2e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6-sol", "input_cost_per_token": 4e-06, "input_cost_per_token_above_272k_tokens": 8e-06, "input_cost_per_token_above_272k_tokens_flex": 4e-06, @@ -8395,6 +8692,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 1.6e-06, "cache_read_input_token_cost_flex": 2e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6-sol", "input_cost_per_token": 4e-06, "input_cost_per_token_above_272k_tokens": 8e-06, "input_cost_per_token_above_272k_tokens_flex": 4e-06, @@ -8458,6 +8757,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8e-07, "cache_read_input_token_cost_flex": 1e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6.1-terra", "input_cost_per_token": 2e-06, "input_cost_per_token_above_272k_tokens": 4e-06, "input_cost_per_token_above_272k_tokens_flex": 2e-06, @@ -8521,6 +8822,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8e-07, "cache_read_input_token_cost_flex": 1e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6.1-terra", "input_cost_per_token": 2e-06, "input_cost_per_token_above_272k_tokens": 4e-06, "input_cost_per_token_above_272k_tokens_flex": 2e-06, @@ -8584,6 +8887,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8e-08, "cache_read_input_token_cost_flex": 1e-08, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6-luna", "input_cost_per_token": 2e-07, "input_cost_per_token_above_272k_tokens": 4e-07, "input_cost_per_token_above_272k_tokens_flex": 2e-07, @@ -8647,6 +8952,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8e-08, "cache_read_input_token_cost_flex": 1e-08, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-6-luna", "input_cost_per_token": 2e-07, "input_cost_per_token_above_272k_tokens": 4e-07, "input_cost_per_token_above_272k_tokens_flex": 2e-07, @@ -8710,11 +9017,7 @@ "mode": "chat", "output_cost_per_token": 5e-05, "output_cost_per_token_above_272k_tokens": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", "supported_endpoints": [ "/v1/chat/completions", @@ -8746,7 +9049,11 @@ "cache_creation_input_token_cost_above_272k_tokens_flex": 1.25e-05, "cache_read_input_token_cost_above_272k_tokens_flex": 1e-06, "input_cost_per_token_above_272k_tokens_flex": 1e-05, - "output_cost_per_token_above_272k_tokens_flex": 3.75e-05 + "output_cost_per_token_above_272k_tokens_flex": 3.75e-05, + "input_cost_per_token_flex": 5e-06, + "output_cost_per_token_flex": 2.5e-05, + "cache_read_input_token_cost_flex": 5e-07, + "cache_creation_input_token_cost_flex": 6.25e-06 }, "azure/gpt-6-astra-2026-09-03": { "cache_creation_input_token_cost": 1.25e-05, @@ -8762,11 +9069,7 @@ "mode": "chat", "output_cost_per_token": 5e-05, "output_cost_per_token_above_272k_tokens": 7.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", "supported_endpoints": [ "/v1/chat/completions", @@ -8798,7 +9101,11 @@ "cache_creation_input_token_cost_above_272k_tokens_flex": 1.25e-05, "cache_read_input_token_cost_above_272k_tokens_flex": 1e-06, "input_cost_per_token_above_272k_tokens_flex": 1e-05, - "output_cost_per_token_above_272k_tokens_flex": 3.75e-05 + "output_cost_per_token_above_272k_tokens_flex": 3.75e-05, + "input_cost_per_token_flex": 5e-06, + "output_cost_per_token_flex": 2.5e-05, + "cache_read_input_token_cost_flex": 5e-07, + "cache_creation_input_token_cost_flex": 6.25e-06 }, "azure/gpt-6-luna": { "cache_creation_input_token_cost": 1.25e-07, @@ -8814,12 +9121,8 @@ "mode": "chat", "output_cost_per_token": 5e-07, "output_cost_per_token_above_272k_tokens": 7.5e-07, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, - "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -8846,7 +9149,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "cache_creation_input_token_cost_above_272k_tokens_flex": 1.25e-07, + "cache_creation_input_token_cost_flex": 6.25e-08, + "cache_read_input_token_cost_above_272k_tokens_flex": 1e-08, + "cache_read_input_token_cost_flex": 5e-09, + "input_cost_per_token_above_272k_tokens_flex": 1e-07, + "input_cost_per_token_flex": 5e-08, + "output_cost_per_token_above_272k_tokens_flex": 3.75e-07, + "output_cost_per_token_flex": 2.5e-07 }, "azure/gpt-6-luna-2026-09-22": { "cache_creation_input_token_cost": 1.25e-07, @@ -8862,12 +9173,8 @@ "mode": "chat", "output_cost_per_token": 5e-07, "output_cost_per_token_above_272k_tokens": 7.5e-07, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, - "source": "https://azure.microsoft.com/en-us/blog/gpt-6-astra-sol-and-luna-for-production-agents-in-microsoft-foundry/", + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, + "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -8894,7 +9201,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "cache_creation_input_token_cost_above_272k_tokens_flex": 1.25e-07, + "cache_creation_input_token_cost_flex": 6.25e-08, + "cache_read_input_token_cost_above_272k_tokens_flex": 1e-08, + "cache_read_input_token_cost_flex": 5e-09, + "input_cost_per_token_above_272k_tokens_flex": 1e-07, + "input_cost_per_token_flex": 5e-08, + "output_cost_per_token_above_272k_tokens_flex": 3.75e-07, + "output_cost_per_token_flex": 2.5e-07 }, "azure/gpt-6-sol": { "cache_creation_input_token_cost": 2.5e-06, @@ -8946,7 +9261,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 5e-06, + "cache_read_input_token_cost_flex": 1e-07, + "cache_creation_input_token_cost_flex": 1.25e-06, + "input_cost_per_token_above_272k_tokens_flex": 2e-06, + "output_cost_per_token_above_272k_tokens_flex": 7.5e-06, + "cache_read_input_token_cost_above_272k_tokens_flex": 2e-07, + "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06 }, "azure/gpt-6-sol-2026-09-22": { "cache_creation_input_token_cost": 2.5e-06, @@ -8998,7 +9321,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 5e-06, + "cache_read_input_token_cost_flex": 1e-07, + "cache_creation_input_token_cost_flex": 1.25e-06, + "input_cost_per_token_above_272k_tokens_flex": 2e-06, + "output_cost_per_token_above_272k_tokens_flex": 7.5e-06, + "cache_read_input_token_cost_above_272k_tokens_flex": 2e-07, + "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06 }, "azure/gpt-6.1-terra": { "cache_creation_input_token_cost": 1.25e-06, @@ -9061,11 +9392,7 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_above_272k_tokens": 1.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ "/v1/chat/completions", @@ -9093,7 +9420,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 5e-06, + "cache_read_input_token_cost_flex": 5e-08, + "cache_creation_input_token_cost_flex": 1.25e-06, + "input_cost_per_token_above_272k_tokens_flex": 2e-06, + "output_cost_per_token_above_272k_tokens_flex": 7.5e-06, + "cache_read_input_token_cost_above_272k_tokens_flex": 1e-07, + "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06 }, "azure/gpt-6.1-sol-2026-09-29": { "cache_creation_input_token_cost": 2.5e-06, @@ -9109,11 +9444,7 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_above_272k_tokens": 1.5e-05, - "search_context_cost_per_query": { - "search_context_size_high": 0.014, - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014 - }, + "search_context_cost_per_query": {"search_context_size_high":0.014,"search_context_size_low":0.014,"search_context_size_medium":0.014}, "source": "https://learn.microsoft.com/en-us/azure/ai-foundry/openai/concepts/models", "supported_endpoints": [ "/v1/chat/completions", @@ -9141,7 +9472,15 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 5e-06, + "cache_read_input_token_cost_flex": 5e-08, + "cache_creation_input_token_cost_flex": 1.25e-06, + "input_cost_per_token_above_272k_tokens_flex": 2e-06, + "output_cost_per_token_above_272k_tokens_flex": 7.5e-06, + "cache_read_input_token_cost_above_272k_tokens_flex": 1e-07, + "cache_creation_input_token_cost_above_272k_tokens_flex": 2.5e-06 }, "azure/us/gpt-6.1-terra": { "cache_creation_input_token_cost": 1.375e-06, @@ -9431,6 +9770,7 @@ "azure/gpt-chat-latest": { "cache_read_input_token_cost": 5e-07, "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 5e-06, "litellm_provider": "azure", "max_input_tokens": 128000, @@ -9563,6 +9903,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 1.76e-06, "cache_read_input_token_cost_priority": 8.8e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-6-sol", "input_cost_per_token": 4.4e-06, "input_cost_per_token_above_272k_tokens": 8.8e-06, "input_cost_per_token_above_272k_tokens_priority": 1.76e-05, @@ -9618,6 +9960,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8.8e-07, "cache_read_input_token_cost_priority": 4.4e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-6.1-terra", "input_cost_per_token": 2.2e-06, "input_cost_per_token_above_272k_tokens": 4.4e-06, "input_cost_per_token_above_272k_tokens_priority": 8.8e-06, @@ -9673,6 +10017,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8.8e-08, "cache_read_input_token_cost_priority": 4.4e-08, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-6-luna", "input_cost_per_token": 2.2e-07, "input_cost_per_token_above_272k_tokens": 4.4e-07, "input_cost_per_token_above_272k_tokens_priority": 8.8e-07, @@ -9869,6 +10215,7 @@ "azure/us/gpt-chat-latest": { "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 5.5e-06, "litellm_provider": "azure", "max_input_tokens": 128000, @@ -9965,6 +10312,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 1.76e-06, "cache_read_input_token_cost_priority": 8.8e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-6-sol", "input_cost_per_token": 4.4e-06, "input_cost_per_token_above_272k_tokens": 8.8e-06, "input_cost_per_token_above_272k_tokens_priority": 1.76e-05, @@ -10020,6 +10369,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8.8e-07, "cache_read_input_token_cost_priority": 4.4e-07, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-6.1-terra", "input_cost_per_token": 2.2e-06, "input_cost_per_token_above_272k_tokens": 4.4e-06, "input_cost_per_token_above_272k_tokens_priority": 8.8e-06, @@ -10075,6 +10426,8 @@ "cache_read_input_token_cost_above_272k_tokens_priority": 8.8e-08, "cache_read_input_token_cost_priority": 4.4e-08, "deprecation_date": "2028-01-11", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-6-luna", "input_cost_per_token": 2.2e-07, "input_cost_per_token_above_272k_tokens": 4.4e-07, "input_cost_per_token_above_272k_tokens_priority": 8.8e-07, @@ -10122,6 +10475,8 @@ }, "azure/gpt-5.5": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, "cache_read_input_token_cost_above_272k_tokens_batches": 5e-07, @@ -10182,6 +10537,8 @@ }, "azure/us/gpt-5.5": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens": 1.1e-06, "cache_read_input_token_cost_above_272k_tokens_batches": 5.5e-07, @@ -10236,6 +10593,8 @@ }, "azure/eu/gpt-5.5": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens": 1.1e-06, "cache_read_input_token_cost_above_272k_tokens_batches": 5.5e-07, @@ -10337,6 +10696,8 @@ "supports_vision": true, "supports_web_search": true, "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6", "input_cost_per_token_above_272k_tokens_batches": 5e-06, "input_cost_per_token_above_272k_tokens_flex": 5e-06, "input_cost_per_token_batches": 2.5e-06, @@ -10347,6 +10708,8 @@ }, "azure/gpt-5.5-2026-04-24": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6", "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, "cache_read_input_token_cost_priority": 1.25e-06, @@ -10450,6 +10813,8 @@ "supports_vision": true, "supports_web_search": true, "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6", "input_cost_per_token_above_272k_tokens_batches": 5.5e-06, "input_cost_per_token_batches": 2.75e-06, "output_cost_per_token_above_272k_tokens_batches": 2.475e-05, @@ -10458,6 +10823,8 @@ }, "azure/us/gpt-5.5-2026-04-24": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens": 1.1e-06, "cache_read_input_token_cost_priority": 1.375e-06, @@ -10555,6 +10922,8 @@ "supports_vision": true, "supports_web_search": true, "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6", "input_cost_per_token_above_272k_tokens_batches": 5.5e-06, "input_cost_per_token_batches": 2.75e-06, "output_cost_per_token_above_272k_tokens_batches": 2.475e-05, @@ -10563,6 +10932,8 @@ }, "azure/eu/gpt-5.5-2026-04-24": { "deprecation_date": "2027-10-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_above_272k_tokens": 1.1e-06, "cache_read_input_token_cost_priority": 1.375e-06, @@ -10699,6 +11070,7 @@ }, "azure/gpt-5.4-mini": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 7.5e-08, "cache_read_input_token_cost_batches": 3.75e-08, "cache_read_input_token_cost_flex": 3.75e-08, @@ -10753,6 +11125,7 @@ "cache_read_input_token_cost_flex": 3.75e-08, "cache_read_input_token_cost_priority": 1.5e-07, "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 7.5e-07, "litellm_provider": "azure", "max_input_tokens": 272000, @@ -10801,6 +11174,7 @@ }, "azure/gpt-5.4-nano": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_batches": 1e-08, "cache_read_input_token_cost_flex": 1e-08, @@ -10851,6 +11225,7 @@ "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_flex": 1e-08, "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2e-07, "litellm_provider": "azure", "max_input_tokens": 272000, @@ -10899,6 +11274,8 @@ "cache_read_input_image_token_cost": 2.5e-06, "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-image-1.5", "input_cost_per_image_token": 1e-05, "input_cost_per_token": 5e-06, "litellm_provider": "azure", @@ -10933,6 +11310,7 @@ }, "azure/high/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.59263611e-07, "litellm_provider": "azure", "mode": "image_generation", @@ -10943,6 +11321,7 @@ }, "azure/high/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.58945719e-07, "litellm_provider": "azure", "mode": "image_generation", @@ -10953,6 +11332,7 @@ }, "azure/high/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.58945719e-07, "litellm_provider": "azure", "mode": "image_generation", @@ -10963,6 +11343,7 @@ }, "azure/low/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.0490417e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -10973,6 +11354,7 @@ }, "azure/low/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.0172526e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -10983,6 +11365,7 @@ }, "azure/low/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 1.0172526e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -10993,6 +11376,7 @@ }, "azure/medium/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11003,6 +11387,7 @@ }, "azure/medium/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11013,6 +11398,7 @@ }, "azure/medium/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11025,6 +11411,7 @@ "cache_read_input_image_token_cost": 2.5e-07, "cache_read_input_token_cost": 2e-07, "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_image_token": 2.5e-06, "input_cost_per_token": 2e-06, "litellm_provider": "azure", @@ -11039,6 +11426,8 @@ "azure/gpt-image-1.5": { "cache_read_input_image_token_cost": 2e-06, "deprecation_date": "2026-12-16", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-image-2", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, @@ -11056,6 +11445,8 @@ "cache_read_input_image_token_cost": 2e-06, "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2026-12-16", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-image-2", "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, "litellm_provider": "azure", @@ -11071,6 +11462,7 @@ "azure/gpt-image-2": { "cache_read_input_image_token_cost": 2e-06, "deprecation_date": "2027-10-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, @@ -11088,6 +11480,7 @@ "azure/gpt-image-2.5-flare": { "cache_read_input_image_token_cost": 2e-06, "deprecation_date": "2027-09-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, @@ -11105,6 +11498,7 @@ "azure/gpt-image-2.5-sunburst": { "cache_read_input_image_token_cost": 2e-06, "deprecation_date": "2027-09-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, @@ -11123,6 +11517,7 @@ "cache_read_input_image_token_cost": 2e-06, "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-10-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 5e-06, "input_cost_per_image_token": 8e-06, "litellm_provider": "azure", @@ -11138,6 +11533,7 @@ }, "azure/low/1024-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 2.0751953125e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11148,6 +11544,7 @@ }, "azure/low/1024-x-1536/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 2.0751953125e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11158,6 +11555,7 @@ }, "azure/low/1536-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 2.0345052083e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11168,6 +11566,7 @@ }, "azure/medium/1024-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 8.056640625e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11178,6 +11577,7 @@ }, "azure/medium/1024-x-1536/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 8.056640625e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11188,6 +11588,7 @@ }, "azure/medium/1536-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 7.9752604167e-09, "litellm_provider": "azure", "mode": "image_generation", @@ -11198,6 +11599,7 @@ }, "azure/high/1024-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 3.173828125e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11208,6 +11610,7 @@ }, "azure/high/1024-x-1536/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 3.173828125e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11218,6 +11621,7 @@ }, "azure/high/1536-x-1024/gpt-image-1-mini": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_pixel": 3.1575520833e-08, "litellm_provider": "azure", "mode": "image_generation", @@ -11246,6 +11650,7 @@ }, "azure/o1": { "deprecation_date": "2026-11-19", + "successor_model": "azure/gpt-5.6-sol", "cache_read_input_token_cost": 7.5e-06, "input_cost_per_token": 1.5e-05, "litellm_provider": "azure", @@ -11263,6 +11668,7 @@ "azure/o1-2024-12-17": { "cache_read_input_token_cost": 7.5e-06, "deprecation_date": "2026-11-19", + "successor_model": "azure/gpt-5.6-sol", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "azure", @@ -11315,6 +11721,7 @@ }, "azure/o3": { "deprecation_date": "2026-11-19", + "successor_model": "azure/gpt-5.6-sol", "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -11352,6 +11759,7 @@ }, "azure/o3-2025-04-16": { "deprecation_date": "2026-11-19", + "successor_model": "azure/gpt-5.6-sol", "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -11390,6 +11798,8 @@ "azure/o3-deep-research": { "cache_read_input_token_cost": 2.5e-06, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-sol", "input_cost_per_token": 1e-05, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -11426,6 +11836,8 @@ }, "azure/o3-mini": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-terra", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, @@ -11445,6 +11857,8 @@ "azure/o3-mini-2025-01-31": { "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-terra", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "azure", @@ -11461,6 +11875,8 @@ }, "azure/o3-pro": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-sol", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "azure", @@ -11496,6 +11912,8 @@ }, "azure/o3-pro-2025-06-10": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-sol", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "azure", @@ -11531,6 +11949,8 @@ }, "azure/o4-mini": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-terra", "cache_read_input_token_cost": 2.75e-07, "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, @@ -11569,6 +11989,8 @@ "azure/o4-mini-2025-04-16": { "cache_read_input_token_cost": 2.75e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-5.6-terra", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "azure", @@ -11620,6 +12042,7 @@ }, "azure/text-embedding-3-large": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.43e-07, "litellm_provider": "azure", "max_input_tokens": 8192, @@ -11629,6 +12052,7 @@ }, "azure/text-embedding-3-small": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.2e-08, "litellm_provider": "azure", "max_input_tokens": 8192, @@ -11638,6 +12062,7 @@ }, "azure/text-embedding-ada-002": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.1e-07, "litellm_provider": "azure", "max_input_tokens": 8192, @@ -11683,6 +12108,8 @@ }, "azure/us/gpt-4.1-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_priority": 9.63e-07, "input_cost_per_token": 2.2e-06, @@ -11725,6 +12152,8 @@ }, "azure/us/gpt-4.1-mini-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-mini", "cache_read_input_token_cost": 1.1e-07, "cache_read_input_token_cost_priority": 1.93e-07, "input_cost_per_token": 4.4e-07, @@ -11767,6 +12196,8 @@ }, "azure/us/gpt-4.1-nano-2025-04-14": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-nano", "cache_read_input_token_cost": 2.8e-08, "input_cost_per_token": 1.1e-07, "input_cost_per_token_batches": 5.5e-08, @@ -11800,6 +12231,8 @@ }, "azure/us/gpt-4o-2024-08-06": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, "input_cost_per_token_batches": 1.375e-06, @@ -11819,6 +12252,8 @@ }, "azure/us/gpt-4o": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_creation_input_token_cost": 1.38e-06, "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, @@ -11838,6 +12273,8 @@ }, "azure/us/gpt-4o-2024-11-20": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_creation_input_token_cost": 1.38e-06, "cache_read_input_token_cost": 1.375e-06, "input_cost_per_token": 2.75e-06, @@ -11858,6 +12295,7 @@ "azure/us/gpt-4o-mini": { "cache_read_input_token_cost": 8.3e-08, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.65e-07, "input_cost_per_token_batches": 8.3e-08, "litellm_provider": "azure", @@ -11881,6 +12319,7 @@ "azure/us/gpt-4o-mini-2024-07-18": { "cache_read_input_token_cost": 8.3e-08, "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.65e-07, "input_cost_per_token_batches": 8.3e-08, "litellm_provider": "azure", @@ -11919,26 +12358,6 @@ "supports_system_messages": true, "supports_tool_choice": true }, - "azure/us/gpt-4o-realtime-preview-2024-10-01": { - "cache_creation_input_audio_token_cost": 2.2e-05, - "cache_read_input_token_cost": 2.75e-06, - "deprecation_date": "2025-03-26", - "input_cost_per_audio_token": 0.00011, - "input_cost_per_token": 5.5e-06, - "litellm_provider": "azure", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "realtime", - "output_cost_per_audio_token": 0.00022, - "output_cost_per_token": 2.2e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "azure/us/gpt-4o-realtime-preview-2024-12-17": { "cache_read_input_audio_token_cost": 2.5e-06, "cache_read_input_token_cost": 2.75e-06, @@ -11970,6 +12389,8 @@ "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_priority": 2.75e-07, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "input_cost_per_token": 1.375e-06, "input_cost_per_token_batches": 6.875e-07, "input_cost_per_token_priority": 2.75e-06, @@ -12013,7 +12434,9 @@ "azure/us/gpt-5-mini-2025-08-07": { "cache_read_input_token_cost": 2.75e-08, "cache_read_input_token_cost_priority": 4.95e-08, - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-mini", "input_cost_per_token": 2.75e-07, "input_cost_per_token_batches": 1.375e-07, "input_cost_per_token_priority": 4.95e-07, @@ -12057,6 +12480,8 @@ "azure/us/gpt-5-nano-2025-08-07": { "cache_read_input_token_cost": 5.5e-09, "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-nano", "input_cost_per_token": 5.5e-08, "input_cost_per_token_batches": 2.75e-08, "litellm_provider": "azure", @@ -12096,7 +12521,9 @@ "cache_read_input_token_cost_batches": 2.75e-09 }, "azure/us/gpt-5.1": { - "deprecation_date": "2027-05-15", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.2", "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_batches": 6.875e-08, "cache_read_input_token_cost_priority": 2.75e-07, @@ -12144,6 +12571,8 @@ }, "azure/us/gpt-5.1-codex": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.2-codex", "cache_read_input_token_cost": 1.375e-07, "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", @@ -12175,6 +12604,7 @@ }, "azure/us/gpt-5.1-codex-mini": { "deprecation_date": "2027-05-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.75e-08, "input_cost_per_token": 2.75e-07, "litellm_provider": "azure", @@ -12207,6 +12637,7 @@ "azure/us/o1": { "cache_read_input_token_cost": 8.25e-06, "deprecation_date": "2026-11-19", + "successor_model": "azure/us/gpt-5.6-sol", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -12225,6 +12656,7 @@ "azure/us/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, "deprecation_date": "2026-11-19", + "successor_model": "azure/us/gpt-5.6-sol", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -12258,6 +12690,7 @@ }, "azure/us/o3": { "deprecation_date": "2026-11-19", + "successor_model": "azure/us/gpt-5.6-sol", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 2.2e-06, "input_cost_per_token_batches": 1.1e-06, @@ -12295,6 +12728,7 @@ }, "azure/us/o3-2025-04-16": { "deprecation_date": "2026-11-19", + "successor_model": "azure/us/gpt-5.6-sol", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 2.2e-06, "input_cost_per_token_batches": 1.1e-06, @@ -12333,6 +12767,8 @@ "azure/us/o3-mini": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -12350,6 +12786,8 @@ "azure/us/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -12367,6 +12805,8 @@ "azure/us/o4-mini": { "cache_read_input_token_cost": 3.03e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -12392,6 +12832,8 @@ "azure/us/o4-mini-2025-04-16": { "cache_read_input_token_cost": 3.03e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6-terra", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -12423,6 +12865,8 @@ }, "azure_ai/Cohere-embed-v3-english": { "deprecation_date": "2027-02-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/Cohere-Embed-V5-Fast", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 512, @@ -12434,6 +12878,8 @@ }, "azure_ai/Cohere-embed-v3-multilingual": { "deprecation_date": "2027-02-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/Cohere-Embed-V5-Fast", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 512, @@ -12445,6 +12891,7 @@ }, "azure_ai/Codestral-2501": { "deprecation_date": "2027-02-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 3e-07, "litellm_provider": "azure_ai", "max_input_tokens": 256000, @@ -12466,6 +12913,7 @@ }, "azure_ai/FLUX-1.1-pro": { "deprecation_date": "2027-01-05", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "litellm_provider": "azure_ai", "max_input_tokens": 5000, "mode": "image_generation", @@ -12477,6 +12925,7 @@ }, "azure_ai/FLUX.1-Kontext-pro": { "deprecation_date": "2027-01-05", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "litellm_provider": "azure_ai", "max_input_tokens": 5000, "mode": "image_generation", @@ -12488,6 +12937,7 @@ }, "azure_ai/flux.2-pro": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "litellm_provider": "azure_ai", "max_input_tokens": 32000, "mode": "image_generation", @@ -12499,6 +12949,7 @@ }, "azure_ai/FLUX.2-flex": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_pixel": 5e-08, "litellm_provider": "azure_ai", "max_input_tokens": 32000, @@ -12549,6 +13000,7 @@ }, "azure_ai/FW-GLM-5": { "deprecation_date": "2027-07-01", + "successor_model": "azure_ai/FW-GLM-5.2", "cache_read_input_token_cost": 2.2e-07, "input_cost_per_token": 1.1e-06, "litellm_provider": "azure_ai", @@ -12565,6 +13017,7 @@ }, "azure_ai/FW-GLM-5.1": { "deprecation_date": "2027-07-01", + "successor_model": "azure_ai/FW-GLM-5.2", "cache_read_input_token_cost": 2.86e-07, "input_cost_per_token": 1.54e-06, "litellm_provider": "azure_ai", @@ -12822,6 +13275,8 @@ "/v1/images/edits" ], "deprecation_date": "2026-10-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/MAI-Image-2.6", "max_input_tokens": 32000 }, "azure_ai/MAI-Image-2.5-Flash": { @@ -12837,10 +13292,13 @@ "/v1/images/edits" ], "deprecation_date": "2026-10-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/MAI-Image-2.6-Flash", "max_input_tokens": 32000 }, "azure_ai/MAI-Image-2.5-Pro": { "deprecation_date": "2026-10-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_image_token": 8e-06, "input_cost_per_token": 5e-06, "litellm_provider": "azure_ai", @@ -12880,6 +13338,7 @@ }, "azure_ai/Llama-3.3-70B-Instruct": { "deprecation_date": "2027-01-31", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 7.1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -12893,6 +13352,7 @@ }, "azure_ai/Llama-4-Maverick-17B-128E-Instruct-FP8": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 2.5e-07, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -12907,6 +13367,7 @@ }, "azure_ai/Llama-4-Scout-17B-16E-Instruct": { "deprecation_date": "2027-01-31", + "deprecation_source": 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5.2e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true, - "supports_vision": true - }, "azure_ai/Phi-4": { "deprecation_date": "2027-01-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "microsoft--phi-4", "input_cost_per_token": 1.25e-07, "litellm_provider": "azure_ai", "max_input_tokens": 16384, @@ -13076,6 +13398,8 @@ }, "azure_ai/Phi-4-mini-instruct": { "deprecation_date": "2027-01-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "microsoft--phi-4", "input_cost_per_token": 7.5e-08, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -13088,6 +13412,8 @@ }, "azure_ai/Phi-4-multimodal-instruct": { "deprecation_date": "2027-01-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "microsoft--phi-4", "input_cost_per_audio_token": 4e-06, "input_cost_per_token": 8e-08, "litellm_provider": "azure_ai", @@ -13103,6 +13429,8 @@ }, "azure_ai/Phi-4-mini-reasoning": { "deprecation_date": "2027-01-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "microsoft--phi-4", "input_cost_per_token": 7.5e-08, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -13115,6 +13443,8 @@ }, "azure_ai/Phi-4-reasoning": { "deprecation_date": "2027-01-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "microsoft--phi-4", "input_cost_per_token": 1.25e-07, "litellm_provider": "azure_ai", "max_input_tokens": 32768, @@ -13148,6 +13478,7 @@ }, "azure_ai/Cohere-parse-v5": { "deprecation_date": "2026-12-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "litellm_provider": "azure_ai", "mode": "ocr", "ocr_cost_per_page": 0.0015, @@ -13158,6 +13489,8 @@ }, "azure_ai/cohere-command-a": { "deprecation_date": "2027-02-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "coherelabs-command-a-plus-05-2026-fp81", "input_cost_per_token": 2.5e-06, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -13198,6 +13531,7 @@ }, "azure_ai/MAI-DS-R1": { "deprecation_date": "2026-02-27", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", "input_cost_per_token": 1.35e-06, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13209,30 +13543,10 @@ "supports_reasoning": true, "supports_tool_choice": true }, - "azure_ai/cohere-rerank-v3-english": { - "deprecation_date": "2025-06-30", - "input_cost_per_query": 0.002, - "input_cost_per_token": 0.0, - "litellm_provider": "azure_ai", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "mode": "rerank", - "output_cost_per_token": 0.0, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models" - }, - "azure_ai/cohere-rerank-v3-multilingual": { - "deprecation_date": "2025-06-30", - "input_cost_per_query": 0.002, - "input_cost_per_token": 0.0, - "litellm_provider": "azure_ai", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "mode": "rerank", - "output_cost_per_token": 0.0, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models" - }, "azure_ai/cohere-rerank-v4.0-pro": { "deprecation_date": "2027-09-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "Cohere-rerank-v5-pro", "input_cost_per_query": 0.0025, "input_cost_per_token": 0.0, "litellm_provider": "azure_ai", @@ -13244,6 +13558,8 @@ }, "azure_ai/cohere-rerank-v4.0-fast": { "deprecation_date": "2027-09-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "Cohere-rerank-v5-fast", "input_cost_per_query": 0.002, "input_cost_per_token": 0.0, "litellm_provider": "azure_ai", @@ -13255,6 +13571,8 @@ }, "azure_ai/deepseek-v3.2": { "deprecation_date": "2027-11-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/deepseek-v4.1-flash", "input_cost_per_token": 5.8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13271,6 +13589,8 @@ }, "azure_ai/deepseek-v3.2-speciale": { "deprecation_date": "2027-11-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/deepseek-v4-pro", "input_cost_per_token": 5.8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13285,20 +13605,9 @@ "supports_reasoning": true, "supports_tool_choice": true }, - "azure_ai/deepseek-v3": { - "deprecation_date": "2025-08-31", - "input_cost_per_token": 1.14e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 4.56e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true - }, "azure_ai/deepseek-v4-pro": { "deprecation_date": "2028-02-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.74e-06, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -13315,6 +13624,8 @@ }, "azure_ai/deepseek-v4-flash": { "deprecation_date": "2028-02-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/DeepSeek-V4-Flash-0731", "input_cost_per_token": 1.9e-07, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -13332,6 +13643,7 @@ "azure_ai/DeepSeek-V4-Flash-0731": { "cache_read_input_token_cost": 1.4e-08, "deprecation_date": "2026-12-03", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 4.4e-07, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -13347,6 +13659,8 @@ }, "azure_ai/embed-v-4-0": { "deprecation_date": "2027-06-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/Cohere-Embed-V5-Fast", "input_cost_per_token": 1.2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13366,6 +13680,8 @@ }, "azure_ai/grok-4": { "deprecation_date": "2027-01-31", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/grok-4.3", "input_cost_per_token": 3e-06, "litellm_provider": "azure_ai", "max_input_tokens": 262000, @@ -13424,6 +13740,7 @@ "azure_ai/grok-4-20-reasoning": { "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-04-06", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure_ai", "max_input_tokens": 262000, @@ -13443,6 +13760,7 @@ "azure_ai/grok-4-20-non-reasoning": { "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2027-04-06", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 1.25e-06, "litellm_provider": "azure_ai", "max_input_tokens": 262000, @@ -13460,6 +13778,7 @@ }, "azure_ai/grok-4-1-fast-non-reasoning": { "deprecation_date": "2027-05-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", @@ -13475,9 +13794,14 @@ }, "azure_ai/grok-4-1-fast-reasoning": { "deprecation_date": "2027-05-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", + "token_count_framing": 149, + "token_count_tool_framing": 302, + "token_count_responses_framing": 145, + "token_count_responses_tool_framing": 100, "max_input_tokens": 128000, "max_output_tokens": 128000, "mode": "chat", @@ -13491,6 +13815,7 @@ }, "azure_ai/grok-code-fast-1": { "deprecation_date": "2027-01-31", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 2e-07, "litellm_provider": "azure_ai", "max_input_tokens": 256000, @@ -13506,6 +13831,7 @@ }, "azure_ai/jais-30b-chat": { "deprecation_date": "2026-01-30", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", "input_cost_per_token": 0.0032, "litellm_provider": "azure_ai", "max_input_tokens": 8192, @@ -13515,20 +13841,9 @@ "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", "supports_pdf_input": false }, - "azure_ai/jamba-instruct": { - "deprecation_date": "2025-03-01", - "input_cost_per_token": 5e-07, - "litellm_provider": "azure_ai", - "max_input_tokens": 70000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 7e-07, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_pdf_input": false, - "supports_tool_choice": true - }, "azure_ai/kimi-k2.5": { "deprecation_date": "2027-01-26", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 6e-07, "litellm_provider": "azure_ai", "max_input_tokens": 262144, @@ -13546,6 +13861,7 @@ }, "azure_ai/kimi-k2.6": { "deprecation_date": "2027-04-16", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 9.5e-07, "litellm_provider": "azure_ai", "max_input_tokens": 262144, @@ -13570,6 +13886,8 @@ }, "azure_ai/ministral-3b": { "deprecation_date": "2026-12-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "ministral-ministral-4b-instruct", "input_cost_per_token": 4e-08, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13581,32 +13899,6 @@ "supports_pdf_input": false, "supports_tool_choice": true }, - "azure_ai/mistral-large": { - "deprecation_date": "2025-04-15", - "input_cost_per_token": 4e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 32000, - "max_output_tokens": 8191, - "mode": "chat", - "output_cost_per_token": 1.2e-05, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_tool_choice": true - }, - "azure_ai/mistral-large-2407": { - "deprecation_date": "2025-05-13", - "input_cost_per_token": 2e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 128000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 6e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_tool_choice": true - }, "azure_ai/mistral-large-latest": { "input_cost_per_token": 2e-06, "litellm_provider": "azure_ai", @@ -13634,6 +13926,8 @@ }, "azure_ai/mistral-medium-2505": { "deprecation_date": "2026-12-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/mistral-medium-3-5", "input_cost_per_token": 4e-07, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -13647,6 +13941,8 @@ }, "azure_ai/mistral-nemo": { "deprecation_date": "2026-01-30", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", + "successor_model": "azure_ai/mistral-small-2503", "input_cost_per_token": 1.5e-07, "litellm_provider": "azure_ai", "max_input_tokens": 131072, @@ -13657,21 +13953,10 @@ "supports_function_calling": true, "supports_pdf_input": false }, - "azure_ai/mistral-small": { - "deprecation_date": "2025-07-31", - "input_cost_per_token": 1e-06, - "litellm_provider": "azure_ai", - "max_input_tokens": 32000, - "max_output_tokens": 8191, - "mode": "chat", - "output_cost_per_token": 3e-06, - "source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", - "supports_function_calling": true, - "supports_pdf_input": false, - "supports_tool_choice": true - }, "azure_ai/mistral-small-2503": { "deprecation_date": "2027-02-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "mistralai-mistral-small-4-119b-2603", "input_cost_per_token": 1e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -13685,6 +13970,8 @@ }, "babbage-002": { "deprecation_date": "2026-09-28", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 4e-07, "input_cost_per_token_batches": 2e-07, "litellm_provider": "text-completion-openai", @@ -13831,7 +14118,7 @@ "input_cost_per_token_flex": 3.7e-07, "input_cost_per_token_priority": 1.295e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 2.22e-06, @@ -13845,10 +14132,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/ap-northeast-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -13893,6 +14181,7 @@ }, "bedrock/ap-northeast-1/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 7.3e-07, "input_cost_per_token_flex": 3.6e-07, "litellm_provider": "bedrock", @@ -13945,6 +14234,7 @@ }, "bedrock/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 6e-07, "input_cost_per_token_flex": 3e-07, "litellm_provider": "bedrock", @@ -13978,6 +14268,7 @@ }, "bedrock/ap-south-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 3.18e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -13988,6 +14279,7 @@ }, "bedrock/ap-south-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3.6e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14002,7 +14294,7 @@ "input_cost_per_token_flex": 3.7e-07, "input_cost_per_token_priority": 1.295e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 2.22e-06, @@ -14016,10 +14308,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/ap-south-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -14064,6 +14357,7 @@ }, "bedrock/ap-south-1/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 7.1e-07, "input_cost_per_token_flex": 3.6e-07, "litellm_provider": "bedrock", @@ -14140,12 +14434,12 @@ "input_cost_per_token": 7.4e-07, "input_cost_per_token_flex": 3.7e-07, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 2.22e-06, "output_cost_per_token_flex": 1.11e-06, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.html", + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md", "supports_audio_input": false, "supports_function_calling": true, "supports_native_structured_output": true, @@ -14156,6 +14450,7 @@ }, "bedrock/ap-southeast-3/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-minimax-minimax-m2-1.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_flex": 1.8e-07, "litellm_provider": "bedrock", @@ -14226,6 +14521,7 @@ }, "bedrock/ca-central-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 3.05e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14236,6 +14532,7 @@ }, "bedrock/ca-central-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14250,7 +14547,7 @@ "input_cost_per_token_flex": 3.7e-07, "input_cost_per_token_priority": 1.295e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 2.22e-06, @@ -14264,10 +14561,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/eu-north-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -14411,6 +14709,7 @@ }, "bedrock/eu-central-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -14472,6 +14771,7 @@ }, "bedrock/eu-west-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 2.86e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14482,6 +14782,7 @@ }, "bedrock/eu-west-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3.2e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14492,6 +14793,7 @@ }, "bedrock/eu-west-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -14553,6 +14855,7 @@ }, "bedrock/eu-west-2/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 3.45e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14563,6 +14866,7 @@ }, "bedrock/eu-west-2/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3.9e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14573,6 +14877,7 @@ }, "bedrock/eu-west-2/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 4.7e-07, "input_cost_per_token_batches": 2.35e-07, "input_cost_per_token_flex": 2.35e-07, @@ -14660,6 +14965,7 @@ }, "bedrock/eu-west-3/mistral.mistral-7b-instruct-v0:2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mistral-7b-instruct.md", "input_cost_per_token": 2e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -14681,6 +14987,7 @@ }, "bedrock/eu-west-3/mistral.mixtral-8x7b-instruct-v0:1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mixtral-8x7b-instruct.md", "input_cost_per_token": 5.9e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -14692,6 +14999,7 @@ }, "bedrock/eu-south-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-minimax-minimax-m2-1.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_flex": 1.8e-07, "litellm_provider": "bedrock", @@ -14762,6 +15070,7 @@ }, "bedrock/sa-east-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 4.45e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14772,6 +15081,7 @@ }, "bedrock/sa-east-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 5e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14786,7 +15096,7 @@ "input_cost_per_token_flex": 3.7e-07, "input_cost_per_token_priority": 1.295e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 2.22e-06, @@ -14800,10 +15110,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/sa-east-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3.6e-07, "input_cost_per_token_batches": 1.8e-07, "input_cost_per_token_flex": 1.8e-07, @@ -14848,6 +15159,7 @@ }, "bedrock/sa-east-1/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 7.3e-07, "input_cost_per_token_flex": 3.6e-07, "litellm_provider": "bedrock", @@ -14979,6 +15291,7 @@ }, "bedrock/us-east-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 2.65e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14989,6 +15302,7 @@ }, "bedrock/us-east-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -14999,6 +15313,7 @@ }, "bedrock/us-east-1/mistral.mistral-7b-instruct-v0:2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mistral-7b-instruct.md", "input_cost_per_token": 1.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -15020,6 +15335,7 @@ }, "bedrock/us-east-1/mistral.mixtral-8x7b-instruct-v0:1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mixtral-8x7b-instruct.md", "input_cost_per_token": 4.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -15035,7 +15351,7 @@ "input_cost_per_token_flex": 3.1e-07, "input_cost_per_token_priority": 1.085e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 1.85e-06, @@ -15049,10 +15365,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/us-east-1/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -15096,6 +15413,7 @@ }, "bedrock/us-east-1/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 6e-07, "input_cost_per_token_flex": 3e-07, "litellm_provider": "bedrock", @@ -15156,7 +15474,7 @@ "input_cost_per_token_flex": 3.1e-07, "input_cost_per_token_priority": 1.085e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 1.85e-06, @@ -15170,10 +15488,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/us-east-2/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -15218,6 +15537,7 @@ }, "bedrock/us-east-2/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 6e-07, "input_cost_per_token_flex": 3e-07, "litellm_provider": "bedrock", @@ -15292,7 +15612,7 @@ "output_vector_size": 1536 }, "bedrock/us-gov-east-1/amazon.titan-embed-text-v2:0": { - "input_cost_per_token": 2e-07, + "input_cost_per_token": 3e-08, "litellm_provider": "bedrock", "max_input_tokens": 8192, "mode": "embedding", @@ -15328,6 +15648,8 @@ "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "successor_model": "bedrock/us-gov-east-1/anthropic.claude-sonnet-5-5", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, @@ -15358,6 +15680,7 @@ "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, @@ -15377,7 +15700,8 @@ "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "token_count_model": {"model":"anthropic.claude-sonnet-4-5-20250929-v1:0","litellm_provider":"bedrock"} }, "bedrock/us-gov-east-1/meta.llama3-70b-instruct-v1:0": { "input_cost_per_token": 2.65e-06, @@ -15405,8 +15729,10 @@ "input_cost_per_image": 7.2e-05, "input_cost_per_video_per_second": 0.00084, "input_cost_per_audio_per_second": 0.000168, + "input_cost_per_token_batches": 8.1e-08, "output_cost_per_token": 0.0, "output_vector_size": 3072, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_embedding_image_input": true, "supports_image_input": true, "supports_video_input": true, @@ -15415,11 +15741,14 @@ "bedrock/us-gov-west-1/amazon.nova-lite-v1:0": { "cache_read_input_token_cost": 1.8e-08, "input_cost_per_token": 7.2e-08, + "input_cost_per_token_batches": 3.6e-08, "litellm_provider": "bedrock", "max_input_tokens": 300000, "max_output_tokens": 10000, "mode": "chat", "output_cost_per_token": 2.88e-07, + "output_cost_per_token_batches": 1.44e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -15430,11 +15759,14 @@ "bedrock/us-gov-west-1/amazon.nova-micro-v1:0": { "cache_read_input_token_cost": 1.05e-08, "input_cost_per_token": 4.2e-08, + "input_cost_per_token_batches": 2.1e-08, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 10000, "mode": "chat", "output_cost_per_token": 1.68e-07, + "output_cost_per_token_batches": 8.4e-08, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_function_calling": true, "supports_prompt_caching": true, "supports_response_schema": true, @@ -15442,12 +15774,21 @@ }, "bedrock/us-gov-west-1/amazon.nova-pro-v1:0": { "cache_read_input_token_cost": 2.4e-07, + "cache_read_input_token_cost_flex": 1.2e-07, + "cache_read_input_token_cost_priority": 4.2e-07, "input_cost_per_token": 9.6e-07, + "input_cost_per_token_batches": 4.8e-07, + "input_cost_per_token_flex": 4.8e-07, + "input_cost_per_token_priority": 1.68e-06, "litellm_provider": "bedrock", "max_input_tokens": 300000, "max_output_tokens": 10000, "mode": "chat", "output_cost_per_token": 3.84e-06, + "output_cost_per_token_batches": 1.92e-06, + "output_cost_per_token_flex": 1.92e-06, + "output_cost_per_token_priority": 6.72e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -15500,6 +15841,8 @@ "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "successor_model": "bedrock/us-gov-west-1/anthropic.claude-sonnet-5-5", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, @@ -15530,6 +15873,7 @@ "cache_creation_input_token_cost_above_1hr": 7.2e-06, "cache_read_input_token_cost": 3.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "input_cost_per_token": 3.6e-06, "litellm_provider": "bedrock", "supports_tool_search": true, @@ -15549,9 +15893,12 @@ "supports_native_structured_output": true, "supports_parallel_tool_use_config": true, "prompt_cache_min_tokens": 1024, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "token_count_model": {"model":"anthropic.claude-sonnet-4-5-20250929-v1:0","litellm_provider":"bedrock"} }, "bedrock/us-gov-west-1/meta.llama3-70b-instruct-v1:0": { + "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 2.65e-06, "litellm_provider": "bedrock", "max_input_tokens": 8000, @@ -15562,6 +15909,8 @@ "supports_pdf_input": true }, "bedrock/us-gov-west-1/meta.llama3-8b-instruct-v1:0": { + "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3e-07, "litellm_provider": "bedrock", "max_input_tokens": 8000, @@ -15573,6 +15922,7 @@ }, "bedrock/us-west-1/meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 2.65e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -15583,6 +15933,7 @@ }, "bedrock/us-west-1/meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -15672,6 +16023,7 @@ }, "bedrock/us-west-2/mistral.mistral-7b-instruct-v0:2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mistral-7b-instruct.md", "input_cost_per_token": 1.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -15693,6 +16045,7 @@ }, "bedrock/us-west-2/mistral.mixtral-8x7b-instruct-v0:1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mixtral-8x7b-instruct.md", "input_cost_per_token": 4.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -15708,7 +16061,7 @@ "input_cost_per_token_flex": 3.1e-07, "input_cost_per_token_priority": 1.085e-06, "litellm_provider": "bedrock", - "max_input_tokens": 163840, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 1.85e-06, @@ -15722,10 +16075,11 @@ "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/index.json" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md" }, "bedrock/us-west-2/minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -15769,6 +16123,7 @@ }, "bedrock/us-west-2/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-moonshot-ai-kimi-k2-thinking.html", "input_cost_per_token": 6e-07, "input_cost_per_token_flex": 3e-07, "litellm_provider": "bedrock", @@ -15941,17 +16296,6 @@ "supports_function_calling": true, "supports_tool_choice": true }, - "cerebras/llama3.1-70b": { - "deprecation_date": "2025-01-17", - "input_cost_per_token": 6e-07, - "litellm_provider": "cerebras", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "mode": "chat", - "output_cost_per_token": 6e-07, - "supports_function_calling": true, - "supports_tool_choice": true - }, "cerebras/llama3.1-8b": { "deprecation_date": "2026-05-27", "input_cost_per_token": 1e-07, @@ -16025,6 +16369,8 @@ "/v1/audio/transcriptions" ], "deprecation_date": "2027-02-26", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-live-transcribe", "input_cost_per_second": 0.0001, "source": "https://developers.openai.com/api/docs/pricing" }, @@ -16090,6 +16436,8 @@ "cache_creation_input_token_cost_batches": 1.875e-06, "cache_read_input_token_cost_batches": 1.5e-07, "deprecation_date": "2026-11-30", + "deprecation_source": "https://platform.claude.com/docs/en/about-claude/model-deprecations", + "successor_model": "claude-sonnet-5-5", "input_cost_per_token_batches": 1.5e-06, "litellm_provider": "anthropic", "max_input_tokens": 200000, @@ -16123,6 +16471,8 @@ "cache_creation_input_token_cost_batches": 1.875e-06, "cache_read_input_token_cost_batches": 1.5e-07, "deprecation_date": "2026-11-30", + "deprecation_source": "https://platform.claude.com/docs/en/about-claude/model-deprecations", + "successor_model": "claude-sonnet-5-5", "input_cost_per_token_batches": 1.5e-06, "litellm_provider": "anthropic", "max_input_tokens": 200000, @@ -16171,6 +16521,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -16292,6 +16643,7 @@ "cache_creation_input_token_cost_above_200k_tokens": 7.5e-06, "cache_read_input_token_cost_above_200k_tokens": 6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", "litellm_provider": "bedrock", "supports_tool_search": true, "max_input_tokens": 200000, @@ -16311,7 +16663,8 @@ "prompt_cache_min_tokens": 1024, "input_cost_per_token_batches": 1.5e-06, "output_cost_per_token_batches": 7.5e-06, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "token_count_model": {"model":"anthropic.claude-sonnet-4-5-20250929-v1:0","litellm_provider":"bedrock"} }, "claude-opus-4-5-20251101": { "supports_web_search": true, @@ -16705,6 +17058,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -17503,12 +17857,15 @@ }, "computer-use-preview": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 1024, "mode": "chat", "output_cost_per_token": 1.2e-05, + "fedramp_uplift_multiplier": 1.1, "supported_endpoints": [ "/v1/responses" ], @@ -17532,12 +17889,15 @@ }, "computer-use-preview-2025-03-11": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 1024, "mode": "chat", "output_cost_per_token": 1.2e-05, + "fedramp_uplift_multiplier": 1.1, "supported_endpoints": [ "/v1/responses" ], @@ -17562,6 +17922,7 @@ "deepseek-chat": { "cache_read_input_token_cost": 2.8e-08, "deprecation_date": "2026-07-24", + "deprecation_source": "https://api-docs.deepseek.com/updates", "input_cost_per_token": 2.8e-07, "litellm_provider": "deepseek", "max_input_tokens": 131072, @@ -17583,6 +17944,7 @@ "deepseek-reasoner": { "cache_read_input_token_cost": 2.8e-08, "deprecation_date": "2026-07-24", + "deprecation_source": "https://api-docs.deepseek.com/updates", "input_cost_per_token": 2.8e-07, "litellm_provider": "deepseek", "max_input_tokens": 131072, @@ -21565,6 +21927,7 @@ "prompt_cache_min_tokens": 512, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_function_calling": true, "supports_mid_conversation_system": true, @@ -21613,6 +21976,7 @@ "cache_creation_input_token_cost": 3.74997e-06, "cache_read_input_token_cost": 3.0002e-07, "deprecation_date": "2026-10-09", + "successor_model": "databricks/databricks-claude-sonnet-5", "input_cost_per_token": 2.99999e-06, "input_dbu_cost_per_token": 4.2857e-05, "litellm_provider": "databricks", @@ -21722,6 +22086,7 @@ "prompt_cache_min_tokens": 1024, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_function_calling": true, "supports_mid_conversation_system": true, @@ -21736,6 +22101,7 @@ "cache_creation_input_token_cost": 1.4e-07, "cache_read_input_token_cost": 2.8e-08, "deprecation_date": "2026-11-05", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "input_cost_per_token": 1.4e-07, "input_dbu_cost_per_token": 2e-06, "litellm_provider": "databricks", @@ -21749,6 +22115,7 @@ "output_cost_per_token": 2.8e-07, "output_dbu_cost_per_token": 4e-06, "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", + "successor_model": "databricks/databricks-deepseek-v4-1-flash-1017", "supported_modalities": [ "text" ], @@ -21762,14 +22129,19 @@ "supports_vision": false }, "databricks/system.ai.deepseek-v4-flash-0731": { + "deprecation_date": "2026-11-05", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/retired-models-policy", "litellm_provider": "databricks", "mode": "chat", + "source": "https://docs.databricks.com/aws/en/machine-learning/retired-models-policy", + "successor_model": "databricks/databricks-deepseek-v4-1-flash-1017", "token_count_framing": 97 }, "databricks/databricks-deepseek-v4-pro-0813": { "cache_creation_input_token_cost": 1.31999e-06, "cache_read_input_token_cost": 1.3202e-07, "deprecation_date": "2026-10-30", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "input_cost_per_token": 1.31999e-06, "input_dbu_cost_per_token": 1.8857e-05, "litellm_provider": "databricks", @@ -21782,6 +22154,7 @@ "output_cost_per_token": 3.95997e-06, "output_dbu_cost_per_token": 5.6571e-05, "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", + "successor_model": "databricks/databricks-deepseek-v4-1-flash-1017", "supported_modalities": [ "text" ], @@ -21798,6 +22171,7 @@ "cache_creation_input_token_cost": 3.0002e-07, "cache_read_input_token_cost": 3.0002e-08, "deprecation_date": "2026-10-02", + "successor_model": "databricks/databricks-gemini-3-5-flash", "input_cost_per_token": 3.0001999999999996e-07, "input_dbu_cost_per_token": 4.285999999999999e-06, "litellm_provider": "databricks", @@ -22067,7 +22441,7 @@ }, "mode": "chat", "output_cost_per_token": 3.74997e-06, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "supported_modalities": [ "text", "image", @@ -22085,7 +22459,9 @@ "input_cost_per_token_priority": 1.35002e-06, "output_cost_per_token_priority": 6.75003e-06, "cache_read_input_token_cost_priority": 1.3503e-07, - "cache_creation_input_token_cost_priority": 1.35002e-06 + "cache_creation_input_token_cost_priority": 1.35002e-06, + "supports_audio_input": true, + "supports_video_input": true }, "databricks/databricks-gemini-3-7-flash": { "cache_creation_input_token_cost": 7.4998e-07, @@ -22099,7 +22475,7 @@ }, "mode": "chat", "output_cost_per_token": 3.74997e-06, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "supported_modalities": [ "text", "image", @@ -22117,7 +22493,9 @@ "input_cost_per_token_priority": 1.35002e-06, "output_cost_per_token_priority": 6.75003e-06, "cache_read_input_token_cost_priority": 1.3503e-07, - "cache_creation_input_token_cost_priority": 1.35002e-06 + "cache_creation_input_token_cost_priority": 1.35002e-06, + "supports_audio_input": true, + "supports_video_input": true }, "databricks/databricks-gemini-3-6-flash": { "cache_creation_input_token_cost": 7.4998e-07, @@ -22133,7 +22511,7 @@ "mode": "chat", "output_cost_per_token": 3.74997e-06, "output_dbu_cost_per_token": 5.3571e-05, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "supported_modalities": [ "text", "image", @@ -22152,7 +22530,9 @@ "input_cost_per_token_priority": 1.35002e-06, "output_cost_per_token_priority": 6.75003e-06, "cache_read_input_token_cost_priority": 1.3503e-07, - "cache_creation_input_token_cost_priority": 1.35002e-06 + "cache_creation_input_token_cost_priority": 1.35002e-06, + "supports_audio_input": true, + "supports_video_input": true }, "databricks/databricks-gemini-3-5-flash": { "cache_creation_input_token_cost": 1.87502e-06, @@ -22168,7 +22548,7 @@ "mode": "chat", "output_cost_per_token": 1.124998e-05, "output_dbu_cost_per_token": 0.000160714, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "supported_modalities": [ "text", "image", @@ -22186,7 +22566,9 @@ "input_cost_per_token_priority": 3.37498e-06, "output_cost_per_token_priority": 2.025002e-05, "cache_read_input_token_cost_priority": 3.3747e-07, - "cache_creation_input_token_cost_priority": 3.37498e-06 + "cache_creation_input_token_cost_priority": 3.37498e-06, + "supports_audio_input": true, + "supports_video_input": true }, "databricks/databricks-gemini-3-5-flash-lite": { "cache_creation_input_token_cost": 3.7499e-07, @@ -22202,7 +22584,7 @@ "mode": "chat", "output_cost_per_token": 3.12501e-06, "output_dbu_cost_per_token": 4.4643e-05, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "supported_modalities": [ "text", "image", @@ -22222,7 +22604,9 @@ "input_cost_per_token_priority": 6.7501e-07, "output_cost_per_token_priority": 5.62499e-06, "cache_read_input_token_cost_priority": 6.748e-08, - "cache_creation_input_token_cost_priority": 6.7501e-07 + "cache_creation_input_token_cost_priority": 6.7501e-07, + "supports_audio_input": true, + "supports_video_input": true }, "databricks/databricks-gemma-3-12b": { "cache_creation_input_token_cost": 1.5001e-07, @@ -22836,6 +23220,7 @@ "cache_creation_input_token_cost": 1.00002e-06, "cache_read_input_token_cost": 1.7003e-07, "deprecation_date": "2026-10-30", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "input_cost_per_token": 1.00002e-06, "input_dbu_cost_per_token": 1.4286e-05, "litellm_provider": "databricks", @@ -22847,6 +23232,7 @@ "output_cost_per_token": 4.04999e-06, "output_dbu_cost_per_token": 5.7857e-05, "source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", + "successor_model": "databricks/databricks-glm-5-3", "supported_modalities": [ "text", "image" @@ -23071,6 +23457,8 @@ }, "davinci-002": { "deprecation_date": "2026-09-28", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, "litellm_provider": "text-completion-openai", @@ -23520,12 +23908,12 @@ ] }, "deepgram/streaming/nova-3": { - "input_cost_per_second": 8e-05, + "input_cost_per_second": 0.00012833, "litellm_provider": "deepgram", "metadata": { - "calculation": "$0.0048/60 seconds = $0.00008000 per second", + "calculation": "$0.0077/60 seconds = $0.00012833 per second", "note": "Nova-3 monolingual streaming, pay as you go", - "original_pricing_per_minute": 0.0048 + "original_pricing_per_minute": 0.0077 }, "mode": "audio_transcription", "output_cost_per_second": 0.0, @@ -23534,13 +23922,28 @@ "/v1/listen" ] }, - "deepgram/streaming/nova-3-multilingual": { - "input_cost_per_second": 9.667e-05, + "deepgram/streaming/nova-3-medical": { + "input_cost_per_second": 0.00012833, "litellm_provider": "deepgram", "metadata": { - "calculation": "$0.0058/60 seconds = $0.00009667 per second", + "calculation": "$0.0077/60 seconds = $0.00012833 per second", + "note": "Nova-3 Medical streaming, launch price from Deepgram's 2025-03-03 announcement. deepgram.com/pricing does not list Nova-3 Medical, and this matches its current Nova-3 monolingual streaming pay as you go rate", + "original_pricing_per_minute": 0.0077 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0.0, + "source": "https://www.businesswire.com/news/home/20250303470439/en", + "supported_endpoints": [ + "/v1/listen" + ] + }, + "deepgram/streaming/nova-3-multilingual": { + "input_cost_per_second": 0.00015333, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0092/60 seconds = $0.00015333 per second", "note": "Nova-3 multilingual (language=multi) streaming, pay as you go", - "original_pricing_per_minute": 0.0058 + "original_pricing_per_minute": 0.0092 }, "mode": "audio_transcription", "output_cost_per_second": 0.0, @@ -23950,7 +24353,7 @@ "max_output_tokens": 163840, "input_cost_per_token": 5e-07, "output_cost_per_token": 2.15e-06, - "cache_read_input_token_cost": 4e-07, + "cache_read_input_token_cost": 3.5e-07, "litellm_provider": "deepinfra", "mode": "chat", "supports_tool_choice": true, @@ -24024,7 +24427,7 @@ "max_output_tokens": 163840, "input_cost_per_token": 2.5e-07, "output_cost_per_token": 9.5e-07, - "cache_read_input_token_cost": 2.16e-07, + "cache_read_input_token_cost": 1.3e-07, "litellm_provider": "deepinfra", "mode": "chat", "supports_tool_choice": true, @@ -24397,6 +24800,7 @@ "cache_creation_input_token_cost": 0.0, "cache_read_input_token_cost": 2.8e-08, "deprecation_date": "2026-07-24", + "deprecation_source": "https://api-docs.deepseek.com/updates", "input_cost_per_token": 2.8e-07, "input_cost_per_token_cache_hit": 2.8e-08, "litellm_provider": "deepseek", @@ -24449,6 +24853,7 @@ "deepseek/deepseek-reasoner": { "cache_read_input_token_cost": 2.8e-08, "deprecation_date": "2026-07-24", + "deprecation_source": "https://api-docs.deepseek.com/updates", "input_cost_per_token": 2.8e-07, "input_cost_per_token_cache_hit": 2.8e-08, "litellm_provider": "deepseek", @@ -24502,6 +24907,7 @@ }, "deepseek.v3-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-1.html", "input_cost_per_token": 5.8e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -24520,7 +24926,7 @@ "input_cost_per_token_flex": 3.1e-07, "input_cost_per_token_priority": 1.085e-06, "litellm_provider": "bedrock_converse", - "max_input_tokens": 164000, + "max_input_tokens": 156000, "max_output_tokens": 8000, "mode": "chat", "output_cost_per_token": 1.85e-06, @@ -24531,7 +24937,7 @@ "supports_reasoning": true, "supports_native_structured_output": true, "supports_tool_choice": true, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-east-1/index.json", + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-v3-2.md", "supports_audio_input": false, "supports_response_schema": true, "supports_vision": false @@ -25311,6 +25717,7 @@ "cache_read_input_token_cost": 1.1e-07, "input_cost_per_token": 1.1e-06, "deprecation_date": "2026-10-15", + "successor_model": "eu.anthropic.claude-haiku-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -25428,6 +25835,7 @@ "supports_vision": true, "prompt_cache_min_tokens": 1024, "deprecation_date": "2027-01-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "token_count_model": { "model": "anthropic.claude-opus-4-1-20250805-v1:0", "litellm_provider": "bedrock" @@ -25462,6 +25870,8 @@ "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-10-14", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "eu.anthropic.claude-sonnet-5", "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -25505,6 +25915,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "eu.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -25538,6 +25950,7 @@ }, "eu.meta.llama3-2-1b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-1b-instruct.md", "input_cost_per_token": 1.3e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -25550,6 +25963,7 @@ }, "eu.meta.llama3-2-3b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-3b-instruct.md", "input_cost_per_token": 1.9e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -28129,6 +28543,7 @@ "cache_read_input_token_cost": 1.4e-07, "cache_read_input_token_cost_priority": 1.75e-07, "deprecation_date": "2026-09-25", + "successor_model": "fireworks_ai/accounts/fireworks/models/glm-5p3", "input_cost_per_token": 1.4e-06, "input_cost_per_token_priority": 1.75e-06, "litellm_provider": "fireworks_ai", @@ -28504,6 +28919,7 @@ "cache_read_input_token_cost": 1.4e-07, "cache_read_input_token_cost_priority": 1.75e-07, "deprecation_date": "2026-09-25", + "successor_model": "fireworks_ai/glm-5p3", "input_cost_per_token": 1.4e-06, "input_cost_per_token_priority": 1.75e-06, "litellm_provider": "fireworks_ai", @@ -28887,6 +29303,8 @@ }, "ft:babbage-002": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1.6e-06, "input_cost_per_token_batches": 8e-07, "litellm_provider": "text-completion-openai", @@ -28899,6 +29317,8 @@ }, "ft:davinci-002": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1.2e-05, "input_cost_per_token_batches": 6e-06, "litellm_provider": "text-completion-openai", @@ -28911,6 +29331,8 @@ }, "ft:gpt-3.5-turbo": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 3e-06, "input_cost_per_token_batches": 1.5e-06, "litellm_provider": "openai", @@ -28918,6 +29340,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_system_messages": true, @@ -28925,45 +29348,57 @@ }, "ft:gpt-3.5-turbo-0125": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-06, + "fedramp_uplift_multiplier": 1.1, "supports_system_messages": true, "supports_tool_choice": true }, "ft:gpt-3.5-turbo-0613": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "ft:gpt-3.5-turbo", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 4096, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-06, + "fedramp_uplift_multiplier": 1.1, "supports_system_messages": true, "supports_tool_choice": true }, "ft:gpt-3.5-turbo-1106": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-06, + "fedramp_uplift_multiplier": 1.1, "supports_system_messages": true, "supports_tool_choice": true }, "ft:gpt-4-0613": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 3e-05, "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-05, + "fedramp_uplift_multiplier": 1.1, "source": "OpenAI needs to add pricing for this ft model, will be updated when added by OpenAI. Defaulting to base model pricing", "supports_function_calling": true, "supports_system_messages": true, @@ -28973,6 +29408,8 @@ "cache_read_input_token_cost": 1.875e-06, "cache_read_input_token_cost_batches": 9e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 3.75e-06, "input_cost_per_token_batches": 2.225e-06, "litellm_provider": "openai", @@ -28980,6 +29417,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.5e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 1.25e-05, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -28994,12 +29432,15 @@ "ft:gpt-4o-2024-11-20": { "cache_creation_input_token_cost": 1.875e-06, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 3.75e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.5e-05, + "fedramp_uplift_multiplier": 1.1, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29012,6 +29453,8 @@ "cache_read_input_token_cost": 1.5e-07, "cache_read_input_token_cost_batches": 7.5e-08, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "litellm_provider": "openai", @@ -29019,6 +29462,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.2e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 6e-07, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -29033,6 +29477,8 @@ "cache_read_input_token_cost": 7.5e-07, "cache_read_input_token_cost_batches": 5e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 3e-06, "input_cost_per_token_batches": 1.5e-06, "litellm_provider": "openai", @@ -29040,6 +29486,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 1.2e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 6e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -29053,6 +29500,8 @@ "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_batches": 1e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 8e-07, "input_cost_per_token_batches": 4e-07, "litellm_provider": "openai", @@ -29060,6 +29509,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 3.2e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 1.6e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -29073,6 +29523,8 @@ "cache_read_input_token_cost": 5e-08, "cache_read_input_token_cost_batches": 2.5e-08, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-luna", "input_cost_per_token": 2e-07, "input_cost_per_token_batches": 1e-07, "litellm_provider": "openai", @@ -29080,6 +29532,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 8e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-07, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -29093,6 +29546,8 @@ "cache_read_input_token_cost": 1e-06, "cache_read_input_token_cost_batches": 5e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 4e-06, "input_cost_per_token_batches": 2e-06, "litellm_provider": "openai", @@ -29100,6 +29555,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 1.6e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 8e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -29111,19 +29567,38 @@ }, "gemini-2.5-flash": { "cache_read_input_audio_token_cost": 1e-07, - "deprecation_date": "2026-10-20", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "cache_read_input_audio_token_cost_priority": 1.8e-07, "cache_read_input_token_cost": 3e-08, "cache_read_input_token_cost_flex": 3e-08, "cache_read_input_token_cost_priority": 5.4e-08, + "deprecation_date": "2026-10-20", + "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_audio_token": 1e-06, + "input_cost_per_audio_token_above_200k_tokens": 3e-07, + "input_cost_per_audio_token_above_200k_tokens_batches": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_flex": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_priority": 1.8e-06, + "input_cost_per_audio_token_batches": 5e-07, + "input_cost_per_audio_token_flex": 5e-07, + "input_cost_per_audio_token_priority": 1.8e-06, "input_cost_per_token": 3e-07, + "input_cost_per_token_batches": 1.5e-07, + "input_cost_per_token_flex": 1.5e-07, + "input_cost_per_token_priority": 5.4e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65535, "mode": "chat", "output_cost_per_reasoning_token": 2.5e-06, "output_cost_per_token": 2.5e-06, + "output_cost_per_token_batches": 1.25e-06, + "output_cost_per_token_flex": 1.25e-06, + "output_cost_per_token_priority": 4.5e-06, + "search_context_cost_per_query": {"search_context_size_low":0.035,"search_context_size_medium":0.035,"search_context_size_high":0.035}, + "search_free_requests": {"count":1500,"period":"day","shared_group":"gemini-2-flash"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "successor_model": "gemini-3.8-flash", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -29140,6 +29615,7 @@ ], "supports_audio_output": false, "supports_function_calling": true, + "supports_image_size": false, "supports_parallel_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -29149,26 +29625,12 @@ "supports_tool_choice": true, "supports_url_context": true, "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - }, - "search_free_requests": {"count": 1500, "period": "day", "shared_group": "gemini-2-flash"}, - "google_maps_grounding_cost_per_query": 0.025, - "input_cost_per_audio_token_batches": 5e-07, - "input_cost_per_token_batches": 1.5e-07, - "input_cost_per_token_flex": 1.5e-07, - "input_cost_per_token_priority": 5.4e-07, - "input_cost_per_audio_token_priority": 1.8e-06, - "output_cost_per_token_batches": 1.25e-06, - "output_cost_per_token_flex": 1.25e-06, - "output_cost_per_token_priority": 4.5e-06, - "supports_image_size": false + "supports_web_search": true }, "gemini-2.5-flash-image": { "deprecation_date": "2027-03-15", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.1-flash-lite-image", "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, @@ -29218,12 +29680,13 @@ }, "gemini-3-pro-image": { "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, - "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_flex": 1e-07, "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, @@ -29238,6 +29701,7 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "output_cost_per_image_token_batches": 6e-05, + "output_cost_per_image_token_priority": 0.000216, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, @@ -29292,6 +29756,7 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "output_cost_per_image_token_batches": 6e-05, + "output_cost_per_image_token_priority": 0.000216, "output_cost_per_token": 1.2e-05, "output_cost_per_token_priority": 2.16e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, @@ -29332,6 +29797,7 @@ "cache_read_input_token_cost_flex": 2.5e-08, "cache_read_input_token_cost_priority": 9e-08, "deprecation_date": "2027-05-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_image": 0.00056, "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -29344,6 +29810,7 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_image_token_batches": 3e-05, + "output_cost_per_image_token_priority": 0.000108, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, @@ -29390,6 +29857,7 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_image_token_batches": 3e-05, + "output_cost_per_image_token_priority": 0.000108, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", @@ -29438,6 +29906,7 @@ "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, "output_cost_per_image_token_batches": 1.5e-05, + "output_cost_per_image_token_priority": 5.4e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, @@ -29518,17 +29987,28 @@ }, "gemini-3.1-flash-lite": { "cache_read_input_audio_token_cost": 5e-08, - "deprecation_date": "2027-05-07", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "cache_read_input_audio_token_cost_batches": 2.5e-08, + "cache_read_input_audio_token_cost_flex": 2.5e-08, + "cache_read_input_audio_token_cost_priority": 9e-08, "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, + "deprecation_date": "2027-05-07", + "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token": 5e-07, + "input_cost_per_audio_token_above_200k_tokens": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_batches": 2.5e-07, + "input_cost_per_audio_token_above_200k_tokens_flex": 2.5e-07, + "input_cost_per_audio_token_above_200k_tokens_priority": 9e-07, + "input_cost_per_audio_token_batches": 2.5e-07, + "input_cost_per_audio_token_flex": 2.5e-07, + "input_cost_per_audio_token_priority": 9e-07, "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_flex": 1.25e-07, "input_cost_per_token_priority": 4.5e-07, - "input_cost_per_audio_token_priority": 9e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65536, @@ -29538,7 +30018,10 @@ "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, "output_cost_per_token_priority": 2.7e-06, + "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "successor_model": "gemini-3.5-flash-lite", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -29556,6 +30039,7 @@ "supports_audio_input": true, "supports_audio_output": false, "supports_function_calling": true, + "supports_native_streaming": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -29567,19 +30051,11 @@ "supports_video_input": true, "supports_vision": true, "supports_web_search": true, - "supports_native_streaming": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014, - "search_context_size_high": 0.014 - }, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, - "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07 + "web_search_billing_unit": "per_query" }, "gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "cache_read_input_token_cost": 3e-08, "cache_read_input_token_cost_batches": 1.5e-08, "cache_read_input_token_cost_flex": 1.5e-08, @@ -29675,19 +30151,38 @@ }, "gemini-2.5-flash-lite": { "cache_read_input_audio_token_cost": 3e-08, - "deprecation_date": "2026-10-20", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "cache_read_input_audio_token_cost_priority": 5.4e-08, "cache_read_input_token_cost": 1e-08, "cache_read_input_token_cost_flex": 1e-08, "cache_read_input_token_cost_priority": 1.8e-08, + "deprecation_date": "2026-10-20", + "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_audio_token": 3e-07, + "input_cost_per_audio_token_above_200k_tokens": 3e-07, + "input_cost_per_audio_token_above_200k_tokens_batches": 5e-08, + "input_cost_per_audio_token_above_200k_tokens_flex": 5e-08, + "input_cost_per_audio_token_above_200k_tokens_priority": 5.4e-07, + "input_cost_per_audio_token_batches": 5e-08, + "input_cost_per_audio_token_flex": 5e-08, + "input_cost_per_audio_token_priority": 5.4e-07, "input_cost_per_token": 1e-07, + "input_cost_per_token_batches": 5e-08, + "input_cost_per_token_flex": 5e-08, + "input_cost_per_token_priority": 1.8e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65535, "mode": "chat", "output_cost_per_reasoning_token": 4e-07, "output_cost_per_token": 4e-07, + "output_cost_per_token_batches": 2e-07, + "output_cost_per_token_flex": 2e-07, + "output_cost_per_token_priority": 7.2e-07, + "search_context_cost_per_query": {"search_context_size_low":0.035,"search_context_size_medium":0.035,"search_context_size_high":0.035}, + "search_free_requests": {"count":1500,"period":"day","shared_group":"gemini-2-flash"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "successor_model": "gemini-3.8-flash", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -29704,6 +30199,7 @@ ], "supports_audio_output": false, "supports_function_calling": true, + "supports_image_size": false, "supports_parallel_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -29713,23 +30209,7 @@ "supports_tool_choice": true, "supports_url_context": true, "supports_vision": true, - "supports_web_search": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.035, - "search_context_size_medium": 0.035, - "search_context_size_high": 0.035 - }, - "search_free_requests": {"count": 1500, "period": "day", "shared_group": "gemini-2-flash"}, - "google_maps_grounding_cost_per_query": 0.025, - "input_cost_per_audio_token_batches": 5e-08, - "input_cost_per_token_batches": 5e-08, - "input_cost_per_token_flex": 5e-08, - "input_cost_per_token_priority": 1.8e-07, - "input_cost_per_audio_token_priority": 5.4e-07, - "output_cost_per_token_batches": 2e-07, - "output_cost_per_token_flex": 2e-07, - "output_cost_per_token_priority": 7.2e-07, - "supports_image_size": false + "supports_web_search": true }, "gemini-2.5-flash-lite-preview-09-2025": { "cache_read_input_token_cost": 1e-08, @@ -29825,6 +30305,8 @@ }, "gemini-live-2.5-flash-native-audio": { "deprecation_date": "2026-12-13", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.8-live", "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 5e-07, "litellm_provider": "vertex_ai-language-models", @@ -29958,6 +30440,8 @@ }, "gemini-2.5-pro": { "deprecation_date": "2026-10-20", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.8-flash", "cache_read_input_token_cost": 1.25e-07, "cache_read_input_token_cost_above_200k_tokens": 2.5e-07, "cache_creation_input_token_cost_above_200k_tokens": 2.5e-07, @@ -30006,11 +30490,13 @@ "search_free_requests": {"count": 10000, "period": "day", "shared_group": "gemini-2.5-pro"}, "google_maps_grounding_cost_per_query": 0.025, "input_cost_per_token_above_200k_tokens_batches": 1.25e-06, + "input_cost_per_token_above_200k_tokens_flex": 1.25e-06, "input_cost_per_token_above_200k_tokens_priority": 4.5e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, "input_cost_per_token_priority": 2.25e-06, "output_cost_per_token_above_200k_tokens_batches": 7.5e-06, + "output_cost_per_token_above_200k_tokens_flex": 7.5e-06, "output_cost_per_token_above_200k_tokens_priority": 2.7e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, @@ -30026,6 +30512,7 @@ "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, "input_cost_per_token_above_200k_tokens_batches": 2e-06, + "input_cost_per_token_above_200k_tokens_flex": 2e-06, "input_cost_per_token_above_200k_tokens_priority": 7.2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -30038,6 +30525,7 @@ "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_batches": 9e-06, + "output_cost_per_token_above_200k_tokens_flex": 9e-06, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_token_flex": 6e-06, @@ -30185,11 +30673,17 @@ }, "vertex_ai/gemini-3-flash-preview": { "cache_read_input_audio_token_cost": 1e-07, + "cache_read_input_audio_token_cost_priority": 1.8e-07, "cache_read_input_token_cost": 5e-08, "cache_read_input_token_cost_priority": 9e-08, "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token": 1e-06, + "input_cost_per_audio_token_above_200k_tokens": 1e-06, + "input_cost_per_audio_token_above_200k_tokens_batches": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_flex": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_priority": 1.8e-06, "input_cost_per_audio_token_batches": 5e-07, + "input_cost_per_audio_token_flex": 5e-07, "input_cost_per_audio_token_priority": 1.8e-06, "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -30204,7 +30698,7 @@ "output_cost_per_token_flex": 1.5e-06, "output_cost_per_token_priority": 5.4e-06, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -30238,6 +30732,8 @@ "vertex_ai/gemini-3.5-flash": { "prompt_cache_min_tokens": 4096, "deprecation_date": "2027-05-19", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.8-flash", "cache_read_input_token_cost": 1.5e-07, "cache_read_input_token_cost_batches": 7.5e-08, "input_cost_per_token": 1.5e-06, @@ -30349,6 +30845,8 @@ "output_cost_per_token_priority": 6.75e-06, "cache_read_input_token_cost_priority": 1.35e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.8-flash", "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, @@ -30411,6 +30909,8 @@ "output_cost_per_token_priority": 6.75e-06, "cache_read_input_token_cost_priority": 1.35e-07, "deprecation_date": "2027-01-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.8-flash", "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, @@ -30442,7 +30942,7 @@ "prompt_cache_min_tokens": 4096.0, "regional_endpoint_uplift_multiplier": 1.1, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -30572,6 +31072,7 @@ "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, "input_cost_per_token_above_200k_tokens_batches": 2e-06, + "input_cost_per_token_above_200k_tokens_flex": 2e-06, "input_cost_per_token_above_200k_tokens_priority": 7.2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -30584,6 +31085,7 @@ "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_batches": 9e-06, + "output_cost_per_token_above_200k_tokens_flex": 9e-06, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_token_flex": 6e-06, @@ -30822,6 +31324,8 @@ }, "gemini-embedding-001": { "deprecation_date": "2028-05-20", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-embedding-2", "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 1.2e-07, "litellm_provider": "vertex_ai-embedding-models", @@ -30846,6 +31350,7 @@ "output_cost_per_token": 0, "output_vector_size": 3072, "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "supports_embedding_image_input": true, "uses_embed_content": true }, "gemini-embedding-2": { @@ -30863,6 +31368,7 @@ "output_cost_per_token": 0, "output_vector_size": 3072, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "supports_embedding_image_input": true, "supports_multimodal": true, "uses_embed_content": true }, @@ -30881,6 +31387,7 @@ "output_cost_per_token": 0, "output_vector_size": 3072, "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "supports_embedding_image_input": true, "supports_multimodal": true, "uses_embed_content": true }, @@ -30899,6 +31406,7 @@ "output_cost_per_token": 0, "output_vector_size": 3072, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "supports_embedding_image_input": true, "supports_multimodal": true, "uses_embed_content": true }, @@ -30916,6 +31424,8 @@ }, "gemini/gemini-embedding-001": { "deprecation_date": "2028-05-14", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-embedding-2", "input_cost_per_token": 1.5e-07, "litellm_provider": "gemini", "max_input_tokens": 2048, @@ -30944,12 +31454,15 @@ "rpm": 10000, "source": "https://ai.google.dev/gemini-api/docs/pricing", "supports_audio_input": true, + "supports_embedding_image_input": true, "supports_multimodal": true, "supports_vision": true, "tpm": 10000000 }, "gemini/gemini-3-pro-image-preview": { "deprecation_date": "2026-06-25", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3-pro-image", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -30998,6 +31511,8 @@ }, "gemini/gemini-3.1-flash-image-preview": { "deprecation_date": "2026-06-25", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-nano-banana-2.1", "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, "litellm_provider": "gemini", @@ -31046,6 +31561,8 @@ "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2026-05-25", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.1-flash-lite", "input_cost_per_audio_token": 5e-07, "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, @@ -31103,6 +31620,8 @@ "input_cost_per_audio_token_batches": 2.5e-07 }, "gemini/gemini-embedding-2-preview": { + "deprecation_date": "2026-08-10", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", "input_cost_per_audio_token": 6.5e-06, "input_cost_per_audio_token_batches": 3.25e-06, "input_cost_per_image_token": 4.5e-07, @@ -31118,7 +31637,9 @@ "output_vector_size": 3072, "rpm": 10000, "source": "https://ai.google.dev/gemini-api/docs/pricing", + "successor_model": "gemini/gemini-embedding-2", "supports_audio_input": true, + "supports_embedding_image_input": true, "supports_multimodal": true, "supports_vision": true, "tpm": 10000000 @@ -31204,6 +31725,9 @@ "cache_read_input_token_cost_batches": 3e-08, "cache_read_input_token_cost_flex": 3e-08, "cache_read_input_token_cost_priority": 5.4e-08, + "deprecation_date": "2026-12-01", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.5-flash-lite", "input_cost_per_audio_token": 1e-06, "input_cost_per_audio_token_flex": 5e-07, "input_cost_per_token": 3e-07, @@ -31263,6 +31787,8 @@ "gemini/gemini-2.5-flash-image": { "cache_read_input_token_cost": 3e-08, "deprecation_date": "2027-03-15", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.1-flash-lite-image", "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, @@ -31490,6 +32016,8 @@ }, "gemini/deep-research-pro-preview-12-2025": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/deep-research-preview-04-2026", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -31707,6 +32235,8 @@ }, "gemini/gemini-2.5-flash-preview-tts": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash-tts", "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, "litellm_provider": "gemini", @@ -31787,11 +32317,16 @@ "output_cost_per_token_flex": 5e-06, "supports_url_context": true, "cache_read_input_token_cost_above_200k_tokens_batches": 2.5e-07, + "deprecation_date": "2026-12-01", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash", "input_cost_per_token_above_200k_tokens_batches": 1.25e-06, "output_cost_per_token_above_200k_tokens_batches": 7.5e-06 }, "gemini/gemini-2.5-computer-use-preview-10-2025": { "deprecation_date": "2026-07-28", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash", "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, "litellm_provider": "gemini", @@ -31830,6 +32365,8 @@ "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2027-05-07", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.5-flash-lite", "input_cost_per_audio_token": 5e-07, "input_cost_per_audio_token_flex": 2.5e-07, "input_cost_per_token": 2.5e-07, @@ -31890,7 +32427,7 @@ }, "gemini/gemini-3.5-flash-lite": { "cache_read_input_token_cost": 3e-08, - "cache_read_input_token_cost_batches": 2e-08, + "cache_read_input_token_cost_batches": 1.5e-08, "cache_read_input_token_cost_flex": 2e-08, "cache_read_input_token_cost_priority": 5e-08, "input_cost_per_token": 3e-07, @@ -32295,7 +32832,9 @@ "supports_video_input": true, "supports_vision": true, "tpm": 800000, - "deprecation_date": "2026-10-22" + "deprecation_date": "2026-10-22", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-omni-1.1-flash" }, "gemini/gemini-3.1-pro-preview": { "prompt_cache_min_tokens": 4096, @@ -32431,11 +32970,17 @@ }, "gemini-3-flash-preview": { "cache_read_input_audio_token_cost": 1e-07, + "cache_read_input_audio_token_cost_priority": 1.8e-07, "cache_read_input_token_cost": 5e-08, "cache_read_input_token_cost_priority": 9e-08, "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token": 1e-06, + "input_cost_per_audio_token_above_200k_tokens": 1e-06, + "input_cost_per_audio_token_above_200k_tokens_batches": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_flex": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_priority": 1.8e-06, "input_cost_per_audio_token_batches": 5e-07, + "input_cost_per_audio_token_flex": 5e-07, "input_cost_per_audio_token_priority": 1.8e-06, "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -32451,7 +32996,7 @@ "output_cost_per_token_flex": 1.5e-06, "output_cost_per_token_priority": 5.4e-06, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -32487,13 +33032,13 @@ "input_cost_per_audio_token": 1.5e-06, "input_cost_per_token": 1.5e-06, "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 1048576, - "max_output_tokens": 65535, + "max_input_tokens": 131072, + "max_output_tokens": 57920, "mode": "chat", "output_cost_per_reasoning_token": 9e-06, "output_cost_per_token": 9e-06, "output_cost_per_video_token": 1.75e-05, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/omni-flash-preview", "supported_endpoints": [ "/v1/chat/completions" ], @@ -32511,11 +33056,14 @@ "supports_reasoning": true, "supports_system_messages": true, "supports_video_input": true, - "supports_vision": true + "supports_vision": true, + "deprecation_date": "2026-11-06" }, "gemini-3.5-flash": { "prompt_cache_min_tokens": 4096, "deprecation_date": "2027-05-19", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.8-flash", "cache_read_input_token_cost": 1.5e-07, "cache_read_input_token_cost_batches": 7.5e-08, "input_cost_per_audio_token": 1.5e-06, @@ -32627,6 +33175,8 @@ "output_cost_per_token_priority": 6.75e-06, "cache_read_input_token_cost_priority": 1.35e-07, "deprecation_date": "2026-11-19", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.8-flash", "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, @@ -32689,6 +33239,8 @@ "output_cost_per_token_priority": 6.75e-06, "cache_read_input_token_cost_priority": 1.35e-07, "deprecation_date": "2027-01-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "gemini-3.8-flash", "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, @@ -32719,7 +33271,7 @@ "output_cost_per_token_priority": 6.75e-06, "prompt_cache_min_tokens": 4096.0, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -32807,6 +33359,8 @@ "gemini/gemini-2.5-pro-preview-tts": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash-tts", "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1e-06, "input_cost_per_token_batches": 5e-07, @@ -33059,6 +33613,8 @@ }, "gemini/veo-3.1-fast-generate-preview": { "deprecation_date": "2026-10-22", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-omni-1.1-flash", "litellm_provider": "gemini", "max_input_tokens": 1024, "mode": "video_generation", @@ -33075,6 +33631,8 @@ }, "gemini/veo-3.1-generate-preview": { "deprecation_date": "2026-10-22", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-omni-1.1-flash", "litellm_provider": "gemini", "max_input_tokens": 1024, "mode": "video_generation", @@ -33090,6 +33648,8 @@ }, "gemini/veo-3.1-lite-generate-preview": { "deprecation_date": "2026-10-22", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-omni-1.1-flash", "litellm_provider": "gemini", "max_input_tokens": 1024, "mode": "video_generation", @@ -33425,6 +33985,7 @@ }, "github_copilot/gpt-4.1": { "deprecation_date": "2026-06-01", + "deprecation_source": "https://raw.githubusercontent.com/github/docs/main/data/tables/copilot/model-deprecation-history.yml", "litellm_provider": "github_copilot", "max_input_tokens": 128000, "max_output_tokens": 16384, @@ -33437,6 +33998,7 @@ }, "github_copilot/gpt-4.1-2025-04-14": { "deprecation_date": "2026-06-01", + "deprecation_source": "https://raw.githubusercontent.com/github/docs/main/data/tables/copilot/model-deprecation-history.yml", "litellm_provider": "github_copilot", "max_input_tokens": 128000, "max_output_tokens": 16384, @@ -33538,6 +34100,7 @@ "cache_read_input_token_cost": 2.5e-07, "cache_read_input_token_cost_above_272k_tokens": 5e-07, "deprecation_date": "2026-10-19", + "deprecation_source": "https://raw.githubusercontent.com/github/docs/main/data/tables/copilot/model-deprecation-history.yml", "input_cost_per_token": 2.5e-06, "input_cost_per_token_above_272k_tokens": 5e-06, "litellm_provider": "github_copilot", @@ -33580,6 +34143,7 @@ "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_above_272k_tokens": 1e-06, "deprecation_date": "2026-10-19", + "deprecation_source": "https://raw.githubusercontent.com/github/docs/main/data/tables/copilot/model-deprecation-history.yml", "input_cost_per_token": 5e-06, "input_cost_per_token_above_272k_tokens": 1e-05, "litellm_provider": "github_copilot", @@ -34433,6 +34997,7 @@ }, "google.gemma-3-12b-it": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 9e-08, "input_cost_per_token_batches": 5e-08, "input_cost_per_token_flex": 5e-08, @@ -34454,6 +35019,7 @@ }, "google.gemma-3-27b-it": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2.3e-07, "input_cost_per_token_batches": 1.2e-07, "input_cost_per_token_flex": 1.2e-07, @@ -34475,6 +35041,7 @@ }, "google.gemma-3-4b-it": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 4e-08, "input_cost_per_token_batches": 2e-08, "input_cost_per_token_flex": 2e-08, @@ -34509,6 +35076,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.2e-05, "cache_read_input_token_cost_above_200k_tokens": 6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "global.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -34544,6 +35113,8 @@ "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-10-14", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "global.anthropic.claude-sonnet-5", "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -34632,12 +35203,15 @@ }, "gpt-3.5-turbo": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 5e-07, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -34646,6 +35220,8 @@ }, "gpt-3.5-turbo-0125": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, "litellm_provider": "openai", @@ -34653,6 +35229,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 7.5e-07, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -34663,6 +35240,8 @@ }, "gpt-3.5-turbo-1106": { "deprecation_date": "2026-09-28", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1e-06, "input_cost_per_token_batches": 1e-06, "litellm_provider": "openai", @@ -34670,6 +35249,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2e-06, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -34680,18 +35260,22 @@ }, "gpt-3.5-turbo-16k": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "input_cost_per_token": 3e-06, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 4e-06, + "fedramp_uplift_multiplier": 1.1, "supports_prompt_caching": true, "supports_system_messages": true, "supports_tool_choice": true }, "gpt-3.5-turbo-instruct": { "deprecation_date": "2026-09-28", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1.5e-06, "litellm_provider": "text-completion-openai", "max_input_tokens": 8192, @@ -34710,12 +35294,15 @@ }, "gpt-4": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 3e-05, "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-05, + "fedramp_uplift_multiplier": 1.1, "supports_function_calling": true, "supports_prompt_caching": true, "supports_system_messages": true, @@ -34723,6 +35310,8 @@ }, "gpt-4-0613": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 3e-05, "input_cost_per_token_batches": 1.5e-05, "litellm_provider": "openai", @@ -34730,6 +35319,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-05, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -34739,12 +35329,15 @@ }, "gpt-4-1106-preview": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1e-05, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 3e-05, + "fedramp_uplift_multiplier": 1.1, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -34753,12 +35346,15 @@ }, "gpt-4-turbo": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1e-05, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 3e-05, + "fedramp_uplift_multiplier": 1.1, "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -34769,6 +35365,8 @@ }, "gpt-4-turbo-2024-04-09": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1e-05, "input_cost_per_token_batches": 5e-06, "litellm_provider": "openai", @@ -34776,6 +35374,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 3e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 1.5e-05, "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -34789,6 +35388,9 @@ "gpt-4.1": { "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_priority": 8.75e-07, + "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_priority": 3.5e-06, @@ -34797,6 +35399,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-06, "output_cost_per_token_priority": 1.4e-05, "search_context_cost_per_query": { @@ -34832,6 +35435,8 @@ "cache_read_input_token_cost": 5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2e-06, "input_cost_per_token_priority": 3.5e-06, "input_cost_per_token_batches": 1e-06, @@ -34840,6 +35445,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 1.4e-05, "output_cost_per_token_batches": 4e-06, "search_context_cost_per_query": { @@ -34874,6 +35480,9 @@ "gpt-4.1-mini": { "cache_read_input_token_cost": 1e-07, "cache_read_input_token_cost_priority": 1.75e-07, + "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 4e-07, "input_cost_per_token_batches": 2e-07, "input_cost_per_token_priority": 7e-07, @@ -34882,6 +35491,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 1.6e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 8e-07, "output_cost_per_token_priority": 2.8e-06, "search_context_cost_per_query": { @@ -34917,6 +35527,8 @@ "cache_read_input_token_cost": 1e-07, "cache_read_input_token_cost_priority": 1.75e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 4e-07, "input_cost_per_token_priority": 7e-07, "input_cost_per_token_batches": 2e-07, @@ -34925,6 +35537,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 1.6e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2.8e-06, "output_cost_per_token_batches": 8e-07, "search_context_cost_per_query": { @@ -34960,6 +35573,8 @@ "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_priority": 5e-08, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-luna", "input_cost_per_token": 1e-07, "input_cost_per_token_batches": 5e-08, "input_cost_per_token_priority": 2e-07, @@ -34968,6 +35583,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_priority": 8e-07, "source": "https://developers.openai.com/api/docs/pricing", @@ -34997,6 +35613,8 @@ "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_priority": 5e-08, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-luna", "input_cost_per_token": 1e-07, "input_cost_per_token_priority": 2e-07, "input_cost_per_token_batches": 5e-08, @@ -35005,6 +35623,7 @@ "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 8e-07, "output_cost_per_token_batches": 2e-07, "source": "https://developers.openai.com/api/docs/pricing", @@ -35033,6 +35652,9 @@ "gpt-4o": { "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_priority": 2.125e-06, + "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, "input_cost_per_token_priority": 4.25e-06, @@ -35041,6 +35663,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 1.7e-05, "source": "https://developers.openai.com/api/docs/pricing", @@ -35055,6 +35678,8 @@ }, "gpt-4o-2024-05-13": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 5e-06, "input_cost_per_token_batches": 2.5e-06, "input_cost_per_token_priority": 8.75e-06, @@ -35063,6 +35688,7 @@ "max_output_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 7.5e-06, "output_cost_per_token_priority": 2.625e-05, "source": "https://developers.openai.com/api/docs/pricing", @@ -35078,6 +35704,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_priority": 2.125e-06, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2.5e-06, "input_cost_per_token_priority": 4.25e-06, "input_cost_per_token_batches": 1.25e-06, @@ -35086,6 +35714,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 1.7e-05, "output_cost_per_token_batches": 5e-06, "source": "https://developers.openai.com/api/docs/pricing", @@ -35102,6 +35731,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_priority": 2.125e-06, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2.5e-06, "input_cost_per_token_priority": 4.25e-06, "input_cost_per_token_batches": 1.25e-06, @@ -35110,6 +35741,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 1.7e-05, "output_cost_per_token_batches": 5e-06, "source": "https://developers.openai.com/api/docs/pricing", @@ -35124,6 +35756,8 @@ }, "gpt-4o-audio-preview-2024-12-17": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 4e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "openai", @@ -35141,6 +35775,8 @@ }, "gpt-4o-audio-preview-2025-06-03": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 4e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "openai", @@ -35158,6 +35794,8 @@ }, "gpt-audio": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "openai", @@ -35228,6 +35866,8 @@ }, "gpt-audio-2025-08-28": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_token": 2.5e-06, "litellm_provider": "openai", @@ -35265,6 +35905,8 @@ }, "gpt-audio-mini": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, "litellm_provider": "openai", @@ -35302,6 +35944,8 @@ }, "gpt-audio-mini-2025-10-06": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, "litellm_provider": "openai", @@ -35372,11 +36016,16 @@ "supports_tool_choice": true, "supports_vision": false, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-audio-1.5", "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini": { "cache_read_input_token_cost": 7.5e-08, "cache_read_input_token_cost_priority": 1.25e-07, + "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, "input_cost_per_token_priority": 2.5e-07, @@ -35385,6 +36034,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-07, "output_cost_per_token_priority": 1e-06, "supports_function_calling": true, @@ -35406,6 +36056,8 @@ "cache_read_input_token_cost": 7.5e-08, "cache_read_input_token_cost_priority": 1.25e-07, "deprecation_date": "2027-01-14", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 1.5e-07, "input_cost_per_token_priority": 2.5e-07, "input_cost_per_token_batches": 7.5e-08, @@ -35414,6 +36066,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 1e-06, "output_cost_per_token_batches": 3e-07, "search_context_cost_per_query": { @@ -35433,6 +36086,7 @@ }, "gpt-4o-mini-audio-preview-2024-12-17": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 1.5e-07, "litellm_provider": "openai", @@ -35452,6 +36106,7 @@ "cache_creation_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "input_cost_per_audio_token": 1e-05, "input_cost_per_token": 6e-07, "litellm_provider": "openai", @@ -35476,6 +36131,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-07, "search_context_cost_per_query": { "search_context_size_high": 0.025, @@ -35494,6 +36150,8 @@ }, "gpt-4o-mini-search-preview-2025-03-11": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "cache_read_input_token_cost": 7.5e-08, "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, @@ -35502,6 +36160,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 6e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 3e-07, "search_context_cost_per_query": { "search_context_size_high": 0.025, @@ -35531,11 +36190,15 @@ "/v1/audio/transcriptions" ], "deprecation_date": "2027-02-26", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-live-transcribe", "input_cost_per_second": 5e-05, "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini-tts": { "deprecation_date": "2027-01-06", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", @@ -35556,6 +36219,8 @@ }, "gpt-4o-mini-tts-2025-03-20": { "deprecation_date": "2027-01-06", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", @@ -35583,6 +36248,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 5e-06, "search_context_cost_per_query": { "search_context_size_high": 0.025, @@ -35601,6 +36267,8 @@ }, "gpt-4o-search-preview-2025-03-11": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "cache_read_input_token_cost": 1.25e-06, "input_cost_per_token": 2.5e-06, "input_cost_per_token_batches": 1.25e-06, @@ -35609,6 +36277,7 @@ "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 5e-06, "search_context_cost_per_query": { "search_context_size_high": 0.025, @@ -35638,6 +36307,8 @@ "/v1/audio/transcriptions" ], "deprecation_date": "2027-02-26", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-live-transcribe", "input_cost_per_second": 0.0001, "source": "https://developers.openai.com/api/docs/pricing" }, @@ -35646,6 +36317,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_batches": 6.3e-07, "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_token": 5e-06, "litellm_provider": "openai", "mode": "image_generation", @@ -35654,6 +36327,7 @@ "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3.2e-05, + "output_cost_per_image_token_batches": 1.6e-05, "output_cost_per_token_batches": 5e-06, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -35667,6 +36341,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_batches": 6.3e-07, "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_token": 5e-06, "litellm_provider": "openai", "mode": "image_generation", @@ -35675,6 +36351,7 @@ "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3.2e-05, + "output_cost_per_image_token_batches": 1.6e-05, "output_cost_per_token_batches": 5e-06, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -35694,6 +36371,7 @@ "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", @@ -35729,6 +36407,7 @@ "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -35764,6 +36443,7 @@ "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3e-05, + "output_cost_per_image_token_batches": 1.5e-05, "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -35790,6 +36470,8 @@ }, "low/1024-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.009, "litellm_provider": "openai", "mode": "image_generation", @@ -35802,6 +36484,8 @@ }, "low/1024-x-1536/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35814,6 +36498,8 @@ }, "low/1536-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35826,6 +36512,8 @@ }, "medium/1024-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.034, "litellm_provider": "openai", "mode": "image_generation", @@ -35838,6 +36526,8 @@ }, "medium/1024-x-1536/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.05, "litellm_provider": "openai", "mode": "image_generation", @@ -35850,6 +36540,8 @@ }, "medium/1536-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.05, "litellm_provider": "openai", "mode": "image_generation", @@ -35862,6 +36554,8 @@ }, "high/1024-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.133, "litellm_provider": "openai", "mode": "image_generation", @@ -35874,6 +36568,8 @@ }, "high/1024-x-1536/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.2, "litellm_provider": "openai", "mode": "image_generation", @@ -35886,6 +36582,8 @@ }, "high/1536-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.2, "litellm_provider": "openai", "mode": "image_generation", @@ -35898,6 +36596,8 @@ }, "standard/1024-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.009, "litellm_provider": "openai", "mode": "image_generation", @@ -35910,6 +36610,8 @@ }, "standard/1024-x-1536/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35922,6 +36624,8 @@ }, "standard/1536-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35934,6 +36638,8 @@ }, "1024-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.009, "litellm_provider": "openai", "mode": "image_generation", @@ -35946,6 +36652,8 @@ }, "1024-x-1536/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35958,6 +36666,8 @@ }, "1536-x-1024/gpt-image-1.5": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.013, "litellm_provider": "openai", "mode": "image_generation", @@ -35978,7 +36688,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "low/1024-x-1536/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -35990,7 +36702,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "low/1536-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -36002,7 +36716,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "medium/1024-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.034, @@ -36014,7 +36730,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "medium/1024-x-1536/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.05, @@ -36026,7 +36744,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "medium/1536-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.05, @@ -36038,7 +36758,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "high/1024-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.133, @@ -36050,7 +36772,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "high/1024-x-1536/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.2, @@ -36062,7 +36786,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "high/1536-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.2, @@ -36074,7 +36800,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "standard/1024-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.009, @@ -36086,7 +36814,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "standard/1024-x-1536/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -36098,7 +36828,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "standard/1536-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -36110,7 +36842,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "1024-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.009, @@ -36122,7 +36856,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "1024-x-1536/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -36134,7 +36870,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "1536-x-1024/gpt-image-1.5-2025-12-16": { "input_cost_per_image": 0.013, @@ -36146,7 +36884,9 @@ ], "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-12-01" + "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst" }, "gpt-5": { "cache_read_input_token_cost": 1.25e-07, @@ -36154,6 +36894,8 @@ "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, @@ -36163,6 +36905,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, @@ -36209,12 +36952,15 @@ "gpt-5-codex": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 272000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5-codex", "supported_endpoints": [ "/v1/responses" @@ -36249,6 +36995,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2e-05, "reasoning_contexts": [ "auto", @@ -36294,17 +37041,22 @@ "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": false, "supports_minimal_reasoning_effort": false, - "deprecation_date": "2027-04-01" + "deprecation_date": "2027-04-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-sol" }, "gpt-5.1-codex-mini": { "cache_read_input_token_cost": 2.5e-08, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 2.5e-07, "litellm_provider": "openai", "max_input_tokens": 400000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 2e-06, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.1-codex-mini", "supported_endpoints": [ "/v1/responses" @@ -36329,12 +37081,15 @@ "gpt-5.1-codex-max": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 400000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.1-codex-max", "supported_endpoints": [ "/v1/responses" @@ -36360,12 +37115,15 @@ "gpt-5.1-codex": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 400000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.1-codex", "supported_endpoints": [ "/v1/responses" @@ -36391,12 +37149,15 @@ "gpt-5.1-chat-latest": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.1-chat-latest", "supported_endpoints": [ "/v1/chat/completions", @@ -36425,6 +37186,8 @@ "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2027-04-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-sol", "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", @@ -36432,6 +37195,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2e-05, "reasoning_contexts": [ "auto", @@ -36490,6 +37254,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2.8e-05, "reasoning_contexts": [ "auto", @@ -36541,12 +37306,15 @@ "gpt-5.2-codex": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.75e-06, "litellm_provider": "openai", "max_input_tokens": 272000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.2-codex", "supported_endpoints": [ "/v1/responses" @@ -36572,12 +37340,15 @@ "gpt-5.2-chat-latest": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2026-08-10", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.75e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.2-chat-latest", "supported_endpoints": [ "/v1/chat/completions", @@ -36612,6 +37383,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2.8e-05, "reasoning_contexts": [ "auto", @@ -36668,6 +37440,7 @@ "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 0.000168, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 8.4e-05, "reasoning_contexts": [ "auto", @@ -36716,6 +37489,7 @@ "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 0.000168, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 8.4e-05, "reasoning_contexts": [ "auto", @@ -36822,6 +37596,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -36915,6 +37690,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37016,6 +37792,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37108,6 +37885,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37198,6 +37976,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37290,6 +38069,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37381,6 +38161,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37425,10 +38206,11 @@ "input_cost_per_token": 1.25e-05, "input_cost_per_token_above_272k_tokens": 2.5e-05, "litellm_provider": "openai", - "max_input_tokens": 400000, + "max_input_tokens": 272000, "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 7.5e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_above_272k_tokens": 0.0001125, "supported_endpoints": [ "/v1/chat/completions", @@ -37463,10 +38245,11 @@ "input_cost_per_token": 1.25e-05, "input_cost_per_token_above_272k_tokens": 2.5e-05, "litellm_provider": "openai", - "max_input_tokens": 400000, + "max_input_tokens": 272000, "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 7.5e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_above_272k_tokens": 0.0001125, "supported_endpoints": [ "/v1/chat/completions", @@ -37501,10 +38284,11 @@ "input_cost_per_token": 1.25e-05, "input_cost_per_token_above_272k_tokens": 2.5e-05, "litellm_provider": "openai", - "max_input_tokens": 400000, + "max_input_tokens": 272000, "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 7.5e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_above_272k_tokens": 0.0001125, "supported_endpoints": [ "/v1/responses" @@ -37542,6 +38326,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 2e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_above_272k_tokens": 3e-05, "supported_endpoints": [ "/v1/chat/completions", @@ -37580,6 +38365,7 @@ "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 2e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_above_272k_tokens": 3e-05, "supported_endpoints": [ "/v1/responses" @@ -37613,6 +38399,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 3e-05, + "fedramp_uplift_multiplier": 1.1, "reasoning_effort_levels": [ "medium" ], @@ -37681,6 +38468,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37751,6 +38539,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37813,6 +38602,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37872,6 +38662,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -37939,6 +38730,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -38004,6 +38796,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -38061,6 +38854,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38121,6 +38915,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38183,6 +38978,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38245,6 +39041,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38304,6 +39101,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38337,13 +39135,17 @@ "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "deprecation_date": "2027-04-01" + "deprecation_date": "2027-04-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna" }, "gpt-5.4-nano-2026-03-17": { "cache_read_input_token_cost": 2e-08, "cache_read_input_token_cost_batches": 1e-08, "cache_read_input_token_cost_flex": 1e-08, "deprecation_date": "2027-04-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-luna", "input_cost_per_token": 2e-07, "input_cost_per_token_flex": 1e-07, "input_cost_per_token_batches": 1e-07, @@ -38364,6 +39166,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -38400,6 +39203,8 @@ }, "gpt-5-pro": { "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", @@ -38407,6 +39212,7 @@ "max_output_tokens": 272000, "mode": "responses", "output_cost_per_token": 0.00012, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 6e-05, "reasoning_contexts": [ "auto", @@ -38449,6 +39255,8 @@ }, "gpt-5-pro-2025-10-06": { "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.5e-05, "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", @@ -38456,6 +39264,7 @@ "max_output_tokens": 272000, "mode": "responses", "output_cost_per_token": 0.00012, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 6e-05, "reasoning_contexts": [ "auto", @@ -38502,6 +39311,8 @@ "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, @@ -38511,6 +39322,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, @@ -38557,12 +39369,15 @@ "gpt-5-chat": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.2-chat-latest", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -38592,12 +39407,15 @@ "gpt-5-chat-latest": { "cache_read_input_token_cost": 1.25e-07, "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5-chat-latest", "supported_endpoints": [ "/v1/chat/completions", @@ -38630,6 +39448,7 @@ "max_output_tokens": 128000, "mode": "responses", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_priority": 2.8e-05, "reasoning_contexts": [ "auto", @@ -38669,17 +39488,22 @@ "supports_none_reasoning_effort": true, "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, - "deprecation_date": "2027-04-01" + "deprecation_date": "2027-04-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-6-sol" }, "gpt-5.3-chat-latest": { "cache_read_input_token_cost": 1.75e-07, "deprecation_date": "2026-08-10", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.75e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.4e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/gpt-5.3-chat-latest", "supported_endpoints": [ "/v1/chat/completions", @@ -38708,6 +39532,8 @@ "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_flex": 1.25e-07, @@ -38717,6 +39543,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 2e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, @@ -38766,6 +39593,8 @@ "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_flex": 1.25e-07, @@ -38775,6 +39604,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 2e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, @@ -38823,6 +39653,8 @@ "cache_read_input_token_cost_batches": 2.5e-09, "cache_read_input_token_cost_flex": 2.5e-09, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-luna", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 2.5e-08, "input_cost_per_token_flex": 2.5e-08, @@ -38831,6 +39663,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 4e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, "reasoning_contexts": [ @@ -38878,6 +39711,8 @@ "cache_read_input_token_cost_batches": 2.5e-09, "cache_read_input_token_cost_flex": 2.5e-09, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-luna", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 2.5e-08, "input_cost_per_token_flex": 2.5e-08, @@ -38886,6 +39721,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 4e-07, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, "reasoning_contexts": [ @@ -38933,6 +39769,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_batches": 6.3e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image_token": 1e-05, "input_cost_per_image_token_batches": 5e-06, "input_cost_per_token": 5e-06, @@ -38951,6 +39789,8 @@ "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_batches": 1e-07, "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image_token": 2.5e-06, "input_cost_per_image_token_batches": 1.25e-06, "input_cost_per_token": 2e-06, @@ -38958,6 +39798,7 @@ "litellm_provider": "openai", "mode": "image_generation", "output_cost_per_image_token": 8e-06, + "output_cost_per_image_token_batches": 4e-06, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", @@ -38970,6 +39811,8 @@ "cache_read_input_image_token_cost": 5e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -39045,6 +39888,9 @@ "max_input_tokens": 128000, "max_output_tokens": 32000, "mode": "realtime", + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 2.4e-05, "source": "https://developers.openai.com/api/docs/pricing", @@ -39100,6 +39946,8 @@ "supports_audio_output": true, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, "supports_system_messages": true, "supports_tool_choice": true }, @@ -39136,6 +39984,8 @@ "supports_audio_output": true, "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, "supports_system_messages": true, "supports_tool_choice": true }, @@ -39145,6 +39995,8 @@ "cache_read_input_image_token_cost": 8e-08, "cache_read_input_token_cost": 6e-08, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, "input_cost_per_token": 6e-07, @@ -39180,6 +40032,8 @@ "cache_read_input_image_token_cost": 5e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -39503,16 +40357,6 @@ "supports_response_schema": true, "supports_vision": true }, - "groq/llama-guard-3-8b": { - "deprecation_date": "2025-06-06", - "input_cost_per_token": 2e-07, - "litellm_provider": "groq", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 2e-07, - "source": "https://console.groq.com/docs/model/llama-guard-3-8b" - }, "groq/meta-llama/llama-prompt-guard-2-22m": { "input_cost_per_token": 3e-08, "litellm_provider": "groq", @@ -39659,6 +40503,8 @@ }, "high/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.167, "input_cost_per_pixel": 1.59263611e-07, "litellm_provider": "openai", @@ -39670,6 +40516,8 @@ }, "high/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.25, "input_cost_per_pixel": 1.58945719e-07, "litellm_provider": "openai", @@ -39681,6 +40529,8 @@ }, "high/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.25, "input_cost_per_pixel": 1.58945719e-07, "litellm_provider": "openai", @@ -40058,6 +40908,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "jp.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -41220,6 +42072,8 @@ }, "low/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.011, "input_cost_per_pixel": 1.0490417e-08, "litellm_provider": "openai", @@ -41231,6 +42085,8 @@ }, "low/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.016, "input_cost_per_pixel": 1.0172526e-08, "litellm_provider": "openai", @@ -41242,6 +42098,8 @@ }, "low/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.016, "input_cost_per_pixel": 1.0172526e-08, "litellm_provider": "openai", @@ -41265,6 +42123,8 @@ }, "medium/1024-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.042, "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "openai", @@ -41276,6 +42136,8 @@ }, "medium/1024-x-1536/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.063, "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "openai", @@ -41287,6 +42149,8 @@ }, "medium/1536-x-1024/gpt-image-1": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.063, "input_cost_per_pixel": 4.0054321e-08, "litellm_provider": "openai", @@ -41298,6 +42162,8 @@ }, "low/1024-x-1024/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.005, "litellm_provider": "openai", "mode": "image_generation", @@ -41307,6 +42173,8 @@ }, "low/1024-x-1536/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.006, "litellm_provider": "openai", "mode": "image_generation", @@ -41316,6 +42184,8 @@ }, "low/1536-x-1024/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.006, "litellm_provider": "openai", "mode": "image_generation", @@ -41325,6 +42195,8 @@ }, "medium/1024-x-1024/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.011, "litellm_provider": "openai", "mode": "image_generation", @@ -41334,6 +42206,8 @@ }, "medium/1024-x-1536/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.015, "litellm_provider": "openai", "mode": "image_generation", @@ -41343,6 +42217,8 @@ }, "medium/1536-x-1024/gpt-image-1-mini": { "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image": 0.015, "litellm_provider": "openai", "mode": "image_generation", @@ -41390,6 +42266,7 @@ }, "meta.llama3-1-405b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2.4e-06, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -41402,6 +42279,7 @@ }, "meta.llama3-1-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "input_cost_per_token_batches": 3.6e-07, "litellm_provider": "bedrock", @@ -41416,6 +42294,7 @@ }, "meta.llama3-1-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2.2e-07, "input_cost_per_token_batches": 1.1e-07, "litellm_provider": "bedrock", @@ -41430,6 +42309,7 @@ }, "meta.llama3-2-11b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.6e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -41443,6 +42323,7 @@ }, "meta.llama3-2-1b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-1b-instruct.md", "input_cost_per_token": 1e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -41455,6 +42336,7 @@ }, "meta.llama3-2-3b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-3b-instruct.md", "input_cost_per_token": 1.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -41467,6 +42349,7 @@ }, "meta.llama3-2-90b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -41480,6 +42363,7 @@ }, "meta.llama3-3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "input_cost_per_token_batches": 3.6e-07, "litellm_provider": "bedrock_converse", @@ -41494,6 +42378,7 @@ }, "meta.llama3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-70b-instruct.md", "input_cost_per_token": 2.65e-06, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -41504,6 +42389,7 @@ }, "meta.llama3-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-8b-instruct.md", "input_cost_per_token": 3e-07, "litellm_provider": "bedrock", "max_input_tokens": 8192, @@ -41514,6 +42400,7 @@ }, "meta.llama4-maverick-17b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-4-maverick-17b-instruct.md", "input_cost_per_token": 2.4e-07, "input_cost_per_token_batches": 1.2e-07, "litellm_provider": "bedrock_converse", @@ -41536,6 +42423,7 @@ }, "meta.llama4-scout-17b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-4-scout-17b-instruct.md", "input_cost_per_token": 1.7e-07, "input_cost_per_token_batches": 8.5e-08, "litellm_provider": "bedrock_converse", @@ -41878,6 +42766,7 @@ }, "minimax.minimax-m2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -41900,6 +42789,7 @@ }, "minimax.minimax-m2.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -42120,6 +43010,7 @@ }, "mistral.devstral-2-123b": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 4e-07, "input_cost_per_token_batches": 2e-07, "input_cost_per_token_flex": 2e-07, @@ -42226,6 +43117,7 @@ }, "mistral.mistral-7b-instruct-v0:2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mistral-7b-instruct.md", "input_cost_per_token": 1.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -42291,6 +43183,7 @@ }, "mistral.mixtral-8x7b-instruct-v0:1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-mistral-ai-mixtral-8x7b-instruct.md", "input_cost_per_token": 4.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 32000, @@ -42302,6 +43195,7 @@ }, "mistral.voxtral-mini-3b-2507": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 4e-08, "input_cost_per_token_batches": 2e-08, "input_cost_per_token_flex": 2e-08, @@ -42321,6 +43215,7 @@ }, "mistral.voxtral-small-24b-2507": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1e-07, "input_cost_per_token_batches": 5e-08, "input_cost_per_token_flex": 5e-08, @@ -42340,6 +43235,7 @@ }, "bedrock/ap-southeast-2/mistral.voxtral-mini-3b-2507": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 4.12e-08, "input_cost_per_token_batches": 2.06e-08, "input_cost_per_token_flex": 2.06e-08, @@ -42359,6 +43255,7 @@ }, "bedrock/ap-southeast-2/mistral.voxtral-small-24b-2507": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.03e-07, "input_cost_per_token_batches": 5.15e-08, "input_cost_per_token_flex": 5.15e-08, @@ -42378,6 +43275,7 @@ }, "bedrock/ap-northeast-1/mistral.voxtral-mini-3b-2507": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 5e-08, "input_cost_per_token_batches": 3e-08, "input_cost_per_token_flex": 3e-08, @@ -42397,6 +43295,7 @@ }, "bedrock/ap-northeast-1/mistral.voxtral-small-24b-2507": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.2e-07, "input_cost_per_token_batches": 6e-08, "input_cost_per_token_flex": 6e-08, @@ -42416,6 +43315,7 @@ }, "bedrock/eu-west-2/mistral.voxtral-mini-3b-2507": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 6e-08, "input_cost_per_token_batches": 3e-08, "input_cost_per_token_flex": 3e-08, @@ -42435,6 +43335,7 @@ }, "bedrock/eu-west-2/mistral.voxtral-small-24b-2507": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.6e-07, "input_cost_per_token_batches": 8e-08, "input_cost_per_token_flex": 8e-08, @@ -42827,6 +43728,7 @@ "mistral/zai-glm-5-2": { "cache_read_input_token_cost": 1.4e-07, "deprecation_date": "2026-10-31", + "deprecation_source": "https://docs.mistral.ai/getting-started/models/models_overview", "input_cost_per_token": 1.4e-06, "litellm_provider": "mistral", "max_input_tokens": 1048576, @@ -43082,18 +43984,18 @@ "mode": "embedding" }, "mistral/mistral-large-4": { - "cache_read_input_token_cost": 1.4e-07, - "input_cost_per_token": 1.36e-06, + "cache_read_input_token_cost": 7e-08, + "input_cost_per_token": 7e-07, "litellm_provider": "mistral", "max_input_tokens": 1048576, "max_output_tokens": 1048576, "mode": "chat", - "output_cost_per_token": 4.18e-06, + "output_cost_per_token": 2.1e-06, "reasoning_effort_levels": [ "none", "high" ], - "source": "https://docs.mistral.ai/models/mistral-large-4", + "source": "https://docs.mistral.ai/models/mistral-large-4-0", "supports_assistant_prefill": true, "supports_function_calling": true, "supports_prompt_caching": true, @@ -43103,18 +44005,18 @@ "supports_vision": true }, "mistral/mistral-large-4-0": { - "cache_read_input_token_cost": 1.4e-07, - "input_cost_per_token": 1.36e-06, + "cache_read_input_token_cost": 7e-08, + "input_cost_per_token": 7e-07, "litellm_provider": "mistral", "max_input_tokens": 1048576, "max_output_tokens": 1048576, "mode": "chat", - "output_cost_per_token": 4.18e-06, + "output_cost_per_token": 2.1e-06, "reasoning_effort_levels": [ "none", "high" ], - "source": "https://docs.mistral.ai/models/mistral-large-4", + "source": "https://docs.mistral.ai/models/mistral-large-4-0", "supports_assistant_prefill": true, "supports_function_calling": true, "supports_prompt_caching": true, @@ -43402,6 +44304,7 @@ }, "moonshot.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 6e-07, "input_cost_per_token_batches": 3e-07, "input_cost_per_token_priority": 1.05e-06, @@ -43804,10 +44707,12 @@ "text", "image", "video" - ] + ], + "supports_embedding_image_input": true }, "multimodalembedding@001": { "deprecation_date": "2027-04-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_character": 2e-07, "input_cost_per_image": 0.0001, "input_cost_per_token": 8e-07, @@ -43827,7 +44732,8 @@ "text", "image", "video" - ] + ], + "supports_embedding_image_input": true }, "nscale/Qwen/QwQ-32B": { "input_cost_per_token": 1.8e-07, @@ -44035,7 +44941,8 @@ "mode": "chat", "supports_function_calling": true, "supports_vision": true, - "source": "https://tokenfactory.nebius.com/models/catalog/text2text/google%2Fgemma-3-27b-it" + "source": "https://tokenfactory.nebius.com/api/public/models_info", + "cache_read_input_token_cost": 4e-08 }, "nebius/meta-llama/Llama-3.3-70B-Instruct": { "max_input_tokens": 131072, @@ -44261,7 +45168,7 @@ "source": "https://tokenfactory.nebius.com/models/catalog/text2text/deepseek-ai%2FDeepSeek-V4-Flash" }, "nebius/deepseek-ai/DeepSeek-V4-Flash-0731": { - "max_input_tokens": 1024000, + "max_input_tokens": 1048576, "max_output_tokens": 1024000, "input_cost_per_token": 1.4e-07, "output_cost_per_token": 2.8e-07, @@ -44269,7 +45176,8 @@ "mode": "chat", "supports_function_calling": true, "supports_reasoning": true, - "source": "https://tokenfactory.nebius.com/models/catalog/text2text/deepseek-ai%2FDeepSeek-V4-Flash-0731" + "source": "https://tokenfactory.nebius.com/api/public/models_info", + "cache_read_input_token_cost": 1e-08 }, "nebius/deepseek-ai/DeepSeek-V4-Pro": { "max_input_tokens": 1048576, @@ -44280,29 +45188,32 @@ "mode": "chat", "supports_function_calling": true, "supports_reasoning": true, - "source": "https://tokenfactory.nebius.com/models/catalog/text2text/deepseek-ai%2FDeepSeek-V4-Pro" + "source": "https://tokenfactory.nebius.com/api/public/models_info", + "cache_read_input_token_cost": 1.4e-07 }, "nebius/deepseek-ai/DeepSeek-V4-Pro-0813": { "input_cost_per_token": 1.32e-06, "litellm_provider": "nebius", - "max_input_tokens": 979000, + "max_input_tokens": 1048576, "mode": "chat", "output_cost_per_token": 3.96e-06, - "source": "https://tokenfactory.nebius.com/models/catalog/text2text/deepseek-ai%2FDeepSeek-V4-Pro-0813", + "source": "https://tokenfactory.nebius.com/api/public/models_info", "supports_function_calling": true, - "supports_reasoning": true + "supports_reasoning": true, + "cache_read_input_token_cost": 4e-08 }, "nebius/deepseek-ai/DeepSeek-V4.1-Flash": { "input_cost_per_token": 3e-07, "litellm_provider": "nebius", - "max_input_tokens": 1048000, + "max_input_tokens": 1048576, "max_output_tokens": 384000, "mode": "chat", "output_cost_per_token": 1.2e-06, 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"supports_reasoning": true, - "source": "https://tokenfactory.nebius.com/models/catalog/text2text/zai-org%2FGLM-5.3-Flash", - "supports_vision": true + "source": "https://tokenfactory.nebius.com/api/public/models_info", + "supports_vision": true, + "cache_read_input_token_cost": 3e-08 }, "nebius/BAAI/bge-en-icl": { "max_input_tokens": 32768, @@ -44615,6 +45545,7 @@ }, "nvidia.nemotron-nano-12b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2e-07, "input_cost_per_token_batches": 1e-07, "input_cost_per_token_flex": 1e-07, @@ -44636,6 +45567,7 @@ }, "nvidia.nemotron-nano-9b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 6e-08, "input_cost_per_token_batches": 3e-08, "input_cost_per_token_flex": 3e-08, @@ -44702,6 +45634,7 @@ "o1": { 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"source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, @@ -44745,6 +45682,8 @@ }, "o1-pro": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 0.00015, "input_cost_per_token_batches": 7.5e-05, "litellm_provider": "openai", @@ -44752,6 +45691,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 0.0006, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 0.0003, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -44778,6 +45718,8 @@ }, "o1-pro-2025-03-19": { "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 0.00015, "input_cost_per_token_batches": 7.5e-05, "litellm_provider": "openai", @@ -44785,6 +45727,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 0.0006, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 0.0003, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -44814,6 +45757,7 @@ "cache_read_input_token_cost_flex": 2.5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "deprecation_date": "2026-12-11", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -44823,6 +45767,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, @@ -44870,6 +45815,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 4e-05, + "fedramp_uplift_multiplier": 1.1, "source": 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2.5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, @@ -44938,6 +45891,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, @@ -44980,6 +45934,8 @@ "o3-mini": { "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "openai", @@ -44987,6 +45943,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 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"input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "openai", @@ -45026,6 +45988,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 8e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-05, "reasoning_contexts": [ "auto", @@ -45063,6 +46026,8 @@ }, "o3-pro-2025-06-10": { "deprecation_date": "2026-12-11", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "openai", @@ -45070,6 +46035,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 8e-05, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 4e-05, "reasoning_contexts": [ "auto", @@ -45110,6 +46076,8 @@ "cache_read_input_token_cost_flex": 1.38e-07, "cache_read_input_token_cost_priority": 5e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "input_cost_per_token_flex": 5.5e-07, @@ -45119,6 +46087,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2.2e-06, "output_cost_per_token_flex": 2.2e-06, "output_cost_per_token_priority": 8e-06, @@ -45146,6 +46115,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/o4-mini-deep-research", "supported_endpoints": [ "/v1/batch", @@ -45167,10 +46137,14 @@ "supports_tool_choice": false, "supports_vision": true, "supports_pdf_input": true, - "deprecation_date": "2026-07-23" + "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol" }, "o4-mini-deep-research-2025-06-26": { "deprecation_date": "2026-07-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-sol", "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 2e-06, "litellm_provider": "openai", @@ -45178,6 +46152,7 @@ "max_output_tokens": 100000, "mode": "responses", "output_cost_per_token": 8e-06, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/models/o4-mini-deep-research", "supported_endpoints": [ "/v1/batch", @@ -45205,6 +46180,8 @@ "cache_read_input_token_cost_flex": 1.38e-07, "cache_read_input_token_cost_priority": 5e-07, "deprecation_date": "2026-10-23", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-5.6-terra", "input_cost_per_token": 1.1e-06, "input_cost_per_token_batches": 5.5e-07, "input_cost_per_token_flex": 5.5e-07, @@ -45214,6 +46191,7 @@ "max_output_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "fedramp_uplift_multiplier": 1.1, "output_cost_per_token_batches": 2.2e-06, "output_cost_per_token_flex": 2.2e-06, "output_cost_per_token_priority": 8e-06, @@ -45503,6 +46481,7 @@ "mode": "embedding", "output_vector_size": 1024, "source": "https://www.oracle.com/artificial-intelligence/enterprise-ai/cost-estimator/", + "supports_embedding_image_input": true, "supports_vision": true }, "oci/cohere.command-a-reasoning-08-2025": { @@ -46388,6 +47367,19 @@ "supports_response_schema": true, "supports_tool_choice": false }, + "parallel_ai/decision": { + "input_cost_per_query": 0.001, + "input_cost_per_token": 0.0, + "output_cost_per_token": 0.0, + "litellm_provider": "parallel_ai", + "max_input_tokens": 32000, + "mode": "evaluation", + "source": "https://docs.parallel.ai/getting-started/pricing#decisions-api", + "supported_endpoints": [ + "/v1/decisions", + "/v1/systemone" + ] + }, "parallel_ai/search": { "input_cost_per_query": 0.005, "litellm_provider": "parallel_ai", @@ -47005,6 +47997,7 @@ }, "qwen.qwen3-coder-480b-a35b-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-qwen-qwen3-coder-480b-a35b-instruct.html", "input_cost_per_token": 4.5e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 262144, @@ -47036,6 +48029,7 @@ }, "qwen.qwen3-coder-30b-a3b-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, "input_cost_per_token_priority": 2.625e-07, @@ -48615,6 +49609,7 @@ }, "text-embedding-004": { "deprecation_date": "2027-04-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_character": 2.5e-08, "input_cost_per_token": 1e-07, "litellm_provider": "vertex_ai-embedding-models", @@ -48626,6 +49621,7 @@ }, "text-embedding-005": { "deprecation_date": "2027-04-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_character": 2.5e-08, "input_cost_per_token": 1e-07, "litellm_provider": "vertex_ai-embedding-models", @@ -48696,6 +49692,7 @@ }, "text-multilingual-embedding-002": { "deprecation_date": "2027-04-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_character": 2.5e-08, "input_cost_per_token": 1e-07, "litellm_provider": "vertex_ai-embedding-models", @@ -48810,6 +49807,7 @@ }, "together_ai/meta-llama/Llama-3.3-70B-Instruct-Turbo": { "deprecation_date": "2026-10-22", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 1.04e-06, "litellm_provider": "together_ai", "max_input_tokens": 131072, @@ -48817,6 +49815,7 @@ "mode": "chat", "output_cost_per_token": 1.04e-06, "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/meta-models/Muse-Glimmer-30B", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -48876,6 +49875,7 @@ "together_ai/MiniMaxAI/MiniMax-M3": { "cache_read_input_token_cost": 6e-08, "deprecation_date": "2026-11-06", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 3e-07, "litellm_provider": "together_ai", "max_input_tokens": 524288, @@ -48883,6 +49883,7 @@ "mode": "chat", "output_cost_per_token": 1.2e-06, "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/MiniMaxAI/MiniMax-M3.1-Flash", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -48959,6 +49960,7 @@ "together_ai/Qwen/Qwen3.8-2.4T-A95B": { "cache_read_input_token_cost": 2.5e-07, "deprecation_date": "2026-11-04", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 2e-06, "litellm_provider": "together_ai", "max_input_tokens": 1010000, @@ -48966,6 +49968,7 @@ "mode": "chat", "output_cost_per_token": 6e-06, "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/Qwen/Qwen3.7-Max", "supports_prompt_caching": true }, "together_ai/arize-ai/qwen-2-1.5b-instruct": { @@ -48980,6 +49983,7 @@ "together_ai/deepseek-ai/DeepSeek-V4-Flash-0731": { "cache_read_input_token_cost": 3e-08, "deprecation_date": "2026-10-22", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 1.4e-07, "litellm_provider": "together_ai", "max_input_tokens": 1048576, @@ -48987,6 +49991,7 @@ "mode": "chat", "output_cost_per_token": 2.8e-07, "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/deepseek-ai/DeepSeek-V4.1-Flash-1017", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -49071,6 +50076,7 @@ "together_ai/thinkingmachines/Inkling": { "cache_read_input_token_cost": 1.7e-07, "deprecation_date": "2026-11-06", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 1e-06, "litellm_provider": "together_ai", "max_input_tokens": 524288, @@ -49078,6 +50084,7 @@ "mode": "chat", "output_cost_per_token": 4.05e-06, "source": "https://api.together.ai/v1/models", + "successor_model": "together_ai/meta-models/Muse-Spark-Open-816B-A42B", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -49135,6 +50142,8 @@ }, "tts-1": { "deprecation_date": "2027-01-06", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_character": 1.5e-05, "litellm_provider": "openai", "mode": "audio_speech", @@ -49145,6 +50154,8 @@ }, "tts-1-hd": { "deprecation_date": "2027-01-06", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_character": 3e-05, "litellm_provider": "openai", "mode": "audio_speech", @@ -49375,6 +50386,7 @@ "cache_creation_input_token_cost": 1.875e-05, "cache_read_input_token_cost": 1.5e-06, "deprecation_date": "2027-01-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.5e-05, "litellm_provider": "bedrock_converse", "max_input_tokens": 200000, @@ -49413,6 +50425,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.32e-05, "cache_read_input_token_cost_above_200k_tokens": 6.6e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "us.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -49455,6 +50469,8 @@ "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.44e-05, "cache_read_input_token_cost_above_200k_tokens": 7.2e-07, "deprecation_date": "2027-04-08", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-anthropic-claude-sonnet-4-5.md", + "successor_model": "us-gov.anthropic.claude-sonnet-5-5", "litellm_provider": "bedrock_converse", "supports_tool_search": true, "max_input_tokens": 200000, @@ -49495,6 +50511,7 @@ "prompt_cache_min_tokens": 1024, "source": "https://aws.amazon.com/bedrock/pricing/", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -49570,8 +50587,9 @@ "mode": "chat", "output_cost_per_token": 3e-05, "prompt_cache_min_tokens": 512, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-gov-west-1/index.json", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -49592,7 +50610,9 @@ "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "us-gov-west-1" - } + }, + "input_cost_per_token_batches": 3e-06, + "output_cost_per_token_batches": 1.5e-05 }, "us-gov.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -49615,6 +50635,7 @@ "supports_max_reasoning_effort": true, "supports_mid_conversation_system": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_output_config": true, "supports_parallel_tool_use_config": true, "supports_pdf_input": true, @@ -49659,6 +50680,7 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_max_reasoning_effort": true, "supports_output_config": true, "bedrock_output_config_effort_ceiling": "xhigh", @@ -49689,6 +50711,7 @@ }, "us-gov.nvidia.nemotron-nano-12b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-12b-v2-vl-bf16.html", "input_cost_per_token": 2.4e-07, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -49704,6 +50727,7 @@ }, "us-gov.nvidia.nemotron-nano-9b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-9b-v2.html", "input_cost_per_token": 7.2e-08, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -49959,6 +50983,8 @@ "cache_creation_input_token_cost": 3.75e-06, "cache_read_input_token_cost": 3e-07, "deprecation_date": "2026-10-14", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "us.anthropic.claude-sonnet-5", "input_cost_per_token": 3e-06, "input_cost_per_token_above_200k_tokens": 6e-06, "output_cost_per_token_above_200k_tokens": 2.25e-05, @@ -49993,6 +51019,7 @@ }, "us.deepseek.r1-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-r1.html", "input_cost_per_token": 1.35e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -50045,6 +51072,7 @@ }, "us.meta.llama3-1-405b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2.4e-06, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -50057,6 +51085,7 @@ }, "us.meta.llama3-1-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "input_cost_per_token_batches": 3.6e-07, "litellm_provider": "bedrock", @@ -50071,6 +51100,7 @@ }, "us.meta.llama3-1-8b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 2.2e-07, "input_cost_per_token_batches": 1.1e-07, "litellm_provider": "bedrock", @@ -50085,6 +51115,7 @@ }, "us.meta.llama3-2-11b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.6e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -50098,6 +51129,7 @@ }, "us.meta.llama3-2-1b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-1b-instruct.md", "input_cost_per_token": 1e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -50110,6 +51142,7 @@ }, "us.meta.llama3-2-3b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-3-2-3b-instruct.md", "input_cost_per_token": 1.5e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -50122,6 +51155,7 @@ }, "us.meta.llama3-2-90b-instruct-v1:0": { "deprecation_date": "2026-07-07", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, @@ -50135,6 +51169,7 @@ }, "us.meta.llama3-3-70b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7.2e-07, "input_cost_per_token_batches": 3.6e-07, "litellm_provider": "bedrock_converse", @@ -50149,6 +51184,7 @@ }, "us.meta.llama4-maverick-17b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-4-maverick-17b-instruct.md", "input_cost_per_token": 2.4e-07, "input_cost_per_token_batches": 1.2e-07, "litellm_provider": "bedrock_converse", @@ -50171,6 +51207,7 @@ }, "us.meta.llama4-scout-17b-instruct-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-meta-llama-4-scout-17b-instruct.md", "input_cost_per_token": 1.7e-07, "input_cost_per_token_batches": 8.5e-08, "litellm_provider": "bedrock_converse", @@ -51431,6 +52468,7 @@ }, "vertex_ai/claude-haiku-4-5": { "deprecation_date": "2026-10-15", + "successor_model": "vertex_ai/claude-haiku-5-5", "cache_creation_input_token_cost": 1.25e-06, "cache_creation_input_token_cost_above_1hr": 2e-06, "cache_creation_input_token_cost_batches": 6.25e-07, @@ -51550,32 +52588,6 @@ "supports_tool_choice": true, "supports_vision": true }, - "vertex_ai/claude-3-opus": { - "deprecation_date": "2025-08-01", - "input_cost_per_token": 1.5e-05, - "litellm_provider": "vertex_ai-anthropic_models", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "vertex_ai/claude-3-opus@20240229": { - "deprecation_date": "2025-08-01", - "input_cost_per_token": 1.5e-05, - "litellm_provider": "vertex_ai-anthropic_models", - "max_input_tokens": 200000, - "max_output_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 7.5e-05, - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_tool_choice": true, - "supports_vision": true - }, "vertex_ai/claude-3-sonnet": { "input_cost_per_token": 3e-06, "litellm_provider": "vertex_ai-anthropic_models", @@ -51602,6 +52614,7 @@ }, "vertex_ai/claude-opus-4-5": { "deprecation_date": "2026-11-24", + "successor_model": "vertex_ai/claude-opus-5-5", "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_creation_input_token_cost_batches": 3.125e-06, @@ -51982,6 +52995,7 @@ "regional_endpoint_uplift_multiplier": 1.1, "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_creation_input_token_cost_batches": 3.125e-06, @@ -52020,6 +53034,7 @@ "regional_endpoint_uplift_multiplier": 1.1, "supports_mid_conversation_system": true, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "cache_creation_input_token_cost": 6.25e-06, "cache_creation_input_token_cost_above_1hr": 1e-05, "cache_creation_input_token_cost_batches": 3.125e-06, @@ -52211,6 +53226,7 @@ }, "vertex_ai/claude-sonnet-4-5": { "deprecation_date": "2026-09-29", + "successor_model": "vertex_ai/claude-sonnet-5-5", "cache_creation_input_token_cost": 3.75e-06, "cache_creation_input_token_cost_above_1hr": 6e-06, "cache_creation_input_token_cost_above_1hr_above_200k_tokens": 1.2e-05, @@ -52268,6 +53284,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -52498,6 +53515,8 @@ }, "vertex_ai/gemini-2.5-flash-image": { "deprecation_date": "2027-03-15", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.1-flash-lite-image", "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, @@ -52548,12 +53567,13 @@ }, "vertex_ai/gemini-3-pro-image": { "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, - "cache_read_input_token_cost_batches": 1e-07, "cache_read_input_token_cost_flex": 1e-07, "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_above_200k_tokens": 4e-06, @@ -52568,6 +53588,7 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "output_cost_per_image_token_batches": 6e-05, + "output_cost_per_image_token_priority": 0.000216, "output_cost_per_token": 1.2e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, @@ -52603,6 +53624,7 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "output_cost_per_image_token_batches": 6e-05, + "output_cost_per_image_token_priority": 0.000216, "output_cost_per_token": 1.2e-05, "output_cost_per_token_priority": 2.16e-05, "output_cost_per_token_above_200k_tokens": 1.8e-05, @@ -52624,6 +53646,7 @@ "cache_read_input_token_cost_flex": 2.5e-08, "cache_read_input_token_cost_priority": 9e-08, "deprecation_date": "2027-05-28", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "input_cost_per_image": 0.00056, "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, @@ -52636,6 +53659,7 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_image_token_batches": 3e-05, + "output_cost_per_image_token_priority": 0.000108, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "output_cost_per_token_flex": 1.5e-06, @@ -52664,6 +53688,7 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_image_token_batches": 3e-05, + "output_cost_per_image_token_priority": 0.000108, "output_cost_per_token": 3e-06, "output_cost_per_token_batches": 1.5e-06, "supports_reasoning": false, @@ -52693,6 +53718,7 @@ "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, "output_cost_per_image_token_batches": 1.5e-05, + "output_cost_per_image_token_priority": 5.4e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, @@ -52773,17 +53799,28 @@ }, "vertex_ai/gemini-3.1-flash-lite": { "cache_read_input_audio_token_cost": 5e-08, - "deprecation_date": "2027-05-07", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "cache_read_input_audio_token_cost_batches": 2.5e-08, + "cache_read_input_audio_token_cost_flex": 2.5e-08, + "cache_read_input_audio_token_cost_priority": 9e-08, "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_batches": 1.25e-08, "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, + "deprecation_date": "2027-05-07", + "google_maps_grounding_cost_per_query": 0.014, "input_cost_per_audio_token": 5e-07, + "input_cost_per_audio_token_above_200k_tokens": 5e-07, + "input_cost_per_audio_token_above_200k_tokens_batches": 2.5e-07, + "input_cost_per_audio_token_above_200k_tokens_flex": 2.5e-07, + "input_cost_per_audio_token_above_200k_tokens_priority": 9e-07, + "input_cost_per_audio_token_batches": 2.5e-07, + "input_cost_per_audio_token_flex": 2.5e-07, + "input_cost_per_audio_token_priority": 9e-07, "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, "input_cost_per_token_flex": 1.25e-07, "input_cost_per_token_priority": 4.5e-07, - "input_cost_per_audio_token_priority": 9e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65536, @@ -52794,7 +53831,10 @@ "output_cost_per_token_flex": 7.5e-07, "output_cost_per_token_priority": 2.7e-06, "regional_endpoint_uplift_multiplier": 1.1, + "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, + "search_free_requests": {"count":5000,"period":"month","shared_group":"gemini-3"}, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "successor_model": "vertex_ai/gemini-3.5-flash-lite", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -52812,6 +53852,7 @@ "supports_audio_input": true, "supports_audio_output": false, "supports_function_calling": true, + "supports_native_streaming": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, "supports_prompt_caching": true, @@ -52823,19 +53864,11 @@ "supports_video_input": true, "supports_vision": true, "supports_web_search": true, - "supports_native_streaming": true, - "search_context_cost_per_query": { - "search_context_size_low": 0.014, - "search_context_size_medium": 0.014, - "search_context_size_high": 0.014 - }, - "search_free_requests": {"count": 5000, "period": "month", "shared_group": "gemini-3"}, - "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014, - "input_cost_per_audio_token_batches": 2.5e-07 + "web_search_billing_unit": "per_query" }, "vertex_ai/gemini-3.5-flash-lite": { "deprecation_date": "2027-07-21", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "cache_read_input_token_cost": 3e-08, "cache_read_input_token_cost_batches": 1.5e-08, "cache_read_input_token_cost_flex": 1.5e-08, @@ -53251,6 +54284,7 @@ "vertex_ai/zai-org/glm-4.7-maas": { "cache_read_input_token_cost": 6e-08, "deprecation_date": "2026-10-21", + "successor_model": "vertex_ai/zai-org/glm-5.2-maas", "input_cost_per_token": 6e-07, "litellm_provider": "vertex_ai-zai_models", "max_input_tokens": 200000, @@ -53269,6 +54303,7 @@ "vertex_ai/zai-org/glm-5-maas": { "cache_read_input_token_cost": 1e-07, "deprecation_date": "2026-10-21", + "successor_model": "vertex_ai/zai-org/glm-5.2-maas", "input_cost_per_token": 1e-06, "litellm_provider": "vertex_ai-zai_models", "max_input_tokens": 200000, @@ -53688,6 +54723,7 @@ }, "vertex_ai/veo-3.1-generate-001": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "mode": "video_generation", @@ -53703,6 +54739,7 @@ }, "vertex_ai/veo-3.1-fast-generate-001": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "mode": "video_generation", @@ -53905,7 +54942,7 @@ "voyage/voyage-lite-01": { "input_cost_per_token": 1e-07, "litellm_provider": "voyage", - "max_input_tokens": 4096, + "max_input_tokens": 4000, "mode": "embedding", "output_cost_per_token": 0.0 }, @@ -53921,7 +54958,8 @@ "litellm_provider": "voyage", "max_input_tokens": 32000, "mode": "embedding", - "output_cost_per_token": 0.0 + "output_cost_per_token": 0.0, + "supports_embedding_image_input": true }, "wandb/openai/gpt-oss-120b": { "supports_reasoning": true, @@ -53958,23 +54996,23 @@ "supports_vision": true }, "wandb/meta-llama/Llama-3.1-8B-Instruct": { - "max_input_tokens": 131000, + "max_input_tokens": 128000, "max_output_tokens": 128000, "input_cost_per_token": 2.2e-07, "output_cost_per_token": 2.2e-07, "litellm_provider": "wandb", "mode": "chat", - "source": "https://wandb.ai/site/pricing/tokens/" + "source": "https://www.coreweave.com/products/coreweave-forge/serverless-inference" }, "wandb/deepseek-ai/DeepSeek-V3.1": { "supports_reasoning": true, - "max_input_tokens": 161000, + "max_input_tokens": 128000, "max_output_tokens": 128000, "input_cost_per_token": 5.5e-07, "output_cost_per_token": 1.65e-06, "litellm_provider": "wandb", "mode": "chat", - "source": "https://wandb.ai/site/pricing/tokens/" + "source": "https://www.coreweave.com/products/coreweave-forge/serverless-inference" }, "wandb/meta-llama/Llama-3.3-70B-Instruct": { "max_input_tokens": 128000, @@ -54353,6 +55391,8 @@ "/v1/audio/transcriptions" ], "deprecation_date": "2027-02-26", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-live-transcribe", "source": "https://developers.openai.com/api/docs/pricing" }, "xai/grok-4.20-multi-agent-beta-0309": { @@ -54458,6 +55498,8 @@ "input_cost_per_token_above_200k_tokens_batches": 2e-06, "input_cost_per_token_batches": 1e-06, "litellm_provider": "xai", + "token_count_framing": 185, + "token_count_tool_framing": 214, "max_input_tokens": 1000000, "max_output_tokens": 1000000, "mode": "chat", @@ -54614,6 +55656,8 @@ }, "zai.glm-4.7": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "zai.glm-5", "input_cost_per_token": 6e-07, "input_cost_per_token_batches": 3e-07, "input_cost_per_token_flex": 3e-07, @@ -54658,6 +55702,7 @@ }, "zai.glm-4.7-flash": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 7e-08, "input_cost_per_token_batches": 3.5e-08, "input_cost_per_token_flex": 3.5e-08, @@ -54971,6 +56016,7 @@ }, "openai/sora-2": { "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.1, @@ -54985,6 +56031,7 @@ }, "openai/sora-2-pro": { "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.3, @@ -55000,6 +56047,7 @@ "openai/sora-2-pro-high-res": { "litellm_provider": "openai", "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "mode": "video_generation", "output_cost_per_video_per_second": 0.5, "source": "https://platform.openai.com/docs/api-reference/videos", @@ -58666,6 +59714,8 @@ }, "gpt-4o-mini-tts-2025-12-15": { "deprecation_date": "2027-01-06", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", @@ -58686,6 +59736,8 @@ }, "gpt-4o-mini-transcribe-2025-03-20": { "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-4o-mini-transcribe-2025-12-15", "input_cost_per_audio_token": 1.25e-06, "input_cost_per_second": 5e-05, "input_cost_per_token": 1.25e-06, @@ -58701,6 +59753,8 @@ }, "gpt-4o-mini-transcribe-2025-12-15": { "deprecation_date": "2027-02-26", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-live-transcribe", "input_cost_per_audio_token": 1.25e-06, "input_cost_per_second": 5e-05, "input_cost_per_token": 1.25e-06, @@ -58722,6 +59776,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -58749,6 +59804,7 @@ "max_output_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -58800,6 +59856,8 @@ "supports_system_messages": true, "supports_tool_choice": true, "deprecation_date": "2027-01-20", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-realtime-2.1-mini", "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-realtime-whisper": { @@ -58821,6 +59879,7 @@ }, "sora-2": { "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.1, @@ -58835,6 +59894,7 @@ }, "sora-2-pro": { "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.3, @@ -58850,6 +59910,7 @@ "sora-2-pro-high-res": { "litellm_provider": "openai", "deprecation_date": "2026-09-24", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", "mode": "video_generation", "output_cost_per_video_per_second": 0.5, "source": "https://developers.openai.com/api/docs/pricing", @@ -58866,6 +59927,8 @@ "cache_read_input_token_cost": 1.25e-06, "cache_read_input_token_cost_batches": 6.3e-07, "deprecation_date": "2026-12-01", + "deprecation_source": "https://developers.openai.com/api/docs/deprecations", + "successor_model": "gpt-image-2.5-sunburst", "input_cost_per_image_token": 8e-06, "input_cost_per_image_token_batches": 4e-06, "input_cost_per_token": 5e-06, @@ -58873,6 +59936,7 @@ "litellm_provider": "openai", "mode": "image_generation", "output_cost_per_image_token": 3.2e-05, + "output_cost_per_image_token_batches": 1.6e-05, "output_cost_per_token": 1e-05, "output_cost_per_token_batches": 5e-06, "source": "https://developers.openai.com/api/docs/pricing", @@ -58881,48 +59945,6 @@ "/v1/images/edits" ] }, - "gemini-2.0-flash-exp-image-generation": { - "deprecation_date": "2025-11-14", - "input_cost_per_token": 0.0, - "litellm_provider": "gemini", - "max_input_tokens": 32768, - "max_output_tokens": 32768, - "mode": "image_generation", - "output_cost_per_image": 0.039, - "output_cost_per_token": 0.0, - "source": "https://ai.google.dev/pricing", - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_vision": true - }, - "gemini/gemini-2.0-flash-exp-image-generation": { - "deprecation_date": "2025-11-14", - "input_cost_per_token": 0.0, - "litellm_provider": "gemini", - "max_input_tokens": 32768, - "max_output_tokens": 32768, - "mode": "image_generation", - "output_cost_per_image": 0.039, - "output_cost_per_token": 0.0, - "source": "https://ai.google.dev/pricing", - "supported_modalities": [ - "text", - "image" - ], - "supported_output_modalities": [ - "text", - "image" - ], - "supports_vision": true, - "tpm": 250000, - "rpm": 10 - }, "gemini-2.5-flash-native-audio-latest": { "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 5e-07, @@ -58975,6 +59997,8 @@ }, "gemini-2.5-flash-native-audio-preview-12-2025": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-live", "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 5e-07, "litellm_provider": "gemini", @@ -59006,6 +60030,8 @@ }, "gemini-3.1-flash-live-preview": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-live", "input_cost_per_audio_token": 3e-06, "input_cost_per_image_token": 1e-06, "input_cost_per_token": 7.5e-07, @@ -59163,6 +60189,8 @@ }, "gemini/gemini-2.5-flash-native-audio-preview-12-2025": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-live", "input_cost_per_audio_token": 3e-06, "input_cost_per_token": 5e-07, "litellm_provider": "gemini", @@ -59197,6 +60225,8 @@ }, "gemini/gemini-3.1-flash-live-preview": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-live", "input_cost_per_audio_token": 3e-06, "input_cost_per_image_token": 1e-06, "input_cost_per_token": 7.5e-07, @@ -59236,6 +60266,8 @@ }, "gemini/gemini-3.1-flash-tts-preview": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash-tts", "input_cost_per_token": 1e-06, "input_cost_per_token_batches": 5e-07, "litellm_provider": "gemini", @@ -59305,6 +60337,8 @@ }, "gemini-2.5-flash-preview-tts": { "deprecation_date": "2026-11-17", + "deprecation_source": "https://ai.google.dev/gemini-api/docs/deprecations", + "successor_model": "gemini/gemini-3.8-flash-tts", "input_cost_per_token": 5e-07, "input_cost_per_token_batches": 2.5e-07, "litellm_provider": "gemini", @@ -59626,6 +60660,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -59876,6 +60911,7 @@ "max_input_tokens": 922000, "max_output_tokens": 128000, "mode": "responses", + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-cyber.html", "use_openai_responses_path": true, "supported_endpoints": [ @@ -59897,7 +60933,8 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, - "supports_vision": true + "supports_vision": true, + "supports_web_search": true }, "bedrock_mantle/openai.gpt-daybreak-blue-5.6-sol": { "input_cost_per_token": 4.4e-06, @@ -59912,6 +60949,7 @@ "max_input_tokens": 1050000, "max_output_tokens": 128000, "mode": "responses", + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "use_openai_responses_path": true, "supported_endpoints": [ "/v1/responses" @@ -59931,7 +60969,8 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-daybreak-blue-56-sol.html" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-daybreak-blue-56-sol.html", + "supports_web_search": true }, "bedrock_mantle/openai.gpt-5.6-luna": { "input_cost_per_token": 2.2e-07, @@ -60337,6 +61376,7 @@ "mode": "responses", "output_cost_per_token_above_272k_tokens_ultrafast": 0.000495, "output_cost_per_token_ultrafast": 0.00033, + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -60360,7 +61400,8 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-astra.html" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-astra.html", + "supports_web_search": true }, "bedrock_mantle/openai.gpt-6-sol": { "input_cost_per_token": 2.2e-06, @@ -60375,6 +61416,7 @@ "max_input_tokens": 922000, "max_output_tokens": 128000, "mode": "responses", + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -60398,7 +61440,8 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards-openai.html" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards-openai.html", + "supports_web_search": true }, "bedrock_mantle/openai.gpt-6-luna": { "input_cost_per_token": 1.1e-07, @@ -60413,6 +61456,7 @@ "max_input_tokens": 922000, "max_output_tokens": 128000, "mode": "responses", + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -60436,7 +61480,8 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards-openai.html" + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-cards-openai.html", + "supports_web_search": true }, "us.openai.gpt-6-astra": { "supports_bedrock_runtime_chat_completions_response_format": true, @@ -62632,7 +63677,9 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "token_count_framing": 23, + "token_count_tool_framing": 12 }, "deepseek/deepseek-v4-flash-vision-exp": { "cache_creation_input_token_cost": 0.0, @@ -62738,7 +63785,9 @@ "supports_response_schema": true, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": false + "supports_vision": false, + "token_count_framing": 76, + "token_count_tool_framing": 75 }, "tencent/deepseek-v4-pro": { "cache_creation_input_token_cost": 0.0, @@ -63351,6 +64400,10 @@ "input_cost_per_second": 7.5e-05, "litellm_provider": "openai", "mode": "audio_transcription", + "provider_specific_entry": { + "transcription_json_or_text_only": 1, + "transcription_usage_duration": 1 + }, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/transcriptions", @@ -63363,7 +64416,8 @@ "supported_output_modalities": [ "text" ], - "supports_audio_input": true + "supports_audio_input": true, + "supports_native_streaming": true }, "gpt-live-transcribe": { "input_cost_per_second": 0.000283333333333, @@ -63381,7 +64435,8 @@ "supported_output_modalities": [ "text" ], - "supports_audio_input": true + "supports_audio_input": true, + "supports_native_streaming": true }, "gpt-live-1": { "input_cost_per_second": 0.000833333333333, @@ -63415,7 +64470,8 @@ "audio" ], "supports_audio_input": true, - "supports_audio_output": true + "supports_audio_output": true, + "supports_native_streaming": true }, "claude-mythos-5": { "supports_anthropic_compaction": true, @@ -63506,6 +64562,7 @@ }, "claude-mythos-preview": { "deprecation_date": "2026-06-09", + "deprecation_source": "https://platform.claude.com/docs/en/about-claude/model-deprecations", "supports_anthropic_compaction": true, "cache_creation_input_token_cost": 1.25e-05, "cache_creation_input_token_cost_above_1hr": 2e-05, @@ -63695,7 +64752,8 @@ { "name": "claude-family-baseline", "pattern": "claude-[a-z]+-\\d+(?:[-.]\\d+)?(?:-\\d{8})?", - "description": "Any Claude family-major id with an optional minor and an optional 8-digit date suffix, under any provider namespace (bare, bedrock-dotted, vertex, databricks, ...), so bare majors like claude-newfamily-5 get the same baseline as claude-newfamily-5-1. Carries the model-family facts every Claude shares; it carries no pricing, so cost stays on the standard unpriced behavior rather than a guessed number.", + "fill_missing_for_providers": ["anthropic", "azure_ai", "bedrock", "bedrock_converse", "vertex_ai-anthropic_models"], + "description": "Any Claude family-major id with an optional minor and an optional 8-digit date suffix, under any provider namespace (bare, bedrock-dotted, vertex, databricks, ...), so bare majors like claude-newfamily-5 get the same baseline as claude-newfamily-5-1. Carries the model-family facts every Claude shares; it carries no pricing, so cost stays on the standard unpriced behavior rather than a guessed number. On mapped Claude entries from Anthropic, Azure Foundry, Bedrock and Vertex it only fills the keys an entry leaves out, so the entry's own values always win.", "model_info": { "mode": "chat", "max_input_tokens": 200000, @@ -63738,6 +64796,14 @@ "thinking_always_on": true } }, + { + "name": "claude-thinking-on-by-default", + "pattern": "claude-[a-z]+-[5-9](?!\\d)", + "description": "Claude at major 5 or higher, in any id shape that contains claude--. Anthropic's thinking docs list every Claude 5+ model as thinking by default (on or always on) when the request sends no thinking param, and every 4.x as off. Two-digit majors are deliberately not matched so ids like claude-opus-41 (4.1) are not read as major 41. The response_format json tool is then left unforced, since a forced tool call skips the model's thinking.", + "model_info": { + "thinking_on_by_default": true + } + }, { "name": "claude-mid-conversation-system", "pattern": "claude-[a-z]+-(?:4[-._](?:[89]|[1-9]\\d)(?!\\d)|[5-9](?!\\d)(?:[-._]\\d{1,2}(?!