diff --git a/.circleci/config.yml b/.circleci/config.yml index 32d2cf0390c..bb4ad0f4019 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -147,6 +147,9 @@ commands: db_name: type: string default: circle_test + image: + type: string + default: postgres:14@sha256:6a70deda415ec296f977890e11aba04a0db9f632a362e3fce45e845e3db74f26 steps: - run: name: Start PostgreSQL @@ -157,7 +160,7 @@ commands: -e POSTGRES_PASSWORD=postgres \ -e POSTGRES_DB=<< parameters.db_name >> \ -p 5432:5432 \ - postgres:14@sha256:6a70deda415ec296f977890e11aba04a0db9f632a362e3fce45e845e3db74f26 + << parameters.image >> - wait_for_service: url: tcp://localhost:5432 timeout: "60" @@ -1084,9 +1087,7 @@ jobs: name: Run tests command: | mkdir -p test-results - TEST_FILES=$(printf "%s\n%s\n" \ - "$(circleci tests glob "tests/ocr_tests/**/test_*.py")" \ - "tests/test_litellm/ocr/test_rust_bridge.py") + TEST_FILES=$(circleci tests glob "tests/ocr_tests/**/test_*.py") echo "$TEST_FILES" | circleci tests run \ --verbose \ --command="tr ' ' '\\n' | awk '/\\.py/ {print; next} {sub(/\\.[A-Z][^.]*$/, \"\"); gsub(/\\./, \"/\"); print \$0 \".py\"}' | xargs uv run --no-sync python -m pytest \ @@ -2914,7 +2915,69 @@ jobs: exit 1 fi + provider_replay_harness: + docker: + - *python312_image + working_directory: ~/project + resource_class: medium + steps: + - setup_litellm_test_deps + - run: + name: Test provider replay harness + command: | + mkdir -p test-results/provider-replay-harness + uv run --no-sync pytest -q --noconftest -o addopts= -o pythonpath=tests/e2e -p no:rerunfailures \ + --junitxml=test-results/provider-replay-harness/junit.xml \ + tests/e2e/test_provider_edge.py tests/e2e/test_fixture_bundle.py \ + tests/e2e/test_fixture_canonical.py tests/e2e/test_fixture_mode.py \ + tests/code_coverage_tests/test_provider_replay_harness.py + - store_test_results: + path: test-results/provider-replay-harness + + integration_contracts: + parameters: + suite: + type: string + machine: + image: ubuntu-2204:2024.04.1 + resource_class: large + working_directory: ~/project + steps: + - setup_litellm_test_deps + - start_postgres: + image: postgres:16@sha256:e17e86066e5ef83e0952a9347f5c792b7ece00972e2aa787a6986f471b3dd3d5 + - start_redis + - run: + name: Run owned integration contracts + command: bash .circleci/scripts/run_integration.sh << parameters.suite >> + no_output_timeout: 15m + - run: + name: Stop owned database and Redis + when: always + command: | + mkdir -p test-results/integration-<< parameters.suite >> + docker logs postgres-db > test-results/integration-<< parameters.suite >>/postgres.log 2>&1 || true + docker logs redis-cache > test-results/integration-<< parameters.suite >>/redis.log 2>&1 || true + docker rm -f postgres-db redis-cache + test -z "$(docker ps -aq --filter name=postgres-db --filter name=redis-cache)" + - store_test_results: + path: test-results + - store_artifacts: + path: test-results + workflows: + integration: + jobs: + - integration_contracts: + name: integration-<< matrix.suite >> + matrix: + parameters: + suite: [management, accounting, providers] + filters: + branches: + only: + - main + - /litellm_.*/ build_and_test: jobs: - using_litellm_on_windows: @@ -2923,6 +2986,7 @@ workflows: only: - main - /litellm_.*/ + - provider_replay_harness - base_sdk_install: filters: *main_branches - local_testing_part1: diff --git a/.circleci/scripts/run_integration.sh b/.circleci/scripts/run_integration.sh new file mode 100644 index 00000000000..9fd2e7c32df --- /dev/null +++ b/.circleci/scripts/run_integration.sh @@ -0,0 +1,142 @@ +#!/usr/bin/env bash +set -euo pipefail + +suite="${1:?integration suite required}" +results="test-results/integration-${suite}" +mkdir -p "$results" +integration_identity="$(.venv/bin/python -c 'import uuid; print(uuid.uuid4().hex)')" +upstream_pid="" +proxy_pid="" +peer_pid="" +launched_pid="" +guard_created=false +guard_installed=false +guard6_created=false +guard6_installed=false +cleanup() { + original_status=$? + trap - EXIT INT TERM + sudo .venv/bin/python .circleci/scripts/stop_integration_processes.py \ + "$integration_identity" "$(id -u)" "$proxy_pid" "$peer_pid" "$upstream_pid" \ + > "$results/process-cleanup.txt" 2>&1 || original_status=1 + for owned_pid in "$peer_pid" "$proxy_pid" "$upstream_pid"; do + if [ -n "$owned_pid" ]; then + kill -- "-$owned_pid" 2>/dev/null || true + for _ in {1..50}; do + kill -0 -- "-$owned_pid" 2>/dev/null || break + sleep 0.1 + done + if kill -0 -- "-$owned_pid" 2>/dev/null; then + kill -KILL -- "-$owned_pid" 2>/dev/null || true + original_status=1 + fi + wait "$owned_pid" 2>/dev/null || true + fi + done + if [ "$guard_installed" = true ]; then + sudo iptables -D OUTPUT -m owner --uid-owner "$(id -u)" -j integration_only || original_status=1 + fi + if [ "$guard_created" = true ]; then + sudo iptables -F integration_only || original_status=1 + sudo iptables -X integration_only || original_status=1 + fi + if [ "$guard6_installed" = true ]; then + sudo ip6tables -D OUTPUT -m owner --uid-owner "$(id -u)" -j integration_only || original_status=1 + fi + if [ "$guard6_created" = true ]; then + sudo ip6tables -F integration_only || original_status=1 + sudo ip6tables -X integration_only || original_status=1 + fi + printf '%s\n' "$original_status" > "$results/exit-status.txt" + exit "$original_status" +} +trap cleanup EXIT +trap 'exit 130' INT +trap 'exit 143' TERM + +export PATH="$PWD/.venv/bin:$PATH" +export PYTHONPATH="$PWD:$PWD/tests:$PWD/tests/e2e" +export DATABASE_URL="postgresql://postgres:postgres@127.0.0.1:5432/circle_test" +export REDIS_HOST=127.0.0.1 REDIS_PORT=6379 +export LITELLM_MASTER_KEY=sk-integration-master LITELLM_SALT_KEY=sk-integration-salt +export LITELLM_MODE=PRODUCTION LITELLM_LOCAL_MODEL_COST_MAP=True +export STORE_MODEL_IN_DB=True AWS_EC2_METADATA_DISABLED=true DO_NOT_TRACK=1 +export INTEGRATION_PROXY_URL=http://127.0.0.1:4000 +export INTEGRATION_PEER_URL="" +export INTEGRATION_UPSTREAM_URL=http://127.0.0.1:8190 +export INTEGRATION_MASTER_KEY="$LITELLM_MASTER_KEY" +export INTEGRATION_SEED="$((16#$(git rev-parse --short=8 HEAD)))" + +uv run --no-sync prisma generate --schema litellm/proxy/schema.prisma > "$results/prisma-generate.log" 2>&1 + +sudo iptables -N integration_only +guard_created=true +sudo iptables -A integration_only -o lo -j ACCEPT +sudo iptables -A integration_only -m conntrack --ctstate ESTABLISHED,RELATED -j ACCEPT +for service in postgres-db redis-cache; do + address="$(docker inspect --format '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' "$service")" + sudo iptables -A integration_only -d "$address" -j ACCEPT +done +sudo iptables -A integration_only -j REJECT +sudo iptables -I OUTPUT 1 -m owner --uid-owner "$(id -u)" -j integration_only +guard_installed=true +sudo ip6tables -N integration_only +guard6_created=true +sudo ip6tables -A integration_only -o lo -j ACCEPT +sudo ip6tables -A integration_only -j REJECT +sudo ip6tables -I OUTPUT 1 -m owner --uid-owner "$(id -u)" -j integration_only +guard6_installed=true + +if curl --noproxy '*' --connect-timeout 2 -s http://198.51.100.1 >/dev/null 2>&1; then + echo "Unexpected outbound network access" >&2 + exit 1 +fi +sudo iptables -L integration_only -n -v -x > "$results/egress-guard.txt" +awk '$3 == "REJECT" && $1 > 0 { rejected=1 } END { exit !rejected }' "$results/egress-guard.txt" + +setsid env -i PATH="$PATH" HOME="$HOME" PYTHONPATH="$PYTHONPATH" INTEGRATION_RUN_ID="$integration_identity" \ + .venv/bin/python -m integration._support.upstream > "$results/upstream.log" 2>&1 & +upstream_pid=$! +start_proxy() { + local port="$1" + local log_name="$2" + setsid env -i PATH="$PATH" HOME="$HOME" PYTHONPATH="$PYTHONPATH" INTEGRATION_RUN_ID="$integration_identity" \ + DATABASE_URL="$DATABASE_URL" REDIS_HOST="$REDIS_HOST" REDIS_PORT="$REDIS_PORT" \ + LITELLM_MASTER_KEY="$LITELLM_MASTER_KEY" LITELLM_SALT_KEY="$LITELLM_SALT_KEY" \ + LITELLM_MODE=PRODUCTION LITELLM_LOCAL_MODEL_COST_MAP=True STORE_MODEL_IN_DB=True \ + AWS_EC2_METADATA_DISABLED=true DO_NOT_TRACK=1 \ + .venv/bin/python -m integration._support.proxy --config tests/integration/proxy_config.yaml \ + --host 127.0.0.1 --port "$port" --num_workers 1 --telemetry False \ + --use_prisma_db_push --enforce_prisma_migration_check \ + > "$results/$log_name" 2>&1 & + launched_pid=$! +} +start_proxy 4000 proxy.log +proxy_pid="$launched_pid" +.venv/bin/python .circleci/scripts/wait_integration_services.py +if [ "$suite" = management ]; then + export INTEGRATION_PEER_URL=http://127.0.0.1:4001 + start_proxy 4001 peer.log + peer_pid="$launched_pid" + .venv/bin/python .circleci/scripts/wait_integration_services.py +fi + +if [ "$suite" = providers ]; then + INTEGRATION_RUN_ID="$integration_identity" .venv/bin/python -m pytest --noconftest -o addopts= \ + --strict-markers --strict-config -p no:pytest-retry -p no:rerunfailures --timeout=30 \ + tests/e2e/test_provider_edge.py::TestReplayMode::test_content_drift_returns_the_miss_status_naming_both_keys \ + tests/e2e/test_provider_edge.py::TestReplayMode::test_exhausted_key_returns_the_miss_status \ + tests/e2e/test_provider_edge.py::TestReplayLeftover::test_partially_consumed_recording_names_the_leftover \ + tests/e2e/test_provider_edge.py::TestStreamingFidelity::test_replay_of_a_stream_makes_no_provider_connection \ + --junitxml="$results/replay-controls.xml" +fi + +timeout --signal=TERM --kill-after=20s 11m env -i PATH="$PATH" HOME="$HOME" PYTHONPATH="$PYTHONPATH" \ + INTEGRATION_RUN_ID="$integration_identity" \ + DATABASE_URL="$DATABASE_URL" REDIS_HOST="$REDIS_HOST" REDIS_PORT="$REDIS_PORT" \ + INTEGRATION_PROXY_URL="$INTEGRATION_PROXY_URL" INTEGRATION_PEER_URL="$INTEGRATION_PEER_URL" \ + INTEGRATION_UPSTREAM_URL="$INTEGRATION_UPSTREAM_URL" \ + INTEGRATION_MASTER_KEY="$INTEGRATION_MASTER_KEY" LITELLM_MODE=PRODUCTION \ + INTEGRATION_SEED="$INTEGRATION_SEED" \ + LITELLM_LOCAL_MODEL_COST_MAP=True AWS_EC2_METADATA_DISABLED=true DO_NOT_TRACK=1 \ + .venv/bin/python tests/integration/run.py "$suite" --results "$results" diff --git a/.circleci/scripts/stop_integration_processes.py b/.circleci/scripts/stop_integration_processes.py new file mode 100644 index 00000000000..8f11aaaddbd --- /dev/null +++ b/.circleci/scripts/stop_integration_processes.py @@ -0,0 +1,53 @@ +import sys +from typing import Final + +import psutil + + +def is_owned(process: psutil.Process, identity: str, owner_uid: int) -> bool: + try: + return process.uids().real == owner_uid and process.environ().get("INTEGRATION_RUN_ID") == identity + except psutil.NoSuchProcess: + return False + + +def owned_processes(identity: str, owner_uid: int) -> tuple[psutil.Process, ...]: + return tuple(process for process in psutil.process_iter() if is_owned(process, identity, owner_uid)) + + +def main(identity: str, owner_uid: int, root_pids: tuple[int, ...]) -> int: + assert owner_uid > 0, "The integration process owner must be a non-root UID" + owned: Final = owned_processes(identity, owner_uid) + roots: Final = tuple(process for process in owned if process.pid in root_pids) + for process in roots: + try: + process.terminate() + except psutil.NoSuchProcess: + continue + psutil.wait_procs(roots, timeout=30) + residual: Final = owned_processes(identity, owner_uid) + for process in residual: + try: + process.terminate() + except psutil.NoSuchProcess: + continue + psutil.wait_procs(residual, timeout=10) + remaining: Final = owned_processes(identity, owner_uid) + for process in remaining: + try: + process.kill() + except psutil.NoSuchProcess: + continue + psutil.wait_procs(remaining, timeout=2) + survivors: Final = owned_processes(identity, owner_uid) + print( + f"Owned integration processes: {len(owned)}, roots: {len(roots)}, " + f"residual: {len(residual)}, forced: {len(remaining)}, remaining: {len(survivors)}" + ) + for process in remaining: + print(f"Forced cleanup was required for PID {process.pid}") + return 1 if remaining or survivors else 0 + + +if __name__ == "__main__": + raise SystemExit(main(sys.argv[1], int(sys.argv[2]), tuple(int(value) for value in sys.argv[3:] if value))) diff --git a/.circleci/scripts/wait_integration_services.py b/.circleci/scripts/wait_integration_services.py new file mode 100644 index 00000000000..486e37cba00 --- /dev/null +++ b/.circleci/scripts/wait_integration_services.py @@ -0,0 +1,43 @@ +import os +import time +from typing import Final + +import httpx +from redis import Redis + + +def main() -> None: + primary: Final = os.environ["INTEGRATION_PROXY_URL"] + peer: Final = os.environ.get("INTEGRATION_PEER_URL") + proxies: Final = (primary, peer) if peer else (primary,) + deadline: Final = time.monotonic() + 90 + headers: Final = {"Authorization": f"Bearer {os.environ['INTEGRATION_MASTER_KEY']}"} + with httpx.Client(trust_env=False, timeout=2) as client, Redis( + host=os.environ["REDIS_HOST"], port=int(os.environ["REDIS_PORT"]), socket_timeout=2 + ) as cache: + while True: + try: + ready: Final = ( + client.get(f"{os.environ['INTEGRATION_UPSTREAM_URL']}/health").status_code == 200 + and all(client.get(f"{url}/health/readiness").status_code == 200 for url in proxies) + ) + if ready: + for url in proxies: + response: Final = client.get(f"{url}/cache/ping", headers=headers) + response.raise_for_status() + result: Final = response.json() + assert result["status"] == "healthy", result + assert result["cache_type"] == "redis", result + assert result["ping_response"] is True, result + assert result["set_cache_response"] == "success", result + if cache.pubsub_numsub("litellm_proxy.auth_cache_invalidation")[0][1] >= len(proxies): + return + except httpx.TransportError: + pass + if time.monotonic() >= deadline: + raise SystemExit("Integration services or auth-cache subscribers did not become ready") + time.sleep(0.2) + + +if __name__ == "__main__": + main() diff --git a/.github/codeql/codeql-config.yml b/.github/codeql/codeql-config.yml index 36d70c1d746..6e15c1069a3 100644 --- a/.github/codeql/codeql-config.yml +++ b/.github/codeql/codeql-config.yml @@ -14,6 +14,17 @@ query-filters: id: py/clear-text-logging-sensitive-data # CWE-312 - exclude: id: py/polynomial-redos # CWE-730 + # Import resolution confuses stdlib types with management_endpoints/types.py. + # The generic cycle query also reports intentional deferred imports. + - exclude: + id: py/cyclic-import + - exclude: + id: py/unsafe-cyclic-import + # Known false positives on live settings and Protocol placeholders. + - exclude: + id: py/unused-global-variable + - exclude: + id: py/ineffectual-statement paths-ignore: - tests diff --git a/.github/e2e-stack/assert_tests_ran.py b/.github/e2e-stack/assert_tests_ran.py index c4348c20873..2303c42f4fb 100644 --- a/.github/e2e-stack/assert_tests_ran.py +++ b/.github/e2e-stack/assert_tests_ran.py @@ -3,6 +3,9 @@ import xml.etree.ElementTree as ET from pathlib import Path from typing import Final +sys.path.insert(0, str(Path(__file__).resolve().parents[2] / "tests/e2e")) +from coverage_registry.management_cases import MANAGEMENT_CASES + def main() -> int: selected: Final = tuple(sys.argv[2:]) @@ -16,6 +19,17 @@ def main() -> int: case.get("file") for case in cases if all(case.find(tag) is None for tag in ("skipped", "failure", "error")) ) missing: Final = tuple(path for path in selected if path not in passed) + required_nodes: Final = frozenset(case.node for case in MANAGEMENT_CASES if case.node.split("::", 1)[0] in selected) + passed_nodes: Final = frozenset( + prop.get("value") + for case in cases + if all(case.find(tag) is None for tag in ("skipped", "failure", "error")) + for prop in case.findall("./properties/property") + if prop.get("name") == "management_node" + ) + missing_nodes: Final = required_nodes - passed_nodes + for node in sorted(missing_nodes): + _ = sys.stdout.write(f"::error::required management case did not pass: {node}\n") for path in selected: collected: Final = sum(case.get("file") == path for case in cases) skipped: Final = sum(case.get("file") == path and case.find("skipped") is not None for case in cases) @@ -27,6 +41,7 @@ def main() -> int: if ( selected and not missing + and not missing_nodes and not any(case.find(tag) is not None for case in cases for tag in ("failure", "error")) ): return 0 diff --git a/.github/e2e-stack/oidc-profile.sh b/.github/e2e-stack/oidc-profile.sh new file mode 100755 index 00000000000..84eaaaf8051 --- /dev/null +++ b/.github/e2e-stack/oidc-profile.sh @@ -0,0 +1,5 @@ +#!/usr/bin/env bash +set -euo pipefail +REPO_ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/../.." && pwd)" +cd "${REPO_ROOT}" +exec uv run --no-sync python tests/e2e/idp.py "$@" diff --git a/.github/e2e-stack/select_tests.py b/.github/e2e-stack/select_tests.py index 238818a0d36..982e93cf642 100644 --- a/.github/e2e-stack/select_tests.py +++ b/.github/e2e-stack/select_tests.py @@ -12,6 +12,8 @@ UNSUPPORTED: Final = re.compile( HARNESS: Final = re.compile( r"^tests/e2e/[A-Za-z0-9_.-]+\.(py|ini)$" r"|^tests/e2e/idp_realm\.json$" + r"|^tests/e2e/management/(management_client|jwt_actors|conftest)\.py$" + r"|^tests/e2e/coverage_registry/management_cases\.py$" r"|^tests/e2e/gateway/" r"|^\.github/e2e-stack/" r"|^\.github/workflows/test-e2e-changed\.yml$" diff --git a/.github/pull_request_template.md b/.github/pull_request_template.md index 1a2c81d1f92..2dc85fce05b 100644 --- a/.github/pull_request_template.md +++ b/.github/pull_request_template.md @@ -47,6 +47,10 @@ After: the same request comes back with real token counts, so the dashboard show +## Affected release + + + ## Linear ticket @@ -154,3 +158,4 @@ Example checklists: ## Final Attestation - [ ] The tests check the right things, including the edge cases, and regressions in the respective real-world customer use-cases are not possible after this PR + diff --git a/.github/scripts/assert_ci_coverage.py b/.github/scripts/assert_ci_coverage.py index 411852acb98..4c66ab251de 100644 --- a/.github/scripts/assert_ci_coverage.py +++ b/.github/scripts/assert_ci_coverage.py @@ -1,6 +1,7 @@ from __future__ import annotations import ast +import json import operator import pathlib import re @@ -498,6 +499,69 @@ def _check_shards() -> int: return 0 +def _integration_ownership(repo_root: pathlib.Path = REPO_ROOT) -> tuple[frozenset[str], tuple[Finding, ...]]: + manifest: Final = repo_root / "tests/integration/contracts.json" + if not manifest.exists(): + return frozenset(), () + entries: Final = json.loads(manifest.read_text()) + paths: Final = frozenset(node.split("::", 1)[0] for node in entries["tests"]) + circle_path: Final = repo_root / ".circleci/config.yml" + circle: Final = yaml.safe_load(circle_path.read_text()) if circle_path.exists() else {} + steps: Final = circle.get("jobs", {}).get("integration_contracts", {}).get("steps", ()) + invoked: Final = any( + ".circleci/scripts/run_integration.sh" in scalar.value + for scalar in _scalars(steps, "integration_contracts") + if scalar.key == "command" + ) + scheduled: Final = frozenset( + suite + for job in circle.get("workflows", {}).get("integration", {}).get("jobs", ()) + if isinstance(job, dict) and "integration_contracts" in job + for suite in job["integration_contracts"] + .get("matrix", {}) + .get("parameters", {}) + .get("suite", (job["integration_contracts"].get("suite"),)) + if isinstance(suite, str) + ) + required: Final = frozenset( + group + for group, folders in entries["groups"].items() + if any(any(path.startswith(f"tests/integration/{folder}/") for folder in folders) for path in paths) + ) + ungrouped: Final = frozenset( + path + for path in paths + if sum( + any(path.startswith(f"tests/integration/{folder}/") for folder in folders) + for folders in entries["groups"].values() + ) + != 1 + ) + gha_tokens: Final = _invoked_test_tokens( + scalar + for path in (repo_root / ".github/workflows").glob("*.y*ml") + for scalar in _scalars(yaml.safe_load(path.read_text()), path.name) + ) + findings: Final = tuple( + Finding(path, "integration contract is also selected by GitHub Actions") + for path in paths + if any(_token_covers(token, path) for token in gha_tokens) + ) + tuple( + Finding(path, "canonical integration test file is missing") + for path in paths + if not (repo_root / path).is_file() + ) + group_findings: Final = tuple( + Finding(group, "canonical integration group is not scheduled by CircleCI") + for group in sorted(required - scheduled) + ) + tuple(Finding(path, "canonical node must have exactly one integration group") for path in sorted(ungrouped)) + if not paths or not invoked or not scheduled: + return frozenset(), findings + ( + Finding(str(manifest.relative_to(repo_root)), "dedicated CircleCI runner is missing"), + ) + return paths, findings + group_findings + + def main() -> int: if "--shards" in sys.argv[1:]: return _check_shards() @@ -507,7 +571,8 @@ def main() -> int: allowlist = _load_allowlist() scalars = _all_scalars() - test_findings = _uncovered_tests(allowlist, _invoked_test_tokens(scalars)) + integration_paths, ownership_findings = _integration_ownership() + test_findings = _uncovered_tests(allowlist, _invoked_test_tokens(scalars) | integration_paths) + ownership_findings dockerfile_findings = _uncovered_dockerfiles(allowlist, _built_dockerfile_tokens(scalars)) stale_findings = _stale_allowlist_paths(allowlist, test_files=_test_files(), dockerfiles=_dockerfiles()) diff --git a/.github/scripts/auto_update_price_and_context_window_file.py b/.github/scripts/auto_update_price_and_context_window_file.py index 461d8d347d9..4c9a05bd4f0 100644 --- a/.github/scripts/auto_update_price_and_context_window_file.py +++ b/.github/scripts/auto_update_price_and_context_window_file.py @@ -1,6 +1,8 @@ import asyncio import aiohttp import json +import math +from typing import Any # Asynchronously fetch data from a given URL async def fetch_data(url): @@ -21,11 +23,157 @@ async def fetch_data(url): print("Error fetching data from URL:", e) return None + +FRIENDLI_API_URL = "https://api.friendli.ai/serverless/v1/models" +FRIENDLI_PROVIDER = "friendliai" + +INHERITABLE_BASE_KEYS = ( + "supports_pdf_input", + "supports_assistant_prefill", + "supports_adaptive_thinking", + "supports_output_config", +) + +REASONING_EFFORT_LEVEL_ORDER = ("none", "minimal", "low", "medium", "high", "xhigh", "max") + + +def _find_base_model_entry(base_model: str, local_data: dict) -> str | None: + if not base_model: + return None + bm_tail = base_model.split("/")[-1].lower() + if base_model in local_data: + return base_model + for key in local_data: + if key.startswith("sample_spec") or key == "fallback_generalizations": + continue + if key.split("/")[-1].lower() == bm_tail: + return key + return None + + +def _reasoning_effort_levels(reasoning_options: list) -> list: + offered = { + val + for opt in reasoning_options or [] + if opt.get("type") == "effort" + for val in opt.get("values", []) + } + return [level for level in REASONING_EFFORT_LEVEL_ORDER if level in offered] + + +def _valid_token_price(value: object) -> bool: + try: + price = float(value) # pyright: ignore[reportArgumentType] # non-numeric values are rejected via the except + except (TypeError, ValueError): + return False + return math.isfinite(price) and price >= 0 + + +def _has_valid_token_prices(pricing: dict | None) -> bool: + prices = pricing or {} + return _valid_token_price(prices.get("input")) and _valid_token_price(prices.get("output")) + + +def _pricing(pricing: dict) -> dict: + out: dict[str, Any] = {} + if not pricing: + return out + if "input" in pricing: + out["input_cost_per_token"] = float(pricing["input"]) + if "output" in pricing: + out["output_cost_per_token"] = float(pricing["output"]) + if "input_cache_read" in pricing and pricing["input_cache_read"] is not None: + out["cache_read_input_token_cost"] = float(pricing["input_cache_read"]) + return out + + +def _modality_flags(input_mods: list) -> dict: + mods = input_mods or [] + has_image = "image" in mods + return { + "supports_vision": has_image, + "supports_image_input": has_image, + "supports_video_input": "video" in mods, + } + + +def transform_friendli_data(data: list, local_data: dict) -> dict: + transformed: dict[str, dict] = {} + if not data: + return transformed + for model in data: + # An unpriced row must never wholesale-replace an already priced local entry: + # missing prices cost-calculate as zero, silently zeroing tracked spend + if not _has_valid_token_prices(model.get("pricing")): + continue + model_id = model["id"] + base_model = model.get("base_model") or "" + entry: dict[str, Any] = { + "litellm_provider": FRIENDLI_PROVIDER, + } + + base_key = _find_base_model_entry(base_model, local_data) + if base_key: + base_entry = local_data[base_key] + for k in INHERITABLE_BASE_KEYS: + if k in base_entry: + entry[k] = base_entry[k] + + ctx = model.get("context_length") + if ctx is not None: + entry["max_input_tokens"] = int(ctx) + max_out = model.get("max_completion_tokens") + if max_out is not None: + entry["max_output_tokens"] = int(max_out) + entry["max_tokens"] = int(max_out) + + pricing = _pricing(model.get("pricing", {})) + entry.update(pricing) + entry["supports_prompt_caching"] = "cache_read_input_token_cost" in pricing + + reasoning = model.get("reasoning") is True + entry["supports_reasoning"] = reasoning + if reasoning: + entry["reasoning_effort_levels"] = _reasoning_effort_levels( + model.get("reasoning_options", []) + ) + + func = model.get("functionality", {}) + entry["supports_function_calling"] = func.get("tool_call") is True + entry["supports_parallel_function_calling"] = func.get("parallel_tool_call") is True + is_struct = func.get("structured_output") is True + entry["supports_response_schema"] = is_struct + entry["supports_native_structured_output"] = is_struct + entry["supports_system_messages"] = func.get("system_messages") is True + entry["supports_tool_choice"] = func.get("tool_choice") is True + + entry.update(_modality_flags(model.get("input_modalities", []))) + + entry["mode"] = model.get("mode", "chat") + + desc = model.get("description") + if desc: + entry["comment"] = desc + + dep = model.get("deprecation_date") + if dep: + entry["deprecation_date"] = dep.split("T")[0] + + entry["source"] = FRIENDLI_API_URL + + transformed[f"{FRIENDLI_PROVIDER}/{model_id}"] = entry + return transformed + # Synchronize local data with remote data -def sync_local_data_with_remote(local_data, remote_data): +def sync_local_data_with_remote(local_data, remote_data, replace_keys=frozenset()): # Update existing keys in local_data with values from remote_data + # (replace_keys entries are swapped wholesale so a field the remote catalog + # dropped, e.g. cache pricing, cannot survive as a stale value) for key in (set(local_data) & set(remote_data)): - local_data[key].update(remote_data[key]) + if key in replace_keys: + local_data[key] = remote_data[key] + else: + local_data[key].update(remote_data[key]) # Add new keys from remote_data to local_data for key in (set(remote_data) - set(local_data)): @@ -46,6 +194,8 @@ def write_to_file(file_path, data): # Update the existing models and add the missing models for OpenRouter def transform_openrouter_data(data): transformed = {} + if not data: + return transformed for row in data: # Add the fields 'max_tokens' and 'input_cost_per_token' obj = { @@ -84,7 +234,14 @@ def transform_openrouter_data(data): # Update the existing models and add the missing models for Vercel AI Gateway def transform_vercel_ai_gateway_data(data): transformed = {} + if not data: + return transformed for row in data: + # Rows without token pricing or token limits (video/embedding models) previously KeyError'd the whole sync + if any(row.get(k) is None for k in ("context_window", "max_tokens")) or any( + row.get("pricing", {}).get(k) is None for k in ("input", "output") + ): + continue obj = { "max_tokens": row["context_window"], "input_cost_per_token": float(row["pricing"]["input"]), @@ -143,13 +300,16 @@ def main(): vercel_data = asyncio.run(fetch_data(vercel_ai_gateway_url)) # Transform the fetched Vercel AI Gateway data vercel_data = transform_vercel_ai_gateway_data(vercel_data) + + friendli_data = asyncio.run(fetch_data(FRIENDLI_API_URL)) + friendli_data = transform_friendli_data(friendli_data, local_data) # Combine both datasets - all_remote_data = {**openrouter_data, **vercel_data} + all_remote_data = {**openrouter_data, **vercel_data, **friendli_data} # If both local and openrouter data are available, synchronize and save if local_data and all_remote_data: - sync_local_data_with_remote(local_data, all_remote_data) + sync_local_data_with_remote(local_data, all_remote_data, replace_keys=frozenset(friendli_data)) write_to_file(local_file_path, local_data) else: print("Failed to fetch model data from either local file or URL.") diff --git a/.github/workflows/_test-unit-base.yml b/.github/workflows/_test-unit-base.yml index 62790e23143..bbf0cb4e891 100644 --- a/.github/workflows/_test-unit-base.yml +++ b/.github/workflows/_test-unit-base.yml @@ -57,6 +57,7 @@ permissions: env: UV_PYTHON: "3.12" + LITELLM_LOCAL_MODEL_COST_MAP: "True" jobs: run: @@ -113,6 +114,7 @@ jobs: if: steps.changes.outputs.decision != 'skip' timeout-minutes: 8 run: | + diff -u model_prices_and_context_window.json litellm/model_prices_and_context_window_backup.json .github/scripts/uv_sync_with_retries.sh --frozen --group ci --group proxy-dev --extra google --extra proxy --extra semantic-router --extra saml 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"]' diff --git a/.github/workflows/guard-main-branch.yml b/.github/workflows/guard-main-branch.yml deleted file mode 100644 index 5bc561c6441..00000000000 --- a/.github/workflows/guard-main-branch.yml +++ /dev/null @@ -1,42 +0,0 @@ -name: Guard main branch - -on: - pull_request: - branches: - - main - merge_group: - -permissions: {} - -# DO NOT RENAME the job's `name:` — it is referenced by GitHub branch -# protection as a required status check on `main`. Renaming silently -# breaks the gate. -jobs: - guard: - name: Verify PR source branch - runs-on: ubuntu-latest - timeout-minutes: 2 - steps: - - name: Reject merge_group events - if: github.event_name == 'merge_group' - run: | - echo "::error::Merge queue is not supported for main. Disable merge queue or update this guard." - exit 1 - - name: Check head branch name - env: - HEAD_REF: ${{ github.head_ref }} - HEAD_REPO: ${{ github.event.pull_request.head.repo.full_name }} - BASE_REPO: ${{ github.repository }} - run: | - echo "PR head repo: $HEAD_REPO" - echo "PR head branch: $HEAD_REF" - if [ "$HEAD_REPO" != "$BASE_REPO" ]; then - echo "::error::PRs to main must originate from the canonical repository ($BASE_REPO), not a fork ($HEAD_REPO). External contributors should open PRs against 'litellm_internal_staging' instead." - exit 1 - fi - if [ "$HEAD_REF" = "litellm_internal_staging" ] || [[ "$HEAD_REF" == litellm_hotfix_?* ]]; then - echo "Allowed source branch." - exit 0 - fi - echo "::error::PRs to main must originate from 'litellm_internal_staging' or a 'litellm_hotfix_*' branch. Got: '$HEAD_REF'. If this is a contribution, retarget the PR against 'litellm_internal_staging' instead." - exit 1 diff --git a/.github/workflows/test-code-quality.yml b/.github/workflows/test-code-quality.yml index 9c7e0db7065..987f66773f2 100644 --- a/.github/workflows/test-code-quality.yml +++ b/.github/workflows/test-code-quality.yml @@ -178,7 +178,7 @@ jobs: version: "0.10.9" - name: Install dependencies - run: uv sync --frozen --extra proxy --python 3.10 + run: uv sync --frozen --extra proxy --extra cli --python 3.10 - run: uv run --no-sync python --version @@ -187,3 +187,6 @@ jobs: - name: Check litellm CLI run: uv run --no-sync litellm --version + + - name: Check lite CLI + run: uv run --no-sync lite version diff --git a/.github/workflows/test-e2e-changed.yml b/.github/workflows/test-e2e-changed.yml index 1db597ff673..c9f08deb36e 100644 --- a/.github/workflows/test-e2e-changed.yml +++ b/.github/workflows/test-e2e-changed.yml @@ -183,7 +183,7 @@ jobs: log="${RUNNER_TEMP}/e2e-pass-${pass}.log" echo "::group::pass ${pass} of 3" set +e - uv run --no-sync pytest "${test_files[@]}" --rootdir=. -v -p no:cacheprovider \ + uv run --no-sync pytest "${test_files[@]}" --rootdir=. -v --reruns 0 -p no:cacheprovider \ -o junit_family=xunit1 --junitxml="${report}" > "${log}" 2>&1 status=$? uv run --no-sync python .github/e2e-stack/assert_tests_ran.py "${report}" "${test_files[@]}" diff --git a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py index c7e1b94a2ef..4899b87da7a 100644 --- a/enterprise/litellm_enterprise/proxy/hooks/managed_files.py +++ b/enterprise/litellm_enterprise/proxy/hooks/managed_files.py @@ -27,10 +27,13 @@ import litellm from litellm import Router, verbose_logger from litellm._uuid import uuid from litellm.caching.caching import DualCache +from litellm.constants import MAX_FILE_LIST_LIMIT from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.prompt_templates.common_utils import ( extract_file_metadata, ) +from openai.types.file_deleted import FileDeleted + from litellm.llms.base_llm.files.transformation import BaseFileEndpoints from litellm.llms.base_llm.managed_resources.isolation import ( build_list_page, @@ -48,7 +51,6 @@ from litellm.proxy._types import ( from litellm.proxy.openai_files_endpoints.common_utils import ( BATCH_CREATE_HIDDEN_PARAM, FILE_LIST_CONTINUATION_CHUNK_SIZE, - MAX_FILE_LIST_LIMIT, _is_base64_encoded_unified_file_id, apply_unified_file_ids, decode_model_from_file_id, @@ -1787,7 +1789,7 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): litellm_parent_otel_span: Optional[Span], llm_router: Router, **data: Dict, - ) -> OpenAIFileObject: + ) -> FileDeleted: # Check if file deletion should be blocked due to batch references await self._check_file_deletion_allowed(file_id) @@ -1795,7 +1797,6 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): # file_id = convert_b64_uid_to_unified_uid(file_id) model_file_id_mapping = await self.get_model_file_id_mapping([file_id], litellm_parent_otel_span) - delete_response = None specific_model_file_id_mapping = model_file_id_mapping.get(file_id) if specific_model_file_id_mapping: # Remove conflicting keys from data to avoid duplicate keyword arguments @@ -1810,23 +1811,14 @@ class _PROXY_LiteLLMManagedFiles(CustomLogger, BaseFileEndpoints): else {} ), } - delete_response = await llm_router.afile_delete(model=model_id, file_id=model_file_id, **delete_data) + await llm_router.afile_delete(model=model_id, file_id=model_file_id, **delete_data) - stored_file_object = await self.delete_unified_file_id(file_id, litellm_parent_otel_span) + await self.delete_unified_file_id(file_id, litellm_parent_otel_span) - # Record successful deletion metric only on actual success - if stored_file_object or delete_response: - prom_logger = self._get_prometheus_logger() - if prom_logger: - prom_logger.record_managed_file_deleted(result="success") - - if stored_file_object: - return OpenAIFileObject.model_validate(stored_file_object).model_copy(update={"id": file_id}) - elif delete_response: - delete_response.id = file_id - return delete_response - else: - raise Exception(f"LiteLLM Managed File object with id={file_id} not found") + prom_logger = self._get_prometheus_logger() + if prom_logger: + prom_logger.record_managed_file_deleted(result="success") + return FileDeleted(id=file_id, object="file", deleted=True) async def afile_content( self, diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260831120000_add_litellm_call_id_spend_logs/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260831120000_add_litellm_call_id_spend_logs/migration.sql new file mode 100644 index 00000000000..3bf6b819715 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260831120000_add_litellm_call_id_spend_logs/migration.sql @@ -0,0 +1,2 @@ +-- AlterTable +ALTER TABLE "LiteLLM_SpendLogs" ADD COLUMN IF NOT EXISTS "litellm_call_id" TEXT; diff --git a/litellm-proxy-extras/litellm_proxy_extras/migrations/20260831120001_spend_logs_litellm_call_id_index/migration.sql b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260831120001_spend_logs_litellm_call_id_index/migration.sql new file mode 100644 index 00000000000..62ad5c42ba7 --- /dev/null +++ b/litellm-proxy-extras/litellm_proxy_extras/migrations/20260831120001_spend_logs_litellm_call_id_index/migration.sql @@ -0,0 +1,12 @@ +-- CreateIndex (CONCURRENTLY) +-- +-- Disclaimer: +-- - CREATE INDEX CONCURRENTLY cannot run inside a transaction. This migration must stay a +-- single statement so Prisma Migrate on PostgreSQL can apply it outside a transaction. +-- - Builds are slower and use more I/O than a blocking CREATE INDEX; if the build is +-- interrupted, Postgres may leave an INVALID index that must be dropped and recreated. +-- - Do not edit this file after it has been applied to any database: Prisma checksums +-- migrations; add a new migration instead. +-- - Requires PostgreSQL that supports CONCURRENTLY with IF NOT EXISTS (use a new migration +-- without IF NOT EXISTS if you must support older versions). +CREATE INDEX CONCURRENTLY IF NOT EXISTS "LiteLLM_SpendLogs_litellm_call_id_idx" ON "LiteLLM_SpendLogs"("litellm_call_id"); diff --git a/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py b/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py index b51de9609d3..9cd48fcf11a 100644 --- a/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py +++ b/litellm-proxy-extras/litellm_proxy_extras/prisma_toolchain.py @@ -37,11 +37,13 @@ raised it above the deploy default keeps that larger budget for deploy unless the deploy override says otherwise. """ +import importlib.util import math import os import shutil import signal import subprocess +import sys from collections.abc import Mapping, Sequence from dataclasses import dataclass from pathlib import Path @@ -64,6 +66,7 @@ DEFAULT_PRISMA_BOOTSTRAP_TIMEOUT = 600.0 DEFAULT_PRISMA_MIGRATE_DEPLOY_TIMEOUT = 600.0 BOOTSTRAP_ARG = "--version" +PRISMA_CONSOLE_SCRIPT = "prisma" @dataclass(frozen=True) @@ -184,6 +187,28 @@ def _kill_process_group(process: "subprocess.Popen[str]") -> None: return +def prisma_cli_available() -> bool: + """Whether some way of running the Prisma CLI exists: the console script on PATH or the importable package.""" + if shutil.which(PRISMA_CONSOLE_SCRIPT) is not None: + return True + return importlib.util.find_spec(PRISMA_CONSOLE_SCRIPT) is not None + + +def resolve_prisma_argv(argv: Sequence[str]) -> tuple[str, ...]: + """Route a bare ``prisma`` command through ``python -m prisma`` when the console script is not on PATH. + + The console script and ``python -m prisma`` are the same entry point, but + only the module form survives an interpreter whose ``bin`` directory is + missing from PATH, which is how the proxy gets started under launchers and + init systems. Any other executable name is left untouched. + """ + if not argv or argv[0] != PRISMA_CONSOLE_SCRIPT: + return tuple(argv) + if shutil.which(PRISMA_CONSOLE_SCRIPT) is not None: + return tuple(argv) + return (sys.executable, "-m", PRISMA_CONSOLE_SCRIPT, *argv[1:]) + + def run_prisma( argv: Sequence[str], *, @@ -200,7 +225,7 @@ def run_prisma( text unless ``stdout``/``stderr`` say otherwise. """ with subprocess.Popen( - argv, + resolve_prisma_argv(argv), env=env, stdout=stdout, stderr=stderr, diff --git a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma index 7d521d54791..dd7967aafe3 100644 --- a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma +++ b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma @@ -659,12 +659,14 @@ model LiteLLM_SpendLogs { mcp_namespaced_tool_name String? agent_id String? proxy_server_request Json? @default("{}") + litellm_call_id String? created_at DateTime @default(now()) @map("created_at") updated_at DateTime @default(now()) @updatedAt @map("updated_at") @@index([startTime]) @@index([startTime, request_id]) @@index([end_user]) @@index([session_id]) + @@index([litellm_call_id]) } model LiteLLM_BudgetWindowSpend { diff --git a/litellm-rust/crates/ai-gateway/src/bin/trace_parity_gateway.rs b/litellm-rust/crates/ai-gateway/src/bin/trace_parity_gateway.rs index 9036deb9871..e247c650fad 100644 --- a/litellm-rust/crates/ai-gateway/src/bin/trace_parity_gateway.rs +++ b/litellm-rust/crates/ai-gateway/src/bin/trace_parity_gateway.rs @@ -5,6 +5,7 @@ use serde_json::Value; #[derive(Deserialize)] struct Input { + path: String, model_alias: String, provider_model: String, api_base: String, @@ -21,7 +22,8 @@ async fn main() { Ok(input) => input, Err(error) => fail(error), }; - let result = litellm_ai_gateway::trace_parity::traced_messages_request( + let result = litellm_ai_gateway::trace_parity::traced_request( + input.path, input.model_alias, input.provider_model, input.api_base, diff --git a/litellm-rust/crates/ai-gateway/src/trace_parity.rs b/litellm-rust/crates/ai-gateway/src/trace_parity.rs index 00c9b53e691..7540a71fb12 100644 --- a/litellm-rust/crates/ai-gateway/src/trace_parity.rs +++ b/litellm-rust/crates/ai-gateway/src/trace_parity.rs @@ -29,14 +29,15 @@ pub struct TracedGatewayResponse { pub trace: Vec, } -pub async fn traced_messages_request( +pub async fn traced_request( + path: String, model_alias: String, provider_model: String, api_base: String, body: Value, ) -> TracedGatewayResponse { let trace = litellm_core::observability::FunctionTrace::default(); - let result = messages_request(model_alias, provider_model, api_base, body) + let result = request(path, model_alias, provider_model, api_base, body) .with_subscriber(trace.dispatcher()) .await; let events = trace.events(); @@ -54,7 +55,8 @@ pub async fn traced_messages_request( } } -pub async fn messages_request( +pub async fn request( + path: String, model_alias: String, provider_model: String, api_base: String, @@ -75,7 +77,7 @@ pub async fn messages_request( }; let request = Request::builder() .method("POST") - .uri("/v1/messages") + .uri(path) .header(AUTHORIZATION, "Bearer trace-master-key") .header(CONTENT_TYPE, "application/json") .body(Body::from(body.to_string())) diff --git a/litellm-rust/crates/python-bridge/src/routes/ocr/callbacks.rs b/litellm-rust/crates/python-bridge/src/routes/ocr/callbacks.rs index 1cbe8a179e3..c7e5f123c19 100644 --- a/litellm-rust/crates/python-bridge/src/routes/ocr/callbacks.rs +++ b/litellm-rust/crates/python-bridge/src/routes/ocr/callbacks.rs @@ -58,6 +58,13 @@ impl PythonLogger { params.set_item(name, value)?; } } + for name in custom_pricing_fields(py)? { + if let Some(value) = kwargs.bind(py).get_item(&name)? + && !value.is_none() + { + params.set_item(name, value)?; + } + } update.set_item("litellm_params", params)?; update.set_item("custom_llm_provider", &pre_call.custom_llm_provider)?; self.object(py) @@ -120,6 +127,17 @@ impl PythonLogger { } } +fn custom_pricing_fields(py: Python<'_>) -> PyResult> { + py.import("litellm.types.utils")? + .getattr("CustomPricingLiteLLMParams")? + .getattr("model_fields")? + .cast_into::()? + .keys() + .iter() + .map(|name| name.extract::()) + .collect() +} + fn redact( py: Python<'_>, params: &Bound<'_, PyDict>, diff --git a/litellm/__init__.py b/litellm/__init__.py index 1dfd146a00e..ccfbf80369f 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -501,6 +501,7 @@ disable_copilot_system_to_assistant: bool = False # If false (default), convert public_mcp_servers: Optional[List[str]] = None public_mcp_hub_strict_whitelist: bool = True public_model_groups: Optional[List[str]] = None +public_skills_index: bool = False public_agent_groups: Optional[List[str]] = None agent_search_embedding_model: Optional[str] = None mcp_tool_search: Optional[Mapping[str, object]] = None diff --git a/litellm/_logging.py b/litellm/_logging.py index c73b5175a31..03a9bcf21cf 100644 --- a/litellm/_logging.py +++ b/litellm/_logging.py @@ -1,5 +1,6 @@ import ast import contextvars +import functools import logging import os import sys @@ -225,6 +226,35 @@ class AccessLogRedactionFilter(logging.Filter): _access_log_filter: Final = AccessLogRedactionFilter() +@functools.lru_cache(maxsize=1) +def _parse_disabled_access_log_paths(raw: str) -> frozenset[str]: + return frozenset(stripped for path in raw.split(",") if (stripped := path.strip())) + + +def _disabled_access_log_paths() -> frozenset[str]: + """Read the variable per record so a value loaded later via proxy config + environment_variables or dotenv is honored.""" + return _parse_disabled_access_log_paths(os.getenv("LITELLM_DISABLE_ACCESS_LOG_PATHS", "")) + + +class AccessLogPathFilter(logging.Filter): + """Drops uvicorn.access records for request paths listed in LITELLM_DISABLE_ACCESS_LOG_PATHS. + + uvicorn passes record.args as (client_addr, method, full_path, http_version, status_code). + """ + + def filter(self, record: logging.LogRecord) -> bool: + if not isinstance(record.args, tuple) or len(record.args) < 3: + return True + full_path: Final = record.args[2] + if not isinstance(full_path, str): + return True + return full_path.partition("?")[0] not in _disabled_access_log_paths() + + +_access_log_path_filter: Final = AccessLogPathFilter() + + def _get_max_string_length_stdout_log() -> int: """Read the limit per record so a value loaded later via proxy config environment_variables is honored.""" @@ -663,6 +693,7 @@ def _redact_third_party_loggers() -> None: for name in _REDACTED_THIRD_PARTY_LOGGERS: logging.getLogger(name).addFilter(_secret_filter) for name in _REDACTED_ACCESS_LOGGERS: + logging.getLogger(name).addFilter(_access_log_path_filter) logging.getLogger(name).addFilter(_access_log_filter) diff --git a/litellm/batches/batch_utils.py b/litellm/batches/batch_utils.py index 87f8fd3946e..26b4318da2d 100644 --- a/litellm/batches/batch_utils.py +++ b/litellm/batches/batch_utils.py @@ -9,6 +9,7 @@ import litellm from litellm._logging import verbose_logger 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.vertex_ai.batches.transformation import vertex_prompt_tokens_details from litellm.types.llms.openai import Batch from litellm.types.utils import ModelInfo, Usage from litellm.utils import token_counter @@ -356,6 +357,7 @@ def calculate_vertex_ai_batch_cost_and_usage( prompt_tokens=_prompt, completion_tokens=_completion, total_tokens=_total, + prompt_tokens_details=vertex_prompt_tokens_details(usage_metadata), ) try: diff --git a/litellm/caching/caching.py b/litellm/caching/caching.py index d6dd2a073af..be82f5def1f 100644 --- a/litellm/caching/caching.py +++ b/litellm/caching/caching.py @@ -679,7 +679,14 @@ class Cache: cache_key, cached_data, kwargs = self._add_cache_logic(result=result, **kwargs) self.cache.set_cache(cache_key, cached_data, **kwargs) except Exception as e: - log_redis_failure(verbose_logger, logging.ERROR, "LiteLLM Cache: exception in add_cache", e) + self._log_add_cache_failure(e) + + def _log_add_cache_failure(self, exc: Exception) -> None: + message: Final = "LiteLLM Cache: exception in add_cache" + if isinstance(self.cache, RedisCache): + log_redis_failure(verbose_logger, logging.ERROR, message, exc) + return + verbose_logger.error("%s: %s", message, exc) async def async_add_cache(self, result, dynamic_cache_object: BaseCache | None = None, **kwargs): """ @@ -698,7 +705,7 @@ class Cache: else: await self.cache.async_set_cache(cache_key, cached_data, **kwargs) except Exception as e: - log_redis_failure(verbose_logger, logging.ERROR, "LiteLLM Cache: exception in add_cache", e) + self._log_add_cache_failure(e) def _convert_to_cached_embedding( self, @@ -877,7 +884,7 @@ class Cache: else: await self.cache.async_set_cache_pipeline(cache_list=cache_list, **kwargs) except Exception as e: - log_redis_failure(verbose_logger, logging.ERROR, "LiteLLM Cache: exception in add_cache", e) + self._log_add_cache_failure(e) def should_use_cache(self, **kwargs): """ diff --git a/litellm/caching/redis_cache.py b/litellm/caching/redis_cache.py index 1a024b6b2b0..b4b2b1a334c 100644 --- a/litellm/caching/redis_cache.py +++ b/litellm/caching/redis_cache.py @@ -15,8 +15,9 @@ import hashlib import inspect import json import logging +import threading import time -from collections.abc import Awaitable, Callable, Sequence +from collections.abc import Awaitable, Callable, Iterator, Sequence from contextvars import ContextVar from dataclasses import dataclass from datetime import timedelta @@ -32,6 +33,7 @@ from litellm.constants import ( REDIS_CIRCUIT_BREAKER_FAILURE_THRESHOLD, REDIS_CIRCUIT_BREAKER_RECOVERY_TIMEOUT, REDIS_CIRCUIT_BREAKER_TIMEOUT_MIN_DURATION, + REDIS_TIMEOUT_LOG_INTERVAL, ) from litellm.litellm_core_utils.core_helpers import _get_parent_otel_span_from_kwargs from litellm.litellm_core_utils.coroutine_checker import coroutine_checker @@ -317,19 +319,37 @@ def _is_redis_health_failure(exc: BaseException) -> bool: def _redis_timeout_error_types() -> tuple[type, ...]: """Health failures that are timeouts rather than unambiguous connectivity errors. - ``builtins.TimeoutError`` covers ``asyncio.TimeoutError`` and ``socket.timeout`` - (aliases since py3.11 / py3.10). ``redis.exceptions.TimeoutError`` does not subclass - either, so it is listed explicitly. + ``builtins.TimeoutError`` covers ``socket.timeout`` (an alias since py3.10) and, from + py3.11, ``asyncio.TimeoutError``; on py3.10 ``asyncio.TimeoutError`` is still its own + class, so it is listed explicitly. ``redis.exceptions.TimeoutError`` subclasses neither. """ try: from redis.exceptions import TimeoutError as RedisTimeoutError except ImportError: - return (TimeoutError,) - return (RedisTimeoutError, TimeoutError) + return (TimeoutError, asyncio.TimeoutError) + return (RedisTimeoutError, TimeoutError, asyncio.TimeoutError) -def _is_redis_timeout_failure(exc: BaseException) -> bool: - return isinstance(exc, _redis_timeout_error_types()) +_MAX_EXCEPTION_CAUSE_DEPTH: Final = 20 + + +def _explicit_causes(exc: BaseException) -> Iterator[BaseException]: + current = exc # rebind-ok: advances one link per iteration of the bounded walk + for _ in range(_MAX_EXCEPTION_CAUSE_DEPTH): + yield current + if current.__cause__ is None: + return + current = current.__cause__ + + +def is_redis_timeout_failure(exc: BaseException) -> bool: + """True when ``exc`` or any exception it was explicitly raised ``from`` is a timeout. + + redis-py's blocking pool reports a pool wait timeout as ``ConnectionError`` chained from + ``asyncio.TimeoutError``, which is a busy pool rather than an unreachable Redis. + """ + timeout_types: Final = _redis_timeout_error_types() + return any(isinstance(link, timeout_types) for link in _explicit_causes(exc)) class _BreakerMetrics: @@ -396,7 +416,7 @@ def _record_swallowed_redis_failure(breaker: RedisCircuitBreaker, exc: BaseExcep """ if not _is_redis_health_failure(exc): return - breaker.record_failure(is_timeout=_is_redis_timeout_failure(exc)) + breaker.record_failure(is_timeout=is_redis_timeout_failure(exc)) _swallowed_redis_failures.set(_swallowed_redis_failures.get() + 1) @@ -404,13 +424,58 @@ class RedisCircuitBreakerOpenError(Exception): pass +class _RedisTimeoutLogThrottle: + """Admits one Redis timeout log line per interval and counts the timeouts it suppressed in between.""" + + def __init__(self, interval: float, clock: Callable[[], float] = time.monotonic) -> None: + self.interval = interval + self._clock = clock + self._lock = threading.Lock() + self._last_logged_at: float | None = None + self._suppressed = 0 + + def admit(self) -> int | None: + """Return the number of timeouts suppressed since the last admitted line, or None to suppress this one.""" + with self._lock: + now: Final = self._clock() + if self._last_logged_at is not None and now - self._last_logged_at < self.interval: + self._suppressed += 1 + return None + suppressed: Final = self._suppressed + self._suppressed = 0 + self._last_logged_at = now + return suppressed + + +_redis_timeout_log_throttle: Final = _RedisTimeoutLogThrottle(REDIS_TIMEOUT_LOG_INTERVAL) + + def log_redis_failure( logger: logging.Logger, level: int, message: str, exc: BaseException, with_traceback: bool = False ) -> None: if isinstance(exc, RedisCircuitBreakerOpenError): - logger.debug("%s: %s", message, exc) + logger.debug("%s: %s", message, exc, stacklevel=2) return - logger.log(level, "%s: %s", message, exc, exc_info=exc if with_traceback else None) + exc_info: Final = exc if with_traceback else None + if not is_redis_timeout_failure(exc): + logger.log(level, "%s: %s", message, exc, exc_info=exc_info, stacklevel=2) + return + suppressed: Final = _redis_timeout_log_throttle.admit() + if suppressed is None: + logger.debug("%s: %s", message, exc, stacklevel=2) + return + if suppressed == 0: + logger.log(level, "%s: %s", message, exc, exc_info=exc_info, stacklevel=2) + return + logger.log( + level, + "%s: %s (%d more Redis timeouts since the previous Redis timeout line were logged at DEBUG)", + message, + exc, + suppressed, + exc_info=exc_info, + stacklevel=2, + ) @dataclass(frozen=True, slots=True) @@ -457,7 +522,7 @@ async def _run_under_circuit_breaker( result: Final = await call() except Exception as e: if _is_redis_health_failure(e): - breaker.record_failure(is_timeout=_is_redis_timeout_failure(e)) + breaker.record_failure(is_timeout=is_redis_timeout_failure(e)) raise _exit_circuit_breaker(breaker, admission) return result @@ -474,7 +539,7 @@ def _run_under_circuit_breaker_sync( result: Final = call() except Exception as e: if _is_redis_health_failure(e): - breaker.record_failure(is_timeout=_is_redis_timeout_failure(e)) + breaker.record_failure(is_timeout=is_redis_timeout_failure(e)) raise _exit_circuit_breaker(breaker, admission) return result @@ -783,10 +848,8 @@ class RedisCache(BaseCache): ## LOGGING ## end_time = time.time() _duration = end_time - start_time - verbose_logger.error( - "LiteLLM Redis Caching: increment_cache() - Got exception from REDIS %s, Writing value=%s", - str(e), - value, + log_redis_failure( + verbose_logger, logging.ERROR, "LiteLLM Redis Caching: increment_cache() - Got exception from REDIS", e ) raise e @@ -992,11 +1055,8 @@ class RedisCache(BaseCache): call_type=f"async_set_cache <- {_get_call_stack_info()}", ) ) - verbose_logger.error( - "LiteLLM Redis Caching: async set() - Got exception from REDIS %s, key=%r, value=%r", - str(e), - key, - value, + log_redis_failure( + verbose_logger, logging.ERROR, "LiteLLM Redis Caching: async set() - Got exception from REDIS", e ) raise e @@ -1044,10 +1104,8 @@ class RedisCache(BaseCache): event_metadata={"key": key}, ) ) - verbose_logger.error( - "LiteLLM Redis Caching: async set() - Got exception from REDIS %s, Writing value=%s", - str(e), - value, + log_redis_failure( + verbose_logger, logging.ERROR, "LiteLLM Redis Caching: async set() - Got exception from REDIS", e ) _record_swallowed_redis_failure(self._circuit_breaker, e) @@ -1094,7 +1152,6 @@ class RedisCache(BaseCache): start_time: Final = time.time() print_verbose(f"Set Async Redis Cache: key list: {cache_list}\nttl={ttl}, redis_version={self.redis_version}") - cache_value: Final = None try: async with _redis_client.pipeline(transaction=False) as pipe: results: Final = await self._pipeline_helper(pipe, cache_list, ttl) @@ -1131,10 +1188,11 @@ class RedisCache(BaseCache): ) ) - verbose_logger.error( - "LiteLLM Redis Caching: async set_cache_pipeline() - Got exception from REDIS %s, Writing value=%s", - str(e), - cache_value, + log_redis_failure( + verbose_logger, + logging.ERROR, + "LiteLLM Redis Caching: async set_cache_pipeline() - Got exception from REDIS", + e, ) _record_swallowed_redis_failure(self._circuit_breaker, e) @@ -1173,8 +1231,11 @@ class RedisCache(BaseCache): end_time=time.time(), ) ) - verbose_logger.error( - "LiteLLM Redis Caching: async_set_cache_pipeline_with_ttls() - Got exception from REDIS %s", str(e) + log_redis_failure( + verbose_logger, + logging.ERROR, + "LiteLLM Redis Caching: async_set_cache_pipeline_with_ttls() - Got exception from REDIS", + e, ) _record_swallowed_redis_failure(self._circuit_breaker, e) @@ -1217,10 +1278,8 @@ class RedisCache(BaseCache): ) ) # NON blocking - notify users Redis is throwing an exception - verbose_logger.error( - "LiteLLM Redis Caching: async set() - Got exception from REDIS %s, Writing value=%s", - str(e), - value, + log_redis_failure( + verbose_logger, logging.ERROR, "LiteLLM Redis Caching: async set() - Got exception from REDIS", e ) raise e @@ -1256,10 +1315,11 @@ class RedisCache(BaseCache): ) ) # NON blocking - notify users Redis is throwing an exception - verbose_logger.error( - "LiteLLM Redis Caching: async set_cache_sadd() - Got exception from REDIS %s, Writing value=%s", - str(e), - value, + log_redis_failure( + verbose_logger, + logging.ERROR, + "LiteLLM Redis Caching: async set_cache_sadd() - Got exception from REDIS", + e, ) _record_swallowed_redis_failure(self._circuit_breaker, e) @@ -1341,10 +1401,11 @@ class RedisCache(BaseCache): parent_otel_span=parent_otel_span, ) ) - verbose_logger.error( - "LiteLLM Redis Caching: async async_increment() - Got exception from REDIS %s, Writing value=%s", - str(e), - value, + log_redis_failure( + verbose_logger, + logging.ERROR, + "LiteLLM Redis Caching: async async_increment() - Got exception from REDIS", + e, ) raise e @@ -1430,7 +1491,9 @@ class RedisCache(BaseCache): print_verbose(f"Got Redis Cache: key: {key}, cached_response {cached_response}") return self._get_cache_logic(cached_response=cached_response) except Exception as e: - verbose_logger.error("litellm.caching.caching: get() - Got exception from REDIS: %s", e) + log_redis_failure( + verbose_logger, logging.ERROR, "litellm.caching.caching: get() - Got exception from REDIS", e + ) _record_swallowed_redis_failure(self._circuit_breaker, e) def _run_redis_mget_operation(self, keys: list[str]) -> Sequence[bytes | str | None]: @@ -1508,7 +1571,7 @@ class RedisCache(BaseCache): end_time=failed_at, parent_otel_span=parent_otel_span, ) - verbose_logger.error("Error occurred in batch get cache - %s", e) + log_redis_failure(verbose_logger, logging.ERROR, "Error occurred in batch get cache", e) _record_swallowed_redis_failure(self._circuit_breaker, e) return key_value_dict @@ -1627,7 +1690,7 @@ class RedisCache(BaseCache): parent_otel_span=parent_otel_span, ) ) - verbose_logger.error("Error occurred in async batch get cache - %s", e) + log_redis_failure(verbose_logger, logging.ERROR, "Error occurred in async batch get cache", e) _record_swallowed_redis_failure(self._circuit_breaker, e) return key_value_dict @@ -1852,9 +1915,11 @@ class RedisCache(BaseCache): parent_otel_span=_get_parent_otel_span_from_kwargs(kwargs), ) ) - verbose_logger.error( - "LiteLLM Redis Caching: async increment_pipeline() - Got exception from REDIS %s", - str(e), + log_redis_failure( + verbose_logger, + logging.ERROR, + "LiteLLM Redis Caching: async increment_pipeline() - Got exception from REDIS", + e, ) raise e @@ -1931,7 +1996,7 @@ class RedisCache(BaseCache): call_type=f"async_rpush <- {_get_call_stack_info()}", ) ) - verbose_logger.error("LiteLLM Redis Cache RPUSH: - Got exception from REDIS : %s", e) + log_redis_failure(verbose_logger, logging.ERROR, "LiteLLM Redis Cache RPUSH: - Got exception from REDIS", e) raise e async def _pipeline_rpush_helper( @@ -1999,9 +2064,11 @@ class RedisCache(BaseCache): call_type=f"async_rpush_pipeline <- {_get_call_stack_info()}", ) ) - verbose_logger.error( - "LiteLLM Redis Caching: async_rpush_pipeline() - Got exception from REDIS %s", - str(e), + log_redis_failure( + verbose_logger, + logging.ERROR, + "LiteLLM Redis Caching: async_rpush_pipeline() - Got exception from REDIS", + e, ) raise e @@ -2077,7 +2144,7 @@ class RedisCache(BaseCache): call_type=f"async_lpop <- {_get_call_stack_info()}", ) ) - verbose_logger.error("LiteLLM Redis Cache LPOP: - Got exception from REDIS : %s", e) + log_redis_failure(verbose_logger, logging.ERROR, "LiteLLM Redis Cache LPOP: - Got exception from REDIS", e) raise e async def _pipeline_lpop_helper( @@ -2188,8 +2255,10 @@ class RedisCache(BaseCache): call_type=f"async_lpop_pipeline <- {_get_call_stack_info()}", ) ) - verbose_logger.error( - "LiteLLM Redis Caching: async_lpop_pipeline() - Got exception from REDIS %s", - str(e), + log_redis_failure( + verbose_logger, + logging.ERROR, + "LiteLLM Redis Caching: async_lpop_pipeline() - Got exception from REDIS", + e, ) raise e diff --git a/litellm/compression/compress.py b/litellm/compression/compress.py index c646baf9d9e..b80f78a50c1 100644 --- a/litellm/compression/compress.py +++ b/litellm/compression/compress.py @@ -205,21 +205,35 @@ def _extract_anthropic_tool_exchange_spans( return spans, None +def _message_has_cache_control(message: Mapping[str, object]) -> bool: + if message.get("cache_control") is not None: + return True + content: Final = message.get("content") + if isinstance(content, list): + return any(isinstance(part, Mapping) and part.get("cache_control") is not None for part in content) + return False + + def get_protected_indices(messages: Sequence[Mapping[str, object]]) -> tuple[int, ...]: """ Return indices of messages that must never be compressed: - All system messages - The last user message - The last assistant message + - Any message carrying an Anthropic cache_control breakpoint The last user message is what the model is being asked to act on right now, so compressing it replaces the live instruction with a marker. Compression - guardrails share this policy; see the Headroom guardrail. + guardrails share this policy; see the Headroom guardrail. A cache_control + breakpoint pins the provider's prompt-cache prefix to that row's exact + bytes, so rewriting a marked row anywhere in history turns the next + request's cache read into a cache write. """ system_indices: Final = tuple(index for index, msg in enumerate(messages) if msg.get("role", "") == "system") last_user: Final = tuple(index for index, msg in enumerate(messages) if msg.get("role", "") == "user")[-1:] - last_assistant = tuple(index for index, msg in enumerate(messages) if msg.get("role", "") == "assistant")[-1:] - return system_indices + last_user + last_assistant + assistant_indices: Final = tuple(index for index, msg in enumerate(messages) if msg.get("role", "") == "assistant") + cache_control_indices: Final = tuple(index for index, msg in enumerate(messages) if _message_has_cache_control(msg)) + return tuple(dict.fromkeys(system_indices + last_user + assistant_indices[-1:] + cache_control_indices)) def _combine_scores( @@ -421,7 +435,7 @@ def compress( combined_scores = bm25_scores # Protected messages are never compressed - protected_indices: Final = get_protected_indices(normalized_messages) + protected_indices: Final = get_protected_indices(original_messages) kept_indices: set[int] = set(protected_indices) tool_exchange_spans: list[set[int]] = [] diff --git a/litellm/constants.py b/litellm/constants.py index 6b984c2673c..09442d6151e 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -53,6 +53,7 @@ S3_BOUNDED_OBJECT_KEY_HEAD_BYTES: Final = 64 S3_PREFIX_DIGEST_CHARS: Final = 16 # s3 allows 2048 bytes of combined metadata headers, which Content-Disposition counts against MAX_S3_OBJECT_DOWNLOAD_FILENAME_BYTES: Final = 1024 +MAX_FILE_LIST_LIMIT: Final = 10000 DEFAULT_SQS_FLUSH_INTERVAL_SECONDS: Final = int(os.getenv("DEFAULT_SQS_FLUSH_INTERVAL_SECONDS", 10)) DEFAULT_NUM_WORKERS_LITELLM_PROXY: Final = int(os.getenv("DEFAULT_NUM_WORKERS_LITELLM_PROXY", 1)) budget_reservation_disabled_info_emitted = False @@ -143,6 +144,7 @@ DEFAULT_MCP_SEMANTIC_FILTER_SIMILARITY_THRESHOLD: Final = float( os.getenv("DEFAULT_MCP_SEMANTIC_FILTER_SIMILARITY_THRESHOLD", 0.3) ) MAX_MCP_SEMANTIC_FILTER_TOOLS_HEADER_LENGTH: Final = int(os.getenv("MAX_MCP_SEMANTIC_FILTER_TOOLS_HEADER_LENGTH", 150)) +MAX_LITELLM_CALL_ID_LENGTH: Final = 256 MAX_GUARDRAIL_SCAN_METADATA_HEADER_LENGTH: Final = 2048 DEFAULT_AUTO_ROUTER_MAX_INPUT_CHARS: Final = 2000 @@ -225,6 +227,9 @@ PRE_CALL_EXECUTED_GUARDRAILS_KEY: Final = "_pre_call_executed_guardrails" # Attribute stamped on log_guardrail_information wrappers so __init_subclass__ does not wrap them again LOGS_GUARDRAIL_INFORMATION_MARKER: Final = "_litellm_logs_guardrail_information" +# llm_provider stamped on proxy-side rate limit errors when the model resolves to no deployment +PROXY_LLM_PROVIDER_FALLBACK: Final = "litellm_proxy" + # Generic fallback for unknown models DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET: Final = int( os.getenv("DEFAULT_REASONING_EFFORT_MINIMAL_THINKING_BUDGET", 128) @@ -309,6 +314,12 @@ REALTIME_CREDENTIAL_RESOLUTION_TIMEOUT_SECONDS: Final = float( # RFC 6455 caps the close frame payload at 125 bytes, 2 of which carry the status code WEBSOCKET_CLOSE_REASON_MAX_BYTES: Final = 123 +BEDROCK_REALTIME_PENDING_SESSION_UPDATE_SCOPE_KEY: Final = "litellm.bedrock_realtime.pending_session_update" +BEDROCK_REALTIME_SESSION_COMMITTED_SCOPE_KEY: Final = "litellm.bedrock_realtime.session_committed" +BEDROCK_REALTIME_COMMITTED_FAILURE_SCOPE_KEY: Final = "litellm.bedrock_realtime.committed_failure" +REALTIME_SESSION_SUCCESS_LOGGED_KEY: Final = "realtime_session_success_logged" +REALTIME_SESSION_FAILURE_LOGGED_KEY: Final = "realtime_session_failure_logged" + # SSL/TLS cipher configuration for faster handshakes # Strategy: Strongly prefer fast modern ciphers, but allow fallback to commonly supported ones # This balances performance with broad compatibility @@ -459,6 +470,7 @@ REDIS_CIRCUIT_BREAKER_ENABLED: Final = os.getenv("REDIS_CIRCUIT_BREAKER_ENABLED" # minimum seconds a timeout-only failure streak must span before it can open the breaker, # so one event-loop stall timing out many queued calls at once does not trip it REDIS_CIRCUIT_BREAKER_TIMEOUT_MIN_DURATION: Final = float(os.getenv("REDIS_CIRCUIT_BREAKER_TIMEOUT_MIN_DURATION", 5.0)) +REDIS_TIMEOUT_LOG_INTERVAL: Final = float(os.getenv("REDIS_TIMEOUT_LOG_INTERVAL", "5.0")) # Seconds of idle before a Redis cluster connection is validated with a PING and # reconnected if dead, so a connection silently dropped by a cluster restart # (e.g. ElastiCache Serverless maintenance) is not reused while broken @@ -571,6 +583,7 @@ ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS: Final = int( LOGGING_WORKER_CONCURRENCY: Final = int(os.getenv("LOGGING_WORKER_CONCURRENCY", 100)) # Must be above 0 LOGGING_WORKER_MAX_QUEUE_SIZE: Final = int(os.getenv("LOGGING_WORKER_MAX_QUEUE_SIZE", 50_000)) LOGGING_WORKER_MAX_TIME_PER_COROUTINE: Final = float(os.getenv("LOGGING_WORKER_MAX_TIME_PER_COROUTINE", 20.0)) +LOGGING_WORKER_TIMEOUT_SUMMARY_WINDOW_SECONDS: Final = 5.0 LOGGING_WORKER_CLEAR_PERCENTAGE: Final = int( os.getenv("LOGGING_WORKER_CLEAR_PERCENTAGE", 50) ) # Percentage of queue to clear (default: 50%) @@ -1963,6 +1976,8 @@ BROWSER_SECURITY_HEADERS: Final[frozenset[str]] = frozenset( UNSAFE_PROXY_RESPONSE_HEADERS: Final[frozenset[str]] = HTTP_FRAMING_HEADERS | BROWSER_SECURITY_HEADERS +STRINGIFIED_NONE: Final[str] = "None" + # A retrieved response replays the usage of the call that created it, so pricing these # read/management routes like inference bills the same tokens twice. NON_INFERENCE_CALL_TYPES: Final[frozenset[str]] = frozenset( diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index 814eaaf76f7..3dc6d81256b 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -9,6 +9,7 @@ from typing import TYPE_CHECKING, Any, Final, Literal, cast from httpx import Response from pydantic import BaseModel +from typing_extensions import ReadOnly, TypedDict import litellm import litellm._logging @@ -96,6 +97,7 @@ from litellm.llms.vertex_ai.cost_calculator import cost_router as google_cost_ro from litellm.llms.xai.cost_calculator import cost_per_token as xai_cost_per_token from litellm.responses.utils import ResponseAPILoggingUtils from litellm.types.agents import LiteLLMSendMessageResponse +from litellm.types.llms.base import CachedTokensDetails from litellm.types.llms.openai import ( HttpxBinaryResponseContent, ImageGenerationRequestQuality, @@ -310,6 +312,15 @@ def _transcription_usage_has_token_details( return (prompt_tokens_val > 0) or (completion_tokens_val > 0) +OCRPricingField = Literal["ocr_cost_per_page", "ocr_cost_per_credit", "annotation_cost_per_page"] + + +class OCRPricing(TypedDict, total=False): + ocr_cost_per_page: ReadOnly[float | None] + ocr_cost_per_credit: ReadOnly[float | None] + annotation_cost_per_page: ReadOnly[float | None] + + def cost_per_token( model: str = "", prompt_tokens: int = 0, @@ -344,6 +355,7 @@ def cost_per_token( response: Any | None = None, ### REQUEST MODEL ### request_model: str | None = None, # original request model for router detection + custom_model_info: OCRPricing | None = None, ) -> tuple[float, float]: """ Calculates the cost per token for a given model, prompt tokens, and completion tokens. @@ -470,7 +482,8 @@ def cost_per_token( else: model_with_provider = f"{custom_llm_provider}/{model}" if region_name is not None: - model_with_provider_and_region: Final = f"{custom_llm_provider}/{region_name}/{model}" + bare_model: Final = model[len(_prov_prefix) :] if model_is_str and model.startswith(_prov_prefix) else model + model_with_provider_and_region: Final = f"{custom_llm_provider}/{region_name}/{bare_model}" if model_with_provider_and_region in model_cost_ref: # use region based pricing, if it's available model_with_provider = model_with_provider_and_region else: @@ -558,6 +571,7 @@ def cost_per_token( model=model, custom_llm_provider=custom_llm_provider, response=response, + model_info=custom_model_info, ) elif ( call_type == "aretrieve_batch" @@ -766,6 +780,7 @@ def _select_model_name_for_cost_calc( custom_pricing: bool | None = None, custom_llm_provider: str | None = None, router_model_id: str | None = None, + region_name: str | None = None, ) -> str | None: """ 1. If custom pricing is true, return received model name @@ -787,8 +802,8 @@ def _select_model_name_for_cost_calc( provider_response_model: Final = _get_hidden_str_for_cost_calc(hidden_params, "provider_response_model") explicit_pricing: Final = custom_pricing is True or base_model is not None priced_from_response: Final = provider_response_model is not None or completion_response_model is not None - region_name: Final = ( - _get_hidden_str_for_cost_calc(hidden_params, "region_name") + priced_region: Final = ( + _get_hidden_str_for_cost_calc(hidden_params, "region_name") or region_name if not explicit_pricing and priced_from_response else None ) @@ -825,8 +840,10 @@ def _select_model_name_for_cost_calc( and custom_llm_provider is not None and not _model_contains_known_llm_provider(return_model) ): # add provider prefix if not already present, to match model_cost - provider_prefix: Final = custom_llm_provider if region_name is None else f"{custom_llm_provider}/{region_name}" - return_model = _strip_unregistered_leading_segments(f"{provider_prefix}/{return_model}", region_name) + provider_prefix: Final = ( + custom_llm_provider if priced_region is None else f"{custom_llm_provider}/{priced_region}" + ) + return_model = _strip_unregistered_leading_segments(f"{provider_prefix}/{return_model}", priced_region) return return_model @@ -1288,6 +1305,7 @@ def completion_cost( service_tier = _normalize_service_tier(service_tier) + explicit_pricing: Final = custom_pricing is True or base_model is not None selected_model: Final = _select_model_name_for_cost_calc( model=model, completion_response=completion_response, @@ -1295,6 +1313,7 @@ def completion_cost( custom_pricing=custom_pricing, base_model=base_model, router_model_id=router_model_id, + region_name=region_name, ) potential_model_names: Final = [ @@ -1432,20 +1451,9 @@ def completion_cost( ) elif call_type in _VIDEO_CALL_TYPES: ### VIDEO GENERATION COST CALCULATION ### - # Extract custom model_info for deployment-specific pricing - _video_model_info: ModelInfo | None = None - if custom_pricing and litellm_logging_obj is not None: - _litellm_params = getattr(litellm_logging_obj, "litellm_params", None) - if _litellm_params is not None: - _video_model_info = next( - ( - model_info - for _metadata_key in ("metadata", "litellm_metadata") - if (model_info := (_litellm_params.get(_metadata_key) or {}).get("model_info")) - is not None - ), - None, - ) + _video_model_info: ModelInfo | None = _deployment_model_info( + litellm_logging_obj, custom_pricing, router_model_id + ) usage_obj = getattr(completion_response, "usage", None) duration_seconds: float | None = None @@ -1650,7 +1658,7 @@ def completion_cost( completion_tokens=completion_tokens or 0, custom_llm_provider=custom_llm_provider, response_time_ms=total_time, - region_name=region_name, + 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, prompt_characters=prompt_characters, @@ -1665,6 +1673,7 @@ def completion_cost( data_residency=data_residency, vertex_location=vertex_location, response=completion_response, + custom_model_info=_ocr_model_info(litellm_logging_obj, custom_pricing, router_model_id), ) # Get additional costs from provider (e.g., routing fees, infrastructure costs) @@ -1859,6 +1868,7 @@ def response_cost_calculator( data_residency: str | None = None, # for OpenAI regional-processing uplift (e.g. "eu", "us") ### VERTEX LOCATION ### vertex_location: str | None = None, # for Vertex AI regional-endpoint uplift (e.g. "us-east5", "global") + region_name: str | None = None, ) -> float: """ Returns @@ -1892,22 +1902,89 @@ def response_cost_calculator( service_tier=service_tier, data_residency=data_residency, vertex_location=vertex_location, + region_name=region_name, ) return response_cost except Exception as e: raise e +def _deployment_model_info( + litellm_logging_obj: LitellmLoggingObject | None, + custom_pricing: bool | None, + router_model_id: str | None, +) -> ModelInfo | None: + if not custom_pricing: + return None + registered_deployment_info: Final = ( + _cost_map_model_info(router_model_id, None) + if router_model_id is not None and router_model_id in litellm.model_cost + else None + ) + if registered_deployment_info is not None: + return registered_deployment_info + if litellm_logging_obj is None: + return None + litellm_params: Final = getattr(litellm_logging_obj, "litellm_params", None) + if litellm_params is None: + return None + return next( + ( + model_info + for metadata_key in ("metadata", "litellm_metadata") + if (metadata := litellm_params.get(metadata_key)) and (model_info := metadata.get("model_info")) is not None + ), + None, + ) + + +def _ocr_model_info( + litellm_logging_obj: LitellmLoggingObject | None, + custom_pricing: bool | None, + router_model_id: str | None, +) -> OCRPricing | None: + deployment_info: Final = _deployment_model_info(litellm_logging_obj, custom_pricing, router_model_id) + litellm_params: Final = getattr(litellm_logging_obj, "litellm_params", None) if custom_pricing else None + if litellm_params is None: + return deployment_info + return _layered_ocr_pricing(litellm_params, deployment_info) + + +def _first_ocr_price(field: OCRPricingField, *sources: Mapping[str, object] | None) -> float | None: + return next( + (price for source in sources if source is not None and isinstance(price := source.get(field), int | float)), + None, + ) + + +def _layered_ocr_pricing(*sources: Mapping[str, object] | None) -> OCRPricing: + return OCRPricing( + ocr_cost_per_page=_first_ocr_price("ocr_cost_per_page", *sources), + ocr_cost_per_credit=_first_ocr_price("ocr_cost_per_credit", *sources), + annotation_cost_per_page=_first_ocr_price("annotation_cost_per_page", *sources), + ) + + +def _cost_map_model_info(model: str, custom_llm_provider: str | None) -> ModelInfo | None: + try: + return litellm.get_model_info(model=model, custom_llm_provider=custom_llm_provider) + except Exception: + return None + + def ocr_cost( model: str, custom_llm_provider: str | None, response: object | None = None, + model_info: OCRPricing | None = None, ) -> tuple[float, float]: """ Args: model: str - model name custom_llm_provider: Optional[str] - custom LLM provider response: Optional[Any] - response object + model_info: Optional[OCRPricing] - deployment-specific OCR pricing; each rate it sets + overrides the model cost map's, the rest fall back to the map Returns: Tuple[float, float]: cost of OCR processing @@ -1925,20 +2002,15 @@ def ocr_cost( if response.usage_info is None: raise ValueError("OCR response usage_info is None") - try: - model_info: ModelInfo | None = litellm.get_model_info(model=model, custom_llm_provider=custom_llm_provider) - except Exception: - model_info = None - credits: Final = getattr(response.usage_info, "credits", None) - cost_per_credit = None - if model_info is not None: - cost_per_credit = model_info.get("ocr_cost_per_credit") + pricing: Final = _layered_ocr_pricing(model_info, _cost_map_model_info(model, custom_llm_provider)) + + cost_per_credit: Final = pricing.get("ocr_cost_per_credit") if credits is not None and cost_per_credit is not None: return cost_per_credit * credits, 0.0 - ocr_cost_per_page: Final = model_info.get("ocr_cost_per_page") if model_info is not None else None - annotation_cost_per_page: Final = model_info.get("annotation_cost_per_page") if model_info is not None else None + ocr_cost_per_page: Final = pricing.get("ocr_cost_per_page") + annotation_cost_per_page: Final = pricing.get("annotation_cost_per_page") annotation_rate: Final = annotation_cost_per_page if annotation_cost_per_page is not None else ocr_cost_per_page pages_processed: Final = response.usage_info.pages_processed @@ -2206,6 +2278,19 @@ def default_video_cost_calculator( return 0.0 +def _batch_rate( + model_info: ModelInfo, + key: Literal[ + "input_cost_per_audio_token_batches", + "input_cost_per_image_token_batches", + "input_cost_per_video_token_batches", + ], + fallback: float, +) -> float: + rate: Final = model_info.get(key) + return fallback if rate is None else rate + + def batch_cost_calculator( usage: Usage, model: str, @@ -2265,7 +2350,29 @@ def batch_cost_calculator( total_prompt_cost = 0.0 total_completion_cost = 0.0 if input_cost_per_token_batches is not None: - total_prompt_cost = usage.prompt_tokens * input_cost_per_token_batches + batch_details: Final = parse_prompt_tokens_details(usage) + audio_tokens, image_tokens, video_tokens = ( + batch_details["audio_tokens"], + batch_details["image_tokens"], + batch_details["video_tokens"], + ) + modality_rates: Final = ( + _batch_rate(model_info, "input_cost_per_audio_token_batches", input_cost_per_token_batches), + _batch_rate(model_info, "input_cost_per_image_token_batches", input_cost_per_token_batches), + _batch_rate(model_info, "input_cost_per_video_token_batches", input_cost_per_token_batches), + ) + total_prompt_cost = sum( + tokens * rate + for tokens, rate in zip( + ( + max((usage.prompt_tokens or 0) - audio_tokens - image_tokens - video_tokens, 0), + audio_tokens, + image_tokens, + video_tokens, + ), + (input_cost_per_token_batches, *modality_rates), + ) + ) elif input_cost_per_token: details: Final = parse_prompt_tokens_details(usage) cache_read_tokens: Final = details["cache_hit_tokens"] @@ -2310,6 +2417,46 @@ def _summable_prompt_token_fields(prompt_tokens_details: BaseModel) -> list[str] return [attr for attr in field_names if attr != "cache_creation_tokens"] +def _combine_cached_tokens_details( + current: CachedTokensDetails | None, new: CachedTokensDetails +) -> CachedTokensDetails: + def _sum_optional(current_value: int | None, new_value: int | None) -> int | None: + if current_value is None and new_value is None: + return None + return (current_value or 0) + (new_value or 0) + + return CachedTokensDetails( + text_tokens=_sum_optional(current.text_tokens if current is not None else None, new.text_tokens), + audio_tokens=_sum_optional(current.audio_tokens if current is not None else None, new.audio_tokens), + image_tokens=_sum_optional(current.image_tokens if current is not None else None, new.image_tokens), + ) + + +def _combine_prompt_tokens_details( + current: PromptTokensDetailsWrapper | None, new: PromptTokensDetailsWrapper +) -> PromptTokensDetailsWrapper: + base: Final = current if current is not None else PromptTokensDetailsWrapper() + base_values: Final = MappingProxyType( + {attr: getattr(base, attr) for attr in type(base).model_fields if hasattr(base, attr)} + ) + summed: Final = MappingProxyType( + { + attr: (getattr(base, attr, 0) or 0) + (getattr(new, attr) or 0) + for attr in _summable_prompt_token_fields(new) + if hasattr(new, attr) and isinstance(getattr(new, attr) or 0, (int, float)) + } + ) + new_cached_tokens_details: Final = getattr(new, "cached_tokens_details", None) + cached_tokens_details: Final = ( + _combine_cached_tokens_details(getattr(base, "cached_tokens_details", None), new_cached_tokens_details) + if isinstance(new_cached_tokens_details, CachedTokensDetails) + else getattr(base, "cached_tokens_details", None) + ) + return PromptTokensDetailsWrapper( + **MappingProxyType({**base_values, **summed, "cached_tokens_details": cached_tokens_details}) + ) + + class BaseTokenUsageProcessor: @staticmethod def combine_usage_objects(usage_objects: list[Usage]) -> Usage: @@ -2318,7 +2465,6 @@ class BaseTokenUsageProcessor: """ from litellm.types.utils import ( CompletionTokensDetailsWrapper, - PromptTokensDetailsWrapper, Usage, ) @@ -2337,27 +2483,10 @@ class BaseTokenUsageProcessor: and isinstance(current_val, (int, float)) ): setattr(combined, attr, current_val + new_val) - # Handle nested prompt_tokens_details if hasattr(usage, "prompt_tokens_details") and usage.prompt_tokens_details: - if not hasattr(combined, "prompt_tokens_details") or not combined.prompt_tokens_details: - combined.prompt_tokens_details = PromptTokensDetailsWrapper() - - # Check what keys exist in the model's prompt_tokens_details - # Access model_fields on the class, not the instance, to avoid Pydantic 2.11+ deprecation warnings - for attr in _summable_prompt_token_fields(usage.prompt_tokens_details): - if ( - hasattr(usage.prompt_tokens_details, attr) - and not attr.startswith("_") - and not callable(_attribute_value(usage.prompt_tokens_details, attr)) - ): - current_val = getattr(combined.prompt_tokens_details, attr, 0) or 0 - new_val = getattr(usage.prompt_tokens_details, attr, 0) or 0 - if new_val is not None and isinstance(new_val, (int, float)): - setattr( - combined.prompt_tokens_details, - attr, - current_val + new_val, - ) + combined.prompt_tokens_details = _combine_prompt_tokens_details( + getattr(combined, "prompt_tokens_details", None), usage.prompt_tokens_details + ) # Handle nested completion_tokens_details if hasattr(usage, "completion_tokens_details") and usage.completion_tokens_details: diff --git a/litellm/files/main.py b/litellm/files/main.py index 218518eb3cd..1d5da29fe6f 100644 --- a/litellm/files/main.py +++ b/litellm/files/main.py @@ -682,6 +682,10 @@ def file_list( ) if provider_config is not None: litellm_params_dict: Final = get_litellm_params(**kwargs) + add_trusted_model_credentials_to_litellm_params( + litellm_params_dict=litellm_params_dict, + kwargs=kwargs, + ) litellm_params_dict["api_key"] = optional_params.api_key litellm_params_dict["api_base"] = optional_params.api_base diff --git a/litellm/integrations/arize/arize_phoenix_prompt_manager.py b/litellm/integrations/arize/arize_phoenix_prompt_manager.py index 0c9e868c146..fbf25ea87fd 100644 --- a/litellm/integrations/arize/arize_phoenix_prompt_manager.py +++ b/litellm/integrations/arize/arize_phoenix_prompt_manager.py @@ -379,7 +379,7 @@ class ArizePhoenixPromptManager(CustomPromptManagement): """Reload prompts from Arize Phoenix.""" if self.prompt_id: self._prompt_manager = None # Reset to force reload - self.prompt_manager # This will trigger reload + _ = self.prompt_manager # access triggers lazy reload def should_run_prompt_management( self, diff --git a/litellm/integrations/bitbucket/bitbucket_prompt_manager.py b/litellm/integrations/bitbucket/bitbucket_prompt_manager.py index ff34bd91e31..e98fa77a562 100644 --- a/litellm/integrations/bitbucket/bitbucket_prompt_manager.py +++ b/litellm/integrations/bitbucket/bitbucket_prompt_manager.py @@ -406,7 +406,7 @@ class BitBucketPromptManager(CustomPromptManagement): """Reload prompts from BitBucket.""" if self.prompt_id: self._prompt_manager = None # Reset to force reload - self.prompt_manager # This will trigger reload + _ = self.prompt_manager # access triggers lazy reload def should_run_prompt_management( self, diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py index 39adea30828..1d00ad8c29a 100644 --- a/litellm/integrations/custom_guardrail.py +++ b/litellm/integrations/custom_guardrail.py @@ -884,7 +884,9 @@ class CustomGuardrail(CustomLogger): """logging_only: run apply_guardrail on copies of the logged request/response and record the verdict.""" from litellm.llms import get_guardrail_translation_mapping - if not self.uses_apply_guardrail_interface() or self.use_native_lifecycle_hooks: + if not self.uses_apply_guardrail_interface(): + return kwargs, result + if not self._event_hook_is_event_type(GuardrailEventHooks.logging_only): return kwargs, result try: translation: Final = get_guardrail_translation_mapping(CallTypes(call_type))() @@ -901,8 +903,18 @@ class CustomGuardrail(CustomLogger): for key, value in (litellm_params.get("metadata") or {}).items() if key != "standard_logging_guardrail_information" } + response: Final = ( + kwargs.get("async_complete_streaming_response") or kwargs.get("complete_streaming_response") or result + ) + from litellm.types.utils import ModelResponse + + output_translation: Final = ( + get_guardrail_translation_mapping(CallTypes.acompletion)() + if isinstance(response, ModelResponse) + else translation + ) try: - await self._scan_logged_call(kwargs, result, translation, scratch_metadata) + await self._scan_logged_call(kwargs, response, translation, output_translation, scratch_metadata) except Exception as e: verbose_logger.warning("Guardrail %s: logging_only scan raised: %s", self.guardrail_name, e) recorded: Final = scratch_metadata.get("standard_logging_guardrail_information") @@ -919,8 +931,9 @@ class CustomGuardrail(CustomLogger): async def _scan_logged_call( self, kwargs: dict, # mutable-ok: CustomLogger.async_logging_hook contract - result: object, + response: object | None, translation: "BaseTranslation", + output_translation: "BaseTranslation", scratch_metadata: dict, # mutable-ok: apply_guardrail records its verdict into request metadata ) -> None: optional_params: Final = kwargs.get("optional_params") or {} @@ -934,8 +947,10 @@ class CustomGuardrail(CustomLogger): "metadata": scratch_metadata, } await translation.process_input_messages(data=scratch_request, guardrail_to_apply=self) - await translation.process_output_response( - response=copy.deepcopy(result), guardrail_to_apply=self, request_data=scratch_request + if response is None: + return + await output_translation.process_output_response( + response=copy.deepcopy(response), guardrail_to_apply=self, request_data=scratch_request ) def supports_scan_only_tool_results(self) -> bool: diff --git a/litellm/integrations/gcs_bucket/gcs_bucket.py b/litellm/integrations/gcs_bucket/gcs_bucket.py index 31ceb338dcd..e338f490496 100644 --- a/litellm/integrations/gcs_bucket/gcs_bucket.py +++ b/litellm/integrations/gcs_bucket/gcs_bucket.py @@ -29,8 +29,6 @@ class GCSBucketLogger(GCSBucketBase, AdditionalLoggingUtils): def __init__(self, bucket_name: str | None = None) -> None: from litellm.proxy.proxy_server import premium_user - super().__init__(bucket_name=bucket_name) - self.batch_size = int(os.getenv("GCS_BATCH_SIZE", GCS_DEFAULT_BATCH_SIZE)) self.flush_interval = int(os.getenv("GCS_FLUSH_INTERVAL", GCS_DEFAULT_FLUSH_INTERVAL_SECONDS)) self.use_batched_logging = ( @@ -38,6 +36,7 @@ class GCSBucketLogger(GCSBucketBase, AdditionalLoggingUtils): ) self.flush_lock = asyncio.Lock() super().__init__( + bucket_name=bucket_name, flush_lock=self.flush_lock, batch_size=self.batch_size, flush_interval=self.flush_interval, diff --git a/litellm/integrations/otel/mappers/openinference.py b/litellm/integrations/otel/mappers/openinference.py index 0ba45170b8e..a7e0f1af3ac 100644 --- a/litellm/integrations/otel/mappers/openinference.py +++ b/litellm/integrations/otel/mappers/openinference.py @@ -12,6 +12,7 @@ from typing import Final from litellm.integrations.otel.mappers.base import AttributeMap, AttrValue, SpanData from litellm.integrations.otel.mappers.utils import ( + MAX_MESSAGE_ATTRS_PER_SPAN, MAX_TOOL_DEFINITION_ATTRS_PER_SPAN, collect, drop_none, @@ -26,6 +27,8 @@ from litellm.integrations.otel.model.payloads import ( ToolDefinition, ) +_MAX_INDEXED_MESSAGES: Final = MAX_MESSAGE_ATTRS_PER_SPAN // 2 + class OpenInferenceMapper: """Emits OpenInference attributes for LLM_CALL spans. @@ -84,27 +87,44 @@ class OpenInferenceMapper: return {} def _llm_call(self, data: LLMCallSpanData) -> AttributeMap: + outputs: Final = output_messages(data) + indexed_in, indexed_out = self._indexed_split(len(data.messages_in), len(outputs)) return { **collect(self._LLM_CALL_ATTRS, data), **collect(self._BLOB_ATTRS, data), - **self._messages("llm.input_messages", "input.value", data.messages_in), - **self._messages("llm.output_messages", "output.value", output_messages(data)), + **self._messages( + "llm.input_messages", + "input.value", + data.messages_in, + self._prompt_positions(len(data.messages_in), indexed_in), + ), + **self._messages("llm.output_messages", "output.value", outputs, range(indexed_out)), **self._tools(data), } @staticmethod - def _messages(prefix: str, value_key: str, messages: Sequence[object]) -> AttributeMap: - """Per-message ``{prefix}.{idx}.message.*`` keys + the ``value_key`` blob.""" + def _indexed_split(inputs: int, outputs: int) -> tuple[int, int]: + """Prompt and response share one allowance; the response is reserved at least half of it.""" + indexed_out: Final = min(outputs, max(_MAX_INDEXED_MESSAGES // 2, _MAX_INDEXED_MESSAGES - inputs)) + return _MAX_INDEXED_MESSAGES - indexed_out, indexed_out + + @staticmethod + def _prompt_positions(total: int, indexed: int) -> tuple[int, ...]: + """Prompt messages that get per-index attributes: message 0 and the most recent turns.""" + if total <= indexed: + return tuple(range(total)) + return (0, *range(total - indexed + 1, total)) + + @staticmethod + def _messages(prefix: str, value_key: str, messages: Sequence[object], positions: Sequence[int]) -> AttributeMap: + """``{prefix}.{idx}.message.*`` keys for the messages at ``positions`` + the ``value_key`` blob of all.""" parsed: Final = [(m.get("role") if isinstance(m, dict) else None, message_content(m)) for m in messages] attrs: Final = drop_none( { key: value - for idx, (role, content) in enumerate(parsed) + for idx, (role, content) in ((idx, parsed[idx]) for idx in positions) for key, value in ( - ( - f"{prefix}.{idx}.message.role", - role if isinstance(role, str) else None, - ), + (f"{prefix}.{idx}.message.role", role if isinstance(role, str) else None), (f"{prefix}.{idx}.message.content", content), ) } diff --git a/litellm/integrations/otel/mappers/utils.py b/litellm/integrations/otel/mappers/utils.py index d45dca782b2..c023621d2ef 100644 --- a/litellm/integrations/otel/mappers/utils.py +++ b/litellm/integrations/otel/mappers/utils.py @@ -32,6 +32,14 @@ core telemetry no matter how many vocabularies are configured. """ +MAX_MESSAGE_ATTRS_PER_SPAN: Final = DEFAULT_SPAN_ATTRIBUTE_LIMIT // 8 +"""Span-wide ceiling on per-index chat message attributes, prompt and response together. + +An eighth is the largest share that still fits beside the tool ceiling and the core +of every vocabulary at once. The complete conversation still rides the JSON blobs. +""" + + def tool_attr_budget(vocabularies: int) -> int: """Split the span-wide tool-definition ceiling across active vocabularies.""" return MAX_TOOL_DEFINITION_ATTRS_PER_SPAN // max(vocabularies, 1) diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index 2528f07f92c..69a38e83835 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -16,6 +16,7 @@ from pydantic import BaseModel import litellm from litellm._logging import print_verbose, verbose_logger +from litellm.constants import PROXY_LLM_PROVIDER_FALLBACK from litellm.exceptions import ( validate_rate_limit_category, validate_rate_limit_type, @@ -2581,6 +2582,15 @@ class PrometheusLogger(CustomLogger): ) return None + @staticmethod + def _extract_api_provider_from_exception(exception: Exception) -> str | None: + if not isinstance(exception, litellm.exceptions.RateLimitError): + return None + llm_provider: Final = exception.llm_provider + if not llm_provider or llm_provider == PROXY_LLM_PROVIDER_FALLBACK: + return None + return llm_provider + async def async_post_call_failure_hook( self, request_data: dict, @@ -2616,7 +2626,9 @@ class PrometheusLogger(CustomLogger): _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) + api_provider: Final = self._extract_api_provider_from_request_data( + request_data + ) or self._extract_api_provider_from_exception(original_exception) enum_values: Final = UserAPIKeyLabelValues( end_user=user_api_key_dict.end_user_id, user=user_api_key_dict.user_id, diff --git a/litellm/integrations/weights_biases.py b/litellm/integrations/weights_biases.py index 97a2acbac08..d1a8ec098cf 100644 --- a/litellm/integrations/weights_biases.py +++ b/litellm/integrations/weights_biases.py @@ -4,18 +4,10 @@ imported_openAIResponse = True try: import io import logging - import sys - from typing import Any, TypeVar + from typing import Any, Literal, Protocol, TypeVar from wandb.sdk.data_types import trace_tree - if sys.version_info >= (3, 8): - from typing import Literal, Protocol - else: - from typing import Literal - - from typing_extensions import Protocol - logger: Final = logging.getLogger(__name__) K = TypeVar("K", bound=str) diff --git a/litellm/litellm_core_utils/core_helpers.py b/litellm/litellm_core_utils/core_helpers.py index aa7d6ca1699..15380bc5d57 100644 --- a/litellm/litellm_core_utils/core_helpers.py +++ b/litellm/litellm_core_utils/core_helpers.py @@ -303,6 +303,16 @@ def get_metadata_variable_name_from_kwargs( return "litellm_metadata" if "litellm_metadata" in kwargs else "metadata" +def max_retries_per_request_hit(kwargs: Mapping[str, object], num_retries_per_request: int | None) -> bool: + if num_retries_per_request is None: + return False + metadata: Final = kwargs.get(get_metadata_variable_name_from_kwargs(kwargs)) + if not isinstance(metadata, Mapping): + return False + retry_count: Final = metadata.get("request_retry_count") + return type(retry_count) is int and 0 < retry_count and num_retries_per_request <= retry_count + + def get_or_create_metadata_bucket( request_data: dict, ) -> tuple[Literal["metadata", "litellm_metadata"], dict]: diff --git a/litellm/litellm_core_utils/coroutine_checker.py b/litellm/litellm_core_utils/coroutine_checker.py index 52fc44ba8dc..7b9a650c66b 100644 --- a/litellm/litellm_core_utils/coroutine_checker.py +++ b/litellm/litellm_core_utils/coroutine_checker.py @@ -36,7 +36,7 @@ class CoroutineChecker: target = callback if not inspect.isfunction(target) and not inspect.ismethod(target): try: - call_attr: Final = getattr(target, "__call__", None) + call_attr: Final = getattr(target, "__call__", None) # noqa: B004 # value unwrap so iscoroutinefunction sees through functors if call_attr is not None: target = call_attr except Exception: diff --git a/litellm/litellm_core_utils/exception_mapping_utils.py b/litellm/litellm_core_utils/exception_mapping_utils.py index 82708d412c9..70675966dfc 100644 --- a/litellm/litellm_core_utils/exception_mapping_utils.py +++ b/litellm/litellm_core_utils/exception_mapping_utils.py @@ -1,6 +1,9 @@ +import inspect import json import re import traceback +from collections.abc import Mapping +from types import MappingProxyType from typing import Any, Final, Protocol, cast import httpx @@ -202,11 +205,17 @@ def _get_response_headers(original_exception: Exception) -> httpx.Headers | None return _response_headers +def _accepted_init_kwargs(exception_class: type[Exception], candidates: Mapping[str, object]) -> Mapping[str, object]: + accepted: Final = inspect.signature(exception_class).parameters + return MappingProxyType({name: value for name, value in candidates.items() if name in accepted}) + + def extract_and_raise_litellm_exception( response: Any | None, error_str: str, model: str, custom_llm_provider: str, + body: object | None = None, ): """ Covers scenario where litellm sdk calling proxy. @@ -216,32 +225,19 @@ def extract_and_raise_litellm_exception( Relevant Issue: https://github.com/BerriAI/litellm/issues/7259 """ pattern: Final = r"litellm\.\w+Error" - - # Search for the exception in the error string match: Final = re.search(pattern, error_str) - - # Extract the exception if found - if match: - exception_name = match.group(0) - exception_name = exception_name.strip().replace("litellm.", "") - raised_exception_obj: Final = getattr(litellm, exception_name, None) - if raised_exception_obj: - # Try with response parameter first, fall back to without it - # Some exceptions (e.g., APIConnectionError) don't accept response param - try: - raise raised_exception_obj( - message=error_str, - llm_provider=custom_llm_provider, - model=model, - response=response, - ) - except TypeError: - # Exception doesn't accept response parameter - raise raised_exception_obj( - message=error_str, - llm_provider=custom_llm_provider, - model=model, - ) + if match is None: + return + exception_name: Final = match.group(0).removeprefix("litellm.") + raised_exception_obj: Final = getattr(litellm, exception_name, None) + if not raised_exception_obj: + return + raise raised_exception_obj( + message=error_str, + llm_provider=custom_llm_provider, + model=model, + **_accepted_init_kwargs(raised_exception_obj, MappingProxyType({"response": response, "body": body})), + ) class _ProviderHTTPException(Protocol): @@ -254,6 +250,23 @@ class _ProviderHTTPException(Protocol): llm_provider: str +def _litellm_proxy_response( + original_exception: _ProviderHTTPException, custom_llm_provider: str +) -> httpx.Response | None: + response: Final = getattr(original_exception, "response", None) + if custom_llm_provider != "litellm_proxy" or not isinstance(response, httpx.Response) or response.headers: + return response + headers: Final = getattr(original_exception, "headers", None) + if not isinstance(headers, Mapping) or not headers: + return response + pairs: Final = headers.multi_items() if isinstance(headers, httpx.Headers) else headers.items() + return httpx.Response( + status_code=response.status_code, + headers=[(str(k), str(v)) for k, v in pairs], + request=getattr(original_exception, "request", None), + ) + + def _map_openai_exception( *, model: str, @@ -264,6 +277,7 @@ def _map_openai_exception( exception_provider: str, extra_information: str, ) -> None: + response: Final = _litellm_proxy_response(original_exception, custom_llm_provider) # custom_llm_provider is openai, make it OpenAI message = get_error_message(error_obj=original_exception) if message is None: @@ -292,14 +306,14 @@ def _map_openai_exception( message=f"RateLimitError: {exception_provider} - {message}", model=model, llm_provider=custom_llm_provider, - response=getattr(original_exception, "response", None), + response=response, ) elif ExceptionCheckers.is_error_str_context_window_exceeded(error_str): raise ContextWindowExceededError( message=f"ContextWindowExceededError: {exception_provider} - {message}", llm_provider=custom_llm_provider, model=model, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, ) elif "invalid_request_error" in error_str and "model_not_found" in error_str: @@ -307,7 +321,7 @@ def _map_openai_exception( message=f"{exception_provider} - {message}", llm_provider=custom_llm_provider, model=model, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, ) elif "A timeout occurred" in error_str: @@ -326,8 +340,9 @@ def _map_openai_exception( message=f"ContentPolicyViolationError: {exception_provider} - {message}", llm_provider=custom_llm_provider, model=model, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, + body=getattr(original_exception, "body", None), ) elif "invalid_encrypted_content" in error_str or "could not be verified" in error_str: helpful_message: Final = ( @@ -345,7 +360,7 @@ def _map_openai_exception( message=helpful_message, llm_provider=custom_llm_provider, model=model, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, body=getattr(original_exception, "body", None), ) @@ -354,7 +369,7 @@ def _map_openai_exception( message=f"{exception_provider} - {message}", llm_provider=custom_llm_provider, model=model, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, body=getattr(original_exception, "body", None), ) @@ -372,7 +387,7 @@ def _map_openai_exception( message=f"RateLimitError: {exception_provider} - {message}", model=model, llm_provider=custom_llm_provider, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, ) elif ( @@ -383,7 +398,7 @@ def _map_openai_exception( message=f"AuthenticationError: {exception_provider} - {message}", llm_provider=custom_llm_provider, model=model, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, ) elif "Mistral API raised a streaming error" in error_str: @@ -402,15 +417,16 @@ def _map_openai_exception( message=f"{exception_provider} - {message}", llm_provider=custom_llm_provider, model=model, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, + body=getattr(original_exception, "body", None), ) elif original_exception.status_code == 401: raise AuthenticationError( message=f"AuthenticationError: {exception_provider} - {message}", llm_provider=custom_llm_provider, model=model, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, ) elif original_exception.status_code == 404: @@ -418,7 +434,7 @@ def _map_openai_exception( message=f"NotFoundError: {exception_provider} - {message}", model=model, llm_provider=custom_llm_provider, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, ) elif original_exception.status_code == 408: @@ -433,7 +449,7 @@ def _map_openai_exception( message=f"{exception_provider} - {message}", model=model, llm_provider=custom_llm_provider, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, body=getattr(original_exception, "body", None), ) @@ -442,7 +458,7 @@ def _map_openai_exception( message=f"RateLimitError: {exception_provider} - {message}", model=model, llm_provider=custom_llm_provider, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, ) elif original_exception.status_code == 500: @@ -450,7 +466,7 @@ def _map_openai_exception( message=f"InternalServerError: {exception_provider} - {message}", model=model, llm_provider=custom_llm_provider, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, ) elif original_exception.status_code == 502: @@ -458,7 +474,7 @@ def _map_openai_exception( message=f"BadGatewayError: {exception_provider} - {message}", model=model, llm_provider=custom_llm_provider, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, ) elif original_exception.status_code == 503: @@ -466,7 +482,7 @@ def _map_openai_exception( message=f"ServiceUnavailableError: {exception_provider} - {message}", model=model, llm_provider=custom_llm_provider, - response=getattr(original_exception, "response", None), + response=response, litellm_debug_info=extra_information, ) elif original_exception.status_code == 504: # gateway timeout error @@ -2423,10 +2439,11 @@ def exception_type( custom_llm_provider == "litellm_proxy" ): # handle special case where calling litellm proxy + exception str contains error message extract_and_raise_litellm_exception( - response=getattr(original_exception, "response", None), + response=_litellm_proxy_response(mappable_exception, custom_llm_provider), error_str=error_str, model=model, custom_llm_provider=custom_llm_provider, + body=getattr(original_exception, "body", None), ) if ( custom_llm_provider == "openai" diff --git a/litellm/litellm_core_utils/fallback_generalizations.py b/litellm/litellm_core_utils/fallback_generalizations.py index 7739fc82c77..be432d1fdd4 100644 --- a/litellm/litellm_core_utils/fallback_generalizations.py +++ b/litellm/litellm_core_utils/fallback_generalizations.py @@ -34,6 +34,11 @@ rules never mix the two and never use ``extends``. A rule whose Rules are only consulted after exact and case-insensitive lookups miss, so an exact cost-map entry always takes precedence over any rule. +Rules flagged with ``fill_missing_for_providers: [..]`` also fill only keys +missing from an exact cost-map entry when the entry's ``litellm_provider`` is +listed, while values already present on the entry win on conflict. Only flagged +capability rules participate in this fill; routing rules never do. + Patterns are matched case-insensitively with ``re.search`` and are not implicitly anchored: a rule must include ``^`` and ``$`` to bind to the whole model name, otherwise it matches as a substring. Keeping anchoring in the regex makes the rule @@ -46,17 +51,19 @@ Rules are compiled and classified once, at install time. The match functions are O(number of rules); callers must only invoke them on a cache miss. """ +import logging import re +from collections.abc import Mapping from dataclasses import dataclass from typing import Final -from litellm._logging import verbose_logger - +verbose_logger: Final = logging.getLogger("LiteLLM") NAME_FIELD: Final = "name" PATTERN_FIELD: Final = "pattern" MODEL_INFO_FIELD: Final = "model_info" PROVIDER_KEY: Final = "litellm_provider" LEGACY_EXTENDS_FIELD: Final = "extends" +FILL_MISSING_FOR_PROVIDERS_FIELD: Final = "fill_missing_for_providers" def _resolve_legacy_extends(rules: list) -> list: @@ -98,11 +105,28 @@ class _RoutingRule: class _CapabilityRule: pattern: re.Pattern model_info: dict + fill_missing_for_providers: frozenset[str] _CompiledRule = _RoutingRule | _CapabilityRule +def _parse_fill_missing_for_providers(rule: Mapping[str, object], pattern_label: object) -> frozenset[str] | None: + if FILL_MISSING_FOR_PROVIDERS_FIELD not in rule: + return frozenset() + raw_fill_missing_for_providers: Final = rule.get(FILL_MISSING_FOR_PROVIDERS_FIELD) + if not isinstance(raw_fill_missing_for_providers, (list, tuple)) or not all( + isinstance(provider, str) for provider in raw_fill_missing_for_providers + ): + verbose_logger.warning( + "LiteLLM: skipping malformed fallback generalization rule %s ('%s' must be a list of provider strings).", + rule.get(NAME_FIELD, pattern_label), + FILL_MISSING_FOR_PROVIDERS_FIELD, + ) + return None + return frozenset(raw_fill_missing_for_providers) + + def _compile_rule(rule: object) -> tuple[_CompiledRule, ...]: if not isinstance(rule, dict): return () @@ -125,8 +149,17 @@ def _compile_rule(rule: object) -> tuple[_CompiledRule, ...]: e, ) return () + fill_missing_for_providers: Final = _parse_fill_missing_for_providers(rule, pattern) + if fill_missing_for_providers is None: + return () if PROVIDER_KEY not in model_info: - return (_CapabilityRule(pattern=compiled, model_info=model_info),) + return ( + _CapabilityRule( + pattern=compiled, + model_info=model_info, + fill_missing_for_providers=fill_missing_for_providers, + ), + ) provider: Final = model_info[PROVIDER_KEY] if not isinstance(provider, str): verbose_logger.warning( @@ -140,7 +173,11 @@ def _compile_rule(rule: object) -> tuple[_CompiledRule, ...]: return (_RoutingRule(pattern=compiled, provider=provider),) return ( _RoutingRule(pattern=compiled, provider=provider), - _CapabilityRule(pattern=compiled, model_info=model_info), + _CapabilityRule( + pattern=compiled, + model_info=model_info, + fill_missing_for_providers=fill_missing_for_providers, + ), ) @@ -151,6 +188,7 @@ class _FallbackGeneralizations: self.rules: list = [] self.routing_rules: tuple = () self.capability_rules: tuple = () + self.fill_missing_rules: tuple[_CapabilityRule, ...] = () def set_rules(self, rules: list | None) -> None: installed: Final = rules if isinstance(rules, list) else [] @@ -158,6 +196,7 @@ class _FallbackGeneralizations: self.rules = installed self.routing_rules = tuple(rule for rule in compiled if isinstance(rule, _RoutingRule)) self.capability_rules = tuple(rule for rule in compiled if isinstance(rule, _CapabilityRule)) + self.fill_missing_rules = tuple(rule for rule in self.capability_rules if rule.fill_missing_for_providers) def match_routing(self, model: str) -> str | None: if not model: @@ -175,6 +214,21 @@ class _FallbackGeneralizations: return None return {key: value for model_info in matched for key, value in model_info.items()} + def match_fill_missing(self, model: str, provider: str) -> Mapping[str, object] | None: + if not model or not provider: + return None + matched = tuple( + rule.model_info + for rule in self.fill_missing_rules + if provider in rule.fill_missing_for_providers and rule.pattern.search(model) is not None + ) + if not matched: + return None + fill_missing: Final[Mapping[str, object]] = { + key: value for model_info in matched for key, value in model_info.items() if key != PROVIDER_KEY + } + return fill_missing or None + _registry: Final = _FallbackGeneralizations() @@ -210,3 +264,14 @@ def match_capability_generalizations(model: str) -> dict | None: capability rule matches. O(number of rules); only call once exact lookups have missed. """ return _registry.match_capabilities(model) + + +def match_fill_missing_generalizations(model: str, provider: str) -> Mapping[str, object] | None: + """Return flagged capability rules matching ``model`` for ``provider``. + + Later rules override earlier ones on key conflicts. Only rules listing + ``provider`` in ``fill_missing_for_providers`` contribute. Returns ``None`` + when no flagged rule matches. O(number of rules); only call once exact + lookups have matched. + """ + return _registry.match_fill_missing(model, provider) diff --git a/litellm/litellm_core_utils/get_llm_provider_logic.py b/litellm/litellm_core_utils/get_llm_provider_logic.py index ce51fb19970..02681d8b499 100644 --- a/litellm/litellm_core_utils/get_llm_provider_logic.py +++ b/litellm/litellm_core_utils/get_llm_provider_logic.py @@ -601,12 +601,15 @@ def _get_openai_compatible_provider_info( dynamic_api_key, ) = litellm.GroqChatConfig()._get_openai_compatible_provider_info(api_base, api_key) elif custom_llm_provider == "bedrock_mantle": + from litellm.llms.bedrock_mantle.common_utils import split_mantle_region_prefix + ( api_base, dynamic_api_key, ) = litellm.BedrockMantleChatConfig()._get_openai_compatible_provider_info( api_base, api_key, litellm_params=litellm_params, model=model ) + model = split_mantle_region_prefix(model)[1] # rebind-ok: the prefix is routing only, not a Mantle model id elif custom_llm_provider == "nvidia_nim": # nvidia_nim is openai compatible, we just need to set this to custom_openai and have the api_base be https://api.endpoints.anyscale.com/v1 api_base = api_base or get_secret("NVIDIA_NIM_API_BASE") or "https://integrate.api.nvidia.com/v1" diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py index 2d3a99abe81..9ba9fd082f3 100644 --- a/litellm/litellm_core_utils/litellm_logging.py +++ b/litellm/litellm_core_utils/litellm_logging.py @@ -454,6 +454,17 @@ def _resolve_vertex_location_for_cost( return VertexBase.get_vertex_region(configured_location, model) +def _resolve_mantle_region_for_cost( + custom_llm_provider: str | None, + litellm_params: Mapping[str, object] | None, +) -> str | None: + if custom_llm_provider != "bedrock_mantle": + return None + from litellm.llms.bedrock_mantle.common_utils import resolve_mantle_region + + return resolve_mantle_region(litellm_params or MappingProxyType({})) + + def _provider_response_id(source: object) -> str | None: candidate: Final = source.get("id") if isinstance(source, dict) else getattr(source, "id", None) return candidate if isinstance(candidate, str) and candidate else None @@ -545,7 +556,7 @@ class Logging(LiteLLMLoggingBaseClass): # ids leaking into a different, later request on the same thread. Sync # support is deferred to a follow-up PR with its own safe-restore # mechanism; async calls (the proxy's only call path) are unaffected. - if supports_correlation_logging: + if supports_correlation_logging and litellm.request_correlation_in_logs: set_trace_id(self.litellm_trace_id) set_session_id(self.litellm_session_id) # set_trace_id()/set_session_id() sanitize (strip control chars, bound @@ -1768,6 +1779,10 @@ class Logging(LiteLLMLoggingBaseClass): optional_params=self.optional_params, model=litellm_model_name or self.model, ), + "region_name": _resolve_mantle_region_for_cost( + custom_llm_provider=self.model_call_details.get("custom_llm_provider", None), + litellm_params=self.model_call_details.get("litellm_params"), + ), } except Exception as e: # error creating kwargs for cost calculation debug_info = StandardLoggingModelCostFailureDebugInformation( @@ -2427,7 +2442,7 @@ class Logging(LiteLLMLoggingBaseClass): call) would leave the outer request's subsequent log lines stamped with the nested call's trace_id/session_id instead of its own. - Uses a plain set() of the captured pre-call value rather than + Uses a plain contextvar set() of the captured pre-call value rather than contextvars.Token-based reset(), since this can end up called from a different asyncio Task/context than __init__ ran in (e.g. the request task's own wrapper() finally block, plus async_success_handler @@ -2438,8 +2453,8 @@ class Logging(LiteLLMLoggingBaseClass): that Task's view of the contextvars, so calling it multiple times (once per Task involved in this attempt) is required, not just safe. """ - set_trace_id(self._pre_call_trace_id) - set_session_id(self._pre_call_session_id) + trace_id_var.set(self._pre_call_trace_id) + session_id_var.set(self._pre_call_session_id) def _restore_correlation_context_if_unclaimed(self) -> None: """Guarded variant for __del__-triggered cleanup only. diff --git a/litellm/litellm_core_utils/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py index e5977ca4156..baa9aab1087 100644 --- a/litellm/litellm_core_utils/llm_cost_calc/utils.py +++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py @@ -9,6 +9,8 @@ from types import MappingProxyType from typing import Any, Final, Literal, TypedDict, cast from zoneinfo import ZoneInfo, ZoneInfoNotFoundError +from typing_extensions import ReadOnly + import litellm from litellm._internal_context import current_billing_time from litellm._logging import verbose_logger @@ -482,11 +484,12 @@ def apply_off_peak_pricing(model_info: ModelInfo, current_time: datetime | None, def _apply_off_peak_to_base_costs( model_info: ModelInfo, current_time: datetime | None, - base_costs: tuple[float, float, float, float, float], + base_costs: tuple[float, float, float, float | None, float], ) -> tuple[float, float, float, float, float]: """Apply off-peak rates to an already-resolved set of base costs, whichever pricing path - produced them. The one-hour cache-creation rate passes through untouched, since - off_peak_pricing has no field for it, and reasoning is left to _resolve_billed_reasoning_rate. + produced them. off_peak_pricing has no field for the one-hour cache-creation rate, so a + present one passes through untouched and an absent one resolves to the applied + cache-creation rate. Reasoning is left to _resolve_billed_reasoning_rate. """ prompt, completion, cache_creation, cache_creation_above_1hr, cache_read = base_costs rates: Final = apply_off_peak_pricing( @@ -504,7 +507,7 @@ def _apply_off_peak_to_base_costs( rates.input_rate, rates.output_rate, rates.cache_creation_rate, - cache_creation_above_1hr, + rates.cache_creation_rate if cache_creation_above_1hr is None else cache_creation_above_1hr, rates.cache_read_rate, ) @@ -530,6 +533,11 @@ def _get_token_base_cost( `missing_cache_read_uses_input` resolves an absent cache-read rate to the resolved input rate instead of 0.0; an explicit 0.0 rate stays a real price either way. + An absent cache-creation rate always resolves to the resolved input rate, the way the + tiered table and custom deployment pricing already do, since a provider that publishes + no write price bills cache writes as ordinary input. An absent 1h write rate resolves + to the cache-creation rate, off-peak included. An explicit 0.0 stays a real price for both. + Returns: Tuple[float, float, float, float] - (prompt_cost, completion_cost, cache_creation_cost, cache_read_cost) """ @@ -552,10 +560,9 @@ def _get_token_base_cost( output_image_cost: Final = _get_cost_per_unit(model_info, "output_cost_per_image_token", None) if output_image_cost is not None: completion_base_cost = cast(float, output_image_cost) - cache_creation_cost = cast(float, _get_cost_per_unit(model_info, cache_creation_cost_key)) - cache_creation_cost_above_1hr = cast( - float, - _get_cost_per_unit(model_info, "cache_creation_input_token_cost_above_1hr"), + cache_creation_cost = _get_cost_per_unit(model_info, cache_creation_cost_key, default_value=None) + cache_creation_cost_above_1hr = _get_cost_per_unit( + model_info, "cache_creation_input_token_cost_above_1hr", default_value=None ) cache_read_cost = _get_cost_per_unit(model_info, cache_read_cost_key, default_value=None) @@ -637,22 +644,10 @@ def _get_token_base_cost( else f"cache_read_input_token_cost_above_{threshold_str}_tokens" ) - cache_creation_cost = cast( - float, - _get_cost_per_unit( - model_info, - cache_creation_tiered_key, - cache_creation_cost, - ), - ) + cache_creation_cost = _get_cost_per_unit(model_info, cache_creation_tiered_key, cache_creation_cost) - cache_creation_cost_above_1hr = cast( - float, - _get_cost_per_unit( - model_info, - cache_creation_1hr_tiered_key, - cache_creation_cost_above_1hr, - ), + cache_creation_cost_above_1hr = _get_cost_per_unit( + model_info, cache_creation_1hr_tiered_key, cache_creation_cost_above_1hr ) cache_read_cost = _get_cost_per_unit(model_info, cache_read_tiered_key, cache_read_cost) @@ -663,16 +658,16 @@ def _get_token_base_cost( except Exception: continue + input_rate_for_missing_cache_rates: Final = _off_peak_rate( + _open_off_peak_block(model_info, current_time) or MappingProxyType({}), + "input_cost_per_token", + prompt_base_cost, + ) if cache_read_cost is None: - cache_read_cost = ( - _off_peak_rate( - _open_off_peak_block(model_info, current_time) or MappingProxyType({}), - "input_cost_per_token", - prompt_base_cost, - ) - if missing_cache_read_uses_input - else 0.0 - ) + cache_read_cost = input_rate_for_missing_cache_rates if missing_cache_read_uses_input else 0.0 + resolved_cache_creation_cost: Final = ( + input_rate_for_missing_cache_rates if cache_creation_cost is None else cache_creation_cost + ) return _apply_off_peak_to_base_costs( model_info, @@ -680,7 +675,7 @@ def _get_token_base_cost( ( prompt_base_cost, completion_base_cost, - cache_creation_cost, + resolved_cache_creation_cost, cache_creation_cost_above_1hr, cache_read_cost, ), @@ -772,6 +767,7 @@ def calculate_cache_writing_cost( class PromptTokensDetailsResult(TypedDict): cache_hit_tokens: int + cache_hit_audio_tokens: ReadOnly[int] cache_creation_tokens: int cache_creation_token_details: CacheCreationTokenDetails | None text_tokens: int @@ -802,12 +798,34 @@ def parse_prompt_tokens_details(usage: Usage) -> PromptTokensDetailsResult: ) or None ) - text_tokens: Final = ( - cast(int | None, getattr(usage.prompt_tokens_details, "text_tokens", None)) - or 0 # default to prompt tokens, if this field is not set + cached_tokens_details: Final = getattr(usage.prompt_tokens_details, "cached_tokens_details", None) + cached_audio_tokens: Final = min( + _get_token_detail_value(cached_tokens_details, "audio_tokens") or 0, cache_hit_tokens + ) + cached_text_tokens: Final = min( + _get_token_detail_value(cached_tokens_details, "text_tokens") or 0, + cache_hit_tokens - cached_audio_tokens, + ) + cached_image_tokens: Final = min( + _get_token_detail_value(cached_tokens_details, "image_tokens") or 0, + cache_hit_tokens - cached_audio_tokens - cached_text_tokens, + ) + text_tokens: Final = max( + ( + cast(int | None, getattr(usage.prompt_tokens_details, "text_tokens", None)) + or 0 # default to prompt tokens, if this field is not set + ) + - cached_text_tokens, + 0, + ) + audio_tokens: Final = max( + (cast(int | None, getattr(usage.prompt_tokens_details, "audio_tokens", 0)) or 0) - cached_audio_tokens, + 0, + ) + image_tokens: Final = max( + (cast(int | None, getattr(usage.prompt_tokens_details, "image_tokens", 0)) or 0) - cached_image_tokens, + 0, ) - audio_tokens: Final = cast(int | None, getattr(usage.prompt_tokens_details, "audio_tokens", 0)) or 0 - image_tokens: Final = cast(int | None, getattr(usage.prompt_tokens_details, "image_tokens", 0)) or 0 video_tokens: Final = _coerce_token_count(getattr(usage.prompt_tokens_details, "video_tokens", 0)) character_count: Final = ( cast( @@ -835,6 +853,7 @@ def parse_prompt_tokens_details(usage: Usage) -> PromptTokensDetailsResult: return PromptTokensDetailsResult( cache_hit_tokens=cache_hit_tokens, + cache_hit_audio_tokens=cached_audio_tokens, cache_creation_tokens=cache_creation_tokens, cache_creation_token_details=cache_creation_token_details, text_tokens=text_tokens, @@ -918,15 +937,28 @@ def _calculate_input_cost( prompt_cost = float(prompt_tokens_details["text_tokens"]) * prompt_base_cost ### CACHE READ COST - Now uses tiered pricing - prompt_cost += float(prompt_tokens_details["cache_hit_tokens"]) * cache_read_cost + 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 + ) ### AUDIO COST - if prompt_tokens_details["audio_tokens"]: + if prompt_tokens_details["audio_tokens"] and not ( + prompt_tokens_details["audio_length_seconds"] and model_info.get("input_cost_per_audio_per_second") is not None + ): audio_cost_key: Final = _get_service_tier_cost_key("input_cost_per_audio_token", service_tier) prompt_cost += calculate_cost_component(model_info, audio_cost_key, prompt_tokens_details["audio_tokens"]) ### IMAGE TOKEN COST - if prompt_tokens_details["image_tokens"]: + if prompt_tokens_details["image_tokens"] and not ( + prompt_tokens_details["image_count"] and model_info.get("input_cost_per_image") is not None + ): # For image token costs: # First check if input_cost_per_image_token is available. If not, default to generic input_cost_per_token. image_token_cost_key = "input_cost_per_image_token" @@ -935,7 +967,9 @@ def _calculate_input_cost( prompt_cost += calculate_cost_component(model_info, image_token_cost_key, prompt_tokens_details["image_tokens"]) ### VIDEO TOKEN COST - if prompt_tokens_details["video_tokens"]: + if prompt_tokens_details["video_tokens"] and not ( + prompt_tokens_details["video_length_seconds"] and model_info.get("input_cost_per_video_per_second") is not None + ): video_token_cost_key = "input_cost_per_video_token" if model_info.get(video_token_cost_key) is None: video_token_cost_key = "input_cost_per_token" @@ -1149,6 +1183,7 @@ def generic_cost_per_token( ### PROCESSING COST prompt_tokens_details = PromptTokensDetailsResult( cache_hit_tokens=0, + cache_hit_audio_tokens=0, cache_creation_tokens=0, cache_creation_token_details=None, text_tokens=usage.prompt_tokens, @@ -1319,6 +1354,7 @@ class BilledTokenRates: input_cost_per_token: float output_cost_per_token: float cache_read_input_token_cost: float + cache_read_input_audio_token_cost: float cache_creation_input_token_cost: float cache_creation_input_token_cost_above_1hr: float output_cost_per_reasoning_token: float @@ -1330,6 +1366,7 @@ class BilledTokenRates: input_cost_per_token=self.input_cost_per_token * multiplier, output_cost_per_token=self.output_cost_per_token * multiplier, cache_read_input_token_cost=self.cache_read_input_token_cost * multiplier, + cache_read_input_audio_token_cost=self.cache_read_input_audio_token_cost * multiplier, cache_creation_input_token_cost=self.cache_creation_input_token_cost * multiplier, cache_creation_input_token_cost_above_1hr=self.cache_creation_input_token_cost_above_1hr * multiplier, output_cost_per_reasoning_token=self.output_cost_per_reasoning_token * multiplier, @@ -1353,15 +1390,16 @@ def _reasoning_token_count(usage: Usage) -> int: return parsed or _coerce_token_count(getattr(usage, "reasoning_tokens", 0)) -def _cache_token_counts(usage: Usage) -> tuple[int, int, CacheCreationTokenDetails | None]: - """(cache read tokens, cache creation tokens, cache creation details): read from prompt_tokens_details - first, then the private top-level counters the Usage constructor mirrors cache tokens onto for - providers/callers that bypass the details.""" +def _cache_token_counts(usage: Usage) -> tuple[int, int, int, CacheCreationTokenDetails | None]: + """(cache read tokens, cached audio tokens, cache creation tokens, cache creation details): read from + prompt_tokens_details first, then the private top-level counters the Usage constructor mirrors cache + tokens onto for providers/callers that bypass the details.""" parsed: Final = parse_prompt_tokens_details(usage) if usage.prompt_tokens_details is not None else None parsed_read: Final = parsed["cache_hit_tokens"] if parsed is not None else 0 parsed_creation: Final = parsed["cache_creation_tokens"] if parsed is not None else 0 return ( parsed_read or _coerce_token_count(getattr(usage, "_cache_read_input_tokens", 0)), + parsed["cache_hit_audio_tokens"] if parsed is not None else 0, parsed_creation or _coerce_token_count(getattr(usage, "_cache_creation_input_tokens", 0)), parsed["cache_creation_token_details"] if parsed is not None else None, ) @@ -1372,11 +1410,13 @@ def _custom_pricing_rates(custom_cost_per_token: CostPerToken) -> BilledTokenRat cache rates (else the input rate) and reasoning at the output rate, as _cost_per_token_custom_pricing_helper does.""" input_rate: Final = custom_cost_per_token["input_cost_per_token"] output_rate: Final = custom_cost_per_token["output_cost_per_token"] + cache_read_rate: Final = custom_cost_per_token.get("cache_read_input_token_cost", input_rate) cache_creation_rate: Final = custom_cost_per_token.get("cache_creation_input_token_cost", input_rate) return BilledTokenRates( input_cost_per_token=input_rate, output_cost_per_token=output_rate, - cache_read_input_token_cost=custom_cost_per_token.get("cache_read_input_token_cost", input_rate), + cache_read_input_token_cost=cache_read_rate, + cache_read_input_audio_token_cost=cache_read_rate, cache_creation_input_token_cost=cache_creation_rate, cache_creation_input_token_cost_above_1hr=cache_creation_rate, output_cost_per_reasoning_token=output_rate, @@ -1413,6 +1453,11 @@ def _cost_map_billed_rates( completion_base_cost=completion_base_cost, current_time=billing_time, ) + 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, + ) multiplier: Final = ( _get_regional_uplift_multiplier(model_info, data_residency) * get_vertex_regional_endpoint_uplift(model_info, vertex_location) @@ -1422,6 +1467,9 @@ def _cost_map_billed_rates( input_cost_per_token=prompt_base_cost, output_cost_per_token=completion_base_cost, cache_read_input_token_cost=cache_read_cost_rate, + cache_read_input_audio_token_cost=( + audio_cache_read_rate if audio_cache_read_rate is not None else cache_read_cost_rate + ), cache_creation_input_token_cost=cache_creation_cost_rate, cache_creation_input_token_cost_above_1hr=cache_creation_cost_above_1hr_rate, output_cost_per_reasoning_token=reasoning_rate, @@ -1494,7 +1542,9 @@ def get_token_type_cost_breakdown( if rates is None: return TokenTypeCostBreakdown(0.0, 0.0, 0.0) - cache_read_tokens, cache_creation_tokens, cache_creation_token_details = _cache_token_counts(usage) + cache_read_tokens, cached_audio_tokens, cache_creation_tokens, cache_creation_token_details = _cache_token_counts( + usage + ) cache_creation_cost: Final = ( float(cache_creation_tokens) * rates.cache_creation_input_token_cost if custom_cost_per_token is not None @@ -1507,7 +1557,10 @@ 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) * rates.cache_read_input_token_cost, + cache_read_cost=( + float(cache_read_tokens - cached_audio_tokens) * rates.cache_read_input_token_cost + + float(cached_audio_tokens) * rates.cache_read_input_audio_token_cost + ), cache_creation_cost=cache_creation_cost, rates=rates, ) diff --git a/litellm/litellm_core_utils/logging_worker.py b/litellm/litellm_core_utils/logging_worker.py index 1d74595781a..5ccc5632646 100644 --- a/litellm/litellm_core_utils/logging_worker.py +++ b/litellm/litellm_core_utils/logging_worker.py @@ -18,11 +18,16 @@ from litellm.constants import ( LOGGING_WORKER_CONCURRENCY, LOGGING_WORKER_MAX_QUEUE_SIZE, LOGGING_WORKER_MAX_TIME_PER_COROUTINE, + LOGGING_WORKER_TIMEOUT_SUMMARY_WINDOW_SECONDS, MAX_ITERATIONS_TO_CLEAR_QUEUE, MAX_TIME_TO_CLEAR_QUEUE, ) +def _coroutine_name(coroutine: Coroutine) -> str: + return getattr(coroutine, "__qualname__", None) or getattr(coroutine, "__name__", None) or type(coroutine).__name__ + + class LoggingTask(TypedDict): """ A logging task with its associated context to ensure logging is executed in @@ -47,10 +52,12 @@ class LoggingWorker: timeout: float = LOGGING_WORKER_MAX_TIME_PER_COROUTINE, max_queue_size: int = LOGGING_WORKER_MAX_QUEUE_SIZE, concurrency: int = LOGGING_WORKER_CONCURRENCY, + timeout_summary_window: float = LOGGING_WORKER_TIMEOUT_SUMMARY_WINDOW_SECONDS, ): self.timeout = timeout self.max_queue_size = max_queue_size self.concurrency = concurrency + self.timeout_summary_window = timeout_summary_window self._queue: asyncio.Queue[LoggingTask] | None = None self._worker_task: asyncio.Task | None = None self._running_tasks: set[asyncio.Task] = set() @@ -59,6 +66,10 @@ class LoggingWorker: self._bound_loop: asyncio.AbstractEventLoop | None = None self._last_aggressive_clear_time: float = 0.0 self._aggressive_clear_in_progress: bool = False + self._timeout_total: int = 0 + self._timeout_burst_count: int = 0 + self._timeout_last_callback: str | None = None + self._timeout_summary_task: asyncio.Task | None = None # Register cleanup handler to flush remaining events on exit atexit.register(self._flush_on_exit) @@ -136,6 +147,8 @@ class LoggingWorker: self._sem = None self._worker_task = None self._running_tasks.clear() + self._timeout_summary_task = None + self._timeout_burst_count = 0 self._queue = new_queue self._bound_loop = current_loop return @@ -156,12 +169,15 @@ class LoggingWorker: """Runs the logging task and handles cleanup. Releases semaphore when done.""" try: if self._queue is not None: + # Run the coroutine in its original context + callback_task: Final = task["context"].run(asyncio.create_task, task["coroutine"]) try: - # Run the coroutine in its original context - await asyncio.wait_for( - task["context"].run(asyncio.create_task, task["coroutine"]), - timeout=self.timeout, - ) + await asyncio.wait_for(callback_task, timeout=self.timeout) + except asyncio.TimeoutError as e: + if callback_task.cancelled(): + self._record_callback_timeout(task["coroutine"]) + else: + verbose_logger.exception("LoggingWorker error: %s", e) except Exception as e: verbose_logger.exception("LoggingWorker error: %s", e) finally: @@ -171,6 +187,35 @@ class LoggingWorker: # Always release semaphore, even if queue is None sem.release() + def _record_callback_timeout(self, coroutine: Coroutine) -> None: + """Count a callback timeout and arm a debounced summary, so a burst of timeouts + (e.g. a slow Redis timing out many callbacks at once) logs one bounded line rather + than a full ERROR stacktrace per callback.""" + self._timeout_total += 1 + self._timeout_burst_count += 1 + self._timeout_last_callback = _coroutine_name(coroutine) + if self._timeout_summary_task is None or self._timeout_summary_task.done(): + self._timeout_summary_task = asyncio.create_task(self._flush_timeout_summary()) + + async def _flush_timeout_summary(self) -> None: + """After the burst settles, log one bounded summary covering every timeout in it.""" + await asyncio.sleep(self.timeout_summary_window) + self._emit_timeout_summary() + + def _emit_timeout_summary(self) -> None: + """Log one bounded summary for the current burst and reset the burst counter.""" + burst_count: Final = self._timeout_burst_count + self._timeout_burst_count = 0 + if burst_count <= 0: + return + verbose_logger.warning( + "LoggingWorker: %d callback(s) timed out after %ss (callback: %s); %d timed out since start", + burst_count, + self.timeout, + self._timeout_last_callback, + self._timeout_total, + ) + async def _worker_loop(self) -> None: """Main worker loop that gets tasks and schedules them to run concurrently.""" try: @@ -406,6 +451,11 @@ class LoggingWorker: async def stop(self) -> None: """Stop the logging worker and clean up resources.""" + if self._timeout_summary_task is not None: + self._timeout_summary_task.cancel() + self._timeout_summary_task = None + self._emit_timeout_summary() + if self._worker_task is None and not self._running_tasks: # No worker launched and no in-flight tasks to drain. return diff --git a/litellm/litellm_core_utils/prompt_templates/factory.py b/litellm/litellm_core_utils/prompt_templates/factory.py index ece619e3883..21ae8b001dd 100644 --- a/litellm/litellm_core_utils/prompt_templates/factory.py +++ b/litellm/litellm_core_utils/prompt_templates/factory.py @@ -1757,7 +1757,7 @@ def convert_to_anthropic_tool_invoke( anthropic_tool_invoke: Final[list[AnthropicMessagesToolUseParam | dict[str, object]]] = [] for tool in tool_calls: - if not get_attribute_or_key(tool, "type") == "function": + if get_attribute_or_key(tool, "type") != "function": continue tool_id = cast(str, get_attribute_or_key(tool, "id")) diff --git a/litellm/litellm_core_utils/realtime_streaming.py b/litellm/litellm_core_utils/realtime_streaming.py index 4923bdda305..fa567bdf4c9 100644 --- a/litellm/litellm_core_utils/realtime_streaming.py +++ b/litellm/litellm_core_utils/realtime_streaming.py @@ -10,6 +10,7 @@ from typing_extensions import ReadOnly import litellm from litellm._logging import redact_internal_details_from_client_message, verbose_logger +from litellm.constants import REALTIME_SESSION_FAILURE_LOGGED_KEY, REALTIME_SESSION_SUCCESS_LOGGED_KEY from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER from litellm.llms.base_llm.realtime.transformation import BaseRealtimeConfig from litellm.types.llms.openai import ( @@ -35,9 +36,6 @@ else: CLIENT_CONNECTION_CLASS = Any -REALTIME_SESSION_SUCCESS_LOGGED_KEY: Final = "realtime_session_success_logged" - - @dataclass(frozen=True, slots=True) class BackendClose: code: int @@ -445,6 +443,12 @@ class RealTimeStreaming: ) sent = False for msg in transformed: + if isinstance(msg, bytes): + await self.provider_config.pace_backend_send(msg) + await self.backend_ws.send(msg) + self._content_sent_after_setup = True + sent = True + continue try: msg_obj = _decode_json_object(msg) except (json.JSONDecodeError, TypeError): @@ -1013,7 +1017,7 @@ class RealTimeStreaming: cast(str, transcript), item_id=cast(str | None, event.get("item_id")), ) - if not blocked: + if not blocked and not self._is_transcription_session: await self._send_to_backend(json.dumps({"type": "response.create"})) continue ## LOGGING @@ -1147,6 +1151,7 @@ class RealTimeStreaming: self._logging_worker.ensure_initialized_and_enqueue( self.logging_obj.dispatch_failure_handlers(error, traceback.format_exc(), prefer_async_handlers=True) ) + self.logging_obj.model_call_details[REALTIME_SESSION_FAILURE_LOGGED_KEY] = True @staticmethod def _detect_beta_header(websocket: ScopedWebSocket) -> bool: diff --git a/litellm/litellm_core_utils/token_counter.py b/litellm/litellm_core_utils/token_counter.py index 3b128899f45..4c61fac82bb 100644 --- a/litellm/litellm_core_utils/token_counter.py +++ b/litellm/litellm_core_utils/token_counter.py @@ -454,7 +454,7 @@ def token_counter( params: Final = _MessageCountParams(model, custom_tokenizer) num_tokens = _count_messages(params, new_messages, use_default_image_token_count, default_token_count) if count_response_tokens is False: - includes_system_message: Final = any([message.get("role", None) == "system" for message in new_messages]) + includes_system_message: Final = any(message.get("role", None) == "system" for message in new_messages) num_tokens += _count_extra(params.count_function, tools, tool_choice, includes_system_message) else: diff --git a/litellm/llms/anthropic/chat/guardrail_translation/handler.py b/litellm/llms/anthropic/chat/guardrail_translation/handler.py index 9d50345d70d..2ea20143f0c 100644 --- a/litellm/llms/anthropic/chat/guardrail_translation/handler.py +++ b/litellm/llms/anthropic/chat/guardrail_translation/handler.py @@ -20,6 +20,7 @@ from itertools import chain, repeat from types import MappingProxyType from typing import TYPE_CHECKING, Any, Final, Protocol, cast, overload, runtime_checkable +from pydantic import TypeAdapter, ValidationError from typing_extensions import ReadOnly, TypedDict, assert_never from litellm._logging import verbose_proxy_logger @@ -44,6 +45,7 @@ from litellm.llms.base_llm.guardrail_translation.utils import ( scoped_structured_message_indices, stream_item_field, stream_item_fingerprint, + unappliable_request_rewrite, ) from litellm.proxy.pass_through_endpoints.llm_provider_handlers.anthropic_passthrough_logging_handler import ( AnthropicPassthroughLoggingHandler, @@ -103,9 +105,24 @@ class ToolResultBlockTextTarget: block_idx: int -InputWriteBackTarget = ( - MessageContentTarget | ContentBlockTextTarget | ToolResultStringTarget | ToolResultBlockTextTarget -) +@dataclass(frozen=True, slots=True) +class SystemStringTarget: + pass + + +@dataclass(frozen=True, slots=True) +class SystemBlockTextTarget: + block_idx: int + + +@dataclass(frozen=True, slots=True) +class ToolUseInputTarget: + msg_idx: int + content_idx: int + + +MessageTextTarget = MessageContentTarget | ContentBlockTextTarget | ToolResultStringTarget | ToolResultBlockTextTarget +InputWriteBackTarget = SystemStringTarget | SystemBlockTextTarget | MessageTextTarget def _as_str_mapping(value: Mapping[str, object]) -> Mapping[str, object]: @@ -146,10 +163,17 @@ class ScannedText: target: InputWriteBackTarget +@dataclass(frozen=True, slots=True) +class ScannedToolCall: + tool_call: ChatCompletionToolCallChunk + target: ToolUseInputTarget + + @dataclass(frozen=True, slots=True) class ExtractedInput: scanned: tuple[ScannedText, ...] images: tuple[str, ...] + tool_calls: tuple[ScannedToolCall, ...] = () EMPTY_EXTRACTED_INPUT: Final = ExtractedInput(scanned=(), images=()) @@ -161,6 +185,74 @@ class _ToolCallShape: arguments: str +def _is_client_tool_use(block: Mapping[str, object]) -> bool: + return ( + block.get("type") == "tool_use" + and isinstance(block.get("id"), str) + and isinstance(block.get("name"), str) + and isinstance(block.get("input"), dict) + ) + + +def _write_back_system_block(system: object, block_idx: int, response: str) -> None: + if not isinstance(system, list): + return + text_blocks: Final = tuple(block for block in system if isinstance(block, dict) and block.get("type") == "text") + if block_idx < len(text_blocks): + text_blocks[block_idx]["text"] = ( + response # mutable-ok: guardrails rewrite the caller's request payload in place + ) + + +def _write_back_message_text(message: _WritableMessage, target: MessageTextTarget, response: str) -> None: + content: Final = message.get("content", None) + if content is None: + return + match target: + case MessageContentTarget(): + if isinstance(content, str): + message["content"] = response # mutable-ok: guardrails rewrite the caller's request payload in place + case ContentBlockTextTarget(content_idx=content_idx): + if isinstance(content, list): + content[content_idx]["text"] = ( + response # mutable-ok: guardrails rewrite the caller's request payload in place + ) + case ToolResultStringTarget(content_idx=content_idx): + if isinstance(content, list): + content[content_idx]["content"] = ( + response # mutable-ok: guardrails rewrite the caller's request payload in place + ) + case ToolResultBlockTextTarget(content_idx=content_idx, block_idx=block_idx): + if isinstance(content, list): + content[content_idx]["content"][block_idx]["text"] = ( + response # mutable-ok: guardrails rewrite the caller's request payload in place + ) + case _: + assert_never(target) + + +_TOOL_USE_INPUT_ADAPTER: Final = TypeAdapter(dict[str, object]) + + +def _rewritten_tool_use_input(arguments: str) -> Mapping[str, object] | None: + try: + return _TOOL_USE_INPUT_ADAPTER.validate_json(arguments) + except ValidationError: + return None + + +def _write_back_tool_use( + message: _WritableMessage, target: ToolUseInputTarget, shape: _ToolCallShape, rewritten_input: Mapping[str, object] +) -> None: + content: Final = message.get("content", None) + block: Final = content[target.content_idx] if isinstance(content, list) else None + if not isinstance(block, dict): + return + block["input"] = rewritten_input # mutable-ok: guardrails rewrite the caller's request payload in place + if shape.name is not None and shape.name != block.get("name"): + block["name"] = shape.name # mutable-ok: guardrails rewrite the caller's request payload in place + + @dataclass(frozen=True, slots=True) class _SSEFieldRewrite: """One field of one nested section of a buffered SSE event, rewritten.""" @@ -452,9 +544,8 @@ class AnthropicMessagesHandler(BaseTranslation): skip_tool: Final = effective_skip_tool_message_for_guardrail(guardrail_to_apply) scan_only_tool_results: Final = effective_scan_only_tool_results_for_guardrail(guardrail_to_apply) - # Exclude only the trusted top-level prompt. In-sequence system entries are untrusted - # and must stay aligned with texts_to_check for positional masking. When the top-level - # prompt is included, the pre-existing count mismatch disables positional masking. + # 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 = { # mutable-ok: API message payload key: value for key, value in data.items() if key != "system" } @@ -490,7 +581,12 @@ class AnthropicMessagesHandler(BaseTranslation): ] ) - # Step 1: Extract all text content and images + # Step 1: Extract all text content, images, and tool calls + top_level_system_scanned: Final = ( + () + if hoisted_system_message is None or scan_only_tool_results + else self._extract_top_level_system_text(hoisted_system_message) + ) extracted: Final = tuple( self._extract_input_text_and_images( message=message, @@ -501,17 +597,27 @@ class AnthropicMessagesHandler(BaseTranslation): ) for msg_idx, message in enumerate(messages) ) - scanned: Final = tuple(item for one_message in extracted for item in one_message.scanned) + scanned: Final = ( + *top_level_system_scanned, + *(item for one_message in extracted for item in one_message.scanned), + ) texts_to_check: Final = [item.text for item in scanned] # mutable-ok: GenericGuardrailAPIInputs takes list[str] images_to_check: Final = [ image for one_message in extracted for image in one_message.images ] # mutable-ok: GenericGuardrailAPIInputs takes list[str] + scanned_tool_calls: Final = tuple(item for one_message in extracted for item in one_message.tool_calls) + tool_calls_to_check: Final = [ + item.tool_call for item in scanned_tool_calls + ] # mutable-ok: GenericGuardrailAPIInputs takes list[ChatCompletionToolCallChunk] + pre_guardrail_tool_calls: Final = _tool_call_shapes(tool_calls_to_check) - # Step 2: Apply guardrail to all texts in batch - if texts_to_check: + # Step 2: Apply guardrail to all texts and tool calls in batch + if texts_to_check or tool_calls_to_check: inputs: Final = GenericGuardrailAPIInputs(texts=texts_to_check) if images_to_check: inputs["images"] = images_to_check + if tool_calls_to_check: + inputs["tool_calls"] = tool_calls_to_check if tools_to_check: inputs["tools"] = tools_to_check original_structured_messages: Final = structured_messages @@ -570,9 +676,18 @@ class AnthropicMessagesHandler(BaseTranslation): preserve_system_messages=has_midturn_system_message, ) else: + if guardrailed_texts and len(guardrailed_texts) != len(scanned): + raise unappliable_request_rewrite(guardrail_to_apply.guardrail_name) + self._apply_guardrail_tool_calls_to_input( + messages=messages, + scanned_tool_calls=scanned_tool_calls, + pre_guardrail_tool_calls=pre_guardrail_tool_calls, + returned_tool_calls=guardrailed_inputs.get("tool_calls"), + guardrail_name=guardrail_to_apply.guardrail_name, + ) # Step 3: Map guardrail responses back to original message structure await self._apply_guardrail_responses_to_input( - messages=messages, + data=data, responses=guardrailed_texts, scanned=scanned, ) @@ -598,6 +713,19 @@ class AnthropicMessagesHandler(BaseTranslation): hoisted: Final = probe.get("messages") or [] # mutable-ok: API message payload return hoisted[0] if hoisted else None + @staticmethod + def _extract_top_level_system_text(hoisted_system_message: AllMessageValues) -> tuple[ScannedText, ...]: + content: Final = hoisted_system_message.get("content") + if isinstance(content, str): + return (ScannedText(content, SystemStringTarget()),) + if not isinstance(content, list): + return () + return tuple( + ScannedText(text_str, SystemBlockTextTarget(block_idx)) + for block_idx, block in enumerate(content) + if isinstance(block, dict) and isinstance(text_str := block.get("text"), str) + ) + @staticmethod def _openai_system_message_to_anthropic( message: Mapping[str, object], @@ -852,9 +980,25 @@ class AnthropicMessagesHandler(BaseTranslation): for content_idx, content_item in enumerate(content) if isinstance(content_item, dict) ) + tool_use_blocks: Final = ( + () + if scan_only_tool_results + else tuple( + (content_idx, content_item) + for content_idx, content_item in enumerate(content) + if isinstance(content_item, dict) and _is_client_tool_use(content_item) + ) + ) return ExtractedInput( scanned=tuple(item for block in blocks for item in block.scanned), images=tuple(image for block in blocks for image in block.images), + tool_calls=tuple( + ScannedToolCall( + tool_call=AnthropicConfig.convert_tool_use_to_openai_format(content_item, tool_call_idx), + target=ToolUseInputTarget(msg_idx, content_idx), + ) + for tool_call_idx, (content_idx, content_item) in enumerate(tool_use_blocks) + ), ) @classmethod @@ -940,43 +1084,59 @@ class AnthropicMessagesHandler(BaseTranslation): async def _apply_guardrail_responses_to_input( self, - messages: Sequence[_WritableMessage], - responses: list[str], + data: dict[str, object], # mutable-ok: API message payload + responses: Sequence[str], scanned: tuple[ScannedText, ...], ) -> None: """ - Apply guardrail responses back to input messages. + Apply guardrail responses back to the top-level system prompt and the input messages. """ + raw_messages: Final = data.get("messages") + messages: Final[Sequence[_WritableMessage]] = raw_messages if isinstance(raw_messages, list) else () for item, guardrail_response in zip(scanned, responses): - target = item.target - message = messages[target.msg_idx] - content = message.get("content", None) - if content is None: - continue - - match target: - case MessageContentTarget(): - if isinstance(content, str): - message["content"] = ( - guardrail_response # mutable-ok: guardrails rewrite the caller's request payload in place - ) - case ContentBlockTextTarget(content_idx=content_idx): - if isinstance(content, list): - content[content_idx]["text"] = ( - guardrail_response # mutable-ok: guardrails rewrite the caller's request payload in place - ) - case ToolResultStringTarget(content_idx=content_idx): - if isinstance(content, list): - content[content_idx]["content"] = ( - guardrail_response # mutable-ok: guardrails rewrite the caller's request payload in place - ) - case ToolResultBlockTextTarget(content_idx=content_idx, block_idx=block_idx): - if isinstance(content, list): - content[content_idx]["content"][block_idx]["text"] = ( + match item.target: + case SystemStringTarget(): + if isinstance(data.get("system"), str): + data["system"] = ( guardrail_response # mutable-ok: guardrails rewrite the caller's request payload in place ) + case SystemBlockTextTarget(block_idx=block_idx): + _write_back_system_block(data.get("system"), block_idx, guardrail_response) + case ( + MessageContentTarget() + | ContentBlockTextTarget() + | ToolResultStringTarget() + | ToolResultBlockTextTarget() as message_target + ): + _write_back_message_text(messages[message_target.msg_idx], message_target, guardrail_response) case _: - assert_never(target) + assert_never(item.target) + + @staticmethod + def _apply_guardrail_tool_calls_to_input( + messages: Sequence[_WritableMessage], + scanned_tool_calls: tuple[ScannedToolCall, ...], + pre_guardrail_tool_calls: tuple[_ToolCallShape, ...], + returned_tool_calls: Sequence[object] | None, + guardrail_name: str | None, + ) -> None: + post_guardrail_tool_calls: Final = _tool_call_shapes( + returned_tool_calls + if returned_tool_calls is not None and len(returned_tool_calls) == len(pre_guardrail_tool_calls) + else tuple(item.tool_call for item in scanned_tool_calls) + ) + rewritten: Final = tuple( + (item, after, _rewritten_tool_use_input(after.arguments)) + for item, before, after in zip(scanned_tool_calls, pre_guardrail_tool_calls, post_guardrail_tool_calls) + if before != after + ) + applicable: Final = tuple( + (item, after, rewritten_input) for item, after, rewritten_input in rewritten if rewritten_input is not None + ) + if len(applicable) != len(rewritten): + raise unappliable_request_rewrite(guardrail_name) + for item, after, rewritten_input in applicable: + _write_back_tool_use(messages[item.target.msg_idx], item.target, after, rewritten_input) async def process_output_response( self, diff --git a/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py b/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py index 9158ff4569f..e7179aad25b 100644 --- a/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py +++ b/litellm/llms/anthropic/experimental_pass_through/adapters/streaming_iterator.py @@ -19,6 +19,8 @@ from typing_extensions import assert_never from litellm._logging import verbose_logger from litellm._uuid import uuid +from litellm.exceptions import MidStreamFallbackError +from litellm.llms.base_llm.chat.transformation import BaseLLMException from litellm.types.llms.anthropic import ( AppliedEdit, CompactionBlock, @@ -58,6 +60,25 @@ def _optional_attr_sequence(obj: object, name: str) -> Sequence[object]: return value if value else () +def _error_status_and_message(exc: Exception) -> tuple[int, str]: + if isinstance(exc, (BaseLLMException, MidStreamFallbackError)): + return exc.status_code, exc.message + return 500, str(exc) or "Upstream stream ended before completion" + + +def _mid_stream_error_sse_event(exc: Exception) -> bytes: + from litellm.anthropic_interface.exceptions.exception_mapping_utils import ( + AnthropicExceptionMapping, + ) + + status_code, message = _error_status_and_message(exc) + error_response = AnthropicExceptionMapping.transform_to_anthropic_error( + status_code=status_code, + raw_message=message, + ) + return f"event: error\ndata: {json.dumps(error_response)}\n\n".encode() + + def _delta_payload_field(delta_type: StreamingContentBlockDeltaType) -> str: match delta_type: case "text_delta": @@ -990,14 +1011,17 @@ class AnthropicStreamWrapper(AdapterCompletionStreamWrapper): Async version of anthropic_sse_wrapper. Convert AnthropicStreamWrapper dict chunks to Server-Sent Events format. """ - async for chunk in self: - if isinstance(chunk, dict): - event_type: str = str(chunk.get("type", "message")) - payload = f"event: {event_type}\ndata: {json.dumps(chunk)}\n\n" - yield payload.encode() - else: - # For non-dict chunks, forward the original value unchanged - yield chunk + try: + async for chunk in self: + if isinstance(chunk, dict): + event_type: str = str(chunk.get("type", "message")) + payload = f"event: {event_type}\ndata: {json.dumps(chunk)}\n\n" + yield payload.encode() + else: + yield chunk + except Exception as e: # noqa: BLE001 # boundary before the socket: any upstream failure becomes an Anthropic error event + verbose_logger.exception("Anthropic Adapter - mid-stream error, emitting Anthropic error event: %s", e) + yield _mid_stream_error_sse_event(e) def _increment_content_block_index(self): self.current_content_block_index += 1 diff --git a/litellm/llms/anthropic/prompt_cache_prediction.py b/litellm/llms/anthropic/prompt_cache_prediction.py new file mode 100644 index 00000000000..e69a02bd93a --- /dev/null +++ b/litellm/llms/anthropic/prompt_cache_prediction.py @@ -0,0 +1,388 @@ +from __future__ import annotations + +import hashlib +import json +from collections.abc import Mapping, Sequence +from dataclasses import dataclass +from itertools import accumulate +from types import MappingProxyType +from typing import Annotated, Final, Literal, Protocol, TypeAlias + +import httpx +from pydantic import BaseModel, ConfigDict, Field, JsonValue, StrictInt, TypeAdapter, ValidationError + +import litellm +from litellm.llms.anthropic.common_utils import AnthropicModelInfo, is_anthropic_oauth_key +from litellm.llms.anthropic.count_tokens.handler import AnthropicCountTokensHandler +from litellm.llms.anthropic.experimental_pass_through.messages.transformation import DEFAULT_ANTHROPIC_API_VERSION +from litellm.types.router import LiteLLM_Params +from litellm.types.utils import ModelResponse + +_JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) +_HEADERS: Final = TypeAdapter(dict[str, str]) +_counter: Final = AnthropicCountTokensHandler() + + +_NATIVE_HEADERS: Final = frozenset( + ( + "host", + "accept", + "accept-encoding", + "connection", + "user-agent", + "content-length", + "content-type", + "x-api-key", + "anthropic-version", + ) +) + +_DEPLOYMENT_OPTIONS: Final = frozenset( + { + "model", + "api_key", + "api_base", + "custom_llm_provider", + "rpm", + "tpm", + "timeout", + "stream_timeout", + "max_retries", + "num_retries", + "max_parallel_requests", + "input_cost_per_token", + "output_cost_per_token", + "cache_read_input_token_cost", + "cache_creation_input_token_cost", + "cache_creation_input_token_cost_above_1hr", + } +) + + +class _StrictModel(BaseModel): + model_config = ConfigDict(extra="forbid", frozen=True, strict=True) + + +class _CacheControl(_StrictModel): + type: Literal["ephemeral"] + ttl: Literal["5m", "1h"] = "5m" + + +class _Text(_StrictModel): + type: Literal["text"] + text: str = Field(min_length=1, pattern=r"\S") + cache_control: _CacheControl | None = None + + +class _ToolUse(_StrictModel): + type: Literal["tool_use"] + id: str = Field(min_length=1) + name: str = Field(min_length=1) + input: Mapping[str, JsonValue] + cache_control: _CacheControl | None = None + + +class _ResultText(_StrictModel): + type: Literal["text"] + text: str + + +class _ToolResult(_StrictModel): + type: Literal["tool_result"] + tool_use_id: str = Field(min_length=1) + content: str | Annotated[tuple[_ResultText, ...], Field(strict=False)] + is_error: bool | None = None + cache_control: _CacheControl | None = None + + +_Block: TypeAlias = Annotated[_Text | _ToolUse | _ToolResult, Field(discriminator="type")] + + +class _Message(_StrictModel): + role: Literal["user", "assistant"] + content: str | Annotated[tuple[_Block, ...], Field(strict=False)] + + def blocks(self) -> tuple[_Text | _ToolUse | _ToolResult, ...]: + return (_Text(type="text", text=self.content),) if isinstance(self.content, str) else tuple(self.content) + + +class _Tool(_StrictModel): + name: str = Field(min_length=1) + description: str | None = None + input_schema: Mapping[str, JsonValue] + type: Literal["custom"] | None = None + + +class _Request(_StrictModel): + messages: tuple[_Message, ...] = Field(min_length=1, strict=False) + system: str | Annotated[tuple[_ResultText, ...], Field(strict=False)] | None = None + tools: Annotated[tuple[_Tool, ...], Field(strict=False)] | None = None + model: str | None = None + max_tokens: int | None = None + stream: bool | None = None + temperature: float | int | None = None + top_p: float | int | None = None + top_k: int | None = None + stop_sequences: Annotated[tuple[str, ...], Field(strict=False)] | None = None + metadata: Mapping[str, JsonValue] | None = None + + +@dataclass(frozen=True, slots=True) +class PromptPrefix: + prefix_body: Mapping[str, JsonValue] + fingerprint: str + fingerprints: tuple[str, ...] + ttl_seconds: int + + +def _digest(value: object) -> str: + return hashlib.sha256( + json.dumps(value, sort_keys=True, separators=(",", ":"), ensure_ascii=False).encode() + ).hexdigest() + + +def _next_digest(previous: str, boundary: tuple[int, str, Mapping[str, JsonValue]]) -> str: + return _digest((previous, boundary)) + + +def parse_prompt(body: Mapping[str, JsonValue]) -> PromptPrefix | None: + try: + request: Final = _Request.model_validate(body) + blocks: Final = tuple(message.blocks() for message in request.messages) + except ValidationError: + return None + markers: Final = tuple( + (message_index, block_index, block.cache_control) + for message_index, message_blocks in enumerate(blocks) + for block_index, block in enumerate(message_blocks) + if block.cache_control is not None + ) + if len(markers) != 1: + return None + message_end, block_end, marker = markers[0] + normalized: Final = _JSON_OBJECT.validate_python(request.model_dump(mode="json", exclude_none=True)) + context: Final = MappingProxyType({key: normalized[key] for key in ("system", "tools") if key in normalized}) + boundaries: Final = tuple( + ( + message_index, + request.messages[message_index].role, + _JSON_OBJECT.validate_python( + block.model_dump(mode="json", exclude=MappingProxyType({"cache_control": True}), exclude_none=True) + ), + ) + for message_index, message_blocks in enumerate(blocks[: message_end + 1]) + for block_index, block in enumerate(message_blocks) + if message_index < message_end or block_index <= block_end + ) + hashes: Final = tuple( + accumulate(boundaries, _next_digest, initial=_digest((_JSON_OBJECT.validate_python(context), marker.ttl))) + )[1:] + prefix_messages: Final = tuple( + _Message( + role=request.messages[message_index].role, + content=tuple( + block + for block_index, block in enumerate(message_blocks) + if message_index < message_end or block_index <= block_end + ), + ) + for message_index, message_blocks in enumerate(blocks[: message_end + 1]) + ) + return PromptPrefix( + prefix_body=MappingProxyType( + _JSON_OBJECT.validate_python( + _Request(messages=prefix_messages, system=request.system, tools=request.tools).model_dump( + mode="json", exclude_none=True + ) + ) + ), + fingerprint=hashes[-1], + fingerprints=tuple(reversed(hashes[-20:])), + ttl_seconds=3600 if marker.ttl == "1h" else 300, + ) + + +def cache_scope( + caller_key_hash: str, + deployment_id: str, + provider_key: str, + model: str, + anthropic_version: str = DEFAULT_ANTHROPIC_API_VERSION, +) -> str: + return _digest((caller_key_hash, deployment_id, provider_key, model, anthropic_version)) + + +class _TTLUsage(BaseModel): + model_config = ConfigDict(strict=True) + ephemeral_5m_input_tokens: int = Field(default=0, ge=0) + ephemeral_1h_input_tokens: int = Field(default=0, ge=0) + + +class _CacheUsage(BaseModel): + model_config = ConfigDict(strict=True) + cached_tokens: int = Field(default=0, ge=0) + cache_creation_tokens: int = Field(default=0, ge=0) + cache_creation_token_details: _TTLUsage | None = None + + +class _Usage(BaseModel): + model_config = ConfigDict(strict=True) + prompt_tokens: int = Field(ge=0) + prompt_tokens_details: _CacheUsage + + +class _Choice(BaseModel): + finish_reason: str = Field(min_length=1) + + +class _Response(BaseModel): + model_config = ConfigDict(strict=True) + model: str + usage: _Usage + choices: tuple[_Choice, ...] = Field(min_length=1, strict=False) + + +class _CountBody(BaseModel): + messages: Sequence[Mapping[str, JsonValue]] + tools: Sequence[Mapping[str, JsonValue]] | None = None + system: str | Sequence[Mapping[str, JsonValue]] | None = None + + +class _CountResult(BaseModel): + input_tokens: Annotated[StrictInt, Field(ge=0)] + + +class TokenCounter(Protocol): + async def __call__(self, model: str, api_key: str, body: Mapping[str, JsonValue]) -> int | None: ... + + +def _count_objects( + values: Sequence[Mapping[str, JsonValue]], +) -> list[dict[str, JsonValue]]: # mutable-ok: the existing provider count API requires JSON lists/dicts + return [dict(value) for value in values] # mutable-ok: serialize read-only inputs at the provider API boundary + + +async def count_prompt_tokens(model: str, api_key: str, body: Mapping[str, JsonValue]) -> int | None: + native: Final = _CountBody.model_validate(body) + try: + result: Final = _CountResult.model_validate( + await _counter.handle_count_tokens_request( + model=model, + messages=_count_objects(native.messages), + tools=_count_objects(native.tools) if native.tools is not None else None, + system=native.system, + api_key=api_key, + timeout=15.0, + ) + ) + except Exception: # noqa: BLE001 # provider/count validation failures are unavailable estimates, not zero tokens + return None + return result.input_tokens + + +@dataclass(frozen=True, slots=True) +class NativePredictionTarget: + model: str + api_key: str + + +@dataclass(frozen=True, slots=True) +class UnsupportedPredictionTarget: + reason: Literal[ + "unsupported_deployment_configuration", + "unsupported_provider_endpoint", + "unsupported_provider", + "unsupported_provider_credentials", + ] + + +def resolve_prediction_target(params: LiteLLM_Params) -> NativePredictionTarget | UnsupportedPredictionTarget: + configured_options: Final = frozenset(params.model_dump(exclude_defaults=True, exclude_none=True)) + if configured_options - _DEPLOYMENT_OPTIONS: + return UnsupportedPredictionTarget("unsupported_deployment_configuration") + api_base: Final = AnthropicModelInfo.get_api_base(params.api_base) + if api_base not in ("https://api.anthropic.com", "https://api.anthropic.com/v1/messages"): + return UnsupportedPredictionTarget("unsupported_provider_endpoint") + try: + model, provider, _, _ = litellm.get_llm_provider( + model=params.model, custom_llm_provider=params.custom_llm_provider + ) + except Exception: # noqa: BLE001 # the shared provider resolver raises for unknown deployments + return UnsupportedPredictionTarget("unsupported_provider") + if provider != "anthropic": + return UnsupportedPredictionTarget("unsupported_provider") + api_key: Final = AnthropicModelInfo.get_api_key(params.api_key) + if api_key is None or not _supported_provider_key(api_key): + return UnsupportedPredictionTarget("unsupported_provider_credentials") + return NativePredictionTarget(model=model, api_key=api_key) + + +def _supported_provider_key(api_key: str) -> bool: + return bool(api_key) and not is_anthropic_oauth_key(api_key) + + +def supported_prediction_headers(headers: Mapping[str, str]) -> bool: + return all( + name.lower() != "anthropic-beta" + and (name.lower() != "anthropic-version" or value == DEFAULT_ANTHROPIC_API_VERSION) + for name, value in headers.items() + ) + + +@dataclass(frozen=True, slots=True) +class ObservedCachePrefix: + prefix: PromptPrefix + scope: str + cached_tokens: int + cache_creation_tokens: int + + +def parse_observed_cache( + wire: httpx.Request, response_obj: ModelResponse, caller_key_hash: str, deployment_id: str +) -> ObservedCachePrefix | None: + try: + response: Final = _Response.model_validate(response_obj, from_attributes=True) + body: Final = _JSON_OBJECT.validate_json(wire.content) + headers: Final = _HEADERS.validate_python(wire.headers) + except (ValidationError, RuntimeError, httpx.RequestNotRead): + return None + if ( + wire.url.scheme != "https" + or wire.url.host != "api.anthropic.com" + or wire.url.path != "/v1/messages" + or wire.url.query + or wire.url.port not in (None, 443) + ): + return None + if ( + frozenset(headers) - _NATIVE_HEADERS + or not supported_prediction_headers(headers) + or headers.get("anthropic-version") != DEFAULT_ANTHROPIC_API_VERSION + ): + return None + provider_key: Final = headers.get("x-api-key", "") + model: Final = body.get("model") + if not _supported_provider_key(provider_key) or not isinstance(model, str) or model != response.model: + return None + prefix: Final = parse_prompt(body) + if prefix is None: + return None + usage: Final = response.usage.prompt_tokens_details + cache_tokens: Final = usage.cached_tokens + usage.cache_creation_tokens + if cache_tokens <= 0 or cache_tokens > response.usage.prompt_tokens: + return None + split: Final = usage.cache_creation_token_details + if usage.cache_creation_tokens and split is None: + return None + if split is not None and ( + split.ephemeral_5m_input_tokens + split.ephemeral_1h_input_tokens != usage.cache_creation_tokens + or (prefix.ttl_seconds == 300 and split.ephemeral_1h_input_tokens > 0) + or (prefix.ttl_seconds == 3600 and split.ephemeral_5m_input_tokens > 0) + ): + return None + return ObservedCachePrefix( + prefix=prefix, + scope=cache_scope(caller_key_hash, deployment_id, provider_key, model), + cached_tokens=cache_tokens, + cache_creation_tokens=usage.cache_creation_tokens, + ) diff --git a/litellm/llms/azure_ai/common_utils.py b/litellm/llms/azure_ai/common_utils.py index 0665b3f64c5..53a864a880a 100644 --- a/litellm/llms/azure_ai/common_utils.py +++ b/litellm/llms/azure_ai/common_utils.py @@ -144,10 +144,13 @@ class AzureFoundryModelInfo(BaseLLMModelInfo): def get_api_key(api_key: str | None = None) -> str | None: return api_key or litellm.api_key or get_secret_str("AZURE_AI_API_KEY") + @staticmethod + def get_api_version(api_version: str | None = None) -> str | None: + return api_version or litellm.api_version or get_secret_str("AZURE_API_VERSION") + @property - def api_version(self, api_version: str | None = None) -> str | None: - api_version = api_version or litellm.api_version or get_secret_str("AZURE_API_VERSION") - return api_version + def api_version(self) -> str | None: + return AzureFoundryModelInfo.get_api_version() def get_token_counter(self) -> BaseTokenCounter | None: """ diff --git a/litellm/llms/base_llm/base_utils.py b/litellm/llms/base_llm/base_utils.py index c5290b41f7b..a446a721307 100644 --- a/litellm/llms/base_llm/base_utils.py +++ b/litellm/llms/base_llm/base_utils.py @@ -50,6 +50,14 @@ class BaseLLMModelInfo(ABC): """ return None + def get_model_cost_key(self, model: str) -> str | None: + """ + Maps the model name a user sends to the key `litellm.model_cost` stores it under, when the two differ. + `get_model_info` tries this key once the exact `model` and `provider/model` keys miss. The default None means + the provider's user-facing names already match the cost map, so there is nothing extra to try. + """ + return None + @abstractmethod def get_models(self, api_key: str | None = None, api_base: str | None = None) -> list[str]: """ diff --git a/litellm/llms/base_llm/files/transformation.py b/litellm/llms/base_llm/files/transformation.py index 7a7088c2fb5..6d16a1cea69 100644 --- a/litellm/llms/base_llm/files/transformation.py +++ b/litellm/llms/base_llm/files/transformation.py @@ -1,5 +1,5 @@ from abc import ABC, abstractmethod -from collections.abc import Iterator +from collections.abc import Iterator, Mapping from typing import TYPE_CHECKING, Any, Union import httpx @@ -160,6 +160,15 @@ class BaseFilesConfig(BaseConfig): ) -> tuple[str, dict]: """Transform file list request into provider-specific format.""" + def transform_list_files_next_request( + self, + raw_response: httpx.Response, + optional_params: Mapping[str, object], + litellm_params: dict, # mutable-ok: carries provider stashes from the request transform to the response one + ) -> tuple[str, dict[str, str]] | None: + """Request for the page after `raw_response`, or None once the listing is complete.""" + return None + @abstractmethod def transform_list_files_response( self, @@ -258,7 +267,7 @@ class BaseFileEndpoints(ABC): litellm_parent_otel_span: Span | None, llm_router: Router, **data: dict, - ) -> OpenAIFileObject: + ) -> FileDeleted: pass @abstractmethod diff --git a/litellm/llms/base_llm/guardrail_translation/utils.py b/litellm/llms/base_llm/guardrail_translation/utils.py index 94a780f8148..51d43436fc9 100644 --- a/litellm/llms/base_llm/guardrail_translation/utils.py +++ b/litellm/llms/base_llm/guardrail_translation/utils.py @@ -1,8 +1,8 @@ from __future__ import annotations import json -from collections.abc import Callable, Iterator, Sequence -from typing import Final, TypeVar +from collections.abc import Callable, Iterator, Mapping, Sequence +from typing import Final, TypeVar, cast # noqa: TID251 # a rebuilt chat row has no typed constructor across roles from pydantic import BaseModel @@ -364,3 +364,67 @@ def merge_guardrailed_scoped_messages( yield from appended return list(_merged()) + + +def _content_part_text(part: object) -> str | None: + if not isinstance(part, Mapping): + return None + text: Final = part.get("text") + return text if isinstance(text, str) else None + + +def message_slot_texts(message: Mapping[str, object]) -> tuple[str, ...]: + content: Final = message.get("content") + if isinstance(content, str): + return (content,) + if isinstance(content, list): + return tuple(text for part in content if (text := _content_part_text(part)) is not None) + return () + + +def message_text_slot_count(message: AllMessageValues) -> int: + return len(message_slot_texts(message)) + + +def _part_with_text(part: object, text: str) -> object: + if not isinstance(part, Mapping): + return part + return {**part, "text": text} # mutable-ok: content parts stay JSON-plain dicts + + +def _content_with_slot_texts(content: Sequence[object], texts: Sequence[str]) -> Sequence[object]: + remaining_texts: Final = iter(texts) + return [ # mutable-ok: message content stays a JSON list + _part_with_text(part, next(remaining_texts)) if _content_part_text(part) is not None else part + for part in content + ] + + +def message_with_slot_texts(message: AllMessageValues, texts: Sequence[str]) -> AllMessageValues | None: + """Swap one rewritten text into each text slot of a chat row, in order. + + A slot is a string ``content`` or one list part carrying a string ``text``; + images and other parts ride along untouched. Returns None unless the counts + line up exactly, so a rewrite never lands on the wrong slot. + """ + if message_text_slot_count(message) != len(texts): + return None + content: Final = message.get("content") + if not isinstance(content, (str, list)): + return message + rewritten_content: Final = texts[0] if isinstance(content, str) else _content_with_slot_texts(content, texts) + rewritten: Final = {**message, "content": rewritten_content} # mutable-ok: chat rows stay JSON-plain dicts + return cast("AllMessageValues", rewritten) # cast-ok: the same row with only its text slots swapped + + +class UnappliableRequestRewrite(Exception): + def __init__(self, guardrail_name: str) -> None: + super().__init__( + f"Guardrail '{guardrail_name}' rewrote the request in a way this endpoint cannot apply, " + "so the request was rejected rather than sent unrewritten" + ) + self.guardrail_name: Final = guardrail_name + + +def unappliable_request_rewrite(guardrail_name: str | None) -> UnappliableRequestRewrite: + return UnappliableRequestRewrite(guardrail_name or "unknown") diff --git a/litellm/llms/base_llm/realtime/transformation.py b/litellm/llms/base_llm/realtime/transformation.py index cfcde7c6e9e..e44cccc1a62 100644 --- a/litellm/llms/base_llm/realtime/transformation.py +++ b/litellm/llms/base_llm/realtime/transformation.py @@ -1,4 +1,5 @@ from abc import ABC, abstractmethod +from collections.abc import Mapping, Sequence from typing import TYPE_CHECKING, Any import httpx @@ -54,9 +55,12 @@ class BaseRealtimeConfig(ABC): message: str, model: str, session_configuration_request: str | None = None, - ) -> list[str]: + ) -> Sequence[str | bytes]: pass + async def pace_backend_send(self, message: bytes) -> None: + return None + def is_setup_message(self, msg_obj: dict) -> bool: return False @@ -79,7 +83,7 @@ class BaseRealtimeConfig(ABC): model: str, logging_session_id: str, session_configuration_request: str | None = None, - ) -> dict | OpenAIRealtimeStreamSessionEvents | None: + ) -> Mapping[str, object] | OpenAIRealtimeStreamSessionEvents | None: """ Optional hook for providers that defer session setup until client `session.update`. diff --git a/litellm/llms/bedrock/base_aws_llm.py b/litellm/llms/bedrock/base_aws_llm.py index f52c1cec6a8..385d5898569 100644 --- a/litellm/llms/bedrock/base_aws_llm.py +++ b/litellm/llms/bedrock/base_aws_llm.py @@ -11,6 +11,7 @@ from concurrent.futures import ThreadPoolExecutor from datetime import datetime from functools import partial from threading import Lock +from types import MappingProxyType from typing import TYPE_CHECKING, Any, ClassVar, Final, Literal, ParamSpec, TypeVar, cast, get_args, overload import httpx @@ -96,6 +97,77 @@ def _assume_role_params( ) +_SecureTransportBool = TypedDict("_SecureTransportBool", {"aws:SecureTransport": ReadOnly[Literal["true"]]}) + + +class _SecureTransportCondition(TypedDict): + Bool: ReadOnly[_SecureTransportBool] + + +class _SessionPolicyStatement(TypedDict): + Sid: ReadOnly[str] + Effect: ReadOnly[Literal["Allow"]] + Action: ReadOnly[tuple[str, ...]] + Resource: ReadOnly[Literal["*"]] + Condition: ReadOnly[_SecureTransportCondition] + + +class WebIdentitySessionPolicy(TypedDict): + Version: ReadOnly[Literal["2012-10-17"]] + Statement: ReadOnly[tuple[_SessionPolicyStatement, ...]] + + +_WEB_IDENTITY_SESSION_POLICY_ACTIONS: Final[Mapping[str, tuple[str, ...]]] = MappingProxyType( + { + "BedrockLiteLLM": ( + "bedrock:InvokeModel", + "bedrock:InvokeModelWithResponseStream", + "bedrock:CountTokens", + "bedrock:Rerank", + "bedrock:Retrieve", + "bedrock:ListKnowledgeBases", + "bedrock:InvokeAgent", + "bedrock:ApplyGuardrail", + "bedrock:GetGuardrail", + "bedrock:ListGuardrails", + ), + "BedrockAgentCoreLiteLLM": ( + "bedrock-agentcore:InvokeAgentRuntime", + "bedrock-agentcore:InvokeAgentRuntimeForUser", + "bedrock-agentcore:InvokeGateway", + ), + "ClaudePlatformLiteLLM": ( + "aws-external-anthropic:CreateInference", + "aws-external-anthropic:CreateBatchInference", + "aws-external-anthropic:CancelBatchInference", + "aws-external-anthropic:DeleteBatchInference", + "aws-external-anthropic:CountTokens", + "aws-external-anthropic:Get*", + "aws-external-anthropic:List*", + ), + "BedrockMantleLiteLLM": ("bedrock-mantle:CreateInference",), + } +) + +_SECURE_TRANSPORT_ONLY: Final = _SecureTransportCondition(Bool=_SecureTransportBool({"aws:SecureTransport": "true"})) + + +def build_web_identity_session_policy() -> WebIdentitySessionPolicy: + return WebIdentitySessionPolicy( + Version="2012-10-17", + Statement=tuple( + _SessionPolicyStatement( + Sid=sid, + Effect="Allow", + Action=actions, + Resource="*", + Condition=_SECURE_TRANSPORT_ONLY, + ) + for sid, actions in _WEB_IDENTITY_SESSION_POLICY_ACTIONS.items() + ), + ) + + class BedrockRequestTarget(BaseModel): aws_region_name: str aws_bedrock_runtime_endpoint: str | None @@ -940,60 +1012,12 @@ class BaseAWSLLM(SignsRequestsWithAWS): # auth only (static creds + IRSA take other code paths). # https://docs.aws.amazon.com/STS/latest/APIReference/API_AssumeRoleWithWebIdentity.html # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sts/client/assume_role_with_web_identity.html - bedrock_session_policy: Final = { - "Version": "2012-10-17", - "Statement": [ - { - "Sid": "BedrockLiteLLM", - "Effect": "Allow", - "Action": [ - "bedrock:InvokeModel", - "bedrock:InvokeModelWithResponseStream", - "bedrock:CountTokens", - "bedrock:ApplyGuardrail", - "bedrock:GetGuardrail", - "bedrock:ListGuardrails", - ], - "Resource": "*", - "Condition": {"Bool": {"aws:SecureTransport": "true"}}, - }, - # Claude Platform on AWS (added by #27678 for the - # ``bedrock/claude_platform/`` route) lives under - # a separate IAM action namespace; without these entries - # the OIDC path 403s on every claude_platform request - # even with a fully permissive identity policy (#30200). - { - "Sid": "ClaudePlatformLiteLLM", - "Effect": "Allow", - "Action": [ - "aws-external-anthropic:CreateInference", - "aws-external-anthropic:CreateBatchInference", - "aws-external-anthropic:CancelBatchInference", - "aws-external-anthropic:DeleteBatchInference", - "aws-external-anthropic:CountTokens", - "aws-external-anthropic:Get*", - "aws-external-anthropic:List*", - ], - "Resource": "*", - "Condition": {"Bool": {"aws:SecureTransport": "true"}}, - }, - { - "Sid": "BedrockMantleLiteLLM", - "Effect": "Allow", - "Action": [ - "bedrock-mantle:CreateInference", - ], - "Resource": "*", - "Condition": {"Bool": {"aws:SecureTransport": "true"}}, - }, - ], - } assume_role_params: Final = { "RoleArn": aws_role_name, "RoleSessionName": aws_session_name, "WebIdentityToken": oidc_token, "DurationSeconds": 3600, - "Policy": json.dumps(bedrock_session_policy, separators=(",", ":")), + "Policy": json.dumps(build_web_identity_session_policy(), separators=(",", ":")), } # Add ExternalId parameter if provided diff --git a/litellm/llms/bedrock/files/transformation.py b/litellm/llms/bedrock/files/transformation.py index 9875ac2b9c3..6e2b0c12090 100644 --- a/litellm/llms/bedrock/files/transformation.py +++ b/litellm/llms/bedrock/files/transformation.py @@ -1,14 +1,18 @@ import base64 import json import os +import posixpath import time +import xml.etree.ElementTree as ET from collections.abc import Iterable, Mapping, MutableMapping, Sequence from contextlib import suppress +from dataclasses import dataclass +from datetime import datetime from functools import cache from itertools import chain from types import MappingProxyType from typing import Any, Final, Literal, TypeAlias, TypedDict -from urllib.parse import unquote +from urllib.parse import quote, unquote, urlencode import httpx from httpx import Headers, Response @@ -23,6 +27,7 @@ from litellm.files.utils import FilesAPIUtils from litellm.litellm_core_utils.aws_partition import get_aws_dns_suffix from litellm.litellm_core_utils.cloud_storage_security import ( BEDROCK_MANAGED_S3_BATCH_PREFIX, + BEDROCK_MANAGED_S3_OUTPUT_PREFIX, BEDROCK_MANAGED_S3_PREFIXES, BEDROCK_MANAGED_S3_UPLOAD_PREFIX, build_managed_cloud_object_name, @@ -62,6 +67,10 @@ from ..common_utils import BedrockError, merge_bedrock_aws_request_params, resol S3_SIGNED_REQUEST_HEADERS_PARAM: Final = "_s3_signed_request_headers" +LIST_FILES_PURPOSE_PARAM: Final = "_s3_list_files_purpose" + +LIST_FILES_LOCATION_PARAM: Final = "_s3_list_files_location" + class _S3DeleteContext(BaseModel): file_id: str = Field(min_length=1) @@ -152,6 +161,13 @@ class _BedrockS3RequestParams(BaseModel): s3_endpoint_url: str | None = None +@dataclass(frozen=True, slots=True) +class _S3RequestTarget: + endpoint_url: str + aws_region_name: str + request_params: _BedrockS3RequestParams + + class _TrustedS3ModelCredentials(BaseModel): """The S3 buckets the server trusts file ids against, from the deployment snapshot.""" @@ -248,6 +264,128 @@ def _validate_file_id_against_configured_buckets( return validate_against(configured_bucket_names[-1]) +_REJECTED_FILE_ID_REQUEST_URL: Final = "https://litellm.ai" + + +def _rejected_file_id(reason: ValueError) -> BedrockError: + message: Final = str(reason) + return BedrockError( + status_code=400, + message=message, + response=httpx.Response( + status_code=400, + text=message, + request=httpx.Request(method="GET", url=_REJECTED_FILE_ID_REQUEST_URL), + ), + ) + + +def _resolve_managed_s3_object(file_id: str, litellm_params: Mapping[str, object]) -> tuple[str, str]: + configured_bucket_names: Final = get_configured_s3_bucket_names(litellm_params) + allow_legacy_cloud_file_ids: Final = should_allow_legacy_cloud_file_ids(litellm_params) + try: + return _validate_file_id_against_configured_buckets( + s3_uri=extract_s3_uri_from_file_id(file_id), + configured_bucket_names=configured_bucket_names, + allow_legacy_cloud_file_ids=allow_legacy_cloud_file_ids, + ) + except ValueError as reason: + raise _rejected_file_id(reason) from reason + + +_ANY_MANAGED_LISTING_PREFIX: Final = os.path.commonprefix(BEDROCK_MANAGED_S3_PREFIXES) +_MANAGED_LISTING_PREFIX_BY_PURPOSE: Final = MappingProxyType( + { + "batch": os.path.commonprefix((BEDROCK_MANAGED_S3_BATCH_PREFIX, BEDROCK_MANAGED_S3_UPLOAD_PREFIX)), + "batch_output": BEDROCK_MANAGED_S3_OUTPUT_PREFIX, + } +) + + +_EMPTY_LISTING_QUERY: Final = (("list-type", "2"), ("max-keys", "0")) + + +def _managed_listing_prefix(configured_prefix: str, purpose: str | None) -> str | None: + managed_prefix: Final = _MANAGED_LISTING_PREFIX_BY_PURPOSE.get(purpose) if purpose else _ANY_MANAGED_LISTING_PREFIX + if managed_prefix is None: + return None + return f"{configured_prefix}/{managed_prefix}" if configured_prefix else managed_prefix + + +def _listing_query(configured_prefix: str, purpose: str | None) -> tuple[tuple[str, str], ...]: + listing_prefix: Final = _managed_listing_prefix(configured_prefix, purpose) + if listing_prefix is None: + return _EMPTY_LISTING_QUERY + return (("list-type", "2"), ("prefix", listing_prefix)) + + +def _requested_listing_purpose(litellm_params: Mapping[str, object]) -> str | None: + requested_purpose: Final = litellm_params.get(LIST_FILES_PURPOSE_PARAM) + return requested_purpose if isinstance(requested_purpose, str) else None + + +def _walked_listing_purpose(litellm_params: Mapping[str, object]) -> str | None: + walked_purpose: Final = litellm_params.get(LIST_FILES_LOCATION_PARAM) + return walked_purpose if isinstance(walked_purpose, str) else _requested_listing_purpose(litellm_params) + + +def _output_location_still_unlisted(litellm_params: Mapping[str, object]) -> bool: + if _walked_listing_purpose(litellm_params) is not None: + return False + return _listing_bucket_name(litellm_params, "batch_output") != _listing_bucket_name(litellm_params, None) + + +def _listing_bucket_name(litellm_params: Mapping[str, object], purpose: str | None) -> str: + if purpose != "batch_output": + return get_configured_s3_bucket_name(litellm_params) + trusted: Final = _trusted_s3_model_credentials(litellm_params) + return ( + trusted.s3_output_bucket_name + or os.getenv("AWS_S3_OUTPUT_BUCKET_NAME") + or get_configured_s3_bucket_name(litellm_params) + ) + + +def _listed_object_created_at(entry: ET.Element) -> int: + last_modified: Final = entry.findtext("{*}LastModified") + if not last_modified: + return 0 + return int(datetime.fromisoformat(last_modified.replace("Z", "+00:00")).timestamp()) + + +def _listed_managed_file( + entry: ET.Element, + bucket_name: str, + configured_bucket_name: str, + allow_legacy_cloud_file_ids: bool, +) -> OpenAIFileObject | None: + object_key: Final = entry.findtext("{*}Key") + if not object_key: + return None + file_id: Final = f"s3://{bucket_name}/{object_key}" + try: + validate_managed_cloud_file_id( + file_id=file_id, + scheme="s3://", + configured_bucket_name=configured_bucket_name, + allowed_object_prefixes=BEDROCK_MANAGED_S3_PREFIXES, + allow_legacy_cloud_file_ids=allow_legacy_cloud_file_ids, + ) + except ValueError: + return None + _, configured_prefix = split_configured_cloud_bucket_name(configured_bucket_name) + relative_key: Final = object_key[len(configured_prefix) + 1 :] if configured_prefix else object_key + return OpenAIFileObject( + id=file_id, + bytes=int(entry.findtext("{*}Size") or 0), + created_at=_listed_object_created_at(entry), + filename=posixpath.basename(object_key), + object="file", + purpose="batch_output" if relative_key.startswith(BEDROCK_MANAGED_S3_OUTPUT_PREFIX) else "batch", + status="uploaded", + ) + + def _uploaded_object_size(litellm_params: Mapping[str, object], raw_response: Response) -> int: """ S3 answers PutObject with an empty body, so the stored object size comes from the @@ -1213,18 +1351,86 @@ class BedrockFilesConfig(BaseAWSLLM, BaseFilesConfig): def transform_list_files_request( self, purpose: str | None, - optional_params: dict, - litellm_params: dict, - ) -> tuple[str, dict]: - raise NotImplementedError("BedrockFilesConfig does not support file listing") + optional_params: Mapping[str, object], + litellm_params: MutableMapping[str, object], + ) -> tuple[str, dict[str, str]]: + litellm_params[LIST_FILES_PURPOSE_PARAM] = purpose # rebind-ok: handed to the response transform + litellm_params[LIST_FILES_LOCATION_PARAM] = purpose # rebind-ok: names the location the next page walks + return self._signed_listing_request(purpose, optional_params, litellm_params, continuation_token=None) + + def transform_list_files_next_request( + self, + raw_response: httpx.Response, + optional_params: Mapping[str, object], + litellm_params: MutableMapping[str, object], + ) -> tuple[str, dict[str, str]] | None: + if raw_response.status_code >= 400: + return None + continuation_token: Final = ET.fromstring(raw_response.content).findtext("{*}NextContinuationToken") + if continuation_token: + return self._signed_listing_request( + _walked_listing_purpose(litellm_params), optional_params, litellm_params, continuation_token + ) + if not _output_location_still_unlisted(litellm_params): + return None + litellm_params[LIST_FILES_LOCATION_PARAM] = "batch_output" # rebind-ok: the input location is fully listed + return self._signed_listing_request("batch_output", optional_params, litellm_params, continuation_token=None) + + def _signed_listing_request( + self, + purpose: str | None, + optional_params: Mapping[str, object], + litellm_params: MutableMapping[str, object], + continuation_token: str | None, + ) -> tuple[str, dict[str, str]]: + bucket_name, configured_prefix = split_configured_cloud_bucket_name( + _listing_bucket_name(litellm_params, purpose) + ) + target: Final = self._s3_request_target(optional_params=optional_params, litellm_params=litellm_params) + url: Final = f"{target.endpoint_url}/{bucket_name}/" + listing_query: Final = _listing_query(configured_prefix, purpose) + continuation_query: Final = (("continuation-token", continuation_token),) if continuation_token else () + query: Final[dict[str, str]] = dict( # mutable-ok: the base files contract returns the query as a dict + listing_query + continuation_query + ) + signed_headers: Final = self._sign_s3_request_without_body( + method="GET", + api_base=f"{url}?{urlencode(query, quote_via=quote, safe='')}", + aws_region_name=target.aws_region_name, + request_params=target.request_params, + ) + litellm_params[S3_SIGNED_REQUEST_HEADERS_PARAM] = signed_headers # rebind-ok: handed to validate_environment + return url, query def transform_list_files_response( self, raw_response: httpx.Response, logging_obj: LiteLLMLoggingObj, - litellm_params: dict, + litellm_params: Mapping[str, object], ) -> list[OpenAIFileObject]: - raise NotImplementedError("BedrockFilesConfig does not support file listing") + if raw_response.status_code >= 400: + raise BedrockError( + status_code=raw_response.status_code, + message=raw_response.text, + headers=raw_response.headers, + response=raw_response, + ) + purpose: Final = _requested_listing_purpose(litellm_params) + configured_bucket_name: Final = _listing_bucket_name(litellm_params, _walked_listing_purpose(litellm_params)) + allow_legacy_cloud_file_ids: Final = should_allow_legacy_cloud_file_ids(litellm_params) + listing: Final = ET.fromstring(raw_response.content) + bucket_name: Final = ( + listing.findtext("{*}Name") or split_configured_cloud_bucket_name(configured_bucket_name)[0] + ) + listed_files: Final = ( + _listed_managed_file(entry, bucket_name, configured_bucket_name, allow_legacy_cloud_file_ids) + for entry in listing.iterfind("{*}Contents") + ) + return [ # mutable-ok: the base files contract returns a list + listed_file + for listed_file in listed_files + if listed_file is not None and (purpose is None or listed_file.purpose == purpose) + ] def transform_file_content_request( self, @@ -1255,39 +1461,54 @@ class BedrockFilesConfig(BaseAWSLLM, BaseFilesConfig): optional_params: Mapping[str, object], litellm_params: MutableMapping[str, object], ) -> tuple[str, dict[str, str]]: - s3_uri: Final = extract_s3_uri_from_file_id(file_id) - bucket_name, object_key = _validate_file_id_against_configured_buckets( - s3_uri=s3_uri, - configured_bucket_names=get_configured_s3_bucket_names(litellm_params), - allow_legacy_cloud_file_ids=should_allow_legacy_cloud_file_ids(litellm_params), + bucket_name, object_key = _resolve_managed_s3_object(file_id=file_id, litellm_params=litellm_params) + target: Final = self._s3_request_target(optional_params=optional_params, litellm_params=litellm_params) + url: Final = f"{target.endpoint_url}/{bucket_name}/{encode_s3_object_key_for_url(object_key)}" + signed_headers: Final = self._sign_s3_request_without_body( + method=method, + api_base=url, + aws_region_name=target.aws_region_name, + request_params=target.request_params, ) + litellm_params[S3_SIGNED_REQUEST_HEADERS_PARAM] = signed_headers # rebind-ok: handed to validate_environment + return url, {} # mutable-ok: the base files contract returns the query as a dict - request_params: Final = _BedrockS3RequestParams.model_validate({**litellm_params, **optional_params}) - + def _s3_request_target( + self, + optional_params: Mapping[str, object], + litellm_params: Mapping[str, object], + ) -> _S3RequestTarget: + """ + The shared files handler passes optional_params={}, so AWS credentials and + region arrive via litellm_params here (unlike the upload path). + s3_region_name wins over aws_region_name, same priority as get_complete_file_url. + """ + request_params: Final = _BedrockS3RequestParams.model_validate( + MappingProxyType({**litellm_params, **optional_params}) + ) region_preference: Final = request_params.s3_region_name or request_params.aws_region_name - region_params: Final[dict[str, str | None]] = {"aws_region_name": region_preference} - aws_region_name: Final = self._get_aws_region_name(optional_params=region_params, model="") - - s3_endpoint_url: Final = ( + aws_region_name: Final = self._get_aws_region_name( + optional_params={"aws_region_name": region_preference}, # mutable-ok: BaseAWSLLM takes a dict + model="", + ) + endpoint_url: Final = ( request_params.s3_endpoint_url or f"https://s3.{aws_region_name}.{get_aws_dns_suffix(aws_region_name)}" ).rstrip("/") - url: Final = f"{s3_endpoint_url}/{bucket_name}/{encode_s3_object_key_for_url(object_key)}" - - litellm_params[S3_SIGNED_REQUEST_HEADERS_PARAM] = self._sign_s3_request_without_body( - api_base=url, - aws_region_name=aws_region_name, - request_params=request_params, - method=method, + return _S3RequestTarget( + endpoint_url=endpoint_url, aws_region_name=aws_region_name, request_params=request_params ) - return url, {} def _sign_s3_request_without_body( self, + method: Literal["GET", "DELETE"], api_base: str, aws_region_name: str, request_params: _BedrockS3RequestParams, - method: Literal["GET", "DELETE"] = "GET", - ) -> dict[str, str]: + ) -> Mapping[str, str]: + """ + SigV4-sign a bodiless S3 request (GetObject, DeleteObject, ListObjectsV2), + mirroring `_sign_s3_request` (PUT). + """ try: import hashlib @@ -1313,11 +1534,11 @@ class BedrockFilesConfig(BaseAWSLLM, BaseFilesConfig): aws_request: Final = AWSRequest( # any-ok: botocore AWSRequest is untyped method=method, url=api_base, - headers={"x-amz-content-sha256": empty_body_hash}, + headers={"x-amz-content-sha256": empty_body_hash}, # mutable-ok: botocore AWSRequest takes a dict ) auth: Final = S3SigV4Auth(credentials, "s3", aws_region_name) # any-ok: botocore untyped auth.add_auth(aws_request) # any-ok: botocore request mutation is untyped - return dict(aws_request.headers) # any-ok: botocore headers are untyped + return MappingProxyType(dict(aws_request.headers)) # any-ok: botocore headers are untyped def transform_file_content_response( self, @@ -1330,6 +1551,7 @@ class BedrockFilesConfig(BaseAWSLLM, BaseFilesConfig): status_code=raw_response.status_code, message=raw_response.text, headers=raw_response.headers, + response=raw_response, ) return HttpxBinaryResponseContent(response=raw_response) diff --git a/litellm/llms/bedrock/realtime/handler.py b/litellm/llms/bedrock/realtime/handler.py index ca2370303f2..2c1ce6068b2 100644 --- a/litellm/llms/bedrock/realtime/handler.py +++ b/litellm/llms/bedrock/realtime/handler.py @@ -7,13 +7,21 @@ This uses aws_sdk_bedrock_runtime for bidirectional streaming with Nova Sonic. import asyncio import contextlib import json -from collections.abc import AsyncIterator, Mapping -from typing import Final, Protocol +from collections.abc import AsyncIterator, Mapping, MutableMapping +from dataclasses import dataclass +from types import MappingProxyType +from typing import Final, NoReturn, Protocol from pydantic import JsonValue, TypeAdapter import litellm from litellm._logging import _redact_string, verbose_proxy_logger +from litellm.constants import ( + BEDROCK_REALTIME_COMMITTED_FAILURE_SCOPE_KEY, + BEDROCK_REALTIME_PENDING_SESSION_UPDATE_SCOPE_KEY, + BEDROCK_REALTIME_SESSION_COMMITTED_SCOPE_KEY, + REALTIME_SESSION_SUCCESS_LOGGED_KEY, +) from litellm.litellm_core_utils.aws_partition import get_aws_dns_suffix from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER @@ -28,6 +36,32 @@ from .transformation import BedrockRealtimeConfig _CLIENT_MODALITIES_ADAPTER: Final[TypeAdapter["list[str] | None"]] = TypeAdapter(list[str] | None) _CLIENT_MESSAGE_ADAPTER: Final[TypeAdapter[JsonValue]] = TypeAdapter(JsonValue) +_EMPTY_JSON_OBJECT: Final[Mapping[str, JsonValue]] = MappingProxyType({}) + +_BEDROCK_STREAM_ERROR_STATUS: Final[Mapping[str, int]] = MappingProxyType( + { + "AccessDeniedException": 403, + "ConflictException": 400, + "InternalServerException": 500, + "ModelErrorException": 424, + "ModelNotReadyException": 429, + "ModelStreamErrorException": 424, + "ModelTimeoutException": 408, + "ResourceNotFoundException": 404, + "ServiceQuotaExceededException": 400, + "ServiceUnavailableException": 503, + "ThrottlingException": 429, + "ValidationException": 400, + } +) + + +def _as_bedrock_error(error: BaseException) -> BaseException: + status_code: Final = _BEDROCK_STREAM_ERROR_STATUS.get(type(error).__name__) + if status_code is None: + return error + return BedrockError(status_code=status_code, message=f"{type(error).__name__}: {error}") + def _json_dict(value: JsonValue) -> dict[str, JsonValue]: return value if isinstance(value, dict) else {} @@ -51,6 +85,8 @@ def _should_log_event(openai_message: Mapping[str, object]) -> bool: class RealtimeClientWebSocket(Protocol): """The client-facing websocket surface the realtime bridge talks to.""" + scope: MutableMapping[str, object] # mutable-ok: the ASGI scope is the per-connection state store + async def receive_text(self) -> str: ... async def send_text(self, data: str) -> None: ... @@ -85,6 +121,81 @@ class BedrockBidirectionalStream(Protocol): async def await_output(self) -> tuple[object, BedrockOutputStream]: ... +@dataclass(frozen=True, slots=True) +class _BridgeOutcome: + logged_events: tuple[OpenAIRealtimeEvents, ...] + provider_failure: BaseException | None + client_disconnected: bool + + +async def _client_messages(client_ws: RealtimeClientWebSocket, initial_message: str | None) -> AsyncIterator[str]: + if initial_message is not None: + yield initial_message + while True: + try: + yield await client_ws.receive_text() + except Exception as e: # noqa: BLE001 # any receive failure means the client is gone + verbose_proxy_logger.debug("Client to Bedrock forwarding ended: %s", e, exc_info=True) + return + + +def _pending_session_update(scope: Mapping[str, object]) -> str | None: + """A fallback attempt on the same websocket replays the session.update the failed attempt never acked.""" + if scope.get(BEDROCK_REALTIME_SESSION_COMMITTED_SCOPE_KEY) is True: + committed_failure: Final = scope.get(BEDROCK_REALTIME_COMMITTED_FAILURE_SCOPE_KEY) + 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 "") + ), + ) + pending: Final = scope.get(BEDROCK_REALTIME_PENDING_SESSION_UPDATE_SCOPE_KEY) + return pending if isinstance(pending, str) else None + + +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 scope.get(BEDROCK_REALTIME_SESSION_COMMITTED_SCOPE_KEY) is True: + scope[BEDROCK_REALTIME_COMMITTED_FAILURE_SCOPE_KEY] = _redact_string(str(error)) + raise error from failure + + +def _parse_client_message(message: str) -> Mapping[str, JsonValue]: + try: + return _json_dict(_CLIENT_MESSAGE_ADAPTER.validate_json(message)) + except ValueError: + return _EMPTY_JSON_OBJECT + + +async def _ack_session_update( + client_ws: RealtimeClientWebSocket, + bedrock_stream: BedrockBidirectionalStream, + transformation_config: BedrockRealtimeConfig, + model: str, + logging_obj: LiteLLMLogging | None, + parsed_client_message: Mapping[str, JsonValue], +) -> bool: + """Ack the client's session.update once Bedrock accepted the stream; False means the client is gone.""" + await bedrock_stream.await_output() + client_ws.scope.pop(BEDROCK_REALTIME_PENDING_SESSION_UPDATE_SCOPE_KEY, None) + client_ws.scope[BEDROCK_REALTIME_SESSION_COMMITTED_SCOPE_KEY] = True # rebind-ok: scope outlives the attempt + if logging_obj is None: + return True + requested_modalities: Final = _CLIENT_MODALITIES_ADAPTER.validate_python( + _json_dict(parsed_client_message.get("session")).get("modalities") + ) + try: + await client_ws.send_text( + json.dumps(transformation_config.session_updated_event(model, logging_obj, requested_modalities)) + ) + except Exception as e: # noqa: BLE001 # any send failure means the client is gone + verbose_proxy_logger.debug("Client to Bedrock forwarding ended: %s", e, exc_info=True) + return False + return True + + class BedrockRealtime(BaseAWSLLM): """Handler for Bedrock Nova Sonic realtime speech-to-speech API.""" @@ -132,6 +243,8 @@ class BedrockRealtime(BaseAWSLLM): except ImportError: raise ImportError("Missing aws_sdk_bedrock_runtime. Install with: pip install aws-sdk-bedrock-runtime") + pending_session_update: Final = _pending_session_update(websocket.scope) + # Get AWS region if aws_region_name is None: optional_params: Final = { @@ -190,90 +303,106 @@ class BedrockRealtime(BaseAWSLLM): transformation_config: Final = BedrockRealtimeConfig() - try: - # Initialize the bidirectional stream - bedrock_stream: Final = await open_bidirectional_stream() + bedrock_stream: Final = await open_bidirectional_stream() - verbose_proxy_logger.debug("Bedrock Realtime: Bidirectional stream established") + verbose_proxy_logger.debug("Bedrock Realtime: Bidirectional stream established") + if pending_session_update is None: await websocket.send_text(json.dumps(transformation_config.session_created_event(model, logging_obj))) verbose_proxy_logger.debug("Bedrock Realtime: sent session.created to client on connect") - # Track state for transformation - session_state: Final[RealtimeResponseTransformInput] = { - "current_output_item_id": None, - "current_response_id": None, - "current_conversation_id": None, - "current_delta_chunks": None, - "current_item_chunks": None, - "current_delta_type": None, - "session_configuration_request": None, - } + # Track state for transformation + session_state: Final[RealtimeResponseTransformInput] = { + "current_output_item_id": None, + "current_response_id": None, + "current_conversation_id": None, + "current_delta_chunks": None, + "current_item_chunks": None, + "current_delta_type": None, + "session_configuration_request": None, + } - # Create tasks for bidirectional forwarding - client_to_bedrock_task: Final = asyncio.create_task( - self._forward_client_to_bedrock( - websocket, - bedrock_stream, - transformation_config, - model, - session_state, - logging_obj, + outcome: Final = await self._bridge( + websocket, + bedrock_stream, + transformation_config, + model, + session_state, + logging_obj, + initial_message=pending_session_update, + ) + + logged_events: Final = ( + *outcome.logged_events, + *( + leftover_event + for leftover_event in transformation_config.leftover_usage_done_events() + if _should_log_event(leftover_event) + ), + ) + if logged_events: + GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue( + logging_obj.dispatch_success_handlers( + list(logged_events), # mutable-ok: realtime spend logging requires a list result + prefer_async_handlers=True, ) ) + logging_obj.model_call_details[REALTIME_SESSION_SUCCESS_LOGGED_KEY] = True - async def forward_bedrock_and_collect_logged_events() -> tuple[OpenAIRealtimeEvents, ...]: - return tuple( - [ - event - async for event in self._forward_bedrock_to_client( - bedrock_stream, - websocket, - transformation_config, - model, - logging_obj, - session_state, - ) - ] - ) - - bedrock_to_client_task: Final = asyncio.create_task(forward_bedrock_and_collect_logged_events()) - - # Wait for both tasks to complete - await asyncio.gather( - client_to_bedrock_task, - bedrock_to_client_task, - return_exceptions=True, + if outcome.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) - forwarded_logged_events: Final = ( - bedrock_to_client_task.result() - if not bedrock_to_client_task.cancelled() and bedrock_to_client_task.exception() is None - else () - ) - logged_events: Final = ( - *forwarded_logged_events, - *( - leftover_event - for leftover_event in transformation_config.leftover_usage_done_events() - if _should_log_event(leftover_event) - ), - ) - if logged_events: - GLOBAL_LOGGING_WORKER.ensure_initialized_and_enqueue( - logging_obj.dispatch_success_handlers( - list(logged_events), # mutable-ok: realtime spend logging requires a list result - prefer_async_handlers=True, - ) - ) + async def _bridge( + self, + websocket: RealtimeClientWebSocket, + bedrock_stream: BedrockBidirectionalStream, + transformation_config: BedrockRealtimeConfig, + model: str, + session_state: RealtimeResponseTransformInput, + logging_obj: LiteLLMLogging, + initial_message: str | None, + ) -> _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 - except Exception as e: - verbose_proxy_logger.exception("Error in BedrockRealtime.async_realtime: %s", e) - try: - await websocket.close(code=1011, reason=_redact_string(f"Internal error: {e}")) - except Exception: - pass - raise + 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) + + client_task: Final = asyncio.create_task( + self._forward_client_to_bedrock( + websocket, bedrock_stream, transformation_config, model, session_state, logging_obj, initial_message + ) + ) + bedrock_task: Final = asyncio.create_task(collect_logged_events()) + + await asyncio.wait((client_task, bedrock_task), return_when=asyncio.FIRST_COMPLETED) + client_disconnected: Final = ( + client_task.done() and not client_task.cancelled() and client_task.exception() is None + ) + client_task.cancel() + bedrock_task.cancel() + client_outcome, bedrock_outcome = await asyncio.gather(client_task, bedrock_task, return_exceptions=True) + + return _BridgeOutcome( + logged_events=tuple(logged), + provider_failure=( + client_outcome + if isinstance(client_outcome, Exception) + else bedrock_outcome + if isinstance(bedrock_outcome, Exception) + else None + ), + client_disconnected=client_disconnected, + ) async def _forward_client_to_bedrock( self, @@ -283,8 +412,12 @@ class BedrockRealtime(BaseAWSLLM): model: str, session_state: RealtimeResponseTransformInput, logging_obj: LiteLLMLogging | None = None, - ): - """Forward messages from client WebSocket to Bedrock stream.""" + initial_message: str | None = None, + ) -> None: + """Forward messages from client WebSocket to Bedrock stream. + + Returns once the client is gone; provider failures (input stream or readiness) propagate to the caller. + """ from aws_sdk_bedrock_runtime.models import ( BidirectionalInputPayloadPart, InvokeModelWithBidirectionalStreamInputChunk, @@ -299,41 +432,28 @@ class BedrockRealtime(BaseAWSLLM): verbose_proxy_logger.debug("Bedrock Realtime: Sent to Bedrock: %s", bedrock_message[:200]) try: - while True: - # Receive message from client - message = await client_ws.receive_text() + async for message in _client_messages(client_ws, initial_message): verbose_proxy_logger.debug("Bedrock Realtime: Received from client: %s", message[:200]) + parsed_client_message = _parse_client_message(message) + is_session_update = _json_str(parsed_client_message.get("type")) == "session.update" + if is_session_update: + client_ws.scope[BEDROCK_REALTIME_PENDING_SESSION_UPDATE_SCOPE_KEY] = ( + message # rebind-ok: scope outlives the attempt + ) - # Transform OpenAI format to Bedrock format transformed_messages = transformation_config.transform_realtime_request( message=message, model=model, session_configuration_request=session_state.get("session_configuration_request"), ) - - # Send transformed messages to Bedrock for bedrock_message in transformed_messages: await send_to_bedrock(bedrock_message) - if logging_obj is not None: - client_message_type: str | None = None - requested_modalities: list[str] | None = None - with contextlib.suppress(Exception): - parsed_client_message = _json_dict(_CLIENT_MESSAGE_ADAPTER.validate_json(message)) - client_message_type = _json_str(parsed_client_message.get("type")) - if client_message_type == "session.update": - requested_modalities = _CLIENT_MODALITIES_ADAPTER.validate_python( - _json_dict(parsed_client_message.get("session")).get("modalities") - ) - if client_message_type == "session.update": - await client_ws.send_text( - json.dumps( - transformation_config.session_updated_event(model, logging_obj, requested_modalities) - ) - ) - - except Exception as e: - verbose_proxy_logger.debug("Client to Bedrock forwarding ended: %s", e, exc_info=True) + if is_session_update and not await _ack_session_update( + client_ws, bedrock_stream, transformation_config, model, logging_obj, parsed_client_message + ): + break + finally: for close_message in transformation_config.session_close_messages(): with contextlib.suppress(Exception): await send_to_bedrock(close_message) @@ -349,68 +469,71 @@ class BedrockRealtime(BaseAWSLLM): logging_obj: LiteLLMLogging, session_state: RealtimeResponseTransformInput, ) -> AsyncIterator[OpenAIRealtimeEvents]: - """Forward messages from Bedrock to the client, yielding the ones to record for spend logging.""" - try: - while True: - # Receive from Bedrock - output = await bedrock_stream.await_output() - result = await output[1].receive() + """Forward messages from Bedrock to the client, yielding the ones to record for spend logging. - if result is None: - verbose_proxy_logger.debug("Bedrock Realtime: Bedrock stream ended") - break + Provider failures propagate to the caller; the client websocket is only closed on a normal stream end. + """ - payload_bytes = result.value.bytes_ if result.value else None - if payload_bytes: - bedrock_response = payload_bytes.decode("utf-8") - verbose_proxy_logger.debug("Bedrock Realtime: Received from Bedrock: %s", bedrock_response[:200]) - - # Transform Bedrock format to OpenAI format - realtime_response_transform_input: RealtimeResponseTransformInput = { - "current_output_item_id": session_state.get("current_output_item_id"), - "current_response_id": session_state.get("current_response_id"), - "current_conversation_id": session_state.get("current_conversation_id"), - "current_delta_chunks": session_state.get("current_delta_chunks"), - "current_item_chunks": session_state.get("current_item_chunks"), - "current_delta_type": session_state.get("current_delta_type"), - "session_configuration_request": session_state.get("session_configuration_request"), - } - - transformed_response = transformation_config.transform_realtime_response( - message=bedrock_response, - model=model, - logging_obj=logging_obj, - realtime_response_transform_input=realtime_response_transform_input, - ) - - # Update session state - session_state.update( - { - "current_output_item_id": transformed_response.get("current_output_item_id"), - "current_response_id": transformed_response.get("current_response_id"), - "current_conversation_id": transformed_response.get("current_conversation_id"), - "current_delta_chunks": transformed_response.get("current_delta_chunks"), - "current_item_chunks": transformed_response.get("current_item_chunks"), - "current_delta_type": transformed_response.get("current_delta_type"), - "session_configuration_request": transformed_response.get("session_configuration_request"), - } - ) - - # Send transformed messages to client - response_value = transformed_response["response"] - openai_messages = response_value if isinstance(response_value, list) else (response_value,) - for openai_message in openai_messages: - message_json = json.dumps(openai_message) - await client_ws.send_text(message_json) - verbose_proxy_logger.debug("Bedrock Realtime: Sent to client: %s", message_json[:200]) - if _should_log_event(openai_message): - yield openai_message - - except Exception as e: - verbose_proxy_logger.debug("Bedrock to client forwarding ended: %s", e, exc_info=True) - finally: - # Close the client WebSocket + async def send_to_client(message_json: str) -> bool: try: - await client_ws.close() - except Exception: - pass + await client_ws.send_text(message_json) + except Exception as e: # noqa: BLE001 # any send failure means the client is gone + verbose_proxy_logger.debug("Bedrock to client forwarding ended: %s", e, exc_info=True) + return False + verbose_proxy_logger.debug("Bedrock Realtime: Sent to client: %s", message_json[:200]) + return True + + output: Final = await bedrock_stream.await_output() + while True: + result = await output[1].receive() + + if result is None: + verbose_proxy_logger.debug("Bedrock Realtime: Bedrock stream ended") + with contextlib.suppress(Exception): + await client_ws.close() + return + + payload_bytes = result.value.bytes_ if result.value else None + if payload_bytes: + bedrock_response = payload_bytes.decode("utf-8") + verbose_proxy_logger.debug("Bedrock Realtime: Received from Bedrock: %s", bedrock_response[:200]) + + # Transform Bedrock format to OpenAI format + realtime_response_transform_input: RealtimeResponseTransformInput = { + "current_output_item_id": session_state.get("current_output_item_id"), + "current_response_id": session_state.get("current_response_id"), + "current_conversation_id": session_state.get("current_conversation_id"), + "current_delta_chunks": session_state.get("current_delta_chunks"), + "current_item_chunks": session_state.get("current_item_chunks"), + "current_delta_type": session_state.get("current_delta_type"), + "session_configuration_request": session_state.get("session_configuration_request"), + } + + transformed_response = transformation_config.transform_realtime_response( + message=bedrock_response, + model=model, + logging_obj=logging_obj, + realtime_response_transform_input=realtime_response_transform_input, + ) + + # Update session state + session_state.update( + { + "current_output_item_id": transformed_response.get("current_output_item_id"), + "current_response_id": transformed_response.get("current_response_id"), + "current_conversation_id": transformed_response.get("current_conversation_id"), + "current_delta_chunks": transformed_response.get("current_delta_chunks"), + "current_item_chunks": transformed_response.get("current_item_chunks"), + "current_delta_type": transformed_response.get("current_delta_type"), + "session_configuration_request": transformed_response.get("session_configuration_request"), + } + ) + + # Send transformed messages to client + response_value = transformed_response["response"] + openai_messages = response_value if isinstance(response_value, list) else (response_value,) + for openai_message in openai_messages: + if not await send_to_client(json.dumps(openai_message)): + return + if _should_log_event(openai_message): + yield openai_message diff --git a/litellm/llms/bedrock_mantle/chat/transformation.py b/litellm/llms/bedrock_mantle/chat/transformation.py index d91157c3d10..a1153dffc93 100644 --- a/litellm/llms/bedrock_mantle/chat/transformation.py +++ b/litellm/llms/bedrock_mantle/chat/transformation.py @@ -29,7 +29,7 @@ from litellm.types.router import GenericLiteLLMParams from ...base_llm.chat.transformation import BaseLLMException from ...bedrock.common_utils import BedrockError from ...openai_like.chat.transformation import OpenAILikeChatConfig -from ..common_utils import mantle_base_segment +from ..common_utils import mantle_base_segment, split_mantle_region_prefix class BedrockMantleChatConfig(BedrockMantleAuthMixin, OpenAILikeChatConfig): @@ -61,8 +61,10 @@ class BedrockMantleChatConfig(BedrockMantleAuthMixin, OpenAILikeChatConfig): litellm_params: GenericLiteLLMParams | None = None, model: str | None = None, ) -> tuple[str | None, str | None]: + prefix_region, base_model = split_mantle_region_prefix(model) if model else (None, None) region: Final = ( (litellm_params.aws_region_name if litellm_params else None) + or prefix_region or get_secret_str("BEDROCK_MANTLE_REGION") or get_secret_str("AWS_REGION_NAME") or get_secret_str("AWS_REGION") @@ -75,7 +77,7 @@ class BedrockMantleChatConfig(BedrockMantleAuthMixin, OpenAILikeChatConfig): api_base = ( api_base or get_secret_str("BEDROCK_MANTLE_API_BASE") - or f"https://bedrock-mantle.{region}.api.aws/{mantle_base_segment(model, litellm.model_cost)}" + or f"https://bedrock-mantle.{region}.api.aws/{mantle_base_segment(base_model, litellm.model_cost)}" ) dynamic_api_key: Final = self._resolve_bearer_token(api_key) return api_base, dynamic_api_key diff --git a/litellm/llms/bedrock_mantle/common_utils.py b/litellm/llms/bedrock_mantle/common_utils.py index ac94d9cb922..9892ef6224e 100644 --- a/litellm/llms/bedrock_mantle/common_utils.py +++ b/litellm/llms/bedrock_mantle/common_utils.py @@ -24,9 +24,11 @@ from botocore.exceptions import ( ) from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM, SignsRequestsWithAWS +from litellm.llms.bedrock.common_utils import AmazonBedrockGlobalConfig from litellm.secret_managers.main import get_secret_str BEDROCK_MANTLE_DEFAULT_REGION: Final = "us-east-1" +BEDROCK_REGIONS: Final = frozenset(AmazonBedrockGlobalConfig().get_all_regions()) # Standard Mantle host: https://bedrock-mantle..api.aws (group 1 = region). MANTLE_HOST_RE: Final = re.compile(r"^https?://bedrock-mantle\.([^/.]+)\.api\.aws(?=/|$)", re.IGNORECASE) @@ -36,6 +38,13 @@ def resolve_mantle_bearer_token(api_key: str | None) -> str | None: return api_key or get_secret_str("BEDROCK_MANTLE_API_KEY") or get_secret_str("AWS_BEARER_TOKEN_BEDROCK") +def split_mantle_region_prefix(model: str) -> tuple[str | None, str]: + head, sep, tail = model.partition("/") + if sep and head in BEDROCK_REGIONS: + return head, tail + return None, model + + def resolve_mantle_region(params: Mapping[str, object]) -> str: region: Final = params.get("aws_region_name") if isinstance(region, str) and region: @@ -130,7 +139,7 @@ def mantle_supports_responses(model: str | None, model_cost: dict) -> bool: gpt-oss substring), so a substring gate would be wrong. A model absent from model_cost simply has no signal and returns False (chat-completions emulation). """ - entry: Final = model_cost.get(f"bedrock_mantle/{model}", {}) + entry: Final = model_cost.get(f"bedrock_mantle/{split_mantle_region_prefix(model)[1]}", {}) if model else {} if "/v1/responses" in (entry.get("supported_endpoints") or []): return True return entry.get("mode") == "responses" @@ -147,5 +156,5 @@ def mantle_base_segment(model: str | None, model_cost: dict) -> str: the base for the model's whole OpenAI-compatible surface, so both the chat and responses configs derive from it -- there is no separate model-name rule. """ - entry: Final = model_cost.get(f"bedrock_mantle/{model}", {}) + entry: Final = model_cost.get(f"bedrock_mantle/{split_mantle_region_prefix(model)[1]}", {}) if model else {} return "openai/v1" if entry.get("use_openai_responses_path") is True else "v1" diff --git a/litellm/llms/bedrock_mantle/responses/transformation.py b/litellm/llms/bedrock_mantle/responses/transformation.py index 53a3e634adf..57590601a3c 100644 --- a/litellm/llms/bedrock_mantle/responses/transformation.py +++ b/litellm/llms/bedrock_mantle/responses/transformation.py @@ -17,7 +17,7 @@ BaseAWSLLM._sign_request after the request body is finalized. import json from collections.abc import Mapping -from typing import Any, Final +from typing import Any, Final, cast # noqa: TID251 # map_openai_params returns the filtered params as a bare dict import httpx from typing_extensions import ReadOnly, TypedDict @@ -32,6 +32,7 @@ from litellm.llms.bedrock_mantle.common_utils import ( BedrockMantleAuthMixin, ) from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig +from litellm.responses.additional_tools import HoistedAdditionalTools, hoist_additional_tools from litellm.secret_managers.main import get_secret_str from litellm.types.llms.openai import ( ResponseInputParam, @@ -58,8 +59,6 @@ _BEDROCK_MANTLE_SUPPORTED_RESPONSE_TOOL_TYPES: Final = frozenset( _BEDROCK_MANTLE_SUPPORTED_SERVICE_TIERS: Final = frozenset({"auto", "default"}) _BEDROCK_MANTLE_OPENAI_PATH_SUPPORTED_REASONING_SUMMARIES: Final = frozenset({"auto"}) -_CODEX_ADDITIONAL_TOOLS_INPUT_ITEM_TYPE: Final = "additional_tools" - _CODEX_AGENT_MESSAGE_INPUT_ITEM_TYPE: Final = "agent_message" _CODEX_CONTEXT_COMPACTION_INPUT_ITEM_TYPE: Final = "context_compaction" _CODEX_LOCAL_SHELL_CALL_INPUT_ITEM_TYPE: Final = "local_shell_call" @@ -233,17 +232,14 @@ class BedrockMantleResponsesAPIConfig(BedrockMantleAuthMixin, OpenAIResponsesAPI litellm_params: GenericLiteLLMParams, headers: dict, ) -> dict: - remaining_input, hoisted_tools = self._hoist_codex_additional_tools(input) - normalized_input: Final = self._normalize_codex_input_items(remaining_input) + params: Final = cast( # cast-ok: the base signature leaves the params dict untyped + "ResponsesAPIOptionalRequestParams", response_api_optional_request_params + ) + hoisted: Final = hoist_additional_tools(input, params.get("tools")) + normalized_input: Final = self._normalize_codex_input_items(hoisted.input) request_params: Final = ( - { - **response_api_optional_request_params, - "tools": [ - *(response_api_optional_request_params.get("tools") or []), - *hoisted_tools, - ], - } - if hoisted_tools + self._params_with_hoisted_tools(params, hoisted) + if hoisted.hoisted else response_api_optional_request_params ) return super().transform_responses_api_request( @@ -254,41 +250,14 @@ class BedrockMantleResponsesAPIConfig(BedrockMantleAuthMixin, OpenAIResponsesAPI headers=headers, ) - @staticmethod - def _is_codex_additional_tools_item(item: Any) -> bool: - return isinstance(item, dict) and item.get("type") == _CODEX_ADDITIONAL_TOOLS_INPUT_ITEM_TYPE - - @staticmethod - def _tools_of_additional_tools_item(item: "dict[str, Any]") -> "list[Any]": - tools: Final = item.get("tools") - return tools if isinstance(tools, list) else [] - @classmethod - def _hoist_codex_additional_tools( - cls, - input: "str | ResponseInputParam", - ) -> "tuple[str | ResponseInputParam, list[Any]]": - """Codex's "responses lite" wire mode ships tool definitions inside - `input` as {"type": "additional_tools", "role": "developer", - "tools": [...]} items. api.openai.com accepts that item type; Mantle - rejects the whole request with 400 "Invalid 'input': value did not - match any expected variant" but accepts the same tools at the top - level, so move them there and strip the items from `input`. - """ - if not isinstance(input, list): - return input, [] - additional_tools_items: Final = [item for item in input if cls._is_codex_additional_tools_item(item)] - if not additional_tools_items: - return input, [] - remaining_input: Final = [item for item in input if not cls._is_codex_additional_tools_item(item)] - hoisted_tools = [tool for item in additional_tools_items for tool in cls._tools_of_additional_tools_item(item)] - verbose_logger.debug( - "Bedrock Mantle Responses API: hoisting %d tool(s) out of %d 'additional_tools' input item(s) " - "into the top-level tools param (Mantle rejects that input item type).", - len(hoisted_tools), - len(additional_tools_items), - ) - return remaining_input, cls._filter_unsupported_tools(hoisted_tools) + def _params_with_hoisted_tools( + cls, params: Mapping[str, object], hoisted: HoistedAdditionalTools + ) -> dict[str, object]: + supported_tools: Final = cls._filter_unsupported_tools(list(hoisted.tools)) + if supported_tools: + return {**params, "tools": supported_tools} + return {key: value for key, value in params.items() if key != "tools"} @staticmethod def _agent_message_text(item: "Mapping[str, object]") -> str: diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py index 7109e6942d1..2fe4130a310 100644 --- a/litellm/llms/custom_httpx/llm_http_handler.py +++ b/litellm/llms/custom_httpx/llm_http_handler.py @@ -18,7 +18,7 @@ import litellm.types import litellm.types.utils from litellm._logging import _redact_string, verbose_logger from litellm.anthropic_beta_headers_manager import update_headers_with_filtered_beta -from litellm.constants import REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES +from litellm.constants import MAX_FILE_LIST_LIMIT, REALTIME_WEBSOCKET_MAX_MESSAGE_SIZE_BYTES from litellm.litellm_core_utils.agentic_loop_settings import ( DEFAULT_MAX_AGENTIC_LOOPS, validated_max_agentic_loops, @@ -4981,15 +4981,16 @@ class BaseLLMHTTPHandler: ) try: - response: Final = sync_httpx_client.get(url=url, headers=headers, params=params) + response: Final = sync_httpx_client.get(url=url, headers=headers, params=params, timeout=timeout) except Exception as e: raise self._handle_error(e=e, provider_config=provider_config) - return provider_config.transform_list_files_response( - raw_response=response, - logging_obj=logging_obj, - litellm_params=litellm_params, + files_per_page: Final = self._files_per_listing_page( + response, provider_config, logging_obj, litellm_params, headers, sync_httpx_client, timeout ) + return [ # mutable-ok: the files contract returns the listing as a list + listed_file for page_files in files_per_page for listed_file in page_files + ] async def async_list_files( self, @@ -5037,16 +5038,101 @@ class BaseLLMHTTPHandler: ) try: - response: Final = await async_httpx_client.get(url=url, headers=headers, params=params) + response: Final = await async_httpx_client.get(url=url, headers=headers, params=params, timeout=timeout) except Exception as e: raise self._handle_error(e=e, provider_config=provider_config) - return provider_config.transform_list_files_response( - raw_response=response, - logging_obj=logging_obj, + files_per_page: Final = self._files_per_async_listing_page( + response, provider_config, logging_obj, litellm_params, headers, async_httpx_client, timeout + ) + return [ # mutable-ok: the files contract returns the listing as a list + listed_file async for page_files in files_per_page for listed_file in page_files + ] + + def _files_per_listing_page( + self, + first_page: httpx.Response, + provider_config: BaseFilesConfig, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, # mutable-ok: handed to the files contract, which types it as a dict + headers: dict, # mutable-ok: handed to validate_environment, which types it as a dict + client: HTTPHandler, + timeout: float | httpx.Timeout | None, + ) -> Iterator[list[OpenAIFileObject]]: # mutable-ok: each page arrives as the list the files contract returns + latest_page = first_page # rebind-ok: advances one page per loop turn + listed_count = 0 # rebind-ok: grows per page so the listing stops at MAX_FILE_LIST_LIMIT, OpenAI's ceiling + while True: + page_files = provider_config.transform_list_files_response( + raw_response=latest_page, logging_obj=logging_obj, litellm_params=litellm_params + ) + yield page_files[: MAX_FILE_LIST_LIMIT - listed_count] + listed_count += len(page_files) + next_request = self._next_listing_request(latest_page, provider_config, litellm_params, listed_count) + if next_request is None: + return + url, params = next_request + next_headers = self._next_listing_page_headers(provider_config, headers, litellm_params) + try: + latest_page = client.get(url=url, headers=next_headers, params=params, timeout=timeout) + except Exception as e: # noqa: BLE001 # _handle_error maps every failure kind, like the first page's fetch + raise self._handle_error(e=e, provider_config=provider_config) + + async def _files_per_async_listing_page( + self, + first_page: httpx.Response, + provider_config: BaseFilesConfig, + logging_obj: LiteLLMLoggingObj, + litellm_params: dict, # mutable-ok: handed to the files contract, which types it as a dict + headers: dict, # mutable-ok: handed to validate_environment, which types it as a dict + client: AsyncHTTPHandler, + timeout: float | httpx.Timeout | None, + ) -> AsyncIterator[list[OpenAIFileObject]]: # mutable-ok: each page arrives as the list the files contract returns + latest_page = first_page # rebind-ok: advances one page per loop turn + listed_count = 0 # rebind-ok: grows per page so the listing stops at MAX_FILE_LIST_LIMIT, OpenAI's ceiling + while True: + page_files = provider_config.transform_list_files_response( + raw_response=latest_page, logging_obj=logging_obj, litellm_params=litellm_params + ) + yield page_files[: MAX_FILE_LIST_LIMIT - listed_count] + listed_count += len(page_files) + next_request = self._next_listing_request(latest_page, provider_config, litellm_params, listed_count) + if next_request is None: + return + url, params = next_request + next_headers = self._next_listing_page_headers(provider_config, headers, litellm_params) + try: + latest_page = await client.get(url=url, headers=next_headers, params=params, timeout=timeout) + except Exception as e: # noqa: BLE001 # _handle_error maps every failure kind, like the first page's fetch + raise self._handle_error(e=e, provider_config=provider_config) + + def _next_listing_page_headers( + self, + provider_config: BaseFilesConfig, + headers: dict, # mutable-ok: handed to validate_environment, which types it as a dict + litellm_params: dict, # mutable-ok: handed to the files contract, which types it as a dict + ) -> dict: # mutable-ok: validate_environment returns the header dict the files contract types + return provider_config.validate_environment( + api_key=litellm_params.get("api_key"), + headers=headers, + model="", + messages=[], + optional_params={}, litellm_params=litellm_params, ) + def _next_listing_request( + self, + latest_page: httpx.Response, + provider_config: BaseFilesConfig, + litellm_params: dict, # mutable-ok: handed to the files contract, which types it as a dict + listed_count: int, + ) -> tuple[str, dict[str, str]] | None: # mutable-ok: the base files contract returns the query as a dict + if listed_count >= MAX_FILE_LIST_LIMIT: + return None + return provider_config.transform_list_files_next_request( + raw_response=latest_page, optional_params={}, litellm_params=litellm_params + ) + def retrieve_file_content( self, file_content_request: "FileContentRequest", diff --git a/litellm/llms/databricks/chat/transformation.py b/litellm/llms/databricks/chat/transformation.py index 09aaf970dc5..82c3b5d91d3 100644 --- a/litellm/llms/databricks/chat/transformation.py +++ b/litellm/llms/databricks/chat/transformation.py @@ -272,6 +272,15 @@ class DatabricksConfig(DatabricksBase, OpenAILikeChatConfig, AnthropicConfig): "thinking", ] + @staticmethod + def _uses_anthropic_thinking_param(model: str) -> bool: + from litellm.utils import supports_anthropic_thinking_payload + + normalized: Final = model.lower().replace(".", "-") + return "claude" in normalized or supports_anthropic_thinking_payload( + model=normalized, custom_llm_provider="databricks" + ) + def convert_anthropic_tool_to_databricks_tool(self, tool: AllAnthropicToolsValues | None) -> DatabricksTool | None: if tool is None: return None @@ -377,7 +386,7 @@ 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 "claude" in model: + if "reasoning_effort" in non_default_params and self._uses_anthropic_thinking_param(model): reasoning_effort_value: Final = non_default_params.get("reasoning_effort") mapped_thinking: Final = AnthropicConfig._map_reasoning_effort( reasoning_effort=reasoning_effort_value, diff --git a/litellm/llms/fireworks_ai/chat/transformation.py b/litellm/llms/fireworks_ai/chat/transformation.py index b4e1856f499..05160d83c12 100644 --- a/litellm/llms/fireworks_ai/chat/transformation.py +++ b/litellm/llms/fireworks_ai/chat/transformation.py @@ -602,6 +602,9 @@ class FireworksAIConfig(FireworksAIMixin, OpenAIGPTConfig): return None return max(matches, key=lambda match: len(match[0]))[1] + def get_model_cost_key(self, model: str) -> str: + return f"fireworks_ai/{resolve_fireworks_resource_name(model)}" + def get_provider_info(self, model: str) -> ProviderSpecificModelInfo: supports_function_calling_value: Final = self._get_model_cost_capability( model=model, capability="supports_function_calling" diff --git a/litellm/llms/gemini/realtime/transformation.py b/litellm/llms/gemini/realtime/transformation.py index c92af7de145..79985569c5f 100644 --- a/litellm/llms/gemini/realtime/transformation.py +++ b/litellm/llms/gemini/realtime/transformation.py @@ -115,6 +115,19 @@ def _parse_setup(session_configuration_request: str) -> BidiGenerateContentSetup return envelope.get("setup", empty_setup) +def _grounding_metadata_from_frame(frame: Mapping[str, object]) -> tuple[Mapping[str, object], ...]: + """Read ``serverContent.groundingMetadata`` off the frame that carries the turn's usage. + + Live reports grounding in the server frames rather than in ``usageMetadata``, and it emits both + on the same frame, so the per-query charge is countable at the point usage is built. + """ + server_content: Final = frame.get("serverContent") + if not isinstance(server_content, Mapping): + return () + metadata: Final = server_content.get("groundingMetadata") + return (metadata,) if isinstance(metadata, Mapping) else () + + # Google bills Live transcription at an estimated 25 audio tokens/sec of input and # 175 text tokens/min of output (ai.google.dev/gemini-api/docs/pricing). GEMINI_LIVE_TRANSCRIBE_AUDIO_TOKENS_PER_SECOND: Final = 25 @@ -323,7 +336,7 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): ) elif key == "input_audio_transcription" and value is not None: optional_params["inputAudioTranscription"] = {} - elif key == "turn_detection": + elif key == "turn_detection" and value is not None: value_typed = cast(OpenAIRealtimeTurnDetection, value) if ( isinstance(value_typed, dict) @@ -1049,6 +1062,11 @@ class GeminiRealtimeConfig(BaseRealtimeConfig): {**cast(dict, message), "usageMetadata": resolved_usage_metadata}, ), ) + grounding_metadata: Final = _grounding_metadata_from_frame(message) + if grounding_metadata: + VertexGeminiConfig._set_grounding_usage_counters( # pyright: ignore[reportPrivateUsage] # shared with the chat path; no public alias exists yet + _chat_completion_usage, grounding_metadata + ) else: _chat_completion_usage = get_empty_usage() diff --git a/litellm/llms/meta/realtime/transformation.py b/litellm/llms/meta/realtime/transformation.py new file mode 100644 index 00000000000..1b8943f0cee --- /dev/null +++ b/litellm/llms/meta/realtime/transformation.py @@ -0,0 +1,719 @@ +import asyncio +import base64 +import binascii +import json +import math +import time +from collections.abc import Awaitable, Callable, Iterator, Mapping +from dataclasses import dataclass +from types import MappingProxyType +from typing import Final, Literal +from urllib.parse import urlparse, urlunparse + +from pydantic import JsonValue, TypeAdapter, ValidationError + +from litellm import verbose_logger +from litellm._uuid import uuid +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms.base_llm.realtime.transformation import BaseRealtimeConfig +from litellm.secret_managers.main import get_secret_str +from litellm.types.llms.meta import MuseAudioEncoding, MuseHandshake, MuseMode, MuseSampleRate +from litellm.types.llms.openai import ( + OpenAIRealtimeErrorEvent, + OpenAIRealtimeEvents, + OpenAIRealtimeInputAudioBufferSpeechEvent, + OpenAIRealtimeInputAudioTranscriptionCompleted, + OpenAIRealtimeInputAudioTranscriptionDelta, + OpenAIRealtimeServerVadTurnDetection, + OpenAIRealtimeTranscriptionSession, + OpenAIRealtimeTranscriptionSessionCreated, + OpenAIRealtimeTranscriptionSettings, +) +from litellm.types.realtime import ( + RealtimeInputAudioTranscriptionDurationUsage, + RealtimeInputAudioTranscriptionUsage, + RealtimeResponseTransformInput, + RealtimeResponseTypedDict, +) + +MUSE_MODEL: Final = "muse-voice-transcribe-1.0" +DEFAULT_MUSE_REALTIME_URL: Final = "wss://api.meta.ai/v1/asr/realtime" +SUPPORTED_SAMPLE_RATES: Final = frozenset((16_000, 24_000)) +SUPPORTED_LANGUAGES: Final = ( + "Arabic", + "Bengali", + "Dutch", + "English", + "French", + "German", + "Hebrew", + "Hindi", + "Indonesian", + "Italian", + "Japanese", + "Kannada", + "Korean", + "Malay", + "Mandarin Chinese", + "Marathi", + "Polish", + "Portuguese", + "Spanish", + "Tagalog", + "Tamil", + "Telugu", + "Thai", + "Turkish", + "Vietnamese", +) +_LANGUAGE_NAMES: Final = MappingProxyType({language.casefold(): language for language in SUPPORTED_LANGUAGES}) +_LANGUAGE_CODES: Final = MappingProxyType( + { + "ar": "Arabic", + "bn": "Bengali", + "de": "German", + "en": "English", + "es": "Spanish", + "fil": "Tagalog", + "fr": "French", + "he": "Hebrew", + "hi": "Hindi", + "id": "Indonesian", + "it": "Italian", + "iw": "Hebrew", + "ja": "Japanese", + "kn": "Kannada", + "ko": "Korean", + "ms": "Malay", + "mr": "Marathi", + "nl": "Dutch", + "pl": "Polish", + "pt": "Portuguese", + "ta": "Tamil", + "te": "Telugu", + "th": "Thai", + "tl": "Tagalog", + "tr": "Turkish", + "vi": "Vietnamese", + "zh": "Mandarin Chinese", + } +) +_SUPPORTED_TRANSCRIPTION_KEYS: Final = frozenset(("model", "language")) +_MAX_AUDIO_BACKLOG_SECONDS: Final = 4 +_PACKET_MS: Final = 80 +_END_STREAM: Final = '{"type":"endStream"}' +_PROVIDER_ERROR_MESSAGE: Final = "Meta Muse realtime transcription failed" +_JSON_ADAPTER: Final[TypeAdapter[JsonValue]] = TypeAdapter(JsonValue) +_EMPTY_OBJECT: Final[Mapping[str, JsonValue]] = MappingProxyType({}) +_SERVER_VAD: Final[OpenAIRealtimeServerVadTurnDetection] = {"type": "server_vad"} + + +class MuseProtocolError(ValueError): + pass + + +@dataclass(frozen=True, slots=True) +class MuseSessionConfig: + model: str + mode: MuseMode + sample_rate: MuseSampleRate + language_bias: tuple[str, ...] + + @property + def audio_encoding(self) -> MuseAudioEncoding: + return "PCM_16KHZ" if self.sample_rate == 16_000 else "PCM_24KHZ" + + @property + def bytes_per_second(self) -> int: + return self.sample_rate * 2 + + @property + def packet_bytes(self) -> int: + return self.bytes_per_second * _PACKET_MS // 1000 + + @property + def max_encoded_append_bytes(self) -> int: + return 4 * ((self.bytes_per_second * _MAX_AUDIO_BACKLOG_SECONDS + 2) // 3) + + def handshake(self, access_token: str) -> MuseHandshake: + base: Final[MuseHandshake] = { + "authorization": {"accessToken": access_token}, + "audioEncoding": self.audio_encoding, + "model": self.model, + "mode": self.mode, + "partialMode": "CUMULATIVE", + "emitAudioProgress": True, + } + if not self.language_bias: + return base + biased: Final[MuseHandshake] = {**base, "languageBias": self.language_bias} + return biased + + def openai_session(self, session_id: str) -> OpenAIRealtimeTranscriptionSession: + session: Final[OpenAIRealtimeTranscriptionSession] = { + "id": session_id, + "object": "realtime.transcription_session", + "type": "transcription", + "audio": { + "input": { + "format": {"type": "audio/pcm", "rate": self.sample_rate}, + "transcription": self._transcription_settings(), + "turn_detection": None if self.mode == "PUSH_TO_TALK" else _SERVER_VAD, + } + }, + } + return session + + def _transcription_settings(self) -> OpenAIRealtimeTranscriptionSettings: + base: Final[OpenAIRealtimeTranscriptionSettings] = {"model": self.model} + if not self.language_bias: + return base + localized: Final[OpenAIRealtimeTranscriptionSettings] = {**base, "language": self.language_bias[0]} + return localized + + +_DEFAULT_SESSION_CONFIG: Final = MuseSessionConfig( + model=MUSE_MODEL, mode="ENDPOINTING", sample_rate=24_000, language_bias=() +) + + +def _json_object(payload: str) -> Mapping[str, JsonValue]: + try: + value: Final = _JSON_ADAPTER.validate_json(payload) + except ValidationError: + raise MuseProtocolError("invalid JSON object") from None + if not isinstance(value, dict): + raise MuseProtocolError("message must be a JSON object") + return value + + +def _mapping(value: JsonValue | None, name: str) -> Mapping[str, JsonValue]: + if value is None: + return _EMPTY_OBJECT + if not isinstance(value, dict): + raise MuseProtocolError(f"{name} must be an object") + return value + + +def _string(value: JsonValue | None, name: str) -> str | None: + if value is None: + return None + if not isinstance(value, str): + raise MuseProtocolError(f"{name} must be a string") + return value + + +def _normalize_model(model: str) -> str: + return model.removeprefix("meta/").strip() + + +def _event_id() -> str: + return f"event_{uuid.uuid4().hex}" + + +def normalize_language(language: str) -> str: + value: Final = language.strip() + if not value: + raise MuseProtocolError("language must be non-empty") + documented_name: Final = _LANGUAGE_NAMES.get(value.casefold()) + if documented_name is not None: + return documented_name + primary: Final = value.replace("_", "-").split("-", 1)[0].casefold() + mapped_name: Final = _LANGUAGE_CODES.get(primary) + if mapped_name is None: + raise MuseProtocolError("unsupported Muse Voice language") + return mapped_name + + +def normalize_access_token(api_key: str) -> str: + stripped: Final = api_key.strip() + if not stripped: + raise ValueError("Meta API key is required") + parts: Final = stripped.split(None, 1) + if parts[0].casefold() != "bearer": + return f"Bearer {stripped}" + if len(parts) != 2 or not parts[1].strip(): + raise ValueError("Meta API key must include a token after Bearer") + return f"Bearer {parts[1].strip()}" + + +def build_muse_realtime_url(api_base: str | None) -> str: + if api_base is None: + return DEFAULT_MUSE_REALTIME_URL + parsed: Final = urlparse(api_base.strip()) + scheme: Final = "wss" if parsed.scheme == "https" else parsed.scheme + if ( + scheme != "wss" + or not parsed.hostname + or parsed.username is not None + or parsed.password is not None + or parsed.fragment + ): + raise ValueError("Meta api_base must be an absolute wss:// or https:// URL without credentials or a fragment") + netloc: Final = f"{parsed.hostname}:{parsed.port}" if parsed.port is not None else parsed.hostname + return urlunparse((scheme, netloc, "/v1/asr/realtime", "", "", "")) + + +def _parse_sample_rate(session: Mapping[str, JsonValue]) -> MuseSampleRate: + beta_format: Final = session.get("input_audio_format") + audio: Final = _mapping(session.get("audio"), "session.audio") + audio_input: Final = _mapping(audio.get("input"), "session.audio.input") + ga_format: Final = audio_input.get("format") + if beta_format is not None and ga_format is not None: + raise MuseProtocolError("input audio format must use either beta or GA layout") + if beta_format is not None: + if beta_format != "pcm16": + raise MuseProtocolError("Muse Voice requires pcm16 input audio") + return 24_000 + if ga_format is None: + return 24_000 + if isinstance(ga_format, str): + if ga_format != "pcm16": + raise MuseProtocolError("Muse Voice requires audio/pcm input audio") + return 24_000 + format_mapping: Final = _mapping(ga_format, "session.audio.input.format") + if format_mapping.get("type") != "audio/pcm": + raise MuseProtocolError("Muse Voice requires audio/pcm input audio") + channels: Final = format_mapping.get("channels", 1) + if isinstance(channels, bool) or channels != 1: + raise MuseProtocolError("Muse Voice requires mono input audio") + rate: Final = format_mapping.get("rate", 24_000) + if isinstance(rate, bool) or not isinstance(rate, int) or rate not in SUPPORTED_SAMPLE_RATES: + raise MuseProtocolError("Muse Voice supports PCM16 at 16000 Hz or 24000 Hz") + return 16_000 if rate == 16_000 else 24_000 + + +def _parse_mode(session: Mapping[str, JsonValue], audio_input: Mapping[str, JsonValue]) -> MuseMode: + turn_detection_present: Final = "turn_detection" in session or "turn_detection" in audio_input + turn_detection: Final = session.get("turn_detection", audio_input.get("turn_detection")) + if turn_detection_present and turn_detection is None: + return "PUSH_TO_TALK" + if turn_detection is None: + return "ENDPOINTING" + turn_detection_mapping: Final = _mapping(turn_detection, "turn_detection") + if turn_detection_mapping.get("type") not in (None, "server_vad"): + raise MuseProtocolError("Muse Voice supports server_vad turn detection or null") + return "ENDPOINTING" + + +def parse_session_update(payload: str, expected_model: str) -> MuseSessionConfig: + message: Final = _json_object(payload) + if message.get("type") not in ("session.update", "transcription_session.update"): + raise MuseProtocolError("expected session.update") + session: Final = _mapping(message.get("session"), "session") + if not session: + raise MuseProtocolError("session.update requires a session object") + if session.get("type") not in (None, "transcription", "realtime"): + raise MuseProtocolError("Muse Voice supports transcription sessions only") + audio: Final = _mapping(session.get("audio"), "session.audio") + audio_input: Final = _mapping(audio.get("input"), "session.audio.input") + beta_transcription: Final = session.get("input_audio_transcription") + ga_transcription: Final = audio_input.get("transcription") + if beta_transcription is not None and ga_transcription is not None: + raise MuseProtocolError("input transcription must use either beta or GA layout") + transcription: Final = _mapping( + beta_transcription if beta_transcription is not None else ga_transcription, + "input audio transcription", + ) + unsupported: Final = tuple(sorted(key for key in transcription if key not in _SUPPORTED_TRANSCRIPTION_KEYS)) + if unsupported: + verbose_logger.warning("Meta realtime: dropping unsupported transcription settings %s", unsupported) + requested_model: Final = _string(transcription.get("model"), "transcription model") + normalized_model: Final = _normalize_model(expected_model) + if normalized_model != MUSE_MODEL: + raise MuseProtocolError("unsupported Meta realtime model") + if requested_model is not None and _normalize_model(requested_model) != normalized_model: + raise MuseProtocolError("realtime session model cannot be changed") + language: Final = _string(transcription.get("language"), "language") + return MuseSessionConfig( + model=normalized_model, + mode=_parse_mode(session, audio_input), + sample_rate=_parse_sample_rate(session), + language_bias=() if language is None else (normalize_language(language),), + ) + + +def session_created_event(config: MuseSessionConfig, session_id: str) -> OpenAIRealtimeTranscriptionSessionCreated: + event: Final[OpenAIRealtimeTranscriptionSessionCreated] = { + "type": "session.created", + "event_id": _event_id(), + "session": config.openai_session(session_id), + } + return event + + +def error_event(message: str) -> OpenAIRealtimeErrorEvent: + event: Final[OpenAIRealtimeErrorEvent] = { + "type": "error", + "error": {"type": "server_error", "message": message}, + } + return event + + +def _speech_event( + event_type: Literal["input_audio_buffer.speech_started", "input_audio_buffer.speech_stopped"], item_id: str +) -> OpenAIRealtimeInputAudioBufferSpeechEvent: + event: Final[OpenAIRealtimeInputAudioBufferSpeechEvent] = { + "type": event_type, + "event_id": _event_id(), + "item_id": item_id, + } + return event + + +def _delta_event(item_id: str, delta: str) -> OpenAIRealtimeInputAudioTranscriptionDelta: + event: Final[OpenAIRealtimeInputAudioTranscriptionDelta] = { + "type": "conversation.item.input_audio_transcription.delta", + "event_id": _event_id(), + "item_id": item_id, + "content_index": 0, + "delta": delta, + } + return event + + +def _completed_event( + item_id: str, transcript: str, usage: RealtimeInputAudioTranscriptionUsage | None +) -> OpenAIRealtimeInputAudioTranscriptionCompleted: + event: Final[OpenAIRealtimeInputAudioTranscriptionCompleted] = { + "type": "conversation.item.input_audio_transcription.completed", + "event_id": _event_id(), + "item_id": item_id, + "content_index": 0, + "transcript": transcript, + } + if usage is None: + return event + billed: Final[OpenAIRealtimeInputAudioTranscriptionCompleted] = {**event, "usage": usage} + return billed + + +def _required_turn_id(message: Mapping[str, JsonValue], event: str) -> str: + value: Final = message.get("turnId") + if isinstance(value, bool) or not isinstance(value, (str, int)): + raise MuseProtocolError(f"{event} event has invalid turnId") + turn_id: Final = str(value).strip() + if not turn_id: + raise MuseProtocolError(f"{event} event has invalid turnId") + return turn_id + + +def _new_suffix(previous: str, current: str) -> str: + return current[len(previous) :] if current.startswith(previous) else "" + + +@dataclass(slots=True) +class _TurnState: + item_id: str + started: bool = False + start_emitted: bool = False + latest_partial: str | None = None + emitted_partial: str = "" + final_text: str | None = None + completed_emitted: bool = False + stopped: bool = False + stopped_emitted: bool = False + + def finish(self, transcript: str) -> None: + self.final_text = transcript + self.stopped = True + + def drain( + self, take_usage: Callable[[], RealtimeInputAudioTranscriptionUsage | None] + ) -> Iterator[OpenAIRealtimeEvents]: + has_content: Final = self.latest_partial is not None or self.final_text is not None + if (self.started or has_content) and not self.start_emitted: + self.start_emitted = True + yield _speech_event("input_audio_buffer.speech_started", self.item_id) + if self.latest_partial is not None and self.final_text is None: + delta: Final = _new_suffix(self.emitted_partial, self.latest_partial) + if delta: + self.emitted_partial = self.latest_partial + yield _delta_event(self.item_id, delta) + if self.stopped and not self.stopped_emitted: + self.stopped_emitted = True + yield _speech_event("input_audio_buffer.speech_stopped", self.item_id) + if self.final_text is not None and self.stopped_emitted and not self.completed_emitted: + self.completed_emitted = True + yield _completed_event(self.item_id, self.final_text, take_usage()) + + +class MuseEventTransformer: + def __init__(self, *, turn_limit: int = 128) -> None: + self._turns: dict[str, _TurnState] = {} # mutable-ok: bounded, insertion-ordered per-turn emit state + self._turn_limit: Final = turn_limit + self._active_turn_id: str | None = None + self._mode: MuseMode = "ENDPOINTING" + self._last_audio_processed_ms: float = 0.0 + self._unbilled_seconds: float = 0.0 + + def configure(self, config: MuseSessionConfig) -> None: + self._mode = config.mode + + def transform(self, message: Mapping[str, JsonValue]) -> tuple[OpenAIRealtimeEvents, ...]: + event_type: Final = message.get("type") + if event_type == "error": + return (error_event(_PROVIDER_ERROR_MESSAGE),) + if event_type == "audioProgress": + self._update_audio_progress(message) + return () + turn: Final = self._apply_turn_event(event_type, message) + if turn is None: + return () + return tuple(turn.drain(self.take_unbilled_usage)) + + def take_unbilled_usage(self) -> RealtimeInputAudioTranscriptionUsage | None: + seconds: Final = self._unbilled_seconds + if seconds <= 0: + return None + self._unbilled_seconds = 0.0 + usage: Final[RealtimeInputAudioTranscriptionDurationUsage] = {"type": "duration", "seconds": seconds} + return usage + + def _apply_turn_event(self, event_type: JsonValue | None, message: Mapping[str, JsonValue]) -> _TurnState | None: + match event_type: + case "speechStart": + return self._speech_start(message) + case "transcript": + return self._transcript(message) + case "speechEnd": + return self._speech_end(message) + case "speechComplete": + return self._speech_complete(message) + case _: + return None + + def _turn(self, turn_id: str) -> _TurnState: + existing: Final = self._turns.get(turn_id) + if existing is not None: + return existing + created: Final = _TurnState(item_id=turn_id) + self._turns[turn_id] = created + if len(self._turns) > self._turn_limit: + del self._turns[next(iter(self._turns))] + return created + + def _speech_start(self, message: Mapping[str, JsonValue]) -> _TurnState: + turn: Final = self._turn(_required_turn_id(message, "speechStart")) + if turn.stopped: + return turn + turn.started = True + self._active_turn_id = turn.item_id + return turn + + def _transcript(self, message: Mapping[str, JsonValue]) -> _TurnState | None: + transcript: Final = message.get("transcript") + if not isinstance(transcript, str): + raise MuseProtocolError("transcript event has invalid transcript") + if not transcript and message.get("turnId") is None and self._active_turn_id is None: + return None + turn: Final = self._turn(self._transcript_turn_id(message)) + if message.get("final") is True: + self._finish(turn, transcript) + elif turn.final_text is None: + turn.latest_partial = transcript + return turn + + def _speech_end(self, message: Mapping[str, JsonValue]) -> _TurnState: + turn: Final = self._turn(_required_turn_id(message, "speechEnd")) + turn.stopped = True + return turn + + def _speech_complete(self, message: Mapping[str, JsonValue]) -> _TurnState: + transcript: Final = message.get("transcript") + if not isinstance(transcript, str): + raise MuseProtocolError("speechComplete event has invalid transcript") + turn: Final = self._turn(_required_turn_id(message, "speechComplete")) + self._finish(turn, transcript) + return turn + + def _finish(self, turn: _TurnState, transcript: str) -> None: + turn.finish(transcript) + self._release_active(turn) + + def _release_active(self, turn: _TurnState) -> None: + if self._active_turn_id == turn.item_id: + self._active_turn_id = None + + def _update_audio_progress(self, message: Mapping[str, JsonValue]) -> None: + processed_ms: Final = message.get("audioProcessedMs") + if ( + isinstance(processed_ms, bool) + or not isinstance(processed_ms, (int, float)) + or not math.isfinite(processed_ms) + or processed_ms < 0 + ): + raise MuseProtocolError("audioProgress event has invalid audioProcessedMs") + if processed_ms <= self._last_audio_processed_ms: + return + self._unbilled_seconds += (float(processed_ms) - self._last_audio_processed_ms) / 1000 + self._last_audio_processed_ms = float(processed_ms) + + def _transcript_turn_id(self, message: Mapping[str, JsonValue]) -> str: + if message.get("turnId") is not None: + return _required_turn_id(message, "transcript") + if self._active_turn_id is not None: + return self._active_turn_id + if self._mode != "PUSH_TO_TALK": + raise MuseProtocolError("transcript event is missing turnId outside an active turn") + turn_id: Final = f"item_{uuid.uuid4().hex}" + self._active_turn_id = turn_id + return turn_id + + +class MetaRealtimeConfig(BaseRealtimeConfig): + def __init__( + self, + *, + monotonic: Callable[[], float] = time.monotonic, + sleep: Callable[[float], Awaitable[None]] = asyncio.sleep, + ) -> None: + self._monotonic: Final = monotonic + self._sleep: Final = sleep + self._transformer: Final = MuseEventTransformer() + self._access_token: str | None = None + self._config: MuseSessionConfig | None = None + self._pending_audio: bytes = b"" + self._end_stream_sent: bool = False + self._pacing_origin: float | None = None + self._sent_duration: float = 0.0 + + def validate_environment( + self, + headers: dict[str, str], # mutable-ok: BaseRealtimeConfig contract + model: str, + api_key: str | None = None, + ) -> dict[str, str]: # mutable-ok: BaseRealtimeConfig contract + token: Final = api_key or get_secret_str("META_API_KEY") + if token is None: + raise ValueError("api_key is required for Meta API calls") + self._access_token = normalize_access_token(token) + return headers + + def get_complete_url(self, api_base: str | None, model: str, api_key: str | None = None) -> str: + if _normalize_model(model) != MUSE_MODEL: + raise ValueError(f"Unsupported Meta realtime model: {model}") + return build_muse_realtime_url(api_base) + + def is_setup_message(self, msg_obj: Mapping[str, object]) -> bool: + return "authorization" in msg_obj + + def transform_session_created_event( + self, + model: str, + logging_session_id: str, + session_configuration_request: str | None = None, + ) -> OpenAIRealtimeTranscriptionSessionCreated: + return session_created_event(_DEFAULT_SESSION_CONFIG, logging_session_id) + + def transform_realtime_request( + self, + message: str, + model: str, + session_configuration_request: str | None = None, + ) -> tuple[str | bytes, ...]: + request: Final = _json_object(message) + event_type: Final = request.get("type") + if event_type in ("session.update", "transcription_session.update"): + return self._configure(message, model) + if event_type == "input_audio_buffer.append": + return self._append_audio(request) + if event_type == "input_audio_buffer.commit": + return self._flush_audio(end_stream=self._require_config().mode == "PUSH_TO_TALK") + if event_type == "input_audio_buffer.end": + return self._flush_audio(end_stream=True) + if event_type == "input_audio_buffer.clear": + self._pending_audio = b"" + return () + verbose_logger.debug("Meta realtime: dropping unsupported client event %s", event_type) + return () + + async def pace_backend_send(self, message: bytes) -> None: + now: Final = self._monotonic() + origin: Final = self._pacing_origin + effective_origin: Final = ( + now - self._sent_duration if origin is None or now > origin + self._sent_duration else origin + ) + delay: Final = effective_origin + self._sent_duration - now + if delay > 0: + await self._sleep(delay) + self._pacing_origin = effective_origin + self._sent_duration += len(message) / self._require_config().bytes_per_second + + def unbilled_usage_on_session_close(self, model: str) -> RealtimeInputAudioTranscriptionUsage | None: + return self._transformer.take_unbilled_usage() + + def transform_realtime_response( + self, + message: str | bytes, + model: str, + logging_obj: LiteLLMLoggingObj, + realtime_response_transform_input: RealtimeResponseTransformInput, + ) -> RealtimeResponseTypedDict: + payload: Final = message.decode("utf-8") if isinstance(message, bytes) else message + result: Final[RealtimeResponseTypedDict] = { + "response": list(self._backend_events(payload)), # mutable-ok: RealtimeResponseTypedDict.response is a list + "current_output_item_id": realtime_response_transform_input.get("current_output_item_id"), + "current_response_id": realtime_response_transform_input.get("current_response_id"), + "current_delta_chunks": realtime_response_transform_input.get("current_delta_chunks"), + "current_conversation_id": realtime_response_transform_input.get("current_conversation_id"), + "current_item_chunks": realtime_response_transform_input.get("current_item_chunks"), + "current_delta_type": realtime_response_transform_input.get("current_delta_type"), + "session_configuration_request": realtime_response_transform_input.get("session_configuration_request"), + } + return result + + def _backend_events(self, payload: str) -> tuple[OpenAIRealtimeEvents, ...]: + frame: Final = _json_object(payload) + session_id: Final = frame.get("sessionId") + if session_id is None: + return self._transformer.transform(frame) + if not isinstance(session_id, str) or not session_id.strip(): + raise MuseProtocolError("provider returned an invalid handshake response") + return (session_created_event(self._require_config(), session_id.strip()),) + + def _configure(self, message: str, model: str) -> tuple[str, ...]: + if self._config is not None: + verbose_logger.debug("Meta realtime: ignoring session.update after the Muse handshake was sent") + return () + access_token: Final = self._access_token + if access_token is None: + raise MuseProtocolError("Meta API key was not validated before the session was configured") + config: Final = parse_session_update(message, model) + self._config = config + self._transformer.configure(config) + return (json.dumps(config.handshake(access_token), separators=(",", ":")),) + + def _append_audio(self, request: Mapping[str, JsonValue]) -> tuple[bytes, ...]: + config: Final = self._require_config() + encoded: Final = request.get("audio") + if not isinstance(encoded, str): + raise MuseProtocolError("Audio must be a base64 string") + if len(encoded) > config.max_encoded_append_bytes: + raise MuseProtocolError("Audio append exceeds the four-second backlog limit") + try: + audio: Final = base64.b64decode(encoded, validate=True) + except (binascii.Error, ValueError): + raise MuseProtocolError("Audio must be valid base64") from None + if len(audio) % 2: + raise MuseProtocolError("PCM16 audio must contain complete samples") + buffered: Final = self._pending_audio + audio + packet_end: Final = len(buffered) - len(buffered) % config.packet_bytes + self._pending_audio = buffered[packet_end:] + return tuple( + buffered[start : start + config.packet_bytes] for start in range(0, packet_end, config.packet_bytes) + ) + + def _flush_audio(self, *, end_stream: bool) -> tuple[str | bytes, ...]: + remainder: Final = self._pending_audio + self._pending_audio = b"" + frames: Final[tuple[bytes, ...]] = (remainder,) if remainder else () + if not end_stream or self._end_stream_sent: + return frames + self._end_stream_sent = True + return (*frames, _END_STREAM) + + def _require_config(self) -> MuseSessionConfig: + if self._config is None: + raise MuseProtocolError("session.update must configure the Muse session before audio is sent") + return self._config diff --git a/litellm/llms/openai/chat/guardrail_translation/handler.py b/litellm/llms/openai/chat/guardrail_translation/handler.py index 58ff03e6a0d..01e14f2248d 100644 --- a/litellm/llms/openai/chat/guardrail_translation/handler.py +++ b/litellm/llms/openai/chat/guardrail_translation/handler.py @@ -42,6 +42,7 @@ from litellm.llms.base_llm.guardrail_translation.utils import ( stream_item_field, stream_item_fingerprint, stream_item_items, + unappliable_request_rewrite, ) from litellm.main import stream_chunk_builder from litellm.types.llms.openai import AllMessageValues, ChatCompletionToolParam @@ -196,6 +197,8 @@ class OpenAIChatCompletionsHandler(BaseTranslation): else: # Step 3: Map guardrail responses back to original message structure if guardrailed_texts and texts_to_check: + if len(guardrailed_texts) != len(text_task_mappings): + raise unappliable_request_rewrite(guardrail_to_apply.guardrail_name) await self._apply_guardrail_responses_to_input_texts( messages=messages, responses=guardrailed_texts, @@ -210,6 +213,17 @@ class OpenAIChatCompletionsHandler(BaseTranslation): task_mappings=tool_call_task_mappings, ) + elif ( + not images_to_check + and not guardrail_to_apply.records_own_guardrail_information + and (not_run_reason := self._not_run_reason(messages)) is not None + ): + guardrail_to_apply.add_standard_logging_guardrail_information_to_request_data( + guardrail_json_response=not_run_reason, + request_data=data, + guardrail_status="not_run", + ) + verbose_proxy_logger.debug( "OpenAI Chat Completions: Processed input messages: %s", data.get("messages"), @@ -217,6 +231,28 @@ class OpenAIChatCompletionsHandler(BaseTranslation): return data + def _not_run_reason( + self, + messages: Sequence[dict[str, Any]], # mutable-ok: raw request messages consumed by _extract_inputs + ) -> str | None: + """Why nothing was scanned, or None when the only unscoped content is images, which this handler never scans.""" + texts: Final[list[str]] = [] # mutable-ok: filled by _extract_inputs + images: Final[list[str]] = [] # mutable-ok: filled by _extract_inputs + tool_calls: Final[list[ChatCompletionToolParam]] = [] # mutable-ok: filled by _extract_inputs + for msg_idx, message in enumerate(messages): + self._extract_inputs( + message=message, + msg_idx=msg_idx, + texts_to_check=texts, + images_to_check=images, + tool_calls_to_check=tool_calls, + text_task_mappings=[], # mutable-ok: required by _extract_inputs, unused here + tool_call_task_mappings=[], # mutable-ok: required by _extract_inputs, unused here + ) + if texts or tool_calls: + return "no scannable content after message scoping" + return None if images else "no scannable content" + def extract_request_tool_names(self, data: dict) -> list[str]: """Extract tool names from OpenAI chat completions request (tools[].function.name, functions[].name).""" names: Final[list[str]] = [] diff --git a/litellm/llms/openai/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py index 2fe11d9f7bd..27ff55f120c 100644 --- a/litellm/llms/openai/responses/guardrail_translation/handler.py +++ b/litellm/llms/openai/responses/guardrail_translation/handler.py @@ -56,6 +56,7 @@ from litellm.llms.base_llm.guardrail_translation.utils import ( stream_item_field, stream_item_fingerprint, stream_item_items, + unappliable_request_rewrite, ) from litellm.llms.openai.responses.guardrail_translation.tool_merge import merge_guardrailed_tools from litellm.responses.litellm_completion_transformation.transformation import ( @@ -495,13 +496,13 @@ class OpenAIResponsesHandler(BaseTranslation): data["instructions"] = written_back.instructions # rebind-ok: data is an out-param elif isinstance(input_data, str): guardrailed_texts: Final = guardrailed_inputs.get("texts") or () + if len(guardrailed_texts) > 1: + raise unappliable_request_rewrite(guardrail_to_apply.guardrail_name) data["input"] = guardrailed_texts[0] if guardrailed_texts else input_data # rebind-ok: data is an out-param else: rewritten_texts: Final = guardrailed_inputs.get("texts") or () if len(rewritten_texts) != len(extracted.task_mappings): - from litellm.proxy.policy_engine.pipeline_executor import UnappliableRequestRewrite - - raise UnappliableRequestRewrite(guardrail_to_apply.guardrail_name or "unknown") + raise unappliable_request_rewrite(guardrail_to_apply.guardrail_name) await self._apply_guardrail_responses_to_input( messages=input_data, responses=rewritten_texts, diff --git a/litellm/llms/openai/responses/guardrail_translation/tool_merge.py b/litellm/llms/openai/responses/guardrail_translation/tool_merge.py index b596adfad6f..ff67c6220e1 100644 --- a/litellm/llms/openai/responses/guardrail_translation/tool_merge.py +++ b/litellm/llms/openai/responses/guardrail_translation/tool_merge.py @@ -6,8 +6,10 @@ from typing import Final, TypeAlias from pydantic import BaseModel, TypeAdapter, ValidationError from litellm._logging import verbose_logger +from litellm.responses.litellm_completion_transformation.custom_tools import custom_tool_grammar_suffix from litellm.responses.litellm_completion_transformation.transformation import ( NAMESPACE_DESCRIPTION_SEPARATOR, + NAMESPACE_MEMBER_TYPES_WITH_CHAT_TOOLS, LiteLLMCompletionResponsesConfig, ) @@ -34,8 +36,8 @@ def _validated_tools(values: Iterable[object]) -> tuple[Tool, ...]: return tuple(tool for tool in validated if tool is not None) -def _is_function(tool: Tool) -> bool: - return tool.get("type") == "function" +def _has_chat_tool(member: Tool) -> bool: + return member.get("type") in NAMESPACE_MEMBER_TYPES_WITH_CHAT_TOOLS def _chat_tool_key(tool: Tool) -> str: @@ -67,18 +69,19 @@ def _function_fields(tool: Tool) -> Tool: return function if function is not None else MappingProxyType({}) -def _without_namespace_prefix(key: str, value: object, prefix: str) -> object: - if key != "description" or not isinstance(value, str) or not value.startswith(prefix): +def _member_description(key: str, value: object, prefix: str, suffix: str) -> object: + if key != "description" or not isinstance(value, str): return value - return value[len(prefix) :] + return value.replace(prefix, "", 1).replace(suffix, "", 1) def _rebuilt_member(member: Tool, flattened: Tool, guardrailed: Tool, namespace_description: str) -> Tool: flattened_function: Final = _function_fields(flattened) prefix: Final = f"{namespace_description}{NAMESPACE_DESCRIPTION_SEPARATOR}" if namespace_description else "" + suffix: Final = custom_tool_grammar_suffix(member.get("format")) if member.get("type") == "custom" else "" changed_function: Final = MappingProxyType( { - key: _without_namespace_prefix(key, value, prefix) + key: _member_description(key, value, prefix, suffix) for key, value in _function_fields(guardrailed).items() if flattened_function.get(key) != value } @@ -93,8 +96,8 @@ def _rebuilt_member(member: Tool, flattened: Tool, guardrailed: Tool, namespace_ return {**member, **changed_extras, **changed_function} # mutable-ok: json.dumps rejects MappingProxyType -def _rebuilt_function_members( - function_members: Sequence[Tool], +def _rebuilt_flattened_members( + flattened_members: Sequence[Tool], flattened_group: Sequence[Tool], group_keys: Sequence[IndexedKey], guardrailed_by_key: Mapping[IndexedKey, Tool], @@ -106,7 +109,7 @@ def _rebuilt_function_members( else member if guardrailed_by_key[key] == flattened else _rebuilt_member(member, flattened, guardrailed_by_key[key], namespace_description) - for member, flattened, key in zip(function_members, flattened_group, group_keys) + for member, flattened, key in zip(flattened_members, flattened_group, group_keys) ) @@ -118,9 +121,9 @@ def _rebuilt_namespace( guardrailed_by_key: Mapping[IndexedKey, Tool], ) -> tuple[Tool, ...]: namespace_description: Final = str(original.get("description") or "") - rebuilt_functions: Final = iter( - _rebuilt_function_members( - tuple(member for member in members if _is_function(member)), + rebuilt_flattened: Final = iter( + _rebuilt_flattened_members( + tuple(member for member in members if _has_chat_tool(member)), flattened_group, group_keys, guardrailed_by_key, @@ -129,7 +132,7 @@ def _rebuilt_namespace( ) rebuilt_members: Final = tuple( rebuilt - for rebuilt in (next(rebuilt_functions) if _is_function(member) else member for member in members) + for rebuilt in (next(rebuilt_flattened) if _has_chat_tool(member) else member for member in members) if rebuilt is not None ) if not rebuilt_members: @@ -149,7 +152,7 @@ def _merged_original( if guardrailed_group == tuple(flattened_group): return (original,) members: Final = _namespace_members(original) if original.get("type") == "namespace" else () - if members and sum(map(_is_function, members)) == len(flattened_group): + if members and sum(map(_has_chat_tool, members)) == len(flattened_group): return _rebuilt_namespace(original, members, flattened_group, group_keys, guardrailed_by_key) if not guardrailed_group: return () diff --git a/litellm/llms/openai_like/providers.json b/litellm/llms/openai_like/providers.json index a458a209ea9..fe10293c420 100644 --- a/litellm/llms/openai_like/providers.json +++ b/litellm/llms/openai_like/providers.json @@ -173,7 +173,7 @@ "api_key_env": "META_API_KEY", "api_base_env": "META_API_BASE", "base_class": "openai_gpt", - "supported_endpoints": ["/v1/chat/completions", "/v1/responses", "/v1/messages"] + "supported_endpoints": ["/v1/chat/completions", "/v1/responses", "/v1/messages", "/v1/realtime"] }, "cognition": { "base_url": "https://api.cognition.ai/v1", diff --git a/litellm/llms/vertex_ai/batches/transformation.py b/litellm/llms/vertex_ai/batches/transformation.py index e63c80dd3cf..f5f1ab2068a 100644 --- a/litellm/llms/vertex_ai/batches/transformation.py +++ b/litellm/llms/vertex_ai/batches/transformation.py @@ -1,3 +1,4 @@ +from collections.abc import Mapping from typing import Any, Final from urllib.parse import unquote @@ -8,7 +9,36 @@ from litellm.llms.vertex_ai.common_utils import ( ) from litellm.types.llms.openai import BatchJobStatus, CreateBatchRequest from litellm.types.llms.vertex_ai import * -from litellm.types.utils import LiteLLMBatch +from litellm.types.utils import LiteLLMBatch, PromptTokensDetailsWrapper + + +def vertex_prompt_tokens_details( + usage_metadata: Mapping[str, object], +) -> PromptTokensDetailsWrapper | None: + raw_details: Final = usage_metadata.get("promptTokensDetails") + if not isinstance(raw_details, list): + return None + + def _normalize(detail: object) -> tuple[str, int] | None: + if not isinstance(detail, Mapping): + return None + modality: Final = detail.get("modality") + token_count: Final = detail.get("tokenCount") + if not isinstance(modality, str) or not isinstance(token_count, int): + return None + return modality.upper(), token_count + + parsed_details: Final = tuple(_normalize(detail) for detail in raw_details) + normalized: Final = tuple(detail for detail in parsed_details if detail is not None) + if len(normalized) != len(parsed_details): + return None + + return PromptTokensDetailsWrapper( + text_tokens=sum(token_count for modality, token_count in normalized if modality in ("TEXT", "DOCUMENT")), + audio_tokens=sum(token_count for modality, token_count in normalized if modality == "AUDIO"), + image_tokens=sum(token_count for modality, token_count in normalized if modality == "IMAGE"), + video_tokens=sum(token_count for modality, token_count in normalized if modality == "VIDEO"), + ) class VertexAIBatchTransformation: diff --git a/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py b/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py index e7fd9a0d08b..d669acecfd9 100644 --- a/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py +++ b/litellm/llms/vertex_ai/gemini_embeddings/batch_embed_content_transformation.py @@ -298,8 +298,6 @@ def transform_openai_input_gemini_embed_content( _IMAGE_MIME_TYPES: Final = frozenset({"image/png", "image/jpeg"}) -_VIDEO_TOKENS_PER_SECOND: Final = 258.0 -_AUDIO_TOKENS_PER_SECOND: Final = 32.0 _usage_metadata_adapter: Final = TypeAdapter(UsageMetadata) @@ -339,11 +337,12 @@ def _is_image_element( return False -def _count_input_images( +def _is_image_only_input( input: GeminiEmbeddingInput, resolved_files: Mapping[str, Mapping[str, str]], -) -> int: - return sum(1 for element in _flatten_input(input) if _is_image_element(element, resolved_files)) +) -> bool: + elements: Final = _flatten_input(input) + return bool(elements) and all(_is_image_element(element, resolved_files) for element in elements) def _tokens_for_modality(details: Sequence[PromptTokensDetails], modality: str) -> int: @@ -372,30 +371,29 @@ def _usage_from_embed_content_response( total_tokens: Final = usage_metadata.get("totalTokenCount") or prompt_tokens details: Final[Sequence[PromptTokensDetails]] = usage_metadata.get("promptTokensDetails") or () + if not details: + return Usage( + prompt_tokens=prompt_tokens, + total_tokens=total_tokens, + prompt_tokens_details=PromptTokensDetailsWrapper( + text_tokens=0, + image_tokens=prompt_tokens if _is_image_only_input(input, resolved_files) else 0, + ), + ) + text_tokens: Final = _tokens_for_modality(details, "TEXT") audio_tokens: Final = _tokens_for_modality(details, "AUDIO") + image_tokens: Final = _tokens_for_modality(details, "IMAGE") video_tokens: Final = _tokens_for_modality(details, "VIDEO") - image_count: Final = _count_input_images(input, resolved_files) - - video_length_seconds: Final = video_tokens / _VIDEO_TOKENS_PER_SECOND if video_tokens > 0 else 0.0 - audio_length_seconds: Final = audio_tokens / _AUDIO_TOKENS_PER_SECOND if audio_tokens > 0 else 0.0 - - # generic_cost_per_token rewrites text_tokens to the full prompt minus - # other modalities when both text_tokens and image_count are zero. For - # video, that misallocates video tokens to text; a 1-token floor sidesteps - # the rewrite and keeps billing on input_cost_per_video_per_second. - needs_video_text_floor: Final = video_length_seconds > 0 and text_tokens == 0 and image_count == 0 - resolved_text_tokens: Final = 1 if needs_video_text_floor else text_tokens return Usage( prompt_tokens=prompt_tokens, total_tokens=total_tokens, prompt_tokens_details=PromptTokensDetailsWrapper( - text_tokens=resolved_text_tokens, + text_tokens=text_tokens, audio_tokens=audio_tokens, - image_count=image_count, - video_length_seconds=video_length_seconds, - audio_length_seconds=audio_length_seconds, + image_tokens=image_tokens, + video_tokens=video_tokens, ), ) @@ -415,8 +413,7 @@ def process_embed_content_response( model_response: EmbeddingResponse to populate model: Model name response_json: Raw JSON response from embedContent endpoint - resolved_files: Mapping of file references (files/abc) to {mime_type, uri}, - used to bill resolved image references at the per-image rate + resolved_files: Mapping of file references to resolved metadata Returns: EmbeddingResponse with single embedding diff --git a/litellm/main.py b/litellm/main.py index 17edafcdfca..f6f4ec1bf63 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -2592,7 +2592,9 @@ def _complete_custom_openai( copilot_headers.update(extra_headers) extra_headers = copilot_headers - if extra_headers is not None: + use_base_llm_http_handler: Final = get_secret_bool("EXPERIMENTAL_OPENAI_BASE_LLM_HTTP_HANDLER") + + if extra_headers is not None and not use_base_llm_http_handler: optional_params["extra_headers"] = extra_headers if litellm.enable_preview_features and metadata is not None: # [PREVIEW] allow metadata to be passed to OPENAI @@ -2609,8 +2611,6 @@ def _complete_custom_openai( optional_params[k] = v ## COMPLETION CALL - use_base_llm_http_handler: Final = get_secret_bool("EXPERIMENTAL_OPENAI_BASE_LLM_HTTP_HANDLER") - try: if use_base_llm_http_handler: response = base_llm_http_handler.completion( diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 7fa09951eae..9f91cf82f41 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -4497,7 +4497,7 @@ }, "azure/eu/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.65e-05, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -4543,7 +4543,7 @@ }, "azure/eu/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, - "deprecation_date": "2026-10-01", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -5513,7 +5513,8 @@ }, "azure/gpt-realtime-2025-08-28": { "cache_creation_input_audio_token_cost": 4e-06, - "cache_read_input_token_cost": 4e-06, + "cache_read_input_audio_token_cost": 4e-07, + "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-03-02", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, @@ -5546,7 +5547,8 @@ }, "azure/gpt-realtime-1.5-2026-02-23": { "cache_creation_input_audio_token_cost": 4e-06, - "cache_read_input_token_cost": 4e-06, + "cache_read_input_audio_token_cost": 4e-07, + "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-08-24", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, @@ -5683,6 +5685,7 @@ }, "azure/gpt-realtime-mini": { "cache_creation_input_audio_token_cost": 3e-07, + "cache_read_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 6e-08, "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, @@ -5715,6 +5718,7 @@ }, "azure/gpt-realtime-mini-2025-10-06": { "cache_creation_input_audio_token_cost": 3e-07, + "cache_read_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 6e-08, "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, @@ -7409,6 +7413,80 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/gpt-chat-latest": { + "cache_read_input_token_cost": 5e-07, + "deprecation_date": "2026-12-02", + "input_cost_per_token": 5e-06, + "litellm_provider": "azure", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "reasoning_effort_levels": [ + "medium" + ], + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, + "azure/chat-latest": { + "cache_read_input_token_cost": 5e-07, + "deprecation_date": "2026-12-02", + "input_cost_per_token": 5e-06, + "litellm_provider": "azure", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "reasoning_effort_levels": [ + "medium" + ], + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "azure/us/gpt-5.6": { "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_272k_tokens": 1.375e-05, @@ -7675,6 +7753,43 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/us/gpt-chat-latest": { + "cache_read_input_token_cost": 5.5e-07, + "deprecation_date": "2026-12-02", + "input_cost_per_token": 5.5e-06, + "litellm_provider": "azure", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3.3e-05, + "reasoning_effort_levels": [ + "medium" + ], + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "azure/eu/gpt-5.6": { "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_272k_tokens": 1.375e-05, @@ -8730,7 +8845,7 @@ "supports_function_calling": true }, "azure/o1": { - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 7.5e-06, "input_cost_per_token": 1.5e-05, "litellm_provider": "azure", @@ -8748,7 +8863,7 @@ }, "azure/o1-2024-12-17": { "cache_read_input_token_cost": 7.5e-06, - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.5e-05, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -8825,7 +8940,7 @@ "supports_vision": false }, "azure/o3": { - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 2e-06, "litellm_provider": "azure", @@ -8855,7 +8970,7 @@ "supports_vision": true }, "azure/o3-2025-04-16": { - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 2e-06, "litellm_provider": "azure", @@ -8886,7 +9001,7 @@ }, "azure/o3-deep-research": { "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-12-26", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1e-05, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -8923,7 +9038,7 @@ "supports_web_search": true }, "azure/o3-mini": { - "deprecation_date": "2026-10-01", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 1.1e-06, "litellm_provider": "azure", @@ -8940,7 +9055,7 @@ }, "azure/o3-mini-2025-01-31": { "cache_read_input_token_cost": 5.5e-07, - "deprecation_date": "2026-10-01", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.1e-06, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -8954,7 +9069,7 @@ "supports_vision": false }, "azure/o3-pro": { - "deprecation_date": "2026-12-17", + "deprecation_date": "2026-11-19", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "azure", @@ -8985,7 +9100,7 @@ "supports_vision": true }, "azure/o3-pro-2025-06-10": { - "deprecation_date": "2026-12-17", + "deprecation_date": "2026-11-19", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "azure", @@ -9016,7 +9131,7 @@ "supports_vision": true }, "azure/o4-mini": { - "deprecation_date": "2026-10-16", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 2.75e-07, "input_cost_per_token": 1.1e-06, "litellm_provider": "azure", @@ -9047,7 +9162,7 @@ }, "azure/o4-mini-2025-04-16": { "cache_read_input_token_cost": 2.75e-07, - "deprecation_date": "2026-10-16", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.1e-06, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -9600,7 +9715,7 @@ }, "azure/us/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.65e-05, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -9645,7 +9760,7 @@ "supports_vision": false }, "azure/us/o3-2025-04-16": { - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 2.2e-06, "litellm_provider": "azure", @@ -9676,7 +9791,7 @@ }, "azure/us/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, - "deprecation_date": "2026-10-01", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -9693,7 +9808,7 @@ }, "azure/us/o4-mini-2025-04-16": { "cache_read_input_token_cost": 3.1e-07, - "deprecation_date": "2026-10-16", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.21e-06, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -11101,12 +11216,15 @@ "babbage-002": { "deprecation_date": "2026-09-28", "input_cost_per_token": 4e-07, + "input_cost_per_token_batches": 2e-07, "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "completion", - "output_cost_per_token": 4e-07 + "output_cost_per_token": 4e-07, + "output_cost_per_token_batches": 2e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "bedrock/*/1-month-commitment/cohere.command-light-text-v14": { "input_cost_per_second": 0.001902, @@ -13171,7 +13289,9 @@ "supported_endpoints": [ "/v1/audio/transcriptions" ], - "deprecation_date": "2027-02-26" + "deprecation_date": "2027-02-26", + "input_cost_per_second": 0.0001, + "source": "https://developers.openai.com/api/docs/pricing" }, "claude-haiku-4-5-20251001": { "deprecation_date": "2026-10-15", @@ -13219,7 +13339,8 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true, - "prompt_cache_min_tokens": 4096 + "prompt_cache_min_tokens": 4096, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-3-7-sonnet-20250219": { "cache_creation_input_token_cost": 3.75e-06, @@ -13378,7 +13499,8 @@ "supports_native_structured_output": true, "supports_tool_choice": true, "supports_vision": true, - "prompt_cache_min_tokens": 1024 + "prompt_cache_min_tokens": 1024, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-sonnet-4-5-20250929": { "deprecation_date": "2026-09-29", @@ -13452,7 +13574,7 @@ }, "supports_output_config": true, "prompt_cache_min_tokens": 1024, - "source": "https://docs.anthropic.com/en/docs/about-claude/models/overview" + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-sonnet-4-6": { "deprecation_date": "2027-02-17", @@ -13488,7 +13610,8 @@ "prompt_cache_min_tokens": 1024, "provider_specific_entry": { "us": 1.1 - } + }, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-sonnet-4-5-20250929-v1:0": { "cache_creation_input_token_cost": 3.75e-06, @@ -13665,7 +13788,8 @@ "supports_tool_choice": true, "supports_vision": true, "supports_output_config": true, - "prompt_cache_min_tokens": 4096 + "prompt_cache_min_tokens": 4096, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-opus-4-6": { "deprecation_date": "2027-02-05", @@ -13702,7 +13826,8 @@ "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_speed": true, - "prompt_cache_min_tokens": 4096 + "prompt_cache_min_tokens": 4096, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-opus-4-6-20260205": { "deprecation_date": "2027-02-05", @@ -13777,7 +13902,8 @@ }, "supports_output_config": true, "supports_speed": true, - "prompt_cache_min_tokens": 2048 + "prompt_cache_min_tokens": 2048, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-opus-4-7-20260416": { "deprecation_date": "2027-04-16", @@ -13855,7 +13981,7 @@ "supports_output_config": true, "prompt_cache_min_tokens": 512, "supports_native_structured_output": true, - "source": "https://docs.anthropic.com/en/docs/about-claude/models/overview" + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-fable-5-1": { "deprecation_date": "2027-09-01", @@ -13896,7 +14022,7 @@ "supports_output_config": true, "prompt_cache_min_tokens": 512, "supports_native_structured_output": true, - "source": "https://platform.claude.com/docs/en/models/fable-5-1/overview" + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-opus-5": { "deprecation_date": "2027-07-24", @@ -13937,7 +14063,7 @@ "supports_output_config": true, "supports_speed": true, "prompt_cache_min_tokens": 512, - "source": "https://docs.anthropic.com/en/docs/about-claude/models/overview" + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-opus-4-8": { "deprecation_date": "2027-05-28", @@ -13977,7 +14103,8 @@ }, "supports_output_config": true, "supports_speed": true, - "prompt_cache_min_tokens": 1024 + "prompt_cache_min_tokens": 1024, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-sonnet-4-20250514": { "deprecation_date": "2026-06-15", @@ -14615,7 +14742,7 @@ }, "computer-use-preview": { "input_cost_per_token": 3e-06, - "litellm_provider": "azure", + "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 1024, "max_tokens": 1024, @@ -14633,12 +14760,14 @@ ], "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_pdf_input": true, "supports_prompt_caching": false, "supports_reasoning": true, - "supports_response_schema": true, + "supports_response_schema": false, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "source": "https://platform.openai.com/docs/models/computer-use-preview" }, "dall-e-2": { "deprecation_date": "2026-05-12", @@ -17597,6 +17726,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true }, "databricks/databricks-claude-fable-5": { @@ -17622,6 +17752,7 @@ "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": false, @@ -17651,6 +17782,7 @@ "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true, @@ -17676,6 +17808,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 4096 }, @@ -17699,6 +17832,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 1024 }, @@ -17722,6 +17856,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 1024 }, @@ -17745,6 +17880,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "supports_output_config": true, "prompt_cache_min_tokens": 4096 @@ -17770,6 +17906,7 @@ "supports_legacy_thinking": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 4096 }, @@ -17795,6 +17932,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true @@ -17822,6 +17960,7 @@ "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true @@ -17849,6 +17988,7 @@ "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true @@ -17875,6 +18015,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true }, "databricks/databricks-claude-sonnet-4-1": { @@ -17897,6 +18038,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true }, "databricks/databricks-claude-sonnet-4-5": { @@ -17919,6 +18061,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 1024 }, @@ -17943,6 +18086,7 @@ "supports_legacy_thinking": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 1024 }, @@ -17969,6 +18113,7 @@ "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true @@ -18047,6 +18192,7 @@ "output_dbu_cost_per_token": 3.5714e-05, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, + "supports_anthropic_thinking_payload": true, "supports_prompt_caching": true, "supports_tool_choice": true }, @@ -18067,6 +18213,7 @@ "output_dbu_cost_per_token": 0.000142857, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, + "supports_anthropic_thinking_payload": true, "supports_prompt_caching": true, "supports_tool_choice": true }, @@ -19226,12 +19373,15 @@ "davinci-002": { "deprecation_date": "2026-09-28", "input_cost_per_token": 2e-06, + "input_cost_per_token_batches": 1e-06, "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "completion", - "output_cost_per_token": 2e-06 + "output_cost_per_token": 2e-06, + "output_cost_per_token_batches": 1e-06, + "source": "https://developers.openai.com/api/docs/pricing" }, "deepgram/base": { "input_cost_per_second": 0.00020833, @@ -22278,15 +22428,18 @@ "supports_vision": false }, "fireworks_ai/accounts/fireworks/models/deepseek-v4-pro": { - "cache_read_input_token_cost": 1.45e-07, - "input_cost_per_token": 1.74e-06, + "cache_read_input_token_cost": 6e-07, + "cache_read_input_token_cost_priority": 6e-07, + "input_cost_per_token": 1.2e-06, + "input_cost_per_token_priority": 1.2e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 384000, "max_tokens": 384000, "mode": "chat", - "output_cost_per_token": 3.48e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token": 1.2e-06, + "output_cost_per_token_priority": 1.2e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22295,14 +22448,17 @@ }, "fireworks_ai/accounts/fireworks/models/deepseek-v4-pro-0813": { "cache_read_input_token_cost": 4.4e-08, + "cache_read_input_token_cost_priority": 5.5e-08, "input_cost_per_token": 1.32e-06, + "input_cost_per_token_priority": 1.65e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 3.96e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 4.95e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22397,14 +22553,17 @@ }, "fireworks_ai/accounts/fireworks/models/glm-5p2": { "cache_read_input_token_cost": 1.4e-07, + "cache_read_input_token_cost_priority": 1.75e-07, "input_cost_per_token": 1.4e-06, + "input_cost_per_token_priority": 1.75e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 5.5e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22413,14 +22572,17 @@ }, "fireworks_ai/accounts/fireworks/models/gpt-oss-120b": { "cache_read_input_token_cost": 1.5e-08, + "cache_read_input_token_cost_priority": 1.8e-08, "input_cost_per_token": 1.5e-07, + "input_cost_per_token_priority": 1.8e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 7.2e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22499,14 +22661,17 @@ }, "fireworks_ai/accounts/fireworks/models/kimi-k2p6": { "cache_read_input_token_cost": 1.6e-07, + "cache_read_input_token_cost_priority": 2.2e-07, "input_cost_per_token": 9.5e-07, + "input_cost_per_token_priority": 1.5e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 6e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22515,14 +22680,17 @@ }, "fireworks_ai/accounts/fireworks/models/kimi-k2p7-code": { "cache_read_input_token_cost": 1.9e-07, + "cache_read_input_token_cost_priority": 2.85e-07, "input_cost_per_token": 9.5e-07, + "input_cost_per_token_priority": 1.425e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 6e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22648,14 +22816,17 @@ }, "fireworks_ai/accounts/fireworks/models/minimax-m2p7": { "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_priority": 6e-07, "input_cost_per_token": 3e-07, + "input_cost_per_token_priority": 1.2e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 196608, "max_output_tokens": 196608, "max_tokens": 196608, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 1.2e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22664,14 +22835,17 @@ }, "fireworks_ai/accounts/fireworks/models/minimax-m3": { "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_priority": 9e-08, "input_cost_per_token": 3e-07, + "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 512000, "max_output_tokens": 512000, "max_tokens": 512000, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 1.8e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22747,15 +22921,18 @@ "supports_vision": false }, "fireworks_ai/deepseek-v4-pro": { - "cache_read_input_token_cost": 1.45e-07, - "input_cost_per_token": 1.74e-06, + "cache_read_input_token_cost": 6e-07, + "cache_read_input_token_cost_priority": 6e-07, + "input_cost_per_token": 1.2e-06, + "input_cost_per_token_priority": 1.2e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 384000, "max_tokens": 384000, "mode": "chat", - "output_cost_per_token": 3.48e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token": 1.2e-06, + "output_cost_per_token_priority": 1.2e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22811,14 +22988,17 @@ }, "fireworks_ai/glm-5p2": { "cache_read_input_token_cost": 1.4e-07, + "cache_read_input_token_cost_priority": 1.75e-07, "input_cost_per_token": 1.4e-06, + "input_cost_per_token_priority": 1.75e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 5.5e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22827,14 +23007,17 @@ }, "fireworks_ai/gpt-oss-120b": { "cache_read_input_token_cost": 1.5e-08, + "cache_read_input_token_cost_priority": 1.8e-08, "input_cost_per_token": 1.5e-07, + "input_cost_per_token_priority": 1.8e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 7.2e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22873,14 +23056,17 @@ }, "fireworks_ai/kimi-k2p6": { "cache_read_input_token_cost": 1.6e-07, + "cache_read_input_token_cost_priority": 2.2e-07, "input_cost_per_token": 9.5e-07, + "input_cost_per_token_priority": 1.5e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 6e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22905,14 +23091,17 @@ }, "fireworks_ai/kimi-k2p7-code": { "cache_read_input_token_cost": 1.9e-07, + "cache_read_input_token_cost_priority": 2.85e-07, "input_cost_per_token": 9.5e-07, + "input_cost_per_token_priority": 1.425e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 6e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22951,14 +23140,17 @@ }, "fireworks_ai/minimax-m2p7": { "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_priority": 6e-07, "input_cost_per_token": 3e-07, + "input_cost_per_token_priority": 1.2e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 196608, "max_output_tokens": 196608, "max_tokens": 196608, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 1.2e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22967,14 +23159,17 @@ }, "fireworks_ai/minimax-m3": { "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_priority": 9e-08, "input_cost_per_token": 3e-07, + "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 512000, "max_output_tokens": 512000, "max_tokens": 512000, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 1.8e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22990,7 +23185,7 @@ "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 1.6e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -23033,112 +23228,234 @@ "output_cost_per_token": 0.0, "source": "https://fireworks.ai/pricing" }, - "friendliai/meta-llama-3.1-70b-instruct": { - "input_cost_per_token": 6e-07, - "litellm_provider": "friendliai", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 6e-07, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - 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"supports_reasoning": true, "reasoning_effort_levels": [ "low", "high", "max" ], + "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, "supports_native_structured_output": true, "supports_system_messages": true, "supports_tool_choice": true, + "supports_vision": false, + "supports_image_input": false, + "supports_video_input": false, "mode": "chat", "comment": "Flagship GLM model for long-horizon coding, agents, and complex project delivery", - "source": "https://api.friendli.ai/serverless/v1/models", + "source": "https://api.friendli.ai/serverless/v1/models" + }, + "friendliai/google/gemma-4-31B-it": { + "litellm_provider": "friendliai", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "max_tokens": 262144, + "input_cost_per_token": 1.4e-07, + "output_cost_per_token": 4e-07, + "supports_prompt_caching": false, + "supports_reasoning": true, + "reasoning_effort_levels": [], + "supports_function_calling": true, + 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"supports_video_input": false, + "mode": "chat", + "comment": "DeepSeek chat model for instruction following, coding, and analysis", + "source": "https://api.friendli.ai/serverless/v1/models" + }, + "friendliai/MiniMaxAI/MiniMax-M2.5": { + "litellm_provider": "friendliai", + "max_input_tokens": 196608, + "max_output_tokens": 196608, + "max_tokens": 196608, + "input_cost_per_token": 3e-07, + "output_cost_per_token": 1.2e-06, + "cache_read_input_token_cost": 6e-08, + "supports_prompt_caching": true, + "supports_reasoning": true, + "reasoning_effort_levels": [], + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_response_schema": true, + "supports_native_structured_output": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": false, + "supports_image_input": false, + "supports_video_input": false, + "mode": "chat", + "comment": "Prior MiniMax coding model for agent workflows, office edits, and automation", + "source": "https://api.friendli.ai/serverless/v1/models" + }, + "friendliai/zai-org/GLM-5.1": { + "litellm_provider": "friendliai", + "max_input_tokens": 202752, + "max_output_tokens": 202752, + "max_tokens": 202752, + "input_cost_per_token": 1.4e-06, + "output_cost_per_token": 4.4e-06, + "cache_read_input_token_cost": 2.6e-07, + "supports_prompt_caching": true, + "supports_reasoning": true, + "reasoning_effort_levels": [], + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_response_schema": true, + "supports_native_structured_output": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": false, + "supports_image_input": false, + "supports_video_input": false, + "mode": "chat", + "comment": "Strong GLM coding model for agentic engineering, terminals, and repository generation", + "source": "https://api.friendli.ai/serverless/v1/models" }, "ft:babbage-002": { "deprecation_date": "2026-10-23", "input_cost_per_token": 1.6e-06, - "input_cost_per_token_batches": 2e-07, + "input_cost_per_token_batches": 8e-07, "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "completion", "output_cost_per_token": 1.6e-06, - "output_cost_per_token_batches": 2e-07 + "output_cost_per_token_batches": 9e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "ft:davinci-002": { "deprecation_date": "2026-10-23", "input_cost_per_token": 1.2e-05, - "input_cost_per_token_batches": 1e-06, + "input_cost_per_token_batches": 6e-06, "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "completion", "output_cost_per_token": 1.2e-05, - "output_cost_per_token_batches": 1e-06 + "output_cost_per_token_batches": 6e-06, + "source": "https://developers.openai.com/api/docs/pricing" }, "ft:gpt-3.5-turbo": { "deprecation_date": "2026-10-23", @@ -23151,6 +23468,7 @@ "mode": "chat", "output_cost_per_token": 6e-06, "output_cost_per_token_batches": 3e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_system_messages": true, "supports_tool_choice": true }, @@ -23207,14 +23525,15 @@ "ft:gpt-4o-2024-08-06": { "cache_read_input_token_cost": 1.875e-06, "input_cost_per_token": 3.75e-06, - "input_cost_per_token_batches": 1.875e-06, + "input_cost_per_token_batches": 2.225e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.5e-05, - "output_cost_per_token_batches": 7.5e-06, + "output_cost_per_token_batches": 1.25e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -23252,6 +23571,7 @@ "mode": "chat", "output_cost_per_token": 1.2e-06, "output_cost_per_token_batches": 6e-07, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -23271,6 +23591,7 @@ "mode": "chat", "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -23289,6 +23610,7 @@ "mode": "chat", "output_cost_per_token": 3.2e-06, "output_cost_per_token_batches": 1.6e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -23308,6 +23630,7 @@ "mode": "chat", "output_cost_per_token": 8e-07, "output_cost_per_token_batches": 4e-07, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -23327,6 +23650,7 @@ "mode": "chat", "output_cost_per_token": 1.6e-05, "output_cost_per_token_batches": 8e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_prompt_caching": true, @@ -23337,15 +23661,18 @@ "gemini-2.0-flash": { "cache_read_input_token_cost": 2.5e-08, "deprecation_date": "2026-06-01", - "input_cost_per_audio_token": 7e-07, - "input_cost_per_token": 1e-07, + "input_cost_per_audio_token": 1e-06, + "input_cost_per_character": 3.75e-08, + "input_cost_per_token": 1.5e-07, + "input_cost_per_token_batches": 7.5e-08, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 8192, "max_tokens": 8192, "mode": "chat", - "output_cost_per_token": 4e-07, - "source": "https://ai.google.dev/pricing#2_0flash", + "output_cost_per_token": 6e-07, + "output_cost_per_token_batches": 3e-07, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_modalities": [ "text", "image", @@ -23414,13 +23741,16 @@ "cache_read_input_token_cost": 1.875e-08, "deprecation_date": "2026-06-01", "input_cost_per_audio_token": 7.5e-08, + "input_cost_per_character": 1.875e-08, "input_cost_per_token": 7.5e-08, + "input_cost_per_token_batches": 3.75e-08, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 3e-07, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-2.0-flash", + "output_cost_per_token_batches": 1.5e-07, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_modalities": [ "text", "image", @@ -23481,8 +23811,11 @@ } }, "gemini-2.5-flash": { + "cache_read_input_audio_token_cost": 1e-07, "deprecation_date": "2026-10-20", "cache_read_input_token_cost": 3e-08, + "cache_read_input_token_cost_flex": 3e-08, + "cache_read_input_token_cost_priority": 5.4e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, "litellm_provider": "vertex_ai-language-models", @@ -23492,7 +23825,7 @@ "mode": "chat", "output_cost_per_reasoning_token": 2.5e-06, "output_cost_per_token": 2.5e-06, - "source": "https://ai.google.dev/gemini-api/docs/models#gemini-2.5-flash-preview", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23525,6 +23858,12 @@ "search_context_size_high": 0.035 }, "google_maps_grounding_cost_per_query": 0.025, + "input_cost_per_token_batches": 1.5e-07, + "input_cost_per_token_flex": 1.5e-07, + "input_cost_per_token_priority": 5.4e-07, + "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 }, "gemini-2.5-flash-image": { @@ -23532,6 +23871,9 @@ "cache_read_input_token_cost": 3e-08, "input_cost_per_audio_token": 1e-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": 32768, "max_output_tokens": 32768, @@ -23541,8 +23883,10 @@ "output_cost_per_image_token": 3e-05, "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, "rpm": 100000, - "source": "https://ai.google.dev/gemini-api/docs/pricing#gemini-2.5-flash-image", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23573,10 +23917,19 @@ "supports_image_size": false }, "gemini-3-pro-image": { + "cache_read_input_token_cost": 2e-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_flex": 1e-07, + "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, + "input_cost_per_token_above_200k_tokens": 4e-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, + "input_cost_per_token_priority": 3.6e-06, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 32768, @@ -23585,8 +23938,12 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "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, "output_cost_per_token_batches": 6e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing#gemini-3-pro-image", + "output_cost_per_token_flex": 6e-06, + "output_cost_per_token_priority": 2.16e-05, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23654,9 +24011,13 @@ "web_search_billing_unit": "per_query" }, "gemini-3.1-flash-image": { + "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_flex": 2.5e-08, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.00056, "input_cost_per_token": 5e-07, + "input_cost_per_token_batches": 2.5e-07, + "input_cost_per_token_flex": 2.5e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 32768, @@ -23665,7 +24026,9 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_token": 3e-06, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "output_cost_per_token_batches": 1.5e-06, + "output_cost_per_token_flex": 1.5e-06, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23732,9 +24095,11 @@ }, "gemini-3.1-flash-lite-image": { "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_flex": 1.25e-08, "input_cost_per_image": 0.00028, "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, + "input_cost_per_token_flex": 1.25e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 4096, @@ -23744,6 +24109,7 @@ "output_cost_per_image_token": 3e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, + "output_cost_per_token_flex": 7.5e-07, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -23818,6 +24184,7 @@ "google_maps_grounding_cost_per_query": 0.014 }, "gemini-3.1-flash-lite": { + "cache_read_input_audio_token_cost": 5e-08, "deprecation_date": "2027-05-07", "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_flex": 1.25e-08, @@ -23837,7 +24204,7 @@ "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, "output_cost_per_token_priority": 2.7e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing#gemini-3.1-flash-lite", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23879,7 +24246,7 @@ "deprecation_date": "2027-07-21", "cache_read_input_token_cost": 3e-08, "cache_read_input_token_cost_flex": 1.5e-08, - "cache_read_input_token_cost_priority": 5e-08, + "cache_read_input_token_cost_priority": 5.4e-08, "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -23894,7 +24261,7 @@ "output_cost_per_token_batches": 1.25e-06, "output_cost_per_token_flex": 1.25e-06, "output_cost_per_token_priority": 4.5e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23933,6 +24300,7 @@ "google_maps_grounding_cost_per_query": 0.014 }, "deep-research-pro-preview-12-2025": { + "cache_read_input_token_cost": 2e-07, "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -23945,7 +24313,7 @@ "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23967,8 +24335,11 @@ "supports_web_search": true }, "gemini-2.5-flash-lite": { + "cache_read_input_audio_token_cost": 3e-08, "deprecation_date": "2026-10-20", "cache_read_input_token_cost": 1e-08, + "cache_read_input_token_cost_flex": 1e-08, + "cache_read_input_token_cost_priority": 1.8e-08, "input_cost_per_audio_token": 3e-07, "input_cost_per_token": 1e-07, "litellm_provider": "vertex_ai-language-models", @@ -23978,7 +24349,7 @@ "mode": "chat", "output_cost_per_reasoning_token": 4e-07, "output_cost_per_token": 4e-07, - "source": "https://ai.google.dev/gemini-api/docs/models#gemini-2.5-flash-preview", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24011,6 +24382,12 @@ "search_context_size_high": 0.035 }, "google_maps_grounding_cost_per_query": 0.025, + "input_cost_per_token_batches": 5e-08, + "input_cost_per_token_flex": 5e-08, + "input_cost_per_token_priority": 1.8e-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 }, "gemini-2.5-flash-lite-preview-09-2025": { @@ -24162,7 +24539,7 @@ "mode": "realtime", "output_cost_per_audio_token": 1.2e-05, "output_cost_per_token": 2e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/vertex_ai/live" ], @@ -24193,7 +24570,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "gemini_native_audio": true + "gemini_native_audio": true, + "input_cost_per_image_token": 3e-06 }, "gemini/gemini-live-2.5-flash-preview-native-audio-09-2025": { "cache_read_input_token_cost": 7.5e-08, @@ -24293,6 +24671,9 @@ "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, + "cache_read_input_token_cost_above_200k_tokens_priority": 4.5e-07, + "cache_read_input_token_cost_flex": 1.25e-07, + "cache_read_input_token_cost_priority": 2.25e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, "litellm_provider": "vertex_ai-language-models", @@ -24302,7 +24683,7 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_above_200k_tokens": 1.5e-05, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions" @@ -24332,7 +24713,15 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "google_maps_grounding_cost_per_query": 0.025 + "google_maps_grounding_cost_per_query": 0.025, + "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_priority": 2.7e-05, + "output_cost_per_token_batches": 5e-06, + "output_cost_per_token_flex": 5e-06, + "output_cost_per_token_priority": 1.8e-05 }, "gemini-3-pro-preview": { "deprecation_date": "2026-03-26", @@ -24407,7 +24796,7 @@ "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_image": 0.00012, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24441,13 +24830,16 @@ "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "cache_read_input_token_cost_priority": 3.6e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, + "cache_read_input_token_cost_flex": 2e-07, "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 6e-06 }, "gemini-3.1-pro-preview-customtools": { "prompt_cache_min_tokens": 4096, @@ -24558,7 +24950,9 @@ "web_search_billing_unit": "per_query" }, "vertex_ai/gemini-3-flash-preview": { + "cache_read_input_audio_token_cost": 1e-07, "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_flex": 5e-08, "input_cost_per_token": 5e-07, "input_cost_per_audio_token": 1e-06, "litellm_provider": "vertex_ai", @@ -24567,7 +24961,7 @@ "max_tokens": 65535, "mode": "chat", "output_cost_per_token": 3e-06, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24604,7 +24998,11 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "input_cost_per_token_batches": 2.5e-07, + "input_cost_per_token_flex": 2.5e-07, + "output_cost_per_token_batches": 1.5e-06, + "output_cost_per_token_flex": 1.5e-06 }, "vertex_ai/gemini-3.5-flash": { "prompt_cache_min_tokens": 4096, @@ -24620,7 +25018,7 @@ "output_cost_per_reasoning_token": 9e-06, "output_cost_per_token": 9e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24683,7 +25081,7 @@ "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24740,7 +25138,7 @@ "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24797,7 +25195,7 @@ "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24854,7 +25252,7 @@ "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_image": 0.00012, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24888,13 +25286,16 @@ "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "cache_read_input_token_cost_priority": 3.6e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, + "cache_read_input_token_cost_flex": 2e-07, "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 6e-06 }, "vertex_ai/gemini-3.1-pro-preview-customtools": { "prompt_cache_min_tokens": 4096, @@ -24959,13 +25360,15 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1e-06, + "input_cost_per_token_batches": 5e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65535, "max_tokens": 65535, "mode": "chat", + "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2e-05, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_modalities": [ "text" ], @@ -25172,7 +25575,7 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_above_200k_tokens": 1.5e-05, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_modalities": [ "text", "image" @@ -25198,10 +25601,14 @@ "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models" }, "gemini-embedding-2-preview": { - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "vertex_ai-embedding-models", "max_input_tokens": 8192, "max_tokens": 8192, @@ -25212,25 +25619,33 @@ "uses_embed_content": true }, "gemini-embedding-2": { - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "vertex_ai-embedding-models", "max_input_tokens": 8192, "max_tokens": 8192, "mode": "embedding", "output_cost_per_token": 0, "output_vector_size": 3072, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supports_multimodal": true, "uses_embed_content": true }, "vertex_ai/gemini-embedding-2-preview": { - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "vertex_ai", "max_input_tokens": 8192, "max_tokens": 8192, @@ -25242,17 +25657,21 @@ "uses_embed_content": true }, "vertex_ai/gemini-embedding-2": { - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "vertex_ai", "max_input_tokens": 8192, "max_tokens": 8192, "mode": "embedding", "output_cost_per_token": 0, "output_vector_size": 3072, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supports_multimodal": true, "uses_embed_content": true }, @@ -25284,10 +25703,14 @@ }, "gemini/gemini-embedding-2-preview": { "deprecation_date": "2026-08-10", - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "gemini", "max_input_tokens": 8192, "max_tokens": 8192, @@ -25300,10 +25723,14 @@ "tpm": 10000000 }, "gemini/gemini-embedding-2": { - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "gemini", "max_input_tokens": 8192, "max_tokens": 8192, @@ -26886,7 +27313,9 @@ "google_maps_grounding_cost_per_query": 0.014 }, "gemini-3-flash-preview": { + "cache_read_input_audio_token_cost": 1e-07, "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_flex": 5e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 5e-07, "litellm_provider": "vertex_ai-language-models", @@ -26896,7 +27325,7 @@ "mode": "chat", "output_cost_per_reasoning_token": 3e-06, "output_cost_per_token": 3e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -26934,7 +27363,11 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "input_cost_per_token_batches": 2.5e-07, + "input_cost_per_token_flex": 2.5e-07, + "output_cost_per_token_batches": 1.5e-06, + "output_cost_per_token_flex": 1.5e-06 }, "gemini-omni-flash-preview": { "input_cost_per_audio_token": 1.5e-06, @@ -26947,7 +27380,7 @@ "output_cost_per_reasoning_token": 9e-06, "output_cost_per_token": 9e-06, "output_cost_per_video_token": 1.75e-05, - "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/omni-flash-preview", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions" ], @@ -26980,7 +27413,7 @@ "mode": "chat", "output_cost_per_reasoning_token": 9e-06, "output_cost_per_token": 9e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -27043,7 +27476,7 @@ "output_cost_per_token": 3.75e-06, "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -27100,7 +27533,7 @@ "output_cost_per_token": 3.75e-06, "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -27157,7 +27590,7 @@ "output_cost_per_token": 3.75e-06, "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -28615,6 +29048,7 @@ "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_prompt_caching": true, "supports_system_messages": true, @@ -28623,12 +29057,15 @@ "gpt-3.5-turbo-0125": { "deprecation_date": "2026-10-23", "input_cost_per_token": 5e-07, + "input_cost_per_token_batches": 2.5e-07, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06, + "output_cost_per_token_batches": 7.5e-07, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -28638,12 +29075,15 @@ "gpt-3.5-turbo-1106": { "deprecation_date": "2026-09-28", "input_cost_per_token": 1e-06, + "input_cost_per_token_batches": 1e-06, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, + "output_cost_per_token_batches": 2e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -28671,7 +29111,8 @@ "max_output_tokens": 4096, "max_tokens": 4096, "mode": "completion", - "output_cost_per_token": 2e-06 + "output_cost_per_token": 2e-06, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-3.5-turbo-instruct-0914": { "input_cost_per_token": 1.5e-06, @@ -28726,12 +29167,15 @@ "gpt-4-0613": { "deprecation_date": "2026-10-23", "input_cost_per_token": 3e-05, + "input_cost_per_token_batches": 1.5e-05, "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-05, + "output_cost_per_token_batches": 3e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_prompt_caching": true, "supports_system_messages": true, @@ -28772,12 +29216,15 @@ "gpt-4-turbo-2024-04-09": { "deprecation_date": "2026-10-23", "input_cost_per_token": 1e-05, + "input_cost_per_token_batches": 5e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 3e-05, + "output_cost_per_token_batches": 1.5e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -28821,6 +29268,7 @@ "search_context_size_low": 0.025, "search_context_size_medium": 0.025 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -28863,6 +29311,7 @@ "search_context_size_low": 0.025, "search_context_size_medium": 0.025 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -28905,6 +29354,7 @@ "search_context_size_low": 0.025, "search_context_size_medium": 0.025 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -28947,6 +29397,7 @@ "search_context_size_low": 0.025, "search_context_size_medium": 0.025 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -28985,6 +29436,7 @@ "output_cost_per_token": 4e-07, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_priority": 8e-07, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -29022,6 +29474,7 @@ "output_cost_per_token": 4e-07, "output_cost_per_token_priority": 8e-07, "output_cost_per_token_batches": 2e-07, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -29058,6 +29511,7 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 1.7e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29080,6 +29534,7 @@ "output_cost_per_token": 1.5e-05, "output_cost_per_token_batches": 7.5e-06, "output_cost_per_token_priority": 2.625e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29102,6 +29557,7 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_priority": 1.7e-05, "output_cost_per_token_batches": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29125,6 +29581,7 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_priority": 1.7e-05, "output_cost_per_token_batches": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29199,6 +29656,7 @@ "mode": "chat", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses", @@ -29235,6 +29693,7 @@ "mode": "chat", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions" ], @@ -29269,6 +29728,7 @@ "mode": "chat", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses", @@ -29306,6 +29766,7 @@ "mode": "chat", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses", @@ -29343,6 +29804,7 @@ "mode": "chat", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses", @@ -29404,7 +29866,8 @@ "supports_system_messages": true, "supports_tool_choice": true, "supports_vision": false, - "deprecation_date": "2027-01-20" + "deprecation_date": "2027-01-20", + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini": { "cache_read_input_token_cost": 7.5e-08, @@ -29432,7 +29895,8 @@ "search_context_size_high": 0.025, "search_context_size_low": 0.025, "search_context_size_medium": 0.025 - } + }, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini-2024-07-18": { "cache_read_input_token_cost": 7.5e-08, @@ -29453,6 +29917,7 @@ "search_context_size_low": 0.025, "search_context_size_medium": 0.025 }, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29601,15 +30066,18 @@ "supported_endpoints": [ "/v1/audio/transcriptions" ], - "deprecation_date": "2027-02-26" + "deprecation_date": "2027-02-26", + "input_cost_per_second": 5e-05, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini-tts": { - "input_cost_per_token": 2.5e-06, + "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", "output_cost_per_audio_token": 1.2e-05, "output_cost_per_second": 0.00025, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/speech" ], @@ -29741,7 +30209,9 @@ "supported_endpoints": [ "/v1/audio/transcriptions" ], - "deprecation_date": "2027-02-26" + "deprecation_date": "2027-02-26", + "input_cost_per_second": 0.0001, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-image-1.5": { "cache_read_input_token_cost": 1.25e-06, @@ -29751,7 +30221,10 @@ "mode": "image_generation", "output_cost_per_token": 1e-05, "input_cost_per_image_token": 8e-06, + "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3.2e-05, + "output_cost_per_token_batches": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations" ], @@ -29766,7 +30239,10 @@ "mode": "image_generation", "output_cost_per_token": 1e-05, "input_cost_per_image_token": 8e-06, + "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3.2e-05, + "output_cost_per_token_batches": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations" ], @@ -29779,7 +30255,9 @@ "litellm_provider": "openai", "mode": "image_generation", "input_cost_per_image_token": 8e-06, + "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -30226,6 +30704,7 @@ "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "input_cost_per_token": 1.25e-06, + "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", @@ -30234,6 +30713,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, "search_context_cost_per_query": { @@ -30241,6 +30721,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -30270,6 +30751,7 @@ }, "gpt-5.1": { "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, @@ -30310,11 +30792,17 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "input_cost_per_token_batches": 6.25e-07, + "input_cost_per_token_flex": 6.25e-07, + "output_cost_per_token_batches": 5e-06, + "output_cost_per_token_flex": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": false, "supports_minimal_reasoning_effort": false }, "gpt-5.1-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, @@ -30355,6 +30843,11 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "input_cost_per_token_batches": 6.25e-07, + "input_cost_per_token_flex": 6.25e-07, + "output_cost_per_token_batches": 5e-06, + "output_cost_per_token_flex": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": false, "supports_minimal_reasoning_effort": false }, @@ -30406,6 +30899,7 @@ }, "gpt-5.2": { "cache_read_input_token_cost": 1.75e-07, + "cache_read_input_token_cost_flex": 8.75e-08, "cache_read_input_token_cost_priority": 3.5e-07, "input_cost_per_token": 1.75e-06, "input_cost_per_token_priority": 3.5e-06, @@ -30447,11 +30941,17 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "input_cost_per_token_batches": 8.75e-07, + "input_cost_per_token_flex": 8.75e-07, + "output_cost_per_token_batches": 7e-06, + "output_cost_per_token_flex": 7e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, "gpt-5.2-2025-12-11": { "cache_read_input_token_cost": 1.75e-07, + "cache_read_input_token_cost_flex": 8.75e-08, "cache_read_input_token_cost_priority": 3.5e-07, "input_cost_per_token": 1.75e-06, "input_cost_per_token_priority": 3.5e-06, @@ -30493,6 +30993,11 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "input_cost_per_token_batches": 8.75e-07, + "input_cost_per_token_flex": 8.75e-07, + "output_cost_per_token_batches": 7e-06, + "output_cost_per_token_flex": 7e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, @@ -30586,17 +31091,20 @@ }, "gpt-5.2-pro": { "input_cost_per_token": 2.1e-05, + "input_cost_per_token_batches": 1.05e-05, "litellm_provider": "openai", "max_input_tokens": 272000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", "output_cost_per_token": 0.000168, + "output_cost_per_token_batches": 8.4e-05, "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": [ "/v1/batch", "/v1/responses" @@ -30625,17 +31133,20 @@ }, "gpt-5.2-pro-2025-12-11": { "input_cost_per_token": 2.1e-05, + "input_cost_per_token_batches": 1.05e-05, "litellm_provider": "openai", "max_input_tokens": 272000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", "output_cost_per_token": 0.000168, + "output_cost_per_token_batches": 8.4e-05, "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": [ "/v1/batch", "/v1/responses" @@ -30701,6 +31212,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -30837,6 +31349,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -30905,6 +31418,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -30972,6 +31486,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -31035,7 +31550,7 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "source": "https://developers.openai.com/api/docs/models/gpt-5.6-cyber", + "source": "https://developers.openai.com/api/docs/pricing", "supports_computer_use": true, "supports_parallel_function_calling": true }, @@ -31205,7 +31720,7 @@ "reasoning_effort_levels": [ "medium" ], - "source": "https://developers.openai.com/api/docs/models/chat-latest", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -31284,7 +31799,8 @@ "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 5e-06, "output_cost_per_token_above_272k_tokens_flex": 2.25e-05, - "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07 + "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5e-07, @@ -31341,7 +31857,8 @@ "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 5e-06, "output_cost_per_token_above_272k_tokens_flex": 2.25e-05, - "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07 + "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.5-pro": { "input_cost_per_token": 3e-05, @@ -31364,6 +31881,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -31412,6 +31930,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -31489,7 +32008,8 @@ "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 2.5e-06, "output_cost_per_token_above_272k_tokens_flex": 1.125e-05, - "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07 + "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.4-2026-03-05": { "cache_read_input_token_cost": 2.5e-07, @@ -31541,7 +32061,8 @@ "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 2.5e-06, "output_cost_per_token_above_272k_tokens_flex": 1.125e-05, - "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07 + "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.4-pro": { "input_cost_per_token": 3e-05, @@ -31590,7 +32111,8 @@ "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 3e-05, - "output_cost_per_token_above_272k_tokens_flex": 0.000135 + "output_cost_per_token_above_272k_tokens_flex": 0.000135, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.4-pro-2026-03-05": { "input_cost_per_token": 3e-05, @@ -31639,7 +32161,8 @@ "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 3e-05, - "output_cost_per_token_above_272k_tokens_flex": 0.000135 + "output_cost_per_token_above_272k_tokens_flex": 0.000135, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.4-mini": { "cache_read_input_token_cost": 7.5e-08, @@ -31690,6 +32213,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, @@ -31742,6 +32266,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, @@ -31791,6 +32316,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, @@ -31840,6 +32366,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, @@ -31858,6 +32385,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/batch", "/v1/responses" @@ -31900,6 +32428,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/batch", "/v1/responses" @@ -31932,6 +32461,7 @@ "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2026-12-11", "input_cost_per_token": 1.25e-06, + "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", @@ -31940,6 +32470,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, "search_context_cost_per_query": { @@ -31947,6 +32478,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -32271,6 +32803,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses" ], @@ -32301,6 +32834,7 @@ "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "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, "litellm_provider": "openai", @@ -32309,6 +32843,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 2e-06, + "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, "search_context_cost_per_query": { @@ -32316,6 +32851,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -32349,6 +32885,7 @@ "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2026-12-11", "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, "litellm_provider": "openai", @@ -32357,6 +32894,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 2e-06, + "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, "search_context_cost_per_query": { @@ -32364,6 +32902,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -32395,6 +32934,7 @@ "cache_read_input_token_cost": 5e-09, "cache_read_input_token_cost_flex": 2.5e-09, "input_cost_per_token": 5e-08, + "input_cost_per_token_batches": 2.5e-08, "input_cost_per_token_flex": 2.5e-08, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", @@ -32403,12 +32943,14 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 4e-07, + "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, "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": [ "/v1/chat/completions", "/v1/batch", @@ -32441,6 +32983,7 @@ "cache_read_input_token_cost_flex": 2.5e-09, "deprecation_date": "2026-12-11", "input_cost_per_token": 5e-08, + "input_cost_per_token_batches": 2.5e-08, "input_cost_per_token_priority": 2.5e-06, "input_cost_per_token_flex": 2.5e-08, "litellm_provider": "openai", @@ -32449,12 +32992,14 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 4e-07, + "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, "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": [ "/v1/chat/completions", "/v1/batch", @@ -32487,9 +33032,11 @@ "deprecation_date": "2026-10-23", "input_cost_per_image_token": 1e-05, "input_cost_per_token": 5e-06, + "input_cost_per_token_batches": 2.5e-06, "litellm_provider": "openai", "mode": "image_generation", "output_cost_per_image_token": 4e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -32500,9 +33047,11 @@ "deprecation_date": "2026-12-01", "input_cost_per_image_token": 2.5e-06, "input_cost_per_token": 2e-06, + "input_cost_per_token_batches": 1e-06, "litellm_provider": "openai", "mode": "image_generation", "output_cost_per_image_token": 8e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -32510,6 +33059,7 @@ }, "gpt-realtime": { "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": "2027-01-20", "input_cost_per_audio_token": 3.2e-05, @@ -32522,6 +33072,7 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32543,6 +33094,7 @@ }, "gpt-realtime-1.5": { "cache_creation_input_audio_token_cost": 4e-07, + "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, @@ -32554,6 +33106,7 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32587,6 +33140,7 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 2.4e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32622,6 +33176,7 @@ "output_cost_per_token": 2.4e-05, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32657,6 +33212,7 @@ "output_cost_per_token": 2.4e-06, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32679,8 +33235,10 @@ "gpt-realtime-mini": { "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": "2027-01-20", "input_cost_per_audio_token": 1e-05, + "input_cost_per_image_token": 8e-07, "input_cost_per_token": 6e-07, "litellm_provider": "openai", "max_input_tokens": 32000, @@ -32689,6 +33247,7 @@ "mode": "realtime", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32710,6 +33269,7 @@ }, "gpt-realtime-2025-08-28": { "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": "2027-01-20", "input_cost_per_audio_token": 3.2e-05, @@ -32722,6 +33282,7 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -34717,6 +35278,22 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "meta/muse-voice-transcribe-1.0": { + "input_cost_per_second": 0.00005, + "litellm_provider": "meta", + "mode": "audio_transcription", + "source": "https://dev.meta.ai/docs/speech-to-text", + "supported_endpoints": [ + "/v1/realtime" + ], + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true + }, "meta_llama/Llama-3.3-70B-Instruct": { "litellm_provider": "meta_llama", "max_input_tokens": 128000, @@ -37425,12 +38002,15 @@ "cache_read_input_token_cost": 7.5e-06, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.5e-05, + "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", "max_input_tokens": 200000, "max_output_tokens": 100000, "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 6e-05, + "output_cost_per_token_batches": 3e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_pdf_input": true, @@ -37445,12 +38025,15 @@ "cache_read_input_token_cost": 7.5e-06, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.5e-05, + "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", "max_input_tokens": 200000, "max_output_tokens": 100000, "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 6e-05, + "output_cost_per_token_batches": 3e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -37472,6 +38055,7 @@ "mode": "responses", "output_cost_per_token": 0.0006, "output_cost_per_token_batches": 0.0003, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -37505,6 +38089,7 @@ "mode": "responses", "output_cost_per_token": 0.0006, "output_cost_per_token_batches": 0.0003, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -37532,6 +38117,7 @@ "cache_read_input_token_cost_flex": 2.5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "input_cost_per_token": 2e-06, + "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, "input_cost_per_token_priority": 3.5e-06, "litellm_provider": "openai", @@ -37540,6 +38126,7 @@ "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06, + "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, "search_context_cost_per_query": { @@ -37547,6 +38134,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/chat/completions", @@ -37576,6 +38164,7 @@ "cache_read_input_token_cost_priority": 8.75e-07, "deprecation_date": "2026-12-11", "input_cost_per_token": 2e-06, + "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, "input_cost_per_token_priority": 3.5e-06, "litellm_provider": "openai", @@ -37584,6 +38173,7 @@ "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06, + "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, "search_context_cost_per_query": { @@ -37591,6 +38181,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/chat/completions", @@ -37700,12 +38291,15 @@ "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.1e-06, + "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "openai", "max_input_tokens": 200000, "max_output_tokens": 100000, "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "output_cost_per_token_batches": 2.2e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_prompt_caching": true, @@ -37718,12 +38312,15 @@ "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.1e-06, + "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "openai", "max_input_tokens": 200000, "max_output_tokens": 100000, "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "output_cost_per_token_batches": 2.2e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_prompt_caching": true, @@ -37747,6 +38344,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -37784,6 +38382,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -37807,10 +38406,11 @@ }, "o4-mini": { "cache_read_input_token_cost": 2.75e-07, - "cache_read_input_token_cost_flex": 1.375e-07, + "cache_read_input_token_cost_flex": 1.38e-07, "cache_read_input_token_cost_priority": 5e-07, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.1e-06, + "input_cost_per_token_batches": 5.5e-07, "input_cost_per_token_flex": 5.5e-07, "input_cost_per_token_priority": 2e-06, "litellm_provider": "openai", @@ -37819,6 +38419,7 @@ "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "output_cost_per_token_batches": 2.2e-06, "output_cost_per_token_flex": 2.2e-06, "output_cost_per_token_priority": 8e-06, "search_context_cost_per_query": { @@ -37826,6 +38427,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_pdf_input": true, @@ -37838,10 +38440,11 @@ }, "o4-mini-2025-04-16": { "cache_read_input_token_cost": 2.75e-07, - "cache_read_input_token_cost_flex": 1.375e-07, + "cache_read_input_token_cost_flex": 1.38e-07, "cache_read_input_token_cost_priority": 5e-07, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.1e-06, + "input_cost_per_token_batches": 5.5e-07, "input_cost_per_token_flex": 5.5e-07, "input_cost_per_token_priority": 2e-06, "litellm_provider": "openai", @@ -37850,6 +38453,7 @@ "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "output_cost_per_token_batches": 2.2e-06, "output_cost_per_token_flex": 2.2e-06, "output_cost_per_token_priority": 8e-06, "search_context_cost_per_query": { @@ -37857,6 +38461,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_pdf_input": true, @@ -39019,7 +39624,9 @@ "supports_max_reasoning_effort": true, "supports_tool_choice": true, "supports_vision": true, - "prompt_cache_min_tokens": 4096 + "prompt_cache_min_tokens": 4096, + "supports_response_schema": true, + "source": "https://openrouter.ai/api/v1/models" }, "openrouter/anthropic/claude-sonnet-4.5": { "input_cost_per_image": 0.0048, @@ -39167,18 +39774,20 @@ }, "openrouter/deepseek/deepseek-v3.2": { "input_cost_per_token": 2.69e-07, - "input_cost_per_token_cache_hit": 2.8e-08, + "input_cost_per_token_cache_hit": 1.345e-07, "litellm_provider": "openrouter", "max_input_tokens": 163840, - "max_output_tokens": 163840, - "max_tokens": 163840, + "max_output_tokens": 65536, + "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 4e-07, "supports_assistant_prefill": true, "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "supports_response_schema": true, + "source": "https://openrouter.ai/api/v1/models" }, "openrouter/deepseek/deepseek-v3.2-exp": { "input_cost_per_token": 2.7e-07, @@ -43015,7 +43624,8 @@ "mode": "embedding", "output_cost_per_token": 0.0, "output_cost_per_token_batches": 0.0, - "output_vector_size": 3072 + "output_vector_size": 3072, + "source": "https://developers.openai.com/api/docs/pricing" }, "text-embedding-3-small": { "input_cost_per_token": 2e-08, @@ -43026,7 +43636,8 @@ "mode": "embedding", "output_cost_per_token": 0.0, "output_cost_per_token_batches": 0.0, - "output_vector_size": 1536 + "output_vector_size": 1536, + "source": "https://developers.openai.com/api/docs/pricing" }, "text-embedding-ada-002": { "input_cost_per_token": 1e-07, @@ -43035,7 +43646,8 @@ "max_tokens": 8191, "mode": "embedding", "output_cost_per_token": 0.0, - "output_vector_size": 1536 + "output_vector_size": 1536, + "source": "https://developers.openai.com/api/docs/pricing" }, "text-embedding-ada-002-v2": { "input_cost_per_token": 1e-07, @@ -43206,7 +43818,7 @@ "input_cost_per_token": 1.2e-06, "output_cost_per_token": 1.2e-06, "max_input_tokens": 131072, - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/Qwen/Qwen2.5-7B-Instruct-Turbo": { "litellm_provider": "together_ai", @@ -43218,7 +43830,7 @@ "input_cost_per_token": 3e-07, "output_cost_per_token": 3e-07, "max_input_tokens": 32768, - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/Qwen/Qwen3-235B-A22B-Instruct-2507-tput": { "deprecation_date": "2026-07-10", @@ -43265,7 +43877,7 @@ "max_input_tokens": 256000, "mode": "chat", "output_cost_per_token": 2e-06, - "source": "https://www.together.ai/models/qwen3-coder-480b-a35b-instruct", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43327,7 +43939,7 @@ }, "mode": "chat", "output_cost_per_token": 1.7e-06, - "source": "https://www.together.ai/models/deepseek-v3-1", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, @@ -43351,7 +43963,7 @@ "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 1.04e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43385,6 +43997,7 @@ "litellm_provider": "together_ai", "mode": "chat", "output_cost_per_token": 5.9e-07, + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43407,6 +44020,7 @@ "litellm_provider": "together_ai", "mode": "chat", "output_cost_per_token": 8.8e-07, + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43418,6 +44032,7 @@ "litellm_provider": "together_ai", "mode": "chat", "output_cost_per_token": 1.8e-07, + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43434,7 +44049,7 @@ "input_cost_per_token": 2e-07, "output_cost_per_token": 2e-07, "max_input_tokens": 32768, - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/mistralai/Mistral-Small-24B-Instruct-2501": { "deprecation_date": "2026-04-02", @@ -43446,7 +44061,7 @@ "input_cost_per_token": 1e-07, "output_cost_per_token": 3e-07, "max_input_tokens": 32768, - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/mistralai/Mixtral-8x7B-Instruct-v0.1": { "deprecation_date": "2026-04-16", @@ -43454,6 +44069,7 @@ "litellm_provider": "together_ai", "mode": "chat", "output_cost_per_token": 6e-07, + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43480,7 +44096,7 @@ "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 6e-07, - "source": "https://www.together.ai/models/gpt-oss-120b", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, @@ -43488,12 +44104,13 @@ "supports_tool_choice": true }, "together_ai/openai/gpt-oss-20b": { + "deprecation_date": "2026-09-14", "input_cost_per_token": 5e-08, "litellm_provider": "together_ai", "max_input_tokens": 131072, "mode": "chat", "output_cost_per_token": 2e-07, - "source": "https://www.together.ai/models/gpt-oss-20b", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43513,7 +44130,7 @@ "max_input_tokens": 128000, "mode": "chat", "output_cost_per_token": 1.1e-06, - "source": "https://www.together.ai/models/glm-4-5-air", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43529,7 +44146,7 @@ }, "mode": "chat", "output_cost_per_token": 2.2e-06, - "source": "https://www.together.ai/models/glm-4-6", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, @@ -43546,7 +44163,7 @@ }, "mode": "chat", "output_cost_per_token": 2e-06, - "source": "https://www.together.ai/models/glm-4-7", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, @@ -43594,7 +44211,7 @@ }, "mode": "chat", "output_cost_per_token": 1.5e-06, - "source": "https://www.together.ai/models/qwen3-next-80b-a3b-instruct", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43610,7 +44227,7 @@ }, "mode": "chat", "output_cost_per_token": 1.5e-06, - "source": "https://www.together.ai/models/qwen3-next-80b-a3b-thinking", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43624,7 +44241,7 @@ "max_input_tokens": 262144, "mode": "chat", "output_cost_per_token": 3.6e-06, - "source": "https://www.together.ai/models/qwen3-5-397b-a17b", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43639,7 +44256,7 @@ "max_tokens": 524288, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43664,7 +44281,7 @@ "max_tokens": 262144, "mode": "chat", "output_cost_per_token": 2.5e-07, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, @@ -43679,7 +44296,7 @@ "max_tokens": 1000000, "mode": "chat", "output_cost_per_token": 3e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_reasoning": true }, "together_ai/Qwen/Qwen3.7-Max": { @@ -43690,7 +44307,7 @@ "max_tokens": 1000000, "mode": "chat", "output_cost_per_token": 7.5e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_prompt_caching": true }, "together_ai/Qwen/Qwen3.7-Plus": { @@ -43700,7 +44317,7 @@ "max_tokens": 1000000, "mode": "chat", "output_cost_per_token": 1.28e-06, - "source": "https://docs.together.ai/docs/serverless-models" + "source": "https://api.together.ai/v1/models" }, "together_ai/Qwen/Qwen3.8-2.4T-A95B": { "cache_read_input_token_cost": 2.5e-07, @@ -43710,7 +44327,7 @@ "max_tokens": 1010000, "mode": "chat", "output_cost_per_token": 6e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_prompt_caching": true }, "together_ai/arize-ai/qwen-2-1.5b-instruct": { @@ -43720,7 +44337,7 @@ "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 1e-07, - "source": "https://docs.together.ai/docs/serverless-models" + "source": "https://api.together.ai/v1/models" }, "together_ai/deepseek-ai/DeepSeek-V4-Flash-0731": { "cache_read_input_token_cost": 3e-08, @@ -43730,7 +44347,7 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 2.8e-07, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43762,7 +44379,7 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 3.96e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43780,13 +44397,14 @@ "source": "https://docs.together.ai/docs/serverless-models" }, "together_ai/google/gemma-4-31B-it": { + "deprecation_date": "2026-09-14", "input_cost_per_token": 3.9e-07, "litellm_provider": "together_ai", "max_input_tokens": 262144, "max_tokens": 262144, "mode": "chat", "output_cost_per_token": 9.7e-07, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43794,6 +44412,7 @@ "supports_vision": true }, "together_ai/intfloat/multilingual-e5-large-instruct": { + "deprecation_date": "2026-09-14", "input_cost_per_token": 2e-08, "litellm_provider": "together_ai", "max_input_tokens": 514, @@ -43821,7 +44440,7 @@ "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 1.5e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_prompt_caching": true }, "together_ai/moonshotai/Kimi-K2.7-Code": { @@ -43833,7 +44452,7 @@ "max_tokens": 262144, "mode": "chat", "output_cost_per_token": 4e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43854,7 +44473,7 @@ "high", "max" ], - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43872,7 +44491,7 @@ "max_tokens": 512288, "mode": "chat", "output_cost_per_token": 3.6e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43898,7 +44517,7 @@ "max_tokens": 524288, "mode": "chat", "output_cost_per_token": 4.05e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43906,6 +44525,7 @@ "supports_tool_choice": true }, "together_ai/thinkingmachines/Inkling-Small": { + "deprecation_date": "2026-09-14", "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 5e-07, "litellm_provider": "together_ai", @@ -43913,7 +44533,7 @@ "max_tokens": 524288, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_prompt_caching": true }, "together_ai/zai-org/GLM-5.2": { @@ -43925,7 +44545,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43942,7 +44562,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43959,7 +44579,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 5e-07, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43972,6 +44592,7 @@ "input_cost_per_character": 1.5e-05, "litellm_provider": "openai", "mode": "audio_speech", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/speech" ] @@ -43980,6 +44601,7 @@ "input_cost_per_character": 3e-05, "litellm_provider": "openai", "mode": "audio_speech", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/speech" ] @@ -47322,6 +47944,9 @@ "cache_read_input_token_cost": 3e-08, "input_cost_per_audio_token": 1e-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": 32768, "max_output_tokens": 32768, @@ -47331,8 +47956,10 @@ "output_cost_per_image_token": 3e-05, "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, "rpm": 100000, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/image-generation#edit-an-image", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -47364,10 +47991,19 @@ "supports_image_size": false }, "vertex_ai/gemini-3-pro-image": { + "cache_read_input_token_cost": 2e-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_flex": 1e-07, + "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, + "input_cost_per_token_above_200k_tokens": 4e-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, + "input_cost_per_token_priority": 3.6e-06, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 32768, @@ -47376,9 +48012,13 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "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, "output_cost_per_token_batches": 6e-06, + "output_cost_per_token_flex": 6e-06, + "output_cost_per_token_priority": 2.16e-05, "supports_reasoning": false, - "source": "https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-pro-image" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -47397,9 +48037,13 @@ "source": "https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-pro-image" }, "vertex_ai/gemini-3.1-flash-image": { + "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_flex": 2.5e-08, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.00056, "input_cost_per_token": 5e-07, + "input_cost_per_token_batches": 2.5e-07, + "input_cost_per_token_flex": 2.5e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 32768, @@ -47408,8 +48052,10 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_token": 3e-06, + "output_cost_per_token_batches": 1.5e-06, + "output_cost_per_token_flex": 1.5e-06, "supports_reasoning": false, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/gemini-3.1-flash-image-preview": { "input_cost_per_image": 0.00056, @@ -47427,9 +48073,11 @@ }, "vertex_ai/gemini-3.1-flash-lite-image": { "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_flex": 1.25e-08, "input_cost_per_image": 0.00028, "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, + "input_cost_per_token_flex": 1.25e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 4096, @@ -47439,6 +48087,7 @@ "output_cost_per_image_token": 3e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, + "output_cost_per_token_flex": 7.5e-07, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -47513,6 +48162,7 @@ "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/gemini-3.1-flash-lite": { + "cache_read_input_audio_token_cost": 5e-08, "deprecation_date": "2027-05-07", "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_flex": 1.25e-08, @@ -47533,7 +48183,7 @@ "output_cost_per_token_flex": 7.5e-07, "output_cost_per_token_priority": 2.7e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -47575,7 +48225,7 @@ "deprecation_date": "2027-07-21", "cache_read_input_token_cost": 3e-08, "cache_read_input_token_cost_flex": 1.5e-08, - "cache_read_input_token_cost_priority": 5e-08, + "cache_read_input_token_cost_priority": 5.4e-08, "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -47591,7 +48241,7 @@ "output_cost_per_token_flex": 1.25e-06, "output_cost_per_token_priority": 4.5e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -47630,6 +48280,7 @@ "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/deep-research-pro-preview-12-2025": { + "cache_read_input_token_cost": 2e-07, "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -47642,7 +48293,7 @@ "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, - "source": "https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-pro-image" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/imagegeneration@006": { "litellm_provider": "vertex_ai-image-models", @@ -49305,7 +49956,8 @@ "supported_endpoints": [ "/v1/audio/transcriptions" ], - "deprecation_date": "2027-02-26" + "deprecation_date": "2027-02-26", + "source": "https://developers.openai.com/api/docs/pricing" }, "xai/grok-3": { "cache_read_input_token_cost": 2e-07, @@ -52402,10 +53054,11 @@ "max_tokens": 40960, "max_input_tokens": 40960, "max_output_tokens": 40960, - "input_cost_per_token": 0.0, + "input_cost_per_token": 2e-07, "output_cost_per_token": 0.0, "litellm_provider": "fireworks_ai", - "mode": "rerank" + "mode": "rerank", + "source": "https://api.fireworks.ai/v1/serverless/models" }, "fireworks_ai/accounts/fireworks/models/qwen3-vl-235b-a22b-instruct": { "max_tokens": 262144, @@ -52470,7 +53123,7 @@ "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 1.6e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -54369,12 +55022,13 @@ }, "gpt-4o-mini-tts-2025-03-20": { "deprecation_date": "2026-07-23", - "input_cost_per_token": 2.5e-06, + "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", "output_cost_per_audio_token": 1.2e-05, "output_cost_per_second": 0.00025, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/speech" ], @@ -54387,12 +55041,13 @@ ] }, "gpt-4o-mini-tts-2025-12-15": { - "input_cost_per_token": 2.5e-06, + "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", "output_cost_per_audio_token": 1.2e-05, "output_cost_per_second": 0.00025, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/speech" ], @@ -54407,24 +55062,28 @@ "gpt-4o-mini-transcribe-2025-03-20": { "deprecation_date": "2027-01-20", "input_cost_per_audio_token": 1.25e-06, + "input_cost_per_second": 5e-05, "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 16000, "max_output_tokens": 2000, "mode": "audio_transcription", "output_cost_per_token": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/transcriptions" ] }, "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, "litellm_provider": "openai", "max_input_tokens": 16000, "max_output_tokens": 2000, "mode": "audio_transcription", "output_cost_per_token": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/transcriptions" ] @@ -54443,6 +55102,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -54470,6 +55130,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -54497,6 +55158,7 @@ "mode": "realtime", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -54548,13 +55210,14 @@ "supports_parallel_function_calling": true, "supports_system_messages": true, "supports_tool_choice": true, - "deprecation_date": "2027-01-20" + "deprecation_date": "2027-01-20", + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-realtime-whisper": { - "input_cost_per_second": 0.0002833333333333333, + "input_cost_per_second": 0.000283333333333, "litellm_provider": "openai", "mode": "audio_transcription", - "source": "https://developers.openai.com/api/docs/models/gpt-realtime-whisper", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime", "/v1/realtime/transcription_sessions" @@ -54572,7 +55235,7 @@ "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.1, - "source": "https://platform.openai.com/docs/api-reference/videos", + "source": "https://developers.openai.com/api/docs/pricing", "supported_modalities": [ "text", "image" @@ -54586,7 +55249,7 @@ "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.3, - "source": "https://platform.openai.com/docs/api-reference/videos", + "source": "https://developers.openai.com/api/docs/pricing", "supported_modalities": [ "text", "image" @@ -54611,11 +55274,15 @@ "chatgpt-image-latest": { "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2026-12-01", - "input_cost_per_image_token": 1e-05, + "input_cost_per_image_token": 8e-06, "input_cost_per_token": 5e-06, + "input_cost_per_token_batches": 2.5e-06, "litellm_provider": "openai", "mode": "image_generation", - "output_cost_per_image_token": 4e-05, + "output_cost_per_image_token": 3.2e-05, + "output_cost_per_token": 1e-05, + "output_cost_per_token_batches": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -57090,7 +57757,7 @@ "input_cost_per_second": 7.5e-05, "litellm_provider": "openai", "mode": "audio_transcription", - "source": "https://developers.openai.com/api/docs/models/gpt-transcribe", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/transcriptions", "/v1/realtime/transcription_sessions" @@ -57105,10 +57772,10 @@ "supports_audio_input": true }, "gpt-live-transcribe": { - "input_cost_per_second": 0.0002833333333333333, + "input_cost_per_second": 0.000283333333333, "litellm_provider": "openai", "mode": "audio_transcription", - "source": "https://developers.openai.com/api/docs/models/gpt-live-transcribe", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime", "/v1/realtime/transcription_sessions" @@ -57123,10 +57790,10 @@ "supports_audio_input": true }, "gpt-live-1": { - "input_cost_per_second": 0.0008333333333333334, + "input_cost_per_second": 0.000833333333333, "litellm_provider": "openai", "mode": "realtime", - "source": "https://developers.openai.com/api/docs/models/gpt-live-1", + "source": "https://developers.openai.com/api/docs/pricing", "supported_modalities": [ "text", "audio" @@ -57140,13 +57807,13 @@ "supports_function_calling": true }, "gpt-realtime-translate": { - "input_cost_per_second": 0.0005666666666666667, + "input_cost_per_second": 0.000566666666667, "litellm_provider": "openai", "max_input_tokens": 16000, "max_output_tokens": 2000, "max_tokens": 2000, "mode": "realtime", - "source": "https://developers.openai.com/api/docs/models/gpt-realtime-translate", + "source": "https://developers.openai.com/api/docs/pricing", "supported_modalities": [ "audio" ], @@ -57174,7 +57841,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, - "source": "https://platform.claude.com/docs/en/about-claude/models/overview", + "source": "https://platform.claude.com/docs/en/about-claude/pricing", "supports_adaptive_thinking": true, "thinking_always_on": true, "supports_mid_conversation_system": true, @@ -57235,7 +57902,7 @@ "supports_output_config": true, "prompt_cache_min_tokens": 512, "supports_native_structured_output": true, - "source": "https://platform.claude.com/docs/en/models/mythos-5-1/overview" + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-mythos-preview": { "cache_creation_input_token_cost": 1.25e-05, @@ -57433,8 +58100,9 @@ }, { "name": "claude-adaptive-thinking", - "pattern": "claude-[a-z]+-(?:4[-._](?:[6-9]|[1-9]\\d)(?!\\d)|(?:[5-9]|[1-9]\\d)(?!\\d)(?:[-._]\\d{1,2}(?!\\d))?)", - "description": "Claude at version 4.6 or higher, in any id shape that contains claude--: minors 4.6 through 4.99, any later major-minor, and bare 5+ majors so a new family shaped like claude-fable-5 matches. Requiring the claude- prefix keeps non-Claude names such as team-sonnet-5-1 out. The minor is capped at two digits so an 8-digit date suffix such as claude-opus-4-20250514 is never read as a >= 4.6 minor. Turns on adaptive thinking for new versions and new families with no code change.", + "pattern": "claude-[a-z]+-(?:4[-._](?:[6-9]|[1-9]\\d)(?!\\d)|[5-9](?!\\d)(?:[-._]\\d{1,2}(?!\\d))?)", + "fill_missing_for_providers": ["anthropic", "azure_ai", "bedrock", "bedrock_converse", "vertex_ai-anthropic_models"], + "description": "Claude at version 4.6 or higher, in any id shape that contains claude--: minors 4.6 through 4.99, any later major-minor, and bare 5+ majors so a new family shaped like claude-fable-5 matches. Requiring the claude- prefix keeps non-Claude names such as team-sonnet-5-1 out. The minor is capped at two digits so an 8-digit date suffix such as claude-opus-4-20250514 is never read as a >= 4.6 minor. Two-digit majors are deliberately not matched so ids like claude-opus-41 (4.1) are not read as major 41. Turns on adaptive thinking for new versions and new families with no code change.", "model_info": { "supports_adaptive_thinking": true } @@ -57442,6 +58110,7 @@ { "name": "claude-legacy-thinking", "pattern": "claude-[a-z]+-4[-._]6(?!\\d)", + "fill_missing_for_providers": ["anthropic", "azure_ai", "bedrock", "bedrock_converse", "vertex_ai-anthropic_models"], "description": "Claude at version 4.6 exactly, in any id shape that contains claude--4-6 (dotted and underscored minors included, dated releases such as claude-sonnet-4-6-20260219 too). The 4.6 family is adaptive-thinking yet still accepts legacy thinking.type=enabled with budget_tokens, so the caller's hard budget cap is forwarded verbatim instead of being rewritten to an uncapped output_config.effort. The lookahead keeps two-digit minors such as 4-60 from matching. 4.7+ and 5+ majors reject the legacy shape and stay on the adaptive translation.", "model_info": { "supports_legacy_thinking": true @@ -57457,8 +58126,9 @@ }, { "name": "claude-mid-conversation-system", - "pattern": "claude-[a-z]+-(?:4[-._](?:[89]|[1-9]\\d)(?!\\d)|(?:[5-9]|[1-9]\\d)(?!\\d)(?:[-._]\\d{1,2}(?!\\d))?)", - "description": "Claude at version 4.8 or higher, in any id shape that contains claude--: minors 4.8 through 4.99, any later major-minor, and bare 5+ majors so a new family like claude-fable-5 matches. Anthropic introduced mid-conversation system messages with Opus 4.8 and every newer Claude keeps them; 4.7 and below reject the system role inside messages.", + "pattern": "claude-[a-z]+-(?:4[-._](?:[89]|[1-9]\\d)(?!\\d)|[5-9](?!\\d)(?:[-._]\\d{1,2}(?!\\d))?)", + "fill_missing_for_providers": ["anthropic", "azure_ai", "bedrock", "bedrock_converse", "vertex_ai-anthropic_models"], + "description": "Claude at version 4.8 or higher, in any id shape that contains claude--: minors 4.8 through 4.99, any later major-minor, and bare 5+ majors so a new family like claude-fable-5 matches. Two-digit majors are deliberately not matched so ids like claude-opus-41 (4.1) are not read as major 41. Anthropic introduced mid-conversation system messages with Opus 4.8 and every newer Claude keeps them; 4.7 and below reject the system role inside messages.", "model_info": { "supports_mid_conversation_system": true } @@ -57470,6 +58140,15 @@ "model_info": { "supports_reasoning": true } + }, + { + "name": "openai-reasoning-family-baseline", + "pattern": "^(?!.*search-api)(?:[a-z0-9_.-]+/)*(?:ft:)?(?:o[1-9]\\d*(?![a-z0-9])|gpt-[5-9](?:\\.\\d+)?(?![0-9.])|(?:gpt-\\d+(?:\\.\\d+)?(?:-[a-z0-9]+)*-)?(?:codex|deep-research|chat-latest)(?![a-z0-9]))", + "fill_missing_for_providers": ["azure", "azure_ai", "openai"], + "description": "OpenAI reasoning families by id shape, under any provider namespace and with an optional ft: prefix: the o-series (o1, o3-pro, o4-mini), gpt-5 through gpt-9 majors including dotted minors and suffixed variants (gpt-5.5-cyber, gpt-6-astra), and the codex, deep-research and chat-latest lines when standalone or on a gpt base. gpt-5-search-api is excluded because it is a search-only surface. Every model here is a reasoning model, and the Responses API drops the caller's reasoning param for any mapped OpenAI model whose info lacks supports_reasoning, so an id the registry has not named yet keeps its reasoning settings instead of silently losing them. Rules lose to exact entries. Carries no mode and no pricing, so cost stays on the standard unpriced behavior.", + "model_info": { + "supports_reasoning": true + } } ] }, @@ -57579,6 +58258,7 @@ }, "vertex_ai/gemini-3.5-live-translate-preview": { "input_cost_per_audio_token": 3.5e-06, + "input_cost_per_second": 8.83333333333e-05, "input_cost_per_token": 3.5e-06, "litellm_provider": "vertex_ai", "mode": "realtime", @@ -57681,14 +58361,17 @@ }, "fireworks_ai/accounts/fireworks/models/deepseek-v4-flash-0731": { "cache_read_input_token_cost": 7e-09, + "cache_read_input_token_cost_priority": 8.75e-09, "input_cost_per_token": 2.2e-07, + "input_cost_per_token_priority": 2.75e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 8.25e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57697,14 +58380,17 @@ }, "fireworks_ai/accounts/fireworks/models/deepseek-v4p1-flash": { "cache_read_input_token_cost": 7e-09, + "cache_read_input_token_cost_priority": 8.75e-09, "input_cost_per_token": 2.2e-07, + "input_cost_per_token_priority": 2.75e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 393216, "max_tokens": 393216, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://fireworks.ai/models/deepseek-ai/deepseek-v4p1-flash", + "output_cost_per_token_priority": 8.25e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, @@ -57720,26 +58406,29 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_tool_choice": true, "supports_vision": true }, "fireworks_ai/accounts/fireworks/models/kimi-k3": { "cache_read_input_token_cost": 3e-07, + "cache_read_input_token_cost_priority": 3.75e-07, "input_cost_per_token": 3e-06, + "input_cost_per_token_priority": 3.75e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 1.5e-05, + "output_cost_per_token_priority": 1.875e-05, "reasoning_effort_levels": [ "low", "high", "max" ], - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57748,14 +58437,17 @@ }, "fireworks_ai/deepseek-v4-flash-0731": { "cache_read_input_token_cost": 7e-09, + "cache_read_input_token_cost_priority": 8.75e-09, "input_cost_per_token": 2.2e-07, + "input_cost_per_token_priority": 2.75e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 8.25e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57764,14 +58456,17 @@ }, "fireworks_ai/deepseek-v4p1-flash": { "cache_read_input_token_cost": 7e-09, + "cache_read_input_token_cost_priority": 8.75e-09, "input_cost_per_token": 2.2e-07, + "input_cost_per_token_priority": 2.75e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 393216, "max_tokens": 393216, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://fireworks.ai/models/deepseek-ai/deepseek-v4p1-flash", + "output_cost_per_token_priority": 8.25e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, @@ -57787,7 +58482,7 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_tool_choice": true, "supports_vision": true @@ -57826,19 +58521,22 @@ }, "fireworks_ai/kimi-k3": { "cache_read_input_token_cost": 3e-07, + "cache_read_input_token_cost_priority": 3.75e-07, "input_cost_per_token": 3e-06, + "input_cost_per_token_priority": 3.75e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 1.5e-05, + "output_cost_per_token_priority": 1.875e-05, "reasoning_effort_levels": [ "low", "high", "max" ], - 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"together_ai/Qwen/Qwen2-72B-Instruct": { + "input_cost_per_token": 9e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 9e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2-VL-72B-Instruct": { + "input_cost_per_token": 1.2e-06, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2.5-14B-Instruct": { + "input_cost_per_token": 8e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 8e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2.5-72B-Instruct": { + "input_cost_per_token": 1.2e-06, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2.5-Coder-32B-Instruct": { + "input_cost_per_token": 8e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 8e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2.5-VL-72B-Instruct": { + "input_cost_per_token": 1.95e-06, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 8e-06, + "source": "https://api.together.ai/v1/models" } } diff --git a/litellm/ocr/legacy.py b/litellm/ocr/legacy.py index ddf6016dce3..a742be274b3 100644 --- a/litellm/ocr/legacy.py +++ b/litellm/ocr/legacy.py @@ -28,6 +28,7 @@ from litellm.llms.base_llm.ocr.transformation import ( from litellm.llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler from litellm.ocr.input import FileReader from litellm.types.router import GenericLiteLLMParams +from litellm.types.utils import CustomPricingLiteLLMParams from litellm.utils import ProviderConfigManager, client base_llm_http_handler: Final = BaseLLMHTTPHandler() @@ -149,6 +150,7 @@ def _prepare_ocr_request( litellm_params={ "litellm_call_id": litellm_call_id, "api_base": resolved_api_base, + **litellm_params.model_dump(include=frozenset(CustomPricingLiteLLMParams.model_fields), exclude_none=True), }, custom_llm_provider=custom_llm_provider, ) diff --git a/litellm/proxy/_experimental/mcp_server/AGENTS.md b/litellm/proxy/_experimental/mcp_server/AGENTS.md index 6e1d121c3be..a35e5d1ce10 100644 --- a/litellm/proxy/_experimental/mcp_server/AGENTS.md +++ b/litellm/proxy/_experimental/mcp_server/AGENTS.md @@ -67,9 +67,8 @@ module materially harder to understand. auth, SSE, streamable HTTP, and stdio as separate flows. Do not collapse them behind a single generic branch unless tests prove every mode still behaves correctly. -- Be especially careful with `available_on_public_internet: false` combined with - `delegate_auth_to_upstream: true`. The local `CLAUDE.md` explains the anonymous - upstream PKCE path that must remain intentional. +- Be especially careful with legacy `delegate_auth_to_upstream: true`. The local + `CLAUDE.md` explains its admitted replacement and public discovery contract. - Keep database-backed fields in sync across migrations, typed models under `litellm/types/mcp.py` or `litellm/types/mcp_server/`, config loading, this package, and dashboard state when the field is user-visible. diff --git a/litellm/proxy/_experimental/mcp_server/CLAUDE.md b/litellm/proxy/_experimental/mcp_server/CLAUDE.md index 0ba8f73315f..7f8d06b4570 100644 --- a/litellm/proxy/_experimental/mcp_server/CLAUDE.md +++ b/litellm/proxy/_experimental/mcp_server/CLAUDE.md @@ -1 +1 @@ -MCP note: **`available_on_public_internet: false` with `delegate_auth_to_upstream: true` (oauth2, interactive - not `client_credentials`)** - LiteLLM still allows the anonymous upstream PKCE path (no proxy API key for `/authorize` and matching MCP routes). The internal-only flag mainly affects other surfaces (e.g. IP-based discovery). Rely on the upstream IdP and network policy; the dashboard shows a warning when both are set, and the proxy logs a warning when the server is loaded from config or the database +MCP note: **`auth_type: oauth2` with `delegate_auth_to_upstream: true` is deprecated** - LiteLLM admission is required for matching MCP routes. Use `auth_type: oauth_delegate` for client-forwarded OAuth. OAuth discovery endpoints stay public so clients can start the RFC 9728 flow diff --git a/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py b/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py index cd6739777dd..b0d57cb6228 100644 --- a/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py +++ b/litellm/proxy/_experimental/mcp_server/auth/user_api_key_auth_mcp.py @@ -129,10 +129,9 @@ def _is_mcp_passthrough_cold_start(mcp_servers: list[str] | None, client_ip: str spec-compliant WWW-Authenticate challenge instead of surfacing a generic admission error. - Uses "all" semantics (mirrors - :meth:`MCPRequestHandler._target_servers_delegate_auth_to_upstream`): one - non-passthrough target in a co-targeted set must not flip the bypass open - for the others. Fails closed when any target cannot be resolved.""" + Uses "all" semantics: one non-passthrough target in a co-targeted set must + not flip the bypass open for the others. Fails closed when any target + cannot be resolved.""" if not mcp_servers: return False from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( @@ -146,6 +145,27 @@ def _is_mcp_passthrough_cold_start(mcp_servers: list[str] | None, client_ip: str return True +def _is_legacy_delegate_cold_start(mcp_servers: list[str] | None, client_ip: str | None) -> bool: + """Allow only credential-free legacy delegates to reach the route's OAuth challenge.""" + if not mcp_servers: + return False + from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( + MCPServerManager, + global_mcp_server_manager, + ) + from litellm.types.mcp import MCPAuth + + for name in mcp_servers: + server = global_mcp_server_manager.get_mcp_server_by_name(name, client_ip=client_ip) + if server is None or server.auth_type != MCPAuth.oauth2: + return False + if server.delegate_auth_to_upstream is not True: + return False + if MCPServerManager.effective_oauth2_flow(server) == "client_credentials": + return False + return True + + def _is_litellm_auth_admission_error(exc: Exception) -> bool: if isinstance(exc, HTTPException): return exc.status_code == 401 @@ -277,9 +297,18 @@ def _admission_failure_fallback( mcp_servers_from_path is not None and not _has_client_supplied_mcp_auth(mcp_auth_header, mcp_server_auth_headers) and _is_litellm_auth_admission_error(exc) - and _is_mcp_passthrough_cold_start( - mcp_servers_from_path, - client_ip=IPAddressUtils.get_mcp_client_ip(request), + and ( + _is_mcp_passthrough_cold_start( + mcp_servers_from_path, + client_ip=IPAddressUtils.get_mcp_client_ip(request), + ) + or ( + not bearer_presented + and _is_legacy_delegate_cold_start( + mcp_servers_from_path, + client_ip=IPAddressUtils.get_mcp_client_ip(request), + ) + ) ) ): verbose_logger.debug("MCP pass-through cold start: deferring admission to route 401 emitter") @@ -434,22 +463,6 @@ class MCPRequestHandler: api_key=f"Bearer {_get_bearer_token_or_received_api_key(litellm_api_key)}", request=request, ) - elif MCPRequestHandler._target_servers_delegate_auth_to_upstream( - path=request_route, - mcp_servers=mcp_servers, - client_ip=IPAddressUtils.get_mcp_client_ip(request), - ): - # Operator opted this oauth2 server into upstream-delegated auth: the - # client authenticates directly with the upstream MCP server, so any - # Authorization bearer is an upstream token, never a LiteLLM key. Skip - # LiteLLM validation entirely — covering both the no-credential - # discovery request and the authenticated call carrying the upstream - # bearer — so a tool call that succeeds never carries a phantom 401 - # auth span; the bearer is forwarded upstream unchanged. Gated by - # _target_servers_delegate_auth_to_upstream, which returns True only - # when EVERY target is auth_type=oauth2 with delegate_auth_to_upstream - # set; fails closed otherwise. - validated_user_api_key_auth = UserAPIKeyAuth() elif MCPRequestHandler._target_servers_are_true_passthrough( path=request_route, mcp_servers=mcp_servers, @@ -660,64 +673,6 @@ class MCPRequestHandler: return [single_server_match.group(1)] return [servers_and_path] - @staticmethod - def _target_servers_delegate_auth_to_upstream( - path: str, mcp_servers: list[str] | None, client_ip: str | None - ) -> bool: - """ - True only when EVERY MCP server the request targets is configured for - ``auth_type == oauth2`` AND has ``delegate_auth_to_upstream=True``. - Fails closed when any target does not opt in or cannot be resolved. - - Used by :meth:`process_mcp_request` to skip LiteLLM API-key/SSO auth - entirely (PKCE passthrough) so the client authenticates directly with - the upstream MCP server. Mixed-target requests (e.g. one delegated + - one non-delegated server) fall back to normal LiteLLM auth. - """ - # Inline imports avoid a circular dependency: mcp_server_manager imports - # from this module. - from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( - MCPServerManager, - global_mcp_server_manager, - ) - from litellm.types.mcp import MCPAuth - - # Must mirror the downstream header-vs-path override - # (``extract_mcp_auth_context``) or an attacker could set - # ``x-mcp-servers`` to a delegate-enabled server while the URL path - # targets a non-delegate server, skipping LiteLLM auth for it. - target_names: Final = MCPRequestHandler._resolve_target_server_names(path=path, mcp_servers_header=mcp_servers) - if not target_names: - return False - - for name in target_names: - server = global_mcp_server_manager.get_mcp_server_by_name(name, client_ip=client_ip) - if server is None or server.auth_type != MCPAuth.oauth2: - return False - # `is True` is intentional: opt-in must be an explicit boolean - # True. A MagicMock attribute (in tests) or any other truthy - # non-bool must not silently enable the bypass. - if getattr(server, "delegate_auth_to_upstream", False) is not True: - return False - # Never delegate for M2M (client_credentials) servers: LiteLLM - # fetches the upstream token automatically using stored credentials, - # so allowing anonymous bypass would let any external caller invoke - # tools authenticated as LiteLLM's service account. - # - # Resolve the flow rather than reading has_client_credentials directly: - # this is a security gate, and a legacy row whose oauth2_flow was never - # stamped still carries the M2M credential shape (client_id/secret + - # token_url, no authorization_url). Treating an unstamped-but-M2M-shaped - # row as non-M2M here would reopen the anonymous bypass the explicit - # column no longer closes on its own. Shares the one resolution helper - # with the egress backstop and the anonymous-delegate allowlist; all fail - # closed on the ambiguous shape and are removed together once no null rows - # remain. A pure-PKCE delegate server (no stored credentials) resolves to a - # non-M2M flow and keeps its bypass. - if MCPServerManager.effective_oauth2_flow(server) == "client_credentials": - return False - return True - @staticmethod def _target_servers_are_true_passthrough(path: str, mcp_servers: list[str] | None, client_ip: str | None) -> bool: """ @@ -726,7 +681,7 @@ class MCPRequestHandler: Used by :meth:`process_mcp_request` to skip LiteLLM admission auth entirely: the gateway is a transparent proxy and the caller's ``Authorization`` is an upstream token, never a LiteLLM key. - Mirrors :meth:`_target_servers_delegate_auth_to_upstream`; a mixed-target request keeps normal auth. + A mixed-target request keeps normal auth. """ from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( global_mcp_server_manager, diff --git a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py index 3291d5effc2..fb0c623473a 100644 --- a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py +++ b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py @@ -1055,7 +1055,7 @@ def _should_strip_caller_authorization( pass-through cold-start case (RFC 9728) the bearer in ``Authorization`` is the upstream OAuth token and must be forwarded, so we keep it. - - **oauth_delegate servers**: admission always runs and there is no + - **Delegated OAuth servers**: admission always runs and there is no anonymous path, so the caller's separate ``Authorization`` is forwarded only when a distinct ``x-litellm-api-key`` carried admission. Without that header the ``Authorization`` *was* the @@ -1075,12 +1075,17 @@ def _should_strip_caller_authorization( # upstream — it would override another user's stored credential. Delegate and # pass-through return None from to_server_spec and keep forwarding the bearer. return True - if not (mcp_server.is_oauth_passthrough or mcp_server.is_oauth_delegate): + is_delegated_oauth: Final = mcp_server.is_oauth_delegate or ( + mcp_server.auth_type == MCPAuth.oauth2 and mcp_server.delegate_auth_to_upstream + ) + if not (mcp_server.is_oauth_passthrough or is_delegated_oauth): return False has_explicit_litellm_admission_header: Final = _has_explicit_litellm_admission_header(raw_headers) - if mcp_server.is_oauth_delegate: - return not has_explicit_litellm_admission_header + if is_delegated_oauth: + return not has_explicit_litellm_admission_header or _authorization_is_litellm_admission_credential( + raw_headers, user_api_key_auth + ) return _authorization_is_litellm_admission_credential(raw_headers, user_api_key_auth) or ( user_api_key_auth is None and not has_explicit_litellm_admission_header ) @@ -1107,15 +1112,11 @@ def _authorization_is_litellm_admission_credential( That is the case when no usable ``x-litellm-api-key`` was sent, or when the client repeated the same key in both headers. """ - if user_api_key_auth is None or not user_api_key_auth.api_key: - return False admission_header: Final = _raw_header_value(raw_headers, "x-litellm-api-key") - if not admission_header: - return True authorization: Final = _raw_header_value(raw_headers, "authorization") - return authorization is not None and strip_auth_scheme(authorization, "Bearer") == strip_auth_scheme( - admission_header, "Bearer" - ) + if admission_header and authorization: + return strip_auth_scheme(authorization, "Bearer") == strip_auth_scheme(admission_header, "Bearer") + return bool(user_api_key_auth and user_api_key_auth.api_key and not admission_header) def _format_byok_openapi_auth_header(mcp_server: MCPServer, mcp_auth_header: str) -> str: @@ -1453,22 +1454,19 @@ def _warn_on_server_name_fields( _warn("server_name", server_name) -def _warn_internal_delegate_pkce_if_applicable(server: MCPServer, *, source: str) -> None: - """Surface internal + upstream PKCE delegate in logs for operators.""" +def _warn_legacy_delegate_auth_if_applicable(server: MCPServer, *, source: str) -> None: + """Direct legacy delegated OAuth configurations to the admitted replacement.""" if server.auth_type != MCPAuth.oauth2: return if getattr(server, "delegate_auth_to_upstream", False) is not True: return - if getattr(server, "available_on_public_internet", True): - return if server.has_client_credentials: return label: Final = get_server_prefix(server) verbose_logger.warning( - "MCP server %r (id=%s, source=%s): internal-only (available_on_public_internet=false) " - "with delegate_auth_to_upstream=true. Anonymous callers can reach the upstream OAuth2 " - "/authorize flow and complete PKCE without a LiteLLM API key session; ensure the " - "upstream IdP and network enforce your access policy.", + "MCP server %r (id=%s, source=%s) uses deprecated auth_type=oauth2 with " + "delegate_auth_to_upstream=true. LiteLLM admission is now required; migrate to " + "auth_type=oauth_delegate for client-forwarded OAuth.", label, server.server_id, source, @@ -2640,7 +2638,7 @@ class MCPServerManager: oauth_identity_binding=server_config.get("oauth_identity_binding", None), ) self._assign_unique_short_prefix(new_server) - _warn_internal_delegate_pkce_if_applicable(new_server, source="config") + _warn_legacy_delegate_auth_if_applicable(new_server, source="config") _warn_config_id_jag_server_outruns_sso(new_server) self._invalidate_discovery_lists(server_id) self.config_mcp_servers[server_id] = new_server @@ -3185,7 +3183,7 @@ class MCPServerManager: timeout=getattr(mcp_server, "timeout", None), max_concurrent_requests=getattr(mcp_server, "max_concurrent_requests", None), ) - _warn_internal_delegate_pkce_if_applicable(new_server, source="database") + _warn_legacy_delegate_auth_if_applicable(new_server, source="database") self._set_oauth_discovery_deferred( new_server.server_id, _requires_oauth_discovery(server_url, use_issuer_anchor, new_server), @@ -3479,10 +3477,6 @@ class MCPServerManager: ) ) - # For anonymous callers (no user_id, no role), also surface any - # servers the operator has opted into upstream-delegated auth. - # These servers handle their own auth at the upstream level, so - # LiteLLM granting access here does not bypass any security gate. is_anonymous: Final = not ( user_api_key_auth and ( @@ -3492,23 +3486,12 @@ class MCPServerManager: ) ) if is_anonymous: - delegate_server_ids: Final = [ + passthrough_server_ids: Final = [ server.server_id for server in self.get_registry().values() - if ( - getattr(server, "auth_type", None) == MCPAuth.oauth2 - and getattr(server, "delegate_auth_to_upstream", False) is True - # M2M servers must not be exposed anonymously: an - # unauthenticated caller would get LiteLLM to proxy tool - # calls using its stored client_credentials. Resolve the flow - # rather than reading has_client_credentials so an unstamped - # M2M-shape row (null column, verbatim-read as non-M2M) still - # fails closed here, matching the anonymous-delegate auth gate. - and MCPServerManager.effective_oauth2_flow(server) != "client_credentials" - ) - or getattr(server, "auth_type", None) == MCPAuth.true_passthrough + if getattr(server, "auth_type", None) == MCPAuth.true_passthrough ] - combined_servers.update(delegate_server_ids) + combined_servers.update(passthrough_server_ids) restrict_allow_all: Final = ( resolved_general_settings.get("mcp_allow_all_keys_respects_mcp_scope", False) diff --git a/litellm/proxy/_experimental/mcp_server/server.py b/litellm/proxy/_experimental/mcp_server/server.py index fc87db69e16..7feb1fd468d 100644 --- a/litellm/proxy/_experimental/mcp_server/server.py +++ b/litellm/proxy/_experimental/mcp_server/server.py @@ -4257,20 +4257,6 @@ if MCP_AVAILABLE: return None return _get_authorization_header_from_scope(scope) - def _is_delegate_upstream_probe_target(server: MCPServer) -> bool: - """Whether ``server`` is an interactive delegate-auth server whose client-supplied - token should be preflighted upstream. - - Mirrors the anonymous-delegate gate in ``get_allowed_mcp_servers``: the flow is - resolved via ``effective_oauth2_flow`` so an unstamped M2M-shape row fails closed - (its stored client credentials drive egress; the caller's bearer is irrelevant). - """ - return ( - server.auth_type == MCPAuth.oauth2 - and server.delegate_auth_to_upstream is True - and MCPServerManager.effective_oauth2_flow(server) != "client_credentials" - ) - async def _probe_upstream_auth( url: str, auth_header: str, @@ -4331,7 +4317,7 @@ if MCP_AVAILABLE: mcp_servers: list[str] | None, client_ip: str | None, ) -> None: - """Probe pass-through and delegate-auth upstream servers in parallel before the MCP session starts. + """Probe pass-through upstream servers in parallel before the MCP session starts. Only servers the caller's key is already authorized to reach are probed — the list is derived from _get_allowed_mcp_servers so that a user cannot @@ -4343,38 +4329,9 @@ if MCP_AVAILABLE: if the upstream accepts it but forbids the caller. Fails-open: network errors are logged and the request is allowed through. - Delegate-auth servers (``auth_type=oauth2`` + ``delegate_auth_to_upstream``) - are probed with the caller's bare ``Authorization`` bearer. That bearer is only - an upstream token (never a LiteLLM key) when admission took the delegate bypass, - so the delegate target is resolved through ``get_mcp_server_by_name`` -- the same - resolver admission used -- rather than the wider allowed-server prefix/access-group - matching. A name that only reaches a delegate server via server_id or an access - group would have been admitted as a real LiteLLM key, so probing it would leak that - key upstream; requiring the admission-resolver match closes that gap. Without the - probe a rejected token is absorbed by the tools/list handler and masked as an empty - tool list. Gated to single-server routes so one rejected token cannot 401 a - multi-server aggregate connect, matching the OBO preflight gating; the challenge - echoes the requested name so aliased routes get the same resource_metadata URL as - the tokenless preemptive challenge. """ forwarded_auth: Final = _get_forwarded_auth_from_scope(scope) - requested_single_target: Final = mcp_servers[0] if mcp_servers is not None and len(mcp_servers) == 1 else None - # The bare Authorization header (no x-litellm-api-key) is a valid upstream token - # only when admission classified it as one, i.e. the single requested name resolves - # to a delegate server under admission's own resolver. Resolve it the same way here - # so a server_id- or access-group-named delegate (which admission would have treated - # as a LiteLLM key) is never probed with that key. - delegate_server: Final = ( - global_mcp_server_manager.get_mcp_server_by_name(requested_single_target, client_ip=client_ip) - if requested_single_target - else None - ) - delegate_auth: Final = ( - _get_authorization_header_from_scope(scope) - if delegate_server is not None and _is_delegate_upstream_probe_target(delegate_server) - else None - ) - if not forwarded_auth and not delegate_auth: + if not forwarded_auth: return # Use the authorized server set, not the raw user-supplied names, so that @@ -4384,35 +4341,20 @@ if MCP_AVAILABLE: mcp_servers=mcp_servers, client_ip=client_ip, ) - passthrough_targets: Final[tuple[tuple[MCPServer, str, str], ...]] = ( - tuple( - (srv, forwarded_auth, srv.name) - for srv in allowed_servers - # Restrict to genuine OAuth pass-through servers (auth_type none + - # Authorization in extra_headers). Gateway-managed OAuth2 servers - # must not receive the ``resource_metadata=`` challenge emitted - # below — they require ``authorization_uri=`` pointing at the - # gateway AS metadata. ``is_oauth_passthrough`` already requires - # ``auth_type in (None, MCPAuth.none)``, which is mutually - # exclusive with ``has_client_credentials`` (oauth2 + M2M flow), - # so M2M servers are implicitly excluded here. - if srv.is_oauth_passthrough - ) - if forwarded_auth - else () + passthrough_targets: Final[tuple[tuple[MCPServer, str, str], ...]] = tuple( + (srv, forwarded_auth, srv.name) + for srv in allowed_servers + # Restrict to genuine OAuth pass-through servers (auth_type none + + # Authorization in extra_headers). Gateway-managed OAuth2 servers + # must not receive the ``resource_metadata=`` challenge emitted + # below — they require ``authorization_uri=`` pointing at the + # gateway AS metadata. ``is_oauth_passthrough`` already requires + # ``auth_type in (None, MCPAuth.none)``, which is mutually + # exclusive with ``has_client_credentials`` (oauth2 + M2M flow), + # so M2M servers are implicitly excluded here. + if srv.is_oauth_passthrough ) - # Probe the admission-resolved delegate server only when the caller is actually - # authorized for it (present in the IP-filtered allowed set), keyed by server_id. - delegate_targets: Final[tuple[tuple[MCPServer, str, str], ...]] = ( - tuple( - (srv, delegate_auth, requested_single_target) - for srv in allowed_servers - if delegate_server is not None and srv.server_id == delegate_server.server_id - ) - if delegate_auth and requested_single_target - else () - ) - probe_targets: Final = passthrough_targets + delegate_targets + probe_targets: Final = passthrough_targets if not probe_targets: return diff --git a/litellm/proxy/_experimental/out/404.html b/litellm/proxy/_experimental/out/404.html index d3fe1f37cd9..1b89865000e 100644 --- a/litellm/proxy/_experimental/out/404.html +++ b/litellm/proxy/_experimental/out/404.html @@ -1 +1 @@ -404: This page could not be found.LiteLLM Dashboard

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r={image_generation:"image",video_generation:"video",chat:"chat",completion:"chat",responses:"responses",image_edit:"image_edits",anthropic_messages:"anthropic_messages",audio_speech:"speech",audio_transcription:"transcription",embedding:"embeddings",realtime:"realtime"};e.s(["EndpointType",()=>s,"ModelMode",()=>n,"getEndpointType",0,e=>Object.values(n).includes(e)?r[e]:"chat"],865361),e.s(["generateCodeSnippet",0,e=>{let t,{apiKeySource:i,accessToken:n,apiKey:r,inputMessage:a,chatHistory:o,selectedTags:l,selectedVectorStores:d,selectedGuardrails:u,selectedPolicies:c,selectedVoice:p,endpointType:m,selectedModel:g,selectedSdk:h,proxySettings:f}=e,b="session"===i?n:r,x=window.location.origin,v=f?.LITELLM_UI_API_DOC_BASE_URL;v&&v.trim()?x=v:f?.PROXY_BASE_URL&&(x=f.PROXY_BASE_URL);let _=a||"Your prompt 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open(image_path, "rb") as image_file: - return base64.b64encode(image_file.read()).decode('utf-8') - -# Example with text only -response = client.responses.create( - model="${j}", - input=${JSON.stringify(n,null,4)}${i} -) - -print(response.output_text) - -# Example with image or PDF (uncomment and provide file path to use) -# base64_file = encode_image("path/to/your/file.jpg") # or .pdf -# response_with_file = client.responses.create( -# model="${j}", -# input=[ -# { -# "role": "user", -# "content": [ -# {"type": "input_text", "text": "${y}"}, -# { -# "type": "input_image", -# "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} -# }, -# ], -# } -# ]${i} -# ) -# print(response_with_file.output_text) -`;break}case s.IMAGE:t="azure"===h?` -# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. -# This snippet uses 'client.images.generate' and will create a new image based on your prompt. -# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. -import os -import requests -import json -import time -from PIL import Image - -result = client.images.generate( - model="${j}", - prompt="${a}", - n=1 -) - -json_response = json.loads(result.model_dump_json()) - -# Set the directory for the stored image -image_dir = os.path.join(os.curdir, 'images') - -# If the directory doesn't exist, create it -if not os.path.isdir(image_dir): - os.mkdir(image_dir) - -# Initialize the image path -image_filename = f"generated_image_{int(time.time())}.png" -image_path = os.path.join(image_dir, image_filename) - -try: - # Retrieve the generated image - if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): - image_url = json_response["data"][0]["url"] - generated_image = requests.get(image_url).content - with open(image_path, "wb") as image_file: - image_file.write(generated_image) - - print(f"Image saved to {image_path}") - # Display the image - image = Image.open(image_path) - image.show() - else: - print("Could not find image URL in response.") - print("Full response:", json_response) -except Exception as e: - print(f"An error occurred: {e}") - print("Full response:", json_response) -`:` -import base64 -import os -import time -import json -from PIL import Image -import requests - -# Helper function to encode images to base64 -def encode_image(image_path): - with open(image_path, "rb") as image_file: - return base64.b64encode(image_file.read()).decode('utf-8') - -# Helper function to create a file (simplified for this example) -def create_file(image_path): - # In a real implementation, this would upload the file to OpenAI - # For this example, we'll just return a placeholder ID - return f"file_{os.path.basename(image_path).replace('.', '_')}" - -# The prompt entered by the user -prompt = "${y}" - -# Encode images to base64 -base64_image1 = encode_image("body-lotion.png") -base64_image2 = encode_image("soap.png") - -# Create file IDs -file_id1 = create_file("body-lotion.png") -file_id2 = create_file("incense-kit.png") - -response = client.responses.create( - model="${j}", - input=[ - { - "role": "user", - "content": [ - {"type": "input_text", "text": prompt}, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image1}", - }, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image2}", - }, - { - "type": "input_image", - "file_id": file_id1, - }, - { - "type": "input_image", - "file_id": file_id2, - } - ], - } - ], - tools=[{"type": "image_generation"}], -) - -# Process the response -image_generation_calls = [ - output - for output in response.output - if output.type == "image_generation_call" -] - -image_data = [output.result for output in image_generation_calls] - -if image_data: - image_base64 = image_data[0] - image_filename = f"edited_image_{int(time.time())}.png" - with open(image_filename, "wb") as f: - f.write(base64.b64decode(image_base64)) - print(f"Image saved to {image_filename}") -else: - # If no image is generated, there might be a text response with an explanation - text_response = [output.text for output in response.output if hasattr(output, 'text')] - if text_response: - print("No image generated. 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e,t;return{localeError:(e={string:{unit:{one:"сімвал",few:"сімвалы",many:"сімвалаў"},verb:"мець"},array:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},set:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},file:{unit:{one:"байт",few:"байты",many:"байтаў"},verb:"мець"}},t={regex:"увод",email:"email адрас",url:"URL",emoji:"эмодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата і час",date:"ISO дата",time:"ISO час",duration:"ISO працягласць",ipv4:"IPv4 адрас",ipv6:"IPv6 адрас",cidrv4:"IPv4 дыяпазон",cidrv6:"IPv6 дыяпазон",base64:"радок у фармаце base64",base64url:"радок у фармаце base64url",json_string:"JSON радок",e164:"нумар E.164",jwt:"JWT",template_literal:"увод"},i=>{switch(i.code){case"invalid_type":return`Няправільны ўвод: чакаўся ${i.expected}, атрымана ${(e=>{let t=typeof e;switch(t){case"number":return 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чакалася, што ${i.origin} павінна быць ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Няправільны радок: павінен пачынацца з "${i.prefix}"`;if("ends_with"===i.format)return`Няправільны радок: павінен заканчвацца на "${i.suffix}"`;if("includes"===i.format)return`Няправільны радок: павінен змяшчаць "${i.includes}"`;if("regex"===i.format)return`Няправільны радок: павінен адпавядаць шаблону ${i.pattern}`;return`Няправільны ${t[i.format]??i.format}`;case"not_multiple_of":return`Няправільны лік: павінен быць кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспазнаны ${i.keys.length>1?"ключы":"ключ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Няправільны ключ у ${i.origin}`;case"invalid_union":default:return"Няправільны ўвод";case"invalid_element":return`Няправільнае значэнне ў ${i.origin}`}})}},"ca",0,function(){let e,t;return{localeError:(e={string:{unit:"caràcters",verb:"contenir"},file:{unit:"bytes",verb:"contenir"},array:{unit:"elements",verb:"contenir"},set:{unit:"elements",verb:"contenir"}},t={regex:"entrada",email:"adreça electrònica",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i hora ISO",date:"data ISO",time:"hora ISO",duration:"durada ISO",ipv4:"adreça IPv4",ipv6:"adreça IPv6",cidrv4:"rang IPv4",cidrv6:"rang IPv6",base64:"cadena codificada en base64",base64url:"cadena codificada en base64url",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipus inv\xe0lid: s'esperava ${i.expected}, s'ha rebut ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Valor inv\xe0lid: s'esperava ${V.stringifyPrimitive(i.values[0])}`;return`Opci\xf3 inv\xe0lida: s'esperava una de ${V.joinValues(i.values," o ")}`;case"too_big":{let t=i.inclusive?"com a màxim":"menys de",r=e[i.origin]??null;if(r)return`Massa gran: s'esperava que ${i.origin??"el valor"} contingu\xe9s ${t} ${i.maximum.toString()} ${r.unit??"elements"}`;return`Massa gran: s'esperava que ${i.origin??"el valor"} fos ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"com a mínim":"més de",r=e[i.origin]??null;if(r)return`Massa petit: s'esperava que ${i.origin} contingu\xe9s ${t} ${i.minimum.toString()} ${r.unit}`;return`Massa petit: s'esperava que ${i.origin} fos ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Format inv\xe0lid: ha de comen\xe7ar amb "${i.prefix}"`;if("ends_with"===i.format)return`Format inv\xe0lid: ha d'acabar amb "${i.suffix}"`;if("includes"===i.format)return`Format inv\xe0lid: ha d'incloure "${i.includes}"`;if("regex"===i.format)return`Format inv\xe0lid: ha de coincidir amb el patr\xf3 ${i.pattern}`;return`Format inv\xe0lid per a ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe0lid: ha de ser m\xfaltiple de ${i.divisor}`;case"unrecognized_keys":return`Clau${i.keys.length>1?"s":""} no reconeguda${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Clau inv\xe0lida a ${i.origin}`;case"invalid_union":default:return"Entrada invàlida";case"invalid_element":return`Element inv\xe0lid a ${i.origin}`}})}},"cs",0,function(){let e,t;return{localeError:(e={string:{unit:"znaků",verb:"mít"},file:{unit:"bajtů",verb:"mít"},array:{unit:"prvků",verb:"mít"},set:{unit:"prvků",verb:"mít"}},t={regex:"regulární výraz",email:"e-mailová adresa",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"datum a čas ve formátu ISO",date:"datum ve formátu ISO",time:"čas ve formátu ISO",duration:"doba trvání ISO",ipv4:"IPv4 adresa",ipv6:"IPv6 adresa",cidrv4:"rozsah IPv4",cidrv6:"rozsah IPv6",base64:"řetězec zakódovaný ve formátu base64",base64url:"řetězec zakódovaný ve formátu base64url",json_string:"řetězec ve formátu JSON",e164:"číslo E.164",jwt:"JWT",template_literal:"vstup"},i=>{switch(i.code){case"invalid_type":return`Neplatn\xfd vstup: oček\xe1v\xe1no ${i.expected}, obdrženo ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"číslo";case"string":return"řetězec";case"boolean":return"boolean";case"bigint":return"bigint";case"function":return"funkce";case"symbol":return"symbol";case"undefined":return"undefined";case"object":if(Array.isArray(e))return"pole";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neplatn\xfd vstup: oček\xe1v\xe1no ${V.stringifyPrimitive(i.values[0])}`;return`Neplatn\xe1 možnost: oček\xe1v\xe1na jedna z hodnot ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${t}${i.maximum.toString()} ${r.unit??"prvků"}`;return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${t}${i.minimum.toString()} ${r.unit??"prvků"}`;return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neplatn\xfd řetězec: mus\xed zač\xednat na "${i.prefix}"`;if("ends_with"===i.format)return`Neplatn\xfd řetězec: mus\xed končit na "${i.suffix}"`;if("includes"===i.format)return`Neplatn\xfd řetězec: mus\xed obsahovat "${i.includes}"`;if("regex"===i.format)return`Neplatn\xfd řetězec: mus\xed odpov\xeddat vzoru ${i.pattern}`;return`Neplatn\xfd form\xe1t ${t[i.format]??i.format}`;case"not_multiple_of":return`Neplatn\xe9 č\xedslo: mus\xed b\xfdt n\xe1sobkem ${i.divisor}`;case"unrecognized_keys":return`Nezn\xe1m\xe9 kl\xedče: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Neplatn\xfd kl\xedč v ${i.origin}`;case"invalid_union":default:return"Neplatný vstup";case"invalid_element":return`Neplatn\xe1 hodnota v ${i.origin}`}})}},"de",0,function(){let e,t;return{localeError:(e={string:{unit:"Zeichen",verb:"zu haben"},file:{unit:"Bytes",verb:"zu haben"},array:{unit:"Elemente",verb:"zu haben"},set:{unit:"Elemente",verb:"zu haben"}},t={regex:"Eingabe",email:"E-Mail-Adresse",url:"URL",emoji:"Emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-Datum und -Uhrzeit",date:"ISO-Datum",time:"ISO-Uhrzeit",duration:"ISO-Dauer",ipv4:"IPv4-Adresse",ipv6:"IPv6-Adresse",cidrv4:"IPv4-Bereich",cidrv6:"IPv6-Bereich",base64:"Base64-codierter String",base64url:"Base64-URL-codierter String",json_string:"JSON-String",e164:"E.164-Nummer",jwt:"JWT",template_literal:"Eingabe"},i=>{switch(i.code){case"invalid_type":return`Ung\xfcltige Eingabe: erwartet ${i.expected}, erhalten ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"Zahl";case"object":if(Array.isArray(e))return"Array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ung\xfcltige Eingabe: erwartet ${V.stringifyPrimitive(i.values[0])}`;return`Ung\xfcltige Option: erwartet eine von ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${t}${i.maximum.toString()} ${r.unit??"Elemente"} hat`;return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${t}${i.maximum.toString()} ist`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Zu klein: erwartet, dass ${i.origin} ${t}${i.minimum.toString()} ${r.unit} hat`;return`Zu klein: erwartet, dass ${i.origin} ${t}${i.minimum.toString()} ist`}case"invalid_format":if("starts_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.suffix}" enden`;if("includes"===i.format)return`Ung\xfcltiger String: muss "${i.includes}" enthalten`;if("regex"===i.format)return`Ung\xfcltiger String: muss dem Muster ${i.pattern} entsprechen`;return`Ung\xfcltig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ung\xfcltige Zahl: muss ein Vielfaches von ${i.divisor} sein`;case"unrecognized_keys":return`${i.keys.length>1?"Unbekannte Schlüssel":"Unbekannter Schlüssel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ung\xfcltiger Schl\xfcssel in ${i.origin}`;case"invalid_union":default:return"Ungültige Eingabe";case"invalid_element":return`Ung\xfcltiger Wert in ${i.origin}`}})}},"en",()=>tT.default,"eo",0,function(){let e,t;return{localeError:(e={string:{unit:"karaktrojn",verb:"havi"},file:{unit:"bajtojn",verb:"havi"},array:{unit:"elementojn",verb:"havi"},set:{unit:"elementojn",verb:"havi"}},t={regex:"enigo",email:"retadreso",url:"URL",emoji:"emoĝio",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datotempo",date:"ISO-dato",time:"ISO-tempo",duration:"ISO-daŭro",ipv4:"IPv4-adreso",ipv6:"IPv6-adreso",cidrv4:"IPv4-rango",cidrv6:"IPv6-rango",base64:"64-ume kodita karaktraro",base64url:"URL-64-ume kodita karaktraro",json_string:"JSON-karaktraro",e164:"E.164-nombro",jwt:"JWT",template_literal:"enigo"},i=>{switch(i.code){case"invalid_type":return`Nevalida enigo: atendiĝis ${i.expected}, riceviĝis ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombro";case"object":if(Array.isArray(e))return"tabelo";if(null===e)return"senvalora";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nevalida enigo: atendiĝis ${V.stringifyPrimitive(i.values[0])}`;return`Nevalida opcio: atendiĝis unu el ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${t}${i.maximum.toString()} ${r.unit??"elementojn"}`;return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Tro malgranda: atendiĝis ke ${i.origin} havu ${t}${i.minimum.toString()} ${r.unit}`;return`Tro malgranda: atendiĝis ke ${i.origin} estu ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nevalida karaktraro: devas komenciĝi per "${i.prefix}"`;if("ends_with"===i.format)return`Nevalida karaktraro: devas finiĝi per "${i.suffix}"`;if("includes"===i.format)return`Nevalida karaktraro: devas inkluzivi "${i.includes}"`;if("regex"===i.format)return`Nevalida karaktraro: devas kongrui kun la modelo ${i.pattern}`;return`Nevalida ${t[i.format]??i.format}`;case"not_multiple_of":return`Nevalida nombro: devas esti oblo de ${i.divisor}`;case"unrecognized_keys":return`Nekonata${i.keys.length>1?"j":""} ŝlosilo${i.keys.length>1?"j":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Nevalida ŝlosilo en ${i.origin}`;case"invalid_union":default:return"Nevalida enigo";case"invalid_element":return`Nevalida valoro en ${i.origin}`}})}},"es",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"tener"},file:{unit:"bytes",verb:"tener"},array:{unit:"elementos",verb:"tener"},set:{unit:"elementos",verb:"tener"}},t={regex:"entrada",email:"dirección de correo electrónico",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"fecha y hora ISO",date:"fecha ISO",time:"hora ISO",duration:"duración ISO",ipv4:"dirección IPv4",ipv6:"dirección IPv6",cidrv4:"rango IPv4",cidrv6:"rango IPv6",base64:"cadena codificada en base64",base64url:"URL codificada en base64",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Entrada inv\xe1lida: se esperaba ${i.expected}, recibido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"arreglo";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: se esperaba ${V.stringifyPrimitive(i.values[0])}`;return`Opci\xf3n 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${i.pattern}`;return`Inv\xe1lido ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe1lido: debe ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Llave${i.keys.length>1?"s":""} desconocida${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Llave inv\xe1lida en ${i.origin}`;case"invalid_union":default:return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido en ${i.origin}`}})}},"fa",0,function(){let e,t;return{localeError:(e={string:{unit:"کاراکتر",verb:"داشته باشد"},file:{unit:"بایت",verb:"داشته باشد"},array:{unit:"آیتم",verb:"داشته باشد"},set:{unit:"آیتم",verb:"داشته باشد"}},t={regex:"ورودی",email:"آدرس ایمیل",url:"URL",emoji:"ایموجی",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاریخ و زمان ایزو",date:"تاریخ ایزو",time:"زمان ایزو",duration:"مدت زمان ایزو",ipv4:"IPv4 آدرس",ipv6:"IPv6 آدرس",cidrv4:"IPv4 دامنه",cidrv6:"IPv6 دامنه",base64:"base64-encoded رشته",base64url:"base64url-encoded رشته",json_string:"JSON رشته",e164:"E.164 عدد",jwt:"JWT",template_literal:"ورودی"},i=>{switch(i.code){case"invalid_type":return`ورودی نامعتبر: می‌بایست ${i.expected} می‌بود، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"آرایه";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} دریافت شد`;case"invalid_value":if(1===i.values.length)return`ورودی نامعتبر: می‌بایست ${V.stringifyPrimitive(i.values[0])} می‌بود`;return`گزینه نامعتبر: می‌بایست یکی از ${V.joinValues(i.values,"|")} می‌بود`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصر"} باشد`;return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${t}${i.maximum.toString()} باشد`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`خیلی کوچک: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} باشد`;return`خیلی کوچک: ${i.origin} باید ${t}${i.minimum.toString()} باشد`}case"invalid_format":if("starts_with"===i.format)return`رشته نامعتبر: باید با "${i.prefix}" شروع شود`;if("ends_with"===i.format)return`رشته نامعتبر: باید با "${i.suffix}" تمام شود`;if("includes"===i.format)return`رشته نامعتبر: باید شامل "${i.includes}" باشد`;if("regex"===i.format)return`رشته نامعتبر: باید با الگوی ${i.pattern} مطابقت داشته باشد`;return`${t[i.format]??i.format} نامعتبر`;case"not_multiple_of":return`عدد نامعتبر: باید مضرب ${i.divisor} باشد`;case"unrecognized_keys":return`کلید${i.keys.length>1?"های":""} ناشناس: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`کلید ناشناس در ${i.origin}`;case"invalid_union":default:return"ورودی نامعتبر";case"invalid_element":return`مقدار نامعتبر در ${i.origin}`}})}},"fi",0,function(){let e,t;return{localeError:(e={string:{unit:"merkkiä",subject:"merkkijonon"},file:{unit:"tavua",subject:"tiedoston"},array:{unit:"alkiota",subject:"listan"},set:{unit:"alkiota",subject:"joukon"},number:{unit:"",subject:"luvun"},bigint:{unit:"",subject:"suuren kokonaisluvun"},int:{unit:"",subject:"kokonaisluvun"},date:{unit:"",subject:"päivämäärän"}},t={regex:"säännöllinen lauseke",email:"sähköpostiosoite",url:"URL-osoite",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-aikaleima",date:"ISO-päivämäärä",time:"ISO-aika",duration:"ISO-kesto",ipv4:"IPv4-osoite",ipv6:"IPv6-osoite",cidrv4:"IPv4-alue",cidrv6:"IPv6-alue",base64:"base64-koodattu merkkijono",base64url:"base64url-koodattu merkkijono",json_string:"JSON-merkkijono",e164:"E.164-luku",jwt:"JWT",template_literal:"templaattimerkkijono"},i=>{switch(i.code){case"invalid_type":return`Virheellinen tyyppi: odotettiin ${i.expected}, oli ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Virheellinen sy\xf6te: t\xe4ytyy olla ${V.stringifyPrimitive(i.values[0])}`;return`Virheellinen valinta: t\xe4ytyy olla yksi seuraavista: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Liian suuri: ${r.subject} t\xe4ytyy olla ${t}${i.maximum.toString()} ${r.unit}`.trim();return`Liian suuri: arvon t\xe4ytyy olla ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Liian pieni: ${r.subject} t\xe4ytyy olla ${t}${i.minimum.toString()} ${r.unit}`.trim();return`Liian pieni: arvon t\xe4ytyy olla ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy alkaa "${i.prefix}"`;if("ends_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy loppua "${i.suffix}"`;if("includes"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy sis\xe4lt\xe4\xe4 "${i.includes}"`;if("regex"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy vastata s\xe4\xe4nn\xf6llist\xe4 lauseketta ${i.pattern}`;return`Virheellinen ${t[i.format]??i.format}`;case"not_multiple_of":return`Virheellinen luku: t\xe4ytyy olla luvun ${i.divisor} monikerta`;case"unrecognized_keys":return`${i.keys.length>1?"Tuntemattomat avaimet":"Tuntematon avain"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return"Virheellinen avain tietueessa";case"invalid_union":return"Virheellinen unioni";case"invalid_element":return"Virheellinen arvo joukossa";default:return"Virheellinen syöte"}})}},"fr",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date et heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",jwt:"JWT",template_literal:"entrée"},i=>{switch(i.code){case"invalid_type":return`Entr\xe9e invalide : ${i.expected} attendu, ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombre";case"object":if(Array.isArray(e))return"tableau";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} re\xe7u`;case"invalid_value":if(1===i.values.length)return`Entr\xe9e invalide : ${V.stringifyPrimitive(i.values[0])} attendu`;return`Option invalide : une valeur parmi ${V.joinValues(i.values,"|")} attendue`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Trop grand : ${i.origin??"valeur"} doit ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"élément(s)"}`;return`Trop grand : ${i.origin??"valeur"} doit \xeatre ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Trop petit : ${i.origin} doit ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : ${i.origin} doit \xeatre ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au mod\xe8le ${i.pattern}`;return`${t[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"frCA",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse courriel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date-heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",jwt:"JWT",template_literal:"entrée"},i=>{switch(i.code){case"invalid_type":return`Entr\xe9e invalide : attendu ${i.expected}, re\xe7u ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entr\xe9e invalide : attendu ${V.stringifyPrimitive(i.values[0])}`;return`Option invalide : attendu l'une des valeurs suivantes ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"≤":"<",r=e[i.origin]??null;if(r)return`Trop grand : attendu que ${i.origin??"la valeur"} ait ${t}${i.maximum.toString()} ${r.unit}`;return`Trop grand : attendu que ${i.origin??"la valeur"} soit ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"≥":">",r=e[i.origin]??null;if(r)return`Trop petit : attendu que ${i.origin} ait ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : attendu que ${i.origin} soit ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au motif ${i.pattern}`;return`${t[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"he",0,function(){let e,t;return{localeError:(e={string:{unit:"אותיות",verb:"לכלול"},file:{unit:"בייטים",verb:"לכלול"},array:{unit:"פריטים",verb:"לכלול"},set:{unit:"פריטים",verb:"לכלול"}},t={regex:"קלט",email:"כתובת אימייל",url:"כתובת רשת",emoji:"אימוג'י",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"תאריך וזמן ISO",date:"תאריך ISO",time:"זמן ISO",duration:"משך זמן ISO",ipv4:"כתובת IPv4",ipv6:"כתובת IPv6",cidrv4:"טווח IPv4",cidrv6:"טווח IPv6",base64:"מחרוזת בבסיס 64",base64url:"מחרוזת בבסיס 64 לכתובות רשת",json_string:"מחרוזת JSON",e164:"מספר E.164",jwt:"JWT",template_literal:"קלט"},i=>{switch(i.code){case"invalid_type":return`קלט לא תקין: צריך ${i.expected}, התקבל ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`קלט לא תקין: צריך ${V.stringifyPrimitive(i.values[0])}`;return`קלט לא תקין: צריך אחת מהאפשרויות ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`גדול מדי: ${i.origin??"value"} צריך להיות ${t}${i.maximum.toString()} ${r.unit??"elements"}`;return`גדול מדי: ${i.origin??"value"} צריך להיות ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`קטן מדי: ${i.origin} צריך להיות ${t}${i.minimum.toString()} ${r.unit}`;return`קטן מדי: ${i.origin} צריך להיות ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`מחרוזת לא תקינה: חייבת להתחיל ב"${i.prefix}"`;if("ends_with"===i.format)return`מחרוזת לא תקינה: חייבת להסתיים ב "${i.suffix}"`;if("includes"===i.format)return`מחרוזת לא תקינה: חייבת לכלול "${i.includes}"`;if("regex"===i.format)return`מחרוזת לא תקינה: חייבת להתאים לתבנית ${i.pattern}`;return`${t[i.format]??i.format} לא תקין`;case"not_multiple_of":return`מספר לא תקין: חייב להיות מכפלה של ${i.divisor}`;case"unrecognized_keys":return`מפתח${i.keys.length>1?"ות":""} לא מזוה${i.keys.length>1?"ים":"ה"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`מפתח לא תקין ב${i.origin}`;case"invalid_union":default:return"קלט לא תקין";case"invalid_element":return`ערך לא תקין ב${i.origin}`}})}},"hu",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"legyen"},file:{unit:"byte",verb:"legyen"},array:{unit:"elem",verb:"legyen"},set:{unit:"elem",verb:"legyen"}},t={regex:"bemenet",email:"email cím",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO időbélyeg",date:"ISO dátum",time:"ISO idő",duration:"ISO időintervallum",ipv4:"IPv4 cím",ipv6:"IPv6 cím",cidrv4:"IPv4 tartomány",cidrv6:"IPv6 tartomány",base64:"base64-kódolt string",base64url:"base64url-kódolt string",json_string:"JSON string",e164:"E.164 szám",jwt:"JWT",template_literal:"bemenet"},i=>{switch(i.code){case"invalid_type":return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${i.expected}, a kapott \xe9rt\xe9k ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"szám";case"object":if(Array.isArray(e))return"tömb";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${V.stringifyPrimitive(i.values[0])}`;return`\xc9rv\xe9nytelen opci\xf3: valamelyik \xe9rt\xe9k v\xe1rt ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`T\xfal nagy: ${i.origin??"érték"} m\xe9rete t\xfal nagy ${t}${i.maximum.toString()} ${r.unit??"elem"}`;return`T\xfal nagy: a bemeneti \xe9rt\xe9k ${i.origin??"érték"} t\xfal nagy: ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} m\xe9rete t\xfal kicsi ${t}${i.minimum.toString()} ${r.unit}`;return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} t\xfal kicsi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.prefix}" \xe9rt\xe9kkel kell kezdődnie`;if("ends_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.suffix}" \xe9rt\xe9kkel kell v\xe9gződnie`;if("includes"===i.format)return`\xc9rv\xe9nytelen string: "${i.includes}" \xe9rt\xe9ket kell tartalmaznia`;if("regex"===i.format)return`\xc9rv\xe9nytelen string: ${i.pattern} mint\xe1nak kell megfelelnie`;return`\xc9rv\xe9nytelen ${t[i.format]??i.format}`;case"not_multiple_of":return`\xc9rv\xe9nytelen sz\xe1m: ${i.divisor} t\xf6bbsz\xf6r\xf6s\xe9nek kell lennie`;case"unrecognized_keys":return`Ismeretlen kulcs${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`\xc9rv\xe9nytelen kulcs ${i.origin}`;case"invalid_union":default:return"Érvénytelen bemenet";case"invalid_element":return`\xc9rv\xe9nytelen \xe9rt\xe9k: ${i.origin}`}})}},"id",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"memiliki"},file:{unit:"byte",verb:"memiliki"},array:{unit:"item",verb:"memiliki"},set:{unit:"item",verb:"memiliki"}},t={regex:"input",email:"alamat email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tanggal dan waktu format ISO",date:"tanggal format ISO",time:"jam format ISO",duration:"durasi format ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"rentang alamat IPv4",cidrv6:"rentang alamat IPv6",base64:"string dengan enkode base64",base64url:"string dengan enkode base64url",json_string:"string JSON",e164:"angka E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak valid: diharapkan ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak valid: diharapkan ${V.stringifyPrimitive(i.values[0])}`;return`Pilihan tidak valid: diharapkan salah satu dari ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: diharapkan ${i.origin??"value"} memiliki ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: diharapkan ${i.origin??"value"} menjadi ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: diharapkan ${i.origin} memiliki ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: diharapkan ${i.origin} menjadi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak valid: harus dimulai dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak valid: harus berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak valid: harus menyertakan "${i.includes}"`;if("regex"===i.format)return`String tidak valid: harus sesuai pola ${i.pattern}`;return`${t[i.format]??i.format} tidak valid`;case"not_multiple_of":return`Angka tidak valid: harus kelipatan dari ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali ${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kunci tidak valid di ${i.origin}`;case"invalid_union":default:return"Input tidak valid";case"invalid_element":return`Nilai tidak valid di ${i.origin}`}})}},"it",0,function(){let e,t;return{localeError:(e={string:{unit:"caratteri",verb:"avere"},file:{unit:"byte",verb:"avere"},array:{unit:"elementi",verb:"avere"},set:{unit:"elementi",verb:"avere"}},t={regex:"input",email:"indirizzo email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e ora ISO",date:"data ISO",time:"ora ISO",duration:"durata ISO",ipv4:"indirizzo IPv4",ipv6:"indirizzo IPv6",cidrv4:"intervallo IPv4",cidrv6:"intervallo IPv6",base64:"stringa codificata in base64",base64url:"URL codificata in base64",json_string:"stringa JSON",e164:"numero E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input non valido: atteso ${i.expected}, ricevuto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numero";case"object":if(Array.isArray(e))return"vettore";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input non valido: atteso ${V.stringifyPrimitive(i.values[0])}`;return`Opzione non valida: atteso uno tra ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Troppo grande: ${i.origin??"valore"} deve avere ${t}${i.maximum.toString()} ${r.unit??"elementi"}`;return`Troppo grande: ${i.origin??"valore"} deve essere ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Troppo piccolo: ${i.origin} deve avere ${t}${i.minimum.toString()} ${r.unit}`;return`Troppo piccolo: ${i.origin} deve essere ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Stringa non valida: deve iniziare con "${i.prefix}"`;if("ends_with"===i.format)return`Stringa non valida: deve terminare con "${i.suffix}"`;if("includes"===i.format)return`Stringa non valida: deve includere "${i.includes}"`;if("regex"===i.format)return`Stringa non valida: deve corrispondere al pattern ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Numero non valido: deve essere un multiplo di ${i.divisor}`;case"unrecognized_keys":return`Chiav${i.keys.length>1?"i":"e"} non riconosciut${i.keys.length>1?"e":"a"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Chiave non valida in ${i.origin}`;case"invalid_union":default:return"Input non valido";case"invalid_element":return`Valore non valido in ${i.origin}`}})}},"ja",0,function(){let e,t;return{localeError:(e={string:{unit:"文字",verb:"である"},file:{unit:"バイト",verb:"である"},array:{unit:"要素",verb:"である"},set:{unit:"要素",verb:"である"}},t={regex:"入力値",email:"メールアドレス",url:"URL",emoji:"絵文字",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日時",date:"ISO日付",time:"ISO時刻",duration:"ISO期間",ipv4:"IPv4アドレス",ipv6:"IPv6アドレス",cidrv4:"IPv4範囲",cidrv6:"IPv6範囲",base64:"base64エンコード文字列",base64url:"base64urlエンコード文字列",json_string:"JSON文字列",e164:"E.164番号",jwt:"JWT",template_literal:"入力値"},i=>{switch(i.code){case"invalid_type":return`無効な入力: ${i.expected}が期待されましたが、${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"数値";case"object":if(Array.isArray(e))return"配列";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}が入力されました`;case"invalid_value":if(1===i.values.length)return`無効な入力: ${V.stringifyPrimitive(i.values[0])}が期待されました`;return`無効な選択: ${V.joinValues(i.values,"、")}のいずれかである必要があります`;case"too_big":{let t=i.inclusive?"以下である":"より小さい",r=e[i.origin]??null;if(r)return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${r.unit??"要素"}${t}必要があります`;return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${t}必要があります`}case"too_small":{let t=i.inclusive?"以上である":"より大きい",r=e[i.origin]??null;if(r)return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${r.unit}${t}必要があります`;return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${t}必要があります`}case"invalid_format":if("starts_with"===i.format)return`無効な文字列: "${i.prefix}"で始まる必要があります`;if("ends_with"===i.format)return`無効な文字列: "${i.suffix}"で終わる必要があります`;if("includes"===i.format)return`無効な文字列: "${i.includes}"を含む必要があります`;if("regex"===i.format)return`無効な文字列: パターン${i.pattern}に一致する必要があります`;return`無効な${t[i.format]??i.format}`;case"not_multiple_of":return`無効な数値: ${i.divisor}の倍数である必要があります`;case"unrecognized_keys":return`認識されていないキー${i.keys.length>1?"群":""}: ${V.joinValues(i.keys,"、")}`;case"invalid_key":return`${i.origin}内の無効なキー`;case"invalid_union":default:return"無効な入力";case"invalid_element":return`${i.origin}内の無効な値`}})}},"kh",0,function(){let e,t;return{localeError:(e={string:{unit:"តួអក្សរ",verb:"គួរមាន"},file:{unit:"បៃ",verb:"គួរមាន"},array:{unit:"ធាតុ",verb:"គួរមាន"},set:{unit:"ធាតុ",verb:"គួរមាន"}},t={regex:"ទិន្នន័យបញ្ចូល",email:"អាសយដ្ឋានអ៊ីមែល",url:"URL",emoji:"សញ្ញាអារម្មណ៍",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"កាលបរិច្ឆេទ និងម៉ោង ISO",date:"កាលបរិច្ឆេទ ISO",time:"ម៉ោង ISO",duration:"រយៈពេល ISO",ipv4:"អាសយដ្ឋាន IPv4",ipv6:"អាសយដ្ឋាន IPv6",cidrv4:"ដែនអាសយដ្ឋាន IPv4",cidrv6:"ដែនអាសយដ្ឋាន IPv6",base64:"ខ្សែអក្សរអ៊ិកូដ base64",base64url:"ខ្សែអក្សរអ៊ិកូដ base64url",json_string:"ខ្សែអក្សរ JSON",e164:"លេខ E.164",jwt:"JWT",template_literal:"ទិន្នន័យបញ្ចូល"},i=>{switch(i.code){case"invalid_type":return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${i.expected} ប៉ុន្តែទទួលបាន ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"មិនមែនជាលេខ (NaN)":"លេខ";case"object":if(Array.isArray(e))return"អារេ (Array)";if(null===e)return"គ្មានតម្លៃ (null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${V.stringifyPrimitive(i.values[0])}`;return`ជម្រើសមិនត្រឹមត្រូវ៖ ត្រូវជាមួយក្នុងចំណោម ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()} ${r.unit??"ធាតុ"}`;return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()} ${r.unit}`;return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវចាប់ផ្តើមដោយ "${i.prefix}"`;if("ends_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវបញ្ចប់ដោយ "${i.suffix}"`;if("includes"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវមាន "${i.includes}"`;if("regex"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវតែផ្គូផ្គងនឹងទម្រង់ដែលបានកំណត់ ${i.pattern}`;return`មិនត្រឹមត្រូវ៖ ${t[i.format]??i.format}`;case"not_multiple_of":return`លេខមិនត្រឹមត្រូវ៖ ត្រូវតែជាពហុគុណនៃ ${i.divisor}`;case"unrecognized_keys":return`រកឃើញសោមិនស្គាល់៖ ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`សោមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`;case"invalid_union":default:return"ទិន្នន័យមិនត្រឹមត្រូវ";case"invalid_element":return`ទិន្នន័យមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`}})}},"ko",0,function(){let e,t;return{localeError:(e={string:{unit:"문자",verb:"to have"},file:{unit:"바이트",verb:"to have"},array:{unit:"개",verb:"to have"},set:{unit:"개",verb:"to have"}},t={regex:"입력",email:"이메일 주소",url:"URL",emoji:"이모지",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 날짜시간",date:"ISO 날짜",time:"ISO 시간",duration:"ISO 기간",ipv4:"IPv4 주소",ipv6:"IPv6 주소",cidrv4:"IPv4 범위",cidrv6:"IPv6 범위",base64:"base64 인코딩 문자열",base64url:"base64url 인코딩 문자열",json_string:"JSON 문자열",e164:"E.164 번호",jwt:"JWT",template_literal:"입력"},i=>{switch(i.code){case"invalid_type":return`잘못된 입력: 예상 타입은 ${i.expected}, 받은 타입은 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}입니다`;case"invalid_value":if(1===i.values.length)return`잘못된 입력: 값은 ${V.stringifyPrimitive(i.values[0])} 이어야 합니다`;return`잘못된 옵션: ${V.joinValues(i.values,"또는 ")} 중 하나여야 합니다`;case"too_big":{let t=i.inclusive?"이하":"미만",r="미만"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()} ${t}${r}`}case"too_small":{let t=i.inclusive?"이상":"초과",r="이상"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()} ${t}${r}`}case"invalid_format":if("starts_with"===i.format)return`잘못된 문자열: "${i.prefix}"(으)로 시작해야 합니다`;if("ends_with"===i.format)return`잘못된 문자열: "${i.suffix}"(으)로 끝나야 합니다`;if("includes"===i.format)return`잘못된 문자열: "${i.includes}"을(를) 포함해야 합니다`;if("regex"===i.format)return`잘못된 문자열: 정규식 ${i.pattern} 패턴과 일치해야 합니다`;return`잘못된 ${t[i.format]??i.format}`;case"not_multiple_of":return`잘못된 숫자: ${i.divisor}의 배수여야 합니다`;case"unrecognized_keys":return`인식할 수 없는 키: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`잘못된 키: ${i.origin}`;case"invalid_union":default:return"잘못된 입력";case"invalid_element":return`잘못된 값: ${i.origin}`}})}},"mk",0,function(){let e,t;return{localeError:(e={string:{unit:"знаци",verb:"да имаат"},file:{unit:"бајти",verb:"да имаат"},array:{unit:"ставки",verb:"да имаат"},set:{unit:"ставки",verb:"да имаат"}},t={regex:"внес",email:"адреса на е-пошта",url:"URL",emoji:"емоџи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO датум и време",date:"ISO датум",time:"ISO време",duration:"ISO времетраење",ipv4:"IPv4 адреса",ipv6:"IPv6 адреса",cidrv4:"IPv4 опсег",cidrv6:"IPv6 опсег",base64:"base64-енкодирана низа",base64url:"base64url-енкодирана низа",json_string:"JSON низа",e164:"E.164 број",jwt:"JWT",template_literal:"внес"},i=>{switch(i.code){case"invalid_type":return`Грешен внес: се очекува ${i.expected}, примено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"број";case"object":if(Array.isArray(e))return"низа";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Invalid input: expected ${V.stringifyPrimitive(i.values[0])}`;return`Грешана опција: се очекува една ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Премногу голем: се очекува ${i.origin??"вредноста"} да има ${t}${i.maximum.toString()} ${r.unit??"елементи"}`;return`Премногу голем: се очекува ${i.origin??"вредноста"} да биде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Премногу мал: се очекува ${i.origin} да има ${t}${i.minimum.toString()} ${r.unit}`;return`Премногу мал: се очекува ${i.origin} да биде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неважечка низа: мора да започнува со "${i.prefix}"`;if("ends_with"===i.format)return`Неважечка низа: мора да завршува со "${i.suffix}"`;if("includes"===i.format)return`Неважечка низа: мора да вклучува "${i.includes}"`;if("regex"===i.format)return`Неважечка низа: мора да одгоара на патернот ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Грешен број: мора да биде делив со ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Непрепознаени клучеви":"Непрепознаен клуч"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Грешен клуч во ${i.origin}`;case"invalid_union":default:return"Грешен внес";case"invalid_element":return`Грешна вредност во ${i.origin}`}})}},"ms",0,function(){let e,t;return{localeError:(e={string:{unit:"aksara",verb:"mempunyai"},file:{unit:"bait",verb:"mempunyai"},array:{unit:"elemen",verb:"mempunyai"},set:{unit:"elemen",verb:"mempunyai"}},t={regex:"input",email:"alamat e-mel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tarikh masa ISO",date:"tarikh ISO",time:"masa ISO",duration:"tempoh ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"julat IPv4",cidrv6:"julat IPv6",base64:"string dikodkan base64",base64url:"string dikodkan base64url",json_string:"string JSON",e164:"nombor E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak sah: dijangka ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombor";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak sah: dijangka ${V.stringifyPrimitive(i.values[0])}`;return`Pilihan tidak sah: dijangka salah satu daripada ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: dijangka ${i.origin??"nilai"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: dijangka ${i.origin??"nilai"} adalah ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: dijangka ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: dijangka ${i.origin} adalah ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak sah: mesti bermula dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak sah: mesti berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak sah: mesti mengandungi "${i.includes}"`;if("regex"===i.format)return`String tidak sah: mesti sepadan dengan corak ${i.pattern}`;return`${t[i.format]??i.format} tidak sah`;case"not_multiple_of":return`Nombor tidak sah: perlu gandaan ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kunci tidak sah dalam ${i.origin}`;case"invalid_union":default:return"Input tidak sah";case"invalid_element":return`Nilai tidak sah dalam ${i.origin}`}})}},"nl",0,function(){let e,t;return{localeError:(e={string:{unit:"tekens"},file:{unit:"bytes"},array:{unit:"elementen"},set:{unit:"elementen"}},t={regex:"invoer",email:"emailadres",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum en tijd",date:"ISO datum",time:"ISO tijd",duration:"ISO duur",ipv4:"IPv4-adres",ipv6:"IPv6-adres",cidrv4:"IPv4-bereik",cidrv6:"IPv6-bereik",base64:"base64-gecodeerde tekst",base64url:"base64 URL-gecodeerde tekst",json_string:"JSON string",e164:"E.164-nummer",jwt:"JWT",template_literal:"invoer"},i=>{switch(i.code){case"invalid_type":return`Ongeldige invoer: verwacht ${i.expected}, ontving ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"getal";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ongeldige invoer: verwacht ${V.stringifyPrimitive(i.values[0])}`;return`Ongeldige optie: verwacht \xe9\xe9n van ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} ${r.unit??"elementen"} bevat`;return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} is`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} ${r.unit} bevat`;return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} is`}case"invalid_format":if("starts_with"===i.format)return`Ongeldige tekst: moet met "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ongeldige tekst: moet op "${i.suffix}" eindigen`;if("includes"===i.format)return`Ongeldige tekst: moet "${i.includes}" bevatten`;if("regex"===i.format)return`Ongeldige tekst: moet overeenkomen met patroon ${i.pattern}`;return`Ongeldig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ongeldig getal: moet een veelvoud van ${i.divisor} zijn`;case"unrecognized_keys":return`Onbekende key${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ongeldige key in ${i.origin}`;case"invalid_union":default:return"Ongeldige invoer";case"invalid_element":return`Ongeldige waarde in ${i.origin}`}})}},"no",0,function(){let e,t;return{localeError:(e={string:{unit:"tegn",verb:"å ha"},file:{unit:"bytes",verb:"å ha"},array:{unit:"elementer",verb:"å inneholde"},set:{unit:"elementer",verb:"å inneholde"}},t={regex:"input",email:"e-postadresse",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO dato- og klokkeslett",date:"ISO-dato",time:"ISO-klokkeslett",duration:"ISO-varighet",ipv4:"IPv4-område",ipv6:"IPv6-område",cidrv4:"IPv4-spekter",cidrv6:"IPv6-spekter",base64:"base64-enkodet streng",base64url:"base64url-enkodet streng",json_string:"JSON-streng",e164:"E.164-nummer",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Ugyldig input: forventet ${i.expected}, fikk ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"tall";case"object":if(Array.isArray(e))return"liste";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ugyldig verdi: forventet ${V.stringifyPrimitive(i.values[0])}`;return`Ugyldig valg: forventet en av ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()} ${r.unit??"elementer"}`;return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()} ${r.unit}`;return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ugyldig streng: m\xe5 starte med "${i.prefix}"`;if("ends_with"===i.format)return`Ugyldig streng: m\xe5 ende med "${i.suffix}"`;if("includes"===i.format)return`Ugyldig streng: m\xe5 inneholde "${i.includes}"`;if("regex"===i.format)return`Ugyldig streng: m\xe5 matche m\xf8nsteret ${i.pattern}`;return`Ugyldig ${t[i.format]??i.format}`;case"not_multiple_of":return`Ugyldig tall: m\xe5 v\xe6re et multiplum av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Ukjente nøkler":"Ukjent nøkkel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ugyldig n\xf8kkel i ${i.origin}`;case"invalid_union":default:return"Ugyldig input";case"invalid_element":return`Ugyldig verdi i ${i.origin}`}})}},"ota",0,function(){let e,t;return{localeError:(e={string:{unit:"harf",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"unsur",verb:"olmalıdır"},set:{unit:"unsur",verb:"olmalıdır"}},t={regex:"giren",email:"epostagâh",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO hengâmı",date:"ISO tarihi",time:"ISO zamanı",duration:"ISO müddeti",ipv4:"IPv4 nişânı",ipv6:"IPv6 nişânı",cidrv4:"IPv4 menzili",cidrv6:"IPv6 menzili",base64:"base64-şifreli metin",base64url:"base64url-şifreli metin",json_string:"JSON metin",e164:"E.164 sayısı",jwt:"JWT",template_literal:"giren"},i=>{switch(i.code){case"invalid_type":return`F\xe2sit giren: umulan ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numara";case"object":if(Array.isArray(e))return"saf";if(null===e)return"gayb";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`F\xe2sit giren: umulan ${V.stringifyPrimitive(i.values[0])}`;return`F\xe2sit tercih: m\xfbteberler ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} ${r.unit??"elements"} sahip olmalıydı.`;return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} olmalıydı.`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} ${r.unit} sahip olmalıydı.`;return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} olmalıydı.`}case"invalid_format":if("starts_with"===i.format)return`F\xe2sit metin: "${i.prefix}" ile başlamalı.`;if("ends_with"===i.format)return`F\xe2sit metin: "${i.suffix}" ile bitmeli.`;if("includes"===i.format)return`F\xe2sit metin: "${i.includes}" ihtiv\xe2 etmeli.`;if("regex"===i.format)return`F\xe2sit metin: ${i.pattern} nakşına uymalı.`;return`F\xe2sit ${t[i.format]??i.format}`;case"not_multiple_of":return`F\xe2sit sayı: ${i.divisor} katı olmalıydı.`;case"unrecognized_keys":return`Tanınmayan anahtar ${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7in tanınmayan anahtar var.`;case"invalid_union":return"Giren tanınamadı.";case"invalid_element":return`${i.origin} i\xe7in tanınmayan kıymet var.`;default:return"Kıymet tanınamadı."}})}},"pl",0,function(){let e,t;return{localeError:(e={string:{unit:"znaków",verb:"mieć"},file:{unit:"bajtów",verb:"mieć"},array:{unit:"elementów",verb:"mieć"},set:{unit:"elementów",verb:"mieć"}},t={regex:"wyrażenie",email:"adres email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i godzina w formacie ISO",date:"data w formacie ISO",time:"godzina w formacie ISO",duration:"czas trwania ISO",ipv4:"adres IPv4",ipv6:"adres IPv6",cidrv4:"zakres IPv4",cidrv6:"zakres IPv6",base64:"ciąg znaków zakodowany w formacie base64",base64url:"ciąg znaków zakodowany w formacie base64url",json_string:"ciąg znaków w formacie JSON",e164:"liczba E.164",jwt:"JWT",template_literal:"wejście"},i=>{switch(i.code){case"invalid_type":return`Nieprawidłowe dane wejściowe: oczekiwano ${i.expected}, otrzymano ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"liczba";case"object":if(Array.isArray(e))return"tablica";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nieprawidłowe dane wejściowe: oczekiwano ${V.stringifyPrimitive(i.values[0])}`;return`Nieprawidłowa opcja: oczekiwano jednej z wartości ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Za duża wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.maximum.toString()} ${r.unit??"elementów"}`;return`Zbyt duż(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Za mała wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.minimum.toString()} ${r.unit??"elementów"}`;return`Zbyt mał(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zaczynać się od "${i.prefix}"`;if("ends_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi kończyć się na "${i.suffix}"`;if("includes"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zawierać "${i.includes}"`;if("regex"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi odpowiadać wzorcowi ${i.pattern}`;return`Nieprawidłow(y/a/e) ${t[i.format]??i.format}`;case"not_multiple_of":return`Nieprawidłowa liczba: musi być wielokrotnością ${i.divisor}`;case"unrecognized_keys":return`Nierozpoznane klucze${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Nieprawidłowy klucz w ${i.origin}`;case"invalid_union":default:return"Nieprawidłowe dane wejściowe";case"invalid_element":return`Nieprawidłowa wartość w ${i.origin}`}})}},"ps",0,function(){let e,t;return{localeError:(e={string:{unit:"توکي",verb:"ولري"},file:{unit:"بایټس",verb:"ولري"},array:{unit:"توکي",verb:"ولري"},set:{unit:"توکي",verb:"ولري"}},t={regex:"ورودي",email:"بریښنالیک",url:"یو آر ال",emoji:"ایموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"نیټه او وخت",date:"نېټه",time:"وخت",duration:"موده",ipv4:"د IPv4 پته",ipv6:"د IPv6 پته",cidrv4:"د IPv4 ساحه",cidrv6:"د IPv6 ساحه",base64:"base64-encoded متن",base64url:"base64url-encoded متن",json_string:"JSON متن",e164:"د E.164 شمېره",jwt:"JWT",template_literal:"ورودي"},i=>{switch(i.code){case"invalid_type":return`ناسم ورودي: باید ${i.expected} وای, مګر ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"ارې";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} ترلاسه شو`;case"invalid_value":if(1===i.values.length)return`ناسم ورودي: باید ${V.stringifyPrimitive(i.values[0])} وای`;return`ناسم انتخاب: باید یو له ${V.joinValues(i.values,"|")} څخه وای`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصرونه"} ولري`;return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} وي`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} ولري`;return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} وي`}case"invalid_format":if("starts_with"===i.format)return`ناسم متن: باید د "${i.prefix}" سره پیل شي`;if("ends_with"===i.format)return`ناسم متن: باید د "${i.suffix}" سره پای ته ورسيږي`;if("includes"===i.format)return`ناسم متن: باید "${i.includes}" ولري`;if("regex"===i.format)return`ناسم متن: باید د ${i.pattern} سره مطابقت ولري`;return`${t[i.format]??i.format} ناسم دی`;case"not_multiple_of":return`ناسم عدد: باید د ${i.divisor} مضرب وي`;case"unrecognized_keys":return`ناسم ${i.keys.length>1?"کلیډونه":"کلیډ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`ناسم کلیډ په ${i.origin} کې`;case"invalid_union":default:return"ناسمه ورودي";case"invalid_element":return`ناسم عنصر په ${i.origin} کې`}})}},"pt",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"ter"},file:{unit:"bytes",verb:"ter"},array:{unit:"itens",verb:"ter"},set:{unit:"itens",verb:"ter"}},t={regex:"padrão",email:"endereço de e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e hora ISO",date:"data ISO",time:"hora ISO",duration:"duração ISO",ipv4:"endereço IPv4",ipv6:"endereço IPv6",cidrv4:"faixa de IPv4",cidrv6:"faixa de IPv6",base64:"texto codificado em base64",base64url:"URL codificada em base64",json_string:"texto JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipo inv\xe1lido: esperado ${i.expected}, recebido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"array";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: esperado ${V.stringifyPrimitive(i.values[0])}`;return`Op\xe7\xe3o inv\xe1lida: esperada uma das ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Muito grande: esperado que ${i.origin??"valor"} tivesse ${t}${i.maximum.toString()} ${r.unit??"elementos"}`;return`Muito grande: esperado que ${i.origin??"valor"} fosse ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Muito pequeno: esperado que ${i.origin} tivesse ${t}${i.minimum.toString()} ${r.unit}`;return`Muito pequeno: esperado que ${i.origin} fosse ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Texto inv\xe1lido: deve come\xe7ar com "${i.prefix}"`;if("ends_with"===i.format)return`Texto inv\xe1lido: deve terminar com "${i.suffix}"`;if("includes"===i.format)return`Texto inv\xe1lido: deve incluir "${i.includes}"`;if("regex"===i.format)return`Texto inv\xe1lido: deve corresponder ao padr\xe3o ${i.pattern}`;return`${t[i.format]??i.format} inv\xe1lido`;case"not_multiple_of":return`N\xfamero inv\xe1lido: deve ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Chave${i.keys.length>1?"s":""} desconhecida${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Chave inv\xe1lida em ${i.origin}`;case"invalid_union":return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido em ${i.origin}`;default:return"Campo inválido"}})}},"ru",0,function(){let e,t;return{localeError:(e={string:{unit:{one:"символ",few:"символа",many:"символов"},verb:"иметь"},file:{unit:{one:"байт",few:"байта",many:"байт"},verb:"иметь"},array:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"},set:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"}},t={regex:"ввод",email:"email адрес",url:"URL",emoji:"эмодзи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата и время",date:"ISO дата",time:"ISO время",duration:"ISO длительность",ipv4:"IPv4 адрес",ipv6:"IPv6 адрес",cidrv4:"IPv4 диапазон",cidrv6:"IPv6 диапазон",base64:"строка в формате base64",base64url:"строка в формате base64url",json_string:"JSON строка",e164:"номер E.164",jwt:"JWT",template_literal:"ввод"},i=>{switch(i.code){case"invalid_type":return`Неверный ввод: ожидалось ${i.expected}, получено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"массив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неверный ввод: ожидалось ${V.stringifyPrimitive(i.values[0])}`;return`Неверный вариант: ожидалось одно из ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r){let e=tA(Number(i.maximum),r.unit.one,r.unit.few,r.unit.many);return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет иметь ${t}${i.maximum.toString()} ${e}`}return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r){let e=tA(Number(i.minimum),r.unit.one,r.unit.few,r.unit.many);return`Слишком маленькое значение: ожидалось, что ${i.origin} будет иметь ${t}${i.minimum.toString()} ${e}`}return`Слишком маленькое значение: ожидалось, что ${i.origin} будет ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неверная строка: должна начинаться с "${i.prefix}"`;if("ends_with"===i.format)return`Неверная строка: должна заканчиваться на "${i.suffix}"`;if("includes"===i.format)return`Неверная строка: должна содержать "${i.includes}"`;if("regex"===i.format)return`Неверная строка: должна соответствовать шаблону ${i.pattern}`;return`Неверный ${t[i.format]??i.format}`;case"not_multiple_of":return`Неверное число: должно быть кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспознанн${i.keys.length>1?"ые":"ый"} ключ${i.keys.length>1?"и":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Неверный ключ в ${i.origin}`;case"invalid_union":default:return"Неверные входные данные";case"invalid_element":return`Неверное значение в ${i.origin}`}})}},"sl",0,function(){let e,t;return{localeError:(e={string:{unit:"znakov",verb:"imeti"},file:{unit:"bajtov",verb:"imeti"},array:{unit:"elementov",verb:"imeti"},set:{unit:"elementov",verb:"imeti"}},t={regex:"vnos",email:"e-poštni naslov",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum in čas",date:"ISO datum",time:"ISO čas",duration:"ISO trajanje",ipv4:"IPv4 naslov",ipv6:"IPv6 naslov",cidrv4:"obseg IPv4",cidrv6:"obseg IPv6",base64:"base64 kodiran niz",base64url:"base64url kodiran niz",json_string:"JSON niz",e164:"E.164 številka",jwt:"JWT",template_literal:"vnos"},i=>{switch(i.code){case"invalid_type":return`Neveljaven vnos: pričakovano ${i.expected}, prejeto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"število";case"object":if(Array.isArray(e))return"tabela";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neveljaven vnos: pričakovano ${V.stringifyPrimitive(i.values[0])}`;return`Neveljavna možnost: pričakovano eno izmed ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} imelo ${t}${i.maximum.toString()} ${r.unit??"elementov"}`;return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Premajhno: pričakovano, da bo ${i.origin} imelo ${t}${i.minimum.toString()} ${r.unit}`;return`Premajhno: pričakovano, da bo ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neveljaven niz: mora se začeti z "${i.prefix}"`;if("ends_with"===i.format)return`Neveljaven niz: mora se končati z "${i.suffix}"`;if("includes"===i.format)return`Neveljaven niz: mora vsebovati "${i.includes}"`;if("regex"===i.format)return`Neveljaven niz: mora ustrezati vzorcu ${i.pattern}`;return`Neveljaven ${t[i.format]??i.format}`;case"not_multiple_of":return`Neveljavno število: mora biti večkratnik ${i.divisor}`;case"unrecognized_keys":return`Neprepoznan${i.keys.length>1?"i ključi":" ključ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Neveljaven ključ v ${i.origin}`;case"invalid_union":default:return"Neveljaven vnos";case"invalid_element":return`Neveljavna vrednost v ${i.origin}`}})}},"sv",0,function(){let e,t;return{localeError:(e={string:{unit:"tecken",verb:"att ha"},file:{unit:"bytes",verb:"att ha"},array:{unit:"objekt",verb:"att innehålla"},set:{unit:"objekt",verb:"att innehålla"}},t={regex:"reguljärt uttryck",email:"e-postadress",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datum och tid",date:"ISO-datum",time:"ISO-tid",duration:"ISO-varaktighet",ipv4:"IPv4-intervall",ipv6:"IPv6-intervall",cidrv4:"IPv4-spektrum",cidrv6:"IPv6-spektrum",base64:"base64-kodad sträng",base64url:"base64url-kodad sträng",json_string:"JSON-sträng",e164:"E.164-nummer",jwt:"JWT",template_literal:"mall-literal"},i=>{switch(i.code){case"invalid_type":return`Ogiltig inmatning: f\xf6rv\xe4ntat ${i.expected}, fick ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"antal";case"object":if(Array.isArray(e))return"lista";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ogiltig inmatning: f\xf6rv\xe4ntat ${V.stringifyPrimitive(i.values[0])}`;return`Ogiltigt val: f\xf6rv\xe4ntade en av ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`F\xf6r stor(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()} ${r.unit??"element"}`;return`F\xf6r stor(t): f\xf6rv\xe4ntat ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()} ${r.unit}`;return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste b\xf6rja med "${i.prefix}"`;if("ends_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste sluta med "${i.suffix}"`;if("includes"===i.format)return`Ogiltig str\xe4ng: m\xe5ste inneh\xe5lla "${i.includes}"`;if("regex"===i.format)return`Ogiltig str\xe4ng: m\xe5ste matcha m\xf6nstret "${i.pattern}"`;return`Ogiltig(t) ${t[i.format]??i.format}`;case"not_multiple_of":return`Ogiltigt tal: m\xe5ste vara en multipel av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Okända nycklar":"Okänd nyckel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ogiltig nyckel i ${i.origin??"värdet"}`;case"invalid_union":default:return"Ogiltig input";case"invalid_element":return`Ogiltigt v\xe4rde i ${i.origin??"värdet"}`}})}},"ta",0,function(){let e,t;return{localeError:(e={string:{unit:"எழுத்துக்கள்",verb:"கொண்டிருக்க வேண்டும்"},file:{unit:"பைட்டுகள்",verb:"கொண்டிருக்க வேண்டும்"},array:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"},set:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"}},t={regex:"உள்ளீடு",email:"மின்னஞ்சல் முகவரி",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO தேதி நேரம்",date:"ISO தேதி",time:"ISO நேரம்",duration:"ISO கால அளவு",ipv4:"IPv4 முகவரி",ipv6:"IPv6 முகவரி",cidrv4:"IPv4 வரம்பு",cidrv6:"IPv6 வரம்பு",base64:"base64-encoded சரம்",base64url:"base64url-encoded சரம்",json_string:"JSON சரம்",e164:"E.164 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t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ${r.unit} ஆக இருக்க வேண்டும்`;return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ஆக இருக்க வேண்டும்`}case"invalid_format":if("starts_with"===i.format)return`தவறான சரம்: "${i.prefix}" இல் தொடங்க வேண்டும்`;if("ends_with"===i.format)return`தவறான சரம்: "${i.suffix}" இல் முடிவடைய வேண்டும்`;if("includes"===i.format)return`தவறான சரம்: "${i.includes}" ஐ உள்ளடக்க வேண்டும்`;if("regex"===i.format)return`தவறான சரம்: ${i.pattern} முறைபாட்டுடன் பொருந்த வேண்டும்`;return`தவறான ${t[i.format]??i.format}`;case"not_multiple_of":return`தவறான எண்: ${i.divisor} இன் பலமாக இருக்க வேண்டும்`;case"unrecognized_keys":return`அடையாளம் தெரியாத விசை${i.keys.length>1?"கள்":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} இல் தவறான விசை`;case"invalid_union":default:return"தவறான உள்ளீடு";case"invalid_element":return`${i.origin} இல் தவறான மதிப்பு`}})}},"th",0,function(){let e,t;return{localeError:(e={string:{unit:"ตัวอักษร",verb:"ควรมี"},file:{unit:"ไบต์",verb:"ควรมี"},array:{unit:"รายการ",verb:"ควรมี"},set:{unit:"รายการ",verb:"ควรมี"}},t={regex:"ข้อมูลที่ป้อน",email:"ที่อยู่อีเมล",url:"URL",emoji:"อิโมจิ",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"วันที่เวลาแบบ ISO",date:"วันที่แบบ ISO",time:"เวลาแบบ ISO",duration:"ช่วงเวลาแบบ ISO",ipv4:"ที่อยู่ IPv4",ipv6:"ที่อยู่ IPv6",cidrv4:"ช่วง IP แบบ IPv4",cidrv6:"ช่วง IP แบบ IPv6",base64:"ข้อความแบบ Base64",base64url:"ข้อความแบบ Base64 สำหรับ URL",json_string:"ข้อความแบบ JSON",e164:"เบอร์โทรศัพท์ระหว่างประเทศ (E.164)",jwt:"โทเคน JWT",template_literal:"ข้อมูลที่ป้อน"},i=>{switch(i.code){case"invalid_type":return`ประเภทข้อมูลไม่ถูกต้อง: ควรเป็น ${i.expected} แต่ได้รับ ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"ไม่ใช่ตัวเลข 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"${i.prefix}"`;if("ends_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องลงท้ายด้วย "${i.suffix}"`;if("includes"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องมี "${i.includes}" อยู่ในข้อความ`;if("regex"===i.format)return`รูปแบบไม่ถูกต้อง: ต้องตรงกับรูปแบบที่กำหนด ${i.pattern}`;return`รูปแบบไม่ถูกต้อง: ${t[i.format]??i.format}`;case"not_multiple_of":return`ตัวเลขไม่ถูกต้อง: ต้องเป็นจำนวนที่หารด้วย ${i.divisor} ได้ลงตัว`;case"unrecognized_keys":return`พบคีย์ที่ไม่รู้จัก: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`คีย์ไม่ถูกต้องใน ${i.origin}`;case"invalid_union":return"ข้อมูลไม่ถูกต้อง: ไม่ตรงกับรูปแบบยูเนียนที่กำหนดไว้";case"invalid_element":return`ข้อมูลไม่ถูกต้องใน ${i.origin}`;default:return"ข้อมูลไม่ถูกต้อง"}})}},"tr",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"olmalı"},file:{unit:"bayt",verb:"olmalı"},array:{unit:"öğe",verb:"olmalı"},set:{unit:"öğe",verb:"olmalı"}},t={regex:"girdi",email:"e-posta adresi",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO tarih ve saat",date:"ISO tarih",time:"ISO saat",duration:"ISO süre",ipv4:"IPv4 adresi",ipv6:"IPv6 adresi",cidrv4:"IPv4 aralığı",cidrv6:"IPv6 aralığı",base64:"base64 ile şifrelenmiş metin",base64url:"base64url ile şifrelenmiş metin",json_string:"JSON dizesi",e164:"E.164 sayısı",jwt:"JWT",template_literal:"Şablon dizesi"},i=>{switch(i.code){case"invalid_type":return`Ge\xe7ersiz değer: beklenen ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ge\xe7ersiz değer: beklenen ${V.stringifyPrimitive(i.values[0])}`;return`Ge\xe7ersiz se\xe7enek: aşağıdakilerden biri olmalı: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()} ${r.unit??"öğe"}`;return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ge\xe7ersiz metin: "${i.prefix}" ile başlamalı`;if("ends_with"===i.format)return`Ge\xe7ersiz metin: "${i.suffix}" ile bitmeli`;if("includes"===i.format)return`Ge\xe7ersiz metin: "${i.includes}" i\xe7ermeli`;if("regex"===i.format)return`Ge\xe7ersiz metin: ${i.pattern} desenine uymalı`;return`Ge\xe7ersiz ${t[i.format]??i.format}`;case"not_multiple_of":return`Ge\xe7ersiz sayı: ${i.divisor} ile tam b\xf6l\xfcnebilmeli`;case"unrecognized_keys":return`Tanınmayan anahtar${i.keys.length>1?"lar":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7inde ge\xe7ersiz anahtar`;case"invalid_union":default:return"Geçersiz değer";case"invalid_element":return`${i.origin} i\xe7inde ge\xe7ersiz değer`}})}},"ua",0,function(){let e,t;return{localeError:(e={string:{unit:"символів",verb:"матиме"},file:{unit:"байтів",verb:"матиме"},array:{unit:"елементів",verb:"матиме"},set:{unit:"елементів",verb:"матиме"}},t={regex:"вхідні дані",email:"адреса електронної пошти",url:"URL",emoji:"емодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"дата та час ISO",date:"дата ISO",time:"час ISO",duration:"тривалість ISO",ipv4:"адреса IPv4",ipv6:"адреса IPv6",cidrv4:"діапазон IPv4",cidrv6:"діапазон IPv6",base64:"рядок у кодуванні base64",base64url:"рядок у кодуванні base64url",json_string:"рядок JSON",e164:"номер E.164",jwt:"JWT",template_literal:"вхідні дані"},i=>{switch(i.code){case"invalid_type":return`Неправильні вхідні дані: очікується ${i.expected}, отримано ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"масив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неправильні вхідні дані: очікується ${V.stringifyPrimitive(i.values[0])}`;return`Неправильна опція: очікується одне з ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Занадто велике: очікується, що ${i.origin??"значення"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"елементів"}`;return`Занадто велике: очікується, що ${i.origin??"значення"} буде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Занадто мале: очікується, що ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Занадто мале: очікується, що ${i.origin} буде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неправильний рядок: повинен починатися з "${i.prefix}"`;if("ends_with"===i.format)return`Неправильний рядок: повинен закінчуватися на "${i.suffix}"`;if("includes"===i.format)return`Неправильний рядок: повинен містити "${i.includes}"`;if("regex"===i.format)return`Неправильний рядок: повинен відповідати шаблону ${i.pattern}`;return`Неправильний ${t[i.format]??i.format}`;case"not_multiple_of":return`Неправильне число: повинно бути кратним ${i.divisor}`;case"unrecognized_keys":return`Нерозпізнаний ключ${i.keys.length>1?"і":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Неправильний ключ у ${i.origin}`;case"invalid_union":default:return"Неправильні вхідні дані";case"invalid_element":return`Неправильне значення у ${i.origin}`}})}},"ur",0,function(){let e,t;return{localeError:(e={string:{unit:"حروف",verb:"ہونا"},file:{unit:"بائٹس",verb:"ہونا"},array:{unit:"آئٹمز",verb:"ہونا"},set:{unit:"آئٹمز",verb:"ہونا"}},t={regex:"ان پٹ",email:"ای میل ایڈریس",url:"یو آر ایل",emoji:"ایموجی",uuid:"یو یو آئی ڈی",uuidv4:"یو یو آئی ڈی وی 4",uuidv6:"یو یو آئی ڈی وی 6",nanoid:"نینو آئی ڈی",guid:"جی یو آئی ڈی",cuid:"سی یو آئی ڈی",cuid2:"سی یو آئی ڈی 2",ulid:"یو ایل آئی ڈی",xid:"ایکس آئی ڈی",ksuid:"کے ایس یو آئی ڈی",datetime:"آئی ایس او ڈیٹ ٹائم",date:"آئی ایس او تاریخ",time:"آئی ایس او وقت",duration:"آئی ایس او مدت",ipv4:"آئی پی وی 4 ایڈریس",ipv6:"آئی پی وی 6 ایڈریس",cidrv4:"آئی پی وی 4 رینج",cidrv6:"آئی پی وی 6 رینج",base64:"بیس 64 ان کوڈڈ سٹرنگ",base64url:"بیس 64 یو آر ایل ان کوڈڈ سٹرنگ",json_string:"جے ایس او این سٹرنگ",e164:"ای 164 نمبر",jwt:"جے ڈبلیو ٹی",template_literal:"ان پٹ"},i=>{switch(i.code){case"invalid_type":return`غلط ان پٹ: ${i.expected} متوقع تھا، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"نمبر";case"object":if(Array.isArray(e))return"آرے";if(null===e)return"نل";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} موصول ہوا`;case"invalid_value":if(1===i.values.length)return`غلط ان پٹ: ${V.stringifyPrimitive(i.values[0])} متوقع تھا`;return`غلط آپشن: ${V.joinValues(i.values,"|")} میں سے ایک متوقع تھا`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`بہت بڑا: ${i.origin??"ویلیو"} کے ${t}${i.maximum.toString()} ${r.unit??"عناصر"} ہونے متوقع تھے`;return`بہت بڑا: ${i.origin??"ویلیو"} کا ${t}${i.maximum.toString()} ہونا متوقع تھا`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`بہت چھوٹا: ${i.origin} کے ${t}${i.minimum.toString()} ${r.unit} ہونے متوقع تھے`;return`بہت چھوٹا: ${i.origin} کا ${t}${i.minimum.toString()} ہونا متوقع تھا`}case"invalid_format":if("starts_with"===i.format)return`غلط سٹرنگ: "${i.prefix}" سے شروع ہونا چاہیے`;if("ends_with"===i.format)return`غلط سٹرنگ: "${i.suffix}" پر ختم ہونا چاہیے`;if("includes"===i.format)return`غلط سٹرنگ: "${i.includes}" شامل ہونا چاہیے`;if("regex"===i.format)return`غلط سٹرنگ: پیٹرن ${i.pattern} سے میچ ہونا چاہیے`;return`غلط ${t[i.format]??i.format}`;case"not_multiple_of":return`غلط نمبر: ${i.divisor} کا مضاعف ہونا چاہیے`;case"unrecognized_keys":return`غیر تسلیم شدہ کی${i.keys.length>1?"ز":""}: ${V.joinValues(i.keys,"، ")}`;case"invalid_key":return`${i.origin} میں غلط کی`;case"invalid_union":default:return"غلط ان پٹ";case"invalid_element":return`${i.origin} میں غلط ویلیو`}})}},"vi",0,function(){let e,t;return{localeError:(e={string:{unit:"ký tự",verb:"có"},file:{unit:"byte",verb:"có"},array:{unit:"phần tử",verb:"có"},set:{unit:"phần tử",verb:"có"}},t={regex:"đầu vào",email:"địa chỉ email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ngày giờ ISO",date:"ngày ISO",time:"giờ ISO",duration:"khoảng thời gian ISO",ipv4:"địa chỉ IPv4",ipv6:"địa chỉ IPv6",cidrv4:"dải IPv4",cidrv6:"dải IPv6",base64:"chuỗi mã hóa base64",base64url:"chuỗi mã hóa base64url",json_string:"chuỗi JSON",e164:"số E.164",jwt:"JWT",template_literal:"đầu vào"},i=>{switch(i.code){case"invalid_type":return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi ${i.expected}, nhận được ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"số";case"object":if(Array.isArray(e))return"mảng";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Đầu v\xe0o kh\xf4ng hợp lệ: mong đợi ${V.stringifyPrimitive(i.values[0])}`;return`T\xf9y chọn kh\xf4ng hợp lệ: mong đợi một trong c\xe1c gi\xe1 trị ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Qu\xe1 lớn: mong đợi ${i.origin??"giá trị"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"phần tử"}`;return`Qu\xe1 lớn: mong đợi ${i.origin??"giá trị"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Qu\xe1 nhỏ: mong đợi ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Qu\xe1 nhỏ: mong đợi ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải bắt đầu bằng "${i.prefix}"`;if("ends_with"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải kết th\xfac bằng "${i.suffix}"`;if("includes"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải bao gồm "${i.includes}"`;if("regex"===i.format)return`Chuỗi kh\xf4ng hợp lệ: phải khớp với mẫu ${i.pattern}`;return`${t[i.format]??i.format} kh\xf4ng hợp lệ`;case"not_multiple_of":return`Số kh\xf4ng hợp lệ: phải l\xe0 bội số của ${i.divisor}`;case"unrecognized_keys":return`Kh\xf3a kh\xf4ng được nhận dạng: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kh\xf3a kh\xf4ng hợp lệ trong ${i.origin}`;case"invalid_union":default:return"Đầu vào không hợp lệ";case"invalid_element":return`Gi\xe1 trị kh\xf4ng hợp lệ trong ${i.origin}`}})}},"zhCN",0,function(){let e,t;return{localeError:(e={string:{unit:"字符",verb:"包含"},file:{unit:"字节",verb:"包含"},array:{unit:"项",verb:"包含"},set:{unit:"项",verb:"包含"}},t={regex:"输入",email:"电子邮件",url:"URL",emoji:"表情符号",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日期时间",date:"ISO日期",time:"ISO时间",duration:"ISO时长",ipv4:"IPv4地址",ipv6:"IPv6地址",cidrv4:"IPv4网段",cidrv6:"IPv6网段",base64:"base64编码字符串",base64url:"base64url编码字符串",json_string:"JSON字符串",e164:"E.164号码",jwt:"JWT",template_literal:"输入"},i=>{switch(i.code){case"invalid_type":return`无效输入：期望 ${i.expected}，实际接收 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"非数字(NaN)":"数字";case"object":if(Array.isArray(e))return"数组";if(null===e)return"空值(null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`无效输入：期望 ${V.stringifyPrimitive(i.values[0])}`;return`无效选项：期望以下之一 ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`数值过大：期望 ${i.origin??"值"} ${t}${i.maximum.toString()} ${r.unit??"个元素"}`;return`数值过大：期望 ${i.origin??"