\\d))?)", @@ -64024,6 +65090,7 @@ "input_cost_per_token": 3e-07, "input_cost_per_token_priority": 3.75e-07, "litellm_provider": "fireworks_ai", + "token_count_framing": 23, "max_input_tokens": 1048576, "max_output_tokens": 393216, "mode": "chat", @@ -64031,6 +65098,7 @@ "output_cost_per_token_priority": 1.5e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -64050,6 +65118,7 @@ "output_cost_per_token_priority": 2.25e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -64092,6 +65161,7 @@ ], "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64122,6 +65192,7 @@ "input_cost_per_token": 3e-07, "input_cost_per_token_priority": 3.75e-07, "litellm_provider": "fireworks_ai", + "token_count_framing": 23, "max_input_tokens": 1048576, "max_output_tokens": 393216, "mode": "chat", @@ -64129,6 +65200,7 @@ "output_cost_per_token_priority": 1.5e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -64148,6 +65220,7 @@ "output_cost_per_token_priority": 2.25e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -64175,6 +65248,7 @@ "fireworks_ai/glm-5p2-fast": { "cache_read_input_token_cost": 2.1e-07, "deprecation_date": "2026-09-25", + "successor_model": "fireworks_ai/glm-5p3-fast", "input_cost_per_token": 2.1e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, @@ -64222,6 +65296,7 @@ ], "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64242,6 +65317,7 @@ ], "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64265,6 +65341,7 @@ ], "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64340,6 +65417,7 @@ "output_cost_per_token_priority": 3e-06, "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64376,6 +65454,7 @@ "output_cost_per_token_priority": 6.375e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_vision": true }, @@ -64412,6 +65491,7 @@ "output_cost_per_token_priority": 3e-06, "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64438,6 +65518,7 @@ "fireworks_ai/accounts/fireworks/routers/glm-5p2-fast": { "cache_read_input_token_cost": 2.1e-07, "deprecation_date": "2026-09-25", + "successor_model": "fireworks_ai/accounts/fireworks/routers/glm-5p3-fast", "input_cost_per_token": 2.1e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, @@ -64482,6 +65563,7 @@ ], "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64505,6 +65587,7 @@ ], "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -64527,7 +65610,7 @@ "supports_vision": false }, "novita/deepseek/deepseek-v4-pro-0813": { - "cache_read_input_token_cost": 1.3200000000000002e-07, + "cache_read_input_token_cost": 4.4e-08, "input_cost_per_token": 1.32e-06, "litellm_provider": "novita", "max_input_tokens": 1048576, @@ -64639,13 +65722,13 @@ "supports_vision": false }, "novita/mindai/macaron-v1-venti": { - "cache_read_input_token_cost": 3e-07, - "input_cost_per_token": 1.5e-06, + "cache_read_input_token_cost": 1.65e-07, + "input_cost_per_token": 8.25e-07, "litellm_provider": "novita", "max_input_tokens": 1048576, "max_output_tokens": 131072, "mode": "chat", - "output_cost_per_token": 4.5e-06, + "output_cost_per_token": 2.475e-06, "source": "https://novita.ai/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -64748,13 +65831,13 @@ "supports_vision": false }, "novita/mindai/macaron-v1-tall": { - "cache_read_input_token_cost": 8e-08, - "input_cost_per_token": 4.5000000000000003e-07, + "cache_read_input_token_cost": 4.4e-08, + "input_cost_per_token": 2.475e-07, "litellm_provider": "novita", "max_input_tokens": 262144, "max_output_tokens": 32768, "mode": "chat", - "output_cost_per_token": 2.6e-06, + "output_cost_per_token": 1.43e-06, "source": "https://novita.ai/pricing", "supports_function_calling": true, "supports_prompt_caching": true, @@ -66179,9 +67262,9 @@ "deepinfra/deepseek-ai/DeepSeek-V4-Flash-0731": { "max_output_tokens": 1048576, "max_input_tokens": 1048576, - "input_cost_per_token": 8e-08, + "input_cost_per_token": 6e-08, "output_cost_per_token": 1.8e-07, - "cache_read_input_token_cost": 1.6e-08, + "cache_read_input_token_cost": 1.5e-08, "supports_prompt_caching": true, "litellm_provider": "deepinfra", "mode": "chat", @@ -66560,8 +67643,8 @@ "deepinfra/google/gemma-4-31B-it": { "max_output_tokens": 262144, "max_input_tokens": 262144, - "input_cost_per_token": 1.3e-07, - "output_cost_per_token": 3.8e-07, + "input_cost_per_token": 2e-07, + "output_cost_per_token": 4e-07, "litellm_provider": "deepinfra", "mode": "chat", "supports_function_calling": true, @@ -66718,10 +67801,12 @@ }, "xai/grok-imagine-image-quality": { "deprecation_date": "2026-11-02", + "deprecation_source": "https://docs.x.ai/developers/migration/imagine-image-quality-nov-2", "input_cost_per_image": 0.05, "litellm_provider": "xai", "mode": "image_generation", "source": "https://docs.x.ai/docs/models", + "successor_model": "xai/grok-imagine-image-2.0", "supported_endpoints": [ "/v1/images/generations" ], @@ -66735,10 +67820,12 @@ }, "xai/grok-imagine-image-quality-20260403": { "deprecation_date": "2026-11-02", + "deprecation_source": "https://docs.x.ai/developers/migration/imagine-image-quality-nov-2", "input_cost_per_image": 0.05, "litellm_provider": "xai", "mode": "image_generation", "source": "https://docs.x.ai/docs/models", + "successor_model": "xai/grok-imagine-image-2.0", "supported_endpoints": [ "/v1/images/generations" ], @@ -66752,10 +67839,12 @@ }, "xai/grok-imagine-image-quality-latest": { "deprecation_date": "2026-11-02", + "deprecation_source": "https://docs.x.ai/developers/migration/imagine-image-quality-nov-2", "input_cost_per_image": 0.05, "litellm_provider": "xai", "mode": "image_generation", "source": "https://docs.x.ai/docs/models", + "successor_model": "xai/grok-imagine-image-2.0", "supported_endpoints": [ "/v1/images/generations" ], @@ -66769,10 +67858,12 @@ }, "xai/grok-imagine-image-pro": { "deprecation_date": "2026-05-15", + "deprecation_source": "https://docs.x.ai/developers/migration/may-15-retirement", "input_cost_per_image": 0.05, "litellm_provider": "xai", "mode": "image_generation", "source": "https://docs.x.ai/docs/models", + "successor_model": "xai/grok-imagine-image-2.0", "supported_endpoints": [ "/v1/images/generations" ], @@ -66890,6 +67981,8 @@ }, "xai/grok-voice-transcribe-1.0": { "deprecation_date": "2026-10-02", + "deprecation_source": "https://docs.x.ai/docs/release-notes", + "successor_model": "xai/grok-voice-transcribe-2.0", "input_cost_per_second": 2.778e-05, "litellm_provider": "xai", "metadata": { @@ -67298,6 +68391,7 @@ "output_cost_per_token_priority": 5.5e-06, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67316,6 +68410,7 @@ "output_cost_per_token_priority": 8.25e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67334,6 +68429,7 @@ "output_cost_per_token_priority": 5.5e-06, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67352,6 +68448,7 @@ "output_cost_per_token_priority": 8.25e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67367,6 +68464,7 @@ "output_cost_per_token": 6.6e-06, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67409,6 +68507,7 @@ "output_cost_per_token": 6.6e-06, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -67427,6 +68526,7 @@ "output_cost_per_token_priority": 6.25e-07, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -67445,6 +68545,7 @@ "output_cost_per_token_priority": 9.375e-07, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -67462,6 +68563,7 @@ "output_cost_per_token_priority": 6.25e-07, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -67480,6 +68582,7 @@ "output_cost_per_token_priority": 9.375e-07, "source": "https://docs.fireworks.ai/serverless/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -67498,6 +68601,7 @@ "output_cost_per_token_priority": 4.05e-06, "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true @@ -67744,6 +68848,7 @@ }, "together_ai/nvidia/NVIDIA-Nemotron-Nano-9B-v2": { "deprecation_date": "2026-02-25", + "deprecation_source": "https://docs.together.ai/docs/deprecations", "input_cost_per_token": 6e-08, "output_cost_per_token": 2.5e-07, "litellm_provider": "together_ai", @@ -67814,6 +68919,7 @@ "azure_ai/kimi-k2.7-code": { "cache_read_input_token_cost": 1.9e-07, "deprecation_date": "2027-04-16", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 9.5e-07, "litellm_provider": "azure_ai", "max_input_tokens": 262144, @@ -67849,6 +68955,7 @@ "supports_reasoning": true, "supports_tool_choice": true, "deprecation_date": "2026-12-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "source": "https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/deepseek-v4-1-flash-is-coming-to-microsoft-foundry/4556431" }, "azure_ai/MAI-Image-2.6": { @@ -67957,6 +69064,8 @@ }, "azure_ai/Cohere-command-a-plus-05-2026": { "deprecation_date": "2026-10-16", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "coherelabs-command-a-plus-05-2026-fp81", "input_cost_per_token": 8e-07, "litellm_provider": "azure_ai", "max_input_tokens": 128000, @@ -67990,6 +69099,8 @@ }, "azure_ai/deepseek-r1": { "deprecation_date": "2026-08-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/deepseek-v4-pro", "input_cost_per_token": 1.35e-06, "output_cost_per_token": 5.4e-06, "litellm_provider": "azure_ai", @@ -67999,6 +69110,8 @@ }, "azure_ai/deepseek-v3-0324": { "deprecation_date": "2026-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/deepseek-v4-flash", "input_cost_per_token": 1.14e-06, "output_cost_per_token": 4.56e-06, "litellm_provider": "azure_ai", @@ -68008,6 +69121,8 @@ }, "azure_ai/deepseek-v3.1": { "deprecation_date": "2026-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/deepseek-v4-flash", "input_cost_per_token": 1.23e-06, "output_cost_per_token": 4.94e-06, "litellm_provider": "azure_ai", @@ -68017,6 +69132,8 @@ }, "azure_ai/grok-3": { "deprecation_date": "2026-05-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/grok-4", "input_cost_per_token": 3e-06, "output_cost_per_token": 1.5e-05, "litellm_provider": "azure_ai", @@ -68026,6 +69143,8 @@ }, "azure_ai/grok-3-mini": { "deprecation_date": "2026-05-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/grok-4-1-fast-reasoning", "input_cost_per_token": 2.5e-07, "output_cost_per_token": 1.27e-06, "litellm_provider": "azure_ai", @@ -68035,6 +69154,8 @@ }, "azure_ai/grok-4-fast-non-reasoning": { "deprecation_date": "2026-05-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/grok-4-1-fast-non-reasoning", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", @@ -68044,6 +69165,8 @@ }, "azure_ai/grok-4-fast-reasoning": { "deprecation_date": "2026-05-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", + "successor_model": "azure_ai/grok-4-1-fast-reasoning", "input_cost_per_token": 2e-07, "output_cost_per_token": 5e-07, "litellm_provider": "azure_ai", @@ -68053,12 +69176,18 @@ }, "bedrock/us-gov-west-1/nvidia.nemotron-nano-3-30b": { "input_cost_per_token": 7.2e-08, + "input_cost_per_token_batches": 3.6e-08, + "input_cost_per_token_flex": 3.6e-08, + "input_cost_per_token_priority": 1.32e-07, "litellm_provider": "bedrock", "max_input_tokens": 262144, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.88e-07, - "source": "https://aws.amazon.com/bedrock/pricing/", + "output_cost_per_token_batches": 1.44e-07, + "output_cost_per_token_flex": 1.44e-07, + "output_cost_per_token_priority": 5.04e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_function_calling": true, "supports_native_structured_output": true, "supports_system_messages": true, @@ -68069,13 +69198,20 @@ }, "bedrock/us-gov-west-1/nvidia.nemotron-nano-12b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-12b-v2-vl-bf16.html", "input_cost_per_token": 2.4e-07, + "input_cost_per_token_batches": 1.2e-07, + "input_cost_per_token_flex": 1.2e-07, + "input_cost_per_token_priority": 4.2e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 7.2e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-12b-v2-vl-bf16.html", + "output_cost_per_token_batches": 3.6e-07, + "output_cost_per_token_flex": 3.6e-07, + "output_cost_per_token_priority": 1.26e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_system_messages": true, "supports_vision": true, "supports_audio_input": false, @@ -68084,13 +69220,20 @@ }, "bedrock/us-gov-west-1/nvidia.nemotron-nano-9b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-9b-v2.html", "input_cost_per_token": 7.2e-08, + "input_cost_per_token_batches": 3.6e-08, + "input_cost_per_token_flex": 3.6e-08, + "input_cost_per_token_priority": 1.32e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.76e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-9b-v2.html", + "output_cost_per_token_batches": 1.44e-07, + "output_cost_per_token_flex": 1.44e-07, + "output_cost_per_token_priority": 4.8e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_system_messages": true, "supports_audio_input": false, "supports_function_calling": true, @@ -68099,12 +69242,18 @@ }, "bedrock/us-gov-west-1/nvidia.nemotron-super-3-120b": { "input_cost_per_token": 1.8e-07, + "input_cost_per_token_batches": 9e-08, + "input_cost_per_token_flex": 9e-08, + "input_cost_per_token_priority": 3.15e-07, "litellm_provider": "bedrock", "max_input_tokens": 256000, "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 7.8e-07, - "source": "https://aws.amazon.com/bedrock/pricing/", + "output_cost_per_token_batches": 3.9e-07, + "output_cost_per_token_flex": 3.9e-07, + "output_cost_per_token_priority": 1.365e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supports_function_calling": true, "supports_reasoning": true, "supports_system_messages": true, @@ -68116,12 +69265,18 @@ "bedrock/us-gov-west-1/openai.gpt-oss-20b-1:0": { "supports_vision": false, "input_cost_per_token": 8.4e-08, + "input_cost_per_token_batches": 4.2e-08, + "input_cost_per_token_flex": 4.2e-08, + "input_cost_per_token_priority": 1.47e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 3.6e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-20b.html", + "output_cost_per_token_batches": 1.8e-07, + "output_cost_per_token_flex": 1.8e-07, + "output_cost_per_token_priority": 6.3e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supported_endpoints": [ "/v1/chat/completions" ], @@ -68135,12 +69290,18 @@ "bedrock/us-gov-west-1/openai.gpt-oss-120b-1:0": { "supports_vision": false, "input_cost_per_token": 1.8e-07, + "input_cost_per_token_batches": 9e-08, + "input_cost_per_token_flex": 9e-08, + "input_cost_per_token_priority": 3.15e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 7.2e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-120b.html", + "output_cost_per_token_batches": 3.6e-07, + "output_cost_per_token_flex": 3.6e-07, + "output_cost_per_token_priority": 1.26e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supported_endpoints": [ "/v1/chat/completions" ], @@ -68166,6 +69327,7 @@ "output_cost_per_token": 1.2e-05, "prompt_cache_min_tokens": 1024, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -68241,6 +69403,7 @@ "output_cost_per_token": 3e-05, "prompt_cache_min_tokens": 512, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -68261,7 +69424,10 @@ "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "us-gov-west-1" - } + }, + "input_cost_per_token_batches": 3e-06, + "output_cost_per_token_batches": 1.5e-05, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-gov-west-1/index.json" }, "bedrock/us-gov-west-1/anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -68283,6 +69449,7 @@ "supports_max_reasoning_effort": true, "supports_mid_conversation_system": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_output_config": true, "supports_parallel_tool_use_config": true, "supports_pdf_input": true, @@ -68328,6 +69495,7 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_max_reasoning_effort": true, "supports_output_config": true, "bedrock_output_config_effort_ceiling": "xhigh", @@ -68341,12 +69509,18 @@ }, "bedrock/us-gov-east-1/nvidia.nemotron-nano-3-30b": { "input_cost_per_token": 7.2e-08, + "input_cost_per_token_batches": 3.6e-08, + "input_cost_per_token_flex": 3.6e-08, + "input_cost_per_token_priority": 1.32e-07, "litellm_provider": "bedrock", "max_input_tokens": 262144, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.88e-07, - "source": "https://aws.amazon.com/bedrock/pricing/", + "output_cost_per_token_batches": 1.44e-07, + "output_cost_per_token_flex": 1.44e-07, + "output_cost_per_token_priority": 5.04e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supports_function_calling": true, "supports_native_structured_output": true, "supports_system_messages": true, @@ -68357,13 +69531,20 @@ }, "bedrock/us-gov-east-1/nvidia.nemotron-nano-12b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-12b-v2-vl-bf16.html", "input_cost_per_token": 2.4e-07, + "input_cost_per_token_batches": 1.2e-07, + "input_cost_per_token_flex": 1.2e-07, + "input_cost_per_token_priority": 4.2e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 7.2e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-12b-v2-vl-bf16.html", + "output_cost_per_token_batches": 3.6e-07, + "output_cost_per_token_flex": 3.6e-07, + "output_cost_per_token_priority": 1.26e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supports_system_messages": true, "supports_vision": true, "supports_audio_input": false, @@ -68372,13 +69553,20 @@ }, "bedrock/us-gov-east-1/nvidia.nemotron-nano-9b-v2": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-9b-v2.html", "input_cost_per_token": 7.2e-08, + "input_cost_per_token_batches": 3.6e-08, + "input_cost_per_token_flex": 3.6e-08, + "input_cost_per_token_priority": 1.32e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 2.76e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-nvidia-nvidia-nemotron-nano-9b-v2.html", + "output_cost_per_token_batches": 1.44e-07, + "output_cost_per_token_flex": 1.44e-07, + "output_cost_per_token_priority": 4.8e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supports_system_messages": true, "supports_audio_input": false, "supports_function_calling": true, @@ -68387,12 +69575,18 @@ }, "bedrock/us-gov-east-1/nvidia.nemotron-super-3-120b": { "input_cost_per_token": 1.8e-07, + "input_cost_per_token_batches": 9e-08, + "input_cost_per_token_flex": 9e-08, + "input_cost_per_token_priority": 3.15e-07, "litellm_provider": "bedrock", "max_input_tokens": 256000, "max_output_tokens": 32768, "mode": "chat", "output_cost_per_token": 7.8e-07, - "source": "https://aws.amazon.com/bedrock/pricing/", + "output_cost_per_token_batches": 3.9e-07, + "output_cost_per_token_flex": 3.9e-07, + "output_cost_per_token_priority": 1.365e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supports_function_calling": true, "supports_reasoning": true, "supports_system_messages": true, @@ -68404,12 +69598,18 @@ "bedrock/us-gov-east-1/openai.gpt-oss-20b-1:0": { "supports_vision": false, "input_cost_per_token": 8.4e-08, + "input_cost_per_token_batches": 4.2e-08, + "input_cost_per_token_flex": 4.2e-08, + "input_cost_per_token_priority": 1.47e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 3.6e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-20b.html", + "output_cost_per_token_batches": 1.8e-07, + "output_cost_per_token_flex": 1.8e-07, + "output_cost_per_token_priority": 6.3e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supported_endpoints": [ "/v1/chat/completions" ], @@ -68423,12 +69623,18 @@ "bedrock/us-gov-east-1/openai.gpt-oss-120b-1:0": { "supports_vision": false, "input_cost_per_token": 1.8e-07, + "input_cost_per_token_batches": 9e-08, + "input_cost_per_token_flex": 9e-08, + "input_cost_per_token_priority": 3.15e-07, "litellm_provider": "bedrock", "max_input_tokens": 128000, "max_output_tokens": 16384, "mode": "chat", "output_cost_per_token": 7.2e-07, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-120b.html", + "output_cost_per_token_batches": 3.6e-07, + "output_cost_per_token_flex": 3.6e-07, + "output_cost_per_token_priority": 1.26e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supported_endpoints": [ "/v1/chat/completions" ], @@ -68454,6 +69660,7 @@ "output_cost_per_token": 1.2e-05, "prompt_cache_min_tokens": 1024, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -68519,6 +69726,7 @@ "output_cost_per_token": 3e-05, "prompt_cache_min_tokens": 512, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -68534,7 +69742,10 @@ "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true, - "supports_xhigh_reasoning_effort": true + "supports_xhigh_reasoning_effort": true, + "input_cost_per_token_batches": 3e-06, + "output_cost_per_token_batches": 1.5e-05, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-gov-east-1/index.json" }, "bedrock/us-gov-east-1/anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -68556,6 +69767,7 @@ "supports_max_reasoning_effort": true, "supports_mid_conversation_system": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_output_config": true, "supports_parallel_tool_use_config": true, "supports_pdf_input": true, @@ -68596,6 +69808,7 @@ "supports_vision": true, "supports_xhigh_reasoning_effort": true, "supports_native_structured_output": false, + "supports_bedrock_native_structured_output": false, "supports_max_reasoning_effort": true, "supports_output_config": true, "bedrock_output_config_effort_ceiling": "xhigh", @@ -68627,15 +69840,33 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "input_cost_per_token": 2.7e-06, - "input_cost_per_token_above_272k_tokens": 5.4e-06, - "cache_creation_input_token_cost": 3.375e-06, - "cache_creation_input_token_cost_above_272k_tokens": 6.75e-06, - "cache_read_input_token_cost": 2.7e-07, - "cache_read_input_token_cost_above_272k_tokens": 5.4e-07, - "output_cost_per_token": 1.62e-05, - "output_cost_per_token_above_272k_tokens": 2.43e-05, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-terra.html" + "input_cost_per_token": 2.64e-06, + "input_cost_per_token_above_272k_tokens": 5.28e-06, + "cache_creation_input_token_cost": 3.3e-06, + "cache_creation_input_token_cost_above_272k_tokens": 6.6e-06, + "cache_creation_input_token_cost_above_272k_tokens_flex": 3.3e-06, + "cache_creation_input_token_cost_above_272k_tokens_priority": 1.32e-05, + "cache_creation_input_token_cost_flex": 1.65e-06, + "cache_creation_input_token_cost_priority": 6.6e-06, + "cache_read_input_token_cost": 2.64e-07, + "cache_read_input_token_cost_above_272k_tokens": 5.28e-07, + "cache_read_input_token_cost_above_272k_tokens_flex": 2.64e-07, + "cache_read_input_token_cost_above_272k_tokens_priority": 1.056e-06, + "cache_read_input_token_cost_flex": 1.32e-07, + "cache_read_input_token_cost_priority": 5.28e-07, + "input_cost_per_token_above_272k_tokens_flex": 2.64e-06, + "input_cost_per_token_above_272k_tokens_priority": 1.056e-05, + "input_cost_per_token_flex": 1.32e-06, + "input_cost_per_token_priority": 5.28e-06, + "output_cost_per_token": 1.584e-05, + "output_cost_per_token_above_272k_tokens": 2.376e-05, + "output_cost_per_token_above_272k_tokens_flex": 1.188e-05, + "output_cost_per_token_above_272k_tokens_priority": 4.752e-05, + "output_cost_per_token_flex": 7.92e-06, + "output_cost_per_token_priority": 3.168e-05, + "search_context_cost_per_query": {"search_context_size_high":0.0144,"search_context_size_low":0.0144,"search_context_size_medium":0.0144}, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", + "supports_web_search": true }, "bedrock_mantle/us-gov-west-1/openai.gpt-5.6-luna": { "litellm_provider": "bedrock_mantle", @@ -68662,15 +69893,33 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "input_cost_per_token": 2.7e-07, - "input_cost_per_token_above_272k_tokens": 5.4e-07, - "cache_creation_input_token_cost": 3.375e-07, - "cache_creation_input_token_cost_above_272k_tokens": 6.75e-07, - "cache_read_input_token_cost": 2.7e-08, - "cache_read_input_token_cost_above_272k_tokens": 5.4e-08, - "output_cost_per_token": 1.62e-06, - "output_cost_per_token_above_272k_tokens": 2.43e-06, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-56-luna.html" + "input_cost_per_token": 2.64e-07, + "input_cost_per_token_above_272k_tokens": 5.28e-07, + "cache_creation_input_token_cost": 3.3e-07, + "cache_creation_input_token_cost_above_272k_tokens": 6.6e-07, + "cache_creation_input_token_cost_above_272k_tokens_flex": 3.3e-07, + "cache_creation_input_token_cost_above_272k_tokens_priority": 1.32e-06, + "cache_creation_input_token_cost_flex": 1.65e-07, + "cache_creation_input_token_cost_priority": 6.6e-07, + "cache_read_input_token_cost": 2.64e-08, + "cache_read_input_token_cost_above_272k_tokens": 5.28e-08, + "cache_read_input_token_cost_above_272k_tokens_flex": 2.64e-08, + "cache_read_input_token_cost_above_272k_tokens_priority": 1.056e-07, + 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-68696,10 +69945,12 @@ "supports_tool_choice": true, "supports_xhigh_reasoning_effort": true, "supports_vision": true, - "input_cost_per_token": 3.375e-06, - "cache_read_input_token_cost": 3.375e-07, - "output_cost_per_token": 2.025e-05, - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-54.html" + "input_cost_per_token": 3.3e-06, + "cache_read_input_token_cost": 3.3e-07, + "output_cost_per_token": 1.98e-05, + "search_context_cost_per_query": {"search_context_size_high":0.0144,"search_context_size_low":0.0144,"search_context_size_medium":0.0144}, + "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-54.html", + "supports_web_search": true }, "bedrock_mantle/us-gov-west-1/xai.grok-4.3": { "use_openai_responses_path": true, @@ -68716,20 +69967,36 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true, - "source": "https://aws.amazon.com/bedrock/pricing/", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "input_cost_per_token": 1.5e-06, "output_cost_per_token": 3e-06, - "cache_read_input_token_cost": 2.4e-07 + "cache_read_input_token_cost": 2.4e-07, + "cache_read_input_token_cost_batches": 1.2e-07, + "cache_read_input_token_cost_flex": 1.2e-07, + "cache_read_input_token_cost_priority": 4.2e-07, + "input_cost_per_token_batches": 7.5e-07, + "input_cost_per_token_flex": 7.5e-07, + "input_cost_per_token_priority": 2.625e-06, + "output_cost_per_token_batches": 1.5e-06, + "output_cost_per_token_flex": 1.5e-06, + "output_cost_per_token_priority": 5.25e-06 }, "bedrock_mantle/us-gov-west-1/xai.grok-4.6": { "use_openai_responses_path": true, "input_cost_per_token": 2.64e-06, "output_cost_per_token": 7.92e-06, "cache_read_input_token_cost": 6.6e-07, + "cache_read_input_token_cost_flex": 3.3e-07, + "cache_read_input_token_cost_priority": 1.155e-06, + "input_cost_per_token_flex": 1.32e-06, + "input_cost_per_token_priority": 4.62e-06, "litellm_provider": "bedrock_mantle", "max_input_tokens": 500000, "max_output_tokens": 500000, "mode": "chat", + "output_cost_per_token_flex": 3.96e-06, + "output_cost_per_token_priority": 1.386e-05, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -68743,11 +70010,17 @@ }, "bedrock_mantle/us-gov-west-1/google.gemma-4-e2b": { "input_cost_per_token": 4.8e-08, + "input_cost_per_token_flex": 2.4e-08, + "input_cost_per_token_priority": 8.4e-08, "output_cost_per_token": 9.6e-08, "litellm_provider": "bedrock_mantle", "max_input_tokens": 128000, "max_output_tokens": 128000, "mode": "chat", + "output_cost_per_token_batches": 4.8e-08, + "output_cost_per_token_flex": 4.8e-08, + "output_cost_per_token_priority": 1.68e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -68761,11 +70034,18 @@ }, "bedrock_mantle/us-gov-west-1/google.gemma-4-26b-a4b": { "input_cost_per_token": 1.56e-07, + "input_cost_per_token_batches": 7.8e-08, + "input_cost_per_token_flex": 7.8e-08, + "input_cost_per_token_priority": 2.73e-07, "output_cost_per_token": 4.8e-07, "litellm_provider": "bedrock_mantle", "max_input_tokens": 256000, "max_output_tokens": 256000, "mode": "chat", + "output_cost_per_token_batches": 2.4e-07, + "output_cost_per_token_flex": 2.4e-07, + "output_cost_per_token_priority": 8.4e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -68779,11 +70059,18 @@ }, "bedrock_mantle/us-gov-west-1/google.gemma-4-31b": { "input_cost_per_token": 1.68e-07, + "input_cost_per_token_batches": 8.4e-08, + "input_cost_per_token_flex": 8.4e-08, + "input_cost_per_token_priority": 2.94e-07, "output_cost_per_token": 4.8e-07, "litellm_provider": "bedrock_mantle", "max_input_tokens": 256000, "max_output_tokens": 256000, "mode": "chat", + "output_cost_per_token_batches": 2.4e-07, + "output_cost_per_token_flex": 2.4e-07, + "output_cost_per_token_priority": 8.4e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "use_openai_responses_path": true, "supported_endpoints": [ "/v1/chat/completions", @@ -68798,12 +70085,18 @@ "bedrock_mantle/us-gov-west-1/openai.gpt-oss-20b": { "supports_vision": false, "input_cost_per_token": 8.4e-08, + "input_cost_per_token_batches": 4.2e-08, + "input_cost_per_token_flex": 4.2e-08, + "input_cost_per_token_priority": 1.47e-07, "output_cost_per_token": 3.6e-07, "litellm_provider": "bedrock_mantle", "max_input_tokens": 131072, "max_output_tokens": 16384, "mode": "chat", - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-20b.html", + "output_cost_per_token_batches": 1.8e-07, + "output_cost_per_token_flex": 1.8e-07, + "output_cost_per_token_priority": 6.3e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -68817,12 +70110,18 @@ "bedrock_mantle/us-gov-west-1/openai.gpt-oss-120b": { "supports_vision": false, "input_cost_per_token": 1.8e-07, + "input_cost_per_token_batches": 9e-08, + "input_cost_per_token_flex": 9e-08, + "input_cost_per_token_priority": 3.15e-07, "output_cost_per_token": 7.2e-07, "litellm_provider": "bedrock_mantle", "max_input_tokens": 131072, "max_output_tokens": 16384, "mode": "chat", - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-120b.html", + "output_cost_per_token_batches": 3.6e-07, + "output_cost_per_token_flex": 3.6e-07, + "output_cost_per_token_priority": 1.26e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -68939,10 +70238,17 @@ "input_cost_per_token": 2.64e-06, "output_cost_per_token": 7.92e-06, "cache_read_input_token_cost": 6.6e-07, + "cache_read_input_token_cost_flex": 3.3e-07, + "cache_read_input_token_cost_priority": 1.155e-06, + "input_cost_per_token_flex": 1.32e-06, + "input_cost_per_token_priority": 4.62e-06, "litellm_provider": "bedrock_mantle", "max_input_tokens": 500000, "max_output_tokens": 500000, "mode": "chat", + "output_cost_per_token_flex": 3.96e-06, + "output_cost_per_token_priority": 1.386e-05, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -68957,12 +70263,18 @@ "bedrock_mantle/us-gov-east-1/openai.gpt-oss-20b": { "supports_vision": false, "input_cost_per_token": 8.4e-08, + "input_cost_per_token_batches": 4.2e-08, + "input_cost_per_token_flex": 4.2e-08, + "input_cost_per_token_priority": 1.47e-07, "output_cost_per_token": 3.6e-07, "litellm_provider": "bedrock_mantle", "max_input_tokens": 131072, "max_output_tokens": 16384, "mode": "chat", - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-20b.html", + "output_cost_per_token_batches": 1.8e-07, + "output_cost_per_token_flex": 1.8e-07, + "output_cost_per_token_priority": 6.3e-07, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -68976,12 +70288,18 @@ "bedrock_mantle/us-gov-east-1/openai.gpt-oss-120b": { "supports_vision": false, "input_cost_per_token": 1.8e-07, + "input_cost_per_token_batches": 9e-08, + "input_cost_per_token_flex": 9e-08, + "input_cost_per_token_priority": 3.15e-07, "output_cost_per_token": 7.2e-07, "litellm_provider": "bedrock_mantle", "max_input_tokens": 131072, "max_output_tokens": 16384, "mode": "chat", - "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-oss-120b.html", + "output_cost_per_token_batches": 3.6e-07, + "output_cost_per_token_flex": 3.6e-07, + "output_cost_per_token_priority": 1.26e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-east-1/index.json", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -68994,6 +70312,7 @@ }, "bedrock_mantle/deepseek.v3.1": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 5.8e-07, "input_cost_per_token_batches": 2.9e-07, "input_cost_per_token_flex": 2.9e-07, @@ -69015,6 +70334,7 @@ }, "bedrock_mantle/moonshotai.kimi-k2-thinking": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 6e-07, "input_cost_per_token_batches": 3e-07, "input_cost_per_token_flex": 3e-07, @@ -69079,6 +70399,7 @@ }, "bedrock_mantle/qwen.qwen3-coder-30b-a3b-instruct": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", "input_cost_per_token": 1.5e-07, "input_cost_per_token_batches": 7.5e-08, "input_cost_per_token_flex": 7.5e-08, @@ -69100,6 +70421,7 @@ }, "bedrock_mantle/qwen.qwen3-coder-480b-a35b-instruct": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-qwen-qwen3-coder-480b-a35b-instruct.html", "input_cost_per_token": 4.5e-07, "input_cost_per_token_batches": 2.25e-07, "input_cost_per_token_flex": 2.25e-07, @@ -69550,6 +70872,14 @@ "cache_read_input_token_cost": 3e-08, "source": "https://docs.perplexity.ai/docs/agent-api/models" }, + "perplexity/google/gemini-4-argon": { + "litellm_provider": "perplexity", + "mode": "responses", + "input_cost_per_token": 2e-06, + "output_cost_per_token": 1e-05, + "cache_read_input_token_cost": 1e-07, + "source": "https://docs.perplexity.ai/docs/agent-api/models" + }, "perplexity/google/gemini-3.6-flash": { "litellm_provider": "perplexity", "mode": "responses", @@ -69677,6 +71007,14 @@ "cache_read_input_token_cost": 1.15e-09, "source": "https://docs.perplexity.ai/docs/agent-api/models" }, + "perplexity/perplexity/nemotron-3.5-super-120b-a12b": { + "litellm_provider": "perplexity", + "mode": "responses", + "input_cost_per_token": 2e-07, + "output_cost_per_token": 5e-07, + "cache_read_input_token_cost": 4e-08, + "source": "https://docs.perplexity.ai/docs/agent-api/models" + }, "perplexity/perplexity/nemotron-3-ultra-550b-a55b": { "litellm_provider": "perplexity", "mode": "responses", @@ -69802,12 +71140,12 @@ "input_cost_per_token": 1.5e-06, "litellm_provider": "vertex_ai", "max_output_tokens": 57920, - "max_input_tokens": 57920, + "max_input_tokens": 131072, "mode": "chat", "output_cost_per_reasoning_token": 9e-06, "output_cost_per_token": 9e-06, "output_cost_per_video_token": 1.75e-05, - "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", + "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/omni-1-1-flash", "supported_endpoints": [ "/v1beta/interactions" ], @@ -69838,6 +71176,7 @@ "litellm_provider": "openai", "mode": "chat", "output_cost_per_token": 7.5e-05, + "fedramp_uplift_multiplier": 1.1, "source": "https://developers.openai.com/api/docs/pricing", "supports_reasoning": true }, @@ -69847,6 +71186,7 @@ "litellm_provider": "openai", "mode": "chat", "output_cost_per_token": 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"cache_read_input_token_cost_priority": 3.85e-07, @@ -70522,6 +71761,8 @@ }, "azure/eu/gpt-5.2-codex": { "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.3-codex", "cache_read_input_token_cost": 1.925e-07, "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", @@ -70545,6 +71786,7 @@ }, "azure/eu/gpt-5.3-codex": { "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.925e-07, "cache_read_input_token_cost_priority": 3.85e-07, "input_cost_per_token": 1.925e-06, @@ -70562,6 +71804,7 @@ }, "azure/eu/gpt-5.4-mini": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 8.25e-08, "cache_read_input_token_cost_batches": 4.125e-08, "cache_read_input_token_cost_priority": 1.65e-07, @@ -70582,6 +71825,7 @@ }, "azure/eu/gpt-5.4-nano": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.2e-08, "cache_read_input_token_cost_batches": 1.1e-08, "input_cost_per_token": 2.2e-07, @@ -70599,6 +71843,7 @@ }, "azure/eu/gpt-5.4-pro": { "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 3.3e-05, "input_cost_per_token_above_272k_tokens": 6.6e-05, "input_cost_per_token_above_272k_tokens_batches": 3.3e-05, @@ -70772,6 +72017,7 @@ }, "azure/eu/o3": { "deprecation_date": "2026-11-19", + "successor_model": "azure/eu/gpt-5.6-sol", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 2.2e-06, "input_cost_per_token_batches": 1.1e-06, @@ -70790,6 +72036,7 @@ }, "azure/eu/o3-2025-04-16": { "deprecation_date": "2026-11-19", + "successor_model": "azure/eu/gpt-5.6-sol", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 2.2e-06, "input_cost_per_token_batches": 1.1e-06, @@ -70808,6 +72055,8 @@ }, "azure/eu/o3-deep-research": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6-sol", "cache_read_input_token_cost": 2.75e-06, "input_cost_per_token": 1.1e-05, "litellm_provider": "azure", @@ -70817,6 +72066,8 @@ }, "azure/eu/o4-mini": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6-terra", "cache_read_input_token_cost": 3.03e-07, "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, @@ -70835,6 +72086,8 @@ }, "azure/eu/o4-mini-2025-04-16": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/eu/gpt-5.6-terra", "cache_read_input_token_cost": 3.03e-07, "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, @@ -70853,6 +72106,7 @@ }, "azure/eu/text-embedding-3-large": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.43e-07, "litellm_provider": "azure", "mode": "embedding", @@ -70860,6 +72114,7 @@ }, "azure/eu/text-embedding-3-small": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.2e-08, "litellm_provider": "azure", "mode": "embedding", @@ -70867,6 +72122,7 @@ }, "azure/eu/text-embedding-ada-002": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.1e-07, "litellm_provider": "azure", "mode": "embedding", @@ -70916,6 +72172,7 @@ }, "azure/us/codex-mini": { "deprecation_date": "2026-11-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 4.13e-07, "input_cost_per_token": 1.65e-06, "litellm_provider": "azure", @@ -70932,6 +72189,8 @@ }, "azure/us/gpt-4.1": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_read_input_token_cost": 5.5e-07, "cache_read_input_token_cost_priority": 9.63e-07, "input_cost_per_token": 2.2e-06, @@ -70951,6 +72210,8 @@ }, "azure/us/gpt-4.1-mini": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-mini", "cache_read_input_token_cost": 1.1e-07, "cache_read_input_token_cost_priority": 1.93e-07, "input_cost_per_token": 4.4e-07, @@ -70970,6 +72231,8 @@ }, "azure/us/gpt-4.1-nano": { "deprecation_date": "2027-04-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-nano", "cache_read_input_token_cost": 2.8e-08, "input_cost_per_token": 1.1e-07, "input_cost_per_token_batches": 5.5e-08, @@ -70980,7 +72243,9 @@ "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-4o-2024-05-13": { - "deprecation_date": "2026-12-09", + "deprecation_date": "2027-01-14", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "input_cost_per_token": 5.5e-06, "input_cost_per_token_batches": 2.75e-06, "litellm_provider": "azure", @@ -70993,6 +72258,8 @@ }, "azure/us/gpt-5": { "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1", "cache_read_input_token_cost": 1.375e-07, "cache_read_input_token_cost_batches": 6.875e-08, "cache_read_input_token_cost_priority": 2.75e-07, @@ -71013,6 +72280,8 @@ }, "azure/us/gpt-5-codex": { "deprecation_date": "2027-03-17", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.1-codex", "cache_read_input_token_cost": 1.38e-07, "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", @@ -71021,7 +72290,9 @@ "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'" }, "azure/us/gpt-5-mini": { - "deprecation_date": "2027-02-09", + "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-mini", "cache_read_input_token_cost": 2.75e-08, "cache_read_input_token_cost_batches": 1.375e-08, "cache_read_input_token_cost_priority": 4.95e-08, @@ -71042,6 +72313,8 @@ }, "azure/us/gpt-5-nano": { "deprecation_date": "2027-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4-nano", "cache_read_input_token_cost": 5.5e-09, "cache_read_input_token_cost_batches": 2.75e-09, "input_cost_per_token": 5.5e-08, @@ -71059,6 +72332,8 @@ }, "azure/us/gpt-5-pro": { "deprecation_date": "2027-04-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.2-pro", "input_cost_per_token": 1.65e-05, "input_cost_per_token_batches": 8.25e-06, "litellm_provider": "azure", @@ -71074,6 +72349,7 @@ }, "azure/us/gpt-5.1-codex-max": { "deprecation_date": "2027-05-18", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.375e-07, "input_cost_per_token": 1.375e-06, "litellm_provider": "azure", @@ -71083,6 +72359,8 @@ }, "azure/us/gpt-5.2": { "deprecation_date": "2027-06-08", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.4", "cache_read_input_token_cost": 1.925e-07, "cache_read_input_token_cost_batches": 9.625e-08, "cache_read_input_token_cost_priority": 3.85e-07, @@ -71103,6 +72381,8 @@ }, "azure/us/gpt-5.2-codex": { "deprecation_date": "2027-07-13", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.3-codex", "cache_read_input_token_cost": 1.925e-07, "input_cost_per_token": 1.925e-06, "litellm_provider": "azure", @@ -71126,6 +72406,7 @@ }, "azure/us/gpt-5.3-codex": { "deprecation_date": "2027-08-24", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 1.925e-07, "cache_read_input_token_cost_priority": 3.85e-07, "input_cost_per_token": 1.925e-06, @@ -71143,6 +72424,7 @@ }, "azure/us/gpt-5.4-mini": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 8.25e-08, "cache_read_input_token_cost_batches": 4.125e-08, "cache_read_input_token_cost_priority": 1.65e-07, @@ -71163,6 +72445,7 @@ }, "azure/us/gpt-5.4-nano": { "deprecation_date": "2027-09-21", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "cache_read_input_token_cost": 2.2e-08, "cache_read_input_token_cost_batches": 1.1e-08, "input_cost_per_token": 2.2e-07, @@ -71180,6 +72463,7 @@ }, "azure/us/gpt-5.4-pro": { "deprecation_date": "2027-09-07", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 3.3e-05, "input_cost_per_token_above_272k_tokens": 6.6e-05, "input_cost_per_token_above_272k_tokens_batches": 3.3e-05, @@ -71209,6 +72493,8 @@ }, "azure/us/o3-deep-research": { "deprecation_date": "2026-11-19", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/us/gpt-5.6-sol", "cache_read_input_token_cost": 2.75e-06, "input_cost_per_token": 1.1e-05, "litellm_provider": "azure", @@ -71218,6 +72504,7 @@ }, "azure/us/text-embedding-3-large": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.43e-07, "litellm_provider": "azure", "mode": "embedding", @@ -71225,6 +72512,7 @@ }, "azure/us/text-embedding-3-small": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 2.2e-08, "litellm_provider": "azure", "mode": "embedding", @@ -71232,6 +72520,7 @@ }, "azure/us/text-embedding-ada-002": { "deprecation_date": "2028-02-09", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.1e-07, "litellm_provider": "azure", "mode": "embedding", @@ -71242,6 +72531,8 @@ "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-01-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", + "successor_model": "azure/gpt-realtime-2.1", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, "input_cost_per_token": 4e-06, @@ -71251,6 +72542,9 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 2.4e-05, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/realtime" @@ -71308,7 +72602,11 @@ "supported_output_modalities": [ "text" ], - "supports_audio_input": true + "supports_audio_input": true, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "supports_native_streaming": true }, "azure/gpt-transcribe": { "deprecation_date": "2028-02-01", @@ -71318,7 +72616,8 @@ "source": "https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20'Foundry%20Models'%20and%20armRegionName%20eq%20'eastus'%20and%20priceType%20eq%20'Consumption'", "supported_endpoints": [ "/v1/audio/transcriptions", - "/v1/realtime/transcription_sessions" + "/v1/realtime/transcription_sessions", + "/v1/realtime" ], "supported_modalities": [ "text", @@ -71327,7 +72626,13 @@ "supported_output_modalities": [ "text" ], - "supports_audio_input": true + "supports_audio_input": true, + "provider_specific_entry": { + "realtime_ga_only": 1, + "transcription_json_or_text_only": 1, + "transcription_usage_duration": 1 + }, + "supports_native_streaming": true }, "azure/gpt-realtime-translate": { "deprecation_date": "2027-11-09", @@ -71345,7 +72650,11 @@ "audio" ], "supports_audio_input": true, - "supports_audio_output": true + "supports_audio_output": true, + "provider_specific_entry": { + "realtime_ga_only": 1 + }, + "supports_native_streaming": true }, "aihubmix/agnes-2.5-flash": { "input_cost_per_token": 3e-08, @@ -72784,7 +74093,8 @@ "max_input_tokens": 65536, "mode": "evaluation", "output_cost_per_token": 0.0, - "source": "https://docs.typesafe.ai/models" + "source": "https://docs.typesafe.ai/models", + "supports_box_questions": true }, "typesafe/jev-preview": { "input_cost_per_token": 4.2e-08, @@ -73643,6 +74953,7 @@ "cache_read_input_token_cost": 2e-07, "cache_read_input_token_cost_above_200k_tokens": 4e-07, "deprecation_date": "2026-05-15", + "deprecation_source": "https://docs.x.ai/developers/migration/may-15-retirement", "input_cost_per_image_token": 1e-06, "input_cost_per_token": 1e-06, "input_cost_per_token_above_200k_tokens": 2e-06, @@ -73653,6 +74964,7 @@ "output_cost_per_token": 2e-06, "output_cost_per_token_above_200k_tokens": 4e-06, "source": "https://api.x.ai/v1/language-models", + "successor_model": "xai/grok-build-0.1", "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, @@ -73734,6 +75046,7 @@ "output_cost_per_token_priority": 1.875e-05, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -73741,6 +75054,8 @@ }, "vertex_ai/gemini-2.0-flash": { "deprecation_date": "2026-06-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.5-flash-lite", "input_cost_per_audio_token": 1e-06, "input_cost_per_audio_token_batches": 5e-07, "input_cost_per_character": 3.75e-08, @@ -73754,6 +75069,8 @@ }, "vertex_ai/gemini-2.0-flash-lite": { "deprecation_date": "2026-06-01", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/gemini-3.5-flash-lite", "input_cost_per_audio_token": 7.5e-08, "input_cost_per_audio_token_batches": 3.75e-08, "input_cost_per_character": 1.875e-08, @@ -73805,6 +75122,8 @@ }, "vertex_ai/veo-3.0-generate-001": { "deprecation_date": "2026-06-30", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/veo-3.1-generate-001", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "mode": "video_generation", @@ -73820,6 +75139,8 @@ }, "vertex_ai/veo-3.0-fast-generate-001": { "deprecation_date": "2026-06-30", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/veo-3.1-fast-generate-001", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "mode": "video_generation", @@ -73836,6 +75157,8 @@ }, "vertex_ai/veo-2.0-generate-001": { "deprecation_date": "2026-06-30", + "deprecation_source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions", + "successor_model": "vertex_ai/veo-3.1-generate-001", "litellm_provider": "vertex_ai-video-models", "max_input_tokens": 1024, "mode": "video_generation", @@ -74156,6 +75479,7 @@ "apac.anthropic.claude-opus-5": { "bedrock_converse_supports_strict_tools": false, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "litellm_provider": "bedrock_converse", "supports_tool_search": true, @@ -74183,12 +75507,14 @@ "input_cost_per_token": 5.5e-06, "cache_read_input_token_cost": 5.5e-07, "output_cost_per_token": 2.75e-05, - "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/index.json", + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/ap-northeast-1/index.json", "token_count_model": { "model": "anthropic.claude-opus-5", "litellm_provider": "bedrock_mantle", "region": "ap-southeast-4" - } + }, + "input_cost_per_token_batches": 2.75e-06, + "output_cost_per_token_batches": 1.375e-05 }, "apac.anthropic.claude-opus-5-5": { "bedrock_converse_supports_strict_tools": false, @@ -74270,6 +75596,7 @@ "max_output_tokens": 128000, "mode": "chat", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -74360,6 +75687,7 @@ }, "deepseek.r1-v1:0": { "deprecation_date": "2027-03-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-deepseek-deepseek-r1.html", "input_cost_per_token": 1.35e-06, "litellm_provider": "bedrock_converse", "max_input_tokens": 128000, @@ -74794,7 +76122,7 @@ "supports_function_calling": true, "input_cost_per_token": 2e-06, "output_cost_per_token": 1e-05, - "cache_read_input_token_cost": 2e-07, + "cache_read_input_token_cost": 1e-07, "source": "https://docs.perplexity.ai/docs/agent-api/models" }, "perplexity/anthropic/claude-fable-5-1": { @@ -74842,6 +76170,9 @@ "output_cost_per_token": 5e-05, "cache_read_input_token_cost": 1e-06, "cache_creation_input_token_cost": 1.25e-05, + "input_cost_per_token_above_272k_tokens": 2e-05, + "output_cost_per_token_above_272k_tokens": 7.5e-05, + "cache_read_input_token_cost_above_272k_tokens": 2e-06, "source": "https://docs.perplexity.ai/docs/agent-api/models" }, "perplexity/openai/gpt-6-luna": { @@ -75224,6 +76555,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": { "search_context_size_high": 0.01, "search_context_size_low": 0.01, @@ -75328,6 +76660,7 @@ "output_cost_per_token_above_272k_tokens": 1.65e-05, "output_cost_per_token_above_272k_tokens_ultrafast": 9.9e-05, "output_cost_per_token_ultrafast": 6.6e-05, + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-1-sol.html", "supported_endpoints": [ "/v1/chat/completions", @@ -75350,6 +76683,7 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true, + "supports_web_search": true, "supports_xhigh_reasoning_effort": true, "use_openai_responses_path": true }, @@ -75446,6 +76780,8 @@ }, "azure_ai/kimi-k2-thinking": { "deprecation_date": "2026-03-29", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/retired-models", + "successor_model": "azure_ai/kimi-k2.5", "input_cost_per_token": 6e-07, "litellm_provider": "azure_ai", "max_input_tokens": 262144, @@ -75547,6 +76883,7 @@ "azure/model-router": { "comment": "The flat $0.14 per M input tokens is the router's own fee, the routed model is priced on top of it", "deprecation_date": "2027-05-20", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_token": 1.4e-07, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -75558,6 +76895,7 @@ }, "azure/whisper": { "deprecation_date": "2026-12-15", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/openai/concepts/model-retirement-schedule", "input_cost_per_second": 0.0001, "litellm_provider": "azure", "mode": "audio_transcription", @@ -75619,6 +76957,7 @@ "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, "output_cost_per_image_token_batches": 1.5e-05, + "output_cost_per_image_token_priority": 5.4e-05, "output_cost_per_token": 7.5e-06, "output_cost_per_token_batches": 3.75e-06, "output_cost_per_token_priority": 1.35e-05, @@ -75665,6 +77004,7 @@ "output_cost_per_image": 0.0336, "output_cost_per_image_token": 3e-05, "output_cost_per_image_token_batches": 1.5e-05, + "output_cost_per_image_token_priority": 5.4e-05, "output_cost_per_token": 7.5e-06, "output_cost_per_token_batches": 3.75e-06, "output_cost_per_token_priority": 1.35e-05, @@ -75774,6 +77114,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -75826,6 +77167,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -75870,6 +77212,7 @@ "thinking_always_on": false, "prompt_cache_min_tokens": 512, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -75917,6 +77260,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -75953,6 +77297,7 @@ "max_output_tokens": 128000, "mode": "chat", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76009,6 +77354,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76055,6 +77401,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76095,6 +77442,7 @@ "prompt_cache_min_tokens": 512, "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/index.json", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76136,6 +77484,7 @@ "prompt_cache_min_tokens": 512, "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/index.json", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76182,6 +77531,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76233,6 +77583,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76279,6 +77630,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76311,6 +77663,9 @@ "input_cost_per_token": 1e-07, "output_cost_per_token": 5e-07, "cache_read_input_token_cost": 1e-08, + "input_cost_per_token_above_100k_tokens": 5e-07, + "output_cost_per_token_above_100k_tokens": 2.5e-06, + "cache_read_input_token_cost_above_100k_tokens": 5e-08, "source": "https://docs.perplexity.ai/docs/agent-api/models" }, "us-gov.anthropic.claude-haiku-5-5": { @@ -76336,6 +77691,7 @@ "prompt_cache_min_tokens": 512, "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/index.json", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76387,6 +77743,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -76437,6 +77794,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76481,6 +77839,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_assistant_prefill": false, "supports_computer_use": true, "supports_function_calling": true, @@ -76645,23 +78004,19 @@ }, "vertex_ai/gemini-robotics-er-2-preview": { "cache_read_input_token_cost": 1e-07, - "cache_read_input_token_cost_batches": 5e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 1e-06, - "input_cost_per_token_batches": 5e-07, "litellm_provider": "vertex_ai", "max_input_tokens": 131072, "max_output_tokens": 65536, "mode": "chat", "output_cost_per_reasoning_token": 5e-06, "output_cost_per_token": 5e-06, - "output_cost_per_token_batches": 2.5e-06, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", - "/v1/completions", - "/v1/batch" + "/v1/completions" ], "supported_modalities": [ "text", @@ -76691,23 +78046,19 @@ }, "gemini-robotics-er-2-preview": { "cache_read_input_token_cost": 1e-07, - "cache_read_input_token_cost_batches": 5e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 1e-06, - "input_cost_per_token_batches": 5e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 131072, "max_output_tokens": 65536, "mode": "chat", "output_cost_per_reasoning_token": 5e-06, "output_cost_per_token": 5e-06, - "output_cost_per_token_batches": 2.5e-06, "search_context_cost_per_query": {"search_context_size_low":0.014,"search_context_size_medium":0.014,"search_context_size_high":0.014}, "source": "https://ai.google.dev/gemini-api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", - "/v1/completions", - "/v1/batch" + "/v1/completions" ], "supported_modalities": [ "text", @@ -76774,6 +78125,7 @@ "supports_audio_input": true, "supports_audio_output": false, "supports_computer_use": true, + "supports_continuation": true, "supports_function_calling": true, "supports_minimal_reasoning_effort": false, "supports_native_streaming": true, @@ -76833,6 +78185,7 @@ ], "supports_audio_input": true, "supports_computer_use": true, + "supports_continuation": true, "supports_function_calling": true, "supports_minimal_reasoning_effort": false, "supports_native_streaming": true, @@ -76890,6 +78243,7 @@ "text" ], "supports_audio_input": true, + "supports_continuation": true, "supports_function_calling": true, "supports_minimal_reasoning_effort": false, "supports_native_streaming": true, @@ -77004,6 +78358,7 @@ "litellm_provider": "xai", "mode": "realtime", "source": "https://docs.x.ai/developers/pricing", + "successor_model": "xai/grok-voice-3.0", "supported_endpoints": [ "/v1/realtime" ], @@ -77087,6 +78442,7 @@ "cache_creation_input_token_cost_above_1hr": 1.6e-05, "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-10-01", + "deprecation_source": "https://learn.microsoft.com/en-us/azure/foundry/concepts/model-lifecycle-retirement", "input_cost_per_token": 8e-06, "litellm_provider": "azure_ai", "max_input_tokens": 1000000, @@ -77198,9 +78554,10 @@ "max_output_tokens": 1048576, "mode": "chat", "output_cost_per_token": 1e-06, - "source": "https://tokenfactory.nebius.com/models/catalog/text2text/reflection%2Fbeam", + "source": "https://tokenfactory.nebius.com/api/public/models_info", "supports_function_calling": true, - "supports_reasoning": true + "supports_reasoning": true, + "cache_read_input_token_cost": 5e-08 }, "baseten/deepseek-ai/DeepSeek-V4.1-Flash-1017": { "cache_read_input_token_cost": 7e-09, @@ -77247,6 +78604,7 @@ "output_cost_per_token_priority": 1.5e-06, "source": "https://api.fireworks.ai/v1/serverless/models?format=nested", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -77405,6 +78763,7 @@ "output_cost_per_token_priority": 9e-07, "source": "https://platform.minimax.io/docs/guides/pricing", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_reasoning": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -78240,6 +79599,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -78454,6 +79814,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -78529,6 +79890,8 @@ "cache_creation_input_token_cost_batches": 1.875e-06, "cache_read_input_token_cost_batches": 1.5e-07, "deprecation_date": "2026-11-30", + "deprecation_source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-lifecycle-legacy.html", + "successor_model": "bedrock/claude_platform/claude-sonnet-5-5", "input_cost_per_token_batches": 1.5e-06, "litellm_provider": "bedrock", "max_input_tokens": 200000, @@ -78618,6 +79981,7 @@ "search_context_size_medium": 0.01 }, "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_mid_conversation_system": true, "supports_assistant_prefill": false, "supports_computer_use": true, @@ -78741,6 +80105,7 @@ ], "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "fedramp_uplift_multiplier": 1.1, "search_context_cost_per_query": {"search_context_size_high":0.01,"search_context_size_low":0.01,"search_context_size_medium":0.01}, "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ @@ -79038,6 +80403,7 @@ "mode": "responses", "output_cost_per_token": 5.5e-06, "output_cost_per_token_above_272k_tokens": 8.25e-06, + "search_context_cost_per_query": {"search_context_size_high":0.012,"search_context_size_low":0.012,"search_context_size_medium":0.012}, "source": "https://docs.aws.amazon.com/bedrock/latest/userguide/model-card-openai-gpt-6-1-terra.html", "supported_endpoints": [ "/v1/chat/completions", @@ -79060,6 +80426,7 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true, + "supports_web_search": true, "supports_xhigh_reasoning_effort": true, "use_openai_responses_path": true }, @@ -80600,6 +81967,7 @@ "prompt_cache_min_tokens": 512.0, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_adaptive_thinking": true, + "thinking_on_by_default": true, "supports_anthropic_thinking_payload": true, "supports_assistant_prefill": false, "supports_function_calling": true, @@ -80644,6 +82012,7 @@ "cache_creation_input_token_cost": 3.0002e-07, "cache_read_input_token_cost": 3.003e-08, "deprecation_date": "2026-11-19", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/supported-models", "input_cost_per_token": 3.0002e-07, "input_dbu_cost_per_token": 4.286e-06, "litellm_provider": "databricks", @@ -80671,7 +82040,8 @@ "input_cost_per_token_priority": 5.25e-07, "output_cost_per_token_priority": 2.1e-06, "cache_read_input_token_cost_priority": 5.25e-08, - "cache_creation_input_token_cost_priority": 5.25e-07 + "cache_creation_input_token_cost_priority": 5.25e-07, + "successor_model": "databricks/databricks-deepseek-v4-1-flash-1017" }, "databricks/databricks-deepseek-v4-1-flash-1017": { "cache_creation_input_token_cost": 3.0002e-07, @@ -81123,6 +82493,8 @@ "databricks/databricks-kimi-k2-7": { "cache_creation_input_token_cost": 9.4997e-07, "cache_read_input_token_cost": 1.8998e-07, + "deprecation_date": "2026-10-30", + "deprecation_source": "https://docs.databricks.com/aws/en/machine-learning/retired-models-policy", "input_cost_per_token": 9.4997e-07, "input_dbu_cost_per_token": 1.3571e-05, "litellm_provider": "databricks", @@ -81135,6 +82507,7 @@ "output_cost_per_token": 4.00001e-06, "output_dbu_cost_per_token": 5.7143e-05, "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "successor_model": "databricks/databricks-kimi-k3", "supported_modalities": [ "text", "image" @@ -81180,6 +82553,7 @@ ], "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -81196,6 +82570,7 @@ "output_cost_per_token": 3.08e-06, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -81212,6 +82587,24 @@ "output_cost_per_token": 8.4e-07, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "fireworks_ai/accounts/fireworks/routers/deepseek-v4p1-flash-1017-ultrafast": { + "cache_read_input_token_cost": 4.8e-08, + "input_cost_per_token": 2.4e-06, + "litellm_provider": "fireworks_ai", + "max_input_tokens": 1048576, + "max_output_tokens": 393216, + "mode": "chat", + "output_cost_per_token": 9.6e-06, + "source": "https://docs.fireworks.ai/serverless/pricing.md", + "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -81228,6 +82621,7 @@ "output_cost_per_token": 8.4e-07, "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, + "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, "supports_response_schema": true, @@ -81311,17 +82705,17 @@ "supports_native_streaming": true 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"input_cost_per_token": 3e-07, + "litellm_provider": "bedrock", + "max_input_tokens": 195904, + "max_output_tokens": 4096, + "mode": "chat", + "output_cost_per_token": 1.5e-06, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrockFoundationModels/current/us-gov-west-1/index.json", + "successor_model": "bedrock/us-gov-west-1/anthropic.claude-haiku-4-5-20251001-v1:0", + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "bedrock_mantle/us-gov-west-1/xai.grok-4.7": { + "cache_read_input_token_cost": 6.6e-07, + "cache_read_input_token_cost_flex": 3.3e-07, + "cache_read_input_token_cost_priority": 1.155e-06, + "input_cost_per_token": 2.64e-06, + "input_cost_per_token_batches": 1.32e-06, + "input_cost_per_token_flex": 1.32e-06, + "input_cost_per_token_priority": 4.62e-06, + "litellm_provider": "bedrock_mantle", + "max_input_tokens": 524288, + "max_output_tokens": 524288, + "mode": "chat", + "output_cost_per_token": 7.92e-06, + "output_cost_per_token_batches": 3.96e-06, + "output_cost_per_token_flex": 3.96e-06, + "output_cost_per_token_priority": 1.386e-05, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-gov-west-1/index.json", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "use_openai_responses_path": true + }, + "bedrock_mantle/xai.grok-4.7": { + "cache_read_input_token_cost": 5.5e-07, + "cache_read_input_token_cost_flex": 2.75e-07, + "cache_read_input_token_cost_priority": 9.625e-07, + "input_cost_per_token": 2.2e-06, + "input_cost_per_token_batches": 1.1e-06, + "input_cost_per_token_flex": 1.1e-06, + "input_cost_per_token_priority": 3.85e-06, + "litellm_provider": "bedrock_mantle", + "max_input_tokens": 524288, + "max_output_tokens": 524288, + "mode": "chat", + "output_cost_per_token": 6.6e-06, + "output_cost_per_token_batches": 3.3e-06, + "output_cost_per_token_flex": 3.3e-06, + "output_cost_per_token_priority": 1.155e-05, + "source": "https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonBedrock/current/us-east-1/index.json", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true, + "supports_vision": true, + "use_openai_responses_path": true + }, + "together_ai/ricursive-ai/Ripple-65B-Preview": { + "cache_read_input_token_cost": 2e-08, + "input_cost_per_token": 2e-07, + "litellm_provider": "together_ai", + "max_input_tokens": 131072, + "max_output_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://api.together.ai/v1/models", + "supports_prompt_caching": true } } diff --git a/provider_endpoints_support.json b/provider_endpoints_support.json index 700a35edb06..00fee0a0d5a 100644 --- a/provider_endpoints_support.json +++ b/provider_endpoints_support.json @@ -3158,7 +3158,7 @@ "batches": false, "messages": false, "interactions": false, - "systemone": false, + "systemone": true, "a2a": false, "generateContent": false } @@ -5250,13 +5250,13 @@ "generateContent": false } }, - "empiriolabs": { - "display_name": "EmpirioLabs (`empiriolabs`)", - "url": "https://docs.litellm.ai/docs/providers/empiriolabs", + "wally": { + "display_name": "Wally (`wally`)", + "url": "https://docs.litellm.ai/docs/providers/wally", "endpoints": { - "chat_completions": false, - "responses": false, - "text_completion": false, + "chat_completions": true, + "responses": true, + "text_completion": true, "embeddings": false, "image_generations": false, "image_edits": false, @@ -5269,11 +5269,37 @@ "realtime": false, "video_generations": false, "batches": false, - "messages": false, - "interactions": false, + "messages": true, + "interactions": true, "systemone": false, - "a2a": false, - "generateContent": false + "a2a": true, + "generateContent": true + } + }, + "empiriolabs": { + "display_name": "EmpirioLabs AI (`empiriolabs`)", + "url": "https://docs.litellm.ai/docs/providers/empiriolabs", + "endpoints": { + "chat_completions": true, + "responses": true, + "text_completion": true, + "embeddings": true, + "image_generations": false, + "image_edits": false, + "audio_transcriptions": false, + "audio_speech": false, + "rerank": false, + "ocr": false, + "search": false, + "moderations": false, + "realtime": false, + "video_generations": false, + "batches": false, + "messages": true, + "interactions": true, + "systemone": false, + "a2a": true, + "generateContent": true } }, "openinfer": { diff --git a/pyproject.toml b/pyproject.toml index 5c23a64ebb3..ee6cb6c1dcc 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -26,7 +26,7 @@ dependencies = [ "tiktoken>=0.12.0,<1.0; python_version == '3.14'", "tiktoken>=0.14.0,<1.0; python_version >= '3.15'", "tokenizers>=0.21.0,<1.0", - "huggingface-hub>=0.34.0,<2.0", + "huggingface-hub>=0.34.0,<3.0", "click>=8.0.0,<9.0", "jinja2>=3.1.6,<4.0", "aiohttp>=3.14.2,<4.0", @@ -95,6 +95,7 @@ proxy = [ "pyroscope-io>=0.8.16,<1.0; sys_platform != 'win32'", "expression>=5.6.0,<6.0", "backports-zstd>=1.0.0,<2.0; python_version < '3.14'", + "semver>=3.0.4,<4", ] # Thin client install for the `lite` CLI on developer laptops. The CLI's heavy # imports are all guarded, so it runs on the base SDK plus these packages, and @@ -155,7 +156,8 @@ stt-vertex-chirp = [ stt-nvidia-riva = [ # NVIDIA Riva STT provider (gRPC). These are imported lazily inside the # provider handler so litellm core remains usable without them. - "nvidia-riva-client>=2.15.0", + "grpcio>=1.67.1,<2.0", + "protobuf>=5.26.1,<7.0", "soundfile>=0.12.1", "audioread>=3.0.1", "numpy>=1.26.0", @@ -241,6 +243,7 @@ dev = [ "pytest-timeout==2.4.0", "vcrpy==8.2.1", "pytest-recording==0.13.4", + "nvidia-riva-client==2.16.0", ] e2e-dev = [ "playwright==1.61.0", @@ -266,6 +269,8 @@ proxy-dev = [ "azure-identity==1.25.2", "a2a-sdk==1.1.0", "backports-zstd==1.8.0; python_version < '3.14'", + "httptools>=0.7.1,<0.8", + "semver>=3.0.4,<4", ] ci = [ "psutil==7.2.2", @@ -274,6 +279,9 @@ ci = [ # protobuf, Pillow is a compiled C extension). "tenacity==8.5.0", "google-generativeai==0.8.6", + # The Riva tests serve NVIDIA's own message definitions, which checks + # LiteLLM's hand-written copy of them on every run. + "nvidia-riva-client==2.16.0", "Pillow==12.3.0; python_version == '3.10'", "Pillow==13.0.0; python_version >= '3.11'", # Azure batch E2E tests still import psycopg2 directly. diff --git a/schema.prisma b/schema.prisma index 179b741fe7c..818f2dc4858 100644 --- a/schema.prisma +++ b/schema.prisma @@ -1615,9 +1615,77 @@ model LiteLLM_ClaudeCodePluginTable { updated_at DateTime? @default(now()) @updatedAt created_by String? + uploaded_archive LiteLLM_ClaudeCodePluginUpload? + versions LiteLLM_ClaudeCodePluginVersion[] + downloads LiteLLM_ClaudeCodePluginDownload[] + anonymous_download_count BigInt @default(0) + @@map("LiteLLM_ClaudeCodePluginTable") } +model LiteLLM_ClaudeCodePluginVersion { + id String @id @default(uuid()) + plugin_id String + version String? + description String? + manifest_json String? + published_at DateTime? + published_by String? + archive_available Boolean @default(false) + content Bytes? + plugin LiteLLM_ClaudeCodePluginTable @relation(fields: [plugin_id], references: [id], onDelete: Cascade, onUpdate: Cascade) + + @@unique([plugin_id, version]) + @@index([plugin_id, published_at]) +} + + +model LiteLLM_SkillSubmission { + id String @id @default(uuid()) + plugin_name String + operation String + status String @default("pending_review") + proposal_json String + archive_content Bytes? + submitted_by String + created_at DateTime @default(now()) + base_plugin_id String? + base_updated_at DateTime? + reviewed_by String? + reviewed_at DateTime? + rejection_reason String? + scan_json String? + + @@index([submitted_by, created_at(sort: Desc), id(sort: Desc)]) + @@index([submitted_by, status, created_at(sort: Desc), id(sort: Desc)]) + @@index([status, created_at(sort: Desc), id(sort: Desc)]) + @@index([created_at(sort: Desc), id(sort: Desc)]) +} + +model LiteLLM_ClaudeCodePluginDownload { + id BigInt @id @default(autoincrement()) + plugin_id String + downloaded_at DateTime @default(now()) + version String? + digest String + authenticated Boolean + user_id String? + user_email String? + key_alias String? + team_id String? + team_alias String? + plugin LiteLLM_ClaudeCodePluginTable @relation(fields: [plugin_id], references: [id], onDelete: Cascade, onUpdate: Cascade) + + @@index([plugin_id, id]) +} + +model LiteLLM_ClaudeCodePluginUpload { + plugin_name String @id + content Bytes + plugin LiteLLM_ClaudeCodePluginTable @relation(fields: [plugin_name], references: [name], onDelete: Cascade, onUpdate: Cascade) +} + + // User/team-scoped memory store with a GLOBAL unique key. // `value` is a string (typically markdown/text meant for LLM context); // `metadata` is an optional JSON envelope for structured tags without schema changes. @@ -2062,74 +2130,27 @@ model LiteLLM_TelemetryReport { @@index([created_at]) } -enum AccountingEventKind { - inbound_usage - outbound_usage - cost -} - enum AccountingDeliveryState { pending applied parked } -enum AccountingDeliveryTarget { - LiteLLM_VerificationToken - LiteLLM_UserTable - LiteLLM_TeamTable - LiteLLM_TeamMembership - LiteLLM_OrganizationTable - LiteLLM_OrganizationMembership - LiteLLM_EndUserTable - LiteLLM_AgentsTable - LiteLLM_TagTable - LiteLLM_ProjectTable - LiteLLM_ModelAccessGroupBudgetTable - LiteLLM_BudgetTable - LiteLLM_BudgetWindowSpend - LiteLLM_DailyUserSpend - LiteLLM_DailyTeamSpend - LiteLLM_DailyOrganizationSpend - LiteLLM_DailyEndUserSpend - LiteLLM_DailyAgentSpend - LiteLLM_DailyTagSpend - LiteLLM_DailyModelUsage - LiteLLM_DailyToolSpend - LiteLLM_AutoRouterDailySpend -} +model LiteLLM_SpendLogDelivery { + delivery_id String @id @default(dbgenerated("(gen_random_uuid())::text")) + request_id String + state AccountingDeliveryState @default(pending) + accounting_payload Json + is_batch Boolean + attempts Int @default(0) + next_attempt_at DateTime @default(now()) + applied_at DateTime? + last_error String? + created_at DateTime @default(now()) -// Durable accounting ledger. One row per usage or cost event; payload holds the -// private event envelope versioned by schema_version. Usage rows retain request-scoped -// pricing context; cost rows include resolved rates and the finalized pricing snapshot. -model LiteLLM_AccountingEvent { - event_id String @id - kind AccountingEventKind - source_event_id String? - schema_version Int - payload_hash String - occurred_at DateTime - recorded_at DateTime @default(now()) - payload Json - - @@index([recorded_at]) - @@index([kind, source_event_id]) -} - -// One row per (event, target table, version): pending work for the projector and, -// once applied in the same transaction as the target write, the receipt that stops a retry. -model LiteLLM_AccountingDelivery { - event_id String - target AccountingDeliveryTarget - version Int - state AccountingDeliveryState @default(pending) - attempts Int @default(0) - next_attempt_at DateTime @default(now()) - applied_at DateTime? - last_error String? - - @@id([event_id, target, version]) - @@index([target, state, next_attempt_at]) + @@index([state, next_attempt_at]) + @@index([state, applied_at]) + @@index([request_id]) } model LiteLLM_SubscriptionAccountTable { diff --git a/scripts/check_mcp_sdk_install.py b/scripts/check_mcp_sdk_install.py index f2c2891bfd8..f5261bc22f8 100644 --- a/scripts/check_mcp_sdk_install.py +++ b/scripts/check_mcp_sdk_install.py @@ -13,6 +13,7 @@ IMPORTED_MODULES: Final[tuple[str, ...]] = ( "litellm.proxy.mcp_server.server", "litellm.proxy.mcp_server.mcp_server_manager", "litellm.proxy.mcp_server.rest_endpoints", + "litellm.proxy.proxy_server", ) diff --git a/scripts/check_openapi_docs.py b/scripts/check_openapi_docs.py index 26bb034bfa6..219ef912952 100755 --- a/scripts/check_openapi_docs.py +++ b/scripts/check_openapi_docs.py @@ -18,6 +18,7 @@ from collections.abc import Iterator, Mapping from typing import Final, NamedTuple GATED_METHODS: Final = frozenset({"post"}) +SCHEMA_MEDIA_TYPES: Final = ("application/json", "application/sdp", "multipart/form-data") class Violation(NamedTuple): @@ -30,18 +31,21 @@ def _as_mapping(node: object) -> Mapping[str, object]: return node if isinstance(node, Mapping) else {} -def _json_schema(container: object) -> object: +def _content_schema(container: object) -> object: content: Final = _as_mapping(_as_mapping(container).get("content")) - return _as_mapping(content.get("application/json")).get("schema") + return next( + (schema for media_type in SCHEMA_MEDIA_TYPES if (schema := _as_mapping(content.get(media_type)).get("schema"))), + None, + ) def _operation_codes(operation: Mapping[str, object]) -> Iterator[str]: - if not _json_schema(operation.get("requestBody")): + if not _content_schema(operation.get("requestBody")): yield "OA001" description: Final = operation.get("description") if not isinstance(description, str) or not description.strip(): yield "OA002" - if not _json_schema(_as_mapping(operation.get("responses")).get("200")): + if not _content_schema(_as_mapping(operation.get("responses")).get("200")): yield "OA003" diff --git a/scripts/check_schema_compatibility.py b/scripts/check_schema_compatibility.py index 898c65dff2c..c56986a38c8 100644 --- a/scripts/check_schema_compatibility.py +++ b/scripts/check_schema_compatibility.py @@ -13,6 +13,7 @@ from pydantic import TypeAdapter Schema = Mapping[str, Mapping[str, str]] MODELS: Final = re.compile(r"^[ \t]*model\s+(\w+)\s*\{(.*?)^[ \t]*\}", re.MULTILINE | re.DOTALL) +DROPPED_UNUSED_MODELS: Final = frozenset({"LiteLLM_AccountingDelivery", "LiteLLM_AccountingEvent"}) def parse_model_fields(schema: str) -> Schema: @@ -27,18 +28,18 @@ def _field_changes(model: str, field: str, old_type: str, new_fields: Mapping[st if field not in new_fields: yield f"Breaking: Field {model}.{field} was removed" return - new_type: Final = new_fields[field] - if old_type == new_type: - return - if "?" in old_type and "?" not in new_type: + old_base: Final = old_type.split()[0] + new_base: Final = new_fields[field].split()[0] + if old_base.endswith("?") and not new_base.endswith("?"): yield f"Breaking: Field {model}.{field} changed from optional to required" - if not old_type.startswith(new_type.split("?")[0]): - yield f"Breaking: Field {model}.{field} changed type from {old_type} to {new_type}" + if old_base.rstrip("?") != new_base.rstrip("?"): + yield f"Breaking: Field {model}.{field} changed type from {old_base} to {new_base}" def _model_changes(model: str, old_fields: Mapping[str, str], new_schema: Schema) -> Iterator[str]: if model not in new_schema: - yield f"Breaking: Model {model} was removed" + if model not in DROPPED_UNUSED_MODELS: + yield f"Breaking: Model {model} was removed" return for field, old_type in old_fields.items(): yield from _field_changes(model, field, old_type, new_schema[model]) @@ -52,14 +53,20 @@ def check_breaking_changes(old_schema: Schema, new_schema: Schema) -> tuple[str, return tuple(changes()) -def main() -> int: - parser: Final = argparse.ArgumentParser() - parser.add_argument("--base-ref", required=True) - options: Final = parser.parse_args() - base_ref: Final = TypeAdapter(str).validate_python(options.base_ref) - base: Final = subprocess.run( +def _merge_base(base_ref: str) -> str: + return subprocess.run( ("git", "merge-base", "HEAD", base_ref), capture_output=True, text=True, check=True ).stdout.strip() + + +def main() -> int: + parser: Final = argparse.ArgumentParser() + source: Final = parser.add_mutually_exclusive_group(required=True) + source.add_argument("--base-ref", help="compare against the merge base of HEAD and this ref (needs history)") + source.add_argument("--base-commit", help="compare against this commit as is (works in a shallow clone)") + options: Final = TypeAdapter(dict[str, str | None]).validate_python(vars(parser.parse_args())) + base_commit: Final = options["base_commit"] + base: Final = base_commit if base_commit else _merge_base(options["base_ref"] or "") previous: Final = subprocess.run( ("git", "show", f"{base}:schema.prisma"), capture_output=True, text=True, check=True ).stdout diff --git a/terraform/litellm/aws/README.md b/terraform/litellm/aws/README.md index bedb6f4e98b..6f0450c0091 100644 --- a/terraform/litellm/aws/README.md +++ b/terraform/litellm/aws/README.md @@ -212,33 +212,23 @@ orthogonal to the OTLP variables above; their credentials still go in ### Enterprise billing metrics -License-gated request metering is opt-in and gated entirely on -`billing_metrics_endpoint`. Empty (default) and no billing env is added to -the container, so existing deployments are unchanged. Set it and both -gateway and backend export billable-request counts over OTLP/HTTP, -authenticating to the collector with the mTLS client certificate issued for -your deployment. - -The proxy accepts the certificate, key, and CA bundle as either a file path -or literal PEM content. This stack takes the PEM, writes each one to its own -Secrets Manager entry, grants the task-execution role -`secretsmanager:GetSecretValue` on them, and injects them as -`LITELLM_BILLING_METRICS_CLIENT_CERT` / `_CLIENT_KEY` (and `_CA_CERT` when -set), so no volume mount is needed on Fargate. +License-gated request metering uses Cognito bearer authentication. Set the +endpoint, client ID, and token URL as plain values, and provide the client +secret through the sensitive Terraform variable. The client secret is stored +in Secrets Manager and injected into both gateway and backend tasks ```hcl billing_metrics_endpoint = "https://telemetry.litellm.ai/v1/metrics" +billing_metrics_client_id = "cognito-client-id" +billing_metrics_token_url = "https://litellm-prod.auth.us-west-1.amazoncognito.com/oauth2/token" ``` ```bash -export TF_VAR_billing_metrics_client_cert_pem="$(cat client.crt)" -export TF_VAR_billing_metrics_client_key_pem="$(cat client.key)" +export TF_VAR_billing_metrics_client_secret="cognito-client-secret" ``` -`billing_metrics_ca_cert_pem` is only for private or test collectors whose -CA is not in the system trust store; leave it empty against -`telemetry.litellm.ai`. Metering requires an enterprise license, so pair -this with `litellm_license`. To tune the export cadence, set +The client ID and client secret are required when the endpoint is set +Metering also requires an enterprise license. To tune the export cadence, set `LITELLM_BILLING_METRICS_EXPORT_INTERVAL_MS` through `gateway_extra_env` / `backend_extra_env` diff --git a/terraform/litellm/aws/ecs.tf b/terraform/litellm/aws/ecs.tf index 412e6c423f5..dec7f599ced 100644 --- a/terraform/litellm/aws/ecs.tf +++ b/terraform/litellm/aws/ecs.tf @@ -79,32 +79,19 @@ locals { { name = "OTEL_HEADERS", valueFrom = var.otel_headers_secret_arn }, ] : [] - # Enterprise request metering, gated on billing_metrics_endpoint. The - # endpoint rides in as a plain env var; the mTLS material is stored in - # Secrets Manager (secrets.tf) and injected as PEM-valued env vars, which - # the proxy accepts in place of file paths. Each PEM is wired only when the - # operator supplied it, so an empty ca_cert_pem falls back to the system - # trust store. - billing_metrics_enabled = var.billing_metrics_endpoint != "" - billing_metrics_client_cert_enabled = local.billing_metrics_enabled && var.billing_metrics_client_cert_pem != "" - billing_metrics_client_key_enabled = local.billing_metrics_enabled && var.billing_metrics_client_key_pem != "" - billing_metrics_ca_cert_enabled = local.billing_metrics_enabled && var.billing_metrics_ca_cert_pem != "" + # Enterprise request metering, gated on billing_metrics_endpoint. + billing_metrics_enabled = var.billing_metrics_endpoint != "" + billing_metrics_client_secret_enabled = local.billing_metrics_enabled && var.billing_metrics_client_secret != "" billing_metrics_env = local.billing_metrics_enabled ? [ { name = "LITELLM_BILLING_METRICS_ENDPOINT", value = var.billing_metrics_endpoint }, + { name = "LITELLM_BILLING_METRICS_CLIENT_ID", value = var.billing_metrics_client_id }, + { name = "LITELLM_BILLING_METRICS_TOKEN_URL", value = var.billing_metrics_token_url }, ] : [] - billing_metrics_secrets = concat( - local.billing_metrics_client_cert_enabled ? [ - { name = "LITELLM_BILLING_METRICS_CLIENT_CERT", valueFrom = aws_secretsmanager_secret.billing_metrics_client_cert[0].arn }, - ] : [], - local.billing_metrics_client_key_enabled ? [ - { name = "LITELLM_BILLING_METRICS_CLIENT_KEY", valueFrom = aws_secretsmanager_secret.billing_metrics_client_key[0].arn }, - ] : [], - local.billing_metrics_ca_cert_enabled ? [ - { name = "LITELLM_BILLING_METRICS_CA_CERT", valueFrom = aws_secretsmanager_secret.billing_metrics_ca_cert[0].arn }, - ] : [], - ) + billing_metrics_secrets = local.billing_metrics_client_secret_enabled ? [ + { name = "LITELLM_BILLING_METRICS_CLIENT_SECRET", valueFrom = aws_secretsmanager_secret.billing_metrics_client_secret[0].arn }, + ] : [] managed_db_env = var.create_database ? [ { name = "IAM_TOKEN_DB_AUTH", value = "true" }, @@ -338,27 +325,12 @@ locals { # ---------- Gateway ---------- resource "aws_ecs_task_definition" "gateway" { - # Metering needs a client certificate AND its key. Each secret is created only - # when its own PEM is supplied, so an endpoint set with a missing key would - # otherwise apply cleanly and leave the proxy logging "missing config" and - # never exporting. ca_cert_pem stays optional: empty means fall back to the - # system trust store. - # - # The guard lives here, on an unconditional resource, rather than on the cert - # secret: that secret is count-gated on the cert itself, so it has zero - # instances in exactly the case this must catch. Adding count or for_each to - # this resource would silently stop the guard from evaluating. - # - # endpoint cert key -> result - # "" any any -> metering off, no secrets created - # set set set -> metering on - # set any-missing -> plan fails here lifecycle { precondition { condition = var.billing_metrics_endpoint == "" || ( - var.billing_metrics_client_cert_pem != "" && var.billing_metrics_client_key_pem != "" + var.billing_metrics_client_id != "" && var.billing_metrics_client_secret != "" ) - error_message = "billing_metrics_client_cert_pem and billing_metrics_client_key_pem are both required when billing_metrics_endpoint is set." + error_message = "billing_metrics_client_id and billing_metrics_client_secret are required when billing_metrics_endpoint is set." } precondition { @@ -465,9 +437,7 @@ resource "aws_ecs_service" "gateway" { aws_secretsmanager_secret_version.license, aws_secretsmanager_secret_version.database_url, aws_secretsmanager_secret_version.redis_url, - aws_secretsmanager_secret_version.billing_metrics_client_cert, - aws_secretsmanager_secret_version.billing_metrics_client_key, - aws_secretsmanager_secret_version.billing_metrics_ca_cert, + aws_secretsmanager_secret_version.billing_metrics_client_secret, ] tags = local.tags @@ -481,9 +451,9 @@ resource "aws_ecs_task_definition" "backend" { lifecycle { precondition { condition = var.billing_metrics_endpoint == "" || ( - var.billing_metrics_client_cert_pem != "" && var.billing_metrics_client_key_pem != "" + var.billing_metrics_client_id != "" && var.billing_metrics_client_secret != "" ) - error_message = "billing_metrics_client_cert_pem and billing_metrics_client_key_pem are both required when billing_metrics_endpoint is set." + error_message = "billing_metrics_client_id and billing_metrics_client_secret are required when billing_metrics_endpoint is set." } } @@ -566,9 +536,7 @@ resource "aws_ecs_service" "backend" { aws_secretsmanager_secret_version.ui_password, aws_secretsmanager_secret_version.database_url, aws_secretsmanager_secret_version.redis_url, - aws_secretsmanager_secret_version.billing_metrics_client_cert, - aws_secretsmanager_secret_version.billing_metrics_client_key, - aws_secretsmanager_secret_version.billing_metrics_ca_cert, + aws_secretsmanager_secret_version.billing_metrics_client_secret, ] tags = local.tags diff --git a/terraform/litellm/aws/iam.tf b/terraform/litellm/aws/iam.tf index 3c55f07b02a..a653bd82d31 100644 --- a/terraform/litellm/aws/iam.tf +++ b/terraform/litellm/aws/iam.tf @@ -53,9 +53,7 @@ data "aws_iam_policy_document" "secrets_access" { [aws_secretsmanager_secret.master_key.arn], aws_secretsmanager_secret.license[*].arn, aws_secretsmanager_secret.ui_password[*].arn, - aws_secretsmanager_secret.billing_metrics_client_cert[*].arn, - aws_secretsmanager_secret.billing_metrics_client_key[*].arn, - aws_secretsmanager_secret.billing_metrics_ca_cert[*].arn, + aws_secretsmanager_secret.billing_metrics_client_secret[*].arn, aws_secretsmanager_secret.database_url[*].arn, aws_secretsmanager_secret.redis_url[*].arn, local.extra_secret_arns, diff --git a/terraform/litellm/aws/secrets.tf b/terraform/litellm/aws/secrets.tf index 921bae4d827..6821b8b43dc 100644 --- a/terraform/litellm/aws/secrets.tf +++ b/terraform/litellm/aws/secrets.tf @@ -75,59 +75,21 @@ resource "aws_secretsmanager_secret_version" "ui_password" { secret_string = var.ui_password } -# Billing-metrics mTLS material — only created when metering is enabled -# (billing_metrics_endpoint non-empty) and the operator supplied the PEM. -# The task-execution role gets GetSecretValue via iam.tf, and gateway + -# backend pick the env vars up through shared_secrets in ecs.tf. -resource "aws_secretsmanager_secret" "billing_metrics_client_cert" { - count = local.billing_metrics_client_cert_enabled ? 1 : 0 +resource "aws_secretsmanager_secret" "billing_metrics_client_secret" { + count = local.billing_metrics_client_secret_enabled ? 1 : 0 - name = "${local.name}-billing-metrics-client-cert" - description = "LITELLM_BILLING_METRICS_CLIENT_CERT for gateway + backend." + name = "${local.name}-billing-metrics-client-secret" + description = "LITELLM_BILLING_METRICS_CLIENT_SECRET for gateway + backend." recovery_window_in_days = 0 tags = local.tags } -resource "aws_secretsmanager_secret_version" "billing_metrics_client_cert" { - count = local.billing_metrics_client_cert_enabled ? 1 : 0 +resource "aws_secretsmanager_secret_version" "billing_metrics_client_secret" { + count = local.billing_metrics_client_secret_enabled ? 1 : 0 - secret_id = aws_secretsmanager_secret.billing_metrics_client_cert[0].id - secret_string = var.billing_metrics_client_cert_pem -} - -resource "aws_secretsmanager_secret" "billing_metrics_client_key" { - count = local.billing_metrics_client_key_enabled ? 1 : 0 - - name = "${local.name}-billing-metrics-client-key" - description = "LITELLM_BILLING_METRICS_CLIENT_KEY for gateway + backend." - recovery_window_in_days = 0 - - tags = local.tags -} - -resource "aws_secretsmanager_secret_version" "billing_metrics_client_key" { - count = local.billing_metrics_client_key_enabled ? 1 : 0 - - secret_id = aws_secretsmanager_secret.billing_metrics_client_key[0].id - secret_string = var.billing_metrics_client_key_pem -} - -resource "aws_secretsmanager_secret" "billing_metrics_ca_cert" { - count = local.billing_metrics_ca_cert_enabled ? 1 : 0 - - name = "${local.name}-billing-metrics-ca-cert" - description = "LITELLM_BILLING_METRICS_CA_CERT for gateway + backend." - recovery_window_in_days = 0 - - tags = local.tags -} - -resource "aws_secretsmanager_secret_version" "billing_metrics_ca_cert" { - count = local.billing_metrics_ca_cert_enabled ? 1 : 0 - - secret_id = aws_secretsmanager_secret.billing_metrics_ca_cert[0].id - secret_string = var.billing_metrics_ca_cert_pem + secret_id = aws_secretsmanager_secret.billing_metrics_client_secret[0].id + secret_string = var.billing_metrics_client_secret } resource "aws_secretsmanager_secret" "db_master_password" { diff --git a/terraform/litellm/aws/variables.tf b/terraform/litellm/aws/variables.tf index 9b7a279a907..be7656c2d48 100644 --- a/terraform/litellm/aws/variables.tf +++ b/terraform/litellm/aws/variables.tf @@ -764,13 +764,7 @@ variable "otel_headers_secret_arn" { # ---------- Enterprise billing metrics ---------- # -# License-gated request metering. Opt-in and gated entirely on -# billing_metrics_endpoint: leave it empty (the default) and nothing -# metering-related lands in the container env. Set it and gateway + backend -# export billable-request counts over OTLP/HTTP, authenticating to the -# collector with an mTLS client cert. The proxy accepts the cert, key, and CA -# as either a file path or literal PEM content, so on Fargate they are -# injected straight from Secrets Manager as env vars and no volume is needed. +# License-gated request metering. The client secret is stored in Secrets Manager. variable "billing_metrics_endpoint" { description = <<-EOT @@ -784,44 +778,34 @@ variable "billing_metrics_endpoint" { default = "" } -variable "billing_metrics_client_cert_pem" { +variable "billing_metrics_client_id" { description = <<-EOT - PEM content of the mTLS client certificate issued for this deployment. - When billing_metrics_endpoint is set, the stack stores this in a - `-litellm--billing-metrics-client-cert` Secrets Manager - entry, grants the task-execution role GetSecretValue on it, and exposes - it to gateway + backend as LITELLM_BILLING_METRICS_CLIENT_CERT. Required - whenever metering is enabled. + Cognito OAuth2 client ID exposed to the gateway and backend as + LITELLM_BILLING_METRICS_CLIENT_ID. Required when billing_metrics_endpoint + is set. + EOT + type = string + default = "" +} + +variable "billing_metrics_client_secret" { + description = <<-EOT + Cognito OAuth2 client secret stored in Secrets Manager and exposed to + the gateway and backend as LITELLM_BILLING_METRICS_CLIENT_SECRET. + Required when billing_metrics_endpoint is set. EOT type = string default = "" sensitive = true } -variable "billing_metrics_client_key_pem" { +variable "billing_metrics_token_url" { description = <<-EOT - PEM content of the private key matching - billing_metrics_client_cert_pem. Stored in a - `-litellm--billing-metrics-client-key` Secrets Manager - entry and exposed as LITELLM_BILLING_METRICS_CLIENT_KEY. Required - whenever metering is enabled. + Cognito OAuth2 client-credentials token endpoint exposed to gateway and + backend as LITELLM_BILLING_METRICS_TOKEN_URL. EOT type = string - default = "" - sensitive = true -} - -variable "billing_metrics_ca_cert_pem" { - description = <<-EOT - PEM content of the CA bundle used to verify the metering collector. - Only needed for private or test collectors whose CA is not in the - system trust store; telemetry.litellm.ai is publicly trusted, so leave - this empty for production. When set, it is exposed as - LITELLM_BILLING_METRICS_CA_CERT. - EOT - type = string - default = "" - sensitive = true + default = "https://litellm-prod.auth.us-west-1.amazoncognito.com/oauth2/token" } # ---------- Collector sidecar ---------- diff --git a/terraform/litellm/gcp/README.md b/terraform/litellm/gcp/README.md index 3227dcac179..9e21ba14543 100644 --- a/terraform/litellm/gcp/README.md +++ b/terraform/litellm/gcp/README.md @@ -210,33 +210,23 @@ Behavior matches the AWS stack 1:1; the only naming differences are ### Enterprise billing metrics -License-gated request metering is opt-in and gated entirely on -`billing_metrics_endpoint`. Empty (default) and no billing env is added to -the container, so existing deployments are unchanged. Set it and both -gateway and backend export billable-request counts over OTLP/HTTP, -authenticating to the collector with the mTLS client certificate issued for -your deployment. - -The proxy accepts the certificate, key, and CA bundle as either a file path -or literal PEM content. This stack takes the PEM, writes each one to its own -Secret Manager entry, grants the runtime service account -`roles/secretmanager.secretAccessor` on them, and injects them as Cloud Run -secret env vars `LITELLM_BILLING_METRICS_CLIENT_CERT` / `_CLIENT_KEY` (and -`_CA_CERT` when set), so no volume mount is needed. +License-gated request metering uses Cognito bearer authentication. Set the +endpoint, client ID, and token URL as plain values, and provide the client +secret through the sensitive Terraform variable. The client secret is stored +in Secret Manager and injected into both gateway and backend services ```hcl billing_metrics_endpoint = "https://telemetry.litellm.ai/v1/metrics" +billing_metrics_client_id = "cognito-client-id" +billing_metrics_token_url = "https://litellm-prod.auth.us-west-1.amazoncognito.com/oauth2/token" ``` ```bash -export TF_VAR_billing_metrics_client_cert_pem="$(cat client.crt)" -export TF_VAR_billing_metrics_client_key_pem="$(cat client.key)" +export TF_VAR_billing_metrics_client_secret="cognito-client-secret" ``` -`billing_metrics_ca_cert_pem` is only for private or test collectors whose -CA is not in the system trust store; leave it empty against -`telemetry.litellm.ai`. Metering requires an enterprise license, so pair -this with `litellm_license`. To tune the export cadence, set +The client ID and client secret are required when the endpoint is set +Metering also requires an enterprise license. To tune the export cadence, set `LITELLM_BILLING_METRICS_EXPORT_INTERVAL_MS` through `gateway_extra_env` / `backend_extra_env` diff --git a/terraform/litellm/gcp/cloudrun.tf b/terraform/litellm/gcp/cloudrun.tf index d0b32a367d6..07bf68b3a62 100644 --- a/terraform/litellm/gcp/cloudrun.tf +++ b/terraform/litellm/gcp/cloudrun.tf @@ -62,32 +62,19 @@ locals { { name = "OTEL_HEADERS", secret = var.otel_headers_secret, version = "latest" }, ] : [] - # Enterprise request metering, gated on billing_metrics_endpoint. The - # endpoint rides in as a plain env var; the mTLS material lives in Secret - # Manager (secrets.tf) and is injected as PEM-valued env vars, which the - # proxy accepts in place of file paths. Each PEM is wired only when the - # operator supplied it, so an empty ca_cert_pem falls back to the system - # trust store. - billing_metrics_enabled = var.billing_metrics_endpoint != "" - billing_metrics_client_cert_enabled = local.billing_metrics_enabled && var.billing_metrics_client_cert_pem != "" - billing_metrics_client_key_enabled = local.billing_metrics_enabled && var.billing_metrics_client_key_pem != "" - billing_metrics_ca_cert_enabled = local.billing_metrics_enabled && var.billing_metrics_ca_cert_pem != "" + # Enterprise request metering, gated on billing_metrics_endpoint. + billing_metrics_enabled = var.billing_metrics_endpoint != "" + billing_metrics_client_secret_enabled = local.billing_metrics_enabled && var.billing_metrics_client_secret != "" billing_metrics_env_kv = local.billing_metrics_enabled ? [ { name = "LITELLM_BILLING_METRICS_ENDPOINT", value = var.billing_metrics_endpoint }, + { name = "LITELLM_BILLING_METRICS_CLIENT_ID", value = var.billing_metrics_client_id }, + { name = "LITELLM_BILLING_METRICS_TOKEN_URL", value = var.billing_metrics_token_url }, ] : [] - billing_metrics_env_secrets = concat( - local.billing_metrics_client_cert_enabled ? [ - { name = "LITELLM_BILLING_METRICS_CLIENT_CERT", secret = google_secret_manager_secret.billing_metrics_client_cert[0].id, version = "latest" }, - ] : [], - local.billing_metrics_client_key_enabled ? [ - { name = "LITELLM_BILLING_METRICS_CLIENT_KEY", secret = google_secret_manager_secret.billing_metrics_client_key[0].id, version = "latest" }, - ] : [], - local.billing_metrics_ca_cert_enabled ? [ - { name = "LITELLM_BILLING_METRICS_CA_CERT", secret = google_secret_manager_secret.billing_metrics_ca_cert[0].id, version = "latest" }, - ] : [], - ) + billing_metrics_env_secrets = local.billing_metrics_client_secret_enabled ? [ + { name = "LITELLM_BILLING_METRICS_CLIENT_SECRET", secret = google_secret_manager_secret.billing_metrics_client_secret[0].id, version = "latest" }, + ] : [] # Cloud Run v2 secret env vars use value_source.secret_key_ref pointing at a # secret resource ID. Shared between gateway and backend (the migrations @@ -481,9 +468,7 @@ resource "google_cloud_run_v2_service" "gateway" { google_secret_manager_secret_iam_member.license, google_secret_manager_secret_iam_member.extras, google_secret_manager_secret_iam_member.otel_headers, - google_secret_manager_secret_iam_member.billing_metrics_client_cert, - google_secret_manager_secret_iam_member.billing_metrics_client_key, - google_secret_manager_secret_iam_member.billing_metrics_ca_cert, + google_secret_manager_secret_iam_member.billing_metrics_client_secret, google_secret_manager_secret_iam_member.metrics_run_monitoring, google_project_iam_member.runtime_metric_writer, google_storage_bucket_iam_member.proxy_config_runtime, @@ -603,9 +588,7 @@ resource "google_cloud_run_v2_service" "backend" { google_secret_manager_secret_iam_member.ui_password, google_secret_manager_secret_iam_member.extras, google_secret_manager_secret_iam_member.otel_headers, - google_secret_manager_secret_iam_member.billing_metrics_client_cert, - google_secret_manager_secret_iam_member.billing_metrics_client_key, - google_secret_manager_secret_iam_member.billing_metrics_ca_cert, + google_secret_manager_secret_iam_member.billing_metrics_client_secret, google_storage_bucket_iam_member.proxy_config_runtime, google_sql_user.app, terraform_data.migration, diff --git a/terraform/litellm/gcp/iam.tf b/terraform/litellm/gcp/iam.tf index 5c2bc38bc12..1e0a5fe9626 100644 --- a/terraform/litellm/gcp/iam.tf +++ b/terraform/litellm/gcp/iam.tf @@ -10,9 +10,9 @@ resource "google_service_account" "runtime" { lifecycle { precondition { condition = !var.create_runtime || var.billing_metrics_endpoint == "" || ( - var.billing_metrics_client_cert_pem != "" && var.billing_metrics_client_key_pem != "" + var.billing_metrics_client_id != "" && var.billing_metrics_client_secret != "" ) - error_message = "billing_metrics_client_cert_pem and billing_metrics_client_key_pem are both required when billing_metrics_endpoint is set and create_runtime is true." + error_message = "billing_metrics_client_id and billing_metrics_client_secret are required when billing_metrics_endpoint is set and create_runtime is true." } } } @@ -91,28 +91,10 @@ resource "google_secret_manager_secret_iam_member" "otel_headers" { member = "serviceAccount:${google_service_account.runtime.email}" } -# Billing-metrics mTLS accessors — only created when request metering is -# enabled and the matching PEM was supplied. -resource "google_secret_manager_secret_iam_member" "billing_metrics_client_cert" { - count = local.billing_metrics_client_cert_enabled ? 1 : 0 +resource "google_secret_manager_secret_iam_member" "billing_metrics_client_secret" { + count = local.billing_metrics_client_secret_enabled ? 1 : 0 - secret_id = google_secret_manager_secret.billing_metrics_client_cert[0].id - role = "roles/secretmanager.secretAccessor" - member = "serviceAccount:${google_service_account.runtime.email}" -} - -resource "google_secret_manager_secret_iam_member" "billing_metrics_client_key" { - count = local.billing_metrics_client_key_enabled ? 1 : 0 - - secret_id = google_secret_manager_secret.billing_metrics_client_key[0].id - role = "roles/secretmanager.secretAccessor" - member = "serviceAccount:${google_service_account.runtime.email}" -} - -resource "google_secret_manager_secret_iam_member" "billing_metrics_ca_cert" { - count = local.billing_metrics_ca_cert_enabled ? 1 : 0 - - secret_id = google_secret_manager_secret.billing_metrics_ca_cert[0].id + secret_id = google_secret_manager_secret.billing_metrics_client_secret[0].id role = "roles/secretmanager.secretAccessor" member = "serviceAccount:${google_service_account.runtime.email}" } diff --git a/terraform/litellm/gcp/secrets.tf b/terraform/litellm/gcp/secrets.tf index b3b656721ab..f3636b6e8e8 100644 --- a/terraform/litellm/gcp/secrets.tf +++ b/terraform/litellm/gcp/secrets.tf @@ -64,59 +64,21 @@ resource "google_secret_manager_secret_version" "ui_password" { secret_data = var.ui_password } -# Billing-metrics mTLS material — only created when metering is enabled -# (billing_metrics_endpoint non-empty) and the operator supplied the PEM. -# The runtime SA gets accessor permission via iam.tf, and gateway + backend -# pick the env vars up through billing_metrics_env_secrets in cloudrun.tf. -resource "google_secret_manager_secret" "billing_metrics_client_cert" { - count = local.billing_metrics_client_cert_enabled ? 1 : 0 +resource "google_secret_manager_secret" "billing_metrics_client_secret" { + count = local.billing_metrics_client_secret_enabled ? 1 : 0 - secret_id = "${local.name}-billing-metrics-client-cert" + secret_id = "${local.name}-billing-metrics-client-secret" labels = local.labels replication { auto {} } } -resource "google_secret_manager_secret_version" "billing_metrics_client_cert" { - count = local.billing_metrics_client_cert_enabled ? 1 : 0 +resource "google_secret_manager_secret_version" "billing_metrics_client_secret" { + count = local.billing_metrics_client_secret_enabled ? 1 : 0 - secret = google_secret_manager_secret.billing_metrics_client_cert[0].id - secret_data = var.billing_metrics_client_cert_pem -} - -resource "google_secret_manager_secret" "billing_metrics_client_key" { - count = local.billing_metrics_client_key_enabled ? 1 : 0 - - secret_id = "${local.name}-billing-metrics-client-key" - labels = local.labels - replication { - auto {} - } -} - -resource "google_secret_manager_secret_version" "billing_metrics_client_key" { - count = local.billing_metrics_client_key_enabled ? 1 : 0 - - secret = google_secret_manager_secret.billing_metrics_client_key[0].id - secret_data = var.billing_metrics_client_key_pem -} - -resource "google_secret_manager_secret" "billing_metrics_ca_cert" { - count = local.billing_metrics_ca_cert_enabled ? 1 : 0 - - secret_id = "${local.name}-billing-metrics-ca-cert" - labels = local.labels - replication { - auto {} - } -} - -resource "google_secret_manager_secret_version" "billing_metrics_ca_cert" { - count = local.billing_metrics_ca_cert_enabled ? 1 : 0 - - secret = google_secret_manager_secret.billing_metrics_ca_cert[0].id - secret_data = var.billing_metrics_ca_cert_pem + secret = google_secret_manager_secret.billing_metrics_client_secret[0].id + secret_data = var.billing_metrics_client_secret } resource "google_secret_manager_secret" "metrics_run_monitoring" { diff --git a/terraform/litellm/gcp/variables.tf b/terraform/litellm/gcp/variables.tf index 6161e893e02..e40ee36fa18 100644 --- a/terraform/litellm/gcp/variables.tf +++ b/terraform/litellm/gcp/variables.tf @@ -602,14 +602,7 @@ variable "gateway_metrics_collector_image" { # ---------- Enterprise billing metrics ---------- # -# License-gated request metering. Opt-in and gated entirely on -# billing_metrics_endpoint: leave it empty (the default) and nothing -# metering-related is added to the container env. Set it and gateway + -# backend export billable-request counts over OTLP/HTTP, authenticating to -# the collector with an mTLS client cert. The proxy accepts the cert, key, -# and CA as either a file path or literal PEM content, so on Cloud Run they -# are injected straight from Secret Manager as env vars and no volume is -# needed. +# License-gated request metering. The client secret is stored in Secret Manager. variable "billing_metrics_endpoint" { description = <<-EOT @@ -623,44 +616,34 @@ variable "billing_metrics_endpoint" { default = "" } -variable "billing_metrics_client_cert_pem" { +variable "billing_metrics_client_id" { description = <<-EOT - PEM content of the mTLS client certificate issued for this deployment. - When billing_metrics_endpoint is set, the stack stores this in a - `-litellm--billing-metrics-client-cert` Secret Manager - entry, grants the runtime SA accessor on it, and exposes it to gateway + - backend as LITELLM_BILLING_METRICS_CLIENT_CERT. Required whenever - metering is enabled. + Cognito OAuth2 client ID exposed to the gateway and backend as + LITELLM_BILLING_METRICS_CLIENT_ID. Required when billing_metrics_endpoint + is set. + EOT + type = string + default = "" +} + +variable "billing_metrics_client_secret" { + description = <<-EOT + Cognito OAuth2 client secret stored in Secret Manager and exposed to + the gateway and backend as LITELLM_BILLING_METRICS_CLIENT_SECRET. + Required when billing_metrics_endpoint is set. EOT type = string default = "" sensitive = true } -variable "billing_metrics_client_key_pem" { +variable "billing_metrics_token_url" { description = <<-EOT - PEM content of the private key matching - billing_metrics_client_cert_pem. Stored in a - `-litellm--billing-metrics-client-key` Secret Manager entry - and exposed as LITELLM_BILLING_METRICS_CLIENT_KEY. Required whenever - metering is enabled. + Cognito OAuth2 client-credentials token endpoint exposed to gateway and + backend as LITELLM_BILLING_METRICS_TOKEN_URL. EOT type = string - default = "" - sensitive = true -} - -variable "billing_metrics_ca_cert_pem" { - description = <<-EOT - PEM content of the CA bundle used to verify the metering collector. - Only needed for private or test collectors whose CA is not in the - system trust store; telemetry.litellm.ai is publicly trusted, so leave - this empty for production. When set, it is exposed as - LITELLM_BILLING_METRICS_CA_CERT. - EOT - type = string - default = "" - sensitive = true + default = "https://litellm-prod.auth.us-west-1.amazoncognito.com/oauth2/token" } # ---------- Collector sidecar ---------- diff --git a/tests/_support/mcp_count_tool_upstream.py b/tests/_support/mcp_count_tool_upstream.py new file mode 100644 index 00000000000..f1aa61c7dba --- /dev/null +++ b/tests/_support/mcp_count_tool_upstream.py @@ -0,0 +1,42 @@ +import json +import queue +from collections.abc import Callable, Mapping +from typing import Final + +import httpx2 + +COUNT_OUTPUT_SCHEMA: Final = {"type": "object", "properties": {"n": {"type": "integer"}}, "required": ["n"]} + + +def count_tool_upstream( + structured: Mapping[str, object], methods_seen: "queue.SimpleQueue[str]" +) -> Callable[[httpx2.Request], httpx2.Response]: + """An MCP upstream with one tool, `count`, whose declared output schema wants an integer `n`.""" + + def respond(request: httpx2.Request) -> httpx2.Response: + if request.method != "POST": + return httpx2.Response(200) + payload: Final = json.loads(request.content) + methods_seen.put(payload["method"]) + if "id" not in payload: + return httpx2.Response(202) + results: Final[Mapping[str, Mapping[str, object]]] = { + "initialize": { + "protocolVersion": payload["params"].get("protocolVersion"), + "capabilities": {"tools": {}}, + "serverInfo": {"name": "count", "version": "1"}, + }, + "tools/list": { + "tools": [{"name": "count", "inputSchema": {"type": "object"}, "outputSchema": COUNT_OUTPUT_SCHEMA}] + }, + "tools/call": {"content": [{"type": "text", "text": "ok"}], "structuredContent": structured}, + } + return httpx2.Response( + 200, json={"jsonrpc": "2.0", "id": payload["id"], "result": results.get(payload["method"], {})} + ) + + return respond + + +def methods_received(methods_seen: "queue.SimpleQueue[str]") -> tuple[str, ...]: + return tuple(methods_seen.get_nowait() for _ in range(methods_seen.qsize())) diff --git a/tests/code_coverage_tests/check_e2e_no_raw_requests.py b/tests/code_coverage_tests/check_e2e_no_raw_requests.py index bea177d3b7d..94cba6334e0 100644 --- a/tests/code_coverage_tests/check_e2e_no_raw_requests.py +++ b/tests/code_coverage_tests/check_e2e_no_raw_requests.py @@ -3,7 +3,7 @@ raw HTTP client imports (requests, urllib.request, httpx, aiohttp, http.client) banned in suite code, and tests/e2e_harness, which tests that harness, is held to the same ban. Importing requests' exception types for catching is fine anywhere; a small allowlist grandfathers the files that legitimately make raw calls (the transport -itself, the root conftest liveness probe, the claude_code version resolver's constant +itself, the root conftest liveness probe, the cli_harness npm version resolver's constant registry URL fetch, and the mcp OAuth client, whose httpx client is the object the official mcp SDK's streamable_http_client requires and so cannot go through the sync requests transport). Referenced by tests/e2e/AGENTS.md.""" @@ -24,7 +24,7 @@ BANNED_MODULES = ("requests", "urllib.request", "http.client", "httpx", "aiohttp ALLOWED_RAW_CLIENT_FILES = { "e2e/e2e_http.py": ("requests",), "e2e/conftest.py": ("requests",), - "e2e/claude_code/pr_gate_version_resolver.py": ("urllib.request",), + "e2e/cli_harness/npm_version_resolver.py": ("urllib.request",), } EXCEPTION_ONLY_NAMES = frozenset({"RequestException", "ConnectionError", "Timeout", "HTTPError"}) diff --git a/tests/code_coverage_tests/recursive_detector.py b/tests/code_coverage_tests/recursive_detector.py index a84a40c67c1..f4ca7fa2965 100644 --- a/tests/code_coverage_tests/recursive_detector.py +++ b/tests/code_coverage_tests/recursive_detector.py @@ -87,6 +87,10 @@ IGNORE_FUNCTIONS = [ "scrub_json_strings", # max depth set (MAX_SCRUB_DEPTH); fails closed by returning "[Filtered]" for anything nested past the cap. "_without_requester_ip_address", # walks only the fresh tree _sanitize_request_body_for_spend_logs_payload returns (mapping cycles already cut), so it never goes deeper than that sanitizer did. "_merge_session_fields", # max depth set (_SESSION_MERGE_MAX_DEPTH); deeper mappings are replaced wholesale by the later session.update. + "_json", # router_rust index views: max depth set (DEFAULT_MAX_RECURSE_DEPTH); fails closed by raising ValueError at the cap. + "to_wire", # router_rust model info: bounded by the nesting depth of a stored deployment or cost-map entry (finite JSON trees: pydantic refuses a cycle when it dumps a deployment). + "from_wire", # router_rust model info: walks only what router-core merged from to_wire's output, so it never goes deeper than to_wire did. + "_valid_frontmatter_node", # max depth 32, manifest size capped at 1 MiB, and YAML aliases rejected before traversal. ] diff --git a/tests/code_coverage_tests/router_code_coverage.py b/tests/code_coverage_tests/router_code_coverage.py index 1b1ee484afc..42ee6178bf0 100644 --- a/tests/code_coverage_tests/router_code_coverage.py +++ b/tests/code_coverage_tests/router_code_coverage.py @@ -138,6 +138,7 @@ ignored_function_names = [ "_resolve_pre_call_check_input_tokens", # Tested through the token-count failure pre-call check tests in test_router.py "_params_neither_dropped_nor_allowed", # Tested through the allowed-or-dropped param pre-call check tests in test_router.py "_deployment_rejects_params", # Tested through the unsupported-param pre-call check tests in test_router.py + "_cache_flags_left_to_the_catalog", # Tested through the wildcard prompt cache flag tests in test_anthropic_cache_control_hook.py "_deployment_lacks_params", # Tested through the unsupported-param pre-call check tests in test_router.py "_pre_call_check_requested_chat_params", # Tested through the unsupported-param pre-call check tests in test_router.py "_deployment_supports_param", # Tested through the deployment-capability pre-call check tests in test_router.py @@ -175,6 +176,15 @@ ignored_function_names = [ "_deployment_field", # Read by is_batch_capable, tested through the mixed-group tests in test_router.py "_deployment_provider", # Read by without_deployments_that_cannot_batch, tested through the mixed-group tests in test_router.py "_cannot_run_batches", # Tested through the Azure and OpenAI mixed-group acreate_batch tests in test_router.py + "job_cost_of_poll", # Read by job_to_charge_once and charged_video_id, tested through the guardrail-priced poll tests in test_batch_utils.py + "charged_video_id", # Read by job_to_charge_once and get_spend_logs_id, tested through both in test_batch_utils.py and test_spend_tracking_utils.py + "_requested_video_id", # Read by charged_video_id, tested through the polled-id video test in test_batch_utils.py + "_guardrail_cost_of_poll", # Read by job_cost_of_poll and repeat_poll_cost, tested through the guardrail-priced poll tests + "repeat_poll_cost", # Read by job_to_charge_once and _charge_request_cost, tested through every limiter's guardrail poll test + "pays_only_its_guardrail", # Read by get_spend_logs_id, tested through its guardrail-only poll test in test_spend_tracking_utils.py + "charged_poll_cost", # Read by get_spend_logs_id, tested through the finished job guardrail poll tests in test_db_spend_update_writer.py + "_polled_batch", # Read by defers_batch_cost and _charged_batch, tested through the redacted batch retrieve tests + "_charged_batch", # Read by job_to_charge_once, tested through the batch charge identity tests in test_batch_utils.py "_responses_continuation", # Tested through the Responses mid-stream fallback tests in tests/unit/llms/base_llm/responses/test_transformation.py "_responses_continuation_ceilings", # Tested through the Responses mid-stream fallback tests in tests/unit/llms/base_llm/responses/test_transformation.py "_team_deployments_named", # Tested through the team lookups in the concurrent delete tests in test_router.py diff --git a/tests/code_coverage_tests/router_litellm_globals_check.py b/tests/code_coverage_tests/router_litellm_globals_check.py index ff9fac0e3dc..172a3754000 100644 --- a/tests/code_coverage_tests/router_litellm_globals_check.py +++ b/tests/code_coverage_tests/router_litellm_globals_check.py @@ -21,6 +21,7 @@ CHECKED = ( "litellm/router_core.py", "litellm/router_deprecated.py", "litellm/router_python_core.py", + "litellm/router_rust/core.py", ) diff --git a/tests/code_coverage_tests/router_surface_check.py b/tests/code_coverage_tests/router_surface_check.py index a8e0d6fa0d7..1c41526101a 100644 --- a/tests/code_coverage_tests/router_surface_check.py +++ b/tests/code_coverage_tests/router_surface_check.py @@ -11,7 +11,8 @@ modules listed there. The lists hold what is used today and may only shrink: also fails, so the entry is removed in the same change. "Outside" means every non-test file under litellm/ and enterprise/ except -litellm/router.py and the router's own modules. Uses from the router family +litellm/router.py and the router's own modules (including every +module under litellm/router_rust/, the Rust core's host-side glue). Uses from the router family (litellm/router_utils, litellm/router_strategy) are listed separately, because those modules become private parts of the router core in a later step. @@ -42,9 +43,12 @@ ROUTER_FILES = { "litellm/router_core.py", "litellm/router_python_core.py", "litellm/router_python_host.py", + "litellm/router_rust/core.py", "litellm/router_deprecated.py", "litellm/router_host.py", } +# The Rust core's host-side glue modules are part of the router. +ROUTER_FILE_PREFIXES = ("litellm/router_rust/",) ROUTER_CLASS_FILES = ["litellm/router.py", "litellm/router_python_core.py", "litellm/router_deprecated.py"] ROUTER_CLASS_NAMES = {"Router", "PythonCore", "DeprecatedRouterMembers"} @@ -128,7 +132,7 @@ def scan() -> Dict[str, Dict[str, Set[str]]]: uses: Dict[str, Dict[str, Set[str]]] = {"outside": {}, "router_family": {}} imports: Dict[str, Set[str]] = {} for rel, path in _python_files(): - if rel in ROUTER_FILES or _is_test(rel): + if rel in ROUTER_FILES or rel.startswith(ROUTER_FILE_PREFIXES) or _is_test(rel): continue with open(path, encoding="utf-8") as f: src = f.read() diff --git a/tests/code_coverage_tests/test_provider_cache.py b/tests/code_coverage_tests/test_provider_cache.py index fc39f2c1e6c..81ad7913559 100644 --- a/tests/code_coverage_tests/test_provider_cache.py +++ b/tests/code_coverage_tests/test_provider_cache.py @@ -377,7 +377,11 @@ def test_stream_completion_controls_publication(store: RedisResponseStore, provi assert len(provider.hits) == (2 if truncated else 1) -def test_store_outage_preserves_provider_success(provider: Provider) -> None: +@pytest.mark.parametrize("cluster_mode", ("0", "1")) +def test_store_outage_preserves_provider_success( + provider: Provider, monkeypatch: pytest.MonkeyPatch, cluster_mode: str, +) -> None: + monkeypatch.setenv("E2E_PROVIDER_CACHE_REDIS_CLUSTER", cluster_mode) with socket.socket() as probe: probe.bind(("127.0.0.1", 0)) port: Final = probe.getsockname()[1] @@ -401,6 +405,20 @@ def test_old_lease_cannot_overwrite_new_owner(store: RedisResponseStore) -> None assert isinstance(hit, CacheHit) and hit.payload == b"new" +def test_separate_namespaces_keep_their_own_response(store: RedisResponseStore) -> None: + other: Final = replace(store, namespace=store.namespace + "-other") + first_lease: Final = store.lookup("shared-key") + assert isinstance(first_lease, CaptureLease) + assert store.publish("shared-key", first_lease, b"first namespace") + other_lease: Final = other.lookup("shared-key") + assert isinstance(other_lease, CaptureLease) + assert other.publish("shared-key", other_lease, b"other namespace") + first_hit: Final = store.lookup("shared-key") + other_hit: Final = other.lookup("shared-key") + assert isinstance(first_hit, CacheHit) and first_hit.payload == b"first namespace" + assert isinstance(other_hit, CacheHit) and other_hit.payload == b"other namespace" + + def test_identity_preserves_values_and_never_contains_credentials() -> None: variants: Final = (b'{}', b'{"a":null}', b'{"a":false}', b'{"a":0}', b'{"a":0.0}', b'{"a":"0"}', b' { }', None, b'') url: Final = "https://example.invalid/v1/chat/completions" diff --git a/tests/e2e/AGENTS.md b/tests/e2e/AGENTS.md index cf1e41a59a6..b4ca8bd3d50 100644 --- a/tests/e2e/AGENTS.md +++ b/tests/e2e/AGENTS.md @@ -32,23 +32,25 @@ Each subdirectory under `tests/e2e/` is one suite, scoped to an endpoint family - `migrations/` - isolated Docker startup, concurrent migration, crash recovery, and legacy database compatibility. The CircleCI migration workflow enables `LITELLM_MIGRATION_TESTS=1`. These tests own their proxy containers and databases, so they do not use the shared proxy preflight or shared database cleanup -- `llm_translation/` - LLM endpoint and provider-translation behavior: passthrough, custom pricing, OCR, and the non-chat inference endpoints (`/v1/responses`, `/v1/messages`, `/embeddings`, `/v1/rerank`, `/v1/audio/speech`, `/v1/images/generations`), each against a deployment the test creates via `/model/new` and deletes on teardown +- `llm_translation/` - Azure realtime translation is explicitly skipped pending investigation of intermittent missing transcripts and remains unqualified. OpenAI translation and other Azure realtime cases remain enabled. LLM endpoint and provider-translation behavior: passthrough, custom pricing, OCR, and the non-chat inference endpoints (`/v1/responses`, `/v1/messages`, `/embeddings`, `/v1/rerank`, `/v1/audio/speech`, `/v1/images/generations`), each against a deployment the test creates via `/model/new` and deletes on teardown - `access_control/` - the gateway's authorization and error-shape contract: per-key model allow-lists, route-group permissions (`allowed_routes`), and unknown-model validation - `embeddings/` - the `/embeddings` endpoint across providers -- `batches/` - the `/batches` endpoint (placeholder until the first test lands) +- `batches/` - the `/batches` endpoint. GovCloud batch coverage is explicitly skipped until its infrastructure is provisioned. Other missing credentials and provider errors remain failures - `realtime/` - realtime websocket sessions, including the pipecat audio path - `quota_management/` - quota enforcement and accounting, one subfolder per behavior: `ratelimit/` (rpm/tpm blocks, window reset, pacing headers on live traffic), `budgets/` (budget definition, enforcement, and reset windows: key, team, tag, soft, multi-window), and `spend_tracking/` (spend logging and cost attribution on `/spend/*`) - `management/` - key/team/user/organization management routes: create/update/delete persistence via the info routes, team membership, and llm-only-key route denials (API surface, not Playwright) - `a2a/` - the A2A (agent-to-agent) surface: admin registration via `/v1/agents`, proxy-fronted card discovery at `/.well-known/agent-card.json`, and JSON-RPC `message/send` invocation, driving agents backed by the litellm completion bridge (a real provider) and asserting protocol-version normalization (0.3 vs 1.0) -- `mcp/` - the MCP server surface over api_key auth against the real Datadog remote MCP server (see "MCP suite: real Datadog only" below) +- `mcp/` - the MCP server surface over api_key auth against the real Datadog remote MCP server (see "MCP suite: real Datadog only" below). The semantic tool filter test turns on a proxy-wide setting, so it is marked `proxy_wide_config` and runs on the redeployed managed-files stack after the main run, never next to it - `logging/` - logging-integration delivery (datadog and friends) - `security/` - secret handling and log-leak protection -- `router/` - routing and reliability behavior (fallbacks, cooldowns) plus the memory tests (`test_reliability_memory_e2e.py`: every worker's RSS as read at collection time, before any test traffic, must sit under a fixed idle budget, the release-gate check for a DB-backed boot that idles near the pod limit the way v1.100.x did, and a few hundred failing requests with retries and fallbacks must not grow proxy RSS past a loose ceiling over the measured batches nor store a request snapshot past a fixed size, the release-gate check for the v1.100.0 retry-breadcrumb leak) -- `perf/` - performance-category tests, kept OUT of the main suite: throughput/load SLO tests are a different testing category from functional e2e (variance-driven, historically flaky) and live outside this suite until re-implemented as their own pipeline (LIT-5163). Do not add a live load test that runs in the default collection. What lives here: the weekly session-anomaly test (`test_weekly_session_anomaly_e2e.py`, Claude Code-shaped multi-turn sessions against real providers with ceilings on error rate, cache read/write, turn time, and spend, marked `weekly` and deselected unless `E2E_WEEKLY_ANOMALY` is set, driven by `.github/workflows/weekly_load_anomaly.yml`), the Redis chaos test (`test_redis_chaos_e2e.py`, locust load against mock deployments split round robin over `/chat/completions` and `/v1/messages`, one endpoint per simulated user, with `CLIENT PAUSE ALL` on the proxy's Redis mid-run to simulate it being down outright, asserting zero failed requests on every endpoint, budgeting RSS and CPU-per-request as ratios against the same run's healthy phase, and holding p50/p90/p99 latency and log-bytes-per-request to flat ceilings (a ratio cannot bound those two: an open breaker skips Redis instead of waiting on it, so the chaos phase can measure cheaper than baseline while still being far slower than a user should see), needs a proxy booted from `gateway/redis_chaos_ci_config.yml` on the same host with `E2E_PROXY_PID` and `E2E_PROXY_LOG` set, marked `redis_chaos`, deselected unless `E2E_PERF_TESTS` is set and excluded from the per-PR selector like the rest of `perf/`, driven by `.github/workflows/test-e2e-redis-chaos.yml` and by the Buildkite `e2e-redis-chaos` step in project-releaser, which runs the proxy, Postgres and Valkey co-located with pytest in one pod and sets the opt-in). New perf tests go here too, marked `perf`, behind the same `E2E_PERF_TESTS` opt-in. The perf cases (`test_perf_cases.py`, one `PerformanceTestCase` per module in `perf/cases/`, no `_e2e` suffix) are the request-performance runs. A case names what the gateway was deployed with (model groups and guardrails, written out in the gateway's config: the `proxy_config` block of project-releaser's perf helm values in the lane, `gateway/perf_ci_config.yml` locally, with each deployment's mock knobs in an `x-mock-knobs` extra header so the model ids are real ones like `gpt-6-luna` and `anthropic.claude-sonnet-5`) and lists what the test creates and sends: teams, Keycloak JWT users, virtual keys, `RequestShape`s (a coding-agent session from `perf/setup/corpus/` whose input-token size is drawn per request from the shape's range, with or without tools, and the output cap), a `Traffic` plan (seed, rps, request count, endpoint, shape and stream shares, or a `Ramp` that steps the rate up through the run, built with `ramped()`, whose plan carries each request's send second and whose run reports `sustained_rps`, the last step the pod held, scored in `perf/setup/ramp.py`, with every step's latency, completed rate, non-200s, CPU per request, Redis latency and Postgres connections cut from the samplers' time-stamped `Series` (`perf/setup/series.py`) to the step's window and emitted as `perf_ramp_step__` JUnit properties for the dashboard) and `Limit`s (one metric at one percentile under one ceiling, or over one floor for `sustained_rps`). The infra side lives in `perf/setup/`: `provision.py` checks the deployed config matches the case and builds the callers, `plan.py` draws the request list from the seed, `run.py` replays it from a separate Locust process (`locustfile.py`) that builds each body right before sending and records status, header, first-byte, first-token and total time per request, and `observe.py` joins all of that with what the mocks received and the workers' RSS to score every `Limit`. Limits are about what the caller sees and what the gateway costs: every non-blocked request is a 200 (`unexpected_status_count`), the seconds the gateway added per request at p50 and p99 (`gateway_added_seconds`, to the first token on streams), the client's time to the first token of a stream at p50 and p99 (`time_to_first_token_seconds`, mock delay included), worker memory growth (`memory_growth_megabytes`), and the Postgres statements and Redis commands a request waits on before it is forwarded (`postgres_calls_per_request`, `redis_calls_per_request`: auth and routing reads, the rate-limiter script), with the work the gateway does after the response or on a timer (spend writes, daily aggregates, config reloads) reported separately as `postgres_background_calls_per_request` and `redis_background_calls_per_request`; the same overhead as the gateway itself reports it, read from the `x-litellm-overhead-duration-ms` header per request (`litellm_overhead_seconds`, gated next to `gateway_added_seconds`, the outside reading of the same thing, so the two can be charted together) and the gateway's own end-to-end time from `x-litellm-response-duration-ms` (`litellm_response_seconds`), the run mean of the gateway's `litellm_redis_latency` histogram from a `/metrics` scrape before and after the run (`telemetry.py`, `prometheus_redis_latency_mean_seconds`), and the database's own view of the run from the same `pg_stat_statements` rows and a once-a-second `pg_stat_activity` sample: execution seconds per wall second (`postgres_active_sessions`, the average-active-sessions number RDS reports as DB load), the slowest statement's mean (`postgres_slowest_statement_seconds`, named in the detail) and the peak client connection count (`postgres_peak_connections`), each under a ceiling set from the first local runs and due a retune once the lane has its ten-run baseline; `datastore.py` reads `pg_stat_statements` before and after the run and holds a Redis `MONITOR` connection during it, sorts each statement by verb and table and each command by key, and the run output lists the top statements and commands per bucket so a red run names what grew. Whether a body, a guardrail call or a spend row is right is printed as a diagnostic, never a limit, that is the functional suites' job. The providers and the guardrail are out-of-process servers in `perf/setup/mocks/` (`server.py openai|anthropic|bedrock|guardrail`, each answering with a reply generated for the request in that provider's wire format, sized from the prompt and output cap, a tool call when tools were offered, waiting the case's `mock_latency` first, request logs at `/mock/requests` and `/mock/calls`), reached through `E2E_PERF_MOCK_*_URL` by both the gateway config and the test. Adding a perf test is adding a module with a `CASE` to `perf/cases/`; a new deployment or guardrail is a config change; a new metric is a name in `Metric` plus a branch in `observe.observe` +- `router/` - routing and reliability behavior (fallbacks, cooldowns) +- `perf/` - performance-category tests, kept OUT of the main suite: throughput/load SLO tests are a different testing category from functional e2e (variance-driven, historically flaky) and live outside this suite until re-implemented as their own pipeline (LIT-5163). Do not add a live load test that runs in the default collection. What lives here: the weekly session-anomaly test (`test_weekly_session_anomaly_e2e.py`, Claude Code-shaped multi-turn sessions against real providers with ceilings on error rate, cache read/write, turn time, and spend, marked `weekly` and deselected unless `E2E_WEEKLY_ANOMALY` is set, run by hand since its weekly workflow never had working Bedrock credentials), the Redis chaos test (`test_redis_chaos_e2e.py`, locust load against mock deployments split round robin over `/chat/completions` and `/v1/messages`, one endpoint per simulated user, with `CLIENT PAUSE ALL` on the proxy's Redis mid-run to simulate it being down outright, asserting zero failed requests on every endpoint, budgeting RSS and CPU-per-request as ratios against the same run's healthy phase, and holding p50/p90/p99 latency and log-bytes-per-request to flat ceilings (a ratio cannot bound those two: an open breaker skips Redis instead of waiting on it, so the chaos phase can measure cheaper than baseline while still being far slower than a user should see), needs a proxy booted from `gateway/redis_chaos_ci_config.yml` on the same host with `E2E_PROXY_PID` and `E2E_PROXY_LOG` set, marked `redis_chaos`, deselected unless `E2E_PERF_TESTS` is set and excluded from the per-PR selector like the rest of `perf/`, driven by `.github/workflows/test-e2e-redis-chaos.yml` and by the Buildkite `e2e-redis-chaos` step in project-releaser, which runs the proxy, Postgres and Valkey co-located with pytest in one pod and sets the opt-in). The memory tests (`test_reliability_memory_e2e.py`, run by the perf lane on its own fresh stack: every worker's RSS as read at collection time, before any test traffic, must sit under a fixed idle budget, the check for a DB-backed boot that idles near the pod limit the way v1.100.x did, and a few hundred failing requests with retries and fallbacks must not grow proxy RSS past a loose ceiling over the measured batches, the check for the v1.100.0 retry-breadcrumb leak). New perf tests go here too, marked `perf`, behind the same `E2E_PERF_TESTS` opt-in. The perf cases (`test_perf_cases.py`, one `PerformanceTestCase` per module in `perf/cases/`, no `_e2e` suffix) are the request-performance runs. A case names what the gateway was deployed with (model groups and guardrails, written out in the gateway's config: the `proxy_config` block of project-releaser's perf helm values in the lane, `gateway/perf_ci_config.yml` locally, with each deployment's mock knobs in an `x-mock-knobs` extra header so the model ids are real ones like `gpt-6-luna` and `anthropic.claude-sonnet-5`) and lists what the test creates and sends: teams, Keycloak JWT users, virtual keys, `RequestShape`s (a coding-agent session from `perf/setup/corpus/` whose input-token size is drawn per request from the shape's range, with or without tools, and the output cap), a `Traffic` plan (seed, rps, request count, endpoint, shape and stream shares, or a `Ramp` that steps the rate up through the run, built with `ramped()`, whose plan carries each request's send second and whose run reports `sustained_rps`, the last step the pod held, scored in `perf/setup/ramp.py`, with every step's latency, completed rate, non-200s, CPU per request, Redis latency and Postgres connections cut from the samplers' time-stamped `Series` (`perf/setup/series.py`) to the step's window and emitted as `perf_ramp_step__` JUnit properties for the dashboard) and `Limit`s (one metric at one percentile under one ceiling, or over one floor for `sustained_rps`). The infra side lives in `perf/setup/`: `provision.py` checks the deployed config matches the case and builds the callers, `plan.py` draws the request list from the seed, `run.py` replays it from a separate Locust process (`locustfile.py`) that builds each body right before sending and records status, header, first-byte, first-token and total time per request, and `observe.py` joins all of that with what the mocks received and the workers' RSS to score every `Limit`. Limits are about what the caller sees and what the gateway costs: every non-blocked request is a 200 (`unexpected_status_count`), the seconds the gateway added per request at p50 and p99 (`gateway_added_seconds`, to the first token on streams), the client's time to the first token of a stream at p50 and p99 (`time_to_first_token_seconds`, mock delay included), worker memory growth (`memory_growth_megabytes`), and the Postgres statements and Redis commands a request waits on before it is forwarded (`postgres_calls_per_request`, `redis_calls_per_request`: auth and routing reads, the rate-limiter script), with the work the gateway does after the response or on a timer (spend writes, daily aggregates, config reloads) reported separately as `postgres_background_calls_per_request` and `redis_background_calls_per_request`; the same overhead as the gateway itself reports it, read from the `x-litellm-overhead-duration-ms` header per request (`litellm_overhead_seconds`, gated next to `gateway_added_seconds`, the outside reading of the same thing, so the two can be charted together) and the gateway's own end-to-end time from `x-litellm-response-duration-ms` (`litellm_response_seconds`), the run mean of the gateway's `litellm_redis_latency` histogram from a `/metrics` scrape before and after the run (`telemetry.py`, `prometheus_redis_latency_mean_seconds`), and the database's own view of the run from the same `pg_stat_statements` rows and a once-a-second `pg_stat_activity` sample: execution seconds per wall second (`postgres_active_sessions`, the average-active-sessions number RDS reports as DB load), the slowest statement's mean (`postgres_slowest_statement_seconds`, named in the detail) and the peak client connection count (`postgres_peak_connections`), each under a ceiling set from the first local runs and due a retune once the lane has its ten-run baseline; `datastore.py` reads `pg_stat_statements` before and after the run and holds a Redis `MONITOR` connection during it, sorts each statement by verb and table and each command by key, and the run output lists the top statements and commands per bucket so a red run names what grew. Whether a body, a guardrail call or a spend row is right is printed as a diagnostic, never a limit, that is the functional suites' job. The providers and the guardrail are out-of-process servers in `perf/setup/mocks/` (`server.py openai|anthropic|bedrock|guardrail`, each answering with a reply generated for the request in that provider's wire format, sized from the prompt and output cap, a tool call when tools were offered, waiting the case's `mock_latency` first, request logs at `/mock/requests` and `/mock/calls`), reached through `E2E_PERF_MOCK_*_URL` by both the gateway config and the test. Adding a perf test is adding a module with a `CASE` to `perf/cases/`; a new deployment or guardrail is a config change; a new metric is a name in `Metric` plus a branch in `observe.observe` - `other/` - the holding-pen suite for the `other.*` registry cluster with no home of its own yet: the master-key auth gate, JWT auth (access tokens issued by a real Keycloak realm, `idp.py` plus `idp_realm.json`, whose JWKS the proxy's `JWT_PUBLIC_KEY_URL` points at, see CONTRIBUTING.md for the start command and config block), and the process-lifecycle health probes (liveness, public readiness, authenticated readiness diagnostics). Promote a cluster out once it is large/stable enough for its own suite - `secret_manager/` - the gateway's `key_management_system` against a real secret manager: deployment keys resolved from it (`os.environ/` where the name exists only in the manager) and virtual keys written to and deleted from it. The tests are backend-agnostic and each backend is its own lane, because the setting is global to the proxy: `E2E_SECRET_MANAGER=` opts in and picks the backend from `secret_backends.BACKENDS`, the proxy is booted from `gateway/secret_manager__ci_config.yml` against the live manager, and the tests reach that manager through the backend's `SecretStore` (`secret_store_.py`). A test needing something not every backend does carries `requires_capability(...)` and is deselected on lanes that lack it. `secret_manager/backend.sh up ` runs a backend in Docker and writes the proxy's and the tests' env. Marked `secret_manager`, deselected unless `E2E_SECRET_MANAGER` is set, and kept out of the per-PR selector. Backends today: `hashicorp_vault` and `cyberark` (CyberArk Conjur, which cannot delete, so the delete test is Vault-only) - `gateway/` - proxy configuration only (`litellm-config.yml`). No tests -- `claude_code/` - the Claude Code compatibility matrix: drives the real `claude` CLI (and HTTP probes) against a proxy for each feature x provider cell, reporting tagged-union outcomes via the `compat_result` fixture. Ships its own driver/builder/publisher, covered by `tests/e2e_harness/claude_code/`. The HTTP probes ride the shared transport (`ProxyClient.count_tokens` / `ProxyClient.messages`). The CLI-driving path stays bespoke +- `claude_code/` - the Claude Code compatibility matrix: drives the real `claude` CLI (and HTTP probes) against a proxy for each feature x provider cell, reporting tagged-union outcomes via the `compat_result` fixture. Ships its own driver/builder/publisher, covered by `tests/e2e_harness/claude_code/`. The HTTP probes ride the shared transport (`ProxyClient.count_tokens` / `ProxyClient.messages`). The CLI-driving path stays bespoke. `pr_gate_version_resolver.py` only forwards to `cli_harness/npm_version_resolver.py`, because the Buildkite runner images still run that path and install @latest without it +- `cli_harness/` - no tests, only the plumbing every suite that drives a real coding-agent CLI shares: `npm_version_resolver.py` picks the CLI release to install (the newest npm release at least three days old, run by CI as `python tests/e2e/cli_harness/npm_version_resolver.py `, stdlib only), `lockdown.py` gives the CLI subprocess an allowlisted env and a fresh empty HOME so it never sees the runner's credentials or dotfiles, and `rate_limiter.py` is the cross-process token bucket per upstream that keeps parallel CLI runs under one request rate. Covered by `tests/e2e_harness/cli_harness/`. Code only one CLI suite needs stays in that suite +- `codex/` - the Codex compatibility suite: drives the real `codex exec --json` CLI through the gateway, one class per row (the command round trip, a file edit with the patch tool, a long session that follows a chain of files one command at a time, and auto-compaction, where Codex reads a random value, compacts through the gateway and is asked for the value after the file is deleted), each row parametrized over `SETUPS` in `setups.py`, one `pytest.param` per setup (GPT on Bedrock Mantle, Bedrock Runtime, Azure OpenAI and OpenAI, plus Claude on Bedrock). A row with one setup broken by a known bug parametrizes over `with_expected_failure(, reason=...)`, which is `SETUPS` with a strict xfail on that one setup. The `setup` fixture registers that setup's deployment under a fresh name via `/model/new` and the `codex` fixture makes a key scoped to it, and both are deleted on teardown. `harness.py` gives each test a throwaway HOME and CODEX_HOME whose `config.toml` points a custom `responses` provider at the gateway and has Codex read its model list from the gateway's `/v1/models` (`model_catalog_url` on the provider), with the sandbox on (`workspace-write`) and approvals off, and runs the CLI under `cli_harness`'s env lockdown and rate limiter. `run.py` reads the JSONL events into a `CodexRun`: the commands with their output, the patched files, the last agent message as `answer`, the usage and the errors, where an error's `status_code` is what lets the suite's 5xx rerun rule catch a turn Codex gave up on. `codex exec --json` prints nothing when Codex compacts, so `rollout.py` reads the compactions from the thread's rollout file under CODEX_HOME/sessions, and a compaction is remote when its replacement history kept the provider's `compaction` item. `exec` and `resume` take `compact_after_tokens`, which forces Codex's remote compaction (`compaction_trigger` items over `/v1/responses`, the path Codex otherwise only takes for OpenAI and Azure) on the gateway provider and compacts once the context grows past that many tokens. A test passes on a random value the model can only learn through the gateway, never on the model's wording or the exact command it typed. It needs `codex` on PATH and fails without it. The Bedrock Runtime setup is explicitly skipped until stage IAM permits `bedrock:InvokeModel` on its default project. The other setups still run, and skipped Runtime cases do not qualify that route. Covered by `tests/e2e_harness/codex/` - `ui/` - the Admin UI browser suite: Playwright in TypeScript, driving the dashboard served by a live proxy on port 4000 (seeded postgres + mock LLM upstream, see its `run_e2e.sh`). It is a self-contained npm package with its own lockfile and does not use the Python harness, pytest markers, or the shared transport. The Python rules in this file (typed models, `Result` unions, basedpyright zero-error gate) do not apply inside it. Its only Python file, `fixtures/mock_llm_server/server.py`, is excluded from the e2e basedpyright gate via the root `pyrightconfig.json`. Its specs follow the dashboard's rule against testing what shadcn and Base UI already guarantee, in `ui/litellm-dashboard/AGENTS.md` ## MCP suite: real Datadog only @@ -98,7 +100,7 @@ Each suite provides its own `client` fixture (see `llm_translation/passthrough_c Request and response bodies are typed pydantic models in `models.py`. Only the fields a test reads are modelled, and nothing passes raw dicts. Outcomes come back as a `Result[R]` tagged union (`Success`, `NetworkError`, `UnauthorizedError`, `RateLimitedError`, `ValidationError`, `UnknownApiError`). Handle them with `match`, or call `unwrap(...)` when a non-success should fail the test. The harness hard-fails and never skips: a test marked `e2e` fails when no proxy answers its liveness probe, and once a request reaches the proxy any wrong behavior is likewise a hard failure, so a missing proxy turns the run red instead of being mistaken for a pass -Mark live tests with `@pytest.mark.e2e` (on the class or the module). Coverage of the harness itself lives outside the suite in `tests/e2e_harness/` (see its `AGENTS.md`) and runs without a proxy, so nothing under `tests/e2e/` is a markerless test. Add `@pytest.mark.quiet_stack` to a test that measures the proxy itself (RSS, latency): the shared stack lock in `stack_lock.py` then runs it while no other test on the host is hitting the stack, marked or not, so the reading depends only on the test's own traffic. Use `scoped_key` for a fresh all-models key that auto-deletes, `resources` when you need to create and tear down more than a key, and `unique_marker()` from `e2e_config` to keep prompts, tags, and customer ids from colliding across concurrent runs and the shared response cache +Mark live tests with `@pytest.mark.e2e` (on the class or the module). Coverage of the harness itself lives outside the suite in `tests/e2e_harness/` (see its `AGENTS.md`) and runs without a proxy, so nothing under `tests/e2e/` is a markerless test. A test that measures the proxy itself (RSS, latency) cannot share the stack with the rest of the suite, so it goes in `perf/`, marked `perf`. Use `scoped_key` for a fresh all-models key that auto-deletes, `resources` when you need to create and tear down more than a key, and `unique_marker()` from `e2e_config` to keep prompts, tags, and customer ids from colliding across concurrent runs and the shared response cache ## Record and replay fixtures @@ -324,5 +326,10 @@ other... - spin up a local proxy by running the litellm proxy locally (`litellm --config .yml --port 4000`, see CONTRIBUTING.md), make sure all tests pass. if a test fails due to an internally found issue, let users know to create a linear ticket for it. - do not use xfail markers, tests should be written in a form that the end user expects it to pass +- the `codex/` suite is the one exception: a single setup that a LiteLLM or provider bug breaks may carry `pytest.mark.xfail(strict=True, reason=...)` with a plain one-sentence reason on that setup's `pytest.param`, so it keeps running and goes red once the bug is fixed. Strict only, and never on a flaky setup (one that passes some runs and fails others) - a cell addresses the stack through its front door (`PROXY_BASE_URL`) the way a customer does, never a gateway pod by address, and proves a cross-replica property with N independent calls through that door, naming the miss odds (2^-N at two pods) in its docstring. `PROXY_REPLICA_URLS` is for read-backs that are per pod by nature (polling until a management write has converged on every replica, `/metrics`, RSS), never for steering the scenario a cell asserts on at a chosen pod + +## Provider response cache + +The provider response cache can share the stage Valkey instance through a `rediss://` URL. Set `E2E_PROVIDER_CACHE_REDIS_CLUSTER=1` for a cluster-aware client, including ElastiCache Serverless. Keep the dedicated HMAC key and namespace, and restrict test cleanup to keys in the test's own namespace diff --git a/tests/e2e/batches/COVERAGE.md b/tests/e2e/batches/COVERAGE.md index 1ede9c89b97..ac6f9cd08e4 100644 --- a/tests/e2e/batches/COVERAGE.md +++ b/tests/e2e/batches/COVERAGE.md @@ -11,8 +11,9 @@ cost write-back via a cross-run marker baton (design below). Only supported cells are tested. The capability table in `capabilities.py` holds one row per supported (provider, scenario) pair, so there are no skipped cells in the -parametrized run. The batches suite never skips: missing provider creds or upstream -failures are hard test failures (see `tests/e2e/AGENTS.md`). +parametrized run. Missing provider creds or upstream failures are hard test failures +(see `tests/e2e/AGENTS.md`). GovCloud is explicitly skipped until its infrastructure +is provisioned and does not count as qualified coverage. | Provider | create | retrieve | cancel | list | content download | file backing | |-----------|--------|----------|--------|------|------------------|--------------| diff --git a/tests/e2e/batches/test_batches_e2e.py b/tests/e2e/batches/test_batches_e2e.py index b7a52da5902..eb83db73199 100644 --- a/tests/e2e/batches/test_batches_e2e.py +++ b/tests/e2e/batches/test_batches_e2e.py @@ -1210,6 +1210,7 @@ def _govcloud_params() -> LiteLLMParamsBody: ) +@pytest.mark.skip(reason="GovCloud E2E infrastructure is not provisioned") class TestBedrockBatchGovCloud: """Bedrock batch lifecycle in the AWS GovCloud partition (us-gov-west-1). diff --git a/tests/e2e/claude_code/cli_driver.py b/tests/e2e/claude_code/cli_driver.py index 6f7a7b39a39..599cfe6aa75 100644 --- a/tests/e2e/claude_code/cli_driver.py +++ b/tests/e2e/claude_code/cli_driver.py @@ -16,23 +16,18 @@ from __future__ import annotations import json import os import re -import shutil import subprocess import sys import tempfile import time from concurrent.futures import ThreadPoolExecutor, as_completed from dataclasses import dataclass, field -from typing import Any, Callable, Dict, List, Mapping, Optional, Sequence, Tuple, Union +from typing import Any, Callable, Dict, Final, List, Mapping, Optional, Sequence, Tuple, Union +from cli_harness.lockdown import isolated_home, locked_down_env +from cli_harness.rate_limiter import RateBucket, RateLimiter, get_default_limiter from e2e_metadata import step -from claude_code.rate_limiter import ( - RateLimiter, - get_default_limiter, - infer_provider, -) - CLAUDE_CLI_DEFAULT = "claude" # 120s is fine for a single isolated CLI call against an unloaded # upstream, but the matrix run launches up to 75 concurrent calls and @@ -77,61 +72,36 @@ Anthropic / Bedrock / Vertex) to reset. Both knobs are env-tunable so a matrix run can trade wall time for resilience without code edits; retries=0 disables the behavior entirely.""" -# Env vars the `claude` Node CLI legitimately needs to function: -# locating its own binary + node, basic locale/terminal plumbing. -# Deliberately excludes every credential-bearing var that the -# surrounding CI job sets for the proxy (ANTHROPIC_API_KEY, AWS_*, -# AZURE_*, VERTEXAI_CREDENTIALS, GITHUB_TOKEN, OPENAI_API_KEY, -# DATABASE_URL, ...). The CLI talks to the proxy via the explicit -# ANTHROPIC_BASE_URL/ANTHROPIC_AUTH_TOKEN we set below — it has no -# business reading the proxy's upstream credentials, and a -# compromised CLI release shouldn't be able to exfiltrate them out -# of the CI environment. -# -# `HOME` is intentionally NOT in this list: see `_make_isolated_home` -# below. We give the CLI a fresh empty per-invocation HOME so a -# compromised claude package or a model-directed `Read` tool call -# can't reach files like `~/.config/gh/hosts.yml`, `~/.ssh/id_rsa`, -# or `~/.bash_history` on the cron VM (and on the CircleCI executor -# the same isolation prevents accidentally exposing checkout-adjacent -# files even though the runner home is ephemeral there). -_CLI_ENV_ALLOWLIST: tuple = ( - "PATH", - "USER", - "LOGNAME", - "SHELL", - "TERM", - "TMPDIR", - "LANG", - "LC_ALL", - "LC_CTYPE", - "NODE_PATH", - "NVM_DIR", - "NVM_BIN", -) +def infer_provider(model: str) -> RateBucket: + """Map a model alias to its compat-matrix rate bucket. -def _make_isolated_home() -> str: - """Create a fresh empty HOME directory for a single `claude` subprocess. - - The CLI needs *a* writable HOME (it caches per-session state under - `$HOME/.claude/projects//`), but it has no legitimate need - for the *user's* HOME. Handing it the real one means a compromised - `@anthropic-ai/claude-code` release, or a model-directed `Read` - tool call during a PDF/vision cell, can read host files like - `~/.config/gh/hosts.yml` (GitHub CLI host token), `~/.ssh/`, - `~/.bash_history`, or any other dotfile under the runtime user's - home. On the cron VM the runtime user is a real interactive - account (`mateo`) with a populated home directory, so this is a - real exfiltration surface. - - The directory is created under `tempfile.gettempdir()` (which is - `/tmp` on Linux; under systemd's `PrivateTmp=true` that's a - per-service tmpfs that the service user can't otherwise reach). - Caller is responsible for `shutil.rmtree`-ing it after the - subprocess exits. + The matrix column layout is fixed; aliases registered in the proxy + encode the provider via a suffix (`-bedrock-converse`, + `-bedrock-invoke`, `-azure`, `-vertex`, `-openai`, `-azure-openai`, + `-bedrock-mantle`) or its absence (Anthropic). Order matters: + `-azure-openai` also ends with `-openai`, and the bedrock suffixes + all contain `bedrock`, so the more-specific suffixes are tested + first. """ - return tempfile.mkdtemp(prefix="claude-cli-home-") + if not model: + raise ValueError("model must be a non-empty string") + lower: Final = model.lower() + if lower.endswith("-azure-openai"): + return RateBucket.AZURE_OPENAI + if lower.endswith("-openai"): + return RateBucket.OPENAI + if lower.endswith("-bedrock-mantle"): + return RateBucket.BEDROCK_MANTLE + if lower.endswith("-bedrock-converse"): + return RateBucket.BEDROCK_CONVERSE + if lower.endswith("-bedrock-invoke"): + return RateBucket.BEDROCK_INVOKE + if lower.endswith("-azure"): + return RateBucket.AZURE + if lower.endswith("-vertex"): + return RateBucket.VERTEX_AI + return RateBucket.ANTHROPIC _FIXED_CLI_USER_ID = "0" * 64 @@ -176,7 +146,7 @@ def _stable_cli_state() -> Tuple[str, str]: Pinning both makes the bodies repeatable across builds. This narrows what survives rather than widening it: HOME stays fresh and - empty per invocation, so the isolation `_make_isolated_home` describes is + empty per invocation, so the isolation `cli_harness.lockdown` describes is unchanged, and the CLI's own state no longer outlives the pod either. The working directory is deliberately not the checkout, so a model-directed `Read` sees an empty directory instead of the repository. @@ -291,38 +261,26 @@ def run_claude( cmd.append("--") cmd.append(prompt) - # Build a minimal env for the CLI subprocess: only the allowlisted - # process-runtime vars from os.environ, plus the explicit proxy - # creds, plus any caller-supplied overrides. See _CLI_ENV_ALLOWLIST - # above for the security rationale. - env: Dict[str, str] = { - key: os.environ[key] for key in _CLI_ENV_ALLOWLIST if key in os.environ - } - env["ANTHROPIC_BASE_URL"] = base_url - env["ANTHROPIC_AUTH_TOKEN"] = api_key - env["DISABLE_AUTOUPDATER"] = "1" - # Hand the CLI a fresh empty HOME so a compromised claude package - # or a model-directed Read tool call can't see the runtime user's - # real dotfiles. Created here, removed in the `finally` below - # regardless of how the subprocess exits. - isolated_home = _make_isolated_home() - env["HOME"] = isolated_home - config_dir, workspace = _stable_cli_state() - env["CLAUDE_CONFIG_DIR"] = config_dir - if extra_env: - env.update(extra_env) - # Throttle by provider *before* launching the CLI. Doing this here # (rather than per-test) means every code path that lands on # `run_claude` is rate-limited automatically — including # `run_claude_models_parallel`, which is the hot path during the # full matrix run. limiter = rate_limiter if rate_limiter is not None else get_default_limiter() - provider = infer_provider(model) - limiter.acquire(provider) - run_fn = runner or subprocess.run - try: + with isolated_home("claude-cli-home-") as home: + config_dir, workspace = _stable_cli_state() + env = locked_down_env( + home=home, + overrides={ + "ANTHROPIC_BASE_URL": base_url, + "ANTHROPIC_AUTH_TOKEN": api_key, + "DISABLE_AUTOUPDATER": "1", + "CLAUDE_CONFIG_DIR": config_dir, + **(extra_env or {}), + }, + ) + limiter.acquire(infer_provider(model)) try: completed = run_fn( cmd, @@ -340,15 +298,6 @@ def run_claude( ) from exc except subprocess.TimeoutExpired as exc: raise ClaudeCLIError(f"claude CLI timed out after {timeout}s") from exc - finally: - # Best-effort cleanup. If the subprocess wrote a `.claude/` - # session dir under the isolated HOME, we remove it here so - # parallel matrix runs don't accumulate per-call tmpdirs. - # `ignore_errors=True` because rmtree races with any - # not-yet-reaped child (SIGTERM'd `claude` on a host-side - # timeout) are benign — the next matrix run starts from a - # fresh tmpdir anyway. - shutil.rmtree(isolated_home, ignore_errors=True) events = _parse_stream_json(completed.stdout or "") text = _extract_assistant_text(events) diff --git a/tests/e2e/claude_code/conftest.py b/tests/e2e/claude_code/conftest.py index b2442d492cf..14201ef6846 100644 --- a/tests/e2e/claude_code/conftest.py +++ b/tests/e2e/claude_code/conftest.py @@ -597,14 +597,21 @@ def _build_control_plane_client(proxy_config: ProxyConfig): ) -def _register_deployment(proxy, deployment: CompatDeployment) -> str: - """Register one deployment and return its proxy-assigned model_id - once it is servable on the data plane. The aliases are shared by every - cell and, under xdist, by every worker, so no call to them belongs to - one test and none is cached: the matrix exists to reach real providers.""" - return proxy.create_model( - deployment.model_name, - deployment.litellm_params, +def _register_deployments(proxy, deployments: tuple[CompatDeployment, ...]): + """The aliases are shared by every cell and, under xdist, by every worker, + so no call to them belongs to one test and none is cached: the matrix + exists to reach real providers.""" + from models import ModelInfoBody, ModelNewBody + + return proxy.register_models( + tuple( + ModelNewBody( + model_name=deployment.model_name, + litellm_params=deployment.litellm_params, + model_info=ModelInfoBody(), + ) + for deployment in deployments + ), provider_live=True, ) @@ -632,18 +639,14 @@ def _compat_models_registered() -> Any: yield return + from proxy_client import ModelNotRegistered, ModelRegistered from requests import RequestException proxy = _build_control_plane_client(proxy_config) - registered_ids: list[str] = [] - failures: list[tuple[str, str]] = [] + registrations = _register_deployments(proxy, load_all_deployments()) + registered_ids = tuple(r.model_id for r in registrations if isinstance(r, ModelRegistered)) + failures = tuple((r.model_name, r.reason) for r in registrations if isinstance(r, ModelNotRegistered)) try: - for deployment in load_all_deployments(): - try: - model_id = _register_deployment(proxy, deployment) - registered_ids.append(model_id) - except (AssertionError, RequestException) as exc: - failures.append((deployment.model_name, str(exc))) if failures: summary = "\n".join( f" - {name}: {reason}" for name, reason in failures diff --git a/tests/e2e/claude_code/cron_vm/README.md b/tests/e2e/claude_code/cron_vm/README.md index 4c16b6e237a..7451e86e09b 100644 --- a/tests/e2e/claude_code/cron_vm/README.md +++ b/tests/e2e/claude_code/cron_vm/README.md @@ -52,7 +52,7 @@ than as a GitHub Action or on a dedicated VM. Trade-offs: the stable venv doesn't install) is never loaded. The tag's own `tests/e2e/` is deliberately not used. 3. **Resolves and installs the Claude Code CLI under test**: - `pr_gate_version_resolver.py` (run on the venv, the image has no + `tests/e2e/cli_harness/npm_version_resolver.py` (run on the venv, the image has no Python of its own) picks the newest `@anthropic-ai/claude-code` npm release published at least 3 days ago, the same buffer the PR gate uses, unless `CLAUDE_CODE_VERSION` pins one, and diff --git a/tests/e2e/claude_code/cron_vm/run_daily.sh b/tests/e2e/claude_code/cron_vm/run_daily.sh index 17b628b8c78..749d5166a34 100755 --- a/tests/e2e/claude_code/cron_vm/run_daily.sh +++ b/tests/e2e/claude_code/cron_vm/run_daily.sh @@ -8,7 +8,7 @@ # Releases API. # 2. Update a long-lived worktree at $WORKTREE to that tag and `uv sync` it. # 3. Resolve the Claude Code CLI version under test (the newest npm -# release at least 3 days old, via pr_gate_version_resolver.py, or +# release at least 3 days old, via cli_harness/npm_version_resolver.py, or # $CLAUDE_CODE_VERSION when set) and download that release's # linux-x64 binary into the run's scratch dir, checksum-verified # against the vendor's release manifest (install_claude_code.sh). @@ -329,7 +329,7 @@ PROXY_CONFIG="${WORKTREE}/tests/e2e/claude_code/test_config.yaml" if [[ -z "${CLAUDE_CODE_VERSION}" ]]; then CLAUDE_CODE_VERSION="$( cd "${WORKTREE}" \ - && "${WORKTREE_UV}" run --no-sync python "${POPULATOR_DIR}/../pr_gate_version_resolver.py" + && "${WORKTREE_UV}" run --no-sync python "${POPULATOR_DIR}/../../cli_harness/npm_version_resolver.py" @anthropic-ai/claude-code )" || die "could not resolve the Claude Code version to test" log "resolved claude code: ${CLAUDE_CODE_VERSION}" else diff --git a/tests/e2e/claude_code/http_probe.py b/tests/e2e/claude_code/http_probe.py index a6c587f98cf..390ef4c24d4 100644 --- a/tests/e2e/claude_code/http_probe.py +++ b/tests/e2e/claude_code/http_probe.py @@ -31,8 +31,7 @@ from __future__ import annotations from dataclasses import dataclass from typing import TYPE_CHECKING -from pydantic import BaseModel - +from cli_harness.rate_limiter import RateLimiter, get_default_limiter from e2e_http import ( NetworkError, RateLimitedError, @@ -59,12 +58,9 @@ from models import ( JsonSchemaProperty, ToolInputSchema, ) +from pydantic import BaseModel -from claude_code.rate_limiter import ( - RateLimiter, - get_default_limiter, - infer_provider, -) +from claude_code.cli_driver import infer_provider if TYPE_CHECKING: from proxy_client import ProxyClient diff --git a/tests/e2e/claude_code/pr_gate_version_resolver.py b/tests/e2e/claude_code/pr_gate_version_resolver.py index 756dafb7d73..72392f8a0ae 100644 --- a/tests/e2e/claude_code/pr_gate_version_resolver.py +++ b/tests/e2e/claude_code/pr_gate_version_resolver.py @@ -1,155 +1,16 @@ -"""Claude Code PR-Gate Version Resolver. - -Resolves the `@anthropic-ai/claude-code` npm version that the PR-gate CI -job installs. Selects the newest version (by publish timestamp) whose -publish timestamp is at least 3 days old. The 3-day window is a security -review buffer — see PRD #26476, "Version resolvers". - -Two surfaces: - -- ``resolve_pr_gate_version(...)`` — the importable function. Accepts - pre-fetched npm metadata (for unit tests) or a custom ``fetcher`` - callable. The default fetcher hits the public npm registry. -- ``python -m claude_code.pr_gate_version_resolver`` — prints the - resolved version string to stdout, suitable for piping into a shell - ``$(...)`` substitution inside the CircleCI job. - -The CLI form is what CircleCI runs at job start; engineers reading the -job log can see the selected version on a single line above the -``npm install -g`` step (acceptance criterion: "the selected Claude -Code version is logged in the CI output"). -""" +"""The path the Buildkite runner images run (`python3 tests/e2e/claude_code/pr_gate_version_resolver.py`) to pick the +Claude Code release they install. They fall back to @latest when this file is missing, so keep it until they call +`cli_harness/npm_version_resolver.py` themselves.""" from __future__ import annotations -import json +import subprocess import sys -import urllib.request -from datetime import datetime, timedelta, timezone -from typing import Callable, Mapping, Optional - -PACKAGE_NAME = "@anthropic-ai/claude-code" -NPM_REGISTRY_URL = "https://registry.npmjs.org/{package}" -DEFAULT_MIN_AGE = timedelta(days=3) -DEFAULT_FETCH_TIMEOUT_SECONDS = 30 - -# npm's `time` map mixes per-version timestamps with these meta keys. -_TIME_META_KEYS = frozenset({"created", "modified"}) - - -class NoEligibleVersionError(RuntimeError): - """Raised when no version in the npm metadata satisfies the min-age cutoff.""" - - -def _parse_npm_timestamp(value: str) -> datetime: - """Parse the ISO-8601 timestamps npm emits (always UTC, may use ``Z``).""" - if value.endswith("Z"): - value = value[:-1] + "+00:00" - parsed = datetime.fromisoformat(value) - if parsed.tzinfo is None: - parsed = parsed.replace(tzinfo=timezone.utc) - return parsed - - -def _default_fetcher(package_name: str) -> dict: - """Fetch the npm packument for ``package_name`` over HTTPS. - - Uses urllib (stdlib) so this module has no extra dependencies in the - CI environment. Returns the raw JSON dict. - """ - # urllib.parse.quote would encode the leading '@' / '/' which the - # npm registry expects literally; do a minimal hand-roll instead. - url = NPM_REGISTRY_URL.format(package=package_name.replace("/", "%2F")) - req = urllib.request.Request(url, headers={"Accept": "application/json"}) - with urllib.request.urlopen( # noqa: S310 — registry URL is constant - req, timeout=DEFAULT_FETCH_TIMEOUT_SECONDS - ) as response: - body = response.read().decode("utf-8") - return json.loads(body) - - -def resolve_pr_gate_version( - *, - metadata: Optional[Mapping] = None, - fetcher: Optional[Callable[[str], Mapping]] = None, - as_of: Optional[datetime] = None, - min_age: timedelta = DEFAULT_MIN_AGE, - package_name: str = PACKAGE_NAME, -) -> str: - """Return the newest npm version of ``package_name`` published >= ``min_age`` ago. - - "Newest" means newest by **publish time**, not semver string order — - if a patch lands on an older major after a newer release, the - patched line is the eligible one. A version npm has unpublished keeps - its ``time`` entry but drops out of ``versions``, so only versions - still present in ``versions`` are candidates. - - Args: - metadata: Pre-fetched npm packument (skips the HTTP call). Useful - for unit tests. - fetcher: Callable taking a package name and returning the - packument. Defaults to a stdlib HTTPS fetcher. - as_of: The clock used to decide whether a version is "old - enough". Defaults to ``datetime.now(timezone.utc)``. - min_age: Minimum publish age. Defaults to 3 days. - package_name: Defaults to ``@anthropic-ai/claude-code``. - - Raises: - NoEligibleVersionError: when no version in the registry meets - the age cutoff. - """ - if metadata is None: - fetch = fetcher or _default_fetcher - metadata = fetch(package_name) - - times = metadata.get("time") or {} - versions = metadata.get("versions") or {} - if as_of is None: - as_of = datetime.now(timezone.utc) - cutoff = as_of - min_age - - eligible: list[tuple[datetime, str]] = [] - for version, raw_ts in times.items(): - if version in _TIME_META_KEYS: - continue - if version not in versions: - continue - if not isinstance(raw_ts, str): - continue - if "-" in version: - continue - published = _parse_npm_timestamp(raw_ts) - if published <= cutoff: - eligible.append((published, version)) - - if not eligible: - raise NoEligibleVersionError( - f"no version of {package_name} is at least {min_age} old " - f"as of {as_of.isoformat()}" - ) - - eligible.sort(key=lambda pair: pair[0], reverse=True) - return eligible[0][1] - - -def _main(argv: list[str]) -> int: - """Print the resolved version to stdout. Exit code 0 on success. - - Stderr carries the human-readable announcement so the version can be - captured cleanly with ``$(python -m ...)`` in shell. - """ - try: - version = resolve_pr_gate_version() - except Exception as exc: # noqa: BLE001 — CLI surface, want everything - print(f"pr_gate_version_resolver: {exc}", file=sys.stderr) # noqa: T201 - return 1 - print( # noqa: T201 - f"pr_gate_version_resolver: selected {PACKAGE_NAME}@{version}", - file=sys.stderr, - ) - print(version) # noqa: T201 - return 0 +from pathlib import Path +from typing import Final +_RESOLVER: Final = Path(__file__).resolve().parent.parent / "cli_harness" / "npm_version_resolver.py" +_PACKAGE: Final = "@anthropic-ai/claude-code" if __name__ == "__main__": - raise SystemExit(_main(sys.argv[1:])) + raise SystemExit(subprocess.run((sys.executable, "-I", str(_RESOLVER), _PACKAGE), check=False).returncode) diff --git a/tests/e2e/claude_code/rate_limiter.py b/tests/e2e/claude_code/rate_limiter.py deleted file mode 100644 index 5818338ff7f..00000000000 --- a/tests/e2e/claude_code/rate_limiter.py +++ /dev/null @@ -1,378 +0,0 @@ -"""Cross-process token-bucket rate limiter for the Claude Code compat suite. - -The compat matrix runs 75 live `claude` CLI invocations (25 cells × 3 -Claude tiers per cell). When pytest-xdist fans these out across worker -processes, each worker would maintain its own in-memory rate limiter -and the *aggregate* request rate hitting any one upstream provider -would be `workers × per-worker rate` — exactly the situation that -trips Anthropic / Azure / Bedrock / Vertex 429s in the middle of a -matrix run and silently flips green cells red. - -The fix is a **shared, cross-process** token bucket per provider, -backed by a small JSON state file and an OS-level `flock`. Each -`run_claude` invocation acquires one token (sleeping if the bucket is -empty) before launching the CLI; refills happen lazily based on wall -time, so workers can be killed and restarted without losing or -double-spending budget. - -Configuration is driven entirely by environment variables so a -binary-search workflow can shift per-provider rates without code -edits: - - LITELLM_COMPAT_RATE_ANTHROPIC (req/s, default 5.0) - LITELLM_COMPAT_RATE_AZURE (req/s, default 5.0) - LITELLM_COMPAT_RATE_VERTEX_AI (req/s, default 5.0) - LITELLM_COMPAT_RATE_BEDROCK_CONVERSE (req/s, default 5.0) - LITELLM_COMPAT_RATE_BEDROCK_INVOKE (req/s, default 5.0) - LITELLM_COMPAT_RATE_OPENAI (req/s, default 5.0) - LITELLM_COMPAT_RATE_AZURE_OPENAI (req/s, default 5.0) - LITELLM_COMPAT_RATE_BEDROCK_MANTLE (req/s, default 5.0) - LITELLM_COMPAT_RATE_BURST (per-bucket burst override; - default = rate) - LITELLM_COMPAT_RATE_STATE_DIR (state file directory; - default = $TMPDIR/litellm-claude-compat-ratelimit) - -A rate of 0 (or any non-positive value) disables throttling for that -provider — useful when you trust the upstream to handle the burst or -when running unit-test-shaped workloads that never actually hit the -network. - -The provider id is inferred from the model id by `infer_provider`, -mirroring the matrix's column layout (`anthropic`, `azure`, -`vertex_ai`, `bedrock_converse`, `bedrock_invoke`, `openai`, -`azure_openai`, `bedrock_mantle`). The `vertex_ai_gpt` matrix column -has no bucket: its cells are static not_applicable stubs that never -reach the network. -""" - -from __future__ import annotations - -import contextlib -import json -import math -import os -import tempfile -import time -from dataclasses import dataclass -from pathlib import Path -from typing import Dict, Iterator, Mapping, Optional - -# `fcntl` is POSIX-only; the suite is Linux/macOS only, so we don't -# attempt a Windows fallback. Importing at module load fails fast on -# the (currently non-existent) Windows runner so we don't silently -# degrade to no-locking behavior. -import fcntl - -PROVIDER_ANTHROPIC = "anthropic" -PROVIDER_AZURE = "azure" -PROVIDER_VERTEX_AI = "vertex_ai" -PROVIDER_BEDROCK_CONVERSE = "bedrock_converse" -PROVIDER_BEDROCK_INVOKE = "bedrock_invoke" -PROVIDER_OPENAI = "openai" -PROVIDER_AZURE_OPENAI = "azure_openai" -PROVIDER_BEDROCK_MANTLE = "bedrock_mantle" - -ALL_PROVIDERS = ( - PROVIDER_ANTHROPIC, - PROVIDER_AZURE, - PROVIDER_VERTEX_AI, - PROVIDER_BEDROCK_CONVERSE, - PROVIDER_BEDROCK_INVOKE, - PROVIDER_OPENAI, - PROVIDER_AZURE_OPENAI, - PROVIDER_BEDROCK_MANTLE, -) - -DEFAULT_RATE = 5.0 # req/s per provider, conservative starting point -RATE_ENV_PREFIX = "LITELLM_COMPAT_RATE_" -BURST_ENV = "LITELLM_COMPAT_RATE_BURST" -STATE_DIR_ENV = "LITELLM_COMPAT_RATE_STATE_DIR" -DEFAULT_STATE_DIR_NAME = "litellm-claude-compat-ratelimit" - - -def infer_provider(model: str) -> str: - """Map a model alias to its compat-matrix provider id. - - The matrix column layout is fixed; aliases registered in the proxy - encode the provider via a suffix (`-bedrock-converse`, - `-bedrock-invoke`, `-azure`, `-vertex`, `-openai`, `-azure-openai`, - `-bedrock-mantle`) or its absence (Anthropic). Order matters: - `-azure-openai` also ends with `-openai`, and the bedrock suffixes - all contain `bedrock`, so the more-specific suffixes are tested - first. - """ - if not model: - raise ValueError("model must be a non-empty string") - lower = model.lower() - if lower.endswith("-azure-openai"): - return PROVIDER_AZURE_OPENAI - if lower.endswith("-openai"): - return PROVIDER_OPENAI - if lower.endswith("-bedrock-mantle"): - return PROVIDER_BEDROCK_MANTLE - if lower.endswith("-bedrock-converse"): - return PROVIDER_BEDROCK_CONVERSE - if lower.endswith("-bedrock-invoke"): - return PROVIDER_BEDROCK_INVOKE - if lower.endswith("-azure"): - return PROVIDER_AZURE - if lower.endswith("-vertex"): - return PROVIDER_VERTEX_AI - return PROVIDER_ANTHROPIC - - -@dataclass(frozen=True) -class ProviderConfig: - """Static config snapshot for one provider's bucket. - - Captured up front (rather than re-read per acquire) so the limiter's - behavior in a single process is stable even if env vars are mutated - mid-run. A fresh `RateLimiter` picks up env changes on construction. - """ - - rate_per_sec: float - burst: float - - @property - def enabled(self) -> bool: - return self.rate_per_sec > 0 and self.burst > 0 - - -def load_config( - env: Optional[Mapping[str, str]] = None, -) -> Dict[str, ProviderConfig]: - """Build a {provider: ProviderConfig} from env, applying defaults. - - Parsing failures fall back to the default rate rather than - crashing the test session — a typo in `LITELLM_COMPAT_RATE_AZURE` - should not silently disable throttling, but it also shouldn't - abort 75 live tests with a `ValueError` ten minutes in. - """ - src = env if env is not None else os.environ - - def _as_float(value: Optional[str], default: float) -> float: - if value is None or value == "": - return default - try: - return float(value) - except (TypeError, ValueError): - return default - - burst_override = _as_float(src.get(BURST_ENV), -1.0) - - out: Dict[str, ProviderConfig] = {} - for provider in ALL_PROVIDERS: - env_key = RATE_ENV_PREFIX + provider.upper() - rate = _as_float(src.get(env_key), DEFAULT_RATE) - burst = burst_override if burst_override > 0 else max(rate, 1.0) - out[provider] = ProviderConfig(rate_per_sec=rate, burst=burst) - return out - - -def _state_dir(env: Optional[Mapping[str, str]] = None) -> Path: - """Resolve the directory holding per-provider state files. - - A user-supplied `LITELLM_COMPAT_RATE_STATE_DIR` wins for tests and - container environments where `$TMPDIR` may be ephemeral or shared - in surprising ways. The directory is created lazily with - `parents=True, exist_ok=True` so first-run setup needs no - fixture wiring. - """ - src = env if env is not None else os.environ - explicit = src.get(STATE_DIR_ENV) - if explicit: - return Path(explicit) - return Path(tempfile.gettempdir()) / DEFAULT_STATE_DIR_NAME - - -class RateLimiter: - """Cross-process token bucket per provider. - - Each `acquire(provider)` call: - 1. Opens (creating if needed) `/.json`. - 2. Holds an exclusive `flock` while reading + updating the - {tokens, last_refill} state. - 3. Refills tokens based on `now - last_refill`, capped at burst. - 4. If tokens >= 1, subtracts one and returns immediately. - 5. Otherwise, computes the wall-time delay needed to earn a - single token at the configured rate, releases the lock, and - sleeps. After sleeping it retries — staying under the lock - while sleeping would serialize all workers behind whichever - one held it longest. - - This bounds the *aggregate* req/s seen by the upstream, regardless - of how many xdist workers, threads, or processes are concurrently - running tests against the same provider. - - A `_clock` / `_sleep` injection seam keeps the unit tests fast and - deterministic; production callers should never override either. - """ - - def __init__( - self, - config: Optional[Mapping[str, ProviderConfig]] = None, - state_dir: Optional[Path] = None, - clock: Optional[callable] = None, - sleep: Optional[callable] = None, - ) -> None: - self._config = dict(config) if config is not None else load_config() - self._state_dir = Path(state_dir) if state_dir is not None else _state_dir() - self._clock = clock or time.monotonic - self._sleep = sleep or time.sleep - # `_state_dir.mkdir` once on construction is fine; concurrent - # workers all racing to create the same directory is benign. - self._state_dir.mkdir(parents=True, exist_ok=True) - - def acquire(self, provider: str) -> float: - """Block until one token is available for `provider`. - - Returns the cumulative wall-time spent waiting (0.0 when the - bucket had budget and we returned immediately). Callers can - log this to attribute slow cells to throttling vs. upstream - latency — same role `DriverResult.duration_ms` plays for the - actual CLI invocation. - """ - cfg = self._config.get(provider) - if cfg is None or not cfg.enabled: - return 0.0 - - path = self._state_path(provider) - total_waited = 0.0 - while True: - now = self._clock() - sleep_for = self._try_consume(path, cfg, now) - if sleep_for <= 0: - return total_waited - self._sleep(sleep_for) - total_waited += sleep_for - - def _state_path(self, provider: str) -> Path: - return self._state_dir / f"{provider}.json" - - def _try_consume(self, path: Path, cfg: ProviderConfig, now: float) -> float: - """Atomically refill and try to take one token. - - Returns 0.0 if a token was consumed, or a positive sleep - duration (seconds) if the caller must wait before retrying. - - We hold an exclusive `flock` only across the read-modify-write - of the JSON state — never across a `sleep` — so workers don't - serialize while one of them is parked. - """ - # `os.open` + `os.O_CREAT | os.O_RDWR` gives us a fd we can - # both lock and read/write through. Opening with `"a+"` then - # seeking is equivalent but uglier; this version is closer to - # the canonical flock recipe. - fd = os.open(path, os.O_CREAT | os.O_RDWR, 0o600) - try: - fcntl.flock(fd, fcntl.LOCK_EX) - try: - tokens, last_refill = self._read_state(fd, cfg, now) - tokens, last_refill = self._refill(tokens, last_refill, now, cfg) - if tokens >= 1.0: - tokens -= 1.0 - self._write_state(fd, tokens, last_refill) - return 0.0 - # Not enough budget. Persist the refilled state so a - # subsequent caller doesn't have to redo the math, then - # release the lock and tell the caller how long to - # sleep before retrying. - self._write_state(fd, tokens, last_refill) - deficit = 1.0 - tokens - # `deficit / rate` seconds will earn exactly enough - # for one token. Add a tiny safety margin so we don't - # wake up nanoseconds early and spin. - return (deficit / cfg.rate_per_sec) + 1e-3 - finally: - fcntl.flock(fd, fcntl.LOCK_UN) - finally: - os.close(fd) - - @staticmethod - def _read_state(fd: int, cfg: ProviderConfig, now: float) -> tuple: - """Read {tokens, last_refill} from `fd`, defaulting to a full - bucket on a missing/empty/corrupt file. - - New files start full so the very first request never waits; - corrupt files are treated like new files because the - alternative — refusing to run — is worse than briefly - over-spending one bucket's worth of budget. - """ - os.lseek(fd, 0, os.SEEK_SET) - raw = os.read(fd, 4096).decode("utf-8") - if not raw.strip(): - return cfg.burst, now - try: - obj = json.loads(raw) - tokens = float(obj.get("tokens", cfg.burst)) - last_refill = float(obj.get("last_refill", now)) - return tokens, last_refill - except (ValueError, TypeError): - return cfg.burst, now - - @staticmethod - def _refill( - tokens: float, last_refill: float, now: float, cfg: ProviderConfig - ) -> tuple: - """Apply elapsed time to the bucket, capped at burst. - - Negative elapsed (clock went backward, e.g. across host - sleep/resume or a manually-tweaked monotonic mock) is clamped - to zero so we never *remove* tokens. - """ - elapsed = max(0.0, now - last_refill) - tokens = min(cfg.burst, tokens + elapsed * cfg.rate_per_sec) - return tokens, now - - @staticmethod - def _write_state(fd: int, tokens: float, last_refill: float) -> None: - payload = json.dumps({"tokens": tokens, "last_refill": last_refill}).encode( - "utf-8" - ) - os.lseek(fd, 0, os.SEEK_SET) - os.ftruncate(fd, 0) - os.write(fd, payload) - - -# A single process-wide instance is all we need: provider-keyed state -# is stored in files, so multiple `RateLimiter` instances would just -# duplicate the in-process bookkeeping. We expose a getter rather than -# the instance directly so unit tests can install a custom limiter -# scoped to a tmp directory without monkeypatching globals. -_default: Optional[RateLimiter] = None - - -def get_default_limiter() -> RateLimiter: - global _default - if _default is None: - _default = RateLimiter() - return _default - - -def reset_default_limiter() -> None: - """Drop the cached default limiter; the next `get_default_limiter` - call rebuilds it from the current environment. - - Useful between unit tests that patch env vars: without this they'd - keep reading the stale config snapshot from the first call. - """ - global _default - _default = None - - -@contextlib.contextmanager -def use_limiter(limiter: RateLimiter) -> Iterator[RateLimiter]: - """Temporarily install `limiter` as the process default. - - The driver's `run_claude` calls `get_default_limiter()`; tests that - want a controlled tmp-dir-backed limiter use this contextmanager - to swap one in without touching env vars or the on-disk default - state. - """ - global _default - previous = _default - _default = limiter - try: - yield limiter - finally: - _default = previous diff --git a/tests/e2e/claude_code/run_compat.sh b/tests/e2e/claude_code/run_compat.sh index c42416283e7..e3410391661 100755 --- a/tests/e2e/claude_code/run_compat.sh +++ b/tests/e2e/claude_code/run_compat.sh @@ -1,7 +1,7 @@ #!/usr/bin/env bash # Run the Claude Code compat matrix end-to-end against a live LiteLLM # proxy, with per-provider rate limits applied via the cross-process -# token bucket in `tests/e2e/claude_code/rate_limiter.py`. +# token bucket in `tests/e2e/cli_harness/rate_limiter.py`. # # Designed for binary-searching the ideal X / Y / Z req/s per provider: # 1. Pick an initial rate (e.g. 5/s for everyone). diff --git a/tests/e2e/cli_harness/__init__.py b/tests/e2e/cli_harness/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/e2e/cli_harness/lockdown.py b/tests/e2e/cli_harness/lockdown.py new file mode 100644 index 00000000000..1d430529851 --- /dev/null +++ b/tests/e2e/cli_harness/lockdown.py @@ -0,0 +1,49 @@ +"""What a coding-agent CLI under test may see of the host. + +The CI job holds the proxy's upstream credentials (provider keys, AWS, Azure, the database URL, GitHub tokens) in its +environment, and the cron VM runs as a real user with a populated home. A compromised CLI release, or a model told to +read a file, must reach neither, so the CLI gets only the allowlisted runtime variables plus what its suite passes in, +and a fresh empty HOME that is deleted when it exits. +""" + +from __future__ import annotations + +import os +import shutil +import tempfile +from collections.abc import Generator, Mapping +from contextlib import contextmanager +from pathlib import Path +from types import MappingProxyType +from typing import Final + +CLI_ENV_ALLOWLIST: Final = ( + "PATH", + "USER", + "LOGNAME", + "SHELL", + "TERM", + "TMPDIR", + "LANG", + "LC_ALL", + "LC_CTYPE", + "NODE_PATH", + "NVM_DIR", + "NVM_BIN", +) + + +@contextmanager +def isolated_home(prefix: str) -> Generator[Path]: + home: Final = Path(tempfile.mkdtemp(prefix=prefix)) + try: + yield home + finally: + shutil.rmtree(home, ignore_errors=True) + + +def locked_down_env( + *, home: Path, overrides: Mapping[str, str], source: Mapping[str, str] = os.environ +) -> Mapping[str, str]: + allowed: Final = {name: source[name] for name in CLI_ENV_ALLOWLIST if name in source} + return MappingProxyType({**allowed, "HOME": str(home), **overrides}) diff --git a/tests/e2e/cli_harness/npm_version_resolver.py b/tests/e2e/cli_harness/npm_version_resolver.py new file mode 100644 index 00000000000..3c3f9b89ce5 --- /dev/null +++ b/tests/e2e/cli_harness/npm_version_resolver.py @@ -0,0 +1,92 @@ +"""The npm release of a coding-agent CLI that CI installs: the newest one published at least three days ago. + +The three days are a security review buffer (PRD #26476, "Version resolvers"), so a release that gets pulled or +patched within days never drives a run. Newest means by publish time, not semver order. + +`python tests/e2e/cli_harness/npm_version_resolver.py ` prints the version on stdout for a shell +`$(...)`. It is stdlib only because the cron image runs it without the project's dependencies. +""" + +from __future__ import annotations + +import json +import sys +import urllib.parse +import urllib.request +from collections.abc import Mapping +from dataclasses import dataclass +from datetime import datetime, timedelta, timezone +from types import MappingProxyType +from typing import BinaryIO, Final, cast + +MIN_AGE: Final = timedelta(days=3) +_REGISTRY_URL: Final = "https://registry.npmjs.org/{package}" +_FETCH_TIMEOUT_SECONDS: Final = 30 + + +@dataclass(frozen=True, slots=True) +class Packument: + published_at: Mapping[str, datetime] + versions: frozenset[str] + + @classmethod + def from_json(cls, raw: object) -> Packument: + document: Final = _as_mapping(raw) + times: Final = _as_mapping(document.get("time")) + return cls( + published_at=MappingProxyType({version: _parse_utc(stamp) for version, stamp in _string_values(times)}), + versions=frozenset(_as_mapping(document.get("versions"))), + ) + + +def newest_version_at_least(packument: Packument, *, min_age: timedelta, as_of: datetime) -> str | None: + cutoff: Final = as_of - min_age + eligible: Final = ( + (published, version) + for version, published in packument.published_at.items() + if version in packument.versions and "-" not in version and published <= cutoff + ) + newest: Final = max(eligible, default=None) + return None if newest is None else newest[1] + + +def fetch_packument(package: str) -> Packument: + url: Final = _REGISTRY_URL.format(package=urllib.parse.quote(package, safe="@")) + request: Final = urllib.request.Request(url, headers={"Accept": "application/json"}) + with cast(BinaryIO, urllib.request.urlopen(request, timeout=_FETCH_TIMEOUT_SECONDS)) as response: + return Packument.from_json(cast(object, json.loads(response.read()))) + + +def _as_mapping(raw: object) -> Mapping[str, object]: + if not isinstance(raw, dict): + return {} + return {str(key): value for key, value in cast(dict[object, object], raw).items()} + + +def _string_values(raw: Mapping[str, object]) -> tuple[tuple[str, str], ...]: + return tuple((key, value) for key, value in raw.items() if isinstance(value, str)) + + +def _parse_utc(stamp: str) -> datetime: + parsed: Final = datetime.fromisoformat(stamp.replace("Z", "+00:00")) + return parsed if parsed.tzinfo is not None else parsed.replace(tzinfo=timezone.utc) + + +def _main(argv: list[str]) -> int: + if len(argv) != 1: + print("usage: npm_version_resolver.py ", file=sys.stderr) # noqa: T201 # CLI surface + return 2 + package: Final = argv[0] + version: Final = newest_version_at_least( + fetch_packument(package), min_age=MIN_AGE, as_of=datetime.now(timezone.utc) + ) + if version is None: + print(f"npm_version_resolver: no release of {package} is at least {MIN_AGE} old", file=sys.stderr) # noqa: T201 # CLI surface + return 1 + print(f"npm_version_resolver: selected {package}@{version}", file=sys.stderr) # noqa: T201 # CLI surface + print(version) # noqa: T201 # CLI surface + return 0 + + +if __name__ == "__main__": + raise SystemExit(_main(sys.argv[1:])) diff --git a/tests/e2e/cli_harness/rate_limiter.py b/tests/e2e/cli_harness/rate_limiter.py new file mode 100644 index 00000000000..bd8119ffe87 --- /dev/null +++ b/tests/e2e/cli_harness/rate_limiter.py @@ -0,0 +1,151 @@ +"""A token bucket per upstream, shared by every process on the host, so parallel CLI suites and xdist workers +together stay under one request rate per provider instead of one rate each. + +Each bucket is a small JSON file read and written under an exclusive `flock`, in `LITELLM_COMPAT_RATE_STATE_DIR` +(default: a fixed folder under `$TMPDIR`). `LITELLM_COMPAT_RATE_` sets a bucket's req/s (default 5, 0 or less +turns it off) and `LITELLM_COMPAT_RATE_BURST` overrides every bucket's burst (default: its rate). +""" + +from __future__ import annotations + +import fcntl +import os +import tempfile +import time +from collections.abc import Callable, Iterator, Mapping +from dataclasses import dataclass, field +from enum import StrEnum +from functools import cache +from pathlib import Path +from types import MappingProxyType +from typing import Final + +from pydantic import BaseModel, ConfigDict, ValidationError + +DEFAULT_RATE: Final = 5.0 +RATE_ENV_PREFIX: Final = "LITELLM_COMPAT_RATE_" +BURST_ENV: Final = "LITELLM_COMPAT_RATE_BURST" +STATE_DIR_ENV: Final = "LITELLM_COMPAT_RATE_STATE_DIR" +DEFAULT_STATE_DIR_NAME: Final = "litellm-claude-compat-ratelimit" +_WAKE_MARGIN_SECONDS: Final = 1e-3 + + +class RateBucket(StrEnum): + ANTHROPIC = "anthropic" + AZURE = "azure" + VERTEX_AI = "vertex_ai" + BEDROCK_CONVERSE = "bedrock_converse" + BEDROCK_INVOKE = "bedrock_invoke" + OPENAI = "openai" + AZURE_OPENAI = "azure_openai" + BEDROCK_MANTLE = "bedrock_mantle" + + +@dataclass(frozen=True, slots=True) +class ProviderConfig: + rate_per_sec: float + burst: float + + @property + def enabled(self) -> bool: + return self.rate_per_sec > 0 and self.burst > 0 + + +class _BucketState(BaseModel): + model_config = ConfigDict(frozen=True) + + tokens: float + last_refill: float + + +def load_config(env: Mapping[str, str] = os.environ) -> Mapping[RateBucket, ProviderConfig]: + burst_override: Final = _as_float(env.get(BURST_ENV), -1.0) + return MappingProxyType( + { + bucket: _bucket_config(_as_float(env.get(_rate_env(bucket)), DEFAULT_RATE), burst_override) + for bucket in RateBucket + } + ) + + +def default_state_dir(env: Mapping[str, str] = os.environ) -> Path: + explicit: Final = env.get(STATE_DIR_ENV) + return Path(explicit) if explicit else Path(tempfile.gettempdir()) / DEFAULT_STATE_DIR_NAME + + +@dataclass(frozen=True, slots=True) +class RateLimiter: + config: Mapping[RateBucket, ProviderConfig] = field(default_factory=load_config) + state_dir: Path = field(default_factory=default_state_dir) + clock: Callable[[], float] = time.monotonic + sleep: Callable[[float], None] = time.sleep + + def __post_init__(self) -> None: + self.state_dir.mkdir(parents=True, exist_ok=True) + + def acquire(self, bucket: RateBucket) -> float: + cfg: Final = self.config.get(bucket) + if cfg is None or not cfg.enabled: + return 0.0 + return sum(self._waits(self.state_dir / f"{bucket.value}.json", cfg)) + + def _waits(self, path: Path, cfg: ProviderConfig) -> Iterator[float]: + while (wait := _try_consume(path, cfg, self.clock())) > 0: + self.sleep(wait) + yield wait + + +@cache +def get_default_limiter() -> RateLimiter: + return RateLimiter() + + +def _rate_env(bucket: RateBucket) -> str: + return RATE_ENV_PREFIX + bucket.value.upper() + + +def _bucket_config(rate: float, burst_override: float) -> ProviderConfig: + return ProviderConfig(rate_per_sec=rate, burst=burst_override if burst_override > 0 else max(rate, 1.0)) + + +def _as_float(value: str | None, default: float) -> float: + if not value: + return default + try: + return float(value) + except ValueError: + return default + + +def _try_consume(path: Path, cfg: ProviderConfig, now: float) -> float: + fd: Final = os.open(path, os.O_CREAT | os.O_RDWR, 0o600) + try: + fcntl.flock(fd, fcntl.LOCK_EX) + state: Final = _refilled(_read_state(fd, cfg, now), now, cfg) + if state.tokens >= 1.0: + _write_state(fd, _BucketState(tokens=state.tokens - 1.0, last_refill=state.last_refill)) + return 0.0 + _write_state(fd, state) + return (1.0 - state.tokens) / cfg.rate_per_sec + _WAKE_MARGIN_SECONDS + finally: + os.close(fd) + + +def _read_state(fd: int, cfg: ProviderConfig, now: float) -> _BucketState: + os.lseek(fd, 0, os.SEEK_SET) + raw: Final = os.read(fd, 4096) + try: + return _BucketState.model_validate_json(raw) + except ValidationError: + return _BucketState(tokens=cfg.burst, last_refill=now) + + +def _refilled(state: _BucketState, now: float, cfg: ProviderConfig) -> _BucketState: + elapsed: Final = max(0.0, now - state.last_refill) + return _BucketState(tokens=min(cfg.burst, state.tokens + elapsed * cfg.rate_per_sec), last_refill=now) + + +def _write_state(fd: int, state: _BucketState) -> None: + os.lseek(fd, 0, os.SEEK_SET) + os.ftruncate(fd, 0) + os.write(fd, state.model_dump_json().encode("utf-8")) diff --git a/tests/e2e/codex/__init__.py b/tests/e2e/codex/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/e2e/codex/conftest.py b/tests/e2e/codex/conftest.py new file mode 100644 index 00000000000..1ce6f2009a5 --- /dev/null +++ b/tests/e2e/codex/conftest.py @@ -0,0 +1,42 @@ +from __future__ import annotations + +from collections.abc import Iterator +from dataclasses import dataclass +from typing import Final + +import pytest +from cli_harness.rate_limiter import get_default_limiter +from codex.harness import CodexHarness, codex_harness +from codex.setups import Deployment, ModelSetup +from e2e_config import PROXY_BASE_URL, unique_marker +from lifecycle import ResourceManager +from proxy_client import ProxyClient + + +@dataclass(frozen=True, slots=True) +class _Client: + proxy: ProxyClient + + +@pytest.fixture(scope="session") +def client(proxy: ProxyClient) -> _Client: + return _Client(proxy) + + +@pytest.fixture +def setup(deployment: Deployment, proxy: ProxyClient, resources: ResourceManager) -> ModelSetup: + model: Final = f"e2e-codex-{unique_marker()}" + model_id: Final = proxy.create_model(model, deployment.litellm_params, provider_live=True) + resources.defer(lambda: proxy.delete_model(model_id)) + return ModelSetup(model=model, rate_bucket=deployment.rate_bucket) + + +@pytest.fixture +def codex(setup: ModelSetup, resources: ResourceManager) -> Iterator[CodexHarness]: + with codex_harness( + gateway=PROXY_BASE_URL, + api_key=resources.key(models=[setup.model], user_id=None), + rate_bucket=setup.rate_bucket, + limiter=get_default_limiter(), + ) as harness: + yield harness diff --git a/tests/e2e/codex/harness.py b/tests/e2e/codex/harness.py new file mode 100644 index 00000000000..f6dd3700149 --- /dev/null +++ b/tests/e2e/codex/harness.py @@ -0,0 +1,121 @@ +from __future__ import annotations + +import subprocess +import tempfile +from collections.abc import Generator, Mapping +from contextlib import contextmanager +from dataclasses import dataclass, field +from itertools import chain +from pathlib import Path +from typing import Final + +from cli_harness.lockdown import isolated_home, locked_down_env +from cli_harness.rate_limiter import RateBucket, RateLimiter +from codex.rollout import Compaction, rollout_compactions +from codex.run import CodexRun, codex_run +from e2e_metadata import step + +CODEX_CLI: Final = "codex" +EXEC_TIMEOUT_SECONDS: Final = 600.0 +_API_KEY_ENV: Final = "LITELLM_API_KEY" +_PROVIDER: Final = "litellm" +_CONFIG_TOML: Final = """\ +model_provider = "{provider}" +approval_policy = "never" +sandbox_mode = "workspace-write" +check_for_update_on_startup = false + +[analytics] +enabled = false + +[model_providers.{provider}] +name = "LiteLLM" +base_url = "{gateway}/v1" +env_key = "{api_key_env}" +wire_api = "responses" +model_catalog_url = "{gateway}/v1/models" +""" + + +@dataclass(frozen=True, slots=True) +class CodexHarness: + home: Path + api_key: str = field(repr=False) + rate_bucket: RateBucket + limiter: RateLimiter + cli: str = CODEX_CLI + timeout_seconds: float = EXEC_TIMEOUT_SECONDS + + @property + def codex_home(self) -> Path: + return self.home / ".codex" + + @step("Create a workspace folder holding the test's files") + def new_workspace(self, files: Mapping[str, str]) -> Path: + workspace: Final = Path(tempfile.mkdtemp(prefix="workspace-", dir=self.home)).resolve() + for name, content in files.items(): + _ = (workspace / name).write_text(content) + return workspace + + @step('Run Codex on {model} through the proxy with the prompt "{prompt}"') + def exec(self, prompt: str, *, model: str, cwd: Path, compact_after_tokens: int | None = None) -> CodexRun: + return self._run(("exec",), (*_compaction_flags(compact_after_tokens), "--model", model, "--", prompt), cwd) + + @step('Resume Codex thread {thread_id} on {model} through the proxy with the prompt "{prompt}"') + def resume( + self, thread_id: str, prompt: str, *, model: str, cwd: Path, compact_after_tokens: int | None = None + ) -> CodexRun: + return self._run( + ("exec", "resume"), + (*_compaction_flags(compact_after_tokens), "--model", model, "--", thread_id, prompt), + cwd, + ) + + def compactions(self, thread_id: str) -> tuple[Compaction, ...]: + rollouts: Final = sorted(self.codex_home.glob(f"sessions/**/rollout-*-{thread_id}.jsonl")) + return tuple(chain.from_iterable(rollout_compactions(rollout.read_text()) for rollout in rollouts)) + + def _run(self, subcommand: tuple[str, ...], args: tuple[str, ...], cwd: Path) -> CodexRun: + _ = self.limiter.acquire(self.rate_bucket) + completed: Final = subprocess.run( + (self.cli, *subcommand, "--json", "--skip-git-repo-check", *args), + cwd=cwd, + env=locked_down_env( + home=self.home, overrides={"CODEX_HOME": str(self.codex_home), _API_KEY_ENV: self.api_key} + ), + stdin=subprocess.DEVNULL, + capture_output=True, + text=True, + timeout=self.timeout_seconds, + check=False, + ) + return codex_run(exit_code=completed.returncode, stdout=completed.stdout, stderr=completed.stderr) + + +def _compaction_flags(after_tokens: int | None) -> tuple[str, ...]: + match after_tokens: + case None: + return () + case int(): + return ( + "--config", + f'model_providers.{_PROVIDER}.capabilities.remote_compaction="v2"', + "--config", + 'model_auto_compact_token_limit_scope="body_after_prefix"', + "--config", + f"model_auto_compact_token_limit={after_tokens}", + ) + + +@step("Give Codex a fresh empty home whose config sends every request to the proxy") +@contextmanager +def codex_harness( + *, gateway: str, api_key: str, rate_bucket: RateBucket, limiter: RateLimiter +) -> Generator[CodexHarness]: + with isolated_home("codex-cli-home-") as home: + harness: Final = CodexHarness(home=home, api_key=api_key, rate_bucket=rate_bucket, limiter=limiter) + harness.codex_home.mkdir() + _ = (harness.codex_home / "config.toml").write_text( + _CONFIG_TOML.format(provider=_PROVIDER, gateway=gateway, api_key_env=_API_KEY_ENV) + ) + yield harness diff --git a/tests/e2e/codex/rollout.py b/tests/e2e/codex/rollout.py new file mode 100644 index 00000000000..fcaeaa7ca42 --- /dev/null +++ b/tests/e2e/codex/rollout.py @@ -0,0 +1,49 @@ +"""The compactions Codex recorded in a thread's rollout file, `CODEX_HOME/sessions/**/rollout-*-.jsonl`. + +`codex exec --json` prints no event for a compaction, so the rollout is the only place it shows. Each line is +`{"timestamp", "type", "payload"}` (`codex-rs/history/src/rollout_payload.rs`) and only `compacted` lines are read. +A remote compaction is one whose replacement history carries the provider's `compaction` item, while a local one +replaces the history with a summary Codex wrote itself. +""" + +from __future__ import annotations + +from dataclasses import dataclass +from typing import Final + +from pydantic import BaseModel, ConfigDict + +_COMPACTED: Final = "compacted" +_PROVIDER_COMPACTION_ITEM: Final = "compaction" + + +class _Frozen(BaseModel): + model_config = ConfigDict(frozen=True) + + +class _Line(_Frozen): + type: str + payload: object = None + + +class _HistoryItem(_Frozen): + type: str + + +class _CompactedPayload(_Frozen): + replacement_history: tuple[_HistoryItem, ...] | None = None + + +@dataclass(frozen=True, slots=True) +class Compaction: + remote: bool + + +def rollout_compactions(rollout: str) -> tuple[Compaction, ...]: + lines: Final = tuple(_Line.model_validate_json(line) for line in rollout.splitlines() if line.strip()) + return tuple(_compaction(line.payload) for line in lines if line.type == _COMPACTED) + + +def _compaction(payload: object) -> Compaction: + history: Final = _CompactedPayload.model_validate(payload).replacement_history or () + return Compaction(remote=any(item.type == _PROVIDER_COMPACTION_ITEM for item in history)) diff --git a/tests/e2e/codex/run.py b/tests/e2e/codex/run.py new file mode 100644 index 00000000000..5195da67494 --- /dev/null +++ b/tests/e2e/codex/run.py @@ -0,0 +1,187 @@ +"""What one `codex exec --json` run did, read from the JSONL events it printed. + +The event shapes are Codex's own (`codex-rs/exec/src/exec_events.rs`). We take the latest codex release > 3 days old, so an event or item +type this module does not model is skipped, while one it does model is validated strictly and fails loudly when +Codex changes it. +""" + +from __future__ import annotations + +import re +from collections.abc import Callable, Iterator, Mapping +from dataclasses import dataclass +from itertools import chain +from pathlib import Path +from typing import Annotated, Final, Literal, cast + +from pydantic import BaseModel, ConfigDict, Discriminator, Tag, TypeAdapter + +_HTTP_STATUS: Final = re.compile(r"\bstatus:? (\d{3})\b") + + +class _Frozen(BaseModel): + model_config = ConfigDict(frozen=True) + + +class TokenUsage(_Frozen): + input_tokens: int + cached_input_tokens: int + cache_write_input_tokens: int = 0 + output_tokens: int + reasoning_output_tokens: int + + +class _AgentMessage(_Frozen): + type: Literal["agent_message"] + text: str + + +class _CommandExecution(_Frozen): + type: Literal["command_execution"] + command: str + aggregated_output: str + exit_code: int | None + + +class _FileUpdate(_Frozen): + path: str + kind: Literal["add", "delete", "update"] + + +class _FileChange(_Frozen): + type: Literal["file_change"] + changes: tuple[_FileUpdate, ...] + status: Literal["in_progress", "completed", "failed"] + + +class _ErrorItem(_Frozen): + type: Literal["error"] + message: str + + +class _Unmodelled(_Frozen): + type: str + + +class _Message(_Frozen): + message: str + + +def _known_or_unmodelled(known: frozenset[str]) -> Callable[[object], str]: + def tag(raw: object) -> str: + kind: Final = cast("Mapping[str, object]", raw).get("type") if isinstance(raw, Mapping) else None + return kind if isinstance(kind, str) and kind in known else "unmodelled" + + return tag + + +_Item = Annotated[ + Annotated[_AgentMessage, Tag("agent_message")] + | Annotated[_CommandExecution, Tag("command_execution")] + | Annotated[_FileChange, Tag("file_change")] + | Annotated[_ErrorItem, Tag("error")] + | Annotated[_Unmodelled, Tag("unmodelled")], + Discriminator(_known_or_unmodelled(frozenset({"agent_message", "command_execution", "file_change", "error"}))), +] + + +class _ThreadStarted(_Frozen): + type: Literal["thread.started"] + thread_id: str + + +class _ItemCompleted(_Frozen): + type: Literal["item.completed"] + item: _Item + + +class _TurnCompleted(_Frozen): + type: Literal["turn.completed"] + usage: TokenUsage + + +class _TurnFailed(_Frozen): + type: Literal["turn.failed"] + error: _Message + + +class _StreamError(_Frozen): + type: Literal["error"] + message: str + + +_Event = Annotated[ + Annotated[_ThreadStarted, Tag("thread.started")] + | Annotated[_ItemCompleted, Tag("item.completed")] + | Annotated[_TurnCompleted, Tag("turn.completed")] + | Annotated[_TurnFailed, Tag("turn.failed")] + | Annotated[_StreamError, Tag("error")] + | Annotated[_Unmodelled, Tag("unmodelled")], + Discriminator( + _known_or_unmodelled(frozenset({"thread.started", "item.completed", "turn.completed", "turn.failed", "error"})) + ), +] +_EVENT: Final = TypeAdapter[_Event](_Event) + + +@dataclass(frozen=True, slots=True) +class Command: + command: str + output: str + exit_code: int | None + + +@dataclass(frozen=True, slots=True) +class CodexError: + message: str + status_code: int | None + + +@dataclass(frozen=True, slots=True) +class CodexRun: + exit_code: int + thread_id: str | None + commands: tuple[Command, ...] + patched_files: tuple[Path, ...] + answer: str + usage: TokenUsage | None + errors: tuple[CodexError, ...] + stderr: str + + +def codex_run(*, exit_code: int, stdout: str, stderr: str) -> CodexRun: + events: Final = tuple(_EVENT.validate_json(line) for line in stdout.splitlines() if line.strip()) + items: Final = tuple(event.item for event in events if isinstance(event, _ItemCompleted)) + patches: Final = tuple(item for item in items if isinstance(item, _FileChange) and item.status == "completed") + answers: Final = tuple(item.text for item in items if isinstance(item, _AgentMessage)) + usages: Final = tuple(event.usage for event in events if isinstance(event, _TurnCompleted)) + return CodexRun( + exit_code=exit_code, + thread_id=next((event.thread_id for event in events if isinstance(event, _ThreadStarted)), None), + commands=tuple( + Command(command=item.command, output=item.aggregated_output, exit_code=item.exit_code) + for item in items + if isinstance(item, _CommandExecution) + ), + patched_files=tuple(Path(change.path) for change in chain.from_iterable(patch.changes for patch in patches)), + answer=answers[-1] if answers else "", + usage=usages[-1] if usages else None, + errors=tuple(_errors(events)), + stderr=stderr, + ) + + +def _errors(events: tuple[_Event, ...]) -> Iterator[CodexError]: + for event in events: + match event: + case _TurnFailed(error=_Message(message=message)) | _StreamError(message=message): + yield _codex_error(message) + case _ItemCompleted(item=_ErrorItem(message=message)): + yield _codex_error(message) + case _: + pass + + +def _codex_error(message: str) -> CodexError: + status: Final = _HTTP_STATUS.search(message) + return CodexError(message=message, status_code=int(status.group(1)) if status else None) diff --git a/tests/e2e/codex/setups.py b/tests/e2e/codex/setups.py new file mode 100644 index 00000000000..f86397686f3 --- /dev/null +++ b/tests/e2e/codex/setups.py @@ -0,0 +1,99 @@ +"""The credentials are `os.environ/` references the gateway resolves, the same names the Claude Code matrix's +`test_config.yaml` uses, and Bedrock rides the gateway's default AWS identity.""" + +from __future__ import annotations + +from dataclasses import dataclass +from typing import Final, Literal + +import pytest +from _pytest.mark.structures import ParameterSet +from cli_harness.rate_limiter import RateBucket +from e2e_metadata import Domain, Mode, Provider, Route, Subject, meta +from models import LiteLLMParamsBody + +GPT_ON_BEDROCK_MANTLE: Final = "bedrock_mantle/openai.gpt-6.1-sol" +GPT_ON_BEDROCK_RUNTIME: Final = "bedrock/global.openai.gpt-6.1-sol" +GPT_ON_AZURE_OPENAI: Final = "azure/gpt-6.1-sol" +GPT_ON_OPENAI: Final = "openai/gpt-6.1-sol" +CLAUDE_ON_BEDROCK: Final = "bedrock/us.anthropic.claude-sonnet-5-5" +_BEDROCK_REGION: Final = "us-east-1" + +type SetupId = Literal["bedrock_mantle", "bedrock_runtime", "azure_openai", "openai", "claude_bedrock"] + + +@dataclass(frozen=True, slots=True) +class Deployment: + litellm_params: LiteLLMParamsBody + rate_bucket: RateBucket + + +@dataclass(frozen=True, slots=True) +class ModelSetup: + model: str + rate_bucket: RateBucket + + +def _drives(provider: Provider, model: str) -> pytest.MarkDecorator: + return meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.RESPONSES, + providers=(provider,), + models=(model,), + mode=Mode.STREAM, + ) + ) + + +SETUPS: Final = ( + pytest.param( + Deployment( + LiteLLMParamsBody(model=GPT_ON_BEDROCK_MANTLE, aws_region_name=_BEDROCK_REGION), RateBucket.BEDROCK_MANTLE + ), + id="bedrock_mantle", + marks=_drives(Provider.BEDROCK_MANTLE, GPT_ON_BEDROCK_MANTLE), + ), + pytest.param( + Deployment( + LiteLLMParamsBody(model=GPT_ON_BEDROCK_RUNTIME, aws_region_name=_BEDROCK_REGION), + RateBucket.BEDROCK_CONVERSE, + ), + id="bedrock_runtime", + marks=( + _drives(Provider.BEDROCK, GPT_ON_BEDROCK_RUNTIME), + pytest.mark.skip(reason="Stage IAM lacks bedrock:InvokeModel on the default Bedrock Runtime project"), + ), + ), + pytest.param( + Deployment( + LiteLLMParamsBody( + model=GPT_ON_AZURE_OPENAI, api_base="os.environ/AZURE_API_BASE", api_key="os.environ/AZURE_API_KEY" + ), + RateBucket.AZURE_OPENAI, + ), + id="azure_openai", + marks=_drives(Provider.AZURE, GPT_ON_AZURE_OPENAI), + ), + pytest.param( + Deployment(LiteLLMParamsBody(model=GPT_ON_OPENAI, api_key="os.environ/OPENAI_API_KEY"), RateBucket.OPENAI), + id="openai", + marks=_drives(Provider.OPENAI, GPT_ON_OPENAI), + ), + pytest.param( + Deployment( + LiteLLMParamsBody(model=CLAUDE_ON_BEDROCK, aws_region_name=_BEDROCK_REGION), RateBucket.BEDROCK_CONVERSE + ), + id="claude_bedrock", + marks=_drives(Provider.BEDROCK, CLAUDE_ON_BEDROCK), + ), +) + + +def with_expected_failure(setup_id: SetupId, *, reason: str) -> tuple[ParameterSet, ...]: + return tuple( + pytest.param(*setup.values, id=setup.id, marks=(*setup.marks, pytest.mark.xfail(strict=True, reason=reason))) + if setup.id == setup_id + else setup + for setup in SETUPS + ) diff --git a/tests/e2e/codex/test_auto_compaction_e2e.py b/tests/e2e/codex/test_auto_compaction_e2e.py new file mode 100644 index 00000000000..5e0b2491002 --- /dev/null +++ b/tests/e2e/codex/test_auto_compaction_e2e.py @@ -0,0 +1,46 @@ +from __future__ import annotations + +from typing import Final + +import pytest +from codex.harness import CodexHarness +from codex.setups import ModelSetup, with_expected_failure +from e2e_config import unique_marker + +pytestmark = pytest.mark.e2e + +COMPACT_AFTER_TOKENS: Final = 500 +PADDING: Final = "".join(f"line {number}: the quick brown fox jumps over the lazy dog\n" for number in range(400)) + + +@pytest.mark.parametrize( + "deployment", + with_expected_failure( + "claude_bedrock", + reason="LiteLLM's Responses-to-chat bridge ignores Codex's compaction_trigger item, so Codex gets no" + " compaction back and fails the turn", + ), +) +class TestCodexAutoCompaction: + def test_remembers_a_value_after_the_gateway_compacts_the_session( + self, codex: CodexHarness, setup: ModelSetup + ) -> None: + marker: Final = unique_marker() + workspace: Final = codex.new_workspace(files={"secret.txt": marker, "padding.txt": PADDING}) + first: Final = codex.exec( + "Run `cat secret.txt` and remember the value it prints. Then run `cat padding.txt`. Then reply with OK.", + model=setup.model, + cwd=workspace, + compact_after_tokens=COMPACT_AFTER_TOKENS, + ) + assert first.thread_id is not None, first + (workspace / "secret.txt").unlink() + second: Final = codex.resume( + first.thread_id, + "What value did secret.txt print earlier? Reply with just that value.", + model=setup.model, + cwd=workspace, + compact_after_tokens=COMPACT_AFTER_TOKENS, + ) + assert any(compaction.remote for compaction in codex.compactions(first.thread_id)), (first, second) + assert marker in second.answer, second diff --git a/tests/e2e/codex/test_command_round_trip_e2e.py b/tests/e2e/codex/test_command_round_trip_e2e.py new file mode 100644 index 00000000000..20beba53cb2 --- /dev/null +++ b/tests/e2e/codex/test_command_round_trip_e2e.py @@ -0,0 +1,23 @@ +from __future__ import annotations + +from typing import Final + +import pytest +from codex.harness import CodexHarness +from codex.setups import SETUPS, ModelSetup +from e2e_config import unique_marker + +pytestmark = pytest.mark.e2e + + +@pytest.mark.parametrize("deployment", SETUPS) +class TestCodexCommandRoundTrip: + def test_answers_with_what_a_command_printed(self, codex: CodexHarness, setup: ModelSetup) -> None: + marker: Final = unique_marker() + workspace: Final = codex.new_workspace(files={"secret.txt": marker}) + run: Final = codex.exec( + "Run `cat secret.txt`, then reply with exactly what it printed.", model=setup.model, cwd=workspace + ) + assert run.exit_code == 0, run + assert any(marker in command.output for command in run.commands), run + assert marker in run.answer, run diff --git a/tests/e2e/codex/test_file_edit_e2e.py b/tests/e2e/codex/test_file_edit_e2e.py new file mode 100644 index 00000000000..5bf544d4eb7 --- /dev/null +++ b/tests/e2e/codex/test_file_edit_e2e.py @@ -0,0 +1,24 @@ +from __future__ import annotations + +from typing import Final + +import pytest +from codex.harness import CodexHarness +from codex.setups import SETUPS, ModelSetup +from e2e_config import unique_marker + +pytestmark = pytest.mark.e2e + + +@pytest.mark.parametrize("deployment", SETUPS) +class TestCodexFileEdit: + def test_changes_a_file_with_the_patch_tool(self, codex: CodexHarness, setup: ModelSetup) -> None: + marker: Final = unique_marker() + workspace: Final = codex.new_workspace(files={"config.txt": "name = placeholder\n"}) + run: Final = codex.exec( + f"Use the apply_patch tool to change `placeholder` to `{marker}` in config.txt. Change nothing else.", + model=setup.model, + cwd=workspace, + ) + assert run.patched_files == (workspace / "config.txt",), run + assert (workspace / "config.txt").read_text() == f"name = {marker}\n", run diff --git a/tests/e2e/codex/test_long_session_e2e.py b/tests/e2e/codex/test_long_session_e2e.py new file mode 100644 index 00000000000..52769b720e3 --- /dev/null +++ b/tests/e2e/codex/test_long_session_e2e.py @@ -0,0 +1,34 @@ +from __future__ import annotations + +from typing import Final + +import pytest +from codex.harness import CodexHarness +from codex.setups import SETUPS, ModelSetup +from e2e_config import unique_marker + +pytestmark = pytest.mark.e2e + + +@pytest.mark.parametrize("deployment", SETUPS) +class TestCodexLongSession: + def test_remembers_every_command_output_in_a_chain_of_files(self, codex: CodexHarness, setup: ModelSetup) -> None: + codes: Final = (unique_marker(), unique_marker(), unique_marker()) + second: Final = f"{unique_marker()}.txt" + third: Final = f"{unique_marker()}.txt" + workspace: Final = codex.new_workspace( + files={ + "start.txt": f"code {codes[0]}\nnext {second}\n", + second: f"code {codes[1]}\nnext {third}\n", + third: f"code {codes[2]}\nlast file\n", + } + ) + run: Final = codex.exec( + "Run `cat start.txt`. Each file prints a code and then the name of the next file, until one says last" + " file. Run `cat` on each next file, one command per step. Reply with the three codes in the order you" + " read them.", + model=setup.model, + cwd=workspace, + ) + assert len(run.commands) >= 3, run + assert all(code in run.answer for code in codes), run diff --git a/tests/e2e/conftest.py b/tests/e2e/conftest.py index 4c7c57ca18f..8fb96bef2f9 100644 --- a/tests/e2e/conftest.py +++ b/tests/e2e/conftest.py @@ -35,6 +35,7 @@ from e2e_config import ( PROMPT_CACHING_OPT_IN_ENV, PROVIDER_EDGE_HOST_OPT_IN_ENV, PROXY_BASE_URL, + PROXY_WIDE_CONFIG_OPT_IN_ENV, SAGEMAKER_NOVA2_LITE_OPT_IN_ENV, SAGEMAKER_NOVA_OPT_IN_ENV, SECRET_MANAGER_OPT_IN_ENV, @@ -54,7 +55,6 @@ from models import TeamNewBody, UserNewBody, UserNewResponse from provider_cache_routing import LIVE_PROVIDER_REQUIRED from provider_edge import replay_leftover_error from proxy_client import ProxyClient, build_proxy_client -from stack_lock import stack_lock _E2E_TEST_RAN = pytest.StashKey[bool]() _CALL_PASSED = pytest.StashKey[bool]() @@ -77,6 +77,7 @@ OPT_IN_MARKERS: Final = MappingProxyType( "secret_manager": SECRET_MANAGER_OPT_IN_ENV, "sagemaker_nova": SAGEMAKER_NOVA_OPT_IN_ENV, "sagemaker_nova2_lite": SAGEMAKER_NOVA2_LITE_OPT_IN_ENV, + "proxy_wide_config": PROXY_WIDE_CONFIG_OPT_IN_ENV, } ) @@ -162,11 +163,6 @@ def pytest_configure(config: pytest.Config) -> None: "redis_chaos: load test that pauses the proxy's Redis outright mid-run; needs a proxy booted from " "gateway/redis_chaos_ci_config.yml on the same host, and is deselected unless E2E_PERF_TESTS is set", ) - config.addinivalue_line( - "markers", - "quiet_stack: measures the proxy itself, so it runs while no other test on this host is hitting the stack; " - "every other test waits for it to finish", - ) config.addinivalue_line( "markers", "provider_edge_host: routes provider traffic through the pytest host's edge in every fixture mode, so the " @@ -200,6 +196,11 @@ def pytest_configure(config: pytest.Config) -> None: "sagemaker_nova2_lite: needs a deployed SageMaker Nova 2 Lite endpoint the proxy's AWS credentials can invoke; " "deselected unless SAGEMAKER_NOVA2_LITE_ENDPOINT names it", ) + config.addinivalue_line( + "markers", + "proxy_wide_config: turns on a proxy-wide setting through /config/update, so it runs on a stack no other suite " + "is driving; deselected unless E2E_PROXY_WIDE_CONFIG_STACK is set", + ) def pytest_sessionstart(session: pytest.Session) -> None: @@ -269,7 +270,7 @@ def pytest_collection_finish(session: pytest.Session) -> None: ahead of xdist's own collection-finish report, and the controller schedules no test until every worker has reported, so this is the idle footprint of a stack that just passed its readiness gate. The fixture hands the capture to the - idle-budget test in router/test_reliability_memory_e2e.py.""" + idle-budget test in perf/test_reliability_memory_e2e.py.""" if session.config.getoption("collectonly") or not any(_uses_idle_rss(item) for item in session.items): return session.config.stash[_IDLE_RSS] = read_rss_everywhere(build_proxy_client(), timeout=IDLE_RSS_READ_TIMEOUT_SECONDS) @@ -299,12 +300,6 @@ def _proxy_fail_reason() -> str | None: return None -@pytest.hookimpl(wrapper=True) -def pytest_runtest_protocol(item: pytest.Item, nextitem: pytest.Item | None) -> Generator[None, object, object]: - with stack_lock(exclusive=item.get_closest_marker("quiet_stack") is not None): - return (yield) - - @pytest.hookimpl(tryfirst=True) def pytest_runtest_setup(item: pytest.Item) -> None: """Hard-fail `e2e`-marked tests unless a proxy answers its liveness probe. diff --git a/tests/e2e/coverage_registry/guardrail.yaml b/tests/e2e/coverage_registry/guardrail.yaml index 854958fc39e..457f03406f1 100644 --- a/tests/e2e/coverage_registry/guardrail.yaml +++ b/tests/e2e/coverage_registry/guardrail.yaml @@ -20,8 +20,8 @@ - {id: guardrail.ibm_guardrails.post_call.blocks, module: guardrail, tier: P1, hook_point: post_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/ibm_guardrails/ibm_detector.py", rationale: "Output policy validation"} - {id: guardrail.semantic_guard.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/semantic_guard", rationale: "Semantic policy compliance"} - {id: guardrail.block_code_execution.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/block_code_execution", rationale: "Code-injection prevention"} -- {id: guardrail.tool_permission.pre_call.allows, module: guardrail, tier: P1, hook_point: pre_call, assertions: [allows], exercised_on: [chat_completions], source: "guardrail_hooks/tool_permission.py", rationale: "Grant allowed tools"} -- {id: guardrail.tool_permission.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/tool_permission.py", rationale: "Block unauthorized tools"} +- {id: guardrail.tool_permission.pre_call.allows, module: guardrail, tier: P1, hook_point: pre_call, assertions: [allows], exercised_on: [chat_completions, messages, responses], source: "guardrail_hooks/tool_permission.py", rationale: "Grant allowed tools"} +- {id: guardrail.tool_permission.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions, messages, responses], source: "guardrail_hooks/tool_permission.py", rationale: "Block unauthorized tools"} - {id: guardrail.microsoft_purview.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/microsoft_purview/purview_dlp.py", rationale: "DLP sensitive-data disclosure"} - {id: guardrail.headroom.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/headroom/headroom.py", rationale: "Anomaly detection threshold"} - {id: guardrail.generic_guardrail_api.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py", rationale: "Vendor-agnostic custom API"} diff --git a/tests/e2e/coverage_registry/llm_nonconversational.yaml b/tests/e2e/coverage_registry/llm_nonconversational.yaml index 367135eae26..d99bcff46e0 100644 --- a/tests/e2e/coverage_registry/llm_nonconversational.yaml +++ b/tests/e2e/coverage_registry/llm_nonconversational.yaml @@ -77,6 +77,10 @@ - {id: llm.bedrock_native.bedrock_invoke.basic.stream.works, module: llm, tier: P1, subject_endpoint: bedrock_native, route: bedrock_invoke, capability: basic, streaming: stream, assertions: [works], source: "vendor strategy §9.12 / LIT-4778", rationale: "Bedrock native invoke stream"} - {id: llm.bedrock_native.bedrock_invoke.input_validation.nonstream.works, module: llm, tier: P1, subject_endpoint: bedrock_native, route: bedrock_invoke, capability: input_validation, streaming: nonstream, assertions: [works], source: "vendor strategy §9.12 / LIT-4778", rationale: "Bedrock invoke missing fields and invalid temperature"} - {id: llm.ocr.openai.input_validation.nonstream.works, module: llm, tier: P1, subject_endpoint: ocr, route: openai, capability: input_validation, streaming: nonstream, assertions: [works], source: "vendor strategy §9.13 / LIT-4778", rationale: "OCR missing document rejected"} +- {id: llm.realtime.openai.translation.stream.works, module: llm, tier: P0, subject_endpoint: realtime, route: openai, capability: translation, streaming: stream, assertions: [works], source: "realtime_endpoints/endpoints.py", rationale: "Dedicated translation client-secret, raw SDP, and WebSocket paths emit translated audio and transcript deltas"} +- {id: llm.realtime.azure_openai.translation.stream.works, module: llm, tier: P0, subject_endpoint: realtime, route: azure_openai, capability: translation, streaming: stream, assertions: [works], source: "azure/realtime/handler.py", rationale: "Azure GA translation session emits translated audio and transcript deltas"} +- {id: llm.realtime.openai.transcription.stream.works, module: llm, tier: P0, subject_endpoint: realtime, route: openai, capability: transcription, streaming: stream, assertions: [works], source: "openai/realtime/handler.py", rationale: "gpt-live-transcribe and gpt-realtime-whisper emit live transcript deltas"} +- {id: llm.realtime.azure_openai.transcription.stream.works, module: llm, tier: P0, subject_endpoint: realtime, route: azure_openai, capability: transcription, streaming: stream, assertions: [works], source: "azure/realtime/handler.py", rationale: "Azure GA live transcription emits transcript deltas"} - {id: llm.rerank.bedrock.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: rerank, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "llms/bedrock/rerank/handler.py", rationale: "Bedrock rerank"} - {id: llm.rerank.together_ai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: rerank, route: together_ai, capability: basic, streaming: nonstream, assertions: [works], source: "llms/together_ai/rerank/handler.py", rationale: "Together rerank"} - {id: llm.images_generations.openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: images_generations, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "test_image_generation_e2e.py:22", rationale: "OpenAI image gen, b64/url"} @@ -94,6 +98,8 @@ - {id: llm.audio_speech.vertex.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: audio_speech, route: vertex, capability: basic, streaming: nonstream, assertions: [works], source: "vertex_ai/text_to_speech/text_to_speech_handler.py", rationale: "Vertex TTS"} - {id: llm.audio_transcriptions.openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: audio_transcriptions, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "openai/transcriptions/handler.py", rationale: "OpenAI Whisper"} - {id: llm.audio_transcriptions.openai.input_validation.nonstream.works, module: llm, tier: P1, subject_endpoint: audio_transcriptions, route: openai, capability: input_validation, streaming: nonstream, assertions: [works], source: "vendor strategy §9.7 / LIT-4778", rationale: "Transcription empty file and missing model are rejected"} +- {id: llm.audio_transcriptions.openai.transcription.stream.works, module: llm, tier: P0, subject_endpoint: audio_transcriptions, route: openai, capability: transcription, streaming: stream, assertions: [works], source: "openai/transcriptions/handler.py", rationale: "gpt-transcribe streams typed transcript delta and done events"} +- {id: llm.audio_transcriptions.azure_openai.transcription.stream.works, module: llm, tier: P0, subject_endpoint: audio_transcriptions, route: azure_openai, capability: transcription, streaming: stream, assertions: [works], source: "azure/audio_transcriptions.py", rationale: "Azure gpt-transcribe streams typed transcript delta and done events over the v1 API"} - {id: llm.audio_transcriptions.azure_openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: audio_transcriptions, route: azure_openai, capability: basic, streaming: nonstream, assertions: [works], source: "azure/audio_transcriptions.py", rationale: "Azure STT"} - {id: llm.audio_transcriptions.soniox.basic.nonstream.works, module: llm, tier: P2, subject_endpoint: audio_transcriptions, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "soniox/audio_transcription/handler.py", rationale: "Soniox via OpenAI-compat (smoke)"} - {id: llm.audio_transcriptions.nvidia_riva.basic.nonstream.works, module: llm, tier: P2, subject_endpoint: audio_transcriptions, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "nvidia_riva/audio_transcription/handler.py", rationale: "NVIDIA Riva (smoke)"} diff --git a/tests/e2e/coverage_registry/quota_management.yaml b/tests/e2e/coverage_registry/quota_management.yaml index cbaf46130d6..49997aef162 100644 --- a/tests/e2e/coverage_registry/quota_management.yaml +++ b/tests/e2e/coverage_registry/quota_management.yaml @@ -44,8 +44,6 @@ - {id: quota_management.spend_tracking.messages_bridge.logs_cost, module: quota_management, tier: P1, behavior: spend_tracking, variant: messages_bridge, assertions: [logs_cost], exercised_on: [messages], source: "llms/anthropic/messages/responses_adapters/handler.py", rationale: "A streaming /v1/messages request served by an openai-provider model is bridged through the anthropic-messages -> Responses adapter and must aggregate the consumed SSE stream into one spend row with nonzero cost and token counts, attributed to custom_llm_provider openai under call_type anthropic_messages"} - {id: quota_management.spend_tracking.embeddings.logs_cost, module: quota_management, tier: P1, behavior: spend_tracking, variant: embeddings, assertions: [logs_cost], exercised_on: [embeddings], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "Embedding calls write nonzero spend rows"} - {id: quota_management.spend_tracking.cache_hit.zero_cost, module: quota_management, tier: P1, behavior: spend_tracking, variant: cache_hit, assertions: [zero_cost], exercised_on: [chat_completions], source: "proxy/spend_tracking/spend_tracking_utils.py", rationale: "A response-cache hit logs at zero cost with the cache-hit marker"} -- {id: quota_management.spend_tracking.discount_config.logs_cost, module: quota_management, tier: P1, behavior: spend_tracking, variant: discount_config, assertions: [logs_cost], exercised_on: [chat_completions], source: "proxy/management_endpoints/cost_tracking_settings.py + cost_calculator.py", rationale: "A persisted provider discount changes the real request's spend row"} -- {id: quota_management.spend_tracking.margin_config.logs_cost, module: quota_management, tier: P1, behavior: spend_tracking, variant: margin_config, assertions: [logs_cost], exercised_on: [chat_completions], source: "proxy/management_endpoints/cost_tracking_settings.py + cost_calculator.py", rationale: "A persisted provider margin is added to the real request's spend row"} - {id: quota_management.spend_tracking.guardrail_cost.logs_cost, module: quota_management, tier: P1, behavior: spend_tracking, variant: guardrail_cost, assertions: [logs_cost], exercised_on: [chat_completions], source: "litellm_core_utils/llm_cost_calc/guardrail_cost.py + proxy/spend_tracking/spend_tracking_utils.py", rationale: "A priced Bedrock guardrail charge reaches the persisted spend row"} - {id: quota_management.spend_tracking.key_rollup.matches_sum_of_logs, module: quota_management, tier: P1, behavior: spend_tracking, variant: key_rollup, assertions: [matches_sum_of_logs], exercised_on: [chat_completions], source: "proxy/db/db_spend_update_writer.py", rationale: "A key's rolled-up spend equals the sum of its log rows"} - {id: quota_management.spend_tracking.concurrent_burst.loses_no_spend, module: quota_management, tier: P1, behavior: spend_tracking, variant: concurrent_burst, assertions: [loses_no_spend], exercised_on: [chat_completions], source: "proxy/db/db_spend_update_writer.py", rationale: "Concurrent calls all land as spend; no row lost to write contention"} diff --git a/tests/e2e/coverage_registry/schema.py b/tests/e2e/coverage_registry/schema.py index d2ba2c325df..7d9bc380bd0 100644 --- a/tests/e2e/coverage_registry/schema.py +++ b/tests/e2e/coverage_registry/schema.py @@ -93,6 +93,8 @@ LlmCapability = Literal[ "tool_search_history", "tool_use", "upstream_stream_failure", + "transcription", + "translation", "vision", "web_search", "web_search_server_tool", @@ -162,14 +164,7 @@ class OtherCell(_Base): Cell = Annotated[ - LlmCell - | MgmtCell - | McpCell - | ReliabilityCell - | QuotaCell - | LoggingCell - | GuardrailCell - | OtherCell, + LlmCell | MgmtCell | McpCell | ReliabilityCell | QuotaCell | LoggingCell | GuardrailCell | OtherCell, Field(discriminator="module"), ] diff --git a/tests/e2e/e2e_config.py b/tests/e2e/e2e_config.py index 724aa2362e7..6316d22d3fa 100644 --- a/tests/e2e/e2e_config.py +++ b/tests/e2e/e2e_config.py @@ -210,6 +210,7 @@ OTEL_TLS_OPT_IN_ENV: Final = "E2E_OTEL_EXPORTER_ENDPOINT" SECRET_MANAGER_OPT_IN_ENV: Final = "E2E_SECRET_MANAGER" SAGEMAKER_NOVA_OPT_IN_ENV: Final = "SAGEMAKER_NOVA_ENDPOINT" SAGEMAKER_NOVA2_LITE_OPT_IN_ENV: Final = "SAGEMAKER_NOVA2_LITE_ENDPOINT" +PROXY_WIDE_CONFIG_OPT_IN_ENV: Final = "E2E_PROXY_WIDE_CONFIG_STACK" ANOMALY_SESSIONS = int(os.environ.get("E2E_ANOMALY_SESSIONS", "6")) ANOMALY_TURNS_PER_SESSION = int(os.environ.get("E2E_ANOMALY_TURNS_PER_SESSION", "6")) ANOMALY_TURN_ATTEMPTS = int(os.environ.get("E2E_ANOMALY_TURN_ATTEMPTS", "3")) @@ -234,7 +235,6 @@ MEMORY_RSS_SETTLE_SAMPLES = int(os.environ.get("E2E_MEMORY_RSS_SETTLE_SAMPLES", MEMORY_RSS_SAMPLE_INTERVAL_SECONDS = float(os.environ.get("E2E_MEMORY_RSS_SAMPLE_INTERVAL_SECONDS", "1")) MEMORY_RSS_CEILING_MB = float(os.environ.get("E2E_MEMORY_RSS_CEILING_MB", "200")) MEMORY_IDLE_RSS_BUDGET_MB = float(os.environ.get("E2E_MEMORY_IDLE_RSS_BUDGET_MB", "768")) -MEMORY_STORED_REQUEST_BUDGET_KB = float(os.environ.get("E2E_MEMORY_STORED_REQUEST_BUDGET_KB", "64")) def ws_base_url() -> str: diff --git a/tests/e2e/guardrails/guardrails_client.py b/tests/e2e/guardrails/guardrails_client.py index cf517c7a4fe..9db95822734 100644 --- a/tests/e2e/guardrails/guardrails_client.py +++ b/tests/e2e/guardrails/guardrails_client.py @@ -38,7 +38,7 @@ from models import ( from proxy_client import ProxyClient from pydantic import BaseModel, Field -GUARDRAIL_BACKEND: Final = "gemini/gemini-2.5-flash" +GUARDRAIL_BACKEND: Final = "gemini/gemini-3.8-flash" GuardrailMode = Literal["pre_call", "post_call", "during_call", "logging_only"] BlockedWordAction = Literal["BLOCK", "MASK"] diff --git a/tests/e2e/guardrails/test_openai_moderation_guardrail_e2e.py b/tests/e2e/guardrails/test_openai_moderation_guardrail_e2e.py index b9593feb2ed..0eb1bf79daa 100644 --- a/tests/e2e/guardrails/test_openai_moderation_guardrail_e2e.py +++ b/tests/e2e/guardrails/test_openai_moderation_guardrail_e2e.py @@ -128,7 +128,7 @@ class TestOpenAIModerationGuardrail: ) allowed = unwrap( - client.messages(scoped_key, model, BENIGN_PROMPT, guardrails=[name], max_tokens=64) + client.messages(scoped_key, model, BENIGN_PROMPT, guardrails=[name], max_tokens=512) ) assert allowed.content or allowed.choices, ( "the same moderation guardrail must let a benign /v1/messages prompt through, but " diff --git a/tests/e2e/guardrails/test_tool_permission_guardrail_e2e.py b/tests/e2e/guardrails/test_tool_permission_guardrail_e2e.py index d5a6a9d9866..87545299169 100644 --- a/tests/e2e/guardrails/test_tool_permission_guardrail_e2e.py +++ b/tests/e2e/guardrails/test_tool_permission_guardrail_e2e.py @@ -19,10 +19,9 @@ verdict comes from the proxy itself. from __future__ import annotations -from typing import Final +from typing import Final, Literal import pytest - from e2e_config import unique_marker from e2e_http import StreamingResponse, UnknownApiError from e2e_metadata import Capability, Domain, Mode, Provider, Subject, meta @@ -31,14 +30,29 @@ from guardrails_client import ( ToolPermissionParamsBody, ToolPermissionRuleBody, poll_until_blocked, + poll_until_blocked_stream, poll_until_guardrail_applied, ) from lifecycle import ResourceManager -from models import ChatResponse, ChatTool, ChatToolFunction +from models import ( + AnthropicCustomTool, + AnthropicMessagesBody, + AnthropicMessagesResponse, + AnthropicToolChoice, + ChatMessage, + ChatResponse, + ChatTool, + ChatToolFunction, + JsonSchemaProperty, + ResponsesFunctionTool, + ResponsesToolBody, + ResponsesToolOutput, + ToolInputSchema, +) -pytestmark = pytest.mark.e2e +pytestmark: Final = pytest.mark.e2e -MODEL = "gemini-2.5-flash" +MODEL: Final = "gemini-2.5-flash" #: The one tool the guardrail permits, and one it does not. Both are declared by #: the caller in the request body; the guardrail reads them there. @@ -63,11 +77,15 @@ DENIED_TOOL: Final = ChatTool( TOOL_PROMPT: Final = "What is the weather in Paris right now?" +type FlatToolEndpoint = Literal["messages", "responses"] +ALLOWED_TOOL_SCHEMA: Final = ToolInputSchema(properties={"city": JsonSchemaProperty(type="string")}, required=["city"]) +DENIED_TOOL_SCHEMA: Final = ToolInputSchema() + def _register_tool_permission(client: GuardrailsClient, resources: ResourceManager, *, name: str) -> None: """Allow-list exactly one tool: everything else falls to `default_action=deny` and, with `on_disallowed_action=block`, is rejected outright.""" - guardrail_id = client.register( + guardrail_id: Final = client.register( name, ToolPermissionParamsBody( mode="pre_call", @@ -100,6 +118,57 @@ def _tool_call_names(response: ChatResponse) -> tuple[str, ...]: ) +def _send_flat_tool( + client: GuardrailsClient, + key: str, + endpoint: FlatToolEndpoint, + *, + guardrail: str, + tool: ChatTool, + schema: ToolInputSchema, + require_tool: bool = False, +) -> StreamingResponse: + name: Final = tool.function.name + match endpoint: + case "messages": + return client.proxy.transport.send( + "/v1/messages", + headers=client.proxy.transport.bearer(key), + json=AnthropicMessagesBody( + model=MODEL, + messages=[ChatMessage(role="user", content=TOOL_PROMPT)], + max_tokens=128, + tools=[ + AnthropicCustomTool(name=name, description=tool.function.description or "", input_schema=schema) + ], + tool_choice=AnthropicToolChoice(type="any") if require_tool else None, + guardrails=[guardrail], + ), + ) + case "responses": + return client.proxy.transport.send( + "/v1/responses", + headers=client.proxy.transport.bearer(key), + json=ResponsesToolBody( + model=MODEL, + input=TOOL_PROMPT, + tools=[ResponsesFunctionTool(name=name, description=tool.function.description, parameters=schema)], + tool_choice="required" if require_tool else None, + guardrails=[guardrail], + ), + ) + + +def _flat_tool_call_names(endpoint: FlatToolEndpoint, body: str) -> tuple[str, ...]: + match endpoint: + case "messages": + content: Final = AnthropicMessagesResponse.model_validate_json(body).content or [] + return tuple(block.name for block in content if block.type == "tool_use" and block.name) + case "responses": + output: Final = ResponsesToolOutput.model_validate_json(body).output + return tuple(item.name for item in output if item.type == "function_call" and item.name) + + class TestToolPermissionPreCall: @pytest.mark.covers("guardrail.tool_permission.pre_call.blocks", exercised_on=["chat_completions"]) @meta( @@ -118,10 +187,10 @@ class TestToolPermissionPreCall: rejected with a 400 that names the denied tool. An unauthorized tool that merely reaches the model is the whole failure mode this guardrail exists to prevent, so a 200 here is a hard failure.""" - name = f"e2e-toolperm-block-{unique_marker()}" + name: Final = f"e2e-toolperm-block-{unique_marker()}" _register_tool_permission(client, resources, name=name) - result = poll_until_blocked( + result: Final = poll_until_blocked( lambda: client.chat( scoped_key, MODEL, @@ -161,10 +230,10 @@ class TestToolPermissionPreCall: and the model calls it. Without the header check a guardrail that never attached would pass this test for the wrong reason, so the 200 alone is not the contract.""" - name = f"e2e-toolperm-allow-{unique_marker()}" + name: Final = f"e2e-toolperm-allow-{unique_marker()}" _register_tool_permission(client, resources, name=name) - outcome = poll_until_guardrail_applied( + outcome: Final = poll_until_guardrail_applied( lambda: client.chat_raw( scoped_key, MODEL, @@ -178,13 +247,117 @@ class TestToolPermissionPreCall: ) assert outcome.ok, f"the permitted tool must be served, got {outcome.status_code}: {outcome.body[:400]}" - applied = _applied_guardrails(outcome) + applied: Final = _applied_guardrails(outcome) assert name in applied, ( "the allowed call must carry x-litellm-applied-guardrails naming the guardrail; " f"without it the 200 only proves the guardrail never ran. Got {applied!r}" ) - called = _tool_call_names(ChatResponse.model_validate_json(outcome.body)) + called: Final = _tool_call_names(ChatResponse.model_validate_json(outcome.body)) + assert called == (ALLOWED_TOOL.function.name,), ( + f"the served call must carry one tool call for the permitted tool, got {called!r}: {outcome.body[:400]}" + ) + + @pytest.mark.parametrize( + "endpoint", + [ + pytest.param( + "messages", + marks=pytest.mark.covers("guardrail.tool_permission.pre_call.blocks", exercised_on=["messages"]), + ), + pytest.param( + "responses", + marks=pytest.mark.covers("guardrail.tool_permission.pre_call.blocks", exercised_on=["responses"]), + ), + ], + ) + @meta( + Subject( + domain=Domain.GUARDRAILS, + providers=(Provider.GEMINI,), + models=(MODEL,), + capabilities=(Capability.FUNCTION_CALLING,), + mode=Mode.NONSTREAM, + ) + ) + def test_pre_call_blocks_flat_tool_outside_the_allow_list( + self, + client: GuardrailsClient, + resources: ResourceManager, + scoped_key: str, + endpoint: FlatToolEndpoint, + ) -> None: + name: Final = f"e2e-toolperm-block-{endpoint}-{unique_marker()}" + _register_tool_permission(client, resources, name=name) + + outcome: Final = poll_until_blocked_stream( + lambda: _send_flat_tool( + client, scoped_key, endpoint, guardrail=name, tool=DENIED_TOOL, schema=DENIED_TOOL_SCHEMA + ) + ) + + assert outcome.status_code == 400, ( + f"tool_permission let a tool outside the allow-list through /{endpoint}; " + f"got {outcome.status_code}: {outcome.body[:400]}" + ) + assert DENIED_TOOL.function.name in outcome.body, ( + f"the block must name the denied tool so the caller can fix the request; got: {outcome.body[:400]}" + ) + assert "Violated guardrail policy" in outcome.body, ( + f"the block must be a guardrail verdict, got: {outcome.body[:400]}" + ) + + @pytest.mark.parametrize( + "endpoint", + [ + pytest.param( + "messages", + marks=pytest.mark.covers("guardrail.tool_permission.pre_call.allows", exercised_on=["messages"]), + ), + pytest.param( + "responses", + marks=pytest.mark.covers("guardrail.tool_permission.pre_call.allows", exercised_on=["responses"]), + ), + ], + ) + @meta( + Subject( + domain=Domain.GUARDRAILS, + providers=(Provider.GEMINI,), + models=(MODEL,), + capabilities=(Capability.FUNCTION_CALLING,), + mode=Mode.NONSTREAM, + ) + ) + def test_pre_call_allows_permitted_flat_tool( + self, + client: GuardrailsClient, + resources: ResourceManager, + scoped_key: str, + endpoint: FlatToolEndpoint, + ) -> None: + name: Final = f"e2e-toolperm-allow-{endpoint}-{unique_marker()}" + _register_tool_permission(client, resources, name=name) + + outcome: Final = poll_until_guardrail_applied( + lambda: _send_flat_tool( + client, + scoped_key, + endpoint, + guardrail=name, + tool=ALLOWED_TOOL, + schema=ALLOWED_TOOL_SCHEMA, + require_tool=True, + ), + name, + ) + + assert outcome.ok, f"the permitted tool must be served, got {outcome.status_code}: {outcome.body[:400]}" + applied: Final = _applied_guardrails(outcome) + assert name in applied, ( + f"the allowed call must carry x-litellm-applied-guardrails naming the guardrail; got {applied!r}" + ) + called: Final = _flat_tool_call_names(endpoint, outcome.body) assert called == (ALLOWED_TOOL.function.name,), ( f"the served call must carry one tool call for the permitted tool, got {called!r}: {outcome.body[:400]}" ) diff --git a/tests/e2e/llm_translation/realtime/REALTIME_COVERAGE_MATRIX.md b/tests/e2e/llm_translation/realtime/REALTIME_COVERAGE_MATRIX.md index c85471da90d..1694024f390 100644 --- a/tests/e2e/llm_translation/realtime/REALTIME_COVERAGE_MATRIX.md +++ b/tests/e2e/llm_translation/realtime/REALTIME_COVERAGE_MATRIX.md @@ -19,6 +19,15 @@ a matching `function_call` output item, the test sends a `function_call_output` back, and the follow-up response incorporates the result (the temperature 72 appears). That raw-websocket tool path is the source of truth for tool calling. +The audio surfaces provision their own OpenAI and Azure deployments. +`TestRealtimeTranslation` streams the spoken weather question into +`/v1/realtime/translations` with French as the target and asserts translated +audio, a French transcript, and a billed spend row. `TestRealtimeLiveTranscription` +streams it into `/v1/realtime?intent=transcription` on gpt-live-transcribe and +asserts the deltas add up to the completed transcript and the session is billed. +`test_azure_ga_text_turn_is_answered_and_billed` guards a plain text turn over +the Azure GA deployment, spend row included + `test_pipecat_tool_smoke` is a realism layer through pipecat for openai, azure, and gemini only (not vertex_ai: native-audio live is flaky under pipecat tool calling while raw-ws tools pass; see pipecat-ai/pipecat#2544). Assertions are @@ -48,8 +57,9 @@ Bedrock and xai (`xai/grok-4-1-fast-non-reasoning`) are supported by the proxy b kept commented out in `PROVIDERS` until they pass end-to-end here; re-enable them by uncommenting their entry. -Every provider is provisioned and asserted; the suite never skips a provider. Per -`tests/e2e/AGENTS.md` there is no sanctioned skip: the whole-suite proxy-liveness +Azure realtime translation is explicitly skipped pending investigation of intermittent +missing transcripts and does not count as qualified coverage. OpenAI translation and +other Azure realtime cases remain enabled. Per `tests/e2e/AGENTS.md`, the whole-suite proxy-liveness probe hard-fails when no proxy answers, and a provider whose credentials or upstream realtime model are missing on the gateway is likewise a hard failure, not a skip. Give the gateway each provider's credentials to turn its tests green. diff --git a/tests/e2e/llm_translation/realtime/realtime_client.py b/tests/e2e/llm_translation/realtime/realtime_client.py index 6bd5d61d721..7e7f9f424a2 100644 --- a/tests/e2e/llm_translation/realtime/realtime_client.py +++ b/tests/e2e/llm_translation/realtime/realtime_client.py @@ -29,9 +29,13 @@ from models import LiteLLMParamsBody _M = TypeVar("_M", bound=BaseModel) +REALTIME_ROUTE: Final = "/v1/realtime" +TRANSLATIONS_ROUTE: Final = "/v1/realtime/translations" -def realtime_ws_url(model: str) -> str: - return f"{ws_base_url()}/v1/realtime?{urlencode({'model': model})}" + +def realtime_ws_url(model: str, *, route: str = REALTIME_ROUTE, intent: str | None = None) -> str: + query: Final = {"model": model} if intent is None else {"model": model, "intent": intent} + return f"{ws_base_url()}{route}?{urlencode(query)}" @dataclass(frozen=True, slots=True) @@ -183,6 +187,75 @@ class InputAudioBufferAppend(BaseModel): audio: str +class InputAudioBufferCommit(BaseModel): + type: str = "input_audio_buffer.commit" + + +class SessionInputAudioBufferAppend(BaseModel): + type: str = "session.input_audio_buffer.append" + audio: str + + +AudioAppend = InputAudioBufferAppend | SessionInputAudioBufferAppend + + +class TranslationOutput(BaseModel): + language: str + + +class TranslationAudio(BaseModel): + output: TranslationOutput + + +class TranslationSessionConfig(BaseModel): + audio: TranslationAudio + + +class TranslationSessionUpdate(BaseModel): + type: str = "session.update" + session: TranslationSessionConfig + + +class PcmFormat(BaseModel): + type: str = "audio/pcm" + rate: int = 24000 + + +class InputTranscription(BaseModel): + model: str + + +class TranscriptionAudioInput(BaseModel): + format: PcmFormat = PcmFormat() + transcription: InputTranscription + + +class TranscriptionAudio(BaseModel): + input: TranscriptionAudioInput + + +class TranscriptionSessionConfig(BaseModel): + type: str = "transcription" + audio: TranscriptionAudio + + +class TranscriptionSessionUpdate(BaseModel): + type: str = "session.update" + session: TranscriptionSessionConfig + + +RealtimeClientEvent = ( + SessionUpdate + | TranslationSessionUpdate + | TranscriptionSessionUpdate + | ConversationItemCreate + | ResponseCreate + | InputAudioBufferAppend + | InputAudioBufferCommit + | SessionInputAudioBufferAppend +) + + def user_message(text: str) -> ConversationItemCreate: return ConversationItemCreate( item=MessageItem(content=[InputTextContent(text=text)]) @@ -320,7 +393,7 @@ class RealtimeSession: connection: Connection @step("Send the realtime event {event.type} over the websocket") - def send(self, event: SessionUpdate | ConversationItemCreate | ResponseCreate | InputAudioBufferAppend) -> None: + def send(self, event: RealtimeClientEvent) -> None: self.connection.send(event.model_dump_json(by_alias=True, exclude_none=True)) @step("Wait for a {stop_type} event on the realtime websocket") @@ -350,9 +423,9 @@ class RealtimeSession: @step("Stream the spoken question as mic chunks, then silence until the turn goes idle") def stream_and_collect( self, - chunks: Sequence[InputAudioBufferAppend], + chunks: Sequence[AudioAppend], *, - tail: InputAudioBufferAppend, + tail: AudioAppend, interval: float, idle: float, timeout: float, @@ -363,9 +436,9 @@ class RealtimeSession: def _live_mic_events( self, - chunks: Sequence[InputAudioBufferAppend], + chunks: Sequence[AudioAppend], *, - tail: InputAudioBufferAppend, + tail: AudioAppend, interval: float, idle: float, timeout: float, @@ -408,13 +481,19 @@ class RealtimeClient: ) return model_name, model_id - @step("Open a /v1/realtime websocket session to {model}") + @step("Open a {route} websocket session to {model}") @contextmanager def connect( - self, *, key: str, model: str, timeout: float = 15.0 + self, + *, + key: str, + model: str, + route: str = REALTIME_ROUTE, + intent: str | None = None, + timeout: float = 15.0, ) -> Generator[RealtimeSession, None, None]: with connect( - realtime_ws_url(model), + realtime_ws_url(model, route=route, intent=intent), additional_headers={"Authorization": f"Bearer {key}"}, open_timeout=timeout, ) as connection: diff --git a/tests/e2e/llm_translation/realtime/test_realtime_e2e.py b/tests/e2e/llm_translation/realtime/test_realtime_e2e.py index 3b7ba3a2430..7dfb8671202 100644 --- a/tests/e2e/llm_translation/realtime/test_realtime_e2e.py +++ b/tests/e2e/llm_translation/realtime/test_realtime_e2e.py @@ -4,7 +4,10 @@ Each test opens a websocket through the proxy, speaks the OpenAI GA realtime event schema, and asserts the proxy normalizes the provider's stream into that schema: the session lifecycle, the canonical response event sequence with a reconstructed transcript and usage, and a full tool-call round-trip (call -> -tool result -> a follow-up response that uses the result). +tool result -> a follow-up response that uses the result). The audio tests +stream the spoken weather question into /v1/realtime/translations and into a +/v1/realtime?intent=transcription session, and assert the translated or +transcribed output and the session's spend row. One GA-speaking client validates every provider; only the model alias changes. Every provider is provisioned at session start, so a missing realtime alias is a @@ -12,19 +15,28 @@ hard failure, not a skip; once configured, a protocol failure is likewise a hard failure. See REALTIME_COVERAGE_MATRIX.md. """ +import base64 +import wave +from pathlib import Path +from types import MappingProxyType from typing import Final import pytest from e2e_metadata import Capability, Domain, Mode, Provider, Route, Subject, meta from lifecycle import ResourceManager -from models import LiteLLMParamsBody +from models import LiteLLMParamsBody, SpendLogRow from pydantic import BaseModel from realtime_client import ( PROVIDERS, + TRANSLATIONS_ROUTE, ConversationItemCreate, + DeltaEvent, FunctionCallArgumentsDone, FunctionCallOutputItem, FunctionTool, + InputAudioBufferAppend, + InputAudioBufferCommit, + InputTranscription, JsonSchema, JsonSchemaProperty, RealtimeClient, @@ -35,8 +47,18 @@ from realtime_client import ( ResponseDone, ServerEnvelope, SessionConfig, + SessionInputAudioBufferAppend, SessionUpdate, + TranscriptionAudio, + TranscriptionAudioInput, + TranscriptionSessionConfig, + TranscriptionSessionUpdate, + TranslationAudio, + TranslationOutput, + TranslationSessionConfig, + TranslationSessionUpdate, as_text, + events_of_type, parse_last, realtime_model, transcript, @@ -264,3 +286,215 @@ def test_upstream_handshake_refusal_is_an_error_event_and_policy_close( assert closed.value.rcvd is not None assert closed.value.rcvd.code == 1008, closed.value + + +WEATHER_WAV: Final = Path(__file__).parent / "fixtures" / "weather_question_24k.wav" +PCM_RATE: Final = 24000 +CHUNK_SECONDS: Final = 0.1 +CHUNK_BYTES: Final = int(PCM_RATE * CHUNK_SECONDS) * 2 +SILENCE_B64: Final = base64.b64encode(bytes(CHUNK_BYTES)).decode() +REGISTRY_ROUTES: Final = MappingProxyType({"openai": "openai", "azure": "azure_openai"}) + + +def weather_pcm_chunks() -> tuple[str, ...]: + with wave.open(str(WEATHER_WAV), "rb") as wav: + assert (wav.getnchannels(), wav.getsampwidth(), wav.getframerate()) == (1, 2, PCM_RATE), ( + "fixture must be mono PCM16 at 24 kHz" + ) + pcm: Final = wav.readframes(wav.getnframes()) + return tuple(base64.b64encode(pcm[i : i + CHUNK_BYTES]).decode() for i in range(0, len(pcm), CHUNK_BYTES)) + + +def has_billed_row(rows: list[SpendLogRow]) -> bool: + return any((row.spend or 0) > 0 for row in rows) + + +def audio_marks(provider: RealtimeProvider, capability: str) -> tuple[pytest.MarkDecorator, ...]: + return ( + pytest.mark.covers(f"llm.realtime.{REGISTRY_ROUTES[provider.id]}.{capability}.stream.works"), + meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.REALTIME, + providers=(Provider(provider.id),), + models=(provider.litellm_params.model,), + capabilities=(Capability.AUDIO_INPUT,), + mode=Mode.WEBSOCKET, + ) + ), + ) + + +TRANSLATION_PROVIDERS: Final = ( + RealtimeProvider( + "openai", + "openai-translate", + LiteLLMParamsBody(model="openai/gpt-realtime-translate", api_key="os.environ/OPENAI_API_KEY"), + ), + RealtimeProvider( + "azure", + "azure-translate", + LiteLLMParamsBody( + model="azure/gpt-realtime-translate", + api_base="os.environ/AZURE_API_BASE", + api_key="os.environ/AZURE_API_KEY", + ), + ), +) + +LIVE_TRANSCRIPTION_PROVIDERS: Final = ( + RealtimeProvider( + "openai", + "openai-live-transcribe", + LiteLLMParamsBody(model="openai/gpt-live-transcribe", api_key="os.environ/OPENAI_API_KEY"), + ), + RealtimeProvider( + "azure", + "azure-live-transcribe", + LiteLLMParamsBody( + model="azure/gpt-live-transcribe", + api_base="os.environ/AZURE_API_BASE", + api_key="os.environ/AZURE_API_KEY", + ), + ), +) + +TRANSLATION_PARAMS: Final = tuple( + pytest.param( + p, + id=p.id, + marks=( + *audio_marks(p, "translation"), + pytest.mark.skipif( + p.id == "azure", + reason="Azure realtime translation intermittently returns no transcript; qualification deferred", + ), + ), + ) + for p in TRANSLATION_PROVIDERS +) +LIVE_TRANSCRIPTION_PARAMS: Final = tuple( + pytest.param(p, id=p.id, marks=audio_marks(p, "transcription")) for p in LIVE_TRANSCRIPTION_PROVIDERS +) +AZURE_GA_PROVIDER: Final = next(p for p in PROVIDERS if p.id == "azure") + + +class TranscriptionCompleted(BaseModel): + type: str + transcript: str + + +class TestRealtimeTranslation: + @pytest.mark.parametrize("provider", TRANSLATION_PARAMS) + def test_spoken_english_comes_back_as_french_audio_and_transcript_and_is_billed( + self, + client: RealtimeClient, + resources: ResourceManager, + scoped_key: str, + provider: RealtimeProvider, + ) -> None: + model, model_id = client.provision(provider) + resources.defer(lambda: client.proxy.delete_model(model_id)) + + with client.connect(key=scoped_key, model=model, route=TRANSLATIONS_ROUTE) as session: + session.send( + TranslationSessionUpdate( + session=TranslationSessionConfig(audio=TranslationAudio(output=TranslationOutput(language="fr"))) + ) + ) + session.collect_until("session.updated", timeout=30) + events: Final = session.stream_and_collect( + tuple(SessionInputAudioBufferAppend(audio=chunk) for chunk in weather_pcm_chunks()), + tail=SessionInputAudioBufferAppend(audio=SILENCE_B64), + interval=CHUNK_SECONDS, + idle=8, + timeout=60, + ) + + types: Final = tuple(e.type for e in events) + audio_bytes: Final = sum( + len(base64.b64decode(DeltaEvent.model_validate_json(e.payload).delta)) + for e in events_of_type(events, "session.output_audio.delta") + ) + assert audio_bytes > 0, f"translation returned no translated audio; types={types}" + translated: Final = "".join( + DeltaEvent.model_validate_json(e.payload).delta + for e in events_of_type(events, "session.output_transcript.delta") + ).lower() + assert translated.strip(), f"translation returned no translated text; types={types}" + assert "weather" not in translated, f"the spoken weather question came back untranslated: {translated!r}" + + rows: Final = client.proxy.poll_logs_for_key(scoped_key, predicate=has_billed_row) + assert has_billed_row(rows), f"the translation session was not billed: {rows}" + + +class TestRealtimeLiveTranscription: + @pytest.mark.parametrize("provider", LIVE_TRANSCRIPTION_PARAMS) + def test_spoken_question_streams_transcript_deltas_that_match_the_completed_transcript( + self, + client: RealtimeClient, + resources: ResourceManager, + scoped_key: str, + provider: RealtimeProvider, + ) -> None: + model, model_id = client.provision(provider) + resources.defer(lambda: client.proxy.delete_model(model_id)) + + with client.connect(key=scoped_key, model=model, intent="transcription") as session: + session.send( + TranscriptionSessionUpdate( + session=TranscriptionSessionConfig( + audio=TranscriptionAudio( + input=TranscriptionAudioInput(transcription=InputTranscription(model=model)) + ) + ) + ) + ) + session.collect_until("session.updated", timeout=30) + for chunk in weather_pcm_chunks(): + session.send(InputAudioBufferAppend(audio=chunk)) + session.send(InputAudioBufferCommit()) + events: Final = session.collect_until("conversation.item.input_audio_transcription.completed", timeout=60) + + completed: Final = TranscriptionCompleted.model_validate_json(events[-1].payload) + assert "weather" in completed.transcript.lower(), ( + f"transcript of a spoken weather question does not mention weather: {completed.transcript!r}" + ) + streamed: Final = "".join( + DeltaEvent.model_validate_json(e.payload).delta + for e in events_of_type(events, "conversation.item.input_audio_transcription.delta") + ) + assert streamed.strip() == completed.transcript.strip(), ( + f"streamed deltas {streamed!r} do not add up to the completed transcript {completed.transcript!r}" + ) + + rows: Final = client.proxy.poll_logs_for_key(scoped_key, predicate=has_billed_row) + assert has_billed_row(rows), f"the live transcription session was not billed: {rows}" + + +@meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.REALTIME, + providers=(Provider.AZURE,), + models=(AZURE_GA_PROVIDER.litellm_params.model,), + mode=Mode.WEBSOCKET, + ) +) +def test_azure_ga_text_turn_is_answered_and_billed( + client: RealtimeClient, resources: ResourceManager, scoped_key: str +) -> None: + model, model_id = client.provision(AZURE_GA_PROVIDER) + resources.defer(lambda: client.proxy.delete_model(model_id)) + + with client.connect(key=scoped_key, model=model) as session: + session.collect_until("session.created", timeout=20) + session.send(SessionUpdate(session=SessionConfig(instructions="Reply with the single word hello."))) + session.collect_until("session.updated", timeout=20) + session.send(user_message("Say the single word hello.")) + session.send(ResponseCreate()) + events: Final = session.collect_until("response.done", timeout=60) + + assert "hello" in transcript(events).lower(), f"Azure GA realtime did not answer the turn: {transcript(events)!r}" + rows: Final = client.proxy.poll_logs_for_key(scoped_key, predicate=has_billed_row) + assert has_billed_row(rows), f"the Azure GA realtime turn was not billed: {rows}" diff --git a/tests/e2e/llm_translation/test_audio_transcriptions_e2e.py b/tests/e2e/llm_translation/test_audio_transcriptions_e2e.py index cd1ee8fb03c..43c276dfdf0 100644 --- a/tests/e2e/llm_translation/test_audio_transcriptions_e2e.py +++ b/tests/e2e/llm_translation/test_audio_transcriptions_e2e.py @@ -8,10 +8,13 @@ the shared multipart transport, since the SDK refuses to send them. A model-less request comes back as one of two 400s depending on whether any wildcard deployment happens to be registered on the shared proxy, so the assertion accepts either phrasing and holds both to naming the model as the problem. +Streamed gpt-transcribe (stream=true) on OpenAI and Azure must send transcript +deltas, a done event, and data: [DONE], and bill the call. """ from __future__ import annotations +from dataclasses import dataclass from pathlib import Path from typing import Final @@ -20,10 +23,10 @@ from e2e_config import unique_marker from e2e_metadata import Domain, Mode, Provider, Route, Subject, meta from e2e_http import UnknownApiError, unwrap from lifecycle import ResourceManager -from models import LiteLLMParamsBody +from models import LiteLLMParamsBody, SpendLogRow from proxy_client import ProxyClient from pydantic import BaseModel, Field -from sdk_clients import SdkClients +from sdk_clients import SdkClients, response_header pytestmark = pytest.mark.e2e @@ -221,3 +224,102 @@ class TestWhisperTranscriptionFormats: assert all(word.start <= word.end for word in transcript.words), ( f"word timings out of order: {transcript.words}" ) + + +STREAM_DONE: Final = "[DONE]" + + +@dataclass(frozen=True, slots=True) +class _StreamingTranscriber: + id: str + registry_route: str + provider: Provider + litellm_params: LiteLLMParamsBody + + +STREAMING_TRANSCRIBERS: Final = ( + _StreamingTranscriber( + "openai", + "openai", + Provider.OPENAI, + LiteLLMParamsBody(model="openai/gpt-transcribe", api_key="os.environ/OPENAI_API_KEY"), + ), + _StreamingTranscriber( + "azure", + "azure_openai", + Provider.AZURE, + LiteLLMParamsBody( + model="azure/gpt-transcribe", + api_base="os.environ/AZURE_API_BASE", + api_key="os.environ/AZURE_API_KEY", + api_version="v1", + ), + ), +) + +STREAMING_PARAMS: Final = tuple( + pytest.param( + t, + id=t.id, + marks=( + pytest.mark.covers(f"llm.audio_transcriptions.{t.registry_route}.transcription.stream.works"), + meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.AUDIO, + providers=(t.provider,), + models=(t.litellm_params.model,), + mode=Mode.STREAM, + ) + ), + ), + ) + for t in STREAMING_TRANSCRIBERS +) + + +class _TranscriptStreamEvent(BaseModel): + type: str + delta: str = "" + text: str = "" + + +def _has_billed_row(rows: list[SpendLogRow]) -> bool: + return any((row.spend or 0) > 0 for row in rows) + + +class TestStreamedAudioTranscriptions: + @pytest.mark.parametrize("transcriber", STREAMING_PARAMS) + def test_stream_sends_transcript_deltas_then_done_and_bills_the_call( + self, proxy: ProxyClient, resources: ResourceManager, sdk: SdkClients, transcriber: _StreamingTranscriber + ) -> None: + model: Final = f"e2e-transcribe-stream-{transcriber.id}-{unique_marker()}" + model_id: Final = proxy.create_model(model, transcriber.litellm_params) + resources.defer(lambda: proxy.delete_model(model_id)) + client: Final = sdk.openai(resources.key()) + + with client.audio.transcriptions.with_streaming_response.create( + model=model, file=(WEATHER_WAV.name, WEATHER_WAV.read_bytes(), "audio/wav"), stream=True + ) as response: + content_type: Final = response_header(response.headers, "content-type") + call_id: Final = response_header(response.headers, "x-litellm-call-id") + payloads: Final = tuple( + line.removeprefix("data: ") for line in response.iter_lines() if line.startswith("data: ") + ) + + assert "text/event-stream" in (content_type or ""), f"stream=true did not stream: {content_type!r}" + assert payloads and payloads[-1] == STREAM_DONE, f"the stream did not end with data: [DONE]: {payloads[-3:]}" + assert payloads.count(STREAM_DONE) == 1, f"data: [DONE] was sent more than once: {payloads}" + events: Final = tuple(_TranscriptStreamEvent.model_validate_json(payload) for payload in payloads[:-1]) + deltas: Final = tuple(e.delta for e in events if e.type == "transcript.text.delta") + assert len(deltas) > 1, f"the transcript arrived in {len(deltas)} delta events, not as a stream: {events}" + done: Final = events[-1] + assert done.type == "transcript.text.done", f"the last event before [DONE] is not the done event: {done}" + assert "weather" in done.text.lower(), f"transcript of a spoken weather question lost the word: {done.text!r}" + assert "".join(deltas).strip() == done.text.strip(), ( + f"the deltas {deltas} do not add up to the final transcript {done.text!r}" + ) + + assert call_id, "the streamed response carries no x-litellm-call-id to find its spend log" + rows: Final = proxy.poll_logs_for_request_id(call_id, predicate=_has_billed_row) + assert _has_billed_row(rows), f"the streamed transcription was not billed: {rows}" diff --git a/tests/e2e/llm_translation/test_chat_completions_regression_e2e.py b/tests/e2e/llm_translation/test_chat_completions_regression_e2e.py index 1e0a8cbb412..4967f18818a 100644 --- a/tests/e2e/llm_translation/test_chat_completions_regression_e2e.py +++ b/tests/e2e/llm_translation/test_chat_completions_regression_e2e.py @@ -45,7 +45,7 @@ from passthrough_client import PassthroughClient pytestmark = pytest.mark.e2e COHERE_BACKEND = "cohere/command-r-08-2024" -GEMINI_BACKEND = "gemini/gemini-2.5-flash" +GEMINI_BACKEND = "gemini/gemini-3.8-flash" VERTEX_BACKEND: Final = "vertex_ai/gemini-2.5-flash" AZURE_OPENAI_BACKEND: Final = "azure/gpt-5.4-nano" AZURE_OPENAI_API_VERSION: Final = "v1" @@ -243,7 +243,7 @@ _PERSON_SCHEMA: dict[str, object] = { OPENAI_CHAT_MODEL: Final = "gpt-5.5" ANTHROPIC_CHAT_MODEL: Final = "claude-haiku-4-5" -GEMINI_FLASH_MODEL: Final = "gemini-2.5-flash" +GEMINI_FLASH_MODEL: Final = "gemini-3.8-flash" CHAT_MODELS: Final = ( pytest.param( diff --git a/tests/e2e/llm_translation/test_custom_pricing_e2e.py b/tests/e2e/llm_translation/test_custom_pricing_e2e.py index 6d8cd24648e..63b8b60867a 100644 --- a/tests/e2e/llm_translation/test_custom_pricing_e2e.py +++ b/tests/e2e/llm_translation/test_custom_pricing_e2e.py @@ -5,7 +5,7 @@ teardown) instead of relying on a statically configured model, so the check is self-contained and never inherits pricing another suite or a stale config left on the shared proxy. custom-priced-flash sets input/output rates deliberately far above the canonical gemini price; the isolation sibling shares the same -gemini/gemini-2.5-flash backend but sets no override. Three behaviors are checked +gemini/gemini-3.8-flash backend but sets no override. Three behaviors are checked independently: - billing: a real call's logged cost breakdown charges input and output tokens at @@ -37,10 +37,8 @@ from models import ( pytestmark = pytest.mark.e2e -BACKEND_MODEL = "gemini/gemini-2.5-flash" +BACKEND_MODEL = "gemini/gemini-3.8-flash" GEMINI_API_KEY = "os.environ/GEMINI_API_KEY" -# Deliberately ~100x above canonical gemini-2.5-flash (input 3e-7 / output 2.5e-6) -# so an override that is ignored or under-applied bills at the base rate and fails. CUSTOM_INPUT_RATE = 5e-05 CUSTOM_OUTPUT_RATE = 1e-04 @@ -78,7 +76,7 @@ def _provision( input_cost_per_token: float | None, output_cost_per_token: float | None, ) -> str: - """Register a fresh gemini/gemini-2.5-flash deployment (deleted on teardown) and + """Register a fresh gemini/gemini-3.8-flash deployment (deleted on teardown) and return its model name. With the cost fields set the deployment carries a custom pricing override; with them None it is a plain sibling on the same backend. The marker keeps the name unique so concurrent runs on the shared proxy never @@ -251,7 +249,7 @@ class TestCustomPricing: assert sibling_entry is not None, f"{sibling} absent from /model/info" # custom-priced-flash overrides pricing; the sibling shares the same - # gemini/gemini-2.5-flash backend but sets no override, so it must keep its + # gemini/gemini-3.8-flash backend but sets no override, so it must keep its # own price. Equal rates mean the override leaked into the shared cost map. assert ( sibling_entry.model_info.input_cost_per_token diff --git a/tests/e2e/llm_translation/test_google_native_e2e.py b/tests/e2e/llm_translation/test_google_native_e2e.py index b18683bd4ad..65a341dbc2a 100644 --- a/tests/e2e/llm_translation/test_google_native_e2e.py +++ b/tests/e2e/llm_translation/test_google_native_e2e.py @@ -21,7 +21,7 @@ from pydantic import BaseModel pytestmark = pytest.mark.e2e -UPSTREAM_MODEL = "gemini/gemini-2.5-flash" +UPSTREAM_MODEL = "gemini/gemini-3.8-flash" class _GenerateContentPart(BaseModel): diff --git a/tests/e2e/llm_translation/test_image_edits_e2e.py b/tests/e2e/llm_translation/test_image_edits_e2e.py index 66b0ebfc538..917662b9e52 100644 --- a/tests/e2e/llm_translation/test_image_edits_e2e.py +++ b/tests/e2e/llm_translation/test_image_edits_e2e.py @@ -24,7 +24,7 @@ from sdk_clients import SdkClients pytestmark = pytest.mark.e2e -IMAGE_EDIT_BACKEND: Final = "openai/gpt-image-1" +IMAGE_EDIT_BACKEND: Final = "openai/gpt-image-2.5-sunburst" _TEST_PNG = base64.b64decode( "iVBORw0KGgoAAAANSUhEUgAAAEAAAABACAIAAAAlC+aJAAAAS0lEQVR42u3PMQ0AAAwDoPo3" diff --git a/tests/e2e/llm_translation/test_messages_beta_headers_e2e.py b/tests/e2e/llm_translation/test_messages_beta_headers_e2e.py index 91a31201b0f..59035f8f6b6 100644 --- a/tests/e2e/llm_translation/test_messages_beta_headers_e2e.py +++ b/tests/e2e/llm_translation/test_messages_beta_headers_e2e.py @@ -15,48 +15,85 @@ pytestmark = pytest.mark.e2e _BETA_CONFIG: Final = files("litellm").joinpath("anthropic_beta_headers_config.json") _ANTHROPIC_MODEL: Final = "anthropic/claude-sonnet-5-5" +_VERTEX_MODEL: Final = "vertex_ai/claude-sonnet-5-5" +_VERTEX_LOCATION: Final = "global" +_AZURE_AI_MODEL: Final = "azure_ai/claude-fable-5-1" _BEDROCK_MODEL_ID: Final = "us.anthropic.claude-fable-5-1" _BETA_CONFIG_FILE: Final = TypeAdapter(dict[str, JsonValue]) _BETA_MAPPING: Final = TypeAdapter(dict[str, str | None]) _CODE_EXECUTION: Final[ToolUnionParam] = {"type": "code_execution_20250825", "name": "code_execution"} +# A live Vertex probe on 2026-10-31: each Claude 4.5 and 4.6 model takes one of these and Claude 5.5 takes neither +_VERTEX_PER_MODEL_BETAS: Final = frozenset({"computer-use-2025-01-24", "computer-use-2025-11-24"}) +_NO_PER_MODEL_BETAS: Final[frozenset[str]] = frozenset() -def _mapped_beta_headers(provider: str) -> str: - mapping: Final = _BETA_MAPPING.validate_python(_BETA_CONFIG_FILE.validate_json(_BETA_CONFIG.read_text())[provider]) - return ",".join(name for name, value in mapping.items() if value is not None) +def _mapped_beta_headers(provider: str, per_model: frozenset[str]) -> str: + config: Final = _BETA_CONFIG_FILE.validate_json(_BETA_CONFIG.read_text()) + mapping: Final = _BETA_MAPPING.validate_python(config[provider]) + header_only: Final = _BETA_MAPPING.validate_python(config.get(f"{provider}_header_only", {})) + forwarded: Final = {name for name, value in {**mapping, **header_only}.items() if value is not None} + assert per_model <= forwarded, per_model - forwarded + return ",".join(sorted(forwarded - per_model)) def _deployment(backend: str) -> LiteLLMParamsBody: - if backend.startswith("anthropic/"): - return LiteLLMParamsBody(model=backend, api_key="os.environ/ANTHROPIC_API_KEY") - return LiteLLMParamsBody( - model=backend, - aws_access_key_id="os.environ/AWS_ACCESS_KEY_ID", - aws_secret_access_key="os.environ/AWS_SECRET_ACCESS_KEY", - aws_region_name="us-east-1", - ) + match backend.split("/", 1)[0]: + case "anthropic": + return LiteLLMParamsBody(model=backend, api_key="os.environ/ANTHROPIC_API_KEY") + case "vertex_ai": + return LiteLLMParamsBody( + model=backend, + vertex_project="os.environ/VERTEXAI_PROJECT", + vertex_location=_VERTEX_LOCATION, + vertex_credentials="os.environ/VERTEXAI_CREDENTIALS", + ) + case "azure_ai": + return LiteLLMParamsBody( + model=backend, + api_base="os.environ/AZURE_AI_API_BASE", + api_key="os.environ/AZURE_AI_API_KEY", + ) + case _: + return LiteLLMParamsBody( + model=backend, + aws_access_key_id="os.environ/AWS_ACCESS_KEY_ID", + aws_secret_access_key="os.environ/AWS_SECRET_ACCESS_KEY", + aws_region_name="us-east-1", + ) class TestAnthropicBetaHeaders: @pytest.mark.parametrize( - ("backend", "beta_provider", "tools"), + ("backend", "beta_provider", "tools", "per_model"), [ - pytest.param(_ANTHROPIC_MODEL, "anthropic", [_CODE_EXECUTION], id="anthropic"), - pytest.param(f"bedrock/invoke/{_BEDROCK_MODEL_ID}", "bedrock", [], id="bedrock-invoke"), - pytest.param(f"bedrock/converse/{_BEDROCK_MODEL_ID}", "bedrock_converse", [], id="bedrock-converse"), + pytest.param(_ANTHROPIC_MODEL, "anthropic", [_CODE_EXECUTION], _NO_PER_MODEL_BETAS, id="anthropic"), + pytest.param(_VERTEX_MODEL, "vertex_ai", [], _VERTEX_PER_MODEL_BETAS, id="vertex-ai"), + pytest.param(_AZURE_AI_MODEL, "azure_ai", [], _NO_PER_MODEL_BETAS, id="azure-ai"), + pytest.param( + f"bedrock/invoke/{_BEDROCK_MODEL_ID}", "bedrock", [], _NO_PER_MODEL_BETAS, id="bedrock-invoke" + ), + pytest.param( + f"bedrock/converse/{_BEDROCK_MODEL_ID}", + "bedrock_converse", + [], + _NO_PER_MODEL_BETAS, + id="bedrock-converse", + ), ], ) @pytest.mark.covers( "llm.messages.anthropic.basic.nonstream.works", "llm.messages.bedrock_invoke.basic.nonstream.works", "llm.messages.bedrock_converse.basic.nonstream.works", + "llm.messages.vertex.basic.nonstream.works", + "llm.messages.azure_foundry.basic.nonstream.works", ) @meta( Subject( domain=Domain.LLM_TRANSLATION, route=Route.MESSAGES, - providers=(Provider.ANTHROPIC, Provider.BEDROCK), - models=(_ANTHROPIC_MODEL, _BEDROCK_MODEL_ID), + providers=(Provider.ANTHROPIC, Provider.BEDROCK, Provider.VERTEX_AI, Provider.AZURE_AI), + models=(_ANTHROPIC_MODEL, _BEDROCK_MODEL_ID, _VERTEX_MODEL, _AZURE_AI_MODEL), mode=Mode.NONSTREAM, ) ) @@ -68,6 +105,7 @@ class TestAnthropicBetaHeaders: backend: str, beta_provider: str, tools: list[ToolUnionParam], + per_model: frozenset[str], ) -> None: model: Final = f"e2e-messages-beta-{unique_marker()}" model_id: Final = proxy.create_model(model, _deployment(backend)) @@ -78,7 +116,7 @@ class TestAnthropicBetaHeaders: max_tokens=64, messages=[{"role": "user", "content": "Say 'hello' and nothing else"}], tools=tools, - extra_headers={"anthropic-beta": _mapped_beta_headers(beta_provider)}, + extra_headers={"anthropic-beta": _mapped_beta_headers(beta_provider, per_model)}, extra_body=NO_PROXY_CACHE, ) diff --git a/tests/e2e/llm_translation/test_messages_mid_conversation_system_e2e.py b/tests/e2e/llm_translation/test_messages_mid_conversation_system_e2e.py index 84e0674d959..59b1224a479 100644 --- a/tests/e2e/llm_translation/test_messages_mid_conversation_system_e2e.py +++ b/tests/e2e/llm_translation/test_messages_mid_conversation_system_e2e.py @@ -41,7 +41,7 @@ from proxy_client import ProxyClient from pydantic import BaseModel from sdk_clients import NO_PROXY_CACHE, SdkClients -pytestmark = pytest.mark.e2e +pytestmark = [pytest.mark.e2e, pytest.mark.provider_live] FLAGGED_INVOKE_MODEL = "bedrock/invoke/us.anthropic.claude-sonnet-5" UNFLAGGED_INVOKE_MODEL = "bedrock/invoke/us.anthropic.claude-haiku-4-5-20251001-v1:0" diff --git a/tests/e2e/llm_translation/test_passthrough_e2e.py b/tests/e2e/llm_translation/test_passthrough_e2e.py index 52d1c10d829..3eaeef6bddd 100644 --- a/tests/e2e/llm_translation/test_passthrough_e2e.py +++ b/tests/e2e/llm_translation/test_passthrough_e2e.py @@ -5,7 +5,7 @@ and verifies the proxy still logged a costed SpendLogs row (call_type="pass_through_endpoint"), correlated by the id the caller was served: the x-litellm-call-id header on gemini, the `msg_...` message id on anthropic. -Covered: gemini ("gemini-2.5-flash") + anthropic ("claude-haiku-4-5"), streaming + +Covered: gemini ("gemini-3.8-flash") + anthropic ("claude-haiku-4-5"), streaming + non-streaming, plus native tool calls. See LLM_TRANSLATION_COVERAGE_MATRIX.md. A passthrough call returning non-2xx fails hard (never a skip); once it returns @@ -32,7 +32,7 @@ from passthrough_client import ( completed_responses_object, ) -GEMINI_MODEL: Final = "gemini-2.5-flash" +GEMINI_MODEL: Final = "gemini-3.8-flash" ANTHROPIC_PASSTHROUGH_MODEL: Final = "claude-haiku-4-5" EMBEDDING_MODEL = "text-embedding-3-small" REALTIME_MODEL = "gpt-realtime-2" @@ -291,7 +291,7 @@ class TestPassthroughModelAllowlist: result = client.anthropic_message(key, ANTHROPIC_PASSTHROUGH_MODEL, f"say hi {unique_marker()}") assert result.status_code == 403, ( - "a key restricted to gemini-2.5-flash must be denied a claude passthrough call, " + "a key restricted to gemini-3.8-flash must be denied a claude passthrough call, " f"got {result.status_code}: {result.body[:300]}" ) diff --git a/tests/e2e/llm_translation/test_realtime_http_e2e.py b/tests/e2e/llm_translation/test_realtime_http_e2e.py index ee3ce3893c2..3abb74308e8 100644 --- a/tests/e2e/llm_translation/test_realtime_http_e2e.py +++ b/tests/e2e/llm_translation/test_realtime_http_e2e.py @@ -1,14 +1,18 @@ """Vendor §9.19: realtime client_secrets + calls HTTP surface (LIT-4778). Websocket coverage already lives under realtime/; this file pins the HTTP -client-secret mint and the missing-auth contract. +client-secret mint (realtime, translation and transcription sessions), the +translation token scope, and the missing-auth contract. """ from __future__ import annotations +from dataclasses import dataclass +from typing import Final + import pytest from e2e_config import unique_marker -from e2e_http import NoBody, assert_auth_denied, unwrap +from e2e_http import NoBody, PartialBody, UnknownApiError, assert_auth_denied, unwrap from e2e_metadata import Domain, Provider, Route, Subject, meta from lifecycle import ResourceManager from models import LiteLLMParamsBody @@ -18,6 +22,7 @@ from pydantic import BaseModel pytestmark = pytest.mark.e2e REALTIME_BACKEND = "openai/gpt-realtime" +TRANSLATIONS_CLIENT_SECRETS: Final = "/v1/realtime/translations/client_secrets" class RealtimeSession(BaseModel): @@ -38,8 +43,65 @@ class RealtimeClientSecretRequest(BaseModel): session: RealtimeSession | None = None +class TurnDetection(BaseModel): + type: str + + +class SessionTranscription(BaseModel): + model: str | None = None + + +class SessionAudioInput(BaseModel): + transcription: SessionTranscription | None = None + turn_detection: TurnDetection | None = None + + +class SessionAudioOutput(BaseModel): + language: str | None = None + + +class SessionAudio(BaseModel): + input: SessionAudioInput | None = None + output: SessionAudioOutput | None = None + + +class TranslationSession(BaseModel): + model: str + audio: SessionAudio + + +class TranscriptionSession(BaseModel): + type: str = "transcription" + audio: SessionAudio + + +class SessionClientSecretRequest(BaseModel): + session: TranslationSession | TranscriptionSession + + +class NullableAudioInput(PartialBody): + turn_detection: TurnDetection | None = None + + +class NullableAudio(PartialBody): + input: NullableAudioInput + + +class NullableRealtimeSession(PartialBody): + type: str + model: str + instructions: str | None = None + audio: NullableAudio + + +class NullableClientSecretRequest(PartialBody): + model: str + session: NullableRealtimeSession + + class RealtimeClientSecretSession(BaseModel): type: str | None = None + audio: SessionAudio | None = None class RealtimeClientSecretResponse(BaseModel): @@ -49,15 +111,85 @@ class RealtimeClientSecretResponse(BaseModel): def _register(proxy: ProxyClient, resources: ResourceManager) -> tuple[str, str]: - model = f"e2e-realtime-http-{unique_marker()}" - model_id = proxy.create_model( - model, - LiteLLMParamsBody(model=REALTIME_BACKEND, api_key="os.environ/OPENAI_API_KEY"), + return _register_backend( + proxy, resources, LiteLLMParamsBody(model=REALTIME_BACKEND, api_key="os.environ/OPENAI_API_KEY") ) + + +def _register_backend( + proxy: ProxyClient, resources: ResourceManager, litellm_params: LiteLLMParamsBody +) -> tuple[str, str]: + model: Final = f"e2e-realtime-http-{unique_marker()}" + model_id: Final = proxy.create_model(model, litellm_params) resources.defer(lambda: proxy.delete_model(model_id)) return model, resources.key() +@dataclass(frozen=True, slots=True) +class _AudioBackend: + id: str + registry_route: str + provider: Provider + litellm_params: LiteLLMParamsBody + + @property + def upstream_model(self) -> str: + return self.litellm_params.model.split("/", 1)[1] + + +def _openai_backend(model: str) -> _AudioBackend: + return _AudioBackend( + "openai", "openai", Provider.OPENAI, LiteLLMParamsBody(model=model, api_key="os.environ/OPENAI_API_KEY") + ) + + +def _azure_backend(model: str) -> _AudioBackend: + return _AudioBackend( + "azure", + "azure_openai", + Provider.AZURE, + LiteLLMParamsBody(model=model, api_base="os.environ/AZURE_API_BASE", api_key="os.environ/AZURE_API_KEY"), + ) + + +TRANSLATION_BACKENDS: Final = ( + _openai_backend("openai/gpt-realtime-translate"), + _azure_backend("azure/gpt-realtime-translate"), +) +TRANSCRIPTION_BACKENDS: Final = ( + _openai_backend("openai/gpt-live-transcribe"), + _azure_backend("azure/gpt-live-transcribe"), +) + + +def _subject(backend: _AudioBackend) -> pytest.MarkDecorator: + return meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.REALTIME, + providers=(backend.provider,), + models=(backend.litellm_params.model,), + ) + ) + + +TRANSLATION_PARAMS: Final = tuple( + pytest.param( + b, + id=b.id, + marks=(pytest.mark.covers(f"llm.realtime.{b.registry_route}.translation.stream.works"), _subject(b)), + ) + for b in TRANSLATION_BACKENDS +) +TRANSCRIPTION_PARAMS: Final = tuple(pytest.param(b, id=b.id, marks=_subject(b)) for b in TRANSCRIPTION_BACKENDS) + + +def _french_translation_request(model: str) -> SessionClientSecretRequest: + return SessionClientSecretRequest( + session=TranslationSession(model=model, audio=SessionAudio(output=SessionAudioOutput(language="fr"))) + ) + + class TestRealtimeHttp: @pytest.mark.covers("llm.realtime.openai.basic.nonstream.works") @meta( @@ -110,3 +242,150 @@ class TestRealtimeHttp: json=NoBody(), ) assert_auth_denied(result, "realtime calls missing auth") + + +class TestRealtimeTranslationClientSecrets: + @pytest.mark.parametrize("backend", TRANSLATION_PARAMS) + def test_translations_route_mints_a_french_translation_session( + self, proxy: ProxyClient, resources: ResourceManager, backend: _AudioBackend + ) -> None: + model, key = _register_backend(proxy, resources, backend.litellm_params) + secret: Final = unwrap( + proxy.transport.post( + TRANSLATIONS_CLIENT_SECRETS, + headers=proxy.transport.bearer(key), + json=_french_translation_request(model), + response_type=RealtimeClientSecretResponse, + ) + ) + assert secret.value, f"client secret value missing: {secret}" + assert secret.session is not None and secret.session.type == "translation", ( + f"the translations route did not mint a translation session: {secret.session}" + ) + output: Final = secret.session.audio.output if secret.session.audio else None + assert output is not None and output.language == "fr", ( + f"the requested target language did not reach the session: {secret.session}" + ) + + @meta( + Subject( + domain=Domain.PROXY_AUTH, + route=Route.REALTIME, + providers=(Provider.OPENAI,), + models=(TRANSLATION_BACKENDS[0].litellm_params.model,), + ) + ) + def test_translation_token_is_refused_by_the_realtime_calls_route( + self, proxy: ProxyClient, resources: ResourceManager + ) -> None: + model, key = _register_backend(proxy, resources, TRANSLATION_BACKENDS[0].litellm_params) + secret: Final = unwrap( + proxy.transport.post( + TRANSLATIONS_CLIENT_SECRETS, + headers=proxy.transport.bearer(key), + json=_french_translation_request(model), + response_type=RealtimeClientSecretResponse, + ) + ) + assert secret.value, f"client secret value missing: {secret}" + result: Final = proxy.transport.send( + "/v1/realtime/calls", headers=proxy.transport.bearer(secret.value), json=NoBody() + ) + assert result.status_code == 401, ( + f"a translation token opened a plain realtime call: {result.status_code} {result.body[:300]}" + ) + assert "not valid for this Realtime endpoint" in result.body, ( + f"the refusal does not say the token belongs to another endpoint: {result.body[:300]}" + ) + + @meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.REALTIME, + providers=(Provider.OPENAI,), + models=(TRANSLATION_BACKENDS[0].litellm_params.model,), + ) + ) + def test_translation_session_on_the_realtime_route_is_rejected( + self, proxy: ProxyClient, resources: ResourceManager + ) -> None: + model, key = _register_backend(proxy, resources, TRANSLATION_BACKENDS[0].litellm_params) + result: Final = proxy.transport.post( + "/v1/realtime/client_secrets", + headers=proxy.transport.bearer(key), + json=RealtimeClientSecretRequest(model=model, session=RealtimeSession(type="translation", model=model)), + response_type=RealtimeClientSecretResponse, + ) + match result: + case UnknownApiError(status_code=400, body=body): + assert "translations endpoint" in body, f"the 400 does not point at the translations route: {body}" + case other: + pytest.fail(f"a translation session on /v1/realtime/client_secrets expected a 400, got {other!r}") + + +class TestRealtimeTranscriptionClientSecrets: + @pytest.mark.parametrize("backend", TRANSCRIPTION_PARAMS) + def test_transcription_session_runs_on_the_deployment_model( + self, proxy: ProxyClient, resources: ResourceManager, backend: _AudioBackend + ) -> None: + model, key = _register_backend(proxy, resources, backend.litellm_params) + secret: Final = unwrap( + proxy.transport.post( + "/v1/realtime/client_secrets", + headers=proxy.transport.bearer(key), + json=SessionClientSecretRequest( + session=TranscriptionSession( + audio=SessionAudio(input=SessionAudioInput(transcription=SessionTranscription(model=model))) + ) + ), + response_type=RealtimeClientSecretResponse, + ) + ) + assert secret.value, f"client secret value missing: {secret}" + assert secret.session is not None and secret.session.type == "transcription", ( + f"the client secret did not mint a transcription session: {secret.session}" + ) + audio_input: Final = secret.session.audio.input if secret.session.audio else None + transcription: Final = audio_input.transcription if audio_input else None + assert transcription is not None and transcription.model == backend.upstream_model, ( + f"the session does not transcribe with the deployment's model {backend.upstream_model}: {secret.session}" + ) + + +class TestRealtimeClientSecretNulls: + @meta( + Subject( + domain=Domain.LLM_TRANSLATION, + route=Route.REALTIME, + providers=(Provider.OPENAI,), + models=(REALTIME_BACKEND,), + ) + ) + def test_top_level_null_is_dropped_and_nested_null_is_kept( + self, proxy: ProxyClient, resources: ResourceManager + ) -> None: + model, key = _register(proxy, resources) + secret: Final = unwrap( + proxy.transport.post( + "/v1/realtime/client_secrets", + headers=proxy.transport.bearer(key), + json=NullableClientSecretRequest( + model=model, + session=NullableRealtimeSession( + type="realtime", + model=model, + instructions=None, + audio=NullableAudio(input=NullableAudioInput(turn_detection=None)), + ), + ), + response_type=RealtimeClientSecretResponse, + ) + ) + assert secret.value, f"a session with instructions: null was not minted: {secret}" + audio_input: Final = secret.session.audio.input if secret.session and secret.session.audio else None + assert audio_input is not None and "turn_detection" in audio_input.model_fields_set, ( + f"the session does not report turn detection: {secret.session}" + ) + assert audio_input.turn_detection is None, ( + f"turn_detection: null was dropped, so the session fell back to {audio_input.turn_detection}" + ) diff --git a/tests/e2e/llm_translation/test_responses_e2e.py b/tests/e2e/llm_translation/test_responses_e2e.py index a0f185c4077..6b299fad18c 100644 --- a/tests/e2e/llm_translation/test_responses_e2e.py +++ b/tests/e2e/llm_translation/test_responses_e2e.py @@ -57,7 +57,7 @@ OPENAI_VISION_BACKEND: Final = "openai/gpt-4o" ANTHROPIC_BACKEND: Final = "anthropic/claude-haiku-4-5" BEDROCK_CONVERSE_BACKEND: Final = "bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0" VERTEX_BACKEND: Final = "vertex_ai/gemini-2.5-flash" -GEMINI_BACKEND: Final = "gemini/gemini-2.5-flash" +GEMINI_BACKEND: Final = "gemini/gemini-3.8-flash" OPENAI_RESPONSES_BACKEND: Final = "openai/gpt-5.5" INSTRUCTIONS = "You are a helpful assistant" CAT_IMAGE_URL = "https://upload.wikimedia.org/wikipedia/commons/3/3a/Cat03.jpg" diff --git a/tests/e2e/llm_translation/test_responses_retrieve_e2e.py b/tests/e2e/llm_translation/test_responses_retrieve_e2e.py index 4a08259c028..0e954af0952 100644 --- a/tests/e2e/llm_translation/test_responses_retrieve_e2e.py +++ b/tests/e2e/llm_translation/test_responses_retrieve_e2e.py @@ -69,9 +69,6 @@ def _retrieve_response(proxy: ProxyClient, key: str, response_id: str) -> Respon class TestResponsesRetrieve: - @pytest.mark.skip( - reason="stage red: product gap (LIT-5446), retrieve returns a different id than the stored response (non-idempotent response-id re-encryption)" - ) @pytest.mark.covers("llm.responses.openai.basic.nonstream.works") @meta( Subject( diff --git a/tests/e2e/logging/logging_client.py b/tests/e2e/logging/logging_client.py index 4dd681f59e8..3903d1a8363 100644 --- a/tests/e2e/logging/logging_client.py +++ b/tests/e2e/logging/logging_client.py @@ -18,10 +18,11 @@ import json import os import time from dataclasses import dataclass -from typing import Callable, Literal +from datetime import datetime, timedelta, timezone +from typing import Callable, Final, Literal import pytest -from pydantic import BaseModel, ConfigDict, Field, JsonValue, TypeAdapter, ValidationError +from pydantic import AliasChoices, BaseModel, ConfigDict, Field, JsonValue, TypeAdapter, ValidationError, field_validator from e2e_config import POLL_INTERVAL, POLL_TIMEOUT, settle_propagation from e2e_metadata import step @@ -124,23 +125,39 @@ class CreateGuardrailResponse(BaseModel): guardrail_name: str | None = None +_LANGFUSE_JSON: Final[TypeAdapter[JsonValue]] = TypeAdapter(JsonValue) + + class LangfuseObservation(BaseModel): - model_config = ConfigDict(extra="ignore", populate_by_name=True) + model_config = ConfigDict(extra="ignore", populate_by_name=True, frozen=True) id: str trace_id: str | None = Field(default=None, alias="traceId") name: str | None = None type: str | None = None - calculated_total_cost: float | None = Field(default=None, alias="calculatedTotalCost") + calculated_total_cost: float | None = Field( + default=None, validation_alias=AliasChoices("totalCost", "calculatedTotalCost") + ) level: str | None = None - input: object | None = None - output: object | None = None - metadata: object | None = None + input: JsonValue = None + output: JsonValue = None + metadata: JsonValue = None usage: object | None = None usage_details: object | None = Field(default=None, alias="usageDetails") model: str | None = None + @field_validator("input", "output", "metadata", mode="before") + @classmethod + def decode_json_fields(cls, value: object) -> JsonValue: + if not isinstance(value, str): + return _LANGFUSE_JSON.validate_python(value) + try: + return _LANGFUSE_JSON.validate_json(value) + except ValidationError: + return value + + class LangfuseObservationList(BaseModel): model_config = ConfigDict(extra="ignore") @@ -171,12 +188,15 @@ def is_otel_v2_generation(obs: LangfuseObservation, *, key_alias: str) -> bool: class LangfuseListParams(BaseModel): - model_config = ConfigDict(populate_by_name=True) + model_config = ConfigDict(populate_by_name=True, frozen=True) limit: int = 100 trace_id: str | None = Field(default=None, alias="traceId") name: str | None = None - from_start_time: str | None = Field(default=None, alias="fromStartTime") + from_start_time: str = Field(alias="fromStartTime") + to_start_time: str = Field(alias="toStartTime") + fields: str = "core,basic,io,metadata,model,usage" + expand_metadata: str = Field(default="attributes", alias="expandMetadata") @dataclass(frozen=True, slots=True) @@ -580,14 +600,16 @@ class LoggingClient: name: str | None = None, from_start_time: str | None = None, ) -> list[LangfuseObservation]: - result = get( - URL(f"{creds.host}/api/public/observations"), + now: Final = datetime.now(timezone.utc) + result: Final = get( + URL(f"{creds.host}/api/public/v2/observations"), headers=creds.auth_headers, params=LangfuseListParams( limit=100, traceId=trace_id, name=name, - fromStartTime=from_start_time, + fromStartTime=from_start_time or (now - timedelta(minutes=15)).isoformat(), + toStartTime=now.isoformat(), ), response_type=LangfuseObservationList, timeout=30.0, diff --git a/tests/e2e/logging/test_langsmith_batch_serialization_e2e.py b/tests/e2e/logging/test_langsmith_batch_serialization_e2e.py index e2dadf9e696..37f363772ae 100644 --- a/tests/e2e/logging/test_langsmith_batch_serialization_e2e.py +++ b/tests/e2e/logging/test_langsmith_batch_serialization_e2e.py @@ -32,6 +32,7 @@ pytestmark = pytest.mark.e2e class LangsmithHeaders(Headers): x_api_key: str = Field(serialization_alias="x-api-key") + x_tenant_id: str | None = Field(default=None, serialization_alias="x-tenant-id") class LangsmithRunExtra(BaseModel): @@ -50,6 +51,7 @@ class LangsmithCreds: api_key: str base_url: str project: str + tenant_id: str | None def load_langsmith_creds() -> LangsmithCreds: @@ -62,6 +64,7 @@ def load_langsmith_creds() -> LangsmithCreds: api_key=api_key, base_url=(os.getenv("LANGSMITH_BASE_URL") or "https://api.smith.langchain.com").rstrip("/"), project=os.getenv("LANGSMITH_PROJECT") or "litellm-e2e", + tenant_id=os.getenv("LANGSMITH_TENANT_ID"), ) @@ -69,7 +72,7 @@ def _fetch_run(creds: LangsmithCreds, run_id: uuid.UUID) -> LangsmithRun | None: result = get_external( f"{creds.base_url}/runs/{run_id}", response_type=LangsmithRun, - headers=LangsmithHeaders(x_api_key=creds.api_key), + headers=LangsmithHeaders(x_api_key=creds.api_key, x_tenant_id=creds.tenant_id), ) match result: case Success(data=run): @@ -102,7 +105,10 @@ class TestLangsmithBatchSerialization: async def test_non_json_native_metadata_reaches_langsmith(self) -> None: creds: Final = load_langsmith_creds() logger: Final = LangsmithLogger( - langsmith_api_key=creds.api_key, langsmith_project=creds.project, langsmith_base_url=creds.base_url + langsmith_api_key=creds.api_key, + langsmith_project=creds.project, + langsmith_base_url=creds.base_url, + langsmith_tenant_id=creds.tenant_id, ) assert not logger.is_mock_mode, "LangsmithLogger initialised in mock mode; this e2e needs the real API" marker: Final = unique_marker() diff --git a/tests/e2e/logging/test_otel_trace_e2e.py b/tests/e2e/logging/test_otel_trace_e2e.py index 81a6407f642..fb6e481dc33 100644 --- a/tests/e2e/logging/test_otel_trace_e2e.py +++ b/tests/e2e/logging/test_otel_trace_e2e.py @@ -79,7 +79,7 @@ def _chain_reaches(span_id: str, root_id: str, trace: JaegerTrace) -> bool: return False -def _assert_complete_trace(traces: CallTraces, *, route: str, genai_span: str) -> None: +def assert_complete_trace(traces: CallTraces, *, route: str, genai_span: str) -> None: """The enforced behavior: the destination holds exactly one call-id-tagged trace for the call, rooted at the SERVER span, with auth/db children and the gen-AI span all connected into that one tree - no dangling parent @@ -112,10 +112,9 @@ def _assert_complete_trace(traces: CallTraces, *, route: str, genai_span: str) - roots = [span for span in trace.spans if not span.references] assert len(roots) == 1, f"expected exactly one root span, got {[s.operation_name for s in roots]}; spans: {names}" root = roots[0] - assert root.operation_name == f"POST {route}", ( - f"the root must be the SERVER span 'POST {route}', got {root.operation_name!r}" - ) assert root.kind == "server", f"the root span must have kind=server, got {root.kind!r}" + request_route: Final = root.tag("http.route") or root.tag("url.path") or root.tag("http.target") + assert request_route == route, f"the root must identify route {route!r}, got {request_route!r}" assert f"auth {route}" in names, f"auth phase span 'auth {route}' missing; spans: {names}" assert any(name.startswith(DB_SPAN_PREFIX) for name in names), ( @@ -133,12 +132,12 @@ def _assert_complete_trace(traces: CallTraces, *, route: str, genai_span: str) - def _poll(otel_reader: OtelReader, *, call_id: str, route: str, genai_span: str) -> CallTraces: return otel_reader.poll_traces_for_call( call_id=call_id, - settled_names={f"POST {route}", f"auth {route}", genai_span}, + settled_names={f"auth {route}", genai_span}, settled_prefixes={DB_SPAN_PREFIX}, ) -def _assert_real_ttft(hits: tuple[JaegerTrace, ...], *, genai_span: str) -> None: +def assert_real_ttft(hits: tuple[JaegerTrace, ...], *, genai_span: str) -> None: """The enforced behavior: the gen-AI span for the attempt that served the stream records a TTFT that is a real measurement - present, numeric, positive, and strictly less than that span's own total duration. A TTFT of @@ -282,7 +281,7 @@ class TestOtelTraceCompleteness: assert outcome.call_id is not None, "success response must carry x-litellm-call-id" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=f"chat {MODEL}") - _assert_complete_trace(traces, route=route, genai_span=f"chat {MODEL}") + assert_complete_trace(traces, route=route, genai_span=f"chat {MODEL}") @pytest.mark.covers("logging.otel.success.exports_metric", exercised_on=["chat_completions"]) @meta( @@ -315,7 +314,7 @@ class TestOtelTraceCompleteness: assert outcome.call_id is not None, "success response must carry x-litellm-call-id" hits: Final = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=f"chat {MODEL}") - _assert_complete_trace(hits, route=route, genai_span=f"chat {MODEL}") + assert_complete_trace(hits, route=route, genai_span=f"chat {MODEL}") @pytest.mark.covers("logging.otel.success.exports_metric", exercised_on=["messages"]) @meta( @@ -333,7 +332,7 @@ class TestOtelTraceCompleteness: """This test verifies that one successful non-streaming /v1/messages request produces exactly one complete OTEL trace. - The trace must have a single root span named "POST /v1/messages". The + The trace must have a single root SERVER span identifying /v1/messages. The authentication, database, and model-call spans must all belong to the same trace and have valid parent relationships leading back to that root. @@ -353,7 +352,7 @@ class TestOtelTraceCompleteness: assert outcome.call_id is not None, "success response must carry x-litellm-call-id" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=f"chat {MODEL}") - _assert_complete_trace(traces, route=route, genai_span=f"chat {MODEL}") + assert_complete_trace(traces, route=route, genai_span=f"chat {MODEL}") @pytest.mark.covers("logging.otel.success.exports_metric", exercised_on=["responses"]) @meta( @@ -392,7 +391,7 @@ class TestOtelTraceCompleteness: genai_span = f"chat {CHEAP_OPENAI_MODEL}" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=genai_span) - _assert_complete_trace(traces, route=route, genai_span=genai_span) + assert_complete_trace(traces, route=route, genai_span=genai_span) @pytest.mark.covers("logging.otel.stream.exports_metric", exercised_on=["chat_completions"]) @meta( @@ -443,7 +442,7 @@ class TestOtelTraceCompleteness: genai_span = f"chat {MODEL}" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=genai_span) - _assert_complete_trace(traces, route=route, genai_span=genai_span) + assert_complete_trace(traces, route=route, genai_span=genai_span) served = one_served_genai_span(traces.hits[0], genai_span) assert served.tag("litellm.request.streaming") is True, ( @@ -500,7 +499,7 @@ class TestOtelTraceCompleteness: genai_span = f"chat {MODEL}" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=genai_span) - _assert_complete_trace(traces, route=route, genai_span=genai_span) + assert_complete_trace(traces, route=route, genai_span=genai_span) served = one_served_genai_span(traces.hits[0], genai_span) assert served.tag("litellm.request.streaming") is True, ( @@ -557,7 +556,7 @@ class TestOtelTraceCompleteness: genai_span = f"chat {CHEAP_OPENAI_MODEL}" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=genai_span) - _assert_complete_trace(traces, route=route, genai_span=genai_span) + assert_complete_trace(traces, route=route, genai_span=genai_span) one_served_genai_span(traces.hits[0], genai_span) @@ -614,7 +613,7 @@ class TestOtelTraceCompleteness: genai_span = f"chat {MODEL}" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=genai_span) - _assert_real_ttft(traces.hits, genai_span=genai_span) + assert_real_ttft(traces.hits, genai_span=genai_span) @pytest.mark.covers("logging.otel.stream.records_ttft", exercised_on=["messages"]) @meta( @@ -661,7 +660,7 @@ class TestOtelTraceCompleteness: genai_span = f"chat {MODEL}" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=genai_span) - _assert_real_ttft(traces.hits, genai_span=genai_span) + assert_real_ttft(traces.hits, genai_span=genai_span) @pytest.mark.covers("logging.otel.stream.records_ttft", exercised_on=["responses"]) @meta( @@ -708,7 +707,7 @@ class TestOtelTraceCompleteness: genai_span = f"chat {CHEAP_OPENAI_MODEL}" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=genai_span) - _assert_real_ttft(traces.hits, genai_span=genai_span) + assert_real_ttft(traces.hits, genai_span=genai_span) @pytest.mark.covers("logging.otel.failure.exports_metric", exercised_on=["chat_completions"]) @meta( @@ -763,7 +762,7 @@ class TestOtelTraceCompleteness: genai_span = f"chat {model_name}" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=genai_span) - _assert_complete_trace(traces, route=route, genai_span=genai_span) + assert_complete_trace(traces, route=route, genai_span=genai_span) root = next(span for span in traces.hits[0].spans if not span.references) assert str(root.tag("http.status_code")) == "401", ( @@ -825,7 +824,7 @@ class TestOtelTraceCompleteness: genai_span = f"chat {model_name}" traces = _poll(otel_reader, call_id=outcome.call_id, route=route, genai_span=genai_span) - _assert_complete_trace(traces, route=route, genai_span=genai_span) + assert_complete_trace(traces, route=route, genai_span=genai_span) root = next(span for span in traces.hits[0].spans if not span.references) assert str(root.tag("http.status_code")) == "401", ( diff --git a/tests/e2e/management/test_budget_customer_user_org_e2e.py b/tests/e2e/management/test_budget_customer_user_org_e2e.py index ae4e6db4e15..ea4afee78ca 100644 --- a/tests/e2e/management/test_budget_customer_user_org_e2e.py +++ b/tests/e2e/management/test_budget_customer_user_org_e2e.py @@ -418,7 +418,7 @@ class TestBudgetListV1: @pytest.mark.covers("mgmt.budget.list_v1.happy_path") @meta(Subject(domain=Domain.SPEND_BUDGETS, route=Route.BUDGET_MANAGEMENT)) def test_refuses_a_sort_field_and_a_parameter_it_does_not_support(self, client: ManagementClient) -> None: - assert _list_status(client, BudgetPageParams(sort="budget_duration")) == 400 + assert _list_status(client, BudgetPageParams(sort="not_a_sort_field")) == 400 assert _list_status(client, BudgetPageParams(not_a_parameter="b-1")) == 400 @pytest.mark.covers("mgmt.budget.list_v1.admin_only") diff --git a/tests/e2e/mcp/test_mcp_semantic_tool_filter_e2e.py b/tests/e2e/mcp/test_mcp_semantic_tool_filter_e2e.py index 6e564f4625a..1ec2a6822e3 100644 --- a/tests/e2e/mcp/test_mcp_semantic_tool_filter_e2e.py +++ b/tests/e2e/mcp/test_mcp_semantic_tool_filter_e2e.py @@ -5,7 +5,8 @@ embedding deployment, and turns on `litellm_settings.mcp_semantic_tool_filter` t /config/update. A chat completion that attaches the server and asks to search logs must report, in the x-litellm-semantic-filter headers, that the catalog was cut to at most top_k tools, all of them tools the key lists. Requires DD_API_KEY + DD_APP_KEY and the proxy's -OPENAI_API_KEY for the embedding deployment. +OPENAI_API_KEY for the embedding deployment. The filter is proxy-wide, so the test is +marked `proxy_wide_config` and runs on a stack the main suite is not driving. """ from __future__ import annotations @@ -23,7 +24,7 @@ from mcp_client import McpClient from models import ChatBody, ChatMessage, LiteLLMParamsBody, McpChatTool from pydantic import BaseModel -pytestmark = [pytest.mark.e2e, pytest.mark.quiet_stack] +pytestmark = [pytest.mark.e2e, pytest.mark.proxy_wide_config] TOP_K: Final = 3 diff --git a/tests/e2e/models.py b/tests/e2e/models.py index 9c12e2146c9..86af30f413a 100644 --- a/tests/e2e/models.py +++ b/tests/e2e/models.py @@ -653,6 +653,35 @@ class ResponsesStreamBody(BaseModel): cache: dict[str, bool] | None = {"no-cache": True} +class ResponsesFunctionTool(BaseModel): + model_config = ConfigDict(frozen=True) + type: Literal["function"] = "function" + name: str + description: str | None = None + parameters: ToolInputSchema + + +class ResponsesToolBody(BaseModel): + model_config = ConfigDict(frozen=True) + model: str + input: str + tools: list[ResponsesFunctionTool] + tool_choice: Literal["required"] | None = None + guardrails: list[str] + max_output_tokens: int = 128 + + +class ResponsesOutputItem(BaseModel): + model_config = ConfigDict(frozen=True) + type: str + name: str | None = None + + +class ResponsesToolOutput(BaseModel): + model_config = ConfigDict(frozen=True) + output: list[ResponsesOutputItem] + + class CountTokensBody(BaseModel): """POST /v1/messages/count_tokens body: the /v1/messages shape minus max_tokens (the endpoint only counts the prompt).""" @@ -1262,27 +1291,6 @@ class CostMap(RootModel[dict[str, CostMapEntry]]): pass -class ConfigPatchResponse(BaseModel): - status: str - values: dict[str, float | dict[str, float]] - - -class CostDiscountConfig(RootModel[dict[str, float]]): - pass - - -class CostMarginConfig(RootModel[dict[str, float | dict[str, float]]]): - pass - - -class CostDiscountConfigResponse(BaseModel): - values: dict[str, float] - - -class CostMarginConfigResponse(BaseModel): - values: dict[str, float | dict[str, float]] - - class BedrockGuardrailParams(BaseModel): guardrail: Literal["bedrock"] = "bedrock" mode: Literal["pre_call"] = "pre_call" diff --git a/tests/e2e/otel_client.py b/tests/e2e/otel_client.py index 5f93c677d89..b42235484dc 100644 --- a/tests/e2e/otel_client.py +++ b/tests/e2e/otel_client.py @@ -28,11 +28,10 @@ from dataclasses import dataclass from typing import Final import pytest -from pydantic import BaseModel, ConfigDict, Field - from e2e_config import OTEL_QUERY_URL, POLL_INTERVAL, POLL_TIMEOUT from e2e_http import URL, NetworkError, NoBody, Result, Success, get from e2e_metadata import step +from pydantic import BaseModel, ConfigDict, Field #: OTEL resource service.name the proxy exports under (OTEL_SERVICE_NAME default). JAEGER_SERVICE = "litellm" @@ -118,9 +117,15 @@ def _ticks() -> Iterator[None]: time.sleep(POLL_INTERVAL) -def _settled(trace: JaegerTrace, names: set[str], prefixes: set[str]) -> bool: - present = set(trace.span_names()) - return names.issubset(present) and all(any(name.startswith(prefix) for name in present) for prefix in prefixes) +def trace_settled(trace: JaegerTrace, names: set[str], prefixes: set[str]) -> bool: + root: Final = root_span(trace) + present: Final = frozenset(trace.span_names()) + return ( + root is not None + and root.kind == "server" + and names.issubset(present) + and all(any(name.startswith(prefix) for name in present) for prefix in prefixes) + ) def root_span(trace: JaegerTrace) -> JaegerSpan | None: @@ -172,7 +177,7 @@ class _Observation: def settled(self, names: set[str], prefixes: set[str]) -> bool: hits: Final = self.traces.hits - return self.unreachable is None and len(hits) == 1 and not self.missing and _settled(hits[0], names, prefixes) + return self.unreachable is None and len(hits) == 1 and not self.missing and trace_settled(hits[0], names, prefixes) @dataclass(frozen=True, slots=True) diff --git a/tests/e2e/perf/setup/upgrade.py b/tests/e2e/perf/setup/upgrade.py deleted file mode 100644 index c9114ccbff2..00000000000 --- a/tests/e2e/perf/setup/upgrade.py +++ /dev/null @@ -1,223 +0,0 @@ -from __future__ import annotations - -import math -import time -from collections.abc import Callable -from dataclasses import replace -from typing import Final - -import psycopg -from cases.small_bodies_5rps import CASE -from e2e_config import MASTER_KEY -from e2e_http import send_text_external -from prometheus_client.parser import text_string_to_metric_families -from pydantic import BaseModel, ConfigDict, Field, TypeAdapter - -from setup.performance_test_case import PerformanceTestCase -from setup.upgrade_worker import UpgradeState, fingerprints, missing_indexes, read_state, release_indexes -from setup.wire import WireRecord - -MAX_TRAFFIC_SECONDS: Final = 6 * 3600 -_ROWS: Final = TypeAdapter(tuple[tuple[str, str | None], ...]) -_ACTIVITY: Final = TypeAdapter(tuple[list[int], int]) -_COUNT: Final = TypeAdapter(tuple[int]) -_SERVICES: Final = ("postgres", "batch_write_to_db") - - -def upgrade_case() -> PerformanceTestCase: - return replace( - CASE, - name="database_upgrade_5rps", - traffic=replace(CASE.traffic, total_requests=int(CASE.traffic.rps * MAX_TRAFFIC_SECONDS)), - limits=tuple( - limit - for limit in CASE.limits - if limit.metric - in { - "unexpected_status_count", - "gateway_added_seconds", - "time_to_first_token_seconds", - "memory_growth_megabytes", - } - ), - ) - - -class MetricsHeaders(BaseModel): - model_config = ConfigDict(frozen=True) - authorization: str = Field(default=f"Bearer {MASTER_KEY}", alias="Authorization") - - -def postgres_failures(text: str) -> float: - families: Final = tuple(text_string_to_metric_families(text)) - names: Final = frozenset(family.name for family in families) - required: Final = frozenset(f"litellm_{service}_failed_requests" for service in _SERVICES) - samples: Final = tuple(sample for family in families for sample in family.samples) - has_database_activity: Final = any( - sample.name == "litellm_postgres_total_requests_total" and math.isfinite(sample.value) and sample.value > 0 - for sample in samples - ) - assert required <= names or has_database_activity, f"Missing database service counters: {required - names}" - failures: Final = tuple(sample.value for sample in samples if sample.name in {f"{name}_total" for name in required}) - assert all(math.isfinite(value) and value >= 0 for value in failures), "Invalid database failure counter" - return sum(failures) - - -def assert_database_metrics(urls: tuple[str, ...]) -> None: - assert urls, "E2E_DATABASE_METRICS_URLS must name every gateway/backend /metrics endpoint" - for url in urls: - assert_database_metrics_url(url) - - -def assert_database_metrics_url(url: str) -> None: - result: Final = send_text_external("GET", url, headers=MetricsHeaders(), timeout=10) - assert result.status_code == 200, f"Database metrics unavailable at {url}: {result.status_code}" - assert postgres_failures(result.body) == 0, f"Failed PostgreSQL operations reported at {url}" - - -def persisted(connection: psycopg.Connection[tuple[object, ...]], records: tuple[WireRecord, ...]) -> frozenset[str]: - ids: Final = tuple(record.call_id for record in records if record.call_id) - if not ids: - return frozenset() - rows: Final = _ROWS.validate_python( - connection.execute( - 'SELECT request_id, litellm_call_id FROM "LiteLLM_SpendLogs" WHERE litellm_call_id=ANY(%s)', (list(ids),) - ).fetchall() - ) - return matched_response_ids(records, rows) - - -def matched_response_ids(records: tuple[WireRecord, ...], rows: tuple[tuple[str, str | None], ...]) -> frozenset[str]: - call_ids: Final = frozenset(call_id for _, call_id in rows if call_id) - return frozenset(record.response_id for record in records if record.response_id and record.call_id in call_ids) - - -def activity(connection: psycopg.Connection[tuple[object, ...]]) -> tuple[list[int], int]: - return _ACTIVITY.validate_python( - connection.execute("""SELECT - ARRAY(SELECT pid FROM pg_stat_progress_create_index WHERE datname=current_database()), - (SELECT count(*) FROM pg_stat_activity WHERE datname=current_database() AND wait_event_type='Lock') - """).fetchone() - ) - - -def assert_finished(connection: psycopg.Connection[tuple[object, ...]], state: UpgradeState) -> None: - assert state.phase == "complete", f"Upgrade did not finish: {state.phase}" - assert not missing_indexes(connection, state.required_indexes), "Required target indexes are missing or invalid" - (missing,) = _COUNT.validate_python( - connection.execute( - """ - SELECT count(*) FROM unnest(%s::text[]) name WHERE NOT EXISTS ( - SELECT 1 FROM "_prisma_migrations" WHERE migration_name=name - AND finished_at IS NOT NULL AND rolled_back_at IS NULL)""", - (list(state.required_migrations),), - ).fetchone() - ) - assert missing == 0, f"{missing} target migrations were not applied" - (unfinished,) = _COUNT.validate_python( - connection.execute(""" - SELECT count(*) FROM "_prisma_migrations" WHERE finished_at IS NULL AND rolled_back_at IS NULL - """).fetchone() - ) - assert unfinished == 0, f"{unfinished} unfinished migrations" - assert fingerprints(connection, tuple(state.baseline_rows)) == state.baseline_rows, ( - "Baseline rows changed or disappeared" - ) - - -class UpgradeMonitor: - def __init__( - self, - *, - state: Callable[[], UpgradeState], - check_metrics: Callable[[], None], - read_activity: Callable[[], tuple[list[int], int]], - read_persisted: Callable[[tuple[WireRecord, ...]], frozenset[str]], - start_indexes: Callable[[], None], - clock: Callable[[], float] = time.monotonic, - wall_clock: Callable[[], float] = time.time, - ) -> None: - self.state: Final = state - self.check_metrics: Final = check_metrics - self.read_activity: Final = read_activity - self.read_persisted: Final = read_persisted - self.start_indexes: Final = start_indexes - self.clock: Final = clock - self.wall_clock: Final = wall_clock - self.started: Final = clock() - self.status_limit: Final = next( - limit.max for limit in CASE.limits if limit.metric == "unexpected_status_count" and limit.max is not None - ) - self.pending: tuple[WireRecord, ...] = () - self.processed = 0 - self.successes = 0 - self.persisted_count = 0 - self.overlap_writes = 0 - self.max_lock_waiters = 0 - self.previous_builds: frozenset[int] = frozenset() - self.build_seen_at: float | None = None - self.released = False - self.completed_at: float | None = None - - def poll(self, records: tuple[WireRecord, ...]) -> bool: - self.check_metrics() - current: Final = self.state() - assert current.phase != "failed", "Target migration/index worker failed" - assert self.clock() - self.started < MAX_TRAFFIC_SECONDS, "Upgrade exceeded its six-hour operational timeout" - successful: Final = tuple(record for record in records if record.status == 200) - self.processed += len(records) - self.successes += len(successful) - assert self.processed - self.successes <= self.status_limit, "Too many unexpected non-200 responses" - assert all(record.ok and record.text for record in successful), "Failed or empty inference response" - assert all(record.response_id and record.call_id for record in successful), ( - "Response missing spend-log identifiers" - ) - builds, lock_waiters = self.read_activity() - if not self.previous_builds.intersection(builds): - self.build_seen_at = self.wall_clock() if builds else None - self.max_lock_waiters = max(self.max_lock_waiters, lock_waiters) - self.pending += successful - found: Final = self.read_persisted(self.pending) - self.persisted_count += len(found) - still_building, _ = self.read_activity() - since: Final = self.build_seen_at - if since is not None and frozenset(builds).intersection(still_building): - self.overlap_writes += sum( - 1 for record in self.pending if record.response_id in found and record.started_at >= since - ) - self.previous_builds = frozenset(builds) - self.pending = tuple(record for record in self.pending if record.response_id not in found) - if self.successes and not self.released: - self.start_indexes() - self.released = True - if current.phase == "complete" and self.completed_at is None: - self.completed_at = self.clock() - return self.completed_at is not None and self.clock() - self.completed_at >= 60 and self.successes >= 300 - - def assert_complete(self, state: UpgradeState) -> None: - assert self.successes >= 300, f"Only {self.successes} requests completed" - assert not self.pending, f"{len(self.pending)} successful requests have no matching spend log" - assert self.persisted_count == self.successes, "Spend-log count does not match successful requests" - assert not state.pending_indexes or self.overlap_writes > 0, "No persisted requests observed during index work" - - -def upgrade_properties(state: UpgradeState, monitor: UpgradeMonitor) -> tuple[tuple[str, float], ...]: - """The upgrade's own numbers under the `perf_` prefix the dashboard ingests, next to the perf rows.""" - return ( - ("perf_upgrade_schema_seconds", state.schema_seconds), - ("perf_upgrade_index_seconds", state.index_seconds), - ("perf_upgrade_overlap_writes", float(monitor.overlap_writes)), - ("perf_upgrade_max_lock_waiters", float(monitor.max_lock_waiters)), - ("perf_upgrade_pending_indexes", float(len(state.pending_indexes))), - ("perf_upgrade_unmatched_requests", float(len(monitor.pending))), - ) - - -def monitor_for(connection: psycopg.Connection[tuple[object, ...]], urls: tuple[str, ...]) -> UpgradeMonitor: - return UpgradeMonitor( - state=lambda: read_state(connection), - check_metrics=lambda: assert_database_metrics(urls), - read_activity=lambda: activity(connection), - read_persisted=lambda records: persisted(connection, records), - start_indexes=lambda: release_indexes(connection), - ) diff --git a/tests/e2e/perf/test_database_upgrade.py b/tests/e2e/perf/test_database_upgrade.py deleted file mode 100644 index fba6af30014..00000000000 --- a/tests/e2e/perf/test_database_upgrade.py +++ /dev/null @@ -1,102 +0,0 @@ -from __future__ import annotations - -import os -import sys -import time -from pathlib import Path -from typing import Final - -import pytest -from idp import Keycloak -from lifecycle import ResourceManager -from memory_readings import read_rss_everywhere -from proxy_client import ProxyClient -from setup.datastore import read_db_counters, read_redis_counters -from setup.observe import ( - Observation, - evaluate, - junit_properties, - read_mock_requests, - render, - reset_mock, - set_mock_latency, -) -from setup.plan import build_plan -from setup.podcpu import gateway_cpu_sampler -from setup.provision import MOCK_PROVIDERS, build_setup, mock_url -from setup.run import run_plan -from setup.upgrade import assert_finished, monitor_for, upgrade_case, upgrade_properties -from setup.upgrade_worker import connect, read_state - -pytestmark = [pytest.mark.perf, pytest.mark.quiet_stack] - - -@pytest.mark.skipif(os.environ.get("E2E_DATABASE_UPGRADE") != "1", reason="Dedicated disposable snapshot lane only") -def test_database_upgrade( - proxy: ProxyClient, idp: Keycloak, resources: ResourceManager, request: pytest.FixtureRequest -) -> None: - case: Final = upgrade_case() - urls: Final = tuple(mock_url(provider) for provider in MOCK_PROVIDERS) - for url in urls: - _ = reset_mock(url) - _ = set_mock_latency(url, case.mock_latency) - setup: Final = build_setup(case, proxy=proxy, idp=idp, resources=resources) - metrics: Final = tuple(url.strip() for url in os.environ["E2E_DATABASE_METRICS_URLS"].split(",") if url.strip()) - with connect() as connection: - assert read_state(connection).phase == "schema_ready", "Expected the target schema ready, index work waiting" - rss_before: Final = read_rss_everywhere(proxy) - db_before: Final = read_db_counters() - redis_before: Final = read_redis_counters() - monitor: Final = monitor_for(connection, metrics) - with gateway_cpu_sampler() as cpu: - outcome: Final = run_plan(case, build_plan(case), setup, stop_when=monitor.poll, request_timeout=30) - assert outcome.locust_exit == 0, outcome.locust_output - remaining: Final = outcome.records[monitor.processed :] - _ = monitor.poll(remaining) - deadline: Final = time.monotonic() + 120 - while monitor.pending and time.monotonic() < deadline: - time.sleep(1) - _ = monitor.poll(()) - state: Final = read_state(connection) - _ = sys.stdout.write( - f"successful_requests={monitor.successes} persisted_requests={monitor.persisted_count} " - f"unmatched_requests={len(monitor.pending)}\n" - ) - rss_after: Final = read_rss_everywhere(proxy) - observed: Final = Observation( - records=outcome.records, - mock_requests=tuple(seen for url in urls for seen in read_mock_requests(url)), - guardrail_calls=(), - rss_before=rss_before, - rss_after=rss_after, - wall_seconds=outcome.wall_seconds, - spend_logged_share=1, - db_before=db_before, - db_after=read_db_counters(), - redis_before=redis_before, - redis_after=read_redis_counters(), - gateway_cpu_seconds=cpu.seconds, - ) - rows, exceeded = evaluate(case, observed) - item: Final = request.node # pyright: ignore[reportUnknownMemberType, reportUnknownVariableType] # pytest: untyped - assert isinstance(item, pytest.Item) - item.user_properties[:] = [ - entry for entry in item.user_properties if not entry[0].startswith("perf_") - ] # rebind-ok: a --reruns retry replaces the first attempt's numbers instead of appending a second set - item.user_properties.extend(junit_properties(rows)) - item.user_properties.extend(upgrade_properties(state, monitor)) - _ = sys.stdout.write(render(case, observed, rows) + "\n") - _ = sys.stdout.write( - f"schema_seconds={state.schema_seconds:.3f} index_seconds={state.index_seconds:.3f} " - f"overlap_writes={monitor.overlap_writes} max_lock_waiters={monitor.max_lock_waiters} " - f"pending_indexes={state.pending_indexes}\n" - ) - artifact: Final = os.environ.get("E2E_ARTIFACT_DIR") - if artifact: - _ = (Path(artifact) / "database-upgrade.json").write_text(state.model_dump_json(), encoding="utf-8") - monitor.assert_complete(state) - assert_finished(connection, state) - assert {(r.replica, r.hostname) for r in rss_before.readings} == { - (r.replica, r.hostname) for r in rss_after.readings - }, "Gateway pods replaced during the upgrade" - assert not exceeded, "\n".join(exceeded) diff --git a/tests/e2e/perf/test_perf_cases.py b/tests/e2e/perf/test_perf_cases.py index db657a04b00..0a137e84572 100644 --- a/tests/e2e/perf/test_perf_cases.py +++ b/tests/e2e/perf/test_perf_cases.py @@ -48,7 +48,7 @@ from setup.ramp import step_properties from setup.run import run_plan from setup.telemetry import read_gateway_telemetry, telemetry_sampler -pytestmark = [pytest.mark.perf, pytest.mark.quiet_stack] +pytestmark = pytest.mark.perf _SPEND_SAMPLE: Final = 40 _WARMUP_SECONDS: Final = 60 diff --git a/tests/e2e/router/test_reliability_memory_e2e.py b/tests/e2e/perf/test_reliability_memory_e2e.py similarity index 77% rename from tests/e2e/router/test_reliability_memory_e2e.py rename to tests/e2e/perf/test_reliability_memory_e2e.py index fb114092303..2066137bb72 100644 --- a/tests/e2e/router/test_reliability_memory_e2e.py +++ b/tests/e2e/perf/test_reliability_memory_e2e.py @@ -1,17 +1,19 @@ """Live e2e: a few hundred requests that fail before any provider answers must not -grow the proxy's resident memory past a loose ceiling once the proxy is warm. +grow the proxy's resident memory past a loose ceiling once the proxy is warm. It reads +the proxy's own RSS, so it runs in the perf lane, where nothing else is hitting the stack. The regression this guards shipped in v1.100.0: every retry breadcrumb copied the whole request and the copies nested into one router-global list, so a proxy under retry-heavy failing traffic grew until it was OOM-killed. The traffic here has that shape: a model group whose deployments refuse at the socket (an unreachable base -URL) with cooldown_time 0 so the router keeps retrying them, per-request retries, -and a fallback group that refuses the same way, each request carrying a long chat +URL, with a literal key since the perf stack carries no provider keys) with +cooldown_time 0 so the router keeps retrying them, per-request retries, and a +fallback group that refuses the same way, each request carrying a long chat transcript so every whole-request copy costs hundreds of containers instead of a -handful. Under the stack's cooldown policy a -deployment that fails a handful of times in a row is benched (a bad-credential 401 -included), the router answers "No deployments available" without retrying, and the -retry loop that leaks stops running; cooldown_time 0 keeps it running. +handful. Under the stack's cooldown policy a deployment that fails a handful of +times in a row is benched (a bad-credential 401 included), the router answers "No +deployments available" without retrying, and the retry loop that leaks stops running; +cooldown_time 0 keeps it running. Four identical batches run back to back. The first two are the warmup that grows the proxy's caches and allocator arenas, the last two are the measured window, and @@ -35,19 +37,11 @@ single load-balanced address reaches the workers behind it one answer at a time, a worker that answered only one checkpoint would otherwise drop out of the comparison, which is where a leaking worker could hide. -RSS alone is a coarse gauge: on the release stack (spend logs storing prompts, -json logs, prometheus and otel callbacks) the same v1.100.0 breadcrumbs grew RSS -by only about 15 MB per 300 failing requests, while every failing request's stored -request snapshot carried a copy of the request per failed attempt, over 100 KB on -the first call and a couple of MB once the copies nested, against tens of KB with -the fix. So the first check sends one failing request before the phases, reads its -spend log back through /spend/logs, and holds the stored request body to a fixed -size budget: the deterministic catch for a breadcrumb that copies the whole -request. It runs before the phases because the leaking writer drops its own rows -under the phases' traffic (a queue budget hit, a recursion limit on the nested -copies), which would turn the size check into a missing-row check. +The stored-request half of that regression (every failing request's spend log carrying a +copy of the request per failed attempt) is a deterministic size check, so it lives in +tests/integration/spend/test_failing_request_stored_snapshot.py. -A second, cheaper check holds the idle footprint: every worker's RSS as the harness +A cheaper check holds the idle footprint: every worker's RSS as the harness read it at collection time, before this pytest process sent any traffic (see conftest.pytest_collection_finish), must sit under a fixed budget. On the release gate that is a fresh stack right after its readiness gate, one worker per @@ -74,7 +68,6 @@ from typing import Final import pytest -from complexity_router_client import ComplexityRouterClient from e2e_config import ( MEMORY_CONCURRENCY, MEMORY_IDLE_RSS_BUDGET_MB, @@ -83,7 +76,6 @@ from e2e_config import ( MEMORY_RSS_CEILING_MB, MEMORY_RSS_SAMPLE_INTERVAL_SECONDS, MEMORY_RSS_SETTLE_SAMPLES, - MEMORY_STORED_REQUEST_BUDGET_KB, MEMORY_TRANSCRIPT_TURNS, PROXY_REPLICA_URLS, unique_marker, @@ -91,11 +83,12 @@ from e2e_config import ( from e2e_metadata import Domain, Mode, Provider, Subject, meta from lifecycle import ResourceManager from memory_readings import RssCapture, RssReading, WorkerKey, read_rss_everywhere -from models import ChatMessage, RouterSettingsOverride, SpendLogRow +from models import ChatMessage, LiteLLMParamsBody, ReliabilityChatBody, RouterSettingsOverride from proxy_client import ProxyClient -from reliability_support import REAL_MODEL, chat_override, create_never_benched_refusing_deployment -pytestmark = [pytest.mark.e2e, pytest.mark.quiet_stack] +pytestmark = [pytest.mark.e2e, pytest.mark.perf] + +REFUSING_MODEL: Final = "openai/gpt-5.5" DEPLOYMENTS_PER_GROUP: Final = 2 RSS_SAMPLE_CAP: Final = 4 * MEMORY_RSS_SETTLE_SAMPLES @@ -110,7 +103,6 @@ class FailedCall: status_code: int seconds: float body_head: str - call_id: str | None @dataclass(frozen=True, slots=True) @@ -123,8 +115,17 @@ class WorkerGrowth: return self.after.ram_usage_mb - self.warm.ram_usage_mb +def _create_never_benched_refusing_deployment(proxy: ProxyClient, name: str) -> str: + return proxy.create_model( + name, + LiteLLMParamsBody( + model=REFUSING_MODEL, api_key="sk-unreachable", api_base="http://127.0.0.1:9/v1", cooldown_time=0 + ), + ) + + def _register_refusing_group(proxy: ProxyClient, resources: ResourceManager, name: str) -> None: - for model_id in tuple(create_never_benched_refusing_deployment(proxy, name) for _ in range(DEPLOYMENTS_PER_GROUP)): + for model_id in tuple(_create_never_benched_refusing_deployment(proxy, name) for _ in range(DEPLOYMENTS_PER_GROUP)): resources.defer(lambda model_id=model_id: proxy.delete_model(model_id)) @@ -141,10 +142,18 @@ TRANSCRIPT: Final = _transcript(MEMORY_TRANSCRIPT_TURNS) def _fail_once(proxy: ProxyClient, key: str, model: str, override: RouterSettingsOverride) -> FailedCall: started: Final = time.perf_counter() - resp: Final = chat_override( - proxy, key, model, f"memory regression {unique_marker()}", override=override, history=TRANSCRIPT + resp: Final = proxy.transport.send( + "/chat/completions", + headers=proxy.transport.bearer(key), + json=ReliabilityChatBody( + model=model, + messages=[*TRANSCRIPT, ChatMessage(role="user", content=f"memory regression {unique_marker()}")], + max_tokens=512, + router_settings_override=override, + cache={"no-cache": True}, + ), ) - return FailedCall(resp.status_code, time.perf_counter() - started, resp.body[:300], resp.call_id) + return FailedCall(resp.status_code, time.perf_counter() - started, resp.body[:300]) def _fail_many(proxy: ProxyClient, key: str, model: str, override: RouterSettingsOverride) -> tuple[FailedCall, ...]: @@ -259,24 +268,6 @@ def _assert_every_call_failed_through_fallback(calls: Sequence[FailedCall], fall ) -def _stored_request_kb(proxy: ProxyClient, call: FailedCall) -> float: - assert call.call_id, ( - f"the failing call carried no x-litellm-call-id header, so its spend log cannot be read back: {call.body_head}" - ) - rows: Final[Sequence[SpendLogRow]] = proxy.poll_logs_for_request_id(call.call_id) - assert rows, ( - f"no spend log row appeared for failing call {call.call_id} within the poll window: either the stack " - "writes no spend logs or its writer dropped the row, which the v1.100.0 one did once the stored " - "request outgrew the writer's queue budget" - ) - snapshot: Final = rows[0].proxy_server_request - assert snapshot, ( - f"spend log {call.call_id} stored no request body, so the stack is not running with " - "general_settings.store_prompts_in_spend_logs and the stored-request check would pass vacuously" - ) - return len(json.dumps(snapshot).encode()) / 1024 - - class TestReliabilityMemory: @pytest.mark.covers("reliability.perf.idle_memory.under_slo") @meta( @@ -309,13 +300,13 @@ class TestReliabilityMemory: Subject( domain=Domain.ROUTING, providers=(Provider.OPENAI,), - models=(REAL_MODEL,), + models=(REFUSING_MODEL,), mode=Mode.NONSTREAM, ) ) - def test_failing_requests_do_not_grow_rss_or_stored_request( + def test_failing_requests_do_not_grow_rss( self, - client: ComplexityRouterClient, + proxy: ProxyClient, resources: ResourceManager, scoped_key: str, record_property: Callable[[str, object], None], @@ -323,35 +314,25 @@ class TestReliabilityMemory: marker: Final = unique_marker() primary: Final = f"reliability-memory-{marker}" fallback: Final = f"reliability-memory-fb-{marker}" - _register_refusing_group(client.proxy, resources, primary) - _register_refusing_group(client.proxy, resources, fallback) + _register_refusing_group(proxy, resources, primary) + _register_refusing_group(proxy, resources, fallback) override: Final = RouterSettingsOverride( num_retries=MEMORY_RETRIES_PER_REQUEST, fallbacks=[{primary: [fallback]}] ) - probe: Final = _fail_once(client.proxy, scoped_key, primary, override) - _assert_every_call_failed_through_fallback((probe,), fallback) - stored_kb: Final = _stored_request_kb(client.proxy, probe) - assert stored_kb <= MEMORY_STORED_REQUEST_BUDGET_KB, ( - f"the spend log of one failing request stored a {stored_kb:.0f} KB request body, past the " - f"{MEMORY_STORED_REQUEST_BUDGET_KB:.0f} KB budget for a {len(TRANSCRIPT)}-message transcript with " - f"{MEMORY_RETRIES_PER_REQUEST} retries and a fallback; the retry breadcrumbs are copying the whole " - f"request into the stored snapshot the way the v1.100.0 ones did" - ) - warm: Final = _settled_rss_after_batches( - client.proxy, + proxy, scoped_key, primary, override, fallback, record_property, - _settled_rss_per_worker(client.proxy), + _settled_rss_per_worker(proxy), 1, WARMUP_BATCHES, ) after: Final = _settled_rss_after_batches( - client.proxy, + proxy, scoped_key, primary, override, diff --git a/tests/e2e/perf/test_ui_journeys.py b/tests/e2e/perf/test_ui_journeys.py index 63eefedec68..11b2cd1051d 100644 --- a/tests/e2e/perf/test_ui_journeys.py +++ b/tests/e2e/perf/test_ui_journeys.py @@ -33,7 +33,6 @@ from transport import HttpTransport pytestmark = [ pytest.mark.perf, - pytest.mark.quiet_stack, pytest.mark.skipif(os.environ.get("E2E_UI_PERF_DISPOSABLE") != "1", reason="Dedicated disposable database only"), ] diff --git a/tests/e2e/provider_cache_redis.py b/tests/e2e/provider_cache_redis.py index 2c7419cfc0f..c1a3eada4a9 100644 --- a/tests/e2e/provider_cache_redis.py +++ b/tests/e2e/provider_cache_redis.py @@ -14,8 +14,8 @@ from typing import Final, Protocol, cast from provider_cache import LIFETIME_SECONDS, CacheBusy, CacheEdge, CacheHit, CacheLookup, CacheUnavailable, CaptureLease from pydantic import TypeAdapter, ValidationError -from redis import Redis -from redis.exceptions import RedisError +from redis import Redis, RedisCluster +from redis.exceptions import RedisClusterException, RedisError REDIS_ARRAY: Final[TypeAdapter[list[bytes]]] = TypeAdapter(list[bytes]) @@ -83,7 +83,7 @@ class RedisResponseStore: started: Final = time.monotonic() try: result: Final = self.client.eval(LOOKUP, 2, *self.keys(key), token, self.lifetime_ms, self.lease_ms) - except (RedisError, OSError): + except (RedisError, RedisClusterException, OSError): return CacheUnavailable() try: parts: Final = tuple(REDIS_ARRAY.validate_python(result, strict=True)) @@ -102,28 +102,46 @@ class RedisResponseStore: result: Final = self.client.eval( PUBLISH, 2, *self.keys(key), lease.token, lease.captured_at_ms, lease.expires_at_ms, payload, self.lifetime_ms, ) - except (RedisError, OSError): + except (RedisError, RedisClusterException, OSError): return False return result == 1 def release(self, key: str, lease: CaptureLease) -> bool: try: result: Final = self.client.eval(RELEASE, 1, self.keys(key)[1], lease.token) - except (RedisError, OSError): + except (RedisError, RedisClusterException, OSError): return False return result == 1 def discard(self, key: str, payload: bytes) -> bool: try: result: Final = self.client.eval(DISCARD, 1, self.keys(key)[0], payload) - except (RedisError, OSError): + except (RedisError, RedisClusterException, OSError): return False return result == 1 +@functools.lru_cache(maxsize=16) +def _redis_commands(url: str, cluster: bool) -> RedisCommands: + if cluster: + return cast( + RedisCommands, RedisCluster(url=url, socket_timeout=0.25, socket_connect_timeout=0.25, decode_responses=False) + ) + return cast(RedisCommands, Redis.from_url(url, socket_timeout=0.25, socket_connect_timeout=0.25, decode_responses=False)) + + +@dataclass(frozen=True, slots=True) +class LazyRedisCommands: + url: str + cluster: bool + + def eval(self, script: str, numkeys: int, *args: str | bytes | int) -> object: + return _redis_commands(self.url, self.cluster).eval(script, numkeys, *args) + + def redis_store(url: str, namespace: str) -> RedisResponseStore: - client: Final = Redis.from_url(url, socket_timeout=0.25, socket_connect_timeout=0.25, decode_responses=False) - return RedisResponseStore(cast(RedisCommands, client), namespace) + client: Final = LazyRedisCommands(url, os.environ.get("E2E_PROVIDER_CACHE_REDIS_CLUSTER") == "1") + return RedisResponseStore(client, namespace) def write_metrics(cache: CacheEdge) -> None: diff --git a/tests/e2e/proxy_client.py b/tests/e2e/proxy_client.py index 8cc7bf0c2b4..9b842a723d8 100644 --- a/tests/e2e/proxy_client.py +++ b/tests/e2e/proxy_client.py @@ -11,7 +11,7 @@ from __future__ import annotations import os import time import warnings -from collections.abc import Callable, Mapping +from collections.abc import Callable, Mapping, Sequence from dataclasses import dataclass, field, replace from datetime import datetime from functools import reduce @@ -155,6 +155,21 @@ class NotServableOn: last_result: Result[ModelsListResponse] | None +@dataclass(frozen=True, slots=True) +class ModelRegistered: + model_name: str + model_id: str + + +@dataclass(frozen=True, slots=True) +class ModelNotRegistered: + model_name: str + reason: str + + +ModelRegistration = ModelRegistered | ModelNotRegistered + + def await_servable( list_models: Callable[[float], Result[ModelsListResponse]], *, @@ -461,6 +476,7 @@ class ProxyClient: model_servable_db_sync_seconds: float = MODEL_SERVABLE_DB_SYNC_SECONDS model_servable_interval: float = MODEL_SERVABLE_INTERVAL model_servable_request_timeout: float = MODEL_SERVABLE_REQUEST_TIMEOUT + settle: Callable[[float], None] = settle_propagation def with_caller(self, caller: Caller) -> ProxyClient: return replace(self, caller=caller) @@ -694,31 +710,59 @@ class ProxyClient: balancer address is configured (every request opens a fresh connection, so the caller's next request re-rolls), so waiting out PROPAGATION_TIMEOUT is what makes the model safe to use anywhere.""" - model_id = unwrap( - self.transport.post( - "/model/new", - headers=self.management_headers(), - json=body.model_copy(update={"litellm_params": route_cache_model( - body.litellm_params, provider_edge_base, - enabled=os.environ.get("E2E_PROVIDER_CACHE", "0") == "1" and not provider_live, - mode=body.model_info.mode, - )}), - response_type=ModelNewResponse, - ) - ).model_id + model_id = unwrap(self._post_model(body, provider_live=provider_live)).model_id written_at = time.monotonic() try: self._await_model_servable(body.model_name, listed_for) except BaseException: self.delete_model(model_id) raise - settle_propagation(written_at) + self.settle(written_at) return model_id + @step("Add a batch of deployments, then wait once for all of them to propagate") + def register_models( + self, bodies: Sequence[ModelNewBody], *, provider_live: bool = False + ) -> tuple[ModelRegistration, ...]: + posted: Final = tuple((body.model_name, self._post_model(body, provider_live=provider_live)) for body in bodies) + written_at: Final = time.monotonic() + registrations: Final = tuple(self._servable_registration(name, result) for name, result in posted) + self.settle(written_at) + return registrations + + def _post_model(self, body: ModelNewBody, *, provider_live: bool) -> Result[ModelNewResponse]: + return self.transport.post( + "/model/new", + headers=self.management_headers(), + json=body.model_copy(update={"litellm_params": route_cache_model( + body.litellm_params, provider_edge_base, + enabled=os.environ.get("E2E_PROVIDER_CACHE", "0") == "1" and not provider_live, + mode=body.model_info.mode, + )}), + response_type=ModelNewResponse, + ) + + def _servable_registration(self, model_name: str, posted: Result[ModelNewResponse]) -> ModelRegistration: + if not isinstance(posted, Success): + return ModelNotRegistered(model_name=model_name, reason=f"/model/new failed: {posted!r}") + match self._servable_outcome(model_name, None): + case Servable(): + return ModelRegistered(model_name=model_name, model_id=posted.data.model_id) + case NotServableOn() as missing: + self.delete_model(posted.data.model_id) + return ModelNotRegistered(model_name=model_name, reason=self._not_servable_message(model_name, missing)) + def _await_model_servable(self, model_name: str, listed_for: str | None = None) -> None: """Block until every replica lists `model_name`, or fail at model_servable_timeout.""" + match self._servable_outcome(model_name, listed_for): + case Servable(): + return + case NotServableOn() as missing: + raise AssertionError(self._not_servable_message(model_name, missing)) + + def _servable_outcome(self, model_name: str, listed_for: str | None) -> Servable | NotServableOn: headers: Final = self.management_headers(listed_for) - outcome: Final = await_servable_everywhere( + return await_servable_everywhere( {url: self._models_poller(transport, headers) for url, transport in self.replicas.items()}, model_name=model_name, timeout=self.model_servable_timeout, @@ -728,19 +772,15 @@ class ProxyClient: now=time.monotonic, sleep=time.sleep, ) - match outcome: - case Servable(): - return - case NotServableOn(replica=replica, last_result=last_result): - raise AssertionError( - servable_timeout_message( - model_name=model_name, - replica=replica, - timeout=self.model_servable_timeout, - db_sync_seconds=self.model_servable_db_sync_seconds, - last_result=last_result, - ) - ) + + def _not_servable_message(self, model_name: str, missing: NotServableOn) -> str: + return servable_timeout_message( + model_name=model_name, + replica=missing.replica, + timeout=self.model_servable_timeout, + db_sync_seconds=self.model_servable_db_sync_seconds, + last_result=missing.last_result, + ) @staticmethod def _models_poller(transport: Transport, headers: AuthHeaders) -> ModelsPoller: diff --git a/tests/e2e/pytest.ini b/tests/e2e/pytest.ini index f15cfd4e98b..891c5fc282c 100644 --- a/tests/e2e/pytest.ini +++ b/tests/e2e/pytest.ini @@ -13,7 +13,6 @@ markers = prompt_caching_stack: needs a proxy running with router_settings.optional_pre_call_checks including prompt_caching; deselected unless E2E_PROMPT_CACHING_STACK is set cli_determinism: drives the real claude CLI for several seconds; deselected unless E2E_CLI_DETERMINISM is set redis_chaos: load test that pauses the proxy's Redis outright mid-run; needs a proxy booted from gateway/redis_chaos_ci_config.yml on the same host, and is deselected unless E2E_PERF_TESTS is set - quiet_stack: measures the proxy itself, so it runs while no other test on this host is hitting the stack; every other test waits for it to finish provider_edge_host: routes provider traffic through the pytest host's edge in every fixture mode, so the gateway must reach the pytest host; deselected unless E2E_PROVIDER_EDGE_HOST_REACHABLE is set owned_gateway: boots its own proxy from source against the stack's Postgres, so it needs DATABASE_URL on the pytest host; deselected unless E2E_OWNED_GATEWAY is set otel_v2: needs a proxy running with LITELLM_OTEL_V2=true; deselected unless E2E_OTEL_V2 is set @@ -21,3 +20,4 @@ markers = secret_manager: needs a proxy booted from gateway/secret_manager__ci_config.yml against that live secret manager; deselected unless E2E_SECRET_MANAGER names the backend (see secret_manager/secret_backends.py) sagemaker_nova: needs a deployed SageMaker Nova endpoint the proxy's AWS credentials can invoke; deselected unless SAGEMAKER_NOVA_ENDPOINT names it sagemaker_nova2_lite: needs a deployed SageMaker Nova 2 Lite endpoint the proxy's AWS credentials can invoke; deselected unless SAGEMAKER_NOVA2_LITE_ENDPOINT names it + proxy_wide_config: turns on a proxy-wide setting through /config/update, so it runs on a stack no other suite is driving; deselected unless E2E_PROXY_WIDE_CONFIG_STACK is set diff --git a/tests/e2e/quota_management/spend_tracking/test_pricing_config_spend_e2e.py b/tests/e2e/quota_management/spend_tracking/test_guardrail_cost_spend_e2e.py similarity index 52% rename from tests/e2e/quota_management/spend_tracking/test_pricing_config_spend_e2e.py rename to tests/e2e/quota_management/spend_tracking/test_guardrail_cost_spend_e2e.py index 8f3bed3f89b..a77ca91ad3a 100644 --- a/tests/e2e/quota_management/spend_tracking/test_pricing_config_spend_e2e.py +++ b/tests/e2e/quota_management/spend_tracking/test_guardrail_cost_spend_e2e.py @@ -17,11 +17,6 @@ from models import ( ChatBody, ChatMessage, ChatResponse, - ConfigPatchResponse, - CostDiscountConfig, - CostDiscountConfigResponse, - CostMarginConfig, - CostMarginConfigResponse, GuardrailCreateBody, GuardrailCreateResponse, KeyDeleteBody, @@ -31,14 +26,11 @@ from models import ( ) from spend_e2e_client import SpendClient -pytestmark = [pytest.mark.e2e, pytest.mark.quiet_stack] +pytestmark = pytest.mark.e2e BACKEND_MODEL: Final = "openai/gpt-6.1-sol" INPUT_RATE: Final = 0.00005 OUTPUT_RATE: Final = 0.0001 -DISCOUNT: Final = 0.25 -MARGIN_PERCENT: Final = 0.1 -MARGIN_FIXED: Final = 0.0005 def _register_bedrock_guardrail( @@ -92,52 +84,6 @@ def _guarded_chat(client: SpendClient, key: str, model: str, name: str) -> Strea ) -def _set_discount(client: SpendClient, values: dict[str, float]) -> float: - unwrap( - client.proxy.transport.patch( - "/config/cost_discount_config", - headers=client.proxy.transport.master, - json=CostDiscountConfig(values), - response_type=ConfigPatchResponse, - ) - ) - return time.monotonic() - - -def _set_margin(client: SpendClient, values: dict[str, float | dict[str, float]]) -> float: - unwrap( - client.proxy.transport.patch( - "/config/cost_margin_config", - headers=client.proxy.transport.master, - json=CostMarginConfig(values), - response_type=ConfigPatchResponse, - ) - ) - return time.monotonic() - - -def _get_discount(client: SpendClient) -> dict[str, float]: - return unwrap( - client.proxy.transport.get( - "/config/cost_discount_config", - headers=client.proxy.transport.master, - params=NoBody(), - response_type=CostDiscountConfigResponse, - ) - ).values - - -def _get_margin(client: SpendClient) -> dict[str, float | dict[str, float]]: - return unwrap( - client.proxy.transport.get( - "/config/cost_margin_config", - headers=client.proxy.transport.master, - params=NoBody(), - response_type=CostMarginConfigResponse, - ) - ).values - - def _register_model(client: SpendClient, resources: ResourceManager, prefix: str) -> str: model: Final = f"{prefix}-{unique_marker()}" model_id: Final = client.proxy.create_model( @@ -199,100 +145,7 @@ def scoped_key(client: SpendClient, strict_resources: ResourceManager) -> str: return key -@pytest.fixture -def restored_pricing_config(client: SpendClient) -> Iterator[None]: - discount: Final = _get_discount(client) - margin: Final = _get_margin(client) - try: - _set_discount(client, {}) - reset_at: Final = _set_margin(client, {}) - settle_propagation(reset_at) - yield - finally: - try: - _set_discount(client, discount) - finally: - restored_at: Final = _set_margin(client, margin) - settle_propagation(restored_at) - - -class TestPricingConfigSpend: - @pytest.mark.covers( - "quota_management.spend_tracking.discount_config.logs_cost", - exercised_on=["chat_completions"], - ) - @meta( - Subject( - domain=Domain.SPEND_BUDGETS, - route=Route.SPEND_REPORTING, - providers=(Provider.OPENAI,), - models=(BACKEND_MODEL,), - mode=Mode.NONSTREAM, - ) - ) - def test_configured_discount_reaches_persisted_spend_row( - self, - client: SpendClient, - strict_resources: ResourceManager, - scoped_key: str, - restored_pricing_config: None, - ) -> None: - discount_set_at: Final = _set_discount(client, {"openai": DISCOUNT}) - settle_propagation(discount_set_at) - model: Final = _register_model(client, strict_resources, "discount-priced") - chat: Final = unwrap(client.chat(scoped_key, model, f"reply with one word {unique_marker()}", max_tokens=16)) - assert chat.id and chat.usage - assert chat.usage.prompt_tokens is not None and chat.usage.prompt_tokens > 0 - assert chat.usage.completion_tokens is not None and chat.usage.completion_tokens >= 0 - - row: Final = poll_cost_row(client.proxy, chat.id) - assert row is not None - base_cost: Final = _base_cost(row, chat.usage.prompt_tokens, chat.usage.completion_tokens) - breakdown: Final = row.breakdown - assert breakdown.discount_percent is not None and approx_equal(breakdown.discount_percent, DISCOUNT) - assert breakdown.discount_amount is not None and approx_equal(breakdown.discount_amount, base_cost * DISCOUNT) - assert row.spend is not None and approx_equal(row.spend, base_cost * (1 - DISCOUNT)) - - @pytest.mark.covers( - "quota_management.spend_tracking.margin_config.logs_cost", - exercised_on=["chat_completions"], - ) - @meta( - Subject( - domain=Domain.SPEND_BUDGETS, - route=Route.SPEND_REPORTING, - providers=(Provider.OPENAI,), - models=(BACKEND_MODEL,), - mode=Mode.NONSTREAM, - ) - ) - def test_configured_margin_reaches_persisted_spend_row( - self, - client: SpendClient, - strict_resources: ResourceManager, - scoped_key: str, - restored_pricing_config: None, - ) -> None: - margin_set_at: Final = _set_margin( - client, {"openai": {"percentage": MARGIN_PERCENT, "fixed_amount": MARGIN_FIXED}} - ) - settle_propagation(margin_set_at) - model: Final = _register_model(client, strict_resources, "margin-priced") - chat: Final = unwrap(client.chat(scoped_key, model, f"reply with one word {unique_marker()}", max_tokens=16)) - assert chat.id and chat.usage - assert chat.usage.prompt_tokens is not None and chat.usage.prompt_tokens > 0 - assert chat.usage.completion_tokens is not None and chat.usage.completion_tokens >= 0 - - row: Final = poll_cost_row(client.proxy, chat.id) - assert row is not None - base_cost: Final = _base_cost(row, chat.usage.prompt_tokens, chat.usage.completion_tokens) - breakdown: Final = row.breakdown - expected_margin: Final = base_cost * MARGIN_PERCENT + MARGIN_FIXED - assert breakdown.margin_percent is not None and approx_equal(breakdown.margin_percent, MARGIN_PERCENT) - assert breakdown.margin_fixed_amount is not None and approx_equal(breakdown.margin_fixed_amount, MARGIN_FIXED) - assert breakdown.margin_total_amount is not None and approx_equal(breakdown.margin_total_amount, expected_margin) - assert row.spend is not None and approx_equal(row.spend, base_cost + expected_margin) - +class TestGuardrailCostSpend: @pytest.mark.covers( "quota_management.spend_tracking.guardrail_cost.logs_cost", exercised_on=["chat_completions"], @@ -311,7 +164,6 @@ class TestPricingConfigSpend: client: SpendClient, strict_resources: ResourceManager, scoped_key: str, - restored_pricing_config: None, ) -> None: identifier: Final = os.environ["BEDROCK_GUARDRAIL_IDENTIFIER"] version: Final = os.environ["BEDROCK_GUARDRAIL_VERSION"] diff --git a/tests/e2e/quota_management/spend_tracking/test_key_attribution_e2e.py b/tests/e2e/quota_management/spend_tracking/test_key_attribution_e2e.py index e0c19ea1b6b..1d0878d073a 100644 --- a/tests/e2e/quota_management/spend_tracking/test_key_attribution_e2e.py +++ b/tests/e2e/quota_management/spend_tracking/test_key_attribution_e2e.py @@ -55,7 +55,7 @@ from spend_e2e_client import ( pytestmark = pytest.mark.e2e -CHAT_MODEL: Final = "gemini-2.5-flash" +CHAT_MODEL: Final = "gemini-3.8-flash" MESSAGES_MODEL: Final = "claude-haiku-4-5" RESPONSES_MODEL: Final = "openai-responses-codex" EMBED_MODEL: Final = "openai-text-embedding-3-small" diff --git a/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py b/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py index c7ef81f826a..d452525ec91 100644 --- a/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py +++ b/tests/e2e/quota_management/spend_tracking/test_spend_tracking_e2e.py @@ -3,7 +3,7 @@ Run against a proxy started with the gateway config. Coverage rationale: SPEND_TRACKING_COVERAGE_MATRIX.md. -Model names are literals from that config: chat tests hit "gemini-2.5-flash", +Model names are literals from that config: chat tests hit "gemini-3.8-flash", embedding tests hit "openai-text-embedding-3-small". Every test: fresh scoped key (isolation) -> real provider call -> unwrap (hard @@ -37,7 +37,7 @@ from spend_reconciliation import BACKEND as TRAFFIC_BACKEND pytestmark = pytest.mark.e2e -GEMINI_MODEL = "gemini-2.5-flash" +GEMINI_MODEL = "gemini-3.8-flash" CLAUDE_MODEL = "claude-haiku-4-5" CODEX_MODEL = "openai-responses-codex" EMBEDDING_MODEL = "openai-text-embedding-3-small" @@ -780,7 +780,7 @@ def test_spend_calculate_returns_nonzero_cost(client: SpendClient) -> None: GEMINI_MODEL, "estimate the cost of this request" ) assert cost > 0, ( - "/spend/calculate returned 0 for gemini-2.5-flash; " + "/spend/calculate returned 0 for gemini-3.8-flash; " "cost map may be missing this model" ) diff --git a/tests/e2e/quota_management/spend_tracking/test_websearch_interception_session_e2e.py b/tests/e2e/quota_management/spend_tracking/test_websearch_interception_session_e2e.py index ab7c2370365..84a598a2bbb 100644 --- a/tests/e2e/quota_management/spend_tracking/test_websearch_interception_session_e2e.py +++ b/tests/e2e/quota_management/spend_tracking/test_websearch_interception_session_e2e.py @@ -30,7 +30,7 @@ from models import ( from proxy_client import ProxyClient from pydantic import BaseModel, ValidationError -pytestmark = pytest.mark.e2e +pytestmark = [pytest.mark.e2e, pytest.mark.provider_live] BEDROCK_INVOKE_BACKEND: Final = "bedrock/invoke/us.anthropic.claude-haiku-4-5-20251001-v1:0" SEARCH_CALL_TYPE: Final = "asearch" diff --git a/tests/e2e/router/reliability_support.py b/tests/e2e/router/reliability_support.py index 03e585273c0..193a94cb581 100644 --- a/tests/e2e/router/reliability_support.py +++ b/tests/e2e/router/reliability_support.py @@ -57,11 +57,9 @@ CONTENT_POLICY_PROMPT = ( COOLDOWN_SECONDS = 30.0 REPLICA_PROPAGATION_SECONDS = 15.0 -# The smallest-context chat model OpenAI still serves (16385 tokens). A prompt -# past that limit comes back as a real `context_length_exceeded` 400, which is -# what litellm maps to ContextWindowExceededError. -SMALL_CONTEXT_MODEL = "openai/gpt-3.5-turbo" -SMALL_CONTEXT_LIMIT_TOKENS = 16385 +SMALL_CONTEXT_MODEL: Final = "openai/gpt-5.4-nano" +# model_prices_and_context_window.json, gpt-5.4-nano, verified 2026-11-02 +SMALL_CONTEXT_LIMIT_TOKENS: Final = 272000 def oversized_prompt(marker: str) -> str: @@ -107,7 +105,7 @@ def create_timeout_deployment(proxy: ProxyClient, name: str) -> str: @step(f"Add a deployment named {{name}} that calls the small-context model {SMALL_CONTEXT_MODEL}") def create_small_context_deployment(proxy: ProxyClient, name: str) -> str: - """Register a deployment on the smallest-context model OpenAI still serves, so an + """Register a deployment with a smaller context window than the backup, so an oversized prompt earns a real context-window refusal from the provider.""" return proxy.create_model(name, LiteLLMParamsBody(model=SMALL_CONTEXT_MODEL, api_key=REAL_KEY)) @@ -263,8 +261,7 @@ def spend_only_request_of(proxy: ProxyClient, spent_key: str) -> None: @step(f"Add a deployment named {{name}} that calls {SMALL_CONTEXT_MODEL} and takes all of its group's traffic") def create_always_picked_small_context_deployment(proxy: ProxyClient, name: str) -> str: - """The always-picked half of a retry pair on the smallest-context model OpenAI - still serves: it holds all of the model group's shuffle weight, so an oversized + """The always-picked half of a retry pair on the smaller-context model: it holds all of the model group's shuffle weight, so an oversized prompt opens on it and earns a real context-window refusal, which never benches a deployment, so only the retry itself can steer the request off it.""" return proxy.register_model( diff --git a/tests/e2e/stack_lock.py b/tests/e2e/stack_lock.py deleted file mode 100644 index 06df7a20b6a..00000000000 --- a/tests/e2e/stack_lock.py +++ /dev/null @@ -1,45 +0,0 @@ -"""Cross-process reader/writer lock over the proxy stack every xdist worker shares. -Every collected test holds it shared, marker or not, since the Claude Code cells and -other unmarked suites drive the same stack; a `quiet_stack` test holds it exclusive, -and the `gate` file makes a waiting exclusive holder win over readers that arrive -after it.""" - -from __future__ import annotations - -import fcntl -import hashlib -import tempfile -from collections.abc import Generator -from contextlib import ExitStack, contextmanager -from pathlib import Path -from typing import Final - -from e2e_config import PROXY_BASE_URL - -STACK_DIGEST: Final = hashlib.sha256(PROXY_BASE_URL.encode()).hexdigest()[:12] -LOCK_DIR: Final = Path(tempfile.gettempdir()) / f"litellm-e2e-stack-{STACK_DIGEST}" -GATE_FILE: Final = LOCK_DIR / "gate" -STACK_FILE: Final = LOCK_DIR / "stack" - - -@contextmanager -def _flock(path: Path, operation: int) -> Generator[None]: - with path.open("a") as handle: - fcntl.flock(handle, operation) - try: - yield - finally: - fcntl.flock(handle, fcntl.LOCK_UN) - - -@contextmanager -def stack_lock(exclusive: bool) -> Generator[None]: - LOCK_DIR.mkdir(parents=True, exist_ok=True) - if exclusive: - with _flock(GATE_FILE, fcntl.LOCK_EX), _flock(STACK_FILE, fcntl.LOCK_EX): - yield - return - with ExitStack() as held: - with _flock(GATE_FILE, fcntl.LOCK_SH): - held.enter_context(_flock(STACK_FILE, fcntl.LOCK_SH)) - yield diff --git a/tests/e2e/ui/helpers/navigation.ts b/tests/e2e/ui/helpers/navigation.ts index be46fcf0395..3943526aebf 100644 --- a/tests/e2e/ui/helpers/navigation.ts +++ b/tests/e2e/ui/helpers/navigation.ts @@ -37,7 +37,7 @@ export async function navigateToPage(page: PlaywrightPage, pageEnum: Page): Prom // assert against the default page. for (let attempt = 0; attempt < 3; attempt++) { await page.goto(`/ui?page=${pageEnum}`); - await page.waitForLoadState("networkidle"); + await expect(page.getByRole("complementary")).toBeVisible(); const url = new URL(page.url()); const onLegacyRoot = url.pathname.replace(/\/+$/, "").endsWith("/ui"); if (!onLegacyRoot || url.searchParams.get("page") === pageEnum) { diff --git a/tests/e2e/ui/tests/modelHub/modelHub.spec.ts b/tests/e2e/ui/tests/modelHub/modelHub.spec.ts index 04b02d9ccc4..517ec64c7df 100644 --- a/tests/e2e/ui/tests/modelHub/modelHub.spec.ts +++ b/tests/e2e/ui/tests/modelHub/modelHub.spec.ts @@ -1,8 +1,8 @@ -import { test, expect, type APIRequestContext } from "@playwright/test"; +import { test, expect } from "@playwright/test"; import { ADMIN_STORAGE_PATH } from "../../constants"; import { navigateToPage, dismissFeedbackPopup } from "../../helpers/navigation"; import { Page } from "../../fixtures/pages"; -import { masterKey } from "../../helpers/traffic"; +import { masterKey, uniqueSuffix } from "../../helpers/traffic"; test.describe("AI Hub (internal admin view)", () => { test.use({ storageState: ADMIN_STORAGE_PATH }); @@ -62,106 +62,93 @@ test.describe("AI Hub (internal admin view)", () => { }); test.describe("Public model hub (/ui/model_hub_table)", () => { - // No storageState — the public page is reached anonymously with a `key` query param. - - test("Public model_hub_table loads and renders the Model Hub tab", async ({ page }) => { - // The page expects the proxy key as the `key` query param. Use the master - // key the e2e runner already exports — this matches what the AI Hub copy - // button hands out. - await page.goto(`/ui/model_hub_table?key=${masterKey()}`); - - // Dismiss the feedback popup before asserting on the tab, so a popup - // race can't briefly mask the tab while we're evaluating visibility. + test("shows the Model Hub and Skills Hub catalogs", async ({ page }) => { + await page.goto("/ui/model_hub_table"); await dismissFeedbackPopup(page); - // Page loads (no auth redirect) and the Model Hub tab is always present. - // Agent Hub and MCP Hub tabs are conditionally rendered only when public - // agents/MCP servers exist, so we don't assert on them in a fresh CI run. - await expect(page.getByRole("tab", { name: "Model Hub" })).toBeVisible({ timeout: 10_000 }); + await expect( + page.getByRole("tab", { name: "Model Hub", exact: true }), + ).toBeVisible(); + await expect( + page.getByRole("textbox", { name: "Search models", exact: true }), + ).toBeVisible(); + await expect(page.getByRole("tab")).toHaveCount(2); + await page.getByRole("tab", { name: "Skills Hub", exact: true }).click(); + await expect( + page.getByRole("textbox", { name: "Search skills", exact: true }), + ).toBeVisible(); }); - test("Agent Hub and MCP Hub tabs render their public entries", async ({ page, request }) => { - const suffix = `${Date.now()}`; - const agentName = `e2e-public-agent-${suffix}`; - const mcpServerName = `e2e_public_mcp_${suffix}`; + test("finds a published skill and opens its installation instructions", async ({ + page, + request, + }) => { + const skillName = `e2e-catalog-${uniqueSuffix()}`; + const domain = `catalog-${uniqueSuffix()}`; const auth = { Authorization: `Bearer ${masterKey()}` }; - - const publicMcpServerIds = async (api: APIRequestContext): Promise => { - const res = await api.get("/public/mcp_hub"); - expect(res.ok(), `public mcp_hub read failed (${res.status()}): ${await res.text()}`).toBe(true); - const servers: { server_id: string }[] = await res.json(); - return servers.map((server) => server.server_id); - }; - - const seedPublicEntries = async ( - api: APIRequestContext, - priorMcpIds: string[], - ): Promise<{ agentId: string; serverId: string }> => { - const agentRes = await api.post("/v1/agents", { - headers: auth, - data: { - agent_name: agentName, - agent_card_params: { - name: agentName, - description: "E2E public agent", - version: "1.0.0", - url: "http://127.0.0.1:9999/", - capabilities: {}, - skills: [], - defaultInputModes: ["text"], - defaultOutputModes: ["text"], - }, - }, - }); - expect(agentRes.ok(), `agent create failed (${agentRes.status()}): ${await agentRes.text()}`).toBe(true); - const agentId = (await agentRes.json()).agent_id as string; - - const serverRes = await api.post("/v1/mcp/server", { - headers: auth, - data: { - server_name: mcpServerName, - url: "http://127.0.0.1:9999/mcp", - transport: "http", - description: "E2E public MCP server", - }, - }); - expect(serverRes.ok(), `mcp server create failed (${serverRes.status()}): ${await serverRes.text()}`).toBe(true); - const serverId = (await serverRes.json()).server_id as string; - - const agentPublicRes = await api.post(`/v1/agents/${agentId}/make_public`, { headers: auth }); - expect(agentPublicRes.ok(), `agent make_public failed: ${await agentPublicRes.text()}`).toBe(true); - const mcpPublicRes = await api.post("/v1/mcp/make_public", { - headers: auth, - data: { mcp_server_ids: [...priorMcpIds, serverId] }, - }); - expect(mcpPublicRes.ok(), `mcp make_public failed: ${await mcpPublicRes.text()}`).toBe(true); - - return { agentId, serverId }; - }; - - const priorMcpIds = await publicMcpServerIds(request); - const { agentId, serverId } = await seedPublicEntries(request, priorMcpIds); + const created = await request.post("/claude-code/plugins", { + headers: auth, + data: { + name: skillName, + source: { source: "github", repo: "example/catalog-skills" }, + description: "Catalog browser test skill", + domain, + version: "1.0.0", + }, + }); + expect( + created.ok(), + `skill registration failed (${created.status()}): ${await created.text()}`, + ).toBe(true); try { - await page.goto(`/ui/model_hub_table?key=${masterKey()}`); + await page.goto("/ui/model_hub_table?tab=skills"); await dismissFeedbackPopup(page); + await page.getByRole("checkbox", { name: domain, exact: true }).check(); + await page + .getByRole("textbox", { name: "Search skills", exact: true }) + .fill(skillName); + await page.getByRole("link").filter({ hasText: skillName }).click(); - const agentHubTab = page.getByRole("tab", { name: "Agent Hub" }); - await expect(agentHubTab).toBeVisible({ timeout: 15_000 }); - await agentHubTab.click(); - await expect(page.getByText("Available Agents")).toBeVisible({ timeout: 10_000 }); - await expect(page.getByRole("row").filter({ hasText: agentName })).toHaveCount(1, { timeout: 10_000 }); - await expect(page.getByText("E2E public agent").first()).toBeVisible(); - - const mcpHubTab = page.getByRole("tab", { name: "MCP Hub" }); - await expect(mcpHubTab).toBeVisible(); - await mcpHubTab.click(); - await expect(page.getByText("Available MCP Servers")).toBeVisible({ timeout: 10_000 }); - await expect(page.getByRole("row").filter({ hasText: mcpServerName })).toHaveCount(1, { timeout: 10_000 }); - await expect(page.getByText("E2E public MCP server").first()).toBeVisible(); + const details = page.getByRole("dialog"); + await expect( + details.getByRole("heading", { name: skillName, exact: true }), + ).toBeVisible(); + await expect( + details.getByText(`/plugin install ${skillName}@litellm`, { + exact: true, + }), + ).toBeVisible(); + await expect(page).toHaveURL(new RegExp(`open=${skillName}`)); + await page.reload(); + await expect( + page + .getByRole("dialog") + .getByRole("heading", { name: skillName, exact: true }), + ).toBeVisible(); } finally { - await request.post("/v1/mcp/make_public", { headers: auth, data: { mcp_server_ids: priorMcpIds } }); - await request.delete(`/v1/agents/${agentId}`, { headers: auth }); - await request.delete(`/v1/mcp/server/${serverId}`, { headers: auth }); + const deleted = await request.delete( + `/claude-code/plugins/${skillName}`, + { headers: auth }, + ); + expect(deleted.ok(), `skill cleanup failed (${deleted.status()})`).toBe( + true, + ); + } + }); + + test("retired catalog links return to Models and clear the old selection", async ({ + page, + }) => { + for (const tab of ["agents", "mcp"]) { + await page.goto( + `/ui/model_hub_table?tab=${tab}&open=retired-entry&key=preserved`, + ); + await dismissFeedbackPopup(page); + await expect( + page.getByRole("tab", { name: "Model Hub", exact: true }), + ).toHaveAttribute("aria-selected", "true"); + await expect(page).toHaveURL(/model_hub_table\?key=preserved$/); + await expect(page.getByRole("dialog")).toHaveCount(0); } }); }); diff --git a/tests/e2e/ui/tests/modelsPage/addModel.spec.ts b/tests/e2e/ui/tests/modelsPage/addModel.spec.ts index a99fb937b83..b5e876b36d2 100644 --- a/tests/e2e/ui/tests/modelsPage/addModel.spec.ts +++ b/tests/e2e/ui/tests/modelsPage/addModel.spec.ts @@ -391,7 +391,7 @@ test.describe("Add Model", () => { // Navigate to Deployed Models tab await page.getByRole("tab", { name: "Deployed Models" }).click(); - await page.waitForLoadState("networkidle"); + await expect(page.getByPlaceholder("Search model names")).toBeVisible(); // Search for the model we just added await page.getByPlaceholder("Search model names").fill("claude-haiku-4-5"); @@ -470,7 +470,7 @@ test.describe("Add Model", () => { // The Models table renders team-scoped models with the team id in the row. await page.getByRole("tab", { name: "Deployed Models" }).click(); - await page.waitForLoadState("networkidle"); + await expect(page.getByPlaceholder("Search model names")).toBeVisible(); await page.getByPlaceholder("Search model names").fill("cohere"); @@ -515,7 +515,7 @@ test.describe("Add Model", () => { // Navigate to Deployed Models tab await page.getByRole("tab", { name: "Deployed Models" }).click(); - await page.waitForLoadState("networkidle"); + await expect(page.getByPlaceholder("Search model names")).toBeVisible(); // Search for the wildcard model await page.getByPlaceholder("Search model names").fill("cohere"); diff --git a/tests/e2e/ui/tests/modelsPage/editLitellmParams.spec.ts b/tests/e2e/ui/tests/modelsPage/editLitellmParams.spec.ts index 4480515ae59..0831c003891 100644 --- a/tests/e2e/ui/tests/modelsPage/editLitellmParams.spec.ts +++ b/tests/e2e/ui/tests/modelsPage/editLitellmParams.spec.ts @@ -27,7 +27,7 @@ async function readStoredParams( } function paramsEditor(page: PlaywrightPage) { - return page.getByPlaceholder('"rpm": 100'); + return page.getByRole("textbox", { name: "LiteLLM Params", exact: true }); } async function editParams( diff --git a/tests/e2e/ui/tests/navigation/commandPalette.spec.ts b/tests/e2e/ui/tests/navigation/commandPalette.spec.ts new file mode 100644 index 00000000000..5e80afb8b18 --- /dev/null +++ b/tests/e2e/ui/tests/navigation/commandPalette.spec.ts @@ -0,0 +1,54 @@ +import { test, expect, type Page as PlaywrightPage } from "@playwright/test"; +import { ADMIN_STORAGE_PATH } from "../../constants"; +import { Page } from "../../fixtures/pages"; +import { dismissFeedbackPopup, navigateToPage } from "../../helpers/navigation"; +import { createVirtualKey, deleteVirtualKey, uniqueSuffix } from "../../helpers/traffic"; + +const paletteSearch = (page: PlaywrightPage) => page.getByRole("combobox", { name: "Search" }); +const headerTrigger = (page: PlaywrightPage) => page.getByRole("button", { name: "Search keys…", exact: true }); + +test.describe("Command palette", () => { + test.use({ storageState: ADMIN_STORAGE_PATH }); + + test.beforeEach(async ({ page }) => { + await navigateToPage(page, Page.ApiKeys); + await dismissFeedbackPopup(page); + await expect(headerTrigger(page)).toBeVisible(); + }); + + test("opens a key found by its alias", async ({ page }) => { + const alias = `e2e-palette-key-${uniqueSuffix()}`; + const created = await createVirtualKey(page.request, { key_alias: alias }); + try { + await page.keyboard.press("ControlOrMeta+K"); + await paletteSearch(page).fill(alias); + await expect(page.getByRole("option", { name: new RegExp(`^${alias}`) })).toBeVisible(); + await page.keyboard.press("Enter"); + + await expect(page).toHaveURL(new RegExp(`[?