值"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`数值过小：期望 ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`数值过小：期望 ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`无效字符串：必须以 "${i.prefix}" 开头`;if("ends_with"===i.format)return`无效字符串：必须以 "${i.suffix}" 结尾`;if("includes"===i.format)return`无效字符串：必须包含 "${i.includes}"`;if("regex"===i.format)return`无效字符串：必须满足正则表达式 ${i.pattern}`;return`无效${t[i.format]??i.format}`;case"not_multiple_of":return`无效数字：必须是 ${i.divisor} 的倍数`;case"unrecognized_keys":return`出现未知的键(key): ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} 中的键(key)无效`;case"invalid_union":default:return"无效输入";case"invalid_element":return`${i.origin} 中包含无效值(value)`}})}},"zhTW",0,function(){let e,t;return{localeError:(e={string:{unit:"字元",verb:"擁有"},file:{unit:"位元組",verb:"擁有"},array:{unit:"項目",verb:"擁有"},set:{unit:"項目",verb:"擁有"}},t={regex:"輸入",email:"郵件地址",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 日期時間",date:"ISO 日期",time:"ISO 時間",duration:"ISO 期間",ipv4:"IPv4 位址",ipv6:"IPv6 位址",cidrv4:"IPv4 範圍",cidrv6:"IPv6 範圍",base64:"base64 編碼字串",base64url:"base64url 編碼字串",json_string:"JSON 字串",e164:"E.164 數值",jwt:"JWT",template_literal:"輸入"},i=>{switch(i.code){case"invalid_type":return`無效的輸入值：預期為 ${i.expected}，但收到 ${(e=>{let t=typeof e;switch(t){case"number":return 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i,{apiKeySource:s,accessToken:n,apiKey:a,inputMessage:r,chatHistory:o,selectedTags:l,selectedVectorStores:d,selectedGuardrails:c,selectedPolicies:u,selectedVoice:p,endpointType:m,selectedModel:g,selectedSdk:h,proxySettings:f}=e,x="session"===s?n:a,b=window.location.origin,v=f?.LITELLM_UI_API_DOC_BASE_URL;v&&v.trim()?b=v:f?.PROXY_BASE_URL&&(b=f.PROXY_BASE_URL);let y=r||"Your prompt here",j=y.replace(/\\/g,"\\\\").replace(/"/g,'\\"').replace(/\n/g,"\\n"),_=o.filter(e=>!e.isImage).map(({role:e,content:t})=>({role:e,content:t})),w={};l.length>0&&(w.tags=l),d.length>0&&(w.vector_stores=d),c.length>0&&(w.guardrails=c),u.length>0&&(w.policies=u);let k=g||"your-model-name",N="azure"===h?`import openai + +client = openai.AzureOpenAI( + api_key="${x||"YOUR_LITELLM_API_KEY"}", + azure_endpoint="${b}", + api_version="2024-02-01" +)`:`import openai + +client = openai.OpenAI( + api_key="${x||"YOUR_LITELLM_API_KEY"}", + base_url="${b}" +)`;switch(m){case t.EndpointType.CHAT:{let e=Object.keys(w).length>0,t="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let s=_.length>0?_:[{role:"user",content:y}];i=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.chat.completions.create( + model="${k}", + messages=${JSON.stringify(s,null,4)}${t} +) + +print(response) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.chat.completions.create( +# model="${k}", +# messages=[ +# { +# "role": "user", +# "content": [ +# { +# "type": "text", +# "text": "${j}" +# }, +# { +# "type": "image_url", +# "image_url": { +# "url": f"data:image/jpeg;base64,{base64_file}" # or data:application/pdf;base64,{base64_file} +# } +# } +# ] +# } +# ]${t} +# ) +# print(response_with_file) +`;break}case t.EndpointType.RESPONSES:{let e=Object.keys(w).length>0,t="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let s=_.length>0?_:[{role:"user",content:y}];i=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.responses.create( + model="${k}", + input=${JSON.stringify(s,null,4)}${t} +) + +print(response.output_text) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.responses.create( +# model="${k}", +# input=[ +# { +# "role": "user", +# "content": [ +# {"type": "input_text", "text": "${j}"}, +# { +# "type": "input_image", +# "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} +# }, +# ], +# } +# ]${t} +# ) +# print(response_with_file.output_text) +`;break}case t.EndpointType.IMAGE:i="azure"===h?` +# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. +# This snippet uses 'client.images.generate' and will create a new image based on your prompt. +# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. +import os +import requests +import json +import time +from PIL import Image + +result = client.images.generate( + model="${k}", + prompt="${r}", + n=1 +) + +json_response = json.loads(result.model_dump_json()) + +# Set the directory for the stored image +image_dir = os.path.join(os.curdir, 'images') + +# If the directory doesn't exist, create it +if not os.path.isdir(image_dir): + os.mkdir(image_dir) + +# Initialize the image path +image_filename = f"generated_image_{int(time.time())}.png" +image_path = os.path.join(image_dir, image_filename) + +try: + # Retrieve the generated image + if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): + image_url = json_response["data"][0]["url"] + generated_image = requests.get(image_url).content + with open(image_path, "wb") as image_file: + image_file.write(generated_image) + + print(f"Image saved to {image_path}") + # Display the image + image = Image.open(image_path) + image.show() + else: + print("Could not find image URL in response.") + print("Full response:", json_response) +except Exception as e: + print(f"An error occurred: {e}") + print("Full response:", json_response) +`:` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${j}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${k}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.IMAGE_EDITS:i="azure"===h?` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# The prompt entered by the user +prompt = "${j}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${k}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`:` +import base64 +import os +import time + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${j}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${k}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.EMBEDDINGS:i=` +response = client.embeddings.create( + input="${r||"Your string here"}", + model="${k}", + encoding_format="base64" # or "float" +) + +print(response.data[0].embedding) +`;break;case t.EndpointType.TRANSCRIPTION:i=` +# Open the audio file +audio_file = open("path/to/your/audio/file.mp3", "rb") + +# Make the transcription request +response = client.audio.transcriptions.create( + model="${k}", + file=audio_file${r?`, + prompt="${r.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""} +) + +print(response.text) +`;break;case t.EndpointType.SPEECH:i=` +# Make the text-to-speech request +response = client.audio.speech.create( + model="${k}", + input="${r||"Your text to convert to speech here"}", + voice="${p}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer +) + 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this.poll(e,s.id,r)}listFiles(e,t,r={},s){return tv(r)?this.listFiles(e,t,{},r):this._client.getAPIList(`/vector_stores/${e}/file_batches/${t}/files`,rf,{query:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}async poll(e,t,r){let s={...r?.headers,"X-Stainless-Poll-Helper":"true"};for(r?.pollIntervalMs&&(s["X-Stainless-Custom-Poll-Interval"]=r.pollIntervalMs.toString());;){let{data:n,response:i}=await this.retrieve(e,t,{...r,headers:s}).withResponse();switch(n.status){case"in_progress":let a=5e3;if(r?.pollIntervalMs)a=r.pollIntervalMs;else{let e=i.headers.get("openai-poll-after-ms");if(e){let t=parseInt(e);isNaN(t)||(a=t)}}await tI(a);break;case"failed":case"cancelled":case"completed":return n}}}async uploadAndPoll(e,{files:t,fileIds:r=[]},s){if(null==t||0==t.length)throw Error("No `files` provided to process. 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tv(e)?this.list({},e):this._client.getAPIList("/vector_stores",rg,{query:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}del(e,t){return this._client.delete(`/vector_stores/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}search(e,t,r){return this._client.getAPIList(`/vector_stores/${e}/search`,ry,{body:t,method:"post",...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}}class rg extends tX{}class ry extends tq{}rm.VectorStoresPage=rg,rm.VectorStoreSearchResponsesPage=ry,rm.Files=rh,rm.VectorStoreFilesPage=rf,rm.FileContentResponsesPage=rd,rm.FileBatches=rp;class rw extends tD{create(e,t){return this._client.post("/assistants",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}retrieve(e,t){return this._client.get(`/assistants/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}update(e,t,r){return this._client.post(`/assistants/${e}`,{body:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}list(e={},t){return tv(e)?this.list({},e):this._client.getAPIList("/assistants",rb,{query:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}del(e,t){return this._client.delete(`/assistants/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}}class rb extends tX{}function r_(e){return"function"==typeof e.parse}rw.AssistantsPage=rb;let rv=e=>e?.role==="assistant",rx=e=>e?.role==="function",rA=e=>e?.role==="tool";var rS=function(e,t,r,s,n){if("m"===s)throw TypeError("Private method is not writable");if("a"===s&&!n)throw TypeError("Private accessor was defined without a setter");if("function"==typeof t?e!==t||!n:!t.has(e))throw TypeError("Cannot write private member to an object whose class did not declare it");return"a"===s?n.call(e,r):n?n.value=r:t.set(e,r),r},rE=function(e,t,r,s){if("a"===r&&!s)throw TypeError("Private accessor was defined without a 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rE(this,A,"f")}abort(){this.controller.abort()}on(e,t){return(rE(this,_,"f")[e]||(rE(this,_,"f")[e]=[])).push({listener:t}),this}off(e,t){let r=rE(this,_,"f")[e];if(!r)return this;let s=r.findIndex(e=>e.listener===t);return s>=0&&r.splice(s,1),this}once(e,t){return(rE(this,_,"f")[e]||(rE(this,_,"f")[e]=[])).push({listener:t,once:!0}),this}emitted(e){return new Promise((t,r)=>{rS(this,S,!0,"f"),"error"!==e&&this.once("error",r),this.once(e,t)})}async done(){rS(this,S,!0,"f"),await rE(this,y,"f")}_emit(e,...t){if(rE(this,v,"f"))return;"end"===e&&(rS(this,v,!0,"f"),rE(this,w,"f").call(this));let r=rE(this,_,"f")[e];if(r&&(rE(this,_,"f")[e]=r.filter(e=>!e.once),r.forEach(({listener:e})=>e(...t))),"abort"===e){let e=t[0];rE(this,S,"f")||r?.length||Promise.reject(e),rE(this,g,"f").call(this,e),rE(this,b,"f").call(this,e),this._emit("end");return}if("error"===e){let e=t[0];rE(this,S,"f")||r?.length||Promise.reject(e),rE(this,g,"f").call(this,e),rE(this,b,"f").call(this,e),this._emit("end")}}_emitFinal(){}}function rR(e){return e?.$brand==="auto-parseable-response-format"}function rI(e){return e?.$brand==="auto-parseable-tool"}function r$(e,t){let r=e.choices.map(e=>{var r,s;if("length"===e.finish_reason)throw new e0;if("content_filter"===e.finish_reason)throw new e1;return{...e,message:{...e.message,...e.message.tool_calls?{tool_calls:e.message.tool_calls?.map(e=>{var r,s;let n;return r=t,s=e,n=r.tools?.find(e=>e.function?.name===s.function.name),{...s,function:{...s.function,parsed_arguments:rI(n)?n.$parseRaw(s.function.arguments):n?.function.strict?JSON.parse(s.function.arguments):null}}})??void 0}:void 0,parsed:e.message.content&&!e.message.refusal?(r=t,s=e.message.content,r.response_format?.type!=="json_schema"?null:r.response_format?.type==="json_schema"?"$parseRaw"in r.response_format?r.response_format.$parseRaw(s):JSON.parse(s):null):null}}});return{...e,choices:r}}function rO(e){return!!rR(e.response_format)||(e.tools?.some(e=>rI(e)||"function"===e.type&&!0===e.function.strict)??!1)}p=new WeakMap,m=new WeakMap,g=new WeakMap,y=new WeakMap,w=new WeakMap,b=new WeakMap,_=new WeakMap,v=new WeakMap,x=new WeakMap,A=new WeakMap,S=new WeakMap,d=new WeakSet,E=function(e){if(rS(this,x,!0,"f"),e instanceof Error&&"AbortError"===e.name&&(e=new eq),e instanceof eq)return rS(this,A,!0,"f"),this._emit("abort",e);if(e instanceof eF)return this._emit("error",e);if(e instanceof Error){let t=new eF(e.message);return t.cause=e,this._emit("error",t)}return this._emit("error",new eF(String(e)))};var rC=function(e,t,r,s){if("a"===r&&!s)throw TypeError("Private accessor was defined without a getter");if("function"==typeof t?e!==t||!s:!t.has(e))throw TypeError("Cannot read private member from an object whose class did not declare it");return"m"===r?s:"a"===r?s.call(e):s?s.value:t.get(e)};class rk extends rP{constructor(){super(...arguments),P.add(this),this._chatCompletions=[],this.messages=[]}_addChatCompletion(e){this._chatCompletions.push(e),this._emit("chatCompletion",e);let t=e.choices[0]?.message;return t&&this._addMessage(t),e}_addMessage(e,t=!0){if("content"in e||(e.content=null),this.messages.push(e),t){if(this._emit("message",e),(rx(e)||rA(e))&&e.content)this._emit("functionCallResult",e.content);else if(rv(e)&&e.function_call)this._emit("functionCall",e.function_call);else if(rv(e)&&e.tool_calls)for(let t of e.tool_calls)"function"===t.type&&this._emit("functionCall",t.function)}}async finalChatCompletion(){await this.done();let e=this._chatCompletions[this._chatCompletions.length-1];if(!e)throw new eF("stream ended without producing a ChatCompletion");return e}async finalContent(){return await this.done(),rC(this,P,"m",R).call(this)}async finalMessage(){return await this.done(),rC(this,P,"m",I).call(this)}async finalFunctionCall(){return await this.done(),rC(this,P,"m",$).call(this)}async finalFunctionCallResult(){return await this.done(),rC(this,P,"m",O).call(this)}async totalUsage(){return await this.done(),rC(this,P,"m",C).call(this)}allChatCompletions(){return[...this._chatCompletions]}_emitFinal(){let e=this._chatCompletions[this._chatCompletions.length-1];e&&this._emit("finalChatCompletion",e);let t=rC(this,P,"m",I).call(this);t&&this._emit("finalMessage",t);let r=rC(this,P,"m",R).call(this);r&&this._emit("finalContent",r);let s=rC(this,P,"m",$).call(this);s&&this._emit("finalFunctionCall",s);let n=rC(this,P,"m",O).call(this);null!=n&&this._emit("finalFunctionCallResult",n),this._chatCompletions.some(e=>e.usage)&&this._emit("totalUsage",rC(this,P,"m",C).call(this))}async _createChatCompletion(e,t,r){let 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this.done(),rC(this,R,"m",P).call(this)}async finalFunctionCall(){return await this.done(),rC(this,R,"m",O).call(this)}async finalFunctionCallResult(){return await this.done(),rC(this,R,"m",$).call(this)}async totalUsage(){return await this.done(),rC(this,R,"m",C).call(this)}allChatCompletions(){return[...this._chatCompletions]}_emitFinal(){let e=this._chatCompletions[this._chatCompletions.length-1];e&&this._emit("finalChatCompletion",e);let t=rC(this,R,"m",P).call(this);t&&this._emit("finalMessage",t);let r=rC(this,R,"m",I).call(this);r&&this._emit("finalContent",r);let s=rC(this,R,"m",O).call(this);s&&this._emit("finalFunctionCall",s);let n=rC(this,R,"m",$).call(this);null!=n&&this._emit("finalFunctionCallResult",n),this._chatCompletions.some(e=>e.usage)&&this._emit("totalUsage",rC(this,R,"m",C).call(this))}async _createChatCompletion(e,t,r){let s=r?.signal;s&&(s.aborted&&this.controller.abort(),s.addEventListener("abort",()=>this.controller.abort())),rC(this,R,"m",k).call(this,t);let n=await e.chat.completions.create({...t,stream:!1},{...r,signal:this.controller.signal});return this._connected(),this._addChatCompletion(rO(n,t))}async _runChatCompletion(e,t,r){for(let e of t.messages)this._addMessage(e,!1);return await this._createChatCompletion(e,t,r)}async _runFunctions(e,t,r){let s="function",{function_call:n="auto",stream:i,...a}=t,o="string"!=typeof n&&n?.name,{maxChatCompletions:l=10}=r||{},u={};for(let e of t.functions)u[e.name||e.function.name]=e;let c=t.functions.map(e=>({name:e.name||e.function.name,parameters:e.parameters,description:e.description}));for(let e of t.messages)this._addMessage(e,!1);for(let t=0;tJSON.stringify(e.name)).join(", ")}. Please try again`;this._addMessage({role:s,name:h,content:e});continue}try{t=r_(d)?await d.parse(f):f}catch(e){this._addMessage({role:s,name:h,content:e instanceof Error?e.message:String(e)});continue}let p=await d.function(t,this),m=rC(this,R,"m",T).call(this,p);if(this._addMessage({role:s,name:h,content:m}),o)return}}async _runTools(e,t,r){let s="tool",{tool_choice:n="auto",stream:i,...a}=t,o="string"!=typeof n&&n?.function?.name,{maxChatCompletions:l=10}=r||{},u=t.tools.map(e=>{if(rP(e)){if(!e.$callback)throw new eF("Tool given to `.runTools()` that does not have an associated function");return{type:"function",function:{function:e.$callback,name:e.function.name,description:e.function.description||"",parameters:e.function.parameters,parse:e.$parseRaw,strict:!0}}}return e}),c={};for(let e of u)"function"===e.type&&(c[e.function.name||e.function.function.name]=e.function);let h="tools"in t?u.map(e=>"function"===e.type?{type:"function",function:{name:e.function.name||e.function.function.name,parameters:e.function.parameters,description:e.function.description,strict:e.function.strict}}:e):void 0;for(let e of t.messages)this._addMessage(e,!1);for(let t=0;tJSON.stringify(e)).join(", ")}. Please try again`;this._addMessage({role:s,tool_call_id:r,content:e});continue}try{t=r_(a)?await a.parse(i):i}catch(t){let e=t instanceof Error?t.message:String(t);this._addMessage({role:s,tool_call_id:r,content:e});continue}let l=await a.function(t,this),u=rC(this,R,"m",T).call(this,l);if(this._addMessage({role:s,tool_call_id:r,content:u}),o)return}}}}R=new WeakSet,I=function(){return rC(this,R,"m",P).call(this).content??null},P=function(){let e=this.messages.length;for(;e-- >0;){let t=this.messages[e];if(rv(t)){let{function_call:e,...r}=t,s={...r,content:t.content??null,refusal:t.refusal??null};return e&&(s.function_call=e),s}}throw new eF("stream ended without producing a ChatCompletionMessage with role=assistant")},O=function(){for(let e=this.messages.length-1;e>=0;e--){let t=this.messages[e];if(rv(t)&&t?.function_call)return t.function_call;if(rv(t)&&t?.tool_calls?.length)return t.tool_calls.at(-1)?.function}},$=function(){for(let e=this.messages.length-1;e>=0;e--){let t=this.messages[e];if(rx(t)&&null!=t.content||rA(t)&&null!=t.content&&"string"==typeof t.content&&this.messages.some(e=>"assistant"===e.role&&e.tool_calls?.some(e=>"function"===e.type&&e.id===t.tool_call_id)))return t.content}},C=function(){let e={completion_tokens:0,prompt_tokens:0,total_tokens:0};for(let{usage:t}of this._chatCompletions)t&&(e.completion_tokens+=t.completion_tokens,e.prompt_tokens+=t.prompt_tokens,e.total_tokens+=t.total_tokens);return e},k=function(e){if(null!=e.n&&e.n>1)throw new eF("ChatCompletion convenience helpers only support n=1 at this time. 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e=[];try{for(;"]"!==r[i];)e.push(l()),d(),","===r[i]&&i++}catch(t){if(rB.ARR&s)return e;a("Expected ']' at end of array")}return i++,e},f=()=>{if(0===i){"-"===r&&rB.NUM&s&&a("Not sure what '-' is");try{return JSON.parse(r)}catch(e){if(rB.NUM&s)try{if("."===r[r.length-1])return JSON.parse(r.substring(0,r.lastIndexOf(".")));return JSON.parse(r.substring(0,r.lastIndexOf("e")))}catch(e){}o(String(e))}}let e=i;for("-"===r[i]&&i++;r[i]&&!",]}".includes(r[i]);)i++;i!=n||rB.NUM&s||a("Unterminated number literal");try{return JSON.parse(r.substring(e,i))}catch(t){"-"===r.substring(e,i)&&rB.NUM&s&&a("Not sure what '-' is");try{return JSON.parse(r.substring(e,r.lastIndexOf("e")))}catch(e){o(String(e))}}},d=()=>{for(;it._fromReadableStream(e)),t}static createChatCompletion(e,t,r){let s=new rD(t);return s._run(()=>s._runChatCompletion(e,{...t,stream:!0},{...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"stream"}})),s}async _createChatCompletion(e,t,r){super._createChatCompletion;let 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e=t.choices[r.index];null!=r.delta.content&&e.message?.role==="assistant"&&e.message?.content&&(this._emit("content",r.delta.content,e.message.content),this._emit("content.delta",{delta:r.delta.content,snapshot:e.message.content,parsed:e.message.parsed})),null!=r.delta.refusal&&e.message?.role==="assistant"&&e.message?.refusal&&this._emit("refusal.delta",{delta:r.delta.refusal,snapshot:e.message.refusal}),r.logprobs?.content!=null&&e.message?.role==="assistant"&&this._emit("logprobs.content.delta",{content:r.logprobs?.content,snapshot:e.logprobs?.content??[]}),r.logprobs?.refusal!=null&&e.message?.role==="assistant"&&this._emit("logprobs.refusal.delta",{refusal:r.logprobs?.refusal,snapshot:e.logprobs?.refusal??[]});let s=rU(this,B,"m",U).call(this,e);for(let t of(e.finish_reason&&(rU(this,B,"m",W).call(this,e),null!=s.current_tool_call_index&&rU(this,B,"m",F).call(this,e,s.current_tool_call_index)),r.delta.tool_calls??[]))s.current_tool_call_index!==t.index&&(rU(this,B,"m",W).call(this,e),null!=s.current_tool_call_index&&rU(this,B,"m",F).call(this,e,s.current_tool_call_index)),s.current_tool_call_index=t.index;for(let t of r.delta.tool_calls??[]){let r=e.message.tool_calls?.[t.index];r?.type&&(r?.type==="function"?this._emit("tool_calls.function.arguments.delta",{name:r.function?.name,index:t.index,arguments:r.function.arguments,parsed_arguments:r.function.parsed_arguments,arguments_delta:t.function?.arguments??""}):rq(r?.type))}}},F=function(e,t){if(rU(this,B,"m",U).call(this,e).done_tool_calls.has(t))return;let r=e.message.tool_calls?.[t];if(!r)throw Error("no tool call snapshot");if(!r.type)throw Error("tool call snapshot missing `type`");if("function"===r.type){let 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l?{...i,index:s,finish_reason:r,logprobs:n,message:{...u,role:c,content:a,refusal:t.refusal??null,tool_calls:l.map((t,r)=>{let{function:n,type:i,id:a,...o}=t,{arguments:l,name:u,...c}=n||{};if(null==a)throw new eF(`missing choices[${s}].tool_calls[${r}].id ${rF(e)}`);if(null==i)throw new eF(`missing choices[${s}].tool_calls[${r}].type ${rF(e)}`);if(null==u)throw new eF(`missing choices[${s}].tool_calls[${r}].function.name ${rF(e)}`);if(null==l)throw new eF(`missing choices[${s}].tool_calls[${r}].function.arguments -${rF(e)}`);return{...o,id:a,type:i,function:{...c,name:u,arguments:l}}})}}:{...i,message:{...u,content:a,role:c,refusal:t.refusal??null},finish_reason:r,index:s,logprobs:n}}),created:i,model:a,object:"chat.completion",...o?{system_fingerprint:o}:{}},t&&rO(t)?r$(r,t):{...r,choices:r.choices.map(e=>({...e,message:{...e.message,parsed:null,...e.message.tool_calls?{tool_calls:e.message.tool_calls}:void 0}}))}}(e,rU(this,M,"f"))},X=function(){let 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e1}if(Object.assign(e,h),!a)continue;let{content:o,refusal:f,function_call:d,role:p,tool_calls:m,...g}=a;if(rW(g),Object.assign(e.message,g),f&&(e.message.refusal=(e.message.refusal||"")+f),p&&(e.message.role=p),d&&(e.message.function_call?(d.name&&(e.message.function_call.name=d.name),d.arguments&&((s=e.message.function_call).arguments??(s.arguments=""),e.message.function_call.arguments+=d.arguments)):e.message.function_call=d),o&&(e.message.content=(e.message.content||"")+o,!e.message.refusal&&rU(this,B,"m",X).call(this)&&(e.message.parsed=rL(e.message.content))),m)for(let{index:t,id:r,type:s,function:i,...a}of(e.message.tool_calls||(e.message.tool_calls=[]),m)){let o=(n=e.message.tool_calls)[t]??(n[t]={});Object.assign(o,a),r&&(o.id=r),s&&(o.type=s),i&&(o.function??(o.function={name:i.name??"",arguments:""})),i?.name&&(o.function.name=i.name),i?.arguments&&(o.function.arguments+=i.arguments,function(e,t){if(!e)return!1;let r=e.tools?.find(e=>e.function?.name===t.function.name);return rI(r)||r?.function.strict||!1}(rU(this,M,"f"),o)&&(o.function.parsed_arguments=rL(o.function.arguments)))}}return i},Symbol.asyncIterator)](){let e=[],t=[],r=!1;return this.on("chunk",r=>{let s=t.shift();s?s.resolve(r):e.push(r)}),this.on("end",()=>{for(let e of(r=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),this.on("error",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:r?{value:void 0,done:!0}:new Promise((e,r)=>t.push({resolve:e,reject:r})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}toReadableStream(){return new e3(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}}function rF(e){return JSON.stringify(e)}function rW(e){}function rq(e){}class rX extends rD{static fromReadableStream(e){let t=new rX(null);return t._run(()=>t._fromReadableStream(e)),t}static runFunctions(e,t,r){let s=new rX(null),n={...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"runFunctions"}};return s._run(()=>s._runFunctions(e,t,n)),s}static runTools(e,t,r){let s=new rX(t),n={...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"runTools"}};return s._run(()=>s._runTools(e,t,n)),s}}class rJ extends tD{parse(e,t){for(let t of e.tools??[]){if("function"!==t.type)throw new eF(`Currently only \`function\` tool types support auto-parsing; Received \`${t.type}\``);if(!0!==t.function.strict)throw new eF(`The \`${t.function.name}\` tool is not marked with \`strict: true\`. Only strict function tools can be auto-parsed`)}return this._client.chat.completions.create(e,{...t,headers:{...t?.headers,"X-Stainless-Helper-Method":"beta.chat.completions.parse"}})._thenUnwrap(t=>r$(t,e))}runFunctions(e,t){return e.stream?rX.runFunctions(this._client,e,t):rT.runFunctions(this._client,e,t)}runTools(e,t){return e.stream?rX.runTools(this._client,e,t):rT.runTools(this._client,e,t)}stream(e,t){return rD.createChatCompletion(this._client,e,t)}}class rH extends tD{constructor(){super(...arguments),this.completions=new rJ(this._client)}}(rH||(rH={})).Completions=rJ;class rV extends tD{create(e,t){return this._client.post("/realtime/sessions",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}}class rK extends tD{create(e,t){return this._client.post("/realtime/transcription_sessions",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}}class rz extends tD{constructor(){super(...arguments),this.sessions=new rV(this._client),this.transcriptionSessions=new rK(this._client)}}rz.Sessions=rV,rz.TranscriptionSessions=rK;var rQ=function(e,t,r,s){if("a"===r&&!s)throw TypeError("Private accessor was defined without a getter");if("function"==typeof t?e!==t||!s:!t.has(e))throw TypeError("Cannot read private member from an object whose class did not declare it");return"m"===r?s:"a"===r?s.call(e):s?s.value:t.get(e)},rY=function(e,t,r,s,n){if("m"===s)throw TypeError("Private method is not writable");if("a"===s&&!n)throw TypeError("Private accessor was defined without a setter");if("function"==typeof t?e!==t||!n:!t.has(e))throw TypeError("Cannot write private member to an object whose class did not declare it");return"a"===s?n.call(e,r):n?n.value=r:t.set(e,r),r};class rG extends rP{constructor(){super(...arguments),H.add(this),V.set(this,[]),K.set(this,{}),z.set(this,{}),Q.set(this,void 0),Y.set(this,void 0),G.set(this,void 0),Z.set(this,void 0),ee.set(this,void 0),et.set(this,void 0),er.set(this,void 0),es.set(this,void 0),en.set(this,void 0)}[(V=new WeakMap,K=new WeakMap,z=new WeakMap,Q=new WeakMap,Y=new WeakMap,G=new WeakMap,Z=new WeakMap,ee=new WeakMap,et=new WeakMap,er=new WeakMap,es=new WeakMap,en=new WeakMap,H=new WeakSet,Symbol.asyncIterator)](){let e=[],t=[],r=!1;return this.on("event",r=>{let s=t.shift();s?s.resolve(r):e.push(r)}),this.on("end",()=>{for(let e of(r=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),this.on("error",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:r?{value:void 0,done:!0}:new Promise((e,r)=>t.push({resolve:e,reject:r})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}static fromReadableStream(e){let t=new rG;return t._run(()=>t._fromReadableStream(e)),t}async _fromReadableStream(e,t){let r=t?.signal;r&&(r.aborted&&this.controller.abort(),r.addEventListener("abort",()=>this.controller.abort())),this._connected();let s=e3.fromReadableStream(e,this.controller);for await(let e of s)rQ(this,H,"m",ei).call(this,e);if(s.controller.signal?.aborted)throw new eq;return this._addRun(rQ(this,H,"m",ea).call(this))}toReadableStream(){return new e3(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}static createToolAssistantStream(e,t,r,s,n){let i=new rG;return i._run(()=>i._runToolAssistantStream(e,t,r,s,{...n,headers:{...n?.headers,"X-Stainless-Helper-Method":"stream"}})),i}async _createToolAssistantStream(e,t,r,s,n){let i=n?.signal;i&&(i.aborted&&this.controller.abort(),i.addEventListener("abort",()=>this.controller.abort()));let a={...s,stream:!0},o=await e.submitToolOutputs(t,r,a,{...n,signal:this.controller.signal});for await(let e of(this._connected(),o))rQ(this,H,"m",ei).call(this,e);if(o.controller.signal?.aborted)throw new eq;return this._addRun(rQ(this,H,"m",ea).call(this))}static createThreadAssistantStream(e,t,r){let s=new rG;return s._run(()=>s._threadAssistantStream(e,t,{...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"stream"}})),s}static createAssistantStream(e,t,r,s){let n=new rG;return n._run(()=>n._runAssistantStream(e,t,r,{...s,headers:{...s?.headers,"X-Stainless-Helper-Method":"stream"}})),n}currentEvent(){return rQ(this,er,"f")}currentRun(){return rQ(this,es,"f")}currentMessageSnapshot(){return rQ(this,Q,"f")}currentRunStepSnapshot(){return rQ(this,en,"f")}async finalRunSteps(){return await this.done(),Object.values(rQ(this,K,"f"))}async finalMessages(){return await this.done(),Object.values(rQ(this,z,"f"))}async finalRun(){if(await this.done(),!rQ(this,Y,"f"))throw Error("Final run was not received.");return rQ(this,Y,"f")}async _createThreadAssistantStream(e,t,r){let s=r?.signal;s&&(s.aborted&&this.controller.abort(),s.addEventListener("abort",()=>this.controller.abort()));let n={...t,stream:!0},i=await e.createAndRun(n,{...r,signal:this.controller.signal});for await(let e of(this._connected(),i))rQ(this,H,"m",ei).call(this,e);if(i.controller.signal?.aborted)throw new eq;return this._addRun(rQ(this,H,"m",ea).call(this))}async _createAssistantStream(e,t,r,s){let n=s?.signal;n&&(n.aborted&&this.controller.abort(),n.addEventListener("abort",()=>this.controller.abort()));let i={...r,stream:!0},a=await e.create(t,i,{...s,signal:this.controller.signal});for await(let e of(this._connected(),a))rQ(this,H,"m",ei).call(this,e);if(a.controller.signal?.aborted)throw new eq;return this._addRun(rQ(this,H,"m",ea).call(this))}static accumulateDelta(e,t){for(let[r,s]of Object.entries(t)){if(!e.hasOwnProperty(r)){e[r]=s;continue}let t=e[r];if(null==t||"index"===r||"type"===r){e[r]=s;continue}if("string"==typeof t&&"string"==typeof s)t+=s;else if("number"==typeof t&&"number"==typeof s)t+=s;else if(tU(t)&&tU(s))t=this.accumulateDelta(t,s);else if(Array.isArray(t)&&Array.isArray(s)){if(t.every(e=>"string"==typeof e||"number"==typeof e)){t.push(...s);continue}for(let e of s){if(!tU(e))throw Error(`Expected array delta entry to be an object but got: ${e}`);let r=e.index;if(null==r)throw console.error(e),Error("Expected array delta entry to have an `index` property");if("number"!=typeof r)throw Error(`Expected array delta entry \`index\` property to be a number but got ${r}`);let s=t[r];null==s?t.push(e):t[r]=this.accumulateDelta(s,e)}continue}else throw Error(`Unhandled record type: ${r}, deltaValue: ${s}, accValue: ${t}`);e[r]=t}return e}_addRun(e){return e}async _threadAssistantStream(e,t,r){return await this._createThreadAssistantStream(t,e,r)}async _runAssistantStream(e,t,r,s){return await this._createAssistantStream(t,e,r,s)}async _runToolAssistantStream(e,t,r,s,n){return await this._createToolAssistantStream(r,e,t,s,n)}}ei=function(e){if(!this.ended)switch(rY(this,er,e,"f"),rQ(this,H,"m",eu).call(this,e),e.event){case"thread.created":break;case"thread.run.created":case"thread.run.queued":case"thread.run.in_progress":case"thread.run.requires_action":case"thread.run.completed":case"thread.run.incomplete":case"thread.run.failed":case"thread.run.cancelling":case"thread.run.cancelled":case"thread.run.expired":rQ(this,H,"m",ed).call(this,e);break;case"thread.run.step.created":case"thread.run.step.in_progress":case"thread.run.step.delta":case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":rQ(this,H,"m",el).call(this,e);break;case"thread.message.created":case"thread.message.in_progress":case"thread.message.delta":case"thread.message.completed":case"thread.message.incomplete":rQ(this,H,"m",eo).call(this,e);break;case"error":throw Error("Encountered an error event in event processing - errors should be processed earlier")}},ea=function(){if(this.ended)throw new eF("stream has ended, this shouldn't happen");if(!rQ(this,Y,"f"))throw Error("Final run has not been received");return rQ(this,Y,"f")},eo=function(e){let[t,r]=rQ(this,H,"m",eh).call(this,e,rQ(this,Q,"f"));for(let e of(rY(this,Q,t,"f"),rQ(this,z,"f")[t.id]=t,r)){let r=t.content[e.index];r?.type=="text"&&this._emit("textCreated",r.text)}switch(e.event){case"thread.message.created":this._emit("messageCreated",e.data);break;case"thread.message.in_progress":break;case"thread.message.delta":if(this._emit("messageDelta",e.data.delta,t),e.data.delta.content)for(let r of e.data.delta.content){if("text"==r.type&&r.text){let e=r.text,s=t.content[r.index];if(s&&"text"==s.type)this._emit("textDelta",e,s.text);else throw Error("The snapshot associated with this text delta is not text or missing")}if(r.index!=rQ(this,G,"f")){if(rQ(this,Z,"f"))switch(rQ(this,Z,"f").type){case"text":this._emit("textDone",rQ(this,Z,"f").text,rQ(this,Q,"f"));break;case"image_file":this._emit("imageFileDone",rQ(this,Z,"f").image_file,rQ(this,Q,"f"))}rY(this,G,r.index,"f")}rY(this,Z,t.content[r.index],"f")}break;case"thread.message.completed":case"thread.message.incomplete":if(void 0!==rQ(this,G,"f")){let t=e.data.content[rQ(this,G,"f")];if(t)switch(t.type){case"image_file":this._emit("imageFileDone",t.image_file,rQ(this,Q,"f"));break;case"text":this._emit("textDone",t.text,rQ(this,Q,"f"))}}rQ(this,Q,"f")&&this._emit("messageDone",e.data),rY(this,Q,void 0,"f")}},el=function(e){let t=rQ(this,H,"m",ec).call(this,e);switch(rY(this,en,t,"f"),e.event){case"thread.run.step.created":this._emit("runStepCreated",e.data);break;case"thread.run.step.delta":let r=e.data.delta;if(r.step_details&&"tool_calls"==r.step_details.type&&r.step_details.tool_calls&&"tool_calls"==t.step_details.type)for(let e of r.step_details.tool_calls)e.index==rQ(this,ee,"f")?this._emit("toolCallDelta",e,t.step_details.tool_calls[e.index]):(rQ(this,et,"f")&&this._emit("toolCallDone",rQ(this,et,"f")),rY(this,ee,e.index,"f"),rY(this,et,t.step_details.tool_calls[e.index],"f"),rQ(this,et,"f")&&this._emit("toolCallCreated",rQ(this,et,"f")));this._emit("runStepDelta",e.data.delta,t);break;case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":rY(this,en,void 0,"f"),"tool_calls"==e.data.step_details.type&&rQ(this,et,"f")&&(this._emit("toolCallDone",rQ(this,et,"f")),rY(this,et,void 0,"f")),this._emit("runStepDone",e.data,t)}},eu=function(e){rQ(this,V,"f").push(e),this._emit("event",e)},ec=function(e){switch(e.event){case"thread.run.step.created":return rQ(this,K,"f")[e.data.id]=e.data,e.data;case"thread.run.step.delta":let t=rQ(this,K,"f")[e.data.id];if(!t)throw Error("Received a RunStepDelta before creation of a snapshot");let r=e.data;if(r.delta){let s=rG.accumulateDelta(t,r.delta);rQ(this,K,"f")[e.data.id]=s}return rQ(this,K,"f")[e.data.id];case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":case"thread.run.step.in_progress":rQ(this,K,"f")[e.data.id]=e.data}if(rQ(this,K,"f")[e.data.id])return rQ(this,K,"f")[e.data.id];throw Error("No snapshot available")},eh=function(e,t){let r=[];switch(e.event){case"thread.message.created":return[e.data,r];case"thread.message.delta":if(!t)throw Error("Received a delta with no existing snapshot (there should be one from message creation)");let s=e.data;if(s.delta.content)for(let e of s.delta.content)if(e.index in t.content){let r=t.content[e.index];t.content[e.index]=rQ(this,H,"m",ef).call(this,e,r)}else t.content[e.index]=e,r.push(e);return[t,r];case"thread.message.in_progress":case"thread.message.completed":case"thread.message.incomplete":if(t)return[t,r];throw Error("Received thread message event with no existing snapshot")}throw Error("Tried to accumulate a non-message event")},ef=function(e,t){return rG.accumulateDelta(t,e)},ed=function(e){switch(rY(this,es,e.data,"f"),e.event){case"thread.run.created":case"thread.run.queued":case"thread.run.in_progress":break;case"thread.run.requires_action":case"thread.run.cancelled":case"thread.run.failed":case"thread.run.completed":case"thread.run.expired":rY(this,Y,e.data,"f"),rQ(this,et,"f")&&(this._emit("toolCallDone",rQ(this,et,"f")),rY(this,et,void 0,"f"))}};class rZ extends tD{create(e,t,r){return this._client.post(`/threads/${e}/messages`,{body:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}retrieve(e,t,r){return this._client.get(`/threads/${e}/messages/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}update(e,t,r,s){return this._client.post(`/threads/${e}/messages/${t}`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}list(e,t={},r){return tv(t)?this.list(e,{},t):this._client.getAPIList(`/threads/${e}/messages`,r0,{query:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}del(e,t,r){return this._client.delete(`/threads/${e}/messages/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}}class r0 extends tX{}rZ.MessagesPage=r0;class r1 extends tD{retrieve(e,t,r,s={},n){return tv(s)?this.retrieve(e,t,r,{},s):this._client.get(`/threads/${e}/runs/${t}/steps/${r}`,{query:s,...n,headers:{"OpenAI-Beta":"assistants=v2",...n?.headers}})}list(e,t,r={},s){return tv(r)?this.list(e,t,{},r):this._client.getAPIList(`/threads/${e}/runs/${t}/steps`,r2,{query:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}}class r2 extends tX{}r1.RunStepsPage=r2;class r8 extends tD{constructor(){super(...arguments),this.steps=new r1(this._client)}create(e,t,r){let{include:s,...n}=t;return this._client.post(`/threads/${e}/runs`,{query:{include:s},body:n,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers},stream:t.stream??!1})}retrieve(e,t,r){return this._client.get(`/threads/${e}/runs/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}update(e,t,r,s){return this._client.post(`/threads/${e}/runs/${t}`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}list(e,t={},r){return tv(t)?this.list(e,{},t):this._client.getAPIList(`/threads/${e}/runs`,r6,{query:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}cancel(e,t,r){return this._client.post(`/threads/${e}/runs/${t}/cancel`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}async createAndPoll(e,t,r){let s=await this.create(e,t,r);return await this.poll(e,s.id,r)}createAndStream(e,t,r){return rG.createAssistantStream(e,this._client.beta.threads.runs,t,r)}async poll(e,t,r){let s={...r?.headers,"X-Stainless-Poll-Helper":"true"};for(r?.pollIntervalMs&&(s["X-Stainless-Custom-Poll-Interval"]=r.pollIntervalMs.toString());;){let{data:n,response:i}=await this.retrieve(e,t,{...r,headers:{...r?.headers,...s}}).withResponse();switch(n.status){case"queued":case"in_progress":case"cancelling":let a=5e3;if(r?.pollIntervalMs)a=r.pollIntervalMs;else{let e=i.headers.get("openai-poll-after-ms");if(e){let t=parseInt(e);isNaN(t)||(a=t)}}await tI(a);break;case"requires_action":case"incomplete":case"cancelled":case"completed":case"failed":case"expired":return n}}}stream(e,t,r){return rG.createAssistantStream(e,this._client.beta.threads.runs,t,r)}submitToolOutputs(e,t,r,s){return this._client.post(`/threads/${e}/runs/${t}/submit_tool_outputs`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers},stream:r.stream??!1})}async submitToolOutputsAndPoll(e,t,r,s){let n=await this.submitToolOutputs(e,t,r,s);return await this.poll(e,n.id,s)}submitToolOutputsStream(e,t,r,s){return rG.createToolAssistantStream(e,t,this._client.beta.threads.runs,r,s)}}class r6 extends tX{}r8.RunsPage=r6,r8.Steps=r1,r8.RunStepsPage=r2;class r5 extends tD{constructor(){super(...arguments),this.runs=new r8(this._client),this.messages=new rZ(this._client)}create(e={},t){return tv(e)?this.create({},e):this._client.post("/threads",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}retrieve(e,t){return this._client.get(`/threads/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}update(e,t,r){return this._client.post(`/threads/${e}`,{body:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}del(e,t){return this._client.delete(`/threads/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}createAndRun(e,t){return this._client.post("/threads/runs",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers},stream:e.stream??!1})}async createAndRunPoll(e,t){let r=await this.createAndRun(e,t);return await this.runs.poll(r.thread_id,r.id,t)}createAndRunStream(e,t){return rG.createThreadAssistantStream(e,this._client.beta.threads,t)}}r5.Runs=r8,r5.RunsPage=r6,r5.Messages=rZ,r5.MessagesPage=r0;class r3 extends tD{constructor(){super(...arguments),this.realtime=new rz(this._client),this.chat=new rH(this._client),this.assistants=new rw(this._client),this.threads=new r5(this._client)}}r3.Realtime=rz,r3.Assistants=rw,r3.AssistantsPage=rb,r3.Threads=r5;class r4 extends tD{create(e,t){return this._client.post("/batches",{body:e,...t})}retrieve(e,t){return this._client.get(`/batches/${e}`,t)}list(e={},t){return tv(e)?this.list({},e):this._client.getAPIList("/batches",r9,{query:e,...t})}cancel(e,t){return this._client.post(`/batches/${e}/cancel`,t)}}class r9 extends tX{}r4.BatchesPage=r9;class r7 extends tD{create(e,t,r){return this._client.post(`/uploads/${e}/parts`,tl({body:t,...r}))}}class se extends tD{constructor(){super(...arguments),this.parts=new 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0),es.set(this,void 0),en.set(this,void 0)}[(V=new WeakMap,K=new WeakMap,z=new WeakMap,Y=new WeakMap,Q=new WeakMap,G=new WeakMap,Z=new WeakMap,ee=new WeakMap,et=new WeakMap,er=new WeakMap,es=new WeakMap,en=new WeakMap,H=new WeakSet,Symbol.asyncIterator)](){let e=[],t=[],r=!1;return this.on("event",r=>{let s=t.shift();s?s.resolve(r):e.push(r)}),this.on("end",()=>{for(let e of(r=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),this.on("error",e=>{for(let s of(r=!0,t))s.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:r?{value:void 0,done:!0}:new Promise((e,r)=>t.push({resolve:e,reject:r})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}static fromReadableStream(e){let t=new rG;return t._run(()=>t._fromReadableStream(e)),t}async _fromReadableStream(e,t){let r=t?.signal;r&&(r.aborted&&this.controller.abort(),r.addEventListener("abort",()=>this.controller.abort())),this._connected();let s=e3.fromReadableStream(e,this.controller);for await(let e of s)rY(this,H,"m",ei).call(this,e);if(s.controller.signal?.aborted)throw new eq;return this._addRun(rY(this,H,"m",ea).call(this))}toReadableStream(){return new e3(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}static createToolAssistantStream(e,t,r,s,n){let i=new rG;return i._run(()=>i._runToolAssistantStream(e,t,r,s,{...n,headers:{...n?.headers,"X-Stainless-Helper-Method":"stream"}})),i}async _createToolAssistantStream(e,t,r,s,n){let i=n?.signal;i&&(i.aborted&&this.controller.abort(),i.addEventListener("abort",()=>this.controller.abort()));let a={...s,stream:!0},o=await e.submitToolOutputs(t,r,a,{...n,signal:this.controller.signal});for await(let e of(this._connected(),o))rY(this,H,"m",ei).call(this,e);if(o.controller.signal?.aborted)throw new eq;return this._addRun(rY(this,H,"m",ea).call(this))}static createThreadAssistantStream(e,t,r){let s=new rG;return s._run(()=>s._threadAssistantStream(e,t,{...r,headers:{...r?.headers,"X-Stainless-Helper-Method":"stream"}})),s}static createAssistantStream(e,t,r,s){let n=new rG;return n._run(()=>n._runAssistantStream(e,t,r,{...s,headers:{...s?.headers,"X-Stainless-Helper-Method":"stream"}})),n}currentEvent(){return rY(this,er,"f")}currentRun(){return rY(this,es,"f")}currentMessageSnapshot(){return rY(this,Y,"f")}currentRunStepSnapshot(){return rY(this,en,"f")}async finalRunSteps(){return await this.done(),Object.values(rY(this,K,"f"))}async finalMessages(){return await this.done(),Object.values(rY(this,z,"f"))}async finalRun(){if(await this.done(),!rY(this,Q,"f"))throw Error("Final run was not received.");return rY(this,Q,"f")}async _createThreadAssistantStream(e,t,r){let s=r?.signal;s&&(s.aborted&&this.controller.abort(),s.addEventListener("abort",()=>this.controller.abort()));let n={...t,stream:!0},i=await e.createAndRun(n,{...r,signal:this.controller.signal});for await(let e of(this._connected(),i))rY(this,H,"m",ei).call(this,e);if(i.controller.signal?.aborted)throw new eq;return this._addRun(rY(this,H,"m",ea).call(this))}async _createAssistantStream(e,t,r,s){let n=s?.signal;n&&(n.aborted&&this.controller.abort(),n.addEventListener("abort",()=>this.controller.abort()));let i={...r,stream:!0},a=await e.create(t,i,{...s,signal:this.controller.signal});for await(let e of(this._connected(),a))rY(this,H,"m",ei).call(this,e);if(a.controller.signal?.aborted)throw new eq;return this._addRun(rY(this,H,"m",ea).call(this))}static accumulateDelta(e,t){for(let[r,s]of Object.entries(t)){if(!e.hasOwnProperty(r)){e[r]=s;continue}let t=e[r];if(null==t||"index"===r||"type"===r){e[r]=s;continue}if("string"==typeof t&&"string"==typeof s)t+=s;else if("number"==typeof t&&"number"==typeof s)t+=s;else if(tU(t)&&tU(s))t=this.accumulateDelta(t,s);else if(Array.isArray(t)&&Array.isArray(s)){if(t.every(e=>"string"==typeof e||"number"==typeof e)){t.push(...s);continue}for(let e of s){if(!tU(e))throw Error(`Expected array delta entry to be an object but got: ${e}`);let r=e.index;if(null==r)throw console.error(e),Error("Expected array delta entry to have an `index` property");if("number"!=typeof r)throw Error(`Expected array delta entry \`index\` property to be a number but got ${r}`);let s=t[r];null==s?t.push(e):t[r]=this.accumulateDelta(s,e)}continue}else throw Error(`Unhandled record type: ${r}, deltaValue: ${s}, accValue: ${t}`);e[r]=t}return e}_addRun(e){return e}async _threadAssistantStream(e,t,r){return await this._createThreadAssistantStream(t,e,r)}async _runAssistantStream(e,t,r,s){return await this._createAssistantStream(t,e,r,s)}async _runToolAssistantStream(e,t,r,s,n){return await this._createToolAssistantStream(r,e,t,s,n)}}ei=function(e){if(!this.ended)switch(rQ(this,er,e,"f"),rY(this,H,"m",eu).call(this,e),e.event){case"thread.created":break;case"thread.run.created":case"thread.run.queued":case"thread.run.in_progress":case"thread.run.requires_action":case"thread.run.completed":case"thread.run.incomplete":case"thread.run.failed":case"thread.run.cancelling":case"thread.run.cancelled":case"thread.run.expired":rY(this,H,"m",ed).call(this,e);break;case"thread.run.step.created":case"thread.run.step.in_progress":case"thread.run.step.delta":case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":rY(this,H,"m",el).call(this,e);break;case"thread.message.created":case"thread.message.in_progress":case"thread.message.delta":case"thread.message.completed":case"thread.message.incomplete":rY(this,H,"m",eo).call(this,e);break;case"error":throw Error("Encountered an error event in event processing - errors should be processed earlier")}},ea=function(){if(this.ended)throw new eF("stream has ended, this shouldn't happen");if(!rY(this,Q,"f"))throw Error("Final run has not been received");return rY(this,Q,"f")},eo=function(e){let[t,r]=rY(this,H,"m",eh).call(this,e,rY(this,Y,"f"));for(let e of(rQ(this,Y,t,"f"),rY(this,z,"f")[t.id]=t,r)){let r=t.content[e.index];r?.type=="text"&&this._emit("textCreated",r.text)}switch(e.event){case"thread.message.created":this._emit("messageCreated",e.data);break;case"thread.message.in_progress":break;case"thread.message.delta":if(this._emit("messageDelta",e.data.delta,t),e.data.delta.content)for(let r of e.data.delta.content){if("text"==r.type&&r.text){let e=r.text,s=t.content[r.index];if(s&&"text"==s.type)this._emit("textDelta",e,s.text);else throw Error("The snapshot associated with this text delta is not text or missing")}if(r.index!=rY(this,G,"f")){if(rY(this,Z,"f"))switch(rY(this,Z,"f").type){case"text":this._emit("textDone",rY(this,Z,"f").text,rY(this,Y,"f"));break;case"image_file":this._emit("imageFileDone",rY(this,Z,"f").image_file,rY(this,Y,"f"))}rQ(this,G,r.index,"f")}rQ(this,Z,t.content[r.index],"f")}break;case"thread.message.completed":case"thread.message.incomplete":if(void 0!==rY(this,G,"f")){let t=e.data.content[rY(this,G,"f")];if(t)switch(t.type){case"image_file":this._emit("imageFileDone",t.image_file,rY(this,Y,"f"));break;case"text":this._emit("textDone",t.text,rY(this,Y,"f"))}}rY(this,Y,"f")&&this._emit("messageDone",e.data),rQ(this,Y,void 0,"f")}},el=function(e){let t=rY(this,H,"m",ec).call(this,e);switch(rQ(this,en,t,"f"),e.event){case"thread.run.step.created":this._emit("runStepCreated",e.data);break;case"thread.run.step.delta":let r=e.data.delta;if(r.step_details&&"tool_calls"==r.step_details.type&&r.step_details.tool_calls&&"tool_calls"==t.step_details.type)for(let e of r.step_details.tool_calls)e.index==rY(this,ee,"f")?this._emit("toolCallDelta",e,t.step_details.tool_calls[e.index]):(rY(this,et,"f")&&this._emit("toolCallDone",rY(this,et,"f")),rQ(this,ee,e.index,"f"),rQ(this,et,t.step_details.tool_calls[e.index],"f"),rY(this,et,"f")&&this._emit("toolCallCreated",rY(this,et,"f")));this._emit("runStepDelta",e.data.delta,t);break;case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":rQ(this,en,void 0,"f"),"tool_calls"==e.data.step_details.type&&rY(this,et,"f")&&(this._emit("toolCallDone",rY(this,et,"f")),rQ(this,et,void 0,"f")),this._emit("runStepDone",e.data,t)}},eu=function(e){rY(this,V,"f").push(e),this._emit("event",e)},ec=function(e){switch(e.event){case"thread.run.step.created":return rY(this,K,"f")[e.data.id]=e.data,e.data;case"thread.run.step.delta":let t=rY(this,K,"f")[e.data.id];if(!t)throw Error("Received a RunStepDelta before creation of a snapshot");let r=e.data;if(r.delta){let s=rG.accumulateDelta(t,r.delta);rY(this,K,"f")[e.data.id]=s}return rY(this,K,"f")[e.data.id];case"thread.run.step.completed":case"thread.run.step.failed":case"thread.run.step.cancelled":case"thread.run.step.expired":case"thread.run.step.in_progress":rY(this,K,"f")[e.data.id]=e.data}if(rY(this,K,"f")[e.data.id])return rY(this,K,"f")[e.data.id];throw Error("No snapshot available")},eh=function(e,t){let r=[];switch(e.event){case"thread.message.created":return[e.data,r];case"thread.message.delta":if(!t)throw Error("Received a delta with no existing snapshot (there should be one from message creation)");let s=e.data;if(s.delta.content)for(let e of s.delta.content)if(e.index in t.content){let r=t.content[e.index];t.content[e.index]=rY(this,H,"m",ef).call(this,e,r)}else t.content[e.index]=e,r.push(e);return[t,r];case"thread.message.in_progress":case"thread.message.completed":case"thread.message.incomplete":if(t)return[t,r];throw Error("Received thread message event with no existing snapshot")}throw Error("Tried to accumulate a non-message event")},ef=function(e,t){return rG.accumulateDelta(t,e)},ed=function(e){switch(rQ(this,es,e.data,"f"),e.event){case"thread.run.created":case"thread.run.queued":case"thread.run.in_progress":break;case"thread.run.requires_action":case"thread.run.cancelled":case"thread.run.failed":case"thread.run.completed":case"thread.run.expired":rQ(this,Q,e.data,"f"),rY(this,et,"f")&&(this._emit("toolCallDone",rY(this,et,"f")),rQ(this,et,void 0,"f"))}};class rZ extends tD{create(e,t,r){return this._client.post(`/threads/${e}/messages`,{body:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}retrieve(e,t,r){return this._client.get(`/threads/${e}/messages/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}update(e,t,r,s){return this._client.post(`/threads/${e}/messages/${t}`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}list(e,t={},r){return tv(t)?this.list(e,{},t):this._client.getAPIList(`/threads/${e}/messages`,r0,{query:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}del(e,t,r){return this._client.delete(`/threads/${e}/messages/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}}class r0 extends tX{}rZ.MessagesPage=r0;class r1 extends tD{retrieve(e,t,r,s={},n){return tv(s)?this.retrieve(e,t,r,{},s):this._client.get(`/threads/${e}/runs/${t}/steps/${r}`,{query:s,...n,headers:{"OpenAI-Beta":"assistants=v2",...n?.headers}})}list(e,t,r={},s){return tv(r)?this.list(e,t,{},r):this._client.getAPIList(`/threads/${e}/runs/${t}/steps`,r2,{query:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}}class r2 extends tX{}r1.RunStepsPage=r2;class r8 extends tD{constructor(){super(...arguments),this.steps=new r1(this._client)}create(e,t,r){let{include:s,...n}=t;return this._client.post(`/threads/${e}/runs`,{query:{include:s},body:n,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers},stream:t.stream??!1})}retrieve(e,t,r){return this._client.get(`/threads/${e}/runs/${t}`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}update(e,t,r,s){return this._client.post(`/threads/${e}/runs/${t}`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers}})}list(e,t={},r){return tv(t)?this.list(e,{},t):this._client.getAPIList(`/threads/${e}/runs`,r6,{query:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}cancel(e,t,r){return this._client.post(`/threads/${e}/runs/${t}/cancel`,{...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}async createAndPoll(e,t,r){let s=await this.create(e,t,r);return await this.poll(e,s.id,r)}createAndStream(e,t,r){return rG.createAssistantStream(e,this._client.beta.threads.runs,t,r)}async poll(e,t,r){let s={...r?.headers,"X-Stainless-Poll-Helper":"true"};for(r?.pollIntervalMs&&(s["X-Stainless-Custom-Poll-Interval"]=r.pollIntervalMs.toString());;){let{data:n,response:i}=await this.retrieve(e,t,{...r,headers:{...r?.headers,...s}}).withResponse();switch(n.status){case"queued":case"in_progress":case"cancelling":let a=5e3;if(r?.pollIntervalMs)a=r.pollIntervalMs;else{let e=i.headers.get("openai-poll-after-ms");if(e){let t=parseInt(e);isNaN(t)||(a=t)}}await tP(a);break;case"requires_action":case"incomplete":case"cancelled":case"completed":case"failed":case"expired":return n}}}stream(e,t,r){return rG.createAssistantStream(e,this._client.beta.threads.runs,t,r)}submitToolOutputs(e,t,r,s){return this._client.post(`/threads/${e}/runs/${t}/submit_tool_outputs`,{body:r,...s,headers:{"OpenAI-Beta":"assistants=v2",...s?.headers},stream:r.stream??!1})}async submitToolOutputsAndPoll(e,t,r,s){let n=await this.submitToolOutputs(e,t,r,s);return await this.poll(e,n.id,s)}submitToolOutputsStream(e,t,r,s){return rG.createToolAssistantStream(e,t,this._client.beta.threads.runs,r,s)}}class r6 extends tX{}r8.RunsPage=r6,r8.Steps=r1,r8.RunStepsPage=r2;class r5 extends tD{constructor(){super(...arguments),this.runs=new r8(this._client),this.messages=new rZ(this._client)}create(e={},t){return tv(e)?this.create({},e):this._client.post("/threads",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}retrieve(e,t){return this._client.get(`/threads/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}update(e,t,r){return this._client.post(`/threads/${e}`,{body:t,...r,headers:{"OpenAI-Beta":"assistants=v2",...r?.headers}})}del(e,t){return this._client.delete(`/threads/${e}`,{...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers}})}createAndRun(e,t){return this._client.post("/threads/runs",{body:e,...t,headers:{"OpenAI-Beta":"assistants=v2",...t?.headers},stream:e.stream??!1})}async createAndRunPoll(e,t){let r=await this.createAndRun(e,t);return await this.runs.poll(r.thread_id,r.id,t)}createAndRunStream(e,t){return rG.createThreadAssistantStream(e,this._client.beta.threads,t)}}r5.Runs=r8,r5.RunsPage=r6,r5.Messages=rZ,r5.MessagesPage=r0;class r3 extends tD{constructor(){super(...arguments),this.realtime=new rz(this._client),this.chat=new rH(this._client),this.assistants=new rw(this._client),this.threads=new r5(this._client)}}r3.Realtime=rz,r3.Assistants=rw,r3.AssistantsPage=rb,r3.Threads=r5;class r4 extends tD{create(e,t){return this._client.post("/batches",{body:e,...t})}retrieve(e,t){return this._client.get(`/batches/${e}`,t)}list(e={},t){return tv(e)?this.list({},e):this._client.getAPIList("/batches",r9,{query:e,...t})}cancel(e,t){return this._client.post(`/batches/${e}/cancel`,t)}}class r9 extends tX{}r4.BatchesPage=r9;class r7 extends tD{create(e,t,r){return this._client.post(`/uploads/${e}/parts`,tl({body:t,...r}))}}class se extends tD{constructor(){super(...arguments),this.parts=new r7(this._client)}create(e,t){return this._client.post("/uploads",{body:e,...t})}cancel(e,t){return this._client.post(`/uploads/${e}/cancel`,t)}complete(e,t,r){return this._client.post(`/uploads/${e}/complete`,{body:t,...r})}}function st(e,t){let r=e.output.map(e=>{if("function_call"===e.type)return{...e,parsed_arguments:function(e,t){var r,s;let n=(r=e.tools??[],s=t.name,r.find(e=>"function"===e.type&&e.name===s));return{...t,...t,parsed_arguments:n?.$brand==="auto-parseable-tool"?n.$parseRaw(t.arguments):n?.strict?JSON.parse(t.arguments):null}}(t,e)};if("message"===e.type){let r=e.content.map(e=>{var r,s;return"output_text"===e.type?{...e,parsed:(r=t,s=e.text,r.text?.format?.type!=="json_schema"?null:"$parseRaw"in r.text?.format?(r.text?.format).$parseRaw(s):JSON.parse(s))}:e});return{...e,content:r}}return e}),s=Object.assign({},e,{output:r});return Object.getOwnPropertyDescriptor(e,"output_text")||sr(s),Object.defineProperty(s,"output_parsed",{enumerable:!0,get(){for(let e of 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Context to Preserve +User preferences or style requirements +Domain-specific details that aren't obvious +Any promises made to the user +Be concise but complete—err on the side of including information that would prevent duplicate work or repeated mistakes. Write in a way that enables immediate resumption of the task. +Wrap your summary in tags.`;function rw(){let e,t;return{promise:new Promise((s,r)=>{e=s,t=r}),resolve:e,reject:t}}class r_{constructor(e,t,s){M.add(this),this.client=e,R.set(this,!1),$.set(this,!1),O.set(this,void 0),L.set(this,void 0),U.set(this,void 0),D.set(this,void 0),z.set(this,void 0),B.set(this,0),tQ(this,O,{params:{...t,messages:structuredClone(t.messages)}},"f");const r=["BetaToolRunner",...s9(t.tools,t.messages)].join(", ");tQ(this,L,{...s,headers:s1([{"x-stainless-helper":r},s?.headers])},"f"),tQ(this,z,rw(),"f"),t.compactionControl?.enabled&&console.warn('Anthropic: The `compactionControl` parameter is deprecated and will be removed in a future version. 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يكون ${t} ${i.minimum.toString()} ${r.unit}`;return`أصغر من اللازم: يفترض لـ ${i.origin} أن يكون ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`نَص غير مقبول: يجب أن يبدأ بـ "${i.prefix}"`;if("ends_with"===i.format)return`نَص غير مقبول: يجب أن ينتهي بـ "${i.suffix}"`;if("includes"===i.format)return`نَص غير مقبول: يجب أن يتضمَّن "${i.includes}"`;if("regex"===i.format)return`نَص غير مقبول: يجب أن يطابق النمط ${i.pattern}`;return`${t[i.format]??i.format} غير مقبول`;case"not_multiple_of":return`رقم غير مقبول: يجب أن يكون من مضاعفات ${i.divisor}`;case"unrecognized_keys":return`معرف${i.keys.length>1?"ات":""} غريب${i.keys.length>1?"ة":""}: ${V.joinValues(i.keys,"، ")}`;case"invalid_key":return`معرف غير مقبول في ${i.origin}`;case"invalid_union":default:return"مدخل غير مقبول";case"invalid_element":return`مدخل غير مقبول في ${i.origin}`}})}},"az",0,function(){let e,t;return{localeError:(e={string:{unit:"simvol",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"element",verb:"olmalıdır"},set:{unit:"element",verb:"olmalıdır"}},t={regex:"input",email:"email address",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datetime",date:"ISO date",time:"ISO time",duration:"ISO duration",ipv4:"IPv4 address",ipv6:"IPv6 address",cidrv4:"IPv4 range",cidrv6:"IPv6 range",base64:"base64-encoded string",base64url:"base64url-encoded string",json_string:"JSON string",e164:"E.164 number",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Yanlış dəyər: g\xf6zlənilən ${i.expected}, daxil olan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Yanlış dəyər: g\xf6zlənilən ${V.stringifyPrimitive(i.values[0])}`;return`Yanlış se\xe7im: aşağıdakılardan biri olmalıdır: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`\xc7ox b\xf6y\xfck: g\xf6zlənilən ${i.origin??"dəyər"} ${t}${i.maximum.toString()} ${r.unit??"element"}`;return`\xc7ox b\xf6y\xfck: g\xf6zlənilən ${i.origin??"dəyər"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`\xc7ox ki\xe7ik: g\xf6zlənilən ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`\xc7ox ki\xe7ik: g\xf6zlənilən ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Yanlış mətn: "${i.prefix}" ilə başlamalıdır`;if("ends_with"===i.format)return`Yanlış mətn: "${i.suffix}" ilə bitməlidir`;if("includes"===i.format)return`Yanlış mətn: "${i.includes}" daxil olmalıdır`;if("regex"===i.format)return`Yanlış mətn: ${i.pattern} şablonuna uyğun olmalıdır`;return`Yanlış ${t[i.format]??i.format}`;case"not_multiple_of":return`Yanlış ədəd: ${i.divisor} ilə b\xf6l\xfcnə bilən olmalıdır`;case"unrecognized_keys":return`Tanınmayan a\xe7ar${i.keys.length>1?"lar":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} daxilində yanlış a\xe7ar`;case"invalid_union":default:return"Yanlış dəyər";case"invalid_element":return`${i.origin} daxilində yanlış dəyər`}})}},"be",0,function(){let e,t;return{localeError:(e={string:{unit:{one:"сімвал",few:"сімвалы",many:"сімвалаў"},verb:"мець"},array:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},set:{unit:{one:"элемент",few:"элементы",many:"элементаў"},verb:"мець"},file:{unit:{one:"байт",few:"байты",many:"байтаў"},verb:"мець"}},t={regex:"увод",email:"email адрас",url:"URL",emoji:"эмодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата і час",date:"ISO дата",time:"ISO час",duration:"ISO працягласць",ipv4:"IPv4 адрас",ipv6:"IPv6 адрас",cidrv4:"IPv4 дыяпазон",cidrv6:"IPv6 дыяпазон",base64:"радок у фармаце base64",base64url:"радок у фармаце base64url",json_string:"JSON радок",e164:"нумар E.164",jwt:"JWT",template_literal:"увод"},i=>{switch(i.code){case"invalid_type":return`Няправільны ўвод: чакаўся ${i.expected}, атрымана ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"лік";case"object":if(Array.isArray(e))return"масіў";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Няправільны ўвод: чакалася ${V.stringifyPrimitive(i.values[0])}`;return`Няправільны варыянт: чакаўся адзін з ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r){let e=tE(Number(i.maximum),r.unit.one,r.unit.few,r.unit.many);return`Занадта вялікі: чакалася, што ${i.origin??"значэнне"} павінна ${r.verb} ${t}${i.maximum.toString()} ${e}`}return`Занадта вялікі: чакалася, што ${i.origin??"значэнне"} павінна быць ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r){let e=tE(Number(i.minimum),r.unit.one,r.unit.few,r.unit.many);return`Занадта малы: чакалася, што ${i.origin} павінна ${r.verb} ${t}${i.minimum.toString()} ${e}`}return`Занадта малы: чакалася, што ${i.origin} павінна быць ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Няправільны радок: павінен пачынацца з "${i.prefix}"`;if("ends_with"===i.format)return`Няправільны радок: павінен заканчвацца на "${i.suffix}"`;if("includes"===i.format)return`Няправільны радок: павінен змяшчаць "${i.includes}"`;if("regex"===i.format)return`Няправільны радок: павінен адпавядаць шаблону ${i.pattern}`;return`Няправільны ${t[i.format]??i.format}`;case"not_multiple_of":return`Няправільны лік: павінен быць кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспазнаны ${i.keys.length>1?"ключы":"ключ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Няправільны ключ у ${i.origin}`;case"invalid_union":default:return"Няправільны ўвод";case"invalid_element":return`Няправільнае значэнне ў ${i.origin}`}})}},"ca",0,function(){let e,t;return{localeError:(e={string:{unit:"caràcters",verb:"contenir"},file:{unit:"bytes",verb:"contenir"},array:{unit:"elements",verb:"contenir"},set:{unit:"elements",verb:"contenir"}},t={regex:"entrada",email:"adreça electrònica",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i hora ISO",date:"data ISO",time:"hora ISO",duration:"durada ISO",ipv4:"adreça IPv4",ipv6:"adreça IPv6",cidrv4:"rang IPv4",cidrv6:"rang IPv6",base64:"cadena codificada en base64",base64url:"cadena codificada en base64url",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipus inv\xe0lid: s'esperava ${i.expected}, s'ha rebut ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Valor inv\xe0lid: s'esperava ${V.stringifyPrimitive(i.values[0])}`;return`Opci\xf3 inv\xe0lida: s'esperava una de ${V.joinValues(i.values," o ")}`;case"too_big":{let t=i.inclusive?"com a màxim":"menys de",r=e[i.origin]??null;if(r)return`Massa gran: s'esperava que ${i.origin??"el valor"} contingu\xe9s ${t} ${i.maximum.toString()} ${r.unit??"elements"}`;return`Massa gran: s'esperava que ${i.origin??"el valor"} fos ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"com a mínim":"més de",r=e[i.origin]??null;if(r)return`Massa petit: s'esperava que ${i.origin} contingu\xe9s ${t} ${i.minimum.toString()} ${r.unit}`;return`Massa petit: s'esperava que ${i.origin} fos ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Format inv\xe0lid: ha de comen\xe7ar amb "${i.prefix}"`;if("ends_with"===i.format)return`Format inv\xe0lid: ha d'acabar amb "${i.suffix}"`;if("includes"===i.format)return`Format inv\xe0lid: ha d'incloure "${i.includes}"`;if("regex"===i.format)return`Format inv\xe0lid: ha de coincidir amb el patr\xf3 ${i.pattern}`;return`Format inv\xe0lid per a ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe0lid: ha de ser m\xfaltiple de ${i.divisor}`;case"unrecognized_keys":return`Clau${i.keys.length>1?"s":""} no reconeguda${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Clau inv\xe0lida a ${i.origin}`;case"invalid_union":default:return"Entrada invàlida";case"invalid_element":return`Element inv\xe0lid a ${i.origin}`}})}},"cs",0,function(){let e,t;return{localeError:(e={string:{unit:"znaků",verb:"mít"},file:{unit:"bajtů",verb:"mít"},array:{unit:"prvků",verb:"mít"},set:{unit:"prvků",verb:"mít"}},t={regex:"regulární výraz",email:"e-mailová adresa",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"datum a čas ve formátu ISO",date:"datum ve formátu ISO",time:"čas ve formátu ISO",duration:"doba trvání ISO",ipv4:"IPv4 adresa",ipv6:"IPv6 adresa",cidrv4:"rozsah IPv4",cidrv6:"rozsah IPv6",base64:"řetězec zakódovaný ve formátu base64",base64url:"řetězec zakódovaný ve formátu base64url",json_string:"řetězec ve formátu JSON",e164:"číslo E.164",jwt:"JWT",template_literal:"vstup"},i=>{switch(i.code){case"invalid_type":return`Neplatn\xfd vstup: oček\xe1v\xe1no ${i.expected}, obdrženo ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"číslo";case"string":return"řetězec";case"boolean":return"boolean";case"bigint":return"bigint";case"function":return"funkce";case"symbol":return"symbol";case"undefined":return"undefined";case"object":if(Array.isArray(e))return"pole";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neplatn\xfd vstup: oček\xe1v\xe1no ${V.stringifyPrimitive(i.values[0])}`;return`Neplatn\xe1 možnost: oček\xe1v\xe1na jedna z hodnot ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${t}${i.maximum.toString()} ${r.unit??"prvků"}`;return`Hodnota je př\xedliš velk\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed m\xedt ${t}${i.minimum.toString()} ${r.unit??"prvků"}`;return`Hodnota je př\xedliš mal\xe1: ${i.origin??"hodnota"} mus\xed b\xfdt ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neplatn\xfd řetězec: mus\xed zač\xednat na "${i.prefix}"`;if("ends_with"===i.format)return`Neplatn\xfd řetězec: mus\xed končit na "${i.suffix}"`;if("includes"===i.format)return`Neplatn\xfd řetězec: mus\xed obsahovat "${i.includes}"`;if("regex"===i.format)return`Neplatn\xfd řetězec: mus\xed odpov\xeddat vzoru ${i.pattern}`;return`Neplatn\xfd form\xe1t ${t[i.format]??i.format}`;case"not_multiple_of":return`Neplatn\xe9 č\xedslo: mus\xed b\xfdt n\xe1sobkem ${i.divisor}`;case"unrecognized_keys":return`Nezn\xe1m\xe9 kl\xedče: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Neplatn\xfd kl\xedč v ${i.origin}`;case"invalid_union":default:return"Neplatný vstup";case"invalid_element":return`Neplatn\xe1 hodnota v ${i.origin}`}})}},"de",0,function(){let e,t;return{localeError:(e={string:{unit:"Zeichen",verb:"zu haben"},file:{unit:"Bytes",verb:"zu haben"},array:{unit:"Elemente",verb:"zu haben"},set:{unit:"Elemente",verb:"zu haben"}},t={regex:"Eingabe",email:"E-Mail-Adresse",url:"URL",emoji:"Emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-Datum und -Uhrzeit",date:"ISO-Datum",time:"ISO-Uhrzeit",duration:"ISO-Dauer",ipv4:"IPv4-Adresse",ipv6:"IPv6-Adresse",cidrv4:"IPv4-Bereich",cidrv6:"IPv6-Bereich",base64:"Base64-codierter String",base64url:"Base64-URL-codierter String",json_string:"JSON-String",e164:"E.164-Nummer",jwt:"JWT",template_literal:"Eingabe"},i=>{switch(i.code){case"invalid_type":return`Ung\xfcltige Eingabe: erwartet ${i.expected}, erhalten ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"Zahl";case"object":if(Array.isArray(e))return"Array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ung\xfcltige Eingabe: erwartet ${V.stringifyPrimitive(i.values[0])}`;return`Ung\xfcltige Option: erwartet eine von ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${t}${i.maximum.toString()} ${r.unit??"Elemente"} hat`;return`Zu gro\xdf: erwartet, dass ${i.origin??"Wert"} ${t}${i.maximum.toString()} ist`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Zu klein: erwartet, dass ${i.origin} ${t}${i.minimum.toString()} ${r.unit} hat`;return`Zu klein: erwartet, dass ${i.origin} ${t}${i.minimum.toString()} ist`}case"invalid_format":if("starts_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ung\xfcltiger String: muss mit "${i.suffix}" enden`;if("includes"===i.format)return`Ung\xfcltiger String: muss "${i.includes}" enthalten`;if("regex"===i.format)return`Ung\xfcltiger String: muss dem Muster ${i.pattern} entsprechen`;return`Ung\xfcltig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ung\xfcltige Zahl: muss ein Vielfaches von ${i.divisor} sein`;case"unrecognized_keys":return`${i.keys.length>1?"Unbekannte Schlüssel":"Unbekannter Schlüssel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ung\xfcltiger Schl\xfcssel in ${i.origin}`;case"invalid_union":default:return"Ungültige Eingabe";case"invalid_element":return`Ung\xfcltiger Wert in ${i.origin}`}})}},"en",()=>tT.default,"eo",0,function(){let e,t;return{localeError:(e={string:{unit:"karaktrojn",verb:"havi"},file:{unit:"bajtojn",verb:"havi"},array:{unit:"elementojn",verb:"havi"},set:{unit:"elementojn",verb:"havi"}},t={regex:"enigo",email:"retadreso",url:"URL",emoji:"emoĝio",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datotempo",date:"ISO-dato",time:"ISO-tempo",duration:"ISO-daŭro",ipv4:"IPv4-adreso",ipv6:"IPv6-adreso",cidrv4:"IPv4-rango",cidrv6:"IPv6-rango",base64:"64-ume kodita karaktraro",base64url:"URL-64-ume kodita karaktraro",json_string:"JSON-karaktraro",e164:"E.164-nombro",jwt:"JWT",template_literal:"enigo"},i=>{switch(i.code){case"invalid_type":return`Nevalida enigo: atendiĝis ${i.expected}, riceviĝis ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombro";case"object":if(Array.isArray(e))return"tabelo";if(null===e)return"senvalora";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nevalida enigo: atendiĝis ${V.stringifyPrimitive(i.values[0])}`;return`Nevalida opcio: atendiĝis unu el ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${t}${i.maximum.toString()} ${r.unit??"elementojn"}`;return`Tro granda: atendiĝis ke ${i.origin??"valoro"} havu ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Tro malgranda: atendiĝis ke ${i.origin} havu ${t}${i.minimum.toString()} ${r.unit}`;return`Tro malgranda: atendiĝis ke ${i.origin} estu ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nevalida karaktraro: devas komenciĝi per "${i.prefix}"`;if("ends_with"===i.format)return`Nevalida karaktraro: devas finiĝi per "${i.suffix}"`;if("includes"===i.format)return`Nevalida karaktraro: devas inkluzivi "${i.includes}"`;if("regex"===i.format)return`Nevalida karaktraro: devas kongrui kun la modelo ${i.pattern}`;return`Nevalida ${t[i.format]??i.format}`;case"not_multiple_of":return`Nevalida nombro: devas esti oblo de ${i.divisor}`;case"unrecognized_keys":return`Nekonata${i.keys.length>1?"j":""} ŝlosilo${i.keys.length>1?"j":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Nevalida ŝlosilo en ${i.origin}`;case"invalid_union":default:return"Nevalida enigo";case"invalid_element":return`Nevalida valoro en ${i.origin}`}})}},"es",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"tener"},file:{unit:"bytes",verb:"tener"},array:{unit:"elementos",verb:"tener"},set:{unit:"elementos",verb:"tener"}},t={regex:"entrada",email:"dirección de correo electrónico",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"fecha y hora ISO",date:"fecha ISO",time:"hora ISO",duration:"duración ISO",ipv4:"dirección IPv4",ipv6:"dirección IPv6",cidrv4:"rango IPv4",cidrv6:"rango IPv6",base64:"cadena codificada en base64",base64url:"URL codificada en base64",json_string:"cadena JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Entrada inv\xe1lida: se esperaba ${i.expected}, recibido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"arreglo";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: se esperaba ${V.stringifyPrimitive(i.values[0])}`;return`Opci\xf3n inv\xe1lida: se esperaba una de ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Demasiado grande: se esperaba que ${i.origin??"valor"} tuviera ${t}${i.maximum.toString()} ${r.unit??"elementos"}`;return`Demasiado grande: se esperaba que ${i.origin??"valor"} fuera ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Demasiado peque\xf1o: se esperaba que ${i.origin} tuviera ${t}${i.minimum.toString()} ${r.unit}`;return`Demasiado peque\xf1o: se esperaba que ${i.origin} fuera ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cadena inv\xe1lida: debe comenzar con "${i.prefix}"`;if("ends_with"===i.format)return`Cadena inv\xe1lida: debe terminar en "${i.suffix}"`;if("includes"===i.format)return`Cadena inv\xe1lida: debe incluir "${i.includes}"`;if("regex"===i.format)return`Cadena inv\xe1lida: debe coincidir con el patr\xf3n ${i.pattern}`;return`Inv\xe1lido ${t[i.format]??i.format}`;case"not_multiple_of":return`N\xfamero inv\xe1lido: debe ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Llave${i.keys.length>1?"s":""} desconocida${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Llave inv\xe1lida en ${i.origin}`;case"invalid_union":default:return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido en ${i.origin}`}})}},"fa",0,function(){let e,t;return{localeError:(e={string:{unit:"کاراکتر",verb:"داشته باشد"},file:{unit:"بایت",verb:"داشته باشد"},array:{unit:"آیتم",verb:"داشته باشد"},set:{unit:"آیتم",verb:"داشته باشد"}},t={regex:"ورودی",email:"آدرس ایمیل",url:"URL",emoji:"ایموجی",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"تاریخ و زمان ایزو",date:"تاریخ ایزو",time:"زمان ایزو",duration:"مدت زمان ایزو",ipv4:"IPv4 آدرس",ipv6:"IPv6 آدرس",cidrv4:"IPv4 دامنه",cidrv6:"IPv6 دامنه",base64:"base64-encoded رشته",base64url:"base64url-encoded رشته",json_string:"JSON رشته",e164:"E.164 عدد",jwt:"JWT",template_literal:"ورودی"},i=>{switch(i.code){case"invalid_type":return`ورودی نامعتبر: می‌بایست ${i.expected} می‌بود، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"آرایه";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} دریافت شد`;case"invalid_value":if(1===i.values.length)return`ورودی نامعتبر: می‌بایست ${V.stringifyPrimitive(i.values[0])} می‌بود`;return`گزینه نامعتبر: می‌بایست یکی از ${V.joinValues(i.values,"|")} می‌بود`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصر"} باشد`;return`خیلی بزرگ: ${i.origin??"مقدار"} باید ${t}${i.maximum.toString()} باشد`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`خیلی کوچک: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} باشد`;return`خیلی کوچک: ${i.origin} باید ${t}${i.minimum.toString()} باشد`}case"invalid_format":if("starts_with"===i.format)return`رشته نامعتبر: باید با "${i.prefix}" شروع شود`;if("ends_with"===i.format)return`رشته نامعتبر: باید با "${i.suffix}" تمام شود`;if("includes"===i.format)return`رشته نامعتبر: باید شامل "${i.includes}" باشد`;if("regex"===i.format)return`رشته نامعتبر: باید با الگوی ${i.pattern} مطابقت داشته باشد`;return`${t[i.format]??i.format} نامعتبر`;case"not_multiple_of":return`عدد نامعتبر: باید مضرب ${i.divisor} باشد`;case"unrecognized_keys":return`کلید${i.keys.length>1?"های":""} ناشناس: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`کلید ناشناس در ${i.origin}`;case"invalid_union":default:return"ورودی نامعتبر";case"invalid_element":return`مقدار نامعتبر در ${i.origin}`}})}},"fi",0,function(){let e,t;return{localeError:(e={string:{unit:"merkkiä",subject:"merkkijonon"},file:{unit:"tavua",subject:"tiedoston"},array:{unit:"alkiota",subject:"listan"},set:{unit:"alkiota",subject:"joukon"},number:{unit:"",subject:"luvun"},bigint:{unit:"",subject:"suuren kokonaisluvun"},int:{unit:"",subject:"kokonaisluvun"},date:{unit:"",subject:"päivämäärän"}},t={regex:"säännöllinen lauseke",email:"sähköpostiosoite",url:"URL-osoite",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-aikaleima",date:"ISO-päivämäärä",time:"ISO-aika",duration:"ISO-kesto",ipv4:"IPv4-osoite",ipv6:"IPv6-osoite",cidrv4:"IPv4-alue",cidrv6:"IPv6-alue",base64:"base64-koodattu merkkijono",base64url:"base64url-koodattu merkkijono",json_string:"JSON-merkkijono",e164:"E.164-luku",jwt:"JWT",template_literal:"templaattimerkkijono"},i=>{switch(i.code){case"invalid_type":return`Virheellinen tyyppi: odotettiin ${i.expected}, oli ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Virheellinen sy\xf6te: t\xe4ytyy olla ${V.stringifyPrimitive(i.values[0])}`;return`Virheellinen valinta: t\xe4ytyy olla yksi seuraavista: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Liian suuri: ${r.subject} t\xe4ytyy olla ${t}${i.maximum.toString()} ${r.unit}`.trim();return`Liian suuri: arvon t\xe4ytyy olla ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Liian pieni: ${r.subject} t\xe4ytyy olla ${t}${i.minimum.toString()} ${r.unit}`.trim();return`Liian pieni: arvon t\xe4ytyy olla ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy alkaa "${i.prefix}"`;if("ends_with"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy loppua "${i.suffix}"`;if("includes"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy sis\xe4lt\xe4\xe4 "${i.includes}"`;if("regex"===i.format)return`Virheellinen sy\xf6te: t\xe4ytyy vastata s\xe4\xe4nn\xf6llist\xe4 lauseketta ${i.pattern}`;return`Virheellinen ${t[i.format]??i.format}`;case"not_multiple_of":return`Virheellinen luku: t\xe4ytyy olla luvun ${i.divisor} monikerta`;case"unrecognized_keys":return`${i.keys.length>1?"Tuntemattomat avaimet":"Tuntematon avain"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return"Virheellinen avain tietueessa";case"invalid_union":return"Virheellinen unioni";case"invalid_element":return"Virheellinen arvo joukossa";default:return"Virheellinen syöte"}})}},"fr",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"date et heure ISO",date:"date ISO",time:"heure ISO",duration:"durée ISO",ipv4:"adresse IPv4",ipv6:"adresse IPv6",cidrv4:"plage IPv4",cidrv6:"plage IPv6",base64:"chaîne encodée en base64",base64url:"chaîne encodée en base64url",json_string:"chaîne JSON",e164:"numéro E.164",jwt:"JWT",template_literal:"entrée"},i=>{switch(i.code){case"invalid_type":return`Entr\xe9e invalide : ${i.expected} attendu, ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombre";case"object":if(Array.isArray(e))return"tableau";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} re\xe7u`;case"invalid_value":if(1===i.values.length)return`Entr\xe9e invalide : ${V.stringifyPrimitive(i.values[0])} attendu`;return`Option invalide : une valeur parmi ${V.joinValues(i.values,"|")} attendue`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Trop grand : ${i.origin??"valeur"} doit ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"élément(s)"}`;return`Trop grand : ${i.origin??"valeur"} doit \xeatre ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Trop petit : ${i.origin} doit ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : ${i.origin} doit \xeatre ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au mod\xe8le ${i.pattern}`;return`${t[i.format]??i.format} invalide`;case"not_multiple_of":return`Nombre invalide : doit \xeatre un multiple de ${i.divisor}`;case"unrecognized_keys":return`Cl\xe9${i.keys.length>1?"s":""} non reconnue${i.keys.length>1?"s":""} : ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Cl\xe9 invalide dans ${i.origin}`;case"invalid_union":default:return"Entrée invalide";case"invalid_element":return`Valeur invalide dans ${i.origin}`}})}},"frCA",0,function(){let e,t;return{localeError:(e={string:{unit:"caractères",verb:"avoir"},file:{unit:"octets",verb:"avoir"},array:{unit:"éléments",verb:"avoir"},set:{unit:"éléments",verb:"avoir"}},t={regex:"entrée",email:"adresse 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l'une des valeurs suivantes ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"≤":"<",r=e[i.origin]??null;if(r)return`Trop grand : attendu que ${i.origin??"la valeur"} ait ${t}${i.maximum.toString()} ${r.unit}`;return`Trop grand : attendu que ${i.origin??"la valeur"} soit ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?"≥":">",r=e[i.origin]??null;if(r)return`Trop petit : attendu que ${i.origin} ait ${t}${i.minimum.toString()} ${r.unit}`;return`Trop petit : attendu que ${i.origin} soit ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Cha\xeene invalide : doit commencer par "${i.prefix}"`;if("ends_with"===i.format)return`Cha\xeene invalide : doit se terminer par "${i.suffix}"`;if("includes"===i.format)return`Cha\xeene invalide : doit inclure "${i.includes}"`;if("regex"===i.format)return`Cha\xeene invalide : doit correspondre au motif ${i.pattern}`;return`${t[i.format]??i.format} 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${t}${i.minimum.toString()} ${r.unit}`;return`קטן מדי: ${i.origin} צריך להיות ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`מחרוזת לא תקינה: חייבת להתחיל ב"${i.prefix}"`;if("ends_with"===i.format)return`מחרוזת לא תקינה: חייבת להסתיים ב "${i.suffix}"`;if("includes"===i.format)return`מחרוזת לא תקינה: חייבת לכלול "${i.includes}"`;if("regex"===i.format)return`מחרוזת לא תקינה: חייבת להתאים לתבנית ${i.pattern}`;return`${t[i.format]??i.format} לא תקין`;case"not_multiple_of":return`מספר לא תקין: חייב להיות מכפלה של ${i.divisor}`;case"unrecognized_keys":return`מפתח${i.keys.length>1?"ות":""} לא מזוה${i.keys.length>1?"ים":"ה"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`מפתח לא תקין ב${i.origin}`;case"invalid_union":default:return"קלט לא תקין";case"invalid_element":return`ערך לא תקין ב${i.origin}`}})}},"hu",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"legyen"},file:{unit:"byte",verb:"legyen"},array:{unit:"elem",verb:"legyen"},set:{unit:"elem",verb:"legyen"}},t={regex:"bemenet",email:"email cím",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO időbélyeg",date:"ISO dátum",time:"ISO idő",duration:"ISO időintervallum",ipv4:"IPv4 cím",ipv6:"IPv6 cím",cidrv4:"IPv4 tartomány",cidrv6:"IPv6 tartomány",base64:"base64-kódolt string",base64url:"base64url-kódolt string",json_string:"JSON string",e164:"E.164 szám",jwt:"JWT",template_literal:"bemenet"},i=>{switch(i.code){case"invalid_type":return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${i.expected}, a kapott \xe9rt\xe9k ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"szám";case"object":if(Array.isArray(e))return"tömb";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`\xc9rv\xe9nytelen bemenet: a v\xe1rt \xe9rt\xe9k ${V.stringifyPrimitive(i.values[0])}`;return`\xc9rv\xe9nytelen opci\xf3: valamelyik \xe9rt\xe9k v\xe1rt ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`T\xfal nagy: ${i.origin??"érték"} m\xe9rete t\xfal nagy ${t}${i.maximum.toString()} ${r.unit??"elem"}`;return`T\xfal nagy: a bemeneti \xe9rt\xe9k ${i.origin??"érték"} t\xfal nagy: ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} m\xe9rete t\xfal kicsi ${t}${i.minimum.toString()} ${r.unit}`;return`T\xfal kicsi: a bemeneti \xe9rt\xe9k ${i.origin} t\xfal kicsi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.prefix}" \xe9rt\xe9kkel kell kezdődnie`;if("ends_with"===i.format)return`\xc9rv\xe9nytelen string: "${i.suffix}" \xe9rt\xe9kkel kell v\xe9gződnie`;if("includes"===i.format)return`\xc9rv\xe9nytelen string: "${i.includes}" \xe9rt\xe9ket kell tartalmaznia`;if("regex"===i.format)return`\xc9rv\xe9nytelen string: ${i.pattern} mint\xe1nak kell megfelelnie`;return`\xc9rv\xe9nytelen ${t[i.format]??i.format}`;case"not_multiple_of":return`\xc9rv\xe9nytelen sz\xe1m: ${i.divisor} t\xf6bbsz\xf6r\xf6s\xe9nek kell lennie`;case"unrecognized_keys":return`Ismeretlen kulcs${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`\xc9rv\xe9nytelen kulcs ${i.origin}`;case"invalid_union":default:return"Érvénytelen bemenet";case"invalid_element":return`\xc9rv\xe9nytelen \xe9rt\xe9k: ${i.origin}`}})}},"id",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"memiliki"},file:{unit:"byte",verb:"memiliki"},array:{unit:"item",verb:"memiliki"},set:{unit:"item",verb:"memiliki"}},t={regex:"input",email:"alamat email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tanggal dan waktu format ISO",date:"tanggal format ISO",time:"jam format ISO",duration:"durasi format ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"rentang alamat IPv4",cidrv6:"rentang alamat IPv6",base64:"string dengan enkode base64",base64url:"string dengan enkode base64url",json_string:"string JSON",e164:"angka E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak valid: diharapkan ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak valid: diharapkan ${V.stringifyPrimitive(i.values[0])}`;return`Pilihan tidak valid: diharapkan salah satu dari ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: diharapkan ${i.origin??"value"} memiliki ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: diharapkan ${i.origin??"value"} menjadi ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: diharapkan ${i.origin} memiliki ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: diharapkan ${i.origin} menjadi ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak valid: harus dimulai dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak valid: harus berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak valid: harus menyertakan "${i.includes}"`;if("regex"===i.format)return`String tidak valid: harus sesuai pola ${i.pattern}`;return`${t[i.format]??i.format} tidak valid`;case"not_multiple_of":return`Angka tidak valid: harus kelipatan dari ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali ${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kunci tidak valid di ${i.origin}`;case"invalid_union":default:return"Input tidak valid";case"invalid_element":return`Nilai tidak valid di ${i.origin}`}})}},"it",0,function(){let e,t;return{localeError:(e={string:{unit:"caratteri",verb:"avere"},file:{unit:"byte",verb:"avere"},array:{unit:"elementi",verb:"avere"},set:{unit:"elementi",verb:"avere"}},t={regex:"input",email:"indirizzo email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e ora ISO",date:"data ISO",time:"ora ISO",duration:"durata ISO",ipv4:"indirizzo IPv4",ipv6:"indirizzo IPv6",cidrv4:"intervallo IPv4",cidrv6:"intervallo IPv6",base64:"stringa codificata in base64",base64url:"URL codificata in base64",json_string:"stringa JSON",e164:"numero E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input non valido: atteso ${i.expected}, ricevuto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numero";case"object":if(Array.isArray(e))return"vettore";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input non valido: atteso ${V.stringifyPrimitive(i.values[0])}`;return`Opzione non valida: atteso uno tra ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Troppo grande: ${i.origin??"valore"} deve avere ${t}${i.maximum.toString()} ${r.unit??"elementi"}`;return`Troppo grande: ${i.origin??"valore"} deve essere ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Troppo piccolo: ${i.origin} deve avere ${t}${i.minimum.toString()} ${r.unit}`;return`Troppo piccolo: ${i.origin} deve essere ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Stringa non valida: deve iniziare con "${i.prefix}"`;if("ends_with"===i.format)return`Stringa non valida: deve terminare con "${i.suffix}"`;if("includes"===i.format)return`Stringa non valida: deve includere "${i.includes}"`;if("regex"===i.format)return`Stringa non valida: deve corrispondere al pattern ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Numero non valido: deve essere un multiplo di ${i.divisor}`;case"unrecognized_keys":return`Chiav${i.keys.length>1?"i":"e"} non riconosciut${i.keys.length>1?"e":"a"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Chiave non valida in ${i.origin}`;case"invalid_union":default:return"Input non valido";case"invalid_element":return`Valore non valido in ${i.origin}`}})}},"ja",0,function(){let e,t;return{localeError:(e={string:{unit:"文字",verb:"である"},file:{unit:"バイト",verb:"である"},array:{unit:"要素",verb:"である"},set:{unit:"要素",verb:"である"}},t={regex:"入力値",email:"メールアドレス",url:"URL",emoji:"絵文字",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO日時",date:"ISO日付",time:"ISO時刻",duration:"ISO期間",ipv4:"IPv4アドレス",ipv6:"IPv6アドレス",cidrv4:"IPv4範囲",cidrv6:"IPv6範囲",base64:"base64エンコード文字列",base64url:"base64urlエンコード文字列",json_string:"JSON文字列",e164:"E.164番号",jwt:"JWT",template_literal:"入力値"},i=>{switch(i.code){case"invalid_type":return`無効な入力: ${i.expected}が期待されましたが、${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"数値";case"object":if(Array.isArray(e))return"配列";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}が入力されました`;case"invalid_value":if(1===i.values.length)return`無効な入力: ${V.stringifyPrimitive(i.values[0])}が期待されました`;return`無効な選択: ${V.joinValues(i.values,"、")}のいずれかである必要があります`;case"too_big":{let t=i.inclusive?"以下である":"より小さい",r=e[i.origin]??null;if(r)return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${r.unit??"要素"}${t}必要があります`;return`大きすぎる値: ${i.origin??"値"}は${i.maximum.toString()}${t}必要があります`}case"too_small":{let t=i.inclusive?"以上である":"より大きい",r=e[i.origin]??null;if(r)return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${r.unit}${t}必要があります`;return`小さすぎる値: ${i.origin}は${i.minimum.toString()}${t}必要があります`}case"invalid_format":if("starts_with"===i.format)return`無効な文字列: "${i.prefix}"で始まる必要があります`;if("ends_with"===i.format)return`無効な文字列: "${i.suffix}"で終わる必要があります`;if("includes"===i.format)return`無効な文字列: "${i.includes}"を含む必要があります`;if("regex"===i.format)return`無効な文字列: パターン${i.pattern}に一致する必要があります`;return`無効な${t[i.format]??i.format}`;case"not_multiple_of":return`無効な数値: ${i.divisor}の倍数である必要があります`;case"unrecognized_keys":return`認識されていないキー${i.keys.length>1?"群":""}: ${V.joinValues(i.keys,"、")}`;case"invalid_key":return`${i.origin}内の無効なキー`;case"invalid_union":default:return"無効な入力";case"invalid_element":return`${i.origin}内の無効な値`}})}},"kh",0,function(){let e,t;return{localeError:(e={string:{unit:"តួអក្សរ",verb:"គួរមាន"},file:{unit:"បៃ",verb:"គួរមាន"},array:{unit:"ធាតុ",verb:"គួរមាន"},set:{unit:"ធាតុ",verb:"គួរមាន"}},t={regex:"ទិន្នន័យបញ្ចូល",email:"អាសយដ្ឋានអ៊ីមែល",url:"URL",emoji:"សញ្ញាអារម្មណ៍",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"កាលបរិច្ឆេទ និងម៉ោង ISO",date:"កាលបរិច្ឆេទ ISO",time:"ម៉ោង ISO",duration:"រយៈពេល ISO",ipv4:"អាសយដ្ឋាន IPv4",ipv6:"អាសយដ្ឋាន IPv6",cidrv4:"ដែនអាសយដ្ឋាន IPv4",cidrv6:"ដែនអាសយដ្ឋាន IPv6",base64:"ខ្សែអក្សរអ៊ិកូដ base64",base64url:"ខ្សែអក្សរអ៊ិកូដ base64url",json_string:"ខ្សែអក្សរ JSON",e164:"លេខ E.164",jwt:"JWT",template_literal:"ទិន្នន័យបញ្ចូល"},i=>{switch(i.code){case"invalid_type":return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${i.expected} ប៉ុន្តែទទួលបាន ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"មិនមែនជាលេខ (NaN)":"លេខ";case"object":if(Array.isArray(e))return"អារេ (Array)";if(null===e)return"គ្មានតម្លៃ (null)";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`ទិន្នន័យបញ្ចូលមិនត្រឹមត្រូវ៖ ត្រូវការ ${V.stringifyPrimitive(i.values[0])}`;return`ជម្រើសមិនត្រឹមត្រូវ៖ ត្រូវជាមួយក្នុងចំណោម ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()} ${r.unit??"ធាតុ"}`;return`ធំពេក៖ ត្រូវការ ${i.origin??"តម្លៃ"} ${t} ${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()} ${r.unit}`;return`តូចពេក៖ ត្រូវការ ${i.origin} ${t} ${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវចាប់ផ្តើមដោយ "${i.prefix}"`;if("ends_with"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវបញ្ចប់ដោយ "${i.suffix}"`;if("includes"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវមាន "${i.includes}"`;if("regex"===i.format)return`ខ្សែអក្សរមិនត្រឹមត្រូវ៖ ត្រូវតែផ្គូផ្គងនឹងទម្រង់ដែលបានកំណត់ ${i.pattern}`;return`មិនត្រឹមត្រូវ៖ ${t[i.format]??i.format}`;case"not_multiple_of":return`លេខមិនត្រឹមត្រូវ៖ ត្រូវតែជាពហុគុណនៃ ${i.divisor}`;case"unrecognized_keys":return`រកឃើញសោមិនស្គាល់៖ ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`សោមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`;case"invalid_union":default:return"ទិន្នន័យមិនត្រឹមត្រូវ";case"invalid_element":return`ទិន្នន័យមិនត្រឹមត្រូវនៅក្នុង ${i.origin}`}})}},"ko",0,function(){let e,t;return{localeError:(e={string:{unit:"문자",verb:"to have"},file:{unit:"바이트",verb:"to have"},array:{unit:"개",verb:"to have"},set:{unit:"개",verb:"to have"}},t={regex:"입력",email:"이메일 주소",url:"URL",emoji:"이모지",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO 날짜시간",date:"ISO 날짜",time:"ISO 시간",duration:"ISO 기간",ipv4:"IPv4 주소",ipv6:"IPv6 주소",cidrv4:"IPv4 범위",cidrv6:"IPv6 범위",base64:"base64 인코딩 문자열",base64url:"base64url 인코딩 문자열",json_string:"JSON 문자열",e164:"E.164 번호",jwt:"JWT",template_literal:"입력"},i=>{switch(i.code){case"invalid_type":return`잘못된 입력: 예상 타입은 ${i.expected}, 받은 타입은 ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}입니다`;case"invalid_value":if(1===i.values.length)return`잘못된 입력: 값은 ${V.stringifyPrimitive(i.values[0])} 이어야 합니다`;return`잘못된 옵션: ${V.joinValues(i.values,"또는 ")} 중 하나여야 합니다`;case"too_big":{let t=i.inclusive?"이하":"미만",r="미만"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 큽니다: ${i.maximum.toString()} ${t}${r}`}case"too_small":{let t=i.inclusive?"이상":"초과",r="이상"===t?"이어야 합니다":"여야 합니다",n=e[i.origin]??null,a=n?.unit??"요소";if(n)return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()}${a} ${t}${r}`;return`${i.origin??"값"}이 너무 작습니다: ${i.minimum.toString()} ${t}${r}`}case"invalid_format":if("starts_with"===i.format)return`잘못된 문자열: "${i.prefix}"(으)로 시작해야 합니다`;if("ends_with"===i.format)return`잘못된 문자열: "${i.suffix}"(으)로 끝나야 합니다`;if("includes"===i.format)return`잘못된 문자열: "${i.includes}"을(를) 포함해야 합니다`;if("regex"===i.format)return`잘못된 문자열: 정규식 ${i.pattern} 패턴과 일치해야 합니다`;return`잘못된 ${t[i.format]??i.format}`;case"not_multiple_of":return`잘못된 숫자: ${i.divisor}의 배수여야 합니다`;case"unrecognized_keys":return`인식할 수 없는 키: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`잘못된 키: ${i.origin}`;case"invalid_union":default:return"잘못된 입력";case"invalid_element":return`잘못된 값: ${i.origin}`}})}},"mk",0,function(){let e,t;return{localeError:(e={string:{unit:"знаци",verb:"да имаат"},file:{unit:"бајти",verb:"да имаат"},array:{unit:"ставки",verb:"да имаат"},set:{unit:"ставки",verb:"да имаат"}},t={regex:"внес",email:"адреса на е-пошта",url:"URL",emoji:"емоџи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO датум и време",date:"ISO датум",time:"ISO време",duration:"ISO времетраење",ipv4:"IPv4 адреса",ipv6:"IPv6 адреса",cidrv4:"IPv4 опсег",cidrv6:"IPv6 опсег",base64:"base64-енкодирана низа",base64url:"base64url-енкодирана низа",json_string:"JSON низа",e164:"E.164 број",jwt:"JWT",template_literal:"внес"},i=>{switch(i.code){case"invalid_type":return`Грешен внес: се очекува ${i.expected}, примено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"број";case"object":if(Array.isArray(e))return"низа";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Invalid input: expected ${V.stringifyPrimitive(i.values[0])}`;return`Грешана опција: се очекува една ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Премногу голем: се очекува ${i.origin??"вредноста"} да има ${t}${i.maximum.toString()} ${r.unit??"елементи"}`;return`Премногу голем: се очекува ${i.origin??"вредноста"} да биде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Премногу мал: се очекува ${i.origin} да има ${t}${i.minimum.toString()} ${r.unit}`;return`Премногу мал: се очекува ${i.origin} да биде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неважечка низа: мора да започнува со "${i.prefix}"`;if("ends_with"===i.format)return`Неважечка низа: мора да завршува со "${i.suffix}"`;if("includes"===i.format)return`Неважечка низа: мора да вклучува "${i.includes}"`;if("regex"===i.format)return`Неважечка низа: мора да одгоара на патернот ${i.pattern}`;return`Invalid ${t[i.format]??i.format}`;case"not_multiple_of":return`Грешен број: мора да биде делив со ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Непрепознаени клучеви":"Непрепознаен клуч"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Грешен клуч во ${i.origin}`;case"invalid_union":default:return"Грешен внес";case"invalid_element":return`Грешна вредност во ${i.origin}`}})}},"ms",0,function(){let e,t;return{localeError:(e={string:{unit:"aksara",verb:"mempunyai"},file:{unit:"bait",verb:"mempunyai"},array:{unit:"elemen",verb:"mempunyai"},set:{unit:"elemen",verb:"mempunyai"}},t={regex:"input",email:"alamat e-mel",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"tarikh masa ISO",date:"tarikh ISO",time:"masa ISO",duration:"tempoh ISO",ipv4:"alamat IPv4",ipv6:"alamat IPv6",cidrv4:"julat IPv4",cidrv6:"julat IPv6",base64:"string dikodkan base64",base64url:"string dikodkan base64url",json_string:"string JSON",e164:"nombor E.164",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Input tidak sah: dijangka ${i.expected}, diterima ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"nombor";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Input tidak sah: dijangka ${V.stringifyPrimitive(i.values[0])}`;return`Pilihan tidak sah: dijangka salah satu daripada ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Terlalu besar: dijangka ${i.origin??"nilai"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"elemen"}`;return`Terlalu besar: dijangka ${i.origin??"nilai"} adalah ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Terlalu kecil: dijangka ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Terlalu kecil: dijangka ${i.origin} adalah ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`String tidak sah: mesti bermula dengan "${i.prefix}"`;if("ends_with"===i.format)return`String tidak sah: mesti berakhir dengan "${i.suffix}"`;if("includes"===i.format)return`String tidak sah: mesti mengandungi "${i.includes}"`;if("regex"===i.format)return`String tidak sah: mesti sepadan dengan corak ${i.pattern}`;return`${t[i.format]??i.format} tidak sah`;case"not_multiple_of":return`Nombor tidak sah: perlu gandaan ${i.divisor}`;case"unrecognized_keys":return`Kunci tidak dikenali: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Kunci tidak sah dalam ${i.origin}`;case"invalid_union":default:return"Input tidak sah";case"invalid_element":return`Nilai tidak sah dalam ${i.origin}`}})}},"nl",0,function(){let e,t;return{localeError:(e={string:{unit:"tekens"},file:{unit:"bytes"},array:{unit:"elementen"},set:{unit:"elementen"}},t={regex:"invoer",email:"emailadres",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum en tijd",date:"ISO datum",time:"ISO tijd",duration:"ISO duur",ipv4:"IPv4-adres",ipv6:"IPv6-adres",cidrv4:"IPv4-bereik",cidrv6:"IPv6-bereik",base64:"base64-gecodeerde tekst",base64url:"base64 URL-gecodeerde tekst",json_string:"JSON string",e164:"E.164-nummer",jwt:"JWT",template_literal:"invoer"},i=>{switch(i.code){case"invalid_type":return`Ongeldige invoer: verwacht ${i.expected}, ontving ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"getal";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ongeldige invoer: verwacht ${V.stringifyPrimitive(i.values[0])}`;return`Ongeldige optie: verwacht \xe9\xe9n van ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} ${r.unit??"elementen"} bevat`;return`Te lang: verwacht dat ${i.origin??"waarde"} ${t}${i.maximum.toString()} is`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} ${r.unit} bevat`;return`Te kort: verwacht dat ${i.origin} ${t}${i.minimum.toString()} is`}case"invalid_format":if("starts_with"===i.format)return`Ongeldige tekst: moet met "${i.prefix}" beginnen`;if("ends_with"===i.format)return`Ongeldige tekst: moet op "${i.suffix}" eindigen`;if("includes"===i.format)return`Ongeldige tekst: moet "${i.includes}" bevatten`;if("regex"===i.format)return`Ongeldige tekst: moet overeenkomen met patroon ${i.pattern}`;return`Ongeldig: ${t[i.format]??i.format}`;case"not_multiple_of":return`Ongeldig getal: moet een veelvoud van ${i.divisor} zijn`;case"unrecognized_keys":return`Onbekende key${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ongeldige key in ${i.origin}`;case"invalid_union":default:return"Ongeldige invoer";case"invalid_element":return`Ongeldige waarde in ${i.origin}`}})}},"no",0,function(){let e,t;return{localeError:(e={string:{unit:"tegn",verb:"å ha"},file:{unit:"bytes",verb:"å ha"},array:{unit:"elementer",verb:"å inneholde"},set:{unit:"elementer",verb:"å inneholde"}},t={regex:"input",email:"e-postadresse",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO dato- og klokkeslett",date:"ISO-dato",time:"ISO-klokkeslett",duration:"ISO-varighet",ipv4:"IPv4-område",ipv6:"IPv6-område",cidrv4:"IPv4-spekter",cidrv6:"IPv6-spekter",base64:"base64-enkodet streng",base64url:"base64url-enkodet streng",json_string:"JSON-streng",e164:"E.164-nummer",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`Ugyldig input: forventet ${i.expected}, fikk ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"tall";case"object":if(Array.isArray(e))return"liste";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ugyldig verdi: forventet ${V.stringifyPrimitive(i.values[0])}`;return`Ugyldig valg: forventet en av ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()} ${r.unit??"elementer"}`;return`For stor(t): forventet ${i.origin??"value"} til \xe5 ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()} ${r.unit}`;return`For lite(n): forventet ${i.origin} til \xe5 ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ugyldig streng: m\xe5 starte med "${i.prefix}"`;if("ends_with"===i.format)return`Ugyldig streng: m\xe5 ende med "${i.suffix}"`;if("includes"===i.format)return`Ugyldig streng: m\xe5 inneholde "${i.includes}"`;if("regex"===i.format)return`Ugyldig streng: m\xe5 matche m\xf8nsteret ${i.pattern}`;return`Ugyldig ${t[i.format]??i.format}`;case"not_multiple_of":return`Ugyldig tall: m\xe5 v\xe6re et multiplum av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Ukjente nøkler":"Ukjent nøkkel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ugyldig n\xf8kkel i ${i.origin}`;case"invalid_union":default:return"Ugyldig input";case"invalid_element":return`Ugyldig verdi i ${i.origin}`}})}},"ota",0,function(){let e,t;return{localeError:(e={string:{unit:"harf",verb:"olmalıdır"},file:{unit:"bayt",verb:"olmalıdır"},array:{unit:"unsur",verb:"olmalıdır"},set:{unit:"unsur",verb:"olmalıdır"}},t={regex:"giren",email:"epostagâh",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO hengâmı",date:"ISO tarihi",time:"ISO zamanı",duration:"ISO müddeti",ipv4:"IPv4 nişânı",ipv6:"IPv6 nişânı",cidrv4:"IPv4 menzili",cidrv6:"IPv6 menzili",base64:"base64-şifreli metin",base64url:"base64url-şifreli metin",json_string:"JSON metin",e164:"E.164 sayısı",jwt:"JWT",template_literal:"giren"},i=>{switch(i.code){case"invalid_type":return`F\xe2sit giren: umulan ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"numara";case"object":if(Array.isArray(e))return"saf";if(null===e)return"gayb";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`F\xe2sit giren: umulan ${V.stringifyPrimitive(i.values[0])}`;return`F\xe2sit tercih: m\xfbteberler ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} ${r.unit??"elements"} sahip olmalıydı.`;return`Fazla b\xfcy\xfck: ${i.origin??"value"}, ${t}${i.maximum.toString()} olmalıydı.`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} ${r.unit} sahip olmalıydı.`;return`Fazla k\xfc\xe7\xfck: ${i.origin}, ${t}${i.minimum.toString()} olmalıydı.`}case"invalid_format":if("starts_with"===i.format)return`F\xe2sit metin: "${i.prefix}" ile başlamalı.`;if("ends_with"===i.format)return`F\xe2sit metin: "${i.suffix}" ile bitmeli.`;if("includes"===i.format)return`F\xe2sit metin: "${i.includes}" ihtiv\xe2 etmeli.`;if("regex"===i.format)return`F\xe2sit metin: ${i.pattern} nakşına uymalı.`;return`F\xe2sit ${t[i.format]??i.format}`;case"not_multiple_of":return`F\xe2sit sayı: ${i.divisor} katı olmalıydı.`;case"unrecognized_keys":return`Tanınmayan anahtar ${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7in tanınmayan anahtar var.`;case"invalid_union":return"Giren tanınamadı.";case"invalid_element":return`${i.origin} i\xe7in tanınmayan kıymet var.`;default:return"Kıymet tanınamadı."}})}},"pl",0,function(){let e,t;return{localeError:(e={string:{unit:"znaków",verb:"mieć"},file:{unit:"bajtów",verb:"mieć"},array:{unit:"elementów",verb:"mieć"},set:{unit:"elementów",verb:"mieć"}},t={regex:"wyrażenie",email:"adres email",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data i godzina w formacie ISO",date:"data w formacie ISO",time:"godzina w formacie ISO",duration:"czas trwania ISO",ipv4:"adres IPv4",ipv6:"adres IPv6",cidrv4:"zakres IPv4",cidrv6:"zakres IPv6",base64:"ciąg znaków zakodowany w formacie base64",base64url:"ciąg znaków zakodowany w formacie base64url",json_string:"ciąg znaków w formacie JSON",e164:"liczba E.164",jwt:"JWT",template_literal:"wejście"},i=>{switch(i.code){case"invalid_type":return`Nieprawidłowe dane wejściowe: oczekiwano ${i.expected}, otrzymano ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"liczba";case"object":if(Array.isArray(e))return"tablica";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Nieprawidłowe dane wejściowe: oczekiwano ${V.stringifyPrimitive(i.values[0])}`;return`Nieprawidłowa opcja: oczekiwano jednej z wartości ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Za duża wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.maximum.toString()} ${r.unit??"elementów"}`;return`Zbyt duż(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Za mała wartość: oczekiwano, że ${i.origin??"wartość"} będzie mieć ${t}${i.minimum.toString()} ${r.unit??"elementów"}`;return`Zbyt mał(y/a/e): oczekiwano, że ${i.origin??"wartość"} będzie wynosić ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zaczynać się od "${i.prefix}"`;if("ends_with"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi kończyć się na "${i.suffix}"`;if("includes"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi zawierać "${i.includes}"`;if("regex"===i.format)return`Nieprawidłowy ciąg znak\xf3w: musi odpowiadać wzorcowi ${i.pattern}`;return`Nieprawidłow(y/a/e) ${t[i.format]??i.format}`;case"not_multiple_of":return`Nieprawidłowa liczba: musi być wielokrotnością ${i.divisor}`;case"unrecognized_keys":return`Nierozpoznane klucze${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Nieprawidłowy klucz w ${i.origin}`;case"invalid_union":default:return"Nieprawidłowe dane wejściowe";case"invalid_element":return`Nieprawidłowa wartość w ${i.origin}`}})}},"ps",0,function(){let e,t;return{localeError:(e={string:{unit:"توکي",verb:"ولري"},file:{unit:"بایټس",verb:"ولري"},array:{unit:"توکي",verb:"ولري"},set:{unit:"توکي",verb:"ولري"}},t={regex:"ورودي",email:"بریښنالیک",url:"یو آر ال",emoji:"ایموجي",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"نیټه او وخت",date:"نېټه",time:"وخت",duration:"موده",ipv4:"د IPv4 پته",ipv6:"د IPv6 پته",cidrv4:"د IPv4 ساحه",cidrv6:"د IPv6 ساحه",base64:"base64-encoded متن",base64url:"base64url-encoded متن",json_string:"JSON متن",e164:"د E.164 شمېره",jwt:"JWT",template_literal:"ورودي"},i=>{switch(i.code){case"invalid_type":return`ناسم ورودي: باید ${i.expected} وای, مګر ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"عدد";case"object":if(Array.isArray(e))return"ارې";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} ترلاسه شو`;case"invalid_value":if(1===i.values.length)return`ناسم ورودي: باید ${V.stringifyPrimitive(i.values[0])} وای`;return`ناسم انتخاب: باید یو له ${V.joinValues(i.values,"|")} څخه وای`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} ${r.unit??"عنصرونه"} ولري`;return`ډیر لوی: ${i.origin??"ارزښت"} باید ${t}${i.maximum.toString()} وي`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} ${r.unit} ولري`;return`ډیر کوچنی: ${i.origin} باید ${t}${i.minimum.toString()} وي`}case"invalid_format":if("starts_with"===i.format)return`ناسم متن: باید د "${i.prefix}" سره پیل شي`;if("ends_with"===i.format)return`ناسم متن: باید د "${i.suffix}" سره پای ته ورسيږي`;if("includes"===i.format)return`ناسم متن: باید "${i.includes}" ولري`;if("regex"===i.format)return`ناسم متن: باید د ${i.pattern} سره مطابقت ولري`;return`${t[i.format]??i.format} ناسم دی`;case"not_multiple_of":return`ناسم عدد: باید د ${i.divisor} مضرب وي`;case"unrecognized_keys":return`ناسم ${i.keys.length>1?"کلیډونه":"کلیډ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`ناسم کلیډ په ${i.origin} کې`;case"invalid_union":default:return"ناسمه ورودي";case"invalid_element":return`ناسم عنصر په ${i.origin} کې`}})}},"pt",0,function(){let e,t;return{localeError:(e={string:{unit:"caracteres",verb:"ter"},file:{unit:"bytes",verb:"ter"},array:{unit:"itens",verb:"ter"},set:{unit:"itens",verb:"ter"}},t={regex:"padrão",email:"endereço de e-mail",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"data e hora ISO",date:"data ISO",time:"hora ISO",duration:"duração ISO",ipv4:"endereço IPv4",ipv6:"endereço IPv6",cidrv4:"faixa de IPv4",cidrv6:"faixa de IPv6",base64:"texto codificado em base64",base64url:"URL codificada em base64",json_string:"texto JSON",e164:"número E.164",jwt:"JWT",template_literal:"entrada"},i=>{switch(i.code){case"invalid_type":return`Tipo inv\xe1lido: esperado ${i.expected}, recebido ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"número";case"object":if(Array.isArray(e))return"array";if(null===e)return"nulo";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Entrada inv\xe1lida: esperado ${V.stringifyPrimitive(i.values[0])}`;return`Op\xe7\xe3o inv\xe1lida: esperada uma das ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Muito grande: esperado que ${i.origin??"valor"} tivesse ${t}${i.maximum.toString()} ${r.unit??"elementos"}`;return`Muito grande: esperado que ${i.origin??"valor"} fosse ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Muito pequeno: esperado que ${i.origin} tivesse ${t}${i.minimum.toString()} ${r.unit}`;return`Muito pequeno: esperado que ${i.origin} fosse ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Texto inv\xe1lido: deve come\xe7ar com "${i.prefix}"`;if("ends_with"===i.format)return`Texto inv\xe1lido: deve terminar com "${i.suffix}"`;if("includes"===i.format)return`Texto inv\xe1lido: deve incluir "${i.includes}"`;if("regex"===i.format)return`Texto inv\xe1lido: deve corresponder ao padr\xe3o ${i.pattern}`;return`${t[i.format]??i.format} inv\xe1lido`;case"not_multiple_of":return`N\xfamero inv\xe1lido: deve ser m\xfaltiplo de ${i.divisor}`;case"unrecognized_keys":return`Chave${i.keys.length>1?"s":""} desconhecida${i.keys.length>1?"s":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Chave inv\xe1lida em ${i.origin}`;case"invalid_union":return"Entrada inválida";case"invalid_element":return`Valor inv\xe1lido em ${i.origin}`;default:return"Campo inválido"}})}},"ru",0,function(){let e,t;return{localeError:(e={string:{unit:{one:"символ",few:"символа",many:"символов"},verb:"иметь"},file:{unit:{one:"байт",few:"байта",many:"байт"},verb:"иметь"},array:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"},set:{unit:{one:"элемент",few:"элемента",many:"элементов"},verb:"иметь"}},t={regex:"ввод",email:"email адрес",url:"URL",emoji:"эмодзи",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO дата и время",date:"ISO дата",time:"ISO время",duration:"ISO длительность",ipv4:"IPv4 адрес",ipv6:"IPv6 адрес",cidrv4:"IPv4 диапазон",cidrv6:"IPv6 диапазон",base64:"строка в формате base64",base64url:"строка в формате base64url",json_string:"JSON строка",e164:"номер E.164",jwt:"JWT",template_literal:"ввод"},i=>{switch(i.code){case"invalid_type":return`Неверный ввод: ожидалось ${i.expected}, получено ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"массив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неверный ввод: ожидалось ${V.stringifyPrimitive(i.values[0])}`;return`Неверный вариант: ожидалось одно из ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r){let e=tA(Number(i.maximum),r.unit.one,r.unit.few,r.unit.many);return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет иметь ${t}${i.maximum.toString()} ${e}`}return`Слишком большое значение: ожидалось, что ${i.origin??"значение"} будет ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r){let e=tA(Number(i.minimum),r.unit.one,r.unit.few,r.unit.many);return`Слишком маленькое значение: ожидалось, что ${i.origin} будет иметь ${t}${i.minimum.toString()} ${e}`}return`Слишком маленькое значение: ожидалось, что ${i.origin} будет ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неверная строка: должна начинаться с "${i.prefix}"`;if("ends_with"===i.format)return`Неверная строка: должна заканчиваться на "${i.suffix}"`;if("includes"===i.format)return`Неверная строка: должна содержать "${i.includes}"`;if("regex"===i.format)return`Неверная строка: должна соответствовать шаблону ${i.pattern}`;return`Неверный ${t[i.format]??i.format}`;case"not_multiple_of":return`Неверное число: должно быть кратным ${i.divisor}`;case"unrecognized_keys":return`Нераспознанн${i.keys.length>1?"ые":"ый"} ключ${i.keys.length>1?"и":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Неверный ключ в ${i.origin}`;case"invalid_union":default:return"Неверные входные данные";case"invalid_element":return`Неверное значение в ${i.origin}`}})}},"sl",0,function(){let e,t;return{localeError:(e={string:{unit:"znakov",verb:"imeti"},file:{unit:"bajtov",verb:"imeti"},array:{unit:"elementov",verb:"imeti"},set:{unit:"elementov",verb:"imeti"}},t={regex:"vnos",email:"e-poštni naslov",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO datum in čas",date:"ISO datum",time:"ISO čas",duration:"ISO trajanje",ipv4:"IPv4 naslov",ipv6:"IPv6 naslov",cidrv4:"obseg IPv4",cidrv6:"obseg IPv6",base64:"base64 kodiran niz",base64url:"base64url kodiran niz",json_string:"JSON niz",e164:"E.164 številka",jwt:"JWT",template_literal:"vnos"},i=>{switch(i.code){case"invalid_type":return`Neveljaven vnos: pričakovano ${i.expected}, prejeto ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"število";case"object":if(Array.isArray(e))return"tabela";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Neveljaven vnos: pričakovano ${V.stringifyPrimitive(i.values[0])}`;return`Neveljavna možnost: pričakovano eno izmed ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} imelo ${t}${i.maximum.toString()} ${r.unit??"elementov"}`;return`Preveliko: pričakovano, da bo ${i.origin??"vrednost"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Premajhno: pričakovano, da bo ${i.origin} imelo ${t}${i.minimum.toString()} ${r.unit}`;return`Premajhno: pričakovano, da bo ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Neveljaven niz: mora se začeti z "${i.prefix}"`;if("ends_with"===i.format)return`Neveljaven niz: mora se končati z "${i.suffix}"`;if("includes"===i.format)return`Neveljaven niz: mora vsebovati "${i.includes}"`;if("regex"===i.format)return`Neveljaven niz: mora ustrezati vzorcu ${i.pattern}`;return`Neveljaven ${t[i.format]??i.format}`;case"not_multiple_of":return`Neveljavno število: mora biti večkratnik ${i.divisor}`;case"unrecognized_keys":return`Neprepoznan${i.keys.length>1?"i ključi":" ključ"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Neveljaven ključ v ${i.origin}`;case"invalid_union":default:return"Neveljaven vnos";case"invalid_element":return`Neveljavna vrednost v ${i.origin}`}})}},"sv",0,function(){let e,t;return{localeError:(e={string:{unit:"tecken",verb:"att ha"},file:{unit:"bytes",verb:"att ha"},array:{unit:"objekt",verb:"att innehålla"},set:{unit:"objekt",verb:"att innehålla"}},t={regex:"reguljärt uttryck",email:"e-postadress",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO-datum och tid",date:"ISO-datum",time:"ISO-tid",duration:"ISO-varaktighet",ipv4:"IPv4-intervall",ipv6:"IPv6-intervall",cidrv4:"IPv4-spektrum",cidrv6:"IPv6-spektrum",base64:"base64-kodad sträng",base64url:"base64url-kodad sträng",json_string:"JSON-sträng",e164:"E.164-nummer",jwt:"JWT",template_literal:"mall-literal"},i=>{switch(i.code){case"invalid_type":return`Ogiltig inmatning: f\xf6rv\xe4ntat ${i.expected}, fick ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"antal";case"object":if(Array.isArray(e))return"lista";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ogiltig inmatning: f\xf6rv\xe4ntat ${V.stringifyPrimitive(i.values[0])}`;return`Ogiltigt val: f\xf6rv\xe4ntade en av ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`F\xf6r stor(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()} ${r.unit??"element"}`;return`F\xf6r stor(t): f\xf6rv\xe4ntat ${i.origin??"värdet"} att ha ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()} ${r.unit}`;return`F\xf6r lite(t): f\xf6rv\xe4ntade ${i.origin??"värdet"} att ha ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste b\xf6rja med "${i.prefix}"`;if("ends_with"===i.format)return`Ogiltig str\xe4ng: m\xe5ste sluta med "${i.suffix}"`;if("includes"===i.format)return`Ogiltig str\xe4ng: m\xe5ste inneh\xe5lla "${i.includes}"`;if("regex"===i.format)return`Ogiltig str\xe4ng: m\xe5ste matcha m\xf6nstret "${i.pattern}"`;return`Ogiltig(t) ${t[i.format]??i.format}`;case"not_multiple_of":return`Ogiltigt tal: m\xe5ste vara en multipel av ${i.divisor}`;case"unrecognized_keys":return`${i.keys.length>1?"Okända nycklar":"Okänd nyckel"}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Ogiltig nyckel i ${i.origin??"värdet"}`;case"invalid_union":default:return"Ogiltig input";case"invalid_element":return`Ogiltigt v\xe4rde i ${i.origin??"värdet"}`}})}},"ta",0,function(){let e,t;return{localeError:(e={string:{unit:"எழுத்துக்கள்",verb:"கொண்டிருக்க வேண்டும்"},file:{unit:"பைட்டுகள்",verb:"கொண்டிருக்க வேண்டும்"},array:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"},set:{unit:"உறுப்புகள்",verb:"கொண்டிருக்க வேண்டும்"}},t={regex:"உள்ளீடு",email:"மின்னஞ்சல் முகவரி",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO தேதி நேரம்",date:"ISO தேதி",time:"ISO நேரம்",duration:"ISO கால அளவு",ipv4:"IPv4 முகவரி",ipv6:"IPv6 முகவரி",cidrv4:"IPv4 வரம்பு",cidrv6:"IPv6 வரம்பு",base64:"base64-encoded சரம்",base64url:"base64url-encoded சரம்",json_string:"JSON சரம்",e164:"E.164 எண்",jwt:"JWT",template_literal:"input"},i=>{switch(i.code){case"invalid_type":return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${i.expected}, பெறப்பட்டது ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"எண் அல்லாதது":"எண்";case"object":if(Array.isArray(e))return"அணி";if(null===e)return"வெறுமை";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`தவறான உள்ளீடு: எதிர்பார்க்கப்பட்டது ${V.stringifyPrimitive(i.values[0])}`;return`தவறான விருப்பம்: எதிர்பார்க்கப்பட்டது ${V.joinValues(i.values,"|")} இல் ஒன்று`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${t}${i.maximum.toString()} ${r.unit??"உறுப்புகள்"} ஆக இருக்க வேண்டும்`;return`மிக பெரியது: எதிர்பார்க்கப்பட்டது ${i.origin??"மதிப்பு"} ${t}${i.maximum.toString()} ஆக இருக்க வேண்டும்`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ${r.unit} ஆக இருக்க வேண்டும்`;return`மிகச் சிறியது: எதிர்பார்க்கப்பட்டது ${i.origin} ${t}${i.minimum.toString()} ஆக இருக்க வேண்டும்`}case"invalid_format":if("starts_with"===i.format)return`தவறான சரம்: "${i.prefix}" இல் தொடங்க வேண்டும்`;if("ends_with"===i.format)return`தவறான சரம்: "${i.suffix}" இல் முடிவடைய வேண்டும்`;if("includes"===i.format)return`தவறான சரம்: "${i.includes}" ஐ உள்ளடக்க வேண்டும்`;if("regex"===i.format)return`தவறான சரம்: ${i.pattern} முறைபாட்டுடன் பொருந்த வேண்டும்`;return`தவறான ${t[i.format]??i.format}`;case"not_multiple_of":return`தவறான எண்: ${i.divisor} இன் பலமாக இருக்க வேண்டும்`;case"unrecognized_keys":return`அடையாளம் தெரியாத விசை${i.keys.length>1?"கள்":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} இல் தவறான விசை`;case"invalid_union":default:return"தவறான உள்ளீடு";case"invalid_element":return`${i.origin} இல் தவறான 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"${i.prefix}"`;if("ends_with"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องลงท้ายด้วย "${i.suffix}"`;if("includes"===i.format)return`รูปแบบไม่ถูกต้อง: ข้อความต้องมี "${i.includes}" อยู่ในข้อความ`;if("regex"===i.format)return`รูปแบบไม่ถูกต้อง: ต้องตรงกับรูปแบบที่กำหนด ${i.pattern}`;return`รูปแบบไม่ถูกต้อง: ${t[i.format]??i.format}`;case"not_multiple_of":return`ตัวเลขไม่ถูกต้อง: ต้องเป็นจำนวนที่หารด้วย ${i.divisor} ได้ลงตัว`;case"unrecognized_keys":return`พบคีย์ที่ไม่รู้จัก: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`คีย์ไม่ถูกต้องใน ${i.origin}`;case"invalid_union":return"ข้อมูลไม่ถูกต้อง: ไม่ตรงกับรูปแบบยูเนียนที่กำหนดไว้";case"invalid_element":return`ข้อมูลไม่ถูกต้องใน ${i.origin}`;default:return"ข้อมูลไม่ถูกต้อง"}})}},"tr",0,function(){let e,t;return{localeError:(e={string:{unit:"karakter",verb:"olmalı"},file:{unit:"bayt",verb:"olmalı"},array:{unit:"öğe",verb:"olmalı"},set:{unit:"öğe",verb:"olmalı"}},t={regex:"girdi",email:"e-posta adresi",url:"URL",emoji:"emoji",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"ISO tarih ve saat",date:"ISO tarih",time:"ISO saat",duration:"ISO süre",ipv4:"IPv4 adresi",ipv6:"IPv6 adresi",cidrv4:"IPv4 aralığı",cidrv6:"IPv6 aralığı",base64:"base64 ile şifrelenmiş metin",base64url:"base64url ile şifrelenmiş metin",json_string:"JSON dizesi",e164:"E.164 sayısı",jwt:"JWT",template_literal:"Şablon dizesi"},i=>{switch(i.code){case"invalid_type":return`Ge\xe7ersiz değer: beklenen ${i.expected}, alınan ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"number";case"object":if(Array.isArray(e))return"array";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Ge\xe7ersiz değer: beklenen ${V.stringifyPrimitive(i.values[0])}`;return`Ge\xe7ersiz se\xe7enek: aşağıdakilerden biri olmalı: ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()} ${r.unit??"öğe"}`;return`\xc7ok b\xfcy\xfck: beklenen ${i.origin??"değer"} ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()} ${r.unit}`;return`\xc7ok k\xfc\xe7\xfck: beklenen ${i.origin} ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Ge\xe7ersiz metin: "${i.prefix}" ile başlamalı`;if("ends_with"===i.format)return`Ge\xe7ersiz metin: "${i.suffix}" ile bitmeli`;if("includes"===i.format)return`Ge\xe7ersiz metin: "${i.includes}" i\xe7ermeli`;if("regex"===i.format)return`Ge\xe7ersiz metin: ${i.pattern} desenine uymalı`;return`Ge\xe7ersiz ${t[i.format]??i.format}`;case"not_multiple_of":return`Ge\xe7ersiz sayı: ${i.divisor} ile tam b\xf6l\xfcnebilmeli`;case"unrecognized_keys":return`Tanınmayan anahtar${i.keys.length>1?"lar":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`${i.origin} i\xe7inde ge\xe7ersiz anahtar`;case"invalid_union":default:return"Geçersiz değer";case"invalid_element":return`${i.origin} i\xe7inde ge\xe7ersiz değer`}})}},"ua",0,function(){let e,t;return{localeError:(e={string:{unit:"символів",verb:"матиме"},file:{unit:"байтів",verb:"матиме"},array:{unit:"елементів",verb:"матиме"},set:{unit:"елементів",verb:"матиме"}},t={regex:"вхідні дані",email:"адреса електронної пошти",url:"URL",emoji:"емодзі",uuid:"UUID",uuidv4:"UUIDv4",uuidv6:"UUIDv6",nanoid:"nanoid",guid:"GUID",cuid:"cuid",cuid2:"cuid2",ulid:"ULID",xid:"XID",ksuid:"KSUID",datetime:"дата та час ISO",date:"дата ISO",time:"час ISO",duration:"тривалість ISO",ipv4:"адреса IPv4",ipv6:"адреса IPv6",cidrv4:"діапазон IPv4",cidrv6:"діапазон IPv6",base64:"рядок у кодуванні base64",base64url:"рядок у кодуванні base64url",json_string:"рядок JSON",e164:"номер E.164",jwt:"JWT",template_literal:"вхідні дані"},i=>{switch(i.code){case"invalid_type":return`Неправильні вхідні дані: очікується ${i.expected}, отримано ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"число";case"object":if(Array.isArray(e))return"масив";if(null===e)return"null";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)}`;case"invalid_value":if(1===i.values.length)return`Неправильні вхідні дані: очікується ${V.stringifyPrimitive(i.values[0])}`;return`Неправильна опція: очікується одне з ${V.joinValues(i.values,"|")}`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`Занадто велике: очікується, що ${i.origin??"значення"} ${r.verb} ${t}${i.maximum.toString()} ${r.unit??"елементів"}`;return`Занадто велике: очікується, що ${i.origin??"значення"} буде ${t}${i.maximum.toString()}`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`Занадто мале: очікується, що ${i.origin} ${r.verb} ${t}${i.minimum.toString()} ${r.unit}`;return`Занадто мале: очікується, що ${i.origin} буде ${t}${i.minimum.toString()}`}case"invalid_format":if("starts_with"===i.format)return`Неправильний рядок: повинен починатися з "${i.prefix}"`;if("ends_with"===i.format)return`Неправильний рядок: повинен закінчуватися на "${i.suffix}"`;if("includes"===i.format)return`Неправильний рядок: повинен містити "${i.includes}"`;if("regex"===i.format)return`Неправильний рядок: повинен відповідати шаблону ${i.pattern}`;return`Неправильний ${t[i.format]??i.format}`;case"not_multiple_of":return`Неправильне число: повинно бути кратним ${i.divisor}`;case"unrecognized_keys":return`Нерозпізнаний ключ${i.keys.length>1?"і":""}: ${V.joinValues(i.keys,", ")}`;case"invalid_key":return`Неправильний ключ у ${i.origin}`;case"invalid_union":default:return"Неправильні вхідні дані";case"invalid_element":return`Неправильне значення у ${i.origin}`}})}},"ur",0,function(){let e,t;return{localeError:(e={string:{unit:"حروف",verb:"ہونا"},file:{unit:"بائٹس",verb:"ہونا"},array:{unit:"آئٹمز",verb:"ہونا"},set:{unit:"آئٹمز",verb:"ہونا"}},t={regex:"ان پٹ",email:"ای میل ایڈریس",url:"یو آر ایل",emoji:"ایموجی",uuid:"یو یو آئی ڈی",uuidv4:"یو یو آئی ڈی وی 4",uuidv6:"یو یو آئی ڈی وی 6",nanoid:"نینو آئی ڈی",guid:"جی یو آئی ڈی",cuid:"سی یو آئی ڈی",cuid2:"سی یو آئی ڈی 2",ulid:"یو ایل آئی ڈی",xid:"ایکس آئی ڈی",ksuid:"کے ایس یو آئی ڈی",datetime:"آئی ایس او ڈیٹ ٹائم",date:"آئی ایس او تاریخ",time:"آئی ایس او وقت",duration:"آئی ایس او مدت",ipv4:"آئی پی وی 4 ایڈریس",ipv6:"آئی پی وی 6 ایڈریس",cidrv4:"آئی پی وی 4 رینج",cidrv6:"آئی پی وی 6 رینج",base64:"بیس 64 ان کوڈڈ سٹرنگ",base64url:"بیس 64 یو آر ایل ان کوڈڈ سٹرنگ",json_string:"جے ایس او این سٹرنگ",e164:"ای 164 نمبر",jwt:"جے ڈبلیو ٹی",template_literal:"ان پٹ"},i=>{switch(i.code){case"invalid_type":return`غلط ان پٹ: ${i.expected} متوقع تھا، ${(e=>{let t=typeof e;switch(t){case"number":return Number.isNaN(e)?"NaN":"نمبر";case"object":if(Array.isArray(e))return"آرے";if(null===e)return"نل";if(Object.getPrototypeOf(e)!==Object.prototype&&e.constructor)return e.constructor.name}return t})(i.input)} موصول ہوا`;case"invalid_value":if(1===i.values.length)return`غلط ان پٹ: ${V.stringifyPrimitive(i.values[0])} متوقع تھا`;return`غلط آپشن: ${V.joinValues(i.values,"|")} میں سے ایک متوقع تھا`;case"too_big":{let t=i.inclusive?"<=":"<",r=e[i.origin]??null;if(r)return`بہت بڑا: ${i.origin??"ویلیو"} کے ${t}${i.maximum.toString()} ${r.unit??"عناصر"} ہونے متوقع تھے`;return`بہت بڑا: ${i.origin??"ویلیو"} کا ${t}${i.maximum.toString()} ہونا متوقع تھا`}case"too_small":{let t=i.inclusive?">=":">",r=e[i.origin]??null;if(r)return`بہت چھوٹا: ${i.origin} کے ${t}${i.minimum.toString()} ${r.unit} ہونے متوقع تھے`;return`بہت چھوٹا: ${i.origin} کا ${t}${i.minimum.toString()} ہونا متوقع تھا`}case"invalid_format":if("starts_with"===i.format)return`غلط سٹرنگ: "${i.prefix}" سے شروع ہونا چاہیے`;if("ends_with"===i.format)return`غلط سٹرنگ: "${i.suffix}" پر ختم ہونا چاہیے`;if("includes"===i.format)return`غلط سٹرنگ: "${i.includes}" شامل ہونا چاہیے`;if("regex"===i.format)return`غلط سٹرنگ: پیٹرن ${i.pattern} سے میچ ہونا چاہیے`;return`غلط ${t[i.format]??i.format}`;case"not_multiple_of":return`غلط نمبر: ${i.divisor} کا مضاعف ہونا چاہیے`;case"unrecognized_keys":return`غیر تسلیم شدہ کی${i.keys.length>1?"ز":""}: ${V.joinValues(i.keys,"، ")}`;case"invalid_key":return`${i.origin} میں غلط کی`;case"invalid_union":default:return"غلط ان پٹ";case"invalid_element":return`${i.origin} میں غلط ویلیو`}})}},"vi",0,function(){let e,t;return{localeError:(e={string:{unit:"ký tự",verb:"có"},file:{unit:"byte",verb:"có"},array:{unit:"phần tử",verb:"có"},set:{unit:"phần tử",verb:"có"}},t={regex:"đầu vào",email:"địa chỉ 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e=t[0];tK(this,er,"f")||s?.length||Promise.reject(e),tK(this,K,"f").call(this,e),tK(this,Q,"f").call(this,e),this._emit("end")}}_emitFinal(){this.receivedMessages.at(-1)&&this._emit("finalMessage",tK(this,W,"m",eo).call(this))}async _fromReadableStream(e,t){let s,r=t?.signal;r&&(r.aborted&&this.controller.abort(),s=this.controller.abort.bind(this.controller),r.addEventListener("abort",s));try{tK(this,W,"m",ec).call(this),this._connected(null);let t=sC.fromReadableStream(e,this.controller);for await(let e of t)tK(this,W,"m",eu).call(this,e);if(t.controller.signal?.aborted)throw new t1;tK(this,W,"m",em).call(this)}finally{r&&s&&r.removeEventListener("abort",s)}}[(V=new WeakMap,H=new WeakMap,G=new WeakMap,J=new WeakMap,K=new WeakMap,X=new WeakMap,Y=new WeakMap,Q=new WeakMap,Z=new WeakMap,ee=new WeakMap,et=new WeakMap,es=new WeakMap,er=new WeakMap,ea=new WeakMap,en=new WeakMap,ei=new WeakMap,ed=new WeakMap,W=new WeakSet,eo=function(){if(0===this.receivedMessages.length)throw new tZ("stream ended without producing a Message with role=assistant");return this.receivedMessages.at(-1)},el=function(){if(0===this.receivedMessages.length)throw new tZ("stream ended without producing a Message with role=assistant");let e=this.receivedMessages.at(-1).content.filter(e=>"text"===e.type).map(e=>e.text);if(0===e.length)throw new tZ("stream ended without producing a content block with type=text");return e.join(" ")},ec=function(){this.ended||tJ(this,V,void 0,"f")},eu=function(e){if(this.ended)return;let t=tK(this,W,"m",eh).call(this,e);switch(this._emit("streamEvent",e,t),e.type){case"content_block_delta":{let s=t.content.at(-1);switch(e.delta.type){case"text_delta":"text"===s.type&&this._emit("text",e.delta.text,s.text||"");break;case"citations_delta":"text"===s.type&&this._emit("citation",e.delta.citation,s.citations??[]);break;case"input_json_delta":rL(s)&&s.input&&this._emit("inputJson",e.delta.partial_json,s.input);break;case"thinking_delta":"thinking"===s.type&&this._emit("thinking",e.delta.thinking,s.thinking);break;case"signature_delta":"thinking"===s.type&&this._emit("signature",s.signature);break;default:rD(e.delta)}break}case"message_stop":this._addMessageParam(t),this._addMessage(rR(t,tK(this,H,"f"),{logger:tK(this,ei,"f")}),!0);break;case"content_block_stop":this._emit("contentBlock",t.content.at(-1));break;case"message_start":tJ(this,V,t,"f")}},em=function(){if(this.ended)throw new tZ("stream has ended, this shouldn't happen");let e=tK(this,V,"f");if(!e)throw new tZ("request ended without sending any chunks");return tJ(this,V,void 0,"f"),rR(e,tK(this,H,"f"),{logger:tK(this,ei,"f")})},eh=function(e){let t=tK(this,V,"f");if("message_start"===e.type){if(t)throw new tZ(`Unexpected event order, got ${e.type} before receiving "message_stop"`);return e.message}if(!t)throw new tZ(`Unexpected event order, got ${e.type} before "message_start"`);switch(e.type){case"message_stop":case"content_block_stop":return t;case"message_delta":return t.stop_reason=e.delta.stop_reason,t.stop_sequence=e.delta.stop_sequence,t.usage.output_tokens=e.usage.output_tokens,null!=e.usage.input_tokens&&(t.usage.input_tokens=e.usage.input_tokens),null!=e.usage.cache_creation_input_tokens&&(t.usage.cache_creation_input_tokens=e.usage.cache_creation_input_tokens),null!=e.usage.cache_read_input_tokens&&(t.usage.cache_read_input_tokens=e.usage.cache_read_input_tokens),null!=e.usage.server_tool_use&&(t.usage.server_tool_use=e.usage.server_tool_use),t;case"content_block_start":return t.content.push({...e.content_block}),t;case"content_block_delta":{let s=t.content.at(e.index);switch(e.delta.type){case"text_delta":s?.type==="text"&&(t.content[e.index]={...s,text:(s.text||"")+e.delta.text});break;case"citations_delta":s?.type==="text"&&(t.content[e.index]={...s,citations:[...s.citations??[],e.delta.citation]});break;case"input_json_delta":if(s&&rL(s)){let r=s[rO]||"";r+=e.delta.partial_json;let a={...s};Object.defineProperty(a,rO,{value:r,enumerable:!1,writable:!0}),r&&(a.input=ru(r)),t.content[e.index]=a}break;case"thinking_delta":s?.type==="thinking"&&(t.content[e.index]={...s,thinking:s.thinking+e.delta.thinking});break;case"signature_delta":s?.type==="thinking"&&(t.content[e.index]={...s,signature:e.delta.signature});break;default:rD(e.delta)}return t}}},Symbol.asyncIterator)](){let e=[],t=[],s=!1;return this.on("streamEvent",s=>{let r=t.shift();r?r.resolve(s):e.push(s)}),this.on("end",()=>{for(let e of(s=!0,t))e.resolve(void 0);t.length=0}),this.on("abort",e=>{for(let r of(s=!0,t))r.reject(e);t.length=0}),this.on("error",e=>{for(let r of(s=!0,t))r.reject(e);t.length=0}),{next:async()=>e.length?{value:e.shift(),done:!1}:s?{value:void 0,done:!0}:new Promise((e,s)=>t.push({resolve:e,reject:s})).then(e=>e?{value:e,done:!1}:{value:void 0,done:!0}),return:async()=>(this.abort(),{value:void 0,done:!0})}}toReadableStream(){return new sC(this[Symbol.asyncIterator].bind(this),this.controller).toReadableStream()}}function rD(e){}class rz extends sK{create(e,t){return this._client.post("/v1/messages/batches",{body:e,...t})}retrieve(e,t){return this._client.get(s0`/v1/messages/batches/${e}`,t)}list(e={},t){return this._client.getAPIList("/v1/messages/batches",sO,{query:e,...t})}delete(e,t){return this._client.delete(s0`/v1/messages/batches/${e}`,t)}cancel(e,t){return this._client.post(s0`/v1/messages/batches/${e}/cancel`,t)}async results(e,t){let s=await this.retrieve(e);if(!s.results_url)throw new tZ(`No batch \`results_url\`; Has it finished processing? 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+)`;switch(c){case t.EndpointType.CHAT:{let e=Object.keys(E).length>0,t="";if(e){let e=JSON.stringify({metadata:E},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let a=w.length>0?w:[{role:"user",content:_}];i=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.chat.completions.create( + model="${C}", + messages=${JSON.stringify(a,null,4)}${t} +) + +print(response) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.chat.completions.create( +# model="${C}", +# messages=[ +# { +# "role": "user", +# "content": [ +# { +# "type": "text", +# "text": "${I}" +# }, +# { +# "type": "image_url", +# "image_url": { +# "url": 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"content": [ +# {"type": "input_text", "text": "${I}"}, +# { +# "type": "input_image", +# "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} +# }, +# ], +# } +# ]${t} +# ) +# print(response_with_file.output_text) +`;break}case t.EndpointType.IMAGE:i="azure"===g?` +# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. +# This snippet uses 'client.images.generate' and will create a new image based on your prompt. +# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. +import os +import requests +import json +import time +from PIL import Image + +result = client.images.generate( + model="${C}", + prompt="${l}", + n=1 +) + +json_response = json.loads(result.model_dump_json()) + +# Set the directory for the stored image +image_dir = os.path.join(os.curdir, 'images') + +# If the directory doesn't exist, create it +if not os.path.isdir(image_dir): + os.mkdir(image_dir) + +# Initialize the image path +image_filename = f"generated_image_{int(time.time())}.png" +image_path = os.path.join(image_dir, image_filename) + +try: + # Retrieve the generated image + if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): + image_url = json_response["data"][0]["url"] + generated_image = requests.get(image_url).content + with open(image_path, "wb") as image_file: + image_file.write(generated_image) + + print(f"Image saved to {image_path}") + # Display the image + image = Image.open(image_path) + image.show() + else: + print("Could not find image URL in response.") + print("Full response:", json_response) +except Exception as e: + print(f"An error occurred: {e}") + print("Full response:", json_response) +`:` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${I}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${C}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.IMAGE_EDITS:i="azure"===g?` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# The prompt entered by the user +prompt = "${I}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${C}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`:` +import base64 +import os +import time + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${I}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${C}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.EMBEDDINGS:i=` +response = client.embeddings.create( + input="${l||"Your string here"}", + model="${C}", + encoding_format="base64" # or "float" +) + +print(response.data[0].embedding) +`;break;case t.EndpointType.TRANSCRIPTION:i=` +# Open the audio file +audio_file = open("path/to/your/audio/file.mp3", "rb") + +# Make the transcription request +response = client.audio.transcriptions.create( + model="${C}", + file=audio_file${l?`, + prompt="${l.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""} +) + +print(response.text) +`;break;case t.EndpointType.SPEECH:i=` +# Make the text-to-speech request +response = client.audio.speech.create( + model="${C}", + input="${l||"Your text to convert to speech here"}", + voice="${m}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer +) + 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This list is a draft and is not final. If you rely on this feature, please share feedback on the `,(0,t.jsx)(o.default,{href:"https://github.com/BerriAI/litellm/discussions/32090",target:"_blank",rel:"noopener noreferrer",className:"underline underline-offset-4",children:"deprecation discussion"}),"."]})]}),(0,t.jsx)("button",{type:"button","aria-label":"Close",onClick:()=>s(!0),className:"shrink-0 rounded-md p-0.5 text-muted-foreground transition-colors hover:text-foreground",children:(0,t.jsx)(a.X,{className:"size-4"})})]})}])},909947,e=>{"use strict";var t=e.i(865361);e.s(["generateCodeSnippet",0,e=>{let r,{apiKeySource:o,accessToken:i,apiKey:a,inputMessage:n,chatHistory:s,selectedTags:l,selectedVectorStores:d,selectedGuardrails:c,selectedPolicies:u,selectedVoice:p,endpointType:h,selectedModel:m,selectedSdk:g,proxySettings:f}=e,b="session"===o?i:a,x=window.location.origin,_=f?.LITELLM_UI_API_DOC_BASE_URL;_&&_.trim()?x=_:f?.PROXY_BASE_URL&&(x=f.PROXY_BASE_URL);let k=n||"Your prompt here",y=k.replace(/\\/g,"\\\\").replace(/"/g,'\\"').replace(/\n/g,"\\n"),v=s.filter(e=>!e.isImage).map(({role:e,content:t})=>({role:e,content:t})),w={};l.length>0&&(w.tags=l),d.length>0&&(w.vector_stores=d),c.length>0&&(w.guardrails=c),u.length>0&&(w.policies=u);let j=m||"your-model-name",C="azure"===g?`import openai + +client = openai.AzureOpenAI( + api_key="${b||"YOUR_LITELLM_API_KEY"}", + azure_endpoint="${x}", + api_version="2024-02-01" +)`:`import openai + +client = openai.OpenAI( + api_key="${b||"YOUR_LITELLM_API_KEY"}", + base_url="${x}" +)`;switch(h){case t.EndpointType.CHAT:{let e=Object.keys(w).length>0,t="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let o=v.length>0?v:[{role:"user",content:k}];r=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.chat.completions.create( + model="${j}", + messages=${JSON.stringify(o,null,4)}${t} +) + +print(response) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.chat.completions.create( +# model="${j}", +# messages=[ +# { +# "role": "user", +# "content": [ +# { +# "type": "text", +# "text": "${y}" +# }, +# { +# "type": "image_url", +# "image_url": { +# "url": f"data:image/jpeg;base64,{base64_file}" # or data:application/pdf;base64,{base64_file} +# } +# } +# ] +# } +# ]${t} +# ) +# print(response_with_file) +`;break}case t.EndpointType.RESPONSES:{let e=Object.keys(w).length>0,t="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let o=v.length>0?v:[{role:"user",content:k}];r=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.responses.create( + model="${j}", + input=${JSON.stringify(o,null,4)}${t} +) + +print(response.output_text) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.responses.create( +# model="${j}", +# input=[ +# { +# "role": "user", +# "content": [ +# {"type": "input_text", "text": "${y}"}, +# { +# "type": "input_image", +# "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} +# }, +# ], +# } +# ]${t} +# ) +# print(response_with_file.output_text) +`;break}case t.EndpointType.IMAGE:r="azure"===g?` +# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. +# This snippet uses 'client.images.generate' and will create a new image based on your prompt. +# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. +import os +import requests +import json +import time +from PIL import Image + +result = client.images.generate( + model="${j}", + prompt="${n}", + n=1 +) + +json_response = json.loads(result.model_dump_json()) + +# Set the directory for the stored image +image_dir = os.path.join(os.curdir, 'images') + +# If the directory doesn't exist, create it +if not os.path.isdir(image_dir): + os.mkdir(image_dir) + +# Initialize the image path +image_filename = f"generated_image_{int(time.time())}.png" +image_path = os.path.join(image_dir, image_filename) + +try: + # Retrieve the generated image + if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): + image_url = json_response["data"][0]["url"] + generated_image = requests.get(image_url).content + with open(image_path, "wb") as image_file: + image_file.write(generated_image) + + print(f"Image saved to {image_path}") + # Display the image + image = Image.open(image_path) + image.show() + else: + print("Could not find image URL in response.") + print("Full response:", json_response) +except Exception as e: + print(f"An error occurred: {e}") + print("Full response:", json_response) +`:` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${y}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${j}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.IMAGE_EDITS:r="azure"===g?` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# The prompt entered by the user +prompt = "${y}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${j}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`:` +import base64 +import os +import time + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${y}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${j}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.EMBEDDINGS:r=` +response = client.embeddings.create( + input="${n||"Your string here"}", + model="${j}", + encoding_format="base64" # or "float" +) + +print(response.data[0].embedding) +`;break;case t.EndpointType.TRANSCRIPTION:r=` +# Open the audio file +audio_file = open("path/to/your/audio/file.mp3", "rb") + +# Make the transcription request +response = client.audio.transcriptions.create( + model="${j}", + file=audio_file${n?`, + prompt="${n.replace(/\\/g,"\\\\").replace(/"/g,'\\"')}"`:""} +) + +print(response.text) +`;break;case t.EndpointType.SPEECH:r=` +# Make the text-to-speech request +response = client.audio.speech.create( + model="${j}", + input="${n||"Your text to convert to speech here"}", + voice="${p}" # Options: alloy, ash, ballad, coral, echo, fable, nova, onyx, sage, shimmer +) + 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= None +_public_card = ( + await resolver.get_agent_card() +) # Fetches from default public path - \`/agents/{agent_id}/\` +final_agent_card_to_use = _public_card + +if _public_card.supports_authenticated_extended_card: + try: + auth_headers_dict = { + 'Authorization': 'Bearer dummy-token-for-extended-card' + } + _extended_card = await resolver.get_agent_card( + relative_card_path=EXTENDED_AGENT_CARD_PATH, + http_kwargs={'headers': auth_headers_dict}, + ) + final_agent_card_to_use = ( + _extended_card # Update to use the extended card + ) + except Exception as e_extended: + logger.warning( + f'Failed to fetch extended agent card: {e_extended}. 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9)))}.max-h-full{max-height:100%}.min-h-0{min-height:0}.min-h-4{min-height:calc(var(--spacing) * 4)}.min-h-5{min-height:calc(var(--spacing) * 5)}.min-h-6{min-height:calc(var(--spacing) * 6)}.min-h-8{min-height:calc(var(--spacing) * 8)}.min-h-9{min-height:calc(var(--spacing) * 9)}.min-h-16{min-height:calc(var(--spacing) * 16)}.min-h-24{min-height:calc(var(--spacing) * 24)}.min-h-\[7\.5rem\]{min-height:7.5rem}.min-h-\[34px\]{min-height:34px}.min-h-\[40px\]{min-height:40px}.min-h-\[44px\]{min-height:44px}.min-h-\[100px\]{min-height:100px}.min-h-\[120px\]{min-height:120px}.min-h-\[170px\]{min-height:170px}.min-h-\[280px\]{min-height:280px}.min-h-\[300px\]{min-height:300px}.min-h-\[400px\]{min-height:400px}.min-h-\[500px\]{min-height:500px}.min-h-\[600px\]{min-height:600px}.min-h-\[750px\]{min-height:750px}.min-h-\[calc\(100vh-160px\)\]{min-height:calc(100vh - 160px)}.min-h-screen{min-height:100vh}.w-\(--anchor-width\){width:var(--anchor-width)}.w-0{width:0}.w-0\.5{width:calc(var(--spacing) * .5)}.w-1{width:var(--spacing)}.w-1\.5{width:calc(var(--spacing) * 1.5)}.w-1\/2{width:50%}.w-1\/3{width:33.3333%}.w-1\/4{width:25%}.w-2{width:calc(var(--spacing) * 2)}.w-2\.5{width:calc(var(--spacing) * 2.5)}.w-2\/3{width:66.6667%}.w-2\/5{width:40%}.w-3{width:calc(var(--spacing) * 3)}.w-3\.5{width:calc(var(--spacing) * 3.5)}.w-3\/4{width:75%}.w-3\/5{width:60%}.w-4{width:calc(var(--spacing) * 4)}.w-5{width:calc(var(--spacing) * 5)}.w-6{width:calc(var(--spacing) * 6)}.w-7{width:calc(var(--spacing) * 7)}.w-8{width:calc(var(--spacing) * 8)}.w-9{width:calc(var(--spacing) * 9)}.w-9\!{width:calc(var(--spacing) * 9)!important}.w-10{width:calc(var(--spacing) * 10)}.w-11{width:calc(var(--spacing) * 11)}.w-11\/12{width:91.6667%}.w-12{width:calc(var(--spacing) * 12)}.w-14{width:calc(var(--spacing) * 14)}.w-16{width:calc(var(--spacing) * 16)}.w-20{width:calc(var(--spacing) * 20)}.w-24{width:calc(var(--spacing) * 24)}.w-28{width:calc(var(--spacing) * 28)}.w-32{width:calc(var(--spacing) * 32)}.w-36{width:calc(var(--spacing) * 36)}.w-40{width:calc(var(--spacing) * 40)}.w-44{width:calc(var(--spacing) * 44)}.w-48{width:calc(var(--spacing) * 48)}.w-50{width:calc(var(--spacing) * 50)}.w-52{width:calc(var(--spacing) * 52)}.w-54{width:calc(var(--spacing) * 54)}.w-55{width:calc(var(--spacing) * 55)}.w-56{width:calc(var(--spacing) * 56)}.w-60{width:calc(var(--spacing) * 60)}.w-64{width:calc(var(--spacing) * 64)}.w-65{width:calc(var(--spacing) * 65)}.w-72{width:calc(var(--spacing) * 72)}.w-80{width:calc(var(--spacing) * 80)}.w-96{width:calc(var(--spacing) * 96)}.w-\[4\.5rem\]{width:4.5rem}.w-\[7px\]{width:7px}.w-\[18\%\]{width:18%}.w-\[20\%\]{width:20%}.w-\[25\%\]{width:25%}.w-\[30\%\]{width:30%}.w-\[35\%\]{width:35%}.w-\[38px\]{width:38px}.w-\[44\%\]{width:44%}.w-\[48\%\]{width:48%}.w-\[50\%\]{width:50%}.w-\[50px\]{width:50px}.w-\[58\%\]{width:58%}.w-\[60\%\]{width:60%}.w-\[64\%\]{width:64%}.w-\[70\%\]{width:70%}.w-\[72\%\]{width:72%}.w-\[72px\]{width:72px}.w-\[80px\]{width:80px}.w-\[110px\]{width:110px}.w-\[120px\]{width:120px}.w-\[130px\]{width:130px}.w-\[140px\]{width:140px}.w-\[150px\]{width:150px}.w-\[180px\]{width:180px}.w-\[200px\]{width:200px}.w-\[216px\]{width:216px}.w-\[220px\]{width:220px}.w-\[260px\]{width:260px}.w-\[268px\]{width:268px}.w-\[280px\]{width:280px}.w-\[300px\]{width:300px}.w-\[400px\]{width:400px}.w-\[calc\(100\%\+1rem\)\]{width:calc(100% + 1rem)}.w-auto{width:auto}.w-fit{width:fit-content}.w-full{width:100%}.w-max{width:max-content}.w-px{width:1px}.max-w-\(--available-width\){max-width:var(--available-width)}.max-w-2xl{max-width:var(--container-2xl)}.max-w-3xl{max-width:var(--container-3xl)}.max-w-4xl{max-width:var(--container-4xl)}.max-w-5xl{max-width:var(--container-5xl)}.max-w-6xl{max-width:var(--container-6xl)}.max-w-32{max-width:calc(var(--spacing) * 32)}.max-w-36{max-width:calc(var(--spacing) * 36)}.max-w-40{max-width:calc(var(--spacing) * 40)}.max-w-44{max-width:calc(var(--spacing) * 44)}.max-w-48{max-width:calc(var(--spacing) * 48)}.max-w-50{max-width:calc(var(--spacing) * 50)}.max-w-52{max-width:calc(var(--spacing) * 52)}.max-w-56{max-width:calc(var(--spacing) * 56)}.max-w-60{max-width:calc(var(--spacing) * 60)}.max-w-64{max-width:calc(var(--spacing) * 64)}.max-w-72{max-width:calc(var(--spacing) * 72)}.max-w-80{max-width:calc(var(--spacing) * 80)}.max-w-100{max-width:calc(var(--spacing) * 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var(--tw-scale-y)}.-rotate-90{rotate:-90deg}.rotate-45{rotate:45deg}.rotate-90{rotate:90deg}.rotate-180{rotate:180deg}.transform{transform:var(--tw-rotate-x,) var(--tw-rotate-y,) var(--tw-rotate-z,) var(--tw-skew-x,) var(--tw-skew-y,)}.scroll-fade-e{--_scroll-fade-size-e:var(--scroll-fade-e-size,var(--scroll-fade-size,min(12%, calc(var(--spacing) * 10))));--scroll-fade-mask:linear-gradient(to right, #000 0, #000 calc(100% - var(--scroll-fade-e,0px)), transparent 100%)}.scroll-fade-e:where([dir=rtl],[dir=rtl] *){--scroll-fade-mask:linear-gradient(to left, #000 0, #000 calc(100% - var(--scroll-fade-e,0px)), transparent 100%)}.scroll-fade-e{-webkit-mask-image:var(--scroll-fade-mask);-webkit-mask-image:var(--scroll-fade-mask);-webkit-mask-image:var(--scroll-fade-mask);-webkit-mask-image:var(--scroll-fade-mask);mask-image:var(--scroll-fade-mask);-webkit-mask-composite:source-in;-webkit-mask-composite:source-in;-webkit-mask-composite:source-in;-webkit-mask-repeat:no-repeat;mask-repeat:no-repeat;-webkit-mask-composite:source-in;mask-composite:intersect}@supports (animation-timeline:scroll()){.scroll-fade-e{animation:1ms ease-in-out scroll-fade-reveal-e;animation-timeline:scroll(self inline);animation-range:calc(100% - var(--scroll-fade-reveal,calc(var(--spacing) * 24))) 100%;animation-fill-mode:both}}@supports not (animation-timeline:scroll()){.scroll-fade-e{--scroll-fade-e:var(--_scroll-fade-size-e)}}.animate-bounce{animation:var(--animate-bounce)}.animate-pulse{animation:var(--animate-pulse)}.animate-spin{animation:var(--animate-spin)}.cursor-col-resize{cursor:col-resize}.cursor-default{cursor:default}.cursor-grab{cursor:grab}.cursor-help{cursor:help}.cursor-not-allowed{cursor:not-allowed}.cursor-pointer{cursor:pointer}.cursor-text{cursor:text}.touch-none{touch-action:none}.resize{resize:both}.resize-none{resize:none}.scroll-my-1{scroll-margin-block:var(--spacing)}.scroll-py-1{scroll-padding-block:var(--spacing)}.list-inside{list-style-position:inside}.list-decimal{list-style-type:decimal}.list-disc{list-style-type:disc}.list-none{list-style-type:none}.auto-rows-fr{grid-auto-rows:minmax(0,1fr)}.auto-rows-min{grid-auto-rows:min-content}.grid-cols-1{grid-template-columns:repeat(1,minmax(0,1fr))}.grid-cols-2{grid-template-columns:repeat(2,minmax(0,1fr))}.grid-cols-3{grid-template-columns:repeat(3,minmax(0,1fr))}.grid-cols-4{grid-template-columns:repeat(4,minmax(0,1fr))}.grid-cols-5{grid-template-columns:repeat(5,minmax(0,1fr))}.grid-cols-10{grid-template-columns:repeat(10,minmax(0,1fr))}.grid-cols-12{grid-template-columns:repeat(12,minmax(0,1fr))}.grid-cols-24{grid-template-columns:repeat(24,minmax(0,1fr))}.grid-cols-\[1fr_auto\]{grid-template-columns:1fr auto}.grid-cols-\[80px_minmax\(0\,1fr\)\]{grid-template-columns:80px minmax(0,1fr)}.grid-cols-\[160px_minmax\(0\,1fr\)\]{grid-template-columns:160px minmax(0,1fr)}.grid-cols-\[auto\]{grid-template-columns:auto}.grid-cols-\[auto_1fr\]{grid-template-columns:auto 1fr}.grid-cols-\[auto_minmax\(0\,1fr\)\]{grid-template-columns:auto minmax(0,1fr)}.grid-cols-\[max-content_1fr\]{grid-template-columns:max-content 1fr}.grid-cols-\[minmax\(0\,14rem\)_minmax\(0\,1fr\)\]{grid-template-columns:minmax(0,14rem) minmax(0,1fr)}.grid-cols-\[repeat\(auto-fill\,minmax\(220px\,1fr\)\)\]{grid-template-columns:repeat(auto-fill,minmax(220px,1fr))}.grid-cols-\[repeat\(auto-fit\,minmax\(7rem\,1fr\)\)\]{grid-template-columns:repeat(auto-fit,minmax(7rem,1fr))}.grid-rows-\[auto_1fr\]{grid-template-rows:auto 1fr}.flex-col{flex-direction:column}.flex-col-reverse{flex-direction:column-reverse}.flex-row{flex-direction:row}.flex-nowrap{flex-wrap:nowrap}.flex-wrap{flex-wrap:wrap}.place-content-center{place-content:center}.place-items-center{place-items:center}.items-baseline{align-items:baseline}.items-center{align-items:center}.items-end{align-items:flex-end}.items-start{align-items:flex-start}.items-stretch{align-items:stretch}.justify-between{justify-content:space-between}.justify-center{justify-content:center}.justify-end{justify-content:flex-end}.justify-start{justify-content:flex-start}.gap-\(--card-spacing\){gap:var(--card-spacing)}.gap-0{gap:0}.gap-0\.5{gap:calc(var(--spacing) * .5)}.gap-1{gap:var(--spacing)}.gap-1\.5{gap:calc(var(--spacing) * 1.5)}.gap-2{gap:calc(var(--spacing) * 2)}.gap-2\.5{gap:calc(var(--spacing) * 2.5)}.gap-3{gap:calc(var(--spacing) * 3)}.gap-4{gap:calc(var(--spacing) * 4)}.gap-5{gap:calc(var(--spacing) * 5)}.gap-6{gap:calc(var(--spacing) * 6)}.gap-7{gap:calc(var(--spacing) * 7)}.gap-8{gap:calc(var(--spacing) * 8)}.gap-10{gap:calc(var(--spacing) * 10)}.gap-16{gap:calc(var(--spacing) * 16)}.gap-px{gap:1px}:where(.space-y-0>:not(:last-child)){--tw-space-y-reverse:0;margin-block:0}:where(.space-y-0\.5>:not(:last-child)){--tw-space-y-reverse:0;margin-block-start:calc(calc(var(--spacing) * .5) * var(--tw-space-y-reverse));margin-block-end:calc(calc(var(--spacing) * .5) * calc(1 - var(--tw-space-y-reverse)))}:where(.space-y-1>:not(:last-child)){--tw-space-y-reverse:0;margin-block-start:calc(var(--spacing) * var(--tw-space-y-reverse));margin-block-end:calc(var(--spacing) * calc(1 - var(--tw-space-y-reverse)))}:where(.space-y-1\.5>:not(:last-child)){--tw-space-y-reverse:0;margin-block-start:calc(calc(var(--spacing) * 1.5) * var(--tw-space-y-reverse));margin-block-end:calc(calc(var(--spacing) * 1.5) * calc(1 - var(--tw-space-y-reverse)))}:where(.space-y-2>:not(:last-child)){--tw-space-y-reverse:0;margin-block-start:calc(calc(var(--spacing) * 2) * var(--tw-space-y-reverse));margin-block-end:calc(calc(var(--spacing) * 2) * calc(1 - var(--tw-space-y-reverse)))}:where(.space-y-3>:not(:last-child)){--tw-space-y-reverse:0;margin-block-start:calc(calc(var(--spacing) * 3) * var(--tw-space-y-reverse));margin-block-end:calc(calc(var(--spacing) * 3) * calc(1 - var(--tw-space-y-reverse)))}:where(.space-y-4>:not(:last-child)){--tw-space-y-reverse:0;margin-block-start:calc(calc(var(--spacing) * 4) * var(--tw-space-y-reverse));margin-block-end:calc(calc(var(--spacing) * 4) * calc(1 - var(--tw-space-y-reverse)))}:where(.space-y-5>:not(:last-child)){--tw-space-y-reverse:0;margin-block-start:calc(calc(var(--spacing) * 5) * var(--tw-space-y-reverse));margin-block-end:calc(calc(var(--spacing) * 5) * calc(1 - var(--tw-space-y-reverse)))}:where(.space-y-6>:not(:last-child)){--tw-space-y-reverse:0;margin-block-start:calc(calc(var(--spacing) * 6) * var(--tw-space-y-reverse));margin-block-end:calc(calc(var(--spacing) * 6) * calc(1 - var(--tw-space-y-reverse)))}:where(.space-y-8>:not(:last-child)){--tw-space-y-reverse:0;margin-block-start:calc(calc(var(--spacing) * 8) * var(--tw-space-y-reverse));margin-block-end:calc(calc(var(--spacing) * 8) * calc(1 - var(--tw-space-y-reverse)))}.gap-x-2{column-gap:calc(var(--spacing) * 2)}.gap-x-3{column-gap:calc(var(--spacing) * 3)}.gap-x-4{column-gap:calc(var(--spacing) * 4)}.gap-x-6{column-gap:calc(var(--spacing) * 6)}.gap-x-8{column-gap:calc(var(--spacing) * 8)}:where(.space-x-1>:not(:last-child)){--tw-space-x-reverse:0;margin-inline-start:calc(var(--spacing) * var(--tw-space-x-reverse));margin-inline-end:calc(var(--spacing) * calc(1 - 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i={keyword:t,punctuation:/[()\[\]{};,:.<>]/};e.languages.apex={comment:e.languages.clike.comment,string:e.languages.clike.string,sql:{pattern:/((?:[=,({:]|\breturn)\s*)\[[^\[\]]*\]/i,lookbehind:!0,greedy:!0,alias:"language-sql",inside:e.languages.sql},annotation:{pattern:/@\w+\b/,alias:"punctuation"},"class-name":[{pattern:r(/(\b(?:class|enum|extends|implements|instanceof|interface|new|trigger\s+\w+\s+on)\s+)/.source),lookbehind:!0,inside:i},{pattern:r(/(\(\s*)(?=\s*\)\s*[\w(])/.source),lookbehind:!0,inside:i},{pattern:r(/(?=\s*\w+\s*[;=,(){:])/.source),inside:i}],trigger:{pattern:/(\btrigger\s+)\w+\b/i,lookbehind:!0,alias:"class-name"},keyword:t,function:/\b[a-z_]\w*(?=\s*\()/i,boolean:/\b(?:false|true)\b/i,number:/(?:\B\.\d+|\b\d+(?:\.\d+|L)?)\b/i,operator:/[!=](?:==?)?|\?\.?|&&|\|\||--|\+\+|[-+*/^&|]=?|:|<{1,3}=?/,punctuation:/[()\[\]{};,.]/}}t.exports=r,r.displayName="apex",r.aliases=[]},991642,(e,t,a)=>{"use strict";function n(e){e.languages.apl={comment:/(?:⍝|#[! 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t;e.register(n),t=[/"(?:\\[\s\S]|\$\([^)]+\)|\$(?!\()|`[^`]+`|[^"\\`$])*"/.source,/'[^']*'/.source,/\$'(?:[^'\\]|\\[\s\S])*'/.source,/<<-?\s*(["']?)(\w+)\1\s[\s\S]*?[\r\n]\2/.source].join("|"),e.languages["shell-session"]={command:{pattern:RegExp(/^/.source+"(?:"+/[^\s@:$#%*!/\\]+@[^\r\n@:$#%*!/\\]+(?::[^\0-\x1F$#%*?"<>:;|]+)?/.source+"|"+/[/~.][^\0-\x1F$#%*?"<>@:;|]*/.source+")?"+/[$#%](?=\s)/.source+/(?:[^\\\r\n \t'"<$]|[ \t](?:(?!#)|#.*$)|\\(?:[^\r]|\r\n?)|\$(?!')|<(?!<)|<>)+/.source.replace(/<>/g,function(){return t}),"m"),greedy:!0,inside:{info:{pattern:/^[^#$%]+/,alias:"punctuation",inside:{user:/^[^\s@:$#%*!/\\]+@[^\r\n@:$#%*!/\\]+/,punctuation:/:/,path:/[\s\S]+/}},bash:{pattern:/(^[$#%]\s*)\S[\s\S]*/,lookbehind:!0,alias:"language-bash",inside:e.languages.bash},"shell-symbol":{pattern:/^[$#%]/,alias:"important"}}},output:/.(?:.*(?:[\r\n]|.$))*/},e.languages["sh-session"]=e.languages.shellsession=e.languages["shell-session"]}t.exports=r,r.displayName="shellSession",r.aliases=[]},864488,(e,t,a)=>{"use strict";function n(e){e.languages.smali={comment:/#.*/,string:{pattern:/"(?:[^\r\n\\"]|\\.)*"|'(?:[^\r\n\\']|\\(?:.|u[\da-fA-F]{4}))'/,greedy:!0},"class-name":{pattern:/(^|[^L])L(?:(?:\w+|`[^`\r\n]*`)\/)*(?:[\w$]+|`[^`\r\n]*`)(?=\s*;)/,lookbehind:!0,inside:{"class-name":{pattern:/(^L|\/)(?:[\w$]+|`[^`\r\n]*`)$/,lookbehind:!0},namespace:{pattern:/^(L)(?:(?:\w+|`[^`\r\n]*`)\/)+/,lookbehind:!0,inside:{punctuation:/\//}},builtin:/^L/}},builtin:[{pattern:/([();\[])[BCDFIJSVZ]+/,lookbehind:!0},{pattern:/([\w$>]:)[BCDFIJSVZ]/,lookbehind:!0}],keyword:[{pattern:/(\.end\s+)[\w-]+/,lookbehind:!0},{pattern:/(^|[^\w.-])\.(?!\d)[\w-]+/,lookbehind:!0},{pattern:/(^|[^\w.-])(?:abstract|annotation|bridge|constructor|enum|final|interface|private|protected|public|runtime|static|synthetic|system|transient)(?![\w.-])/,lookbehind:!0}],function:{pattern:/(^|[^\w.-])(?:\w+|<[\w$-]+>)(?=\()/,lookbehind:!0},field:{pattern:/[\w$]+(?=:)/,alias:"variable"},register:{pattern:/(^|[^\w.-])[vp]\d(?![\w.-])/,lookbehind:!0,alias:"variable"},boolean:{pattern:/(^|[^\w.-])(?:false|true)(?![\w.-])/,lookbehind:!0},number:{pattern:/(^|[^/\w.-])-?(?:NAN|INFINITY|0x(?:[\dA-F]+(?:\.[\dA-F]*)?|\.[\dA-F]+)(?:p[+-]?[\dA-F]+)?|(?:\d+(?:\.\d*)?|\.\d+)(?:e[+-]?\d+)?)[dflst]?(?![\w.-])/i,lookbehind:!0},label:{pattern:/(:)\w+/,lookbehind:!0,alias:"property"},operator:/->|\.\.|[\[=]/,punctuation:/[{}(),;:]/}}t.exports=n,n.displayName="smali",n.aliases=[]},223592,(e,t,a)=>{"use strict";function n(e){e.languages.smalltalk={comment:{pattern:/"(?:""|[^"])*"/,greedy:!0},char:{pattern:/\$./,greedy:!0},string:{pattern:/'(?:''|[^'])*'/,greedy:!0},symbol:/#[\da-z]+|#(?:-|([+\/\\*~<>=@%|&?!])\1?)|#(?=\()/i,"block-arguments":{pattern:/(\[\s*):[^\[|]*\|/,lookbehind:!0,inside:{variable:/:[\da-z]+/i,punctuation:/\|/}},"temporary-variables":{pattern:/\|[^|]+\|/,inside:{variable:/[\da-z]+/i,punctuation:/\|/}},keyword:/\b(?:new|nil|self|super)\b/,boolean:/\b(?:false|true)\b/,number:[/\d+r-?[\dA-Z]+(?:\.[\dA-Z]+)?(?:e-?\d+)?/,/\b\d+(?:\.\d+)?(?:e-?\d+)?/],operator:/[<=]=?|:=|~[~=]|\/\/?|\\\\|>[>=]?|[!^+\-*&|,@]/,punctuation:/[.;:?\[\](){}]/}}t.exports=n,n.displayName="smalltalk",n.aliases=[]},935950,(e,t,a)=>{"use strict";var n=e.r(426226);function r(e){var t,a;e.register(n),e.languages.smarty={comment:{pattern:/^\{\*[\s\S]*?\*\}/,greedy:!0},"embedded-php":{pattern:/^\{php\}[\s\S]*?\{\/php\}/,greedy:!0,inside:{smarty:{pattern:/^\{php\}|\{\/php\}$/,inside:null},php:{pattern:/[\s\S]+/,alias:"language-php",inside:e.languages.php}}},string:[{pattern:/"(?:\\.|[^"\\\r\n])*"/,greedy:!0,inside:{interpolation:{pattern:/\{[^{}]*\}|`[^`]*`/,inside:{"interpolation-punctuation":{pattern:/^[{`]|[`}]$/,alias:"punctuation"},expression:{pattern:/[\s\S]+/,inside:null}}},variable:/\$\w+/}},{pattern:/'(?:\\.|[^'\\\r\n])*'/,greedy:!0}],keyword:{pattern:/(^\{\/?)[a-z_]\w*\b(?!\()/i,lookbehind:!0,greedy:!0},delimiter:{pattern:/^\{\/?|\}$/,greedy:!0,alias:"punctuation"},number:/\b0x[\dA-Fa-f]+|(?:\b\d+(?:\.\d*)?|\B\.\d+)(?:[Ee][-+]?\d+)?/,variable:[/\$(?!\d)\w+/,/#(?!\d)\w+#/,{pattern:/(\.|->|\w\s*=)(?!\d)\w+\b(?!\()/,lookbehind:!0},{pattern:/(\[)(?!\d)\w+(?=\])/,lookbehind:!0}],function:{pattern:/(\|\s*)@?[a-z_]\w*|\b[a-z_]\w*(?=\()/i,lookbehind:!0},"attr-name":/\b[a-z_]\w*(?=\s*=)/i,boolean:/\b(?:false|no|off|on|true|yes)\b/,punctuation:/[\[\](){}.,:`]|->/,operator:[/[+\-*\/%]|==?=?|[!<>]=?|&&|\|\|?/,/\bis\s+(?:not\s+)?(?:div|even|odd)(?:\s+by)?\b/,/\b(?:and|eq|gt?e|gt|lt?e|lt|mod|neq?|not|or)\b/]},e.languages.smarty["embedded-php"].inside.smarty.inside=e.languages.smarty,e.languages.smarty.string[0].inside.interpolation.inside.expression.inside=e.languages.smarty,t=/"(?:\\.|[^"\\\r\n])*"|'(?:\\.|[^'\\\r\n])*'/,a=RegExp(/\{\*[\s\S]*?\*\}/.source+"|"+/\{php\}[\s\S]*?\{\/php\}/.source+"|"+/\{(?:[^{}"']||\{(?:[^{}"']||\{(?:[^{}"']|)*\})*\})*\}/.source.replace(//g,function(){return t.source}),"g"),e.hooks.add("before-tokenize",function(t){var n=!1;e.languages["markup-templating"].buildPlaceholders(t,"smarty",a,function(e){return"{/literal}"===e&&(n=!1),!n&&("{literal}"===e&&(n=!0),!0)})}),e.hooks.add("after-tokenize",function(t){e.languages["markup-templating"].tokenizePlaceholders(t,"smarty")})}t.exports=r,r.displayName="smarty",r.aliases=[]},888705,(e,t,a)=>{"use strict";function n(e){var t;t=/\b(?:abstype|and|andalso|as|case|datatype|do|else|end|eqtype|exception|fn|fun|functor|handle|if|in|include|infix|infixr|let|local|nonfix|of|op|open|orelse|raise|rec|sharing|sig|signature|struct|structure|then|type|val|where|while|with|withtype)\b/i,e.languages.sml={comment:/\(\*(?:[^*(]|\*(?!\))|\((?!\*)|\(\*(?:[^*(]|\*(?!\))|\((?!\*))*\*\))*\*\)/,string:{pattern:/#?"(?:[^"\\]|\\.)*"/,greedy:!0},"class-name":[{pattern:RegExp(/((?:^|[^:]):\s*)(?:\s*(?:(?:\*|->)\s*|,\s*(?:(?=)|(?!)\s+)))*/.source.replace(//g,function(){return/\s*(?:[*,]|->)/.source}).replace(//g,function(){return/(?:'[\w']*||\((?:[^()]|\([^()]*\))*\)|\{(?:[^{}]|\{[^{}]*\})*\})(?:\s+)*/.source}).replace(//g,function(){return/(?!)[a-z\d_][\w'.]*/.source}).replace(//g,function(){return 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n(e){e.languages.solidity=e.languages.extend("clike",{"class-name":{pattern:/(\b(?:contract|enum|interface|library|new|struct|using)\s+)(?!\d)[\w$]+/,lookbehind:!0},keyword:/\b(?:_|anonymous|as|assembly|assert|break|calldata|case|constant|constructor|continue|contract|default|delete|do|else|emit|enum|event|external|for|from|function|if|import|indexed|inherited|interface|internal|is|let|library|mapping|memory|modifier|new|payable|pragma|private|public|pure|require|returns?|revert|selfdestruct|solidity|storage|struct|suicide|switch|this|throw|using|var|view|while)\b/,operator:/=>|->|:=|=:|\*\*|\+\+|--|\|\||&&|<<=?|>>=?|[-+*/%^&|<>!=]=?|[~?]/}),e.languages.insertBefore("solidity","keyword",{builtin:/\b(?:address|bool|byte|u?int(?:8|16|24|32|40|48|56|64|72|80|88|96|104|112|120|128|136|144|152|160|168|176|184|192|200|208|216|224|232|240|248|256)?|string|bytes(?:[1-9]|[12]\d|3[0-2])?)\b/}),e.languages.insertBefore("solidity","number",{version:{pattern:/([<>]=?|\^)\d+\.\d+\.\d+\b/,lookbehind:!0,alias:"number"}}),e.languages.sol=e.languages.solidity}t.exports=n,n.displayName="solidity",n.aliases=["sol"]},285035,(e,t,a)=>{"use 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t,a;e.register(n),t=/(["'])(?:\\(?:\r\n|[\s\S])|(?!\1)[^\\\r\n])*\1/,a=/\b\d+(?:\.\d+)?(?:[eE][+-]?\d+)?\b|\b0x[\dA-F]+\b/,e.languages.soy={comment:[/\/\*[\s\S]*?\*\//,{pattern:/(\s)\/\/.*/,lookbehind:!0,greedy:!0}],"command-arg":{pattern:/(\{+\/?\s*(?:alias|call|delcall|delpackage|deltemplate|namespace|template)\s+)\.?[\w.]+/,lookbehind:!0,alias:"string",inside:{punctuation:/\./}},parameter:{pattern:/(\{+\/?\s*@?param\??\s+)\.?[\w.]+/,lookbehind:!0,alias:"variable"},keyword:[{pattern:/(\{+\/?[^\S\r\n]*)(?:\\[nrt]|alias|call|case|css|default|delcall|delpackage|deltemplate|else(?:if)?|fallbackmsg|for(?:each)?|if(?:empty)?|lb|let|literal|msg|namespace|nil|@?param\??|rb|sp|switch|template|xid)/,lookbehind:!0},/\b(?:any|as|attributes|bool|css|float|html|in|int|js|list|map|null|number|string|uri)\b/],delimiter:{pattern:/^\{+\/?|\/?\}+$/,alias:"punctuation"},property:/\w+(?==)/,variable:{pattern:/\$[^\W\d]\w*(?:\??(?:\.\w+|\[[^\]]+\]))*/,inside:{string:{pattern:t,greedy:!0},number:a,punctuation:/[\[\].?]/}},string:{pattern:t,greedy:!0},function:[/\w+(?=\()/,{pattern:/(\|[^\S\r\n]*)\w+/,lookbehind:!0}],boolean:/\b(?:false|true)\b/,number:a,operator:/\?:?|<=?|>=?|==?|!=|[+*/%-]|\b(?:and|not|or)\b/,punctuation:/[{}()\[\]|.,:]/},e.hooks.add("before-tokenize",function(t){var a=!1;e.languages["markup-templating"].buildPlaceholders(t,"soy",/\{\{.+?\}\}|\{.+?\}|\s\/\/.*|\/\*[\s\S]*?\*\//g,function(e){return"{/literal}"===e&&(a=!1),!a&&("{literal}"===e&&(a=!0),!0)})}),e.hooks.add("after-tokenize",function(t){e.languages["markup-templating"].tokenizePlaceholders(t,"soy")})}t.exports=r,r.displayName="soy",r.aliases=[]},834341,(e,t,a)=>{"use strict";function n(e){e.languages.turtle={comment:{pattern:/#.*/,greedy:!0},"multiline-string":{pattern:/"""(?:(?:""?)?(?:[^"\\]|\\.))*"""|'''(?:(?:''?)?(?:[^'\\]|\\.))*'''/,greedy:!0,alias:"string",inside:{comment:/#.*/}},string:{pattern:/"(?:[^\\"\r\n]|\\.)*"|'(?:[^\\'\r\n]|\\.)*'/,greedy:!0},url:{pattern:/<(?:[^\x00-\x20<>"{}|^`\\]|\\(?:u[\da-fA-F]{4}|U[\da-fA-F]{8}))*>/,greedy:!0,inside:{punctuation:/[<>]/}},function:{pattern:/(?:(?![-.\d\xB7])[-.\w\xB7\xC0-\uFFFD]+)?:(?:(?![-.])(?:[-.:\w\xC0-\uFFFD]|%[\da-f]{2}|\\.)+)?/i,inside:{"local-name":{pattern:/([^:]*:)[\s\S]+/,lookbehind:!0},prefix:{pattern:/[\s\S]+/,inside:{punctuation:/:/}}}},number:/[+-]?\b\d+(?:\.\d*)?(?:e[+-]?\d+)?/i,punctuation:/[{}.,;()[\]]|\^\^/,boolean:/\b(?:false|true)\b/,keyword:[/(?:\ba|@prefix|@base)\b|=/,/\b(?:base|graph|prefix)\b/i],tag:{pattern:/@[a-z]+(?:-[a-z\d]+)*/i,inside:{punctuation:/@/}}},e.languages.trig=e.languages.turtle}t.exports=n,n.displayName="turtle",n.aliases=[]},46802,(e,t,a)=>{"use strict";var n=e.r(834341);function r(e){e.register(n),e.languages.sparql=e.languages.extend("turtle",{boolean:/\b(?:false|true)\b/i,variable:{pattern:/[?$]\w+/,greedy:!0}}),e.languages.insertBefore("sparql","punctuation",{keyword:[/\b(?:A|ADD|ALL|AS|ASC|ASK|BNODE|BY|CLEAR|CONSTRUCT|COPY|CREATE|DATA|DEFAULT|DELETE|DESC|DESCRIBE|DISTINCT|DROP|EXISTS|FILTER|FROM|GROUP|HAVING|INSERT|INTO|LIMIT|LOAD|MINUS|MOVE|NAMED|NOT|NOW|OFFSET|OPTIONAL|ORDER|RAND|REDUCED|SELECT|SEPARATOR|SERVICE|SILENT|STRUUID|UNION|USING|UUID|VALUES|WHERE)\b/i,/\b(?:ABS|AVG|BIND|BOUND|CEIL|COALESCE|CONCAT|CONTAINS|COUNT|DATATYPE|DAY|ENCODE_FOR_URI|FLOOR|GROUP_CONCAT|HOURS|IF|IRI|isBLANK|isIRI|isLITERAL|isNUMERIC|isURI|LANG|LANGMATCHES|LCASE|MAX|MD5|MIN|MINUTES|MONTH|REGEX|REPLACE|ROUND|sameTerm|SAMPLE|SECONDS|SHA1|SHA256|SHA384|SHA512|STR|STRAFTER|STRBEFORE|STRDT|STRENDS|STRLANG|STRLEN|STRSTARTS|SUBSTR|SUM|TIMEZONE|TZ|UCASE|URI|YEAR)\b(?=\s*\()/i,/\b(?:BASE|GRAPH|PREFIX)\b/i]}),e.languages.rq=e.languages.sparql}t.exports=r,r.displayName="sparql",r.aliases=["rq"]},424105,(e,t,a)=>{"use 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your prompt. -# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. -import os -import requests -import json -import time -from PIL import Image - -result = client.images.generate( - model="${C}", - prompt="${s}", - n=1 -) - -json_response = json.loads(result.model_dump_json()) - -# Set the directory for the stored image -image_dir = os.path.join(os.curdir, 'images') - -# If the directory doesn't exist, create it -if not os.path.isdir(image_dir): - os.mkdir(image_dir) - -# Initialize the image path -image_filename = f"generated_image_{int(time.time())}.png" -image_path = os.path.join(image_dir, image_filename) - -try: - # Retrieve the generated image - if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): - image_url = json_response["data"][0]["url"] - generated_image = requests.get(image_url).content - with open(image_path, "wb") as image_file: - image_file.write(generated_image) - - print(f"Image saved to {image_path}") - # Display the image - image = Image.open(image_path) - image.show() - else: - print("Could not find image URL in response.") - print("Full response:", json_response) -except Exception as e: - print(f"An error occurred: {e}") - print("Full response:", json_response) -`:` -import base64 -import os -import time -import json -from PIL import Image -import requests - -# Helper function to encode images to base64 -def encode_image(image_path): - with open(image_path, "rb") as image_file: - return base64.b64encode(image_file.read()).decode('utf-8') - -# Helper function to create a file (simplified for this example) -def create_file(image_path): - # In a real implementation, this would upload the file to OpenAI - # For this example, we'll just return a placeholder ID - return f"file_{os.path.basename(image_path).replace('.', '_')}" - -# The prompt entered by the user -prompt = "${_}" - -# Encode images to base64 -base64_image1 = encode_image("body-lotion.png") -base64_image2 = encode_image("soap.png") - -# Create file IDs -file_id1 = create_file("body-lotion.png") -file_id2 = create_file("incense-kit.png") - -response = client.responses.create( - model="${C}", - input=[ - { - "role": "user", - "content": [ - {"type": "input_text", "text": prompt}, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image1}", - }, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image2}", - }, - { - "type": "input_image", - "file_id": file_id1, - }, - { - "type": "input_image", - "file_id": file_id2, - } - ], - } - ], - tools=[{"type": "image_generation"}], -) - -# Process the response -image_generation_calls = [ - output - for output in response.output - if output.type == "image_generation_call" -] - -image_data = [output.result for output in image_generation_calls] - -if image_data: - image_base64 = image_data[0] - image_filename = 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q(e){let t="[0-5]\\d";e.precision?t=`${t}\\.\\d{${e.precision}}`:null==e.precision&&(t=`${t}(\\.\\d+)?`);let s=e.precision?"+":"?";return`([01]\\d|2[0-3]):[0-5]\\d(:${t})${s}`}function V(e){let t=`${B}T${q(e)}`,s=[];return s.push(e.local?"Z?":"Z"),e.offset&&s.push("([+-]\\d{2}:?\\d{2})"),t=`${t}(${s.join("|")})`,RegExp(`^${t}$`)}class K extends C{_parse(e){var s,a,i,l;let o;if(this._def.coerce&&(e.data=String(e.data)),this._getType(e)!==r.string){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.string,received:t.parsedType}),x}let d=new g;for(let r of this._def.checks)if("min"===r.kind)e.data.lengthr.value&&(f(o=this._getOrReturnCtx(e,o),{code:n.too_big,maximum:r.value,type:"string",inclusive:!0,exact:!1,message:r.message}),d.dirty());else if("length"===r.kind){let t=e.data.length>r.value,s=e.data.lengthe.test(t),{validation:t,code:n.invalid_string,...tp.errToObj(s)})}_addCheck(e){return new K({...this._def,checks:[...this._def.checks,e]})}email(e){return this._addCheck({kind:"email",...tp.errToObj(e)})}url(e){return this._addCheck({kind:"url",...tp.errToObj(e)})}emoji(e){return this._addCheck({kind:"emoji",...tp.errToObj(e)})}uuid(e){return this._addCheck({kind:"uuid",...tp.errToObj(e)})}nanoid(e){return this._addCheck({kind:"nanoid",...tp.errToObj(e)})}cuid(e){return this._addCheck({kind:"cuid",...tp.errToObj(e)})}cuid2(e){return this._addCheck({kind:"cuid2",...tp.errToObj(e)})}ulid(e){return this._addCheck({kind:"ulid",...tp.errToObj(e)})}base64(e){return this._addCheck({kind:"base64",...tp.errToObj(e)})}base64url(e){return this._addCheck({kind:"base64url",...tp.errToObj(e)})}jwt(e){return this._addCheck({kind:"jwt",...tp.errToObj(e)})}ip(e){return this._addCheck({kind:"ip",...tp.errToObj(e)})}cidr(e){return this._addCheck({kind:"cidr",...tp.errToObj(e)})}datetime(e){return"string"==typeof e?this._addCheck({kind:"datetime",precision:null,offset:!1,local:!1,message:e}):this._addCheck({kind:"datetime",precision:void 0===e?.precision?null:e?.precision,offset:e?.offset??!1,local:e?.local??!1,...tp.errToObj(e?.message)})}date(e){return this._addCheck({kind:"date",message:e})}time(e){return"string"==typeof e?this._addCheck({kind:"time",precision:null,message:e}):this._addCheck({kind:"time",precision:void 0===e?.precision?null:e?.precision,...tp.errToObj(e?.message)})}duration(e){return this._addCheck({kind:"duration",...tp.errToObj(e)})}regex(e,t){return this._addCheck({kind:"regex",regex:e,...tp.errToObj(t)})}includes(e,t){return this._addCheck({kind:"includes",value:e,position:t?.position,...tp.errToObj(t?.message)})}startsWith(e,t){return this._addCheck({kind:"startsWith",value:e,...tp.errToObj(t)})}endsWith(e,t){return this._addCheck({kind:"endsWith",value:e,...tp.errToObj(t)})}min(e,t){return this._addCheck({kind:"min",value:e,...tp.errToObj(t)})}max(e,t){return this._addCheck({kind:"max",value:e,...tp.errToObj(t)})}length(e,t){return this._addCheck({kind:"length",value:e,...tp.errToObj(t)})}nonempty(e){return this.min(1,tp.errToObj(e))}trim(){return new K({...this._def,checks:[...this._def.checks,{kind:"trim"}]})}toLowerCase(){return new K({...this._def,checks:[...this._def.checks,{kind:"toLowerCase"}]})}toUpperCase(){return new K({...this._def,checks:[...this._def.checks,{kind:"toUpperCase"}]})}get isDatetime(){return!!this._def.checks.find(e=>"datetime"===e.kind)}get isDate(){return!!this._def.checks.find(e=>"date"===e.kind)}get isTime(){return!!this._def.checks.find(e=>"time"===e.kind)}get isDuration(){return!!this._def.checks.find(e=>"duration"===e.kind)}get isEmail(){return!!this._def.checks.find(e=>"email"===e.kind)}get isURL(){return!!this._def.checks.find(e=>"url"===e.kind)}get isEmoji(){return!!this._def.checks.find(e=>"emoji"===e.kind)}get isUUID(){return!!this._def.checks.find(e=>"uuid"===e.kind)}get isNANOID(){return!!this._def.checks.find(e=>"nanoid"===e.kind)}get isCUID(){return!!this._def.checks.find(e=>"cuid"===e.kind)}get isCUID2(){return!!this._def.checks.find(e=>"cuid2"===e.kind)}get isULID(){return!!this._def.checks.find(e=>"ulid"===e.kind)}get isIP(){return!!this._def.checks.find(e=>"ip"===e.kind)}get isCIDR(){return!!this._def.checks.find(e=>"cidr"===e.kind)}get isBase64(){return!!this._def.checks.find(e=>"base64"===e.kind)}get isBase64url(){return!!this._def.checks.find(e=>"base64url"===e.kind)}get minLength(){let e=null;for(let t of this._def.checks)"min"===t.kind&&(null===e||t.value>e)&&(e=t.value);return e}get maxLength(){let e=null;for(let t of this._def.checks)"max"===t.kind&&(null===e||t.valuenew K({checks:[],typeName:tf.ZodString,coerce:e?.coerce??!1,...T(e)});class H extends C{constructor(){super(...arguments),this.min=this.gte,this.max=this.lte,this.step=this.multipleOf}_parse(e){let t;if(this._def.coerce&&(e.data=Number(e.data)),this._getType(e)!==r.number){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.number,received:t.parsedType}),x}let s=new g;for(let a of this._def.checks)"int"===a.kind?tm.isInteger(e.data)||(f(t=this._getOrReturnCtx(e,t),{code:n.invalid_type,expected:"integer",received:"float",message:a.message}),s.dirty()):"min"===a.kind?(a.inclusive?e.dataa.value:e.data>=a.value)&&(f(t=this._getOrReturnCtx(e,t),{code:n.too_big,maximum:a.value,type:"number",inclusive:a.inclusive,exact:!1,message:a.message}),s.dirty()):"multipleOf"===a.kind?0!==function(e,t){let s=(e.toString().split(".")[1]||"").length,a=(t.toString().split(".")[1]||"").length,r=s>a?s:a;return Number.parseInt(e.toFixed(r).replace(".",""))%Number.parseInt(t.toFixed(r).replace(".",""))/10**r}(e.data,a.value)&&(f(t=this._getOrReturnCtx(e,t),{code:n.not_multiple_of,multipleOf:a.value,message:a.message}),s.dirty()):"finite"===a.kind?Number.isFinite(e.data)||(f(t=this._getOrReturnCtx(e,t),{code:n.not_finite,message:a.message}),s.dirty()):tm.assertNever(a);return{status:s.value,value:e.data}}gte(e,t){return this.setLimit("min",e,!0,tp.toString(t))}gt(e,t){return this.setLimit("min",e,!1,tp.toString(t))}lte(e,t){return this.setLimit("max",e,!0,tp.toString(t))}lt(e,t){return this.setLimit("max",e,!1,tp.toString(t))}setLimit(e,t,s,a){return new H({...this._def,checks:[...this._def.checks,{kind:e,value:t,inclusive:s,message:tp.toString(a)}]})}_addCheck(e){return new H({...this._def,checks:[...this._def.checks,e]})}int(e){return this._addCheck({kind:"int",message:tp.toString(e)})}positive(e){return this._addCheck({kind:"min",value:0,inclusive:!1,message:tp.toString(e)})}negative(e){return this._addCheck({kind:"max",value:0,inclusive:!1,message:tp.toString(e)})}nonpositive(e){return this._addCheck({kind:"max",value:0,inclusive:!0,message:tp.toString(e)})}nonnegative(e){return this._addCheck({kind:"min",value:0,inclusive:!0,message:tp.toString(e)})}multipleOf(e,t){return this._addCheck({kind:"multipleOf",value:e,message:tp.toString(t)})}finite(e){return this._addCheck({kind:"finite",message:tp.toString(e)})}safe(e){return this._addCheck({kind:"min",inclusive:!0,value:Number.MIN_SAFE_INTEGER,message:tp.toString(e)})._addCheck({kind:"max",inclusive:!0,value:Number.MAX_SAFE_INTEGER,message:tp.toString(e)})}get minValue(){let e=null;for(let t of this._def.checks)"min"===t.kind&&(null===e||t.value>e)&&(e=t.value);return e}get maxValue(){let e=null;for(let t of this._def.checks)"max"===t.kind&&(null===e||t.value"int"===e.kind||"multipleOf"===e.kind&&tm.isInteger(e.value))}get isFinite(){let e=null,t=null;for(let s of this._def.checks)if("finite"===s.kind||"int"===s.kind||"multipleOf"===s.kind)return!0;else"min"===s.kind?(null===t||s.value>t)&&(t=s.value):"max"===s.kind&&(null===e||s.valuenew H({checks:[],typeName:tf.ZodNumber,coerce:e?.coerce||!1,...T(e)});class W extends C{constructor(){super(...arguments),this.min=this.gte,this.max=this.lte}_parse(e){let t;if(this._def.coerce)try{e.data=BigInt(e.data)}catch{return this._getInvalidInput(e)}if(this._getType(e)!==r.bigint)return this._getInvalidInput(e);let s=new g;for(let a of this._def.checks)"min"===a.kind?(a.inclusive?e.dataa.value:e.data>=a.value)&&(f(t=this._getOrReturnCtx(e,t),{code:n.too_big,type:"bigint",maximum:a.value,inclusive:a.inclusive,message:a.message}),s.dirty()):"multipleOf"===a.kind?e.data%a.value!==BigInt(0)&&(f(t=this._getOrReturnCtx(e,t),{code:n.not_multiple_of,multipleOf:a.value,message:a.message}),s.dirty()):tm.assertNever(a);return{status:s.value,value:e.data}}_getInvalidInput(e){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.bigint,received:t.parsedType}),x}gte(e,t){return this.setLimit("min",e,!0,tp.toString(t))}gt(e,t){return this.setLimit("min",e,!1,tp.toString(t))}lte(e,t){return this.setLimit("max",e,!0,tp.toString(t))}lt(e,t){return this.setLimit("max",e,!1,tp.toString(t))}setLimit(e,t,s,a){return new W({...this._def,checks:[...this._def.checks,{kind:e,value:t,inclusive:s,message:tp.toString(a)}]})}_addCheck(e){return new W({...this._def,checks:[...this._def.checks,e]})}positive(e){return this._addCheck({kind:"min",value:BigInt(0),inclusive:!1,message:tp.toString(e)})}negative(e){return this._addCheck({kind:"max",value:BigInt(0),inclusive:!1,message:tp.toString(e)})}nonpositive(e){return this._addCheck({kind:"max",value:BigInt(0),inclusive:!0,message:tp.toString(e)})}nonnegative(e){return this._addCheck({kind:"min",value:BigInt(0),inclusive:!0,message:tp.toString(e)})}multipleOf(e,t){return this._addCheck({kind:"multipleOf",value:e,message:tp.toString(t)})}get minValue(){let e=null;for(let t of this._def.checks)"min"===t.kind&&(null===e||t.value>e)&&(e=t.value);return e}get maxValue(){let e=null;for(let t of this._def.checks)"max"===t.kind&&(null===e||t.valuenew W({checks:[],typeName:tf.ZodBigInt,coerce:e?.coerce??!1,...T(e)});class G extends C{_parse(e){if(this._def.coerce&&(e.data=!!e.data),this._getType(e)!==r.boolean){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.boolean,received:t.parsedType}),x}return b(e.data)}}G.create=e=>new G({typeName:tf.ZodBoolean,coerce:e?.coerce||!1,...T(e)});class Y extends C{_parse(e){let t;if(this._def.coerce&&(e.data=new Date(e.data)),this._getType(e)!==r.date){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.date,received:t.parsedType}),x}if(Number.isNaN(e.data.getTime()))return f(this._getOrReturnCtx(e),{code:n.invalid_date}),x;let s=new g;for(let a of this._def.checks)"min"===a.kind?e.data.getTime()a.value&&(f(t=this._getOrReturnCtx(e,t),{code:n.too_big,message:a.message,inclusive:!0,exact:!1,maximum:a.value,type:"date"}),s.dirty()):tm.assertNever(a);return{status:s.value,value:new Date(e.data.getTime())}}_addCheck(e){return new Y({...this._def,checks:[...this._def.checks,e]})}min(e,t){return this._addCheck({kind:"min",value:e.getTime(),message:tp.toString(t)})}max(e,t){return this._addCheck({kind:"max",value:e.getTime(),message:tp.toString(t)})}get minDate(){let e=null;for(let t of this._def.checks)"min"===t.kind&&(null===e||t.value>e)&&(e=t.value);return null!=e?new Date(e):null}get maxDate(){let e=null;for(let t of this._def.checks)"max"===t.kind&&(null===e||t.valuenew Y({checks:[],coerce:e?.coerce||!1,typeName:tf.ZodDate,...T(e)});class X extends C{_parse(e){if(this._getType(e)!==r.symbol){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.symbol,received:t.parsedType}),x}return b(e.data)}}X.create=e=>new X({typeName:tf.ZodSymbol,...T(e)});class Q extends C{_parse(e){if(this._getType(e)!==r.undefined){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.undefined,received:t.parsedType}),x}return b(e.data)}}Q.create=e=>new Q({typeName:tf.ZodUndefined,...T(e)});class J extends C{_parse(e){if(this._getType(e)!==r.null){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.null,received:t.parsedType}),x}return b(e.data)}}J.create=e=>new J({typeName:tf.ZodNull,...T(e)});class ee extends C{constructor(){super(...arguments),this._any=!0}_parse(e){return b(e.data)}}ee.create=e=>new ee({typeName:tf.ZodAny,...T(e)});class et extends C{constructor(){super(...arguments),this._unknown=!0}_parse(e){return b(e.data)}}et.create=e=>new et({typeName:tf.ZodUnknown,...T(e)});class es extends C{_parse(e){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.never,received:t.parsedType}),x}}es.create=e=>new es({typeName:tf.ZodNever,...T(e)});class ea extends C{_parse(e){if(this._getType(e)!==r.undefined){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.void,received:t.parsedType}),x}return b(e.data)}}ea.create=e=>new ea({typeName:tf.ZodVoid,...T(e)});class er extends C{_parse(e){let{ctx:t,status:s}=this._processInputParams(e),a=this._def;if(t.parsedType!==r.array)return f(t,{code:n.invalid_type,expected:r.array,received:t.parsedType}),x;if(null!==a.exactLength){let e=t.data.length>a.exactLength.value,r=t.data.lengtha.maxLength.value&&(f(t,{code:n.too_big,maximum:a.maxLength.value,type:"array",inclusive:!0,exact:!1,message:a.maxLength.message}),s.dirty()),t.common.async)return Promise.all([...t.data].map((e,s)=>a.type._parseAsync(new N(t,e,t.path,s)))).then(e=>g.mergeArray(s,e));let i=[...t.data].map((e,s)=>a.type._parseSync(new N(t,e,t.path,s)));return g.mergeArray(s,i)}get element(){return this._def.type}min(e,t){return new er({...this._def,minLength:{value:e,message:tp.toString(t)}})}max(e,t){return new er({...this._def,maxLength:{value:e,message:tp.toString(t)}})}length(e,t){return new er({...this._def,exactLength:{value:e,message:tp.toString(t)}})}nonempty(e){return this.min(1,e)}}er.create=(e,t)=>new er({type:e,minLength:null,maxLength:null,exactLength:null,typeName:tf.ZodArray,...T(t)});class ei extends C{constructor(){super(...arguments),this._cached=null,this.nonstrict=this.passthrough,this.augment=this.extend}_getCached(){if(null!==this._cached)return this._cached;let e=this._def.shape(),t=tm.objectKeys(e);return this._cached={shape:e,keys:t},this._cached}_parse(e){if(this._getType(e)!==r.object){let t=this._getOrReturnCtx(e);return f(t,{code:n.invalid_type,expected:r.object,received:t.parsedType}),x}let{status:t,ctx:s}=this._processInputParams(e),{shape:a,keys:i}=this._getCached(),l=[];if(!(this._def.catchall instanceof es&&"strip"===this._def.unknownKeys))for(let e in s.data)i.includes(e)||l.push(e);let o=[];for(let e of i){let t=a[e],r=s.data[e];o.push({key:{status:"valid",value:e},value:t._parse(new N(s,r,s.path,e)),alwaysSet:e in s.data})}if(this._def.catchall instanceof es){let e=this._def.unknownKeys;if("passthrough"===e)for(let e of l)o.push({key:{status:"valid",value:e},value:{status:"valid",value:s.data[e]}});else if("strict"===e)l.length>0&&(f(s,{code:n.unrecognized_keys,keys:l}),t.dirty());else if("strip"===e);else throw Error("Internal ZodObject error: invalid unknownKeys value.")}else{let e=this._def.catchall;for(let t of l){let a=s.data[t];o.push({key:{status:"valid",value:t},value:e._parse(new N(s,a,s.path,t)),alwaysSet:t in s.data})}}return s.common.async?Promise.resolve().then(async()=>{let e=[];for(let t of o){let s=await t.key,a=await t.value;e.push({key:s,value:a,alwaysSet:t.alwaysSet})}return e}).then(e=>g.mergeObjectSync(t,e)):g.mergeObjectSync(t,o)}get shape(){return this._def.shape()}strict(e){return tp.errToObj,new ei({...this._def,unknownKeys:"strict",...void 0!==e?{errorMap:(t,s)=>{let a=this._def.errorMap?.(t,s).message??s.defaultError;return"unrecognized_keys"===t.code?{message:tp.errToObj(e).message??a}:{message:a}}}:{}})}strip(){return new ei({...this._def,unknownKeys:"strip"})}passthrough(){return new ei({...this._def,unknownKeys:"passthrough"})}extend(e){return new ei({...this._def,shape:()=>({...this._def.shape(),...e})})}merge(e){return new ei({unknownKeys:e._def.unknownKeys,catchall:e._def.catchall,shape:()=>({...this._def.shape(),...e._def.shape()}),typeName:tf.ZodObject})}setKey(e,t){return this.augment({[e]:t})}catchall(e){return new ei({...this._def,catchall:e})}pick(e){let t={};for(let s of tm.objectKeys(e))e[s]&&this.shape[s]&&(t[s]=this.shape[s]);return new ei({...this._def,shape:()=>t})}omit(e){let t={};for(let s of tm.objectKeys(this.shape))e[s]||(t[s]=this.shape[s]);return new ei({...this._def,shape:()=>t})}deepPartial(){return function e(t){if(t instanceof ei){let s={};for(let a in t.shape){let r=t.shape[a];s[a]=ej.create(e(r))}return new ei({...t._def,shape:()=>s})}if(t instanceof er)return new er({...t._def,type:e(t.element)});if(t instanceof ej)return ej.create(e(t.unwrap()));if(t instanceof ew)return ew.create(e(t.unwrap()));if(t instanceof ec)return ec.create(t.items.map(t=>e(t)));else return t}(this)}partial(e){let t={};for(let s of tm.objectKeys(this.shape)){let a=this.shape[s];e&&!e[s]?t[s]=a:t[s]=a.optional()}return new ei({...this._def,shape:()=>t})}required(e){let t={};for(let s of tm.objectKeys(this.shape))if(e&&!e[s])t[s]=this.shape[s];else{let e=this.shape[s];for(;e instanceof ej;)e=e._def.innerType;t[s]=e}return new ei({...this._def,shape:()=>t})}keyof(){return ex(tm.objectKeys(this.shape))}}ei.create=(e,t)=>new ei({shape:()=>e,unknownKeys:"strip",catchall:es.create(),typeName:tf.ZodObject,...T(t)}),ei.strictCreate=(e,t)=>new ei({shape:()=>e,unknownKeys:"strict",catchall:es.create(),typeName:tf.ZodObject,...T(t)}),ei.lazycreate=(e,t)=>new ei({shape:e,unknownKeys:"strip",catchall:es.create(),typeName:tf.ZodObject,...T(t)});class en extends C{_parse(e){let{ctx:t}=this._processInputParams(e),s=this._def.options;if(t.common.async)return Promise.all(s.map(async e=>{let s={...t,common:{...t.common,issues:[]},parent:null};return{result:await e._parseAsync({data:t.data,path:t.path,parent:s}),ctx:s}})).then(function(e){for(let t of e)if("valid"===t.result.status)return t.result;for(let s of e)if("dirty"===s.result.status)return t.common.issues.push(...s.ctx.common.issues),s.result;let s=e.map(e=>new o(e.ctx.common.issues));return f(t,{code:n.invalid_union,unionErrors:s}),x});{let e,a=[];for(let r of s){let s={...t,common:{...t.common,issues:[]},parent:null},i=r._parseSync({data:t.data,path:t.path,parent:s});if("valid"===i.status)return i;"dirty"!==i.status||e||(e={result:i,ctx:s}),s.common.issues.length&&a.push(s.common.issues)}if(e)return t.common.issues.push(...e.ctx.common.issues),e.result;let r=a.map(e=>new o(e));return f(t,{code:n.invalid_union,unionErrors:r}),x}}get options(){return this._def.options}}en.create=(e,t)=>new en({options:e,typeName:tf.ZodUnion,...T(t)});let el=e=>{if(e instanceof ef)return el(e.schema);if(e instanceof ey)return el(e.innerType());if(e instanceof eg)return[e.value];if(e instanceof e_)return e.options;if(e instanceof eb)return tm.objectValues(e.enum);else if(e instanceof eN)return el(e._def.innerType);else if(e instanceof Q)return[void 0];else if(e instanceof J)return[null];else if(e instanceof ej)return[void 0,...el(e.unwrap())];else if(e instanceof ew)return[null,...el(e.unwrap())];else if(e instanceof eS)return el(e.unwrap());else if(e instanceof eE)return el(e.unwrap());else if(e instanceof ek)return el(e._def.innerType);else return[]};class eo extends C{_parse(e){let{ctx:t}=this._processInputParams(e);if(t.parsedType!==r.object)return f(t,{code:n.invalid_type,expected:r.object,received:t.parsedType}),x;let s=this.discriminator,a=t.data[s],i=this.optionsMap.get(a);return i?t.common.async?i._parseAsync({data:t.data,path:t.path,parent:t}):i._parseSync({data:t.data,path:t.path,parent:t}):(f(t,{code:n.invalid_union_discriminator,options:Array.from(this.optionsMap.keys()),path:[s]}),x)}get discriminator(){return this._def.discriminator}get options(){return this._def.options}get optionsMap(){return this._def.optionsMap}static create(e,t,s){let a=new Map;for(let s of t){let t=el(s.shape[e]);if(!t.length)throw Error(`A discriminator value for key \`${e}\` could not be extracted from all schema options`);for(let r of t){if(a.has(r))throw Error(`Discriminator property ${String(e)} has duplicate value ${String(r)}`);a.set(r,s)}}return new eo({typeName:tf.ZodDiscriminatedUnion,discriminator:e,options:t,optionsMap:a,...T(s)})}}class ed extends C{_parse(e){let{status:t,ctx:s}=this._processInputParams(e),a=(e,a)=>{if(v(e)||v(a))return x;let l=function e(t,s){let a=i(t),n=i(s);if(t===s)return{valid:!0,data:t};if(a===r.object&&n===r.object){let a=tm.objectKeys(s),r=tm.objectKeys(t).filter(e=>-1!==a.indexOf(e)),i={...t,...s};for(let a of r){let r=e(t[a],s[a]);if(!r.valid)return{valid:!1};i[a]=r.data}return{valid:!0,data:i}}if(a===r.array&&n===r.array){if(t.length!==s.length)return{valid:!1};let a=[];for(let r=0;ra(e,t)):a(this._def.left._parseSync({data:s.data,path:s.path,parent:s}),this._def.right._parseSync({data:s.data,path:s.path,parent:s}))}}ed.create=(e,t,s)=>new ed({left:e,right:t,typeName:tf.ZodIntersection,...T(s)});class ec extends C{_parse(e){let{status:t,ctx:s}=this._processInputParams(e);if(s.parsedType!==r.array)return f(s,{code:n.invalid_type,expected:r.array,received:s.parsedType}),x;if(s.data.lengththis._def.items.length&&(f(s,{code:n.too_big,maximum:this._def.items.length,inclusive:!0,exact:!1,type:"array"}),t.dirty());let a=[...s.data].map((e,t)=>{let a=this._def.items[t]||this._def.rest;return a?a._parse(new N(s,e,s.path,t)):null}).filter(e=>!!e);return s.common.async?Promise.all(a).then(e=>g.mergeArray(t,e)):g.mergeArray(t,a)}get items(){return this._def.items}rest(e){return new ec({...this._def,rest:e})}}ec.create=(e,t)=>{if(!Array.isArray(e))throw Error("You must pass an array of schemas to z.tuple([ ... ])");return new ec({items:e,typeName:tf.ZodTuple,rest:null,...T(t)})};class eu extends C{get keySchema(){return this._def.keyType}get valueSchema(){return this._def.valueType}_parse(e){let{status:t,ctx:s}=this._processInputParams(e);if(s.parsedType!==r.object)return f(s,{code:n.invalid_type,expected:r.object,received:s.parsedType}),x;let a=[],i=this._def.keyType,l=this._def.valueType;for(let e in s.data)a.push({key:i._parse(new N(s,e,s.path,e)),value:l._parse(new N(s,s.data[e],s.path,e)),alwaysSet:e in s.data});return s.common.async?g.mergeObjectAsync(t,a):g.mergeObjectSync(t,a)}get element(){return this._def.valueType}static create(e,t,s){return new eu(t instanceof C?{keyType:e,valueType:t,typeName:tf.ZodRecord,...T(s)}:{keyType:K.create(),valueType:e,typeName:tf.ZodRecord,...T(t)})}}class em extends C{get keySchema(){return this._def.keyType}get valueSchema(){return this._def.valueType}_parse(e){let{status:t,ctx:s}=this._processInputParams(e);if(s.parsedType!==r.map)return f(s,{code:n.invalid_type,expected:r.map,received:s.parsedType}),x;let a=this._def.keyType,i=this._def.valueType,l=[...s.data.entries()].map(([e,t],r)=>({key:a._parse(new N(s,e,s.path,[r,"key"])),value:i._parse(new N(s,t,s.path,[r,"value"]))}));if(s.common.async){let e=new Map;return Promise.resolve().then(async()=>{for(let s of l){let a=await s.key,r=await s.value;if("aborted"===a.status||"aborted"===r.status)return x;("dirty"===a.status||"dirty"===r.status)&&t.dirty(),e.set(a.value,r.value)}return{status:t.value,value:e}})}{let e=new Map;for(let s of l){let a=s.key,r=s.value;if("aborted"===a.status||"aborted"===r.status)return x;("dirty"===a.status||"dirty"===r.status)&&t.dirty(),e.set(a.value,r.value)}return{status:t.value,value:e}}}}em.create=(e,t,s)=>new em({valueType:t,keyType:e,typeName:tf.ZodMap,...T(s)});class eh extends C{_parse(e){let{status:t,ctx:s}=this._processInputParams(e);if(s.parsedType!==r.set)return f(s,{code:n.invalid_type,expected:r.set,received:s.parsedType}),x;let a=this._def;null!==a.minSize&&s.data.sizea.maxSize.value&&(f(s,{code:n.too_big,maximum:a.maxSize.value,type:"set",inclusive:!0,exact:!1,message:a.maxSize.message}),t.dirty());let i=this._def.valueType;function l(e){let s=new Set;for(let a of e){if("aborted"===a.status)return x;"dirty"===a.status&&t.dirty(),s.add(a.value)}return{status:t.value,value:s}}let o=[...s.data.values()].map((e,t)=>i._parse(new N(s,e,s.path,t)));return s.common.async?Promise.all(o).then(e=>l(e)):l(o)}min(e,t){return new eh({...this._def,minSize:{value:e,message:tp.toString(t)}})}max(e,t){return new eh({...this._def,maxSize:{value:e,message:tp.toString(t)}})}size(e,t){return this.min(e,t).max(e,t)}nonempty(e){return this.min(1,e)}}eh.create=(e,t)=>new eh({valueType:e,minSize:null,maxSize:null,typeName:tf.ZodSet,...T(t)});class ep extends C{constructor(){super(...arguments),this.validate=this.implement}_parse(e){let{ctx:t}=this._processInputParams(e);if(t.parsedType!==r.function)return f(t,{code:n.invalid_type,expected:r.function,received:t.parsedType}),x;function s(e,s){return h({data:e,path:t.path,errorMaps:[t.common.contextualErrorMap,t.schemaErrorMap,m(),d].filter(e=>!!e),issueData:{code:n.invalid_arguments,argumentsError:s}})}function a(e,s){return h({data:e,path:t.path,errorMaps:[t.common.contextualErrorMap,t.schemaErrorMap,m(),d].filter(e=>!!e),issueData:{code:n.invalid_return_type,returnTypeError:s}})}let i={errorMap:t.common.contextualErrorMap},l=t.data;if(this._def.returns instanceof ev){let e=this;return b(async function(...t){let r=new o([]),n=await e._def.args.parseAsync(t,i).catch(e=>{throw r.addIssue(s(t,e)),r}),d=await Reflect.apply(l,this,n);return await e._def.returns._def.type.parseAsync(d,i).catch(e=>{throw r.addIssue(a(d,e)),r})})}{let e=this;return b(function(...t){let r=e._def.args.safeParse(t,i);if(!r.success)throw new o([s(t,r.error)]);let n=Reflect.apply(l,this,r.data),d=e._def.returns.safeParse(n,i);if(!d.success)throw new o([a(n,d.error)]);return d.data})}}parameters(){return this._def.args}returnType(){return this._def.returns}args(...e){return new ep({...this._def,args:ec.create(e).rest(et.create())})}returns(e){return new ep({...this._def,returns:e})}implement(e){return this.parse(e)}strictImplement(e){return this.parse(e)}static create(e,t,s){return new ep({args:e||ec.create([]).rest(et.create()),returns:t||et.create(),typeName:tf.ZodFunction,...T(s)})}}class ef extends C{get schema(){return this._def.getter()}_parse(e){let{ctx:t}=this._processInputParams(e);return this._def.getter()._parse({data:t.data,path:t.path,parent:t})}}ef.create=(e,t)=>new ef({getter:e,typeName:tf.ZodLazy,...T(t)});class eg extends C{_parse(e){if(e.data!==this._def.value){let t=this._getOrReturnCtx(e);return f(t,{received:t.data,code:n.invalid_literal,expected:this._def.value}),x}return{status:"valid",value:e.data}}get value(){return this._def.value}}function ex(e,t){return new e_({values:e,typeName:tf.ZodEnum,...T(t)})}eg.create=(e,t)=>new eg({value:e,typeName:tf.ZodLiteral,...T(t)});class e_ extends C{_parse(e){if("string"!=typeof e.data){let t=this._getOrReturnCtx(e),s=this._def.values;return f(t,{expected:tm.joinValues(s),received:t.parsedType,code:n.invalid_type}),x}if(this._cache||(this._cache=new Set(this._def.values)),!this._cache.has(e.data)){let t=this._getOrReturnCtx(e),s=this._def.values;return f(t,{received:t.data,code:n.invalid_enum_value,options:s}),x}return b(e.data)}get options(){return this._def.values}get enum(){let e={};for(let t of this._def.values)e[t]=t;return e}get Values(){let e={};for(let t of this._def.values)e[t]=t;return e}get Enum(){let e={};for(let t of this._def.values)e[t]=t;return e}extract(e,t=this._def){return e_.create(e,{...this._def,...t})}exclude(e,t=this._def){return e_.create(this.options.filter(t=>!e.includes(t)),{...this._def,...t})}}e_.create=ex;class eb extends C{_parse(e){let t=tm.getValidEnumValues(this._def.values),s=this._getOrReturnCtx(e);if(s.parsedType!==r.string&&s.parsedType!==r.number){let e=tm.objectValues(t);return f(s,{expected:tm.joinValues(e),received:s.parsedType,code:n.invalid_type}),x}if(this._cache||(this._cache=new Set(tm.getValidEnumValues(this._def.values))),!this._cache.has(e.data)){let e=tm.objectValues(t);return f(s,{received:s.data,code:n.invalid_enum_value,options:e}),x}return b(e.data)}get enum(){return this._def.values}}eb.create=(e,t)=>new eb({values:e,typeName:tf.ZodNativeEnum,...T(t)});class ev extends C{unwrap(){return this._def.type}_parse(e){let{ctx:t}=this._processInputParams(e);return t.parsedType!==r.promise&&!1===t.common.async?(f(t,{code:n.invalid_type,expected:r.promise,received:t.parsedType}),x):b((t.parsedType===r.promise?t.data:Promise.resolve(t.data)).then(e=>this._def.type.parseAsync(e,{path:t.path,errorMap:t.common.contextualErrorMap})))}}ev.create=(e,t)=>new ev({type:e,typeName:tf.ZodPromise,...T(t)});class ey extends C{innerType(){return this._def.schema}sourceType(){return this._def.schema._def.typeName===tf.ZodEffects?this._def.schema.sourceType():this._def.schema}_parse(e){let{status:t,ctx:s}=this._processInputParams(e),a=this._def.effect||null,r={addIssue:e=>{f(s,e),e.fatal?t.abort():t.dirty()},get path(){return s.path}};if(r.addIssue=r.addIssue.bind(r),"preprocess"===a.type){let e=a.transform(s.data,r);if(s.common.async)return Promise.resolve(e).then(async e=>{if("aborted"===t.value)return x;let a=await this._def.schema._parseAsync({data:e,path:s.path,parent:s});return"aborted"===a.status?x:"dirty"===a.status||"dirty"===t.value?_(a.value):a});{if("aborted"===t.value)return x;let a=this._def.schema._parseSync({data:e,path:s.path,parent:s});return"aborted"===a.status?x:"dirty"===a.status||"dirty"===t.value?_(a.value):a}}if("refinement"===a.type){let e=e=>{let t=a.refinement(e,r);if(s.common.async)return Promise.resolve(t);if(t instanceof Promise)throw Error("Async refinement encountered during synchronous parse operation. Use .parseAsync instead.");return e};if(!1!==s.common.async)return this._def.schema._parseAsync({data:s.data,path:s.path,parent:s}).then(s=>"aborted"===s.status?x:("dirty"===s.status&&t.dirty(),e(s.value).then(()=>({status:t.value,value:s.value}))));{let a=this._def.schema._parseSync({data:s.data,path:s.path,parent:s});return"aborted"===a.status?x:("dirty"===a.status&&t.dirty(),e(a.value),{status:t.value,value:a.value})}}if("transform"===a.type)if(!1!==s.common.async)return this._def.schema._parseAsync({data:s.data,path:s.path,parent:s}).then(e=>j(e)?Promise.resolve(a.transform(e.value,r)).then(e=>({status:t.value,value:e})):x);else{let e=this._def.schema._parseSync({data:s.data,path:s.path,parent:s});if(!j(e))return x;let i=a.transform(e.value,r);if(i instanceof Promise)throw Error("Asynchronous transform encountered during synchronous parse operation. Use .parseAsync instead.");return{status:t.value,value:i}}tm.assertNever(a)}}ey.create=(e,t,s)=>new ey({schema:e,typeName:tf.ZodEffects,effect:t,...T(s)}),ey.createWithPreprocess=(e,t,s)=>new ey({schema:t,effect:{type:"preprocess",transform:e},typeName:tf.ZodEffects,...T(s)});class ej extends C{_parse(e){return this._getType(e)===r.undefined?b(void 0):this._def.innerType._parse(e)}unwrap(){return this._def.innerType}}ej.create=(e,t)=>new ej({innerType:e,typeName:tf.ZodOptional,...T(t)});class ew extends C{_parse(e){return this._getType(e)===r.null?b(null):this._def.innerType._parse(e)}unwrap(){return this._def.innerType}}ew.create=(e,t)=>new ew({innerType:e,typeName:tf.ZodNullable,...T(t)});class eN extends C{_parse(e){let{ctx:t}=this._processInputParams(e),s=t.data;return t.parsedType===r.undefined&&(s=this._def.defaultValue()),this._def.innerType._parse({data:s,path:t.path,parent:t})}removeDefault(){return this._def.innerType}}eN.create=(e,t)=>new 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i={image_generation:"image",video_generation:"video",chat:"chat",completion:"chat",responses:"responses",image_edit:"image_edits",anthropic_messages:"anthropic_messages",audio_speech:"speech",audio_transcription:"transcription",embedding:"embeddings",realtime:"realtime"};e.s(["EndpointType",()=>r,"ModelMode",()=>s,"getEndpointType",0,e=>Object.values(s).includes(e)?i[e]:"chat"],865361),e.s(["generateCodeSnippet",0,e=>{let t,{apiKeySource:a,accessToken:s,apiKey:i,inputMessage:n,chatHistory:o,selectedTags:l,selectedVectorStores:d,selectedGuardrails:c,selectedPolicies:m,selectedVoice:p,endpointType:u,selectedModel:g,selectedSdk:h,proxySettings:x}=e,f="session"===a?s:i,b=window.location.origin,_=x?.LITELLM_UI_API_DOC_BASE_URL;_&&_.trim()?b=_:x?.PROXY_BASE_URL&&(b=x.PROXY_BASE_URL);let j=n||"Your prompt 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with text only -response = client.chat.completions.create( - model="${N}", - messages=${JSON.stringify(s,null,4)}${a} -) - -print(response) - -# Example with image or PDF (uncomment and provide file path to use) -# base64_file = encode_image("path/to/your/file.jpg") # or .pdf -# response_with_file = client.chat.completions.create( -# model="${N}", -# messages=[ -# { -# "role": "user", -# "content": [ -# { -# "type": "text", -# "text": "${y}" -# }, -# { -# "type": "image_url", -# "image_url": { -# "url": f"data:image/jpeg;base64,{base64_file}" # or data:application/pdf;base64,{base64_file} -# } -# } -# ] -# } -# ]${a} -# ) -# print(response_with_file) -`;break}case r.RESPONSES:{let e=Object.keys(v).length>0,a="";if(e){let e=JSON.stringify({metadata:v},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();a=`, - extra_body=${e}`}let s=w.length>0?w:[{role:"user",content:j}];t=` -import base64 - -# Helper function to encode images to base64 -def encode_image(image_path): - with open(image_path, "rb") as image_file: - return base64.b64encode(image_file.read()).decode('utf-8') - -# Example with text only -response = client.responses.create( - model="${N}", - input=${JSON.stringify(s,null,4)}${a} -) - -print(response.output_text) - -# Example with image or PDF (uncomment and provide file path to use) -# base64_file = encode_image("path/to/your/file.jpg") # or .pdf -# response_with_file = client.responses.create( -# model="${N}", -# input=[ -# { -# "role": "user", -# "content": [ -# {"type": "input_text", "text": "${y}"}, -# { -# "type": "input_image", -# "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} -# }, -# ], -# } -# ]${a} -# ) -# print(response_with_file.output_text) -`;break}case r.IMAGE:t="azure"===h?` -# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. -# This snippet uses 'client.images.generate' and will create a new image based on your prompt. -# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. -import os -import requests -import json -import time -from PIL import Image - -result = client.images.generate( - model="${N}", - prompt="${n}", - n=1 -) - -json_response = json.loads(result.model_dump_json()) - -# Set the directory for the stored image -image_dir = os.path.join(os.curdir, 'images') - -# If the directory doesn't exist, create it -if not os.path.isdir(image_dir): - os.mkdir(image_dir) - -# Initialize the image path -image_filename = f"generated_image_{int(time.time())}.png" -image_path = os.path.join(image_dir, image_filename) - -try: - # Retrieve the generated image - if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): - image_url = json_response["data"][0]["url"] - generated_image = requests.get(image_url).content - with open(image_path, "wb") as image_file: - image_file.write(generated_image) - - print(f"Image saved to {image_path}") - # Display the image - image = Image.open(image_path) - image.show() - else: - print("Could not find image URL in response.") - print("Full response:", json_response) -except Exception as e: - print(f"An error occurred: {e}") - print("Full response:", json_response) -`:` -import base64 -import os -import time -import json -from PIL import Image -import requests - -# Helper function to encode images to base64 -def encode_image(image_path): - with open(image_path, "rb") as image_file: - return base64.b64encode(image_file.read()).decode('utf-8') - -# Helper function to create a file (simplified for this example) -def create_file(image_path): - # In a real implementation, this would upload the file to OpenAI - # For this example, we'll just return a placeholder ID - return f"file_{os.path.basename(image_path).replace('.', '_')}" - -# The prompt entered by the user -prompt = "${y}" - -# Encode images to base64 -base64_image1 = encode_image("body-lotion.png") -base64_image2 = encode_image("soap.png") - -# Create file IDs -file_id1 = create_file("body-lotion.png") -file_id2 = create_file("incense-kit.png") - -response = client.responses.create( - model="${N}", - input=[ - { - "role": "user", - "content": [ - {"type": "input_text", "text": prompt}, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image1}", - }, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image2}", - }, - { - "type": "input_image", - "file_id": file_id1, - }, - { - "type": "input_image", - "file_id": file_id2, - } - ], - } - ], - tools=[{"type": "image_generation"}], -) - -# Process the response -image_generation_calls = [ - output - for output in response.output - if output.type == "image_generation_call" -] - -image_data = [output.result for output in image_generation_calls] - -if image_data: - image_base64 = image_data[0] - image_filename = f"edited_image_{int(time.time())}.png" - with open(image_filename, "wb") as f: - f.write(base64.b64decode(image_base64)) - print(f"Image saved to {image_filename}") -else: - # If no image is generated, there might be a text response with an explanation - text_response = [output.text for output in response.output if hasattr(output, 'text')] - if text_response: - print("No image generated. Model response:") - print("\\n".join(text_response)) - else: - print("No image data found in response.") - print("Full response for debugging:") - print(response) -`;break;case r.IMAGE_EDITS:t="azure"===h?` -import base64 -import os -import time -import json -from PIL import Image -import requests - -# Helper function to encode images to base64 -def encode_image(image_path): - with open(image_path, "rb") as image_file: - return base64.b64encode(image_file.read()).decode('utf-8') - -# The prompt entered by the user -prompt = "${y}" - -# Encode images to base64 -base64_image1 = encode_image("body-lotion.png") -base64_image2 = encode_image("soap.png") - -# Create file IDs -file_id1 = create_file("body-lotion.png") -file_id2 = create_file("incense-kit.png") - -response = client.responses.create( - model="${N}", - input=[ - { - "role": "user", - "content": [ - {"type": "input_text", "text": prompt}, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image1}", - }, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image2}", - }, - { - "type": "input_image", - "file_id": file_id1, - }, - { - "type": "input_image", - "file_id": file_id2, - } - ], - } - ], - tools=[{"type": "image_generation"}], -) - -# Process the response -image_generation_calls = [ - output - for output in response.output - if output.type == "image_generation_call" -] - -image_data = [output.result for output in image_generation_calls] - -if image_data: - image_base64 = image_data[0] - image_filename = f"edited_image_{int(time.time())}.png" - with open(image_filename, "wb") as f: - f.write(base64.b64decode(image_base64)) - print(f"Image saved to {image_filename}") -else: - # If no image is generated, there might be a text response with an explanation - text_response = [output.text for output in response.output if hasattr(output, 'text')] - if text_response: - print("No image generated. Model response:") - print("\\n".join(text_response)) - else: - print("No image data found in response.") - print("Full response for debugging:") - print(response) -`:` -import base64 -import os -import time - -# Helper function to encode images to base64 -def encode_image(image_path): - with open(image_path, "rb") as image_file: - return base64.b64encode(image_file.read()).decode('utf-8') - -# Helper function to create a file (simplified for this example) -def create_file(image_path): - # In a real implementation, this would upload the file to OpenAI - # For this example, we'll just return a placeholder ID - return f"file_{os.path.basename(image_path).replace('.', '_')}" - -# The prompt entered by the user -prompt = "${y}" - -# Encode images to base64 -base64_image1 = encode_image("body-lotion.png") -base64_image2 = encode_image("soap.png") - -# Create file IDs -file_id1 = create_file("body-lotion.png") -file_id2 = create_file("incense-kit.png") - -response = client.responses.create( - model="${N}", - input=[ - { - "role": "user", - "content": [ - {"type": "input_text", "text": prompt}, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image1}", - }, - { - "type": "input_image", - "image_url": f"data:image/jpeg;base64,{base64_image2}", - }, - { - "type": "input_image", - "file_id": file_id1, - }, - { - "type": "input_image", - "file_id": file_id2, - } - ], - } - ], - tools=[{"type": "image_generation"}], -) - -# Process the response -image_generation_calls = [ - output - for output in response.output - if output.type == "image_generation_call" -] - -image_data = [output.result for output in image_generation_calls] - -if image_data: - image_base64 = image_data[0] - image_filename = f"edited_image_{int(time.time())}.png" - with open(image_filename, "wb") as f: - f.write(base64.b64decode(image_base64)) - print(f"Image saved to {image_filename}") -else: - # If no image is generated, there might be a text response with an explanation - text_response = [output.text for output in response.output if hasattr(output, 'text')] - if text_response: - print("No image generated. 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i={keyword:t,punctuation:/[()\[\]{};,:.<>]/};e.languages.apex={comment:e.languages.clike.comment,string:e.languages.clike.string,sql:{pattern:/((?:[=,({:]|\breturn)\s*)\[[^\[\]]*\]/i,lookbehind:!0,greedy:!0,alias:"language-sql",inside:e.languages.sql},annotation:{pattern:/@\w+\b/,alias:"punctuation"},"class-name":[{pattern:r(/(\b(?:class|enum|extends|implements|instanceof|interface|new|trigger\s+\w+\s+on)\s+)/.source),lookbehind:!0,inside:i},{pattern:r(/(\(\s*)(?=\s*\)\s*[\w(])/.source),lookbehind:!0,inside:i},{pattern:r(/(?=\s*\w+\s*[;=,(){:])/.source),inside:i}],trigger:{pattern:/(\btrigger\s+)\w+\b/i,lookbehind:!0,alias:"class-name"},keyword:t,function:/\b[a-z_]\w*(?=\s*\()/i,boolean:/\b(?:false|true)\b/i,number:/(?:\B\.\d+|\b\d+(?:\.\d+|L)?)\b/i,operator:/[!=](?:==?)?|\?\.?|&&|\|\||--|\+\+|[-+*/^&|]=?|:|<{1,3}=?/,punctuation:/[()\[\]{};,.]/}}t.exports=r,r.displayName="apex",r.aliases=[]},991642,(e,t,a)=>{"use strict";function n(e){e.languages.apl={comment:/(?:⍝|#[! 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t;e.register(n),t=[/"(?:\\[\s\S]|\$\([^)]+\)|\$(?!\()|`[^`]+`|[^"\\`$])*"/.source,/'[^']*'/.source,/\$'(?:[^'\\]|\\[\s\S])*'/.source,/<<-?\s*(["']?)(\w+)\1\s[\s\S]*?[\r\n]\2/.source].join("|"),e.languages["shell-session"]={command:{pattern:RegExp(/^/.source+"(?:"+/[^\s@:$#%*!/\\]+@[^\r\n@:$#%*!/\\]+(?::[^\0-\x1F$#%*?"<>:;|]+)?/.source+"|"+/[/~.][^\0-\x1F$#%*?"<>@:;|]*/.source+")?"+/[$#%](?=\s)/.source+/(?:[^\\\r\n \t'"<$]|[ \t](?:(?!#)|#.*$)|\\(?:[^\r]|\r\n?)|\$(?!')|<(?!<)|<>)+/.source.replace(/<>/g,function(){return t}),"m"),greedy:!0,inside:{info:{pattern:/^[^#$%]+/,alias:"punctuation",inside:{user:/^[^\s@:$#%*!/\\]+@[^\r\n@:$#%*!/\\]+/,punctuation:/:/,path:/[\s\S]+/}},bash:{pattern:/(^[$#%]\s*)\S[\s\S]*/,lookbehind:!0,alias:"language-bash",inside:e.languages.bash},"shell-symbol":{pattern:/^[$#%]/,alias:"important"}}},output:/.(?:.*(?:[\r\n]|.$))*/},e.languages["sh-session"]=e.languages.shellsession=e.languages["shell-session"]}t.exports=r,r.displayName="shellSession",r.aliases=[]},864488,(e,t,a)=>{"use strict";function n(e){e.languages.smali={comment:/#.*/,string:{pattern:/"(?:[^\r\n\\"]|\\.)*"|'(?:[^\r\n\\']|\\(?:.|u[\da-fA-F]{4}))'/,greedy:!0},"class-name":{pattern:/(^|[^L])L(?:(?:\w+|`[^`\r\n]*`)\/)*(?:[\w$]+|`[^`\r\n]*`)(?=\s*;)/,lookbehind:!0,inside:{"class-name":{pattern:/(^L|\/)(?:[\w$]+|`[^`\r\n]*`)$/,lookbehind:!0},namespace:{pattern:/^(L)(?:(?:\w+|`[^`\r\n]*`)\/)+/,lookbehind:!0,inside:{punctuation:/\//}},builtin:/^L/}},builtin:[{pattern:/([();\[])[BCDFIJSVZ]+/,lookbehind:!0},{pattern:/([\w$>]:)[BCDFIJSVZ]/,lookbehind:!0}],keyword:[{pattern:/(\.end\s+)[\w-]+/,lookbehind:!0},{pattern:/(^|[^\w.-])\.(?!\d)[\w-]+/,lookbehind:!0},{pattern:/(^|[^\w.-])(?:abstract|annotation|bridge|constructor|enum|final|interface|private|protected|public|runtime|static|synthetic|system|transient)(?![\w.-])/,lookbehind:!0}],function:{pattern:/(^|[^\w.-])(?:\w+|<[\w$-]+>)(?=\()/,lookbehind:!0},field:{pattern:/[\w$]+(?=:)/,alias:"variable"},register:{pattern:/(^|[^\w.-])[vp]\d(?![\w.-])/,lookbehind:!0,alias:"variable"},boolean:{pattern:/(^|[^\w.-])(?:false|true)(?![\w.-])/,lookbehind:!0},number:{pattern:/(^|[^/\w.-])-?(?:NAN|INFINITY|0x(?:[\dA-F]+(?:\.[\dA-F]*)?|\.[\dA-F]+)(?:p[+-]?[\dA-F]+)?|(?:\d+(?:\.\d*)?|\.\d+)(?:e[+-]?\d+)?)[dflst]?(?![\w.-])/i,lookbehind:!0},label:{pattern:/(:)\w+/,lookbehind:!0,alias:"property"},operator:/->|\.\.|[\[=]/,punctuation:/[{}(),;:]/}}t.exports=n,n.displayName="smali",n.aliases=[]},223592,(e,t,a)=>{"use strict";function n(e){e.languages.smalltalk={comment:{pattern:/"(?:""|[^"])*"/,greedy:!0},char:{pattern:/\$./,greedy:!0},string:{pattern:/'(?:''|[^'])*'/,greedy:!0},symbol:/#[\da-z]+|#(?:-|([+\/\\*~<>=@%|&?!])\1?)|#(?=\()/i,"block-arguments":{pattern:/(\[\s*):[^\[|]*\|/,lookbehind:!0,inside:{variable:/:[\da-z]+/i,punctuation:/\|/}},"temporary-variables":{pattern:/\|[^|]+\|/,inside:{variable:/[\da-z]+/i,punctuation:/\|/}},keyword:/\b(?:new|nil|self|super)\b/,boolean:/\b(?:false|true)\b/,number:[/\d+r-?[\dA-Z]+(?:\.[\dA-Z]+)?(?:e-?\d+)?/,/\b\d+(?:\.\d+)?(?:e-?\d+)?/],operator:/[<=]=?|:=|~[~=]|\/\/?|\\\\|>[>=]?|[!^+\-*&|,@]/,punctuation:/[.;:?\[\](){}]/}}t.exports=n,n.displayName="smalltalk",n.aliases=[]},935950,(e,t,a)=>{"use strict";var n=e.r(426226);function r(e){var t,a;e.register(n),e.languages.smarty={comment:{pattern:/^\{\*[\s\S]*?\*\}/,greedy:!0},"embedded-php":{pattern:/^\{php\}[\s\S]*?\{\/php\}/,greedy:!0,inside:{smarty:{pattern:/^\{php\}|\{\/php\}$/,inside:null},php:{pattern:/[\s\S]+/,alias:"language-php",inside:e.languages.php}}},string:[{pattern:/"(?:\\.|[^"\\\r\n])*"/,greedy:!0,inside:{interpolation:{pattern:/\{[^{}]*\}|`[^`]*`/,inside:{"interpolation-punctuation":{pattern:/^[{`]|[`}]$/,alias:"punctuation"},expression:{pattern:/[\s\S]+/,inside:null}}},variable:/\$\w+/}},{pattern:/'(?:\\.|[^'\\\r\n])*'/,greedy:!0}],keyword:{pattern:/(^\{\/?)[a-z_]\w*\b(?!\()/i,lookbehind:!0,greedy:!0},delimiter:{pattern:/^\{\/?|\}$/,greedy:!0,alias:"punctuation"},number:/\b0x[\dA-Fa-f]+|(?:\b\d+(?:\.\d*)?|\B\.\d+)(?:[Ee][-+]?\d+)?/,variable:[/\$(?!\d)\w+/,/#(?!\d)\w+#/,{pattern:/(\.|->|\w\s*=)(?!\d)\w+\b(?!\()/,lookbehind:!0},{pattern:/(\[)(?!\d)\w+(?=\])/,lookbehind:!0}],function:{pattern:/(\|\s*)@?[a-z_]\w*|\b[a-z_]\w*(?=\()/i,lookbehind:!0},"attr-name":/\b[a-z_]\w*(?=\s*=)/i,boolean:/\b(?:false|no|off|on|true|yes)\b/,punctuation:/[\[\](){}.,:`]|->/,operator:[/[+\-*\/%]|==?=?|[!<>]=?|&&|\|\|?/,/\bis\s+(?:not\s+)?(?:div|even|odd)(?:\s+by)?\b/,/\b(?:and|eq|gt?e|gt|lt?e|lt|mod|neq?|not|or)\b/]},e.languages.smarty["embedded-php"].inside.smarty.inside=e.languages.smarty,e.languages.smarty.string[0].inside.interpolation.inside.expression.inside=e.languages.smarty,t=/"(?:\\.|[^"\\\r\n])*"|'(?:\\.|[^'\\\r\n])*'/,a=RegExp(/\{\*[\s\S]*?\*\}/.source+"|"+/\{php\}[\s\S]*?\{\/php\}/.source+"|"+/\{(?:[^{}"']||\{(?:[^{}"']||\{(?:[^{}"']|)*\})*\})*\}/.source.replace(//g,function(){return t.source}),"g"),e.hooks.add("before-tokenize",function(t){var n=!1;e.languages["markup-templating"].buildPlaceholders(t,"smarty",a,function(e){return"{/literal}"===e&&(n=!1),!n&&("{literal}"===e&&(n=!0),!0)})}),e.hooks.add("after-tokenize",function(t){e.languages["markup-templating"].tokenizePlaceholders(t,"smarty")})}t.exports=r,r.displayName="smarty",r.aliases=[]},888705,(e,t,a)=>{"use strict";function n(e){var t;t=/\b(?:abstype|and|andalso|as|case|datatype|do|else|end|eqtype|exception|fn|fun|functor|handle|if|in|include|infix|infixr|let|local|nonfix|of|op|open|orelse|raise|rec|sharing|sig|signature|struct|structure|then|type|val|where|while|with|withtype)\b/i,e.languages.sml={comment:/\(\*(?:[^*(]|\*(?!\))|\((?!\*)|\(\*(?:[^*(]|\*(?!\))|\((?!\*))*\*\))*\*\)/,string:{pattern:/#?"(?:[^"\\]|\\.)*"/,greedy:!0},"class-name":[{pattern:RegExp(/((?:^|[^:]):\s*)(?:\s*(?:(?:\*|->)\s*|,\s*(?:(?=)|(?!)\s+)))*/.source.replace(//g,function(){return/\s*(?:[*,]|->)/.source}).replace(//g,function(){return/(?:'[\w']*||\((?:[^()]|\([^()]*\))*\)|\{(?:[^{}]|\{[^{}]*\})*\})(?:\s+)*/.source}).replace(//g,function(){return/(?!)[a-z\d_][\w'.]*/.source}).replace(//g,function(){return 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n(e){e.languages.solidity=e.languages.extend("clike",{"class-name":{pattern:/(\b(?:contract|enum|interface|library|new|struct|using)\s+)(?!\d)[\w$]+/,lookbehind:!0},keyword:/\b(?:_|anonymous|as|assembly|assert|break|calldata|case|constant|constructor|continue|contract|default|delete|do|else|emit|enum|event|external|for|from|function|if|import|indexed|inherited|interface|internal|is|let|library|mapping|memory|modifier|new|payable|pragma|private|public|pure|require|returns?|revert|selfdestruct|solidity|storage|struct|suicide|switch|this|throw|using|var|view|while)\b/,operator:/=>|->|:=|=:|\*\*|\+\+|--|\|\||&&|<<=?|>>=?|[-+*/%^&|<>!=]=?|[~?]/}),e.languages.insertBefore("solidity","keyword",{builtin:/\b(?:address|bool|byte|u?int(?:8|16|24|32|40|48|56|64|72|80|88|96|104|112|120|128|136|144|152|160|168|176|184|192|200|208|216|224|232|240|248|256)?|string|bytes(?:[1-9]|[12]\d|3[0-2])?)\b/}),e.languages.insertBefore("solidity","number",{version:{pattern:/([<>]=?|\^)\d+\.\d+\.\d+\b/,lookbehind:!0,alias:"number"}}),e.languages.sol=e.languages.solidity}t.exports=n,n.displayName="solidity",n.aliases=["sol"]},285035,(e,t,a)=>{"use 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t,a;e.register(n),t=/(["'])(?:\\(?:\r\n|[\s\S])|(?!\1)[^\\\r\n])*\1/,a=/\b\d+(?:\.\d+)?(?:[eE][+-]?\d+)?\b|\b0x[\dA-F]+\b/,e.languages.soy={comment:[/\/\*[\s\S]*?\*\//,{pattern:/(\s)\/\/.*/,lookbehind:!0,greedy:!0}],"command-arg":{pattern:/(\{+\/?\s*(?:alias|call|delcall|delpackage|deltemplate|namespace|template)\s+)\.?[\w.]+/,lookbehind:!0,alias:"string",inside:{punctuation:/\./}},parameter:{pattern:/(\{+\/?\s*@?param\??\s+)\.?[\w.]+/,lookbehind:!0,alias:"variable"},keyword:[{pattern:/(\{+\/?[^\S\r\n]*)(?:\\[nrt]|alias|call|case|css|default|delcall|delpackage|deltemplate|else(?:if)?|fallbackmsg|for(?:each)?|if(?:empty)?|lb|let|literal|msg|namespace|nil|@?param\??|rb|sp|switch|template|xid)/,lookbehind:!0},/\b(?:any|as|attributes|bool|css|float|html|in|int|js|list|map|null|number|string|uri)\b/],delimiter:{pattern:/^\{+\/?|\/?\}+$/,alias:"punctuation"},property:/\w+(?==)/,variable:{pattern:/\$[^\W\d]\w*(?:\??(?:\.\w+|\[[^\]]+\]))*/,inside:{string:{pattern:t,greedy:!0},number:a,punctuation:/[\[\].?]/}},string:{pattern:t,greedy:!0},function:[/\w+(?=\()/,{pattern:/(\|[^\S\r\n]*)\w+/,lookbehind:!0}],boolean:/\b(?:false|true)\b/,number:a,operator:/\?:?|<=?|>=?|==?|!=|[+*/%-]|\b(?:and|not|or)\b/,punctuation:/[{}()\[\]|.,:]/},e.hooks.add("before-tokenize",function(t){var a=!1;e.languages["markup-templating"].buildPlaceholders(t,"soy",/\{\{.+?\}\}|\{.+?\}|\s\/\/.*|\/\*[\s\S]*?\*\//g,function(e){return"{/literal}"===e&&(a=!1),!a&&("{literal}"===e&&(a=!0),!0)})}),e.hooks.add("after-tokenize",function(t){e.languages["markup-templating"].tokenizePlaceholders(t,"soy")})}t.exports=r,r.displayName="soy",r.aliases=[]},834341,(e,t,a)=>{"use strict";function n(e){e.languages.turtle={comment:{pattern:/#.*/,greedy:!0},"multiline-string":{pattern:/"""(?:(?:""?)?(?:[^"\\]|\\.))*"""|'''(?:(?:''?)?(?:[^'\\]|\\.))*'''/,greedy:!0,alias:"string",inside:{comment:/#.*/}},string:{pattern:/"(?:[^\\"\r\n]|\\.)*"|'(?:[^\\'\r\n]|\\.)*'/,greedy:!0},url:{pattern:/<(?:[^\x00-\x20<>"{}|^`\\]|\\(?:u[\da-fA-F]{4}|U[\da-fA-F]{8}))*>/,greedy:!0,inside:{punctuation:/[<>]/}},function:{pattern:/(?:(?![-.\d\xB7])[-.\w\xB7\xC0-\uFFFD]+)?:(?:(?![-.])(?:[-.:\w\xC0-\uFFFD]|%[\da-f]{2}|\\.)+)?/i,inside:{"local-name":{pattern:/([^:]*:)[\s\S]+/,lookbehind:!0},prefix:{pattern:/[\s\S]+/,inside:{punctuation:/:/}}}},number:/[+-]?\b\d+(?:\.\d*)?(?:e[+-]?\d+)?/i,punctuation:/[{}.,;()[\]]|\^\^/,boolean:/\b(?:false|true)\b/,keyword:[/(?:\ba|@prefix|@base)\b|=/,/\b(?:base|graph|prefix)\b/i],tag:{pattern:/@[a-z]+(?:-[a-z\d]+)*/i,inside:{punctuation:/@/}}},e.languages.trig=e.languages.turtle}t.exports=n,n.displayName="turtle",n.aliases=[]},46802,(e,t,a)=>{"use strict";var n=e.r(834341);function r(e){e.register(n),e.languages.sparql=e.languages.extend("turtle",{boolean:/\b(?:false|true)\b/i,variable:{pattern:/[?$]\w+/,greedy:!0}}),e.languages.insertBefore("sparql","punctuation",{keyword:[/\b(?:A|ADD|ALL|AS|ASC|ASK|BNODE|BY|CLEAR|CONSTRUCT|COPY|CREATE|DATA|DEFAULT|DELETE|DESC|DESCRIBE|DISTINCT|DROP|EXISTS|FILTER|FROM|GROUP|HAVING|INSERT|INTO|LIMIT|LOAD|MINUS|MOVE|NAMED|NOT|NOW|OFFSET|OPTIONAL|ORDER|RAND|REDUCED|SELECT|SEPARATOR|SERVICE|SILENT|STRUUID|UNION|USING|UUID|VALUES|WHERE)\b/i,/\b(?:ABS|AVG|BIND|BOUND|CEIL|COALESCE|CONCAT|CONTAINS|COUNT|DATATYPE|DAY|ENCODE_FOR_URI|FLOOR|GROUP_CONCAT|HOURS|IF|IRI|isBLANK|isIRI|isLITERAL|isNUMERIC|isURI|LANG|LANGMATCHES|LCASE|MAX|MD5|MIN|MINUTES|MONTH|REGEX|REPLACE|ROUND|sameTerm|SAMPLE|SECONDS|SHA1|SHA256|SHA384|SHA512|STR|STRAFTER|STRBEFORE|STRDT|STRENDS|STRLANG|STRLEN|STRSTARTS|SUBSTR|SUM|TIMEZONE|TZ|UCASE|URI|YEAR)\b(?=\s*\()/i,/\b(?:BASE|GRAPH|PREFIX)\b/i]}),e.languages.rq=e.languages.sparql}t.exports=r,r.displayName="sparql",r.aliases=["rq"]},424105,(e,t,a)=>{"use 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e=Object.keys(w).length>0,t="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let i=v.length>0?v:[{role:"user",content:y}];a=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.chat.completions.create( + model="${N}", + messages=${JSON.stringify(i,null,4)}${t} +) + +print(response) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.chat.completions.create( +# model="${N}", +# messages=[ +# { +# "role": "user", +# "content": [ +# { +# "type": "text", +# "text": "${j}" +# }, +# { +# "type": "image_url", +# "image_url": { +# "url": f"data:image/jpeg;base64,{base64_file}" # or data:application/pdf;base64,{base64_file} +# } +# } +# ] +# } +# ]${t} +# ) +# print(response_with_file) +`;break}case t.EndpointType.RESPONSES:{let e=Object.keys(w).length>0,t="";if(e){let e=JSON.stringify({metadata:w},null,2).split("\n").map(e=>" ".repeat(4)+e).join("\n").trim();t=`, + extra_body=${e}`}let i=v.length>0?v:[{role:"user",content:y}];a=` +import base64 + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Example with text only +response = client.responses.create( + model="${N}", + input=${JSON.stringify(i,null,4)}${t} +) + +print(response.output_text) + +# Example with image or PDF (uncomment and provide file path to use) +# base64_file = encode_image("path/to/your/file.jpg") # or .pdf +# response_with_file = client.responses.create( +# model="${N}", +# input=[ +# { +# "role": "user", +# "content": [ +# {"type": "input_text", "text": "${j}"}, +# { +# "type": "input_image", +# "image_url": f"data:image/jpeg;base64,{base64_file}", # or data:application/pdf;base64,{base64_file} +# }, +# ], +# } +# ]${t} +# ) +# print(response_with_file.output_text) +`;break}case t.EndpointType.IMAGE:a="azure"===f?` +# NOTE: The Azure SDK does not have a direct equivalent to the multi-modal 'responses.create' method shown for OpenAI. +# This snippet uses 'client.images.generate' and will create a new image based on your prompt. +# It does not use the uploaded image, as 'client.images.generate' does not support image inputs in this context. +import os +import requests +import json +import time +from PIL import Image + +result = client.images.generate( + model="${N}", + prompt="${n}", + n=1 +) + +json_response = json.loads(result.model_dump_json()) + +# Set the directory for the stored image +image_dir = os.path.join(os.curdir, 'images') + +# If the directory doesn't exist, create it +if not os.path.isdir(image_dir): + os.mkdir(image_dir) + +# Initialize the image path +image_filename = f"generated_image_{int(time.time())}.png" +image_path = os.path.join(image_dir, image_filename) + +try: + # Retrieve the generated image + if json_response.get("data") && len(json_response["data"]) > 0 && json_response["data"][0].get("url"): + image_url = json_response["data"][0]["url"] + generated_image = requests.get(image_url).content + with open(image_path, "wb") as image_file: + image_file.write(generated_image) + + print(f"Image saved to {image_path}") + # Display the image + image = Image.open(image_path) + image.show() + else: + print("Could not find image URL in response.") + print("Full response:", json_response) +except Exception as e: + print(f"An error occurred: {e}") + print("Full response:", json_response) +`:` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${j}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${N}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`;break;case t.EndpointType.IMAGE_EDITS:a="azure"===f?` +import base64 +import os +import time +import json +from PIL import Image +import requests + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# The prompt entered by the user +prompt = "${j}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${N}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. Model response:") + print("\\n".join(text_response)) + else: + print("No image data found in response.") + print("Full response for debugging:") + print(response) +`:` +import base64 +import os +import time + +# Helper function to encode images to base64 +def encode_image(image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode('utf-8') + +# Helper function to create a file (simplified for this example) +def create_file(image_path): + # In a real implementation, this would upload the file to OpenAI + # For this example, we'll just return a placeholder ID + return f"file_{os.path.basename(image_path).replace('.', '_')}" + +# The prompt entered by the user +prompt = "${j}" + +# Encode images to base64 +base64_image1 = encode_image("body-lotion.png") +base64_image2 = encode_image("soap.png") + +# Create file IDs +file_id1 = create_file("body-lotion.png") +file_id2 = create_file("incense-kit.png") + +response = client.responses.create( + model="${N}", + input=[ + { + "role": "user", + "content": [ + {"type": "input_text", "text": prompt}, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image1}", + }, + { + "type": "input_image", + "image_url": f"data:image/jpeg;base64,{base64_image2}", + }, + { + "type": "input_image", + "file_id": file_id1, + }, + { + "type": "input_image", + "file_id": file_id2, + } + ], + } + ], + tools=[{"type": "image_generation"}], +) + +# Process the response +image_generation_calls = [ + output + for output in response.output + if output.type == "image_generation_call" +] + +image_data = [output.result for output in image_generation_calls] + +if image_data: + image_base64 = image_data[0] + image_filename = f"edited_image_{int(time.time())}.png" + with open(image_filename, "wb") as f: + f.write(base64.b64decode(image_base64)) + print(f"Image saved to {image_filename}") +else: + # If no image is generated, there might be a text response with an explanation + text_response = [output.text for output in response.output if hasattr(output, 'text')] + if text_response: + print("No image generated. 