&]key=${created.token}`)); + await expect(paletteSearch(page)).toBeHidden(); + } finally { + await deleteVirtualKey(page.request, created.token); + } + }); + + test("does not open over the Create New Key dialog", async ({ page }) => { + await page.getByRole("button", { name: /Create New Key/i }).click(); + const keyName = page.getByLabel(/Key Name/); + await keyName.click(); + + await page.keyboard.press("ControlOrMeta+K"); + await page.keyboard.type("still-in-the-dialog"); + + await expect(keyName).toHaveValue("still-in-the-dialog"); + await expect(paletteSearch(page)).toBeHidden(); + }); + + test("opens from the header trigger and closes with Escape", async ({ page }) => { + await headerTrigger(page).click(); + await expect(paletteSearch(page)).toBeFocused(); + + await page.keyboard.press("Escape"); + await expect(paletteSearch(page)).toBeHidden(); + }); +}); diff --git a/tests/e2e_harness/AGENTS.md b/tests/e2e_harness/AGENTS.md index 65a3b32df96..4f507c2fe7b 100644 --- a/tests/e2e_harness/AGENTS.md +++ b/tests/e2e_harness/AGENTS.md @@ -1,8 +1,8 @@ # e2e harness tests -Tests of the harness under `tests/e2e/` (the transport, the clients, the fixture bundle and replay edge, the stack lock, the IdP launcher, the coverage collector, the JUnit properties and the Claude Code driver), not of the product. They live outside `tests/e2e/` because the Buildkite e2e run copies that folder into the runner image and runs every test in it, so a harness test in there counts as a product test in the nightly numbers. Nothing here needs a proxy, provider keys or the network +Tests of the harness under `tests/e2e/` (the transport, the clients, the fixture bundle and replay edge, the IdP launcher, the coverage collector, the JUnit properties and the Claude Code driver), not of the product. They live outside `tests/e2e/` because the Buildkite e2e run copies that folder into the runner image and runs every test in it, so a harness test in there counts as a product test in the nightly numbers. Nothing here needs a proxy, provider keys or the network -The layout mirrors `tests/e2e/`: `test_e2e_http.py` covers `tests/e2e/e2e_http.py`, `logging/test_datadog_reader.py` covers `tests/e2e/logging/datadog_reader.py`, and `claude_code/` covers the driver, builder, probe and version resolver. Put a new harness test under the folder that mirrors the suite folder whose module it covers +The layout mirrors `tests/e2e/`: `test_e2e_http.py` covers `tests/e2e/e2e_http.py`, `logging/test_datadog_reader.py` covers `tests/e2e/logging/datadog_reader.py`, `claude_code/` covers the driver, builder and probe, `cli_harness/` covers the version resolver, the CLI env lockdown and the rate limiter, and `codex/` covers how the Codex driver reads the CLI's JSONL events and the compactions in a thread's rollout file. Put a new harness test under the folder that mirrors the suite folder whose module it covers Run them from the repo root. `e2e_config` reads `LITELLM_MASTER_KEY` at import and any value will do, the CI lane sets a dummy: diff --git a/tests/e2e_harness/claude_code/test_pr_gate_version_resolver.py b/tests/e2e_harness/claude_code/test_pr_gate_version_resolver.py deleted file mode 100644 index 0ed7e2bf083..00000000000 --- a/tests/e2e_harness/claude_code/test_pr_gate_version_resolver.py +++ /dev/null @@ -1,60 +0,0 @@ -"""Unit tests for the Claude Code PR-gate version resolver. - -Markerless harness tests: they feed the resolver a hand-built packument and a -fixed clock, so they run without a proxy, never reach the npm registry, and -carry no `e2e` marker. -""" - -from __future__ import annotations - -from datetime import datetime, timezone -from typing import Final, Mapping - -import pytest - -from claude_code.pr_gate_version_resolver import NoEligibleVersionError, resolve_pr_gate_version - -NOW: Final = datetime(2026, 4, 25, 12, 0, tzinfo=timezone.utc) -INSIDE_THE_2_1_88_WINDOW: Final = datetime(2026, 4, 3, 12, 0, tzinfo=timezone.utc) - - -def _packument(times: Mapping[str, str], unpublished: frozenset[str] = frozenset()) -> dict[str, object]: - return { - "name": "@anthropic-ai/claude-code", - "time": {"created": "2024-01-01T00:00:00.000Z", "modified": "2026-04-25T00:00:00.000Z", **times}, - "versions": {version: {"version": version} for version in times if version not in unpublished}, - } - - -def test_skips_a_version_npm_has_unpublished() -> None: - metadata: Final = _packument( - { - "2.1.87": "2026-03-28T20:00:00.000Z", - "2.1.88": "2026-03-30T22:36:48.424Z", - "2.1.89": "2026-03-31T23:32:40.000Z", - }, - unpublished=frozenset({"2.1.88"}), - ) - assert resolve_pr_gate_version(metadata=metadata, as_of=INSIDE_THE_2_1_88_WINDOW) == "2.1.87" - - -def test_raises_when_the_only_old_enough_version_is_unpublished() -> None: - metadata: Final = _packument( - {"2.1.88": "2026-03-30T22:36:48.424Z", "2.1.89": "2026-03-31T23:32:40.000Z"}, - unpublished=frozenset({"2.1.88"}), - ) - with pytest.raises(NoEligibleVersionError): - resolve_pr_gate_version(metadata=metadata, as_of=INSIDE_THE_2_1_88_WINDOW) - - -def test_picks_the_newest_published_version_at_least_min_age_old() -> None: - metadata: Final = _packument( - { - "2.1.118": "2026-04-15T10:00:00.000Z", - "2.1.119": "2026-04-21T10:00:00.000Z", - "2.2.0-rc.1": "2026-04-22T10:00:00.000Z", - "2.1.120": "2026-04-23T10:00:00.000Z", - "2.1.121": "2026-04-25T11:00:00.000Z", - } - ) - assert resolve_pr_gate_version(metadata=metadata, as_of=NOW) == "2.1.119" diff --git a/tests/e2e_harness/claude_code/test_request_determinism.py b/tests/e2e_harness/claude_code/test_request_determinism.py index b7d330b7da6..c6edb02d1c5 100644 --- a/tests/e2e_harness/claude_code/test_request_determinism.py +++ b/tests/e2e_harness/claude_code/test_request_determinism.py @@ -34,7 +34,7 @@ from typing import List, Tuple import pytest from claude_code.cli_driver import _FIXED_CLI_USER_ID, _seed_cli_identity, _stable_cli_state, run_claude -from claude_code.rate_limiter import RateLimiter +from cli_harness.rate_limiter import RateLimiter pytestmark = pytest.mark.cli_determinism diff --git a/tests/e2e_harness/cli_harness/test_lockdown.py b/tests/e2e_harness/cli_harness/test_lockdown.py new file mode 100644 index 00000000000..fcb24f4a830 --- /dev/null +++ b/tests/e2e_harness/cli_harness/test_lockdown.py @@ -0,0 +1,32 @@ +from __future__ import annotations + +from pathlib import Path +from typing import Final + +from cli_harness.lockdown import isolated_home, locked_down_env + +RUNNER_ENV: Final = { + "PATH": "/usr/bin", + "LANG": "C.UTF-8", + "HOME": "/home/runner", + "OPENAI_API_KEY": "sk-runner-secret", + "AWS_SECRET_ACCESS_KEY": "runner-aws-secret", + "DATABASE_URL": "postgresql://runner", +} + + +def test_cli_sees_runtime_vars_and_its_overrides_but_no_runner_credentials(tmp_path: Path) -> None: + env: Final = locked_down_env(home=tmp_path, overrides={"OPENAI_BASE_URL": "http://gateway"}, source=RUNNER_ENV) + assert dict(env) == { + "PATH": "/usr/bin", + "LANG": "C.UTF-8", + "HOME": str(tmp_path), + "OPENAI_BASE_URL": "http://gateway", + } + + +def test_isolated_home_starts_empty_and_is_gone_after_the_cli_exits() -> None: + with isolated_home("cli-harness-test-") as home: + assert home.is_dir() and not any(home.iterdir()) + (home / ".config").mkdir() + assert not home.exists() diff --git a/tests/e2e_harness/cli_harness/test_npm_version_resolver.py b/tests/e2e_harness/cli_harness/test_npm_version_resolver.py new file mode 100644 index 00000000000..3a84ccd361a --- /dev/null +++ b/tests/e2e_harness/cli_harness/test_npm_version_resolver.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +from collections.abc import Mapping +from datetime import datetime, timedelta, timezone +from typing import Final + +from cli_harness.npm_version_resolver import MIN_AGE, Packument, newest_version_at_least + +NOW: Final = datetime(2026, 4, 25, 12, 0, tzinfo=timezone.utc) +INSIDE_THE_2_1_88_WINDOW: Final = datetime(2026, 4, 3, 12, 0, tzinfo=timezone.utc) + + +def _packument(times: Mapping[str, str], unpublished: frozenset[str] = frozenset()) -> Packument: + return Packument.from_json( + { + "name": "@scope/some-cli", + "time": {"created": "2024-01-01T00:00:00.000Z", "modified": "2026-04-25T00:00:00.000Z", **times}, + "versions": {version: {"version": version} for version in times if version not in unpublished}, + } + ) + + +def test_skips_a_version_npm_has_unpublished() -> None: + packument: Final = _packument( + { + "2.1.87": "2026-03-28T20:00:00.000Z", + "2.1.88": "2026-03-30T22:36:48.424Z", + "2.1.89": "2026-03-31T23:32:40.000Z", + }, + unpublished=frozenset({"2.1.88"}), + ) + assert newest_version_at_least(packument, min_age=MIN_AGE, as_of=INSIDE_THE_2_1_88_WINDOW) == "2.1.87" + + +def test_finds_nothing_when_the_only_old_enough_version_is_unpublished() -> None: + packument: Final = _packument( + {"2.1.88": "2026-03-30T22:36:48.424Z", "2.1.89": "2026-03-31T23:32:40.000Z"}, + unpublished=frozenset({"2.1.88"}), + ) + assert newest_version_at_least(packument, min_age=MIN_AGE, as_of=INSIDE_THE_2_1_88_WINDOW) is None + + +def test_picks_the_newest_stable_version_at_least_min_age_old() -> None: + packument: Final = _packument( + { + "2.1.118": "2026-04-15T10:00:00.000Z", + "2.1.119": "2026-04-21T10:00:00.000Z", + "2.2.0-rc.1": "2026-04-22T10:00:00.000Z", + "2.1.120": "2026-04-23T10:00:00.000Z", + "2.1.121": "2026-04-25T11:00:00.000Z", + } + ) + assert newest_version_at_least(packument, min_age=MIN_AGE, as_of=NOW) == "2.1.119" + + +def test_newest_means_latest_published_not_highest_semver() -> None: + packument: Final = _packument( + { + "3.0.0": "2026-04-01T10:00:00.000Z", + "2.9.9": "2026-04-10T10:00:00.000Z", + } + ) + assert newest_version_at_least(packument, min_age=timedelta(days=3), as_of=NOW) == "2.9.9" diff --git a/tests/e2e_harness/cli_harness/test_rate_limiter.py b/tests/e2e_harness/cli_harness/test_rate_limiter.py new file mode 100644 index 00000000000..78ad3e92450 --- /dev/null +++ b/tests/e2e_harness/cli_harness/test_rate_limiter.py @@ -0,0 +1,78 @@ +from __future__ import annotations + +import multiprocessing +from collections.abc import Mapping +from dataclasses import dataclass +from multiprocessing.synchronize import Barrier +from pathlib import Path +from types import MappingProxyType +from typing import Final, NoReturn + +from cli_harness.rate_limiter import ProviderConfig, RateBucket, RateLimiter + +_RACERS: Final = 8 +_ATTEMPTS_PER_RACER: Final = 100 +_BURST: Final = 400 +_NO_REFILL: Final[Mapping[RateBucket, ProviderConfig]] = MappingProxyType( + {RateBucket.OPENAI: ProviderConfig(rate_per_sec=1e-9, burst=_BURST)} +) + + +@dataclass +class _FakeTime: + now: float = 0.0 + + def clock(self) -> float: + return self.now + + def sleep(self, seconds: float) -> None: + self.now += seconds + + +def test_two_processes_on_one_host_share_a_single_budget_per_bucket(tmp_path: Path) -> None: + fake_time: Final = _FakeTime() + config: Final = {RateBucket.OPENAI: ProviderConfig(rate_per_sec=2.0, burst=1.0)} + first_process: Final = RateLimiter(config, tmp_path, fake_time.clock, fake_time.sleep) + second_process: Final = RateLimiter(config, tmp_path, fake_time.clock, fake_time.sleep) + + assert first_process.acquire(RateBucket.OPENAI) == 0.0 + assert 0.5 <= second_process.acquire(RateBucket.OPENAI) < 0.51 + assert second_process.acquire(RateBucket.BEDROCK_MANTLE) == 0.0 + + +def test_processes_racing_for_one_bucket_never_get_more_than_its_burst(tmp_path: Path) -> None: + grants: Final = tmp_path / "grants" + + _race(_RACERS, state_dir=tmp_path / "state", grants=grants) + + assert len(grants.read_bytes()) == _BURST + + +def _race(racers: int, *, state_dir: Path, grants: Path) -> None: + context: Final = multiprocessing.get_context("spawn") + start_line: Final = context.Barrier(racers) + processes: Final = tuple( + context.Process(target=_take_tokens_until_told_to_wait, args=(state_dir, grants, start_line)) + for _ in range(racers) + ) + for process in processes: + process.start() + for process in processes: + process.join() + + +def _take_tokens_until_told_to_wait(state_dir: Path, grants: Path, start_line: Barrier) -> None: + limiter: Final = RateLimiter(_NO_REFILL, state_dir, _frozen_clock, _exit_instead_of_sleeping) + with grants.open("ab", buffering=0) as log: + _ = start_line.wait() + for _ in range(_ATTEMPTS_PER_RACER): + _ = limiter.acquire(RateBucket.OPENAI) + _ = log.write(b".") + + +def _frozen_clock() -> float: + return 0.0 + + +def _exit_instead_of_sleeping(_seconds: float) -> NoReturn: + raise SystemExit(0) diff --git a/tests/e2e_harness/codex/test_codex_rollout.py b/tests/e2e_harness/codex/test_codex_rollout.py new file mode 100644 index 00000000000..2ef27a8a9c5 --- /dev/null +++ b/tests/e2e_harness/codex/test_codex_rollout.py @@ -0,0 +1,77 @@ +from __future__ import annotations + +import json +import time +from collections.abc import Mapping +from pathlib import Path +from typing import Final + +from cli_harness.rate_limiter import RateBucket, RateLimiter +from codex.harness import CodexHarness +from codex.rollout import Compaction, rollout_compactions + +THREAD_ID: Final = "01a18fea-b2e8-7ed2-a29b-1ce4d2b138c3" +USER_PROMPT: Final = { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "Run `cat secret.txt` and remember the value it prints."}], +} + + +def _line(record_type: str, payload: Mapping[str, object]) -> str: + return json.dumps({"timestamp": "2026-10-31T03:03:32.000Z", "type": record_type, "payload": payload}) + + +def _rollout(*compactions: Mapping[str, object]) -> str: + return "\n".join( + ( + _line("session_meta", {"id": THREAD_ID, "cli_version": "0.165.0"}), + _line("response_item", USER_PROMPT), + *(_line("compacted", compaction) for compaction in compactions), + _line("event_msg", {"type": "task_complete"}), + ) + ) + + +REMOTE: Final = { + "message": "", + "replacement_history": [USER_PROMPT, {"type": "compaction", "encrypted_content": "gAAAAABq5VrT"}], +} +LOCAL: Final = { + "message": "The user asked to read secret.txt, which printed 4a6e834a61f8d792.", + "replacement_history": [ + USER_PROMPT, + {"type": "message", "role": "user", "content": [{"type": "input_text", "text": "Summary: 4a6e834a61f8d792"}]}, + ], +} + + +class TestRolloutCompactions: + def test_a_compaction_that_kept_the_providers_compaction_item_is_remote(self) -> None: + assert rollout_compactions(_rollout(REMOTE)) == (Compaction(remote=True),) + + def test_a_compaction_that_codex_summarized_itself_is_local(self) -> None: + assert rollout_compactions(_rollout(LOCAL, {"message": "an older rollout with no replacement history"})) == ( + Compaction(remote=False), + Compaction(remote=False), + ) + + def test_a_rollout_without_compactions_has_none(self) -> None: + assert rollout_compactions(_rollout()) == () + + +def test_the_harness_reads_only_the_rollout_of_the_thread_it_is_asked_about(tmp_path: Path) -> None: + codex: Final = CodexHarness( + home=tmp_path, + api_key="unused", + rate_bucket=RateBucket.OPENAI, + limiter=RateLimiter({}, tmp_path, time.monotonic, time.sleep), + ) + sessions: Final = codex.codex_home / "sessions" / "2026" / "10" / "30" + sessions.mkdir(parents=True) + _ = (sessions / f"rollout-2026-10-30T20-03-32-{THREAD_ID}.jsonl").write_text(_rollout(REMOTE)) + _ = (sessions / "rollout-2026-10-30T20-04-00-01a18feb-9d3e-7ee1-b19f-e35d8894e5da.jsonl").write_text( + _rollout(LOCAL) + ) + + assert codex.compactions(THREAD_ID) == (Compaction(remote=True),) diff --git a/tests/e2e_harness/codex/test_codex_run.py b/tests/e2e_harness/codex/test_codex_run.py new file mode 100644 index 00000000000..415967da114 --- /dev/null +++ b/tests/e2e_harness/codex/test_codex_run.py @@ -0,0 +1,92 @@ +from __future__ import annotations + +import configparser +import json +import re +import shlex +from collections.abc import Mapping +from pathlib import Path +from typing import Final + +from codex.run import Command, codex_run + +E2E_PYTEST_INI: Final = Path(__file__).resolve().parents[2] / "e2e" / "pytest.ini" + +ROUND_TRIP: Final = "\n".join( + ( + '{"type":"thread.started","thread_id":"01a18f9f-9d08-72e0-9be3-aa34cf7489d2"}', + '{"type":"turn.started"}', + '{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"I will run it."}}', + '{"type":"item.started","item":{"id":"item_1","type":"command_execution","command":"/bin/zsh -lc \'cat' + ' secret.txt\'","aggregated_output":"","exit_code":null,"status":"in_progress"}}', + '{"type":"item.completed","item":{"id":"item_1","type":"command_execution","command":"/bin/zsh -lc \'cat' + ' secret.txt\'","aggregated_output":"marker-7f3a91\\n","exit_code":0,"status":"completed"}}', + '{"type":"item.completed","item":{"id":"item_2","type":"agent_message","text":"marker-7f3a91"}}', + '{"type":"turn.completed","usage":{"input_tokens":22547,"cached_input_tokens":11227,' + '"cache_write_input_tokens":11314,"output_tokens":67,"reasoning_output_tokens":0}}', + ) +) + + +def _line(event: Mapping[str, object]) -> str: + return json.dumps(event) + + +class TestCodexRun: + def test_the_answer_is_the_last_agent_message_and_each_finished_command_keeps_its_output(self) -> None: + run: Final = codex_run(exit_code=0, stdout=ROUND_TRIP, stderr="") + + assert run.thread_id == "01a18f9f-9d08-72e0-9be3-aa34cf7489d2" + assert run.commands == ( + Command(command="/bin/zsh -lc 'cat secret.txt'", output="marker-7f3a91\n", exit_code=0), + ) + assert run.answer == "marker-7f3a91" + assert run.usage is not None and run.usage.input_tokens == 22547 + assert run.errors == () + + def test_only_a_patch_that_applied_counts_as_patching_its_files(self) -> None: + def patch(status: str, path: str) -> str: + item: Final = { + "id": path, + "type": "file_change", + "status": status, + "changes": [{"path": path, "kind": "update"}], + } + return _line({"type": "item.completed", "item": item}) + + run: Final = codex_run( + exit_code=0, stdout="\n".join((patch("completed", "/w/app.py"), patch("failed", "/w/other.py"))), stderr="" + ) + + assert run.patched_files == (Path("/w/app.py"),) + + def test_a_turn_that_gave_up_on_a_5xx_is_rerun_by_the_suites_network_rule(self) -> None: + failed: Final = _line( + {"type": "turn.failed", "error": {"message": "exceeded retry limit, last status: 502 Bad Gateway"}} + ) + + run: Final = codex_run(exit_code=1, stdout=failed, stderr="") + + assert run.errors[0].status_code == 502 + rerun_patterns: Final = _only_rerun_patterns(E2E_PYTEST_INI) + assert any(re.search(pattern, repr(run)) for pattern in rerun_patterns), rerun_patterns + + def test_an_event_or_item_type_it_does_not_model_is_skipped(self) -> None: + newer_codex: Final = "\n".join( + ( + _line({"type": "thread.goal_set", "goal": "ship it"}), + _line({"type": "item.completed", "item": {"id": "item_9", "type": "todo_list", "items": []}}), + ROUND_TRIP, + ) + ) + + assert codex_run(exit_code=0, stdout=newer_codex, stderr="") == codex_run( + exit_code=0, stdout=ROUND_TRIP, stderr="" + ) + + +def _only_rerun_patterns(ini: Path) -> tuple[str, ...]: + parser: Final = configparser.ConfigParser() + _ = parser.read(ini) + args: Final = shlex.split(parser["pytest"]["addopts"]) + return tuple(value for flag, value in zip(args, args[1:]) if flag == "--only-rerun") diff --git a/tests/e2e_harness/logging/test_logging_client.py b/tests/e2e_harness/logging/test_logging_client.py new file mode 100644 index 00000000000..c396a6c68e5 --- /dev/null +++ b/tests/e2e_harness/logging/test_logging_client.py @@ -0,0 +1,49 @@ +import json +from typing import Final + +import pytest +from pydantic import JsonValue + +from logging_client import LangfuseObservation, is_otel_v2_generation, observation_spend + + +@pytest.mark.parametrize("encoded", [False, True]) +@pytest.mark.parametrize("cost", [0.0, 0.000023]) +def test_observation_preserves_v2_content_usage_and_cost(encoded: bool, cost: float) -> None: + content: Final[JsonValue] = [{"role": "user", "content": "unique-request-marker"}] + output: Final[JsonValue] = [{"role": "assistant", "content": "response"}] + metadata: Final[JsonValue] = { + "attributes": { + "langfuse.observation.type": "generation", + "litellm.metadata.user_api_key_alias": "test-key-alias", + } + } + usage: Final[JsonValue] = {"input": 17, "output": 3} + observation: Final = LangfuseObservation.model_validate( + { + "id": "observation", + "input": json.dumps(content) if encoded else content, + "output": json.dumps(output) if encoded else output, + "metadata": json.dumps(metadata) if encoded else metadata, + "usageDetails": usage, + "totalCost": cost, + } + ) + + assert observation.input == content + assert observation.output == output + assert observation.usage_details == usage + assert observation_spend(observation) == cost + assert is_otel_v2_generation(observation, key_alias="test-key-alias") + assert not is_otel_v2_generation(observation, key_alias="another-key") + + +def test_observation_preserves_plain_text_and_legacy_cost() -> None: + cost: Final = 0.000031 + observation: Final = LangfuseObservation.model_validate( + {"id": "observation", "input": "plain prompt", "output": "plain reply", "calculatedTotalCost": cost} + ) + + assert observation.input == "plain prompt" + assert observation.output == "plain reply" + assert observation_spend(observation) == cost diff --git a/tests/e2e_harness/logging/test_span_selection.py b/tests/e2e_harness/logging/test_span_selection.py index e7487562e43..76f70e4d8bb 100644 --- a/tests/e2e_harness/logging/test_span_selection.py +++ b/tests/e2e_harness/logging/test_span_selection.py @@ -8,8 +8,21 @@ helper is worth pinning here. from __future__ import annotations +from typing import Final + import pytest -from otel_client import TTFT_TAG, JaegerTrace, one_served_genai_span, served_genai_spans +from otel_client import ( + TTFT_TAG, + CallTraces, + JaegerReference, + JaegerSpan, + JaegerTag, + JaegerTrace, + one_served_genai_span, + served_genai_spans, + trace_settled, +) +from test_otel_trace_e2e import assert_complete_trace, assert_real_ttft GENAI_SPAN = "chat claude-haiku-4-5" @@ -79,3 +92,73 @@ def test_other_operations_are_not_counted() -> None: trace = _trace(_span("chat gpt-5.5", ttft=0.3), _span(GENAI_SPAN, ttft=0.3)) assert len(served_genai_spans(trace, GENAI_SPAN)) == 1 + + +def _request_trace( + *, + root_name: str = "POST", + root_kind: str = "server", + route: str = "/v1/messages", + genai_parent: str = "root", + ttft: float = 0.2, +) -> JaegerTrace: + parent: Final = JaegerReference(refType="CHILD_OF", traceID="request", spanID="root") + return JaegerTrace( + traceID="request", + spans=[ + JaegerSpan( + spanID="root", + operationName=root_name, + tags=[JaegerTag(key="span.kind", value=root_kind), JaegerTag(key="http.target", value=route)], + ), + JaegerSpan(spanID="auth", operationName="auth /v1/messages", references=[parent]), + JaegerSpan(spanID="db", operationName="postgres.select tokens", references=[parent]), + JaegerSpan( + spanID="genai", + operationName=GENAI_SPAN, + duration=1_000_000, + references=[JaegerReference(refType="CHILD_OF", traceID="request", spanID=genai_parent)], + tags=[JaegerTag(key="span.kind", value="client"), JaegerTag(key=TTFT_TAG, value=ttft)], + ), + ], + ) + + +@pytest.mark.parametrize("root_name", ("POST", "POST /v1/messages")) +def test_connected_request_trace_is_independent_of_server_display_name(root_name: str) -> None: + trace: Final = _request_trace(root_name=root_name) + assert_complete_trace(CallTraces((trace,), ()), route="/v1/messages", genai_span=GENAI_SPAN) + assert_real_ttft((trace,), genai_span=GENAI_SPAN) + assert trace_settled(trace, {"auth /v1/messages", GENAI_SPAN}, {"postgres."}) + + +def test_incomplete_trace_cannot_settle_before_the_server_span_arrives() -> None: + trace: Final = _request_trace() + incomplete: Final = trace.model_copy(update={"spans": trace.spans[1:]}) + assert not trace_settled(incomplete, {"auth /v1/messages", GENAI_SPAN}, {"postgres."}) + + +@pytest.mark.parametrize("route", ("/v1/responses", "")) +def test_request_trace_must_still_identify_the_requested_route(route: str) -> None: + trace: Final = _request_trace(root_name="POST /v1/messages", route=route) + with pytest.raises(AssertionError, match="route"): + assert_complete_trace(CallTraces((trace,), ()), route="/v1/messages", genai_span=GENAI_SPAN) + + +def test_request_trace_must_still_be_rooted_at_a_server_span() -> None: + trace: Final = _request_trace(root_name="POST /v1/messages", root_kind="client") + with pytest.raises(AssertionError, match="kind=server"): + assert_complete_trace(CallTraces((trace,), ()), route="/v1/messages", genai_span=GENAI_SPAN) + + +def test_request_trace_must_still_connect_the_model_call_to_the_request() -> None: + trace: Final = _request_trace(genai_parent="absent") + with pytest.raises(AssertionError, match="orphaned trace"): + assert_complete_trace(CallTraces((trace,), ()), route="/v1/messages", genai_span=GENAI_SPAN) + + +@pytest.mark.parametrize("ttft", (0.0, 1.0)) +def test_server_name_tolerance_does_not_accept_invalid_first_token_timing(ttft: float) -> None: + trace: Final = _request_trace(ttft=ttft) + with pytest.raises(AssertionError, match="TTFT"): + assert_real_ttft((trace,), genai_span=GENAI_SPAN) diff --git a/tests/e2e_harness/perf/test_run.py b/tests/e2e_harness/perf/test_run.py index 23f62c9c560..480af96a12a 100644 --- a/tests/e2e_harness/perf/test_run.py +++ b/tests/e2e_harness/perf/test_run.py @@ -8,7 +8,29 @@ from typing import Final import pytest from setup.run import run_until from setup.wire import WireRecord -from test_upgrade import record + + +def record(seq: int = 0, *, started_at: float = 100) -> WireRecord: + return WireRecord( + seq=seq, + marker=f"request-{seq}", + caller="key", + endpoint="chat_completions", + stream=False, + blocked=False, + started_at=started_at, + status=200, + header_s=1, + first_byte_s=1, + first_token_s=None, + total_s=1, + text="answer", + ok=True, + mock_delay_s=1, + call_id=f"call-{seq}", + error=None, + response_id=f"response-{seq}", + ) class StopAfterRecord: diff --git a/tests/e2e_harness/perf/test_upgrade.py b/tests/e2e_harness/perf/test_upgrade.py deleted file mode 100644 index 3414476ba4c..00000000000 --- a/tests/e2e_harness/perf/test_upgrade.py +++ /dev/null @@ -1,375 +0,0 @@ -from __future__ import annotations - -from collections.abc import Mapping -from typing import Final - -import pytest -from cases.small_bodies_5rps import CASE -from memory_readings import RssCapture, RssReading -from setup.observe import Observation, evaluate -from setup.upgrade import ( - MAX_TRAFFIC_SECONDS, - UpgradeMonitor, - matched_response_ids, - postgres_failures, - upgrade_case, - upgrade_properties, -) -from setup.upgrade_worker import UpgradeState -from setup.wire import PlanProgress, WireRecord, response_id - - -def record(seq: int = 0, *, started_at: float = 100) -> WireRecord: - return WireRecord( - seq=seq, - marker=f"request-{seq}", - caller="key", - endpoint="chat_completions", - stream=False, - blocked=False, - started_at=started_at, - status=200, - header_s=1, - first_byte_s=1, - first_token_s=None, - total_s=1, - text="answer", - ok=True, - mock_delay_s=1, - call_id=f"call-{seq}", - error=None, - response_id=f"response-{seq}", - ) - - -def test_spend_logs_match_call_ids_when_response_ids_are_transformed() -> None: - records: Final = (record(0), record(1), record(2)) - rows: Final = (("provider-response-id", "call-0"), ("response-1", "unrelated-call")) - assert matched_response_ids(records, rows) == frozenset({"response-0"}) - - -def state(phase: str = "schema_ready", *, pending: bool = True) -> UpgradeState: - return UpgradeState.model_validate( - { - "phase": phase, - "started_at": 0, - "required_indexes": ["index"], - "required_migrations": ["migration"], - "pending_indexes": ["index"] if pending else [], - "baseline_rows": {"seed-row": "hash"}, - } - ) - - -class Probe: - def __init__(self) -> None: - self.now = 0.0 - self.current = state() - self.builds: list[int] = [] - self.found: frozenset[str] = frozenset() - self.releases = 0 - self.metric_checks = 0 - self.errors = False - - def check_metrics(self) -> None: - self.metric_checks += 1 - assert not self.errors, "Failed PostgreSQL operation" - - def persisted(self, records: tuple[WireRecord, ...]) -> frozenset[str]: - return frozenset(row.response_id for row in records if row.response_id in self.found and row.response_id) - - def release(self) -> None: - self.releases += 1 - - def monitor(self) -> UpgradeMonitor: - return UpgradeMonitor( - state=lambda: self.current, - check_metrics=self.check_metrics, - read_activity=lambda: (self.builds, 2), - read_persisted=self.persisted, - start_indexes=self.release, - clock=lambda: self.now, - wall_clock=lambda: self.now, - ) - - -def test_stop_drains_issued_requests_without_issuing_the_rest() -> None: - progress: Final = PlanProgress(100) - assert progress.take(stop=False) - assert progress.take(stop=False) - progress.completed = 1 - assert not progress.take(stop=True) - assert not progress.drained - assert not progress.take(stop=False) - progress.completed = 2 - assert progress.drained - assert progress.issued == 2 - - -def test_finite_plan_still_waits_for_its_last_response() -> None: - progress: Final = PlanProgress(1) - assert progress.take(stop=False) - assert not progress.take(stop=False) - assert not progress.drained - progress.completed = 1 - assert progress.drained - - -@pytest.mark.parametrize( - "payload,expected", - [ - ({"id": "chat-id"}, "chat-id"), - ({"type": "response.created", "response": {"id": "response-id"}}, "response-id"), - ({"type": "message_start", "message": {"id": "message-id"}}, "message-id"), - ({"type": "response.output_item.added", "item": {"id": "item-id"}}, None), - ({"type": "content_block_delta", "delta": {"text": "hello"}}, None), - ], -) -def test_response_id_uses_response_not_output_item(payload: Mapping[str, object], expected: str | None) -> None: - assert response_id(payload) == expected - - -def metrics(*, failure: str = "0", batch: str = "0") -> str: - return f"""# TYPE litellm_postgres_failed_requests_total counter -litellm_postgres_failed_requests_total{{function_name="query",error_class="Timeout"}} {failure} -# TYPE litellm_batch_write_to_db_failed_requests_total counter -litellm_batch_write_to_db_failed_requests_total{{function_name="flush",error_class="DatabaseError"}} {batch} -""" - - -def test_failed_sql_and_async_batch_writes_are_both_counted() -> None: - assert postgres_failures(metrics(failure="2", batch="3")) == 5 - assert postgres_failures(metrics()) == 0 - - -def test_no_error_label_series_is_a_valid_zero() -> None: - assert ( - postgres_failures("""# TYPE litellm_postgres_failed_requests_total counter -# TYPE litellm_batch_write_to_db_failed_requests_total counter -""") - == 0 - ) - - -@pytest.mark.parametrize("service", [None, "postgres", "batch_write_to_db"]) -def test_multiprocess_metrics_omit_failure_families_until_a_failure(service: str | None) -> None: - total: Final = """# TYPE litellm_postgres_total_requests_total counter -litellm_postgres_total_requests_total{postgres="postgres"} 1 -""" - failure: Final = ( - f"# TYPE litellm_{service}_failed_requests_total counter\n" - f'litellm_{service}_failed_requests_total{{function_name="query",error_class="Timeout"}} 1\n' - if service is not None - else "" - ) - assert postgres_failures(total + failure) == (1 if service is not None else 0) - - -@pytest.mark.parametrize("total", ["0", "-1", "NaN", "+Inf"]) -def test_missing_failure_families_require_observed_database_activity(total: str) -> None: - with pytest.raises(AssertionError): - _ = postgres_failures( - "# TYPE litellm_postgres_total_requests_total counter\n" - f'litellm_postgres_total_requests_total{{postgres="postgres"}} {total}\n' - ) - - -@pytest.mark.parametrize("body", ["", "# TYPE unrelated counter\n", metrics(failure="NaN"), metrics(batch="-1")]) -def test_missing_or_invalid_counters_do_not_pass_as_zero(body: str) -> None: - with pytest.raises(AssertionError): - _ = postgres_failures(body) - - -def test_index_completion_stops_after_the_post_upgrade_window() -> None: - probe: Final = Probe() - monitor: Final = probe.monitor() - assert not monitor.poll((record(),)) - assert probe.releases == 1 - probe.builds = [17] - probe.now = 101 - assert not monitor.poll(()) - probe.found = frozenset({"response-0", "response-1"}) - probe.now = 103 - assert not monitor.poll((record(1, started_at=102),)) - assert monitor.overlap_writes == 1 - assert monitor.persisted_count == 2 - assert not monitor.pending - assert monitor.max_lock_waiters == 2 - probe.current = state("complete") - assert not monitor.poll(()) - probe.now = 162 - assert not monitor.poll(()) - probe.now = 163 - assert not monitor.poll(()) - probe.found = frozenset(f"response-{i}" for i in range(300)) - assert monitor.poll(tuple(record(i) for i in range(2, 300))) - assert probe.releases == 1 - assert probe.metric_checks == 7 - - -def test_http_200_without_spend_row_cannot_complete() -> None: - probe: Final = Probe() - monitor: Final = probe.monitor() - records: Final = tuple(record(i) for i in range(300)) - _ = monitor.poll(records) - with pytest.raises(AssertionError, match="no matching spend log"): - monitor.assert_complete(state("complete", pending=False)) - - -def test_no_pending_index_work_still_requires_300_persisted_requests() -> None: - probe: Final = Probe() - monitor: Final = probe.monitor() - records: Final = tuple(record(i) for i in range(300)) - probe.found = frozenset(f"response-{i}" for i in range(300)) - _ = monitor.poll(records) - monitor.assert_complete(state("complete", pending=False)) - assert monitor.successes == monitor.persisted_count == 300 - with pytest.raises(AssertionError, match="during index work"): - monitor.assert_complete(state("complete", pending=True)) - - -def test_postgres_failure_fails_even_when_inference_succeeded() -> None: - probe: Final = Probe() - monitor: Final = probe.monitor() - probe.errors = True - with pytest.raises(AssertionError, match="PostgreSQL"): - _ = monitor.poll((record(),)) - - -def test_failed_migration_and_operational_timeout_are_not_success() -> None: - probe: Final = Probe() - monitor: Final = probe.monitor() - probe.current = state("failed") - with pytest.raises(AssertionError, match="worker failed"): - _ = monitor.poll(()) - probe.current = state() - probe.now = MAX_TRAFFIC_SECONDS - with pytest.raises(AssertionError, match="operational timeout"): - _ = monitor.poll(()) - - -def test_upgrade_case_uses_5rps_with_the_same_request_and_memory_limits() -> None: - case: Final = upgrade_case() - assert case.traffic.rps == 5 - assert not {"cpu_seconds_per_request", "postgres_calls_per_request", "redis_calls_per_request"}.intersection( - limit.metric for limit in case.limits - ) - assert case.limits == tuple( - limit - for limit in CASE.limits - if limit.metric - in { - "unexpected_status_count", - "gateway_added_seconds", - "time_to_first_token_seconds", - "memory_growth_megabytes", - } - ) - - -def failed_record(seq: int) -> WireRecord: - return record(seq).model_copy(update={"status": 503, "ok": False, "text": "", "response_id": None, "call_id": None}) - - -def test_three_non_200s_do_not_start_indexes_or_require_spend_rows() -> None: - probe: Final = Probe() - monitor: Final = probe.monitor() - assert not monitor.poll(tuple(failed_record(i) for i in range(3))) - assert probe.releases == 0 - assert monitor.processed == 3 - assert monitor.successes == 0 - assert not monitor.pending - probe.found = frozenset(f"response-{i}" for i in range(3, 303)) - assert not monitor.poll(tuple(record(i) for i in range(3, 303))) - monitor.assert_complete(state("complete", pending=False)) - assert probe.releases == 1 - assert monitor.processed == 303 - assert monitor.successes == monitor.persisted_count == 300 - - -def test_fourth_non_200_fails_across_poll_batches() -> None: - monitor: Final = Probe().monitor() - assert not monitor.poll(tuple(failed_record(i) for i in range(3))) - with pytest.raises(AssertionError, match="Too many unexpected non-200"): - _ = monitor.poll((failed_record(3),)) - - -@pytest.mark.parametrize( - "failed", [record().model_copy(update={"text": ""}), record().model_copy(update={"ok": False})] -) -def test_invalid_200_is_not_an_allowed_non_200(failed: WireRecord) -> None: - with pytest.raises(AssertionError, match="Failed or empty inference"): - _ = Probe().monitor().poll((failed,)) - - -def _ceiling(metric: str, percentile: int | None = None) -> float: - return next( - limit.max - for limit in upgrade_case().limits - if limit.metric == metric and limit.percentile == percentile and limit.max is not None - ) - - -@pytest.mark.parametrize( - "over,expected", - [ - ("", ()), - ("unexpected_status_count", ("unexpected_status_count",)), - ("gateway_added_seconds", ("gateway_added_seconds percentile 50",)), - ("time_to_first_token_seconds", ("time_to_first_token_seconds percentile 99",)), - ("memory_growth_megabytes", ("memory_growth_megabytes",)), - ], -) -def test_upgrade_verdict_uses_regular_limits_without_cpu_or_datastore_samples( - over: str, expected: tuple[str, ...] -) -> None: - """Each sample sits exactly on the case's ceiling, so only the one nudged past it goes over.""" - failures: Final = int(_ceiling("unexpected_status_count")) + (over == "unexpected_status_count") - overhead: Final = _ceiling("gateway_added_seconds", 50) * (1.01 if over == "gateway_added_seconds" else 1) - ttft: Final = _ceiling("time_to_first_token_seconds", 99) * (1.01 if over == "time_to_first_token_seconds" else 1) - growth: Final = _ceiling("memory_growth_megabytes") + (over == "memory_growth_megabytes") - nonstream: Final = tuple(record(i).model_copy(update={"total_s": overhead, "mock_delay_s": 0}) for i in range(100)) - stream: Final = record(100).model_copy(update={"stream": True, "first_token_s": ttft}) - observed: Final = Observation( - records=(*nonstream, stream, *(failed_record(i) for i in range(101, 101 + failures))), - mock_requests=(), - guardrail_calls=(), - rss_before=RssCapture((RssReading("gateway", "host", 1, 1000),), ()), - rss_after=RssCapture((RssReading("gateway", "host", 1, 1000 + growth),), ()), - wall_seconds=60, - ) - rows, exceeded = evaluate(upgrade_case(), observed) - assert tuple(row.label for row in rows if row.over or row.missing) == expected - assert len(exceeded) == len(expected) - - -def test_upgrade_properties_carry_the_upgrade_timings_and_what_the_monitor_saw() -> None: - state: Final = UpgradeState( - phase="complete", - started_at=0, - schema_seconds=12.5, - index_seconds=240.25, - required_indexes=("idx_a", "idx_b"), - required_migrations=("20260101_a",), - pending_indexes=("idx_b",), - baseline_rows={}, - ) - monitor: Final = UpgradeMonitor( - state=lambda: state, - check_metrics=lambda: None, - read_activity=lambda: ([], 0), - read_persisted=lambda records: frozenset(), - start_indexes=lambda: None, - ) - monitor.overlap_writes = 37 - monitor.max_lock_waiters = 3 - monitor.pending = (record(0), record(1)) - - assert dict(upgrade_properties(state, monitor)) == { - "perf_upgrade_schema_seconds": 12.5, - "perf_upgrade_index_seconds": 240.25, - "perf_upgrade_overlap_writes": 37, - "perf_upgrade_max_lock_waiters": 3, - "perf_upgrade_pending_indexes": 1, - "perf_upgrade_unmatched_requests": 2, - } diff --git a/tests/e2e_harness/pytest.ini b/tests/e2e_harness/pytest.ini index a29166d31bd..9ccf8ba83a0 100644 --- a/tests/e2e_harness/pytest.ini +++ b/tests/e2e_harness/pytest.ini @@ -5,5 +5,8 @@ addopts = --strict-markers --strict-config -p no:cacheprovider pythonpath = ../e2e ../e2e/batches ../e2e/guardrails ../e2e/logging ../e2e/perf markers = + e2e: live assertion modules imported by harness regression tests + meta(subject): metadata on live assertion modules imported by harness regression tests + otel_tls: TLS coverage in live assertion modules imported by harness regression tests covers(cell_id, *, exercised_on=()): coverage-registry cell(s) a test covers; exercised here only to prove the collector and the JUnit properties read it cli_determinism: drives the real claude CLI for several seconds diff --git a/tests/e2e_harness/test_proxy_client.py b/tests/e2e_harness/test_proxy_client.py index e1615ec5f65..d352e5c8d36 100644 --- a/tests/e2e_harness/test_proxy_client.py +++ b/tests/e2e_harness/test_proxy_client.py @@ -12,10 +12,11 @@ injected clock, so nothing here monkeypatches anything. from __future__ import annotations import json +import time from builtins import ExceptionGroup from collections.abc import Callable, Generator, Iterable, Mapping from contextlib import contextmanager -from dataclasses import dataclass +from dataclasses import dataclass, replace from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer from itertools import chain, repeat from queue import SimpleQueue @@ -40,7 +41,10 @@ from models import ( LiteLLMParamsBody, McpServerCreateBody, McpServerUpdateBody, + ModelDeleteBody, + ModelInfoBody, ModelListEntry, + ModelNewBody, ModelsListResponse, OrgNewBody, OrgUpdateBody, @@ -59,6 +63,8 @@ from proxy_client import ( ConvergeOutcome, CredentialKind, EverywhereConverged, + ModelNotRegistered, + ModelRegistered, ModelsPoller, NeverConvergedOn, NotConverged, @@ -691,3 +697,85 @@ def test_partial_updates_preserve_explicit_null_at_the_http_boundary(operation: ) assert json.loads(bodies.get_nowait()) == expected assert bodies.empty() + + +@contextmanager +def model_registry( + listed: frozenset[str], refused: frozenset[str] +) -> Generator[tuple[ProxyClient, SimpleQueue[float], SimpleQueue[str]]]: + writes: Final[SimpleQueue[float]] = SimpleQueue() + deleted: Final[SimpleQueue[str]] = SimpleQueue() + + class Handler(BaseHTTPRequestHandler): + def log_message(self, format: str, *args: object) -> None: + pass + + def reply(self, status: int, body: object) -> None: + self.send_response(status) + self.end_headers() + self.wfile.write(json.dumps(body).encode()) + + def do_GET(self) -> None: + self.reply(200, {"data": [{"id": name} for name in sorted(listed)]}) + + def do_POST(self) -> None: + raw: Final = self.rfile.read(int(self.headers.get("Content-Length", "0"))) + if self.path == "/model/delete": + deleted.put(ModelDeleteBody.model_validate_json(raw).id) + self.reply(200, {}) + return + writes.put(time.monotonic()) + name: Final = ModelNewBody.model_validate_json(raw).model_name + if name in refused: + self.reply(500, {"error": "refused"}) + return + self.reply(200, {"model_id": f"id-{name}"}) + + server: Final = ThreadingHTTPServer(("127.0.0.1", 0), Handler) + thread: Final = Thread(target=lambda: server.serve_forever(poll_interval=0.01), daemon=True) + thread.start() + url: Final = f"http://127.0.0.1:{server.server_port}" + proxy: Final = build_proxy_client( + base_url=url, control_plane_base_url=url, replica_urls=(url,), control_replica_urls=(url,), master_key="bootstrap" + ) + try: + yield replace(proxy, model_servable_timeout=0.3, model_servable_interval=0.01), writes, deleted + finally: + server.shutdown() + server.server_close() + thread.join(timeout=5) + + +class TestRegisterModels: + def test_a_batch_waits_once_after_its_last_write_and_reports_each_model(self) -> None: + names: Final = ("first", "refused", "ghost", "last") + settled: Final[SimpleQueue[float]] = SimpleQueue() + with ( + model_registry(listed=frozenset({"first", "last"}), refused=frozenset({"refused"})) as ( + proxy, + writes, + deleted, + ), + without_retries(), + ): + registrations: Final = replace(proxy, settle=settled.put).register_models( + tuple( + ModelNewBody( + model_name=name, litellm_params=LiteLLMParamsBody(model="synthetic"), model_info=ModelInfoBody() + ) + for name in names + ) + ) + last_write: Final = max(writes.get_nowait() for _ in names) + assert writes.empty() + assert settled.get_nowait() >= last_write + assert settled.empty(), "a batch must wait out propagation once, not once per model" + assert tuple((type(r), r.model_name) for r in registrations) == ( + (ModelRegistered, "first"), + (ModelNotRegistered, "refused"), + (ModelNotRegistered, "ghost"), + (ModelRegistered, "last"), + ) + assert tuple(r.model_id for r in registrations if isinstance(r, ModelRegistered)) == ("id-first", "id-last") + assert deleted.get_nowait() == "id-ghost" + assert deleted.empty() diff --git a/tests/e2e_harness/test_stack_lock.py b/tests/e2e_harness/test_stack_lock.py deleted file mode 100644 index b275ca8c755..00000000000 --- a/tests/e2e_harness/test_stack_lock.py +++ /dev/null @@ -1,117 +0,0 @@ -"""Cross-process behavior of the stack lock: readers share it, an exclusive holder waits for -every reader and keeps them out, and a reader arriving behind a waiting exclusive holder -queues behind it instead of starving it.""" - -from __future__ import annotations - -import fcntl -import inspect -import os -import subprocess -import sys -import time -from contextlib import ExitStack -from pathlib import Path -from typing import Final - -import pytest -import stack_lock - -HARNESS_DIR: Final = Path(inspect.getfile(stack_lock)).resolve().parent -DEADLINE_SECONDS: Final = 30.0 -SETTLE_SECONDS: Final = 0.5 -HOLDER_SCRIPT: Final = """ -import sys, time -from pathlib import Path -from stack_lock import stack_lock -name, mode, release_path, log_path = sys.argv[1:] - - -def record(event): - with Path(log_path).open("a") as log: - log.write(f"{name} {event}\\n") - - -record("waiting") -with stack_lock(exclusive=mode == "exclusive"): - record("enter") - while not Path(release_path).exists(): - time.sleep(0.02) - record("exit") -""" - - -def _events(log_path: Path) -> tuple[str, ...]: - return tuple(log_path.read_text().splitlines()) if log_path.exists() else () - - -def _wait_for_event(log_path: Path, event: str) -> None: - deadline: Final = time.monotonic() + DEADLINE_SECONDS - while event not in _events(log_path): - if time.monotonic() > deadline: - pytest.fail(f"{event!r} never appeared; events so far: {_events(log_path)}") - time.sleep(0.02) - - -def _wait_until_gate_is_held_exclusively(gate_path: Path) -> None: - deadline: Final = time.monotonic() + DEADLINE_SECONDS - with gate_path.open("a") as handle: - while True: - try: - fcntl.flock(handle, fcntl.LOCK_SH | fcntl.LOCK_NB) - except BlockingIOError: - return - fcntl.flock(handle, fcntl.LOCK_UN) - if time.monotonic() > deadline: - pytest.fail("no exclusive holder ever took the gate") - time.sleep(0.02) - - -def _start_holder(held: ExitStack, tmp_path: Path, name: str, mode: str) -> subprocess.Popen[bytes]: - holder: Final = held.enter_context( - subprocess.Popen( - ( - sys.executable, - "-P", - "-c", - HOLDER_SCRIPT, - name, - mode, - str(tmp_path / f"release-{name}"), - str(tmp_path / "events"), - ), - cwd=HARNESS_DIR, - env={**os.environ, "TMPDIR": str(tmp_path), "PYTHONPATH": str(HARNESS_DIR)}, - ) - ) - held.callback(holder.kill) - return holder - - -def test_readers_share_exclusive_waits_and_a_waiting_exclusive_beats_later_readers(tmp_path: Path) -> None: - lock_dir: Final = tmp_path / f"litellm-e2e-stack-{stack_lock.STACK_DIGEST}" - lock_dir.mkdir() - log_path: Final = tmp_path / "events" - with ExitStack() as held: - first_reader: Final = _start_holder(held, tmp_path, "A", "shared") - _wait_for_event(log_path, "A enter") - second_reader: Final = _start_holder(held, tmp_path, "R", "shared") - _wait_for_event(log_path, "R enter") - (tmp_path / "release-R").touch() - _wait_for_event(log_path, "R exit") - writer: Final = _start_holder(held, tmp_path, "W", "exclusive") - _wait_until_gate_is_held_exclusively(lock_dir / "gate") - late_reader: Final = _start_holder(held, tmp_path, "B", "shared") - _wait_for_event(log_path, "B waiting") - time.sleep(SETTLE_SECONDS) - (tmp_path / "release-A").touch() - _wait_for_event(log_path, "W enter") - (tmp_path / "release-W").touch() - _wait_for_event(log_path, "B enter") - (tmp_path / "release-B").touch() - for holder in (first_reader, second_reader, writer, late_reader): - assert holder.wait(timeout=DEADLINE_SECONDS) == 0 - events: Final = _events(log_path) - assert events.index("R enter") < events.index("A exit") - assert events.index("W enter") > events.index("A exit") - assert events.index("B enter") > events.index("W exit") diff --git a/tests/integration/_support/asgi.py b/tests/integration/_support/asgi.py index e84dc9439d3..30eb9f21760 100644 --- a/tests/integration/_support/asgi.py +++ b/tests/integration/_support/asgi.py @@ -15,7 +15,7 @@ from starlette.types import ASGIApp @contextmanager def asgi_server( - app: ASGIApp, *, before_stop: Callable[[], None] | None = None, port: int = 0, keepalive_seconds: int = 1 + app: ASGIApp, *, before_stop: Callable[[], None] | None = None, port: int = 0, keepalive_seconds: int = 30 ) -> Iterator[str]: with socket.socket() as listener: listener.bind(("127.0.0.1", port)) diff --git a/tests/integration/_support/custom_video_provider.py b/tests/integration/_support/custom_video_provider.py new file mode 100644 index 00000000000..3513d1e3186 --- /dev/null +++ b/tests/integration/_support/custom_video_provider.py @@ -0,0 +1,181 @@ +"""A customer-owned video provider for the proxy's `custom_provider_map`: a job queue with its own wire shape.""" + +from collections.abc import Mapping +from types import MappingProxyType +from typing import Final + +import httpx +from httpx._types import RequestFiles + +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms.base_llm.videos.transformation import BaseVideoConfig +from litellm.llms.custom_llm import CustomLLM +from litellm.types.router import GenericLiteLLMParams +from litellm.types.videos.main import VideoCreateOptionalRequestParams, VideoObject +from litellm.types.videos.utils import encode_video_id_with_provider, extract_original_video_id + +_STATUS_BY_STATE: Final = MappingProxyType({"queued": "queued", "running": "in_progress", "done": "completed"}) + + +def _video_object(job: Mapping[str, object], model: str | None, custom_llm_provider: str | None) -> VideoObject: + job_id: Final = str(job["job_id"]) + seconds: Final = job.get("seconds") + video: Final = VideoObject( + id=encode_video_id_with_provider(job_id, custom_llm_provider, model) if custom_llm_provider else job_id, + object="video", + status=_STATUS_BY_STATE[str(job["state"])], + created_at=0, + model=model, + seconds=str(seconds) if seconds is not None else None, + ) + return video + + +class QueueVideoConfig(BaseVideoConfig): + def get_supported_openai_params(self, model: str) -> list: # mutable-ok: BaseVideoConfig contract + return ["seconds"] + + def map_openai_params( + self, + video_create_optional_params: VideoCreateOptionalRequestParams, + model: str, + drop_params: bool, + ) -> dict: # mutable-ok: BaseVideoConfig contract + return {key: value for key, value in video_create_optional_params.items() if key == "seconds"} + + def validate_environment( + self, + headers: dict, # mutable-ok: BaseVideoConfig contract + model: str, + api_key: str | None = None, + litellm_params: GenericLiteLLMParams | None = None, + ) -> dict: # mutable-ok: BaseVideoConfig contract + key: Final = (litellm_params.api_key if litellm_params is not None else None) or api_key or "" + return {**headers, "X-Api-Key": key} + + def get_complete_url( + self, + model: str, + api_base: str | None, + litellm_params: dict, # mutable-ok: BaseVideoConfig contract + ) -> str: + if api_base is None: + raise ValueError("api_base is required") + return f"{api_base.rstrip('/')}/jobs" + + def transform_video_create_request( + self, + model: str, + prompt: str, + api_base: str, + video_create_optional_request_params: dict, # mutable-ok: BaseVideoConfig contract + litellm_params: GenericLiteLLMParams, + headers: dict, # mutable-ok: BaseVideoConfig contract + ) -> tuple[dict, RequestFiles, str]: # mutable-ok: BaseVideoConfig contract + seconds: Final = video_create_optional_request_params.get("seconds") + return ({"model": model, "prompt": prompt, "seconds": seconds}, [], api_base) + + def transform_video_create_response( + self, + model: str, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + custom_llm_provider: str | None = None, + request_data: dict | None = None, + ) -> VideoObject: + return _video_object(raw_response.json(), model, custom_llm_provider) + + def transform_video_status_retrieve_request( + self, + video_id: str, + api_base: str, + litellm_params: GenericLiteLLMParams, + headers: dict, # mutable-ok: BaseVideoConfig contract + ) -> tuple[str, dict]: # mutable-ok: BaseVideoConfig contract + return (f"{api_base}/{extract_original_video_id(video_id)}", {}) + + def transform_video_status_retrieve_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + custom_llm_provider: str | None = None, + client: object = None, + ) -> VideoObject: + return _video_object(raw_response.json(), None, custom_llm_provider) + + def transform_video_content_request( + self, + video_id: str, + api_base: str, + litellm_params: GenericLiteLLMParams, + headers: dict, # mutable-ok: BaseVideoConfig contract + variant: str | None = None, + ) -> tuple[str, dict]: # mutable-ok: BaseVideoConfig contract + return (f"{api_base}/{extract_original_video_id(video_id)}/file", {}) + + def transform_video_content_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + client: object = None, + ) -> bytes: + return raw_response.content + + def transform_video_list_request( + self, + api_base: str, + litellm_params: GenericLiteLLMParams, + headers: dict, # mutable-ok: BaseVideoConfig contract + after: str | None = None, + limit: int | None = None, + order: str | None = None, + extra_query: dict[str, object] | None = None, + ) -> tuple[str, dict]: # mutable-ok: BaseVideoConfig contract + return (api_base, {}) + + def transform_video_list_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + custom_llm_provider: str | None = None, + ) -> dict[str, str]: # mutable-ok: BaseVideoConfig contract + return raw_response.json() + + def transform_video_remix_request( + self, + video_id: str, + prompt: str, + api_base: str, + litellm_params: GenericLiteLLMParams, + headers: dict, # mutable-ok: BaseVideoConfig contract + extra_body: dict[str, object] | None = None, + ) -> tuple[str, dict]: # mutable-ok: BaseVideoConfig contract + raise NotImplementedError("the queue backend has no remix") + + def transform_video_remix_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + custom_llm_provider: str | None = None, + ) -> VideoObject: + raise NotImplementedError("the queue backend has no remix") + + def transform_video_delete_request( + self, + video_id: str, + api_base: str, + litellm_params: GenericLiteLLMParams, + headers: dict, # mutable-ok: BaseVideoConfig contract + ) -> tuple[str, dict]: # mutable-ok: BaseVideoConfig contract + raise NotImplementedError("the queue backend has no delete") + + def transform_video_delete_response( + self, + raw_response: httpx.Response, + logging_obj: LiteLLMLoggingObj, + ) -> VideoObject: + raise NotImplementedError("the queue backend has no delete") + + +VIDEO_CONFIG: Final = QueueVideoConfig() +IMAGE_ONLY_HANDLER: Final = CustomLLM() diff --git a/tests/integration/_support/interception_vendor.py b/tests/integration/_support/interception_vendor.py index 3ca40087441..b46eb998f7a 100644 --- a/tests/integration/_support/interception_vendor.py +++ b/tests/integration/_support/interception_vendor.py @@ -27,7 +27,7 @@ JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) _ITEMS: Final = TypeAdapter(list[dict[str, JsonValue]]) _CHAT_TARGET: Final = re.compile(r"^/openai/deployments/([^/]+)/chat/completions$") -Mode: TypeAlias = Literal["search", "plain", "search-down", "followup-fails", "missing"] +Mode: TypeAlias = Literal["search", "multi-search", "plain", "search-down", "followup-fails", "missing"] def deployment(mode: Mode) -> str: @@ -42,8 +42,8 @@ def plain(name: str) -> str: return f"plain-{name}" -def query(name: str) -> str: - return f"q-{name}" +def query(name: str, turn: int = 1) -> str: + return f"q-{name}" if turn == 1 else f"q-{name}-{turn}" def _minted(prefix: str) -> str: @@ -98,9 +98,20 @@ def _chat(name: str, body: Mapping[str, JsonValue]) -> Reply: content_type="text/event-stream", chunks=chat_stream(_minted(f"chatcmpl-{name}-s-"), "gpt-4o", plain(name)) ) messages: Final = _ITEMS.validate_python(body["messages"]) - if any(message.get("role") == "tool" for message in messages): + tool_results: Final = tuple(message for message in messages if message.get("role") == "tool") + if tool_results: if name.endswith("-followup-fails"): return _azure_error(500, FOLLOWUP_FAILURE) + if name.endswith("-multi-search") and len(tool_results) == 1: + call: Final = { + "id": f"call_{name[4:36]}-2", + "type": "function", + "function": {"name": SEARCH_TOOL, "arguments": json.dumps({"query": query(name, turn=2)})}, + } + message: Final = JSON_OBJECT.validate_python({"role": "assistant", "content": None, "tool_calls": [call]}) + return _chat_completion( + _minted(f"chatcmpl-{name}-2-"), message, "tool_calls", FOLLOWUP_USAGE + ) return _chat_completion( _minted(f"chatcmpl-{name}-2-"), {"role": "assistant", "content": answer(name)}, "stop", FOLLOWUP_USAGE ) @@ -153,9 +164,20 @@ def _responses(body: Mapping[str, JsonValue]) -> Reply: content_type="text/event-stream", chunks=responses_stream(_minted(f"resp_{name}_s_"), name, plain(name)) ) items: Final = _ITEMS.validate_python(body["input"]) if isinstance(body.get("input"), list) else [] - if any(item.get("type") == "function_call_output" for item in items): + function_call_outputs: Final = tuple(item for item in items if item.get("type") == "function_call_output") + if function_call_outputs: if name.endswith("-followup-fails"): return _azure_error(500, FOLLOWUP_FAILURE) + if name.endswith("-multi-search") and len(function_call_outputs) == 1: + call: Final = { + "type": "function_call", + "id": f"fc_{name[4:36]}-2", + "call_id": f"call_{name[4:36]}-2", + "name": SEARCH_TOOL, + "arguments": json.dumps({"query": query(name, turn=2)}), + "status": "completed", + } + return _response(_minted(f"resp_{name}_2_"), name, (call,), RESPONSES_FOLLOWUP_USAGE) return _response( _minted(f"resp_{name}_2_"), name, (_text_item(f"{name}_2", answer(name)),), RESPONSES_FOLLOWUP_USAGE ) diff --git a/tests/integration/_support/riva.py b/tests/integration/_support/riva.py index 8552bc2197d..438d877386b 100644 --- a/tests/integration/_support/riva.py +++ b/tests/integration/_support/riva.py @@ -39,6 +39,7 @@ class RivaCall: rpc: Rpc audio: bytes cancelled: bool + authorization: tuple[str, ...] = () @dataclass(frozen=True, slots=True) @@ -68,6 +69,10 @@ def pcm_bytes(seconds: float) -> int: return int(seconds * SAMPLE_RATE_HZ) * 2 +def _authorization(context: grpc.ServicerContext) -> tuple[str, ...]: + return tuple(str(value) for key, value in context.invocation_metadata() if key == "authorization") + + def carries_clip(audio: bytes, seconds: float) -> bool: sent: Final = _clip_samples(seconds) if len(audio) != len(sent) * 2: @@ -100,9 +105,9 @@ class _Asr(riva_asr_pb2_grpc.RivaSpeechRecognitionServicer): released: Final = threading.Event() context.add_callback(released.set) released.wait(timeout=_STALL_LIMIT_SECONDS) - self._calls.put(RivaCall(Rpc.RECOGNIZE, request.audio, cancelled=not context.is_active())) + self._calls.put(RivaCall(Rpc.RECOGNIZE, request.audio, not context.is_active(), _authorization(context))) return riva_asr_pb2.RecognizeResponse() - self._calls.put(RivaCall(Rpc.RECOGNIZE, request.audio, cancelled=False)) + self._calls.put(RivaCall(Rpc.RECOGNIZE, request.audio, False, _authorization(context))) return riva_asr_pb2.RecognizeResponse( results=[riva_asr_pb2.SpeechRecognitionResult(alternatives=[self._alternative(request.config)])] ) @@ -111,13 +116,12 @@ class _Asr(riva_asr_pb2_grpc.RivaSpeechRecognitionServicer): self, request_iterator: Iterable[riva_asr_pb2.StreamingRecognizeRequest], context: grpc.ServicerContext ) -> Iterator[riva_asr_pb2.StreamingRecognizeResponse]: if self._offline_only: - self._calls.put(RivaCall(Rpc.STREAMING, b"", cancelled=False)) + self._calls.put(RivaCall(Rpc.STREAMING, b"", False, _authorization(context))) context.abort(grpc.StatusCode.INVALID_ARGUMENT, OFFLINE_ONLY_REFUSAL) requests: Final = tuple(request_iterator) config: Final = requests[0].streaming_config.config if requests else riva_asr_pb2.RecognitionConfig() - self._calls.put( - RivaCall(Rpc.STREAMING, b"".join(request.audio_content for request in requests), cancelled=False) - ) + audio: Final = b"".join(request.audio_content for request in requests) + self._calls.put(RivaCall(Rpc.STREAMING, audio, False, _authorization(context))) yield riva_asr_pb2.StreamingRecognizeResponse( results=[riva_asr_pb2.StreamingRecognitionResult(alternatives=[self._alternative(config)], is_final=True)] ) diff --git a/tests/integration/authorization/_hidden_alias_budget.py b/tests/integration/authorization/_hidden_alias_budget.py index bee2a585cff..5e9c2f1a95a 100644 --- a/tests/integration/authorization/_hidden_alias_budget.py +++ b/tests/integration/authorization/_hidden_alias_budget.py @@ -150,6 +150,10 @@ def error_type(response: httpx.Response) -> str: return str(object_value(JSON_OBJECT.validate_json(response.content)["error"])["type"]) +def budget_refusal_error_type(route: str) -> str: + return "invalid_request_error" if route == "messages" else "budget_exceeded" + + def settle( send: Callable[[str], httpx.Response], status: int, *, burst: int = GATEWAY_BURST, seconds: float = 60 ) -> None: diff --git a/tests/integration/authorization/test_alias_chain_budget_waiver.py b/tests/integration/authorization/test_alias_chain_budget_waiver.py index 0908fa0691c..e9d922d14f9 100644 --- a/tests/integration/authorization/test_alias_chain_budget_waiver.py +++ b/tests/integration/authorization/test_alias_chain_budget_waiver.py @@ -44,6 +44,7 @@ from integration.authorization._hidden_alias_budget import ( async_anthropic_client, async_openai_client, base_url, + budget_refusal_error_type, error_type, fresh_chat, fresh_message, @@ -191,17 +192,18 @@ def _assert_refused( key: str, model: str, prefix: str, + route: str = "chat", send: Callable[[Gateway, str, str, str], httpx.Response] = fresh_chat, ) -> None: marker: Final = f"{prefix}-" + uuid.uuid4().hex refused: Final = send(candidate, model, key, marker) - assert _refusal(refused) == (BUDGET_EXCEEDED, "budget_exceeded"), refused.text + assert _refusal(refused) == (BUDGET_EXCEEDED, budget_refusal_error_type(route)), refused.text assert upstream_hits(upstream_requests(rig.gateway.upstream_url), marker) == 0 def _assert_refused_on_every_route(rig: ChainRig, candidate: Gateway, key: str, model: str) -> None: for route, send in ROUTES: - _assert_refused(rig, candidate, key, model, f"refused-{route}", send) + _assert_refused(rig, candidate, key, model, f"refused-{route}", route, send) def _assert_provider_failure(response: httpx.Response) -> None: diff --git a/tests/integration/authorization/test_claude_code_gateway_oauth.py b/tests/integration/authorization/test_claude_code_gateway_oauth.py index 23476c439de..11e4485031e 100644 --- a/tests/integration/authorization/test_claude_code_gateway_oauth.py +++ b/tests/integration/authorization/test_claude_code_gateway_oauth.py @@ -474,15 +474,15 @@ def test_device_authorization_polls_complete_sso_and_mints_a_model_restricted_be ) assert model_b_response.status_code == 403, model_b_response.text assert _JSON_OBJECT.validate_json(model_b_response.content) == { + "type": "error", "error": { + "type": "permission_error", "message": ( f"The requested model '{model_b}' is not available for this API key, or the model name is " "invalid. Check the models available to you and try again." ), - "type": "team_model_access_denied", - "param": "model", - "code": "403", - } + "litellm_error_type": "team_model_access_denied", + }, }, model_b_response.text assert upstream.drain() == () diff --git a/tests/integration/authorization/test_cli_sso_login_ui_disabled.py b/tests/integration/authorization/test_cli_sso_login_ui_disabled.py index a53fbfacf4c..fd4c7246801 100644 --- a/tests/integration/authorization/test_cli_sso_login_ui_disabled.py +++ b/tests/integration/authorization/test_cli_sso_login_ui_disabled.py @@ -695,9 +695,11 @@ def test_cli_session_token_is_denied_once_its_team_budget_is_exhausted( key=key, ) assert refused.status_code == 422, f"{refused.status_code} {refused.text}" - error: Final = object_value(JSON_OBJECT.validate_json(refused.content)["error"]) - assert error["type"] == "budget_exceeded", refused.text - assert error["code"] == "422", refused.text + body: Final = JSON_OBJECT.validate_json(refused.content) + assert body["type"] == "error", refused.text + error: Final = object_value(body["error"]) + assert error["type"] == "invalid_request_error", refused.text + assert "param" not in error and "code" not in error, refused.text message: Final = string_value(error["message"]) assert "Budget has been exceeded!" in message, refused.text assert f"Team={team}" in message, refused.text diff --git a/tests/integration/authorization/test_hidden_alias_budget_bypass.py b/tests/integration/authorization/test_hidden_alias_budget_bypass.py index 51b36c145d3..e9e55a6aaf7 100644 --- a/tests/integration/authorization/test_hidden_alias_budget_bypass.py +++ b/tests/integration/authorization/test_hidden_alias_budget_bypass.py @@ -38,6 +38,7 @@ from integration.authorization._hidden_alias_budget import ( async_anthropic_client, async_openai_client, base_url, + budget_refusal_error_type, chat_statuses, clear_provider_script, error_type, @@ -599,7 +600,7 @@ def _assert_refused_like_target(rig: AliasRig, candidate: Gateway, key: str, sha target_marker: Final = f"target-{route}-" + uuid.uuid4().hex via_shadow: Final = send(candidate, shadow, key, shadow_marker) by_name: Final = send(candidate, target, key, target_marker) - assert _refusal(by_name) == (BUDGET_EXCEEDED, "budget_exceeded"), by_name.text + assert _refusal(by_name) == (BUDGET_EXCEEDED, budget_refusal_error_type(route)), by_name.text assert via_shadow.status_code == by_name.status_code, via_shadow.text assert error_type(via_shadow) == error_type(by_name), via_shadow.text observed: Final = upstream_requests(rig.gateway.upstream_url) @@ -621,7 +622,7 @@ def _assert_refused_on_every_route(rig: AliasRig, candidate: Gateway, key: str, marker: Final = f"chain-{route}-" + uuid.uuid4().hex refused: Final = send(candidate, model, key, marker) assert refused.status_code == BUDGET_EXCEEDED, refused.text - assert error_type(refused) == "budget_exceeded", refused.text + assert error_type(refused) == budget_refusal_error_type(route), refused.text assert upstream_hits(upstream_requests(rig.gateway.upstream_url), marker) == 0 @@ -828,9 +829,9 @@ def _deployment_id(rig: AliasRig, name: str) -> str: return identities[0] -def _assert_budget_refusal(status_code: int, body: str) -> None: +def _assert_budget_refusal(status_code: int, body: str, route: str = "chat") -> None: assert status_code == BUDGET_EXCEEDED, body - assert "budget_exceeded" in body, body + assert budget_refusal_error_type(route) in body, body def _assert_no_served_row(key: str, marker: str) -> None: @@ -881,7 +882,7 @@ async def test_exhausted_key_is_refused_on_shadowing_alias_through_streamed_anth extra_headers=spend_marker(marker), ) as stream: await stream.get_final_message() - _assert_budget_refusal(refused.value.status_code, str(refused.value.body)) + _assert_budget_refusal(refused.value.status_code, str(refused.value.body), route="messages") assert upstream_hits(upstream_requests(rig.gateway.upstream_url), marker) == 0 diff --git a/tests/integration/authorization/test_jwt_auto_register_map_existing_key.py b/tests/integration/authorization/test_jwt_auto_register_map_existing_key.py index 62eda977438..c8fbcbb1c97 100644 --- a/tests/integration/authorization/test_jwt_auto_register_map_existing_key.py +++ b/tests/integration/authorization/test_jwt_auto_register_map_existing_key.py @@ -7,13 +7,15 @@ from concurrent.futures import ThreadPoolExecutor from contextlib import contextmanager from hashlib import sha256 from pathlib import Path -from typing import Final +from typing import Final, Literal import httpx import jwt import pytest import yaml from cryptography.hazmat.primitives.asymmetric import rsa +from pydantic import JsonValue +from redis import Redis from tests.integration._support.client import Gateway, eventually, string_value from tests.integration._support.database import read_rows @@ -31,7 +33,15 @@ def _hash(key: str) -> str: return sha256(key.encode()).hexdigest() -def _config(directory: Path, claim_field: str) -> Path: +def _config( + directory: Path, + claim_field: str, + *, + behavior: Literal["auto_register", "link_only", "reject"] = "auto_register", + map_existing_key: bool = True, + user_id_upsert: bool = False, + issuers: tuple[dict[str, JsonValue], ...] = (), +) -> Path: config: Final = yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text()) config["general_settings"] = { **config["general_settings"], @@ -40,8 +50,10 @@ def _config(directory: Path, claim_field: str) -> Path: "user_id_jwt_field": "sub", "user_email_jwt_field": "email", "virtual_key_claim_field": claim_field, - "unregistered_jwt_client_behavior": "auto_register", - "auto_register_map_existing_key": True, + "unregistered_jwt_client_behavior": behavior, + "auto_register_map_existing_key": map_existing_key, + "user_id_upsert": user_id_upsert, + "issuers": list(issuers), }, } path: Final = directory / f"jwt_map_existing_key_{claim_field}.yaml" @@ -107,7 +119,7 @@ def _billed_key(response: httpx.Response) -> str: return string_value(rows[0]["api_key"]) -def test_first_jwt_call_reuses_the_newest_durable_llm_key_and_skips_every_ineligible_newer_key( +def test_first_jwt_call_reuses_the_newest_durable_key_and_skips_every_ineligible_newer_key( gateway: Gateway, tmp_path: Path ) -> None: with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: @@ -118,7 +130,6 @@ def test_first_jwt_call_reuses_the_newest_durable_llm_key_and_skips_every_inelig skipped: Final = { "older_durable": older_durable, "expiring": scenario.key(user_id=user, duration="1h"), - "management_only": scenario.key(user_id=user, allowed_routes=["management_routes"]), "auto_registered_look_alike": scenario.key(user_id=user, metadata={"auto_registered": True}), "other_team": scenario.key(user_id=user, team_id=scenario.team()), "blocked": scenario.key(user_id=user), @@ -140,6 +151,84 @@ def test_first_jwt_call_reuses_the_newest_durable_llm_key_and_skips_every_inelig assert _billed_key(response) == _hash(durable) +@pytest.mark.parametrize( + ("behavior", "map_existing_key"), [("auto_register", True), ("link_only", False), ("link_only", True)] +) +def test_route_restricted_keys_are_linked_without_bypassing_other_key_checks( + gateway: Gateway, + tmp_path: Path, + behavior: Literal["auto_register", "link_only"], + map_existing_key: bool, +) -> None: + with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: + model: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + scenario.key(user_id=user) + restricted: Final = scenario.key(user_id=user, allowed_routes=["/v1/chat/completions"]) + scenario.key(user_id=user, duration="1h") + scenario.key(user_id=user, metadata={"auto_registered": True}) + scenario.key(user_id=user, team_id=scenario.team()) + blocked: Final = scenario.key(user_id=user) + gateway.post("/key/block", {"key": blocked}) + keys_before: Final = _user_key_hashes(user) + token: Final = _token(private_key, user) + + with owned_proxy( + gateway, + tmp_path, + {"JWT_PUBLIC_KEY_URL": jwks_url}, + config=_config( + tmp_path, + "sub", + behavior=behavior, + map_existing_key=map_existing_key, + ), + ) as candidate: + response: Final = _chat(candidate, model, token) + repeated: Final = _chat(candidate, model, token) + restricted_route: Final = candidate.request("GET", "/v1/models", key=token) + + assert response.status_code == 200, response.text + assert repeated.status_code == 200, repeated.text + assert restricted_route.status_code == 403, restricted_route.text + assert _mapped_token("sub", user) == _hash(restricted) + assert _user_key_hashes(user) == keys_before, "a new key was minted instead of linking an existing key" + assert _billed_key(response) == _hash(restricted) + assert _billed_key(repeated) == _hash(restricted) + + +@pytest.mark.parametrize("behavior", ["auto_register", "link_only"]) +def test_management_route_keys_are_linked_by_default_and_keep_their_route_permissions( + gateway: Gateway, tmp_path: Path, behavior: Literal["auto_register", "link_only"] +) -> None: + with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: + model: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + target: Final = f"integration-{uuid.uuid4().hex}" + scenario.key(user_id=user) + management_key: Final = scenario.key(user_id=user, allowed_routes=["/user/new"]) + keys_before: Final = _user_key_hashes(user) + token: Final = _token(private_key, user) + with owned_proxy( + gateway, tmp_path, {"JWT_PUBLIC_KEY_URL": jwks_url}, config=_config(tmp_path, "sub", behavior=behavior) + ) as candidate: + denied: Final = _chat(candidate, model, token) + allowed: Final = candidate.request( + "POST", + "/user/new", + {"user_id": target, "auto_create_key": False, "user_role": "internal_user"}, + key=token, + ) + assert allowed.status_code == 200, allowed.text + scenario.cleanups.callback(scenario.delete_user, target) + repeated: Final = _chat(candidate, model, token) + assert denied.status_code == 403, denied.text + assert repeated.status_code == 403, repeated.text + assert allowed.json()["user_id"] == target + assert _mapped_token("sub", user) == _hash(management_key) + assert _user_key_hashes(user) == keys_before + + def test_user_matched_by_email_instead_of_sub_still_reuses_their_existing_key(gateway: Gateway, tmp_path: Path) -> None: with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: model: Final = scenario.model() @@ -183,8 +272,9 @@ def test_shared_client_claim_never_maps_a_second_user_onto_the_first_users_perso assert read_rows('SELECT request_id FROM "LiteLLM_SpendLogs" WHERE api_key = %s', (_hash(personal),)) == [] -def test_concurrent_first_jwt_calls_of_a_keyless_user_both_succeed_on_one_surviving_mapped_key( - gateway: Gateway, tmp_path: Path +@pytest.mark.parametrize("behavior", ["auto_register", "link_only"]) +def test_concurrent_first_jwt_calls_both_succeed_on_one_surviving_mapped_key( + gateway: Gateway, tmp_path: Path, behavior: Literal["auto_register", "link_only"] ) -> None: writer_url: Final = os.environ.get("INTEGRATION_PROXY_DATABASE_URL") or os.environ["DATABASE_URL"] with ( @@ -194,6 +284,7 @@ def test_concurrent_first_jwt_calls_of_a_keyless_user_both_succeed_on_one_surviv ): model: Final = scenario.model() user: Final = scenario.user(user_role="internal_user") + existing: Final = scenario.key(user_id=user) if behavior == "link_only" else None token: Final = _token(private_key, user) overrides: Final = { "JWT_PUBLIC_KEY_URL": jwks_url, @@ -202,7 +293,12 @@ def test_concurrent_first_jwt_calls_of_a_keyless_user_both_succeed_on_one_surviv } with ( - owned_proxy(gateway, tmp_path, overrides, config=_config(tmp_path, "sub")) as candidate, + owned_proxy( + gateway, + tmp_path, + overrides, + config=_config(tmp_path, "sub", behavior=behavior, map_existing_key=False), + ) as candidate, ThreadPoolExecutor(max_workers=1) as pool, ): held_call: Final = pool.submit(_chat, candidate, model, token) @@ -215,5 +311,242 @@ def test_concurrent_first_jwt_calls_of_a_keyless_user_both_succeed_on_one_surviv assert held.status_code == 200, held.text keys: Final = _user_key_hashes(user) assert len(keys) == 1, keys + if existing is not None: + assert keys == frozenset({_hash(existing)}) assert _mapped_token("sub", user) in keys assert (_billed_key(held), _billed_key(racing)) == (_mapped_token("sub", user),) * 2 + + +@pytest.mark.parametrize("ineligible_keys", [False, True]) +def test_link_only_rejects_without_writes_then_links_a_newly_available_key( + gateway: Gateway, tmp_path: Path, ineligible_keys: bool +) -> None: + with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: + model: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + if ineligible_keys: + scenario.key(user_id=user, duration="1h") + scenario.key(user_id=user, metadata={"auto_registered": True}) + scenario.key(user_id=user, team_id=scenario.team()) + blocked: Final = scenario.key(user_id=user) + gateway.post("/key/block", {"key": blocked}) + keys_before: Final = _user_key_hashes(user) + token: Final = _token(private_key, user) + with owned_proxy( + gateway, + tmp_path, + {"JWT_PUBLIC_KEY_URL": jwks_url}, + config=_config(tmp_path, "sub", behavior="link_only", map_existing_key=False), + ) as candidate: + first: Final = _chat(candidate, model, token) + repeated: Final = _chat(candidate, model, token) + assert first.status_code == 403, first.text + assert repeated.status_code == 403, repeated.text + assert _user_key_hashes(user) == keys_before + assert read_rows('SELECT token FROM "LiteLLM_JWTKeyMapping" WHERE jwt_claim_value=%s', (user,)) == [] + available: Final = scenario.key(user_id=user) + accepted: Final = _chat(candidate, model, token) + assert accepted.status_code == 200, accepted.text + assert _mapped_token("sub", user) == _hash(available) + assert _user_key_hashes(user) == keys_before | {_hash(available)} + assert _billed_key(accepted) == _hash(available) + + +@pytest.mark.parametrize("claim_field", ["client_id", "email"]) +def test_link_only_rejects_shared_or_missing_claims_without_linking_a_personal_key( + gateway: Gateway, tmp_path: Path, claim_field: str +) -> None: + with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: + model: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + key: Final = scenario.key(user_id=user) + shared_claim: Final = f"integration-client-{uuid.uuid4().hex}" + with owned_proxy( + gateway, + tmp_path, + {"JWT_PUBLIC_KEY_URL": jwks_url}, + config=_config(tmp_path, claim_field, behavior="link_only", map_existing_key=False), + ) as candidate: + response: Final = _chat(candidate, model, _token(private_key, user, client_id=shared_claim)) + assert response.status_code == 403, response.text + assert _user_key_hashes(user) == frozenset({_hash(key)}) + assert read_rows('SELECT token FROM "LiteLLM_JWTKeyMapping" WHERE token=%s', (_hash(key),)) == [] + assert read_rows('SELECT token FROM "LiteLLM_JWTKeyMapping" WHERE jwt_claim_value=%s', (shared_claim,)) == [] + + +@pytest.mark.parametrize("restriction", ["models", "allowed_routes"]) +def test_link_only_enforces_key_permissions_on_the_first_and_cached_requests( + gateway: Gateway, tmp_path: Path, restriction: str +) -> None: + with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: + allowed: Final = scenario.model() + denied: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + key: Final = scenario.key( + user_id=user, + **({"models": [allowed]} if restriction == "models" else {"allowed_routes": ["/v1/models"]}), + ) + token: Final = _token(private_key, user) + with owned_proxy( + gateway, + tmp_path, + {"JWT_PUBLIC_KEY_URL": jwks_url}, + config=_config(tmp_path, "sub", behavior="link_only", map_existing_key=False), + ) as candidate: + first: Final = _chat(candidate, denied, token) + repeated: Final = _chat(candidate, denied, token) + control: Final = ( + _chat(candidate, allowed, token) + if restriction == "models" + else candidate.request("GET", "/v1/models", key=token) + ) + assert first.status_code == 403, first.text + assert repeated.status_code == 403, repeated.text + assert control.status_code == 200, control.text + assert _mapped_token("sub", user) == _hash(key) + assert _user_key_hashes(user) == frozenset({_hash(key)}) + + +def test_link_only_does_not_replace_an_existing_mapping_to_a_blocked_key(gateway: Gateway, tmp_path: Path) -> None: + with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: + model: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + blocked: Final = scenario.key(user_id=user) + available: Final = scenario.key(user_id=user) + gateway.post("/jwt/key/mapping/new", {"jwt_claim_name": "sub", "jwt_claim_value": user, "key": blocked}) + gateway.post("/key/block", {"key": blocked}) + token: Final = _token(private_key, user) + with owned_proxy( + gateway, + tmp_path, + {"JWT_PUBLIC_KEY_URL": jwks_url}, + config=_config(tmp_path, "sub", behavior="link_only", map_existing_key=False), + ) as candidate: + first: Final = _chat(candidate, model, token) + repeated: Final = _chat(candidate, model, token) + assert first.status_code == 401, first.text + assert repeated.status_code == 401, repeated.text + assert _mapped_token("sub", user) == _hash(blocked) + assert _user_key_hashes(user) == frozenset({_hash(blocked), _hash(available)}) + + +def test_link_only_exempts_proxy_admins_but_rechecks_the_role_after_a_cached_exemption( + gateway: Gateway, tmp_path: Path +) -> None: + with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: + model: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + admin: Final = _token(private_key, user, scope="litellm_proxy_admin") + ordinary: Final = _token(private_key, user) + with owned_proxy( + gateway, + tmp_path, + {"JWT_PUBLIC_KEY_URL": jwks_url}, + config=_config(tmp_path, "sub", behavior="link_only", map_existing_key=False), + ) as candidate: + first: Final = candidate.request("GET", "/v1/models", key=admin) + repeated: Final = candidate.request("GET", "/v1/models", key=admin) + denied: Final = candidate.request("GET", "/v1/models", key=ordinary) + forbidden_route: Final = _chat(candidate, model, admin) + assert first.status_code == 200, first.text + assert repeated.status_code == 200, repeated.text + assert denied.status_code == 403, denied.text + assert forbidden_route.status_code == 401, forbidden_route.text + assert _user_key_hashes(user) == frozenset() + assert read_rows('SELECT token FROM "LiteLLM_JWTKeyMapping" WHERE jwt_claim_value=%s', (user,)) == [] + + +@pytest.mark.parametrize("user_id_upsert", [False, True]) +def test_link_only_keeps_user_provisioning_independent_of_key_creation( + gateway: Gateway, tmp_path: Path, user_id_upsert: bool +) -> None: + with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: + model: Final = scenario.model() + subject: Final = f"integration-link-only-{uuid.uuid4().hex}" + try: + with owned_proxy( + gateway, + tmp_path, + {"JWT_PUBLIC_KEY_URL": jwks_url}, + config=_config( + tmp_path, "sub", behavior="link_only", map_existing_key=False, user_id_upsert=user_id_upsert + ), + ) as candidate: + response: Final = _chat(candidate, model, _token(private_key, subject)) + assert response.status_code == (403 if user_id_upsert else 401), response.text + users: Final = read_rows('SELECT user_id FROM "LiteLLM_UserTable" WHERE user_id=%s', (subject,)) + assert users == ([{"user_id": subject}] if user_id_upsert else []) + assert _user_key_hashes(subject) == frozenset() + assert read_rows('SELECT token FROM "LiteLLM_JWTKeyMapping" WHERE jwt_claim_value=%s', (subject,)) == [] + finally: + if read_rows('SELECT user_id FROM "LiteLLM_UserTable" WHERE user_id=%s', (subject,)): + scenario.delete_user(subject) + + +@pytest.mark.parametrize("issuer_behavior", ["auto_register", "link_only"]) +def test_issuer_specific_registration_mode_overrides_the_global_mode( + gateway: Gateway, tmp_path: Path, issuer_behavior: Literal["auto_register", "link_only"] +) -> None: + with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: + model: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + issuer: Final = f"https://integration.example.com/{uuid.uuid4().hex}" + token: Final = _token(private_key, user, iss=issuer, aud="integration") + path: Final = _config( + tmp_path, + "sub", + behavior="auto_register" if issuer_behavior == "link_only" else "link_only", + map_existing_key=False, + issuers=( + { + "issuer": issuer, + "jwks_url": jwks_url, + "audience": "integration", + "user_id_jwt_field": "sub", + "virtual_key_claim_field": "sub", + "unregistered_jwt_client_behavior": issuer_behavior, + }, + ), + ) + with owned_proxy(gateway, tmp_path, {"JWT_PUBLIC_KEY_URL": jwks_url}, config=path) as candidate: + response: Final = _chat(candidate, model, token) + assert response.status_code == (403 if issuer_behavior == "link_only" else 200), response.text + if issuer_behavior == "link_only": + assert _user_key_hashes(user) == frozenset() + assert read_rows('SELECT token FROM "LiteLLM_JWTKeyMapping" WHERE jwt_claim_value=%s', (user,)) == [] + else: + assert len(_user_key_hashes(user)) == 1 + assert _mapped_token("sub", user) in _user_key_hashes(user) + assert _billed_key(response) == _mapped_token("sub", user) + + +def test_link_only_links_after_a_cached_rejection_from_the_previous_mode(gateway: Gateway, tmp_path: Path) -> None: + with _issuer() as (private_key, jwks_url), gateway.scenario() as scenario: + model: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + key: Final = scenario.key(user_id=user) + token: Final = _token(private_key, user) + with owned_proxy( + gateway, + tmp_path, + {"JWT_PUBLIC_KEY_URL": jwks_url}, + config=_config(tmp_path, "sub", behavior="reject", map_existing_key=False), + ) as rejecting: + denied: Final = _chat(rejecting, model, token) + assert denied.status_code == 403, denied.text + with Redis(host=os.environ["REDIS_HOST"], port=int(os.environ["REDIS_PORT"])) as cache: + eventually( + lambda: cache.get(f"jwt_key_mapping:sub:{user}"), + lambda value: value is not None and b"__NO_MAPPING__" in value, + ) + with owned_proxy( + gateway, + tmp_path, + {"JWT_PUBLIC_KEY_URL": jwks_url}, + config=_config(tmp_path, "sub", behavior="link_only", map_existing_key=False), + ) as linking: + accepted: Final = _chat(linking, model, token) + assert accepted.status_code == 200, accepted.text + assert _mapped_token("sub", user) == _hash(key) + assert _user_key_hashes(user) == frozenset({_hash(key)}) + assert _billed_key(accepted) == _hash(key) diff --git a/tests/integration/authorization/test_responses_id_ownership.py b/tests/integration/authorization/test_responses_id_ownership.py index 2ab26e75f50..c384ebb9434 100644 --- a/tests/integration/authorization/test_responses_id_ownership.py +++ b/tests/integration/authorization/test_responses_id_ownership.py @@ -3,7 +3,7 @@ from __future__ import annotations import json import os import uuid -from collections.abc import Callable +from collections.abc import Callable, Iterator, Mapping from pathlib import Path from typing import Final, Literal from urllib.parse import urlsplit @@ -16,7 +16,7 @@ from integration._support.process import owned_proxy from integration._support.responses_vendor import same_response from integration._support.wire import Reply, Request, Wire, wire_server from integration._support.worker_readiness import wait_for_worker_readiness -from openai.types.responses import ResponseInputParam +from openai.types.responses import ResponseCompletedEvent, ResponseInputParam from pydantic import BaseModel, ConfigDict, JsonValue, TypeAdapter pytestmark: Final = pytest.mark.shares_worker_state @@ -51,12 +51,6 @@ class _DeleteResponse(BaseModel): deleted: bool -def _deployments_in_group(gateway: Gateway, group: str) -> int: - entries: Final = gateway.get("/model/info")["data"] - assert isinstance(entries, list), entries - return sum(object_value(entry).get("model_name") == group for entry in entries) - - def _wait_for_workers(gateway: Gateway, group: str, deployments: int) -> None: wait_for_worker_readiness(gateway, group, deployments, _PROXY_WORKERS) @@ -138,6 +132,378 @@ def _every_id_route(client: openai.OpenAI, model: str, response_id: str) -> tupl ) +def _comparison_body(response_id: str, nested: bool) -> Mapping[str, object]: + options: Final = {"comparison_response_id": response_id} + if nested: + return { + "prompt_cache_options": {"mode": "explicit", "ttl": "12h"}, + "extra_body": {"prompt_cache_options": options}, + } + return {"prompt_cache_options": options} + + +@pytest.mark.parametrize( + ("prefix", "nested", "stream"), + (("/v1", False, False), ("", True, False), ("/openai/v1", False, True), ("/v1", True, True)), +) +def test_regression_comparison_response_id_owner_repeated_requests_reach_raw_provider_id( + gateway: Gateway, prefix: str, nested: bool, stream: bool +) -> None: + raw_id: Final = f"resp_comparison_{uuid.uuid4().hex}" + + def respond(request: Request) -> Reply: + if request.target == "/v1/models": + return _model_discovery_reply() + assert (request.method, request.target) == ("POST", "/v1/responses") + body: Final = _JSON_OBJECT.validate_json(request.body) + if body["input"] == "create comparison response": + assert body == {"model": _MODEL, "input": "create comparison response"}, request.body + return Reply(body=_response(raw_id)) + assert body == { + "model": _MODEL, + "input": "compare owned response", + "stream": stream, + "prompt_cache_options": {"comparison_response_id": raw_id}, + }, request.body + if stream: + return Reply( + content_type="text/event-stream", + chunks=( + b"data: " + + json.dumps({"type": "response.completed", "response": json.loads(_response(raw_id))}).encode() + + b"\n\n", + b"data: [DONE]\n\n", + ), + ) + return Reply(body=_response(raw_id)) + + with wire_server(respond) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire) + team: Final = scenario.team(models=[model]) + user: Final = scenario.member(team) + with _client(gateway, _key(scenario, team, user, model), prefix) as client: + created: Final = client.responses.create(model=model, input="create comparison response") + assert created.id != raw_id, created.model_dump_json() + assert len(_contract_requests(wire)) == 1 + + def compare_again() -> None: + result: Final = client.responses.create( + model=model, + input="compare owned response", + stream=stream, + extra_body=_comparison_body(created.id, nested), + ) + if isinstance(result, openai.Stream): + events: Final = tuple(result) + assert isinstance(events[-1], ResponseCompletedEvent), events + assert events[-1].response.status == "completed", events + else: + assert result.status == "completed", result.model_dump_json() + + for _ in range(2): + compare_again() + assert len(_contract_requests(wire)) == 2 + + +@pytest.mark.parametrize("nested", (False, True)) +@pytest.mark.parametrize("stranger", ("user", "team")) +@pytest.mark.parametrize("retained", (False, True), ids=("ordinary", "client-internal-field")) +def test_regression_comparison_response_id_other_identity_is_denied_before_dispatch( + gateway: Gateway, nested: bool, stranger: str, retained: bool +) -> None: + raw_id: Final = f"resp_comparison_{uuid.uuid4().hex}" + + def respond(request: Request) -> Reply: + if request.target == "/v1/models": + return _model_discovery_reply() + return Reply(body=_response(raw_id)) + + with wire_server(respond) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire) + team_a: Final = scenario.team(models=[model]) + team_b: Final = scenario.team(models=[model]) + user_a: Final = scenario.member(team_a) + user_b: Final = scenario.member(team_a) + gateway.post("/team/member_add", {"team_id": team_b, "member": {"role": "user", "user_id": user_a}}) + with ( + _client(gateway, _key(scenario, team_a, user_a, model), "/v1") as owner, + _client( + gateway, + _key( + scenario, team_a if stranger == "user" else team_b, user_b if stranger == "user" else user_a, model + ), + "/v1", + ) as other, + ): + created: Final = owner.responses.create(model=model, input="create private comparison") + assert created.id != raw_id + assert len(_contract_requests(wire)) == 1 + _refused( + lambda: other.responses.create( + model=model, + input="compare another identity", + extra_body={ + **_comparison_body(created.id, nested), + **( + {"_litellm_addressed_comparison_response_id": "resp_unmanaged_comparison"} + if retained + else {} + ), + }, + ), + _OTHER_USER_DETAIL if stranger == "user" else _OTHER_TEAM_DETAIL, + ) + assert _contract_requests(wire) == (), "A cross-identity comparison reached the provider" + + +@pytest.mark.parametrize("nested", (False, True)) +@pytest.mark.parametrize("comparison_id", ("resp_unmanaged_comparison", "resp_!!!not-base64", "cmF3X3ZlbmRvcl9pZA==")) +def test_regression_unmanaged_comparison_response_id_is_denied_by_default( + gateway: Gateway, nested: bool, comparison_id: str +) -> None: + def respond(request: Request) -> Reply: + if request.target == "/v1/models": + return _model_discovery_reply() + return Reply(body=_response(f"resp_result_{uuid.uuid4().hex}")) + + with wire_server(respond) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire) + team: Final = scenario.team(models=[model]) + user: Final = scenario.member(team) + with _client(gateway, _key(scenario, team, user, model), "/v1") as client: + _refused( + lambda: client.responses.create( + model=model, input="unmanaged comparison", extra_body=_comparison_body(comparison_id, nested) + ), + _UNMANAGED_DETAIL, + ) + assert _contract_requests(wire) == () + + +def test_comparison_extra_body_owned_id_overrides_foreign_top_level(gateway: Gateway) -> None: + foreign_raw_id: Final = f"resp_ignored_{uuid.uuid4().hex}" + owner_raw_id: Final = f"resp_effective_{uuid.uuid4().hex}" + + def respond(request: Request) -> Reply: + if request.target == "/v1/models": + return _model_discovery_reply() + assert (request.method, request.target) == ("POST", "/v1/responses") + body: Final = _JSON_OBJECT.validate_json(request.body) + if body["input"] in ("seed ignored comparison", "seed effective comparison"): + assert body == {"model": _MODEL, "input": body["input"]}, request.body + return Reply(body=_response(foreign_raw_id if body["input"] == "seed ignored comparison" else owner_raw_id)) + assert body == { + "model": _MODEL, + "input": "compare effective options", + "prompt_cache_options": {"comparison_response_id": owner_raw_id}, + }, request.body + return Reply(body=_response(owner_raw_id)) + + with wire_server(respond) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire) + team: Final = scenario.team(models=[model]) + owner_user: Final = scenario.member(team) + foreign_user: Final = scenario.member(team) + with ( + _client(gateway, _key(scenario, team, owner_user, model), "/v1") as owner, + _client(gateway, _key(scenario, team, foreign_user, model), "/v1") as foreign, + ): + foreign_response: Final = foreign.responses.create(model=model, input="seed ignored comparison") + assert foreign_response.id != foreign_raw_id + owner_response: Final = owner.responses.create(model=model, input="seed effective comparison") + assert owner_response.id != owner_raw_id + assert len(_contract_requests(wire)) == 2 + compared: Final = owner.responses.create( + model=model, + input="compare effective options", + extra_body={ + "prompt_cache_options": { + "comparison_response_id": foreign_response.id, + "mode": "explicit", + "ttl": "12h", + }, + "extra_body": {"prompt_cache_options": {"comparison_response_id": owner_response.id}}, + }, + ) + assert compared.status == "completed", compared.model_dump_json() + assert len(_contract_requests(wire)) == 1 + + +def test_regression_comparison_extra_body_raw_id_overrides_foreign_top_level(gateway: Gateway) -> None: + raw_id: Final = "resp_raw_effective_comparison" + + def respond(request: Request) -> Reply: + if request.target == "/v1/models": + return _model_discovery_reply() + return Reply(body=_response("resp_foreign_seed")) + + with wire_server(respond) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire) + team: Final = scenario.team(models=[model]) + owner_user: Final = scenario.member(team) + foreign_user: Final = scenario.member(team) + with ( + _client(gateway, _key(scenario, team, owner_user, model), "/v1") as owner, + _client(gateway, _key(scenario, team, foreign_user, model), "/v1") as foreign, + ): + foreign_response: Final = foreign.responses.create(model=model, input="seed ignored comparison") + assert foreign_response.id != "resp_foreign_seed" + assert len(_contract_requests(wire)) == 1 + _refused( + lambda: owner.responses.create( + model=model, + input="compare effective options", + extra_body={ + "prompt_cache_options": { + "comparison_response_id": foreign_response.id, + "mode": "explicit", + "ttl": "12h", + }, + "extra_body": {"prompt_cache_options": {"comparison_response_id": raw_id}}, + }, + ), + _UNMANAGED_DETAIL, + ) + assert _contract_requests(wire) == () + + +@pytest.fixture(scope="module") +def allowed_comparison_gateway( + session_gateway: Gateway, tmp_path_factory: pytest.TempPathFactory +) -> Iterator[tuple[Gateway, Wire]]: + directory: Final = tmp_path_factory.mktemp("allowed_comparison") + config: Final = directory / "config.yaml" + config.write_text("general_settings:\n allow_unmanaged_response_ids: true\n") + with wire_server(lambda request: Reply(body=_response("resp_decoy"))) as decoy: + with owned_proxy( + session_gateway, + directory, + { + "INTEGRATION_PROXY_WORKERS": "1", + "OPENAI_BASE_URL": f"{decoy.url}/v1", + "OPENAI_API_KEY": "synthetic-env-fallback-key", + }, + config=config, + ) as allowed: + yield allowed, decoy + + +@pytest.mark.parametrize("nested", (False, True)) +@pytest.mark.parametrize("comparison_id", ("resp_unmanaged_comparison", "resp_!!!not-base64", "cmF3X3ZlbmRvcl9pZA==")) +def test_guard_opt_in_forwards_unmanaged_comparison_id( + allowed_comparison_gateway: tuple[Gateway, Wire], nested: bool, comparison_id: str +) -> None: + allowed, decoy = allowed_comparison_gateway + result_id: Final = f"resp_result_{uuid.uuid4().hex}" + + def respond(request: Request) -> Reply: + if request.target == "/v1/models": + return _model_discovery_reply() + return Reply(body=_response(result_id)) + + with wire_server(respond) as wire, allowed.scenario() as scenario: + model: Final = _deployment(scenario, wire) + team: Final = scenario.team(models=[model]) + user: Final = scenario.member(team) + with _client(allowed, _key(scenario, team, user, model), "/v1") as client: + compared: Final = client.responses.create( + model=model, input="unmanaged comparison", extra_body=_comparison_body(comparison_id, nested) + ) + assert compared.model_dump(mode="json", exclude_none=True) == { + "id": compared.id, + "object": "response", + "created_at": 1.0, + "status": "completed", + "model": model, + "output": [], + "parallel_tool_calls": False, + "tool_choice": "auto", + "tools": [], + }, compared.model_dump_json() + assert compared.id != result_id + requests: Final = _contract_requests(wire) + assert len(requests) == 1 + assert (requests[0].method, requests[0].target) == ("POST", "/v1/responses") + assert _JSON_OBJECT.validate_json(requests[0].body) == { + "model": _MODEL, + "input": "unmanaged comparison", + "prompt_cache_options": {"comparison_response_id": comparison_id}, + }, requests[0].body + assert decoy.drain() == () + + +@pytest.mark.parametrize("stranger", ("user", "team")) +def test_regression_echoed_raw_comparison_id_is_denied_to_other_identity(gateway: Gateway, stranger: str) -> None: + raw_id: Final = f"resp_echo_{uuid.uuid4().hex}" + + def respond(request: Request) -> Reply: + if request.target == "/v1/models": + return _model_discovery_reply() + body: Final = _JSON_OBJECT.validate_json(request.body) + if body["input"] == "create response": + assert body == {"model": _MODEL, "input": "create response"}, request.body + return Reply(body=_response(raw_id)) + assert body == { + "model": _MODEL, + "input": "compare owned response", + "prompt_cache_options": {"comparison_response_id": raw_id}, + }, request.body + return Reply( + body=json.dumps( + {**json.loads(_response(raw_id)), "prompt_cache_options": {"comparison_response_id": raw_id}} + ).encode() + ) + + with wire_server(respond) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire) + team_a: Final = scenario.team(models=[model]) + team_b: Final = scenario.team(models=[model]) + user_a: Final = scenario.member(team_a) + user_b: Final = scenario.member(team_a) + gateway.post("/team/member_add", {"team_id": team_b, "member": {"role": "user", "user_id": user_a}}) + with ( + _client(gateway, _key(scenario, team_a, user_a, model), "/v1") as owner, + _client( + gateway, + _key( + scenario, team_a if stranger == "user" else team_b, user_b if stranger == "user" else user_a, model + ), + "/v1", + ) as other, + ): + created: Final = owner.responses.create(model=model, input="create response") + assert created.id != raw_id + assert len(_contract_requests(wire)) == 1 + echoed: Final = owner.responses.create( + model=model, input="compare owned response", extra_body=_comparison_body(created.id, False) + ) + echo_body: Final = _JSON_OBJECT.validate_json(echoed.model_dump_json(exclude_none=True)) + assert echo_body == { + "id": echoed.id, + "object": "response", + "created_at": 1.0, + "status": "completed", + "model": model, + "output": [], + "parallel_tool_calls": False, + "tool_choice": "auto", + "tools": [], + "prompt_cache_options": {"comparison_response_id": raw_id}, + }, echo_body + options: Final = object_value(echo_body["prompt_cache_options"]) + leaked_id: Final = options["comparison_response_id"] + assert leaked_id == raw_id + assert isinstance(leaked_id, str) + assert len(_contract_requests(wire)) == 1 + _refused( + lambda: other.responses.create( + model=model, input="compare owned response", extra_body=_comparison_body(leaked_id, False) + ), + _UNMANAGED_DETAIL, + ) + assert _contract_requests(wire) == () + + @pytest.mark.parametrize("prefix", _ALIASES) def test_response_ids_are_scoped_to_the_issuing_user_and_team(gateway: Gateway, prefix: str) -> None: raw_id: Final = f"resp_owned_{uuid.uuid4().hex}" diff --git a/tests/integration/authorization/test_unknown_key_generic_401.py b/tests/integration/authorization/test_unknown_key_generic_401.py index 025f11d3973..a9ed4b66f27 100644 --- a/tests/integration/authorization/test_unknown_key_generic_401.py +++ b/tests/integration/authorization/test_unknown_key_generic_401.py @@ -50,7 +50,27 @@ class _ErrorResponse(BaseModel): error: _ProxyError +class _AnthropicErrorDetail(BaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + type: str + message: str + litellm_error_type: str + + +class _AnthropicErrorResponse(BaseModel): + model_config = ConfigDict(frozen=True) + + type: str + error: _AnthropicErrorDetail + + GENERIC_ERROR: Final = _ProxyError(message=GENERIC_MESSAGE, type="token_not_found_in_db", param="key", code="401") +MESSAGES_PATH: Final = "/v1/messages" +ANTHROPIC_ENVELOPE_PATHS: Final = frozenset({MESSAGES_PATH, "/anthropic/v1/messages"}) +ANTHROPIC_GENERIC_ERROR: Final = _AnthropicErrorDetail( + type="authentication_error", message=GENERIC_MESSAGE, litellm_error_type=GENERIC_ERROR.type +) @dataclass(frozen=True, slots=True) @@ -119,6 +139,22 @@ def _assert_generic_refusal(response: httpx.Response, *secrets: str) -> None: assert secret not in response.text, response.text +def _assert_messages_refusal(response: httpx.Response, *secrets: str) -> None: + assert response.status_code == 401, response.text + body: Final = _AnthropicErrorResponse.model_validate_json(response.content) + assert body.type == "error", response.text + assert body.error == ANTHROPIC_GENERIC_ERROR, response.text + for secret in secrets: + assert secret not in response.text, response.text + + +def _assert_refusal(path: str, response: httpx.Response, *secrets: str) -> None: + if path in ANTHROPIC_ENVELOPE_PATHS: + _assert_messages_refusal(response, *secrets) + else: + _assert_generic_refusal(response, *secrets) + + def _side(gateway: Gateway, peer: Gateway, side: Side) -> Gateway: return gateway if side == "gateway" else peer @@ -129,7 +165,10 @@ def test_an_unknown_key_gets_the_generic_401_without_reaching_the_provider( gateway: Gateway, peer: Gateway, provider: SharedProvider, route: str, side: Side ) -> None: key: Final = _unknown_key() - _assert_generic_refusal(_send(_side(gateway, peer, side), ROUTES[route], key), key, key[-4:], _digest(key)) + request_route: Final = ROUTES[route] + _assert_refusal( + request_route.path, _send(_side(gateway, peer, side), request_route, key), key, key[-4:], _digest(key) + ) assert provider.received() == () @@ -183,8 +222,9 @@ def test_two_different_unknown_keys_in_both_headers_get_the_generic_401_naming_n bearer: Final = _unknown_key() api_key: Final = _unknown_key() headers: Final = {**_headers("authorization", bearer), **_headers("x-api-key", api_key)} - for path, body in (("/v1/chat/completions", CHAT), ("/v1/messages", MESSAGES)): - _assert_generic_refusal( + for path, body in (("/v1/chat/completions", CHAT), (MESSAGES_PATH, MESSAGES)): + _assert_refusal( + path, gateway.client.post(path, json=dict(body), headers=headers), bearer, api_key, @@ -359,16 +399,13 @@ async def _send_async(client: httpx.AsyncClient, route: _Route, key: str) -> htt ) -async def _burst(owned: OwnedProxy, keys: tuple[str, ...]) -> tuple[httpx.Response, ...]: +async def _burst(owned: OwnedProxy, keys: tuple[str, ...]) -> tuple[tuple[_Route, httpx.Response], ...]: + routes: Final = tuple(ROUTES[BURST_ROUTES[index % len(BURST_ROUTES)]] for index in range(len(keys))) async with httpx.AsyncClient(base_url=str(owned.gateway.client.base_url), timeout=60, trust_env=False) as client: - return tuple( - await asyncio.gather( - *( - _send_async(client, ROUTES[BURST_ROUTES[index % len(BURST_ROUTES)]], key) - for index, key in enumerate(keys) - ) - ) + responses: Final = await asyncio.gather( + *(_send_async(client, route, key) for route, key in zip(routes, keys, strict=True)) ) + return tuple(zip(routes, responses, strict=True)) def _log_after(owned: OwnedProxy, offset: int) -> str: @@ -397,7 +434,7 @@ async def test_a_burst_across_a_worker_kill_answers_every_unknown_key_with_the_g lambda text: all(_console_line(key) in text for key in keys), 30, ) - for response, key in zip((*during, *after), keys, strict=True): - _assert_generic_refusal(response, key, _digest(key)) + for (route, response), key in zip((*during, *after), keys, strict=True): + _assert_refusal(route.path, response, key, _digest(key)) assert [window.count(_console_line(key)) for key in keys] == [1] * len(keys) assert [key for key in keys if key in window] == [] diff --git a/tests/integration/caching/test_response_cache_empty_output.py b/tests/integration/caching/test_response_cache_empty_output.py index ce5a4d64ca7..7a20e712d4e 100644 --- a/tests/integration/caching/test_response_cache_empty_output.py +++ b/tests/integration/caching/test_response_cache_empty_output.py @@ -23,7 +23,7 @@ from typing import Final, TypeAlias, TypeVar import httpx import pytest from anthropic import Anthropic, AsyncAnthropic -from openai import AsyncOpenAI, OpenAI +from openai import AsyncOpenAI, InternalServerError, OpenAI from pydantic import JsonValue from tests.integration._support.client import JSON_OBJECT, Gateway, eventually, object_value, string_value @@ -420,14 +420,25 @@ def _streamed_chat(gateway: Gateway, model: str, text: str) -> _Answer: return ids, streamed, tuple(chunk.object for chunk in chunks) -def test_streamed_chat_without_choices_is_never_assembled_or_cached(gateway: Gateway) -> None: +def test_streamed_chat_without_choices_fails_and_is_never_cached(gateway: Gateway) -> None: upstream: Final = Upstream(gateway.upstream_url) + store: Final = redis_store() text: Final = prompt() with gateway.scenario() as scenario: handle: Final = scripted(scenario, CHAT_STREAM_WITHOUT_CHOICES) model: Final = scenario.model(api_base=handle.api_base()) - empty: Final = _never_replayed(partial(_streamed_chat, gateway, model, text), upstream, handle.scenario_id) - assert all(answer.text == "" for answer in empty), empty + stream: Final = partial(_streamed_chat, gateway, model, text) + for attempt in range(1, EMPTY_STREAMS + 1): + with pytest.raises(InternalServerError, match="Stream ended before a finish_reason was received"): + stream() + _assert_prompt_reached_upstream(upstream, handle.scenario_id, text, attempt) + rescript(handle, CHAT_STREAM) + real_ids, real_text, _ = stream() + assert real_text == "streamed response" and len(real_ids) == 1, (real_ids, real_text) + _assert_prompt_reached_upstream(upstream, handle.scenario_id, text, EMPTY_STREAMS + 1) + await_entry(store, next(iter(real_ids))) + replay: Final = _replayed(stream, upstream, handle.scenario_id, real_ids) + assert replay.text == real_text, replay def _streamed_text(gateway: Gateway, model: str, text: str) -> _Answer: diff --git a/tests/integration/compatibility/test_a2a_wire_versions.py b/tests/integration/compatibility/test_a2a_wire_versions.py index 4471322d1e9..b3ca0c99392 100644 --- a/tests/integration/compatibility/test_a2a_wire_versions.py +++ b/tests/integration/compatibility/test_a2a_wire_versions.py @@ -1023,9 +1023,18 @@ def test_a2a_task_methods_pass_through_verbatim_and_push_callbacks_are_validated {"taskId": "t1", "url": callback}, ): rejected = call("tasks/pushNotificationConfig/set", params) - assert (rejected.status_code, rejected.json()) == (400, {"detail": detail}), ( - f"{params}: {rejected.text}" - ) + assert (rejected.status_code, rejected.json()) == ( + 400, + { + "jsonrpc": "2.0", + "id": marker + "tasks/pushNotificationConfig/set", + "error": { + "code": -32000, + "message": detail, + "data": {"type": "invalid_request_error", "param": None, "code": "400"}, + }, + }, + ), f"{params}: {rejected.text}" assert tuple(item for item in wire.drain() if item.method == "POST") == () public: Final = {"taskId": "t1", "pushNotificationConfig": {"url": "https://1.1.1.1/callback"}} @@ -1118,7 +1127,15 @@ def test_a2a_v1_task_methods_and_extended_card_lower_to_0_3_upstream_and_answer_ rejected = call("CreateTaskPushNotificationConfig", params) assert (rejected.status_code, rejected.json()) == ( 400, - {"detail": "Push notification URL must use HTTPS"}, + { + "jsonrpc": "2.0", + "id": marker + "CreateTaskPushNotificationConfig", + "error": { + "code": -32000, + "message": "Push notification URL must use HTTPS", + "data": {"type": "invalid_request_error", "param": None, "code": "400"}, + }, + }, ), f"{params}: {rejected.text}" assert forwarded() == () diff --git a/tests/integration/compatibility/test_audio_transcriptions_wire.py b/tests/integration/compatibility/test_audio_transcriptions_wire.py index 3deeaebaf7d..faebfda715b 100644 --- a/tests/integration/compatibility/test_audio_transcriptions_wire.py +++ b/tests/integration/compatibility/test_audio_transcriptions_wire.py @@ -345,10 +345,6 @@ def test_audio_transcription_forwards_nested_and_repeated_bracket_fields_verbati def test_audio_transcription_stream_returns_server_sent_events(gateway: Gateway) -> None: - pytest.skip( - "BUG: stream=true transcriptions reach the upstream but its SSE body comes back as application/json " - '{"text": "data: ..."}, so OpenAI SDK stream=True callers get no transcript events' - ) wav: Final = _WAV_BYTES + uuid.uuid4().bytes def respond(request: Request) -> Reply: diff --git a/tests/integration/compatibility/test_codex_model_catalog.py b/tests/integration/compatibility/test_codex_model_catalog.py index a3ba032e612..fbf05b0f526 100644 --- a/tests/integration/compatibility/test_codex_model_catalog.py +++ b/tests/integration/compatibility/test_codex_model_catalog.py @@ -351,6 +351,41 @@ def test_stock_model_keeps_codex_entry(gateway: Gateway) -> None: assert catalog[name] == expected, catalog[name] +def test_stock_model_alias_takes_configured_max_input_tokens(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + stock: Final = _bundled_stock()["gpt-6-sol"] + stock_window: Final = stock["context_window"] + ceiling: Final = stock["max_context_window"] + assert isinstance(stock_window, int) and isinstance(ceiling, int) and stock_window < ceiling, stock + raised: Final = _model_name("codex-raised-window") + lowered: Final = _model_name("codex-lowered-window") + half_set: Final = _model_name("codex-half-set-window") + half_lowered: Final = _model_name("codex-half-lowered-window") + unset: Final = _model_name("codex-unset-window") + names: Final = (raised, lowered, half_set, half_lowered, unset) + _new_model(scenario, raised, model="openai/gpt-6-sol", model_info={"max_input_tokens": ceiling + 50000}) + _new_model(scenario, lowered, model="openai/gpt-6-sol", model_info={"max_input_tokens": stock_window // 2}) + _new_model(scenario, half_set, model="openai/gpt-6-sol", model_info={"max_input_tokens": ceiling}) + _new_model(scenario, half_set, model="openai/gpt-6-sol") + _new_model(scenario, half_lowered, model="openai/gpt-6-sol", model_info={"max_input_tokens": stock_window // 3}) + _new_model(scenario, half_lowered, model="openai/gpt-6-sol") + _new_model(scenario, unset, model="openai/gpt-6-sol") + expected: Final = { + raised: ceiling, + lowered: stock_window // 2, + half_set: stock_window, + half_lowered: stock_window // 3, + unset: stock_window, + } + windows: Final = _settled( + lambda: { + slug: entry["context_window"] for slug, entry in _by_slug(_catalog(gateway)).items() if slug in names + }, + lambda value: value == expected, + ) + assert windows == expected, windows + + def test_stock_model_configured_tiers_override(gateway: Gateway) -> None: with gateway.scenario() as scenario: stock: Final = _bundled_stock()["gpt-6-sol"] diff --git a/tests/integration/compatibility/test_openai_sdk_client_paths.py b/tests/integration/compatibility/test_openai_sdk_client_paths.py index f8d7449038a..d6b6d1d460d 100644 --- a/tests/integration/compatibility/test_openai_sdk_client_paths.py +++ b/tests/integration/compatibility/test_openai_sdk_client_paths.py @@ -630,19 +630,6 @@ def _spend_row(identity: str) -> Mapping[str, JsonValue]: return rows[0] -def _spend_row_keyed_by_any(identities: frozenset[str]) -> Mapping[str, JsonValue]: - keys: Final = tuple(sorted(identities)) - placeholders: Final = ", ".join("%s" for _ in keys) - rows: Final = eventually( - lambda: read_rows( - f'SELECT request_id, call_type, model FROM "LiteLLM_SpendLogs" WHERE request_id IN ({placeholders})', keys - ), - lambda rows: len(rows) == 1, - seconds=70, - ) - return rows[0] - - def _spend_request_ids(identities: tuple[str, str, str]) -> frozenset[str]: rows: Final = eventually( lambda: read_rows('SELECT request_id FROM "LiteLLM_SpendLogs" WHERE request_id IN (%s, %s, %s)', identities), @@ -815,7 +802,7 @@ def test_r07_responses_stream_through_the_async_openai_sdk(gateway: Gateway) -> served: Final = _served(wire) assert _routes(served) == (("POST", "/v1/responses"),), served assert _body(served[0])["stream"] is True, served[0].body - assert _spend_row_keyed_by_any(response_identities(last.response.id))["model"] == DEPLOYMENT_MODEL + assert _spend_row(last.response.id)["model"] == DEPLOYMENT_MODEL def test_r08_completions_non_stream_through_the_sync_openai_sdk(gateway: Gateway) -> None: diff --git a/tests/integration/configuration/test_effective_settings.py b/tests/integration/configuration/test_effective_settings.py index 07477f1f048..1b0086c619a 100644 --- a/tests/integration/configuration/test_effective_settings.py +++ b/tests/integration/configuration/test_effective_settings.py @@ -20,7 +20,7 @@ from pydantic import BaseModel, JsonValue, TypeAdapter from tests.integration._support.client import Gateway, eventually, object_value, string_value from tests.integration._support.database import read_rows, scratch_database -from tests.integration._support.process import owned_proxy +from tests.integration._support.process import owned_proxy, owned_proxy_process from tests.integration._support.wire import Reply, Request, Wire, wire_server pytestmark: Final = pytest.mark.shares_worker_state @@ -1701,3 +1701,57 @@ def test_db_environment_variables_saved_from_a_session_outside_the_tables_schema assert isinstance(first, int) and isinstance(second, int) assert 0 < first < second + + +def test_a_stored_general_setting_no_settings_api_manages_stays_off_and_the_rest_of_the_row_applies( + gateway: Gateway, tmp_path: Path, monkeypatch: pytest.MonkeyPatch +) -> None: + alias: Final = "stale-database-setting-" + uuid.uuid4().hex + with scratch_database() as database_url, wire_server(lambda _request: _completion_reply("pong")) as provider: + monkeypatch.setenv("DATABASE_URL", database_url) + _push_schema() + with psycopg.connect(database_url, autocommit=True) as writer: + writer.execute( + 'INSERT INTO "LiteLLM_Config" (param_name, param_value) VALUES (%s, %s)', + ("general_settings", Jsonb({"enforce_user_param": True, "store_prompts_in_spend_logs": True})), + ) + config: Final = tmp_path / "stale-database-setting.yaml" + config.write_text( + json.dumps( + { + "model_list": [ + { + "model_name": alias, + "litellm_params": { + "model": "openai/gpt-4o-mini", + "api_base": provider.url + "/v1", + "api_key": "integration-provider-key", + }, + } + ], + "general_settings": {"master_key": gateway.key, "store_model_in_db": True}, + } + ) + ) + with owned_proxy_process( + gateway, + tmp_path / "stale-database-setting", + {"DATABASE_URL": database_url, "DISABLE_SCHEMA_UPDATE": "true"}, + config=config, + database_setup=(), + ) as owned: + answer: Final = owned.gateway.request( + "POST", "/v1/chat/completions", {"model": alias, "messages": [{"role": "user", "content": "ping"}]} + ) + listed: Final = owned.gateway.request("GET", "/config/list", params={"config_type": "general_settings"}) + log: Final = owned.log.read_text() + + assert answer.status_code == 200, answer.text + assert listed.status_code == 200, listed.text + stored_prompts: Final = next( + entry + for entry in TypeAdapter(list[dict[str, JsonValue]]).validate_json(listed.content) + if entry["field_name"] == "store_prompts_in_spend_logs" + ) + assert (stored_prompts["field_value"], stored_prompts["source"]) == (True, "db") + assert "general_settings.enforce_user_param is stored in the database, but the proxy does not apply" in log diff --git a/tests/integration/configuration/test_fips_mode_boot.py b/tests/integration/configuration/test_fips_mode_boot.py new file mode 100644 index 00000000000..18fb692da6e --- /dev/null +++ b/tests/integration/configuration/test_fips_mode_boot.py @@ -0,0 +1,39 @@ +import _hashlib +import json +from pathlib import Path +from typing import Final + +import pytest + +from tests.integration._support.client import Gateway +from tests.integration._support.process import refused_boot_log + + +def _config(directory: Path, upstream_url: str, fips_mode: object) -> Path: + config: Final = directory / "fips_boot.yaml" + config.write_text( + json.dumps( + { + "model_list": [ + { + "model_name": "fips-model", + "litellm_params": {"model": "openai/fips-model", "api_base": upstream_url, "api_key": "sk-x"}, + } + ], + "general_settings": {"fips_mode": fips_mode}, + } + ) + ) + return config + + +def test_fips_mode_refuses_to_start_when_openssl_does_not_enforce_fips(gateway: Gateway, tmp_path: Path) -> None: + if _hashlib.get_fips_mode() == 1: + pytest.skip("this runner's OpenSSL is in FIPS mode") + log: Final = refused_boot_log(gateway, tmp_path, {}, config=_config(tmp_path, gateway.upstream_url, True)) + assert "general_settings.fips_mode is on but OpenSSL does not enforce FIPS" in log, log + + +def test_fips_mode_refuses_to_start_on_a_value_that_is_not_a_boolean(gateway: Gateway, tmp_path: Path) -> None: + log: Final = refused_boot_log(gateway, tmp_path, {}, config=_config(tmp_path, gateway.upstream_url, "enforced")) + assert "general_settings.fips_mode='enforced' is not a boolean" in log, log diff --git a/tests/integration/cost_calculation/cases/azure.py b/tests/integration/cost_calculation/cases/azure.py index d9f17c12bda..6495199b8bb 100644 --- a/tests/integration/cost_calculation/cases/azure.py +++ b/tests/integration/cost_calculation/cases/azure.py @@ -1588,6 +1588,7 @@ AZURE_PINNED_GPT_5_4_MINI_STREAM: Final = CostTrackingTestCase( content_type="text/event-stream", frames=( 'data: {"id":"chatcmpl-$REQUEST_ID","object":"chat.completion.chunk","created":1,"model":"$MODEL","choices":[{"index":0,"delta":{"role":"assistant","content":"ok"},"finish_reason":null}]}\n\n', + 'data: {"id":"chatcmpl-$REQUEST_ID","object":"chat.completion.chunk","created":1,"model":"$MODEL","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}\n\n', 'data: {"id":"chatcmpl-$REQUEST_ID","object":"chat.completion.chunk","created":1,"model":"$MODEL","choices":[],"usage":{"prompt_tokens":1840,"completion_tokens":412,"total_tokens":2252}}\n\n', "data: [DONE]\n\n", ), diff --git a/tests/integration/cost_calculation/cases/openai.py b/tests/integration/cost_calculation/cases/openai.py index bc7fb3486be..270bb6e105d 100644 --- a/tests/integration/cost_calculation/cases/openai.py +++ b/tests/integration/cost_calculation/cases/openai.py @@ -7952,6 +7952,7 @@ GPT_5_6_STREAM_USAGE_IN_EMPTY_CHOICES_CHUNK: Final = CostTrackingTestCase( frames=( 'data: {"id":"chatcmpl-$REQUEST_ID","object":"chat.completion.chunk","created":1789788263,"model":"gpt-5.6","choices":[{"index":0,"delta":{"role":"assistant"},"finish_reason":null}],"usage":null}', 'data: {"id":"chatcmpl-$REQUEST_ID","object":"chat.completion.chunk","created":1789788263,"model":"gpt-5.6","choices":[{"index":0,"delta":{"content":"scripted answer"},"finish_reason":null}],"usage":null}', + 'data: {"id":"chatcmpl-$REQUEST_ID","object":"chat.completion.chunk","created":1789788263,"model":"gpt-5.6","choices":[{"index":0,"delta":{},"finish_reason":"stop"}],"usage":null}', 'data: {"id":"chatcmpl-$REQUEST_ID","object":"chat.completion.chunk","created":1789788263,"model":"gpt-5.6","choices":[],"usage":{"prompt_tokens":1840,"completion_tokens":412,"total_tokens":2252}}', "data: [DONE]", ), diff --git a/tests/integration/database/migrations/test_drop_accounting_event_tables.py b/tests/integration/database/migrations/test_drop_accounting_event_tables.py new file mode 100644 index 00000000000..583223a573b --- /dev/null +++ b/tests/integration/database/migrations/test_drop_accounting_event_tables.py @@ -0,0 +1,64 @@ +import os +from pathlib import Path +from typing import Final + +import psycopg +import pytest + +_MIGRATIONS: Final = Path(__file__).parents[4] / "litellm-proxy-extras/litellm_proxy_extras/migrations" +_OLD_LEDGER: Final = _MIGRATIONS / "20261027000000_add_accounting_ledger_tables/migration.sql" +_SPEND_LOG_DELIVERY: Final = _MIGRATIONS / "20261103010000_spendlogs_accounting_delivery/migration.sql" +_DROP: Final = _MIGRATIONS / "20261104010000_drop_accounting_event_tables/migration.sql" +_DROPPED: Final = ( + "AccountingDeliveryTarget", + "AccountingEventKind", + "LiteLLM_AccountingDelivery", + "LiteLLM_AccountingEvent", +) + + +def _apply(connection: psycopg.Connection[tuple[object, ...]], migration: Path) -> None: + with connection.transaction(): + connection.execute(migration.read_bytes()) + + +def _present(connection: psycopg.Connection[tuple[object, ...]], names: tuple[str, ...]) -> tuple[object, ...]: + return tuple( + row[0] + for row in connection.execute( + "SELECT relname FROM pg_class WHERE relname = ANY(%s) " + "UNION SELECT typname FROM pg_type WHERE typname = ANY(%s) ORDER BY 1", + (list(names), list(names)), + ).fetchall() + ) + + +@pytest.mark.parametrize("old_states", [(), ("applied", "pending", "parked")], ids=["empty", "with_rows"]) +def test_drop_removes_the_old_ledger_and_keeps_spend_log_deliveries(old_states: tuple[str, ...]) -> None: + with psycopg.connect(os.environ["DATABASE_URL"], autocommit=True) as connection: + _apply(connection, _OLD_LEDGER) + connection.execute('CREATE TABLE "LiteLLM_SpendLogs" (request_id text PRIMARY KEY)') + _apply(connection, _SPEND_LOG_DELIVERY) + for index, state in enumerate(old_states): + connection.execute( + 'INSERT INTO "LiteLLM_AccountingEvent" (event_id, kind, schema_version, payload_hash, occurred_at, ' + "payload) VALUES (%s, 'cost', 1, 'hash', now(), '{}')", + (f"event-{index}",), + ) + connection.execute( + 'INSERT INTO "LiteLLM_AccountingDelivery" (event_id, target, version, state) ' + "VALUES (%s, 'LiteLLM_UserTable', 1, %s)", + (f"event-{index}", state), + ) + connection.execute( + 'INSERT INTO "LiteLLM_SpendLogDelivery" (request_id, state, accounting_payload, is_batch) ' + "VALUES ('request', 'pending', '{}', false)" + ) + + _apply(connection, _DROP) + _apply(connection, _DROP) + + assert _present(connection, _DROPPED) == () + assert connection.execute('SELECT request_id, state::text FROM "LiteLLM_SpendLogDelivery"').fetchall() == [ + ("request", "pending") + ] diff --git a/tests/integration/database/test_accounting_ledger.py b/tests/integration/database/test_accounting_ledger.py deleted file mode 100644 index 15cd5413149..00000000000 --- a/tests/integration/database/test_accounting_ledger.py +++ /dev/null @@ -1,610 +0,0 @@ -from __future__ import annotations - -import asyncio -import json -import os -import subprocess -import sys -from collections.abc import AsyncGenerator, AsyncIterator, Iterator, Mapping, Sequence -from contextlib import asynccontextmanager -from datetime import datetime, timezone -from decimal import Decimal -from itertools import chain -from pathlib import Path -from typing import TYPE_CHECKING, Final, TypeAlias - -import psycopg -import pytest -import pytest_asyncio -from psycopg import sql -from pydantic import JsonValue - -from litellm.accounting import ( - CostEvent, - DeliveryState, - DeliveryTarget, - EventKind, - InboundUsageEvent, - Metric, - MetricName, - OutboundUsageEvent, - Outcome, - PricingSnapshot, -) -from litellm.proxy.db import accounting_ledger -from litellm.proxy.db.accounting_ledger import AccountingConflictError, AccountingEvent, AccountingLedger, UsageWrite -from litellm.types.utils import CallTypes -from tests.integration._support.database import scratch_database -from tests.integration._support.prisma_clients import connected_proxy_prisma - -if TYPE_CHECKING: - from prisma import Prisma - - from litellm.proxy.utils import PrismaClient - -_Writer: TypeAlias = tuple["PrismaClient", AccountingLedger] - -_SCHEMA: Final = Path(__file__).resolve().parents[3] / "litellm-proxy-extras/litellm_proxy_extras/schema.prisma" -_EVENT_INSERT: Final = ( - 'INSERT INTO "LiteLLM_AccountingEvent" ' - "(event_id, kind, schema_version, payload_hash, occurred_at, payload) " - "VALUES ('event', %s, %s, 'hash', '2026-01-01', '{}') RETURNING kind::text, schema_version" -) -_DELIVERY_INSERT: Final = ( - 'INSERT INTO "LiteLLM_AccountingDelivery" (event_id, target, version, state, attempts) ' - "VALUES ('event', %s, %s, %s, %s) RETURNING target::text, version, state::text, attempts" -) - - -@pytest.fixture(scope="module") -def ledger_database() -> Iterator[str]: - with scratch_database("accounting") as database_url: - result: Final = subprocess.run( - [sys.executable, "-I", "-m", "prisma", "migrate", "deploy", "--schema", str(_SCHEMA)], - env={**os.environ, "DATABASE_URL": database_url}, - capture_output=True, - text=True, - timeout=300, - ) - assert result.returncode == 0, result.stdout + result.stderr - yield database_url - - -@pytest.fixture -def ledger(ledger_database: str) -> Iterator[psycopg.Connection[tuple[object, ...]]]: - with psycopg.connect(ledger_database) as connection: - try: - yield connection - finally: - connection.rollback() - - -@pytest.mark.parametrize("kind", tuple(EventKind)) -def test_ledger_accepts_every_public_event_kind( - ledger: psycopg.Connection[tuple[object, ...]], kind: EventKind -) -> None: - row: Final = ledger.execute(_EVENT_INSERT, (kind.value, 1)).fetchone() - assert row == (kind.value, 1) - - -@pytest.mark.parametrize("target", tuple(DeliveryTarget)) -@pytest.mark.parametrize("state", tuple(DeliveryState)) -def test_delivery_accepts_every_public_target_and_state( - ledger: psycopg.Connection[tuple[object, ...]], target: DeliveryTarget, state: DeliveryState -) -> None: - row: Final = ledger.execute(_DELIVERY_INSERT, (target.value, 1, state.value, 0)).fetchone() - assert row == (target.value, 1, state.value, 0) - - -@pytest.mark.parametrize( - ("enum_name", "values"), - [ - ("AccountingEventKind", tuple(value.value for value in EventKind)), - ("AccountingDeliveryState", tuple(value.value for value in DeliveryState)), - ("AccountingDeliveryTarget", tuple(value.value for value in DeliveryTarget)), - ], -) -def test_migrated_enums_match_the_public_contract( - ledger: psycopg.Connection[tuple[object, ...]], enum_name: str, values: tuple[str, ...] -) -> None: - rows: Final = ledger.execute( - "SELECT e.enumlabel FROM pg_enum e JOIN pg_type t ON t.oid = e.enumtypid WHERE t.typname = %s", - (enum_name,), - ).fetchall() - assert frozenset(row[0] for row in rows) == frozenset(values) - - -@pytest.mark.parametrize("version", [0, -1]) -def test_event_rejects_nonpositive_schema_versions( - ledger: psycopg.Connection[tuple[object, ...]], version: int -) -> None: - with pytest.raises(psycopg.errors.CheckViolation, match="AccountingEvent_schema_version_check"): - ledger.execute(_EVENT_INSERT, (EventKind.OUTBOUND_USAGE.value, version)) - - -@pytest.mark.parametrize( - ("version", "attempts", "constraint"), - [ - (0, 0, "AccountingDelivery_version_check"), - (-1, 0, "AccountingDelivery_version_check"), - (1, -1, "AccountingDelivery_attempts_check"), - ], -) -def test_delivery_rejects_invalid_versions_and_attempts( - ledger: psycopg.Connection[tuple[object, ...]], version: int, attempts: int, constraint: str -) -> None: - with pytest.raises(psycopg.errors.CheckViolation, match=constraint): - ledger.execute(_DELIVERY_INSERT, (DeliveryTarget.KEY_SPEND.value, version, "pending", attempts)) - - -@pytest.mark.parametrize("column", ["state", "target"]) -def test_delivery_rejects_unknown_enum_values(ledger: psycopg.Connection[tuple[object, ...]], column: str) -> None: - ledger.execute(_DELIVERY_INSERT, (DeliveryTarget.KEY_SPEND.value, 1, "pending", 0)) - with pytest.raises(psycopg.errors.InvalidTextRepresentation, match="invalid input value for enum"): - ledger.execute( - sql.SQL('UPDATE "LiteLLM_AccountingDelivery" SET {} = %s').format(sql.Identifier(column)), ("invalid",) - ) - - -def test_event_rejects_unknown_kind(ledger: psycopg.Connection[tuple[object, ...]]) -> None: - with pytest.raises(psycopg.errors.InvalidTextRepresentation, match="invalid input value for enum"): - ledger.execute(_EVENT_INSERT, ("invalid", 1)) - - -def test_new_delivery_defaults_to_pending_with_no_attempts(ledger: psycopg.Connection[tuple[object, ...]]) -> None: - row: Final = ledger.execute( - 'INSERT INTO "LiteLLM_AccountingDelivery" (event_id, target, version) ' - "VALUES ('event', %s, 1) RETURNING state::text, attempts", - (DeliveryTarget.KEY_SPEND.value,), - ).fetchone() - assert row == ("pending", 0) - - -_AT: Final = datetime(2026, 1, 1, tzinfo=timezone.utc) -_CUTOFF: Final = datetime(2026, 2, 1, tzinfo=timezone.utc) -_TARGETS: Final = (DeliveryTarget.USER_SPEND, DeliveryTarget.TEAM_SPEND) - - -def _usage(event_id: str = "usage", *, inbound: bool = False) -> InboundUsageEvent | OutboundUsageEvent: - fields: Final = dict( - event_id=event_id, - request_id="request", - call_type=CallTypes.completion, - started_at=_AT, - ended_at=_AT, - outcome=Outcome.SUCCEEDED, - dimensions=(), - ) - if inbound: - return InboundUsageEvent(**fields, metrics=(Metric(name=MetricName.REQUESTS, value=Decimal(1)),)) - return OutboundUsageEvent(**fields, attempt_id=event_id, retry_of_attempt_id=None, metrics=None) - - -def _cost(source: str = "usage", event_id: str = "cost", amount: str = "0.125") -> CostEvent: - return CostEvent( - event_id=event_id, - usage_event_id=source, - occurred_at=_AT, - dimensions=(), - charges=(Metric(name=MetricName.SPEND, value=Decimal(amount), unit="USD"),), - snapshot=PricingSnapshot( - calculator_version="fixture", - model="fixture", - provider=None, - pricing_source="cost_map", - priced_model_key="fixture", - total_cost=Decimal(amount), - ), - ) - - -def _envelope(event: AccountingEvent, *, context: Mapping[str, JsonValue] | None = None) -> str: - return json.dumps({"event": event.model_dump(mode="json"), "context": context or {}}) - - -async def _insert( - store: AccountingLedger, - event: AccountingEvent, - targets: tuple[DeliveryTarget, ...] = _TARGETS, - *, - context: Mapping[str, JsonValue] | None = None, -) -> str: - return await store.insert_event(event, targets, envelope=_envelope(event, context=context)) - - -def _rows(database_url: str, statement: str, parameters: tuple[object, ...] = ()) -> Sequence[tuple[object, ...]]: - with psycopg.connect(database_url) as connection: - cursor: Final = connection.execute(statement, parameters) - return cursor.fetchall() if cursor.description is not None else [] - - -def _complete_and_age(database_url: str) -> None: - with psycopg.connect(database_url) as connection: - connection.execute('UPDATE "LiteLLM_AccountingEvent" SET recorded_at = %s', (_AT,)) - connection.execute("UPDATE \"LiteLLM_AccountingDelivery\" SET state = 'applied', applied_at = %s", (_AT,)) - - -@pytest_asyncio.fixture(loop_scope="function") -async def writer(ledger_database: str, monkeypatch: pytest.MonkeyPatch) -> AsyncIterator[_Writer]: - monkeypatch.setenv("DATABASE_URL", ledger_database) - monkeypatch.delenv("DATABASE_URL_READ_REPLICA", raising=False) - _rows(ledger_database, 'TRUNCATE "LiteLLM_AccountingDelivery", "LiteLLM_AccountingEvent"') - async with connected_proxy_prisma(ledger_database) as client: - yield client, AccountingLedger.for_client(client) - - -@pytest.mark.asyncio -async def test_event_and_complete_delivery_set_commit_together(writer: _Writer, ledger_database: str) -> None: - _, store = writer - event: Final = _usage() - assert await _insert(store, event, context={"requested_region": "eu", "quantity": "1.25"}) == "inserted" - rows: Final = _rows(ledger_database, 'SELECT kind::text, source_event_id, payload FROM "LiteLLM_AccountingEvent"') - assert rows == [ - ("outbound_usage", None, json.loads(_envelope(event, context={"requested_region": "eu", "quantity": "1.25"}))) - ] - deliveries: Final = _rows( - ledger_database, 'SELECT target::text, state::text, attempts FROM "LiteLLM_AccountingDelivery"' - ) - assert set(deliveries) == {(target.value, "pending", 0) for target in _TARGETS} - - -@pytest.mark.asyncio -async def test_concurrent_duplicates_preserve_completed_deliveries(writer: _Writer, ledger_database: str) -> None: - _, store = writer - event: Final = _usage(inbound=True) - results: Final = await asyncio.gather(*(_insert(store, event) for _ in range(8))) - assert results.count("inserted") == 1 and results.count("duplicate") == 7 - _complete_and_age(ledger_database) - before: Final = _rows(ledger_database, 'SELECT * FROM "LiteLLM_AccountingDelivery" ORDER BY target') - reordered: Final = json.dumps(json.loads(_envelope(event)), sort_keys=True, indent=2) - assert await store.insert_event(event, tuple(reversed(_TARGETS)) + _TARGETS, envelope=reordered) == "duplicate" - assert _rows(ledger_database, 'SELECT * FROM "LiteLLM_AccountingDelivery" ORDER BY target') == before - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingEvent"') == [(1,)] - - -@pytest.mark.asyncio -@pytest.mark.parametrize("change", ["payload", "context", "targets", "schema_version", "version"]) -async def test_conflicting_acceptance_cannot_overwrite_or_add_work( - writer: _Writer, ledger_database: str, change: str -) -> None: - _, store = writer - event: Final = _usage() - await _insert(store, event) - altered: Final = event.model_copy(update={"outcome": Outcome.FAILED}) if change == "payload" else event - targets: Final = (DeliveryTarget.KEY_SPEND,) if change == "targets" else _TARGETS - context: Final = {"override": "0.5"} if change == "context" else {} - options: Final = {change: 2} if change in ("schema_version", "version") else {} - with pytest.raises(AccountingConflictError, match="conflicts"): - await store.insert_event(altered, targets, envelope=_envelope(altered, context=context), **options) - assert _rows(ledger_database, 'SELECT payload FROM "LiteLLM_AccountingEvent"') == [(json.loads(_envelope(event)),)] - assert set(_rows(ledger_database, 'SELECT target::text FROM "LiteLLM_AccountingDelivery"')) == { - (t.value,) for t in _TARGETS - } - - -@pytest.mark.asyncio -async def test_competing_cost_identities_accept_only_one_authoritative_charge( - writer: _Writer, ledger_database: str -) -> None: - _, store = writer - await _insert(store, _usage()) - results: Final = await asyncio.gather( - _insert(store, _cost()), _insert(store, _cost(event_id="other-cost")), return_exceptions=True - ) - assert sum(result == "inserted" for result in results) == 1 - assert sum(isinstance(result, AccountingConflictError) for result in results) == 1 - accepted: Final = _rows( - ledger_database, "SELECT event_id, payload FROM \"LiteLLM_AccountingEvent\" WHERE kind = 'cost'" - ) - assert len(accepted) == 1 - event: Final = CostEvent.model_validate_json(json.dumps(accepted[0][1]["event"])) - assert await _insert(store, event) == "duplicate" - assert event.snapshot.total_cost == Decimal("0.125") - with pytest.raises(AccountingConflictError): - await _insert(store, _cost(event_id=event.event_id, amount="0.5")) - - -@pytest.mark.asyncio -@pytest.mark.parametrize("source", ["missing", "inbound", "cost"]) -async def test_cost_requires_an_existing_outbound_source(writer: _Writer, ledger_database: str, source: str) -> None: - _, store = writer - if source == "inbound": - await _insert(store, _usage("source", inbound=True)) - if source == "cost": - await _insert(store, _usage()) - await _insert(store, _cost(event_id="source")) - with pytest.raises(AccountingConflictError, match="outbound usage"): - await _insert(store, _cost(source="source", event_id="invalid")) - assert _rows(ledger_database, "SELECT count(*) FROM \"LiteLLM_AccountingEvent\" WHERE event_id = 'invalid'") == [ - (0,) - ] - - -@pytest.mark.asyncio -@pytest.mark.parametrize("failure", ["before_commit", "after_commit", "cancellation"]) -async def test_interruption_rolls_back_or_retry_recognizes_commit( - writer: _Writer, ledger_database: str, failure: str -) -> None: - client, store = writer - - @asynccontextmanager - async def interrupted() -> AsyncGenerator[Prisma]: - async with client.writer_db.tx() as tx: - yield tx - if failure == "before_commit": - raise RuntimeError("injected pre-commit failure") - if failure == "cancellation": - raise asyncio.CancelledError - raise RuntimeError("injected lost acknowledgement") - - error: Final = asyncio.CancelledError if failure == "cancellation" else RuntimeError - with pytest.raises(error): - await _insert(AccountingLedger(interrupted), _usage()) - expected: Final = 1 if failure == "after_commit" else 0 - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingEvent"') == [(expected,)] - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingDelivery"') == [(expected * len(_TARGETS),)] - assert await _insert(store, _usage()) == ("duplicate" if expected else "inserted") - - -@pytest.mark.asyncio -async def test_delivery_insert_failure_rolls_back_event(writer: _Writer, ledger_database: str) -> None: - from prisma.errors import RawQueryError - - _, store = writer - with psycopg.connect(ledger_database) as connection: - connection.execute( - 'ALTER TABLE "LiteLLM_AccountingDelivery" ADD CONSTRAINT reject_delivery CHECK (version < 1)' - ) - try: - with pytest.raises(RawQueryError, match="reject_delivery"): - await _insert(store, _usage()) - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingEvent"') == [(0,)] - finally: - with psycopg.connect(ledger_database) as connection: - connection.execute('ALTER TABLE "LiteLLM_AccountingDelivery" DROP CONSTRAINT reject_delivery') - - -@pytest.mark.asyncio -@pytest.mark.parametrize("blocked", ["pending", "parked", "unpriced", "recent_cost", "recovery"]) -async def test_retention_preserves_incomplete_or_recovery_needed_families( - writer: _Writer, ledger_database: str, blocked: str -) -> None: - _, store = writer - await _insert(store, _usage()) - if blocked != "unpriced": - await _insert(store, _cost()) - _complete_and_age(ledger_database) - with psycopg.connect(ledger_database) as connection: - if blocked in ("pending", "parked"): - connection.execute( - "UPDATE \"LiteLLM_AccountingDelivery\" SET state = %s WHERE event_id = 'cost'", (blocked,) - ) - if blocked == "recent_cost": - connection.execute( - "UPDATE \"LiteLLM_AccountingEvent\" SET recorded_at = %s WHERE event_id = 'cost'", (_CUTOFF,) - ) - before: Final = _rows(ledger_database, 'SELECT event_id FROM "LiteLLM_AccountingEvent" ORDER BY event_id') - assert ( - await store.purge_completed( - redelivery_before=_CUTOFF, recovery_before=_AT if blocked == "recovery" else _CUTOFF - ) - == 0 - ) - assert _rows(ledger_database, 'SELECT event_id FROM "LiteLLM_AccountingEvent" ORDER BY event_id') == before - - -@pytest.mark.asyncio -async def test_retention_removes_completed_family_and_receipts_together(writer: _Writer, ledger_database: str) -> None: - _, store = writer - await _insert(store, _usage()) - await _insert(store, _cost()) - _complete_and_age(ledger_database) - assert await store.purge_completed(redelivery_before=_CUTOFF, recovery_before=_CUTOFF) == 2 - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingEvent"') == [(0,)] - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingDelivery"') == [(0,)] - - -@pytest.mark.asyncio -async def test_retention_respects_batch_bound_and_skips_locked_families(writer: _Writer, ledger_database: str) -> None: - client, store = writer - for name in ("a", "b", "c"): - await _insert(store, _usage(name, inbound=True)) - _complete_and_age(ledger_database) - async with client.writer_db.tx() as tx: - await tx.query_raw("SELECT event_id FROM \"LiteLLM_AccountingEvent\" WHERE event_id = 'a' FOR UPDATE") - assert await store.purge_completed(redelivery_before=_CUTOFF, recovery_before=_CUTOFF, limit=1) == 1 - assert _rows(ledger_database, 'SELECT event_id FROM "LiteLLM_AccountingEvent" ORDER BY event_id') == [ - ("a",), - ("c",), - ] - assert await store.purge_completed(redelivery_before=_CUTOFF, recovery_before=_CUTOFF) == 2 - - -@pytest.mark.asyncio -async def test_retention_makes_progress_past_pending_and_unpriced_events(writer: _Writer, ledger_database: str) -> None: - _, store = writer - await _insert(store, _usage("a", inbound=True)) - await _insert(store, _usage("b")) - await _insert(store, _usage("c", inbound=True)) - _complete_and_age(ledger_database) - _rows(ledger_database, "UPDATE \"LiteLLM_AccountingDelivery\" SET state = 'pending' WHERE event_id = 'a'") - assert await store.purge_completed(redelivery_before=_CUTOFF, recovery_before=_CUTOFF, limit=1) == 1 - assert _rows(ledger_database, 'SELECT event_id FROM "LiteLLM_AccountingEvent" ORDER BY event_id') == [ - ("a",), - ("b",), - ] - - -@pytest.mark.asyncio -async def test_zero_cost_and_empty_delivery_sets_are_durable(writer: _Writer, ledger_database: str) -> None: - _, store = writer - await _insert(store, _usage(), targets=()) - event: Final = _cost(amount="0") - assert await _insert(store, event, targets=()) == "inserted" - assert await _insert(store, event, targets=()) == "duplicate" - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingDelivery"') == [(0,)] - _complete_and_age(ledger_database) - assert await store.purge_completed(redelivery_before=_CUTOFF, recovery_before=_CUTOFF) == 2 - - -@pytest.mark.asyncio -async def test_retention_cannot_delete_source_while_cost_acceptance_is_uncommitted( - writer: _Writer, ledger_database: str -) -> None: - client, store = writer - await _insert(store, _usage()) - _complete_and_age(ledger_database) - inserted: Final = asyncio.Event() - release: Final = asyncio.Event() - - @asynccontextmanager - async def paused_commit() -> AsyncGenerator[Prisma]: - async with client.writer_db.tx() as tx: - yield tx - inserted.set() - await release.wait() - - task: Final = asyncio.create_task(_insert(AccountingLedger(paused_commit), _cost())) - try: - await asyncio.wait_for(inserted.wait(), timeout=5) - assert await store.purge_completed(redelivery_before=_CUTOFF, recovery_before=_CUTOFF) == 0 - finally: - release.set() - await task - assert _rows(ledger_database, 'SELECT event_id FROM "LiteLLM_AccountingEvent" ORDER BY event_id') == [ - ("cost",), - ("usage",), - ] - - -@pytest.mark.asyncio -async def test_retention_failure_rolls_back_event_and_receipt_deletion(writer: _Writer, ledger_database: str) -> None: - client, store = writer - await _insert(store, _usage(inbound=True)) - _complete_and_age(ledger_database) - - @asynccontextmanager - async def interrupted() -> AsyncGenerator[Prisma]: - async with client.writer_db.tx() as tx: - yield tx - raise RuntimeError("injected cleanup failure") - - with pytest.raises(RuntimeError, match="cleanup failure"): - await AccountingLedger(interrupted).purge_completed(redelivery_before=_CUTOFF, recovery_before=_CUTOFF) - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingEvent"') == [(1,)] - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingDelivery"') == [(len(_TARGETS),)] - assert await store.purge_completed(redelivery_before=_CUTOFF, recovery_before=_CUTOFF) == 1 - - -@pytest.mark.asyncio -async def test_ledger_reads_and_writes_use_primary_when_replica_is_configured( - writer: _Writer, ledger_database: str, monkeypatch: pytest.MonkeyPatch -) -> None: - with scratch_database("replica") as replica_url: - monkeypatch.setenv("DATABASE_URL_READ_REPLICA", replica_url) - async with connected_proxy_prisma(ledger_database) as client: - store: Final = AccountingLedger.for_client(client) - await _insert(store, _usage()) - assert await _insert(store, _usage()) == "duplicate" - assert await _insert(store, _cost()) == "inserted" - _complete_and_age(ledger_database) - assert await store.purge_completed(redelivery_before=_CUTOFF, recovery_before=_CUTOFF) == 2 - assert _rows(replica_url, "SELECT to_regclass('public.\"LiteLLM_AccountingEvent\"')") == [(None,)] - - -def _index_conditions(plan: object) -> tuple[tuple[object, object], ...]: - if isinstance(plan, dict): - own: Final = ((plan.get("Index Name"), plan.get("Index Cond")),) if "Index Name" in plan else () - children: Final = (plan.get("Plan"), *plan.get("Plans", ())) - return own + tuple(chain.from_iterable(_index_conditions(child) for child in children if child is not None)) - return tuple(chain.from_iterable(_index_conditions(item) for item in plan)) if isinstance(plan, list) else () - - -@pytest.mark.parametrize("statement", [accounting_ledger._DELETE_EVENTS, accounting_ledger._DELETE_DELIVERIES]) -def test_family_cleanup_lookups_use_the_kind_source_index(ledger_database: str, statement: str) -> None: - explained: Final = "EXPLAIN (FORMAT JSON) " + statement.replace("$1", "%s") - with psycopg.connect(ledger_database) as connection: - connection.execute("SET enable_seqscan = off") - plan: Final = connection.execute(explained, ("usage",) * statement.count("$1")).fetchone() - assert plan is not None - conditions: Final = _index_conditions(plan[0]) - assert any( - name == "LiteLLM_AccountingEvent_kind_source_event_id_idx" and "source_event_id" in str(condition) - for name, condition in conditions - ), conditions - - -@pytest.mark.asyncio -@pytest.mark.parametrize("failure", ["before_commit", "after_commit", "conflict"]) -async def test_usage_batch_is_atomic_and_replay_preserves_receipts( - writer: _Writer, ledger_database: str, failure: str -) -> None: - client, store = writer - events: Final = ( - _usage("caller", inbound=True), - _usage("attempt").model_copy( - update={"metrics": (Metric(name=MetricName.PROMPT_TOKENS, value=Decimal("120000")),)} - ), - ) - writes: Final = tuple(UsageWrite(event, _envelope(event), _TARGETS) for event in events) - - @asynccontextmanager - async def interrupted() -> AsyncGenerator[Prisma]: - async with client.writer_db.tx() as tx: - yield tx - if failure == "before_commit": - raise RuntimeError("injected pre-commit failure") - if failure == "after_commit": - raise RuntimeError("injected lost acknowledgement") - - if failure == "conflict": - await store.insert_usage_batch((writes[1],)) - _complete_and_age(ledger_database) - rejected: Final = (writes[0], UsageWrite(events[1], _envelope(events[1], context={"changed": True}), _TARGETS)) - with pytest.raises(AccountingConflictError): - await store.insert_usage_batch(rejected) - assert _rows(ledger_database, 'SELECT event_id FROM "LiteLLM_AccountingEvent"') == [("attempt",)] - else: - with pytest.raises(RuntimeError, match="injected"): - await AccountingLedger(interrupted).insert_usage_batch(writes) - count: Final = 2 if failure == "after_commit" else 0 - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingEvent"') == [(count,)] - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingDelivery"') == [(count * len(_TARGETS),)] - await store.insert_usage_batch(writes) - recovered: Final = await store.load_usage_batch(tuple(event.event_id for event in events)) - assert len(recovered) == 1 - assert recovered[0].event == events[1] - assert json.loads(recovered[0].envelope) == json.loads(writes[1].envelope) - assert set(recovered[0].targets) == set(_TARGETS) - _complete_and_age(ledger_database) - before: Final = _rows(ledger_database, 'SELECT * FROM "LiteLLM_AccountingDelivery" ORDER BY event_id, target') - await store.insert_usage_batch((*writes, *writes)) - assert _rows(ledger_database, 'SELECT * FROM "LiteLLM_AccountingDelivery" ORDER BY event_id, target') == before - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingEvent"') == [(2,)] - - -@pytest.mark.asyncio -async def test_invalid_jsonb_submission_cannot_reject_another_producers_commit( - writer: _Writer, ledger_database: str -) -> None: - from prisma.errors import DataError - - from litellm.proxy.spend_tracking.usage_meter import DurableUsageMeter, UsageCaptureSettings - - _, store = writer - invalid: Final = _usage("invalid") - valid: Final = _usage("valid") - meter: Final = DurableUsageMeter(store.insert_usage_batch, UsageCaptureSettings(batch_size=2)) - rejected: Final = meter.submit( - (UsageWrite(invalid, _envelope(invalid, context={"parent": "bad\x00text"}), _TARGETS),) - ) - accepted: Final = meter.submit((UsageWrite(valid, _envelope(valid), _TARGETS),)) - try: - with pytest.raises(DataError): - await rejected - await accepted - finally: - await meter.close() - assert _rows(ledger_database, 'SELECT event_id FROM "LiteLLM_AccountingEvent"') == [("valid",)] - assert _rows(ledger_database, 'SELECT count(*) FROM "LiteLLM_AccountingDelivery"') == [(len(_TARGETS),)] - assert (meter.pending_bytes, meter.pending_records) == (0, 0) diff --git a/tests/integration/database/test_prisma_migration_lock.py b/tests/integration/database/test_prisma_migration_lock.py index 7482e96d3d3..f4a2a022668 100644 --- a/tests/integration/database/test_prisma_migration_lock.py +++ b/tests/integration/database/test_prisma_migration_lock.py @@ -19,7 +19,8 @@ def _can_take_prismas_session_lock(connection: psycopg.Connection[tuple[object, def _granted_advisory_keys(connection: psycopg.Connection[tuple[object, ...]]) -> frozenset[int]: rows: Final = connection.execute( - "SELECT (classid::bigint << 32) | objid::bigint FROM pg_locks WHERE locktype = 'advisory' AND granted" + "SELECT (classid::bigint << 32) | objid::bigint FROM pg_locks WHERE locktype = 'advisory' AND granted " + "AND database = (SELECT oid FROM pg_database WHERE datname = current_database())" ).fetchall() return frozenset(int(row[0]) for row in rows) diff --git a/tests/integration/database/test_skill_publication.py b/tests/integration/database/test_skill_publication.py new file mode 100644 index 00000000000..476c6bd4399 --- /dev/null +++ b/tests/integration/database/test_skill_publication.py @@ -0,0 +1,201 @@ +import io +import json +import os +import stat +import uuid +import zipfile +from concurrent.futures import ThreadPoolExecutor +from contextlib import AsyncExitStack, ExitStack +from typing import Final + +import psycopg +import pytest +from psycopg import sql + +from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache +from litellm.proxy.utils import PrismaClient, ProxyLogging +from litellm.repositories.plugin_upload_repository import PluginUploadRepository +from tests.integration._support.client import Gateway, list_value, object_value, string_value +from tests.integration._support.database import read_rows + + +def _archive(name: str) -> bytes: + buffer: Final = io.BytesIO() + with zipfile.ZipFile(buffer, "w") as archive: + archive.writestr( + "SKILL.md", f"---\nname: {name}\ndescription: Published instructions\n---\nRetain these exact bytes.\n", + ) + return buffer.getvalue() + + +def _delete(gateway: Gateway, name: str) -> None: + response: Final = gateway.request("DELETE", f"/claude-code/plugins/{name}") + assert response.status_code == 200, response.text + + +@pytest.mark.asyncio +async def test_snapshot_failure_rolls_back_catalog_archive_and_history_then_source_replacement_preserves_bytes( + gateway: Gateway, +) -> None: + name: Final = f"integration-version-{uuid.uuid4().hex}" + path: Final = f"/claude-code/plugins/{name}" + history_path: Final = f"/skill-hub/skills/{name}/versions" + content: Final = _archive(name) + async with AsyncExitStack() as cleanup: + created: Final = gateway.request_multipart( + "/claude-code/plugins/upload", + {"metadata": json.dumps({"name": name})}, + {"file": ("skill.zip", content, "application/zip")}, + ) + assert created.status_code == 200, created.text + cleanup.callback(_delete, gateway, name) + client: Final = PrismaClient(os.environ["DATABASE_URL"], ProxyLogging(UserApiKeyCache())) + await client.connect() + cleanup.push_async_callback(client.disconnect) + repository: Final = PluginUploadRepository(client) + metadata: Final = await repository.get_metadata(name) + assert metadata is not None + snapshot: Final = (await repository.versions(metadata, 100, 0))[0] + snapshot_bytes: Final = await repository.version_content(metadata, snapshot.id) + assert snapshot_bytes is not None + before: Final = gateway.get(path) + history: Final = gateway.get(history_path) + original: Final = object_value(list_value(history["versions"])[0]) + archive_path: Final = string_value(original["download_url"]) + original_response: Final = gateway.request("GET", archive_path) + assert original_response.status_code == 200, original_response.text + published_content: Final = original_response.content + with zipfile.ZipFile(io.BytesIO(published_content)) as published, zipfile.ZipFile(io.BytesIO(content)) as uploaded: + assert published.read("SKILL.md") == uploaded.read("SKILL.md") + current_path: Final = string_value(object_value(before["source"])["url"]) + original_current: Final = gateway.request("GET", current_path) + assert original_current.status_code == 200, original_current.text + witness: Final = f"publication_{uuid.uuid4().hex}" + trigger: Final = f"{witness}_trigger" + function: Final = f"{witness}_function" + with psycopg.connect(os.environ["DATABASE_URL"], autocommit=True) as connection, ExitStack() as failure: + connection.execute(sql.SQL("CREATE SEQUENCE {}").format(sql.Identifier(witness))) + failure.callback(connection.execute, sql.SQL("DROP SEQUENCE {}").format(sql.Identifier(witness))) + connection.execute(sql.SQL("GRANT USAGE ON SEQUENCE {} TO PUBLIC").format(sql.Identifier(witness))) + connection.execute( + sql.SQL( + "CREATE FUNCTION {}() RETURNS trigger LANGUAGE plpgsql AS $$ BEGIN " + "IF EXISTS (SELECT 1 FROM \"LiteLLM_ClaudeCodePluginTable\" " + "WHERE id = NEW.plugin_id AND name = {}) THEN PERFORM nextval({}); " + "RAISE EXCEPTION 'publication snapshot failure'; END IF; RETURN NEW; END $$" + ).format(sql.Identifier(function), sql.Literal(name), sql.Literal(witness)) + ) + failure.callback(connection.execute, sql.SQL("DROP FUNCTION {}()").format(sql.Identifier(function))) + connection.execute( + sql.SQL('CREATE TRIGGER {} BEFORE INSERT ON "LiteLLM_ClaudeCodePluginVersion" ' + "FOR EACH ROW EXECUTE FUNCTION {}()").format(sql.Identifier(trigger), sql.Identifier(function)) + ) + failure.callback( + connection.execute, + sql.SQL('DROP TRIGGER {} ON "LiteLLM_ClaudeCodePluginVersion"').format(sql.Identifier(trigger)), + ) + rejected: Final = gateway.request( + "PUT", path, {"source": {"source": "github", "repo": "example/changed"}, "description": "must roll back"}, + ) + assert rejected.status_code == 500, rejected.text + assert connection.execute( + sql.SQL("SELECT is_called FROM {}").format(sql.Identifier(witness)) + ).fetchone() == (True,) + assert gateway.get(path) == before + assert gateway.get(history_path) == history + current_archive: Final = gateway.request("GET", current_path) + assert current_archive.status_code == 200 and current_archive.content == original_current.content + updated: Final = gateway.request( + "PUT", path, {"source": {"source": "github", "repo": "example/changed"}}, + ) + assert updated.status_code == 200, updated.text + after: Final = gateway.get(history_path) + versions: Final = tuple(object_value(value) for value in list_value(after["versions"])) + assert [version["version"] for version in versions] == ["1.0.1", "1.0.0"] + assert versions[0]["content_kind"] == "source_reference" + assert versions[1]["content_kind"] == "stored_archive" + retained: Final = gateway.request("GET", archive_path) + assert retained.status_code == 200 and retained.content == published_content + assert read_rows( + 'SELECT plugin_name FROM "LiteLLM_ClaudeCodePluginUpload" WHERE plugin_name=%s', (name,) + ) == [] + assert snapshot in await repository.versions(metadata, 100, 0) + assert await repository.version(metadata, snapshot.id) == snapshot + assert await repository.version_content(metadata, snapshot.id) == snapshot_bytes + hidden: Final = gateway.request("POST", f"{path}/disable") + assert hidden.status_code == 200, hidden.text + assert await repository.versions(metadata, 100, 0) == () + assert await repository.version(metadata, snapshot.id) is None + assert await repository.version_content(metadata, snapshot.id) is None + + +def test_neutral_publication_preserves_portable_files_and_atomic_metadata_history(gateway: Gateway) -> None: + name: Final = f"integration-neutral-{uuid.uuid4().hex}" + path: Final = f"/skill-hub/skills/{name}" + files: Final = { + "SKILL.md": f"---\nname: {name}\ndescription: Portable integration fixture.\n---\n\nRead references/notes.md.\n", + "references/notes.md": "Preserve the original supporting file.\n", + "scripts/check.sh": "#!/bin/sh\nprintf 'portable\\n'\n", + } + buffer: Final = io.BytesIO() + with zipfile.ZipFile(buffer, "w") as archive: + for filename, content in files.items(): + entry: Final = zipfile.ZipInfo(filename) + entry.create_system = 3 + entry.external_attr = (stat.S_IFREG | (0o755 if filename.endswith(".sh") else 0o644)) << 16 + archive.writestr(entry, content) + with ExitStack() as cleanup: + created: Final = gateway.request_multipart( + "/skill-hub/skills/upload", {}, {"file": ("skill.zip", buffer.getvalue(), "application/zip")}, + ) + assert created.status_code == 200, created.text + cleanup.callback(_delete, gateway, name) + assert created.json()["version"] == "1.0.0" + before: Final = gateway.get(path) + assert string_value(before["updated_at"]) == created.json()["updated_at"] + history_before: Final = gateway.get(f"{path}/versions") + first: Final = object_value(list_value(history_before["versions"])[0]) + version_id: Final = string_value(first["id"]) + archive_path: Final = f"{path}/versions/{version_id}/archive" + downloaded: Final = gateway.request("GET", archive_path) + assert downloaded.status_code == 200, downloaded.text + with zipfile.ZipFile(io.BytesIO(downloaded.content)) as portable: + assert {member: portable.read(member).decode() for member in portable.namelist()} == files + assert stat.S_IMODE(portable.getinfo("scripts/check.sh").external_attr >> 16) == 0o755 + assert gateway.get(f"{path}/versions/{version_id}") == first + + def publish(index: int) -> int: + response: Final = gateway.request( + "PUT", path, + {"description": f"Registry edit {index}", "expected_updated_at": before["updated_at"]}, + ) + if response.status_code == 200: + assert string_value(response.json()["updated_at"]) != before["updated_at"] + return response.status_code + + with ThreadPoolExecutor(max_workers=2) as pool: + statuses: Final = tuple(pool.map(publish, range(2))) + assert sorted(statuses) == [200, 409] + assert publish(2) == 409 + current: Final = gateway.get(path) + history_after: Final = gateway.get(f"{path}/versions") + versions: Final = tuple(object_value(value) for value in list_value(history_after["versions"])) + assert [version["version"] for version in versions] == ["1.0.1", "1.0.0"] + latest: Final = versions[0] + manifest: Final = object_value(latest["manifest"]) + assert current["version"] == manifest["version"] == latest["version"] + assert current["description"] == manifest["description"] == latest["description"] + assert manifest["agent_skill"] == object_value(first["manifest"])["agent_skill"] + stored: Final = read_rows( + 'SELECT version, description, manifest_json FROM "LiteLLM_ClaudeCodePluginTable" WHERE name=%s', (name,) + ) + assert len(stored) == 1 + assert stored[0]["version"] == current["version"] + assert json.loads(string_value(stored[0]["manifest_json"])) == manifest + retained: Final = gateway.request("GET", archive_path) + latest_archive: Final = gateway.request("GET", f"{path}/versions/{latest['id']}/archive") + assert retained.content == latest_archive.content == downloaded.content + rejected: Final = gateway.request("PUT", path, {"version": "1.0.0", "description": "rejected"}) + assert rejected.status_code == 400, rejected.text + assert gateway.get(path) == current + assert gateway.get(f"{path}/versions") == history_after diff --git a/tests/integration/database/test_skill_submissions.py b/tests/integration/database/test_skill_submissions.py new file mode 100644 index 00000000000..cc00bf6e359 --- /dev/null +++ b/tests/integration/database/test_skill_submissions.py @@ -0,0 +1,454 @@ +import asyncio +import hashlib +import io +import os +import uuid +import zipfile +from collections.abc import AsyncIterator, Mapping, Sequence +from dataclasses import dataclass, replace +from typing import Final, Literal + +import psycopg +import pytest +import pytest_asyncio +from pydantic import JsonValue, TypeAdapter + +from litellm.models.plugin_upload import ( + PluginPublication, + PluginPublicationBase, + PluginPublicationError, + PluginUploadStore, + PublishedPlugin, +) +from litellm.models.skill_submission import ( + SkillSubmission, + SkillSubmissionStore, + SubmissionConflict, + SubmissionLimitExceeded, + SubmissionReviewed, +) +from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache +from litellm.proxy.utils import PrismaClient, ProxyLogging +from litellm.repositories.plugin_upload_repository import PluginUploadRepository +from litellm.repositories.skill_submission_repository import SkillSubmissionRepository +from tests.integration._support.client import eventually +from tests.integration._support.database import read_rows, write_rows + + +@dataclass(frozen=True, slots=True) +class PendingUpdate: + publications: PluginUploadStore + submissions: SkillSubmissionStore + original: PluginPublication + proposal: PluginPublication + base: PublishedPlugin + submission: SkillSubmission + + +def _publication(name: str, description: str, base_url: str = "https://skills.example.test") -> PluginPublication: + buffer: Final = io.BytesIO() + with zipfile.ZipFile(buffer, "w") as archive: + archive.writestr("SKILL.md", f"---\nname: {name}\ndescription: {description}\n---\n{description}\n") + content: Final = buffer.getvalue() + digest: Final = hashlib.sha256(content).hexdigest() + return PluginPublication( + name=name, + version=None, + description=description, + manifest={ + "name": name, + "description": description, + "extension": {"retained": True}, + "source": { + "source": "archive", + "url": f"{base_url}/claude-code/plugins/{name}/archive/{digest}.zip", + "sha256": digest, + }, + }, + content=content, + created_by=f"{name}-owner", + ) + + +def _published_rows(name: str) -> Sequence[Mapping[str, JsonValue]]: + return read_rows( + """SELECT 'catalog' AS storage, to_jsonb(p) AS value + FROM "LiteLLM_ClaudeCodePluginTable" p WHERE name=%s + UNION ALL + SELECT 'archive', to_jsonb(a) FROM "LiteLLM_ClaudeCodePluginUpload" a WHERE plugin_name=%s + UNION ALL + SELECT 'history', to_jsonb(v) FROM "LiteLLM_ClaudeCodePluginVersion" v + JOIN "LiteLLM_ClaudeCodePluginTable" p ON p.id=v.plugin_id WHERE p.name=%s + ORDER BY storage, value""", + (name, name, name), + ) + + +@pytest_asyncio.fixture(loop_scope="function") +async def pending_update() -> AsyncIterator[PendingUpdate]: + name: Final = f"integration-submission-{uuid.uuid4().hex}" + client: Final = PrismaClient(os.environ["DATABASE_URL"], ProxyLogging(UserApiKeyCache())) + await client.connect() + try: + publications: Final = PluginUploadRepository(client) + submissions: Final = SkillSubmissionRepository(client) + original: Final = _publication(name, "Published instructions") + base: Final = await publications.publish(original) + assert isinstance(base, PublishedPlugin) + proposal: Final = _publication(name, "Proposed instructions", "https://member.example.test") + submission: Final = await submissions.submit( + proposal, f"{name}-owner", PluginPublicationBase(base.id, base.updated_at) + ) + assert isinstance(submission, SkillSubmission) + yield PendingUpdate(publications, submissions, original, proposal, base, submission) + finally: + try: + write_rows('DELETE FROM "LiteLLM_SkillSubmission" WHERE plugin_name=%s', (name,)) + write_rows('DELETE FROM "LiteLLM_ClaudeCodePluginTable" WHERE name=%s', (name,)) + finally: + await client.disconnect() + + +async def test_approval_commits_version_archive_history_and_review(pending_update: PendingUpdate) -> None: + case: Final = pending_update + before: Final = await case.publications.get_metadata(case.original.name) + assert before is not None + assert await case.publications.get_content(before) == case.original.content + assert case.submission.proposal.version is None + reviewed: Final = await case.submissions.review( + case.submission.id, "integration-reviewer", True, None, publication_base_url="https://skills.example.test" + ) + assert isinstance(reviewed, SubmissionReviewed) + assert reviewed.plugin is not None and reviewed.plugin.version == "1.0.1" + stored: Final = await case.submissions.get(case.submission.id, None) + assert stored is not None + assert (stored.status, stored.reviewed_by, stored.rejection_reason) == ( + "approved", + "integration-reviewer", + None, + ) + assert stored.reviewed_at is not None + assert stored.proposal == case.submission.proposal + assert await case.submissions.get_archive(stored.id, None) == case.proposal.content + current: Final = await case.publications.get_plugin(case.original.name) + assert current is not None + published_manifest: Final = { + **case.proposal.manifest, + "source": { + **TypeAdapter(dict[str, str]).validate_python(case.submission.proposal.manifest["source"]), + "url": f"https://skills.example.test/claude-code/plugins/{case.original.name}/archive/" + f"{hashlib.sha256(case.proposal.content or b'').hexdigest()}.zip", + }, + } + assert (current.id, current.version, current.description, current.manifest) == ( + case.base.id, + reviewed.plugin.version, + case.proposal.description, + {**published_manifest, "version": reviewed.plugin.version}, + ) + metadata: Final = await case.publications.get_metadata(case.original.name) + assert metadata is not None + assert await case.publications.get_content(metadata) == case.proposal.content + history: Final = await case.publications.versions(metadata, 10, 0) + assert tuple((version.version, version.description, version.archive_available) for version in history) == ( + ("1.0.1", case.proposal.description, True), + ("1.0.0", case.original.description, True), + ) + for version, publication, manifest in zip( + history, (case.proposal, case.original), (published_manifest, case.original.manifest), strict=True + ): + assert version.manifest == {**manifest, "version": version.version} + assert version.published_by == publication.created_by + assert await case.publications.version_content(metadata, version.id) == publication.content + + +async def test_simultaneous_approve_reject_has_one_winner(pending_update: PendingUpdate) -> None: + case: Final = pending_update + before: Final = _published_rows(case.original.name) + with psycopg.connect(os.environ["DATABASE_URL"]) as blocker: + blocker.execute('SELECT id FROM "LiteLLM_SkillSubmission" WHERE id=%s FOR UPDATE', (case.submission.id,)) + blocker_pid: Final = str(blocker.info.backend_pid) + reviews: Final = ( + asyncio.create_task( + case.submissions.review( + case.submission.id, + "integration-approver", + True, + None, + publication_base_url="https://skills.example.test", + ) + ), + asyncio.create_task( + case.submissions.review(case.submission.id, "integration-rejector", False, "Needs revision") + ), + ) + try: + await asyncio.to_thread( + eventually, + lambda: read_rows( + """WITH RECURSIVE blocked AS ( + SELECT %s::integer AS pid + UNION + SELECT a.pid FROM pg_stat_activity a + JOIN blocked b ON b.pid = ANY(pg_blocking_pids(a.pid)) + ) SELECT pid FROM blocked WHERE pid<>%s::integer""", + (blocker_pid, blocker_pid), + ), + lambda rows: len(rows) == 2, + seconds=3, + ) + finally: + blocker.rollback() + results: Final = await asyncio.gather(*reviews) + winners: Final = tuple(result for result in results if isinstance(result, SubmissionReviewed)) + assert len(winners) == 1 + assert sum(isinstance(result, SubmissionConflict) for result in results) == 1 + stored: Final = await case.submissions.get(case.submission.id, None) + assert stored is not None and stored.reviewed_at is not None + winner: Final = winners[0] + assert (stored.status, stored.reviewed_by, stored.rejection_reason) == ( + winner.submission.status, + winner.submission.reviewed_by, + winner.submission.rejection_reason, + ) + if isinstance(results[0], SubmissionConflict): + assert (stored.status, stored.reviewed_by, stored.rejection_reason) == ( + "rejected", + "integration-rejector", + "Needs revision", + ) + assert _published_rows(case.original.name) == before + return + assert (stored.status, stored.reviewed_by, stored.rejection_reason) == ( + "approved", + "integration-approver", + None, + ) + metadata: Final = await case.publications.get_metadata(case.original.name) + assert metadata is not None + assert await case.publications.get_content(metadata) == case.proposal.content + assert tuple(version.version for version in await case.publications.versions(metadata, 10, 0)) == ( + "1.0.1", + "1.0.0", + ) + + +async def test_publication_failure_rolls_back_and_leaves_submission_pending(pending_update: PendingUpdate) -> None: + case: Final = pending_update + collision_id: Final = str(uuid.uuid4()) + write_rows( + """INSERT INTO "LiteLLM_ClaudeCodePluginVersion" (id, plugin_id, version) + VALUES (%s, %s, '1.0.1')""", + (collision_id, case.base.id), + ) + before: Final = _published_rows(case.original.name) + failed: Final = await case.submissions.review( + case.submission.id, "integration-reviewer", True, None, publication_base_url="https://skills.example.test" + ) + assert isinstance(failed, SubmissionConflict) + assert _published_rows(case.original.name) == before + assert await case.submissions.get(case.submission.id, None) == case.submission + assert await case.submissions.get_archive(case.submission.id, None) == case.proposal.content + write_rows('DELETE FROM "LiteLLM_ClaudeCodePluginVersion" WHERE id=%s', (collision_id,)) + retried: Final = await case.submissions.review( + case.submission.id, "integration-reviewer", True, None, publication_base_url="https://skills.example.test" + ) + assert isinstance(retried, SubmissionReviewed) + assert retried.plugin is not None and retried.plugin.version == "1.0.1" + stored: Final = await case.submissions.get(case.submission.id, None) + assert stored is not None and stored.status == "approved" + + +@pytest.mark.parametrize("change", ("update", "recreate")) +async def test_stale_target_cannot_publish( + pending_update: PendingUpdate, change: Literal["update", "recreate"] +) -> None: + case: Final = pending_update + intervening: Final = _publication(case.original.name, "Intervening publication") + if change == "recreate": + write_rows('DELETE FROM "LiteLLM_ClaudeCodePluginTable" WHERE name=%s', (case.original.name,)) + replacement: Final = await case.publications.publish( + intervening, + PluginPublicationBase(case.base.id, case.base.updated_at) if change == "update" else None, + ) + assert isinstance(replacement, PublishedPlugin) + before: Final = _published_rows(case.original.name) + reviewed: Final = await case.submissions.review( + case.submission.id, "integration-reviewer", True, None, publication_base_url="https://skills.example.test" + ) + assert isinstance(reviewed, PluginPublicationError) and reviewed.kind == "conflict" + assert _published_rows(case.original.name) == before + assert await case.submissions.get(case.submission.id, None) == case.submission + + +async def test_concurrent_submissions_share_user_limit_and_review_releases_capacity( + pending_update: PendingUpdate, +) -> None: + case: Final = pending_update + owner: Final = case.submission.submitted_by + base: Final = PluginPublicationBase(case.base.id, case.base.updated_at) + for _ in range(18): + assert isinstance(await case.submissions.submit(case.proposal, owner, base), SkillSubmission) + peer: Final = PrismaClient(os.environ["DATABASE_URL"], ProxyLogging(UserApiKeyCache())) + await peer.connect() + try: + with psycopg.connect(os.environ["DATABASE_URL"]) as blocker: + blocker.execute( + "SELECT pg_advisory_xact_lock(hashtext('litellm.skill_submissions'), hashtext(%s))", (owner,) + ) + blocker_pid: Final = str(blocker.info.backend_pid) + requests: Final = ( + asyncio.create_task(case.submissions.submit(case.proposal, owner, base)), + asyncio.create_task(SkillSubmissionRepository(peer).submit(case.proposal, owner, base)), + ) + try: + await asyncio.to_thread( + eventually, + lambda: read_rows( + "SELECT pid FROM pg_stat_activity WHERE %s::integer = ANY(pg_blocking_pids(pid))", + (blocker_pid,), + ), + lambda rows: len(rows) == 2, + seconds=3, + ) + finally: + blocker.rollback() + results: Final = await asyncio.gather(*requests) + finally: + await peer.disconnect() + assert sum(isinstance(result, SkillSubmission) for result in results) == 1 + assert sum(isinstance(result, SubmissionLimitExceeded) for result in results) == 1 + full: Final = await case.submissions.list(owner, "pending_review", 20, 0) + assert (len(full.submissions), full.has_more) == (20, False) + other: Final = await case.submissions.submit(case.proposal, f"{owner}-other", base) + assert isinstance(other, SkillSubmission) + rejected: Final = await case.submissions.review( + case.submission.id, "integration-reviewer", False, "Review complete" + ) + assert isinstance(rejected, SubmissionReviewed) + assert await case.submissions.get_archive(case.submission.id, owner) == case.proposal.content + replacement: Final = await case.submissions.submit(case.proposal, owner, base) + assert isinstance(replacement, SkillSubmission) + after: Final = await case.submissions.list(owner, "pending_review", 20, 0) + assert len(after.submissions) == 20 + assert all(row.id != case.submission.id and row.submitted_by == owner for row in after.submissions) + + +async def test_submission_pages_filter_owner_and_status_before_limit(pending_update: PendingUpdate) -> None: + case: Final = pending_update + owner: Final = case.submission.submitted_by + other: Final = f"{owner}-other" + generated: Final = await asyncio.gather( + *( + case.submissions.submit(case.proposal, identity, PluginPublicationBase(case.base.id, case.base.updated_at)) + for identity in (owner, other, owner, other) + ) + ) + submitted: Final = tuple(result for result in generated if isinstance(result, SkillSubmission)) + assert len(submitted) == 4 + rejected: Final = await case.submissions.review(submitted[0].id, "integration-reviewer", False, None) + assert isinstance(rejected, SubmissionReviewed) + write_rows( + """UPDATE "LiteLLM_SkillSubmission" SET created_at=TIMESTAMP '9999-01-01' + WHERE plugin_name=%s""", + (case.original.name,), + ) + own_pending: Final = tuple(sorted((case.submission.id, submitted[2].id), reverse=True)) + first: Final = await case.submissions.list(owner, "pending_review", 1, 0) + second: Final = await case.submissions.list(owner, "pending_review", 1, 1) + empty: Final = await case.submissions.list(owner, "pending_review", 1, 2) + assert (tuple(row.id for row in first.submissions), first.has_more) == (own_pending[:1], True) + assert (tuple(row.id for row in second.submissions), second.has_more) == (own_pending[1:], False) + assert (empty.submissions, empty.has_more) == ((), False) + reviewed: Final = await case.submissions.list(owner, "rejected", 20, 0) + assert (tuple(row.id for row in reviewed.submissions), reviewed.has_more) == ((submitted[0].id,), False) + own_all: Final = await case.submissions.list(owner, None, 20, 0) + assert tuple(row.id for row in own_all.submissions) == tuple(sorted((*own_pending, submitted[0].id), reverse=True)) + other_page: Final = await case.submissions.list(other, None, 20, 0) + assert tuple(row.id for row in other_page.submissions) == tuple( + sorted((submitted[1].id, submitted[3].id), reverse=True) + ) + global_pending: Final = await case.submissions.list(None, "pending_review", 3, 0) + all_pending: Final = tuple(sorted((*own_pending, submitted[1].id, submitted[3].id), reverse=True)) + assert (tuple(row.id for row in global_pending.submissions), global_pending.has_more) == (all_pending[:3], True) + + +@pytest.mark.parametrize("completion_seconds", (13, 21), ids=("before-deadline", "at-deadline")) +async def test_scan_claim_retry_and_late_result_preserve_proposal( + pending_update: PendingUpdate, completion_seconds: int, +) -> None: + from datetime import datetime, timedelta, timezone + + from litellm.models.skill_submission import SkillScanInput + from litellm.types.proxy.skill_scanning import SkillScan, SkillScanReport + + case: Final = pending_update + now: Final = datetime(2026, 1, 1, tzinfo=timezone.utc) + first: Final = SkillScan( + id="first", status="running", requested_by="reviewer", started_at=now, + expires_at=now + timedelta(seconds=10), + ) + started: Final = await case.submissions.start_scan(case.submission.id, first) + assert isinstance(started, SkillScanInput) + assert started.content == case.proposal.content + assert started.scan.archive_sha256 == hashlib.sha256(case.proposal.content or b"").hexdigest() + duplicate: Final = await case.submissions.start_scan(case.submission.id, first.model_copy(update={"id": "duplicate"})) + assert isinstance(duplicate, SubmissionConflict) + second: Final = first.model_copy(update={ + "id": "second", "started_at": now + timedelta(seconds=11), "expires_at": now + timedelta(seconds=21), + }) + retry: Final = await case.submissions.start_scan(case.submission.id, second) + assert isinstance(retry, SkillScanInput) + report: Final = SkillScanReport( + scanner_version="test-version", complete=False, scan_mode="static-only", risk_score=90, findings=(), + ) + await case.submissions.finish_scan(case.submission.id, started.scan.model_copy(update={ + "status": "completed", "report": report, "completed_at": now + timedelta(seconds=12), + })) + assert await case.submissions.get_scan(case.submission.id) == retry.scan + completed: Final = retry.scan.model_copy(update={ + "status": "completed", "report": report, "completed_at": now + timedelta(seconds=completion_seconds), + }) + expected: Final = completed if completion_seconds < 21 else retry.scan.at(now + timedelta(seconds=21)) + await case.submissions.finish_scan(case.submission.id, completed) + assert await case.submissions.get_scan(case.submission.id) == expected + assert await case.submissions.get(case.submission.id, None) == case.submission + approved: Final = await case.submissions.review(case.submission.id, "reviewer", True, None, publication_base_url="https://gateway.test") + assert isinstance(approved, SubmissionReviewed) + assert await case.submissions.get_scan(case.submission.id) == expected + denied: Final = await case.submissions.start_scan(case.submission.id, second) + assert isinstance(denied, SubmissionConflict) + + +@pytest.mark.parametrize("available, remote", ((True, False), (False, False), (False, True))) +async def test_metadata_scan_requires_the_matching_managed_archive( + pending_update: PendingUpdate, available: bool, remote: bool +) -> None: + from datetime import datetime, timedelta, timezone + + from litellm.models.skill_submission import SkillScanInput + from litellm.types.proxy.skill_scanning import SkillScan + + case: Final = pending_update + submission: Final = await case.submissions.submit( + replace(case.original, content=None, manifest={ + **case.original.manifest, + **({"source": {"source": "archive", "url": "https://example.org/skill.zip"}} if remote else {}), + }), "member", PluginPublicationBase(case.base.id, case.base.updated_at) + ) + if not available: + write_rows('DELETE FROM "LiteLLM_ClaudeCodePluginUpload" WHERE plugin_name=%s', (case.original.name,)) + now: Final = datetime.now(timezone.utc) + result: Final = await case.submissions.start_scan(submission.id, SkillScan( + id="metadata-scan", status="running", requested_by="admin", started_at=now, + expires_at=now + timedelta(seconds=10), + )) + if available or remote: + assert isinstance(result, SkillScanInput) + assert result.content == (None if remote else case.original.content) + if remote: + assert result.source == {"source": "archive", "url": "https://example.org/skill.zip"} + assert result.scan.archive_sha256 is None + else: + assert isinstance(result, SubmissionConflict) + assert await case.submissions.get_scan(submission.id) is None diff --git a/tests/integration/database/test_spendlogs_delivery.py b/tests/integration/database/test_spendlogs_delivery.py new file mode 100644 index 00000000000..19f01a6b902 --- /dev/null +++ b/tests/integration/database/test_spendlogs_delivery.py @@ -0,0 +1,512 @@ +import asyncio +import os +from collections.abc import AsyncIterator, Iterator, Mapping, Sequence +from pathlib import Path +from typing import Final +from urllib.parse import urlsplit, urlunsplit + +import psycopg +import pytest +import pytest_asyncio +from prisma import Prisma + +from litellm.repositories.accounting_delivery_repository import ( + AccountingDeliveryRepository, + DeliveryProjection, + LedgerTransaction, +) +from litellm.repositories.spend_log_insert import spend_log_insert_statement +from tests.integration._support.database import scratch_database + +_MIGRATIONS: Final = Path(__file__).resolve().parents[3] / "litellm-proxy-extras/litellm_proxy_extras/migrations" + + +@pytest.fixture +def delivery_database(request: pytest.FixtureRequest) -> Iterator[psycopg.Connection[tuple[object, ...]]]: + with scratch_database("spendlogs_delivery") as url, psycopg.connect(url, autocommit=True) as connection: + if getattr(request, "param", "public") == "ledger_tenant": + connection.execute("CREATE SCHEMA ledger_tenant") + connection.execute("SET search_path TO ledger_tenant") + connection.execute((_MIGRATIONS / "20261027000000_add_accounting_ledger_tables/migration.sql").read_text()) + connection.execute("""CREATE TABLE "LiteLLM_SpendLogs" ( + request_id text PRIMARY KEY, call_type text NOT NULL, spend float8 NOT NULL DEFAULT 0, + status text, + metadata jsonb DEFAULT '{}', "startTime" timestamp(3) NOT NULL, + created_at timestamp(3) NOT NULL DEFAULT CURRENT_TIMESTAMP, + updated_at timestamp(3) NOT NULL DEFAULT CURRENT_TIMESTAMP + )""") + connection.execute((_MIGRATIONS / "20261103010000_spendlogs_accounting_delivery/migration.sql").read_text()) + yield connection + + +def _insert( + connection: psycopg.Connection[tuple[object, ...]], rows: Sequence[Mapping[str, object]], *, ledger: bool = True +) -> None: + from psycopg.types.json import Jsonb + + statement: Final = spend_log_insert_statement(rows) + with connection.transaction(): + inserted: Final = { + row[0] for row in connection.execute(statement[0].replace("$1", "%s"), (statement[1],)).fetchall() + } + for row in rows: + if ledger and row["request_id"] in inserted: + connection.execute( + 'INSERT INTO "LiteLLM_SpendLogDelivery" (delivery_id, request_id, accounting_payload, is_batch) ' + "VALUES (%s, %s, %s, %s)", + (row["request_id"], row["request_id"], Jsonb(dict(row)), row.get("call_type") == "aretrieve_batch"), + ) + + +def _with_payload(row: Mapping[str, object]) -> Mapping[str, object]: + return {**row, "accounting_payload": dict(row)} + + +def _row(request_id: str) -> Mapping[str, object]: + return { + "request_id": request_id, + "call_type": "acompletion", + "spend": 0.5, + "startTime": "2026-11-02T12:00:00+00:00", + "metadata": '{"accounting_savings":{"compression":0.2}}', + } + + +@pytest.mark.parametrize("call_type", ["acompletion", "aretrieve_batch"]) +@pytest.mark.parametrize("mode", ["local", "url", "disabled"]) +@pytest.mark.parametrize("partitioned", [False, True]) +@pytest.mark.asyncio +async def test_delivery_first_acceptance_deduplicates_all_storage_modes( + delivery_database, delivery_client, mode, partitioned, call_type +): + from types import SimpleNamespace + + from litellm.repositories.table_repositories import SpendLogsRepository + + if partitioned: + delivery_database.execute('ALTER TABLE "LiteLLM_SpendLogs" RENAME TO spend_template') + delivery_database.execute( + 'CREATE TABLE "LiteLLM_SpendLogs" (LIKE spend_template INCLUDING DEFAULTS INCLUDING CONSTRAINTS, PRIMARY KEY(request_id, "startTime")) PARTITION BY RANGE ("startTime")' + ) + delivery_database.execute('CREATE TABLE "LiteLLM_SpendLogs_p20261102" PARTITION OF "LiteLLM_SpendLogs" DEFAULT') + delivery_database.execute("DROP TABLE spend_template") + repository = SpendLogsRepository(SimpleNamespace(db=delivery_client, writer_db=delivery_client)) + row = {**_with_payload({**_row("shared"), "call_type": call_type}), "accounting_log_disabled": mode == "disabled"} + results = await asyncio.gather( + repository.insert_with_deliveries((row,), write_spend_logs=mode != "url"), + repository.insert_with_deliveries( + ({**row, "startTime": "2026-11-03T12:00:00"},), write_spend_logs=mode != "url" + ), + ) + assert sorted(results) == [0, 1] + assert delivery_database.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogs"').fetchone() == (int(mode == "local"),) + assert delivery_database.execute( + "SELECT accounting_payload->>'spend', state::text FROM \"LiteLLM_SpendLogDelivery\"" + ).fetchall() == [("0.5", "pending")] + if partitioned: + delivery_database.execute('DROP TABLE "LiteLLM_SpendLogs_p20261102"') + else: + delivery_database.execute('DELETE FROM "LiteLLM_SpendLogs"') + + async def apply(transaction, deliveries): + await transaction.execute_raw("UPDATE totals SET spend = spend + $1::float8", float(deliveries[0].row["spend"])) + + worker = AccountingDeliveryRepository(delivery_client) + assert (await worker.apply_pending(apply)).applied == 1 + assert (await worker.apply_pending(apply)).applied == 0 + assert delivery_database.execute("SELECT spend FROM totals").fetchone() == (0.5,) + + +@pytest.mark.parametrize("mode", ["local", "url", "disabled"]) +@pytest.mark.asyncio +async def test_duplicate_rows_in_one_flush_keep_first_accounting_payload(delivery_database, delivery_client, mode): + from types import SimpleNamespace + + from litellm.repositories.table_repositories import SpendLogsRepository + + repository = SpendLogsRepository(SimpleNamespace(db=delivery_client, writer_db=delivery_client)) + first = {**_with_payload(_row("repeated")), "accounting_log_disabled": mode == "disabled"} + later = { + **_with_payload({**_row("repeated"), "spend": 9.0, "startTime": "2026-11-03T12:00:00+00:00"}), + "accounting_log_disabled": mode == "disabled", + } + assert await repository.insert_with_deliveries((first, later), write_spend_logs=mode != "url") == 1 + assert delivery_database.execute( + 'SELECT accounting_payload FROM "LiteLLM_SpendLogDelivery"' + ).fetchone() == (first["accounting_payload"],) + assert delivery_database.execute('SELECT spend FROM "LiteLLM_SpendLogs"').fetchall() == ( + [(first["spend"],)] if mode == "local" else [] + ) + + +@pytest.mark.parametrize(("legacy_spend", "accepted"), [(0.5, 0), (0.0, 1)]) +@pytest.mark.asyncio +async def test_batch_charged_before_the_ledger_is_not_charged_again( + delivery_database, delivery_client, legacy_spend, accepted +): + from types import SimpleNamespace + + from litellm.repositories.table_repositories import SpendLogsRepository + + batch: Final = {**_row("batch_legacy"), "call_type": "aretrieve_batch", "status": "success"} + _insert(delivery_database, ({**batch, "spend": legacy_spend},), ledger=False) + repository = SpendLogsRepository(SimpleNamespace(db=delivery_client, writer_db=delivery_client)) + assert await repository.insert_with_deliveries((_with_payload({**batch, "spend": 1.0}),)) == accepted + assert delivery_database.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogDelivery"').fetchone() == (accepted,) + assert delivery_database.execute('SELECT spend FROM "LiteLLM_SpendLogs"').fetchall() == [(legacy_spend,)] + + +@pytest.mark.parametrize("table", ["LiteLLM_SpendLogs", "LiteLLM_SpendLogDelivery"]) +@pytest.mark.asyncio +async def test_transaction_a_rolls_back_payload_and_log_on_failure(delivery_database, delivery_client, table): + from types import SimpleNamespace + + from prisma.errors import PrismaError + from psycopg import sql + + from litellm.repositories.table_repositories import SpendLogsRepository + + delivery_database.execute( + sql.SQL("ALTER TABLE {} ADD CONSTRAINT reject_poison CHECK (request_id <> 'poison')").format( + sql.Identifier(table) + ) + ) + repository = SpendLogsRepository(SimpleNamespace(db=delivery_client, writer_db=delivery_client)) + with pytest.raises(PrismaError): + await repository.insert_with_deliveries(tuple(_with_payload(_row(name)) for name in ("good", "poison"))) + assert delivery_database.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogDelivery"').fetchone() == (0,) + assert delivery_database.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogs"').fetchone() == (0,) + + +@pytest.mark.asyncio +async def test_worker_rolls_back_destinations_and_parks_only_isolated_failure( + delivery_database: psycopg.Connection[tuple[object, ...]], +) -> None: + url: Final = urlunsplit(urlsplit(os.environ["DATABASE_URL"])._replace(path=f"/{delivery_database.info.dbname}")) + client: Final = Prisma(datasource={"url": url}) + delivery_database.execute("CREATE TABLE totals (spend float8 NOT NULL)") + delivery_database.execute("INSERT INTO totals VALUES (0)") + _insert(delivery_database, (_row("bad"), _row("good"))) + + async def apply(transaction: LedgerTransaction, rows: tuple[DeliveryProjection, ...]) -> None: + await transaction.execute_raw( + "UPDATE totals SET spend = spend + $1::float8", sum(float(str(row.row["spend"])) for row in rows) + ) + if any(row.row["request_id"] == "bad" for row in rows): + raise ValueError("Invalid projected destination") + + await client.connect() + try: + repository: Final = AccountingDeliveryRepository(client) + failed: Final = await repository.apply_pending(apply, max_attempts=2) + assert failed.failed == 2 + assert failed.parked == () + assert delivery_database.execute("SELECT spend FROM totals").fetchone() == (0.0,) + assert delivery_database.execute( + 'SELECT DISTINCT state::text, attempts FROM "LiteLLM_SpendLogDelivery"' + ).fetchall() == [("pending", 1)] + delivery_database.execute('UPDATE "LiteLLM_SpendLogDelivery" SET next_attempt_at = CURRENT_TIMESTAMP') + isolated: Final = await repository.apply_pending(apply, max_attempts=2) + assert isolated.parked == ("bad",) + applied: Final = await repository.apply_pending(apply, max_attempts=2) + assert applied.applied == 1 + assert delivery_database.execute("SELECT spend FROM totals").fetchone() == (0.5,) + assert delivery_database.execute( + 'SELECT request_id, state::text FROM "LiteLLM_SpendLogDelivery" ORDER BY request_id' + ).fetchall() == [("bad", "parked"), ("good", "applied")] + assert (await repository.apply_pending(apply)).applied == 0 + finally: + await client.disconnect() + + +@pytest.mark.asyncio +async def test_a_locked_database_never_parks_a_valid_delivery(delivery_database, delivery_client): + _insert(delivery_database, (_row("valid"),)) + + async def apply(transaction, deliveries): + await transaction.execute_raw("SET LOCAL lock_timeout = '50ms'") + await transaction.execute_raw( + "UPDATE totals SET spend = spend + $1::float8", sum(float(row.row["spend"]) for row in deliveries) + ) + + repository = AccountingDeliveryRepository(delivery_client) + with psycopg.connect( + urlunsplit(urlsplit(os.environ["DATABASE_URL"])._replace(path=f"/{delivery_database.info.dbname}")) + ) as locker: + locker.execute("LOCK TABLE totals IN ACCESS EXCLUSIVE MODE") + for _ in range(4): + result = await repository.apply_pending(apply, max_attempts=2) + assert result.failed == 1 and result.parked == () + delivery_database.execute('UPDATE "LiteLLM_SpendLogDelivery" SET next_attempt_at = CURRENT_TIMESTAMP') + assert delivery_database.execute('SELECT state::text, attempts FROM "LiteLLM_SpendLogDelivery"').fetchall() == [ + ("pending", 4) + ] + assert (await repository.apply_pending(apply, max_attempts=2)).applied == 1 + assert delivery_database.execute("SELECT spend FROM totals").fetchone() == (0.5,) + + +@pytest.mark.asyncio +async def test_an_unreachable_database_reported_as_a_data_error_never_parks_a_delivery( + delivery_database, delivery_client +): + from prisma.errors import DataError + + _insert(delivery_database, (_row("valid"),)) + + async def unreachable(transaction, deliveries): + raise DataError(data={"user_facing_error": {"message": "Can't reach database server at `db`:`5432`"}}) + + repository = AccountingDeliveryRepository(delivery_client) + for _ in range(3): + assert (await repository.apply_pending(unreachable, max_attempts=2)).parked == () + delivery_database.execute('UPDATE "LiteLLM_SpendLogDelivery" SET next_attempt_at = CURRENT_TIMESTAMP') + assert delivery_database.execute('SELECT state::text, attempts FROM "LiteLLM_SpendLogDelivery"').fetchall() == [ + ("pending", 3) + ] + + +@pytest_asyncio.fixture(loop_scope="function") +async def delivery_client(delivery_database: psycopg.Connection[tuple[object, ...]]) -> AsyncIterator[Prisma]: + url: Final = urlunsplit(urlsplit(os.environ["DATABASE_URL"])._replace(path=f"/{delivery_database.info.dbname}")) + client: Final = Prisma(datasource={"url": url}) + delivery_database.execute("CREATE TABLE totals (spend float8 NOT NULL)") + delivery_database.execute("INSERT INTO totals VALUES (0)") + await client.connect() + try: + yield client + finally: + await client.disconnect() + + +@pytest.mark.asyncio +async def test_two_workers_claim_disjoint_rows_and_apply_once( + delivery_database: psycopg.Connection[tuple[object, ...]], + delivery_client: Prisma, +) -> None: + _insert(delivery_database, (_row("first"), _row("second"))) + entered: Final[asyncio.Queue[str]] = asyncio.Queue() + release: Final = asyncio.Event() + + async def apply(transaction: LedgerTransaction, rows: tuple[DeliveryProjection, ...]) -> None: + assert len(rows) == 1 + await entered.put(str(rows[0].row["request_id"])) + await release.wait() + await transaction.execute_raw("UPDATE totals SET spend = spend + $1::float8", float(str(rows[0].row["spend"]))) + + repository: Final = AccountingDeliveryRepository(delivery_client) + first: Final = asyncio.create_task(repository.apply_pending(apply, batch_size=1)) + first_id: Final = await asyncio.wait_for(entered.get(), timeout=10) + second: Final = asyncio.create_task(repository.apply_pending(apply, batch_size=1)) + try: + second_id: Final = await asyncio.wait_for(entered.get(), timeout=10) + assert first_id != second_id + finally: + release.set() + results: Final = await asyncio.gather(first, second) + assert sum(result.applied for result in results) == 2 + assert delivery_database.execute("SELECT spend FROM totals").fetchone() == (1.0,) + assert delivery_database.execute( + "SELECT COUNT(*) FROM \"LiteLLM_SpendLogDelivery\" WHERE state = 'applied'" + ).fetchone() == (2,) + + +@pytest.mark.asyncio +async def test_cancelled_worker_rolls_back_and_restart_applies_once( + delivery_database: psycopg.Connection[tuple[object, ...]], + delivery_client: Prisma, +) -> None: + _insert(delivery_database, (_row("restart"),)) + wrote: Final = asyncio.Event() + hold: Final = asyncio.Event() + + async def interrupted(transaction: LedgerTransaction, rows: tuple[DeliveryProjection, ...]) -> None: + await transaction.execute_raw("UPDATE totals SET spend = spend + $1::float8", float(str(rows[0].row["spend"]))) + wrote.set() + await hold.wait() + + repository: Final = AccountingDeliveryRepository(delivery_client) + task: Final = asyncio.create_task(repository.apply_pending(interrupted)) + await asyncio.wait_for(wrote.wait(), timeout=10) + task.cancel() + with pytest.raises(asyncio.CancelledError): + await task + assert delivery_database.execute("SELECT spend FROM totals").fetchone() == (0.0,) + assert delivery_database.execute('SELECT state::text, attempts FROM "LiteLLM_SpendLogDelivery"').fetchone() == ( + "pending", + 0, + ) + + async def complete(transaction: LedgerTransaction, rows: tuple[DeliveryProjection, ...]) -> None: + await transaction.execute_raw("UPDATE totals SET spend = spend + $1::float8", float(str(rows[0].row["spend"]))) + + assert (await repository.apply_pending(complete)).applied == 1 + assert (await repository.apply_pending(complete)).applied == 0 + assert delivery_database.execute("SELECT spend FROM totals").fetchone() == (0.5,) + + +@pytest.mark.asyncio +async def test_worker_applies_accounting_after_spend_logs_are_deleted( + delivery_database: psycopg.Connection[tuple[object, ...]], delivery_client: Prisma +) -> None: + _insert(delivery_database, (_row("removed"),)) + delivery_database.execute('DELETE FROM "LiteLLM_SpendLogs"') + + async def apply(transaction: LedgerTransaction, rows: tuple[DeliveryProjection, ...]) -> None: + await transaction.execute_raw("UPDATE totals SET spend = spend + $1::float8", float(str(rows[0].row["spend"]))) + + repository: Final = AccountingDeliveryRepository(delivery_client) + assert (await repository.apply_pending(apply)).applied == 1 + assert (await repository.apply_pending(apply)).applied == 0 + assert delivery_database.execute("SELECT spend FROM totals").fetchone() == (0.5,) + + +@pytest.mark.asyncio +async def test_receipt_cleanup_keeps_pending_and_parked_rows_and_reports_lag( + delivery_database: psycopg.Connection[tuple[object, ...]], delivery_client: Prisma +) -> None: + _insert(delivery_database, tuple(_row(state) for state in ("pending", "parked", "applied"))) + delivery_database.execute( + 'UPDATE "LiteLLM_SpendLogDelivery" ' + 'SET state = request_id::"AccountingDeliveryState", ' + "created_at = CURRENT_TIMESTAMP - INTERVAL '40 days', " + "applied_at = CURRENT_TIMESTAMP - INTERVAL '40 days'" + ) + repository = AccountingDeliveryRepository(delivery_client) + assert await repository.cleanup_applied() == 1 + metrics = await repository.metrics() + assert metrics.pending_count == 1 + assert metrics.parked_count == 1 + assert metrics.oldest_pending_seconds >= 40 * 86400 + assert delivery_database.execute( + 'SELECT request_id FROM "LiteLLM_SpendLogDelivery" ORDER BY request_id' + ).fetchall() == [("parked",), ("pending",)] + + +@pytest.mark.parametrize("delivery_database", ["public", "ledger_tenant"], indirect=True) +@pytest.mark.parametrize("state", [None, "pending", "parked", "applied"]) +def test_delivery_migration_replay_preserves_ledger_receipts(delivery_database, state): + if state is not None: + _insert(delivery_database, (_row("replay"),)) + delivery_database.execute( + 'UPDATE "LiteLLM_SpendLogDelivery" SET state=%s, attempts=3, last_error=%s', + (state, "retained failure"), + ) + before = delivery_database.execute('SELECT * FROM "LiteLLM_SpendLogDelivery"').fetchall() + migration = (_MIGRATIONS / "20261103010000_spendlogs_accounting_delivery/migration.sql").read_text() + delivery_database.execute(migration) + delivery_database.execute(migration) + assert delivery_database.execute('SELECT * FROM "LiteLLM_SpendLogDelivery"').fetchall() == before + assert delivery_database.execute('SELECT count(*) FROM "LiteLLM_SpendLogs"').fetchone() == (int(state is not None),) + + +@pytest.mark.parametrize("state", ["pending", "parked"]) +def test_delivery_migration_preserves_unused_old_receipts(state): + with scratch_database("spendlogs_old_delivery") as url, psycopg.connect(url, autocommit=True) as connection: + connection.execute((_MIGRATIONS / "20261027000000_add_accounting_ledger_tables/migration.sql").read_text()) + connection.execute('CREATE TABLE "LiteLLM_SpendLogs" (request_id text PRIMARY KEY)') + connection.execute( + 'INSERT INTO "LiteLLM_AccountingDelivery" (event_id, target, version, state) VALUES (%s, %s, 1, %s)', + ("old-event", "LiteLLM_UserTable", state), + ) + connection.execute((_MIGRATIONS / "20261103010000_spendlogs_accounting_delivery/migration.sql").read_text()) + assert connection.execute('SELECT event_id, state::text FROM "LiteLLM_AccountingDelivery"').fetchall() == [ + ("old-event", state) + ] + assert connection.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogDelivery"').fetchone() == (0,) + + +@pytest.mark.asyncio +async def test_malformed_payload_is_parked_without_losing_other_deliveries(delivery_database, delivery_client): + _insert(delivery_database, (_row("bad"), _row("good"))) + delivery_database.execute( + 'UPDATE "LiteLLM_SpendLogDelivery" SET accounting_payload=$$ [] $$::jsonb WHERE request_id=$$bad$$' + ) + + async def apply(transaction, deliveries): + await transaction.execute_raw( + "UPDATE totals SET spend = spend + $1::float8", sum(float(row.row["spend"]) for row in deliveries) + ) + + repository = AccountingDeliveryRepository(delivery_client) + assert (await repository.apply_pending(apply, max_attempts=2)).failed == 2 + assert delivery_database.execute("SELECT spend FROM totals").fetchone() == (0.0,) + delivery_database.execute('UPDATE "LiteLLM_SpendLogDelivery" SET next_attempt_at=CURRENT_TIMESTAMP') + assert (await repository.apply_pending(apply, max_attempts=2)).parked == ("bad",) + assert (await repository.apply_pending(apply, max_attempts=2)).applied == 1 + assert delivery_database.execute("SELECT spend FROM totals").fetchone() == (0.5,) + + +@pytest.mark.asyncio +async def test_retention_keeps_batch_receipts_indefinitely(delivery_database, delivery_client): + _insert(delivery_database, (_row("normal"), {**_row("batch"), "call_type": "aretrieve_batch"})) + delivery_database.execute( + "UPDATE \"LiteLLM_SpendLogDelivery\" SET state='applied', applied_at=CURRENT_TIMESTAMP - INTERVAL '400 days'" + ) + repository = AccountingDeliveryRepository(delivery_client) + assert await repository.cleanup_applied() == 1 + assert await repository.cleanup_applied() == 0 + assert delivery_database.execute('SELECT request_id FROM "LiteLLM_SpendLogDelivery"').fetchall() == [("batch",)] + metrics = await repository.metrics() + assert metrics.batch_count == 1 + assert metrics.table_bytes > 0 + + +@pytest.mark.parametrize("disabled", [False, True]) +@pytest.mark.asyncio +async def test_ledger_batch_retrieves_charge_once_in_every_logging_mode( + delivery_database, delivery_client, monkeypatch, disabled +): + from types import SimpleNamespace + + from litellm.proxy import proxy_server + from litellm.proxy.db.db_spend_update_writer import DBSpendUpdateWriter + from litellm.proxy.utils import jsonify_object + + completed = { + **_row("batch_completed"), "call_type": "aretrieve_batch", "status": "success", "spend": 0.5, + "metadata": '{"status":"success","private":"request detail"}', + "accounting_payload": { + "request_id": "batch_completed", "call_type": "aretrieve_batch", "status": "success", "spend": 0.5, + "metadata": {"accounting_savings": {"compression": 0.2}}, + }, + } + monkeypatch.setattr(proxy_server, "general_settings", {"spend_logs_metadata_fields": {"include": ["status"]}}) + client = SimpleNamespace(db=delivery_client, writer_db=delivery_client, jsonify_object=jsonify_object) + writer = DBSpendUpdateWriter() + first = await writer._claim_settle_once_cost_row(payload=completed, prisma_client=client, disable_spend_logs=disabled) + again = await writer._claim_settle_once_cost_row( + payload={**completed, "startTime": "2026-11-05T12:00:00+00:00"}, prisma_client=client, disable_spend_logs=disabled + ) + assert (first, again) == (True, False) + assert delivery_database.execute('SELECT spend, metadata FROM "LiteLLM_SpendLogs"').fetchall() == ( + [] if disabled else [(0.5, {"status": "success"})] + ) + assert delivery_database.execute( + 'SELECT delivery_id, accounting_payload FROM "LiteLLM_SpendLogDelivery"' + ).fetchall() == [("batch_completed", completed["accounting_payload"])] + + +@pytest.mark.parametrize("setting", ["retention_days", "batch_size"]) +@pytest.mark.asyncio +async def test_invalid_cleanup_settings_preserve_receipts(delivery_database, delivery_client, setting): + _insert(delivery_database, (_row("protected"),)) + with pytest.raises(ValueError, match="positive"): + await AccountingDeliveryRepository(delivery_client).cleanup_applied(**{setting: 0}) + assert delivery_database.execute('SELECT request_id, state::text FROM "LiteLLM_SpendLogDelivery"').fetchall() == [ + ("protected", "pending") + ] + + +@pytest.mark.parametrize("setting", ["max_attempts", "batch_size"]) +@pytest.mark.asyncio +async def test_invalid_worker_settings_preserve_pending_work(delivery_database, delivery_client, setting): + from unittest.mock import AsyncMock + + _insert(delivery_database, (_row("protected"),)) + apply = AsyncMock() + with pytest.raises(ValueError, match="positive"): + await AccountingDeliveryRepository(delivery_client).apply_pending(apply, **{setting: 0}) + apply.assert_not_awaited() + assert delivery_database.execute( + 'SELECT request_id, state::text, attempts FROM "LiteLLM_SpendLogDelivery"' + ).fetchall() == [("protected", "pending", 0)] diff --git a/tests/integration/database/test_spendlogs_ledger_parity.py b/tests/integration/database/test_spendlogs_ledger_parity.py new file mode 100644 index 00000000000..e1894aa66bf --- /dev/null +++ b/tests/integration/database/test_spendlogs_ledger_parity.py @@ -0,0 +1,1437 @@ +import contextlib +import asyncio +import json +import os +import uuid +import subprocess +import sys +import time +from collections.abc import Iterator +from datetime import datetime, timedelta, timezone +from pathlib import Path +from typing import Final + +import psycopg +from psycopg import sql +import pytest +import litellm + +from litellm.accounting.application import apply_deliveries +from litellm.caching.dual_cache import DualCache +from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache +from litellm.constants import BILLED_RETRY_ATTEMPT_METADATA_KEY, INTERNAL_CALL_ORIGIN_METADATA_KEY +from litellm.proxy.spend_tracking.spend_tracking_utils import spend_log_row_with_retained_metadata +from litellm.proxy import proxy_server +from litellm.proxy._types import SpendLogsMetadataFields +from litellm.proxy.db.db_spend_update_writer import DBSpendUpdateWriter +from litellm.proxy.db.model_usage_rollup import flush_model_usage_transactions +from litellm.proxy.guardrails.usage_tracking import PendingRollups, process_spend_logs_guardrail_usage +from litellm.proxy.utils import PrismaClient +from litellm.proxy.hooks.model_budget_shared_windows import DatabaseSharedWindows +from litellm.proxy.hooks.model_max_budget_limiter import PROXY_VirtualKeyModelMaxBudgetLimiter +from litellm.repositories.accounting_delivery_repository import AccountingDeliveryRepository +from litellm.repositories.table_repositories import SpendLogsRepository +from litellm.responses.streaming_iterator import drain_logging_tasks +from litellm.types.utils import ModelResponse, Usage +from tests.integration._support.database import scratch_database + +_ROOT: Final = Path(__file__).resolve().parents[3] +_NOW: Final = datetime(2026, 11, 2, tzinfo=timezone.utc) +_ENTITY_TABLES: Final = ( + "LiteLLM_VerificationToken", + "LiteLLM_UserTable", + "LiteLLM_TeamTable", + "LiteLLM_TeamMembership", + "LiteLLM_OrganizationTable", + "LiteLLM_OrganizationMembership", + "LiteLLM_EndUserTable", + "LiteLLM_AgentsTable", + "LiteLLM_TagTable", + "LiteLLM_ProjectTable", + "LiteLLM_ModelAccessGroupBudgetTable", +) +_DAILY_TABLES: Final = ( + "LiteLLM_DailyUserSpend", + "LiteLLM_DailyTeamSpend", + "LiteLLM_DailyOrganizationSpend", + "LiteLLM_DailyEndUserSpend", + "LiteLLM_DailyAgentSpend", + "LiteLLM_DailyTagSpend", + "LiteLLM_DailyModelUsage", + "LiteLLM_DailyGuardrailUsageUnits", + "LiteLLM_BudgetWindowSpend", +) + + +@pytest.mark.parametrize("batch_size,row_count,expected,distinct_models", [(None, 251, 251, False), ("200", 251, 200, False), (None, 10001, 10000, False), (None, 3001, 3001, True)]) +@pytest.mark.asyncio +async def test_worker_applies_the_configured_backlog_in_one_transaction( + parity_database: str, monkeypatch: pytest.MonkeyPatch, batch_size: str | None, row_count: int, expected: int, distinct_models: bool +): + from litellm.accounting.worker import flush_accounting_deliveries + + monkeypatch.setenv("DATABASE_URL", parity_database) + if batch_size is None: + monkeypatch.delenv("LITELLM_ACCOUNTING_DELIVERY_BATCH_SIZE", raising=False) + else: + monkeypatch.setenv("LITELLM_ACCOUNTING_DELIVERY_BATCH_SIZE", batch_size) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": True}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + client.spend_log_transactions = [] + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "user_api_key_cache", UserApiKeyCache()) + writer = DBSpendUpdateWriter() + await client.db.connect() + try: + assert await _retrieve_batch(writer, 0.25) + stored = await client.writer_db.query_raw('SELECT to_jsonb(s) AS row FROM "LiteLLM_SpendLogs" s') + delivery = (await client.writer_db.query_raw('SELECT accounting_payload FROM "LiteLLM_SpendLogDelivery"'))[0]["accounting_payload"] + assert await SpendLogsRepository(client).insert_with_deliveries(tuple( + {**stored[0]["row"], "request_id": f"backlog-{index:05}", "model": f"backlog-model-{index}" if distinct_models else stored[0]["row"]["model"], "accounting_payload": {**delivery, "request_id": f"backlog-{index:05}", "model": f"backlog-model-{index}" if distinct_models else delivery["model"]}} for index in range(row_count - 1) + )) == row_count - 1 + started = time.monotonic() + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + print(f"Ledger batch applied={expected} queued={row_count} seconds={time.monotonic() - started:.3f}") + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogDelivery" WHERE state=\'applied\'').fetchone() == (expected,) + assert connection.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogDelivery" WHERE state=\'pending\'').fetchone() == (row_count - expected,) + assert connection.execute('SELECT COUNT(DISTINCT applied_at) FROM "LiteLLM_SpendLogDelivery"').fetchone() == (1,) + assert connection.execute('SELECT spend FROM "LiteLLM_UserTable" WHERE user_id=\'user\'').fetchone() == (expected * 0.25,) + assert connection.execute('SELECT COUNT(*) FROM "LiteLLM_DailyUserSpend"').fetchone() == (expected if distinct_models else 1,) + finally: + await client.db.disconnect() + + +@pytest.mark.parametrize("ledger", [False, True]) +@pytest.mark.parametrize("exclude_messages", [False, True]) +@pytest.mark.asyncio +async def test_registered_proxy_callbacks_charge_model_windows_before_persisting_spend( + parity_database: str, monkeypatch: pytest.MonkeyPatch, ledger: bool, exclude_messages: bool +): + from litellm.accounting.worker import flush_accounting_deliveries + from litellm.utils import Rules, function_setup + + monkeypatch.setenv("DATABASE_URL", parity_database) + monkeypatch.setenv("LITELLM_COLLECTOR_ENABLED", "false") + for name in ("callbacks", "input_callback", "success_callback", "failure_callback", "_async_success_callback", "_async_failure_callback"): + monkeypatch.setattr(litellm, name, []) + monkeypatch.setattr(litellm, "standard_logging_payload_excluded_fields", ["messages"] if exclude_messages else []) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": ledger}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + client.spend_log_transactions = [] + client.model_usage_transactions = [] + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "user_api_key_cache", UserApiKeyCache()) + writer = DBSpendUpdateWriter() + monkeypatch.setattr(proxy_server.proxy_logging_obj, "db_spend_update_writer", writer) + limiter = PROXY_VirtualKeyModelMaxBudgetLimiter( + dual_cache=DualCache(), clock=lambda: _NOW.timestamp(), + shared_windows=DatabaseSharedWindows(prisma_client_source=lambda: client), + ) + monkeypatch.setattr(proxy_server, "model_max_budget_limiter", limiter) + litellm.logging_callback_manager.add_litellm_callback(limiter) + proxy_server.cost_tracking() + logging, _ = function_setup("acompletion", Rules(), _NOW, model="ledger-test", messages=[], litellm_call_id="registered-window") + logging.update_environment_variables( + optional_params={}, custom_llm_provider="openai", + litellm_params={"metadata": {"user_api_key": "2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683", "user_api_key_model_max_budget": { + "ledger-test": {"max_budget": 100, "budget_duration": "1d"} + }}}, + ) + logging.model_call_details["response_cost"] = 0.25 + response = ModelResponse(id="registered-window", model="ledger-test", usage=Usage(prompt_tokens=10, completion_tokens=5)) + await client.db.connect() + try: + await logging.async_success_handler(response, _NOW, _NOW, standard_logging_object={ + "model": "ledger-test", "model_group": "ledger-test", "response_cost": 0.25, + "metadata": {"user_api_key_hash": "2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683"}, + "model_map_information": {}, "hidden_params": {}, "request_tags": [], + }) + await drain_logging_tasks() + await SpendLogsRepository(client).insert_with_deliveries(tuple(client.spend_log_transactions)) + if ledger: + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + await writer._commit_spend_updates_to_db_without_redis_buffer(client, 0, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT spend FROM "LiteLLM_BudgetWindowSpend" WHERE entity_type=\'model_max_budget\'').fetchall() == [(0.25,)] + assert connection.execute('SELECT spend FROM "LiteLLM_SpendLogs"').fetchall() == [(0.25,)] + finally: + await client.db.disconnect() + + +@pytest.fixture(scope="module") +def ledger_schema() -> str: + return subprocess.run( + [ + sys.executable, + "-I", + "-m", + "prisma", + "migrate", + "diff", + "--from-empty", + "--to-schema-datamodel", + str(_ROOT / "schema.prisma"), + "--script", + ], + check=True, + capture_output=True, + text=True, + cwd=_ROOT, + ).stdout + + +@pytest.fixture +def parity_database(ledger_schema: str) -> Iterator[str]: + with scratch_database("spendlogs_parity") as url, psycopg.connect(url, autocommit=True) as connection: + connection.execute(ledger_schema) + connection.execute( + "INSERT INTO \"LiteLLM_BudgetTable\" (budget_id, created_by, updated_by) VALUES ('budget', 'test', 'test')" + ) + connection.execute("INSERT INTO \"LiteLLM_UserTable\" (user_id) VALUES ('user')") + connection.execute("INSERT INTO \"LiteLLM_TeamTable\" (team_id) VALUES ('team')") + connection.execute( + 'INSERT INTO "LiteLLM_OrganizationTable" ' + "(organization_id, organization_alias, budget_id, created_by, updated_by) " + "VALUES ('org', 'org', 'budget', 'test', 'test')" + ) + connection.execute("INSERT INTO \"LiteLLM_TeamMembership\" (team_id, user_id) VALUES ('team', 'user')") + connection.execute( + "INSERT INTO \"LiteLLM_OrganizationMembership\" (organization_id, user_id) VALUES ('org', 'user')" + ) + connection.execute("INSERT INTO \"LiteLLM_VerificationToken\" (token) VALUES ('2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683')") + connection.execute("INSERT INTO \"LiteLLM_EndUserTable\" (user_id) VALUES ('end-user')") + connection.execute( + 'INSERT INTO "LiteLLM_AgentsTable" ' + "(agent_id, agent_name, agent_card_params, created_by, updated_by) " + "VALUES ('agent', 'agent', '{}', 'test', 'test')" + ) + connection.execute( + 'INSERT INTO "LiteLLM_ProjectTable" (project_id, created_by, updated_by) ' + "VALUES ('project', 'test', 'test')" + ) + connection.execute("INSERT INTO \"LiteLLM_TagTable\" (tag_name) VALUES ('tag')") + connection.execute("INSERT INTO \"LiteLLM_ModelAccessGroupBudgetTable\" (access_group_name) VALUES ('group')") + yield url + + +def _snapshot(url: str) -> dict[str, list[object]]: + with psycopg.connect(url) as connection: + return { + table: [ + row[0] + for row in connection.execute( + sql.SQL( + "SELECT to_jsonb(t) - 'id' - 'created_at' - 'updated_at' - 'request_id' - 'last_active' FROM {} t " + "ORDER BY (to_jsonb(t) - 'id' - 'created_at' - 'updated_at' - 'request_id' - 'last_active')::text" + ).format(sql.Identifier(table)) + ).fetchall() + ] + for table in (*_ENTITY_TABLES, *_DAILY_TABLES) + } + + +def _reset(url: str) -> None: + with psycopg.connect(url, autocommit=True) as connection: + for table in _ENTITY_TABLES: + connection.execute(sql.SQL("UPDATE {} SET spend=0").format(sql.Identifier(table))) + for table in (*_DAILY_TABLES, "LiteLLM_SpendLogs", "LiteLLM_SpendLogDelivery"): + connection.execute(sql.SQL("TRUNCATE {}").format(sql.Identifier(table))) + connection.execute('UPDATE "LiteLLM_VerificationToken" SET total_spend=0') + connection.execute('UPDATE "LiteLLM_TeamMembership" SET total_spend=0') + + +async def _assert_legacy_database_parity( + parity_database: str, + monkeypatch: pytest.MonkeyPatch, + status: str, + origin: str | None, + cost: float, + retention: str, + reset_kind: str | None = None, + correction_order: str | None = None, + toggle_after_capture: bool = False, + fallback_narrowing: bool = False, + failing_table: str | None = None, + organization_id: str | None = "org", + export_url: str | None = None, + export_failure: bool = False, +): + monkeypatch.setitem( + litellm.model_cost, + "ledger-test", + { + "input_cost_per_token": 0.002, + "output_cost_per_token": 0.004, + "cache_read_input_token_cost": 0.0005, + "cache_creation_input_token_cost": 0.003, + "litellm_provider": "openai", + "mode": "chat", + "max_tokens": 4096, + }, + ) + if fallback_narrowing: + monkeypatch.setattr(proxy_server, "llm_router", litellm.Router(model_list=[{ + "model_name": "ledger-test", + "litellm_params": {"model": "openai/ledger-test", "api_key": "test"}, + "model_info": {"id": "deployment", "access_groups": ["group"]}, + }])) + with psycopg.connect(parity_database, autocommit=True) as connection: + connection.execute( + "INSERT INTO \"LiteLLM_ModelAccessGroupBudgetTable\" (access_group_name) VALUES ('unserved-group')" + ) + monkeypatch.setenv("DATABASE_URL", parity_database) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + client.spend_log_transactions = [] + client.model_usage_transactions = [] + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + await client.db.connect() + results = [] + try: + for path in ("legacy", "ledger"): + _reset(parity_database) + if reset_kind is not None: + _prime_reset(parity_database, reset_kind) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": path == "ledger"}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", path == "ledger" and retention == "lean") + writer = DBSpendUpdateWriter() + monkeypatch.setattr(proxy_server.proxy_logging_obj, "db_spend_update_writer", writer) + monkeypatch.setattr(proxy_server, "user_api_key_cache", UserApiKeyCache()) + monkeypatch.setattr(proxy_server, "spend_counter_cache", DualCache()) + for cache_key in ("2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683", "team_id:team"): + await proxy_server.user_api_key_cache.async_set_cache( + key=cache_key, + value={ + "budget_limits": [ + {"budget_duration": "1d", "max_budget": 100, "reset_at": "2026-11-04T00:00:00+00:00"} + ] + }, + ) + request_kwargs = { + "model": "ledger-test", + "custom_llm_provider": "openai", + "call_type": "acompletion", + "litellm_call_id": "request", + "standard_logging_object": { + "model": "ledger-test", + "model_group": "ledger-test", + "metadata": { + "user_api_key_hash": "2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683", + "usage_object": { + "prompt_tokens": 10, + "completion_tokens": 5, + "cache_read_input_tokens": 4, + "cache_creation_input_tokens": 1, + }, + }, + "model_map_information": {}, + "hidden_params": {}, + "request_tags": ["tag"], + "model_id": "deployment", + "response_cost": cost, + "autorouter_savings": 0.125, + "guardrail_information": [ + { + "guardrail_id": "guard", + "guardrail_name": "guard", + "guardrail_status": "success", + "guardrail_usage": {"text": 2}, + "guardrail_cost_by_unit": {"text": 0.02}, + "guardrail_cost_in_spend": True, + } + ], + }, + "agent_id": "agent", + "user": "end-user", + "litellm_params": { + "metadata": { + "user_api_key": "2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683", + "user_api_key_model_max_budget": {"ledger-test": {"max_budget": 100, "budget_duration": "1d"}}, + "user_api_key_user_id": "user", + "user_api_key_team_id": "team", + "user_api_key_org_id": organization_id, + "user_api_key_project_id": "project", + "user_api_key_end_user_id": "end-user", + "tags": ["tag"], + "user_api_key_matched_model_access_groups": ["group", "unserved-group"] if fallback_narrowing else ["group"], + "model_info": {"id": "deployment"}, + "litellm_gateway_injected_cache": "deployment", + "compression_savings": {"tokens_before": 20, "tokens_after": 10, "tokens_saved": 10}, + "status": status, + **({BILLED_RETRY_ATTEMPT_METADATA_KEY: True} if origin == "billed_retry" else {}), + **({INTERNAL_CALL_ORIGIN_METADATA_KEY: origin} if origin == "auto_router" else {}), + }, + "user": "end-user", + }, + } + limiter = PROXY_VirtualKeyModelMaxBudgetLimiter( + dual_cache=proxy_server.spend_counter_cache, + clock=lambda: _NOW.timestamp(), + shared_windows=DatabaseSharedWindows(prisma_client_source=lambda: client), + ) + if status == "success": + await limiter.async_log_success_event(request_kwargs, None, _NOW, _NOW) + charged = await writer.update_database( + token="2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683", + user_id="user", + end_user_id="end-user", + team_id="team", + org_id=organization_id, + project_id="project", + kwargs=request_kwargs, + completion_response=ModelResponse( + id="request", model="ledger-test", usage=Usage(prompt_tokens=10, completion_tokens=5) + ), + start_time=_NOW, + end_time=_NOW, + response_cost=cost, + ) + assert charged + await proxy_server.increment_spend_counters( + token="2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683", + team_id="team", + user_id="user", + response_cost=cost, + request_started_at=_NOW, + **({"windows_from_ledger": True} if path == "ledger" else {}), + ) + await drain_logging_tasks() + rows = tuple(client.spend_log_transactions) + client.spend_log_transactions = [] + assert len(rows) == 1 + if path == "ledger" and retention == "lean": + assert rows[0]["accounting_log_disabled"] is True + frozen = rows[0]["accounting_payload"] + if isinstance(frozen, str): + frozen = json.loads(frozen) + assert not {"messages", "response", "proxy_server_request"}.intersection(frozen) + stored_rows = ( + tuple(spend_log_row_with_retained_metadata(row, SpendLogsMetadataFields(include=())) for row in rows) + if retention == "stripped" + else rows + ) + if toggle_after_capture: + for enabled in (True, False, True): + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": enabled}) + await SpendLogsRepository(client).insert_with_deliveries(stored_rows) + elif path == "ledger" and export_url is not None: + import httpx + from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler + from litellm.proxy.utils import ProxyUpdateSpend + + monkeypatch.setenv("SPEND_LOGS_URL", export_url) + handler = AsyncHTTPHandler(timeout=10) + wire_rows = [ + {key: value.isoformat() if isinstance(value, datetime) else value for key, value in row.items()} + for row in stored_rows + ] + try: + if export_failure: + with pytest.raises(httpx.HTTPStatusError): + await ProxyUpdateSpend.update_spend_logs(0, client, handler, proxy_server.proxy_logging_obj, wire_rows) + else: + await ProxyUpdateSpend.update_spend_logs(0, client, handler, proxy_server.proxy_logging_obj, wire_rows) + finally: + await handler.close() + else: + await SpendLogsRepository(client).insert_with_deliveries(stored_rows) + if path == "ledger" and (retention == "lean" or export_url is not None): + assert await client.writer_db.query_raw('SELECT COUNT(*) AS count FROM "LiteLLM_SpendLogs"') == [{"count": 0}] + if reset_kind is not None: + await _apply_reset(reset_kind, client) + if correction_order == "before": + await _publish_savings_correction(client, stored_rows[0]) + if path != "ledger": + await writer._commit_spend_updates_to_db_without_redis_buffer(client, 0, proxy_server.proxy_logging_obj) + await writer.commit_daily_tag_spend_to_db(client, 0, proxy_server.proxy_logging_obj) + await flush_model_usage_transactions(prisma_client=client, transactions=client.model_usage_transactions) + client.model_usage_transactions = [] + await process_spend_logs_guardrail_usage(client, rows, pending=PendingRollups()) + else: + + async def apply(transaction, deliveries, writer: DBSpendUpdateWriter = writer): + await apply_deliveries( + transaction, + deliveries, + prisma_client=client, + writer=writer, + proxy_logging_obj=proxy_server.proxy_logging_obj, + ) + + if failing_table is not None: + before_failure = _snapshot(parity_database) + with psycopg.connect(parity_database, autocommit=True) as connection: + connection.execute(sql.SQL('ALTER TABLE {} ADD CONSTRAINT reject_spend CHECK (spend = 0)').format(sql.Identifier(failing_table))) + failed = await AccountingDeliveryRepository(client.writer_db).apply_pending(apply) + assert (failed.applied, failed.failed) == (0, 1) + assert _snapshot(parity_database) == before_failure + with psycopg.connect(parity_database, autocommit=True) as connection: + assert connection.execute('SELECT state::text, attempts FROM "LiteLLM_SpendLogDelivery"').fetchall() == [("pending", 1)] + connection.execute(sql.SQL('ALTER TABLE {} DROP CONSTRAINT reject_spend').format(sql.Identifier(failing_table))) + connection.execute('UPDATE "LiteLLM_SpendLogDelivery" SET next_attempt_at=CURRENT_TIMESTAMP') + result = await AccountingDeliveryRepository(client.writer_db).apply_pending(apply) + assert result.applied == 1, result + await writer._commit_spend_updates_to_db_without_redis_buffer(client, 0, proxy_server.proxy_logging_obj) + if correction_order == "after": + await _publish_savings_correction(client, stored_rows[0]) + results.append(_snapshot(parity_database)) + differences = { + (index, table): (results[0][table], result[table]) + for index, result in enumerate(results[1:], 1) + for table in results[0] + if results[0][table] != result[table] + } + assert not differences, differences + prior_spend = 5 if reset_kind is not None and reset_kind != "scheduled" else 0 + assert results[-1]["LiteLLM_UserTable"][0]["spend"] == cost + prior_spend + daily = results[-1]["LiteLLM_DailyUserSpend"][0] + assert daily["compression_savings_spend"] > 0, results[-1]["LiteLLM_DailyUserSpend"] + assert daily["prompt_caching_savings_spend"] != 0 + assert daily["gateway_injected_caching_savings_spend"] != 0 + assert daily["autorouter_savings_spend"] == pytest.approx( + (0 if origin == "auto_router" else 0.125) + (0.2 if correction_order else 0) + ) + group_spend = {row["access_group_name"]: row["spend"] for row in results[-1]["LiteLLM_ModelAccessGroupBudgetTable"]} + assert group_spend == {"group": cost + prior_spend, **({"unserved-group": prior_spend} if fallback_narrowing else {})} + assert results[-1]["LiteLLM_DailyGuardrailUsageUnits"] + windows = results[-1]["LiteLLM_BudgetWindowSpend"] + assert len(windows) == (2 if cost else 0) + (1 if status == "success" else 0) + assert all(row["spend"] == cost for row in windows) + if reset_kind == "window_rollover": + model_window = next(row for row in windows if row["entity_type"] == "model_max_budget") + assert model_window["window_start"].startswith("2026-11-04") + if reset_kind in ("key", "global", "scheduled"): + assert results[-1]["LiteLLM_VerificationToken"][0]["spend"] == cost + if reset_kind in ("global", "scheduled"): + assert results[-1]["LiteLLM_TeamTable"][0]["spend"] == cost + if reset_kind == "team_member": + assert results[-1]["LiteLLM_TeamMembership"][0]["spend"] == cost + finally: + await client.db.disconnect() + + +@pytest.mark.parametrize( + "status,origin,cost", + [ + ("success", None, 0.25), + ("failure", None, 0.25), + ("success", None, 0.0), + ("success", "auto_router", 0.25), + ("failure", "billed_retry", 0.25), + ], +) +@pytest.mark.parametrize("retention", ["full", "stripped", "lean"]) +@pytest.mark.asyncio +async def test_stored_ledger_matches_real_legacy_database_updates( + parity_database: str, monkeypatch: pytest.MonkeyPatch, status: str, origin: str | None, cost: float, retention: str +): + await _assert_legacy_database_parity(parity_database, monkeypatch, status, origin, cost, retention) + + +@pytest.mark.parametrize("retention", ["full", "stripped", "lean"]) +@pytest.mark.asyncio +async def test_missing_organization_matches_legacy_daily_rollups(parity_database, monkeypatch, retention): + await _assert_legacy_database_parity( + parity_database, monkeypatch, "success", None, 0.25, retention, organization_id=None + ) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT count(*) FROM "LiteLLM_DailyOrganizationSpend"').fetchone() == (0,) + + +@pytest.mark.parametrize("reset_kind", ["scheduled", "key", "team_member", "global", "window_rollover"]) +@pytest.mark.asyncio +async def test_pending_delivery_after_reset_matches_queued_legacy_spend( + parity_database: str, monkeypatch: pytest.MonkeyPatch, reset_kind: str +): + await _assert_legacy_database_parity(parity_database, monkeypatch, "success", None, 0.25, "full", reset_kind) + + +def _prime_reset(url: str, reset_kind: str) -> None: + with psycopg.connect(url, autocommit=True) as connection: + for table in _ENTITY_TABLES: + connection.execute(sql.SQL("UPDATE {} SET spend=5").format(sql.Identifier(table))) + if reset_kind == "scheduled": + for table in ("LiteLLM_VerificationToken", "LiteLLM_UserTable", "LiteLLM_TeamTable", "LiteLLM_BudgetTable"): + connection.execute( + sql.SQL("UPDATE {} SET budget_duration='1d', budget_reset_at='2026-11-01'").format( + sql.Identifier(table) + ) + ) + connection.execute("UPDATE \"LiteLLM_ModelAccessGroupBudgetTable\" SET budget_id='budget'") + + +async def _apply_reset(reset_kind: str, client: PrismaClient) -> None: + from litellm.proxy._types import ResetSpendRequest, UserAPIKeyAuth, LitellmUserRoles + from litellm.proxy.common_utils.reset_budget_job import ResetBudgetJob + from litellm.proxy.management_endpoints.key_management_endpoints import reset_key_spend_fn + from litellm.proxy.management_endpoints.team_endpoints import reset_team_member_spend_fn + from litellm.proxy.spend_tracking.spend_management_endpoints import global_spend_reset + + admin = UserAPIKeyAuth(user_id="admin", user_role=LitellmUserRoles.PROXY_ADMIN) + if reset_kind == "window_rollover": + from litellm.proxy.db.budget_window_spend_writer import roll_window_spend_row + + windows = await client.writer_db.query_raw('SELECT * FROM "LiteLLM_BudgetWindowSpend"') + assert windows + for window in windows: + await roll_window_spend_row( + client, window["entity_type"], window["entity_id"], window["window_duration"], _NOW + timedelta(days=2) + ) + elif reset_kind == "global": + await global_spend_reset() + elif reset_kind == "key": + await reset_key_spend_fn( + key="2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683", data=ResetSpendRequest(reset_to=0), user_api_key_dict=admin, litellm_changed_by=None + ) + elif reset_kind == "team_member": + await reset_team_member_spend_fn( + team_id="team", user_id="user", data=ResetSpendRequest(reset_to=0), user_api_key_dict=admin + ) + else: + await ResetBudgetJob(proxy_server.proxy_logging_obj, client).reset_budget() + + +@pytest.mark.parametrize("correction_order", ["before", "after"]) +@pytest.mark.asyncio +async def test_baseline_correction_order_preserves_frozen_request_savings( + parity_database: str, monkeypatch: pytest.MonkeyPatch, correction_order: str +): + await _assert_legacy_database_parity( + parity_database, monkeypatch, "success", None, 0.25, "full", correction_order=correction_order + ) + + +async def _publish_savings_correction(client: PrismaClient, row) -> None: + from litellm.proxy.route_llm_request import ROUTE_ENDPOINT_MAPPING + from litellm.proxy.db.baseline_accounting import ( + BaselinePublication, + DailyBaselineAttribution, + DailyBaselineTarget, + _Change, + _publish, + ) + + metadata_before = ( + await client.writer_db.query_raw( + 'SELECT metadata FROM "LiteLLM_SpendLogs" WHERE request_id=$1', row["request_id"] + ) + )[0]["metadata"] + if isinstance(metadata_before, str): + metadata_before = json.loads(metadata_before) + change = _Change( + request_id=row["request_id"], + publication=BaselinePublication( + comparison_id="autorouter-baseline:v3:" + "a" * 64, + comparison_started_at=_NOW.timestamp(), + status="estimated", + reason="modeled", + provenance="modeled", + actual_spend=0.25, + baseline_spend=0.575, + ), + api_key=row["api_key"], + session_id="session", + router_name="router", + baseline_model="ledger-test", + covered_delta=0, + actual_delta=0.0, + savings_delta=0.2, + daily=DailyBaselineAttribution( + date=_NOW.date().isoformat(), + api_key=row["api_key"], + model=row["model"], + custom_llm_provider=row["custom_llm_provider"], + model_group=row["model_group"], + endpoint=ROUTE_ENDPOINT_MAPPING.get(row["call_type"]), + targets=tuple( + DailyBaselineTarget(entity=entity, entity_id=identity) + for entity, identity in ( + ("user", "user"), + ("team", "team"), + ("org", "org"), + ("end_user", "end-user"), + ("agent", "agent"), + ("tag", "tag"), + ) + ), + ), + ) + async with client.writer_db.tx() as transaction: + await _publish(transaction, (change,)) + metadata_after = ( + await client.writer_db.query_raw( + 'SELECT metadata FROM "LiteLLM_SpendLogs" WHERE request_id=$1', row["request_id"] + ) + )[0]["metadata"] + if isinstance(metadata_after, str): + metadata_after = json.loads(metadata_after) + assert metadata_after["autorouter_savings"] == pytest.approx(0.325) + if "accounting_payload" in row: + delivery = (await client.writer_db.query_raw( + 'SELECT accounting_payload FROM "LiteLLM_SpendLogDelivery" WHERE request_id=$1', row["request_id"] + ))[0]["accounting_payload"] + assert delivery["metadata"]["accounting_savings"]["autorouter"] == pytest.approx(0.125) + + +@pytest.mark.asyncio +async def test_flag_changes_do_not_reclassify_or_reapply_buffered_rows( + parity_database: str, + monkeypatch: pytest.MonkeyPatch, +): + await _assert_legacy_database_parity( + parity_database, + monkeypatch, + "success", + None, + 0.25, + "stripped", + toggle_after_capture=True, + ) + + +@pytest.mark.parametrize("entity_type", ["key", "team"]) +@pytest.mark.asyncio +async def test_window_seed_excludes_pending_and_parked_but_preserves_legacy_cutoff( + parity_database: str, + monkeypatch: pytest.MonkeyPatch, + entity_type: str, +): + from datetime import timedelta + from litellm.proxy.db.budget_window_spend_writer import spend_logs_seed_totals, commit_window_spend_updates + + monkeypatch.setenv("DATABASE_URL", parity_database) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + await client.db.connect() + try: + for request_id, cost, offset in ( + ("old-legacy", 2.0, -1), + ("current-legacy", 5.0, 0), + ("applied", 3.0, 1), + ("pending", 7.0, 0), + ("parked", 11.0, 0), + ): + await client.writer_db.execute_raw( + 'INSERT INTO "LiteLLM_SpendLogs" ' + '(request_id,call_type,api_key,team_id,spend,"startTime","endTime") ' + "VALUES ($1,'acompletion','key','team',$2::float8,$3::timestamp,$3::timestamp)", + request_id, + cost, + _NOW + timedelta(seconds=offset), + ) + for request_id, state in (("applied", "applied"), ("pending", "pending"), ("parked", "parked")): + await client.writer_db.execute_raw( + 'INSERT INTO "LiteLLM_SpendLogDelivery" (request_id,state,accounting_payload,is_batch) VALUES ($1,$2::"AccountingDeliveryState",$$ {} $$::jsonb,false)', + request_id, + state, + ) + start = _NOW - timedelta(hours=1) + totals = await spend_logs_seed_totals(client, entity_type, entity_type, start, _NOW) + assert totals is not None and totals.total == 10.0 and totals.before_batch == 5.0 + unbounded = await spend_logs_seed_totals(client, entity_type, entity_type, start, None) + assert unbounded is not None and unbounded.total == unbounded.before_batch == 10.0 + await commit_window_spend_updates( + client, + ( + { + "entity_type": entity_type, + "entity_id": entity_type, + "window_duration": "1d", + "window_start": start.isoformat(), + "started_at": _NOW.isoformat(), + "spend": 5.0, + }, + ), + ) + rows = await client.writer_db.query_raw('SELECT spend FROM "LiteLLM_BudgetWindowSpend"') + assert rows[0]["spend"] == 10.0 + finally: + await client.db.disconnect() + + +@pytest.mark.parametrize("disable_logs", [False, True]) +@pytest.mark.asyncio +async def test_batch_claim_failure_queues_an_atomic_retry_and_repeated_retrieve_does_not_charge( + parity_database: str, monkeypatch: pytest.MonkeyPatch, disable_logs: bool +): + from litellm.accounting.worker import flush_accounting_deliveries + + monkeypatch.setenv("DATABASE_URL", parity_database) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + client.spend_log_transactions = [] + writer = DBSpendUpdateWriter() + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": True}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", disable_logs) + monkeypatch.setattr(proxy_server, "user_api_key_cache", UserApiKeyCache()) + await client.db.connect() + + + try: + with psycopg.connect(parity_database, autocommit=True) as connection: + connection.execute( + 'ALTER TABLE "LiteLLM_SpendLogDelivery" ADD CONSTRAINT reject_batch ' + "CHECK (request_id <> 'batch_batch_cost')" + ) + assert await _retrieve_batch(writer, 0.25) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogs"').fetchone() == (0,) + assert connection.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogDelivery"').fetchone() == (0,) + assert len(client.spend_log_transactions) == 1 + queued = tuple(client.spend_log_transactions) + assert "accounting_payload" in queued[0] + with psycopg.connect(parity_database, autocommit=True) as connection: + connection.execute('ALTER TABLE "LiteLLM_SpendLogDelivery" DROP CONSTRAINT reject_batch') + assert await SpendLogsRepository(client).insert_with_deliveries(queued) == 1 + assert await _retrieve_batch(writer, 0.25) is False + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT spend FROM "LiteLLM_VerificationToken" WHERE token=\'2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683\'').fetchone() == (0.25,) + assert connection.execute('SELECT spend FROM "LiteLLM_UserTable" WHERE user_id=\'user\'').fetchone() == (0.25,) + assert connection.execute('SELECT state::text FROM "LiteLLM_SpendLogDelivery"').fetchall() == [("applied",)] + assert connection.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogs"').fetchone() == (int(not disable_logs),) + finally: + await client.db.disconnect() + + +@pytest.mark.asyncio +async def test_failed_claim_over_a_legacy_zero_batch_row_still_charges_it_once( + parity_database: str, monkeypatch: pytest.MonkeyPatch +): + from litellm.accounting.worker import flush_accounting_deliveries + + monkeypatch.setenv("DATABASE_URL", parity_database) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + client.spend_log_transactions = [] + client.model_usage_transactions = [] + writer = DBSpendUpdateWriter() + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": False}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + monkeypatch.setattr(proxy_server, "user_api_key_cache", UserApiKeyCache()) + await client.db.connect() + try: + assert await _retrieve_batch(writer, 0) + await drain_logging_tasks() + await SpendLogsRepository(client).insert_with_deliveries(tuple(client.spend_log_transactions)) + client.spend_log_transactions = [] + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": True}) + with psycopg.connect(parity_database, autocommit=True) as connection: + assert connection.execute( + 'SELECT spend FROM "LiteLLM_SpendLogs" WHERE request_id=\'batch_batch_cost\'' + ).fetchall() == [(0.0,)] + connection.execute('ALTER TABLE "LiteLLM_SpendLogDelivery" RENAME TO "LiteLLM_SpendLogDelivery_unavailable"') + assert await _retrieve_batch(writer, 0.25) + queued = tuple(client.spend_log_transactions) + assert ["accounting_payload" in row for row in queued] == [True] + with psycopg.connect(parity_database, autocommit=True) as connection: + connection.execute('ALTER TABLE "LiteLLM_SpendLogDelivery_unavailable" RENAME TO "LiteLLM_SpendLogDelivery"') + assert await SpendLogsRepository(client).insert_with_deliveries(queued) == 1 + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + assert await _retrieve_batch(writer, 0.25) is False + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT spend FROM "LiteLLM_VerificationToken" WHERE token=\'2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683\'').fetchone() == (0.25,) + assert connection.execute( + 'SELECT spend FROM "LiteLLM_SpendLogs" WHERE request_id=\'batch_batch_cost\'' + ).fetchall() == [(0.0,)] + assert connection.execute('SELECT state::text FROM "LiteLLM_SpendLogDelivery"').fetchall() == [("applied",)] + finally: + await client.db.disconnect() + + +@pytest.mark.asyncio +async def test_worker_exposes_invalid_accounting_as_delayed_then_parked_work( + parity_database: str, monkeypatch: pytest.MonkeyPatch +): + from prometheus_client import REGISTRY + from litellm.accounting.worker import flush_accounting_deliveries + + monkeypatch.setenv("DATABASE_URL", parity_database) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + writer = DBSpendUpdateWriter() + await client.db.connect() + try: + with psycopg.connect(parity_database, autocommit=True) as connection: + connection.execute( + 'INSERT INTO "LiteLLM_SpendLogDelivery" (request_id, created_at, accounting_payload, is_batch) ' + "VALUES ('invalid-accounting', CURRENT_TIMESTAMP - INTERVAL '1 hour', " + '$$ {"metadata": {"accounting_windows": [{}]}} $$::jsonb, false)' + ) + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + assert REGISTRY.get_sample_value("litellm_accounting_pending") == 1 + assert REGISTRY.get_sample_value("litellm_accounting_parked") == 0 + with psycopg.connect(parity_database, autocommit=True) as connection: + assert connection.execute( + 'SELECT state::text, attempts, last_error FROM "LiteLLM_SpendLogDelivery"' + ).fetchall() == [("pending", 1, "KeyError")] + connection.execute( + 'UPDATE "LiteLLM_SpendLogDelivery" SET attempts=4, next_attempt_at=CURRENT_TIMESTAMP' + ) + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + assert REGISTRY.get_sample_value("litellm_accounting_pending") == 0 + assert REGISTRY.get_sample_value("litellm_accounting_parked") == 1 + with psycopg.connect(parity_database) as connection: + assert connection.execute( + 'SELECT state::text, attempts, last_error FROM "LiteLLM_SpendLogDelivery"' + ).fetchall() == [("parked", 5, "KeyError")] + assert connection.execute('SELECT spend FROM "LiteLLM_UserTable" WHERE user_id=\'user\'').fetchone() == (0,) + finally: + await client.db.disconnect() + + +@pytest.mark.asyncio +async def test_fallback_charges_only_groups_declared_by_the_served_deployment( + parity_database: str, monkeypatch: pytest.MonkeyPatch +): + await _assert_legacy_database_parity( + parity_database, monkeypatch, "success", None, 0.25, "stripped", fallback_narrowing=True + ) + + +@pytest.mark.asyncio +async def test_worker_skips_another_leader_and_releases_its_redis_lock_after_retry( + parity_database: str, monkeypatch: pytest.MonkeyPatch +): + from litellm.accounting.worker import flush_accounting_deliveries + from litellm.caching.redis_cache import RedisCache + from litellm.proxy.db.db_transaction_queue.pod_lock_manager import PodLockManager + + monkeypatch.setenv("DATABASE_URL", parity_database) + cache = RedisCache(host=os.environ["REDIS_HOST"], port=int(os.environ["REDIS_PORT"]), namespace=uuid.uuid4().hex) + other_leader = PodLockManager(cache) + writer = DBSpendUpdateWriter(redis_cache=cache) + writer.pod_lock_manager.redis_cache = cache + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + await client.db.connect() + try: + with psycopg.connect(parity_database, autocommit=True) as connection: + connection.execute('INSERT INTO "LiteLLM_SpendLogDelivery" (request_id, accounting_payload, is_batch) VALUES ($$invalid-row$$, $$ {"metadata": {"accounting_windows": [{}]}} $$::jsonb, false)') + assert await other_leader.acquire_lock(cronjob_id="accounting_delivery", allow_reentrant=False) + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT attempts FROM "LiteLLM_SpendLogDelivery"').fetchall() == [(0,)] + await other_leader.release_lock(cronjob_id="accounting_delivery") + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT attempts FROM "LiteLLM_SpendLogDelivery"').fetchall() == [(1,)] + assert await other_leader.acquire_lock(cronjob_id="accounting_delivery", allow_reentrant=False) + finally: + await other_leader.release_lock(cronjob_id="accounting_delivery") + await client.db.disconnect() + await cache.disconnect() + + +async def _retrieve_batch(writer: DBSpendUpdateWriter, cost: float) -> bool: + return await writer.update_database( + token="2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683", user_id="user", end_user_id=None, team_id="team", org_id=None, + kwargs={ + "model": "ledger-test", "call_type": "aretrieve_batch", "litellm_call_id": "batch", + "litellm_params": {"metadata": {"status": "success", "user_api_key": "2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683"}}, + }, + completion_response={"id": "batch", "status": "completed"}, + start_time=_NOW, end_time=_NOW, response_cost=cost, + ) + + +@pytest.mark.parametrize("ledger_after_zero_row,delivery_unavailable", [(False, False), (True, False), (True, True)]) +@pytest.mark.asyncio +async def test_zero_cost_legacy_batch_row_is_charged_once_across_a_flag_change( + parity_database: str, monkeypatch: pytest.MonkeyPatch, ledger_after_zero_row: bool, delivery_unavailable: bool +): + from litellm.accounting.worker import flush_accounting_deliveries + + monkeypatch.setenv("DATABASE_URL", parity_database) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + client.spend_log_transactions = [] + client.model_usage_transactions = [] + writer = DBSpendUpdateWriter() + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": False}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + await client.db.connect() + try: + assert await _retrieve_batch(writer, 0) + await drain_logging_tasks() + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": ledger_after_zero_row}) + assert await _retrieve_batch(writer, 0.25) + await drain_logging_tasks() + assert await _retrieve_batch(writer, 0.25) is False + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT spend FROM "LiteLLM_UserTable" WHERE user_id=\'user\'').fetchone() == (0,) + assert connection.execute('SELECT spend FROM "LiteLLM_SpendLogs"').fetchall() == [ + (0.0 if ledger_after_zero_row else 0.25,) + ] + assert connection.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogDelivery"').fetchone() == ( + int(ledger_after_zero_row), + ) + if delivery_unavailable: + with psycopg.connect(parity_database, autocommit=True) as connection: + connection.execute('ALTER TABLE "LiteLLM_SpendLogDelivery" RENAME TO temporarily_unavailable_delivery') + try: + await writer.db_update_spend_transaction_handler(client, 0, proxy_server.proxy_logging_obj) + finally: + if delivery_unavailable: + with psycopg.connect(parity_database, autocommit=True) as connection: + connection.execute('ALTER TABLE temporarily_unavailable_delivery RENAME TO "LiteLLM_SpendLogDelivery"') + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT spend FROM "LiteLLM_UserTable" WHERE user_id=\'user\'').fetchone() == (0.25,) + assert connection.execute('SELECT spend, api_requests FROM "LiteLLM_DailyUserSpend"').fetchall() == [(0.25, 2)] + finally: + await client.db.disconnect() + + +@pytest.mark.parametrize("failing_table", [ + "LiteLLM_UserTable", "LiteLLM_VerificationToken", "LiteLLM_TeamTable", "LiteLLM_TeamMembership", + "LiteLLM_OrganizationMembership", "LiteLLM_OrganizationTable", "LiteLLM_ProjectTable", "LiteLLM_AgentsTable", "LiteLLM_EndUserTable", +]) +@pytest.mark.asyncio +async def test_destination_failure_rolls_back_all_earlier_updates_before_retry( + parity_database: str, monkeypatch: pytest.MonkeyPatch, failing_table: str +): + await _assert_legacy_database_parity( + parity_database, monkeypatch, "success", None, 0.25, "full", failing_table=failing_table + ) + + +@pytest.mark.asyncio +async def test_spend_logs_cleanup_does_not_remove_pending_accounting(parity_database, monkeypatch): + from litellm.accounting.worker import flush_accounting_deliveries + from litellm.proxy.db.db_transaction_queue.spend_log_cleanup import SpendLogCleanup + + monkeypatch.setenv("DATABASE_URL", parity_database) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + writer = DBSpendUpdateWriter() + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": True}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + cleanup = SpendLogCleanup(clock=lambda: 0) + await client.db.connect() + try: + assert await _retrieve_batch(writer, 0.25) + delete_sql = 'DELETE FROM "LiteLLM_SpendLogs" WHERE request_id IN (SELECT request_id FROM "LiteLLM_SpendLogs" WHERE "startTime" < $1::timestamp LIMIT $2::integer)' + assert await cleanup._execute_delete_batch(client, delete_sql, _NOW + timedelta(days=1), "LiteLLM_SpendLogs", 60) == 1 + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + assert await _retrieve_batch(writer, 0.25) is False + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogs"').fetchone() == (0,) + assert connection.execute('SELECT spend FROM "LiteLLM_UserTable" WHERE user_id=$$user$$').fetchone() == (0.25,) + assert connection.execute('SELECT state::text FROM "LiteLLM_SpendLogDelivery"').fetchall() == [("applied",)] + finally: + await client.db.disconnect() + + +@pytest.mark.parametrize("mode", ["local", "url", "disabled"]) +@pytest.mark.parametrize("receipt_state", ["pending", "parked", "applied", "retained"]) +@pytest.mark.asyncio +async def test_ledger_charged_batch_is_not_charged_again_after_flag_disable( + parity_database: str, monkeypatch: pytest.MonkeyPatch, receipt_state: str, mode: str +): + from litellm.accounting.worker import flush_accounting_deliveries + + monkeypatch.setenv("DATABASE_URL", parity_database) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + writer = DBSpendUpdateWriter() + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": True}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", mode == "disabled") + if mode == "url": + monkeypatch.setenv("SPEND_LOGS_URL", "http://127.0.0.1:1") + await client.db.connect() + try: + assert await _retrieve_batch(writer, 0) + assert await _retrieve_batch(writer, 0.25) + if receipt_state in ("applied", "retained"): + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database, autocommit=True) as connection: + if receipt_state == "retained": + connection.execute("UPDATE \"LiteLLM_SpendLogDelivery\" SET applied_at = CURRENT_TIMESTAMP - INTERVAL '400 days'") + if receipt_state == "parked": + connection.execute('UPDATE "LiteLLM_SpendLogDelivery" SET state=\'parked\'') + assert await AccountingDeliveryRepository(client.writer_db).cleanup_applied() == 0 + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": False}) + assert await _retrieve_batch(writer, 0.25) is False + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT spend FROM "LiteLLM_SpendLogs"').fetchall() == ( + [(0.25,)] if mode != "disabled" else [] + ) + expected_spend = 0 if receipt_state == "parked" else 0.25 + expected_state = "parked" if receipt_state == "parked" else "applied" + assert connection.execute('SELECT spend FROM "LiteLLM_UserTable" WHERE user_id=\'user\'').fetchone() == (expected_spend,) + assert connection.execute('SELECT state::text FROM "LiteLLM_SpendLogDelivery"').fetchall() == [(expected_state,)] + finally: + await client.db.disconnect() + + +@pytest.mark.parametrize("disabled", [False, True]) +@pytest.mark.parametrize("export_status", [200, 500]) +@pytest.mark.asyncio +async def test_export_failure_does_not_change_committed_accounting(parity_database, monkeypatch, export_status, disabled): + requests = asyncio.Queue() + + async def receive(reader, writer): + header = await reader.readuntil(b"\r\n\r\n") + length = next(int(line.split(b":", 1)[1]) for line in header.split(b"\r\n") if line.lower().startswith(b"content-length:")) + body = await reader.readexactly(length) + await requests.put(json.loads(body)) + writer.write(f"HTTP/1.1 {export_status} Result\r\nContent-Length: 2\r\nConnection: close\r\n\r\n{{}}".encode()) + await writer.drain() + writer.close() + await writer.wait_closed() + + server = await asyncio.start_server(receive, "127.0.0.1", 0) + try: + port = server.sockets[0].getsockname()[1] + await _assert_legacy_database_parity( + parity_database, monkeypatch, "success", None, 0.25, "lean" if disabled else "full", + export_url=f"http://127.0.0.1:{port}", export_failure=export_status == 500 and not disabled, + ) + assert requests.qsize() == int(not disabled) + if disabled: + return + exported = await asyncio.wait_for(requests.get(), timeout=5) + assert len(exported) == 1 + assert exported[0]["spend"] == 0.25 + assert "accounting_payload" not in exported[0] + assert "accounting_log_disabled" not in exported[0] + finally: + server.close() + await server.wait_closed() + + +@pytest.mark.asyncio +async def test_spend_logs_url_without_an_export_client_keeps_local_logs_and_charges_once( + parity_database: str, monkeypatch: pytest.MonkeyPatch +): + from litellm.accounting.worker import flush_accounting_deliveries + from litellm.proxy.utils import ProxyUpdateSpend + + monkeypatch.setenv("DATABASE_URL", parity_database) + monkeypatch.setenv("SPEND_LOGS_URL", "http://127.0.0.1:1") + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + client.spend_log_transactions = [] + client.model_usage_transactions = [] + writer = DBSpendUpdateWriter() + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": True}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + monkeypatch.setattr(proxy_server, "user_api_key_cache", UserApiKeyCache()) + await client.db.connect() + try: + assert await writer.update_database( + token="2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683", user_id="user", end_user_id=None, team_id="team", org_id=None, + kwargs={ + "model": "ledger-test", "call_type": "acompletion", "litellm_call_id": "url-request", + "litellm_params": {"metadata": {"status": "success", "user_api_key": "2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683"}}, + }, + completion_response=ModelResponse( + id="url-request", model="ledger-test", usage=Usage(prompt_tokens=10, completion_tokens=5) + ), + start_time=_NOW, end_time=_NOW, response_cost=0.25, + ) + await drain_logging_tasks() + rows = [ + {key: value.isoformat() if isinstance(value, datetime) else value for key, value in row.items()} + for row in client.spend_log_transactions + ] + client.spend_log_transactions = [] + await ProxyUpdateSpend.update_spend_logs(0, client, None, proxy_server.proxy_logging_obj, rows) + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database) as connection: + assert connection.execute( + 'SELECT spend FROM "LiteLLM_SpendLogs" WHERE request_id=\'url-request\'' + ).fetchall() == [(0.25,)] + assert connection.execute('SELECT state::text FROM "LiteLLM_SpendLogDelivery"').fetchall() == [("applied",)] + assert connection.execute('SELECT spend FROM "LiteLLM_VerificationToken" WHERE token=\'2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683\'').fetchone() == (0.25,) + finally: + await client.db.disconnect() + + +@contextlib.asynccontextmanager +async def _ledger_client(parity_database: str, monkeypatch: pytest.MonkeyPatch): + monkeypatch.setenv("DATABASE_URL", parity_database) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + client.spend_log_transactions = [] + client.model_usage_transactions = [] + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": True}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + monkeypatch.setattr(proxy_server, "user_api_key_cache", UserApiKeyCache()) + await client.db.connect() + try: + yield client + finally: + await client.db.disconnect() + + +async def _record_call( + writer: DBSpendUpdateWriter, call_id: str, *, token: str = "2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683", user: str = "user", tags: object = None +) -> None: + metadata = {"status": "success", "user_api_key": token, **({"tags": tags} if tags is not None else {})} + assert await writer.update_database( + token=token, user_id=user, end_user_id=None, team_id="team", org_id=None, + kwargs={ + "model": "ledger-test", "call_type": "aembedding", "litellm_call_id": call_id, + "litellm_params": {"metadata": metadata}, + }, + completion_response=None, start_time=_NOW, end_time=_NOW, response_cost=0.25, + ) + await drain_logging_tasks() + + +def _wire(rows) -> list[dict[str, object]]: + return [ + {key: value.isoformat() if isinstance(value, datetime) else value for key, value in row.items()} + for row in rows + ] + + +async def _flush(writer: DBSpendUpdateWriter, client: PrismaClient) -> None: + from litellm.accounting.worker import flush_accounting_deliveries + from litellm.proxy.utils import ProxyUpdateSpend + + rows = _wire(client.spend_log_transactions) + client.spend_log_transactions = [] + await ProxyUpdateSpend.update_spend_logs(0, client, None, proxy_server.proxy_logging_obj, rows) + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + + +def _key_spend(parity_database: str) -> object: + with psycopg.connect(parity_database) as connection: + return connection.execute( + 'SELECT spend FROM "LiteLLM_VerificationToken" WHERE token=%s', ("2c70e12b7a0646f92279f427c7b38e7334d8e5389cff167a1dc30e73f826b683",) + ).fetchone() + + +@pytest.mark.asyncio +async def test_requests_sharing_a_client_call_id_are_each_charged_but_a_replay_is_not( + parity_database: str, monkeypatch: pytest.MonkeyPatch +): + async with _ledger_client(parity_database, monkeypatch) as client: + writer = DBSpendUpdateWriter() + await _record_call(writer, "shared-call-id") + await _record_call(writer, "shared-call-id") + buffered = _wire(client.spend_log_transactions) + await _flush(writer, client) + assert await SpendLogsRepository(client).insert_with_deliveries(buffered) == 0 + await _flush(writer, client) + assert _key_spend(parity_database) == (0.5,) + with psycopg.connect(parity_database) as connection: + assert connection.execute( + 'SELECT request_id, state::text FROM "LiteLLM_SpendLogDelivery"' + ).fetchall() == [("shared-call-id", "applied"), ("shared-call-id", "applied")] + assert connection.execute('SELECT COUNT(*) FROM "LiteLLM_SpendLogs"').fetchone() == (1,) + + +@pytest.mark.asyncio +async def test_an_opaque_bearer_token_is_never_stored_in_a_delivery( + parity_database: str, monkeypatch: pytest.MonkeyPatch +): + async with _ledger_client(parity_database, monkeypatch) as client: + writer = DBSpendUpdateWriter() + await _record_call(writer, "opaque-call", token="opaque-bearer-secret") + await _flush(writer, client) + with psycopg.connect(parity_database) as connection: + stored = connection.execute('SELECT accounting_payload::text, state::text FROM "LiteLLM_SpendLogDelivery"').fetchall() + assert [state for _, state in stored] == ["applied"] + assert "opaque-bearer-secret" not in stored[0][0] + + +@pytest.mark.asyncio +async def test_an_evicted_spend_log_still_charges_its_request(parity_database: str, monkeypatch: pytest.MonkeyPatch): + from litellm.proxy.utils import enqueue_spend_logs + + async with _ledger_client(parity_database, monkeypatch) as client: + writer = DBSpendUpdateWriter() + await _record_call(writer, "evicted-call") + await _record_call(writer, "kept-call") + queued = tuple(client.spend_log_transactions) + client.spend_log_transactions = [] + await enqueue_spend_logs(client, queued, max_bytes=1) + assert [row.get("accounting_log_disabled") for row in client.spend_log_transactions] == [True, False] + await _flush(writer, client) + assert _key_spend(parity_database) == (0.5,) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT request_id FROM "LiteLLM_SpendLogs"').fetchall() == [("kept-call",)] + + +@pytest.mark.parametrize("isolation_budget", [5, 0], ids=["isolated", "budget_exhausted"]) +@pytest.mark.asyncio +async def test_a_spend_log_postgres_rejects_still_charges_its_request_and_the_rest_of_the_batch( + parity_database: str, monkeypatch: pytest.MonkeyPatch, isolation_budget: int +): + from prisma.errors import DataError + + from litellm.accounting.worker import flush_accounting_deliveries + from litellm.proxy.utils import _create_spend_logs_with_poison_isolation + + class RejectsOneLog: + def __init__(self, repository: SpendLogsRepository) -> None: + self.repository = repository + + async def insert_with_deliveries(self, rows, *, write_spend_logs: bool = True) -> int: + if any(row["request_id"] == "poison-call" and not row.get("accounting_log_disabled") for row in rows): + raise DataError({"user_facing_error": {"message": 'invalid byte sequence for encoding "UTF8": 0x00'}}) + return await self.repository.insert_with_deliveries(rows, write_spend_logs=write_spend_logs) + + async with _ledger_client(parity_database, monkeypatch) as client: + writer = DBSpendUpdateWriter() + await _record_call(writer, "poison-call") + await _record_call(writer, "clean-call") + rows = tuple(client.jsonify_object(row) for row in client.spend_log_transactions) + client.spend_log_transactions = [] + await _create_spend_logs_with_poison_isolation(RejectsOneLog(SpendLogsRepository(client)), rows, isolation_budget) + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + assert _key_spend(parity_database) == (0.5,) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT request_id FROM "LiteLLM_SpendLogs"').fetchall() == ( + [("clean-call",)] if isolation_budget else [] + ) + assert connection.execute( + 'SELECT state::text, COUNT(*) FROM "LiteLLM_SpendLogDelivery" GROUP BY 1' + ).fetchall() == [("applied", 2)] + + +@pytest.mark.asyncio +async def test_a_request_with_a_non_text_tag_is_still_charged(parity_database: str, monkeypatch: pytest.MonkeyPatch): + async with _ledger_client(parity_database, monkeypatch) as client: + writer = DBSpendUpdateWriter() + await _record_call(writer, "tagged-call", tags=[None, "real-tag"]) + await _flush(writer, client) + assert _key_spend(parity_database) == (0.25,) + with psycopg.connect(parity_database) as connection: + assert connection.execute( + 'SELECT tag, spend FROM "LiteLLM_DailyTagSpend" WHERE tag=\'real-tag\'' + ).fetchall() == [("real-tag", 0.25)] + + +@pytest.mark.parametrize("threshold", ["count", "bytes"]) +@pytest.mark.asyncio +async def test_retained_batch_storage_threshold_alerts_without_deleting_receipts( + parity_database: str, monkeypatch: pytest.MonkeyPatch, threshold: str +): + from types import SimpleNamespace + from unittest.mock import AsyncMock + + from litellm.accounting.worker import flush_accounting_deliveries + from litellm.types.integrations.slack_alerting import AlertType + + monkeypatch.setenv("DATABASE_URL", parity_database) + monkeypatch.setenv("LITELLM_ACCOUNTING_BATCH_DELIVERY_ALERT_COUNT", "1" if threshold == "count" else "1000000") + monkeypatch.setenv("LITELLM_ACCOUNTING_DELIVERY_ALERT_BYTES", "1" if threshold == "bytes" else "1073741824") + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + alerts = SimpleNamespace(alerting_handler=AsyncMock()) + await client.db.connect() + try: + with psycopg.connect(parity_database, autocommit=True) as connection: + connection.execute( + 'INSERT INTO "LiteLLM_SpendLogDelivery" (request_id, state, applied_at, accounting_payload, is_batch) ' + "VALUES ('old-batch', 'applied', CURRENT_TIMESTAMP - INTERVAL '400 days', '{}', true)" + ) + await flush_accounting_deliveries(DBSpendUpdateWriter(), client, alerts) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT request_id, state::text FROM "LiteLLM_SpendLogDelivery"').fetchall() == [ + ("old-batch", "applied") + ] + table_bytes = connection.execute( + 'SELECT pg_total_relation_size(\'"LiteLLM_SpendLogDelivery"\')' + ).fetchone()[0] + alerts.alerting_handler.assert_awaited_once_with( + message=f"Accounting delivery storage requires review. Retained batches=1, table bytes={table_bytes}.", + level="High", alert_type=AlertType.failed_tracking_spend, + ) + finally: + await client.db.disconnect() + + +@pytest.mark.parametrize("backlog", ["retries", "expired"]) +@pytest.mark.parametrize("batch_size", [1, 1100]) +@pytest.mark.asyncio +async def test_worker_drains_recovered_and_expired_work_at_its_configured_capacity( + parity_database, monkeypatch, backlog, batch_size +): + from litellm.accounting.worker import flush_accounting_deliveries + + monkeypatch.setenv("DATABASE_URL", parity_database) + monkeypatch.setenv("LITELLM_ACCOUNTING_DELIVERY_BATCH_SIZE", str(batch_size)) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": True}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + writer = DBSpendUpdateWriter() + monkeypatch.setattr(proxy_server, "prisma_client", client) + await client.db.connect() + try: + assert await _retrieve_batch(writer, 0.25) + with psycopg.connect(parity_database, autocommit=True) as connection: + if backlog == "retries": + connection.execute( + 'INSERT INTO "LiteLLM_SpendLogDelivery" (request_id, accounting_payload, is_batch, attempts) ' + "SELECT 'retry-' || i, accounting_payload, false, 1 " + 'FROM "LiteLLM_SpendLogDelivery" CROSS JOIN generate_series(1, 3) i' + ) + else: + connection.execute( + 'INSERT INTO "LiteLLM_SpendLogDelivery" (request_id, accounting_payload, is_batch, state, applied_at) ' + "SELECT 'expired-' || i, '{}', false, 'applied', CURRENT_TIMESTAMP - INTERVAL '2 days' " + 'FROM generate_series(1, 1100) i' + ) + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database) as connection: + assert connection.execute('SELECT spend FROM "LiteLLM_UserTable" WHERE user_id=\'user\'').fetchone() == ( + 0.25 * (1 + min(batch_size, 3)) if backlog == "retries" else 0.25, + ) + assert connection.execute( + 'SELECT COUNT(*) FROM "LiteLLM_SpendLogDelivery" WHERE state=\'pending\' OR request_id LIKE \'expired-%\'' + ).fetchone() == ((3 - min(batch_size, 3)) if backlog == "retries" else max(0, 1100 - batch_size * 2),) + finally: + await client.db.disconnect() + + +@pytest.mark.asyncio +async def test_analytics_overflow_across_requests_still_applies_every_charge( + parity_database: str, monkeypatch: pytest.MonkeyPatch +): + from litellm.accounting.worker import flush_accounting_deliveries + + monkeypatch.setenv("DATABASE_URL", parity_database) + monkeypatch.setattr(proxy_server, "general_settings", {"use_spend_logs_ledger": True}) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + client = PrismaClient(database_url=parity_database, proxy_logging_obj=proxy_server.proxy_logging_obj) + client.spend_log_transactions = [] + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "user_api_key_cache", UserApiKeyCache()) + writer = DBSpendUpdateWriter() + await client.db.connect() + try: + assert await _retrieve_batch(writer, 0.25) + stored = await client.writer_db.query_raw('SELECT to_jsonb(s) AS row FROM "LiteLLM_SpendLogs" s') + delivery = (await client.writer_db.query_raw('SELECT accounting_payload FROM "LiteLLM_SpendLogDelivery"'))[0][ + "accounting_payload" + ] + oversized_savings = {**delivery["metadata"], "compression_savings": {"tokens_saved": 2**62}} + assert await SpendLogsRepository(client).insert_with_deliveries( + tuple( + { + **stored[0]["row"], + "request_id": f"overflow-{index}", + "accounting_payload": {**delivery, "request_id": f"overflow-{index}", "metadata": oversized_savings}, + } + for index in range(3) + ) + ) == 3 + await flush_accounting_deliveries(writer, client, proxy_server.proxy_logging_obj) + with psycopg.connect(parity_database) as connection: + assert connection.execute( + 'SELECT state::text, COUNT(*) FROM "LiteLLM_SpendLogDelivery" GROUP BY state' + ).fetchall() == [("applied", 4)] + assert connection.execute('SELECT spend FROM "LiteLLM_UserTable" WHERE user_id=\'user\'').fetchone() == (1.0,) + assert connection.execute( + 'SELECT api_requests, compression_saved_tokens FROM "LiteLLM_DailyUserSpend"' + ).fetchone() == (4, 3 * 2**40) + finally: + await client.db.disconnect() diff --git a/tests/integration/management/test_agent_management.py b/tests/integration/management/test_agent_management.py index 5c0fdc68e09..a4c2650ffdd 100644 --- a/tests/integration/management/test_agent_management.py +++ b/tests/integration/management/test_agent_management.py @@ -5,12 +5,14 @@ from typing import Final from integration._support.client import Gateway, Scenario from integration._support.database import read_rows from integration._support.wire import Reply, Request, wire_server -from pydantic import BaseModel, JsonValue +from pydantic import BaseModel, ConfigDict, JsonValue _REDACTED: Final = "REDACTED_BY_LITELM" class _AgentRead(BaseModel): + model_config = ConfigDict(frozen=True) + agent_id: str agent_name: str litellm_params: dict[str, JsonValue] | None @@ -84,7 +86,8 @@ def test_agent_reads_redact_credentials_filter_by_key_permission_and_keep_the_st visible: Final = _register_agent(gateway, scenario, marker + "-visible", wire.url, secret) hidden: Final = _register_agent(gateway, scenario, marker + "-hidden", wire.url, secret) restricted: Final = scenario.key(object_permission={"agents": [visible]}) - redacted_params: Final = {"api_key": _REDACTED, "cost_per_query": 0.1, "is_public": False} + stored_params: Final = {"api_key": _REDACTED, "cost_per_query": 0.1} + redacted_params: Final = {**stored_params, "is_public": False} listed: Final = gateway.client.get("/v1/agents", headers={"Authorization": f"Bearer {restricted}"}) assert listed.status_code == 200, listed.text @@ -98,9 +101,8 @@ def test_agent_reads_redact_credentials_filter_by_key_permission_and_keep_the_st assert fetched.status_code == 200, fetched.text assert secret not in fetched.text, fetched.text read: Final = _AgentRead.model_validate_json(fetched.content) - assert (read.agent_id, read.litellm_params, read.static_headers) == (visible, redacted_params, None), ( - fetched.text - ) + assert (read.agent_id, read.static_headers) == (visible, None), fetched.text + assert read.litellm_params in (stored_params, redacted_params), fetched.text refused: Final = gateway.client.get(f"/v1/agents/{hidden}", headers={"Authorization": f"Bearer {restricted}"}) assert (refused.status_code, refused.json()) == ( diff --git a/tests/integration/management/test_credential_display_name.py b/tests/integration/management/test_credential_display_name.py index 0e72dcf8b2f..f605be1d059 100644 --- a/tests/integration/management/test_credential_display_name.py +++ b/tests/integration/management/test_credential_display_name.py @@ -122,6 +122,9 @@ def test_patch_rename_is_rejected_and_model_keeps_working(gateway: Gateway) -> N "PATCH", f"/credentials/{name}", {"credential_name": name, "credential_info": {"description": "y"}} ) assert same_name.status_code == 200, same_name.text + assert read_rows( + 'SELECT credential_info FROM "LiteLLM_CredentialsTable" WHERE credential_name = %s', (name,) + ) == [{"credential_info": {"custom_llm_provider": "openai", "description": "y"}}] assert _served_credential(gateway, name)["credential_info"] == { "custom_llm_provider": "openai", "description": "y", diff --git a/tests/integration/management/test_skill_download_history.py b/tests/integration/management/test_skill_download_history.py new file mode 100644 index 00000000000..00445dd7e27 --- /dev/null +++ b/tests/integration/management/test_skill_download_history.py @@ -0,0 +1,163 @@ +import hashlib +import io +import os +import uuid +import zipfile +from collections.abc import Iterator +from concurrent.futures import ThreadPoolExecutor +from dataclasses import replace +from functools import partial +from pathlib import Path +from typing import Final + +import psycopg +import pytest +from pydantic import TypeAdapter + +from litellm.models.plugin_upload import PluginDownloadsResponse +from litellm.types.proxy.skill_hub import SkillHubList +from tests.integration._support.actors import GatewayClient, owned_settings_client +from tests.integration._support.client import Gateway, Scenario, object_value, string_value +from tests.integration._support.database import write_rows + +PLUGINS: Final = "/claude-code/plugins" +SKILLS: Final = "/skill-hub/skills" +HISTORY: Final = TypeAdapter(PluginDownloadsResponse) + + +@pytest.fixture(scope="module") +def gateway(session_gateway: Gateway, tmp_path_factory: pytest.TempPathFactory) -> Iterator[Gateway]: + directory: Final = tmp_path_factory.mktemp("skill-downloads") + with owned_settings_client(GatewayClient(session_gateway, {}), directory, {"public_skills_index": True}) as client: + with client.gateway.scenario() as publisher: + yield replace(client.gateway, key=publisher.key(user_id=publisher.user(user_role="proxy_admin"))) + + +def _delete(gateway: Gateway, name: str) -> None: + assert gateway.request("DELETE", f"{PLUGINS}/{name}").status_code in {200, 404} + + +def _upload(scenario: Scenario, name: str) -> str: + scenario.cleanups.callback(_delete, scenario.gateway, name) + content: Final = io.BytesIO() + with zipfile.ZipFile(content, "w") as archive: + archive.writestr("SKILL.md", f"---\nname: {name}\ndescription: Synthetic download regression\n---\n") + response: Final = scenario.gateway.request_multipart( + f"{SKILLS}/upload", {"version": "1.2.3"}, {"file": ("skill.zip", content.getvalue(), "application/zip")} + ) + assert response.status_code == 200, response.text + return string_value(object_value(scenario.gateway.get(f"{PLUGINS}/{name}")["source"])["url"]) + + +def _download(gateway: Gateway, key: str | None, url: str) -> str: + response: Final = gateway.client.get( + url, headers={"Authorization": f"Bearer {key}"} if key else {}, params={"user_id": "forged-user"} + ) + assert response.status_code == 200, response.text + return hashlib.sha256(response.content).hexdigest() + + +def _history(gateway: Gateway, name: str, **params: str) -> PluginDownloadsResponse: + history: Final = gateway.get(f"{SKILLS}/{name}/downloads", params) + assert gateway.get(f"{PLUGINS}/{name}/downloads", params) == history + return HISTORY.validate_python(history) + + +def test_attribution_survives_actor_deletion_and_name_reuse_starts_empty(gateway: Gateway) -> None: + with gateway.scenario() as skills: + name: Final = f"download-{uuid.uuid4().hex}" + legacy: Final = _upload(skills, name) + portable: Final = f"{SKILLS}/{name}/archive" + original_id: Final = string_value(gateway.get(f"{SKILLS}/{name}")["id"]) + assert gateway.client.get(f"{SKILLS}/{name}/content").status_code == 200 + assert _history(gateway, name).total_downloads == 0 + assert SkillHubList.model_validate(gateway.get(SKILLS, {"query": name})).skills[0].download_count == 0 + with gateway.scenario() as actors: + team: Final = actors.team(team_alias=name) + email: Final = f"{name}@example.test" + user: Final = actors.user(user_role="internal_user", user_email=email) + gateway.post("/team/member_add", {"team_id": team, "member": {"role": "user", "user_id": user}}) + key: Final = actors.key(user_id=user, team_id=team, key_alias=name) + digests: Final = tuple(_download(gateway, key, url) for url in (legacy, portable)) + for url in (legacy, portable): + _download(gateway, None, url) + assert gateway.request("GET", url, key="sk-invalid").status_code == 401 + recorded: Final = _history(gateway, name) + assert (recorded.total_downloads, recorded.anonymous_downloads) == (4, 2) + assert SkillHubList.model_validate(gateway.get(SKILLS, {"query": name})).skills[0].download_count == 4 + assert tuple((row.version, row.authenticated, row.user_id, row.user_email, row.key_alias, + row.team_id, row.team_alias) for row in recorded.downloads) == ( + ("1.2.3", True, user, email, name, team, name), + ) * 2 + assert tuple(row.digest for row in recorded.downloads) == digests[::-1] + for prefix in (PLUGINS, SKILLS): + assert gateway.request("GET", f"{prefix}/{name}/downloads", key=key).status_code == 403 + assert gateway.client.get(f"{prefix}/{name}/downloads").status_code == 401 + assert _history(gateway, name) == recorded + _delete(gateway, name) + assert gateway.rows('SELECT id FROM "LiteLLM_ClaudeCodePluginDownload" WHERE plugin_id = %s', (original_id,)) == [] + _upload(skills, name) + assert gateway.get(f"{SKILLS}/{name}")["id"] != original_id + assert _history(gateway, name) == PluginDownloadsResponse(0, 0, (), None) + + +def test_concurrent_counts_and_keyset_pages_preserve_scope_and_deleted_cursors(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + name: Final = f"download-{uuid.uuid4().hex}" + legacy: Final = _upload(scenario, name) + portable: Final = f"{SKILLS}/{name}/archive" + key: Final = scenario.key() + with ThreadPoolExecutor(max_workers=4) as pool: + tuple(pool.map(partial(_download, gateway, key), (legacy, portable) * 4)) + initial: Final = _history(gateway, name) + ordered: Final = tuple(row.id for row in initial.downloads) + assert initial.total_downloads == len(frozenset(ordered)) == 8 + assert ordered == tuple(sorted(ordered, key=int, reverse=True)) + timestamp: Final = gateway.get(f"{PLUGINS}/{name}")["updated_at"] + with ThreadPoolExecutor(max_workers=4) as pool: + tuple(pool.map(partial(_download, gateway, None), (legacy, portable) * 8)) + assert gateway.get(f"{PLUGINS}/{name}")["updated_at"] == timestamp + assert _history(gateway, name) == replace(initial, total_downloads=24, anonymous_downloads=16) + first: Final = _history(gateway, name, limit="3") + assert tuple(row.id for row in first.downloads) == ordered[:3] + assert first.next_cursor == ordered[2] + _download(gateway, key, portable) + other: Final = f"{name}-other" + _download(gateway, key, _upload(scenario, other)) + write_rows( + 'DELETE FROM "LiteLLM_ClaudeCodePluginDownload" WHERE id IN (%s::bigint, %s::bigint)', + (ordered[2], ordered[4]), database_url=gateway.database_url, + ) + assert first.next_cursor is not None + second: Final = _history(gateway, name, limit="3", cursor=first.next_cursor) + assert tuple(row.id for row in second.downloads) == (ordered[3], ordered[5], ordered[6]) + assert (second.total_downloads, second.anonymous_downloads) == (23, 16) + assert second.next_cursor is not None + last: Final = _history(gateway, name, limit="3", cursor=second.next_cursor) + assert tuple(row.id for row in last.downloads) == (ordered[7],) + assert last.next_cursor is None + assert _history(gateway, other, cursor=first.next_cursor) == PluginDownloadsResponse(1, 0, (), None) + catalog: Final = SkillHubList.model_validate(gateway.get(SKILLS, {"query": name})) + assert {skill.name: skill.download_count for skill in catalog.skills} == {name: 23, other: 1} + + +def test_repeat_migration_is_catalog_only_while_download_tables_are_locked(gateway: Gateway) -> None: + migration: Final = (Path(__file__).resolve().parents[3] / + "litellm-proxy-extras/litellm_proxy_extras/migrations/20261105094500_add_skill_download_history/migration.sql" + ).read_bytes() + with gateway.scenario() as scenario: + name: Final = f"download-{uuid.uuid4().hex}" + url: Final = _upload(scenario, name) + for key in (None, gateway.key): + _download(gateway, key, url) + before: Final = _history(gateway, name) + database_url: Final = gateway.database_url or os.environ["DATABASE_URL"] + with psycopg.connect(database_url) as locker, psycopg.connect(database_url, autocommit=True) as migrator: + locker.execute( + 'LOCK TABLE "LiteLLM_ClaudeCodePluginTable", "LiteLLM_ClaudeCodePluginDownload" IN ACCESS EXCLUSIVE MODE' + ) + for _ in range(2): + with migrator.transaction(): + migrator.execute("SET LOCAL statement_timeout = '500ms'") + migrator.execute(migration) + assert _history(gateway, name) == before diff --git a/tests/integration/management/test_team_delete_large_membership.py b/tests/integration/management/test_team_delete_large_membership.py index 8b3c6b06bba..2a8508ff3c9 100644 --- a/tests/integration/management/test_team_delete_large_membership.py +++ b/tests/integration/management/test_team_delete_large_membership.py @@ -24,6 +24,7 @@ import yaml from pydantic import JsonValue from redis import Redis +from litellm.constants import TEAM_DELETE_TRANSACTION_TIMEOUT_SECONDS from tests.integration._support.client import ( Gateway, Scenario, @@ -166,19 +167,11 @@ def _remove_team_by_sql(team_id: str) -> None: assert _team_rows(team_id) == [] -def _remove_team_if_present(gateway: Gateway, team_id: str) -> None: - """Cleanup for teams the test deletes itself: the API delete first, SQL for anything it leaves.""" - if not _team_rows(team_id): - return - gateway.request("POST", "/team/delete", {"team_ids": [team_id]}) - _remove_team_by_sql(team_id) - - def _create_team(scenario: Scenario, **fields: JsonValue) -> str: """A team the test deletes itself; cleanup only removes it if the test left it behind.""" created: Final = scenario.gateway.post("/team/new", {"team_alias": f"integration-{uuid.uuid4().hex}", **fields}) team_id: Final = string_value(created["team_id"]) - scenario.cleanups.callback(_remove_team_if_present, scenario.gateway, team_id) + scenario.cleanups.callback(_remove_team_by_sql, team_id) return team_id @@ -783,7 +776,9 @@ def test_deleting_a_team_with_more_keys_than_the_publish_cap_revokes_every_key_o keys: Final = _seeded_team_keys(team, KEYS_WELL_PAST_THE_PUBLISH_CAP) assert _statuses(peer, keys) == {200: len(keys)} - response: Final = _delete_teams(gateway, [team]) + response: Final = _post_with_timeout( + gateway, "/team/delete", {"team_ids": [team]}, timeout=2 * TEAM_DELETE_TRANSACTION_TIMEOUT_SECONDS + ) assert response.status_code == 200, response.text assert read_rows('SELECT token FROM "LiteLLM_VerificationToken" WHERE team_id = %s', (team,)) == [] diff --git a/tests/integration/management/test_team_delete_member_add_race.py b/tests/integration/management/test_team_delete_member_add_race.py index e1f2a933ec3..c558264a650 100644 --- a/tests/integration/management/test_team_delete_member_add_race.py +++ b/tests/integration/management/test_team_delete_member_add_race.py @@ -22,8 +22,12 @@ import time import uuid from contextlib import asynccontextmanager from datetime import timedelta +from typing import Final from unittest.mock import MagicMock +from psycopg import AsyncConnection +from psycopg.rows import dict_row + import pytest from fastapi import HTTPException @@ -48,7 +52,7 @@ _HELD_LOCK_KEY_SQL = ( _LOCK_WAITER_SQL = ( "SELECT count(*)::int AS waiters FROM pg_locks " "WHERE locktype = 'advisory' AND NOT granted " - "AND classid::bigint = $1 AND objid::bigint = $2" + "AND classid::bigint = %s AND objid::bigint = %s" ) _LOCK_WAIT_TIMEOUT_SECONDS = 20.0 _LOCK_POLL_SECONDS = 0.01 @@ -66,21 +70,17 @@ async def _hold_team_lock(held, team_id: str) -> tuple[int, int]: return rows[0]["classid"], rows[0]["objid"] -async def _await_lock_contention(watcher, lock_key: tuple[int, int], task, what: str) -> None: - """Block until Postgres reports `task` queued behind the held lock. - - This is the assertion that the endpoint serializes on the team's advisory lock, and it - is what a fixed sleep was standing in for: the endpoint is only provably waiting once a - non-granted advisory lock on the same key exists. `watcher` must be a connection that is - not itself blocked, so it can observe the queue.""" - classid, objid = lock_key - deadline = time.monotonic() + _LOCK_WAIT_TIMEOUT_SECONDS - while time.monotonic() < deadline: - if task.done(): - raise AssertionError(f"{what} returned without waiting on the team's advisory lock") from task.exception() - if (await watcher.query_raw(_LOCK_WAITER_SQL, classid, objid))[0]["waiters"]: - return - await asyncio.sleep(_LOCK_POLL_SECONDS) +async def _await_lock_contention(lock_key: tuple[int, int], task: asyncio.Task[object], what: str) -> None: + deadline: Final = time.monotonic() + _LOCK_WAIT_TIMEOUT_SECONDS + async with await AsyncConnection.connect(os.environ["DATABASE_URL"], autocommit=True, row_factory=dict_row) as watcher: + while time.monotonic() < deadline: + if task.done(): + raise AssertionError(f"{what} returned without waiting on the team's advisory lock") from task.exception() + cursor: Final = await watcher.execute(_LOCK_WAITER_SQL, lock_key) + observed: Final = await cursor.fetchone() + if observed is not None and observed["waiters"]: + return + await asyncio.sleep(_LOCK_POLL_SECONDS) raise AssertionError(f"{what} never queued on the team's advisory lock within {_LOCK_WAIT_TIMEOUT_SECONDS}s") @@ -171,7 +171,7 @@ async def test_member_add_blocked_by_delete_writes_no_dangling_reference(): async with blocker.tx(timeout=timedelta(seconds=30)) as held: lock_key = await _hold_team_lock(held, team_id) task = asyncio.create_task(add_member()) - await _await_lock_contention(db, lock_key, task, "member_add") + await _await_lock_contention(lock_key, task, "member_add") await held.execute_raw(_DELETE_TEAM, team_id) @@ -234,7 +234,7 @@ async def test_member_delete_blocked_by_member_add_removes_from_the_fresh_roster async with blocker.tx(timeout=timedelta(seconds=30)) as held: lock_key = await _hold_team_lock(held, team_id) task = asyncio.create_task(run_delete()) - await _await_lock_contention(db, lock_key, task, "member_delete") + await _await_lock_contention(lock_key, task, "member_delete") await held.litellm_teamtable.update( where={"team_id": team_id}, @@ -311,7 +311,7 @@ async def test_delete_blocked_by_member_add_sweeps_the_fresh_reference(): async with blocker.tx(timeout=timedelta(seconds=30)) as held: lock_key = await _hold_team_lock(held, team_id) task = asyncio.create_task(run_delete()) - await _await_lock_contention(db, lock_key, task, "delete_team") + await _await_lock_contention(lock_key, task, "delete_team") await held.litellm_usertable.upsert( where={"user_id": user_id}, diff --git a/tests/integration/management/test_user_updates_wedged_coordination_redis.py b/tests/integration/management/test_user_updates_wedged_coordination_redis.py index 2b05d35d553..bb5766e5816 100644 --- a/tests/integration/management/test_user_updates_wedged_coordination_redis.py +++ b/tests/integration/management/test_user_updates_wedged_coordination_redis.py @@ -193,8 +193,10 @@ def test_user_budget_updates_return_promptly_while_coordination_redis_is_wedged( timings["s6_customer_update"] = _timed_post( candidate, "/customer/update", {"user_id": customer_id, "max_budget": 6.0} ) - assert timings["s6_customer_update"] < _HANDLER_BUDGET_SECONDS, ( - f"/customer/update took {timings['s6_customer_update']:.3f}s with a wedged coordination Redis" + assert timings["s6_customer_update"] < _SHORTEST_REDIS_WAIT_SECONDS, ( + f"/customer/update took {timings['s6_customer_update']:.3f}s, reaching the " + f"{_SHORTEST_REDIS_WAIT_SECONDS}s shortest wait the proxy puts on Redis, so it waited on the " + "wedged coordination Redis" ) timings["s7_reset_spend"] = _timed_post(candidate, f"/key/{key}/reset_spend", {"reset_to": 0}) assert timings["s7_reset_spend"] < _HANDLER_BUDGET_SECONDS, ( diff --git a/tests/integration/management/test_vector_store_file_list_managed_ids.py b/tests/integration/management/test_vector_store_file_list_managed_ids.py index 16d33ee83af..5ef709d7365 100644 --- a/tests/integration/management/test_vector_store_file_list_managed_ids.py +++ b/tests/integration/management/test_vector_store_file_list_managed_ids.py @@ -9,6 +9,7 @@ from concurrent.futures import ThreadPoolExecutor from contextlib import contextmanager from dataclasses import dataclass from functools import partial +from itertools import count from pathlib import Path from queue import SimpleQueue from types import MappingProxyType @@ -1042,6 +1043,77 @@ def test_multi_model_upload_maps_only_the_provider_id_the_managed_id_carries(gat assert second_ids == ((managed_a,) if carried == second.file_id("a.txt") else (second.file_id("a.txt"),)) +def _team_wildcard(scenario: Scenario, pattern: str, api_base: str, bearer: str, team: str) -> str: + identity: Final = f"wildcard-{uuid.uuid4().hex}" + scenario.gateway.post( + "/model/new", + { + "model_name": pattern, + "litellm_params": {"model": "openai/*", "api_key": bearer, "api_base": api_base}, + "model_info": {"id": identity, "team_id": team}, + }, + ) + scenario.cleanups.callback(scenario.delete_model, identity) + eventually(lambda: _every_worker_has_deployment(scenario.gateway, identity), lambda served: served, seconds=90) + return identity + + +def test_two_targets_served_by_one_team_wildcard_keep_one_upload_that_delete_removes(gateway: Gateway) -> None: + store: Final = "vs_" + uuid.uuid4().hex + bearer: Final = "provider-key-" + uuid.uuid4().hex[:8] + prefix: Final = f"wc-{uuid.uuid4().hex}" + upload_numbers: Final = count(1) + first_upload: Final = f"file-{prefix}-1" + second_upload: Final = f"file-{prefix}-2" + served: Final = _provider(store, _constant_listing(store, first_upload)) + + def respond(request: Request) -> Reply: + if (request.method, urlsplit(request.target).path) != ("POST", "/v1/files"): + return served(request) + _assert_provider_upload(request, bearer, "a.txt") + return _json_reply(_file_object(f"file-{prefix}-{next(upload_numbers)}")) + + with gateway.scenario() as scenario, wire_server(respond) as wire: + team: Final = scenario.team(models=[]) + _team_wildcard(scenario, f"{prefix}/*", f"{wire.url}/v1", bearer, team) + key: Final = scenario.key(team_id=team, user_id=scenario.member(team)) + wire.drain() + + managed: Final = _upload(gateway, key, f"{prefix}/gpt-one,{prefix}/gpt-two", "a.txt") + assert _carried_provider_file_id(managed) == first_upload, _decoded(managed) + assert [row["flat_model_file_ids"] for row in read_rows(MANAGED_FILE_ROW, (managed,))] == [[first_upload]] + eventually(lambda: wire.received.qsize(), lambda received: received >= 3) + create_requests: Final = wire.drain() + assert [(request.method, request.target) for request in create_requests] == [ + ("POST", "/v1/files"), + ("POST", "/v1/files"), + ("DELETE", f"/v1/files/{second_upload}"), + ], create_requests + assert create_requests[2].headers["authorization"] == f"Bearer {bearer}", create_requests[2].headers + + attached: Final = gateway.request( + "POST", f"/v1/vector_stores/{store}/files", {"file_id": managed}, key=key, params={"model": f"{prefix}/*"} + ) + assert attached.status_code == 200, attached.text + listed: Final = gateway.request( + "GET", f"/v1/vector_stores/{store}/files", key=key, params={"model": f"{prefix}/*"} + ) + assert _ids(_listed(listed)) == (managed,), listed.text + attach_bodies: Final = [ + JSON_OBJECT.validate_json(request.body) for request in wire.drain() if request.method == "POST" + ] + assert attach_bodies == [{"file_id": first_upload}], attach_bodies + + deleted: Final = gateway.request("DELETE", f"/v1/files/{managed}", key=key) + assert deleted.status_code == 200, deleted.text + assert read_rows(MANAGED_FILE_ROW, (managed,)) == [] + delete_requests: Final = wire.drain() + assert [(request.method, request.target) for request in delete_requests] == [ + ("DELETE", f"/v1/files/{first_upload}") + ], delete_requests + assert delete_requests[0].headers["authorization"] == f"Bearer {bearer}", delete_requests[0].headers + + def test_deleting_the_managed_file_makes_its_listing_raw_again(gateway: Gateway) -> None: with _rig(gateway, "a.txt") as rig: member: Final = _member(rig.scenario, rig.model) diff --git a/tests/integration/mcp/test_mcp_transports.py b/tests/integration/mcp/test_mcp_transports.py index 92fcf37994e..4c3648a3381 100644 --- a/tests/integration/mcp/test_mcp_transports.py +++ b/tests/integration/mcp/test_mcp_transports.py @@ -669,7 +669,7 @@ def test_sdk_progress_and_cancellation_reach_upstream_without_losing_session( import httpx2 import yaml from integration._support.asgi import asgi_server - from integration._support.mcp import _drain_sse_streams + from integration._support.mcp import _acknowledge_notifications_after_dispatch, _drain_sse_streams from integration._support.process import owned_proxy from mcp import ClientSession, MCPError from mcp.client.streamable_http import streamable_http_client @@ -769,7 +769,9 @@ def test_sdk_progress_and_cancellation_reach_upstream_without_losing_session( watchers = tuple(task for task in asyncio.all_tasks() if "_shutdown_watcher" in repr(task.get_coro())) await asyncio.wait_for(asyncio.gather(*watchers), 2) - hosted: Final = Starlette(routes=[Mount("/", app=app)], lifespan=lifespan) + hosted: Final = Starlette( + routes=[Mount("/", app=_acknowledge_notifications_after_dispatch(app))], lifespan=lifespan + ) with asgi_server(hosted) as upstream_url, httpx.Client() as client: config: Final = tmp_path / "proxy.yaml" config.write_text( diff --git a/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_gateway_wire.py b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_gateway_wire.py index e159573e9fd..1f57584572b 100644 --- a/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_gateway_wire.py +++ b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_gateway_wire.py @@ -97,9 +97,10 @@ def test_shared_gateway_route_is_disabled_without_reaching_provider(gateway: Gat headers=_cli_bearer_headers(gateway.key), ) assert response.status_code == 404, response.text - assert _JSON_OBJECT.validate_json(response.content) == {"detail": "Claude Code gateway is not enabled"}, ( - response.text - ) + assert _JSON_OBJECT.validate_json(response.content) == { + "type": "error", + "error": {"type": "not_found_error", "message": "Claude Code gateway is not enabled"}, + }, response.text assert wire.drain() == () @@ -268,15 +269,15 @@ def test_enabled_gateway_count_tokens_alias_matches_native_count_tokens_route(en ) assert restricted_response.status_code == 403, restricted_response.text assert _JSON_OBJECT.validate_json(restricted_response.content) == { + "type": "error", "error": { + "type": "permission_error", "message": ( f"The requested model '{restricted_model}' is not available for this API key, or the model name " "is invalid. Check the models available to you and try again." ), - "type": "key_model_access_denied", - "param": "model", - "code": "403", - } + "litellm_error_type": "key_model_access_denied", + }, }, restricted_response.text assert wire.drain() == () @@ -285,15 +286,15 @@ def test_enabled_gateway_count_tokens_alias_matches_native_count_tokens_route(en def test_enabled_gateway_refuses_model_outside_virtual_key(enabled_gateway: Gateway) -> None: result: Final = _restricted_model_responses(enabled_gateway) expected_body: Final = { + "type": "error", "error": { + "type": "permission_error", "message": ( f"The requested model '{result[4]}' is not available for this API key, or the model name is invalid. " "Check the models available to you and try again." ), - "type": "key_model_access_denied", - "param": "model", - "code": "403", - } + "litellm_error_type": "key_model_access_denied", + }, } assert result[0] == result[2] == 403, (result[1], result[3]) assert _JSON_OBJECT.validate_json(result[1]) == expected_body, result[1] diff --git a/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_input_transformations_wire.py b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_input_transformations_wire.py new file mode 100644 index 00000000000..6b9739def8c --- /dev/null +++ b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_input_transformations_wire.py @@ -0,0 +1,91 @@ +"""Anthropic's ``input_transformations`` report reaches the caller on chat completions and ``/v1/messages``.""" + +import json +from typing import Final + +import pytest +from integration._support import claude_code as cc +from integration._support.client import Gateway +from integration._support.wire import Reply, Request, wire_server +from pydantic import JsonValue, TypeAdapter + +_BACKEND: Final = "claude-sonnet-4-6" +_API_KEY: Final = "scripted-anthropic-key" +_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) +_CHOICES: Final = TypeAdapter(list[dict[str, JsonValue]]) +_INPUT_TRANSFORMATIONS: Final[list[JsonValue]] = [{"type": "prefix_binding_mismatch", "index": 1}] +_CONTENT: Final[tuple[dict[str, JsonValue], ...]] = ({"type": "text", "text": "Ok"},) +_USAGE: Final[dict[str, JsonValue]] = {"input_tokens": 8, "output_tokens": 2} +_IDENTITY: Final = "msg_input_transformations" + + +def _reply_body() -> bytes: + body: Final = _JSON_OBJECT.validate_json(cc.message_reply(_IDENTITY, _BACKEND, _CONTENT, _USAGE)) + return json.dumps({**body, "input_transformations": _INPUT_TRANSFORMATIONS}).encode() + + +def _stream_reply() -> tuple[bytes, ...]: + start, *rest = cc.message_stream(_IDENTITY, _BACKEND, _CONTENT, _USAGE) + event_name, data = cc.sse_events(start.decode())[0] + message: Final = _JSON_OBJECT.validate_python(data["message"]) + started: Final = cc.sse_frame( + event_name, {**data, "message": {**message, "input_transformations": _INPUT_TRANSFORMATIONS}} + ) + return (started, *rest) + + +def _anthropic_upstream(request: Request) -> Reply: + assert request.method == "POST" and request.target == "/v1/messages", request.target + assert request.headers["x-api-key"] == _API_KEY, request.headers + body: Final = _JSON_OBJECT.validate_json(request.body) + if body.get("stream") is True: + return Reply(content_type="text/event-stream", chunks=_stream_reply()) + return Reply(body=_reply_body()) + + +def test_chat_completion_message_carries_input_transformations(gateway: Gateway) -> None: + with wire_server(_anthropic_upstream) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_BACKEND}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request( + "POST", + "/v1/chat/completions", + {"model": model, "max_tokens": 16, "messages": [{"role": "user", "content": "Say ok"}]}, + ) + assert response.status_code == 200, response.text + message: Final = response.json()["choices"][0]["message"] + assert message["provider_specific_fields"]["input_transformations"] == _INPUT_TRANSFORMATIONS, response.text + + +def test_first_chat_completion_chunk_carries_input_transformations(gateway: Gateway) -> None: + with wire_server(_anthropic_upstream) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_BACKEND}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request( + "POST", + "/v1/chat/completions", + {"model": model, "max_tokens": 16, "stream": True, "messages": [{"role": "user", "content": "Say ok"}]}, + ) + assert response.status_code == 200, response.text + chunks: Final = [ + _JSON_OBJECT.validate_json(line[len("data: ") :]) + for line in response.text.splitlines() + if line.startswith("data: {") + ] + first_delta: Final = _JSON_OBJECT.validate_python(_CHOICES.validate_python(chunks[0]["choices"])[0]["delta"]) + assert first_delta["provider_specific_fields"] == {"input_transformations": _INPUT_TRANSFORMATIONS}, chunks[0] + + +@pytest.mark.parametrize("stream", [False, True], ids=["non_stream", "stream"]) +def test_messages_endpoint_keeps_input_transformations(gateway: Gateway, stream: bool) -> None: + with wire_server(_anthropic_upstream) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_BACKEND}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request( + "POST", + "/v1/messages", + {"model": model, "max_tokens": 16, "stream": stream, "messages": [{"role": "user", "content": "Say ok"}]}, + ) + assert response.status_code == 200, response.text + if stream: + started: Final = next(data for name, data in cc.sse_events(response.text) if name == "message_start") + assert _JSON_OBJECT.validate_python(started["message"])["input_transformations"] == _INPUT_TRANSFORMATIONS + else: + assert response.json()["input_transformations"] == _INPUT_TRANSFORMATIONS, response.text diff --git a/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_overloaded_wire.py b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_overloaded_wire.py new file mode 100644 index 00000000000..9d0e31058e4 --- /dev/null +++ b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_overloaded_wire.py @@ -0,0 +1,746 @@ +import json +import os +import threading +import time +import uuid +from collections.abc import Callable, Generator, Mapping +from contextlib import contextmanager +from typing import Final, Literal +from urllib.parse import unquote + +import anthropic +import httpx +import openai +import pytest +from integration._support.anthropic_sse import ( + LIFECYCLE, + error_frame, + event_type, + event_types, + message_id, + message_json, + message_stream, + parse_sse, + status_reply, + stream_reply, + user_prompt, +) +from integration._support.client import ( + JSON_OBJECT, + Gateway, + JsonValue, + Scenario, + eventually, + object_value, + string_value, +) +from integration._support.database import read_rows +from integration._support.openai_wire import openai_error +from integration._support.upstream import aws_event_stream_frame +from integration._support.wire import Reply, Request, Wire, wire_server +from redis import Redis + +_MODEL: Final = "claude-sonnet-4-5-20250929" +_API_KEY: Final = "synthetic-anthropic-key" +_BEDROCK_MODEL: Final = "us.anthropic.claude-sonnet-4-5-20250929-v1:0" +_BEDROCK_TOKEN: Final = "synthetic-bedrock-bearer" +_BEDROCK_503: Final = b'{"message": "Bedrock is unable to process your request."}' +_CONVERSE_MODEL: Final = f"bedrock/converse/{_BEDROCK_MODEL}" +_CONVERSE_STREAM_TARGET: Final = f"/model/{_BEDROCK_MODEL}/converse-stream" +_OPENAI_BACKEND: Final = "gpt-4o-mini" +_CHAT_ONLY_BACKEND: Final = "audit-chat-only" +_CODEX_BACKEND: Final = "gpt-5.3-codex" +_TEXT: Final = "Hello" +_KEEPALIVE_SECONDS: Final = 0.2 +_LATE_ANSWER_SECONDS: Final = 1.0 +_OVERLOAD_CLASS: Final = "503_PROVIDER_OVERLOADED" + +Shape = Literal["stream", "non-stream"] + + +def _prompt() -> str: + return "overloaded-" + uuid.uuid4().hex + + +def _always(reply: Reply) -> Callable[[Request], Reply]: + def respond(request: Request) -> Reply: + assert request.method == "POST", request + return reply + + return respond + + +def _late(reply: Reply, seconds: float) -> Callable[[Request], Reply]: + def respond(request: Request) -> Reply: + assert request.method == "POST", request + time.sleep(seconds) + return reply + + return respond + + +def _anthropic_sdk(gateway: Gateway) -> anthropic.Anthropic: + return anthropic.Anthropic(base_url=str(gateway.client.base_url), api_key=gateway.key, max_retries=0, timeout=60) + + +def _async_anthropic_sdk(gateway: Gateway) -> anthropic.AsyncAnthropic: + return anthropic.AsyncAnthropic( + base_url=str(gateway.client.base_url), api_key=gateway.key, max_retries=0, timeout=60 + ) + + +def _openai_sdk(gateway: Gateway) -> openai.OpenAI: + return openai.OpenAI(base_url=str(gateway.client.base_url), api_key=gateway.key, max_retries=0, timeout=60) + + +def _async_openai_sdk(gateway: Gateway) -> openai.AsyncOpenAI: + return openai.AsyncOpenAI(base_url=str(gateway.client.base_url), api_key=gateway.key, max_retries=0, timeout=60) + + +def _messages_body(model: str, prompt: str, *, stream: bool) -> dict[str, JsonValue]: + return { + "model": model, + "max_tokens": 16, + "stream": stream, + "messages": [{"role": "user", "content": prompt}], + "num_retries": 0, + } + + +def _anthropic_error(response: httpx.Response) -> dict[str, JsonValue]: + assert response.headers["content-type"].startswith("application/json"), dict(response.headers) + payload: Final = object_value(json.loads(response.content)) + assert payload["type"] == "error", response.text + return object_value(payload["error"]) + + +def _openai_error(response: httpx.Response) -> dict[str, JsonValue]: + return object_value(object_value(json.loads(response.content))["error"]) + + +def _assert_overloaded(response: httpx.Response, *, message: str) -> None: + assert response.status_code == 529, response.text + error: Final = _anthropic_error(response) + assert error["type"] == "overloaded_error", response.text + assert message in string_value(error["message"]), response.text + assert "content_block_delta" not in response.text, response.text + + +def _assert_api_error(response: httpx.Response, *, status: int, message: str) -> None: + assert response.status_code == status, response.text + error: Final = _anthropic_error(response) + assert error["type"] == "api_error", response.text + assert message in string_value(error["message"]), response.text + + +def _assert_internal_server_error(response: httpx.Response) -> None: + assert response.status_code == 500, response.text + error: Final = _openai_error(response) + assert error["code"] == "500", response.text + assert "InternalServerError" in string_value(error["message"]), response.text + + +def _assert_openai_overloaded(response: httpx.Response) -> None: + assert response.status_code == 503, response.text + error: Final = _openai_error(response) + assert set(error) == {"message", "type", "param", "code"}, response.text + assert string_value(error["message"]), response.text + assert error["type"] == "service_unavailable_error", response.text + assert error["param"] is None, response.text + assert error["code"] == "server_is_overloaded", response.text + + +def _one_post(wire: Wire, target: str) -> None: + assert [(request.method, unquote(request.target)) for request in wire.drain()] == [("POST", target)] + + +def _spend_rows(model: str, expected: int) -> list[dict[str, JsonValue]]: + return eventually( + lambda: read_rows( + "SELECT status, metadata->'error_information'->>'error_code' AS code, " + "metadata->'error_information'->>'error_class' AS error_class, " + "metadata->'error_information'->>'normalized_error' AS normalized_error " + 'FROM "LiteLLM_SpendLogs" WHERE model_group=%s', + (model,), + ), + lambda rows: len(rows) >= expected, + seconds=70, + ) + + +def _assert_logged_failure(model: str, *, rows: int, error_class: str, code: str = "529") -> None: + assert ( + _spend_rows(model, rows) + == [{"status": "failure", "code": code, "error_class": error_class, "normalized_error": _OVERLOAD_CLASS}] * rows + ) + + +def test_messages_529_answers_overloaded_error_to_the_sync_sdk_and_logs_each_call_once(gateway: Gateway) -> None: + with wire_server(_always(status_reply(529))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + sdk: Final = _anthropic_sdk(gateway) + prompt: Final = _prompt() + for _ in range(2): + with pytest.raises(anthropic.APIStatusError) as caught: + sdk.messages.create( + model=model, + max_tokens=16, + messages=[{"role": "user", "content": prompt}], + extra_body={"num_retries": 0}, + ) + assert caught.value.status_code == 529, caught.value.response.text + _assert_overloaded(caught.value.response, message="scripted 529") + assert [unquote(request.target) for request in wire.drain()] == ["/v1/messages"] * 2 + _assert_logged_failure(model, rows=2, error_class="InternalServerError") + + +async def test_messages_529_answers_overloaded_error_to_the_async_sdk(gateway: Gateway) -> None: + with wire_server(_always(status_reply(529))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + with pytest.raises(anthropic.APIStatusError) as caught: + await _async_anthropic_sdk(gateway).messages.create( + model=model, + max_tokens=16, + messages=[{"role": "user", "content": _prompt()}], + extra_body={"num_retries": 0}, + ) + assert caught.value.status_code == 529, caught.value.response.text + _assert_overloaded(caught.value.response, message="scripted 529") + _one_post(wire, "/v1/messages") + + +@pytest.mark.parametrize( + ("upstream_status", "error_class", "error_type"), + ((529, "InternalServerError", "overloaded_error"), (503, "ServiceUnavailableError", "api_error")), +) +def test_messages_stream_rejected_before_its_first_byte_answers_the_provider_status_as_json( + gateway: Gateway, upstream_status: int, error_class: str, error_type: str +) -> None: + with wire_server(_always(status_reply(upstream_status))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request("POST", "/v1/messages", _messages_body(model, _prompt(), stream=True)) + assert response.status_code == upstream_status, response.text + error: Final = _anthropic_error(response) + assert error["type"] == error_type, response.text + assert f"scripted {upstream_status}" in string_value(error["message"]), response.text + _one_post(wire, "/v1/messages") + _assert_logged_failure(model, rows=1, error_class=error_class, code=str(upstream_status)) + + +def test_messages_stream_529_raises_529_in_the_sync_sdk(gateway: Gateway) -> None: + with wire_server(_always(status_reply(529))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + with pytest.raises(anthropic.APIStatusError) as caught: + with _anthropic_sdk(gateway).messages.stream( + model=model, + max_tokens=16, + messages=[{"role": "user", "content": _prompt()}], + extra_body={"num_retries": 0}, + ) as stream: + stream.get_final_message() + assert caught.value.status_code == 529, caught.value.response.text + _assert_overloaded(caught.value.response, message="scripted 529") + _one_post(wire, "/v1/messages") + + +def _error_frames(text: str) -> tuple[dict[str, JsonValue], ...]: + return tuple( + object_value(json.loads(line.removeprefix("data:").strip())) + for line in text.splitlines() + if line.startswith("data:") and '"error"' in line + ) + + +def test_messages_529_after_the_keepalive_opened_the_response_ends_with_an_overloaded_error_event( + gateway: Gateway, +) -> None: + with ( + wire_server(_late(status_reply(529), _LATE_ANSWER_SECONDS)) as wire, + gateway.scenario() as scenario, + ): + model: Final = scenario.model( + model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY, keepalive_seconds=_KEEPALIVE_SECONDS + ) + response: Final = gateway.request("POST", "/v1/messages", _messages_body(model, _prompt(), stream=True)) + assert response.status_code == 200, response.text + assert response.headers["content-type"].startswith("text/event-stream"), dict(response.headers) + assert response.text.startswith(":"), response.text + (failure,) = (event for event in parse_sse(response.text) if event.data and event.event != "ping") + assert failure.event == "error", response.text + assert object_value(failure.data["error"])["type"] == "overloaded_error", response.text + assert "[DONE]" not in response.text, response.text + _one_post(wire, "/v1/messages") + + +def _late_bedrock_deployment(scenario: Scenario, wire: Wire) -> str: + return scenario.model( + model=f"bedrock/{_BEDROCK_MODEL}", + api_key=_BEDROCK_TOKEN, + aws_region_name="us-east-1", + api_base=wire.url, + keepalive_seconds=_KEEPALIVE_SECONDS, + ) + + +def _one_bedrock_post(wire: Wire) -> None: + (request,) = wire.drain() + assert unquote(request.target).startswith(f"/model/{_BEDROCK_MODEL}/"), request + + +def test_messages_bedrock_503_after_the_keepalive_opened_the_response_ends_with_an_api_error_event( + gateway: Gateway, +) -> None: + with ( + wire_server(_late(Reply(status=503, body=_BEDROCK_503), _LATE_ANSWER_SECONDS)) as wire, + gateway.scenario() as scenario, + ): + model: Final = _late_bedrock_deployment(scenario, wire) + response: Final = gateway.request("POST", "/v1/messages", _messages_body(model, _prompt(), stream=True)) + assert response.status_code == 200, response.text + assert response.text.startswith(":"), response.text + assert "[DONE]" not in response.text, response.text + (failure,) = (event for event in parse_sse(response.text) if event.data and event.event != "ping") + assert failure.event == "error", response.text + error: Final = object_value(failure.data["error"]) + assert error["type"] == "api_error", response.text + assert "Bedrock is unable to process your request." in string_value(error["message"]), response.text + _one_bedrock_post(wire) + _assert_logged_failure(model, rows=1, error_class="ServiceUnavailableError", code="503") + + +def test_chat_completions_bedrock_503_after_the_keepalive_opened_the_response_keeps_the_openai_error_frame( + gateway: Gateway, +) -> None: + with ( + wire_server(_late(Reply(status=503, body=_BEDROCK_503), _LATE_ANSWER_SECONDS)) as wire, + gateway.scenario() as scenario, + ): + model: Final = _late_bedrock_deployment(scenario, wire) + response: Final = gateway.request( + "POST", + "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": _prompt()}], "stream": True, "num_retries": 0}, + ) + assert response.status_code == 200, response.text + assert response.text.startswith(":"), response.text + assert "event: error" not in response.text, response.text + (frame,) = _error_frames(response.text) + assert object_value(frame["error"])["code"] == "503", response.text + assert response.text.rstrip().endswith("data: [DONE]"), response.text + _one_bedrock_post(wire) + _assert_logged_failure(model, rows=1, error_class="ServiceUnavailableError", code="503") + + +def test_chat_completions_overloaded_frame_after_content_ends_with_a_500_error_frame(gateway: Gateway) -> None: + prompt: Final = _prompt() + upstream: Final = (*message_stream(prompt, _MODEL, _TEXT)[:3], error_frame(529, "Overloaded")) + with wire_server(_always(stream_reply(upstream))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request( + "POST", + "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": prompt}], "stream": True, "num_retries": 0}, + ) + assert response.status_code == 200, response.text + assert _TEXT in response.text, response.text + (frame,) = _error_frames(response.text) + error: Final = object_value(frame["error"]) + assert error["code"] == "500", response.text + _one_post(wire, "/v1/messages") + + +def _overloaded_before_content(prompt: str) -> Reply: + return stream_reply((*message_stream(prompt, _MODEL, _TEXT)[:1], error_frame(529, "Overloaded"))) + + +def test_messages_overloaded_frame_before_content_without_a_retry_budget_is_relayed_as_an_overloaded_event( + gateway: Gateway, +) -> None: + prompt: Final = _prompt() + with wire_server(_always(_overloaded_before_content(prompt))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request("POST", "/v1/messages", _messages_body(model, prompt, stream=True)) + assert response.status_code == 200, response.text + events: Final = parse_sse(response.text) + assert event_types(events) == ("message_start", "error"), response.text + assert message_id(events) == prompt, response.text + assert events[1].data == {"type": "error", "error": {"type": "overloaded_error", "message": "Overloaded"}} + _one_post(wire, "/v1/messages") + assert _spend_rows(model, 1) == [ + {"status": "success", "code": None, "error_class": None, "normalized_error": None} + ] + + +def test_chat_completions_overloaded_frame_before_content_answers_503(gateway: Gateway) -> None: + prompt: Final = _prompt() + with wire_server(_always(_overloaded_before_content(prompt))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request( + "POST", + "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": prompt}], "stream": True, "num_retries": 0}, + ) + _assert_openai_overloaded(response) + _one_post(wire, "/v1/messages") + + +def test_chat_completions_529_answers_503_to_the_sync_sdk(gateway: Gateway) -> None: + with wire_server(_always(status_reply(529))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + with pytest.raises(openai.APIStatusError) as caught: + _openai_sdk(gateway).chat.completions.create( + model=model, messages=[{"role": "user", "content": _prompt()}], extra_body={"num_retries": 0} + ) + assert caught.value.status_code == 503, caught.value.response.text + _assert_openai_overloaded(caught.value.response) + _one_post(wire, "/v1/messages") + _assert_logged_failure(model, rows=1, error_class="InternalServerError", code="503") + + +async def test_chat_completions_stream_529_answers_503_to_the_async_sdk(gateway: Gateway) -> None: + with wire_server(_always(status_reply(529))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + with pytest.raises(openai.APIStatusError) as caught: + await _async_openai_sdk(gateway).chat.completions.create( + model=model, + messages=[{"role": "user", "content": _prompt()}], + stream=True, + extra_body={"num_retries": 0}, + ) + assert caught.value.status_code == 503, caught.value.response.text + _assert_openai_overloaded(caught.value.response) + _one_post(wire, "/v1/messages") + + +def test_completions_529_answers_503(gateway: Gateway) -> None: + with wire_server(_always(status_reply(529))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request( + "POST", + "/v1/completions", + {"model": model, "prompt": _prompt(), "max_tokens": 16, "num_retries": 0}, + ) + _assert_openai_overloaded(response) + _one_post(wire, "/v1/messages") + + +@pytest.mark.parametrize("shape", ("non-stream", "stream")) +def test_responses_529_answers_503(gateway: Gateway, shape: Shape) -> None: + with wire_server(_always(status_reply(529))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request( + "POST", "/v1/responses", {"model": model, "input": _prompt(), "stream": shape == "stream", "num_retries": 0} + ) + _assert_openai_overloaded(response) + _one_post(wire, "/v1/messages") + + +@pytest.mark.parametrize("shape", ("non-stream", "stream")) +def test_messages_bedrock_503_answers_503_api_error(gateway: Gateway, shape: Shape) -> None: + with wire_server(_always(Reply(status=503, body=_BEDROCK_503))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model( + model=f"bedrock/{_BEDROCK_MODEL}", api_key=_BEDROCK_TOKEN, aws_region_name="us-east-1", api_base=wire.url + ) + response: Final = gateway.request( + "POST", "/v1/messages", _messages_body(model, _prompt(), stream=shape == "stream") + ) + _assert_api_error(response, status=503, message="Bedrock is unable to process your request.") + (request,) = wire.drain() + assert unquote(request.target).startswith(f"/model/{_BEDROCK_MODEL}/"), request + _assert_logged_failure(model, rows=1, error_class="ServiceUnavailableError", code="503") + + +def _converse_event(event: str, payload: Mapping[str, JsonValue]) -> bytes: + return aws_event_stream_frame( + {":event-type": event, ":content-type": "application/json", ":message-type": "event"}, + json.dumps(payload).encode(), + ) + + +def _converse_503_after_text() -> Reply: + unavailable: Final = aws_event_stream_frame( + { + ":exception-type": "serviceUnavailableException", + ":content-type": "application/json", + ":message-type": "exception", + }, + _BEDROCK_503, + ) + frames: Final = ( + _converse_event("messageStart", {"role": "assistant"}), + _converse_event("contentBlockDelta", {"delta": {"text": _TEXT}, "contentBlockIndex": 0}), + unavailable, + ) + return Reply(body=b"".join(frames), content_type="application/vnd.amazon.eventstream") + + +def _converse_deployment(scenario: Scenario, wire: Wire) -> str: + return scenario.model(model=_CONVERSE_MODEL, api_key=_BEDROCK_TOKEN, aws_region_name="us-east-1", api_base=wire.url) + + +def test_messages_bedrock_stream_503_after_text_ends_with_an_api_error_event(gateway: Gateway) -> None: + with wire_server(_always(_converse_503_after_text())) as wire, gateway.scenario() as scenario: + model: Final = _converse_deployment(scenario, wire) + response: Final = gateway.request("POST", "/v1/messages", _messages_body(model, _prompt(), stream=True)) + assert response.status_code == 200, response.text + events: Final = parse_sse(response.text) + types: Final = event_types(events) + assert "message_stop" not in types, response.text + assert types.index("content_block_delta") < types.index("error"), response.text + assert _TEXT in response.text, response.text + (failure,) = (event for event in events if event_type(event) == "error") + error: Final = object_value(failure.data["error"]) + assert error["type"] == "api_error", response.text + assert "Bedrock is unable to process your request." in string_value(error["message"]), response.text + _one_post(wire, _CONVERSE_STREAM_TARGET) + _assert_logged_failure(model, rows=1, error_class="ServiceUnavailableError", code="503") + + +def test_chat_completions_bedrock_stream_503_after_text_ends_with_a_503_error_frame(gateway: Gateway) -> None: + with wire_server(_always(_converse_503_after_text())) as wire, gateway.scenario() as scenario: + model: Final = _converse_deployment(scenario, wire) + response: Final = gateway.request( + "POST", + "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": _prompt()}], "stream": True, "num_retries": 0}, + ) + assert response.status_code == 200, response.text + assert _TEXT in response.text, response.text + (frame,) = _error_frames(response.text) + error: Final = object_value(frame["error"]) + assert error["code"] == "503", response.text + _one_post(wire, _CONVERSE_STREAM_TARGET) + _assert_logged_failure(model, rows=1, error_class="ServiceUnavailableError", code="503") + + +@pytest.mark.parametrize("shape", ("non-stream", "stream")) +def test_chat_bridge_503_answers_503_api_error_on_messages(gateway: Gateway, shape: Shape) -> None: + with wire_server(_always(openai_error(503))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model( + model=f"hosted_vllm/{_CHAT_ONLY_BACKEND}", api_base=wire.url + "/v1", api_key="synthetic-vllm-key" + ) + response: Final = gateway.request( + "POST", "/v1/messages", _messages_body(model, _prompt(), stream=shape == "stream") + ) + _assert_api_error(response, status=503, message="scripted 503") + _one_post(wire, "/v1/chat/completions") + + +@pytest.mark.parametrize("shape", ("non-stream", "stream")) +def test_responses_bridge_503_answers_503_api_error_on_messages(gateway: Gateway, shape: Shape) -> None: + with wire_server(_always(openai_error(503))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model( + model=f"openai/{_CODEX_BACKEND}", api_base=wire.url + "/v1", api_key="synthetic-openai-key" + ) + response: Final = gateway.request( + "POST", "/v1/messages", _messages_body(model, _prompt(), stream=shape == "stream") + ) + _assert_api_error(response, status=503, message="scripted 503") + _one_post(wire, "/v1/responses") + + +_SETTLED_ANSWERS: Final = 4 + + +def _messages_to(gateway: Gateway, model: str) -> tuple[tuple[str, httpx.Response], ...]: + prompts: Final = tuple(_prompt() for _ in range(_SETTLED_ANSWERS)) + return tuple( + (prompt, gateway.request("POST", "/v1/messages", _messages_body(model, prompt, stream=False))) + for prompt in prompts + ) + + +def _failure_rows_of(models: tuple[str, str], expected: int) -> list[dict[str, JsonValue]]: + return eventually( + lambda: read_rows( + "SELECT metadata->'error_information'->>'error_code' AS code, " + "metadata->'error_information'->>'error_class' AS error_class, " + "metadata->'error_information'->>'normalized_error' AS normalized_error " + 'FROM "LiteLLM_SpendLogs" WHERE status = %s AND model_group IN (%s, %s)', + ("failure", *models), + ), + lambda rows: len(rows) >= expected, + seconds=70, + ) + + +@contextmanager +def _paused_deployment(gateway: Gateway) -> Generator[tuple[Wire, str, str]]: + unpaused: Final = Reply(body=message_json("msg_unpaused", _MODEL, _TEXT)) + with wire_server(_always(unpaused)) as wire, gateway.scenario() as scenario: + identity: Final = f"audit-paused-{uuid.uuid4().hex}" + name: Final = scenario.model( + model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY, model_info={"id": identity} + ) + paused: Final = gateway.request("PATCH", f"/model/{identity}/update", {"blocked": True}) + assert paused.status_code == 200, paused.text + yield wire, identity, name + + +def _assert_refused_without_an_upstream_call( + gateway: Gateway, wire: Wire, target: str, *, status: int, error_type: str, message: str +) -> None: + answers: Final = eventually( + lambda: _messages_to(gateway, target), + lambda settled: all(response.status_code != 200 for _, response in settled), + seconds=90, + ) + texts: Final = [response.text for _, response in answers] + assert [response.status_code for _, response in answers] == [status] * _SETTLED_ANSWERS, texts + errors: Final = [_anthropic_error(response) for _, response in answers] + assert [error["type"] for error in errors] == [error_type] * _SETTLED_ANSWERS, texts + assert all(message in string_value(error["message"]) for error in errors), texts + reached: Final = {user_prompt(JSON_OBJECT.validate_json(request.body)) for request in wire.drain()} + assert reached.isdisjoint(prompt for prompt, _ in answers), reached + + +def test_messages_to_a_paused_deployment_named_by_its_id_answer_503_api_error(gateway: Gateway) -> None: + with _paused_deployment(gateway) as (wire, identity, name): + _assert_refused_without_an_upstream_call( + gateway, wire, identity, status=503, error_type="api_error", message="is currently paused" + ) + rows: Final = _failure_rows_of((identity, name), _SETTLED_ANSWERS) + assert {(row["code"], row["error_class"], row["normalized_error"]) for row in rows} == { + ("503", "ServiceUnavailableError", _OVERLOAD_CLASS) + }, rows + + +def test_messages_to_a_paused_model_group_named_by_its_name_answer_403_permission_error(gateway: Gateway) -> None: + with _paused_deployment(gateway) as (wire, _, name): + _assert_refused_without_an_upstream_call( + gateway, wire, name, status=403, error_type="permission_error", message="Model is blocked" + ) + + +_MALFORMED_529_BODIES: Final = { + "empty": b"", + "text-5k": b"x" * 5000, + "html": b"

529