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Admin UI"}],["$","link","2",{"rel":"icon","href":"/favicon.ico?favicon.3arlap5n8tyzg.ico","sizes":"48x48","type":"image/x-icon"}],["$","link","3",{"rel":"icon","href":"/get_favicon"}],["$","$L1e","4",{}]] diff --git a/litellm/proxy/_lazy_openapi_snapshot.json b/litellm/proxy/_lazy_openapi_snapshot.json index cb7a18cd107..fb2f014e3d8 100644 --- a/litellm/proxy/_lazy_openapi_snapshot.json +++ b/litellm/proxy/_lazy_openapi_snapshot.json @@ -3234,6 +3234,17 @@ } ], "title": "User Email" + }, + "user_id": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "null" + } + ], + "title": "User Id" } }, "title": "KeyMetadata", @@ -5134,6 +5145,49 @@ "anthropic_skills" ] } + }, + "/v1/skills/{skill_id}/archive": { + "get": { + "description": "Stored skill upload, repacked so SKILL.md sits at the archive root.", + "operationId": "agent_skills_archive_v1_skills__skill_id__archive_get", + "parameters": [ + { + "in": "path", + "name": "skill_id", + "required": true, + "schema": { + "title": "Skill Id", + "type": "string" + } + } + ], + "responses": { + "200": { + "content": { + "application/zip": { + "schema": { + "type": "string" + } + } + }, + "description": "Successful Response" + }, + "422": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + }, + "description": "Validation Error" + } + }, + "summary": "Agent Skills Archive", + "tags": [ + "anthropic_skills" + ] + } } } }, @@ -11449,6 +11503,12 @@ "description": "Enable content moderation to check for harmful content (harassment, hate speech, etc.).", "title": "Content Moderation Check" }, + "contextual_grounding_from_messages": { + "default": false, + "description": "ApplyGuardrail: when True, post-call scans of a request with no grounding_source / query content parts send the system and developer messages as the grounding source and the latest user message as the query, so the guardrail's contextual grounding policy can score the response. Bedrock bills contextual grounding units for these scans and rejects queries, sources and responses over its contextual grounding length limits, so leave this off for guardrails without a contextual grounding policy. Default False: plain messages are never sent as grounding context.", + "title": "Contextual Grounding From Messages", + "type": "boolean" + }, "credentials": { "anyOf": [ { diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index ae6c042ab3a..d40f518d4b8 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -4,11 +4,12 @@ import os from collections.abc import Callable, Mapping from datetime import datetime from types import MappingProxyType -from typing import TYPE_CHECKING, Any, Final, Literal, NamedTuple +from typing import TYPE_CHECKING, Annotated, Any, Final, Literal, NamedTuple import httpx from pydantic import ( BaseModel, + BeforeValidator, ConfigDict, Field, Json, @@ -47,6 +48,7 @@ from litellm.types.proxy.carried_budget_state import ( ) from litellm.types.proxy.control_plane_endpoints import WorkerRegistryEntry from litellm.types.router import RouterErrors, UpdateRouterConfig +from litellm.types.router_weights import validate_router_settings_dict from litellm.types.secret_managers.main import KeyManagementSystem from litellm.types.utils import ( CallTypes, @@ -887,6 +889,7 @@ class LiteLLMRoutes(enum.Enum): "/auto_router/validate_complexity_router_config", # Per-session auto-router read - the endpoint scopes the row to the caller's own key hash "/auto_router/session", + "/cost/predict-cache", # Agent registry - reads are role-scoped and writes are proxy-admin-gated # inside agent_endpoints/endpoints.py *agent_management_routes, @@ -1980,8 +1983,14 @@ class OrgMember(MemberBase): from litellm.models.team import TeamBase as TeamBase # noqa: E402 +RouterSettingsDict = Annotated[ + dict[str, object], + BeforeValidator(validate_router_settings_dict, json_schema_input_type=UpdateRouterConfig), +] + class NewTeamRequest(TeamBase): + router_settings: RouterSettingsDict | None = None model_aliases: dict | None = None tags: list | None = None guardrails: list[str] | None = None @@ -2079,7 +2088,7 @@ class UpdateTeamRequest(LiteLLMPydanticObjectBase): allowed_vector_store_indexes: list[AllowedVectorStoreIndexItem] | None = None enforced_batch_output_expires_after: dict | None = None enforced_file_expires_after: dict | None = None - router_settings: dict | None = None + router_settings: RouterSettingsDict | None = None access_group_ids: list[str] | None = None budget_limits: list[BudgetLimitEntry] | None = None # multiple concurrent budget windows default_team_member_models: list[str] | None = None # default allowed_models seeded onto new team members @@ -2635,9 +2644,13 @@ class ConfigGeneralSettings(LiteLLMPydanticObjectBase): None, description="max file size in MB for /v1/files uploads, for any purpose, if a file is larger than this size it will be rejected before being forwarded to the provider", ) + allowed_file_extensions: tuple[str, ...] | None = Field( + None, + description="the only file extensions (e.g. ['.jsonl', '.pdf', '.txt']) accepted on /v1/files uploads, for any purpose, matched case-insensitively against the uploaded filename. Files with any other extension, or none, are rejected. An empty list rejects every upload. Unset means no allowlist is applied", + ) blocked_file_extensions: tuple[str, ...] | None = Field( None, - description="file extensions (e.g. ['.exe', '.sh']) rejected on /v1/files uploads, for any purpose, matched case-insensitively against the uploaded filename", + description="file extensions (e.g. ['.exe', '.sh']) rejected on /v1/files uploads, for any purpose, matched case-insensitively against the uploaded filename. Deprecated in favour of allowed_file_extensions; still enforced, after the allowlist, when set", ) max_response_size_mb: int | None = Field( None, @@ -3882,6 +3895,7 @@ class SpendLogsPayload(TypedDict): session_id: str | None request_duration_ms: int | None status: Literal["success", "failure"] + litellm_call_id: ReadOnly[str | None] class SpanAttributes(str, enum.Enum): @@ -4413,6 +4427,9 @@ class TeamInfoResponseObjectTeamTable(LiteLLM_TeamTable): access_group_mcp_server_ids: list[str] | None = None access_group_agent_ids: list[str] | None = None access_group_details: tuple[TeamAccessGroupModelGrant, ...] | None = None + # Parent org's model ceiling, reported only to callers who can manage the team. + # None = no org or not a manager; [] or ["all-proxy-models"] = no ceiling. + organization_models: list[str] | None = None class TeamInfoResponseObject(TypedDict): @@ -4580,7 +4597,6 @@ class UserManagementEndpointParamDocStringEnums(str, enum.Enum): ) metadata_doc_str = """Optional[dict] - Metadata for user, store information for user. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" }""" max_parallel_requests_doc_str = """Optional[int] - Rate limit a user based on the number of parallel requests. Raises 429 error, if user's parallel requests > x.""" - soft_budget_doc_str = """Optional[float] - Get alerts when user crosses given budget, doesn't block requests.""" model_max_budget_doc_str = """Optional[dict] - Model-specific max budget for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys)""" model_rpm_limit_doc_str = """Optional[float] - Model-specific rpm limit for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-limits-to-keys)""" model_tpm_limit_doc_str = """Optional[float] - Model-specific tpm limit for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-limits-to-keys)""" @@ -4837,6 +4853,14 @@ class JWTIssuerConfig(BaseModel): default=None, description="Issuer-specific claim path to normalize into LiteLLM's end-user id.", ) + virtual_key_claim_field: str | None = Field( + default=None, + description="Issuer-specific claim path used for the virtual key mapping lookup. Falls back to the global field.", + ) + unregistered_jwt_client_behavior: UnregisteredJWTClientBehavior | None = Field( + default=None, + description="Issuer-specific policy when the virtual key claim has no mapping. Falls back to the global policy.", + ) model_config = { "extra": "forbid", @@ -5063,6 +5087,28 @@ class LiteLLM_JWTAuth(LiteLLMPydanticObjectBase): super().__init__(**kwargs) + def get_issuer_config(self, issuer: str | None) -> JWTIssuerConfig | None: + if issuer is None or self.issuers is None: + return None + return next((config for config in self.issuers if config.issuer == issuer), None) + + def is_virtual_key_mapping_configured(self) -> bool: + if self.virtual_key_claim_field is not None: + return True + return any(config.virtual_key_claim_field is not None for config in self.issuers or ()) + + def get_virtual_key_claim_field(self, issuer: str | None) -> str | None: + issuer_config: Final = self.get_issuer_config(issuer) + if issuer_config is not None and issuer_config.virtual_key_claim_field is not None: + return issuer_config.virtual_key_claim_field + return self.virtual_key_claim_field + + def get_unregistered_jwt_client_behavior(self, issuer: str | None) -> UnregisteredJWTClientBehavior: + issuer_config: Final = self.get_issuer_config(issuer) + if issuer_config is not None and issuer_config.unregistered_jwt_client_behavior is not None: + return issuer_config.unregistered_jwt_client_behavior + return self.unregistered_jwt_client_behavior + class PrismaCompatibleUpdateDBModel(TypedDict, total=False): model_name: str diff --git a/litellm/proxy/analytics_endpoints/cache_activity.py b/litellm/proxy/analytics_endpoints/cache_activity.py index b87b8eac3ef..902e3fb3db3 100644 --- a/litellm/proxy/analytics_endpoints/cache_activity.py +++ b/litellm/proxy/analytics_endpoints/cache_activity.py @@ -6,10 +6,13 @@ from typing import TYPE_CHECKING, Final from pydantic import BaseModel, TypeAdapter +from litellm.proxy._types import LiteLLMRoutes + 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 CacheActivityGroup(BaseModel): @@ -69,6 +72,7 @@ GROUPS_SQL: Final = """ OR COALESCE(vt."key_alias", 'Unnamed Key') IN (SELECT jsonb_array_elements_text($3::jsonb))) AND ($4::jsonb = '[]'::jsonb OR sl."model" IN (SELECT jsonb_array_elements_text($4::jsonb))) + AND sl."call_type" NOT IN (SELECT jsonb_array_elements_text($5::jsonb)) GROUP BY 1 ORDER BY (COUNT(*)) DESC """ @@ -89,6 +93,7 @@ ERROR_BREAKDOWN_SQL: Final = """ OR COALESCE(vt."key_alias", 'Unnamed Key') IN (SELECT jsonb_array_elements_text($3::jsonb))) AND ($4::jsonb = '[]'::jsonb OR sl."model" IN (SELECT jsonb_array_elements_text($4::jsonb))) + AND sl."call_type" NOT IN (SELECT jsonb_array_elements_text($5::jsonb)) GROUP BY 1, 2, 3 ORDER BY (COUNT(*)) DESC """ @@ -100,6 +105,7 @@ KEY_ALIAS_OPTIONS_SQL: Final = """ WHERE sl."startTime" >= ($1::timestamptz AT TIME ZONE 'UTC') AND sl."startTime" < (($2::timestamptz + INTERVAL '1 day') AT TIME ZONE 'UTC') + AND sl."call_type" NOT IN (SELECT jsonb_array_elements_text($3::jsonb)) ORDER BY 1 """ @@ -110,6 +116,7 @@ MODEL_OPTIONS_SQL: Final = """ sl."startTime" >= ($1::timestamptz AT TIME ZONE 'UTC') AND sl."startTime" < (($2::timestamptz + INTERVAL '1 day') AT TIME ZONE 'UTC') AND sl."model" != '' + AND sl."call_type" NOT IN (SELECT jsonb_array_elements_text($3::jsonb)) ORDER BY 1 """ @@ -152,10 +159,12 @@ async def get_cache_activity( key_aliases_json: Final = json.dumps(list(key_aliases)) models_json: Final = json.dumps(list(models)) 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), - prisma_client.db.query_raw(ERROR_BREAKDOWN_SQL, start_date, end_date, key_aliases_json, models_json), - prisma_client.db.query_raw(KEY_ALIAS_OPTIONS_SQL, start_date, end_date), - prisma_client.db.query_raw(MODEL_OPTIONS_SQL, start_date, end_date), + prisma_client.db.query_raw(GROUPS_SQL, start_date, end_date, key_aliases_json, models_json, INFO_ROUTES_JSON), + prisma_client.db.query_raw( + ERROR_BREAKDOWN_SQL, start_date, end_date, key_aliases_json, models_json, INFO_ROUTES_JSON + ), + prisma_client.db.query_raw(KEY_ALIAS_OPTIONS_SQL, start_date, end_date, INFO_ROUTES_JSON), + prisma_client.db.query_raw(MODEL_OPTIONS_SQL, start_date, end_date, INFO_ROUTES_JSON), ) groups: Final = _groups_adapter.validate_python(group_rows or []) return CacheActivityResponse( diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 9c175242a9a..6d61ad4d3e8 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -72,6 +72,7 @@ from litellm.proxy.auth.budget_throttle import ( ) from litellm.proxy.auth.route_checks import RouteChecks from litellm.proxy.common_utils.auth_cache_invalidation_pubsub import publish_auth_cache_invalidation +from litellm.proxy.common_utils.cache_pydantic_utils import CacheCodec from litellm.proxy.common_utils.http_parsing_utils import ( _safe_get_request_headers, _safe_get_request_query_params, @@ -80,6 +81,7 @@ from litellm.proxy.common_utils.timezone_utils import get_budget_reset_time from litellm.proxy.common_utils.user_api_key_cache import ( END_USER_RESTRICTED_REGISTRY_OVERFLOW_SENTINEL, MODEL_ACCESS_GROUP_REGISTRY_OVERFLOW_SENTINEL, + NO_TEAM_MEMBERSHIP_SENTINEL, TAG_REGISTRY_OVERFLOW_SENTINEL, UserApiKeyCache, end_user_cache_key, @@ -121,6 +123,7 @@ from litellm.repositories.table_repositories import ( from litellm.repositories.team_repository import TeamRepository from litellm.repositories.user_repository import UserRepository from litellm.router import Router +from litellm.types.proxy.auth.auth_checks import UserNotFoundError from litellm.types.proxy.model_access_group_budget import ModelAccessGroupBudget from litellm.utils import get_utc_datetime @@ -325,9 +328,23 @@ _safe_json_loads_obj: Final = _typed_json_loads(safe_json_loads) last_db_access_time: Final = LimitedSizeOrderedDict(max_size=100) db_cache_expiry: Final = DEFAULT_IN_MEMORY_TTL # refresh every 5s +_TEAM_MEMBERSHIP_INFLIGHT_MAX: Final = 10000 +_team_membership_inflight: Final = LimitedSizeOrderedDict(max_size=_TEAM_MEMBERSHIP_INFLIGHT_MAX) + + +class _TeamMembershipCacheMiss: + __slots__ = () + + +_TEAM_MEMBERSHIP_CACHE_MISS: Final = _TeamMembershipCacheMiss() + all_routes: Final = LiteLLMRoutes.openai_routes.value + LiteLLMRoutes.management_routes.value +def _membership_from_shared_load(result: object) -> LiteLLM_TeamMembership | None: + return result if isinstance(result, LiteLLM_TeamMembership) else None + + def _log_budget_lookup_failure(entity: str, error: Exception) -> None: """ Log a warning when budget lookup fails; cache will not be populated. @@ -878,6 +895,7 @@ async def common_checks( request_query_params=_safe_get_request_query_params(request=request), llm_router=llm_router, request=request, + team_id=valid_token.team_id if valid_token is not None else None, ) skip_all_budget_checks: Final = skip_budget_checks or ( @@ -885,6 +903,22 @@ async def common_checks( and (route in MODEL_DISCOVERY_ROUTES or not RouteChecks.is_llm_api_route(route=route)) ) + membership_user_id: Final = ( + valid_token.user_id if valid_token is not None and (bool(_model) or not skip_all_budget_checks) else None + ) + team_membership_loaded: Final = team_object is not None and membership_user_id is not None + loaded_team_membership: Final = ( + await get_team_membership( + user_id=membership_user_id, + team_id=team_object.team_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + ) + if team_object is not None and membership_user_id is not None + else None + ) + unpriced_models: Final = ( _unpriced_models_in_request(model=_model, llm_router=llm_router) if litellm.block_requests_for_models_without_pricing and RouteChecks.is_llm_api_route(route=route) @@ -934,6 +968,8 @@ async def common_checks( prisma_client=prisma_client, user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, + team_membership=loaded_team_membership, + team_membership_loaded=team_membership_loaded, ) # Require trace id for agent keys when agent has require_trace_id_on_calls_by_agent @@ -985,6 +1021,8 @@ async def common_checks( prisma_client=prisma_client, user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, + team_membership=loaded_team_membership, + team_membership_loaded=team_membership_loaded, ) # Run before apply_key_tags_pre_auth injects key metadata.tags into request_body. @@ -1094,6 +1132,8 @@ async def common_checks( prisma_client=prisma_client, user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, + team_membership=loaded_team_membership, + team_membership_loaded=team_membership_loaded, ), _check_end_user_budget(end_user_obj=end_user_object, route=route) if end_user_object is not None and end_user_object.litellm_budget_table is not None @@ -2139,7 +2179,76 @@ async def get_tag_object( return tag_objects.get(tag_name) +def _membership_from_cached_payload( + cached: object, +) -> LiteLLM_TeamMembership | None | _TeamMembershipCacheMiss: + if cached is None: + return _TEAM_MEMBERSHIP_CACHE_MISS + if cached == NO_TEAM_MEMBERSHIP_SENTINEL: + return None + cached_membership: Final = CacheCodec.deserialize(cached, model_type=LiteLLM_TeamMembership) + return cached_membership if cached_membership is not None else _TEAM_MEMBERSHIP_CACHE_MISS + + @log_db_metrics +async def _fetch_team_membership_from_db( + user_id: str, + team_id: str, + prisma_client: PrismaClient, + user_api_key_cache: UserApiKeyCache, + parent_otel_span: Span | None = None, + proxy_logging_obj: ProxyLogging | None = None, +) -> LiteLLM_TeamMembership | None: + _ = parent_otel_span, proxy_logging_obj + response: Final = await _dictable_table(TeamMembershipRepository(prisma_client)).find_unique( + where={"user_id_team_id": {"user_id": user_id, "team_id": team_id}}, + include={"litellm_budget_table": True}, + ) + membership: Final = None if response is None else LiteLLM_TeamMembership.model_validate(response.dict()) + _key: Final = team_membership_reservation_cache_key(user_id=user_id, team_id=team_id) + if membership is None: + await user_api_key_cache.async_set_cache( + key=_key, + value=NO_TEAM_MEMBERSHIP_SENTINEL, + ttl=get_management_object_ttl(user_api_key_cache), + ) + else: + await user_api_key_cache.async_set_cache( + key=_key, + value=membership, + model_type=LiteLLM_TeamMembership, + ) + return membership + + +async def _load_team_membership_on_cache_miss( + user_id: str, + team_id: str, + cache_key: str, + prisma_client: PrismaClient, + user_api_key_cache: UserApiKeyCache, + parent_otel_span: Span | None, + proxy_logging_obj: ProxyLogging | None, +) -> LiteLLM_TeamMembership | None: + try: + redis_cached: Final[object] = await user_api_key_cache.async_get_cache(key=cache_key) + redis_membership: Final = _membership_from_cached_payload(redis_cached) + if not isinstance(redis_membership, _TeamMembershipCacheMiss): + return redis_membership + + return await _fetch_team_membership_from_db( + user_id=user_id, + team_id=team_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) + except Exception: + verbose_proxy_logger.exception("Error getting team membership") + return None + + async def get_team_membership( user_id: str, team_id: str, @@ -2153,49 +2262,42 @@ async def get_team_membership( Do a isolated check for team membership vs. doing a combined key + team + user + team-membership check, as key might come in frequently for different users/teams. Larger call will slowdown query time. This way we get to cache the constant (key/team/user info) and only update based on the changing value (team membership). """ - from litellm.proxy._types import LiteLLM_TeamMembership - - if prisma_client is None: - raise Exception("No db connected") - if user_id is None or team_id is None: return None _key: Final = team_membership_reservation_cache_key(user_id=user_id, team_id=team_id) - # check if in cache - cached_membership_obj: Final = await user_api_key_cache.async_get_cache( - key=_key, - model_type=LiteLLM_TeamMembership, + l1_cached: Final[object] = await user_api_key_cache.async_get_cache(key=_key, local_only=True) + l1_membership: Final = _membership_from_cached_payload(l1_cached) + if not isinstance(l1_membership, _TeamMembershipCacheMiss): + return l1_membership + + inflight: Final[object] = _team_membership_inflight.get(_key) + if isinstance(inflight, asyncio.Task): + return _membership_from_shared_load(await asyncio.shield(inflight)) + + if prisma_client is None: + raise Exception("No db connected") + + task: Final = asyncio.ensure_future( + _load_team_membership_on_cache_miss( + user_id=user_id, + team_id=team_id, + cache_key=_key, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) ) - if cached_membership_obj is not None: - return cached_membership_obj + _team_membership_inflight[_key] = task - # else, check db - try: - response: Final = await _dictable_table(TeamMembershipRepository(prisma_client)).find_unique( - where={"user_id_team_id": {"user_id": user_id, "team_id": team_id}}, - include={"litellm_budget_table": True}, - ) + def _clear_inflight(_done: object) -> None: + if _team_membership_inflight.get(_key) is task: + _team_membership_inflight.pop(_key, None) - if response is None: - return None - - _response: Final = LiteLLM_TeamMembership.model_validate(response.dict()) - await user_api_key_cache.async_set_cache( - key=_key, - value=_response, - model_type=LiteLLM_TeamMembership, - ) - - return _response - except Exception: - verbose_proxy_logger.exception( - "Error getting team membership for user_id: %s, team_id: %s", - user_id, - team_id, - ) - return None + task.add_done_callback(_clear_inflight) + return _membership_from_shared_load(await asyncio.shield(task)) def model_in_access_group(model: str, team_models: list[str] | None, llm_router: Router | None) -> bool: @@ -2368,13 +2470,6 @@ async def _backfill_null_user_email( return updated_row -class UserNotFoundError(ValueError): - """The user row is provably absent, as opposed to merely unreadable, so a caller that reads a missing row as no user-level limits can key on it without also swallowing a database that would not answer.""" - - def __init__(self, user_id: str) -> None: - super().__init__(f"User doesn't exist in db. 'user_id'={user_id}. Create user via `/user/new` call.") - - @log_db_metrics async def get_user_object( user_id: str | None, @@ -2661,6 +2756,12 @@ async def invalidate_team_member_spend_state( publish_auth_cache_invalidation, ) + inflight: Final[object] = _team_membership_inflight.pop( + team_membership_reservation_cache_key(user_id=user_id, team_id=team_id), None + ) + if isinstance(inflight, asyncio.Task) and inflight is not asyncio.current_task(): + await asyncio.wait((inflight,)) + if new_spend is not None: from litellm.proxy.proxy_server import SPEND_DB_FLOOR_CACHE_TTL_SECONDS, spend_counter_cache @@ -4115,18 +4216,21 @@ async def _team_member_granted_models( prisma_client: PrismaClient, user_api_key_cache: UserApiKeyCache, proxy_logging_obj: ProxyLogging, + team_membership: LiteLLM_TeamMembership | None = None, + team_membership_loaded: bool = False, ) -> Sequence[str]: """The member's own ``allowed_models`` scope; empty when the member is not narrowed below the team.""" if team_object is None or valid_token.user_id is None: return () - team_membership: Final = await get_team_membership( - user_id=valid_token.user_id, - team_id=team_object.team_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, - ) + if not team_membership_loaded: + team_membership = await get_team_membership( + user_id=valid_token.user_id, + team_id=team_object.team_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + ) return () if team_membership is None else _member_allowed_models(team_membership) @@ -4162,6 +4266,8 @@ async def _granted_model_lists( prisma_client: PrismaClient, user_api_key_cache: UserApiKeyCache, proxy_logging_obj: ProxyLogging, + team_membership: LiteLLM_TeamMembership | None = None, + team_membership_loaded: bool = False, ) -> tuple[Sequence[str], ...]: """One model allowlist per level that participates in authorizing the request.""" return ( @@ -4173,6 +4279,8 @@ async def _granted_model_lists( prisma_client=prisma_client, user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, + team_membership=team_membership, + team_membership_loaded=team_membership_loaded, ), project_object.models if project_object is not None else (), await _org_granted_models( @@ -4267,6 +4375,8 @@ async def collect_matched_model_access_groups( prisma_client: PrismaClient | None, user_api_key_cache: UserApiKeyCache, proxy_logging_obj: ProxyLogging, + team_membership: LiteLLM_TeamMembership | None = None, + team_membership_loaded: bool = False, ) -> tuple[str, ...]: """ The budgeted model access groups that authorized this request, sorted and deduplicated. @@ -4312,6 +4422,8 @@ async def collect_matched_model_access_groups( prisma_client=prisma_client, user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, + team_membership=team_membership, + team_membership_loaded=team_membership_loaded, ) for granted_model in granted_models ) @@ -4327,6 +4439,8 @@ async def stamp_matched_model_access_groups( prisma_client: PrismaClient | None, user_api_key_cache: UserApiKeyCache, proxy_logging_obj: ProxyLogging, + team_membership: LiteLLM_TeamMembership | None = None, + team_membership_loaded: bool = False, ) -> tuple[str, ...]: """Record the groups that authorized this request on its auth object, for the post-call spend writer and the reservation counters, and hand them back for the budget check.""" @@ -4343,6 +4457,8 @@ async def stamp_matched_model_access_groups( prisma_client=prisma_client, user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, + team_membership=team_membership, + team_membership_loaded=team_membership_loaded, ) except Exception as e: # noqa: BLE001 # fail-safe: attribution is spend telemetry, it must never break auth verbose_proxy_logger.debug("model access group attribution failed: %s", e) @@ -4356,7 +4472,7 @@ async def stamp_matched_model_access_groups( async def can_key_call_model( model: str | list[str], - llm_model_list: list | None, + llm_model_list: Sequence[object] | None, valid_token: UserAPIKeyAuth, llm_router: litellm.Router | None, ) -> Literal[True]: @@ -4403,7 +4519,7 @@ async def can_key_call_model( async def can_key_call_resolved_model( model: str, - llm_model_list: list | None, + llm_model_list: Sequence[object] | None, valid_token: UserAPIKeyAuth, llm_router: litellm.Router | None, ) -> None: @@ -5145,6 +5261,8 @@ async def _check_team_member_budget( prisma_client: PrismaClient | None, user_api_key_cache: UserApiKeyCache, proxy_logging_obj: ProxyLogging, + team_membership: LiteLLM_TeamMembership | None = None, + team_membership_loaded: bool = False, ): """Check if team member is over their max budget within the team.""" if ( @@ -5153,23 +5271,25 @@ async def _check_team_member_budget( and valid_token is not None and valid_token.user_id is not None ): - team_membership: Final = await get_team_membership( - user_id=valid_token.user_id, - team_id=team_object.team_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, - ) + if not team_membership_loaded: + team_membership = await get_team_membership( + user_id=valid_token.user_id, + team_id=team_object.team_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + ) + loaded_membership = team_membership # Per-member override wins; otherwise fall back to the team-level # default configured via team.metadata["team_member_budget_id"]. team_member_budget: float | None = None if ( - team_membership is not None - and team_membership.litellm_budget_table is not None - and team_membership.litellm_budget_table.max_budget is not None + loaded_membership is not None + and loaded_membership.litellm_budget_table is not None + and loaded_membership.litellm_budget_table.max_budget is not None ): - team_member_budget = team_membership.litellm_budget_table.max_budget + team_member_budget = loaded_membership.litellm_budget_table.max_budget else: default_budget_id: Final = (team_object.metadata or {}).get("team_member_budget_id") if isinstance(default_budget_id, str): @@ -5188,7 +5308,7 @@ async def _check_team_member_budget( team_member_budget = default_budget.max_budget if team_member_budget is not None: - team_member_spend = (team_membership.spend if team_membership is not None else 0.0) or 0.0 + team_member_spend = (loaded_membership.spend if loaded_membership is not None else 0.0) or 0.0 # Read from cross-pod counter (Redis-first) if available from litellm.proxy.proxy_server import get_current_spend @@ -5217,6 +5337,8 @@ async def _check_team_member_model_access( prisma_client: Optional["PrismaClient"], user_api_key_cache: UserApiKeyCache, proxy_logging_obj: ProxyLogging, + team_membership: LiteLLM_TeamMembership | None = None, + team_membership_loaded: bool = False, ) -> None: """ Check if a team member's per-member model scope allows access to the requested model. @@ -5227,22 +5349,24 @@ async def _check_team_member_model_access( if valid_token.user_id is None or team_object.team_id is None: return - team_membership: Final = await get_team_membership( - user_id=valid_token.user_id, - team_id=team_object.team_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - proxy_logging_obj=proxy_logging_obj, - ) + if not team_membership_loaded: + team_membership = await get_team_membership( + user_id=valid_token.user_id, + team_id=team_object.team_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + ) + loaded_membership = team_membership if ( - team_membership is None - or team_membership.litellm_budget_table is None - or not team_membership.litellm_budget_table.allowed_models + loaded_membership is None + or loaded_membership.litellm_budget_table is None + or not loaded_membership.litellm_budget_table.allowed_models ): return # no per-member restriction — inherit team-level check - member_allowed_models: Final[list[str]] = team_membership.litellm_budget_table.allowed_models + member_allowed_models: Final[list[str]] = loaded_membership.litellm_budget_table.allowed_models try: _can_object_call_model( model=model, diff --git a/litellm/proxy/auth/auth_utils.py b/litellm/proxy/auth/auth_utils.py index be65c3b39ec..dc304a156cf 100644 --- a/litellm/proxy/auth/auth_utils.py +++ b/litellm/proxy/auth/auth_utils.py @@ -33,7 +33,7 @@ from litellm.proxy.common_utils.http_parsing_utils import extract_nested_form_me from litellm.types.passthrough_endpoints.pass_through_endpoints import ( LITELLM_PASS_THROUGH_ENDPOINT_MARKER, ) -from litellm.types.router import CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS +from litellm.types.router import CONFIGURABLE_CLIENTSIDE_AUTH_PARAMS, Deployment from litellm.types.utils import CustomPricingLiteLLMParams @@ -1736,7 +1736,7 @@ def _append_model_candidates(candidates: list[str], value: Any) -> None: candidates.extend(model for model in model_names if model) -def _dedupe_model_candidates(candidates: list[str]) -> list[str]: +def _dedupe_model_candidates(candidates: Collection[str]) -> list[str]: deduped: Final[list[str]] = [] for model in candidates: if model not in deduped: @@ -1845,13 +1845,42 @@ def _resolve_model_id_with_router(model_id: str | None, llm_router: Router | Non return model_id +def get_cache_prediction_deployments( + *, current_deployment_id: str, candidate_deployment_id: str, llm_router: Router, team_id: str | None +) -> tuple[Deployment, Deployment] | None: + current: Final = llm_router.get_deployment(current_deployment_id) + candidate: Final = llm_router.get_deployment(candidate_deployment_id) + if current is None or candidate is None: + return None + if any(deployment.model_info.team_id not in (None, team_id) for deployment in (current, candidate)): + return None + return current, candidate + + +def _cache_prediction_model_candidates( + request_data: Mapping[str, object], llm_router: Router | None, team_id: str | None +) -> tuple[str, ...]: + current_id: Final = request_data.get("current_deployment_id") + candidate_id: Final = request_data.get("candidate_deployment_id") + if llm_router is None or not isinstance(current_id, str) or not isinstance(candidate_id, str): + return () + deployments: Final = get_cache_prediction_deployments( + current_deployment_id=current_id, candidate_deployment_id=candidate_id, llm_router=llm_router, team_id=team_id + ) + return tuple(deployment.model_name for deployment in deployments) if deployments is not None else () + + def _extract_model_candidates_from_request( request_data: dict, route: str, request_headers: Mapping[str, object] | None = None, request_query_params: Mapping[str, object] | None = None, llm_router: Router | None = None, + team_id: str | None = None, ) -> list[str]: + if route == "/cost/predict-cache": + prediction_models: Final = _cache_prediction_model_candidates(request_data, llm_router, team_id) # pyright: ignore[reportUnknownArgumentType] # the typed reader validates each deployment ID from this legacy payload + return _dedupe_model_candidates(prediction_models) candidates: Final[list[str]] = [] uses_model_routing_sources: Final = _route_uses_model_routing_sources(route=route) uses_header_or_query_model_sources: Final = _route_matches_any_marker( @@ -1945,6 +1974,7 @@ def get_model_from_request( request_query_params: Mapping[str, object] | None = None, llm_router: Router | None = None, request: Request | None = None, + team_id: str | None = None, ) -> str | list[str] | None: """Resolve the model(s) a request targets, for model-access and budget checks. @@ -1967,6 +1997,7 @@ def get_model_from_request( request_headers=request_headers, request_query_params=request_query_params, llm_router=llm_router, + team_id=team_id, ) model = _format_model_candidates(candidates) diff --git a/litellm/proxy/auth/handle_jwt.py b/litellm/proxy/auth/handle_jwt.py index 69091ee8344..4304542fc83 100644 --- a/litellm/proxy/auth/handle_jwt.py +++ b/litellm/proxy/auth/handle_jwt.py @@ -52,6 +52,7 @@ from litellm.proxy._types import ( UserAPIKeyAuth, ) from litellm.proxy.auth.auth_checks import can_team_access_model +from litellm.proxy.auth.resolvers.grants import GrantResolver, UserLookup, canonical_user_id from litellm.proxy.auth.route_checks import RouteChecks from litellm.proxy.auth.team_grants import team_model_aliases from litellm.proxy.common_utils.user_api_key_cache import ( @@ -1656,9 +1657,7 @@ class JWTAuthManager: ``get_user_object`` resolved a legacy row with a different ``user_id``, use that row's id; otherwise keep the claim. GH #26789. """ - if user_object is not None and user_object.user_id: - return user_object.user_id - return user_id + return canonical_user_id(user_id=user_id, user_object=user_object) @staticmethod async def get_objects( @@ -1725,22 +1724,23 @@ class JWTAuthManager: code=403, ) - user_object: LiteLLM_UserTable | None = None - if user_id: - user_object = ( - await get_user_object( - user_id=user_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - user_id_upsert=jwt_handler.is_upsert_user_id(valid_user_email=valid_user_email), - parent_otel_span=parent_otel_span, - proxy_logging_obj=proxy_logging_obj, - user_email=user_email, - sso_user_id=user_id, - ) - if user_id - else None - ) + user_object, team_membership_object, effective_user_id = await GrantResolver( + prisma_client, + user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + load_user=get_user_object, + load_team=get_team_object, + load_membership=get_team_membership, + ).resolve_identity( + UserLookup( + user_id=user_id, + user_email=user_email, + sso_user_id=user_id, + upsert=jwt_handler.is_upsert_user_id(valid_user_email=valid_user_email), + ), + team_id=team_id, + ) end_user_object: LiteLLM_EndUserTable | None = None if end_user_id: @@ -1757,37 +1757,12 @@ class JWTAuthManager: else None ) - # Rebind to resolved DB user_id for team_membership + auth_builder (GH #26789). - effective_user_id: Final = JWTAuthManager._canonical_user_id_from_db(user_id=user_id, user_object=user_object) - if effective_user_id != user_id: - verbose_proxy_logger.debug( - "JWT Auth: rebinding user_id %r -> DB user_id %r (email/sso match)", - user_id, - effective_user_id, - ) - user_id = effective_user_id - - team_membership_object: LiteLLM_TeamMembership | None = None - if user_id and team_id: - team_membership_object = ( - await get_team_membership( - user_id=user_id, - team_id=team_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - parent_otel_span=parent_otel_span, - proxy_logging_obj=proxy_logging_obj, - ) - if user_id and team_id - else None - ) - return ( user_object, org_object, end_user_object, team_membership_object, - user_id, + effective_user_id, ) @staticmethod diff --git a/litellm/proxy/auth/login_utils.py b/litellm/proxy/auth/login_utils.py index c0a76a4fc20..b7064802878 100644 --- a/litellm/proxy/auth/login_utils.py +++ b/litellm/proxy/auth/login_utils.py @@ -249,6 +249,7 @@ async def authenticate_user( if os.getenv("DATABASE_URL") is not None: response = await generate_key_helper_fn( + llm_router=None, request_type="key", **{ "user_role": LitellmUserRoles.PROXY_ADMIN, @@ -324,6 +325,7 @@ async def authenticate_user( await _rehash_password_if_needed(_user_row.user_id, password, _password) if os.getenv("DATABASE_URL") is not None: response = await generate_key_helper_fn( + llm_router=None, request_type="key", **{ "user_role": user_role, diff --git a/litellm/proxy/auth/resolvers/grants.py b/litellm/proxy/auth/resolvers/grants.py new file mode 100644 index 00000000000..cbfe21924ec --- /dev/null +++ b/litellm/proxy/auth/resolvers/grants.py @@ -0,0 +1,267 @@ +"""Load a caller's user row, team row, and team membership from the database and validate them together. + +The virtual-key path reads these off the combined-view SQL join. Every other credential (an IdP JWT, a +``lite login`` session token) carries only identifiers, or a snapshot of grants taken when it was minted, so +it has to read the live rows on each request. Both of those paths resolve the same rows with the same +membership rule, and ``GrantResolver`` is the one place that rule lives. +""" + +from __future__ import annotations + +from collections.abc import Coroutine, Mapping +from dataclasses import dataclass +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, NoReturn, Protocol, TypeAlias + +from fastapi import HTTPException, status +from pydantic import BaseModel, ValidationError +from pydantic.main import IncEx +from typing_extensions import assert_never + +from litellm._logging import verbose_proxy_logger +from litellm.proxy._types import ( + LiteLLM_TeamMembership, + LiteLLM_TeamTableCachedObj, + LiteLLM_UserTable, + ProxyErrorTypes, + ProxyException, +) +from litellm.proxy.auth.auth_checks import ( + TeamNotFoundError, + get_team_membership, + get_team_object, + get_user_object, +) +from litellm.types.proxy.auth.auth_checks import UserNotFoundError + +if TYPE_CHECKING: + from litellm.proxy._types import Span + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache + from litellm.proxy.utils import PrismaClient, ProxyLogging + + +class UserLoader(Protocol): + def __call__( + self, + *, + user_id: str | None, + prisma_client: PrismaClient | None, + user_api_key_cache: UserApiKeyCache, + user_id_upsert: bool, + parent_otel_span: Span | None, + proxy_logging_obj: ProxyLogging | None, + sso_user_id: str | None, + user_email: str | None, + ) -> Coroutine[object, object, LiteLLM_UserTable | None]: ... + + +class TeamLoader(Protocol): + def __call__( + self, + *, + team_id: str, + prisma_client: PrismaClient | None, + user_api_key_cache: UserApiKeyCache, + parent_otel_span: Span | None, + proxy_logging_obj: ProxyLogging | None, + ) -> Coroutine[object, object, LiteLLM_TeamTableCachedObj]: ... + + +class MembershipLoader(Protocol): + def __call__( + self, + *, + user_id: str, + team_id: str, + prisma_client: PrismaClient | None, + user_api_key_cache: UserApiKeyCache, + parent_otel_span: Span | None, + proxy_logging_obj: ProxyLogging | None, + ) -> Coroutine[object, object, LiteLLM_TeamMembership | None]: ... + + +@dataclass(frozen=True, slots=True) +class UserLookup: + """The user a credential names, plus the hints ``get_user_object`` may fall back to when the id alone + matches no row.""" + + user_id: str | None + user_email: str | None = None + sso_user_id: str | None = None + upsert: bool = False + + +@dataclass(frozen=True, slots=True) +class ResolvedGrants: + """The live rows behind a credential. ``effective_user_id`` is the DB row's id when a fuzzy match found a + legacy row under a different id (GH #26789), otherwise the id the credential named.""" + + user_object: LiteLLM_UserTable | None + team_object: LiteLLM_TeamTableCachedObj | None + team_membership: LiteLLM_TeamMembership | None + effective_user_id: str | None + + +@dataclass(frozen=True, slots=True) +class UserGone: + user_id: str + + +@dataclass(frozen=True, slots=True) +class TeamGone: + team_id: str + + +@dataclass(frozen=True, slots=True) +class NotAMember: + user_id: str + team_id: str + + +@dataclass(frozen=True, slots=True) +class LookupDegraded: + """A row could not be read for a reason that says nothing about the caller: the database is down or a + loader failed. The caller decides whether a grant it already holds may stand in.""" + + error: Exception + + +GrantDenial: TypeAlias = UserGone | TeamGone | NotAMember +GrantOutcome: TypeAlias = ResolvedGrants | GrantDenial | LookupDegraded + + +_MODELS_COLUMN: Final[Mapping[str, IncEx | bool]] = MappingProxyType({"models": True}) + + +class _UserModelColumn(BaseModel): + """``LiteLLM_UserTable.models`` is a bare ``list``; re-read it with the shape a token's ``models`` takes.""" + + models: tuple[str, ...] = () + + +def user_models(user_object: LiteLLM_UserTable) -> tuple[str, ...]: + try: + return _UserModelColumn.model_validate(user_object.model_dump(include=_MODELS_COLUMN)).models + except ValidationError: + return () + + +def canonical_user_id(user_id: str | None, user_object: LiteLLM_UserTable | None) -> str | None: + if user_object is not None and user_object.user_id: + return user_object.user_id + return user_id + + +def raise_public(denial: GrantDenial) -> NoReturn: + match denial: + case UserGone(user_id=user_id): + raise ProxyException( + message=f"Authentication Error, user '{user_id}' no longer exists.", + type=ProxyErrorTypes.auth_error, + param="user_id", + code=status.HTTP_401_UNAUTHORIZED, + ) + case TeamGone(team_id=team_id): + raise TeamNotFoundError(team_id=team_id) + case NotAMember(team_id=team_id): + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail=f"Team '{team_id}' is not in your team memberships.", + ) + case _: + assert_never(denial) + + +class GrantResolver: + """Reads the user, membership, and team rows for a credential through injected loaders. + + The loaders default to the shared ``auth_checks`` readers. A caller passes its own module's names for them + so the reads stay interceptable where that module's callers already intercept them. ``resolve_identity`` + is the JWT half: user and membership only, since the JWT builder selects the team itself and lets loader + errors surface as they are. ``resolve`` also reads the team row and applies the membership rule, which is + what a credential carrying a grant snapshot needs to refresh it. + """ + + def __init__( + self, + prisma_client: PrismaClient | None, + cache: UserApiKeyCache, + *, + parent_otel_span: Span | None = None, + proxy_logging_obj: ProxyLogging | None = None, + load_user: UserLoader = get_user_object, + load_team: TeamLoader = get_team_object, + load_membership: MembershipLoader = get_team_membership, + ) -> None: + self._prisma = prisma_client + self._cache = cache + self._parent_otel_span = parent_otel_span + self._proxy_logging_obj = proxy_logging_obj + self._load_user = load_user + self._load_team = load_team + self._load_membership = load_membership + + async def resolve_identity( + self, lookup: UserLookup, team_id: str | None + ) -> tuple[LiteLLM_UserTable | None, LiteLLM_TeamMembership | None, str | None]: + user_object: Final = await self._user(lookup) if lookup.user_id else None + effective_user_id: Final = canonical_user_id(lookup.user_id, user_object) + if effective_user_id != lookup.user_id: + verbose_proxy_logger.debug( + "Auth: rebinding user_id %r -> DB user_id %r (email/sso match)", + lookup.user_id, + effective_user_id, + ) + membership: Final = ( + await self._membership(user_id=effective_user_id, team_id=team_id) + if effective_user_id and team_id + else None + ) + return user_object, membership, effective_user_id + + async def resolve(self, lookup: UserLookup, team_id: str | None) -> GrantOutcome: + try: + user_object, membership, effective_user_id = await self.resolve_identity(lookup, team_id) + except UserNotFoundError: + return UserGone(user_id=lookup.user_id or "") + except Exception as error: + return LookupDegraded(error=error) + if team_id is None: + return ResolvedGrants(user_object, None, membership, effective_user_id) + if user_object is not None and team_id not in user_object.teams: + return NotAMember(user_id=user_object.user_id, team_id=team_id) + try: + team_object: Final = await self._load_team( + team_id=team_id, + prisma_client=self._prisma, + user_api_key_cache=self._cache, + parent_otel_span=self._parent_otel_span, + proxy_logging_obj=self._proxy_logging_obj, + ) + except TeamNotFoundError: + return TeamGone(team_id=team_id) + except Exception as error: + return LookupDegraded(error=error) + return ResolvedGrants(user_object, team_object, membership, effective_user_id) + + async def _user(self, lookup: UserLookup) -> LiteLLM_UserTable | None: + return await self._load_user( + user_id=lookup.user_id, + prisma_client=self._prisma, + user_api_key_cache=self._cache, + user_id_upsert=lookup.upsert, + parent_otel_span=self._parent_otel_span, + proxy_logging_obj=self._proxy_logging_obj, + user_email=lookup.user_email, + sso_user_id=lookup.sso_user_id, + ) + + async def _membership(self, user_id: str, team_id: str) -> LiteLLM_TeamMembership | None: + return await self._load_membership( + user_id=user_id, + team_id=team_id, + prisma_client=self._prisma, + user_api_key_cache=self._cache, + parent_otel_span=self._parent_otel_span, + proxy_logging_obj=self._proxy_logging_obj, + ) diff --git a/litellm/proxy/auth/route_checks.py b/litellm/proxy/auth/route_checks.py index 953e3cf3e88..1789b080897 100644 --- a/litellm/proxy/auth/route_checks.py +++ b/litellm/proxy/auth/route_checks.py @@ -136,6 +136,9 @@ class RouteChecks: # For llm_api_routes, also check registered pass-through endpoints ################################################ if allowed_route == "llm_api_routes": + if route == "/auto_router/session" and RouteChecks._get_request_method(request) == "GET": + return True + from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( InitPassThroughEndpointHelpers, ) diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py index 9828311112e..9491f77ecfc 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -56,6 +56,7 @@ from litellm.proxy.auth.auth_checks import ( get_jwt_key_mapping_object, get_object_permission, get_project_object, + get_team_membership, get_team_object, get_user_object, is_valid_fallback_model, @@ -82,6 +83,14 @@ from litellm.proxy.auth.network import TrustedProxyConfig, resolve_network_conte from litellm.proxy.auth.oauth2_check import Oauth2Handler from litellm.proxy.auth.oauth2_proxy_hook import handle_oauth2_proxy_request from litellm.proxy.auth.resolvers import CredentialRef, Principal +from litellm.proxy.auth.resolvers.grants import ( + GrantResolver, + LookupDegraded, + ResolvedGrants, + UserLookup, + raise_public, + user_models, +) from litellm.proxy.auth.resolvers.store import IdentityStore from litellm.proxy.auth.route_checks import RouteChecks from litellm.proxy.auth.team_grants import team_grants @@ -182,6 +191,7 @@ def _get_model_from_request_context( route: str, request: Request | None, llm_router: Any | None = None, + team_id: str | None = None, ) -> str | list[str] | None: return get_model_from_request( request_data=request_data, @@ -190,6 +200,7 @@ def _get_model_from_request_context( request_query_params=_safe_get_request_query_params(request=request), llm_router=llm_router, request=request, + team_id=team_id, ) @@ -208,7 +219,7 @@ async def _normalize_claude_model( return if request is not None and request.scope.get(_CLAUDE_MODEL_NORMALIZED) is True: return - requested: Final = _get_model_from_request_context(request_data, route, request, llm_router) + requested: Final = _get_model_from_request_context(request_data, route, request, llm_router, valid_token.team_id) if not isinstance(requested, str) or requested != request_data.get("model"): return if not requested.startswith("claude-router-") and not requested.lower().endswith("[1m]"): @@ -867,6 +878,7 @@ async def _auto_register_jwt_mapping( # the NOT NULL @id constraint. Every successful key-creation caller (e.g. # /key/generate) passes table_name="key" explicitly. key_data: Final = await generate_key_helper_fn( + llm_router=None, request_type="key", table_name="key", team_id=team_id, @@ -987,9 +999,12 @@ async def _resolve_jwt_to_virtual_key( - Raises HTTPException: REJECT policy hit, missing claim under REJECT/AUTO_REGISTER, or other policy violations. """ - virtual_key_claim_field: Final = jwt_handler.litellm_jwtauth.virtual_key_claim_field + raw_issuer: Final = jwt_claims.get(JWTHandler.LITELLM_JWT_ISSUER_CLAIM) + normalized_issuer: Final = raw_issuer if isinstance(raw_issuer, str) else None + virtual_key_claim_field: Final = jwt_handler.litellm_jwtauth.get_virtual_key_claim_field(normalized_issuer) if virtual_key_claim_field is None: return None + behavior: Final = jwt_handler.litellm_jwtauth.get_unregistered_jwt_client_behavior(normalized_issuer) claim_value: Final = get_nested_value( data=jwt_claims, @@ -1006,7 +1021,6 @@ async def _resolve_jwt_to_virtual_key( # simply by presenting a JWT that omits the configured field. For # AUTO_REGISTER there is no stable identity to map without a claim # value, so we deny rather than create a sentinel-keyed record. - behavior = jwt_handler.litellm_jwtauth.unregistered_jwt_client_behavior if behavior in ( UnregisteredJWTClientBehavior.REJECT, UnregisteredJWTClientBehavior.AUTO_REGISTER, @@ -1021,7 +1035,13 @@ async def _resolve_jwt_to_virtual_key( return None cache_key: Final = jwt_key_mapping_cache_key(virtual_key_claim_field, str(claim_value)) - cached_mapping: Final = await user_api_key_cache.async_get_cache(cache_key) + raw_cached_mapping: Final = await user_api_key_cache.async_get_cache(cache_key) + sentinel_written_by_this_policy: Final = behavior == UnregisteredJWTClientBehavior.AUTO_REGISTER + cached_mapping: Final = ( + None + if raw_cached_mapping == _JWT_PROXY_ADMIN_SENTINEL and not sentinel_written_by_this_policy + else raw_cached_mapping + ) if cached_mapping == _JWT_PROXY_ADMIN_SENTINEL: # Previously resolved to a proxy admin via auth_builder; skip the @@ -1030,7 +1050,6 @@ async def _resolve_jwt_to_virtual_key( return None if cached_mapping == "__NO_MAPPING__": - behavior = jwt_handler.litellm_jwtauth.unregistered_jwt_client_behavior if behavior == UnregisteredJWTClientBehavior.REJECT: raise HTTPException( status_code=403, @@ -1093,8 +1112,6 @@ async def _resolve_jwt_to_virtual_key( ) # No mapping found (DB miss or no DB) — apply no-match policy. - behavior = jwt_handler.litellm_jwtauth.unregistered_jwt_client_behavior - if behavior == UnregisteredJWTClientBehavior.REJECT: # Cache the miss before raising so repeated rejections are served from # cache and don't re-query the DB on every request. @@ -1230,6 +1247,52 @@ async def _record_unparsable_body_failure( verbose_proxy_logger.exception("Failed to log the request rejected for an unparsable body: %s", e) +async def _refresh_session_token_grants( + valid_token: UserAPIKeyAuth, + prisma_client: PrismaClient, + user_api_key_cache: UserApiKeyCache, + parent_otel_span: Span | None, + proxy_logging_obj: ProxyLogging, +) -> UserAPIKeyAuth: + """Rebuild a ``lite login`` session token's grants from the live user and team rows. + + The blob only proves who logged in and which team they picked. Team models, aliases, the user's own model + list, and their role are re-read every request, so a `/team/update` or a demotion shows up without a + re-login, and a user removed from the team or deleted outright is refused. When a row cannot be read for + a reason unrelated to the caller, the minted grants stand in exactly as they did before this refresh. + """ + outcome: Final = await GrantResolver( + prisma_client, + user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + load_user=get_user_object, + load_team=get_team_object, + load_membership=get_team_membership, + ).resolve(UserLookup(user_id=valid_token.user_id), team_id=valid_token.team_id) + match outcome: + case ResolvedGrants( + user_object=LiteLLM_UserTable() as user_object, team_object=team_object, team_membership=team_membership + ): + return UserAPIKeyAuth.model_validate( + MappingProxyType( + { + **valid_token.model_dump(exclude_none=True), + **team_grants(team_object, team_membership, user_object.user_id), + "user_role": _get_user_role(user_object), + "models": () if team_object is not None else user_models(user_object), + } + ) + ) + case ResolvedGrants(): + return valid_token + case LookupDegraded(error=error): + verbose_proxy_logger.debug("Session token grants not refreshed, keeping minted grants: %s", error) + return valid_token + case _: + raise_public(outcome) + + async def _resolve_object_permission_for_unresolvable_team( object_permission_id: str | None, prisma_client: PrismaClient | None, @@ -1428,7 +1491,7 @@ async def _user_api_key_auth_builder( # unnecessary DB queries in auth_builder do_standard_jwt_auth = True pending_auto_register: _PendingAutoRegister | None = None - if jwt_handler.litellm_jwtauth.virtual_key_claim_field is not None: + if jwt_handler.litellm_jwtauth.is_virtual_key_mapping_configured(): # Decode JWT to get claims without running full auth_builder jwt_claims: dict | None if jwt_handler.litellm_jwtauth.oidc_userinfo_enabled and not is_jwt: @@ -1592,6 +1655,7 @@ async def _user_api_key_auth_builder( route=route, request=request, llm_router=llm_router, + team_id=valid_token.team_id, ) skip_budget_checks = False if model is not None and llm_router is not None: @@ -1632,6 +1696,7 @@ async def _user_api_key_auth_builder( route=route, request=request, llm_router=llm_router, + team_id=valid_token.team_id, ) ), ) @@ -1774,6 +1839,15 @@ async def _user_api_key_auth_builder( ): valid_token = ExperimentalUIJWTToken.get_key_object_from_ui_hash_key(api_key) + if valid_token is not None and valid_token.is_session_token and prisma_client is not None: + valid_token = await _refresh_session_token_grants( # rebind-ok: later checks read this name + valid_token=valid_token, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) + if ( valid_token is not None and isinstance(valid_token, UserAPIKeyAuth) @@ -2022,6 +2096,7 @@ async def _user_api_key_auth_builder( route=route, request=request, llm_router=llm_router, + team_id=valid_token.team_id, ) skip_budget_checks = False if model is not None and llm_router is not None: @@ -2140,6 +2215,7 @@ async def _user_api_key_auth_builder( route=route, request=request, llm_router=llm_router, + team_id=valid_token.team_id, ) current_models = _get_model_names_for_budget_checks(model=current_model) @@ -2170,6 +2246,7 @@ async def _user_api_key_auth_builder( route=route, request=request, llm_router=llm_router, + team_id=valid_token.team_id, ) current_models = _get_model_names_for_budget_checks(model=current_model) @@ -2665,6 +2742,7 @@ async def _run_centralized_common_checks( route=route, request=request, llm_router=llm_router, + team_id=user_api_key_auth_obj.team_id, ) # Pin the metadata variable name (litellm_metadata vs metadata) before @@ -2781,12 +2859,14 @@ def _should_skip_budget_checks( route: str, request: Request | None, llm_router: Any | None, + team_id: str | None = None, ) -> bool: model: Final = _get_model_from_request_context( request_data=request_data, route=route, request=request, llm_router=llm_router, + team_id=team_id, ) if model is not None and llm_router is not None: return _is_model_cost_zero(model=model, llm_router=llm_router) @@ -3232,6 +3312,7 @@ async def _enforce_key_and_fallback_model_access( route=route, request=request, llm_router=llm_router, + team_id=valid_token.team_id, ) if model is not None: @@ -3339,6 +3420,7 @@ async def _run_post_custom_auth_checks( route=route, request=request, llm_router=llm_router, + team_id=valid_token.team_id, ) current_models = _get_model_names_for_budget_checks(model=current_model) @@ -3380,6 +3462,7 @@ async def _run_post_custom_auth_checks( route=route, request=request, llm_router=llm_router, + team_id=valid_token.team_id, ) current_models = _get_model_names_for_budget_checks(model=current_model) diff --git a/litellm/proxy/client/cli/README.md b/litellm/proxy/client/cli/README.md index 3b0ff9d7add..a5a2675ed6e 100644 --- a/litellm/proxy/client/cli/README.md +++ b/litellm/proxy/client/cli/README.md @@ -580,12 +580,14 @@ What the command changed is recorded in `~/.litellm/claude_configure_state.json` `lite configure claude`, `lite login --config-claude`, `lite up` and `lite autoroute up` also install a status line (`~/.litellm/statusline.py`, registered as `statusLine` in `~/.claude/settings.json` unless you already run one) that shows which model the auto-router actually served the last turn and, once the proxy has recorded the session, what the session cost against the router's savings baseline: ``` -claude-auto · Routed to: claude-haiku-4-5 -63% vs Claude Opus 5 -LiteLLM ████████░░░░░░░░░░░░░░░░ $0.14 +Routed to: claude-haiku-4-5 -63% vs Claude Opus 5 +claude-auto ████████░░░░░░░░░░░░░░░░ $0.14 Claude Opus 5 ████████████████████████ $0.38 ``` -The routed model comes from Claude Code's own transcript, so it only names the tier model when the auto-router deployment sets `return_raw_model_name: true` (the `lite autoroute` wizard does); otherwise it shows the alias you requested. The cost lines come from `GET /auto_router/session?session_id=...`, which any virtual key may call for its own sessions, and are cached for five seconds under a per-user `$TMPDIR/litellm-statusline-` directory. The baseline is the priciest model in the router's hardest tier, the same counterfactual the auto-router's savings reports use. `lite unconfigure claude` removes the `statusLine` entry only while it still points at that script. +After the first response, the status line uses the latest routed model recorded by `GET /auto_router/session?session_id=...`, so it can show the tier model even when the transcript contains the router alias. If no session record is available, it falls back to Claude Code's transcript. Session records and costs are cached for five seconds under a per-user `$TMPDIR/litellm-statusline-` directory. The gateway records turns asynchronously, so the display can briefly lag a completed turn. Any virtual key may read its own sessions. The baseline is the priciest model in the router's hardest tier, the same counterfactual the auto-router's savings reports use. `lite unconfigure claude` removes the `statusLine` entry only while it still points at that script + +After upgrading the CLI, rerun your original `lite configure claude` command with the same gateway, key and model choice to refresh `~/.litellm/statusline.py`. Keep any explicit `--model` value: omitting it removes the earlier model pin. Package upgrades alone do not refresh this installed copy `lite codex` registers the same script as a Codex `Stop` hook for the launch, so after each turn Codex prints the same block as a system message. Codex asks once to trust the hook; the answer is remembered for later launches. diff --git a/litellm/proxy/client/cli/commands/pi.py b/litellm/proxy/client/cli/commands/pi.py index 9810e81ae36..5c749959638 100644 --- a/litellm/proxy/client/cli/commands/pi.py +++ b/litellm/proxy/client/cli/commands/pi.py @@ -10,7 +10,7 @@ import os import tempfile from collections.abc import Callable, Mapping from dataclasses import dataclass -from enum import StrEnum +from enum import Enum from pathlib import Path from types import MappingProxyType from typing import Annotated, Final @@ -25,7 +25,7 @@ LITELLM_PROXY_API_KEY_ENV: Final = "LITELLM_PROXY_API_KEY" _REJECTED_STATUSES: Final = frozenset((401, 403)) -class ListingFailure(StrEnum): +class ListingFailure(str, Enum): """Why a proxy could not be listed, decided once where the HTTP outcome is classified. `unreachable` means no response at all; the other kinds prove the proxy answered, so callers diff --git a/litellm/proxy/client/cli/commands/statusline_script.py b/litellm/proxy/client/cli/commands/statusline_script.py index a8abeb68978..47be3888a58 100644 --- a/litellm/proxy/client/cli/commands/statusline_script.py +++ b/litellm/proxy/client/cli/commands/statusline_script.py @@ -7,19 +7,17 @@ status refresh (about every 300ms while typing), so the proxy is asked at most o TTL per session and every other refresh is served from a small on-disk cache that holds only the proxy's answer, never the key. -Claude Code pipes a JSON payload on stdin (session_id, transcript_path, model); the routed -model is the `message.model` of the latest foreground assistant line in the transcript, -which is the proxy's response `model` field. That only names the tier model when the -auto-router deployment sets `return_raw_model_name: true`; otherwise it is the alias the -client requested. Codex pipes its Stop event instead (hook_event_name, session_id) and has -no transcript to read, so the routed model comes from the proxy's session record and the -result is printed as a `systemMessage` for the transcript. The proxy key is read from the -agent's own environment (the static token `lite configure claude` writes); nothing here -spawns a credential helper. +Claude Code pipes a JSON payload on stdin (session_id, transcript_path, model). After the +first foreground assistant response, the routed model comes from the proxy's session +record, falling back to the latest foreground assistant `message.model` in the transcript +when no record is available. Codex pipes its Stop event instead (hook_event_name, session_id) +and prints the session record as a `systemMessage` for the transcript. The proxy key is read +from the agent's own environment (the static token `lite configure claude` writes); nothing +here spawns a credential helper. -Cost figures come from GET /auto_router/session on the proxy, which reads the per-session -rollup written by the spend flush. That flush is asynchronous, so a turn's cost lands a -second or two after the turn; the cache TTL absorbs it. +The routed model and cost figures come from GET /auto_router/session on the proxy, which +reads the per-session rollup written by the asynchronous spend flush. The record and cache +can briefly lag a completed turn. """ from __future__ import annotations @@ -30,6 +28,7 @@ import os import sys import tempfile import time +import unicodedata import urllib.error import urllib.request from collections.abc import Callable, Mapping @@ -44,7 +43,6 @@ FETCH_TIMEOUT_SECONDS: Final = 3 BAR_WIDTH: Final = 24 BAR_FULL: Final = "\u2588" BAR_EMPTY: Final = "\u2591" -SEPARATOR: Final = " \u00b7 " TRANSCRIPT_SCAN_LIMIT_BYTES: Final = 4 * 1024 * 1024 CLAUDE_BASE_URL_ENV_KEYS: Final = ("ANTHROPIC_BASE_URL",) CLAUDE_API_KEY_ENV_KEYS: Final = ("ANTHROPIC_AUTH_TOKEN", "ANTHROPIC_API_KEY") @@ -52,7 +50,6 @@ CODEX_BASE_URL_ENV_KEYS: Final = ("OPENAI_BASE_URL",) CODEX_API_KEY_ENV_KEYS: Final = ("OPENAI_API_KEY",) CODEX_STOP_EVENT: Final = "Stop" SYNTHETIC_MODEL: Final = "" -LITELLM_LABEL: Final = "LiteLLM" RESET: Final = "\033[0m" BOLD: Final = "\033[1m" DIM: Final = "\033[90m" @@ -304,31 +301,37 @@ def _bar(fraction: float, color: str, width: int, use_color: bool) -> str: return f"{color}{BAR_FULL * filled}{DIM}{BAR_EMPTY * (width - filled)}{RESET}" +def _display_width(label: str) -> int: + return sum( + 2 if unicodedata.east_asian_width(character) in ("W", "F") else 1 + for character in label + if unicodedata.category(character) not in ("Mn", "Me") + ) + + def render(model: str, session: Session | None, config_dir: Path, use_color: bool, bar_width: int = BAR_WIDTH) -> str: def paint(code: str, text: str) -> str: return f"{code}{text}{RESET}" if use_color else text routed: Final = paint(BOLD, f"Routed to: {model}") - if session is None: + if session is None or session.baseline_model is None or session.baseline_spend <= 0: return routed - header: Final = f"{session.router_name}{SEPARATOR}{routed}" - if session.baseline_model is None or session.baseline_spend <= 0: - return header reference: Final = baseline_label(session.baseline_model, config_dir) pct: Final = (session.baseline_spend - session.spend) / session.baseline_spend * 100 delta: Final = paint(LITELLM_COLOR, f"{'-' if pct >= 0 else '+'}{abs(round(pct))}% vs {reference}") peak: Final = max(session.spend, session.baseline_spend) - label_width: Final = max(len(LITELLM_LABEL), len(reference)) + label_width: Final = max(_display_width(session.router_name), _display_width(reference)) rows: Final = ( - (LITELLM_LABEL, session.spend, LITELLM_COLOR), + (session.router_name, session.spend, LITELLM_COLOR), (reference, session.baseline_spend, BASELINE_COLOR), ) lines: Final = ( - f"{paint(DIM, label.ljust(label_width))} {_bar(amount / peak, color, bar_width, use_color)} " + f"{paint(DIM, label + ' ' * (label_width - _display_width(label)))} " + f"{_bar(amount / peak, color, bar_width, use_color)} " f"{paint(DIM, f'${amount:.2f}')}" for label, amount, color in rows ) - return "\n".join((f"{header} {delta}", *lines)) + return "\n".join((f"{routed} {delta}", *lines)) def color_enabled(env: Mapping[str, str]) -> bool: @@ -348,7 +351,8 @@ def status_line( if not session_id or not credentials.usable: return render(label, None, config_dir, color_enabled(env)) session: Final = load_session(credentials, session_id, cache_dir, fetch) - return render(label, session, config_dir, color_enabled(env)) + routed_label: Final = model_label(session.last_model, config_dir) if session is not None else label + return render(routed_label, session, config_dir, color_enabled(env)) def codex_stop_message( diff --git a/litellm/proxy/common_request_processing.py b/litellm/proxy/common_request_processing.py index e6ed60ba177..4a4daa68cce 100644 --- a/litellm/proxy/common_request_processing.py +++ b/litellm/proxy/common_request_processing.py @@ -14,6 +14,7 @@ import httpx import orjson from fastapi import HTTPException, Request, status from fastapi.responses import JSONResponse, Response, StreamingResponse +from pydantic import ValidationError from starlette.types import Receive, Scope, Send import litellm @@ -24,6 +25,7 @@ from litellm.constants import ( DEFAULT_MAX_RECURSE_DEPTH, LITELLM_DETAILED_TIMING, LITELLM_HTTP_STATUS_CLIENT_DISCONNECTED, + MAX_LITELLM_CALL_ID_LENGTH, MAX_PAYLOAD_SIZE_FOR_DEBUG_LOG, NON_INFERENCE_CALL_TYPES, RETURN_RAW_MODEL_NAME_METADATA_KEY, @@ -75,6 +77,7 @@ from litellm.router_utils.add_retry_fallback_headers import get_hidden_params_di from litellm.router_utils.common_utils import resolve_model_group_alias from litellm.types.guardrails import GuardrailEventHooks from litellm.types.router import RouterRateLimitError +from litellm.types.router_weights import validate_router_weights _LateResponseT = TypeVar("_LateResponseT", bound=Response) _LlmCallT = TypeVar("_LlmCallT") @@ -217,6 +220,12 @@ def _withheld_provider_output(response: object) -> bool: return getattr(response, "has_buffered_provider_output", False) is True +def resolve_litellm_call_id(client_call_id: str | None) -> str: + if client_call_id is not None and 0 < len(client_call_id) <= MAX_LITELLM_CALL_ID_LENGTH: + return client_call_id + return str(uuid.uuid4()) + + def _should_return_raw_model_name(request_data: dict[str, object]) -> bool: return any( isinstance(metadata, dict) and metadata.get(RETURN_RAW_MODEL_NAME_METADATA_KEY) is True @@ -1564,6 +1573,9 @@ class ProxyBaseLLMRequestProcessing: ) -> dict: exclude_values: Final = {"", None, "None"} hidden_params = hidden_params or {} + resolved_call_id: Final = ( + call_id or hidden_params.get("litellm_call_id") or (request_data or {}).get("litellm_call_id") + ) timing_values: Final = _timing_values( hidden_params=hidden_params, logging_obj=litellm_logging_obj, @@ -1591,7 +1603,7 @@ class ProxyBaseLLMRequestProcessing: classifier_cost: Final = _classifier_cost_from_request_data(request_data) headers: Final = { - "x-litellm-call-id": call_id, + "x-litellm-call-id": resolved_call_id, "x-litellm-model-id": model_id, "x-litellm-model-name": model_name, "x-litellm-cache-key": cache_key, @@ -1929,6 +1941,13 @@ class ProxyBaseLLMRequestProcessing: # This avoids expensive Router instantiation on each request if router_settings is not None: self.data["router_settings_override"] = router_settings + try: + self.data["_router_weights"] = validate_router_weights(router_settings.get("weights")) + except ValidationError: + self.data["_router_weights"] = None + verbose_proxy_logger.warning( + "Ignoring invalid saved router weights; update team/key router_settings" + ) alias_target: Final = await _resolve_per_request_model_group_alias( requested_model=self.data.get("model"), router_settings=router_settings, @@ -1938,7 +1957,7 @@ class ProxyBaseLLMRequestProcessing: if alias_target is not None: self.data["model"] = alias_target - self.data["litellm_call_id"] = request.headers.get("x-litellm-call-id", str(uuid.uuid4())) + self.data["litellm_call_id"] = resolve_litellm_call_id(request.headers.get("x-litellm-call-id")) DDSpanTagger.tag_call_id(self.data.get("litellm_call_id")) DDSpanTagger.tag_request( user_api_key_dict=user_api_key_dict, @@ -3445,15 +3464,13 @@ class ProxyBaseLLMRequestProcessing: # a failed request reports no timing, matching /v1/chat/completions read_timing_from_logging_obj=False, ) - # Extract headers from exception - check both e.headers and e.response.headers headers = getattr(e, "headers", None) or {} if not headers: - # Try to get headers from e.response.headers (httpx.Response) _response: Final = attribute_of(e, "response") - if _response is not None: - _response_headers: Final = getattr(_response, "headers", None) - if _response_headers: - headers = get_response_headers(dict(_response_headers)) + _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) + if _provider_headers: + headers = get_response_headers(dict(_provider_headers)) headers.update(custom_headers) # Call response headers hook for failure diff --git a/litellm/proxy/common_utils/config_includes.py b/litellm/proxy/common_utils/config_includes.py new file mode 100644 index 00000000000..c1bb5ae952f --- /dev/null +++ b/litellm/proxy/common_utils/config_includes.py @@ -0,0 +1,132 @@ +import os +from collections.abc import Awaitable, Mapping +from types import MappingProxyType +from typing import Final, Protocol + +from litellm._logging import verbose_proxy_logger + +INCLUDE_KEY: Final = "include" + + +def resolve_include_file_path(include_file: str, declared_in: str, root_config_path: str) -> str: + """ + Resolve one `include` entry to the file it names, next to the config that declares it. + + A config written before nested entries resolved this way can name a file sitting next to the root + config instead, so that file is still read, with a warning naming where it was found. When both + files exist the one next to the declaring config wins and the other is named in a warning. + """ + declared_relative: Final = os.path.abspath(os.path.join(os.path.dirname(declared_in), include_file)) + root_relative: Final = os.path.abspath(os.path.join(os.path.dirname(root_config_path), include_file)) + if root_relative == declared_relative or not os.path.exists(root_relative): + return declared_relative + + if not os.path.exists(declared_relative): + verbose_proxy_logger.warning( + "Config include '%s' declared in %s was not found next to it, so %s was read instead. " + "Move the included file next to the config that declares it.", + include_file, + declared_in, + root_relative, + ) + return root_relative + + verbose_proxy_logger.warning( + "Config include '%s' declared in %s matches two files. %s sits next to that config and was read, " + "so %s was skipped. Rename one of the two to say which one you meant.", + include_file, + declared_in, + declared_relative, + root_relative, + ) + return declared_relative + + +class IncludeResolver(Protocol): + def __call__(self, include_entry: str, declared_in: str, /) -> str: ... + + +class ConfigReader(Protocol): + def __call__(self, location: str, /) -> Awaitable[Mapping[str, object]]: ... + + +def _merged_value(base_value: object, included_value: object) -> object: + if isinstance(included_value, list) and isinstance(base_value, list): + return [*base_value, *included_value] # mutable-ok: a merged config value stays the plain list the proxy loads + return included_value + + +def _merged_entry(base: Mapping[str, object], included: Mapping[str, object], key: str) -> object: + if key not in included: + return base[key] + return _merged_value(base.get(key), included[key]) + + +def _merged(base: Mapping[str, object], included: Mapping[str, object]) -> Mapping[str, object]: + return MappingProxyType({key: _merged_entry(base, included, key) for key in (*base, *included)}) + + +def _without_include(config: Mapping[str, object]) -> Mapping[str, object]: + return MappingProxyType({key: value for key, value in config.items() if key != INCLUDE_KEY}) + + +def include_entries(config: Mapping[str, object]) -> tuple[str, ...]: + if INCLUDE_KEY not in config: + return () + + entries: Final = config[INCLUDE_KEY] + if not isinstance(entries, list): + raise ValueError("'include' must be a list of file paths") + + paths: Final = tuple(entry for entry in entries if isinstance(entry, str)) + if len(paths) != len(entries): + raise ValueError("'include' must be a list of file paths") + + return paths + + +def _pending_from(config: Mapping[str, object], location: str) -> tuple[tuple[str, str], ...]: + return tuple((entry, location) for entry in include_entries(config)) + + +async def _resolve( + config: Mapping[str, object], + pending: tuple[tuple[str, str], ...], + loaded: frozenset[str], + resolve: IncludeResolver, + read: ConfigReader, +) -> Mapping[str, object]: + if not pending: + return _without_include(config) + + entry, declared_in = pending[0] + location: Final = resolve(entry, declared_in) + if location in loaded: + return await _resolve(config, pending[1:], loaded, resolve, read) + + included: Final = await read(location) + return await _resolve( + _merged(config, _without_include(included)), + (*pending[1:], *_pending_from(included, location)), + loaded | frozenset((location,)), + resolve, + read, + ) + + +async def resolve_includes( + config: Mapping[str, object], + location: str, + resolve: IncludeResolver, + read: ConfigReader, +) -> dict[str, object]: + """ + Merge every config named by the `include` directive into the config that declares it. + + List values are extended and every other value is overridden, `resolve` turns each entry into the + location it names relative to the config that declares it, a config already pulled in is neither + read nor merged a second time, and `read` decides where a location is read from, so the same merge + applies to configs on disk and to configs hosted in a bucket. + """ + merged: Final = await _resolve(config, _pending_from(config, location), frozenset((location,)), resolve, read) + return dict(merged) # mutable-ok: the proxy mutates the config it loads diff --git a/litellm/proxy/common_utils/html_forms/default_credentials_hint.py b/litellm/proxy/common_utils/html_forms/default_credentials_hint.py new file mode 100644 index 00000000000..e3ed948501b --- /dev/null +++ b/litellm/proxy/common_utils/html_forms/default_credentials_hint.py @@ -0,0 +1,10 @@ +import os +from collections.abc import Mapping + + +def should_hide_default_credentials_hint(general_settings: Mapping[str, object]) -> bool: + return ( + os.getenv("LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", "false").lower() == "true" + or general_settings.get("hide_default_credentials_hint", False) is True + or bool(os.getenv("UI_PASSWORD")) + ) diff --git a/litellm/proxy/common_utils/load_config_utils.py b/litellm/proxy/common_utils/load_config_utils.py index 62649ad6ca1..4a082eb307b 100644 --- a/litellm/proxy/common_utils/load_config_utils.py +++ b/litellm/proxy/common_utils/load_config_utils.py @@ -1,12 +1,47 @@ +import asyncio import os -from typing import Final +import posixpath +from collections.abc import Awaitable, Mapping +from types import MappingProxyType +from typing import TYPE_CHECKING, Final, Protocol import yaml +from pydantic import TypeAdapter, ValidationError from litellm._logging import verbose_proxy_logger +from litellm.proxy.common_utils.config_includes import resolve_includes + +if TYPE_CHECKING: + from litellm.integrations.gcs_bucket.gcs_bucket_base import GCSBucketBase + +_BUCKET_CONFIG_ADAPTER: Final = TypeAdapter(dict[str, object]) -def get_file_contents_from_s3(bucket_name, object_key): +class BucketObjectFetcher(Protocol): + def __call__(self, object_key: str, /) -> Awaitable[Mapping[str, object] | None]: ... + + +class BucketObjectReader(Protocol): + def __call__(self, object_key: str, /) -> Awaitable[object | None]: ... + + +class SyncBucketObjectReader(Protocol): + def __call__(self, object_key: str, /) -> object | None: ... + + +def _parsed_config(object_key: str, file_contents: str) -> object | None: + try: + parsed: Final = yaml.safe_load(file_contents) + except yaml.YAMLError as e: + verbose_proxy_logger.error("Config object %s is not valid YAML: %s", object_key, e) + return None + return MappingProxyType({}) if parsed is None else parsed + + +def s3_object_reader(bucket_name: str) -> SyncBucketObjectReader: + """ + Build one reader for a whole config, so an `include` tree costs one S3 client rather than one per object. + """ try: # v0 rely on boto3 for authentication - allowing boto3 to handle IAM credentials etc import boto3 @@ -21,46 +56,147 @@ def get_file_contents_from_s3(bucket_name, object_key): aws_secret_access_key=credentials.secret_key, aws_session_token=credentials.token, # Optional, if using temporary credentials ) - verbose_proxy_logger.debug("Retrieving %s from S3 bucket: %s", object_key, bucket_name) - response: Final = s3_client.get_object(Bucket=bucket_name, Key=object_key) - verbose_proxy_logger.debug("Response: %s", response) - - # Read the file contents and directly parse YAML - file_contents: Final = response["Body"].read().decode("utf-8") - verbose_proxy_logger.debug("File contents retrieved from S3") - - # Parse YAML directly from string - config: Final = yaml.safe_load(file_contents) - return config - except ImportError as e: # this is most likely if a user is not using the litellm docker container verbose_proxy_logger.error("ImportError: %s", e) + return lambda object_key: None except Exception as e: - verbose_proxy_logger.error("Error retrieving file contents: %s", e) + verbose_proxy_logger.error("Error creating the S3 client for bucket %s: %s", bucket_name, e) + return lambda object_key: None + + def read(object_key: str) -> object | None: + try: + verbose_proxy_logger.debug("Retrieving %s from S3 bucket: %s", object_key, bucket_name) + response: Final = s3_client.get_object(Bucket=bucket_name, Key=object_key) + file_contents: Final = response["Body"].read().decode("utf-8") + except Exception as e: # noqa: BLE001 # any boto3 error must read as a missing object + verbose_proxy_logger.error("Error retrieving %s from S3 bucket %s: %s", object_key, bucket_name, e) + return None + + return _parsed_config(object_key, file_contents) + + return read + + +def get_file_contents_from_s3(bucket_name: str, object_key: str) -> object | None: + return s3_object_reader(bucket_name)(object_key) + + +def gcs_config_bucket(bucket_name: str) -> "GCSBucketBase | None": + """ + Build a plain GCS client for reading config objects. + + Reading a config out of a bucket is not GCS logging, so it neither needs the enterprise license + that gate covers nor the batching task the logger starts and never stops. + """ + try: + from litellm.integrations.gcs_bucket.gcs_bucket_base import GCSBucketBase + + return GCSBucketBase(bucket_name=bucket_name) + except Exception as e: # noqa: BLE001 # an unbuildable client must read as an unreadable bucket + verbose_proxy_logger.error("Error creating the GCS client for bucket %s: %s", bucket_name, e) return None -async def get_config_file_contents_from_gcs(bucket_name, object_key): +async def get_config_file_contents_from_gcs( + bucket_name: str, + object_key: str, + gcs_bucket: "GCSBucketBase | None" = None, +) -> object | None: try: - from litellm.integrations.gcs_bucket.gcs_bucket import GCSBucketLogger - - gcs_bucket: Final = GCSBucketLogger( - bucket_name=bucket_name, - ) - file_contents = await gcs_bucket.download_gcs_object(object_key) + bucket: Final = gcs_config_bucket(bucket_name) if gcs_bucket is None else gcs_bucket + if bucket is None: + return None + file_contents: Final = await bucket.download_gcs_object(object_key) if file_contents is None: raise Exception(f"File contents are None for {object_key}") - # file_contentis is a bytes object, so we need to convert it to yaml - file_contents = file_contents.decode("utf-8") - # convert to yaml - config: Final = yaml.safe_load(file_contents) - return config + decoded: Final = file_contents.decode("utf-8") except Exception as e: - verbose_proxy_logger.error("Error retrieving file contents: %s", e) + verbose_proxy_logger.error("Error retrieving %s from GCS bucket %s: %s", object_key, bucket_name, e) return None + return _parsed_config(object_key, decoded) + + +def resolve_include_object_key(config_object_key: str, include_entry: str) -> str: + """ + Resolve one `include` entry to the object key it names, relative to the config object's prefix. + + A leading "/" means the bucket root, mirroring how an absolute path on disk ignores the + directory the including config sits in. + """ + if include_entry.startswith("/"): + return posixpath.normpath(include_entry).lstrip("/") + return posixpath.normpath(posixpath.join(posixpath.dirname(config_object_key), include_entry)) + + +async def resolve_bucket_includes( + *, + config: Mapping[str, object], + object_key: str, + fetch: BucketObjectFetcher, +) -> dict[str, object]: + async def read(include_key: str) -> Mapping[str, object]: + included: Final = await fetch(include_key) + if included is None: + raise FileNotFoundError( + f"Included config could not be read from bucket: {include_key}. " + "The underlying bucket error is logged above." + ) + return included + + def resolve(include_entry: str, declared_in: str) -> str: + return resolve_include_object_key(declared_in, include_entry) + + return await resolve_includes(config=config, location=object_key, resolve=resolve, read=read) + + +async def bucket_object_reader(bucket_type: str | None, bucket_name: str) -> BucketObjectReader: + """ + Build one reader for a whole config, so an `include` tree costs one bucket client rather than one per object. + """ + if bucket_type != "gcs": + read_object: Final = await asyncio.to_thread(s3_object_reader, bucket_name) + + async def read_from_s3(object_key: str) -> object | None: + return await asyncio.to_thread(read_object, object_key) + + return read_from_s3 + + gcs_bucket: Final = gcs_config_bucket(bucket_name) + + async def read_from_gcs(object_key: str) -> object | None: + if gcs_bucket is None: + return None + return await get_config_file_contents_from_gcs(bucket_name, object_key, gcs_bucket) + + return read_from_gcs + + +async def get_config_from_bucket( + *, + bucket_type: str | None, + bucket_name: str, + object_key: str, +) -> dict[str, object] | None: + read: Final = await bucket_object_reader(bucket_type, bucket_name) + + async def fetch(key: str) -> Mapping[str, object] | None: + raw: Final = await read(key) + if raw is None: + return None + try: + return _BUCKET_CONFIG_ADAPTER.validate_python(raw) + except ValidationError as e: + raise ValueError(f"Config object in bucket is not a YAML mapping: {key}") from e + + config: Final = await fetch(object_key) + if not config: + return None + + return await resolve_bucket_includes(config=config, object_key=object_key, fetch=fetch) + def download_python_file_from_s3( bucket_name: str, @@ -136,11 +272,9 @@ async def download_python_file_from_gcs( bool: True if successful, False otherwise """ try: - from litellm.integrations.gcs_bucket.gcs_bucket import GCSBucketLogger + from litellm.integrations.gcs_bucket.gcs_bucket_base import GCSBucketBase - gcs_bucket: Final = GCSBucketLogger( - bucket_name=bucket_name, - ) + gcs_bucket: Final = GCSBucketBase(bucket_name=bucket_name) file_contents = await gcs_bucket.download_gcs_object(object_key) if file_contents is None: raise Exception(f"File contents are None for {object_key}") diff --git a/litellm/proxy/common_utils/openai_error_payload.py b/litellm/proxy/common_utils/openai_error_payload.py index 89f735ee8b6..fe23ab2c4b6 100644 --- a/litellm/proxy/common_utils/openai_error_payload.py +++ b/litellm/proxy/common_utils/openai_error_payload.py @@ -8,6 +8,8 @@ from typing import Final from fastapi import status +from litellm.constants import STRINGIFIED_NONE + _OPENAI_ERROR_TYPE_BY_STATUS: Final[Mapping[int, str]] = MappingProxyType( { status.HTTP_401_UNAUTHORIZED: "authentication_error", @@ -35,7 +37,7 @@ def openai_error_type(exc: object, status_code: int) -> str: """OpenAI types ``error.type`` as a required string, so an exception carrying none falls back to the type its status code stands for.""" carried: Final = attribute_of(exc, "type") - if isinstance(carried, str): + if isinstance(carried, str) and carried != STRINGIFIED_NONE: return carried mapped: Final = _OPENAI_ERROR_TYPE_BY_STATUS.get(status_code) if mapped is not None: @@ -49,4 +51,4 @@ def openai_error_param(exc: object) -> str | None: """OpenAI types ``error.param`` as nullable, so an exception carrying none serializes as JSON ``null``.""" carried: Final = attribute_of(exc, "param") - return carried if isinstance(carried, str) else None + return carried if isinstance(carried, str) and carried != STRINGIFIED_NONE else None diff --git a/litellm/proxy/common_utils/prompt_cache_pricing.py b/litellm/proxy/common_utils/prompt_cache_pricing.py new file mode 100644 index 00000000000..ff070853b46 --- /dev/null +++ b/litellm/proxy/common_utils/prompt_cache_pricing.py @@ -0,0 +1,91 @@ +from collections.abc import Mapping +from math import isfinite +from typing import Final + +from pydantic import TypeAdapter + +import litellm +from litellm.cost_calculator import ( + _select_model_name_for_cost_calc, # pyright: ignore[reportPrivateUsage] # shares completion_cost's deployment tariff selection + completion_cost, # pyright: ignore[reportUnknownVariableType] # legacy optional parameters are untyped +) +from litellm.litellm_core_utils.litellm_logging import Logging +from litellm.types.management_endpoints.prompt_cache_prediction import CacheTokenBuckets +from litellm.types.utils import CacheCreationTokenDetails, ModelResponse, PromptTokensDetailsWrapper, Usage + +_PRICE_ENTRY: Final = TypeAdapter(Mapping[str, object]) + + +def _valid_price(value: object) -> bool: + return isinstance(value, (int, float)) and not isinstance(value, bool) and isfinite(value) and value >= 0 + + +def _has_required_prices(prices: Mapping[str, object], tokens: CacheTokenBuckets) -> bool: + required: Final = ( + ("input_cost_per_token", True), + ("cache_read_input_token_cost", tokens.cache_read_input_tokens > 0), + ("cache_creation_input_token_cost", tokens.cache_creation_5m_input_tokens > 0), + ("cache_creation_input_token_cost_above_1hr", tokens.cache_creation_1h_input_tokens > 0), + ) + if any(needed and not _valid_price(prices.get(key)) for key, needed in required): + return False + return all( + _valid_price(value) + for key, value in prices.items() + if value is not None and any(needed and key.startswith(f"{base}_above_") for base, needed in required) + ) + + +def price_cache_tokens(model: str, deployment_id: str, tokens: CacheTokenBuckets) -> float | None: + try: + selected_model: Final = _select_model_name_for_cost_calc( + model=model, + completion_response=None, + custom_pricing=True, + custom_llm_provider="anthropic", + router_model_id=deployment_id, + ) + if selected_model is None: + return None + model_info: Final = litellm.get_model_info(model=selected_model, custom_llm_provider="anthropic") + registry: Final = _PRICE_ENTRY.validate_python(litellm.model_cost) # pyright: ignore[reportUnknownMemberType] # legacy registry is validated at this boundary + price_entry: Final = registry.get(model_info["key"]) + if price_entry is None: + return None + prices: Final = _PRICE_ENTRY.validate_python(price_entry) + if not _has_required_prices(prices, tokens): + return None + usage: Final = Usage( + prompt_tokens=tokens.total_tokens, + completion_tokens=0, + total_tokens=tokens.total_tokens, + prompt_tokens_details=PromptTokensDetailsWrapper( + cached_tokens=tokens.cache_read_input_tokens, + cache_creation_tokens=tokens.cache_creation_5m_input_tokens + tokens.cache_creation_1h_input_tokens, + cache_creation_token_details=CacheCreationTokenDetails( + ephemeral_5m_input_tokens=tokens.cache_creation_5m_input_tokens, + ephemeral_1h_input_tokens=tokens.cache_creation_1h_input_tokens, + ), + ), + ) + logging_obj: Final = Logging( + model=model, + messages=[], # mutable-ok: Logging requires a list + stream=False, + call_type="completion", + start_time=None, + litellm_call_id="prompt-cache-prediction", + function_id="prompt-cache-prediction", + ) + completion_cost( + completion_response=ModelResponse(model=model, usage=usage), + model=model, + custom_llm_provider="anthropic", + custom_pricing=True, + router_model_id=deployment_id, + litellm_logging_obj=logging_obj, + ) + cost: Final = logging_obj.cost_breakdown.get("input_cost") if logging_obj.cost_breakdown is not None else None + return cost if cost is not None and _valid_price(cost) else None + except Exception: # noqa: BLE001 # the shared pricing owners raise plain Exception for unpriceable models + return None diff --git a/litellm/proxy/common_utils/user_api_key_cache.py b/litellm/proxy/common_utils/user_api_key_cache.py index cb72088ee4a..1c7a379897f 100644 --- a/litellm/proxy/common_utils/user_api_key_cache.py +++ b/litellm/proxy/common_utils/user_api_key_cache.py @@ -336,6 +336,14 @@ def team_membership_reservation_cache_key(user_id: str, team_id: str) -> str: return f"team_membership:{user_id}:{team_id}" +#: Cached under ``team_membership_reservation_cache_key`` when a member has no ``LiteLLM_TeamMembership`` +#: row, so a session-token member without a per-member budget costs no DB read per request. Lives beside +#: the key builder because it is part of the same cache protocol: every reader of the key must know that +#: a plain string here means "no row", distinct from a serialized membership. The two budget readers +#: already treat a non-model value as "no row", so they need no change to stay correct. +NO_TEAM_MEMBERSHIP_SENTINEL: Final = "__no_team_membership__" + + 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/compliance_checks.py b/litellm/proxy/compliance_checks.py index ff311911742..9d2f2dc7c69 100644 --- a/litellm/proxy/compliance_checks.py +++ b/litellm/proxy/compliance_checks.py @@ -26,7 +26,7 @@ class ComplianceChecker: def __init__(self, data: ComplianceCheckRequest): self.data = data - self.guardrails = data.guardrail_information or [] + self.guardrails = tuple(g for g in data.guardrail_information or () if g.get("guardrail_status") != "not_run") def _get_guardrails_by_mode(self, mode: str) -> list[dict]: """ diff --git a/litellm/proxy/db/health_check_latest.py b/litellm/proxy/db/health_check_latest.py index 35bc838379c..21438f095bb 100644 --- a/litellm/proxy/db/health_check_latest.py +++ b/litellm/proxy/db/health_check_latest.py @@ -74,10 +74,14 @@ class LatestHealthCheckRow(BaseModel): _ROWS_ADAPTER: Final = TypeAdapter(tuple[LatestHealthCheckRow, ...]) +async def query_latest_health_checks(prisma_client: PrismaClient) -> tuple[LatestHealthCheckRow, ...]: + rows: Final = await prisma_client.db.query_raw(LATEST_HEALTH_CHECKS_SQL) + return _ROWS_ADAPTER.validate_python(rows) + + async def fetch_latest_health_checks(prisma_client: PrismaClient) -> tuple[LatestHealthCheckRow, ...]: try: - rows: Final = await prisma_client.db.query_raw(LATEST_HEALTH_CHECKS_SQL) - return _ROWS_ADAPTER.validate_python(rows) + return await query_latest_health_checks(prisma_client) except Exception as query_err: # noqa: BLE001 # health decorates other reads; a driver error must not fail them verbose_proxy_logger.error("Error getting all latest health checks: %s", query_err) return () diff --git a/litellm/proxy/db/spend_log_tool_index.py b/litellm/proxy/db/spend_log_tool_index.py index 93bbc567430..c01fe15fc09 100644 --- a/litellm/proxy/db/spend_log_tool_index.py +++ b/litellm/proxy/db/spend_log_tool_index.py @@ -5,8 +5,10 @@ At request time the spend writer builds one ToolUsageTransaction per request tha invoked tools (MCP namespaced tool name plus response tool_calls; declared-but-not- invoked tools are excluded) and queues it on the prisma client. The spend-log flush job drains the queue into LiteLLM_SpendLogToolIndex (per-request drill-down) and -LiteLLM_DailyToolSpend (the per-day rollup the Cost Optimization card reads) in a -single transaction, so a failed flush never leaves a partial rollup increment. +LiteLLM_DailyToolSpend (the per-day rollup the Cost Optimization card reads). The +index rows are keyed on (request_id, tool_name) and written with skip_duplicates, +so they go out as bounded standalone statements; every rollup upsert stays in one +transaction, so a failed flush never leaves a partial rollup increment. """ from __future__ import annotations @@ -19,7 +21,10 @@ from datetime import datetime, timezone from itertools import groupby from typing import TYPE_CHECKING, Any, Final +from litellm.constants import SPEND_LOG_WRITE_BATCH_MAX_BYTES, SPEND_LOG_WRITE_BATCH_MAX_ROWS from litellm.proxy._types import DB_RETRY_SAFE_ERROR_TYPES +from litellm.proxy.db.spend_log_batching import spend_log_write_batches +from litellm.repositories.table_repositories import SpendLogToolIndexRepository if TYPE_CHECKING: from litellm.proxy.utils import PrismaClient @@ -98,14 +103,19 @@ async def flush_tool_usage_transactions( transactions: Sequence[ToolUsageTransaction], n_retry_times: int = 3, ) -> None: - """Write index rows and rollup upserts for a drained queue batch in one - transaction. Retries only ConnectError, the one failure that proves the - statements never reached the database. Post-send failures (Read timeouts - and errors) are ambiguous and are NOT retried: the engine can abandon the - transaction open on the pooled connection, so a retry's statements stack - into the same transaction and one commit applies both increment sets. - Ambiguous failures drop the batch; the caller logs it at error. Callers - must not add their own retry around this function.""" + """Write the index rows as bounded standalone statements, then every rollup + upsert for the drained queue batch in one transaction. One flush fans out to + transactions x tools index rows, so the index write is split by the spend-log + statement budgets; a split inside ``batch_()`` would not help, since the + batcher ships every queued statement to the query engine as one payload. + Retries only ConnectError, the one failure that proves the statements never + reached the database; replayed index rows are no-ops under skip_duplicates. + Post-send failures (Read timeouts and errors) are ambiguous and are NOT + retried: the engine can abandon the transaction open on the pooled + connection, so a retry's statements stack into the same transaction and one + commit applies both increment sets. Ambiguous failures drop the batch; the + caller logs it at error. Callers must not add their own retry around this + function.""" if not transactions: return @@ -119,10 +129,14 @@ async def flush_tool_usage_transactions( key=lambda entry: (entry[0], entry[1]), ) + index_table: Final = SpendLogToolIndexRepository(prisma_client).table for attempt in range(n_retry_times + 1): try: + for statement_rows in spend_log_write_batches( + index_rows, SPEND_LOG_WRITE_BATCH_MAX_BYTES, SPEND_LOG_WRITE_BATCH_MAX_ROWS + ): + await index_table.create_many(data=statement_rows, skip_duplicates=True) async with prisma_client.db.batch_() as batcher: - batcher.litellm_spendlogtoolindex.create_many(data=index_rows, skip_duplicates=True) for (date_key, tool_name), grouped in groupby(per_tool_day, key=lambda entry: (entry[0], entry[1])): entries = tuple(grouped) spend = sum(entry[2] for entry in entries) diff --git a/litellm/proxy/discovery_endpoints/__init__.py b/litellm/proxy/discovery_endpoints/__init__.py index a6401c2f1b4..52602f30b77 100644 --- a/litellm/proxy/discovery_endpoints/__init__.py +++ b/litellm/proxy/discovery_endpoints/__init__.py @@ -1,3 +1,4 @@ +from .agent_skills_endpoints import router as agent_skills_discovery_router from .ui_discovery_endpoints import router as ui_discovery_endpoints_router -__all__ = ["ui_discovery_endpoints_router"] +__all__ = ["agent_skills_discovery_router", "ui_discovery_endpoints_router"] diff --git a/litellm/proxy/discovery_endpoints/agent_skills_archive.py b/litellm/proxy/discovery_endpoints/agent_skills_archive.py new file mode 100644 index 00000000000..1f2fca3992e --- /dev/null +++ b/litellm/proxy/discovery_endpoints/agent_skills_archive.py @@ -0,0 +1,130 @@ +"""Repack a stored skill upload into the archive shape Agent Skills clients install from. + +Uploads follow the Anthropic Skills API layout, where every file sits under a single +top-level folder. Discovery clients read ``SKILL.md`` from the archive root, so that +folder is stripped and the zip is rebuilt with fixed entry timestamps, which keeps the +SHA-256 digest published in the index reproducible for identical uploads. +""" + +import hashlib +import io +import re +import zipfile +from collections.abc import Mapping +from dataclasses import dataclass +from types import MappingProxyType +from typing import Final + +import yaml + +MAX_ARCHIVE_UNPACKED_BYTES: Final = 50 * 1024 * 1024 +MAX_ARCHIVE_ENTRIES: Final = 1000 +SKILL_MANIFEST_FILENAME: Final = "SKILL.md" + +_ZIP_ENTRY_TIMESTAMP: Final = (1980, 1, 1, 0, 0, 0) +_ZIP_ENTRY_PERMISSIONS: Final = 0o644 << 16 +_FRONTMATTER_PATTERN: Final = re.compile(r"^---\s*\n(.*?)\n---\s*(?:\n|$)", re.DOTALL) +_WINDOWS_DRIVE_PATTERN: Final = re.compile(r"^[A-Za-z]:") +_EMPTY_FRONTMATTER: Final[Mapping[str, object]] = MappingProxyType({}) + + +@dataclass(frozen=True, slots=True) +class SkillArchive: + content: bytes + digest: str + declared_name: str | None + declared_description: str | None + + +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 + + 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) + return SkillArchive( + content=content, + digest=f"sha256:{hashlib.sha256(content).hexdigest()}", + declared_name=_frontmatter_text(frontmatter, "name"), + declared_description=_frontmatter_text(frontmatter, "description"), + ) + + +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()) + 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) + 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): + return None + + return tuple((name, uploaded.read(info)) for info, name in sorted(flattened, key=lambda member: member[1])) + + +def _common_root_prefix(paths: tuple[str, ...]) -> str: + roots: Final = frozenset(path.split("/", 1)[0] for path in paths) + if len(roots) != 1 or not all("/" in path for path in paths): + return "" + return f"{next(iter(roots))}/" + + +def _normalized_path(raw_path: str) -> str | None: + if not raw_path or "\0" in raw_path or "\\" in raw_path: + return None + if raw_path.startswith("/") or _WINDOWS_DRIVE_PATTERN.match(raw_path): + return None + parts: Final = tuple(part for part in raw_path.split("/") if part) + if not parts or any(part in (".", "..") for part in parts): + return None + return "/".join(parts) + + +def _manifest_frontmatter(manifest: bytes) -> Mapping[str, object]: + match: Final = _FRONTMATTER_PATTERN.match(manifest.decode("utf-8", errors="replace")) + if match is None: + return _EMPTY_FRONTMATTER + try: + parsed: Final = yaml.safe_load(match.group(1)) + except yaml.YAMLError: + return _EMPTY_FRONTMATTER + if not isinstance(parsed, dict): + return _EMPTY_FRONTMATTER + return parsed + + +def _frontmatter_text(frontmatter: Mapping[str, object], key: str) -> str | None: + value: Final = frontmatter.get(key) + if not isinstance(value, str): + return None + return value.strip() or None + + +def _zip_entry(name: str) -> 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 + return entry + + +def _repack(members: tuple[tuple[str, bytes], ...]) -> 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) + return buffer.getvalue() diff --git a/litellm/proxy/discovery_endpoints/agent_skills_endpoints.py b/litellm/proxy/discovery_endpoints/agent_skills_endpoints.py new file mode 100644 index 00000000000..3084cbfd84f --- /dev/null +++ b/litellm/proxy/discovery_endpoints/agent_skills_endpoints.py @@ -0,0 +1,200 @@ +"""Serve skills stored on the proxy as an Agent Skills well-known discovery index. + +``npx skills add -a `` reads ``/.well-known/agent-skills/index.json`` +and downloads each entry's archive. Discovery clients send no credentials, so both +routes are unauthenticated and stay off until ``litellm_settings.public_skills_index`` +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 operator import itemgetter +from types import MappingProxyType +from typing import Final + +from fastapi import APIRouter, Depends, HTTPException, Request, Response + +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.discovery_endpoints.agent_skills_archive import SkillArchive, build_skill_archive +from litellm.types.proxy.discovery_endpoints.agent_skills_endpoints import ( + MAX_SKILL_DESCRIPTION_LENGTH, + MAX_SKILL_NAME_LENGTH, + AgentSkillsIndex, + AgentSkillsIndexEntry, +) + +MAX_INDEXED_SKILLS: Final = 1000 +MAX_CACHED_ARCHIVES: Final = 128 +MAX_CACHED_ARCHIVE_BYTES: Final = 512 * 1024 +ARCHIVE_CACHE_TTL_SECONDS: Final = 3600 + +_ARCHIVE_CACHE: Final = InMemoryCache( + max_size_in_memory=MAX_CACHED_ARCHIVES, + default_ttl=ARCHIVE_CACHE_TTL_SECONDS, + max_size_per_item=MAX_CACHED_ARCHIVE_BYTES // 1024, +) + +_NON_SLUG_PATTERN: Final = re.compile(r"[^a-z0-9]+") +_FALLBACK_SKILL_NAME: Final = "skill" + +router: Final = APIRouter(tags=["public", "skills"]) # mutable-ok: fastapi types tags as list[str | Enum] + + +class ZipArchiveResponse(Response): + """Response whose OpenAPI entry declares an application/zip download rather than JSON.""" + + media_type = "application/zip" + + +def ensure_index_enabled() -> None: + if litellm.public_skills_index is not True: + raise HTTPException(status_code=404, detail="Not Found") + + +async def stored_skills() -> Sequence[LiteLLM_SkillsTable]: + from litellm.llms.litellm_proxy.skills.handler import LiteLLMSkillsHandler + + return await LiteLLMSkillsHandler.list_skills(limit=MAX_INDEXED_SKILLS) + + +async def stored_skill(skill_id: str) -> LiteLLM_SkillsTable | None: + from litellm.llms.litellm_proxy.skills.handler import LiteLLMSkillsHandler + + try: + return await LiteLLMSkillsHandler.get_skill(skill_id) + except ValueError: + return None + + +@router.get( + "/.well-known/agent-skills/index.json", + response_model=AgentSkillsIndex, + dependencies=(Depends(ensure_index_enabled),), +) +@router.get( + "/.well-known/skills/index.json", + response_model=AgentSkillsIndex, + dependencies=(Depends(ensure_index_enabled),), + include_in_schema=False, +) +async def agent_skills_index( + request: Request, + skills: Sequence[LiteLLM_SkillsTable] = Depends(stored_skills), +) -> AgentSkillsIndex: + """Agent Skills v0.2.0 discovery index over every skill stored on this proxy.""" + from litellm.proxy.utils import get_custom_url + + installable: Final = await _installable(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) + ) + ) + + +@router.get( + "/v1/skills/{skill_id}/archive", + dependencies=(Depends(ensure_index_enabled),), + response_class=ZipArchiveResponse, +) +async def agent_skills_archive( + skill_id: str, + skill: LiteLLM_SkillsTable | None = Depends(stored_skill), +) -> ZipArchiveResponse: + """Stored skill upload, repacked so SKILL.md sits at the archive root.""" + archive: Final = await _archive_for(skill) if skill is not None else None + if archive is None: + raise HTTPException(status_code=404, detail=f"No installable skill archive for: {skill_id}") + + return ZipArchiveResponse( + content=archive.content, + headers=MappingProxyType({"Content-Disposition": f'attachment; filename="{skill_id}.zip"'}), + ) + + +async def _installable( + skills: Sequence[LiteLLM_SkillsTable], +) -> tuple[tuple[LiteLLM_SkillsTable, SkillArchive], ...]: + built: Final = tuple([(skill, await _archive_for(skill)) for skill in reversed(skills)]) + return tuple((skill, archive) for skill, archive in built if archive is not None) + + +async def _archive_for(skill: LiteLLM_SkillsTable) -> SkillArchive | None: + if skill.file_content is None: + return None + + cache_key: Final = None if skill.updated_at is None else f"{skill.skill_id}:{skill.updated_at.isoformat()}" + cached: Final = None if cache_key is None else _ARCHIVE_CACHE.get_cache(cache_key) + if isinstance(cached, SkillArchive): + return cached + + archive: Final = await asyncio.to_thread(build_skill_archive, skill.file_content) + if archive is None: + verbose_proxy_logger.warning( + "Agent Skills index: skipping skill %s, its upload is not a zip holding SKILL.md at the root of a " + "single top-level folder", + skill.skill_id, + ) + return None + + if cache_key is not None and len(archive.content) <= MAX_CACHED_ARCHIVE_BYTES: + _ARCHIVE_CACHE.set_cache(cache_key, archive) + return archive + + +def _base_name(skill: LiteLLM_SkillsTable, archive: SkillArchive) -> str: + candidates: Final = (archive.declared_name, skill.display_title, skill.skill_id) + return next( + (slug for slug in (_slugify(candidate) for candidate in candidates) if slug is not None), + _FALLBACK_SKILL_NAME, + ) + + +def _slugify(raw: str | None) -> str | None: + if raw is None: + return None + return _NON_SLUG_PATTERN.sub("-", raw.lower()).strip("-")[:MAX_SKILL_NAME_LENGTH].rstrip("-") or None + + +def _deduplicated(names: Sequence[str]) -> tuple[str, ...]: + ordinals: Final = MappingProxyType( + { + position: ordinal + for _, duplicates in groupby(sorted(enumerate(names), key=itemgetter(1)), key=itemgetter(1)) + for ordinal, (position, _) in enumerate(duplicates) + } + ) + return tuple(_with_ordinal(name, ordinals[position]) for position, name in enumerate(names)) + + +def _with_ordinal(name: str, ordinal: int) -> str: + if ordinal == 0: + return name + suffix: Final = f"-{ordinal + 1}" + return f"{name[: MAX_SKILL_NAME_LENGTH - len(suffix)].rstrip('-')}{suffix}" + + +def _description(skill: LiteLLM_SkillsTable, archive: SkillArchive, name: str) -> str: + candidates: Final = (archive.declared_description, skill.description, skill.display_title) + chosen: Final = next( + (candidate.strip() for candidate in candidates if candidate is not None and candidate.strip()), + name, + ) + return chosen[:MAX_SKILL_DESCRIPTION_LENGTH] diff --git a/litellm/proxy/discovery_endpoints/ui_discovery_endpoints.py b/litellm/proxy/discovery_endpoints/ui_discovery_endpoints.py index c2053693f2e..8b042d18cd0 100644 --- a/litellm/proxy/discovery_endpoints/ui_discovery_endpoints.py +++ b/litellm/proxy/discovery_endpoints/ui_discovery_endpoints.py @@ -4,6 +4,7 @@ from typing import Final from fastapi import APIRouter +from litellm.proxy.common_utils.html_forms.default_credentials_hint import should_hide_default_credentials_hint from litellm.types.proxy.discovery_endpoints.ui_discovery_endpoints import ( UiDiscoveryEndpoints, ) @@ -23,10 +24,7 @@ async def get_ui_config(): or general_settings.get("auto_redirect_ui_login_to_sso", False) is True ) admin_ui_disabled: Final = os.getenv("DISABLE_ADMIN_UI", "false").lower() == "true" - hide_default_credentials_hint: Final = bool( - os.getenv("LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", "false").lower() == "true" - or general_settings.get("hide_default_credentials_hint", False) is True - ) + hide_default_credentials_hint: Final = should_hide_default_credentials_hint(general_settings) sso_configured: Final = has_user_setup_sso() diff --git a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py index 6a7ac4361b9..2c407d91a48 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py +++ b/litellm/proxy/guardrails/guardrail_hooks/bedrock_guardrails.py @@ -244,6 +244,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): prompt_attack_threshold: float | None = 0.5, pii_confidence_threshold: float | None = 0.5, chunk_budget_chars: int = BEDROCK_APPLY_GUARDRAIL_CHUNK_BUDGET_CHARS, + contextual_grounding_from_messages: bool = False, streaming_buffer_until_moderated: bool | None = None, streaming_sampling_rate: int | None = None, streaming_end_of_stream_only: bool | None = None, @@ -265,6 +266,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): self.guardrailVersion = guardrailVersion self.guardrail_provider = "bedrock" self.chunk_budget_chars = chunk_budget_chars + self.contextual_grounding_from_messages = contextual_grounding_from_messages self.experimental_use_latest_role_message_only = bool(kwargs.get("experimental_use_latest_role_message_only")) # Resource-less, detect-only InvokeGuardrailChecks mode. Present `checks` @@ -459,8 +461,8 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): """ Flatten a message into text blocks, preserving any contextual-grounding qualifier carried by the content-block ``type`` (grounding_source / query). - Untagged text keeps ``qualifier=None`` so the payload is unchanged for - callers that do not use grounding. + Untagged text keeps ``qualifier=None``; the OUTPUT scan decides whether to + derive grounding qualifiers from it. """ content: Final = message.get("content") if content is None: @@ -493,6 +495,10 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): result carrying externally-influenced content can supply fake evidence for the contextual-grounding check to grade the response against. ``query`` is accepted from any role (it is the user's question). + + With ``contextual_grounding_from_messages`` on, a request with no tagged blocks + falls back to the plain messages: system / developer text is the grounding + source and the latest user message is the query. """ grounding: Final[list[QualifiedTextBlock]] = [] for message in messages or []: @@ -504,7 +510,33 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): and role in _GROUNDING_SOURCE_TRUSTED_ROLES ): grounding.append(block) - return grounding + if grounding or not self.contextual_grounding_from_messages: + return grounding + return self._derive_grounding_blocks_from_plain_messages(messages) + + def _derive_grounding_blocks_from_plain_messages( + self, messages: list[AllMessageValues] | None + ) -> list[QualifiedTextBlock]: + if not messages: + return [] + latest_user_index: Final = self._find_latest_message_index(messages, target_role="user") + if latest_user_index is None: + return [] + sources: Final = tuple( + QualifiedTextBlock(text=block.text, qualifier="grounding_source") + for message in messages + if message.get("role") in _GROUNDING_SOURCE_TRUSTED_ROLES + for block in self.get_content_items_for_message(message=message) or [] + if block.text + ) + queries: Final = tuple( + QualifiedTextBlock(text=block.text, qualifier="query") + for block in self.get_content_items_for_message(message=messages[latest_user_index]) or [] + if block.text + ) + if not sources or not queries: + return [] + return [*sources, *queries] def supports_scan_only_tool_results(self) -> bool: return self.experimental_use_latest_role_message_only is not True @@ -3210,6 +3242,7 @@ class BedrockGuardrail(CustomGuardrail, BaseAWSLLM): bedrock_response = await self.make_bedrock_api_request( source="OUTPUT", response=synthetic_response, + messages=request_data.get("messages"), request_data=request_data, logging_event_type=_log_hook, ) diff --git a/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py b/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py index d8296003ae9..3d1a173635e 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py +++ b/litellm/proxy/guardrails/guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py @@ -7,7 +7,7 @@ import fnmatch import os -from collections.abc import Mapping +from collections.abc import Mapping, Sequence from typing import TYPE_CHECKING, Any, Final, Literal, Optional import httpx @@ -24,7 +24,7 @@ from litellm.llms.custom_httpx.http_handler import ( httpxSpecialProvider, ) from litellm.types.guardrails import GuardrailEventHooks -from litellm.types.llms.openai import ChatCompletionToolParam +from litellm.types.llms.openai import AllMessageValues, ChatCompletionToolParam from litellm.types.proxy.guardrails.guardrail_hooks.generic_guardrail_api import ( GenericGuardrailAPIMetadata, GenericGuardrailAPIRequest, @@ -150,6 +150,26 @@ def _extract_inbound_headers( return None +def _structured_rows_to_write_back( + original_rows: Sequence[AllMessageValues] | None, + shown_rows: Sequence[AllMessageValues] | None, + returned_rows: Sequence[AllMessageValues], +) -> tuple[AllMessageValues, ...] | None: + """The request model drops row keys its message types do not declare, so a + row the server echoes back verbatim is restored to the original row object. + A server that echoes every row back unchanged has not rewritten anything + per row, so its answer is read from texts, as it was before rows could be + returned at all.""" + if original_rows is None or shown_rows is None or len(returned_rows) != len(original_rows): + return tuple(returned_rows) + if all(returned == shown for shown, returned in zip(shown_rows, returned_rows)): + return None + return tuple( + original if returned == shown else returned + for original, shown, returned in zip(original_rows, shown_rows, returned_rows) + ) + + class GenericGuardrailAPI(CustomGuardrail): """ Generic Guardrail API integration for LiteLLM. @@ -322,6 +342,8 @@ class GenericGuardrailAPI(CustomGuardrail): texts: list, images: list[str] | None, tools: list[ChatCompletionToolParam] | None, + structured_messages: Sequence[AllMessageValues] | None, + shown_messages: Sequence[AllMessageValues] | None, guardrail_response: GenericGuardrailAPIResponse, ) -> GenericGuardrailAPIInputs: # Action is NONE or no modifications needed @@ -336,6 +358,13 @@ class GenericGuardrailAPI(CustomGuardrail): return_inputs["tools"] = guardrail_response.tools elif tools: return_inputs["tools"] = tools + rows_to_write_back: Final = ( + _structured_rows_to_write_back(structured_messages, shown_messages, guardrail_response.structured_messages) + if guardrail_response.structured_messages + else None + ) + if rows_to_write_back is not None: + return_inputs["structured_messages"] = list(rows_to_write_back) # mutable-ok: guardrail inputs take a list if guardrail_response.stream_holdback_chars is not None: return_inputs["stream_holdback_chars"] = guardrail_response.stream_holdback_chars return return_inputs @@ -473,6 +502,8 @@ class GenericGuardrailAPI(CustomGuardrail): texts=texts, images=images, tools=tools, + structured_messages=structured_messages, + shown_messages=guardrail_request.structured_messages, guardrail_response=guardrail_response, ) diff --git a/litellm/proxy/guardrails/guardrail_hooks/javelin/javelin.py b/litellm/proxy/guardrails/guardrail_hooks/javelin/javelin.py index 3e5d8fb311d..e54e07b6a1b 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/javelin/javelin.py +++ b/litellm/proxy/guardrails/guardrail_hooks/javelin/javelin.py @@ -44,7 +44,7 @@ class JavelinGuardrail(CustomGuardrail): application: str | None = None, **kwargs, ): - f""" + """ Initialize the JavelinGuardrail class. This calls: {api_base}/{api_version}/guardrail/{guardrail_name}/apply diff --git a/litellm/proxy/guardrails/guardrail_hooks/mcp_end_user_permission/__init__.py b/litellm/proxy/guardrails/guardrail_hooks/mcp_end_user_permission/__init__.py index a911c78ddc3..95db4bd4f77 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/mcp_end_user_permission/__init__.py +++ b/litellm/proxy/guardrails/guardrail_hooks/mcp_end_user_permission/__init__.py @@ -15,7 +15,7 @@ def initialize_guardrail(litellm_params: "LitellmParams", guardrail: "Guardrail" # We check the raw guardrail dict because LitellmParams normalizes None → False, # making it impossible to distinguish "not set" from "explicitly false" via litellm_params. _raw_default_on: Final = cast(dict[str, Any], guardrail).get("litellm_params", {}).get("default_on") - _default_on: Final = False if _raw_default_on is False else True + _default_on: Final = _raw_default_on is not False _callback: Final = MCPEndUserPermissionGuardrail( guardrail_name=guardrail.get("guardrail_name", ""), diff --git a/litellm/proxy/guardrails/guardrail_hooks/model_armor/model_armor.py b/litellm/proxy/guardrails/guardrail_hooks/model_armor/model_armor.py index fde40111d49..a7c93e63b32 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/model_armor/model_armor.py +++ b/litellm/proxy/guardrails/guardrail_hooks/model_armor/model_armor.py @@ -1,11 +1,13 @@ -from collections.abc import AsyncGenerator, Mapping, Sequence +import time +from collections.abc import AsyncGenerator, Awaitable, Callable, Mapping, Sequence from enum import Enum, auto -from typing import TYPE_CHECKING, Any, Final, Literal +from typing import TYPE_CHECKING, Any, ClassVar, Final, Literal import httpx from fastapi import HTTPException if TYPE_CHECKING: + from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.types.proxy.guardrails.guardrail_hooks.base import GuardrailConfigModel import json @@ -23,6 +25,7 @@ from litellm.litellm_core_utils.core_helpers import ( get_or_create_metadata_bucket, ) from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, get_async_httpx_client, httpxSpecialProvider, ) @@ -52,6 +55,7 @@ from litellm.types.utils import ( CallTypes, CallTypesLiteral, Choices, + GenericGuardrailAPIInputs, GuardrailStatus, ModelResponse, ModelResponseStream, @@ -118,8 +122,12 @@ class ModelArmorGuardrail(CustomGuardrail, VertexBase): Supports: - Pre-call sanitization (sanitizeUserPrompt) - Post-call sanitization (sanitizeModelResponse) + - logging_only: scans the completed response after it reaches the client and + records the verdict in spend logs without blocking """ + use_native_lifecycle_hooks: ClassVar[bool] = True + @classmethod def get_supported_event_hooks(cls) -> list[GuardrailEventHooks]: return [ @@ -128,6 +136,7 @@ class ModelArmorGuardrail(CustomGuardrail, VertexBase): GuardrailEventHooks.post_call, GuardrailEventHooks.pre_mcp_call, GuardrailEventHooks.during_mcp_call, + GuardrailEventHooks.logging_only, ] def __init__( @@ -138,6 +147,8 @@ class ModelArmorGuardrail(CustomGuardrail, VertexBase): credentials: VERTEX_CREDENTIALS_TYPES | None = None, api_endpoint: str | None = None, sanitize_error_detail: "bool | None" = True, + async_handler: AsyncHTTPHandler | None = None, + access_token_provider: Callable[[], Awaitable[tuple[str, str]]] | None = None, **kwargs, ): # Set supported event hooks if not already provided @@ -154,7 +165,10 @@ class ModelArmorGuardrail(CustomGuardrail, VertexBase): VertexBase.__init__(self) # Then set our attributes (this ensures project_id is not overwritten) - self.async_handler = get_async_httpx_client(llm_provider=httpxSpecialProvider.GuardrailCallback) + self.async_handler = async_handler or get_async_httpx_client( + llm_provider=httpxSpecialProvider.GuardrailCallback + ) + self.access_token_provider = access_token_provider self.template_id = template_id self.project_id = project_id self.location = location or "us-central1" @@ -278,11 +292,14 @@ class ModelArmorGuardrail(CustomGuardrail, VertexBase): If file_bytes and file_type are provided, file prompt sanitization is performed. """ # Get access token using VertexBase auth - access_token, resolved_project_id = await self._ensure_access_token_async( - credentials=self.credentials, - project_id=self.project_id, - custom_llm_provider="vertex_ai", - ) + if self.access_token_provider is not None: + access_token, resolved_project_id = await self.access_token_provider() + else: + access_token, resolved_project_id = await self._ensure_access_token_async( + credentials=self.credentials, + project_id=self.project_id, + custom_llm_provider="vertex_ai", + ) # Use resolved project ID if not explicitly set if not self.project_id and resolved_project_id: @@ -1096,6 +1113,11 @@ class ModelArmorGuardrail(CustomGuardrail, VertexBase): add_guardrail_to_applied_guardrails_header, ) + if self.should_run_guardrail(data=request_data, event_type=GuardrailEventHooks.post_call) is not True: + async for chunk in response: + yield chunk + return + all_chunks: Final[Sequence[object]] = tuple([chunk async for chunk in response]) if not all_chunks or self._is_terminal_error_stream(all_chunks): @@ -1213,6 +1235,60 @@ class ModelArmorGuardrail(CustomGuardrail, VertexBase): for chunk in all_chunks: yield chunk + @log_guardrail_information + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict, + input_type: Literal["request", "response"], + logging_obj: "LiteLLMLoggingObj | None" = None, + ) -> GenericGuardrailAPIInputs: + content: Final = "\n".join(text for text in inputs.get("texts") or () if text) + if not content: + return inputs + + source: Final[Literal["user_prompt", "model_response"]] = ( + "user_prompt" if input_type == "request" else "model_response" + ) + start_time: Final = time.time() + try: + armor_response: Final = await self.make_model_armor_request( + content=content, source=source, request_data=request_data + ) + except (ModelArmorAPIError, httpx.HTTPError) as e: + error_end_time: Final = time.time() + self.add_standard_logging_guardrail_information_to_request_data( + guardrail_json_response=str(e), + request_data=request_data, + guardrail_status="guardrail_failed_to_respond", + guardrail_provider="model_armor", + start_time=start_time, + end_time=error_end_time, + duration=error_end_time - start_time, + ) + return inputs + + flagged: Final = self._should_block_content(armor_response, allow_sanitization=False) + end_time: Final = time.time() + self.add_standard_logging_guardrail_information_to_request_data( + guardrail_json_response=self._build_logging_response(armor_response), + request_data=request_data, + guardrail_status="guardrail_flagged" if flagged else "success", + guardrail_provider="model_armor", + start_time=start_time, + end_time=end_time, + duration=end_time - start_time, + ) + if flagged and not self._event_hook_is_event_type(GuardrailEventHooks.logging_only): + raise HTTPException( + status_code=400, + detail=self._build_block_error_detail( + "Response blocked by Model Armor" if input_type == "response" else "Content blocked by Model Armor", + armor_response, + ), + ) + return inputs + @staticmethod def get_config_model() -> type["GuardrailConfigModel"] | None: """ diff --git a/litellm/proxy/guardrails/guardrail_hooks/panw_prisma_airs/panw_prisma_airs.py b/litellm/proxy/guardrails/guardrail_hooks/panw_prisma_airs/panw_prisma_airs.py index 3bc0dfabefc..9002e2aea07 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/panw_prisma_airs/panw_prisma_airs.py +++ b/litellm/proxy/guardrails/guardrail_hooks/panw_prisma_airs/panw_prisma_airs.py @@ -1600,8 +1600,8 @@ class PanwPrismaAirsHandler(CustomGuardrail): Args: texts: Flattened text entries from the framework. - messages: Original request messages (request_data["messages"]), - NOT structured_messages (which may have injected system content). + messages: The structured messages the framework flattened into ``texts``, + hoisted top-level system prompt included, so positions line up. Returns a set of scannable indices, or None on count mismatch or no user/developer message (safety fallback to existing role-filter behavior). @@ -1788,15 +1788,10 @@ class PanwPrismaAirsHandler(CustomGuardrail): structured_messages: Final = inputs.get("structured_messages") if structured_messages: # For Anthropic /v1/messages: default to latest-user-only scanning. - # Uses request_data["messages"] (original format), NOT structured_messages - # (which has injected system content from adapter translation). if self._use_latest_user_only(request_data, logging_obj): - original_messages: Final = request_data.get("messages") - if original_messages: - scannable_indices = self._get_latest_user_text_indices(texts, original_messages) + scannable_indices = self._get_latest_user_text_indices(texts, structured_messages) # Fall through to existing role filtering if: # - not Anthropic, OR flag explicitly False, OR - # - no original messages, OR # - latest-user extraction returned None (no user / count mismatch) if scannable_indices is None: scannable_indices = self._get_scannable_text_indices(texts, structured_messages) diff --git a/litellm/proxy/guardrails/guardrail_hooks/prompt_security/prompt_security.py b/litellm/proxy/guardrails/guardrail_hooks/prompt_security/prompt_security.py index 0954fe1698a..7e43566f224 100644 --- a/litellm/proxy/guardrails/guardrail_hooks/prompt_security/prompt_security.py +++ b/litellm/proxy/guardrails/guardrail_hooks/prompt_security/prompt_security.py @@ -2,6 +2,7 @@ import asyncio import base64 import os from collections.abc import Mapping, Sequence +from types import MappingProxyType from typing import TYPE_CHECKING, Final, Literal, Optional import httpx @@ -14,11 +15,13 @@ from litellm.integrations.custom_guardrail import ( CustomGuardrail, log_guardrail_information, ) +from litellm.llms.base_llm.guardrail_translation.utils import message_slot_texts, message_with_slot_texts from litellm.llms.custom_httpx.http_handler import ( get_async_httpx_client, httpxSpecialProvider, ) from litellm.types.guardrails import GuardrailEventHooks +from litellm.types.llms.openai import AllMessageValues from litellm.types.utils import GenericGuardrailAPIInputs if TYPE_CHECKING: @@ -27,12 +30,37 @@ if TYPE_CHECKING: _SANITIZE_FILE_FAIL_OPEN_TIMEOUT_SECONDS: Final = 30.0 +_SANITIZE_FILE_QUEUED_STATUSES: Final = frozenset({"created", "in progress"}) +_PROTECT_ROLES: Final = frozenset({"system", "user", "assistant"}) class PromptSecurityGuardrailMissingSecrets(Exception): pass +def _inputs_with_structured_messages( + inputs: GenericGuardrailAPIInputs, rewritten_messages: Sequence[AllMessageValues] | None +) -> GenericGuardrailAPIInputs: + if rewritten_messages is None: + return inputs + patched: Final[GenericGuardrailAPIInputs] = { + **inputs, + "structured_messages": list(rewritten_messages), # mutable-ok: the TypedDict field is declared as a list + } + return patched + + +def _inputs_with_modifications( + inputs: GenericGuardrailAPIInputs, + modified_texts: list[str], + rewritten_messages: Sequence[AllMessageValues] | None, +) -> GenericGuardrailAPIInputs: + if not modified_texts: + return _inputs_with_structured_messages(inputs, rewritten_messages) + with_texts: Final[GenericGuardrailAPIInputs] = {**inputs, "texts": modified_texts} + return _inputs_with_structured_messages(with_texts, rewritten_messages) + + class _ProtectVerdict(TypedDict, total=False): """One side (``prompt`` or ``response``) of an ``/api/protect`` verdict.""" @@ -275,14 +303,39 @@ class PromptSecurityGuardrail(CustomGuardrail): detail="Blocked by Prompt Security, Violations: " + ", ".join(violations), ) elif action == "modify": - # Extract modified texts from modified_messages modified_messages: Final = result.get("modified_messages", []) - modified_texts: Final = self._extract_texts_from_messages(modified_messages) - if modified_texts: - inputs["texts"] = modified_texts + return _inputs_with_modifications( + inputs, + self._extract_texts_from_messages(modified_messages), + self._structured_messages_with_modifications(structured_messages, modified_messages), + ) return inputs + def _is_sent_to_protect(self, message: Mapping[str, object]) -> bool: + return self.check_tool_results or message.get("role") in _PROTECT_ROLES + + def _structured_messages_with_modifications( + self, + structured_messages: Sequence[AllMessageValues], + modified_messages: Sequence[Mapping[str, object]], + ) -> tuple[AllMessageValues, ...] | None: + sent_indices: Final = tuple( + index for index, message in enumerate(structured_messages) if self._is_sent_to_protect(message) + ) + if not sent_indices or len(sent_indices) != len(modified_messages): + return None + rewritten: Final = tuple( + message_with_slot_texts(structured_messages[index], self._extract_texts_from_messages((modified,))) + for index, modified in zip(sent_indices, modified_messages) + ) + replacements: Final = MappingProxyType( + {index: message for index, message in zip(sent_indices, rewritten) if message is not None} + ) + if len(replacements) != len(sent_indices): + return None + return tuple(replacements.get(index, message) for index, message in enumerate(structured_messages)) + async def _apply_guardrail_on_response( self, inputs: GenericGuardrailAPIInputs, @@ -346,19 +399,7 @@ class PromptSecurityGuardrail(CustomGuardrail): return inputs def _extract_texts_from_messages(self, messages: Sequence[Mapping[str, object]]) -> list[str]: - """Extract text content from messages.""" - texts: Final = [] - for message in messages: - content = message.get("content") - if isinstance(content, str): - texts.append(content) - elif isinstance(content, list): - for item in content: - if isinstance(item, dict) and item.get("type") == "text": - text = item.get("text") - if text: - texts.append(text) - return texts + return [text for message in messages for text in message_slot_texts(message)] async def _process_standalone_images(self, images: list[str], user_api_key_alias: str | None) -> None: """Process standalone images from inputs (data URLs).""" @@ -512,16 +553,18 @@ class PromptSecurityGuardrail(CustomGuardrail): "metadata": result.get("metadata", {}), "violations": result.get("metadata", {}).get("violations", []), } - elif status == "in progress": - verbose_proxy_logger.debug( - "Prompt Security Guardrail: File sanitization in progress (attempt %d/%d)", - attempt + 1, - self.max_poll_attempts, - ) - continue - else: + + if status not in _SANITIZE_FILE_QUEUED_STATUSES: raise HTTPException(status_code=500, detail=f"Unexpected sanitization status: {status}") + verbose_proxy_logger.debug( + "Prompt Security Guardrail: File sanitization status=%s for jobId=%s (attempt %d/%d)", + status, + job_id, + attempt + 1, + self.max_poll_attempts, + ) + raise HTTPException(status_code=408, detail="File sanitization timeout") def _raise_if_file_blocked(self, sanitization_result: _SanitizeResult, resource_name: str) -> None: @@ -678,14 +721,13 @@ class PromptSecurityGuardrail(CustomGuardrail): This allows checking tool results for indirect prompt injection when enabled. """ - supported_roles: Final = ["system", "user", "assistant"] filtered_messages: Final = [] transformed_count = 0 filtered_count = 0 for message in messages: role = message.get("role", "") - if role in supported_roles: + if role in _PROTECT_ROLES: filtered_messages.append(message) else: if self.check_tool_results: diff --git a/litellm/proxy/guardrails/guardrail_initializers.py b/litellm/proxy/guardrails/guardrail_initializers.py index 16369abbfb0..7858adeb55d 100644 --- a/litellm/proxy/guardrails/guardrail_initializers.py +++ b/litellm/proxy/guardrails/guardrail_initializers.py @@ -23,6 +23,7 @@ def initialize_bedrock(litellm_params: LitellmParams, guardrail: Guardrail): prompt_attack_threshold=litellm_params.prompt_attack_threshold, pii_confidence_threshold=litellm_params.pii_confidence_threshold, chunk_budget_chars=litellm_params.chunk_budget_chars, + contextual_grounding_from_messages=litellm_params.contextual_grounding_from_messages, default_on=litellm_params.default_on, disable_exception_on_block=litellm_params.disable_exception_on_block, mask_request_content=litellm_params.mask_request_content, diff --git a/litellm/proxy/guardrails/usage_endpoints.py b/litellm/proxy/guardrails/usage_endpoints.py index 6259efb6654..556b6a4e919 100644 --- a/litellm/proxy/guardrails/usage_endpoints.py +++ b/litellm/proxy/guardrails/usage_endpoints.py @@ -42,7 +42,7 @@ if TYPE_CHECKING: router: Final = APIRouter() _EMPTY_UNITS: Final[Mapping[str, int]] = MappingProxyType({}) -_ACTION_SEVERITY: Final[Mapping[str, int]] = MappingProxyType({"passed": 0, "flagged": 1, "blocked": 2}) +_ACTION_SEVERITY: Final[Mapping[str, int]] = MappingProxyType({"not_run": 0, "passed": 1, "flagged": 2, "blocked": 3}) _T = TypeVar("_T") @@ -325,7 +325,7 @@ class UsageDetailResponse(BaseModel): class UsageLogEntry(BaseModel): id: str timestamp: str - action: str # blocked | passed | flagged + action: str # blocked | passed | flagged | not_run score: float | None latency_ms: float | None model: str | None diff --git a/litellm/proxy/guardrails/usage_tracking.py b/litellm/proxy/guardrails/usage_tracking.py index df967058cf0..7e11b69108b 100644 --- a/litellm/proxy/guardrails/usage_tracking.py +++ b/litellm/proxy/guardrails/usage_tracking.py @@ -17,8 +17,10 @@ from typing import TYPE_CHECKING, Any, Final, NamedTuple, TypeVar from typing_extensions import ReadOnly, TypedDict from litellm._logging import verbose_proxy_logger +from litellm.constants import SPEND_LOG_WRITE_BATCH_MAX_BYTES, SPEND_LOG_WRITE_BATCH_MAX_ROWS from litellm.litellm_core_utils.llm_cost_calc.guardrail_cost import billed_guardrail_cost_by_unit 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.table_repositories import ( DailyGuardrailMetricsRepository, @@ -191,10 +193,12 @@ async def _upsert_rows_with_retry( def guardrail_status_to_action(status: str | None) -> str: - """Map StandardLogging guardrail_status to blocked/passed/flagged.""" + """Map StandardLogging guardrail_status to blocked/passed/flagged/not_run.""" if not status: return "passed" s: Final = (status or "").lower() + if s == "not_run": + return "not_run" if "intervened" in s or "block" in s: return "blocked" if "flagged" in s or "fail" in s or "error" in s: @@ -352,37 +356,49 @@ async def process_spend_logs_guardrail_usage( "flagged_count": 0, } ) - index_rows: Final[list[dict[str, object]]] = [] + index_rows_by_key: Final[dict[tuple[str, str], dict[str, object]]] = {} for payload in logs_to_process: request_id = payload.get("request_id") start_time = _parse_payload_start_time(payload) - if not request_id or start_time is None: + if not isinstance(request_id, str) or not request_id or start_time is None: continue date_key = _date_str(start_time) - for entry in _parse_guardrail_info_from_payload(payload): - guardrail_id = entry.get("guardrail_id") or entry.get("guardrail_name") or "" - if not guardrail_id: + entries = _parse_guardrail_info_from_payload(payload) + ids_by_name = MappingProxyType( + { + e["guardrail_name"]: e["guardrail_id"] + for e in entries + if e.get("guardrail_id") and isinstance(e.get("guardrail_name"), str) and e["guardrail_name"] + } + ) + for entry in entries: + raw_name = entry.get("guardrail_name") + guardrail_name = raw_name if isinstance(raw_name, str) else "" + guardrail_id = entry.get("guardrail_id") or ids_by_name.get(guardrail_name) or guardrail_name + if not isinstance(guardrail_id, str) or not guardrail_id: continue - key = _MetricsKey(guardrail_id, date_key) - daily_guardrail[key]["requests_evaluated"] += 1 action = guardrail_status_to_action(entry.get("guardrail_status")) - if action == "passed": - daily_guardrail[key]["passed_count"] += 1 - elif action == "blocked": - daily_guardrail[key]["blocked_count"] += 1 - else: - daily_guardrail[key]["flagged_count"] += 1 + if action != "not_run": + key = _MetricsKey(guardrail_id, date_key) + daily_guardrail[key]["requests_evaluated"] += 1 + if action == "passed": + daily_guardrail[key]["passed_count"] += 1 + elif action == "blocked": + daily_guardrail[key]["blocked_count"] += 1 + else: + daily_guardrail[key]["flagged_count"] += 1 policy_id = entry.get("policy_id") - index_rows.append( - { + prior = index_rows_by_key.get((request_id, guardrail_id)) + if prior is None or (prior["policy_id"] is None and policy_id is not None): + index_rows_by_key[(request_id, guardrail_id)] = { "request_id": request_id, "guardrail_id": guardrail_id, "policy_id": policy_id, "start_time": start_time, } - ) + index_rows: Final = tuple(index_rows_by_key.values()) async with pending.lock: pending_metrics: Final = pending.metrics @@ -401,13 +417,12 @@ async def process_spend_logs_guardrail_usage( return try: - # Insert index rows (skip duplicates by request_id + guardrail_id) - if index_rows: + index_table: Final = SpendLogGuardrailIndexRepository(prisma_client).table + for statement_rows in spend_log_write_batches( + index_rows, SPEND_LOG_WRITE_BATCH_MAX_BYTES, SPEND_LOG_WRITE_BATCH_MAX_ROWS + ): try: - await SpendLogGuardrailIndexRepository(prisma_client).table.create_many( - data=index_rows, - skip_duplicates=True, - ) + await index_table.create_many(data=statement_rows, skip_duplicates=True) except Exception as e: verbose_proxy_logger.debug("Guardrail usage tracking: index create_many skipped: %s", e) diff --git a/litellm/proxy/health_endpoints/_health_endpoints.py b/litellm/proxy/health_endpoints/_health_endpoints.py index b9964c0e342..64fd59bbe44 100644 --- a/litellm/proxy/health_endpoints/_health_endpoints.py +++ b/litellm/proxy/health_endpoints/_health_endpoints.py @@ -45,7 +45,10 @@ from litellm.proxy.auth.auth_utils import ( from litellm.proxy.auth.model_checks import get_key_models from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.db.exception_handler import PrismaDBExceptionHandler -from litellm.proxy.db.health_check_latest import LatestHealthCheckRow +from litellm.proxy.db.health_check_latest import ( + LatestHealthCheckRow, + query_latest_health_checks, +) from litellm.proxy.db.proxy_worker_heartbeat import count_live_proxy_workers from litellm.proxy.health_check import ( ADMIN_ONLY_HEALTH_DISPLAY_PARAMS, @@ -443,6 +446,11 @@ async def health_services_endpoint( } return pointfive_health if service == "webhook": + if not _is_proxy_admin(user_api_key_dict): + webhook_non_admin_detail: Final[_ServiceTestErrorDetail] = { + "error": "Only proxy admins can trigger the webhook test alert." + } + raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail=webhook_non_admin_detail) user_info: Final = CallInfo( token=user_api_key_dict.token or "", spend=1, @@ -871,7 +879,7 @@ async def _save_background_health_checks_to_db( ) # Step 3: Get latest health checks for all models in one query to compare status - latest_checks: Final = await prisma_client.get_all_latest_health_checks() + latest_checks: Final = await query_latest_health_checks(prisma_client) latest_checks_map: Final = {} for check in latest_checks: # Use model_id as primary key, fallback to model_name diff --git a/litellm/proxy/hooks/__init__.py b/litellm/proxy/hooks/__init__.py index 8714dd5f3d2..f3542098f95 100644 --- a/litellm/proxy/hooks/__init__.py +++ b/litellm/proxy/hooks/__init__.py @@ -9,6 +9,7 @@ from .max_budget_per_session_limiter import _PROXY_MaxBudgetPerSessionHandler from .max_iterations_limiter import _PROXY_MaxIterationsHandler from .parallel_request_limiter import _PROXY_MaxParallelRequestsHandler from .parallel_request_limiter_v3 import _PROXY_MaxParallelRequestsHandler_v3 +from .prompt_cache_prediction import PromptCacheObserver from .responses_id_security import ResponsesIDSecurity from .sensitive_data_routing import _PROXY_SensitiveDataRoutingHandler @@ -25,6 +26,7 @@ PROXY_HOOKS: Final = { "max_iterations_limiter": _PROXY_MaxIterationsHandler, "max_budget_per_session_limiter": _PROXY_MaxBudgetPerSessionHandler, "sensitive_data_routing": _PROXY_SensitiveDataRoutingHandler, + "prompt_cache_prediction": PromptCacheObserver, } ## FEATURE FLAG HOOKS ## diff --git a/litellm/proxy/hooks/parallel_request_limiter_v3.py b/litellm/proxy/hooks/parallel_request_limiter_v3.py index c398abff099..a34dc99e472 100644 --- a/litellm/proxy/hooks/parallel_request_limiter_v3.py +++ b/litellm/proxy/hooks/parallel_request_limiter_v3.py @@ -9,10 +9,12 @@ import binascii import logging import os import uuid -from collections.abc import Awaitable, Callable, Mapping, Sequence, Set +from collections.abc import AsyncGenerator, Awaitable, Callable, Mapping, Sequence, Set +from contextlib import asynccontextmanager from contextvars import ContextVar from dataclasses import dataclass, field from datetime import datetime +from types import MappingProxyType from typing import ( TYPE_CHECKING, Any, @@ -23,6 +25,7 @@ from typing import ( TypedDict, ) +from pydantic import TypeAdapter from typing_extensions import NotRequired, ReadOnly from litellm import DualCache @@ -84,6 +87,9 @@ else: InternalUsageCache = Any +_REQUEST_RATE_LIMIT_DATA: Final = TypeAdapter(Mapping[str, object]) + + BATCH_RATE_LIMITER_SCRIPT: Final = """ local results = {} local now = tonumber(ARGV[1]) @@ -2673,12 +2679,7 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): Returns list of descriptors for API key, user, team, team member, end user, model-specific, agent, and agent-session limits. """ - from litellm.proxy.auth.auth_utils import ( - get_team_model_rpm_limit, - get_team_model_tpm_limit, - ) - - descriptors: Final = [] + descriptors: Final[list[RateLimitDescriptor]] = [] # mutable-ok: existing descriptor helpers append in place # API Key rate limits if user_api_key_dict.api_key and ( @@ -2803,34 +2804,11 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): descriptors=descriptors, ) - if ( - get_team_model_rpm_limit(user_api_key_dict) is not None - or get_team_model_tpm_limit(user_api_key_dict) is not None - ): - _tpm_limit_for_team_model: Final = get_team_model_tpm_limit(user_api_key_dict) or {} - _rpm_limit_for_team_model: Final = get_team_model_rpm_limit(user_api_key_dict) or {} - should_check_rate_limit = False - if requested_model in _tpm_limit_for_team_model or requested_model in _rpm_limit_for_team_model: - should_check_rate_limit = True - - if should_check_rate_limit: - model_specific_tpm_limit = None - model_specific_rpm_limit = None - if requested_model in _tpm_limit_for_team_model: - model_specific_tpm_limit = _tpm_limit_for_team_model[requested_model] - if requested_model in _rpm_limit_for_team_model: - model_specific_rpm_limit = _rpm_limit_for_team_model[requested_model] - descriptors.append( - RateLimitDescriptor( - key="model_per_team", - value=f"{user_api_key_dict.team_id}:{requested_model}", - rate_limit={ - "requests_per_unit": model_specific_rpm_limit, - "tokens_per_unit": model_specific_tpm_limit, - "window_size": self.window_size, - }, - ) - ) + self._add_team_model_rate_limit_descriptor_from_metadata( + user_api_key_dict=user_api_key_dict, + requested_model=requested_model if isinstance(requested_model, str) else None, + descriptors=descriptors, + ) # Agent-level and session-level rate limits resolved_agent_id: Final = self._get_resolved_agent_id(user_api_key_dict, data) @@ -3416,6 +3394,108 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): requested_model, ) + async def _build_request_rate_limit_descriptors( + self, + user_api_key_dict: UserAPIKeyAuth, + data: Mapping[str, object], + call_type: str | None, + ) -> list[RateLimitDescriptor]: # mutable-ok: the shared generation reservation helpers require a list + metadata: Final = _REQUEST_RATE_LIMIT_DATA.validate_python( + user_api_key_dict.metadata or MappingProxyType({}) # pyright: ignore[reportUnknownMemberType] # validates the legacy auth metadata boundary + ) + rpm_value: Final = metadata.get("rpm_limit_type") + tpm_value: Final = metadata.get("tpm_limit_type") + rpm_limit_type: Final = rpm_value if isinstance(rpm_value, str) else None + tpm_limit_type: Final = tpm_value if isinstance(tpm_value, str) else None + model_value: Final = data.get("model") + requested_model: Final = model_value if isinstance(model_value, str) else None + model_has_failures: Final = ( + await self._check_model_has_recent_failures( + model=requested_model, + parent_otel_span=user_api_key_dict.parent_otel_span, + ) + if requested_model and self._is_dynamic_rate_limiting_enabled(rpm_limit_type, tpm_limit_type) + else False + ) + descriptors: Final = self._create_rate_limit_descriptors( # pyright: ignore[reportUnknownMemberType] # legacy helper reads a dictionary with validated keys + user_api_key_dict=user_api_key_dict, + data=dict(data), # mutable-ok: legacy descriptor helpers accept a request dictionary + rpm_limit_type=rpm_limit_type, + tpm_limit_type=tpm_limit_type, + model_has_failures=model_has_failures, + call_type=call_type, + ) + self._add_project_model_rate_limit_descriptor_from_metadata( + user_api_key_dict=user_api_key_dict, + requested_model=requested_model, + descriptors=descriptors, + ) + self.add_project_io_token_rate_limit_descriptors_from_metadata( + user_api_key_dict=user_api_key_dict, + requested_model=requested_model, + descriptors=descriptors, + ) + return [ # mutable-ok: the shared generation reservation helpers require a list + *descriptors, + *self.create_organization_rate_limit_descriptor(user_api_key_dict, requested_model), + ] + + async def _release_request_capacity_when_admitted( + self, + admission: asyncio.Task[RateLimitResponse], + acquisition: ParallelSlotAcquisition, + user_api_key_dict: UserAPIKeyAuth, + ) -> None: + response: Final = await admission + if response["overall_code"] == "OK": + await self._release_parallel_request_slots(acquisition, user_api_key_dict.parent_otel_span) + + @asynccontextmanager + async def request_capacity( + self, + user_api_key_dict: UserAPIKeyAuth, + model: str, + *, + request_data: Mapping[str, object] | None = None, + ) -> AsyncGenerator[None, None]: + """Charge one non-generation provider request to RPM and hold its concurrency slot.""" + data: Final = MappingProxyType({**(request_data or MappingProxyType({})), "model": model}) + descriptors: Final = await self._build_request_rate_limit_descriptors(user_api_key_dict, data, None) + acquisition: Final = ParallelSlotAcquisition( + slot_id=uuid.uuid4().hex, + counter_keys=[ # mutable-ok: the shared slot-release contract requires a list + self.create_rate_limit_keys(d["key"], d["value"], "max_parallel_requests") + for d in descriptors + if d["rate_limit"] is not None and d["rate_limit"].get("max_parallel_requests") is not None + ], + ) + admission: Final = asyncio.create_task( + self.should_rate_limit( + descriptors=descriptors, + parent_otel_span=user_api_key_dict.parent_otel_span, + skip_tpm_check=True, + parallel_slot_id=acquisition["slot_id"], + ) + ) + try: + response: Final = await asyncio.shield(admission) + if response["overall_code"] == "OVER_LIMIT": + self._handle_rate_limit_error(response, descriptors, model) + yield + finally: + cleanup: Final = asyncio.create_task( + self._release_request_capacity_when_admitted(admission, acquisition, user_api_key_dict) + ) + cancellation: asyncio.CancelledError | None = None # rebind-ok: retain cancellation until cleanup finishes + while not cleanup.done(): + try: + await asyncio.shield(cleanup) + except asyncio.CancelledError as exc: + cancellation = exc # rebind-ok: retain the latest cancellation without interrupting slot release + cleanup.result() + if cancellation is not None: + raise cancellation + async def async_pre_call_hook( self, user_api_key_dict: UserAPIKeyAuth, @@ -3444,59 +3524,15 @@ class _PROXY_MaxParallelRequestsHandler_v3(CustomLogger): call_type=call_type, ) - # Get rate limit types from metadata - metadata: Final = user_api_key_dict.metadata or {} - rpm_limit_type: Final = metadata.get("rpm_limit_type") - tpm_limit_type: Final = metadata.get("tpm_limit_type") - - # For dynamic mode, check if the model has recent failures - model_has_failures = False - requested_model: Final = data.get("model", None) - - if ( - self._is_dynamic_rate_limiting_enabled( - rpm_limit_type=rpm_limit_type, - tpm_limit_type=tpm_limit_type, - ) - and requested_model - ): - model_has_failures = await self._check_model_has_recent_failures( - model=requested_model, - parent_otel_span=user_api_key_dict.parent_otel_span, - ) - - # Create rate limit descriptors - descriptors: Final = self._create_rate_limit_descriptors( + request_data: Final = _REQUEST_RATE_LIMIT_DATA.validate_python(data) + model_value: Final = request_data.get("model") + requested_model: Final = model_value if isinstance(model_value, str) else None + descriptors: Final = await self._build_request_rate_limit_descriptors( user_api_key_dict=user_api_key_dict, - data=data, - rpm_limit_type=rpm_limit_type, - tpm_limit_type=tpm_limit_type, - model_has_failures=model_has_failures, + data=request_data, call_type=call_type, ) - # Add team model rate limits from team_metadata - self._add_team_model_rate_limit_descriptor_from_metadata( - user_api_key_dict=user_api_key_dict, - requested_model=requested_model, - descriptors=descriptors, - ) - - # Project Level Rate Limits - self._add_project_model_rate_limit_descriptor_from_metadata( - user_api_key_dict=user_api_key_dict, - requested_model=requested_model, - descriptors=descriptors, - ) - self.add_project_io_token_rate_limit_descriptors_from_metadata( - user_api_key_dict=user_api_key_dict, - requested_model=requested_model, - descriptors=descriptors, - ) - - # Org Level Rate Limits - descriptors.extend(self.create_organization_rate_limit_descriptor(user_api_key_dict, requested_model)) - # Only check rate limits if we have descriptors with actual limits if descriptors: # First pass: RPM and max_parallel_requests sliding-window check. diff --git a/litellm/proxy/hooks/prompt_cache_prediction.py b/litellm/proxy/hooks/prompt_cache_prediction.py new file mode 100644 index 00000000000..65c456c5666 --- /dev/null +++ b/litellm/proxy/hooks/prompt_cache_prediction.py @@ -0,0 +1,142 @@ +from __future__ import annotations + +import asyncio +import time +from collections.abc import Callable, Mapping +from datetime import datetime +from typing import TYPE_CHECKING, Final, Literal + +import httpx +from pydantic import BaseModel, ConfigDict, Field, TypeAdapter, ValidationError + +from litellm.caching.dual_cache import DualCache +from litellm.integrations.custom_logger import CustomLogger +from litellm.llms.anthropic.prompt_cache_prediction import PromptPrefix, parse_observed_cache +from litellm.types.utils import ModelResponse + +if TYPE_CHECKING: + from litellm.proxy.utils import InternalUsageCache + +_RETENTION_SECONDS: Final = 86_400 + + +class CacheObservation(BaseModel): + model_config = ConfigDict(extra="forbid", frozen=True, strict=True) + + fingerprint: str = Field(pattern=r"^[0-9a-f]{64}$") + cached_tokens: int = Field(gt=0) + observed_at: float = Field(ge=0, allow_inf_nan=False) + expires_at: float = Field(ge=0, allow_inf_nan=False) + + +_CACHE_ENTRY: Final[TypeAdapter[CacheObservation | str | None]] = TypeAdapter(CacheObservation | str | None) + + +def _cache_key(scope: str, fingerprint: str) -> str: + return f"prompt-cache-observation:{scope}:{fingerprint}" + + +async def lookup( + cache: DualCache, scope: str, prefix: PromptPrefix, now: float | None = None +) -> CacheObservation | None: + checked_at: Final = time.time() if now is None else now + exact: Final = await _read_exact(cache, scope, prefix.fingerprint) + if exact is not None and exact.expires_at > checked_at: + return exact + older: Final = await asyncio.gather( + *(_read_exact(cache, scope, fingerprint) for fingerprint in prefix.fingerprints[1:]) + ) + observations: Final = tuple(observation for observation in (exact, *older) if observation is not None) + return next( + (observation for observation in observations if observation.expires_at > checked_at), + next(iter(observations), None), + ) + + +async def _read_exact(cache: DualCache, scope: str, fingerprint: str) -> CacheObservation | None: + try: + value: Final = _CACHE_ENTRY.validate_python(await cache.async_get_cache(_cache_key(scope, fingerprint), ttl=1)) # pyright: ignore[reportUnknownMemberType, reportUnknownArgumentType] # validate the legacy cache's untyped result at the I/O boundary + if value is None: + return None + observation: Final = CacheObservation.model_validate_json(value) if isinstance(value, str) else value + except ValidationError: + return None + return observation if observation.fingerprint == fingerprint else None + + +class _Metadata(BaseModel): + model_config = ConfigDict(strict=True) + user_api_key_hash: str = Field(min_length=1) + + +class _Logged(BaseModel): + model_config = ConfigDict(strict=True) + status: Literal["success"] + model_id: str = Field(min_length=1) + metadata: _Metadata + + +class _Event(BaseModel): + model_config = ConfigDict(strict=True, arbitrary_types_allowed=True) + call_type: Literal["anthropic_messages"] + custom_llm_provider: Literal["anthropic"] + cache_hit: bool | None = None + httpx_response: httpx.Response + first_api_call_start_time: datetime + standard_logging_object: _Logged + stream: bool = False + prompt_cache_response_complete: bool = False + + +class PromptCacheObserver(CustomLogger): + def __init__(self, internal_usage_cache: InternalUsageCache, clock: Callable[[], float] = time.time) -> None: + super().__init__() # pyright: ignore[reportUnknownMemberType] # base callback constructor accepts untyped kwargs + self.cache = internal_usage_cache.dual_cache + self.clock = clock + + async def async_log_success_event( + self, kwargs: Mapping[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + if not isinstance(response_obj, ModelResponse): + return + try: + event: Final = _Event.model_validate(kwargs) + wire: Final = event.httpx_response.request + except (ValidationError, RuntimeError, httpx.RequestNotRead): + return + if ( + event.cache_hit + or event.httpx_response.status_code != 200 + or (event.stream and not event.prompt_cache_response_complete) + ): + return + observed: Final = parse_observed_cache( + wire, + response_obj, + event.standard_logging_object.metadata.user_api_key_hash, + event.standard_logging_object.model_id, + ) + if observed is None: + return + prefix: Final = observed.prefix + scope: Final = observed.scope + cache_tokens: Final = observed.cached_tokens + now: Final = self.clock() + started: Final = event.first_api_call_start_time.timestamp() + if started > now: + return + if observed.cache_creation_tokens == 0: + previous: Final = await _read_exact(self.cache, scope, prefix.fingerprint) + if previous is None or previous.fingerprint != prefix.fingerprint or previous.cached_tokens != cache_tokens: + return + observation: Final = CacheObservation( + fingerprint=prefix.fingerprint, + cached_tokens=cache_tokens, + observed_at=now, + expires_at=started + prefix.ttl_seconds, + ) + key: Final = _cache_key(scope, prefix.fingerprint) + payload: Final = observation.model_dump_json() + await self.cache.async_set_cache(key, payload, ttl=_RETENTION_SECONDS) # pyright: ignore[reportUnknownMemberType] # legacy cache accepts a serialized validated observation + if self.cache.redis_cache is not None: + await self.cache.async_set_cache(key, payload, local_only=True, ttl=1) # pyright: ignore[reportUnknownMemberType] # keep the local copy short-lived while Redis retains stale evidence diff --git a/litellm/proxy/hooks/proxy_track_cost_callback.py b/litellm/proxy/hooks/proxy_track_cost_callback.py index 64da2ad00f6..3a61f773001 100644 --- a/litellm/proxy/hooks/proxy_track_cost_callback.py +++ b/litellm/proxy/hooks/proxy_track_cost_callback.py @@ -64,6 +64,7 @@ _UNATTRIBUTED_TRACKABLE_CALL_TYPES: Final[frozenset[str]] = frozenset( CallTypes.pass_through.value, CallTypes.llm_passthrough_route.value, CallTypes.allm_passthrough_route.value, + CallTypes.call_mcp_tool.value, # CheckBatchCost's synthetic logging_obj for a completed managed batch carries # whatever LiteLLM_ManagedObjectTable stored at create time, and all of it is # None for a batch created before those columns were persisted, or by the master diff --git a/litellm/proxy/hooks/rate_limiter_utils.py b/litellm/proxy/hooks/rate_limiter_utils.py index cdc3896c10d..bbe38068638 100644 --- a/litellm/proxy/hooks/rate_limiter_utils.py +++ b/litellm/proxy/hooks/rate_limiter_utils.py @@ -6,11 +6,10 @@ from typing import Final import litellm from litellm._logging import verbose_proxy_logger +from litellm.constants import PROXY_LLM_PROVIDER_FALLBACK from litellm.types.router import ModelGroupInfo from litellm.types.utils import PriorityReservationDict -PROXY_LLM_PROVIDER_FALLBACK: Final = "litellm_proxy" - def resolve_llm_provider_for_rate_limit( model: str | None, diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py index 59971e54e46..563db811edc 100644 --- a/litellm/proxy/litellm_pre_call_utils.py +++ b/litellm/proxy/litellm_pre_call_utils.py @@ -221,6 +221,8 @@ LITELLM_TRACE_CONTROL_METADATA_FIELDS: Final = frozenset( ) _UNTRUSTED_ROOT_CONTROL_FIELDS: Final = ( + "weights", + "_router_weights", "proxy_server_request", "standard_logging_object", "secret_fields", @@ -334,7 +336,7 @@ _CLIENT_PRICING_METADATA_FIELDS: Final = frozenset({"model_info", "standard_logg # and read by spend logs as fact; a client value has no legitimate meaning and no # key or team setting keeps it, so the strip is never gated. _ROUTER_RESERVED_METADATA_FIELDS: Final = frozenset( - {"attempted_fallbacks", "original_model_group", CLIENT_OUTPUT_CEILING_METADATA_KEY} + {"attempted_fallbacks", "original_model_group", "request_retry_count", CLIENT_OUTPUT_CEILING_METADATA_KEY} ) _ALLOW_CLIENT_PRICING_OVERRIDE_METADATA_KEY: Final = "allow_client_pricing_override" diff --git a/litellm/proxy/management_endpoints/common_daily_activity.py b/litellm/proxy/management_endpoints/common_daily_activity.py index a8aef30107c..44ed0017e42 100644 --- a/litellm/proxy/management_endpoints/common_daily_activity.py +++ b/litellm/proxy/management_endpoints/common_daily_activity.py @@ -127,6 +127,7 @@ def _key_metadata(api_key_metadata: Mapping[str, _KeyMetadataDict], api_key: str return KeyMetadata( key_alias=meta.get("key_alias"), team_id=meta.get("team_id"), + user_id=meta.get("user_id"), user_email=meta.get("user_email"), ) diff --git a/litellm/proxy/management_endpoints/cost_tracking_settings.py b/litellm/proxy/management_endpoints/cost_tracking_settings.py index dc0da63555f..cb376f286ec 100644 --- a/litellm/proxy/management_endpoints/cost_tracking_settings.py +++ b/litellm/proxy/management_endpoints/cost_tracking_settings.py @@ -28,6 +28,7 @@ from litellm.proxy._types import ( UserAPIKeyAuth, ) from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.management_endpoints.prompt_cache_prediction import router as prompt_cache_prediction_router from litellm.types.utils import ( CostBreakdown, CostPerToken, @@ -39,6 +40,7 @@ from litellm.types.utils import ( ) router: Final = APIRouter() +router.include_router(prompt_cache_prediction_router) @dataclass(frozen=True, slots=True) diff --git a/litellm/proxy/management_endpoints/internal_user_endpoints.py b/litellm/proxy/management_endpoints/internal_user_endpoints.py index 000b7f874ee..ba7a3309a90 100644 --- a/litellm/proxy/management_endpoints/internal_user_endpoints.py +++ b/litellm/proxy/management_endpoints/internal_user_endpoints.py @@ -478,7 +478,6 @@ async def new_user( - permissions: Optional[dict] - [Not Implemented Yet] User-specific permissions, eg. turning off pii masking. - metadata: Optional[dict] - Metadata for user, store information for user. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } - max_parallel_requests: Optional[int] - Rate limit a user based on the number of parallel requests. Raises 429 error, if user's parallel requests > x. - - soft_budget: Optional[float] - Get alerts when user crosses given budget, doesn't block requests. - model_max_budget: Optional[dict] - Model-specific max budget for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. - model_rpm_limit: Optional[float] - Model-specific rpm limit for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-limits-to-keys) @@ -568,7 +567,7 @@ async def new_user( teams = check_if_default_team_set() organization_ids: Final = cast(list[str] | None, data_json.pop("organizations", None)) - response: Final = await generate_key_helper_fn(request_type="user", **data_json) + response: Final = await generate_key_helper_fn(request_type="user", **data_json, llm_router=None) # Admin UI Logic # Add User to Team and Organization # if team_id passed add this user to the team @@ -1651,7 +1650,6 @@ async def user_update( - permissions: Optional[dict] - [Not Implemented Yet] User-specific permissions, eg. turning off pii masking. - metadata: Optional[dict] - Metadata for user, store information for user. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } - max_parallel_requests: Optional[int] - Rate limit a user based on the number of parallel requests. Raises 429 error, if user's parallel requests > x. - - soft_budget: Optional[float] - Get alerts when user crosses given budget, doesn't block requests. - model_max_budget: Optional[dict] - Model-specific max budget for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-budgets-to-keys) - budget_fallbacks: Optional[Dict[str, List[str]]] - Per-model fallback chain tried in order when that model's own `model_max_budget` is exceeded, e.g. {"gpt-4o": ["gpt-4o-mini"]}. - model_rpm_limit: Optional[float] - Model-specific rpm limit for user. [Docs](https://docs.litellm.ai/docs/proxy/users#add-model-specific-limits-to-keys) diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py index 8aaaba09e22..e5450785117 100644 --- a/litellm/proxy/management_endpoints/key_management_endpoints.py +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -96,6 +96,7 @@ from litellm.proxy.management_endpoints.common_utils import ( from litellm.proxy.management_endpoints.model_management_endpoints import ( _add_model_to_db, ) +from litellm.proxy.management_endpoints.router_weights import validate_router_settings_weights from litellm.proxy.management_helpers.access_group_key_sync import ( sync_key_access_group_membership, sync_key_regeneration_access_group_membership, @@ -202,6 +203,10 @@ class _KeyUpdateResult(TypedDict): data: ReadOnly[Mapping[str, object]] +class _StoredKeyRouterSettings(BaseModel): + router_settings: Mapping[str, object] | None = None + + class _KeyRowWhere(TypedDict): token: ReadOnly[str] @@ -1498,7 +1503,7 @@ async def _common_key_generation_helper( prisma_client=prisma_client, ) - response = await generate_key_helper_fn(request_type="key", **data_json, table_name="key") + response = await generate_key_helper_fn(request_type="key", **data_json, table_name="key", llm_router=llm_router) response["soft_budget"] = data.soft_budget # include the user-input soft budget in the response @@ -2402,7 +2407,26 @@ async def _update_key_row_with_soft_budget( async def prepare_key_update_data( data: UpdateKeyRequest | RegenerateKeyRequest, existing_key_row: LiteLLM_VerificationToken, + *, + prisma_client: PrismaClient | None = None, + llm_router: Router | None = None, ): + if data.router_settings is not None or ( + "router_settings" not in data.model_fields_set + and "team_id" in data.model_fields_set + and data.team_id != existing_key_row.team_id + ): + effective_settings: Final = ( + data.router_settings + if data.router_settings is not None + else _StoredKeyRouterSettings.model_validate(existing_key_row, from_attributes=True).router_settings + ) + await validate_router_settings_weights( + effective_settings, + team_id=data.team_id if "team_id" in data.model_fields_set else existing_key_row.team_id, + prisma_client=prisma_client, + llm_router=llm_router, + ) data_json: Final[dict] = data.model_dump(exclude_unset=True) data_json.pop("key", None) data_json.pop("new_key", None) @@ -2737,7 +2761,9 @@ async def _process_single_key_update( ) # Prepare update data - non_default_values = await prepare_key_update_data(data=update_key_request, existing_key_row=existing_key_row) + non_default_values = await prepare_key_update_data( + data=update_key_request, existing_key_row=existing_key_row, prisma_client=prisma_client, llm_router=llm_router + ) await _enforce_custom_key_policy( hook=user_custom_key_policy, @@ -3258,7 +3284,9 @@ async def update_key_fn( # Enforce upperbound key params on update (don't fill defaults) _enforce_upperbound_key_params(data, fill_defaults=False) - non_default_values: Final = await prepare_key_update_data(data=data, existing_key_row=existing_key_row) + non_default_values: Final = await prepare_key_update_data( + data=data, existing_key_row=existing_key_row, prisma_client=prisma_client, llm_router=llm_router + ) # Only validate key_alias format if it's actually being changed new_key_alias: Final = non_default_values.get("key_alias", None) @@ -4321,15 +4349,24 @@ async def generate_key_helper_fn( object_permission: LiteLLM_ObjectPermissionBase | None = None, auto_rotate: bool | None = None, rotation_interval: str | None = None, - router_settings: dict | None = None, + router_settings: dict[str, object] | None = None, access_group_ids: list[str] | None = None, budget_limits: list | None = None, # multiple concurrent budget windows + *, + llm_router: Router | None = None, ): from litellm.proxy.proxy_server import premium_user, prisma_client if prisma_client is None: raise Exception("Connect Proxy to database to generate keys - https://docs.litellm.ai/docs/proxy/virtual_keys ") + await validate_router_settings_weights( + router_settings, + team_id=team_id, + prisma_client=prisma_client, + llm_router=llm_router, + ) + if token is None: if key is not None: token = key @@ -5254,6 +5291,7 @@ async def _insert_deprecated_key( async def _execute_virtual_key_regeneration( *, prisma_client: PrismaClient, + llm_router: Router | None = None, key_in_db: LiteLLM_VerificationToken, hashed_api_key: str, key: str, @@ -5317,7 +5355,9 @@ async def _execute_virtual_key_regeneration( await _enforce_custom_key_update_policy(hook=_custom_key_update_hook(proxy_server), data=update_request) # Enforce upperbound key params on regenerate (don't fill defaults) _enforce_upperbound_key_params(data, fill_defaults=False) - non_default_values = await prepare_key_update_data(data=data, existing_key_row=key_in_db) + non_default_values = await prepare_key_update_data( + data=data, existing_key_row=key_in_db, prisma_client=prisma_client, llm_router=llm_router + ) # Only validate key_alias format if it's actually being changed new_key_alias: Final = non_default_values.get("key_alias") if new_key_alias != key_in_db.key_alias: @@ -5477,6 +5517,7 @@ async def regenerate_key_fn( try: from litellm.proxy.proxy_server import ( hash_token, + llm_router, master_key, premium_user, prisma_client, @@ -5654,6 +5695,7 @@ async def regenerate_key_fn( return await _execute_virtual_key_regeneration( prisma_client=prisma_client, + llm_router=llm_router, key_in_db=_key_in_db, hashed_api_key=hashed_api_key, key=key, @@ -6169,7 +6211,7 @@ async def list_keys( key_hash: str | None = Query(None, description="Filter keys by key hash"), key_alias: str | None = Query( None, - description="Filter keys by key alias. Exact match by default; set substring_matching=true (admin only) for case-insensitive substring matching.", + description="Filter keys by key alias. Exact match by default; set substring_matching=true for case-insensitive substring matching.", ), search: str | None = Query( None, @@ -6190,7 +6232,7 @@ async def list_keys( agent_id: str | None = Query(None, description="Filter keys by agent ID"), substring_matching: bool = Query( False, - description="If true (proxy admins only), match user_id/key_alias as case-insensitive substrings instead of exact values. Defaults to false: /key/list matched these exactly before substring search was added, and an exact user_id/key_alias filter must never return another user's keys.", + description="If true, match key_alias (any caller) and user_id (proxy admins only) as case-insensitive substrings instead of exact values. Defaults to false: /key/list matched these exactly before substring search was added, and an exact user_id filter must never return another user's keys.", ), expires: str | None = Query( None, @@ -6284,13 +6326,14 @@ async def list_keys( LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY.value, ] - # Substring matching is opt-in (admin-only). /key/list matched user_id and - # key_alias exactly before substring search was added; auto-applying a - # substring match to every admin call broke that contract and let a caller - # passing an exact user_id (e.g. an integration scoping to one user with an - # admin key) receive other users' keys (user_id="alice" -> "alice2"). Exact - # by default restores the prior behavior; the dashboard opts in explicitly. + # Substring matching is opt-in. /key/list matched user_id and key_alias + # exactly before substring search was added; auto-applying a substring + # match to every admin call broke that contract and let a caller passing + # an exact user_id (e.g. an integration scoping to one user with an admin + # key) receive other users' keys (user_id="alice" -> "alice2"). Exact by + # default restores the prior behavior; the dashboard opts in explicitly. use_substring_matching: Final = substring_matching and is_proxy_admin + use_key_alias_substring_matching: Final = substring_matching # Admins may omit user_id to list all keys; non-admins are scoped to self. if not user_id and not is_proxy_admin: @@ -6317,6 +6360,7 @@ async def list_keys( access_group_id=access_group_id, agent_id=agent_id, use_substring_matching=use_substring_matching, + use_key_alias_substring_matching=use_key_alias_substring_matching, expires_filter=expires if isinstance(expires, str) else None, search=search, ) @@ -6562,6 +6606,7 @@ def _build_key_filter_conditions( access_group_id: str | None = None, agent_id: str | None = None, use_substring_matching: bool = False, + use_key_alias_substring_matching: bool = False, expires_filter: str | None = None, search: str | None = None, ) -> Mapping[str, object]: @@ -6657,7 +6702,7 @@ def _build_key_filter_conditions( *( ( {"key_alias": {"contains": key_alias, "mode": "insensitive"}} - if use_substring_matching + if use_key_alias_substring_matching else {"key_alias": key_alias}, ) if key_alias and isinstance(key_alias, str) @@ -6703,6 +6748,7 @@ async def _list_key_helper( access_group_id: str | None = None, agent_id: str | None = None, use_substring_matching: bool = False, + use_key_alias_substring_matching: bool = False, expires_filter: str | None = None, search: str | None = None, ) -> KeyListResponseObject: @@ -6742,6 +6788,7 @@ async def _list_key_helper( access_group_id=access_group_id, agent_id=agent_id, use_substring_matching=use_substring_matching, + use_key_alias_substring_matching=use_key_alias_substring_matching, expires_filter=expires_filter, search=search, ) diff --git a/litellm/proxy/management_endpoints/model_management_endpoints.py b/litellm/proxy/management_endpoints/model_management_endpoints.py index 8484279c69a..2234e825090 100644 --- a/litellm/proxy/management_endpoints/model_management_endpoints.py +++ b/litellm/proxy/management_endpoints/model_management_endpoints.py @@ -123,6 +123,7 @@ from litellm.types.router import ( ModelInfo, updateDeployment, ) +from litellm.types.utils import without_server_derived_pricing from litellm.utils import get_utc_datetime if TYPE_CHECKING: @@ -747,11 +748,10 @@ def update_db_model(db_model: Deployment, updated_patch: updateDeployment) -> Pr # update model info if updated_patch.model_info: - merged_model_info.update(updated_patch.model_info.model_dump(exclude_none=True)) + merged_model_info.update(without_server_derived_pricing(updated_patch.model_info.model_dump(exclude_none=True))) - # Honor explicit-null clears LAST, after both merges, so a model_info blob the UI - # passes through (which today re-sends the OLD pricing on every save) cannot - # silently undo a litellm_params clear via .update(). + # Honor explicit-null clears LAST, after both merges, so a model_info blob a client + # passes through cannot silently undo a litellm_params clear via .update(). # # Restricted to SPECIAL_MODEL_INFO_PARAMS (input/output cost per token/character # and cache read/write costs) so this path cannot be used to null out privileged @@ -2094,6 +2094,10 @@ async def add_new_model( enforced=bool(general_settings.get(ENFORCE_RPM_TPM_ON_MODEL_ADD_SETTING, False)), ) + model_params.model_info = ModelInfo( # rebind-ok: downstream team-model handling mutates this same object + **without_server_derived_pricing(model_params.model_info.model_dump(exclude_none=True)) + ) + model_response: prisma_models.LiteLLM_ProxyModelTable | LiteLLM_ProxyModelTable | None = None # update DB incoming_model_info: Final = model_params.model_info.model_dump(exclude_none=True) diff --git a/litellm/proxy/management_endpoints/prompt_cache_prediction.py b/litellm/proxy/management_endpoints/prompt_cache_prediction.py new file mode 100644 index 00000000000..56e844214d6 --- /dev/null +++ b/litellm/proxy/management_endpoints/prompt_cache_prediction.py @@ -0,0 +1,278 @@ +import time +from collections.abc import Mapping +from types import MappingProxyType +from typing import Annotated, Final + +from fastapi import APIRouter, Depends, HTTPException, Request +from pydantic import BaseModel, JsonValue, TypeAdapter + +import litellm +from litellm._internal_context import current_billing_time, pinned_billing_time +from litellm.caching.caching import DualCache +from litellm.integrations.custom_logger import CustomLogger +from litellm.llms.anthropic.prompt_cache_prediction import ( + PromptPrefix, + TokenCounter, + UnsupportedPredictionTarget, + cache_scope, + count_prompt_tokens, + parse_prompt, + resolve_prediction_target, + supported_prediction_headers, +) +from litellm.proxy._types import UserAPIKeyAuth +from litellm.proxy.auth.auth_checks import can_key_call_resolved_model +from litellm.proxy.auth.auth_utils import get_cache_prediction_deployments +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.common_utils.http_parsing_utils import ( + _read_request_body, # pyright: ignore[reportPrivateUsage, reportUnknownVariableType] # canonical parsed-body owner; validate its legacy result at the endpoint boundary +) +from litellm.proxy.common_utils.prompt_cache_pricing import price_cache_tokens +from litellm.proxy.hooks.parallel_request_limiter_v3 import ( + _PROXY_MaxParallelRequestsHandler_v3, # pyright: ignore[reportPrivateUsage] # use the configured proxy limiter's shared capacity owner +) +from litellm.proxy.hooks.prompt_cache_prediction import lookup +from litellm.proxy.litellm_pre_call_utils import LiteLLMProxyRequestSetup +from litellm.types.management_endpoints.prompt_cache_prediction import ( + CacheCostScenario, + CacheEvidence, + CachePredictionArm, + CachePredictionRequest, + CachePredictionResponse, + CacheTokenBuckets, +) +from litellm.types.router import Deployment +from litellm.utils import get_prompt_cache_min_tokens + +router: Final = APIRouter() +_REQUEST_DATA: Final = TypeAdapter(Mapping[str, object]) + + +class _CallerSettings(BaseModel): + config: Mapping[str, object] | None = None + + +def has_request_transforms() -> bool: + from litellm.proxy.hooks import PROXY_HOOKS + + builtins: Final = frozenset(PROXY_HOOKS.values()) + hooks: Final = ("async_pre_call_hook", "async_pre_request_hook", "async_pre_call_deployment_hook") + callbacks: Final = litellm.logging_callback_manager.get_custom_loggers_for_type(callback_type=CustomLogger) + return any( + type(callback) not in builtins + and any(getattr(type(callback), hook) is not getattr(CustomLogger, hook) for hook in hooks) + for callback in callbacks + ) + + +def _buckets(prefix_tokens: int, suffix_tokens: int, read_tokens: int, ttl_seconds: int) -> CacheTokenBuckets: + return CacheTokenBuckets( + uncached_input_tokens=suffix_tokens, + cache_read_input_tokens=read_tokens, + cache_creation_5m_input_tokens=prefix_tokens - read_tokens if ttl_seconds == 300 else 0, + cache_creation_1h_input_tokens=prefix_tokens - read_tokens if ttl_seconds == 3600 else 0, + ) + + +def _scenario(model: str, deployment_id: str, tokens: CacheTokenBuckets) -> CacheCostScenario | None: + cost: Final = price_cache_tokens(model=model, deployment_id=deployment_id, tokens=tokens) + return CacheCostScenario(tokens=tokens, input_cost=cost) if cost is not None else None + + +def _capacity_counter( + limiter: _PROXY_MaxParallelRequestsHandler_v3, + caller: UserAPIKeyAuth, + model_name: str, + request_data: Mapping[str, object], +) -> TokenCounter: + async def count(model: str, api_key: str, body: Mapping[str, JsonValue]) -> int | None: + async with limiter.request_capacity(caller, model_name, request_data=request_data): + return await count_prompt_tokens(model, api_key, body) + + return count + + +def _capacity_request_data( + http_request: Request, caller: UserAPIKeyAuth, request_data: Mapping[str, object] +) -> Mapping[str, object]: + # The parsed-body cache retains only original top-level keys. Replay the + # shared idempotent tag merges on limiter-only data when auth added metadata. + data: Final = dict(request_data) # mutable-ok: the existing tag merge owners accept a dictionary out-param + LiteLLMProxyRequestSetup.apply_client_tag_policy_pre_auth(http_request, data, caller) # pyright: ignore[reportUnknownMemberType] # legacy tag owner takes the validated capacity dictionary + LiteLLMProxyRequestSetup.apply_key_tags_pre_auth(data, caller) # pyright: ignore[reportUnknownMemberType] # legacy tag owner merges trusted key tags into capacity metadata + return MappingProxyType(data) + + +async def predict_arm( + deployment: Deployment, + body: Mapping[str, JsonValue], + prefix: PromptPrefix, + caller_key_hash: str, + cache: DualCache, + token_counter: TokenCounter, +) -> CachePredictionArm: + deployment_id: Final = deployment.model_info.id or "" + params: Final = deployment.litellm_params + unknown: Final = CachePredictionArm(deployment_id=deployment_id, model=params.model) + if deployment.model_info.blocked: + return unknown.model_copy(update=MappingProxyType({"reason": "unsupported_deployment_configuration"})) + target: Final = resolve_prediction_target(params) + if isinstance(target, UnsupportedPredictionTarget): + return unknown.model_copy(update=MappingProxyType({"reason": target.reason})) + model: Final = target.model + api_key: Final = target.api_key + total_count: Final = await token_counter(model, api_key, body) + prefix_count: Final = await token_counter(model, api_key, prefix.prefix_body) + if total_count is None or prefix_count is None or total_count < prefix_count: + return unknown.model_copy(update=MappingProxyType({"reason": "token_count_unavailable"})) + scope: Final = cache_scope(caller_key_hash, deployment_id, api_key, model) + observation: Final = await lookup(cache, scope, prefix) + exact: Final = observation is not None and observation.fingerprint == prefix.fingerprint + cacheable: Final = observation.cached_tokens if exact and observation is not None else prefix_count + if cacheable > total_count or (observation is not None and observation.cached_tokens > cacheable): + return unknown.model_copy(update=MappingProxyType({"reason": "inconsistent_prefix_token_count"})) + suffix: Final = total_count - cacheable + evidence: Final = ( + CacheEvidence(observed_at=observation.observed_at, expires_at=observation.expires_at) + if observation is not None + else None + ) + if cacheable < get_prompt_cache_min_tokens(params.model): + disabled: Final = _scenario(model, deployment_id, CacheTokenBuckets(uncached_input_tokens=total_count)) + if disabled is None: + return unknown.model_copy(update=MappingProxyType({"reason": "pricing_unavailable"})) + return CachePredictionArm( + deployment_id=deployment_id, + model=model, + cache_state="disabled", + reason="below_cache_minimum", + estimate=disabled, + cold=disabled, + warm=disabled, + token_count_source="anthropic_count_tokens", + ) + fresh: Final = observation is not None and observation.expires_at > time.time() + read: Final = observation.cached_tokens if fresh and observation is not None else 0 + with pinned_billing_time(current_billing_time()): + cold: Final = _scenario(model, deployment_id, _buckets(cacheable, suffix, 0, prefix.ttl_seconds)) + warm: Final = _scenario(model, deployment_id, _buckets(cacheable, suffix, cacheable, prefix.ttl_seconds)) + estimate: Final = _scenario(model, deployment_id, _buckets(cacheable, suffix, read, prefix.ttl_seconds)) + if cold is None or warm is None or estimate is None: + return unknown.model_copy(update=MappingProxyType({"reason": "pricing_unavailable"})) + return CachePredictionArm( + deployment_id=deployment_id, + model=model, + cache_state="warm" if fresh and exact else "partial" if fresh else "stale" if observation else "unknown", + reason=None if fresh else "observation_expired" if observation else "no_compatible_observation", + estimate=estimate, + cold=cold, + warm=warm, + evidence=evidence, + token_count_source="anthropic_count_tokens", + ) + + +@router.post( + "/cost/predict-cache", + tags=["Cost Tracking"], # mutable-ok: FastAPI requires a list for OpenAPI tags + response_model=CachePredictionResponse, +) +async def predict_cache_cost( + request: CachePredictionRequest, + http_request: Request, + user_api_key_dict: Annotated[UserAPIKeyAuth, Depends(user_api_key_auth)], +) -> CachePredictionResponse: + """Compare the next native Anthropic request on two configured deployment IDs. + + Estimates use provider token counting and recent successful cache telemetry for this key. + Unknown cache state uses the cold scenario when prices/counts are available. Cache observations + do not guarantee retention. v0 supports one message-content breakpoint, text and client tools; + system/tool-only breakpoints, thinking, images, nondefault Anthropic versions, beta headers and + request transforms are unknown. + Each provider count consumes one RPM unit and holds concurrency capacity; a comparison uses + up to four counts. The legacy rate limiter returns unknown without contacting the provider. + This endpoint does not generate tokens, prewarm caches, choose a model or alter routing. + """ + from litellm.proxy.proxy_server import llm_router, proxy_logging_obj + + if llm_router is None: + raise HTTPException(status_code=503, detail="Model router is unavailable") + deployments: Final = get_cache_prediction_deployments( + current_deployment_id=request.current_deployment_id, + candidate_deployment_id=request.candidate_deployment_id, + llm_router=llm_router, + team_id=user_api_key_dict.team_id, + ) + if deployments is None: + raise HTTPException(status_code=404, detail="Deployment not found") + current, candidate = deployments + for deployment in (current, candidate): + await can_key_call_resolved_model( + model=deployment.model_name, + llm_model_list=llm_router.get_model_list(), + valid_token=user_api_key_dict, + llm_router=llm_router, + ) + prefix: Final = parse_prompt(request.request) + caller: Final = user_api_key_dict.api_key + caller_settings: Final = _CallerSettings.model_validate(user_api_key_dict, from_attributes=True) + unsupported_transform: Final = bool(caller_settings.config) or has_request_transforms() + unsupported_headers: Final = not supported_prediction_headers(http_request.headers) + limiter: Final = proxy_logging_obj.get_proxy_hook("parallel_request_limiter") + if ( + prefix is None + or not caller + or unsupported_transform + or unsupported_headers + or not isinstance(limiter, _PROXY_MaxParallelRequestsHandler_v3) + ): + reason: Final = ( + "unsupported_provider_headers" + if unsupported_headers + else "unsupported_request_transform" + if unsupported_transform + else "unsupported_prompt_shape" + if prefix is None + else "caller_identity_unavailable" + if not caller + else "limiter_unavailable" + ) + return CachePredictionResponse( + stay=CachePredictionArm(deployment_id=request.current_deployment_id, reason=reason), + switch=CachePredictionArm(deployment_id=request.candidate_deployment_id, reason=reason), + switch_delta=None, + cache_rebuild_penalty=None, + ) + request_data: Final = _capacity_request_data( + http_request, user_api_key_dict, _REQUEST_DATA.validate_python(await _read_request_body(http_request)) + ) + stay: Final = await predict_arm( + current, + request.request, + prefix, + caller, + proxy_logging_obj.internal_usage_cache.dual_cache, + _capacity_counter(limiter, user_api_key_dict, current.model_name, request_data), + ) + switch: Final = ( + stay + if current.model_info.id == candidate.model_info.id + else await predict_arm( + candidate, + request.request, + prefix, + caller, + proxy_logging_obj.internal_usage_cache.dual_cache, + _capacity_counter(limiter, user_api_key_dict, candidate.model_name, request_data), + ) + ) + return CachePredictionResponse( + stay=stay, + switch=switch, + switch_delta=(switch.estimate.input_cost - stay.estimate.input_cost) + if switch.estimate is not None and stay.estimate is not None + else None, + cache_rebuild_penalty=(switch.estimate.input_cost - switch.warm.input_cost) + if switch.estimate is not None and switch.warm is not None + else None, + ) diff --git a/litellm/proxy/management_endpoints/router_weights.py b/litellm/proxy/management_endpoints/router_weights.py new file mode 100644 index 00000000000..99b368808c3 --- /dev/null +++ b/litellm/proxy/management_endpoints/router_weights.py @@ -0,0 +1,129 @@ +from abc import abstractmethod +from collections.abc import Mapping +from typing import Annotated, Final, Protocol + +from fastapi import HTTPException +from pydantic import BaseModel, BeforeValidator, ValidationError + +from litellm.repositories.prisma_protocols import TableActions +from litellm.types.router_weights import RouterWeights + + +class _StoredModel(Protocol): + @property + @abstractmethod + def model_id(self) -> str: + pass + + +class _ModelDb(Protocol): + @property + @abstractmethod + def litellm_proxymodeltable(self) -> TableActions[_StoredModel]: + pass + + +class _PrismaClient(Protocol): + @property + @abstractmethod + def db(self) -> _ModelDb: + pass + + +class _Router(Protocol): + @abstractmethod + def get_deployment(self, model_id: str) -> object | None: + pass + + +class _RouterWeightSettings(BaseModel): + weights: RouterWeights | None = None + + +class _RouterWeightModelInfo(BaseModel): + team_id: str | None = None + db_model: bool | None = None + team_public_model_name: str | None = None + + +def _router_weight_model_info(value: object) -> _RouterWeightModelInfo: + if isinstance(value, str): + return _RouterWeightModelInfo.model_validate_json(value) + return _RouterWeightModelInfo.model_validate(value or {}, from_attributes=True) + + +class _RouterWeightDeployment(BaseModel): + model_name: str + model_info: Annotated[_RouterWeightModelInfo, BeforeValidator(_router_weight_model_info)] + + +def _validate_router_weight_reference( + model_group: str, + deployment_id: str, + team_id: str | None, + stored: _RouterWeightDeployment | None, + configured: object | None, +) -> None: + reference: Final = ( + stored + if stored is not None + else ( + _RouterWeightDeployment.model_validate(configured, from_attributes=True) if configured is not None else None + ) + ) + if ( + reference is None + or (stored is None and reference.model_info.db_model) + or (reference.model_info.team_id is not None and reference.model_info.team_id != team_id) + ): + raise HTTPException(status_code=400, detail=f"Unknown deployment ID in router weights: {deployment_id}") + canonical_group: Final = ( + reference.model_info.team_public_model_name if reference.model_info.team_id is not None else None + ) or reference.model_name + if model_group != canonical_group: + raise HTTPException( + status_code=400, + detail=f"Deployment {deployment_id} does not belong to model group {model_group}", + ) + + +async def validate_router_settings_weights( + router_settings: BaseModel | Mapping[str, object] | None, + *, + team_id: str | None, + prisma_client: _PrismaClient | None, + llm_router: _Router | None, +) -> None: + try: + weights: Final = ( + _RouterWeightSettings.model_validate(router_settings, from_attributes=True).weights + if router_settings is not None + else None + ) + except ValidationError: + raise HTTPException( + status_code=400, + detail="Invalid router weights. Replace or clear router_settings.weights.", + ) from None + if not weights: + return + deployment_ids: Final = frozenset(deployment_id for group in weights.values() for deployment_id in group) + if not deployment_ids: + return + if prisma_client is None: + raise HTTPException(status_code=503, detail="Database unavailable while validating router weights") + stored_models: Final = await prisma_client.db.litellm_proxymodeltable.find_many( + where={"model_id": {"in": list(deployment_ids)}} + ) + stored_by_id: Final = { + row.model_id: _RouterWeightDeployment.model_validate(row, from_attributes=True) for row in stored_models + } + for model_group, group_weights in weights.items(): + for deployment_id in group_weights: + _validate_router_weight_reference( + model_group, + deployment_id, + team_id, + stored_by_id.get(deployment_id), + llm_router.get_deployment(model_id=deployment_id) if llm_router is not None else None, + ) diff --git a/litellm/proxy/management_endpoints/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py index e9e37540dd8..2d04a4d1e04 100644 --- a/litellm/proxy/management_endpoints/team_endpoints.py +++ b/litellm/proxy/management_endpoints/team_endpoints.py @@ -14,7 +14,7 @@ import copy import json import math import traceback -from collections.abc import Mapping, Sequence +from collections.abc import Iterable, Mapping, Sequence from collections.abc import Set as AbstractSet from datetime import datetime, timezone from types import MappingProxyType @@ -112,6 +112,7 @@ from litellm.proxy.management_endpoints.common_utils import ( from litellm.proxy.management_endpoints.organization_endpoints import ( add_member_to_organization, ) +from litellm.proxy.management_endpoints.router_weights import validate_router_settings_weights from litellm.proxy.management_endpoints.tag_management_endpoints import ( get_daily_activity, ) @@ -156,6 +157,7 @@ from litellm.repositories.verification_token_repository import ( VerificationTokenRepository, ) from litellm.router import Router +from litellm.types.proxy.auth.auth_checks import UserNotFoundError from litellm.types.proxy.management_endpoints.common_daily_activity import ( SpendAnalyticsPaginatedResponse, ) @@ -179,6 +181,7 @@ from litellm.types.proxy.management_endpoints.team_endpoints import ( if TYPE_CHECKING: from prisma import Prisma from prisma import models as prisma_models + from prisma import types as prisma_types router: Final = APIRouter() @@ -429,27 +432,26 @@ async def _refresh_cached_team( ) +async def _can_manage_team( + team_obj: LiteLLM_TeamTable, + user_api_key_dict: UserAPIKeyAuth, +) -> bool: + """True for a proxy admin, an admin of this team, or an org admin for the team's organization.""" + if user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN: + return True + + if _is_user_team_admin(user_api_key_dict=user_api_key_dict, team_obj=team_obj): + return True + + return await _is_user_org_admin_for_team(user_api_key_dict=user_api_key_dict, team_obj=team_obj) + + async def _verify_team_access( team_obj: LiteLLM_TeamTable, user_api_key_dict: UserAPIKeyAuth, ) -> None: - """ - Verify the caller is authorized to manage the given team. - - Access is granted if: - - Caller is a proxy admin, OR - - Caller is an org admin for the team's organization, OR - - Caller is a team admin of this team - - Raises HTTPException(403) otherwise. - """ - if user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN: - return - - if _is_user_team_admin(user_api_key_dict=user_api_key_dict, team_obj=team_obj): - return - - if await _is_user_org_admin_for_team(user_api_key_dict=user_api_key_dict, team_obj=team_obj): + """Raise HTTPException(403) unless the caller can manage the given team.""" + if await _can_manage_team(team_obj=team_obj, user_api_key_dict=user_api_key_dict): return raise HTTPException( @@ -1287,6 +1289,7 @@ async def new_team( create_audit_log_for_update, general_settings, litellm_proxy_admin_name, + llm_router, prisma_client, user_api_key_cache, ) @@ -1461,6 +1464,13 @@ async def new_team( user_api_key_dict=user_api_key_dict, ) + await validate_router_settings_weights( + data.router_settings, + team_id=data.team_id, + prisma_client=prisma_client, + llm_router=llm_router, + ) + ## ADD TO MODEL TABLE _model_id = None if data.model_aliases is not None and isinstance(data.model_aliases, dict): @@ -1903,6 +1913,39 @@ def validate_team_org_change( return True +def _member_user_ids(members_with_roles: Sequence[dict[str, object]]) -> tuple[str, ...]: + """Extract the string ``user_id`` of each team member, dropping rows without one. + + ``members_with_roles`` is a Prisma-deserialized JSON column, so its ``user_id`` is typed + ``object``; the ``isinstance`` narrows it to the ``str`` ``invalidate_team_member_spend_state`` needs. + """ + return tuple(user_id for member in members_with_roles if isinstance((user_id := member.get("user_id")), str)) + + +async def _evict_created_membership_caches( + user_ids: Iterable[str], + team_id: str, + user_api_key_cache: UserApiKeyCache, +) -> None: + """Evict the ``get_team_membership`` negative-cache sentinel for members whose row was just created. + + A session-token request caches ``NO_TEAM_MEMBERSHIP_SENTINEL`` for a member with no + ``LiteLLM_TeamMembership`` row. When a create path (``/team/member_add`` or the ``/team/update`` + budget backfill) later writes that row with a per-member budget, the stale sentinel keeps the + member's budget unenforced until the membership cache TTL expires, so it must be evicted here. + """ + await asyncio.gather( + *( + invalidate_team_member_spend_state( + user_id=user_id, + team_id=team_id, + user_api_key_cache=user_api_key_cache, + ) + for user_id in user_ids + ) + ) + + @router.post("/team/update", tags=["team management"], dependencies=[Depends(user_api_key_auth)]) @management_endpoint_wrapper async def update_team( @@ -2041,6 +2084,13 @@ async def update_team( user_api_key_dict=user_api_key_dict, ) + await validate_router_settings_weights( + data.router_settings, + team_id=data.team_id, + prisma_client=prisma_client, + llm_router=llm_router, + ) + _existing_team_metadata: Final[object] = getattr(existing_team_row, "metadata", None) enforce_output_token_estimates_are_admin_only( data=data, @@ -2239,6 +2289,11 @@ async def update_team( team_member_budget_id=_backfill_budget_id, prisma_client=prisma_client, ) + await _evict_created_membership_caches( + user_ids=_member_user_ids(existing_team_row.members_with_roles), + team_id=data.team_id, + user_api_key_cache=user_api_key_cache, + ) elif _team_member_fields_in_request: updated_kv = await TeamMemberBudgetHandler.clear_team_member_budget_fields( team_table=existing_team_row, @@ -3191,6 +3246,12 @@ async def team_member_add( litellm_proxy_admin_name=litellm_proxy_admin_name, ) + await _evict_created_membership_caches( + user_ids=(tm.user_id for tm in updated_team_memberships), + team_id=data.team_id, + user_api_key_cache=user_api_key_cache, + ) + _emit_team_members_metric(complete_team_data) await _create_team_member_add_audit_logs( @@ -4324,6 +4385,20 @@ async def _hydrate_member_user_details( return tuple(hydrate(m) for m in members) +class _OrganizationModelsRow(BaseModel): + models: list[str] = [] # mutable-ok: pydantic field default + + +class _TeamRowWithOrganization(BaseModel): + litellm_organization_table: _OrganizationModelsRow | None = None + + +def _parent_organization_models(team_row: BaseModel) -> list[str] | None: + """Return the parent org's model allow-list, or None when the team has no org.""" + organization: Final = _TeamRowWithOrganization.model_validate(team_row.model_dump()).litellm_organization_table + return organization.models if organization is not None else None + + async def _resolve_team_access_group_resources( _team_info: TeamInfoResponseObjectTeamTable, ) -> TeamInfoResponseObjectTeamTable: @@ -4395,7 +4470,11 @@ async def team_info( try: team_info: BaseModel | None = await _team_db(prisma_client).find_unique( where={"team_id": team_id}, - include={"litellm_model_table": True, "object_permission": True}, + include={ + "litellm_model_table": True, + "object_permission": True, + "litellm_organization_table": True, + }, ) if team_info is None: raise Exception @@ -4404,9 +4483,12 @@ async def team_info( status_code=status.HTTP_404_NOT_FOUND, detail={"message": f"Team not found, passed team id: {team_id}."}, ) - await validate_membership( - user_api_key_dict=user_api_key_dict, - team_table=LiteLLM_TeamTable.model_validate(team_info.model_dump()), + team_table: Final = LiteLLM_TeamTable.model_validate(team_info.model_dump()) + await validate_membership(user_api_key_dict=user_api_key_dict, team_table=team_table) + organization_models: Final[list[str] | None] = ( + _parent_organization_models(team_info) + if await _can_manage_team(team_obj=team_table, user_api_key_dict=user_api_key_dict) + else None ) ## GET ALL KEYS ## @@ -4466,7 +4548,10 @@ async def team_info( members=resolved_team_info.members_with_roles, ) hydrated_team_info: Final = resolved_team_info.model_copy( - update={"members_with_roles": hydrated_members} # mutable-ok: pydantic update payload + update={ # mutable-ok: pydantic update payload + "members_with_roles": hydrated_members, + "organization_models": organization_models, + } ) response_object: Final = TeamInfoResponseObject( @@ -4813,6 +4898,26 @@ async def _get_org_admin_org_ids( return org_ids if org_ids else None +async def _get_user_team_ids_from_db( + user_id: str, + prisma_client: PrismaClient, + user_api_key_cache: UserApiKeyCache, + proxy_logging_obj: ProxyLogging, +) -> tuple[str, ...]: + try: + user: Final = await get_user_object( + user_id=user_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + user_id_upsert=False, + proxy_logging_obj=proxy_logging_obj, + check_db_only=True, + ) + except UserNotFoundError: + return () + return tuple(user.teams or ()) if user is not None else () + + async def _build_team_list_where_conditions( prisma_client: PrismaClient, team_id: str | None, @@ -4823,12 +4928,16 @@ async def _build_team_list_where_conditions( search: str | None = None, search_team_id_match: TeamIdSearchMatch = "exact", org_admin_org_ids: list[str] | None = None, + own_team_ids: tuple[str, ...] = (), user_api_key_cache: UserApiKeyCache | None = None, proxy_logging_obj: ProxyLogging | None = None, ) -> dict[str, object] | None: """ Build where conditions for team list query. + An org admin listing their own teams sees the union of the teams in the + orgs they administer and `own_team_ids`, the teams they are a member of. + Returns None when the query is guaranteed to yield no results (e.g. user has no team memberships), allowing the caller to skip the DB round-trip. """ @@ -4851,6 +4960,11 @@ async def _build_team_list_where_conditions( if organization_id: where_conditions["organization_id"] = organization_id + elif org_admin_org_ids is not None and own_team_ids: + org_or_membership_scope: Final[prisma_types.LiteLLM_TeamTableWhereInput] = { + "OR": [{"organization_id": {"in": org_admin_org_ids}}, {"team_id": {"in": list(own_team_ids)}}] + } + where_conditions["AND"] = [org_or_membership_scope] elif org_admin_org_ids is not None: # Org admin: always scope to their orgs, even when filtering by user_id. where_conditions["organization_id"] = {"in": org_admin_org_ids} @@ -4982,66 +5096,72 @@ async def _enforce_list_team_v2_access( prisma_client: PrismaClient, user_api_key_cache: UserApiKeyCache, proxy_logging_obj: ProxyLogging, -) -> tuple[str | None, list[str] | None]: +) -> tuple[str | None, list[str] | None, tuple[str, ...]]: """Enforce access control for list_team_v2. - Proxy admins and admin viewers can query any teams. - - Org admins can query teams within their organizations. + - Org admins can query teams within their organizations, plus the teams + they are a member of when listing their own teams. - Regular users can only query their own teams. - Returns the (possibly overridden) user_id and org_admin_org_ids. + Returns the (possibly overridden) user_id, org_admin_org_ids and, for an + org admin's own query, the caller's own team ids. """ is_proxy_admin: Final = _user_has_admin_view(user_api_key_dict) - org_admin_org_ids: list[str] | None = None + caller_user_id: Final = user_api_key_dict.user_id if is_proxy_admin: - return user_id, org_admin_org_ids + return user_id, None, () # Always check org admin status so that even own-queries see # the full set of organisation teams, not just direct memberships. - if user_api_key_dict.user_id: - org_admin_org_ids = await _get_org_admin_org_ids( - user_id=user_api_key_dict.user_id, + org_admin_org_ids: Final = ( + await _get_org_admin_org_ids( + user_id=caller_user_id, prisma_client=prisma_client, user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, ) + if caller_user_id + else None + ) - if org_admin_org_ids is not None: + if caller_user_id and org_admin_org_ids is not None: # Org admin: validate org_id filter if provided if organization_id and organization_id not in org_admin_org_ids: raise HTTPException( status_code=403, detail={"error": "You can only view teams within your organizations."}, ) - # When the caller is an org admin querying their own teams (or no - # specific user), null out user_id so that - # _build_team_list_where_conditions scopes only by organization_id - # — org admins should see all teams in their orgs, not just teams - # they are a direct member of. Keep user_id when the org admin - # explicitly queries a *different* user's teams. - if user_id is None or user_id == user_api_key_dict.user_id: - user_id = None + is_own_query: Final = user_id is None or user_id == caller_user_id + own_team_ids: Final = ( + await _get_user_team_ids_from_db( + user_id=caller_user_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + proxy_logging_obj=proxy_logging_obj, + ) + if is_own_query + else () + ) verbose_proxy_logger.debug( "list_team_v2: org admin access for user=%s, org_ids=%s, user_id_filter=%s", - user_api_key_dict.user_id, + _sanitize_for_log(caller_user_id), org_admin_org_ids, - user_id, + _sanitize_for_log(None if is_own_query else user_id), ) - else: - # Not an org admin — fall back to standard route check - if not allowed_route_check_inside_route(user_api_key_dict=user_api_key_dict, requested_user_id=user_id): - raise HTTPException( - status_code=401, - detail={ - "error": f"Only admin users can query all teams/other teams. Your user role={user_api_key_dict.user_role}" - }, - ) - # Regular user — auto-inject caller's user_id - if user_id is None: - user_id = user_api_key_dict.user_id + return None if is_own_query else user_id, org_admin_org_ids, own_team_ids - return user_id, org_admin_org_ids + # Not an org admin — fall back to standard route check + if not allowed_route_check_inside_route(user_api_key_dict=user_api_key_dict, requested_user_id=user_id): + raise HTTPException( + status_code=401, + detail={ + "error": f"Only admin users can query all teams/other teams. Your user role={user_api_key_dict.user_role}" + }, + ) + # Regular user — auto-inject caller's user_id + return user_id if user_id is not None else caller_user_id, None, () @router.get( @@ -5119,7 +5239,7 @@ async def list_team_v2( ) # --- Access control --- - user_id, org_admin_org_ids = await _enforce_list_team_v2_access( + user_id, org_admin_org_ids, own_team_ids = await _enforce_list_team_v2_access( user_api_key_dict=user_api_key_dict, user_id=user_id, organization_id=organization_id, @@ -5151,6 +5271,7 @@ async def list_team_v2( search=search, search_team_id_match=search_team_id_match, org_admin_org_ids=org_admin_org_ids, + own_team_ids=own_team_ids, user_api_key_cache=user_api_key_cache, proxy_logging_obj=proxy_logging_obj, ) @@ -5247,17 +5368,16 @@ async def _authorize_and_filter_teams( - Proxy admins: all teams (or filtered by user_id if provided). - Org admins: teams from their orgs (scoped to user_id if provided). - - Own query (user_id matches caller): teams the user is a member of. + - Own query (user_id matches caller): teams the user is a member of, across all orgs. - Others: 401. """ is_proxy_admin: Final = _user_has_admin_view(user_api_key_dict) + is_own_query: Final = ( + user_id is not None and user_api_key_dict.user_id is not None and user_api_key_dict.user_id == user_id + ) allowed_org_ids: list[str] | None = None if not is_proxy_admin: - is_own_query: Final = ( - user_id is not None and user_api_key_dict.user_id is not None and user_api_key_dict.user_id == user_id - ) - # Check if user is an org admin (even for own queries, so they see org teams) if user_api_key_dict.user_id is not None: caller_user: Final = await get_user_object( @@ -5284,33 +5404,30 @@ async def _authorize_and_filter_teams( }, ) - if allowed_org_ids is not None: - # Org admin: query DB for teams in their orgs + if allowed_org_ids is not None and not is_own_query: org_teams: Final = await _raw_team_db(TeamRepository(prisma_client)).find_many( where={"organization_id": {"in": allowed_org_ids}}, include={"litellm_model_table": True}, ) if not user_id: return list(org_teams) - # Filter org teams to only those where the target user is a member return [ team for team in org_teams if team.members_with_roles and any(m.get("user_id") == user_id for m in team.members_with_roles) ] - elif user_id: - # Regular user: fetch all and filter by membership (Prisma can't filter JSON arrays) - response: Final = await _raw_team_db(TeamRepository(prisma_client)).find_many( - include={"litellm_model_table": True} - ) - return [ - team - for team in response - if team.members_with_roles and any(m.get("user_id") == user_id for m in team.members_with_roles) - ] - else: + + response: Final = await _raw_team_db(TeamRepository(prisma_client)).find_many(include={"litellm_model_table": True}) + if not user_id: # Proxy admin: all teams - return list(await _raw_team_db(TeamRepository(prisma_client)).find_many(include={"litellm_model_table": True})) + return list(response) + + # Prisma can't filter JSON arrays, so membership is filtered in Python + return [ + team + for team in response + if team.members_with_roles and any(m.get("user_id") == user_id for m in team.members_with_roles) + ] @router.get("/team/list", tags=["team management"], dependencies=[Depends(user_api_key_auth)]) diff --git a/litellm/proxy/management_endpoints/ui_sso.py b/litellm/proxy/management_endpoints/ui_sso.py index 1ba90725eff..329443148a2 100644 --- a/litellm/proxy/management_endpoints/ui_sso.py +++ b/litellm/proxy/management_endpoints/ui_sso.py @@ -101,6 +101,7 @@ from litellm.proxy.common_utils.admin_ui_utils import ( admin_ui_disabled, show_missing_vars_in_env, ) +from litellm.proxy.common_utils.html_forms.default_credentials_hint import should_hide_default_credentials_hint from litellm.proxy.common_utils.html_forms.jwt_display_template import ( jwt_display_template, ) @@ -1110,10 +1111,7 @@ async def google_login( from fastapi.responses import HTMLResponse - hide_default_credentials_hint: Final = ( - os.getenv("LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", "false").lower() == "true" - or general_settings.get("hide_default_credentials_hint", False) is True - ) + hide_default_credentials_hint: Final = should_hide_default_credentials_hint(general_settings) form_response: Final = HTMLResponse( content=build_ui_login_form( show_deprecation_banner=True, @@ -3594,6 +3592,7 @@ class SSOAuthenticationHandler: verbose_proxy_logger.info("user_defined_values for creating ui key: %s", user_defined_values) response: Final = await generate_key_helper_fn( + llm_router=None, request_type="key", duration=LITELLM_UI_SESSION_DURATION, key_max_budget=litellm.max_ui_session_budget, diff --git a/litellm/proxy/management_helpers/team_metadata_validation.py b/litellm/proxy/management_helpers/team_metadata_validation.py index 7bc66c240c7..76477ab2988 100644 --- a/litellm/proxy/management_helpers/team_metadata_validation.py +++ b/litellm/proxy/management_helpers/team_metadata_validation.py @@ -115,15 +115,15 @@ async def run_team_metadata_validation( "error": f"custom_team_metadata_validate is an Enterprise feature. {CommonProxyErrors.not_premium_user.value}" }, ) - if not ( - inspect.iscoroutinefunction(validator) or inspect.iscoroutinefunction(getattr(validator, "__call__", None)) - ): - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail={ # mutable-ok: HTTPException.detail has no immutable form - "error": "custom_team_metadata_validate must be an async function" - }, - ) + if not inspect.iscoroutinefunction(validator): + validator_call: Final = getattr(validator, "__call__", None) # noqa: B004 # value unwrap for the functor check + if not inspect.iscoroutinefunction(validator_call): + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail={ # mutable-ok: HTTPException.detail has no immutable form + "error": "custom_team_metadata_validate must be an async function" + }, + ) try: raw_result: Final = await asyncio.wait_for(validator(payload), timeout=timeout_seconds) diff --git a/litellm/proxy/openai_files_endpoints/common_utils.py b/litellm/proxy/openai_files_endpoints/common_utils.py index b1f282a0978..38a907892b4 100644 --- a/litellm/proxy/openai_files_endpoints/common_utils.py +++ b/litellm/proxy/openai_files_endpoints/common_utils.py @@ -16,6 +16,7 @@ from typing import ( ) from litellm.batches.batch_utils import batch_cost_is_final +from litellm.constants import MAX_FILE_LIST_LIMIT from litellm.proxy._types import ProxyException from litellm.repositories.table_repositories import ( ManagedFileRepository, @@ -34,8 +35,6 @@ if TYPE_CHECKING: from litellm.types.utils import LiteLLMBatch -MAX_FILE_LIST_LIMIT: Final = 10000 - FILE_LIST_CONTINUATION_CHUNK_SIZE: Final = 500 BATCH_CREATE_HIDDEN_PARAM: Final = "batch_create" diff --git a/litellm/proxy/openai_files_endpoints/files_endpoints.py b/litellm/proxy/openai_files_endpoints/files_endpoints.py index c315d30b8f3..ae6e222a863 100644 --- a/litellm/proxy/openai_files_endpoints/files_endpoints.py +++ b/litellm/proxy/openai_files_endpoints/files_endpoints.py @@ -33,6 +33,7 @@ from litellm.litellm_core_utils.cloud_storage_security import ( ) from litellm.litellm_core_utils.core_helpers import get_or_create_metadata_bucket from litellm.llms.base_llm.files.transformation import BaseFileEndpoints +from litellm.llms.base_llm.managed_resources.isolation import build_list_page from litellm.proxy._types import * from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.common_request_processing import ProxyBaseLLMRequestProcessing @@ -77,6 +78,7 @@ from litellm.proxy.openai_files_endpoints.common_utils import ( ) from litellm.proxy.openai_files_endpoints.general_upload_validation import ( MB, + check_allowed_extension, check_blocked_extension, check_unsafe_filename, check_upload_file_size, @@ -90,6 +92,7 @@ from litellm.router import Router from litellm.types.llms.openai import ( CREATE_FILE_REQUESTS_PURPOSE, FileExpiresAfter, + FileListPage, OpenAIFileObject, OpenAIFilesPurpose, ) @@ -97,6 +100,7 @@ from litellm.types.llms.openai import ( router: Final = APIRouter() _MAX_BATCH_FILE_SIZE_MB_ADAPTER: Final = TypeAdapter(int | None) +_LISTED_FILES_ADAPTER: Final = TypeAdapter(list[OpenAIFileObject]) class UploadedFileInfo(TypedDict): @@ -470,6 +474,11 @@ async def create_file( if general_size_failure is not None: raise_upload_validation_failure(general_size_failure) + allowed_extensions: Final = coerce_optional_str_list_setting(general_settings.get("allowed_file_extensions")) + allowed_extension_failure: Final = check_allowed_extension(file.filename, allowed_extensions) + if allowed_extension_failure is not None: + raise_upload_validation_failure(allowed_extension_failure) + blocked_extensions: Final = coerce_optional_str_list_setting(general_settings.get("blocked_file_extensions")) blocked_extension_failure: Final = check_blocked_extension(file.filename, blocked_extensions) if blocked_extension_failure is not None: @@ -1287,6 +1296,11 @@ async def delete_file( user_api_key_dict=user_api_key_dict, managed_files_obj=proxy_logging_obj.get_proxy_hook("managed_files"), ) + if is_managed_cloud_storage_uri(file_id) and user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN: + raise HTTPException( + status_code=403, + detail="Raw cloud storage file ids can only be deleted by a proxy admin key. Use the LiteLLM managed file id returned when the file was created.", + ) custom_llm_provider: Final = ( provider @@ -1446,6 +1460,12 @@ async def delete_file( ) +def _as_file_list_page(response: object) -> object: + if not isinstance(response, list): + return response + return FileListPage(**build_list_page(_LISTED_FILES_ADAPTER.validate_python(response))) + + @router.get( "/{provider}/v1/files", dependencies=[Depends(user_api_key_auth)], @@ -1524,7 +1544,7 @@ async def list_files( if should_route and credentials is not None: # Use model-based routing with credentials from config - prepare_data_with_credentials(data=data, credentials=credentials) + prepare_data_with_credentials(data=data, credentials=credentials, include_internal_credentials=True) response = await litellm.afile_list( custom_llm_provider=credentials["custom_llm_provider"], purpose=purpose, @@ -1550,7 +1570,7 @@ async def list_files( model_id=target_model_names_list[0], operation_context="file list", ) - prepare_data_with_credentials(data=data, credentials=credentials) + prepare_data_with_credentials(data=data, credentials=credentials, include_internal_credentials=True) response = await litellm.afile_list( custom_llm_provider=credentials["custom_llm_provider"], purpose=purpose, @@ -1592,6 +1612,7 @@ async def list_files( status_code=500, detail="Either 'provider' or 'target_model_names' must be provided e.g. `?target_model_names=gpt-4o`", ) + response = _as_file_list_page(response) # rebind-ok: each dispatch branch above binds response ## POST CALL HOOKS ### _response: Final = await proxy_logging_obj.post_call_success_hook( diff --git a/litellm/proxy/openai_files_endpoints/general_upload_validation.py b/litellm/proxy/openai_files_endpoints/general_upload_validation.py index 8c59a520272..e9b6c319fe5 100644 --- a/litellm/proxy/openai_files_endpoints/general_upload_validation.py +++ b/litellm/proxy/openai_files_endpoints/general_upload_validation.py @@ -2,8 +2,8 @@ Upload validation applied to every purpose at POST /v1/files. batch_file_validation.py checks the JSONL shape of purpose="batch" uploads; this -module applies the same fast-fail-before-forwarding shape (size cap, blocked -extensions, path-traversal filenames) regardless of purpose. +module applies the same fast-fail-before-forwarding shape (size cap, allowed and +blocked extensions, path-traversal filenames) regardless of purpose. """ from dataclasses import dataclass @@ -31,10 +31,9 @@ def coerce_optional_int_setting(raw: object) -> int | None: raise TypeError(f"expected an integer, got {raw!r}") -def coerce_optional_str_list_setting(raw: object) -> tuple[str, ...]: - """A general_settings value declared as an optional list of strings, e.g. blocked_file_extensions.""" +def coerce_optional_str_list_setting(raw: object) -> tuple[str, ...] | None: if raw is None: - return () + return None if not isinstance(raw, list) or not all(isinstance(item, str) for item in raw): raise TypeError(f"expected a list of strings, got {raw!r}") return tuple(raw) @@ -46,6 +45,11 @@ class UploadedFileTooLarge: limit_mb: int +@dataclass(frozen=True, slots=True) +class UploadedFileExtensionNotAllowed: + extension: str + + @dataclass(frozen=True, slots=True) class UploadedFileBlockedExtension: extension: str @@ -56,7 +60,9 @@ class UploadedFileUnsafeFilename: filename: str -UploadValidationFailure = UploadedFileTooLarge | UploadedFileBlockedExtension | UploadedFileUnsafeFilename +UploadValidationFailure = ( + UploadedFileTooLarge | UploadedFileExtensionNotAllowed | UploadedFileBlockedExtension | UploadedFileUnsafeFilename +) def _file_size_bytes(file_source: bytes | BinaryIO) -> int: @@ -81,19 +87,35 @@ def check_upload_file_size( return None +def _normalized_extension(filename: str | None) -> str: + if not filename: + return "" + try: + return Path(safe_filename(filename)).suffix.lower() + except ValueError: + return "" + + +def check_allowed_extension( + filename: str | None, + allowed_extensions: tuple[str, ...] | None, +) -> UploadedFileExtensionNotAllowed | None: + if allowed_extensions is None: + return None + extension: Final = _normalized_extension(filename) + normalized_allowed: Final = frozenset(item.lower() for item in allowed_extensions) + if extension and extension in normalized_allowed: + return None + return UploadedFileExtensionNotAllowed(extension=extension) + + def check_blocked_extension( filename: str | None, - blocked_extensions: tuple[str, ...], + blocked_extensions: tuple[str, ...] | None, ) -> UploadedFileBlockedExtension | None: - if not blocked_extensions or not filename: + if not blocked_extensions: return None - try: - extension: Final = Path(safe_filename(filename)).suffix.lower() - except ValueError: - return None - # The uploaded name's extension is normalized above; blocked_extensions comes - # straight from config.yaml or the DB and is normalized here too, so a - # differently-cased entry (".EXE") still catches a lowercase upload. + extension: Final = _normalized_extension(filename) normalized_blocked: Final = frozenset(item.lower() for item in blocked_extensions) if extension and extension in normalized_blocked: return UploadedFileBlockedExtension(extension=extension) @@ -128,6 +150,17 @@ def raise_upload_validation_failure(failure: UploadValidationFailure) -> NoRetur param="file", code=413, ) + case UploadedFileExtensionNotAllowed(extension=extension): + raise ProxyException( + message=( + (f"File extension '{extension}'" if extension else "A file without an extension") + + " is not in this proxy's allowed_file_extensions setting. " + "The file was not forwarded to the provider." + ), + type="invalid_request_error", + param="file", + code=400, + ) case UploadedFileBlockedExtension(extension=extension): raise ProxyException( message=( diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py index 30b75a7b482..7cec3bac207 100644 --- a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py +++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/anthropic_passthrough_logging_handler.py @@ -216,11 +216,14 @@ class AnthropicPassthroughLoggingHandler: model=model, speed=AnthropicPassthroughLoggingHandler._cost_relevant_speed(request_body), ) - if response is None: - return None - AnthropicPassthroughLoggingHandler._recover_interrupted_stream_output_tokens( + if not isinstance(response, ModelResponse): + return response + recovered_usage: Final = AnthropicPassthroughLoggingHandler._recover_interrupted_stream_output_tokens( response=response, all_chunks=all_chunks, model=model ) + if recovered_usage is None: + return response + AnthropicPassthroughLoggingHandler._clear_placeholder_cost(response=response, usage=recovered_usage) return response @staticmethod @@ -259,7 +262,9 @@ class AnthropicPassthroughLoggingHandler: ) except Exception as e: # noqa: BLE001 # an uncostable partial stream still bills its tokens, at zero cost verbose_proxy_logger.warning( - "Anthropic passthrough: could not cost the partial usage of a failed stream (model=%s): %s", model, e + "Anthropic passthrough: could not cost the partial usage of an interrupted stream (model=%s): %s", + model, + e, ) return 0.0 @@ -359,7 +364,7 @@ class AnthropicPassthroughLoggingHandler: response: ModelResponse | TextCompletionResponse, all_chunks: Sequence[str | bytes], model: str, - ) -> None: + ) -> Usage | None: """ An Anthropic stream interrupted before its terminal ``message_delta`` (client disconnect) carries only the ``message_start`` ``output_tokens`` @@ -369,24 +374,24 @@ class AnthropicPassthroughLoggingHandler: untouched because their terminal ``message_delta`` short-circuits here. """ if not isinstance(response, ModelResponse): - return + return None if not AnthropicPassthroughLoggingHandler._stream_was_interrupted(all_chunks): - return + return None usage: Final = getattr(response, "usage", None) - if usage is None: - return + if not isinstance(usage, Usage): + return None output_text: Final = get_content_from_model_response(response) if not output_text: - return + return None try: recovered_output_tokens = litellm.token_counter(model=model, text=output_text, count_response_tokens=True) except Exception: verbose_proxy_logger.warning( "Could not re-tokenize interrupted stream output; keeping placeholder completion token count." ) - return + return None if recovered_output_tokens <= (usage.completion_tokens or 0): - return + return None usage.completion_tokens = recovered_output_tokens usage.total_tokens = (usage.prompt_tokens or 0) + recovered_output_tokens # Anthropic costing reads completion_tokens_details.text_tokens, so the @@ -395,6 +400,12 @@ class AnthropicPassthroughLoggingHandler: details: Final = getattr(usage, "completion_tokens_details", None) if details is not None and getattr(details, "text_tokens", None) is not None: details.text_tokens = recovered_output_tokens + return usage + + @staticmethod + def _clear_placeholder_cost(response: ModelResponse, usage: Usage) -> None: + usage.cost = None + response._hidden_params.pop("response_cost", None) # pyright: ignore[reportPrivateUsage] # no public accessor @staticmethod def _create_anthropic_response_logging_payload( diff --git a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_ai_live_passthrough_logging_handler.py b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_ai_live_passthrough_logging_handler.py index e26f5f57532..0ff02b29c58 100644 --- a/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_ai_live_passthrough_logging_handler.py +++ b/litellm/proxy/pass_through_endpoints/llm_provider_handlers/vertex_ai_live_passthrough_logging_handler.py @@ -5,18 +5,105 @@ Handles cost tracking and logging for Vertex AI Live API WebSocket passthrough e Supports different modalities: text, audio, video, and web search. """ +from collections.abc import Mapping, Sequence from datetime import datetime -from typing import Any, Final +from itertools import chain, pairwise +from types import MappingProxyType +from typing import Final, Literal, TypeAlias from litellm._logging import verbose_proxy_logger +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj +from litellm.llms.vertex_ai.gemini.grounding_requests import GroundingRequests, calculate_grounding_requests from litellm.proxy.pass_through_endpoints.llm_provider_handlers.base_passthrough_logging_handler import ( BasePassthroughLoggingHandler, ) from litellm.proxy.pass_through_endpoints.llm_provider_handlers.openai_passthrough_logging_handler import ( PassThroughEndpointLoggingTypedDict, ) -from litellm.types.utils import LlmProviders, ModelResponse, Usage -from litellm.utils import get_model_info +from litellm.types.utils import ( + CompletionTokensDetailsWrapper, + CostBreakdown, + LlmProviders, + ModelResponse, + PromptTokensDetailsWrapper, + Usage, +) + +_NO_GROUNDING: Final = GroundingRequests(web_search_requests=None, google_maps_grounding_requests=None) + +_AGGREGATED_FIELDS: Final = frozenset( + { + "promptTokenCount", + "candidatesTokenCount", + "totalTokenCount", + "toolUsePromptTokenCount", + "promptTokensDetails", + "candidatesTokensDetails", + } +) + + +def _detail_entries(raw: object) -> tuple[Mapping[str, object], ...]: + """Narrow one turn's ``*TokensDetails`` value to the entries that are actually shaped like one.""" + return tuple(entry for entry in raw if isinstance(entry, Mapping)) if isinstance(raw, Sequence) else () + + +def _grounding_metadata(websocket_messages: Sequence[object]) -> tuple[Mapping[str, object], ...]: + """Collect every ``serverContent.groundingMetadata`` a session emitted. + + Live reports grounding in the server frames, never in ``usageMetadata``, so the per-query + charge has to be counted here rather than derived from the token totals. + """ + return tuple( + metadata + for message in websocket_messages + if isinstance(message, Mapping) + for server_content in (message.get("serverContent"),) + if isinstance(server_content, Mapping) + for metadata in (server_content.get("groundingMetadata"),) + if isinstance(metadata, Mapping) + ) + + +def _turns(websocket_messages: Sequence[object]) -> tuple[tuple[object, ...], ...]: + """Split a session at every ``usageMetadata`` frame; frames after the last one never got their usage.""" + closes: Final = tuple( + index + 1 + for index, message in enumerate(websocket_messages) + if isinstance(message, Mapping) and isinstance(message.get("usageMetadata"), dict) + ) + return tuple(tuple(websocket_messages[start:end]) for start, end in pairwise((0, *closes))) + + +def _session_grounding_requests(websocket_messages: Sequence[object]) -> GroundingRequests: + per_turn: Final = tuple( + calculate_grounding_requests(_grounding_metadata(turn)) for turn in _turns(websocket_messages) + ) + web_search_requests: Final = sum(requests.web_search_requests or 0 for requests in per_turn) + google_maps_grounding_requests: Final = sum(requests.google_maps_grounding_requests or 0 for requests in per_turn) + return GroundingRequests( + web_search_requests=web_search_requests or None, + google_maps_grounding_requests=google_maps_grounding_requests or None, + ) + + +_SummedField: TypeAlias = Literal[ + "input_cost", + "output_cost", + "tool_usage_cost", + "cache_read_cost", + "cache_creation_cost", + "reasoning_cost", + "original_cost", + "discount_amount", + "margin_fixed_amount", + "margin_total_amount", +] + + +def _summed(breakdowns: Sequence[CostBreakdown], field: _SummedField) -> float | None: + values: Final = tuple(value for breakdown in breakdowns if (value := breakdown.get(field)) is not None) + return sum(values) if values else None class VertexAILivePassthroughLoggingHandler(BasePassthroughLoggingHandler): @@ -48,186 +135,110 @@ class VertexAILivePassthroughLoggingHandler(BasePassthroughLoggingHandler): """Return the LLM provider name.""" return LlmProviders.VERTEX_AI + @staticmethod + def _resolve_detail_counts( + details: Sequence[Mapping[str, object]], + declared_total: object, + ) -> tuple[tuple[str, int], ...]: + """ + Pair each of one turn's ``*TokensDetails`` entries with its token count. + + Live sometimes names the modality that carries the rest of a turn without a + ``tokenCount``, and reading the absent key as zero drops those tokens from the + breakdown, so real audio ends up priced as text. A lone unpriced entry therefore takes + whatever the turn's declared count leaves over. Two or more cannot be told apart, so + they are left out and the cost calculator charges the remainder as text. + """ + priced: Final = tuple( + (str(detail.get("modality", "TEXT")), count) + for detail in details + if isinstance(count := detail.get("tokenCount"), int) + ) + unpriced: Final = tuple( + str(detail.get("modality", "TEXT")) for detail in details if not isinstance(detail.get("tokenCount"), int) + ) + if len(unpriced) != 1 or not isinstance(declared_total, int): + return priced + residual: Final = declared_total - sum(count for _, count in priced) + return priced if residual <= 0 else (*priced, (unpriced[0], residual)) + + @staticmethod + def _sum_by_modality(counts: Sequence[tuple[str, int]]) -> Mapping[str, int]: + """Total the (modality, tokenCount) pairs of one or more turns per modality.""" + return MappingProxyType({modality: sum(c for m, c in counts if m == modality) for modality, _ in counts}) + + @staticmethod + def _merged_modality_totals( + snapshots: Sequence[Mapping[str, object]], + count_key: str, + details_key: str, + ) -> Mapping[str, int]: + """Total every turn's per-modality counts, so the breakdown adds up the way the totals do.""" + return VertexAILivePassthroughLoggingHandler._sum_by_modality( + tuple( + chain.from_iterable( + VertexAILivePassthroughLoggingHandler._resolve_detail_counts( + _detail_entries(snapshot.get(details_key)), snapshot.get(count_key) + ) + for snapshot in snapshots + ) + ) + ) + @staticmethod def _extract_usage_metadata_from_websocket_messages( - websocket_messages: list[dict], + websocket_messages: Sequence[object], ) -> dict | None: """ Extract and aggregate usage metadata from a list of WebSocket messages. + Live emits one ``usageMetadata`` per turn and Google charges per turn for every token in + the session context window, which is the current turn's tokens plus all accumulated + tokens from previous turns, so the turns add up rather than restating each other. See + the Live API note under https://cloud.google.com/vertex-ai/generative-ai/pricing. + Args: websocket_messages: List of WebSocket messages from the Live API Returns: Dictionary containing aggregated usage metadata, or None if not found """ - all_usage_metadata: Final = [] + snapshots: Final = tuple( + metadata + for message in websocket_messages + if isinstance(message, Mapping) + for metadata in (message.get("usageMetadata"),) + if isinstance(metadata, dict) + ) - # Collect all usage metadata messages - for message in websocket_messages: - if isinstance(message, dict) and "usageMetadata" in message: - all_usage_metadata.append(message["usageMetadata"]) - - if not all_usage_metadata: + if not snapshots: return None - # If only one usage metadata, return it as-is - if len(all_usage_metadata) == 1: - return all_usage_metadata[0] - - # Aggregate multiple usage metadata messages - aggregated: Final[dict[str, Any]] = { - "promptTokenCount": 0, - "candidatesTokenCount": 0, - "totalTokenCount": 0, - "promptTokensDetails": [], - "candidatesTokensDetails": [], + prompt_totals: Final = VertexAILivePassthroughLoggingHandler._merged_modality_totals( + snapshots, "promptTokenCount", "promptTokensDetails" + ) + candidate_totals: Final = VertexAILivePassthroughLoggingHandler._merged_modality_totals( + snapshots, "candidatesTokenCount", "candidatesTokensDetails" + ) + return { + **{key: value for key, value in snapshots[0].items() if key not in _AGGREGATED_FIELDS}, + "promptTokenCount": sum(snapshot.get("promptTokenCount", 0) for snapshot in snapshots), + "candidatesTokenCount": sum(snapshot.get("candidatesTokenCount", 0) for snapshot in snapshots), + "totalTokenCount": sum(snapshot.get("totalTokenCount", 0) for snapshot in snapshots), + "toolUsePromptTokenCount": sum(snapshot.get("toolUsePromptTokenCount", 0) for snapshot in snapshots), + "promptTokensDetails": [ + {"modality": modality, "tokenCount": count} for modality, count in prompt_totals.items() if count > 0 + ], + "candidatesTokensDetails": [ + {"modality": modality, "tokenCount": count} for modality, count in candidate_totals.items() if count > 0 + ], } - # Aggregate token counts - for usage in all_usage_metadata: - aggregated["promptTokenCount"] += usage.get("promptTokenCount", 0) - aggregated["candidatesTokenCount"] += usage.get("candidatesTokenCount", 0) - aggregated["totalTokenCount"] += usage.get("totalTokenCount", 0) - - # Aggregate token details by modality - modality_totals: Final = {} - - for usage in all_usage_metadata: - # Process prompt tokens details - for detail in usage.get("promptTokensDetails", []): - modality = detail.get("modality", "TEXT") - token_count = detail.get("tokenCount", 0) - - if modality not in modality_totals: - modality_totals[modality] = {"prompt": 0, "candidate": 0} - modality_totals[modality]["prompt"] += token_count - - # Process candidate tokens details - for detail in usage.get("candidatesTokensDetails", []): - modality = detail.get("modality", "TEXT") - token_count = detail.get("tokenCount", 0) - - if modality not in modality_totals: - modality_totals[modality] = {"prompt": 0, "candidate": 0} - modality_totals[modality]["candidate"] += token_count - - # Convert aggregated modality totals back to details format - for modality, totals in modality_totals.items(): - if totals["prompt"] > 0: - aggregated["promptTokensDetails"].append({"modality": modality, "tokenCount": totals["prompt"]}) - if totals["candidate"] > 0: - aggregated["candidatesTokensDetails"].append({"modality": modality, "tokenCount": totals["candidate"]}) - - # Add any additional fields from the first usage metadata - first_usage: Final = all_usage_metadata[0] - for key, value in first_usage.items(): - if key not in aggregated: - aggregated[key] = value - - return aggregated - - @staticmethod - def _calculate_live_api_cost( - model: str, - usage_metadata: dict, - custom_llm_provider: str = "vertex_ai", - ) -> float: - """ - Calculate cost for Vertex AI Live API based on usage metadata. - - Args: - model: The model name (e.g., "gemini-2.0-flash-live-preview-04-09") - usage_metadata: Usage metadata from the Live API response - custom_llm_provider: The LLM provider (default: "vertex_ai") - - Returns: - Total cost in USD - """ - try: - # Get model pricing information - model_info: Final = get_model_info(model=model, custom_llm_provider=custom_llm_provider) - - verbose_proxy_logger.debug("Vertex AI Live API model info for '%s': %s", model, model_info) - - # Check if pricing info is available - if not model_info or not model_info.get("input_cost_per_token"): - verbose_proxy_logger.error("No pricing info found for %s in local model pricing database", model) - return 0.0 - - total_cost = 0.0 - - # Extract token counts from usage metadata - prompt_token_count: Final = usage_metadata.get("promptTokenCount", 0) - candidates_token_count: Final = usage_metadata.get("candidatesTokenCount", 0) - - # Calculate base text token costs - input_cost_per_token: Final = model_info.get("input_cost_per_token", 0.0) - output_cost_per_token: Final = model_info.get("output_cost_per_token", 0.0) - - total_cost += prompt_token_count * input_cost_per_token - total_cost += candidates_token_count * output_cost_per_token - - # Handle modality-specific costs if present - prompt_tokens_details: Final = usage_metadata.get("promptTokensDetails", []) - candidates_tokens_details: Final = usage_metadata.get("candidatesTokensDetails", []) - - # Process prompt tokens by modality - for detail in prompt_tokens_details: - modality = detail.get("modality", "TEXT") - token_count = detail.get("tokenCount", 0) - - if modality == "AUDIO": - audio_cost_per_token = model_info.get("input_cost_per_audio_token", 0.0) - total_cost += token_count * audio_cost_per_token - elif modality == "VIDEO": - # Video tokens are typically per second, but we'll treat as per token for now - video_cost_per_token = model_info.get("input_cost_per_video_per_second", 0.0) - total_cost += token_count * video_cost_per_token - # TEXT tokens are already handled above - - # Process candidate tokens by modality - for detail in candidates_tokens_details: - modality = detail.get("modality", "TEXT") - token_count = detail.get("tokenCount", 0) - - if modality == "AUDIO": - audio_cost_per_token = model_info.get("output_cost_per_audio_token", 0.0) - total_cost += token_count * audio_cost_per_token - elif modality == "VIDEO": - # Video tokens are typically per second, but we'll treat as per token for now - video_cost_per_token = model_info.get("output_cost_per_video_per_second", 0.0) - total_cost += token_count * video_cost_per_token - # TEXT tokens are already handled above - - # Handle web search costs if present - tool_use_prompt_token_count: Final = usage_metadata.get("toolUsePromptTokenCount", 0) - if tool_use_prompt_token_count > 0: - # Web search typically has a fixed cost per request - web_search_cost: Final = model_info.get("web_search_cost_per_request", 0.0) - if isinstance(web_search_cost, (int, float)) and web_search_cost > 0: - total_cost += web_search_cost - else: - # Fallback to token-based pricing for tool use - total_cost += tool_use_prompt_token_count * input_cost_per_token - - verbose_proxy_logger.debug( - f"Vertex AI Live API cost calculation - Model: {model}, " - f"Prompt tokens: {prompt_token_count}, " - f"Candidate tokens: {candidates_token_count}, " - f"Total cost: ${total_cost:.6f}" - ) - - return total_cost - - except Exception as e: - verbose_proxy_logger.error("Error calculating Vertex AI Live API cost: %s", e) - return 0.0 - @staticmethod def _create_usage_object_from_metadata( usage_metadata: dict, model: str, + grounding_requests: GroundingRequests = _NO_GROUNDING, ) -> Usage: """ Create a LiteLLM Usage object from Live API usage metadata. @@ -235,48 +246,124 @@ class VertexAILivePassthroughLoggingHandler(BasePassthroughLoggingHandler): Args: usage_metadata: Usage metadata from the Live API response model: The model name + grounding_requests: The Search and Maps grounding requests summed over the session's + turns, matching the per-turn charge Returns: LiteLLM Usage object """ - prompt_tokens: Final = usage_metadata.get("promptTokenCount", 0) - completion_tokens: Final = usage_metadata.get("candidatesTokenCount", 0) - total_tokens: Final = usage_metadata.get("totalTokenCount", 0) + prompt_by_modality: Final = VertexAILivePassthroughLoggingHandler._sum_by_modality( + VertexAILivePassthroughLoggingHandler._resolve_detail_counts( + _detail_entries(usage_metadata.get("promptTokensDetails")), usage_metadata.get("promptTokenCount") + ) + ) + candidates_by_modality: Final = VertexAILivePassthroughLoggingHandler._sum_by_modality( + VertexAILivePassthroughLoggingHandler._resolve_detail_counts( + _detail_entries(usage_metadata.get("candidatesTokensDetails")), + usage_metadata.get("candidatesTokenCount"), + ) + ) - # Create modality-specific token details if available - prompt_tokens_details: Final = usage_metadata.get("promptTokensDetails", []) - candidates_tokens_details: Final = usage_metadata.get("candidatesTokensDetails", []) - - # Extract text tokens from details - text_prompt_tokens = 0 - text_completion_tokens = 0 - - for detail in prompt_tokens_details: - if detail.get("modality") == "TEXT": - text_prompt_tokens = detail.get("tokenCount", 0) - break - - for detail in candidates_tokens_details: - if detail.get("modality") == "TEXT": - text_completion_tokens = detail.get("tokenCount", 0) - break - - # If no text tokens found in details, use total counts - if text_prompt_tokens == 0: - text_prompt_tokens = prompt_tokens - if text_completion_tokens == 0: - text_completion_tokens = completion_tokens + prompt_tokens: Final = usage_metadata.get("promptTokenCount", 0) or sum(prompt_by_modality.values()) + completion_tokens: Final = usage_metadata.get("candidatesTokenCount", 0) or sum(candidates_by_modality.values()) return Usage( - prompt_tokens=text_prompt_tokens, - completion_tokens=text_completion_tokens, - total_tokens=total_tokens, + prompt_tokens=prompt_tokens, + completion_tokens=completion_tokens, + total_tokens=usage_metadata.get("totalTokenCount", 0) or (prompt_tokens + completion_tokens), + prompt_tokens_details=PromptTokensDetailsWrapper( + text_tokens=prompt_by_modality.get("TEXT"), + audio_tokens=prompt_by_modality.get("AUDIO"), + image_tokens=prompt_by_modality.get("IMAGE"), + video_tokens=prompt_by_modality.get("VIDEO"), + tool_use_tokens=usage_metadata.get("toolUsePromptTokenCount") or None, + web_search_requests=grounding_requests.web_search_requests, + google_maps_grounding_requests=grounding_requests.google_maps_grounding_requests, + ), + completion_tokens_details=CompletionTokensDetailsWrapper( + text_tokens=candidates_by_modality.get("TEXT"), + audio_tokens=candidates_by_modality.get("AUDIO"), + image_tokens=candidates_by_modality.get("IMAGE"), + video_tokens=candidates_by_modality.get("VIDEO"), + ), ) + def _session_usage(self, websocket_messages: Sequence[object], model: str) -> Usage | None: + usage_metadata: Final = self._extract_usage_metadata_from_websocket_messages(websocket_messages) + if usage_metadata is None: + return None + return self._create_usage_object_from_metadata( + usage_metadata=usage_metadata, + grounding_requests=_session_grounding_requests(websocket_messages), + model=model, + ) + + def _turn_cost( + self, + turn: Sequence[object], + model: str, + logging_obj: LiteLLMLoggingObj, + ) -> tuple[float, CostBreakdown] | None: + usage: Final = self._session_usage(turn, model) + if usage is None: + return None + cost: Final = logging_obj._response_cost_calculator( # pyright: ignore[reportPrivateUsage] # the call's own calculator keeps custom pricing and the deployment's region in step with the spend row + result=ModelResponse(model=model, usage=usage), + litellm_model_name=model, + ) + if cost is None: + return None + breakdown: Final = logging_obj.cost_breakdown + return None if breakdown is None else (cost, breakdown) + + def _session_cost( + self, + websocket_messages: Sequence[object], + model: str, + logging_obj: LiteLLMLoggingObj, + ) -> float | None: + """Price each turn on its own tokens and grounding, so two grounded turns pay the query fee twice. + + The fixed cost margin is a flat per-request fee, so the session's single spend row carries it once + rather than once per turn. + """ + turn_costs: Final = tuple(self._turn_cost(turn, model, logging_obj) for turn in _turns(websocket_messages)) + priced: Final = tuple(turn_cost for turn_cost in turn_costs if turn_cost is not None) + if not priced or len(priced) != len(turn_costs): + return None + breakdowns: Final = tuple(breakdown for _, breakdown in priced) + first: Final = breakdowns[0] + fixed_margin: Final = first.get("margin_fixed_amount") or 0.0 + duplicated_fixed_margin: Final = fixed_margin * (len(priced) - 1) + total_cost: Final = sum(cost for cost, _ in priced) - duplicated_fixed_margin + summed_margin_total: Final = _summed(breakdowns, "margin_total_amount") + margin_total_amount: Final = ( + None if summed_margin_total is None else summed_margin_total - duplicated_fixed_margin + ) + logging_obj.set_cost_breakdown( + input_cost=_summed(breakdowns, "input_cost") or 0.0, + output_cost=_summed(breakdowns, "output_cost") or 0.0, + total_cost=total_cost, + cost_for_built_in_tools_cost_usd_dollar=_summed(breakdowns, "tool_usage_cost") or 0.0, + original_cost=_summed(breakdowns, "original_cost"), + discount_percent=first.get("discount_percent"), + discount_amount=_summed(breakdowns, "discount_amount"), + margin_percent=first.get("margin_percent"), + margin_fixed_amount=first.get("margin_fixed_amount"), + margin_total_amount=margin_total_amount, + cache_read_cost=_summed(breakdowns, "cache_read_cost"), + cache_creation_cost=_summed(breakdowns, "cache_creation_cost"), + reasoning_cost=_summed(breakdowns, "reasoning_cost"), + service_tier=first.get("service_tier"), + data_residency=first.get("data_residency"), + vertex_location=first.get("vertex_location"), + ) + return total_cost + def vertex_ai_live_passthrough_handler( self, - websocket_messages: list[dict], - logging_obj, + websocket_messages: Sequence[object], + logging_obj: LiteLLMLoggingObj, url_route: str, start_time: datetime, end_time: datetime, @@ -300,34 +387,25 @@ class VertexAILivePassthroughLoggingHandler(BasePassthroughLoggingHandler): """ try: # Extract model from request body or kwargs - model: Final = kwargs.get("model", "gemini-2.0-flash-live-preview-04-09") + requested_model: Final = kwargs.get("model") + model: Final = ( + requested_model if isinstance(requested_model, str) else "gemini-2.0-flash-live-preview-04-09" + ) custom_llm_provider: Final = kwargs.get("custom_llm_provider", "vertex_ai") verbose_proxy_logger.debug( "Vertex AI Live API model: %s, custom_llm_provider: %s", model, custom_llm_provider ) - # Extract usage metadata from WebSocket messages - usage_metadata: Final = self._extract_usage_metadata_from_websocket_messages(websocket_messages) + usage: Final = self._session_usage(websocket_messages, model) - if not usage_metadata: + if usage is None: verbose_proxy_logger.warning("No usage metadata found in Vertex AI Live API WebSocket messages") return { "result": None, "kwargs": kwargs, } - # Calculate cost using Live API specific pricing - response_cost: Final = self._calculate_live_api_cost( - model=model, - usage_metadata=usage_metadata, - custom_llm_provider=custom_llm_provider, - ) - - # Create Usage object for standard LiteLLM logging - usage: Final = self._create_usage_object_from_metadata( - usage_metadata=usage_metadata, - model=model, - ) + response_cost: Final = self._session_cost(websocket_messages, model, logging_obj) # Create a mock ModelResponse for standard logging litellm_model_response: Final = ModelResponse( @@ -338,9 +416,9 @@ class VertexAILivePassthroughLoggingHandler(BasePassthroughLoggingHandler): usage=usage, choices=[], ) + if response_cost is not None: + litellm_model_response._hidden_params["response_cost"] = response_cost # pyright: ignore[reportPrivateUsage] # the logger reads the cost off the response's hidden params; the constructor's hidden_params kwarg is reset by pydantic - # Update kwargs with cost information - kwargs["response_cost"] = response_cost kwargs["model"] = model kwargs["custom_llm_provider"] = custom_llm_provider @@ -348,12 +426,15 @@ class VertexAILivePassthroughLoggingHandler(BasePassthroughLoggingHandler): import re allowed_pattern: Final = re.compile(r"^[A-Za-z0-9._\-:]+$") - safe_model: Final = model if isinstance(model, str) and allowed_pattern.match(model) else "[REDACTED]" + safe_model: Final = model if allowed_pattern.match(model) else "[REDACTED]" verbose_proxy_logger.debug( - f"Vertex AI Live API passthrough cost tracking - " - f"Model: {safe_model}, Cost: ${response_cost:.6f}, " - f"Prompt tokens: {usage.prompt_tokens}, " - f"Completion tokens: {usage.completion_tokens}" + "Vertex AI Live API passthrough cost tracking - Model: %s, " + "Prompt tokens: %s %s, Completion tokens: %s %s", + safe_model, + usage.prompt_tokens, + usage.prompt_tokens_details, + usage.completion_tokens, + usage.completion_tokens_details, ) return { diff --git a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py index ea4ede7e513..b66c295d1aa 100644 --- a/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py +++ b/litellm/proxy/pass_through_endpoints/pass_through_endpoints.py @@ -2090,6 +2090,22 @@ def _rewrite_vertex_live_setup_model(text_data: str, setup_model_rewriter: Calla return json.dumps({**message, "setup": {**setup, "model": rewritten_model}}) # mutable-ok: one-shot json payload +def _resolved_vertex_live_setup( + setup_data: Mapping[str, object], setup_model_rewriter: Callable[[str], str] | None +) -> Mapping[str, object]: + """ + Give the model extractor the same fully qualified path the upstream will receive. + + Clients may name a bare gateway alias, which the rewriter turns into a ``projects/...