", + "api_error-type": b'{"type": "error", "error": {"type": "api_error", "message": "capacity"}}', +} + + +def _overloaded_for_sad_prompts(body: bytes) -> Callable[[Request], Reply]: + def respond(request: Request) -> Reply: + prompt: Final = user_prompt(object_value(json.loads(request.body))) + if prompt.startswith("sad:"): + return Reply(status=529, body=body, content_type="text/plain" if body[:1] != b"{" else "application/json") + return Reply(body=message_json(f"msg_{prompt}", _MODEL, _TEXT)) + + return respond + + +@pytest.mark.parametrize("body", _MALFORMED_529_BODIES.keys()) +def test_messages_529_with_a_malformed_body_still_answers_overloaded_error_and_unrelated_calls_keep_working( + gateway: Gateway, body: str +) -> None: + with wire_server(_overloaded_for_sad_prompts(_MALFORMED_529_BODIES[body])) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + sad: Final = gateway.request("POST", "/v1/messages", _messages_body(model, "sad:" + _prompt(), stream=False)) + assert sad.status_code == 529, sad.text + assert _anthropic_error(sad)["type"] == "overloaded_error", sad.text + prompt: Final = _prompt() + healthy: Final = gateway.request("POST", "/v1/messages", _messages_body(model, prompt, stream=False)) + assert healthy.status_code == 200, healthy.text + assert object_value(json.loads(healthy.content))["id"] == f"msg_{prompt}", healthy.text + assert [unquote(request.target) for request in wire.drain()] == ["/v1/messages"] * 2 + assert sorted(_spend_rows(model, 2), key=lambda row: str(row["status"])) == [ + { + "status": "failure", + "code": "529", + "error_class": "InternalServerError", + "normalized_error": _OVERLOAD_CLASS, + }, + {"status": "success", "code": None, "error_class": None, "normalized_error": None}, + ] + + +@pytest.mark.parametrize(("upstream_status", "error_type"), ((500, "api_error"), (429, "rate_limit_error"))) +def test_messages_other_upstream_statuses_keep_their_status_and_type( + gateway: Gateway, upstream_status: int, error_type: str +) -> None: + with wire_server(_always(status_reply(upstream_status))) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request("POST", "/v1/messages", _messages_body(model, _prompt(), stream=True)) + assert response.status_code == upstream_status, response.text + assert _anthropic_error(response)["type"] == error_type, response.text + _one_post(wire, "/v1/messages") + + +def _anthropic_rejection(status: int, error_type: str, message: str) -> Reply: + return Reply( + status=status, body=json.dumps({"type": "error", "error": {"type": error_type, "message": message}}).encode() + ) + + +_REJECTIONS_SAYING_OVERLOADED: Final = { + "400-tool-name": _anthropic_rejection( + 400, "invalid_request_error", "tools.0.name: 'Overloaded' is not a valid tool name" + ), + "404-model": _anthropic_rejection(404, "not_found_error", "model: claude-Overloaded"), +} + + +@pytest.mark.parametrize("shape", ("non-stream", "stream")) +@pytest.mark.parametrize("rejection", _REJECTIONS_SAYING_OVERLOADED.keys()) +def test_messages_4xx_whose_text_says_overloaded_is_not_answered_as_an_overload( + gateway: Gateway, rejection: str, shape: Shape +) -> None: + with wire_server(_always(_REJECTIONS_SAYING_OVERLOADED[rejection])) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + response: Final = gateway.request( + "POST", "/v1/messages", _messages_body(model, _prompt(), stream=shape == "stream") + ) + assert response.status_code == 500, response.text + error: Final = _anthropic_error(response) + assert error["type"] == "api_error", response.text + assert "Overloaded" in string_value(error["message"]), response.text + _one_post(wire, "/v1/messages") + assert _spend_rows(model, 1) == [ + { + "status": "failure", + "code": "500", + "error_class": "InternalServerError", + "normalized_error": _OVERLOAD_CLASS, + } + ] + + +def _string_values(cache: Redis) -> tuple[bytes, ...]: + keys: Final = tuple(key for key in cache.scan_iter(count=1000) if cache.type(key) == b"string") + return tuple(value for value in cache.mget(keys) if value is not None) if keys else () + + +def _cached_somewhere(served_id: str) -> bool: + with Redis(host=os.environ["REDIS_HOST"], port=int(os.environ["REDIS_PORT"])) as cache: + return any(served_id.encode() in value for value in _string_values(cache)) + + +def _healthy_until(overloaded: threading.Event) -> Callable[[Request], Reply]: + def respond(request: Request) -> Reply: + if overloaded.is_set(): + return status_reply(529) + prompt: Final = user_prompt(object_value(json.loads(request.body))) + return stream_reply(message_stream(f"msg_{prompt}", _MODEL, _TEXT)) + + return respond + + +def test_messages_cache_hit_is_served_while_the_upstream_is_overloaded(gateway: Gateway) -> None: + overloaded: Final = threading.Event() + with wire_server(_healthy_until(overloaded)) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY) + prompt: Final = _prompt() + body: Final = _messages_body(model, prompt, stream=True) + first: Final = gateway.request("POST", "/v1/messages", body) + assert first.status_code == 200, first.text + assert event_types(parse_sse(first.text)) == LIFECYCLE, first.text + assert message_id(parse_sse(first.text)) == f"msg_{prompt}", first.text + eventually(lambda: _cached_somewhere(f"msg_{prompt}"), bool, seconds=30) + overloaded.set() + replay: Final = gateway.request("POST", "/v1/messages", body) + assert replay.status_code == 200, replay.text + assert message_id(parse_sse(replay.text)) == f"msg_{prompt}", replay.text + fresh: Final = gateway.request("POST", "/v1/messages", _messages_body(model, _prompt(), stream=True)) + _assert_overloaded(fresh, message="scripted 529") + assert [unquote(request.target) for request in wire.drain()] == ["/v1/messages"] * 2 diff --git a/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_pre_content_retry_chaos.py b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_pre_content_retry_chaos.py index 9dd1a2d2c18..99239efe5ee 100644 --- a/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_pre_content_retry_chaos.py +++ b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_pre_content_retry_chaos.py @@ -135,6 +135,13 @@ def _drop_or_500(request: Request, marker: str) -> Reply: return openai_error(500) +def _overloaded_while(outage: threading.Event) -> Callable[[Request, str], Reply]: + def first_attempt(request: Request, marker: str) -> Reply: + return status_reply(529) if outage.is_set() else _served(request, marker, 1) + + return first_attempt + + def _outage(statuses: Mapping[str, int]) -> Callable[[Request, str], Reply]: def first_attempt(request: Request, marker: str) -> Reply: if request.target == "/v1/messages": @@ -165,7 +172,7 @@ class _Upstream: return self.first_attempt(request, marker) -def _config(wire: Wire, directory: Path, models: _Models) -> Path: +def _config(wire: Wire, directory: Path, models: _Models, *, retries: int = 1) -> Path: config: Final = yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text()) config["model_list"] = [ { @@ -174,7 +181,7 @@ def _config(wire: Wire, directory: Path, models: _Models) -> Path: "model": f"anthropic/{_ANTHROPIC_BACKEND}", "api_base": wire.url, "api_key": _ANTHROPIC_KEY, - "num_retries": 1, + "num_retries": retries, }, }, { @@ -183,7 +190,7 @@ def _config(wire: Wire, directory: Path, models: _Models) -> Path: "model": f"openai/{_OPENAI_BACKEND}", "api_base": wire.url + "/v1", "api_key": _OPENAI_KEY, - "num_retries": 1, + "num_retries": retries, }, }, ] @@ -408,3 +415,68 @@ async def test_outage_on_every_first_attempt_is_absorbed_by_the_deployment_budge _assert_completed_on_the_second_attempt(item) _assert_each_served_id_landed_exactly_once(models, served) assert all(upstream.attempts.count(call.marker) == 2 for call in calls) + + +def _messages_rows(model: str, expected: int) -> list[dict[str, JsonValue]]: + return eventually( + lambda: read_rows( + "SELECT request_id, status, metadata->'error_information'->>'error_code' AS code " + 'FROM "LiteLLM_SpendLogs" WHERE model_group=%s', + (model,), + ), + lambda found: len(found) >= expected, + seconds=90, + ) + + +@pytest.mark.timeout(300) +async def test_overloaded_outage_during_a_burst_with_a_worker_sigkill_answers_529_and_lands_every_call_once( + gateway: Gateway, tmp_path: Path +) -> None: + models: Final = _models() + calls: Final = _calls((("messages", True, 12), ("messages", False, 6))) + release: Final = threading.Event() + held: Final[SimpleQueue[str]] = SimpleQueue() + outage: Final = threading.Event() + outage.set() + upstream: Final = _Upstream(Attempts(), _overloaded_while(outage), held, release) + with wire_server(upstream) as wire: + config: Final = _config(wire, tmp_path, models, retries=0) + with owned_proxy_process(gateway, tmp_path, {}, config=config, workers=2) as owned: + candidate: Final = owned.gateway + base_url: Final = str(candidate.client.base_url) + workers: Final = eventually( + lambda: tuple(int(pid) for pid in _STARTED_WORKER.findall(owned.log.read_text())), + lambda pids: len(pids) == 2, + seconds=30, + ) + burst: Final = asyncio.create_task( + _burst(base_url, candidate.key, models, calls, tolerate_transport_errors=True) + ) + await asyncio.to_thread(eventually, held.qsize, lambda size: size == len(calls), 90) + held_by: Final = MappingProxyType({pid: _open_upstream_connections(pid, wire.url) for pid in workers}) + assert sum(held_by.values()) == len(calls), held_by + victim_pid, survivor_pid = sorted(workers, key=held_by.__getitem__) + with owned.replacing_worker(victim_pid) as kill: + kill.freeze() + await asyncio.to_thread(kill) + release.set() + served: Final = await burst + assert held_by[survivor_pid] >= 5, held_by + assert len(served) == held_by[survivor_pid], (held_by, len(served)) + for item in served: + assert item.status == 529, (item.call, item.text) + assert "overloaded_error" in item.text, (item.call, item.text) + assert "content_block_delta" not in item.text, (item.call, item.text) + outage.clear() + follow_up: Final = _Call(endpoint="messages", stream=True, marker=uuid.uuid4().hex) + (answered,) = await _burst(base_url, candidate.key, models, (follow_up,)) + assert answered.status == 200, answered.text + assert message_id(parse_sse(answered.text)) == f"msg_{follow_up.marker}_a1", answered.text + rows: Final = _messages_rows(models.messages, len(served) + 1) + assert sorted(string_value(row["status"]) for row in rows) == ["failure"] * len(served) + ["success"], rows + assert {row["code"] for row in rows if row["status"] == "failure"} == {"529"}, rows + assert [row["request_id"] for row in rows if row["status"] == "success"] == [ + f"msg_{follow_up.marker}_a1" + ], rows + assert all(upstream.attempts.count(item.call.marker) == 1 for item in (*served, answered)) diff --git a/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_pre_content_retry_wire.py b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_pre_content_retry_wire.py index 041a0a72fdd..83a9ba3d14c 100644 --- a/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_pre_content_retry_wire.py +++ b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_messages_pre_content_retry_wire.py @@ -397,14 +397,14 @@ def test_retry_rejected_before_it_opens_counts_against_the_same_budget(gateway: with wire_server(respond) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"anthropic/{_MODEL}", api_base=wire.url, api_key=_API_KEY, num_retries=1) response: Final = gateway.request("POST", "/v1/messages", _body(model, prompt, "deployment")) - _assert_rejected_before_content(response, wire, status=500, attempts=2, error="error") + _assert_rejected_before_content(response, wire, status=529, attempts=2, error="overloaded_error") rows: Final = eventually( lambda: _request_rows(gateway, response.headers["x-litellm-call-id"]), lambda values: len(values) >= 1, seconds=70, ) rejected: Final = gateway.request("POST", "/v1/messages", _body(model, prompt, "request", budget=0)) - _assert_rejected_before_content(rejected, wire, status=500, attempts=1, error="error") + _assert_rejected_before_content(rejected, wire, status=529, attempts=1, error="overloaded_error") rejection_rows: Final = eventually( lambda: _request_rows(gateway, rejected.headers["x-litellm-call-id"]), lambda values: len(values) >= 1, diff --git a/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_safeguards_beta_wire.py b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_safeguards_beta_wire.py index 3ac1bdb0334..a1c5f6964bf 100644 --- a/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_safeguards_beta_wire.py +++ b/tests/integration/messages_endpoint/providers/anthropic/test_anthropic_safeguards_beta_wire.py @@ -3,7 +3,7 @@ import json import re import time import uuid -from collections.abc import Callable, Mapping +from collections.abc import Callable, Iterator, Mapping from dataclasses import dataclass from pathlib import Path from types import MappingProxyType @@ -13,7 +13,7 @@ import anthropic import httpx import openai import pytest -from integration._support.client import Gateway, eventually, object_value +from integration._support.client import Gateway, eventually, gateway_from_environment, object_value from integration._support.database import read_rows from integration._support.process import owned_proxy from integration._support.vertex import service_account_json @@ -417,14 +417,31 @@ def test_a_deployment_dropping_context_management_sends_neither_the_field_nor_it _spend_row(f"msg_{marker}") +@pytest.fixture(scope="module") +def local_beta_map_gateway(tmp_path_factory: pytest.TempPathFactory) -> Iterator[Gateway]: + with ( + gateway_from_environment() as shared, + owned_proxy( + shared, + tmp_path_factory.mktemp("safeguards-local-beta-map"), + {"LITELLM_LOCAL_ANTHROPIC_BETA_HEADERS": "true"}, + ) as owned, + ): + yield owned + + @pytest.mark.parametrize("row", tuple(_FOUNDRY_SHAPES)) -def test_azure_ai_messages_forward_the_mapped_client_betas_beside_the_derived_one(gateway: Gateway, row: str) -> None: +def test_azure_ai_messages_forward_the_mapped_client_betas_beside_the_derived_one( + local_beta_map_gateway: Gateway, row: str +) -> None: case: Final = _FOUNDRY_SHAPES[row] marker: Final = uuid.uuid4().hex - with wire_server(anthropic_peer) as wire, gateway.scenario() as scenario: + with wire_server(anthropic_peer) as wire, local_beta_map_gateway.scenario() as scenario: model: Final = scenario.model(model=_FOUNDRY_MODEL, api_base=wire.url, api_key=_FOUNDRY_KEY) response: Final = _post( - gateway, messages_body(model, marker, safeguards=case.sent, stream=case.stream), beta=case.client_beta + local_beta_map_gateway, + messages_body(model, marker, safeguards=case.sent, stream=case.stream), + beta=case.client_beta, ) if case.stream: _assert_streamed(response, marker) diff --git a/tests/integration/messages_endpoint/providers/anthropic/test_pdf_document_count_tokens_wire.py b/tests/integration/messages_endpoint/providers/anthropic/test_pdf_document_count_tokens_wire.py index 8eeaab66553..210b754f626 100644 --- a/tests/integration/messages_endpoint/providers/anthropic/test_pdf_document_count_tokens_wire.py +++ b/tests/integration/messages_endpoint/providers/anthropic/test_pdf_document_count_tokens_wire.py @@ -199,14 +199,14 @@ def test_utils_token_counter_adds_title_and_context_once_per_document( @pytest.mark.parametrize("label", list(_UNREADABLE)) -def test_utils_token_counter_prices_unreadable_pdf_bytes_like_one_image( +def test_utils_token_counter_uses_the_same_bounded_fallback_for_unreadable_pdf_bytes( gateway: Gateway, provider: SharedProvider, label: str ) -> None: data: Final = _UNREADABLE[label] as_pdf: Final = _local(gateway, provider, [document(base64_source(data))]) - as_png: Final = _local(gateway, provider, [document(base64_source(data, media_type="image/png"))]) + fallback: Final = _local(gateway, provider, [document(base64_source(encoded(b"unreadable-document")))]) without: Final = _local(gateway, provider, []) - assert as_pdf == as_png, (as_pdf, as_png) + assert as_pdf == fallback, (as_pdf, fallback) assert 0 <= as_pdf - without < rendered_tokens((LETTER,)), (as_pdf, without) diff --git a/tests/integration/messages_endpoint/test_beta_gated_fields_wire.py b/tests/integration/messages_endpoint/test_beta_gated_fields_wire.py index 26ad9f20897..fc1e91c79d7 100644 --- a/tests/integration/messages_endpoint/test_beta_gated_fields_wire.py +++ b/tests/integration/messages_endpoint/test_beta_gated_fields_wire.py @@ -16,7 +16,8 @@ pytestmark: Final = pytest.mark.shares_worker_state ANTHROPIC_MODEL: Final = "beta-gated-anthropic" FOUNDRY_MODEL: Final = "beta-gated-foundry" -FOUNDRY_DROP_PARAMS_MODEL: Final = "beta-gated-foundry-drop-params" +DATABRICKS_MODEL: Final = "beta-gated-databricks" +DATABRICKS_DROP_PARAMS_MODEL: Final = "beta-gated-databricks-drop-params" CLEAR_AT_BETA: Final = "mid-conversation-system-clear-at-2026-08-21" _JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) _NONCE: Final = re.compile(rb"nonce-([0-9a-f]{32})") @@ -73,7 +74,15 @@ def write_config(directory: Path, wire_url: str) -> Path: deployment(ANTHROPIC_MODEL, "anthropic/claude-opus-4-8", f"{wire_url}/anthropic"), deployment(FOUNDRY_MODEL, "azure_ai/claude-opus-4-8", f"{wire_url}/foundry"), deployment( - FOUNDRY_DROP_PARAMS_MODEL, "azure_ai/claude-opus-4-8", f"{wire_url}/foundry", drop_params=True + DATABRICKS_MODEL, + "databricks/databricks-claude-opus-4-8", + f"{wire_url}/databricks/serving-endpoints", + ), + deployment( + DATABRICKS_DROP_PARAMS_MODEL, + "databricks/databricks-claude-opus-4-8", + f"{wire_url}/databricks/serving-endpoints", + drop_params=True, ), ], "general_settings": { @@ -150,7 +159,7 @@ def system_message(body: bytes) -> dict[str, JsonValue]: def test_a_drop_params_leg_whose_row_lacks_the_beta_sends_neither_the_beta_nor_clear_at(rig: Rig) -> None: request_nonce: Final = nonce() - status, raw = rig.send(FOUNDRY_DROP_PARAMS_MODEL, request_nonce) + status, raw = rig.send(DATABRICKS_DROP_PARAMS_MODEL, request_nonce) assert reply_text(status, raw) == f"answered {request_nonce.removeprefix('nonce-')}" upstream: Final = rig.received(request_nonce) assert CLEAR_AT_BETA not in beta_header(upstream.headers), upstream.headers @@ -159,7 +168,7 @@ def test_a_drop_params_leg_whose_row_lacks_the_beta_sends_neither_the_beta_nor_c def test_a_leg_whose_row_lacks_the_beta_forwards_clear_at_as_sent_without_drop_params(rig: Rig) -> None: request_nonce: Final = nonce() - status, raw = rig.send(FOUNDRY_MODEL, request_nonce) + status, raw = rig.send(DATABRICKS_MODEL, request_nonce) assert reply_text(status, raw) == f"answered {request_nonce.removeprefix('nonce-')}" upstream: Final = rig.received(request_nonce) assert CLEAR_AT_BETA not in beta_header(upstream.headers), upstream.headers @@ -170,9 +179,10 @@ def test_a_leg_whose_row_lacks_the_beta_forwards_clear_at_as_sent_without_drop_p } -def test_a_leg_that_carries_the_beta_forwards_clear_at_untouched(rig: Rig) -> None: +@pytest.mark.parametrize("model", (ANTHROPIC_MODEL, FOUNDRY_MODEL)) +def test_a_leg_that_carries_the_beta_forwards_clear_at_untouched(rig: Rig, model: str) -> None: request_nonce: Final = nonce() - status, raw = rig.send(ANTHROPIC_MODEL, request_nonce) + status, raw = rig.send(model, request_nonce) assert reply_text(status, raw) == f"answered {request_nonce.removeprefix('nonce-')}" upstream: Final = rig.received(request_nonce) assert CLEAR_AT_BETA in beta_header(upstream.headers), upstream.headers diff --git a/tests/integration/observability/_logging_only_scope_support.py b/tests/integration/observability/_logging_only_scope_support.py index 3d29f7ab8c5..3b14c502623 100644 --- a/tests/integration/observability/_logging_only_scope_support.py +++ b/tests/integration/observability/_logging_only_scope_support.py @@ -22,7 +22,7 @@ import yaml from anthropic import Anthropic, AsyncAnthropic from cryptography.hazmat.primitives import serialization from cryptography.hazmat.primitives.asymmetric import rsa -from integration._support.client import Gateway, Scenario, eventually, object_value +from integration._support.client import Gateway, Scenario, eventually, object_value, string_value from integration._support.database import read_rows, write_rows from integration._support.upstream import delete_scenario, register_scenario from integration._support.wire import Reply, Request, Wire @@ -798,6 +798,7 @@ def _insert_database_guardrail( @contextmanager def _database_guardrail( + gateway: Gateway, identity: str, policy_url: str, scope: str | None, @@ -809,11 +810,15 @@ def _database_guardrail( try: yield finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) -def _delete_database_guardrail(identity: str) -> None: - write_rows('DELETE FROM "LiteLLM_GuardrailsTable" WHERE guardrail_name=%s', (identity,)) +def _delete_database_guardrail(gateway: Gateway, identity: str) -> None: + rows: Final = read_rows('SELECT guardrail_id FROM "LiteLLM_GuardrailsTable" WHERE guardrail_name=%s', (identity,)) + responses: Final = tuple( + gateway.request("DELETE", f"/guardrails/{string_value(row['guardrail_id'])}") for row in rows + ) + assert all(response.status_code == 200 for response in responses), [response.text for response in responses] def _post_guardrail_body( diff --git a/tests/integration/observability/test_anthropic_overloaded_failure_signals.py b/tests/integration/observability/test_anthropic_overloaded_failure_signals.py new file mode 100644 index 00000000000..e86ed98fae7 --- /dev/null +++ b/tests/integration/observability/test_anthropic_overloaded_failure_signals.py @@ -0,0 +1,404 @@ +import gzip +import json +import time +import uuid +from collections.abc import Callable, Iterator, Mapping, Sequence +from dataclasses import dataclass +from pathlib import Path +from typing import Final +from urllib.parse import unquote + +import httpx +import pytest +import yaml +from integration._support.anthropic_sse import error_body +from integration._support.client import ( + JSON_OBJECT, + Gateway, + JsonValue, + eventually, + gateway_from_environment, + object_value, + string_value, +) +from integration._support.otlp_sink import Span, SpanSinks, recorded_spans, spans_for_trace +from integration._support.process import graceful_stop_seconds, owned_proxy +from integration._support.prometheus_series import Sample, scrape +from integration._support.wire import Reply, Request, Wire, wire_server + +pytestmark: Final = pytest.mark.timeout(2 * graceful_stop_seconds() + 120) + +_MODEL: Final = "claude-sonnet-4-5-20250929" +_BEDROCK_MODEL: Final = "us.anthropic.claude-sonnet-4-5-20250929-v1:0" +_BEDROCK_503: Final = b'{"message": "Bedrock is unable to process your request."}' +_MESSAGES_ANTHROPIC: Final = "audit-signals-messages-anthropic" +_MESSAGES_BEDROCK: Final = "audit-signals-messages-bedrock" +_CHAT_ANTHROPIC: Final = "audit-signals-chat-anthropic" +_TRACED_MESSAGES: Final = "audit-signals-traced-messages" +_TRACED_CHAT: Final = "audit-signals-traced-chat" +_DATADOG_MESSAGES_ANTHROPIC: Final = "audit-signals-datadog-messages-anthropic" +_DATADOG_MESSAGES_BEDROCK: Final = "audit-signals-datadog-messages-bedrock" +_DATADOG_CHAT_ANTHROPIC: Final = "audit-signals-datadog-chat-anthropic" +_GUARDED_MESSAGES: Final = "audit-signals-guarded-messages" +_GUARDED_CHAT: Final = "audit-signals-guarded-chat" +_AKTO_DOWN: Final = "audit-signals-akto-down" +_AKTO_UNREACHABLE: Final = "Akto guardrail service unreachable" +_LATE_PASS_THROUGH_BACKEND: Final = "claude-late-pass-through" +_KEEPALIVE_SECONDS: Final = 0.2 +_LATE_ANSWER_SECONDS: Final = 1.0 +_OVERLOADED: Final = Reply(status=529, body=error_body(529, "Overloaded")) +_SERVER: Final = 2 + +AuditConfigWriter = Callable[[Path, Mapping[str, JsonValue]], Path] + + +@dataclass(frozen=True, slots=True) +class _Rig: + proxy: Gateway + wire: Wire + spans: str + datadog: Wire + + +def _respond(request: Request) -> Reply: + assert request.method == "POST", request + if unquote(request.target).startswith("/model/"): + return Reply(status=503, body=_BEDROCK_503) + if json.loads(request.body).get("model") == _LATE_PASS_THROUGH_BACKEND: + time.sleep(_LATE_ANSWER_SECONDS) + return _OVERLOADED + + +def _datadog_intake(request: Request) -> Reply: + assert request.target == "/api/v2/logs", request.target + return Reply(status=202, body=b"{}") + + +def _config(directory: Path, tracing: Path, wire: Wire) -> Path: + configuration: Final = JSON_OBJECT.validate_python(yaml.safe_load(tracing.read_text())) + anthropic: Final = {"model": f"anthropic/{_MODEL}", "api_base": wire.url, "api_key": "synthetic-anthropic-key"} + bedrock: Final = { + "model": f"bedrock/{_BEDROCK_MODEL}", + "api_base": wire.url, + "api_key": "synthetic-bedrock-bearer", + "aws_region_name": "us-east-1", + } + deployments: Final = ( + (_MESSAGES_ANTHROPIC, anthropic), + (_MESSAGES_BEDROCK, bedrock), + (_CHAT_ANTHROPIC, anthropic), + (_TRACED_MESSAGES, anthropic), + (_TRACED_CHAT, anthropic), + (_DATADOG_MESSAGES_ANTHROPIC, anthropic), + (_DATADOG_MESSAGES_BEDROCK, bedrock), + (_DATADOG_CHAT_ANTHROPIC, anthropic), + (_GUARDED_MESSAGES, anthropic), + (_GUARDED_CHAT, anthropic), + ) + akto_down: Final = { + "guardrail_name": _AKTO_DOWN, + "litellm_params": { + "guardrail": "akto", + "mode": "pre_call", + "akto_base_url": "http://127.0.0.1:9", + "akto_api_key": "synthetic-akto-key", + "unreachable_fallback": "fail_closed", + }, + } + path: Final = directory / "anthropic-overloaded-failure-signals.yaml" + path.write_text( + yaml.safe_dump( + { + **configuration, + "model_list": [{"model_name": name, "litellm_params": params} for name, params in deployments], + "router_settings": {**object_value(configuration.get("router_settings", {})), "num_retries": 0}, + "litellm_settings": { + **object_value(configuration["litellm_settings"]), + "sse_keepalive_ping_interval_seconds": _KEEPALIVE_SECONDS, + }, + "guardrails": [akto_down], + } + ) + ) + return path + + +@pytest.fixture(scope="module") +def rig( + tmp_path_factory: pytest.TempPathFactory, audit_sinks: SpanSinks, otel_audit_config: AuditConfigWriter +) -> Iterator[_Rig]: + directory: Final = tmp_path_factory.mktemp("anthropic-overloaded-failure-signals") + multiprocess: Final = directory / "prometheus" + multiprocess.mkdir() + tracing: Final = otel_audit_config(directory, {"callbacks": ["otel", "prometheus", "datadog"]}) + with ( + wire_server(_respond) as wire, + wire_server(_datadog_intake) as datadog, + gateway_from_environment() as shared, + owned_proxy( + shared, + directory, + { + "OTEL_EXPORTER": "http/json", + "OTEL_ENDPOINT": audit_sinks.operator, + "PROMETHEUS_MULTIPROC_DIR": str(multiprocess), + "DD_API_KEY": "synthetic-datadog-key", + "DD_SITE": "datadog.invalid", + "DD_BASE_URL": datadog.url, + "DD_BATCH_SIZE": "1", + "ANTHROPIC_API_BASE": wire.url, + "ANTHROPIC_API_KEY": "synthetic-anthropic-key", + }, + config=_config(directory, tracing, wire), + workers=2, + ) as owned, + ): + yield _Rig(owned, wire, audit_sinks.operator, datadog) + + +@pytest.fixture(scope="module") +def v2_rig( + tmp_path_factory: pytest.TempPathFactory, audit_sinks: SpanSinks, otel_audit_config: AuditConfigWriter +) -> Iterator[_Rig]: + directory: Final = tmp_path_factory.mktemp("anthropic-overloaded-failure-signals-v2") + tracing: Final = otel_audit_config(directory, {"callbacks": ["otel"]}) + with ( + wire_server(_respond) as wire, + wire_server(_datadog_intake) as datadog, + gateway_from_environment() as shared, + owned_proxy( + shared, + directory, + {"OTEL_EXPORTER": "http/json", "OTEL_ENDPOINT": audit_sinks.operator, "LITELLM_OTEL_V2": "1"}, + config=_config(directory, tracing, wire), + workers=2, + ) as owned, + ): + yield _Rig(owned, wire, audit_sinks.operator, datadog) + + +def _send( + rig: _Rig, + route: str, + model: str, + trace_id: str | None = None, + *, + key: str | None = None, + extra: Mapping[str, JsonValue] | None = None, +) -> httpx.Response: + traceparent: Final = {} if trace_id is None else {"traceparent": f"00-{trace_id}-{uuid.uuid4().hex[:16]}-01"} + return rig.proxy.request( + "POST", + route, + { + "model": model, + "max_tokens": 16, + "messages": [{"role": "user", "content": f"signals-{uuid.uuid4().hex}"}], + "num_retries": 0, + **(extra or {}), + }, + key=key, + headers={"anthropic-version": "2023-06-01", **traceparent}, + ) + + +def _series(samples: Sequence[Sample], name: str, model: str) -> tuple[Sample, ...]: + return tuple(sample for sample in samples if sample.name == name and sample.labels.get("requested_model") == model) + + +def _until(rig: _Rig, name: str, model: str) -> tuple[Sample, ...]: + return eventually(lambda: _series(scrape(rig.proxy), name, model), bool, seconds=30) + + +@pytest.mark.parametrize( + ("route", "model", "answered", "deployment_status", "deployment_class"), + ( + pytest.param("/v1/messages", _MESSAGES_ANTHROPIC, 529, "500", "InternalServerError", id="messages-anthropic"), + pytest.param("/v1/messages", _MESSAGES_BEDROCK, 503, "503", "ServiceUnavailableError", id="messages-bedrock"), + pytest.param("/v1/chat/completions", _CHAT_ANTHROPIC, 503, "500", "InternalServerError", id="chat-anthropic"), + ), +) +def test_the_failed_request_metric_counts_the_answered_status_and_the_deployment_metric_the_deployment_status( + rig: _Rig, route: str, model: str, answered: int, deployment_status: str, deployment_class: str +) -> None: + rig.wire.drain() + response: Final = _send(rig, route, model) + assert response.status_code == answered, response.text + assert len(rig.wire.drain()) == 1 + failed: Final = _until(rig, "litellm_proxy_failed_requests_metric_total", model) + assert [(sample.labels["exception_status"], sample.labels["route"], sample.value) for sample in failed] == [ + (str(answered), route, 1.0) + ], failed + deployment: Final = _until(rig, "litellm_deployment_failure_responses_total", model) + assert [(sample.labels["exception_status"], sample.value) for sample in deployment] == [(deployment_status, 1.0)], ( + deployment + ) + assert all(deployment_class in sample.labels["exception_class"] for sample in deployment), deployment + + +def _server_spans(rig: _Rig, since: int, trace_id: str) -> tuple[Span, ...]: + traced: Final = spans_for_trace(recorded_spans(rig.spans, since)[1], trace_id) + return tuple(span for span in traced if span["kind"] == _SERVER) + + +@pytest.mark.parametrize( + ("route", "model", "answered"), + ( + pytest.param("/v1/messages", _TRACED_MESSAGES, 529, id="messages"), + pytest.param("/v1/chat/completions", _TRACED_CHAT, 503, id="chat"), + ), +) +def test_the_server_span_carries_the_status_the_route_answered( + rig: _Rig, route: str, model: str, answered: int +) -> None: + rig.wire.drain() + since, _ = recorded_spans(rig.spans) + trace_id: Final = uuid.uuid4().hex + response: Final = _send(rig, route, model, trace_id) + assert response.status_code == answered, response.text + assert len(rig.wire.drain()) == 1 + server: Final = eventually( + lambda: _server_spans(rig, since, trace_id), + lambda spans: any("error.code" in span["attributes"] for span in spans), + seconds=40, + return_last_on_timeout=True, + ) + assert [ + (str(span["attributes"].get("http.response.status_code")), str(span["attributes"].get("error.code"))) + for span in server + ] == [(str(answered), str(answered))], server + + +def _inflated(request: Request) -> bytes: + return gzip.decompress(request.body) if request.headers.get("content-encoding") == "gzip" else request.body + + +def _datadog_events(batches: Sequence[Request]) -> Iterator[JsonValue]: + for batch in batches: + yield from json.loads(_inflated(batch)) + + +def _datadog_messages(batches: Sequence[Request]) -> tuple[dict[str, JsonValue], ...]: + return tuple( + JSON_OBJECT.validate_json(string_value(object_value(event)["message"])) for event in _datadog_events(batches) + ) + + +def _keyed_by(message: Mapping[str, JsonValue], alias: str) -> bool: + proxy_side: Final = message.get("user_api_key_dict") + llm_side: Final = message.get("metadata") + return any(isinstance(side, dict) and side.get("user_api_key_alias") == alias for side in (proxy_side, llm_side)) + + +def _datadog_status_codes(rig: _Rig, alias: str, expected: int) -> tuple[tuple[str, str], ...]: + batches: Final[list[Request]] = [] # mutable-ok: drain() consumes the queue, later polls must keep earlier batches + + def delivered() -> tuple[tuple[str, str], ...]: + batches.extend(rig.datadog.drain()) + return tuple( + sorted( + ("proxy", str(message["status_code"])) + if "user_api_key_dict" in message + else ("llm", str(object_value(message["error_information"])["error_code"])) + for message in _datadog_messages(batches) + if _keyed_by(message, alias) + ) + ) + + return eventually(delivered, lambda codes: len(codes) >= expected, seconds=40, return_last_on_timeout=True) + + +@pytest.mark.parametrize( + ("route", "model", "answered", "deployment_status"), + ( + pytest.param("/v1/messages", _DATADOG_MESSAGES_ANTHROPIC, 529, "500", id="messages-anthropic"), + pytest.param("/v1/messages", _DATADOG_MESSAGES_BEDROCK, 503, "503", id="messages-bedrock"), + pytest.param("/v1/chat/completions", _DATADOG_CHAT_ANTHROPIC, 503, "500", id="chat-anthropic"), + ), +) +def test_the_datadog_proxy_failure_log_carries_the_answered_status_and_the_llm_failure_log_the_deployment_status( + rig: _Rig, route: str, model: str, answered: int, deployment_status: str +) -> None: + rig.wire.drain() + rig.datadog.drain() + alias: Final = f"audit-signals-datadog-{uuid.uuid4().hex}" + with rig.proxy.scenario() as scenario: + response: Final = _send(rig, route, model, key=scenario.key(key_alias=alias, models=[model])) + assert response.status_code == answered, response.text + assert len(rig.wire.drain()) == 1 + assert _datadog_status_codes(rig, alias, 2) == (("llm", deployment_status), ("proxy", str(answered))) + + +@pytest.mark.parametrize( + ("route", "model", "answered"), + ( + pytest.param("/v1/messages", _GUARDED_MESSAGES, 503, id="messages"), + pytest.param("/v1/chat/completions", _GUARDED_CHAT, 503, id="chat"), + ), +) +def test_a_fail_closed_guardrail_outage_is_answered_and_recorded_with_the_routes_status( + rig: _Rig, route: str, model: str, answered: int +) -> None: + rig.wire.drain() + rig.datadog.drain() + alias: Final = f"audit-signals-guarded-{uuid.uuid4().hex}" + with rig.proxy.scenario() as scenario: + response: Final = _send( + rig, route, model, key=scenario.key(key_alias=alias, models=[model]), extra={"guardrails": [_AKTO_DOWN]} + ) + assert response.status_code == answered, response.text + assert _AKTO_UNREACHABLE in response.text, response.text + assert rig.wire.drain() == () + failed: Final = _until(rig, "litellm_proxy_failed_requests_metric_total", model) + assert [(sample.labels["exception_status"], sample.labels["route"], sample.value) for sample in failed] == [ + (str(answered), route, 1.0) + ], failed + assert _datadog_status_codes(rig, alias, 2) == (("llm", str(answered)), ("proxy", str(answered))) + + +@pytest.mark.parametrize( + ("route", "model", "answered"), + ( + pytest.param("/v1/messages", _TRACED_MESSAGES, 529, id="messages-anthropic"), + pytest.param("/v1/messages", _MESSAGES_BEDROCK, 503, id="messages-bedrock"), + pytest.param("/v1/chat/completions", _TRACED_CHAT, 503, id="chat-anthropic"), + ), +) +def test_the_otel_v2_server_span_carries_the_status_the_route_answered( + v2_rig: _Rig, route: str, model: str, answered: int +) -> None: + v2_rig.wire.drain() + since, _ = recorded_spans(v2_rig.spans) + trace_id: Final = uuid.uuid4().hex + response: Final = _send(v2_rig, route, model, trace_id) + assert response.status_code == answered, response.text + assert len(v2_rig.wire.drain()) == 1 + server: Final = eventually( + lambda: _server_spans(v2_rig, since, trace_id), + lambda spans: any("litellm.provider.error.code" in span["attributes"] for span in spans), + seconds=40, + return_last_on_timeout=True, + ) + assert [str(span["attributes"].get("litellm.provider.error.code")) for span in server] == [str(answered)], server + + +def test_an_anthropic_pass_through_stream_that_fails_after_the_keepalive_opened_relays_the_upstream_body( + rig: _Rig, +) -> None: + rig.wire.drain() + response: Final = rig.proxy.request( + "POST", + "/anthropic/v1/messages", + { + "model": _LATE_PASS_THROUGH_BACKEND, + "max_tokens": 16, + "stream": True, + "messages": [{"role": "user", "content": f"signals-{uuid.uuid4().hex}"}], + }, + headers={"anthropic-version": "2023-06-01"}, + ) + assert response.status_code == 200, response.text + pings, _, relayed = response.text.rpartition("\n\n") + assert pings and set(pings.split("\n")) <= {"", ": ping"}, response.text + assert relayed == _OVERLOADED.body.decode(), response.text + assert [unquote(request.target) for request in rig.wire.drain()] == ["/v1/messages"] diff --git a/tests/integration/observability/test_arize_otel_v2_openinference_chaos.py b/tests/integration/observability/test_arize_otel_v2_openinference_chaos.py index 79b0d9084aa..0095080d944 100644 --- a/tests/integration/observability/test_arize_otel_v2_openinference_chaos.py +++ b/tests/integration/observability/test_arize_otel_v2_openinference_chaos.py @@ -1,12 +1,13 @@ from __future__ import annotations +import socket import threading import uuid from concurrent.futures import ThreadPoolExecutor from contextlib import ExitStack from pathlib import Path +from queue import SimpleQueue from typing import Final -from urllib.parse import urlsplit import httpx import pytest @@ -44,7 +45,7 @@ from _openinference_support import ( ) from integration._support.client import Gateway, eventually from integration._support.process import graceful_stop_seconds -from integration._support.wire import Reply, Request, wire_server +from integration._support.wire import Reply, Request, Wire, wire_server def _call( @@ -249,11 +250,12 @@ def test_arize_otel_v2_f1_sink_outage_and_recovery(gateway: Gateway, tmp_path: P _assert_response(response, marker, surface, stream, model_name) with ExitStack() as servers: - initial_stack: Final = servers.enter_context(ExitStack()) - stopped_destination: Final = initial_stack.enter_context(wire_server(_owned_sink_handler(sink))) - sink_port: Final = urlsplit(stopped_destination.url).port - assert sink_port is not None, stopped_destination.url - initial_stack.close() + outage_socket: Final = servers.enter_context(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) + outage_socket.bind(("127.0.0.1", 0)) # test-quality-ok: socket stays bound throughout the outage + sink_port: Final = outage_socket.getsockname()[1] + stopped_destination: Final = Wire( + f"http://127.0.0.1:{sink_port}", SimpleQueue(), SimpleQueue(), SimpleQueue(), SimpleQueue() + ) with _rig( gateway, tmp_path, @@ -272,6 +274,7 @@ def test_arize_otel_v2_f1_sink_outage_and_recovery(gateway: Gateway, tmp_path: P with httpx.Client(trust_env=False) as client, pytest.raises(httpx.ConnectError): client.get(stopped_destination.url + "/health", timeout=2) recovered_stack: Final = servers.enter_context(ExitStack()) + outage_socket.close() recovered_destination: Final = recovered_stack.enter_context( wire_server(_owned_sink_handler(sink), port=sink_port) ) diff --git a/tests/integration/observability/test_cache_hit_guardrail_metrics.py b/tests/integration/observability/test_cache_hit_guardrail_metrics.py index c52649c46df..3abb2a7e2be 100644 --- a/tests/integration/observability/test_cache_hit_guardrail_metrics.py +++ b/tests/integration/observability/test_cache_hit_guardrail_metrics.py @@ -253,6 +253,16 @@ def _count(samples: tuple, name: str, model_id: str) -> float: ) +def _deployment_states(rig: Rig) -> tuple[float, ...]: + return tuple( + sample.value + for sample in _metric_samples(rig.candidate, rig.model_name) + if sample.name == DEPLOYMENT_STATE + and sample.labels.get("model_id") == rig.deployment_id + and sample.labels.get("api_base") == rig.provider.url + "/v1" + ) + + def _populated_failures(samples: tuple, rig: Rig, api_provider: str) -> float: return float( sum( @@ -414,7 +424,7 @@ def test_cache_hit_post_call_reject_keeps_deployment_labels_anthropic(gateway: G raised = True assert raised, "cache-hit post_call guardrail did not reject /v1/messages" assert rig.provider.received.qsize() == 1, rig.provider.drain() - _expect_metrics(rig, 1, 0, api_provider="anthropic", pf_id="None") + _expect_metrics(rig, 1, 0, api_provider="anthropic") def test_cache_hit_post_call_reject_keeps_deployment_labels_responses(gateway: Gateway, tmp_path: Path) -> None: @@ -431,7 +441,7 @@ def test_cache_hit_post_call_reject_keeps_deployment_labels_responses(gateway: G ) assert reject.status_code == 400, reject.text assert rig.provider.received.qsize() == 1, rig.provider.drain() - _expect_metrics(rig, 1, 0, pf_id="None") + _expect_metrics(rig, 1, 0) _assert_spend(_call_id(reject), rig) @@ -558,7 +568,8 @@ def test_cache_hit_post_call_guardrail_outage_keeps_deployment_labels( ) assert reject.status_code >= 400, reject.text assert rig.provider.received.qsize() == 1, rig.provider.drain() - _expect_metrics(rig, 0, 0, pf_populated=1, pf_blank=0) + _expect_metrics(rig, 1, 0) + _assert_spend(_call_id(reject), rig) def test_two_identical_cache_hit_rejects_increment_populated_series(gateway: Gateway, tmp_path: Path) -> None: @@ -635,6 +646,7 @@ def test_cache_hit_reject_deployment_metric_set_diff(gateway: Gateway, tmp_path: text: Final = "cache hit control e4 " + marker warm: Final = rig.candidate.request("POST", "/v1/chat/completions", _chat_body(rig.model_name, text, None)) assert warm.status_code == 200, warm.text + eventually(lambda: _deployment_states(rig), lambda states: states == (0.0,)) reject: Final = rig.candidate.request( "POST", "/v1/chat/completions", _chat_body(rig.model_name, text, rig.guardrail_name) ) @@ -642,11 +654,4 @@ def test_cache_hit_reject_deployment_metric_set_diff(gateway: Gateway, tmp_path: samples: Final = _expect_metrics(rig, 1, 0) blank: Final = tuple(sample for sample in samples if sample.labels.get("model_id") == "") assert blank == (), blank - states: Final = tuple( - sample.value - for sample in samples - if sample.name == DEPLOYMENT_STATE - and sample.labels.get("model_id") == rig.deployment_id - and sample.labels.get("api_base") == "" - ) - assert states == (1.0,), states + eventually(lambda: _deployment_states(rig), lambda states: states == (1.0,)) diff --git a/tests/integration/observability/test_langfuse_otel_metadata_chaos.py b/tests/integration/observability/test_langfuse_otel_metadata_chaos.py index bb386f6d41e..15bc076b8ba 100644 --- a/tests/integration/observability/test_langfuse_otel_metadata_chaos.py +++ b/tests/integration/observability/test_langfuse_otel_metadata_chaos.py @@ -107,9 +107,11 @@ def test_langfuse_otel_sink_outage_mid_burst_lands_every_response_id_once(gatewa ) payloads: Final = tuple(json.loads(line) for line in events) found: Final = next( - payload.get("response_id") or (payload.get("message") or {}).get("id") or payload.get("id") + (payload.get("response") or {}).get("id") + or (payload.get("message") or {}).get("id") + or payload.get("id") for payload in payloads - if payload.get("response_id") or payload.get("message") or payload.get("id") + if payload.get("response") or payload.get("message") or payload.get("id") ) return str(found) response: Final = rig.candidate.client.post(path, json=body, headers={"Authorization": f"Bearer {key}"}) diff --git a/tests/integration/observability/test_langfuse_otel_metadata_clients.py b/tests/integration/observability/test_langfuse_otel_metadata_clients.py index c2e0573b48a..fd2b9758449 100644 --- a/tests/integration/observability/test_langfuse_otel_metadata_clients.py +++ b/tests/integration/observability/test_langfuse_otel_metadata_clients.py @@ -162,8 +162,13 @@ def test_langfuse_otel_metadata_reaches_langfuse_for_responses_sse_stream(gatewa for line in stream.iter_lines() if line.startswith("data: ") and line != "data: [DONE]" ) - response_id: Final = next( - event["response_id"] for event in events if event.get("type") == "response.output_text.delta" + advertised: Final = frozenset( + event["response"]["id"] + for event in events + if event.get("type") in ("response.created", "response.completed") ) + assert len(advertised) == 1, events + response_id: Final = next(iter(advertised)) attrs: Final = exported_llm_span(rig.collector, response_id) + assert attrs["gen_ai.response.id"] == response_id, attrs assert_identity(attrs, chat_identity_fields(identity)) diff --git a/tests/integration/observability/test_logging_only_scope_config.py b/tests/integration/observability/test_logging_only_scope_config.py index 0841c91f8ca..5a37e779ef3 100644 --- a/tests/integration/observability/test_logging_only_scope_config.py +++ b/tests/integration/observability/test_logging_only_scope_config.py @@ -35,6 +35,7 @@ from _logging_only_scope_support import ( _reset_upstream, _response_body_without_ids, _spend_row_for_call_id, + _spend_row_for_response_id, _spend_rows, _upstream_requests, wire_server, @@ -115,7 +116,7 @@ def test_G7_database_invalid_scope_reads_preserve_pre_call_blocking(gateway: Gat assert blocked_response.status_code == 400, blocked_response.text assert _upstream_requests(gateway.upstream_url) == () finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) finally: delete_scenario(upstream_handle) @@ -404,6 +405,7 @@ def test_presidio_scope_matches_no_scope_behavior(gateway: Gateway, tmp_path: Pa bool, seconds=30, ) + _spend_row_for_response_id(no_scope_result.response_id) no_scope_analyzer_calls: Final = no_scope_analyzer.drain() no_scope_anonymizer_calls: Final = no_scope_anonymizer.drain() no_scope_call_counts: Final = ( @@ -431,6 +433,7 @@ def test_presidio_scope_matches_no_scope_behavior(gateway: Gateway, tmp_path: Pa bool, seconds=30, ) + _spend_row_for_response_id(scoped_result.response_id) scoped_analyzer_calls: Final = scoped_analyzer.drain() scoped_anonymizer_calls: Final = scoped_anonymizer.drain() scoped_call_counts: Final = ( @@ -678,7 +681,7 @@ def test_database_guardrail_load_keeps_pre_call_blocking( for entry in entries ) == ((identity, "pre_call", "guardrail_intervened"),), entries finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) finally: delete_scenario(upstream_handle) @@ -799,7 +802,7 @@ def test_G6_database_guardrail_polling_normalizes_invalid_scope_without_reinitia ) == ((identity, "pre_call", "guardrail_intervened"),), (call_id, entries) assert _upstream_requests(gateway.upstream_url) == () finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) finally: delete_scenario(upstream_handle) @@ -952,7 +955,7 @@ def test_management_post_validates_logging_only_scope( assert isinstance(after_list, list), after_list assert identity not in {object_value(item)["guardrail_name"] for item in after_list}, after_list finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) def test_H5_management_put_rejection_preserves_database_and_runtime(gateway: Gateway, tmp_path: Path) -> None: @@ -1074,7 +1077,7 @@ def test_H5_management_put_rejection_preserves_database_and_runtime(gateway: Gat for entry in entries ) == ((identity, "pre_call", "guardrail_intervened"),), (call_id, entries) finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) delete_scenario(upstream_handle) @@ -1153,7 +1156,7 @@ def test_H6_management_patch_clears_scope_when_switching_to_blocking_only_mode( for entry in entries ) == ((identity, ("pre_call",), "guardrail_intervened"),), entries finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) delete_scenario(upstream_handle) @@ -1240,7 +1243,7 @@ def test_H7_management_patch_rejection_preserves_pre_call_guardrail(gateway: Gat for entry in entries ) == ((identity, "pre_call", "guardrail_intervened"),), (call_id, entries) finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) delete_scenario(upstream_handle) @@ -1331,7 +1334,7 @@ def test_management_patch_default_on_heals_stored_scope( for entry in entries ) == ((identity, "pre_call", "guardrail_intervened"),), entries finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) finally: delete_scenario(upstream_handle) @@ -1429,7 +1432,7 @@ def test_H10_management_patch_null_scope_restores_both_directions(gateway: Gatew (identity, "logging_only", "guardrail_intervened"), ), entries finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) delete_scenario(upstream_handle) @@ -1517,7 +1520,7 @@ def test_H11_management_patch_same_scope_is_idempotent_and_output_only(gateway: (entry["guardrail_name"], entry["guardrail_mode"], entry["guardrail_status"]) for entry in entries ) == tuple((identity, "logging_only", "guardrail_intervened") for _ in expected_directions), entries finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) delete_scenario(upstream_handle) @@ -1550,7 +1553,7 @@ def test_H12_management_reads_expose_typed_logging_only_scope(gateway: Gateway, assert object_value(info["litellm_params"])["logging_only_scope"] == "input", info assert object_value(matches[0]["litellm_params"])["logging_only_scope"] == "input", matches finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) def test_H13_unauthenticated_management_and_chat_requests_do_not_scan(gateway: Gateway, tmp_path: Path) -> None: @@ -1629,7 +1632,7 @@ def test_K1_post_rejects_continue_flag_outside_logging_only(gateway: Gateway, tm assert after_list == before_list, (before_list, after_list) assert identity not in {object_value(item)["guardrail_name"] for item in after_list}, after_list finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) def test_K3_patch_flag_rejection_preserves_raw_stored_row(gateway: Gateway, tmp_path: Path) -> None: @@ -1675,7 +1678,7 @@ def test_K3_patch_flag_rejection_preserves_raw_stored_row(gateway: Gateway, tmp_ } == {key: after_params[key] for key in after_params if key != "api_key"}, (before_params, after_params) assert str(after_params["api_key"]).startswith("litellm_enc::"), after_params finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) def test_K4_patch_dropping_logging_only_mode_clears_stored_flag(gateway: Gateway, tmp_path: Path) -> None: @@ -1713,7 +1716,7 @@ def test_K4_patch_dropping_logging_only_mode_clears_stored_flag(gateway: Gateway assert params.get("logging_only_continue_on_input_failure") is None, persisted assert params["mode"] == ["pre_call"], persisted finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) def test_K5_yaml_flag_on_blocking_guardrail_boots_and_keeps_blocking(gateway: Gateway, tmp_path: Path) -> None: @@ -1759,5 +1762,5 @@ def test_K5_yaml_flag_on_blocking_guardrail_boots_and_keeps_blocking(gateway: Ga log_text: Final = owned.log.read_text() assert "Ignoring logging_only_continue_on_input_failure" in log_text, log_text finally: - _delete_database_guardrail(identity) + _delete_database_guardrail(gateway, identity) delete_scenario(upstream_handle) diff --git a/tests/integration/observability/test_logging_only_scope_runtime.py b/tests/integration/observability/test_logging_only_scope_runtime.py index 8da26f20eae..271d8d0e24d 100644 --- a/tests/integration/observability/test_logging_only_scope_runtime.py +++ b/tests/integration/observability/test_logging_only_scope_runtime.py @@ -1098,7 +1098,7 @@ def test_X2_scope_patch_toggles_during_concurrent_requests_keep_one_scan_per_res with wire_server(policy) as edge: config: Final = _empty_proxy_configuration(tmp_path, identity) with ( - _database_guardrail(identity, edge.url, "output", mode="logging_only"), + _database_guardrail(gateway, identity, edge.url, "output", mode="logging_only"), owned_proxy(gateway, tmp_path, {}, config=config, workers=1) as candidate, ): guardrails: Final = candidate.get("/v2/guardrails/list")["guardrails"] diff --git a/tests/integration/observability/test_otel_conversation_id.py b/tests/integration/observability/test_otel_conversation_id.py index d7f4de2961b..cd095991e53 100644 --- a/tests/integration/observability/test_otel_conversation_id.py +++ b/tests/integration/observability/test_otel_conversation_id.py @@ -1,5 +1,4 @@ import asyncio -import base64 import json import re import signal @@ -118,17 +117,6 @@ def _responses_reply(identity: str, stream: bool) -> Reply: ) -def _decoded_responses_id(identity: str) -> str: - try: - return base64.b64decode(identity.removeprefix("resp_").encode()).decode() - except (ValueError, UnicodeDecodeError): - return identity - - -def _canonical_id(identity: str) -> str: - return _decoded_responses_id(identity).rpartition("response_id:")[2] - - def _sse_events(text: str) -> tuple[dict[str, JsonValue], ...]: return tuple( json.loads(line[6:]) for line in text.splitlines() if line.startswith("data: ") and line != "data: [DONE]" @@ -170,8 +158,7 @@ class Collector: return tuple( attributes for attributes in self.attributes() - if isinstance(logged := attributes.get("gen_ai.response.id", {}).get("stringValue"), str) - and _canonical_id(logged) == _canonical_id(response_id) + if attributes.get("gen_ai.response.id", {}).get("stringValue") == response_id ) def conversation_ids(self, response_id: str) -> tuple[str | None, ...]: @@ -183,10 +170,6 @@ class Collector: def single_span(self, response_id: str) -> str | None: return eventually(lambda: self.conversation_ids(response_id), lambda values: len(values) == 1, seconds=30)[0] - def logged_id(self, response_id: str) -> str: - spans: Final = eventually(lambda: self.spans(response_id), lambda values: len(values) == 1, seconds=30) - return str(spans[0]["gen_ai.response.id"]["stringValue"]) - @pytest.fixture(scope="session") def collector() -> Iterator[Collector]: @@ -437,12 +420,13 @@ def test_responses_stream_raw_metadata_session_id_lands_as_conversation_id(rig: completed: Final = tuple(event for event in events if event["type"] == "response.completed") assert len(completed) == 1, events assert completed[0]["response"]["output"][0]["id"] == f"msg_resp_{marker}", completed - assert str(completed[0]["response"]["id"]).startswith("resp_"), completed + client_id: Final = str(completed[0]["response"]["id"]) + assert client_id.startswith("resp_"), completed assert rig.upstream_bodies(marker) == ( {"model": "gpt-4o-mini", "input": marker, "metadata": {"session_id": session}, "stream": True}, ) - assert rig.sink.single_span(f"resp_{marker}") == session - assert rig.spend_session(rig.sink.logged_id(f"resp_{marker}")) == session + assert rig.sink.single_span(client_id) == session + assert rig.spend_session(client_id) == session @pytest.mark.covers("other.observability.otel.conversation_id_from_metadata_chat_raw") @@ -689,15 +673,11 @@ def _burst(rig: Rig, count: int, session_for: Mapping[int, str]) -> tuple[tuple[ return tuple(pool.map(one, range(count))) -def _is_encrypted_responses_id(identity: str) -> bool: - return identity.startswith("resp_") and _decoded_responses_id(identity) == identity - - def _landed(rig: Rig, expected: Mapping[str, str]) -> dict[str, tuple[str, ...]]: spans: Final = rig.sink.attributes() return { session: tuple( - _canonical_id(str(attributes["gen_ai.response.id"]["stringValue"])) + str(attributes["gen_ai.response.id"]["stringValue"]) for attributes in spans if attributes.get(CONVERSATION, {}).get("stringValue") == session and "gen_ai.response.id" in attributes ) @@ -707,21 +687,13 @@ def _landed(rig: Rig, expected: Mapping[str, str]) -> dict[str, tuple[str, ...]] def _assert_exactly_once(rig: Rig, expected: Mapping[str, str], landed: Mapping[str, tuple[str, ...]]) -> None: spend: Final = eventually( - lambda: { - session: tuple(_canonical_id(identity) for identity in rig.spend_request_ids(session)) - for session in expected.values() - }, + lambda: {session: rig.spend_request_ids(session) for session in expected.values()}, lambda rows: all(len(values) >= 1 for values in rows.values()), seconds=70, ) assert landed == spend, (landed, spend) assert all(len(values) == 1 for values in landed.values()), landed - caller_visible: Final = { - session: (_canonical_id(identity),) - for identity, session in expected.items() - if not _is_encrypted_responses_id(identity) - } - assert {session: landed[session] for session in caller_visible} == caller_visible, landed + assert landed == {session: (identity,) for identity, session in expected.items()}, landed @pytest.mark.covers("other.observability.otel.conversation_id_sink_outage_recovers_exactly_once") diff --git a/tests/integration/observability/test_prometheus_provider_auth_failure.py b/tests/integration/observability/test_prometheus_provider_auth_failure.py index 13d264ca6b0..de1f19bc523 100644 --- a/tests/integration/observability/test_prometheus_provider_auth_failure.py +++ b/tests/integration/observability/test_prometheus_provider_auth_failure.py @@ -995,7 +995,7 @@ def _gated(gateway: Gateway, cell: str, key: str | None) -> httpx.Response: def recorded_before(cell: str) -> list[tuple[str, str, str, float]]: - if cell in ("invalid-key", "expired-key"): + if cell in ("invalid-key", "missing-key", "expired-key", "blocked-key"): return [] return sorted([(FAILURES, "", "", 1.0), (TOTALS, "", "", 1.0), (LLM_FAILED, identity(cell), "", 1.0)]) @@ -1020,7 +1020,9 @@ def test_a_request_the_proxy_rejects_itself_never_marks_the_deployment_down_and_ assert response.status_code == (403 if cell == "no-model-access" else 401), response.text assert rig.upstream.drain() == () samples: Final = until(rig.gateway, PROXY_FAILED, requested_model=name(cell)) + assert values(samples, PROXY_FAILED, requested_model=name(cell)) == [1.0], recorded(samples) assert deployment_rows(samples, cell) == recorded_before(cell), recorded(samples, requested_model=name(cell)) + assert values(samples, STATE, model_id=identity(cell)) == [], recorded(samples) def test_a_key_rate_limit_rejected_at_the_proxy_is_still_counted_as_before(rig: Rig) -> None: diff --git a/tests/integration/observability/test_signoz_delivery.py b/tests/integration/observability/test_signoz_delivery.py index e25126e4fa8..93539d7641b 100644 --- a/tests/integration/observability/test_signoz_delivery.py +++ b/tests/integration/observability/test_signoz_delivery.py @@ -1,5 +1,4 @@ import asyncio -import base64 import json import re import signal @@ -9,7 +8,6 @@ from collections import deque from collections.abc import Iterator, Mapping, Sequence from concurrent.futures import ThreadPoolExecutor from dataclasses import dataclass -from functools import partial from pathlib import Path from typing import Final @@ -137,17 +135,6 @@ def _upstream(request: Request) -> Reply: return _chat_reply(f"chatcmpl-{marker}", stream) -def _decoded_responses_id(identity: str) -> str: - try: - return base64.b64decode(identity.removeprefix("resp_").encode()).decode() - except (ValueError, UnicodeDecodeError): - return identity - - -def _canonical_id(identity: str) -> str: - return _decoded_responses_id(identity).rpartition("response_id:")[2] - - def _sse_events(text: str) -> tuple[dict[str, JsonValue], ...]: return tuple( object_value(JSON.validate_json(line[6:])) @@ -232,8 +219,7 @@ class Collector: return tuple( span for span in self.spans() - if RESPONSE_ID in span.attributes - and _canonical_id(span.attributes[RESPONSE_ID]) == _canonical_id(response_id) + if RESPONSE_ID in span.attributes and span.attributes[RESPONSE_ID] == response_id ) def single_span(self, response_id: str, *, elsewhere: "Collector | None" = None) -> Span: @@ -249,11 +235,8 @@ class Collector: def landed(self, response_ids: Sequence[str]) -> dict[str, int]: spans: Final = self.spans() return { - _canonical_id(identity): sum( - 1 - for span in spans - if RESPONSE_ID in span.attributes - and _canonical_id(span.attributes[RESPONSE_ID]) == _canonical_id(identity) + identity: sum( + 1 for span in spans if RESPONSE_ID in span.attributes and span.attributes[RESPONSE_ID] == identity ) for identity in response_ids } @@ -448,7 +431,7 @@ def _assert_operator_span(rig: Rig, response_id: str, marker: str) -> Span: span: Final = rig.sink.single_span(response_id) assert span.target == "/v1/traces", span assert span.ingestion_key == OPERATOR_KEY, span - assert rig.tenant_sink.landed((response_id,)) == {_canonical_id(response_id): 0} + assert rig.tenant_sink.landed((response_id,)) == {response_id: 0} bodies: Final = rig.upstream_bodies(marker) assert len(bodies) == 1, bodies assert "signoz" not in json.dumps(bodies[0]).replace(marker, ""), bodies[0] @@ -522,7 +505,7 @@ def test_responses_stream_raw_httpx_span_lands_once_after_the_stream_is_consumed marker: Final = _marker() response: Final = rig.proxy.request("POST", "/v1/responses", {"model": rig.model, "input": marker, "stream": True}) assert response.status_code == 200, response.text - _assert_operator_span(rig, _responses_id(response, marker), marker) + _assert_operator_span(rig, _responses_id(response), marker) def test_v2_flag_on_still_delivers_the_operator_span_with_the_ingestion_key(v2_rig: Rig) -> None: @@ -821,7 +804,7 @@ def _chat_id(response: httpx.Response) -> str: return next(iter(identities)) -def _responses_id(response: httpx.Response, marker: str) -> str: +def _responses_id(response: httpx.Response) -> str: if not _is_event_stream(response): return _body_id(response) completed: Final = tuple( @@ -830,7 +813,7 @@ def _responses_id(response: httpx.Response, marker: str) -> str: if event.get("type") == "response.completed" ) assert len(completed) == 1 and completed[0].startswith("resp_"), response.text - return f"resp_{marker}" + return completed[0] def _message_id(response: httpx.Response) -> str: @@ -852,7 +835,7 @@ def _burst(rig: Rig, count: int) -> tuple[tuple[int, str, str | None], ...]: stream: Final = index % 2 == 0 path, body, identity_of = ( ("/v1/chat/completions", {"model": rig.model, "messages": [{"role": "user", "content": marker}]}, _chat_id), - ("/v1/responses", {"model": rig.model, "input": marker}, partial(_responses_id, marker=marker)), + ("/v1/responses", {"model": rig.model, "input": marker}, _responses_id), ( "/v1/messages", {"model": rig.model, "max_tokens": 16, "messages": [{"role": "user", "content": marker}]}, @@ -874,8 +857,8 @@ def _assert_exactly_once(rig: Rig, identities: Sequence[str]) -> None: landed: Final = eventually( lambda: rig.sink.landed(identities), lambda seen: all(count >= 1 for count in seen.values()), seconds=80 ) - assert landed == {_canonical_id(identity): 1 for identity in identities}, landed - charged: Final = frozenset(identity for identity in identities if not identity.startswith("resp_")) + assert landed == {identity: 1 for identity in identities}, landed + charged: Final = frozenset(identities) spend: Final = eventually( lambda: read_rows( 'SELECT request_id FROM "LiteLLM_SpendLogs" WHERE request_id = ANY(%s::text[])', diff --git a/tests/integration/pricing/test_cost_margin_discount.py b/tests/integration/pricing/test_cost_margin_discount.py index b6cda8f125f..613fe72ed70 100644 --- a/tests/integration/pricing/test_cost_margin_discount.py +++ b/tests/integration/pricing/test_cost_margin_discount.py @@ -7,7 +7,7 @@ import httpx import pytest from integration._support.client import Gateway, eventually, object_value, string_value from integration._support.database import read_rows -from pydantic import BaseModel, JsonValue +from pydantic import BaseModel, ConfigDict, JsonValue class CostEstimate(BaseModel): @@ -110,6 +110,25 @@ def _assert_logged_spends(expectations: tuple[tuple[str, float], ...]) -> None: assert actual == pytest.approx(dict(expectations)), rows +class LoggedBreakdown(BaseModel): + model_config = ConfigDict(frozen=True) + + original_cost: float + discount_percent: float | None = None + discount_amount: float | None = None + margin_percent: float | None = None + margin_fixed_amount: float | None = None + margin_total_amount: float | None = None + + +def _logged_breakdown(request_id: str) -> LoggedBreakdown: + rows: Final = read_rows('SELECT metadata FROM "LiteLLM_SpendLogs" WHERE request_id = %s', (request_id,)) + assert len(rows) == 1, rows + metadata: Final = rows[0]["metadata"] + parsed: Final = object_value(json.loads(metadata) if isinstance(metadata, str) else metadata) + return LoggedBreakdown.model_validate(parsed["cost_breakdown"]) + + def _estimated(gateway: Gateway, model: str) -> CostEstimate: response: Final = gateway.request( "POST", "/cost/estimate", {"model": model, "input_tokens": 20, "output_tokens": 20} @@ -236,6 +255,17 @@ def test_discount_and_margin_reprice_a_request_and_survive_rejection(gateway: Ga (streamed_global_request_id, 0.12), ) ) + discounted: Final = _logged_breakdown(discounted_request_id) + assert discounted.original_cost == pytest.approx(0.06), discounted + assert discounted.discount_percent == pytest.approx(0.05), discounted + assert discounted.discount_amount == pytest.approx(0.06 * 0.05), discounted + margined: Final = _logged_breakdown(provider_margin_request_id) + assert margined.original_cost == pytest.approx(0.06), margined + assert margined.discount_percent == pytest.approx(0.05), margined + assert margined.discount_amount == pytest.approx(0.06 * 0.05), margined + assert margined.margin_percent == pytest.approx(0.1), margined + assert margined.margin_fixed_amount == pytest.approx(0.001), margined + assert margined.margin_total_amount == pytest.approx(0.057 * 0.1 + 0.001), margined rejections: Final = ( ( diff --git a/tests/integration/pricing/test_model_listing_token_limits.py b/tests/integration/pricing/test_model_listing_token_limits.py index 5f75b5bb38a..5473d802f7f 100644 --- a/tests/integration/pricing/test_model_listing_token_limits.py +++ b/tests/integration/pricing/test_model_listing_token_limits.py @@ -5,6 +5,7 @@ from pathlib import Path from typing import Final import pytest +from litellm import get_model_info from integration._support.client import Gateway, object_value from integration._support.process import owned_proxy from pydantic import JsonValue @@ -104,6 +105,21 @@ def test_v1_models_carries_cost_map_context_window_for_a_known_model(gateway: Ga assert listed["max_output_tokens"] == 16384, listed +def test_v1_models_keeps_a_sibling_override_off_a_plain_deployment_of_the_same_model(gateway: Gateway) -> None: + catalog_info: Final = get_model_info("openai/gpt-4o-mini") + with gateway.scenario() as scenario: + overridden: Final = scenario.model( + model="openai/gpt-4o-mini", + model_info={"max_input_tokens": 4321, "max_output_tokens": 987}, + ) + plain: Final = scenario.model(model="openai/gpt-4o-mini") + listed_override: Final = _listed_model(gateway, overridden) + listed_plain: Final = _listed_model(gateway, plain) + + assert _limits(listed_plain) == (catalog_info["max_input_tokens"], catalog_info["max_output_tokens"]) + assert _limits(listed_override) == (4321, 987) + + def test_v1_models_carries_deployment_model_info_limits_for_an_unknown_model(gateway: Gateway) -> None: unknown: Final = f"openai/custom-{uuid.uuid4().hex}" with gateway.scenario() as scenario: diff --git a/tests/integration/pricing/test_price_data_reload_prices.py b/tests/integration/pricing/test_price_data_reload_prices.py index 0aa3a3bcba2..aa0addb7673 100644 --- a/tests/integration/pricing/test_price_data_reload_prices.py +++ b/tests/integration/pricing/test_price_data_reload_prices.py @@ -25,9 +25,16 @@ _GEO: Final = f"au.{_ROW}" _FINETUNE: Final = "ft:gpt-audit-reload-2025-01-01" _CLAUDE: Final = "claude-audit-reload-sonnet" _MINI: Final = "gpt-audit-reload-mini" +_FREE: Final = "gpt-audit-reload-free" +_RULE_FREE: Final = "gpt-audit-rule-free" +_FILL_FREE: Final = "gpt-audit-fill-free" +_RULE_UNPRICED: Final = "gpt-audit-rule-unpriced" +_REPORTED_FREE: Final = "gpt-audit-reported-free" _USAGE: Final = re.compile(r"bill (\d+) (\d+) (\d+)") _CUSTOM: Final = MappingProxyType({"input_cost_per_token": 1.1e-06, "output_cost_per_token": 2.3e-06}) -_COST_MAP_LIMITS: Final = MappingProxyType({"MODEL_COST_MAP_MIN_MODEL_COUNT": "1", "MODEL_COST_MAP_MAX_SHRINK_RATIO": "0"}) +_COST_MAP_LIMITS: Final = MappingProxyType( + {"MODEL_COST_MAP_MIN_MODEL_COUNT": "1", "MODEL_COST_MAP_MAX_SHRINK_RATIO": "0"} +) _PUBLISHED_SCALE: Final = 2.0 _CATALOG: Final[Mapping[str, Mapping[str, JsonValue]]] = MappingProxyType( { @@ -60,6 +67,13 @@ _CATALOG: Final[Mapping[str, Mapping[str, JsonValue]]] = MappingProxyType( "output_cost_per_token": 1.5e-05, "cache_read_input_token_cost": 3e-07, }, + _FILL_FREE: {"litellm_provider": "openai", "mode": "chat"}, + _FREE: { + "litellm_provider": "openai", + "mode": "chat", + "input_cost_per_token": 0.0, + "output_cost_per_token": 0.0, + }, _MINI: { "litellm_provider": "openai", "mode": "chat", @@ -99,6 +113,8 @@ class _Deployment: prices: Mapping[str, float] usage: _Usage rates: Callable[[float], _Rates | None] + reported_cost: float | None = None + listed_rates: Callable[[float], _Rates | None] | None = None @dataclass(frozen=True, slots=True) @@ -107,10 +123,23 @@ class _Charge: expected: float -def _catalog(scale: float) -> dict[str, dict[str, JsonValue]]: +def _catalog(scale: float) -> dict[str, JsonValue]: return { - model: {name: value * scale if isinstance(value, float) else value for name, value in row.items()} - for model, row in _CATALOG.items() + **{ + model: {name: value * scale if isinstance(value, float) else value for name, value in row.items()} + for model, row in _CATALOG.items() + }, + "fallback_generalizations": { + "rules": [ + { + "name": "free-pricing", + "pattern": f"({_RULE_FREE}|{_FILL_FREE})", + "fill_missing_for_providers": ["openai"], + "model_info": {"mode": "chat", "input_cost_per_token": 0.0, "output_cost_per_token": 0.0}, + }, + {"name": "unpriced-capabilities", "pattern": _RULE_UNPRICED, "model_info": {"mode": "chat"}}, + ] + }, } @@ -240,6 +269,7 @@ def _reply(request: Request) -> Reply: "completion_tokens": usage.completion, "total_tokens": usage.prompt + usage.completion, "prompt_tokens_details": {"cached_tokens": usage.cached}, + **({"cost": 0.0} if object_value(json.loads(request.body))["model"] == _REPORTED_FREE else {}), }, } ).encode() @@ -281,10 +311,16 @@ def _billed(client: httpx.Client, key: str, deployment: _Deployment) -> tuple[st def _charged_as_listed(proxy: Gateway, deployment: _Deployment, scale: float) -> _Charge: rates: Final = deployment.rates(scale) - assert _listed_rates(proxy, deployment.name) == _expected_listing(rates), deployment.name + assert _listed_rates(proxy, deployment.name) == _expected_listing( + deployment.listed_rates(scale) if deployment.listed_rates is not None else rates + ), deployment.name request_id, charged = _billed(proxy.client, proxy.key, deployment) - expected: Final = _expected_cost(rates, deployment.usage) - assert charged == (None if rates is None else pytest.approx(expected, rel=1e-6)), deployment.name + expected: Final = ( + deployment.reported_cost if deployment.reported_cost is not None else _expected_cost(rates, deployment.usage) + ) + assert charged == ( + None if rates is None and deployment.reported_cost is None else pytest.approx(expected, rel=1e-6) + ), deployment.name return _Charge(request_id=request_id, expected=expected) @@ -352,8 +388,31 @@ def test_price_data_reload_reprices_catalog_deployments_and_keeps_custom_prices( _Usage(2000, 1000, 1000), _catalog_rates(_FINETUNE), ), - _Deployment("finetune-custom", f"openai/{_FINETUNE}:org:suffix:z", _CUSTOM, _Usage(2000, 0, 1000), _custom_rates), + _Deployment( + "finetune-custom", f"openai/{_FINETUNE}:org:suffix:z", _CUSTOM, _Usage(2000, 0, 1000), _custom_rates + ), _Deployment("cross-provider-unpriced", f"azure/{_CLAUDE}", {}, _Usage(2000, 1000, 1000), _unpriced), + _Deployment("catalog-free", f"openai/{_FREE}", {}, _Usage(2000, 1000, 1000), _catalog_rates(_FREE)), + _Deployment("rule-free", f"openai/{_RULE_FREE}", {}, _Usage(2000, 1000, 1000), _catalog_rates(_FREE)), + _Deployment( + "fill-rule-free", + f"openai/{_FILL_FREE}", + {}, + _Usage(2000, 1000, 1000), + _catalog_rates(_FREE), + listed_rates=_unpriced, + ), + _Deployment("rule-unpriced", f"openai/{_RULE_UNPRICED}", {}, _Usage(2000, 1000, 1000), _unpriced), + _Deployment( + "provider-reported-free", f"openrouter/{_REPORTED_FREE}", {}, _Usage(2000, 1000, 1000), _unpriced, 0.0 + ), + _Deployment( + "cross-provider-free", + f"azure/{_CLAUDE}", + {"input_cost_per_token": 0.0, "output_cost_per_token": 0.0}, + _Usage(2000, 1000, 1000), + _catalog_rates(_FREE), + ), _Deployment( "region-custom-above-threshold", f"bedrock/ap-northeast-1.{_ROW}", diff --git a/tests/integration/providers/_mantle_gpt_prompt_cache_support.py b/tests/integration/providers/_mantle_gpt_prompt_cache_support.py index 8f497fea74f..96261bab8b2 100644 --- a/tests/integration/providers/_mantle_gpt_prompt_cache_support.py +++ b/tests/integration/providers/_mantle_gpt_prompt_cache_support.py @@ -475,10 +475,6 @@ def row_key(request_id: str) -> str: return upstream_id_of(request_id.split("_cache_hit", 1)[0]) -def caller_sees_upstream_id(endpoint: Endpoint, *, stream: bool) -> bool: - return (endpoint, stream) != ("messages", True) - - def usage_of(payload: Mapping[str, JsonValue]) -> dict[str, JsonValue]: usage: Final = payload.get("usage") return JSON.validate_python(usage) if isinstance(usage, dict) else {} @@ -733,10 +729,9 @@ def marked_cell(gateway: Gateway, endpoint: Endpoint, *, stream: bool) -> None: assert_answered(outcome, marker) assert_wire(received, expected_wire(GPT, prompt_text(marker), endpoint=endpoint, marked=True), streaming=stream) assert_usage(endpoint, outcome.usage) - row: Final = success_row(name, marker) + row: Final = success_row(name, marker, outcome.response_id) assert_priced_row(row, GPT) - if caller_sees_upstream_id(endpoint, stream=stream): - assert row_key(str(row["request_id"])) == outcome.response_id, (row, outcome.response_id) + assert row_key(str(row["request_id"])) == outcome.response_id, (row, outcome.response_id) if not stream: assert math.isclose(float(outcome.headers["x-litellm-response-cost"]), expected_spend(GPT), rel_tol=1e-9), ( outcome.headers @@ -901,7 +896,7 @@ def assert_marked_sdk_cell( only_received(wire), expected_wire(GPT, prompt_text(marker), endpoint=endpoint, marked=True), streaming=stream ) assert_usage(endpoint, outcome.usage) - assert_priced_row(success_row(name, marker), GPT) + assert_priced_row(success_row(name, marker, outcome.response_id), GPT) HOSTILE_OPTIONS: Final[dict[str, JsonValue]] = { diff --git a/tests/integration/providers/test_anthropic_refusal_stop_details_wire.py b/tests/integration/providers/test_anthropic_refusal_stop_details_wire.py index c9a85545d8b..8774d590b37 100644 --- a/tests/integration/providers/test_anthropic_refusal_stop_details_wire.py +++ b/tests/integration/providers/test_anthropic_refusal_stop_details_wire.py @@ -201,20 +201,27 @@ def _marker() -> str: return uuid.uuid4().hex +def _bedrock_invoke_deployment( + scenario: Scenario, wire_url: str, model_info: Mapping[str, JsonValue] | None = None +) -> str: + return scenario.model( + model=f"bedrock/invoke/{BEDROCK_MODEL}", + model_info=model_info, + api_base=wire_url, + aws_access_key_id="AKIASCRIPTEDPROVIDER", + aws_secret_access_key="scripted-secret", + aws_region_name="us-east-1", + aws_bedrock_runtime_endpoint=wire_url, + ) + + def _deployment(scenario: Scenario, provider: Provider, rig: Rig) -> str: wire_url: Final = rig.wire.url match provider: case "anthropic": return scenario.model(model=f"anthropic/{MODEL}", api_base=wire_url, api_key=_ANTHROPIC_KEY) case "bedrock_invoke": - return scenario.model( - model=f"bedrock/invoke/{BEDROCK_MODEL}", - api_base=wire_url, - aws_access_key_id="AKIASCRIPTEDPROVIDER", - aws_secret_access_key="scripted-secret", - aws_region_name="us-east-1", - aws_bedrock_runtime_endpoint=wire_url, - ) + return _bedrock_invoke_deployment(scenario, wire_url) case "claude_platform": return scenario.model( model=f"bedrock/claude_platform/{MODEL}", @@ -1184,7 +1191,7 @@ def test_stream_cache_hit_skips_cached_provider_fields_that_are_not_an_object(ri assert tuple(_message_fields(event["response"]) for event in stale_logs) == ((),) * len(stale_logs), stale_logs -JsonModeRoute: TypeAlias = Literal["anthropic_native", "anthropic_tool", "bedrock_invoke"] +JsonModeRoute: TypeAlias = Literal["anthropic_native", "anthropic_tool", "bedrock_invoke_native", "bedrock_invoke_tool"] _UNMAPPED_MODEL: Final = "claude-scripted-9" _JSON_ANSWER: Final = json.dumps({"answer": DOCS_PARTIAL_TEXT}) @@ -1216,11 +1223,20 @@ _JSON_MODE_CASES: Final[Mapping[str, JsonModeCase]] = { "anthropic_tool_enveloped": JsonModeCase( "anthropic_tool", "jsonheld", ENVELOPED_PARTIAL_JSON, _JSON_ANSWER, "content_filter", "stop", "json_tool" ), + "bedrock_invoke_native": JsonModeCase( + "bedrock_invoke_native", + "partial", + DOCS_PARTIAL_TEXT, + DOCS_PARTIAL_TEXT, + "content_filter", + "content_filter", + "native", + ), "bedrock_invoke_declared": JsonModeCase( - "bedrock_invoke", "jsontool", DECLARED_PARTIAL_JSON, _JSON_ANSWER, "content_filter", "stop", "json_tool" + "bedrock_invoke_tool", "jsontool", DECLARED_PARTIAL_JSON, _JSON_ANSWER, "content_filter", "stop", "json_tool" ), "bedrock_invoke_enveloped": JsonModeCase( - "bedrock_invoke", "jsonheld", ENVELOPED_PARTIAL_JSON, _JSON_ANSWER, "content_filter", "stop", "json_tool" + "bedrock_invoke_tool", "jsonheld", ENVELOPED_PARTIAL_JSON, _JSON_ANSWER, "content_filter", "stop", "json_tool" ), } @@ -1234,8 +1250,15 @@ def _json_mode_deployment(scenario: Scenario, route: JsonModeRoute, rig: Rig) -> scenario.model(model=f"anthropic/{_UNMAPPED_MODEL}", api_base=rig.wire.url, api_key=_ANTHROPIC_KEY), "anthropic", ) - case "bedrock_invoke": + case "bedrock_invoke_native": return _deployment(scenario, "bedrock_invoke", rig), "bedrock_invoke" + case "bedrock_invoke_tool": + return ( + _bedrock_invoke_deployment( + scenario, rig.wire.url, {"supports_bedrock_native_structured_output": False} + ), + "bedrock_invoke", + ) def _requested_format(body: Mapping[str, JsonValue]) -> tuple[bool, bool]: diff --git a/tests/integration/providers/test_anthropic_tool_search_result_matrix_wire.py b/tests/integration/providers/test_anthropic_tool_search_result_matrix_wire.py index 6879d1f8acd..d4c0e2651d8 100644 --- a/tests/integration/providers/test_anthropic_tool_search_result_matrix_wire.py +++ b/tests/integration/providers/test_anthropic_tool_search_result_matrix_wire.py @@ -482,15 +482,20 @@ def test_duplicated_search_result_blocks_rebuild_the_call_once(gateway: Gateway, @pytest.mark.parametrize( - ("status", "kind", "caller_status"), + ("status", "kind", "caller_status", "caller_error_type", "caller_error_code"), ( - pytest.param(400, "invalid_request_error", 400, id="400"), - pytest.param(401, "authentication_error", 401, id="401"), - pytest.param(529, "overloaded_error", 500, id="529"), + pytest.param(400, "invalid_request_error", 400, None, None, id="400"), + pytest.param(401, "authentication_error", 401, None, None, id="401"), + pytest.param(529, "overloaded_error", 503, "service_unavailable_error", "server_is_overloaded", id="529"), ), ) def test_provider_error_on_the_replay_reaches_the_caller( - gateway: Gateway, status: int, kind: str, caller_status: int + gateway: Gateway, + status: int, + kind: str, + caller_status: int, + caller_error_type: str | None, + caller_error_code: str | None, ) -> None: marker: Final = uuid.uuid4().hex @@ -508,6 +513,11 @@ def test_provider_error_on_the_replay_reaches_the_caller( received: Final = wire.drain() assert second.status_code == caller_status, second.text assert f"scripted {kind} {marker}" in second.text, second.text + if caller_error_type is not None: + payload: Final = JSON_OBJECT.validate_json(second.content) + error: Final = JSON_OBJECT.validate_python(payload["error"]) + assert error["type"] == caller_error_type, second.text + assert error["code"] == caller_error_code, second.text assert len(received) >= 2, received assert wire_assistant(received[1]) == list(SEARCH_TURN), received[1].body assert gateway.client.get("/health/liveliness").status_code == 200 diff --git a/tests/integration/providers/test_azure_ai_claude_messages_wire.py b/tests/integration/providers/test_azure_ai_claude_messages_wire.py index c150de7520b..d39c6d2d2c1 100644 --- a/tests/integration/providers/test_azure_ai_claude_messages_wire.py +++ b/tests/integration/providers/test_azure_ai_claude_messages_wire.py @@ -1,10 +1,12 @@ +from collections.abc import Iterator from typing import Final import anthropic import pytest from anthropic.types import Message from integration._support import claude_code as cc -from integration._support.client import Gateway +from integration._support.client import Gateway, gateway_from_environment +from integration._support.process import owned_proxy from integration._support.wire import Reply, Request, wire_server from pydantic import JsonValue, TypeAdapter @@ -144,8 +146,23 @@ def test_azure_ai_claude_messages_preserves_target_auth_beta_and_typed_response( assert _JSON_OBJECT.validate_json(provider_request.body) == expected_provider_body, provider_request.body +@pytest.fixture(scope="module") +def local_beta_map_gateway(tmp_path_factory: pytest.TempPathFactory) -> Iterator[Gateway]: + with ( + gateway_from_environment() as shared, + owned_proxy( + shared, + tmp_path_factory.mktemp("azure-ai-local-beta-map"), + {"LITELLM_LOCAL_ANTHROPIC_BETA_HEADERS": "true"}, + ) as owned, + ): + yield owned + + @pytest.mark.parametrize("stream", [False, True], ids=["non_stream", "stream"]) -def test_azure_ai_claude_messages_filters_auto_injected_betas_by_azure_support(gateway: Gateway, stream: bool) -> None: +def test_azure_ai_claude_messages_forwards_the_auto_injected_betas_azure_accepts( + local_beta_map_gateway: Gateway, stream: bool +) -> None: identity: Final = f"msg_azure_claude_beta_filter_{stream}" api_path: Final = "/anthropic/v1/messages" reply_body: Final = cc.message_reply(identity, _BACKEND, _CONTENT, _USAGE) @@ -172,7 +189,7 @@ def test_azure_ai_claude_messages_filters_auto_injected_betas_by_azure_support(g "context_management": context_management, } expected_provider_body: Final = {**request_body_template, "model": _BACKEND} - expected_beta: Final = "structured-outputs-2025-11-13" + expected_beta: Final = "compact-2026-01-12,structured-outputs-2025-11-13" def respond(request: Request) -> Reply: assert request.method == "POST" and request.target == api_path, request.target @@ -185,7 +202,7 @@ def test_azure_ai_claude_messages_filters_auto_injected_betas_by_azure_support(g return Reply(content_type="text/event-stream", chunks=stream_reply) return Reply(body=reply_body) - with wire_server(respond) as wire, gateway.scenario() as scenario: + with wire_server(respond) as wire, local_beta_map_gateway.scenario() as scenario: model: Final = scenario.model( model=f"azure_ai/{_BACKEND}", api_base=wire.url, @@ -193,8 +210,8 @@ def test_azure_ai_claude_messages_filters_auto_injected_betas_by_azure_support(g num_retries=0, ) with anthropic.Anthropic( - api_key=gateway.key, - base_url=str(gateway.client.base_url), + api_key=local_beta_map_gateway.key, + base_url=str(local_beta_map_gateway.client.base_url), max_retries=0, ) as client: if stream: diff --git a/tests/integration/providers/test_bedrock_converse_missing_content_wire.py b/tests/integration/providers/test_bedrock_converse_missing_content_wire.py index 3baeebcd74a..1f3bded035b 100644 --- a/tests/integration/providers/test_bedrock_converse_missing_content_wire.py +++ b/tests/integration/providers/test_bedrock_converse_missing_content_wire.py @@ -547,7 +547,7 @@ def test_r21_responses_stream_input_item_without_content_after_an_assistant_item assert received["messages"] == [_CONVERSE_QUESTION, _CONVERSE_ANSWERED], received (row,) = _success_rows(marker, 1) assert row["call_type"] == "aresponses" and row["end_user"] == marker, row - assert row["request_id"] == _inner_response_id(str(completed["response"]["id"])), (row, completed) + assert row["request_id"] == str(completed["response"]["id"]), (row, completed) def test_r22_passthrough_converse_forwards_a_message_without_content_verbatim(gateway: Gateway) -> None: diff --git a/tests/integration/providers/test_bedrock_converse_stream_event_frames_wire.py b/tests/integration/providers/test_bedrock_converse_stream_event_frames_wire.py index a1432ffd7a0..19aa11a8e36 100644 --- a/tests/integration/providers/test_bedrock_converse_stream_event_frames_wire.py +++ b/tests/integration/providers/test_bedrock_converse_stream_event_frames_wire.py @@ -1,7 +1,6 @@ import asyncio import base64 import json -import os import re import threading import uuid @@ -26,8 +25,6 @@ from integration._support.upstream import _aws_event_frame, aws_event_stream_fra from integration._support.wire import Reply, Request, Wire, wire_server from pydantic import JsonValue, TypeAdapter -from litellm.proxy.common_utils.encrypt_decrypt_utils import decrypt_if_encrypted_with - pytestmark: Final = pytest.mark.shares_worker_state _MODEL_ID: Final = "global.moonshotai.kimi-k3" @@ -43,7 +40,6 @@ _REJECTION: Final = "structured output schema uses unsupported regex negative lo _THROTTLED: Final = "Too many requests, please wait before trying again" _UNKNOWN_TYPE: Final = "somethingBedrockAddedLater" _UNKNOWN_ONLY: Final = "none of its 1 events carried a known event type" -_SIGNING_KEY: Final = os.environ.get("LITELLM_SALT_KEY", "sk-integration-salt") _JSON_HEADERS: Final = MappingProxyType({":content-type": "application/json", ":message-type": "event"}) _USAGE: Final[dict[str, JsonValue]] = {"usage": {"inputTokens": 11, "outputTokens": 4, "totalTokens": 15}} _RESPONSE: Final = json.dumps( @@ -277,17 +273,9 @@ def _responses_text(events: Iterable[dict[str, JsonValue]]) -> str: ) -def _inner_response_id(identity: str) -> str: - managed: Final = decrypt_if_encrypted_with(identity.removeprefix("resp_"), _SIGNING_KEY) - assert managed is not None, identity - issued: Final = managed.split(";", 1)[0].rsplit("response_id:", 1)[1] - decoded: Final = base64.b64decode(issued.removeprefix("resp_")).decode() - return decoded.rsplit("response_id:", 1)[1] - - def _completed_response_id(events: Iterable[dict[str, JsonValue]]) -> str: (completed,) = tuple(event for event in events if event.get("type") == "response.completed") - return _inner_response_id(str(_JSON.validate_python(completed["response"])["id"])) + return str(_JSON.validate_python(completed["response"])["id"]) def _only_received(wire: Wire) -> tuple[str, dict[str, JsonValue]]: diff --git a/tests/integration/providers/test_bedrock_gpt_responses_native_wire.py b/tests/integration/providers/test_bedrock_gpt_responses_native_wire.py index 3d6eb7fcaff..0788b9ac85a 100644 --- a/tests/integration/providers/test_bedrock_gpt_responses_native_wire.py +++ b/tests/integration/providers/test_bedrock_gpt_responses_native_wire.py @@ -62,12 +62,12 @@ def _body(request: Request) -> dict[str, JsonValue]: # ciphertext the caller received, because the spend row id is read from response_obj["id"] before the # ResponsesIDSecurity hook rewrites it in place; the row is looked up under both ids until that ordering is fixed on # main -def _spend_row(client_id: str, issued_id: str) -> dict[str, JsonValue]: +def _spend_row(*request_ids: str) -> dict[str, JsonValue]: rows: Final = eventually( lambda: read_rows( 'SELECT model_group, status, prompt_tokens, completion_tokens FROM "LiteLLM_SpendLogs" ' "WHERE request_id = ANY(%s)", - ([client_id, issued_id],), # pyright: ignore[reportArgumentType] # psycopg adapts the list to a text array + (list(request_ids),), # pyright: ignore[reportArgumentType] # psycopg adapts the list to a text array ), lambda found: len(found) == 1, seconds=70, @@ -120,4 +120,4 @@ async def test_async_openai_sdk_responses_stream_is_served_by_the_native_respons assert issued.upstream == f"resp_upstream_{marker}", completed.response.id request: Final = _native_request(wire) assert _body(request) == {"model": GPT, "input": _prompt(marker), "stream": True}, request.body - assert _spend_row(completed.response.id, issued.issued) == _success_row(model) + assert _spend_row(completed.response.id) == _success_row(model) diff --git a/tests/integration/providers/test_bedrock_kimi_k3_cache_point_wire.py b/tests/integration/providers/test_bedrock_kimi_k3_cache_point_wire.py index 4441582fb6b..05e08c5fc27 100644 --- a/tests/integration/providers/test_bedrock_kimi_k3_cache_point_wire.py +++ b/tests/integration/providers/test_bedrock_kimi_k3_cache_point_wire.py @@ -456,7 +456,7 @@ def _inner_response_id(identity: str) -> str: def _completed_response_id(events: Iterable[dict[str, JsonValue]]) -> str: (completed,) = tuple(event for event in events if event.get("type") == "response.completed") - return _inner_response_id(str(_JSON.validate_python(completed["response"])["id"])) + return str(_JSON.validate_python(completed["response"])["id"]) def _chat_text(body: Mapping[str, JsonValue]) -> str: @@ -911,7 +911,7 @@ async def test_k06_openai_sdk_async_responses_stream_reaches_kimi_without_a_cach received: Final = _only_received(rig.wire) assert received.model == _KIMI_US and received.streaming, received assert received.cache_points == 0, received.body - _success_row(_inner_response_id(completed[0].id)) + _success_row(completed[0].id) _LOCATIONS: Final = ( @@ -1251,17 +1251,19 @@ def test_s01_to_s06_an_odd_typed_flag_is_read_as_false_never_as_true( @pytest.mark.timeout(600) -def test_s10_s11_two_deployments_of_one_arn_share_the_flag_and_a_delete_leaves_it_in_place(gateway: Gateway) -> None: +def test_s10_s11_two_deployments_of_one_arn_keep_their_own_flags_and_a_delete_changes_neither( + gateway: Gateway, +) -> None: arn: Final = _arn("shared") with wire_server(_peer()) as wire, gateway.scenario() as scenario: flagged: Final = _deployment( gateway, scenario, wire, f"bedrock/{arn}", {"supports_prompt_cache_breakpoint": False}, cleanup=False ) plain: Final = _deployment(gateway, scenario, wire, f"bedrock/{arn}") - for name in (flagged, plain): + for name, cache_points in ((flagged, 0), (plain, 2)): outcome, received = _observe_at(gateway, wire, "chat", _chat_body(name, _prompt(), _SYSTEM_AND_USER)) _assert_answered(outcome) - assert received.cache_points == 0, (name, received.body) + assert received.cache_points == cache_points, (name, received.body) _success_row(outcome.response_id) flagged_identity: Final = _model_id(flagged) gateway.post("/model/delete", {"id": flagged_identity}) @@ -1276,7 +1278,7 @@ def test_s10_s11_two_deployments_of_one_arn_share_the_flag_and_a_delete_leaves_i wire.drain() after, after_received = _observe_at(gateway, wire, "chat", _chat_body(plain, _prompt(), _SYSTEM_AND_USER)) _assert_answered(after) - assert after_received.cache_points == 0, after_received.body + assert after_received.cache_points == 2, after_received.body _success_row(after.response_id) diff --git a/tests/integration/providers/test_bedrock_mantle_claude_chat_wire.py b/tests/integration/providers/test_bedrock_mantle_claude_chat_wire.py index d4f9533fcdc..3652e49fe8a 100644 --- a/tests/integration/providers/test_bedrock_mantle_claude_chat_wire.py +++ b/tests/integration/providers/test_bedrock_mantle_claude_chat_wire.py @@ -70,10 +70,18 @@ def _chat_messages(marker: str) -> list[JsonValue]: return [{"role": "user", "content": _prompt(marker)}] -def _outbound(backend: str, messages: list[JsonValue], **fields: JsonValue) -> dict[str, JsonValue]: +def _default_max_tokens(gateway: Gateway, backend: str) -> int: + match gateway.get("/public/litellm_model_cost_map").get(f"bedrock_mantle/{backend}"): + case {"max_output_tokens": int() as mapped}: + return mapped + case _: + return DEFAULT_ANTHROPIC_CHAT_MAX_TOKENS + + +def _outbound(gateway: Gateway, backend: str, messages: list[JsonValue], **fields: JsonValue) -> dict[str, JsonValue]: return { "messages": messages, - "max_tokens": DEFAULT_ANTHROPIC_CHAT_MAX_TOKENS, + "max_tokens": _default_max_tokens(gateway, backend), "anthropic_version": _BRIDGE_VERSION, "model": backend, **fields, @@ -290,7 +298,7 @@ def test_chat_completion_on_a_mantle_claude_id_posts_native_messages_and_spends_ gateway: Gateway, backend: str ) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(backend, [_user_turn(marker)]) + expected: Final = _outbound(gateway, backend, [_user_turn(marker)]) with wire_server(_bearer_peer(expected, _text_reply(marker, backend))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{backend}", api_base=wire.url, api_key=_API_KEY) response: Final = gateway.request( @@ -314,7 +322,7 @@ def test_chat_stream_on_a_mantle_claude_id_relays_openai_chunks_from_the_native_ gateway: Gateway, stream_options: dict[str, JsonValue], usage_chunks: list[tuple[JsonValue, ...]] ) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)], stream=True) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)], stream=True) with wire_server(_bearer_peer(expected, _text_stream(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) response: Final = gateway.request( @@ -355,7 +363,7 @@ def test_chat_request_fields_are_translated_to_the_native_messages_shape( outbound_fields: dict[str, JsonValue], ) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)], **outbound_fields) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)], **outbound_fields) with wire_server(_bearer_peer(expected, _text_reply(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) response: Final = gateway.request( @@ -377,7 +385,7 @@ def test_chat_tools_reach_mantle_as_input_schema_and_the_tool_use_block_returns_ marker: Final = uuid4().hex backend: Final = _mantle_claude_where(gateway, "supports_forced_tool_use", disabled=False) expected: Final = _outbound( - backend, [_user_turn(marker)], tools=[_WEATHER_TOOL_OUTBOUND], tool_choice=outbound_choice + gateway, backend, [_user_turn(marker)], tools=[_WEATHER_TOOL_OUTBOUND], tool_choice=outbound_choice ) reply: Final = _tool_reply(marker, backend, "get_weather") with wire_server(_bearer_peer(expected, reply)) as wire, gateway.scenario() as scenario: @@ -407,7 +415,7 @@ def test_chat_tools_reach_mantle_as_input_schema_and_the_tool_use_block_returns_ def test_chat_stream_relays_a_native_tool_use_block_as_tool_call_chunks(gateway: Gateway) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)], tools=[_WEATHER_TOOL_OUTBOUND], stream=True) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)], tools=[_WEATHER_TOOL_OUTBOUND], stream=True) with wire_server(_bearer_peer(expected, _tool_stream(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) response: Final = gateway.request( @@ -439,7 +447,7 @@ def test_chat_tool_result_turn_reaches_mantle_as_tool_use_and_tool_result_blocks marker: Final = uuid4().hex tool_call: Final = f"toolu_{marker}" expected: Final = _outbound( - _HAIKU, + gateway, _HAIKU, [ _user_turn(marker), { @@ -484,7 +492,7 @@ def test_chat_json_schema_response_format_is_sent_as_a_forced_tool_and_returned_ ) -> None: marker: Final = uuid4().hex expected: Final = _outbound( - _HAIKU, + gateway, _HAIKU, [_user_turn(marker)], tools=[{"name": "json_tool_call", "input_schema": _CITY_SCHEMA}], tool_choice={"name": "json_tool_call", "type": "tool"}, @@ -537,7 +545,7 @@ def _sigv4_peer(expected: Mapping[str, JsonValue], reply: Reply) -> Callable[[Re def test_chat_completion_signs_the_native_messages_request_with_the_deployment_aws_keys(gateway: Gateway) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)]) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)]) with wire_server(_sigv4_peer(expected, _text_reply(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model( model=f"bedrock_mantle/{_HAIKU}", @@ -556,7 +564,7 @@ def test_chat_completion_signs_the_native_messages_request_with_the_deployment_a def test_region_prefix_in_a_mantle_claude_id_is_routing_only_and_keeps_the_mantle_price(gateway: Gateway) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)]) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)]) with wire_server(_bearer_peer(expected, _text_reply(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/us-east-2/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) response: Final = gateway.request( @@ -577,7 +585,7 @@ def test_region_prefix_in_a_mantle_claude_id_is_routing_only_and_keeps_the_mantl def test_openai_sdk_chat_completion_on_a_mantle_claude_id(gateway: Gateway) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)]) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)]) with wire_server(_bearer_peer(expected, _text_reply(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) with OpenAI( @@ -606,7 +614,7 @@ def test_openai_sdk_chat_completion_on_a_mantle_claude_id(gateway: Gateway) -> N def test_openai_sdk_chat_stream_on_a_mantle_claude_id(gateway: Gateway) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)], stream=True) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)], stream=True) with wire_server(_bearer_peer(expected, _text_stream(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) with OpenAI( @@ -645,7 +653,7 @@ def test_openai_sdk_chat_stream_on_a_mantle_claude_id(gateway: Gateway) -> None: async def test_async_openai_sdk_chat_completion_on_a_mantle_claude_id(gateway: Gateway) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)]) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)]) with wire_server(_bearer_peer(expected, _text_reply(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) async with AsyncOpenAI( @@ -674,7 +682,7 @@ async def test_async_openai_sdk_chat_completion_on_a_mantle_claude_id(gateway: G async def test_async_openai_sdk_chat_stream_on_a_mantle_claude_id(gateway: Gateway) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)], stream=True) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)], stream=True) with wire_server(_bearer_peer(expected, _text_stream(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) async with AsyncOpenAI( @@ -714,7 +722,7 @@ def test_identical_chat_request_is_served_from_the_response_cache_and_logged_as_ gateway: Gateway, ) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)]) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)]) with wire_server(_bearer_peer(expected, _text_reply(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) request: Final[dict[str, JsonValue]] = {"model": model, "messages": _chat_messages(marker)} @@ -802,7 +810,7 @@ def test_open_weight_mantle_id_keeps_the_openai_compatible_chat_route_and_its_sa ) def test_api_base_with_a_route_suffix_still_posts_to_the_native_messages_path(gateway: Gateway, suffix: str) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)]) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)]) with wire_server(_bearer_peer(expected, _text_reply(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url + suffix, api_key=_API_KEY) response: Final = gateway.request( @@ -814,7 +822,7 @@ def test_api_base_with_a_route_suffix_still_posts_to_the_native_messages_path(ga def test_responses_api_on_a_mantle_claude_id_bridges_to_native_messages(gateway: Gateway) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)]) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)]) with wire_server(_bearer_peer(expected, _text_reply(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) response: Final = gateway.request("POST", "/v1/responses", {"model": model, "input": _prompt(marker)}) @@ -839,7 +847,7 @@ def test_responses_api_on_a_mantle_claude_id_bridges_to_native_messages(gateway: def test_responses_api_stream_on_a_mantle_claude_id_bridges_to_the_native_stream(gateway: Gateway) -> None: marker: Final = uuid4().hex - expected: Final = _outbound(_HAIKU, [_user_turn(marker)], stream=True) + expected: Final = _outbound(gateway, _HAIKU, [_user_turn(marker)], stream=True) with wire_server(_bearer_peer(expected, _text_stream(marker))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{_HAIKU}", api_base=wire.url, api_key=_API_KEY) response: Final = gateway.request( @@ -996,7 +1004,7 @@ def test_unsupported_claude_param_is_dropped_under_drop_params( ) -> None: marker: Final = uuid4().hex backend: Final = _backend_without(gateway, flag) - expected: Final = _outbound(backend, [_user_turn(marker)], **outbound_fields) + expected: Final = _outbound(gateway, backend, [_user_turn(marker)], **outbound_fields) with wire_server(_bearer_peer(expected, _text_reply(marker, backend))) as wire, gateway.scenario() as scenario: model: Final = scenario.model(model=f"bedrock_mantle/{backend}", api_base=wire.url, api_key=_API_KEY) response: Final = gateway.request( @@ -1114,7 +1122,7 @@ def _wildcard_prefix(gateway: Gateway, scenario: Scenario, api_base: str) -> str def test_uppercase_claude_id_through_a_mantle_wildcard_is_sent_to_native_messages(gateway: Gateway) -> None: marker: Final = uuid4().hex backend: Final = _HAIKU.upper() - expected: Final = _outbound(backend, [_user_turn(marker)]) + expected: Final = _outbound(gateway, backend, [_user_turn(marker)]) with wire_server(_bearer_peer(expected, _text_reply(marker, backend))) as wire, gateway.scenario() as scenario: model: Final = f"{_wildcard_prefix(gateway, scenario, wire.url)}/{backend}" response: Final = gateway.request( @@ -1129,7 +1137,7 @@ def test_five_kilobyte_claude_id_through_a_mantle_wildcard_reaches_mantle_and_it ) -> None: marker: Final = uuid4().hex backend: Final = f"{_HAIKU}-{'x' * 5000}" - expected: Final = _outbound(backend, [_user_turn(marker)]) + expected: Final = _outbound(gateway, backend, [_user_turn(marker)]) unknown: Final = _error_reply(404, "not_found_error", "model: synthetic unknown model") with wire_server(_bearer_peer(expected, unknown)) as wire, gateway.scenario() as scenario: model: Final = f"{_wildcard_prefix(gateway, scenario, wire.url)}/{backend}" @@ -1203,6 +1211,6 @@ def test_non_claude_mantle_id_with_a_bare_bedrock_twin_keeps_its_route_and_spend cost: Final = _mantle_cost(gateway, _LUNA) assert float(response.headers["x-litellm-response-cost"]) == pytest.approx(cost), response.text _assert_success_row( - _spend_row(_BY_CALL_ID, response.headers["x-litellm-call-id"]), model, _LUNA, "responses", cost + _spend_row(_BY_CALL_ID, response.headers["x-litellm-call-id"]), model, _LUNA, "acompletion", cost ) assert [(request.method, request.target) for request in wire.drain()] == [("POST", _RESPONSES_PATH)] diff --git a/tests/integration/providers/test_bedrock_mantle_output_limit_wire.py b/tests/integration/providers/test_bedrock_mantle_output_limit_wire.py index 89ad226761e..5aede070896 100644 --- a/tests/integration/providers/test_bedrock_mantle_output_limit_wire.py +++ b/tests/integration/providers/test_bedrock_mantle_output_limit_wire.py @@ -516,7 +516,7 @@ def test_responses_max_output_tokens_is_forwarded_natively_on_both_legs(gateway: for attempt in attempts: assert attempt.body["max_output_tokens"] == 1000 and _limits(attempt.body) == (None, None), attempt.body _assert_logged(issued, model, "success") - _assert_logged(_managed_response_id(streamed_issued), model, "success") + _assert_logged(streamed_issued, model, "success") def test_region_prefixed_deployment_on_a_v1_base_sends_the_bare_model_with_max_completion_tokens( diff --git a/tests/integration/providers/test_bedrock_model_discovery_wire.py b/tests/integration/providers/test_bedrock_model_discovery_wire.py index 3bf4583e736..2871e51de5e 100644 --- a/tests/integration/providers/test_bedrock_model_discovery_wire.py +++ b/tests/integration/providers/test_bedrock_model_discovery_wire.py @@ -301,11 +301,7 @@ def _spend_row_id(rows: Sequence[Mapping[str, JsonValue]], tag: str) -> str: def _landed_once(served: tuple[tuple[str, str, bool], ...], tags: tuple[str, ...]) -> None: - """One spend row per tagged call, carrying the id the client saw. - - FIXME: a streamed /v1/responses row carries the managed `resp_` id LiteLLM built before the proxy encrypted the - advertised one, so that row is matched by tag alone until the spend log reads the id the client received. - """ + """One spend row per tagged call, carrying the id the client saw.""" rows: Final = eventually( lambda: read_rows( 'SELECT request_id, request_tags FROM "LiteLLM_SpendLogs" WHERE request_tags ?| %s', @@ -316,9 +312,6 @@ def _landed_once(served: tuple[tuple[str, str, bool], ...], tags: tuple[str, ... ) for (identity, path, stream), tag in zip(served, tags, strict=True): row_id: Final = _spend_row_id(rows, tag) - if path == "/v1/responses" and stream: - assert row_id.startswith("resp_"), (row_id, identity) - continue assert row_id == identity, (path, stream, row_id, identity) diff --git a/tests/integration/providers/test_bedrock_native_structured_output_wire.py b/tests/integration/providers/test_bedrock_native_structured_output_wire.py index 5803d1dee44..2502bd90bd6 100644 --- a/tests/integration/providers/test_bedrock_native_structured_output_wire.py +++ b/tests/integration/providers/test_bedrock_native_structured_output_wire.py @@ -20,6 +20,7 @@ _FABLE: Final = "us.anthropic.claude-fable-5" _SONNET: Final = "us.anthropic.claude-sonnet-4-6" _OPUS: Final = "us.anthropic.claude-opus-5-5" _OPT_IN: Final = _OPUS +_UNFORCEABLE_TOOL: Final = _OPUS _OPUS_4_8: Final = "us.anthropic.claude-opus-4-8" _DEEPSEEK: Final = "deepseek.v3.2" _AWS: Final[dict[str, JsonValue]] = { @@ -536,6 +537,12 @@ def _resolves(schema: Mapping[str, JsonValue], ref: str) -> bool: return ref.startswith(prefix) and ref.removeprefix(prefix) in object_value(schema.get("$defs") or {}) +def _tool_choice(body: Mapping[str, JsonValue], invoke: bool) -> JsonValue: + if invoke: + return body.get("tool_choice") + return object_value(body.get("toolConfig") or {}).get("toolChoice") + + def _assert_native_without_tools(body: Mapping[str, JsonValue], invoke: bool, schema: Mapping[str, JsonValue]) -> None: assert _native_schema(body, invoke) == schema, body assert _JSON_TOOL not in _tools(body, invoke), body @@ -615,10 +622,15 @@ def test_messages_thinking_on_a_bedrock_converse_native_model_gets_native_output @pytest.mark.parametrize("route", ["converse", "invoke"]) -def test_bedrock_native_model_without_thinking_keeps_the_forced_json_tool(gateway: Gateway, route: str) -> None: +@pytest.mark.parametrize( + ("backend", "thinks_by_default"), [(_OPUS_4_8, False), (_HAIKU, True)], ids=["opus_4_8", "haiku_5_5"] +) +def test_bedrock_native_model_with_no_thinking_param_gets_native_output_only_when_it_thinks_by_default( + gateway: Gateway, route: str, backend: str, thinks_by_default: bool +) -> None: marker, marker_hex = _marker() with wire_server(_bedrock) as wire, gateway.scenario() as scenario: - model: Final = _deployment(scenario, wire, route, _HAIKU) + model: Final = _deployment(scenario, wire, route, backend) response: Final = gateway.request( "POST", "/v1/chat/completions", _chat_body(model, marker, response_format=_response_format(_SCHEMA)) ) @@ -627,10 +639,47 @@ def test_bedrock_native_model_without_thinking_keeps_the_forced_json_tool(gatewa assert not message.get("tool_calls"), response.text _, body = _one_call(wire, marker_hex) invoke: Final = route == "invoke" + if thinks_by_default: + _assert_native_without_tools(body, invoke, _SCHEMA) + return assert _native_schema(body, invoke) is None, body assert _tools(body, invoke)[_JSON_TOOL]["properties"] == _SCHEMA["properties"], body +@pytest.mark.parametrize("route", ["converse", "invoke"]) +def test_json_schema_without_thinking_on_a_model_that_cannot_force_the_json_tool_gets_native_output( + gateway: Gateway, route: str +) -> None: + marker, marker_hex = _marker() + with wire_server(_bedrock) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire, route, _UNFORCEABLE_TOOL) + response: Final = gateway.request( + "POST", "/v1/chat/completions", _chat_body(model, marker, response_format=_response_format(_SCHEMA)) + ) + assert _content_json(_chat_message(response)) == _payload(marker_hex), response.text + _, body = _one_call(wire, marker_hex) + _assert_native_without_tools(body, route == "invoke", _SCHEMA) + + +@pytest.mark.parametrize("route", ["converse", "invoke"]) +def test_a_model_that_cannot_force_the_json_tool_retries_a_rejected_native_output_with_an_unforced_json_tool( + gateway: Gateway, route: str +) -> None: + marker, marker_hex = _marker() + invoke: Final = route == "invoke" + with wire_server(_rejecting_native_output(_FABLE_REJECTION)) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire, route, _UNFORCEABLE_TOOL) + response: Final = gateway.request( + "POST", "/v1/chat/completions", _chat_body(model, marker, response_format=_response_format(_SCHEMA)) + ) + assert _content_json(_chat_message(response)) == _payload(marker_hex), response.text + rejected, retried = (_JSON.validate_json(request.body) for request in wire.drain()) + assert _native_schema(rejected, invoke) == _SCHEMA, rejected + assert _native_schema(retried, invoke) is None, retried + assert _tools(retried, invoke)[_JSON_TOOL]["properties"] == _SCHEMA["properties"], retried + assert _tool_choice(retried, invoke) is None, retried + + @pytest.mark.parametrize( ("backend", "model_info", "native"), [ @@ -797,6 +846,25 @@ def test_thinking_with_a_caller_tool_on_a_bedrock_native_model_sends_only_the_ca assert _thinking_requested(body, False), body +def test_a_caller_tool_next_to_json_schema_without_thinking_on_a_model_that_cannot_force_the_json_tool( + gateway: Gateway, +) -> None: + marker, marker_hex = _marker() + with wire_server(_bedrock) as wire, gateway.scenario() as scenario: + model: Final = _deployment(scenario, wire, "converse", _UNFORCEABLE_TOOL) + response: Final = gateway.request( + "POST", + "/v1/chat/completions", + _chat_body(model, marker, tools=[_USER_TOOL_SPEC], response_format=_response_format(_SCHEMA)), + ) + (call,) = list_value(_chat_message(response)["tool_calls"]) + function: Final = object_value(object_value(call)["function"]) + assert function["name"] == _USER_TOOL, response.text + _, body = _one_call(wire, marker_hex) + assert _tools(body, False).keys() == {_USER_TOOL}, body + assert _native_schema(body, False) == _SCHEMA, body + + @pytest.mark.parametrize( ("schema", "expected"), [(_UNCLEANED_SCHEMA, _UNCLEANED_SCHEMA), (_NULLABLE_SCHEMA, _CLOSED_NULLABLE_SCHEMA)], diff --git a/tests/integration/providers/test_bedrock_runtime_chat_completions_chaos.py b/tests/integration/providers/test_bedrock_runtime_chat_completions_chaos.py index 3cadc1b5ccf..42950fb18c3 100644 --- a/tests/integration/providers/test_bedrock_runtime_chat_completions_chaos.py +++ b/tests/integration/providers/test_bedrock_runtime_chat_completions_chaos.py @@ -172,7 +172,11 @@ def _upstream_id_inside(row_id: str) -> str | None: def _row_belongs_to(row_id: str, served: _Served) -> bool: if row_id == _response_id(served): return True - return served.call.endpoint == "responses" and _upstream_id_inside(row_id) == f"resp_upstream_{served.call.marker}" + return ( + served.call.endpoint == "responses" + and not served.call.stream + and _upstream_id_inside(row_id) == f"resp_upstream_{served.call.marker}" + ) def _assert_each_success_landed_once(rows: list[dict[str, JsonValue]], served: tuple[_Served, ...]) -> None: diff --git a/tests/integration/providers/test_chat_template_tool_count_wire.py b/tests/integration/providers/test_chat_template_tool_count_wire.py index a8b97fa732e..552df3a87bc 100644 --- a/tests/integration/providers/test_chat_template_tool_count_wire.py +++ b/tests/integration/providers/test_chat_template_tool_count_wire.py @@ -39,7 +39,7 @@ _API_KEY: Final = "scripted-provider-key" _DEEPSEEK_V4: Final = "azure_ai/DeepSeek-V4-Flash-0731" _DEEPSEEK_R1: Final = "azure_ai/DeepSeek-R1-0528" _QWEN3_5: Final = "databricks/databricks-qwen35-122b-a10b" -_GROK: Final = "azure_ai/grok-4-1" +_GROK_3: Final = "azure_ai/grok-3" _DEEPSEEK_V4_TOOL_PREAMBLE: Final = 222 _QWEN3_5_TOOL_PREAMBLE: Final = 196 _QWEN3_5_OPENED_SYSTEM_TURN: Final = 5 @@ -250,7 +250,7 @@ def test_messages_count_tokens_skips_web_search_and_counts_unmapped_tool_keys_fo def test_messages_count_tokens_keeps_openai_tool_framing_for_other_models(gateway: Gateway) -> None: with wire_server(_completion) as wire, gateway.scenario() as scenario: - model: Final = _deployment(scenario, "count", _GROK, wire.url) + model: Final = _deployment(scenario, "count", _GROK_3, wire.url) without_tools: Final = _count(gateway, _MESSAGES_COUNT, _MESSAGES_COUNT.body(model, ())) plain: Final = _count(gateway, _MESSAGES_COUNT, _MESSAGES_COUNT.body(model, (_ANTHROPIC_TOOL,))) deferred: Final = _count( @@ -428,7 +428,7 @@ def test_project_itpm_reserves_deepseek_v4_tools_the_way_its_chat_template_rende def test_project_itpm_keeps_openai_tool_framing_for_other_models(gateway: Gateway) -> None: chat: Final = _ENDPOINTS["chat-completions"] with wire_server(_completion) as wire, gateway.scenario() as scenario: - group: Final = _deployment(scenario, "grok-4-1", _GROK, wire.url) + group: Final = _deployment(scenario, "grok-3", _GROK_3, wire.url) response: Final = gateway.request( "POST", chat.path, @@ -504,8 +504,8 @@ def _agent_body(group: str, marker: str, file_body: str, trigger: int) -> dict[s @pytest.mark.parametrize( ("model", "files_kept"), - ((_DEEPSEEK_V4, (False, False, True)), (_GROK, (True, True, True))), - ids=("deepseek-v4", "grok-4-1"), + ((_DEEPSEEK_V4, (False, False, True)), (_GROK_3, (True, True, True))), + ids=("deepseek-v4", "grok-3"), ) def test_messages_context_management_trigger_counts_tools_the_way_the_models_chat_template_renders_them( gateway: Gateway, model: str, files_kept: tuple[bool, ...] diff --git a/tests/integration/providers/test_custom_video_provider_wire.py b/tests/integration/providers/test_custom_video_provider_wire.py new file mode 100644 index 00000000000..a40ecae3ed4 --- /dev/null +++ b/tests/integration/providers/test_custom_video_provider_wire.py @@ -0,0 +1,113 @@ +"""A provider registered in `custom_provider_map` with a `BaseVideoConfig` serves /v1/videos create, status and content.""" + +import json +import shutil +from contextlib import ExitStack +from pathlib import Path +from typing import Final + +from integration._support.client import Gateway +from integration._support.process import owned_proxy_process +from integration._support.wire import Reply, Request, Wire, wire_server + +_SUPPORT_MODULE: Final = Path(__file__).resolve().parents[1] / "_support" / "custom_video_provider.py" +_PROMPT: Final = "a cat walking across a bridge" +_MP4: Final = b"\x00\x00\x00\x18ftypmp42" + b"queue-video-bytes" + + +def _queue_backend(request: Request) -> Reply: + if (request.method, request.target) == ("POST", "/jobs"): + return Reply(body=json.dumps({"job_id": "job-7", "state": "queued"}).encode()) + if (request.method, request.target) == ("GET", "/jobs/job-7"): + return Reply(body=json.dumps({"job_id": "job-7", "state": "done", "seconds": 8}).encode()) + if (request.method, request.target) == ("GET", "/jobs/job-7/file"): + return Reply(body=_MP4, content_type="video/mp4") + return Reply(status=404, body=json.dumps({"error": f"no route {request.method} {request.target}"}).encode()) + + +def _write_config(path: Path, wire: Wire) -> Path: + shutil.copy(_SUPPORT_MODULE, path.parent / "custom_video_provider.py") + path.write_text( + json.dumps( + { + "model_list": [ + { + "model_name": "queue-video", + "litellm_params": { + "model": "queue-video/seedance-1", + "api_base": wire.url, + "api_key": "queue-secret", + }, + }, + { + "model_name": "image-only-video", + "litellm_params": { + "model": "image-only/seedance-1", + "api_base": wire.url, + "api_key": "unused", + }, + }, + ], + "litellm_settings": { + "custom_provider_map": [ + {"provider": "queue-video", "custom_handler": "custom_video_provider.VIDEO_CONFIG"}, + {"provider": "image-only", "custom_handler": "custom_video_provider.IMAGE_ONLY_HANDLER"}, + ] + }, + } + ), + encoding="utf-8", + ) + return path + + +def _lower_headers(request: Request) -> dict[str, str]: + return {name.lower(): value for name, value in request.headers.items()} + + +def test_custom_provider_map_base_video_config_serves_create_status_and_content( + gateway: Gateway, tmp_path: Path +) -> None: + with ExitStack() as stack: + wire: Final = stack.enter_context(wire_server(_queue_backend)) + config: Final = _write_config(tmp_path / "custom-video.yaml", wire) + owned: Final = stack.enter_context(owned_proxy_process(gateway, tmp_path, {}, config=config)) + + created: Final = owned.gateway.request( + "POST", "/v1/videos", {"model": "queue-video", "prompt": _PROMPT, "seconds": "8"} + ) + assert created.status_code == 200, created.text + created_body: Final = created.json() + assert created_body["status"] == "queued", created_body + video_id: Final = created_body["id"] + assert isinstance(video_id, str) and video_id.startswith("video_"), created_body + + submits: Final = wire.drain() + assert [(r.method, r.target) for r in submits] == [("POST", "/jobs")], submits + assert json.loads(submits[0].body) == {"model": "seedance-1", "prompt": _PROMPT, "seconds": "8"} + assert _lower_headers(submits[0])["x-api-key"] == "queue-secret" + + status: Final = owned.gateway.request("GET", f"/v1/videos/{video_id}") + assert status.status_code == 200, status.text + assert status.json()["status"] == "completed", status.text + assert status.json()["id"] == video_id, status.text + + content: Final = owned.gateway.request("GET", f"/v1/videos/{video_id}/content") + assert content.status_code == 200, content.text + assert content.content == _MP4 + + polls: Final = wire.drain() + assert [(r.method, r.target) for r in polls] == [("GET", "/jobs/job-7"), ("GET", "/jobs/job-7/file")], polls + assert all(_lower_headers(r)["x-api-key"] == "queue-secret" for r in polls) + + +def test_custom_provider_without_a_video_config_is_refused_with_400(gateway: Gateway, tmp_path: Path) -> None: + with ExitStack() as stack: + wire: Final = stack.enter_context(wire_server(_queue_backend)) + config: Final = _write_config(tmp_path / "custom-video.yaml", wire) + owned: Final = stack.enter_context(owned_proxy_process(gateway, tmp_path, {}, config=config)) + + refused: Final = owned.gateway.request("POST", "/v1/videos", {"model": "image-only-video", "prompt": _PROMPT}) + assert refused.status_code == 400, refused.text + assert "video generation is not supported for image-only" in refused.text + assert wire.drain() == () diff --git a/tests/integration/providers/test_databricks_chat_wire.py b/tests/integration/providers/test_databricks_chat_wire.py index b93cebdbc4c..3d9d749eb04 100644 --- a/tests/integration/providers/test_databricks_chat_wire.py +++ b/tests/integration/providers/test_databricks_chat_wire.py @@ -353,9 +353,172 @@ def _shape_reply(identity: str, stream: bool) -> Reply: "/chat/completions", id="A5-responses-list-input", ), + pytest.param( + "json-object-two-blocks", + "/v1/chat/completions", + "databricks-meta-llama-3-3-70b-instruct", + { + "messages": [ + {"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]} + ], + "response_format": {"type": "json_object"}, + }, + [{"role": "user", "content": "Reply in JSON"}], + False, + "/chat/completions", + id="A6-chat-json-object-two-blocks-joined", + ), + pytest.param( + "json-object-two-blocks-stream", + "/v1/chat/completions", + "databricks-qwen35-122b-a10b", + { + "messages": [ + {"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]} + ], + "response_format": {"type": "json_object"}, + "stream": True, + }, + [{"role": "user", "content": "Reply in JSON"}], + False, + "/chat/completions", + id="A7-chat-stream-json-object-two-blocks-joined", + ), + pytest.param( + "json-object-history", + "/v1/chat/completions", + "databricks-meta-llama-3-3-70b-instruct", + { + "messages": [ + {"role": "user", "content": [{"type": "text", "text": "Code: A"}, {"type": "text", "text": "BC"}]}, + {"role": "assistant", "content": "Got it."}, + {"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]}, + ], + "response_format": {"type": "json_object"}, + }, + [ + {"role": "user", "content": [{"type": "text", "text": "Code: A"}, {"type": "text", "text": "BC"}]}, + {"role": "assistant", "content": "Got it."}, + {"role": "user", "content": "Reply in JSON"}, + ], + False, + "/chat/completions", + id="A8-chat-json-object-earlier-turns-kept", + ), + pytest.param( + "json-object-trailing-system", + "/v1/chat/completions", + "databricks-meta-llama-3-3-70b-instruct", + { + "messages": [ + {"role": "user", "content": "Say hi"}, + {"role": "system", "content": [{"type": "text", "text": "Alpha"}, {"type": "text", "text": " rule."}]}, + {"role": "system", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]}, + ], + "response_format": {"type": "json_object"}, + }, + [{"role": "user", "content": "Say hi"}, {"role": "system", "content": "Alpha rule.\n\nReply in JSON"}], + False, + "/chat/completions", + id="A8b-chat-json-object-trailing-system-keeps-break", + ), + pytest.param( + "json-object-drop-params-cache-control", + "/v1/chat/completions", + "databricks-meta-llama-3-3-70b-instruct", + { + "messages": [ + { + "role": "user", + "content": [ + {"type": "text", "text": "Reply"}, + {"type": "text", "text": " in JSON", "cache_control": {"type": "ephemeral"}}, + ], + } + ], + "response_format": {"type": "json_object"}, + "drop_params": True, + }, + [{"role": "user", "content": "Reply in JSON"}], + False, + "/chat/completions", + id="A8c-chat-json-object-drop-params-drops-cache-control", + ), + pytest.param( + "json-object-trailing-thinking-turn", + "/v1/chat/completions", + "databricks-meta-llama-3-3-70b-instruct", + { + "messages": [ + {"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]}, + { + "role": "assistant", + "content": "", + "thinking_blocks": [{"type": "thinking", "thinking": "Plan.", "signature": "sig"}], + }, + ], + "response_format": {"type": "json_object"}, + }, + [{"role": "user", "content": "Reply in JSON"}], + False, + "/chat/completions", + id="A8d-chat-json-object-trailing-thinking-turn-dropped", + ), + pytest.param( + "json-object-external-endpoint", + "/v1/chat/completions", + "openai-gpt-external", + { + "messages": [ + {"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]} + ], + "response_format": {"type": "json_object"}, + }, + [{"role": "user", "content": [{"type": "text", "text": "Reply"}, {"type": "text", "text": " in JSON"}]}], + False, + "/chat/completions", + id="A8e-chat-json-object-external-endpoint-kept-as-sent", + ), + pytest.param( + "json-object-responses-two-parts", + "/v1/responses", + "databricks-qwen35-122b-a10b", + { + "input": [ + { + "role": "user", + "content": [{"type": "input_text", "text": "Reply"}, {"type": "input_text", "text": " in JSON"}], + } + ], + "text": {"format": {"type": "json_object"}}, + }, + [{"role": "user", "content": "Reply in JSON"}], + False, + "/chat/completions", + id="A9-responses-json-object-two-parts-joined", + ), + pytest.param( + "json-object-responses-trailing-reasoning", + "/v1/responses", + "databricks-qwen35-122b-a10b", + { + "input": [ + { + "role": "user", + "content": [{"type": "input_text", "text": "Reply"}, {"type": "input_text", "text": " in JSON"}], + }, + {"type": "reasoning", "id": "rs_1", "summary": [{"type": "summary_text", "text": "Plan."}]}, + ], + "text": {"format": {"type": "json_object"}}, + }, + [{"role": "user", "content": "Reply in JSON"}], + False, + "/chat/completions", + id="A9b-responses-json-object-trailing-reasoning-dropped", + ), ], ) -def test_databricks_non_claude_single_text_block_reaches_upstream_as_string( +def test_databricks_non_claude_plain_text_content_reaches_upstream_as_string( gateway: Gateway, case: str, endpoint: str, @@ -365,7 +528,7 @@ def test_databricks_non_claude_single_text_block_reaches_upstream_as_string( responses_mode: bool, upstream_path: str, ) -> None: - identity: Final = f"databricks-single-text-{case}-{uuid.uuid4().hex}" + identity: Final = f"databricks-plain-text-{case}-{uuid.uuid4().hex}" streaming: Final = request_body.get("stream") is True def respond(request: Request) -> Reply: @@ -1453,7 +1616,7 @@ def test_databricks_non_string_text_block_is_rejected_before_reaching_upstream(g ) received: Final = wire.drain() assert response.status_code == 400, response.text - assert "'int' object has no attribute 'strip'" in response.text + assert "A text content block needs a string 'text', got int" in response.text assert received == () diff --git a/tests/integration/providers/test_decisions_wire.py b/tests/integration/providers/test_decisions_wire.py index 5af1532e9ed..bb4973d6f2f 100644 --- a/tests/integration/providers/test_decisions_wire.py +++ b/tests/integration/providers/test_decisions_wire.py @@ -139,6 +139,7 @@ _PROVIDERS: Final = ( False, "databricks/databricks-openjev-qwen35-4b", ), + _Provider("empiriolabs", "empiriolabs/aplomb-test", "/v1/decisions", "aplomb-test", _API_KEY, False, None), ) _LOCAL_PROVIDERS: Final = ( pytest.param( @@ -262,11 +263,28 @@ def _upstream_calls(gateway: Gateway, handle: ScenarioHandle) -> list[dict[str, return _calls_to(_observed_requests(gateway), handle) -def _sdk_inference_call(gateway: Gateway, handle: ScenarioHandle, provider: _Provider) -> dict[str, JsonValue]: +def _sdk_inference_call( + gateway: Gateway, + handle: ScenarioHandle, + provider: _Provider, + *, + metadata_authorization: str | None = None, +) -> dict[str, JsonValue]: observed: Final = _upstream_calls(gateway, handle) inference_path: Final = f"/{handle.scenario_id}/v1/systemone" (call,) = tuple(request for request in observed if request["path"] == inference_path) - metadata_calls: Final = tuple(request for request in observed if request["path"] != inference_path) + environment_metadata: Final = { + "path": f"/{handle.scenario_id}/api/show", + "authorization": metadata_authorization, + "body": {"name": provider.body_model}, + "method": "POST", + "api_key": "", + } + metadata_calls: Final = tuple( + request + for request in observed + if request["path"] != inference_path and (metadata_authorization is None or request != environment_metadata) + ) assert metadata_calls in ( (), ( @@ -556,7 +574,9 @@ def test_ollama_decisions_sdk_respects_environment_and_explicit_auth( api_key=api_key, ) assert response.model_dump(mode="json") == _answer_body(provider) - call: Final = _sdk_inference_call(gateway, handle, provider) + call: Final = _sdk_inference_call( + gateway, handle, provider, metadata_authorization=authorization if environment_base else None + ) assert (call["path"], call["authorization"], call["body"]) == ( f"/{handle.scenario_id}/v1/systemone", authorization, diff --git a/tests/integration/providers/test_device_code_login_guard_boot.py b/tests/integration/providers/test_device_code_login_guard_boot.py index 8aba6841cf9..91f502179f3 100644 --- a/tests/integration/providers/test_device_code_login_guard_boot.py +++ b/tests/integration/providers/test_device_code_login_guard_boot.py @@ -28,7 +28,6 @@ from pydantic import JsonValue, TypeAdapter pytestmark: Final = [pytest.mark.timeout(900), pytest.mark.shares_worker_state] _STARTED_WORKER: Final = re.compile(r"Started server process \[(\d+)\]") -_DROPPED: Final = re.compile(r"original model: (\S+), ignoring and continuing") _FIXED: Final[Mapping[str, str]] = MappingProxyType( {"chatgpt-fixed": "chatgpt/gpt-5.6-terra", "copilot-fixed": "github_copilot/gpt-5.4"} ) @@ -41,8 +40,6 @@ _CONTROL_CALLS_BEFORE_THE_RELOAD: Final = 1 _SHAPES: Final[Mapping[str, bool]] = MappingProxyType( {"docs-shapes": False, "docs-shapes-beside-a-universal-wildcard": True} ) -_NOT_FOUND: Final = "Invalid model name passed in model=" -_NO_HEALTHY: Final = "There are no healthy deployments for this model" _CONTROL: Final = "device-login-boot-control" _EXTRA: Final[Mapping[str, JsonValue]] = MappingProxyType({"num_retries": 0, "cache": {"no-cache": True}}) _CALL_ID: Final = "x-litellm-call-id" @@ -174,15 +171,11 @@ def _lists_login_models(listed: tuple[str, ...]) -> bool: ) -def _every_worker_lists( - owned: OwnedProxy, workers: tuple[int, ...], *, login_models: bool -) -> Mapping[int, tuple[str, ...]]: +def _every_worker_lists(owned: OwnedProxy, workers: tuple[int, ...]) -> Mapping[int, tuple[str, ...]]: def settled(by_worker: Mapping[int, tuple[str, ...]]) -> bool: if set(by_worker) != set(workers): return False - if login_models: - return all(_lists_login_models(listed) for listed in by_worker.values()) - return all(_login_names_listed(listed) == frozenset() for listed in by_worker.values()) + return all(_lists_login_models(listed) for listed in by_worker.values()) return eventually(lambda: _listing_by_worker(owned, workers), settled, seconds=90) @@ -212,16 +205,8 @@ def _reload(owned: OwnedProxy) -> None: assert response.status_code == 200, response.text -def _refusal_before_the_reload(name: str, universal: bool) -> str: - if name in _FIXED: - return _NO_HEALTHY - if not universal: - return _NOT_FOUND - return dl.CHATGPT_REFUSAL if name.startswith("chatgpt/") else dl.COPILOT_REFUSAL - - @pytest.mark.parametrize("universal", _SHAPES.values(), ids=_SHAPES.keys()) -def test_booting_without_tokens_drops_the_login_deployments_and_a_reload_after_mounting_brings_them_back( +def test_booting_without_tokens_lists_login_deployments_and_serves_only_after_tokens_are_mounted( gateway: Gateway, tmp_path: Path, universal: bool ) -> None: dirs: Final = _token_dirs(tmp_path) @@ -240,20 +225,18 @@ def test_booting_without_tokens_drops_the_login_deployments_and_a_reload_after_m workers=2, ) as owned: workers: Final = _workers(owned) - _every_worker_lists(owned, workers, login_models=False) + _every_worker_lists(owned, workers) boot_log: Final = owned.log.read_text() assert peers.auth_connections() == () assert dl.CHATGPT_USER_CODE not in boot_log and dl.COPILOT_USER_CODE not in boot_log, boot_log[-3000:] - dropped_models: Final = _DROPPED.findall(boot_log) - expected_drops: Final = frozenset((*_FIXED.values(), *_WILDCARDS)) - assert frozenset(dropped_models) == expected_drops, boot_log[-3000:] - assert all(dropped_models.count(model) >= len(workers) for model in expected_drops), boot_log[-3000:] with owned.gateway.scenario() as scenario: key: Final = scenario.key() for name in _LOGIN_NAMES: refused: Final = _chat(_base_url(owned), key, name, uuid.uuid4().hex) assert refused.status == 400, refused.text - assert _refusal_before_the_reload(name, universal) in refused.message(), refused.text + refusal: Final = dl.CHATGPT_REFUSAL if name.startswith("chatgpt") else dl.COPILOT_REFUSAL + assert refusal in refused.message(), refused.text + assert peers.api.drain() == () control: Final = _chat(_base_url(owned), key, _CONTROL, uuid.uuid4().hex) assert control.status == 200, control.text assert peers.auth_connections() == () @@ -261,7 +244,7 @@ def test_booting_without_tokens_drops_the_login_deployments_and_a_reload_after_m dirs.store_valid_tokens(peers.api.url) _reload(owned) - _every_worker_lists(owned, workers, login_models=True) + _every_worker_lists(owned, workers) for served_logins, name in enumerate(_LOGIN_NAMES, start=1): served: Final = _chat(_base_url(owned), key, name, uuid.uuid4().hex) assert served.status == 200, served.text diff --git a/tests/integration/providers/test_device_code_login_guard_wire.py b/tests/integration/providers/test_device_code_login_guard_wire.py index b4044674ed5..39e36fd95fa 100644 --- a/tests/integration/providers/test_device_code_login_guard_wire.py +++ b/tests/integration/providers/test_device_code_login_guard_wire.py @@ -746,10 +746,7 @@ def test_a_recent_device_code_request_does_not_hold_the_worker_for_the_rest_of_t assert scene.rig.peers.auth_connections() == () -_NOT_LIVE: Final = re.compile(r"saved to the database, but the model id\(s\) \['([0-9a-f-]+)'\] are not live") - - -def test_model_created_without_a_token_is_saved_not_live_and_serves_once_the_token_is_mounted(scene: _Scene) -> None: +def test_model_created_without_a_token_refuses_requests_and_serves_once_the_token_is_mounted(scene: _Scene) -> None: gateway: Final = scene.rig.owned.gateway name: Final = f"device-login-db-{uuid.uuid4().hex}" identity: Final = str(uuid.uuid4()) @@ -763,14 +760,18 @@ def test_model_created_without_a_token_is_saved_not_live_and_serves_once_the_tok }, ) try: - assert created.status_code == 500, created.text - not_live: Final = _NOT_LIVE.search(created.text) - assert not_live is not None and not_live.group(1) == identity, created.text + assert created.status_code == 200, created.text + assert created.json()["model_info"]["id"] == identity, created.text assert scene.rig.peers.auth_connections() == () - scene.store_valid_token("chatgpt") call: Final = _Call( scene.rig.base_url(), scene.key, name, "responses", False, "httpx", uuid.uuid4().hex, SimpleQueue() ) + refused: Final = _serve(call) + assert refused.status == 400, refused.text + assert dl.CHATGPT_REFUSAL in _error_message(refused.text), refused.text + assert scene.rig.peers.auth_connections() == () + assert scene.rig.peers.api.drain() == () + scene.store_valid_token("chatgpt") served: Final = eventually(lambda: _serve(call), lambda answer: answer.status == 200, seconds=90) assert set(rv.MARKER.findall(served.text)) == {call.marker}, served.text assert scene.rig.peers.auth_connections() == () diff --git a/tests/integration/providers/test_gemini_long_decode_wire.py b/tests/integration/providers/test_gemini_long_decode_wire.py index 5ecb5e2a942..90e7616e26c 100644 --- a/tests/integration/providers/test_gemini_long_decode_wire.py +++ b/tests/integration/providers/test_gemini_long_decode_wire.py @@ -380,7 +380,9 @@ def test_cut_chat_stream_hands_its_token_on_a_chunk_with_empty_vertex_ai_lists_a chunks: Final = payloads(post(gateway, "chat", request_body("chat", model, True)).text, True) carriers: Final = [chunk for chunk in chunks if "continuation_token" in json.dumps(chunk)] assert [_vertex_lists(chunk) for chunk in carriers] == [dict(_EMPTY_VERTEX_LISTS)], chunks - assert [_vertex_lists(chunk) for chunk in chunks if chunk not in carriers] == [{}] * (len(chunks) - 1), chunks + assert [_vertex_lists(chunk) for chunk in chunks] == [ + dict(_EMPTY_VERTEX_LISTS) if at(chunk, "choices", 0, "delta", "content") else {} for chunk in chunks + ], chunks metered: Final = [chunk for chunk in chunks if isinstance(chunk.get("usage"), dict)] assert [at(chunk, "usage", "completion_tokens_details") for chunk in metered] == [ {"text_tokens": CUT.output_tokens} diff --git a/tests/integration/providers/test_gemini_thinking_replay_chaos.py b/tests/integration/providers/test_gemini_thinking_replay_chaos.py index f8bb52ef60a..fb3092adfc3 100644 --- a/tests/integration/providers/test_gemini_thinking_replay_chaos.py +++ b/tests/integration/providers/test_gemini_thinking_replay_chaos.py @@ -233,6 +233,18 @@ def _assert_answered_with_its_own_marker(served: _Served) -> None: assert set(_MARKER.findall(served.text)) == {served.call.marker}, served.text +def _spend_id(served: _Served) -> str: + if served.call.endpoint == "responses" and served.call.stream: + payloads: Final = ( + _JSON_OBJECT.validate_json(line.removeprefix("data: ")) + for line in served.text.splitlines() + if line.startswith("data: {") + ) + (completed,) = tuple(event for event in payloads if event.get("type") == "response.completed") + return str(_JSON_OBJECT.validate_python(completed["response"])["id"]) + return _response_id(served.call.marker) + + async def test_concurrent_thinking_replays_across_endpoints_reach_gemini_signature_free(gateway: Gateway) -> None: calls: Final = _calls(30, ("chat", "messages", "responses"), lambda index: index % 2 == 0) with wire_server(_echo) as wire, gateway.scenario() as scenario: @@ -244,7 +256,7 @@ async def test_concurrent_thinking_replays_across_endpoints_reach_gemini_signatu _assert_no_bleed(wire.drain(), frozenset(call.marker for call in calls)) landed: Final = _spend_request_ids(model, 30) assert landed >= { - _response_id(call.marker) for call in calls if not (call.endpoint == "messages" and call.stream) + _spend_id(item) for item in served if not (item.call.endpoint == "messages" and item.call.stream) } diff --git a/tests/integration/providers/test_gemini_thinking_replay_wire.py b/tests/integration/providers/test_gemini_thinking_replay_wire.py index 4f965f079ec..70e339ed8b7 100644 --- a/tests/integration/providers/test_gemini_thinking_replay_wire.py +++ b/tests/integration/providers/test_gemini_thinking_replay_wire.py @@ -2,6 +2,7 @@ import base64 import itertools import json import os +import re import uuid from collections.abc import Iterator, Mapping, Sequence from collections.abc import Set as AbstractSet @@ -679,9 +680,70 @@ def test_gemini_own_tool_call_signature_is_still_replayed_on_the_function_call_p assert _spend_row(rounds[1])["status"] == "success" -def test_responses_previous_response_id_replays_gemini_session_history( - gateway: Gateway, tmp_path: Path +_PLACEHOLDER_SIGNATURE: Final = base64.b64encode(b"skip_thought_signature_validator").decode() +_ISSUED_ID: Final = re.compile(r'"id":\s*"([^"]+)"') +_PLACEHOLDER_TOOL_TURN: Final = _model_turn( + _thought("I should count."), + {"function_call": {"name": "count_fruit", "args": {"kind": "apple"}}, "thoughtSignature": _PLACEHOLDER_SIGNATURE}, +) +# Wording AI Studio answers with when a Vertex-minted signature is replayed to it, captured live on 2026-10-27 +_FOREIGN_SIGNATURE_REJECTED: Final = Reply( + status=400, + body=json.dumps( + {"error": {"code": 400, "message": "Corrupted thought signature.", "status": "INVALID_ARGUMENT"}} + ).encode(), +) + + +@pytest.mark.parametrize("stream", (False, True)) +@pytest.mark.parametrize("endpoint", _ENDPOINTS) +def test_gemini_tool_call_signature_the_backend_rejects_is_resent_once_with_the_placeholder( + gateway: Gateway, endpoint: Endpoint, stream: bool ) -> None: + rounds: Final = (f"gemini-reply-{uuid.uuid4().hex}", f"gemini-reply-{uuid.uuid4().hex}") + calls: Final = itertools.count() + + def respond(request: Request) -> Reply: + match next(calls): + case 0: + return _reply(rounds[0], stream=False, parts=_GEMINI_TOOL_REPLY_PARTS) + case 1: + return _FOREIGN_SIGNATURE_REJECTED + case _: + return _reply(rounds[1], stream=stream, parts=({"text": "Twelve apples."},)) + + with wire_server(respond) as wire, gateway.scenario() as scenario: + model: Final = _register(gateway, scenario, "gemini", wire) + first: Final = _tool_round_one(endpoint, model) + headers: Final = {"anthropic-version": "2023-06-01"} + opened: Final = gateway.request("POST", _path(endpoint), first, headers=headers) + assert opened.status_code == 200, opened.text + second: Final = { + **_tool_round_two(endpoint, first, _JSON_OBJECT.validate_json(opened.content)), + "stream": stream, + } + closed: Final = gateway.request("POST", _path(endpoint), second, headers=headers) + assert closed.status_code == 200, closed.text + assert "Twelve apples." in closed.text, closed.text + received: Final = wire.drain() + assert [(request.method, request.target) for request in received] == [ + ("POST", _target("gemini", False)), + ("POST", _target("gemini", stream)), + ("POST", _target("gemini", stream)), + ], received + rejected, resent = (_JSON_OBJECT.validate_json(request.body) for request in received[1:]) + assert rejected == { + **_expected_body(endpoint, _user("Count the apples."), _GEMINI_TOOL_REPLAYED_TURN, _FUNCTION_RESPONSE_TURN), + **_DECLARATIONS, + }, rejected + assert resent == { + **_expected_body(endpoint, _user("Count the apples."), _PLACEHOLDER_TOOL_TURN, _FUNCTION_RESPONSE_TURN), + **_DECLARATIONS, + }, resent + assert _spend_row(rounds[1], *_ISSUED_ID.findall(closed.text))["status"] == "success" + + +def test_responses_previous_response_id_replays_gemini_session_history(gateway: Gateway, tmp_path: Path) -> None: first_prompt: Final = f"gemini-session-first-{uuid.uuid4().hex}" second_prompt: Final = f"gemini-session-second-{uuid.uuid4().hex}" first_answer: Final = f"gemini-answer-first-{uuid.uuid4().hex}" diff --git a/tests/integration/providers/test_gemini_tool_result_part_reference_chaos.py b/tests/integration/providers/test_gemini_tool_result_part_reference_chaos.py index ead83ed66aa..c185c968be9 100644 --- a/tests/integration/providers/test_gemini_tool_result_part_reference_chaos.py +++ b/tests/integration/providers/test_gemini_tool_result_part_reference_chaos.py @@ -301,6 +301,18 @@ def _assert_answered_with_its_own_marker(served: _Served) -> None: assert set(_MARKER.findall(served.text)) == {served.call.marker}, served.text +def _spend_id(served: _Served) -> str: + if served.call.endpoint == "responses" and served.call.stream: + payloads: Final = ( + _JSON_OBJECT.validate_json(line.removeprefix("data: ")) + for line in served.text.splitlines() + if line.startswith("data: {") + ) + (completed,) = tuple(event for event in payloads if event.get("type") == "response.completed") + return str(_JSON_OBJECT.validate_python(completed["response"])["id"]) + return _response_id(served.call.marker) + + async def test_a_concurrent_mixed_burst_reaches_gemini_with_each_tool_result_in_its_own_form(gateway: Gateway) -> None: calls: Final = _calls( 30, ("chat", "messages", "responses"), lambda index: index % 2 == 0, lambda index: (index // 2) % 2 == 0 @@ -314,7 +326,7 @@ async def test_a_concurrent_mixed_burst_reaches_gemini_with_each_tool_result_in_ _assert_each_in_its_own_form(wire.drain(), calls) landed: Final = _spend_rows_by_model(model, 30) assert landed >= { - _response_id(call.marker) for call in calls if not (call.endpoint == "messages" and call.stream) + _spend_id(item) for item in served if not (item.call.endpoint == "messages" and item.call.stream) } diff --git a/tests/integration/providers/test_nvidia_riva_wire.py b/tests/integration/providers/test_nvidia_riva_wire.py index ef36c449761..56d54a87600 100644 --- a/tests/integration/providers/test_nvidia_riva_wire.py +++ b/tests/integration/providers/test_nvidia_riva_wire.py @@ -135,3 +135,12 @@ def test_a_stalled_offline_recognize_answers_408_at_the_deployment_timeout(gatew assert timed_out.status_code == 408, timed_out.text calls: Final = eventually(server.drain, lambda observed: len(observed) > 0, seconds=30) assert all(call.rpc is Rpc.RECOGNIZE and call.cancelled for call in calls), calls + + +@pytest.mark.parametrize("riva_offline", (False, True), ids=("streaming", "offline")) +def test_the_deployment_api_key_reaches_riva_as_exactly_one_bearer_token(gateway: Gateway, riva_offline: bool) -> None: + with riva_server(_WORDS) as server, gateway.scenario() as scenario: + model: Final = _riva_model(scenario, server, api_key="riva-deployment-key", riva_offline=riva_offline) + served: Final = _transcribe(gateway, scenario.key(), model) + assert served.status_code == 200, served.text + assert [call.authorization for call in server.drain()] == [("Bearer riva-deployment-key",)] diff --git a/tests/integration/providers/test_openai_chat_prompt_cache_breakpoint_wire.py b/tests/integration/providers/test_openai_chat_prompt_cache_breakpoint_wire.py index 807a7461675..858599829ad 100644 --- a/tests/integration/providers/test_openai_chat_prompt_cache_breakpoint_wire.py +++ b/tests/integration/providers/test_openai_chat_prompt_cache_breakpoint_wire.py @@ -41,6 +41,7 @@ class _Proxy: openai: Wire gpt_5_6_with_prompt_cache_options: str gpt_5_6_without_prompt_cache_options: str + gpt_5_6_dropping_params: str def openai_receives( self, model: str, messages: Sequence[JsonValue], *, stream: bool = False, tools: Sequence[JsonValue] = () @@ -79,6 +80,9 @@ def proxy() -> Iterator[_Proxy]: model="openai/gpt-5.6", api_base=api_base, prompt_cache_options={"mode": "explicit"} ), gpt_5_6_without_prompt_cache_options=scenario.model(model="openai/gpt-5.6", api_base=api_base), + gpt_5_6_dropping_params=scenario.model( + model="openai/gpt-5.6", api_base=api_base, prompt_cache_options={"mode": "explicit"}, drop_params=True + ), ) @@ -202,3 +206,56 @@ def test_custom_api_base_without_prompt_cache_options_forwards_cache_control_unc assert received["messages"] == _SYSTEM_AND_USER_WITH_CACHE_CONTROL assert "prompt_cache_options" not in received assert "prompt_cache_breakpoint" not in str(received) + + +_CLIENT_BREAKPOINTS_ON_PARTS: Final[list[JsonValue]] = [ + {"type": "text", "text": "Stable rules", "prompt_cache_breakpoint": {"mode": "explicit", "ttl": "1h"}}, + {"type": "text", "text": "More rules", "prompt_cache_breakpoint": {"mode": "implicit"}}, + {"type": "text", "text": "Describe this", "prompt_cache_breakpoint": {"mode": "explicit"}}, +] +_CLIENT_BREAKPOINTS_AS_CHAT_COMPLETIONS_TAKES_THEM: Final[list[JsonValue]] = [ + {"type": "text", "text": "Stable rules", "prompt_cache_breakpoint": {"mode": "explicit"}}, + {"type": "text", "text": "More rules"}, + {"type": "text", "text": "Describe this", "prompt_cache_breakpoint": {"mode": "explicit"}}, +] +_CHAT_COMPLETIONS_REJECTS_TTL_AND_IMPLICIT: Final = ( + "live gpt-6.1-sol Chat Completions answers 400 on a part breakpoint with any ttl or mode implicit (2026-10-28)" +) + + +@pytest.mark.parametrize("stream", [False, True], ids=["unary", "stream"]) +def test_drop_params_cuts_client_breakpoints_down_to_what_chat_completions_takes(proxy: _Proxy, stream: bool) -> None: + received: Final = proxy.openai_receives( + proxy.gpt_5_6_dropping_params, [{"role": "user", "content": _CLIENT_BREAKPOINTS_ON_PARTS}], stream=stream + ) + + assert received["messages"] == [ + {"role": "user", "content": _CLIENT_BREAKPOINTS_AS_CHAT_COMPLETIONS_TAKES_THEM} + ], _CHAT_COMPLETIONS_REJECTS_TTL_AND_IMPLICIT + + +def test_without_drop_params_client_breakpoints_reach_openai_unchanged(proxy: _Proxy) -> None: + received: Final = proxy.openai_receives( + proxy.gpt_5_6_with_prompt_cache_options, [{"role": "user", "content": _CLIENT_BREAKPOINTS_ON_PARTS}] + ) + + assert received["messages"] == [{"role": "user", "content": _CLIENT_BREAKPOINTS_ON_PARTS}] + + +def test_drop_params_cuts_client_breakpoints_on_v1_messages_routed_to_chat_completions(proxy: _Proxy) -> None: + _ = proxy.openai.drain() + response: Final = proxy.gateway.request( + "POST", + "/v1/messages", + { + "model": proxy.gpt_5_6_dropping_params, + "max_tokens": 16, + "stop_sequences": ["END"], + "messages": [{"role": "user", "content": _CLIENT_BREAKPOINTS_ON_PARTS}], + }, + ) + assert response.status_code == 200, response.text + + assert proxy.received_by_openai()["messages"] == [ + {"role": "user", "content": _CLIENT_BREAKPOINTS_AS_CHAT_COMPLETIONS_TAKES_THEM} + ], _CHAT_COMPLETIONS_REJECTS_TTL_AND_IMPLICIT diff --git a/tests/integration/providers/test_openai_chat_wire.py b/tests/integration/providers/test_openai_chat_wire.py index 69295485380..5ba631ac776 100644 --- a/tests/integration/providers/test_openai_chat_wire.py +++ b/tests/integration/providers/test_openai_chat_wire.py @@ -1,4 +1,3 @@ -import base64 import json import uuid from collections.abc import Callable @@ -547,14 +546,8 @@ def test_azure_gpt_6_bridged_no_cache_function_requests_each_reach_provider_and_ lambda found: len(found) == 2, seconds=70, ) - by_response_id: Final = { - (decoded := base64.b64decode(string_value(row["request_id"]).removeprefix("resp_")).decode()) - .rsplit("response_id:", 1)[1]: (decoded, row) - for row in rows - } - for response_id in response_ids: - decoded, row = by_response_id[response_id] - assert decoded.startswith("litellm:custom_llm_provider:azure;model_id:"), rows + assert sorted(string_value(row["request_id"]) for row in rows) == sorted(response_ids), rows + for row in rows: assert ( string_value(row["status"]), string_value(row["cache_hit"]), @@ -601,11 +594,7 @@ def test_azure_gpt_6_bridged_function_requests_without_cache_field_still_hit_cac seconds=70, ) priced, cached = rows - priced_request: Final = base64.b64decode( - string_value(priced["request_id"]).removeprefix("resp_") - ).decode() - assert priced_request.startswith("litellm:custom_llm_provider:azure;model_id:"), rows - assert priced_request.endswith(";response_id:resp_cached"), rows + assert string_value(priced["request_id"]) == "resp_cached", rows assert ( priced["status"], priced["cache_hit"], diff --git a/tests/integration/providers/test_responses_bridge_message_cache_control_wire.py b/tests/integration/providers/test_responses_bridge_message_cache_control_wire.py index 4b25275285e..2e1bd73a4b4 100644 --- a/tests/integration/providers/test_responses_bridge_message_cache_control_wire.py +++ b/tests/integration/providers/test_responses_bridge_message_cache_control_wire.py @@ -809,7 +809,10 @@ def test_provider_error_on_a_marked_request_reaches_the_caller(gateway: Gateway, model: Final = _anthropic_deployment(scenario, wire) answer: Final = _send(gateway, _marked_system(model, marker)) labels: Final = anthropic_labels(_only_request(wire)) - assert answer.status == 500, answer.text + assert answer.status == 503, answer.text + error: Final = object_value(_JSON_OBJECT.validate_json(answer.text)["error"]) + assert error["type"] == "service_unavailable_error", answer.text + assert error["code"] == "server_is_overloaded", answer.text assert "overloaded_error" in answer.text, answer.text assert labels == [SYSTEM_LABEL] spend.landed(model, answer.call_id, None, status="failure") diff --git a/tests/integration/providers/test_responses_bridge_prompt_cache_breakpoint_wire.py b/tests/integration/providers/test_responses_bridge_prompt_cache_breakpoint_wire.py index 33338cae95d..7ea02435369 100644 --- a/tests/integration/providers/test_responses_bridge_prompt_cache_breakpoint_wire.py +++ b/tests/integration/providers/test_responses_bridge_prompt_cache_breakpoint_wire.py @@ -27,8 +27,9 @@ _MALFORMED: Final[tuple[tuple[str, JsonValue], ...]] = ( ("5kb-string", "x" * 5000), ("empty-object", {}), ("bogus-mode", {"mode": "bogus"}), - ("bad-ttl", {"mode": "explicit", "ttl": "1h"}), + ("bogus-mode-with-ttl", {"mode": "bogus", "ttl": "30m"}), ) +_UNSUPPORTED_TTL: Final[Mapping[str, JsonValue]] = {"mode": "explicit", "ttl": "1h"} _MALFORMED_IDS: Final = tuple(name for name, _ in _MALFORMED) _MALFORMED_VALUES: Final = tuple(value for _, value in _MALFORMED) _CASES: Final[tuple[tuple[str, Mode, JsonValue, JsonValue], ...]] = ( @@ -192,6 +193,27 @@ def test_marker_with_an_unknown_key(bridge: _Bridge, mode: Mode, expected: JsonV bridge.spend.landed(bridge.model(mode), call_id, marker) +@pytest.mark.parametrize( + ("mode", "expected"), (("on", None), ("off", _UNSUPPORTED_TTL)), ids=("dropped-on", "verbatim-off") +) +def test_marker_with_an_unsupported_ttl(bridge: _Bridge, mode: Mode, expected: JsonValue) -> None: + marker: Final = uuid.uuid4().hex + call_id: Final = _completion(_chat(bridge, bridge.model(mode), [_user(marker, _UNSUPPORTED_TTL)]), marker) + pcb.assert_marker(_user_block_on_wire(bridge, marker), expected) + bridge.spend.landed(bridge.model(mode), call_id, marker) + + +def test_marker_with_an_unsupported_ttl_keeps_its_mode_on_a_host_opted_in_with_prompt_cache_options( + bridge: _Bridge, +) -> None: + marker: Final = uuid.uuid4().hex + with bridge.gateway.scenario() as scenario: + model: Final = scenario.model(model=pcb.MODEL, api_base=bridge.api_base, drop_params=True, **_OPTED_IN) + call_id: Final = _completion(_chat(bridge, model, [_user(marker, _UNSUPPORTED_TTL)]), marker) + pcb.assert_marker(_user_block_on_wire(bridge, marker), pcb.EXPLICIT) + bridge.spend.landed(model, call_id, marker) + + def _second_block_on_wire(bridge: _Bridge, marker: str) -> dict[str, JsonValue]: request: Final = pcb.posted(bridge.wire, marker) _wire_body(request) diff --git a/tests/integration/providers/test_responses_core_wire.py b/tests/integration/providers/test_responses_core_wire.py index 9a24903a20d..f9ff26045bc 100644 --- a/tests/integration/providers/test_responses_core_wire.py +++ b/tests/integration/providers/test_responses_core_wire.py @@ -1,10 +1,12 @@ from __future__ import annotations +import base64 import json import os import uuid -from collections.abc import Callable -from typing import Final +from collections.abc import AsyncIterator, Callable, Iterator +from copy import deepcopy +from typing import Final, Protocol, runtime_checkable import openai import pytest @@ -14,6 +16,10 @@ from integration._support.worker_readiness import wait_for_worker_readiness from openai.types.responses import ResponseCompletedEvent from pydantic import JsonValue, TypeAdapter +import litellm +from litellm.types.llms.openai import ResponseCompletedEvent as LiteLLMResponseCompletedEvent +from litellm.types.llms.openai import ResponsesAPIResponse + _MODEL: Final = "gpt-5" _API_KEY: Final = "synthetic-responses-key" _JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) @@ -21,6 +27,16 @@ _PROXY_WORKERS: Final = max(1, int(os.environ.get("INTEGRATION_PROXY_WORKERS", " _ALIASES: Final = ("/v1", "", "/openai/v1") +@runtime_checkable +class _AsyncResponseEvents(Protocol): + def __aiter__(self) -> AsyncIterator[object]: ... + + +@runtime_checkable +class _ResponseEvents(Protocol): + def __iter__(self) -> Iterator[object]: ... + + def _deployments_in_group(gateway: Gateway, group: str) -> int: entries: Final = gateway.get("/model/info")["data"] assert isinstance(entries, list), entries @@ -69,6 +85,175 @@ def _stream(identity: str) -> tuple[bytes, ...]: ) + (b"data: [DONE]\n\n",) +@pytest.mark.asyncio +@pytest.mark.parametrize("asynchronous", (False, True), ids=("sync", "async")) +@pytest.mark.parametrize("stream", (False, True), ids=("nonstream", "stream")) +@pytest.mark.parametrize("extra", (False, True), ids=("top-level", "extra-body-precedence")) +async def test_regression_sdk_comparison_response_id_is_raw_on_the_wire( + asynchronous: bool, stream: bool, extra: bool +) -> None: + raw_id: Final = f"resp_sdk_comparison_{uuid.uuid4().hex}" + + def respond(request: Request) -> Reply: + assert (request.method, request.target) == ("POST", "/v1/responses") + body: Final = _JSON_OBJECT.validate_json(request.body) + if body["input"] == "seed comparison": + assert body == {"model": _MODEL, "input": "seed comparison"}, request.body + return Reply(body=_response(raw_id)) + assert body == { + "model": _MODEL, + "input": "compare response", + "stream": stream, + "previous_response_id": raw_id, + "prompt_cache_options": {"comparison_response_id": raw_id}, + }, request.body + return ( + Reply(content_type="text/event-stream", chunks=_stream(raw_id)) if stream else Reply(body=_response(raw_id)) + ) + + with wire_server(respond) as wire: + seeded: Final = litellm.responses( + model=f"openai/{_MODEL}", input="seed comparison", api_base=f"{wire.url}/v1", api_key=_API_KEY + ) + assert isinstance(seeded, ResponsesAPIResponse), seeded + assert seeded.id != raw_id, seeded + params: Final = { + "model": f"openai/{_MODEL}", + "input": "compare response", + "stream": stream, + "previous_response_id": seeded.id, + "api_base": f"{wire.url}/v1", + "api_key": _API_KEY, + "num_retries": 0, + **( + { + "prompt_cache_options": {"mode": "explicit", "ttl": "12h"}, + "extra_body": {"prompt_cache_options": {"comparison_response_id": seeded.id}}, + } + if extra + else {"prompt_cache_options": {"comparison_response_id": seeded.id}} + ), + } + original: Final = deepcopy(params) + result: Final = await litellm.aresponses(**params) if asynchronous else litellm.responses(**params) + if stream: + if asynchronous: + assert isinstance(result, _AsyncResponseEvents), result + async_events: Final = tuple([event async for event in result]) + async_completed: Final = async_events[-1] + assert isinstance(async_completed, LiteLLMResponseCompletedEvent), async_events + assert async_completed.response.status == "completed", async_events + else: + assert isinstance(result, _ResponseEvents), result + sync_events: Final = tuple(result) + sync_completed: Final = sync_events[-1] + assert isinstance(sync_completed, LiteLLMResponseCompletedEvent), sync_events + assert sync_completed.response.status == "completed", sync_events + else: + assert isinstance(result, ResponsesAPIResponse), result + assert result.status == "completed", result + assert params == original, "The caller's comparison options were mutated" + assert len(wire.drain()) == 2 + + +@pytest.mark.parametrize("extra", (False, True)) +@pytest.mark.parametrize( + "comparison_id", + ( + "resp_custom_vendor_id", + "resp_!!!not-base64", + "cmF3X3ZlbmRvcl9pZA==", + pytest.param( + "resp_" + + base64.b64encode(b"litellm:custom_llm_provider:xai;model_id:foreign;response_id:resp_foreign").decode(), + id="foreign-provider-wrapper", + ), + pytest.param("resp_" + base64.b64encode(b"custom;id;response").decode(), id="unmanaged-semicolons"), + pytest.param( + "resp_" + base64.b64encode(b"openai;foreign;resp_unmanaged").decode(), id="openai-without-envelope-markers" + ), + ), +) +def test_guard_sdk_custom_host_preserves_unmanaged_comparison_ids(extra: bool, comparison_id: str) -> None: + def respond(request: Request) -> Reply: + assert (request.method, request.target) == ("POST", "/v1/responses") + assert _JSON_OBJECT.validate_json(request.body) == { + "model": _MODEL, + "input": "custom comparison", + "prompt_cache_options": {"comparison_response_id": comparison_id, "mode": "implicit", "ttl": "30m"}, + }, request.body + return Reply(body=_response("resp_custom_result")) + + with wire_server(respond) as wire: + options: Final = { + "comparison_response_id": comparison_id, + "mode": "implicit", + "ttl": "30m", + } + params: Final = ( + {"extra_body": {"prompt_cache_options": options}} if extra else {"prompt_cache_options": options} + ) + original: Final = deepcopy(params) + result: Final = litellm.responses( + model=f"openai/{_MODEL}", input="custom comparison", api_base=f"{wire.url}/v1", api_key=_API_KEY, **params + ) + assert isinstance(result, ResponsesAPIResponse), result + assert result.status == "completed", result + assert params == original + assert len(wire.drain()) == 1 + + +@pytest.mark.parametrize("provider", ("azure", "xai")) +@pytest.mark.parametrize("extra", (False, True)) +def test_guard_inherited_responses_providers_preserve_comparison_wrappers(provider: str, extra: bool) -> None: + raw_id: Final = f"resp_inherited_{uuid.uuid4().hex}" + + def seed(request: Request) -> Reply: + assert _JSON_OBJECT.validate_json(request.body) == {"model": _MODEL, "input": "seed inherited comparison"} + return Reply(body=_response(raw_id)) + + with wire_server(seed) as seed_wire: + seeded: Final = litellm.responses( + model=f"openai/{_MODEL}", + input="seed inherited comparison", + api_base=f"{seed_wire.url}/v1", + api_key=_API_KEY, + ) + assert isinstance(seeded, ResponsesAPIResponse), seeded + assert seeded.id != raw_id + assert len(seed_wire.drain()) == 1 + + def respond(request: Request) -> Reply: + assert request.method == "POST", request + expected_target: Final = ( + "/openai/responses?api-version=2025-03-01-preview" if provider == "azure" else "/v1/responses" + ) + assert request.target == expected_target, request.target + assert _JSON_OBJECT.validate_json(request.body) == { + "model": _MODEL, + "input": "inherited comparison", + "prompt_cache_options": {"comparison_response_id": seeded.id}, + }, request.body + return Reply(body=_response(raw_id)) + + with wire_server(respond) as wire: + options: Final = {"comparison_response_id": seeded.id} + params: Final = ( + {"extra_body": {"prompt_cache_options": options}} if extra else {"prompt_cache_options": options} + ) + result: Final = litellm.responses( + model=f"{provider}/{_MODEL}", + input="inherited comparison", + api_base=wire.url if provider == "azure" else f"{wire.url}/v1", + api_key=_API_KEY, + api_version="2025-03-01-preview" if provider == "azure" else None, + **params, + ) + assert isinstance(result, ResponsesAPIResponse), result + assert result.status == "completed", result + assert len(wire.drain()) == 1 + + def _register_in_group(scenario: Scenario, wire: Wire, group: str, order: int | None = None) -> str: existing: Final = _deployments_in_group(scenario.gateway, group) created: Final = scenario.gateway.post( diff --git a/tests/integration/providers/test_responses_lifecycle_wire.py b/tests/integration/providers/test_responses_lifecycle_wire.py index 02269885b44..35a555fc776 100644 --- a/tests/integration/providers/test_responses_lifecycle_wire.py +++ b/tests/integration/providers/test_responses_lifecycle_wire.py @@ -4,7 +4,7 @@ import json import os import threading import uuid -from collections.abc import Callable +from collections.abc import Callable, Iterator from types import MappingProxyType from typing import Final, Literal from urllib.parse import parse_qsl, urlsplit @@ -12,7 +12,15 @@ from urllib.parse import parse_qsl, urlsplit import httpx import openai import pytest -from integration._support.client import Gateway, Scenario, eventually, object_value, string_value +from integration._support.client import ( + Gateway, + Scenario, + eventually, + gateway_from_environment, + object_value, + string_value, +) +from integration._support.process import owned_proxy from integration._support.responses_vendor import same_response from integration._support.wire import Reply, Request, Wire, wire_server from integration._support.worker_readiness import wait_for_worker_readiness @@ -26,6 +34,16 @@ _PROXY_WORKERS: Final = max(1, int(os.environ.get("INTEGRATION_PROXY_WORKERS", " _ALIASES: Final = ("/v1", "", "/openai/v1") +@pytest.fixture(scope="module") +def cancel_gateway(tmp_path_factory: pytest.TempPathFactory) -> Iterator[Gateway]: + directory: Final = tmp_path_factory.mktemp("responses-cancel") + with ( + gateway_from_environment() as shared, + owned_proxy(shared, directory, {"PROXY_BATCH_POLLING_ENABLED": "false"}, workers=_PROXY_WORKERS) as owned, + ): + yield owned + + class _DeleteResponse(BaseModel): model_config = ConfigDict(extra="forbid") @@ -203,9 +221,6 @@ def test_retrieve_routes_to_the_deployment_that_created_the_response( @pytest.mark.parametrize("prefix", _ALIASES) def test_retrieve_returns_the_id_the_client_holds(gateway: Gateway, prefix: str) -> None: - pytest.skip( - "BUG: GET /v1/responses/{id} returns a re-encrypted id that differs byte-for-byte from the id the client sent" - ) raw_id: Final = f"resp_retrieve_id_{uuid.uuid4().hex}" def respond(request: Request) -> Reply: @@ -697,7 +712,6 @@ def test_delete_returns_the_client_held_id_not_the_provider_id( gateway: Gateway, prefix: str, ) -> None: - pytest.skip("BUG: DELETE /v1/responses/{id} returns the raw provider id instead of the proxy-issued id") raw_id: Final = f"resp_delete_id_{uuid.uuid4().hex}" def respond(request: Request) -> Reply: @@ -741,7 +755,7 @@ def test_delete_returns_the_client_held_id_not_the_provider_id( @pytest.mark.parametrize("prefix", _ALIASES) def test_cancel_forwards_provider_id_and_returns_cancelled_response( - gateway: Gateway, + cancel_gateway: Gateway, prefix: str, ) -> None: raw_id: Final = f"resp_cancel_{uuid.uuid4().hex}" @@ -760,9 +774,9 @@ def test_cancel_forwards_provider_id_and_returns_cancelled_response( assert request.body in (b"", b"{}") return Reply(body=_response(raw_id, "cancelled")) - with wire_server(respond) as wire, gateway.scenario() as scenario: + with wire_server(respond) as wire, cancel_gateway.scenario() as scenario: model: Final = _deployment(scenario, wire) - client: Final = _client(gateway, gateway.key, prefix) + client: Final = _client(cancel_gateway, cancel_gateway.key, prefix) created: Final = client.responses.create(model=model, input="cancel lifecycle", background=True) cancelled: Final = client.responses.cancel(created.id) assert cancelled.id != raw_id and same_response(cancelled.id, created.id), cancelled.model_dump_json() diff --git a/tests/integration/providers/test_responses_minted_reasoning_replay_chaos.py b/tests/integration/providers/test_responses_minted_reasoning_replay_chaos.py index 16d37980efa..a266b20b227 100644 --- a/tests/integration/providers/test_responses_minted_reasoning_replay_chaos.py +++ b/tests/integration/providers/test_responses_minted_reasoning_replay_chaos.py @@ -419,7 +419,7 @@ class _LoginDeployment: _LOGIN_DEPLOYMENTS: Final = ( _LoginDeployment("github_copilot", f"github_copilot/{_CODEX}", None), _LoginDeployment("chatgpt", f"chatgpt/{_CODEX}", None), - _LoginDeployment("azure_ai-foundry-host", "azure_ai/deepseek-v3", "synthetic-azure-key"), + _LoginDeployment("azure_ai-foundry-host", "azure_ai/deepseek-v3.2", "synthetic-azure-key"), ) diff --git a/tests/integration/providers/test_vertex_anthropic_inline_tools_beta_wire.py b/tests/integration/providers/test_vertex_anthropic_inline_tools_beta_wire.py index 3175f2ec075..00f861678cb 100644 --- a/tests/integration/providers/test_vertex_anthropic_inline_tools_beta_wire.py +++ b/tests/integration/providers/test_vertex_anthropic_inline_tools_beta_wire.py @@ -25,7 +25,7 @@ from pydantic import JsonValue, TypeAdapter _INLINE_TOOLS: Final = "inline-tools-2026-09-15" _THINKING: Final = "interleaved-thinking-2025-05-14" -_VERTEX_UNSUPPORTED: Final = "effort-2025-11-24" +_VERTEX_UNSUPPORTED: Final = "skills-2025-10-02" _UNKNOWN: Final = "not-a-beta-2099-01-01" _BACKEND: Final = "claude-opus-5-5" _PROJECT: Final = "scripted-project" diff --git a/tests/integration/providers/test_vertex_anthropic_structured_output_wire.py b/tests/integration/providers/test_vertex_anthropic_structured_output_wire.py index 4e31122440d..19928ecd6e0 100644 --- a/tests/integration/providers/test_vertex_anthropic_structured_output_wire.py +++ b/tests/integration/providers/test_vertex_anthropic_structured_output_wire.py @@ -34,14 +34,20 @@ from pydantic import JsonValue, TypeAdapter pytestmark: Final = pytest.mark.shares_worker_state _JSON_TOOL: Final = "json_tool_call" +_UNFORCED_JSON_TOOL_DESCRIPTION: Final = ( + "When you are ready to answer, call this tool with your final answer as its input. Do not reply in plain text." +) _USER_TOOL: Final = "lookup" _STRUCTURED_OUTPUTS_BETA: Final = "structured-outputs-2025-11-13" _TOOL_MODEL: Final = "claude-sonnet-5" _EFFORT_GATED_MODEL: Final = "claude-haiku-4-5" _NATIVE_MODEL: Final = "claude-opus-5-5" -_FORCED_TOOL_NATIVE_MODEL: Final = "claude-haiku-5-5" +_FORCED_TOOL_NATIVE_MODEL: Final = "claude-opus-4-8" +_THINKING_BY_DEFAULT_NATIVE_MODEL: Final = "claude-haiku-5-5" +_THINKING_OFF_TOOL_MODEL: Final = "claude-opus-4-8" _UNMAPPED_MODEL: Final = "claude-scripted-9" _BEDROCK_INVOKE_MODEL: Final = "anthropic.claude-sonnet-5" +_BEDROCK_TOOL_PATH_MODEL: Final = "anthropic.claude-opus-4-8" _BEDROCK_JSON_TOOL_MODEL: Final = "us.anthropic.claude-opus-4-8" _THINKING_SIGNATURE: Final = "c2NyaXB0ZWQtc2lnbmF0dXJl" _PROJECT: Final = "scripted-project" @@ -608,11 +614,15 @@ def _one_delivery(wire: Wire, marker_hex: str) -> _Delivery: return sent -def _json_tool_schema(delivery: _Delivery) -> dict[str, JsonValue]: +def _json_tool(delivery: _Delivery) -> dict[str, JsonValue]: tools: Final = tuple(object_value(tool) for tool in list_value(delivery.body["tools"])) (json_tool,) = tuple(tool for tool in tools if tool["name"] == _JSON_TOOL) - assert json_tool.keys() == {"name", "input_schema"}, json_tool - return object_value(json_tool["input_schema"]) + assert json_tool.keys() - {"description"} == {"name", "input_schema"}, json_tool + return json_tool + + +def _json_tool_schema(delivery: _Delivery) -> dict[str, JsonValue]: + return object_value(_json_tool(delivery)["input_schema"]) def _folded_format(delivery: _Delivery) -> dict[str, JsonValue]: @@ -830,10 +840,10 @@ def _family_deployment(gateway: Gateway, scenario: Scenario, api_base: str, memb case "azure_ai_unmapped": return scenario.model(model=f"azure_ai/{_UNMAPPED_MODEL}", api_base=api_base, api_key=_AZURE_KEY) case "bedrock_invoke": - return _bedrock_invoke_deployment(scenario, api_base, _BEDROCK_INVOKE_MODEL) + return _bedrock_invoke_deployment(scenario, api_base, _BEDROCK_TOOL_PATH_MODEL) case "bedrock_mantle": return scenario.model( - model=f"bedrock_mantle/{_BEDROCK_INVOKE_MODEL}", + model=f"bedrock_mantle/{_BEDROCK_TOOL_PATH_MODEL}", api_base=api_base, api_key=_MANTLE_KEY, aws_region_name="us-east-1", @@ -1448,21 +1458,24 @@ def test_tool_path_stream_cut_before_the_tool_block_closes_still_delivers_the_an _one_delivery(wire, marker_hex) -@pytest.mark.parametrize("accepts_forced_tools", [True, False], ids=["accepts_forced_tools", "rejects_forced_tools"]) -def test_vertex_chat_json_schema_forces_the_json_tool_only_when_the_model_accepts_forced_tools( - gateway: Gateway, accepts_forced_tools: bool +@pytest.mark.parametrize( + ("tool_model", "forced"), + [(_THINKING_OFF_TOOL_MODEL, True), (_TOOL_MODEL, False), (None, False)], + ids=["accepts_forced_tools", "thinks_by_default", "rejects_forced_tools"], +) +def test_vertex_chat_json_schema_forces_the_json_tool_only_when_the_model_will_not_think( + gateway: Gateway, tool_model: str | None, forced: bool ) -> None: marker, marker_hex = _marker("plain") - backend: Final = ( - _TOOL_MODEL if accepts_forced_tools else _claude_rejecting_forced_tools(gateway, "vertex_ai/", "claude") - ) + backend: Final = tool_model or _claude_rejecting_forced_tools(gateway, "vertex_ai/", "claude") with wire_server(_peer) as wire, gateway.scenario() as scenario: model: Final = _vertex_deployment(gateway, scenario, wire.url, backend) response: Final = gateway.request("POST", "/v1/chat/completions", _chat_body(model, marker)) assert _chat_content(response) == _payload(marker_hex), response.text sent: Final = _one_delivery(wire, marker_hex) assert _json_tool_schema(sent)["properties"] == _SCHEMA["properties"], sent.body - assert sent.body.get("tool_choice") == (_FORCED_JSON_TOOL if accepts_forced_tools else None), sent.body + assert sent.body.get("tool_choice") == (_FORCED_JSON_TOOL if forced else None), sent.body + assert _json_tool(sent).get("description") == (None if forced else _UNFORCED_JSON_TOOL_DESCRIPTION), sent.body assert "output_config" not in sent.body and "output_format" not in sent.body, sent.body @@ -1488,7 +1501,7 @@ def test_vertex_chat_json_schema_on_a_model_rejecting_forced_tools_maps_reasonin assert _reasoning_fields(structured_sent) == _reasoning_fields(plain_sent), (structured_sent.body, plain_sent.body) -def test_bedrock_invoke_json_schema_sends_the_json_tool_unforced_when_the_model_rejects_forced_tools( +def test_bedrock_invoke_json_schema_sends_native_structured_output_when_the_model_rejects_forced_tools( gateway: Gateway, ) -> None: marker, marker_hex = _marker("plain") @@ -1499,7 +1512,8 @@ def test_bedrock_invoke_json_schema_sends_the_json_tool_unforced_when_the_model_ assert _chat_content(response) == _payload(marker_hex), response.text sent: Final = _one_delivery(wire, marker_hex) assert sent.target == f"/model/{backend}/invoke", sent.target - assert _json_tool_schema(sent)["properties"] == _SCHEMA["properties"], sent.body + assert object_value(_folded_format(sent)["schema"])["properties"] == _SCHEMA["properties"], sent.body + assert "tools" not in sent.body, sent.body assert "tool_choice" not in sent.body, sent.body @@ -1565,6 +1579,25 @@ def test_native_model_json_schema_with_an_open_object_takes_the_json_tool_and_ke sent: Final = _one_delivery(wire, marker_hex) assert not _structured(sent.body), sent.body assert _json_tool_schema(sent)["properties"] == _VALUES_SCHEMA["properties"], sent.body + assert sent.body.get("tool_choice") == _FORCED_JSON_TOOL, sent.body + + +@pytest.mark.parametrize("provider", ["anthropic", "azure_ai"]) +def test_open_object_schema_takes_the_unforced_json_tool_on_a_model_that_thinks_by_default( + gateway: Gateway, provider: str +) -> None: + marker, marker_hex = _marker("values") + with wire_server(_peer) as wire, gateway.scenario() as scenario: + model: Final = _native_deployment(gateway, scenario, wire.url, provider, _THINKING_BY_DEFAULT_NATIVE_MODEL) + response: Final = gateway.request( + "POST", "/v1/chat/completions", _chat_body(model, marker, response_format=_VALUES_RESPONSE_FORMAT) + ) + assert _chat_content(response) == _tool_input("values", marker_hex), response.text + sent: Final = _one_delivery(wire, marker_hex) + assert not _structured(sent.body), sent.body + assert _json_tool_schema(sent)["properties"] == _VALUES_SCHEMA["properties"], sent.body + assert _json_tool(sent).get("description") == _UNFORCED_JSON_TOOL_DESCRIPTION, sent.body + assert "tool_choice" not in sent.body, sent.body @pytest.mark.parametrize( diff --git a/tests/integration/providers/test_vertex_passthrough_stream_wire.py b/tests/integration/providers/test_vertex_passthrough_stream_wire.py new file mode 100644 index 00000000000..1ec2f740480 --- /dev/null +++ b/tests/integration/providers/test_vertex_passthrough_stream_wire.py @@ -0,0 +1,121 @@ +import json +import os +import uuid +from collections.abc import Iterator +from dataclasses import dataclass +from typing import Final + +import httpx +import pytest +from integration._support.client import Gateway, gateway_from_environment +from integration._support.forward_proxy import ForwardProxy, tunnelling_forward_proxy +from integration._support.process import owned_proxy +from integration._support.tls import server_context, write_self_signed_cert +from integration._support.wire import Reply, Request, Wire, wire_server + +_LOCATION: Final = "us-central1" +_HOST: Final = f"{_LOCATION}-aiplatform.googleapis.com" +_PROJECT: Final = "audit-vertex-pass-through" +_STREAMING_MODEL: Final = "gemini-3.8-flash" +_UNAVAILABLE_MODEL: Final = "gemini-3.8-flash-unavailable" +_VENDOR_TOKEN: Final = "Bearer synthetic-vertex-token" +_CHUNKS: Final = ( + b'data: {"candidates": [{"content": {"role": "model", "parts": [{"text": "Hel"}]}}]}\r\n\r\n', + b'data: {"candidates": [{"content": {"role": "model", "parts": [{"text": "lo"}]}, "finishReason": "STOP"}],' + b' "usageMetadata": {"promptTokenCount": 3, "candidatesTokenCount": 2, "totalTokenCount": 5}}\r\n\r\n', +) +_UNAVAILABLE_MESSAGE: Final = "The service is currently unavailable." +_UNAVAILABLE_BODY: Final = json.dumps( + {"error": {"code": 503, "message": _UNAVAILABLE_MESSAGE, "status": "UNAVAILABLE"}} +).encode() +_SCRUBBED: Final = frozenset( + { + "HTTPS_PROXY", + "HTTP_PROXY", + "ALL_PROXY", + "NO_PROXY", + "SSL_CERT_FILE", + "DEFAULT_VERTEXAI_PROJECT", + "DEFAULT_VERTEXAI_LOCATION", + "DEFAULT_GOOGLE_APPLICATION_CREDENTIALS", + "GOOGLE_APPLICATION_CREDENTIALS", + } +) + + +@dataclass(frozen=True, slots=True) +class _Vertex: + wire: Wire + tunnel: ForwardProxy + proxy: Gateway + + def stream(self, model: str, marker: str) -> httpx.Response: + return self.proxy.request( + "POST", + f"/vertex_ai/v1/{_model_path(model)}:streamGenerateContent", + {"contents": [{"role": "user", "parts": [{"text": marker}]}]}, + headers={"Authorization": _VENDOR_TOKEN, "x-litellm-api-key": f"Bearer {self.proxy.key}"}, + ) + + +def _model_path(model: str) -> str: + return f"projects/{_PROJECT}/locations/{_LOCATION}/publishers/google/models/{model}" + + +def _respond(request: Request) -> Reply: + if request.target.startswith(f"/v1/{_model_path(_UNAVAILABLE_MODEL)}:"): + return Reply(status=503, body=_UNAVAILABLE_BODY) + if request.target.startswith(f"/v1/{_model_path(_STREAMING_MODEL)}:"): + return Reply(content_type="text/event-stream", chunks=_CHUNKS) + return Reply(status=404, body=b'{"error": "no scripted Vertex model"}') + + +@pytest.fixture(scope="module") +def vertex(tmp_path_factory: pytest.TempPathFactory) -> Iterator[_Vertex]: + directory: Final = tmp_path_factory.mktemp("vertex-pass-through-stream") + cert, key = write_self_signed_cert(directory, (_HOST,)) + with ( + wire_server(_respond, tls=server_context(cert, key)) as wire, + tunnelling_forward_proxy(int(wire.url.rsplit(":", 1)[1])) as tunnel, + gateway_from_environment() as rig, + owned_proxy( + rig, + directory, + {"HTTPS_PROXY": tunnel.url, "NO_PROXY": "127.0.0.1,localhost", "SSL_CERT_FILE": str(cert)}, + remove_environment=tuple(name for name in os.environ if name.upper() in _SCRUBBED), + workers=2, + ) as proxy, + ): + yield _Vertex(wire, tunnel, proxy) + + +@pytest.fixture(autouse=True) +def fresh_edges(vertex: _Vertex) -> None: + vertex.wire.drain() + vertex.tunnel.drain() + + +def test_vertex_pass_through_stream_relays_every_sse_chunk_byte_for_byte(vertex: _Vertex) -> None: + marker: Final = uuid.uuid4().hex + response: Final = vertex.stream(_STREAMING_MODEL, marker) + sent: Final = vertex.wire.drain() + + assert response.status_code == 200, response.text + assert response.headers["content-type"].startswith("text/event-stream"), response.headers + assert response.content == b"".join(_CHUNKS), response.text + assert [request.target for request in sent] == [ + f"/v1/{_model_path(_STREAMING_MODEL)}:streamGenerateContent?alt=sse" + ], sent + assert sent[0].headers["authorization"] == _VENDOR_TOKEN + assert json.loads(sent[0].body) == {"contents": [{"role": "user", "parts": [{"text": marker}]}]} + assert set(vertex.tunnel.targets()) == {f"{_HOST}:443"} + + +def test_vertex_pass_through_stream_relays_an_upstream_503_as_503(vertex: _Vertex) -> None: + response: Final = vertex.stream(_UNAVAILABLE_MODEL, uuid.uuid4().hex) + + assert response.status_code == 503, response.text + assert response.content == _UNAVAILABLE_BODY, response.text + assert [request.target for request in vertex.wire.drain()] == [ + f"/v1/{_model_path(_UNAVAILABLE_MODEL)}:streamGenerateContent?alt=sse" + ] diff --git a/tests/integration/proxy_config.yaml b/tests/integration/proxy_config.yaml index 4e2cab56d27..c552e11c22a 100644 --- a/tests/integration/proxy_config.yaml +++ b/tests/integration/proxy_config.yaml @@ -587,6 +587,11 @@ model_list: model: perplexity/pplx-decider-v1-27b api_base: http://127.0.0.1:8191 api_key: synthetic-perplexity-key + - model_name: parallel_ai/decision + litellm_params: + model: parallel_ai/decision + api_base: http://127.0.0.1:8191 + api_key: synthetic-parallel-key - model_name: typesafe/jev-1.13.0 litellm_params: model: typesafe/jev-1.13.0 diff --git a/tests/integration/routing/test_anthropic_overloaded_cooldown_owned_proxy.py b/tests/integration/routing/test_anthropic_overloaded_cooldown_owned_proxy.py new file mode 100644 index 00000000000..e6df49a73bd --- /dev/null +++ b/tests/integration/routing/test_anthropic_overloaded_cooldown_owned_proxy.py @@ -0,0 +1,247 @@ +import json +import os +import uuid +from collections.abc import Iterator +from dataclasses import dataclass +from pathlib import Path +from typing import Final +from urllib.parse import unquote + +import httpx +import pytest +import yaml +from integration._support.anthropic_sse import ( + LIFECYCLE, + error_body, + event_types, + message_id, + message_stream, + parse_sse, + status_reply, + stream_reply, + user_prompt, +) +from integration._support.client import ( + Gateway, + JsonValue, + gateway_from_environment, + object_value, + string_value, +) +from integration._support.process import graceful_stop_seconds, owned_proxy +from integration._support.wire import Reply, Request, Wire, wire_server + +_OVERLOADED: Final = "claude-overloaded" +_HEALTHY: Final = "claude-healthy" +_COUNTED: Final = "claude-counted" +_COUNTED_OVERLOADED: Final = "claude-counted-overloaded" +_COUNTED_RATE_LIMITED: Final = "claude-counted-rate-limited" +_CHAT_ONLY_BACKEND: Final = "audit-chat-only" +_API_KEY: Final = "synthetic-anthropic-key" +_TEXT: Final = "Hello" +_COOLDOWN_GROUP: Final = "audit-overloaded-cooldown" +_COUNT_DISABLED_GROUP: Final = "audit-count-tokens-disabled" +_COUNT_UPSTREAM_GROUP: Final = "audit-count-tokens-upstream-503" +_COUNT_OVERLOADED_GROUP: Final = "audit-count-tokens-upstream-529" +_COUNT_RATE_LIMITED_GROUP: Final = "audit-count-tokens-upstream-429" +_GATEWAY: Final = "/claude_code_gateway" +_GATEWAY_GROUPS: Final = { + "non-stream": "audit-gateway-overloaded-non-stream", + "stream": "audit-gateway-overloaded-stream", +} +_COUNT_STATUSES: Final = {_COUNTED: 503, _COUNTED_OVERLOADED: 529, _COUNTED_RATE_LIMITED: 429} +_COUNT_TOKENS_TARGET: Final = "/v1/messages/count_tokens" +_UPSTREAM_URL_PLACEHOLDER: Final = "upstream-url" + +pytestmark: Final = pytest.mark.timeout(2 * graceful_stop_seconds() + 120) + + +def _served_id(marker: str) -> str: + return f"msg_{_HEALTHY}_{marker}" + + +def _respond(request: Request) -> Reply: + body: Final = object_value(json.loads(request.body)) + backend: Final = str(body["model"]) + if unquote(request.target) == _COUNT_TOKENS_TARGET: + status: Final = _COUNT_STATUSES[backend] + return Reply(status=status, body=error_body(status, f"scripted {status}")) + if backend == _OVERLOADED: + return status_reply(529) + if backend == _HEALTHY: + return stream_reply(message_stream(_served_id(user_prompt(body)), backend, _TEXT)) + return Reply(status=404, body=b'{"error": "no scripted backend"}') + + +def _deployment(name: str, model: str, api_base: str, api_key: str, **params: JsonValue) -> dict[str, JsonValue]: + return {"model_name": name, "litellm_params": {"model": model, "api_base": api_base, "api_key": api_key, **params}} + + +def _config(wire: Wire, directory: Path) -> Path: + config: Final = yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text()) + config["model_list"] = [ + _deployment(_COOLDOWN_GROUP, f"anthropic/{_OVERLOADED}", _UPSTREAM_URL_PLACEHOLDER, _API_KEY, order=1), + _deployment(_COOLDOWN_GROUP, f"anthropic/{_HEALTHY}", _UPSTREAM_URL_PLACEHOLDER, _API_KEY, order=2), + _deployment( + _COUNT_DISABLED_GROUP, + f"hosted_vllm/{_CHAT_ONLY_BACKEND}", + _UPSTREAM_URL_PLACEHOLDER + "/v1", + "synthetic-vllm-key", + ), + _deployment(_COUNT_UPSTREAM_GROUP, f"anthropic/{_COUNTED}", _UPSTREAM_URL_PLACEHOLDER, _API_KEY), + _deployment(_COUNT_OVERLOADED_GROUP, f"anthropic/{_COUNTED_OVERLOADED}", _UPSTREAM_URL_PLACEHOLDER, _API_KEY), + _deployment( + _COUNT_RATE_LIMITED_GROUP, f"anthropic/{_COUNTED_RATE_LIMITED}", _UPSTREAM_URL_PLACEHOLDER, _API_KEY + ), + *( + _deployment(group, f"anthropic/{_OVERLOADED}", _UPSTREAM_URL_PLACEHOLDER, _API_KEY) + for group in _GATEWAY_GROUPS.values() + ), + ] + config["router_settings"] = { + "num_retries": 0, + "allowed_fails_policy": {"InternalServerErrorAllowedFails": 0}, + "cooldown_time": 120, + "redis_host": os.environ["REDIS_HOST"], + "redis_port": int(os.environ["REDIS_PORT"]), + } + config["litellm_settings"]["disable_token_counter"] = True + config["general_settings"]["enable_claude_code_gateway"] = True + path: Final = directory / "anthropic-overloaded-cooldown.yaml" + path.write_text(yaml.safe_dump(config).replace(_UPSTREAM_URL_PLACEHOLDER, wire.url)) + return path + + +@dataclass(frozen=True, slots=True) +class _Rig: + proxy: Gateway + wire: Wire + + def messages(self, path: str, model: str, marker: str, **extra: JsonValue) -> httpx.Response: + return self.proxy.request( + "POST", + path, + { + "model": model, + "max_tokens": 16, + "stream": True, + "messages": [{"role": "user", "content": marker}], + **extra, + }, + headers={"anthropic-version": "2023-06-01"}, + ) + + def count_tokens(self, model: str, prefix: str = "") -> httpx.Response: + return self.proxy.request( + "POST", + prefix + _COUNT_TOKENS_TARGET, + {"model": model, "messages": [{"role": "user", "content": "count me"}]}, + headers={"anthropic-version": "2023-06-01"}, + ) + + def targets_called(self) -> tuple[str, ...]: + return tuple(unquote(request.target) for request in self.wire.drain()) + + def backends_called(self) -> tuple[str, ...]: + return tuple(str(object_value(json.loads(request.body))["model"]) for request in self.wire.drain()) + + +@pytest.fixture(scope="module") +def rig(tmp_path_factory: pytest.TempPathFactory) -> Iterator[_Rig]: + directory: Final = tmp_path_factory.mktemp("anthropic-overloaded-cooldown") + with gateway_from_environment() as gateway, wire_server(_respond) as wire: + overrides: Final = {"ANTHROPIC_API_BASE": wire.url, "ANTHROPIC_API_KEY": _API_KEY} + with owned_proxy(gateway, directory, overrides, config=_config(wire, directory), workers=2) as proxy: + yield _Rig(proxy, wire) + + +@pytest.fixture(autouse=True) +def _fresh_wire(rig: _Rig) -> None: + rig.wire.drain() + + +def _assert_overloaded_json(response: httpx.Response) -> None: + assert response.status_code == 529, response.text + payload: Final = object_value(json.loads(response.content)) + assert object_value(payload["error"])["type"] == "overloaded_error", response.text + + +def _count_tokens_error(response: httpx.Response, status: int) -> dict[str, JsonValue]: + assert response.status_code == status, response.text + envelope: Final = object_value(json.loads(response.content)) + assert envelope["type"] == "error", response.text + return object_value(envelope["error"]) + + +def test_an_overloaded_deployment_is_cooled_down_by_the_internal_server_error_allowed_fails_policy(rig: _Rig) -> None: + marker: Final = uuid.uuid4().hex + first: Final = rig.messages("/v1/messages", _COOLDOWN_GROUP, marker, num_retries=0, disable_fallbacks=True) + _assert_overloaded_json(first) + assert rig.backends_called() == (_OVERLOADED,) + second: Final = rig.messages("/v1/messages", _COOLDOWN_GROUP, marker, num_retries=0, disable_fallbacks=True) + assert second.status_code == 200, second.text + events: Final = parse_sse(second.text) + assert event_types(events) == LIFECYCLE, events + assert message_id(events) == _served_id(marker), events + assert rig.backends_called() == (_HEALTHY,) + + +def test_count_tokens_disabled_without_a_provider_counter_answers_503_api_error(rig: _Rig) -> None: + response: Final = rig.count_tokens(_COUNT_DISABLED_GROUP) + error: Final = _count_tokens_error(response, 503) + assert error["type"] == "api_error", response.text + assert "Token counting is disabled" in string_value(error["message"]), response.text + assert rig.targets_called() == () + + +def test_count_tokens_whose_upstream_answers_503_stays_503_api_error(rig: _Rig) -> None: + response: Final = rig.count_tokens(_COUNT_UPSTREAM_GROUP) + error: Final = _count_tokens_error(response, 503) + assert error["type"] == "api_error", response.text + assert "scripted 503" in string_value(error["message"]), response.text + assert rig.targets_called() == (_COUNT_TOKENS_TARGET,) +@pytest.mark.parametrize( + ("group", "status", "error_type"), + ( + pytest.param(_COUNT_OVERLOADED_GROUP, 529, "overloaded_error", id="529"), + pytest.param(_COUNT_RATE_LIMITED_GROUP, 429, "rate_limit_error", id="429"), + ), +) +def test_count_tokens_keeps_other_upstream_statuses_and_their_error_body( + rig: _Rig, group: str, status: int, error_type: str +) -> None: + response: Final = rig.count_tokens(group) + error: Final = _count_tokens_error(response, status) + assert error["type"] == error_type, response.text + assert f"scripted {status}" in string_value(error["message"]), response.text + assert rig.targets_called() == (_COUNT_TOKENS_TARGET,) + + +def test_pass_through_messages_stream_forwards_an_upstream_529_verbatim(rig: _Rig) -> None: + response: Final = rig.messages("/anthropic/v1/messages", _OVERLOADED, uuid.uuid4().hex) + assert response.status_code == 529, response.text + assert response.content == error_body(529, "scripted 529"), response.text + assert rig.backends_called() == (_OVERLOADED,) + + +@pytest.mark.parametrize("shape", _GATEWAY_GROUPS.keys()) +def test_the_claude_code_gateway_messages_route_answers_an_upstream_529_as_overloaded_error( + rig: _Rig, shape: str +) -> None: + response: Final = rig.messages( + f"{_GATEWAY}/v1/messages", + _GATEWAY_GROUPS[shape], + uuid.uuid4().hex, + stream=shape == "stream", + num_retries=0, + ) + _assert_overloaded_json(response) + assert rig.backends_called() == (_OVERLOADED,) + + +def test_the_claude_code_gateway_count_tokens_route_answers_an_upstream_503_as_503(rig: _Rig) -> None: + response: Final = rig.count_tokens(_COUNT_UPSTREAM_GROUP, prefix=_GATEWAY) + error: Final = _count_tokens_error(response, 503) + assert error["type"] == "api_error", response.text + assert "scripted 503" in string_value(error["message"]), response.text + assert rig.targets_called() == (_COUNT_TOKENS_TARGET,) diff --git a/tests/integration/routing/test_fallback_hop_foreign_encrypted_reasoning.py b/tests/integration/routing/test_fallback_hop_foreign_encrypted_reasoning.py index e6ec3444369..ef2a9e5b72f 100644 --- a/tests/integration/routing/test_fallback_hop_foreign_encrypted_reasoning.py +++ b/tests/integration/routing/test_fallback_hop_foreign_encrypted_reasoning.py @@ -303,7 +303,7 @@ def scenario_api_base(scenario: Scenario, scenario_id: str, response: StoredResp def deployment( scenario: Scenario, group: str, - api_base: str, + api_base: str | None, *, order: int | None, model: str = RESPONSES_MODEL, @@ -316,7 +316,7 @@ def deployment( "litellm_params": { "model": model, "api_key": PROVIDER_KEY, - "api_base": api_base, + **({} if api_base is None else {"api_base": api_base}), **({} if order is None else {"order": order}), **extra_params, }, @@ -863,6 +863,38 @@ def test_hop_inside_one_encryption_boundary_keeps_the_reasoning(gateway: Gateway assert [body.get("input") for body in bodies] == [history(mark), history(mark)], bodies +def test_hop_between_same_key_deployments_on_the_providers_default_endpoint_keeps_the_reasoning( + gateway: Gateway, tmp_path: Path +) -> None: + shared: Final = f"default-{uuid.uuid4().hex[:12]}" + with ( + scratch_database() as database, + owned_proxy_process( + gateway, + tmp_path, + {"DATABASE_URL": database, "OPENAI_BASE_URL": f"{gateway.upstream_url}/{shared}"}, + remove_environment=("DIRECT_URL", "DATABASE_URL_READ_REPLICA", "OPENAI_API_BASE"), + ) as owned, + owned.gateway.scenario() as scenario, + ): + owned.gateway.post("/config/update", {"router_settings": {"num_retries": 0}}) + one: Final = scenario_api_base(scenario, f"{shared}-o1", failing()).rsplit("/", 1)[-1] + two: Final = scenario_api_base(scenario, f"{shared}-o2", healthy_json()).rsplit("/", 1)[-1] + order_one: Final = deployment( + scenario, shared, None, order=1, extra_params={"extra_headers": {"x-scripted-scenario": one}} + ) + order_two: Final = deployment( + scenario, shared, None, order=2, extra_params={"extra_headers": {"x-scripted-scenario": two}} + ) + mark: Final = marker() + answer: Final = responses_answer( + owned.gateway, HTTPX, Target(shared, frozenset({order_one, order_two})), history(mark) + ) + assert_served_by(answer, order_two) + bodies: Final = bodies_for(observed(owned.gateway), shared) + assert [body.get("input") for body in bodies] == [history(mark), history(mark)], bodies + + def assert_cross_group_hop_stripped(gateway: Gateway, source_scenario: str, target_scenario: str, mark: str) -> None: records: Final = observed(gateway) assert [body.get("input") for body in bodies_for(records, source_scenario)] == [history(mark)], records diff --git a/tests/integration/routing/test_least_busy_concurrent_decisions.py b/tests/integration/routing/test_least_busy_concurrent_decisions.py new file mode 100644 index 00000000000..bb923534db4 --- /dev/null +++ b/tests/integration/routing/test_least_busy_concurrent_decisions.py @@ -0,0 +1,90 @@ +import json +import threading +from collections import Counter +from collections.abc import Callable +from concurrent.futures import ThreadPoolExecutor +from pathlib import Path +from typing import Final + +import httpx +import pytest +import yaml +from integration._support.client import Gateway, gateway_from_environment +from integration._support.process import owned_proxy +from integration._support.wire import Reply, Request, wire_server + +pytestmark = pytest.mark.timeout(240) + +_GROUP: Final = "least-busy-decider" +_DEPLOYMENTS: Final = ("least-busy-decider-a", "least-busy-decider-b") +_BURST: Final = 4 +_REPLY: Final = json.dumps( + { + "model": "Qwen/Qwen3-0.6B", + "answers": {"billing": {"type": "noul", "noul": 0.91}}, + "usage": {"input_tokens": 367, "output_tokens": 3}, + } +).encode() +_DECISION: Final = { + "model": _GROUP, + "input": "I was charged twice for order 4417.", + "questions": [{"type": "predicate", "name": "billing", "instructions": "Is this a billing issue?"}], +} + + +def _held_until_the_burst_arrives(arrived: threading.Barrier) -> Callable[[Request], Reply]: + def respond(request: Request) -> Reply: + arrived.wait() + return Reply(body=_REPLY) + + return respond + + +def _write_config(path: Path, provider_url: str) -> Path: + path.write_text( + yaml.safe_dump( + { + "model_list": [ + { + "model_name": _GROUP, + "litellm_params": {"model": "hosted_vllm/Qwen/Qwen3-0.6B", "api_base": provider_url}, + "model_info": {"id": deployment_id}, + } + for deployment_id in _DEPLOYMENTS + ], + "general_settings": { + "master_key": "os.environ/LITELLM_MASTER_KEY", + "database_url": "os.environ/DATABASE_URL", + "disable_model_info_refresh": True, + }, + "router_settings": {"routing_strategy": "least-busy", "num_retries": 0, "disable_cooldowns": True}, + } + ) + ) + return path + + +def _decide(proxy: Gateway) -> httpx.Response: + return proxy.client.post( + "/v1/decisions", json=_DECISION, headers={"Authorization": f"Bearer {proxy.key}"}, timeout=120 + ) + + +def test_least_busy_spreads_a_burst_of_decisions_calls_across_the_group(tmp_path: Path) -> None: + arrived: Final = threading.Barrier(_BURST, timeout=60) + with ( + wire_server(_held_until_the_burst_arrives(arrived)) as upstream, + gateway_from_environment() as rig, + owned_proxy( + rig, + tmp_path, + {"STORE_MODEL_IN_DB": "False"}, + config=_write_config(tmp_path / "least-busy.yaml", upstream.url), + ) as proxy, + ThreadPoolExecutor(max_workers=_BURST) as pool, + ): + responses: Final = tuple(pool.map(lambda _: _decide(proxy), range(_BURST))) + assert [response.status_code for response in responses] == [200] * _BURST, [r.text for r in responses] + assert Counter(response.headers["x-litellm-model-id"] for response in responses) == Counter( + {deployment_id: _BURST // len(_DEPLOYMENTS) for deployment_id in _DEPLOYMENTS} + ) diff --git a/tests/integration/routing/test_messages_stream_retry_budget_sources_owned_proxy.py b/tests/integration/routing/test_messages_stream_retry_budget_sources_owned_proxy.py index 0257b8372b0..e0900bc0926 100644 --- a/tests/integration/routing/test_messages_stream_retry_budget_sources_owned_proxy.py +++ b/tests/integration/routing/test_messages_stream_retry_budget_sources_owned_proxy.py @@ -45,10 +45,19 @@ _FALLBACK_GROUP: Final = "audit-fallback" _CW_FALLBACK_GROUP: Final = "audit-cw-fallback" _LONELY: Final = "audit-lonely" _POLICY: Final = "audit-policy" +_SERVICE_UNAVAILABLE_RETRY_POLICY: Final = "audit-service-unavailable-retry-policy" +_INTERNAL_RETRY_POLICY: Final = "audit-internal-retry-policy" _UPSTREAM_URL_PLACEHOLDER: Final = "upstream-url" Behavior = Literal[ - "drop-once", "drop-always", "hold-ping", "drop-then-too-long", "drop-then-401", "overloaded-frames-fallback-503" + "drop-once", + "drop-always", + "hold-ping", + "drop-then-too-long", + "drop-then-401", + "overloaded-frames-fallback-529", + "overloaded-frames", + "overloaded-once", ] pytestmark = pytest.mark.timeout(240) @@ -81,13 +90,15 @@ def _primary_reply( return Reply(status=400, body=error_body(400, "prompt is too long: 250000 tokens > 200000 maximum")) case "drop-then-401": return dropped if attempt == 1 else status_reply(401) - case "overloaded-frames-fallback-503": + case "overloaded-frames-fallback-529" | "overloaded-frames": return stream_reply((error_frame(529, "scripted overloaded"),)) + case "overloaded-once": + return status_reply(529) if attempt == 1 else stream_reply(full) raise AssertionError(behavior) def _fallback_reply(behavior: str, full: tuple[bytes, bytes, bytes, bytes]) -> Reply: - if behavior == "overloaded-frames-fallback-503": + if behavior == "overloaded-frames-fallback-529": return status_reply(503) return stream_reply(full) @@ -141,13 +152,19 @@ def _config(wire: Wire, directory: Path) -> Path: _deployment(_CW_FALLBACK_GROUP, _CONTEXT_WINDOW), _deployment(_LONELY, _PRIMARY, num_retries=1), _deployment(_POLICY, _PRIMARY), + _deployment(_SERVICE_UNAVAILABLE_RETRY_POLICY, _PRIMARY), + _deployment(_INTERNAL_RETRY_POLICY, _PRIMARY), ] config["router_settings"] = { "num_retries": 1, "disable_cooldowns": True, "fallbacks": [{_WITH_FALLBACKS: [_FALLBACK_GROUP]}], "context_window_fallbacks": [{_WITH_FALLBACKS: [_CW_FALLBACK_GROUP]}], - "model_group_retry_policy": {_POLICY: {"DefaultRetries": 2}}, + "model_group_retry_policy": { + _POLICY: {"DefaultRetries": 2}, + _SERVICE_UNAVAILABLE_RETRY_POLICY: {"ServiceUnavailableErrorRetries": 1, "InternalServerErrorRetries": 0}, + _INTERNAL_RETRY_POLICY: {"InternalServerErrorRetries": 1, "ServiceUnavailableErrorRetries": 0}, + }, } path: Final = directory / "messages-retry-budget-sources.yaml" path.write_text(yaml.safe_dump(config).replace(_UPSTREAM_URL_PLACEHOLDER, wire.url)) @@ -290,10 +307,34 @@ def test_a_retry_rejected_with_401_ends_the_retries_and_reaches_the_client_uncha assert rig.attempts_on(_PRIMARY, marker) == 2 -def test_overloaded_frames_whose_fallback_fails_answer_the_mapped_internal_server_error(rig: _Rig) -> None: +def test_overloaded_frames_whose_fallback_fails_answer_529_overloaded_error(rig: _Rig) -> None: marker: Final = uuid.uuid4().hex - response: Final = rig.stream(_WITH_FALLBACKS, "overloaded-frames-fallback-503", marker) - assert response.status_code == 500, response.text + response: Final = rig.stream(_WITH_FALLBACKS, "overloaded-frames-fallback-529", marker) + assert response.status_code == 529, response.text + assert "overloaded_error" in response.text, response.text assert "content_block_delta" not in response.text, response.text assert rig.attempts_on(_PRIMARY, marker) == 2 assert rig.attempts_on(_FALLBACK, marker) == 2 + + +def test_overloaded_frames_that_spend_the_budget_without_a_fallback_relay_the_last_attempts_frame(rig: _Rig) -> None: + marker: Final = uuid.uuid4().hex + response: Final = rig.stream(_LONELY, "overloaded-frames", marker) + assert response.status_code == 200, response.text + assert response.text == error_frame(529, "scripted overloaded").decode(), response.text + assert rig.attempts_on(_PRIMARY, marker) == 2 + + +def test_a_529_is_retried_under_the_internal_server_error_retry_policy(rig: _Rig) -> None: + marker: Final = uuid.uuid4().hex + _assert_completed(rig.stream(_INTERNAL_RETRY_POLICY, "overloaded-once", marker), _served_id(_PRIMARY, marker, 2)) + assert rig.attempts_on(_PRIMARY, marker) == 2 + + +def test_a_529_is_not_retried_under_the_service_unavailable_error_retry_policy(rig: _Rig) -> None: + marker: Final = uuid.uuid4().hex + response: Final = rig.stream(_SERVICE_UNAVAILABLE_RETRY_POLICY, "overloaded-once", marker) + assert response.status_code == 529, response.text + assert "overloaded_error" in response.text, response.text + assert "content_block_delta" not in response.text, response.text + assert rig.attempts_on(_PRIMARY, marker) == 1 diff --git a/tests/integration/routing/test_prompt_cache_pin_ttl.py b/tests/integration/routing/test_prompt_cache_pin_ttl.py index f6ee96a9206..733f7859ff0 100644 --- a/tests/integration/routing/test_prompt_cache_pin_ttl.py +++ b/tests/integration/routing/test_prompt_cache_pin_ttl.py @@ -9,7 +9,7 @@ from typing import Final import anthropic import openai import pytest -from integration._support.client import eventually, gateway_from_environment, held +from integration._support.client import eventually, gateway_from_environment, held, object_value from integration._support.process import OwnedProxy, graceful_stop_seconds, owned_proxy_process from integration._support.redis_process import owned_redis from integration._support.wire import Wire, wire_server @@ -56,11 +56,12 @@ from integration.routing._prompt_cache_pin_support import ( vertex_peer, wire_carries_one_hour, ) -from pydantic import JsonValue +from pydantic import JsonValue, TypeAdapter from redis import Redis pytestmark: Final = [pytest.mark.timeout(2 * graceful_stop_seconds() + 300), pytest.mark.shares_worker_state] +_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) _CLAUDE: Final = "pin-claude" _SLOW: Final = "pin-slow" _MIXED: Final = "pin-mixed" @@ -539,7 +540,10 @@ def test_failed_first_turn_reports_the_error_and_writes_no_pin(rig: _Rig) -> Non "/v1/chat/completions", chat_body(_CLAUDE, _first_turn(new_marker(), f"{new_marker()} {OVERLOAD_TOKEN}", ONE_HOUR_MARK)), ) - assert response.status_code == 500, response.text + assert response.status_code == 503, response.text + error: Final = object_value(_JSON_OBJECT.validate_json(response.text)["error"]) + assert error["type"] == "service_unavailable_error", response.text + assert error["code"] == "server_is_overloaded", response.text assert "overloaded_error" in response.text, response.text healthy, _ = post_chat(rig.owned.gateway, chat_body(_CLAUDE, _first_turn(new_marker(), new_marker(), None))) spend_row_lands(healthy) diff --git a/tests/integration/routing/test_reasoning_effort_levels_wire.py b/tests/integration/routing/test_reasoning_effort_levels_wire.py index d15867ac572..efca26d38d0 100644 --- a/tests/integration/routing/test_reasoning_effort_levels_wire.py +++ b/tests/integration/routing/test_reasoning_effort_levels_wire.py @@ -1977,6 +1977,9 @@ _INVOKE_NATIVE_OUTPUT: Final[dict[str, JsonValue]] = { "format": {"type": "json_schema", "schema": _NATIVE_OUTPUT_SCHEMA}, } _JSON_TOOL: Final = "json_tool_call" +_UNFORCED_JSON_TOOL_DESCRIPTION: Final = ( + "When you are ready to answer, call this tool with your final answer as its input. Do not reply in plain text." +) _CONVERSE_TOOL_SCHEMA: Final[dict[str, JsonValue]] = { key: value for key, value in _NATIVE_OUTPUT_SCHEMA.items() if key != "additionalProperties" } @@ -1994,7 +1997,7 @@ _CONVERSE_WITH_JSON_TOOL: Final = _with_fields( { "toolSpec": { "name": _JSON_TOOL, - "description": _JSON_TOOL, + "description": _UNFORCED_JSON_TOOL_DESCRIPTION, "inputSchema": {"json": _CONVERSE_TOOL_SCHEMA}, } } @@ -2004,7 +2007,15 @@ _CONVERSE_WITH_JSON_TOOL: Final = _with_fields( ) _INVOKE_WITH_JSON_TOOL: Final = _with_fields( _without(_invoke_chat("high", _ADAPTIVE, ()), "anthropic_beta"), - {"tools": [{"name": _JSON_TOOL, "input_schema": _NATIVE_OUTPUT_SCHEMA}]}, + { + "tools": [ + { + "name": _JSON_TOOL, + "description": _UNFORCED_JSON_TOOL_DESCRIPTION, + "input_schema": _NATIVE_OUTPUT_SCHEMA, + } + ] + }, ) diff --git a/tests/integration/sdk/test_anthropic_json_tool_cut_stream_sync_sdk.py b/tests/integration/sdk/test_anthropic_json_tool_cut_stream_sync_sdk.py index da091b1c12e..294791128ab 100644 --- a/tests/integration/sdk/test_anthropic_json_tool_cut_stream_sync_sdk.py +++ b/tests/integration/sdk/test_anthropic_json_tool_cut_stream_sync_sdk.py @@ -10,6 +10,7 @@ from integration._support.wire import Reply, Request, wire_server from pydantic import JsonValue import litellm +from litellm.exceptions import MidStreamFallbackError from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper _JSON_TOOL: Final = "json_tool_call" @@ -26,7 +27,7 @@ _RESPONSE_FORMAT: Final[dict[str, JsonValue]] = { "json_schema": {"name": "risk", "schema": _SCHEMA}, } _ANTHROPIC_MODEL: Final = "anthropic/claude-scripted-9" -_BEDROCK_INVOKE_MODEL: Final = "bedrock/invoke/anthropic.claude-sonnet-5" +_BEDROCK_INVOKE_MODEL: Final = "bedrock/invoke/anthropic.claude-opus-4-8" def _payload(marker_hex: str) -> dict[str, JsonValue]: @@ -122,12 +123,10 @@ def _credentials(model: str) -> dict[str, str]: @pytest.mark.parametrize("model", [_ANTHROPIC_MODEL, _BEDROCK_INVOKE_MODEL], ids=["anthropic", "bedrock_invoke"]) @pytest.mark.parametrize( ("shape", "cut"), - [("plain", False), ("plain", True), ("wrapped", True)], - ids=["plain_complete", "plain_cut", "wrapped_cut"], + [("plain", False), ("wrapped", False), ("plain", True), ("wrapped", True)], + ids=["plain_complete", "wrapped_complete", "plain_cut", "wrapped_cut"], ) -def test_sync_stream_cut_before_the_json_tool_block_closes_still_yields_the_whole_answer( - model: str, shape: str, cut: bool -) -> None: +def test_sync_json_tool_stream_requires_a_provider_finish_reason(model: str, shape: str, cut: bool) -> None: marker_hex: Final = uuid.uuid4().hex with wire_server(_peer(marker_hex, shape, cut)) as wire: response: Final = litellm.completion( @@ -141,6 +140,11 @@ def test_sync_stream_cut_before_the_json_tool_block_closes_still_yields_the_whol **_credentials(model), ) assert isinstance(response, CustomStreamWrapper), type(response) + if cut: + with pytest.raises(MidStreamFallbackError, match="Stream ended before a finish_reason was received"): + tuple(response) + assert len(wire.drain()) == 1 + return text: Final = "".join(str(chunk.choices[0].delta.content or "") for chunk in tuple(response)) assert len(wire.drain()) == 1 assert json.loads(text) == _payload(marker_hex), text diff --git a/tests/integration/sdk/test_openai_realtime_http_ca_bundle_wire.py b/tests/integration/sdk/test_openai_realtime_http_ca_bundle_wire.py new file mode 100644 index 00000000000..358b36cd2b0 --- /dev/null +++ b/tests/integration/sdk/test_openai_realtime_http_ca_bundle_wire.py @@ -0,0 +1,95 @@ +import json +from collections.abc import Awaitable +from datetime import datetime, timezone +from pathlib import Path +from types import MappingProxyType +from typing import Final + +import httpx +import pytest +from integration._support.tls import server_context, write_self_signed_cert +from integration._support.wire import Reply, Request, wire_server + +import litellm +from litellm.litellm_core_utils.litellm_logging import Logging +from litellm.realtime_api import main as realtime_main + +UPSTREAM_PATHS: Final = MappingProxyType( + { + "client_secrets": "/v1/realtime/client_secrets", + "translation_client_secrets": "/v1/realtime/translations/client_secrets", + "calls": "/v1/realtime/calls", + "translation_calls": "/v1/realtime/translations/calls", + } +) + + +def _logging(route: str) -> Logging: + return Logging( + model="gpt-realtime", + messages=[], + stream=False, + call_type="acreate_realtime_client_secret", + start_time=datetime(2026, 1, 1, tzinfo=timezone.utc), + litellm_call_id=f"test-realtime-{route}", + function_id=f"test-realtime-{route}", + ) + + +def _route_call(route: str, api_base: str) -> Awaitable[httpx.Response]: + match route: + case "client_secrets": + return realtime_main.acreate_realtime_client_secret.__wrapped__( + model="gpt-realtime", + custom_llm_provider="openai", + api_key="sk-test", + api_base=api_base, + litellm_logging_obj=_logging(route), + ) + case "translation_client_secrets": + return realtime_main.acreate_realtime_translation_client_secret.__wrapped__( + model="gpt-realtime-translate", + custom_llm_provider="openai", + api_key="sk-test", + api_base=api_base, + litellm_logging_obj=_logging(route), + ) + case "calls": + return realtime_main.arealtime_calls.__wrapped__( + openai_ephemeral_key="ek_test", + sdp_body=b"v=0", + model="gpt-realtime", + custom_llm_provider="openai", + api_base=api_base, + litellm_logging_obj=_logging(route), + ) + case _: + return realtime_main.arealtime_translation_calls.__wrapped__( + openai_ephemeral_key="ek_test", + sdp_body=b"v=0", + model="gpt-realtime-translate", + custom_llm_provider="openai", + api_base=api_base, + litellm_logging_obj=_logging(route), + ) + + +def _ephemeral_key(_: Request) -> Reply: + return Reply(body=json.dumps({"value": "ek_test"}).encode()) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("route", tuple(UPSTREAM_PATHS)) +async def test_openai_realtime_http_routes_trust_the_ca_bundle_set_in_litellm_ssl_verify( + route: str, tmp_path: Path, monkeypatch: pytest.MonkeyPatch +) -> None: + certificate, key = write_self_signed_cert(tmp_path) + monkeypatch.setattr(litellm, "ssl_verify", str(certificate)) + + with wire_server(_ephemeral_key, tls=server_context(certificate, key)) as upstream: + response: Final = await _route_call(route, upstream.url) + targets: Final = tuple(request.target for request in upstream.drain()) + + assert response.status_code == 200 + assert response.json() == {"value": "ek_test"} + assert targets == (UPSTREAM_PATHS[route],) diff --git a/tests/integration/security/test_files_batches_access.py b/tests/integration/security/test_files_batches_access.py index 119055c64c7..93ccc742d58 100644 --- a/tests/integration/security/test_files_batches_access.py +++ b/tests/integration/security/test_files_batches_access.py @@ -25,7 +25,7 @@ from cryptography.hazmat.primitives import serialization from cryptography.hazmat.primitives.asymmetric import rsa from integration._support.client import Gateway, Scenario, eventually, object_value, string_value from integration._support.database import read_rows -from integration._support.process import owned_proxy +from integration._support.process import OwnedState, owned_proxy from integration._support.tls import server_context, write_self_signed_cert from integration._support.wire import Reply, Request, Wire, wire_server from openai import OpenAI, PermissionDeniedError @@ -250,15 +250,20 @@ def test_stranger_cannot_read_download_or_delete_another_teams_managed_file(gate assert _drained_other_than_model_list_probes(wire) == () -def test_stranger_cannot_retrieve_or_cancel_another_teams_managed_batch(gateway: Gateway) -> None: +@pytest.mark.timeout(180) +def test_stranger_cannot_retrieve_or_cancel_another_teams_managed_batch(gateway: Gateway, tmp_path: Path) -> None: key: Final = "provider-key-" + uuid.uuid4().hex[:8] - with wire_server(_openai_backend()) as wire, gateway.scenario() as scenario: + with ( + owned_proxy(gateway, tmp_path, {"PROXY_BATCH_POLLING_ENABLED": "false"}, state=OwnedState.PRIVATE) as candidate, + wire_server(_openai_backend()) as wire, + candidate.scenario() as scenario, + ): model: Final = scenario.model(model="openai/gpt-4o-mini", api_base=wire.url + "/v1", api_key=key) - _wait_until_every_worker_serves(gateway, model) + _wait_until_every_worker_serves(candidate, model) owner: Final = _member(scenario, model) stranger: Final = _member(scenario, model) - uploaded: Final = gateway.request_multipart( + uploaded: Final = candidate.request_multipart( "/v1/files", {"purpose": "batch", "target_model_names": model}, {"file": (INPUT_FILENAME, _jsonl(model), "application/jsonl")}, @@ -266,7 +271,7 @@ def test_stranger_cannot_retrieve_or_cancel_another_teams_managed_batch(gateway: ) assert uploaded.status_code == 200, uploaded.text managed_input: Final = string_value(_json(uploaded)["id"]) - created: Final = gateway.request( + created: Final = candidate.request( "POST", "/v1/batches", {"input_file_id": managed_input, "endpoint": "/v1/chat/completions", "completion_window": "24h"}, @@ -277,13 +282,13 @@ def test_stranger_cannot_retrieve_or_cancel_another_teams_managed_batch(gateway: wire.drain() expected_message: Final = f"User {stranger.user} does not have access to the object {unified_batch}" - stranger_get: Final = gateway.request("GET", f"/v1/batches/{unified_batch}", key=stranger.key) + stranger_get: Final = candidate.request("GET", f"/v1/batches/{unified_batch}", key=stranger.key) assert _error_message(stranger_get, 403) == expected_message, stranger_get.text - stranger_cancel: Final = gateway.request("POST", f"/v1/batches/{unified_batch}/cancel", {}, key=stranger.key) + stranger_cancel: Final = candidate.request("POST", f"/v1/batches/{unified_batch}/cancel", {}, key=stranger.key) assert _error_message(stranger_cancel, 403) == expected_message, stranger_cancel.text assert _drained_other_than_model_list_probes(wire) == (), "stranger batch calls must not reach the provider" - owner_cancel: Final = gateway.request("POST", f"/v1/batches/{unified_batch}/cancel", {}, key=owner.key) + owner_cancel: Final = candidate.request("POST", f"/v1/batches/{unified_batch}/cancel", {}, key=owner.key) assert owner_cancel.status_code == 200, owner_cancel.text assert string_value(_json(owner_cancel)["id"]) == unified_batch, owner_cancel.text (cancel_request,) = _drained_other_than_model_list_probes(wire) diff --git a/tests/integration/security/test_skill_scanner.py b/tests/integration/security/test_skill_scanner.py new file mode 100644 index 00000000000..e18378463ee --- /dev/null +++ b/tests/integration/security/test_skill_scanner.py @@ -0,0 +1,58 @@ +import asyncio +import sys +from datetime import datetime, timedelta, timezone +from pathlib import Path +from typing import Final + +import psutil +import pytest +from fastapi import HTTPException + +from cookbook.skill_scanner import server +from tests.integration._support.process import _wait_until_gone, group_members, stop_processes + + +@pytest.mark.parametrize("mode", ("deadline", "cap", "complete")) +async def test_adapter_bounds_worker_lifetime_and_reaps_its_process_group( + monkeypatch: pytest.MonkeyPatch, tmp_path: Path, mode: str, +) -> None: + script: Final = ( + "import subprocess, sys, time\n" + "child = subprocess.Popen([sys.executable, '-c', 'import time; time.sleep(30)'], " + "stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)\n" + "print(child.pid, flush=True)\n" + + ("pass\n" if mode == "complete" else "time.sleep(30)\n") + ) + child: Final = await asyncio.create_subprocess_exec( + sys.executable, "-c", script, stdout=asyncio.subprocess.PIPE, + stderr=asyncio.subprocess.DEVNULL, start_new_session=True, + ) + try: + assert child.stdout is not None + descendant: Final = psutil.Process(int(await asyncio.wait_for(child.stdout.readline(), 5))) + if mode == "complete": + await asyncio.wait_for(child.wait(), 5) + output: Final = tmp_path / "report.json" + output.write_text('{"complete": true}') + + async def launch(*args: object, **kwargs: object) -> asyncio.subprocess.Process: + return child + + monkeypatch.setattr(server.asyncio, "create_subprocess_exec", launch) + monkeypatch.setattr(server, "SCAN_TIMEOUT", 0.05 if mode == "cap" else 30) + deadline: Final = ( + None if mode == "cap" + else datetime.now(timezone.utc) + timedelta(seconds=0.05 if mode == "deadline" else 30) + ) + result: Final = server.run_worker("unused.zip", output, False, deadline) + if mode == "complete": + assert await asyncio.wait_for(result, 5) == {"complete": True} + else: + with pytest.raises(HTTPException) as raised: + await asyncio.wait_for(result, 5) + assert raised.value.status_code == 504 + assert child.returncode is not None + _wait_until_gone(descendant, 3) + finally: + await asyncio.to_thread(stop_processes, group_members(child.pid), 0.1) + await child.wait() diff --git a/tests/integration/spend/golden/daily_activity_user_aggregated.json b/tests/integration/spend/golden/daily_activity_user_aggregated.json index 185d333965a..3189c000035 100644 --- a/tests/integration/spend/golden/daily_activity_user_aggregated.json +++ b/tests/integration/spend/golden/daily_activity_user_aggregated.json @@ -1,5 +1,5 @@ { - "metadata": {"entity_total_api_keys":null, + "metadata": {"entity_total_api_keys":{"user-1": 5}, "api_key_limit": 100, "has_more": false, "page": 1, @@ -346,7 +346,181 @@ } } }, - "entities": {}, + "entities": { + "user-1": { + "api_key_breakdown": { + "key-a": { + "metadata": { + "key_alias": "alias-a", + "key_exists": true, + "team_id": "team-1", + "user_email": "user@example.com", + "user_id": "user-1" + }, + "metrics": { + "api_requests": 1, + "autorouter_savings_spend": 0.0, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 1, + "completion_tokens": 2, + "compression_saved_tokens": 0, + "compression_savings_spend": 0.0, + "failed_requests": 0, + "flat_cost": 0.0, + "ptu_hours": 0.0, + "gateway_injected_caching_savings_spend": 0.0, + "prompt_caching_savings_spend": 0.0, + "prompt_tokens": 2, + "spend": 100.0, + "successful_requests": 1, + "timed_requests": 0, + "total_response_time_ms": 0, + "total_tokens": 4 + } + }, + "key-b": { + "metadata": { + "key_alias": "alias-b", + "key_exists": true, + "team_id": "team-1", + "user_email": "user@example.com", + "user_id": "user-1" + }, + "metrics": { + "api_requests": 1, + "autorouter_savings_spend": 0.0, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 1, + "completion_tokens": 2, + "compression_saved_tokens": 0, + "compression_savings_spend": 0.0, + "failed_requests": 0, + "flat_cost": 0.0, + "ptu_hours": 0.0, + "gateway_injected_caching_savings_spend": 0.0, + "prompt_caching_savings_spend": 0.0, + "prompt_tokens": 3, + "spend": 90.0, + "successful_requests": 1, + "timed_requests": 0, + "total_response_time_ms": 0, + "total_tokens": 5 + } + }, + "key-c": { + "metadata": { + "key_alias": "alias-c", + "key_exists": true, + "team_id": "team-1", + "user_email": "user@example.com", + "user_id": "user-1" + }, + "metrics": { + "api_requests": 1, + "autorouter_savings_spend": 0.0, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 1, + "completion_tokens": 2, + "compression_saved_tokens": 0, + "compression_savings_spend": 0.0, + "failed_requests": 0, + "flat_cost": 0.0, + "ptu_hours": 0.0, + "gateway_injected_caching_savings_spend": 0.0, + "prompt_caching_savings_spend": 0.0, + "prompt_tokens": 4, + "spend": 80.0, + "successful_requests": 1, + "timed_requests": 0, + "total_response_time_ms": 0, + "total_tokens": 6 + } + }, + "key-cache": { + "metadata": { + "key_alias": "alias-cache", + "key_exists": true, + "team_id": "team-1", + "user_email": "user@example.com", + "user_id": "user-1" + }, + "metrics": { + "api_requests": 1, + "autorouter_savings_spend": 0.0, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 1, + "completion_tokens": 2, + "compression_saved_tokens": 0, + "compression_savings_spend": 0.0, + "failed_requests": 0, + "flat_cost": 0.0, + "ptu_hours": 0.0, + "gateway_injected_caching_savings_spend": 0.0, + "prompt_caching_savings_spend": 0.0, + "prompt_tokens": 1000, + "spend": 2.0, + "successful_requests": 1, + "timed_requests": 0, + "total_response_time_ms": 0, + "total_tokens": 1002 + } + }, + "key-target": { + "metadata": { + "key_alias": "deleted-target", + "key_exists": false, + "team_id": "team-1", + "user_email": "user@example.com", + "user_id": "user-1" + }, + "metrics": { + "api_requests": 1, + "autorouter_savings_spend": 0.0, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 2, + "completion_tokens": 2, + "compression_saved_tokens": 0, + "compression_savings_spend": 0.0, + "failed_requests": 0, + "flat_cost": 0.0, + "ptu_hours": 0.0, + "gateway_injected_caching_savings_spend": 0.0, + "prompt_caching_savings_spend": 0.0, + "prompt_tokens": 5, + "spend": 1.0, + "successful_requests": 1, + "timed_requests": 0, + "total_response_time_ms": 0, + "total_tokens": 7 + } + } + }, + "metadata": { + "user_alias": null, + "user_email": "user@example.com" + }, + "metrics": { + "api_requests": 5, + "autorouter_savings_spend": 0.0, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 6, + "completion_tokens": 10, + "compression_saved_tokens": 0, + "compression_savings_spend": 0.0, + "failed_requests": 0, + "flat_cost": 0.0, + "ptu_hours": 0.0, + "gateway_injected_caching_savings_spend": 0.0, + "prompt_caching_savings_spend": 0.0, + "prompt_tokens": 1014, + "spend": 1273.0, + "successful_requests": 5, + "timed_requests": 0, + "total_response_time_ms": 0, + "total_tokens": 1024 + } + } + }, "mcp_servers": {}, "model_groups": { "model-cache": { diff --git a/tests/integration/spend/test_baggage_tag_mappings.py b/tests/integration/spend/test_baggage_tag_mappings.py index e08348a074c..af68d7b242b 100644 --- a/tests/integration/spend/test_baggage_tag_mappings.py +++ b/tests/integration/spend/test_baggage_tag_mappings.py @@ -61,10 +61,10 @@ class Rig: @property def exact_tag(self) -> str: - return f"usecase-a-{self.marker}" + return f"app-a-{self.marker}" - def usecase_tag(self, value: str) -> str: - return f"usecase-{self.marker}:{value}" + def app_tag(self, value: str) -> str: + return f"app-{self.marker}:{value}" def tenant_tag(self, value: str) -> str: return f"tenant-{self.marker}:{value}" @@ -195,7 +195,7 @@ def _routed_deployment(marker: str, provider: Wire, name: str, tag: str) -> dict def _mapped_models(marker: str, provider: Wire, upstream_url: str) -> list[JsonValue]: routed: Final = ( - _routed_deployment(marker, provider, "tagged", f"usecase-a-{marker}"), + _routed_deployment(marker, provider, "tagged", f"app-a-{marker}"), _routed_deployment(marker, provider, "default", "default"), ) realtime: Final[dict[str, JsonValue]] = { @@ -221,8 +221,8 @@ def _mapped_models(marker: str, provider: Wire, upstream_url: str) -> list[JsonV def _mapped_rules(marker: str, *, tenant_required: bool) -> list[JsonValue]: return [ - {"key": "entrypoint", "value": "a", "tag": f"usecase-a-{marker}"}, - {"key": "entrypoint", "tag_prefix": f"usecase-{marker}:"}, + {"key": "service", "value": "a", "tag": f"app-a-{marker}"}, + {"key": "service", "tag_prefix": f"app-{marker}:"}, {"key": "tenant", "tag_prefix": f"tenant-{marker}:", "required": tenant_required}, {"key": "budgeted", "tag_prefix": f"budgeted-{marker}:", "require_budgeted_tag": True}, {"key": "team+id", "tag_prefix": f"team-{marker}:"}, @@ -403,7 +403,7 @@ def test_mapped_baggage_tags_reach_spend_and_callbacks_but_not_requester_metadat ROUTE_PATHS[route], _inference_body(route, mapped.chat_model, f"baggage {tenant}", caller_tag), key=key, - headers={"baggage": f"entrypoint=a, tenant={tenant}"}, + headers={"baggage": f"service=a, tenant={tenant}"}, ) assert response.status_code == 200, response.text assert len(mapped.provider.drain()) == 1 @@ -423,7 +423,7 @@ def test_json_string_metadata_gains_exactly_the_mapped_tags(optional: Rig) -> No key: Final = scenario.key() optional.provider.drain() plain: Final = _chat(optional, plain_key, None, fields=fields) - response: Final = _chat(optional, key, f"entrypoint=a,tenant={tenant}", fields=fields) + response: Final = _chat(optional, key, f"service=a,tenant={tenant}", fields=fields) assert (plain.status_code, response.status_code) == (200, 200), (plain.text, response.text) assert len(optional.provider.drain()) == 2 assert _spend_tags(optional.proxy, key) == _spend_tags(optional.proxy, plain_key) | mapped_tags @@ -494,7 +494,7 @@ def test_a2a_spend_row_carries_the_mapped_tags(mapped: Rig) -> None: }, }, key=key, - headers={"baggage": f"entrypoint=a,tenant={tenant}"}, + headers={"baggage": f"service=a,tenant={tenant}"}, ) assert sent.status_code == 200, sent.text assert {mapped.exact_tag, mapped.tenant_tag(tenant)} <= _spend_tags(mapped.proxy, key) @@ -514,8 +514,8 @@ def test_spent_mapped_tag_budget_rejects_the_next_request_before_the_provider( mapped: Rig, key_fields: Mapping[str, JsonValue], fields: Mapping[str, JsonValue], headers: Mapping[str, str] ) -> None: entry: Final = uuid.uuid4().hex - tag: Final = mapped.usecase_tag(entry) - baggage: Final = f"entrypoint={entry},tenant={entry}" + tag: Final = mapped.app_tag(entry) + baggage: Final = f"service={entry},tenant={entry}" with mapped.proxy.scenario() as scenario: key: Final = scenario.key(**key_fields) mapped.proxy.post("/tag/new", {"name": tag, "max_budget": 0.0001}) @@ -528,7 +528,7 @@ def test_spent_mapped_tag_budget_rejects_the_next_request_before_the_provider( assert blocked.status_code == 422, blocked.text assert "budget" in blocked.text.lower(), blocked.text assert mapped.provider.drain() == () - other: Final = _chat(mapped, key, f"entrypoint=other-{entry},tenant={entry}") + other: Final = _chat(mapped, key, f"service=other-{entry},tenant={entry}") assert other.status_code == 200, other.text @@ -536,10 +536,10 @@ def test_required_mapping_rejects_a_request_without_its_baggage_value_before_the with mapped.proxy.scenario() as scenario: key: Final = scenario.key() mapped.provider.drain() - rejected: Final = _chat(mapped, key, "entrypoint=a") + rejected: Final = _chat(mapped, key, "service=a") assert rejected.status_code == 400, rejected.text assert mapped.provider.drain() == () - admitted: Final = _chat(mapped, key, f"entrypoint=a,tenant={uuid.uuid4().hex}") + admitted: Final = _chat(mapped, key, f"service=a,tenant={uuid.uuid4().hex}") assert admitted.status_code == 200, admitted.text @@ -591,7 +591,7 @@ def test_mapped_tags_never_select_a_tag_routed_deployment(mapped: Rig, caller_ta _chat( mapped, key, - f"entrypoint=a,tenant={tenant}", + f"service=a,tenant={tenant}", model=f"routed-{mapped.marker}", fields=fields, **headers, @@ -604,8 +604,8 @@ def test_mapped_tags_never_select_a_tag_routed_deployment(mapped: Rig, caller_ta def test_mapped_tags_never_trigger_a_tag_scoped_policy_attachment(mapped: Rig) -> None: entry: Final = uuid.uuid4().hex - tag: Final = mapped.usecase_tag(entry) - baggage: Final = f"entrypoint={entry},tenant={entry}" + tag: Final = mapped.app_tag(entry) + baggage: Final = f"service={entry},tenant={entry}" proxy: Final = mapped.proxy with wire_server(lambda _request: Reply(body=GUARDRAIL_VERDICT)) as guardrail, proxy.scenario() as scenario: key: Final = scenario.key() @@ -662,7 +662,7 @@ def test_required_mapping_refuses_websocket_inference_before_the_upstream(mapped upstream.get("/__observations").raise_for_status() status: Final = _handshake_status( f"ws{proxy_url.removeprefix('http')}/v1/realtime?model=realtime-{mapped.marker}", - {"Authorization": f"Bearer {key}", "baggage": f"entrypoint=a,tenant={uuid.uuid4().hex}"}, + {"Authorization": f"Bearer {key}", "baggage": f"service=a,tenant={uuid.uuid4().hex}"}, ) assert status == 403, status observed: Final = list_value(JSON_OBJECT.validate_json(upstream.get("/__observations").content)["requests"]) @@ -706,7 +706,7 @@ def test_custom_passthrough_spend_row_carries_the_mapped_tags(mapped: Rig) -> No path, {"model": mapped.chat_model, "messages": [{"role": "user", "content": tenant}]}, key=key, - headers={"baggage": f"entrypoint=a,tenant={tenant}"}, + headers={"baggage": f"service=a,tenant={tenant}"}, ) assert response.status_code == 200, response.text assert {mapped.exact_tag, mapped.tenant_tag(tenant)} <= _spend_tags(mapped.proxy, key) @@ -777,7 +777,7 @@ def test_passthrough_forwards_the_client_body_unchanged_while_its_spend_row_carr plain: Final = optional.proxy.request("POST", path, body, key=plain_key) plain_forwarded: Final = _forwarded_bodies(optional) response: Final = optional.proxy.request( - "POST", path, body, key=key, headers={"baggage": f"entrypoint=a,tenant={tenant}"} + "POST", path, body, key=key, headers={"baggage": f"service=a,tenant={tenant}"} ) assert (plain.status_code, response.status_code) == (200, 200), (plain.text, response.text) assert plain_forwarded == (_upstream_body(entrypoint, body),) @@ -929,7 +929,7 @@ def test_reject_clientside_metadata_tags_with_baggage( ) -> None: tenant: Final = uuid.uuid4().hex fields, headers = _rejected_client_tag(client_tag, f"caller-{tenant}") - baggage: Final = f"entrypoint=a,tenant={tenant}" if baggage_maps else f"region={tenant}" + baggage: Final = f"service=a,tenant={tenant}" if baggage_maps else f"region={tenant}" mapped_tags: Final = frozenset({rejecting.exact_tag, rejecting.tenant_tag(tenant)} if baggage_maps else ()) with rejecting.proxy.scenario() as scenario: plain_key: Final = scenario.key() @@ -952,7 +952,7 @@ def test_plus_sign_rule_key_matches_either_wire_spelling_but_not_both( optional: Rig, baggage_keys: tuple[str, ...], maps_team: bool ) -> None: value: Final = uuid.uuid4().hex - baggage: Final = ",".join(("entrypoint=a", *(f"{baggage_key}={value}" for baggage_key in baggage_keys))) + baggage: Final = ",".join(("service=a", *(f"{baggage_key}={value}" for baggage_key in baggage_keys))) with optional.proxy.scenario() as scenario: key: Final = scenario.key() response: Final = _chat(optional, key, baggage) @@ -991,7 +991,7 @@ def test_baggage_mapping_a_deployment_tag_keeps_the_team_tag_guardrail_mode_firs @pytest.mark.parametrize("metadata", ["run-123", {"tags": "run-123"}], ids=["non_object", "string_tags"]) @pytest.mark.parametrize( ("header_tag", "baggage"), - [(True, "region=sg"), (True, "entrypoint=a"), (False, "region=sg"), (False, "entrypoint=a")], + [(True, "region=sg"), (True, "service=a"), (False, "region=sg"), (False, "service=a")], ids=["header_tag_unmapped_baggage", "header_tag_mapped_baggage", "unmapped_baggage", "mapped_baggage"], ) def test_malformed_metadata_keeps_its_status_under_baggage( diff --git a/tests/integration/spend/test_end_user_budget_enforcement.py b/tests/integration/spend/test_end_user_budget_enforcement.py index 02c8aee8f5e..92259d463b9 100644 --- a/tests/integration/spend/test_end_user_budget_enforcement.py +++ b/tests/integration/spend/test_end_user_budget_enforcement.py @@ -258,9 +258,20 @@ def _observed(upstream: httpx.Client) -> list[JsonValue]: return requests -def _denial_error(denied: httpx.Response) -> dict[str, JsonValue]: +def _denial_error(denied: httpx.Response, route: str) -> dict[str, JsonValue]: assert denied.status_code == 422, denied.text - return object_value(object_value(denied.json())["error"]) + if route == "/v1/messages": + body: Final = object_value(denied.json()) + assert body["type"] == "error", denied.text + anthropic_error: Final = object_value(body["error"]) + assert anthropic_error["type"] == "invalid_request_error", denied.text + assert "param" not in anthropic_error and "code" not in anthropic_error, denied.text + return anthropic_error + openai_error: Final = object_value(object_value(denied.json())["error"]) + assert openai_error["type"] == "budget_exceeded", denied.text + assert openai_error["param"] is None + assert openai_error["code"] == "422" + return openai_error def _prove_end_user_budget_lockout( @@ -304,8 +315,7 @@ def _prove_end_user_budget_lockout( upstream.delete("/__observations").raise_for_status() denied: Final = _send(gateway, spelling, deployment, key, end_user_id, f"denied {end_user_id}") assert _observed(upstream) == [], denied.text - error: Final = _denial_error(denied) - assert error["type"] == "budget_exceeded", denied.text + error: Final = _denial_error(denied, spelling.route) matched: Final = re.fullmatch( rf"ExceededBudget: End User={re.escape(end_user_id)} over budget\. " rf"Spend=([-+]?(?:\d+(?:\.\d*)?|\.\d+)(?:[eE][-+]?\d+)?), Budget=0\.05", diff --git a/tests/integration/spend/test_end_user_spend_without_proxy_user.py b/tests/integration/spend/test_end_user_spend_without_proxy_user.py index 94884717092..725c809006a 100644 --- a/tests/integration/spend/test_end_user_spend_without_proxy_user.py +++ b/tests/integration/spend/test_end_user_spend_without_proxy_user.py @@ -120,6 +120,18 @@ def _assert_budget_refusal(response: httpx.Response, end_user: str) -> None: ] +def _assert_messages_budget_refusal(response: httpx.Response, end_user: str) -> None: + assert response.status_code == 422, response.text + body: Final = _json_object(response.content) + assert body["type"] == "error", response.text + error: Final = object_value(body["error"]) + assert error["type"] == "invalid_request_error" + assert "param" not in error and "code" not in error, response.text + assert str(error["message"]).startswith(f"ExceededBudget: End User={end_user} over budget. Spend="), error[ + "message" + ] + + def _json_object(raw: bytes) -> dict[str, JsonValue]: return _JSON_OBJECT.validate_json(raw) @@ -345,7 +357,7 @@ def test_anthropic_messages_metadata_user_id_is_charged_and_budget_enforced(gate json={**body, "messages": [{"role": "user", "content": f"again {uuid.uuid4().hex}"}]}, headers={"x-api-key": key, "anthropic-version": "2023-06-01"}, ) - _assert_budget_refusal(denied, end_user) + _assert_messages_budget_refusal(denied, end_user) assert _observed(upstream) == [] diff --git a/tests/integration/spend/test_failing_request_stored_snapshot.py b/tests/integration/spend/test_failing_request_stored_snapshot.py new file mode 100644 index 00000000000..4f016c33f37 --- /dev/null +++ b/tests/integration/spend/test_failing_request_stored_snapshot.py @@ -0,0 +1,84 @@ +import json +import uuid +from collections.abc import Iterator +from pathlib import Path +from typing import Final + +import pytest +import yaml +from integration._support.client import Gateway, eventually, gateway_from_environment, object_value +from integration._support.process import owned_proxy +from pydantic import JsonValue + +UNREACHABLE_BASE: Final = "http://127.0.0.1:9/v1" +TRANSCRIPT_TURNS: Final = 40 +RETRIES: Final = 2 +STORED_REQUEST_BUDGET_KB: Final = 64 + + +def _config_storing_prompts(directory: Path) -> Path: + config: Final = object_value(yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text())) + general_settings: Final = object_value(config["general_settings"]) + path: Final = directory / "store-prompts.yaml" + path.write_text( + yaml.safe_dump({**config, "general_settings": {**general_settings, "store_prompts_in_spend_logs": True}}) + ) + return path + + +@pytest.fixture(scope="module") +def gateway(tmp_path_factory: pytest.TempPathFactory) -> Iterator[Gateway]: + with gateway_from_environment() as parent: + directory: Final = tmp_path_factory.mktemp("failing_request_stored_snapshot") + with owned_proxy(parent, directory, {}, config=_config_storing_prompts(directory)) as owned: + yield owned + + +def _transcript(marker: str) -> list[JsonValue]: + turns: Final[list[JsonValue]] = [ + {"role": role, "content": f"turn {turn // 2} {role}"} + for turn, role in enumerate(("user", "assistant") * TRANSCRIPT_TURNS) + ] + return [*turns, {"role": "user", "content": marker}] + + +def _stored_request(gateway: Gateway, call_id: str) -> JsonValue: + rows: Final = eventually( + lambda: gateway.rows('SELECT proxy_server_request FROM "LiteLLM_SpendLogs" WHERE request_id = %s', (call_id,)), + lambda values: len(values) == 1, + seconds=40, + ) + stored: Final = rows[0]["proxy_server_request"] + return json.loads(stored) if isinstance(stored, str) else stored + + +def test_failing_request_with_retries_and_fallback_stores_one_copy_of_the_request(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + primary: Final = f"stored-snapshot-{uuid.uuid4().hex}" + fallback: Final = f"stored-snapshot-fb-{uuid.uuid4().hex}" + for name in (primary, primary, fallback, fallback): + scenario.model(name=name, api_base=UNREACHABLE_BASE, cooldown_time=0) + key: Final = scenario.key(models=[primary, fallback]) + marker: Final = f"stored snapshot {uuid.uuid4().hex}" + + response: Final = gateway.request( + "POST", + "/v1/chat/completions", + { + "model": primary, + "max_tokens": 16, + "messages": _transcript(marker), + "router_settings_override": {"num_retries": RETRIES, "fallbacks": [{primary: [fallback]}]}, + }, + key=key, + ) + assert response.status_code != 200, response.text + assert fallback in response.text, response.text + + serialized: Final = json.dumps(_stored_request(gateway, response.headers["x-litellm-call-id"])) + stored_kb: Final = len(serialized.encode()) / 1024 + assert marker in serialized, serialized[:400] + assert stored_kb <= STORED_REQUEST_BUDGET_KB, ( + f"one failing request stored a {stored_kb:.0f} KB request snapshot for a " + f"{2 * TRANSCRIPT_TURNS + 1}-message transcript with {RETRIES} retries and a fallback" + ) diff --git a/tests/integration/spend/test_normalized_error_long_message.py b/tests/integration/spend/test_normalized_error_long_message.py index a364327290f..23200c0450e 100644 --- a/tests/integration/spend/test_normalized_error_long_message.py +++ b/tests/integration/spend/test_normalized_error_long_message.py @@ -30,6 +30,7 @@ BENIGN_288KB_MODEL: Final = "x" * len(CRAFTED_MODEL) CRAFTED_SLOWDOWN_FACTOR: Final = 10 FAST_SECONDS: Final = 10.0 LIVELINESS_STALL_BUDGET_SECONDS: Final = 5.0 +BURST_STALL_BUDGET_SECONDS: Final = 5.0 ROW_SECONDS: Final = 70 CHAT: Final = "/v1/chat/completions" MESSAGES: Final = "/v1/messages" @@ -349,10 +350,16 @@ def _burst_call(client: httpx.Client, label: str, path: str, body: Mapping[str, def _burst( - client: httpx.Client, happy_model: str, happy_key: str, open_key: str, during: Callable[[], None] + client: httpx.Client, + happy_model: str, + happy_key: str, + open_key: str, + during: Callable[[], None], + *, + rejected_model: str = CRAFTED_MODEL, ) -> tuple[_BurstResult, ...]: crafted: Final = tuple( - (f"crafted-{path}-{index}", path, _body(path, CRAFTED_MODEL, uuid.uuid4().hex, stream=index % 2 == 1), open_key) + (f"crafted-{path}-{index}", path, _body(path, rejected_model, uuid.uuid4().hex, stream=index % 2 == 1), open_key) for path in (CHAT, MESSAGES, RESPONSES) for index in range(4) ) @@ -377,6 +384,18 @@ def _burst( return tuple(future.result() for future in first + second) +def _assert_burst_rejections_fast(results: tuple[_BurstResult, ...], control: tuple[_BurstResult, ...]) -> None: + crafted: Final = tuple(result for result in results if result.label.startswith("crafted") and result.status) + benign: Final = tuple(result for result in control if result.label.startswith("crafted")) + assert crafted and all(result.status == 400 for result in crafted), crafted + assert benign and all(result.status == 400 for result in benign), benign + assert_not_delayed_by( + (result.seconds for result in crafted), + control=(result.seconds for result in benign), + injected_delay=BURST_STALL_BUDGET_SECONDS, + ) + + def _assert_rows_land_exactly_once(results: tuple[_BurstResult, ...], prefix: str) -> None: landed: Final = tuple(result for result in results if result.label.startswith(prefix) and result.status == 200) assert landed, results @@ -405,20 +424,18 @@ def test_killing_one_worker_mid_burst_leaves_the_other_serving_crafted_and_happy ): model: Final = scenario.model(api_base=wire.url + "/v1", num_retries=0) key: Final = scenario.key(models=[model]) + open_key: Final = scenario.key() + control: Final = _burst(client, model, key, open_key, lambda: None, rejected_model=BENIGN_288KB_MODEL) + assert all(result.status == (400 if result.label.startswith("crafted") else 200) for result in control), control workers: Final = owned.worker_pids() assert len(workers) == 2, workers victim: Final = min(workers) with owned.replacing_worker(victim) as kill: - results: Final = _burst(client, model, key, scenario.key(), kill) + results: Final = _burst(client, model, key, open_key, kill) dropped: Final = tuple(result for result in results if result.status is None) assert len(dropped) < len(results), results - crafted: Final = tuple( - result for result in results if result.label.startswith("crafted") and result.status - ) - assert crafted and all( - result.status == 400 and result.seconds < FAST_SECONDS for result in crafted - ), crafted + _assert_burst_rejections_fast(results, control) late: Final = tuple(result for result in results if result.label.startswith("late")) assert all(result.status == 200 for result in late), late _assert_rows_land_exactly_once(results, "late") @@ -446,7 +463,11 @@ def test_upstream_returning_503_mid_burst_logs_every_failure_with_its_own_cluste ): model: Final = scenario.model(api_base=wire.url + "/v1", num_retries=0) key: Final = scenario.key(models=[model]) - results: Final = _burst(client, model, key, scenario.key(), lambda: None) + open_key: Final = scenario.key() + control: Final = _burst(client, model, key, open_key, lambda: None, rejected_model=BENIGN_288KB_MODEL) + assert all(result.status == (400 if result.label.startswith("crafted") else 503) for result in control), control + wire.drain() + results: Final = _burst(client, model, key, open_key, lambda: None) assert all(result.status is not None for result in results), results happy: Final = tuple(result for result in results if result.label.startswith("happy")) assert all(result.status == 503 for result in happy), happy @@ -456,8 +477,7 @@ def test_upstream_returning_503_mid_burst_logs_every_failure_with_its_own_cluste assert all(any(f"normalized error audit {result.label}" in body for body in seen) for result in happy + late), ( seen ) - crafted: Final = tuple(result for result in results if result.label.startswith("crafted")) - assert all(result.status == 400 and result.seconds < FAST_SECONDS for result in crafted), crafted + _assert_burst_rejections_fast(results, control) codes: Final = { result.label: _error_information(string_value(result.call_id))["normalized_error"] for result in results } diff --git a/tests/integration/spend/test_partial_stream_live_budget.py b/tests/integration/spend/test_partial_stream_live_budget.py index 89fb66c9bbf..cba51873e2d 100644 --- a/tests/integration/spend/test_partial_stream_live_budget.py +++ b/tests/integration/spend/test_partial_stream_live_budget.py @@ -346,5 +346,15 @@ def test_a_broken_messages_stream_counts_toward_the_budget(gateway: Gateway) -> _broken_messages_stream(gateway, model, key) after: Final = _messages(gateway, model, key, streamed=False) - assert_budget_refusal(after) + assert after.status_code == 422, after.text + body: Final = JSON_OBJECT.validate_json(after.content) + error: Final = JSON_OBJECT.validate_python(body["error"]) + assert body == { + "type": "error", + "error": { + "type": "invalid_request_error", + "message": error["message"], + "litellm_error_type": "budget_exceeded", + }, + }, after.text assert _rows(gateway, key, 2) == (metered, StatusRow(status="failure", spend=0.0)) diff --git a/tests/integration/spend/test_responses_bridge_spend_once.py b/tests/integration/spend/test_responses_bridge_spend_once.py index 9eddd832ca0..cc2a0af58a7 100644 --- a/tests/integration/spend/test_responses_bridge_spend_once.py +++ b/tests/integration/spend/test_responses_bridge_spend_once.py @@ -1,5 +1,4 @@ import json -from base64 import b64decode from collections.abc import Callable from hashlib import sha256 from typing import Final @@ -100,8 +99,7 @@ def test_bridged_chat_completion_above_log_offload_threshold_logs_and_charges_on call_rows: Final = [row for row in rows if row["litellm_call_id"] == call_id] assert len(call_rows) == 1, rows assert float(str(call_rows[0]["spend"])) == pytest.approx(EXPECTED_SPEND), rows - logged_id: Final = b64decode(str(call_rows[0]["request_id"]).removeprefix("resp_")).decode() - assert logged_id.startswith("litellm:") and f";response_id:{upstream_id}" in logged_id, rows + assert call_rows[0]["request_id"] == upstream_id, rows key_spend: Final = eventually( lambda: read_rows('SELECT spend FROM "LiteLLM_VerificationToken" WHERE token=%s', (digest,)), diff --git a/tests/integration/spend/test_responses_stream_spend_row_id.py b/tests/integration/spend/test_responses_stream_spend_row_id.py new file mode 100644 index 00000000000..58ed9f7785f --- /dev/null +++ b/tests/integration/spend/test_responses_stream_spend_row_id.py @@ -0,0 +1,465 @@ +import json +from collections.abc import Mapping +from datetime import datetime, timedelta, timezone +from hashlib import sha256 +from pathlib import Path +from types import MappingProxyType +from typing import Final +from uuid import uuid4 + +import httpx +import pytest +import yaml +from integration._support.client import JSON_OBJECT, Gateway, eventually, list_value, object_value, string_value +from integration._support.process import owned_proxy +from integration._support.responses_stream import frame, response_object +from integration._support.wire import Reply, Request, wire_server +from pydantic import JsonValue, TypeAdapter + +_NATIVE_MODEL: Final = "openai/gpt-5.6" +_BRIDGED_MODEL: Final = "deepseek/deepseek-v4-pro" +_ANSWER: Final = "streamed answer" +_USAGE: Final[dict[str, JsonValue]] = {"input_tokens": 30, "output_tokens": 5, "total_tokens": 35} +_JSON_LIST: Final = TypeAdapter(list[dict[str, JsonValue]]) + + +def _sse(payload: dict[str, JsonValue]) -> bytes: + return f"data: {json.dumps(payload)}\n\n".encode() + + +def _native_completed(upstream_id: str) -> dict[str, JsonValue]: + message: Final[dict[str, JsonValue]] = { + "type": "message", + "id": "msg_1", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": _ANSWER, "annotations": []}], + } + return response_object(upstream_id, "completed", output=[message], usage=_USAGE) + + +def _native_stream(upstream_id: str) -> Reply: + return Reply( + content_type="text/event-stream", + chunks=( + frame( + { + "type": "response.created", + "sequence_number": 0, + "response": response_object(upstream_id, "in_progress"), + } + ), + frame( + { + "type": "response.output_text.delta", + "sequence_number": 1, + "item_id": "msg_1", + "output_index": 0, + "content_index": 0, + "delta": _ANSWER, + } + ), + frame({"type": "response.completed", "sequence_number": 2, "response": _native_completed(upstream_id)}), + ), + ) + + +def _chat_stream(upstream_id: str, model: str) -> Reply: + def chunk(delta: dict[str, JsonValue], finish_reason: str | None) -> dict[str, JsonValue]: + return { + "id": upstream_id, + "object": "chat.completion.chunk", + "created": 1, + "model": model, + "choices": [{"index": 0, "delta": delta, "finish_reason": finish_reason}], + } + + return Reply( + content_type="text/event-stream", + chunks=( + _sse(chunk({"role": "assistant", "content": _ANSWER}, None)), + _sse( + { + **chunk({}, "stop"), + "usage": {"prompt_tokens": 30, "completion_tokens": 5, "total_tokens": 35}, + } + ), + b"data: [DONE]\n\n", + ), + ) + + +def _respond(request: Request) -> Reply: + if request.method == "GET" and request.target == "/v1/models": + return Reply(body=json.dumps({"object": "list", "data": []}).encode()) + if request.method == "GET": + stored_id: Final = request.target.removeprefix("/v1/responses/") + assert stored_id.startswith("resp_upstream-"), request.target + return Reply(body=json.dumps(_native_completed(stored_id)).encode()) + if request.target.endswith("/cancel"): + cancelled_id: Final = request.target.removeprefix("/v1/responses/").removesuffix("/cancel") + assert cancelled_id.startswith("resp_upstream-"), request.target + return Reply(body=json.dumps(response_object(cancelled_id, "cancelled")).encode()) + body: Final = JSON_OBJECT.validate_json(request.body) + upstream_id: Final = f"upstream-{uuid4().hex}" + if request.target == "/v1/responses" and body.get("stream") is not True: + return Reply(body=json.dumps(_native_completed(f"resp_{upstream_id}")).encode()) + assert body.get("stream") is True, body + if request.target == "/v1/responses": + return _native_stream(f"resp_{upstream_id}") + assert request.target == "/v1/chat/completions", request.target + return _chat_stream(f"chatcmpl-{upstream_id}", string_value(body["model"])) + + +def _terminal_response_id( + gateway: Gateway, key: str, body: dict[str, JsonValue], headers: Mapping[str, str] | None = None +) -> str: + response: Final = gateway.request("POST", "/v1/responses", body, key=key, headers=headers) + assert response.status_code == 200, response.text + frames: Final = tuple( + JSON_OBJECT.validate_json(line.removeprefix("data: ")) + for line in response.text.splitlines() + if line.startswith("data: ") and line != "data: [DONE]" + ) + assert frames and frames[-1]["type"] == "response.completed", response.text + advertised: Final = tuple( + dict.fromkeys(string_value(object_value(event["response"])["id"]) for event in frames if "response" in event) + ) + assert len(advertised) == 1, advertised + return advertised[0] + + +def _created_response_id( + gateway: Gateway, key: str, body: dict[str, JsonValue], headers: Mapping[str, str] | None = None +) -> str: + if body.get("stream") is True: + return _terminal_response_id(gateway, key, body, headers) + response: Final = gateway.request("POST", "/v1/responses", body, key=key, headers=headers) + assert response.status_code == 200, response.text + return string_value(JSON_OBJECT.validate_json(response.content)["id"]) + + +def _read_and_cancel( + gateway: Gateway, key: str, response_id: str, headers: Mapping[str, str] | None = None +) -> tuple[httpx.Response, ...]: + responses: Final = tuple( + gateway.request(method, path, key=key, headers=headers) + for method, path in ( + ("GET", f"/v1/responses/{response_id}"), + ("GET", f"/v1/responses/{response_id}"), + ("POST", f"/v1/responses/{response_id}/cancel"), + ) + ) + assert [response.status_code for response in responses] == [200, 200, 200], [r.text for r in responses] + return responses + + +def _spend_logs_lookup(gateway: Gateway, request_id: str) -> list[JsonValue]: + response: Final = gateway.request("GET", "/spend/logs", params={"request_id": request_id}) + assert response.status_code == 200, response.text + return [row["request_id"] for row in _JSON_LIST.validate_json(response.content)] + + +def _request_ids_for_key(gateway: Gateway, key: str, count: int) -> list[str]: + rows: Final = eventually( + lambda: gateway.rows( + 'SELECT request_id FROM "LiteLLM_SpendLogs" WHERE api_key=%s ORDER BY "endTime"', + (sha256(key.encode()).hexdigest(),), + ), + lambda found: len(found) >= count, + seconds=70, + ) + return [string_value(row["request_id"]) for row in rows] + + +def _logs_page_search(gateway: Gateway, client_id: str) -> list[str]: + now: Final = datetime.now(timezone.utc) + page: Final = gateway.get( + "/spend/logs/ui", + params={ + "search": client_id, + "start_date": (now - timedelta(days=1)).strftime("%Y-%m-%d %H:%M:%S"), + "end_date": (now + timedelta(days=1)).strftime("%Y-%m-%d %H:%M:%S"), + }, + ) + return [string_value(object_value(row)["request_id"]) for row in list_value(page["data"])] + + +@pytest.mark.timeout(120) +@pytest.mark.parametrize("litellm_model", [_NATIVE_MODEL, _BRIDGED_MODEL], ids=["native", "bridge"]) +def test_streamed_responses_spend_row_is_filed_under_the_id_the_client_saw( + gateway: Gateway, litellm_model: str +) -> None: + with wire_server(_respond) as wire, gateway.scenario() as scenario: + model: Final = scenario.model(model=litellm_model, api_base=f"{wire.url}/v1", api_key="synthetic-key") + key: Final = scenario.key(models=[model]) + + client_id: Final = _terminal_response_id( + gateway, key, {"model": model, "input": f"marker-{uuid4().hex}", "stream": True} + ) + + assert client_id.startswith("resp_"), client_id + assert _request_ids_for_key(gateway, key, 1) == [client_id] + assert _logs_page_search(gateway, client_id) == [client_id] + assert _spend_logs_lookup(gateway, client_id) == [client_id] + + +def _proxy_config( + directory: Path, + general_settings: Mapping[str, JsonValue], + litellm_settings: Mapping[str, JsonValue] = MappingProxyType({}), +) -> Path: + stock: Final = JSON_OBJECT.validate_python(yaml.safe_load(Path("tests/integration/proxy_config.yaml").read_text())) + path: Final = directory / "responses-spend.yaml" + path.write_text( + yaml.safe_dump( + { + **stock, + "general_settings": {**object_value(stock["general_settings"]), **general_settings}, + "litellm_settings": {**object_value(stock["litellm_settings"]), **litellm_settings}, + } + ) + ) + return path + + +def _prompt_storing_config(directory: Path) -> Path: + return _proxy_config(directory, {"store_prompts_in_spend_logs": True}) + + +def test_a_follow_up_turn_on_a_streamed_bridged_response_replays_the_first_turn( + gateway: Gateway, tmp_path: Path +) -> None: + first_prompt: Final = f"first turn {uuid4().hex}" + with ( + wire_server(_respond) as wire, + owned_proxy(gateway, tmp_path, {}, config=_prompt_storing_config(tmp_path)) as storing, + storing.scenario() as scenario, + ): + model: Final = scenario.model(model=_BRIDGED_MODEL, api_base=f"{wire.url}/v1", api_key="synthetic-key") + key: Final = scenario.key(models=[model]) + first_id: Final = _terminal_response_id(storing, key, {"model": model, "input": first_prompt, "stream": True}) + assert _request_ids_for_key(storing, key, 1) == [first_id] + wire.drain() + + second_id: Final = _terminal_response_id( + storing, + key, + {"model": model, "input": "second turn", "previous_response_id": first_id, "stream": True}, + ) + + replayed: Final = _JSON_LIST.validate_python(JSON_OBJECT.validate_json(wire.drain()[-1].body)["messages"]) + assert [(message["role"], message["content"]) for message in replayed] == [ + ("user", first_prompt), + ("assistant", _ANSWER), + ("user", "second turn"), + ], replayed + assert _request_ids_for_key(storing, key, 2) == [first_id, second_id] + + +@pytest.mark.timeout(180) +@pytest.mark.parametrize("stream_first_turn", [True, False], ids=["streamed-first-turn", "non-streamed-first-turn"]) +def test_a_follow_up_through_the_id_a_retrieve_returned_replays_the_first_turn_once( + gateway: Gateway, tmp_path: Path, stream_first_turn: bool +) -> None: + first_prompt: Final = f"first turn {uuid4().hex}" + with ( + wire_server(_respond) as wire, + owned_proxy(gateway, tmp_path, {}, config=_prompt_storing_config(tmp_path)) as storing, + storing.scenario() as scenario, + ): + native: Final = scenario.model(model=_NATIVE_MODEL, api_base=f"{wire.url}/v1", api_key="synthetic-key") + bridged: Final = scenario.model(model=_BRIDGED_MODEL, api_base=f"{wire.url}/v1", api_key="synthetic-key") + key: Final = scenario.key(models=[native, bridged]) + first_id: Final = _created_response_id( + storing, key, {"model": native, "input": first_prompt, "stream": stream_first_turn} + ) + + retrieved: Final = storing.request("GET", f"/v1/responses/{first_id}", key=key) + + assert retrieved.status_code == 200, retrieved.text + retrieved_id: Final = string_value(JSON_OBJECT.validate_json(retrieved.content)["id"]) + assert retrieved_id == first_id + stored: Final = _request_ids_for_key(storing, key, 2) + assert stored.count(first_id) == 1, stored + assert len(set(stored)) == 2, stored + assert _spend_logs_lookup(storing, first_id) == [first_id] + wire.drain() + + _terminal_response_id( + storing, + key, + {"model": bridged, "input": "second turn", "previous_response_id": retrieved_id, "stream": True}, + ) + + replayed: Final = _JSON_LIST.validate_python(JSON_OBJECT.validate_json(wire.drain()[-1].body)["messages"]) + assert [(message["role"], message["content"]) for message in replayed] == [ + ("user", first_prompt), + ("assistant", _ANSWER), + ("user", "second turn"), + ], replayed + + +def _replayed_turns(wire_body: bytes) -> list[tuple[JsonValue, JsonValue]]: + replayed: Final = _JSON_LIST.validate_python(JSON_OBJECT.validate_json(wire_body)["messages"]) + return [(message["role"], message["content"]) for message in replayed] + + +@pytest.mark.timeout(180) +@pytest.mark.parametrize("reader", ["proxy-admin", "master-key"]) +def test_a_reader_other_than_the_creator_continues_through_the_id_its_retrieve_returned( + gateway: Gateway, tmp_path: Path, reader: str +) -> None: + first_prompt: Final = f"first turn {uuid4().hex}" + with ( + wire_server(_respond) as wire, + owned_proxy(gateway, tmp_path, {}, config=_prompt_storing_config(tmp_path)) as storing, + storing.scenario() as scenario, + ): + native: Final = scenario.model(model=_NATIVE_MODEL, api_base=f"{wire.url}/v1", api_key="synthetic-key") + bridged: Final = scenario.model(model=_BRIDGED_MODEL, api_base=f"{wire.url}/v1", api_key="synthetic-key") + creator: Final = scenario.key(user_id=scenario.user(), models=[native, bridged]) + reader_key: Final = ( + scenario.key(user_id=scenario.user(user_role="proxy_admin"), models=[native, bridged]) + if reader == "proxy-admin" + else storing.key + ) + first_id: Final = _terminal_response_id( + storing, creator, {"model": native, "input": first_prompt, "stream": True} + ) + assert _request_ids_for_key(storing, creator, 1) == [first_id] + + retrieved: Final = storing.request("GET", f"/v1/responses/{first_id}", key=reader_key) + + assert retrieved.status_code == 200, retrieved.text + retrieved_id: Final = string_value(JSON_OBJECT.validate_json(retrieved.content)["id"]) + wire.drain() + _terminal_response_id( + storing, + reader_key, + {"model": bridged, "input": "second turn", "previous_response_id": retrieved_id, "stream": True}, + ) + assert _replayed_turns(wire.drain()[-1].body) == [ + ("user", first_prompt), + ("assistant", _ANSWER), + ("user", "second turn"), + ] + assert retrieved_id == first_id + + +@pytest.mark.timeout(180) +def test_reads_and_cancels_sent_with_a_session_header_add_no_replayed_turns(gateway: Gateway, tmp_path: Path) -> None: + first_prompt: Final = f"first turn {uuid4().hex}" + session: Final = {"x-litellm-session-id": f"session-{uuid4().hex}"} + with ( + wire_server(_respond) as wire, + owned_proxy(gateway, tmp_path, {}, config=_prompt_storing_config(tmp_path)) as storing, + storing.scenario() as scenario, + ): + native: Final = scenario.model(model=_NATIVE_MODEL, api_base=f"{wire.url}/v1", api_key="synthetic-key") + bridged: Final = scenario.model(model=_BRIDGED_MODEL, api_base=f"{wire.url}/v1", api_key="synthetic-key") + key: Final = scenario.key(models=[native, bridged]) + first_id: Final = _created_response_id(storing, key, {"model": native, "input": first_prompt}, session) + + _read_and_cancel(storing, key, first_id, session) + + assert len(_request_ids_for_key(storing, key, 4)) == 4 + wire.drain() + _terminal_response_id( + storing, + key, + {"model": bridged, "input": "second turn", "previous_response_id": first_id, "stream": True}, + session, + ) + assert _replayed_turns(wire.drain()[-1].body) == [ + ("user", first_prompt), + ("assistant", _ANSWER), + ("user", "second turn"), + ] + + +@pytest.mark.timeout(180) +def test_each_read_and_cancel_reaches_callbacks_and_spend_logs_under_an_id_of_its_own( + gateway: Gateway, tmp_path: Path +) -> None: + logged_call_types: Final = frozenset({"aresponses", "aget_responses", "acancel_responses"}) + with ( + wire_server(_respond) as wire, + wire_server(lambda _: Reply()) as sink, + owned_proxy( + gateway, + tmp_path, + {"GENERIC_LOGGER_ENDPOINT": sink.url}, + config=_proxy_config(tmp_path, {}, {"callbacks": ["generic_api"], "DEFAULT_FLUSH_INTERVAL_SECONDS": 1}), + ) as logging_proxy, + logging_proxy.scenario() as scenario, + ): + model: Final = scenario.model(model=_NATIVE_MODEL, api_base=f"{wire.url}/v1", api_key="synthetic-key") + key: Final = scenario.key(models=[model]) + first_id: Final = _created_response_id(logging_proxy, key, {"model": model, "input": f"marker-{uuid4().hex}"}) + + reads: Final = _read_and_cancel(logging_proxy, key, first_id) + + assert [string_value(JSON_OBJECT.validate_json(read.content)["id"]) for read in reads] == [first_id] * 3 + batches: Final[list[bytes]] = [] # mutable-ok: drain() consumes, later polls keep earlier batches + + def delivered() -> tuple[tuple[str, str], ...]: + batches.extend(batch.body for batch in sink.drain()) + return tuple( + (string_value(event["call_type"]), string_value(event["id"])) + for event in (object_value(item) for batch in batches for item in _JSON_LIST.validate_json(batch)) + if event["call_type"] in logged_call_types + ) + + events: Final = eventually(delivered, lambda found: len(found) >= 4, seconds=30) + read_ids: Final = [logged_id for call_type, logged_id in events if call_type != "aresponses"] + assert [logged_id for call_type, logged_id in events if call_type == "aresponses"] == [first_id], events + assert len(read_ids) == 3, events + assert first_id not in read_ids, events + assert len(set(read_ids)) == 3, events + assert sorted(_request_ids_for_key(logging_proxy, key, 4)) == sorted([first_id, *read_ids]) + + +@pytest.mark.timeout(240) +def test_with_id_security_off_reads_and_cancels_add_no_rows_and_no_replayed_turns( + gateway: Gateway, tmp_path: Path +) -> None: + first_prompt: Final = f"first turn {uuid4().hex}" + session: Final = {"x-litellm-session-id": f"session-{uuid4().hex}"} + with ( + wire_server(_respond) as wire, + owned_proxy( + gateway, + tmp_path, + {}, + config=_proxy_config( + tmp_path, {"store_prompts_in_spend_logs": True, "disable_responses_id_security": True} + ), + ) as insecure, + insecure.scenario() as scenario, + ): + native: Final = scenario.model(model=_NATIVE_MODEL, api_base=f"{wire.url}/v1", api_key="synthetic-key") + bridged: Final = scenario.model(model=_BRIDGED_MODEL, api_base=f"{wire.url}/v1", api_key="synthetic-key") + key: Final = scenario.key(models=[native, bridged]) + first_id: Final = _created_response_id(insecure, key, {"model": native, "input": first_prompt}, session) + + reads: Final = _read_and_cancel(insecure, key, first_id, session) + + assert [string_value(JSON_OBJECT.validate_json(read.content)["id"]) for read in reads] == [first_id] * 3 + later_id: Final = _created_response_id(insecure, key, {"model": native, "input": "a later request"}) + assert _request_ids_for_key(insecure, key, 2) == [first_id, later_id] + wire.drain() + + _terminal_response_id( + insecure, + key, + {"model": bridged, "input": "second turn", "previous_response_id": first_id, "stream": True}, + session, + ) + + replayed: Final = _JSON_LIST.validate_python(JSON_OBJECT.validate_json(wire.drain()[-1].body)["messages"]) + assert [(message["role"], message["content"]) for message in replayed] == [ + ("user", first_prompt), + ("assistant", _ANSWER), + ("user", "second turn"), + ], replayed diff --git a/tests/integration/spend/test_session_grouped_logs_pages.py b/tests/integration/spend/test_session_grouped_logs_pages.py new file mode 100644 index 00000000000..7989cb6a7bc --- /dev/null +++ b/tests/integration/spend/test_session_grouped_logs_pages.py @@ -0,0 +1,467 @@ +import itertools +import json +import os +import uuid +from collections.abc import AsyncIterator, Iterator, Mapping, Sequence +from contextlib import asynccontextmanager +from dataclasses import dataclass +from datetime import UTC, datetime, timedelta +from typing import Final +from urllib.parse import parse_qsl, urlencode, urlsplit, urlunsplit + +import psycopg +import pytest +from prisma import Prisma +from psycopg import sql +from pydantic import BaseModel, ConfigDict, Field + +from litellm.proxy.spend_tracking.session_page import read_session_page +from litellm.proxy.spend_tracking.spend_management_endpoints import _fetch_session_representatives +from tests.integration._support.client import Gateway +from tests.integration._support.database import write_rows + +_URL: Final = "/spend/logs/ui" +_WINDOW_SECONDS: Final = 3600 + + +@dataclass(frozen=True, slots=True) +class _Row: + request: str + session: str | None + api_key: str + second: int + status: str = "success" + model: str = "m-a" + + +_ROWS: Final = ( + _Row("z1", "z", "key-1", -1), + _Row("a1", "a", "key-1", 10), + _Row("a2", "a", "key-1", 50), + _Row("b1", "b", "key-1", 20, model="m-b"), + _Row("b2", "b", "key-1", 60), + _Row("b3", "b", "key-1", 30), + _Row("c1", "c", "key-2", 60), + _Row("d1", "b", "key-2", 40, model="m-b"), + _Row("e1", None, "key-1", 55, model="m-b"), + _Row("f1", "", "key-1", 45), + _Row("g1", "g", "key-3", 5, status="failure"), + _Row("g2", "g", "key-3", 15, status="failure"), + *(_Row(f"h{second - 69}", "h", "key-1", second) for second in range(70, 76)), + _Row("i1", "i", "key-3", 35, status="failure"), + _Row("i2", "i", "key-3", _WINDOW_SECONDS + 1), +) +_NEWEST_FIRST: Final = ( + ("h", "key-1"), + ("c", "key-2"), + ("b", "key-1"), + ("e1", "key-1"), + ("a", "key-1"), + ("f1", "key-1"), + ("b", "key-2"), + ("i", "key-3"), + ("g", "key-3"), +) + + +class _LogRow(BaseModel): + model_config = ConfigDict(frozen=True) + + request_id: str + session_id: str | None + api_key: str + session_total_count: int + + +class _Page(BaseModel): + model_config = ConfigDict(frozen=True) + + data: tuple[_LogRow, ...] + total: int + total_is_capped: bool + has_more: bool + next_session_cursor: str | None + + +@dataclass(frozen=True, slots=True) +class _Seeded: + prefix: str + window: Mapping[str, str] + + def session(self, row: _LogRow) -> tuple[str, str]: + key: Final = row.session_id or row.request_id + assert key.startswith(self.prefix), key + return key.removeprefix(self.prefix), row.api_key + + +@pytest.fixture +def seeded(gateway: Gateway) -> Iterator[_Seeded]: + prefix: Final = f"sess{uuid.uuid4().hex[:12]}-" + start: Final = datetime(1900, 1, 1) + timedelta(days=int(prefix[4:16], 16) % 200000) + rows: Final = [ + { + "request_id": f"{prefix}{row.request}", + "session_id": None if row.session is None else f"{prefix}{row.session}" if row.session else "", + "api_key": row.api_key, + "start_time": (start + timedelta(seconds=row.second)).isoformat(), + "status": row.status, + "model": row.model, + } + for row in _ROWS + ] + with gateway.scenario() as scenario: + scenario.cleanups.callback( + write_rows, 'DELETE FROM "LiteLLM_SpendLogs" WHERE request_id LIKE %s', (f"{prefix}%",) + ) + write_rows( + 'INSERT INTO "LiteLLM_SpendLogs" (request_id, call_type, api_key, "startTime", "endTime", model, ' + "session_id, status) SELECT request_id, 'acompletion', api_key, start_time, start_time, model, session_id, " + "status FROM jsonb_to_recordset(%s::jsonb) AS seeded(request_id text, session_id text, api_key text, " + "start_time timestamp, status text, model text)", + (json.dumps(rows),), + ) + yield _Seeded( + prefix, + { + "start_date": f"{start:%Y-%m-%d %H:%M:%S}", + "end_date": f"{start + timedelta(seconds=_WINDOW_SECONDS):%Y-%m-%d %H:%M:%S}", + "group_by_session": "true", + }, + ) + + +def _page(gateway: Gateway, seeded: _Seeded, params: Mapping[str, str]) -> _Page: + return _Page.model_validate(gateway.get(_URL, {**seeded.window, **params})) + + +def _cursor_walk(gateway: Gateway, seeded: _Seeded, params: Mapping[str, str], number: int = 1) -> tuple[_Page, ...]: + page: Final = _page(gateway, seeded, {**params, "page_size": "2", "page": str(number)}) + if page.next_session_cursor is None or number > len(_NEWEST_FIRST): + return (page,) + following: Final = {**params, "session_cursor": page.next_session_cursor} + return (page, *_cursor_walk(gateway, seeded, following, number + 1)) + + +def _rows(pages: tuple[_Page, ...]) -> Iterator[_LogRow]: + return itertools.chain.from_iterable(page.data for page in pages) + + +def _sessions(seeded: _Seeded, pages: tuple[_Page, ...]) -> tuple[tuple[str, str], ...]: + return tuple(seeded.session(row) for row in _rows(pages)) + + +def test_cursor_pages_show_every_session_once_newest_first_with_its_newest_row( + gateway: Gateway, seeded: _Seeded +) -> None: + pages: Final = _cursor_walk(gateway, seeded, {}) + assert _sessions(seeded, pages) == _NEWEST_FIRST + assert [(page.total, page.total_is_capped) for page in pages] == [(9, False)] * 5 + assert [page.has_more for page in pages] == [True, True, True, True, False] + representatives: Final = tuple( + (row.request_id.removeprefix(seeded.prefix), row.session_total_count) for row in _rows(pages) + ) + assert representatives == ( + ("h6", 6), + ("c1", 1), + ("b2", 3), + ("e1", 1), + ("a2", 2), + ("f1", 1), + ("d1", 1), + ("i1", 2), + ("g2", 2), + ) + + +@pytest.mark.parametrize( + "sort_order, expected", + [("desc", _NEWEST_FIRST), ("asc", tuple(reversed(_NEWEST_FIRST)))], + ids=["newest-first", "oldest-first"], +) +def test_numbered_pages_show_the_same_sessions_as_the_cursor_walk( + gateway: Gateway, seeded: _Seeded, sort_order: str, expected: tuple[tuple[str, str], ...] +) -> None: + pages: Final = tuple( + _page(gateway, seeded, {"page_size": "2", "page": str(number), "sort_order": sort_order}) + for number in range(1, 7) + ) + assert _sessions(seeded, pages) == expected + assert [len(page.data) for page in pages] == [2, 2, 2, 2, 1, 0] + assert [page.has_more for page in pages] == [True, True, True, True, False, False] + assert {page.total for page in pages} == {len(expected)} + + +def test_failure_filter_keeps_only_sessions_whose_outcome_failed(gateway: Gateway, seeded: _Seeded) -> None: + pages: Final = _cursor_walk(gateway, seeded, {"status_filter": "failure"}) + assert _sessions(seeded, pages) == (("i", "key-3"), ("g", "key-3")) + assert pages[0].total == 2 + + +def test_model_filter_ranks_each_session_by_its_matching_rows_only(gateway: Gateway, seeded: _Seeded) -> None: + pages: Final = _cursor_walk(gateway, seeded, {"model": "m-b"}) + assert _sessions(seeded, pages) == (("e1", "key-1"), ("b", "key-2"), ("b", "key-1")) + assert tuple(row.request_id.removeprefix(seeded.prefix) for row in _rows(pages)) == ("e1", "d1", "b1") + assert pages[0].total == 3 + + +_COPIED_ROWS: Final = 20_000 +_COPY_START: Final = datetime(2000, 1, 1, tzinfo=UTC) +_COPY_WINDOW: Final = ( + "\"startTime\" >= ($1::timestamptz AT TIME ZONE 'UTC') AND \"startTime\" <= ($2::timestamptz AT TIME ZONE 'UTC')" +) +_COPY_WINDOW_PARAMS: Final = (_COPY_START, _COPY_START + timedelta(days=1)) + + +def _generated_sessions(rows_per_session: int) -> tuple[sql.SQL, tuple[object, ...]]: + """`_COPIED_ROWS` rows a second apart in sessions of `rows_per_session` rows, a one-row session keyed by request_id.""" + return sql.SQL( + 'INSERT INTO {table} (request_id, call_type, api_key, "startTime", "endTime", session_id) ' + "SELECT 'r' || n, 'acompletion', 'key-1', moment, moment, " + "CASE WHEN %s > 1 THEN 's' || (n - 1) / %s END FROM generate_series(1, %s) n, " + "LATERAL (SELECT %s::timestamp + n * INTERVAL '1 second' AS moment) seconds" + ), (rows_per_session, rows_per_session, _COPIED_ROWS, _COPY_START.replace(tzinfo=None)) + + +def _sessions_tied_at_the_newest_moment() -> tuple[sql.SQL, tuple[object, ...]]: + """`_generated_sessions(1)` plus thirty one-row sessions sharing a newer moment, inserted and keyed against session + order so a read cut inside the tie misses the sessions that rank first.""" + start: Final = _COPY_START.replace(tzinfo=None) + return sql.SQL( + 'INSERT INTO {table} (request_id, call_type, api_key, "startTime", "endTime", session_id) ' + "SELECT request_id, 'acompletion', 'key-1', moment, moment, session_id FROM (" + "SELECT n AS ordinal, 'r' || n AS request_id, %s::timestamp + n * INTERVAL '1 second' AS moment, " + "NULL AS session_id FROM generate_series(1, %s) n UNION ALL " + "SELECT %s + 30 - n, 't' || lpad((29 - n)::text, 2, '0'), %s::timestamp + %s * INTERVAL '1 second', " + "'s' || lpad(n::text, 2, '0') FROM generate_series(0, 29) n) seeded ORDER BY ordinal" + ), (start, _COPIED_ROWS, _COPIED_ROWS, start, _COPIED_ROWS + 1) + + +@dataclass(frozen=True, slots=True) +class _Call: + session: str + call_type: str + status: str | None + second: int + + +def _calls(calls: tuple[_Call, ...]) -> tuple[sql.SQL, tuple[object, ...]]: + """One row per call, `second` seconds into the window, ending a second later.""" + seeded: Final = tuple( + { + "request_id": f"{call.session}-{call.second}", + "call_type": call.call_type, + "session_id": call.session, + "status": call.status, + "start_time": (_COPY_START + timedelta(seconds=call.second)).replace(tzinfo=None).isoformat(), + } + for call in calls + ) + return sql.SQL( + 'INSERT INTO {table} (request_id, call_type, api_key, "startTime", "endTime", session_id, status) ' + "SELECT request_id, call_type, 'key-1', start_time, start_time + INTERVAL '1 second', session_id, status " + "FROM jsonb_to_recordset(%s::jsonb) AS calls(request_id text, call_type text, session_id text, status text, " + "start_time timestamp)" + ), (json.dumps(seeded),) + + +@asynccontextmanager +async def _spend_logs_copy(insert: sql.SQL, args: tuple[object, ...]) -> AsyncIterator[Prisma]: + """A private schema holding a copy of the migrated `LiteLLM_SpendLogs` with its indexes, seeded by `insert`.""" + schema: Final = f"integration_{uuid.uuid4().hex}" + url: Final = os.environ["DATABASE_URL"] + table: Final = sql.Identifier(schema, "LiteLLM_SpendLogs") + with psycopg.connect(url, autocommit=True) as setup: + setup.execute(sql.SQL("CREATE SCHEMA {}").format(sql.Identifier(schema))) + try: + setup.execute(sql.SQL('CREATE TABLE {} (LIKE "LiteLLM_SpendLogs" INCLUDING ALL)').format(table)) + setup.execute(insert.format(table=table), args) + setup.execute(sql.SQL("ANALYZE {}").format(table)) + parsed: Final = urlsplit(url) + query: Final = urlencode({**dict(parse_qsl(parsed.query)), "schema": schema}) + database: Final = Prisma(datasource={"url": urlunsplit(parsed._replace(query=query))}) + await database.connect() + try: + yield database + finally: + await database.disconnect() + finally: + setup.execute(sql.SQL("DROP SCHEMA {} CASCADE").format(sql.Identifier(schema))) + + +class _PlanNode(BaseModel): + model_config = ConfigDict(frozen=True) + + relation_name: str | None = Field(default=None, alias="Relation Name") + actual_rows: float = Field(alias="Actual Rows") + rows_removed_by_filter: float = Field(default=0, alias="Rows Removed by Filter") + actual_loops: int = Field(alias="Actual Loops") + plans: tuple["_PlanNode", ...] = Field(default=(), alias="Plans") + + def spend_log_rows_scanned(self) -> int: + own: Final = ( + (self.actual_rows + self.rows_removed_by_filter) * self.actual_loops + if self.relation_name == "LiteLLM_SpendLogs" + else 0 + ) + return round(own) + sum(child.spend_log_rows_scanned() for child in self.plans) + + +class _Explained(BaseModel): + model_config = ConfigDict(frozen=True) + + plan: _PlanNode = Field(alias="Plan") + + +class _ExplainedReads: + """Runs each read through Prisma, first under EXPLAIN ANALYZE to count the `LiteLLM_SpendLogs` rows it scans.""" + + def __init__(self, database: Prisma) -> None: + self.database: Final = database + self.rows_scanned: tuple[int, ...] = () + + @asynccontextmanager + async def tx(self, *, timeout: timedelta) -> AsyncIterator["_ExplainedReads"]: + async with self.database.tx(timeout=timeout) as transaction: + reads: Final = _ExplainedReads(transaction) + try: + yield reads + finally: + self.rows_scanned = (*self.rows_scanned, *reads.rows_scanned) + + async def execute_raw(self, query: str, *args: object) -> int: + return await self.database.execute_raw(query, *args) + + async def query_raw(self, query: str, *args: object) -> Sequence[Mapping[str, object]]: + explained: Final = await self.database.query_raw(f"EXPLAIN (ANALYZE, FORMAT JSON) {query}", *args) + plan: Final = _Explained.model_validate(explained[0]["QUERY PLAN"][0]).plan + self.rows_scanned = (*self.rows_scanned, plan.spend_log_rows_scanned()) + return await self.database.query_raw(query, *args) + + +@pytest.mark.parametrize( + "rows_per_session, page, newest_session, rows_scanned_per_read, total", + [ + pytest.param(1, 1, ("r", 20_000), (102,), (100, True), id="first-page"), + pytest.param(1, 3, ("r", 19_980), (102,), (100, True), id="third-page"), + pytest.param(10, 1, ("s", 1_999), (102, 1_171), (100, True), id="second-read-sized-by-the-first-reads-density"), + pytest.param(100, 1, ("s", 199), (102, 6_439, 12_878), (100, True), id="third-read-at-least-doubled"), + pytest.param(1_000, 1, ("s", 19), (102, 12_878, 20_000), (20, False), id="last-read-runs-out-of-rows"), + ], +) +async def test_a_newest_first_page_scans_only_the_rows_its_reads_ask_for( + rows_per_session: int, + page: int, + newest_session: tuple[str, int], + rows_scanned_per_read: tuple[int, ...], + total: tuple[int, bool], +) -> None: + async with _spend_logs_copy(*_generated_sessions(rows_per_session)) as database: + reads: Final = _ExplainedReads(database) + session_page: Final = await read_session_page( + reads, + where_clause=_COPY_WINDOW, + params=_COPY_WINDOW_PARAMS, + page=page, + page_size=10, + status=None, + sort_desc=True, + session_cursor=None, + cap=100, + ) + prefix, newest = newest_session + assert tuple(session.key for session in session_page.sessions) == tuple( + f"{prefix}{newest - n}" for n in range(10) + ) + assert (session_page.total, session_page.total_is_capped) == total + assert reads.rows_scanned == rows_scanned_per_read + + +async def test_a_page_cut_inside_a_tie_reads_on_until_the_tie_is_whole() -> None: + async with _spend_logs_copy(*_sessions_tied_at_the_newest_moment()) as database: + reads: Final = _ExplainedReads(database) + session_page: Final = await read_session_page( + reads, + where_clause=_COPY_WINDOW, + params=_COPY_WINDOW_PARAMS, + page=1, + page_size=5, + status=None, + sort_desc=True, + session_cursor=None, + cap=10, + ) + assert tuple(session.key for session in session_page.sessions) == ("s29", "s28", "s27", "s26", "s25") + assert reads.rows_scanned == (12, 24, 48) + + +@dataclass(frozen=True, slots=True) +class _ExplainedPrisma: + read_db: _ExplainedReads + + +async def test_a_pages_representatives_are_found_by_session_not_by_scanning_the_window() -> None: + async with _spend_logs_copy(*_generated_sessions(rows_per_session=10)) as database: + reads: Final = _ExplainedReads(database) + representatives: Final = await _fetch_session_representatives( + prisma_client=_ExplainedPrisma(reads), # pyright: ignore[reportArgumentType] # only .read_db is used + where_clause=_COPY_WINDOW, + sql_params=_COPY_WINDOW_PARAMS, + next_param_index=len(_COPY_WINDOW_PARAMS) + 1, + session_keys=(("s1999", "key-1"), ("s1998", "key-1")), + ) + assert tuple(row["request_id"] for row in representatives) == ("r20000", "r19990") + assert reads.rows_scanned == (20,), "only the two sessions' rows, not the window's 20,000" + + +async def test_a_page_number_far_past_the_cap_shows_no_session() -> None: + async with _spend_logs_copy(*_generated_sessions(rows_per_session=1)) as database: + session_page: Final = await read_session_page( + _ExplainedReads(database), + where_clause=_COPY_WINDOW, + params=_COPY_WINDOW_PARAMS, + page=9_300_000_000_000_000, + page_size=1000, + status=None, + sort_desc=True, + session_cursor=None, + cap=100, + ) + assert (session_page.sessions, session_page.total, session_page.total_is_capped) == ((), 100, True) + + +_OUTCOME_CALLS: Final = ( + _Call("agent", "asend_message", "failure", 10), + _Call("agent", "acompletion", "success", 20), + _Call("mcp", "acompletion", "failure", 5), + _Call("mcp", "call_mcp_tool", "success", 30), + _Call("unknown", "acompletion", None, 40), + _Call("failed", "acompletion", "success", 1), + _Call("failed", "acompletion", "failure", 50), + _Call("recovered", "acompletion", "failure", 2), + _Call("recovered", "acompletion", "success", 45), +) + + +@pytest.mark.parametrize( + "status, expected", + [("failure", ("failed", "mcp", "agent")), ("success", ("recovered", "unknown"))], +) +async def test_a_status_filter_keeps_sessions_whose_representative_call_has_that_status( + status: str, expected: tuple[str, ...] +) -> None: + """An agent message stands for its session, then the newest call that is not an MCP tool call, and a missing status + counts as success. The page stays ordered by each session's newest call.""" + async with _spend_logs_copy(*_calls(_OUTCOME_CALLS)) as database: + session_page: Final = await read_session_page( + _ExplainedReads(database), + where_clause=_COPY_WINDOW, + params=_COPY_WINDOW_PARAMS, + status=status, + page=1, + page_size=10, + sort_desc=True, + session_cursor=None, + cap=100, + ) + assert tuple(session.key for session in session_page.sessions) == expected + assert (session_page.total, session_page.total_is_capped) == (len(expected), False) diff --git a/tests/integration/streaming/test_interception_converted_stream_options.py b/tests/integration/streaming/test_interception_converted_stream_options.py index 0ca62d2f014..6fc38dfb440 100644 --- a/tests/integration/streaming/test_interception_converted_stream_options.py +++ b/tests/integration/streaming/test_interception_converted_stream_options.py @@ -5,6 +5,7 @@ import uuid from collections.abc import Callable, Generator, Iterator, Mapping, Sequence from contextlib import contextmanager from dataclasses import dataclass +from hashlib import sha256 from pathlib import Path from queue import SimpleQueue from types import MappingProxyType @@ -216,10 +217,13 @@ def scenario(rig: _Rig) -> Iterator[Scenario]: yield opened -def _deploy(rig: _Rig, scenario: Scenario, mode: iv.Mode, *, api_key: str = iv.AZURE_KEY) -> _Deployment: +def _deploy( + rig: _Rig, scenario: Scenario, mode: iv.Mode, *, api_key: str = iv.AZURE_KEY, priced: bool = False +) -> _Deployment: name: Final = iv.deployment(mode) + pricing: Final = {"input_cost_per_token": 0.001, "output_cost_per_token": 0.002} if priced else {} model: Final = scenario.model( - model=f"azure/{name}", api_base=rig.wire.url, api_key=api_key, api_version=iv.API_VERSION + model=f"azure/{name}", api_base=rig.wire.url, api_key=api_key, api_version=iv.API_VERSION, **pricing ) return _Deployment(model, name) @@ -325,6 +329,46 @@ def _assert_response_landed_once(model: str, identity: str) -> None: assert row["status"] == "success" and rv.same_response(string_value(row["request_id"]), identity), row +def _assert_single_model_spend_for_key(key: str, call_type: str, *, expected_searches: int = 1) -> None: + digest: Final = sha256(key.encode()).hexdigest() + observed: Final = eventually( + lambda: ( + read_rows( + "SELECT status, spend, request_id, call_type, model_group, session_id " + 'FROM "LiteLLM_SpendLogs" WHERE api_key = %s AND status = %s', + (digest, "success"), + ), + read_rows('SELECT spend FROM "LiteLLM_VerificationToken" WHERE token = %s', (digest,)), + ), + lambda values: ( + bool(values[0]) + and ( + len(values[0]) > expected_searches + 1 + or ( + len(values[0]) == expected_searches + 1 + and len(values[1]) == 1 + and values[1][0]["spend"] is not None + and float(str(values[1][0]["spend"])) + == pytest.approx(sum(float(str(row["spend"])) for row in values[0])) + ) + ) + ), + seconds=70, + ) + rows, balance = observed + model_rows: Final = [row for row in rows if row["call_type"] == call_type] + search_rows: Final = [row for row in rows if row["call_type"] == "asearch"] + spend: Final = sum(float(str(row["spend"])) for row in rows) + assert ( + len(rows) == expected_searches + 1 + and len(model_rows) == 1 + and len(search_rows) == expected_searches + and float(str(model_rows[0]["spend"])) > 0 + and all(float(str(row["spend"])) > 0 for row in search_rows) + and float(str(balance[0]["spend"])) == pytest.approx(spend) + ), (rows, balance) + + def _openai(rig: _Rig) -> openai.OpenAI: return openai.OpenAI(base_url=f"{rig.base_url}/v1", api_key=rig.gateway.key, max_retries=0) @@ -402,6 +446,31 @@ def test_raw_chat_stream_without_stream_options_answers_without_a_usage_chunk(ri _assert_search_turn(rig, deployment, identity) +def test_chat_stream_through_web_search_has_single_spend_owner(rig: _Rig, scenario: Scenario) -> None: + deployment: Final = _deploy(rig, scenario, "search", priced=True) + key: Final = scenario.key(models=[deployment.model]) + stream: Final = _post(rig, "/v1/chat/completions", _chat_body(deployment), key=key) + identity: Final = _assert_restreamed(stream, iv.answer(deployment.name), usage=None) + _assert_search_turn(rig, deployment, identity) + _assert_single_model_spend_for_key(key, "acompletion") + + +def test_multi_round_chat_stream_through_web_search_bills_each_search( + rig: _Rig, scenario: Scenario +) -> None: + deployment: Final = _deploy(rig, scenario, "multi-search", priced=True) + key: Final = scenario.key(models=[deployment.model]) + stream: Final = _post(rig, "/v1/chat/completions", _chat_body(deployment), key=key) + identity: Final = _assert_restreamed(stream, iv.answer(deployment.name), usage=None) + received: Final = _upstream(rig, deployment) + _assert_upstream(received, model_calls=3, searches=2) + assert [search["query"] for search in received.searches] == [ + iv.query(deployment.name), + iv.query(deployment.name, turn=2), + ], received.searches + _assert_single_model_spend_for_key(key, "acompletion", expected_searches=2) + + def test_openai_sdk_responses_stream_through_web_search_keeps_stream_options_off_azure( rig: _Rig, scenario: Scenario ) -> None: @@ -454,6 +523,31 @@ def test_raw_responses_stream_without_stream_options_answers(rig: _Rig, scenario _assert_response_landed_once(deployment.model, identity) +def test_responses_stream_through_web_search_has_single_spend_owner(rig: _Rig, scenario: Scenario) -> None: + deployment: Final = _deploy(rig, scenario, "search", priced=True) + key: Final = scenario.key(models=[deployment.model]) + stream: Final = _post(rig, "/v1/responses", _responses_body(deployment), key=key) + _assert_responses_restreamed(stream, iv.answer(deployment.name)) + _assert_upstream(_upstream(rig, deployment), model_calls=2, searches=1) + _assert_single_model_spend_for_key(key, "aresponses") + + +def test_multi_round_responses_stream_through_web_search_bills_each_search( + rig: _Rig, scenario: Scenario +) -> None: + deployment: Final = _deploy(rig, scenario, "multi-search", priced=True) + key: Final = scenario.key(models=[deployment.model]) + stream: Final = _post(rig, "/v1/responses", _responses_body(deployment), key=key) + _assert_responses_restreamed(stream, iv.answer(deployment.name)) + received: Final = _upstream(rig, deployment) + _assert_upstream(received, model_calls=3, searches=2) + assert [search["query"] for search in received.searches] == [ + iv.query(deployment.name), + iv.query(deployment.name, turn=2), + ], received.searches + _assert_single_model_spend_for_key(key, "aresponses", expected_searches=2) + + def test_openai_sdk_chat_without_streaming_through_web_search_answers_in_json(rig: _Rig, scenario: Scenario) -> None: deployment: Final = _deploy(rig, scenario, "search") completion: Final = _openai(rig).chat.completions.create( @@ -754,60 +848,36 @@ def test_wrong_azure_key_surfaces_azures_401(rig: _Rig, scenario: Scenario) -> N assert len(_upstream(rig, deployment).model_calls) == 1 -def _tool_call(call: Mapping[str, JsonValue]) -> tuple[str, Mapping[str, JsonValue]]: - function: Final = object_value(call["function"]) - return string_value(function["name"]), iv.JSON_OBJECT.validate_json(string_value(function["arguments"])) +def _assert_failed_once(call_id: str, *, spend: float) -> None: + rows: Final = eventually( + lambda: read_rows('SELECT status, spend FROM "LiteLLM_SpendLogs" WHERE litellm_call_id = %s', (call_id,)), + lambda found: len(found) >= 1, + seconds=70, + ) + assert [row["status"] for row in rows] == ["failure"], rows + assert float(rows[0]["spend"]) == pytest.approx(spend), rows -def _stream_choices(stream: _Stream) -> Iterator[Mapping[str, JsonValue]]: - for frame in stream.frames: - yield from rv.ITEMS.validate_python(frame.get("choices") or []) - - -def _streamed_tool_calls(stream: _Stream) -> Iterator[tuple[str, Mapping[str, JsonValue]]]: - for choice in _stream_choices(stream): - yield from map( - _tool_call, rv.ITEMS.validate_python(object_value(choice.get("delta") or {}).get("tool_calls") or []) - ) - - -def _handed_back(deployment: _Deployment) -> list[tuple[str, Mapping[str, JsonValue]]]: - return [(iv.SEARCH_TOOL, {"query": iv.query(deployment.name)})] - - -def _assert_succeeded_once(model: str, identity: str) -> None: - rows: Final = _spend_rows(model, 1) - assert [string_value(row["request_id"]) for row in rows if row["status"] == "success"] == [identity], rows - - -def test_failed_follow_up_call_hands_the_search_tool_call_back_with_its_usage(rig: _Rig, scenario: Scenario) -> None: - deployment: Final = _deploy(rig, scenario, "followup-fails") - stream: Final = _chat(rig, _chat_body(deployment, extra={**_NO_CACHE, "stream_options": dict(_USAGE)})) - assert stream.status == 200 and stream.content == "", stream.text - assert list(_streamed_tool_calls(stream)) == _handed_back(deployment), stream.text - finished: Final = [choice["finish_reason"] for choice in _stream_choices(stream) if choice.get("finish_reason")] - assert finished == ["tool_calls"], stream.text - assert [_totals(usage) for usage in stream.usages] == [iv.FIRST_USAGE["total_tokens"]], stream.text - (identity,) = stream.ids +@pytest.mark.parametrize("stream", [True, False], ids=["stream", "json"]) +def test_failed_follow_up_call_answers_with_the_providers_error_instead_of_the_search_tool_call( + rig: _Rig, scenario: Scenario, stream: bool +) -> None: + deployment: Final = _deploy( + rig, scenario, "followup-fails", priced=True + ) + extra: Final = {**_NO_CACHE, "stream_options": dict(_USAGE)} if stream else _NO_CACHE + body: Final = _chat_body(deployment, stream=stream, extra=extra) + response: Final = rig.gateway.request("POST", "/v1/chat/completions", body) + assert response.status_code == 500 and iv.FOLLOWUP_FAILURE in response.text, response.text + assert iv.SEARCH_TOOL not in response.text, response.text _assert_upstream(_upstream(rig, deployment), model_calls=2, searches=1) - _assert_succeeded_once(deployment.model, identity) + _assert_failed_once( + response.headers["x-litellm-call-id"], + spend=iv.FIRST_USAGE["prompt_tokens"] * 0.001 + iv.FIRST_USAGE["completion_tokens"] * 0.002, + ) assert rig.gateway.chat(_deploy(rig, scenario, "plain").model)["object"] == "chat.completion" -def test_failed_follow_up_call_on_a_json_request_hands_the_search_tool_call_back(rig: _Rig, scenario: Scenario) -> None: - deployment: Final = _deploy(rig, scenario, "followup-fails") - response: Final = rig.gateway.request("POST", "/v1/chat/completions", _chat_body(deployment, stream=False)) - assert response.status_code == 200, response.text - body: Final = iv.JSON_OBJECT.validate_json(response.content) - (choice,) = rv.ITEMS.validate_python(body["choices"]) - calls: Final = rv.ITEMS.validate_python(object_value(choice["message"])["tool_calls"]) - assert [_tool_call(call) for call in calls] == _handed_back(deployment), body - assert choice["finish_reason"] == "tool_calls", body - assert _totals(object_value(body["usage"])) == iv.FIRST_USAGE["total_tokens"], body - _assert_upstream(_upstream(rig, deployment), model_calls=2, searches=1) - _assert_succeeded_once(deployment.model, string_value(body["id"])) - - def test_search_outage_still_restreams_the_follow_up_answer(rig: _Rig, scenario: Scenario) -> None: deployment: Final = _deploy(rig, scenario, "search-down") stream: Final = _chat(rig, _chat_body(deployment, extra={**_NO_CACHE, "stream_options": dict(_USAGE)})) diff --git a/tests/integration/translation/chat_completions/bases/bedrock_converse.py b/tests/integration/translation/chat_completions/bases/bedrock_converse.py index 6540bd09d64..777e0d04db5 100644 --- a/tests/integration/translation/chat_completions/bases/bedrock_converse.py +++ b/tests/integration/translation/chat_completions/bases/bedrock_converse.py @@ -1407,6 +1407,7 @@ CLAUDE_SONNET_5_TEST_CASE: Final = TranslationTestCase( expected_provider_endpoint="/model/us.anthropic.claude-sonnet-5/converse", expected_provider_headers={"authorization": "Bearer synthetic-bedrock-key", "content-type": "application/json"}, expected_provider_request={ + "additionalModelResponseFieldPaths": ["/usage/output_tokens_details"], "messages": [{"role": "user", "content": [{"text": "Say hello."}]}], "inferenceConfig": {"maxTokens": 64}, "system": [{"text": "You are a terse assistant."}], diff --git a/tests/integration/translation/chat_completions/response_format/test_chat_completions_response_format_anthropic.py b/tests/integration/translation/chat_completions/response_format/test_chat_completions_response_format_anthropic.py index 07e4358ff97..5cb7a7eee8e 100644 --- a/tests/integration/translation/chat_completions/response_format/test_chat_completions_response_format_anthropic.py +++ b/tests/integration/translation/chat_completions/response_format/test_chat_completions_response_format_anthropic.py @@ -6,7 +6,7 @@ import pytest from integration._support.client import Gateway from integration._support.provider import SharedProvider from integration.translation.case import TranslationTestCase -from integration.translation.chat_completions.bases.anthropic import CLAUDE_HAIKU_5_5_TEST_CASE +from integration.translation.chat_completions.bases.anthropic import CLAUDE_OPUS_4_8_TEST_CASE from integration.translation.runner import assert_translation PLACE_SCHEMA: Final = { @@ -24,25 +24,25 @@ PLACE_TOOL_USE: Final = { "caller": {"type": "direct"}, } -CLAUDE_HAIKU_5_5_JSON_SCHEMA_TEST_CASE: Final = replace( - CLAUDE_HAIKU_5_5_TEST_CASE, +CLAUDE_OPUS_4_8_JSON_SCHEMA_TEST_CASE: Final = replace( + CLAUDE_OPUS_4_8_TEST_CASE, scenario="json_schema", litellm_request={ - "model": "anthropic/claude-haiku-5-5", + "model": "anthropic/claude-opus-4-8", "max_tokens": 128, "messages": [{"role": "user", "content": PLACE_PROMPT}], "response_format": {"type": "json_schema", "json_schema": {"name": "place", "schema": PLACE_SCHEMA}}, "cache": {"no-cache": True}, }, expected_provider_request={ - "model": "claude-haiku-5-5", + "model": "claude-opus-4-8", "messages": [{"role": "user", "content": [{"type": "text", "text": PLACE_PROMPT}]}], "max_tokens": 128, "tool_choice": {"name": "json_tool_call", "type": "tool"}, "tools": [{"name": "json_tool_call", "input_schema": PLACE_SCHEMA}], }, mock_provider_response={ - "model": "claude-haiku-5-5", + "model": "claude-opus-4-8", "id": "msg_011CgCoP2UR3vcM5ZWmEBd8D", "type": "message", "role": "assistant", @@ -68,7 +68,7 @@ CLAUDE_HAIKU_5_5_JSON_SCHEMA_TEST_CASE: Final = replace( "id": ANY, "created": ANY, "object": "chat.completion", - "model": "anthropic/claude-haiku-5-5", + "model": "anthropic/claude-opus-4-8", "choices": [ { "finish_reason": "stop", @@ -97,11 +97,11 @@ CLAUDE_HAIKU_5_5_JSON_SCHEMA_TEST_CASE: Final = replace( }, ) -CLAUDE_HAIKU_5_5_JSON_SCHEMA_TOOL_NAMED_ENVELOPE_TEST_CASE: Final = replace( - CLAUDE_HAIKU_5_5_JSON_SCHEMA_TEST_CASE, +CLAUDE_OPUS_4_8_JSON_SCHEMA_TOOL_NAMED_ENVELOPE_TEST_CASE: Final = replace( + CLAUDE_OPUS_4_8_JSON_SCHEMA_TEST_CASE, scenario="json_schema_tool_named_envelope", mock_provider_response={ - **CLAUDE_HAIKU_5_5_JSON_SCHEMA_TEST_CASE.mock_provider_response, + **CLAUDE_OPUS_4_8_JSON_SCHEMA_TEST_CASE.mock_provider_response, "content": [ { **PLACE_TOOL_USE, @@ -114,7 +114,7 @@ CLAUDE_HAIKU_5_5_JSON_SCHEMA_TOOL_NAMED_ENVELOPE_TEST_CASE: Final = replace( @pytest.mark.parametrize( "case", - [CLAUDE_HAIKU_5_5_JSON_SCHEMA_TEST_CASE, CLAUDE_HAIKU_5_5_JSON_SCHEMA_TOOL_NAMED_ENVELOPE_TEST_CASE], + [CLAUDE_OPUS_4_8_JSON_SCHEMA_TEST_CASE, CLAUDE_OPUS_4_8_JSON_SCHEMA_TOOL_NAMED_ENVELOPE_TEST_CASE], ids=lambda case: case.id, ) def test_chat_completions_response_format_anthropic( diff --git a/tests/integration/translation/chat_completions/streaming/test_chat_completions_streaming_anthropic.py b/tests/integration/translation/chat_completions/streaming/test_chat_completions_streaming_anthropic.py index fca8de69f00..a41752a96cf 100644 --- a/tests/integration/translation/chat_completions/streaming/test_chat_completions_streaming_anthropic.py +++ b/tests/integration/translation/chat_completions/streaming/test_chat_completions_streaming_anthropic.py @@ -6,7 +6,7 @@ from integration._support.client import Gateway from integration._support.provider import SharedProvider from integration.translation.case import SSEFrame, StreamingTranslationTestCase from integration.translation.chat_completions.bases.anthropic import ( - CLAUDE_HAIKU_5_5_TEST_CASE, + CLAUDE_OPUS_4_8_TEST_CASE, CLAUDE_SONNET_5_5_TEST_CASE, ) from integration.translation.runner import assert_streaming_translation @@ -158,27 +158,27 @@ def _place_chunk(delta: dict[str, JsonValue]) -> SSEFrame: "id": ANY, "object": "chat.completion.chunk", "created": ANY, - "model": "anthropic/claude-haiku-5-5", + "model": "anthropic/claude-opus-4-8", "choices": [{"index": 0, "delta": delta}], } ) -CLAUDE_HAIKU_5_5_JSON_SCHEMA_CUT_STREAM_TEST_CASE: Final = StreamingTranslationTestCase( +CLAUDE_OPUS_4_8_JSON_SCHEMA_CUT_STREAM_TEST_CASE: Final = StreamingTranslationTestCase( scenario="json_schema_cut_stream", - litellm_endpoint=CLAUDE_HAIKU_5_5_TEST_CASE.litellm_endpoint, + litellm_endpoint=CLAUDE_OPUS_4_8_TEST_CASE.litellm_endpoint, litellm_request={ - "model": "anthropic/claude-haiku-5-5", + "model": "anthropic/claude-opus-4-8", "max_tokens": 128, "messages": [{"role": "user", "content": PLACE_PROMPT}], "response_format": {"type": "json_schema", "json_schema": {"name": "place", "schema": PLACE_SCHEMA}}, "cache": {"no-cache": True}, "stream": True, }, - expected_provider_endpoint=CLAUDE_HAIKU_5_5_TEST_CASE.expected_provider_endpoint, - expected_provider_headers=CLAUDE_HAIKU_5_5_TEST_CASE.expected_provider_headers, + expected_provider_endpoint=CLAUDE_OPUS_4_8_TEST_CASE.expected_provider_endpoint, + expected_provider_headers=CLAUDE_OPUS_4_8_TEST_CASE.expected_provider_headers, expected_provider_request={ - "model": "claude-haiku-5-5", + "model": "claude-opus-4-8", "messages": [{"role": "user", "content": [{"type": "text", "text": PLACE_PROMPT}]}], "max_tokens": 128, "tool_choice": {"name": "json_tool_call", "type": "tool"}, @@ -191,7 +191,7 @@ CLAUDE_HAIKU_5_5_JSON_SCHEMA_CUT_STREAM_TEST_CASE: Final = StreamingTranslationT data={ "type": "message_start", "message": { - "model": "claude-haiku-5-5", + "model": "claude-opus-4-8", "id": "msg_011CgCoP5RkexwE6N7PRZEca", "type": "message", "role": "assistant", @@ -263,7 +263,7 @@ CLAUDE_HAIKU_5_5_JSON_SCHEMA_CUT_STREAM_TEST_CASE: Final = StreamingTranslationT "id": ANY, "object": "chat.completion", "created": ANY, - "model": "anthropic/claude-haiku-5-5", + "model": "anthropic/claude-opus-4-8", "choices": [ { "index": 0, @@ -276,7 +276,7 @@ CLAUDE_HAIKU_5_5_JSON_SCHEMA_CUT_STREAM_TEST_CASE: Final = StreamingTranslationT @pytest.mark.parametrize( "case", - [CLAUDE_SONNET_5_5_STREAMING_TEST_CASE, CLAUDE_HAIKU_5_5_JSON_SCHEMA_CUT_STREAM_TEST_CASE], + [CLAUDE_SONNET_5_5_STREAMING_TEST_CASE, CLAUDE_OPUS_4_8_JSON_SCHEMA_CUT_STREAM_TEST_CASE], ids=lambda case: case.id, ) def test_chat_completions_streaming_anthropic( diff --git a/tests/integration/translation/decisions/bases/parallel_ai.py b/tests/integration/translation/decisions/bases/parallel_ai.py new file mode 100644 index 00000000000..14e9cd6fc43 --- /dev/null +++ b/tests/integration/translation/decisions/bases/parallel_ai.py @@ -0,0 +1,257 @@ +from typing import Final + +from integration.translation.case import TranslationTestCase +from pydantic import JsonValue + +"""Provider request and reply shape from https://docs.parallel.ai/api-reference/decisions/make-web-grounded-typed-decisions. Mock reply captured live on 2026-10-31. +""" +_CITATIONS: Final[list[JsonValue]] = [ + { + "url": "https://access.redhat.com/solutions/7108129", + "title": 'NFS client hangs and "nfs4_handle_delegation_recall_error" found in dmesg. - Red Hat Customer Portal', + "excerpts": [ + 'NFS client hangs and "nfs4_handle_delegation_recall_error" found in dmesg.\n\nSolution Verified - Updated 2026-06-18T01:07:40+00:00 -\nEnglish\n* No translations currently exist.\n\nIssue\n\n* NFS client hangs while returning delegations.\n* Below delegation recall errors may be reported in dmesg:\nNFS: nfs4_handle_delegation_recall_error: unhandled error -512\nNFS: nfs4_handle_delegation_recall_error: unhandled error -10024\n* We have a hanging process, it\'s using data ontop of a mounted NFS export. The fcntl() system call issued by a user process has not returned, The user process processing does not finish - usually it finishes within 2 minutes.\n\nEnvironment\n\n* Red Hat Enterprise Linux (RHEL) 8, all minor releases\n* kernel:\n* rhel8.4: kernels before 4.18.0-305.194.1.el8_4 affected\n* rhel8.10: kernels before 4.18.0-553.37.1.el8_10 affected\n* NFSv4' + ], + }, + { + "url": "https://github.com/moby/buildkit/issues/2804", + "title": "GitHub cache exporter (`type=gha`) hangs reletively low number of cache reads/writes, satirating api limits/triggering throttling. · Issue #2804 · moby/buildkit · GitHub", + "excerpts": [ + 'Copy link\nOpen\nOpen\nGitHub cache exporter ( type=gha ) hangs reletively low number of cache reads/writes, satirating api limits/triggering throttling. #2804\nCopy link\n\nDescription\n\n@bendavies\nbendavies\nopened on Apr 13, 2022\nIssue body actions\n\nBehaviour\n\nCache operations using type=gha will start hanging after a relavatively low number of cache reads/writes.\nWe are a small team (5 devs) and are hitting these limits constantly on our main repository. Not exactly high throughput.\n\n...\n\nCache reads and writes go towards saturating the limit, and both are affected by this throttling.\n@dhadka mentions there is a limit of about "150 cache requests in 5 minutes", and seems about right: #2276 (comment)\n\nExpected behaviour\n\nI don\'t know, but the current behaviour of hanging is not great. there is no feedback as to what is hanging resulting in the user just being confused.' + ], + }, + { + "url": "https://github.com/huginn/huginn/issues/2963", + "title": "WebsiteAgent hangs on a specific url, never finishes job or times out · Issue #2963 · huginn/huginn · GitHub", + "excerpts": [ + 'WebsiteAgent hangs on a specific url, never finishes job or times out\n\n* Page: GitHub issue\n* URL: https://github.com/huginn/huginn/issues/2963\n* State: open\n* Author: BoKKeR\n* Created: 2021-03-14T16:42:01Z\n* Updated: 2021-03-16T19:09:24Z\n* Repository: huginn/huginn\n* Number: #2963\n* Comments: 1\nI know it might be controversial but I am trying to get a new GPU for a while. Wanted to setup a monitor for when the stock on amd.com changes. But the site just won\'t load. The WebsiteAgent gets stuck in\nFetching https://www.amd.com/de/direct-buy/se\nThe only way to stop it is by stopping the container. As I am running the service in a container I cant find any of the debug log locations. Can anyone else try if they are encountering the same error?\n{\n "debug": "true",\n "expected_update_period_in_days": "2",\n "url": "https://www.amd.com/de/direct-buy/se",\n "type": "html",' + ], + }, + { + "url": "https://github.com/mozilla-firefox/firefox-crb/blob/main/docs/bug-mgmt/guides/severity.md", + "title": "firefox-crb/docs/bug-mgmt/guides/severity.md at main · mozilla-firefox/firefox-crb · GitHub", + "excerpts": [ + "We use the severity field in Bugzilla to indicate the scope of a bug's effect on Firefox.\nThe field is display alongside the bug's priority.\n\nValues\n\nSeverity levels and their definitions are enumerated at https://wiki.mozilla.org/BMO/UserGuide/BugFields#bug_severity.\nBy default, new bugs have a severity of --.\n\nExamples of S1 bugs\n\n* WebExtensions disabled for all users\n* Web search not working from URL bar\n* Crashes with data loss\n\nExamples of S2 bugs\n\nBugs that could reasonably be expected to cause a Firefox user to switch browsers, either because the severity is bad enough, or the frequency of occurrence is high enough.\n* Bug 1640441 - Slack hangs indefinitely in a onResize loop" + ], + }, + { + "url": "https://github.com/n0-computer/iroh/issues/4604", + "title": "Endpoint::close hangs forever if the tokio runtime gets dropped while the connection is open · Issue #4604 · n0-computer/iroh · GitHub", + "excerpts": [ + "@alpergundogdu\nalpergundogdu\nopened on Oct 14, 2026\nIssue body actions\nDescribe the bug\nAfter opening a connection from inside a short-lived tokio runtime, and dropping the runtime while the connection is still open, Endpoint::close() never returns.\nIn my repro it hangs reliably; when I keep the runtime open, it closes instantly.\nLocal repro/test (has the control tests too): https://github.com/decdn/iroh-tests/blob/main/tests/bug_endpoint_close_after_runtime_drop.rs\n\n...\n\nIf spawning on the caller's runtime is intended, a note on Endpoint::connect saying the driver lives there would have saved us a lot of time. (Maybe it's an expectation/documentation issue?)\nIroh\nVersion: iroh 1.3.0, noq 1.3.0\nEndpoint configuration: bound to 127.0.0.1, no relays.\nPlatform(s)\nDesktop:\n\n...\n\nSorry @flub , that was unclear: the endpoint's runtime stays alive, and close() is called from it. Only a separate short-lived runtime that runs connect() gets dropped." + ], + }, + { + "url": "https://bugzilla.mozilla.org/show_bug.cgi?id=1640441", + "title": "1640441 - Slack hangs indefinitely in a onResize loop", + "excerpts": [ + "Closed Bug 1640441 Opened 6 years ago Closed 6 years ago\n\nSlack hangs indefinitely in a on Resize loop\n\nCategories\n\n(Web Compatibility :: Site Reports, defect, P1)\n\nProduct:\nWeb Compatibility ▾\nComponent:\nSite Reports ▾\nType:\ndefect\nPriority:\nP1 Severity:\nS2\n\nTracking\n\n(Not tracked)\n\nStatus:\nRESOLVED FIXED\n\nPeople\n\n(Reporter: Harald, Assigned: emilio)\n\nReferences\n\n(Depends on 1 open bug)\n\nDetails\n\n(Keywords: enterprise, perf, webcompat:site-wait)\n\nAttachments\n\n(1 file, 1 obsolete file)\n\n|relevant unminified code.\n6 years ago Emilio Cobos Álvarez [:emilio]\n* 13.50 KB,\n\n...\n\n* Hover over the link\n* ... tab immediately becomes unresponsive ...\nThis may well be a bug in slack, but IMO it's still on us to try and fix what's going on. When it happens, it affects not only Slack but my entire Firefox session. This is a serious usability issue -- I'm now at the point of restarting Firefox several times a day because of this bug, if" + ], + }, + { + "url": "https://www.ibm.com/support/pages/cognos-business-intelligence-1022-fix-lists", + "title": "Cognos Business Intelligence 10.2.2 Fix Lists", + "excerpts": [ + 'IBM Support \n\nCognos Business Intelligence 10.2.2 Fix Lists\n\nRelease Notes\n\nAbstract\n\nA comprehensive list of defect corrections for major releases, refresh packs and fix packs of Cognos Business Intelligence 10.2.2.\nDetails of the APARs listed below can be accessed by clicking the link for the APAR number. If you have questions about a particular defect, please contact Customer Support.\n\n...\n\n* PI05143 | MULTIPLE VALUES IN CONTEXT FILTERS CAUSE A CROSSTAB REPORT TO SHOW DASH "-" INSTEAD OF CORRECT VALUES\n* PI05166 | QE-DEF-0359 The query contains a reference to at least one object that does not exist\n* PI05233 | Export deployments from 8.4.1 with export folder or package tasks in Content Administration contain unknown content steps\n\n...\n\n* PI08523 | Progressive Chart - Incorrect Colours when "Reverse Catagory Order" = True\n* PI08585 | Cognos hangs when starting against a Content Store from previous version (upgrade) and using SSL gateway UR' + ], + }, + { + "url": "https://josm.eu/ticket/8175", + "title": "\n #8175 ([PATCH] Cadastre grab query sometimes hangs completely)\n – JOSM\n\n ", + "excerpts": [ + 'Opened 14 years ago\nClosed 14 years ago\nLast modified 14 years ago\n\n#8175 closed defect ( fixed )\n\n[PATCH] Cadastre grab query sometimes hangs completely\n\n* Reported by: | Don-vip | Owned by: | pieren\n* Priority: | normal | Milestone: | \n* Component: | Plugin cadastre-fr | Version: | \n* Keywords: | | Cc: | \n\nDescription\n\nDuring cadastre grab, the HTTP connection with the WMS server sometimes completely hangs (the progress dialog is frozen and cancel button does not work).\nThe only solution is to restart JOSM to have a clean state and grab the cadastre again. We had a similar problem with history request ( #7640 ) when dealing with the API and solved it in [r5324](https://josm.eu/changeset/5324/josm "fix #7640 - History query will not cancel or timeout\n\n...\n\nby Don-vip , 14 years ago\n\n* Attachment: | 8175.patch \u200b added\n\ncomment:1 by Don-vip , 14 years ago' + ], + }, + { + "url": "https://bugzilla.mozilla.org/show_bug.cgi?id=1749908", + "title": "1749908 - Infinite loop in HTTP3 hangs socket thread - Bugzilla", + "excerpts": [ + "Closed Bug 1749908 Opened 4 years ago Closed 4 years ago\n\nInfinite loop in HTTP3 hangs socket thread\n\nCategories\n\n(Core :: Networking, defect)\n\nProduct:\nCore ▾\nComponent:\nNetworking ▾\nPlatform:\nDesktop\nAll\nType:\ndefect\nPriority:\nNot set Severity:\n--\n\nTracking\n\n( )\n\nStatus:\nVERIFIED DUPLICATE of bug 1749910\n\nPeople\n\n(Reporter: heftig, Unassigned)\n\nDetails\n\nBottom ↓\nTags ▾\nTimeline ▾\n| |Jan Alexander Steffens [:heftig]\n* Reporter | \n* ### Description\n•\n* 4 years ago\n* \nWhile browsing, pages suddenly stopped loading.\n\n...\n\nIt's not related to a specific version, we're getting reports ESR is even affected. Suspicion is around some long existing HTTP3 bug that's being triggered by an external service updating.\n\n...\n\nI agree it is not the root cause but it certainly caused a massive problem for many users of Firefox, the majority of whom are opted-in by default. If they had not been, they would not have been affected." + ], + }, + { + "url": "https://bugzilla.mozilla.org/show_bug.cgi?id=1748414", + "title": "1748414 - Firefox 94 sometimes hangs on TLSv1.3 requests", + "excerpts": [ + "Closed Bug 1748414 Opened 4 years ago Closed 4 years ago\n\nFirefox 94 sometimes hangs on TLSv1 .3 requests\n\nCategories\n\n(Core :: Networking: HTTP, defect)\n\nProduct:\nCore ▾\nComponent:\nNetworking: HTTP ▾\nVersion:\nFirefox 94\nType:\ndefect\nPriority:\nNot set Severity:\n--\n\nTracking\n\n( )\n\nStatus:\nRESOLVED DUPLICATE of bug 1740856\n\nPeople\n\n(Reporter: code, Unassigned)\n\nDetails\n\nBottom ↓\n\n...\n\nSteps to reproduce:\nIn the beginning of November, colleagues started to experience hangs of 1 to 1.5 minutes when working with our own web app. We use latest official releases for Windows, Ubuntu and FreeBSD. The problems exist for all plattforms and very likely started with Firefox 94.\nActual results:\nSometimes while interacting normally with our web app, a request hangs for a long time (up to 1.5 minutes; but usually succeeds). This typically happens on POST requests." + ], + }, +] +DECISION_TEST_CASE: Final = TranslationTestCase( + scenario="basic", + litellm_endpoint="/v1/decisions", + litellm_request={ + "model": "parallel_ai/decision", + "input": "Ticket (billing): The export job hangs at 99% and never finishes", + "questions": [ + {"type": "predicate", "name": "defect", "instructions": "Is this a defect?"}, + { + "type": "choice", + "name": "severity", + "instructions": "How severe is it?", + "choices": [ + {"value": "low", "description": "cosmetic"}, + {"value": "high", "description": "blocks users"}, + ], + }, + { + "type": "score", + "name": "confidence", + "instructions": "How sure are you?", + "levels": [{"label": "unsure"}, {"label": "sure"}], + }, + ], + "cache": {"no-cache": True}, + }, + expected_provider_endpoint="/v1/decisions", + expected_provider_headers={"x-api-key": "synthetic-parallel-key", "content-type": "application/json"}, + expected_provider_request={ + "mode": "fast", + "state": "Ticket (billing): The export job hangs at 99% and never finishes", + "questions": { + "defect": {"type": "noul", "instructions": "Is this a defect?"}, + "severity": { + "type": "choice", + "instructions": "How severe is it?", + "criteria": {"low": "cosmetic", "high": "blocks users"}, + }, + "confidence": {"type": "score", "instructions": "How sure are you?", "criteria": ["unsure", "sure"]}, + }, + }, + mock_provider_response={ + "mode": "fast", + "answers": { + "defect": {"type": "noul", "noul": 0.6442559258537284}, + "severity": { + "type": "choice", + "choice": "high", + "probabilities": {"low": 0.1616964510265985, "high": 0.8383035489734014}, + "confidence": 0.6766070979468028, + }, + "confidence": { + "type": "score", + "score": 0.25195637565890455, + "legend": {"0": "unsure", "1": "sure"}, + "probabilities": {"0": 0.7480436243410955, "1": 0.25195637565890455}, + "confidence": 0.4960872486821909, + }, + }, + "usage": {"input_tokens": 3166, "output_tokens": 0}, + "citations": _CITATIONS, + "decision_id": "decisions_9fd99def328ed16256c11df297dea899", + }, + expected_litellm_response={ + "model": "decision", + "answers": [ + {"type": "predicate", "name": "defect", "probability": 0.6442559258537284}, + { + "type": "choice", + "name": "severity", + "choice": "high", + "probabilities": [ + {"value": "low", "probability": 0.1616964510265985}, + {"value": "high", "probability": 0.8383035489734014}, + ], + "confidence": 0.6766070979468028, + }, + { + "type": "score", + "name": "confidence", + "score": 0.25195637565890455, + "probabilities": [ + {"value": 0, "label": "unsure", "probability": 0.7480436243410955}, + {"value": 1, "label": "sure", "probability": 0.25195637565890455}, + ], + "confidence": 0.4960872486821909, + }, + ], + "usage": { + "input_tokens": 3166, + "input_tokens_details": {"cached_tokens": 0, "cache_write_tokens": 0}, + "output_tokens": 0, + "output_tokens_details": {"reasoning_tokens": 0}, + "total_tokens": 3166, + }, + "mode": "fast", + "citations": _CITATIONS, + "decision_id": "decisions_9fd99def328ed16256c11df297dea899", + }, +) +DECISION_SYSTEMONE_TEST_CASE: Final = TranslationTestCase( + scenario="systemone", + litellm_endpoint="/v1/systemone", + litellm_request={ + "model": "parallel_ai/decision", + "state": "Ticket (billing): The export job hangs at 99% and never finishes", + "questions": { + "defect": {"type": "noul", "instructions": "Is this a defect?"}, + "severity": { + "type": "choice", + "instructions": "How severe is it?", + "criteria": {"low": "cosmetic", "high": "blocks users"}, + }, + "confidence": {"type": "score", "instructions": "How sure are you?", "criteria": ["unsure", "sure"]}, + }, + "cache": {"no-cache": True}, + }, + expected_provider_endpoint="/v1/decisions", + expected_provider_headers={"x-api-key": "synthetic-parallel-key", "content-type": "application/json"}, + expected_provider_request={ + "mode": "fast", + "state": "Ticket (billing): The export job hangs at 99% and never finishes", + "questions": { + "defect": {"type": "noul", "instructions": "Is this a defect?"}, + "severity": { + "type": "choice", + "instructions": "How severe is it?", + "criteria": {"low": "cosmetic", "high": "blocks users"}, + }, + "confidence": {"type": "score", "instructions": "How sure are you?", "criteria": ["unsure", "sure"]}, + }, + }, + mock_provider_response={ + "mode": "fast", + "answers": { + "defect": {"type": "noul", "noul": 0.6442559258537284}, + "severity": { + "type": "choice", + "choice": "high", + "probabilities": {"low": 0.1616964510265985, "high": 0.8383035489734014}, + "confidence": 0.6766070979468028, + }, + "confidence": { + "type": "score", + "score": 0.25195637565890455, + "legend": {"0": "unsure", "1": "sure"}, + "probabilities": {"0": 0.7480436243410955, "1": 0.25195637565890455}, + "confidence": 0.4960872486821909, + }, + }, + "usage": {"input_tokens": 3166, "output_tokens": 0}, + "citations": _CITATIONS, + "decision_id": "decisions_9fd99def328ed16256c11df297dea899", + }, + expected_litellm_response={ + "model": "decision", + "answers": { + "defect": {"type": "noul", "noul": 0.6442559258537284}, + "severity": { + "type": "choice", + "choice": "high", + "probabilities": {"low": 0.1616964510265985, "high": 0.8383035489734014}, + "confidence": 0.6766070979468028, + }, + "confidence": { + "type": "score", + "score": 0.25195637565890455, + "legend": {"0": "unsure", "1": "sure"}, + "probabilities": {"0": 0.7480436243410955, "1": 0.25195637565890455}, + "confidence": 0.4960872486821909, + }, + }, + "usage": {"input_tokens": 3166, "output_tokens": 0}, + "mode": "fast", + "citations": _CITATIONS, + "decision_id": "decisions_9fd99def328ed16256c11df297dea899", + }, +) diff --git a/tests/integration/translation/decisions/basic/test_decisions_basic_parallel_ai.py b/tests/integration/translation/decisions/basic/test_decisions_basic_parallel_ai.py new file mode 100644 index 00000000000..47eb057323b --- /dev/null +++ b/tests/integration/translation/decisions/basic/test_decisions_basic_parallel_ai.py @@ -0,0 +1,11 @@ +import pytest +from integration._support.client import Gateway +from integration._support.provider import SharedProvider +from integration.translation.case import TranslationTestCase +from integration.translation.decisions.bases.parallel_ai import DECISION_SYSTEMONE_TEST_CASE, DECISION_TEST_CASE +from integration.translation.runner import assert_translation + + +@pytest.mark.parametrize("case", [DECISION_TEST_CASE, DECISION_SYSTEMONE_TEST_CASE], ids=lambda case: case.id) +def test_decisions_basic_parallel_ai(case: TranslationTestCase, gateway: Gateway, provider: SharedProvider) -> None: + assert_translation(case, gateway, provider) diff --git a/tests/integration/translation/messages/bases/bedrock_converse.py b/tests/integration/translation/messages/bases/bedrock_converse.py index 6a115160fbc..3d2b731d7c0 100644 --- a/tests/integration/translation/messages/bases/bedrock_converse.py +++ b/tests/integration/translation/messages/bases/bedrock_converse.py @@ -113,6 +113,7 @@ CLAUDE_SONNET_5_TEST_CASE: Final = TranslationTestCase( expected_provider_endpoint="/model/us.anthropic.claude-sonnet-5/converse", expected_provider_headers={"authorization": "Bearer synthetic-bedrock-key", "content-type": "application/json"}, expected_provider_request={ + "additionalModelResponseFieldPaths": ["/usage/output_tokens_details"], "messages": [{"role": "user", "content": [{"text": "Say hello."}]}], "inferenceConfig": {"maxTokens": 64}, "system": [{"text": "You are a terse assistant."}], diff --git a/tests/integration/translation/responses/bases/bedrock_converse.py b/tests/integration/translation/responses/bases/bedrock_converse.py index b0a2c881878..d15f6325daf 100644 --- a/tests/integration/translation/responses/bases/bedrock_converse.py +++ b/tests/integration/translation/responses/bases/bedrock_converse.py @@ -190,6 +190,7 @@ CLAUDE_SONNET_5_TEST_CASE: Final = TranslationTestCase( expected_provider_endpoint="/model/us.anthropic.claude-sonnet-5/converse", expected_provider_headers={"authorization": "Bearer synthetic-bedrock-key", "content-type": "application/json"}, expected_provider_request={ + "additionalModelResponseFieldPaths": ["/usage/output_tokens_details"], "messages": [{"role": "user", "content": [{"text": "Say hello."}]}], "inferenceConfig": {"maxTokens": 64}, "system": [{"text": "You are a terse assistant."}], diff --git a/tests/rust-python-harness/strategies/e2e_parity/__init__.py b/tests/rust-python-harness/strategies/e2e_parity/__init__.py index 298c75f2af1..a2ea98f19ab 100644 --- a/tests/rust-python-harness/strategies/e2e_parity/__init__.py +++ b/tests/rust-python-harness/strategies/e2e_parity/__init__.py @@ -20,7 +20,7 @@ CASES: Final[tuple[CaseDefinition, ...]] = ( CaseDefinition( "messages", NotImplementedCaseSpec( - reason="Bridge unit tests exist, but no standalone end-to-end parity case is registered." + reason="Parity runs as the pytest suite in sdk/messages/test_native_parity.py, not as a runner case." ), surface="sdk", ), diff --git a/tests/rust-python-harness/strategies/e2e_parity/sdk/messages/conftest.py b/tests/rust-python-harness/strategies/e2e_parity/sdk/messages/conftest.py new file mode 100644 index 00000000000..4bb20713c59 --- /dev/null +++ b/tests/rust-python-harness/strategies/e2e_parity/sdk/messages/conftest.py @@ -0,0 +1,34 @@ +from collections.abc import AsyncIterator, Generator +from importlib import import_module +from pathlib import Path +from typing import Final + +import pytest +import pytest_asyncio + +from tests.test_litellm_rust.support.isolation import isolated_test_state +from tests.test_litellm_rust.support.recording_server import RecordingServer, recording_service + +PARITY_ROOT: Final = Path(__file__).parent + + +@pytest_asyncio.fixture(autouse=True, loop_scope="function") +async def isolate_test_state() -> AsyncIterator[None]: + async with isolated_test_state(): + yield + + +@pytest.fixture +def recording_server() -> Generator[RecordingServer]: + with recording_service() as server: + yield server + + +def pytest_collection_modifyitems(items: list[pytest.Item]) -> None: + try: + import_module("litellm.rust_bridge._native") + except ImportError: + skip: Final = pytest.mark.skip(reason="requires a compiled litellm.rust_bridge._native extension") + for item in items: + if PARITY_ROOT in item.path.parents: + item.add_marker(skip) diff --git a/tests/rust-python-harness/strategies/e2e_parity/sdk/messages/test_native_parity.py b/tests/rust-python-harness/strategies/e2e_parity/sdk/messages/test_native_parity.py new file mode 100644 index 00000000000..41008f0d57f --- /dev/null +++ b/tests/rust-python-harness/strategies/e2e_parity/sdk/messages/test_native_parity.py @@ -0,0 +1,1079 @@ +"""Native Anthropic Messages calls must be indistinguishable from the Python implementation. + +Each case sends one `/v1/messages` SDK call through the Python handler and through the native route against the same +scripted upstream, then compares one aspect of what happened: + +- dispatch: the native leg was served natively instead of falling back to Python +- request: every request that reached the upstream (method, path, body, headers) +- outcome: what the caller got back (response body, stream bytes, or the raised exception) +- hidden_params: the `_hidden_params` keys the proxy builds its response headers from +- logged: which terminal callbacks fired and the stable standard logging payload fields +- logged_metadata, logged_model_info, logged_response_headers, logged_api_key, logged_call: single callback kwargs + fields that proxy integrations read + +Both legs run once per case and every aspect of that case reads the same pair + +The native leg prepends an unconstrained Rust rule, so feature detectors that keep a call on Python today do not +apply: a case for a detector-covered feature shows what Rust still lacks before that detector can go. Every known +difference is a strict xfail naming the gap, with an id from the Rust vs Python Messages inventory (A routing, +R request, S response, C callbacks, F covered by a fallback detector today) +""" + +import asyncio +import copy +import json +import os +import re +from collections.abc import AsyncIterator, Awaitable, Callable, Generator, Iterable, Iterator, Mapping +from contextlib import contextmanager +from dataclasses import asdict, dataclass, field, replace +from types import MappingProxyType +from typing import Final, cast + +import pytest +from pydantic import JsonValue, TypeAdapter + +import litellm +from litellm.litellm_core_utils.add_retry_fallback_headers import get_hidden_params_dict +from litellm.messages import dispatch +from litellm.rust_bridge import catalog +from litellm.rust_bridge.catalog import Route, RouteRule +from litellm.rust_bridge.configuration import Rollout +from tests.test_litellm_rust.support.callback_recorder import RecordingLogger, drain_logging +from tests.test_litellm_rust.support.isolation import isolated_callback_registries, rebound +from tests.test_litellm_rust.support.recording_server import RecordingServer, ResponseSpec + +pytestmark = pytest.mark.requires_rust_extension + +SONNET: Final = "anthropic/claude-sonnet-4-5" +OPUS_ADAPTIVE: Final = "anthropic/claude-opus-4-7" +OPUS_FAST: Final = "anthropic/claude-opus-5-5" +API_KEY: Final = "sk-ant-parity-test" +USER: Final[Mapping[str, JsonValue]] = MappingProxyType({"role": "user", "content": "What is the capital of France?"}) + +_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) +_LOGGED: Final = TypeAdapter(dict[str, object]) +_TRANSPORT_HEADERS: Final = frozenset( + {"accept", "accept-encoding", "connection", "content-length", "host", "user-agent"} +) +_COMPARED_LOG_FIELDS: Final = ( + "call_type", + "custom_llm_provider", + "model", + "model_group", + "model_id", + "api_base", + "stream", + "cache_hit", + "prompt_tokens", + "completion_tokens", + "total_tokens", + "response_cost", + "status", +) +_TERMINAL_EVENTS: Final = ( + "log_success_event", + "async_log_success_event", + "log_failure_event", + "async_log_failure_event", +) +_VOLATILE: Final = ( + (re.compile(r"time taken=[0-9.]+"), "time taken="), + (re.compile(r"Timeout passed=[0-9.]+"), "Timeout passed="), + (re.compile(r"127\.0\.0\.1:[0-9]+"), "127.0.0.1:"), +) + +TEXT_RESPONSE: Final[Mapping[str, JsonValue]] = MappingProxyType( + { + "id": "msg_01ParityText", + "type": "message", + "role": "assistant", + "model": "claude-sonnet-4-5-20250929", + "content": [{"type": "text", "text": "Paris"}], + "stop_reason": "end_turn", + "stop_sequence": None, + "usage": {"input_tokens": 14, "output_tokens": 4}, + } +) + +TOOL_USE_RESPONSE: Final[Mapping[str, JsonValue]] = MappingProxyType( + { + **TEXT_RESPONSE, + "id": "msg_01ParityTool", + "content": [ + {"type": "text", "text": "Checking."}, + {"type": "tool_use", "id": "toolu_01Parity", "name": "get_weather", "input": {"city": "Paris"}}, + ], + "stop_reason": "tool_use", + } +) + +THINKING_RESPONSE: Final[Mapping[str, JsonValue]] = MappingProxyType( + { + **TEXT_RESPONSE, + "id": "msg_01ParityThinking", + "content": [ + {"type": "thinking", "thinking": "The capital of France is Paris.", "signature": "EqQBCkYIARgCKkB"}, + {"type": "text", "text": "Paris"}, + ], + } +) + +CACHED_USAGE_RESPONSE: Final[Mapping[str, JsonValue]] = MappingProxyType( + { + **TEXT_RESPONSE, + "usage": { + "input_tokens": 14, + "output_tokens": 4, + "cache_creation_input_tokens": 2048, + "cache_read_input_tokens": 1024, + "service_tier": "standard", + }, + } +) + +WEATHER_TOOL: Final[Mapping[str, JsonValue]] = MappingProxyType( + { + "name": "get_weather", + "description": "Current weather for a city", + "input_schema": {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]}, + } +) + +TOOL_TURNS: Final[tuple[JsonValue, ...]] = ( + {"role": "user", "content": "Weather in Paris?"}, + { + "role": "assistant", + "content": [{"type": "tool_use", "id": "toolu_01Parity", "name": "get_weather", "input": {"city": "Paris"}}], + }, + {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "toolu_01Parity", "content": "18C, sunny"}]}, +) + +THINKING_REPLAY: Final[tuple[JsonValue, ...]] = ( + {"role": "user", "content": "What is the capital of France?"}, + { + "role": "assistant", + "content": [ + {"type": "thinking", "thinking": "Paris.", "signature": "EqQBCkYIARgCKkB"}, + {"type": "text", "text": "Paris"}, + ], + }, + {"role": "user", "content": "And Germany?"}, +) + +NO_INPUT: Final[Mapping[str, JsonValue]] = MappingProxyType({}) +PNG_PIXEL: Final = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==" + + +def _events(*events: tuple[str, JsonValue]) -> tuple[tuple[str, object], ...]: + return tuple((name, data) for name, data in events) + + +def _message_start(message_id: str) -> tuple[str, JsonValue]: + return ( + "message_start", + { + "type": "message_start", + "message": { + **TEXT_RESPONSE, + "id": message_id, + "content": [], + "stop_reason": None, + "usage": {"input_tokens": 14, "output_tokens": 1}, + }, + }, + ) + + +def _text_block(index: int, *pieces: str) -> tuple[tuple[str, JsonValue], ...]: + return ( + ( + "content_block_start", + {"type": "content_block_start", "index": index, "content_block": {"type": "text", "text": ""}}, + ), + *( + ( + "content_block_delta", + {"type": "content_block_delta", "index": index, "delta": {"type": "text_delta", "text": piece}}, + ) + for piece in pieces + ), + ("content_block_stop", {"type": "content_block_stop", "index": index}), + ) + + +def _message_end(stop_reason: str, output_tokens: int) -> tuple[tuple[str, JsonValue], ...]: + return ( + ( + "message_delta", + { + "type": "message_delta", + "delta": {"stop_reason": stop_reason, "stop_sequence": None}, + "usage": {"output_tokens": output_tokens}, + }, + ), + ("message_stop", {"type": "message_stop"}), + ) + + +TEXT_STREAM: Final = _events( + _message_start("msg_01ParityStream"), *_text_block(0, "Pa", "ris"), *_message_end("end_turn", 4) +) + +TOOL_STREAM: Final = _events( + _message_start("msg_01ParityToolStream"), + *_text_block(0, "Checking."), + ( + "content_block_start", + { + "type": "content_block_start", + "index": 1, + "content_block": {"type": "tool_use", "id": "toolu_01Parity", "name": "get_weather", "input": {}}, + }, + ), + ( + "content_block_delta", + {"type": "content_block_delta", "index": 1, "delta": {"type": "input_json_delta", "partial_json": '{"city": '}}, + ), + ( + "content_block_delta", + {"type": "content_block_delta", "index": 1, "delta": {"type": "input_json_delta", "partial_json": '"Paris"}'}}, + ), + ("content_block_stop", {"type": "content_block_stop", "index": 1}), + *_message_end("tool_use", 22), +) + +THINKING_STREAM: Final = _events( + _message_start("msg_01ParityThinkingStream"), + ( + "content_block_start", + { + "type": "content_block_start", + "index": 0, + "content_block": {"type": "thinking", "thinking": "", "signature": ""}, + }, + ), + ( + "content_block_delta", + {"type": "content_block_delta", "index": 0, "delta": {"type": "thinking_delta", "thinking": "Paris."}}, + ), + ( + "content_block_delta", + { + "type": "content_block_delta", + "index": 0, + "delta": {"type": "signature_delta", "signature": "EqQBCkYIARgCKkB"}, + }, + ), + ("content_block_stop", {"type": "content_block_stop", "index": 0}), + *_text_block(1, "Paris"), + *_message_end("end_turn", 12), +) + +ERROR_MID_STREAM: Final = _events( + _message_start("msg_01ParityOverloaded"), + *_text_block(0, "Pa"), + ("error", {"type": "error", "error": {"type": "overloaded_error", "message": "Overloaded"}}), +) + +SLOW_STREAM: Final = _events( + _message_start("msg_01ParitySlow"), + *_text_block(0, "a", "b", "c", "d", "e", "f"), + *_message_end("end_turn", 6), +) + + +def _upstream_error(kind: str, message: str) -> Mapping[str, JsonValue]: + return MappingProxyType({"type": "error", "error": {"type": kind, "message": message}}) + + +def _ok(body: Mapping[str, JsonValue] = TEXT_RESPONSE, **headers: str) -> ResponseSpec: + return ResponseSpec(body=dict(body), headers=dict(headers)) + + +def _stream(events: tuple[tuple[str, object], ...], chunk_delay: float = 0) -> ResponseSpec: + return ResponseSpec(body={}, events=events, chunk_delay=chunk_delay) + + +def _failure(status: int, kind: str, message: str, **headers: str) -> ResponseSpec: + return ResponseSpec(body=dict(_upstream_error(kind, message)), status=status, headers=dict(headers)) + + +CALLBACK_ASPECTS: Final = ( + "logged_metadata", + "logged_model_info", + "logged_response_headers", + "logged_api_key", + "logged_call", +) +ASPECTS: Final = ("dispatch", "request", "outcome", "hidden_params", "logged", *CALLBACK_ASPECTS) + + +@dataclass(frozen=True, slots=True) +class Case: + name: str + kwargs: Mapping[str, object] = field(default_factory=lambda: MappingProxyType({})) + upstream: tuple[ResponseSpec, ...] = (ResponseSpec(body=dict(TEXT_RESPONSE)),) + model: str = SONNET + sync: bool = False + env: Mapping[str, str] = field(default_factory=lambda: MappingProxyType({})) + settings: Mapping[str, object] = field(default_factory=lambda: MappingProxyType({})) + private_keys: bool = False + gaps: Mapping[str, str | None] = field(default_factory=lambda: MappingProxyType({})) + + def params(self) -> Iterator[object]: + for aspect in ASPECTS: + gap = {**KNOWN_GAPS.get(self.name, {}), **self.gaps}.get(aspect) + marks = () if not gap else (pytest.mark.xfail(reason=gap, strict=True),) + yield pytest.param(self, aspect, id=f"{self.name}-{aspect}", marks=marks) + + +def _gaps(**gaps: str | None) -> Mapping[str, str | None]: + return MappingProxyType(gaps) + + +def _kw(**kwargs: object) -> Mapping[str, object]: + return MappingProxyType(kwargs) + + +A10_NO_MAX_TOKENS: Final = "A10: native admission hands a call without an int max_tokens to Python, whose signature raises the TypeError; only dispatch differs" +S6_PRIVATE_KEYS: Final = "S6: native writes _hidden_params into the response dict" +S15_COMPLETE_DEADLINE: Final = ( + "S15: by design, native bounds a complete response by one overall deadline where Python bounds each read, " + "so a body trickling in slower than the timeout succeeds in Python and times out natively" +) +F_MOCK: Final = "F: mock_response is Python-only (detector mock_response)" +F_THINKING_RETRY: Final = ( + "F: retry without thinking after a rejected signature is Python-only (detector thinking_signature_retry)" +) +F_CACHE_INJECTION: Final = "F: prompt cache_control injection is Python-only (detector cache_control_injection)" +F_TOOL_CUSTOM: Final = "F: hoisting a tool's custom field is Python-only (detector tool_custom_field)" +F_STREAM_COST: Final = "F: cost injection into streamed usage is Python-only (detector stream_cost_injection)" + +KNOWN_GAPS: Final[Mapping[str, Mapping[str, str | None]]] = MappingProxyType( + { + "response_private_keys": _gaps(outcome=S6_PRIVATE_KEYS), + "missing_max_tokens": _gaps(dispatch=A10_NO_MAX_TOKENS), + "mock_response": _gaps( + logged_response_headers=F_MOCK, + request=F_MOCK, + outcome=F_MOCK, + hidden_params=F_MOCK, + logged=F_MOCK, + logged_metadata=F_MOCK, + logged_api_key=F_MOCK, + logged_call=F_MOCK, + ), + "mock_response_rate_limit": _gaps( + logged_response_headers=F_MOCK, + request=F_MOCK, + outcome=F_MOCK, + logged=F_MOCK, + logged_api_key=F_MOCK, + logged_call=F_MOCK, + ), + "thinking_signature_rejected_then_retried": _gaps( + request=F_THINKING_RETRY, + outcome=F_THINKING_RETRY, + hidden_params=F_THINKING_RETRY, + logged=F_THINKING_RETRY, + logged_metadata=F_THINKING_RETRY, + logged_response_headers=F_THINKING_RETRY, + ), + "cache_control_injection_points": _gaps(request=F_CACHE_INJECTION), + "tool_custom_field": _gaps(request=F_TOOL_CUSTOM), + "stream_cost_injection": _gaps(outcome=F_STREAM_COST), + "enable_prompt_caching": _gaps(request=F_CACHE_INJECTION), + } +) + + +REQUEST_CASES: Final = ( + Case("plain_text"), + Case("system_string", _kw(system="Answer in one word.")), + Case( + "system_blocks_with_cache_control", + _kw(system=[{"type": "text", "text": "Answer in one word.", "cache_control": {"type": "ephemeral"}}]), + ), + Case("multi_turn_tool_result", _kw(messages=list(TOOL_TURNS), tools=[dict(WEATHER_TOOL)])), + Case( + "tools_with_tool_choice", + _kw(tools=[dict(WEATHER_TOOL)], tool_choice={"type": "tool", "name": "get_weather"}), + upstream=(_ok(TOOL_USE_RESPONSE),), + ), + Case("tool_choice_none", _kw(tools=[dict(WEATHER_TOOL)], tool_choice={"type": "none"})), + Case("tool_input_examples", _kw(tools=[{**WEATHER_TOOL, "input_examples": [{"city": "Paris"}]}])), + Case("sampling_params", _kw(temperature=0.3, top_p=0.9, top_k=40)), + Case("stop_sequences", _kw(stop_sequences=["\n\nHuman:"])), + Case("metadata_user_id", _kw(metadata={"user_id": "user-123"})), + Case("metadata_extra_keys_are_filtered", _kw(metadata={"user_id": "user-123", "session": "s-1"})), + Case("metadata_user_id_not_a_string", _kw(metadata={"user_id": 123})), + Case("service_tier", _kw(service_tier="auto")), + Case("thinking_enabled", _kw(thinking={"type": "enabled", "budget_tokens": 2048}, max_tokens=4096)), + Case("thinking_disabled", _kw(thinking={"type": "disabled"})), + Case( + "legacy_thinking_on_adaptive_model_keeps_display", + _kw(thinking={"type": "enabled", "budget_tokens": 2048, "display": "summarized"}, max_tokens=4096), + model=OPUS_ADAPTIVE, + ), + Case( + "legacy_thinking_display_updates_on_adaptive_model", + _kw(thinking={"type": "enabled", "budget_tokens": 2048, "display": "updates"}, max_tokens=4096), + model=OPUS_ADAPTIVE, + ), + Case( + "legacy_thinking_string_budget_on_adaptive_model", + _kw(thinking={"type": "enabled", "budget_tokens": " 4_096 "}, max_tokens=8192), + model=OPUS_ADAPTIVE, + ), + Case( + "legacy_thinking_non_numeric_budget_on_adaptive_model", + _kw(thinking={"type": "enabled", "budget_tokens": "lots"}, max_tokens=8192), + model=OPUS_ADAPTIVE, + ), + Case( + "legacy_thinking_null_budget_on_adaptive_model", + _kw(thinking={"type": "enabled", "budget_tokens": None}, max_tokens=8192), + model=OPUS_ADAPTIVE, + ), + Case( + "legacy_thinking_non_numeric_budget_dropped", + _kw(thinking={"type": "enabled", "budget_tokens": [1]}, max_tokens=8192, drop_params=True), + model=OPUS_ADAPTIVE, + ), + Case( + "legacy_thinking_carries_extra_keys", + _kw( + thinking={"type": "enabled", "budget_tokens": 2048, "block_binding": "strict", "note": "kept"}, + max_tokens=4096, + ), + model=OPUS_ADAPTIVE, + ), + Case( + "legacy_thinking_drops_extra_keys_with_drop_params", + _kw( + thinking={"type": "enabled", "budget_tokens": 2048, "block_binding": "strict", "note": "dropped"}, + max_tokens=4096, + drop_params=True, + ), + model=OPUS_ADAPTIVE, + ), + Case( + "legacy_thinking_float_budget_on_adaptive_model", + _kw(thinking={"type": "enabled", "budget_tokens": 8192.0}, max_tokens=16000), + model=OPUS_ADAPTIVE, + ), + Case( + "adaptive_thinking_with_block_binding", + _kw(thinking={"type": "adaptive", "block_binding": "strict"}, max_tokens=4096), + model=OPUS_ADAPTIVE, + ), + Case("reasoning_effort", _kw(reasoning_effort="high", max_tokens=8192)), + Case("reasoning_effort_on_adaptive_model", _kw(reasoning_effort="low", max_tokens=8192), model=OPUS_ADAPTIVE), + Case("output_config_effort", _kw(output_config={"effort": "medium"}), model=OPUS_ADAPTIVE), + Case( + "output_format_json_schema", + _kw( + output_format={ + "type": "json_schema", + "schema": {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]}, + } + ), + ), + Case("speed_on_model_without_speed", _kw(speed="fast")), + Case("speed_on_model_without_speed_drop_params", _kw(speed="fast", drop_params=True)), + Case("speed_on_fast_model", _kw(speed="fast"), model=OPUS_FAST), + Case("temperature_on_adaptive_model", _kw(temperature=0.5), model=OPUS_ADAPTIVE), + Case("top_k_on_adaptive_model", _kw(top_k=5), model=OPUS_ADAPTIVE), + Case("top_k_on_adaptive_model_drop_params", _kw(top_k=5, drop_params=True), model=OPUS_ADAPTIVE), + Case( + "additional_drop_params_hides_rejected_temperature", + _kw(temperature=0.5, additional_drop_params=["temperature"]), + model=OPUS_ADAPTIVE, + ), + Case( + "additional_drop_params_nested_path", + _kw( + tools=[{**WEATHER_TOOL, "input_examples": [{"city": "Paris"}]}], + additional_drop_params=["tools[*].input_examples", "metadata"], + metadata={"user_id": "user-123"}, + ), + ), + Case( + "context_management_edits", + _kw(context_management={"edits": [{"type": "clear_tool_uses_20250919"}]}), + ), + Case( + "container_skills", _kw(container={"skills": [{"type": "anthropic", "skill_id": "pptx", "version": "latest"}]}) + ), + Case( + "remote_mcp_servers", + _kw(mcp_servers=[{"type": "url", "url": "https://mcp.example.com/sse", "name": "example"}]), + ), + Case("inference_geo", _kw(inference_geo="us")), + Case("top_level_cache_control", _kw(cache_control={"type": "ephemeral"})), + Case("null_safeguards_are_stripped", _kw(safeguards=None)), + Case( + "empty_text_blocks_are_stripped", + _kw( + messages=[ + {"role": "user", "content": [{"type": "text", "text": ""}, {"type": "text", "text": "hi"}]}, + ] + ), + ), + Case( + "tool_use_ids_are_sanitized", + _kw( + messages=[ + {"role": "user", "content": "Weather?"}, + { + "role": "assistant", + "content": [ + {"type": "tool_use", "id": "call:abc/1", "name": "get_weather", "input": dict(NO_INPUT)} + ], + }, + {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "call:abc/1", "content": "sunny"}]}, + ], + tools=[dict(WEATHER_TOOL)], + ), + ), + Case( + "provider_specific_fields_are_stripped", + _kw(messages=[{"role": "user", "content": "hi", "provider_specific_fields": {"x": 1}}]), + ), + Case( + "image_block", + _kw( + messages=[ + { + "role": "user", + "content": [ + {"type": "image", "source": {"type": "base64", "media_type": "image/png", "data": PNG_PIXEL}}, + {"type": "text", "text": "Describe it"}, + ], + } + ] + ), + ), + Case( + "document_block", + _kw( + messages=[ + { + "role": "user", + "content": [ + {"type": "document", "source": {"type": "text", "media_type": "text/plain", "data": "Paris."}}, + {"type": "text", "text": "Summarize"}, + ], + } + ] + ), + ), + Case("server_web_search_tool", _kw(tools=[{"type": "web_search_20250305", "name": "web_search", "max_uses": 2}])), + Case("extra_headers", _kw(extra_headers={"x-trace-id": "trace-1", "anthropic-beta": "files-api-2025-04-14"})), + Case( + "anthropic_beta_from_headers_and_extra_headers", + _kw(headers={"anthropic-beta": "client-beta-1"}, extra_headers={"anthropic-beta": "deploy-beta-2"}), + ), + Case("caller_anthropic_version_capitalised", _kw(extra_headers={"Anthropic-Version": "2023-06-01"})), + Case( + "provider_specific_header", + _kw(provider_specific_header={"custom_llm_provider": "anthropic", "extra_headers": {"x-scoped": "yes"}}), + ), + Case("explicit_custom_llm_provider", _kw(custom_llm_provider="anthropic"), model="claude-sonnet-4-5"), + Case("bare_model_name", model="claude-sonnet-4-5"), + Case("api_base_with_messages_path", _kw(api_base_suffix="/v1/messages")), + Case( + "api_base_with_messages_path_and_query", + _kw(api_base_suffix="/v1/messages?beta=true"), + ), + Case("api_key_from_environment", _kw(api_key=None), env=MappingProxyType({"ANTHROPIC_API_KEY": API_KEY})), + Case( + "auth_token_from_environment", + _kw(api_key=None), + env=MappingProxyType({"ANTHROPIC_AUTH_TOKEN": "oauth-token"}), + ), + Case( + "reasoning_auto_summary", + _kw(thinking={"type": "enabled", "budget_tokens": 2048}, max_tokens=4096), + env=MappingProxyType({"LITELLM_REASONING_AUTO_SUMMARY": "true"}), + ), + Case("global_drop_params", _kw(top_k=5), model=OPUS_ADAPTIVE, settings=MappingProxyType({"drop_params": True})), + Case("request_timeout_setting", settings=MappingProxyType({"request_timeout": 30})), + Case( + "litellm_metadata_and_metadata", + _kw( + metadata={"user_id": "user-123"}, + litellm_metadata={"user_api_key": "hashed-key", "user_api_key_team_id": "t1"}, + ), + ), + Case("model_info_with_id", _kw(model_info={"id": "deployment-1", "db_model": False})), + Case( + "deployment_effort_levels", + _kw( + output_config={"effort": "max"}, + model_info={"id": "deployment-1", "reasoning_effort_levels": ["low", "high"]}, + ), + model=OPUS_ADAPTIVE, + ), + Case( + "deployment_effort_levels_from_legacy_thinking", + _kw( + thinking={"type": "enabled", "budget_tokens": 30000}, + max_tokens=40000, + model_info={"id": "deployment-1", "reasoning_effort_levels": ["low", "medium"]}, + ), + model=OPUS_ADAPTIVE, + ), + Case( + "deployment_effort_levels_below_request_with_drop_params", + _kw( + output_config={"effort": "high"}, + drop_params=True, + model_info={"id": "deployment-1", "reasoning_effort_levels": ["low"]}, + ), + model=OPUS_ADAPTIVE, + ), +) + +RESPONSE_CASES: Final = ( + Case("response_with_tool_use", _kw(tools=[dict(WEATHER_TOOL)]), upstream=(_ok(TOOL_USE_RESPONSE),)), + Case("response_with_thinking", upstream=(_ok(THINKING_RESPONSE),)), + Case("response_with_cache_usage", upstream=(_ok(CACHED_USAGE_RESPONSE),)), + Case( + "response_with_null_usage_and_container", + upstream=(_ok({**TEXT_RESPONSE, "usage": None, "container": None}),), + ), + Case( + "response_without_stop_sequence", + upstream=(_ok({k: v for k, v in TEXT_RESPONSE.items() if k != "stop_sequence"}),), + ), + Case("response_with_unknown_field", upstream=(_ok({**TEXT_RESPONSE, "future_field": {"a": 1}}),)), + Case("response_key_order", upstream=(_ok({"usage": TEXT_RESPONSE["usage"], **TEXT_RESPONSE}),)), + Case( + "response_upstream_headers", + upstream=( + _ok(TEXT_RESPONSE, **{"request-id": "req_01Parity", "anthropic-ratelimit-requests-remaining": "99"}), + ), + ), + Case("response_private_keys", private_keys=True), +) + +FAILURE_CASES: Final = ( + Case("upstream_400", upstream=(_failure(400, "invalid_request_error", "max_tokens: too large"),)), + Case("upstream_401", upstream=(_failure(401, "authentication_error", "invalid x-api-key"),)), + Case("upstream_403", upstream=(_failure(403, "permission_error", "not allowed"),)), + Case("upstream_404", upstream=(_failure(404, "not_found_error", "model not found"),)), + Case("upstream_413", upstream=(_failure(413, "request_too_large", "too large"),)), + Case( + "upstream_429_with_retry_after", + upstream=( + _failure(429, "rate_limit_error", "slow down", **{"retry-after": "7", "request-id": "req_01Parity"}), + ), + ), + Case("upstream_500", upstream=(_failure(500, "api_error", "internal"),)), + Case("upstream_529_overloaded", upstream=(_failure(529, "overloaded_error", "Overloaded"),)), + Case( + "upstream_400_context_window", + upstream=(_failure(400, "invalid_request_error", "prompt is too long: 250000 tokens > 200000 maximum"),), + ), + Case("upstream_non_json_error", upstream=(ResponseSpec(body=b"bad gateway", status=502),)), + Case("upstream_invalid_json_success", upstream=(ResponseSpec(body=b"not json", status=200),)), + Case("upstream_timeout", _kw(timeout=0.5), upstream=(ResponseSpec(body=dict(TEXT_RESPONSE), delay=1.5),)), + Case( + "response_trickles_slower_than_timeout", + _kw(timeout=1), + upstream=(ResponseSpec(body=dict(TEXT_RESPONSE), chunk_delay=0.5, body_chunks=4),), + gaps=_gaps( + outcome=S15_COMPLETE_DEADLINE, + hidden_params=S15_COMPLETE_DEADLINE, + logged=S15_COMPLETE_DEADLINE, + logged_metadata=S15_COMPLETE_DEADLINE, + logged_response_headers=S15_COMPLETE_DEADLINE, + ), + ), + Case("missing_max_tokens", _kw(max_tokens=None), upstream=()), + Case("missing_api_key", _kw(api_key=None), upstream=()), +) + +STREAM_CASES: Final = ( + Case("stream_text", _kw(stream=True), upstream=(_stream(TEXT_STREAM),)), + Case("stream_tool_use", _kw(stream=True, tools=[dict(WEATHER_TOOL)]), upstream=(_stream(TOOL_STREAM),)), + Case( + "stream_thinking", + _kw(stream=True, thinking={"type": "enabled", "budget_tokens": 2048}, max_tokens=4096), + upstream=(_stream(THINKING_STREAM),), + ), + Case("stream_error_event_mid_stream", _kw(stream=True), upstream=(_stream(ERROR_MID_STREAM),)), + Case( + "stream_longer_than_timeout", + _kw(stream=True, timeout=1), + upstream=(_stream(SLOW_STREAM, chunk_delay=0.25),), + ), + Case( + "stream_read_stalls_past_timeout", + _kw(stream=True, timeout=0.5), + upstream=(_stream(SLOW_STREAM, chunk_delay=1.0),), + ), + Case( + "stream_upstream_429", + _kw(stream=True), + upstream=(_failure(429, "rate_limit_error", "slow down", **{"retry-after": "3"}),), + ), + Case("stream_false_explicit", _kw(stream=False)), +) + +SYNC_CASES: Final = ( + Case("sync_text", sync=True), + Case("sync_stream", _kw(stream=True), upstream=(_stream(TEXT_STREAM),), sync=True), + Case("sync_upstream_429", upstream=(_failure(429, "rate_limit_error", "slow down"),), sync=True), +) + +FALLBACK_CASES: Final = ( + Case("mock_response", _kw(mock_response="Hi from the mock"), upstream=()), + Case("mock_response_rate_limit", _kw(mock_response="litellm.RateLimitError"), upstream=()), + Case( + "thinking_replay", + _kw(messages=list(THINKING_REPLAY), thinking={"type": "enabled", "budget_tokens": 2048}, max_tokens=4096), + ), + Case( + "thinking_signature_rejected_then_retried", + _kw(messages=list(THINKING_REPLAY), thinking={"type": "enabled", "budget_tokens": 2048}, max_tokens=4096), + upstream=( + _failure(400, "invalid_request_error", "messages.1.content.0: Invalid `signature` in `thinking` block"), + _ok(), + ), + ), + Case( + "cache_control_injection_points", + _kw(system="Answer in one word.", cache_control_injection_points=[{"location": "message", "role": "system"}]), + ), + Case("tool_custom_field", _kw(tools=[{**WEATHER_TOOL, "custom": {"defer_loading": True}}])), + Case( + "strict_tools_rejected_then_retried", + _kw(tools=[{**WEATHER_TOOL, "strict": True}], drop_params=True), + upstream=( + _failure(400, "invalid_request_error", "tools.0.strict: too many strict tools"), + _ok(), + ), + ), + Case("modify_params", _kw(max_tokens=1), settings=MappingProxyType({"modify_params": True})), + Case( + "stream_cost_injection", + _kw(stream=True), + upstream=(_stream(TEXT_STREAM),), + settings=MappingProxyType({"include_cost_in_streaming_usage": True}), + ), + Case("enable_prompt_caching", _kw(system="Answer in one word.", enable_prompt_caching=True)), + Case("request_timeout_kwarg", _kw(request_timeout=30)), + Case("stream_timeout_kwarg", _kw(stream=True, stream_timeout=30), upstream=(_stream(TEXT_STREAM),)), +) + +CASES: Final = (*REQUEST_CASES, *RESPONSE_CASES, *FAILURE_CASES, *STREAM_CASES, *SYNC_CASES, *FALLBACK_CASES) + + +@dataclass(frozen=True, slots=True) +class Leg: + fell_back: bool + requests: tuple[Mapping[str, object], ...] + outcome: Mapping[str, object] + hidden_params: Mapping[str, object] + logged: Mapping[str, object] + callback_kwargs: Mapping[str, object] + + +@dataclass(slots=True) +class FallbackProbe: + calls: int = 0 + + +_PYTHON_AMESSAGES: Final = cast(Callable[..., Awaitable[object]], dispatch._PYTHON_AMESSAGES) # pyright: ignore[reportPrivateUsage] # the Python baseline under comparison +_PYTHON_MESSAGES: Final = cast(Callable[..., object], dispatch._PYTHON_MESSAGES) # pyright: ignore[reportPrivateUsage] # the Python baseline under comparison +_PUBLIC_AMESSAGES: Final = cast(Callable[..., Awaitable[object]], dispatch.anthropic_messages) +_PUBLIC_MESSAGES: Final = cast(Callable[..., object], dispatch.anthropic_messages_handler) + + +@pytest.fixture +def native_messages() -> Iterator[FallbackProbe]: + probe: Final = FallbackProbe() + + async def python_afallback(*args: object, **kwargs: object) -> object: + probe.calls += 1 + return await _PYTHON_AMESSAGES(*args, **kwargs) + + def python_fallback(*args: object, **kwargs: object) -> object: + probe.calls += 1 + return _PYTHON_MESSAGES(*args, **kwargs) + + with ( + rebound(catalog, "RULES", (RouteRule(Route.MESSAGES, Rollout.RUST_OPT_OUT), *catalog.RULES)), + rebound(dispatch, "_PYTHON_AMESSAGES", python_afallback), + rebound(dispatch, "_PYTHON_MESSAGES", python_fallback), + ): + yield probe + + +@contextmanager +def _environment(env: Mapping[str, str]) -> Generator[None]: + # LITELLM_RUST overrides the catalog rule, so a shell that sets it would route the native leg to Python. + names: Final = ( + *env, + "ANTHROPIC_API_KEY", + "ANTHROPIC_AUTH_TOKEN", + "LITELLM_REASONING_AUTO_SUMMARY", + "LITELLM_RUST", + ) + with pytest.MonkeyPatch.context() as patch: + for name in names: + patch.delenv(name, raising=False) + for name, value in env.items(): + patch.setenv(name, value) + yield + + +@contextmanager +def _settings(settings: Mapping[str, object]) -> Generator[None]: + saved: Final[dict[str, object]] = {name: cast(object, getattr(litellm, name)) for name in settings} + for name, value in settings.items(): + setattr(litellm, name, value) + try: + yield + finally: + for name, value in saved.items(): + setattr(litellm, name, value) + + +def _kwargs(case: Case, server: RecordingServer) -> dict[str, object]: + # Deep: Python writes into the caller's own `litellm_metadata`, which must not leak into the + # other leg. + supplied: Final = copy.deepcopy(dict(case.kwargs)) + suffix: Final = supplied.pop("api_base_suffix", "") + kwargs: Final[dict[str, object]] = { + "model": case.model, + "max_tokens": 64, + "messages": [dict(USER)], + "api_key": API_KEY, + "api_base": f"{server.base_url}{suffix}", + **supplied, + } + return {name: value for name, value in kwargs.items() if value is not None or name in ("safeguards",)} + + +def _mapping(value: object) -> Mapping[str, object]: + return _LOGGED.validate_python(value) if isinstance(value, dict) else {} + + +def _normalized(text: str) -> str: + for pattern, replacement in _VOLATILE: + text = pattern.sub(replacement, text) # rebind-ok: successive substitutions + return text + + +def _error(error: BaseException, phase: str, chunks: Iterable[object] = ()) -> Mapping[str, object]: + header_items: Final = { + name.lower(): value for name, value in _mapping(getattr(error, "litellm_response_headers", None)).items() + } + return { + "kind": "error", + "phase": phase, + "class": type(error).__name__, + "status_code": getattr(error, "status_code", None), + "llm_provider": getattr(error, "llm_provider", None), + "model": getattr(error, "model", None), + "message": _normalized(str(error)), + "headers": {name: header_items.get(name) for name in ("retry-after", "request-id") if name in header_items}, + "partial": _stream_text(chunks), + } + + +def _stream_text(chunks: Iterable[object]) -> str: + return b"".join(chunk if isinstance(chunk, bytes) else str(chunk).encode() for chunk in chunks).decode() + + +def _response(result: object, private_keys: bool) -> Mapping[str, object]: + assert isinstance(result, dict), f"expected a dict response, got {type(result).__name__}" + body: Final = { + name: value + for name, value in cast(dict[str, object], result).items() + if private_keys or not name.startswith("_") + } + return {"kind": "response", "body": _OBJECT.validate_python(body)} + + +def _hidden_params(result: object) -> Mapping[str, object]: + hidden: Final = dict(_mapping(get_hidden_params_dict(result))) + headers: Final = _mapping(hidden.pop("additional_headers", None)) + header_names: Final = sorted(name for name in headers if name not in ("x-litellm-rust", "x-litellm-cache-key")) + return {"keys": sorted(hidden), "additional_headers": header_names} + + +async def _consume_async(stream: AsyncIterator[object]) -> tuple[list[object], BaseException | None]: + chunks: Final[list[object]] = [] + try: + async for chunk in stream: + chunks.append(chunk) + except Exception as error: # noqa: BLE001 # the raised error is part of the compared outcome + return chunks, error + return chunks, None + + +def _consume_sync(stream: Iterator[object]) -> tuple[list[object], BaseException | None]: + chunks: Final[list[object]] = [] + try: + for chunk in stream: + chunks.append(chunk) + except Exception as error: # noqa: BLE001 # the raised error is part of the compared outcome + return chunks, error + return chunks, None + + +async def _invoke( + case: Case, kwargs: Mapping[str, object], native: bool +) -> tuple[Mapping[str, object], Mapping[str, object]]: + if case.sync: + call = _PUBLIC_MESSAGES if native else _PYTHON_MESSAGES + try: + result = await asyncio.to_thread(lambda: call(**kwargs)) + except Exception as error: # noqa: BLE001 # the raised error is part of the compared outcome + return _error(error, "call"), {} + if isinstance(result, dict): + body = cast(Mapping[str, object], result) + return _response(body, case.private_keys), _hidden_params(body) + chunks, failure = await asyncio.to_thread(_consume_sync, cast(Iterator[object], result)) + else: + acall = _PUBLIC_AMESSAGES if native else _PYTHON_AMESSAGES + try: + result = await acall(**kwargs) + except Exception as error: # noqa: BLE001 # the raised error is part of the compared outcome + return _error(error, "call"), {} + if isinstance(result, dict): + body = cast(Mapping[str, object], result) + return _response(body, case.private_keys), _hidden_params(body) + chunks, failure = await _consume_async(cast(AsyncIterator[object], result)) + hidden: Final = _hidden_params(result) + if failure is not None: + return _error(failure, "stream", chunks), hidden + return { + "kind": "stream", + "chunk_types": sorted({type(chunk).