`` path before + it reaches Vertex. The extractor only reads a path containing ``/models/``, so running it on the raw + frame logs the session as ``unknown`` at no cost, which is precisely the supported client form + """ + setup_model: Final = setup_data.get("model") + if setup_model_rewriter is None or not isinstance(setup_model, str): + return setup_data + return {**setup_data, "model": setup_model_rewriter(setup_model)} + + def _truncated_close_reason(reason: str) -> str: """ Fit a close reason inside the byte budget a WebSocket close frame allows, without splitting a character @@ -2314,7 +2330,9 @@ async def websocket_passthrough_request( setup_data, ) if isinstance(setup_data, dict) and "model" in setup_data: - extracted_model = _extract_model_from_vertex_ai_setup(setup_data) + extracted_model = _extract_model_from_vertex_ai_setup( + _resolved_vertex_live_setup(setup_data, setup_model_rewriter) + ) if extracted_model: kwargs["model"] = extracted_model kwargs["custom_llm_provider"] = "vertex_ai-language-models" diff --git a/litellm/proxy/pass_through_endpoints/streaming_handler.py b/litellm/proxy/pass_through_endpoints/streaming_handler.py index 4be0235adbb..b310fc661c4 100644 --- a/litellm/proxy/pass_through_endpoints/streaming_handler.py +++ b/litellm/proxy/pass_through_endpoints/streaming_handler.py @@ -270,6 +270,24 @@ class PassThroughStreamingHandler: - Vertex AI - OpenAI """ + from litellm.llms.anthropic.experimental_pass_through.messages.streaming_iterator import ( + _is_message_stop_chunk, # pyright: ignore[reportPrivateUsage] # both native stream paths share terminal-event detection + _is_provider_error_chunk, # pyright: ignore[reportPrivateUsage] # provider errors must not become cache evidence + ) + + # Transport reads can split event names and JSON payloads. Recognize terminal + # events only after the shared SSE framer has reassembled the collected bytes. + complete_frames, incomplete_tail = split_complete_sse_frames( + b"".join(raw_bytes) if endpoint_type == EndpointType.ANTHROPIC else b"" + ) + litellm_logging_obj.model_call_details[ # rebind-ok: stamp evidence on the per-request state read by callbacks + "prompt_cache_response_complete" + ] = ( + endpoint_type == EndpointType.ANTHROPIC + and not incomplete_tail.strip() + and _is_message_stop_chunk(complete_frames) + and not _is_provider_error_chunk(complete_frames) + ) try: ( standard_logging_response_object, diff --git a/litellm/proxy/policy_engine/pipeline_executor.py b/litellm/proxy/policy_engine/pipeline_executor.py index ad45781d5d2..ed193c7f434 100644 --- a/litellm/proxy/policy_engine/pipeline_executor.py +++ b/litellm/proxy/policy_engine/pipeline_executor.py @@ -58,15 +58,6 @@ class UndeliverableStreamRewrite(Exception): self.guardrail_name: Final = guardrail_name -class UnappliableRequestRewrite(Exception): - def __init__(self, guardrail_name: str) -> None: - super().__init__( - f"Guardrail '{guardrail_name}' rewrote the request in a way this endpoint cannot apply, " - "so the request was rejected rather than sent unrewritten" - ) - self.guardrail_name: Final = guardrail_name - - def _tool_call_shape(tool_call: object) -> tuple[object, object]: plain: Final = tool_call.model_dump() if isinstance(tool_call, BaseModel) else tool_call function: Final = plain.get("function") if isinstance(plain, Mapping) else None diff --git a/litellm/proxy/prisma_migration.py b/litellm/proxy/prisma_migration.py index 1b95d24c011..7e3aff75cef 100644 --- a/litellm/proxy/prisma_migration.py +++ b/litellm/proxy/prisma_migration.py @@ -14,6 +14,8 @@ sys.path.insert(0, os.path.abspath("./")) from typing import Final +from litellm_proxy_extras.prisma_toolchain import resolve_prisma_argv + from litellm._logging import verbose_proxy_logger from litellm.proxy.proxy_cli import run_server from litellm.secret_managers.main import str_to_bool @@ -29,7 +31,7 @@ def main() -> int: run_server(run_server_args, standalone_mode=False) verbose_proxy_logger.info("Running 'prisma generate'...") - result: Final = subprocess.run(("prisma", "generate"), capture_output=True, text=True) + result: Final = subprocess.run(resolve_prisma_argv(("prisma", "generate")), capture_output=True, text=True) verbose_proxy_logger.info("'prisma generate' stdout: %s", result.stdout) if result.returncode != 0: diff --git a/litellm/proxy/proxy_cli.py b/litellm/proxy/proxy_cli.py index c2d60cd5488..01a3da08998 100644 --- a/litellm/proxy/proxy_cli.py +++ b/litellm/proxy/proxy_cli.py @@ -1267,73 +1267,69 @@ def run_server( flush=True, ) sys.exit(1) - try: - from litellm.secret_managers.main import get_secret + from litellm.secret_managers.main import get_secret - connection_url_params: Final = _build_db_connection_url_params( - connection_limit=db_connection_pool_limit, - pool_timeout=db_connection_timeout, - connect_timeout=db_connect_timeout, - socket_timeout=db_socket_timeout, - disable_prepared_statements=db_disable_prepared_statements, - extra_params=db_extra_connection_params, + connection_url_params: Final = _build_db_connection_url_params( + connection_limit=db_connection_pool_limit, + pool_timeout=db_connection_timeout, + connect_timeout=db_connect_timeout, + socket_timeout=db_socket_timeout, + disable_prepared_statements=db_disable_prepared_statements, + extra_params=db_extra_connection_params, + ) + lifetime_params: Final = idle_lifetime_params(general_settings.get("database_max_idle_connection_lifetime")) + if os.getenv("DATABASE_URL", None) is not None: + database_url = get_secret("DATABASE_URL", default_value=None) + resolved_url: Final[str | None] = str(database_url) if database_url else None + pg_options: Final[str] = _pg_options_with_timeouts( + _url_query_value(resolved_url, "options"), + db_statement_timeout, + db_lock_timeout, ) - lifetime_params: Final = idle_lifetime_params( - general_settings.get("database_max_idle_connection_lifetime") + writer_url: Final = ( + _with_query_value(resolved_url, "options", pg_options) + if resolved_url and pg_options + else resolved_url ) - if os.getenv("DATABASE_URL", None) is not None: - database_url = get_secret("DATABASE_URL", default_value=None) - resolved_url: Final[str | None] = str(database_url) if database_url else None - pg_options: Final[str] = _pg_options_with_timeouts( - _url_query_value(resolved_url, "options"), - db_statement_timeout, - db_lock_timeout, - ) - writer_url: Final = ( - _with_query_value(resolved_url, "options", pg_options) - if resolved_url and pg_options - else resolved_url - ) - modified_url = append_query_params( - writer_url, - connection_url_params, - ) - os.environ["DATABASE_URL"] = translate_libpq_ssl_params( - add_missing_query_params(modified_url, lifetime_params) - ) - if os.getenv("DIRECT_URL", None) is not None: - database_url = os.getenv("DIRECT_URL") - modified_url = append_query_params(database_url, connection_url_params) - os.environ["DIRECT_URL"] = translate_libpq_ssl_params( - add_missing_query_params(modified_url, lifetime_params) - ) - # The reader pool is a real pool against the same configured cap, so it - # gets the allowlisted pool params. Schema-affecting ones, including any - # the operator smuggled in through database_extra_connection_params, stay - # on the writer. Anything pinned on the replica URL wins, unlike the - # writer where the config is applied on top. - read_replica_url: Final[str | None] = os.getenv("DATABASE_URL_READ_REPLICA") - if read_replica_url: - reader_options: Final[str] = _pg_options_with_timeouts( - _url_query_value(read_replica_url, "options"), - db_statement_timeout, - db_lock_timeout, - ) - os.environ["DATABASE_URL_READ_REPLICA"] = translate_libpq_ssl_params( + modified_url = append_query_params( + writer_url, + connection_url_params, + ) + os.environ["DATABASE_URL"] = translate_libpq_ssl_params( + add_missing_query_params(modified_url, lifetime_params) + ) + if os.getenv("DIRECT_URL", None) is not None: + database_url = os.getenv("DIRECT_URL") + modified_url = append_query_params(database_url, connection_url_params) + os.environ["DIRECT_URL"] = translate_libpq_ssl_params( + add_missing_query_params(modified_url, lifetime_params) + ) + # The reader pool is a real pool against the same configured cap, so it + # gets the allowlisted pool params. Schema-affecting ones, including any + # the operator smuggled in through database_extra_connection_params, stay + # on the writer. Anything pinned on the replica URL wins, unlike the + # writer where the config is applied on top. + read_replica_url: Final[str | None] = os.getenv("DATABASE_URL_READ_REPLICA") + if read_replica_url: + reader_options: Final[str] = _pg_options_with_timeouts( + _url_query_value(read_replica_url, "options"), + db_statement_timeout, + db_lock_timeout, + ) + os.environ["DATABASE_URL_READ_REPLICA"] = translate_libpq_ssl_params( + add_missing_query_params( add_missing_query_params( - add_missing_query_params( - _with_query_value(read_replica_url, "options", reader_options) - if reader_options - else read_replica_url, - reader_shareable_params(connection_url_params), - ), - lifetime_params, - ) + _with_query_value(read_replica_url, "options", reader_options) + if reader_options + else read_replica_url, + reader_shareable_params(connection_url_params), + ), + lifetime_params, ) - subprocess.run(["prisma"], capture_output=True) - is_prisma_runnable = True - except FileNotFoundError: - is_prisma_runnable = False + ) + from litellm_proxy_extras.prisma_toolchain import prisma_cli_available + + is_prisma_runnable: Final = prisma_cli_available() if is_prisma_runnable: from litellm.proxy.db.check_migration import check_prisma_schema_diff @@ -1382,7 +1378,8 @@ def run_server( ) else: print( - f"Unable to connect to DB. DATABASE_URL found in environment, but prisma package not found." # noqa: F541 + "Unable to connect to DB. DATABASE_URL found in environment, but the prisma CLI is neither on " + "PATH nor importable as a package." ) pgbouncer_settings: Final = PgBouncerSettings() upstream_database_url: Final = os.getenv("DATABASE_URL") diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 9d258f6fd92..63c62099b25 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -250,7 +250,7 @@ import litellm._redis from litellm import Router from litellm._logging import _redact_string, verbose_proxy_logger, verbose_router_logger from litellm.caching.caching import DualCache, RedisCache -from litellm.caching.redis_cache import RedisCircuitBreakerOpenError +from litellm.caching.redis_cache import RedisCircuitBreakerOpenError, is_redis_timeout_failure from litellm.caching.redis_cluster_cache import RedisClusterCache from litellm.constants import ( _REALTIME_BODY_CACHE_SIZE, @@ -274,6 +274,8 @@ from litellm.constants import ( PROXY_BUDGET_RESCHEDULER_MAX_TIME, PROXY_BUDGET_RESCHEDULER_MIN_TIME, PROXY_CONFIG_RELOAD_INTERVAL_SECONDS, + REALTIME_SESSION_FAILURE_LOGGED_KEY, + REALTIME_SESSION_SUCCESS_LOGGED_KEY, ROUTER_SETTINGS_MANAGED_OUTSIDE_CONFIG, USER_SPEND_ALERTS_JOB_ID, WEEKLY_SPEND_REPORT_JOB_ID, @@ -353,6 +355,7 @@ from litellm.proxy.common_utils.auth_cache_invalidation_pubsub import ( AuthCacheInvalidationSubscriber, ) from litellm.proxy.common_utils.callback_utils import initialize_callbacks_on_proxy +from litellm.proxy.common_utils.config_includes import resolve_include_file_path, resolve_includes from litellm.proxy.common_utils.config_sync_pubsub import ConfigSyncSubscriber from litellm.proxy.common_utils.debug_utils import init_verbose_loggers from litellm.proxy.common_utils.debug_utils import router as debugging_endpoints_router @@ -364,6 +367,7 @@ from litellm.proxy.common_utils.healthy_model_filter import ( get_hidden_unhealthy_model_names, is_healthy_only_listing_default, ) +from litellm.proxy.common_utils.html_forms.default_credentials_hint import should_hide_default_credentials_hint from litellm.proxy.common_utils.html_forms.ui_login import build_ui_login_form from litellm.proxy.common_utils.http_parsing_utils import ( _read_request_body, @@ -371,10 +375,7 @@ from litellm.proxy.common_utils.http_parsing_utils import ( check_file_size_under_limit, get_form_data, ) -from litellm.proxy.common_utils.load_config_utils import ( - get_config_file_contents_from_gcs, - get_file_contents_from_s3, -) +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 ( ClaudeCodeRoutingNames, @@ -448,7 +449,10 @@ from litellm.proxy.db.proxy_worker_heartbeat import ( ProxyWorkerHeartbeat, ) from litellm.proxy.db.spend_counter_reseed import END_USER_COUNTER_PREFIX, SpendCounterReseed -from litellm.proxy.discovery_endpoints import ui_discovery_endpoints_router +from litellm.proxy.discovery_endpoints import ( + agent_skills_discovery_router, + ui_discovery_endpoints_router, +) from litellm.proxy.fine_tuning_endpoints.endpoints import router as fine_tuning_router from litellm.proxy.fine_tuning_endpoints.endpoints import set_fine_tuning_config from litellm.proxy.google_endpoints.endpoints import router as google_router @@ -3452,8 +3456,10 @@ async def _invalidate_spend_counter(counter_key: str): async def _apply_spend_counter_increments(pending: Sequence[PendingSpendIncrement]) -> None: try: await increment_spend_counters_pipeline(pending=pending) - except RedisCircuitBreakerOpenError: - return + except Exception as e: + if isinstance(e, RedisCircuitBreakerOpenError) or is_redis_timeout_failure(e): + return + raise async def increment_spend_counters_pipeline(pending: Sequence[PendingSpendIncrement]) -> None: @@ -4807,12 +4813,12 @@ class ProxyConfig: if config is None: raise Exception("Config cannot be None or Empty.") # Process includes - config = self._process_includes(config=config, base_dir=os.path.dirname(os.path.abspath(file_path or ""))) + config = await self._process_includes(config=config, config_file_path=os.path.abspath(file_path or "")) # verbose_proxy_logger.debug(f"loaded config={json.dumps(config, indent=4)}") return config - def _process_includes(self, config: dict, base_dir: str) -> dict: + async def _process_includes(self, config: dict, config_file_path: str) -> dict: """ Process includes by appending their contents to the main config @@ -4827,29 +4833,21 @@ class ProxyConfig: callbacks: ["prometheus"] ``` """ - if "include" not in config: - return config - if not isinstance(config["include"], list): - raise ValueError("'include' must be a list of file paths") + included_config_adapter: Final = TypeAdapter(dict[str, object]) - # Load and append all included files - for include_file in config["include"]: - file_path = os.path.join(base_dir, include_file) + def resolve(include_file: str, declared_in: str) -> str: + return resolve_include_file_path(include_file, declared_in, config_file_path) + + async def read_included(file_path: str) -> Mapping[str, object]: if not os.path.exists(file_path): raise FileNotFoundError(f"Included file not found: {file_path}") + try: + return included_config_adapter.validate_python(self._load_yaml_file(file_path)) + except ValidationError as e: + raise ValueError(f"Included config file is not a YAML mapping: {file_path}") from e - included_config = self._load_yaml_file(file_path) - # Simply update/extend the main config with included config - for key, value in included_config.items(): - if isinstance(value, list) and key in config: - config[key].extend(value) - else: - config[key] = value - - # Remove the include directive - del config["include"] - return config + return await resolve_includes(config=config, location=config_file_path, resolve=resolve, read=read_included) async def save_config(self, new_config: dict, include_env_vars: bool = False): global prisma_client, general_settings, user_config_file_path, store_model_in_db @@ -5207,15 +5205,19 @@ class ProxyConfig: global prisma_client, store_model_in_db # Load existing config - if os.environ.get("LITELLM_CONFIG_BUCKET_NAME") is not None: - bucket_name: Final = os.environ.get("LITELLM_CONFIG_BUCKET_NAME") + bucket_name: Final = os.environ.get("LITELLM_CONFIG_BUCKET_NAME") + if bucket_name is not None: object_key: Final = os.environ.get("LITELLM_CONFIG_BUCKET_OBJECT_KEY") bucket_type: Final = os.environ.get("LITELLM_CONFIG_BUCKET_TYPE") verbose_proxy_logger.debug("bucket_name: %s, object_key: %s", bucket_name, object_key) - if bucket_type == "gcs": - config = await get_config_file_contents_from_gcs(bucket_name=bucket_name, object_key=object_key) - else: - config = get_file_contents_from_s3(bucket_name=bucket_name, object_key=object_key) + if object_key is None: + raise Exception("LITELLM_CONFIG_BUCKET_OBJECT_KEY must be set to load the config from a bucket.") + + config = await get_config_from_bucket( + bucket_type=bucket_type, + bucket_name=bucket_name, + object_key=object_key, + ) if config is None: raise Exception("Unable to load config from given source.") @@ -7077,6 +7079,9 @@ class ProxyConfig: if "max_file_size_mb" not in self._yaml_general_settings_keys: general_settings["max_file_size_mb"] = _general_settings.get("max_file_size_mb") + if "allowed_file_extensions" not in self._yaml_general_settings_keys: + general_settings["allowed_file_extensions"] = _general_settings.get("allowed_file_extensions") + if "blocked_file_extensions" not in self._yaml_general_settings_keys: general_settings["blocked_file_extensions"] = _general_settings.get("blocked_file_extensions") @@ -9550,6 +9555,7 @@ class ProxyStartupEvent: gate the first duration window. """ await generate_key_helper_fn( + llm_router=llm_router, request_type="user", table_name="user", user_id=LITELLM_PROXY_BUDGET_NAME, @@ -11905,6 +11911,13 @@ async def _release_realtime_budget_reservation(user_api_key_dict: UserAPIKeyAuth ) +async def _release_realtime_max_parallel_slot(user_api_key_dict: UserAPIKeyAuth) -> None: + release_like_http_disconnect: Final = ( + proxy_logging_obj._arelease_max_parallel_requests_on_disconnect # pyright: ignore[reportPrivateUsage] # shared + ) + await release_like_http_disconnect(user_api_key_dict) + + async def _reject_realtime_session( websocket: WebSocket, user_api_key_dict: UserAPIKeyAuth, @@ -11924,6 +11937,7 @@ async def _reject_realtime_session( await websocket.close(code=code, reason=reason) finally: await _release_realtime_budget_reservation(user_api_key_dict) + await _release_realtime_max_parallel_slot(user_api_key_dict) @app.websocket("/openai/v1/realtime") @@ -12027,6 +12041,9 @@ async def realtime_websocket_endpoint( websocket, user_api_key_dict, code=1011, reason="Pre-call error", error_message=str(e) ) return + except BaseException: + await _release_realtime_max_parallel_slot(user_api_key_dict) + raise # Phase 2: route to upstream LLM. try: @@ -12056,12 +12073,10 @@ async def realtime_websocket_endpoint( except Exception: # noqa: BLE001 # the lower layer may have closed the socket already; closing twice is not an error verbose_proxy_logger.debug("Could not close realtime client websocket; it is already gone") finally: - from litellm.litellm_core_utils.realtime_streaming import ( - REALTIME_SESSION_SUCCESS_LOGGED_KEY, - ) - if not litellm_logging_obj.model_call_details.get(REALTIME_SESSION_SUCCESS_LOGGED_KEY): await _release_realtime_budget_reservation(user_api_key_dict) + if not litellm_logging_obj.model_call_details.get(REALTIME_SESSION_FAILURE_LOGGED_KEY): + await _release_realtime_max_parallel_slot(user_api_key_dict) ###################################################################### @@ -15045,6 +15060,13 @@ def _get_proxy_model_info(model: dict) -> dict: return _translate_model_name_for_response(model) +def _model_info_json_response(data: Sequence[Mapping[str, object]] | Mapping[str, object]) -> Response: + return Response( + content=orjson.dumps({"data": data}, default=jsonable_encoder, option=orjson.OPT_NON_STR_KEYS), + media_type="application/json", + ) + + @router.get( "/model/info", tags=["model management"], @@ -15092,7 +15114,7 @@ async def model_info_v1( `model_info.direct_access` when the proxy database is connected. Returns: - Returns a dictionary containing information about each model. + A JSON response whose `data` list holds one entry per model. Example Response: ```json @@ -15140,7 +15162,7 @@ async def model_info_v1( deployment_dict=_deployment_info_dict, excluded_keys={"litellm_credential_name"}, ) - return {"data": _deployment_info_dict} + return _model_info_json_response(_deployment_info_dict) if llm_model_list is None: raise HTTPException( @@ -15191,7 +15213,7 @@ async def model_info_v1( llm_router=llm_router, user_api_key_dict=user_api_key_dict, ) - return {"data": single_model_list} + return _model_info_json_response(single_model_list) # Return router deployments (same source as /v2/model/info), not wildcard- # expanded model names from get_complete_model_list(). Team-scoped rows @@ -15259,7 +15281,7 @@ async def model_info_v1( visible_models: Final = [model for model in all_models if model.get("model_name") not in hidden_names] verbose_proxy_logger.debug("all_models: %s", visible_models) - return {"data": visible_models} + return _model_info_json_response(visible_models) @router.get( @@ -15828,10 +15850,7 @@ async def fallback_login(request: Request): from fastapi.responses import HTMLResponse - hide_default_credentials_hint: Final = ( - os.getenv("LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", "false").lower() == "true" - or general_settings.get("hide_default_credentials_hint", False) is True - ) + hide_default_credentials_hint: Final = should_hide_default_credentials_hint(general_settings) return HTMLResponse( content=build_ui_login_form( show_deprecation_banner=False, @@ -16281,6 +16300,7 @@ async def _generate_onboarding_ui_session_token(user_obj: _UserTableRow) -> str: global master_key, general_settings response: Final = await generate_key_helper_fn( + llm_router=llm_router, request_type="key", **{ "user_role": user_obj.user_role, @@ -17048,6 +17068,7 @@ _GENERAL_SETTINGS_CONFIG_LIST_FIELD_TYPES: Final[Mapping[str, str]] = MappingPro "max_request_size_mb": "Integer", "max_batch_file_size_mb": "Integer", "max_file_size_mb": "Integer", + "allowed_file_extensions": "List", "blocked_file_extensions": "List", "max_response_size_mb": "Integer", "proxy_config_reload_interval_seconds": "Integer", @@ -18807,6 +18828,7 @@ app.include_router(user_agent_analytics_router) app.include_router(gateway_request_router) app.include_router(enterprise_router) app.include_router(ui_discovery_endpoints_router) +app.include_router(agent_skills_discovery_router) # Eager: /models/{name}:method overlaps with the OpenAI /models endpoint. app.include_router(google_router) diff --git a/litellm/proxy/schema.prisma b/litellm/proxy/schema.prisma index 7d521d54791..dd7967aafe3 100644 --- a/litellm/proxy/schema.prisma +++ b/litellm/proxy/schema.prisma @@ -659,12 +659,14 @@ model LiteLLM_SpendLogs { mcp_namespaced_tool_name String? agent_id String? proxy_server_request Json? @default("{}") + litellm_call_id String? created_at DateTime @default(now()) @map("created_at") updated_at DateTime @default(now()) @updatedAt @map("updated_at") @@index([startTime]) @@index([startTime, request_id]) @@index([end_user]) @@index([session_id]) + @@index([litellm_call_id]) } model LiteLLM_BudgetWindowSpend { diff --git a/litellm/proxy/spend_tracking/spend_management_endpoints.py b/litellm/proxy/spend_tracking/spend_management_endpoints.py index 8cfb6354dd0..0ec2788fbaa 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 itertools import groupby from types import MappingProxyType @@ -17,6 +18,7 @@ from typing import ( TypeAlias, TypedDict, TypeVar, + cast, # noqa: TID251 # custom-logger and cold-storage payloads are untyped JSON ) import fastapi @@ -75,6 +77,7 @@ _SPEND_LOG_LIST_COLUMNS: Final = """ cache_hit, cache_key, request_tags, team_id, organization_id, end_user, requester_ip_address, session_id, status, mcp_namespaced_tool_name, agent_id, + litellm_call_id, COALESCE(request_duration_ms, (EXTRACT(EPOCH FROM ("endTime" - "startTime")) * 1000)::INTEGER) AS request_duration_ms """ @@ -91,9 +94,9 @@ class _SupportsModelDump(Protocol): def model_dump(self) -> Mapping[str, object]: ... -class _SpendLogOwnershipRow(Protocol): - user: str | None - team_id: str | None +class _SpendLogOwnerRow(TypedDict): + user: ReadOnly[str | None] + team_id: ReadOnly[str | None] class _ActivityRow(TypedDict): @@ -330,12 +333,37 @@ async def _find_spend_logs( return rows -async def _find_spend_log_row(prisma_client: PrismaClient, request_id: str) -> _SpendLogOwnershipRow | None: - """Read the single spend log row identified by ``request_id``.""" - return await _spend_logs_table(prisma_client).find_unique( - where={"request_id": request_id}, - include=None, - ) +class _RequestIdEquals(TypedDict): + request_id: ReadOnly[str] + + +class _LitellmCallIdEquals(TypedDict): + litellm_call_id: ReadOnly[str] + + +def _request_id_or_call_id_clause(request_id: str) -> tuple[_RequestIdEquals, _LitellmCallIdEquals]: + request_id_clause: Final[_RequestIdEquals] = {"request_id": request_id} + call_id_clause: Final[_LitellmCallIdEquals] = {"litellm_call_id": request_id} + return (request_id_clause, call_id_clause) + + +async def _find_spend_log_owners(prisma_client: PrismaClient, request_id: str) -> Sequence[_SpendLogOwnerRow]: + """Read the distinct ``(user, team_id)`` owner pairs across every spend log row + identified by ``request_id`` or ``litellm_call_id``. + + ``litellm_call_id`` is populated from the client-settable ``x-litellm-call-id`` + request header, so it is not guaranteed unique to one tenant: any number of rows + can match one id. The read is uncapped because a flood of another tenant's rows + carrying the caller's id could otherwise push the caller's own owner pair past a + row-sample cap and lock them out of their own lookup. + """ + sql_query: Final = """ + SELECT DISTINCT "user", team_id + FROM "LiteLLM_SpendLogs" + WHERE request_id = $1 OR litellm_call_id = $1 + """ + owners: Final[Sequence[_SpendLogOwnerRow] | None] = await _query_raw_or_none(prisma_client, sql_query, request_id) + return owners if owners is not None else () async def _count_spend_logs(prisma_client: PrismaClient, where: Mapping[str, object]) -> int: @@ -2599,10 +2627,11 @@ async def ui_view_spend_logs( if max_spend is not None: where_conditions["spend"]["lte"] = max_spend # A request_id lookup drops the date window, so a non-admin could otherwise - # reach any single row by id; require they own it, mirroring the detail - # endpoint. That ownership check fully authorizes the one row, so the - # general scoping below is skipped for id lookups. Scoped to the UI route - # so the public v2 contract is unchanged. + # reach any single row by id; require they own one of the matches, mirroring + # the detail endpoint, and keep the general scoping below so a colliding + # foreign row is filtered out rather than served or allowed to deny the + # caller their own row. Scoped to the UI route so the public v2 contract is + # unchanged. if request_id is not None and not is_v2 and not is_admin_view: await _assert_user_can_view_request_id( prisma_client=prisma_client, @@ -2610,10 +2639,9 @@ async def ui_view_spend_logs( request_id=request_id, ) user_scope_applies: Final = ( - not is_request_id_lookup - and not is_admin_view + not is_admin_view and team_id is None - and _can_user_view_spend_log(user_api_key_dict=user_api_key_dict) + and (is_request_id_lookup or _can_user_view_spend_log(user_api_key_dict=user_api_key_dict)) ) permitted_team_ids: Final = ( await _get_permitted_team_ids_for_spend_logs_or_empty( @@ -2626,7 +2654,7 @@ async def ui_view_spend_logs( explicit_user_requires_caller_scope: Final = ( user_scope_applies and not permitted_team_ids and user_id is not None ) - if not is_request_id_lookup and not is_admin_view: + if not is_admin_view: if team_id is not None: can_view_team: Final = await _can_team_member_view_log( prisma_client=prisma_client, @@ -2696,7 +2724,6 @@ async def ui_view_spend_logs( ("team_id", "team_id"), ('"user"', "user"), ("api_key", "api_key"), - ("request_id", "request_id"), ("model", "model"), ("model_id", "model_id"), ("model_group", "model_group"), @@ -2708,6 +2735,13 @@ async def ui_view_spend_logs( sql_params.append(val) p += 1 + request_id_filter: Final = where_conditions.get("request_id") + exact_request_id_first: Final = f"(request_id = ${p}) DESC, " if isinstance(request_id_filter, str) else "" + if isinstance(request_id_filter, str): + sql_conditions.append(f"(request_id = ${p} OR litellm_call_id = ${p})") + sql_params.append(request_id_filter) + p += 1 + # Multi-team OR filter: (user = $X OR team_id = ANY($Y)) if permitted_team_ids: or_clause: Final = f'("user" = ${p} OR team_id = ANY(${p + 1}::text[]))' @@ -2837,7 +2871,7 @@ async def ui_view_spend_logs( WHERE {joined_conditions} ORDER BY {_SESSION_GROUP_KEY_SQL}, call_type IN {_MCP_CALL_TYPES_SQL}, "startTime" DESC ) AS session_representatives - ORDER BY {_order_expr} {_sql_dir}{_nulls_clause}, request_id + ORDER BY {exact_request_id_first}{_order_expr} {_sql_dir}{_nulls_clause}, request_id LIMIT ${p} OFFSET ${p + 1} """ if session_grouping @@ -2846,7 +2880,7 @@ async def ui_view_spend_logs( {_SPEND_LOG_LIST_COLUMNS} FROM "LiteLLM_SpendLogs" WHERE {joined_conditions} - ORDER BY {_order_expr} {_sql_dir}{_nulls_clause} + ORDER BY {exact_request_id_first}{_order_expr} {_sql_dir}{_nulls_clause} LIMIT ${p} OFFSET ${p + 1} """ ) @@ -2854,6 +2888,14 @@ async def ui_view_spend_logs( data: Final = await prisma_client.db.query_raw(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( + prisma_client=prisma_client, + user_api_key_dict=user_api_key_dict, + rows=data, + request_id=request_id, + ) + _hydrate_spend_log_metadata(data) # Calculate total pages @@ -3104,7 +3146,7 @@ def _hydrate_spend_log_metadata(rows: Sequence[Mapping[str, object]]) -> None: def _cold_storage_object_key_from_metadata( - metadata: str | dict | None, + metadata: str | Mapping[str, object] | None, ) -> str | None: if isinstance(metadata, str): try: @@ -3209,7 +3251,8 @@ async def ui_view_request_response_for_request_id( """ from litellm.proxy.proxy_server import prisma_client - if not _is_admin_view_safe(user_api_key_dict=user_api_key_dict): + caller_is_admin: Final = _is_admin_view_safe(user_api_key_dict=user_api_key_dict) + if not caller_is_admin: if prisma_client is None: raise HTTPException( status_code=status.HTTP_403_FORBIDDEN, @@ -3234,38 +3277,45 @@ async def ui_view_request_response_for_request_id( if end_date is not None: end_date_obj = datetime.strptime(end_date, "%Y-%m-%d %H:%M:%S").replace(tzinfo=timezone.utc) + spend_log_row: Final = ( + None + if prisma_client is None + else await _resolve_spend_log_payload_row( + prisma_client=prisma_client, + user_api_key_dict=user_api_key_dict, + request_id=request_id, + caller_is_admin=caller_is_admin, + ) + ) + stored_request_id: Final = _stored_request_id(spend_log_row, request_id) + for custom_logger in custom_loggers: payload = await custom_logger.get_request_response_payload( - request_id=request_id, + request_id=stored_request_id, start_time_utc=start_date_obj, end_time_utc=end_date_obj, ) if payload is not None: + if not caller_is_admin and prisma_client is not None: + await _assert_user_owns_cold_storage_payload( + prisma_client=prisma_client, + user_api_key_dict=user_api_key_dict, + payload=cast(Mapping[str, object], payload), # cast-ok: custom-logger payload is untyped + request_id=request_id, + ) return payload + if spend_log_row is None: + return None + # Fallback: the list endpoint omits the heavy columns for performance, so # serve them here. When prompts were offloaded to cold storage the DB holds # only placeholders, so _resolve_request_response_payload fetches the real # payload from the configured cold storage backend by object key. - if prisma_client is not None: - from litellm.proxy.spend_tracking.cold_storage_handler import ( - ColdStorageHandler, - ) + from litellm.proxy.spend_tracking.cold_storage_handler import ColdStorageHandler - sql_query: Final = """ - SELECT messages, response, proxy_server_request, metadata - FROM "LiteLLM_SpendLogs" - WHERE request_id = $1 - LIMIT 1 - """ - db_result: Final[Sequence[Mapping[str, object]] | None] = await _query_raw_or_none( - prisma_client, sql_query, request_id - ) - if db_result and len(db_result) > 0: - resolved = await _resolve_request_response_payload(db_result[0], cold_storage_handler=ColdStorageHandler()) - return resolved._asdict() - - return None + resolved: Final = await _resolve_request_response_payload(spend_log_row, cold_storage_handler=ColdStorageHandler()) + return resolved._asdict() @router.get( @@ -3391,7 +3441,7 @@ async def view_spend_logs( if api_key is not None and isinstance(api_key, str): filter_query["api_key"] = summary_api_key if request_id is not None and isinstance(request_id, str): - filter_query["request_id"] = request_id + filter_query["OR"] = _request_id_or_call_id_clause(request_id) if user_id is not None and isinstance(user_id, str): filter_query["user"] = user_id @@ -3439,7 +3489,7 @@ async def view_spend_logs( return [*summary_items, *padding] else: - scoped_filter: Final[dict[str, str]] = {} + scoped_filter: Final[dict[str, object]] = {} if api_key is not None and isinstance(api_key, str): if api_key.startswith("sk-"): hashed_token = prisma_client.hash_token(token=api_key) @@ -3447,7 +3497,7 @@ async def view_spend_logs( hashed_token = api_key scoped_filter["api_key"] = hashed_token if request_id is not None and isinstance(request_id, str): - scoped_filter["request_id"] = request_id + scoped_filter["OR"] = _request_id_or_call_id_clause(request_id) if user_id is not None and isinstance(user_id, str): scoped_filter["user"] = user_id @@ -4676,39 +4726,190 @@ def _can_user_view_spend_log(user_api_key_dict: UserAPIKeyAuth) -> bool: ) +async def _user_can_view_spend_log_owner( + prisma_client: PrismaClient, + user_api_key_dict: UserAPIKeyAuth, + owner_user: str | None, + owner_team_id: str | None, +) -> bool: + if owner_user is not None and owner_user == user_api_key_dict.user_id: + return True + if owner_team_id: + return await _can_team_member_view_log( + prisma_client=prisma_client, + user_api_key_dict=user_api_key_dict, + team_id=owner_team_id, + ) + return False + + +def _spend_log_forbidden(request_id: str) -> HTTPException: + return HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail={"error": f"Not authorized to view spend log for request_id={request_id}"}, + ) + + async def _assert_user_can_view_request_id( prisma_client: PrismaClient, user_api_key_dict: UserAPIKeyAuth, request_id: str, ) -> None: """ - Verify the requesting non-admin user is allowed to view this spend-log row. - Allowed when the log belongs to the user directly, or to one of their - permitted teams (admin or ``/spend/logs`` permission). - Raises HTTP 403 if not, including when no spend-log row exists for the - request_id (e.g. it was pruned by retention), so a missing row can't be - used to read a payload out of cold storage via the detail endpoint. + Verify the requesting non-admin user is allowed to view at least one spend-log + row identified by ``request_id`` or ``litellm_call_id``. The latter is + client-settable, so an id lookup can match rows across different tenants; the + data queries scope a non-admin's results to rows they own directly or via a + permitted team, so a colliding foreign row can neither be served nor deny the + caller their own. Raises HTTP 403 when none of the matching rows is theirs to + view, including when no row exists at all (e.g. it was pruned by retention), + so a missing row can't be used to read a payload out of cold storage via the + detail endpoint. """ - row: Final = await _find_spend_log_row(prisma_client, request_id) + owners: Final = await _find_spend_log_owners(prisma_client, request_id) + for owner in owners: + if await _user_can_view_spend_log_owner(prisma_client, user_api_key_dict, owner["user"], owner["team_id"]): + return + raise _spend_log_forbidden(request_id) - if row is not None and row.user is not None and row.user == user_api_key_dict.user_id: - return - if row is not None and row.team_id: - can_view: Final = await _can_team_member_view_log( +@dataclass(frozen=True, slots=True) +class _SpendLogViewer: + user_id: str | None + team_ids: tuple[str, ...] + + +async def _spend_log_viewer(prisma_client: PrismaClient, user_api_key_dict: UserAPIKeyAuth) -> _SpendLogViewer: + return _SpendLogViewer( + user_id=user_api_key_dict.user_id, + team_ids=await _get_permitted_team_ids_for_spend_logs_or_empty( prisma_client=prisma_client, user_api_key_dict=user_api_key_dict, - team_id=row.team_id, - ) - if can_view: - return - - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, - detail={"error": f"Not authorized to view spend log for request_id={request_id}"}, + ), ) +def _viewer_scope_clause(viewer: _SpendLogViewer | None) -> tuple[str, tuple[object, ...]]: + match viewer: + case None: + return ("", ()) + case _SpendLogViewer(user_id=user_id, team_ids=()): + return (' AND "user" = $2', (user_id,)) + case _SpendLogViewer(user_id=user_id, team_ids=team_ids): + return (' AND ("user" = $2 OR team_id = ANY($3::text[]))', (user_id, team_ids)) + + +def _spend_log_payload_query(request_id: str, viewer: _SpendLogViewer | None) -> tuple[str, tuple[object, ...]]: + """ + Fetch the one row an id lookup resolves to, preferring the exact ``request_id`` + match over rows that merely carry the id as their client-set ``litellm_call_id``. + A non-admin viewer only ever gets rows they own or rows of a team they may view. + """ + scope, scope_params = _viewer_scope_clause(viewer) + return ( + f""" + SELECT request_id, messages, response, proxy_server_request, metadata, "user", team_id + FROM "LiteLLM_SpendLogs" + WHERE (request_id = $1 OR litellm_call_id = $1){scope} + ORDER BY (request_id = $1) DESC + LIMIT 1 + """, + (request_id, *scope_params), + ) + + +async def _resolve_spend_log_payload_row( + prisma_client: PrismaClient, + user_api_key_dict: UserAPIKeyAuth, + request_id: str, + caller_is_admin: bool, +) -> Mapping[str, object] | None: + """ + Resolve an id lookup to the caller's own spend-log row before any payload + store is consulted. Cold storage is keyed by the provider ``request_id``, so + asking it for the raw lookup id could hand back another tenant's payload when + that id is only the caller's ``litellm_call_id``; the row's stored + ``request_id`` is the key that names the caller's own request. + """ + viewer: Final = None if caller_is_admin else await _spend_log_viewer(prisma_client, user_api_key_dict) + sql_query, sql_params = _spend_log_payload_query(request_id, viewer) + rows: Final[Sequence[Mapping[str, object]] | None] = await _query_raw_or_none(prisma_client, sql_query, *sql_params) + if not rows: + return None + if not caller_is_admin: + await _assert_user_owns_fetched_spend_rows( + prisma_client=prisma_client, + user_api_key_dict=user_api_key_dict, + rows=rows, + request_id=request_id, + ) + return rows[0] + + +def _stored_request_id(row: Mapping[str, object] | None, lookup_id: str) -> str: + stored: Final = None if row is None else row.get("request_id") + return stored if isinstance(stored, str) else lookup_id + + +def _fetched_row_owner(row: Mapping[str, object]) -> tuple[str | None, str | None]: + user: Final = row.get("user") + team_id: Final = row.get("team_id") + return ( + user if isinstance(user, str) else None, + team_id if isinstance(team_id, str) else None, + ) + + +async def _assert_user_owns_fetched_spend_rows( + prisma_client: PrismaClient, + user_api_key_dict: UserAPIKeyAuth, + rows: Sequence[Mapping[str, object]], + request_id: str, +) -> None: + """ + Re-verify ownership on the rows an id lookup actually fetched. + ``_assert_user_can_view_request_id`` and the data query read the table at + different moments, so a foreign row inserted between them could otherwise be + returned even though the pre-check passed. Checking the fetched rows + themselves means no interleaving can return another tenant's row. + """ + for user, team_id in frozenset(_fetched_row_owner(row) for row in rows): + if not await _user_can_view_spend_log_owner(prisma_client, user_api_key_dict, user, team_id): + raise _spend_log_forbidden(request_id) + + +def _cold_storage_payload_owner(payload: Mapping[str, object]) -> tuple[str | None, str | None]: + metadata: Final = payload.get("metadata") + if not isinstance(metadata, Mapping): + return (None, None) + owner: Final = cast(Mapping[str, object], metadata) # cast-ok: cold-storage JSON is untyped + user: Final = owner.get("user_api_key_user_id") + team_id: Final = owner.get("user_api_key_team_id") + return ( + user if isinstance(user, str) else None, + team_id if isinstance(team_id, str) else None, + ) + + +async def _assert_user_owns_cold_storage_payload( + prisma_client: PrismaClient, + user_api_key_dict: UserAPIKeyAuth, + payload: Mapping[str, object], + request_id: str, +) -> None: + """ + Authorize a cold-storage payload against the owner recorded inside it. + The custom logger reads the payload straight from cold storage, written + independently of the spend-log table and able to outlive its row, so a + request_id lookup could otherwise hand back another tenant's stored payload + when no row exists for the pre-check to catch. Verifying the payload's own + owner closes that gap, and a payload that records no owner fails closed. + """ + owner_user, owner_team_id = _cold_storage_payload_owner(payload) + if not await _user_can_view_spend_log_owner(prisma_client, user_api_key_dict, owner_user, owner_team_id): + raise _spend_log_forbidden(request_id) + + async def _get_permitted_team_ids_for_spend_logs( prisma_client: PrismaClient, user_api_key_dict: UserAPIKeyAuth, diff --git a/litellm/proxy/spend_tracking/spend_tracking_utils.py b/litellm/proxy/spend_tracking/spend_tracking_utils.py index 3fd20bb7e81..4bcdf6aad22 100644 --- a/litellm/proxy/spend_tracking/spend_tracking_utils.py +++ b/litellm/proxy/spend_tracking/spend_tracking_utils.py @@ -159,7 +159,7 @@ def _get_spend_logs_metadata( requester_ip_address=None, additional_usage_values=None, applied_guardrails=None, - status=None or "success", + status="success", error_information=None, proxy_server_request=None, batch_models=None, @@ -621,6 +621,7 @@ def get_logging_payload(kwargs, response_obj, start_time, end_time) -> SpendLogs status=_get_status_for_spend_log( metadata=metadata, ), + litellm_call_id=litellm_call_id, ) verbose_proxy_logger.debug( diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index 89625021e37..d201ac4bc88 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -4,6 +4,7 @@ import copy import hashlib import inspect import json +import math import os import smtplib import ssl @@ -93,6 +94,7 @@ from litellm.integrations.custom_logger import CustomLogger from litellm.integrations.prometheus import PrometheusLogger from litellm.integrations.SlackAlerting.slack_alerting import SlackAlerting from litellm.integrations.SlackAlerting.utils import _add_langfuse_trace_id_to_alert +from litellm.litellm_core_utils.api_route_to_call_types import get_call_types_for_route from litellm.litellm_core_utils.core_helpers import ( coerce_token_limit, get_or_create_metadata_bucket, @@ -879,6 +881,18 @@ def _failure_usage_to_lift( _EMPTY_LIFT: Final = MappingProxyType({}) +def _call_type_for_route(route: str | None) -> str | None: + """The route's call type when it maps to a single operation (its async and sync variants); + None for routes shared by several operations, since the method is not known here.""" + if route is None: + return None + call_types: Final = get_call_types_for_route(route) + if not call_types: + return None + operations: Final = frozenset(call_type.value.removeprefix("a") for call_type in call_types) + return call_types[0].value if len(operations) == 1 else None + + def _failure_fields_to_lift(request_data: Mapping[str, object]) -> 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 @@ -2549,10 +2563,6 @@ class ProxyLogging: @staticmethod def _stream_requires_guardrail_translation(user_api_key_dict: UserAPIKeyAuth) -> bool: - from litellm.litellm_core_utils.api_route_to_call_types import ( - get_call_types_for_route, - ) - route: Final = user_api_key_dict.request_route if not route: return False @@ -3020,6 +3030,7 @@ class ProxyLogging: start_time=datetime.now(), **request_data, ) + request_data["litellm_logging_obj"] = litellm_logging_obj # rebind-ok: lifted then popped by the caller if "metadata" not in request_data: request_data["metadata"] = {} request_data["metadata"].update(user_api_key_logged_metadata) @@ -3044,25 +3055,23 @@ class ProxyLogging: ) input: list | str | dict = "" - normalized_call_type: str | None = None + body_shape_call_type: str | None = None if "messages" in request_data and isinstance(request_data["messages"], list): input = request_data["messages"] litellm_logging_obj.model_call_details["messages"] = input - if litellm_logging_obj.call_type != CallTypes.pass_through.value: - normalized_call_type = CallTypes.acompletion.value + body_shape_call_type = CallTypes.acompletion.value elif "prompt" in request_data and isinstance(request_data["prompt"], str): input = request_data["prompt"] litellm_logging_obj.model_call_details["prompt"] = input - if litellm_logging_obj.call_type != CallTypes.pass_through.value: - normalized_call_type = CallTypes.atext_completion.value + body_shape_call_type = CallTypes.atext_completion.value elif "input" in request_data and isinstance(request_data["input"], list): input = request_data["input"] litellm_logging_obj.model_call_details["input"] = input - if litellm_logging_obj.call_type != CallTypes.pass_through.value: - normalized_call_type = CallTypes.aembedding.value - if normalized_call_type is not None: - litellm_logging_obj.call_type = normalized_call_type - litellm_logging_obj.model_call_details["call_type"] = normalized_call_type + body_shape_call_type = CallTypes.aembedding.value + resolved_call_type: Final = _call_type_for_route(route) 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 + litellm_logging_obj.model_call_details["call_type"] = resolved_call_type # Pass-through endpoints are logged via the callback loop's # async_post_call_failure_hook — skip pre_call and failure handlers. if litellm_logging_obj.call_type == CallTypes.pass_through.value: @@ -6396,7 +6405,7 @@ class PrismaClient: return None try: value: Final = float(response_time_ms) - return value if value == value and value not in (float("inf"), float("-inf")) else None + return value if math.isfinite(value) else None except (ValueError, TypeError): verbose_proxy_logger.warning("Invalid response_time_ms value: %s", response_time_ms) return None diff --git a/litellm/responses/additional_tools.py b/litellm/responses/additional_tools.py new file mode 100644 index 00000000000..ea0d7af350c --- /dev/null +++ b/litellm/responses/additional_tools.py @@ -0,0 +1,65 @@ +from collections.abc import Sequence +from dataclasses import dataclass +from typing import Final, cast # noqa: TID251 # validating the openai tool union strips vendor keys from raw tools + +from pydantic import BaseModel, ValidationError + +from litellm._logging import verbose_logger +from litellm.types.llms.openai import ALL_RESPONSES_API_TOOL_PARAMS, ResponseInputParam + +ADDITIONAL_TOOLS_INPUT_ITEM_TYPE: Final = "additional_tools" + + +class _InputItemType(BaseModel): + type: str = "" + + +class _AdditionalToolsItem(BaseModel): + tools: tuple[dict[str, object], ...] = () + + +@dataclass(frozen=True, slots=True) +class HoistedAdditionalTools: + input: str | ResponseInputParam + tools: tuple[ALL_RESPONSES_API_TOOL_PARAMS, ...] + hoisted: tuple[ALL_RESPONSES_API_TOOL_PARAMS, ...] + + +def _is_additional_tools_item(item: object) -> bool: + try: + return _InputItemType.model_validate(item).type == ADDITIONAL_TOOLS_INPUT_ITEM_TYPE + except ValidationError: + return False + + +def _tools_of_item(item: object) -> tuple[ALL_RESPONSES_API_TOOL_PARAMS, ...]: + try: + parsed: Final = _AdditionalToolsItem.model_validate(item) + except ValidationError: + return () + return tuple( + cast( + "ALL_RESPONSES_API_TOOL_PARAMS", tool + ) # cast-ok: nested tools carry the same raw tool JSON as top-level tools + for tool in parsed.tools + ) + + +def hoist_additional_tools( + input: str | ResponseInputParam, + tools: Sequence[ALL_RESPONSES_API_TOOL_PARAMS] | None, +) -> HoistedAdditionalTools: + existing: Final = tuple(tools or ()) + if isinstance(input, str): + return HoistedAdditionalTools(input=input, tools=existing, hoisted=()) + items: Final = tuple(item for item in input if _is_additional_tools_item(item)) + if not items: + return HoistedAdditionalTools(input=input, tools=existing, hoisted=()) + hoisted: Final = tuple(tool for item in items for tool in _tools_of_item(item)) + verbose_logger.debug( + "Responses API: hoisting %d tool(s) out of %d 'additional_tools' input item(s) into the top-level tools param.", + len(hoisted), + len(items), + ) + remaining_input: Final = [item for item in input if not _is_additional_tools_item(item)] + return HoistedAdditionalTools(input=remaining_input, tools=(*existing, *hoisted), hoisted=hoisted) diff --git a/litellm/responses/litellm_completion_transformation/custom_tools.py b/litellm/responses/litellm_completion_transformation/custom_tools.py index 4aa489d9e50..7888a07e248 100644 --- a/litellm/responses/litellm_completion_transformation/custom_tools.py +++ b/litellm/responses/litellm_completion_transformation/custom_tools.py @@ -39,15 +39,38 @@ def openai_shaped_tool_call_item_id(item_type: str, tool_id: str) -> str: return f"{prefix}_{tool_id}" +class _ToolNameFields(BaseModel): + type: str = "" + name: str = "" + tools: tuple[object, ...] = () + + +def _tool_name_fields_of(tool: object) -> _ToolNameFields | None: + try: + return _ToolNameFields.model_validate(tool) + except ValidationError: + return None + + +def _custom_tool_name_of(tool: object) -> str | None: + parsed: Final = _tool_name_fields_of(tool) + if parsed is None or parsed.type != "custom" or not parsed.name: + return None + return parsed.name + + +def _nested_tools_of(tool: object) -> tuple[object, ...]: + parsed: Final = _tool_name_fields_of(tool) + if parsed is None or parsed.type != "namespace": + return () + return parsed.tools + + def extract_custom_tool_names(tools: Sequence[object] | None) -> set[str]: - """Extract names of tools originally defined as ``type: "custom"``.""" - if not tools: - return set() - names: Final[set[str]] = set() - for tool in tools: - if isinstance(tool, dict) and tool.get("type") == "custom" and "name" in tool: - names.add(tool["name"]) - return names + """Extract names of ``type: "custom"`` tools, at the top level or one level inside a ``namespace`` tool.""" + top_level: Final = tuple(tools or ()) + nested: Final = tuple(nested_tool for tool in top_level for nested_tool in _nested_tools_of(tool)) + return {name for tool in (*top_level, *nested) if (name := _custom_tool_name_of(tool)) is not None} def is_custom_tool_call(tool_name: str, custom_tool_names: set[str]) -> bool: @@ -143,7 +166,7 @@ def validated_allowed_callers(value: object) -> list[str] | None: raise ValueError("allowed_callers must be a list of strings") from exc -def _grammar_suffix(fmt: object) -> str: +def custom_tool_grammar_suffix(fmt: object) -> str: try: parsed: Final = _CustomToolFormat.model_validate(fmt) except ValidationError: @@ -167,7 +190,9 @@ def convert_custom_tool_to_function_tool(tool: Mapping[str, object]) -> ChatComp raw_name: Final = tool.get("name") name: Final = raw_name if isinstance(raw_name, str) else "" raw_description: Final = tool.get("description") - description = (raw_description if isinstance(raw_description, str) else "") + _grammar_suffix(tool.get("format")) + description: Final = (raw_description if isinstance(raw_description, str) else "") + custom_tool_grammar_suffix( + tool.get("format") + ) allowed_callers: Final = validated_allowed_callers(tool.get("allowed_callers")) function_chunk: Final = ChatCompletionToolParamFunctionChunk( name=name, diff --git a/litellm/responses/litellm_completion_transformation/handler.py b/litellm/responses/litellm_completion_transformation/handler.py index a0e8cd278e6..505b5b09433 100644 --- a/litellm/responses/litellm_completion_transformation/handler.py +++ b/litellm/responses/litellm_completion_transformation/handler.py @@ -6,6 +6,7 @@ from collections.abc import Coroutine, Mapping from typing import Final import litellm +from litellm.responses.additional_tools import hoist_additional_tools from litellm.responses.litellm_completion_transformation.streaming_iterator import ( LiteLLMCompletionStreamingIterator, ) @@ -37,11 +38,16 @@ class LiteLLMCompletionTransformationHandler: | BaseResponsesAPIStreamingIterator | Coroutine[object, object, ResponsesAPIResponse | BaseResponsesAPIStreamingIterator] ): + hoisted: Final = hoist_additional_tools(input, responses_api_request.get("tools")) + bridged_input: Final = hoisted.input + bridged_request: Final[ResponsesAPIOptionalRequestParams] = ( + {**responses_api_request, "tools": list(hoisted.tools)} if hoisted.hoisted else responses_api_request + ) litellm_completion_request: Final[dict] = ( LiteLLMCompletionResponsesConfig.transform_responses_api_request_to_chat_completion_request( model=model, - input=input, - responses_api_request=responses_api_request, + input=bridged_input, + responses_api_request=bridged_request, custom_llm_provider=custom_llm_provider, stream=stream, extra_headers=extra_headers, @@ -52,8 +58,8 @@ class LiteLLMCompletionTransformationHandler: if _is_async: return self.async_response_api_handler( litellm_completion_request=litellm_completion_request, - request_input=input, - responses_api_request=responses_api_request, + request_input=bridged_input, + responses_api_request=bridged_request, **kwargs, ) @@ -70,8 +76,8 @@ class LiteLLMCompletionTransformationHandler: responses_api_response: Final[ResponsesAPIResponse] = ( LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response( chat_completion_response=litellm_completion_response, - request_input=input, - responses_api_request=responses_api_request, + request_input=bridged_input, + responses_api_request=bridged_request, ) ) @@ -81,8 +87,8 @@ class LiteLLMCompletionTransformationHandler: return LiteLLMCompletionStreamingIterator( model=model, litellm_custom_stream_wrapper=litellm_completion_response, - request_input=input, - responses_api_request=responses_api_request, + request_input=bridged_input, + responses_api_request=bridged_request, custom_llm_provider=custom_llm_provider, litellm_metadata=kwargs.get("litellm_metadata", {}), ) diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py index 126b976e2c5..c28b5558c75 100644 --- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py +++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py @@ -8,6 +8,7 @@ from litellm.main import stream_chunk_builder from litellm.responses.litellm_completion_transformation.custom_tools import ( build_tool_call_item_kwargs, extract_custom_tool_names, + is_custom_tool_call, serialize_tool_call_arguments, ) from litellm.responses.litellm_completion_transformation.transformation import ( @@ -166,6 +167,14 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): return tool_name, namespace return fn_name, None + def _tool_call_item_kwargs(self, call_id: str, fn_name: str, arguments: str, status: str) -> dict[str, str]: + item_kwargs: Final = build_tool_call_item_kwargs(call_id, fn_name, arguments, status, self._custom_tool_names) + if is_custom_tool_call(fn_name, self._custom_tool_names): + return item_kwargs + tool_name, tool_namespace = self._responses_namespace_tool_call_fields(fn_name) + namespace_kwargs: Final = {"namespace": tool_namespace} if tool_namespace else {} + return {**item_kwargs, "name": tool_name, **namespace_kwargs} + def _is_reasoning_end(self, chunk): delta: Final = chunk.choices[0].delta @@ -244,17 +253,13 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): else: fn_name = str(getattr(fn, "name", "") or "") fn_args_delta = serialize_tool_call_arguments(getattr(fn, "arguments", "")) - tool_name, tool_namespace = self._responses_namespace_tool_call_fields(fn_name) output_index = self._get_or_assign_tool_output_index(call_id) if call_id not in self._tool_args_by_call_id: self._tool_args_by_call_id[call_id] = "" self._sequence_number += 1 - names = self._custom_tool_names - item_kwargs = build_tool_call_item_kwargs(call_id, tool_name, "", "in_progress", names) + item_kwargs = self._tool_call_item_kwargs(call_id, fn_name, "", "in_progress") self._tool_item_id_by_call_id[call_id] = item_kwargs["id"] - if tool_namespace: - item_kwargs["namespace"] = tool_namespace event = OutputItemAddedEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, output_index=output_index, @@ -315,7 +320,6 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): else: fn_name = str(getattr(fn, "name", "") or "") fn_args = serialize_tool_call_arguments(getattr(fn, "arguments", "")) - tool_name, tool_namespace = self._responses_namespace_tool_call_fields(fn_name) web_search_call = self._web_search_calls.get(call_id) if web_search_call is not None: if call_id not in self._queued_web_search_call_ids: @@ -330,11 +334,8 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): if is_new_tool_call: self._tool_args_by_call_id[call_id] = "" self._sequence_number += 1 - names = self._custom_tool_names - item_kwargs = build_tool_call_item_kwargs(call_id, tool_name, "", "in_progress", names) + item_kwargs = self._tool_call_item_kwargs(call_id, fn_name, "", "in_progress") self._tool_item_id_by_call_id[call_id] = item_kwargs["id"] - if tool_namespace: - item_kwargs["namespace"] = tool_namespace event = OutputItemAddedEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED, output_index=output_index, @@ -376,11 +377,8 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): self._pending_tool_events.append(done_event) self._sequence_number += 1 - names = self._custom_tool_names - item_kwargs = build_tool_call_item_kwargs(call_id, tool_name, final_args, "completed", names) + 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"]) - if tool_namespace: - item_kwargs["namespace"] = tool_namespace item_done_event = OutputItemDoneEvent( type=ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE, output_index=output_index, diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py index cc594f167c7..01fb6cb483d 100644 --- a/litellm/responses/litellm_completion_transformation/transformation.py +++ b/litellm/responses/litellm_completion_transformation/transformation.py @@ -43,6 +43,7 @@ from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLogging from litellm.responses.litellm_completion_transformation.session_handler import ( ResponsesSessionHandler, ) +from litellm.types.llms.base import CachedTokensDetails from litellm.types.llms.openai import ( AllMessageValues, ChatCompletionAssistantMessage, @@ -109,6 +110,7 @@ NamespaceTool: TypeAlias = Mapping[str, object] ResponseTools: TypeAlias = Sequence[Mapping[str, object]] | None ChatToolParam: TypeAlias = ChatCompletionToolParam | OpenAIMcpServerTool NAMESPACE_DESCRIPTION_SEPARATOR: Final = "\n\n" +NAMESPACE_MEMBER_TYPES_WITH_CHAT_TOOLS: Final = frozenset({"function", "custom"}) @dataclass(frozen=True, slots=True) @@ -117,6 +119,14 @@ class ResponsesToolChatForm: web_search_options: OpenAIWebSearchOptions | None +@dataclass(frozen=True, slots=True) +class ResponsesReasoningChatForm: + """The Responses ``reasoning`` object as the two params Chat Completions takes.""" + + effort: str | None + summary: str | None + + if TYPE_CHECKING: from openai.types.responses.response_apply_patch_tool_call import ( ResponseApplyPatchToolCall, @@ -309,6 +319,79 @@ class LiteLLMCompletionResponsesConfig: ) return supported_params is not None and "web_search_options" not in supported_params + @staticmethod + def _completion_bridges_back_to_responses_api( + model: str, + custom_llm_provider: str | None, + tools: Sequence[ChatCompletionToolParam | OpenAIMcpServerTool] | None, + web_search_options: OpenAIWebSearchOptions | None, + reasoning_effort: str | None, + reasoning_summary: str | None, + api_base: str | None, + ) -> bool: + """ + Whether ``litellm.completion`` will route this model back onto the Responses API. + + Delegates to the same check ``litellm.completion`` itself runs, and is asked with the + params this transform is about to emit, so the two cannot reach different answers. + """ + from litellm.main import responses_api_bridge_check + + try: + model_info, _ = responses_api_bridge_check( + model=model, + custom_llm_provider=custom_llm_provider or "", + web_search_options=web_search_options, + tools=tools, + reasoning_effort=reasoning_effort, + reasoning_summary=reasoning_summary, + api_base=api_base, + ) + except Exception as e: # noqa: BLE001 # a capability probe must never fail the request it probes for + verbose_logger.debug("responses bridge: reasoning effort mode check failed: %s", e) + return False + return model_info.get("mode") == "responses" + + @staticmethod + def _transform_reasoning_for_chat_completion( + reasoning_param: Reasoning | str | None, + model: str, + custom_llm_provider: str | None, + tools: Sequence[ChatCompletionToolParam | OpenAIMcpServerTool] | None = None, + web_search_options: OpenAIWebSearchOptions | None = None, + api_base: str | None = None, + ) -> ResponsesReasoningChatForm: + """ + Split the Responses ``reasoning`` object into the params Chat Completions understands. + + ``reasoning_effort`` is a string enum there, so the object is never forwarded whole: a chat + provider either rejects it or silently drops it, and dropping it turns reasoning off while + still billing for the turn. ``summary`` has no chat equivalent, so it rides the + ``reasoning_summary`` alias, which ``litellm.completion`` reassembles into ``{effort, + summary}`` when it bridges the model back onto the Responses API, and is sent to nothing + else. + """ + if not reasoning_param: + return ResponsesReasoningChatForm(effort=None, summary=None) + if isinstance(reasoning_param, str): + return ResponsesReasoningChatForm(effort=reasoning_param, summary=None) + + effort: Final = reasoning_param.get("effort") + summary: Final = reasoning_param.get("summary") + if summary is None: + return ResponsesReasoningChatForm(effort=effort, summary=None) + + bridges_back: Final = LiteLLMCompletionResponsesConfig._completion_bridges_back_to_responses_api( + model=model, + custom_llm_provider=custom_llm_provider, + tools=tools, + web_search_options=web_search_options, + reasoning_effort=effort, + reasoning_summary=summary, + api_base=api_base, + ) + return ResponsesReasoningChatForm(effort=effort, summary=summary if bridges_back else None) + @staticmethod def transform_responses_api_request_to_chat_completion_request( model: str, @@ -339,23 +422,14 @@ class LiteLLMCompletionResponsesConfig: if text_param: response_format = LiteLLMCompletionResponsesConfig._transform_text_format_to_response_format(text_param) - # Extract reasoning_effort from reasoning parameter - reasoning_effort: Reasoning | str | None = None - reasoning_param: Final = responses_api_request.get("reasoning") - if reasoning_param: - if isinstance(reasoning_param, dict): - # reasoning can be {"effort": "low|medium|high", "summary": "detailed"} - # Keep the full dict when summary is set so the responses API bridge can - # forward it; otherwise use the effort string for chat completion (e.g. Gemini). - if "summary" in reasoning_param: - reasoning_effort = reasoning_param - elif "effort" in reasoning_param: - reasoning_effort = reasoning_param.get("effort") - else: - reasoning_effort = reasoning_param - elif isinstance(reasoning_param, str): - # reasoning could be a string directly - reasoning_effort = reasoning_param + reasoning: Final = LiteLLMCompletionResponsesConfig._transform_reasoning_for_chat_completion( + reasoning_param=responses_api_request.get("reasoning"), + model=model, + custom_llm_provider=custom_llm_provider, + tools=tools, + web_search_options=web_search_options, + api_base=kwargs.get("api_base"), + ) litellm_completion_request: dict = { "messages": LiteLLMCompletionResponsesConfig.transform_responses_api_input_to_messages( @@ -378,7 +452,8 @@ class LiteLLMCompletionResponsesConfig: "service_tier": kwargs.get("service_tier"), "web_search_options": web_search_options, "response_format": response_format, - "reasoning_effort": reasoning_effort, + "reasoning_effort": reasoning.effort, + "reasoning_summary": reasoning.summary, "context_management": responses_api_request.get("context_management"), # litellm specific params "custom_llm_provider": custom_llm_provider, @@ -1817,9 +1892,21 @@ class LiteLLMCompletionResponsesConfig: namespace_tool: NamespaceTool, nested: bool, ) -> ChatCompletionToolParam | None: - if nested and namespace_tool.get("type") != "function": + tool_type: Final = namespace_tool.get("type") + if nested and tool_type not in NAMESPACE_MEMBER_TYPES_WITH_CHAT_TOOLS: return None + raw_description: Final = str(namespace_tool.get("description") or "") + description: Final = ( + f"{namespace_description}{NAMESPACE_DESCRIPTION_SEPARATOR}{raw_description}" + if nested and namespace_description and raw_description + else namespace_description + if nested and namespace_description + else raw_description + ) + if nested and tool_type == "custom": + return convert_custom_tool_to_function_tool({**namespace_tool, "description": description}) + raw_parameters: Final = namespace_tool.get("parameters") parameters: Final = ( MappingProxyType(raw_parameters) if isinstance(raw_parameters, Mapping) else MappingProxyType({}) @@ -1828,14 +1915,6 @@ class LiteLLMCompletionResponsesConfig: parameters if parameters and "type" in parameters else MappingProxyType({**parameters, "type": "object"}) ) tool_name: Final = str(namespace_tool.get("name") or "") - raw_description: Final = str(namespace_tool.get("description") or "") - description: Final = ( - f"{namespace_description}{NAMESPACE_DESCRIPTION_SEPARATOR}{raw_description}" - if nested and namespace_description and raw_description - else namespace_description - if nested and namespace_description - else raw_description - ) chat_tool_name: Final = f"{namespace}__{tool_name}" if nested else tool_name function: Final = ChatCompletionToolParamFunctionChunk( name=chat_tool_name, @@ -2743,27 +2822,41 @@ class LiteLLMCompletionResponsesConfig: # Translate prompt_tokens_details to input_tokens_details if hasattr(usage, "prompt_tokens_details") and usage.prompt_tokens_details is not None: prompt_details: Final = usage.prompt_tokens_details - input_details_dict: Final[dict[str, int]] = {} - - if hasattr(prompt_details, "cached_tokens") and prompt_details.cached_tokens is not None: - input_details_dict["cached_tokens"] = prompt_details.cached_tokens - else: - input_details_dict["cached_tokens"] = 0 - - if hasattr(prompt_details, "text_tokens") and prompt_details.text_tokens is not None: - input_details_dict["text_tokens"] = prompt_details.text_tokens - - if hasattr(prompt_details, "audio_tokens") and prompt_details.audio_tokens is not None: - input_details_dict["audio_tokens"] = prompt_details.audio_tokens - - cache_write_tokens = getattr(prompt_details, "cache_write_tokens", None) or getattr( + cached_tokens_details: Final = getattr(prompt_details, "cached_tokens_details", None) + cache_write_tokens: Final = getattr(prompt_details, "cache_write_tokens", None) or getattr( prompt_details, "cache_creation_tokens", None ) - if cache_write_tokens is not None: - input_details_dict["cache_write_tokens"] = cache_write_tokens - - if input_details_dict: - response_usage.input_tokens_details = InputTokensDetails(**input_details_dict) + cache_write_extra: Final[Mapping[str, int]] = ( + MappingProxyType({"cache_write_tokens": cache_write_tokens}) + if cache_write_tokens is not None + else MappingProxyType({}) + ) + # The cost path reads the grounding counters off the input details, and a realtime + # session's usage is rebuilt from its own response.done, so dropping them here bills + # no per-query grounding fee at all. + grounding_request_counts: Final[Mapping[str, int]] = MappingProxyType( + { + counter: count + for counter, count in ( + ("web_search_requests", getattr(prompt_details, "web_search_requests", None)), + ( + "google_maps_grounding_requests", + getattr(prompt_details, "google_maps_grounding_requests", None), + ), + ) + if count is not None + } + ) + response_usage.input_tokens_details = InputTokensDetails( + cached_tokens=prompt_details.cached_tokens if prompt_details.cached_tokens is not None else 0, + text_tokens=prompt_details.text_tokens, + audio_tokens=prompt_details.audio_tokens, + cached_tokens_details=( + cached_tokens_details if isinstance(cached_tokens_details, CachedTokensDetails) else None + ), + **cache_write_extra, + **grounding_request_counts, + ) # Translate completion_tokens_details to output_tokens_details if hasattr(usage, "completion_tokens_details") and usage.completion_tokens_details is not None: diff --git a/litellm/responses/streaming_iterator.py b/litellm/responses/streaming_iterator.py index 40ff88fc557..b39e130242d 100644 --- a/litellm/responses/streaming_iterator.py +++ b/litellm/responses/streaming_iterator.py @@ -221,6 +221,13 @@ def _status_code_for_error_fields(error_type: str | None, error_code: str | None ) +def _mid_stream_fallback_eligible(mapped_exception: Exception) -> bool: + if isinstance(mapped_exception, litellm.ContentPolicyViolationError): + return True + status_code: Final = getattr(mapped_exception, "status_code", None) + return not isinstance(status_code, int) or status_code >= 500 or status_code == 429 + + class BaseResponsesAPIStreamingIterator: """ Base class for streaming iterators that process responses from the Responses API. @@ -521,15 +528,8 @@ class BaseResponsesAPIStreamingIterator: getattr(self.completed_response, "response", None) if self.completed_response else None ) error_info: Final = getattr(response_obj, "error", None) if response_obj else None - error_message, error_type, error_code = _error_event_fields(error_info) self._record_failed_response_usage(response_obj) - exception: Final = litellm.APIError( - status_code=_status_code_for_error_fields(error_type, error_code), - message=error_message, - llm_provider=self.custom_llm_provider or "", - model=self.model or "", - ) - self._handle_failure(exception) + self._handle_failure(self._map_error_event_exception(error_info)) def _record_failed_response_usage(self, response_obj: ResponsesAPIResponse | None) -> None: if response_obj is None or self.logging_obj is None: @@ -551,6 +551,28 @@ class BaseResponsesAPIStreamingIterator: self.logging_obj._response_cost_calculator(result=response_obj) or 0.0 ) + def _map_error_event_exception(self, error_obj: object) -> Exception: + from litellm.llms.base_llm.chat.transformation import BaseLLMException + + error_message, error_type, error_code = _error_event_fields(error_obj) + status_code: Final = _status_code_for_error_fields(error_type, error_code) + error_body: Final = {"message": error_message, "type": error_type, "code": error_code} + provider_exception: Final = BaseLLMException( + status_code=status_code, + message=f"Error code: {status_code} - {{'error': {error_body}}}", + body=error_body, + ) + try: + return litellm.exception_type( + model=self.model or "", + custom_llm_provider=self.custom_llm_provider or "", + original_exception=provider_exception, + completion_kwargs={}, + extra_kwargs={}, + ) + except Exception as mapped_exception: + return mapped_exception + def _maybe_raise_for_error_event(self, result: object) -> None: chunk_type: Final = getattr(result, "type", None) if chunk_type not in ("error", "response.failed"): @@ -562,15 +584,8 @@ class BaseResponsesAPIStreamingIterator: else getattr(result, "error", None) ) - error_message, error_type, error_code = _error_event_fields(error_obj) - status_code: Final = _status_code_for_error_fields(error_type, error_code) - mapped_exception: Final = litellm.APIError( - status_code=status_code, - message=error_message, - llm_provider=self.custom_llm_provider or "", - model=self.model or "", - ) - if 400 <= status_code < 500 and status_code != 429: + mapped_exception: Final = self._map_error_event_exception(error_obj) + if not _mid_stream_fallback_eligible(mapped_exception): raise mapped_exception raise MidStreamFallbackError( message=str(mapped_exception), diff --git a/litellm/responses/utils.py b/litellm/responses/utils.py index 599e978df6a..41a3ded7022 100644 --- a/litellm/responses/utils.py +++ b/litellm/responses/utils.py @@ -1179,7 +1179,14 @@ class ResponseAPILoggingUtils: audio_tokens=getattr(response_api_usage.input_tokens_details, "audio_tokens", None), text_tokens=getattr(response_api_usage.input_tokens_details, "text_tokens", None), image_tokens=getattr(response_api_usage.input_tokens_details, "image_tokens", None), + cached_tokens_details=getattr( + response_api_usage.input_tokens_details, "cached_tokens_details", None + ), cache_write_tokens=getattr(response_api_usage.input_tokens_details, "cache_write_tokens", None), + web_search_requests=getattr(response_api_usage.input_tokens_details, "web_search_requests", None), + google_maps_grounding_requests=getattr( + response_api_usage.input_tokens_details, "google_maps_grounding_requests", None + ), ) completion_tokens_details: CompletionTokensDetailsWrapper | None = None output_tokens_details: Final[OutputTokensDetails | None] = getattr( diff --git a/litellm/router.py b/litellm/router.py index 8865543badd..a414bdabf80 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -96,7 +96,6 @@ from litellm.litellm_core_utils.request_timeout_resolver import ( from litellm.litellm_core_utils.secret_redaction import redact_string from litellm.litellm_core_utils.sensitive_data_masker import ( SensitiveDataMasker, - mask_credentials_in_payload, mask_sensitive_structure, ) from litellm.litellm_core_utils.token_counter import offload_token_count @@ -623,20 +622,6 @@ def _replay_live_router_model_cost() -> None: set_live_deployment_replay(_replay_live_router_model_cost) -# Kwargs that carry no signal about the failed attempt, so log_retry drops them from a -# breadcrumb entirely: the request payload, the proxy's snapshot of the inbound request (its body -# aliases the live request metadata, earlier breadcrumbs included, so copying it would nest every -# breadcrumb inside the next one), and the router-internal walk state. Credentials are handled -# separately by mask_credentials_in_payload, which scrubs credential-named values from whatever -# kwargs remain rather than trying to enumerate every credential-bearing key here. -RETRY_BREADCRUMB_EXCLUDED_KWARGS: Final = frozenset( - ( - "messages", - "original_function", - "attempted_targets", - "proxy_server_request", - ) -) RETRY_BREADCRUMB_LIMIT: Final = 4 @@ -1553,6 +1538,18 @@ class Router: return False return sum(len(self.model_name_to_deployment_indices.get(member) or ()) for member in group.models) > 1 + def team_model_has_alternatives(self, deployment_id: str) -> bool: + deployment: Final = self.get_deployment(model_id=deployment_id) + if deployment is None: + return False + team_id: Final = deployment.model_info.team_id + public_model_name: Final = deployment.model_info.team_public_model_name + if team_id is None or public_model_name is None: + return False + sibling_indices: Final = self.team_model_to_deployment_indices.get((team_id, public_model_name)) or () + routable_siblings: Final = self._filter_blocked_deployments([self.model_list[idx] for idx in sibling_indices]) + return len(routable_siblings) > 1 + _OVERRIDABLE_ROUTING_STRATEGIES: frozenset[str] = frozenset({"simple-shuffle", *_DEFAULT_SELECTOR_ATTR_BY_STRATEGY}) def _get_request_routing_strategy_override(self, request_kwargs: dict | None) -> str | None: @@ -3271,8 +3268,15 @@ class Router: kwargs=initial_kwargs, metadata_variable_name="litellm_metadata", ) + # The content-policy dispatch branch matches on the trigger's own type, so a refusal's + # MidStreamFallbackError envelope is unwrapped here or the wrong fallback list is consulted. + fallback_trigger: Final[Exception] = ( + e.original_exception + if isinstance(e.original_exception, litellm.ContentPolicyViolationError) + else e + ) fallback_response = await self.async_function_with_fallbacks_common_utils( - e=e, + e=fallback_trigger, disable_fallbacks=False, fallbacks=fallbacks, context_window_fallbacks=context_window_fallbacks, @@ -4108,16 +4112,16 @@ class Router: models: Final = [m.strip() for m in model.split(",")] async def _async_completion_no_exceptions( - model: str, messages: list[dict[str, str]], stream: bool, **kwargs: Any + model_name: str, messages: list[dict[str, str]], stream: bool, **kwargs: Any ) -> ModelResponse | CustomStreamWrapper | Exception: """ Wrapper around self.acompletion that catches exceptions and returns them as a result """ try: - result = await self.acompletion(model=model, messages=messages, stream=stream, **kwargs) + result = await self.acompletion(model=model_name, messages=messages, stream=stream, **kwargs) return result except asyncio.CancelledError: - verbose_router_logger.debug("Received 'task.cancel'. Cancelling call w/ model=%s.", model) + verbose_router_logger.debug("Received 'task.cancel'. Cancelling call w/ model=%s.", model_name) raise except Exception as e: return e @@ -4144,9 +4148,9 @@ class Router: except KeyError: pass - for model in models: + for model_name in models: task = asyncio.create_task( - _async_completion_no_exceptions(model=model, messages=messages, stream=stream, **kwargs) + _async_completion_no_exceptions(model_name=model_name, messages=messages, stream=stream, **kwargs) ) pending_tasks.append(task) @@ -4845,6 +4849,7 @@ class Router: model=model, messages=messages, specific_deployment=kwargs.pop("specific_deployment", None), + request_kwargs=kwargs, ) data: Final = deployment["litellm_params"].copy() @@ -5159,13 +5164,11 @@ class Router: return healthy_deployments[0] # Use simple_shuffle for weighted selection - return cast( - GuardrailTypedDict, - simple_shuffle( - llm_router_instance=self, - healthy_deployments=healthy_deployments, - model=guardrail_name, - ), + return simple_shuffle( + resolve_model_alias=self._get_model_from_alias, + healthy_deployments=healthy_deployments, + model=guardrail_name, + request_kwargs=None, ) async def _ageneric_api_call_with_fallbacks(self, model: str, original_function: Callable, **kwargs): @@ -8374,32 +8377,35 @@ class Router: def log_retry(self, kwargs: dict, e: Exception) -> dict: """ - When a retry or fallback happens, log the details of the just failed model call - similar to Sentry breadcrumbing + When a retry or fallback happens, record which model group, deployment and attempt just failed and why, + and count it toward the request-wide num_retries_per_request cap """ + from litellm.types.router import RetryAttemptRecord + _metadata_var: Final = "litellm_metadata" if "litellm_metadata" in kwargs else "metadata" request_metadata: Final[Mapping[str, object]] = kwargs[_metadata_var] - attempt_kwargs: Final = MappingProxyType( - {k: v for k, v in kwargs.items() if k != _metadata_var and k not in RETRY_BREADCRUMB_EXCLUDED_KWARGS} - ) - attempt_metadata: Final = MappingProxyType( - {k: v for k, v in request_metadata.items() if k != "previous_models"} - ) - previous_model: Final = MappingProxyType( - { - "exception_type": type(e).__name__, - "exception_string": str(e), - **attempt_kwargs, - _metadata_var: attempt_metadata, - } - ) + model_group: Final = kwargs.get("model") + model_info: Final = request_metadata.get("model_info") + deployment_id: Final = model_info.get("id") if isinstance(model_info, Mapping) else None + attempted_retries: Final = request_metadata.get("attempted_retries") + attempt_record: Final[RetryAttemptRecord] = { + "model_group": model_group if isinstance(model_group, str) else None, + "deployment_id": deployment_id if isinstance(deployment_id, str) else None, + "exception_type": type(e).__name__, + "exception_string": str(e), + "attempted_retries": attempted_retries if type(attempted_retries) is int else None, + } earlier_breadcrumbs: Final = request_metadata.get("previous_models") kept_breadcrumbs: Final[tuple[object, ...]] = ( tuple(earlier_breadcrumbs)[-(RETRY_BREADCRUMB_LIMIT - 1) :] if isinstance(earlier_breadcrumbs, (list, tuple)) else () ) - breadcrumbs: Final = (*kept_breadcrumbs, mask_credentials_in_payload(previous_model)) + breadcrumbs: Final = (*kept_breadcrumbs, attempt_record) + earlier: Final = request_metadata.get("request_retry_count") + request_retry_count: Final = (earlier if type(earlier) is int and 0 <= earlier else 0) + 1 kwargs[_metadata_var]["previous_models"] = breadcrumbs # rebind-ok: the logging object already holds this dict + kwargs[_metadata_var]["request_retry_count"] = request_retry_count # rebind-ok: same dict, read by the cap return kwargs def _update_usage(self, deployment_id: str, parent_otel_span: Span | None) -> int: @@ -13042,9 +13048,10 @@ class Router: start_time: Final = time.time() if strategy == "simple-shuffle": return simple_shuffle( - llm_router_instance=self, + resolve_model_alias=self._get_model_from_alias, healthy_deployments=healthy_deployments, model=model, + request_kwargs=request_kwargs, ) deployment: Final = await self._select_deployment_async( strategy=strategy, @@ -13187,9 +13194,10 @@ class Router: start_time: Final = time.perf_counter() if strategy == "simple-shuffle": return simple_shuffle( - llm_router_instance=self, + resolve_model_alias=self._get_model_from_alias, healthy_deployments=pass_through_deployments, model=model, + request_kwargs=request_kwargs, ) deployment: Final = await self._select_deployment_async( strategy=strategy, @@ -13878,15 +13886,17 @@ class Router: cooldown_time=_cooldown_time, enable_pre_call_checks=self.enable_pre_call_checks, cooldown_list=_cooldown_list, + model_ids=model_ids, ) if strategy == "simple-shuffle": # if users pass rpm or tpm, we do a random weighted pick - based on rpm/tpm ############## Check 'weight' param set for weighted pick ################# return simple_shuffle( - llm_router_instance=self, + resolve_model_alias=self._get_model_from_alias, healthy_deployments=healthy_deployments, model=model, + request_kwargs=request_kwargs, ) deployment: Final = self._select_deployment_sync( strategy=strategy, @@ -13910,6 +13920,7 @@ class Router: cooldown_time=_cooldown_time, enable_pre_call_checks=self.enable_pre_call_checks, cooldown_list=_cooldown_list, + model_ids=model_ids, ) self._override_selector_pre_call_check(strategy, strategy_selector, deployment) verbose_router_logger.info( @@ -13953,6 +13964,7 @@ class Router: messages=messages, input=input, specific_deployment=specific_deployment, + request_kwargs=request_kwargs, ) strategy, strategy_selector = self._get_routing_context(model, request_kwargs) @@ -13987,6 +13999,11 @@ class Router: model=model, llm_provider="", ) + pass_through_model_ids: Final = tuple( + deployment["model_info"]["id"] + for deployment in pass_through_deployments + if "id" in deployment.get("model_info", {}) + ) # 4. Apply health-check and cooldown filtering parent_otel_span: Final[Span | None] = _get_parent_otel_span_from_kwargs(request_kwargs) @@ -14024,14 +14041,16 @@ class Router: cooldown_time=_cooldown_time, enable_pre_call_checks=self.enable_pre_call_checks, cooldown_list=_cooldown_list, + model_ids=pass_through_model_ids, ) # 6. Apply load balancing strategy if strategy == "simple-shuffle": return simple_shuffle( - llm_router_instance=self, + resolve_model_alias=self._get_model_from_alias, healthy_deployments=pass_through_deployments, model=model, + request_kwargs=request_kwargs, ) deployment: Final = self._select_deployment_sync( strategy=strategy, @@ -14057,6 +14076,7 @@ class Router: cooldown_time=_cooldown_time, enable_pre_call_checks=self.enable_pre_call_checks, cooldown_list=_cooldown_list, + model_ids=model_ids, ) self._override_selector_pre_call_check(strategy, strategy_selector, deployment) diff --git a/litellm/router_strategy/simple_shuffle.py b/litellm/router_strategy/simple_shuffle.py index 860e89cea22..4f2c5e8d933 100644 --- a/litellm/router_strategy/simple_shuffle.py +++ b/litellm/router_strategy/simple_shuffle.py @@ -1,71 +1,67 @@ -""" -Returns a random deployment from the list of healthy deployments. +"""Choose among eligible deployments using request weights, then global metrics.""" -If weights are provided, it will return a deployment based on the weights. - -""" +from __future__ import annotations +import logging import random -from typing import TYPE_CHECKING, Any, Final +from collections.abc import Callable, Mapping, Sequence +from itertools import chain +from typing import Final, TypeVar -from litellm._logging import verbose_router_logger +from litellm.types.router_weights import validate_router_weights -if TYPE_CHECKING: - from litellm.router import Router as _Router +_DeploymentT = TypeVar("_DeploymentT", bound=Mapping[str, object]) +_ROUTER_LOGGER: Final = logging.getLogger("LiteLLM Router") - LitellmRouter = _Router -else: - LitellmRouter = Any + +def _metric_weight(deployment: Mapping[str, object], metric: str) -> float: + params: Final = deployment.get("litellm_params") + value: Final = params.get(metric) if isinstance(params, Mapping) else None + if value is None: + return 0.0 + if isinstance(value, (int, float)): + return float(value) + raise TypeError(f"Deployment {metric} must be numeric") + + +def _scoped_weights( + deployments: Sequence[Mapping[str, object]], + model: str, + request_kwargs: Mapping[str, object] | None, +) -> tuple[float, ...]: + settings: Final = validate_router_weights((request_kwargs or {}).get("_router_weights")) + model_weights: Final = settings.get(model) if settings is not None else None + if not model_weights: + return () + return tuple( + model_weights.get(str(info.get("id")), 0.0) if isinstance(info, Mapping) else 0.0 + for deployment in deployments + for info in (deployment.get("model_info"),) + ) def simple_shuffle( - llm_router_instance: LitellmRouter, - healthy_deployments: list[Any] | dict[Any, Any], + resolve_model_alias: Callable[[str], str | None], + healthy_deployments: Sequence[_DeploymentT], model: str, -) -> dict: - """ - Returns a random deployment from the list of healthy deployments. - - If weights are provided, it will return a deployment based on the weights. - - If users pass `rpm` or `tpm`, we do a random weighted pick - based on `rpm`/`tpm`. - - Args: - llm_router_instance: LitellmRouter instance - healthy_deployments: List of healthy deployments - model: Model name - - Returns: - Dict: A single healthy deployment - """ - - ############## Check if 'weight' or 'rpm' or 'tpm' param set for a weighted pick ################# - for weight_by in ["weight", "rpm", "tpm"]: - if any(m["litellm_params"].get(weight_by) is not None for m in healthy_deployments): - weights = [m["litellm_params"].get(weight_by, 0) for m in healthy_deployments] - verbose_router_logger.debug("\nweight %s", weights) - total_weight = sum(weights) - if total_weight <= 0: - # All remaining candidates have weight 0 for this metric (e.g. - # after a weighted-failover exclusion left only zero-weight - # backups). Skip to the next metric (rpm/tpm) which may still - # provide a meaningful weighted pick; if none do, we fall - # through to the uniform random pick at the end. - continue - weights = [weight / total_weight for weight in weights] - verbose_router_logger.debug("\n weights %s by %s", weights, weight_by) - # Perform weighted random pick - selected_index = random.choices(range(len(weights)), weights=weights)[0] - verbose_router_logger.debug("\n selected index, %s", selected_index) - deployment = healthy_deployments[selected_index] - verbose_router_logger.info( - "get_available_deployment for model: %s, Selected deployment: %s for model: %s", - model, - llm_router_instance.print_deployment(deployment) or deployment[0], - model, - ) - return deployment or deployment[0] - - ############## No RPM/TPM passed, we do a random pick ################# - item: Final = random.choice(healthy_deployments) - return item or item[0] + request_kwargs: Mapping[str, object] | None, +) -> _DeploymentT: + resolved_model: Final = resolve_model_alias(model) or model + weight_sets: Final = chain( + (_scoped_weights(healthy_deployments, resolved_model, request_kwargs),), + ( + tuple(_metric_weight(deployment, metric) for deployment in healthy_deployments) + for metric in ("weight", "rpm", "tpm") + ), + ) + for weights in weight_sets: + largest = max(weights, default=0.0) + if largest <= 0: + continue + normalized = tuple(weight / largest for weight in weights) + if sum(normalized) <= 0: + continue + selected = random.choices(healthy_deployments, weights=normalized)[0] + _ROUTER_LOGGER.info("Selected deployment for model %s: %s", model, selected.get("model_info")) + return selected + return random.choice(healthy_deployments) diff --git a/litellm/router_utils/cooldown_handlers.py b/litellm/router_utils/cooldown_handlers.py index f722b6fd20c..027f0a9ca05 100644 --- a/litellm/router_utils/cooldown_handlers.py +++ b/litellm/router_utils/cooldown_handlers.py @@ -343,8 +343,9 @@ def _should_cooldown_deployment( model_group: Final = litellm_router_instance.get_model_group(id=deployment) is_single_deployment_model_group = False if model_group is not None and len(model_group) == 1: - is_single_deployment_model_group = not litellm_router_instance.routing_group_has_alternatives( - requested_model_group + is_single_deployment_model_group = not ( + litellm_router_instance.routing_group_has_alternatives(requested_model_group) + or litellm_router_instance.team_model_has_alternatives(deployment) ) ## CHECK DEPLOYMENT-LEVEL POLICY FIRST (overrides router-level) diff --git a/litellm/router_utils/handle_error.py b/litellm/router_utils/handle_error.py index 0e7490d31b1..bfe02675162 100644 --- a/litellm/router_utils/handle_error.py +++ b/litellm/router_utils/handle_error.py @@ -93,4 +93,5 @@ async def async_raise_no_deployment_exception( cooldown_time=_cooldown_time, enable_pre_call_checks=litellm_router_instance.enable_pre_call_checks, cooldown_list=cooldown_list_ids, + model_ids=model_ids, ) 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 cdd70e6baf2..cb5c3089685 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 @@ -48,6 +48,7 @@ from litellm.exceptions import ( ServiceUnavailableError, ) from litellm.integrations.custom_logger import CustomLogger, Span +from litellm.litellm_core_utils.credential_accessor import CredentialAccessor from litellm.litellm_core_utils.prompt_templates.common_utils import ( encrypted_content_of_block, strip_encrypted_reasoning_from_messages, @@ -215,11 +216,11 @@ class EncryptedContentAffinityCheck(CustomLogger): @staticmethod def _encryption_boundary_key( litellm_params: object, - ) -> tuple | None: + ) -> tuple[object, object] | None: """ - ``(api_base, api_key)`` pair identifying an Azure resource. Two - deployments sharing both are interchangeable for ``encrypted_content`` - follow-ups; Azure rejects content produced by any other resource. + ``(api_base, api_key)`` identifies an upstream encryption boundary. + The values are resolved from the deployment and its named credential + without modifying the deployment. Accepts any object exposing dict-style ``.get(key, default)``: plain dicts (the common case in ``healthy_deployments``) as well as @@ -234,9 +235,25 @@ class EncryptedContentAffinityCheck(CustomLogger): return None api_base: Final = getter("api_base") api_key: Final = getter("api_key") - if not api_base or not 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_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: return None - return (api_base, api_key) + return (effective_api_base, effective_api_key) def _find_deployments_on_same_encryption_boundary( self, diff --git a/litellm/rust_bridge/lifecycle.py b/litellm/rust_bridge/lifecycle.py index f5e0c1b0fc6..f1cc912129d 100644 --- a/litellm/rust_bridge/lifecycle.py +++ b/litellm/rust_bridge/lifecycle.py @@ -99,23 +99,13 @@ def setup( def check_limits(kwargs: Mapping[str, object]) -> None: import litellm + from litellm.litellm_core_utils.core_helpers import max_retries_per_request_hit current_cost: Final = litellm._current_cost # pyright: ignore[reportPrivateUsage] # shared SDK budget counter has no public accessor if litellm.max_budget and current_cost > litellm.max_budget: raise litellm.BudgetExceededError(current_cost=current_cost, max_budget=litellm.max_budget) - metadata: Final = kwargs.get("metadata") - if isinstance(metadata, Mapping): - typed_metadata: Final = cast( # cast-ok: runtime Mapping check establishes read-only metadata - Mapping[str, object], metadata - ) - previous: Final = typed_metadata.get("previous_models") - if ( - isinstance(previous, list) - and litellm.num_retries_per_request is not None - and len(cast(list[object], previous)) # cast-ok: runtime list check establishes the retry history - >= litellm.num_retries_per_request - ): - raise RuntimeError("Max retries per request hit!") + if max_retries_per_request_hit(kwargs, litellm.num_retries_per_request): + raise RuntimeError("Max retries per request hit!") def finalize( diff --git a/litellm/types/guardrails.py b/litellm/types/guardrails.py index 69cb88bfa2f..ab2f9edea1d 100644 --- a/litellm/types/guardrails.py +++ b/litellm/types/guardrails.py @@ -552,6 +552,16 @@ class BedrockGuardrailConfigModel(BaseModel): "still rejects is bisected automatically, so this value only trades round trips against " "batch size and cannot fail a request on its own.", ) + contextual_grounding_from_messages: bool = Field( + default=False, + description="ApplyGuardrail: when True, post-call scans of a request with no grounding_source / " + "query content parts send the system and developer messages as the grounding source and " + "the latest user message as the query, so the guardrail's contextual grounding policy can " + "score the response. Bedrock bills contextual grounding units for these scans and rejects " + "queries, sources and responses over its contextual grounding length limits, so leave this " + "off for guardrails without a contextual grounding policy. Default False: plain messages " + "are never sent as grounding context.", + ) class BedrockGuardrailStreamingParams(BaseModel): diff --git a/litellm/types/llms/base.py b/litellm/types/llms/base.py index f09727ad92b..938aa8064c9 100644 --- a/litellm/types/llms/base.py +++ b/litellm/types/llms/base.py @@ -75,3 +75,9 @@ class HiddenParams(OpenAIObject): data: Final = super().model_dump(**kwargs) data["_response_ms"] = self._response_ms return data + + +class CachedTokensDetails(BaseModel): + text_tokens: int | None = None + audio_tokens: int | None = None + image_tokens: int | None = None diff --git a/litellm/types/llms/meta.py b/litellm/types/llms/meta.py new file mode 100644 index 00000000000..40ecd6f7b67 --- /dev/null +++ b/litellm/types/llms/meta.py @@ -0,0 +1,21 @@ +from typing import Literal, TypeAlias + +from typing_extensions import NotRequired, ReadOnly, TypedDict + +MuseMode: TypeAlias = Literal["PUSH_TO_TALK", "ENDPOINTING"] +MuseAudioEncoding: TypeAlias = Literal["PCM_16KHZ", "PCM_24KHZ"] +MuseSampleRate: TypeAlias = Literal[16000, 24000] + + +class MuseAuthorization(TypedDict): + accessToken: ReadOnly[str] + + +class MuseHandshake(TypedDict): + authorization: ReadOnly[MuseAuthorization] + audioEncoding: ReadOnly[MuseAudioEncoding] + model: ReadOnly[str] + mode: ReadOnly[MuseMode] + partialMode: ReadOnly[Literal["CUMULATIVE"]] + emitAudioProgress: ReadOnly[bool] + languageBias: NotRequired[ReadOnly[tuple[str, ...]]] diff --git a/litellm/types/llms/openai.py b/litellm/types/llms/openai.py index 6612227f532..e3eac9b9205 100644 --- a/litellm/types/llms/openai.py +++ b/litellm/types/llms/openai.py @@ -91,6 +91,8 @@ from litellm.types.responses.main import ( OutputImageGenerationCall, ) +from .base import CachedTokensDetails + FileContent = IO[bytes] | bytes | PathLike FileTypes = ( @@ -1288,6 +1290,7 @@ class OutputTokensDetails(BaseLiteLLMOpenAIResponseObject): class InputTokensDetails(BaseLiteLLMOpenAIResponseObject): audio_tokens: int | None = None cached_tokens: int = 0 + cached_tokens_details: CachedTokensDetails | None = None text_tokens: int | None = None model_config = {"extra": "allow"} @@ -2190,6 +2193,53 @@ class OpenAIRealtimeInputAudioBufferSpeechEvent(TypedDict): item_id: ReadOnly[str] +class OpenAIRealtimeErrorDetail(TypedDict): + type: ReadOnly[str] + message: ReadOnly[str] + + +class OpenAIRealtimeErrorEvent(TypedDict): + type: ReadOnly[Literal["error"]] + error: ReadOnly[OpenAIRealtimeErrorDetail] + + +class OpenAIRealtimeTranscriptionAudioFormat(TypedDict): + type: ReadOnly[Literal["audio/pcm"]] + rate: ReadOnly[int] + + +class OpenAIRealtimeTranscriptionSettings(TypedDict): + model: ReadOnly[str] + language: NotRequired[ReadOnly[str]] + + +class OpenAIRealtimeServerVadTurnDetection(TypedDict): + type: ReadOnly[Literal["server_vad"]] + + +class OpenAIRealtimeTranscriptionAudioInput(TypedDict): + format: ReadOnly[OpenAIRealtimeTranscriptionAudioFormat] + transcription: ReadOnly[OpenAIRealtimeTranscriptionSettings] + turn_detection: ReadOnly[OpenAIRealtimeServerVadTurnDetection | None] + + +class OpenAIRealtimeTranscriptionAudio(TypedDict): + input: ReadOnly[OpenAIRealtimeTranscriptionAudioInput] + + +class OpenAIRealtimeTranscriptionSession(TypedDict): + id: ReadOnly[str] + object: ReadOnly[Literal["realtime.transcription_session"]] + type: ReadOnly[Literal["transcription"]] + audio: ReadOnly[OpenAIRealtimeTranscriptionAudio] + + +class OpenAIRealtimeTranscriptionSessionCreated(TypedDict): + type: ReadOnly[Literal["session.created"]] + event_id: ReadOnly[str] + session: ReadOnly[OpenAIRealtimeTranscriptionSession] + + class OpenAIRealtimeInputAudioTranscriptionDelta(TypedDict): type: ReadOnly[Literal["conversation.item.input_audio_transcription.delta"]] event_id: ReadOnly[str] @@ -2204,12 +2254,20 @@ class OpenAIRealtimeInputAudioTranscriptionCompleted(TypedDict): item_id: ReadOnly[str] content_index: ReadOnly[int] transcript: ReadOnly[str] + usage: NotRequired[ReadOnly[Mapping[str, object]]] + + +class OpenAIRealtimeCachedTokensDetails(TypedDict, total=False): + text_tokens: ReadOnly[int] + audio_tokens: ReadOnly[int] + image_tokens: ReadOnly[int] class OpenAIRealtimeUsageTokenDetails(TypedDict): audio_tokens: ReadOnly[int] text_tokens: ReadOnly[int] cached_tokens: NotRequired[ReadOnly[int]] + cached_tokens_details: NotRequired[ReadOnly[OpenAIRealtimeCachedTokensDetails]] class OpenAIRealtimeResponseUsage(TypedDict): @@ -2260,6 +2318,8 @@ OpenAIRealtimeEvents = ( | OpenAIRealtimeInputAudioBufferSpeechEvent | OpenAIRealtimeInputAudioTranscriptionDelta | OpenAIRealtimeInputAudioTranscriptionCompleted + | OpenAIRealtimeTranscriptionSessionCreated + | OpenAIRealtimeErrorEvent ) OpenAIRealtimeStreamList = list[OpenAIRealtimeEvents] diff --git a/litellm/types/management_endpoints/prompt_cache_prediction.py b/litellm/types/management_endpoints/prompt_cache_prediction.py new file mode 100644 index 00000000000..3789607b021 --- /dev/null +++ b/litellm/types/management_endpoints/prompt_cache_prediction.py @@ -0,0 +1,67 @@ +from collections.abc import Mapping +from typing import Annotated, Literal, TypeAlias + +from pydantic import BaseModel, ConfigDict, Field, JsonValue, StrictInt + +TokenCount: TypeAlias = Annotated[StrictInt, Field(ge=0)] + + +class CacheTokenBuckets(BaseModel): + model_config = ConfigDict(frozen=True, extra="forbid") + + uncached_input_tokens: TokenCount = 0 + cache_read_input_tokens: TokenCount = 0 + cache_creation_5m_input_tokens: TokenCount = 0 + cache_creation_1h_input_tokens: TokenCount = 0 + + @property + def total_tokens(self) -> int: + return ( + self.uncached_input_tokens + + self.cache_read_input_tokens + + self.cache_creation_5m_input_tokens + + self.cache_creation_1h_input_tokens + ) + + +class CacheEvidence(BaseModel): + model_config = ConfigDict(frozen=True) + + observed_at: float + expires_at: float + source: Literal["provider_usage"] = "provider_usage" + confidence: Literal["observed"] = "observed" + + +class CacheCostScenario(BaseModel): + tokens: CacheTokenBuckets + input_cost: float + + +class CachePredictionArm(BaseModel): + deployment_id: str + model: str | None = None + cache_state: Literal["warm", "partial", "stale", "unknown", "disabled"] = "unknown" + reason: str | None = None + estimate: CacheCostScenario | None = None + cold: CacheCostScenario | None = None + warm: CacheCostScenario | None = None + evidence: CacheEvidence | None = None + token_count_source: Literal["anthropic_count_tokens"] | None = None + + +class CachePredictionRequest(BaseModel): + model_config = ConfigDict(extra="forbid") + + current_deployment_id: str = Field(min_length=1, max_length=256) + candidate_deployment_id: str = Field(min_length=1, max_length=256) + request: Mapping[str, JsonValue] + + +class CachePredictionResponse(BaseModel): + stay: CachePredictionArm + switch: CachePredictionArm + switch_delta: float | None + cache_rebuild_penalty: float | None + pricing_basis: Literal["input_before_discounts_and_margins"] = "input_before_discounts_and_margins" + cache_guarantee: Literal[False] = False diff --git a/litellm/types/mcp_server/mcp_server_manager.py b/litellm/types/mcp_server/mcp_server_manager.py index 58f9dadc1ce..985d31af997 100644 --- a/litellm/types/mcp_server/mcp_server_manager.py +++ b/litellm/types/mcp_server/mcp_server_manager.py @@ -155,11 +155,9 @@ class MCPServer(BaseModel): access_groups: list[str] | None = None allow_all_keys: bool = False available_on_public_internet: bool = True - # Explicit opt-in to upstream-delegated authentication for ``oauth2`` - # servers. When ``auth_type == oauth2`` and this is ``True``, MCP requests - # bypass LiteLLM API-key/SSO auth (and the pre-emptive 401) so the client - # completes PKCE directly with the upstream MCP server. See - # ``MCPRequestHandler._target_servers_delegate_auth_to_upstream``. + # Legacy opt-in to upstream-delegated authentication for ``oauth2`` + # servers. LiteLLM admission still applies; use ``oauth_delegate`` for the + # supported client-forwarded OAuth flow. # # Honored only for ``auth_type == oauth2``; ignored for any other # ``auth_type``. OAuth pass-through for non-oauth2 servers diff --git a/litellm/types/proxy/auth/auth_checks.py b/litellm/types/proxy/auth/auth_checks.py new file mode 100644 index 00000000000..80c65d14113 --- /dev/null +++ b/litellm/types/proxy/auth/auth_checks.py @@ -0,0 +1,8 @@ +"""Failure values raised by `litellm/proxy/auth/auth_checks.py`. Kept free of `litellm` imports so any proxy module can import them without joining the `litellm.proxy` import cycle.""" + + +class UserNotFoundError(ValueError): + """The user row is provably absent, as opposed to merely unreadable, so a caller that reads a missing row as no user-level limits can key on it without also swallowing a database that would not answer.""" + + def __init__(self, user_id: str) -> None: + super().__init__(f"User doesn't exist in db. 'user_id'={user_id}. Create user via `/user/new` call.") diff --git a/litellm/types/proxy/discovery_endpoints/agent_skills_endpoints.py b/litellm/types/proxy/discovery_endpoints/agent_skills_endpoints.py new file mode 100644 index 00000000000..0d8bb29e172 --- /dev/null +++ b/litellm/types/proxy/discovery_endpoints/agent_skills_endpoints.py @@ -0,0 +1,25 @@ +"""Agent Skills discovery index, version 0.2.0. + +Schema: https://schemas.agentskills.io/discovery/0.2.0/schema.json +""" + +from typing import Final, Literal + +from pydantic import BaseModel, Field + +AGENT_SKILLS_DISCOVERY_SCHEMA_URL: Final = "https://schemas.agentskills.io/discovery/0.2.0/schema.json" +MAX_SKILL_NAME_LENGTH: Final = 64 +MAX_SKILL_DESCRIPTION_LENGTH: Final = 1024 + + +class AgentSkillsIndexEntry(BaseModel): + name: str + type: Literal["archive"] + description: str + url: str + digest: str + + +class AgentSkillsIndex(BaseModel): + discovery_schema: str = Field(default=AGENT_SKILLS_DISCOVERY_SCHEMA_URL, alias="$schema") + skills: tuple[AgentSkillsIndexEntry, ...] diff --git a/litellm/types/proxy/guardrails/guardrail_hooks/generic_guardrail_api.py b/litellm/types/proxy/guardrails/guardrail_hooks/generic_guardrail_api.py index 4a868c48352..44e2cc2404f 100644 --- a/litellm/types/proxy/guardrails/guardrail_hooks/generic_guardrail_api.py +++ b/litellm/types/proxy/guardrails/guardrail_hooks/generic_guardrail_api.py @@ -1,4 +1,5 @@ -from typing import Any, Final, Literal +from collections.abc import Mapping, Sequence +from typing import Any, Final, Literal, cast # noqa: TID251 # JSON chat rows have no typed constructor across roles from pydantic import BaseModel, ConfigDict, Field from typing_extensions import TypedDict @@ -158,12 +159,21 @@ def coerce_stream_holdback_value(value: Any) -> int: return 0 +def structured_messages_from_response(value: object) -> Sequence[AllMessageValues] | None: + if not isinstance(value, list): + return None + if not all(isinstance(message, Mapping) and isinstance(message.get("role"), str) for message in value): + return None + return cast("Sequence[AllMessageValues]", value) # cast-ok: JSON rows checked for a role, the same trust texts get + + class GenericGuardrailAPIResponse: """Response model for the Generic Guardrail API""" texts: list[str] | None images: list[str] | None tools: list[GuardrailToolParam] | None + structured_messages: Sequence[AllMessageValues] | None action: str blocked_reason: str | None stream_holdback_chars: list[int] | None @@ -176,12 +186,14 @@ class GenericGuardrailAPIResponse: images: list[str] | None = None, tools: list[GuardrailToolParam] | None = None, stream_holdback_chars: list[int] | None = None, + structured_messages: Sequence[AllMessageValues] | None = None, ) -> None: self.action = action self.blocked_reason = blocked_reason self.texts = texts self.images = images self.tools = tools + self.structured_messages = structured_messages # Number of trailing chars, indexed the same as ``texts``, that the # framework must withhold from streaming emission until the next # processing round (word-boundary safety for text transformations). @@ -200,4 +212,5 @@ class GenericGuardrailAPIResponse: images=data.get("images"), tools=data.get("tools"), stream_holdback_chars=stream_holdback_chars, + structured_messages=structured_messages_from_response(data.get("structured_messages")), ) diff --git a/litellm/types/proxy/management_endpoints/common_daily_activity.py b/litellm/types/proxy/management_endpoints/common_daily_activity.py index 2b39c5dbb9b..090e5c42376 100644 --- a/litellm/types/proxy/management_endpoints/common_daily_activity.py +++ b/litellm/types/proxy/management_endpoints/common_daily_activity.py @@ -43,6 +43,7 @@ class KeyMetadata(BaseModel): key_alias: str | None = None team_id: str | None = None + user_id: str | None = None user_email: str | None = None diff --git a/litellm/types/realtime.py b/litellm/types/realtime.py index 17dc70126f3..30db794c96e 100644 --- a/litellm/types/realtime.py +++ b/litellm/types/realtime.py @@ -169,9 +169,19 @@ class RealtimeInputAudioTranscriptionUsageInputTokenDetails(TypedDict): audio_tokens: ReadOnly[int] -class RealtimeInputAudioTranscriptionUsage(TypedDict): +class RealtimeInputAudioTranscriptionTokenUsage(TypedDict): type: ReadOnly[Literal["tokens"]] input_tokens: ReadOnly[int] output_tokens: ReadOnly[int] total_tokens: ReadOnly[int] input_token_details: ReadOnly[RealtimeInputAudioTranscriptionUsageInputTokenDetails] + + +class RealtimeInputAudioTranscriptionDurationUsage(TypedDict): + type: ReadOnly[Literal["duration"]] + seconds: ReadOnly[float] + + +RealtimeInputAudioTranscriptionUsage = ( + RealtimeInputAudioTranscriptionTokenUsage | RealtimeInputAudioTranscriptionDurationUsage +) diff --git a/litellm/types/router.py b/litellm/types/router.py index fc09c40fe08..49109e4fbbe 100644 --- a/litellm/types/router.py +++ b/litellm/types/router.py @@ -15,6 +15,7 @@ from typing_extensions import Protocol, ReadOnly, Required, TypedDict, runtime_c from litellm._logging import verbose_logger from litellm._uuid import uuid from litellm.litellm_core_utils.core_helpers import normalize_drop_params +from litellm.types.router_weights import RouterWeights if TYPE_CHECKING: from litellm.router import Router @@ -146,6 +147,7 @@ class UpdateRouterConfig(BaseModel): context_window_fallbacks: list[dict] | None = None model_group_alias: dict[str, str | dict] | None = {} enable_tag_filtering: bool | None = None + weights: RouterWeights | None = None tag_routing_prefix: str | None = None optional_pre_call_checks: OptionalPreCallChecks | None = None @@ -268,6 +270,12 @@ class CredentialLiteLLMParams(BaseModel): # callers see it, breaking Azure deployments configured with # ``azure_ad_token`` instead of a static ``api_key`` (#30235). azure_ad_token: str | None = None + tenant_id: str | None = None + client_id: str | None = None + client_secret: str | None = None + azure_scope: str | None = None + azure_username: str | None = None + azure_password: str | None = None ## VERTEX AI ## vertex_project: str | None = None vertex_location: str | None = None @@ -639,6 +647,7 @@ class RouterErrors(enum.Enum): user_defined_ratelimit_error = "Deployment over user-defined ratelimit." no_deployments_available = "No deployments available for selected model" + all_deployments_in_cooldown = "All deployments for selected model are in cooldown" no_deployments_with_tag_routing = "Not allowed to access model due to tags configuration" no_deployments_with_provider_budget_routing = "No deployments available - crossed budget" no_healthy_deployments = "There are no healthy deployments for this model" @@ -862,6 +871,11 @@ class RouterRateLimitErrorBasic(ValueError): super().__init__(_message) +class RouterErrorTypes(str, enum.Enum): + rate_limit_error = "rate_limit_error" + all_deployments_in_cooldown = "all_deployments_in_cooldown" + + class RouterRateLimitError(ValueError): def __init__( self, @@ -869,12 +883,25 @@ class RouterRateLimitError(ValueError): cooldown_time: float, enable_pre_call_checks: bool, cooldown_list: list, + model_ids: Sequence[str] = (), ) -> None: self.model = model self.cooldown_time = cooldown_time self.enable_pre_call_checks = enable_pre_call_checks self.cooldown_list = cooldown_list - _message = f"{RouterErrors.no_deployments_available.value}, Try again in {cooldown_time} seconds. Passed model={model}. pre-call-checks={enable_pre_call_checks}, cooldown_list={cooldown_list}" + self.all_deployments_in_cooldown = bool(model_ids) and frozenset(model_ids) <= frozenset(cooldown_list) + self.type = ( + RouterErrorTypes.all_deployments_in_cooldown.value + if self.all_deployments_in_cooldown + else RouterErrorTypes.rate_limit_error.value + ) + _reason: Final = ( + f" {RouterErrors.all_deployments_in_cooldown.value}." if self.all_deployments_in_cooldown else "" + ) + _message: Final = ( + f"{RouterErrors.no_deployments_available.value}, Try again in {cooldown_time} seconds.{_reason} " + f"Passed model={model}. pre-call-checks={enable_pre_call_checks}, cooldown_list={cooldown_list}" + ) super().__init__(_message) @@ -883,6 +910,14 @@ class RouterModelGroupAliasItem(TypedDict): hidden: bool # if 'True', don't return on `.get_model_list` +class RetryAttemptRecord(TypedDict): + model_group: ReadOnly[str | None] + deployment_id: ReadOnly[str | None] + exception_type: ReadOnly[str] + exception_string: ReadOnly[str] + attempted_retries: ReadOnly[int | None] + + VALID_LITELLM_ENVIRONMENTS = [ "development", "staging", diff --git a/litellm/types/router_weights.py b/litellm/types/router_weights.py new file mode 100644 index 00000000000..fa156661564 --- /dev/null +++ b/litellm/types/router_weights.py @@ -0,0 +1,30 @@ +from collections.abc import Mapping +from typing import Annotated, Final + +from pydantic import AfterValidator, Field, TypeAdapter + + +def _validate_positive_router_weights(weights: Mapping[str, Mapping[str, float]]) -> Mapping[str, Mapping[str, float]]: + if any(group and not any(weight > 0 for weight in group.values()) for group in weights.values()): + raise ValueError("Each nonempty weights group must contain at least one positive weight") + return weights + + +RouterWeightIdentifier = Annotated[str, Field(strict=True, min_length=1, pattern=r"\S")] +RouterWeight = Annotated[float, Field(strict=True, ge=0, allow_inf_nan=False)] +RouterWeights = Annotated[ + dict[RouterWeightIdentifier, dict[RouterWeightIdentifier, RouterWeight]], + AfterValidator(_validate_positive_router_weights), +] +_ROUTER_WEIGHTS_ADAPTER: Final[TypeAdapter[RouterWeights | None]] = TypeAdapter(RouterWeights | None) +_ROUTER_SETTINGS_DICT_ADAPTER: Final = TypeAdapter(dict[str, object]) + + +def validate_router_weights(value: object) -> RouterWeights | None: + return _ROUTER_WEIGHTS_ADAPTER.validate_python(value) + + +def validate_router_settings_dict(value: object) -> dict[str, object]: + settings: Final = _ROUTER_SETTINGS_DICT_ADAPTER.validate_python(value) + validate_router_weights(settings.get("weights")) + return settings diff --git a/litellm/types/utils.py b/litellm/types/utils.py index e3ea37dc0c8..8bab7c349ff 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -1,4 +1,5 @@ import json +import re import time from collections.abc import Mapping, Sequence from enum import Enum @@ -47,6 +48,7 @@ from litellm._logging import verbose_logger from litellm._uuid import uuid from litellm.types.llms.base import ( BaseLiteLLMOpenAIResponseObject, + CachedTokensDetails, LiteLLMPydanticObjectBase, ) from litellm.types.mcp import MCPServerCostInfo @@ -169,6 +171,7 @@ class ProviderSpecificModelInfo(TypedDict, total=False): default_reasoning_effort: ReadOnly[Literal["none", "minimal", "low", "medium", "high", "xhigh"] | None] supports_output_config: bool | None supports_image_size: bool | None + supports_anthropic_thinking_payload: ReadOnly[bool | None] supported_audio_formats: ReadOnly[Sequence[Literal["mp3", "wav"]] | None] vertex_ai_audio_api: ReadOnly[Literal["lyria_predict", "lyria_interactions"] | None] bedrock_output_config_effort_ceiling: Literal["low", "medium", "high", "max", "xhigh"] | None @@ -250,6 +253,7 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): cache_creation_input_token_cost_priority: float | None # OpenAI priority service tier pricing cache_creation_input_token_cost_ultrafast: ReadOnly[float | None] # OpenAI ultrafast service tier pricing cache_read_input_token_cost: float | None + cache_read_input_audio_token_cost: ReadOnly[float | None] cache_read_input_token_cost_flex: float | None # OpenAI flex service tier pricing cache_read_input_token_cost_priority: float | None # OpenAI priority service tier pricing cache_read_input_token_cost_ultrafast: ReadOnly[float | None] # OpenAI ultrafast service tier pricing @@ -279,8 +283,11 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False): input_cost_per_video_token: float | None # for gemini omni models with video input input_cost_per_audio_per_second: float | None # only for vertex ai models input_cost_per_video_per_second: float | None # only for vertex ai models + input_cost_per_audio_token_batches: ReadOnly[float | None] + input_cost_per_image_token_batches: ReadOnly[float | None] input_cost_per_second: float | None # for OpenAI Speech models input_cost_per_token_batches: float | None + input_cost_per_video_token_batches: ReadOnly[float | None] output_cost_per_token_batches: float | None output_cost_per_token: Required[float | None] output_cost_per_token_flex: float | None # OpenAI flex service tier pricing @@ -1708,6 +1715,9 @@ class PromptTokensDetailsWrapper( cache_creation_token_details: CacheCreationTokenDetails | None = None """Details of cache creation tokens sent to the model. Used for tracking 5m/1h cache creation tokens for Anthropic prompt caching.""" + cached_tokens_details: CachedTokensDetails | None = None + """Details of cached (cache-hit) tokens sent to the model. OpenAI realtime naming; carries the per-modality cache-read split.""" + def __setattr__(self, name: str, value: object) -> None: super().__setattr__(name, value) if name == "cache_write_tokens": @@ -1754,6 +1764,8 @@ class PromptTokensDetailsWrapper( del self.cache_creation_tokens if self.cache_creation_token_details is None: del self.cache_creation_token_details + if self.cached_tokens_details is None: + del self.cached_tokens_details class ServerToolUse(BaseModel): @@ -3574,7 +3586,10 @@ class CustomPricingLiteLLMParams(MirroredPricingParams): input_cost_per_video_per_second_above_128k_tokens: float | None = None input_cost_per_video_per_second_above_15s_interval: float | None = None input_cost_per_video_per_second_above_8s_interval: float | None = None + input_cost_per_audio_token_batches: float | None = None + input_cost_per_image_token_batches: float | None = None input_cost_per_token_batches: float | None = None + input_cost_per_video_token_batches: float | None = None output_cost_per_token_batches: float | None = None output_cost_per_token_flex: float | None = None output_cost_per_token_priority: float | None = None @@ -3645,6 +3660,38 @@ def shared_backend_model_info(model_info: dict[str, Any]) -> dict[str, Any]: return {k: v for k, v in model_info.items() if k in SHARED_BACKEND_MODEL_INFO_FIELDS} +ABOVE_THRESHOLD_COST_KEY_PATTERN: Final = re.compile(r"_above_\d+k?_tokens$") + +_PRICING_FIELD_EXEMPTIONS: Final[frozenset[str]] = frozenset({"output_vector_size"}) + +SERVER_DERIVED_PRICING_FIELDS: Final[frozenset[str]] = ( + frozenset(CustomPricingLiteLLMParams.model_fields) - _PRICING_FIELD_EXEMPTIONS +) + + +def is_server_derived_pricing_key(key: str) -> bool: + """Whether ``/model/info`` can fill ``key`` into ``model_info`` from the cost map. + + Two sources, because ``get_model_info`` emits two: the declared pricing fields, and + the tiered ``*_above__tokens`` rates that ride through on a pattern match and are + declared nowhere. Both are read here from the same objects the read path uses, so the + set cannot drift as new rates are added. + """ + return key in SERVER_DERIVED_PRICING_FIELDS or ABOVE_THRESHOLD_COST_KEY_PATTERN.search(key) is not None + + +def without_server_derived_pricing(model_info: Mapping[str, Any]) -> Mapping[str, Any]: + """Drop the pricing ``/model/info`` derives for display, keeping everything else. + + ``/model/info`` fills a deployment's missing pricing in from the cost map so the + Admin UI has a rate to show. Clients that echo that response back on save would + otherwise persist the display value as a real per-deployment override, freezing the + deployment at that day's price where no cost map refresh can reach it. A deployment's + own pricing belongs on ``litellm_params``, which is unaffected. + """ + return MappingProxyType({k: v for k, v in model_info.items() if not is_server_derived_pricing_key(k)}) + + # Server-controlled fields that bound or drive an interceptor's agentic loop # (depth, cycle fingerprints, ceiling, code-interpreter sandbox state). Listed # in all_litellm_params so they are treated as LiteLLM-level and excluded from @@ -3720,11 +3767,22 @@ all_litellm_params = ( "model_file_id_mapping", "litellm_logging_obj", "litellm_call_id", + "completion_call_id", + "model_alias_map", + "custom_prompt_dict", + "stream_response", + "cost_per_query", + "ssl_verify", + "data_residency", + "async_call", + "aembedding", + "allm_passthrough_route", "_litellm_strip_stream_usage", "use_client", "id", "fallbacks", "routing_strategy", + "_router_weights", "azure", "headers", "model_list", diff --git a/litellm/utils.py b/litellm/utils.py index 1a77655a5a4..18df5e2abf7 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -84,6 +84,7 @@ from litellm.constants import ( from litellm.litellm_core_utils.core_helpers import normalize_drop_params from litellm.litellm_core_utils.fallback_generalizations import ( match_capability_generalizations, + match_fill_missing_generalizations, ) from litellm.litellm_core_utils.sensitive_data_masker import redact_credentials_in_payload @@ -216,6 +217,7 @@ from litellm.types.llms.openai import ( OpenAIWebSearchOptions, ) from litellm.types.utils import ( + ABOVE_THRESHOLD_COST_KEY_PATTERN, OPENAI_RESPONSE_HEADERS, CallTypes, ChatCompletionDeltaToolCall, @@ -253,6 +255,7 @@ from litellm.types.utils import ( ) _CALL_TYPE_ENUM_MAP: Final[dict] = {ct.value: ct for ct in CallTypes} +_BACKFILL_MODES: Final = frozenset({"chat", "responses"}) # +-----------------------------------------------+ # | | @@ -1205,30 +1208,13 @@ def _dispatch_success_logging( is_litellm_internal_call: bool, ) -> None: if not is_litellm_internal_call: - if getattr(logging_obj, "_defer_async_logging", False): - - def _enqueue_deferred_logging() -> None: - asyncio.create_task( - _client_async_logging_helper( - logging_obj=logging_obj, - result=result, - start_time=start_time, - end_time=end_time, - is_completion_with_fallbacks=is_completion_with_fallbacks, - ) - ) - - logging_obj._enqueue_deferred_logging = _enqueue_deferred_logging - else: - asyncio.create_task( - _client_async_logging_helper( - logging_obj=logging_obj, - result=result, - start_time=start_time, - end_time=end_time, - is_completion_with_fallbacks=is_completion_with_fallbacks, - ) - ) + _schedule_async_success_logging( + logging_obj=logging_obj, + result=result, + start_time=start_time, + end_time=end_time, + is_completion_with_fallbacks=is_completion_with_fallbacks, + ) logging_obj.handle_sync_success_callbacks_for_async_calls( result=result, @@ -1237,6 +1223,43 @@ def _dispatch_success_logging( ) +def _schedule_async_success_logging( + logging_obj: LiteLLMLoggingObject, + result: object, + start_time: datetime.datetime, + end_time: datetime.datetime, + is_completion_with_fallbacks: bool, +) -> None: + """Fire the async success log for ``result`` now, or park it on the logging object while + the proxy defers logging past its post-call guardrails. + + Nested @client wrappers (Anthropic Messages over the chat adapter, chat over the Responses + bridge) each exit through here with the same logging object and their own shape of the same + response. The immediate path already logs one request once, since the first task marks + ``has_logged_async_success`` and the later ones skip. The deferred slot keeps the same + first-wins rule: the innermost wrapper's provider-shaped result is the one the spend log + reads usage from, and a later wrapper never swaps in its client-shaped translation. + """ + + def _enqueue_async_logging() -> None: + asyncio.create_task( + _client_async_logging_helper( + logging_obj=logging_obj, + result=result, + start_time=start_time, + end_time=end_time, + is_completion_with_fallbacks=is_completion_with_fallbacks, + ) + ) + + if not getattr(logging_obj, "_defer_async_logging", False): + _enqueue_async_logging() + return + if getattr(logging_obj, "_enqueue_deferred_logging", None) is not None: + return + logging_obj._enqueue_deferred_logging = _enqueue_async_logging + + async def _client_async_logging_helper( logging_obj: LiteLLMLoggingObject, result, @@ -1259,15 +1282,6 @@ async def _client_async_logging_helper( async_coroutine=logging_obj.async_success_handler(result=result, start_time=start_time, end_time=end_time) ) - ################################################ - # Sync Logging Worker - ################################################ - logging_obj.handle_sync_success_callbacks_for_async_calls( - result=result, - start_time=start_time, - end_time=end_time, - ) - def _get_wrapper_num_retries(kwargs: dict[str, Any], exception: Exception) -> tuple[int | None, dict[str, Any]]: """ @@ -1499,6 +1513,8 @@ def post_call_processing( def client(original_function): + from litellm.litellm_core_utils.core_helpers import max_retries_per_request_hit + Rules: Final = litellm_utils.Rules rules_obj: Final = Rules() @@ -1509,12 +1525,8 @@ def client(original_function): call_type = original_function.__name__ if _is_async_request(kwargs): # [OPTIONAL] CHECK MAX RETRIES / REQUEST - if litellm.num_retries_per_request is not None: - # check if previous_models passed in as ['litellm_params']['metadata]['previous_models'] - previous_models = (kwargs.get("metadata") or {}).get("previous_models", None) - if previous_models is not None: - if litellm.num_retries_per_request <= len(previous_models): - raise Exception("Max retries per request hit!") + if max_retries_per_request_hit(kwargs, litellm.num_retries_per_request): + raise Exception("Max retries per request hit!") # MODEL CALL result = original_function(*args, **kwargs) @@ -1573,12 +1585,8 @@ def client(original_function): ) # [OPTIONAL] CHECK MAX RETRIES / REQUEST - if litellm.num_retries_per_request is not None: - # check if previous_models passed in as ['litellm_params']['metadata]['previous_models'] - previous_models = (kwargs.get("metadata") or {}).get("previous_models", None) - if previous_models is not None: - if litellm.num_retries_per_request <= len(previous_models): - raise Exception("Max retries per request hit!") + if max_retries_per_request_hit(kwargs, litellm.num_retries_per_request): + raise Exception("Max retries per request hit!") # [OPTIONAL] CHECK CACHE print_verbose( @@ -2850,6 +2858,12 @@ def supports_reasoning(model: str, custom_llm_provider: str | None = None) -> bo return _supports_factory(model=model, custom_llm_provider=custom_llm_provider, key="supports_reasoning") +def supports_anthropic_thinking_payload(model: str, custom_llm_provider: str | None = None) -> bool: + return _supports_factory( + model=model, custom_llm_provider=custom_llm_provider, key="supports_anthropic_thinking_payload" + ) + + def supports_none_reasoning_effort(model: str, custom_llm_provider: str | None = None) -> bool: """ Check if the given model accepts reasoning effort "none" and return a boolean value. @@ -5556,12 +5570,21 @@ def _get_potential_model_names(model: str, custom_llm_provider: str | None) -> P split_model = strip_bedrock_routing_prefix(split_model) + provider_model_info: Final = ( + ProviderConfigManager.get_provider_model_info(model=split_model, provider=LlmProviders(custom_llm_provider)) + if custom_llm_provider in LlmProvidersSet + else None + ) + provider_cost_key: Final = ( + provider_model_info.get_model_cost_key(split_model) if provider_model_info is not None else None + ) + return PotentialModelNamesAndCustomLLMProvider( split_model=split_model, combined_model_name=combined_model_name, stripped_model_name=stripped_model_name, combined_stripped_model_name=combined_stripped_model_name, - provider_prefixed_model_name=provider_prefixed_model_name, + provider_prefixed_model_name=provider_cost_key or provider_prefixed_model_name, custom_llm_provider=cast(str, custom_llm_provider), ) @@ -5637,7 +5660,7 @@ def _is_potential_model_name_in_model_cost( ) -_ABOVE_THRESHOLD_COST_KEY: Final = re.compile(r"_above_\d+k?_tokens$") +_ABOVE_THRESHOLD_COST_KEY: Final = ABOVE_THRESHOLD_COST_KEY_PATTERN def _get_model_info_helper( @@ -5803,6 +5826,14 @@ def _get_model_info_helper( ): _model_info = None + if _model_info is not None and key is not None and _model_info.get("mode", "chat") in _BACKFILL_MODES: + fill_missing: Final = match_fill_missing_generalizations(key, _model_info.get("litellm_provider", "")) + if fill_missing is not None: + _model_info = { + **{k: v for k, v in fill_missing.items() if k not in _model_info}, + **_model_info, + } + if _model_info is None: generalization: Final = _get_model_info_from_generalization( model=model, @@ -5866,6 +5897,7 @@ def _get_model_info_helper( "cache_creation_input_token_cost_ultrafast", None ), cache_read_input_token_cost=_model_info.get("cache_read_input_token_cost", None), + cache_read_input_audio_token_cost=_model_info.get("cache_read_input_audio_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 @@ -5911,10 +5943,13 @@ def _get_model_info_helper( input_cost_per_audio_token=_model_info.get("input_cost_per_audio_token", 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), + input_cost_per_audio_token_batches=_model_info.get("input_cost_per_audio_token_batches", None), + input_cost_per_image_token_batches=_model_info.get("input_cost_per_image_token_batches", None), input_cost_per_image=_model_info.get("input_cost_per_image", None), input_cost_per_audio_per_second=_model_info.get("input_cost_per_audio_per_second", None), input_cost_per_video_per_second=_model_info.get("input_cost_per_video_per_second", None), input_cost_per_token_batches=_model_info.get("input_cost_per_token_batches"), + input_cost_per_video_token_batches=_model_info.get("input_cost_per_video_token_batches", None), output_cost_per_token_batches=_model_info.get("output_cost_per_token_batches"), output_cost_per_token=_output_cost_per_token, output_cost_per_token_flex=_model_info.get("output_cost_per_token_flex", None), @@ -5996,6 +6031,7 @@ def _get_model_info_helper( thinking_always_on=_model_info.get("thinking_always_on", 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), supports_none_reasoning_effort=_model_info.get("supports_none_reasoning_effort", None), supports_minimal_reasoning_effort=_model_info.get("supports_minimal_reasoning_effort", None), supports_low_reasoning_effort=_model_info.get("supports_low_reasoning_effort", None), @@ -6247,7 +6283,7 @@ def function_to_dict(input_function) -> dict: "enum": param_enum, } - parameters[param_name] = dict([(k, v) for k, v in param_dict.items() if isinstance(v, str)]) + parameters[param_name] = {k: v for k, v in param_dict.items() if isinstance(v, str)} # Check if the parameter has no default value (i.e., it's required) if param.default == param.empty: @@ -9285,6 +9321,10 @@ class ProviderConfigManager: from litellm.llms.gemini.realtime.transformation import GeminiRealtimeConfig return GeminiRealtimeConfig() + if LlmProviders.META == provider: + from litellm.llms.meta.realtime.transformation import MetaRealtimeConfig + + return MetaRealtimeConfig() return None @staticmethod diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 7fa09951eae..9f91cf82f41 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -4497,7 +4497,7 @@ }, "azure/eu/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.65e-05, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -4543,7 +4543,7 @@ }, "azure/eu/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, - "deprecation_date": "2026-10-01", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -5513,7 +5513,8 @@ }, "azure/gpt-realtime-2025-08-28": { "cache_creation_input_audio_token_cost": 4e-06, - "cache_read_input_token_cost": 4e-06, + "cache_read_input_audio_token_cost": 4e-07, + "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-03-02", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, @@ -5546,7 +5547,8 @@ }, "azure/gpt-realtime-1.5-2026-02-23": { "cache_creation_input_audio_token_cost": 4e-06, - "cache_read_input_token_cost": 4e-06, + "cache_read_input_audio_token_cost": 4e-07, + "cache_read_input_token_cost": 4e-07, "deprecation_date": "2027-08-24", "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, @@ -5683,6 +5685,7 @@ }, "azure/gpt-realtime-mini": { "cache_creation_input_audio_token_cost": 3e-07, + "cache_read_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 6e-08, "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, @@ -5715,6 +5718,7 @@ }, "azure/gpt-realtime-mini-2025-10-06": { "cache_creation_input_audio_token_cost": 3e-07, + "cache_read_input_audio_token_cost": 3e-07, "cache_read_input_token_cost": 6e-08, "input_cost_per_audio_token": 1e-05, "input_cost_per_image_token": 8e-07, @@ -7409,6 +7413,80 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/gpt-chat-latest": { + "cache_read_input_token_cost": 5e-07, + "deprecation_date": "2026-12-02", + "input_cost_per_token": 5e-06, + "litellm_provider": "azure", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "reasoning_effort_levels": [ + "medium" + ], + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, + "azure/chat-latest": { + "cache_read_input_token_cost": 5e-07, + "deprecation_date": "2026-12-02", + "input_cost_per_token": 5e-06, + "litellm_provider": "azure", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3e-05, + "reasoning_effort_levels": [ + "medium" + ], + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "azure/us/gpt-5.6": { "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_272k_tokens": 1.375e-05, @@ -7675,6 +7753,43 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "azure/us/gpt-chat-latest": { + "cache_read_input_token_cost": 5.5e-07, + "deprecation_date": "2026-12-02", + "input_cost_per_token": 5.5e-06, + "litellm_provider": "azure", + "max_input_tokens": 272000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "mode": "chat", + "output_cost_per_token": 3.3e-05, + "reasoning_effort_levels": [ + "medium" + ], + "source": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/", + "supported_endpoints": [ + "/v1/chat/completions", + "/v1/responses" + ], + "supported_modalities": [ + "text", + "image" + ], + "supported_output_modalities": [ + "text" + ], + "supports_function_calling": true, + "supports_native_streaming": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true, + "supports_web_search": true + }, "azure/eu/gpt-5.6": { "cache_creation_input_token_cost": 6.875e-06, "cache_creation_input_token_cost_above_272k_tokens": 1.375e-05, @@ -8730,7 +8845,7 @@ "supports_function_calling": true }, "azure/o1": { - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 7.5e-06, "input_cost_per_token": 1.5e-05, "litellm_provider": "azure", @@ -8748,7 +8863,7 @@ }, "azure/o1-2024-12-17": { "cache_read_input_token_cost": 7.5e-06, - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.5e-05, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -8825,7 +8940,7 @@ "supports_vision": false }, "azure/o3": { - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 2e-06, "litellm_provider": "azure", @@ -8855,7 +8970,7 @@ "supports_vision": true }, "azure/o3-2025-04-16": { - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5e-07, "input_cost_per_token": 2e-06, "litellm_provider": "azure", @@ -8886,7 +9001,7 @@ }, "azure/o3-deep-research": { "cache_read_input_token_cost": 2.5e-06, - "deprecation_date": "2026-12-26", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1e-05, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -8923,7 +9038,7 @@ "supports_web_search": true }, "azure/o3-mini": { - "deprecation_date": "2026-10-01", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 1.1e-06, "litellm_provider": "azure", @@ -8940,7 +9055,7 @@ }, "azure/o3-mini-2025-01-31": { "cache_read_input_token_cost": 5.5e-07, - "deprecation_date": "2026-10-01", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.1e-06, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -8954,7 +9069,7 @@ "supports_vision": false }, "azure/o3-pro": { - "deprecation_date": "2026-12-17", + "deprecation_date": "2026-11-19", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "azure", @@ -8985,7 +9100,7 @@ "supports_vision": true }, "azure/o3-pro-2025-06-10": { - "deprecation_date": "2026-12-17", + "deprecation_date": "2026-11-19", "input_cost_per_token": 2e-05, "input_cost_per_token_batches": 1e-05, "litellm_provider": "azure", @@ -9016,7 +9131,7 @@ "supports_vision": true }, "azure/o4-mini": { - "deprecation_date": "2026-10-16", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 2.75e-07, "input_cost_per_token": 1.1e-06, "litellm_provider": "azure", @@ -9047,7 +9162,7 @@ }, "azure/o4-mini-2025-04-16": { "cache_read_input_token_cost": 2.75e-07, - "deprecation_date": "2026-10-16", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.1e-06, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -9600,7 +9715,7 @@ }, "azure/us/o1-2024-12-17": { "cache_read_input_token_cost": 8.25e-06, - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.65e-05, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -9645,7 +9760,7 @@ "supports_vision": false }, "azure/us/o3-2025-04-16": { - "deprecation_date": "2026-10-21", + "deprecation_date": "2026-11-19", "cache_read_input_token_cost": 5.5e-07, "input_cost_per_token": 2.2e-06, "litellm_provider": "azure", @@ -9676,7 +9791,7 @@ }, "azure/us/o3-mini-2025-01-31": { "cache_read_input_token_cost": 6.05e-07, - "deprecation_date": "2026-10-01", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.21e-06, "input_cost_per_token_batches": 6.05e-07, "litellm_provider": "azure", @@ -9693,7 +9808,7 @@ }, "azure/us/o4-mini-2025-04-16": { "cache_read_input_token_cost": 3.1e-07, - "deprecation_date": "2026-10-16", + "deprecation_date": "2026-11-19", "input_cost_per_token": 1.21e-06, "litellm_provider": "azure", "max_input_tokens": 200000, @@ -11101,12 +11216,15 @@ "babbage-002": { "deprecation_date": "2026-09-28", "input_cost_per_token": 4e-07, + "input_cost_per_token_batches": 2e-07, "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "completion", - "output_cost_per_token": 4e-07 + "output_cost_per_token": 4e-07, + "output_cost_per_token_batches": 2e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "bedrock/*/1-month-commitment/cohere.command-light-text-v14": { "input_cost_per_second": 0.001902, @@ -13171,7 +13289,9 @@ "supported_endpoints": [ "/v1/audio/transcriptions" ], - "deprecation_date": "2027-02-26" + "deprecation_date": "2027-02-26", + "input_cost_per_second": 0.0001, + "source": "https://developers.openai.com/api/docs/pricing" }, "claude-haiku-4-5-20251001": { "deprecation_date": "2026-10-15", @@ -13219,7 +13339,8 @@ "supports_response_schema": true, "supports_tool_choice": true, "supports_vision": true, - "prompt_cache_min_tokens": 4096 + "prompt_cache_min_tokens": 4096, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-3-7-sonnet-20250219": { "cache_creation_input_token_cost": 3.75e-06, @@ -13378,7 +13499,8 @@ "supports_native_structured_output": true, "supports_tool_choice": true, "supports_vision": true, - "prompt_cache_min_tokens": 1024 + "prompt_cache_min_tokens": 1024, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-sonnet-4-5-20250929": { "deprecation_date": "2026-09-29", @@ -13452,7 +13574,7 @@ }, "supports_output_config": true, "prompt_cache_min_tokens": 1024, - "source": "https://docs.anthropic.com/en/docs/about-claude/models/overview" + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-sonnet-4-6": { "deprecation_date": "2027-02-17", @@ -13488,7 +13610,8 @@ "prompt_cache_min_tokens": 1024, "provider_specific_entry": { "us": 1.1 - } + }, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-sonnet-4-5-20250929-v1:0": { "cache_creation_input_token_cost": 3.75e-06, @@ -13665,7 +13788,8 @@ "supports_tool_choice": true, "supports_vision": true, "supports_output_config": true, - "prompt_cache_min_tokens": 4096 + "prompt_cache_min_tokens": 4096, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-opus-4-6": { "deprecation_date": "2027-02-05", @@ -13702,7 +13826,8 @@ "supports_output_config": true, "supports_max_reasoning_effort": true, "supports_speed": true, - "prompt_cache_min_tokens": 4096 + "prompt_cache_min_tokens": 4096, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-opus-4-6-20260205": { "deprecation_date": "2027-02-05", @@ -13777,7 +13902,8 @@ }, "supports_output_config": true, "supports_speed": true, - "prompt_cache_min_tokens": 2048 + "prompt_cache_min_tokens": 2048, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-opus-4-7-20260416": { "deprecation_date": "2027-04-16", @@ -13855,7 +13981,7 @@ "supports_output_config": true, "prompt_cache_min_tokens": 512, "supports_native_structured_output": true, - "source": "https://docs.anthropic.com/en/docs/about-claude/models/overview" + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-fable-5-1": { "deprecation_date": "2027-09-01", @@ -13896,7 +14022,7 @@ "supports_output_config": true, "prompt_cache_min_tokens": 512, "supports_native_structured_output": true, - "source": "https://platform.claude.com/docs/en/models/fable-5-1/overview" + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-opus-5": { "deprecation_date": "2027-07-24", @@ -13937,7 +14063,7 @@ "supports_output_config": true, "supports_speed": true, "prompt_cache_min_tokens": 512, - "source": "https://docs.anthropic.com/en/docs/about-claude/models/overview" + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-opus-4-8": { "deprecation_date": "2027-05-28", @@ -13977,7 +14103,8 @@ }, "supports_output_config": true, "supports_speed": true, - "prompt_cache_min_tokens": 1024 + "prompt_cache_min_tokens": 1024, + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-sonnet-4-20250514": { "deprecation_date": "2026-06-15", @@ -14615,7 +14742,7 @@ }, "computer-use-preview": { "input_cost_per_token": 3e-06, - "litellm_provider": "azure", + "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 1024, "max_tokens": 1024, @@ -14633,12 +14760,14 @@ ], "supports_function_calling": true, "supports_parallel_function_calling": true, + "supports_pdf_input": true, "supports_prompt_caching": false, "supports_reasoning": true, - "supports_response_schema": true, + "supports_response_schema": false, "supports_system_messages": true, "supports_tool_choice": true, - "supports_vision": true + "supports_vision": true, + "source": "https://platform.openai.com/docs/models/computer-use-preview" }, "dall-e-2": { "deprecation_date": "2026-05-12", @@ -17597,6 +17726,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true }, "databricks/databricks-claude-fable-5": { @@ -17622,6 +17752,7 @@ "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": false, @@ -17651,6 +17782,7 @@ "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true, @@ -17676,6 +17808,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 4096 }, @@ -17699,6 +17832,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 1024 }, @@ -17722,6 +17856,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 1024 }, @@ -17745,6 +17880,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "supports_output_config": true, "prompt_cache_min_tokens": 4096 @@ -17770,6 +17906,7 @@ "supports_legacy_thinking": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 4096 }, @@ -17795,6 +17932,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true @@ -17822,6 +17960,7 @@ "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true @@ -17849,6 +17988,7 @@ "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true @@ -17875,6 +18015,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true }, "databricks/databricks-claude-sonnet-4-1": { @@ -17897,6 +18038,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true }, "databricks/databricks-claude-sonnet-4-5": { @@ -17919,6 +18061,7 @@ "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 1024 }, @@ -17943,6 +18086,7 @@ "supports_legacy_thinking": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_tool_choice": true, "prompt_cache_min_tokens": 1024 }, @@ -17969,6 +18113,7 @@ "supports_mid_conversation_system": true, "supports_prompt_caching": true, "supports_reasoning": true, + "supports_anthropic_thinking_payload": true, "supports_sampling_params": false, "supports_tool_choice": true, "supports_vision": true @@ -18047,6 +18192,7 @@ "output_dbu_cost_per_token": 3.5714e-05, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, + "supports_anthropic_thinking_payload": true, "supports_prompt_caching": true, "supports_tool_choice": true }, @@ -18067,6 +18213,7 @@ "output_dbu_cost_per_token": 0.000142857, "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", "supports_function_calling": true, + "supports_anthropic_thinking_payload": true, "supports_prompt_caching": true, "supports_tool_choice": true }, @@ -19226,12 +19373,15 @@ "davinci-002": { "deprecation_date": "2026-09-28", "input_cost_per_token": 2e-06, + "input_cost_per_token_batches": 1e-06, "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "completion", - "output_cost_per_token": 2e-06 + "output_cost_per_token": 2e-06, + "output_cost_per_token_batches": 1e-06, + "source": "https://developers.openai.com/api/docs/pricing" }, "deepgram/base": { "input_cost_per_second": 0.00020833, @@ -22278,15 +22428,18 @@ "supports_vision": false }, "fireworks_ai/accounts/fireworks/models/deepseek-v4-pro": { - "cache_read_input_token_cost": 1.45e-07, - "input_cost_per_token": 1.74e-06, + "cache_read_input_token_cost": 6e-07, + "cache_read_input_token_cost_priority": 6e-07, + "input_cost_per_token": 1.2e-06, + "input_cost_per_token_priority": 1.2e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 384000, "max_tokens": 384000, "mode": "chat", - "output_cost_per_token": 3.48e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token": 1.2e-06, + "output_cost_per_token_priority": 1.2e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22295,14 +22448,17 @@ }, "fireworks_ai/accounts/fireworks/models/deepseek-v4-pro-0813": { "cache_read_input_token_cost": 4.4e-08, + "cache_read_input_token_cost_priority": 5.5e-08, "input_cost_per_token": 1.32e-06, + "input_cost_per_token_priority": 1.65e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 3.96e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 4.95e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22397,14 +22553,17 @@ }, "fireworks_ai/accounts/fireworks/models/glm-5p2": { "cache_read_input_token_cost": 1.4e-07, + "cache_read_input_token_cost_priority": 1.75e-07, "input_cost_per_token": 1.4e-06, + "input_cost_per_token_priority": 1.75e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 5.5e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22413,14 +22572,17 @@ }, "fireworks_ai/accounts/fireworks/models/gpt-oss-120b": { "cache_read_input_token_cost": 1.5e-08, + "cache_read_input_token_cost_priority": 1.8e-08, "input_cost_per_token": 1.5e-07, + "input_cost_per_token_priority": 1.8e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 7.2e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22499,14 +22661,17 @@ }, "fireworks_ai/accounts/fireworks/models/kimi-k2p6": { "cache_read_input_token_cost": 1.6e-07, + "cache_read_input_token_cost_priority": 2.2e-07, "input_cost_per_token": 9.5e-07, + "input_cost_per_token_priority": 1.5e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 6e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22515,14 +22680,17 @@ }, "fireworks_ai/accounts/fireworks/models/kimi-k2p7-code": { "cache_read_input_token_cost": 1.9e-07, + "cache_read_input_token_cost_priority": 2.85e-07, "input_cost_per_token": 9.5e-07, + "input_cost_per_token_priority": 1.425e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 6e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22648,14 +22816,17 @@ }, "fireworks_ai/accounts/fireworks/models/minimax-m2p7": { "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_priority": 6e-07, "input_cost_per_token": 3e-07, + "input_cost_per_token_priority": 1.2e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 196608, "max_output_tokens": 196608, "max_tokens": 196608, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 1.2e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22664,14 +22835,17 @@ }, "fireworks_ai/accounts/fireworks/models/minimax-m3": { "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_priority": 9e-08, "input_cost_per_token": 3e-07, + "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 512000, "max_output_tokens": 512000, "max_tokens": 512000, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 1.8e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22747,15 +22921,18 @@ "supports_vision": false }, "fireworks_ai/deepseek-v4-pro": { - "cache_read_input_token_cost": 1.45e-07, - "input_cost_per_token": 1.74e-06, + "cache_read_input_token_cost": 6e-07, + "cache_read_input_token_cost_priority": 6e-07, + "input_cost_per_token": 1.2e-06, + "input_cost_per_token_priority": 1.2e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 384000, "max_tokens": 384000, "mode": "chat", - "output_cost_per_token": 3.48e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token": 1.2e-06, + "output_cost_per_token_priority": 1.2e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22811,14 +22988,17 @@ }, "fireworks_ai/glm-5p2": { "cache_read_input_token_cost": 1.4e-07, + "cache_read_input_token_cost_priority": 1.75e-07, "input_cost_per_token": 1.4e-06, + "input_cost_per_token_priority": 1.75e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 5.5e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22827,14 +23007,17 @@ }, "fireworks_ai/gpt-oss-120b": { "cache_read_input_token_cost": 1.5e-08, + "cache_read_input_token_cost_priority": 1.8e-08, "input_cost_per_token": 1.5e-07, + "input_cost_per_token_priority": 1.8e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 131072, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 7.2e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22873,14 +23056,17 @@ }, "fireworks_ai/kimi-k2p6": { "cache_read_input_token_cost": 1.6e-07, + "cache_read_input_token_cost_priority": 2.2e-07, "input_cost_per_token": 9.5e-07, + "input_cost_per_token_priority": 1.5e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 6e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22905,14 +23091,17 @@ }, "fireworks_ai/kimi-k2p7-code": { "cache_read_input_token_cost": 1.9e-07, + "cache_read_input_token_cost_priority": 2.85e-07, "input_cost_per_token": 9.5e-07, + "input_cost_per_token_priority": 1.425e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "max_output_tokens": 32768, "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 6e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22951,14 +23140,17 @@ }, "fireworks_ai/minimax-m2p7": { "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_priority": 6e-07, "input_cost_per_token": 3e-07, + "input_cost_per_token_priority": 1.2e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 196608, "max_output_tokens": 196608, "max_tokens": 196608, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 1.2e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22967,14 +23159,17 @@ }, "fireworks_ai/minimax-m3": { "cache_read_input_token_cost": 6e-08, + "cache_read_input_token_cost_priority": 9e-08, "input_cost_per_token": 3e-07, + "input_cost_per_token_priority": 4.5e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 512000, "max_output_tokens": 512000, "max_tokens": 512000, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 1.8e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -22990,7 +23185,7 @@ "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 1.6e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -23033,112 +23228,234 @@ "output_cost_per_token": 0.0, "source": "https://fireworks.ai/pricing" }, - "friendliai/meta-llama-3.1-70b-instruct": { - "input_cost_per_token": 6e-07, - "litellm_provider": "friendliai", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 6e-07, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "friendliai/meta-llama-3.1-8b-instruct": { - "input_cost_per_token": 1e-07, - "litellm_provider": "friendliai", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_token": 1e-07, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, "friendliai/zai-org/GLM-5.3-Flash": { "litellm_provider": "friendliai", - "supports_reasoning": true, - "supports_function_calling": true, "max_input_tokens": 1048576, - "max_tokens": 1048576, "max_output_tokens": 1048576, + "max_tokens": 1048576, "input_cost_per_token": 1.5e-07, "output_cost_per_token": 5e-07, "cache_read_input_token_cost": 3e-08, "supports_prompt_caching": true, + "supports_reasoning": true, "reasoning_effort_levels": [ "low", "high", "max" ], + "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, "supports_native_structured_output": true, "supports_system_messages": true, "supports_tool_choice": true, - "mode": "chat", - "comment": "Native multimodal GLM model for efficient coding and long-horizon agent tasks", - "source": "https://api.friendli.ai/serverless/v1/models", "supports_vision": true, "supports_image_input": true, - "supports_video_input": true + "supports_video_input": true, + "mode": "chat", + "comment": "Native multimodal GLM model for efficient coding and long-horizon agent tasks", + "source": "https://api.friendli.ai/serverless/v1/models" }, "friendliai/zai-org/GLM-5.3": { "litellm_provider": "friendliai", - "supports_reasoning": true, - "supports_function_calling": true, "max_input_tokens": 1048576, - "max_tokens": 1048576, "max_output_tokens": 1048576, + "max_tokens": 1048576, "input_cost_per_token": 1.26e-06, "output_cost_per_token": 3.96e-06, "cache_read_input_token_cost": 2.34e-07, "supports_prompt_caching": true, + "supports_reasoning": true, "reasoning_effort_levels": [ "low", "high", "max" ], + "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, "supports_native_structured_output": true, "supports_system_messages": true, "supports_tool_choice": true, + "supports_vision": false, + "supports_image_input": false, + "supports_video_input": false, "mode": "chat", "comment": "Flagship GLM model for long-horizon coding, agents, and complex project delivery", - "source": "https://api.friendli.ai/serverless/v1/models", + "source": "https://api.friendli.ai/serverless/v1/models" + }, + "friendliai/google/gemma-4-31B-it": { + "litellm_provider": "friendliai", + "max_input_tokens": 262144, + "max_output_tokens": 262144, + "max_tokens": 262144, + "input_cost_per_token": 1.4e-07, + "output_cost_per_token": 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repository generation", + "source": "https://api.friendli.ai/serverless/v1/models" }, "ft:babbage-002": { "deprecation_date": "2026-10-23", "input_cost_per_token": 1.6e-06, - "input_cost_per_token_batches": 2e-07, + "input_cost_per_token_batches": 8e-07, "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "completion", "output_cost_per_token": 1.6e-06, - "output_cost_per_token_batches": 2e-07 + "output_cost_per_token_batches": 9e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "ft:davinci-002": { "deprecation_date": "2026-10-23", "input_cost_per_token": 1.2e-05, - "input_cost_per_token_batches": 1e-06, + "input_cost_per_token_batches": 6e-06, "litellm_provider": "text-completion-openai", "max_input_tokens": 16384, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "completion", "output_cost_per_token": 1.2e-05, - "output_cost_per_token_batches": 1e-06 + "output_cost_per_token_batches": 6e-06, + "source": "https://developers.openai.com/api/docs/pricing" }, "ft:gpt-3.5-turbo": { "deprecation_date": "2026-10-23", @@ -23151,6 +23468,7 @@ "mode": "chat", "output_cost_per_token": 6e-06, "output_cost_per_token_batches": 3e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_system_messages": true, "supports_tool_choice": true }, @@ -23207,14 +23525,15 @@ "ft:gpt-4o-2024-08-06": { "cache_read_input_token_cost": 1.875e-06, "input_cost_per_token": 3.75e-06, - "input_cost_per_token_batches": 1.875e-06, + "input_cost_per_token_batches": 2.225e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 16384, "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.5e-05, - "output_cost_per_token_batches": 7.5e-06, + "output_cost_per_token_batches": 1.25e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -23252,6 +23571,7 @@ "mode": "chat", "output_cost_per_token": 1.2e-06, "output_cost_per_token_batches": 6e-07, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -23271,6 +23591,7 @@ "mode": "chat", "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -23289,6 +23610,7 @@ "mode": "chat", "output_cost_per_token": 3.2e-06, "output_cost_per_token_batches": 1.6e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -23308,6 +23630,7 @@ "mode": "chat", "output_cost_per_token": 8e-07, "output_cost_per_token_batches": 4e-07, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -23327,6 +23650,7 @@ "mode": "chat", "output_cost_per_token": 1.6e-05, "output_cost_per_token_batches": 8e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_prompt_caching": true, @@ -23337,15 +23661,18 @@ "gemini-2.0-flash": { "cache_read_input_token_cost": 2.5e-08, "deprecation_date": "2026-06-01", - "input_cost_per_audio_token": 7e-07, - "input_cost_per_token": 1e-07, + "input_cost_per_audio_token": 1e-06, + "input_cost_per_character": 3.75e-08, + "input_cost_per_token": 1.5e-07, + "input_cost_per_token_batches": 7.5e-08, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 8192, "max_tokens": 8192, "mode": "chat", - "output_cost_per_token": 4e-07, - "source": "https://ai.google.dev/pricing#2_0flash", + "output_cost_per_token": 6e-07, + "output_cost_per_token_batches": 3e-07, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_modalities": [ "text", "image", @@ -23414,13 +23741,16 @@ "cache_read_input_token_cost": 1.875e-08, "deprecation_date": "2026-06-01", "input_cost_per_audio_token": 7.5e-08, + "input_cost_per_character": 1.875e-08, "input_cost_per_token": 7.5e-08, + "input_cost_per_token_batches": 3.75e-08, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 8192, "mode": "chat", "output_cost_per_token": 3e-07, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-2.0-flash", + "output_cost_per_token_batches": 1.5e-07, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_modalities": [ "text", "image", @@ -23481,8 +23811,11 @@ } }, "gemini-2.5-flash": { + "cache_read_input_audio_token_cost": 1e-07, "deprecation_date": "2026-10-20", "cache_read_input_token_cost": 3e-08, + "cache_read_input_token_cost_flex": 3e-08, + "cache_read_input_token_cost_priority": 5.4e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 3e-07, "litellm_provider": "vertex_ai-language-models", @@ -23492,7 +23825,7 @@ "mode": "chat", "output_cost_per_reasoning_token": 2.5e-06, "output_cost_per_token": 2.5e-06, - "source": "https://ai.google.dev/gemini-api/docs/models#gemini-2.5-flash-preview", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23525,6 +23858,12 @@ "search_context_size_high": 0.035 }, "google_maps_grounding_cost_per_query": 0.025, + "input_cost_per_token_batches": 1.5e-07, + "input_cost_per_token_flex": 1.5e-07, + "input_cost_per_token_priority": 5.4e-07, + "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 }, "gemini-2.5-flash-image": { @@ -23532,6 +23871,9 @@ "cache_read_input_token_cost": 3e-08, "input_cost_per_audio_token": 1e-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": 32768, "max_output_tokens": 32768, @@ -23541,8 +23883,10 @@ "output_cost_per_image_token": 3e-05, "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, "rpm": 100000, - "source": "https://ai.google.dev/gemini-api/docs/pricing#gemini-2.5-flash-image", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23573,10 +23917,19 @@ "supports_image_size": false }, "gemini-3-pro-image": { + "cache_read_input_token_cost": 2e-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_flex": 1e-07, + "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, + "input_cost_per_token_above_200k_tokens": 4e-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, + "input_cost_per_token_priority": 3.6e-06, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 32768, @@ -23585,8 +23938,12 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "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, "output_cost_per_token_batches": 6e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing#gemini-3-pro-image", + "output_cost_per_token_flex": 6e-06, + "output_cost_per_token_priority": 2.16e-05, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23654,9 +24011,13 @@ "web_search_billing_unit": "per_query" }, "gemini-3.1-flash-image": { + "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_flex": 2.5e-08, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.00056, "input_cost_per_token": 5e-07, + "input_cost_per_token_batches": 2.5e-07, + "input_cost_per_token_flex": 2.5e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 32768, @@ -23665,7 +24026,9 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_token": 3e-06, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "output_cost_per_token_batches": 1.5e-06, + "output_cost_per_token_flex": 1.5e-06, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23732,9 +24095,11 @@ }, "gemini-3.1-flash-lite-image": { "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_flex": 1.25e-08, "input_cost_per_image": 0.00028, "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, + "input_cost_per_token_flex": 1.25e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 4096, @@ -23744,6 +24109,7 @@ "output_cost_per_image_token": 3e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, + "output_cost_per_token_flex": 7.5e-07, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -23818,6 +24184,7 @@ "google_maps_grounding_cost_per_query": 0.014 }, "gemini-3.1-flash-lite": { + "cache_read_input_audio_token_cost": 5e-08, "deprecation_date": "2027-05-07", "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_flex": 1.25e-08, @@ -23837,7 +24204,7 @@ "output_cost_per_token_batches": 7.5e-07, "output_cost_per_token_flex": 7.5e-07, "output_cost_per_token_priority": 2.7e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing#gemini-3.1-flash-lite", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23879,7 +24246,7 @@ "deprecation_date": "2027-07-21", "cache_read_input_token_cost": 3e-08, "cache_read_input_token_cost_flex": 1.5e-08, - "cache_read_input_token_cost_priority": 5e-08, + "cache_read_input_token_cost_priority": 5.4e-08, "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -23894,7 +24261,7 @@ "output_cost_per_token_batches": 1.25e-06, "output_cost_per_token_flex": 1.25e-06, "output_cost_per_token_priority": 4.5e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23933,6 +24300,7 @@ "google_maps_grounding_cost_per_query": 0.014 }, "deep-research-pro-preview-12-2025": { + "cache_read_input_token_cost": 2e-07, "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -23945,7 +24313,7 @@ "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -23967,8 +24335,11 @@ "supports_web_search": true }, "gemini-2.5-flash-lite": { + "cache_read_input_audio_token_cost": 3e-08, "deprecation_date": "2026-10-20", "cache_read_input_token_cost": 1e-08, + "cache_read_input_token_cost_flex": 1e-08, + "cache_read_input_token_cost_priority": 1.8e-08, "input_cost_per_audio_token": 3e-07, "input_cost_per_token": 1e-07, "litellm_provider": "vertex_ai-language-models", @@ -23978,7 +24349,7 @@ "mode": "chat", "output_cost_per_reasoning_token": 4e-07, "output_cost_per_token": 4e-07, - "source": "https://ai.google.dev/gemini-api/docs/models#gemini-2.5-flash-preview", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24011,6 +24382,12 @@ "search_context_size_high": 0.035 }, "google_maps_grounding_cost_per_query": 0.025, + "input_cost_per_token_batches": 5e-08, + "input_cost_per_token_flex": 5e-08, + "input_cost_per_token_priority": 1.8e-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 }, "gemini-2.5-flash-lite-preview-09-2025": { @@ -24162,7 +24539,7 @@ "mode": "realtime", "output_cost_per_audio_token": 1.2e-05, "output_cost_per_token": 2e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/vertex_ai/live" ], @@ -24193,7 +24570,8 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "gemini_native_audio": true + "gemini_native_audio": true, + "input_cost_per_image_token": 3e-06 }, "gemini/gemini-live-2.5-flash-preview-native-audio-09-2025": { "cache_read_input_token_cost": 7.5e-08, @@ -24293,6 +24671,9 @@ "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, + "cache_read_input_token_cost_above_200k_tokens_priority": 4.5e-07, + "cache_read_input_token_cost_flex": 1.25e-07, + "cache_read_input_token_cost_priority": 2.25e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_above_200k_tokens": 2.5e-06, "litellm_provider": "vertex_ai-language-models", @@ -24302,7 +24683,7 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_above_200k_tokens": 1.5e-05, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions" @@ -24332,7 +24713,15 @@ "search_context_size_medium": 0.035, "search_context_size_high": 0.035 }, - "google_maps_grounding_cost_per_query": 0.025 + "google_maps_grounding_cost_per_query": 0.025, + "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_priority": 2.7e-05, + "output_cost_per_token_batches": 5e-06, + "output_cost_per_token_flex": 5e-06, + "output_cost_per_token_priority": 1.8e-05 }, "gemini-3-pro-preview": { "deprecation_date": "2026-03-26", @@ -24407,7 +24796,7 @@ "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_image": 0.00012, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24441,13 +24830,16 @@ "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "cache_read_input_token_cost_priority": 3.6e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, + "cache_read_input_token_cost_flex": 2e-07, "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 6e-06 }, "gemini-3.1-pro-preview-customtools": { "prompt_cache_min_tokens": 4096, @@ -24558,7 +24950,9 @@ "web_search_billing_unit": "per_query" }, "vertex_ai/gemini-3-flash-preview": { + "cache_read_input_audio_token_cost": 1e-07, "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_flex": 5e-08, "input_cost_per_token": 5e-07, "input_cost_per_audio_token": 1e-06, "litellm_provider": "vertex_ai", @@ -24567,7 +24961,7 @@ "max_tokens": 65535, "mode": "chat", "output_cost_per_token": 3e-06, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24604,7 +24998,11 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "input_cost_per_token_batches": 2.5e-07, + "input_cost_per_token_flex": 2.5e-07, + "output_cost_per_token_batches": 1.5e-06, + "output_cost_per_token_flex": 1.5e-06 }, "vertex_ai/gemini-3.5-flash": { "prompt_cache_min_tokens": 4096, @@ -24620,7 +25018,7 @@ "output_cost_per_reasoning_token": 9e-06, "output_cost_per_token": 9e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24683,7 +25081,7 @@ "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24740,7 +25138,7 @@ "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24797,7 +25195,7 @@ "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24854,7 +25252,7 @@ "output_cost_per_token_above_200k_tokens": 1.8e-05, "output_cost_per_token_batches": 6e-06, "output_cost_per_image": 0.00012, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -24888,13 +25286,16 @@ "output_cost_per_token_above_200k_tokens_priority": 3.24e-05, "cache_read_input_token_cost_priority": 3.6e-07, "cache_read_input_token_cost_above_200k_tokens_priority": 7.2e-07, + "cache_read_input_token_cost_flex": 2e-07, "search_context_cost_per_query": { "search_context_size_low": 0.014, "search_context_size_medium": 0.014, "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "input_cost_per_token_flex": 1e-06, + "output_cost_per_token_flex": 6e-06 }, "vertex_ai/gemini-3.1-pro-preview-customtools": { "prompt_cache_min_tokens": 4096, @@ -24959,13 +25360,15 @@ "cache_read_input_token_cost": 1.25e-07, "input_cost_per_audio_token": 7e-07, "input_cost_per_token": 1e-06, + "input_cost_per_token_batches": 5e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 1048576, "max_output_tokens": 65535, "max_tokens": 65535, "mode": "chat", + "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2e-05, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_modalities": [ "text" ], @@ -25172,7 +25575,7 @@ "mode": "chat", "output_cost_per_token": 1e-05, "output_cost_per_token_above_200k_tokens": 1.5e-05, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_modalities": [ "text", "image" @@ -25198,10 +25601,14 @@ "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models" }, "gemini-embedding-2-preview": { - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "vertex_ai-embedding-models", "max_input_tokens": 8192, "max_tokens": 8192, @@ -25212,25 +25619,33 @@ "uses_embed_content": true }, "gemini-embedding-2": { - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "vertex_ai-embedding-models", "max_input_tokens": 8192, "max_tokens": 8192, "mode": "embedding", "output_cost_per_token": 0, "output_vector_size": 3072, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supports_multimodal": true, "uses_embed_content": true }, "vertex_ai/gemini-embedding-2-preview": { - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "vertex_ai", "max_input_tokens": 8192, "max_tokens": 8192, @@ -25242,17 +25657,21 @@ "uses_embed_content": true }, "vertex_ai/gemini-embedding-2": { - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "vertex_ai", "max_input_tokens": 8192, "max_tokens": 8192, "mode": "embedding", "output_cost_per_token": 0, "output_vector_size": 3072, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supports_multimodal": true, "uses_embed_content": true }, @@ -25284,10 +25703,14 @@ }, "gemini/gemini-embedding-2-preview": { "deprecation_date": "2026-08-10", - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "gemini", "max_input_tokens": 8192, "max_tokens": 8192, @@ -25300,10 +25723,14 @@ "tpm": 10000000 }, "gemini/gemini-embedding-2": { - "input_cost_per_audio_per_second": 0.00016, - "input_cost_per_image": 0.00012, + "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, + "input_cost_per_image_token_batches": 2.25e-07, "input_cost_per_token": 2e-07, - "input_cost_per_video_per_second": 0.00079, + "input_cost_per_token_batches": 1e-07, + "input_cost_per_video_token": 1.2e-05, + "input_cost_per_video_token_batches": 6e-06, "litellm_provider": "gemini", "max_input_tokens": 8192, "max_tokens": 8192, @@ -26886,7 +27313,9 @@ "google_maps_grounding_cost_per_query": 0.014 }, "gemini-3-flash-preview": { + "cache_read_input_audio_token_cost": 1e-07, "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_flex": 5e-08, "input_cost_per_audio_token": 1e-06, "input_cost_per_token": 5e-07, "litellm_provider": "vertex_ai-language-models", @@ -26896,7 +27325,7 @@ "mode": "chat", "output_cost_per_reasoning_token": 3e-06, "output_cost_per_token": 3e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -26934,7 +27363,11 @@ "search_context_size_high": 0.014 }, "web_search_billing_unit": "per_query", - "google_maps_grounding_cost_per_query": 0.014 + "google_maps_grounding_cost_per_query": 0.014, + "input_cost_per_token_batches": 2.5e-07, + "input_cost_per_token_flex": 2.5e-07, + "output_cost_per_token_batches": 1.5e-06, + "output_cost_per_token_flex": 1.5e-06 }, "gemini-omni-flash-preview": { "input_cost_per_audio_token": 1.5e-06, @@ -26947,7 +27380,7 @@ "output_cost_per_reasoning_token": 9e-06, "output_cost_per_token": 9e-06, "output_cost_per_video_token": 1.75e-05, - "source": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/gemini/omni-flash-preview", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions" ], @@ -26980,7 +27413,7 @@ "mode": "chat", "output_cost_per_reasoning_token": 9e-06, "output_cost_per_token": 9e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -27043,7 +27476,7 @@ "output_cost_per_token": 3.75e-06, "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -27100,7 +27533,7 @@ "output_cost_per_token": 3.75e-06, "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -27157,7 +27590,7 @@ "output_cost_per_token": 3.75e-06, "output_cost_per_token_batches": 1.875e-06, "output_cost_per_token_flex": 1.875e-06, - "source": "https://ai.google.dev/gemini-api/docs/pricing", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -28615,6 +29048,7 @@ "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_prompt_caching": true, "supports_system_messages": true, @@ -28623,12 +29057,15 @@ "gpt-3.5-turbo-0125": { "deprecation_date": "2026-10-23", "input_cost_per_token": 5e-07, + "input_cost_per_token_batches": 2.5e-07, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 1.5e-06, + "output_cost_per_token_batches": 7.5e-07, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -28638,12 +29075,15 @@ "gpt-3.5-turbo-1106": { "deprecation_date": "2026-09-28", "input_cost_per_token": 1e-06, + "input_cost_per_token_batches": 1e-06, "litellm_provider": "openai", "max_input_tokens": 16385, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 2e-06, + "output_cost_per_token_batches": 2e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -28671,7 +29111,8 @@ "max_output_tokens": 4096, "max_tokens": 4096, "mode": "completion", - "output_cost_per_token": 2e-06 + "output_cost_per_token": 2e-06, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-3.5-turbo-instruct-0914": { "input_cost_per_token": 1.5e-06, @@ -28726,12 +29167,15 @@ "gpt-4-0613": { "deprecation_date": "2026-10-23", "input_cost_per_token": 3e-05, + "input_cost_per_token_batches": 1.5e-05, "litellm_provider": "openai", "max_input_tokens": 8192, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 6e-05, + "output_cost_per_token_batches": 3e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_prompt_caching": true, "supports_system_messages": true, @@ -28772,12 +29216,15 @@ "gpt-4-turbo-2024-04-09": { "deprecation_date": "2026-10-23", "input_cost_per_token": 1e-05, + "input_cost_per_token_batches": 5e-06, "litellm_provider": "openai", "max_input_tokens": 128000, "max_output_tokens": 4096, "max_tokens": 4096, "mode": "chat", "output_cost_per_token": 3e-05, + "output_cost_per_token_batches": 1.5e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -28821,6 +29268,7 @@ "search_context_size_low": 0.025, "search_context_size_medium": 0.025 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -28863,6 +29311,7 @@ "search_context_size_low": 0.025, "search_context_size_medium": 0.025 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -28905,6 +29354,7 @@ "search_context_size_low": 0.025, "search_context_size_medium": 0.025 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -28947,6 +29397,7 @@ "search_context_size_low": 0.025, "search_context_size_medium": 0.025 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -28985,6 +29436,7 @@ "output_cost_per_token": 4e-07, "output_cost_per_token_batches": 2e-07, "output_cost_per_token_priority": 8e-07, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -29022,6 +29474,7 @@ "output_cost_per_token": 4e-07, "output_cost_per_token_priority": 8e-07, "output_cost_per_token_batches": 2e-07, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -29058,6 +29511,7 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_batches": 5e-06, "output_cost_per_token_priority": 1.7e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29080,6 +29534,7 @@ "output_cost_per_token": 1.5e-05, "output_cost_per_token_batches": 7.5e-06, "output_cost_per_token_priority": 2.625e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29102,6 +29557,7 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_priority": 1.7e-05, "output_cost_per_token_batches": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29125,6 +29581,7 @@ "output_cost_per_token": 1e-05, "output_cost_per_token_priority": 1.7e-05, "output_cost_per_token_batches": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29199,6 +29656,7 @@ "mode": "chat", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses", @@ -29235,6 +29693,7 @@ "mode": "chat", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions" ], @@ -29269,6 +29728,7 @@ "mode": "chat", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses", @@ -29306,6 +29766,7 @@ "mode": "chat", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses", @@ -29343,6 +29804,7 @@ "mode": "chat", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses", @@ -29404,7 +29866,8 @@ "supports_system_messages": true, "supports_tool_choice": true, "supports_vision": false, - "deprecation_date": "2027-01-20" + "deprecation_date": "2027-01-20", + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini": { "cache_read_input_token_cost": 7.5e-08, @@ -29432,7 +29895,8 @@ "search_context_size_high": 0.025, "search_context_size_low": 0.025, "search_context_size_medium": 0.025 - } + }, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini-2024-07-18": { "cache_read_input_token_cost": 7.5e-08, @@ -29453,6 +29917,7 @@ "search_context_size_low": 0.025, "search_context_size_medium": 0.025 }, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -29601,15 +30066,18 @@ "supported_endpoints": [ "/v1/audio/transcriptions" ], - "deprecation_date": "2027-02-26" + "deprecation_date": "2027-02-26", + "input_cost_per_second": 5e-05, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-4o-mini-tts": { - "input_cost_per_token": 2.5e-06, + "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", "output_cost_per_audio_token": 1.2e-05, "output_cost_per_second": 0.00025, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/speech" ], @@ -29741,7 +30209,9 @@ "supported_endpoints": [ "/v1/audio/transcriptions" ], - "deprecation_date": "2027-02-26" + "deprecation_date": "2027-02-26", + "input_cost_per_second": 0.0001, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-image-1.5": { "cache_read_input_token_cost": 1.25e-06, @@ -29751,7 +30221,10 @@ "mode": "image_generation", "output_cost_per_token": 1e-05, "input_cost_per_image_token": 8e-06, + "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3.2e-05, + "output_cost_per_token_batches": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations" ], @@ -29766,7 +30239,10 @@ "mode": "image_generation", "output_cost_per_token": 1e-05, "input_cost_per_image_token": 8e-06, + "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3.2e-05, + "output_cost_per_token_batches": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations" ], @@ -29779,7 +30255,9 @@ "litellm_provider": "openai", "mode": "image_generation", "input_cost_per_image_token": 8e-06, + "input_cost_per_token_batches": 2.5e-06, "output_cost_per_image_token": 3e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -30226,6 +30704,7 @@ "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "input_cost_per_token": 1.25e-06, + "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", @@ -30234,6 +30713,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, "search_context_cost_per_query": { @@ -30241,6 +30721,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -30270,6 +30751,7 @@ }, "gpt-5.1": { "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, @@ -30310,11 +30792,17 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "input_cost_per_token_batches": 6.25e-07, + "input_cost_per_token_flex": 6.25e-07, + "output_cost_per_token_batches": 5e-06, + "output_cost_per_token_flex": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": false, "supports_minimal_reasoning_effort": false }, "gpt-5.1-2025-11-13": { "cache_read_input_token_cost": 1.25e-07, + "cache_read_input_token_cost_flex": 6.25e-08, "cache_read_input_token_cost_priority": 2.5e-07, "input_cost_per_token": 1.25e-06, "input_cost_per_token_priority": 2.5e-06, @@ -30355,6 +30843,11 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "input_cost_per_token_batches": 6.25e-07, + "input_cost_per_token_flex": 6.25e-07, + "output_cost_per_token_batches": 5e-06, + "output_cost_per_token_flex": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": false, "supports_minimal_reasoning_effort": false }, @@ -30406,6 +30899,7 @@ }, "gpt-5.2": { "cache_read_input_token_cost": 1.75e-07, + "cache_read_input_token_cost_flex": 8.75e-08, "cache_read_input_token_cost_priority": 3.5e-07, "input_cost_per_token": 1.75e-06, "input_cost_per_token_priority": 3.5e-06, @@ -30447,11 +30941,17 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "input_cost_per_token_batches": 8.75e-07, + "input_cost_per_token_flex": 8.75e-07, + "output_cost_per_token_batches": 7e-06, + "output_cost_per_token_flex": 7e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, "gpt-5.2-2025-12-11": { "cache_read_input_token_cost": 1.75e-07, + "cache_read_input_token_cost_flex": 8.75e-08, "cache_read_input_token_cost_priority": 3.5e-07, "input_cost_per_token": 1.75e-06, "input_cost_per_token_priority": 3.5e-06, @@ -30493,6 +30993,11 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "input_cost_per_token_batches": 8.75e-07, + "input_cost_per_token_flex": 8.75e-07, + "output_cost_per_token_batches": 7e-06, + "output_cost_per_token_flex": 7e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, @@ -30586,17 +31091,20 @@ }, "gpt-5.2-pro": { "input_cost_per_token": 2.1e-05, + "input_cost_per_token_batches": 1.05e-05, "litellm_provider": "openai", "max_input_tokens": 272000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", "output_cost_per_token": 0.000168, + "output_cost_per_token_batches": 8.4e-05, "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": [ "/v1/batch", "/v1/responses" @@ -30625,17 +31133,20 @@ }, "gpt-5.2-pro-2025-12-11": { "input_cost_per_token": 2.1e-05, + "input_cost_per_token_batches": 1.05e-05, "litellm_provider": "openai", "max_input_tokens": 272000, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "responses", "output_cost_per_token": 0.000168, + "output_cost_per_token_batches": 8.4e-05, "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": [ "/v1/batch", "/v1/responses" @@ -30701,6 +31212,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -30837,6 +31349,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -30905,6 +31418,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -30972,6 +31486,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -31035,7 +31550,7 @@ "supports_tool_choice": true, "supports_vision": true, "supports_web_search": true, - "source": "https://developers.openai.com/api/docs/models/gpt-5.6-cyber", + "source": "https://developers.openai.com/api/docs/pricing", "supports_computer_use": true, "supports_parallel_function_calling": true }, @@ -31205,7 +31720,7 @@ "reasoning_effort_levels": [ "medium" ], - "source": "https://developers.openai.com/api/docs/models/chat-latest", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/responses" @@ -31284,7 +31799,8 @@ "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 5e-06, "output_cost_per_token_above_272k_tokens_flex": 2.25e-05, - "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07 + "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.5-2026-04-23": { "cache_read_input_token_cost": 5e-07, @@ -31341,7 +31857,8 @@ "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 5e-06, "output_cost_per_token_above_272k_tokens_flex": 2.25e-05, - "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07 + "cache_read_input_token_cost_above_272k_tokens_flex": 5e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.5-pro": { "input_cost_per_token": 3e-05, @@ -31364,6 +31881,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -31412,6 +31930,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -31489,7 +32008,8 @@ "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 2.5e-06, "output_cost_per_token_above_272k_tokens_flex": 1.125e-05, - "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07 + "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.4-2026-03-05": { "cache_read_input_token_cost": 2.5e-07, @@ -31541,7 +32061,8 @@ "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 2.5e-06, "output_cost_per_token_above_272k_tokens_flex": 1.125e-05, - "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07 + "cache_read_input_token_cost_above_272k_tokens_flex": 2.5e-07, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.4-pro": { "input_cost_per_token": 3e-05, @@ -31590,7 +32111,8 @@ "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 3e-05, - "output_cost_per_token_above_272k_tokens_flex": 0.000135 + "output_cost_per_token_above_272k_tokens_flex": 0.000135, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.4-pro-2026-03-05": { "input_cost_per_token": 3e-05, @@ -31639,7 +32161,8 @@ "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false, "input_cost_per_token_above_272k_tokens_flex": 3e-05, - "output_cost_per_token_above_272k_tokens_flex": 0.000135 + "output_cost_per_token_above_272k_tokens_flex": 0.000135, + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-5.4-mini": { "cache_read_input_token_cost": 7.5e-08, @@ -31690,6 +32213,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, @@ -31742,6 +32266,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, @@ -31791,6 +32316,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, @@ -31840,6 +32366,7 @@ "supports_web_search": true, "supports_none_reasoning_effort": true, "default_reasoning_effort": "none", + "source": "https://developers.openai.com/api/docs/pricing", "supports_xhigh_reasoning_effort": true, "supports_minimal_reasoning_effort": false }, @@ -31858,6 +32385,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/batch", "/v1/responses" @@ -31900,6 +32428,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/batch", "/v1/responses" @@ -31932,6 +32461,7 @@ "cache_read_input_token_cost_priority": 2.5e-07, "deprecation_date": "2026-12-11", "input_cost_per_token": 1.25e-06, + "input_cost_per_token_batches": 6.25e-07, "input_cost_per_token_flex": 6.25e-07, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", @@ -31940,6 +32470,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 1e-05, + "output_cost_per_token_batches": 5e-06, "output_cost_per_token_flex": 5e-06, "output_cost_per_token_priority": 2e-05, "search_context_cost_per_query": { @@ -31947,6 +32478,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -32271,6 +32803,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses" ], @@ -32301,6 +32834,7 @@ "cache_read_input_token_cost_flex": 1.25e-08, "cache_read_input_token_cost_priority": 4.5e-08, "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, "litellm_provider": "openai", @@ -32309,6 +32843,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 2e-06, + "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, "search_context_cost_per_query": { @@ -32316,6 +32851,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -32349,6 +32885,7 @@ "cache_read_input_token_cost_priority": 4.5e-08, "deprecation_date": "2026-12-11", "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, "litellm_provider": "openai", @@ -32357,6 +32894,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 2e-06, + "output_cost_per_token_batches": 1e-06, "output_cost_per_token_flex": 1e-06, "output_cost_per_token_priority": 3.6e-06, "search_context_cost_per_query": { @@ -32364,6 +32902,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/batch", @@ -32395,6 +32934,7 @@ "cache_read_input_token_cost": 5e-09, "cache_read_input_token_cost_flex": 2.5e-09, "input_cost_per_token": 5e-08, + "input_cost_per_token_batches": 2.5e-08, "input_cost_per_token_flex": 2.5e-08, "input_cost_per_token_priority": 2.5e-06, "litellm_provider": "openai", @@ -32403,12 +32943,14 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 4e-07, + "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, "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": [ "/v1/chat/completions", "/v1/batch", @@ -32441,6 +32983,7 @@ "cache_read_input_token_cost_flex": 2.5e-09, "deprecation_date": "2026-12-11", "input_cost_per_token": 5e-08, + "input_cost_per_token_batches": 2.5e-08, "input_cost_per_token_priority": 2.5e-06, "input_cost_per_token_flex": 2.5e-08, "litellm_provider": "openai", @@ -32449,12 +32992,14 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 4e-07, + "output_cost_per_token_batches": 2e-07, "output_cost_per_token_flex": 2e-07, "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": [ "/v1/chat/completions", "/v1/batch", @@ -32487,9 +33032,11 @@ "deprecation_date": "2026-10-23", "input_cost_per_image_token": 1e-05, "input_cost_per_token": 5e-06, + "input_cost_per_token_batches": 2.5e-06, "litellm_provider": "openai", "mode": "image_generation", "output_cost_per_image_token": 4e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -32500,9 +33047,11 @@ "deprecation_date": "2026-12-01", "input_cost_per_image_token": 2.5e-06, "input_cost_per_token": 2e-06, + "input_cost_per_token_batches": 1e-06, "litellm_provider": "openai", "mode": "image_generation", "output_cost_per_image_token": 8e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -32510,6 +33059,7 @@ }, "gpt-realtime": { "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": "2027-01-20", "input_cost_per_audio_token": 3.2e-05, @@ -32522,6 +33072,7 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32543,6 +33094,7 @@ }, "gpt-realtime-1.5": { "cache_creation_input_audio_token_cost": 4e-07, + "cache_read_input_audio_token_cost": 4e-07, "cache_read_input_token_cost": 4e-07, "input_cost_per_audio_token": 3.2e-05, "input_cost_per_image_token": 5e-06, @@ -32554,6 +33106,7 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32587,6 +33140,7 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 2.4e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32622,6 +33176,7 @@ "output_cost_per_token": 2.4e-05, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32657,6 +33212,7 @@ "output_cost_per_token": 2.4e-06, "regional_processing_uplift_multiplier_eu": 1.1, "regional_processing_uplift_multiplier_us": 1.1, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32679,8 +33235,10 @@ "gpt-realtime-mini": { "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": "2027-01-20", "input_cost_per_audio_token": 1e-05, + "input_cost_per_image_token": 8e-07, "input_cost_per_token": 6e-07, "litellm_provider": "openai", "max_input_tokens": 32000, @@ -32689,6 +33247,7 @@ "mode": "realtime", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -32710,6 +33269,7 @@ }, "gpt-realtime-2025-08-28": { "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": "2027-01-20", "input_cost_per_audio_token": 3.2e-05, @@ -32722,6 +33282,7 @@ "mode": "realtime", "output_cost_per_audio_token": 6.4e-05, "output_cost_per_token": 1.6e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -34717,6 +35278,22 @@ "supports_web_search": true, "supports_xhigh_reasoning_effort": true }, + "meta/muse-voice-transcribe-1.0": { + "input_cost_per_second": 0.00005, + "litellm_provider": "meta", + "mode": "audio_transcription", + "source": "https://dev.meta.ai/docs/speech-to-text", + "supported_endpoints": [ + "/v1/realtime" + ], + "supported_modalities": [ + "audio" + ], + "supported_output_modalities": [ + "text" + ], + "supports_audio_input": true + }, "meta_llama/Llama-3.3-70B-Instruct": { "litellm_provider": "meta_llama", "max_input_tokens": 128000, @@ -37425,12 +38002,15 @@ "cache_read_input_token_cost": 7.5e-06, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.5e-05, + "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", "max_input_tokens": 200000, "max_output_tokens": 100000, "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 6e-05, + "output_cost_per_token_batches": 3e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_pdf_input": true, @@ -37445,12 +38025,15 @@ "cache_read_input_token_cost": 7.5e-06, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.5e-05, + "input_cost_per_token_batches": 7.5e-06, "litellm_provider": "openai", "max_input_tokens": 200000, "max_output_tokens": 100000, "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 6e-05, + "output_cost_per_token_batches": 3e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -37472,6 +38055,7 @@ "mode": "responses", "output_cost_per_token": 0.0006, "output_cost_per_token_batches": 0.0003, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -37505,6 +38089,7 @@ "mode": "responses", "output_cost_per_token": 0.0006, "output_cost_per_token_batches": 0.0003, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -37532,6 +38117,7 @@ "cache_read_input_token_cost_flex": 2.5e-07, "cache_read_input_token_cost_priority": 8.75e-07, "input_cost_per_token": 2e-06, + "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, "input_cost_per_token_priority": 3.5e-06, "litellm_provider": "openai", @@ -37540,6 +38126,7 @@ "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06, + "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, "search_context_cost_per_query": { @@ -37547,6 +38134,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/chat/completions", @@ -37576,6 +38164,7 @@ "cache_read_input_token_cost_priority": 8.75e-07, "deprecation_date": "2026-12-11", "input_cost_per_token": 2e-06, + "input_cost_per_token_batches": 1e-06, "input_cost_per_token_flex": 1e-06, "input_cost_per_token_priority": 3.5e-06, "litellm_provider": "openai", @@ -37584,6 +38173,7 @@ "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 8e-06, + "output_cost_per_token_batches": 4e-06, "output_cost_per_token_flex": 4e-06, "output_cost_per_token_priority": 1.4e-05, "search_context_cost_per_query": { @@ -37591,6 +38181,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/chat/completions", @@ -37700,12 +38291,15 @@ "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.1e-06, + "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "openai", "max_input_tokens": 200000, "max_output_tokens": 100000, "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "output_cost_per_token_batches": 2.2e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_prompt_caching": true, @@ -37718,12 +38312,15 @@ "cache_read_input_token_cost": 5.5e-07, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.1e-06, + "input_cost_per_token_batches": 5.5e-07, "litellm_provider": "openai", "max_input_tokens": 200000, "max_output_tokens": 100000, "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "output_cost_per_token_batches": 2.2e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_prompt_caching": true, @@ -37747,6 +38344,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -37784,6 +38382,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/responses", "/v1/batch" @@ -37807,10 +38406,11 @@ }, "o4-mini": { "cache_read_input_token_cost": 2.75e-07, - "cache_read_input_token_cost_flex": 1.375e-07, + "cache_read_input_token_cost_flex": 1.38e-07, "cache_read_input_token_cost_priority": 5e-07, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.1e-06, + "input_cost_per_token_batches": 5.5e-07, "input_cost_per_token_flex": 5.5e-07, "input_cost_per_token_priority": 2e-06, "litellm_provider": "openai", @@ -37819,6 +38419,7 @@ "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "output_cost_per_token_batches": 2.2e-06, "output_cost_per_token_flex": 2.2e-06, "output_cost_per_token_priority": 8e-06, "search_context_cost_per_query": { @@ -37826,6 +38427,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_pdf_input": true, @@ -37838,10 +38440,11 @@ }, "o4-mini-2025-04-16": { "cache_read_input_token_cost": 2.75e-07, - "cache_read_input_token_cost_flex": 1.375e-07, + "cache_read_input_token_cost_flex": 1.38e-07, "cache_read_input_token_cost_priority": 5e-07, "deprecation_date": "2026-10-23", "input_cost_per_token": 1.1e-06, + "input_cost_per_token_batches": 5.5e-07, "input_cost_per_token_flex": 5.5e-07, "input_cost_per_token_priority": 2e-06, "litellm_provider": "openai", @@ -37850,6 +38453,7 @@ "max_tokens": 100000, "mode": "chat", "output_cost_per_token": 4.4e-06, + "output_cost_per_token_batches": 2.2e-06, "output_cost_per_token_flex": 2.2e-06, "output_cost_per_token_priority": 8e-06, "search_context_cost_per_query": { @@ -37857,6 +38461,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": false, "supports_pdf_input": true, @@ -39019,7 +39624,9 @@ "supports_max_reasoning_effort": true, "supports_tool_choice": true, "supports_vision": true, - "prompt_cache_min_tokens": 4096 + "prompt_cache_min_tokens": 4096, + "supports_response_schema": true, + "source": "https://openrouter.ai/api/v1/models" }, "openrouter/anthropic/claude-sonnet-4.5": { "input_cost_per_image": 0.0048, @@ -39167,18 +39774,20 @@ }, "openrouter/deepseek/deepseek-v3.2": { "input_cost_per_token": 2.69e-07, - "input_cost_per_token_cache_hit": 2.8e-08, + "input_cost_per_token_cache_hit": 1.345e-07, "litellm_provider": "openrouter", "max_input_tokens": 163840, - "max_output_tokens": 163840, - "max_tokens": 163840, + "max_output_tokens": 65536, + "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 4e-07, "supports_assistant_prefill": true, "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, - "supports_tool_choice": true + "supports_tool_choice": true, + "supports_response_schema": true, + "source": "https://openrouter.ai/api/v1/models" }, "openrouter/deepseek/deepseek-v3.2-exp": { "input_cost_per_token": 2.7e-07, @@ -43015,7 +43624,8 @@ "mode": "embedding", "output_cost_per_token": 0.0, "output_cost_per_token_batches": 0.0, - "output_vector_size": 3072 + "output_vector_size": 3072, + "source": "https://developers.openai.com/api/docs/pricing" }, "text-embedding-3-small": { "input_cost_per_token": 2e-08, @@ -43026,7 +43636,8 @@ "mode": "embedding", "output_cost_per_token": 0.0, "output_cost_per_token_batches": 0.0, - "output_vector_size": 1536 + "output_vector_size": 1536, + "source": "https://developers.openai.com/api/docs/pricing" }, "text-embedding-ada-002": { "input_cost_per_token": 1e-07, @@ -43035,7 +43646,8 @@ "max_tokens": 8191, "mode": "embedding", "output_cost_per_token": 0.0, - "output_vector_size": 1536 + "output_vector_size": 1536, + "source": "https://developers.openai.com/api/docs/pricing" }, "text-embedding-ada-002-v2": { "input_cost_per_token": 1e-07, @@ -43206,7 +43818,7 @@ "input_cost_per_token": 1.2e-06, "output_cost_per_token": 1.2e-06, "max_input_tokens": 131072, - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/Qwen/Qwen2.5-7B-Instruct-Turbo": { "litellm_provider": "together_ai", @@ -43218,7 +43830,7 @@ "input_cost_per_token": 3e-07, "output_cost_per_token": 3e-07, "max_input_tokens": 32768, - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/Qwen/Qwen3-235B-A22B-Instruct-2507-tput": { "deprecation_date": "2026-07-10", @@ -43265,7 +43877,7 @@ "max_input_tokens": 256000, "mode": "chat", "output_cost_per_token": 2e-06, - "source": "https://www.together.ai/models/qwen3-coder-480b-a35b-instruct", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43327,7 +43939,7 @@ }, "mode": "chat", "output_cost_per_token": 1.7e-06, - "source": "https://www.together.ai/models/deepseek-v3-1", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, @@ -43351,7 +43963,7 @@ "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 1.04e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43385,6 +43997,7 @@ "litellm_provider": "together_ai", "mode": "chat", "output_cost_per_token": 5.9e-07, + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43407,6 +44020,7 @@ "litellm_provider": "together_ai", "mode": "chat", "output_cost_per_token": 8.8e-07, + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43418,6 +44032,7 @@ "litellm_provider": "together_ai", "mode": "chat", "output_cost_per_token": 1.8e-07, + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43434,7 +44049,7 @@ "input_cost_per_token": 2e-07, "output_cost_per_token": 2e-07, "max_input_tokens": 32768, - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/mistralai/Mistral-Small-24B-Instruct-2501": { "deprecation_date": "2026-04-02", @@ -43446,7 +44061,7 @@ "input_cost_per_token": 1e-07, "output_cost_per_token": 3e-07, "max_input_tokens": 32768, - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/mistralai/Mixtral-8x7B-Instruct-v0.1": { "deprecation_date": "2026-04-16", @@ -43454,6 +44069,7 @@ "litellm_provider": "together_ai", "mode": "chat", "output_cost_per_token": 6e-07, + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43480,7 +44096,7 @@ "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 6e-07, - "source": "https://www.together.ai/models/gpt-oss-120b", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, @@ -43488,12 +44104,13 @@ "supports_tool_choice": true }, "together_ai/openai/gpt-oss-20b": { + "deprecation_date": "2026-09-14", "input_cost_per_token": 5e-08, "litellm_provider": "together_ai", "max_input_tokens": 131072, "mode": "chat", "output_cost_per_token": 2e-07, - "source": "https://www.together.ai/models/gpt-oss-20b", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43513,7 +44130,7 @@ "max_input_tokens": 128000, "mode": "chat", "output_cost_per_token": 1.1e-06, - "source": "https://www.together.ai/models/glm-4-5-air", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43529,7 +44146,7 @@ }, "mode": "chat", "output_cost_per_token": 2.2e-06, - "source": "https://www.together.ai/models/glm-4-6", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, @@ -43546,7 +44163,7 @@ }, "mode": "chat", "output_cost_per_token": 2e-06, - "source": "https://www.together.ai/models/glm-4-7", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, @@ -43594,7 +44211,7 @@ }, "mode": "chat", "output_cost_per_token": 1.5e-06, - "source": "https://www.together.ai/models/qwen3-next-80b-a3b-instruct", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43610,7 +44227,7 @@ }, "mode": "chat", "output_cost_per_token": 1.5e-06, - "source": "https://www.together.ai/models/qwen3-next-80b-a3b-thinking", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43624,7 +44241,7 @@ "max_input_tokens": 262144, "mode": "chat", "output_cost_per_token": 3.6e-06, - "source": "https://www.together.ai/models/qwen3-5-397b-a17b", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43639,7 +44256,7 @@ "max_tokens": 524288, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43664,7 +44281,7 @@ "max_tokens": 262144, "mode": "chat", "output_cost_per_token": 2.5e-07, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_reasoning": true, @@ -43679,7 +44296,7 @@ "max_tokens": 1000000, "mode": "chat", "output_cost_per_token": 3e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_reasoning": true }, "together_ai/Qwen/Qwen3.7-Max": { @@ -43690,7 +44307,7 @@ "max_tokens": 1000000, "mode": "chat", "output_cost_per_token": 7.5e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_prompt_caching": true }, "together_ai/Qwen/Qwen3.7-Plus": { @@ -43700,7 +44317,7 @@ "max_tokens": 1000000, "mode": "chat", "output_cost_per_token": 1.28e-06, - "source": "https://docs.together.ai/docs/serverless-models" + "source": "https://api.together.ai/v1/models" }, "together_ai/Qwen/Qwen3.8-2.4T-A95B": { "cache_read_input_token_cost": 2.5e-07, @@ -43710,7 +44327,7 @@ "max_tokens": 1010000, "mode": "chat", "output_cost_per_token": 6e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_prompt_caching": true }, "together_ai/arize-ai/qwen-2-1.5b-instruct": { @@ -43720,7 +44337,7 @@ "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 1e-07, - "source": "https://docs.together.ai/docs/serverless-models" + "source": "https://api.together.ai/v1/models" }, "together_ai/deepseek-ai/DeepSeek-V4-Flash-0731": { "cache_read_input_token_cost": 3e-08, @@ -43730,7 +44347,7 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 2.8e-07, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43762,7 +44379,7 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 3.96e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43780,13 +44397,14 @@ "source": "https://docs.together.ai/docs/serverless-models" }, "together_ai/google/gemma-4-31B-it": { + "deprecation_date": "2026-09-14", "input_cost_per_token": 3.9e-07, "litellm_provider": "together_ai", "max_input_tokens": 262144, "max_tokens": 262144, "mode": "chat", "output_cost_per_token": 9.7e-07, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_response_schema": true, @@ -43794,6 +44412,7 @@ "supports_vision": true }, "together_ai/intfloat/multilingual-e5-large-instruct": { + "deprecation_date": "2026-09-14", "input_cost_per_token": 2e-08, "litellm_provider": "together_ai", "max_input_tokens": 514, @@ -43821,7 +44440,7 @@ "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 1.5e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_prompt_caching": true }, "together_ai/moonshotai/Kimi-K2.7-Code": { @@ -43833,7 +44452,7 @@ "max_tokens": 262144, "mode": "chat", "output_cost_per_token": 4e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43854,7 +44473,7 @@ "high", "max" ], - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43872,7 +44491,7 @@ "max_tokens": 512288, "mode": "chat", "output_cost_per_token": 3.6e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43898,7 +44517,7 @@ "max_tokens": 524288, "mode": "chat", "output_cost_per_token": 4.05e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43906,6 +44525,7 @@ "supports_tool_choice": true }, "together_ai/thinkingmachines/Inkling-Small": { + "deprecation_date": "2026-09-14", "cache_read_input_token_cost": 1e-07, "input_cost_per_token": 5e-07, "litellm_provider": "together_ai", @@ -43913,7 +44533,7 @@ "max_tokens": 524288, "mode": "chat", "output_cost_per_token": 1.2e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_prompt_caching": true }, "together_ai/zai-org/GLM-5.2": { @@ -43925,7 +44545,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43942,7 +44562,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43959,7 +44579,7 @@ "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 5e-07, - "source": "https://docs.together.ai/docs/serverless-models", + "source": "https://api.together.ai/v1/models", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_prompt_caching": true, @@ -43972,6 +44592,7 @@ "input_cost_per_character": 1.5e-05, "litellm_provider": "openai", "mode": "audio_speech", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/speech" ] @@ -43980,6 +44601,7 @@ "input_cost_per_character": 3e-05, "litellm_provider": "openai", "mode": "audio_speech", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/speech" ] @@ -47322,6 +47944,9 @@ "cache_read_input_token_cost": 3e-08, "input_cost_per_audio_token": 1e-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": 32768, "max_output_tokens": 32768, @@ -47331,8 +47956,10 @@ "output_cost_per_image_token": 3e-05, "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, "rpm": 100000, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/image-generation#edit-an-image", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -47364,10 +47991,19 @@ "supports_image_size": false }, "vertex_ai/gemini-3-pro-image": { + "cache_read_input_token_cost": 2e-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_flex": 1e-07, + "cache_read_input_token_cost_priority": 3.6e-07, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, + "input_cost_per_token_above_200k_tokens": 4e-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, + "input_cost_per_token_priority": 3.6e-06, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 32768, @@ -47376,9 +48012,13 @@ "output_cost_per_image": 0.134, "output_cost_per_image_token": 0.00012, "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, "output_cost_per_token_batches": 6e-06, + "output_cost_per_token_flex": 6e-06, + "output_cost_per_token_priority": 2.16e-05, "supports_reasoning": false, - "source": "https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-pro-image" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/gemini-3-pro-image-preview": { "input_cost_per_image": 0.0011, @@ -47397,9 +48037,13 @@ "source": "https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-pro-image" }, "vertex_ai/gemini-3.1-flash-image": { + "cache_read_input_token_cost": 5e-08, + "cache_read_input_token_cost_flex": 2.5e-08, "deprecation_date": "2027-05-28", "input_cost_per_image": 0.00056, "input_cost_per_token": 5e-07, + "input_cost_per_token_batches": 2.5e-07, + "input_cost_per_token_flex": 2.5e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 32768, @@ -47408,8 +48052,10 @@ "output_cost_per_image": 0.0672, "output_cost_per_image_token": 6e-05, "output_cost_per_token": 3e-06, + "output_cost_per_token_batches": 1.5e-06, + "output_cost_per_token_flex": 1.5e-06, "supports_reasoning": false, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/gemini-3.1-flash-image-preview": { "input_cost_per_image": 0.00056, @@ -47427,9 +48073,11 @@ }, "vertex_ai/gemini-3.1-flash-lite-image": { "cache_read_input_token_cost": 2.5e-08, + "cache_read_input_token_cost_flex": 1.25e-08, "input_cost_per_image": 0.00028, "input_cost_per_token": 2.5e-07, "input_cost_per_token_batches": 1.25e-07, + "input_cost_per_token_flex": 1.25e-07, "litellm_provider": "vertex_ai-language-models", "max_input_tokens": 65536, "max_output_tokens": 4096, @@ -47439,6 +48087,7 @@ "output_cost_per_image_token": 3e-05, "output_cost_per_token": 1.5e-06, "output_cost_per_token_batches": 7.5e-07, + "output_cost_per_token_flex": 7.5e-07, "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", @@ -47513,6 +48162,7 @@ "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/gemini-3.1-flash-lite": { + "cache_read_input_audio_token_cost": 5e-08, "deprecation_date": "2027-05-07", "cache_read_input_token_cost": 2.5e-08, "cache_read_input_token_cost_flex": 1.25e-08, @@ -47533,7 +48183,7 @@ "output_cost_per_token_flex": 7.5e-07, "output_cost_per_token_priority": 2.7e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -47575,7 +48225,7 @@ "deprecation_date": "2027-07-21", "cache_read_input_token_cost": 3e-08, "cache_read_input_token_cost_flex": 1.5e-08, - "cache_read_input_token_cost_priority": 5e-08, + "cache_read_input_token_cost_priority": 5.4e-08, "input_cost_per_token": 3e-07, "input_cost_per_token_batches": 1.5e-07, "input_cost_per_token_flex": 1.5e-07, @@ -47591,7 +48241,7 @@ "output_cost_per_token_flex": 1.25e-06, "output_cost_per_token_priority": 4.5e-06, "regional_endpoint_uplift_multiplier": 1.1, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#gemini-models", + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing", "supported_endpoints": [ "/v1/chat/completions", "/v1/completions", @@ -47630,6 +48280,7 @@ "google_maps_grounding_cost_per_query": 0.014 }, "vertex_ai/deep-research-pro-preview-12-2025": { + "cache_read_input_token_cost": 2e-07, "input_cost_per_image": 0.0011, "input_cost_per_token": 2e-06, "input_cost_per_token_batches": 1e-06, @@ -47642,7 +48293,7 @@ "output_cost_per_image_token": 0.00012, "output_cost_per_token": 1.2e-05, "output_cost_per_token_batches": 6e-06, - "source": "https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/3-pro-image" + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" }, "vertex_ai/imagegeneration@006": { "litellm_provider": "vertex_ai-image-models", @@ -49305,7 +49956,8 @@ "supported_endpoints": [ "/v1/audio/transcriptions" ], - "deprecation_date": "2027-02-26" + "deprecation_date": "2027-02-26", + "source": "https://developers.openai.com/api/docs/pricing" }, "xai/grok-3": { "cache_read_input_token_cost": 2e-07, @@ -52402,10 +53054,11 @@ "max_tokens": 40960, "max_input_tokens": 40960, "max_output_tokens": 40960, - "input_cost_per_token": 0.0, + "input_cost_per_token": 2e-07, "output_cost_per_token": 0.0, "litellm_provider": "fireworks_ai", - "mode": "rerank" + "mode": "rerank", + "source": "https://api.fireworks.ai/v1/serverless/models" }, "fireworks_ai/accounts/fireworks/models/qwen3-vl-235b-a22b-instruct": { "max_tokens": 262144, @@ -52470,7 +53123,7 @@ "max_tokens": 65536, "mode": "chat", "output_cost_per_token": 1.6e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -54369,12 +55022,13 @@ }, "gpt-4o-mini-tts-2025-03-20": { "deprecation_date": "2026-07-23", - "input_cost_per_token": 2.5e-06, + "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", "output_cost_per_audio_token": 1.2e-05, "output_cost_per_second": 0.00025, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/speech" ], @@ -54387,12 +55041,13 @@ ] }, "gpt-4o-mini-tts-2025-12-15": { - "input_cost_per_token": 2.5e-06, + "input_cost_per_token": 6e-07, "litellm_provider": "openai", "mode": "audio_speech", "output_cost_per_audio_token": 1.2e-05, "output_cost_per_second": 0.00025, "output_cost_per_token": 1e-05, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/speech" ], @@ -54407,24 +55062,28 @@ "gpt-4o-mini-transcribe-2025-03-20": { "deprecation_date": "2027-01-20", "input_cost_per_audio_token": 1.25e-06, + "input_cost_per_second": 5e-05, "input_cost_per_token": 1.25e-06, "litellm_provider": "openai", "max_input_tokens": 16000, "max_output_tokens": 2000, "mode": "audio_transcription", "output_cost_per_token": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/transcriptions" ] }, "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, "litellm_provider": "openai", "max_input_tokens": 16000, "max_output_tokens": 2000, "mode": "audio_transcription", "output_cost_per_token": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/transcriptions" ] @@ -54443,6 +55102,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -54470,6 +55130,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, + "source": "https://developers.openai.com/api/docs/pricing", "supports_function_calling": true, "supports_parallel_function_calling": true, "supports_pdf_input": true, @@ -54497,6 +55158,7 @@ "mode": "realtime", "output_cost_per_audio_token": 2e-05, "output_cost_per_token": 2.4e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime" ], @@ -54548,13 +55210,14 @@ "supports_parallel_function_calling": true, "supports_system_messages": true, "supports_tool_choice": true, - "deprecation_date": "2027-01-20" + "deprecation_date": "2027-01-20", + "source": "https://developers.openai.com/api/docs/pricing" }, "gpt-realtime-whisper": { - "input_cost_per_second": 0.0002833333333333333, + "input_cost_per_second": 0.000283333333333, "litellm_provider": "openai", "mode": "audio_transcription", - "source": "https://developers.openai.com/api/docs/models/gpt-realtime-whisper", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime", "/v1/realtime/transcription_sessions" @@ -54572,7 +55235,7 @@ "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.1, - "source": "https://platform.openai.com/docs/api-reference/videos", + "source": "https://developers.openai.com/api/docs/pricing", "supported_modalities": [ "text", "image" @@ -54586,7 +55249,7 @@ "litellm_provider": "openai", "mode": "video_generation", "output_cost_per_video_per_second": 0.3, - "source": "https://platform.openai.com/docs/api-reference/videos", + "source": "https://developers.openai.com/api/docs/pricing", "supported_modalities": [ "text", "image" @@ -54611,11 +55274,15 @@ "chatgpt-image-latest": { "cache_read_input_token_cost": 1.25e-06, "deprecation_date": "2026-12-01", - "input_cost_per_image_token": 1e-05, + "input_cost_per_image_token": 8e-06, "input_cost_per_token": 5e-06, + "input_cost_per_token_batches": 2.5e-06, "litellm_provider": "openai", "mode": "image_generation", - "output_cost_per_image_token": 4e-05, + "output_cost_per_image_token": 3.2e-05, + "output_cost_per_token": 1e-05, + "output_cost_per_token_batches": 5e-06, + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/images/generations", "/v1/images/edits" @@ -57090,7 +57757,7 @@ "input_cost_per_second": 7.5e-05, "litellm_provider": "openai", "mode": "audio_transcription", - "source": "https://developers.openai.com/api/docs/models/gpt-transcribe", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/audio/transcriptions", "/v1/realtime/transcription_sessions" @@ -57105,10 +57772,10 @@ "supports_audio_input": true }, "gpt-live-transcribe": { - "input_cost_per_second": 0.0002833333333333333, + "input_cost_per_second": 0.000283333333333, "litellm_provider": "openai", "mode": "audio_transcription", - "source": "https://developers.openai.com/api/docs/models/gpt-live-transcribe", + "source": "https://developers.openai.com/api/docs/pricing", "supported_endpoints": [ "/v1/realtime", "/v1/realtime/transcription_sessions" @@ -57123,10 +57790,10 @@ "supports_audio_input": true }, "gpt-live-1": { - "input_cost_per_second": 0.0008333333333333334, + "input_cost_per_second": 0.000833333333333, "litellm_provider": "openai", "mode": "realtime", - "source": "https://developers.openai.com/api/docs/models/gpt-live-1", + "source": "https://developers.openai.com/api/docs/pricing", "supported_modalities": [ "text", "audio" @@ -57140,13 +57807,13 @@ "supports_function_calling": true }, "gpt-realtime-translate": { - "input_cost_per_second": 0.0005666666666666667, + "input_cost_per_second": 0.000566666666667, "litellm_provider": "openai", "max_input_tokens": 16000, "max_output_tokens": 2000, "max_tokens": 2000, "mode": "realtime", - "source": "https://developers.openai.com/api/docs/models/gpt-realtime-translate", + "source": "https://developers.openai.com/api/docs/pricing", "supported_modalities": [ "audio" ], @@ -57174,7 +57841,7 @@ "search_context_size_low": 0.01, "search_context_size_medium": 0.01 }, - "source": "https://platform.claude.com/docs/en/about-claude/models/overview", + "source": "https://platform.claude.com/docs/en/about-claude/pricing", "supports_adaptive_thinking": true, "thinking_always_on": true, "supports_mid_conversation_system": true, @@ -57235,7 +57902,7 @@ "supports_output_config": true, "prompt_cache_min_tokens": 512, "supports_native_structured_output": true, - "source": "https://platform.claude.com/docs/en/models/mythos-5-1/overview" + "source": "https://platform.claude.com/docs/en/about-claude/pricing" }, "claude-mythos-preview": { "cache_creation_input_token_cost": 1.25e-05, @@ -57433,8 +58100,9 @@ }, { "name": "claude-adaptive-thinking", - "pattern": "claude-[a-z]+-(?:4[-._](?:[6-9]|[1-9]\\d)(?!\\d)|(?:[5-9]|[1-9]\\d)(?!\\d)(?:[-._]\\d{1,2}(?!\\d))?)", - "description": "Claude at version 4.6 or higher, in any id shape that contains claude--: minors 4.6 through 4.99, any later major-minor, and bare 5+ majors so a new family shaped like claude-fable-5 matches. Requiring the claude- prefix keeps non-Claude names such as team-sonnet-5-1 out. The minor is capped at two digits so an 8-digit date suffix such as claude-opus-4-20250514 is never read as a >= 4.6 minor. Turns on adaptive thinking for new versions and new families with no code change.", + "pattern": "claude-[a-z]+-(?:4[-._](?:[6-9]|[1-9]\\d)(?!\\d)|[5-9](?!\\d)(?:[-._]\\d{1,2}(?!\\d))?)", + "fill_missing_for_providers": ["anthropic", "azure_ai", "bedrock", "bedrock_converse", "vertex_ai-anthropic_models"], + "description": "Claude at version 4.6 or higher, in any id shape that contains claude--: minors 4.6 through 4.99, any later major-minor, and bare 5+ majors so a new family shaped like claude-fable-5 matches. Requiring the claude- prefix keeps non-Claude names such as team-sonnet-5-1 out. The minor is capped at two digits so an 8-digit date suffix such as claude-opus-4-20250514 is never read as a >= 4.6 minor. Two-digit majors are deliberately not matched so ids like claude-opus-41 (4.1) are not read as major 41. Turns on adaptive thinking for new versions and new families with no code change.", "model_info": { "supports_adaptive_thinking": true } @@ -57442,6 +58110,7 @@ { "name": "claude-legacy-thinking", "pattern": "claude-[a-z]+-4[-._]6(?!\\d)", + "fill_missing_for_providers": ["anthropic", "azure_ai", "bedrock", "bedrock_converse", "vertex_ai-anthropic_models"], "description": "Claude at version 4.6 exactly, in any id shape that contains claude--4-6 (dotted and underscored minors included, dated releases such as claude-sonnet-4-6-20260219 too). The 4.6 family is adaptive-thinking yet still accepts legacy thinking.type=enabled with budget_tokens, so the caller's hard budget cap is forwarded verbatim instead of being rewritten to an uncapped output_config.effort. The lookahead keeps two-digit minors such as 4-60 from matching. 4.7+ and 5+ majors reject the legacy shape and stay on the adaptive translation.", "model_info": { "supports_legacy_thinking": true @@ -57457,8 +58126,9 @@ }, { "name": "claude-mid-conversation-system", - "pattern": "claude-[a-z]+-(?:4[-._](?:[89]|[1-9]\\d)(?!\\d)|(?:[5-9]|[1-9]\\d)(?!\\d)(?:[-._]\\d{1,2}(?!\\d))?)", - "description": "Claude at version 4.8 or higher, in any id shape that contains claude--: minors 4.8 through 4.99, any later major-minor, and bare 5+ majors so a new family like claude-fable-5 matches. Anthropic introduced mid-conversation system messages with Opus 4.8 and every newer Claude keeps them; 4.7 and below reject the system role inside messages.", + "pattern": "claude-[a-z]+-(?:4[-._](?:[89]|[1-9]\\d)(?!\\d)|[5-9](?!\\d)(?:[-._]\\d{1,2}(?!\\d))?)", + "fill_missing_for_providers": ["anthropic", "azure_ai", "bedrock", "bedrock_converse", "vertex_ai-anthropic_models"], + "description": "Claude at version 4.8 or higher, in any id shape that contains claude--: minors 4.8 through 4.99, any later major-minor, and bare 5+ majors so a new family like claude-fable-5 matches. Two-digit majors are deliberately not matched so ids like claude-opus-41 (4.1) are not read as major 41. Anthropic introduced mid-conversation system messages with Opus 4.8 and every newer Claude keeps them; 4.7 and below reject the system role inside messages.", "model_info": { "supports_mid_conversation_system": true } @@ -57470,6 +58140,15 @@ "model_info": { "supports_reasoning": true } + }, + { + "name": "openai-reasoning-family-baseline", + "pattern": "^(?!.*search-api)(?:[a-z0-9_.-]+/)*(?:ft:)?(?:o[1-9]\\d*(?![a-z0-9])|gpt-[5-9](?:\\.\\d+)?(?![0-9.])|(?:gpt-\\d+(?:\\.\\d+)?(?:-[a-z0-9]+)*-)?(?:codex|deep-research|chat-latest)(?![a-z0-9]))", + "fill_missing_for_providers": ["azure", "azure_ai", "openai"], + "description": "OpenAI reasoning families by id shape, under any provider namespace and with an optional ft: prefix: the o-series (o1, o3-pro, o4-mini), gpt-5 through gpt-9 majors including dotted minors and suffixed variants (gpt-5.5-cyber, gpt-6-astra), and the codex, deep-research and chat-latest lines when standalone or on a gpt base. gpt-5-search-api is excluded because it is a search-only surface. Every model here is a reasoning model, and the Responses API drops the caller's reasoning param for any mapped OpenAI model whose info lacks supports_reasoning, so an id the registry has not named yet keeps its reasoning settings instead of silently losing them. Rules lose to exact entries. Carries no mode and no pricing, so cost stays on the standard unpriced behavior.", + "model_info": { + "supports_reasoning": true + } } ] }, @@ -57579,6 +58258,7 @@ }, "vertex_ai/gemini-3.5-live-translate-preview": { "input_cost_per_audio_token": 3.5e-06, + "input_cost_per_second": 8.83333333333e-05, "input_cost_per_token": 3.5e-06, "litellm_provider": "vertex_ai", "mode": "realtime", @@ -57681,14 +58361,17 @@ }, "fireworks_ai/accounts/fireworks/models/deepseek-v4-flash-0731": { "cache_read_input_token_cost": 7e-09, + "cache_read_input_token_cost_priority": 8.75e-09, "input_cost_per_token": 2.2e-07, + "input_cost_per_token_priority": 2.75e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 8.25e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57697,14 +58380,17 @@ }, "fireworks_ai/accounts/fireworks/models/deepseek-v4p1-flash": { "cache_read_input_token_cost": 7e-09, + "cache_read_input_token_cost_priority": 8.75e-09, "input_cost_per_token": 2.2e-07, + "input_cost_per_token_priority": 2.75e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 393216, "max_tokens": 393216, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://fireworks.ai/models/deepseek-ai/deepseek-v4p1-flash", + "output_cost_per_token_priority": 8.25e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, @@ -57720,26 +58406,29 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_tool_choice": true, "supports_vision": true }, "fireworks_ai/accounts/fireworks/models/kimi-k3": { "cache_read_input_token_cost": 3e-07, + "cache_read_input_token_cost_priority": 3.75e-07, "input_cost_per_token": 3e-06, + "input_cost_per_token_priority": 3.75e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 1.5e-05, + "output_cost_per_token_priority": 1.875e-05, "reasoning_effort_levels": [ "low", "high", "max" ], - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57748,14 +58437,17 @@ }, "fireworks_ai/deepseek-v4-flash-0731": { "cache_read_input_token_cost": 7e-09, + "cache_read_input_token_cost_priority": 8.75e-09, "input_cost_per_token": 2.2e-07, + "input_cost_per_token_priority": 2.75e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 8.25e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57764,14 +58456,17 @@ }, "fireworks_ai/deepseek-v4p1-flash": { "cache_read_input_token_cost": 7e-09, + "cache_read_input_token_cost_priority": 8.75e-09, "input_cost_per_token": 2.2e-07, + "input_cost_per_token_priority": 2.75e-07, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 393216, "max_tokens": 393216, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://fireworks.ai/models/deepseek-ai/deepseek-v4p1-flash", + "output_cost_per_token_priority": 8.25e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_prompt_caching": true, "supports_reasoning": true, @@ -57787,7 +58482,7 @@ "max_tokens": 1048576, "mode": "chat", "output_cost_per_token": 6.6e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_tool_choice": true, "supports_vision": true @@ -57826,19 +58521,22 @@ }, "fireworks_ai/kimi-k3": { "cache_read_input_token_cost": 3e-07, + "cache_read_input_token_cost_priority": 3.75e-07, "input_cost_per_token": 3e-06, + "input_cost_per_token_priority": 3.75e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 131072, "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 1.5e-05, + "output_cost_per_token_priority": 1.875e-05, "reasoning_effort_levels": [ "low", "high", "max" ], - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57889,12 +58587,15 @@ }, "fireworks_ai/qwen3p8-max": { "cache_read_input_token_cost": 2.5e-07, + "cache_read_input_token_cost_priority": 3.75e-07, "input_cost_per_token": 2e-06, + "input_cost_per_token_priority": 3e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "mode": "chat", "output_cost_per_token": 6e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 9e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57910,7 +58611,7 @@ "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.5e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57942,7 +58643,7 @@ "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 2.4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57958,7 +58659,7 @@ "max_tokens": 16384, "mode": "chat", "output_cost_per_token": 1.5e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57990,7 +58691,7 @@ "max_tokens": 32768, "mode": "chat", "output_cost_per_token": 2.4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -57999,12 +58700,15 @@ }, "fireworks_ai/accounts/fireworks/models/qwen3p8-max": { "cache_read_input_token_cost": 2.5e-07, + "cache_read_input_token_cost_priority": 3.75e-07, "input_cost_per_token": 2e-06, + "input_cost_per_token_priority": 3e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 262144, "mode": "chat", "output_cost_per_token": 6e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 9e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -58020,7 +58724,7 @@ "max_tokens": 131072, "mode": "chat", "output_cost_per_token": 6.6e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -58057,7 +58761,7 @@ "high", "max" ], - "source": "https://docs.fireworks.ai/serverless/pricing", + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -59098,9 +59802,9 @@ "litellm_provider": "wandb", "mode": "chat", "supports_reasoning": true, - "input_cost_per_token": 0.00000131, - "output_cost_per_token": 0.00000396, - "cache_read_input_token_cost": 0.000000044, + "input_cost_per_token": 1.31e-06, + "output_cost_per_token": 3.96e-06, + "cache_read_input_token_cost": 4.4e-08, "supports_prompt_caching": true, "source": "https://wandb.ai/site/pricing/tokens/" }, @@ -59108,9 +59812,9 @@ "litellm_provider": "wandb", "mode": "chat", "supports_reasoning": true, - "input_cost_per_token": 0.0000001, - "output_cost_per_token": 0.00000015, - "cache_read_input_token_cost": 0.00000005, + "input_cost_per_token": 1e-07, + "output_cost_per_token": 1.5e-07, + "cache_read_input_token_cost": 5e-08, "supports_prompt_caching": true, "source": "https://wandb.ai/site/pricing/tokens/" }, @@ -60755,14 +61459,17 @@ }, "fireworks_ai/accounts/fireworks/models/glm-5p3": { "cache_read_input_token_cost": 2.6e-07, + "cache_read_input_token_cost_priority": 3.25e-07, "input_cost_per_token": 1.4e-06, + "input_cost_per_token_priority": 1.75e-06, "litellm_provider": "fireworks_ai", "max_input_tokens": 1048576, "max_output_tokens": 128000, "max_tokens": 128000, "mode": "chat", "output_cost_per_token": 4.4e-06, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 5.5e-06, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_reasoning": true, "supports_response_schema": true, @@ -60771,13 +61478,16 @@ }, "fireworks_ai/accounts/fireworks/models/glm-5p3-flash": { "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_tokens": 1048576, "mode": "chat", "output_cost_per_token": 5e-07, - "source": "https://docs.fireworks.ai/serverless/pricing", + "output_cost_per_token_priority": 6.25e-07, + "source": "https://api.fireworks.ai/v1/serverless/models", "supports_function_calling": true, "supports_response_schema": true, "supports_tool_choice": true, @@ -60805,7 +61515,7 @@ "max_output_tokens": 40960, "max_tokens": 40960, "mode": "embedding", - "source": "https://docs.fireworks.ai/serverless/pricing" + "source": "https://api.fireworks.ai/v1/serverless/models" }, "zai/glm-5.2": { "cache_creation_input_token_cost": 0, @@ -60829,16 +61539,17 @@ "max_tokens": 1000000, "mode": "chat", "output_cost_per_token": 4.7e-07, - "source": "https://docs.together.ai/docs/serverless-models" + "source": "https://api.together.ai/v1/models" }, "together_ai/moonshotai/Kimi-K2.6": { + "deprecation_date": "2026-08-19", "input_cost_per_token": 1.2e-06, "output_cost_per_token": 4.5e-06, "cache_read_input_token_cost": 2e-07, "litellm_provider": "together_ai", "max_input_tokens": 262144, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/moonshotai/Kimi-K2.5-fp4": { "input_cost_per_token": 5e-07, @@ -60846,7 +61557,7 @@ "litellm_provider": "together_ai", "max_input_tokens": 262144, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/MiniMaxAI/MiniMax-M2.7": { "input_cost_per_token": 3e-07, @@ -60855,24 +61566,26 @@ "litellm_provider": "together_ai", "max_input_tokens": 196608, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/zai-org/GLM-5": { + "deprecation_date": "2026-06-22", "input_cost_per_token": 1e-06, "output_cost_per_token": 3.2e-06, "litellm_provider": "together_ai", "max_input_tokens": 202752, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/zai-org/GLM-5.1": { + "deprecation_date": "2026-07-10", "input_cost_per_token": 1.4e-06, "output_cost_per_token": 4.4e-06, "cache_read_input_token_cost": 2.6e-07, "litellm_provider": "together_ai", "max_input_tokens": 202752, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/deepseek-ai/DeepSeek-R1-0528": { "input_cost_per_token": 3e-06, @@ -60880,31 +61593,34 @@ "litellm_provider": "together_ai", "max_input_tokens": 163840, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/Qwen/Qwen3-Coder-Next-FP8": { + "deprecation_date": "2026-05-14", "input_cost_per_token": 5e-07, "output_cost_per_token": 1.2e-06, "litellm_provider": "together_ai", "max_input_tokens": 262144, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/Qwen/Qwen3-VL-32B-Instruct": { + "deprecation_date": "2026-02-25", "input_cost_per_token": 5e-07, "output_cost_per_token": 1.5e-06, "litellm_provider": "together_ai", "max_input_tokens": 262144, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/Qwen/Qwen3-VL-8B-Instruct": { + "deprecation_date": "2026-04-16", "input_cost_per_token": 1.8e-07, "output_cost_per_token": 6.8e-07, "litellm_provider": "together_ai", "max_input_tokens": 262144, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/mistralai/Ministral-3-14B-Instruct-2512": { "input_cost_per_token": 2e-07, @@ -60912,7 +61628,7 @@ "litellm_provider": "together_ai", "max_input_tokens": 262144, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/nvidia/NVIDIA-Nemotron-Nano-9B-v2": { "input_cost_per_token": 6e-08, @@ -60920,7 +61636,7 @@ "litellm_provider": "together_ai", "max_input_tokens": 131072, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/mistralai/Mistral-7B-Instruct-v0.3": { "input_cost_per_token": 2e-07, @@ -60928,15 +61644,16 @@ "litellm_provider": "together_ai", "max_input_tokens": 32768, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "together_ai/Qwen/QwQ-32B": { + "deprecation_date": "2025-11-13", "input_cost_per_token": 1.2e-06, "output_cost_per_token": 1.2e-06, "litellm_provider": "together_ai", "max_input_tokens": 131072, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "cerebras/gemma-4-31b": { "input_cost_per_token": 9.9e-07, @@ -65063,5 +65780,263 @@ "supports_tool_choice": false, "supports_response_schema": true, "supports_vision": false + }, + "fireworks_ai/accounts/fireworks/routers/glm-5p3-fast": { + "cache_read_input_token_cost": 3.9e-07, + "input_cost_per_token": 2.1e-06, + "litellm_provider": "fireworks_ai", + "mode": "chat", + "output_cost_per_token": 6.6e-06, + "source": "https://api.fireworks.ai/v1/serverless/models" + }, + "together_ai/arcee-ai/trinity-mini": { + "input_cost_per_token": 4.5e-08, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 1.5e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/deepseek-ai/deepseek-coder-33b-instruct": { + "input_cost_per_token": 8e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 8e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/deepseek-ai/DeepSeek-R1-Distill-Llama-70B": { + "input_cost_per_token": 2e-06, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 2e-06, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B": { + "input_cost_per_token": 1.8e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 1.8e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B": { + "input_cost_per_token": 1.6e-06, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 1.6e-06, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/deepseek-ai/DeepSeek-V4.1-Flash": { + "cache_read_input_token_cost": 6e-09, + "input_cost_per_token": 3e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://api.together.ai/v1/models" + }, + "vertex_ai/gemini-2.5-flash-native-audio": { + "input_cost_per_audio_token": 3e-06, + "input_cost_per_token": 5e-07, + "litellm_provider": "vertex_ai", + "mode": "realtime", + "output_cost_per_audio_token": 1.2e-05, + "output_cost_per_token": 2e-06, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + }, + "vertex_ai/gemini-2.5-flash-preview-tts": { + "input_cost_per_token": 5e-07, + "input_cost_per_token_batches": 2.5e-07, + "litellm_provider": "vertex_ai", + "mode": "audio_speech", + "output_cost_per_audio_token": 1e-05, + "output_cost_per_token": 1e-05, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + }, + "vertex_ai/gemini-3.1-flash-live-preview": { + "input_cost_per_audio_token": 3e-06, + "input_cost_per_second": 8.33333333333e-05, + "input_cost_per_token": 7.5e-07, + "litellm_provider": "vertex_ai", + "mode": "realtime", + "output_cost_per_audio_token": 1.2e-05, + "output_cost_per_token": 4.5e-06, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + }, + "vertex_ai/gemini-3.1-flash-tts-preview": { + "input_cost_per_token": 1e-06, + "input_cost_per_token_batches": 5e-07, + "litellm_provider": "vertex_ai", + "mode": "audio_speech", + "output_cost_per_audio_token": 2e-05, + "output_cost_per_token": 2e-05, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + }, + "vertex_ai/gemini-3.5-transcribe": { + "input_cost_per_audio_token": 2e-06, + "input_cost_per_second": 5e-05, + "litellm_provider": "vertex_ai", + "mode": "audio_transcription", + "output_cost_per_token": 1.2e-05, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + }, + "vertex_ai/gemini-3.5-transcribe-live": { + "input_cost_per_audio_token": 3.5e-06, + "input_cost_per_second": 8.33333333333e-05, + "litellm_provider": "vertex_ai", + "mode": "audio_transcription", + "output_cost_per_token": 2.1e-05, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + }, + "vertex_ai/gemini-omni-1.1-flash": { + "input_cost_per_token": 1.5e-06, + "litellm_provider": "vertex_ai", + "mode": "chat", + "output_cost_per_token": 9e-06, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + }, + "vertex_ai/gemini-robotics-er-2": { + "cache_read_input_token_cost": 1e-07, + "input_cost_per_token": 1e-06, + "input_cost_per_token_batches": 5e-07, + "litellm_provider": "vertex_ai", + "mode": "chat", + "output_cost_per_token": 5e-06, + "output_cost_per_token_batches": 2.5e-06, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + }, + "vertex_ai/gemma-4-26b-a4b-it": { + "cache_read_input_token_cost": 1.5e-08, + "input_cost_per_token": 1.5e-07, + "litellm_provider": "vertex_ai", + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://cloud.google.com/gemini-enterprise-agent-platform/generative-ai/pricing" + }, + "together_ai/google/gemma-2-27b-it": { + "input_cost_per_token": 8e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 8e-07, + "source": "https://api.together.ai/v1/models" + }, + "gpt-5.5-cyber": { + "cache_read_input_token_cost": 1.25e-06, + "input_cost_per_token": 1.25e-05, + "litellm_provider": "openai", + "mode": "chat", + "output_cost_per_token": 7.5e-05, + "source": "https://developers.openai.com/api/docs/pricing", + "supports_reasoning": true + }, + "gpt-rosalind-research": { + "cache_read_input_token_cost": 5e-07, + "input_cost_per_token": 5e-06, + "litellm_provider": "openai", + "mode": "chat", + "output_cost_per_token": 2.5e-05, + "source": "https://developers.openai.com/api/docs/pricing" + }, + "together_ai/meta-llama/Llama-3-8b-chat-hf": { + "input_cost_per_token": 2e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 2e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/meta-llama/Llama-3.1-405B-Instruct": { + "input_cost_per_token": 3.5e-06, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 3.5e-06, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/meta-llama/Llama-3.2-1B-Instruct": { + "input_cost_per_token": 6e-08, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 6e-08, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/meta-llama/Llama-3.2-3B-Instruct": { + "input_cost_per_token": 6e-08, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 6e-08, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/meta-llama/Meta-Llama-3-70B-Instruct-Turbo": { + "input_cost_per_token": 8.8e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 8.8e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/meta-llama/Meta-Llama-3-8B-Instruct": { + "input_cost_per_token": 2e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 2e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO": { + "input_cost_per_token": 6e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 6e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/nvidia/Llama-3.1-Nemotron-70B-Instruct-HF": { + "input_cost_per_token": 8.8e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 8.8e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2-1.5B-Instruct": { + "input_cost_per_token": 2e-08, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 2e-08, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2-72B-Instruct": { + "input_cost_per_token": 9e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 9e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2-VL-72B-Instruct": { + "input_cost_per_token": 1.2e-06, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2.5-14B-Instruct": { + "input_cost_per_token": 8e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 8e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2.5-72B-Instruct": { + "input_cost_per_token": 1.2e-06, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 1.2e-06, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2.5-Coder-32B-Instruct": { + "input_cost_per_token": 8e-07, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 8e-07, + "source": "https://api.together.ai/v1/models" + }, + "together_ai/Qwen/Qwen2.5-VL-72B-Instruct": { + "input_cost_per_token": 1.95e-06, + "litellm_provider": "together_ai", + "mode": "chat", + "output_cost_per_token": 8e-06, + "source": "https://api.together.ai/v1/models" } } diff --git a/model_prices_and_context_window.schema.json b/model_prices_and_context_window.schema.json index 7ed1e7e568b..c2490041cf7 100644 --- a/model_prices_and_context_window.schema.json +++ b/model_prices_and_context_window.schema.json @@ -249,6 +249,10 @@ "type": "number", "minimum": 0 }, + "input_cost_per_audio_token_batches": { + "type": "number", + "minimum": 0 + }, "input_cost_per_audio_token_priority": { "type": "number", "minimum": 0, @@ -276,6 +280,10 @@ "type": "number", "minimum": 0 }, + "input_cost_per_image_token_batches": { + "type": "number", + "minimum": 0 + }, "input_cost_per_pixel": { "type": "number", "minimum": 0 @@ -375,6 +383,14 @@ "minimum": 0, "description": "Rate applied once the prompt exceeds the token threshold in the field name." }, + "input_cost_per_video_token": { + "type": "number", + "minimum": 0 + }, + "input_cost_per_video_token_batches": { + "type": "number", + "minimum": 0 + }, "input_dbu_cost_per_token": { "type": "number", "minimum": 0 @@ -682,6 +698,9 @@ "supports_adaptive_thinking": { "type": "boolean" }, + "supports_anthropic_thinking_payload": { + "type": "boolean" + }, "supports_assistant_prefill": { "type": "boolean" }, diff --git a/osv-scanner.toml b/osv-scanner.toml index 3e070fc8cf7..482254d4da6 100644 --- a/osv-scanner.toml +++ b/osv-scanner.toml @@ -5,5 +5,5 @@ reason = "diskcache has no fixed release published; remove this entry once one e [[IgnoredVulns]] id = "GHSA-h7x2-h6g9-p789" -ignoreUntil = 2026-09-14 -reason = "mlflow has no fixed release published; remove this entry once one exists" +ignoreUntil = 2026-10-14 +reason = "mlflow has no fixed release published (3.16.0, 2026-09-04, and master still store gateway secret api_base unvalidated); remove this entry once one exists" diff --git a/ruff.toml b/ruff.toml index 3ac4c1fc94d..fab3fe27aed 100644 --- a/ruff.toml +++ b/ruff.toml @@ -4,11 +4,12 @@ lint.ignore = ["F405", "E402", "F403"] # That gives editors and `ruff check --fix` the diagnostic, which the gate script cannot. lint.extend-select = [ "T20", "PGH004", "RUF008", "RUF009", "RUF100", - "B033", "FURB136", "FURB168", "FURB188", "I001", "PERF402", "PIE790", "PIE800", "PLC0208", - "PLR0402", "PLR1711", "PLR1730", "PLR2044", "PLW0133", "PYI030", "PYI041", "PYI064", "RET501", - "RUF010", "RUF022", "RUF023", "RUF051", "S113", "SIM114", "SIM118", "TC005", "UP006", "UP007", - "UP008", - "UP012", "UP018", "UP024", "UP032", "UP034", "UP035", "UP037", "UP045", + "B004", "B018", "B021", "B033", "FURB136", "FURB168", "FURB188", "I001", "PERF402", "PIE790", + "PIE800", "PLC0208", "PLR0124", "PLR0402", "PLR0206", "PLR1704", "PLR1711", "PLR1730", "PLR2044", + "PLW0133", "PYI030", "PYI041", "PYI064", "RET501", "RUF010", "RUF022", "RUF023", "RUF051", "S113", + "SIM114", "SIM118", "SIM201", "SIM211", "SIM222", "TC005", "UP006", "UP007", "UP008", + "UP012", "UP018", "UP024", "UP032", "UP034", "UP035", "UP036", "UP037", "UP045", + "C404", "C419", ] # RUF100 (unused-noqa) only knows the rules enabled in THIS config, so it would strip # `# noqa` directives that protect rules enforced elsewhere. List those codes as external diff --git a/schema.prisma b/schema.prisma index 7d521d54791..dd7967aafe3 100644 --- a/schema.prisma +++ b/schema.prisma @@ -659,12 +659,14 @@ model LiteLLM_SpendLogs { mcp_namespaced_tool_name String? agent_id String? proxy_server_request Json? @default("{}") + litellm_call_id String? created_at DateTime @default(now()) @map("created_at") updated_at DateTime @default(now()) @updatedAt @map("updated_at") @@index([startTime]) @@index([startTime, request_id]) @@index([end_user]) @@index([session_id]) + @@index([litellm_call_id]) } model LiteLLM_BudgetWindowSpend { diff --git a/tests/code_coverage_tests/test_e2e_changed_gate.py b/tests/code_coverage_tests/test_e2e_changed_gate.py index 588402e3996..101816c7f11 100644 --- a/tests/code_coverage_tests/test_e2e_changed_gate.py +++ b/tests/code_coverage_tests/test_e2e_changed_gate.py @@ -81,6 +81,25 @@ def test_missing_execution_evidence_fails(tmp_path: Path, contents: str) -> None assert result.returncode == 1 +@pytest.mark.parametrize("omitted_role", ("proxy_admin", "team_member", "internal_user_viewer")) +def test_one_passing_management_case_cannot_hide_a_missing_actor(tmp_path: Path, omitted_role: str) -> None: + suite: Final = ET.Element("testsuite") + path: Final = "tests/e2e/management/test_jwt_management_e2e.py" + case: Final = ET.SubElement(suite, "testcase", file=path) + properties: Final = ET.SubElement(case, "properties") + _ = ET.SubElement( + properties, + "property", + name="management_node", + value=f"{path}::TestJwtManagement::test_actor_subject_and_database_role[proxy_admin_viewer]", + ) + report: Final = tmp_path / "report.xml" + ET.ElementTree(suite).write(report) + result: Final = subprocess.run([sys.executable, str(GATE), str(report), path], capture_output=True, text=True) + assert result.returncode == 1 + assert f"test_actor_subject_and_database_role[{omitted_role}]" in result.stdout + + def test_short_values_are_written_without_masking_every_digit_in_the_log(tmp_path: Path) -> None: env_path: Final = tmp_path / ".env" @@ -141,6 +160,10 @@ def test_changed_suite_files_are_selected_unless_the_stack_cannot_run_them( ( "tests/e2e/proxy_client.py", "tests/e2e/conftest.py", + "tests/e2e/management/management_client.py", + "tests/e2e/management/jwt_actors.py", + "tests/e2e/management/conftest.py", + "tests/e2e/coverage_registry/management_cases.py", "tests/e2e/pytest.ini", "tests/e2e/gateway/stage_mirror_ci_config.yml", ".github/e2e-stack/up.sh", diff --git a/tests/code_coverage_tests/test_provider_replay_harness.py b/tests/code_coverage_tests/test_provider_replay_harness.py new file mode 100644 index 00000000000..e7c5c96b64b --- /dev/null +++ b/tests/code_coverage_tests/test_provider_replay_harness.py @@ -0,0 +1,329 @@ +from __future__ import annotations + +import json +import os +import subprocess +import sys +import threading +from pathlib import Path +from typing import Final + +import pytest +from fixture_bundle import BundleRecorder, LoadedBundle, load_bundle, prepare_bundle +from fixture_mode import current_test_key +from fixture_profile import MatchProfile +from provider_edge import REPLAY_MISS_STATUS, RecordEdge, ReplayEdge, ReplaySource +from test_provider_edge import ( + CHAT_PATH, + SSE_CHUNKS, + STREAM_BODY, + UPLOAD_PATH, + call_edge, + chunked_provider, + fake_provider, + json_object, + provider_url, + raw_stream_post, + running_edge, + this_tests_files, +) + + +class TestStrictIdentity: + @pytest.mark.parametrize("path", [CHAT_PATH, "/anthropic/v1/messages"]) + def test_roundtrip_rejects_semantic_changes(self, tmp_path: Path, path: str) -> None: + recorder: Final = prepare_bundle(tmp_path / "strict", profile="stateless_v1") + assert isinstance(recorder, BundleRecorder) + original: Final = ( + b'{"model":"synthetic","messages":[{"role":"user",' + b'"content":"2031-04-05 00000000-0000-0000-0000-000000000001"}],"options":[1,2]}' + ) + headers: Final = { + "content-type": "application/json", + "accept": "application/json", + "anthropic-version": "2023-06-01", + "anthropic-beta": "feature-a", + "openai-beta": "feature-b", + "authorization": "Bearer synthetic-secret-one", + } + query: Final = "?part=one&part=two&blank=" + with fake_provider() as provider: + mounts: Final = {"openai": provider_url(provider), "anthropic": provider_url(provider)} + with running_edge(RecordEdge(recorder, threading.Lock()), mounts) as edge: + captured: Final = call_edge(edge, "POST", path + query, body=original, headers=headers) + assert captured.status_code == 200 + assert json_object(captured.body)["echo"] == original.decode() + loaded: Final = load_bundle(recorder.root, profile="stateless_v1") + assert isinstance(loaded, LoadedBundle) + assert loaded.manifest.match_profile == "stateless_v1" + source: Final = ReplaySource(loaded) + with running_edge(ReplayEdge(source), mounts) as edge: + cases: Final = ( + (original.replace(b"2031-04-05", b"2032-06-07"), headers, query, "body"), + (original.replace(b"000000000001", b"000000000002"), headers, query, "body"), + (original.replace(b"[1,2]", b"[2,1]"), headers, query, "body"), + (original.replace(b"synthetic", b"other"), headers, query, "body"), + (original, headers, "?part=three&part=two&blank=", "query"), + (original, headers, "?part=two&part=one&blank=", "query"), + *( + (original, {k: v for k, v in headers.items() if k != name}, query, "headers") + for name in ("accept", "anthropic-version", "anthropic-beta", "openai-beta") + ), + *( + (original, {**headers, name: value}, query, "headers") + for name in ("accept", "anthropic-version", "anthropic-beta", "openai-beta") + for value in ("different", "") + ), + (original, {**headers, "authorization": "Basic synthetic-secret-two"}, query, "auth"), + (original, {k: v for k, v in headers.items() if k != "authorization"}, query, "auth"), + ) + for rejected, reason in ( + (call_edge(edge, "POST", path + changed_query, body=body, headers=changed_headers), reason) + for body, changed_headers, changed_query, reason in cases + ): + assert rejected.status_code == REPLAY_MISS_STATUS + assert reason in rejected.body.decode() + assert b"synthetic-secret" not in rejected.body + reordered: Final = json.dumps(dict(reversed(list(json_object(original).items())))).encode() + accepted: Final = call_edge( + edge, "POST", path + query, body=reordered, headers={k.upper(): v for k, v in headers.items()} + ) + assert accepted.status_code == 200 + assert accepted.body == captured.body + assert source.leftover_error(current_test_key()) is None + assert len(provider.hits) == 1 + assert "synthetic-secret" not in "".join(file.read_text() for file in recorder.root.rglob("*.json")) + + @pytest.mark.parametrize( + "body", + [ + b'{"value":null}', + b'{"value":""}', + b'{"value":false}', + b'{"value":0}', + b'{"value":[]}', + b'{"value":{}}', + b'{"value":0.123456789012345678901}', + b'{"value":0.123456789012345678902}', + b'{"value":1e400}', + b'{"value":1}', + b'{"value":1e0}', + b'{"value":-0}', + b'{"value":1e9999999999999999999}', + ], + ) + def test_json_values_remain_distinct(self, tmp_path: Path, body: bytes) -> None: + recorder: Final = prepare_bundle(tmp_path / "strict", profile="stateless_v1") + assert isinstance(recorder, BundleRecorder) + with fake_provider() as provider: + mounts: Final = {"openai": provider_url(provider)} + with running_edge(RecordEdge(recorder, threading.Lock()), mounts) as edge: + assert ( + call_edge( + edge, "POST", CHAT_PATH, body=body, headers={"content-type": "application/json"} + ).status_code + == 200 + ) + loaded: Final = load_bundle(recorder.root, profile="stateless_v1") + assert isinstance(loaded, LoadedBundle) + with running_edge(ReplayEdge(ReplaySource(loaded)), mounts) as edge: + values: Final = ( + b"{}", + b'{"value":null}', + b'{"value":""}', + b'{"value":false}', + b'{"value":0}', + b'{"value":[]}', + b'{"value":{}}', + b'{"value":0.123456789012345678901}', + b'{"value":0.123456789012345678902}', + b'{"value":1e400}', + b'{"value":1}', + b'{"value":1e0}', + b'{"value":-0}', + b'{"value":1e9999999999999999999}', + ) + for rejected in ( + call_edge(edge, "POST", CHAT_PATH, body=value, headers={"content-type": "application/json"}) + for value in values + if value != body + ): + assert rejected.status_code == REPLAY_MISS_STATUS + assert b"body" in rejected.body + assert ( + call_edge( + edge, "POST", CHAT_PATH, body=body, headers={"content-type": "application/json"} + ).status_code + == 200 + ) + assert len(provider.hits) == 1 + + @pytest.mark.parametrize( + "path,body,headers", + [ + (UPLOAD_PATH, b"{}", {"content-type": "application/json"}), + (CHAT_PATH + "?part=%FF", b"{}", {"content-type": "application/json"}), + (CHAT_PATH + "?part=%FE", b"{}", {"content-type": "application/json"}), + (CHAT_PATH, b"opaque", {"content-type": "application/octet-stream"}), + (CHAT_PATH, b"--boundary", {"content-type": "multipart/form-data; boundary=boundary"}), + (CHAT_PATH, b'{"x":1,"x":2}', {"content-type": "application/json"}), + (CHAT_PATH, b"{}", {"content-type": "application/json", "x-custom-behavior": "synthetic-private-value"}), + ], + ) + def test_ineligible_capture_never_calls_provider( + self, tmp_path: Path, path: str, body: bytes, headers: dict[str, str] + ) -> None: + recorder: Final = prepare_bundle(tmp_path / "strict", profile="stateless_v1") + assert isinstance(recorder, BundleRecorder) + with fake_provider() as provider: + with running_edge(RecordEdge(recorder, threading.Lock()), {"openai": provider_url(provider)}) as edge: + result: Final = call_edge(edge, "POST", path, body=body, headers=headers) + assert result.status_code == REPLAY_MISS_STATUS + assert b"eligibility error" in result.body + assert b"synthetic-private-value" not in result.body + assert provider.hits == [] + assert this_tests_files(recorder.root) == [] + + def test_destination_is_part_of_actual_http_identity(self, tmp_path: Path) -> None: + recorder: Final = prepare_bundle(tmp_path / "strict", profile="stateless_v1") + assert isinstance(recorder, BundleRecorder) + with fake_provider() as provider: + with running_edge(RecordEdge(recorder, threading.Lock()), {"openai": provider_url(provider)}) as edge: + assert ( + call_edge( + edge, "POST", CHAT_PATH, body=b"{}", headers={"content-type": "application/json"} + ).status_code + == 200 + ) + loaded: Final = load_bundle(recorder.root, profile="stateless_v1") + assert isinstance(loaded, LoadedBundle) + with running_edge(ReplayEdge(ReplaySource(loaded)), {"openai": provider_url(provider) + "/other"}) as edge: + result: Final = call_edge( + edge, "POST", CHAT_PATH, body=b"{}", headers={"content-type": "application/json"} + ) + assert result.status_code == REPLAY_MISS_STATUS + assert b"upstream" in result.body + assert len(provider.hits) == 1 + + def test_credentials_are_not_identity_and_fresh_process_replays(self, tmp_path: Path) -> None: + recorder: Final = prepare_bundle(tmp_path / "strict", profile="stateless_v1") + assert isinstance(recorder, BundleRecorder) + headers: Final = { + "content-type": "application/json", + "authorization": "bEaReR synthetic-token", + "x-api-key": "synthetic-api-key", + "cookie": "synthetic-cookie", + } + path: Final = CHAT_PATH + "?api_key=synthetic-query-secret&part=one&part=two" + body: Final = b'{"model":"synthetic","messages":[]}' + with fake_provider(echo_request=False) as provider: + mounts: Final = {"openai": provider_url(provider)} + with running_edge(RecordEdge(recorder, threading.Lock()), mounts) as edge: + captured: Final = call_edge(edge, "POST", path, body=body, headers=headers) + assert captured.status_code == 200 + seen_headers, seen_body = provider.requests[0] + assert {k.lower(): v for k, v in seen_headers.items()}.items() >= headers.items() + assert seen_body == body + assert provider.hits == ["POST " + path.removeprefix("/openai")] + artifacts: Final = "".join(file.read_text() for file in recorder.root.rglob("*.json")) + for secret in ("synthetic-token", "synthetic-api-key", "synthetic-cookie", "synthetic-query-secret"): + assert secret not in artifacts + child: Final = subprocess.run( + [ + sys.executable, + "-c", + """ +import json, sys +from pathlib import Path +from fixture_bundle import LoadedBundle, load_bundle +from provider_edge import ProviderRequestObservation, observed_provider_edge, replay_leftover_error +from test_provider_edge import call_edge +from fixture_profile import MatchProfile +from fixture_mode import current_test_key +loaded = load_bundle(Path(sys.argv[1]), profile="stateless_v1") +assert isinstance(loaded, LoadedBundle) +with observed_provider_edge(ProviderRequestObservation("synthetic"), mode_raw="replay", bundle_dir=Path(sys.argv[1]), bind_host="127.0.0.1", advertise_host="127.0.0.1", mounts={"openai": sys.argv[2]}) as edge: + response = call_edge(edge, "POST", sys.argv[3], body=sys.argv[4].encode(), headers=json.loads(sys.argv[5])) + assert response.status_code == 200 + print(response.body.decode()) +assert replay_leftover_error(mode_raw="replay", bundle_dir=Path(sys.argv[1]), test_key=current_test_key()) is None +""", + str(recorder.root), + provider_url(provider), + path.replace("synthetic-query-secret", "new-query-credential"), + body.decode(), + json.dumps({**headers, "authorization": "Bearer another-credential", "x-api-key": "another-key"}), + ], + env={ + **os.environ, + "PYTHONPATH": str(Path(__file__).resolve().parents[1] / "e2e"), + "E2E_REPLAY_MATCH_PROFILE": "stateless_v1", + }, + capture_output=True, + text=True, + timeout=30, + ) + assert child.returncode == 0, child.stderr + assert child.stdout.strip().encode() == captured.body + assert len(provider.hits) == 1 + + @pytest.mark.parametrize("profile,other", [("legacy", "stateless_v1"), ("stateless_v1", "legacy")]) + def test_profiles_cannot_load_each_others_bundles( + self, tmp_path: Path, profile: MatchProfile, other: MatchProfile + ) -> None: + from fixture_bundle import UnreadableBundle + + recorder: Final = prepare_bundle(tmp_path / profile, profile=profile) + assert isinstance(recorder, BundleRecorder) + mismatch: Final = load_bundle(recorder.root, profile=other) + assert isinstance(mismatch, UnreadableBundle) + assert "profile mismatch" in mismatch.reason + assert "re-record" in mismatch.reason + + @pytest.mark.parametrize("abort_after", [None, 2]) + def test_strict_stream_preserves_chunks_and_truncation(self, tmp_path: Path, abort_after: int | None) -> None: + recorder: Final = prepare_bundle(tmp_path / "strict", profile="stateless_v1") + assert isinstance(recorder, BundleRecorder) + with chunked_provider(abort_after=abort_after) as provider: + mounts: Final = {"anthropic": provider_url(provider)} + with running_edge(RecordEdge(recorder, threading.Lock()), mounts) as edge: + _, captured, captured_ending = raw_stream_post(edge.port, "/anthropic/v1/messages", STREAM_BODY) + loaded: Final = load_bundle(recorder.root, profile="stateless_v1") + assert isinstance(loaded, LoadedBundle) + source: Final = ReplaySource(loaded) + with running_edge(ReplayEdge(source), mounts) as edge: + _, replayed, ending = raw_stream_post(edge.port, "/anthropic/v1/messages", STREAM_BODY) + assert captured == replayed == list(SSE_CHUNKS[:abort_after]) + assert ending == captured_ending + assert (ending == "terminated") == (abort_after is None) + assert source.leftover_error(current_test_key()) is None + assert len(provider.hits) == 1 + + def test_auth_scheme_survives_missing_credentials(self, tmp_path: Path) -> None: + recorder: Final = prepare_bundle(tmp_path / "strict", profile="stateless_v1") + assert isinstance(recorder, BundleRecorder) + headers: Final = {"content-type": "application/json", "authorization": "Bearer"} + with fake_provider() as provider: + mounts: Final = {"openai": provider_url(provider)} + with running_edge(RecordEdge(recorder, threading.Lock()), mounts) as edge: + assert call_edge(edge, "POST", CHAT_PATH, body=b"{}", headers=headers).status_code == 200 + loaded: Final = load_bundle(recorder.root, profile="stateless_v1") + assert isinstance(loaded, LoadedBundle) + with running_edge(ReplayEdge(ReplaySource(loaded)), mounts) as edge: + for result in ( + call_edge(edge, "POST", CHAT_PATH, body=b"{}", headers={**headers, "authorization": scheme}) + for scheme in ("Basic", "Digest") + ): + assert result.status_code == REPLAY_MISS_STATUS + assert b"auth" in result.body + assert ( + call_edge( + edge, + "POST", + CHAT_PATH, + body=b"{}", + headers={**headers, "authorization": "bEaReR synthetic-token"}, + ).status_code + == 200 + ) + assert len(provider.hits) == 1 diff --git a/tests/e2e/CLAUDE.md b/tests/e2e/CLAUDE.md index a58c13d6a1c..0541ce25d4b 100644 --- a/tests/e2e/CLAUDE.md +++ b/tests/e2e/CLAUDE.md @@ -69,7 +69,7 @@ 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). Pure coverage of the harness itself carries no marker and runs regardless. 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). 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 @@ -221,7 +221,7 @@ other... ``` ## Hard Rules -- no monkeypatching or mock tests, and never substitute a unit test for e2e feature coverage: a product feature is proven end to end against a live proxy, not with a unit test. if a contributor asks you to write an end to end test, do NOT stage a unit test of the feature with it; if you find a product gap, call it out in the PR description. tests that cover the harness itself are the exception and are allowed (for example `coverage_registry/test_collector.py`, which unit-tests the coverage collector): they carry no `e2e` marker, exercise harness plumbing rather than a product feature, and run whether or not a proxy is up +- no unit tests of any kind under `tests/e2e`. a product feature is proven end to end against a live proxy, never with a unit test, and the harness itself is not unit-tested here either. no monkeypatching or mock tests. if a contributor asks you to write an end to end test, do NOT stage a unit test with it; if you find a product gap, call it out in the PR description - use model management endpoints to create new models for a test. this could be in a conftest / inline for each test. ask the user what they want. diff --git a/tests/e2e/CONTRIBUTING.md b/tests/e2e/CONTRIBUTING.md index 44564a51e26..53a05931ca7 100644 --- a/tests/e2e/CONTRIBUTING.md +++ b/tests/e2e/CONTRIBUTING.md @@ -60,7 +60,11 @@ The suites run against a live proxy, so bring one up first by running the litell Keycloak's password grant is a test-only provisioning shortcut, not a production login recommendation. The `litellm-e2e-admin` client adds the proxy's admin scope; the normal client does not. Never reuse this permissive realm outside an isolated test stack. - Management tests can use the shared `idp` and `jwt_identity` fixtures. Each test gets a unique Keycloak group/user and a matching proxy user/team. Setup and fallback cleanup use the master key; the operations and read-backs being tested must explicitly use `caller_key=idp.access_token(jwt_identity, client_id=ADMIN_CLIENT_ID)` (or a member token). See `management/test_jwt_management_e2e.py` for create/read/update/clear/delete and tenant-denial examples. A group claim alone is not database team membership: permission tests explicitly add the member and prove an allowed read before asserting the denied write. + Management tests can bind a credential once with `client.with_caller(Caller(...))`; direct calls, delegated helpers and replica read-backs then retain that caller. Explicit `caller_key` arguments override the binding. Keep the original master-backed client for bootstrap and cleanup. `actor_factory` lazily provisions database roles and tenant memberships, with `database_role` tokens carrying no groups and `group_scoped` actors retaining the existing team route gate. Token minting is explicit through `actor.mint_caller(idp)`. The factory runs requests without backend retries and reports cleanup failures. `coverage_registry/management_cases.py` records exact canary nodes and non-secret actor labels; the CI execution assertion rejects a missing or skipped actor row + + For the opt-in browser profile, start the existing IdP first, then run `.github/e2e-stack/oidc-profile.sh "$PROXY_BASE_URL" `. The wrapper creates a confidential client with an exact `/sso/callback` redirect and S256 PKCE, passes the client secret only through the child process environment, and removes the client on exit. It uses the existing generic OIDC handler with `GENERIC_USER_ID_ATTRIBUTE=sub`. Preserve the IdP's PostgreSQL data across restarts + + `tests/e2e/ui/playwright.oidc.config.ts` uses an already running OIDC stack and separate storage/output files. Supply `E2E_OIDC_UI_URL`, `JWT_ISSUER`, `E2E_OIDC_USERNAME` and `E2E_OIDC_PASSWORD` for a seeded actor. Its setup follows the real login and callback path. The current Python canary qualifies browser-client configuration and token/userinfo identity mapping; browser journey specs under `ui/oidc/` are a separate coverage step Every successful IdP create immediately registers cleanup, including partial setup failures. Cleanup failures emit warnings. Tokens are minted on demand, and the expiration test waits relative to the token's actual `exp` with a bounded clock-drift check. To check first-attempt behavior locally, run both files with `--reruns 0`: @@ -232,3 +236,15 @@ Before you push 4. Capture screenshots of the test run and attach them to the PR as proof 5. If a test fails because it surfaced a real issue in the product, flag that explicitly in the PR rather than reworking the test until it passes + +### Strict stateless replay matching + +Set `E2E_REPLAY_MATCH_PROFILE=stateless_v1` for both recording and replay to bind OpenAI `/v1/chat/completions` and Anthropic `/v1/messages` requests to their upstream destination, ordered query pairs, semantic headers and literal JSON content. The default remains `legacy`. Strict bundles use format 5 and cannot load as legacy bundles; select the matching profile or re-record with `E2E_FIXTURE_MODE=record`. Missing profile metadata never enrolls a legacy bundle in strict matching + +Strict matching preserves dates, UUIDs, hashes, model names, tool arguments, array order and omitted/null/empty/false/zero values. JSON object key order and header name casing may change. The strict body uses tagged JSON values so number precision and JSON types survive persistence, including exact numeric spelling and numbers larger than a floating-point value. Invalid UTF-8 query values fail eligibility. Duplicate JSON keys, unsupported endpoints, non-JSON bodies and unknown semantic headers fail eligibility before contacting a provider + +The semantic header set is `content-type`, `accept`, `anthropic-version`, `anthropic-beta` and `openai-beta`, including missing versus present values. Authorization records presence and the case-insensitive scheme; `x-api-key` records presence only. Credential values and cookies are excluded. Credential query values are redacted while their position and field name remain in the identity. Never use real customer inputs in fixture qualification + +Excluded transport and telemetry headers are `host`, `content-length`, `connection`, `accept-encoding`, `user-agent`, `traceparent`, `tracestate`, `x-request-id`, `x-client-request-id` and `x-stainless-*`. Inbound transfer-encoding is unsupported; send JSON with content-length framing. The destination represents host identity and the relay carries original body bytes. Replay does not verify credentials, SDK timeout/retry behavior, transport performance, model availability or stateful remote IDs. Live relay uses original request bytes and header values, never the stored identity + +Strict replay harness regression tests live in `tests/code_coverage_tests/test_provider_replay_harness.py`. The CircleCI `provider_replay_harness` job runs them alongside the existing legacy harness files with `--noconftest -o pythonpath=tests/e2e`; they need only synthetic HTTP providers and temporary fixture storage diff --git a/tests/e2e/coverage_registry/management_cases.py b/tests/e2e/coverage_registry/management_cases.py new file mode 100644 index 00000000000..812dbfe5b8d --- /dev/null +++ b/tests/e2e/coverage_registry/management_cases.py @@ -0,0 +1,151 @@ +from dataclasses import dataclass +from typing import Final, Literal + +CredentialKind = Literal["master", "idp_admin", "direct_jwt", "virtual_key", "dashboard_session"] +DependencyProfile = Literal["management_only", "real_oidc_browser", "external_provider_required"] + + +@dataclass(frozen=True, slots=True) +class ManagementCase: + node: str + credential_kind: CredentialKind + actor: str + profile: str + method: Literal["GET", "POST"] + path: str + operation_family: str + dependency_profile: DependencyProfile = "management_only" + + +JWT_FILE: Final = "tests/e2e/management/test_jwt_management_e2e.py" +JWT_CLASS: Final = f"{JWT_FILE}::TestJwtManagement" +ACTORS: Final = ( + "proxy_admin", + "proxy_admin_viewer", + "organization_admin", + "team_admin", + "team_member", + "internal_user", + "internal_user_viewer", + "unrelated_user", +) +MANAGEMENT_CASES: Final = tuple( + ManagementCase( + node=f"{JWT_CLASS}::test_actor_subject_and_database_role[{role}]", + credential_kind="direct_jwt", + actor=role, + profile="database_role", + method="GET", + path="/user/info", + operation_family="identity", + ) + for role in ACTORS +) + ( + ManagementCase( + node=f"{JWT_CLASS}::test_admin_viewer_reads_but_cannot_update", + credential_kind="direct_jwt", + actor="proxy_admin_viewer", + profile="database_role", + method="POST", + path="/key/update", + operation_family="denial", + ), + ManagementCase( + node=f"{JWT_CLASS}::test_admin_creates_reads_updates_clears_and_deletes_a_key[direct_jwt]", + credential_kind="direct_jwt", + actor="proxy_admin", + profile="group_scoped", + method="POST", + path="/key/generate", + operation_family="key_lifecycle", + ), + ManagementCase( + node=f"{JWT_CLASS}::test_admin_creates_reads_updates_clears_and_deletes_a_key[virtual_key]", + credential_kind="virtual_key", + actor="proxy_admin", + profile="group_scoped", + method="POST", + path="/key/generate", + operation_family="key_lifecycle", + ), + ManagementCase( + node=f"{JWT_CLASS}::test_two_actor_sets_keep_tenants_and_keys_isolated", + credential_kind="direct_jwt", + actor="team_member", + profile="group_scoped", + method="GET", + path="/key/info", + operation_family="tenant_isolation", + ), + ManagementCase( + node=f"{JWT_CLASS}::test_member_cannot_write_and_another_team_cannot_read_the_key", + credential_kind="direct_jwt", + actor="team_member", + profile="group_scoped", + method="POST", + path="/key/update", + operation_family="tenant_isolation", + ), + ManagementCase( + node=f"{JWT_CLASS}::test_multi_group_actor_keeps_exact_memberships", + credential_kind="master", + actor="bootstrap", + profile="group_scoped", + method="GET", + path="/team/info", + operation_family="memberships", + ), + ManagementCase( + node=f"{JWT_CLASS}::test_successful_actor_cleanup_removes_owned_state", + credential_kind="master", + actor="bootstrap", + profile="failure_cleanup", + method="GET", + path="/team/info", + operation_family="cleanup", + ), + ManagementCase( + node=f"{JWT_CLASS}::test_partial_setup_removes_previously_created_identities[group]", + credential_kind="idp_admin", + actor="idp_admin", + profile="failure_cleanup", + method="POST", + path="/groups", + operation_family="cleanup", + ), + ManagementCase( + node=f"{JWT_CLASS}::test_partial_setup_removes_previously_created_identities[user]", + credential_kind="idp_admin", + actor="idp_admin", + profile="failure_cleanup", + method="POST", + path="/users", + operation_family="cleanup", + ), + ManagementCase( + node=f"{JWT_CLASS}::test_oidc_browser_profile_identity_mapping", + credential_kind="direct_jwt", + actor="internal_user", + profile="oidc_configuration", + method="GET", + path="/protocol/openid-connect/userinfo", + operation_family="oidc_identity", + ), +) + + +def canonical_node(node: str) -> str: + return node if node.startswith("tests/e2e/") else f"tests/e2e/{node}" + + +def case_properties(node: str) -> tuple[tuple[str, str], ...]: + case: Final = next((case for case in MANAGEMENT_CASES if case.node == canonical_node(node)), None) + if case is None: + return () + return ( + ("management_node", case.node), + ("credential_kind", case.credential_kind), + ("actor", case.actor), + ("auth_profile", case.profile), + ("dependency_profile", case.dependency_profile), + ) diff --git a/tests/e2e/coverage_registry/mcp.yaml b/tests/e2e/coverage_registry/mcp.yaml index f853e9ff8d6..a7d4135d550 100644 --- a/tests/e2e/coverage_registry/mcp.yaml +++ b/tests/e2e/coverage_registry/mcp.yaml @@ -78,7 +78,7 @@ auth_family: none assertions: [succeeds] source: "mcp_server_manager.py:1485-1492" - rationale: Public/anonymous servers; delegate_auth_to_upstream + rationale: Explicitly anonymous true_passthrough servers - id: mcp.call_tool.none.succeeds module: mcp tier: P1 diff --git a/tests/e2e/coverage_registry/mgmt.yaml b/tests/e2e/coverage_registry/mgmt.yaml index d1227fe7c0c..31ad61ba3e2 100644 --- a/tests/e2e/coverage_registry/mgmt.yaml +++ b/tests/e2e/coverage_registry/mgmt.yaml @@ -90,3 +90,11 @@ - {id: mgmt.mcp_toolset.update.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "mcp_management_endpoints.py:3098", rationale: "Narrowing the tools to one entry reads back exactly that entry"} - {id: mgmt.mcp_toolset.update.clear_persists, module: mgmt, tier: P0, surface: api, assertions: [clear_persists], source: "mcp_management_endpoints.py:3098", fail_before_fix: proven, rationale: "An explicit null clears the stored description; the update used to drop null and keep the old value"} - {id: mgmt.mcp_toolset.delete.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "mcp_management_endpoints.py:3149", rationale: "A deleted toolset is gone by id and from the list on every replica"} + +- {id: mgmt.user.jwt.database_roles, module: mgmt, tier: P0, surface: api, assertions: [database_roles], source: "auth/handle_jwt.py", rationale: "User-only JWT subjects retain their seeded database roles and memberships"} +- {id: mgmt.key.jwt.viewer_denied, module: mgmt, tier: P0, surface: api, assertions: [viewer_denied], source: "auth/route_checks.py", rationale: "An admin viewer can read a key but cannot update it or change stored state"} +- {id: mgmt.user.oidc.identity_mapping, module: mgmt, tier: P0, surface: api, assertions: [identity_mapping], source: "tests/e2e/idp.py", rationale: "IdP configuration canary only: confidential-client token and userinfo subjects match the seeded user; application SSO is separate"} +- {id: mgmt.team.jwt.tenant_isolation, module: mgmt, tier: P0, surface: api, assertions: [tenant_isolation], source: "auth/handle_jwt.py", rationale: "Isolated team actors read their own key and receive 403 for the other tenant key"} +- {id: mgmt.team.jwt.multiple_memberships, module: mgmt, tier: P0, surface: api, assertions: [multiple_memberships], source: "auth/handle_jwt.py", rationale: "A multi-group actor has exactly the configured memberships without admin scope"} +- {id: mgmt.user.jwt.cleanup, module: mgmt, tier: P0, surface: api, assertions: [cleanup], source: "management_endpoints/internal_user_endpoints.py", rationale: "Owned users teams organizations keys and IdP objects disappear after successful cleanup"} +- {id: mgmt.user.jwt.partial_cleanup, module: mgmt, tier: P0, surface: api, assertions: [partial_cleanup], source: "auth/handle_jwt.py", rationale: "Partial identity setup removes the group and user created before failure"} diff --git a/tests/e2e/e2e_http.py b/tests/e2e/e2e_http.py index ce069720c6e..e0a20495964 100644 --- a/tests/e2e/e2e_http.py +++ b/tests/e2e/e2e_http.py @@ -16,9 +16,11 @@ requests itself imports. from __future__ import annotations import time -from collections.abc import Callable, Mapping +from collections.abc import Callable, Generator, Iterator, Mapping +from contextlib import contextmanager +from contextvars import ContextVar from dataclasses import dataclass -from typing import Final, Generator, Generic, Iterator, Literal, NewType, Protocol, TypeVar, cast +from typing import Final, Generic, Literal, NewType, Protocol, TypeVar, cast import pytest import requests @@ -36,8 +38,8 @@ class Headers(BaseModel): class AuthHeaders(Headers): # litellm accepts either; set whichever the call needs, leave the other None. - authorization: str | None = None - x_litellm_api_key: str | None = Field(default=None, alias="x-litellm-api-key") + authorization: str | None = Field(default=None, repr=False) + x_litellm_api_key: str | None = Field(default=None, alias="x-litellm-api-key", repr=False) class AnthropicHeaders(AuthHeaders): @@ -168,6 +170,7 @@ class StreamingResponse(BaseModel): # the consumed body is elided, so this is the only place they surface. stream_error: str | None = None stream_done: bool = False + stream_done_positions: tuple[int, ...] = () @property def ok(self) -> bool: @@ -292,6 +295,22 @@ def _params(params: BaseModel | None) -> dict[str, str]: TRANSIENT_STATUSES: frozenset[int] = frozenset({529}) RETRY_ATTEMPTS: int = 3 +_QUALIFICATION: Final[ContextVar[bool]] = ContextVar("e2e_qualification", default=False) + + +def retry_attempts(default: int) -> int: + return 1 if _QUALIFICATION.get() else default + + +@contextmanager +def without_retries() -> Generator[None]: + token: Final = _QUALIFICATION.set(True) + try: + yield + finally: + _QUALIFICATION.reset(token) + + RETRY_BACKOFF_SECONDS: float = 0.5 @@ -319,7 +338,7 @@ def request_with_retry[T: RetryableResponse]( hang should surface as a hang instead of doubling the wall clock. Every retry prints, so flakiness stays visible in the run log instead of vanishing into green.""" - for attempt in range(1, RETRY_ATTEMPTS): + for attempt in range(1, retry_attempts(RETRY_ATTEMPTS)): resp = issue() if resp.status_code not in TRANSIENT_STATUSES: return resp @@ -414,6 +433,7 @@ def get_external[R: BaseModel]( url: str, *, response_type: type[R], + headers: BaseModel | None = None, timeout: float = 30.0, ) -> Result[R]: """GET an absolute URL outside the proxy (e.g. a public /.well-known document). @@ -422,7 +442,7 @@ def get_external[R: BaseModel]( try: resp = requests.get( url, - headers={"Accept": "application/json"}, + headers={"Accept": "application/json", **(_headers(headers) if headers is not None else {})}, timeout=timeout, ) except requests.RequestException as exc: @@ -628,6 +648,7 @@ def streaming_outcome( stream_events=[payload for payload, _ in events], stream_event_arrivals=[arrived for _, arrived in events], stream_done=any(payload == _SSE_DONE for payload, _ in payloads), + stream_done_positions=tuple(index for index, (payload, _) in enumerate(payloads) if payload == _SSE_DONE), stream_error=next( (line.decode(errors="replace")[:300] for line, _ in stamped if _is_stream_error_line(line)), None, diff --git a/tests/e2e/fixture_bundle.py b/tests/e2e/fixture_bundle.py index 7c9dab1a687..4467d7e4ecc 100644 --- a/tests/e2e/fixture_bundle.py +++ b/tests/e2e/fixture_bundle.py @@ -30,9 +30,11 @@ from datetime import datetime, timedelta, timezone from pathlib import Path from typing import Annotated, Final, Literal +from fixture_profile import MatchProfile, StrictIdentity from pydantic import BaseModel, Field, JsonValue BUNDLE_FORMAT_VERSION: Final = 4 +STRICT_BUNDLE_FORMAT_VERSION: Final = 5 MAX_BUNDLE_AGE: Final = timedelta(days=7) MANIFEST_FILENAME: Final = "manifest.json" @@ -41,6 +43,7 @@ class Manifest(BaseModel): format_version: int recorded_at: datetime harness_version: str + match_profile: MatchProfile = "legacy" class RecordedRequest(BaseModel): @@ -69,6 +72,7 @@ class RecordedRequest(BaseModel): file_name: str | None = None file_sha256: str | None = None file_bytes: int | None = None + strict_identity: StrictIdentity | None = None class RecordedHttpResponse(BaseModel): @@ -100,9 +104,7 @@ class RecordedStreamedResponse(BaseModel): truncated: str | None = None -type RecordedResponse = Annotated[ - RecordedHttpResponse | RecordedStreamedResponse, Field(discriminator="kind") -] +type RecordedResponse = Annotated[RecordedHttpResponse | RecordedStreamedResponse, Field(discriminator="kind")] class Interaction(BaseModel): @@ -152,6 +154,7 @@ class BundleRecorder: manifest, so record mode never reads (or merges into) an existing bundle.""" root: Path + profile: MatchProfile = "legacy" _ordinals: dict[str, int] = field(default_factory=dict) def record(self, *, test_key: str, request: RecordedRequest, response: RecordedResponse) -> None: @@ -162,7 +165,12 @@ class BundleRecorder: directory.mkdir(parents=True, exist_ok=True) interaction = Interaction(request=request, response=response) target = directory / interaction_filename(ordinal, request) - target.write_text(interaction.model_dump_json(indent=2), encoding="utf-8") + target.write_text( + interaction.model_dump_json( + indent=2, exclude={"request": {"strict_identity"}} if self.profile == "legacy" else None + ), + encoding="utf-8", + ) @dataclass(frozen=True, slots=True) @@ -171,7 +179,7 @@ class UnsafeBundleDir: reason: str -def prepare_bundle(root: Path) -> BundleRecorder | UnsafeBundleDir: +def prepare_bundle(root: Path, *, profile: MatchProfile = "legacy") -> BundleRecorder | UnsafeBundleDir: """Start a fresh bundle at ``root`` for record mode: wipe whatever bundle is there and write a new manifest. Refuses to wipe a directory that is neither empty nor a bundle (no manifest.json), so a mistyped E2E_FIXTURE_DIR can @@ -188,12 +196,15 @@ def prepare_bundle(root: Path) -> BundleRecorder | UnsafeBundleDir: shutil.rmtree(root) root.mkdir(parents=True) manifest = Manifest( - format_version=BUNDLE_FORMAT_VERSION, + format_version=BUNDLE_FORMAT_VERSION if profile == "legacy" else STRICT_BUNDLE_FORMAT_VERSION, + match_profile=profile, recorded_at=datetime.now(timezone.utc), harness_version=harness_version(), ) - (root / MANIFEST_FILENAME).write_text(manifest.model_dump_json(indent=2), encoding="utf-8") - return BundleRecorder(root=root) + (root / MANIFEST_FILENAME).write_text( + manifest.model_dump_json(indent=2, exclude={"match_profile"} if profile == "legacy" else None), encoding="utf-8" + ) + return BundleRecorder(root=root, profile=profile) @dataclass(frozen=True, slots=True) @@ -226,25 +237,30 @@ def _read_manifest(root: Path) -> Manifest | UnreadableBundle: return UnreadableBundle(reason=f"{MANIFEST_FILENAME} is invalid: {exc}") -def _supported_manifest(root: Path) -> Manifest | UnreadableBundle: +def _supported_manifest(root: Path, profile: MatchProfile = "legacy") -> Manifest | UnreadableBundle: """The manifest, refused when it was written under a different format version. A bundle is atomic (record wipes and rewrites the whole directory and never merges), so a foreign version is a hard reject rather than a partial read.""" manifest = _read_manifest(root) if isinstance(manifest, UnreadableBundle): return manifest - if manifest.format_version != BUNDLE_FORMAT_VERSION: + expected_version: Final = BUNDLE_FORMAT_VERSION if profile == "legacy" else STRICT_BUNDLE_FORMAT_VERSION + if manifest.match_profile != profile: + return UnreadableBundle( + reason="match profile mismatch; select the recorded E2E_REPLAY_MATCH_PROFILE or re-record" + ) + if manifest.format_version != expected_version: return UnreadableBundle( reason=( - f"format_version {manifest.format_version} != supported {BUNDLE_FORMAT_VERSION}; " + f"format_version {manifest.format_version} != supported {expected_version}; " "re-record with E2E_FIXTURE_MODE=record" ) ) return manifest -def check_freshness(root: Path, *, now: datetime) -> BundleFreshness: - manifest = _supported_manifest(root) +def check_freshness(root: Path, *, now: datetime, profile: MatchProfile = "legacy") -> BundleFreshness: + manifest = _supported_manifest(root, profile) if isinstance(manifest, UnreadableBundle): return manifest recorded_at = ( @@ -269,16 +285,27 @@ class LoadedBundle: interactions: dict[str, tuple[Interaction, ...]] -def load_bundle(root: Path) -> LoadedBundle | UnreadableBundle: - manifest = _supported_manifest(root) +def load_bundle(root: Path, *, profile: MatchProfile = "legacy") -> LoadedBundle | UnreadableBundle: + manifest = _supported_manifest(root, profile) if isinstance(manifest, UnreadableBundle): return manifest - interactions = { - directory.name: tuple( - Interaction.model_validate_json(file.read_text(encoding="utf-8")) - for file in sorted(directory.glob("*.json")) - ) - for directory in sorted(root.iterdir()) - if directory.is_dir() - } + try: + interactions = { + directory.name: tuple( + Interaction.model_validate_json(file.read_text(encoding="utf-8")) + for file in sorted(directory.glob("*.json")) + ) + for directory in sorted(root.iterdir()) + if directory.is_dir() + } + except (ValueError, OSError): + if profile == "legacy": + raise + return UnreadableBundle(reason="invalid stateless_v1 interaction; re-record with the selected profile") + if any( + (item.request.strict_identity is not None) != (profile == "stateless_v1") + for items in interactions.values() + for item in items + ): + return UnreadableBundle(reason="request identity/profile mismatch; re-record with the selected profile") return LoadedBundle(manifest=manifest, interactions=interactions) diff --git a/tests/e2e/fixture_canonical.py b/tests/e2e/fixture_canonical.py index c043951a108..e76d63ca33b 100644 --- a/tests/e2e/fixture_canonical.py +++ b/tests/e2e/fixture_canonical.py @@ -23,9 +23,8 @@ from dataclasses import dataclass from functools import reduce from typing import Final -from pydantic import JsonValue - from fixture_bundle import RecordedRequest +from pydantic import JsonValue VOLATILE_HEADER_NAMES: Final[frozenset[str]] = frozenset( { @@ -123,6 +122,12 @@ class CanonicalRequest: def canonicalize(request: RecordedRequest) -> CanonicalRequest: + if request.strict_identity is not None: + return CanonicalRequest( + method=request.method, + path=request.path, + content=json.dumps(request.strict_identity.model_dump(mode="json"), sort_keys=True, separators=(",", ":")), + ) file_identity: Final[JsonValue | None] = ( None if request.file_name is None and request.file_sha256 is None diff --git a/tests/e2e/fixture_mode.py b/tests/e2e/fixture_mode.py index 110f44380b4..9a7c1b6db12 100644 --- a/tests/e2e/fixture_mode.py +++ b/tests/e2e/fixture_mode.py @@ -26,6 +26,7 @@ from fixture_bundle import ( check_freshness, format_age, ) +from fixture_profile import match_profile type FixtureMode = Literal["live", "record", "replay"] @@ -82,6 +83,7 @@ def fixture_mode_collection_error(mode_raw: str, bundle_dir: Path, *, now: datet Called at collection time (conftest pytest_sessionstart) so a stale or missing bundle fails the whole run up front, naming the bundle age, instead of failing every test individually.""" + match_profile() mode = parse_fixture_mode(mode_raw) match mode: case InvalidFixtureMode(value=value): @@ -89,7 +91,7 @@ def fixture_mode_collection_error(mode_raw: str, bundle_dir: Path, *, now: datet case "live" | "record": return None case "replay": - freshness = check_freshness(bundle_dir, now=now) + freshness = check_freshness(bundle_dir, now=now, profile=match_profile()) match freshness: case FreshBundle(): return None @@ -110,6 +112,7 @@ def fixture_mode_collection_error(mode_raw: str, bundle_dir: Path, *, now: datet def fixture_report_lines(mode_raw: str, bundle_dir: Path, *, now: datetime) -> list[str]: """pytest report-header lines; empty in live mode so an unset E2E_FIXTURE_MODE keeps today's output byte-identical.""" + match_profile() mode = parse_fixture_mode(mode_raw) match mode: case InvalidFixtureMode() | "live": @@ -117,7 +120,7 @@ def fixture_report_lines(mode_raw: str, bundle_dir: Path, *, now: datetime) -> l case "record": return [f"e2e fixture mode: record -> {bundle_dir}"] case "replay": - freshness = check_freshness(bundle_dir, now=now) + freshness = check_freshness(bundle_dir, now=now, profile=match_profile()) match freshness: case FreshBundle(manifest=manifest): return [ diff --git a/tests/e2e/fixture_profile.py b/tests/e2e/fixture_profile.py new file mode 100644 index 00000000000..f8405be746b --- /dev/null +++ b/tests/e2e/fixture_profile.py @@ -0,0 +1,179 @@ +from __future__ import annotations + +import json +import os +from collections.abc import Mapping +from dataclasses import dataclass +from typing import Final, Literal +from urllib.parse import parse_qsl, urlsplit + +from pydantic import BaseModel, JsonValue, TypeAdapter + +type MatchProfile = Literal["legacy", "stateless_v1"] + + +@dataclass(frozen=True, slots=True) +class NumberToken: + literal: str + + +type ExactJson = dict[str, ExactJson] | list[ExactJson] | str | bool | NumberToken | None + +SEMANTIC_HEADERS: Final = frozenset({"content-type", "accept", "anthropic-version", "anthropic-beta", "openai-beta"}) +AUTH_HEADERS: Final = frozenset({"authorization", "x-api-key"}) +EXCLUDED_HEADERS: Final = frozenset( + { + "host", + "content-length", + "transfer-encoding", + "connection", + "accept-encoding", + "user-agent", + "traceparent", + "tracestate", + "x-request-id", + "x-client-request-id", + "cookie", + } +) +CREDENTIAL_QUERY: Final = frozenset( + { + "api_key", + "api-key", + "apikey", + "key", + "token", + "access_token", + "signature", + "password", + "secret", + "credentials", + "authorization", + "sig", + "client_secret", + "aws_access_key_id", + "aws_secret_access_key", + "aws_session_token", + } +) +JSON_VALUE: Final[TypeAdapter[ExactJson]] = TypeAdapter(ExactJson) + + +def match_profile() -> MatchProfile: + raw: Final = os.environ.get("E2E_REPLAY_MATCH_PROFILE", "legacy") + if raw in ("legacy", "stateless_v1"): + return raw + raise ValueError("E2E_REPLAY_MATCH_PROFILE must be legacy or stateless_v1") + + +class StrictIdentity(BaseModel): + upstream: str + mount: str + query: tuple[tuple[str, str], ...] + headers: dict[str, str] + auth: dict[str, str] + body_present: bool + body: JsonValue + + +@dataclass(frozen=True, slots=True) +class IneligibleRequest: + reason: str + + +def _unique_object(pairs: list[tuple[str, ExactJson]]) -> dict[str, ExactJson]: + if len({key for key, _ in pairs}) != len(pairs): + raise ValueError("duplicate JSON object keys") + return dict(pairs) + + +def _invalid_constant(value: str) -> ExactJson: + raise ValueError("nonfinite JSON number") + + +def _exact_value(value: ExactJson) -> JsonValue: + match value: + case dict(): + return {"object": {key: _exact_value(item) for key, item in value.items()}} + case list(): + return {"array": [_exact_value(item) for item in value]} + case bool(): + return {"boolean": value} + case NumberToken(literal=literal): + return {"number": literal} + case str(): + return {"string": value} + case None: + return None + + +def strict_identity( + *, + method: str, + path: str, + query: str, + headers: Mapping[str, str], + body: bytes | None, + mount: str, + upstream_base: str, +) -> StrictIdentity | IneligibleRequest: + if (mount, path, method.upper()) not in { + ("openai", "/openai/v1/chat/completions", "POST"), + ("anthropic", "/anthropic/v1/messages", "POST"), + }: + return IneligibleRequest("unsupported endpoint or method") + lowered: Final = {key.lower(): value for key, value in headers.items()} + if len(lowered) != len(headers): + return IneligibleRequest("duplicate header names") + if any( + key not in SEMANTIC_HEADERS | AUTH_HEADERS | EXCLUDED_HEADERS and not key.startswith("x-stainless-") + for key in lowered + ): + return IneligibleRequest("unsupported semantic header") + if "transfer-encoding" in lowered: + return IneligibleRequest("unsupported request transfer-encoding; send a content-length framed JSON body") + authorization: Final = lowered.get("authorization") + if authorization is not None and authorization.partition(" ")[0].lower() not in {"bearer", "basic", "digest"}: + return IneligibleRequest("unsupported authorization scheme") + destination: Final = urlsplit(upstream_base) + if destination.username or destination.password or destination.query or destination.fragment: + return IneligibleRequest("upstream destination contains credentials, query or fragment") + if destination.scheme not in ("http", "https") or not destination.netloc: + return IneligibleRequest("unsupported upstream destination") + if body and lowered.get("content-type", "").split(";", 1)[0].strip().lower() != "application/json": + return IneligibleRequest("unsupported body content-type; stateless_v1 requires JSON") + try: + parsed: Final = ( + JSON_VALUE.validate_python( + json.loads( + body, + object_pairs_hook=_unique_object, + parse_constant=_invalid_constant, + parse_float=NumberToken, + parse_int=NumberToken, + ) + ) + if body + else None + ) + except (ValueError, UnicodeError): + return IneligibleRequest("invalid JSON or duplicate JSON object keys") + if body and not isinstance(parsed, dict): + return IneligibleRequest("stateless inference requires a JSON object") + try: + query_pairs: Final = tuple(parse_qsl(query, keep_blank_values=True, errors="strict")) + except UnicodeError: + return IneligibleRequest("invalid UTF-8 query encoding") + return StrictIdentity( + upstream=upstream_base, + mount=mount, + query=tuple((key, "" if key.lower() in CREDENTIAL_QUERY else value) for key, value in query_pairs), + headers={key: value for key, value in lowered.items() if key in SEMANTIC_HEADERS}, + auth={ + key: (value.partition(" ")[0].lower() if key == "authorization" else "present") + for key, value in lowered.items() + if key in AUTH_HEADERS + }, + body_present=bool(body), + body=_exact_value(parsed), + ) diff --git a/tests/e2e/idp.py b/tests/e2e/idp.py index 6d2fc84eb27..2dc7c2ad71b 100644 --- a/tests/e2e/idp.py +++ b/tests/e2e/idp.py @@ -2,11 +2,18 @@ from __future__ import annotations +import base64 import os import secrets +import signal +import subprocess +import sys +import time import warnings from collections.abc import Callable -from dataclasses import dataclass, field +from contextlib import ExitStack +from dataclasses import dataclass, field, replace +from types import FrameType from typing import Final, Literal import pytest @@ -14,11 +21,15 @@ from e2e_http import ( AuthHeaders, ExternalWrite, NetworkError, + NoBody, Result, Success, + UnknownApiError, delete_external, + get_external, post_form_external, post_json_external, + unwrap, ) from pydantic import BaseModel, Field @@ -46,7 +57,9 @@ class TokenGrantForm(BaseModel): grant_type: Literal["password"] = "password" client_id: str username: str - password: str + password: str = Field(repr=False) + client_secret: str | None = Field(default=None, repr=False) + scope: str | None = None class TokenResponse(BaseModel): @@ -63,7 +76,7 @@ class GroupCreateBody(BaseModel): class PasswordCredential(BaseModel): type: Literal["password"] = "password" - value: str + value: str = Field(repr=False) temporary: bool = False @@ -101,8 +114,20 @@ class Identity: user_id: str username: str password: str = field(repr=False) - group: str - group_id: str + groups: tuple[str, ...] + group_ids: tuple[str, ...] + + @property + def group(self) -> str: + if len(self.groups) != 1: + raise ValueError("A single-group identity is required") + return self.groups[0] + + @property + def group_id(self) -> str: + if len(self.group_ids) != 1: + raise ValueError("A single-group identity is required") + return self.group_ids[0] @dataclass(frozen=True, slots=True) @@ -111,6 +136,10 @@ class Keycloak: realm: str admin_username: str admin_password: str = field(repr=False) + strict_cleanup: bool = False + + def with_strict_cleanup(self) -> Keycloak: + return replace(self, strict_cleanup=True) @property def issuer(self) -> str: @@ -150,7 +179,9 @@ class Keycloak: f"group {name}", ) - def create_user(self, *, username: str, email: str, password: str, group: str) -> str: + def create_user( + self, *, username: str, email: str, password: str, group: str | None = None, groups: tuple[str, ...] = () + ) -> str: return created_id( post_json_external( self._admin_url("/users"), @@ -158,7 +189,7 @@ class Keycloak: json=UserCreateBody( username=username, email=email, - groups=(group,), + groups=(group,) if group is not None else groups, credentials=(PasswordCredential(value=password),), ), ), @@ -171,14 +202,28 @@ class Keycloak: def delete_group(self, group_id: str) -> None: self._delete(f"/groups/{group_id}") + def assert_absent(self, kind: Literal["users", "groups", "clients"], resource_id: str) -> None: + result: Final = get_external( + self._admin_url(f"/{kind}/{resource_id}"), + headers=self._admin_headers(), + response_type=NoBody, + ) + assert isinstance(result, UnknownApiError) and result.status_code == 404, ( + f"Owned IdP {kind} still exists: {result}" + ) + def _delete(self, path: str) -> None: try: headers: Final = self._admin_headers() except pytest.fail.Exception as exc: + if self.strict_cleanup: + raise RuntimeError(f"Keycloak cleanup could not authenticate for {path}") from exc warnings.warn(f"Keycloak cleanup could not authenticate for {path}: {exc}", RuntimeWarning, stacklevel=2) return result: Final = delete_external(self._admin_url(path), headers=headers) if result.status_code not in (204, 404): + if self.strict_cleanup: + raise RuntimeError(f"Keycloak cleanup failed for {path}: HTTP {result.status_code}") warnings.warn( f"Keycloak cleanup failed for {path}: HTTP {result.status_code} {result.body[:300]}", RuntimeWarning, @@ -188,15 +233,34 @@ class Keycloak: def provision(self, *, marker: str, group: str, defer: Callable[[Callable[[], object]], None]) -> Identity: """Create `group` and a user in it, credentialed with a password generated for this test alone, and hand back the identity a token can be minted for.""" - group_id: Final = self.create_group(group) - defer(lambda: self.delete_group(group_id)) + return self.provision_groups(marker=marker, groups=(group,), defer=defer) + + def provision_groups( + self, *, marker: str, groups: tuple[str, ...], defer: Callable[[Callable[[], object]], None] + ) -> Identity: + def provision_group(name: str) -> str: + created: Final = self.create_group(name) + defer(lambda: self.delete_group(created)) + return created + + group_ids: Final = tuple(provision_group(group) for group in groups) + return self.provision_user(marker=marker, groups=groups, group_ids=group_ids, defer=defer) + + def provision_user( + self, + *, + marker: str, + groups: tuple[str, ...], + group_ids: tuple[str, ...], + defer: Callable[[Callable[[], object]], None], + ) -> Identity: username: Final = f"e2e-jwt-user-{marker}" password: Final = secrets.token_urlsafe(24) user_id: Final = self.create_user( - username=username, email=f"{username}@example.com", password=password, group=group + username=username, email=f"{username}@example.com", password=password, groups=groups ) defer(lambda: self.delete_user(user_id)) - return Identity(user_id=user_id, username=username, password=password, group=group, group_id=group_id) + return Identity(user_id=user_id, username=username, password=password, groups=groups, group_ids=group_ids) def access_token( self, identity: Identity, *, client_id: str = TESTS_CLIENT_ID, issuer_host: str | None = None @@ -211,6 +275,65 @@ class Keycloak: ) return self._token(result, f"a token for {identity.username}") + def discovery(self) -> Discovery: + return unwrap(get_external(f"{self.issuer}/.well-known/openid-configuration", response_type=Discovery)) + + def browser_client(self, *, callback_url: str, defer: Callable[[Callable[[], object]], None]) -> BrowserClient: + client: Final = BrowserClient( + client_id=f"e2e-browser-{secrets.token_hex(8)}", + secret=secrets.token_urlsafe(32), + callback_url=callback_url, + ) + resource_id: Final = created_id( + post_json_external( + self._admin_url("/clients"), + headers=self._admin_headers(), + json=BrowserClientBody( + clientId=client.client_id, + secret=client.secret, + redirectUris=(callback_url,), + ), + ), + "browser client", + ) + defer(lambda: self._delete(f"/clients/{resource_id}")) + configured: Final = unwrap( + get_external( + self._admin_url(f"/clients/{resource_id}"), + headers=self._admin_headers(), + response_type=BrowserClientBody, + ) + ) + assert configured.redirect_uris == (callback_url,) + assert configured.standard_flow_enabled and not configured.public_client + assert configured.attributes.pkce == "S256" + return client + + def browser_token(self, identity: Identity, client: BrowserClient) -> str: + return self._token( + post_form_external( + self.token_url(self.realm), + form=TokenGrantForm( + client_id=client.client_id, + client_secret=client.secret, + username=identity.username, + password=identity.password, + scope="openid email", + ), + response_type=TokenResponse, + ), + "browser-profile identity mapping", + ) + + def userinfo(self, token: str) -> UserInfo: + return unwrap( + get_external( + f"{self.issuer}/protocol/openid-connect/userinfo", + headers=AuthHeaders(authorization=f"Bearer {token}"), + response_type=UserInfo, + ) + ) + def keycloak_from_env() -> Keycloak: admin_username: Final = os.environ.get(KEYCLOAK_ADMIN_USER_ENV, "").strip() @@ -226,3 +349,137 @@ def keycloak_from_env() -> Keycloak: admin_username=admin_username, admin_password=admin_password, ) + + +class TokenClaims(BaseModel): + sub: str + iss: str + aud: str | tuple[str, ...] + exp: int + scope: str = "" + groups: tuple[str, ...] = () + + +class Discovery(BaseModel): + issuer: str + authorization_endpoint: str + token_endpoint: str + userinfo_endpoint: str + jwks_uri: str + + +class UserInfo(BaseModel): + sub: str + email: str + + +class BrowserAttributes(BaseModel): + pkce: str = Field(default="S256", alias="pkce.code.challenge.method") + + +class AudienceConfig(BaseModel): + audience: str = Field(default="litellm-e2e", alias="included.custom.audience") + access_token: str = Field(default="true", alias="access.token.claim") + id_token: str = Field(default="false", alias="id.token.claim") + + +class AudienceMapper(BaseModel): + name: str = "litellm-audience" + protocol: str = "openid-connect" + mapper: str = Field(default="oidc-audience-mapper", alias="protocolMapper") + config: AudienceConfig = Field(default_factory=AudienceConfig) + + +class BrowserClientBody(BaseModel): + client_id: str = Field(alias="clientId") + secret: str = Field(repr=False) + redirect_uris: tuple[str, ...] = Field(alias="redirectUris") + enabled: bool = True + public_client: bool = Field(default=False, alias="publicClient") + standard_flow_enabled: bool = Field(default=True, alias="standardFlowEnabled") + direct_access_grants_enabled: bool = Field(default=True, alias="directAccessGrantsEnabled") + default_client_scopes: tuple[str, ...] = Field(default=("email", "basic"), alias="defaultClientScopes") + attributes: BrowserAttributes = Field(default_factory=BrowserAttributes) + protocol_mappers: tuple[AudienceMapper, ...] = Field(default=(AudienceMapper(),), alias="protocolMappers") + + +@dataclass(frozen=True, slots=True) +class BrowserClient: + client_id: str + secret: str = field(repr=False) + callback_url: str + + def environment(self, discovery: Discovery) -> dict[str, str]: + return { + "GENERIC_CLIENT_ID": self.client_id, + "GENERIC_CLIENT_SECRET": self.secret, + "GENERIC_USER_ID_ATTRIBUTE": "sub", + "GENERIC_AUTHORIZATION_ENDPOINT": discovery.authorization_endpoint, + "GENERIC_TOKEN_ENDPOINT": discovery.token_endpoint, + "GENERIC_USERINFO_ENDPOINT": discovery.userinfo_endpoint, + "GENERIC_CLIENT_USE_PKCE": "true", + "GENERIC_SCOPE": "openid email", + } + + +def token_claims(token: str) -> TokenClaims: + payload: Final = token.split(".")[1] + return TokenClaims.model_validate_json(base64.urlsafe_b64decode(payload + "=" * (-len(payload) % 4))) + + +def _signal_process_group(process_id: int, signum: int) -> bool: + try: + os.killpg(process_id, signum) + except ProcessLookupError: + return False + return True + + +def _stop_process_group(child: subprocess.Popen[bytes]) -> None: + _signal_process_group(child.pid, signal.SIGTERM) + deadline: Final = time.monotonic() + 5 + while _process_group_exists(child.pid): + child.poll() + if time.monotonic() >= deadline: + _signal_process_group(child.pid, signal.SIGKILL) + break + time.sleep(0.05) + child.wait() + + +def _process_group_exists(process_id: int) -> bool: + try: + os.killpg(process_id, 0) + except ProcessLookupError: + return False + except PermissionError: + return True + return True + + +def run_oidc_profile(proxy_url: str, command: list[str]) -> int: + idp: Final = keycloak_from_env().with_strict_cleanup() + with ExitStack() as cleanup: + + def terminate(signum: int, frame: FrameType | None) -> None: + raise SystemExit(128 + signum) + + previous: Final = signal.signal(signal.SIGTERM, terminate) + cleanup.callback(signal.signal, signal.SIGTERM, previous) + + def defer(callback: Callable[[], object]) -> None: + cleanup.callback(callback) + + client: Final = idp.browser_client(callback_url=f"{proxy_url.rstrip('/')}/sso/callback", defer=defer) + environment: Final = {**os.environ, **client.environment(idp.discovery()), "PROXY_BASE_URL": proxy_url} + with subprocess.Popen(command, env=environment, start_new_session=True) as child: + try: + return child.wait() + finally: + _stop_process_group(child) + + +if __name__ == "__main__": + if len(sys.argv) < 3: + raise SystemExit("Usage: idp.py PROXY_URL COMMAND [ARG ...]; requires a running test IdP") + raise SystemExit(run_oidc_profile(sys.argv[1], sys.argv[2:])) diff --git a/tests/e2e/junit_properties.py b/tests/e2e/junit_properties.py index c5971c5362c..b9f5da871ae 100644 --- a/tests/e2e/junit_properties.py +++ b/tests/e2e/junit_properties.py @@ -19,6 +19,7 @@ from __future__ import annotations from collections.abc import Iterable import pytest +from coverage_registry.management_cases import case_properties # Hardcoded because the runner image copies tests/e2e/ to /app/e2e, so nothing # at runtime names this suite's place in the repo. test_junit_properties.py @@ -94,7 +95,7 @@ def result_properties(item: pytest.Item) -> tuple[tuple[str, str], ...]: ("package", package_from_nodeid(item.nodeid)), ("covers", ",".join(covers_from_item(item))), ("source", source_from_item(item)), - ) + ) + case_properties(item.nodeid) def attach_result_properties(item: pytest.Item) -> None: diff --git a/tests/e2e/llm_translation/test_chat_stream_contract_e2e.py b/tests/e2e/llm_translation/test_chat_stream_contract_e2e.py index 4db2fe004c5..fdb76df703d 100644 --- a/tests/e2e/llm_translation/test_chat_stream_contract_e2e.py +++ b/tests/e2e/llm_translation/test_chat_stream_contract_e2e.py @@ -1,51 +1,90 @@ -"""Vendor §12.3: chat completions streaming SSE contract (LIT-4778). - -Asserts a streamed /chat/completions response is SSE, carries content chunks, -and terminates with the OpenAI [DONE] sentinel. -""" - from __future__ import annotations +from typing import Final + import pytest -from e2e_config import unique_marker +from e2e_config import provider_edge_base, unique_marker from e2e_http import require_successful_call from lifecycle import ResourceManager -from models import ChatBody, ChatMessage, LiteLLMParamsBody +from models import ChatBody, ChatMessage, ChatStreamOptions, LiteLLMParamsBody, Usage from proxy_client import ProxyClient +from pydantic import BaseModel -pytestmark = pytest.mark.e2e +pytestmark = [pytest.mark.e2e, pytest.mark.replayable] + + +class _Delta(BaseModel): + content: str | None = None + + +class _Choice(BaseModel): + index: int + delta: _Delta + finish_reason: str | None = None + + +class _Chunk(BaseModel): + choices: tuple[_Choice, ...] + usage: Usage | None = None class TestChatStreamContract: @pytest.mark.covers("llm.chat_completions.openai.basic.stream.works") def test_chat_stream_is_sse_and_ends_with_done(self, proxy: ProxyClient, resources: ResourceManager) -> None: - model = f"e2e-chat-stream-{unique_marker()}" - model_id = proxy.create_model( + model: Final = f"e2e-chat-stream-{unique_marker()}" + base: Final = provider_edge_base("openai") + model_id: Final = proxy.create_model( model, - LiteLLMParamsBody(model="openai/gpt-4o-mini", api_key="os.environ/OPENAI_API_KEY"), + LiteLLMParamsBody( + model="openai/gpt-5.6", + api_key="os.environ/OPENAI_API_KEY", + api_base=f"{base}/v1" if base else None, + ), ) resources.defer(lambda: proxy.delete_model(model_id)) - key = resources.key() - - result = proxy.chat_stream( + key: Final = resources.key() + expected: Final = "The amber kite crosses the quiet lake." + result: Final = proxy.chat_stream( key, ChatBody( model=model, messages=[ ChatMessage( - role="user", - content=f"Reply with the single word ok. {unique_marker()}", + role="user", content=f"Repeat exactly this sentence, with no additional text: {expected}" ) ], stream=True, - max_completion_tokens=32, - temperature=0.0, + stream_options=ChatStreamOptions(include_usage=True), + max_completion_tokens=256, + reasoning_effort="none", ), ) require_successful_call(result) assert result.is_streaming, f"expected SSE content-type, got {result.content_type!r}" assert result.stream_events, "stream returned no data events" - assert result.stream_done, ( - f"stream must terminate with [DONE]; " - f"chunks={result.chunks} done={result.stream_done} events={len(result.stream_events)}" + assert not result.stream_error, f"stream errored: {result.stream_error}" + assert result.stream_done, "stream must terminate with [DONE]" + assert result.stream_done_positions == (len(result.stream_events),), "[DONE] must occur once after all events" + chunks: Final = tuple(_Chunk.model_validate_json(event) for event in result.stream_events) + text_positions: Final = tuple( + i for i, chunk in enumerate(chunks) if any(c.delta.content for c in chunk.choices) ) + terminal_positions: Final = tuple( + i for i, chunk in enumerate(chunks) if any(c.finish_reason is not None for c in chunk.choices) + ) + assert text_positions, "stream completed without meaningful text" + assert len(terminal_positions) == 1, "expected exactly one terminal choice" + assert text_positions[0] < terminal_positions[0], "meaningful text must arrive before termination" + assert text_positions[-1] <= terminal_positions[0], "text arrived after termination" + assert all(c.index == 0 for chunk in chunks for c in chunk.choices) + assert tuple(c.finish_reason for c in chunks[terminal_positions[0]].choices) == ("stop",) + text: Final = "".join(c.delta.content or "" for chunk in chunks for c in chunk.choices) + assert text.strip() == expected, f"streamed answer was altered or incomplete: {text!r}" + usage_positions: Final = tuple(i for i, chunk in enumerate(chunks) if chunk.usage is not None) + assert usage_positions == (len(chunks) - 1,), "expected one final usage chunk" + assert terminal_positions[0] < usage_positions[0], "usage must follow the terminal choice" + usage: Final = chunks[-1].usage + assert usage is not None + assert usage.prompt_tokens is not None and usage.prompt_tokens > 0 + assert usage.completion_tokens is not None and usage.completion_tokens > 0 + assert usage.total_tokens == usage.prompt_tokens + usage.completion_tokens diff --git a/tests/e2e/llm_translation/test_messages_e2e.py b/tests/e2e/llm_translation/test_messages_e2e.py index c731b52acd8..ca58c30d40c 100644 --- a/tests/e2e/llm_translation/test_messages_e2e.py +++ b/tests/e2e/llm_translation/test_messages_e2e.py @@ -21,7 +21,12 @@ from e2e_http import assert_client_error, require_successful_call, unwrap from endpoints_client import EndpointsClient, MessagesResult from lifecycle import ResourceManager from models import ( + AnthropicAssistantTurn, + AnthropicContentBlock, AnthropicCustomTool, + AnthropicToolChoice, + AnthropicToolResultBlock, + AnthropicToolResultTurn, AnthropicMessagesBody, ChatMessage, JsonSchemaProperty, @@ -29,7 +34,7 @@ from models import ( SpendLogRow, ToolInputSchema, ) -from pydantic import BaseModel +from pydantic import BaseModel, ConfigDict pytestmark = [pytest.mark.e2e, pytest.mark.replayable] @@ -284,8 +289,139 @@ class TestAnthropicMessages: result = endpoints_client.proxy.transport.send( "/v1/messages", headers=endpoints_client.proxy.transport.bearer(key), - json=_OptionalMessagesBody( - messages=[ChatMessage(role="user", content="hi")], max_tokens=50 - ), + json=_OptionalMessagesBody(messages=[ChatMessage(role="user", content="hi")], max_tokens=50), ) assert_client_error(result, "messages missing model") + + +class _BridgeDelta(BaseModel): + type: str | None = None + partial_json: str | None = None + stop_reason: str | None = None + + +class _BridgeEvent(BaseModel): + type: str + index: int | None = None + content_block: AnthropicContentBlock | None = None + delta: _BridgeDelta | None = None + + +class _ParcelInput(BaseModel): + model_config = ConfigDict(extra="forbid", strict=True) + parcel: str + shelf: int + + +def _tool_from_stream(events: tuple[_BridgeEvent, ...]) -> AnthropicContentBlock: + starts: Final = tuple( + event + for event in events + if event.type == "content_block_start" + and event.content_block is not None + and event.content_block.type == "tool_use" + ) + assert len(starts) == 1, "expected exactly one tool call" + start: Final = starts[0] + block: Final = start.content_block + assert block is not None and block.id and start.index is not None + fragments: Final = tuple( + event + for event in events + if event.type == "content_block_delta" and event.delta is not None and event.delta.type == "input_json_delta" + ) + assert fragments, "tool stream contained no argument fragments" + assert all(event.index == start.index for event in fragments), "tool fragments changed index" + positions: Final = tuple(i for i, event in enumerate(events) if event in fragments) + stops: Final = tuple( + i for i, event in enumerate(events) if event.type == "content_block_stop" and event.index == start.index + ) + assert len(stops) == 1 and events.index(start) < positions[0] <= positions[-1] < stops[0] + assert tuple( + event.delta.stop_reason for event in events if event.type == "message_delta" and event.delta is not None + ) == ("tool_use",) + terminal_positions: Final = tuple(i for i, event in enumerate(events) if event.type == "message_delta") + assert len(terminal_positions) == 1 and stops[0] < terminal_positions[0] < len(events) - 1 + assert tuple(i for i, event in enumerate(events) if event.type == "message_stop") == (len(events) - 1,), ( + "tool stream did not terminate exactly once" + ) + arguments: Final = _ParcelInput.model_validate_json( + "".join(event.delta.partial_json or "" for event in fragments if event.delta is not None) + ) + return AnthropicContentBlock(type="tool_use", id=block.id, name=block.name, input=arguments.model_dump()) + + +def _parcel_result(tool: AnthropicContentBlock, result: AnthropicToolResultBlock) -> AnthropicToolResultTurn: + assert tool.id and result.tool_use_id == tool.id, "tool result ID does not match the emitted call" + return AnthropicToolResultTurn(content=[result]) + + +def _request_tool( + client: EndpointsClient, key: str, request: AnthropicMessagesBody, stream: bool +) -> AnthropicContentBlock: + if stream: + response: Final = client.proxy.messages_stream(key, request) + require_successful_call(response) + assert response.is_streaming and not response.stream_error + return _tool_from_stream(tuple(_BridgeEvent.model_validate_json(event) for event in response.stream_events)) + response_body: Final = unwrap(client.proxy.messages(key, request)) + blocks: Final = tuple(block for block in response_body.content or () if block.type == "tool_use") + assert len(blocks) == 1 + return blocks[0] + + +class TestOpenAIMessagesToolContinuation: + @pytest.mark.parametrize("stream", [True, False], ids=["stream", "nonstream"]) + def test_required_tool_arguments_and_correlated_result( + self, endpoints_client: EndpointsClient, resources: ResourceManager, stream: bool + ) -> None: + model: Final = f"e2e-bridge-tool-{unique_marker()}" + base: Final = provider_edge_base("openai") + model_id: Final = endpoints_client.create_model( + model, + LiteLLMParamsBody( + model="openai/gpt-5.6", api_key="os.environ/OPENAI_API_KEY", api_base=f"{base}/v1" if base else None + ), + ) + resources.defer(lambda: endpoints_client.delete_model(model_id)) + key: Final = resources.key(models=[model]) + tool: Final = AnthropicCustomTool( + name="locate_parcel", + description="Look up the receipt for a parcel on a shelf. Return the receipt verbatim.", + input_schema=ToolInputSchema( + properties={"parcel": JsonSchemaProperty(type="string"), "shelf": JsonSchemaProperty(type="integer")}, + required=["parcel", "shelf"], + ), + ) + question: Final = ChatMessage( + role="user", + content="Call locate_parcel with parcel exactly amber-kite and shelf exactly 7. After the tool result, reply with only the receipt returned by the tool.", + ) + request: Final = AnthropicMessagesBody( + model=model, + max_tokens=2048, + messages=[question], + tools=[tool], + tool_choice=AnthropicToolChoice(type="tool", name=tool.name), + stream=stream, + ) + emitted: Final = _request_tool(endpoints_client, key, request, stream) + assert emitted.id and emitted.name == "locate_parcel" + assert emitted.input == {"parcel": "amber-kite", "shelf": 7}, "required tool arguments were lost or changed" + receipt: Final = f"receipt-{unique_marker()}" + result_turn: Final = _parcel_result(emitted, AnthropicToolResultBlock(tool_use_id=emitted.id, content=receipt)) + continuation: Final = unwrap( + endpoints_client.proxy.messages( + key, + AnthropicMessagesBody( + model=model, + max_tokens=2048, + tools=[tool], + tool_choice=AnthropicToolChoice(type="none"), + messages=[question, AnthropicAssistantTurn(content=[emitted]), result_turn], + ), + ) + ) + answer: Final = "".join(block.text or "" for block in continuation.content or ()) + assert answer.strip() == receipt, "continuation did not consume the correlated tool result" + assert all(block.type != "tool_use" for block in continuation.content or ()) diff --git a/tests/e2e/management/conftest.py b/tests/e2e/management/conftest.py index bd69c8c0ff3..5a11b634085 100644 --- a/tests/e2e/management/conftest.py +++ b/tests/e2e/management/conftest.py @@ -5,8 +5,14 @@ holds the shared ProxyClient so `resources` / `scoped_key` clean up keys, teams, users, and orgs this suite creates. """ -import pytest +from collections.abc import Generator +from typing import Final +import pytest +from e2e_http import without_retries +from idp import Keycloak +from lifecycle import ResourceManager +from management.jwt_actors import ActorFactory from management_client import ManagementClient, build_client from proxy_client import ProxyClient @@ -21,3 +27,14 @@ def pytest_configure(config: pytest.Config) -> None: @pytest.fixture(scope="session") def client(proxy: ProxyClient) -> ManagementClient: return build_client(proxy) + + +@pytest.fixture +def actor_factory(proxy: ProxyClient, idp: Keycloak) -> Generator[ActorFactory]: + bootstrap: Final = build_client(proxy) + resources: Final = ResourceManager(client=proxy, strict_cleanup=True) + with without_retries(): + try: + yield ActorFactory(bootstrap=bootstrap, idp=idp, resources=resources) + finally: + resources.teardown() diff --git a/tests/e2e/management/jwt_actors.py b/tests/e2e/management/jwt_actors.py new file mode 100644 index 00000000000..2d23549fe71 --- /dev/null +++ b/tests/e2e/management/jwt_actors.py @@ -0,0 +1,175 @@ +from __future__ import annotations + +from dataclasses import dataclass +from typing import Final, Literal + +from e2e_config import unique_marker +from e2e_http import NoBody, unwrap +from idp import ADMIN_CLIENT_ID, TESTS_CLIENT_ID, Identity, Keycloak +from lifecycle import ResourceManager +from management.management_client import ManagementClient +from models import ( + KeyGenerateBody, + KeyGenerateResponse, + OrgDeleteBody, + OrgDeleteResponse, + OrgMemberAddBody, + OrgMemberEntry, + OrgNewBody, + TeamDeleteBody, + TeamMemberAddBody, + TeamMemberEntry, + TeamNewBody, + UserNewBody, + UserRole, +) +from proxy_client import Caller + +ActorRole = Literal[ + "proxy_admin", + "proxy_admin_viewer", + "organization_admin", + "team_admin", + "team_member", + "internal_user", + "internal_user_viewer", + "unrelated_user", +] +ActorProfile = Literal["database_role", "group_scoped"] + + +@dataclass(frozen=True, slots=True) +class Tenant: + organization_id: str + team_id: str + group_id: str + + +@dataclass(frozen=True, slots=True) +class Actor: + identity: Identity + role: ActorRole + global_role: UserRole + profile: ActorProfile + tenants: tuple[Tenant, ...] + + def mint_caller(self, idp: Keycloak) -> Caller: + return Caller( + credential=idp.access_token( + self.identity, client_id=ADMIN_CLIENT_ID if self.role == "proxy_admin" else TESTS_CLIENT_ID + ), + kind="direct_jwt", + role=self.role, + tenant=self.tenants[0].organization_id if self.tenants else None, + ) + + +@dataclass(frozen=True, slots=True) +class ActorFactory: + bootstrap: ManagementClient + idp: Keycloak + resources: ResourceManager + + def __post_init__(self) -> None: + if self.bootstrap.proxy.caller is not None: + raise ValueError("Actor bootstrap requires a separately held master client") + + def key(self, tenant: Tenant | None = None, *, user_id: str | None = None) -> KeyGenerateResponse: + created: Final = unwrap( + self.bootstrap.generate_key( + KeyGenerateBody( + team_id=tenant.team_id if tenant is not None else None, + user_id=user_id, + key_alias=f"e2e-actor-key-{unique_marker()}", + ) + ) + ) + self.resources.defer(lambda: self.bootstrap.delete_key_strict(created.key, missing_ok=True)) + return created + + def tenant(self) -> Tenant: + marker: Final = unique_marker() + organization_id: Final = self.bootstrap.create_org(OrgNewBody(organization_alias=f"e2e-organization-{marker}")) + self.resources.defer( + lambda: unwrap( + self.bootstrap.proxy.transport.delete( + "/organization/delete", + headers=self.bootstrap.proxy.management_headers(), + json=OrgDeleteBody(organization_ids=[organization_id]), + response_type=OrgDeleteResponse, + ) + ) + ) + team_id: Final = self.bootstrap.proxy.create_team( + TeamNewBody(team_alias=f"e2e-team-{marker}", organization_id=organization_id) + ) + self.resources.defer( + lambda: unwrap( + self.bootstrap.proxy.transport.post( + "/team/delete", + headers=self.bootstrap.proxy.management_headers(), + json=TeamDeleteBody(team_ids=[team_id]), + response_type=NoBody, + ) + ) + ) + self.bootstrap.delete_team_member(team_id, self.bootstrap.user_info().user_id) + group_id: Final = self.idp.create_group(team_id) + self.resources.defer(lambda: self.idp.with_strict_cleanup().delete_group(group_id)) + return Tenant(organization_id=organization_id, team_id=team_id, group_id=group_id) + + def create( + self, role: ActorRole, *, tenants: tuple[Tenant, ...] = (), profile: ActorProfile = "database_role" + ) -> Actor: + if role in ("team_admin", "team_member", "organization_admin") and not tenants: + raise ValueError("A membership actor requires a tenant") + identity: Final = self.idp.with_strict_cleanup().provision_user( + marker=unique_marker(), + groups=tuple(tenant.team_id for tenant in tenants) if profile == "group_scoped" else (), + group_ids=tuple(tenant.group_id for tenant in tenants) if profile == "group_scoped" else (), + defer=self.resources.defer, + ) + global_role: Final[UserRole] = ( + role + if role in ("proxy_admin", "proxy_admin_viewer", "internal_user", "internal_user_viewer") + else "internal_user" + ) + self.bootstrap.create_user( + UserNewBody( + user_id=identity.user_id, + user_email=f"{identity.username}@example.com", + user_role=global_role, + auto_create_key=False, + ) + ) + self.resources.defer(lambda: self.bootstrap.delete_user_strict(identity.user_id)) + for tenant in tenants: + unwrap( + self.bootstrap.proxy.transport.post( + "/organization/member_add", + headers=self.bootstrap.proxy.management_headers(), + json=OrgMemberAddBody( + organization_id=tenant.organization_id, + member=OrgMemberEntry( + user_id=identity.user_id, + role="org_admin" if role == "organization_admin" else "internal_user", + ), + ), + response_type=NoBody, + ) + ) + unwrap( + self.bootstrap.proxy.transport.post( + "/team/member_add", + headers=self.bootstrap.proxy.management_headers(), + json=TeamMemberAddBody( + team_id=tenant.team_id, + member=TeamMemberEntry( + user_id=identity.user_id, + role="admin" if role == "team_admin" else "user", + ), + ), + response_type=NoBody, + ) + ) + return Actor(identity=identity, role=role, global_role=global_role, profile=profile, tenants=tenants) diff --git a/tests/e2e/management/management_client.py b/tests/e2e/management/management_client.py index e17b92a13ed..8470d318db8 100644 --- a/tests/e2e/management/management_client.py +++ b/tests/e2e/management/management_client.py @@ -7,7 +7,8 @@ llm-only key hitting a management route). from __future__ import annotations import time -from dataclasses import dataclass +import warnings +from dataclasses import dataclass, field, replace import jwt from e2e_config import MASTER_KEY @@ -20,6 +21,7 @@ from e2e_http import ( StreamingResponse, Success, UnknownApiError, + retry_attempts, unwrap, ) from models import ( @@ -81,7 +83,7 @@ from models import ( UserNewResponse, UserUpdateBody, ) -from proxy_client import ProxyClient +from proxy_client import Caller, ProxyClient MODEL_ACCESS_DENIED_MARKER = "key_model_access_denied" ROUTE_NOT_ALLOWED_MARKER = "not allowed to call this route" @@ -98,7 +100,7 @@ class DashboardSession: its bearer on every subsequent call, the claims it renders the signed-in user from, and where it lands the browser.""" - session_key: str + session_key: str = field(repr=False) claims: UiSessionClaims redirect_url: str @@ -106,7 +108,10 @@ class DashboardSession: @dataclass(frozen=True, slots=True) class ManagementClient: proxy: ProxyClient - master_key: str + master_key: str = field(repr=False) + + def with_caller(self, caller: Caller) -> ManagementClient: + return replace(self, proxy=self.proxy.with_caller(caller)) def llm_only_key(self) -> str: return self.proxy.generate_key(KeyGenerateBody(models=[], allowed_routes=["llm_api_routes"])) @@ -117,7 +122,7 @@ class ManagementClient: dashboard creates it under the session key their sign-in minted). Returns the outcome rather than unwrapping it, so a caller can poll a route that is only transiently refusing.""" - headers = self.proxy.transport.master if caller_key is None else self.proxy.transport.bearer(caller_key) + headers = self.proxy.management_headers(caller_key) return self.proxy.transport.post( "/key/generate", headers=headers, @@ -131,9 +136,9 @@ class ManagementClient: sign-in minted, never the master key). Returns the outcome rather than unwrapping it, so a caller can poll a route that is only transiently refusing; `update_key_models` is the unwrapping shorthand.""" - headers = self.proxy.transport.master if caller_key is None else self.proxy.transport.bearer(caller_key) + headers = self.proxy.management_headers(caller_key) last: Result[NoBody] = NetworkError(message="/key/update was never attempted") - for attempt in range(_KEY_WRITE_ATTEMPTS): + for attempt in range(retry_attempts(_KEY_WRITE_ATTEMPTS)): last = self.proxy.transport.post( "/key/update", headers=headers, @@ -144,6 +149,7 @@ class ManagementClient: case UnknownApiError(body=error_body) if any( marker in error_body.lower() for marker in _TRANSIENT_BACKEND_MARKERS ): + warnings.warn(f"Transient backend response on attempt {attempt + 1}", RuntimeWarning, stacklevel=2) time.sleep(0.5 * (attempt + 1)) continue case _: @@ -153,25 +159,26 @@ class ManagementClient: def update_key_models(self, key: str, models: list[str]) -> None: _ = unwrap(self.update_key(KeyUpdateBody(key=key, models=models))) - def key_info_as(self, key: str, *, caller_key: str) -> Result[KeyInfoResponse]: + def key_info_as(self, key: str, *, caller_key: str | None = None) -> Result[KeyInfoResponse]: return self.proxy.transport.get( "/key/info", - headers=self.proxy.transport.bearer(caller_key), + headers=self.proxy.management_headers(caller_key), params=KeyInfoParams(key=key), response_type=KeyInfoResponse, ) - def delete_key_strict(self, key: str, *, caller_key: str | None = None) -> None: + def delete_key_strict(self, key: str, *, caller_key: str | None = None, missing_ok: bool = False) -> None: """Strict delete for the act phase of a test: a failed delete is a hard failure, unlike the warn-only ProxyClient.delete_key used at teardown.""" - _ = unwrap( - self.proxy.transport.post( - "/key/delete", - headers=self.proxy.transport.master if caller_key is None else self.proxy.transport.bearer(caller_key), - json=KeyDeleteBody(keys=[key]), - response_type=NoBody, - ) + result = self.proxy.transport.post( + "/key/delete", + headers=self.proxy.management_headers(caller_key), + json=KeyDeleteBody(keys=[key]), + response_type=NoBody, ) + if missing_ok and isinstance(result, UnknownApiError) and result.status_code == 404: + return + _ = unwrap(result) def delete_model_strict(self, model_id: str) -> None: """Strict delete for the act phase of a test: a failed delete is a hard @@ -179,7 +186,7 @@ class ManagementClient: _ = unwrap( self.proxy.transport.post( "/model/delete", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=ModelDeleteBody(id=model_id), response_type=NoBody, ) @@ -190,7 +197,7 @@ class ManagementClient: Connection button, probing the live provider with the supplied params.""" return self.proxy.transport.post( "/health/test_connection", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=body, response_type=ConnectionTestResponse, timeout=120.0, @@ -200,7 +207,7 @@ class ManagementClient: _ = unwrap( self.proxy.transport.post( "/key/block", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=KeyBlockBody(key=key), response_type=NoBody, ) @@ -209,7 +216,7 @@ class ManagementClient: return unwrap( self.proxy.transport.post( "/key/regenerate", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=KeyRegenerateBody(key=key, grace_period=grace_period), response_type=KeyGenerateResponse, ) @@ -219,7 +226,7 @@ class ManagementClient: return unwrap( self.proxy.transport.post( f"/key/{key}/reset_spend", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=KeyResetSpendBody(reset_to=reset_to), response_type=KeyResetSpendResponse, ) @@ -228,7 +235,7 @@ class ManagementClient: def key_list(self, key_alias: str, *, caller_key: str | None = None) -> Result[KeyListResponse]: """GET /key/list, the Virtual Keys page's own inventory call. `caller_key` is who is asking: the master key by default, or a virtual key.""" - headers = self.proxy.transport.master if caller_key is None else self.proxy.transport.bearer(caller_key) + headers = self.proxy.management_headers(caller_key) return self.proxy.transport.get( "/key/list", headers=headers, @@ -266,7 +273,7 @@ class ManagementClient: team_id = unwrap( self.proxy.transport.post( "/team/new", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=body, response_type=TeamNewResponse, ) @@ -276,10 +283,10 @@ class ManagementClient: def update_team(self, body: TeamUpdateBody) -> None: last: Result[NoBody] | None = None - for attempt in range(5): + for attempt in range(retry_attempts(5)): last = self.proxy.transport.post( "/team/update", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=body, response_type=NoBody, ) @@ -289,6 +296,7 @@ class ManagementClient: case UnknownApiError(body=body_text) if ( "connecting to redis" in body_text.lower() or "name resolution" in body_text.lower() ): + warnings.warn(f"Transient backend response on attempt {attempt + 1}", RuntimeWarning, stacklevel=2) time.sleep(0.5 * (attempt + 1)) continue case _: @@ -299,7 +307,7 @@ class ManagementClient: def delete_team(self, team_id: str) -> None: _ = self.proxy.transport.post( "/team/delete", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=TeamDeleteBody(team_ids=[team_id]), response_type=NoBody, ) @@ -308,7 +316,7 @@ class ManagementClient: return unwrap( self.proxy.transport.get( "/team/info", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), params=TeamInfoParams(team_id=team_id), response_type=TeamInfoResponse, ) @@ -320,7 +328,7 @@ class ManagementClient: for entry in unwrap( self.proxy.transport.get( "/team/list", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), params=NoBody(), response_type=TeamListResponse, ) @@ -328,14 +336,16 @@ class ManagementClient: ) def team_info_status(self, team_id: str) -> ProbeResult: - return self.proxy.transport.probe("/team/info", params=TeamInfoParams(team_id=team_id)) + return self.proxy.transport.probe( + "/team/info", params=TeamInfoParams(team_id=team_id), headers=self.proxy.management_headers() + ) def _wait_for_team(self, team_id: str) -> None: last: Result[TeamInfoResponse] | None = None - for _ in range(_TEAM_READY_ATTEMPTS): + for _ in range(retry_attempts(_TEAM_READY_ATTEMPTS)): last = self.proxy.transport.get( "/team/info", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), params=TeamInfoParams(team_id=team_id), response_type=TeamInfoResponse, ) @@ -343,25 +353,29 @@ class ManagementClient: case Success(): return case _: + warnings.warn("Repeating team read while the team becomes available", RuntimeWarning, stacklevel=2) time.sleep(_TEAM_READY_SLEEP_SECONDS) assert last is not None raise AssertionError(last) def add_team_member(self, team_id: str, user_id: str) -> None: last: Result[NoBody] | None = None - for attempt in range(_TEAM_READY_ATTEMPTS): + for attempt in range(retry_attempts(_TEAM_READY_ATTEMPTS)): last = self.proxy.transport.post( "/team/member_add", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=TeamMemberAddBody(team_id=team_id, member=TeamMemberEntry(role="user", user_id=user_id)), response_type=NoBody, ) match last: case Success(): return - case UnknownApiError(body=body) if ( - "doesn't exist" in body and attempt + 1 < _TEAM_READY_ATTEMPTS + case UnknownApiError(body=body) if "doesn't exist" in body and attempt + 1 < retry_attempts( + _TEAM_READY_ATTEMPTS ): + warnings.warn( + "Retrying team membership while the team becomes available", RuntimeWarning, stacklevel=2 + ) time.sleep(_TEAM_READY_SLEEP_SECONDS) continue case _: @@ -373,7 +387,7 @@ class ManagementClient: _ = unwrap( self.proxy.transport.post( "/team/member_delete", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=TeamMemberDeleteBody(team_id=team_id, user_id=user_id), response_type=NoBody, ) @@ -383,7 +397,7 @@ class ManagementClient: return unwrap( self.proxy.transport.post( "/user/new", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=body, response_type=UserNewResponse, ) @@ -393,7 +407,7 @@ class ManagementClient: _ = unwrap( self.proxy.transport.post( "/customer/new", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=CustomerNewBody(user_id=user_id), response_type=CustomerResponse, ) @@ -404,7 +418,7 @@ class ManagementClient: return unwrap( self.proxy.transport.get( "/customer/info", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), params=CustomerInfoParams(end_user_id=end_user_id), response_type=CustomerResponse, ) @@ -413,7 +427,7 @@ class ManagementClient: def delete_customer(self, user_id: str) -> None: _ = self.proxy.transport.post( "/customer/delete", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=CustomerDeleteBody(user_ids=[user_id]), response_type=NoBody, ) @@ -422,7 +436,7 @@ class ManagementClient: _ = unwrap( self.proxy.transport.post( "/user/update", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=body, response_type=NoBody, ) @@ -431,7 +445,7 @@ class ManagementClient: def delete_user(self, user_id: str) -> None: _ = self.proxy.transport.post( "/user/delete", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=UserDeleteBody(user_ids=[user_id]), response_type=NoBody, ) @@ -442,17 +456,17 @@ class ManagementClient: _ = unwrap( self.proxy.transport.post( "/user/delete", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=UserDeleteBody(user_ids=[user_id]), response_type=UserDeleteResponse, ) ) - def user_info(self, user_id: str) -> UserInfoResponse: + def user_info(self, user_id: str | None = None) -> UserInfoResponse: return unwrap( self.proxy.transport.get( "/user/info", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), params=UserInfoParams(user_id=user_id), response_type=UserInfoResponse, ) @@ -462,7 +476,7 @@ class ManagementClient: return unwrap( self.proxy.transport.get( "/user/list", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), params=UserListParams(user_ids=user_id), response_type=UserListResponse, ) @@ -472,7 +486,7 @@ class ManagementClient: listing = unwrap( self.proxy.transport.get( "/user/list", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), params=UserListParams(user_ids=user_id), response_type=UserListResponse, ) @@ -483,7 +497,7 @@ class ManagementClient: return unwrap( self.proxy.transport.post( "/organization/new", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=body, response_type=OrgNewResponse, ) @@ -493,7 +507,7 @@ class ManagementClient: _ = unwrap( self.proxy.transport.patch( "/organization/update", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=body, response_type=NoBody, ) @@ -502,7 +516,7 @@ class ManagementClient: def delete_org(self, organization_id: str) -> None: _ = self.proxy.transport.delete( "/organization/delete", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=OrgDeleteBody(organization_ids=[organization_id]), response_type=NoBody, ) @@ -511,19 +525,24 @@ class ManagementClient: return unwrap( self.proxy.transport.get( "/organization/info", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), params=OrgInfoParams(organization_id=organization_id), response_type=OrgInfoResponse, ) ) def org_info_status(self, organization_id: str) -> ProbeResult: - return self.proxy.transport.probe("/organization/info", params=OrgInfoParams(organization_id=organization_id)) + return self.proxy.transport.probe( + "/organization/info", + params=OrgInfoParams(organization_id=organization_id), + headers=self.proxy.management_headers(), + ) + def create_tag(self, body: TagNewBody) -> None: _ = unwrap( self.proxy.transport.post( "/tag/new", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=body, response_type=NoBody, ) @@ -532,7 +551,7 @@ class ManagementClient: def delete_tag(self, name: str) -> None: _ = self.proxy.transport.post( "/tag/delete", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=TagDeleteBody(name=name), response_type=NoBody, ) @@ -542,7 +561,7 @@ class ManagementClient: unwrap( self.proxy.transport.get( "/tag/list", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), params=NoBody(), response_type=TagListResponse, ) @@ -553,7 +572,7 @@ class ManagementClient: return unwrap( self.proxy.transport.post( "/v1/mcp/server", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=body, response_type=McpServerRow, ) @@ -565,7 +584,7 @@ class ManagementClient: return unwrap( self.proxy.transport.put( "/v1/mcp/server", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=body, response_type=McpServerRow, ) @@ -576,7 +595,7 @@ class ManagementClient: unwrap it while a deferred teardown can ignore an already-deleted server.""" return self.proxy.transport.delete( f"/v1/mcp/server/{server_id}", - headers=self.proxy.transport.master, + headers=self.proxy.management_headers(), json=NoBody(), response_type=NoBody, ) diff --git a/tests/e2e/management/test_jwt_management_e2e.py b/tests/e2e/management/test_jwt_management_e2e.py index 22306da8eb8..5898073a4e6 100644 --- a/tests/e2e/management/test_jwt_management_e2e.py +++ b/tests/e2e/management/test_jwt_management_e2e.py @@ -2,60 +2,247 @@ from __future__ import annotations -from typing import Final +from typing import Final, Literal import pytest -from e2e_config import CHEAP_OPENAI_MODEL, unique_marker +from e2e_config import CHEAP_OPENAI_MODEL, PROXY_BASE_URL, unique_marker from e2e_http import UnauthorizedError, UnknownApiError, unwrap -from idp import ADMIN_CLIENT_ID, Identity, Keycloak +from idp import ADMIN_CLIENT_ID, Identity, Keycloak, token_claims from lifecycle import ResourceManager +from management.jwt_actors import ActorFactory, ActorRole from management_client import ManagementClient -from models import KeyGenerateBody, KeyUpdateBody, TeamNewBody, UserNewBody +from models import KeyGenerateBody, KeyUpdateBody, TeamNewBody, UserInfoParams, UserInfoResponse, UserNewBody +from proxy_client import Caller pytestmark = pytest.mark.e2e class TestJwtManagement: - @pytest.mark.covers("mgmt.key.jwt.lifecycle") - def test_admin_creates_reads_updates_clears_and_deletes_a_key( - self, client: ManagementClient, idp: Keycloak, jwt_identity: Identity, resources: ResourceManager - ) -> None: - admin: Final = idp.access_token(jwt_identity, client_id=ADMIN_CLIENT_ID) - alias: Final = f"e2e-jwt-key-{unique_marker()}" - created: Final = unwrap( - client.generate_key( - KeyGenerateBody(key_alias=alias, team_id=jwt_identity.group, models=[CHEAP_OPENAI_MODEL]), - caller_key=admin, + @pytest.mark.parametrize( + "role", + ( + "proxy_admin", + "proxy_admin_viewer", + "organization_admin", + "team_admin", + "team_member", + "internal_user", + "internal_user_viewer", + "unrelated_user", + ), + ) + @pytest.mark.covers("mgmt.user.jwt.database_roles") + def test_actor_subject_and_database_role(self, actor_factory: ActorFactory, role: ActorRole) -> None: + tenants: Final = ( + (actor_factory.tenant(),) if role in ("organization_admin", "team_admin", "team_member") else () + ) + actor: Final = actor_factory.create(role, tenants=tenants) + caller: Final = actor.mint_caller(actor_factory.idp) + claims: Final = token_claims(caller.credential) + assert claims.sub == actor.identity.user_id + assert claims.iss == actor_factory.idp.issuer + assert claims.aud == "litellm-e2e" or "litellm-e2e" in claims.aud + assert actor.identity.groups == () + assert ("litellm_proxy_admin" in claims.scope.split()) == (role == "proxy_admin") + stored: Final = actor_factory.bootstrap.user_info(actor.identity.user_id) + assert stored.user_id == actor.identity.user_id + assert stored.user_info.user_role == actor.global_role + bound: Final = actor_factory.bootstrap.with_caller(caller) + own: Final = unwrap( + bound.proxy.transport.get( + "/user/info", + headers=bound.proxy.management_headers(), + params=UserInfoParams(), + response_type=UserInfoResponse, ) ) - resources.defer(lambda: client.proxy.delete_key(created.key)) + assert own.user_id == actor.identity.user_id + assert own.user_info.user_role == actor.global_role + for tenant in tenants: + info = actor_factory.bootstrap.team_info(tenant.team_id) + assert info.organization_id == tenant.organization_id + assert {(member.user_id, member.role) for member in info.members_with_roles} == { + (actor.identity.user_id, "admin" if role == "team_admin" else "user") + } + assert { + (member.user_id, member.user_role) + for member in actor_factory.bootstrap.org_info(tenant.organization_id).members + } == {(actor.identity.user_id, "org_admin" if role == "organization_admin" else "internal_user")} - original: Final = unwrap(client.key_info_as(created.key, caller_key=admin)).info - assert original.key_alias == alias and original.team_id == jwt_identity.group + @pytest.mark.covers("mgmt.key.jwt.viewer_denied") + def test_admin_viewer_reads_but_cannot_update(self, actor_factory: ActorFactory) -> None: + actor: Final = actor_factory.create("proxy_admin_viewer") + viewer: Final = actor_factory.bootstrap.with_caller(actor.mint_caller(actor_factory.idp)) + alias: Final = f"e2e-viewer-{unique_marker()}" + key: Final = actor_factory.key().key + unwrap(actor_factory.bootstrap.update_key(KeyUpdateBody(key=key, key_alias=alias))) + assert viewer.proxy.key_info(key).key_alias == alias + denied: Final = viewer.update_key(KeyUpdateBody(key=key, key_alias="forbidden")) + assert isinstance(denied, UnknownApiError) and denied.status_code == 403, f"viewer write was accepted: {denied}" + assert "proxy_admin_viewer" in denied.body and "/key/update" in denied.body + assert actor_factory.bootstrap.proxy.key_info(key).key_alias == alias + + @pytest.mark.covers("mgmt.user.oidc.identity_mapping") + def test_oidc_browser_profile_identity_mapping(self, actor_factory: ActorFactory) -> None: + actor: Final = actor_factory.create("internal_user") + idp: Final = actor_factory.idp.with_strict_cleanup() + discovery: Final = idp.discovery() + assert discovery.issuer == idp.issuer + assert discovery.jwks_uri == idp.jwks_url + callback: Final = f"{PROXY_BASE_URL}/sso/callback" + browser: Final = idp.browser_client(callback_url=callback, defer=actor_factory.resources.defer) + token: Final = idp.browser_token(actor.identity, browser) + assert token_claims(token).sub == actor.identity.user_id + userinfo: Final = idp.userinfo(token) + assert userinfo.sub == actor.identity.user_id + assert userinfo.email == f"{actor.identity.username}@example.com" + assert browser.environment(discovery)["GENERIC_USER_ID_ATTRIBUTE"] == "sub" + + @pytest.mark.covers("mgmt.key.jwt.lifecycle") + @pytest.mark.parametrize("credential_kind", ("direct_jwt", "virtual_key")) + def test_admin_creates_reads_updates_clears_and_deletes_a_key( + self, + actor_factory: ActorFactory, + credential_kind: Literal["direct_jwt", "virtual_key"], + ) -> None: + tenant: Final = actor_factory.tenant() + actor: Final = actor_factory.create("proxy_admin", tenants=(tenant,), profile="group_scoped") + virtual_key: Final = ( + actor_factory.key(user_id=actor.identity.user_id).key if credential_kind == "virtual_key" else None + ) + admin: Final = virtual_key if virtual_key is not None else actor.mint_caller(actor_factory.idp).credential + bound: Final = actor_factory.bootstrap.with_caller( + Caller(credential=admin, kind=credential_kind, role="proxy_admin") + ) + assert bound.user_info().user_id == actor.identity.user_id + alias: Final = f"e2e-jwt-key-{unique_marker()}" + created: Final = unwrap( + bound.generate_key( + KeyGenerateBody(key_alias=alias, team_id=tenant.team_id, models=[CHEAP_OPENAI_MODEL]), + ) + ) + actor_factory.resources.defer(lambda: actor_factory.bootstrap.delete_key_strict(created.key, missing_ok=True)) + + original: Final = unwrap(bound.key_info_as(created.key)).info + assert original.key_alias == alias and original.team_id == tenant.team_id assert original.models == [CHEAP_OPENAI_MODEL] updated_alias: Final = f"{alias}-updated" - unwrap( - client.update_key(KeyUpdateBody(key=created.key, key_alias=updated_alias, rpm_limit=120), caller_key=admin) - ) - updated: Final = unwrap(client.key_info_as(created.key, caller_key=admin)).info + unwrap(bound.update_key(KeyUpdateBody(key=created.key, key_alias=updated_alias, rpm_limit=120))) + updated: Final = unwrap(bound.key_info_as(created.key)).info assert updated.key_alias == updated_alias and updated.rpm_limit == 120 assert updated.models == [CHEAP_OPENAI_MODEL], "omitted models must preserve the restriction" - unwrap(client.update_key(KeyUpdateBody(key=created.key, models=[]), caller_key=admin)) - cleared: Final = unwrap(client.key_info_as(created.key, caller_key=admin)).info + unwrap(bound.update_key(KeyUpdateBody(key=created.key, models=[]))) + cleared: Final = unwrap(bound.key_info_as(created.key)).info assert cleared.models == [] and cleared.rpm_limit == 120 - assert unwrap(client.key_list(updated_alias, caller_key=admin)).total_count == 1 - client.delete_key_strict(created.key, caller_key=admin) - assert unwrap(client.key_list(updated_alias, caller_key=admin)).total_count == 0 + assert unwrap(bound.key_list(updated_alias)).total_count == 1 + bound.delete_key_strict(created.key) + assert unwrap(bound.key_list(updated_alias)).total_count == 0 + + @pytest.mark.covers("mgmt.team.jwt.tenant_isolation") + def test_two_actor_sets_keep_tenants_and_keys_isolated(self, actor_factory: ActorFactory) -> None: + first: Final = actor_factory.tenant() + second: Final = actor_factory.tenant() + assert first.organization_id != second.organization_id and first.team_id != second.team_id + actors: Final = tuple( + actor_factory.create("team_member", tenants=(tenant,), profile="group_scoped") for tenant in (first, second) + ) + assert actors[0].identity.user_id != actors[1].identity.user_id + callers: Final = tuple( + actor_factory.bootstrap.with_caller(actor.mint_caller(actor_factory.idp)) for actor in actors + ) + keys: Final = tuple(actor_factory.key(tenant) for tenant in (first, second)) + assert keys[0].key != keys[1].key + assert callers[0].proxy.key_info(keys[0].key).team_id == first.team_id + assert callers[1].proxy.key_info(keys[1].key).team_id == second.team_id + for caller, other_key in ((callers[0], keys[1].key), (callers[1], keys[0].key)): + hidden = caller.key_info_as(other_key) + assert isinstance(hidden, UnknownApiError) and hidden.status_code == 403 + assert tuple(actor.identity.groups for actor in actors) == ((first.team_id,), (second.team_id,)) + + @pytest.mark.covers("mgmt.team.jwt.multiple_memberships") + def test_multi_group_actor_keeps_exact_memberships(self, actor_factory: ActorFactory) -> None: + tenants: Final = (actor_factory.tenant(), actor_factory.tenant()) + actor: Final = actor_factory.create("team_member", tenants=tenants, profile="group_scoped") + claims: Final = token_claims(actor.mint_caller(actor_factory.idp).credential) + assert set(claims.groups) == {tenant.team_id for tenant in tenants} + assert "litellm_proxy_admin" not in claims.scope.split() + assert actor.identity.groups == tuple(tenant.team_id for tenant in tenants) + for tenant in tenants: + assert { + (entry.user_id, entry.role) + for entry in actor_factory.bootstrap.team_info(tenant.team_id).members_with_roles + } == {(actor.identity.user_id, "user")} + + @pytest.mark.covers("mgmt.user.jwt.cleanup") + def test_successful_actor_cleanup_removes_owned_state(self, actor_factory: ActorFactory) -> None: + resources: Final = ResourceManager(client=actor_factory.bootstrap.proxy, strict_cleanup=True) + factory: Final = ActorFactory(bootstrap=actor_factory.bootstrap, idp=actor_factory.idp, resources=resources) + try: + tenant: Final = factory.tenant() + actor: Final = factory.create("team_member", tenants=(tenant,), profile="group_scoped") + key: Final = factory.key(tenant) + alias: Final = factory.bootstrap.proxy.key_info(key.key).key_alias + assert alias is not None + finally: + resources.teardown() + assert factory.bootstrap.user_count(actor.identity.user_id) == 0 + assert factory.bootstrap.key_alias_count(alias) == 0 + assert factory.bootstrap.team_info_status(tenant.team_id).status_code == 404 + assert factory.bootstrap.org_info_status(tenant.organization_id).status_code == 404 + factory.idp.assert_absent("users", actor.identity.user_id) + factory.idp.assert_absent("groups", tenant.group_id) + + @pytest.mark.parametrize("stage", ("group", "user")) + @pytest.mark.covers("mgmt.user.jwt.partial_cleanup") + def test_partial_setup_removes_previously_created_identities( + self, + actor_factory: ActorFactory, + stage: Literal["group", "user"], + ) -> None: + idp: Final = actor_factory.idp.with_strict_cleanup() + resources: Final = ResourceManager(client=actor_factory.bootstrap.proxy, strict_cleanup=True) + marker: Final = unique_marker() + group_id: Final = idp.create_group(f"e2e-partial-{marker}") + resources.defer(lambda: idp.delete_group(group_id)) + try: + identity: Final = ( + idp.provision_user( + marker=marker, + groups=(f"e2e-partial-{marker}",), + group_ids=(group_id,), + defer=resources.defer, + ) + if stage == "user" + else None + ) + if identity is None: + with pytest.raises(pytest.fail.Exception, match="HTTP 409"): + idp.create_group(f"e2e-partial-{marker}") + else: + with pytest.raises(pytest.fail.Exception, match="HTTP 409"): + idp.create_user( + username=identity.username, + email=f"{identity.username}@example.com", + password=identity.password, + groups=identity.groups, + ) + finally: + resources.teardown() + idp.assert_absent("groups", group_id) + if identity is not None: + idp.assert_absent("users", identity.user_id) @pytest.mark.covers("mgmt.key.jwt.member_denied", "mgmt.key.jwt.other_team_denied") def test_member_cannot_write_and_another_team_cannot_read_the_key( self, client: ManagementClient, idp: Keycloak, jwt_identity: Identity, resources: ResourceManager ) -> None: admin: Final = idp.access_token(jwt_identity, client_id=ADMIN_CLIENT_ID) + bound: Final = client.with_caller(Caller(credential=admin, kind="direct_jwt", role="proxy_admin")) member: Final = idp.access_token(jwt_identity) + member_client: Final = client.with_caller(Caller(credential=member, kind="direct_jwt", role="team_member")) alias: Final = f"e2e-jwt-owned-{unique_marker()}" created: Final = unwrap( client.generate_key(KeyGenerateBody(key_alias=alias, team_id=jwt_identity.group), caller_key=admin) @@ -63,14 +250,14 @@ class TestJwtManagement: resources.defer(lambda: client.proxy.delete_key(created.key)) client.add_team_member(jwt_identity.group, jwt_identity.user_id) - assert unwrap(client.key_info_as(created.key, caller_key=member)).info.key_alias == alias + assert unwrap(member_client.key_info_as(created.key)).info.key_alias == alias - refused: Final = client.update_key(KeyUpdateBody(key=created.key, key_alias="forbidden"), caller_key=member) + refused: Final = member_client.update_key(KeyUpdateBody(key=created.key, key_alias="forbidden")) assert isinstance(refused, UnauthorizedError), f"member write was accepted: {refused}" assert "does not have permissions for endpoint" in refused.body.lower(), ( f"expected a permission denial: {refused}" ) - assert unwrap(client.key_info_as(created.key, caller_key=admin)).info.key_alias == alias + assert unwrap(bound.key_info_as(created.key)).info.key_alias == alias marker: Final = unique_marker() outsider: Final = idp.provision(marker=marker, group=f"e2e-jwt-team-{marker}", defer=resources.defer) @@ -88,4 +275,4 @@ class TestJwtManagement: assert isinstance(hidden, UnknownApiError) and hidden.status_code == 403, ( f"another team must not read this key: {hidden}" ) - assert unwrap(client.key_info_as(created.key, caller_key=admin)).info.team_id == jwt_identity.group + assert unwrap(bound.key_info_as(created.key)).info.team_id == jwt_identity.group diff --git a/tests/e2e/models.py b/tests/e2e/models.py index 3cab0334dea..ba6d0fe3334 100644 --- a/tests/e2e/models.py +++ b/tests/e2e/models.py @@ -283,10 +283,15 @@ class ChatToolResultTurn(BaseModel): type ChatTurn = ChatMessage | ChatAssistantTurn | ChatToolResultTurn +class ChatStreamOptions(BaseModel): + include_usage: bool + + class ChatBody(BaseModel): model: str messages: Sequence[ChatTurn] stream: bool = False + stream_options: ChatStreamOptions | None = None max_tokens: int | None = None max_completion_tokens: int | None = None temperature: float | None = None @@ -488,12 +493,18 @@ class AnthropicToolResultTurn(BaseModel): type AnthropicMessage = ChatMessage | AnthropicAssistantTurn | AnthropicToolResultTurn +class AnthropicToolChoice(BaseModel): + type: Literal["auto", "any", "tool", "none"] + name: str | None = None + + class AnthropicMessagesBody(BaseModel): model: str messages: list[AnthropicMessage] max_tokens: int stream: bool | None = None tools: list[AnthropicTool] | None = None + tool_choice: AnthropicToolChoice | None = None guardrails: list[str] | None = None cache: dict[str, bool] | None = {"no-cache": True} @@ -1091,13 +1102,13 @@ class UiLoginBody(BaseModel): class UiLoginResponse(BaseModel): - token: str + token: str = Field(repr=False) redirect_url: str class UiSessionClaims(BaseModel): user_id: str - key: str + key: str = Field(repr=False) user_role: str login_method: Literal["sso", "username_password"] exp: int @@ -1135,6 +1146,7 @@ class TeamInfoParams(BaseModel): class TeamData(BaseModel): + organization_id: str | None = None team_alias: str | None = None models: list[str] = [] members_with_roles: list[TeamMemberEntry] = [] @@ -1175,6 +1187,7 @@ class UserNewBody(BaseModel): user_email: str user_role: UserRole user_id: str | None = None + auto_create_key: bool | None = None class UserNewResponse(BaseModel): @@ -1187,7 +1200,7 @@ class UserUpdateBody(BaseModel): class UserInfoParams(BaseModel): - user_id: str + user_id: str | None = None class UserData(BaseModel): @@ -1240,16 +1253,36 @@ class OrgInfoParams(BaseModel): organization_id: str +class OrgMembership(BaseModel): + user_id: str + user_role: str + + class OrgInfoResponse(BaseModel): organization_id: str organization_alias: str | None = None models: list[str] = [] + members: tuple[OrgMembership, ...] = () + + +class OrgMemberEntry(BaseModel): + user_id: str + role: Literal["org_admin", "internal_user"] + + +class OrgMemberAddBody(BaseModel): + organization_id: str + member: OrgMemberEntry class OrgDeleteBody(BaseModel): organization_ids: list[str] +class OrgDeleteResponse(RootModel[tuple[OrgInfoResponse, ...]]): + pass + + # ---------- tags (management) ---------- diff --git a/tests/e2e/provider_edge.py b/tests/e2e/provider_edge.py index 6c87c7ef7ac..de36895ebb6 100644 --- a/tests/e2e/provider_edge.py +++ b/tests/e2e/provider_edge.py @@ -92,6 +92,7 @@ from fixture_mode import ( current_test_key, parse_fixture_mode, ) +from fixture_profile import IneligibleRequest, MatchProfile, match_profile, strict_identity from pydantic import JsonValue, TypeAdapter EDGE_MOUNTS: Final[Mapping[str, str]] = MappingProxyType( @@ -404,6 +405,12 @@ def _miss_message(test_key: str, slug: str, canonical: CanonicalRequest, bundle: f"under {slug}; re-record with E2E_FIXTURE_MODE=record" ) closest, closest_file = _closest_recorded(canonical, recorded) + if bundle.manifest.match_profile == "stateless_v1": + expected: Final = _JSON.validate_json(closest.content) + actual: Final = _JSON.validate_json(canonical.content) + assert isinstance(expected, dict) and isinstance(actual, dict) + changed: Final = ", ".join(key for key in expected if expected[key] != actual.get(key)) + return f"stateless_v1 replay mismatch: {changed or 'method/path'}; re-record with E2E_FIXTURE_MODE=record" diff: Final = "\n".join( islice( difflib.unified_diff( @@ -785,11 +792,33 @@ def handle_edge_request( mount, _, upstream_path = split.path.lstrip("/").partition("/") upstream_base: Final = mounts.get(mount) if upstream_base is None: - return _text_reply( - 404, f"unknown provider mount {mount!r}; known mounts: {', '.join(sorted(mounts))}" + return _text_reply(404, f"unknown provider mount {mount!r}; known mounts: {', '.join(sorted(mounts))}") + profile: Final = ( + backend.recorder.profile + if isinstance(backend, RecordEdge) + else backend.source.bundle.manifest.match_profile + if isinstance(backend, ReplayEdge) + else "legacy" + ) + identity: Final = ( + strict_identity( + method=method, + path=split.path, + query=split.query, + headers=headers, + body=body, + mount=mount, + upstream_base=upstream_base, ) - request: Final = edge_request( - method, split.path, split.query, body, _header_value(headers, "content-type") + if profile == "stateless_v1" + else None + ) + if isinstance(identity, IneligibleRequest): + return _text_reply(REPLAY_MISS_STATUS, f"stateless_v1 eligibility error: {identity.reason}") + request: Final = ( + RecordedRequest(method=method.lower(), path=split.path, headers={}, strict_identity=identity) + if identity is not None + else edge_request(method, split.path, split.query, body, _header_value(headers, "content-type")) ) match backend: case LiveEdge(): @@ -837,6 +866,14 @@ class _EdgeHandler(BaseHTTPRequestHandler): body: Final = self.rfile.read(length) if length else None if edge_server.observation is not None: edge_server.observation.observe(body) + strict: Final = ( + isinstance(edge_server.backend, RecordEdge) and edge_server.backend.recorder.profile == "stateless_v1" + or isinstance(edge_server.backend, ReplayEdge) + and edge_server.backend.source.bundle.manifest.match_profile == "stateless_v1" + ) + if strict and len({name.lower() for name in self.headers.keys()}) != len(self.headers): + self._write_reply(_text_reply(REPLAY_MISS_STATUS, "stateless_v1 eligibility error: duplicate headers")) + return outcome: Final = handle_edge_request( edge_server.backend, edge_server.mounts, @@ -955,16 +992,16 @@ def start_provider_edge( @functools.lru_cache(maxsize=8) -def _shared_recorder(root: Path) -> BundleRecorder: - prepared = prepare_bundle(root) +def _shared_recorder(root: Path, profile: MatchProfile = "legacy") -> BundleRecorder: + prepared = prepare_bundle(root, profile=profile) if isinstance(prepared, UnsafeBundleDir): raise ValueError(f"E2E_FIXTURE_DIR {prepared.path} {prepared.reason}") return prepared @functools.lru_cache(maxsize=8) -def _shared_replay_source(root: Path) -> ReplaySource: - loaded = load_bundle(root) +def _shared_replay_source(root: Path, profile: MatchProfile = "legacy") -> ReplaySource: + loaded = load_bundle(root, profile=profile) if isinstance(loaded, UnreadableBundle): raise ValueError(f"cannot replay from {root}: {loaded.reason}") return ReplaySource(bundle=loaded) @@ -977,11 +1014,12 @@ def _shared_edge( bind_host: str, advertise_host: str, forward_timeout: float, + profile: MatchProfile, ) -> ProviderEdge: backend: Final[EdgeBackend] = ( - RecordEdge(recorder=_shared_recorder(bundle_dir), lock=threading.Lock()) + RecordEdge(recorder=_shared_recorder(bundle_dir, profile), lock=threading.Lock()) if mode == "record" - else ReplayEdge(source=_shared_replay_source(bundle_dir)) + else ReplayEdge(source=_shared_replay_source(bundle_dir, profile)) ) return start_provider_edge( backend, @@ -998,7 +1036,7 @@ def replay_leftover_error(*, mode_raw: str, bundle_dir: Path, test_key: str) -> recording it no longer matches. Inert in every other mode.""" if parse_fixture_mode(mode_raw) != "replay": return None - return _shared_replay_source(bundle_dir).leftover_error(test_key) + return _shared_replay_source(bundle_dir, match_profile()).leftover_error(test_key) def provider_edge_api_base( @@ -1021,10 +1059,10 @@ def provider_edge_api_base( return None case "record" | "replay": if mount not in EDGE_MOUNTS: - raise ValueError( - f"unknown provider mount {mount!r}; known mounts: {', '.join(sorted(EDGE_MOUNTS))}" - ) - return _shared_edge(mode, bundle_dir, bind_host, advertise_host, forward_timeout).api_base(mount) + raise ValueError(f"unknown provider mount {mount!r}; known mounts: {', '.join(sorted(EDGE_MOUNTS))}") + return _shared_edge(mode, bundle_dir, bind_host, advertise_host, forward_timeout, match_profile()).api_base( + mount + ) case _: assert_never(mode) @@ -1037,9 +1075,9 @@ def _observed_backend(mode_raw: str, bundle_dir: Path) -> EdgeBackend: case "live": return LiveEdge() case "record": - return RecordEdge(_shared_recorder(bundle_dir), threading.Lock()) + return RecordEdge(_shared_recorder(bundle_dir, match_profile()), threading.Lock()) case "replay": - return ReplayEdge(_shared_replay_source(bundle_dir)) + return ReplayEdge(_shared_replay_source(bundle_dir, match_profile())) case _: assert_never(mode) diff --git a/tests/e2e/proxy_client.py b/tests/e2e/proxy_client.py index 1fe2ec905ef..48a6110dc0b 100644 --- a/tests/e2e/proxy_client.py +++ b/tests/e2e/proxy_client.py @@ -11,14 +11,23 @@ from __future__ import annotations import time import warnings from collections.abc import Callable, Mapping -from dataclasses import dataclass -from functools import reduce +from dataclasses import dataclass, field, replace from datetime import datetime +from functools import reduce from types import MappingProxyType -from typing import Final - -from pydantic import BaseModel +from typing import Final, Literal +from e2e_config import ( + CONTROL_PLANE_BASE_URL, + MASTER_KEY, + POLL_INTERVAL, + POLL_TIMEOUT, + PROXY_BASE_URL, + PROXY_REPLICA_URLS, + REQUEST_TIMEOUT, + SLOW_PROVIDER_TIMEOUT_SECONDS, + settle_propagation, +) from e2e_http import ( AnthropicHeaders, AuthHeaders, @@ -55,6 +64,7 @@ from models import ( KeyInfoParams, KeyInfoResponse, LiteLLMParamsBody, + MemorySummaryResponse, ModelDeleteBody, ModelInfoBody, ModelInfoEntry, @@ -63,7 +73,6 @@ from models import ( ModelNewBody, ModelNewResponse, ModelsListParams, - MemorySummaryResponse, ModelsListResponse, ModelUpdateBody, OcrBody, @@ -76,23 +85,13 @@ from models import ( TeamDeleteBody, TeamNewBody, TeamNewResponse, - UserDeleteBody, - UserDeleteResponse, ToolsetCreateBody, ToolsetRow, ToolsetUpdateBody, + UserDeleteBody, + UserDeleteResponse, ) -from e2e_config import ( - CONTROL_PLANE_BASE_URL, - MASTER_KEY, - POLL_INTERVAL, - POLL_TIMEOUT, - PROXY_BASE_URL, - PROXY_REPLICA_URLS, - REQUEST_TIMEOUT, - SLOW_PROVIDER_TIMEOUT_SECONDS, - settle_propagation, -) +from pydantic import BaseModel from transport import HttpTransport, SplitTransport, Transport, is_control_plane_path RowsPredicate = Callable[[list[SpendLogRow]], bool] @@ -421,11 +420,23 @@ def converge_timeout_message(*, what: str, replica: str, timeout: float, last_re ) +CredentialKind = Literal["master", "direct_jwt", "virtual_key", "dashboard_session"] + + +@dataclass(frozen=True, slots=True) +class Caller: + credential: str = field(repr=False) + kind: CredentialKind + role: str + tenant: str | None = None + + @dataclass(frozen=True, slots=True) class ProxyClient: transport: Transport replicas: Mapping[str, Transport] control_replicas: Mapping[str, Transport] + caller: Caller | None = None poll_timeout: float = 120.0 poll_interval: float = 5.0 model_servable_timeout: float = MODEL_SERVABLE_TIMEOUT @@ -433,13 +444,24 @@ class ProxyClient: model_servable_interval: float = MODEL_SERVABLE_INTERVAL model_servable_request_timeout: float = MODEL_SERVABLE_REQUEST_TIMEOUT + def with_caller(self, caller: Caller) -> ProxyClient: + return replace(self, caller=caller) + + def management_headers(self, caller_key: str | None = None, *, transport: Transport | None = None) -> AuthHeaders: + selected: Final = self.transport if transport is None else transport + if caller_key is not None: + return selected.bearer(caller_key) + if self.caller is not None: + return selected.bearer(self.caller.credential) + return selected.master + # ---- keys / customers (satisfies lifecycle.ResourceClient) ---------- def generate_key(self, body: KeyGenerateBody) -> str: return unwrap( self.transport.post( "/key/generate", - headers=self.transport.master, + headers=self.management_headers(), json=body, response_type=KeyGenerateResponse, ) @@ -448,7 +470,7 @@ class ProxyClient: def delete_key(self, key: str) -> None: _ = self.transport.post( "/key/delete", - headers=self.transport.master, + headers=self.management_headers(), json=KeyDeleteBody(keys=[key]), response_type=NoBody, ) @@ -458,7 +480,7 @@ class ProxyClient: return _ = self.transport.post( "/customer/delete", - headers=self.transport.master, + headers=self.management_headers(), json=CustomerDeleteBody(user_ids=user_ids), response_type=NoBody, ) @@ -467,7 +489,7 @@ class ProxyClient: return unwrap( self.transport.get( "/key/info", - headers=self.transport.master, + headers=self.management_headers(), params=KeyInfoParams(key=key), response_type=KeyInfoResponse, ) @@ -477,7 +499,7 @@ class ProxyClient: return { url: transport.get( "/debug/memory/summary", - headers=transport.master, + headers=self.management_headers(transport=transport), params=NoBody(), response_type=MemorySummaryResponse, ) @@ -524,11 +546,12 @@ class ProxyClient: {replica: outcome.result for replica, outcome in outcomes.items() if isinstance(outcome, Converged)} ) - @staticmethod def _body_poller[R: BaseModel]( - transport: Transport, path: str, params: BaseModel, response_type: type[R] + self, transport: Transport, path: str, params: BaseModel, response_type: type[R] ) -> Poller[Result[R]]: - return lambda: transport.get(path, headers=transport.master, params=params, response_type=response_type) + return lambda: transport.get( + path, headers=self.management_headers(transport=transport), params=params, response_type=response_type + ) def model_info(self) -> list[ModelInfoEntry]: """Every configured deployment with the price the proxy resolved for it @@ -536,7 +559,7 @@ class ProxyClient: return unwrap( self.transport.get( "/model/info", - headers=self.transport.master, + headers=self.management_headers(), params=NoBody(), response_type=ModelInfoResponse, ) @@ -546,7 +569,7 @@ class ProxyClient: return unwrap( self.transport.get( "/public/litellm_model_cost_map", - headers=self.transport.master, + headers=self.management_headers(), params=NoBody(), response_type=CostMap, ) @@ -607,7 +630,7 @@ class ProxyClient: model_id = unwrap( self.transport.post( "/model/new", - headers=self.transport.master, + headers=self.management_headers(), json=body, response_type=ModelNewResponse, ) @@ -623,7 +646,7 @@ class ProxyClient: 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.""" - headers: Final = self.transport.master if listed_for is None else self.transport.bearer(listed_for) + headers: Final = self.management_headers(listed_for) outcome: Final = await_servable_everywhere( {url: self._models_poller(transport, headers) for url, transport in self.replicas.items()}, model_name=model_name, @@ -666,7 +689,7 @@ class ProxyClient: unwrap( self.transport.post( "/model/update", - headers=self.transport.master, + headers=self.management_headers(), json=ModelUpdateBody( litellm_params=litellm_params, model_info=ModelInfoBody(id=model_id), @@ -678,7 +701,7 @@ class ProxyClient: def delete_model(self, model_id: str) -> None: result = self.transport.post( "/model/delete", - headers=self.transport.master, + headers=self.management_headers(), json=ModelDeleteBody(id=model_id), response_type=NoBody, ) @@ -747,11 +770,10 @@ class ProxyClient: f"GET {path} on {replica} still answers {self.poll_timeout}s after the delete; last read: {last}" ) - @staticmethod - def _reader[R: BaseModel](transport: Transport, path: str, response_type: type[R]) -> ReplicaRead[Result[R]]: + def _reader[R: BaseModel](self, transport: Transport, path: str, response_type: type[R]) -> ReplicaRead[Result[R]]: return lambda request_timeout: transport.get( path, - headers=transport.master, + headers=self.management_headers(transport=transport), params=NoBody(), response_type=response_type, timeout=request_timeout, @@ -763,7 +785,7 @@ class ProxyClient: return unwrap( self.transport.post( "/v1/mcp/toolset", - headers=self.transport.master, + headers=self.management_headers(), json=body, response_type=ToolsetRow, ) @@ -775,7 +797,7 @@ class ProxyClient: return unwrap( self.transport.put( "/v1/mcp/toolset", - headers=self.transport.master, + headers=self.management_headers(), json=body, response_type=ToolsetRow, ) @@ -786,7 +808,7 @@ class ProxyClient: can unwrap it while a deferred teardown can ignore an already-deleted row.""" return self.transport.delete( f"/v1/mcp/toolset/{toolset_id}", - headers=self.transport.master, + headers=self.management_headers(), json=NoBody(), response_type=NoBody, ) @@ -795,7 +817,7 @@ class ProxyClient: unwrap( self.transport.post( "/credentials", - headers=self.transport.master, + headers=self.management_headers(), json=body, response_type=CredentialCreateResponse, ) @@ -804,7 +826,7 @@ class ProxyClient: def delete_credential(self, credential_name: str) -> None: result = self.transport.delete( f"/credentials/{credential_name}", - headers=self.transport.master, + headers=self.management_headers(), json=NoBody(), response_type=NoBody, ) @@ -815,7 +837,7 @@ class ProxyClient: return unwrap( self.transport.post( "/team/new", - headers=self.transport.master, + headers=self.management_headers(), json=body, response_type=TeamNewResponse, ) @@ -824,7 +846,7 @@ class ProxyClient: def delete_team(self, team_id: str) -> None: result = self.transport.post( "/team/delete", - headers=self.transport.master, + headers=self.management_headers(), json=TeamDeleteBody(team_ids=[team_id]), response_type=NoBody, ) @@ -836,7 +858,7 @@ class ProxyClient: a user the proxy only upserts after a successful auth.""" result = self.transport.post( "/user/delete", - headers=self.transport.master, + headers=self.management_headers(), json=UserDeleteBody(user_ids=[user_id]), response_type=UserDeleteResponse, ) @@ -909,7 +931,7 @@ class ProxyClient: def spend_logs(self, params: SpendLogsParams) -> list[SpendLogRow]: result = self.transport.get( "/spend/logs", - headers=self.transport.master, + headers=self.management_headers(), params=params, response_type=SpendLogs, ) @@ -924,7 +946,7 @@ class ProxyClient: return unwrap( self.transport.get( "/spend/logs/v2", - headers=self.transport.master, + headers=self.management_headers(), params=SpendLogsPageParams( start_date=start.strftime("%Y-%m-%d %H:%M:%S"), end_date=end.strftime("%Y-%m-%d %H:%M:%S"), @@ -977,7 +999,7 @@ class ProxyClient: # ---- route probe ---------------------------------------------------- def probe(self, path: str, *, params: NoBody) -> ProbeResult: - return self.transport.probe(path, params=params) + return self.transport.probe(path, params=params, headers=self.management_headers()) def build_proxy_client( diff --git a/tests/e2e/quota_management/spend_tracking/spend_reconciliation.py b/tests/e2e/quota_management/spend_tracking/spend_reconciliation.py new file mode 100644 index 00000000000..26809874aed --- /dev/null +++ b/tests/e2e/quota_management/spend_tracking/spend_reconciliation.py @@ -0,0 +1,113 @@ +from concurrent.futures import ThreadPoolExecutor +from dataclasses import dataclass +from math import isclose +from typing import Final + +from e2e_config import provider_edge_base, unique_marker +from e2e_http import unwrap +from lifecycle import ResourceManager +from models import ChatBody, ChatMessage, ChatResponse, KeyGenerateBody, LiteLLMParamsBody, TeamNewBody +from spend_e2e_client import SpendClient + +INPUT_RATE: Final = 0.00004 +OUTPUT_RATE: Final = 0.00008 + + +@dataclass(frozen=True) +class TeamTraffic: + team_id: str + key: str + responses: tuple[ChatResponse, ...] + + @property + def prompt_tokens(self) -> int: + return sum(response.usage.prompt_tokens or 0 for response in self.responses if response.usage) + + @property + def completion_tokens(self) -> int: + return sum(response.usage.completion_tokens or 0 for response in self.responses if response.usage) + + @property + def spend(self) -> float: + return self.prompt_tokens * INPUT_RATE + self.completion_tokens * OUTPUT_RATE + + +def create_traffic(client: SpendClient, resources: ResourceManager) -> tuple[TeamTraffic, ...]: + base: Final = provider_edge_base("openai") + model: Final = f"e2e-reconciliation-{unique_marker()}" + model_id: Final = client.proxy.create_model( + model, + LiteLLMParamsBody( + model="openai/gpt-5.6-luna", + api_key="os.environ/OPENAI_API_KEY", + api_base=None if base is None else f"{base}/v1", + input_cost_per_token=INPUT_RATE, + output_cost_per_token=OUTPUT_RATE, + ), + ) + resources.defer(lambda: client.proxy.delete_model(model_id)) + + def team_traffic() -> TeamTraffic: + team: Final = client.proxy.create_team(TeamNewBody(team_alias=f"e2e-spend-{unique_marker()}")) + resources.defer(lambda: client.proxy.delete_team(team)) + key: Final = client.proxy.generate_key(KeyGenerateBody(team_id=team, models=[model])) + resources.defer(lambda: client.proxy.delete_key(key)) + + prompts: Final = tuple(f"Reply with one word. {index} {unique_marker()}" for index in range(7)) + + def call(index: int) -> ChatResponse: + response: Final = unwrap( + client.proxy.chat( + key, + ChatBody( + model=model, + messages=[ChatMessage(role="user", content=prompts[index])], + max_completion_tokens=128, + ), + ) + ) + assert response.id, "successful response must have an ID" + assert response.usage is not None, "successful response must have usage" + assert response.usage.prompt_tokens is not None and response.usage.prompt_tokens > 0 + assert response.usage.completion_tokens is not None and response.usage.completion_tokens > 0 + assert response.usage.total_tokens == response.usage.prompt_tokens + response.usage.completion_tokens + assert not response.usage.cache_creation_input_tokens + assert not response.usage.cache_read_input_tokens + assert not response.usage.prompt_tokens_details or not response.usage.prompt_tokens_details.cached_tokens + return response + + sequential: Final = call(0) + with ThreadPoolExecutor(max_workers=6) as pool: + concurrent: Final = tuple(pool.map(call, range(1, 7))) + return TeamTraffic(team, key, (sequential, *concurrent)) + + return tuple(team_traffic() for _ in range(2)) + + +def assert_logs_match(client: SpendClient, traffic: TeamTraffic) -> None: + expected_ids: Final = frozenset(response.id for response in traffic.responses) + assert len(expected_ids) == len(traffic.responses), "responses must have distinct IDs" + rows: Final = client.poll_logs_for_key( + traffic.key, + min_rows=len(traffic.responses), + predicate=lambda values: frozenset(row.request_id for row in values) == expected_ids, + ) + assert frozenset(row.request_id for row in rows) == expected_ids, "stored IDs must equal returned response IDs" + assert len(rows) == len(traffic.responses), "expected exactly one scoped spend row per response" + by_id: Final = {row.request_id: row for row in rows} + + def assert_response(response: ChatResponse) -> None: + row: Final = by_id[response.id] + usage: Final = response.usage + assert usage is not None and usage.prompt_tokens is not None and usage.completion_tokens is not None + assert row.team_id == traffic.team_id + assert row.status == "success" + assert row.cache_hit != "True" + assert row.prompt_tokens == usage.prompt_tokens + assert row.completion_tokens == usage.completion_tokens + assert row.total_tokens == usage.total_tokens + expected_cost: Final = usage.prompt_tokens * INPUT_RATE + usage.completion_tokens * OUTPUT_RATE + assert row.spend is not None and isclose(row.spend, expected_cost, rel_tol=1e-6, abs_tol=1e-9) + + for response in traffic.responses: + assert_response(response) 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 c5d76d44580..8a91e53e7d7 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 @@ -17,13 +17,13 @@ fails the test; a pricing or token-count drift does not. import time from collections.abc import Callable -from concurrent.futures import ThreadPoolExecutor +from math import isclose +from typing import Final import pytest - -from e2e_http import Result, Success +from e2e_http import Success from lifecycle import ResourceManager -from models import ChatResponse, LiteLLMParamsBody, SpendLogs, SpendLogsParams +from models import LiteLLMParamsBody, SpendLogs, SpendLogsParams from spend_e2e_client import SpendClient, SpendLogRow, is_ok, unique_marker, unwrap pytestmark = pytest.mark.e2e @@ -280,51 +280,22 @@ def test_key_spend_equals_sum_of_logs(client: SpendClient, scoped_key: str) -> N ), f"key aggregate {key_spend} != sum of logs {logs_total}; rows: {_summarize(rows)}" +@pytest.mark.replayable @pytest.mark.covers("quota_management.spend_tracking.concurrent_burst.loses_no_spend") def test_burst_of_concurrent_calls_loses_no_spend( - client: SpendClient, scoped_key: str + client: SpendClient, resources: ResourceManager ) -> None: - """Six concurrent calls on one key: every call lands its own spend row under a - distinct request_id and the key aggregate equals the sum of the rows. - Sequential accuracy is covered by test_key_spend_equals_sum_of_logs; this pins - the concurrent increment path (parallel writers racing on one key's counter), - where a lost update can never be reproduced by sequential calls.""" - burst = 6 + from spend_reconciliation import TeamTraffic, assert_logs_match, create_traffic - def call(idx: int) -> Result[ChatResponse]: - return client.chat( - scoped_key, - "gemini-2.5-flash", - f"burst call {idx} {unique_marker()}", - max_tokens=16, - ) + traffic: Final = create_traffic(client, resources) - with ThreadPoolExecutor(max_workers=burst) as pool: - results = tuple(pool.map(call, range(burst))) - failed = [r for r in results if not is_ok(r)] - assert not failed, f"{len(failed)}/{burst} burst calls failed; first: {failed[0]}" + def assert_team(team: TeamTraffic) -> None: + assert_logs_match(client, team) + key_spend: Final = client.poll_key_spend(team.key, minimum=team.spend * 0.999999) + assert isclose(key_spend, team.spend, rel_tol=1e-6, abs_tol=1e-9) - rows = client.poll_logs_for_key( - scoped_key, - min_rows=burst, - predicate=lambda rs: len([r for r in rs if (r.spend or 0) > 0]) >= burst, - ) - costed = [r for r in rows if (r.spend or 0) > 0] - assert len(costed) >= burst, ( - f"only {len(costed)}/{burst} burst calls produced a costed row - " - f"rows lost under concurrency: {_summarize(rows)}" - ) - request_ids = [r.request_id for r in costed] - assert len(set(request_ids)) == len(request_ids), ( - f"concurrent rows collapsed onto shared request_ids: {_summarize(rows)}" - ) - - logs_total = sum((r.spend or 0) for r in rows) - key_spend = client.poll_key_spend(scoped_key, minimum=logs_total * 0.999) - assert _approx_equal(key_spend, logs_total), ( - f"key aggregate {key_spend} != sum of {len(rows)} rows {logs_total} - " - f"spend increments lost under concurrency: {_summarize(rows)}" - ) + for team in traffic: + assert_team(team) @pytest.mark.covers("quota_management.spend_tracking.pagination.keeps_total") diff --git a/tests/e2e/quota_management/spend_tracking/test_team_daily_activity_e2e.py b/tests/e2e/quota_management/spend_tracking/test_team_daily_activity_e2e.py index ed0a6af4ec9..ef635e59743 100644 --- a/tests/e2e/quota_management/spend_tracking/test_team_daily_activity_e2e.py +++ b/tests/e2e/quota_management/spend_tracking/test_team_daily_activity_e2e.py @@ -7,13 +7,18 @@ missing start/end dates are rejected. from __future__ import annotations +import time from datetime import datetime, timedelta, timezone +from math import isclose +from typing import Final import pytest from e2e_http import ProbeResult -from models import DateRangeParams +from lifecycle import ResourceManager +from proxy_client import Converged, await_converged from pydantic import BaseModel from spend_e2e_client import SpendClient +from spend_reconciliation import TeamTraffic, assert_logs_match, create_traffic pytestmark = pytest.mark.e2e @@ -24,22 +29,45 @@ class TeamDailyActivityParams(BaseModel): start_date: str | None = None end_date: str | None = None page: int = 1 + page_size: int = 1 + team_ids: str | None = None class TeamDailyActivityRow(BaseModel): date: str metrics: TeamDailyActivityMetrics + breakdown: TeamDailyActivityBreakdown class TeamDailyActivityMetrics(BaseModel): spend: float total_tokens: int + prompt_tokens: int + completion_tokens: int + api_requests: int + successful_requests: int + failed_requests: int + + +class TeamDailyActivityEntity(BaseModel): + metrics: TeamDailyActivityMetrics + + +class TeamDailyActivityBreakdown(BaseModel): + entities: dict[str, TeamDailyActivityEntity] class TeamDailyActivityMetadata(BaseModel): page: int total_pages: int has_more: bool + total_spend: float + total_prompt_tokens: int + total_completion_tokens: int + total_tokens: int + total_api_requests: int + total_successful_requests: int + total_failed_requests: int class TeamDailyActivityResponse(BaseModel): @@ -47,32 +75,128 @@ class TeamDailyActivityResponse(BaseModel): metadata: TeamDailyActivityMetadata -def _range_days(days: int) -> DateRangeParams: - end = datetime.now(timezone.utc).date() - start = end - timedelta(days=days) - return DateRangeParams(start_date=start.isoformat(), end_date=end.isoformat()) - - def _probe(client: SpendClient, params: BaseModel) -> ProbeResult: return client.proxy.transport.probe(ROUTE, params=params) class TestTeamDailyActivity: + @pytest.mark.replayable @pytest.mark.covers("mgmt.team.daily_activity.happy_path") - @pytest.mark.parametrize("days", [1, 7, 30]) - def test_valid_date_range_returns_results_and_metadata(self, client: SpendClient, days: int) -> None: - result = _probe(client, _range_days(days)) - assert result.status_code == 200, ( - f"{ROUTE} range={days}d must be 200, got {result.status_code}: {result.body[:600]}" + def test_valid_date_range_returns_results_and_metadata( + self, client: SpendClient, resources: ResourceManager + ) -> None: + started: Final = datetime.now(timezone.utc).date() + traffic: Final = create_traffic(client, resources) + for team in traffic: + assert_logs_match(client, team) + ended: Final = datetime.now(timezone.utc).date() + team_ids: Final = ",".join(team.team_id for team in traffic) + + def fetch( + page: int, start: str = (started - timedelta(days=1)).isoformat(), end: str = ended.isoformat() + ) -> TeamDailyActivityResponse: + result: Final = _probe( + client, + TeamDailyActivityParams( + start_date=start, + end_date=end, + page=page, + page_size=1, + team_ids=team_ids, + ), + ) + assert result.status_code == 200, f"daily activity failed: {result.status_code} {result.body[:300]}" + return TeamDailyActivityResponse.model_validate_json(result.body) + + def pages() -> tuple[TeamDailyActivityResponse, ...]: + first: Final = fetch(1) + assert first.metadata.total_pages <= len(traffic) * 2, "unexpected extra scoped daily groups" + return (first, *(fetch(page) for page in range(2, first.metadata.total_pages + 1))) + + outcome: Final = await_converged( + pages, + converged=lambda values: ( + sum(page.metadata.total_api_requests for page in values) >= sum(len(team.responses) for team in traffic) + ), + timeout=client.proxy.poll_timeout, + interval=client.proxy.poll_interval, + now=time.monotonic, + sleep=time.sleep, ) - parsed = TeamDailyActivityResponse.model_validate_json(result.body) - assert parsed.metadata.page == 1 - assert parsed.metadata.total_pages >= 1 - if parsed.results: - first = parsed.results[0] - assert first.date - assert first.metrics.spend >= 0 - assert first.metrics.total_tokens >= 0 + observed: Final = outcome.result if isinstance(outcome, Converged) else outcome.last_result + assert observed is not None, "daily aggregation must return a response before the deadline" + + assert len(observed) >= 2, "two teams must exercise a page boundary" + + def assert_page(index: int, page: TeamDailyActivityResponse) -> None: + assert page.metadata.page == index + assert page.metadata.total_pages == len(observed) + assert page.metadata.has_more == (index < len(observed)) + assert len(page.results) == 1, "each fetched daily group must appear in results" + row: Final = page.results[0] + assert started <= datetime.fromisoformat(row.date).date() <= ended + assert len(row.breakdown.entities) == 1 + assert row.metrics.total_tokens == page.metadata.total_tokens + assert row.metrics.prompt_tokens == page.metadata.total_prompt_tokens + assert row.metrics.completion_tokens == page.metadata.total_completion_tokens + assert row.metrics.api_requests == page.metadata.total_api_requests + assert row.metrics.successful_requests == page.metadata.total_successful_requests + assert row.metrics.failed_requests == page.metadata.total_failed_requests + assert isclose(row.metrics.spend, page.metadata.total_spend, rel_tol=1e-6, abs_tol=1e-9) + + for index, page in enumerate(observed, 1): + assert_page(index, page) + + entities: Final = tuple( + (team_id, entity.metrics) + for page in observed + for row in page.results + for team_id, entity in row.breakdown.entities.items() + ) + assert frozenset(team_id for team_id, _ in entities) == frozenset(team.team_id for team in traffic) + + def assert_team(team: TeamTraffic) -> None: + metrics: Final = tuple(metrics for team_id, metrics in entities if team_id == team.team_id) + assert sum(m.api_requests for m in metrics) == len(team.responses) + assert sum(m.successful_requests for m in metrics) == len(team.responses) + assert sum(m.failed_requests for m in metrics) == 0 + assert sum(m.prompt_tokens for m in metrics) == team.prompt_tokens + assert sum(m.completion_tokens for m in metrics) == team.completion_tokens + assert sum(m.total_tokens for m in metrics) == team.prompt_tokens + team.completion_tokens + assert isclose(sum(m.spend for m in metrics), team.spend, rel_tol=1e-6, abs_tol=1e-9) + + for team in traffic: + assert_team(team) + + assert isclose( + sum(page.metadata.total_spend for page in observed), + sum(team.spend for team in traffic), + rel_tol=1e-6, + abs_tol=1e-9, + ) + assert sum(page.metadata.total_tokens for page in observed) == sum( + team.prompt_tokens + team.completion_tokens for team in traffic + ) + + for days in (7, 30): + assert ( + tuple(fetch(page, (started - timedelta(days=days)).isoformat()) for page in range(1, len(observed) + 1)) + == observed + ), f"{days}-day activity must preserve the same isolated groups and totals" + + empty_date: Final = (started - timedelta(days=7)).isoformat() + empty: Final = fetch(1, empty_date, empty_date) + assert empty.results == [] + assert empty.metadata.total_pages == 0 + assert empty.metadata.page == 1 + assert not empty.metadata.has_more + assert empty.metadata.total_spend == 0 + assert empty.metadata.total_tokens == 0 + assert empty.metadata.total_api_requests == 0 + assert empty.metadata.total_prompt_tokens == 0 + assert empty.metadata.total_completion_tokens == 0 + assert empty.metadata.total_successful_requests == 0 + assert empty.metadata.total_failed_requests == 0 @pytest.mark.covers("mgmt.team.daily_activity.missing_start_date_rejected") def test_missing_start_date_is_rejected(self, client: SpendClient) -> None: diff --git a/tests/e2e/test_e2e_http.py b/tests/e2e/test_e2e_http.py index 81cd6c8d3d1..7201da84924 100644 --- a/tests/e2e/test_e2e_http.py +++ b/tests/e2e/test_e2e_http.py @@ -29,6 +29,7 @@ from e2e_http import ( request_with_retry, streaming_outcome, wire_body, + without_retries, ) from pydantic import BaseModel, TypeAdapter @@ -56,6 +57,15 @@ def _issue_from(responses: Sequence[FakeResponse]) -> Callable[[], FakeResponse] class TestTransientRetryPolicy: + def test_qualification_disables_retries_and_restores_the_default(self) -> None: + responses: Final = (FakeResponse(529), FakeResponse(200)) + sleep: Final = SleepRecorder() + with without_retries(): + assert request_with_retry(_issue_from(responses), sleep=sleep) is responses[0] + assert sleep.delays == () + assert request_with_retry(_issue_from(responses), sleep=sleep) is responses[1] + assert sleep.delays == (0.5,) + def test_transient_set_is_only_statuses_the_proxy_cannot_emit(self) -> None: assert TRANSIENT_STATUSES == frozenset({529}) assert 429 not in TRANSIENT_STATUSES diff --git a/tests/e2e/test_idp.py b/tests/e2e/test_idp.py index 33a09a0f13a..cf2d4f3118a 100644 --- a/tests/e2e/test_idp.py +++ b/tests/e2e/test_idp.py @@ -4,12 +4,20 @@ these carry no `e2e` marker and run everywhere.""" from __future__ import annotations +import os +import signal +import socket +import subprocess +import sys +import time +from builtins import ExceptionGroup from collections.abc import Callable, Generator from contextlib import ExitStack, contextmanager from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer +from pathlib import Path from queue import SimpleQueue from threading import Thread -from typing import Final +from typing import Final, Literal import pytest from e2e_http import ExternalWrite @@ -18,6 +26,8 @@ from idp import ( KEYCLOAK_ADMIN_USER_ENV, KEYCLOAK_REALM_ENV, KEYCLOAK_URL_ENV, + BrowserClientBody, + Discovery, Keycloak, PasswordCredential, UserCreateBody, @@ -60,24 +70,48 @@ def _idp_server( ) -> Generator[tuple[Keycloak, SimpleQueue[str]]]: """Exercise provisioning failures through the same HTTP transport as live tests.""" deletions: SimpleQueue[str] = SimpleQueue() + clients: SimpleQueue[BrowserClientBody] = SimpleQueue() class Handler(BaseHTTPRequestHandler): def log_message(self, format: str, *args: object) -> None: pass def do_POST(self) -> None: - self.rfile.read(int(self.headers.get("Content-Length", "0"))) + body: Final = self.rfile.read(int(self.headers.get("Content-Length", "0"))) if self.path.endswith("/token"): self.send_response(admin_status) self.end_headers() self.wfile.write(b'{"access_token":"synthetic-harness-token"}') else: + if self.path.endswith("/clients"): + clients.put(BrowserClientBody.model_validate_json(body)) self.send_response(user_status if self.path.endswith("/users") else 201) self.send_header("Location", f"{self.path}/resource-1") self.end_headers() if user_status != 201 and self.path.endswith("/users"): self.wfile.write(b"injected create failure") + def do_GET(self) -> None: + self.send_response(200) + self.end_headers() + if "/clients/" in self.path: + client: Final = clients.get_nowait() + clients.put(client) + self.wfile.write(client.model_dump_json(by_alias=True).encode()) + else: + issuer: Final = f"http://127.0.0.1:{server.server_port}/realms/test" + self.wfile.write( + Discovery( + issuer=issuer, + authorization_endpoint=f"{issuer}/auth", + token_endpoint=f"{issuer}/token", + userinfo_endpoint=f"{issuer}/userinfo", + jwks_uri=f"{issuer}/certs", + ) + .model_dump_json() + .encode() + ) + def do_DELETE(self) -> None: deletions.put(self.path) self.send_response(delete_status) @@ -115,6 +149,68 @@ def test_partial_provisioning_removes_the_group_when_user_creation_fails() -> No assert deletions.empty() +@pytest.mark.parametrize( + ("exit_mode", "ignore_termination"), (("normal", False), ("parent", False), ("group", False), ("parent", True)) +) +def test_oidc_launcher_removes_client_on_exit_and_termination( + tmp_path: Path, exit_mode: Literal["normal", "parent", "group"], ignore_termination: bool +) -> None: + ready: Final = tmp_path / "ready" + descendant_command: Final = ( + "import signal,socket,time; from pathlib import Path; " + + ("signal.signal(signal.SIGTERM, signal.SIG_IGN); " if ignore_termination else "") + + "listener=socket.socket(); listener.bind(('127.0.0.1',0)); listener.listen(); " + f"Path({str(ready)!r}).write_text(str(listener.getsockname()[1])); time.sleep(120)" + ) + child_command: Final = ( + "import os,subprocess,sys,time; from pathlib import Path; " + 'assert os.environ["GENERIC_CLIENT_SECRET"]; ' + 'assert os.environ["GENERIC_CLIENT_USE_PKCE"] == "true"; ' + f"subprocess.Popen([sys.executable, '-c', {descendant_command!r}]); " + f"ready=Path({str(ready)!r})\n" + "while not ready.exists(): time.sleep(0.05)\n" + + ("raise SystemExit(7)" if exit_mode == "normal" else "time.sleep(120)") + ) + with _idp_server() as (idp, deletions): + with subprocess.Popen( + [ + sys.executable, + str(Path(__file__).with_name("idp.py")), + "http://127.0.0.1:9999", + sys.executable, + "-c", + child_command, + ], + env={ + **os.environ, + KEYCLOAK_URL_ENV: idp.base_url, + KEYCLOAK_REALM_ENV: idp.realm, + KEYCLOAK_ADMIN_USER_ENV: idp.admin_username, + KEYCLOAK_ADMIN_PASSWORD_ENV: idp.admin_password, + }, + start_new_session=True, + ) as process: + try: + deadline: Final = time.monotonic() + 15 + while not ready.exists() and time.monotonic() < deadline and process.poll() is None: + time.sleep(0.05) + assert ready.exists(), "OIDC child did not start" + if exit_mode == "parent": + process.terminate() + elif exit_mode == "group": + os.killpg(process.pid, signal.SIGTERM) + assert process.wait(timeout=15) == (7 if exit_mode == "normal" else 143) + with socket.socket() as connection: + connection.settimeout(1) + assert connection.connect_ex(("127.0.0.1", int(ready.read_text()))) != 0 + finally: + if process.poll() is None: + os.killpg(process.pid, signal.SIGKILL) + process.wait(timeout=5) + assert deletions.get(timeout=5) == "/admin/realms/test/clients/resource-1" + assert deletions.empty() + + def test_successful_provisioning_cleans_up_user_before_group() -> None: with _idp_server() as (idp, deletions): with ExitStack() as cleanup: @@ -134,6 +230,43 @@ def test_cleanup_failure_is_visible() -> None: idp.delete_group("group") +def test_strict_cleanup_reports_each_failure_and_continues() -> None: + from lifecycle import ResourceManager + from proxy_client import build_proxy_client + + with _idp_server(delete_status=500) as (idp, deletions): + resources: Final = ResourceManager(client=build_proxy_client(), strict_cleanup=True) + strict: Final = idp.with_strict_cleanup() + resources.defer(lambda: strict.delete_group("group")) + resources.defer(lambda: strict.delete_user("user")) + with pytest.raises(ExceptionGroup, match="Resource cleanup failed") as error: + resources.teardown() + assert len(error.value.exceptions) == 2 + assert deletions.get_nowait() == "/admin/realms/test/users/user" + assert deletions.get_nowait() == "/admin/realms/test/groups/group" + + +@pytest.mark.parametrize("groups", ((), ("one",), ("one", "two"))) +def test_provisioning_records_zero_one_or_multiple_groups(groups: tuple[str, ...]) -> None: + with _idp_server() as (idp, deletions): + with ExitStack() as cleanup: + + def defer(callback: Callable[[], object]) -> None: + cleanup.callback(callback) + + identity: Final = idp.provision_groups( + marker="memberships", + groups=groups, + defer=defer, + ) + assert identity.groups == groups + assert len(identity.group_ids) == len(groups) + assert deletions.get_nowait() == "/admin/realms/test/users/resource-1" + for _ in groups: + assert deletions.get_nowait() == "/admin/realms/test/groups/resource-1" + assert deletions.empty() + + def test_expired_admin_credentials_do_not_abort_remaining_cleanups() -> None: with _idp_server(admin_status=401) as (idp, _): cleanup: Final = ExitStack() diff --git a/tests/e2e/test_provider_edge.py b/tests/e2e/test_provider_edge.py index 18f72ac0e7a..81be81e7b59 100644 --- a/tests/e2e/test_provider_edge.py +++ b/tests/e2e/test_provider_edge.py @@ -31,6 +31,7 @@ from concurrent.futures import ThreadPoolExecutor from contextlib import contextmanager from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer from pathlib import Path +from types import MappingProxyType from typing import Final import pytest @@ -81,9 +82,14 @@ def json_object(body: bytes) -> dict[str, object]: class _FakeProvider(ThreadingHTTPServer): daemon_threads = True - def __init__(self, bind: tuple[str, int]) -> None: + def __init__(self, bind: tuple[str, int], *, echo_request: bool = True) -> None: super().__init__(bind, _FakeProviderHandler) self.hits: list[str] = [] + self.echo_request = echo_request + self.requests: tuple[tuple[Mapping[str, str], bytes], ...] = () + + def capture_request(self, headers: Mapping[str, str], body: bytes) -> None: + self.requests = (*self.requests, (MappingProxyType(dict(headers)), body)) class _FakeProviderHandler(BaseHTTPRequestHandler): @@ -101,8 +107,11 @@ class _FakeProviderHandler(BaseHTTPRequestHandler): length = int(self.headers.get("content-length") or "0") body = self.rfile.read(length) if length else b"" provider.hits.append(f"{self.command} {self.path}") - payload = json.dumps( + provider.capture_request(dict(self.headers.items()), body) + payload: Final = json.dumps( {"echo": body.decode("utf-8"), "path": self.path, "hit": len(provider.hits)} + if provider.echo_request + else {"ok": True} ).encode() self.send_response(200) self.send_header("content-type", "application/json") @@ -117,8 +126,8 @@ class _FakeProviderHandler(BaseHTTPRequestHandler): @contextmanager -def fake_provider() -> Generator[_FakeProvider]: - server = _FakeProvider(("127.0.0.1", 0)) +def fake_provider(*, echo_request: bool = True) -> Generator[_FakeProvider]: + server = _FakeProvider(("127.0.0.1", 0), echo_request=echo_request) thread = threading.Thread(target=server.serve_forever, daemon=True) thread.start() try: diff --git a/tests/e2e/test_proxy_client.py b/tests/e2e/test_proxy_client.py index 1b0133f12cb..0c4aed5bd65 100644 --- a/tests/e2e/test_proxy_client.py +++ b/tests/e2e/test_proxy_client.py @@ -11,19 +11,53 @@ injected clock, so nothing here monkeypatches anything. from __future__ import annotations -from collections.abc import Iterable, Mapping +import json +from builtins import ExceptionGroup +from collections.abc import Callable, Generator, Iterable, Mapping +from contextlib import contextmanager from dataclasses import dataclass +from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer from itertools import chain, repeat +from queue import SimpleQueue +from threading import Thread from types import MappingProxyType from typing import Final, cast import pytest from e2e_config import parse_replica_urls -from e2e_http import Result, Success -from models import KeyInfo, KeyInfoResponse, ModelListEntry, ModelsListResponse +from e2e_http import NoBody, Result, Success, without_retries +from idp import Keycloak +from lifecycle import ResourceManager +from management.jwt_actors import ActorFactory +from management.management_client import ManagementClient +from models import ( + ConnectionTestBody, + CredentialCreateBody, + KeyGenerateBody, + KeyInfo, + KeyInfoResponse, + KeyUpdateBody, + LiteLLMParamsBody, + McpServerCreateBody, + McpServerUpdateBody, + ModelListEntry, + ModelsListResponse, + OrgNewBody, + OrgUpdateBody, + SpendLogsParams, + TagNewBody, + TeamNewBody, + TeamUpdateBody, + ToolsetCreateBody, + ToolsetUpdateBody, + UserNewBody, + UserUpdateBody, +) from proxy_client import ( - ConvergeOutcome, + Caller, Converged, + ConvergeOutcome, + CredentialKind, EverywhereConverged, ModelsPoller, NeverConvergedOn, @@ -42,6 +76,115 @@ from proxy_client import ( ) from transport import Transport + +@contextmanager +def caller_boundary( + status: int = 200, bodies: SimpleQueue[bytes] | None = None, *, delete_status: int | None = None +) -> Generator[tuple[ManagementClient, SimpleQueue[str]]]: + received: Final[SimpleQueue[str]] = SimpleQueue() + + class Handler(BaseHTTPRequestHandler): + def log_message(self, format: str, *args: object) -> None: + pass + + def do_GET(self) -> None: + received.put(self.headers.get("Authorization", "")) + self.send_response(delete_status if self.path == "/key/delete" and delete_status is not None else status) + self.end_headers() + self.wfile.write( + b'{"key":"owned","info":{"key_alias":"owned"},"data":[{"id":"owned"}],"team_id":"owned","team_info":{},"model_id":"owned"}' + ) + + def do_POST(self) -> None: + body: Final = self.rfile.read(int(self.headers.get("Content-Length", "0"))) + if bodies is not None: + bodies.put(body) + self.do_GET() + + do_PATCH = do_POST + do_PUT = do_POST + do_DELETE = do_POST + + 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,), master_key="bootstrap" + ) + try: + yield ManagementClient(proxy=proxy, master_key="bootstrap"), received + finally: + server.shutdown() + server.server_close() + thread.join(timeout=5) + + +class TestBoundManagementCaller: + def test_strict_key_cleanup_accepts_missing_only_when_requested(self) -> None: + with caller_boundary(delete_status=404) as (bootstrap, received), without_retries(): + with pytest.raises(AssertionError): + bootstrap.delete_key_strict("owned") + bootstrap.delete_key_strict("owned", missing_ok=True) + assert (received.get_nowait(), received.get_nowait()) == ("Bearer bootstrap", "Bearer bootstrap") + + def test_actor_key_cleanup_reports_failure_and_continues(self) -> None: + with caller_boundary(delete_status=500) as (bootstrap, received), without_retries(): + resources: Final = ResourceManager(client=bootstrap.proxy, strict_cleanup=True) + remaining: SimpleQueue[str] = SimpleQueue() + resources.defer(lambda: remaining.put("cleaned")) + factory: Final = ActorFactory( + bootstrap=bootstrap, + idp=Keycloak(base_url="http://unused.test", realm="test", admin_username="test", admin_password="test"), + resources=resources, + ) + assert factory.key().key == "owned" + with pytest.raises(ExceptionGroup, match="Resource cleanup failed") as failure: + resources.teardown() + assert len(failure.value.exceptions) == 1 + assert remaining.get_nowait() == "cleaned" + assert (received.get_nowait(), received.get_nowait()) == ("Bearer bootstrap", "Bearer bootstrap") + + @pytest.mark.parametrize("kind", ("direct_jwt", "virtual_key", "dashboard_session")) + def test_direct_delegated_and_replica_reads_keep_the_bound_caller(self, kind: CredentialKind) -> None: + with caller_boundary() as (bootstrap, received): + caller: Final = Caller(credential="synthetic-caller", kind=kind, role="internal_user", tenant="tenant-a") + bound: Final = bootstrap.with_caller(caller) + bound.update_key(KeyUpdateBody(key="owned", key_alias="updated")) + bound.proxy.key_info("owned") + bound.proxy.read_back_everywhere( + "/key/info", + params=KeyUpdateBody(key="owned"), + response_type=KeyInfoResponse, + converged=lambda result: isinstance(result, Success), + ) + bound.proxy.read_body_back_everywhere( + "/key/info", KeyInfoResponse, settled=lambda result: result.info.key_alias == "owned" + ) + assert tuple(received.get_nowait() for _ in range(4)) == ("Bearer synthetic-caller",) * 4 + assert received.empty() + bootstrap.proxy.key_info("owned") + assert received.get_nowait() == "Bearer bootstrap" + + def test_explicit_override_wins_without_rebinding_or_changing_master(self) -> None: + with caller_boundary() as (bootstrap, received): + bound: Final = bootstrap.with_caller(Caller(credential="bound", kind="direct_jwt", role="internal_user")) + bound.update_key(KeyUpdateBody(key="owned"), caller_key="override") + bound.proxy.key_info("owned") + assert received.get_nowait() == "Bearer override" + assert received.get_nowait() == "Bearer bound" + assert bound.master_key == "bootstrap" + + def test_credentials_are_absent_from_binding_and_header_diagnostics(self) -> None: + with caller_boundary() as (bootstrap, _): + caller: Final = Caller(credential="private-value", kind="direct_jwt", role="internal_user") + bound: Final = bootstrap.with_caller(caller) + assert "private-value" not in repr(caller) + assert "private-value" not in repr(bound) + assert "private-value" not in repr(bound.proxy.management_headers()) + assert "bootstrap" not in repr(bound) + + MODEL: Final = "gpt-under-test" _NO_TRANSPORTS: Final = cast(Transport, None) TIMEOUT: Final = 10.0 @@ -275,3 +418,166 @@ class TestReplicasFor: client: Final = ProxyClient(transport=_NO_TRANSPORTS, replicas={}, control_replicas={}) with pytest.raises(AssertionError, match="no replica is configured"): _ = client.replicas_for("/v1/models") + + +MANAGEMENT_OPERATIONS: Final[tuple[tuple[str, Callable[[ManagementClient], object]], ...]] = ( + ("generate_key", lambda c: c.generate_key(KeyGenerateBody())), + ("llm_only_key", lambda c: c.llm_only_key()), + ("update_key", lambda c: c.update_key(KeyUpdateBody(key="owned"))), + ("update_key_models", lambda c: c.update_key_models("owned", [])), + ("key_info", lambda c: c.key_info_as("owned")), + ("delete_key_strict", lambda c: c.delete_key_strict("owned")), + ("delete_model_strict", lambda c: c.delete_model_strict("owned")), + ( + "connection_test", + lambda c: c.connection_test( + ConnectionTestBody(litellm_params=LiteLLMParamsBody(model="synthetic"), mode="chat") + ), + ), + ("block_key", lambda c: c.block_key("owned")), + ("regenerate_key", lambda c: c.regenerate_key("owned")), + ("reset_key_spend", lambda c: c.reset_key_spend("owned", 0)), + ("key_list", lambda c: c.key_list("owned")), + ("key_alias_count", lambda c: c.key_alias_count("owned")), + ("create_team", lambda c: c.create_team(TeamNewBody(team_alias="owned"))), + ("update_team", lambda c: c.update_team(TeamUpdateBody(team_id="owned", team_alias="updated"))), + ("delete_team", lambda c: c.delete_team("owned")), + ("team_info", lambda c: c.team_info("owned")), + ("team_list_ids", lambda c: c.team_list_ids()), + ("team_info_status", lambda c: c.team_info_status("owned")), + ("add_team_member", lambda c: c.add_team_member("owned", "user")), + ("delete_team_member", lambda c: c.delete_team_member("owned", "user")), + ("create_user", lambda c: c.create_user(UserNewBody(user_email="actor@example.com", user_role="internal_user"))), + ("create_customer", lambda c: c.create_customer("owned")), + ("customer_info", lambda c: c.customer_info("owned")), + ("delete_customer", lambda c: c.delete_customer("owned")), + ("update_user", lambda c: c.update_user(UserUpdateBody(user_id="owned", user_role="internal_user"))), + ("delete_user", lambda c: c.delete_user("owned")), + ("delete_user_strict", lambda c: c.delete_user_strict("owned")), + ("user_info", lambda c: c.user_info("owned")), + ("user_count", lambda c: c.user_count("owned")), + ("user_list_ids", lambda c: c.user_list_ids("owned")), + ("create_org", lambda c: c.create_org(OrgNewBody(organization_alias="owned"))), + ("update_org", lambda c: c.update_org(OrgUpdateBody(organization_id="owned", organization_alias="updated"))), + ("delete_org", lambda c: c.delete_org("owned")), + ("org_info", lambda c: c.org_info("owned")), + ("org_info_status", lambda c: c.org_info_status("owned")), + ("create_tag", lambda c: c.create_tag(TagNewBody(name="owned"))), + ("delete_tag", lambda c: c.delete_tag("owned")), + ("tag_list", lambda c: c.tag_list()), + ("create_mcp_server", lambda c: c.create_mcp_server(McpServerCreateBody(alias="owned", url="http://example.test"))), + ("update_mcp_server", lambda c: c.update_mcp_server(McpServerUpdateBody(server_id="owned", alias=None))), + ("delete_mcp_server", lambda c: c.delete_mcp_server("owned")), + ("proxy.generate_key", lambda c: c.proxy.generate_key(KeyGenerateBody())), + ("proxy.delete_key", lambda c: c.proxy.delete_key("owned")), + ("proxy.delete_customers", lambda c: c.proxy.delete_customers(["owned"])), + ("proxy.key_info", lambda c: c.proxy.key_info("owned")), + ("proxy.memory_summary", lambda c: c.proxy.memory_summary_everywhere()), + ("proxy.model_info", lambda c: c.proxy.model_info()), + ("proxy.model_cost_map", lambda c: c.proxy.model_cost_map()), + ("proxy.create_model", lambda c: c.proxy.create_model("owned", LiteLLMParamsBody(model="synthetic"))), + ("proxy.update_model", lambda c: c.proxy.update_model("owned", LiteLLMParamsBody(model="synthetic"))), + ("proxy.delete_model", lambda c: c.proxy.delete_model("owned")), + ("proxy.create_toolset", lambda c: c.proxy.create_toolset(ToolsetCreateBody(toolset_name="owned", tools=[]))), + ("proxy.update_toolset", lambda c: c.proxy.update_toolset(ToolsetUpdateBody(toolset_id="owned", description=None))), + ("proxy.delete_toolset", lambda c: c.proxy.delete_toolset("owned")), + ( + "proxy.create_credential", + lambda c: c.proxy.create_credential(CredentialCreateBody(credential_name="owned", credential_values={})), + ), + ("proxy.delete_credential", lambda c: c.proxy.delete_credential("owned")), + ("proxy.create_team", lambda c: c.proxy.create_team(TeamNewBody(team_alias="owned"))), + ("proxy.delete_team", lambda c: c.proxy.delete_team("owned")), + ("proxy.delete_user", lambda c: c.proxy.delete_user("owned")), + ("proxy.spend_logs", lambda c: c.proxy.spend_logs(SpendLogsParams(api_key="owned"))), + ("proxy.probe", lambda c: c.proxy.probe("/user/info", params=NoBody())), +) + + +@pytest.mark.parametrize( + ("name", "operation"), MANAGEMENT_OPERATIONS, ids=tuple(name for name, _ in MANAGEMENT_OPERATIONS) +) +@pytest.mark.parametrize("kind", ("master", "direct_jwt", "virtual_key", "dashboard_session")) +def test_management_operations_send_the_selected_credential( + name: str, + operation: Callable[[ManagementClient], object], + kind: CredentialKind, +) -> None: + with caller_boundary(status=401) as (bootstrap, received), without_retries(): + client: Final = ( + bootstrap + if kind == "master" + else bootstrap.with_caller(Caller(credential=f"synthetic-{kind}", kind=kind, role="internal_user")) + ) + try: + operation(client) + except AssertionError: + pass + expected: Final = "Bearer bootstrap" if kind == "master" else f"Bearer synthetic-{kind}" + assert received.get_nowait() == expected, name + assert received.empty(), "an unauthorized request must not be retried" + + +class TestSplitCallerPropagation: + def test_control_and_data_replica_readers_keep_the_caller(self) -> None: + with caller_boundary() as (data, data_headers), caller_boundary() as (control, control_headers): + data_url: Final = next(iter(data.proxy.replicas)) + control_url: Final = next(iter(control.proxy.replicas)) + proxy: Final = build_proxy_client( + base_url=data_url, + control_plane_base_url=control_url, + replica_urls=(data_url,), + master_key="bootstrap", + ).with_caller(Caller(credential="tenant-token", kind="direct_jwt", role="team_member")) + proxy.key_info("owned") + proxy.read_body_back_everywhere( + "/key/info", KeyInfoResponse, settled=lambda info: info.info.key_alias == "owned" + ) + proxy.read_back_everywhere( + "/key/info", + params=NoBody(), + response_type=KeyInfoResponse, + converged=lambda result: isinstance(result, Success), + ) + assert control_headers.get_nowait() == "Bearer tenant-token" + assert control_headers.get_nowait() == "Bearer tenant-token" + assert data_headers.get_nowait() == "Bearer tenant-token" + assert control_headers.empty() and data_headers.empty() + + def test_successful_team_and_model_polling_uses_the_bound_caller(self) -> None: + with caller_boundary() as (bootstrap, received): + bound: Final = bootstrap.with_caller(Caller(credential="caller", kind="direct_jwt", role="proxy_admin")) + bound.create_team(TeamNewBody(team_alias="owned")) + bound.proxy.create_model("owned", LiteLLMParamsBody(model="synthetic")) + assert tuple(received.get_nowait() for _ in range(4)) == ("Bearer caller",) * 4 + assert received.empty() + + def test_expired_shaped_token_is_sent_once_without_renewal(self) -> None: + with caller_boundary(status=401) as (bootstrap, received): + bound: Final = bootstrap.with_caller( + Caller(credential="expired.payload.signature", kind="direct_jwt", role="internal_user") + ) + result: Final = bound.key_info_as("owned") + assert not isinstance(result, Success) + assert received.get_nowait() == "Bearer expired.payload.signature" + assert received.empty() + + +@pytest.mark.parametrize("operation", ("server", "toolset")) +def test_partial_updates_preserve_explicit_null_at_the_http_boundary(operation: str) -> None: + bodies: Final[SimpleQueue[bytes]] = SimpleQueue() + with caller_boundary(status=401, bodies=bodies) as (bootstrap, _): + try: + if operation == "server": + bootstrap.update_mcp_server(McpServerUpdateBody(server_id="owned", alias=None)) + else: + bootstrap.proxy.update_toolset(ToolsetUpdateBody(toolset_id="owned", description=None)) + except AssertionError: + pass + expected: Final = ( + {"server_id": "owned", "alias": None} + if operation == "server" + else {"toolset_id": "owned", "description": None} + ) + assert json.loads(bodies.get_nowait()) == expected + assert bodies.empty() diff --git a/tests/e2e/transport.py b/tests/e2e/transport.py index e8caa801467..037db0c340f 100644 --- a/tests/e2e/transport.py +++ b/tests/e2e/transport.py @@ -7,11 +7,9 @@ client touches requests.* or builds raw dicts; they pass pydantic models here. from __future__ import annotations -from dataclasses import dataclass +from dataclasses import dataclass, field from typing import Protocol -from pydantic import BaseModel - import e2e_http from e2e_http import ( URL, @@ -21,6 +19,7 @@ from e2e_http import ( Result, StreamingResponse, ) +from pydantic import BaseModel class Transport(Protocol): @@ -85,7 +84,7 @@ class Transport(Protocol): self, path: str, *, headers: BaseModel, json: BaseModel, response_type: type[R] ) -> Result[R]: ... - def probe(self, path: str, *, params: BaseModel) -> ProbeResult: ... + def probe(self, path: str, *, params: BaseModel, headers: BaseModel | None = None) -> ProbeResult: ... def upload[R: BaseModel]( self, @@ -113,7 +112,7 @@ class Transport(Protocol): @dataclass(frozen=True, slots=True) class HttpTransport: base_url: str - master_key: str + master_key: str = field(repr=False) request_timeout: float = 60.0 def _url(self, path: str) -> URL: @@ -245,10 +244,10 @@ class HttpTransport: timeout=self.request_timeout, ) - def probe(self, path: str, *, params: BaseModel) -> ProbeResult: + def probe(self, path: str, *, params: BaseModel, headers: BaseModel | None = None) -> ProbeResult: return e2e_http.probe( self._url(path), - headers=self.master, + headers=self.master if headers is None else headers, params=params, timeout=self.request_timeout, ) @@ -434,8 +433,8 @@ class SplitTransport: path, headers=headers, json=json, params=params, stream=stream ) - def probe(self, path: str, *, params: BaseModel) -> ProbeResult: - return self._route(path).probe(path, params=params) + def probe(self, path: str, *, params: BaseModel, headers: BaseModel | None = None) -> ProbeResult: + return self._route(path).probe(path, params=params, headers=headers) def upload[R: BaseModel]( self, diff --git a/tests/e2e/ui/oidcSetup.ts b/tests/e2e/ui/oidcSetup.ts new file mode 100644 index 00000000000..943fa23cab3 --- /dev/null +++ b/tests/e2e/ui/oidcSetup.ts @@ -0,0 +1,30 @@ +import { chromium, expect } from "@playwright/test"; +import * as fs from "fs"; +import * as path from "path"; + +export default async function oidcSetup() { + const baseURL = process.env.E2E_OIDC_UI_URL; + const issuer = process.env.JWT_ISSUER; + const username = process.env.E2E_OIDC_USERNAME; + const password = process.env.E2E_OIDC_PASSWORD; + if (!baseURL || !issuer || !username || !password) { + throw new Error("The OIDC setup requires a running stack, issuer, and provisioned actor credentials"); + } + const artifactDir = process.env.E2E_UI_ARTIFACT_DIR || "."; + fs.mkdirSync(artifactDir, { recursive: true }); + const browser = await chromium.launch(); + try { + const page = await browser.newPage(); + await page.goto(`${baseURL.replace(/\/$/, "")}/sso/key/generate`); + await expect(page).toHaveURL(new RegExp(`^${issuer.replace(/[.*+?^${}()|[\]\\]/g, "\\$&")}/`)); + await page.getByLabel("Username or email").fill(username); + await page.getByLabel("Password", { exact: true }).fill(password); + await page.getByRole("button", { name: "Sign In", exact: true }).click(); + await page.waitForURL((url) => url.origin === new URL(baseURL).origin && url.pathname.startsWith("/ui")); + const statePath = path.join(artifactDir, "oidc.storageState.json"); + await page.context().storageState({ path: statePath }); + fs.chmodSync(statePath, 0o600); + } finally { + await browser.close(); + } +} diff --git a/tests/e2e/ui/playwright.oidc.config.ts b/tests/e2e/ui/playwright.oidc.config.ts new file mode 100644 index 00000000000..0fbe77e9bd2 --- /dev/null +++ b/tests/e2e/ui/playwright.oidc.config.ts @@ -0,0 +1,22 @@ +import { defineConfig, devices } from "@playwright/test"; +import * as path from "path"; + +const baseURL = process.env.E2E_OIDC_UI_URL; +if (!baseURL) throw new Error("E2E_OIDC_UI_URL must point to the running OIDC stack"); + +export default defineConfig({ + testDir: ".", + testMatch: "oidc/**/*.spec.ts", + retries: 0, + workers: 1, + outputDir: path.join(process.env.E2E_UI_ARTIFACT_DIR || ".", "oidc", "test-results"), + globalSetup: require.resolve("./oidcSetup"), + use: { + ...devices["Desktop Chrome"], + baseURL, + storageState: path.join(process.env.E2E_UI_ARTIFACT_DIR || ".", "oidc.storageState.json"), + trace: "off", + screenshot: "off", + video: "off", + }, +}); diff --git a/tests/integration/README.md b/tests/integration/README.md new file mode 100644 index 00000000000..5af4fdb9d06 --- /dev/null +++ b/tests/integration/README.md @@ -0,0 +1,19 @@ +# Integration contracts + +These tests exercise a running gateway, PostgreSQL and Redis with an owned local upstream. CircleCI owns this suite. Tests are grouped by behavior, with no automatic test retries or fallback to paid provider calls + +Use `tests/integration/run.py management`, `accounting` or `providers` to run a selected group. Set `INTEGRATION_PROXY_URL`, `INTEGRATION_UPSTREAM_URL`, `INTEGRATION_MASTER_KEY` and `DATABASE_URL` to an isolated test deployment. The runner selects the new domain directories explicitly; the legacy OCI and sandbox selections remain separate + +Management also requires `INTEGRATION_PEER_URL`, `REDIS_HOST` and `REDIS_PORT`. CircleCI starts two directly addressed proxy processes sharing only that job's stores. The test-only CLI wrapper supplies enterprise route entitlement, following the existing behavior suite's convention. It does not qualify license validation; run it with one worker and no reload + +The generated lifecycle models use 20 examples, eight steps, generation and shrinking, with isolated resources per example. HTTP operation caps include generation and shrinking and exempt cleanup. Local qualification defaults to seed 4106601; CircleCI derives its exploration seed from the checked-out revision. Use `--seed` to reproduce a run. Actual installed Hypothesis version, settings and seed are written beside the execution manifest + +Reuse the existing canned provider handlers through `_support/upstream.py`. It rejects internal request fields and exposes actual received requests for independent assertions. Register every created resource for cleanup immediately, keep expected values independent of production calculations, and assert readback plus the runtime effect of a change + +The CircleCI workflow starts its own database and Redis, restricts test-phase egress to its owned services and writes JUnit plus an executed-node manifest. Missing setup, skipped tests, failed cleanup or a selected test without a passed call fail qualification. Existing GitHub Actions jobs do not own these tests + +Define integration contract IDs and their canonical test nodes in `contracts.json`. Every node must declare the same IDs with `covers`. The runner checks exact collected and passed selections against that mapping. These IDs belong to this CircleCI suite and must not be added to the separate E2E coverage registry. A manifest declaration alone does not mean a test passed + +Provider sentinels currently use the controlled server, not live recordings. The provider shard also runs the existing strict replay controls for changed requests, exhausted interactions, leftover interactions and no provider connection. Future recorded scenarios must use that replay-only implementation; missing recordings cannot fall back to a real provider. The observation endpoint is destructive and the current selection runs serially against one owned upstream + +Fixtures must contain synthetic data only. Keep private incident records and source documents out of code, fixtures, logs and PR descriptions diff --git a/tests/integration/__init__.py b/tests/integration/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/integration/_support/__init__.py b/tests/integration/_support/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/tests/integration/_support/client.py b/tests/integration/_support/client.py new file mode 100644 index 00000000000..8d6744c60a2 --- /dev/null +++ b/tests/integration/_support/client.py @@ -0,0 +1,170 @@ +from __future__ import annotations + +import os +import time +import uuid +from hashlib import sha256 +from collections.abc import Callable, Iterator, Mapping +from contextlib import ExitStack, contextmanager +from dataclasses import dataclass +from typing import Final, TypeVar + +import httpx +from pydantic import JsonValue, TypeAdapter + +from integration._support.database import read_rows + +JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) +T = TypeVar("T") + + +def object_value(value: JsonValue) -> dict[str, JsonValue]: + return JSON_OBJECT.validate_python(value) + + +def string_value(value: JsonValue) -> str: + assert isinstance(value, str), f"Expected a string, received {type(value).__name__}" + return value + + +def eventually(read: Callable[[], T], satisfied: Callable[[T], bool], seconds: float = 10) -> T: + deadline: Final = time.monotonic() + seconds + while True: + observed: Final = read() + if satisfied(observed): + return observed + assert time.monotonic() < deadline, f"State did not converge: {observed!r}" + time.sleep(0.1) + + +@dataclass(frozen=True, slots=True) +class Gateway: + client: httpx.Client + key: str + upstream_url: str + + def request( + self, + method: str, + path: str, + body: Mapping[str, JsonValue] | None = None, + *, + key: str | None = None, + params: Mapping[str, str] | None = None, + ) -> httpx.Response: + return self.client.request( + method, + path, + json=body, + params=params, + headers={"Authorization": f"Bearer {self.key if key is None else key}"}, + ) + + def post(self, path: str, body: Mapping[str, JsonValue], *, key: str | None = None) -> dict[str, JsonValue]: + response: Final = self.request("POST", path, body, key=key) + assert response.status_code == 200, f"POST {path}: {response.status_code} {response.text}" + return JSON_OBJECT.validate_json(response.content) + + def get(self, path: str, params: Mapping[str, str] | None = None) -> dict[str, JsonValue]: + response: Final = self.request("GET", path, params=params) + assert response.status_code == 200, f"GET {path}: {response.status_code} {response.text}" + return JSON_OBJECT.validate_json(response.content) + + def chat(self, model: str, *, key: str | None = None, text: str = "integration control") -> dict[str, JsonValue]: + return self.post( + "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": text}]}, + key=key, + ) + + @contextmanager + def scenario(self) -> Iterator[Scenario]: + with ExitStack() as cleanups: + yield Scenario(self, cleanups) + + +@dataclass(frozen=True, slots=True) +class Scenario: + gateway: Gateway + cleanups: ExitStack + + def key(self, **fields: JsonValue) -> str: + created: Final = self.gateway.post("/key/generate", fields) + token: Final = string_value(created["key"]) + self.cleanups.callback(self.delete_key, token) + return token + + def team(self, **fields: JsonValue) -> str: + created: Final = self.gateway.post("/team/new", {"team_alias": f"integration-{uuid.uuid4().hex}", **fields}) + identity: Final = string_value(created["team_id"]) + self.cleanups.callback(self.delete_team, identity) + return identity + + def delete_team(self, identity: str) -> None: + self.gateway.post("/team/delete", {"team_ids": [identity]}) + assert read_rows('SELECT team_id FROM "LiteLLM_TeamTable" WHERE team_id = %s', (identity,)) == [] + + def project(self, team_id: str, **fields: JsonValue) -> str: + created: Final = self.gateway.post( + "/project/new", {"team_id": team_id, "project_alias": f"integration-{uuid.uuid4().hex}", **fields} + ) + identity: Final = string_value(created["project_id"]) + self.cleanups.callback(self.delete_project, identity) + return identity + + def delete_project(self, identity: str) -> None: + response: Final = self.gateway.request("DELETE", "/project/delete", {"project_ids": [identity]}) + assert response.status_code == 200, response.text + assert read_rows('SELECT project_id FROM "LiteLLM_ProjectTable" WHERE project_id = %s', (identity,)) == [] + + def user(self, **fields: JsonValue) -> str: + created: Final = self.gateway.post( + "/user/new", {"user_id": f"integration-{uuid.uuid4().hex}", "auto_create_key": False, **fields} + ) + identity: Final = string_value(created["user_id"]) + self.cleanups.callback(self.delete_user, identity) + return identity + + def delete_user(self, identity: str) -> None: + response: Final = self.gateway.request("POST", "/user/delete", {"user_ids": [identity]}) + assert response.status_code == 200 and response.json() == 1, response.text + assert read_rows('SELECT user_id FROM "LiteLLM_UserTable" WHERE user_id = %s', (identity,)) == [] + + def delete_key(self, token: str) -> None: + self.gateway.post("/key/delete", {"keys": [token]}) + response: Final = self.gateway.request("GET", "/key/info", params={"key": sha256(token.encode()).hexdigest()}) + assert response.status_code == 404, f"Deleted key remains readable: {response.status_code}" + + def delete_model(self, identity: str) -> None: + self.gateway.post("/model/delete", {"id": identity}) + entries: Final = self.gateway.get("/model/info")["data"] + assert isinstance(entries, list) + assert all(object_value(object_value(entry)["model_info"])["id"] != identity for entry in entries) + assert read_rows('SELECT model_id FROM "LiteLLM_ProxyModelTable" WHERE model_id = %s', (identity,)) == [] + + def model(self, **parameters: JsonValue) -> str: + name: Final = f"integration-{uuid.uuid4().hex}" + created: Final = self.gateway.post( + "/model/new", + { + "model_name": name, + "litellm_params": { + "model": "openai/gpt-4o-mini", + "api_key": "integration-provider-key", + "api_base": f"{self.gateway.upstream_url}/v1", + **parameters, + }, + "model_info": {}, + }, + ) + identity: Final = string_value(object_value(created["model_info"])["id"]) + self.cleanups.callback(self.delete_model, identity) + return name + + +@contextmanager +def gateway_from_environment() -> Iterator[Gateway]: + url: Final = os.environ["INTEGRATION_PROXY_URL"] + upstream: Final = os.environ["INTEGRATION_UPSTREAM_URL"] + with httpx.Client(base_url=url, timeout=15, trust_env=False) as client: + yield Gateway(client, os.environ["INTEGRATION_MASTER_KEY"], upstream) diff --git a/tests/integration/_support/database.py b/tests/integration/_support/database.py new file mode 100644 index 00000000000..283d26a632e --- /dev/null +++ b/tests/integration/_support/database.py @@ -0,0 +1,14 @@ +import os +from typing import Final + +import psycopg +from psycopg.rows import dict_row +from pydantic import JsonValue, TypeAdapter + +ROWS: Final = TypeAdapter(list[dict[str, JsonValue]]) + + +def read_rows(query: str, parameters: tuple[str, ...]) -> list[dict[str, JsonValue]]: + with psycopg.connect(os.environ["DATABASE_URL"], row_factory=dict_row) as connection: + connection.execute("SET TRANSACTION READ ONLY") + return ROWS.validate_python(connection.execute(query, parameters).fetchall()) diff --git a/tests/integration/_support/generation.py b/tests/integration/_support/generation.py new file mode 100644 index 00000000000..afb3ec2e768 --- /dev/null +++ b/tests/integration/_support/generation.py @@ -0,0 +1,52 @@ +from typing import Final +from dataclasses import dataclass +from collections.abc import Iterator, Sequence +from contextlib import contextmanager + +import httpx +from hypothesis import Phase, settings + +from integration._support.client import Gateway + +LIFECYCLE_SETTINGS: Final = settings( + max_examples=20, + stateful_step_count=8, + deadline=None, + database=None, + phases=(Phase.generate, Phase.shrink), + print_blob=True, +) + + +@dataclass(slots=True) +class RequestBudget: + limit: int + requests: int = 0 + cleaning: bool = False + + def observe(self, _request: httpx.Request) -> None: + if self.cleaning: + return + self.requests += 1 + assert self.requests <= self.limit, f"Generated HTTP operation budget exceeded: {self.limit}" + + @contextmanager + def cleanup(self) -> Iterator[None]: + self.cleaning = True + try: + yield + finally: + self.cleaning = False + + +@contextmanager +def bounded_http_requests(gateways: Sequence[Gateway], limit: int) -> Iterator[RequestBudget]: + budget: Final = RequestBudget(limit) + for gateway in gateways: + gateway.client.event_hooks["request"].append(budget.observe) + try: + yield budget + finally: + for gateway in gateways: + gateway.client.event_hooks["request"].remove(budget.observe) + print(f"Generated HTTP operations: {budget.requests}/{budget.limit}; cleanup excluded") diff --git a/tests/integration/_support/manifest.py b/tests/integration/_support/manifest.py new file mode 100644 index 00000000000..b3a82fa4cdd --- /dev/null +++ b/tests/integration/_support/manifest.py @@ -0,0 +1,31 @@ +import json +from pathlib import Path +from typing import Final + +from pydantic import TypeAdapter + +MAPPING: Final = TypeAdapter(dict[str, tuple[str, ...]]) +OWNED_DIRECTORIES: Final = frozenset( + { + "management", + "authorization", + "database", + "pricing", + "spend", + "routing", + "providers", + "streaming", + "configuration", + "mcp", + "observability", + "compatibility", + } +) + + +def contracts() -> dict[str, tuple[str, ...]]: + document: Final = json.loads((Path(__file__).resolve().parents[1] / "contracts.json").read_bytes()) + result: Final = MAPPING.validate_python(document["tests"]) + if not result or any(not values or any(not value.strip() for value in values) for values in result.values()): + raise ValueError("Integration manifest must contain nodes with contract IDs") + return result diff --git a/tests/integration/_support/proxy.py b/tests/integration/_support/proxy.py new file mode 100644 index 00000000000..3139beaeb01 --- /dev/null +++ b/tests/integration/_support/proxy.py @@ -0,0 +1,16 @@ +"""Run the normal single-process CLI with the existing behavior-suite test entitlement.""" + +from unittest.mock import patch + +from litellm import run_server + + +def main() -> None: + with patch( # test-quality-ok: route entitlement only; license validation is outside these HTTP/DB contracts + "litellm.proxy.auth.litellm_license.LicenseCheck.is_premium", return_value=True + ): + run_server() + + +if __name__ == "__main__": + main() diff --git a/tests/integration/_support/upstream.py b/tests/integration/_support/upstream.py new file mode 100644 index 00000000000..8bc4100abfd --- /dev/null +++ b/tests/integration/_support/upstream.py @@ -0,0 +1,122 @@ +from __future__ import annotations + +import argparse +from dataclasses import dataclass, field +from collections import deque +from queue import SimpleQueue +from typing import Final + +import uvicorn +from pydantic import JsonValue, TypeAdapter +from starlette.applications import Starlette +from starlette.requests import Request +from starlette.responses import JSONResponse, Response +from starlette.routing import Route + +from _fake_openai_endpoint_server import chat_completions, completions, embeddings, health, moderations + +JSON_OBJECT: Final = TypeAdapter(dict[str, JsonValue]) +INTERNAL_FIELDS: Final = frozenset( + { + "litellm_params", + "litellm_logging_obj", + "litellm_call_id", + "litellm_metadata", + "proxy_server_request", + "rpm", + "tpm", + "timeout", + "stream_chunk_size", + } +) + + +@dataclass(frozen=True, slots=True) +class Observation: + path: str + authorization: str + body: dict[str, JsonValue] + + +@dataclass(frozen=True, slots=True) +class Provider: + observations: SimpleQueue[Observation] = field(default_factory=SimpleQueue) + scripts: dict[str, deque[int]] = field(default_factory=dict) + + async def chat(self, request: Request) -> Response: + body: Final = JSON_OBJECT.validate_json(await request.body()) + self.observations.put(Observation(request.url.path, request.headers.get("authorization", ""), body)) + leaked: Final = tuple(sorted(INTERNAL_FIELDS.intersection(body))) + if leaked: + return JSONResponse({"error": {"message": f"Unexpected provider fields: {leaked}"}}, status_code=400) + messages: Final = body.get("messages") + if not isinstance(body.get("model"), str) or not isinstance(messages, list) or not messages: + return JSONResponse({"error": {"message": "model and nonempty messages are required"}}, status_code=400) + if any( + not isinstance(message, dict) + or message.get("role") not in {"system", "developer", "user", "assistant", "tool"} + or "content" not in message + for message in messages + ): + return JSONResponse({"error": {"message": "Invalid selected message contract"}}, status_code=400) + script: Final = self.scripts.get(str(body["model"])) + if script is not None: + if not script: + return JSONResponse({"error": {"message": "Script exhausted", "type": "api_error"}}, status_code=500) + status: Final = script.popleft() + if status != 200: + return JSONResponse( + {"error": {"message": "Controlled provider failure", "type": "api_error", "code": str(status)}}, + status_code=status, + ) + return await chat_completions(request) + + async def script(self, request: Request) -> Response: + name: Final = request.path_params["model"] + if request.method in {"DELETE", "GET"} and name not in self.scripts: + return JSONResponse({"error": "Script not found"}, status_code=404) + if request.method == "GET": + return JSONResponse({"remaining": list(self.scripts[name])}) + if request.method == "DELETE": + remaining: Final = self.scripts.pop(name) + return JSONResponse({"remaining": list(remaining)}) + body: Final = JSON_OBJECT.validate_json(await request.body()) + statuses: Final = body.get("statuses") + if not isinstance(statuses, list) or not statuses or any(type(value) is not int for value in statuses): + return JSONResponse({"error": "A nonempty list of HTTP status codes is required"}, status_code=400) + self.scripts[name] = deque(int(str(value)) for value in statuses) + return JSONResponse({"configured": len(statuses)}) + + async def observed(self, _request: Request) -> Response: + values: Final = tuple(self.observations.get() for _ in range(self.observations.qsize())) + return JSONResponse( + { + "requests": [ + {"path": value.path, "authorization": value.authorization, "body": value.body} for value in values + ] + } + ) + + def app(self) -> Starlette: + return Starlette( + routes=[ + Route("/health", health), + Route("/__observations", self.observed), + Route("/__scripts/{model}", self.script, methods=["POST", "DELETE", "GET"]), + Route("/v1/chat/completions", self.chat, methods=["POST"]), + Route("/v1/completions", completions, methods=["POST"]), + Route("/v1/embeddings", embeddings, methods=["POST"]), + Route("/v1/moderations", moderations, methods=["POST"]), + ] + ) + + +def main() -> None: + parser: Final = argparse.ArgumentParser() + parser.add_argument("--port", type=int, default=8190) + arguments: Final = parser.parse_args() + uvicorn.run(Provider().app(), host="127.0.0.1", port=arguments.port, access_log=False) + + +if __name__ == "__main__": + main() diff --git a/tests/integration/authorization/test_warmed_policy.py b/tests/integration/authorization/test_warmed_policy.py new file mode 100644 index 00000000000..fd4271dbc41 --- /dev/null +++ b/tests/integration/authorization/test_warmed_policy.py @@ -0,0 +1,197 @@ +from contextlib import ExitStack +from hashlib import sha256 +from typing import Final +import os + +import psycopg +import pytest +from hypothesis import strategies as st +from hypothesis.stateful import RuleBasedStateMachine, invariant, rule, run_state_machine_as_test + +from integration._support.client import Gateway, eventually, object_value +from integration._support.database import read_rows +from integration._support.generation import LIFECYCLE_SETTINGS, bounded_http_requests + + +def assert_serving(gateway: Gateway, model: str, key: str, status: int, error_type: str = "auth_error") -> None: + response: Final = eventually( + lambda: gateway.request( + "POST", "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": "warmed policy control"}]}, key=key, + ), + lambda value: value.status_code == status, + seconds=3, + ) + if status == 200: + assert response.json()["usage"]["total_tokens"] == 40 + assert response.json()["choices"][0]["message"]["content"] == ( + "Hello! This is a mock response from the fake OpenAI endpoint." + ) + else: + assert response.json()["error"]["type"] == error_type + + +@pytest.mark.covers("mgmt.key.update.two_workers_enforce_warmed_policy") +def test_generated_policy_changes_reach_both_warmed_workers(gateway: Gateway, peer: Gateway) -> None: + class Policies(RuleBasedStateMachine): + def __init__(self) -> None: + super().