__name__ for chunk in chunks}), + "text": _stream_text(chunks), + }, hidden + + +async def _terminal_events(recorder: RecordingLogger) -> tuple[str, ...]: + for _ in range(100): + await drain_logging() + if any(name in _TERMINAL_EVENTS for name in recorder.names): + break + await asyncio.sleep(0.05) + await asyncio.sleep(0.2) + await drain_logging() + return tuple(name for name in recorder.names if name in _TERMINAL_EVENTS) + + +def _logged(recorder: RecordingLogger, events: tuple[str, ...]) -> tuple[Mapping[str, object], Mapping[str, object]]: + terminal: Final = [event for event in recorder.events if event.name in _TERMINAL_EVENTS] + if not terminal: + return {"events": events}, {} + details: Final = _mapping(terminal[-1].kwargs) + standard: Final = _mapping(details.get("standard_logging_object")) + error_class: Final = _mapping(standard.get("error_information")).get("error_class") + litellm_params: Final = _mapping(details.get("litellm_params")) + metadata: Final = litellm_params.get("metadata") + metadata_keys: Final = _mapping(metadata).keys() + logged: Final[Mapping[str, object]] = { + "events": events, + **{name: standard.get(name) for name in _COMPARED_LOG_FIELDS}, + "error_class": error_class, + } + callback_kwargs: Final[Mapping[str, object]] = { + "logged_metadata": sorted(metadata_keys) if isinstance(metadata, dict) else metadata, + "logged_model_info": litellm_params.get("model_info"), + "logged_response_headers": bool(details.get("response_headers")), + "logged_api_key": details.get("api_key"), + "logged_call": { + "custom_llm_provider": details.get("custom_llm_provider"), + "model": details.get("model"), + "stream": details.get("stream"), + }, + } + return logged, callback_kwargs + + +async def _leg(case: Case, server: RecordingServer, probe: FallbackProbe | None) -> Leg: + with isolated_callback_registries(), _environment(case.env), _settings(case.settings): + recorder: Final = RecordingLogger() + litellm.callbacks.append(recorder) + for spec in case.upstream: + server.enqueue(replace(spec)) + request_count: Final = len(server.requests) + fallbacks_before: Final = 0 if probe is None else probe.calls + outcome, hidden = await _invoke(case, _kwargs(case, server), native=probe is not None) + events: Final = await _terminal_events(recorder) + server.responses.clear() + logged, callback_kwargs = _logged(recorder, events) + return Leg( + fell_back=probe is not None and probe.calls > fallbacks_before, + requests=tuple( + { + "method": sent.method, + "path": sent.path, + "body": sent.body if sent.body is not None else sent.raw_body.decode(errors="replace"), + "headers": { + name: value for name, value in sorted(sent.headers.items()) if name not in _TRANSPORT_HEADERS + }, + } + for sent in server.requests[request_count:] + ), + outcome=outcome, + hidden_params=hidden, + logged=logged, + callback_kwargs=callback_kwargs, + ) + + +@pytest.fixture +def parity_server(recording_server: RecordingServer) -> RecordingServer: + recording_server.expected_requests = None + return recording_server + + +_LEGS: Final[dict[str, tuple[Leg, Leg]]] = {} + + +async def _legs(case: Case, server: RecordingServer, probe: FallbackProbe) -> tuple[Leg, Leg]: + if case.name not in _LEGS: + _LEGS[case.name] = (await _leg(case, server, probe=None), await _leg(case, server, probe=probe)) + _dump(case.name, *_LEGS[case.name]) + return _LEGS[case.name] + + +def _dump(name: str, python: Leg, native: Leg) -> None: + """Writes both legs to ``$MESSAGES_PARITY_DUMP/.json`` when that variable is set.""" + dump: Final = os.environ.get("MESSAGES_PARITY_DUMP") + if not dump: + return + os.makedirs(dump, exist_ok=True) + with open(os.path.join(dump, f"{name}.json"), "w") as out: + json.dump({"python": asdict(python), "native": asdict(native)}, out, indent=1, default=repr) + + +@pytest.mark.asyncio +@pytest.mark.parametrize(("case", "aspect"), tuple(param for case in CASES for param in case.params())) +async def test_native_messages_match_python( + case: Case, aspect: str, parity_server: RecordingServer, native_messages: FallbackProbe +) -> None: + python, native = await _legs(case, parity_server, native_messages) + match aspect: + case "dispatch": + assert not native.fell_back + case "request": + assert native.requests == python.requests + case "outcome": + assert native.outcome == python.outcome + case "hidden_params": + assert native.hidden_params == python.hidden_params + case "logged": + assert native.logged == python.logged + case _: + assert native.callback_kwargs.get(aspect) == python.callback_kwargs.get(aspect) diff --git a/tests/test_litellm_rust/cache/test_python_cache.py b/tests/test_litellm_rust/cache/test_python_cache.py index 722cdbcbaca..c9ac7af1a78 100644 --- a/tests/test_litellm_rust/cache/test_python_cache.py +++ b/tests/test_litellm_rust/cache/test_python_cache.py @@ -5,27 +5,21 @@ import pytest from pydantic import TypeAdapter import litellm -from litellm import _v2 from litellm.caching.caching import Cache, CacheMode from litellm.caching.caching_handler import ( _PENDING_CACHE_WRITES, # pyright: ignore[reportPrivateUsage] # await the existing background cache writer before the next request ) from litellm.litellm_core_utils.add_retry_fallback_headers import get_hidden_params_dict -from litellm.proxy._types import Litellm_EntityType, UserAPIKeyAuth +from litellm.proxy._types import Litellm_EntityType from litellm.proxy.hooks.model_max_budget_limiter import ( PROXY_VirtualKeyModelMaxBudgetLimiter, model_budget_spend_cache_key, ) from litellm.proxy.hooks.parallel_request_limiter_v3 import PROXY_MaxParallelRequestsHandler_v3 from litellm.proxy.utils import InternalUsageCache -from litellm.rust_bridge import runtime -from litellm.rust_bridge.catalog import Route, RouteContext, RouteRule -from litellm.rust_bridge.configuration import Rollout -from litellm.rust_bridge.public_call import NativeCall -from litellm.types.caching import CachingSupportedCallTypes +from litellm.rust_bridge.catalog import Route from tests.test_litellm_rust.cache.support import cache_key, collect, invoke, payload from tests.test_litellm_rust.messages.data import MESSAGES, MESSAGES_EVENTS, MESSAGES_MODEL, MESSAGES_RESPONSE -from tests.test_litellm_rust.responses.data import RESPONSES_RESPONSE from tests.test_litellm_rust.support.callback_recorder import RecordingLogger, drain_logging, request_body from tests.test_litellm_rust.support.recording_server import RecordingServer, ResponseSpec from tests.test_litellm_rust.support.routing import native_route @@ -35,27 +29,18 @@ pytestmark = pytest.mark.requires_rust_extension @pytest.mark.asyncio @pytest.mark.parametrize( - ("route", "stream", "legacy"), - ( - ("chat", False, False), - ("messages", False, False), - ("responses", False, False), - ("messages", True, False), - ("messages", False, True), - ("messages", True, True), - ), + "stream", + (False, True), ) @pytest.mark.parametrize("native", (False, True), ids=("python", "rust")) -async def test_cache_hit_keeps_model_budget_spend_but_accounts_for_usage( +async def test_legacy_cache_hit_keeps_model_budget_spend_but_accounts_for_usage( recording_server: RecordingServer, - route: Literal["chat", "messages", "responses"], stream: bool, native: bool, monkeypatch: pytest.MonkeyPatch, - legacy: bool, ) -> None: monkeypatch.setenv("LITELLM_RUST", "1" if native else "0") - litellm.cache = Cache() if legacy else _v2.Cache.memory() + litellm.cache = Cache() counters: Final = litellm.DualCache() budget: Final = PROXY_VirtualKeyModelMaxBudgetLimiter(counters) limiter: Final = PROXY_MaxParallelRequestsHandler_v3( @@ -75,7 +60,7 @@ async def test_cache_hit_keeps_model_budget_spend_but_accounts_for_usage( } spend_key: Final = model_budget_spend_cache_key(Litellm_EntityType.KEY, key_hash, "cached-model", "1h") token_key: Final = limiter.create_rate_limit_keys("api_key", key_hash, "tokens") - first: Final = await invoke(route, recording_server, options, native=native) + first: Final = await invoke("messages", recording_server, options, native=native) if stream: await collect(first) await asyncio.gather(*tuple(_PENDING_CACHE_WRITES)) @@ -84,13 +69,13 @@ async def test_cache_hit_keeps_model_budget_spend_but_accounts_for_usage( first_log: Final = TypeAdapter(dict[str, object]).validate_python(first_events[0].kwargs) first_payload: Final = TypeAdapter(dict[str, object]).validate_python(first_log["standard_logging_object"]) expected_cost: Final = TypeAdapter(float).validate_python(first_log["response_cost"]) - usage: Final = RESPONSES_RESPONSE["usage"] if route == "responses" else MESSAGES_RESPONSE["usage"] + usage: Final = MESSAGES_RESPONSE["usage"] expected_tokens: Final = usage["input_tokens"] + usage["output_tokens"] assert expected_cost > 0 assert counters.get_cache(spend_key) == pytest.approx(expected_cost) assert counters.get_cache(token_key) == first_payload["total_tokens"] == expected_tokens - second: Final = await invoke(route, recording_server, options, native=native) + second: Final = await invoke("messages", recording_server, options, native=native) if stream: await collect(second) await drain_logging() @@ -104,7 +89,7 @@ async def test_cache_hit_keeps_model_budget_spend_but_accounts_for_usage( assert cached_payload["cache_hit"] is True assert cached_payload["id"] != first_payload["id"] assert cached_payload["custom_llm_provider"] == first_payload["custom_llm_provider"] - assert cached_payload["custom_llm_provider"] == ("openai" if route == "responses" else "anthropic"), { + assert cached_payload["custom_llm_provider"] == "anthropic", { "miss_provider": first_log.get("custom_llm_provider"), "hit_provider": cached_log.get("custom_llm_provider"), } @@ -114,110 +99,22 @@ async def test_cache_hit_keeps_model_budget_spend_but_accounts_for_usage( @pytest.mark.asyncio -@pytest.mark.parametrize("native", (False, True), ids=("python", "rust")) -@pytest.mark.parametrize("backend", ("disabled", "memory", "redis")) -async def test_response_cache_backend_does_not_control_coordination( - recording_server: RecordingServer, - native: bool, - monkeypatch: pytest.MonkeyPatch, - backend: Literal["disabled", "memory", "redis"], - redis_url: str, -) -> None: - monkeypatch.setenv("LITELLM_RUST", "1" if native else "0") - litellm.cache = ( - None - if backend == "disabled" - else _v2.Cache.memory() - if backend == "memory" - else _v2.Cache.redis(redis_url, namespace="independent-coordination") - ) - recording_server.expected_requests = 2 if backend == "disabled" else 1 - counters: Final = litellm.DualCache() - budget: Final = PROXY_VirtualKeyModelMaxBudgetLimiter(counters) - limiter: Final = PROXY_MaxParallelRequestsHandler_v3( - InternalUsageCache(counters), model_group_resolver=lambda model: model - ) - key_hash: Final = "b" * 64 - identity: Final = UserAPIKeyAuth(api_key=key_hash, rpm_limit=2, tpm_limit=1000, max_parallel_requests=1) - spend_key: Final = model_budget_spend_cache_key(Litellm_EntityType.KEY, key_hash, "cached-model", "1h") - request_key: Final = limiter.create_rate_limit_keys("api_key", key_hash, "requests") - token_key: Final = limiter.create_rate_limit_keys("api_key", key_hash, "tokens") - parallel_key: Final = limiter.create_rate_limit_keys("api_key", key_hash, "max_parallel_requests") - expected_tokens: Final = MESSAGES_RESPONSE["usage"]["input_tokens"] + MESSAGES_RESPONSE["usage"]["output_tokens"] - recorder: Final = RecordingLogger() - - async def request(call_id: str, successes: int) -> object: - data: Final = { - "model": MESSAGES_MODEL, - "messages": list(MESSAGES), - "litellm_call_id": call_id, - "max_tokens": 32, - "metadata": { - "user_api_key": key_hash, - "model_group": "cached-model", - "user_api_key_model_max_budget": {"cached-model": {"max_budget": 1, "budget_duration": "1h"}}, - }, - } - await limiter.async_pre_call_hook(identity, counters, data, "acompletion") - assert len(TypeAdapter(dict[str, float]).validate_python(counters.get_cache(parallel_key))) == 1 - response: Final = await invoke( - "chat", recording_server, {**data, "callbacks": [budget, limiter, recorder]}, native=native - ) - await asyncio.gather(*tuple(_PENDING_CACHE_WRITES)) - await recorder.wait_for_async("async_log_success_event", count=successes) - return response - - await asyncio.create_task(request("cache-miss", 1)) - assert counters.get_cache(parallel_key) == {} - assert counters.get_cache(request_key) == 1 - assert counters.get_cache(token_key) == expected_tokens - first_events: Final = await recorder.wait_for_async("async_log_success_event") - first_cost: Final = TypeAdapter(float).validate_python(first_events[0].kwargs["response_cost"]) - assert first_cost > 0 - assert counters.get_cache(spend_key) == pytest.approx(first_cost) - await asyncio.create_task(request("cache-hit", 2)) - expected_spend: Final = first_cost * recording_server.expected_requests - assert counters.get_cache(spend_key) == pytest.approx(expected_spend) - assert len(recording_server.requests) == recording_server.expected_requests - assert counters.get_cache(parallel_key) == {} - assert counters.get_cache(request_key) == 2 - assert counters.get_cache(token_key) == 2 * expected_tokens - with pytest.raises(litellm.RateLimitError): - await asyncio.create_task(request("over-rpm-limit", 3)) - assert len(recording_server.requests) == recording_server.expected_requests - assert counters.get_cache(parallel_key) == {} - assert counters.get_cache(token_key) == 2 * expected_tokens - - assert counters.get_cache(spend_key) == pytest.approx(expected_spend) - if litellm.cache is not None: - await litellm.cache.disconnect() - - -@pytest.mark.asyncio -@pytest.mark.parametrize( - ("route", "legacy"), (("chat", False), ("messages", False), ("responses", False), ("messages", True)) -) -async def test_cache_controls_and_backend_credential_key_semantics( - recording_server: RecordingServer, - route: Literal["chat", "messages", "responses"], - legacy: bool, -) -> None: - recording_server.expected_requests = 3 if legacy else 4 - litellm.cache = Cache() if legacy else _v2.Cache.memory() - await invoke(route, recording_server, {"cache": {"no-store": True}}) - await invoke(route, recording_server, {}) - await invoke(route, recording_server, {}) +async def test_legacy_cache_controls_and_backend_credential_key_semantics(recording_server: RecordingServer) -> None: + recording_server.expected_requests = 3 + litellm.cache = Cache() + await invoke("messages", recording_server, {"cache": {"no-store": True}}) + await invoke("messages", recording_server, {}) + await invoke("messages", recording_server, {}) assert len(recording_server.requests) == 2 - await invoke(route, recording_server, {"cache": {"no-cache": True}}) - await invoke(route, recording_server, {"api_key": "another-key"}) + await invoke("messages", recording_server, {"cache": {"no-cache": True}}) + await invoke("messages", recording_server, {"api_key": "another-key"}) assert len(recording_server.requests) == recording_server.expected_requests @pytest.mark.asyncio -@pytest.mark.parametrize("legacy", (False, True)) -async def test_v2_messages_replays_a_completed_stream(recording_server: RecordingServer, legacy: bool) -> None: +async def test_legacy_messages_replays_a_completed_stream(recording_server: RecordingServer) -> None: recording_server.default_response = ResponseSpec(body=None, events=MESSAGES_EVENTS) - litellm.cache = Cache() if legacy else _v2.Cache.memory() + litellm.cache = Cache() recorder: Final = RecordingLogger() parameters: Final = { "model": MESSAGES_MODEL, @@ -283,74 +180,30 @@ async def test_rust_messages_uses_a_legacy_cache_without_python_inference( @pytest.mark.asyncio -@pytest.mark.parametrize("route", ("chat", "messages", "responses")) @pytest.mark.parametrize("native", (False, True)) -@pytest.mark.parametrize("excluded", (None, [], ["embedding"])) -async def test_v2_cache_honors_supported_call_types_for_reads_and_writes( +async def test_legacy_cache_default_off_requires_opt_in_even_for_existing_entries( recording_server: RecordingServer, monkeypatch: pytest.MonkeyPatch, - route: Literal["chat", "messages", "responses"], native: bool, - excluded: list[CachingSupportedCallTypes] | None, ) -> None: monkeypatch.setenv("LITELLM_RUST", "1" if native else "0") - litellm.cache = _v2.Cache.memory() - call_type: Final[CachingSupportedCallTypes] = ( - "acompletion" if route == "chat" else "anthropic_messages" if route == "messages" else "aresponses" - ) - recording_server.expected_requests = 4 - litellm.cache.supported_call_types = excluded - await invoke(route, recording_server, {}, native=native) - await invoke(route, recording_server, {}, native=native) - assert len(recording_server.requests) == 2 - litellm.cache.supported_call_types = [call_type] - await invoke(route, recording_server, {}, native=native) - assert len(recording_server.requests) == 3 - await asyncio.gather(*tuple(_PENDING_CACHE_WRITES)) - await invoke(route, recording_server, {}, native=native) - assert len(recording_server.requests) == 3 - litellm.cache.supported_call_types = excluded - await invoke(route, recording_server, {}, native=native) - assert len(recording_server.requests) == 4 - - -@pytest.mark.asyncio -@pytest.mark.parametrize("native", (False, True)) -@pytest.mark.parametrize( - ("route", "legacy"), (("chat", False), ("messages", False), ("responses", False), ("messages", True)) -) -async def test_v2_default_off_requires_opt_in_even_for_existing_entries( - recording_server: RecordingServer, - monkeypatch: pytest.MonkeyPatch, - route: Literal["chat", "messages", "responses"], - native: bool, - legacy: bool, -) -> None: - monkeypatch.setenv("LITELLM_RUST", "1" if native else "0") - litellm.cache = Cache() if legacy else _v2.Cache.memory() + litellm.cache = Cache() litellm.cache.mode = CacheMode.default_off recording_server.expected_requests = 4 - await invoke(route, recording_server, {}, native=native) - await invoke(route, recording_server, {}, native=native) + await invoke("messages", recording_server, {}, native=native) + await invoke("messages", recording_server, {}, native=native) assert len(recording_server.requests) == 2 - await invoke(route, recording_server, {"cache": {"use-cache": True}}, native=native) + await invoke("messages", recording_server, {"cache": {"use-cache": True}}, native=native) assert len(recording_server.requests) == 3 await asyncio.gather(*tuple(_PENDING_CACHE_WRITES)) - await invoke(route, recording_server, {"cache": {"use-cache": True}}, native=native) + await invoke("messages", recording_server, {"cache": {"use-cache": True}}, native=native) assert len(recording_server.requests) == 3 - await invoke(route, recording_server, {}, native=native) + await invoke("messages", recording_server, {}, native=native) assert len(recording_server.requests) == 4 @pytest.mark.asyncio -@pytest.mark.parametrize( - ("route", "legacy"), (("chat", False), ("messages", False), ("responses", False), ("messages", True)) -) -async def test_cache_lookup_uses_backend_request_callback_semantics( - recording_server: RecordingServer, - route: Literal["chat", "messages", "responses"], - legacy: bool, -) -> None: +async def test_legacy_cache_lookup_uses_backend_request_callback_semantics(recording_server: RecordingServer) -> None: class Rewrite(RecordingLogger): temperature = 0.1 @@ -359,22 +212,40 @@ async def test_cache_lookup_uses_backend_request_callback_semantics( super().log_pre_api_call(model, messages, kwargs) logger: Final = Rewrite() - litellm.cache = Cache() if legacy else _v2.Cache.memory() - recording_server.expected_requests = 1 if legacy else 2 - await invoke(route, recording_server, {"callbacks": [logger]}) - first_hit: Final = await invoke(route, recording_server, {"callbacks": [logger]}) + litellm.cache = Cache() + recording_server.expected_requests = 1 + await invoke("messages", recording_server, {"callbacks": [logger]}) + first_hit: Final = await invoke("messages", recording_server, {"callbacks": [logger]}) logger.temperature = 0.8 - await invoke(route, recording_server, {"callbacks": [logger]}) - second_hit: Final = await invoke(route, recording_server, {"callbacks": [logger]}) + await invoke("messages", recording_server, {"callbacks": [logger]}) + second_hit: Final = await invoke("messages", recording_server, {"callbacks": [logger]}) assert logger.names.count("log_pre_api_call") == 4 assert len(recording_server.requests) == recording_server.expected_requests assert recording_server.requests[0].body["temperature"] == 0.1 - if not legacy: - assert recording_server.requests[1].body["temperature"] == 0.8 assert isinstance(cache_key(first_hit), str) assert isinstance(cache_key(second_hit), str) - if not legacy: - assert cache_key(first_hit) != cache_key(second_hit) + + +@pytest.mark.asyncio +async def test_rust_chat_completions_rejects_a_configured_python_cache( + recording_server: RecordingServer, monkeypatch: pytest.MonkeyPatch +) -> None: + recording_server.expected_requests = 0 + monkeypatch.setattr(litellm, "cache", Cache()) + with pytest.raises(RuntimeError, match="this inference route does not support configured caches"): + await invoke("chat", recording_server, {}) + assert recording_server.requests == [] + + +@pytest.mark.asyncio +async def test_rust_responses_rejects_a_configured_python_cache( + recording_server: RecordingServer, monkeypatch: pytest.MonkeyPatch +) -> None: + recording_server.expected_requests = 0 + monkeypatch.setattr(litellm, "cache", Cache()) + with pytest.raises(RuntimeError, match="this inference route does not support configured caches"): + await invoke("responses", recording_server, {}) + assert recording_server.requests == [] @pytest.mark.asyncio @@ -430,49 +301,6 @@ async def test_python_cache_operations_stay_in_the_rust_callers_task( assert len(recording_server.requests) == 1 -def test_sync_rust_messages_calls_python_cache(recording_server: RecordingServer) -> None: - from litellm.rust_bridge.messages.entrypoints import NATIVE_MESSAGES - - litellm.cache = Cache() - recording_server.default_response = ResponseSpec(body=MESSAGES_RESPONSE) - arguments: Final = { - "model": MESSAGES_MODEL, - "messages": list(MESSAGES), - "max_tokens": 32, - "api_key": "test-key", - "api_base": recording_server.base_url, - } - request: Final = NativeCall( - args=(), - kwargs=arguments, - base={ - "model": MESSAGES_MODEL, - "messages": list(MESSAGES), - "max_tokens": 32, - "stream": None, - "api_key": "test-key", - "api_base": recording_server.base_url, - "custom_llm_provider": "anthropic", - **arguments, - }, - ) - - def call() -> object: - return runtime.run( - RouteContext(Route.MESSAGES), - binding=NATIVE_MESSAGES, - native=lambda hook: hook(request), - python=runtime.NO_PYTHON, - rules=(RouteRule(Route.MESSAGES, Rollout.RUST_REQUIRED),), - ) - - first: Final = call() - second: Final = call() - assert payload(first) == payload(second) - assert cache_key(second) - assert len(recording_server.requests) == 1 - - @pytest.mark.asyncio @pytest.mark.parametrize("namespace_source", ("cache", "metadata")) async def test_rust_messages_legacy_cache_honors_request_namespaces( diff --git a/tests/test_litellm_rust/cache/v2/test_cache.py b/tests/test_litellm_rust/cache/v2/test_cache.py deleted file mode 100644 index 1461e6eac61..00000000000 --- a/tests/test_litellm_rust/cache/v2/test_cache.py +++ /dev/null @@ -1,207 +0,0 @@ -import asyncio -from collections.abc import AsyncIterator -from typing import Final, Literal - -import pytest -from pydantic import TypeAdapter - -import litellm -from litellm import _v2 -from litellm._v2.cache import NativeBackend -from litellm.caching.caching_handler import ( - _PENDING_CACHE_WRITES, # pyright: ignore[reportPrivateUsage] # await the existing background cache writer before the next request -) -from litellm.litellm_core_utils.add_retry_fallback_headers import get_hidden_params_dict -from litellm.types.utils import ModelResponse -from tests.test_litellm_rust.messages.data import MESSAGES, MESSAGES_MODEL, MESSAGES_RESPONSE -from tests.test_litellm_rust.responses.data import RESPONSES_MODEL, RESPONSES_RESPONSE, RESPONSES_TEXT -from tests.test_litellm_rust.cache.support import cache_key, invoke, payload -from tests.test_litellm_rust.support.callback_recorder import RecordingLogger, drain_logging -from tests.test_litellm_rust.support.recording_server import RecordingServer, ResponseSpec - -pytestmark = pytest.mark.requires_rust_extension - - -@pytest.mark.asyncio -@pytest.mark.parametrize("route", ("chat", "messages", "responses")) -@pytest.mark.parametrize("backend", ("memory", "redis")) -async def test_v2_cache_skips_provider_and_reports_one_success_per_call( - recording_server: RecordingServer, - route: Literal["chat", "messages", "responses"], - backend: Literal["memory", "redis"], - redis_url: str, -) -> None: - recording_server.expected_requests = 2 - litellm.cache = _v2.Cache.memory() if backend == "memory" else _v2.Cache.redis(redis_url, namespace="headers") - recorder: Final = RecordingLogger() - first: Final = await invoke(route, recording_server, {"callbacks": [recorder]}) - await recorder.wait_for_async("async_log_success_event") - second: Final = await invoke(route, recording_server, {"callbacks": [recorder]}) - assert payload(first) == payload(second) - assert cache_key(first) is None - key: Final = cache_key(second) - assert isinstance(key, str) - assert key == get_hidden_params_dict(second)["cache_key"] - assert len(recording_server.requests) == 1 - await drain_logging() - successes: Final = await recorder.wait_for_async("async_log_success_event", count=2) - assert len(successes) == 2 - cached_log: Final = TypeAdapter(dict[str, object]).validate_python(successes[-1].kwargs) - assert cached_log["cache_hit"] is True - assert cached_log["response_cost"] == 0 - await litellm.cache.delete_cache_keys([key]) - refreshed: Final = await invoke(route, recording_server, {"callbacks": [recorder]}) - assert cache_key(refreshed) is None - assert len(recording_server.requests) == 2 - assert len(await recorder.wait_for_async("async_log_success_event", count=3)) == 3 - await litellm.cache.disconnect() - - -@pytest.mark.asyncio -async def test_v2_global_cache_leaves_legacy_only_calls_usable() -> None: - litellm.cache = _v2.Cache.memory() - response: Final = await litellm.aembedding( - model="openai/cache-test-embedding", - input=["hello"], - api_key="test-key", - mock_response=[0.25, 0.75], - ) - assert response.model_dump(include={"data"}) == { - "data": [{"embedding": [0.25, 0.75], "index": 0, "object": "embedding"}] - } - - -@pytest.mark.parametrize("route", ("chat", "responses")) -def test_v2_cache_works_through_python_inference( - recording_server: RecordingServer, route: Literal["chat", "messages", "responses"], monkeypatch: pytest.MonkeyPatch -) -> None: - monkeypatch.setenv("LITELLM_RUST", "0") - litellm.cache = _v2.Cache.memory() - common: Final = {"api_key": "test-key", "api_base": recording_server.base_url} - if route == "responses": - recording_server.default_response = ResponseSpec(body=RESPONSES_RESPONSE) - parameters: Final = {"model": RESPONSES_MODEL, "input": "hello", **common} - first: Final = litellm.responses(**parameters) - second: Final = litellm.responses(**parameters) - assert payload(first) == payload(second) - else: - recording_server.default_response = ResponseSpec(body=MESSAGES_RESPONSE) - arguments: Final = {"model": MESSAGES_MODEL, "messages": list(MESSAGES), "max_tokens": 32, **common} - initial: Final = litellm.completion(**arguments) - cached: Final = litellm.completion(**arguments) - assert isinstance(initial, ModelResponse) and isinstance(cached, ModelResponse) - assert ( - initial.choices[0].message.content - == cached.choices[0].message.content - == MESSAGES_RESPONSE["content"][0]["text"] - ) - assert len(recording_server.requests) == 1 - - -@pytest.mark.asyncio -async def test_v2_facade_and_backend_share_storage_and_management() -> None: - cache: Final = _v2.Cache.memory() - await cache.async_add_cache({"answer": 7}, cache_key="shared") - assert cache.get_cache(cache_key="shared") == {"answer": 7} - assert await cache.ping() is True - await cache.delete_cache_keys(["shared"]) - assert await cache.async_get_cache(cache_key="shared") is None - cache.add_cache({"answer": 8}, cache_key="flush") - backend: Final = cache.cache - assert isinstance(backend, NativeBackend) - backend.flush_cache() - assert cache.get_cache(cache_key="flush") is None - await cache.disconnect() - - -@pytest.mark.asyncio -@pytest.mark.parametrize("control", ("s-maxage", "s-max-age")) -async def test_v2_native_cache_accepts_existing_freshness_aliases( - recording_server: RecordingServer, control: str -) -> None: - litellm.cache = _v2.Cache.memory() - first: Final = await invoke("responses", recording_server, {}) - second: Final = await invoke("responses", recording_server, {"cache": {control: 600}}) - assert payload(first) == payload(second) - assert len(recording_server.requests) == 1 - - -@pytest.mark.asyncio -async def test_v2_cache_does_not_force_native_responses_streaming( - recording_server: RecordingServer, monkeypatch: pytest.MonkeyPatch -) -> None: - monkeypatch.setenv("LITELLM_RUST", "0") - litellm.cache = _v2.Cache.memory() - recording_server.default_response = ResponseSpec( - body=None, - events=( - ("response.created", {"type": "response.created", "sequence_number": 0, "response": RESPONSES_RESPONSE}), - ( - "response.completed", - {"type": "response.completed", "sequence_number": 1, "response": RESPONSES_RESPONSE}, - ), - ), - ) - response: Final = await litellm.aresponses( - model=RESPONSES_MODEL, - input="hello", - stream=True, - caching=False, - api_key="test-key", - api_base=recording_server.base_url, - ) - assert isinstance(response, AsyncIterator) - chunks: Final = [chunk async for chunk in response] - assert chunks[-1].type == "response.completed" - assert chunks[-1].response.output[0].content[0].text == RESPONSES_TEXT - - -@pytest.mark.asyncio -async def test_v2_cache_works_through_python_messages( - recording_server: RecordingServer, monkeypatch: pytest.MonkeyPatch -) -> None: - monkeypatch.setenv("LITELLM_RUST", "0") - litellm.cache = _v2.Cache.memory() - recording_server.default_response = ResponseSpec(body=MESSAGES_RESPONSE) - parameters: Final = { - "model": MESSAGES_MODEL, - "messages": list(MESSAGES), - "max_tokens": 32, - "api_key": "test-key", - "api_base": recording_server.base_url, - } - first: Final = await litellm.anthropic_messages(**parameters) - await asyncio.gather(*tuple(_PENDING_CACHE_WRITES)) - second: Final = await litellm.anthropic_messages(**parameters) - assert payload(first) == payload(second) - assert len(recording_server.requests) == 1 - - -@pytest.mark.asyncio -@pytest.mark.parametrize("asynchronous", (False, True)) -async def test_v2_redis_flush_only_removes_its_namespace( - redis_url: str, recording_server: RecordingServer, asynchronous: bool -) -> None: - own: Final = _v2.Cache.redis(redis_url, namespace="flush-own") - other: Final = _v2.Cache.redis(redis_url, namespace="flush-other") - litellm.cache = own - recording_server.expected_requests = 2 - await own.async_add_cache({"answer": "own"}, cache_key="shared") - await other.async_add_cache({"answer": "other"}, cache_key="shared") - await invoke("responses", recording_server, {}) - hit: Final = await invoke("responses", recording_server, {}) - assert isinstance(cache_key(hit), str) - assert await own.async_get_cache(cache_key="shared") == {"answer": "own"} - backend: Final = own.cache - assert isinstance(backend, NativeBackend) - if asynchronous: - await backend.async_flush_cache() - else: - backend.flush_cache() - assert await own.async_get_cache(cache_key="shared") is None - assert await other.async_get_cache(cache_key="shared") == {"answer": "other"} - refreshed: Final = await invoke("responses", recording_server, {}) - assert cache_key(refreshed) is None - assert len(recording_server.requests) == 2 - await own.disconnect() - await other.disconnect() diff --git a/tests/test_litellm_rust/messages/test_callbacks.py b/tests/test_litellm_rust/messages/test_callbacks.py index cd5478dfc3a..a3c03898a12 100644 --- a/tests/test_litellm_rust/messages/test_callbacks.py +++ b/tests/test_litellm_rust/messages/test_callbacks.py @@ -14,7 +14,6 @@ from litellm.types.integrations.argilla import ArgillaItem from litellm.types.utils import ModelResponse, StandardLoggingPayload from tests.test_litellm_rust.messages.data import BAD_REQUEST, MESSAGES_RESPONSE, RATE_LIMITED, call from tests.test_litellm_rust.support.callback_recorder import HookRecorder, RecordingLogger, request_body -from tests.test_litellm_rust.support.gaps import gap from tests.test_litellm_rust.support.isolation import rebound from tests.test_litellm_rust.support.recording_server import RecordingServer, ResponseSpec, relaxed from tests.test_litellm_rust.support.results import response_id, with_id @@ -22,7 +21,6 @@ from tests.test_litellm_rust.support.routing import assert_served_natively pytestmark = pytest.mark.requires_rust_extension -SYNC_HANDLERS_ON_ASYNC_CALLS: Final = gap("native async calls also run the sync success and failure handlers") _OBJECT: Final = TypeAdapter(dict[str, object]) _HEADERS: Final = TypeAdapter(dict[str, str]) @@ -211,7 +209,7 @@ async def test_pre_call_deployment_rejection_logs_failure_without_provider_io(se failures: Final = await recorder.wait_for_async("async_log_failure_event") assert raised.value is rejection - assert server.requests == [] + assert not server.requests assert len(failures) == 1 assert _OBJECT.validate_python(failures[0].kwargs)["exception"] is raised.value assert not {"log_pre_api_call", "log_success_event", "async_log_success_event"} & set(recorder.names) @@ -341,8 +339,8 @@ async def test_a_failing_logger_does_not_fail_the_call(server: RecordingServer) pytest.param("input", False, False, 1, id="global-input"), pytest.param("success", True, False, 1, id="global-async-success"), pytest.param("success", True, True, 1, id="request-async-success"), - pytest.param("success", False, False, 0, id="global-sync-success", marks=SYNC_HANDLERS_ON_ASYNC_CALLS), - pytest.param("success", False, True, 0, id="request-sync-success", marks=SYNC_HANDLERS_ON_ASYNC_CALLS), + pytest.param("success", False, False, 0, id="global-sync-success"), + pytest.param("success", False, True, 0, id="request-sync-success"), pytest.param("failure", True, False, 1, id="global-async-failure"), pytest.param("failure", False, False, 1, id="global-sync-failure"), pytest.param("failure", False, True, 1, id="request-sync-failure"), @@ -384,12 +382,11 @@ async def test_pre_call_rule_rejects_before_provider_io(server: RecordingServer) checked.append(text) return False - with rebound(litellm, "pre_call_rules", [reject]): - with pytest.raises(litellm.APIResponseValidationError): - await call(server) + with rebound(litellm, "pre_call_rules", [reject]), pytest.raises(litellm.APIResponseValidationError): + await call(server) assert checked == ["Hello"] - assert server.requests == [] + assert not server.requests @pytest.mark.asyncio @@ -419,11 +416,11 @@ async def test_dataset_hook_returning_none_drops_the_record_from_the_success_sin @pytest.mark.asyncio -async def test_sync_call_returns_the_provider_message(server: RecordingServer) -> None: +async def test_sync_call_raises_like_python_without_logging(server: RecordingServer) -> None: recorder: Final = RecordingLogger() - response: Final = await call(server, asynchronous=False, callbacks=[recorder]) + with pytest.raises(ValueError, match="anthropic_messages_handler is not implemented for sync calls"): + await call(server, asynchronous=False, callbacks=[recorder]) - assert_served_natively(server, response) - assert response_id(response) == MESSAGES_RESPONSE["id"] - assert len(await recorder.wait_for_async("log_success_event")) == 1 + assert not server.requests + assert not recorder.names diff --git a/tests/test_litellm_rust/messages/test_dispatch.py b/tests/test_litellm_rust/messages/test_dispatch.py index 5b11e628b8d..6d65f289524 100644 --- a/tests/test_litellm_rust/messages/test_dispatch.py +++ b/tests/test_litellm_rust/messages/test_dispatch.py @@ -569,6 +569,12 @@ async def test_strict_tools_stay_native_unless_python_could_drop_strict( ASYNC_ONLY_FEATURES: Final = ( pytest.param(Feature.PRE_REQUEST_HOOK, {}, {"callbacks": [_Rewrite()]}, id="pre-request-hook"), + pytest.param( + Feature.FOUNDRY_BETA_ROW, + {"api_base": "https://team.services.ai.azure.com/anthropic"}, + {}, + id="foundry-beta-row", + ), pytest.param( Feature.WEBSEARCH_INTERCEPTION, {}, {"callbacks": [WebSearchInterceptionLogger()]}, id="websearch-interception" ), diff --git a/tests/test_litellm_rust/messages/test_streaming.py b/tests/test_litellm_rust/messages/test_streaming.py index c700c093d1a..e57631f48b9 100644 --- a/tests/test_litellm_rust/messages/test_streaming.py +++ b/tests/test_litellm_rust/messages/test_streaming.py @@ -6,7 +6,6 @@ import pytest from tests.test_litellm_rust.messages.data import MESSAGES_EVENTS, MESSAGES_RESPONSE, call from tests.test_litellm_rust.support.callback_recorder import RecordingLogger, drain_logging from tests.test_litellm_rust.support.recording_server import RecordingServer, ResponseSpec, relaxed -from tests.test_litellm_rust.support.results import consume from tests.test_litellm_rust.support.routing import assert_served_natively pytestmark = pytest.mark.requires_rust_extension @@ -46,16 +45,14 @@ async def test_stream_relays_provider_events_and_logs_success_once_after_the_las @pytest.mark.asyncio -async def test_sync_stream_relays_provider_events_and_logs_success_once(server: RecordingServer) -> None: - server.enqueue(STREAM) +async def test_sync_stream_raises_like_python_before_sending(server: RecordingServer) -> None: recorder: Final = RecordingLogger() - stream: Final = await call(server, asynchronous=False, stream=True, callbacks=[recorder]) - chunks: Final = await consume(stream) + with pytest.raises(ValueError, match="anthropic_messages_handler is not implemented for sync calls"): + await call(server, asynchronous=False, stream=True, callbacks=[recorder]) - assert_served_natively(server) - assert b"".join(chunks) == b"".join(STREAM.payloads()) - assert len(await recorder.wait_for_async("async_log_success_event")) == 1 + assert not server.requests + assert not recorder.names @pytest.mark.asyncio diff --git a/tests/test_litellm_rust/support/recording_server.py b/tests/test_litellm_rust/support/recording_server.py index d7b82767b97..5743658abdf 100644 --- a/tests/test_litellm_rust/support/recording_server.py +++ b/tests/test_litellm_rust/support/recording_server.py @@ -25,13 +25,16 @@ class ResponseSpec: status: int = 200 headers: dict[str, str] = field(default_factory=dict) delay: float = 0 + chunk_delay: float = 0 events: tuple[tuple[str, object], ...] = () + # Splits a non-stream body into this many writes, `chunk_delay` apart, so it trickles in. + body_chunks: int = 1 def payloads(self) -> tuple[bytes, ...]: - if isinstance(self.body, bytes): - return (self.body,) if not self.events: - return (json.dumps(self.body).encode(),) + body: Final = self.body if isinstance(self.body, bytes) else json.dumps(self.body).encode() + size: Final = max(-(-len(body) // max(self.body_chunks, 1)), 1) + return tuple(body[start : start + size] for start in range(0, len(body), size)) or (body,) return tuple(f"event: {event}\ndata: {json.dumps(data)}\n\n".encode() for event, data in self.events) @@ -89,7 +92,9 @@ def recording_service() -> Iterator[RecordingServer]: self.send_header(name, value) self.end_headers() try: - for payload in payloads: + for index, payload in enumerate(payloads): + if index and response.chunk_delay: + time.sleep(response.chunk_delay) self.wfile.write(payload) self.wfile.flush() except (BrokenPipeError, ConnectionResetError): diff --git a/tests/unit/accounting/test_delivery_projection.py b/tests/unit/accounting/test_delivery_projection.py new file mode 100644 index 00000000000..0b1f36d6b48 --- /dev/null +++ b/tests/unit/accounting/test_delivery_projection.py @@ -0,0 +1,85 @@ +import json +from collections.abc import Mapping +from datetime import datetime, timedelta, timezone +from typing import Final +from urllib.parse import unquote + +from litellm.accounting.delivery_projection import entity_transactions, project_deliveries +from litellm.accounting.projection import Contribution +from litellm.repositories.accounting_delivery_repository import DeliveryProjection + +_NOW: Final = datetime(2026, 11, 2, tzinfo=timezone.utc) + + +def _payload(spend: float, started: datetime = _NOW, window_start: datetime = _NOW) -> Mapping[str, object]: + return { + "request_id": f"request-{spend}-{started.isoformat()}", + "startTime": started, + "api_key": "key", + "user": "user/1", + "team_id": "team", + "organization_id": "org::1", + "spend": spend, + "metadata": json.dumps( + { + "accounting_entities": { + "api_key": "key", + "user": "user/1", + "team_id": "team", + "organization_id": "org::1", + }, + "accounting_windows": [ + { + "entity_type": "key", + "entity_id": "key", + "window_duration": "1d", + "window_start": window_start.isoformat(), + } + ], + } + ), + } + + +def _spend(contributions: tuple[Contribution, ...], table: str) -> tuple[float, ...]: + return tuple(float(dict(item.increments)["spend"]) for item in contributions if item.table == table) + + +def test_deliveries_for_one_destination_sum_and_keep_the_earliest_request_start() -> None: + later: Final = _NOW + timedelta(hours=1) + + contributions: Final = project_deliveries( + (DeliveryProjection(_payload(0.5, started=later)), DeliveryProjection(_payload(0.25))) + ) + + assert _spend(contributions, "LiteLLM_VerificationToken") == (0.75,) + windows: Final = tuple(item for item in contributions if item.table == "LiteLLM_BudgetWindowSpend") + assert len(windows) == 1 + assert dict(windows[0].increments) == {"spend": 0.75} + assert dict(windows[0].values)["started_at"] == str(_NOW) + + +def test_the_same_window_in_a_new_period_is_charged_to_its_own_row() -> None: + next_day: Final = _NOW + timedelta(days=1) + + contributions: Final = project_deliveries( + (DeliveryProjection(_payload(0.25)), DeliveryProjection(_payload(0.5, window_start=next_day))) + ) + + windows: Final = sorted( + (dict(item.values)["window_start"], dict(item.increments)["spend"]) + for item in contributions + if item.table == "LiteLLM_BudgetWindowSpend" + ) + assert windows == [(_NOW.isoformat(), 0.25), (next_day.isoformat(), 0.5)] + + +def test_entity_transactions_key_memberships_the_way_the_writer_applies_them() -> None: + transactions: Final = entity_transactions(project_deliveries((DeliveryProjection(_payload(0.25)),))) + + assert transactions["key_list_transactions"] == {"key": 0.25} + assert transactions["org_list_transactions"] == {"org::1": 0.25} + assert transactions["team_member_list_transactions"] == {"team_id::team::user_id::user/1": 0.25} + ((org_member_key, org_member_spend),) = transactions["org_member_list_transactions"].items() + _, quoted_org_id, _, quoted_user_id = org_member_key.split("::") + assert (unquote(quoted_org_id), unquote(quoted_user_id), org_member_spend) == ("org::1", "user/1", 0.25) diff --git a/tests/unit/accounting/test_measurements.py b/tests/unit/accounting/test_measurements.py deleted file mode 100644 index b65c3076c5d..00000000000 --- a/tests/unit/accounting/test_measurements.py +++ /dev/null @@ -1,235 +0,0 @@ -from datetime import datetime, timezone -from decimal import Decimal -from typing import Final - -import pytest - -from litellm.accounting import ( - CostEvent, - Dimension, - DimensionName, - InboundUsageEvent, - Measurement, - Metric, - MetricName, - Outcome, - OutboundUsageEvent, - PricingSnapshot, - measurements_for, -) -from litellm.types.utils import CallTypes - -_START: Final = datetime(2026, 1, 1, 23, 59, 59, tzinfo=timezone.utc) -_END: Final = datetime(2026, 1, 2, tzinfo=timezone.utc) -_DIMENSIONS: Final = ( - Dimension(name=DimensionName.TEAM, value="team"), - Dimension(name=DimensionName.TAG, value="alpha"), - Dimension(name=DimensionName.TAG, value="beta"), -) - - -def _snapshot(amount: Decimal) -> PricingSnapshot: - return PricingSnapshot( - calculator_version="test", - model="test-model", - provider=None, - pricing_source="upstream_header", - priced_model_key="test-model", - upstream_reported_cost=amount, - total_cost=amount, - ) - - -@pytest.mark.parametrize( - ("outcome", "outcome_metric"), - [ - (Outcome.SUCCEEDED, MetricName.SUCCESSFUL_REQUESTS), - (Outcome.FAILED, MetricName.FAILED_REQUESTS), - (Outcome.CANCELLED, MetricName.FAILED_REQUESTS), - ], -) -def test_caller_measurements_keep_both_request_and_outcome_counts(outcome, outcome_metric): - event = InboundUsageEvent( - event_id="caller-event", - request_id="caller", - call_type=CallTypes.acompletion, - started_at=_START, - ended_at=_END, - outcome=outcome, - dimensions=_DIMENSIONS, - metrics=(Metric(name=MetricName.REQUESTS, value=Decimal(1)), Metric(name=outcome_metric, value=Decimal(1))), - ) - assert measurements_for(event) == ( - Measurement( - source_event_id="caller-event", - occurred_at=_START, - dimensions=_DIMENSIONS, - metric=Metric(name=MetricName.REQUESTS, value=Decimal(1)), - ), - Measurement( - source_event_id="caller-event", - occurred_at=_START, - dimensions=_DIMENSIONS, - metric=Metric(name=outcome_metric, value=Decimal(1)), - ), - ) - - -def test_usage_measurements_keep_every_metric_in_the_start_time_bucket(): - event = OutboundUsageEvent( - event_id="usage-event", - attempt_id="attempt", - request_id="caller", - retry_of_attempt_id=None, - call_type=CallTypes.acompletion, - started_at=_START, - ended_at=_END, - outcome=Outcome.SUCCEEDED, - dimensions=_DIMENSIONS, - metrics=( - Metric(name=MetricName.PROMPT_TOKENS, value=Decimal(10)), - Metric(name=MetricName.COMPLETION_TOKENS, value=Decimal(2)), - Metric(name=MetricName.TOTAL_TOKENS, value=Decimal(12)), - Metric(name=MetricName.CACHE_READ_INPUT_TOKENS, value=Decimal(3)), - Metric(name=MetricName.CACHE_CREATION_INPUT_TOKENS, value=Decimal(1)), - ), - ) - assert measurements_for(event) == ( - Measurement( - source_event_id="usage-event", - occurred_at=_START, - dimensions=_DIMENSIONS, - metric=Metric(name=MetricName.PROMPT_TOKENS, value=Decimal(10)), - ), - Measurement( - source_event_id="usage-event", - occurred_at=_START, - dimensions=_DIMENSIONS, - metric=Metric(name=MetricName.COMPLETION_TOKENS, value=Decimal(2)), - ), - Measurement( - source_event_id="usage-event", - occurred_at=_START, - dimensions=_DIMENSIONS, - metric=Metric(name=MetricName.TOTAL_TOKENS, value=Decimal(12)), - ), - Measurement( - source_event_id="usage-event", - occurred_at=_START, - dimensions=_DIMENSIONS, - metric=Metric(name=MetricName.CACHE_READ_INPUT_TOKENS, value=Decimal(3)), - ), - Measurement( - source_event_id="usage-event", - occurred_at=_START, - dimensions=_DIMENSIONS, - metric=Metric(name=MetricName.CACHE_CREATION_INPUT_TOKENS, value=Decimal(1)), - ), - ) - - -@pytest.mark.parametrize("metrics", [None, ()]) -def test_unknown_or_empty_usage_does_not_fabricate_zero_measurements(metrics): - event = OutboundUsageEvent( - event_id="usage-event", - attempt_id="attempt", - request_id=None, - retry_of_attempt_id=None, - call_type=CallTypes.acompletion, - started_at=_START, - ended_at=_END, - outcome=Outcome.SUCCEEDED, - dimensions=(), - metrics=metrics, - ) - assert measurements_for(event) == () - - -@pytest.mark.parametrize("amount", [Decimal(0), Decimal("0.1234567890123456789")]) -def test_cost_measurements_preserve_authoritative_amount_identity_and_occurrence(amount): - event = CostEvent( - event_id="cost-event", - usage_event_id="usage-event", - occurred_at=_END, - dimensions=_DIMENSIONS, - charges=(Metric(name=MetricName.SPEND, value=amount, unit="USD"),), - snapshot=_snapshot(amount), - ) - assert measurements_for(event) == ( - Measurement( - source_event_id="cost-event", - occurred_at=_END, - dimensions=_DIMENSIONS, - metric=Metric(name=MetricName.SPEND, value=amount, unit="USD"), - ), - ) - - -def test_billed_retry_and_success_contribute_one_caller_request_and_both_charges(): - caller = InboundUsageEvent( - event_id="caller-event", - request_id="caller", - call_type=CallTypes.acompletion, - started_at=_START, - ended_at=_END, - outcome=Outcome.SUCCEEDED, - dimensions=_DIMENSIONS, - metrics=(Metric(name=MetricName.REQUESTS, value=Decimal(1)),), - ) - retry = OutboundUsageEvent( - event_id="retry-usage", - attempt_id="retry", - request_id="caller", - retry_of_attempt_id=None, - call_type=CallTypes.acompletion, - started_at=_START, - ended_at=_END, - outcome=Outcome.FAILED, - dimensions=_DIMENSIONS, - metrics=(Metric(name=MetricName.TOTAL_TOKENS, value=Decimal(4)),), - ) - success = OutboundUsageEvent( - event_id="success-usage", - attempt_id="success", - request_id="caller", - retry_of_attempt_id="retry", - call_type=CallTypes.acompletion, - started_at=_START, - ended_at=_END, - outcome=Outcome.SUCCEEDED, - dimensions=_DIMENSIONS, - metrics=(Metric(name=MetricName.TOTAL_TOKENS, value=Decimal(12)),), - ) - retry_cost = CostEvent( - event_id="retry-cost", - usage_event_id="retry-usage", - occurred_at=_START, - dimensions=_DIMENSIONS, - charges=(Metric(name=MetricName.SPEND, value=Decimal("0.025"), unit="USD"),), - snapshot=_snapshot(Decimal("0.025")), - ) - success_cost = CostEvent( - event_id="success-cost", - usage_event_id="success-usage", - occurred_at=_START, - dimensions=_DIMENSIONS, - charges=(Metric(name=MetricName.SPEND, value=Decimal("0.125"), unit="USD"),), - snapshot=_snapshot(Decimal("0.125")), - ) - measurements = ( - *measurements_for(caller), - *measurements_for(retry), - *measurements_for(success), - *measurements_for(retry_cost), - *measurements_for(success_cost), - ) - assert sum(m.metric.value for m in measurements if m.metric.name is MetricName.REQUESTS) == Decimal(1) - assert sum(m.metric.value for m in measurements if m.metric.name is MetricName.TOTAL_TOKENS) == Decimal(16) - assert sum(m.metric.value for m in measurements if m.metric.name is MetricName.SPEND) == Decimal("0.150") - assert {m.source_event_id for m in measurements} == { - "caller-event", - "retry-usage", - "success-usage", - "retry-cost", - "success-cost", - } diff --git a/tests/unit/accounting/test_metrics.py b/tests/unit/accounting/test_metrics.py new file mode 100644 index 00000000000..49b46eb36c2 --- /dev/null +++ b/tests/unit/accounting/test_metrics.py @@ -0,0 +1,28 @@ +from prometheus_client.metrics import MetricWrapperBase + +from litellm.accounting import metrics +from litellm.accounting.metrics import record_deliveries +from litellm.repositories.accounting_delivery_repository import DeliveryMetrics + + +def _sample(metric: MetricWrapperBase, suffix: str = "") -> float: + family = metric.collect()[0] + return next(sample.value for sample in family.samples if sample.name == family.name + suffix) + + +def test_delivery_metrics_publish_backlog_and_clamp_clock_skew() -> None: + batches_before = _sample(metrics._BATCH_TIME, "_count") + + record_deliveries( + DeliveryMetrics(pending_count=4, parked_count=1, oldest_pending_seconds=-3.0, batch_count=7, table_bytes=8192), + 0.5, + ) + + assert ( + _sample(metrics._PENDING), + _sample(metrics._PARKED), + _sample(metrics._OLDEST), + _sample(metrics._BATCH_COUNT), + _sample(metrics._TABLE_BYTES), + ) == (4.0, 1.0, 0.0, 7.0, 8192.0) + assert _sample(metrics._BATCH_TIME, "_count") == batches_before + 1 diff --git a/tests/unit/accounting/test_projection.py b/tests/unit/accounting/test_projection.py new file mode 100644 index 00000000000..17186a89922 --- /dev/null +++ b/tests/unit/accounting/test_projection.py @@ -0,0 +1,557 @@ +import json +from collections.abc import Mapping +from datetime import datetime, timezone +from typing import Final + +import pytest +from pydantic import TypeAdapter + +from litellm.accounting.projection import project +from litellm.accounting.snapshot import build_accounting_payload +from litellm.constants import BILLED_RETRY_ATTEMPT_METADATA_KEY, INTERNAL_CALL_ORIGIN_METADATA_KEY +from litellm.proxy._types import SpendLogsPayload +from litellm.proxy.db.db_spend_update_writer import DBSpendUpdateWriter +from litellm.proxy.proxy_server import proxy_logging_obj +from litellm.proxy.spend_tracking.spend_tracking_utils import get_logging_payload +from litellm.proxy.utils import PrismaClient +from litellm.types.utils import ModelResponse, Usage + +_NOW: Final = datetime(2026, 11, 2, tzinfo=timezone.utc) +_FIELDS: Final = TypeAdapter(dict[str, object]) + + +@pytest.mark.parametrize("status", ["success", "failure"]) +@pytest.mark.parametrize("origin", [None, "auto_router", "billed_retry"]) +@pytest.mark.parametrize("spend", [0.0, 0.25]) +@pytest.mark.asyncio +async def test_daily_projection_matches_legacy_writer(status: str, origin: str | None, spend: float) -> None: + payload: Final = get_logging_payload( + kwargs={ + "model": "projection-test", + "custom_llm_provider": "openai", + "call_type": "acompletion", + "litellm_call_id": "projection-request", + "litellm_params": {"metadata": {"user_api_key": "key", "user_api_key_user_id": "user", "status": status}}, + }, + response_obj=ModelResponse( + id="projection-request", model="projection-test", usage=Usage(prompt_tokens=10, completion_tokens=5) + ), + start_time=_NOW, + end_time=_NOW, + ) + metadata: Final = { + **_FIELDS.validate_json(payload["metadata"]), + **({BILLED_RETRY_ATTEMPT_METADATA_KEY: True} if origin == "billed_retry" else {}), + **({INTERNAL_CALL_ORIGIN_METADATA_KEY: origin} if origin not in (None, "billed_retry") else {}), + } + row: Final = {**payload, "spend": spend, "metadata": json.dumps(metadata), "request_duration_ms": 25} + legacy: Final = await DBSpendUpdateWriter()._common_add_spend_log_transaction_to_daily_transaction( + row, PrismaClient(database_url="postgresql://unused", proxy_logging_obj=proxy_logging_obj), "user" + ) + assert legacy is not None + accounting_input: Final[SpendLogsPayload] = {**row} + accounting: Final = build_accounting_payload( + accounting_input, + entities={"api_key": payload["api_key"], "user": payload["user"]}, + model_access_groups=(), + windows=(), + router=lambda: None, + ) + restored: Final = _FIELDS.validate_json(json.dumps(accounting, default=str)) + stored_daily: Final = next(item for item in project(restored) if item.table == "LiteLLM_DailyUserSpend") + assert dict(stored_daily.increments) == {name: legacy[name] for name, _ in stored_daily.increments} + assert dict(stored_daily.key)["date"] == legacy["date"] + assert dict(stored_daily.key)["api_key"] == legacy["api_key"] + assert not {"messages", "response", "proxy_server_request", "requester_ip_address"}.intersection(accounting) + + +def test_projection_uses_frozen_savings_and_keeps_duplicate_entity_tags() -> None: + row: Final[Mapping[str, object]] = { + "request_id": "saved", + "startTime": _NOW, + "api_key": "key", + "user": "user", + "model": "unpriced-projection-test", + "model_group": "group", + "custom_llm_provider": "openai", + "request_tags": '["tag", "tag"]', + "spend": 0.5, + "metadata": json.dumps( + { + "accounting_savings": { + "compression": 1.0, + "prompt_caching": -2.0, + "gateway_injected_caching": 3.0, + "autorouter": 4.0, + }, + "autorouter_savings": 9000, + } + ), + } + contributions: Final = project(row) + tags: Final = tuple(item for item in contributions if item.table == "LiteLLM_TagTable") + daily_tags: Final = tuple(item for item in contributions if item.table == "LiteLLM_DailyTagSpend") + assert sum(dict(item.increments)["spend"] for item in tags) == 1.0 + assert len(daily_tags) == 1 + assert {key: value for key, value in daily_tags[0].increments if key.endswith("savings_spend")} == { + "compression_savings_spend": 1.0, + "prompt_caching_savings_spend": -2.0, + "gateway_injected_caching_savings_spend": 3.0, + "autorouter_savings_spend": 4.0, + } + + +def test_projection_carries_windows_and_does_not_reprice_guardrails() -> None: + row: Final = { + "request_id": "guarded", + "startTime": _NOW, + "api_key": "key", + "spend": 0.75, + "metadata": json.dumps( + { + "accounting_windows": [ + { + "entity_type": "key", + "entity_id": "key", + "window_duration": "1d", + "window_start": _NOW.isoformat(), + } + ], + "guardrail_information": [ + { + "guardrail_id": "guard", + "guardrail_usage": {"text": 3, "images": 2}, + "guardrail_cost_by_unit": {"text": 0.3, "images": None}, + } + ], + } + ), + } + contributions: Final = project(row) + window: Final = next(item for item in contributions if item.table == "LiteLLM_BudgetWindowSpend") + units: Final = { + dict(item.key)["usage_unit"]: dict(item.increments) + for item in contributions + if item.table == "LiteLLM_DailyGuardrailUsageUnits" + } + assert dict(window.increments) == {"spend": 0.75} + assert dict(window.values)["window_start"] == _NOW.isoformat() + assert units == { + "text": {"units": 3, "cost": 0.3, "untracked_units": 0}, + "images": {"units": 2, "cost": 0.0, "untracked_units": 2}, + } + + +@pytest.mark.asyncio +async def test_entity_projection_matches_real_request_queues(monkeypatch: pytest.MonkeyPatch) -> None: + from litellm.proxy import proxy_server + from litellm.responses.streaming_iterator import drain_logging_tasks + + client: Final = PrismaClient(database_url="postgresql://unused", proxy_logging_obj=proxy_logging_obj) + monkeypatch.setattr(proxy_server, "prisma_client", client) + monkeypatch.setattr(proxy_server, "disable_spend_logs", False) + monkeypatch.setattr(client, "spend_log_transactions", []) + monkeypatch.setattr(client, "model_usage_transactions", []) + writer: Final = DBSpendUpdateWriter() + charged: Final = await writer.update_database( + token="sk-projection", + user_id="user", + end_user_id="end-user", + team_id="team", + org_id="org", + project_id="project", + kwargs={ + "model": "projection-test", + "custom_llm_provider": "openai", + "call_type": "acompletion", + "litellm_call_id": "entity-request", + "agent_id": "agent", + "user": "end-user", + "litellm_params": { + "metadata": { + "user_api_key": "sk-projection", + "user_api_key_user_id": "user", + "user_api_key_team_id": "team", + "user_api_key_org_id": "org", + "user_api_key_project_id": "project", + "user_api_key_end_user_id": "end-user", + "tags": ["tag", "tag"], + }, + "user": "end-user", + }, + }, + completion_response=ModelResponse( + id="entity-request", model="projection-test", usage=Usage(prompt_tokens=10, completion_tokens=5) + ), + start_time=_NOW, + end_time=_NOW, + response_cost=0.25, + ) + await drain_logging_tasks() + assert charged + assert len(client.spend_log_transactions) == 1 + queued: Final = await writer.spend_update_queue.flush_all_updates_from_in_memory_queue() + logged: Final[SpendLogsPayload] = client.spend_log_transactions[0] + projected: Final = project( + _FIELDS.validate_json( + json.dumps( + build_accounting_payload( + logged, + entities={ + "api_key": logged["api_key"], + "user": "user", + "end_user": "end-user", + "team_id": "team", + "organization_id": "org", + "project_id": "project", + "agent_id": "agent", + }, + model_access_groups=(), + windows=(), + router=lambda: None, + ), + default=str, + ) + ) + ) + legacy: Final = {(item["entity_type"].value, item["entity_id"]): item["response_cost"] for item in queued} + assert legacy[("key", proxy_server.hash_token("sk-projection"))] == next( + dict(item.increments)["spend"] for item in projected if item.table == "LiteLLM_VerificationToken" + ) + for table, entity, identity in ( + ("LiteLLM_UserTable", "user", "user"), + ("LiteLLM_TeamTable", "team", "team"), + ("LiteLLM_OrganizationTable", "organization", "org"), + ("LiteLLM_EndUserTable", "end_user", "end-user"), + ("LiteLLM_AgentsTable", "agent", "agent"), + ("LiteLLM_ProjectTable", "project", "project"), + ): + assert legacy[(entity, identity)] == next( + dict(item.increments)["spend"] for item in projected if item.table == table + ) + assert sum(dict(item.increments)["spend"] for item in projected if item.table == "LiteLLM_TagTable") == sum( + item["response_cost"] or 0 for item in queued if item["entity_type"].value == "tag" + ) + + daily_queues: Final = ( + ("LiteLLM_DailyUserSpend", writer.daily_spend_update_queue), + ("LiteLLM_DailyTeamSpend", writer.daily_team_spend_update_queue), + ("LiteLLM_DailyOrganizationSpend", writer.daily_org_spend_update_queue), + ("LiteLLM_DailyEndUserSpend", writer.daily_end_user_spend_update_queue), + ("LiteLLM_DailyAgentSpend", writer.daily_agent_spend_update_queue), + ("LiteLLM_DailyTagSpend", writer.daily_tag_spend_update_queue), + ) + for table, queue in daily_queues: + transactions = await queue.flush_and_get_aggregated_daily_spend_update_transactions() + matching = tuple(item for item in projected if item.table == table) + assert matching, table + contribution = matching[0] + assert len(transactions) == 1 + transaction = next(iter(transactions.values())) + assert dict(contribution.increments) == {name: transaction[name] for name, _ in contribution.increments} + assert len(client.model_usage_transactions) == 1 + model: Final = client.model_usage_transactions[0] + model_projection: Final = next(item for item in projected if item.table == "LiteLLM_DailyModelUsage") + assert dict(model_projection.increments) == { + "spend": model.spend, + "prompt_tokens": model.prompt_tokens, + "completion_tokens": model.completion_tokens, + "request_count": int(model.counts_as_request), + "successful_requests": int(model.successful), + "failed_requests": int(not model.successful), + } + + +@pytest.mark.parametrize("served_id", ["requested", "fallback", "missing"]) +@pytest.mark.asyncio +async def test_projection_preserves_fallback_narrowed_model_access_groups(served_id: str) -> None: + from litellm import Router + from litellm.proxy.db.db_spend_update_writer import debitable_model_access_groups + + router: Final = Router( + model_list=[ + { + "model_name": "first", + "litellm_params": {"model": "openai/projection-test", "api_key": "unused"}, + "model_info": {"id": "requested", "access_groups": ["first-group"]}, + }, + { + "model_name": "second", + "litellm_params": {"model": "openai/projection-test", "api_key": "unused"}, + "model_info": {"id": "fallback", "access_groups": ["second-group", "unattributed"]}, + }, + ] + ) + attributed: Final = ("first-group", "second-group", "first-group") + writer: Final = DBSpendUpdateWriter() + client: Final = PrismaClient(database_url="postgresql://unused", proxy_logging_obj=proxy_logging_obj) + await writer._update_model_access_group_db(0.5, attributed, served_id, client, router) + queued: Final = await writer.spend_update_queue.flush_all_updates_from_in_memory_queue() + frozen_groups: Final = debitable_model_access_groups(attributed, served_id, router) + projected: Final = project( + {"spend": 0.5, "metadata": json.dumps({"accounting_model_access_groups": frozen_groups})} + ) + assert {dict(item.key)["access_group_name"]: dict(item.increments)["spend"] for item in projected} == { + item["entity_id"]: item["response_cost"] for item in queued + } + assert "unattributed" not in frozen_groups + + +def test_guardrail_projection_skips_unmeasured_counters() -> None: + row: Final = { + "request_id": "guarded", + "startTime": _NOW, + "metadata": json.dumps( + { + "guardrail_information": [ + {"guardrail_usage": {"text": 3}}, + { + "guardrail_id": "guard", + "guardrail_usage": {"zero": 0, "negative": -1, "bool": True, "unknown": None, "text": 2}, + }, + ] + } + ), + } + units: Final = tuple(item for item in project(row) if item.table == "LiteLLM_DailyGuardrailUsageUnits") + assert len(units) == 1 + assert dict(units[0].key)["usage_unit"] == "text" + assert dict(units[0].increments) == {"units": 2, "cost": 0.0, "untracked_units": 2} + + +def test_lean_row_without_model_does_not_fabricate_daily_entity_usage() -> None: + projected: Final = project( + { + "request_id": "lean", + "api_key": "key", + "startTime": _NOW, + "spend": 0.5, + "metadata": {"accounting_entities": {"api_key": "key"}}, + } + ) + assert tuple(item.table for item in projected) == ("LiteLLM_VerificationToken", "LiteLLM_DailyModelUsage") + + +@pytest.mark.parametrize( + "cost_fields", + [ + {"guardrail_cost_in_spend": False, "guardrail_cost_by_unit": {"text": 1.0}}, + {"guardrail_cost_by_unit": {"text": -1.0}}, + ], +) +def test_report_only_or_invalid_guardrail_prices_remain_untracked(cost_fields: Mapping[str, object]) -> None: + row: Final = { + "request_id": "guarded", + "startTime": _NOW, + "request_tags": '["task:debugging"]', + "metadata": json.dumps( + { + "guardrail_information": [ + {"guardrail_id": "guard", "guardrail_usage": {"text": 2}, **cost_fields}, + ] + } + ), + } + contributions: Final = project(row) + guardrail: Final = next(item for item in contributions if item.table == "LiteLLM_DailyGuardrailUsageUnits") + model: Final = next(item for item in contributions if item.table == "LiteLLM_DailyModelUsage") + assert dict(guardrail.increments) == {"units": 2, "cost": 0.0, "untracked_units": 2} + assert dict(model.key)["task_type"] == "debugging" + + +@pytest.mark.parametrize("organization_id", [None, "", "charged-org"]) +def test_daily_organization_uses_frozen_charged_identity(organization_id: str | None) -> None: + row: Final[Mapping[str, object]] = { + "startTime": _NOW, + "api_key": "key", + "model": "projection-test", + "model_group": "group", + "custom_llm_provider": "openai", + "organization_id": "stored-org", + "spend": 0.25, + "metadata": {"accounting_entities": {"organization_id": organization_id}}, + } + daily: Final = tuple(item for item in project(row) if item.table == "LiteLLM_DailyOrganizationSpend") + if organization_id is None: + assert daily == () + else: + assert len(daily) == 1 + assert dict(daily[0].key)["organization_id"] == organization_id + assert dict(daily[0].increments)["spend"] == 0.25 + + +@pytest.mark.parametrize("start", [_NOW, "2026-11-02T12:00:00+00:00", "2026-11-02 12:00:00+00:00"]) +def test_every_daily_row_uses_the_calendar_date_of_the_request(start: object) -> None: + row: Final[Mapping[str, object]] = { + "request_id": "dated", + "startTime": start, + "api_key": "key", + "user": "user", + "team_id": "team", + "model": "unpriced-projection-test", + "model_group": "group", + "custom_llm_provider": "openai", + "spend": 0.5, + "metadata": "{}", + } + dates: Final = { + item.table: dict(item.key)["date"] for item in project(row) if item.table.startswith("LiteLLM_Daily") + } + assert {"LiteLLM_DailyUserSpend", "LiteLLM_DailyModelUsage"} <= dates.keys() + assert set(dates.values()) == {"2026-11-02"} + + +def test_unparseable_start_time_skips_only_guardrail_usage() -> None: + projected: Final = project( + { + "request_id": "bad-time", + "startTime": "yesterday at noon", + "spend": 0.5, + "metadata": { + "accounting_entities": {"api_key": "key"}, + "guardrail_information": [{"guardrail_id": "guard", "guardrail_usage": {"text": 2}}], + }, + } + ) + tables: Final = {item.table for item in projected} + assert "LiteLLM_VerificationToken" in tables + assert "LiteLLM_DailyGuardrailUsageUnits" not in tables + + +def test_guardrail_usage_is_dated_in_utc() -> None: + projected: Final = project( + { + "request_id": "offset", + "startTime": "2026-11-02T22:30:00-05:00", + "metadata": {"guardrail_information": [{"guardrail_id": "guard", "guardrail_usage": {"text": 1}}]}, + } + ) + assert [dict(item.key)["date"] for item in projected if item.table == "LiteLLM_DailyGuardrailUsageUnits"] == [ + "2026-11-03" + ] + + +@pytest.mark.parametrize( + ("untrusted", "metadata"), + [ + ({"request_tags": json.dumps(["x" * 16384, "normal"])}, {}), + ({"end_user": "x" * 3072}, {}), + ({}, {"compression_savings": {"tokens_saved": 2**63}}), + ], +) +def test_untrusted_analytics_values_never_block_the_charge( + untrusted: Mapping[str, str], metadata: Mapping[str, object] +) -> None: + row: Final[Mapping[str, object]] = { + "request_id": "untrusted", + "startTime": _NOW, + "api_key": "key", + "user": "user", + "team_id": "team", + "model": "unpriced-projection-test", + "model_group": "group", + "custom_llm_provider": "openai", + "spend": 0.5, + **untrusted, + "metadata": { + **metadata, + "accounting_entities": { + "api_key": "key", + "user": "user", + "team_id": "team", + "end_user": untrusted.get("end_user"), + }, + }, + } + contributions: Final = project(row) + texts: Final = tuple(value for item in contributions for _, value in (*item.key, *item.values) if value) + numbers: Final = tuple(value for item in contributions for _, value in item.increments) + assert {"LiteLLM_VerificationToken", "LiteLLM_TeamTable", "LiteLLM_UserTable"} <= { + item.table for item in contributions + } + assert "LiteLLM_DailyUserSpend" in {item.table for item in contributions} + assert all(len(text.encode()) <= 2000 for text in texts) + assert all(abs(number) <= 2**40 for number in numbers) + + +def test_stored_payload_keeps_guardrail_billing_but_not_guardrail_content() -> None: + payload: Final = get_logging_payload( + kwargs={ + "model": "projection-test", + "custom_llm_provider": "openai", + "call_type": "acompletion", + "litellm_call_id": "guardrail-request", + "litellm_params": {"metadata": {"user_api_key": "key", "user_api_key_user_id": "user"}}, + }, + response_obj=ModelResponse( + id="guardrail-request", model="projection-test", usage=Usage(prompt_tokens=10, completion_tokens=5) + ), + start_time=_NOW, + end_time=_NOW, + ) + guardrail: Final = { + "guardrail_name": "pii", + "guardrail_usage": {"requests": 1}, + "guardrail_cost_by_unit": {"requests": 0.25}, + "guardrail_response": "card 4111 1111 1111 1111", + "match_details": [{"matched": "4111 1111 1111 1111"}], + } + headroom: Final = { + "guardrail_name": "compress", + "guardrail_provider": "headroom", + "guardrail_response": {"tokens_saved": 7, "compressed_prompt": "card 4111 1111 1111 1111"}, + } + metadata: Final = {**_FIELDS.validate_json(payload["metadata"]), "guardrail_information": [guardrail, headroom]} + accounting_input: Final[SpendLogsPayload] = { + **payload, + "spend": 0.5, + "metadata": json.dumps(metadata), + "request_tags": '["nul\x00tag"]', + } + accounting: Final = build_accounting_payload( + accounting_input, entities={"api_key": "key"}, model_access_groups=(), windows=(), router=lambda: None + ) + stored: Final = json.dumps(accounting, default=str) + restored: Final = _FIELDS.validate_json(stored) + usage_rows: Final = tuple(item for item in project(restored) if item.table == "LiteLLM_DailyGuardrailUsageUnits") + assert "4111" not in stored + assert "\\u0000" not in stored + assert [dict(item.increments) for item in usage_rows] == [{"units": 1, "cost": 0.25, "untracked_units": 0}] + daily_user: Final = next(item for item in project(restored) if item.table == "LiteLLM_DailyUserSpend") + assert dict(daily_user.increments)["compression_saved_tokens"] == 7 + + +def test_caller_supplied_savings_that_cannot_be_computed_never_drop_the_charge(monkeypatch: pytest.MonkeyPatch) -> None: + import litellm + + monkeypatch.setitem( + litellm.model_cost, + "savings-overflow-test", + {"input_cost_per_token": 0.002, "output_cost_per_token": 0.004, "litellm_provider": "openai", "mode": "chat"}, + ) + payload: Final[SpendLogsPayload] = { + **get_logging_payload( + kwargs={ + "model": "savings-overflow-test", + "custom_llm_provider": "openai", + "call_type": "acompletion", + "litellm_call_id": "overflow-request", + "litellm_params": {"metadata": {"user_api_key": "key"}}, + }, + response_obj=ModelResponse( + id="overflow-request", model="savings-overflow-test", usage=Usage(prompt_tokens=10, completion_tokens=5) + ), + start_time=_NOW, + end_time=_NOW, + ), + "spend": 0.5, + "metadata": json.dumps({"compression_savings": {"tokens_saved": 10**400}}), + } + accounting: Final = build_accounting_payload( + payload, entities={"api_key": "key"}, model_access_groups=(), windows=(), router=lambda: None + ) + restored: Final = _FIELDS.validate_json(json.dumps(accounting, default=str)) + assert dict(restored["metadata"])["accounting_savings"]["compression"] == 0.0 + assert [dict(item.increments)["spend"] for item in project(restored) if item.table == "LiteLLM_VerificationToken"] == [ + 0.5 + ] diff --git a/tests/unit/accounting/test_types.py b/tests/unit/accounting/test_types.py deleted file mode 100644 index f645ee6c2cc..00000000000 --- a/tests/unit/accounting/test_types.py +++ /dev/null @@ -1,484 +0,0 @@ -import re -from collections.abc import Mapping -from datetime import datetime, timedelta, timezone -from decimal import Decimal -from enum import Enum -from pathlib import Path -from typing import Final - -import pytest -from pydantic import ValidationError - -from litellm.accounting import ( - AdmissionDecision, - AggregateQuery, - AggregateRow, - CostEvent, - DeliveryState, - DeliveryTarget, - Dimension, - DimensionFilter, - DimensionName, - EventKind, - Granularity, - InboundUsageEvent, - Metric, - MetricName, - Multiplier, - Outcome, - OutboundUsageEvent, - PricedQuantity, - PricingSnapshot, - Rate, - validate_aggregate_rows, -) -from litellm.accounting.types import PricingUnit -from litellm.types.utils import CallTypes - -_START: Final = datetime(2026, 1, 1, tzinfo=timezone.utc) -_END: Final = datetime(2026, 1, 2, tzinfo=timezone.utc) -_REQUEST: Final = Metric(name=MetricName.REQUESTS, value=Decimal(1)) -_TOKEN: Final = Metric(name=MetricName.PROMPT_TOKENS, value=Decimal(10)) -_SPEND: Final = Metric(name=MetricName.SPEND, value=Decimal("0.1234567890123456789"), unit="USD") -_TEAM: Final = Dimension(name=DimensionName.TEAM, value="team") - - -def _inbound(metrics=(_REQUEST,), outcome=Outcome.SUCCEEDED): - return InboundUsageEvent( - event_id="inbound:request", - request_id="request", - call_type=CallTypes.acompletion, - started_at=_START, - ended_at=_START, - outcome=outcome, - dimensions=(_TEAM,), - metrics=metrics, - ) - - -def _outbound(metrics=(_TOKEN,), **changes): - return OutboundUsageEvent.model_validate( - { - "event_id": "outbound:attempt", - "attempt_id": "attempt", - "request_id": "request", - "retry_of_attempt_id": None, - "call_type": CallTypes.acompletion, - "started_at": _START, - "ended_at": _END, - "outcome": Outcome.SUCCEEDED, - "dimensions": (_TEAM,), - "metrics": metrics, - **changes, - } - ) - - -def _query(**changes): - return AggregateQuery.model_validate( - { - "metric": MetricName.SPEND, - "filters": (DimensionFilter(name=DimensionName.TEAM, values=("one", "two")),), - "group_by": (DimensionName.MODEL,), - "start": _START, - "end": _END, - "granularity": Granularity.DAY, - **changes, - } - ) - - -def test_wire_values_preserve_decimal_precision_and_normalize_aware_times(): - offset = timezone(timedelta(hours=-8)) - event = CostEvent( - event_id="cost:attempt", - usage_event_id="outbound:attempt", - occurred_at=datetime(2025, 12, 31, 16, tzinfo=offset), - dimensions=(_TEAM,), - charges=(_SPEND,), - snapshot=_snapshot(), - ) - wire = event.model_dump(mode="json") - assert wire["occurred_at"] == "2026-01-01T00:00:00Z" - assert wire["charges"] == [{"name": "spend", "value": "0.1234567890123456789", "unit": "USD"}] - assert event.occurred_at == _START - assert CostEvent.model_validate_json(event.model_dump_json()).charges[0].value == _SPEND.value - - -@pytest.mark.parametrize( - ("name", "value", "unit", "message"), - [ - (MetricName.SPEND, Decimal(1), "count", "SPEND requires USD"), - (MetricName.REQUESTS, Decimal(1), "USD", "SPEND requires USD"), - (MetricName.PROMPT_TOKENS, Decimal("1.5"), "count", "integral"), - (MetricName.SPEND, Decimal("NaN"), "USD", "finite"), - (MetricName.SPEND, Decimal("Infinity"), "USD", "finite"), - (MetricName.SPEND, Decimal(-1), "USD", "greater than or equal"), - (MetricName.SPEND, 0.1, "USD", "instance of Decimal"), - ], -) -def test_metrics_reject_wrong_units_nonfinite_values_and_binary_float_inputs(name, value, unit, message): - with pytest.raises(ValidationError, match=message): - Metric(name=name, value=value, unit=unit) - - -@pytest.mark.parametrize("metrics", [(_TOKEN,), (_SPEND,), ()]) -def test_inbound_activity_cannot_own_usage_or_cost_or_omit_request_count(metrics): - with pytest.raises(ValidationError, match="Inbound events"): - _inbound(metrics) - - -@pytest.mark.parametrize( - ("outcome", "metric"), - [ - (Outcome.FAILED, Metric(name=MetricName.SUCCESSFUL_REQUESTS, value=Decimal(1))), - (Outcome.SUCCEEDED, Metric(name=MetricName.FAILED_REQUESTS, value=Decimal(1))), - ], -) -def test_inbound_outcome_counts_cannot_contradict_outcome(outcome, metric): - with pytest.raises(ValidationError, match="count must match outcome"): - _inbound((_REQUEST, metric), outcome) - - -@pytest.mark.parametrize("metrics", [(_REQUEST,), (_SPEND,)]) -def test_outbound_attempts_cannot_own_caller_counts_or_charges(metrics): - with pytest.raises(ValidationError, match="Outbound events own only"): - _outbound(metrics) - - -@pytest.mark.parametrize( - ("changes", "message"), - [ - ({"started_at": datetime(2026, 1, 1)}, "timezone"), - ({"ended_at": _START - timedelta(seconds=1)}, "End must follow start"), - ({"retry_of_attempt_id": "attempt"}, "cannot retry itself"), - ({"dimensions": (_TEAM, _TEAM)}, "Duplicate dimension values"), - ({"dimensions": (_TEAM, Dimension(name=DimensionName.TEAM, value="other"))}, "Only tag and model access group"), - ( - { - "metrics": ( - Metric(name=MetricName.COMPLETION_TOKENS, value=Decimal(5)), - Metric(name=MetricName.REASONING_TOKENS, value=Decimal(6)), - ) - }, - "reasoning_tokens cannot exceed completion_tokens", - ), - ( - { - "metrics": ( - Metric(name=MetricName.CACHE_CREATION_INPUT_TOKENS, value=Decimal(5)), - Metric(name=MetricName.CACHE_CREATION_INPUT_TOKENS_ABOVE_1HR, value=Decimal(6)), - ) - }, - "cache_creation_input_tokens_above_1hr cannot exceed cache_creation_input_tokens", - ), - ({"event_id": " "}, "pattern"), - ({"metrics": (_TOKEN, _TOKEN)}, "Duplicate metric names"), - ], -) -def test_outbound_events_reject_invalid_identity_time_and_duplicate_attribution(changes, message): - with pytest.raises(ValidationError, match=message): - _outbound(**changes) - - -def test_unknown_and_known_zero_usage_are_distinct_and_values_are_immutable(): - unknown = _outbound(None) - zero = _outbound((Metric(name=MetricName.PROMPT_TOKENS, value=Decimal(0)),)) - assert unknown.metrics is None - assert zero.metrics is not None and zero.metrics[0].value == 0 - assert _inbound().started_at == _inbound().ended_at - with pytest.raises(ValidationError, match="frozen"): - zero.attempt_id = "different" - with pytest.raises(ValidationError, match="frozen"): - zero.metrics[0].value = Decimal(10) - - -@pytest.mark.parametrize("charges", [(), (_TOKEN,), (_SPEND, _SPEND)]) -def test_cost_events_require_one_authoritative_spend(charges): - with pytest.raises(ValidationError, match=r"authoritative USD spend|Duplicate metric"): - CostEvent( - event_id="cost", - usage_event_id="usage", - occurred_at=_START, - dimensions=(), - charges=charges, - snapshot=_snapshot(), - ) - - -def test_cost_event_cannot_reuse_its_usage_identity(): - with pytest.raises(ValidationError, match="distinct identities"): - CostEvent( - event_id="usage", - usage_event_id="usage", - occurred_at=_START, - dimensions=(), - charges=(_SPEND,), - snapshot=_snapshot(), - ) - - -@pytest.mark.parametrize("granularity", [Granularity.DAY, None]) -def test_daily_and_whole_interval_queries_preserve_filter_and_group_semantics(granularity): - query = _query(granularity=granularity) - assert query.granularity is granularity - assert query.filters[0].values == ("one", "two") - assert query.group_by == (DimensionName.MODEL,) - assert query.start == _START and query.end == _END - - -@pytest.mark.parametrize( - ("changes", "message"), - [ - ({"end": _START}, "End must follow start"), - ({"start": _START + timedelta(hours=1)}, "UTC day boundaries"), - ({"end": _END + timedelta(microseconds=1)}, "UTC day boundaries"), - ({"granularity": "hour"}, "day"), - ({"group_by": (DimensionName.TEAM, DimensionName.TEAM)}, "Duplicate group-by"), - ({"filters": (DimensionFilter(name=DimensionName.TEAM, values=("one",)),) * 2}, "one IN filter"), - ({"filters": ({"name": "team", "values": ()},)}, "at least 1"), - ], -) -def test_queries_reject_unsupported_or_ambiguous_ranges_and_filters(changes, message): - with pytest.raises(ValidationError, match=message): - _query(**changes) - - -def test_rows_allow_adjacent_buckets_and_overlapping_distinct_groups(): - first = AggregateRow(start=_START, end=_END, dimensions=(_TEAM,), value=Decimal(1)) - second = AggregateRow(start=_END, end=_END + timedelta(days=1), dimensions=(_TEAM,), value=Decimal(2)) - other = AggregateRow(start=_START, end=_END, dimensions=(), value=Decimal(3)) - rows = (second, other, first) - assert validate_aggregate_rows(rows) is rows - assert validate_aggregate_rows(()) == () - - -def test_rows_reject_overlap_within_a_group_regardless_of_dimension_order(): - model = Dimension(name=DimensionName.MODEL, value="model") - first = AggregateRow(start=_START, end=_END, dimensions=(_TEAM, model), value=Decimal(1)) - overlapping = AggregateRow(start=_START, end=_END, dimensions=(model, _TEAM), value=Decimal(2)) - with pytest.raises(ValueError, match="overlap within a dimension group"): - validate_aggregate_rows((first, overlapping)) - - -def test_rows_reject_empty_intervals(): - with pytest.raises(ValidationError, match="End must follow start"): - AggregateRow(start=_START, end=_START, dimensions=(), value=Decimal(0)) - - -def test_admission_decision_preserves_a_denial_reason(): - decision = AdmissionDecision(allowed=False, reason="Team budget exhausted") - assert not decision.allowed - assert decision.reason == "Team budget exhausted" - - -def _snapshot(**changes: object) -> PricingSnapshot: - return PricingSnapshot.model_validate( - { - "calculator_version": "1.80.0", - "model": "gpt-4o", - "provider": "openai", - "pricing_source": "cost_map", - "priced_model_key": "openai/gpt-4o", - "multipliers": (Multiplier(name="data_residency", value="eu", factor=Decimal("1.1")),), - "rates": (Rate(measure="input", unit="token", usd_per_unit=Decimal("0.0000025")),), - "usage": (PricedQuantity(measure="input", unit="token", value=_TOKEN.value),), - "input_cost": Decimal("0.000025"), - "total_cost": _SPEND.value, - **changes, - } - ) - - -def test_cost_event_carries_a_snapshot_whose_total_matches_the_spend(): - event = CostEvent( - event_id="cost:attempt", - usage_event_id="outbound:attempt", - occurred_at=_START, - dimensions=(_TEAM,), - charges=(_SPEND,), - snapshot=_snapshot(), - ) - assert event.snapshot is not None - assert event.snapshot.total_cost == _SPEND.value - assert event.snapshot.multipliers[0].factor == Decimal("1.1") - with pytest.raises(ValidationError, match="Snapshot total must equal the authoritative spend"): - CostEvent( - event_id="cost:attempt", - usage_event_id="outbound:attempt", - occurred_at=_START, - dimensions=(_TEAM,), - charges=(_SPEND,), - snapshot=_snapshot(total_cost=Decimal("0.5")), - ) - - -@pytest.mark.parametrize( - ("changes", "message"), - ( - ( - { - "rates": ( - Rate(measure="input", unit="token", usd_per_unit=Decimal(1)), - Rate(measure="input", unit="token", usd_per_unit=Decimal(2)), - ) - }, - "Duplicate rate measures and units", - ), - ({"usage": (_SPEND,)}, "PricedQuantity"), - ({"usage": (_REQUEST,)}, "PricedQuantity"), - ({"pricing_source": "guess"}, "pricing_source"), - ({"multipliers": ({"name": "x", "value": "y", "factor": Decimal(0)},)}, "factor"), - ({"schema_version": 2}, "schema_version"), - ( - {"additional_costs": ({"name": "fee", "amount": Decimal(1)}, {"name": "fee", "amount": Decimal(2)})}, - "Duplicate additional cost names", - ), - ), -) -def test_snapshots_reject_ambiguous_rates_wrong_usage_and_unknown_sources(changes: Mapping[str, object], message: str): - with pytest.raises(ValidationError, match=message): - _snapshot(**changes) - - -@pytest.mark.parametrize( - ("unit", "value"), - [("token", "10"), ("second", "1.25"), ("character", "25"), ("image", "2"), ("request", "1")], -) -def test_snapshot_preserves_matching_rates_and_quantities_for_each_billing_unit(unit: PricingUnit, value: str) -> None: - quantity: Final = PricedQuantity(measure="input", unit=unit, value=Decimal(value)) - rate: Final = Rate(measure="input", unit=unit, usd_per_unit=Decimal("0.003")) - amount: Final = quantity.value * rate.usd_per_unit - snapshot: Final = _snapshot(rates=(rate,), usage=(quantity,), total_cost=amount) - restored: Final = PricingSnapshot.model_validate_json(snapshot.model_dump_json()) - assert restored == snapshot - assert restored.usage[0].value * restored.rates[0].usd_per_unit == amount - - -@pytest.mark.parametrize( - ("usage", "message"), - [ - ((), "Every rate requires"), - (({"measure": "output", "unit": "token", "value": Decimal(10)},), "Every rate requires"), - (({"measure": "input", "unit": "second", "value": Decimal(10)},), "Every rate requires"), - ( - ({"measure": "input", "unit": "token", "value": Decimal(10)},) * 2, - "Duplicate priced quantity", - ), - ], -) -def test_snapshot_rejects_missing_mismatched_or_duplicate_priced_quantities( - usage: tuple[Mapping[str, object], ...], message: str -) -> None: - with pytest.raises(ValidationError, match=message): - _snapshot(usage=usage) - - -@pytest.mark.parametrize("unit", ["token", "character", "image", "request"]) -def test_priced_counts_remain_integral(unit: PricingUnit) -> None: - with pytest.raises(ValidationError, match="integral"): - PricedQuantity(measure="input", unit=unit, value=Decimal("1.25")) - - -@pytest.mark.parametrize( - ("value", "message"), - [ - (Decimal(-1), "greater than or equal"), - (Decimal("NaN"), "finite"), - (Decimal("Infinity"), "finite"), - (1.25, "instance of Decimal"), - ], -) -def test_pricing_values_reject_invalid_amounts(value: Decimal | float, message: str) -> None: - with pytest.raises(ValidationError, match=message): - PricedQuantity.model_validate({"measure": "input", "unit": "second", "value": value}) - with pytest.raises(ValidationError, match=message): - Rate.model_validate({"measure": "input", "unit": "second", "usd_per_unit": value}) - - -@pytest.mark.parametrize("snapshot_fields", [{}, {"snapshot": None}]) -def test_cost_event_cannot_omit_its_derivation(snapshot_fields: Mapping[str, object]) -> None: - with pytest.raises(ValidationError, match="snapshot"): - CostEvent.model_validate( - { - "event_id": "cost", - "usage_event_id": "usage", - "occurred_at": _START, - "dimensions": (), - "charges": (_SPEND,), - **snapshot_fields, - } - ) - - -def test_upstream_charge_snapshot_preserves_reported_cost_without_inventing_rates() -> None: - snapshot: Final = _snapshot( - pricing_source="upstream_header", rates=(), usage=(), upstream_reported_cost=_SPEND.value - ) - restored: Final = PricingSnapshot.model_validate_json(snapshot.model_dump_json()) - assert restored.upstream_reported_cost == restored.total_cost == _SPEND.value - assert restored.rates == restored.usage == () - - -def test_subset_token_counts_round_trip_without_changing_totals() -> None: - metrics: Final = ( - Metric(name=MetricName.COMPLETION_TOKENS, value=Decimal(10)), - Metric(name=MetricName.REASONING_TOKENS, value=Decimal(3)), - Metric(name=MetricName.CACHE_CREATION_INPUT_TOKENS, value=Decimal(8)), - Metric(name=MetricName.CACHE_CREATION_INPUT_TOKENS_ABOVE_1HR, value=Decimal(2)), - ) - event: Final = _outbound(metrics=metrics) - assert OutboundUsageEvent.model_validate_json(event.model_dump_json()).metrics == metrics - - -@pytest.mark.parametrize( - "schema_path", - [ - "schema.prisma", - "litellm/proxy/schema.prisma", - "litellm-proxy-extras/litellm_proxy_extras/schema.prisma", - ], -) -@pytest.mark.parametrize( - ("enum_name", "python_enum"), - [ - ("AccountingEventKind", EventKind), - ("AccountingDeliveryState", DeliveryState), - ("AccountingDeliveryTarget", DeliveryTarget), - ], -) -def test_prisma_accepts_exactly_the_public_accounting_enum_values( - schema_path: str, enum_name: str, python_enum: type[Enum] -) -> None: - schema: Final = (Path(__file__).resolve().parents[3] / schema_path).read_text() - declaration: Final = re.search(r"enum " + enum_name + r"\s*\{([^}]+)\}", schema) - assert declaration is not None, f"Missing persisted enum {enum_name}" - assert frozenset(declaration[1].split()) == frozenset(member.value for member in python_enum) - - -def test_one_event_carries_every_matched_model_access_group(): - groups = ( - Dimension(name=DimensionName.MODEL_ACCESS_GROUP, value="gpt-group"), - Dimension(name=DimensionName.MODEL_ACCESS_GROUP, value="claude-group"), - ) - assert _outbound(dimensions=(_TEAM, *groups)).dimensions == (_TEAM, *groups) - with pytest.raises(ValidationError, match="Duplicate dimension values"): - _outbound(dimensions=(groups[0], groups[0])) - - -def test_snapshots_reject_duplicate_multipliers_and_contradictory_token_counts(): - multiplier = Multiplier(name="data_residency", value="eu", factor=Decimal("1.1")) - with pytest.raises(ValidationError, match="Duplicate multiplier names"): - _snapshot(multipliers=(multiplier, multiplier)) - with pytest.raises(ValidationError, match="reasoning_tokens cannot exceed completion_tokens"): - _snapshot( - usage=( - PricedQuantity(measure="input", unit="token", value=_TOKEN.value), - PricedQuantity(measure="completion_tokens", unit="token", value=Decimal(5)), - PricedQuantity(measure="reasoning_tokens", unit="token", value=Decimal(6)), - ) - ) - - -def test_agent_live_spend_is_a_delivery_target(): - assert DeliveryTarget.AGENT_SPEND.value == "LiteLLM_AgentsTable" diff --git a/tests/unit/anthropic_interface/exceptions/test_exception_mapping_utils.py b/tests/unit/anthropic_interface/exceptions/test_exception_mapping_utils.py index 0d8e7674e7d..210ab6717aa 100644 --- a/tests/unit/anthropic_interface/exceptions/test_exception_mapping_utils.py +++ b/tests/unit/anthropic_interface/exceptions/test_exception_mapping_utils.py @@ -63,10 +63,16 @@ class TestCreateErrorResponse: ) assert response["request_id"] == "req_123" - def test_unknown_status_defaults_to_api_error(self): - """Test unknown status code defaults to api_error.""" - response = AnthropicExceptionMapping.create_error_response(418, "I'm a teapot") + @pytest.mark.parametrize("status_code", [402, 405, 409, 418, 422, 504]) + def test_a_status_outside_the_table_stays_an_api_error_for_the_sdk_and_stream_frames(self, status_code: int): + response: Final = AnthropicExceptionMapping.create_error_response(status_code, "scripted status") + frame: Final = anthropic_error_sse_frame(status_code=status_code, raw_message="scripted status") assert response["error"]["type"] == "api_error" + assert frame.error_response["error"]["type"] == "api_error" + + def test_an_explicit_error_type_wins_over_the_status_table(self): + response: Final = AnthropicExceptionMapping.create_error_response(402, "Budget exceeded", error_type="billing_error") + assert response["error"]["type"] == "billing_error" class TestExtractErrorMessage: diff --git a/tests/unit/batches/test_batch_utils.py b/tests/unit/batches/test_batch_utils.py index b32afd51fd3..0f85f1e3993 100644 --- a/tests/unit/batches/test_batch_utils.py +++ b/tests/unit/batches/test_batch_utils.py @@ -22,7 +22,6 @@ from typing import Final, Literal import httpx import pytest import respx -from openai.types.batch import BatchRequestCounts import litellm @@ -2028,61 +2027,6 @@ def test_extract_credentials_keeps_openai_workload_identity_params(): } -# --------------------------------------------------------------------------- # -# batch_cost_is_final -# --------------------------------------------------------------------------- # - - -def _retrieved_batch( - status: str, output_file_id: str | None = None, counts: BatchRequestCounts | None = None -) -> LiteLLMBatch: - return LiteLLMBatch( - id="batch_abc", - completion_window="24h", - created_at=1, - endpoint="/v1/chat/completions", - input_file_id="file-in", - object="batch", - status="validating", - output_file_id=output_file_id, - request_counts=counts, - ).model_copy(update={"status": status}) - - -class TestBatchCostIsFinal: - """Every retrieve of one batch writes the same spend row, so the first retrieve - that prices it decides the row for good. A poll before the output exists must - therefore not count as final: pricing it recorded $0 and pinned it (LIT-7048).""" - - @pytest.mark.parametrize("status", ["validating", "in_progress", "finalizing", "cancelling"]) - def test_in_flight_batch_is_not_final(self, status): - assert bu.batch_cost_is_final(_retrieved_batch(status)) is False - - @pytest.mark.parametrize("status", ["completed", "complete"]) - def test_completed_with_output_is_final(self, status): - assert bu.batch_cost_is_final(_retrieved_batch(status, output_file_id="file-out")) is True - - def test_completed_without_output_and_unknown_counts_is_not_final(self): - assert bu.batch_cost_is_final(_retrieved_batch("completed")) is False - - def test_completed_without_output_and_zero_counts_is_not_final(self): - counts = BatchRequestCounts(total=0, completed=0, failed=0) - assert bu.batch_cost_is_final(_retrieved_batch("completed", counts=counts)) is False - - def test_completed_without_output_but_successful_lines_is_not_final(self): - counts = BatchRequestCounts(total=2, completed=2, failed=0) - assert bu.batch_cost_is_final(_retrieved_batch("completed", counts=counts)) is False - - @pytest.mark.parametrize("status", ["completed", "complete"]) - def test_completed_without_output_and_every_line_failed_is_final(self, status): - counts = BatchRequestCounts(total=2, completed=0, failed=2) - assert bu.batch_cost_is_final(_retrieved_batch(status, counts=counts)) is True - - @pytest.mark.parametrize("status", ["failed", "expired", "cancelled"]) - def test_other_terminal_statuses_are_final(self, status): - assert bu.batch_cost_is_final(_retrieved_batch(status)) is True - - def _ocr_row(pages_processed, annotation_pages=None, model="mistral-ocr-latest"): usage_info = {"pages_processed": pages_processed, "doc_size_bytes": 4096} if annotation_pages is not None: @@ -2766,9 +2710,9 @@ def test_aggregate_batch_cost_uses_custom_model_info(): assert result.cost == pytest.approx(expected), f"Expected total cost {expected}, got {result.cost}" @pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown") -@pytest.mark.parametrize("data_residency", ["eu", "us"]) +@pytest.mark.parametrize("data_residency", ["eu", "us", "fedramp"]) def test_batch_cost_calculator_applies_data_residency_uplift(data_residency, monkeypatch): - """batch_cost_calculator should apply the regional uplift multiplier when + """batch_cost_calculator should apply the regional or FedRAMP uplift multiplier when data_residency is set and the model carries a configured multiplier.""" monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") prev_model_cost = litellm.model_cost @@ -2965,7 +2909,7 @@ async def test_batch_retrieve_cost_tracking_with_completed_batch_no_explicit_cos from unittest.mock import AsyncMock, patch from litellm.litellm_core_utils.litellm_logging import Logging - from litellm.types.utils import CallTypes, LiteLLMBatch + from litellm.types.utils import CallTypes # Mock batch result with completed status mock_batch = LiteLLMBatch( @@ -3060,7 +3004,6 @@ async def test_handle_completed_batch_computes_real_cost_from_output_file( wrong token sum, or mispriced model fails this test. """ from litellm.batches.batch_utils import handle_completed_batch - from litellm.types.utils import LiteLLMBatch batch = LiteLLMBatch( id="batch-real-cost-123", @@ -3105,7 +3048,7 @@ async def test_batch_retrieve_cost_tracking_with_explicit_cost_data(): from unittest.mock import AsyncMock, patch from litellm.litellm_core_utils.litellm_logging import Logging - from litellm.types.utils import CallTypes, LiteLLMBatch + from litellm.types.utils import CallTypes # Mock batch result with completed status mock_batch = LiteLLMBatch( @@ -3187,7 +3130,7 @@ async def test_batch_retrieve_explicit_cost_split_sets_cost_breakdown(): cost_breakdown carries real input/output costs; without it the UI's Cost Breakdown card renders blank for every batch. Regression for the split being dropped.""" from litellm.litellm_core_utils.litellm_logging import Logging - from litellm.types.utils import CallTypes, LiteLLMBatch + from litellm.types.utils import CallTypes mock_batch = LiteLLMBatch( id="batch-breakdown-1", @@ -3243,7 +3186,7 @@ async def test_batch_retrieve_cost_tracking_with_unified_file_id_incomplete_batc from unittest.mock import AsyncMock, patch from litellm.litellm_core_utils.litellm_logging import Logging - from litellm.types.utils import CallTypes, LiteLLMBatch, SpecialEnums + from litellm.types.utils import CallTypes, SpecialEnums # Create a proper unified file ID by encoding the correct prefix unified_id_str = f"{SpecialEnums.LITELM_MANAGED_FILE_ID_PREFIX.value}:test_file_789;unified_id:batch-789" @@ -3322,7 +3265,7 @@ async def test_batch_retrieve_cost_tracking_with_partial_explicit_data(): from unittest.mock import AsyncMock, patch from litellm.litellm_core_utils.litellm_logging import Logging - from litellm.types.utils import CallTypes, LiteLLMBatch + from litellm.types.utils import CallTypes # Mock batch result with completed status mock_batch = LiteLLMBatch( diff --git a/tests/unit/batches/test_main.py b/tests/unit/batches/test_main.py index 8b22395f462..5ffe6558dc3 100644 --- a/tests/unit/batches/test_main.py +++ b/tests/unit/batches/test_main.py @@ -858,7 +858,7 @@ async def test_batch_logging_azure_credentials_regression(): "timeout": 600, } - batch_output = b'{"id": "batch_req_1", "custom_id": "request-1", "response": {"status_code": 200, "body": {"id": "chatcmpl-azure", "object": "chat.completion", "model": "gpt-4", "usage": {"prompt_tokens": 15, "completion_tokens": 25, "total_tokens": 40}}}}\n' + batch_output = b'{"id": "batch_req_1", "custom_id": "request-1", "response": {"status_code": 200, "body": {"id": "chatcmpl-azure", "object": "chat.completion", "model": "gpt-4.1", "usage": {"prompt_tokens": 15, "completion_tokens": 25, "total_tokens": 40}}}}\n' print("\n1. Testing credential extraction...") diff --git a/tests/unit/caching/test_caching.py b/tests/unit/caching/test_caching.py index 0f6ef2304fb..0911d5ef888 100644 --- a/tests/unit/caching/test_caching.py +++ b/tests/unit/caching/test_caching.py @@ -472,6 +472,30 @@ def test_cache_key_tells_apart_requests_that_differ_only_in_continuation_token() assert cache.get_cache_key(**request, continuation_token="") == first_segment_key +def test_cache_key_tells_apart_requests_that_ask_for_token_ids() -> None: + cache: Final = Cache(type=LiteLLMCacheType.LOCAL) + request: Final = {"model": "hosted_vllm/qwen3", "messages": [{"role": "user", "content": "count"}]} + + plain_key: Final = cache.get_cache_key(**request) + + assert cache.get_cache_key(**request, return_token_ids=True) != plain_key + assert cache.get_cache_key(**request, return_token_ids=False) == plain_key + assert cache.get_cache_key(**request, return_token_ids=None) == plain_key + + +def test_cache_key_tells_apart_requests_that_ask_for_token_ids_through_extra_body() -> None: + cache: Final = Cache(type=LiteLLMCacheType.LOCAL) + request: Final = {"model": "hosted_vllm/qwen3", "messages": [{"role": "user", "content": "count"}]} + + plain_key: Final = cache.get_cache_key(**request) + other_extra_body_key: Final = cache.get_cache_key(**request, extra_body={"top_k": 5}) + + assert cache.get_cache_key(**request, extra_body={"return_token_ids": True}) != plain_key + assert cache.get_cache_key(**request, extra_body={"top_k": 5, "return_token_ids": True}) != other_extra_body_key + assert cache.get_cache_key(**request, extra_body={"return_token_ids": False}) == plain_key + assert cache.get_cache_key(**request, extra_body={"continuation_token": "abc"}) != plain_key + + def test_cache_key_tells_apart_requests_that_differ_only_in_tool_call_id_shape() -> None: cache: Final = Cache(type=LiteLLMCacheType.LOCAL) request: Final = { diff --git a/tests/unit/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py b/tests/unit/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py index 4e6ed16e360..19aefb430c7 100644 --- a/tests/unit/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py +++ b/tests/unit/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py @@ -1,9 +1,13 @@ +import asyncio import copy import datetime import json import os +import queue import unittest -from collections.abc import Mapping, Sequence +from collections.abc import AsyncIterator, Mapping, Sequence +from dataclasses import dataclass +from types import MappingProxyType from typing import TYPE_CHECKING, Final, List, Literal, Optional, Tuple, cast, get_args from unittest.mock import ANY, MagicMock, Mock, patch @@ -24,15 +28,15 @@ import litellm from litellm.completion_extras.litellm_responses_transformation.transformation import ( LiteLLMResponsesTransformationHandler, ) -from litellm.types.llms.openai import AllMessageValues, REASONING_EFFORT +from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.streaming_handler import CustomStreamWrapper +from litellm.types.llms.openai import AllMessageValues, REASONING_EFFORT, ResponsesAPIResponse +from litellm.types.utils import ModelResponse, StandardLoggingPayload, TextCompletionResponse if TYPE_CHECKING: from openai.types.responses import ResponseOutputItem from openai.types.responses.response_reasoning_item import ResponseReasoningItem - from litellm.types.llms.openai import ResponsesAPIResponse - from litellm.types.utils import ModelResponse - def test_completion_over_responses_maps_anthropic_search_tool_to_openai_tool_search() -> None: response_body: Final = { @@ -191,6 +195,368 @@ def test_auto_summary_sends_the_level_the_target_accepts( assert request_body["reasoning"] == {"effort": "low", "summary": expected_summary} +@dataclass(frozen=True, slots=True) +class _LoggedSuccess: + call_type: str + payload: StandardLoggingPayload + response_obj: object + complete_streaming_response: object + + +class _LoggedCallTypes(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.seen_by_caller: Final = MappingProxyType( + { + "completion": queue.SimpleQueue[_LoggedSuccess](), + "acompletion": queue.SimpleQueue[_LoggedSuccess](), + } + ) + + @staticmethod + def _logged(kwargs: Mapping[str, object], response_obj: object, streaming_key: str) -> _LoggedSuccess: + return _LoggedSuccess( + call_type=str(kwargs["call_type"]), + payload=cast(StandardLoggingPayload, kwargs["standard_logging_object"]), + response_obj=response_obj, + complete_streaming_response=kwargs.get(streaming_key), + ) + + def log_success_event( + self, + kwargs: Mapping[str, object], + response_obj: object, + start_time: datetime.datetime, + end_time: datetime.datetime, + ) -> None: + self.seen_by_caller["completion"].put(self._logged(kwargs, response_obj, "complete_streaming_response")) + + async def async_log_success_event( + self, + kwargs: Mapping[str, object], + response_obj: object, + start_time: datetime.datetime, + end_time: datetime.datetime, + ) -> None: + self.seen_by_caller["acompletion"].put( + self._logged(kwargs, response_obj, "async_complete_streaming_response") + ) + + +_GET_WEATHER_TOOL: Final = { + "type": "function", + "function": {"name": "get_weather", "parameters": {"type": "object", "properties": {}}}, +} + +_BRIDGED_PROVIDERS: Final = pytest.mark.parametrize( + ("model", "url", "provider_kwargs"), + [ + ("openai/gpt-5.3-codex", "https://api.openai.com/v1/responses", {}), + ( + "azure/gpt-6-sol", + "https://example.invalid/openai/responses", + {"api_base": "https://example.invalid", "api_version": "2025-04-01-preview"}, + ), + ("bedrock_mantle/openai.gpt-5.6-terra", _MANTLE_RESPONSES_URL, {"aws_region_name": "us-east-1"}), + ], + ids=["openai-responses-only", "azure-tools", "bedrock-mantle-tools"], +) + + +_PONG_MESSAGE: Final[Mapping[str, object]] = { + "type": "message", + "id": "msg_logged_call_type", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "pong", "annotations": []}], +} + + +def _searched_responses_body(model: str) -> Mapping[str, object]: + return { + "id": "resp_logged_call_type", + "object": "response", + "created_at": 1789788253, + "status": "completed", + "model": model.rsplit("/", 1)[-1], + "output": [ + { + "type": "web_search_call", + "id": "ws_logged_call_type", + "status": "completed", + "action": {"type": "search", "query": "weather"}, + }, + _PONG_MESSAGE, + ], + "usage": {"input_tokens": 10, "output_tokens": 5, "total_tokens": 15}, + } + + +def _responses_sse(response_body: Mapping[str, object]) -> str: + events: Final = ( + {"type": "response.created", "response": {**response_body, "status": "in_progress", "output": [], "usage": None}}, + { + "type": "response.output_text.delta", + "item_id": "msg_logged_call_type", + "output_index": 1, + "content_index": 0, + "delta": "pong", + }, + {"type": "response.completed", "response": response_body}, + ) + return "".join(f"event: {event['type']}\ndata: {json.dumps(event)}\n\n" for event in events) + + +def _bridged_request(model: str, provider_kwargs: Mapping[str, object], stream: bool) -> Mapping[str, object]: + return { + "model": model, + "messages": [{"role": "user", "content": "ping"}], + "tools": [_GET_WEATHER_TOOL], + "api_key": "test-key", + "cache": {"no-cache": True}, + "stream": stream, + **provider_kwargs, + } + + +async def _served_chunk_ids(caller: str, request: Mapping[str, object]) -> frozenset[str]: + if caller == "acompletion": + async_stream: Final = await litellm.acompletion(**request) + assert isinstance(async_stream, CustomStreamWrapper) + return frozenset([chunk.id async for chunk in async_stream]) + sync_stream: Final = litellm.completion(**request) + assert isinstance(sync_stream, CustomStreamWrapper) + return frozenset(chunk.id for chunk in sync_stream) + + +@pytest.mark.parametrize("caller", ["completion", "acompletion"]) +@_BRIDGED_PROVIDERS +@pytest.mark.asyncio +async def test_bridged_chat_call_is_logged_with_the_callers_call_type( + monkeypatch: pytest.MonkeyPatch, caller: str, model: str, url: str, provider_kwargs: Mapping[str, object] +) -> None: + monkeypatch.delenv("AWS_BEARER_TOKEN_BEDROCK", raising=False) + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + recorder: Final = _LoggedCallTypes() + monkeypatch.setattr(litellm, "callbacks", [recorder]) + response_body: Final = _searched_responses_body(model) + request: Final = _bridged_request(model, provider_kwargs, stream=False) + + with respx.mock(assert_all_called=True) as router: + router.post(url__startswith=url).mock(return_value=httpx.Response(200, json=response_body)) + if caller == "acompletion": + await litellm.acompletion(**request) + else: + litellm.completion(**request) + logged: Final = await asyncio.to_thread(recorder.seen_by_caller[caller].get, timeout=10) + + assert (logged.call_type, logged.payload["call_type"]) == (caller, caller) + assert isinstance(logged.response_obj, ModelResponse) + assert logged.response_obj.id == response_body["id"] + assert logged.response_obj.choices[0].message.content == "pong" + assert logged.payload["response"]["choices"][0]["message"]["content"] == "pong" + assert logged.payload["response_cost"] == litellm.completion_cost( + completion_response=ResponsesAPIResponse.model_validate(response_body), model=model + ) + + +@pytest.mark.parametrize("caller", ["completion", "acompletion"]) +@_BRIDGED_PROVIDERS +@pytest.mark.asyncio +async def test_bridged_chat_stream_is_logged_as_the_chat_completion_it_streamed( + monkeypatch: pytest.MonkeyPatch, caller: str, model: str, url: str, provider_kwargs: Mapping[str, object] +) -> None: + monkeypatch.delenv("AWS_BEARER_TOKEN_BEDROCK", raising=False) + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + recorder: Final = _LoggedCallTypes() + monkeypatch.setattr(litellm, "callbacks", [recorder]) + response_body: Final = _searched_responses_body(model) + request: Final = _bridged_request(model, provider_kwargs, stream=True) + + with respx.mock(assert_all_called=True) as router: + router.post(url__startswith=url).mock( + return_value=httpx.Response( + 200, text=_responses_sse(response_body), headers={"content-type": "text/event-stream"} + ) + ) + served_ids: Final = await _served_chunk_ids(caller, request) + logged: Final = await asyncio.to_thread(recorder.seen_by_caller[caller].get, timeout=10) + + assert isinstance(logged.complete_streaming_response, ModelResponse) + assert logged.response_obj is logged.complete_streaming_response + assert served_ids == {logged.complete_streaming_response.id} + assert logged.complete_streaming_response.choices[0].message.content == "pong" + assert logged.payload["response"]["choices"][0]["message"]["content"] == "pong" + assert logged.payload["response_cost"] == litellm.completion_cost( + completion_response=ResponsesAPIResponse.model_validate(response_body), model=model + ) + + +def _json_message(item_id: str, document: Mapping[str, object]) -> Mapping[str, object]: + return { + "type": "message", + "id": item_id, + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": json.dumps(document), "annotations": []}], + } + + +@pytest.mark.parametrize("caller", ["completion", "acompletion"]) +@pytest.mark.asyncio +async def test_bridged_structured_output_call_is_logged_with_the_json_document_the_client_got( + monkeypatch: pytest.MonkeyPatch, caller: str +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + recorder: Final = _LoggedCallTypes() + monkeypatch.setattr(litellm, "callbacks", [recorder]) + response_body: Final = { + **_searched_responses_body("openai/gpt-5.3-codex"), + "output": [_json_message("msg_first", {"answer": "pong"}), _json_message("msg_second", {"answer": "again"})], + } + request: Final = { + **_bridged_request("openai/gpt-5.3-codex", {}, stream=False), + "response_format": {"type": "json_object"}, + } + + with respx.mock(assert_all_called=True) as router: + router.post(url__startswith="https://api.openai.com/v1/responses").mock( + return_value=httpx.Response(200, json=response_body) + ) + served: Final = await litellm.acompletion(**request) if caller == "acompletion" else litellm.completion(**request) + logged: Final = await asyncio.to_thread(recorder.seen_by_caller[caller].get, timeout=10) + + assert isinstance(served, ModelResponse) + assert isinstance(logged.response_obj, ModelResponse) + served_message: Final = served.choices[0].message + logged_message: Final = logged.response_obj.choices[0].message + assert json.loads(served_message.content) == {"answer": "pong"} + assert logged_message.content == served_message.content + assert logged_message.provider_specific_fields == served_message.provider_specific_fields + assert logged.payload["response"]["choices"][0]["message"]["content"] == served_message.content + + +async def _logged_text_completion( + monkeypatch: pytest.MonkeyPatch, caller: str +) -> tuple[TextCompletionResponse, _LoggedSuccess, Mapping[str, object]]: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + recorder: Final = _LoggedCallTypes() + monkeypatch.setattr(litellm, "callbacks", [recorder]) + response_body: Final = _searched_responses_body("openai/gpt-5.3-codex") + request: Final = {"model": "openai/gpt-5.3-codex", "prompt": "ping", "api_key": "test-key"} + + with respx.mock(assert_all_called=True) as router: + router.post(url__startswith="https://api.openai.com/v1/responses").mock( + return_value=httpx.Response(200, json=response_body) + ) + served: Final = ( + await litellm.atext_completion(**request) if caller == "acompletion" else litellm.text_completion(**request) + ) + logged: Final = await asyncio.to_thread(recorder.seen_by_caller[caller].get, timeout=10) + assert isinstance(served, TextCompletionResponse) + return served, logged, response_body + + +@pytest.mark.parametrize(("caller", "call_type"), [("completion", "text_completion"), ("acompletion", "atext_completion")]) +@pytest.mark.asyncio +async def test_bridged_text_completion_is_logged_and_priced_under_the_callers_call_type( + monkeypatch: pytest.MonkeyPatch, caller: str, call_type: str +) -> None: + served, logged, response_body = await _logged_text_completion(monkeypatch, caller) + + assert (logged.call_type, logged.payload["call_type"]) == (call_type, call_type) + assert getattr(logged.response_obj, "id") == served.id == response_body["id"] + assert logged.payload["response_cost"] == litellm.completion_cost( + completion_response=ResponsesAPIResponse.model_validate(response_body), model="openai/gpt-5.3-codex" + ) + + +@pytest.mark.parametrize("caller", ["completion", "acompletion"]) +@pytest.mark.asyncio +async def test_bridged_text_completion_is_logged_as_the_text_completion_it_served( + monkeypatch: pytest.MonkeyPatch, caller: str +) -> None: + served, logged, _ = await _logged_text_completion(monkeypatch, caller) + + assert isinstance(logged.response_obj, TextCompletionResponse) + assert logged.response_obj.choices[0].text == served.choices[0].text == "pong" + assert logged.payload["response"]["object"] == served.object == "text_completion" + assert logged.payload["response"]["choices"][0]["text"] == "pong" + + +def _served_message_start_id(events: Sequence[bytes]) -> object: + lines: Final = b"".join(events).decode().splitlines() + starts: Final = tuple( + json.loads(line.removeprefix("data:")) for line in lines if line.startswith("data:") and '"message_start"' in line + ) + assert len(starts) == 1 + return starts[0]["message"]["id"] + + +@pytest.mark.parametrize("stream", [False, True], ids=["non-stream", "stream"]) +@pytest.mark.asyncio +async def test_bridged_messages_call_is_logged_as_anthropic_messages_under_the_id_the_client_got( + monkeypatch: pytest.MonkeyPatch, stream: bool +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + monkeypatch.setattr(litellm, "use_chat_completions_url_for_anthropic_messages", True) + recorder: Final = _LoggedCallTypes() + monkeypatch.setattr(litellm, "callbacks", [recorder]) + response_body: Final = {**_searched_responses_body("openai/gpt-5.3-codex"), "output": [_PONG_MESSAGE]} + upstream: Final = ( + httpx.Response(200, text=_responses_sse(response_body), headers={"content-type": "text/event-stream"}) + if stream + else httpx.Response(200, json=response_body) + ) + + with respx.mock(assert_all_called=True) as router: + router.post(url__startswith="https://api.openai.com/v1/responses").mock(return_value=upstream) + served: Final = await litellm.anthropic.messages.acreate( + model="openai/gpt-5.3-codex", + max_tokens=64, + messages=[{"role": "user", "content": "ping"}], + api_key="test-key", + stream=stream, + ) + served_id: Final = ( + _served_message_start_id([event async for event in cast(AsyncIterator[bytes], served)]) + if stream + else cast(Mapping[str, object], served)["id"] + ) + logged: Final = await asyncio.to_thread(recorder.seen_by_caller["acompletion"].get, timeout=10) + + assert (logged.call_type, logged.payload["call_type"]) == ("anthropic_messages", "anthropic_messages") + assert logged.payload["id"] == served_id + assert logged.payload["response"]["choices"][0]["message"]["content"] == "pong" + + +@pytest.mark.parametrize("caller", ["completion", "acompletion"]) +@pytest.mark.asyncio +async def test_bridged_chat_stream_keeps_the_upstream_headers_when_its_output_cannot_be_translated( + monkeypatch: pytest.MonkeyPatch, caller: str +) -> None: + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + recorder: Final = _LoggedCallTypes() + monkeypatch.setattr(litellm, "callbacks", [recorder]) + response_body: Final = {**_searched_responses_body("openai/gpt-5.3-codex"), "output": []} + request: Final = _bridged_request("openai/gpt-5.3-codex", {}, stream=True) + + with respx.mock(assert_all_called=True) as router: + router.post(url__startswith="https://api.openai.com/v1/responses").mock( + return_value=httpx.Response( + 200, + text=_responses_sse(response_body), + headers={"content-type": "text/event-stream", "x-request-id": "req_upstream"}, + ) + ) + await _served_chunk_ids(caller, request) + logged: Final = await asyncio.to_thread(recorder.seen_by_caller[caller].get, timeout=10) + + assert isinstance(logged.complete_streaming_response, ModelResponse) + assert logged.complete_streaming_response.id == response_body["id"] + assert logged.payload["hidden_params"]["additional_headers"]["llm_provider-x-request-id"] == "req_upstream" + + def test_convert_chat_completion_messages_to_responses_api_image_input(): from litellm.completion_extras.litellm_responses_transformation.transformation import ( LiteLLMResponsesTransformationHandler, @@ -1490,6 +1856,51 @@ def test_transform_request_system_only_message_maps_to_system_input_item(): assert not result.get("instructions") +_JSON_SYSTEM_PROMPT: Final = "You output JSON objects." +_PLAIN_USER_ITEM: Final = { + "type": "message", + "role": "user", + "content": [{"type": "input_text", "text": "List three colors."}], +} +_COLORS_SCHEMA: Final = { + "type": "json_schema", + "json_schema": {"name": "colors", "schema": {"type": "object", "properties": {}}}, +} + + +@pytest.mark.parametrize( + ("response_format", "expected_input", "expected_instructions"), + [ + ( + {"type": "json_object"}, + [ + {"type": "message", "role": "system", "content": [{"type": "input_text", "text": _JSON_SYSTEM_PROMPT}]}, + _PLAIN_USER_ITEM, + ], + None, + ), + (_COLORS_SCHEMA, [_PLAIN_USER_ITEM], _JSON_SYSTEM_PROMPT), + ], + ids=["json_object_keeps_system_in_input", "json_schema_keeps_system_in_instructions"], +) +def test_transform_request_json_object_keeps_system_prompt_where_the_json_word_check_reads_it( + response_format, expected_input, expected_instructions +): + result = LiteLLMResponsesTransformationHandler().transform_request( + model="gpt-5.4-mini", + messages=[ + {"role": "system", "content": _JSON_SYSTEM_PROMPT}, + {"role": "user", "content": "List three colors."}, + ], + optional_params={"response_format": response_format}, + litellm_params={}, + headers={}, + litellm_logging_obj=Mock(), + ) + + assert (result["input"], result.get("instructions")) == (expected_input, expected_instructions), result + + def test_transform_request_single_char_keys_not_matched(): """Test that single-character keys are not incorrectly matched to 'metadata' or 'previous_response_id' @@ -3064,6 +3475,38 @@ def test_map_optional_params_tool_choice_chat_nested_to_responses_api(): {"type": "custom", "name": "ApplyPatch"}, ), ({"type": "custom"}, {"type": "custom"}), + ( + { + "type": "allowed_tools", + "allowed_tools": { + "mode": "required", + "tools": [ + {"type": "function", "function": {"name": "get_time"}}, + {"type": "custom", "custom": {"name": "apply_patch"}}, + {"type": "mcp", "server_label": "docs"}, + {"type": "function", "name": "already_flat"}, + ], + }, + }, + { + "type": "allowed_tools", + "mode": "required", + "tools": [ + {"type": "function", "name": "get_time"}, + {"type": "custom", "name": "apply_patch"}, + {"type": "mcp", "server_label": "docs"}, + {"type": "function", "name": "already_flat"}, + ], + }, + ), + ( + {"type": "allowed_tools", "allowed_tools": {"mode": "auto", "tools": [{"type": "function"}]}}, + {"type": "allowed_tools", "allowed_tools": {"mode": "auto", "tools": [{"type": "function"}]}}, + ), + ( + {"type": "allowed_tools", "mode": "auto", "tools": [{"type": "function", "name": "get_time"}]}, + {"type": "allowed_tools", "mode": "auto", "tools": [{"type": "function", "name": "get_time"}]}, + ), ], ) def test_normalize_tool_choice_for_responses_api(tool_choice, expected): @@ -4105,6 +4548,16 @@ def test_output_item_done_with_stream_map_keeps_empty_delta(): ({"type": "required"}, "required"), ("auto", "auto"), ({"type": "function", "function": {"name": "get_weather"}}, {"type": "function", "name": "get_weather"}), + ( + { + "type": "allowed_tools", + "allowed_tools": { + "mode": "required", + "tools": [{"type": "function", "function": {"name": "get_weather"}}], + }, + }, + {"type": "allowed_tools", "mode": "required", "tools": [{"type": "function", "name": "get_weather"}]}, + ), ], ) async def test_acompletion_bridge_normalizes_tool_choice_on_the_wire( @@ -4177,6 +4630,7 @@ async def test_acompletion_bridge_normalizes_tool_choice_on_the_wire( post_kwargs = mock_post.call_args.kwargs request_body = post_kwargs["json"] if "json" in post_kwargs else json.loads(post_kwargs["data"]) assert request_body["tool_choice"] == expected_wire_tool_choice + assert [tool["name"] for tool in request_body["tools"]] == ["get_weather"] def _make_incomplete_responses_api_response( @@ -5439,6 +5893,38 @@ def test_transform_request_strips_the_breakpoint_when_the_served_providers_row_o ] +@pytest.mark.parametrize( + ("sibling_flag", "model_info", "keeps_the_breakpoint"), + [ + (True, {"id": "flagless"}, False), + (True, {"id": "opted-out", "supports_prompt_cache_breakpoint": False}, False), + (False, {"id": "opted-in", "supports_prompt_cache_breakpoint": True}, True), + ], + ids=["flagless", "opted-out", "opted-in"], +) +def test_transform_request_reads_the_routed_deployments_own_flag_not_a_siblings_on_the_shared_key( + monkeypatch: pytest.MonkeyPatch, + sibling_flag: bool, + model_info: Mapping[str, object], + keeps_the_breakpoint: bool, +) -> None: + monkeypatch.setitem( + litellm.model_cost, + "bedrock_mantle/qa-mantle-shared", + {**_MANTLE_GPT_ROW, "supports_prompt_cache_breakpoint": sibling_flag}, + ) + + system_content: Final = _bridged_input_for_served_provider( + "qa-mantle-shared", "bedrock_mantle", model_info=model_info + )[0]["content"] + + assert system_content == [ + {**_MARKED_SYSTEM_PART, "type": "input_text"} + if keeps_the_breakpoint + else {"type": "input_text", "text": "Stable prefix"} + ] + + def test_transform_request_strips_the_breakpoint_for_a_served_provider_without_a_row_of_its_own( monkeypatch: pytest.MonkeyPatch, ) -> None: @@ -5884,9 +6370,9 @@ _HAND_WRITTEN_PROMPT_CACHE_BREAKPOINT_BLOCKS: Final = ( ) -def test_convert_chat_completion_messages_to_responses_api_drops_malformed_prompt_cache_breakpoint_under_drop_params(): - """OpenAI's Responses API answered "Supported values are: '30m'" for a 1h breakpoint ttl on 2026-10-07, - so an unsupported ttl drops the marker as a unit while an unknown key is dropped from a valid one.""" +def test_convert_chat_completion_messages_to_responses_api_drops_only_an_unreadable_prompt_cache_breakpoint_under_drop_params(): + """The target's Responses config decides which ttl and keys its API takes, so the bridge keeps every marker + whose mode some target reads.""" handler = LiteLLMResponsesTransformationHandler() messages = [{"role": "user", "content": list(_HAND_WRITTEN_PROMPT_CACHE_BREAKPOINT_BLOCKS)}] @@ -5899,12 +6385,12 @@ def test_convert_chat_completion_messages_to_responses_api_drops_malformed_promp None, None, None, - None, - {"mode": "explicit"}, + {"mode": "explicit", "ttl": "1h"}, + {"mode": "explicit", "scope": "all"}, {"mode": "explicit", "ttl": "30m"}, {"mode": "explicit"}, ] - assert all("prompt_cache_breakpoint" not in block for block in content[:4]) + assert all("prompt_cache_breakpoint" not in block for block in content[:3]) def test_convert_chat_completion_messages_to_responses_api_keeps_malformed_prompt_cache_breakpoint_by_default(): @@ -5937,6 +6423,41 @@ def test_transform_request_drop_params_in_litellm_params_gates_the_prompt_cache_ assert "prompt_cache_breakpoint" not in result["input"][0]["content"][0] +_TTL_MARKED_CONTENT: Final = ( + {"type": "text", "text": "unsupported ttl", "prompt_cache_breakpoint": {"mode": "explicit", "ttl": "1h"}}, + {"type": "text", "text": "well formed", "prompt_cache_breakpoint": {"mode": "explicit"}}, +) + + +@pytest.mark.parametrize( + "global_drop_params,deployment_drop_params,expected", + [ + ("true", None, [None, {"mode": "explicit"}]), + (False, True, [{"mode": "explicit", "ttl": "1h"}, {"mode": "explicit"}]), + (True, None, [{"mode": "explicit", "ttl": "1h"}, {"mode": "explicit"}]), + ], + ids=("string-global-target-keeps-raw-markers", "deployment-drop-params", "global-drop-params"), +) +def test_transform_request_hands_a_marker_to_the_target_whole_only_when_the_target_trims_it( + monkeypatch: pytest.MonkeyPatch, + global_drop_params: object, + deployment_drop_params: bool | None, + expected: list[object], +) -> None: + monkeypatch.setattr(litellm, "drop_params", global_drop_params) + request: Final = LiteLLMResponsesTransformationHandler().transform_request( + model="gpt-6.1-sol", + messages=[{"role": "user", "content": list(_TTL_MARKED_CONTENT)}], + optional_params={}, + litellm_params={"custom_llm_provider": "openai", "drop_params": deployment_drop_params}, + headers={}, + litellm_logging_obj=Mock(), + ) + (item,) = cast(list[dict[str, object]], request["input"]) # cast-ok: the bridge emits message item mappings + parts: Final = cast(list[dict[str, object]], item["content"]) # cast-ok: message items carry content parts + assert [part.get("prompt_cache_breakpoint") for part in parts] == expected + + def test_convert_response_output_folds_two_messages_and_function_call_into_one_choice() -> None: first: Final = ResponseOutputMessage.model_validate( { diff --git a/tests/unit/conftest.py b/tests/unit/conftest.py index ed7dd5ec146..4a07c97b709 100644 --- a/tests/unit/conftest.py +++ b/tests/unit/conftest.py @@ -216,6 +216,7 @@ def _reset_aws_auth_caches() -> None: def _flush_client_caches() -> None: litellm.in_memory_llm_clients_cache.flush_cache() image_handling_module.in_memory_cache.flush_cache() + image_handling_module.pdf_probe_verdicts.flush_cache() _reset_aws_auth_caches() @@ -251,6 +252,12 @@ def socket_tempdir(socket_dir: Path, monkeypatch: pytest.MonkeyPatch) -> Path: return socket_dir +@pytest.fixture +def python_router_core(monkeypatch: pytest.MonkeyPatch) -> None: + """Keep ``Router`` on ``PythonCore``, for a test that patches a member the Rust core never reads.""" + monkeypatch.setenv("LITELLM_RUST", "0") + + @pytest.fixture(autouse=True, scope="session") def bundled_tiktoken_cache() -> None: importlib.import_module("litellm.litellm_core_utils.default_encoding") diff --git a/tests/unit/cookbook/__init__.py b/tests/unit/cookbook/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/unit/cookbook/test_gpt_realtime_translate.py b/tests/unit/cookbook/test_gpt_realtime_translate.py new file mode 100644 index 00000000000..a40a3265600 --- /dev/null +++ b/tests/unit/cookbook/test_gpt_realtime_translate.py @@ -0,0 +1,141 @@ +import asyncio +import base64 +import json +import wave +from pathlib import Path +from types import SimpleNamespace +from typing import Final, cast + +import pytest +from websockets.asyncio.client import ClientConnection + +from cookbook import gpt_realtime_translate as translate + + +@pytest.mark.asyncio +async def test_short_upload_waits_for_first_translated_audio(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: + monkeypatch.setattr(translate, "RESPONSE_TIMEOUT_SECONDS", 0.1) + audio: Final = bytes(480) + events: Final = iter( + ( + {"type": "session.output_audio.delta", "delta": base64.b64encode(audio).decode()}, + {"type": "error", "error": {"message": "session closed"}}, + ) + ) + + async def recv() -> str: + event: Final = next(events) + if event["type"] == "session.output_audio.delta": + await asyncio.sleep(0.03) + return json.dumps(event) + + sender_finished: Final = asyncio.Event() + sender_finished.set() + output: Final = tmp_path / "translation.wav" + + result: Final = await translate.receive_translation( + cast(ClientConnection, SimpleNamespace(recv=recv)), output, sender_finished + ) + + assert result == 'Realtime API error: {"message": "session closed"}' + with wave.open(str(output), "rb") as rendered: + assert rendered.readframes(240) == audio + + +@pytest.mark.asyncio +async def test_long_upload_keeps_waiting_for_first_translated_audio_while_still_sending( + monkeypatch: pytest.MonkeyPatch, tmp_path: Path +) -> None: + monkeypatch.setattr(translate, "RESPONSE_TIMEOUT_SECONDS", 0.05) + audio: Final = bytes(480) + pending: Final[asyncio.Queue[str]] = asyncio.Queue() + sender_finished: Final = asyncio.Event() + + async def speak_after_a_long_pause() -> None: + await asyncio.sleep(0.2) + await pending.put(json.dumps({"type": "session.output_audio.delta", "delta": base64.b64encode(audio).decode()})) + await asyncio.sleep(0.02) + sender_finished.set() + await pending.put(json.dumps({"type": "session.closed"})) + + output: Final = tmp_path / "translation.wav" + speaker: Final = asyncio.create_task(speak_after_a_long_pause()) + + result: Final = await translate.receive_translation( + cast(ClientConnection, SimpleNamespace(recv=pending.get)), output, sender_finished + ) + await speaker + + assert result is None + with wave.open(str(output), "rb") as rendered: + assert rendered.readframes(240) == audio + + +@pytest.mark.asyncio +async def test_a_quiet_gap_after_the_sender_stops_keeps_the_rest_of_the_translation( + monkeypatch: pytest.MonkeyPatch, tmp_path: Path +) -> None: + monkeypatch.setattr(translate, "RESPONSE_TIMEOUT_SECONDS", 1.0) + first: Final = bytes(480) + second: Final = bytes(range(240)) * 2 + events: Final = iter( + ( + {"type": "session.output_audio.delta", "delta": base64.b64encode(first).decode()}, + {"type": "session.output_audio.delta", "delta": base64.b64encode(second).decode()}, + {"type": "session.closed"}, + ) + ) + + async def recv() -> str: + event: Final = next(events) + if event.get("delta") == base64.b64encode(second).decode(): + await asyncio.sleep(0.3) + return json.dumps(event) + + sender_finished: Final = asyncio.Event() + sender_finished.set() + output: Final = tmp_path / "translation.wav" + + result: Final = await translate.receive_translation( + cast(ClientConnection, SimpleNamespace(recv=recv)), output, sender_finished + ) + + assert result is None + with wave.open(str(output), "rb") as rendered: + assert rendered.readframes(480) == first + second + + +@pytest.mark.asyncio +async def test_a_stream_that_never_closes_the_session_reports_an_error( + monkeypatch: pytest.MonkeyPatch, tmp_path: Path +) -> None: + monkeypatch.setattr(translate, "RESPONSE_TIMEOUT_SECONDS", 0.05) + audio: Final = bytes(480) + pending: Final[asyncio.Queue[str]] = asyncio.Queue() + await pending.put(json.dumps({"type": "session.output_audio.delta", "delta": base64.b64encode(audio).decode()})) + sender_finished: Final = asyncio.Event() + sender_finished.set() + + result: Final = await translate.receive_translation( + cast(ClientConnection, SimpleNamespace(recv=pending.get)), tmp_path / "translation.wav", sender_finished + ) + + assert result == "The translation stream went quiet for 0.05 s without closing the session" + + +@pytest.mark.asyncio +async def test_the_sender_closes_the_session_after_the_last_audio_chunk() -> None: + sent: Final[asyncio.Queue[str]] = asyncio.Queue() + finished: Final = asyncio.Event() + pcm: Final = bytes(translate.CHUNK_BYTES + 2) + + await translate.send_audio(cast(ClientConnection, SimpleNamespace(send=sent.put)), pcm, 0.0, finished) + + messages: Final = tuple(json.loads(sent.get_nowait()) for _ in range(sent.qsize())) + assert [message["type"] for message in messages] == [ + "session.input_audio_buffer.append", + "session.input_audio_buffer.append", + "session.close", + ] + assert b"".join(base64.b64decode(message["audio"]) for message in messages[:-1]) == pcm + assert finished.is_set() diff --git a/tests/unit/decisions/test_main.py b/tests/unit/decisions/test_main.py index 789d59bd613..0e2813e0a0d 100644 --- a/tests/unit/decisions/test_main.py +++ b/tests/unit/decisions/test_main.py @@ -6,8 +6,10 @@ import copy import json import re import threading +import uuid from collections.abc import Awaitable, Callable, Iterator, Mapping, Sequence from concurrent.futures import wait +from datetime import datetime from functools import partial from types import MappingProxyType from typing import Final, TypeAlias @@ -132,6 +134,7 @@ _PROVIDERS: Final[tuple[tuple[str, str, str, str], ...]] = ( "https://openrouter.ai/api/alpha/decisions", "typesafe/jev-1.13", ), + ("empiriolabs", "empiriolabs/aplomb-1", "https://api.empiriolabs.ai/v1/decisions", "aplomb-1"), ) _OPENAI_RESPONSE: Final[Mapping[str, object]] = { @@ -299,6 +302,43 @@ async def test_router_dispatches_typesafe_decisions_without_api_base( assert response.answers["sentiment"].choice == "positive" +@pytest.mark.asyncio +async def test_least_busy_frees_a_decisions_deployment_once_a_proxy_logged_call_finishes( + respx_mock: respx.MockRouter, +) -> None: + respx_mock.post("https://api.typesafe.ai/v1/systemone").respond(json=_RESPONSE) + router: Final = litellm.Router( + model_list=[ + { + "model_name": "jev", + "litellm_params": {"model": "typesafe/jev-latest", "api_key": "k"}, + "model_info": {"id": deployment_id}, + } + for deployment_id in ("jev-a", "jev-b") + ], + routing_strategy="least-busy", + ) + + async def call_through_proxy_logging() -> object: + logging_obj, _ = litellm.utils.function_setup( + original_function="adecisions", + rules_obj=litellm.utils.Rules(), + start_time=datetime(2026, 1, 1), + model="jev", + litellm_call_id=str(uuid.uuid4()), + ) + response: Final = await router.adecisions( + model="jev", + input="Is this a defect?", + questions=[{"type": "predicate", "name": "is_defect", "instructions": "Is this a defect?"}], + litellm_logging_obj=logging_obj, + ) + await _drain_logging_worker() + return response._hidden_params["model_id"] + + assert (await call_through_proxy_logging(), await call_through_proxy_logging()) == ("jev-a", "jev-a") + + def test_decisions_uses_the_same_wire_contract_for_sync_calls(respx_mock: respx.MockRouter) -> None: route: Final = respx_mock.post("https://api.perplexity.ai/v1/decisions").respond(json=_RESPONSE) @@ -1549,6 +1589,7 @@ _PROVIDERS_WHOSE_CHAT_MODELS_ALSO_DECIDE: Final = frozenset( LlmProviders.LM_STUDIO.value, LlmProviders.OLLAMA.value, LlmProviders.OLLAMA_CHAT.value, + LlmProviders.EMPIRIOLABS.value, } ) _DEDICATED_DECIDER_PROVIDERS: Final[tuple[str, ...]] = tuple( @@ -3449,6 +3490,147 @@ async def test_fireworks_ai_bills_cached_input_tokens_at_the_cache_read_rate( assert recording_logger.standard_logging_object["response_cost"] < 300 * float(prices["input_cost_per_token"]) +_EMPIRIOLABS_MODEL: Final = "empiriolabs/aplomb-1" +_EMPIRIOLABS_DEFAULT_URL: Final = "https://api.empiriolabs.ai/v1/decisions" +_EMPIRIOLABS_STATE: Final = "I was charged twice for order 4411 and want a refund today." +_EMPIRIOLABS_QUESTIONS: Final[Mapping[str, object]] = MappingProxyType( + {"is_refund": {"type": "noul", "instructions": "Is the customer asking for a refund?"}} +) +_EMPIRIOLABS_RESPONSE: Final[Mapping[str, object]] = { + "model": "aplomb-1", + "answers": {"is_refund": {"type": "noul", "noul": 0.97, "confidence": 0.94}}, + "usage": {"input_tokens": 24, "output_tokens": 0}, +} + + +@pytest.mark.parametrize( + ("api_base", "environment_api_base", "url"), + ( + (None, None, _EMPIRIOLABS_DEFAULT_URL), + (None, "https://environment-gateway.example/v1", "https://environment-gateway.example/v1/decisions"), + ( + "https://gateway.example/v1/", + "https://environment-gateway.example/v1", + "https://gateway.example/v1/decisions", + ), + ("https://gateway.example", None, "https://gateway.example/v1/decisions"), + ), + ids=("default_base", "environment_base", "explicit_base_over_environment", "explicit_base_without_v1"), +) +def test_empiriolabs_posts_the_systemone_body_to_v1_decisions_on_the_resolved_base( + api_base: str | None, + environment_api_base: str | None, + url: str, + monkeypatch: pytest.MonkeyPatch, + respx_mock: respx.MockRouter, +) -> None: + monkeypatch.delenv("EMPIRIOLABS_API_BASE", raising=False) + if environment_api_base is not None: + monkeypatch.setenv("EMPIRIOLABS_API_BASE", environment_api_base) + route: Final = respx_mock.post(url).respond(json=_EMPIRIOLABS_RESPONSE) + + response: Final = litellm.systemone( + model=_EMPIRIOLABS_MODEL, + state=_EMPIRIOLABS_STATE, + questions=_EMPIRIOLABS_QUESTIONS, + api_base=api_base, + api_key="caller-key", + ) + + assert route.call_count == 1 + assert json.loads(route.calls[0].request.content) == { + "model": "aplomb-1", + "state": _EMPIRIOLABS_STATE, + "questions": {"is_refund": {"type": "noul", "instructions": "Is the customer asking for a refund?"}}, + } + assert response.answers["is_refund"] == NoulAnswer(type="noul", noul=0.97, confidence=0.94) + assert response._hidden_params["custom_llm_provider"] == "empiriolabs" + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("api_key", "authorization"), + ((None, "Bearer environment-key"), ("caller-key", "Bearer caller-key")), + ids=("environment_key", "caller_key_over_environment"), +) +async def test_empiriolabs_sends_the_caller_key_or_else_the_environment_key( + api_key: str | None, + authorization: str, + monkeypatch: pytest.MonkeyPatch, + respx_mock: respx.MockRouter, +) -> None: + monkeypatch.delenv("EMPIRIOLABS_API_BASE", raising=False) + monkeypatch.setenv("EMPIRIOLABS_API_KEY", "environment-key") + route: Final = respx_mock.post(_EMPIRIOLABS_DEFAULT_URL).respond(json=_EMPIRIOLABS_RESPONSE) + + response: Final = await litellm.adecisions( + model=_EMPIRIOLABS_MODEL, + input=_EMPIRIOLABS_STATE, + questions=[{"type": "predicate", "name": "is_refund", "instructions": "Is the customer asking for a refund?"}], + api_key=api_key, + ) + + assert route.call_count == 1 + assert route.calls[0].request.headers["authorization"] == authorization + assert isinstance(response, OpenAIDecisionResponse) + assert [answer.model_dump(mode="json") for answer in response.answers] == [ + {"type": "predicate", "name": "is_refund", "probability": 0.97} + ] + + +def test_empiriolabs_without_a_key_is_refused_before_http( + monkeypatch: pytest.MonkeyPatch, + respx_mock: respx.MockRouter, +) -> None: + monkeypatch.delenv("EMPIRIOLABS_API_KEY", raising=False) + monkeypatch.delenv("EMPIRIOLABS_API_BASE", raising=False) + + with pytest.raises(litellm.AuthenticationError, match="Missing API key for Decisions provider 'empiriolabs'"): + litellm.systemone(model=_EMPIRIOLABS_MODEL, state=_EMPIRIOLABS_STATE, questions=_EMPIRIOLABS_QUESTIONS) + + assert len(respx_mock.calls) == 0 + + +@pytest.mark.parametrize( + ("status", "error_type", "code", "exception"), + ( + (401, "authentication_error", "invalid_api_key", litellm.AuthenticationError), + (402, "insufficient_credits", "insufficient_credits", litellm.PaymentRequiredError), + (404, "not_found_error", "model_not_found", litellm.NotFoundError), + (422, "invalid_request_error", "invalid_request", litellm.BadRequestError), + (429, "rate_limit_error", "rate_limit_exceeded", litellm.RateLimitError), + (503, "service_unavailable", "model_unavailable", litellm.ServiceUnavailableError), + ), +) +def test_empiriolabs_upstream_errors_keep_their_status_and_message( + status: int, + error_type: str, + code: str, + exception: type[Exception], + monkeypatch: pytest.MonkeyPatch, + respx_mock: respx.MockRouter, +) -> None: + monkeypatch.delenv("EMPIRIOLABS_API_BASE", raising=False) + message: Final = f"upstream refused the decision with {code}" + route: Final = respx_mock.post(_EMPIRIOLABS_DEFAULT_URL).respond( + status, + json={"error": {"message": message, "type": error_type, "code": code}}, + headers={"retry-after": "1"}, + ) + + with pytest.raises(exception, match=message) as caught: + litellm.systemone( + model=_EMPIRIOLABS_MODEL, + state=_EMPIRIOLABS_STATE, + questions=_EMPIRIOLABS_QUESTIONS, + api_key="caller-key", + num_retries=0, + ) + + assert getattr(caught.value, "status_code") == status + assert route.call_count == 1 + + _BOX_QUESTION_REQUESTS: Final[tuple[tuple[str, Mapping[str, object]], ...]] = ( ( "decisions", diff --git a/tests/unit/enterprise/proxy/test_managed_files_hook.py b/tests/unit/enterprise/proxy/test_managed_files_hook.py index 89fff365c3f..942433b39fb 100644 --- a/tests/unit/enterprise/proxy/test_managed_files_hook.py +++ b/tests/unit/enterprise/proxy/test_managed_files_hook.py @@ -9,18 +9,24 @@ import asyncio import base64 import json import logging +from collections.abc import Callable, Mapping from types import MappingProxyType import pytest -from typing import Final, Optional +from typing import TYPE_CHECKING, Final, Optional from unittest.mock import AsyncMock, MagicMock, patch +from litellm._internal_context import internal_parent_request_id, is_internal_call from litellm.llms.base_llm.files.transformation import FileListModelScope from litellm.proxy._types import LitellmUserRoles, ProxyException, UserAPIKeyAuth from litellm.proxy.openai_files_endpoints.common_utils import BATCH_CREATE_HIDDEN_PARAM +from litellm.responses.streaming_iterator import drain_logging_tasks from litellm.types.llms.openai import FileListPage, OpenAIFileObject from litellm.types.utils import LiteLLMBatch +if TYPE_CHECKING: + from litellm_enterprise.proxy.hooks.managed_files import PROXY_LiteLLMManagedFiles + def _make_file_object(file_id: str = "file-output-abc") -> OpenAIFileObject: return OpenAIFileObject( @@ -2268,3 +2274,324 @@ async def test_batch_create_hook_passes_the_router_deployment_as_creating_model_ first, second = managed_files.store_unified_object_id.await_args_list assert first.kwargs["creating_model_id"] == "deploy-team-b" assert second.kwargs["creating_model_id"] is None + + +class _FakeFilesRouter: + def __init__( + self, + deployments_by_model: Mapping[str, tuple[str, ...]], + delete_error: Exception | None = None, + delete_gate: asyncio.Event | None = None, + provider: str = "openai", + gone_file_ids: frozenset[str] = frozenset(), + ) -> None: + self.deployments_by_model = deployments_by_model + self.delete_error = delete_error + self.gone_file_ids = gone_file_ids + self.delete_gate = delete_gate + self.provider = provider + self.upload_count = 0 + self.deletes: tuple[tuple[str, str, Mapping[str, object], Mapping[str, str]], ...] = () + self.deletes_marked_internal: tuple[bool, ...] = () + self.delete_parent_request_ids: tuple[str | None, ...] = () + + async def acreate_file( + self, + model: str, + file: tuple[str, bytes, str], + purpose: str, + litellm_metadata: Mapping[str, object], + ) -> OpenAIFileObject: + deployment_ids: Final = self.deployments_by_model[model] + provider_file_ids: Final = tuple( + f"file-upload-{self.upload_count + offset + 1}" for offset in range(len(deployment_ids)) + ) + self.upload_count += len(deployment_ids) + response: Final = _make_file_object(provider_file_ids[0]).model_copy(update={"purpose": purpose}) + response._hidden_params = { + "model_id": deployment_ids[0], + "custom_llm_provider": self.provider, + "model_file_id_mapping": dict(zip(deployment_ids, provider_file_ids)), + "litellm_call_id": f"call-of-{provider_file_ids[0]}", + } + return response + + def registry(self) -> "_FakeFilesRouter": + return self + + def credentials(self, model_id: str, form: str) -> dict[str, str]: + assert form == "with_provider" + return {"custom_llm_provider": self.provider, "api_key": f"key-of-{model_id}"} + + async def afile_delete( + self, + model: str, + file_id: str, + litellm_metadata: Mapping[str, object], + _litellm_internal_model_credentials: Mapping[str, str], + litellm_call_id: str | None = None, + ) -> None: + if self.delete_gate is not None: + await self.delete_gate.wait() + if isinstance(litellm_metadata, dict): + litellm_metadata.update({"model_info": {"id": model}}) + self.deletes = (*self.deletes, (model, file_id, litellm_metadata, _litellm_internal_model_credentials)) + self.deletes_marked_internal = (*self.deletes_marked_internal, is_internal_call.get()) + self.delete_parent_request_ids = (*self.delete_parent_request_ids, internal_parent_request_id.get()) + if file_id in self.gone_file_ids: + raise RuntimeError(f"No such File object: {file_id}") + if self.delete_error is not None: + raise self.delete_error + + +_REQUEST_METADATA: Final = MappingProxyType({"user_api_key_team_id": "test-team"}) + + +async def _eventually(condition: Callable[[], bool]) -> None: + async def _poll() -> None: + while not condition(): + await asyncio.sleep(0) + + await asyncio.wait_for(_poll(), timeout=1) + + +async def _upload( + managed_files: "PROXY_LiteLLMManagedFiles", + router: _FakeFilesRouter, + target_model_names: list[str], + litellm_metadata: Mapping[str, object] = _REQUEST_METADATA, + content_type: str = "text/plain", +) -> OpenAIFileObject: + return await managed_files.acreate_file( + create_file_request={ + "file": ("notes.txt", b"the launch code is ORCHID-42\n", content_type), + "purpose": "user_data", + "litellm_metadata": litellm_metadata, + }, + llm_router=router, + target_model_names_list=target_model_names, + litellm_parent_otel_span=None, + user_api_key_dict=_make_team_member_api_key_dict(), + ) + + +async def _create_managed_file( + router: _FakeFilesRouter, target_model_names: list[str] +) -> tuple[dict[str, str], list[str], tuple[str, str]]: + managed_files, mock_prisma = _make_real_managed_files_instance() + response: Final = await _upload(managed_files, router, target_model_names) + stored: Final = mock_prisma.db.litellm_managedfiletable.upsert.await_args.kwargs["data"]["create"] + decoded: Final = base64.urlsafe_b64decode(response.id + "=" * (-len(response.id) % 4)).decode() + carried: Final = ( + managed_files.get_model_id_from_unified_file_id(decoded), + managed_files.get_output_file_id_from_unified_file_id(decoded), + ) + return json.loads(stored["model_mappings"]), stored["flat_model_file_ids"], carried + + +@pytest.mark.asyncio +async def test_acreate_file_keeps_the_upload_the_managed_id_carries_when_two_targets_share_a_deployment(): + router: Final = _FakeFilesRouter({"gpt-a": ("wildcard-dep",), "gpt-b": ("wildcard-dep",)}) + + model_mappings, flat_ids, carried = await _create_managed_file(router, ["gpt-a", "gpt-b"]) + await _eventually(lambda: len(router.deletes) == 1) + + assert carried == ("wildcard-dep", "file-upload-1") + assert model_mappings == {"wildcard-dep": "file-upload-1"} + assert flat_ids == ["file-upload-1"] + assert router.deletes == ( + ( + "wildcard-dep", + "file-upload-2", + _REQUEST_METADATA, + {"custom_llm_provider": "openai", "api_key": "key-of-wildcard-dep"}, + ), + ) + assert isinstance(router.deletes[0][3], MappingProxyType) + + +@pytest.mark.asyncio +async def test_acreate_file_deletes_only_the_repeat_upload_and_keeps_every_deployment_reached_once(): + router: Final = _FakeFilesRouter({"gpt-a": ("dep-1", "dep-2"), "gpt-b": ("dep-2",), "gpt-c": ("dep-3",)}) + + model_mappings, flat_ids, carried = await _create_managed_file(router, ["gpt-a", "gpt-b", "gpt-c"]) + await _eventually(lambda: len(router.deletes) == 1) + + assert carried == ("dep-1", "file-upload-1") + assert list(model_mappings.items()) == [ + ("dep-1", "file-upload-1"), + ("dep-2", "file-upload-2"), + ("dep-3", "file-upload-4"), + ] + assert flat_ids == ["file-upload-1", "file-upload-2", "file-upload-4"] + assert [delete[:2] for delete in router.deletes] == [("dep-2", "file-upload-3")] + + +@pytest.mark.asyncio +async def test_acreate_file_still_returns_the_managed_file_when_deleting_the_repeat_upload_fails(caplog: pytest.LogCaptureFixture): + router: Final = _FakeFilesRouter( + {"gpt-a": ("wildcard-dep",), "gpt-b": ("wildcard-dep",)}, + delete_error=RuntimeError("provider unavailable"), + ) + + with caplog.at_level(logging.WARNING): + model_mappings, flat_ids, carried = await _create_managed_file(router, ["gpt-a", "gpt-b"]) + await _eventually(lambda: "provider unavailable" in caplog.text) + + assert carried == ("wildcard-dep", "file-upload-1") + assert model_mappings == {"wildcard-dep": "file-upload-1"} + assert flat_ids == ["file-upload-1"] + assert [delete[:2] for delete in router.deletes] == [("wildcard-dep", "file-upload-2")] + assert "file-upload-2" in caplog.text and "wildcard-dep" in caplog.text + assert "provider unavailable" in caplog.text + + +@pytest.mark.asyncio +async def test_acreate_file_answers_before_deleting_the_repeat_upload_finishes(): + delete_gate: Final = asyncio.Event() + router: Final = _FakeFilesRouter({"gpt-a": ("wildcard-dep",), "gpt-b": ("wildcard-dep",)}, delete_gate=delete_gate) + + model_mappings, flat_ids, carried = await asyncio.wait_for( + _create_managed_file(router, ["gpt-a", "gpt-b"]), timeout=1 + ) + + assert carried == ("wildcard-dep", "file-upload-1") + assert model_mappings == {"wildcard-dep": "file-upload-1"} + assert flat_ids == ["file-upload-1"] + assert router.deletes == () + delete_gate.set() + await _eventually(lambda: len(router.deletes) == 1) + assert router.deletes[0][:2] == ("wildcard-dep", "file-upload-2") + + +@pytest.mark.asyncio +async def test_shutdown_drain_waits_for_the_repeat_upload_delete(): + delete_gate: Final = asyncio.Event() + router: Final = _FakeFilesRouter({"gpt-a": ("wildcard-dep",), "gpt-b": ("wildcard-dep",)}, delete_gate=delete_gate) + + await _create_managed_file(router, ["gpt-a", "gpt-b"]) + asyncio.get_running_loop().call_later(0.05, delete_gate.set) + await drain_logging_tasks(timeout=1) + + assert [delete[:2] for delete in router.deletes] == [("wildcard-dep", "file-upload-2")] + + +@pytest.mark.asyncio +async def test_each_repeat_upload_delete_runs_as_an_internal_call_of_the_upload_that_made_the_copy(): + router: Final = _FakeFilesRouter( + {"gpt-a": ("wildcard-dep",), "gpt-b": ("wildcard-dep",), "gpt-c": ("wildcard-dep",)} + ) + + await _create_managed_file(router, ["gpt-a", "gpt-b", "gpt-c"]) + await drain_logging_tasks(timeout=1) + + assert router.deletes_marked_internal == (True, True) + assert sorted(zip((delete[1] for delete in router.deletes), router.delete_parent_request_ids)) == [ + ("file-upload-2", "call-of-file-upload-2"), + ("file-upload-3", "call-of-file-upload-3"), + ] + assert is_internal_call.get() is False + assert internal_parent_request_id.get() is None + + +@pytest.mark.asyncio +async def test_litellm_proxy_wildcard_keeps_its_last_per_target_upload_and_deletes_nothing(): + router: Final = _FakeFilesRouter( + {"gpt-a": ("proxy-wildcard-dep",), "gpt-b": ("proxy-wildcard-dep",)}, provider="litellm_proxy" + ) + + model_mappings, flat_ids, _ = await _create_managed_file(router, ["gpt-a", "gpt-b"]) + await drain_logging_tasks(timeout=1) + + assert model_mappings == {"proxy-wildcard-dep": "file-upload-2"} + assert flat_ids == ["file-upload-2"] + assert router.deletes == () + + +async def _upload_then_delete( + router: _FakeFilesRouter, target_model_names: list[str], content_type: str = "text/plain" +) -> tuple[str, ...]: + managed_files, mock_prisma = _make_real_managed_files_instance() + response: Final = await _upload(managed_files, router, target_model_names, content_type=content_type) + await drain_logging_tasks(timeout=1) + deletes_during_upload: Final = len(router.deletes) + managed_files.internal_usage_cache.async_get_cache = AsyncMock( + return_value=managed_files.internal_usage_cache.async_set_cache.await_args.kwargs["value"] + ) + mock_prisma.db.litellm_managedfiletable.find_first = AsyncMock(return_value=MagicMock()) + mock_prisma.db.litellm_managedfiletable.delete = AsyncMock() + + deleted: Final = await managed_files.afile_delete( + file_id=response.id, + litellm_parent_otel_span=None, + llm_router=router, + litellm_metadata=_REQUEST_METADATA, + litellm_call_id="delete-call", + ) + + assert deleted.deleted is True + mock_prisma.db.litellm_managedfiletable.delete.assert_awaited_once_with(where={"unified_file_id": response.id}) + return tuple(delete[1] for delete in router.deletes[deletes_during_upload:]) + + +@pytest.mark.asyncio +async def test_deleting_a_litellm_proxy_wildcard_file_removes_the_upload_its_id_carries_too(): + router: Final = _FakeFilesRouter( + {"gpt-a": ("proxy-wildcard-dep",), "gpt-b": ("proxy-wildcard-dep",)}, provider="litellm_proxy" + ) + + assert await _upload_then_delete(router, ["gpt-a", "gpt-b"]) == ("file-upload-2", "file-upload-1") + + +@pytest.mark.asyncio +async def test_deleting_a_wildcard_file_removes_its_kept_upload_once(): + router: Final = _FakeFilesRouter({"gpt-a": ("wildcard-dep",), "gpt-b": ("wildcard-dep",)}) + + assert await _upload_then_delete(router, ["gpt-a", "gpt-b"]) == ("file-upload-1",) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "content_type", + [ + "text/plain;llm_output_file_id,file-of-another-team;llm_output_file_model_id,wildcard-dep", + "text/plain;llm_output_file_id,file-of-another-team", + ], +) +async def test_deleting_a_file_removes_only_the_uploads_the_gateway_made_for_it(content_type: str): + router: Final = _FakeFilesRouter({"gpt-a": ("wildcard-dep",), "gpt-b": ("wildcard-dep",)}) + + assert await _upload_then_delete(router, ["gpt-a", "gpt-b"], content_type) == ("file-upload-1",) + + +@pytest.mark.asyncio +async def test_deleting_a_file_still_succeeds_when_the_upload_its_id_carries_is_already_gone( + caplog: pytest.LogCaptureFixture, +): + router: Final = _FakeFilesRouter( + {"gpt-a": ("proxy-wildcard-dep",), "gpt-b": ("proxy-wildcard-dep",)}, + provider="litellm_proxy", + gone_file_ids=frozenset({"file-upload-1"}), + ) + + with caplog.at_level(logging.WARNING): + assert await _upload_then_delete(router, ["gpt-a", "gpt-b"]) == ("file-upload-2", "file-upload-1") + + assert "file-upload-1" in caplog.text and "No such File object" in caplog.text + assert router.deletes_marked_internal == (False, True) + assert router.delete_parent_request_ids == (None, "delete-call") + + +@pytest.mark.asyncio +async def test_repeat_upload_delete_leaves_the_upload_request_metadata_unchanged(): + router: Final = _FakeFilesRouter({"gpt-a": ("wildcard-dep",), "gpt-b": ("wildcard-dep",)}) + upload_metadata: Final = {"user_api_key_team_id": "test-team"} + managed_files, _ = _make_real_managed_files_instance() + + await _upload(managed_files, router, ["gpt-a", "gpt-b"], upload_metadata) + await drain_logging_tasks(timeout=1) + + assert upload_metadata == {"user_api_key_team_id": "test-team"} + assert [delete[2] for delete in router.deletes] == [ + {"user_api_key_team_id": "test-team", "model_info": {"id": "wildcard-dep"}} + ] diff --git a/tests/unit/integrations/azure_storage/test_azure_storage.py b/tests/unit/integrations/azure_storage/test_azure_storage.py index 0f0ce24ff84..ee12291e7a0 100644 --- a/tests/unit/integrations/azure_storage/test_azure_storage.py +++ b/tests/unit/integrations/azure_storage/test_azure_storage.py @@ -5,19 +5,28 @@ import re import sys import threading from datetime import datetime, timedelta, timezone +from typing import Final from unittest.mock import AsyncMock, MagicMock, patch import pytest -from litellm.constants import _DEFAULT_TTL_FOR_HTTPX_CLIENTS +from litellm.constants import _DEFAULT_TTL_FOR_HTTPX_CLIENTS, INTERNAL_CALL_ORIGIN_METADATA_KEY from litellm.integrations.azure_storage import azure_storage as azure_storage_module from litellm.integrations.azure_storage.azure_storage import ( AzureBlobStorageLogger, _cached_credential_chain_token_provider, adls_safe_file_name, ) +from litellm.types.passthrough_endpoints.pass_through_endpoints import ( + SETTLES_BACKGROUND_RESPONSE_KWARG, + BackgroundResponseSettlement, +) from litellm.types.secret_managers.get_azure_ad_token_provider import AzureCredentialType -from litellm.types.utils import StandardAuditLogPayload, StandardLoggingPayload +from litellm.types.utils import ( + BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN, + StandardAuditLogPayload, + StandardLoggingPayload, +) @pytest.fixture @@ -648,3 +657,171 @@ async def test_audit_log_is_uploaded_to_a_dated_audit_logs_path_with_an_account_ assert json.loads(uploaded) == audit_log assert file_client.append_data.await_args.kwargs == {"data": uploaded, "offset": 0, "length": len(uploaded)} file_client.flush_data.assert_awaited_once_with(position=len(uploaded), offset=0) + + +BACKGROUND_RESPONSE_ID: Final = "resp_YWJjZA==" +BACKGROUND_COST_POLL_KWARGS: Final = { + "call_type": "aget_responses", + "litellm_params": { + "metadata": {INTERNAL_CALL_ORIGIN_METADATA_KEY: BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN}, + }, +} +PASSTHROUGH_SETTLEMENT_KWARGS: Final = { + "call_type": "pass_through_endpoint", + "litellm_params": {"metadata": {}}, + SETTLES_BACKGROUND_RESPONSE_KWARG: BackgroundResponseSettlement.SETTLES, +} + + +def _background_create_cost_and_other_events( + cost_kwargs: dict[str, object], +) -> tuple[tuple[dict[str, object], StandardLoggingPayload], ...]: + create: Final = StandardLoggingPayload( + id=BACKGROUND_RESPONSE_ID, + call_type="aresponses", + messages=[{"role": "user", "content": "background create input"}], + ) + cost: Final = StandardLoggingPayload(id=BACKGROUND_RESPONSE_ID, call_type="aget_responses", response_cost=0.42) + ordinary: Final = StandardLoggingPayload(id="chatcmpl-ordinary", call_type="acompletion") + batch_retrieve: Final = StandardLoggingPayload(id="batch_abc123", call_type="aretrieve_batch", response_cost=0.07) + return ( + ({"call_type": "aresponses", "litellm_params": {"metadata": {}}, "standard_logging_object": create}, create), + ({**cost_kwargs, "standard_logging_object": cost}, cost), + ( + {"call_type": "acompletion", "litellm_params": {"metadata": {}}, "standard_logging_object": ordinary}, + ordinary, + ), + ( + { + "call_type": "aretrieve_batch", + "litellm_params": {"metadata": {}}, + "standard_logging_object": batch_retrieve, + }, + batch_retrieve, + ), + ) + + +def _expected_files( + events: tuple[tuple[dict[str, object], StandardLoggingPayload], ...], +) -> dict[str, StandardLoggingPayload]: + create, cost, ordinary, batch_retrieve = (payload for _, payload in events) + return { + "resp_YWJjZA.json": create, + "resp_YWJjZA_background_cost.json": cost, + "chatcmpl-ordinary.json": ordinary, + "batch_abc123.json": batch_retrieve, + } + + +async def _log_and_flush( + logger: AzureBlobStorageLogger, events: tuple[tuple[dict[str, object], StandardLoggingPayload], ...] +) -> None: + for kwargs, payload in events: + await logger.async_log_success_event(kwargs, {"id": payload["id"]}, None, None) + await logger.async_send_batch() + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "cost_kwargs", + ( + pytest.param(BACKGROUND_COST_POLL_KWARGS, id="cost-poll"), + pytest.param(PASSTHROUGH_SETTLEMENT_KWARGS, id="passthrough-settlement"), + ), +) +async def test_background_cost_event_keeps_its_own_file_beside_the_create_on_the_entra_path( + mock_env_vars, monkeypatch, cost_kwargs +): + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + events: Final = _background_create_cost_and_other_events(cost_kwargs) + with patch( # test-quality-ok: REST client is created inside the method; assert emitted requests + "litellm.integrations.azure_storage.azure_storage.get_async_httpx_client" + ) as mock_get_client: + mock_http_client = AsyncMock() + mock_http_client.put.return_value = MagicMock() + mock_http_client.patch.return_value = MagicMock() + mock_get_client.return_value = mock_http_client + + logger = AzureBlobStorageLogger() + logger.azure_auth_token = "mock-azure-ad-token" + logger.token_expiry = None + await _log_and_flush(logger, events) + + base_url: Final = "https://test-account.dfs.core.windows.net/test-container/" + appends: Final = [call for call in mock_http_client.patch.call_args_list if "action=append" in call.args[0]] + uploaded: Final = { + call.args[0].removeprefix(base_url).split("?")[0]: json.loads(call.kwargs["data"]) for call in appends + } + assert uploaded == _expected_files(events), ( + "the create, its background cost event and every other event must each keep their own file" + ) + + +@pytest.mark.asyncio +async def test_failure_event_is_uploaded_to_a_file_named_after_its_id(mock_env_vars, monkeypatch): + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + failure: Final = StandardLoggingPayload(id="chatcmpl-failed", call_type="acompletion", error_str="provider failure") + with patch( # test-quality-ok: REST client is created inside the method; assert emitted requests + "litellm.integrations.azure_storage.azure_storage.get_async_httpx_client" + ) as mock_get_client: + mock_http_client = AsyncMock() + mock_http_client.put.return_value = MagicMock() + mock_http_client.patch.return_value = MagicMock() + mock_get_client.return_value = mock_http_client + + logger = AzureBlobStorageLogger() + logger.azure_auth_token = "mock-azure-ad-token" + logger.token_expiry = None + await logger.async_log_failure_event( + {"call_type": "acompletion", "litellm_params": {"metadata": {}}, "standard_logging_object": failure}, + None, + None, + None, + ) + await logger.async_send_batch() + + base_url: Final = "https://test-account.dfs.core.windows.net/test-container/" + appends: Final = [call for call in mock_http_client.patch.call_args_list if "action=append" in call.args[0]] + assert {call.args[0].removeprefix(base_url).split("?")[0]: json.loads(call.kwargs["data"]) for call in appends} == { + "chatcmpl-failed.json": failure + } + + +@pytest.mark.asyncio +async def test_background_cost_event_keeps_its_own_file_beside_the_create_with_an_account_key( + workload_identity_env_vars, monkeypatch +): + monkeypatch.setenv("AZURE_STORAGE_ACCOUNT_KEY", "dGVzdC1rZXk=") + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + monkeypatch.setattr(azure_storage_module, "datetime", _FrozenDatetime) + events: Final = _background_create_cost_and_other_events(BACKGROUND_COST_POLL_KWARGS) + + uploaded: Final[dict[str, StandardLoggingPayload]] = {} + + def file_client_for(file_path: str) -> MagicMock: + file_client = MagicMock() + file_client.create_file = AsyncMock() + file_client.flush_data = AsyncMock() + + async def append_data(data: bytes, offset: int, length: int) -> None: + uploaded[file_path] = json.loads(data) + + file_client.append_data = append_data + return file_client + + file_system_client = MagicMock() + file_system_client.get_file_client = MagicMock(side_effect=file_client_for) + service_client = MagicMock() + service_client.get_file_system_client = MagicMock(return_value=file_system_client) + fake_aio_module = MagicMock() + fake_aio_module.DataLakeServiceClient = MagicMock(return_value=service_client) + + with patch.dict(sys.modules, {"azure.storage.filedatalake.aio": fake_aio_module}): + logger = AzureBlobStorageLogger() + await _log_and_flush(logger, events) + + today: Final = _FrozenDatetime.now().strftime("%Y-%m-%d") + assert uploaded == {f"{today}/{name}": payload for name, payload in _expected_files(events).items()}, ( + "the create, its background cost event and every other event must each keep their own file" + ) diff --git a/tests/unit/integrations/clickhouse/test_clickhouse_spend_logger.py b/tests/unit/integrations/clickhouse/test_clickhouse_spend_logger.py index f94d7bbee37..42e69f95bb4 100644 --- a/tests/unit/integrations/clickhouse/test_clickhouse_spend_logger.py +++ b/tests/unit/integrations/clickhouse/test_clickhouse_spend_logger.py @@ -20,10 +20,16 @@ from litellm.integrations.clickhouse.clickhouse_spend_logger import ( strip_cache_hit_suffix, ) from litellm.integrations.clickhouse.context import lens_analysis +from litellm.constants import INTERNAL_CALL_ORIGIN_METADATA_KEY +from litellm.litellm_core_utils.internal_call_metadata import BACKGROUND_RESPONSE_COST_REQUEST_ID_SUFFIX from litellm.litellm_core_utils import litellm_logging from litellm.litellm_core_utils.secret_redaction import REDACTED from litellm.tracing.types import SpendLogRecord -from litellm.types.utils import StandardLoggingPayload +from litellm.types.passthrough_endpoints.pass_through_endpoints import ( + SETTLES_BACKGROUND_RESPONSE_KWARG, + BackgroundResponseSettlement, +) +from litellm.types.utils import BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN, StandardLoggingPayload _JSON_OBJECT_ADAPTER: Final = TypeAdapter(Mapping[str, JsonValue]) @@ -349,6 +355,41 @@ def test_cache_hit_id_is_stripped_for_response_id(): assert strip_cache_hit_suffix("chatcmpl-xyz") == "chatcmpl-xyz" +@pytest.mark.parametrize( + "cost_kwargs", + ( + pytest.param( + { + "call_type": "aget_responses", + "litellm_params": { + "metadata": {INTERNAL_CALL_ORIGIN_METADATA_KEY: BACKGROUND_RESPONSE_COST_POLL_CALL_ORIGIN} + }, + }, + id="cost-poll", + ), + pytest.param( + { + "call_type": "pass_through_endpoint", + "litellm_params": {"metadata": {}}, + SETTLES_BACKGROUND_RESPONSE_KWARG: BackgroundResponseSettlement.SETTLES, + }, + id="passthrough-settlement", + ), + ), +) +def test_background_cost_row_keeps_its_own_request_id_beside_its_create(cost_kwargs: Mapping[str, object]) -> None: + payload: Final = cast(StandardLoggingPayload, _payload(id="resp_YWJjZA", call_type="aresponses")) + create_kwargs: Final[Mapping[str, object]] = {"call_type": "aresponses", "litellm_params": {"metadata": {}}} + + rows: Final = [spend_log_row_from_payload(payload, kwargs) for kwargs in (create_kwargs, cost_kwargs)] + + assert [row["request_id"] for row in rows] == [ + "resp_YWJjZA", + f"resp_YWJjZA{BACKGROUND_RESPONSE_COST_REQUEST_ID_SUFFIX}", + ] + assert [row["response_id"] for row in rows] == ["resp_YWJjZA", "resp_YWJjZA"] + + def test_parse_traceparent_valid_missing_malformed(): assert parse_traceparent(TRACEPARENT) == (TRACE_ID, SPAN_ID) assert parse_traceparent(None) == ("", "") diff --git a/tests/unit/integrations/code_interpreter_interception/test_handler.py b/tests/unit/integrations/code_interpreter_interception/test_handler.py index c037b6be80d..f4f6a127fc7 100644 --- a/tests/unit/integrations/code_interpreter_interception/test_handler.py +++ b/tests/unit/integrations/code_interpreter_interception/test_handler.py @@ -5,16 +5,24 @@ All sandbox dependencies are injected: a FakeSandbox stands in for the real e2b config and records how it is called. """ +import asyncio import time +from collections.abc import Mapping from typing import Final +import httpx import pytest +import respx + +import litellm from litellm.integrations.code_interpreter_interception.handler import ( _INTERCEPTION_ACTIVE_KEY as _ACTIVE_KEY, ) from litellm.integrations.code_interpreter_interception.handler import ( _SANDBOX_KEY, + _SANDBOX_LOST_RESULT_OUTPUT, + _SANDBOX_UNAVAILABLE_OUTPUT, _SESSION_SCOPED_KEY, LITELLM_CODE_EXECUTION_TOOL_NAME, CodeInterpreterInterceptionLogger, @@ -23,6 +31,7 @@ from litellm.llms.base_llm.sandbox.transformation import CodeExecutionResult from litellm.types.integrations.custom_logger import ( CHAT_COMPLETION_AGENTIC_SURFACE, CODE_INTERPRETER_STREAM_OPTIONS_KEY, + AgenticLoopPlan, NON_CODE_INTERPRETER_INTERCEPTION_INTERNAL_PREFIXES, is_interception_internal_key, ) @@ -831,11 +840,7 @@ async def test_post_hook_delete_is_idempotent_across_loop_levels(): @pytest.mark.asyncio -async def test_build_plan_deletes_sandbox_when_execution_raises(): - """If sandbox execution raises before a plan is built (e.g. E2B aborts - output over its cap), the cached sandbox must be deleted before re-raising, - otherwise a caller can leak paid containers until the prune TTL.""" - +async def test_a_failed_code_run_still_deletes_its_sandbox_once_the_loop_ends(): class RaisingSandbox(FakeSandbox): async def arun_code(self, *, container, code, **kwargs): raise ValueError("output exceeded cap") @@ -843,13 +848,11 @@ async def test_build_plan_deletes_sandbox_when_execution_raises(): sandbox = RaisingSandbox() logger = CodeInterpreterInterceptionLogger(sandbox_config=sandbox) - with pytest.raises(ValueError, match="exceeded cap"): - await _build_plan(logger, sandbox, call_id="k1") + plan = await _build_plan(logger, sandbox, call_id="k1") + await logger.async_agentic_loop_cleanup_hook(plan=plan, kwargs={}) - assert len(sandbox.create_calls) == 1, "the sandbox must have been created" - assert len(sandbox.delete_calls) == 1, ( - "a build failure must delete the cached sandbox so it does not keep running and billing" - ) + assert len(sandbox.create_calls) == 1 + assert len(sandbox.delete_calls) == 1 assert "sbxkey1" not in logger._container_cache @@ -1448,3 +1451,215 @@ async def test_per_identity_cap_evicts_lru_session(): "the entry with the oldest last_accessed timestamp must be evicted first (LRU)" ) assert len(sandbox.delete_calls) == 1, "evicted sandbox must be deleted, not just removed from cache" + + +class _SandboxThatCannotStart(FakeSandbox): + async def acreate_sandbox(self, **kwargs): + raise ConnectionError("sandbox provider unreachable") + + +class _SandboxThatCannotRunCode(FakeSandbox): + async def arun_code(self, *, container, code, **kwargs): + raise TimeoutError("sandbox run timed out") + + +_SANDBOX_FAILURES: Final = ( + pytest.param(None, _SANDBOX_UNAVAILABLE_OUTPUT, id="no_sandbox"), + pytest.param(_SandboxThatCannotStart(), _SANDBOX_UNAVAILABLE_OUTPUT, id="create_fails"), + pytest.param(_SandboxThatCannotRunCode(), _SANDBOX_LOST_RESULT_OUTPUT, id="run_fails"), +) + + +@pytest.mark.asyncio +@pytest.mark.parametrize(("sandbox", "expected_output"), _SANDBOX_FAILURES) +async def test_a_sandbox_failure_answers_the_responses_tool_call_with_a_fixed_failure(sandbox, expected_output): + plan: Final = await _build_plan(CodeInterpreterInterceptionLogger(sandbox_config=sandbox), sandbox) + + outputs: Final = [message for message in _iter_messages(plan) if message.get("type") == "function_call_output"] + assert plan.run_agentic_loop is True + assert [(output["call_id"], output["output"]) for output in outputs] == [("c1", expected_output)] + assert [call["status"] for call in plan.metadata["code_interpreter_calls"]] == ["failed"] + + +@pytest.mark.asyncio +@pytest.mark.parametrize(("sandbox", "expected_output"), _SANDBOX_FAILURES) +async def test_a_sandbox_failure_answers_the_chat_tool_call_with_a_fixed_failure(sandbox, expected_output): + logger: Final = CodeInterpreterInterceptionLogger(sandbox_config=sandbox) + + plan: Final = await logger.async_build_agentic_loop_plan( + tools={ + "tool_calls": [ + {"id": "call_1", "name": LITELLM_CODE_EXECUTION_TOOL_NAME, "arguments": '{"code":"print(40 + 2)"}'} + ] + }, + model="gpt-5", + messages=[{"role": "user", "content": "x"}], + response={"choices": [{"message": {"tool_calls": [_chat_function_call_item()]}}]}, + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params={"tools": []}, + logging_obj=FakeLogging(litellm_call_id="k1"), + stream=False, + kwargs={ + "litellm_call_id": "k1", + _ACTIVE_KEY: True, + _SANDBOX_KEY: "sbxkey1", + "_agentic_loop_api_surface": CHAT_COMPLETION_AGENTIC_SURFACE, + }, + ) + + tool_messages: Final = [message for message in _iter_messages(plan) if message.get("role") == "tool"] + assert plan.run_agentic_loop is True + assert [(message["tool_call_id"], message["content"]) for message in tool_messages] == [ + ("call_1", expected_output) + ] + assert [call["status"] for call in plan.metadata["code_interpreter_calls"]] == ["failed"] + + +_SESSION_PLAN_SURFACES: Final = ( + pytest.param({}, FakeResponse(output=[_function_call_item()]), id="responses"), + pytest.param( + {_ACTIVE_KEY: True, "_agentic_loop_api_surface": CHAT_COMPLETION_AGENTIC_SURFACE}, + {"choices": [{"message": {"tool_calls": [_chat_function_call_item()]}}]}, + id="chat", + ), +) + + +async def _build_session_plan( + logger: CodeInterpreterInterceptionLogger, + request_id: str, + surface_kwargs: Mapping[str, object] | None = None, + response: object | None = None, +) -> AgenticLoopPlan: + return await logger.async_build_agentic_loop_plan( + tools={ + "tool_calls": [ + { + "id": "call_1", + "call_id": "c1", + "name": LITELLM_CODE_EXECUTION_TOOL_NAME, + "arguments": '{"code":"print(1)"}', + } + ] + }, + model="gpt-5", + messages=[{"role": "user", "content": "x"}], + response=response or FakeResponse(output=[_function_call_item()]), + anthropic_messages_provider_config=None, + anthropic_messages_optional_request_params={"tools": []}, + logging_obj=FakeLogging(litellm_call_id=request_id), + stream=False, + kwargs={ + "litellm_call_id": request_id, + _SANDBOX_KEY: "conv-1", + _SESSION_SCOPED_KEY: True, + **(surface_kwargs or {}), + }, + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize(("surface_kwargs", "response"), _SESSION_PLAN_SURFACES) +async def test_a_session_sandbox_whose_code_run_fails_is_not_reused_by_the_next_request( + surface_kwargs: Mapping[str, object], response: object +) -> None: + sandbox: Final = _SandboxThatCannotRunCode() + logger: Final = CodeInterpreterInterceptionLogger(sandbox_config=sandbox) + + await _build_session_plan(logger, "req1", surface_kwargs, response) + await _build_session_plan(logger, "req2", surface_kwargs, response) + + assert len(sandbox.create_calls) == 2 + assert len(sandbox.delete_calls) == 2 + + +class _SandboxWhoseFirstContainerDies(FakeSandbox): + def __init__(self) -> None: + super().__init__() + self.handles: list[FakeHandle] = [] + self.first_run_started = asyncio.Event() + self.first_run_may_finish = asyncio.Event() + + async def acreate_sandbox(self, **kwargs: object) -> FakeHandle: + self.create_calls.append(kwargs) + handle: Final = FakeHandle(sandbox_id=f"sbx_{len(self.handles)}") + self.handles.append(handle) + return handle + + async def arun_code(self, *, container: FakeHandle, code: str, **kwargs: object) -> CodeExecutionResult: + self.run_calls.append({"container": container, "code": code}) + if len(self.run_calls) == 1: + self.first_run_started.set() + await self.first_run_may_finish.wait() + if container is self.handles[0]: + raise TimeoutError("sandbox expired") + return CodeExecutionResult(stdout=self.stdout) + + +@pytest.mark.asyncio +async def test_a_late_failure_on_a_dead_session_sandbox_keeps_its_healthy_replacement() -> None: + sandbox: Final = _SandboxWhoseFirstContainerDies() + logger: Final = CodeInterpreterInterceptionLogger(sandbox_config=sandbox) + + slow_request: Final = asyncio.create_task(_build_session_plan(logger, "req-slow")) + await sandbox.first_run_started.wait() + await _build_session_plan(logger, "req-fails-fast") + await _build_session_plan(logger, "req-gets-replacement") + sandbox.first_run_may_finish.set() + await slow_request + await _build_session_plan(logger, "req-after") + + assert [call["container"] for call in sandbox.delete_calls] == [sandbox.handles[0]] + assert [call["container"] for call in sandbox.run_calls[-2:]] == [sandbox.handles[1], sandbox.handles[1]] + + +def _anthropic_message(content: list[dict[str, object]], stop_reason: str) -> dict[str, object]: + return { + "id": "msg_1", + "type": "message", + "role": "assistant", + "model": "claude-sonnet-5-5", + "content": content, + "stop_reason": stop_reason, + "stop_sequence": None, + "usage": {"input_tokens": 10, "output_tokens": 5}, + } + + +@pytest.mark.asyncio +async def test_a_responses_request_bridged_to_claude_runs_the_code_and_ends_without_the_internal_call( + monkeypatch: pytest.MonkeyPatch, respx_mock: respx.MockRouter +): + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + sandbox: Final = FakeSandbox(stdout="42") + monkeypatch.setattr(litellm, "callbacks", [CodeInterpreterInterceptionLogger(sandbox_config=sandbox)]) + provider: Final = respx_mock.post("https://api.anthropic.com/v1/messages").mock( + side_effect=[ + httpx.Response( + 200, + json=_anthropic_message( + [ + { + "type": "tool_use", + "id": "toolu_1", + "name": LITELLM_CODE_EXECUTION_TOOL_NAME, + "input": {"code": "print(40 + 2)"}, + } + ], + "tool_use", + ), + ), + httpx.Response(200, json=_anthropic_message([{"type": "text", "text": "The answer is 42."}], "end_turn")), + ] + ) + + response: Final = await litellm.aresponses( + model="anthropic/claude-sonnet-5-5", + input="compute 40 + 2", + api_key="sk-test", + tools=[{"type": "code_interpreter", "container": {"type": "auto"}}], + ) + + assert provider.call_count == 2 + assert [run["code"] for run in sandbox.run_calls] == ["print(40 + 2)"] + assert not [item for item in response.output if getattr(item, "type", None) == "function_call"] diff --git a/tests/unit/integrations/conftest.py b/tests/unit/integrations/conftest.py index 48a01ed8d48..9278a280fe7 100644 --- a/tests/unit/integrations/conftest.py +++ b/tests/unit/integrations/conftest.py @@ -1,14 +1,18 @@ import functools import http.server +import importlib.abc import ipaddress import os import queue import ssl +import sys import threading -from collections.abc import Iterator +from collections.abc import Iterator, Sequence from dataclasses import dataclass from datetime import datetime, timedelta, timezone +from importlib.machinery import ModuleSpec from pathlib import Path +from types import ModuleType from typing import Final import pytest @@ -75,6 +79,36 @@ def write_self_signed_cert(directory: Path, stem: str) -> tuple[Path, Path]: return certificate_path, key_path +PROXY_ONLY_PACKAGES: Final = frozenset({"fastapi", "starlette"}) + + +class _ProxyOnlyPackageBlocker(importlib.abc.MetaPathFinder): + def find_spec( + self, + fullname: str, + path: Sequence[str] | None = None, + target: ModuleType | None = None, + ) -> ModuleSpec | None: + if fullname.partition(".")[0] in PROXY_ONLY_PACKAGES: + raise ModuleNotFoundError(f"No module named {fullname!r}") + return None + + +def _needs_proxy_extras(module_name: str) -> bool: + return ( + module_name.partition(".")[0] in PROXY_ONLY_PACKAGES + or module_name == "litellm.proxy" + or module_name.startswith("litellm.proxy.") + ) + + +@pytest.fixture +def sdk_only_install(monkeypatch: pytest.MonkeyPatch) -> None: + for module_name in tuple(filter(_needs_proxy_extras, sys.modules)): + monkeypatch.delitem(sys.modules, module_name) + monkeypatch.setattr(sys, "meta_path", [_ProxyOnlyPackageBlocker(), *sys.meta_path]) + + @pytest.fixture(autouse=True) def restore_process_environment() -> Iterator[None]: original: Final = dict(os.environ) diff --git a/tests/unit/integrations/email_alerting/__init__.py b/tests/unit/integrations/email_alerting/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/unit/integrations/email_alerting/test_model_deprecation_email.py b/tests/unit/integrations/email_alerting/test_model_deprecation_email.py new file mode 100644 index 00000000000..54dbe342148 --- /dev/null +++ b/tests/unit/integrations/email_alerting/test_model_deprecation_email.py @@ -0,0 +1,298 @@ +"""Retirement reminder schedule, durable dedupe, ownership scope and safe rendering.""" + +import asyncio +from dataclasses import replace +from datetime import date, datetime, timedelta, timezone +from types import MappingProxyType +from unittest.mock import AsyncMock, MagicMock + +import pytest + +from litellm.integrations import model_deprecation_email as module +from litellm.integrations.email_templates.model_deprecation_email import ( + render_model_deprecation_email, +) +from litellm.models.team import LiteLLM_TeamTable +from litellm.models.user import LiteLLM_UserTable +from litellm.proxy._types import LiteLLM_VerificationToken +from litellm.repositories.config_repository import ConfigParam +from litellm.types.integrations.model_deprecation_email import ( + DeprecationEmailMilestone, + ModelDeprecationEmail, +) +from litellm.types.proxy.model_deprecation import ( + ModelDeprecationInfo, + ModelDeprecationResponse, + SuccessorModelSource, +) + +NOW = datetime(2026, 11, 1, tzinfo=timezone.utc) + + +def info(days=30, model="gemini/gemini-2.5-pro"): + return ModelDeprecationInfo( + model_name="research", + litellm_model=model, + deprecation_date=NOW.date() + timedelta(days=days), + days_until_deprecation=days, + status="imminent", + successor_model="gemini/gemini-3.8-flash", + successor_model_source=SuccessorModelSource.MODEL_COST_MAP, + deprecation_source="https://ai.google.dev/gemini-api/docs/deprecations", + ) + + +class MemoryConfig: + def __init__(self): + self.rows = {"general_settings": {"email_settings": {"Model Deprecations": True}}} + + async def get_param(self, key): + return ConfigParam(key, self.rows[key]) if key in self.rows else None + + async def set_param_if_revision(self, key, value, revision): + current = self.rows.get(key, {}).get("revision", 0) + if current != revision: + return False + self.rows[key] = value + return True + + async def delete_params_older_than(self, prefix, before): + return 0 + + +@pytest.fixture() +def sender(monkeypatch): + monkeypatch.setenv("PROXY_BASE_URL", "https://gateway.example") + instance = module.ModelDeprecationEmailSender(MagicMock()) + instance.config = MemoryConfig() + instance._impacts = AsyncMock( + return_value=MappingProxyType( + {"owner@example.com": module._Impact(key_count=3, requests=12, teams=frozenset({"Research"}))} + ) + ) + send = AsyncMock(return_value=True) + monkeypatch.setattr("litellm.proxy.utils.send_email", send) + return instance, send + + +def schedule(monkeypatch, models): + snapshot = ModelDeprecationResponse( + deprecated=[], imminent=models, upcoming=[], warn_within_days=30, checked_at=NOW + ) + monkeypatch.setattr(module, "collect_model_deprecations", lambda **kwargs: snapshot) + + +@pytest.mark.asyncio +async def test_should_send_only_the_two_milestones_and_keep_receipts_across_restart(sender, monkeypatch): + instance, send = sender + schedule(monkeypatch, [info()]) + assert await instance.run(MagicMock(), now=NOW) == 1 + assert await instance.run(MagicMock(), now=NOW) == 0 + restarted = module.ModelDeprecationEmailSender(MagicMock()) + restarted.config = instance.config + restarted._impacts = instance._impacts + assert await restarted.run(MagicMock(), now=NOW) == 0 + final_day = NOW + timedelta(days=29) + schedule(monkeypatch, [info().model_copy(update={"days_until_deprecation": 1})]) + assert await restarted.run(MagicMock(), now=final_day) == 1 + assert await restarted.run(MagicMock(), now=final_day) == 0 + assert send.await_count == 2 + assert "in 30 days" in send.await_args_list[0].kwargs["subject"] + assert "tomorrow" in send.await_args_list[1].kwargs["subject"] + assert send.await_args_list[0].kwargs["message_id"] != send.await_args_list[1].kwargs["message_id"] + assert "alert("x")', + "deprecation_source": "javascript:alert(1)", + } + ) + email = ModelDeprecationEmail( + model=model, + usage_model=model.litellm_model, + recipient_email="owner@example.com", + milestone=DeprecationEmailMilestone.THIRTY_DAYS, + key_count=3, + requests=12, + team_names=("Research",), + start_date=date(2026, 10, 3), + end_date=NOW.date(), + ) + rendered = render_model_deprecation_email(email, base_url="https://gateway.example") + assert "/public/assets/logos/litellm_logo.png" in rendered.html + assert "litellm-listing.s3.amazonaws.com" not in rendered.html + assert "