__init__() + self.resources = ExitStack() + try: + scenario = self.resources.enter_context(gateway.scenario()) + self.models = (scenario.model(), scenario.model()) + self.allowed = 0 + self.blocked = False + self.key = scenario.key(models=[self.models[0]], blocked=False) + self.control = scenario.key(models=list(self.models)) + for worker in (gateway, peer): + assert_serving(worker, self.models[0], self.key, 200) + assert_serving(worker, self.models[1], self.control, 200) + except BaseException: + with budget.cleanup(): + self.resources.close() + raise + + @rule(index=st.integers(min_value=0, max_value=1)) + def model_grant(self, index: int) -> None: + gateway.post("/key/update", {"key": self.key, "models": [self.models[index]]}) + self.allowed = index + + @rule(blocked=st.booleans()) + def block(self, blocked: bool) -> None: + gateway.post("/key/update", {"key": self.key, "blocked": blocked}) + self.blocked = blocked + + @invariant() + def both_workers_enforce_policy(self) -> None: + rows: Final = read_rows( + 'SELECT models, blocked FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(self.key.encode()).hexdigest(),), + ) + assert rows == [{"models": [self.models[self.allowed]], "blocked": self.blocked}] + for worker in (gateway, peer): + for index, model in enumerate(self.models): + status: Final = 401 if self.blocked else 200 if index == self.allowed else 403 + kind: Final = "auth_error" if self.blocked else "key_model_access_denied" + assert_serving(worker, model, self.key, status, kind) + assert_serving(worker, self.models[1], self.control, 200) + + def teardown(self) -> None: + with budget.cleanup(): + self.resources.close() + + with bounded_http_requests((gateway, peer), limit=3000) as budget: + run_state_machine_as_test(Policies, settings=LIFECYCLE_SETTINGS) + + +@pytest.mark.covers("mgmt.user.scim.deactivation_includes_nullable_blocked_keys") +def test_scim_deactivation_blocks_null_and_false_keys_but_preserves_other_owners(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + model: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + other: Final = scenario.user(user_role="internal_user") + null_key: Final = scenario.key(user_id=user, models=[model]) + false_key: Final = scenario.key(user_id=user, models=[model], blocked=False) + manual: Final = scenario.key(user_id=user, models=[model], blocked=True) + control: Final = scenario.key(user_id=other, models=[model]) + team: Final = scenario.team(models=[model]) + service: Final = gateway.post("/key/service-account/generate", {"team_id": team, "models": [model]}) + service_key: Final = service["key"] + assert isinstance(service_key, str) + scenario.cleanups.callback(scenario.delete_key, service_key) + with psycopg.connect(os.environ["DATABASE_URL"]) as connection: + connection.execute( + 'UPDATE "LiteLLM_VerificationToken" SET blocked = NULL WHERE token = %s', + (sha256(null_key.encode()).hexdigest(),), + ) + assert read_rows( + 'SELECT user_id, blocked FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(null_key.encode()).hexdigest(),), + ) == [{"user_id": user, "blocked": None}] + assert read_rows( + 'SELECT user_id FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(service_key.encode()).hexdigest(),), + ) == [{"user_id": None}] + for token in (null_key, false_key, control, service_key): + assert_serving(gateway, model, token, 200) + for active in (False, True): + response: Final = gateway.request( + "PATCH", f"/scim/v2/Users/{user}", + {"schemas": ["urn:ietf:params:scim:api:messages:2.0:PatchOp"], + "Operations": [{"op": "replace", "path": "active", "value": active}]}, + ) + assert response.status_code == 200, response.text + for token in (null_key, false_key): + rows: Final = read_rows( + 'SELECT blocked, metadata FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(token.encode()).hexdigest(),), + ) + assert rows[0]["blocked"] is not active + assert object_value(rows[0]["metadata"]).get("scim_blocked") is (None if active else True) + assert_serving(gateway, model, token, 200 if active else 401) + assert_serving(gateway, model, manual, 401) + for token in (control, service_key): + assert_serving(gateway, model, token, 200) + + +@pytest.mark.covers("mgmt.team.member_update.demoted_role_cannot_write") +def test_warmed_team_role_demotion_prevents_later_management_writes(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + model: Final = scenario.model() + user: Final = scenario.user(user_role="internal_user") + team: Final = scenario.team(models=[model], members_with_roles=[{"user_id": user, "role": "admin"}]) + control_team: Final = scenario.team(models=[model]) + caller: Final = scenario.key( + user_id=user, team_id=team, models=[model], allowed_routes=["/team/update", "/v1/chat/completions"] + ) + gateway.chat(model, key=caller) + changed: Final = gateway.request("POST", "/team/update", {"team_id": team, "team_alias": "permitted"}, key=caller) + assert changed.status_code == 200, changed.text + unrelated_before: Final = read_rows( + 'SELECT team_alias FROM "LiteLLM_TeamTable" WHERE team_id = %s', (control_team,) + ) + unrelated: Final = gateway.request( + "POST", "/team/update", {"team_id": control_team, "team_alias": "must-not-persist"}, key=caller + ) + assert unrelated.status_code == 403, unrelated.text + assert read_rows( + 'SELECT team_alias FROM "LiteLLM_TeamTable" WHERE team_id = %s', (control_team,) + ) == unrelated_before + gateway.post("/team/member_update", {"team_id": team, "user_id": user, "role": "user"}) + for target in (team, control_team): + before: Final = read_rows('SELECT team_alias FROM "LiteLLM_TeamTable" WHERE team_id = %s', (target,)) + denied: Final = gateway.request( + "POST", "/team/update", {"team_id": target, "team_alias": "must-not-persist"}, key=caller + ) + assert denied.status_code == 403, denied.text + assert read_rows('SELECT team_alias FROM "LiteLLM_TeamTable" WHERE team_id = %s', (target,)) == before + roster: Final = read_rows('SELECT members_with_roles FROM "LiteLLM_TeamTable" WHERE team_id = %s', (team,)) + members: Final = roster[0]["members_with_roles"] + assert isinstance(members, list) + assert next(object_value(member)["role"] for member in members if object_value(member)["user_id"] == user) == "user" + assert_serving(gateway, model, caller, 200) + + +@pytest.mark.covers("mgmt.key.update.expiry_changes_reach_warmed_workers") +def test_expiry_and_explicit_clear_reach_both_warmed_workers(gateway: Gateway, peer: Gateway) -> None: + with gateway.scenario() as scenario: + model: Final = scenario.model() + key: Final = scenario.key(models=[model], duration="1h") + control: Final = scenario.key(models=[model]) + for worker in (gateway, peer): + assert_serving(worker, model, key, 200) + gateway.post("/key/update", {"key": key, "duration": "0s"}) + assert read_rows( + "SELECT expires <= timezone('UTC', now()) AS expired FROM \"LiteLLM_VerificationToken\" WHERE token = %s", + (sha256(key.encode()).hexdigest(),), + ) == [{"expired": True}] + for worker in (gateway, peer): + assert_serving(worker, model, key, 401, "expired_key") + assert_serving(worker, model, control, 200) + gateway.post("/key/update", {"key": key, "duration": None}) + assert read_rows( + 'SELECT expires IS NULL AS cleared FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(key.encode()).hexdigest(),), + ) == [{"cleared": True}] + for worker in (gateway, peer): + assert_serving(worker, model, key, 200) diff --git a/tests/integration/configuration/test_effective_settings.py b/tests/integration/configuration/test_effective_settings.py new file mode 100644 index 00000000000..7fa440d1d8d --- /dev/null +++ b/tests/integration/configuration/test_effective_settings.py @@ -0,0 +1,123 @@ +import uuid +from typing import Final + +import httpx +import pytest + +from integration._support.client import Gateway, object_value, string_value +from integration._support.database import read_rows + + +def model_identity(gateway: Gateway, alias: str) -> str: + entries: Final = gateway.get("/model/info")["data"] + assert isinstance(entries, list) + entry: Final = next(object_value(value) for value in entries if object_value(value)["model_name"] == alias) + return string_value(object_value(entry["model_info"])["id"]) + + +@pytest.mark.covers("mgmt.model.block.changes_serving_and_preserves_control") +def test_model_block_changes_actual_route_and_leaves_other_route_working(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + model: Final = scenario.model() + other: Final = scenario.model() + identity: Final = model_identity(gateway, model) + gateway.chat(model) + gateway.chat(other) + gateway.post("/model/block", {"model_id": identity}) + assert read_rows( + 'SELECT blocked FROM "LiteLLM_ProxyModelTable" WHERE model_id = %s', (identity,) + ) == [{"blocked": True}] + response: Final = gateway.request( + "POST", "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": "blocked deployment"}]}, + ) + assert response.status_code == 403, response.text + assert response.json()["error"]["type"] == "permission_error" + assert response.json()["error"]["message"] == "litellm.PermissionDeniedError: Model is blocked" + assert object_value(gateway.chat(other)["usage"])["total_tokens"] == 40 + gateway.post("/model/unblock", {"model_id": identity}) + assert read_rows( + 'SELECT blocked FROM "LiteLLM_ProxyModelTable" WHERE model_id = %s', (identity,) + ) == [{"blocked": False}] + assert object_value(gateway.chat(model)["usage"])["total_tokens"] == 40 + + +@pytest.mark.covers("mgmt.router_settings.update.changes_observed_attempt_count") +def test_saved_retry_setting_controls_real_attempts_and_restores(gateway: Gateway) -> None: + with httpx.Client(base_url=gateway.upstream_url, timeout=5, trust_env=False) as upstream, gateway.scenario() as scenario: + original: Final = object_value(gateway.get("/router/settings")["current_values"])["num_retries"] + provider_model: Final = f"retry-{uuid.uuid4().hex}" + model: Final = scenario.model(model=f"openai/{provider_model}", input_cost_per_token=0, output_cost_per_token=0) + + def remove_script() -> None: + response: Final = upstream.delete(f"/__scripts/{provider_model}") + assert response.status_code in (200, 404), response.text + assert upstream.get(f"/__scripts/{provider_model}").status_code == 404 + + scenario.cleanups.callback(remove_script) + try: + for generation, retries in enumerate((0, 1, original)): + gateway.post("/config/update", {"router_settings": {"num_retries": retries}}) + assert object_value(gateway.get("/router/settings")["current_values"])["num_retries"] == retries + configured: Final = upstream.post(f"/__scripts/{provider_model}", json={"statuses": [500, 200]}) + assert configured.status_code == 200, configured.text + upstream.get("/__observations").raise_for_status() + response: Final = gateway.request( + "POST", "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": f"{provider_model} attempt {generation}"}]}, + ) + observed: Final = upstream.get("/__observations") + observed.raise_for_status() + requests: Final = observed.json()["requests"] + assert len(requests) == (1 if retries == 0 else 2), (response.status_code, response.text, requests) + assert all(value["body"]["model"] == provider_model for value in requests) + assert response.status_code == (500 if retries == 0 else 200), response.text + if retries != 0: + assert response.json()["usage"]["total_tokens"] == 40 + remaining: Final = upstream.delete(f"/__scripts/{provider_model}") + assert remaining.status_code == 200, remaining.text + assert remaining.json()["remaining"] == ([200] if retries == 0 else []) + finally: + gateway.post("/config/update", {"router_settings": {"num_retries": original}}) + assert object_value(gateway.get("/router/settings")["current_values"])["num_retries"] == original + + +@pytest.mark.covers("mgmt.credential.update.saved_value_reaches_wire") +def test_credential_value_update_and_model_reload_reach_provider(gateway: Gateway) -> None: + with gateway.scenario() as scenario, httpx.Client(base_url=gateway.upstream_url, timeout=5, trust_env=False) as upstream: + name: Final = f"credential-{uuid.uuid4().hex}" + gateway.post("/credentials", { + "credential_name": name, "credential_values": {"api_key": "synthetic-credential-first"}, "credential_info": {} + }) + + def remove_credential() -> None: + response: Final = gateway.request("DELETE", f"/credentials/{name}") + assert response.status_code == 200, response.text + assert read_rows( + 'SELECT credential_name FROM "LiteLLM_CredentialsTable" WHERE credential_name = %s', (name,) + ) == [] + + scenario.cleanups.callback(remove_credential) + model: Final = scenario.model(api_key=None, litellm_credential_name=name) + identity: Final = model_identity(gateway, model) + for value in ("synthetic-credential-first", "synthetic-credential-second"): + patched: Final = gateway.request("PATCH", f"/credentials/{name}", { + "credential_name": name, "credential_values": {"api_key": value}, "credential_info": {} + }) + assert patched.status_code == 200, patched.text + rows: Final = read_rows( + 'SELECT credential_values FROM "LiteLLM_CredentialsTable" WHERE credential_name = %s', (name,) + ) + assert len(rows) == 1 + stored: Final = object_value(rows[0]["credential_values"]) + assert isinstance(stored["api_key"], str) and stored["api_key"] != value + for reload in (False, True): + if reload: + response: Final = gateway.request("PATCH", f"/model/{identity}/update", {"model_info": {"description": value}}) + assert response.status_code == 200, response.text + upstream.get("/__observations").raise_for_status() + assert object_value(gateway.chat(model, text=f"{name} {value} reload={reload}")["usage"])["total_tokens"] == 40 + observed: Final = upstream.get("/__observations") + observed.raise_for_status() + assert len(observed.json()["requests"]) == 1, (value, reload, observed.text) + assert observed.json()["requests"][0]["authorization"] == f"Bearer {value}" diff --git a/tests/integration/conftest.py b/tests/integration/conftest.py new file mode 100644 index 00000000000..f5a018d305a --- /dev/null +++ b/tests/integration/conftest.py @@ -0,0 +1,103 @@ +from __future__ import annotations + +import json +import os +from importlib.metadata import version +from collections.abc import Generator, Iterator +from pathlib import Path +from typing import Final + +import pytest +import httpx +from redis import Redis + +from integration._support.client import Gateway, eventually, gateway_from_environment +from integration._support.manifest import OWNED_DIRECTORIES, contracts +from integration._support.generation import LIFECYCLE_SETTINGS + +COLLECTED: Final = pytest.StashKey[tuple[str, ...]]() +REPORTS: Final = pytest.StashKey[list[pytest.TestReport]]() + + +def pytest_configure(config: pytest.Config) -> None: + config.addinivalue_line("markers", "integration: owned real-service integration contracts") + config.addinivalue_line("markers", "covers(*ids): independently asserted behavior contracts") + config.stash[REPORTS] = [] + + +def pytest_collection_modifyitems(config: pytest.Config, items: list[pytest.Item]) -> None: + manifest: Final = contracts() + root: Final = Path(__file__).parent + owned: Final = tuple( + item + for item in items + if item.path.is_relative_to(root) and item.path.relative_to(root).parts[0] in OWNED_DIRECTORIES + ) + if owned and os.environ.get("GITHUB_ACTIONS") == "true": + raise pytest.UsageError("Integration contracts are owned by CircleCI") + for item in owned: + if item.nodeid not in manifest: + raise pytest.UsageError(f"Integration node missing from manifest: {item.nodeid}") + item.add_marker(pytest.mark.integration) + declared: Final = tuple(value for mark in item.iter_markers("covers") for value in mark.args) + if set(declared) != set(manifest[item.nodeid]): + raise pytest.UsageError(f"Contract mapping differs for {item.nodeid}") + config.stash[COLLECTED] = tuple(item.nodeid for item in owned) + + +@pytest.hookimpl(wrapper=True) +def pytest_runtest_makereport( + item: pytest.Item, call: pytest.CallInfo[None] +) -> Generator[None, pytest.TestReport, pytest.TestReport]: + report: Final = yield + item.config.stash[REPORTS].append(report) + return report + + +def pytest_sessionfinish(session: pytest.Session, exitstatus: int) -> None: + destination: Final = os.environ.get("INTEGRATION_RESULTS_DIR") + if destination is None: + return + collected: Final = session.config.stash.get(COLLECTED, ()) + reports: Final = tuple(report for report in session.config.stash[REPORTS] if report.nodeid in collected) + passed: Final = tuple(report.nodeid for report in reports if report.when == "call" and report.passed) + complete: Final = ( + exitstatus == 0 + and bool(collected) + and sorted(collected) == sorted(passed) + and all(report.passed for report in reports) + ) + output: Final = Path(destination) + output.mkdir(parents=True, exist_ok=True) + (output / "execution.json").write_text( + json.dumps({ + "collected": collected, "passed": passed, "complete": complete, "exitstatus": exitstatus, + "hypothesis_version": version("hypothesis"), + "hypothesis_seed": session.config.getoption("hypothesis_seed"), + "generation": { + "max_examples": LIFECYCLE_SETTINGS.max_examples, + "stateful_step_count": LIFECYCLE_SETTINGS.stateful_step_count, + "database": str(LIFECYCLE_SETTINGS.database), + "phases": [phase.name for phase in LIFECYCLE_SETTINGS.phases], + }, + }, indent=2) + + "\n" + ) + if not complete and exitstatus == 0: + session.exitstatus = pytest.ExitCode.TESTS_FAILED + + +@pytest.fixture +def gateway() -> Iterator[Gateway]: + with gateway_from_environment() as value: + yield value + + +@pytest.fixture +def peer(gateway: Gateway) -> Iterator[Gateway]: + url: Final = os.environ["INTEGRATION_PEER_URL"] + assert url.rstrip("/") != str(gateway.client.base_url).rstrip("/") + with Redis(host=os.environ["REDIS_HOST"], port=int(os.environ["REDIS_PORT"])) as cache: + eventually(lambda: cache.pubsub_numsub("litellm_proxy.auth_cache_invalidation")[0][1], lambda count: count >= 2) + with httpx.Client(base_url=url, timeout=15, trust_env=False) as client: + yield Gateway(client, gateway.key, gateway.upstream_url) diff --git a/tests/integration/contracts.json b/tests/integration/contracts.json new file mode 100644 index 00000000000..82cc64dd5c6 --- /dev/null +++ b/tests/integration/contracts.json @@ -0,0 +1,80 @@ +{ + "groups": { + "management": [ + "management", + "authorization", + "configuration" + ], + "accounting": [ + "pricing", + "spend" + ], + "database": [ + "database" + ], + "providers": [ + "providers", + "routing", + "streaming" + ], + "extensions": [ + "mcp", + "observability", + "compatibility" + ] + }, + "tests": { + "tests/integration/management/test_key_updates.py::test_update_preserves_independent_fields_and_serving": [ + "mgmt.key.update.preserves_independent_fields" + ], + "tests/integration/pricing/test_configured_prices.py::test_custom_price_is_reported_and_charged": [ + "quota_management.spend_tracking.custom_price.matches_input_rates" + ], + "tests/integration/providers/test_request_boundary.py::test_internal_request_state_does_not_reach_provider": [ + "other.provider_wire.internal_parameters_filtered" + ], + "tests/integration/pricing/test_configured_prices.py::test_default_prices_survive_nullable_sibling_and_reload": [ + "quota_management.spend_tracking.default_prices.survive_nullable_sibling_reload" + ], + "tests/integration/providers/test_request_boundary.py::test_upstream_rejects_corruption_and_accepts_supported_metadata": [ + "other.provider_wire.validator_rejects_corruption" + ], + "tests/integration/pricing/test_configured_prices.py::test_loaded_router_preserves_cached_defaults_during_real_requests": [ + "quota_management.spend_tracking.default_prices.loaded_router_preserves_cached_defaults" + ], + "tests/integration/management/test_partial_update_sequences.py::test_generated_partial_updates_preserve_persisted_and_effective_state": [ + "mgmt.key.update.generated_sequences_preserve_state" + ], + "tests/integration/management/test_partial_update_sequences.py::test_zero_false_and_empty_values_are_not_treated_as_omission": [ + "mgmt.key.update.false_zero_and_empty_values_affect_serving" + ], + "tests/integration/management/test_partial_update_sequences.py::test_project_omission_clear_and_invalid_update_have_distinct_effects": [ + "mgmt.key.update.project_clear_preserves_scope", + "mgmt.key.update.invalid_batch_is_atomic" + ], + "tests/integration/authorization/test_warmed_policy.py::test_generated_policy_changes_reach_both_warmed_workers": [ + "mgmt.key.update.two_workers_enforce_warmed_policy" + ], + "tests/integration/authorization/test_warmed_policy.py::test_scim_deactivation_blocks_null_and_false_keys_but_preserves_other_owners": [ + "mgmt.user.scim.deactivation_includes_nullable_blocked_keys" + ], + "tests/integration/authorization/test_warmed_policy.py::test_warmed_team_role_demotion_prevents_later_management_writes": [ + "mgmt.team.member_update.demoted_role_cannot_write" + ], + "tests/integration/configuration/test_effective_settings.py::test_model_block_changes_actual_route_and_leaves_other_route_working": [ + "mgmt.model.block.changes_serving_and_preserves_control" + ], + "tests/integration/configuration/test_effective_settings.py::test_saved_retry_setting_controls_real_attempts_and_restores": [ + "mgmt.router_settings.update.changes_observed_attempt_count" + ], + "tests/integration/configuration/test_effective_settings.py::test_credential_value_update_and_model_reload_reach_provider": [ + "mgmt.credential.update.saved_value_reaches_wire" + ], + "tests/integration/management/test_partial_update_sequences.py::test_denied_key_update_preserves_saved_grants_and_serving": [ + "mgmt.key.update.denied_request_preserves_effective_state" + ], + "tests/integration/authorization/test_warmed_policy.py::test_expiry_and_explicit_clear_reach_both_warmed_workers": [ + "mgmt.key.update.expiry_changes_reach_warmed_workers" + ] + } +} diff --git a/tests/integration/management/test_key_updates.py b/tests/integration/management/test_key_updates.py new file mode 100644 index 00000000000..6f2e850b17a --- /dev/null +++ b/tests/integration/management/test_key_updates.py @@ -0,0 +1,40 @@ +from typing import Final +from hashlib import sha256 + +import pytest + +from integration._support.client import Gateway, object_value +from integration._support.database import read_rows + + +@pytest.mark.covers("mgmt.key.update.preserves_independent_fields") +def test_update_preserves_independent_fields_and_serving(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + model: Final = scenario.model() + key: Final = scenario.key(models=[model], key_alias="before", metadata={"retained": "value"}) + gateway.chat(model, key=key) + gateway.post("/key/update", {"key": key, "key_alias": "after"}) + info: Final = object_value(gateway.get("/key/info", {"key": key})["info"]) + assert info["key_alias"] == "after" + assert info["models"] == [model] + assert object_value(info["metadata"])["retained"] == "value" + response: Final = gateway.chat(model, key=key) + assert object_value(response["usage"])["total_tokens"] == 40 + replacement: Final = scenario.model() + gateway.post("/key/update", {"key": key, "models": [replacement]}) + saved: Final = read_rows( + 'SELECT key_alias, models, metadata FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(key.encode()).hexdigest(),), + ) + assert len(saved) == 1 + assert saved[0]["models"] == [replacement] + assert saved[0]["key_alias"] == "after" + denied: Final = gateway.request( + "POST", + "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": "old grant"}]}, + key=key, + ) + assert denied.status_code == 403, denied.text + assert object_value(object_value(denied.json())["error"])["type"] == "key_model_access_denied" + assert object_value(gateway.chat(replacement, key=key)["usage"])["total_tokens"] == 40 diff --git a/tests/integration/management/test_partial_update_sequences.py b/tests/integration/management/test_partial_update_sequences.py new file mode 100644 index 00000000000..c645b896448 --- /dev/null +++ b/tests/integration/management/test_partial_update_sequences.py @@ -0,0 +1,200 @@ +from contextlib import ExitStack +from hashlib import sha256 +from typing import Final + +import pytest +from hypothesis import strategies as st +from hypothesis.stateful import RuleBasedStateMachine, invariant, rule, run_state_machine_as_test +from pydantic import JsonValue + +from integration._support.client import Gateway, object_value +from integration._support.database import read_rows +from integration._support.generation import LIFECYCLE_SETTINGS, bounded_http_requests + + +@pytest.mark.covers("mgmt.key.update.generated_sequences_preserve_state") +def test_generated_partial_updates_preserve_persisted_and_effective_state(gateway: Gateway) -> None: + class KeyUpdates(RuleBasedStateMachine): + def __init__(self) -> None: + super().__init__() + self.resources = ExitStack() + try: + scenario = self.resources.enter_context(gateway.scenario()) + self.models = (scenario.model(), scenario.model()) + self.key = scenario.key(models=[self.models[0]], key_alias="initial", metadata={"revision": "initial"}) + self.expected: dict[str, JsonValue] = { + "models": [self.models[0]], "key_alias": "initial", "metadata": {"revision": "initial"} + } + gateway.chat(self.models[0], key=self.key) + except BaseException: + with budget.cleanup(): + self.resources.close() + raise + + @rule(alias=st.sampled_from(("first", "second", "", "unicode-λ"))) + def alias(self, alias: str) -> None: + gateway.post("/key/update", {"key": self.key, "key_alias": alias}) + self.expected["key_alias"] = alias + + @rule(index=st.integers(min_value=0, max_value=1), both=st.booleans()) + def grant(self, index: int, both: bool) -> None: + models: Final = list(self.models) if both else [self.models[index]] + gateway.post("/key/update", {"key": self.key, "models": models}) + self.expected["models"] = models + + @rule(value=st.sampled_from(("", "a", "different", "λ"))) + def metadata(self, value: str) -> None: + gateway.post("/key/update", {"key": self.key, "metadata": {"revision": value}}) + self.expected["metadata"] = {"revision": value} + + @invariant() + def persisted_state_and_serving_match(self) -> None: + rows: Final = read_rows( + 'SELECT models, key_alias, metadata FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(self.key.encode()).hexdigest(),), + ) + assert rows == [self.expected] + info: Final = object_value(gateway.get("/key/info", {"key": self.key})["info"]) + assert {field: info[field] for field in self.expected} == self.expected + for model in self.models: + response: Final = gateway.request( + "POST", "/v1/chat/completions", + {"model": model, "messages": [{"role": "user", "content": "generated update control"}]}, + key=self.key, + ) + if model in self.expected["models"]: + assert response.status_code == 200, response.text + assert response.json()["usage"]["total_tokens"] == 40 + else: + assert response.status_code == 403, response.text + assert response.json()["error"]["type"] == "key_model_access_denied" + + def teardown(self) -> None: + with budget.cleanup(): + self.resources.close() + + with bounded_http_requests((gateway,), limit=2000) as budget: + run_state_machine_as_test(KeyUpdates, settings=LIFECYCLE_SETTINGS) + + +@pytest.mark.covers("mgmt.key.update.false_zero_and_empty_values_affect_serving") +def test_zero_false_and_empty_values_are_not_treated_as_omission(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + models: Final = (scenario.model(), scenario.model()) + key: Final = scenario.key(models=[models[0]], max_budget=0, metadata={"ordinary": "value"}) + denied: Final = gateway.request( + "POST", "/v1/chat/completions", + {"model": models[0], "messages": [{"role": "user", "content": "zero budget"}]}, key=key, + ) + assert denied.status_code == 429, denied.text + assert denied.json()["error"]["type"] == "budget_exceeded" + gateway.post("/key/update", {"key": key, "max_budget": 1, "models": [], "metadata": {}}) + info: Final = object_value(gateway.get("/key/info", {"key": key})["info"]) + assert (info["models"], info["metadata"], info["max_budget"]) == ([], {}, 1) + for model in models: + assert object_value(gateway.chat(model, key=key)["usage"])["total_tokens"] == 40 + gateway.post("/key/update", {"key": key, "blocked": True}) + blocked: Final = gateway.request( + "POST", "/v1/chat/completions", + {"model": models[0], "messages": [{"role": "user", "content": "blocked control"}]}, key=key, + ) + assert blocked.status_code == 401, blocked.text + assert blocked.json()["error"]["type"] == "auth_error" + gateway.post("/key/update", {"key": key, "blocked": False}) + assert object_value(gateway.chat(models[0], key=key)["usage"])["total_tokens"] == 40 + rows: Final = read_rows( + 'SELECT blocked, models, metadata, max_budget FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(key.encode()).hexdigest(),), + ) + assert rows == [{"blocked": False, "models": [], "metadata": {}, "max_budget": 1.0}] + gateway.post("/key/update", {"key": key, "max_budget": 0}) + assert read_rows( + 'SELECT max_budget FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(key.encode()).hexdigest(),), + ) == [{"max_budget": 0.0}] + zero_after_update: Final = gateway.request( + "POST", "/v1/chat/completions", + {"model": models[0], "messages": [{"role": "user", "content": "updated zero budget"}]}, key=key, + ) + assert zero_after_update.status_code == 429, zero_after_update.text + assert zero_after_update.json()["error"]["type"] == "budget_exceeded" + gateway.post("/key/update", {"key": key, "max_budget": None}) + assert read_rows( + 'SELECT max_budget FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(key.encode()).hexdigest(),), + ) == [{"max_budget": None}] + assert object_value(gateway.chat(models[0], key=key)["usage"])["total_tokens"] == 40 + + +@pytest.mark.covers("mgmt.key.update.project_clear_preserves_scope", "mgmt.key.update.invalid_batch_is_atomic") +def test_project_omission_clear_and_invalid_update_have_distinct_effects(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + model: Final = scenario.model() + outside: Final = scenario.model() + team: Final = scenario.team(models=[model]) + project: Final = scenario.project(team, models=[model]) + other: Final = scenario.project(team, models=[model]) + key: Final = scenario.key(team_id=team, project_id=project, models=[model], key_alias="before", max_budget=5) + gateway.chat(model, key=key) + gateway.post("/key/update", {"key": key, "key_alias": "after"}) + digest: Final = sha256(key.encode()).hexdigest() + + def saved() -> list[dict[str, object]]: + return read_rows( + 'SELECT key_alias, project_id, team_id, models, max_budget FROM "LiteLLM_VerificationToken" ' + 'WHERE token = %s', (digest,), + ) + + before: Final = saved() + assert before == [{"key_alias": "after", "project_id": project, "team_id": team, "models": [model], "max_budget": 5}] + for invalid in (other, ""): + rejected: Final = gateway.request( + "POST", "/key/update", {"key": key, "project_id": invalid, "key_alias": "must-not-persist"} + ) + assert rejected.status_code == 400, rejected.text + assert saved() == before + gateway.chat(model, key=key) + gateway.post("/project/update", {"project_id": project, "blocked": True}) + denied: Final = gateway.request( + "POST", "/v1/chat/completions", {"model": model, "messages": [{"role": "user", "content": "blocked project"}]}, + key=key, + ) + assert denied.status_code == 401, denied.text + assert denied.json()["error"]["type"] == "auth_error" + for _ in range(2): + gateway.post("/key/update", {"key": key, "project_id": None}) + assert saved() == [{**before[0], "project_id": None}] + assert object_value(gateway.chat(model, key=key)["usage"])["total_tokens"] == 40 + outside_request: Final = gateway.request( + "POST", "/v1/chat/completions", + {"model": outside, "messages": [{"role": "user", "content": "detached scope control"}]}, key=key, + ) + assert outside_request.status_code == 403, outside_request.text + assert outside_request.json()["error"]["type"] == "key_model_access_denied" + + +@pytest.mark.covers("mgmt.key.update.denied_request_preserves_effective_state") +def test_denied_key_update_preserves_saved_grants_and_serving(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + model: Final = scenario.model() + outside: Final = scenario.model() + owner: Final = scenario.user(user_role="internal_user") + other: Final = scenario.user(user_role="internal_user") + key: Final = scenario.key(user_id=owner, models=[model], key_alias="unchanged", max_budget=2) + caller: Final = scenario.key(user_id=other, models=[model], allowed_routes=["/key/update", "/v1/chat/completions"]) + gateway.chat(model, key=key) + denied: Final = gateway.request( + "POST", "/key/update", {"key": key, "key_alias": "wrong", "models": [outside], "max_budget": 0}, key=caller + ) + assert denied.status_code == 403, denied.text + assert read_rows( + 'SELECT user_id, models, key_alias, max_budget FROM "LiteLLM_VerificationToken" WHERE token = %s', + (sha256(key.encode()).hexdigest(),), + ) == [{"user_id": owner, "models": [model], "key_alias": "unchanged", "max_budget": 2.0}] + assert object_value(gateway.chat(model, key=key)["usage"])["total_tokens"] == 40 + rejected: Final = gateway.request( + "POST", "/v1/chat/completions", + {"model": outside, "messages": [{"role": "user", "content": "unchanged scope"}]}, key=key, + ) + assert rejected.status_code == 403, rejected.text + assert rejected.json()["error"]["type"] == "key_model_access_denied" diff --git a/tests/integration/pricing/test_configured_prices.py b/tests/integration/pricing/test_configured_prices.py new file mode 100644 index 00000000000..151103f6df5 --- /dev/null +++ b/tests/integration/pricing/test_configured_prices.py @@ -0,0 +1,148 @@ +from collections.abc import Iterator, Mapping +from typing import Final +from pathlib import Path +import uuid + +import pytest +import yaml + +from integration._support.client import Gateway, eventually, object_value, string_value +from integration._support.database import read_rows + + +@pytest.mark.covers("quota_management.spend_tracking.custom_price.matches_input_rates") +def test_custom_price_is_reported_and_charged(gateway: Gateway) -> None: + with gateway.scenario() as scenario: + model: Final = scenario.model(input_cost_per_token=0.001, output_cost_per_token=0.002) + response: Final = gateway.request( + "POST", "/v1/chat/completions", {"model": model, "messages": [{"role": "user", "content": "price control"}]} + ) + assert response.status_code == 200, response.text + assert float(response.headers["x-litellm-response-cost"]) == pytest.approx(20 * 0.001 + 20 * 0.002) + entries: Final = gateway.get("/model/info")["data"] + assert isinstance(entries, list) + matching: Final = tuple(object_value(entry) for entry in entries if object_value(entry)["model_name"] == model) + assert len(matching) == 1 + params: Final = object_value(matching[0]["litellm_params"]) + assert params["input_cost_per_token"] == 0.001 + assert params["output_cost_per_token"] == 0.002 + + +@pytest.mark.covers("quota_management.spend_tracking.default_prices.survive_nullable_sibling_reload") +def test_default_prices_survive_nullable_sibling_and_reload(gateway: Gateway) -> None: + for registration_order in (("custom", "omitted", "nullable"), ("nullable", "omitted", "custom")): + with gateway.scenario() as scenario: + configured: Final = { + "custom": {"input_cost_per_token": 0.001, "output_cost_per_token": 0.002}, + "omitted": {}, + "nullable": {"input_cost_per_token": None, "output_cost_per_token": None}, + } + rates: Final = { + "custom": (0.001, 0.002), + "omitted": (0.00000015, 0.0000006), + "nullable": (0.00000015, 0.0000006), + } + models: Final = {kind: scenario.model(**configured[kind]) for kind in registration_order} + + def observe_requests( + registration_order: tuple[str, ...], + models: Mapping[str, str], + rates: Mapping[str, tuple[float, float]], + ) -> Iterator[tuple[str, float]]: + for generation in range(2): + entries: Final = gateway.get("/model/info")["data"] + assert isinstance(entries, list) + kinds: Final = tuple(reversed(registration_order)) if generation else registration_order + for index, kind in enumerate(kinds): + model: Final = models[kind] + target: Final = next( + object_value(entry) for entry in entries if object_value(entry)["model_name"] == model + ) + info: Final = object_value(target["model_info"]) + assert info["input_cost_per_token"] == rates[kind][0] + assert info["output_cost_per_token"] == rates[kind][1] + response: Final = gateway.request( + "POST", + "/v1/chat/completions", + { + "model": model, + "messages": [ + {"role": "user", "content": f"price {generation * len(registration_order) + index}"} + ], + }, + ) + assert response.status_code == 200, response.text + expected: Final = 20 * rates[kind][0] + 20 * rates[kind][1] + assert float(response.headers["x-litellm-response-cost"]) == pytest.approx(expected, rel=1e-6) + request_id: Final = string_value(object_value(response.json())["id"]) + yield request_id, expected + target: Final = next( + object_value(entry) + for entry in entries + if object_value(entry)["model_name"] == models["nullable"] + ) + identity: Final = string_value(object_value(target["model_info"])["id"]) + updated: Final = gateway.request( + "PATCH", f"/model/{identity}/update", {"model_info": {"description": "reload price contract"}} + ) + assert updated.status_code == 200, updated.text + + observations: Final = tuple(observe_requests(registration_order, models, rates)) + for request_id, expected in observations: + rows: Final = eventually( + lambda request_id=request_id: read_rows( + 'SELECT request_id, spend, prompt_tokens, completion_tokens FROM "LiteLLM_SpendLogs" ' + "WHERE request_id = %s", + (request_id,), + ), + lambda values: len(values) == 1, + seconds=70, + ) + assert rows[0]["prompt_tokens"] == 20 + assert rows[0]["completion_tokens"] == 20 + assert float(rows[0]["spend"]) == pytest.approx(expected, rel=1e-6) + + +@pytest.mark.covers("quota_management.spend_tracking.default_prices.loaded_router_preserves_cached_defaults") +def test_loaded_router_preserves_cached_defaults_during_real_requests(gateway: Gateway, tmp_path: Path) -> None: + from litellm import Router + + aliases: Final = (f"pricing-{uuid.uuid4().hex}", f"pricing-{uuid.uuid4().hex}") + path: Final = tmp_path / "models.yaml" + path.write_text( + yaml.safe_dump( + { + "model_list": [ + { + "model_name": alias, + "litellm_params": { + "model": "openai/gpt-4o-mini", + "api_key": "integration-provider-key", + "api_base": f"{gateway.upstream_url}/v1", + }, + "model_info": {"id": alias, **pricing}, + } + for alias, pricing in zip( + aliases, ({}, {"input_cost_per_token": None, "output_cost_per_token": None}), strict=True + ) + ] + } + ) + ) + for reverse in (False, True): + configured: Final = yaml.safe_load(path.read_text())["model_list"] + router: Final = Router(model_list=list(reversed(configured)) if reverse else configured, num_retries=0) + try: + for alias in (*aliases, *reversed(aliases)): + result: Final = router.completion( + model=alias, messages=[{"role": "user", "content": "router price control"}] + ) + assert result.usage.prompt_tokens == 20 + assert result.usage.completion_tokens == 20 + deployment: Final = router.get_deployment(model_id=alias) + assert deployment is not None + info: Final = router.get_router_model_info(deployment=deployment, received_model_name=alias) + assert info["input_cost_per_token"] == 0.00000015 + assert info["output_cost_per_token"] == 0.0000006 + finally: + router.reset() diff --git a/tests/integration/providers/test_request_boundary.py b/tests/integration/providers/test_request_boundary.py new file mode 100644 index 00000000000..aad10843642 --- /dev/null +++ b/tests/integration/providers/test_request_boundary.py @@ -0,0 +1,57 @@ +from typing import Final + +import httpx +import pytest + +from integration._support.client import Gateway, JSON_OBJECT, object_value + + +@pytest.mark.covers("other.provider_wire.internal_parameters_filtered") +def test_internal_request_state_does_not_reach_provider(gateway: Gateway) -> None: + with gateway.scenario() as scenario, httpx.Client(base_url=gateway.upstream_url, trust_env=False) as upstream: + upstream.get("/__observations").raise_for_status() + model: Final = scenario.model() + key: Final = scenario.key(models=[model], tpm_limit=10000, rpm_limit=100) + result: Final = gateway.post( + "/v1/chat/completions", + { + "model": model, + "messages": [{"role": "user", "content": "wire contract"}], + "temperature": 0.4, + "max_tokens": 20, + "timeout": 12, + }, + key=key, + ) + assert object_value(result["usage"])["total_tokens"] == 40 + observations: Final = JSON_OBJECT.validate_json(upstream.get("/__observations").content)["requests"] + assert isinstance(observations, list) + assert len(observations) == 1 + observed: Final = object_value(observations[0]) + body: Final = object_value(observed["body"]) + assert body["model"] == "gpt-4o-mini" + assert body["messages"] == [{"role": "user", "content": "wire contract"}] + assert body["temperature"] == 0.4 + assert body["max_tokens"] == 20 + assert observed["authorization"] == "Bearer integration-provider-key" + assert "litellm_metadata" not in body + assert "litellm_params" not in body + assert "timeout" not in body + assert "tpm" not in body + + +@pytest.mark.covers("other.provider_wire.validator_rejects_corruption") +def test_upstream_rejects_corruption_and_accepts_supported_metadata(gateway: Gateway) -> None: + with httpx.Client(base_url=gateway.upstream_url, trust_env=False) as upstream: + missing: Final = upstream.post("/v1/chat/completions", json={"model": "gpt-4o-mini"}) + assert missing.status_code == 400 + assert ( + object_value(object_value(missing.json())["error"])["message"] == "model and nonempty messages are required" + ) + body: Final = {"model": "gpt-4o-mini", "messages": [{"role": "user", "content": "strict control"}]} + leaked: Final = upstream.post("/v1/chat/completions", json={**body, "litellm_metadata": {"hidden": "value"}}) + assert leaked.status_code == 400 + assert "litellm_metadata" in str(object_value(object_value(leaked.json())["error"])["message"]) + valid: Final = upstream.post("/v1/chat/completions", json={**body, "metadata": {"purpose": "synthetic"}}) + assert valid.status_code == 200, valid.text + assert object_value(object_value(valid.json())["usage"])["total_tokens"] == 40 diff --git a/tests/integration/proxy_config.yaml b/tests/integration/proxy_config.yaml new file mode 100644 index 00000000000..b6f9767c210 --- /dev/null +++ b/tests/integration/proxy_config.yaml @@ -0,0 +1,17 @@ +model_list: [] +general_settings: + master_key: os.environ/LITELLM_MASTER_KEY + database_url: os.environ/DATABASE_URL + store_model_in_db: true + disable_spend_logs: false + proxy_batch_write_at: 1 +litellm_settings: + enable_redis_auth_cache: true + cache: true + cache_params: + type: redis + host: os.environ/REDIS_HOST + port: os.environ/REDIS_PORT +router_settings: + num_retries: 0 + disable_cooldowns: true diff --git a/tests/integration/run.py b/tests/integration/run.py new file mode 100644 index 00000000000..a48798475a2 --- /dev/null +++ b/tests/integration/run.py @@ -0,0 +1,71 @@ +from __future__ import annotations + +import argparse +import json +import os +import subprocess +import sys +from pathlib import Path +from types import MappingProxyType +from typing import Final + +GROUPS: Final = MappingProxyType(json.loads(Path(__file__).with_name("contracts.json").read_text())["groups"]) + + +def main() -> int: + parser: Final = argparse.ArgumentParser() + parser.add_argument("group", choices=tuple(GROUPS)) + parser.add_argument("--results", type=Path, default=Path("test-results/integration")) + parser.add_argument("--seed", type=int, default=int(os.environ.get("INTEGRATION_SEED", "4106601"))) + options: Final = parser.parse_args() + root: Final = Path(__file__).resolve().parents[2] + selected: Final = tuple( + str(path.relative_to(root)) + for folder in GROUPS[options.group] + for path in sorted((root / "tests/integration" / folder).glob("test_*.py")) + ) + if not selected: + parser.error(f"No integration contracts selected for {options.group}") + output: Final = options.results.resolve() + output.mkdir(parents=True, exist_ok=True) + manifest: Final = json.loads((root / "tests/integration/contracts.json").read_text())["tests"] + expected: Final = sorted(node for node in manifest if node.split("::", 1)[0] in selected) + if not expected or set(selected) != {node.split("::", 1)[0] for node in expected}: + parser.error("Every selected file must have canonical manifest nodes") + environment: Final = { + **os.environ, + "PYTHONPATH": os.pathsep.join((str(root), str(root / "tests"), str(root / "tests/e2e"))), + "INTEGRATION_RESULTS_DIR": str(output), + "LITELLM_LOCAL_MODEL_COST_MAP": "True", + } + result: Final = subprocess.call( + [ + sys.executable, + "-m", + "pytest", + *selected, + "-vv", + "--strict-markers", + "-p", + "no:pytest-retry", + "-p", + "no:rerunfailures", + "--timeout=90", + "--durations=15", + f"--hypothesis-seed={options.seed}", + f"--junitxml={output / 'junit.xml'}", + ], + cwd=root, + env=environment, + ) + if result != 0: + return result + evidence: Final = json.loads((output / "execution.json").read_text()) + if not evidence["complete"] or sorted(evidence["passed"]) != expected or sorted(evidence["collected"]) != expected: + print("Executed integration nodes differ from the canonical manifest", file=sys.stderr) + return 1 + return 0 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/tests/llm_responses_api_testing/test_openai_responses_api.py b/tests/llm_responses_api_testing/test_openai_responses_api.py index 05bb9113835..c7712d96969 100644 --- a/tests/llm_responses_api_testing/test_openai_responses_api.py +++ b/tests/llm_responses_api_testing/test_openai_responses_api.py @@ -1627,9 +1627,10 @@ async def test_openai_responses_api_token_limit_error(): Parsing the in-stream ErrorEvent must not raise "pydantic_core._pydantic_core.ValidationError: 3 validation errors for ErrorEvent". - The iterator now surfaces the event as litellm.APIError with status 400 - (invalid_request_error is a non-retriable client error, so no - MidStreamFallbackError wrapping) carrying the provider's message. + The iterator routes the event through litellm.exception_type, so it surfaces as + the typed 400 client error the non-streaming path raises (litellm.BadRequestError) + carrying the provider's message. invalid_request_error is a non-retriable client + error, so there is no MidStreamFallbackError wrapping. """ litellm._turn_on_debug() @@ -1644,7 +1645,7 @@ async def test_openai_responses_api_token_limit_error(): async for event in response: print(event) - with pytest.raises(litellm.APIError) as exc_info: + with pytest.raises(litellm.BadRequestError) as exc_info: await _drain() assert exc_info.value.status_code == 400 diff --git a/tests/logging_callback_tests/test_gcs_pub_sub.py b/tests/logging_callback_tests/test_gcs_pub_sub.py index 10957fa2f92..1f1ca8960f6 100644 --- a/tests/logging_callback_tests/test_gcs_pub_sub.py +++ b/tests/logging_callback_tests/test_gcs_pub_sub.py @@ -28,6 +28,7 @@ verbose_logger.setLevel(logging.DEBUG) ignored_keys = [ "request_id", + "litellm_call_id", "metadata.litellm_call_id", "session_id", "startTime", diff --git a/tests/pass_through_unit_tests/test_vertex_ai_live_passthrough.py b/tests/pass_through_unit_tests/test_vertex_ai_live_passthrough.py index e2eb6d0b68b..8b3dc436b8f 100644 --- a/tests/pass_through_unit_tests/test_vertex_ai_live_passthrough.py +++ b/tests/pass_through_unit_tests/test_vertex_ai_live_passthrough.py @@ -6,12 +6,15 @@ including the logging handler, cost tracking, and WebSocket message processing. """ import json +from collections.abc import Sequence from datetime import datetime from unittest.mock import AsyncMock, Mock, patch, MagicMock from typing import Dict, List, Any, Optional import pytest import httpx +import litellm +from typing_extensions import NotRequired, ReadOnly, TypedDict # Add the parent directory to the system path @@ -22,10 +25,16 @@ from litellm.proxy.pass_through_endpoints.success_handler import ( PassThroughEndpointLogging, ) from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj -from litellm.types.utils import LlmProviders +from litellm.types.utils import CostBreakdown, LlmProviders, Usage from litellm.proxy._types import UserAPIKeyAuth +class _LiveTurn(TypedDict): + prompt: ReadOnly[tuple[int, int]] + candidates: ReadOnly[tuple[int, int]] + candidate_audio_token_count_missing: NotRequired[ReadOnly[bool]] + + class TestVertexAILivePassthroughLoggingHandler: """Test the Vertex AI Live Passthrough Logging Handler""" @@ -39,6 +48,7 @@ class TestVertexAILivePassthroughLoggingHandler: """Create a mock logging object""" mock = MagicMock(spec=LiteLLMLoggingObj) mock.model_call_details = {} + mock._response_cost_calculator.return_value = None return mock @pytest.fixture @@ -201,88 +211,490 @@ class TestVertexAILivePassthroughLoggingHandler: assert text_prompt["tokenCount"] == 10 assert audio_prompt["tokenCount"] == 10 - @patch( - "litellm.proxy.pass_through_endpoints.llm_provider_handlers.vertex_ai_live_passthrough_logging_handler.get_model_info" - ) - def test_calculate_cost_basic(self, mock_get_model_info, handler): - """Test basic cost calculation""" - mock_get_model_info.return_value = { - "input_cost_per_token": 0.000001, - "output_cost_per_token": 0.000002, - } + def test_usage_carries_every_modality(self, handler): + """Regression: the Usage object reported only TEXT, so audio and image billed as nothing. + prompt_tokens must be the full count and the details must name each modality, + because the cost calculator prices audio and image from *_tokens_details. + """ usage_metadata = { - "promptTokenCount": 100, - "candidatesTokenCount": 50, - "totalTokenCount": 150, - } - - cost = handler._calculate_live_api_cost("gemini-1.5-pro", usage_metadata) - - # The cost calculation may include additional factors, so we check it's reasonable - expected_min_cost = (100 * 0.000001) + (50 * 0.000002) - assert cost >= expected_min_cost - assert cost > 0 - - @patch( - "litellm.proxy.pass_through_endpoints.llm_provider_handlers.vertex_ai_live_passthrough_logging_handler.get_model_info" - ) - def test_calculate_cost_with_audio(self, mock_get_model_info, handler): - """Test cost calculation with audio tokens""" - mock_get_model_info.return_value = { - "input_cost_per_token": 0.000001, - "output_cost_per_token": 0.000002, - "input_cost_per_audio_token": 0.0001, - "output_cost_per_audio_token": 0.0002, - } - - usage_metadata = { - "promptTokenCount": 100, - "candidatesTokenCount": 50, - "totalTokenCount": 150, + "promptTokenCount": 1300, + "candidatesTokenCount": 124, + "totalTokenCount": 1424, "promptTokensDetails": [ - {"modality": "TEXT", "tokenCount": 80}, - {"modality": "AUDIO", "tokenCount": 20}, + {"modality": "TEXT", "tokenCount": 13}, + {"modality": "AUDIO", "tokenCount": 127}, + {"modality": "IMAGE", "tokenCount": 1160}, ], "candidatesTokensDetails": [ - {"modality": "TEXT", "tokenCount": 30}, - {"modality": "AUDIO", "tokenCount": 20}, + {"modality": "TEXT", "tokenCount": 29}, + {"modality": "AUDIO", "tokenCount": 95}, ], } - cost = handler._calculate_live_api_cost("gemini-1.5-pro", usage_metadata) + usage = handler._create_usage_object_from_metadata( + usage_metadata=usage_metadata, model="gemini-live-2.5-flash" + ) - # Should include both text and audio costs - assert cost > 0 - assert cost > (100 * 0.000001) + ( - 50 * 0.000002 - ) # Should be higher due to audio + assert usage.prompt_tokens == 1300, "the full prompt count must survive, not just its text share" + assert usage.completion_tokens == 124 + assert usage.prompt_tokens_details.text_tokens == 13 + assert usage.prompt_tokens_details.audio_tokens == 127 + assert usage.prompt_tokens_details.image_tokens == 1160 + assert usage.completion_tokens_details.text_tokens == 29 + assert usage.completion_tokens_details.audio_tokens == 95 - @patch( - "litellm.proxy.pass_through_endpoints.llm_provider_handlers.vertex_ai_live_passthrough_logging_handler.get_model_info" + def test_usage_sums_repeated_modality_entries(self, handler): + """A modality can appear more than once across aggregated turns; sum, don't overwrite.""" + usage = handler._create_usage_object_from_metadata( + usage_metadata={ + "promptTokenCount": 40, + "candidatesTokenCount": 0, + "promptTokensDetails": [ + {"modality": "IMAGE", "tokenCount": 10}, + {"modality": "IMAGE", "tokenCount": 25}, + {"modality": "TEXT", "tokenCount": 5}, + ], + }, + model="gemini-live-2.5-flash", + ) + assert usage.prompt_tokens_details.image_tokens == 35 + assert usage.prompt_tokens_details.text_tokens == 5 + + NATIVE_AUDIO_MODEL = "gemini-live-2.5-flash-preview-native-audio-09-2025" + + # A four-turn native-audio session. Google charges per turn for the whole session context + # window, so the prompt side repeats the accumulated audio while the candidates side reports + # only that turn's own response. The last turn names AUDIO and omits its tokenCount, which is + # the shape Live really emits at the end of a spoken answer. + AUDIO_SESSION: tuple[_LiveTurn, ...] = ( + {"prompt": (14, 122), "candidates": (8, 20)}, + {"prompt": (21, 182), "candidates": (5, 50)}, + {"prompt": (24, 203), "candidates": (13, 27)}, + {"prompt": (24, 203), "candidates": (0, 3), "candidate_audio_token_count_missing": True}, ) - def test_calculate_cost_with_web_search(self, mock_get_model_info, handler): - """Test cost calculation with web search (tool use)""" - mock_get_model_info.return_value = { - "input_cost_per_token": 0.000001, - "output_cost_per_token": 0.000002, - "web_search_cost_per_request": 0.01, - } - usage_metadata = { - "promptTokenCount": 100, - "candidatesTokenCount": 50, - "totalTokenCount": 150, - "toolUsePromptTokenCount": 10, - } + @staticmethod + def _live_messages(turns: Sequence[_LiveTurn]) -> list[dict[str, object]]: + """Wrap (text, audio) prompt/candidate pairs as the server messages a Live session emits.""" + return [{"type": "session.created", "session": {"id": "s"}}] + [ + { + "type": "response.done", + "usageMetadata": { + "promptTokenCount": sum(turn["prompt"]), + "candidatesTokenCount": sum(turn["candidates"]), + "totalTokenCount": sum(turn["prompt"]) + sum(turn["candidates"]), + "promptTokensDetails": [ + {"modality": "TEXT", "tokenCount": turn["prompt"][0]}, + {"modality": "AUDIO", "tokenCount": turn["prompt"][1]}, + ], + "candidatesTokensDetails": ( + [{"modality": "AUDIO"}] + if turn.get("candidate_audio_token_count_missing") + else [ + {"modality": "TEXT", "tokenCount": turn["candidates"][0]}, + {"modality": "AUDIO", "tokenCount": turn["candidates"][1]}, + ] + ), + }, + } + for turn in turns + ] - cost = handler._calculate_live_api_cost("gemini-1.5-pro", usage_metadata) + @staticmethod + def _session_usage( + handler: VertexAILivePassthroughLoggingHandler, + mock_logging_obj: MagicMock, + messages: list[dict[str, object]], + model: str, + ) -> Usage: + result = handler.vertex_ai_live_passthrough_handler( + websocket_messages=messages, + logging_obj=mock_logging_obj, + url_route="/vertex_ai/live", + start_time=datetime.now(), + end_time=datetime.now(), + request_body={}, + model=model, + ) + assert result["result"] is not None, "the handler must produce a usage-bearing response to bill" + return result["result"].usage - # Should include web search cost - expected_base_cost = (100 * 0.000001) + (50 * 0.000002) - # The web search cost might be handled differently, so just check it's reasonable - assert cost >= expected_base_cost - assert cost > 0 + @classmethod + def _session_cost( + cls, + handler: VertexAILivePassthroughLoggingHandler, + mock_logging_obj: MagicMock, + messages: list[dict[str, object]], + model: str, + ) -> float: + from litellm.cost_calculator import completion_cost + from litellm.types.utils import ModelResponse + + usage = cls._session_usage(handler, mock_logging_obj, messages, model) + return completion_cost( + completion_response=ModelResponse( + id="x", object="chat.completion", created=0, model=model, usage=usage, choices=[] + ), + model=f"vertex_ai/{model}", + custom_llm_provider="vertex_ai", + call_type="acompletion", + ) + + @classmethod + def _expected_session_cost(cls, turns: Sequence[_LiveTurn]) -> float: + from litellm.utils import get_model_info + + info = get_model_info(model=cls.NATIVE_AUDIO_MODEL, custom_llm_provider="vertex_ai") + return ( + sum(turn["prompt"][0] for turn in turns) * info["input_cost_per_token"] + + sum(turn["prompt"][1] for turn in turns) * info["input_cost_per_audio_token"] + + sum(turn["candidates"][0] for turn in turns) * info["output_cost_per_token"] + + sum(turn["candidates"][1] for turn in turns) * info["output_cost_per_audio_token"] + ) + + def test_every_turn_of_a_session_is_billed(self, handler, mock_logging_obj): + """Google charges per turn for the whole context window, so every turn adds to the bill. + + Billing one snapshot instead gives away all the other turns: on this session the + largest single turn is well under the session total, and its share of the audio is + priced 6x the text rate, so the gap is money rather than rounding. + """ + turns = self.AUDIO_SESSION[:3] + cost = self._session_cost(handler, mock_logging_obj, self._live_messages(turns), self.NATIVE_AUDIO_MODEL) + + assert cost == pytest.approx(self._expected_session_cost(turns), rel=1e-9) + widest_single_turn = max(self._expected_session_cost([turn]) for turn in turns) + assert cost > widest_single_turn, "billing one snapshot drops every other turn of the session" + + def test_audio_named_without_a_token_count_bills_at_the_audio_rate(self, handler, mock_logging_obj): + """Live can name the modality carrying the rest of a turn and omit its tokenCount. + + Reading the absent key as zero left those tokens inside candidatesTokenCount but outside + the breakdown, so the calculator charged real speech at the text output rate. At this + entry's rates the last turn's 3 audio tokens are $0.0000360 rather than $0.0000060. + """ + turns = self.AUDIO_SESSION + usage = self._session_usage(handler, mock_logging_obj, self._live_messages(turns), self.NATIVE_AUDIO_MODEL) + + assert usage.completion_tokens_details.audio_tokens == 100, "the unpriced entry takes the turn's residual" + assert usage.completion_tokens_details.text_tokens == 26 + assert usage.completion_tokens == 126 + + cost = self._session_cost(handler, mock_logging_obj, self._live_messages(turns), self.NATIVE_AUDIO_MODEL) + assert cost == pytest.approx(self._expected_session_cost(turns), rel=1e-9) + + TOOL_USE_PER_TURN = (100, 250, 400) + + def _grounded_messages(self): + """The three-turn session again, with each turn's own toolUsePromptTokenCount attached.""" + messages = self._live_messages(self.AUDIO_SESSION[:3]) + head, turns = messages[0], messages[1:] + return [head] + [ + {**message, "usageMetadata": {**message["usageMetadata"], "toolUsePromptTokenCount": tool_use}} + for message, tool_use in zip(turns, self.TOOL_USE_PER_TURN) + ] + + def test_server_side_tool_use_prompt_tokens_are_summed_over_the_session(self, handler, mock_logging_obj): + """toolUsePromptTokenCount rode the unknown-key pass-through, so it took the first turn only. + + Every other total beside it is summed across the session, and the first turn is the + smallest number in the series, so a grounded session logged far fewer tool-use tokens + than it used. This session's turns are deliberately distinct, so 750 can only come from + summing: first-turn selection gives 100, last-turn or max gives 400. + """ + grounded = self._grounded_messages() + + usage = self._session_usage(handler, mock_logging_obj, grounded, self.NATIVE_AUDIO_MODEL) + assert usage.prompt_tokens_details.tool_use_tokens == sum(self.TOOL_USE_PER_TURN) + + @staticmethod + def _grounding_frame(metadata: dict[str, object]) -> dict[str, object]: + """One server frame carrying grounding metadata, the way Live reports it.""" + return {"type": "response.done", "serverContent": {"groundingMetadata": metadata}} + + def test_web_grounding_is_counted_so_it_can_be_billed(self, handler, mock_logging_obj): + """Live reports grounding in the server frames and never in usageMetadata. + + Nothing read those frames, so web_search_requests stayed unset and the cost path's only + trigger for the per-query grounding charge never fired. Google bills a grounded Live + prompt on top of its tokens, so the whole fee was missing from the bill. + """ + messages = [ + self._grounding_frame( + { + "webSearchQueries": ["who won the 2026 world cup final"], + "groundingChunks": [{"web": {"uri": "https://example.com"}}], + } + ), + *self._live_messages(self.AUDIO_SESSION[:1]), + ] + + usage = self._session_usage(handler, mock_logging_obj, messages, self.NATIVE_AUDIO_MODEL) + + assert usage.prompt_tokens_details.web_search_requests == 1, "a grounded turn must report its query" + assert getattr(usage.prompt_tokens_details, "google_maps_grounding_requests", None) is None + + def test_maps_grounding_is_counted_under_its_own_sku(self, handler, mock_logging_obj): + """Maps grounding is a separate SKU from web search, so it needs its own counter. + + A maps-only turn carries grounding chunks but no webSearchQueries, so counting queries + alone would report nothing and bill nothing. + """ + messages = [ + self._grounding_frame({"groundingChunks": [{"maps": {"placeId": "abc123"}}]}), + *self._live_messages(self.AUDIO_SESSION[:1]), + ] + + usage = self._session_usage(handler, mock_logging_obj, messages, self.NATIVE_AUDIO_MODEL) + + assert usage.prompt_tokens_details.google_maps_grounding_requests == 1 + assert getattr(usage.prompt_tokens_details, "web_search_requests", None) is None + + def test_an_ungrounded_session_reports_no_grounding(self, handler, mock_logging_obj): + """The counters must stay absent when no tool ran, or every session pays a grounding fee.""" + usage = self._session_usage( + handler, mock_logging_obj, self._live_messages(self.AUDIO_SESSION[:1]), self.NATIVE_AUDIO_MODEL + ) + + assert getattr(usage.prompt_tokens_details, "web_search_requests", None) is None + assert getattr(usage.prompt_tokens_details, "google_maps_grounding_requests", None) is None + + def test_grounding_adds_its_query_fee_to_the_session_bill(self, handler, mock_logging_obj): + """The counter only matters if it reaches the bill, so assert against the cost, not the field. + + Same tokens either way: the difference between the two sessions is the grounding fee alone. + """ + turns = self.AUDIO_SESSION[:1] + plain = self._session_cost(handler, mock_logging_obj, self._live_messages(turns), self.NATIVE_AUDIO_MODEL) + grounded = self._session_cost( + handler, + mock_logging_obj, + [self._grounding_frame({"webSearchQueries": ["q"]}), *self._live_messages(turns)], + self.NATIVE_AUDIO_MODEL, + ) + + assert grounded > plain, "a grounded session must cost more than the same tokens ungrounded" + + def _priced_logging_obj(self) -> LiteLLMLoggingObj: + """A real logging object, since the session's price is handed to it turn by turn.""" + logging_obj = LiteLLMLoggingObj( + model=self.NATIVE_AUDIO_MODEL, + messages=[], + stream=True, + call_type="pass_through_endpoint", + start_time=datetime.now(), + litellm_call_id="live-session", + function_id="live", + ) + logging_obj.update_environment_variables( + model=self.NATIVE_AUDIO_MODEL, + user="u", + optional_params={}, + litellm_params={}, + call_type="pass_through_endpoint", + ) + logging_obj.model_call_details["custom_llm_provider"] = "vertex_ai" + return logging_obj + + def _billed_session( + self, handler: VertexAILivePassthroughLoggingHandler, messages: list[dict[str, object]] + ) -> tuple[float, CostBreakdown]: + logging_obj = self._priced_logging_obj() + result = handler.vertex_ai_live_passthrough_handler( + websocket_messages=messages, + logging_obj=logging_obj, + url_route="/vertex_ai/live", + start_time=datetime.now(), + end_time=datetime.now(), + request_body={}, + model=self.NATIVE_AUDIO_MODEL, + custom_llm_provider="vertex_ai", + ) + assert result["result"] is not None, "the handler must produce a usage-bearing response to bill" + assert logging_obj.cost_breakdown is not None, "the session's price must reach the logging object" + return result["result"]._hidden_params["response_cost"], logging_obj.cost_breakdown + + def test_each_grounded_turn_pays_its_own_query_fee(self, handler): + """Google charges the grounding fee per grounded prompt, not per session. + + Summing the session into one usage collapsed two grounded turns into one query, so the + second question was answered for free. The bill now grows by one fee per grounded turn. + """ + head, turn = self._live_messages(self.AUDIO_SESSION[:1]) + grounding = self._grounding_frame({"webSearchQueries": ["q"]}) + + plain_cost, _ = self._billed_session(handler, [head, turn, turn]) + one_cost, one_breakdown = self._billed_session(handler, [head, grounding, turn, turn]) + two_cost, two_breakdown = self._billed_session(handler, [head, grounding, turn, grounding, turn]) + + fee = one_cost - plain_cost + assert fee > 0, "a grounded turn must cost more than the same tokens ungrounded" + assert two_cost - plain_cost == pytest.approx(2 * fee), "two grounded turns must pay the fee twice" + assert two_breakdown["total_cost"] == pytest.approx(two_cost) + assert two_breakdown["tool_usage_cost"] == pytest.approx(2 * one_breakdown["tool_usage_cost"]) + + def test_a_query_repeated_across_turns_is_reported_once_per_turn(self, handler): + """The reported query count must agree with the bill, which charges every grounded turn. + + The session usage collapsed duplicate query strings across turns while the price was + per turn, so two turns asking the same question paid two fees yet reported one query. + Duplicates within one turn still collapse, since that turn ran one search. + """ + head, turn = self._live_messages(self.AUDIO_SESSION[:1]) + grounding = self._grounding_frame({"webSearchQueries": ["q"]}) + logging_obj = self._priced_logging_obj() + + result = handler.vertex_ai_live_passthrough_handler( + websocket_messages=[head, grounding, turn, grounding, turn], + logging_obj=logging_obj, + url_route="/vertex_ai/live", + start_time=datetime.now(), + end_time=datetime.now(), + request_body={}, + model=self.NATIVE_AUDIO_MODEL, + custom_llm_provider="vertex_ai", + ) + _, one_breakdown = self._billed_session(handler, [head, grounding, turn]) + repeated_within_turn = handler._session_usage( + [head, self._grounding_frame({"webSearchQueries": ["q", "q"]}), turn], self.NATIVE_AUDIO_MODEL + ) + + assert result["result"].usage.prompt_tokens_details.web_search_requests == 2 + assert logging_obj.cost_breakdown["tool_usage_cost"] == pytest.approx(2 * one_breakdown["tool_usage_cost"]) + assert repeated_within_turn.prompt_tokens_details.web_search_requests == 1 + + def test_the_fixed_cost_margin_is_charged_once_per_session(self, handler): + """A fixed cost margin is a flat per-request fee, and a Live session is one spend row. + + Pricing each turn on its own applied the fixed margin per turn, so a two-turn session paid it + twice. The session now carries the fixed margin once no matter how many turns it billed. + """ + head, turn = self._live_messages(self.AUDIO_SESSION[:1]) + grounding = self._grounding_frame({"webSearchQueries": ["q"]}) + messages = [head, grounding, turn, grounding, turn] + + plain_cost, _ = self._billed_session(handler, messages) + + fixed_amount = 0.01 + with patch.object(litellm, "cost_margin_config", {"vertex_ai": {"fixed_amount": fixed_amount}}): + margined_cost, breakdown = self._billed_session(handler, messages) + + assert margined_cost - plain_cost == pytest.approx( + fixed_amount + ), "a two-turn session must add the fixed margin once, not once per billed turn" + assert breakdown["margin_fixed_amount"] == pytest.approx(fixed_amount) + assert breakdown["margin_total_amount"] == pytest.approx(fixed_amount) + + def test_reporting_tool_use_tokens_does_not_move_the_bill(self, handler, mock_logging_obj): + """Deliberate boundary: these tokens are reported here, and priced nowhere. + + generic_cost_per_token reads the input bill out of prompt_tokens_details, and falls + back to prompt_tokens only when the details carry no text or a cache hit overlaps them, + so adding tool-use tokens to prompt_tokens is worth nothing on an ordinary Live turn and + over-charges against the cache-overlap correction when it is not. Pricing them belongs + in the shared input-cost path, beside the modality terms that already read the details. + """ + turns = self.AUDIO_SESSION[:3] + plain_cost = self._session_cost(handler, mock_logging_obj, self._live_messages(turns), self.NATIVE_AUDIO_MODEL) + grounded_cost = self._session_cost( + handler, mock_logging_obj, self._grounded_messages(), self.NATIVE_AUDIO_MODEL + ) + + assert plain_cost == pytest.approx(self._expected_session_cost(turns), rel=1e-9) + assert grounded_cost == pytest.approx(plain_cost, rel=1e-9), "reporting tool use must not move the bill" + + def test_a_malformed_details_entry_does_not_cost_the_whole_session(self, handler, mock_logging_obj): + """A ``*TokensDetails`` value that is not a list of objects must not take the session down. + + The handler's only error path returns no result at all, so one odd frame used to throw + while reading it and the whole session billed nothing. The good turns still bill. + """ + turns = self.AUDIO_SESSION[:3] + messages = self._live_messages(turns) + mangled = [dict(message) for message in messages] + mangled[1]["usageMetadata"] = {**mangled[1]["usageMetadata"], "promptTokensDetails": "TEXT"} + + usage = self._session_usage(handler, mock_logging_obj, mangled, self.NATIVE_AUDIO_MODEL) + + surviving = turns[1:] + assert usage.prompt_tokens_details.audio_tokens == sum(turn["prompt"][1] for turn in surviving) + assert usage.prompt_tokens_details.text_tokens == sum(turn["prompt"][0] for turn in surviving) + assert usage.prompt_tokens == sum(sum(turn["prompt"]) for turn in turns), "the totals still cover every turn" + + direct = handler._create_usage_object_from_metadata( + usage_metadata={ + "promptTokenCount": 40, + "candidatesTokenCount": 12, + "promptTokensDetails": [{"modality": "AUDIO", "tokenCount": 40}, "AUDIO"], + "candidatesTokensDetails": {"modality": "TEXT", "tokenCount": 12}, + }, + model=self.NATIVE_AUDIO_MODEL, + ) + assert direct.prompt_tokens_details.audio_tokens == 40, "the well-formed entry beside a bad one still counts" + assert direct.completion_tokens == 12 + + @pytest.mark.parametrize( + "label,prompt_details,candidate_details", + [ + ("text only", [("TEXT", 6)], [("TEXT", 2)]), + ("audio in", [("TEXT", 13), ("AUDIO", 127)], [("TEXT", 18)]), + ("image in", [("TEXT", 10), ("IMAGE", 258)], [("TEXT", 24)]), + ("frames in", [("TEXT", 11), ("IMAGE", 1032)], [("TEXT", 26)]), + ("audio both ways", [("TEXT", 13), ("AUDIO", 127)], [("TEXT", 29), ("AUDIO", 95)]), + ], + ) + def test_live_session_bills_each_modality_at_its_own_rate(self, handler, label, prompt_details, candidate_details): + """Every payload here is a real Vertex Live session's usageMetadata. + + Before the fix these billed the text share only, from 1x (text) to 55x under. + The expected amount is derived from the entry's own rates rather than hardcoded, + so this stays correct as prices move, and it is asserted exactly, so dropping a + modality and double-charging one both fail. + """ + from litellm.cost_calculator import completion_cost + from litellm.types.utils import ModelResponse + from litellm.utils import get_model_info + + model = self.NATIVE_AUDIO_MODEL + info = get_model_info(model=model, custom_llm_provider="vertex_ai") + + text_in = info["input_cost_per_token"] + audio_in = info.get("input_cost_per_audio_token") or text_in + image_in = info.get("input_cost_per_image_token") or text_in + text_out = info["output_cost_per_token"] + audio_out = info.get("output_cost_per_audio_token") or text_out + rate_in = {"TEXT": text_in, "AUDIO": audio_in, "IMAGE": image_in} + rate_out = {"TEXT": text_out, "AUDIO": audio_out} + + expected = sum(c * rate_in[m] for m, c in prompt_details) + sum(c * rate_out[m] for m, c in candidate_details) + + usage = handler._create_usage_object_from_metadata( + usage_metadata={ + "promptTokenCount": sum(c for _, c in prompt_details), + "candidatesTokenCount": sum(c for _, c in candidate_details), + "promptTokensDetails": [{"modality": m, "tokenCount": c} for m, c in prompt_details], + "candidatesTokensDetails": [{"modality": m, "tokenCount": c} for m, c in candidate_details], + }, + model=model, + ) + + cost = completion_cost( + completion_response=ModelResponse( + id="x", object="chat.completion", created=0, model=model, usage=usage, choices=[] + ), + model=f"vertex_ai/{model}", + custom_llm_provider="vertex_ai", + call_type="acompletion", + ) + + assert cost == pytest.approx(expected, rel=1e-9), label + + text_only = sum(c for m, c in prompt_details if m == "TEXT") * text_in + sum( + c for m, c in candidate_details if m == "TEXT" + ) * text_out + if any(m != "TEXT" for m, _ in prompt_details + candidate_details) and audio_in != text_in: + assert cost > text_only, f"{label}: non-text modalities must add cost" def test_vertex_ai_live_passthrough_handler_integration( self, handler, mock_logging_obj, sample_websocket_messages @@ -376,6 +788,7 @@ class TestVertexAILivePassthroughIntegration: """Create a mock logging object""" mock = MagicMock(spec=LiteLLMLoggingObj) mock.model_call_details = {} + mock._response_cost_calculator.return_value = None return mock @patch( @@ -509,6 +922,7 @@ class TestVertexAILivePassthroughErrorHandling: """Create a mock logging object""" mock = MagicMock(spec=LiteLLMLoggingObj) mock.model_call_details = {} + mock._response_cost_calculator.return_value = None return mock def test_invalid_websocket_messages_format(self): @@ -540,25 +954,24 @@ class TestVertexAILivePassthroughErrorHandling: result = handler._extract_usage_metadata_from_websocket_messages(messages) assert result is None - @patch( - "litellm.proxy.pass_through_endpoints.llm_provider_handlers.vertex_ai_live_passthrough_logging_handler.get_model_info" - ) - def test_cost_calculation_with_missing_model_info(self, mock_get_model_info): - """Test cost calculation when model info is missing""" + def test_usage_without_modality_details(self): + """Older payloads carry only the totals; fall back to them rather than reporting zero.""" handler = VertexAILivePassthroughLoggingHandler() - # Mock missing model info - mock_get_model_info.return_value = {} + usage = handler._create_usage_object_from_metadata( + usage_metadata={ + "promptTokenCount": 100, + "candidatesTokenCount": 50, + "totalTokenCount": 150, + }, + model="unknown-model", + ) - usage_metadata = { - "promptTokenCount": 100, - "candidatesTokenCount": 50, - "totalTokenCount": 150, - } - - # Should not raise an exception, should return 0 or handle gracefully - cost = handler._calculate_live_api_cost("unknown-model", usage_metadata) - assert cost == 0.0 + assert usage.prompt_tokens == 100 + assert usage.completion_tokens == 50 + assert usage.total_tokens == 150 + assert usage.prompt_tokens_details.audio_tokens is None + assert usage.prompt_tokens_details.image_tokens is None def test_handler_with_none_websocket_messages(self, mock_logging_obj): """Test handler with None websocket messages""" diff --git a/tests/proxy_behavior/auth/test_auth_object_prefetch.py b/tests/proxy_behavior/auth/test_auth_object_prefetch.py index e2d947f4284..cfa958500af 100644 --- a/tests/proxy_behavior/auth/test_auth_object_prefetch.py +++ b/tests/proxy_behavior/auth/test_auth_object_prefetch.py @@ -22,6 +22,11 @@ from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache pytestmark = pytest.mark.asyncio(loop_scope="session") +def _frozen_cache() -> UserApiKeyCache: + """The org entries carry a 5s TTL; a frozen clock keeps a slow first call from expiring them mid-test.""" + return UserApiKeyCache(in_memory_cache=InMemoryCache(clock=lambda: 1_000_000.0), redis_cache=None) + + def _dead_db() -> MagicMock: prisma = MagicMock(name="prisma_client") prisma.db.query_first = AsyncMock(return_value=None) @@ -58,9 +63,10 @@ async def test_join_binds_the_membership_to_the_requested_team(prisma): data={"user_id": user_id, "team_id": team_b, "litellm_budget_table": {"connect": {"budget_id": f"b-{run}"}}} ) - cache = UserApiKeyCache(in_memory_cache=InMemoryCache(), redis_cache=None) + cache = _frozen_cache() refs = AuthObjectRefs(user_id=user_id, team_id=team_a, membership_user_id=user_id, organization_id=org_id) await prefetch_auth_objects(refs=refs, user_api_key_cache=cache, prisma_client=prisma) + assert cache.in_memory_cache.get_cache(f"org_id:{org_id}") is not None dead_db = _dead_db() membership = await get_team_membership( @@ -100,7 +106,7 @@ async def test_join_reads_team_model_aliases_from_the_mapped_column(prisma): where={"team_id": team_id}, include={"litellm_model_table": True} ) - cache = UserApiKeyCache(in_memory_cache=InMemoryCache(), redis_cache=None) + cache = _frozen_cache() refs = AuthObjectRefs(user_id=None, team_id=team_id, membership_user_id=None, organization_id=None) await prefetch_auth_objects(refs=refs, user_api_key_cache=cache, prisma_client=prisma) @@ -144,7 +150,7 @@ async def test_join_reads_null_nested_lists_the_way_prisma_does(prisma): where={"user_id_team_id": {"user_id": user_id, "team_id": team_id}}, include={"litellm_budget_table": True} ) - cache = UserApiKeyCache(in_memory_cache=InMemoryCache(), redis_cache=None) + cache = _frozen_cache() refs = AuthObjectRefs(user_id=user_id, team_id=team_id, membership_user_id=user_id, organization_id=None) await prefetch_auth_objects(refs=refs, user_api_key_cache=cache, prisma_client=prisma) diff --git a/tests/proxy_behavior/spend/test_cache_activity.py b/tests/proxy_behavior/spend/test_cache_activity.py new file mode 100644 index 00000000000..f4a7e8eb2b2 --- /dev/null +++ b/tests/proxy_behavior/spend/test_cache_activity.py @@ -0,0 +1,102 @@ +""" +Behavior tests for the cache analytics queries against a real Postgres. The info-route +exclusion and the Unknown grouping live in SQL, so these tests are the ones that exercise +them; the endpoint wiring is unit-tested in +tests/test_litellm/proxy/analytics_endpoints/test_analytics_endpoints.py. +""" + +import json +import uuid +from datetime import datetime +from typing import Final + +import pytest + +from litellm.proxy.analytics_endpoints.cache_activity import ( + ERROR_BREAKDOWN_SQL, + GROUPS_SQL, + INFO_ROUTES_JSON, + KEY_ALIAS_OPTIONS_SQL, + MODEL_OPTIONS_SQL, +) + +pytestmark = pytest.mark.asyncio(loop_scope="session") + +DAY: Final = datetime(2001, 3, 7) +AT_NOON: Final = DAY.replace(hour=12) +RUN: Final = uuid.uuid4() +INFERENCE_KEY: Final = f"ca-inference-{RUN}" +INFO_ONLY_KEY: Final = f"ca-info-only-{RUN}" +INFERENCE_ALIAS: Final = f"alias-inference-{RUN}" +INFO_ONLY_ALIAS: Final = f"alias-info-only-{RUN}" +INFERENCE_MODEL: Final = f"gpt-5.4-mini-{RUN}" +INFO_ONLY_MODEL: Final = f"ghost-model-{RUN}" +NO_FILTER: Final = "[]" + + +async def _spend_log(db, api_key: str, call_type: str, status: str, model: str = "", error_code: str = "") -> None: + metadata: Final = {"error_information": {"error_code": error_code, "error_class": "ProxyException"}} + await db.execute_raw( + 'INSERT INTO "LiteLLM_SpendLogs" ("request_id", "call_type", "api_key", "startTime", "endTime", "model", ' + '"status", "metadata") VALUES ($1, $2, $3, $4::timestamp, $4::timestamp, $5, $6, $7::jsonb)', + str(uuid.uuid4()), + call_type, + api_key, + AT_NOON, + model, + status, + json.dumps(metadata if status == "failure" else {}), + ) + + +@pytest.fixture(scope="module", autouse=True) +async def seeded(db): + for token, alias in ((INFERENCE_KEY, INFERENCE_ALIAS), (INFO_ONLY_KEY, INFO_ONLY_ALIAS)): + await db.execute_raw( + 'INSERT INTO "LiteLLM_VerificationToken" ("token", "key_alias") VALUES ($1, $2)', token, alias + ) + await _spend_log(db, INFERENCE_KEY, "acompletion", "success", model=INFERENCE_MODEL) + await _spend_log(db, INFERENCE_KEY, "acompletion", "failure", model=INFERENCE_MODEL, error_code="429") + await _spend_log(db, INFERENCE_KEY, "", "failure", error_code="401") + await _spend_log(db, INFERENCE_KEY, "/model/info", "failure", error_code="401") + await _spend_log(db, INFO_ONLY_KEY, "/v1/models", "failure", model=INFO_ONLY_MODEL, error_code="401") + await _spend_log(db, INFO_ONLY_KEY, "/key/info", "success") + yield + keys: Final = [INFERENCE_KEY, INFO_ONLY_KEY] + await db.execute_raw('DELETE FROM "LiteLLM_SpendLogs" WHERE "api_key" = ANY($1::text[])', keys) + await db.execute_raw('DELETE FROM "LiteLLM_VerificationToken" WHERE "token" = ANY($1::text[])', keys) + + +async def _groups(db, key_aliases: list[str]) -> dict[str, dict]: + rows: Final = await db.query_raw(GROUPS_SQL, DAY, DAY, json.dumps(key_aliases), NO_FILTER, INFO_ROUTES_JSON) + return {row["call_type"]: row for row in rows} + + +async def test_groups_drop_info_routes_and_keep_unknown_for_rows_without_an_endpoint(db): + groups: Final = await _groups(db, [INFERENCE_ALIAS]) + assert set(groups) == {"acompletion", "Unknown"} + assert (groups["acompletion"]["api_requests"], groups["acompletion"]["failed_requests"]) == (1, 1) + assert (groups["Unknown"]["api_requests"], groups["Unknown"]["failed_requests"]) == (0, 1) + + +async def test_key_with_only_info_route_traffic_has_no_groups(db): + assert await _groups(db, [INFO_ONLY_ALIAS]) == {} + + +async def test_error_breakdown_drops_info_routes(db): + rows: Final = await db.query_raw( + ERROR_BREAKDOWN_SQL, DAY, DAY, json.dumps([INFERENCE_ALIAS, INFO_ONLY_ALIAS]), NO_FILTER, INFO_ROUTES_JSON + ) + assert {(row["call_type"], row["error_code"], row["count"]) for row in rows} == { + ("acompletion", "429", 1), + ("Unknown", "401", 1), + } + + +async def test_filter_options_only_offer_values_that_return_analytics(db): + key_alias_rows: Final = await db.query_raw(KEY_ALIAS_OPTIONS_SQL, DAY, DAY, INFO_ROUTES_JSON) + model_rows: Final = await db.query_raw(MODEL_OPTIONS_SQL, DAY, DAY, INFO_ROUTES_JSON) + key_aliases: Final = {row["key_alias"] for row in key_alias_rows} + models: Final = {row["model"] for row in model_rows} + assert INFERENCE_ALIAS in key_aliases and INFO_ONLY_ALIAS not in key_aliases + assert INFERENCE_MODEL in models and INFO_ONLY_MODEL not in models diff --git a/tests/proxy_migration_tests/test_prisma_toolchain.py b/tests/proxy_migration_tests/test_prisma_toolchain.py index 0ed33193a9b..4e2274cc582 100644 --- a/tests/proxy_migration_tests/test_prisma_toolchain.py +++ b/tests/proxy_migration_tests/test_prisma_toolchain.py @@ -37,7 +37,10 @@ from litellm_proxy_extras.prisma_toolchain import ( node_binary_path, prisma_bootstrap_timeout, prisma_command_timeout, + prisma_cli_available, prisma_migrate_deploy_timeout, + resolve_prisma_argv, + run_prisma, ) from litellm_proxy_extras.utils import ProxyExtrasDBManager @@ -401,3 +404,95 @@ def test_every_prisma_command_timeout_is_overridable(module: str) -> None: f"{module} still hardcodes a Prisma timeout at lines {literals}; " "route it through prisma_command_timeout() so it can be raised without a release" ) + + +FAKE_PRISMA_MODULE_MAIN = """import json +import sys + +print(json.dumps({"module_argv": sys.argv[1:]})) +""" + + +def _write_fake_prisma_module(tmp_path: Path) -> Path: + package_dir = tmp_path / "fakemodule" / "prisma" + package_dir.mkdir(parents=True) + (package_dir / "__init__.py").write_text("") + (package_dir / "__main__.py").write_text(FAKE_PRISMA_MODULE_MAIN) + return package_dir.parent + + +def _empty_bin(tmp_path: Path) -> Path: + bin_dir = tmp_path / "emptybin" + bin_dir.mkdir() + return bin_dir + + +def test_run_prisma_uses_the_module_when_the_console_script_is_not_on_path( + tmp_path: Path, monkeypatch: pytest.MonkeyPatch +) -> None: + empty_bin = _empty_bin(tmp_path) + module_root = _write_fake_prisma_module(tmp_path) + monkeypatch.setenv("PATH", str(empty_bin)) + + result = run_prisma( + ["prisma", "migrate", "deploy"], + timeout=60, + env={"PATH": str(empty_bin), "PYTHONPATH": str(module_root)}, + ) + + assert json.loads(result.stdout) == {"module_argv": ["migrate", "deploy"]} + + +def test_run_prisma_prefers_the_console_script_on_path( + toolchain_env: tuple[Path, Path], tmp_path: Path +) -> None: + _, log_path = toolchain_env + module_root = _write_fake_prisma_module(tmp_path) + + result = run_prisma( + ["prisma", "--version"], + timeout=60, + env={**os.environ, "PYTHONPATH": str(module_root)}, + ) + + assert [call["args"] for call in _fake_prisma_calls(log_path)] == [["--version"]] + assert "module_argv" not in result.stdout + + +def test_resolve_prisma_argv_leaves_an_explicit_cli_path_alone( + tmp_path: Path, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("PATH", str(_empty_bin(tmp_path))) + explicit = ("/app/.cache/prisma-python/prisma", "migrate", "deploy") + + assert resolve_prisma_argv(explicit) == explicit + + +def test_prisma_cli_is_unavailable_with_neither_script_nor_package( + tmp_path: Path, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("PATH", str(_empty_bin(tmp_path))) + monkeypatch.delitem(sys.modules, "prisma", raising=False) + monkeypatch.setattr(sys, "path", []) + + assert prisma_cli_available() is False + + +def test_prisma_cli_is_available_through_the_package_alone( + tmp_path: Path, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("PATH", str(_empty_bin(tmp_path))) + monkeypatch.delitem(sys.modules, "prisma", raising=False) + monkeypatch.setattr(sys, "path", [str(_write_fake_prisma_module(tmp_path))]) + + assert prisma_cli_available() is True + + +def test_prisma_cli_is_available_through_the_console_script_alone( + tmp_path: Path, monkeypatch: pytest.MonkeyPatch +) -> None: + monkeypatch.setenv("PATH", str(_write_fake_prisma(tmp_path))) + monkeypatch.delitem(sys.modules, "prisma", raising=False) + monkeypatch.setattr(sys, "path", []) + + assert prisma_cli_available() is True diff --git a/tests/proxy_unit_tests/test_proxy_server.py b/tests/proxy_unit_tests/test_proxy_server.py index d06eb0426c9..9c8dd90dd2b 100644 --- a/tests/proxy_unit_tests/test_proxy_server.py +++ b/tests/proxy_unit_tests/test_proxy_server.py @@ -2139,7 +2139,7 @@ async def test_model_info_alias_without_prisma(hidden): user_api_key_dict=UserAPIKeyAuth(models=[]), ) - models = resp["data"] + models = json.loads(resp.body)["data"] alias_found = any( m["model_name"] == model_alias @@ -2203,7 +2203,7 @@ async def test_proxy_model_group_alias_checks(prisma_client, hidden): # noqa: F resp = await model_info_v1( user_api_key_dict=UserAPIKeyAuth(models=[]), ) - models = resp["data"] + models = json.loads(resp.body)["data"] is_model_alias_in_list = False for item in models: if model_alias == item["model_name"]: @@ -2280,7 +2280,7 @@ async def test_proxy_model_group_info_rerank(prisma_client): # noqa: F811 # py resp = await model_info_v1( user_api_key_dict=UserAPIKeyAuth(models=[]), ) - models = resp["data"] + models = json.loads(resp.body)["data"] assert models[0]["model_info"]["mode"] == "rerank" resp = await model_group_info( user_api_key_dict=UserAPIKeyAuth(models=[]), diff --git a/tests/router_unit_tests/test_router_aresponses_streaming_fallback.py b/tests/router_unit_tests/test_router_aresponses_streaming_fallback.py index ee4750e9db8..0d33435cf7a 100644 --- a/tests/router_unit_tests/test_router_aresponses_streaming_fallback.py +++ b/tests/router_unit_tests/test_router_aresponses_streaming_fallback.py @@ -372,7 +372,7 @@ async def test_aresponses_fallback_on_in_stream_error_event(): raised = mock_fallback.await_args.kwargs["e"] assert isinstance(raised, MidStreamFallbackError) assert raised.status_code == 429 - assert isinstance(raised.original_exception, litellm.APIError) + assert isinstance(raised.original_exception, litellm.RateLimitError) assert raised.original_exception.status_code == 429 assert mock_fallback.await_args.kwargs["kwargs"]["input"] == "original question" diff --git a/tests/router_unit_tests/test_router_helper_utils.py b/tests/router_unit_tests/test_router_helper_utils.py index 7dbac243d55..b18bf9351c8 100644 --- a/tests/router_unit_tests/test_router_helper_utils.py +++ b/tests/router_unit_tests/test_router_helper_utils.py @@ -1,3 +1,4 @@ +import json import os import traceback from dotenv import load_dotenv @@ -10,7 +11,7 @@ import litellm from unittest.mock import patch, MagicMock, AsyncMock from create_mock_standard_logging_payload import create_standard_logging_payload from litellm.types.utils import StandardLoggingPayload -from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo +from litellm.types.router import Deployment, DeploymentTypedDict, LiteLLM_Params, ModelInfo from litellm.constants import DEFAULT_AUTO_ROUTER_MAX_INPUT_CHARS @@ -628,17 +629,35 @@ def test_deployment_callback_respects_cooldown_time(model_list): assert mock_set.call_args.kwargs["time_to_cooldown"] == 0 -def test_log_retry(model_list): - """Test if the '_log_retry' function is working correctly""" - import time - +@pytest.mark.parametrize("metadata_key", ["metadata", "litellm_metadata"]) +def test_log_retry(model_list: list[DeploymentTypedDict], metadata_key: str) -> None: + """log_retry appends one flat record per failed attempt, copies neither the request kwargs nor the + request metadata into it, counts every failed attempt of the request independently of the + per-hop attempted_retries, and never trusts a negative count planted before the first failure""" router = Router(model_list=model_list) + rate_limit_error = litellm.RateLimitError(message="slow down", llm_provider="openai", model="gpt-3.5-turbo") new_kwargs = router.log_retry( - kwargs={"metadata": {}}, - e=Exception(), + kwargs={ + "model": "gpt-3.5-turbo", + "api_key": "sk-must-not-be-recorded", + "messages": [{"role": "user", "content": "hi"}], + metadata_key: {"model_info": {"id": "deployment-1"}, "attempted_retries": 2, "user_api_key": "sk-proxy"}, + }, + e=rate_limit_error, ) - assert "metadata" in new_kwargs - assert "previous_models" in new_kwargs["metadata"] + assert json.loads(json.dumps(new_kwargs[metadata_key]["previous_models"])) == [ + { + "model_group": "gpt-3.5-turbo", + "deployment_id": "deployment-1", + "exception_type": "RateLimitError", + "exception_string": "litellm.RateLimitError: slow down", + "attempted_retries": 2, + } + ] + assert new_kwargs[metadata_key]["request_retry_count"] == 1 + assert router.log_retry(kwargs=new_kwargs, e=rate_limit_error)[metadata_key]["request_retry_count"] == 2 + planted_kwargs = {"model": "gpt-3.5-turbo", metadata_key: {"request_retry_count": -100}} + assert router.log_retry(kwargs=planted_kwargs, e=rate_limit_error)[metadata_key]["request_retry_count"] == 1 def test_update_usage(model_list): diff --git a/tests/rust-python-harness/AGENTS.md b/tests/rust-python-harness/AGENTS.md index 017668d4289..71e17541fd2 100644 --- a/tests/rust-python-harness/AGENTS.md +++ b/tests/rust-python-harness/AGENTS.md @@ -63,7 +63,7 @@ tests/rust-python-harness/ - Examples: `run e2e_parity --surface sdk --function ocr`, `run unit_tests_parity --function ocr --pytest-arg=-x`, or `run all --function ocr` - `cli/catalog.py` discovers strategies, validates their Python definitions, and orders them; `cli/__init__.py` builds the Click command tree; `cli/commands.py` runs selected cases - `e2e_parity/` compares SDK objects, exceptions, callbacks, and streams, or gateway HTTP responses -- `trace_parity/` compares mapped operations, call counts, and required execution ordering; before running it rebuilds the native bridge with the `trace-parity` feature whenever `litellm-rust` sources are newer than the installed extension (`shared/native_build.py`) +- `trace_parity/` prints every collected Python call under `litellm/` and every Rust span without comparing them; mappings only filter the separate unit-test mapping strategy. Before running it rebuilds the native bridge with the `trace-parity` feature whenever `litellm-rust` sources are newer than the installed extension (`shared/native_build.py`) - E2E and trace strategies load their registered module cases and run surface-specific execution from their folders - `unit_tests_mapping/contracts.py` owns typed harness-side mapping contracts, per-function contracts live below `cases/`, and `mappings.py` exports the registry; live test discovery derives unmapped Python and Rust-only tests without an exhaustive manifest - `unit_tests_mapping/runner.py` validates confirmed mappings against the live Python and Rust inventories and attaches the derived status report diff --git a/tests/rust-python-harness/cli/__init__.py b/tests/rust-python-harness/cli/__init__.py index 13b995825dd..d2bfdc55b19 100644 --- a/tests/rust-python-harness/cli/__init__.py +++ b/tests/rust-python-harness/cli/__init__.py @@ -58,16 +58,29 @@ def _strategy_command(strategy: Strategy) -> click.Command: help=runner_argument.help, ) ) + for runner_option in strategy.definition.runner_options: + name: Final = runner_option.option.removeprefix("--").replace("-", "_") + params.append( + click.Option( + (runner_option.option, name), + type=click.Choice(runner_option.choices), + help=runner_option.help, + ) + ) def run_strategy( sdk_functions: tuple[str, ...], surface: str | None = None, runner_args: tuple[str, ...] = (), + **runner_options: str | None, ) -> int: selected_functions: Final = cast(frozenset[SdkFunction], frozenset(sdk_functions)) selected_surface: Final = cast(Surface | None, surface) cases: Final = select_cases((strategy,), selected_functions, selected_surface) - return run_command((strategy,), cases, runner_args) + option_args: Final = tuple( + f"--{name.replace('_', '-')}={value}" for name, value in runner_options.items() if value is not None + ) + return run_command((strategy,), cases, (*runner_args, *option_args)) return click.Command( strategy.id, diff --git a/tests/rust-python-harness/cli/catalog.py b/tests/rust-python-harness/cli/catalog.py index 03eb032d9c6..073873d0121 100644 --- a/tests/rust-python-harness/cli/catalog.py +++ b/tests/rust-python-harness/cli/catalog.py @@ -21,9 +21,7 @@ def _load_strategy_module(name: str, folder: Path, prefix: str | None) -> Module if prefix is not None: return importlib.import_module(f"{prefix}.{name}") module_name: Final = _synthetic_module_name(folder) - spec: Final = importlib.util.spec_from_file_location( - module_name, folder / "__init__.py" - ) + spec: Final = importlib.util.spec_from_file_location(module_name, folder / "__init__.py") if spec is None or spec.loader is None: raise ValueError(f"{folder}: cannot load strategy package") module: Final = importlib.util.module_from_spec(spec) @@ -59,9 +57,7 @@ def _load_strategy(name: str, folder: Path, prefix: str | None) -> Strategy: if duplicates: raise ValueError(f"{folder}: duplicate strategy cases: {duplicates}") expected: Final = frozenset( - (surface, function) - for surface in (definition.surfaces or (None,)) - for function in SDK_FUNCTIONS + (surface, function) for surface in (definition.surfaces or (None,)) for function in SDK_FUNCTIONS ) actual: Final = frozenset(keys) if actual != expected: @@ -73,8 +69,7 @@ def _load_strategy(name: str, folder: Path, prefix: str | None) -> Strategy: incompatible: Final = tuple( (case.surface, case.sdk_function) for case in definition.cases - if case.spec.disposition is CaseDisposition.RUNNABLE - and not isinstance(case.spec, definition.runnable_spec) + if case.spec.disposition is CaseDisposition.RUNNABLE and not isinstance(case.spec, definition.runnable_spec) ) if incompatible: raise ValueError(f"{folder}: runnable cases do not match {definition.runnable_spec.__name__}: {incompatible}") @@ -102,14 +97,10 @@ def _load_strategy(name: str, folder: Path, prefix: str | None) -> Strategy: def load_catalog(root: Path | None = None) -> tuple[Strategy, ...]: resolved: Final = STRATEGIES_ROOT if root is None else root prefix: Final = _STRATEGIES_PACKAGE.__name__ if resolved == STRATEGIES_ROOT else None - folders: Final = tuple( - info.name for info in pkgutil.iter_modules([str(resolved)]) if info.ispkg - ) + folders: Final = tuple(info.name for info in pkgutil.iter_modules([str(resolved)]) if info.ispkg) if not folders: raise ValueError(f"No strategy packages found below {resolved}") - strategies: Final = tuple( - _load_strategy(name, resolved / name, prefix) for name in sorted(folders) - ) + strategies: Final = tuple(_load_strategy(name, resolved / name, prefix) for name in sorted(folders)) ids: Final = [strategy.id for strategy in strategies] if len(set(ids)) != len(ids): raise ValueError(f"Duplicate strategy id in {resolved}") diff --git a/tests/rust-python-harness/cli/commands.py b/tests/rust-python-harness/cli/commands.py index f94c3277dc2..e51bbb5d966 100644 --- a/tests/rust-python-harness/cli/commands.py +++ b/tests/rust-python-harness/cli/commands.py @@ -21,8 +21,7 @@ def select_cases( case for strategy in strategies for case in strategy.cases - if (not sdk_functions or case.sdk_function in sdk_functions) - and (surface is None or case.surface == surface) + if (not sdk_functions or case.sdk_function in sdk_functions) and (surface is None or case.surface == surface) ) @@ -32,8 +31,7 @@ def run_command( runner_args: Sequence[str] = (), ) -> int: grouped: Final = { - strategy.id: tuple(case for case in cases if case.strategy_id == strategy.id) - for strategy in strategies + strategy.id: tuple(case for case in cases if case.strategy_id == strategy.id) for strategy in strategies } visible: Final = tuple(strategy for strategy in strategies if grouped[strategy.id]) runners: Final = tuple(replace(strategy, cases=grouped[strategy.id]) for strategy in visible) diff --git a/tests/rust-python-harness/cli/test_cli.py b/tests/rust-python-harness/cli/test_cli.py index 226c89843d0..5641aa8a539 100644 --- a/tests/rust-python-harness/cli/test_cli.py +++ b/tests/rust-python-harness/cli/test_cli.py @@ -242,7 +242,7 @@ def _assert_unavailable_cell(strategy: Strategy, case: HarnessCase, section_titl def test_every_unavailable_case_finishes_and_explains_itself() -> None: section_titles: Final = { "e2e_parity": "End-to-end parity outcomes", - "trace_parity": "trace comparisons", + "trace_parity": "traces", "unit_tests_mapping": "Python/Rust unit-test mappings", "unit_tests_parity": "Python backend parity outcomes", "unit_tests_rust": "Native Rust unit-test outcomes", @@ -359,6 +359,25 @@ def test_strategy_command_forwards_repeated_filters_and_runner_arguments( ] +def test_trace_command_forwards_engine_and_scenario(monkeypatch: pytest.MonkeyPatch) -> None: + cli: Final = importlib.import_module("tests.rust-python-harness.cli") + captured: list[tuple[str, ...]] = [] + + def capture_run( + strategies: Sequence[Strategy], + cases: Sequence[HarnessCase], + runner_args: Sequence[str] = (), + ) -> int: + del strategies, cases + captured.append(tuple(runner_args)) + return 0 + + monkeypatch.setattr(cli, "run_command", capture_run) + + assert main(["run", "trace_parity", "--scenario", "async-mistral", "--engine", "python"]) == 0 + assert captured == [("async-mistral", "--engine=python")] + + def test_omitted_surface_selects_every_strategy_surface(monkeypatch: pytest.MonkeyPatch) -> None: cli: Final = importlib.import_module("tests.rust-python-harness.cli") selected: list[str] = [] diff --git a/tests/rust-python-harness/conftest.py b/tests/rust-python-harness/conftest.py index d50d0fa4204..c487b25a9cc 100644 --- a/tests/rust-python-harness/conftest.py +++ b/tests/rust-python-harness/conftest.py @@ -19,9 +19,7 @@ def subprocess_test_environment(monkeypatch: pytest.MonkeyPatch) -> None: def cargo_project(tmp_path: Path) -> Callable[[str, str], Path]: def create(package: str, source: str) -> Path: manifest: Final = tmp_path / "Cargo.toml" - manifest.write_text( - f'[package]\nname = "{package}"\nversion = "0.1.0"\nedition = "2021"\n[workspace]\n' - ) + manifest.write_text(f'[package]\nname = "{package}"\nversion = "0.1.0"\nedition = "2021"\n[workspace]\n') (tmp_path / "src").mkdir() (tmp_path / "src/lib.rs").write_text(source) return manifest diff --git a/tests/rust-python-harness/shared/native_build.py b/tests/rust-python-harness/shared/native_build.py index 8693cf3bac2..f67488cecb4 100644 --- a/tests/rust-python-harness/shared/native_build.py +++ b/tests/rust-python-harness/shared/native_build.py @@ -16,6 +16,11 @@ _RUST_ROOT: Final = "litellm-rust" _LOCKFILE: Final = "Cargo.lock" _SOURCE_SUFFIXES: Final = frozenset({".rs", ".toml"}) _FAILURE_OUTPUT_LINES: Final = 15 +_TRACE_CHECK: Final = ( + "from litellm.rust_bridge import get_native_bridge; " + "bridge = get_native_bridge(); " + "raise SystemExit(0 if bridge is not None and getattr(bridge, '_trace', None) is not None else 1)" +) def needs_rebuild(native_mtime: float | None, newest_source_mtime: float | None) -> bool: @@ -73,6 +78,17 @@ def _rebuild(repo_root: Path) -> tuple[bool, str]: return completed.returncode == 0, "\n".join(lines[-_FAILURE_OUTPUT_LINES:]) +def _installed_bridge_has_trace(repo_root: Path) -> bool: + completed: Final = subprocess.run( + (sys.executable, "-c", _TRACE_CHECK), + cwd=repo_root, + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + check=False, + ) + return completed.returncode == 0 + + def trace_bridge_error() -> str | None: bridge: Final = get_native_bridge() if bridge is None: @@ -85,7 +101,10 @@ def trace_bridge_error() -> str | None: def ensure_trace_bridge(repo_root: Path) -> str | None: native_path: Final = _native_module_path() native_mtime: Final = native_path.stat().st_mtime if native_path is not None and native_path.exists() else None - if needs_rebuild(native_mtime, _newest_source_mtime(repo_root)): + rebuild_required: Final = needs_rebuild( + native_mtime, _newest_source_mtime(repo_root) + ) or not _installed_bridge_has_trace(repo_root) + if rebuild_required: print(f"Rebuilding native Rust bridge ({BRIDGE_FEATURE} feature)...", flush=True) succeeded: Final output: Final diff --git a/tests/rust-python-harness/shared/parity/fixtures/recording.py b/tests/rust-python-harness/shared/parity/fixtures/recording.py index ee0d4b6de7b..cb6ed968b90 100644 --- a/tests/rust-python-harness/shared/parity/fixtures/recording.py +++ b/tests/rust-python-harness/shared/parity/fixtures/recording.py @@ -191,6 +191,7 @@ class _RecordingHandler(LocalHttpHandler): self.end_headers() self.wfile.write(body) + def _recording_provider(spec: UpstreamEndpoint) -> AbstractContextManager[_RecordingProvider]: return serve_in_thread(_RecordingProvider(spec)) diff --git a/tests/rust-python-harness/shared/parity/fixtures/store.py b/tests/rust-python-harness/shared/parity/fixtures/store.py index 270af2a7625..1145b5d7d27 100644 --- a/tests/rust-python-harness/shared/parity/fixtures/store.py +++ b/tests/rust-python-harness/shared/parity/fixtures/store.py @@ -15,6 +15,8 @@ from .cassette import deserialize_cassette, serialize_cassette from .recording import RecordedInteraction FIXTURE_SCHEMA_VERSION: Final = 1 + + class FixtureInput(Protocol): def canonical_input(self) -> dict[str, object]: ... diff --git a/tests/rust-python-harness/shared/parity/fixtures/test_pipeline.py b/tests/rust-python-harness/shared/parity/fixtures/test_pipeline.py index 4535ba05bf6..b162e4949d2 100644 --- a/tests/rust-python-harness/shared/parity/fixtures/test_pipeline.py +++ b/tests/rust-python-harness/shared/parity/fixtures/test_pipeline.py @@ -45,8 +45,8 @@ class _Upstream(LocalHttpServer): super().__init__(("127.0.0.1", 0), _UpstreamHandler) self.response_status: Final = status -class _UpstreamHandler(LocalHttpHandler): +class _UpstreamHandler(LocalHttpHandler): def do_POST(self) -> None: length: Final = int(self.headers.get("content-length") or "0") self.rfile.read(length) @@ -59,6 +59,7 @@ class _UpstreamHandler(LocalHttpHandler): self.end_headers() self.wfile.write(body) + def _upstream(status: int = 200) -> AbstractContextManager[_Upstream]: return serve_in_thread(_Upstream(status)) diff --git a/tests/rust-python-harness/shared/parity/fixtures/test_recording.py b/tests/rust-python-harness/shared/parity/fixtures/test_recording.py index 6181f18e89a..c1e7c2af8d8 100644 --- a/tests/rust-python-harness/shared/parity/fixtures/test_recording.py +++ b/tests/rust-python-harness/shared/parity/fixtures/test_recording.py @@ -238,6 +238,7 @@ class _ControlledUpstreamHandler(LocalHttpHandler): self.end_headers() self.wfile.write(body) + def _controlled_upstream( stream_chunks: tuple[bytes, ...] = _SSE_CHUNKS, ) -> AbstractContextManager[_ControlledUpstream]: diff --git a/tests/rust-python-harness/shared/reporting/models.py b/tests/rust-python-harness/shared/reporting/models.py index 1ebba6c9793..4a46a6d4cfe 100644 --- a/tests/rust-python-harness/shared/reporting/models.py +++ b/tests/rust-python-harness/shared/reporting/models.py @@ -180,15 +180,11 @@ class HarnessRun: @property def unique_checks(self) -> int: - return len( - {nodeid for result in self.results.values() for nodeid in result.collected} - ) + return len({nodeid for result in self.results.values() for nodeid in result.collected}) @property def completed_checks(self) -> int: - return len( - {nodeid for result in self.results.values() for nodeid in result.completed} - ) + return len({nodeid for result in self.results.values() for nodeid in result.completed}) @classmethod def from_cases(cls, cases: Iterable[HarnessCase]) -> HarnessRun: diff --git a/tests/rust-python-harness/shared/reporting/strategy.py b/tests/rust-python-harness/shared/reporting/strategy.py index 7e76f035e20..d8e9d9e5ba9 100644 --- a/tests/rust-python-harness/shared/reporting/strategy.py +++ b/tests/rust-python-harness/shared/reporting/strategy.py @@ -67,6 +67,13 @@ class RunnerArgumentDefinition: metavar: str = "ARG" +@dataclass(frozen=True, slots=True) +class RunnerOptionDefinition: + option: str + help: str + choices: tuple[str, ...] + + class StrategyRunner(Protocol): def __call__( self, @@ -90,3 +97,4 @@ class StrategyDefinition: render: StrategyRenderer surfaces: tuple[Surface, ...] = () runner_argument: RunnerArgumentDefinition | None = None + runner_options: tuple[RunnerOptionDefinition, ...] = () diff --git a/tests/rust-python-harness/shared/test_native_build.py b/tests/rust-python-harness/shared/test_native_build.py index f3e5aead846..dc08bc1a2b6 100644 --- a/tests/rust-python-harness/shared/test_native_build.py +++ b/tests/rust-python-harness/shared/test_native_build.py @@ -89,8 +89,8 @@ def test_ensure_trace_bridge_reports_failed_rebuild(tmp_path: Final, monkeypatch assert "boom" in message -def test_ensure_trace_bridge_flags_missing_trace_feature_without_rebuild( - tmp_path: Final, monkeypatch: pytest.MonkeyPatch +def test_ensure_trace_bridge_rebuilds_when_trace_feature_is_missing( + tmp_path: Final, monkeypatch: pytest.MonkeyPatch, capsys: pytest.CaptureFixture[str] ) -> None: native: Final = tmp_path / "_native.abi3.so" native.write_bytes(b"") @@ -105,12 +105,17 @@ def test_ensure_trace_bridge_flags_missing_trace_feature_without_rebuild( state.rebuilt = True return True, "" + def fake_get_native_bridge() -> SimpleNamespace: + assert state.rebuilt + return SimpleNamespace(_trace=object()) + monkeypatch.setattr(native_build, "_native_module_path", lambda: native) monkeypatch.setattr(native_build, "_rebuild", fake_rebuild) - monkeypatch.setattr(native_build, "get_native_bridge", lambda: SimpleNamespace(_trace=None)) + monkeypatch.setattr(native_build, "_installed_bridge_has_trace", lambda repo_root: False) + monkeypatch.setattr(native_build, "get_native_bridge", fake_get_native_bridge) message: Final = native_build.ensure_trace_bridge(tmp_path) - assert message is not None - assert "_trace" in message - assert state.rebuilt is False + assert message is None + assert state.rebuilt is True + assert "Rebuilding native Rust bridge" in capsys.readouterr().out diff --git a/tests/rust-python-harness/shared/tracing/profiler.py b/tests/rust-python-harness/shared/tracing/profiler.py index abfb6a2425d..e72a36a5289 100644 --- a/tests/rust-python-harness/shared/tracing/profiler.py +++ b/tests/rust-python-harness/shared/tracing/profiler.py @@ -2,7 +2,8 @@ from __future__ import annotations import sys import threading -from collections.abc import Generator, Iterator, Mapping +import warnings +from collections.abc import Callable, Generator, Iterator, Mapping from contextlib import contextmanager from dataclasses import dataclass from functools import lru_cache @@ -32,6 +33,7 @@ class PythonProfiler: self._source_root: Final = str(source_root.resolve()) + "/" self._seen_frames: Final[set[FrameType]] = set() self._event_ids: Final[dict[FrameType, int]] = {} + self._lock: Final = threading.Lock() self.events: Final[list[FunctionTraceEvent]] = [] def __call__(self, frame: FrameType, event: str, _arg: object) -> None: @@ -40,14 +42,15 @@ class PythonProfiler: function_name: Final = self.function_name(frame) if function_name is None: return - event_id: Final = len(self.events) - parent_id: Final = next( - (self._event_ids[ancestor] for ancestor in _frame_ancestors(frame) if ancestor in self._event_ids), - None, - ) - self._seen_frames.add(frame) - self._event_ids[frame] = event_id - self.events.append(FunctionTraceEvent(id=event_id, parent_id=parent_id, function=function_name)) + with self._lock: + event_id: Final = len(self.events) + parent_id: Final = next( + (self._event_ids[ancestor] for ancestor in _frame_ancestors(frame) if ancestor in self._event_ids), + None, + ) + self._seen_frames.add(frame) + self._event_ids[frame] = event_id + self.events.append(FunctionTraceEvent(id=event_id, parent_id=parent_id, function=function_name)) def function_name(self, frame: FrameType) -> str | None: code: Final = frame.f_code @@ -137,21 +140,51 @@ def _frame_ancestors(frame: FrameType) -> Generator[FrameType]: @contextmanager -def profile_python(source_root: Path, *, threads: bool = False) -> Generator[PythonProfiler]: - profiler: Final = PythonProfiler(source_root) +def _installed_profiler(profiler: Callable[[FrameType, str, object], None], *, threads: bool) -> Generator[None]: + if threads and sys.version_info >= (3, 12): + tool_id: Final = next((slot for slot in (2, 3, 4, 0, 1, 5) if sys.monitoring.get_tool(slot) is None), None) + if tool_id is None: + raise RuntimeError("no sys.monitoring tool ID is available for Python trace collection") + + def started(_code: CodeType, _offset: int) -> None: + profiler(sys._getframe(1), "call", None) + + sys.monitoring.use_tool_id(tool_id, "litellm-python-trace") + try: + sys.monitoring.register_callback(tool_id, sys.monitoring.events.PY_START, started) + sys.monitoring.set_events(tool_id, sys.monitoring.events.PY_START) + yield + finally: + sys.monitoring.set_events(tool_id, 0) + sys.monitoring.register_callback(tool_id, sys.monitoring.events.PY_START, None) + sys.monitoring.free_tool_id(tool_id) + return + if threads: + warnings.warn( + "Python <3.12 cannot trace existing worker threads; use Python 3.12+ for complete threaded traces", + RuntimeWarning, + stacklevel=3, + ) previous_thread: Final = threading.getprofile() if threads: threading.setprofile(profiler) previous: Final = sys.getprofile() sys.setprofile(profiler) try: - yield profiler + yield finally: sys.setprofile(previous) if threads: threading.setprofile(previous_thread) +@contextmanager +def profile_python(source_root: Path, *, threads: bool = False) -> Generator[PythonProfiler]: + profiler: Final = PythonProfiler(source_root) + with _installed_profiler(profiler, threads=threads): + yield profiler + + @contextmanager def profile_python_function_usage( source_root: Path, @@ -160,14 +193,5 @@ def profile_python_function_usage( threads: bool = False, ) -> Generator[PythonFunctionUsageProfiler]: profiler: Final = PythonFunctionUsageProfiler(source_root, functions) - previous_thread: Final = threading.getprofile() - if threads: - threading.setprofile(profiler) - previous: Final = sys.getprofile() - sys.setprofile(profiler) - try: + with _installed_profiler(profiler, threads=threads): yield profiler - finally: - sys.setprofile(previous) - if threads: - threading.setprofile(previous_thread) diff --git a/tests/rust-python-harness/shared/tracing/steps.py b/tests/rust-python-harness/shared/tracing/steps.py index 2475f0fdcc5..492ffab64e5 100644 --- a/tests/rust-python-harness/shared/tracing/steps.py +++ b/tests/rust-python-harness/shared/tracing/steps.py @@ -76,7 +76,7 @@ def _span_for(engine: Engine, function: str, mappings: Sequence[TraceMapping]) - def pipeline_projection( - engine: Engine, events: Sequence[FunctionTraceEvent], mappings: Sequence[TraceMapping] + engine: Engine, events: Sequence[FunctionTraceEvent], mappings: Sequence[TraceMapping] | None = None ) -> PipelineProjection: raw_parents: dict[int, int | None] = {} projected_ids: set[int] = set() @@ -88,7 +88,7 @@ def pipeline_projection( if event.parent_id is not None and event.parent_id not in raw_parents: raise ValueError(f"trace event {event.id} references unknown or later parent {event.parent_id}") raw_parents[event.id] = event.parent_id - span = _span_for(engine, event.function, mappings) + span = event.function if mappings is None else _span_for(engine, event.function, mappings) if span is None: unmatched += 1 continue @@ -181,12 +181,7 @@ class TraceDiff: @property def matches(self) -> bool: - return ( - not self.python_only - and not self.rust_only - and not self.missing_mappings - and self.shared_order_matches - ) + return not self.python_only and not self.rust_only and not self.missing_mappings and self.shared_order_matches def _missing_mappings( @@ -257,9 +252,7 @@ def trace_diff( rust_counts: Final = Counter(rust_spans) python_only_counts: Final = python_counts - rust_counts rust_only_counts: Final = rust_counts - python_counts - python_only: Final = tuple( - span for span, count in python_only_counts.items() for _ in range(count) - ) + python_only: Final = tuple(span for span, count in python_only_counts.items() for _ in range(count)) rust_only: Final = tuple(span for span, count in rust_only_counts.items() for _ in range(count)) first_difference: Final = _first_difference(python, rust, mappings, contract) return TraceDiff( diff --git a/tests/rust-python-harness/shared/tracing/test_profiler.py b/tests/rust-python-harness/shared/tracing/test_profiler.py index 616e9c23e75..b9a07f249a3 100644 --- a/tests/rust-python-harness/shared/tracing/test_profiler.py +++ b/tests/rust-python-harness/shared/tracing/test_profiler.py @@ -4,9 +4,10 @@ import asyncio import sys import threading from collections.abc import Callable +from concurrent.futures import ThreadPoolExecutor from functools import wraps from pathlib import Path -from types import FunctionType +from types import FrameType, FunctionType from typing import Final, ParamSpec, TypeVar, cast import pytest @@ -41,11 +42,12 @@ def _events_named(profiler: PythonProfiler, name: str) -> tuple[FunctionTraceEve return tuple(event for event in profiler.events if event.function.endswith(name)) -def test_profiler_keeps_repeated_calls() -> None: +@pytest.mark.parametrize("threads", (False, True)) +def test_profiler_keeps_repeated_calls(threads: bool) -> None: def called() -> None: return None - with profile_python(Path(__file__).parent) as profiler: + with profile_python(Path(__file__).parent, threads=threads) as profiler: called() called() @@ -60,14 +62,15 @@ def test_profiler_qualifies_decorated_methods_by_class() -> None: assert _module_qualnames(__name__)[cast(FunctionType, Decorated.call.__wrapped__).__code__] == "Decorated.call" -def test_profiler_records_real_frame_ancestry() -> None: +@pytest.mark.parametrize("threads", (False, True)) +def test_profiler_records_real_frame_ancestry(threads: bool) -> None: def called() -> None: return None def outer() -> None: called() - with profile_python(Path(__file__).parent) as profiler: + with profile_python(Path(__file__).parent, threads=threads) as profiler: outer() outer_event, called_event = (event for event in profiler.events if event.function.endswith(("outer", "called"))) @@ -84,18 +87,20 @@ def test_profiler_restores_previous_profiler_after_failure() -> None: assert sys.getprofile() is previous -def test_profiler_does_not_count_coroutine_resumption_as_another_call() -> None: +@pytest.mark.parametrize("threads", (False, True)) +def test_profiler_does_not_count_coroutine_resumption_as_another_call(threads: bool) -> None: async def suspended() -> None: await asyncio.sleep(0) await asyncio.sleep(0) - with profile_python(Path(__file__).parent) as profiler: + with profile_python(Path(__file__).parent, threads=threads) as profiler: asyncio.run(suspended()) assert len(_events_named(profiler, "suspended")) == 1 -def test_profiler_preserves_parent_across_coroutine_suspension() -> None: +@pytest.mark.parametrize("threads", (False, True)) +def test_profiler_preserves_parent_across_coroutine_suspension(threads: bool) -> None: def called() -> None: return None @@ -103,7 +108,7 @@ def test_profiler_preserves_parent_across_coroutine_suspension() -> None: await asyncio.sleep(0) called() - with profile_python(Path(__file__).parent) as profiler: + with profile_python(Path(__file__).parent, threads=threads) as profiler: asyncio.run(suspended()) suspended_event: Final = _events_named(profiler, "suspended")[0] @@ -124,6 +129,96 @@ def test_profiler_captures_worker_threads_when_enabled() -> None: assert called_event.parent_id is None +@pytest.mark.skipif(sys.version_info < (3, 12), reason="existing worker capture requires sys.monitoring") +@pytest.mark.parametrize("prewarm", (False, True)) +def test_profiler_captures_reused_workers_without_leaking_between_sessions(prewarm: bool) -> None: + def called() -> None: + return None + + with ThreadPoolExecutor(max_workers=1) as executor: + if prewarm: + executor.submit(called).result(timeout=5) + with profile_python(Path(__file__).parent, threads=True) as first: + executor.submit(called).result(timeout=5) + executor.submit(called).result(timeout=5) + with profile_python(Path(__file__).parent, threads=True) as second: + executor.submit(called).result(timeout=5) + executor.submit(called).result(timeout=5) + + assert len(_events_named(first, "called")) == 1 + assert len(_events_named(second, "called")) == 1 + + +def test_profiler_restores_main_and_worker_hooks_after_failure() -> None: + previous: Final = sys.getprofile() + previous_thread: Final = threading.getprofile() + + with ThreadPoolExecutor(max_workers=1) as executor: + worker_previous: Final = executor.submit(sys.getprofile).result(timeout=5) + with pytest.raises(RuntimeError, match="stop"): + with profile_python(Path(__file__).parent, threads=True): + raise RuntimeError("stop") + assert executor.submit(sys.getprofile).result(timeout=5) is worker_previous + + assert sys.getprofile() is previous + assert threading.getprofile() is previous_thread + + +@pytest.mark.skipif(sys.version_info < (3, 12), reason="existing worker capture requires sys.monitoring") +def test_function_usage_profiler_captures_reused_workers() -> None: + def selected() -> None: + return None + + function: Final = f"{Path(__file__).name}:{selected.__code__.co_firstlineno} {selected.__qualname__}" + with ThreadPoolExecutor(max_workers=1) as executor: + executor.submit(selected).result(timeout=5) + with profile_python_function_usage(Path(__file__).parent, frozenset((function,)), threads=True) as profiler: + executor.submit(selected).result(timeout=5) + + assert profiler.called == {function} + + +@pytest.mark.skipif(sys.version_info < (3, 12), reason="independent thread hooks require sys.monitoring") +def test_threaded_profiler_preserves_custom_worker_hook_and_releases_monitoring_slot() -> None: + def worker_hook(_frame: FrameType, _event: str, _arg: object) -> None: + return None + + def fail_with_profile(executor: ThreadPoolExecutor) -> None: + with profile_python(Path(__file__).parent, threads=True): + assert executor.submit(sys.getprofile).result(timeout=5) is worker_hook + raise RuntimeError("stop") + + tools_before: Final = tuple(sys.monitoring.get_tool(slot) for slot in range(6)) + with ThreadPoolExecutor(max_workers=1, initializer=lambda: sys.setprofile(worker_hook)) as executor: + assert executor.submit(sys.getprofile).result(timeout=5) is worker_hook + with pytest.raises(RuntimeError, match="stop"): + fail_with_profile(executor) + assert executor.submit(sys.getprofile).result(timeout=5) is worker_hook + + assert tuple(sys.monitoring.get_tool(slot) for slot in range(6)) == tools_before + + +@pytest.mark.skipif(sys.version_info < (3, 12), reason="existing worker capture requires sys.monitoring") +def test_threaded_profiler_keeps_concurrent_event_ids_and_parent_links() -> None: + def child() -> None: + return None + + def parent() -> None: + child() + + with ThreadPoolExecutor(max_workers=4) as executor: + with profile_python(Path(__file__).parent, threads=True) as profiler: + futures: Final = tuple(executor.submit(parent) for _ in range(200)) + for future in futures: + future.result(timeout=5) + + parent_ids: Final = frozenset(event.id for event in _events_named(profiler, "parent")) + children: Final = _events_named(profiler, "child") + assert len(parent_ids) == len(children) == 200 + assert frozenset(event.parent_id for event in children) == parent_ids + assert tuple(event.id for event in profiler.events) == tuple(range(len(profiler.events))) + + def test_function_usage_profiler_records_only_selected_functions() -> None: def selected() -> None: return None diff --git a/tests/rust-python-harness/shared/tracing/test_steps.py b/tests/rust-python-harness/shared/tracing/test_steps.py index 2efc6a3c579..ee5e0bafd28 100644 --- a/tests/rust-python-harness/shared/tracing/test_steps.py +++ b/tests/rust-python-harness/shared/tracing/test_steps.py @@ -40,6 +40,23 @@ def test_python_projection_collapses_unmapped_parents_and_counts_noise() -> None ] +@pytest.mark.parametrize("engine", ("python", "rust")) +def test_projection_without_mappings_keeps_every_call_and_parent(engine: Engine) -> None: + events: Final = ( + event(0, "module.py:1 entry"), + event(1, "module.py:2 internal_helper", 0), + event(2, "module.py:3 nested", 1), + event(3, "module.py:2 internal_helper", 0), + ) + + projection: Final = pipeline_projection(engine, events) + + assert projection.unmatched == 0 + assert tuple((step.id, step.parent_id, step.span, step.raw) for step in projection.steps) == tuple( + (item.id, item.parent_id, item.function, item.raw) for item in events + ) + + def test_rust_projection_keeps_unknown_spans() -> None: projection: Final = pipeline_projection("rust", (event(0, "route"), event(1, "new_span", 0)), MAPPINGS) assert [(step.span, step.parent_id) for step in projection.steps] == [("route", None), ("new_span", 0)] @@ -146,9 +163,7 @@ def test_trace_diff_allows_reordered_concurrent_children() -> None: def test_trace_diff_prunes_declared_engine_only_nodes_but_requires_them() -> None: mappings: Final = (MAPPINGS[0], mapping(rust_span="rust_prepare")) python: Final = pipeline_projection("python", (event(0, "module.py:1 entry"),), mappings).steps - rust: Final = pipeline_projection( - "rust", (event(0, "route"), event(1, "rust_prepare", 0)), mappings - ).steps + rust: Final = pipeline_projection("rust", (event(0, "route"), event(1, "rust_prepare", 0)), mappings).steps assert trace_diff(python, rust, mappings).matches assert trace_diff(python, rust[:1], mappings).missing_mappings == ("rust_prepare",) diff --git a/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/fixtures/reducto.py b/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/fixtures/reducto.py index bcca8ac6d42..1b283d75ca5 100644 --- a/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/fixtures/reducto.py +++ b/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/fixtures/reducto.py @@ -264,9 +264,7 @@ def _formatting_strategy() -> SearchStrategy[ReductoFormatting]: ), st.sampled_from((False, True)).map(lambda value: {"add_page_markers": value}), st.sampled_from((False, True)).map(lambda value: {"merge_tables": value}), - st.sampled_from(REDUCTO_FORMATTING_INCLUDE_GROUPS) - .map(list) - .map(lambda value: {"include": value}), + st.sampled_from(REDUCTO_FORMATTING_INCLUDE_GROUPS).map(list).map(lambda value: {"include": value}), ) return values.map(ReductoFormatting.model_validate) diff --git a/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/test_sdk_parity.py b/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/test_sdk_parity.py index 5c4abc78081..f14296fbf06 100644 --- a/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/test_sdk_parity.py +++ b/tests/rust-python-harness/strategies/e2e_parity/sdk/ocr/test_sdk_parity.py @@ -124,10 +124,7 @@ class RecordingCallback(CustomLogger): if isinstance(value, Mapping): if any(not isinstance(map_key, str) for map_key in value): raise TypeError("callback kwarg mappings must use string keys") - return { - map_key: self._normalized_kwargs(map_value, map_key) - for map_key, map_value in value.items() - } + return {map_key: self._normalized_kwargs(map_value, map_key) for map_key, map_value in value.items()} if isinstance(value, (list, tuple)): return [self._normalized_kwargs(item) for item in value] raise TypeError(f"unsupported callback kwarg type: {type(value)}") diff --git a/tests/rust-python-harness/strategies/trace_parity/AGENTS.md b/tests/rust-python-harness/strategies/trace_parity/AGENTS.md index bb7cb8c91d8..19861aea2b4 100644 --- a/tests/rust-python-harness/strategies/trace_parity/AGENTS.md +++ b/tests/rust-python-harness/strategies/trace_parity/AGENTS.md @@ -1 +1 @@ -Maps Python profiler frames onto feature-gated Rust span names via an explicit per-case mapping (Rust span name is the identity) and compares steps, order, and nesting of both live traces against a replayed provider response. +Prints every collected Python call under litellm/ and every feature-gated Rust span from live traces against replayed HTTP responses. The two traces are independent and are not compared. API-key and Vertex credentials scenarios exercise separate authentication paths; credentials scenarios replay the token exchange locally. diff --git a/tests/rust-python-harness/strategies/trace_parity/__init__.py b/tests/rust-python-harness/strategies/trace_parity/__init__.py index ec88b0169fa..710bdaa3d39 100644 --- a/tests/rust-python-harness/strategies/trace_parity/__init__.py +++ b/tests/rust-python-harness/strategies/trace_parity/__init__.py @@ -7,6 +7,7 @@ from ...shared.reporting.strategy import ( ModuleCaseSpec, NotImplementedCaseSpec, RunnerArgumentDefinition, + RunnerOptionDefinition, StrategyDefinition, ) from .reporting import render_trace_results @@ -26,13 +27,17 @@ CASES: Final[tuple[CaseDefinition, ...]] = ( ModuleCaseSpec( coverage=Coverage.PARTIAL, module="tests.rust-python-harness.strategies.trace_parity.sdk.messages.case", - note="Async only until anthropic_messages_handler supports sync calls.", + note="Success paths are async; sync tracing captures the currently unsupported behavior.", ), surface="sdk", ), CaseDefinition( "responses", - NotImplementedCaseSpec(reason="No Responses trace-parity case is registered."), + ModuleCaseSpec( + coverage=Coverage.PARTIAL, + module="tests.rust-python-harness.strategies.trace_parity.sdk.responses.case", + note="Core create paths: native, streaming, provider error, Azure override, and chat bridge.", + ), surface="sdk", ), CaseDefinition( @@ -70,13 +75,17 @@ CASES: Final[tuple[CaseDefinition, ...]] = ( ModuleCaseSpec( coverage=Coverage.PARTIAL, module="tests.rust-python-harness.strategies.trace_parity.gateway.messages.case", - note="Non-streaming success paths only.", + note="Anthropic/Azure provider routes plus a fully consumed downstream streaming path.", ), surface="gateway", ), CaseDefinition( "responses", - NotImplementedCaseSpec(reason="No gateway Responses trace-parity case is registered."), + ModuleCaseSpec( + coverage=Coverage.PARTIAL, + module="tests.rust-python-harness.strategies.trace_parity.gateway.responses.case", + note="Native OpenAI non-streaming and fully consumed downstream streaming paths.", + ), surface="gateway", ), CaseDefinition( @@ -86,7 +95,11 @@ CASES: Final[tuple[CaseDefinition, ...]] = ( ), CaseDefinition( "chat_completions", - NotImplementedCaseSpec(reason="No gateway chat trace-parity case is registered."), + ModuleCaseSpec( + coverage=Coverage.PARTIAL, + module="tests.rust-python-harness.strategies.trace_parity.gateway.chat_completions.case", + note="Anthropic non-streaming and fully consumed downstream streaming paths.", + ), surface="gateway", ), CaseDefinition( @@ -99,8 +112,8 @@ CASES: Final[tuple[CaseDefinition, ...]] = ( STRATEGY: Final = StrategyDefinition( id="trace_parity", order=20, - label="Trace parity", - description="Compare pipeline steps, order, and nesting between Python profiler frames and Rust spans via an explicit mapping.", + label="Traces", + description="Print Python profiler frames and Rust spans for representative pipeline scenarios.", directory=Path(__file__).parent, runnable_spec=ModuleCaseSpec, cases=CASES, @@ -112,4 +125,11 @@ STRATEGY: Final = StrategyDefinition( metavar="NAME", help="run only this named trace scenario; repeat to select more than one", ), + runner_options=( + RunnerOptionDefinition( + option="--engine", + choices=("python", "rust"), + help="show only this engine's trace; omit to print both engines", + ), + ), ) diff --git a/tests/rust-python-harness/strategies/trace_parity/fixtures.py b/tests/rust-python-harness/strategies/trace_parity/fixtures.py new file mode 100644 index 00000000000..a3d084c97de --- /dev/null +++ b/tests/rust-python-harness/strategies/trace_parity/fixtures.py @@ -0,0 +1,177 @@ +from __future__ import annotations + +import base64 +import binascii +import json +import struct +from collections.abc import Iterable, Mapping +from typing import Final + +from ...shared.parity.recorded_http import ( + HttpHeader, + RecordedHttpResponse, + RecordedHttpStreamResponse, + RecordedStreamChunk, +) + +JSON_HEADERS: Final = (HttpHeader(name="content-type", value="application/json"),) +SSE_HEADERS: Final = (HttpHeader(name="content-type", value="text/event-stream"),) +AWS_EVENT_STREAM_HEADERS: Final = (HttpHeader(name="content-type", value="application/vnd.amazon.eventstream"),) + + +def json_response(body: Mapping[str, object] | bytes, *, status: int = 200) -> RecordedHttpResponse: + encoded: Final = body if isinstance(body, bytes) else json.dumps(body).encode() + return RecordedHttpResponse.from_bytes(status, JSON_HEADERS, encoded) + + +def sse_event(event: str, payload: Mapping[str, object]) -> bytes: + return f"event: {event}\ndata: {json.dumps(payload, separators=(',', ':'))}\n\n".encode() + + +def sse_response(events: Iterable[tuple[str, Mapping[str, object]]]) -> RecordedHttpStreamResponse: + return RecordedHttpStreamResponse( + kind="http_stream", + status_code=200, + headers=SSE_HEADERS, + chunks=tuple(RecordedStreamChunk.from_bytes(sse_event(event, payload)) for event, payload in events), + ) + + +def _aws_string_header(name: str, value: str) -> bytes: + name_bytes: Final = name.encode() + value_bytes: Final = value.encode() + return ( + struct.pack("!B", len(name_bytes)) + + name_bytes + + struct.pack("!B", 7) + + struct.pack("!H", len(value_bytes)) + + value_bytes + ) + + +def aws_event_stream_frame(payload: Mapping[str, object]) -> bytes: + event_payload: Final = json.dumps( + {"bytes": base64.b64encode(json.dumps(payload, separators=(",", ":")).encode()).decode()}, + separators=(",", ":"), + ).encode() + headers: Final = ( + _aws_string_header(":event-type", "chunk") + + _aws_string_header(":content-type", "application/json") + + _aws_string_header(":message-type", "event") + ) + total_length: Final = 12 + len(headers) + len(event_payload) + 4 + prelude: Final = struct.pack("!II", total_length, len(headers)) + prelude_crc: Final = binascii.crc32(prelude) & 0xFFFFFFFF + prelude_crc_bytes: Final = struct.pack("!I", prelude_crc) + message_crc: Final = binascii.crc32(prelude_crc_bytes + headers + event_payload, prelude_crc) & 0xFFFFFFFF + return prelude + prelude_crc_bytes + headers + event_payload + struct.pack("!I", message_crc) + + +def aws_event_stream_response( + events: Iterable[Mapping[str, object]], *, corrupt_last_frame: bool = False +) -> RecordedHttpStreamResponse: + frames: Final = tuple(aws_event_stream_frame(event) for event in events) + body: Final = ( + b"".join((*frames[:-1], frames[-1][:-1] + bytes((frames[-1][-1] ^ 0xFF,)))) + if corrupt_last_frame + else b"".join(frames) + ) + return RecordedHttpStreamResponse( + kind="http_stream", + status_code=200, + headers=AWS_EVENT_STREAM_HEADERS, + chunks=(RecordedStreamChunk.from_bytes(body),), + ) + + +def anthropic_response_body(*, model: str = "claude-sonnet-5") -> dict[str, object]: + return { + "id": "msg_trace", + "type": "message", + "role": "assistant", + "model": model, + "content": [{"type": "text", "text": "hello"}], + "stop_reason": "end_turn", + "stop_sequence": None, + "usage": {"input_tokens": 2, "output_tokens": 3}, + } + + +def anthropic_stream_events(*, model: str = "claude-sonnet-5") -> tuple[tuple[str, Mapping[str, object]], ...]: + return ( + ( + "message_start", + { + "type": "message_start", + "message": { + "id": "msg_trace", + "type": "message", + "role": "assistant", + "model": model, + "content": [], + "stop_reason": None, + "stop_sequence": None, + "usage": {"input_tokens": 2, "output_tokens": 0}, + }, + }, + ), + ( + "content_block_start", + {"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}}, + ), + ( + "content_block_delta", + {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "hello"}}, + ), + ("content_block_stop", {"type": "content_block_stop", "index": 0}), + ( + "message_delta", + { + "type": "message_delta", + "delta": {"stop_reason": "end_turn", "stop_sequence": None}, + "usage": {"output_tokens": 1}, + }, + ), + ("message_stop", {"type": "message_stop"}), + ) + + +def responses_body(*, model: str = "gpt-5", status: str = "completed") -> dict[str, object]: + return { + "id": "resp_trace", + "object": "response", + "created_at": 1_750_000_000, + "status": status, + "model": model, + "output": [ + { + "type": "message", + "id": "msg_trace", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "hello", "annotations": []}], + } + ], + "usage": {"input_tokens": 2, "output_tokens": 3, "total_tokens": 5}, + } + + +def responses_stream_events(*, model: str = "gpt-5") -> tuple[tuple[str, Mapping[str, object]], ...]: + response: Final = responses_body(model=model) + return ( + ( + "response.created", + {"type": "response.created", "response": {**response, "status": "in_progress", "output": []}}, + ), + ( + "response.output_text.delta", + { + "type": "response.output_text.delta", + "item_id": "msg_trace", + "output_index": 0, + "content_index": 0, + "delta": "hello", + }, + ), + ("response.completed", {"type": "response.completed", "response": response}), + ) diff --git a/tests/rust-python-harness/strategies/trace_parity/gateway/chat_completions/case.py b/tests/rust-python-harness/strategies/trace_parity/gateway/chat_completions/case.py new file mode 100644 index 00000000000..3dc6d731b4b --- /dev/null +++ b/tests/rust-python-harness/strategies/trace_parity/gateway/chat_completions/case.py @@ -0,0 +1,63 @@ +from __future__ import annotations + +from typing import Final + +from .....shared.tracing.steps import Engine, mapping +from ...fixtures import anthropic_response_body, anthropic_stream_events, json_response, sse_response +from ...models import GatewayRouteSpec, RouteFixture, TraceScenario, TraceSuite + +MAPPINGS: Final = ( + mapping(span="python_chat_gateway_route", python_frame=r"proxy_server\.py:\d+ chat_completion$"), + mapping(span="python_gateway_service", python_frame=r"ProxyBaseLLMRequestProcessing\.base_process_llm_request$"), + mapping(span="python_chat_entrypoint", python_frame=r"main\.py:\d+ a?completion$"), + mapping(span="python_provider_config", python_frame=r"ProviderConfigManager\.get_provider_chat_config$"), + mapping(rust_span="validate_environment", python_frame=r"(? RouteFixture: + return RouteFixture( + kwargs={ + "model_alias": "trace-model", + "provider_model": "anthropic/claude-sonnet-5", + "body": { + "model": "trace-model", + "messages": [{"role": "user", "content": "hello"}], + "max_tokens": 16, + }, + }, + provider_responses=(json_response(anthropic_response_body()),), + ) + + +def _stream_fixture(engine: Engine, base_url: str) -> RouteFixture: + fixture: Final = _fixture(engine, base_url) + return fixture.with_body(stream=True).derive( + provider_responses=(sse_response(anthropic_stream_events()),), + ) + + +TRACE_SUITE: Final = TraceSuite( + route=GatewayRouteSpec("chat_completions", rust_supported=False), + scenarios=( + TraceScenario(name="async-anthropic", fixture=_fixture, mappings=MAPPINGS, asynchronous=True), + TraceScenario( + name="async-anthropic-downstream-stream", + fixture=_stream_fixture, + mappings=(*MAPPINGS, *STREAM_MAPPINGS), + asynchronous=True, + ), + ), +) diff --git a/tests/rust-python-harness/strategies/trace_parity/gateway/execution.py b/tests/rust-python-harness/strategies/trace_parity/gateway/execution.py index 860e872dd44..94d6be7cebf 100644 --- a/tests/rust-python-harness/strategies/trace_parity/gateway/execution.py +++ b/tests/rust-python-harness/strategies/trace_parity/gateway/execution.py @@ -13,8 +13,8 @@ from ....shared.parity.replay import replay_server from ....shared.tracing.native import TraceResponsePayload, native_trace_events from ....shared.tracing.profiler import FunctionTraceEvent, profile_python from ....shared.tracing.steps import Engine, PipelineProjection, pipeline_projection -from ..models import GatewayRouteSpec, RouteFixture, TraceExecutionFailure, TraceMode, TraceScenario -from ..reporting import TraceComparisonArtifact +from ..models import GatewayRouteSpec, RouteFixture, TraceEngine, TraceExecutionFailure, TraceScenario +from ..reporting import TraceArtifact class _GatewayResponsePayload(BaseModel): @@ -28,7 +28,14 @@ class _GatewayClient(Protocol): def post(self, url: str, *, json: object, headers: dict[str, str]) -> httpx.Response: ... -def _collect_python(fixture: RouteFixture) -> tuple[FunctionTraceEvent, ...]: +_ROUTE_PATHS: Final = { + "messages": "/v1/messages", + "chat_completions": "/v1/chat/completions", + "responses": "/v1/responses", +} + + +def _collect_python(fixture: RouteFixture, route: GatewayRouteSpec) -> tuple[FunctionTraceEvent, ...]: from fastapi.testclient import TestClient import litellm @@ -61,7 +68,7 @@ def _collect_python(fixture: RouteFixture) -> tuple[FunctionTraceEvent, ...]: with profile_python(Path(litellm.__file__).parent, threads=True) as profiler: client: Final = cast(_GatewayClient, TestClient(proxy_server.app)) response: Final = client.post( - "/v1/messages", + _ROUTE_PATHS[route.route], json=fixture.kwargs["body"], headers={"authorization": "Bearer trace-key"}, ) @@ -76,9 +83,10 @@ def _collect_python(fixture: RouteFixture) -> tuple[FunctionTraceEvent, ...]: proxy_server.app.dependency_overrides[user_api_key_auth] = old_override -def _collect_rust(fixture: RouteFixture) -> tuple[FunctionTraceEvent, ...]: +def _collect_rust(fixture: RouteFixture, route: GatewayRouteSpec) -> tuple[FunctionTraceEvent, ...]: payload: Final = json.dumps( { + "path": _ROUTE_PATHS[route.route], "model_alias": fixture.kwargs["model_alias"], "provider_model": fixture.kwargs["provider_model"], "api_base": fixture.kwargs["api_base"], @@ -130,7 +138,9 @@ def _gateway_trace_binary() -> Path: return rust_root / "target" / "debug" / "trace-parity-gateway" -def _collect(scenario: TraceScenario, engine: Engine) -> tuple[FunctionTraceEvent, ...] | TraceExecutionFailure: +def _collect( + route: GatewayRouteSpec, scenario: TraceScenario, engine: Engine +) -> tuple[FunctionTraceEvent, ...] | TraceExecutionFailure: try: with replay_server() as provider: base_fixture: Final = scenario.fixture(engine, provider.url) @@ -140,7 +150,7 @@ def _collect(scenario: TraceScenario, engine: Engine) -> tuple[FunctionTraceEven ) for response in fixture.provider_responses: provider.enqueue_response(response) - events: Final = _collect_python(fixture) if engine == "python" else _collect_rust(fixture) + events: Final = _collect_python(fixture, route) if engine == "python" else _collect_rust(fixture, route) provider.take_requests(len(fixture.provider_responses)) return events except Exception as error: @@ -150,40 +160,38 @@ def _collect(scenario: TraceScenario, engine: Engine) -> tuple[FunctionTraceEven def _projections( python_events: tuple[FunctionTraceEvent, ...], rust_events: tuple[FunctionTraceEvent, ...], - scenario: TraceScenario, - mode: TraceMode, ) -> tuple[PipelineProjection, PipelineProjection, str | None]: - mappings: Final = scenario.mappings_for(mode) try: return ( - pipeline_projection("python", python_events, mappings), - pipeline_projection("rust", rust_events, mappings), + pipeline_projection("python", python_events), + pipeline_projection("rust", rust_events), None, ) except ValueError as error: return PipelineProjection(), PipelineProjection(), f"harness: {error}" -def execute_gateway_trace(route: GatewayRouteSpec, scenario: TraceScenario, mode: TraceMode) -> TraceComparisonArtifact: - mappings: Final = scenario.mappings_for(mode) - python_trace: Final = _collect(scenario, "python") - rust_trace: Final = _collect(scenario, "rust") +def execute_gateway_trace( + route: GatewayRouteSpec, + scenario: TraceScenario, + engine: TraceEngine = "both", +) -> TraceArtifact: + effective_engine: Final[TraceEngine] = "python" if engine == "both" and not route.rust_supported else engine + python_trace: Final = _collect(route, scenario, "python") if effective_engine != "rust" else () + rust_trace: Final = _collect(route, scenario, "rust") if effective_engine != "python" else () collection_python_error: Final = None if isinstance(python_trace, tuple) else f"python: {python_trace.message}" rust_error: Final = None if isinstance(rust_trace, tuple) else f"rust: {rust_trace.message}" python_events: Final = python_trace if isinstance(python_trace, tuple) else () rust_events: Final = rust_trace if isinstance(rust_trace, tuple) else () - python, rust, projection_error = _projections(python_events, rust_events, scenario, mode) + python, rust, projection_error = _projections(python_events, rust_events) python_error: Final = projection_error or collection_python_error - return TraceComparisonArtifact.from_traces( + return TraceArtifact.from_traces( + engine=effective_engine, surface="gateway", sdk_function=route.route, scenario=scenario.name, - mode=mode, - mappings=mappings, - contract=scenario.contract, python=python.steps, rust=rust.steps, - python_unmatched=python.unmatched, python_error=python_error, rust_error=rust_error, ) diff --git a/tests/rust-python-harness/strategies/trace_parity/gateway/messages/case.py b/tests/rust-python-harness/strategies/trace_parity/gateway/messages/case.py index 30f51cee353..ca9c858f6b7 100644 --- a/tests/rust-python-harness/strategies/trace_parity/gateway/messages/case.py +++ b/tests/rust-python-harness/strategies/trace_parity/gateway/messages/case.py @@ -1,10 +1,9 @@ from __future__ import annotations -import json from typing import Final -from .....shared.parity.recorded_http import HttpHeader, RecordedHttpResponse from .....shared.tracing.steps import Engine, mapping +from ...fixtures import anthropic_response_body, anthropic_stream_events, json_response, sse_response from ...models import GatewayRouteSpec, RouteFixture, TraceScenario, TraceSuite @@ -49,24 +48,7 @@ def _fixture(_engine: Engine, provider: str) -> RouteFixture: "max_tokens": 16, }, }, - provider_responses=( - RecordedHttpResponse.from_bytes( - 200, - (HttpHeader(name="content-type", value="application/json"),), - json.dumps( - { - "id": "msg_trace", - "type": "message", - "role": "assistant", - "model": "claude-sonnet-5", - "content": [{"type": "text", "text": "hello"}], - "stop_reason": "end_turn", - "stop_sequence": None, - "usage": {"input_tokens": 2, "output_tokens": 3}, - } - ).encode(), - ), - ), + provider_responses=(json_response(anthropic_response_body()),), ) @@ -78,6 +60,13 @@ def _azure_fixture(engine: Engine, _base_url: str) -> RouteFixture: return _fixture(engine, "azure_ai") +def _stream_fixture(engine: Engine, _base_url: str) -> RouteFixture: + fixture: Final = _anthropic_fixture(engine, _base_url) + return fixture.with_body(stream=True).derive( + provider_responses=(sse_response(anthropic_stream_events()),), + ) + + ANTHROPIC_MAPPINGS: Final = ( *GATEWAY_MAPPINGS, mapping( @@ -100,7 +89,22 @@ AZURE_MAPPINGS: Final = ( TRACE_SUITE: Final = TraceSuite( route=GatewayRouteSpec("messages"), scenarios=( - TraceScenario(name="anthropic", fixture=_anthropic_fixture, mappings=ANTHROPIC_MAPPINGS, modes=("async",)), - TraceScenario(name="azure-ai", fixture=_azure_fixture, mappings=AZURE_MAPPINGS, modes=("async",)), + TraceScenario( + name="async-anthropic", fixture=_anthropic_fixture, mappings=ANTHROPIC_MAPPINGS, asynchronous=True + ), + TraceScenario(name="async-azure-ai", fixture=_azure_fixture, mappings=AZURE_MAPPINGS, asynchronous=True), + TraceScenario( + name="async-anthropic-downstream-stream", + fixture=_stream_fixture, + mappings=( + *ANTHROPIC_MAPPINGS, + mapping(span="python_upstream_stream", python_frame=r"AnthropicMessagesStreamingResponse\.__anext__$"), + mapping( + span="python_downstream_stream", python_frame=r"DataGenerator\.__anext__$|async_data_generator$" + ), + mapping(span="python_stream_callback", python_frame=r"Logging\.async_success_handler$"), + ), + asynchronous=True, + ), ), ) diff --git a/tests/rust-python-harness/strategies/trace_parity/gateway/responses/case.py b/tests/rust-python-harness/strategies/trace_parity/gateway/responses/case.py new file mode 100644 index 00000000000..7d805a0603c --- /dev/null +++ b/tests/rust-python-harness/strategies/trace_parity/gateway/responses/case.py @@ -0,0 +1,62 @@ +from __future__ import annotations + +from typing import Final + +from .....shared.tracing.steps import Engine, mapping +from ...fixtures import json_response, responses_body, responses_stream_events, sse_response +from ...models import GatewayRouteSpec, RouteFixture, TraceScenario, TraceSuite + +MAPPINGS: Final = ( + mapping( + span="python_responses_gateway_route", python_frame=r"response_api_endpoints/endpoints\.py:\d+ responses_api$" + ), + mapping(span="python_gateway_service", python_frame=r"ProxyBaseLLMRequestProcessing\.base_process_llm_request$"), + mapping(span="python_responses", python_frame=r"responses/main\.py:\d+ a?responses$"), + mapping(span="python_provider_config", python_frame=r"ProviderConfigManager\.get_provider_responses_api_config$"), + mapping(rust_span="validate_environment", python_frame=r"OpenAIResponsesAPIConfig\.validate_environment$"), + mapping(rust_span="complete_url", python_frame=r"OpenAIResponsesAPIConfig\.get_complete_url$"), + mapping(rust_span="transform_request", python_frame=r"OpenAIResponsesAPIConfig\.transform_responses_api_request$"), + mapping(span="python_logging_pre_call", python_frame=r"Logging\.pre_call$"), + mapping(rust_span="http_request", python_frame=r"AsyncHTTPHandler\.post$|HTTPHandler\.post$"), + mapping(rust_span="transform_response", python_frame=r"OpenAIResponsesAPIConfig\.transform_response_api_response$"), + mapping(span="python_success_callback", python_frame=r"Logging\.async_success_handler$|Logging\.success_handler$"), +) + +STREAM_MAPPINGS: Final = ( + mapping(span="python_stream_iterator", python_frame=r"ResponsesAPIStreamingIterator\.__init__$"), + mapping(span="python_stream_next", python_frame=r"ResponsesAPIStreamingIterator\.__anext__$"), + mapping(span="python_stream_transform", python_frame=r"OpenAIResponsesAPIConfig\.transform_streaming_response$"), + mapping(span="python_downstream_stream", python_frame=r"DataGenerator\.__anext__$|async_data_generator$"), +) + + +def _fixture(_engine: Engine, _base_url: str) -> RouteFixture: + return RouteFixture( + kwargs={ + "model_alias": "trace-model", + "provider_model": "openai/gpt-5", + "body": {"model": "trace-model", "input": "hello"}, + }, + provider_responses=(json_response(responses_body()),), + ) + + +def _stream_fixture(engine: Engine, base_url: str) -> RouteFixture: + fixture: Final = _fixture(engine, base_url) + return fixture.with_body(stream=True).derive( + provider_responses=(sse_response(responses_stream_events()),), + ) + + +TRACE_SUITE: Final = TraceSuite( + route=GatewayRouteSpec("responses", rust_supported=False), + scenarios=( + TraceScenario(name="async-openai", fixture=_fixture, mappings=MAPPINGS, asynchronous=True), + TraceScenario( + name="async-openai-downstream-stream", + fixture=_stream_fixture, + mappings=(*MAPPINGS, *STREAM_MAPPINGS), + asynchronous=True, + ), + ), +) diff --git a/tests/rust-python-harness/strategies/trace_parity/models.py b/tests/rust-python-harness/strategies/trace_parity/models.py index 04659b25382..d6ed42250c4 100644 --- a/tests/rust-python-harness/strategies/trace_parity/models.py +++ b/tests/rust-python-harness/strategies/trace_parity/models.py @@ -1,35 +1,61 @@ from __future__ import annotations -from collections.abc import Callable +from collections.abc import Callable, Mapping from dataclasses import dataclass -from typing import Final, Literal, TypeAlias +from typing import Final, Literal, TypeAlias, cast -from ...shared.parity.recorded_http import RecordedHttpResponse +from ...shared.parity.recorded_http import RecordedResponse from ...shared.reporting.models import SdkFunction -from ...shared.tracing.steps import Engine, TraceContract, TraceMapping +from ...shared.tracing.steps import Engine, TraceMapping -TraceMode = Literal["sync", "async"] +TraceEngine = Literal["python", "rust", "both"] TraceFailureSource = Literal["python", "rust", "harness"] @dataclass(frozen=True, slots=True) class RouteFixture: kwargs: dict[str, object] - provider_responses: tuple[RecordedHttpResponse, ...] + provider_responses: tuple[RecordedResponse, ...] expected_failure: bool = False + consume_stream: bool = False + environment: tuple[tuple[str, str], ...] = () + + def derive( + self, + *, + kwargs: Mapping[str, object] | None = None, + provider_responses: tuple[RecordedResponse, ...] | None = None, + expected_failure: bool | None = None, + consume_stream: bool | None = None, + ) -> RouteFixture: + return RouteFixture( + kwargs={**self.kwargs, **(kwargs or {})}, + provider_responses=self.provider_responses if provider_responses is None else provider_responses, + expected_failure=self.expected_failure if expected_failure is None else expected_failure, + consume_stream=self.consume_stream if consume_stream is None else consume_stream, + environment=self.environment, + ) + + def with_body(self, **updates: object) -> RouteFixture: + raw_body: Final = self.kwargs.get("body") + if not isinstance(raw_body, dict): + raise ValueError("route fixture does not contain an object body") + body: Final = cast(dict[str, object], raw_body) + return self.derive(kwargs={"body": {**body, **updates}}) @dataclass(frozen=True, slots=True) class RouteSpec: route: SdkFunction python_entrypoints: tuple[str, str] - rust_entrypoints: tuple[str, str] + rust_entrypoints: tuple[str, str] | None fixture: Callable[[Engine, str], RouteFixture] @dataclass(frozen=True, slots=True) class GatewayRouteSpec: route: SdkFunction + rust_supported: bool = True TraceRouteSpec: TypeAlias = RouteSpec | GatewayRouteSpec @@ -40,14 +66,7 @@ class TraceScenario: name: str fixture: Callable[[Engine, str], RouteFixture] mappings: tuple[TraceMapping, ...] - modes: tuple[TraceMode, ...] = ("sync", "async") - contract: TraceContract = TraceContract() - sync_mappings: tuple[TraceMapping, ...] | None = None - async_mappings: tuple[TraceMapping, ...] | None = None - - def mappings_for(self, mode: TraceMode) -> tuple[TraceMapping, ...]: - selected: Final = self.async_mappings if mode == "async" else self.sync_mappings - return self.mappings if selected is None else selected + asynchronous: bool @dataclass(frozen=True, slots=True) diff --git a/tests/rust-python-harness/strategies/trace_parity/reporting.py b/tests/rust-python-harness/strategies/trace_parity/reporting.py index 9c5bf9e88cd..e7c07ef9c0f 100644 --- a/tests/rust-python-harness/strategies/trace_parity/reporting.py +++ b/tests/rust-python-harness/strategies/trace_parity/reporting.py @@ -1,31 +1,24 @@ from __future__ import annotations import os -import re import sys from collections.abc import Sequence -from typing import Final, Literal +from typing import Final from pydantic import BaseModel, ConfigDict, ValidationError from ...shared.reporting.models import SURFACES, CaseResult, RunStatus, SdkFunction, Surface from ...shared.reporting.rendering import ReportSection from ...shared.reporting.strategy import NotImplementedCaseSpec, SkippedCaseSpec -from ...shared.tracing.steps import ( - PipelineStep, - TraceContract, - TraceDiff, - TraceMapping, - trace_depths, - trace_diff, -) +from ...shared.tracing.steps import PipelineStep, trace_depths +from .models import TraceEngine -TRACE_COMPARISON_ARTIFACT: Final = "trace_comparison" +TRACE_ARTIFACT: Final = "trace" TRACE_PARITY_HINT: Final = ( "rebuild the native bridge with the trace-parity feature, e.g. `uvx maturin develop --features trace-parity`" ) -_COLORS: Final[dict[str, str]] = {"green": "32", "yellow": "33", "red": "31", "cyan": "36"} +_COLORS: Final[dict[str, str]] = {"yellow": "33", "red": "31", "cyan": "36"} _RESET: Final = "\033[0m" @@ -47,26 +40,15 @@ class TraceEventArtifact(BaseModel): return PipelineStep(self.id, self.parent_id, self.span, self.raw) -class TraceMappingArtifact(BaseModel): - model_config = ConfigDict(frozen=True, extra="forbid") - - span: str - python: str | None - rust: str | None - - -class TraceComparisonArtifact(BaseModel): +class TraceArtifact(BaseModel): model_config = ConfigDict(frozen=True, extra="forbid") + engine: TraceEngine = "both" surface: Surface sdk_function: SdkFunction scenario: str - mode: Literal["sync", "async"] - mappings: tuple[TraceMappingArtifact, ...] python: tuple[TraceEventArtifact, ...] rust: tuple[TraceEventArtifact, ...] - python_unmatched: int - unordered_children_of: frozenset[str] python_error: str | None = None rust_error: str | None = None @@ -74,41 +56,27 @@ class TraceComparisonArtifact(BaseModel): def from_traces( cls, *, + engine: TraceEngine = "both", surface: Surface, sdk_function: SdkFunction, scenario: str, - mode: Literal["sync", "async"], - mappings: Sequence[TraceMapping], - contract: TraceContract, python: Sequence[PipelineStep], rust: Sequence[PipelineStep], - python_unmatched: int, python_error: str | None = None, rust_error: str | None = None, - ) -> TraceComparisonArtifact: + ) -> TraceArtifact: return cls( + engine=engine, surface=surface, sdk_function=sdk_function, scenario=scenario, - mode=mode, - mappings=tuple( - TraceMappingArtifact( - span=item.span, - python=item.python.pattern if item.python else None, - rust=item.rust, - ) - for item in mappings - ), python=tuple( TraceEventArtifact(id=step.id, parent_id=step.parent_id, span=step.span, raw=step.raw) for step in python ), rust=tuple( - TraceEventArtifact(id=step.id, parent_id=step.parent_id, span=step.span, raw=step.raw) - for step in rust + TraceEventArtifact(id=step.id, parent_id=step.parent_id, span=step.span, raw=step.raw) for step in rust ), - python_unmatched=python_unmatched, - unordered_children_of=contract.unordered_children_of, python_error=python_error, rust_error=rust_error, ) @@ -119,32 +87,9 @@ class TraceComparisonArtifact(BaseModel): def rust_steps(self) -> tuple[PipelineStep, ...]: return tuple(event.step() for event in self.rust) - def diff(self) -> TraceDiff: - return trace_diff( - self.python_steps(), - self.rust_steps(), - tuple( - TraceMapping( - item.span, - re.compile(item.python) if item.python is not None else None, - item.rust, - ) - for item in self.mappings - ), - TraceContract(self.unordered_children_of), - ) - - def exact_match(self) -> bool: - return self.diff().matches - def has_errors(self) -> bool: return self.python_error is not None or self.rust_error is not None - def contract_matches(self) -> bool: - if self.has_errors(): - return False - return self.diff().matches - def _split_raw(raw: str) -> tuple[str, str]: location, separator, name = raw.partition(" ") @@ -153,72 +98,28 @@ def _split_raw(raw: str) -> tuple[str, str]: return raw, "" -def _python_line(index: int, step: PipelineStep, depth: int, exclusive: frozenset[str]) -> str: +def _python_line(index: int, step: PipelineStep, depth: int) -> str: name: Final = _split_raw(step.raw)[0] location: Final = _split_raw(step.raw)[1] suffix: Final = f" ({location})" if location else "" - marker: Final = " [python only]" if step.span in exclusive else "" - return _paint(f"{index} {' ' * depth}{name}{suffix}{marker}", "cyan") + return _paint(f"{index} {' ' * depth}{name}{suffix}", "cyan") -def _python_lines(steps: tuple[PipelineStep, ...], exclusive: frozenset[str]) -> str: +def _python_lines(steps: tuple[PipelineStep, ...]) -> str: depths: Final = trace_depths(steps) - lines: Final = tuple( - _python_line(index, step, depths[step.id], exclusive) for index, step in enumerate(steps, start=1) - ) + lines: Final = tuple(_python_line(index, step, depths[step.id]) for index, step in enumerate(steps, start=1)) return f"{_paint('PYTHON', 'cyan')} ({len(steps)} steps)\n" + ("\n".join(lines) if lines else "(empty)") -def _python_references(steps: tuple[PipelineStep, ...]) -> dict[tuple[str, int], str]: - references: dict[tuple[str, int], str] = {} - occurrences: dict[str, int] = {} - for index, step in enumerate(steps, start=1): - name = _split_raw(step.raw)[0] - occurrence = occurrences.get(step.span, 0) + 1 - occurrences[step.span] = occurrence - references[(step.span, occurrence)] = f"{index} {name}" - return references - - -def _rust_line( - step: PipelineStep, - depth: int, - occurrence: int, - references: dict[tuple[str, int], str], -) -> str: - span: Final = _paint(step.span, "yellow") - key: Final = (step.span, occurrence) - reference: Final = ( - _paint(references[key], "cyan") if key in references else _paint("[rust only]", "yellow") - ) - suffix: Final = f"#{occurrence}" if occurrence > 1 else "" - return f"{' ' * depth}{span}{suffix} -> {reference}" - - -def _rust_lines(steps: tuple[PipelineStep, ...], references: dict[tuple[str, int], str]) -> str: +def _rust_lines(steps: tuple[PipelineStep, ...]) -> str: depths: Final = trace_depths(steps) - occurrences: dict[str, int] = {} - lines: list[str] = [] - for step in steps: - occurrence = occurrences.get(step.span, 0) + 1 - occurrences[step.span] = occurrence - lines.append(_rust_line(step, depths[step.id], occurrence, references)) + lines: Final = tuple( + _paint(f"{index} {' ' * depths[step.id]}{step.span}", "yellow") for index, step in enumerate(steps, 1) + ) return f"{_paint('RUST', 'yellow')} ({len(steps)} steps)\n" + ("\n".join(lines) if lines else "(empty)") -def _state_text(state: str, *, good: bool) -> str: - return _paint(state, "green" if good else "red") - - -def _contract_line(artifact: TraceComparisonArtifact) -> str: - matches: Final = artifact.contract_matches() - status: Final = _state_text("PASS" if matches else "FAIL", good=matches) - if artifact.python_error or artifact.rust_error: - return f"Contract: {status}" - return f"Contract: {status}" - - -def _error_lines(artifact: TraceComparisonArtifact) -> tuple[str, ...]: +def _error_lines(artifact: TraceArtifact) -> tuple[str, ...]: lines: list[str] = [] for engine, error in (("Python", artifact.python_error), ("Rust", artifact.rust_error)): if error is None: @@ -229,68 +130,20 @@ def _error_lines(artifact: TraceComparisonArtifact) -> tuple[str, ...]: return tuple(lines) -def _unseen_mappings( - artifact: TraceComparisonArtifact, - python: tuple[PipelineStep, ...], - rust: tuple[PipelineStep, ...], -) -> tuple[str, ...]: - return artifact.diff().missing_mappings - - -def _comparison_status_lines( - artifact: TraceComparisonArtifact, - python: tuple[PipelineStep, ...], - rust: tuple[PipelineStep, ...], -) -> tuple[str, ...]: - diff: Final = artifact.diff() - exact_match: Final = artifact.exact_match() - if artifact.has_errors(): - return (*_error_lines(artifact), _contract_line(artifact)) - unseen: Final = _unseen_mappings(artifact, python, rust) - unseen_line: Final[tuple[str, ...]] = (f"Unseen mappings: {', '.join(unseen)}",) if unseen else () - drift_lines: Final[tuple[str, ...]] = ( - (_state_text("Same steps, order, and nesting", good=True),) - if exact_match - else ( - _paint(f"Python only: {', '.join(diff.python_only) or 'none'}", "cyan"), - _paint(f"Rust only: {', '.join(diff.rust_only) or 'none'}", "yellow"), - f"First difference: {diff.first_difference or 'none'}", - f"Python frames outside mapping: {artifact.python_unmatched}", - ) - ) - return ( - f"Trace: {_state_text('MATCH' if exact_match else 'DRIFT', good=exact_match)}", - *drift_lines, - *unseen_line, - _contract_line(artifact), - ) - - -def _render_comparison(artifact: TraceComparisonArtifact) -> str: - python: Final = artifact.python_steps() - rust: Final = artifact.rust_steps() - diff: Final = artifact.diff() - python_exclusive: Final = frozenset(item.span for item in artifact.mappings if item.rust is None) - status_lines: Final = _comparison_status_lines(artifact, python, rust) - return "\n\n".join( - ( - _python_lines(python, python_exclusive | frozenset(diff.python_only)), - _rust_lines(rust, _python_references(python)), - "\n".join(status_lines), - ) - ) - - -def _mode(nodeid: str) -> str: - if "[" in nodeid: - return nodeid.rsplit("[", 1)[-1].removesuffix("]") - head, _, tail = nodeid.rpartition(":") - return tail if head else "unknown mode" +def _render_trace(artifact: TraceArtifact) -> str: + traces: tuple[str, ...] + if artifact.engine == "python": + traces = (_python_lines(artifact.python_steps()),) + elif artifact.engine == "rust": + traces = (_rust_lines(artifact.rust_steps()),) + else: + traces = (_python_lines(artifact.python_steps()), _rust_lines(artifact.rust_steps())) + return "\n\n".join((*traces, *_error_lines(artifact))) def _scenario(nodeid: str) -> str: parts: Final = nodeid.split(":") - return parts[-2] if len(parts) >= 5 else "default" + return parts[-1] if len(parts) >= 4 else "default" def _unavailable(status: RunStatus) -> str: @@ -299,20 +152,20 @@ def _unavailable(status: RunStatus) -> str: def _render_artifact(body: str) -> str: try: - artifact: Final = TraceComparisonArtifact.model_validate_json(body) + artifact: Final = TraceArtifact.model_validate_json(body) except ValidationError as error: - return f"Trace comparison artifact is invalid: {error}" - return _render_comparison(artifact) + return f"Trace artifact is invalid: {error}" + return _render_trace(artifact) -def _mode_section(result: CaseResult, nodeid: str, status: RunStatus) -> str: +def _scenario_section(result: CaseResult, nodeid: str, status: RunStatus) -> str: artifacts: Final = tuple( - artifact for artifact in result.artifacts.get(nodeid, ()) if artifact.kind == TRACE_COMPARISON_ARTIFACT + artifact for artifact in result.artifacts.get(nodeid, ()) if artifact.kind == TRACE_ARTIFACT ) body: Final = ( "\n\n".join(_render_artifact(artifact.body) for artifact in artifacts) if artifacts else _unavailable(status) ) - label: Final = f"Scenario: {_scenario(nodeid)} / Mode: {_mode(nodeid)}" + label: Final = f"Scenario: {_scenario(nodeid)}" return f"{label}\n{'-' * len(label)}\n\n{body}" @@ -321,7 +174,7 @@ def _case_block(result: CaseResult) -> str: outcomes: Final = tuple(result.outcomes.items()) or ( (nodeid, RunStatus.NOT_RUN) for nodeid in sorted(result.collected) ) - sections: Final = tuple(_mode_section(result, nodeid, status) for nodeid, status in outcomes) + sections: Final = tuple(_scenario_section(result, nodeid, status) for nodeid, status in outcomes) return "\n\n".join((f"{header}\n{'=' * len(header)}", *sections)) @@ -357,11 +210,11 @@ def _surface_section(surface: Surface, results: Sequence[CaseResult]) -> ReportS *((not_implemented,) if not_implemented else ()), *((skipped,) if skipped else ()), ) - return ReportSection(f"{surface.upper()} trace comparisons", blocks or ("No runnable trace comparisons",)) + return ReportSection(f"{surface.upper()} traces", blocks or ("No runnable traces",)) def render_trace_results(results: Sequence[CaseResult]) -> tuple[ReportSection, ...]: sections: Final = tuple( section for surface in SURFACES if (section := _surface_section(surface, results)) is not None ) - return sections or (ReportSection("Trace comparisons", ("No trace comparisons selected",)),) + return sections or (ReportSection("Traces", ("No traces selected",)),) diff --git a/tests/rust-python-harness/strategies/trace_parity/runner.py b/tests/rust-python-harness/strategies/trace_parity/runner.py index b78a3c7da3f..706e054bf52 100644 --- a/tests/rust-python-harness/strategies/trace_parity/runner.py +++ b/tests/rust-python-harness/strategies/trace_parity/runner.py @@ -4,13 +4,20 @@ import importlib from collections.abc import Sequence from pathlib import Path from time import monotonic -from typing import Final +from typing import Final, cast +from ...shared.native_build import ensure_trace_bridge from ...shared.reporting.models import CaseResult, HarnessCase, HarnessRun, ResultArtifact, RunStatus, Surface from ...shared.reporting.strategy import ModuleCaseSpec, UpdateCallback -from ...shared.native_build import ensure_trace_bridge -from .models import GatewayRouteSpec, RouteSpec, TraceExecutionFailure, TraceMode, TraceScenario, TraceSuite -from .reporting import TRACE_COMPARISON_ARTIFACT, TraceComparisonArtifact +from .models import ( + GatewayRouteSpec, + RouteSpec, + TraceEngine, + TraceExecutionFailure, + TraceScenario, + TraceSuite, +) +from .reporting import TRACE_ARTIFACT, TraceArtifact from .sdk.execution import execute_trace @@ -32,15 +39,13 @@ def validate_trace_suite(suite: TraceSuite, harness_case: HarnessCase) -> str | names: Final = tuple(scenario.name for scenario in suite.scenarios) if not names or len(names) != len(set(names)) or any(not name or ":" in name for name in names): return "scenario names must be non-empty, unique, and colon-free" - invalid_modes: Final = tuple( + invalid_names: Final = tuple( scenario.name for scenario in suite.scenarios - if not scenario.modes - or len(scenario.modes) != len(set(scenario.modes)) - or any(mode not in {"sync", "async"} for mode in scenario.modes) + if not scenario.name.startswith("async-" if scenario.asynchronous else "sync-") ) - if invalid_modes: - return f"scenarios must use non-empty, unique sync/async modes: {', '.join(invalid_modes)}" + if invalid_names: + return f"scenario names must start with sync- or async-: {', '.join(invalid_names)}" surface: Final = harness_case.surface if surface == "sdk" and not isinstance(suite.route, RouteSpec): return "must use RouteSpec for the sdk surface" @@ -57,15 +62,14 @@ def scenario_nodeids( trace_suite: TraceSuite, harness_case: HarnessCase, selected_scenarios: frozenset[str] = frozenset(), -) -> tuple[tuple[TraceScenario, TraceMode, str], ...]: +) -> tuple[tuple[TraceScenario, str], ...]: surface: Final = harness_case.surface if surface is None: return () return tuple( - (scenario, mode, f"trace:{surface}:{harness_case.sdk_function}:{scenario.name}:{mode}") + (scenario, f"trace:{surface}:{harness_case.sdk_function}:{scenario.name}") for scenario in trace_suite.scenarios if not selected_scenarios or scenario.name in selected_scenarios - for mode in scenario.modes ) @@ -77,54 +81,49 @@ def _record_setup_failure(run: HarnessRun, case: HarnessCase, message: str, stag run.failures.append((nodeid, message)) -def run_trace_mode( +def run_trace_scenario( run: HarnessRun, result: CaseResult, trace_suite: TraceSuite, scenario: TraceScenario, - mode: TraceMode, surface: Surface, nodeid: str, on_update: UpdateCallback, + engine: TraceEngine = "both", ) -> None: started_at: Final = monotonic() - comparison: Final = _execute_mode(trace_suite, scenario, mode, surface) + trace: Final = _execute_scenario(trace_suite, scenario, surface, engine) duration: Final = monotonic() - started_at - if isinstance(comparison, TraceExecutionFailure): + if isinstance(trace, TraceExecutionFailure): result.record(nodeid, RunStatus.ERROR, duration) - run.failures.append((nodeid, comparison.message)) + run.failures.append((nodeid, trace.message)) on_update(run) return - artifact: Final = ResultArtifact(TRACE_COMPARISON_ARTIFACT, comparison.model_dump_json()) - if comparison.has_errors(): + artifact: Final = ResultArtifact(TRACE_ARTIFACT, trace.model_dump_json()) + if trace.has_errors(): result.record(nodeid, RunStatus.ERROR, duration, (artifact,)) - run.failures.append( - (nodeid, "\n".join(error for error in (comparison.python_error, comparison.rust_error) if error)) - ) + run.failures.append((nodeid, "\n".join(error for error in (trace.python_error, trace.rust_error) if error))) else: - status: Final = RunStatus.PASSED if comparison.contract_matches() else RunStatus.FAILED - result.record(nodeid, status, duration, (artifact,)) - if status is RunStatus.FAILED: - run.failures.append((nodeid, "trace contract mismatch; see the rendered comparison")) + result.record(nodeid, RunStatus.PASSED, duration, (artifact,)) on_update(run) -def _execute_mode( +def _execute_scenario( trace_suite: TraceSuite, scenario: TraceScenario, - mode: TraceMode, surface: Surface, -) -> TraceComparisonArtifact | TraceExecutionFailure: + engine: TraceEngine, +) -> TraceArtifact | TraceExecutionFailure: route: Final = trace_suite.route if isinstance(route, GatewayRouteSpec): if surface != "gateway": return TraceExecutionFailure("harness", "gateway route cannot run on the sdk surface") from .gateway.execution import execute_gateway_trace - return execute_gateway_trace(route, scenario, mode) + return execute_gateway_trace(route, scenario, engine) if surface != "sdk": return TraceExecutionFailure("harness", "sdk route cannot run on the gateway surface") - return execute_trace(route, scenario, mode, surface) + return execute_trace(route, scenario, surface, engine) def _run_case( @@ -132,6 +131,7 @@ def _run_case( harness_case: HarnessCase, selected_scenarios: frozenset[str], on_update: UpdateCallback, + engine: TraceEngine, ) -> None: result: Final = run.results[harness_case.key] spec: Final = harness_case.spec @@ -146,15 +146,29 @@ def _run_case( on_update(run) return nodeids: Final = scenario_nodeids(trace_suite, harness_case, selected_scenarios) - result.collected.update(nodeid for _, _, nodeid in nodeids) + result.collected.update(nodeid for _, nodeid in nodeids) if not nodeids: result.status = RunStatus.SKIPPED on_update(run) return result.status = RunStatus.RUNNING on_update(run) - for scenario, mode, nodeid in nodeids: - run_trace_mode(run, result, trace_suite, scenario, mode, surface, nodeid, on_update) + for scenario, nodeid in nodeids: + run_trace_scenario(run, result, trace_suite, scenario, surface, nodeid, on_update, engine) + + +def runner_selection(runner_args: Sequence[str]) -> tuple[frozenset[str], TraceEngine]: + engine: TraceEngine = "both" + scenarios: list[str] = [] + for argument in runner_args: + if argument.startswith("--engine="): + value = argument.removeprefix("--engine=") + if value not in {"python", "rust"}: + raise ValueError(f"invalid trace engine: {value}") + engine = cast(TraceEngine, value) + else: + scenarios.append(argument) + return frozenset(scenarios), engine def run_trace_cases( @@ -163,10 +177,10 @@ def run_trace_cases( on_update: UpdateCallback, runner_args: Sequence[str] = (), ) -> tuple[int, HarnessRun]: - selected_scenarios: Final = frozenset(runner_args) + selected_scenarios, engine = runner_selection(runner_args) run: Final = HarnessRun.from_cases(cases) runnable_cases: Final = tuple(case for case in cases if isinstance(case.spec, ModuleCaseSpec)) - bridge_error: Final = ensure_trace_bridge(repo_root) if runnable_cases else None + bridge_error: Final = ensure_trace_bridge(repo_root) if runnable_cases and engine != "python" else None if bridge_error is not None: for harness_case in runnable_cases: _record_setup_failure(run, harness_case, bridge_error, "bridge") @@ -174,7 +188,7 @@ def run_trace_cases( on_update(run) return 1, run for harness_case in cases: - _run_case(run, harness_case, selected_scenarios, on_update) + _run_case(run, harness_case, selected_scenarios, on_update, engine) run.finished_at = monotonic() on_update(run) failed: Final = any( diff --git a/tests/rust-python-harness/strategies/trace_parity/sdk/chat_completions/case.py b/tests/rust-python-harness/strategies/trace_parity/sdk/chat_completions/case.py index 6be5afd60d6..1221f237570 100644 --- a/tests/rust-python-harness/strategies/trace_parity/sdk/chat_completions/case.py +++ b/tests/rust-python-harness/strategies/trace_parity/sdk/chat_completions/case.py @@ -1,10 +1,15 @@ from __future__ import annotations -import json from typing import Final -from .....shared.parity.recorded_http import HttpHeader, RecordedHttpResponse from .....shared.tracing.steps import Engine, mapping +from ...fixtures import ( + anthropic_response_body, + anthropic_stream_events, + aws_event_stream_response, + json_response, + sse_response, +) from ...models import RouteFixture, RouteSpec, TraceScenario, TraceSuite COMMON_MAPPINGS: Final = ( @@ -24,6 +29,22 @@ COMMON_MAPPINGS: Final = ( mapping(rust_span="execute_chat_completions_provider_call"), mapping(rust_span="http_request", python_frame=r"AsyncHTTPHandler\.post$|HTTPHandler\.post$"), mapping(rust_span="transform_response", python_frame=r"(? RouteFixture: - response: Final = json.dumps( - { - "id": "msg_trace", - "type": "message", - "role": "assistant", - "model": "claude-sonnet-5", - "content": [{"type": "text", "text": "hello"}], - "stop_reason": "end_turn", - "stop_sequence": None, - "usage": {"input_tokens": 2, "output_tokens": 3}, - } - ).encode() return RouteFixture( kwargs={ "model": "anthropic/claude-sonnet-5", "messages": [{"role": "user", "content": "hello"}], **({"optional_params": {"max_tokens": 16}} if engine == "rust" else {"max_tokens": 16}), }, - provider_responses=( - RecordedHttpResponse.from_bytes( - 200, (HttpHeader(name="content-type", value="application/json"),), response - ), - ), + provider_responses=(json_response(anthropic_response_body()),), ) def _bedrock_fixture(engine: Engine, _base_url: str) -> RouteFixture: - response: Final = json.dumps( - { - "output": {"message": {"role": "assistant", "content": [{"text": "hello"}]}}, - "stopReason": "end_turn", - "usage": {"inputTokens": 2, "outputTokens": 3, "totalTokens": 5}, - "metrics": {"latencyMs": 1}, - } - ).encode() + response: Final[dict[str, object]] = { + "output": {"message": {"role": "assistant", "content": [{"text": "hello"}]}}, + "stopReason": "end_turn", + "usage": {"inputTokens": 2, "outputTokens": 3, "totalTokens": 5}, + "metrics": {"latencyMs": 1}, + } credentials: Final = { "aws_access_key_id": "test-access", "aws_secret_access_key": "test-secret", @@ -94,11 +97,60 @@ def _bedrock_fixture(engine: Engine, _base_url: str) -> RouteFixture: else {**credentials, "max_tokens": 16} ), }, + provider_responses=(json_response(response),), + ) + + +def _anthropic_stream_fixture(engine: Engine, _base_url: str) -> RouteFixture: + fixture: Final = _anthropic_fixture(engine, _base_url) + return fixture.derive( + kwargs={"stream": True}, + provider_responses=(sse_response(anthropic_stream_events()),), + consume_stream=True, + ) + + +def _bedrock_stream_fixture(engine: Engine, _base_url: str) -> RouteFixture: + fixture: Final = _bedrock_fixture(engine, _base_url) + events: Final[tuple[dict[str, object], ...]] = ( + {"messageStart": {"role": "assistant"}}, + {"contentBlockStart": {"contentBlockIndex": 0, "start": {}}}, + {"contentBlockDelta": {"contentBlockIndex": 0, "delta": {"text": "hello"}}}, + {"contentBlockStop": {"contentBlockIndex": 0}}, + {"messageStop": {"stopReason": "end_turn"}}, + {"metadata": {"usage": {"inputTokens": 2, "outputTokens": 1, "totalTokens": 3}}}, + ) + return fixture.derive( + kwargs={"stream": True}, + provider_responses=(aws_event_stream_response(events),), + consume_stream=True, + ) + + +def _provider_error_fixture(engine: Engine, _base_url: str) -> RouteFixture: + fixture: Final = _anthropic_fixture(engine, _base_url) + return fixture.derive( provider_responses=( - RecordedHttpResponse.from_bytes( - 200, (HttpHeader(name="content-type", value="application/json"),), response + json_response( + {"type": "error", "error": {"type": "invalid_request_error", "message": "bad request"}}, + status=400, ), ), + expected_failure=True, + ) + + +def _stream_error_fixture(engine: Engine, base_url: str) -> RouteFixture: + fixture: Final = _anthropic_fixture(engine, base_url) + events: Final = ( + anthropic_stream_events()[0], + ("error", {"type": "error", "error": {"type": "overloaded_error", "message": "overloaded"}}), + ) + return fixture.derive( + kwargs={"stream": True}, + provider_responses=(sse_response(events),), + expected_failure=True, + consume_stream=True, ) @@ -132,18 +184,64 @@ TRACE_SUITE: Final = TraceSuite( route=SPEC, scenarios=( TraceScenario( - name="anthropic", + name="sync-anthropic", fixture=_anthropic_fixture, - mappings=COMMON_MAPPINGS, - sync_mappings=SYNC_MAPPINGS, - async_mappings=ASYNC_MAPPINGS, + mappings=SYNC_MAPPINGS, + asynchronous=False, ), TraceScenario( - name="bedrock", + name="async-anthropic", + fixture=_anthropic_fixture, + mappings=ASYNC_MAPPINGS, + asynchronous=True, + ), + TraceScenario( + name="sync-anthropic-stream", + fixture=_anthropic_stream_fixture, + mappings=(*SYNC_MAPPINGS, *STREAM_MAPPINGS), + asynchronous=False, + ), + TraceScenario( + name="async-anthropic-stream", + fixture=_anthropic_stream_fixture, + mappings=(*ASYNC_MAPPINGS, *STREAM_MAPPINGS), + asynchronous=True, + ), + TraceScenario( + name="async-anthropic-provider-error", + fixture=_provider_error_fixture, + mappings=(*ASYNC_MAPPINGS, *FAILURE_MAPPINGS), + asynchronous=True, + ), + TraceScenario( + name="async-anthropic-stream-error", + fixture=_stream_error_fixture, + mappings=(*ASYNC_MAPPINGS, *STREAM_MAPPINGS, *FAILURE_MAPPINGS), + asynchronous=True, + ), + TraceScenario( + name="sync-bedrock", fixture=_bedrock_fixture, - mappings=BEDROCK_COMMON_MAPPINGS, - sync_mappings=BEDROCK_SYNC_MAPPINGS, - async_mappings=BEDROCK_ASYNC_MAPPINGS, + mappings=BEDROCK_SYNC_MAPPINGS, + asynchronous=False, + ), + TraceScenario( + name="async-bedrock", + fixture=_bedrock_fixture, + mappings=BEDROCK_ASYNC_MAPPINGS, + asynchronous=True, + ), + TraceScenario( + name="sync-bedrock-event-stream", + fixture=_bedrock_stream_fixture, + mappings=(*BEDROCK_SYNC_MAPPINGS, *STREAM_MAPPINGS), + asynchronous=False, + ), + TraceScenario( + name="async-bedrock-event-stream", + fixture=_bedrock_stream_fixture, + mappings=(*BEDROCK_ASYNC_MAPPINGS, *STREAM_MAPPINGS), + asynchronous=True, ), ), ) diff --git a/tests/rust-python-harness/strategies/trace_parity/sdk/execution.py b/tests/rust-python-harness/strategies/trace_parity/sdk/execution.py index eb6c9233565..783c22a0dc0 100644 --- a/tests/rust-python-harness/strategies/trace_parity/sdk/execution.py +++ b/tests/rust-python-harness/strategies/trace_parity/sdk/execution.py @@ -1,18 +1,20 @@ from __future__ import annotations import asyncio -from collections.abc import Awaitable +import os +from collections.abc import AsyncIterable, Awaitable, Iterable from dataclasses import dataclass from pathlib import Path from typing import Final, Protocol, cast +from unittest.mock import patch from ....shared.parity.replay import replay_server from ....shared.reporting.models import Surface from ....shared.tracing.native import TraceResponsePayload, native_trace_events from ....shared.tracing.profiler import FunctionTraceEvent, profile_python from ....shared.tracing.steps import Engine, pipeline_projection -from ..models import RouteFixture, RouteSpec, TraceExecutionFailure, TraceMode, TraceScenario -from ..reporting import TraceComparisonArtifact +from ..models import RouteFixture, RouteSpec, TraceEngine, TraceExecutionFailure, TraceScenario +from ..reporting import TraceArtifact class SdkCall(Protocol): @@ -25,10 +27,20 @@ class _CollectedTrace: error: str | None = None -def _invoke(function: SdkCall, kwargs: dict[str, object], *, asynchronous: bool) -> object: +def _invoke( + function: SdkCall, + kwargs: dict[str, object], + *, + asynchronous: bool, + consume_stream: bool = False, +) -> object: async def invoke_async() -> object: try: - return await cast(Awaitable[object], function(**kwargs)) + response: Final = await cast(Awaitable[object], function(**kwargs)) + if consume_stream and isinstance(response, AsyncIterable): + stream = cast(AsyncIterable[object], response) + return tuple([item async for item in stream]) + return response finally: await asyncio.sleep(0) from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER @@ -38,7 +50,10 @@ def _invoke(function: SdkCall, kwargs: dict[str, object], *, asynchronous: bool) if asynchronous: return asyncio.run(invoke_async()) - return function(**kwargs) + response: Final = function(**kwargs) + if consume_stream and isinstance(response, Iterable): + return tuple(cast(Iterable[object], response)) + return response def _entrypoint(spec: RouteSpec, engine: Engine, *, asynchronous: bool) -> SdkCall | TraceExecutionFailure: @@ -47,6 +62,8 @@ def _entrypoint(spec: RouteSpec, engine: Engine, *, asynchronous: bool) -> SdkCa from litellm.rust_bridge import get_native_bridge if engine == "rust": + if spec.rust_entrypoints is None: + return TraceExecutionFailure("rust", f"{spec.route} has no native Rust trace entrypoint") bridge: Final = cast(object | None, get_native_bridge()) if bridge is None: return TraceExecutionFailure("rust", "native Rust bridge is required for trace parity") @@ -62,14 +79,6 @@ def _entrypoint(spec: RouteSpec, engine: Engine, *, asynchronous: bool) -> SdkCa return cast(SdkCall, getattr(owner, spec.python_entrypoints[int(asynchronous)])) -def _python_invocation_error(function: SdkCall, kwargs: dict[str, object], *, asynchronous: bool) -> str | None: - try: - _invoke(function, kwargs, asynchronous=asynchronous) - except Exception as error: - return f"{type(error).__name__}: {error}" - return None - - def _collect( function: SdkCall, fixture: RouteFixture, @@ -83,14 +92,23 @@ def _collect( return _CollectedTrace(native_trace_events(payload), payload.error) import litellm - with profile_python(Path(litellm.__file__).parent, threads=True) as profiler: - error: Final = _python_invocation_error(function, kwargs, asynchronous=asynchronous) + previous_suppress_debug_info: Final = litellm.suppress_debug_info + try: + if fixture.expected_failure: + litellm.suppress_debug_info = True + with profile_python(Path(litellm.__file__).parent, threads=True) as profiler: + error: str | None + try: + _invoke(function, kwargs, asynchronous=asynchronous, consume_stream=fixture.consume_stream) + error = None + except Exception as caught: + error = f"{type(caught).__name__}: {caught}" + finally: + litellm.suppress_debug_info = previous_suppress_debug_info return _CollectedTrace(tuple(profiler.events), error) -def collect_trace( - spec: RouteSpec, engine: Engine, *, asynchronous: bool -) -> tuple[FunctionTraceEvent, ...] | TraceExecutionFailure: +def collect_trace(spec: RouteSpec, engine: Engine, *, asynchronous: bool) -> tuple[FunctionTraceEvent, ...] | TraceExecutionFailure: function: Final = _entrypoint(spec, engine, asynchronous=asynchronous) if isinstance(function, TraceExecutionFailure): return function @@ -101,15 +119,18 @@ def collect_trace( provider.enqueue_response(response) fixture: Final = RouteFixture( kwargs={ - **base_fixture.kwargs, "api_key": "test-key", + **base_fixture.kwargs, "api_base": provider.url, **({"timeout_seconds": 5} if engine == "rust" else {"timeout": 5}), }, provider_responses=base_fixture.provider_responses, expected_failure=base_fixture.expected_failure, + consume_stream=base_fixture.consume_stream, + environment=base_fixture.environment, ) - collected: Final = _collect(function, fixture, engine, asynchronous=asynchronous) + with patch.dict(os.environ, fixture.environment): + collected: Final = _collect(function, fixture, engine, asynchronous=asynchronous) provider.take_requests(len(fixture.provider_responses)) except Exception as error: return TraceExecutionFailure(engine, f"{type(error).__name__}: {error}") @@ -129,48 +150,56 @@ def _failure_message(result: tuple[FunctionTraceEvent, ...] | TraceExecutionFail def execute_trace( - route: RouteSpec, scenario: TraceScenario, mode: TraceMode, surface: Surface -) -> TraceComparisonArtifact: - asynchronous: Final = mode == "async" - mappings: Final = scenario.mappings_for(mode) + route: RouteSpec, + scenario: TraceScenario, + surface: Surface, + engine: TraceEngine = "both", +) -> TraceArtifact: + effective_engine: Final[TraceEngine] = "python" if engine == "both" and route.rust_entrypoints is None else engine scenario_route: Final = RouteSpec( route=route.route, python_entrypoints=route.python_entrypoints, rust_entrypoints=route.rust_entrypoints, fixture=scenario.fixture, ) - python_trace: Final = collect_trace(scenario_route, "python", asynchronous=asynchronous) - rust_trace: Final = collect_trace(scenario_route, "rust", asynchronous=asynchronous) + python_trace: Final = ( + collect_trace( + scenario_route, + "python", + asynchronous=scenario.asynchronous, + ) + if effective_engine != "rust" + else () + ) + rust_trace: Final = ( + collect_trace(scenario_route, "rust", asynchronous=scenario.asynchronous) + if effective_engine != "python" + else () + ) python_error: Final = _failure_message(python_trace) rust_error: Final = _failure_message(rust_trace) python_events: Final = python_trace if isinstance(python_trace, tuple) else () rust_events: Final = rust_trace if isinstance(rust_trace, tuple) else () try: - python: Final = pipeline_projection("python", python_events, mappings) - rust: Final = pipeline_projection("rust", rust_events, mappings) + python: Final = pipeline_projection("python", python_events) + rust: Final = pipeline_projection("rust", rust_events) except ValueError as error: - return TraceComparisonArtifact.from_traces( + return TraceArtifact.from_traces( + engine=effective_engine, surface=surface, sdk_function=route.route, scenario=scenario.name, - mode=mode, - mappings=mappings, - contract=scenario.contract, python=(), rust=(), - python_unmatched=0, python_error=f"harness: {error}", ) - return TraceComparisonArtifact.from_traces( + return TraceArtifact.from_traces( + engine=effective_engine, surface=surface, sdk_function=route.route, scenario=scenario.name, - mode=mode, - mappings=mappings, - contract=scenario.contract, python=python.steps, rust=rust.steps, - python_unmatched=python.unmatched, python_error=python_error, rust_error=rust_error, ) diff --git a/tests/rust-python-harness/strategies/trace_parity/sdk/messages/case.py b/tests/rust-python-harness/strategies/trace_parity/sdk/messages/case.py index 27079c28cd8..211c454eadf 100644 --- a/tests/rust-python-harness/strategies/trace_parity/sdk/messages/case.py +++ b/tests/rust-python-harness/strategies/trace_parity/sdk/messages/case.py @@ -1,14 +1,26 @@ from __future__ import annotations -import json from typing import Final -from .....shared.parity.recorded_http import HttpHeader, RecordedHttpResponse from .....shared.tracing.steps import Engine, mapping +from ...fixtures import ( + anthropic_response_body, + anthropic_stream_events, + aws_event_stream_response, + json_response, + sse_response, +) from ...models import RouteFixture, RouteSpec, TraceScenario, TraceSuite COMMON_MAPPINGS: Final = ( mapping(rust_span="messages", python_frame=r"anthropic_interface/messages/__init__\.py:\d+ a?create$"), + mapping(span="python_sanitize_empty_content", python_frame=r"strip_empty_content_blocks_from_anthropic_messages$"), + mapping(span="python_sanitize_tool_ids", python_frame=r"sanitize_tool_use_ids_in_anthropic_messages$"), + mapping( + span="python_flatten_web_search", python_frame=r"flatten_unencrypted_web_search_results_in_anthropic_messages$" + ), + mapping(span="python_cache_control", python_frame=r"AnthropicCacheControlHook\.maybe_inject_cache_control$"), + mapping(span="python_pre_request_hooks", python_frame=r"_execute_pre_request_hooks$"), mapping( span="python_messages_provider_config", python_frame=r"ProviderConfigManager\.get_provider_anthropic_messages_config$", @@ -30,10 +42,42 @@ COMMON_MAPPINGS: Final = ( ), mapping(rust_span="http_request", python_frame=r"AsyncHTTPHandler\.post$|HTTPHandler\.post$"), mapping(rust_span="transform_response", python_frame=r"(? RouteFixture: conversation: Final = {"messages": [{"role": "user", "content": "hello"}], "max_tokens": 16} - response: Final = json.dumps( - { - "id": "msg_trace", - "type": "message", - "role": "assistant", - "model": "claude-sonnet-5", - "content": [{"type": "text", "text": "hello"}], - "stop_reason": "end_turn", - "stop_sequence": None, - "usage": {"input_tokens": 2, "output_tokens": 3}, - } - ).encode() return RouteFixture( kwargs={ "model": f"{provider}/claude-sonnet-5", **({"body": {**conversation, "model": "claude-sonnet-5"}} if engine == "rust" else conversation), }, - provider_responses=( - RecordedHttpResponse.from_bytes( - 200, (HttpHeader(name="content-type", value="application/json"),), response - ), - ), + provider_responses=(json_response(anthropic_response_body()),), ) @@ -88,11 +156,170 @@ def _azure_fixture(engine: Engine, _base_url: str) -> RouteFixture: return _fixture(engine, "azure_ai") +def _bedrock_kwargs(engine: Engine) -> dict[str, object]: + conversation: Final = {"messages": [{"role": "user", "content": "hello"}], "max_tokens": 16} + return { + "model": "bedrock/anthropic.claude-3-sonnet-20240229-v1:0", + **( + {"body": {**conversation, "model": "anthropic.claude-3-sonnet-20240229-v1:0"}} + if engine == "rust" + else conversation + ), + "aws_access_key_id": "AKIAIOSFODNN7EXAMPLE", + "aws_secret_access_key": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY", + "aws_region_name": "us-east-1", + } + + +def _bedrock_fixture(engine: Engine, _base_url: str) -> RouteFixture: + response_fixture: Final = _fixture(engine, "anthropic") + return RouteFixture(kwargs=_bedrock_kwargs(engine), provider_responses=response_fixture.provider_responses) + + +def _bedrock_retry_fixture(engine: Engine, _base_url: str) -> RouteFixture: + success_fixture: Final = _bedrock_fixture(engine, _base_url) + messages: Final = [ + {"role": "user", "content": "hello"}, + { + "role": "assistant", + "content": [ + {"type": "thinking", "thinking": "old reasoning", "signature": ""}, + {"type": "text", "text": "partial answer"}, + ], + }, + {"role": "user", "content": "continue"}, + ] + kwargs: Final = { + **_bedrock_kwargs(engine), + **( + {"body": {"messages": messages, "max_tokens": 16, "model": "anthropic.claude-3-sonnet-20240229-v1:0"}} + if engine == "rust" + else {"messages": messages} + ), + } + return success_fixture.derive( + kwargs=kwargs, + provider_responses=( + json_response({"message": "messages.1.content.0: Invalid `signature` in `thinking` block"}, status=400), + *success_fixture.provider_responses, + ), + ) + + +def _mock_fixture(engine: Engine, _base_url: str) -> RouteFixture: + fixture: Final = _fixture(engine, "anthropic") + return fixture.derive(kwargs={"mock_response": "hello from mock"}, provider_responses=()) + + +def _provider_error_fixture(engine: Engine, _base_url: str) -> RouteFixture: + fixture: Final = _fixture(engine, "anthropic") + return fixture.derive( + provider_responses=( + json_response( + {"type": "error", "error": {"type": "invalid_request_error", "message": "bad request"}}, + status=400, + ), + ), + expected_failure=True, + ) + + +def _sync_unsupported_fixture(engine: Engine, base_url: str) -> RouteFixture: + if engine == "rust": + return _anthropic_fixture(engine, base_url) + fixture: Final = _fixture(engine, "anthropic") + return fixture.derive(provider_responses=(), expected_failure=True) + + +def _stream_fixture_for(engine: Engine, provider: str) -> RouteFixture: + fixture: Final = _fixture(engine, provider) + return fixture.derive( + kwargs={"stream": True}, + provider_responses=(sse_response(anthropic_stream_events()),), + consume_stream=True, + ) + + +def _stream_fixture(engine: Engine, _base_url: str) -> RouteFixture: + return _stream_fixture_for(engine, "anthropic") + + +def _azure_stream_fixture(engine: Engine, _base_url: str) -> RouteFixture: + return _stream_fixture_for(engine, "azure_ai") + + +def _bedrock_stream_fixture(engine: Engine, base_url: str) -> RouteFixture: + fixture: Final = _bedrock_fixture(engine, base_url) + events: Final = tuple(payload for _, payload in anthropic_stream_events()) + return fixture.derive( + kwargs={"stream": True}, + provider_responses=(aws_event_stream_response(events),), + consume_stream=True, + ) + + +def _bedrock_stream_error_fixture(engine: Engine, base_url: str) -> RouteFixture: + fixture: Final = _bedrock_fixture(engine, base_url) + start: Final = anthropic_stream_events(model="anthropic.claude-3-sonnet-20240229-v1:0")[0][1] + return fixture.derive( + kwargs={"stream": True}, + provider_responses=(aws_event_stream_response((start, {"type": "message_stop"}), corrupt_last_frame=True),), + expected_failure=True, + consume_stream=True, + ) + + SPEC: Final = RouteSpec("messages", ("create", "acreate"), ("messages", "amessages"), _anthropic_fixture) TRACE_SUITE: Final = TraceSuite( route=SPEC, scenarios=( - TraceScenario(name="anthropic", fixture=_anthropic_fixture, mappings=ANTHROPIC_MAPPINGS, modes=("async",)), - TraceScenario(name="azure-ai", fixture=_azure_fixture, mappings=AZURE_MAPPINGS, modes=("async",)), + TraceScenario( + name="async-anthropic", fixture=_anthropic_fixture, mappings=ANTHROPIC_MAPPINGS, asynchronous=True + ), + TraceScenario(name="async-azure-ai", fixture=_azure_fixture, mappings=AZURE_MAPPINGS, asynchronous=True), + TraceScenario(name="async-bedrock", fixture=_bedrock_fixture, mappings=BEDROCK_MAPPINGS, asynchronous=True), + TraceScenario( + name="async-bedrock-invalid-thinking-retry", + fixture=_bedrock_retry_fixture, + mappings=RETRY_MAPPINGS, + asynchronous=True, + ), + TraceScenario(name="async-mock-response", fixture=_mock_fixture, mappings=MOCK_MAPPINGS, asynchronous=True), + TraceScenario( + name="async-anthropic-provider-error", + fixture=_provider_error_fixture, + mappings=ANTHROPIC_FAILURE_MAPPINGS, + asynchronous=True, + ), + TraceScenario( + name="async-anthropic-stream", + fixture=_stream_fixture, + mappings=(*ANTHROPIC_MAPPINGS, *STREAM_MAPPINGS), + asynchronous=True, + ), + TraceScenario( + name="async-azure-ai-stream", + fixture=_azure_stream_fixture, + mappings=(*AZURE_MAPPINGS, *STREAM_MAPPINGS), + asynchronous=True, + ), + TraceScenario( + name="async-bedrock-event-stream", + fixture=_bedrock_stream_fixture, + mappings=(*BEDROCK_MAPPINGS, *STREAM_MAPPINGS), + asynchronous=True, + ), + TraceScenario( + name="async-bedrock-event-stream-error", + fixture=_bedrock_stream_error_fixture, + mappings=(*BEDROCK_MAPPINGS, *STREAM_MAPPINGS, *FAILURE_MAPPINGS), + asynchronous=True, + ), + TraceScenario( + name="sync-unsupported", + fixture=_sync_unsupported_fixture, + mappings=ANTHROPIC_MAPPINGS, + asynchronous=False, + ), ), ) diff --git a/tests/rust-python-harness/strategies/trace_parity/sdk/ocr/case.py b/tests/rust-python-harness/strategies/trace_parity/sdk/ocr/case.py index 2a4a1b3a152..bb21e8ab0c5 100644 --- a/tests/rust-python-harness/strategies/trace_parity/sdk/ocr/case.py +++ b/tests/rust-python-harness/strategies/trace_parity/sdk/ocr/case.py @@ -1,7 +1,7 @@ from __future__ import annotations import json -from typing import Final, cast +from typing import Final from .....shared.parity.recorded_http import HttpHeader, RecordedHttpResponse from .....shared.tracing.steps import Engine, mapping @@ -53,6 +53,23 @@ ASYNC_MAPPINGS: Final = ( ), ) +PUBLIC_RUST_DISPATCH_MAPPINGS: Final = ( + mapping(span="public_sdk_entrypoint", python_frame=r"ocr/main\.py:\d+ a?ocr$"), + mapping(span="public_request", python_frame=r"ocr/main\.py:\d+ _public_request$"), + mapping(span="bind_request", python_frame=r"ocr/main\.py:\d+ _bind_request$"), + mapping(span="rust_ocr_enabled", python_frame=r"rust_bridge/configuration\.py:\d+ rust_ocr_enabled$"), + mapping(span="select_native_ocr", python_frame=r"rust_bridge/ocr_lifecycle\.py:\d+ select$"), + mapping(span="load_native_bridge", python_frame=r"rust_bridge/bindings\.py:\d+ NativeBinding\.load$"), + mapping(span="native_call_setup", python_frame=r"rust_bridge/lifecycle\.py:\d+ setup$"), + mapping(span="native_response", python_frame=r"rust_bridge/ocr\.py:\d+ _response$"), + mapping(span="native_call_finalize", python_frame=r"rust_bridge/lifecycle\.py:\d+ finalize$"), + mapping( + span="native_success_bookkeeping", + python_frame=r"rust_bridge/lifecycle\.py:\d+ success_bookkeeping$", + ), + *(mapping(rust_span=item.rust) for item in SYNC_MAPPINGS if item.rust is not None), +) + CALLBACK_SUCCESS_SYNC_MAPPINGS: Final = (*SYNC_MAPPINGS, SUCCESS_CALLBACK_SYNC_MAPPING) CALLBACK_SUCCESS_ASYNC_MAPPINGS: Final = (*ASYNC_MAPPINGS, SUCCESS_CALLBACK_ASYNC_MAPPING) CALLBACK_FAILURE_SYNC_MAPPINGS: Final = ( @@ -164,23 +181,6 @@ def _azure_fixture(engine: Engine, _base_url: str) -> RouteFixture: ) -def _vertex_fixture(engine: Engine, _base_url: str) -> RouteFixture: - fixture: Final = _fixture( - engine, - "vertex_ai/mistral-ocr-maas", - {"type": "image_url", "image_url": "data:image/png;base64,aGVsbG8="}, - ) - vertex: Final = {"vertex_project": "trace-project", "vertex_location": "us-central1"} - optional_params: Final = cast(dict[str, object], fixture.kwargs.get("optional_params", {})) - return RouteFixture( - kwargs={ - **fixture.kwargs, - **({"optional_params": {**optional_params, **vertex}} if engine == "rust" else vertex), - }, - provider_responses=fixture.provider_responses, - ) - - def _vertex_deepseek_fixture(engine: Engine, _base_url: str) -> RouteFixture: vertex: Final = {"vertex_project": "trace-project", "vertex_location": "us-central1"} return RouteFixture( @@ -204,6 +204,62 @@ def _vertex_deepseek_fixture(engine: Engine, _base_url: str) -> RouteFixture: ) +def _vertex_deepseek_credentials_fixture(engine: Engine, base_url: str) -> RouteFixture: + from cryptography.hazmat.primitives import serialization + from cryptography.hazmat.primitives.asymmetric import rsa + + fixture: Final = _vertex_deepseek_fixture(engine, base_url) + private_key: Final = rsa.generate_private_key(public_exponent=65537, key_size=2048) + credentials: Final = json.dumps( + { + "type": "service_account", + "project_id": "trace-project", + "private_key_id": "trace-key", + "private_key": private_key.private_bytes( + serialization.Encoding.PEM, + serialization.PrivateFormat.PKCS8, + serialization.NoEncryption(), + ).decode(), + "client_email": "trace@trace-project.iam.gserviceaccount.com", + "token_uri": f"{base_url}/token", + } + ) + return RouteFixture( + kwargs={**fixture.kwargs, "api_key": None}, + environment=(("VERTEXAI_CREDENTIALS", credentials), ("VERTEX_AI_API_KEY", "")), + provider_responses=( + RecordedHttpResponse.from_bytes( + 200, + (HttpHeader(name="content-type", value="application/json"),), + b'{"access_token":"trace-token","token_type":"Bearer","expires_in":3600}', + ), + *fixture.provider_responses, + ), + ) + + +def _cohere_fixture(engine: Engine, _base_url: str) -> RouteFixture: + return RouteFixture( + kwargs={ + "model": "cohere/parse-v5.0", + "document": {"type": "image_url", "image_url": "data:image/png;base64,aGVsbG8="}, + **({"optional_params": {"output_format": "blocks"}} if engine == "rust" else {"output_format": "blocks"}), + }, + provider_responses=( + RecordedHttpResponse.from_bytes( + 200, + (HttpHeader(name="content-type", value="application/json"),), + json.dumps( + { + "pages": [{"index": 0, "blocks": [{"type": "text", "text": {"content": "hello"}}]}], + "meta": {"billed_units": {"pages": 1}}, + } + ).encode(), + ), + ), + ) + + def _azure_document_intelligence_fixture(engine: Engine, base_url: str) -> RouteFixture: completed: Final = json.dumps( { @@ -249,30 +305,6 @@ def _azure_document_intelligence_fixture(engine: Engine, base_url: str) -> Route ) -VERTEX_COMMON_MAPPINGS: Final = ( - *COMMON_MAPPINGS[:7], - mapping( - rust_span="transform_ocr_request", - python_frame=( - r"VertexAIOCRConfig\.(?:async_)?transform_ocr_request$" - r"|MistralOCRConfig\.transform_ocr_request$" - ), - ), - COMMON_MAPPINGS[-1], -) -VERTEX_SYNC_MAPPINGS: Final = ( - *VERTEX_COMMON_MAPPINGS, - mapping(rust_span="execute_ocr_provider_call", python_frame=r"BaseLLMHTTPHandler\.ocr$"), - mapping(span="python_transform_ocr_response_wrapper", python_frame=r"BaseLLMHTTPHandler\._transform_ocr_response$"), - mapping(rust_span="transform_ocr_response", python_frame=r"MistralOCRConfig\.transform_ocr_response$"), -) -VERTEX_ASYNC_MAPPINGS: Final = ( - *VERTEX_COMMON_MAPPINGS, - mapping(span="python_ocr_wrapper", python_frame=r"BaseLLMHTTPHandler\.ocr$"), - mapping(rust_span="execute_ocr_provider_call", python_frame=r"BaseLLMHTTPHandler\.async_ocr$"), - mapping(rust_span="transform_ocr_response", python_frame=r"MistralOCRConfig\.transform_ocr_response$"), -) - DEEPSEEK_COMMON_MAPPINGS: Final = ( mapping(rust_span="ocr", python_frame=r"ocr/main\.py:\d+ a?ocr$"), mapping(rust_span="prepare_ocr_call", python_frame=r"ocr/main\.py:\d+ _prepare_ocr_request$"), @@ -352,59 +384,126 @@ DOCUMENT_INTELLIGENCE_ASYNC_MAPPINGS: Final = ( mapping(span="python_poll_http_request", python_frame=r"AsyncHTTPHandler\.get$"), ) +COHERE_COMMON_MAPPINGS: Final = ( + *COMMON_MAPPINGS[:7], + mapping( + rust_span="transform_ocr_request", + python_frame=r"CohereParseConfig\.(?:async_)?transform_ocr_request$", + ), + COMMON_MAPPINGS[-1], + mapping(rust_span="transform_ocr_response", python_frame=r"CohereParseConfig\.transform_ocr_response$"), +) +COHERE_ASYNC_MAPPINGS: Final = ( + *COHERE_COMMON_MAPPINGS, + mapping(span="python_ocr_wrapper", python_frame=r"BaseLLMHTTPHandler\.ocr$"), + mapping(rust_span="execute_ocr_provider_call", python_frame=r"BaseLLMHTTPHandler\.async_ocr$"), +) SPEC: Final = RouteSpec("ocr", ("ocr", "aocr"), ("ocr", "aocr"), _mistral_fixture) TRACE_SUITE: Final = TraceSuite( route=SPEC, scenarios=( TraceScenario( - name="mistral", + name="sync-mistral", fixture=_mistral_fixture, - mappings=COMMON_MAPPINGS, - sync_mappings=(*SYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), - async_mappings=(*ASYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + mappings=(*SYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + asynchronous=False, ), TraceScenario( - name="mistral-callback-success", + name="async-mistral", + fixture=_mistral_fixture, + mappings=(*ASYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + asynchronous=True, + ), + TraceScenario( + name="sync-mistral-callback-success", fixture=_mistral_callback_success_fixture, - mappings=COMMON_MAPPINGS, - sync_mappings=CALLBACK_SUCCESS_SYNC_MAPPINGS, - async_mappings=CALLBACK_SUCCESS_ASYNC_MAPPINGS, + mappings=CALLBACK_SUCCESS_SYNC_MAPPINGS, + asynchronous=False, ), TraceScenario( - name="mistral-callback-failure", + name="async-mistral-callback-success", + fixture=_mistral_callback_success_fixture, + mappings=CALLBACK_SUCCESS_ASYNC_MAPPINGS, + asynchronous=True, + ), + TraceScenario( + name="sync-mistral-callback-failure", fixture=_mistral_callback_failure_fixture, - mappings=(*COMMON_MAPPINGS, FAILURE_CALLBACK_MAPPING), - sync_mappings=CALLBACK_FAILURE_SYNC_MAPPINGS, - async_mappings=CALLBACK_FAILURE_ASYNC_MAPPINGS, + mappings=CALLBACK_FAILURE_SYNC_MAPPINGS, + asynchronous=False, ), TraceScenario( - name="azure-ai", + name="async-mistral-callback-failure", + fixture=_mistral_callback_failure_fixture, + mappings=CALLBACK_FAILURE_ASYNC_MAPPINGS, + asynchronous=True, + ), + TraceScenario( + name="sync-azure-ai", fixture=_azure_fixture, - mappings=AZURE_COMMON_MAPPINGS, - sync_mappings=(*AZURE_SYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), - async_mappings=(*AZURE_ASYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + mappings=(*AZURE_SYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + asynchronous=False, ), TraceScenario( - name="azure-document-intelligence", + name="async-azure-ai", + fixture=_azure_fixture, + mappings=(*AZURE_ASYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + asynchronous=True, + ), + TraceScenario( + name="sync-azure-document-intelligence", fixture=_azure_document_intelligence_fixture, - mappings=DOCUMENT_INTELLIGENCE_COMMON_MAPPINGS, - sync_mappings=(*DOCUMENT_INTELLIGENCE_SYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), - async_mappings=(*DOCUMENT_INTELLIGENCE_ASYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + mappings=(*DOCUMENT_INTELLIGENCE_SYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + asynchronous=False, ), TraceScenario( - name="vertex-ai", - fixture=_vertex_fixture, - mappings=VERTEX_COMMON_MAPPINGS, - sync_mappings=(*VERTEX_SYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), - async_mappings=(*VERTEX_ASYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + name="async-azure-document-intelligence", + fixture=_azure_document_intelligence_fixture, + mappings=(*DOCUMENT_INTELLIGENCE_ASYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + asynchronous=True, ), TraceScenario( - name="vertex-deepseek", + name="sync-vertex-deepseek", fixture=_vertex_deepseek_fixture, - mappings=DEEPSEEK_COMMON_MAPPINGS, - sync_mappings=(*DEEPSEEK_SYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), - async_mappings=(*DEEPSEEK_ASYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + mappings=(*DEEPSEEK_SYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + asynchronous=False, + ), + TraceScenario( + name="async-vertex-deepseek", + fixture=_vertex_deepseek_fixture, + mappings=(*DEEPSEEK_ASYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + asynchronous=True, + ), + TraceScenario( + name="sync-vertex-deepseek-credentials", + fixture=_vertex_deepseek_credentials_fixture, + mappings=DEEPSEEK_SYNC_MAPPINGS, + asynchronous=False, + ), + TraceScenario( + name="async-vertex-deepseek-credentials", + fixture=_vertex_deepseek_credentials_fixture, + mappings=DEEPSEEK_ASYNC_MAPPINGS, + asynchronous=True, + ), + TraceScenario( + name="async-cohere", + fixture=_cohere_fixture, + mappings=(*COHERE_ASYNC_MAPPINGS, IGNORED_SUCCESS_CALLBACK_MAPPING), + asynchronous=True, + ), + TraceScenario( + name="sync-public-rust-dispatch", + fixture=_mistral_fixture, + mappings=PUBLIC_RUST_DISPATCH_MAPPINGS, + asynchronous=False, + ), + TraceScenario( + name="async-public-rust-dispatch", + fixture=_mistral_fixture, + mappings=PUBLIC_RUST_DISPATCH_MAPPINGS, + asynchronous=True, ), ), ) diff --git a/tests/rust-python-harness/strategies/trace_parity/sdk/responses/case.py b/tests/rust-python-harness/strategies/trace_parity/sdk/responses/case.py new file mode 100644 index 00000000000..3f6e540efc5 --- /dev/null +++ b/tests/rust-python-harness/strategies/trace_parity/sdk/responses/case.py @@ -0,0 +1,216 @@ +from __future__ import annotations + +from typing import Final + +from .....shared.tracing.steps import Engine, mapping +from ...fixtures import ( + anthropic_response_body, + anthropic_stream_events, + json_response, + responses_body, + responses_stream_events, + sse_response, +) +from ...models import RouteFixture, RouteSpec, TraceScenario, TraceSuite + +COMMON_MAPPINGS: Final = ( + mapping(span="python_responses", python_frame=r"responses/main\.py:\d+ a?responses$"), + mapping( + span="python_responses_provider_config", + python_frame=r"ProviderConfigManager\.get_provider_responses_api_config$", + ), + mapping(rust_span="responses_provider_config"), + mapping(rust_span="validate_environment", python_frame=r"validate_environment$"), + mapping(rust_span="complete_url", python_frame=r"get_complete_url$"), + mapping( + rust_span="transform_request", + python_frame=r"(? RouteFixture: + model: Final = "gpt-5" + return RouteFixture( + kwargs={ + "model": f"{provider}/{model}", + "input": "hello", + **({"body": {"model": model, "input": "hello"}} if engine == "rust" else {}), + }, + provider_responses=(json_response(responses_body(model=model)),), + ) + + +def _openai_fixture(engine: Engine, _base_url: str) -> RouteFixture: + return _native_fixture(engine, "openai") + + +def _azure_fixture(engine: Engine, _base_url: str) -> RouteFixture: + fixture: Final = _native_fixture(engine, "azure") + return fixture.derive(kwargs={"api_version": "2025-04-01-preview"}) + + +def _openai_stream_fixture(engine: Engine, _base_url: str) -> RouteFixture: + fixture: Final = _openai_fixture(engine, _base_url) + return fixture.derive( + kwargs={"stream": True}, + provider_responses=(sse_response(responses_stream_events()),), + consume_stream=True, + ) + + +def _provider_error_fixture(engine: Engine, _base_url: str) -> RouteFixture: + fixture: Final = _openai_fixture(engine, _base_url) + return fixture.derive( + provider_responses=( + json_response({"error": {"message": "bad request", "type": "invalid_request_error"}}, status=400), + ), + expected_failure=True, + ) + + +def _stream_failed_fixture(engine: Engine, base_url: str) -> RouteFixture: + fixture: Final = _openai_fixture(engine, base_url) + failed_response: Final[dict[str, object]] = { + **responses_body(), + "status": "failed", + "output": [], + "error": {"message": "stream failed", "type": "server_error", "code": "server_error"}, + } + events: Final = ( + ( + "response.created", + {"type": "response.created", "response": {**failed_response, "status": "in_progress", "error": None}}, + ), + ("response.failed", {"type": "response.failed", "response": failed_response}), + ) + return fixture.derive( + kwargs={"stream": True}, + provider_responses=(sse_response(events),), + expected_failure=True, + consume_stream=True, + ) + + +def _anthropic_bridge_fixture(engine: Engine, _base_url: str) -> RouteFixture: + return RouteFixture( + kwargs={ + "model": "anthropic/claude-sonnet-5", + "input": "hello", + "max_output_tokens": 16, + **({"body": {"model": "claude-sonnet-5", "input": "hello"}} if engine == "rust" else {}), + }, + provider_responses=(json_response(anthropic_response_body()),), + ) + + +def _anthropic_bridge_stream_fixture(engine: Engine, _base_url: str) -> RouteFixture: + fixture: Final = _anthropic_bridge_fixture(engine, _base_url) + return fixture.derive( + kwargs={"stream": True}, + provider_responses=(sse_response(anthropic_stream_events()),), + consume_stream=True, + ) + + +SPEC: Final = RouteSpec("responses", ("responses", "aresponses"), None, _openai_fixture) +TRACE_SUITE: Final = TraceSuite( + route=SPEC, + scenarios=( + TraceScenario(name="sync-openai", fixture=_openai_fixture, mappings=COMMON_MAPPINGS, asynchronous=False), + TraceScenario(name="async-openai", fixture=_openai_fixture, mappings=COMMON_MAPPINGS, asynchronous=True), + TraceScenario( + name="sync-openai-stream", + fixture=_openai_stream_fixture, + mappings=(*COMMON_MAPPINGS, *STREAM_MAPPINGS), + asynchronous=False, + ), + TraceScenario( + name="async-openai-stream", + fixture=_openai_stream_fixture, + mappings=(*COMMON_MAPPINGS, *STREAM_MAPPINGS), + asynchronous=True, + ), + TraceScenario( + name="async-openai-provider-error", + fixture=_provider_error_fixture, + mappings=(*COMMON_MAPPINGS, *FAILURE_MAPPINGS), + asynchronous=True, + ), + TraceScenario( + name="async-openai-stream-failed", + fixture=_stream_failed_fixture, + mappings=(*COMMON_MAPPINGS, *STREAM_MAPPINGS, *FAILURE_MAPPINGS), + asynchronous=True, + ), + TraceScenario(name="async-azure", fixture=_azure_fixture, mappings=AZURE_MAPPINGS, asynchronous=True), + TraceScenario( + name="async-anthropic-chat-bridge", + fixture=_anthropic_bridge_fixture, + mappings=BRIDGE_MAPPINGS, + asynchronous=True, + ), + TraceScenario( + name="async-anthropic-chat-bridge-stream", + fixture=_anthropic_bridge_stream_fixture, + mappings=( + *BRIDGE_MAPPINGS, + mapping(span="python_chat_stream_wrapper", python_frame=r"CustomStreamWrapper\.__init__$"), + mapping(span="python_chat_stream_next", python_frame=r"CustomStreamWrapper\.__anext__$"), + mapping( + span="python_responses_bridge_stream_iterator", + python_frame=r"LiteLLMCompletionStreamingIterator\.__init__$|LiteLLMCompletionStreamingIterator\.__anext__$", + ), + ), + asynchronous=True, + ), + ), +) diff --git a/tests/rust-python-harness/strategies/trace_parity/sdk/test_core_scenario_matrix.py b/tests/rust-python-harness/strategies/trace_parity/sdk/test_core_scenario_matrix.py new file mode 100644 index 00000000000..d0dbd281a97 --- /dev/null +++ b/tests/rust-python-harness/strategies/trace_parity/sdk/test_core_scenario_matrix.py @@ -0,0 +1,69 @@ +from __future__ import annotations + +from importlib import import_module +from typing import Final, cast + +from ..models import TraceSuite + + +def _suite(module: str) -> TraceSuite: + loaded: Final = import_module(module) + candidate: Final = cast(object, getattr(loaded, "TRACE_SUITE")) + assert isinstance(candidate, TraceSuite) + return candidate + + +def test_core_sdk_scenario_matrix_keeps_distinct_migration_paths() -> None: + chat: Final = _suite("tests.rust-python-harness.strategies.trace_parity.sdk.chat_completions.case") + messages: Final = _suite("tests.rust-python-harness.strategies.trace_parity.sdk.messages.case") + ocr: Final = _suite("tests.rust-python-harness.strategies.trace_parity.sdk.ocr.case") + responses: Final = _suite("tests.rust-python-harness.strategies.trace_parity.sdk.responses.case") + + assert {(scenario.name, scenario.asynchronous) for scenario in chat.scenarios} >= { + ("sync-anthropic", False), + ("async-anthropic", True), + ("sync-anthropic-stream", False), + ("async-anthropic-stream", True), + ("async-anthropic-provider-error", True), + ("async-anthropic-stream-error", True), + ("sync-bedrock", False), + ("async-bedrock", True), + ("sync-bedrock-event-stream", False), + ("async-bedrock-event-stream", True), + } + assert {(scenario.name, scenario.asynchronous) for scenario in messages.scenarios} >= { + ("async-anthropic-stream", True), + ("async-azure-ai-stream", True), + ("async-bedrock-event-stream", True), + ("async-bedrock-event-stream-error", True), + ("async-bedrock-invalid-thinking-retry", True), + ("sync-unsupported", False), + } + assert {(scenario.name, scenario.asynchronous) for scenario in ocr.scenarios} >= { + ("async-cohere", True), + ("sync-public-rust-dispatch", False), + ("async-public-rust-dispatch", True), + } + assert {(scenario.name, scenario.asynchronous) for scenario in responses.scenarios} >= { + ("sync-openai", False), + ("async-openai", True), + ("sync-openai-stream", False), + ("async-openai-stream", True), + ("async-openai-provider-error", True), + ("async-openai-stream-failed", True), + ("async-azure", True), + ("async-anthropic-chat-bridge", True), + ("async-anthropic-chat-bridge-stream", True), + } + + +def test_core_gateway_matrix_keeps_downstream_streams_separate() -> None: + modules: Final = ( + "tests.rust-python-harness.strategies.trace_parity.gateway.chat_completions.case", + "tests.rust-python-harness.strategies.trace_parity.gateway.messages.case", + "tests.rust-python-harness.strategies.trace_parity.gateway.responses.case", + ) + + for module in modules: + suite = _suite(module) + assert any("downstream-stream" in scenario.name for scenario in suite.scenarios) diff --git a/tests/rust-python-harness/strategies/trace_parity/sdk/transcription/case.py b/tests/rust-python-harness/strategies/trace_parity/sdk/transcription/case.py index 2fb1054d10a..3b4d2e1447d 100644 --- a/tests/rust-python-harness/strategies/trace_parity/sdk/transcription/case.py +++ b/tests/rust-python-harness/strategies/trace_parity/sdk/transcription/case.py @@ -92,11 +92,16 @@ TRACE_SUITE: Final = TraceSuite( route=SPEC, scenarios=( TraceScenario( - name="bedrock", + name="sync-bedrock", fixture=_fixture, - mappings=MAPPINGS, - sync_mappings=SYNC_MAPPINGS, - async_mappings=ASYNC_MAPPINGS, + mappings=SYNC_MAPPINGS, + asynchronous=False, + ), + TraceScenario( + name="async-bedrock", + fixture=_fixture, + mappings=ASYNC_MAPPINGS, + asynchronous=True, ), ), ) diff --git a/tests/rust-python-harness/strategies/trace_parity/test_reporting.py b/tests/rust-python-harness/strategies/trace_parity/test_reporting.py index 68264064c92..22cc87592b8 100644 --- a/tests/rust-python-harness/strategies/trace_parity/test_reporting.py +++ b/tests/rust-python-harness/strategies/trace_parity/test_reporting.py @@ -1,58 +1,46 @@ from __future__ import annotations -from collections.abc import Sequence from typing import Final, Literal import pytest from ...shared.reporting.models import CaseResult, Coverage, HarnessCase, ResultArtifact, RunStatus from ...shared.reporting.strategy import ModuleCaseSpec, NotImplementedCaseSpec -from ...shared.tracing.steps import PipelineStep, TraceContract, TraceMapping, mapping +from ...shared.tracing.steps import PipelineStep from . import reporting -from .reporting import TRACE_COMPARISON_ARTIFACT, TraceComparisonArtifact, render_trace_results - -MAPPINGS: Final = ( - mapping(rust_span="ocr", python_frame=r"ocr/main\.py:\d+ a?ocr$"), - mapping(rust_span="http_request", python_frame=r"AsyncHTTPHandler\.post$"), -) +from .reporting import TRACE_ARTIFACT, TraceArtifact, render_trace_results -def _result(comparison: TraceComparisonArtifact) -> CaseResult: +def _result(trace: TraceArtifact) -> CaseResult: case: Final = HarnessCase( strategy_id="trace_parity", strategy_label="Trace parity", - sdk_function=comparison.sdk_function, + sdk_function=trace.sdk_function, spec=ModuleCaseSpec(coverage=Coverage.PARTIAL, module="example"), - surface=comparison.surface, + surface=trace.surface, ) result: Final = CaseResult(case=case) - nodeid: Final = f"trace:sdk:{comparison.sdk_function}:{comparison.scenario}:{comparison.mode}" + nodeid: Final = f"trace:{trace.surface}:{trace.sdk_function}:{trace.scenario}" result.collected.add(nodeid) - result.record( - nodeid, - RunStatus.PASSED, - artifacts=(ResultArtifact(TRACE_COMPARISON_ARTIFACT, comparison.model_dump_json()),), - ) + result.record(nodeid, RunStatus.PASSED, artifacts=(ResultArtifact(TRACE_ARTIFACT, trace.model_dump_json()),)) return result -def _comparison( +def _trace( python: tuple[PipelineStep, ...], rust: tuple[PipelineStep, ...], *, - mappings: Sequence[TraceMapping] = MAPPINGS, rust_error: str | None = None, -) -> TraceComparisonArtifact: - return TraceComparisonArtifact.from_traces( + engine: Literal["python", "rust", "both"] = "both", + scenario: str = "sync-default", +) -> TraceArtifact: + return TraceArtifact.from_traces( + engine=engine, surface="sdk", sdk_function="ocr", - scenario="default", - mode="sync", - mappings=mappings, - contract=TraceContract(), + scenario=scenario, python=python, rust=rust, - python_unmatched=796, rust_error=rust_error, ) @@ -67,107 +55,55 @@ def _events(*items: tuple[str, int, str | None]) -> tuple[PipelineStep, ...]: return tuple(steps) -def test_renderer_shows_matching_python_and_rust_paths() -> None: - rust: Final = _events(("ocr", 0, None), ("http_request", 1, None)) +def test_renderer_prints_python_and_rust_traces_independently() -> None: python: Final = _events( ("ocr", 0, "ocr/main.py:88 aocr"), - ("http_request", 1, "http_handler.py:673 AsyncHTTPHandler.post"), + ("python_prepare", 1, "prep.py:1 python_prepare"), ) - - section: Final = render_trace_results((_result(_comparison(python, rust)),))[0] - report: Final = "\n\n".join(section.blocks) - - assert section.title == "SDK trace comparisons" - assert "Case: ocr" in report - assert "PYTHON (2 steps)\n1 aocr (ocr/main.py:88)\n2 AsyncHTTPHandler.post (http_handler.py:673)" in report - assert "RUST (2 steps)\nocr -> 1 aocr\n http_request -> 2 AsyncHTTPHandler.post" in report - assert "Mapping (identifier -> span)" not in report - assert "Trace: MATCH" in report - assert "Same steps, order, and nesting" in report - assert "Unseen mappings:" not in report - - -def test_renderer_reports_mappings_that_matched_nothing() -> None: - events: Final = _events(("ocr", 0, None)) - - section: Final = render_trace_results((_result(_comparison(events, events)),))[0] - report: Final = "\n\n".join(section.blocks) - - assert "Unseen mappings: http_request" in report - assert "Contract: FAIL" in report - - -def test_renderer_numbers_repeated_span_occurrences() -> None: - mappings: Final = (MAPPINGS[0], MAPPINGS[1]) - rust: Final = _events(("ocr", 0, None), ("http_request", 1, None), ("http_request", 1, None)) - python: Final = _events( - ("ocr", 0, "ocr/main.py:88 aocr"), - ("http_request", 1, "http_handler.py:673 AsyncHTTPHandler.post"), - ("http_request", 1, "http_handler.py:673 AsyncHTTPHandler.post"), - ) - - report: Final = "\n\n".join(render_trace_results((_result(_comparison(python, rust, mappings=mappings)),))[0].blocks) - - assert "http_request#2" in report - - -def test_renderer_accepts_declared_engine_specific_steps() -> None: - mappings: Final = ( - *MAPPINGS[:1], - mapping(span="python_prepare", python_frame=r"python_prepare$"), - mapping(rust_span="rust_prepare"), - ) - python: Final = _events(("ocr", 0, None), ("python_prepare", 1, "prep.py:1 python_prepare")) rust: Final = _events(("ocr", 0, None), ("rust_prepare", 1, None)) - section: Final = render_trace_results((_result(_comparison(python, rust, mappings=mappings)),))[0] + section: Final = render_trace_results((_result(_trace(python, rust)),))[0] report: Final = "\n\n".join(section.blocks) - assert "2 python_prepare (prep.py:1) [python only]" in report - assert "rust_prepare -> [rust only]" in report - assert "Trace: MATCH" in report - assert "Contract: PASS" in report + assert section.title == "SDK traces" + assert "PYTHON (2 steps)\n1 aocr (ocr/main.py:88)\n2 python_prepare (prep.py:1)" in report + assert "RUST (2 steps)\n1 ocr\n2 rust_prepare" in report + assert "python only" not in report + assert "rust only" not in report + assert " -> " not in report + assert "Trace: MATCH" not in report + assert "Trace: DRIFT" not in report + assert "Contract:" not in report -def test_unavailable_check_reports_mode_from_nodeid() -> None: - case: Final = HarnessCase( - strategy_id="trace_parity", - strategy_label="Trace parity", - sdk_function="ocr", - spec=ModuleCaseSpec(coverage=Coverage.PARTIAL, module="example"), - surface="sdk", - ) - result: Final = CaseResult(case=case) - result.collected.add("trace:sdk:ocr:default:sync") - result.record("trace:sdk:ocr:default:sync", RunStatus.ERROR) +@pytest.mark.parametrize( + ("engine", "present", "absent"), + (("python", "PYTHON (1 steps)", "RUST"), ("rust", "RUST (1 steps)", "PYTHON")), +) +def test_renderer_prints_only_selected_engine(engine: Literal["python", "rust"], present: str, absent: str) -> None: + events: Final = _events(("ocr", 0, None)) - section: Final = render_trace_results((result,))[0] - report: Final = "\n\n".join(section.blocks) + report: Final = "\n\n".join(render_trace_results((_result(_trace(events, events, engine=engine)),))[0].blocks) - assert "Case: ocr" in report - assert "Scenario: default / Mode: sync" in report - assert "Trace: NOT AVAILABLE\nTest outcome: error" in report - assert "unknown mode" not in report + assert present in report + assert absent not in report def test_renderer_keeps_collected_trace_when_one_engine_errors() -> None: - python: Final = _events( - ("ocr", 0, "ocr/main.py:88 aocr"), - ("http_request", 1, "http_handler.py:673 AsyncHTTPHandler.post"), + python: Final = _events(("ocr", 0, "ocr/main.py:88 aocr")) + + report: Final = "\n\n".join( + render_trace_results( + (_result(_trace(python, (), rust_error="rust: native Rust bridge must include the trace-parity feature")),) + )[0].blocks ) - section: Final = render_trace_results( - (_result(_comparison(python, (), rust_error="rust: native Rust bridge must include the trace-parity feature")),) - )[0] - report: Final = "\n\n".join(section.blocks) - - assert "PYTHON (2 steps)\n1 aocr (ocr/main.py:88) [python only]" in report + assert "PYTHON (1 steps)\n1 aocr (ocr/main.py:88)" in report assert "Rust error: rust: native Rust bridge must include the trace-parity feature" in report assert "hint: rebuild the native bridge with the trace-parity feature" in report - assert "Contract: FAIL" in report -def test_renderer_groups_all_modes_under_one_case_header() -> None: +def test_unavailable_trace_reports_scenario_from_nodeid() -> None: case: Final = HarnessCase( strategy_id="trace_parity", strategy_label="Trace parity", @@ -176,76 +112,55 @@ def test_renderer_groups_all_modes_under_one_case_header() -> None: surface="sdk", ) result: Final = CaseResult(case=case) - events: Final = _events(("ocr", 0, None)) - modes: Final[tuple[Literal["sync", "async"], ...]] = ("sync", "async") - for mode in modes: - nodeid = f"trace:sdk:ocr:default:{mode}" - result.collected.add(nodeid) - comparison = TraceComparisonArtifact.from_traces( - surface="sdk", - sdk_function="ocr", - scenario="default", - mode=mode, - mappings=MAPPINGS, - contract=TraceContract(), - python=events, - rust=events, - python_unmatched=0, - ) - result.record( - nodeid, - RunStatus.PASSED, - artifacts=(ResultArtifact(TRACE_COMPARISON_ARTIFACT, comparison.model_dump_json()),), - ) + result.collected.add("trace:sdk:ocr:async-error") + result.record("trace:sdk:ocr:async-error", RunStatus.ERROR) - section: Final = render_trace_results((result,))[0] + report: Final = "\n\n".join(render_trace_results((result,))[0].blocks) + + assert "Scenario: async-error" in report + assert "Trace: NOT AVAILABLE\nTest outcome: error" in report + + +def test_renderer_groups_scenarios_under_one_case_header() -> None: + result: Final = _result(_trace(_events(("ocr", 0, None)), (), scenario="sync-default")) + async_trace: Final = _trace((), _events(("ocr", 0, None)), scenario="async-default") + nodeid: Final = "trace:sdk:ocr:async-default" + result.collected.add(nodeid) + result.record(nodeid, RunStatus.PASSED, artifacts=(ResultArtifact(TRACE_ARTIFACT, async_trace.model_dump_json()),)) + + report: Final = render_trace_results((result,))[0].blocks[0] - assert len(section.blocks) == 1 - report: Final = section.blocks[0] assert report.count("Case: ocr") == 1 - assert "Scenario: default / Mode: sync" in report - assert "Scenario: default / Mode: async" in report + assert "Scenario: sync-default" in report + assert "Scenario: async-default" in report def test_renderer_colors_every_trace_line_in_a_terminal(monkeypatch: pytest.MonkeyPatch) -> None: - rust: Final = _events(("ocr", 0, None), ("http_request", 1, None)) - python: Final = _events( - ("ocr", 0, "ocr/main.py:88 aocr"), - ("http_request", 1, "http_handler.py:673 AsyncHTTPHandler.post"), - ) + events: Final = _events(("ocr", 0, "ocr/main.py:88 aocr")) monkeypatch.setattr(reporting.sys.stdout, "isatty", lambda: True) monkeypatch.delenv("NO_COLOR", raising=False) - section: Final = render_trace_results((_result(_comparison(python, rust)),))[0] - report: Final = "\n\n".join(section.blocks) + report: Final = "\n\n".join(render_trace_results((_result(_trace(events, events)),))[0].blocks) - assert "\033[36mPYTHON\033[0m (2 steps)" in report + assert "\033[36mPYTHON\033[0m (1 steps)" in report assert "\033[36m1 aocr (ocr/main.py:88)\033[0m" in report - assert "\033[33mRUST\033[0m (2 steps)" in report - assert "\033[33mocr\033[0m -> \033[36m1 aocr\033[0m" in report - assert "\033[33mhttp_request\033[0m -> \033[36m2 AsyncHTTPHandler.post\033[0m" in report + assert "\033[33mRUST\033[0m (1 steps)" in report + assert "\033[33m1 ocr\033[0m" in report -def test_renderer_groups_cases_and_unavailable_entries_by_surface() -> None: - events: Final = _events(("ocr", 0, None)) - gateway_results: Final = tuple( - CaseResult( - case=HarnessCase( - strategy_id="trace_parity", - strategy_label="Trace parity", - sdk_function=sdk_function, - spec=NotImplementedCaseSpec(reason=f"No {sdk_function} case is registered."), - surface="gateway", - ), - status=RunStatus.NOT_IMPLEMENTED, - ) - for sdk_function in ("ocr", "messages") +def test_renderer_groups_unavailable_entries_by_surface() -> None: + gateway_result: Final = CaseResult( + case=HarnessCase( + strategy_id="trace_parity", + strategy_label="Trace parity", + sdk_function="messages", + spec=NotImplementedCaseSpec(reason="No messages case is registered."), + surface="gateway", + ), + status=RunStatus.NOT_IMPLEMENTED, ) - sections: Final = render_trace_results((_result(_comparison(events, events)), *gateway_results)) + sections: Final = render_trace_results((_result(_trace((), ())), gateway_result)) - assert tuple(section.title for section in sections) == ("SDK trace comparisons", "GATEWAY trace comparisons") - gateway_report: Final = "\n\n".join(sections[1].blocks) - assert gateway_report.count("Not implemented") == 1 - assert "- ocr: No ocr case is registered." in gateway_report - assert "- messages: No messages case is registered." in gateway_report + assert tuple(section.title for section in sections) == ("SDK traces", "GATEWAY traces") + assert "- messages: No messages case is registered." in "\n\n".join(sections[1].blocks) diff --git a/tests/rust-python-harness/strategies/trace_parity/test_runner.py b/tests/rust-python-harness/strategies/trace_parity/test_runner.py index 0fcc5860ff2..be25dd53b02 100644 --- a/tests/rust-python-harness/strategies/trace_parity/test_runner.py +++ b/tests/rust-python-harness/strategies/trace_parity/test_runner.py @@ -1,12 +1,23 @@ from __future__ import annotations -from typing import Final +import importlib +import os +from pathlib import Path +from types import SimpleNamespace +from typing import Final, cast + +import pytest + +import litellm from ...shared.reporting.models import Coverage, HarnessCase, HarnessRun, RunStatus, SdkFunction, Surface from ...shared.reporting.strategy import ModuleCaseSpec -from ...shared.tracing.steps import Engine +from ...shared.tracing.profiler import FunctionTraceEvent +from ...shared.tracing.steps import Engine, PipelineStep, mapping from .models import GatewayRouteSpec, RouteFixture, RouteSpec, TraceScenario, TraceSuite -from .runner import run_trace_mode, scenario_nodeids, validate_trace_suite +from .reporting import TraceArtifact +from .runner import run_trace_cases, run_trace_scenario, runner_selection, scenario_nodeids, validate_trace_suite +from .sdk.execution import SdkCall, collect_trace, execute_trace def _fixture(_engine: Engine, _base_url: str) -> RouteFixture: @@ -27,46 +38,243 @@ def test_scenario_filtering_and_occurrence_node_ids() -> None: suite: Final = TraceSuite( route=RouteSpec("ocr", ("ocr", "aocr"), ("ocr", "aocr"), _fixture), scenarios=( - TraceScenario("one", _fixture, (), modes=("sync", "async")), - TraceScenario("two", _fixture, (), modes=("async",)), + TraceScenario("sync-one", _fixture, (), asynchronous=False), + TraceScenario("async-one", _fixture, (), asynchronous=True), + TraceScenario("async-two", _fixture, (), asynchronous=True), ), ) case: Final = _case() - nodes: Final = scenario_nodeids(suite, case, frozenset({"two"})) + nodes: Final = scenario_nodeids(suite, case, frozenset({"async-two"})) - assert tuple(nodeid for _, _, nodeid in nodes) == ("trace:sdk:ocr:two:async",) + assert tuple(nodeid for _, nodeid in nodes) == ("trace:sdk:ocr:async-two",) + + +def test_python_engine_is_separate_from_scenario_selection() -> None: + assert runner_selection(("mistral", "--engine=python")) == (frozenset({"mistral"}), "python") + + +def test_python_engine_skips_native_bridge(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> None: + runner: Final = importlib.import_module("tests.rust-python-harness.strategies.trace_parity.runner") + case: Final = _case() + selected: list[tuple[frozenset[str], str]] = [] + + def reject_bridge(_repo_root: Path) -> str | None: + raise AssertionError("Python-only tracing must not inspect or build the native bridge") + + def capture_case( + _run: HarnessRun, + _case: HarnessCase, + scenarios: frozenset[str], + _on_update: object, + engine: str, + ) -> None: + selected.append((scenarios, engine)) + + monkeypatch.setattr(runner, "ensure_trace_bridge", reject_bridge) + monkeypatch.setattr(runner, "_run_case", capture_case) + + exit_code, _ = run_trace_cases((case,), tmp_path, lambda _: None, ("mistral", "--engine=python")) + + assert exit_code == 0 + assert selected == [(frozenset({"mistral"}), "python")] + + +def test_python_trace_preserves_native_ocr_dispatch_setting(monkeypatch: pytest.MonkeyPatch) -> None: + execution: Final = importlib.import_module("tests.rust-python-harness.strategies.trace_parity.sdk.execution") + route: Final = RouteSpec("ocr", ("ocr", "aocr"), ("ocr", "aocr"), _fixture) + observed: list[str | None] = [] + + def collect( + _function: SdkCall, + _fixture: RouteFixture, + _engine: Engine, + *, + asynchronous: bool, + ) -> SimpleNamespace: + observed.append(os.environ.get("LITELLM_RUST")) + return SimpleNamespace( + events=(FunctionTraceEvent(0, None, "aocr" if asynchronous else "ocr"),), + error=None, + ) + + monkeypatch.setattr(execution, "_collect", collect) + + monkeypatch.setenv("LITELLM_RUST", "0") + collect_trace(route, "python", asynchronous=False) + monkeypatch.setenv("LITELLM_RUST", "1") + collect_trace(route, "python", asynchronous=True) + + assert observed == ["0", "1"] + assert os.environ["LITELLM_RUST"] == "1" + + +def test_expected_provider_failure_omits_feedback_banner( + capsys: pytest.CaptureFixture[str], monkeypatch: pytest.MonkeyPatch +) -> None: + loaded: Final = importlib.import_module("tests.rust-python-harness.strategies.trace_parity.sdk.responses.case") + suite: Final = cast(TraceSuite, loaded.TRACE_SUITE) + scenario: Final = next(item for item in suite.scenarios if item.name == "async-openai-provider-error") + monkeypatch.setattr(litellm, "suppress_debug_info", False) + assert isinstance(suite.route, RouteSpec) + + result: Final = execute_trace(suite.route, scenario, "sdk", engine="python") + + assert result.python_error is None + assert "Give Feedback / Get Help" not in capsys.readouterr().out + assert litellm.suppress_debug_info is False + + +@pytest.mark.parametrize("asynchronous", (False, True)) +def test_vertex_trace_keeps_unmapped_helpers_and_parents(asynchronous: bool) -> None: + loaded: Final = importlib.import_module("tests.rust-python-harness.strategies.trace_parity.sdk.ocr.case") + suite: Final = cast(TraceSuite, loaded.TRACE_SUITE) + name: Final = f"{'async' if asynchronous else 'sync'}-vertex-deepseek" + scenario: Final = next(item for item in suite.scenarios if item.name == name) + assert isinstance(suite.route, RouteSpec) + + trace: Final = execute_trace(suite.route, scenario, "sdk", engine="python") + + assert trace.python_error is None + url: Final = next( + event for event in trace.python if event.raw.endswith(" VertexAIDeepSeekOCRConfig.get_complete_url") + ) + project: Final = next( + event for event in trace.python if event.raw.endswith(" VertexBase.safe_get_vertex_ai_project") + ) + location: Final = next( + event for event in trace.python if event.raw.endswith(" VertexBase.safe_get_vertex_ai_location") + ) + assert project.parent_id == location.parent_id == url.id + assert not any(event.raw.endswith(" VertexBase.get_access_token") for event in trace.python) + + +@pytest.mark.parametrize("asynchronous", (False, True)) +def test_vertex_credentials_trace_runs_real_auth_helpers(asynchronous: bool, monkeypatch: pytest.MonkeyPatch) -> None: + loaded: Final = importlib.import_module("tests.rust-python-harness.strategies.trace_parity.sdk.ocr.case") + suite: Final = cast(TraceSuite, loaded.TRACE_SUITE) + name: Final = f"{'async' if asynchronous else 'sync'}-vertex-deepseek-credentials" + scenario: Final = next(item for item in suite.scenarios if item.name == name) + monkeypatch.setenv("VERTEXAI_CREDENTIALS", "original-credentials") + monkeypatch.setenv("VERTEX_AI_API_KEY", "original-api-key") + assert isinstance(suite.route, RouteSpec) + + trace: Final = execute_trace(suite.route, scenario, "sdk", engine="python") + + assert trace.python_error is None + validate: Final = next( + event for event in trace.python if event.raw.endswith(" VertexAIDeepSeekOCRConfig.validate_environment") + ) + helpers: Final = ( + "VertexBase.safe_get_vertex_ai_project", + "VertexBase.safe_get_vertex_ai_credentials", + "VertexBase.get_access_token", + ) + assert tuple(event.raw.split(" ", 1)[1] for event in trace.python if event.parent_id == validate.id) == helpers + token: Final = next(event for event in trace.python if event.raw.endswith(" VertexBase.get_access_token")) + load: Final = next(event for event in trace.python if event.raw.endswith(" VertexBase.load_auth")) + refresh: Final = next(event for event in trace.python if event.raw.endswith(" VertexBase.refresh_auth")) + assert load.parent_id == token.id + assert refresh.parent_id == load.id + assert os.environ["VERTEXAI_CREDENTIALS"] == "original-credentials" + assert os.environ["VERTEX_AI_API_KEY"] == "original-api-key" + + +def test_gateway_trace_keeps_calls_outside_scenario_mappings(monkeypatch: pytest.MonkeyPatch) -> None: + execution: Final = importlib.import_module("tests.rust-python-harness.strategies.trace_parity.gateway.execution") + events: Final = ( + FunctionTraceEvent(0, None, "route.py:1 entry"), + FunctionTraceEvent(1, 0, "auth.py:2 authenticate"), + FunctionTraceEvent(2, 1, "auth.py:3 credentials"), + ) + scenario: Final = TraceScenario( + "async-gateway", + _fixture, + (mapping(rust_span="entry", python_frame=r" entry$"),), + asynchronous=True, + ) + monkeypatch.setattr(execution, "_collect", lambda *_args: events) + + trace: Final = execution.execute_gateway_trace(GatewayRouteSpec("messages"), scenario, engine="python") + + assert trace.python_error is None + assert tuple((event.id, event.parent_id, event.raw) for event in trace.python) == tuple( + (event.id, event.parent_id, event.raw) for event in events + ) + + +def test_default_trace_skips_unavailable_rust_sdk_entrypoint(monkeypatch: pytest.MonkeyPatch) -> None: + execution: Final = importlib.import_module("tests.rust-python-harness.strategies.trace_parity.sdk.execution") + route: Final = RouteSpec("responses", ("responses", "aresponses"), None, _fixture) + scenario: Final = TraceScenario("sync-openai", _fixture, (), asynchronous=False) + engines: list[Engine] = [] + + def collect(_route: RouteSpec, engine: Engine, *, asynchronous: bool) -> tuple[FunctionTraceEvent, ...]: + engines.append(engine) + return (FunctionTraceEvent(0, None, "responses"),) + + monkeypatch.setattr(execution, "collect_trace", collect) + + trace: Final = execution.execute_trace(route, scenario, "sdk") + + assert engines == ["python"] + assert trace.engine == "python" + assert trace.rust_error is None + + +def test_default_trace_skips_unavailable_rust_gateway_route(monkeypatch: pytest.MonkeyPatch) -> None: + execution: Final = importlib.import_module("tests.rust-python-harness.strategies.trace_parity.gateway.execution") + route: Final = GatewayRouteSpec("responses", rust_supported=False) + scenario: Final = TraceScenario("async-openai", _fixture, (), asynchronous=True) + engines: list[Engine] = [] + + def collect(_route: GatewayRouteSpec, _scenario: TraceScenario, engine: Engine) -> tuple[FunctionTraceEvent, ...]: + engines.append(engine) + return (FunctionTraceEvent(0, None, "responses"),) + + monkeypatch.setattr(execution, "_collect", collect) + + trace: Final = execution.execute_gateway_trace(route, scenario) + + assert engines == ["python"] + assert trace.engine == "python" + assert trace.rust_error is None def test_scenario_validation_rejects_duplicate_and_unsafe_names() -> None: route: Final = RouteSpec("ocr", ("ocr", "aocr"), ("ocr", "aocr"), _fixture) duplicate: Final = TraceSuite( route=route, - scenarios=(TraceScenario("same", _fixture, ()), TraceScenario("same", _fixture, ())), + scenarios=( + TraceScenario("sync-same", _fixture, (), asynchronous=False), + TraceScenario("sync-same", _fixture, (), asynchronous=False), + ), + ) + unsafe: Final = TraceSuite( + route=route, scenarios=(TraceScenario("sync-bad:name", _fixture, (), asynchronous=False),) ) - unsafe: Final = TraceSuite(route=route, scenarios=(TraceScenario("bad:name", _fixture, ()),)) case: Final = _case() assert validate_trace_suite(duplicate, case) is not None assert validate_trace_suite(unsafe, case) is not None -def test_scenario_validation_rejects_invalid_modes_and_route_registration() -> None: - invalid_modes: Final = TraceSuite( +def test_scenario_validation_rejects_invalid_names_and_route_registration() -> None: + invalid_name: Final = TraceSuite( route=RouteSpec("ocr", ("ocr", "aocr"), ("ocr", "aocr"), _fixture), - scenarios=(TraceScenario("invalid", _fixture, (), modes=("sync", "sync")),), + scenarios=(TraceScenario("bedrock", _fixture, (), asynchronous=True),), ) wrong_function: Final = TraceSuite( route=RouteSpec("messages", ("create", "acreate"), ("messages", "amessages"), _fixture), - scenarios=(TraceScenario("one", _fixture, ()),), + scenarios=(TraceScenario("sync-one", _fixture, (), asynchronous=False),), ) wrong_surface: Final = TraceSuite( route=GatewayRouteSpec("ocr"), - scenarios=(TraceScenario("one", _fixture, ()),), + scenarios=(TraceScenario("sync-one", _fixture, (), asynchronous=False),), ) case: Final = _case() - assert "unique sync/async modes" in (validate_trace_suite(invalid_modes, case) or "") + assert "start with sync- or async-" in (validate_trace_suite(invalid_name, case) or "") assert "does not match case function" in (validate_trace_suite(wrong_function, case) or "") assert "must use RouteSpec" in (validate_trace_suite(wrong_surface, case) or "") @@ -77,11 +285,35 @@ def test_invalid_route_dispatch_records_harness_error() -> None: result: Final = run.results[case.key] suite: Final = TraceSuite( route=GatewayRouteSpec("ocr"), - scenarios=(TraceScenario("one", _fixture, (), modes=("sync",)),), + scenarios=(TraceScenario("sync-one", _fixture, (), asynchronous=False),), ) - nodeid: Final = "trace:sdk:ocr:one:sync" + nodeid: Final = "trace:sdk:ocr:sync-one" - run_trace_mode(run, result, suite, suite.scenarios[0], "sync", "sdk", nodeid, lambda _: None) + run_trace_scenario(run, result, suite, suite.scenarios[0], "sdk", nodeid, lambda _: None) assert result.outcomes[nodeid] is RunStatus.ERROR assert run.failures == [(nodeid, "gateway route cannot run on the sdk surface")] + + +def test_different_python_and_rust_traces_pass(monkeypatch: pytest.MonkeyPatch) -> None: + runner: Final = importlib.import_module("tests.rust-python-harness.strategies.trace_parity.runner") + case: Final = _case() + run: Final = HarnessRun.from_cases((case,)) + result: Final = run.results[case.key] + suite: Final = TraceSuite( + route=RouteSpec("ocr", ("ocr", "aocr"), ("ocr", "aocr"), _fixture), + scenarios=(TraceScenario("sync-one", _fixture, (), asynchronous=False),), + ) + trace: Final = TraceArtifact.from_traces( + surface="sdk", + sdk_function="ocr", + scenario="sync-one", + python=(PipelineStep(0, None, "python_step", "python.py:1 python_step"),), + rust=(PipelineStep(0, None, "rust_step", "rust_step"),), + ) + monkeypatch.setattr(runner, "_execute_scenario", lambda *_args: trace) + + run_trace_scenario(run, result, suite, suite.scenarios[0], "sdk", "trace:sdk:ocr:sync-one", lambda _: None) + + assert result.outcomes["trace:sdk:ocr:sync-one"] is RunStatus.PASSED + assert run.failures == [] diff --git a/tests/rust-python-harness/strategies/unit_tests_mapping/mapping_validator.py b/tests/rust-python-harness/strategies/unit_tests_mapping/mapping_validator.py index 98ea0b02e68..9dd79e860e6 100644 --- a/tests/rust-python-harness/strategies/unit_tests_mapping/mapping_validator.py +++ b/tests/rust-python-harness/strategies/unit_tests_mapping/mapping_validator.py @@ -38,30 +38,28 @@ def _trace_functions( python_functions: Final[dict[str, PythonFunctionIdentity]] = {} rust_functions: Final[dict[str, RustFunctionIdentity]] = {} for scenario in suite.scenarios: - for mode in scenario.modes: - route: Final = RouteSpec( - route=suite.route.route, - python_entrypoints=suite.route.python_entrypoints, - rust_entrypoints=suite.route.rust_entrypoints, - fixture=scenario.fixture, - ) - python_trace: Final = collect_trace(route, "python", asynchronous=mode == "async") - rust_trace: Final = collect_trace(route, "rust", asynchronous=mode == "async") - if isinstance(python_trace, TraceExecutionFailure): - raise ValueError(f"Python trace discovery failed for {scenario.name}/{mode}: {python_trace.message}") - if isinstance(rust_trace, TraceExecutionFailure): - raise ValueError(f"Rust trace discovery failed for {scenario.name}/{mode}: {rust_trace.message}") - mappings: Final = scenario.mappings_for(mode) - python_projection: Final = pipeline_projection("python", python_trace, mappings) - rust_projection: Final = pipeline_projection("rust", rust_trace, mappings) - for step in python_projection.steps: - if step.span in spec.trace_spans: - function: Final = PythonFunctionIdentity.from_trace(step.raw) - python_functions[function.raw] = function - for step in rust_projection.steps: - if step.span in spec.trace_spans: - function: Final = RustFunctionIdentity.from_trace(step.raw) - rust_functions[step.raw] = function + route: Final = RouteSpec( + route=suite.route.route, + python_entrypoints=suite.route.python_entrypoints, + rust_entrypoints=suite.route.rust_entrypoints, + fixture=scenario.fixture, + ) + python_trace: Final = collect_trace(route, "python", asynchronous=scenario.asynchronous) + rust_trace: Final = collect_trace(route, "rust", asynchronous=scenario.asynchronous) + if isinstance(python_trace, TraceExecutionFailure): + raise ValueError(f"Python trace discovery failed for {scenario.name}: {python_trace.message}") + if isinstance(rust_trace, TraceExecutionFailure): + raise ValueError(f"Rust trace discovery failed for {scenario.name}: {rust_trace.message}") + python_projection: Final = pipeline_projection("python", python_trace, scenario.mappings) + rust_projection: Final = pipeline_projection("rust", rust_trace, scenario.mappings) + for step in python_projection.steps: + if step.span in spec.trace_spans: + function: Final = PythonFunctionIdentity.from_trace(step.raw) + python_functions[function.raw] = function + for step in rust_projection.steps: + if step.span in spec.trace_spans: + function: Final = RustFunctionIdentity.from_trace(step.raw) + rust_functions[step.raw] = function if not python_functions or not rust_functions: raise ValueError(f"Python trace discovery found no functions for spans: {', '.join(spec.trace_spans)}") return ( diff --git a/tests/test_litellm/batches/test_batch_utils.py b/tests/test_litellm/batches/test_batch_utils.py index 768ea332677..8b04d7af70a 100644 --- a/tests/test_litellm/batches/test_batch_utils.py +++ b/tests/test_litellm/batches/test_batch_utils.py @@ -695,6 +695,38 @@ def test_vertex_cost_and_usage_aggregation(monkeypatch): assert result.failed_requests == 0 +def test_vertex_batch_usage_preserves_modality_token_details(monkeypatch): + monkeypatch.setitem( + litellm.model_cost, + "vertex_ai/gemini-embedding-2", + { + "input_cost_per_token_batches": 1e-7, + "input_cost_per_audio_token_batches": 3.25e-6, + "input_cost_per_image_token_batches": 2.25e-7, + "input_cost_per_video_token_batches": 6e-6, + }, + ) + responses = [ + { + "response": { + "usageMetadata": { + "promptTokenCount": 84, + "candidatesTokenCount": 0, + "totalTokenCount": 84, + "promptTokensDetails": [ + {"modality": "AUDIO", "tokenCount": 64}, + {"modality": "TEXT", "tokenCount": 20}, + ], + } + } + } + ] + + result = bu.calculate_vertex_ai_batch_cost_and_usage(responses, "gemini-embedding-2") + + assert result.prompt_cost == pytest.approx(64 * 3.25e-6 + 20 * 1e-7) + + def test_vertex_cost_skips_none_response_body(monkeypatch): import litellm.cost_calculator as cc diff --git a/tests/test_litellm/caching/test_caching.py b/tests/test_litellm/caching/test_caching.py index 4d0ec0fb677..c7ec8abc31e 100644 --- a/tests/test_litellm/caching/test_caching.py +++ b/tests/test_litellm/caching/test_caching.py @@ -1,9 +1,12 @@ import logging import re +from unittest.mock import MagicMock import pytest +import litellm.caching.redis_cache as redis_cache_module from litellm.caching.caching import Cache +from litellm.caching.redis_cache import RedisCache, _RedisTimeoutLogThrottle from litellm.types.caching import LiteLLMCacheType, SemanticCacheScope from litellm.types.utils import Embedding, EmbeddingResponse, Usage @@ -53,6 +56,29 @@ def test_cache_key_debug_log_does_not_include_prompt_material(caplog): assert any(cache_key in message for message in created_cache_key_logs) +@pytest.mark.parametrize( + ("backend", "expected_level"), + [ + pytest.param(MagicMock(spec=RedisCache), logging.DEBUG, id="redis_backend_is_throttled"), + pytest.param(MagicMock(), logging.ERROR, id="other_backend_logs_every_timeout"), + ], +) +def test_add_cache_timeout_only_joins_redis_throttle_for_redis_backends(backend, expected_level, caplog, monkeypatch): + throttle = _RedisTimeoutLogThrottle(interval=5.0, clock=MagicMock(return_value=1_000.0)) + assert throttle.admit() == 0 + monkeypatch.setattr(redis_cache_module, "_redis_timeout_log_throttle", throttle) + + cache = Cache(type=LiteLLMCacheType.LOCAL) + backend.set_cache.side_effect = TimeoutError("lit7520 backend timed out") + cache.cache = backend + + with caplog.at_level(logging.DEBUG, logger="LiteLLM"): + cache.add_cache("result", model="gpt-4.1-mini", messages=[{"role": "user", "content": "hi"}]) + + records = [r for r in caplog.records if "lit7520 backend timed out" in r.getMessage()] + assert [r.levelno for r in records] == [expected_level] + + def _embedding_response(prompt_tokens, num_items): return EmbeddingResponse( model="amazon.titan-embed-image-v1", diff --git a/tests/test_litellm/caching/test_dual_cache.py b/tests/test_litellm/caching/test_dual_cache.py index 4c9068722b8..95395878c25 100644 --- a/tests/test_litellm/caching/test_dual_cache.py +++ b/tests/test_litellm/caching/test_dual_cache.py @@ -704,3 +704,58 @@ async def test_open_breaker_keeps_async_batch_read_memory_hits_and_releases_rese assert list(await cache.async_batch_get_cache(["k1", "k2"])) == ["v1", None] assert "k2" not in cache.last_redis_batch_access_time + + +@pytest.mark.asyncio +async def test_redis_timeouts_falling_back_to_memory_log_once_per_interval(caplog, monkeypatch): + """The first fallback WARNING of a timeout streak logs, the rest stay at DEBUG until the summary.""" + from redis.exceptions import TimeoutError as RedisTimeoutError + + from litellm.caching import redis_cache as redis_cache_module + from litellm.caching.redis_cache import _RedisTimeoutLogThrottle + + clock = MagicMock(return_value=1_000.0) + monkeypatch.setattr( + redis_cache_module, "_redis_timeout_log_throttle", _RedisTimeoutLogThrottle(interval=5.0, clock=clock) + ) + + class _TimingOutRedis: + async def async_increment_pipeline(self, increment_list, **kwargs): + raise RedisTimeoutError("Timeout reading from 127.0.0.1:6379") + + async def async_increment(self, key, value, **kwargs): + raise RedisTimeoutError("Timeout reading from 127.0.0.1:6379") + + cache = DualCache( + in_memory_cache=InMemoryCache(), + redis_cache=_TimingOutRedis(), # pyright: ignore[reportArgumentType] # duck-typed Redis double + ) + increments = [RedisPipelineIncrementOperation(key="k", increment_value=1.0, ttl=60)] + + with caplog.at_level(logging.DEBUG, logger="LiteLLM"): + for _ in range(100): + await cache.async_increment_cache_pipeline(increment_list=increments) + await cache.async_increment_cache("k", 1.0) + + visible = [r for r in caplog.records if r.levelno >= logging.WARNING] + assert [(r.levelno, r.getMessage()) for r in visible] == [ + ( + logging.WARNING, + "Redis async_increment_cache_pipeline failed, falling back to in-memory result:" + " Timeout reading from 127.0.0.1:6379", + ) + ] + assert visible[0].filename == "dual_cache.py" + assert sum("Timeout reading from" in r.getMessage() for r in caplog.records) == 200 + + caplog.clear() + clock.return_value += 5.0 + with caplog.at_level(logging.DEBUG, logger="LiteLLM"): + await cache.async_increment_cache("k", 1.0) + assert [(r.levelno, r.getMessage()) for r in caplog.records] == [ + ( + logging.WARNING, + "Redis async_increment_cache failed, falling back to in-memory result: Timeout reading from 127.0.0.1:6379" + " (199 more Redis timeouts since the previous Redis timeout line were logged at DEBUG)", + ) + ] diff --git a/tests/test_litellm/caching/test_redis_cache.py b/tests/test_litellm/caching/test_redis_cache.py index 4bf7894829e..19638c60b4b 100644 --- a/tests/test_litellm/caching/test_redis_cache.py +++ b/tests/test_litellm/caching/test_redis_cache.py @@ -978,17 +978,17 @@ async def test_stale_timeout_does_not_let_sub_threshold_hard_failures_open_the_b from redis.exceptions import ConnectionError as RedisConnectionError from redis.exceptions import TimeoutError as RedisTimeoutError - from litellm.caching.redis_cache import RedisCircuitBreaker, _is_redis_timeout_failure + from litellm.caching.redis_cache import RedisCircuitBreaker, is_redis_timeout_failure breaker = RedisCircuitBreaker(failure_threshold=3, recovery_timeout=60, timeout_min_duration=0.05) - breaker.record_failure(is_timeout=_is_redis_timeout_failure(RedisTimeoutError("read timed out"))) + breaker.record_failure(is_timeout=is_redis_timeout_failure(RedisTimeoutError("read timed out"))) await asyncio.sleep(0.06) for _ in range(breaker.failure_threshold - 1): - breaker.record_failure(is_timeout=_is_redis_timeout_failure(RedisConnectionError("refused"))) + breaker.record_failure(is_timeout=is_redis_timeout_failure(RedisConnectionError("refused"))) assert breaker.is_open() is False, "2 hard failures and 1 stale timeout are below both thresholds" - breaker.record_failure(is_timeout=_is_redis_timeout_failure(RedisConnectionError("refused"))) + breaker.record_failure(is_timeout=is_redis_timeout_failure(RedisConnectionError("refused"))) assert breaker.is_open() is True, "the threshold-th hard failure must still open it" @@ -1000,19 +1000,19 @@ async def test_hard_failure_resets_timeout_streak_so_a_later_burst_must_earn_its from redis.exceptions import ConnectionError as RedisConnectionError from redis.exceptions import TimeoutError as RedisTimeoutError - from litellm.caching.redis_cache import RedisCircuitBreaker, _is_redis_timeout_failure + from litellm.caching.redis_cache import RedisCircuitBreaker, is_redis_timeout_failure breaker = RedisCircuitBreaker(failure_threshold=3, recovery_timeout=60, timeout_min_duration=0.05) - breaker.record_failure(is_timeout=_is_redis_timeout_failure(RedisTimeoutError("read timed out"))) - breaker.record_failure(is_timeout=_is_redis_timeout_failure(RedisConnectionError("refused"))) + breaker.record_failure(is_timeout=is_redis_timeout_failure(RedisTimeoutError("read timed out"))) + breaker.record_failure(is_timeout=is_redis_timeout_failure(RedisConnectionError("refused"))) await asyncio.sleep(0.06) for _ in range(breaker.failure_threshold): - breaker.record_failure(is_timeout=_is_redis_timeout_failure(RedisTimeoutError("read timed out"))) + breaker.record_failure(is_timeout=is_redis_timeout_failure(RedisTimeoutError("read timed out"))) assert breaker.is_open() is False, "the burst is instantaneous, so the duration gate must hold it closed" await asyncio.sleep(0.06) - breaker.record_failure(is_timeout=_is_redis_timeout_failure(RedisTimeoutError("read timed out"))) + breaker.record_failure(is_timeout=is_redis_timeout_failure(RedisTimeoutError("read timed out"))) assert breaker.is_open() is True, "the same run of timeouts persisting past the duration must open it" @@ -1023,7 +1023,7 @@ async def test_breaker_metrics_track_state_and_failure_class(): from redis.exceptions import ConnectionError as RedisConnectionError from redis.exceptions import TimeoutError as RedisTimeoutError - from litellm.caching.redis_cache import RedisCircuitBreaker, _is_redis_timeout_failure + from litellm.caching.redis_cache import RedisCircuitBreaker, is_redis_timeout_failure def sample(name, labels=None): return REGISTRY.get_sample_value(name, labels) or 0.0 @@ -1035,9 +1035,9 @@ async def test_breaker_metrics_track_state_and_failure_class(): closed_gauge_before = sample("litellm_redis_circuit_breaker_state", {"state": "closed"}) breaker = RedisCircuitBreaker(failure_threshold=2, recovery_timeout=60, timeout_min_duration=5.0) - breaker.record_failure(is_timeout=_is_redis_timeout_failure(RedisTimeoutError("t"))) - breaker.record_failure(is_timeout=_is_redis_timeout_failure(RedisConnectionError("refused"))) - breaker.record_failure(is_timeout=_is_redis_timeout_failure(RedisConnectionError("refused"))) + breaker.record_failure(is_timeout=is_redis_timeout_failure(RedisTimeoutError("t"))) + breaker.record_failure(is_timeout=is_redis_timeout_failure(RedisConnectionError("refused"))) + breaker.record_failure(is_timeout=is_redis_timeout_failure(RedisConnectionError("refused"))) assert sample("litellm_redis_circuit_breaker_failures_total", {"failure_class": "timeout"}) == timeout_before + 1 assert sample("litellm_redis_circuit_breaker_failures_total", {"failure_class": "connectivity"}) == hard_before + 2 @@ -1205,6 +1205,177 @@ async def test_a_probe_overtaken_by_a_later_outage_leaves_the_breaker_to_the_new assert breaker._state == breaker.CLOSED +def test_timeouts_during_a_blip_log_once_per_interval_not_once_per_call(sync_batch_redis_cache, caplog, monkeypatch): + """A timeout streak logs its first failure plus one summary per interval; other failures log per call.""" + import logging + + from redis.exceptions import TimeoutError as RedisTimeoutError + + from litellm.caching import redis_cache as redis_cache_module + from litellm.caching.redis_cache import _RedisTimeoutLogThrottle + + clock = MagicMock(return_value=1_000.0) + monkeypatch.setattr( + redis_cache_module, "_redis_timeout_log_throttle", _RedisTimeoutLogThrottle(interval=5.0, clock=clock) + ) + sync_batch_redis_cache.redis_client.get.side_effect = RedisTimeoutError("Timeout reading from 127.0.0.1:6379") + sync_batch_redis_cache.redis_client.mget.side_effect = RedisTimeoutError("Timeout reading from 127.0.0.1:6379") + + with caplog.at_level(logging.DEBUG, logger="LiteLLM"): + for _ in range(200): + assert sync_batch_redis_cache.get_cache("lit7520") is None + assert sync_batch_redis_cache.batch_get_cache(key_list=["lit7520"]) == {} + + timeout_records = [r for r in caplog.records if "Timeout reading from" in r.getMessage()] + assert len(timeout_records) == 201, "every timeout must stay visible at DEBUG" + assert [r.getMessage() for r in timeout_records if r.levelno >= logging.WARNING] == [ + "litellm.caching.caching: get() - Got exception from REDIS: Timeout reading from 127.0.0.1:6379" + ] + assert timeout_records[0].levelno == logging.ERROR + assert timeout_records[0].filename == "redis_cache.py" + assert timeout_records[0].lineno != timeout_records[-1].lineno, "the record must point at the cache operation" + + caplog.clear() + clock.return_value += 5.0 + with caplog.at_level(logging.DEBUG, logger="LiteLLM"): + assert sync_batch_redis_cache.batch_get_cache(key_list=["lit7520"]) == {} + assert [(r.levelno, r.getMessage()) for r in caplog.records] == [ + ( + logging.ERROR, + "Error occurred in batch get cache: Timeout reading from 127.0.0.1:6379" + " (200 more Redis timeouts since the previous Redis timeout line were logged at DEBUG)", + ) + ] + + caplog.clear() + sync_batch_redis_cache.redis_client.get.side_effect = OSError("redis unavailable") + with caplog.at_level(logging.DEBUG, logger="LiteLLM"): + for _ in range(3): + assert sync_batch_redis_cache.get_cache("lit7520") is None + assert [r.levelno for r in caplog.records if "redis unavailable" in r.getMessage()] == [logging.ERROR] * 3 + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "call_method", + [ + pytest.param(lambda c: c.async_set_cache_pipeline([("lit7520", "v")]), id="async_set_cache_pipeline"), + pytest.param( + lambda c: c.async_set_cache_pipeline_with_ttls([("lit7520", "v", 60.0)]), + id="async_set_cache_pipeline_with_ttls", + ), + pytest.param(lambda c: c.async_set_cache_sadd("lit7520", ["v"], ttl=None), id="async_set_cache_sadd"), + pytest.param(lambda c: c.async_increment("lit7520", 1.0), id="async_increment"), + pytest.param( + lambda c: c.async_increment_pipeline([{"key": "lit7520", "increment_value": 1.0, "ttl": 60}]), + id="async_increment_pipeline", + ), + pytest.param(lambda c: c.async_rpush("lit7520", ["v"]), id="async_rpush"), + pytest.param( + lambda c: c.async_rpush_pipeline([{"key": "lit7520", "values": ["v"]}]), id="async_rpush_pipeline" + ), + pytest.param(lambda c: c.async_lpop("lit7520"), id="async_lpop"), + pytest.param(lambda c: c.async_lpop_pipeline([{"key": "lit7520", "count": 1}]), id="async_lpop_pipeline"), + ], +) +async def test_write_path_timeouts_inside_the_interval_stay_at_debug(call_method, caplog, monkeypatch, redis_no_ping): + """A write or list operation timing out mid-streak is counted by the throttle instead of logging its own ERROR.""" + import contextlib + import logging + + from redis.exceptions import TimeoutError as RedisTimeoutError + + from litellm.caching import redis_cache as redis_cache_module + from litellm.caching.redis_cache import _RedisTimeoutLogThrottle + + clock = MagicMock(return_value=1_000.0) + throttle = _RedisTimeoutLogThrottle(interval=5.0, clock=clock) + assert throttle.admit() == 0 + monkeypatch.setattr(redis_cache_module, "_redis_timeout_log_throttle", throttle) + + timeout = RedisTimeoutError("Timeout reading from 127.0.0.1:6379") + client = MagicMock() + client.pipeline.return_value.__aenter__.side_effect = timeout + client.sadd = AsyncMock(side_effect=timeout) + client.incrbyfloat = AsyncMock(side_effect=timeout) + client.rpush = AsyncMock(side_effect=timeout) + client.lpop = AsyncMock(side_effect=timeout) + monkeypatch.setenv("REDIS_HOST", "https://my-test-host") + cache = RedisCache() + + with ( + patch.object(cache, "init_async_client", return_value=client), + caplog.at_level(logging.DEBUG, logger="LiteLLM"), + ): + with contextlib.suppress(RedisTimeoutError): + await call_method(cache) + + timeout_records = [r for r in caplog.records if "Timeout reading from" in r.getMessage()] + assert [(r.levelno, r.filename) for r in timeout_records] == [(logging.DEBUG, "redis_cache.py")] + clock.return_value += 5.0 + assert throttle.admit() == 1 + + +@pytest.mark.asyncio +async def test_pool_wait_timeout_is_a_timeout_failure_not_hard_connectivity(): + """A saturated blocking pool must not open the breaker before the timeout minimum duration. + + redis-py's async BlockingConnectionPool gives up waiting for a free connection by raising + ConnectionError("No connection available.") chained from asyncio.TimeoutError. Redis itself + is healthy in that case, so the failure has to be classed as a timeout and stay behind the + duration gate instead of being counted as a hard connectivity failure. + """ + from fakeredis import FakeServer + from fakeredis.aioredis import FakeConnection + from redis.asyncio import BlockingConnectionPool, Redis + from redis.exceptions import ConnectionError as RedisConnectionError + + from litellm.caching.redis_cache import RedisCircuitBreaker, _run_under_circuit_breaker + + pool = BlockingConnectionPool(connection_class=FakeConnection, server=FakeServer(), max_connections=1, timeout=0.01) + client = Redis(connection_pool=pool) + breaker = RedisCircuitBreaker(failure_threshold=3, recovery_timeout=60, timeout_min_duration=5.0) + + busy_connection = await pool.get_connection() + try: + for _ in range(breaker.failure_threshold * 2): + with pytest.raises(RedisConnectionError, match="No connection available"): + await _run_under_circuit_breaker(breaker, "op", lambda: client.get("k")) + finally: + await pool.release(busy_connection) + + assert breaker.is_open() is False, "a busy pool is a timeout gated on duration, not a dead Redis" + assert await _run_under_circuit_breaker(breaker, "op", lambda: client.get("k")) is None + await client.aclose() + + +def test_timeout_classification_follows_the_explicit_cause_chain_only(): + from redis.exceptions import ConnectionError as RedisConnectionError + + from litellm.caching.redis_cache import is_redis_timeout_failure + + def raise_chained_from_timeout() -> None: + try: + raise asyncio.TimeoutError() + except asyncio.TimeoutError as err: + raise RedisConnectionError("No connection available.") from err + + def raise_while_handling_timeout() -> None: + try: + raise asyncio.TimeoutError() + except asyncio.TimeoutError: + raise RedisConnectionError("refused") + + with pytest.raises(RedisConnectionError) as chained: + raise_chained_from_timeout() + with pytest.raises(RedisConnectionError) as contextual: + raise_while_handling_timeout() + + assert is_redis_timeout_failure(chained.value) is True + assert is_redis_timeout_failure(contextual.value) is False + assert is_redis_timeout_failure(RedisConnectionError("refused")) is False + + class _RoundTripCountingRedis: """Fake redis.asyncio client: one round trip per awaited command or pipeline execute.""" diff --git a/tests/test_litellm/caching/test_redis_semantic_cache.py b/tests/test_litellm/caching/test_redis_semantic_cache.py index df990c43530..9884e9d9bc0 100644 --- a/tests/test_litellm/caching/test_redis_semantic_cache.py +++ b/tests/test_litellm/caching/test_redis_semantic_cache.py @@ -1,3 +1,5 @@ +from collections.abc import Iterator +from contextlib import contextmanager from importlib import import_module import sys from unittest.mock import AsyncMock, MagicMock, patch @@ -5,18 +7,19 @@ from unittest.mock import AsyncMock, MagicMock, patch import pytest +@contextmanager +def _fake_redisvl_modules(semantic_cache_mock: MagicMock, custom_vectorizer_mock: MagicMock) -> Iterator[None]: + with pytest.MonkeyPatch.context() as mp: + mp.setitem(sys.modules, "redisvl.extensions.llmcache", MagicMock(SemanticCache=semantic_cache_mock)) + mp.setitem(sys.modules, "redisvl.utils.vectorize", MagicMock(CustomTextVectorizer=custom_vectorizer_mock)) + yield + # Tests for RedisSemanticCache def test_redis_semantic_cache_initialization(monkeypatch): # Mock the redisvl import semantic_cache_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock(CustomTextVectorizer=MagicMock()), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, MagicMock()): from litellm.caching.redis_semantic_cache import RedisSemanticCache # Set environment variables @@ -44,15 +47,7 @@ def test_redis_semantic_cache_get_cache(monkeypatch): semantic_cache_mock = MagicMock() custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache # Set environment variables @@ -110,15 +105,7 @@ def test_redis_semantic_cache_rejects_unscoped_cache_hit(monkeypatch): semantic_cache_mock = MagicMock() custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache monkeypatch.setenv("REDIS_HOST", "localhost") @@ -162,15 +149,7 @@ def test_redis_semantic_cache_set_cache_stores_cache_key_filter(monkeypatch): semantic_cache_mock = MagicMock() custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache monkeypatch.setenv("REDIS_HOST", "localhost") @@ -210,15 +189,7 @@ def test_redis_semantic_cache_uses_isolated_index_for_old_schema(monkeypatch): ) custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache monkeypatch.setenv("REDIS_HOST", "localhost") @@ -252,15 +223,7 @@ def test_redis_semantic_cache_overwrites_stale_isolated_index(monkeypatch): ) custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache monkeypatch.setenv("REDIS_HOST", "localhost") @@ -292,15 +255,7 @@ def test_redis_semantic_cache_reraises_unexpected_isolated_index_error(monkeypat ) custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache monkeypatch.setenv("REDIS_HOST", "localhost") @@ -369,15 +324,15 @@ def test_redis_semantic_cache_builds_filter_expression(monkeypatch): def __eq__(self, value): return (self.field_name, value) - with patch.dict("sys.modules", {"redisvl.query.filter": MagicMock(Tag=FakeTag)}): - from litellm.caching.redis_semantic_cache import RedisSemanticCache + monkeypatch.setitem(sys.modules, "redisvl.query.filter", MagicMock(Tag=FakeTag)) + from litellm.caching.redis_semantic_cache import RedisSemanticCache - redis_semantic_cache = RedisSemanticCache.__new__(RedisSemanticCache) + redis_semantic_cache = RedisSemanticCache.__new__(RedisSemanticCache) - assert redis_semantic_cache._get_cache_key_filter_expression("test_key") == ( - RedisSemanticCache.CACHE_KEY_FIELD_NAME, - "test_key", - ) + assert redis_semantic_cache._get_cache_key_filter_expression("test_key") == ( + RedisSemanticCache.CACHE_KEY_FIELD_NAME, + "test_key", + ) @pytest.mark.asyncio @@ -386,15 +341,7 @@ async def test_redis_semantic_cache_async_get_cache(monkeypatch): semantic_cache_mock = MagicMock() custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache # Set environment variables @@ -449,15 +396,7 @@ async def test_redis_semantic_cache_async_get_cache_rejects_unscoped_hit(monkeyp semantic_cache_mock = MagicMock() custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache monkeypatch.setenv("REDIS_HOST", "localhost") @@ -499,15 +438,7 @@ async def test_redis_semantic_cache_async_set_cache_stores_cache_key_filter( semantic_cache_mock = MagicMock() custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache monkeypatch.setenv("REDIS_HOST", "localhost") @@ -1255,15 +1186,7 @@ def test_redis_init_defers_redisvl_construction(monkeypatch): semantic_cache_mock = MagicMock() custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache monkeypatch.setenv("REDIS_HOST", "localhost") @@ -1291,15 +1214,7 @@ def test_redis_failed_llmcache_build_is_not_memoized(monkeypatch): ) custom_vectorizer_mock = MagicMock() - with patch.dict( - "sys.modules", - { - "redisvl.extensions.llmcache": MagicMock(SemanticCache=semantic_cache_mock), - "redisvl.utils.vectorize": MagicMock( - CustomTextVectorizer=custom_vectorizer_mock - ), - }, - ): + with _fake_redisvl_modules(semantic_cache_mock, custom_vectorizer_mock): from litellm.caching.redis_semantic_cache import RedisSemanticCache monkeypatch.setenv("REDIS_HOST", "localhost") diff --git a/tests/test_litellm/compression/test_compress.py b/tests/test_litellm/compression/test_compress.py index 6827c37dfd5..6e908bcbdcd 100644 --- a/tests/test_litellm/compression/test_compress.py +++ b/tests/test_litellm/compression/test_compress.py @@ -6,7 +6,8 @@ never rewrite. It is consumed by compress() and by the Headroom guardrail, so the two agree on what "never compress this" means. """ -from litellm.compression.compress import get_protected_indices +from litellm.compression.compress import compress, get_protected_indices +from litellm.types.utils import CallTypes def test_protects_system_last_user_and_last_assistant(): @@ -53,3 +54,94 @@ def test_every_system_row_is_protected(): def test_no_user_or_assistant_rows(): assert sorted(get_protected_indices([{"role": "system", "content": "sys"}])) == [0] assert get_protected_indices([]) == () + + +def test_mid_history_cache_control_part_is_protected(): + # A large cached tool result from a few turns back, not the last user or + # last assistant row -- exactly the row a provider prompt-cache pins to + # exact bytes. Rewriting it (even leaving the marker on) changes those + # bytes and turns the next request's cache read into a cache write. + messages = [ + {"role": "user", "content": "old question"}, + {"role": "assistant", "content": "old answer"}, + { + "role": "user", + "content": [ + {"type": "text", "text": "a large cached tool result", "cache_control": {"type": "ephemeral"}}, + ], + }, + {"role": "assistant", "content": "ack"}, + {"role": "user", "content": "live instruction"}, + ] + + # index 3 = last assistant, index 4 = last user (both protected by role + # regardless), index 2 = the cache_control-marked row itself. + assert sorted(get_protected_indices(messages)) == [2, 3, 4] + + +def test_cache_control_directly_on_message_is_protected(): + messages = [ + {"role": "user", "content": "old question", "cache_control": {"type": "ephemeral"}}, + {"role": "assistant", "content": "old answer"}, + {"role": "user", "content": "live instruction"}, + ] + + assert sorted(get_protected_indices(messages)) == [0, 1, 2] + + +def test_cache_control_protection_does_not_duplicate_already_protected_rows(): + # The last user row is already protected by role; marking it too must not + # produce a duplicate index. + messages = [ + {"role": "system", "content": "sys"}, + {"role": "user", "content": "live", "cache_control": {"type": "ephemeral"}}, + ] + + protected = get_protected_indices(messages) + + assert sorted(protected) == [0, 1] + assert len(protected) == len(set(protected)) + + +def test_content_that_is_not_a_list_of_mappings_is_not_treated_as_cache_control(): + # Defensive: a plain string content, or a list of non-dict items, must not + # raise or be misread as carrying a breakpoint. + messages = [ + {"role": "assistant", "content": "plain string content"}, + {"role": "user", "content": ["not", "a", "dict", "list"]}, + {"role": "user", "content": "live instruction"}, + ] + + assert sorted(get_protected_indices(messages)) == [0, 2] + + +def test_compress_keeps_part_level_cache_control_row_verbatim(): + # compress() scores text-only copies of the rows, where a part-level marker + # is gone; protection has to read the original rows or the pinned row is stubbed. + stale_log = {"role": "user", "content": [{"type": "text", "text": "stale log line " * 2000}]} + pinned = { + "role": "user", + "content": [ + {"type": "text", "text": "cached tool result " * 2000, "cache_control": {"type": "ephemeral"}}, + ], + } + messages = [ + stale_log, + {"role": "assistant", "content": "old answer"}, + pinned, + {"role": "assistant", "content": "ack"}, + {"role": "user", "content": "live instruction"}, + ] + + result = compress( + messages, + model="gpt-4o", + call_type=CallTypes.anthropic_messages, + compression_trigger=1000, + compression_target=500, + ) + + assert len(result["messages"]) == len(messages) + assert result["messages"][2] == pinned + assert result["messages"][0] != stale_log + assert len(result["cache"]) >= 1 diff --git a/tests/test_litellm/enterprise/proxy/test_managed_files_hook.py b/tests/test_litellm/enterprise/proxy/test_managed_files_hook.py index 48fceb50403..cb08e00ff65 100644 --- a/tests/test_litellm/enterprise/proxy/test_managed_files_hook.py +++ b/tests/test_litellm/enterprise/proxy/test_managed_files_hook.py @@ -1193,7 +1193,7 @@ async def test_afile_delete_returns_managed_id_for_stored_provider_output(): assert response.id == unified_file_id assert response.object == "file" - assert response.filename == stored_file.filename + assert response.deleted is True assert stored_file.id == provider_file_id router.afile_delete.assert_awaited_once_with(model="model-123", file_id=provider_file_id) table.delete.assert_awaited_once_with(where={"unified_file_id": unified_file_id}) @@ -1730,3 +1730,100 @@ async def test_batch_retrieve_hook_does_not_claim_attribution(): managed_files.store_unified_object_id.assert_awaited_once() assert managed_files.store_unified_object_id.await_args.kwargs["persist_attribution"] is False + + +@pytest.mark.asyncio +async def test_afile_delete_passes_trusted_model_credentials_to_router(): + """ + afile_delete must hand the deployment's credential snapshot to the router + call, since Bedrock validates the s3:// file id against the bucket in it. + """ + from types import MappingProxyType + + managed_files = _make_managed_files_instance() + unified_file_id = "unified-file-id" + s3_uri = "s3://my-bucket/litellm-bedrock-files/job-123/input.jsonl" + managed_files.get_model_file_id_mapping = AsyncMock(return_value={unified_file_id: {"model-123": s3_uri}}) + managed_files.delete_unified_file_id = AsyncMock(return_value=_make_file_object(unified_file_id)) + + mock_router = MagicMock() + mock_router.get_deployment_credentials_with_provider = MagicMock( + return_value={ + "custom_llm_provider": "bedrock", + "s3_bucket_name": "my-bucket", + "aws_region_name": "us-west-2", + } + ) + mock_router.afile_delete = AsyncMock(return_value=MagicMock()) + + await managed_files.afile_delete( + file_id=unified_file_id, + litellm_parent_otel_span=None, + llm_router=mock_router, + ) + + call_kwargs = mock_router.afile_delete.call_args.kwargs + assert call_kwargs["model"] == "model-123" + assert call_kwargs["file_id"] == s3_uri + trusted_credentials = call_kwargs["_litellm_internal_model_credentials"] + assert isinstance(trusted_credentials, MappingProxyType) + assert trusted_credentials["s3_bucket_name"] == "my-bucket" + + +@pytest.mark.asyncio +async def test_afile_delete_bedrock_unified_id_end_to_end(monkeypatch): + """ + Proxy repro for deleting a Bedrock batch input file by unified id: the + s3:// object must be removed via a SigV4-signed S3 DELETE using the + deployment's s3_bucket_name (no AWS_S3_BUCKET_NAME env). + + Regression test for "BedrockFilesConfig does not support file deletion" + raised on this path. + """ + import httpx + import respx + + import litellm + from litellm import Router + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + litellm.in_memory_llm_clients_cache.flush_cache() + + router = Router( + model_list=[ + { + "model_name": "bedrock-claude", + "litellm_params": { + "model": "bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0", + "aws_access_key_id": "AKIAEXAMPLE", + "aws_secret_access_key": "secret", + "aws_region_name": "us-west-2", + "s3_bucket_name": "my-bucket", + }, + "model_info": {"id": "model-123"}, + } + ] + ) + + managed_files = _make_managed_files_instance() + unified_file_id = "unified-file-id" + s3_uri = "s3://my-bucket/litellm-bedrock-files/job-123/input.jsonl" + managed_files.get_model_file_id_mapping = AsyncMock(return_value={unified_file_id: {"model-123": s3_uri}}) + managed_files.delete_unified_file_id = AsyncMock(return_value=_make_file_object(unified_file_id)) + + expected_url = "https://s3.us-west-2.amazonaws.com/my-bucket/litellm-bedrock-files/job-123/input.jsonl" + with respx.mock: + route = respx.delete(expected_url).mock(return_value=httpx.Response(204)) + + response = await managed_files.afile_delete( + file_id=unified_file_id, + litellm_parent_otel_span=None, + llm_router=router, + ) + + assert route.called + assert route.calls[0].request.headers["Authorization"].startswith("AWS4-HMAC-SHA256") + assert response.id == unified_file_id + assert response.model_dump() == {"id": unified_file_id, "object": "file", "deleted": True} + managed_files.delete_unified_file_id.assert_awaited_once_with(unified_file_id, None) diff --git a/tests/test_litellm/integrations/gcs_bucket/test_gcs_bucket_base.py b/tests/test_litellm/integrations/gcs_bucket/test_gcs_bucket_base.py index 8d662311da1..a458752bed0 100644 --- a/tests/test_litellm/integrations/gcs_bucket/test_gcs_bucket_base.py +++ b/tests/test_litellm/integrations/gcs_bucket/test_gcs_bucket_base.py @@ -128,3 +128,20 @@ class TestGCSBucketBase: assert object_name.endswith("-target_uploadType_media") assert ".." not in object_name assert "?" not in object_name + + +class TestGCSBucketLoggerBucketName: + @pytest.mark.asyncio + async def test_the_bucket_name_it_is_constructed_with_survives(self, monkeypatch): + """Reading config.yaml out of a GCS bucket asks for that bucket, not the logging one (LIT-6982).""" + monkeypatch.setenv("GCS_BUCKET_NAME", "logging-bucket") + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + + assert GCSBucketLogger(bucket_name="config-bucket").BUCKET_NAME == "config-bucket" + + @pytest.mark.asyncio + async def test_no_bucket_name_still_falls_back_to_the_environment(self, monkeypatch): + monkeypatch.setenv("GCS_BUCKET_NAME", "logging-bucket") + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + + assert GCSBucketLogger().BUCKET_NAME == "logging-bucket" diff --git a/tests/test_litellm/integrations/otel/test_otel_v2_emitter.py b/tests/test_litellm/integrations/otel/test_otel_v2_emitter.py index b1b1b62c820..6e2e467b856 100644 --- a/tests/test_litellm/integrations/otel/test_otel_v2_emitter.py +++ b/tests/test_litellm/integrations/otel/test_otel_v2_emitter.py @@ -1,6 +1,8 @@ """Golden tests for the OTel v2 engine: span shape, kinds, semconv attributes, legacy dual-emit, hierarchy, error status, and idempotency. Needs the OTel SDK.""" +import json + import pytest pytest.importorskip("opentelemetry") @@ -18,6 +20,7 @@ from litellm.integrations.otel.plumbing import providers # noqa: E402 from litellm.integrations.otel.emitter import SpanEmitter # noqa: E402 from litellm.integrations.otel.emitter import stamp_error # noqa: E402 from litellm.integrations.otel.mappers.utils import ( # noqa: E402 + MAX_MESSAGE_ATTRS_PER_SPAN, MAX_TOOL_DEFINITION_ATTRS_PER_SPAN, ) from litellm.integrations.otel.model.payloads import ( # noqa: E402 @@ -440,3 +443,161 @@ def test_vendor_tool_definitions_are_truncated_not_dropped(): assert a["llm.tools.0.tool.name"] == "tool_0" assert a["llm.tools.0.tool.json_schema"] assert "llm.tools.126.tool.name" not in a + + +def _conversation_payload(turns, choices=1, **overrides): + """A ``turns``-message chat with ``choices`` response choices, content-bearing.""" + return _payload( + messages=[{"role": ("user", "assistant")[i % 2], "content": f"turn {i}"} for i in range(turns)], + response={ + "id": "resp_1", + "model": "gpt-4o-2024", + "choices": [ + {"finish_reason": "stop", "message": {"role": "assistant", "content": f"reply {i}"}} + for i in range(choices) + ], + }, + **overrides, + ) + + +def _conversation_span(mapper_names, payload, legacy_compat=False): + """The exported LLM-call span for ``payload`` with content capture on.""" + cfg = OpenTelemetryV2Config( + exporter="in_memory", + legacy_compat=legacy_compat, + mapper_names=list(mapper_names), + capture_message_content="span_only", + ) + provider, exporter = providers.in_memory_provider(cfg) + engine = SpanEmitter(providers.get_tracer(provider, "litellm-test"), cfg) + engine.emit( + SpanRole.LLM_CALL, + LLMCallSpanData.from_standard_logging_payload(payload, capture_content=True), + ) + (span,) = exporter.get_finished_spans() + return span + + +def _indexed_message_count(attributes, prefix): + return len({key.split(".")[2] for key in attributes if key.startswith(f"{prefix}.")}) + + +@pytest.mark.parametrize("turns", [60, 200]) +def test_long_conversation_does_not_evict_core_attributes(turns): + """Per-message OpenInference attributes must never crowd core telemetry off the span.""" + span = _conversation_span(["genai", "openinference"], _conversation_payload(turns)) + a = span.attributes + + assert span.dropped_attributes == 0 + assert a[GenAI.REQUEST_MODEL] == "gpt-4o" + assert a[GenAI.PROVIDER_NAME] == "openai" + assert a[GenAI.USAGE_INPUT_TOKENS] == 10 + assert a[GenAI.USAGE_OUTPUT_TOKENS] == 5 + assert a[GenAI.RESPONSE_FINISH_REASONS] == ("stop",) + assert a[f"{LiteLLM.COST_PREFIX}total"] == 0.002 + + assert a["llm.input_messages.0.message.content"] == "turn 0" + assert a["llm.output_messages.0.message.content"] == "reply 0" + assert a[f"llm.input_messages.{turns - 1}.message.content"] == f"turn {turns - 1}" + assert f"llm.input_messages.{turns // 2}.message.role" not in a + assert len(json.loads(a["input.value"])) == turns + assert len(json.loads(a["output.value"])) == 1 + assert len(json.loads(a[GenAI.INPUT_MESSAGES])) == turns + + +def test_short_conversation_keeps_every_message_indexed(): + """Below the cap nothing is truncated in either direction.""" + a = _conversation_span(["genai", "openinference"], _conversation_payload(4, choices=2)).attributes + for idx in range(4): + assert a[f"llm.input_messages.{idx}.message.content"] == f"turn {idx}" + for idx in range(2): + assert a[f"llm.output_messages.{idx}.message.content"] == f"reply {idx}" + + +def test_indexed_prompt_keeps_opener_and_latest_turns_under_a_value_length_limit(monkeypatch): + """The system prompt and the live turn keep their own keys once the SDK clips ``input.value``.""" + monkeypatch.setenv("OTEL_SPAN_ATTRIBUTE_VALUE_LENGTH_LIMIT", "256") + chat = _conversation_payload(60) + payload = { + **chat, + "messages": [ + {"role": "system", "content": "be terse"}, + *chat["messages"][1:-1], + {"role": "user", "content": "LATEST-TURN"}, + ], + } + a = _conversation_span(["genai", "openinference"], payload).attributes + + assert len(a["input.value"]) == 256 + assert a["llm.input_messages.0.message.role"] == "system" + assert a["llm.input_messages.0.message.content"] == "be terse" + assert a["llm.input_messages.59.message.role"] == "user" + assert a["llm.input_messages.59.message.content"] == "LATEST-TURN" + assert a["llm.output_messages.0.message.content"] == "reply 0" + assert [int(key.split(".")[2]) for key in a if key.endswith("message.content") and key.startswith("llm.input_")] == [ + 0, + *range(54, 60), + ] + + +def test_message_cap_is_shared_across_input_and_output(): + """One span-wide allowance covers both directions, and the response always keeps a share.""" + long_prompt = _conversation_span(["genai", "openinference"], _conversation_payload(60, choices=1)).attributes + many_choices = _conversation_span(["genai", "openinference"], _conversation_payload(60, choices=20)).attributes + + single_reply_indexed = _indexed_message_count(long_prompt, "llm.output_messages") + assert single_reply_indexed == 1 + assert _indexed_message_count(long_prompt, "llm.input_messages") + single_reply_indexed == ( + MAX_MESSAGE_ATTRS_PER_SPAN // 2 + ) + + assert _indexed_message_count(many_choices, "llm.input_messages") > 0 + assert _indexed_message_count(many_choices, "llm.output_messages") > single_reply_indexed + assert _indexed_message_count(many_choices, "llm.input_messages") + _indexed_message_count( + many_choices, "llm.output_messages" + ) == (MAX_MESSAGE_ATTRS_PER_SPAN // 2) + + +def test_fully_populated_span_with_every_vocabulary_stays_within_the_attribute_limit(): + """Every capped family maxed at once still leaves the whole core intact.""" + payload = _conversation_payload( + 200, + choices=20, + stream=True, + model_parameters={ + **_tools_payload(127)["model_parameters"], + "top_p": 0.9, + "frequency_penalty": 0.1, + "presence_penalty": 0.1, + "seed": 7, + "stop": ["\n"], + }, + cost_breakdown={ + key: 0.001 + for key in ( + "input_cost", + "output_cost", + "cache_read_cost", + "cache_creation_cost", + "tool_usage_cost", + "original_cost", + "discount_amount", + "discount_percent", + "margin_fixed_amount", + "margin_percent", + "margin_total_amount", + "total_cost", + ) + }, + ) + span = _conversation_span(["genai", "openinference", "langfuse", "weave", "langtrace"], payload, legacy_compat=True) + a = span.attributes + + assert span.dropped_attributes == 0 + assert a[GenAI.REQUEST_MODEL] == "gpt-4o" + assert a[f"{LiteLLM.COST_PREFIX}total"] == 0.002 + assert a[LiteLLM.TOOLS_DECLARED] == 127 + assert a["llm.input_messages.0.message.content"] == "turn 0" + assert a["llm.input_messages.199.message.content"] == "turn 199" + assert a["llm.output_messages.0.message.content"] == "reply 0" diff --git a/tests/test_litellm/integrations/test_custom_guardrail.py b/tests/test_litellm/integrations/test_custom_guardrail.py index 2fd5fa76d8e..bb29bfed283 100644 --- a/tests/test_litellm/integrations/test_custom_guardrail.py +++ b/tests/test_litellm/integrations/test_custom_guardrail.py @@ -2625,7 +2625,7 @@ class TestLoggingOnlyApplyGuardrail: assert [e["guardrail_status"] for e in entries] == ["success"] @pytest.mark.asyncio - async def test_native_lifecycle_hook_guardrail_is_left_alone(self): + async def test_native_lifecycle_hook_guardrail_scans_in_logging_only(self): class _NativeHooks(_ApplyOnlyObserver): use_native_lifecycle_hooks = True @@ -2634,9 +2634,9 @@ class TestLoggingOnlyApplyGuardrail: out_kwargs, out_response = await guardrail.async_logging_hook(kwargs, response, CallTypes.acompletion.value) - assert guardrail.calls == [] - assert out_kwargs is kwargs + assert guardrail.calls == [("request", ["hello there"]), ("response", ["general kenobi"])] assert out_response is response + assert out_kwargs["standard_logging_object"]["guardrail_information"] @pytest.mark.asyncio async def test_aresponses_scans_logged_messages_when_input_is_cleared(self): @@ -2890,6 +2890,61 @@ class TestCustomGuardrailPostCallSuccessDeploymentHook: assert len(_guardrail_entries(request_data)) == 1 +class _NativeLifecycleLoggingGuardrail(CustomGuardrail): + """Native lifecycle guardrail that also implements apply_guardrail, like the azure guards.""" + + use_native_lifecycle_hooks: ClassVar[bool] = True + + def __init__(self): + from litellm.types.guardrails import GuardrailEventHooks + + super().__init__( + guardrail_name="native-logging-guardrail", + event_hook=GuardrailEventHooks.logging_only, + ) + self.calls: list[tuple[Literal["request", "response"], list[str]]] = [] + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict[str, object], + input_type: Literal["request", "response"], + logging_obj: "LiteLLMLoggingObj | None" = None, + ) -> GenericGuardrailAPIInputs: + self.calls.append((input_type, list(inputs.get("texts") or []))) + return inputs + + +@pytest.mark.asyncio +async def test_native_lifecycle_guardrail_logging_only_scans_assembled_response(): + """A use_native_lifecycle_hooks guardrail accepts mode logging_only and its + async_logging_hook scans kwargs["async_complete_streaming_response"], not the raw result.""" + from litellm.types.utils import Choices, Message, ModelResponse + + guardrail = _NativeLifecycleLoggingGuardrail() + assembled = ModelResponse( + choices=[Choices(message=Message(role="assistant", content="assembled stream text"))] + ) + sentinel_result = object() + kwargs = { + "model": "gpt-5.4-mini", + "messages": [{"role": "user", "content": "hi"}], + "litellm_call_id": "call-1", + "litellm_params": {"metadata": {}}, + "optional_params": {}, + "standard_logging_object": {"guardrail_information": None}, + "async_complete_streaming_response": assembled, + } + + out_kwargs, out_result = await guardrail.async_logging_hook( + kwargs=kwargs, result=sentinel_result, call_type=CallTypes.acompletion.value + ) + + assert out_result is sentinel_result + assert ("response", ["assembled stream text"]) in guardrail.calls + assert out_kwargs["standard_logging_object"]["guardrail_information"] + + class TestPreCallHookResponseIsNotLoggedVerbatim: """Regression for LIT-6935: a pre_call hook returning the request payload leaked the prompt into ``guardrail_response`` and from there onto OTEL guardrail spans.""" diff --git a/tests/test_litellm/integrations/test_langsmith_init.py b/tests/test_litellm/integrations/test_langsmith_init.py index 025aa86466c..0bc9e279fbf 100644 --- a/tests/test_litellm/integrations/test_langsmith_init.py +++ b/tests/test_litellm/integrations/test_langsmith_init.py @@ -1,5 +1,6 @@ +import asyncio import os -from unittest.mock import MagicMock, patch +from unittest.mock import AsyncMock, MagicMock, patch import pytest @@ -154,24 +155,22 @@ class TestLangsmithLoggerInit: assert logger._start_periodic_flush_task() is None mock_get_running_loop.assert_called_once() - @patch("asyncio.get_running_loop") - def test_langsmith_init_starts_periodic_flush_with_running_loop( - self, mock_get_running_loop - ): + @pytest.mark.asyncio + async def test_langsmith_init_starts_periodic_flush_with_running_loop(self): """Test that init schedules periodic flush when a running loop exists.""" - mock_loop = MagicMock() - mock_task = MagicMock() - mock_loop.create_task.return_value = mock_task - mock_get_running_loop.return_value = mock_loop - logger = LangsmithLogger( - langsmith_api_key="test-key", langsmith_project="test-project" + langsmith_api_key="test-key", langsmith_project="test-project", flush_interval=0.01 ) + batch_sent = asyncio.Event() + logger.async_send_batch = AsyncMock(side_effect=batch_sent.set) + logger.log_queue.append({"id": "run-id"}) - assert logger._flush_task == mock_task - mock_loop.create_task.assert_called_once() - scheduled_coro = mock_loop.create_task.call_args.args[0] - scheduled_coro.close() + flush_task = logger._flush_task + assert isinstance(flush_task, asyncio.Task) + await asyncio.wait_for(batch_sent.wait(), timeout=5) + flush_task.cancel() + with pytest.raises(asyncio.CancelledError): + await flush_task @pytest.mark.asyncio async def test_async_log_success_event_lazily_starts_periodic_flush(self): diff --git a/tests/test_litellm/integrations/test_prometheus_labels.py b/tests/test_litellm/integrations/test_prometheus_labels.py index 859cdd30c11..200f8e65add 100644 --- a/tests/test_litellm/integrations/test_prometheus_labels.py +++ b/tests/test_litellm/integrations/test_prometheus_labels.py @@ -716,6 +716,77 @@ async def test_failure_hook_emits_api_provider_value_on_failed_requests_metric() _clear_prometheus_registry() +async def _failed_requests_api_provider_labels( + request_data: dict[str, object], + original_exception: Exception, +) -> list[str]: + from litellm.integrations.prometheus import PrometheusLogger + from litellm.proxy._types import UserAPIKeyAuth + + _clear_prometheus_registry() + try: + await PrometheusLogger().async_post_call_failure_hook( + request_data=request_data, + original_exception=original_exception, + user_api_key_dict=UserAPIKeyAuth(token="tok"), + ) + return [ + s.labels.get("api_provider") + for s in _collected_samples("litellm_proxy_failed_requests_metric_total") + ] + finally: + _clear_prometheus_registry() + + +@pytest.mark.asyncio +async def test_failure_hook_emits_api_provider_from_pre_call_rate_limit_error_for_router_alias(): + """ + Pre-call limiters reject before a deployment lands on request_data and a + router alias cannot be inferred from its name, so the provider the limiter + resolved onto the exception is the only source for the label. + """ + from litellm.exceptions import RateLimitType + from litellm.proxy.common_utils.proxy_rate_limit_error import ProxyRateLimitError + + err = ProxyRateLimitError( + detail={"error": "rpm exceeded"}, + rate_limit_type=RateLimitType.REQUESTS, + model="openai/gpt-5.4-mini", + llm_provider="openai", + ) + + assert await _failed_requests_api_provider_labels( + {"model": "team-chat-model", "metadata": {}}, err + ) == ["openai"] + + +@pytest.mark.asyncio +async def test_failure_hook_leaves_api_provider_unset_when_rate_limiter_could_not_resolve_provider(): + from litellm.proxy.common_utils.proxy_rate_limit_error import ProxyRateLimitError + + err = ProxyRateLimitError(detail={"error": "rpm exceeded"}, model="unknown-alias") + + assert await _failed_requests_api_provider_labels( + {"model": "unknown-alias", "metadata": {}}, err + ) == ["None"] + + +@pytest.mark.asyncio +async def test_failure_hook_prefers_request_data_provider_over_exception_provider(): + from litellm.exceptions import RateLimitError + + err = RateLimitError(message="upstream 429", llm_provider="openai", model="gpt-4o") + + assert await _failed_requests_api_provider_labels( + { + "model": "gpt-4o", + "metadata": {}, + "litellm_params": {"custom_llm_provider": "azure"}, + }, + err, + ) == ["azure"] + + if __name__ == "__main__": test_user_email_in_required_metrics() test_user_email_label_exists() diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py index cbe6fe198c9..30b158e3b2c 100644 --- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py +++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py @@ -2,6 +2,7 @@ import json from datetime import datetime, timezone import pytest +from collections.abc import Mapping from fastapi.testclient import TestClient import litellm @@ -74,6 +75,108 @@ def test_missing_cache_read_policy_preserves_billing(prompt_tokens, read_rate, s assert prompt_cost == pytest.approx((prompt_tokens - 100) * billed[0] + 100 * billed[4]) +def test_generic_cost_per_token_prefers_audio_per_second_rate() -> None: + model_info: ModelInfo = { + "key": "gemini-embedding-2", + "max_tokens": None, + "max_input_tokens": None, + "max_output_tokens": None, + "input_cost_per_token": 2e-7, + "input_cost_per_audio_token": 6.5e-6, + "input_cost_per_audio_per_second": 0.00016, + "output_cost_per_token": 0.0, + "litellm_provider": "vertex_ai", + "mode": "embedding", + "supported_openai_params": None, + } + usage = Usage( + prompt_tokens=64, + completion_tokens=0, + total_tokens=64, + prompt_tokens_details=PromptTokensDetailsWrapper( + audio_tokens=64, + audio_length_seconds=2, + ), + ) + + prompt_cost, _ = generic_cost_per_token( + model="gemini-embedding-2", + usage=usage, + custom_llm_provider="vertex_ai", + model_info=model_info, + ) + + assert prompt_cost == pytest.approx(2 * 0.00016) + + +def test_generic_cost_per_token_prefers_image_per_image_rate() -> None: + model_info: ModelInfo = { + "key": "gemini-embedding-2", + "max_tokens": None, + "max_input_tokens": None, + "max_output_tokens": None, + "input_cost_per_token": 2e-7, + "input_cost_per_image_token": 4.5e-7, + "input_cost_per_image": 0.00012, + "output_cost_per_token": 0.0, + "litellm_provider": "vertex_ai", + "mode": "embedding", + "supported_openai_params": None, + } + usage = Usage( + prompt_tokens=258, + completion_tokens=0, + total_tokens=258, + prompt_tokens_details=PromptTokensDetailsWrapper( + image_tokens=258, + image_count=1, + ), + ) + + prompt_cost, _ = generic_cost_per_token( + model="gemini-embedding-2", + usage=usage, + custom_llm_provider="vertex_ai", + model_info=model_info, + ) + + assert prompt_cost == pytest.approx(0.00012) + + +def test_generic_cost_per_token_prefers_video_per_second_rate() -> None: + model_info: ModelInfo = { + "key": "gemini-embedding-2", + "max_tokens": None, + "max_input_tokens": None, + "max_output_tokens": None, + "input_cost_per_token": 2e-7, + "input_cost_per_video_token": 1.2e-5, + "input_cost_per_video_per_second": 0.00079, + "output_cost_per_token": 0.0, + "litellm_provider": "vertex_ai", + "mode": "embedding", + "supported_openai_params": None, + } + usage = Usage( + prompt_tokens=516, + completion_tokens=0, + total_tokens=516, + prompt_tokens_details=PromptTokensDetailsWrapper( + video_tokens=516, + video_length_seconds=2, + ), + ) + + prompt_cost, _ = generic_cost_per_token( + model="gemini-embedding-2", + usage=usage, + custom_llm_provider="vertex_ai", + model_info=model_info, + ) + + assert prompt_cost == pytest.approx(2 * 0.00079) + + def test_missing_cache_read_uses_off_peak_input_rate(): from datetime import datetime, timezone @@ -2101,6 +2204,37 @@ def test_generic_cost_per_token_azure_gpt_6_astra_foundry_price_sheet( assert completion_cost == pytest.approx(zone_multiplier * output_multiplier * completion_tokens * 5e-5) +@pytest.mark.parametrize( + "model,input_rate,cache_read_rate,output_rate", + [ + ("azure/gpt-chat-latest", 5e-6, 5e-7, 3e-5), + ("azure/chat-latest", 5e-6, 5e-7, 3e-5), + ("azure/us/gpt-chat-latest", 5.5e-6, 5.5e-7, 3.3e-5), + ], +) +def test_generic_cost_per_token_azure_gpt_chat_latest_price_sheet( + _local_model_cost_map, model, input_rate, cache_read_rate, output_rate +): + """The Azure OpenAI price sheet lists GPT-Chat Latest at $5 input, $0.50 cached input and $30 output per 1M + tokens on Global, and $5.50, $0.55 and $33 on Data Zone. Foundry names the product gpt-chat-latest and the + OpenAI API names the same model chat-latest, so both spellings bill the Global sheet. + """ + prompt_tokens = 100000 + cached_tokens = 40000 + completion_tokens = 1000 + usage = Usage( + prompt_tokens=prompt_tokens, + completion_tokens=completion_tokens, + total_tokens=prompt_tokens + completion_tokens, + prompt_tokens_details=PromptTokensDetailsWrapper(cached_tokens=cached_tokens), + ) + + prompt_cost, completion_cost = generic_cost_per_token(model=model, usage=usage, custom_llm_provider="azure") + + assert prompt_cost == pytest.approx((prompt_tokens - cached_tokens) * input_rate + cached_tokens * cache_read_rate) + assert completion_cost == pytest.approx(completion_tokens * output_rate) + + def test_generic_cost_per_token_azure_ai_gpt_6_astra_flex_bills_the_standard_rate(_local_model_cost_map): usage = Usage(prompt_tokens=1000, completion_tokens=100, total_tokens=1100) @@ -2648,6 +2782,7 @@ def test_cache_writing_cost_with_zero_creation_tokens_and_ephemeral_details(): prompt_tokens_details: PromptTokensDetailsResult = { "cache_hit_tokens": 0, + "cache_hit_audio_tokens": 0, "cache_creation_tokens": 0, "cache_creation_token_details": CacheCreationTokenDetails( ephemeral_5m_input_tokens=100, @@ -4005,8 +4140,9 @@ def test_billed_token_rates_follow_the_token_tier_the_breakdown_bills_at(monkeyp input_cost_per_token=6e-6, output_cost_per_token=3e-5, cache_read_input_token_cost=6e-7, + cache_read_input_audio_token_cost=6e-7, cache_creation_input_token_cost=7.5e-6, - cache_creation_input_token_cost_above_1hr=0.0, + cache_creation_input_token_cost_above_1hr=7.5e-6, output_cost_per_reasoning_token=3e-5, ) assert breakdown.cache_read_cost == pytest.approx(200_000 * rates.cache_read_input_token_cost) @@ -4527,7 +4663,7 @@ GEMINI_35_FLASH_LITE_TIER_RATES_BY_SURFACE = [ ("gemini", "priority", 5.4e-07, 4.5e-06, 5e-08), ("vertex_ai", None, 3e-07, 2.5e-06, 3e-08), ("vertex_ai", "flex", 1.5e-07, 1.25e-06, 1.5e-08), - ("vertex_ai", "priority", 5.4e-07, 4.5e-06, 5e-08), + ("vertex_ai", "priority", 5.4e-07, 4.5e-06, 5.4e-08), ] @@ -5147,3 +5283,226 @@ def test_generic_cost_per_token_bills_nested_reasoning_once_beside_audio_output( assert completion_cost == pytest.approx( 30 * info["output_cost_per_token"] + 70 * info["output_cost_per_audio_token"] ) + + +def test_cached_realtime_audio_tokens_billed_at_audio_cache_read_rate( + _local_model_cost_map: None, +) -> None: + usage = Usage( + prompt_tokens=283, + completion_tokens=0, + total_tokens=283, + prompt_tokens_details=PromptTokensDetailsWrapper( + text_tokens=116, + audio_tokens=167, + cached_tokens=192, + cached_tokens_details={"text_tokens": 64, "audio_tokens": 128}, + ), + ) + + prompt_cost, _ = generic_cost_per_token( + model="gpt-realtime-2", usage=usage, custom_llm_provider="openai" + ) + assert prompt_cost == pytest.approx(0.0015328) + + +def test_prompt_tokens_details_without_cached_tokens_details_unchanged( + _local_model_cost_map: None, +) -> None: + usage = Usage( + prompt_tokens=283, + completion_tokens=0, + total_tokens=283, + prompt_tokens_details=PromptTokensDetailsWrapper( + text_tokens=116, audio_tokens=167, cached_tokens=192 + ), + ) + + prompt_cost, _ = generic_cost_per_token( + model="gpt-realtime-2", usage=usage, custom_llm_provider="openai" + ) + assert prompt_cost == pytest.approx(0.0029888) + + +def test_cached_audio_tokens_fall_back_to_cache_read_input_token_cost() -> None: + model_info: ModelInfo = { + "input_cost_per_token": 4e-6, + "input_cost_per_audio_token": 32e-6, + "cache_read_input_token_cost": 5e-7, + } + usage = Usage( + prompt_tokens=283, + completion_tokens=0, + total_tokens=283, + prompt_tokens_details=PromptTokensDetailsWrapper( + text_tokens=116, + audio_tokens=167, + cached_tokens=192, + cached_tokens_details={"text_tokens": 64, "audio_tokens": 128}, + ), + ) + + prompt_cost, _ = generic_cost_per_token( + model="some-realtime-model", + usage=usage, + custom_llm_provider="openai", + model_info=model_info, + ) + expected = 52 * 4e-6 + 64 * 5e-7 + 39 * 32e-6 + 128 * 5e-7 + assert prompt_cost == pytest.approx(expected) + + +def test_cached_audio_tokens_capped_at_cached_tokens(_local_model_cost_map: None) -> None: + """Nested cached_tokens_details exceeding cached_tokens must not over-subtract the audio bucket.""" + usage = Usage( + prompt_tokens=283, + completion_tokens=0, + total_tokens=283, + prompt_tokens_details=PromptTokensDetailsWrapper( + text_tokens=116, + audio_tokens=167, + cached_tokens=100, + cached_tokens_details={"audio_tokens": 128}, + ), + ) + + prompt_cost, _ = generic_cost_per_token( + model="gpt-realtime-2", usage=usage, custom_llm_provider="openai" + ) + assert prompt_cost == pytest.approx(116 * 4e-6 + (167 - 100) * 32e-6 + 100 * 4e-7) + + +def test_cached_audio_tokens_billed_at_audio_cache_rate_through_model_info_lookup(_local_model_cost_map: None) -> None: + usage = Usage( + prompt_tokens=1000, + completion_tokens=0, + total_tokens=1000, + prompt_tokens_details=PromptTokensDetailsWrapper( + text_tokens=400, + audio_tokens=600, + cached_tokens=500, + cached_tokens_details={"text_tokens": 100, "audio_tokens": 400}, + ), + ) + + prompt_cost, _ = generic_cost_per_token(model="gpt-realtime-2.1-mini", usage=usage, custom_llm_provider="openai") + assert prompt_cost == pytest.approx(300 * 6e-7 + 100 * 6e-8 + 200 * 1e-5 + 400 * 3e-7) + + +def test_cache_read_breakdown_splits_cached_audio_at_the_audio_cache_rate(_local_model_cost_map: None) -> None: + usage = Usage( + prompt_tokens=4863, + completion_tokens=1087, + total_tokens=5950, + prompt_tokens_details=PromptTokensDetailsWrapper( + text_tokens=1693, + audio_tokens=3170, + cached_tokens=2816, + cached_tokens_details={"text_tokens": 896, "audio_tokens": 1920}, + ), + ) + + breakdown = get_token_type_cost_breakdown(model="gpt-realtime-2.1-mini", custom_llm_provider="openai", usage=usage) + prompt_cost, _ = generic_cost_per_token(model="gpt-realtime-2.1-mini", usage=usage, custom_llm_provider="openai") + + assert breakdown.cache_read_cost == pytest.approx(896 * 6e-8 + 1920 * 3e-7) + assert breakdown.rates is not None + assert breakdown.rates.cache_read_input_audio_token_cost == pytest.approx(3e-7) + assert prompt_cost == pytest.approx((1693 - 896) * 6e-7 + (3170 - 1920) * 1e-5 + breakdown.cache_read_cost) + + +@pytest.mark.parametrize( + ("model", "custom_llm_provider", "expected_prompt_cost"), + ( + pytest.param("azure/gpt-realtime-2025-08-28", "azure", 300 * 4e-6 + 100 * 4e-7 + 200 * 3.2e-5 + 400 * 4e-7, id="azure-gpt-realtime"), + pytest.param("azure/gpt-realtime-1.5-2026-02-23", "azure", 300 * 4e-6 + 100 * 4e-7 + 200 * 3.2e-5 + 400 * 4e-7, id="azure-gpt-realtime-1.5"), + pytest.param("azure/gpt-realtime-mini", "azure", 300 * 6e-7 + 100 * 6e-8 + 200 * 1e-5 + 400 * 3e-7, id="azure-gpt-realtime-mini"), + pytest.param("gpt-realtime-mini", "openai", 300 * 6e-7 + 100 * 6e-8 + 200 * 1e-5 + 400 * 3e-7, id="openai-gpt-realtime-mini"), + ), +) +def test_realtime_models_bill_cached_text_and_audio_at_their_cache_read_rates( + _local_model_cost_map: None, model: str, custom_llm_provider: str, expected_prompt_cost: float +) -> None: + usage = Usage( + prompt_tokens=1000, + completion_tokens=0, + total_tokens=1000, + prompt_tokens_details=PromptTokensDetailsWrapper( + text_tokens=400, + audio_tokens=600, + cached_tokens=500, + cached_tokens_details={"text_tokens": 100, "audio_tokens": 400}, + ), + ) + + prompt_cost, _ = generic_cost_per_token(model=model, usage=usage, custom_llm_provider=custom_llm_provider) + assert prompt_cost == pytest.approx(expected_prompt_cost) + + +def test_generic_cost_per_token_bills_cache_creation_at_the_input_rate_without_a_write_price(): + """Azure and OpenAI publish no cache-write price and bill cache writes as ordinary input. + A deployment priced with only input, output, and cache-read rates must bill the creation + tokens the provider reports at the input rate, never at 0. The numbers are a cold 7,336-token + prompt on a deployment that reports all but 3 of them as cache creation.""" + model_info = { + "input_cost_per_token": 2e-7, + "output_cost_per_token": 1.25e-6, + "cache_read_input_token_cost": 2e-8, + } + usage = Usage( + prompt_tokens=7336, + completion_tokens=23, + total_tokens=7359, + prompt_tokens_details=PromptTokensDetailsWrapper(cached_tokens=0, cache_creation_tokens=7333), + ) + + prompt_cost, completion_cost = generic_cost_per_token( + model="custom-priced-deployment", usage=usage, custom_llm_provider="azure", model_info=model_info + ) + + assert prompt_cost == pytest.approx(7336 * 2e-7) + assert completion_cost == pytest.approx(23 * 1.25e-6) + + +@pytest.mark.parametrize( + ("cache_rates", "current_time", "expected_creation", "expected_creation_1h"), + ( + pytest.param({}, None, 2e-7, 2e-7, id="no-write-price-uses-the-input-rate"), + pytest.param({"cache_creation_input_token_cost": 2.5e-7}, None, 2.5e-7, 2.5e-7, id="no-1h-price-uses-the-write-price"), + pytest.param({"cache_creation_input_token_cost": 0.0}, None, 0.0, 0.0, id="explicit-zero-stays-zero"), + pytest.param( + {"off_peak_pricing": {"hours_utc": "00:00-23:59", "input_cost_per_token": 1e-7}}, + datetime(2026, 9, 14, 12, tzinfo=timezone.utc), + 1e-7, + 1e-7, + id="no-write-price-uses-the-off-peak-input-rate", + ), + pytest.param( + { + "off_peak_pricing": { + "hours_utc": "00:00-23:59", + "input_cost_per_token": 1e-7, + "cache_creation_input_token_cost": 3e-7, + } + }, + datetime(2026, 9, 14, 12, tzinfo=timezone.utc), + 3e-7, + 3e-7, + id="no-1h-price-uses-the-off-peak-write-price", + ), + ), +) +def test_get_token_base_cost_resolves_missing_cache_write_rates_like_the_tiered_path( + cache_rates: Mapping[str, float | Mapping[str, float | str]], + current_time: datetime | None, + expected_creation: float, + expected_creation_1h: float, +) -> None: + model_info = {"input_cost_per_token": 2e-7, "output_cost_per_token": 1.25e-6, **cache_rates} + usage = Usage(prompt_tokens=10, completion_tokens=1, total_tokens=11) + + _, _, creation, creation_1h, _ = _get_token_base_cost(model_info, usage, current_time=current_time) + + assert creation == pytest.approx(expected_creation) + assert creation_1h == pytest.approx(expected_creation_1h) + diff --git a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_openai_cache_write_cost.py b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_openai_cache_write_cost.py index 92cb417f96c..18acfeda07d 100644 --- a/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_openai_cache_write_cost.py +++ b/tests/test_litellm/litellm_core_utils/llm_cost_calc/test_openai_cache_write_cost.py @@ -39,7 +39,7 @@ def test_openai_cache_write_tokens_billed_at_the_cache_creation_rate(local_model input_rate = rates["input_cost_per_token"] cache_write_rate = rates["cache_creation_input_token_cost"] output_rate = rates["output_cost_per_token"] - assert cache_write_rate == pytest.approx(input_rate * 1.25) + assert cache_write_rate > input_rate prompt_tokens = 12317 cache_write_tokens = 12314 diff --git a/tests/test_litellm/litellm_core_utils/test_exception_mapping_utils.py b/tests/test_litellm/litellm_core_utils/test_exception_mapping_utils.py index 42d3df76902..acc6248bf3e 100644 --- a/tests/test_litellm/litellm_core_utils/test_exception_mapping_utils.py +++ b/tests/test_litellm/litellm_core_utils/test_exception_mapping_utils.py @@ -1,4 +1,3 @@ - import httpx import openai import pytest @@ -178,9 +177,7 @@ class TestExceptionCheckers: ] for error_str in error_strings: - result = ExceptionCheckers.is_azure_content_policy_violation_error( - error_str - ) + result = ExceptionCheckers.is_azure_content_policy_violation_error(error_str) assert result is True, f"Should detect policy violation in: {error_str}" def test_is_azure_content_policy_violation_error_case_insensitive(self): @@ -194,12 +191,8 @@ class TestExceptionCheckers: ] for error_str in error_strings: - result = ExceptionCheckers.is_azure_content_policy_violation_error( - error_str - ) - assert ( - result is True - ), f"Should detect policy violation in uppercase: {error_str}" + result = ExceptionCheckers.is_azure_content_policy_violation_error(error_str) + assert result is True, f"Should detect policy violation in uppercase: {error_str}" def test_is_azure_content_policy_violation_error_with_non_policy_errors(self): """Test that non-policy violation errors are not detected as policy violations""" @@ -216,12 +209,8 @@ class TestExceptionCheckers: ] for error_str in error_strings: - result = ExceptionCheckers.is_azure_content_policy_violation_error( - error_str - ) - assert ( - result is False - ), f"Should NOT detect policy violation in: {error_str}" + result = ExceptionCheckers.is_azure_content_policy_violation_error(error_str) + assert result is False, f"Should NOT detect policy violation in: {error_str}" def test_is_azure_content_policy_violation_error_with_partial_matches(self): """Test that partial keyword matches work correctly""" @@ -234,9 +223,7 @@ class TestExceptionCheckers: ] for error_str in positive_cases: - result = ExceptionCheckers.is_azure_content_policy_violation_error( - error_str - ) + result = ExceptionCheckers.is_azure_content_policy_violation_error(error_str) assert result is True, f"Should detect policy violation in: {error_str}" # These should not match even though they contain similar words @@ -248,12 +235,8 @@ class TestExceptionCheckers: ] for error_str in negative_cases: - result = ExceptionCheckers.is_azure_content_policy_violation_error( - error_str - ) - assert ( - result is False - ), f"Should NOT detect policy violation in: {error_str}" + result = ExceptionCheckers.is_azure_content_policy_violation_error(error_str) + assert result is False, f"Should NOT detect policy violation in: {error_str}" gemini_context_window_test_cases = [ @@ -271,12 +254,8 @@ gemini_context_window_test_cases = [ ] -@pytest.mark.parametrize( - "error_message, should_raise_context_window", gemini_context_window_test_cases -) -def test_gemini_context_window_error_mapping( - error_message, should_raise_context_window -): +@pytest.mark.parametrize("error_message, should_raise_context_window", gemini_context_window_test_cases) +def test_gemini_context_window_error_mapping(error_message, should_raise_context_window): """ Tests that the exception_type function correctly maps Gemini's context window exceeded errors to litellm.ContextWindowExceededError. @@ -421,9 +400,7 @@ vertex_rate_limit_test_cases = [ ] -@pytest.mark.parametrize( - "error_message, should_raise_rate_limit", vertex_rate_limit_test_cases -) +@pytest.mark.parametrize("error_message, should_raise_rate_limit", vertex_rate_limit_test_cases) def test_vertex_ai_rate_limit_error_mapping(error_message, should_raise_rate_limit): """ Tests that the exception_type function correctly maps Vertex AI's @@ -458,10 +435,7 @@ class TestGetBodyErrorCode: """Unit tests for _get_body_error_code helper.""" def test_parses_int_code(self): - body = ( - '{"error":{"message":"high demand","type":"upstream_error",' - '"param":"","code":429}}' - ) + body = '{"error":{"message":"high demand","type":"upstream_error","param":"","code":429}}' assert _get_body_error_code(body) == 429 def test_parses_string_code(self): @@ -498,8 +472,7 @@ gemini_body_code_429_test_cases = [ ), ( 503, - '{"error":{"message":"upstream unavailable","type":"upstream_error",' - '"param":"","code":429}}', + '{"error":{"message":"upstream unavailable","type":"upstream_error","param":"","code":429}}', litellm.RateLimitError, "HTTP 503 envelope with body code:429 -> RateLimitError", ), @@ -769,9 +742,7 @@ class _UpstreamHTTPError(Exception): self.message = "upstream failure" self.status_code = status_code self.request = httpx.Request("POST", "https://api.example.com/v1/chat/completions") - self.response = httpx.Response( - status_code=status_code, request=self.request, text="upstream failure" - ) + self.response = httpx.Response(status_code=status_code, request=self.request, text="upstream failure") UPSTREAM_STATUS_CODES = (400, 401, 403, 404, 408, 422, 429, 500, 503) @@ -892,15 +863,13 @@ PROVIDERS_WITHOUT_A_HANDLER = tuple( MINIMAX_401_BODY = ( '{"type":"error","error":{"type":"authorized_error","message":"login fail: Please carry the API secret key ' - "in the 'Authorization' field of the request header (1004)\",\"http_code\":\"401\"}," + 'in the \'Authorization\' field of the request header (1004)","http_code":"401"},' '"request_id":"06ddc9ba97ee6340e38f10e09787f547"}' ) def _expected_for(provider: str, status_code: int) -> tuple[type[Exception], int]: - return DEVIATIONS_FROM_THE_OPENAI_SHAPE.get(provider, {}).get( - status_code, OPENAI_SHAPED[status_code] - ) + return DEVIATIONS_FROM_THE_OPENAI_SHAPE.get(provider, {}).get(status_code, OPENAI_SHAPED[status_code]) @pytest.fixture @@ -910,9 +879,7 @@ def quiet_exception_mapping(monkeypatch): @pytest.mark.parametrize("status_code", UPSTREAM_STATUS_CODES) @pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER) -def test_an_upstream_status_maps_to_one_exception_per_provider( - provider, status_code, quiet_exception_mapping -): +def test_an_upstream_status_maps_to_one_exception_per_provider(provider, status_code, quiet_exception_mapping): expected_class, expected_status = _expected_for(provider, status_code) with pytest.raises(openai.APIError) as raised: @@ -928,9 +895,7 @@ def test_an_upstream_status_maps_to_one_exception_per_provider( @pytest.mark.parametrize("status_code", UPSTREAM_STATUS_CODES) @pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER) -def test_a_mapped_exception_keeps_the_provider_and_model_it_came_from( - provider, status_code, quiet_exception_mapping -): +def test_a_mapped_exception_keeps_the_provider_and_model_it_came_from(provider, status_code, quiet_exception_mapping): with pytest.raises(openai.APIError) as raised: exception_type( model="test-model", @@ -943,12 +908,8 @@ def test_a_mapped_exception_keeps_the_provider_and_model_it_came_from( @pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER) -def test_an_already_mapped_litellm_exception_passes_through_untouched( - provider, quiet_exception_mapping -): - already_mapped = litellm.RateLimitError( - message="already mapped", llm_provider=provider, model="test-model" - ) +def test_an_already_mapped_litellm_exception_passes_through_untouched(provider, quiet_exception_mapping): + already_mapped = litellm.RateLimitError(message="already mapped", llm_provider=provider, model="test-model") returned = exception_type( model="test-model", @@ -961,9 +922,7 @@ def test_an_already_mapped_litellm_exception_passes_through_untouched( @pytest.mark.parametrize("status_code", UPSTREAM_STATUS_CODES) @pytest.mark.parametrize("provider", PROVIDERS_WITHOUT_A_HANDLER) -def test_a_provider_without_a_handler_maps_by_the_upstream_status( - provider, status_code, quiet_exception_mapping -): +def test_a_provider_without_a_handler_maps_by_the_upstream_status(provider, status_code, quiet_exception_mapping): expected_class, expected_status = STATUS_KEYED[status_code] with pytest.raises(openai.APIError) as raised: @@ -1015,9 +974,7 @@ def test_an_unmapped_exception_with_no_model_or_provider_is_a_connection_error(q assert "boom" in raised.value.message -def _raise_and_map( - model: str | None, original_exception: Exception, custom_llm_provider: str | None -) -> None: +def _raise_and_map(model: str | None, original_exception: Exception, custom_llm_provider: str | None) -> None: """Calls exception_type() from inside the except block, as litellm/main.py does, so traceback.format_exc() has a real stack.""" try: @@ -1058,9 +1015,7 @@ def test_an_unmapped_exception_with_no_model_or_provider_message_keeps_traceback CONTEXT_WINDOW_MESSAGE = "This model's maximum context length is 4096 tokens." -CONTENT_POLICY_MESSAGE = ( - '{"error": {"type": "invalid_request_error", "code": "content_policy_violation"}}' -) +CONTENT_POLICY_MESSAGE = '{"error": {"type": "invalid_request_error", "code": "content_policy_violation"}}' TIMEOUT_MESSAGE = "Request timed out." PROVIDERS_THAT_RECOGNISE_A_FULL_CONTEXT_WINDOW = ( @@ -1103,15 +1058,11 @@ class _UpstreamErrorWithMessage(_UpstreamHTTPError): super().__init__(status_code=status_code) self.args = (message,) self.message = message - self.response = httpx.Response( - status_code=status_code, request=self.request, text=message - ) + self.response = httpx.Response(status_code=status_code, request=self.request, text=message) @pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER) -def test_a_full_context_window_reaches_the_caller_as_the_router_needs_it( - provider, quiet_exception_mapping -): +def test_a_full_context_window_reaches_the_caller_as_the_router_needs_it(provider, quiet_exception_mapping): if provider in PROVIDERS_THAT_RECOGNISE_A_FULL_CONTEXT_WINDOW: expected_class, expected_status = litellm.ContextWindowExceededError, 400 else: @@ -1129,9 +1080,7 @@ def test_a_full_context_window_reaches_the_caller_as_the_router_needs_it( @pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER) -def test_a_content_policy_block_reaches_the_caller_as_the_router_needs_it( - provider, quiet_exception_mapping -): +def test_a_content_policy_block_reaches_the_caller_as_the_router_needs_it(provider, quiet_exception_mapping): if provider in PROVIDERS_THAT_RECOGNISE_A_CONTENT_POLICY_BLOCK: expected_class, expected_status = litellm.ContentPolicyViolationError, 400 else: @@ -1149,9 +1098,7 @@ def test_a_content_policy_block_reaches_the_caller_as_the_router_needs_it( @pytest.mark.parametrize("provider", PROVIDERS_WITH_A_HANDLER) -def test_a_timed_out_request_is_a_timeout_for_every_provider( - provider, quiet_exception_mapping -): +def test_a_timed_out_request_is_a_timeout_for_every_provider(provider, quiet_exception_mapping): with pytest.raises(litellm.Timeout) as raised: exception_type( model="test-model", @@ -1409,3 +1356,97 @@ def test_bedrock_timeout_mapping_keeps_retry_after_readable(status_code): exception_headers = _get_response_headers(original_exception=exc_info.value) assert exception_headers is not None assert litellm.utils._get_retry_after_from_exception_header(response_headers=exception_headers) == 7 + + +_GUARDRAIL_BLOCK_ERROR = { + "message": "Content blocked: secret_project_codename pattern detected", + "param": "None", + "code": "400", + "provider_specific_fields": { + "error": "Content blocked: secret_project_codename pattern detected", + "pattern": "secret_project_codename", + "guardrail_name": "block-secret-project", + "guardrail_mode": "pre_call", + }, +} + + +def _openai_handler_error( + error_type: str, + headers: dict[str, str] | list[tuple[str, str]], + status_code: int = 400, + message: str = _GUARDRAIL_BLOCK_ERROR["message"], +) -> OpenAIError: + wire_error = {**_GUARDRAIL_BLOCK_ERROR, "type": error_type, "code": str(status_code), "message": message} + return OpenAIError( + status_code=status_code, + message=f"Error code: {status_code} - {{'error': {wire_error}}}", + headers=httpx.Headers(headers), + body=wire_error, + ) + + +_PROXY_HEADERS = {"x-litellm-call-id": "call-guardrail", "x-litellm-applied-guardrails": "block-secret-project"} + + +@pytest.mark.parametrize(("error_type", "status_code"), [("None", 400), ("invalid_request_error", 400), ("None", 422)]) +def test_litellm_proxy_guardrail_block_keeps_body_and_headers(error_type: str, status_code: int): + with pytest.raises(litellm.BadRequestError) as exc_info: + exception_type( + model="claude-haiku-4-5", + original_exception=_openai_handler_error(error_type, _PROXY_HEADERS, status_code=status_code), + custom_llm_provider="litellm_proxy", + completion_kwargs={}, + extra_kwargs={}, + ) + + assert exc_info.value.body["provider_specific_fields"]["guardrail_name"] == "block-secret-project" + assert exc_info.value.body["type"] == error_type + assert dict(exc_info.value.response.headers) == _PROXY_HEADERS + + +@pytest.mark.parametrize("relayed_class", [litellm.BadRequestError, litellm.ContentPolicyViolationError]) +def test_litellm_proxy_relayed_litellm_error_keeps_body_and_headers(relayed_class: type[litellm.BadRequestError]): + message = f"litellm.{relayed_class.__name__}: {_GUARDRAIL_BLOCK_ERROR['message']}" + + with pytest.raises(relayed_class) as exc_info: + exception_type( + model="claude-haiku-4-5", + original_exception=_openai_handler_error("None", _PROXY_HEADERS, message=message), + custom_llm_provider="litellm_proxy", + completion_kwargs={}, + extra_kwargs={}, + ) + + assert type(exc_info.value) is relayed_class + assert exc_info.value.body["provider_specific_fields"]["guardrail_name"] == "block-secret-project" + assert dict(exc_info.value.response.headers) == _PROXY_HEADERS + + +def test_openai_compatible_vendor_400_keeps_body_but_not_headers(): + with pytest.raises(litellm.BadRequestError) as exc_info: + exception_type( + model="gpt-5.4-mini", + original_exception=_openai_handler_error("vendor_specific_error", {"openai-organization": "org-1"}), + custom_llm_provider="openai", + completion_kwargs={}, + extra_kwargs={}, + ) + + assert exc_info.value.body["type"] == "vendor_specific_error" + assert not exc_info.value.response.headers + + +def test_litellm_proxy_repeated_response_header_keeps_each_value(): + repeated = [("x-litellm-call-id", "call-guardrail"), ("set-cookie", "a=1"), ("set-cookie", "b=2")] + + with pytest.raises(litellm.BadRequestError) as exc_info: + exception_type( + model="claude-haiku-4-5", + original_exception=_openai_handler_error("None", repeated), + custom_llm_provider="litellm_proxy", + completion_kwargs={}, + extra_kwargs={}, + ) + + assert exc_info.value.response.headers.multi_items() == repeated diff --git a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py index b0220a36054..b2cc3ebe4c6 100644 --- a/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py +++ b/tests/test_litellm/litellm_core_utils/test_fallback_generalizations.py @@ -11,12 +11,12 @@ import logging import pytest - import litellm from litellm._logging import verbose_logger from litellm.litellm_core_utils.fallback_generalizations import ( get_fallback_generalization_rules, match_capability_generalizations, + match_fill_missing_generalizations, match_routing_generalization, set_fallback_generalizations, ) @@ -116,6 +116,67 @@ def test_capability_union_is_last_wins_in_file_order(restore_generalizations): } +def test_fill_missing_requires_per_rule_opt_in(restore_generalizations): + restore_generalizations( + [ + {"name": "base", "pattern": r"^acme-", "model_info": {"supports_reasoning": True}}, + { + "name": "opt-in", + "pattern": r"^acme-", + "fill_missing_for_providers": ["openai"], + "model_info": {"supports_vision": True}, + }, + ] + ) + assert match_fill_missing_generalizations("acme-1", "openai") == {"supports_vision": True} + assert match_fill_missing_generalizations("acme-1", "azure") is None + assert match_capability_generalizations("acme-1") == { + "supports_reasoning": True, + "supports_vision": True, + } + + restore_generalizations( + [{"name": "base", "pattern": r"^acme-", "model_info": {"supports_reasoning": True}}] + ) + assert match_fill_missing_generalizations("acme-1", "openai") is None + + restore_generalizations( + [ + { + "name": "mixed", + "pattern": r"^acme-", + "fill_missing_for_providers": ["openai"], + "model_info": {"litellm_provider": "openai", "supports_vision": True}, + } + ] + ) + assert match_fill_missing_generalizations("acme-1", "openai") == {"supports_vision": True} + + restore_generalizations( + [ + { + "name": "route", + "pattern": r"^acme-", + "fill_missing_for_providers": ["openai"], + "model_info": {"litellm_provider": "openai"}, + } + ] + ) + assert match_fill_missing_generalizations("acme-1", "openai") is None + + restore_generalizations( + [ + { + "name": "malformed", + "pattern": r"^acme-", + "fill_missing_for_providers": "openai", + "model_info": {"supports_vision": True}, + } + ] + ) + assert match_fill_missing_generalizations("acme-1", "openai") is None + + def test_routing_rules_are_excluded_from_capability_results(restore_generalizations): restore_generalizations( [ @@ -299,6 +360,76 @@ def test_exact_entry_takes_precedence_over_rule(restore_generalizations): assert info["input_cost_per_token"] != 999.0 +def test_exact_entries_fill_only_missing_fields(restore_generalizations, monkeypatch): + monkeypatch.setattr( + litellm, + "model_cost", + { + **litellm.model_cost, + "acme-full": { + "input_cost_per_token": 1e-6, + "output_cost_per_token": 2e-6, + "litellm_provider": "openai", + "mode": "chat", + "max_tokens": 7, + "supports_reasoning": False, + }, + "acme-bare": { + "input_cost_per_token": 3e-6, + "output_cost_per_token": 4e-6, + "litellm_provider": "openai", + "mode": "chat", + }, + "acme-image": { + "input_cost_per_token": 5e-6, + "output_cost_per_token": 6e-6, + "litellm_provider": "openai", + "mode": "image_generation", + }, + "acme-other": { + "input_cost_per_token": 7e-6, + "output_cost_per_token": 8e-6, + "litellm_provider": "openrouter", + "mode": "chat", + }, + }, + ) + restore_generalizations( + [ + { + "name": "acme-backfill", + "pattern": r"^acme-", + "fill_missing_for_providers": ["openai"], + "model_info": {"supports_reasoning": True, "max_tokens": 5}, + } + ] + ) + litellm.get_model_info.cache_clear() + + full = litellm.get_model_info("acme-full", custom_llm_provider="openai") + assert full["supports_reasoning"] is False + assert full["max_tokens"] == 7 + + bare = litellm.get_model_info("acme-bare", custom_llm_provider="openai") + assert bare["supports_reasoning"] is True + assert bare["max_tokens"] == 5 + assert bare["input_cost_per_token"] == 3e-6 + assert bare["key"] == "acme-bare" + + other = litellm.get_model_info("acme-other", custom_llm_provider="openrouter") + assert other.get("supports_reasoning") is None + + image = litellm.get_model_info("acme-image", custom_llm_provider="openai") + assert image.get("supports_reasoning") is None + + restore_generalizations( + [{"name": "acme-backfill", "pattern": r"^acme-", "model_info": {"supports_reasoning": True, "max_tokens": 5}}] + ) + litellm.get_model_info.cache_clear() + unflagged = litellm.get_model_info("acme-bare", custom_llm_provider="openai") + assert unflagged.get("supports_reasoning") is None + + # --------------------------------------------------------------------------- # # Shipped rules (bundled cost map) # --------------------------------------------------------------------------- # @@ -415,6 +546,18 @@ def test_shipped_version_boundaries(shipped_cost_map, model, provider, adaptive, assert info.get("supports_mid_conversation_system") is mid_conversation, model +def test_shipped_claude_version_regex_excludes_undelimited_41(shipped_cost_map): + unmatched = match_capability_generalizations("github_copilot/claude-opus-41") + assert unmatched is None or "supports_adaptive_thinking" not in unmatched + assert unmatched is None or "supports_mid_conversation_system" not in unmatched + + for model in ("claude-opus-5", "claude-sonnet-4-8"): + matched = match_capability_generalizations(model) + assert matched is not None + assert matched["supports_adaptive_thinking"] is True + assert matched["supports_mid_conversation_system"] is True + + def test_shipped_rules_cover_new_families_like_fable_at_5_plus(shipped_cost_map): """Both version gates accept any claude-- id at major 5 or higher, bare major or major-minor, so a new family shaped like claude-fable-5 gets adaptive @@ -605,6 +748,10 @@ def test_shipped_wandb_rule_loses_to_mapped_non_reasoning_entries(shipped_cost_m assert litellm.supports_reasoning(model=model, custom_llm_provider="wandb") is False, model +def test_shipped_wandb_rule_does_not_fill_missing_mapped_entries(shipped_cost_map): + assert match_fill_missing_generalizations("wandb/meta-llama/Llama-3.1-8B-Instruct", "wandb") is None + + def test_shipped_wandb_rule_is_anchored_to_the_wandb_namespace(shipped_cost_map): """``^wandb/`` is anchored, so it cannot leak onto another provider's ids.""" assert match_capability_generalizations("wandb/some-new-model") == {"supports_reasoning": True} @@ -677,3 +824,103 @@ def test_deployment_model_info_beats_the_seeded_rule_defaults(shipped_cost_map): assert litellm.model_cost[model]["supports_reasoning"] is False assert litellm.supports_reasoning(model="some-org/NoThink-1", custom_llm_provider="wandb") is False + + +def test_shipped_rules_flag_unmapped_openai_reasoning_families(shipped_cost_map): + for model in ( + "gpt-5.7-nova", + "openai/gpt-6", + "ft:gpt-5.1-2025-11-13:org::abc", + "o5-mini", + "gpt-5.6-codex-max", + "o4-mini-deep-research-2027-01-01", + "gpt-5.7-chat-latest", + "azure/gpt-5.7-cyber", + "openai/codex-mini-latest-2027", + ): + assert model not in litellm.model_cost, model + assert match_capability_generalizations(model) == {"supports_reasoning": True}, model + info = litellm.get_model_info("gpt-5.7-nova", custom_llm_provider="openai") + assert info["litellm_provider"] == "openai" + assert info["supports_reasoning"] is True + assert info.get("mode") is None + assert not info.get("input_cost_per_token") + assert litellm.supports_reasoning(model="gpt-5.7-nova", custom_llm_provider="openai") is True + + +def test_shipped_openai_reasoning_rule_skips_non_reasoning_gpt_ids(shipped_cost_map): + for model in ( + "gpt-4o", + "gpt-4.1-nano-new", + "gpt-oss-120b", + "gpt-realtime-2027", + "gpt-image-2", + "gpt-5-search-api-2027-01-01", + "omni-moderation-new", + "text-embedding-4", + "vendor/my-codex-embedding", + "some-codex-model", + "azure/gpt-35-turbo-0125-custom", + "github_copilot/gpt-41-copilot-new", + ): + assert match_capability_generalizations(model) is None, model + + +def test_shipped_openai_reasoning_rule_loses_to_mapped_entries(shipped_cost_map): + assert "gpt-5-search-api" in litellm.model_cost + assert litellm.supports_reasoning(model="gpt-5-search-api", custom_llm_provider="openai") is False + + +@pytest.mark.parametrize( + "model,provider,expected_supports_reasoning", + [ + ("azure/us/o1-2024-12-17", "azure", True), + ("github_copilot/gpt-5", "github_copilot", None), + ("openrouter/openai/o1", "openrouter", None), + ("perplexity/openai/gpt-5.4-mini", "perplexity", None), + ], +) +def test_shipped_openai_reasoning_rule_backfills_only_approved_providers( + shipped_cost_map, model, provider, expected_supports_reasoning +): + assert model in litellm.model_cost + raw_entry = litellm.model_cost[model] + assert "supports_reasoning" not in raw_entry + model_without_provider = model.removeprefix(f"{provider}/") + info = litellm.get_model_info(model=model_without_provider, custom_llm_provider=provider) + assert info.get("supports_reasoning") is expected_supports_reasoning + assert info["input_cost_per_token"] == raw_entry.get("input_cost_per_token", 0) + + +def test_shipped_openai_reasoning_rule_matches_only_openai(shipped_cost_map): + assert match_fill_missing_generalizations("gpt-5.4", "openai") == {"supports_reasoning": True} + assert match_fill_missing_generalizations("gpt-5.4", "openrouter") is None + + +def test_shipped_openai_reasoning_rule_skips_non_text_modes(shipped_cost_map): + model = "gemini/deep-research-pro-preview-12-2025" + assert model in litellm.model_cost + raw_entry = litellm.model_cost[model] + assert "supports_reasoning" not in raw_entry + assert raw_entry["mode"] == "image_generation" + + info = litellm.get_model_info("deep-research-pro-preview-12-2025", custom_llm_provider="gemini") + assert info.get("supports_reasoning") is None + + +def test_shipped_claude_thinking_rules_backfill_only_anthropic(shipped_cost_map): + model = "perplexity/anthropic/claude-sonnet-4-6" + assert model in litellm.model_cost + raw_entry = litellm.model_cost[model] + assert "supports_adaptive_thinking" not in raw_entry + assert "max_input_tokens" not in raw_entry + + info = litellm.get_model_info(model="anthropic/claude-sonnet-4-6", custom_llm_provider="perplexity") + assert info.get("supports_adaptive_thinking") is None + assert info.get("supports_legacy_thinking") is None + assert info.get("max_input_tokens") is None + assert match_fill_missing_generalizations("claude-sonnet-4-6", "anthropic") == { + "supports_adaptive_thinking": True, + "supports_legacy_thinking": True, + } + assert match_fill_missing_generalizations("claude-sonnet-4-6", "perplexity") is None diff --git a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py index 2f6339dcdbb..70f9bae283b 100644 --- a/tests/test_litellm/litellm_core_utils/test_litellm_logging.py +++ b/tests/test_litellm/litellm_core_utils/test_litellm_logging.py @@ -5221,10 +5221,11 @@ def test_handle_anthropic_messages_parsed_response_logging_preserves_fast_mode_s assert getattr(result.usage, "speed", None) == "fast" -def test_logging_init_sets_trace_id(): +def test_logging_init_sets_trace_id(monkeypatch): """Logging.__init__() must call set_trace_id with self.litellm_trace_id.""" from litellm.litellm_core_utils.litellm_logging import Logging + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("") log_obj = Logging( @@ -5240,7 +5241,7 @@ def test_logging_init_sets_trace_id(): assert trace_id_var.get() == log_obj.litellm_trace_id -def test_logging_init_skips_stamping_when_correlation_logging_unsupported(): +def test_logging_init_skips_stamping_when_correlation_logging_unsupported(monkeypatch): """supports_correlation_logging=False (what wrapper(), the sync entry point, always passes) must leave trace_id_var/session_id_var completely untouched, even though self.litellm_trace_id/litellm_session_id (the @@ -5248,6 +5249,7 @@ def test_logging_init_skips_stamping_when_correlation_logging_unsupported(): usual - only the ambient contextvar stamping is gated.""" from litellm.litellm_core_utils.litellm_logging import Logging + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("") session_id_var.set("") @@ -5271,10 +5273,48 @@ def test_logging_init_skips_stamping_when_correlation_logging_unsupported(): assert log_obj.litellm_session_id == "should-not-be-stamped" -def test_logging_init_sets_session_id_when_provided(): +def test_logging_init_skips_stamping_when_request_correlation_in_logs_disabled(monkeypatch): + from litellm.litellm_core_utils.litellm_logging import Logging + + monkeypatch.setattr(litellm, "request_correlation_in_logs", False) + trace_id_var.set("outer") + session_id_var.set("outer-sid") + try: + with ( + patch( # test-quality-ok: regression test verifies disabled stamping skips both setters + "litellm.litellm_core_utils.litellm_logging.set_trace_id" + ) as mock_set_trace_id, + patch( # test-quality-ok: regression test verifies disabled stamping skips both setters + "litellm.litellm_core_utils.litellm_logging.set_session_id" + ) as mock_set_session_id, + ): + log_obj = Logging( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type="completion", + start_time=None, + litellm_call_id="call-disabled", + function_id="fn-disabled", + kwargs={"litellm_session_id": "disabled-session"}, + supports_correlation_logging=True, + ) + + assert trace_id_var.get() == "outer" + assert session_id_var.get() == "outer-sid" + assert log_obj._own_trace_id == "outer" + mock_set_trace_id.assert_not_called() + mock_set_session_id.assert_not_called() + finally: + trace_id_var.set("") + session_id_var.set("") + + +def test_logging_init_sets_session_id_when_provided(monkeypatch): """Logging.__init__() must call set_session_id when litellm_session_id is in kwargs.""" from litellm.litellm_core_utils.litellm_logging import Logging + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) session_id_var.set("") Logging( @@ -5290,11 +5330,12 @@ def test_logging_init_sets_session_id_when_provided(): assert session_id_var.get() == "my-session-99" -def test_logging_init_resets_session_id_to_empty_when_absent(): +def test_logging_init_resets_session_id_to_empty_when_absent(monkeypatch): """When no session_id is in kwargs, Logging.__init__() must reset session_id_var to "" so a prior request's session_id does not leak into subsequent log records.""" from litellm.litellm_core_utils.litellm_logging import Logging + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) session_id_var.set("preexisting-sid") Logging( @@ -5310,7 +5351,7 @@ def test_logging_init_resets_session_id_to_empty_when_absent(): assert session_id_var.get() == "" -def test_restore_correlation_context_resets_to_pre_call_value(): +def test_restore_correlation_context_resets_to_pre_call_value(monkeypatch): """_restore_correlation_context() must put trace_id_var/session_id_var back to whatever they were immediately before this Logging instance was constructed. This is the mechanism that prevents a nested call (e.g. a guardrail's own @@ -5318,6 +5359,7 @@ def test_restore_correlation_context_resets_to_pre_call_value(): session_id into the outer call's subsequent log lines.""" from litellm.litellm_core_utils.litellm_logging import Logging + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace") session_id_var.set("outer-session") try: @@ -5343,7 +5385,7 @@ def test_restore_correlation_context_resets_to_pre_call_value(): session_id_var.set("") -def test_restore_correlation_context_safe_to_call_repeatedly(): +def test_restore_correlation_context_safe_to_call_repeatedly(monkeypatch): """Calling _restore_correlation_context() more than once must not raise. It's deliberately NOT guarded against repeat calls: wrapper()'s finally @@ -5353,6 +5395,7 @@ def test_restore_correlation_context_safe_to_call_repeatedly(): the contextvars, so repeat calls are expected, not just tolerated.""" from litellm.litellm_core_utils.litellm_logging import Logging + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) log_obj = Logging( model="gpt-3.5-turbo", messages=[{"role": "user", "content": "hi"}], @@ -5367,8 +5410,40 @@ def test_restore_correlation_context_safe_to_call_repeatedly(): log_obj._restore_correlation_context() # must not raise +def test_restore_correlation_context_does_not_resanitize(monkeypatch): + from litellm.litellm_core_utils.litellm_logging import Logging + from litellm._logging import _sanitize_correlation_id + + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) + trace_id_var.set("outer-trace") + session_id_var.set("outer-session") + try: + log_obj = Logging( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type="completion", + start_time=None, + litellm_call_id="call-no-resanitize", + function_id="fn-no-resanitize", + kwargs={"litellm_session_id": "inner-session"}, + ) + + with patch( # test-quality-ok: regression test verifies restore avoids sanitization + "litellm._logging._sanitize_correlation_id", wraps=_sanitize_correlation_id + ) as mock_sanitize: + log_obj._restore_correlation_context() + + mock_sanitize.assert_not_called() + assert trace_id_var.get() == "outer-trace" + assert session_id_var.get() == "outer-session" + finally: + trace_id_var.set("") + session_id_var.set("") + + @pytest.mark.asyncio -async def test_restore_correlation_context_works_across_asyncio_task_boundary(): +async def test_restore_correlation_context_works_across_asyncio_task_boundary(monkeypatch): """_restore_correlation_context() must succeed even when it's called from a different asyncio Task than the one Logging.__init__() ran in - exactly what happens on litellm's real async success path, where async_success_handler is @@ -5385,6 +5460,7 @@ async def test_restore_correlation_context_works_across_asyncio_task_boundary(): """ from litellm.litellm_core_utils.litellm_logging import Logging + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace-cross-task") session_id_var.set("outer-session-cross-task") try: @@ -5890,6 +5966,81 @@ def test_resolve_vertex_location_for_cost_default_region(monkeypatch): assert _resolve("vertex_ai", None, None, "gemini-3.5-flash") == "us-central1" +def test_resolve_mantle_region_for_cost(monkeypatch): + """Bedrock Mantle requests resolve the served region the way dispatch does (explicit + aws_region_name, then the api_base host, then the default); other providers get None.""" + from litellm.litellm_core_utils.litellm_logging import _resolve_mantle_region_for_cost + + for var in ("BEDROCK_MANTLE_REGION", "BEDROCK_MANTLE_API_BASE", "AWS_REGION_NAME", "AWS_REGION"): + monkeypatch.delenv(var, raising=False) + + assert _resolve_mantle_region_for_cost("bedrock", {"aws_region_name": "us-gov-west-1"}) is None + assert _resolve_mantle_region_for_cost(None, {"aws_region_name": "us-gov-west-1"}) is None + assert _resolve_mantle_region_for_cost("bedrock_mantle", {"aws_region_name": "us-gov-west-1"}) == "us-gov-west-1" + assert ( + _resolve_mantle_region_for_cost( + "bedrock_mantle", + {"api_base": "https://bedrock-mantle.us-gov-west-1.api.aws/openai/v1/chat/completions"}, + ) + == "us-gov-west-1" + ) + assert _resolve_mantle_region_for_cost("bedrock_mantle", None) == "us-east-1" + + +def test_response_cost_calculator_prices_mantle_calls_on_the_served_region(monkeypatch): + """ + Mantle responses carry no region of their own (the OpenAI-compatible transform rebuilds the + response, and streams never had one), so the logging layer must price them from the region + the deployment was served in: an explicit aws_region_name or the api_base host, both of which + must select the GovCloud row over the commercial one. + """ + from datetime import datetime + + from litellm.litellm_core_utils.get_model_cost_map import get_model_cost_map + + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + monkeypatch.setattr(litellm, "model_cost", get_model_cost_map(url="")) + for var in ("BEDROCK_MANTLE_REGION", "BEDROCK_MANTLE_API_BASE", "AWS_REGION_NAME", "AWS_REGION"): + monkeypatch.delenv(var, raising=False) + + def cost_with(litellm_params): + logging_obj = LitellmLogging( + model="xai.grok-4.3", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type="completion", + start_time=datetime.now(), + litellm_call_id="mantle-region", + function_id="f", + ) + logging_obj.update_environment_variables( + model="xai.grok-4.3", + user="", + optional_params={}, + litellm_params=litellm_params, + custom_llm_provider="bedrock_mantle", + ) + response = ModelResponse( + id="resp-1", + model="xai.grok-4.3", + choices=[{"message": {"role": "assistant", "content": "hello"}, "index": 0, "finish_reason": "stop"}], + usage={"prompt_tokens": 38, "completion_tokens": 20, "total_tokens": 58}, + ) + return logging_obj._response_cost_calculator(result=response) + + commercial = litellm.model_cost["bedrock_mantle/xai.grok-4.3"] + gov = litellm.model_cost["bedrock_mantle/us-gov-west-1/xai.grok-4.3"] + expected_commercial = 38 * commercial["input_cost_per_token"] + 20 * commercial["output_cost_per_token"] + expected_gov = 38 * gov["input_cost_per_token"] + 20 * gov["output_cost_per_token"] + assert expected_gov != expected_commercial + + assert cost_with({"api_base": ""}) == pytest.approx(expected_commercial) + assert cost_with({"aws_region_name": "us-gov-west-1"}) == pytest.approx(expected_gov) + assert cost_with( + {"api_base": "https://bedrock-mantle.us-gov-west-1.api.aws/openai/v1/chat/completions"} + ) == pytest.approx(expected_gov) + + def test_response_cost_calculator_prices_proxy_vertex_calls_on_the_configured_location(monkeypatch): """ Proxy-shaped logging objects (created before the router picks a deployment) carry the diff --git a/tests/test_litellm/litellm_core_utils/test_logging_worker.py b/tests/test_litellm/litellm_core_utils/test_logging_worker.py index eb4e893adb8..1553e788472 100644 --- a/tests/test_litellm/litellm_core_utils/test_logging_worker.py +++ b/tests/test_litellm/litellm_core_utils/test_logging_worker.py @@ -14,6 +14,18 @@ from litellm.constants import LOGGING_WORKER_AGGRESSIVE_CLEAR_COOLDOWN_SECONDS from litellm.litellm_core_utils.logging_worker import LoggingWorker +class _RecordCollector(logging.Handler): + """Captures emitted log records so a test can assert on real logging output + (level, message args, traceback) instead of patching the logger object.""" + + def __init__(self) -> None: + super().__init__() + self.records: list[logging.LogRecord] = [] + + def emit(self, record: logging.LogRecord) -> None: + self.records.append(record) + + class TestLoggingWorker: """Test cases for LoggingWorker functionality.""" @@ -26,9 +38,7 @@ class TestLoggingWorker: async def test_graceful_shutdown_with_clear_queue(self, logging_worker): """Test that cancellation triggers clear_queue to prevent 'never awaited' warnings.""" # Mock the clear_queue method to verify it's called during cancellation - with patch.object( - logging_worker, "clear_queue", new_callable=AsyncMock - ) as mock_clear_queue: + with patch.object(logging_worker, "clear_queue", new_callable=AsyncMock) as mock_clear_queue: # Start the worker logging_worker.start() @@ -195,9 +205,7 @@ class TestLoggingWorker: async def test_worker_handles_cancellation_gracefully(self, logging_worker): """Test that the worker handles cancellation without throwing exceptions.""" # Mock verbose_logger to capture debug messages - with patch( - "litellm.litellm_core_utils.logging_worker.verbose_logger" - ) as mock_logger: + with patch("litellm.litellm_core_utils.logging_worker.verbose_logger") as mock_logger: # Start the worker logging_worker.start() @@ -264,29 +272,21 @@ class TestLoggingWorker: small_worker._ensure_queue() # Mock verbose_logger to capture exception messages - with patch( - "litellm.litellm_core_utils.logging_worker.verbose_logger" - ) as mock_logger: + with patch("litellm.litellm_core_utils.logging_worker.verbose_logger") as mock_logger: # Fill the queue beyond capacity mock_coro = AsyncMock() for _ in range(5): # More than max_queue_size of 2 small_worker.enqueue(mock_coro()) # Should have logged queue full exceptions - exception_calls = [ - call - for call in mock_logger.exception.call_args_list - if "queue is full" in str(call) - ] + exception_calls = [call for call in mock_logger.exception.call_args_list if "queue is full" in str(call)] assert len(exception_calls) > 0 @pytest.mark.asyncio async def test_context_propagation(self, logging_worker): """Test that enqueued tasks execute in their original context.""" # Create a context variable for testing - test_context_var: contextvars.ContextVar[str] = contextvars.ContextVar( - "test_context_var" - ) + test_context_var: contextvars.ContextVar[str] = contextvars.ContextVar("test_context_var") # Track results from multiple tasks using asyncio.Event for synchronization task_results = [] @@ -364,36 +364,28 @@ class TestLoggingWorker: task_results.sort(key=lambda x: x["task_id"]) # Verify that each task saw its own context - assert ( - len(task_results) == 3 - ), f"Expected 3 results, got {len(task_results)}: {task_results}" + assert len(task_results) == 3, f"Expected 3 results, got {len(task_results)}: {task_results}" # Task 1 should see "context_1" task1_result = next((r for r in task_results if r["task_id"] == "task_1"), None) assert task1_result is not None, "Task 1 result not found" - assert ( - task1_result["context_accessible"] is True - ), "Task 1 should have access to context variable" - assert ( - task1_result["context_value"] == "context_1" - ), f"Task 1 should see 'context_1', got: {task1_result['context_value']}" + assert task1_result["context_accessible"] is True, "Task 1 should have access to context variable" + assert task1_result["context_value"] == "context_1", ( + f"Task 1 should see 'context_1', got: {task1_result['context_value']}" + ) # Task 2 should see "context_2" task2_result = next((r for r in task_results if r["task_id"] == "task_2"), None) assert task2_result is not None, "Task 2 result not found" - assert ( - task2_result["context_accessible"] is True - ), "Task 2 should have access to context variable" - assert ( - task2_result["context_value"] == "context_2" - ), f"Task 2 should see 'context_2', got: {task2_result['context_value']}" + assert task2_result["context_accessible"] is True, "Task 2 should have access to context variable" + assert task2_result["context_value"] == "context_2", ( + f"Task 2 should see 'context_2', got: {task2_result['context_value']}" + ) # Task 3 should not have access to the context variable task3_result = next((r for r in task_results if r["task_id"] == "task_3"), None) assert task3_result is not None, "Task 3 result not found" - assert ( - task3_result["context_accessible"] is False - ), "Task 3 should not have access to context variable" + assert task3_result["context_accessible"] is False, "Task 3 should not have access to context variable" @pytest.mark.asyncio async def test_semaphore_concurrency_limit(self): @@ -525,3 +517,182 @@ class TestLoggingWorker: asyncio.run(rebind_on_second_loop()) assert sorted(executed) == [0, 1, 2, 3, 4] + + @pytest.mark.asyncio + async def test_timeout_burst_logs_one_bounded_summary(self): + """Regression (LIT-7519): a burst of callback timeouts must log one bounded summary, + not a full ERROR traceback per timed-out callback. + + Before the fix every timed-out callback hit ``verbose_logger.exception`` in + ``_process_log_task``, so a slow Redis timing out many spend-tracking callbacks at once + produced one stacktrace each, clustered milliseconds apart. They must collapse into a + single WARNING that counts them, with no tracebacks. + """ + timeout_count = 25 + worker = LoggingWorker( + timeout=0.05, + max_queue_size=100, + concurrency=100, + timeout_summary_window=1.0, + ) + + async def slow_callback() -> None: + await asyncio.sleep(10) + + logger = logging.getLogger("LiteLLM") + collector = _RecordCollector() + previous_level = logger.level + logger.addHandler(collector) + logger.setLevel(logging.DEBUG) + try: + worker.start() + for _ in range(timeout_count): + worker.enqueue(slow_callback()) + + await worker.flush() + assert worker._timeout_summary_task is not None + await worker._timeout_summary_task + await worker.stop() + finally: + logger.removeHandler(collector) + logger.setLevel(previous_level) + + errors = [r for r in collector.records if r.levelno >= logging.ERROR] + warnings = [r for r in collector.records if r.levelno == logging.WARNING] + assert errors == [], "a timeout burst must not emit any ERROR tracebacks" + assert len(warnings) == 1, "the whole burst must collapse into one summary line" + summary = warnings[0].getMessage() + assert f"{timeout_count} callback(s) timed out" in summary + assert f"{timeout_count} timed out since start" in summary + assert "slow_callback" in summary + + @pytest.mark.asyncio + async def test_non_timeout_error_keeps_traceback(self): + """A real programming error in a callback must still log a full traceback, so the + timeout aggregation never hides genuine failures. + """ + worker = LoggingWorker(timeout=5.0, max_queue_size=10) + + async def failing_callback() -> None: + raise ValueError("boom") + + logger = logging.getLogger("LiteLLM") + collector = _RecordCollector() + previous_level = logger.level + logger.addHandler(collector) + logger.setLevel(logging.DEBUG) + try: + worker.start() + worker.enqueue(failing_callback()) + + await worker.flush() + await worker.stop() + finally: + logger.removeHandler(collector) + logger.setLevel(previous_level) + + errors = [r for r in collector.records if r.levelno >= logging.ERROR] + warnings = [r for r in collector.records if r.levelno == logging.WARNING] + assert len(errors) == 1, "a real error must still be logged once" + assert errors[0].exc_info is not None, "the traceback must be preserved" + assert warnings == [], "a single real error is not a timeout summary" + assert worker._timeout_summary_task is None + + @pytest.mark.asyncio + async def test_callback_raised_timeout_keeps_traceback(self): + """A callback that raises TimeoutError on its own did not hit the worker's deadline, + so it is a real failure and must keep its traceback rather than being folded into the + bounded burst summary. + """ + worker = LoggingWorker(timeout=5.0, max_queue_size=10, timeout_summary_window=1.0) + + async def raises_own_timeout() -> None: + raise asyncio.TimeoutError("callback's own downstream timeout") + + logger = logging.getLogger("LiteLLM") + collector = _RecordCollector() + previous_level = logger.level + logger.addHandler(collector) + logger.setLevel(logging.DEBUG) + try: + worker.start() + worker.enqueue(raises_own_timeout()) + + await worker.flush() + await worker.stop() + finally: + logger.removeHandler(collector) + logger.setLevel(previous_level) + + errors = [r for r in collector.records if r.levelno >= logging.ERROR] + warnings = [r for r in collector.records if r.levelno == logging.WARNING] + assert len(errors) == 1, "a callback-raised TimeoutError must still be logged once" + assert errors[0].exc_info is not None, "the traceback must be preserved" + assert warnings == [], "a callback-raised TimeoutError is not a worker-deadline timeout" + assert worker._timeout_summary_task is None + + @pytest.mark.asyncio + async def test_stop_flushes_pending_timeout_summary(self): + """A burst still inside its summary window when the worker stops must still emit its one + summary, instead of losing it when the event loop tears down. + """ + worker = LoggingWorker( + timeout=0.05, + max_queue_size=10, + concurrency=10, + timeout_summary_window=30.0, + ) + + async def slow_callback() -> None: + await asyncio.sleep(10) + + logger = logging.getLogger("LiteLLM") + collector = _RecordCollector() + previous_level = logger.level + logger.addHandler(collector) + logger.setLevel(logging.DEBUG) + try: + worker.start() + for _ in range(3): + worker.enqueue(slow_callback()) + + await worker.flush() + assert worker._timeout_summary_task is not None + assert not worker._timeout_summary_task.done(), "precondition: the summary window has not elapsed" + await worker.stop() + finally: + logger.removeHandler(collector) + logger.setLevel(previous_level) + + warnings = [r for r in collector.records if r.levelno == logging.WARNING] + assert len(warnings) == 1, "stop must flush the pending summary exactly once" + assert "3 callback(s) timed out" in warnings[0].getMessage() + assert worker._timeout_summary_task is None + + def test_loop_change_resets_timeout_summary_state(self): + """On an event-loop change the summary task is bound to the dead loop; it and the pending + burst count must reset so timeouts on the new loop arm a fresh summary rather than a stale, + stuck one that silently drops later summaries. + """ + worker = LoggingWorker(timeout=1.0, max_queue_size=10, timeout_summary_window=30.0) + + async def timed_out_callback() -> None: + await asyncio.sleep(10) + + async def arm_on_first_loop() -> None: + worker._ensure_queue() + coro = timed_out_callback() + worker._record_callback_timeout(coro) + coro.close() + assert worker._timeout_summary_task is not None + assert worker._timeout_burst_count == 1 + + asyncio.run(arm_on_first_loop()) + assert worker._timeout_summary_task is not None + + async def rebind_on_second_loop() -> None: + worker._ensure_queue() + assert worker._timeout_summary_task is None, "stale summary task must drop on loop change" + assert worker._timeout_burst_count == 0, "stale burst count must reset on loop change" + + asyncio.run(rebind_on_second_loop()) diff --git a/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py b/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py index 9c0f6f59463..7e6d4d24905 100644 --- a/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py +++ b/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py @@ -10,20 +10,14 @@ from websockets.exceptions import ConnectionClosed from websockets.frames import Close import litellm - - +from litellm.constants import REALTIME_SESSION_FAILURE_LOGGED_KEY, REALTIME_SESSION_SUCCESS_LOGGED_KEY from litellm.integrations.custom_guardrail import CustomGuardrail from litellm.litellm_core_utils.realtime_streaming import ( - REALTIME_SESSION_SUCCESS_LOGGED_KEY, RealTimeStreaming, client_sent_openai_beta_realtime_header, ) from litellm.llms.xai.realtime.transformation import XAIRealtimeNormalizer from litellm.types.guardrails import GuardrailEventHooks -from litellm.types.llms.openai import ( - OpenAIRealtimeStreamResponseBaseObject, - OpenAIRealtimeStreamSessionEvents, -) def _make_transcript_event(text: str, item_id: str = "item_x") -> bytes: @@ -161,6 +155,7 @@ async def test_backend_to_client_send_text_receives_str_not_bytes(): logging_obj = MagicMock() logging_obj.async_success_handler = AsyncMock() logging_obj.success_handler = MagicMock() + logging_obj.dispatch_success_handlers = AsyncMock() streaming = RealTimeStreaming(client_ws, backend_ws, logging_obj) await streaming.backend_to_client_send_messages() @@ -812,7 +807,6 @@ async def test_transcription_captured_in_backend_to_client(): Test that conversation.item.input_audio_transcription.completed events from the backend are captured as user input during the WebSocket session. """ - import litellm client_ws = MagicMock() client_ws.send_text = AsyncMock() @@ -838,6 +832,7 @@ async def test_transcription_captured_in_backend_to_client(): logging_obj.model_call_details = {"messages": "default-message-value"} logging_obj.async_success_handler = AsyncMock() logging_obj.success_handler = MagicMock() + logging_obj.dispatch_success_handlers = AsyncMock() streaming = RealTimeStreaming(client_ws, backend_ws, logging_obj) await streaming.backend_to_client_send_messages() @@ -883,6 +878,7 @@ async def test_transcription_session_captures_usage_and_skips_response_create(): logging_obj.model_call_details = {} logging_obj.async_success_handler = AsyncMock() logging_obj.success_handler = MagicMock() + logging_obj.dispatch_success_handlers = AsyncMock() streaming = RealTimeStreaming(client_ws, backend_ws, logging_obj) await streaming.backend_to_client_send_messages() @@ -1100,7 +1096,6 @@ def test_capture_transcription_usage_deduplicates_when_already_stored(): When the event is already in messages (logged via store_message), it must not be appended a second time by _capture_transcription_usage. """ - import litellm streaming = RealTimeStreaming(MagicMock(), MagicMock(), MagicMock()) # Add the event type to the default logged list so _should_store_message returns True. @@ -1409,7 +1404,6 @@ async def test_realtime_guardrail_blocks_prompt_injection(monkeypatch: pytest.Mo ) - @pytest.mark.asyncio async def test_realtime_guardrail_allows_clean_transcript(monkeypatch: pytest.MonkeyPatch): """ @@ -1466,7 +1460,6 @@ async def test_realtime_guardrail_allows_clean_transcript(monkeypatch: pytest.Mo assert len(response_creates) == 1, f"Clean transcript should trigger response.create, got: {sent_to_backend}" - @pytest.mark.asyncio async def test_realtime_text_input_guardrail_blocks_and_returns_error(monkeypatch: pytest.MonkeyPatch): """ @@ -1560,7 +1553,6 @@ async def test_realtime_text_input_guardrail_blocks_and_returns_error(monkeypatc assert len(original_items) == 0, f"Blocked item should not be forwarded to backend, got: {original_items}" - @pytest.mark.asyncio async def test_realtime_function_call_output_guardrail_blocks_and_returns_error(monkeypatch: pytest.MonkeyPatch): """ @@ -1649,7 +1641,6 @@ async def test_realtime_function_call_output_guardrail_blocks_and_returns_error( assert "test@example.com" not in sanitized_item["output"] - @pytest.mark.asyncio async def test_realtime_function_call_output_guardrail_allows_clean_output(monkeypatch: pytest.MonkeyPatch): """ @@ -1714,7 +1705,6 @@ async def test_realtime_function_call_output_guardrail_allows_clean_output(monke assert len(forwarded) == 1, f"Clean function_call_output should be forwarded, got: {forwarded}" - @pytest.mark.asyncio async def test_realtime_text_input_guardrail_uses_pre_call_mode(monkeypatch: pytest.MonkeyPatch): """ @@ -1750,7 +1740,6 @@ async def test_realtime_text_input_guardrail_uses_pre_call_mode(monkeypatch: pyt ) - @pytest.mark.asyncio async def test_realtime_session_created_injects_session_update_for_audio_guardrail(monkeypatch: pytest.MonkeyPatch): """ @@ -1807,7 +1796,6 @@ async def test_realtime_session_created_injects_session_update_for_audio_guardra ) - @pytest.mark.asyncio async def test_realtime_session_created_does_not_inject_session_update_for_pre_call_only( monkeypatch: pytest.MonkeyPatch, @@ -1852,7 +1840,6 @@ async def test_realtime_session_created_does_not_inject_session_update_for_pre_c assert len(session_updates) == 0, f"pre_call-only guardrail must not inject session.update, got: {sent_to_backend}" - @pytest.mark.asyncio async def test_pre_call_and_post_call_guardrails_do_not_disable_server_vad(monkeypatch: pytest.MonkeyPatch): """Model Armor-style pre_call + post_call must not gate audio VAD.""" @@ -1868,17 +1855,17 @@ async def test_pre_call_and_post_call_guardrails_do_not_disable_server_vad(monke litellm, "callbacks", [ - ModelArmorStyleGuardrail( - guardrail_name="model_armor_all_pre_call", - event_hook=GuardrailEventHooks.pre_call, - default_on=False, - ), - ModelArmorStyleGuardrail( - guardrail_name="model_armor_all_post_call", - event_hook=GuardrailEventHooks.post_call, - default_on=False, - ), - ], + ModelArmorStyleGuardrail( + guardrail_name="model_armor_all_pre_call", + event_hook=GuardrailEventHooks.pre_call, + default_on=False, + ), + ModelArmorStyleGuardrail( + guardrail_name="model_armor_all_post_call", + event_hook=GuardrailEventHooks.post_call, + default_on=False, + ), + ], ) client_ws = MagicMock() @@ -1902,7 +1889,6 @@ async def test_pre_call_and_post_call_guardrails_do_not_disable_server_vad(monke assert streaming._has_audio_transcription_guardrails() is False - @pytest.mark.asyncio async def test_end_session_after_n_fails_closes_connection(monkeypatch: pytest.MonkeyPatch): """ @@ -1949,7 +1935,6 @@ async def test_end_session_after_n_fails_closes_connection(monkeypatch: pytest.M assert streaming._violation_count == 2 - @pytest.mark.asyncio async def test_on_violation_end_session_closes_on_first_fail(monkeypatch: pytest.MonkeyPatch): """ @@ -1995,7 +1980,6 @@ async def test_on_violation_end_session_closes_on_first_fail(monkeypatch: pytest assert streaming._violation_count == 1 - @pytest.mark.asyncio async def test_provider_path_suppresses_duplicate_session_created_after_synthetic(): client_ws = MagicMock() @@ -2956,7 +2940,9 @@ async def test_log_messages_routes_async_logging_through_bounded_worker(): mock_worker.ensure_initialized_and_enqueue.assert_called_once() enqueued = mock_worker.ensure_initialized_and_enqueue.call_args - assert (enqueued.args or tuple(enqueued.kwargs.values()))[0] is logging_obj.dispatch_success_handlers.return_value + assert (enqueued.args or tuple(enqueued.kwargs.values()))[ + 0 + ] is logging_obj.dispatch_success_handlers.return_value logging_obj.dispatch_success_handlers.assert_called_once_with(streaming.messages, prefer_async_handlers=True) logging_obj.success_handler.assert_not_called() # the bare create_task path must no longer be used for success logging @@ -3041,6 +3027,7 @@ async def test_session_close_flushes_unbilled_transcription_usage(): logging_obj: Final = MagicMock() logging_obj.async_success_handler = AsyncMock() logging_obj.success_handler = MagicMock() + logging_obj.dispatch_success_handlers = AsyncMock() usage: Final[RealtimeInputAudioTranscriptionUsage] = { "type": "tokens", @@ -3116,6 +3103,7 @@ async def test_session_close_flush_noop_without_unbilled_usage(): logging_obj: Final = MagicMock() logging_obj.async_success_handler = AsyncMock() logging_obj.success_handler = MagicMock() + logging_obj.dispatch_success_handlers = AsyncMock() provider_config: Final = MagicMock() provider_config.unbilled_usage_on_session_close = MagicMock(return_value=None) @@ -3136,7 +3124,6 @@ async def test_session_close_flush_noop_without_unbilled_usage(): ) - _UPSTREAM_REFUSAL: Final = "Publisher model `publishers/google/models/gemini-live-2.5-flash` was not found" @@ -3204,9 +3191,7 @@ def _backend_ws_closing_with(*frames: bytes | Exception) -> MagicMock: def _relay_session(client_ws: MagicMock, backend_ws: MagicMock) -> _RelaySession: logging: Final = _RecordingLogging() worker: Final = _InlineLoggingWorker() - streaming: Final = RealTimeStreaming( - client_ws, backend_ws, logging, model="gpt-realtime", logging_worker=worker - ) + streaming: Final = RealTimeStreaming(client_ws, backend_ws, logging, model="gpt-realtime", logging_worker=worker) return _RelaySession(streaming=streaming, logging=logging, worker=worker) @@ -3412,3 +3397,156 @@ async def test_refused_session_does_not_stamp_the_reservation_ownership_marker() assert session.logging.logged_failures == (upstream_close,) assert REALTIME_SESSION_SUCCESS_LOGGED_KEY not in session.logging.model_call_details + + +@pytest.mark.asyncio +async def test_refused_session_stamps_the_failure_ownership_marker(): + """LIT-6463: the enqueued failure callback releases the key's max_parallel_requests + slot from the logging worker, so a refusal stamps REALTIME_SESSION_FAILURE_LOGGED_KEY. + The proxy endpoint reads it to leave the slot to that callback instead of racing it. + A session that relayed frames logs a success and must not carry the failure stamp.""" + upstream_close: Final = ConnectionClosed(Close(1008, _UPSTREAM_REFUSAL), None) + refused: Final = _relay_session(_client_ws_that_never_sends(), _backend_ws_closing_with(upstream_close)) + session_created: Final = json.dumps({"type": "session.created", "session": {"id": "sess_1"}}).encode() + relayed: Final = _relay_session( + _client_ws_that_never_sends(), _backend_ws_closing_with(session_created, upstream_close) + ) + + await refused.run() + await relayed.run() + + assert refused.logging.model_call_details.get(REALTIME_SESSION_FAILURE_LOGGED_KEY) is True + assert REALTIME_SESSION_FAILURE_LOGGED_KEY not in relayed.logging.model_call_details + + +@pytest.mark.asyncio +async def test_transformed_transcription_completion_never_sends_response_create(): + from typing import Final + + completed_event: Final = { + "type": "conversation.item.input_audio_transcription.completed", + "event_id": "event_1", + "item_id": "turn_1", + "content_index": 0, + "transcript": "private transcript", + "usage": {"type": "duration", "seconds": 0.5}, + } + provider_config: Final = MagicMock() + provider_config.requires_session_configuration.return_value = True + provider_config.transform_realtime_response.return_value = { + "response": completed_event, + "current_output_item_id": None, + "current_response_id": None, + "current_delta_chunks": None, + "current_conversation_id": None, + "current_item_chunks": None, + "current_delta_type": None, + "session_configuration_request": None, + } + provider_config.transform_realtime_request.return_value = (json.dumps({"type": "response.create"}),) + provider_config.is_setup_message.return_value = False + provider_config.is_content_message.return_value = False + client_ws: Final = MagicMock() + client_ws.send_text = AsyncMock() + backend_ws: Final = MagicMock() + backend_ws.send = AsyncMock() + + streaming: Final = RealTimeStreaming( + client_ws, + backend_ws, + MagicMock(), + provider_config=provider_config, + model="muse-voice-transcribe-1.0", + force_transcription_model="muse-voice-transcribe-1.0", + ) + + await streaming._handle_provider_config_message("{}") + + assert json.loads(client_ws.send_text.await_args.args[0]) == completed_event + backend_ws.send.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_transcription_session_still_runs_transcription_guardrail(monkeypatch: pytest.MonkeyPatch): + class BlockingGuardrail(CustomGuardrail): + async def apply_guardrail(self, inputs, request_data, input_type, logging_obj=None): + raise ValueError("blocked transcript") + + guardrail: Final = BlockingGuardrail( + guardrail_name="transcription-blocker", + event_hook=GuardrailEventHooks.realtime_input_transcription, + default_on=True, + ) + monkeypatch.setattr(litellm, "callbacks", [guardrail]) + + completed_event: Final = { + "type": "conversation.item.input_audio_transcription.completed", + "event_id": "event_1", + "item_id": "turn_1", + "content_index": 0, + "transcript": "blocked transcript", + "usage": {"type": "duration", "seconds": 0.5}, + } + provider_config: Final = MagicMock() + provider_config.requires_session_configuration.return_value = True + provider_config.transform_realtime_response.return_value = { + "response": completed_event, + "current_output_item_id": None, + "current_response_id": None, + "current_delta_chunks": None, + "current_conversation_id": None, + "current_item_chunks": None, + "current_delta_type": None, + "session_configuration_request": None, + } + provider_config.transform_realtime_request.return_value = () + provider_config.is_setup_message.return_value = False + provider_config.is_content_message.return_value = False + client_ws: Final = MagicMock() + client_ws.send_text = AsyncMock() + backend_ws: Final = MagicMock() + backend_ws.send = AsyncMock() + + streaming: Final = RealTimeStreaming( + client_ws, + backend_ws, + MagicMock(), + provider_config=provider_config, + model="muse-voice-transcribe-1.0", + force_transcription_model="muse-voice-transcribe-1.0", + ) + + await streaming._handle_provider_config_message("{}") + + sent_to_client: Final = [json.loads(call.args[0]) for call in client_ws.send_text.await_args_list] + assert completed_event in sent_to_client + error_events: Final = [event for event in sent_to_client if event.get("type") == "error"] + assert len(error_events) == 1 + assert error_events[0]["error"]["type"] == "guardrail_violation" + backend_ws.send.assert_not_awaited() + assert streaming._violation_count == 1 + + +@pytest.mark.asyncio +async def test_provider_bytes_are_sent_raw_after_pacing(): + from typing import Final + + backend_ws: Final = MagicMock() + backend_ws.send = AsyncMock() + provider_config: Final = MagicMock() + provider_config.requires_session_configuration.return_value = True + provider_config.transform_realtime_request.return_value = (b"\x00\x01", '{"type":"endStream"}') + provider_config.pace_backend_send = AsyncMock() + provider_config.is_setup_message.return_value = False + streaming: Final = RealTimeStreaming( + MagicMock(), + backend_ws, + MagicMock(), + provider_config=provider_config, + model="muse-voice-transcribe-1.0", + ) + + assert await streaming._send_to_backend(json.dumps({"type": "input_audio_buffer.commit"})) is True + + assert [call.args[0] for call in backend_ws.send.await_args_list] == [b"\x00\x01", '{"type":"endStream"}'] + provider_config.pace_backend_send.assert_awaited_once_with(b"\x00\x01") diff --git a/tests/test_litellm/litellm_core_utils/test_streaming_handler.py b/tests/test_litellm/litellm_core_utils/test_streaming_handler.py index 37e2031fdf4..784468c839b 100644 --- a/tests/test_litellm/litellm_core_utils/test_streaming_handler.py +++ b/tests/test_litellm/litellm_core_utils/test_streaming_handler.py @@ -4100,7 +4100,7 @@ async def test_async_streaming_completion_does_not_reset_context_before_iteratio session_id_var.set("") -def test_stream_wrapper_del_restores_correlation_context(): +def test_stream_wrapper_del_restores_correlation_context(monkeypatch): """CustomStreamWrapper.__del__ is the best-effort fallback for an abandoned stream (caller never exhausts it, so the normal terminal-handler restore never fires). Testing this via real garbage collection is unreliable in @@ -4112,6 +4112,7 @@ def test_stream_wrapper_del_restores_correlation_context(): doesn't run actual finalization, and this exercises exactly the logic that real garbage collection would eventually trigger. """ + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace-abandoned") session_id_var.set("outer-session-abandoned") try: @@ -4159,12 +4160,13 @@ def test_stream_wrapper_del_never_raises_with_broken_logging_obj(): wrapper.__del__() # must not raise -def test_stream_wrapper_del_does_not_clobber_a_newer_active_call(): +def test_stream_wrapper_del_does_not_clobber_a_newer_active_call(monkeypatch): """A delayed finalizer must never stomp a different, still-active call's context. If an abandoned stream's __del__ fires late - after a new call has already started in the same Task/thread and claimed the contextvars - unconditionally restoring the abandoned stream's own pre-call snapshot would corrupt the active call's subsequent log lines with stale ids.""" + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace-before-abandoned-call") session_id_var.set("outer-session-before-abandoned-call") try: @@ -4210,13 +4212,14 @@ def test_stream_wrapper_del_does_not_clobber_a_newer_active_call(): session_id_var.set("") -def test_stream_wrapper_del_restores_when_own_session_id_needed_sanitizing(): +def test_stream_wrapper_del_restores_when_own_session_id_needed_sanitizing(monkeypatch): """The __del__ guard must compare against the *sanitized* id actually stored in the contextvar, not the raw litellm_session_id/litellm_trace_id - set_session_id()/set_trace_id() strip control characters before storing, so a caller-supplied id containing e.g. a newline would never equal the raw attribute, and the guard would wrongly conclude some other call has claimed the context and skip cleanup forever.""" + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace-needs-sanitizing") session_id_var.set("outer-session-needs-sanitizing") try: @@ -4250,7 +4253,7 @@ def test_stream_wrapper_del_restores_when_own_session_id_needed_sanitizing(): session_id_var.set("") -def test_stream_wrapper_next_keeps_context_active_through_synthesized_finish_reason_chunk(): +def test_stream_wrapper_next_keeps_context_active_through_synthesized_finish_reason_chunk(monkeypatch): """When the underlying stream ends without ever emitting an explicit finish_reason chunk, __next__ synthesizes one via finish_reason_handler() and returns it. That chunk is still this call's own data - the caller's @@ -4261,6 +4264,7 @@ def test_stream_wrapper_next_keeps_context_active_through_synthesized_finish_rea correct, deterministic restore on the very next __next__() call, since completion_stream is already exhausted and immediately re-raises StopIteration.""" + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace-finish-reason") session_id_var.set("outer-session-finish-reason") try: @@ -4300,12 +4304,13 @@ def test_stream_wrapper_next_keeps_context_active_through_synthesized_finish_rea session_id_var.set("") -def test_stream_wrapper_del_cleans_up_after_synthesized_finish_reason_chunk(): +def test_stream_wrapper_del_cleans_up_after_synthesized_finish_reason_chunk(monkeypatch): """A caller that breaks immediately after seeing finish_reason (the early-break pattern) never triggers the next()-driven restore above - it relies on the best-effort __del__ guard instead, same as any other abandoned stream. The guard must still recognize this call's own (unrestored) ids as unclaimed and clean them up.""" + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace-finish-reason-del") session_id_var.set("outer-session-finish-reason-del") try: @@ -4338,10 +4343,11 @@ def test_stream_wrapper_del_cleans_up_after_synthesized_finish_reason_chunk(): @pytest.mark.asyncio -async def test_stream_wrapper_anext_keeps_context_active_through_synthesized_finish_reason_chunk(): +async def test_stream_wrapper_anext_keeps_context_active_through_synthesized_finish_reason_chunk(monkeypatch): """Async sibling of test_stream_wrapper_next_keeps_context_active_through_synthesized_finish_reason_chunk - _finalize_completed_stream()'s else branch must not restore before returning the synthesized chunk either.""" + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace-anext-finish-reason") session_id_var.set("outer-session-anext-finish-reason") try: @@ -4394,6 +4400,7 @@ async def test_stream_wrapper_anext_max_duration_timeout_restores_consumer_corre path as every other failure so the consumer's outer correlation context gets restored - calling the check before entering __anext__()'s try block would let the Timeout bypass that restoration entirely.""" + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) monkeypatch.setattr(litellm.constants, "LITELLM_MAX_STREAMING_DURATION_SECONDS", 1) trace_id_var.set("outer-trace-max-duration") session_id_var.set("outer-session-max-duration") @@ -4434,12 +4441,13 @@ async def test_stream_wrapper_anext_max_duration_timeout_restores_consumer_corre @pytest.mark.asyncio -async def test_stream_wrapper_aclose_restores_consumer_correlation_context(): +async def test_stream_wrapper_aclose_restores_consumer_correlation_context(monkeypatch): """Explicit early termination (aclose(), e.g. on client disconnect or a router fallback aborting an in-progress stream) must restore the caller's correlation context too - not just __del__'s best-effort GC-timed fallback, since aclose() is normally called deterministically by the consumer/ framework, unlike __del__.""" + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace-aclose") session_id_var.set("outer-session-aclose") try: @@ -4481,6 +4489,7 @@ async def test_stream_wrapper_aclose_keeps_context_active_through_close_failure_ branch logs a debug diagnostic. That log line must still carry the closing stream's own trace_id/session_id - the outer context must not be restored until after the close attempt (and its diagnostic) completes.""" + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace-close-fail") session_id_var.set("outer-session-close-fail") try: @@ -4541,6 +4550,7 @@ def test_handle_stream_fallback_error_restores_context_only_after_exception_mapp mapping. The consumer's outer context must not be restored until that mapping call returns, or the diagnostic log line would carry the outer (or empty) trace_id/session_id instead of the failing stream's own.""" + monkeypatch.setattr(litellm, "request_correlation_in_logs", True) trace_id_var.set("outer-trace-fallback") session_id_var.set("outer-session-fallback") try: diff --git a/tests/test_litellm/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py b/tests/test_litellm/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py index 9fe56f4dc65..7522e9a62e5 100644 --- a/tests/test_litellm/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py +++ b/tests/test_litellm/llms/anthropic/chat/guardrail_translation/test_anthropic_guardrail_handler.py @@ -13,6 +13,7 @@ import pytest from litellm.integrations.custom_guardrail import CustomGuardrail +from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.llms.base_llm.guardrail_translation.base_translation import StreamingScanKey from litellm.llms.anthropic.chat.guardrail_translation.handler import ( AnthropicMessagesHandler, @@ -635,14 +636,19 @@ class TestAnthropicMessagesHandlerInputProcessing: await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) assert guardrail.inputs is not None - assert guardrail.inputs["texts"] == ["safe text", "prohibited correction"] + assert guardrail.inputs["texts"] == [ + "trusted top-level system prompt", + "safe text", + "prohibited correction", + ] structured = guardrail.inputs["structured_messages"] assert [m["role"] for m in structured] == ["system", "user", "system"] assert structured[0]["content"] == "trusted top-level system prompt" + assert data["system"] == "trusted top-level system prompt" assert data["messages"][1]["content"] == "[MASKED]" @pytest.mark.asyncio - async def test_bedrock_masking_slice_is_unavailable_when_top_level_system_is_included( + async def test_bedrock_masking_slice_lines_up_when_top_level_system_is_included( self, ): from litellm.proxy.guardrails.guardrail_hooks.bedrock_guardrails import ( @@ -668,25 +674,25 @@ class TestAnthropicMessagesHandlerInputProcessing: structured = guardrail.inputs["structured_messages"] bedrock = BedrockGuardrail(guardrailIdentifier="gi", guardrailVersion="1") - assert sum(bedrock._count_message_texts(m) for m in structured) == len(texts) + 1 + assert sum(bedrock._count_message_texts(m) for m in structured) == len(texts) latest_user_index = bedrock._find_latest_message_index(structured, target_role="user") - assert ( - bedrock._locate_message_texts_slice( - structured_messages=structured, - target_index=latest_user_index, - texts=texts, - ) - is None - ) - assert ( - bedrock._merge_masked_texts( - masked_texts=["{MASKED}"], - texts=texts, - scanned_slice=None, - scanned_role_subset=True, - ) - == texts + scanned_slice = bedrock._locate_message_texts_slice( + structured_messages=structured, + target_index=latest_user_index, + texts=texts, ) + assert scanned_slice == (3, 1) + assert bedrock._merge_masked_texts( + masked_texts=["{MASKED}"], + texts=texts, + scanned_slice=scanned_slice, + scanned_role_subset=True, + ) == [ + "trusted top-level system prompt", + "safe text", + "prohibited correction", + "{MASKED}", + ] @pytest.mark.asyncio @pytest.mark.parametrize("skip_system_message_in_guardrail", [True, None]) @@ -1611,7 +1617,8 @@ class TestAnthropicMessagesIncrementalScan: ) assert mock_api.call_count == 1 assert [m["content"] for m in mock_api.call_args.kwargs["messages"]] == [ - "What is the capital of France?" + "You are a helpful geography assistant.", + "What is the capital of France?", ] mock_api.reset_mock() await handler.process_input_messages( @@ -2150,6 +2157,213 @@ class TestAnthropicMessagesScanOnlyToolResults: assert guardrail.captured_inputs.get("images") == ["TOOL_IMG"] +class ToolCallArgumentsMaskingGuardrail(InputsRecordingGuardrail): + """Masks the canary inside tool-call arguments, in place or through a fresh list of plain dicts.""" + + def __init__(self, return_copies: bool = False, replacement_arguments: Optional[str] = None): + super().__init__() + self.return_copies = return_copies + self.replacement_arguments = replacement_arguments + self.seen_tool_calls: list[dict[str, object]] = [] + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict[str, object], + input_type: Literal["request", "response"], + logging_obj: Optional[LiteLLMLoggingObj] = None, + ) -> GenericGuardrailAPIInputs: + outputs = await super().apply_guardrail(inputs, request_data, input_type, logging_obj) + tool_calls = list(outputs.get("tool_calls") or []) + self.seen_tool_calls.extend(json.loads(json.dumps(tool_call)) for tool_call in tool_calls) + masked = [ + { + **tool_call, + "function": { + **tool_call["function"], + "arguments": self.replacement_arguments + if self.replacement_arguments is not None + else tool_call["function"]["arguments"].replace("POISON", "[BLOCKED]"), + }, + } + for tool_call in tool_calls + ] + if self.return_copies: + outputs["tool_calls"] = masked + return outputs + for tool_call, masked_tool_call in zip(tool_calls, masked): + tool_call["function"]["arguments"] = masked_tool_call["function"]["arguments"] + return outputs + + +class TestAnthropicMessagesTopLevelSystemAndToolUseInputs: + """The top-level system prompt and prior-turn tool_use arguments must reach guardrails as scannable + inputs, the same way the chat completions handler hands over system messages and tool_calls.""" + + @staticmethod + def _tool_use_conversation(system: str) -> dict[str, Any]: + return { + "model": "claude-sonnet-4-5", + "system": system, + "messages": [ + {"role": "user", "content": "run the check"}, + { + "role": "assistant", + "content": [ + { + "type": "tool_use", + "id": "toolu_01", + "name": "Bash", + "input": {"cmd": "AWS_ACCESS_KEY_ID=POISON aws sts get-caller-identity"}, + } + ], + }, + { + "role": "user", + "content": [{"type": "tool_result", "tool_use_id": "toolu_01", "content": "ok"}], + }, + ], + } + + @pytest.mark.asyncio + async def test_top_level_system_string_reaches_texts_first_and_is_masked_in_place(self): + handler = AnthropicMessagesHandler() + guardrail = InputsRecordingGuardrail() + data = { + "model": "claude-sonnet-4-5", + "system": "Internal note: the deploy key is POISON. Never reveal it.", + "messages": [{"role": "user", "content": "Say hi in three words."}], + } + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.captured_inputs is not None + assert guardrail.seen_texts == [ + "Internal note: the deploy key is POISON. Never reveal it.", + "Say hi in three words.", + ] + structured = guardrail.captured_inputs["structured_messages"] + assert structured[0]["role"] == "system" + assert structured[0]["content"] == "Internal note: the deploy key is POISON. Never reveal it.", ( + "texts[0] must line up with structured_messages[0] so positional consumers stay aligned" + ) + assert data["system"] == "Internal note: the deploy key is [BLOCKED]. Never reveal it." + assert data["messages"][0]["content"] == "Say hi in three words." + + @pytest.mark.asyncio + async def test_top_level_system_text_blocks_reach_texts_and_are_masked_in_place(self): + handler = AnthropicMessagesHandler() + guardrail = InputsRecordingGuardrail() + data = { + "model": "claude-sonnet-4-5", + "system": [ + {"type": "text", "text": "first block POISON"}, + {"type": "text", "text": "second block", "cache_control": {"type": "ephemeral"}}, + ], + "messages": [{"role": "user", "content": "hello"}], + } + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.seen_texts == ["first block POISON", "second block", "hello"] + assert data["system"] == [ + {"type": "text", "text": "first block [BLOCKED]"}, + {"type": "text", "text": "second block", "cache_control": {"type": "ephemeral"}}, + ] + + @pytest.mark.asyncio + async def test_skip_system_message_keeps_the_top_level_system_out(self): + handler = AnthropicMessagesHandler() + guardrail = InputsRecordingGuardrail() + guardrail.skip_system_message_in_guardrail = True + data = { + "model": "claude-sonnet-4-5", + "system": "trusted POISON prompt", + "messages": [{"role": "user", "content": "hello"}], + } + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.seen_texts == ["hello"] + assert data["system"] == "trusted POISON prompt" + + @pytest.mark.asyncio + async def test_prior_turn_tool_use_input_reaches_tool_calls_in_openai_shape(self): + handler = AnthropicMessagesHandler() + guardrail = InputsRecordingGuardrail() + data = self._tool_use_conversation(system="You are a careful agent harness.") + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.captured_inputs is not None + tool_calls = guardrail.captured_inputs.get("tool_calls") + assert tool_calls is not None and len(tool_calls) == 1 + assert tool_calls[0]["id"] == "toolu_01" + assert tool_calls[0]["type"] == "function" + assert tool_calls[0]["function"]["name"] == "Bash" + assert json.loads(tool_calls[0]["function"]["arguments"]) == { + "cmd": "AWS_ACCESS_KEY_ID=POISON aws sts get-caller-identity" + } + assert data["messages"][1]["content"][0]["input"] == { + "cmd": "AWS_ACCESS_KEY_ID=POISON aws sts get-caller-identity" + }, "a guardrail that leaves tool_calls alone must leave the tool_use input alone" + + @pytest.mark.asyncio + @pytest.mark.parametrize("return_copies", [False, True]) + async def test_masked_tool_call_arguments_write_back_into_the_tool_use_input(self, return_copies: bool): + handler = AnthropicMessagesHandler() + guardrail = ToolCallArgumentsMaskingGuardrail(return_copies=return_copies) + data = self._tool_use_conversation(system="You are a careful agent harness.") + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert [tool_call["function"]["name"] for tool_call in guardrail.seen_tool_calls] == ["Bash"] + tool_use = data["messages"][1]["content"][0] + assert tool_use == { + "type": "tool_use", + "id": "toolu_01", + "name": "Bash", + "input": {"cmd": "AWS_ACCESS_KEY_ID=[BLOCKED] aws sts get-caller-identity"}, + } + assert data["messages"][2]["content"][0]["tool_use_id"] == "toolu_01" + + @pytest.mark.asyncio + async def test_non_json_rewritten_arguments_are_rejected_by_name(self): + from litellm.llms.base_llm.guardrail_translation.utils import UnappliableRequestRewrite + + handler = AnthropicMessagesHandler() + guardrail = ToolCallArgumentsMaskingGuardrail(replacement_arguments="[REDACTED]") + data = self._tool_use_conversation(system="Internal note: the deploy key is POISON. Never reveal it.") + data["messages"][2]["content"][0]["content"] = "fetched POISON page" + original = json.loads(json.dumps(data)) + + with pytest.raises(UnappliableRequestRewrite) as excinfo: + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert excinfo.value.guardrail_name == "scan-only-capture" + assert data["system"] == original["system"], "a rejected rewrite must leave the request untouched" + assert data["messages"] == original["messages"], "a rejected rewrite must leave the request untouched" + + @pytest.mark.asyncio + async def test_scan_only_tool_results_keeps_system_and_tool_use_out(self): + handler = AnthropicMessagesHandler() + guardrail = InputsRecordingGuardrail() + guardrail.scan_only_tool_results = True + data = self._tool_use_conversation(system="trusted POISON prompt") + data["messages"][2]["content"][0]["content"] = "fetched POISON page" + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.seen_texts == ["fetched POISON page"] + assert guardrail.captured_inputs is not None + assert guardrail.captured_inputs.get("tool_calls") is None + assert data["system"] == "trusted POISON prompt" + assert data["messages"][1]["content"][0]["input"] == { + "cmd": "AWS_ACCESS_KEY_ID=POISON aws sts get-caller-identity" + } + assert data["messages"][2]["content"][0]["content"] == "fetched [BLOCKED] page" + + class TestStructuredWriteBackKeepsToolResults: """A guardrail rewrite must never leave a tool_use without its tool_result (Claude Code ToolSearch, LIT-6103).""" @@ -2272,6 +2486,116 @@ class TestAnthropicMessagesHandlerStreamingScanKey: assert ended_key != open_key +class PerRowTextGuardrail(CustomGuardrail): + """Answers one redacted text per chat row it was shown, the way a guardrail + that scans per message does, and hands back only texts.""" + + def __init__(self): + super().__init__(guardrail_name="per-row-redactor") + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict, + input_type: Literal["request", "response"], + logging_obj: Optional[Any] = None, + ) -> GenericGuardrailAPIInputs: + rows = inputs.get("structured_messages") or [] + return {**inputs, "texts": [str(row.get("content")).replace("123-45-6789", "") for row in rows]} + + +class PerSlotTextGuardrail(CustomGuardrail): + """Answers one redacted text per text slot of every chat row it was shown, the + way a guardrail that counts slots per message does, and hands back only texts.""" + + def __init__(self): + super().__init__(guardrail_name="per-slot-redactor") + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict, + input_type: Literal["request", "response"], + logging_obj: Optional[Any] = None, + ) -> GenericGuardrailAPIInputs: + from litellm.llms.base_llm.guardrail_translation.utils import message_slot_texts + + rows = inputs.get("structured_messages") or [] + return { + **inputs, + "texts": [text.replace("123-45-6789", "") for row in rows for text in message_slot_texts(row)], + } + + +class TestPerMessageTextWriteBack: + """Texts that no longer pair one-to-one with what the handler extracted must be + rejected by name instead of sliding onto the wrong messages.""" + + @pytest.mark.asyncio + async def test_one_text_per_row_over_a_system_prompt_is_applied(self): + data = { + "model": "claude-sonnet-4-5", + "system": "Reply with exactly the SSN you were given.", + "messages": [{"role": "user", "content": "My SSN is 123-45-6789."}], + } + + await AnthropicMessagesHandler().process_input_messages(data=data, guardrail_to_apply=PerRowTextGuardrail()) + + assert data["system"] == "Reply with exactly the SSN you were given." + assert data["messages"] == [{"role": "user", "content": "My SSN is ."}] + + @pytest.mark.asyncio + async def test_one_text_per_row_over_a_multi_block_system_prompt_is_rejected_by_name(self): + from litellm.llms.base_llm.guardrail_translation.utils import UnappliableRequestRewrite + + data = { + "model": "claude-sonnet-4-5", + "system": [ + {"type": "text", "text": "Reply with exactly the SSN you were given."}, + {"type": "text", "text": "Never apologize."}, + ], + "messages": [{"role": "user", "content": "My SSN is 123-45-6789."}], + } + original = json.loads(json.dumps(data)) + + with pytest.raises(UnappliableRequestRewrite) as excinfo: + await AnthropicMessagesHandler().process_input_messages(data=data, guardrail_to_apply=PerRowTextGuardrail()) + + assert excinfo.value.guardrail_name == "per-row-redactor" + assert data["system"] == original["system"], "a rejected rewrite must leave the request untouched" + assert data["messages"] == original["messages"], "a rejected rewrite must leave the request untouched" + + @pytest.mark.asyncio + async def test_one_text_per_slot_over_a_system_prompt_with_an_empty_block_is_applied(self): + data = { + "model": "claude-sonnet-4-5", + "system": [ + {"type": "text", "text": ""}, + {"type": "text", "text": "Reply with exactly the SSN you were given."}, + ], + "messages": [{"role": "user", "content": "My SSN is 123-45-6789."}], + } + + await AnthropicMessagesHandler().process_input_messages(data=data, guardrail_to_apply=PerSlotTextGuardrail()) + + assert data["system"] == [ + {"type": "text", "text": ""}, + {"type": "text", "text": "Reply with exactly the SSN you were given."}, + ] + assert data["messages"] == [{"role": "user", "content": "My SSN is ."}] + + @pytest.mark.asyncio + async def test_one_text_per_row_without_a_system_prompt_is_applied(self): + data = { + "model": "claude-sonnet-4-5", + "messages": [{"role": "user", "content": "My SSN is 123-45-6789."}], + } + + await AnthropicMessagesHandler().process_input_messages(data=data, guardrail_to_apply=PerRowTextGuardrail()) + + assert data["messages"] == [{"role": "user", "content": "My SSN is ."}] + + class TestAnthropicMessagesHandlerPostCallHookResponse: def test_openai_shaped_stream_assembly_reaches_the_hook_as_a_messages_response(self): from litellm.types.utils import Choices, Message, ModelResponse, Usage diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_mid_stream_error.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_mid_stream_error.py new file mode 100644 index 00000000000..45ec18733f7 --- /dev/null +++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_mid_stream_error.py @@ -0,0 +1,142 @@ +""" +Regression tests for the ``/v1/messages`` async adapter dropping the socket on a +mid-stream provider error. + +When a non-Anthropic model (e.g. Bedrock Converse) is served through +``/v1/messages``, the proxy hands Starlette the async SSE iterator directly. If +the upstream provider stream raises while being pulled (Bedrock raises +``BedrockError`` when a ConverseStream ends without a terminal ``messageStop`` +event, common on cross-region inference profiles), the exception escaped the +request handler's try/except and tore down the connection. Clients like Claude +Code then showed a bare "Connection closed mid-response". + +The async SSE wrapper must instead surface the failure as a well-formed +Anthropic ``error`` event so the stream stays valid and the client can retry. +""" + +import json +import os +import sys +from typing import List, Optional +from unittest.mock import MagicMock + +import pytest + +sys.path.insert(0, os.path.abspath("../../../../..")) + +from litellm.exceptions import MidStreamFallbackError +from litellm.llms.anthropic.experimental_pass_through.adapters.streaming_iterator import ( + AnthropicStreamWrapper, + _mid_stream_error_sse_event, +) +from litellm.llms.bedrock.common_utils import BedrockError +from litellm.types.utils import Delta, StreamingChoices + + +def _make_chunk(delta: Delta, finish_reason: Optional[str] = None) -> MagicMock: + chunk = MagicMock() + chunk.choices = [ + StreamingChoices(finish_reason=finish_reason, index=0, delta=delta, logprobs=None) + ] + chunk.usage = None + chunk._hidden_params = {} + return chunk + + +class _AsyncStreamThenRaise: + """Yields the given chunks, then raises ``exc`` (mimics a provider stream + that terminates mid-response).""" + + def __init__(self, items: List[MagicMock], exc: BaseException): + self._it = iter(items) + self._exc = exc + + def __aiter__(self): + return self + + async def __anext__(self): + try: + return next(self._it) + except StopIteration: + raise self._exc + + +def _parse_sse(raw: bytes) -> tuple[str, dict]: + text = raw.decode() + event_line, data_line = text.strip().split("\n", 1) + return event_line.removeprefix("event: "), json.loads(data_line.removeprefix("data: ")) + + +async def _drain_sse(wrapper: AnthropicStreamWrapper) -> List[bytes]: + return [event async for event in wrapper.async_anthropic_sse_wrapper()] + + +@pytest.mark.asyncio +async def test_mid_stream_bedrock_error_becomes_anthropic_error_event(): + """A ``BedrockError`` raised after partial content must be surfaced as a + terminal Anthropic ``error`` event, not propagated (which drops the socket + and yields "Connection closed mid-response").""" + chunks = [_make_chunk(Delta(content="Creating a file"))] + bedrock_err = BedrockError( + status_code=500, + message="Bedrock ConverseStream ended without a terminal 'messageStop' event", + ) + wrapper = AnthropicStreamWrapper( + completion_stream=_AsyncStreamThenRaise(chunks, bedrock_err), + model="bedrock-converse-sonnet-4-6", + ) + + events = await _drain_sse(wrapper) + + parsed = [_parse_sse(e) for e in events] + event_types = [name for name, _ in parsed] + assert "message_start" in event_types + assert event_types[-1] == "error" + _, error_payload = parsed[-1] + assert error_payload["type"] == "error" + assert error_payload["error"]["type"] == "api_error" + assert "messageStop" in error_payload["error"]["message"] + + +@pytest.mark.asyncio +async def test_mid_stream_error_does_not_raise_out_of_wrapper(): + """The async wrapper must fully drain without letting the upstream exception + escape — escaping is exactly what tore down the connection before the fix.""" + wrapper = AnthropicStreamWrapper( + completion_stream=_AsyncStreamThenRaise([], BedrockError(status_code=500, message="boom")), + model="claude-x", + ) + events = await _drain_sse(wrapper) + assert _parse_sse(events[-1])[0] == "error" + + +@pytest.mark.parametrize( + "status_code, expected_type", + [(500, "api_error"), (529, "overloaded_error"), (429, "rate_limit_error")], +) +def test_error_event_maps_status_code_to_anthropic_type(status_code, expected_type): + raw = _mid_stream_error_sse_event(BedrockError(status_code=status_code, message="upstream failed")) + name, payload = _parse_sse(raw) + assert name == "error" + assert payload["error"]["type"] == expected_type + assert payload["error"]["message"] == "upstream failed" + + +def test_error_event_defaults_to_500_when_status_missing(): + raw = _mid_stream_error_sse_event(ValueError("no status here")) + _, payload = _parse_sse(raw) + assert payload["error"]["type"] == "api_error" + assert payload["error"]["message"] == "no status here" + + +def test_error_event_preserves_midstream_fallback_error(): + exc = MidStreamFallbackError( + message="BedrockException - internalServerException", + model="bedrock-converse-sonnet-4-6", + llm_provider="bedrock", + original_exception=BedrockError(status_code=500, message="internalServerException"), + ) + name, payload = _parse_sse(_mid_stream_error_sse_event(exc)) + assert name == "error" + assert payload["error"]["type"] == "api_error" + assert "internalServerException" in payload["error"]["message"] diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_tool_args.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_tool_args.py index 29e9279731d..a20aaf2e324 100644 --- a/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_tool_args.py +++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_streaming_iterator_tool_args.py @@ -8,6 +8,8 @@ Without the fix, the AnthropicStreamWrapper silently dropped these arguments, causing tool_use blocks to arrive with empty input {}. """ +import json + from typing import List from unittest.mock import MagicMock @@ -139,9 +141,7 @@ async def test_async_stream_emits_input_json_delta_for_bundled_tool_args(): # Verify the delta carries the tool arguments delta_event = events[input_json_delta_idx] - assert delta_event["delta"][ - "partial_json" - ], "input_json_delta should have non-empty partial_json" + assert json.loads(delta_event["delta"]["partial_json"]) == {"location": "Boston"} @pytest.mark.asyncio @@ -300,7 +300,7 @@ def test_sync_stream_emits_input_json_delta_for_bundled_tool_args(): assert ( input_json_delta_idx == tool_start_idx + 1 ), "input_json_delta should immediately follow the tool_use content_block_start" - assert events[input_json_delta_idx]["delta"]["partial_json"] + assert json.loads(events[input_json_delta_idx]["delta"]["partial_json"]) == {"location": "Boston"} def test_sync_stream_no_extra_delta_when_tool_args_empty(): diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py index 01f7a2fb7ab..997a97c6fd3 100644 --- a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py +++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_anthropic_experimental_pass_through_messages_handler.py @@ -1246,7 +1246,7 @@ async def _flush_logging_worker(capture: "_SuccessPayloadCapture") -> None: await asyncio.sleep(0) try: await asyncio.wait_for(GLOBAL_LOGGING_WORKER.flush(), timeout=10.0) - except (asyncio.TimeoutError, RuntimeError): + except asyncio.TimeoutError: pass deadline = asyncio.get_running_loop().time() + 10.0 while not capture.payloads and asyncio.get_running_loop().time() < deadline: diff --git a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_streaming_iterator.py b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_streaming_iterator.py index be33b2ee3b1..8043496f299 100644 --- a/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_streaming_iterator.py +++ b/tests/test_litellm/llms/anthropic/experimental_pass_through/messages/test_streaming_iterator.py @@ -1,6 +1,7 @@ import asyncio import json from datetime import datetime +from unittest.mock import patch import pytest @@ -824,6 +825,174 @@ async def test_async_sse_wrapper_bills_partial_when_detached_drains_disabled(mon assert len(streaming_iterator_module._DETACHED_STREAM_DRAINS) == 0 +class _SuccessRecorder(CustomLogger): + def __init__(self): + super().__init__() + self.success_kwargs: list = [] + + async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): + self.success_kwargs.append(kwargs) + + +def _make_priced_logging_obj(call_id: str, recorder: _SuccessRecorder, model: str) -> LiteLLMLoggingObj: + logging_obj = LiteLLMLoggingObj( + model=model, + messages=[{"role": "user", "content": "hi"}], + stream=True, + call_type="anthropic_messages", + start_time=datetime.now(), + litellm_call_id=call_id, + function_id=call_id, + dynamic_async_success_callbacks=[recorder], + ) + logging_obj.update_environment_variables( + model=model, + user="", + optional_params={}, + litellm_params={"custom_llm_provider": "anthropic"}, + custom_llm_provider="anthropic", + ) + return logging_obj + + +class _UpstreamClosedOnDetach: + """Upstream that yields its events and then, like a socket read, waits until it is closed.""" + + def __init__(self, events: tuple[dict, ...]): + self._events = iter(events) + self._closed = asyncio.Event() + + def __aiter__(self): + return self + + async def __anext__(self) -> dict: + if self._closed.is_set(): + raise StopAsyncIteration + try: + return next(self._events) + except StopIteration: + await self._closed.wait() + raise StopAsyncIteration + + async def aclose(self) -> None: + self._closed.set() + + +@pytest.mark.asyncio +async def test_client_disconnect_partial_billing_prices_recovered_tokens(monkeypatch): + """ + Regression (LIT-6872): a client disconnect that lands on partial billing + re-tokenizes the buffered text into completion_tokens, but the logged cost + stayed priced at the message_start placeholder (1 output token). The success + row's response_cost must match its recovered completion_tokens. + """ + import litellm + from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER + + monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_MAX_DETACHED_STREAM_DRAINS", 0) + monkeypatch.setattr(streaming_iterator_module, "ANTHROPIC_MESSAGES_STREAM_RELAY_QUEUE_MAXSIZE", 4) + model = "claude-sonnet-5" + recorder = _SuccessRecorder() + iterator = BaseAnthropicMessagesStreamingIterator( + litellm_logging_obj=_make_priced_logging_obj("disconnect_partial_cost", recorder, model), + request_body={"model": model, "stream": True}, + ) + sentence = "The history of computing spans centuries of mechanical and electronic invention. " + + async def _stream(): + yield {"type": "message_start", "message": {"id": "msg_1", "usage": {"input_tokens": 29, "output_tokens": 1}}} + yield {"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}} + for _ in range(100): + yield {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": sentence}} + yield {"type": "message_delta", "delta": {"stop_reason": "end_turn"}, "usage": {"output_tokens": 1500}} + yield {"type": "message_stop"} + + enqueued: list = [] + + def _capture(async_coroutine): + enqueued.append(async_coroutine) + + with patch.object( # test-quality-ok: GLOBAL_LOGGING_WORKER is a process-global singleton with no injection seam + GLOBAL_LOGGING_WORKER, "ensure_initialized_and_enqueue", side_effect=_capture + ): + gen = iterator.async_sse_wrapper(_stream()) + for _ in range(4): + await gen.__anext__() + await gen.aclose() + for _ in range(500): + if enqueued: + break + await asyncio.sleep(0.01) + + assert len(enqueued) == 1, "client disconnect never reached partial billing" + await enqueued[0] + + assert len(recorder.success_kwargs) == 1 + logged = recorder.success_kwargs[0]["standard_logging_object"] + assert 1 < logged["completion_tokens"] < 1500 + prompt_cost, completion_cost = litellm.cost_per_token( + model=model, prompt_tokens=29, completion_tokens=logged["completion_tokens"] + ) + assert logged["response_cost"] == pytest.approx(prompt_cost + completion_cost) + + +@pytest.mark.asyncio +async def test_proxy_disconnect_closing_upstream_prices_recovered_tokens(): + """ + Regression (LIT-6872), proxy path: after a client disconnect the proxy's + shielded cleanup closes the upstream stream while the pump is still reading + it, so the pump bills the chunks collected so far without ever seeing + message_delta. That row's response_cost must be priced from its recovered + completion_tokens, not from the message_start placeholder. + """ + import litellm + from litellm.litellm_core_utils.logging_worker import GLOBAL_LOGGING_WORKER + + model = "claude-sonnet-5" + recorder = _SuccessRecorder() + iterator = BaseAnthropicMessagesStreamingIterator( + litellm_logging_obj=_make_priced_logging_obj("disconnect_upstream_closed", recorder, model), + request_body={"model": model, "stream": True}, + ) + sentence = "The history of computing spans centuries of mechanical and electronic invention. " + upstream = _UpstreamClosedOnDetach( + ( + {"type": "message_start", "message": {"id": "msg_1", "usage": {"input_tokens": 29, "output_tokens": 1}}}, + {"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}}, + *({"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": sentence}} for _ in range(6)), + ) + ) + enqueued: list = [] + + def _capture(async_coroutine): + enqueued.append(async_coroutine) + + with patch.object( # test-quality-ok: GLOBAL_LOGGING_WORKER is a process-global singleton with no injection seam + GLOBAL_LOGGING_WORKER, "ensure_initialized_and_enqueue", side_effect=_capture + ): + gen = iterator.async_sse_wrapper(upstream) + for _ in range(4): + await gen.__anext__() + await gen.aclose() + assert not enqueued, "billing must wait for the upstream read to end, not the client detach" + await upstream.aclose() + for _ in range(500): + if enqueued: + break + await asyncio.sleep(0.01) + + assert len(enqueued) == 1, "closing the upstream never reached partial billing" + await enqueued[0] + + assert len(recorder.success_kwargs) == 1 + logged = recorder.success_kwargs[0]["standard_logging_object"] + assert logged["completion_tokens"] > 1 + prompt_cost, completion_cost = litellm.cost_per_token( + model=model, prompt_tokens=29, completion_tokens=logged["completion_tokens"] + ) + assert logged["response_cost"] == pytest.approx(prompt_cost + completion_cost) + + @pytest.mark.asyncio async def test_async_sse_wrapper_aborts_upstream_when_detached_drain_cap_reached(monkeypatch): """ diff --git a/tests/test_litellm/llms/anthropic/test_anthropic_prompt_cache_prediction.py b/tests/test_litellm/llms/anthropic/test_anthropic_prompt_cache_prediction.py new file mode 100644 index 00000000000..2b36866a1a0 --- /dev/null +++ b/tests/test_litellm/llms/anthropic/test_anthropic_prompt_cache_prediction.py @@ -0,0 +1,209 @@ +import json +from collections.abc import Mapping +from datetime import datetime +from types import SimpleNamespace +from typing import Final + +import httpx +import pytest +import respx +from pydantic import JsonValue + +import litellm +from litellm.caching.dual_cache import DualCache +from litellm.caching.llm_caching_handler import LLMClientCache +from litellm.llms.anthropic.count_tokens import handler as count_handler +from litellm.llms.anthropic.experimental_pass_through.messages.transformation import DEFAULT_ANTHROPIC_API_VERSION +from litellm.llms.anthropic.prompt_cache_prediction import ( + NativePredictionTarget, + cache_scope, + count_prompt_tokens, + parse_observed_cache, + parse_prompt, + resolve_prediction_target, + supported_prediction_headers, +) +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler +from litellm.models.credentials import CredentialItem +from litellm.proxy import proxy_server +from litellm.proxy.hooks.prompt_cache_prediction import PromptCacheObserver, lookup +from litellm.proxy.management_endpoints.prompt_cache_prediction import predict_arm +from litellm.proxy.utils import InternalUsageCache +from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo +from litellm.types.utils import CacheCreationTokenDetails, ModelResponse, PromptTokensDetailsWrapper, Usage + +_MODEL: Final = "claude-sonnet-5" +_KEY: Final = "test-provider-key" +_CALLER: Final = "test-caller-hash" +_DEPLOYMENT: Final = "test-native-deployment" + + +def _body() -> dict[str, JsonValue]: + return { + "model": _MODEL, + "system": "Keep this context", + "tools": [{"name": "lookup", "input_schema": {"type": "object"}}], + "messages": [{"role": "user", "content": [ + {"type": "text", "text": "A cacheable prefix", "cache_control": {"type": "ephemeral"}} + ]}], + } + + +@pytest.mark.parametrize("version", [None, "2099-01-01", DEFAULT_ANTHROPIC_API_VERSION]) +@pytest.mark.asyncio +async def test_observer_records_only_version_supported_by_token_counter(version: str | None) -> None: + cache: Final = DualCache() + observer: Final = PromptCacheObserver(InternalUsageCache(dual_cache=cache), clock=lambda: 1010.0) + body: Final = _body() + prefix: Final = parse_prompt(body) + assert prefix is not None + headers: Final = {"x-api-key": _KEY, **({"anthropic-version": version} if version is not None else {})} + wire: Final = httpx.Request("POST", "https://api.anthropic.com/v1/messages", headers=headers, json=body) + response: Final = ModelResponse( + model=_MODEL, + usage=Usage( + prompt_tokens=311, + completion_tokens=2, + total_tokens=313, + prompt_tokens_details=PromptTokensDetailsWrapper( + cached_tokens=100, + cache_creation_tokens=200, + cache_creation_token_details=CacheCreationTokenDetails( + ephemeral_5m_input_tokens=200, ephemeral_1h_input_tokens=0 + ), + ), + ), + ) + await observer.async_log_success_event( + { + "call_type": "anthropic_messages", + "custom_llm_provider": "anthropic", + "httpx_response": httpx.Response(200, request=wire), + "first_api_call_start_time": datetime.fromtimestamp(1000.0), + "standard_logging_object": { + "status": "success", "model_id": _DEPLOYMENT, + "metadata": {"user_api_key_hash": _CALLER}, + }, + }, + response, + datetime.fromtimestamp(1010.0), + datetime.fromtimestamp(1010.0), + ) + default_scope: Final = cache_scope(_CALLER, _DEPLOYMENT, _KEY, _MODEL) + found: Final = await lookup(cache, default_scope, prefix, now=1010.0) + assert (found is not None) == (version == DEFAULT_ANTHROPIC_API_VERSION) + if version != DEFAULT_ANTHROPIC_API_VERSION: + other_scope: Final = cache_scope(_CALLER, _DEPLOYMENT, _KEY, _MODEL, version or "") + assert await lookup(cache, other_scope, prefix, now=1010.0) is None + + +@pytest.mark.parametrize("headers, supported", [ + ({}, True), + ({"Anthropic-Version": DEFAULT_ANTHROPIC_API_VERSION}, True), + ({"anthropic-version": "2099-01-01"}, False), + ({"Anthropic-Beta": ""}, False), + ({"anthropic-beta": "future-feature"}, False), +]) +def test_prediction_header_eligibility(headers: Mapping[str, str], supported: bool) -> None: + assert supported_prediction_headers(headers) is supported + + +@pytest.mark.asyncio +async def test_provider_count_uses_same_version_and_preserves_native_input(monkeypatch: pytest.MonkeyPatch) -> None: + body: Final = _body() + requests: Final[list[httpx.Request]] = [] + + def provider(request: httpx.Request) -> httpx.Response: + requests.append(request) + return httpx.Response(200, json={"input_tokens": 311}) + + client: Final = AsyncHTTPHandler() + await client.client.aclose() + client.client = httpx.AsyncClient(transport=httpx.MockTransport(provider)) + monkeypatch.setattr(count_handler, "get_async_httpx_client", lambda **kwargs: client) + try: + assert await count_prompt_tokens(_MODEL, _KEY, body) == 311 + finally: + await client.client.aclose() + assert len(requests) == 1 + assert requests[0].headers["anthropic-version"] == DEFAULT_ANTHROPIC_API_VERSION + assert requests[0].url == "https://api.anthropic.com/v1/messages/count_tokens" + assert json.loads(requests[0].content) == body + + +@pytest.mark.parametrize("source", ["static", "database"]) +@pytest.mark.asyncio +async def test_environment_credential_matches_native_count_and_observed_scope( + source: str, monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setenv("LIT7658_PROVIDER_KEY", _KEY) + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + monkeypatch.setattr(litellm, "in_memory_llm_clients_cache", LLMClientCache()) + params: Final = { + "model": f"anthropic/{_MODEL}", "api_key": "os.environ/LIT7658_PROVIDER_KEY", + "api_base": "https://api.anthropic.com", + } + router: Final = litellm.Router(model_list=[{ + "model_name": "test-native", "litellm_params": dict(params), "model_info": {"id": _DEPLOYMENT}, + }] if source == "static" else [], num_retries=0) + if source == "database": + monkeypatch.setattr(proxy_server, "llm_router", router) + assert proxy_server.ProxyConfig()._add_deployment([SimpleNamespace( + model_id=_DEPLOYMENT, model_name="test-native", model_info={}, litellm_params=dict(params), + )]) == 1 + deployment: Final = router.get_deployment(_DEPLOYMENT) + assert deployment is not None + target: Final = resolve_prediction_target(deployment.litellm_params) + assert isinstance(target, NativePredictionTarget) + body: Final = _body() + with respx.mock() as upstream: + native: Final = upstream.post("https://api.anthropic.com/v1/messages").respond(200, json={ + "id": "msg_test", "type": "message", "role": "assistant", "model": _MODEL, + "content": [{"type": "text", "text": "Hello"}], "stop_reason": "end_turn", "stop_sequence": None, + "usage": {"input_tokens": 11, "output_tokens": 1, "cache_read_input_tokens": 300}, + }) + counter: Final = upstream.post("https://api.anthropic.com/v1/messages/count_tokens").respond( + 200, json={"input_tokens": 311}, + ) + await router.aanthropic_messages( + model="test-native", max_tokens=1, **{key: value for key, value in body.items() if key != "model"}, + ) + assert await count_prompt_tokens(target.model, target.api_key, body) == 311 + assert native.call_count == counter.call_count == 1 + assert native.calls.last.request.headers["x-api-key"] == counter.calls.last.request.headers["x-api-key"] == _KEY + observed: Final = parse_observed_cache(native.calls.last.request, ModelResponse( + model=_MODEL, usage=Usage( + prompt_tokens=311, completion_tokens=1, total_tokens=312, + prompt_tokens_details=PromptTokensDetailsWrapper(cached_tokens=300), + ), + ), _CALLER, _DEPLOYMENT) + assert observed is not None + assert observed.scope == cache_scope(_CALLER, _DEPLOYMENT, target.api_key, target.model) + + +@pytest.mark.parametrize("inline_key", [None, _KEY]) +@pytest.mark.asyncio +async def test_named_credential_is_explicitly_unsupported_before_count( + inline_key: str | None, monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setattr(litellm, "credential_list", [CredentialItem( + credential_name="test-named", credential_info={}, credential_values={"api_key": "test-named-provider-key"}, + )]) + deployment: Final = Deployment( + model_name="test-native", + litellm_params=LiteLLM_Params( + model=f"anthropic/{_MODEL}", api_key=inline_key, litellm_credential_name="test-named", + ), + model_info=ModelInfo(id=_DEPLOYMENT), + ) + body: Final = _body() + prefix: Final = parse_prompt(body) + assert prefix is not None + + async def count(model: str, api_key: str, body: Mapping[str, JsonValue]) -> int | None: + pytest.fail("Unsupported named credentials must not reach provider counting") + + arm: Final = await predict_arm(deployment, body, prefix, _CALLER, DualCache(), count) + assert arm.cache_state == "unknown" + assert arm.reason == "unsupported_deployment_configuration" + assert arm.estimate is None and arm.cold is None and arm.warm is None diff --git a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py index 3b01a4f2054..c609455f3d8 100644 --- a/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py +++ b/tests/test_litellm/llms/bedrock/files/test_bedrock_files_transformation.py @@ -1948,11 +1948,13 @@ class TestBedrockFileDeletion: def test_delete_rejects_untrusted_objects_before_signing( self, file_id: str, message: str, monkeypatch: pytest.MonkeyPatch ) -> None: + from litellm.llms.bedrock.common_utils import BedrockError from litellm.llms.bedrock.files.transformation import BedrockFilesConfig monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") - with pytest.raises(ValueError, match=message): + with pytest.raises(BedrockError, match=message) as rejection: BedrockFilesConfig().transform_delete_file_request(file_id=file_id, optional_params={}, litellm_params={}) + assert rejection.value.status_code == 400 class TestBedrockFileContentTransformation: @@ -2030,11 +2032,12 @@ class TestBedrockFileContentTransformation: assert url == self.EXPECTED_URL def test_transform_file_content_request_rejects_foreign_bucket(self, monkeypatch): + from litellm.llms.bedrock.common_utils import BedrockError from litellm.llms.bedrock.files.transformation import BedrockFilesConfig monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") - with pytest.raises(ValueError, match="configured storage bucket"): + with pytest.raises(BedrockError, match="configured storage bucket") as rejection: BedrockFilesConfig().transform_file_content_request( file_content_request={ "file_id": "s3://other-bucket/litellm-batch-outputs/job/x.jsonl.out" @@ -2043,18 +2046,25 @@ class TestBedrockFileContentTransformation: litellm_params=self._litellm_params(), ) + assert rejection.value.status_code == 400 + + def test_transform_file_content_request_rejects_unmanaged_key(self, monkeypatch): + from litellm.llms.bedrock.common_utils import BedrockError from litellm.llms.bedrock.files.transformation import BedrockFilesConfig monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") - with pytest.raises(ValueError, match="LiteLLM-managed"): + with pytest.raises(BedrockError, match="LiteLLM-managed") as rejection: BedrockFilesConfig().transform_file_content_request( file_content_request={"file_id": "s3://my-bucket/private/x.jsonl"}, optional_params={}, litellm_params=self._litellm_params(), ) + assert rejection.value.status_code == 400 + + def test_extract_s3_uri_rejects_non_managed_file_id(self): """A file id that is neither an s3:// URI nor a unified id must be rejected.""" from litellm.llms.bedrock.files.transformation import ( @@ -2183,12 +2193,13 @@ class TestBedrockFileContentTransformation: def test_rejects_bucket_outside_input_and_output(self, monkeypatch): """A file id whose bucket is neither the input nor the output bucket is still rejected (SSRF / bucket-confusion guard).""" + from litellm.llms.bedrock.common_utils import BedrockError from litellm.llms.bedrock.files.transformation import BedrockFilesConfig monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) - with pytest.raises(ValueError, match="configured storage bucket"): + with pytest.raises(BedrockError, match="configured storage bucket") as rejection: BedrockFilesConfig().transform_file_content_request( file_content_request={ "file_id": "s3://other-bucket/litellm-batch-outputs/job/x.jsonl.out" @@ -2199,6 +2210,9 @@ class TestBedrockFileContentTransformation: ), ) + assert rejection.value.status_code == 400 + + def test_sign_request_without_botocore_raises_helpful_error(self, monkeypatch): """A missing botocore must surface an actionable 'install boto3' error rather than a raw import failure.""" @@ -2605,6 +2619,7 @@ def test_sign_s3_request_without_body_assumes_role_with_external_id(monkeypatch) with patch.object(boto3, "client", return_value=FakeSTSClient()): signed_headers = BedrockFilesConfig()._sign_s3_request_without_body( + method="GET", api_base="https://s3.us-east-1.amazonaws.com/safe-bucket/litellm-bedrock-files-model-id-abc.jsonl", aws_region_name="us-east-1", request_params=request_params, @@ -2612,3 +2627,1058 @@ def test_sign_s3_request_without_body_assumes_role_with_external_id(monkeypatch) authorization = {key.lower(): value for key, value in signed_headers.items()}["authorization"] assert "ASIAFILESGETROLE" in authorization + + +def _s3_signature_for(method: str, url: str, headers: Mapping[str, str]) -> str: + sent = {name.lower(): value for name, value in headers.items()} + signed_names = sent["authorization"].split("SignedHeaders=")[1].split(",")[0].split(";") + request = AWSRequest( + method=method, + url=url, + headers={name: sent[name] for name in signed_names if name in sent}, + ) + request.context["timestamp"] = sent["x-amz-date"] + signer = S3SigV4Auth(Credentials("AKIAEXAMPLE", "secret"), "s3", "us-west-2") + return signer.signature(signer.string_to_sign(request, signer.canonical_request(request)), request) + + +def _sent_signature(headers: Mapping[str, str]) -> str: + authorization = {name.lower(): value for name, value in headers.items()}["authorization"] + return authorization.split("Signature=")[1].strip() + + +def _bedrock_s3_params() -> dict: + return { + "aws_access_key_id": "AKIAEXAMPLE", + "aws_secret_access_key": "secret", + "aws_region_name": "us-west-2", + } + + +def _trusted_bucket_snapshot(**deployment_litellm_params) -> dict: + from types import MappingProxyType + + from litellm.types.router import CredentialLiteLLMParams + + snapshot = CredentialLiteLLMParams(**deployment_litellm_params).model_dump(exclude_none=True) + return {**_bedrock_s3_params(), "_litellm_internal_model_credentials": MappingProxyType(snapshot)} + + +class TestBedrockFileDeletionTransformation: + """SigV4-signed S3 DeleteObject for LiteLLM-managed Bedrock batch files.""" + + S3_URI = "s3://my-bucket/litellm-bedrock-files/job-123/input.jsonl" + EXPECTED_URL = "https://s3.us-west-2.amazonaws.com/my-bucket/litellm-bedrock-files/job-123/input.jsonl" + + def test_transform_delete_file_request_signs_s3_delete(self, monkeypatch): + import hashlib + + from litellm.llms.bedrock.files.transformation import ( + S3_SIGNED_REQUEST_HEADERS_PARAM, + BedrockFilesConfig, + ) + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + litellm_params = _bedrock_s3_params() + + url, params = BedrockFilesConfig().transform_delete_file_request( + file_id=self.S3_URI, + optional_params={}, + litellm_params=litellm_params, + ) + + assert url == self.EXPECTED_URL + assert params == {} + signed_headers = litellm_params[S3_SIGNED_REQUEST_HEADERS_PARAM] + lowered = {name.lower(): value for name, value in signed_headers.items()} + assert lowered["x-amz-content-sha256"] == hashlib.sha256(b"").hexdigest() + assert "/us-west-2/s3/aws4_request" in lowered["authorization"] + assert _sent_signature(signed_headers) == _s3_signature_for("DELETE", url, signed_headers) + + def test_transform_delete_file_request_decodes_unified_file_id(self, monkeypatch): + import base64 + + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + from litellm.types.utils import SpecialEnums + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + unified_file_id = SpecialEnums.LITELLM_MANAGED_FILE_COMPLETE_STR.value.format( + "application/json", "unified-id", "", self.S3_URI, "model-id" + ) + encoded_file_id = base64.urlsafe_b64encode(unified_file_id.encode()).decode().rstrip("=") + litellm_params = _bedrock_s3_params() + + url, _ = BedrockFilesConfig().transform_delete_file_request( + file_id=encoded_file_id, + optional_params={}, + litellm_params=litellm_params, + ) + + assert url == self.EXPECTED_URL + + def test_transform_delete_file_request_uses_trusted_snapshot_bucket(self, monkeypatch): + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + + url, _ = BedrockFilesConfig().transform_delete_file_request( + file_id=self.S3_URI, + optional_params={}, + litellm_params=_trusted_bucket_snapshot(s3_bucket_name="my-bucket"), + ) + + assert url == self.EXPECTED_URL + + def test_transform_delete_file_request_rejects_foreign_bucket(self, monkeypatch): + from litellm.llms.bedrock.common_utils import BedrockError + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + with pytest.raises(BedrockError, match="configured storage bucket") as rejection: + BedrockFilesConfig().transform_delete_file_request( + file_id="s3://other-bucket/litellm-bedrock-files/job-123/input.jsonl", + optional_params={}, + litellm_params=_bedrock_s3_params(), + ) + + assert rejection.value.status_code == 400 + + + def test_transform_delete_file_request_rejects_unmanaged_key(self, monkeypatch): + from litellm.llms.bedrock.common_utils import BedrockError + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + with pytest.raises(BedrockError, match="LiteLLM-managed") as rejection: + BedrockFilesConfig().transform_delete_file_request( + file_id="s3://my-bucket/private/x.jsonl", + optional_params={}, + litellm_params=_bedrock_s3_params(), + ) + + assert rejection.value.status_code == 400 + + + def test_transform_delete_file_response_echoes_the_deleted_id(self): + import httpx + + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + deleted = BedrockFilesConfig().transform_delete_file_response( + raw_response=httpx.Response(204), + logging_obj=MagicMock(model_call_details={"additional_args": {"file_id": self.S3_URI}}), + litellm_params={}, + ) + + assert deleted.id == self.S3_URI + assert deleted.deleted is True + assert deleted.object == "file" + + def test_transform_delete_file_response_raises_on_s3_error(self): + import httpx + + from litellm.llms.bedrock.common_utils import BedrockError + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + with pytest.raises(BedrockError) as excinfo: + BedrockFilesConfig().transform_delete_file_response( + raw_response=httpx.Response(403, text="AccessDenied"), + logging_obj=MagicMock(), + litellm_params={}, + ) + + assert excinfo.value.status_code == 403 + + def test_file_delete_end_to_end_sends_signed_delete(self, monkeypatch): + import httpx + import respx + + import litellm + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + with respx.mock: + route = respx.delete(self.EXPECTED_URL).mock(return_value=httpx.Response(204)) + + response = litellm.file_delete( + file_id=self.S3_URI, + custom_llm_provider="bedrock", + **_bedrock_s3_params(), + ) + + assert route.called + request = route.calls[0].request + assert request.headers["Authorization"].startswith("AWS4-HMAC-SHA256") + assert _sent_signature(request.headers) == _s3_signature_for("DELETE", str(request.url), request.headers) + assert response.id == self.S3_URI + assert response.deleted is True + + @pytest.mark.asyncio + async def test_afile_delete_end_to_end_sends_signed_delete(self, monkeypatch): + import httpx + import respx + + import litellm + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + litellm.in_memory_llm_clients_cache.flush_cache() + + with respx.mock: + route = respx.delete(self.EXPECTED_URL).mock(return_value=httpx.Response(204)) + + response = await litellm.afile_delete( + file_id=self.S3_URI, + custom_llm_provider="bedrock", + **_bedrock_s3_params(), + ) + + assert route.called + request = route.calls[0].request + assert _sent_signature(request.headers) == _s3_signature_for("DELETE", str(request.url), request.headers) + assert response.id == self.S3_URI + assert response.deleted is True + + def test_file_delete_end_to_end_answers_400_for_a_foreign_bucket(self, monkeypatch): + import respx + + import litellm + from litellm.llms.bedrock.common_utils import BedrockError + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + with respx.mock, pytest.raises(BedrockError) as rejection: + litellm.file_delete( + file_id="s3://other-bucket/litellm-bedrock-files/job-123/input.jsonl", + custom_llm_provider="bedrock", + **_bedrock_s3_params(), + ) + + assert rejection.value.status_code == 400 + assert "configured storage bucket" in rejection.value.message + + def test_file_delete_end_to_end_answers_400_for_a_non_managed_id(self, monkeypatch): + import respx + + import litellm + from litellm.llms.bedrock.common_utils import BedrockError + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + with respx.mock, pytest.raises(BedrockError) as rejection: + litellm.file_delete(file_id="file-1234567890", custom_llm_provider="bedrock", **_bedrock_s3_params()) + + assert rejection.value.status_code == 400 + assert "managed LiteLLM S3 file id" in rejection.value.message + + def test_file_delete_end_to_end_surfaces_the_s3_error_body(self, monkeypatch): + import httpx + import respx + + import litellm + from litellm.llms.bedrock.common_utils import BedrockError + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + with respx.mock: + respx.delete(self.EXPECTED_URL).mock( + return_value=httpx.Response(403, text="AccessDenied") + ) + with pytest.raises(BedrockError) as denied: + litellm.file_delete(file_id=self.S3_URI, custom_llm_provider="bedrock", **_bedrock_s3_params()) + + assert denied.value.status_code == 403 + assert "AccessDenied" in denied.value.message + + +class TestBedrockFileListTransformation: + """SigV4-signed S3 ListObjectsV2 over the LiteLLM-managed key prefixes.""" + + BUCKET_URL = "https://s3.us-west-2.amazonaws.com/my-bucket/" + MANAGED_QUERY = {"list-type": "2", "prefix": "litellm-b"} + BATCH_QUERY = {"list-type": "2", "prefix": "litellm-bedrock-files"} + OUTPUT_QUERY = {"list-type": "2", "prefix": "litellm-batch-outputs/"} + OUTPUT_BUCKET_URL = "https://s3.us-west-2.amazonaws.com/my-output-bucket/" + OUTPUT_BUCKET_LISTING = b""" + + my-output-bucket + litellm-batch-outputs/ + + litellm-batch-outputs/job-9/input.jsonl.out + 2026-09-04T08:00:00.000Z + 70 + +""" + OUTPUT_BUCKET_ID = "s3://my-output-bucket/litellm-batch-outputs/job-9/input.jsonl.out" + LISTING = b""" + + my-bucket + litellm-b + 4 + false + + litellm-bedrock-files-model-abc.jsonl + 2026-09-01T10:00:00.000Z + 120 + + + litellm-bedrock-files/job-123/input.jsonl + 2026-09-02T11:30:00.000Z + 340 + + + litellm-batch-outputs/job-123/input.jsonl.out + 2026-09-03T12:45:00.000Z + 560 + + + litellm-bogus/other.jsonl + 2026-09-03T12:45:00.000Z + 1 + +""" + BATCH_IDS = ( + "s3://my-bucket/litellm-bedrock-files-model-abc.jsonl", + "s3://my-bucket/litellm-bedrock-files/job-123/input.jsonl", + ) + OUTPUT_ID = "s3://my-bucket/litellm-batch-outputs/job-123/input.jsonl.out" + CONTINUATION_TOKEN = "1ueGcxLPRx1Tr/XYExHnhbYLgveDs2J/wm36Hy4vbOwM=" + FIRST_PAGE = b""" + + my-bucket + litellm-bedrock-files + 1 + 1 + true + 1ueGcxLPRx1Tr/XYExHnhbYLgveDs2J/wm36Hy4vbOwM= + + litellm-bedrock-files/job-1/input.jsonl + 2026-09-01T10:00:00.000Z + 10 + +""" + LAST_PAGE = b""" + + my-bucket + litellm-bedrock-files + 1 + 1 + false + 1ueGcxLPRx1Tr/XYExHnhbYLgveDs2J/wm36Hy4vbOwM= + + litellm-bedrock-files/job-2/input.jsonl + 2026-09-02T10:00:00.000Z + 20 + +""" + PAGED_IDS = ( + "s3://my-bucket/litellm-bedrock-files/job-1/input.jsonl", + "s3://my-bucket/litellm-bedrock-files/job-2/input.jsonl", + ) + + def test_transform_list_files_request_signs_managed_prefix_listing(self, monkeypatch): + from litellm.llms.bedrock.files.transformation import ( + LIST_FILES_PURPOSE_PARAM, + S3_SIGNED_REQUEST_HEADERS_PARAM, + BedrockFilesConfig, + ) + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + litellm_params = _bedrock_s3_params() + + url, params = BedrockFilesConfig().transform_list_files_request( + purpose="batch", + optional_params={}, + litellm_params=litellm_params, + ) + + assert url == self.BUCKET_URL + assert params == self.BATCH_QUERY + signed_headers = litellm_params[S3_SIGNED_REQUEST_HEADERS_PARAM] + assert _sent_signature(signed_headers) == _s3_signature_for( + "GET", f"{url}?list-type=2&prefix=litellm-bedrock-files", signed_headers + ) + assert litellm_params[LIST_FILES_PURPOSE_PARAM] == "batch" + + def test_transform_list_files_request_scopes_to_configured_prefix(self, monkeypatch): + from litellm.llms.bedrock.files.transformation import ( + S3_SIGNED_REQUEST_HEADERS_PARAM, + BedrockFilesConfig, + ) + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket/LLM AI Projects") + litellm_params = _bedrock_s3_params() + + url, params = BedrockFilesConfig().transform_list_files_request( + purpose=None, + optional_params={}, + litellm_params=litellm_params, + ) + + assert url == self.BUCKET_URL + assert params == {"list-type": "2", "prefix": "LLM AI Projects/litellm-b"} + signed_headers = litellm_params[S3_SIGNED_REQUEST_HEADERS_PARAM] + assert _sent_signature(signed_headers) == _s3_signature_for( + "GET", f"{url}?list-type=2&prefix=LLM%20AI%20Projects%2Flitellm-b", signed_headers + ) + + def test_transform_list_files_request_uses_trusted_snapshot_bucket(self, monkeypatch): + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + + url, params = BedrockFilesConfig().transform_list_files_request( + purpose=None, + optional_params={}, + litellm_params=_trusted_bucket_snapshot(s3_bucket_name="my-bucket"), + ) + + assert url == self.BUCKET_URL + assert params == self.MANAGED_QUERY + + def _list_response(self, purpose: str | None, listing: bytes | None = None, status_code: int = 200): + import httpx + + from litellm.llms.bedrock.files.transformation import ( + LIST_FILES_PURPOSE_PARAM, + BedrockFilesConfig, + ) + + return BedrockFilesConfig().transform_list_files_response( + raw_response=httpx.Response(status_code, content=listing if listing is not None else self.LISTING), + logging_obj=MagicMock(), + litellm_params={**_bedrock_s3_params(), LIST_FILES_PURPOSE_PARAM: purpose}, + ) + + def test_transform_list_files_response_maps_managed_objects(self, monkeypatch): + from datetime import datetime, timezone + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + files = self._list_response(purpose=None) + + assert [file.id for file in files] == [*self.BATCH_IDS, self.OUTPUT_ID] + assert [file.purpose for file in files] == ["batch", "batch", "batch_output"] + assert [file.bytes for file in files] == [120, 340, 560] + assert [file.filename for file in files] == [ + "litellm-bedrock-files-model-abc.jsonl", + "input.jsonl", + "input.jsonl.out", + ] + assert files[1].created_at == int(datetime(2026, 9, 2, 11, 30, tzinfo=timezone.utc).timestamp()) + assert {file.object for file in files} == {"file"} + assert {file.status for file in files} == {"uploaded"} + + def test_transform_list_files_response_filters_by_purpose(self, monkeypatch): + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + assert [file.id for file in self._list_response(purpose="batch")] == list(self.BATCH_IDS) + assert [file.id for file in self._list_response(purpose="batch_output")] == [self.OUTPUT_ID] + + def test_transform_list_files_response_scopes_to_configured_prefix(self, monkeypatch): + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket/team-a") + listing = b""" + + my-bucket + team-a/litellm-bedrock-files/job-1/input.jsonl10 + team-a/litellm-batch-outputs/job-1/input.jsonl.out20 + litellm-bedrock-files/job-2/input.jsonl30 +""" + + files = self._list_response(purpose=None, listing=listing) + + assert [(file.id, file.purpose) for file in files] == [ + ("s3://my-bucket/team-a/litellm-bedrock-files/job-1/input.jsonl", "batch"), + ("s3://my-bucket/team-a/litellm-batch-outputs/job-1/input.jsonl.out", "batch_output"), + ] + + def test_transform_list_files_response_raises_on_s3_error(self, monkeypatch): + from litellm.llms.bedrock.common_utils import BedrockError + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + with pytest.raises(BedrockError) as excinfo: + self._list_response(purpose=None, listing=b"AccessDenied", status_code=403) + + assert excinfo.value.status_code == 403 + + def test_file_list_end_to_end_sends_signed_listing(self, monkeypatch): + import httpx + import respx + + import litellm + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + with respx.mock: + route = respx.get(self.BUCKET_URL, params__contains=self.BATCH_QUERY).mock( + return_value=httpx.Response(200, content=self.LISTING) + ) + + files = litellm.file_list(custom_llm_provider="bedrock", purpose="batch", **_bedrock_s3_params()) + + assert route.called + request = route.calls[0].request + assert request.headers["Authorization"].startswith("AWS4-HMAC-SHA256") + assert _sent_signature(request.headers) == _s3_signature_for("GET", str(request.url), request.headers) + assert [file.id for file in files] == list(self.BATCH_IDS) + + def test_file_list_uses_trusted_snapshot_bucket_without_env(self, monkeypatch): + import httpx + import respx + + import litellm + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + + with respx.mock: + route = respx.get(self.BUCKET_URL, params__contains=self.MANAGED_QUERY).mock( + return_value=httpx.Response(200, content=self.LISTING) + ) + + files = litellm.file_list( + custom_llm_provider="bedrock", + **_trusted_bucket_snapshot(s3_bucket_name="my-bucket"), + ) + + assert route.called + assert [file.id for file in files] == [*self.BATCH_IDS, self.OUTPUT_ID] + + @pytest.mark.asyncio + async def test_afile_list_end_to_end_sends_signed_listing(self, monkeypatch): + import httpx + import respx + + import litellm + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + litellm.in_memory_llm_clients_cache.flush_cache() + + with respx.mock: + route = respx.get(self.BUCKET_URL, params__contains=self.OUTPUT_QUERY).mock( + return_value=httpx.Response(200, content=self.LISTING) + ) + + files = await litellm.afile_list( + custom_llm_provider="bedrock", purpose="batch_output", **_bedrock_s3_params() + ) + + assert route.called + request = route.calls[0].request + assert _sent_signature(request.headers) == _s3_signature_for("GET", str(request.url), request.headers) + assert [file.id for file in files] == [self.OUTPUT_ID] + + def test_transform_list_files_request_narrows_prefix_to_requested_purpose(self, monkeypatch): + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + + batch_url, batch_params = BedrockFilesConfig().transform_list_files_request( + purpose="batch", optional_params={}, litellm_params=_bedrock_s3_params() + ) + output_url, output_params = BedrockFilesConfig().transform_list_files_request( + purpose="batch_output", optional_params={}, litellm_params=_bedrock_s3_params() + ) + + assert (batch_url, batch_params) == (self.BUCKET_URL, self.BATCH_QUERY) + assert (output_url, output_params) == (self.BUCKET_URL, self.OUTPUT_QUERY) + + def test_transform_list_files_request_lists_configured_output_bucket_for_batch_output(self, monkeypatch): + from litellm.llms.bedrock.files.transformation import ( + S3_SIGNED_REQUEST_HEADERS_PARAM, + BedrockFilesConfig, + ) + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + litellm_params = _trusted_bucket_snapshot( + s3_bucket_name="my-bucket", s3_output_bucket_name="my-output-bucket/team-a" + ) + + url, params = BedrockFilesConfig().transform_list_files_request( + purpose="batch_output", optional_params={}, litellm_params=litellm_params + ) + signed_headers = litellm_params[S3_SIGNED_REQUEST_HEADERS_PARAM] + input_url, input_params = BedrockFilesConfig().transform_list_files_request( + purpose="batch", optional_params={}, litellm_params=dict(litellm_params) + ) + + assert url == self.OUTPUT_BUCKET_URL + assert params == {"list-type": "2", "prefix": "team-a/litellm-batch-outputs/"} + assert _sent_signature(signed_headers) == _s3_signature_for( + "GET", f"{url}?list-type=2&prefix=team-a%2Flitellm-batch-outputs%2F", signed_headers + ) + assert (input_url, input_params) == (self.BUCKET_URL, self.BATCH_QUERY) + + def test_transform_list_files_request_reads_output_bucket_from_env(self, monkeypatch): + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + monkeypatch.setenv("AWS_S3_OUTPUT_BUCKET_NAME", "my-output-bucket") + + url, params = BedrockFilesConfig().transform_list_files_request( + purpose="batch_output", optional_params={}, litellm_params=_bedrock_s3_params() + ) + + assert (url, params) == (self.OUTPUT_BUCKET_URL, self.OUTPUT_QUERY) + + EMPTY_LISTING = b""" + + my-bucket + + 0 + 0 + false +""" + NO_KEYS_QUERY = {"list-type": "2", "max-keys": "0"} + + def test_transform_list_files_request_asks_for_no_keys_when_bedrock_never_stores_the_purpose(self, monkeypatch): + import httpx + + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + litellm_params = _bedrock_s3_params() + config = BedrockFilesConfig() + + url, params = config.transform_list_files_request( + purpose="user_data", optional_params={}, litellm_params=litellm_params + ) + next_request = config.transform_list_files_next_request( + raw_response=httpx.Response(200, content=self.EMPTY_LISTING), + optional_params={}, + litellm_params=litellm_params, + ) + + assert (url, params) == (self.BUCKET_URL, self.NO_KEYS_QUERY) + assert next_request is None + + def test_file_list_never_walks_the_bucket_for_a_purpose_bedrock_never_stores(self, monkeypatch): + import httpx + import respx + + import litellm + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + with respx.mock: + route = respx.get(self.BUCKET_URL, params__contains=self.NO_KEYS_QUERY).mock( + return_value=httpx.Response(200, content=self.EMPTY_LISTING) + ) + + files = litellm.file_list(custom_llm_provider="bedrock", purpose="user_data", **_bedrock_s3_params()) + + assert route.call_count == 1 + assert "prefix" not in route.calls[0].request.url.params + assert files == [] + + def test_transform_list_files_request_lists_the_output_bucket_without_an_input_bucket(self, monkeypatch): + from litellm.llms.bedrock.files.transformation import BedrockFilesConfig + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + litellm_params = _trusted_bucket_snapshot(s3_output_bucket_name="my-output-bucket") + + url, params = BedrockFilesConfig().transform_list_files_request( + purpose="batch_output", optional_params={}, litellm_params=litellm_params + ) + + assert (url, params) == (self.OUTPUT_BUCKET_URL, self.OUTPUT_QUERY) + with pytest.raises(ValueError, match="s3_bucket_name"): + BedrockFilesConfig().transform_list_files_request( + purpose="batch", optional_params={}, litellm_params=dict(litellm_params) + ) + + def test_transform_list_files_response_accepts_output_bucket_objects(self, monkeypatch): + import httpx + + from litellm.llms.bedrock.files.transformation import ( + LIST_FILES_PURPOSE_PARAM, + BedrockFilesConfig, + ) + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + + files = BedrockFilesConfig().transform_list_files_response( + raw_response=httpx.Response(200, content=self.OUTPUT_BUCKET_LISTING), + logging_obj=MagicMock(), + litellm_params={ + **_trusted_bucket_snapshot(s3_bucket_name="my-bucket", s3_output_bucket_name="my-output-bucket"), + LIST_FILES_PURPOSE_PARAM: "batch_output", + }, + ) + + assert [(file.id, file.purpose, file.bytes) for file in files] == [(self.OUTPUT_BUCKET_ID, "batch_output", 70)] + + def test_file_list_batch_output_end_to_end_lists_output_bucket(self, monkeypatch): + import httpx + import respx + + import litellm + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + + with respx.mock: + route = respx.get(self.OUTPUT_BUCKET_URL, params__contains=self.OUTPUT_QUERY).mock( + return_value=httpx.Response(200, content=self.OUTPUT_BUCKET_LISTING) + ) + + files = litellm.file_list( + custom_llm_provider="bedrock", + purpose="batch_output", + **_trusted_bucket_snapshot(s3_bucket_name="my-bucket", s3_output_bucket_name="my-output-bucket"), + ) + + assert route.called + request = route.calls[0].request + assert _sent_signature(request.headers) == _s3_signature_for("GET", str(request.url), request.headers) + assert [file.id for file in files] == [self.OUTPUT_BUCKET_ID] + + def test_file_list_without_purpose_also_walks_a_separate_output_bucket(self, monkeypatch): + import httpx + import respx + + import litellm + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + + with respx.mock: + input_route = respx.get(self.BUCKET_URL, params__contains=self.MANAGED_QUERY).mock( + return_value=httpx.Response(200, content=self.LISTING) + ) + output_route = respx.get(self.OUTPUT_BUCKET_URL, params__contains=self.OUTPUT_QUERY).mock( + return_value=httpx.Response(200, content=self.OUTPUT_BUCKET_LISTING) + ) + + files = litellm.file_list( + custom_llm_provider="bedrock", + **_trusted_bucket_snapshot(s3_bucket_name="my-bucket", s3_output_bucket_name="my-output-bucket"), + ) + + assert (input_route.call_count, output_route.call_count) == (1, 1) + output_request = output_route.calls[0].request + assert _sent_signature(output_request.headers) == _s3_signature_for( + "GET", str(output_request.url), output_request.headers + ) + assert [file.id for file in files] == [*self.BATCH_IDS, self.OUTPUT_ID, self.OUTPUT_BUCKET_ID] + + def test_file_list_without_purpose_walks_the_output_bucket_after_the_last_input_page(self, monkeypatch): + import httpx + import respx + + import litellm + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + + with respx.mock: + respx.get(self.BUCKET_URL, params__contains={"continuation-token": self.CONTINUATION_TOKEN}).mock( + return_value=httpx.Response(200, content=self.LAST_PAGE) + ) + respx.get(self.BUCKET_URL, params__contains=self.MANAGED_QUERY).mock( + return_value=httpx.Response(200, content=self.FIRST_PAGE) + ) + respx.get(self.OUTPUT_BUCKET_URL, params__contains=self.OUTPUT_QUERY).mock( + return_value=httpx.Response(200, content=self.OUTPUT_BUCKET_LISTING) + ) + + files = litellm.file_list( + custom_llm_provider="bedrock", + **_trusted_bucket_snapshot(s3_bucket_name="my-bucket", s3_output_bucket_name="my-output-bucket"), + ) + requested_urls = [str(call.request.url) for call in respx.calls] + + assert requested_urls == [ + f"{self.BUCKET_URL}?list-type=2&prefix=litellm-b", + f"{self.BUCKET_URL}?list-type=2&prefix=litellm-b" + "&continuation-token=1ueGcxLPRx1Tr%2FXYExHnhbYLgveDs2J%2Fwm36Hy4vbOwM%3D", + f"{self.OUTPUT_BUCKET_URL}?list-type=2&prefix=litellm-batch-outputs%2F", + ] + assert [file.id for file in files] == [*self.PAGED_IDS, self.OUTPUT_BUCKET_ID] + + @pytest.mark.parametrize( + ("purpose", "bucket_snapshot"), + [ + pytest.param(None, {"s3_bucket_name": "my-bucket"}, id="outputs-share-the-input-bucket"), + pytest.param( + "batch", + {"s3_bucket_name": "my-bucket", "s3_output_bucket_name": "my-output-bucket"}, + id="input-purpose-requested", + ), + ], + ) + def test_file_list_leaves_the_output_bucket_alone_unless_an_unfiltered_list_needs_it( + self, monkeypatch, purpose, bucket_snapshot + ): + import httpx + import respx + + import litellm + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + + with respx.mock: + input_route = respx.get(self.BUCKET_URL).mock(return_value=httpx.Response(200, content=self.LISTING)) + output_route = respx.get(self.OUTPUT_BUCKET_URL).mock( + return_value=httpx.Response(200, content=self.OUTPUT_BUCKET_LISTING) + ) + + files = litellm.file_list( + custom_llm_provider="bedrock", purpose=purpose, **_trusted_bucket_snapshot(**bucket_snapshot) + ) + + assert (input_route.call_count, output_route.call_count) == (1, 0) + assert [file.id for file in files] == [*self.BATCH_IDS, *(() if purpose else (self.OUTPUT_ID,))] + + def test_transform_list_files_next_request_walks_an_output_prefix_inside_the_input_bucket(self, monkeypatch): + import httpx + + from litellm.llms.bedrock.files.transformation import ( + S3_SIGNED_REQUEST_HEADERS_PARAM, + BedrockFilesConfig, + ) + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + litellm_params = _trusted_bucket_snapshot(s3_bucket_name="my-bucket", s3_output_bucket_name="my-bucket/out") + config = BedrockFilesConfig() + config.transform_list_files_request(purpose=None, optional_params={}, litellm_params=litellm_params) + litellm_params.pop(S3_SIGNED_REQUEST_HEADERS_PARAM) + + output_request = config.transform_list_files_next_request( + raw_response=httpx.Response(200, content=self.LISTING), optional_params={}, litellm_params=litellm_params + ) + after_output_request = config.transform_list_files_next_request( + raw_response=httpx.Response(200, content=self.LISTING), optional_params={}, litellm_params=litellm_params + ) + + assert output_request == (self.BUCKET_URL, {"list-type": "2", "prefix": "out/litellm-batch-outputs/"}) + signed_headers = litellm_params[S3_SIGNED_REQUEST_HEADERS_PARAM] + assert _sent_signature(signed_headers) == _s3_signature_for( + "GET", f"{self.BUCKET_URL}?list-type=2&prefix=out%2Flitellm-batch-outputs%2F", signed_headers + ) + assert after_output_request is None + + def test_transform_list_files_next_request_signs_the_continuation_page(self, monkeypatch): + import httpx + + from litellm.llms.bedrock.files.transformation import ( + S3_SIGNED_REQUEST_HEADERS_PARAM, + BedrockFilesConfig, + ) + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + litellm_params = _bedrock_s3_params() + config = BedrockFilesConfig() + config.transform_list_files_request(purpose="batch", optional_params={}, litellm_params=litellm_params) + first_signature = _sent_signature(litellm_params.pop(S3_SIGNED_REQUEST_HEADERS_PARAM)) + + next_request = config.transform_list_files_next_request( + raw_response=httpx.Response(200, content=self.FIRST_PAGE), + optional_params={}, + litellm_params=litellm_params, + ) + + assert next_request == (self.BUCKET_URL, {**self.BATCH_QUERY, "continuation-token": self.CONTINUATION_TOKEN}) + signed_headers = litellm_params[S3_SIGNED_REQUEST_HEADERS_PARAM] + signed_url = ( + f"{self.BUCKET_URL}?list-type=2&prefix=litellm-bedrock-files" + "&continuation-token=1ueGcxLPRx1Tr%2FXYExHnhbYLgveDs2J%2Fwm36Hy4vbOwM%3D" + ) + assert _sent_signature(signed_headers) == _s3_signature_for("GET", signed_url, signed_headers) + assert _sent_signature(signed_headers) != first_signature + + @pytest.mark.parametrize( + ("status_code", "content"), + [ + pytest.param(200, LAST_PAGE, id="last-page"), + pytest.param(403, b"AccessDenied", id="error-page"), + ], + ) + def test_transform_list_files_next_request_stops_after_the_last_page(self, monkeypatch, status_code, content): + import httpx + + from litellm.llms.bedrock.files.transformation import ( + S3_SIGNED_REQUEST_HEADERS_PARAM, + BedrockFilesConfig, + ) + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + litellm_params = _bedrock_s3_params() + + next_request = BedrockFilesConfig().transform_list_files_next_request( + raw_response=httpx.Response(status_code, content=content), + optional_params={}, + litellm_params=litellm_params, + ) + + assert next_request is None + assert S3_SIGNED_REQUEST_HEADERS_PARAM not in litellm_params + + def _mock_paged_listing(self, respx_module): + import httpx + + last_page = respx_module.get( + self.BUCKET_URL, params__contains={"continuation-token": self.CONTINUATION_TOKEN} + ).mock(return_value=httpx.Response(200, content=self.LAST_PAGE)) + first_page = respx_module.get(self.BUCKET_URL, params__contains=self.BATCH_QUERY).mock( + return_value=httpx.Response(200, content=self.FIRST_PAGE) + ) + return first_page, last_page + + def _assert_paged_listing(self, first_page, last_page, files): + assert (first_page.call_count, last_page.call_count) == (1, 1) + read_timeouts = [call.request.extensions["timeout"]["read"] for call in (*first_page.calls, *last_page.calls)] + assert read_timeouts == [12.0, 12.0] + assert "continuation-token" not in str(first_page.calls[0].request.url) + last_request = last_page.calls[0].request + assert _sent_signature(last_request.headers) == _s3_signature_for( + "GET", str(last_request.url), last_request.headers + ) + assert [file.id for file in files] == list(self.PAGED_IDS) + + def test_file_list_follows_continuation_tokens_across_pages(self, monkeypatch): + import respx + + import litellm + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + + with respx.mock: + first_page, last_page = self._mock_paged_listing(respx) + files = litellm.file_list( + custom_llm_provider="bedrock", + purpose="batch", + timeout=12, + **_trusted_bucket_snapshot(s3_bucket_name="my-bucket"), + ) + + self._assert_paged_listing(first_page, last_page, files) + + @pytest.mark.asyncio + async def test_afile_list_follows_continuation_tokens_across_pages(self, monkeypatch): + import respx + + import litellm + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + litellm.in_memory_llm_clients_cache.flush_cache() + + with respx.mock: + first_page, last_page = self._mock_paged_listing(respx) + files = await litellm.afile_list( + custom_llm_provider="bedrock", + purpose="batch", + timeout=12, + **_trusted_bucket_snapshot(s3_bucket_name="my-bucket"), + ) + + self._assert_paged_listing(first_page, last_page, files) + + OVERSIZED_PAGE_SIZE = 3000 + OVERSIZED_PAGE_COUNT = 6 + + def _oversized_listing_page(self, page_index: int) -> bytes: + contents = "".join( + f"litellm-bedrock-files/page-{page_index}/obj-{index}.jsonl" + "2026-09-01T10:00:00.000Z1" + for index in range(self.OVERSIZED_PAGE_SIZE) + ) + continuation = ( + f"truepage-{page_index + 1}" + if page_index < self.OVERSIZED_PAGE_COUNT - 1 + else "false" + ) + return ( + '' + '' + f"{continuation}{contents}" + ).encode() + + def _mock_oversized_listing(self, respx_module): + import httpx + + def page_for(request): + token = request.url.params.get("continuation-token", "page-0") + return httpx.Response(200, content=self._oversized_listing_page(int(token.removeprefix("page-")))) + + return respx_module.get(self.BUCKET_URL, params__contains=self.BATCH_QUERY).mock(side_effect=page_for) + + def _assert_capped_listing(self, route, files): + from litellm.constants import MAX_FILE_LIST_LIMIT + + pages_needed = -(-MAX_FILE_LIST_LIMIT // self.OVERSIZED_PAGE_SIZE) + last_index = MAX_FILE_LIST_LIMIT - (pages_needed - 1) * self.OVERSIZED_PAGE_SIZE - 1 + assert pages_needed < self.OVERSIZED_PAGE_COUNT + assert route.call_count == pages_needed + assert len(files) == MAX_FILE_LIST_LIMIT + assert files[-1].id == f"s3://my-bucket/litellm-bedrock-files/page-{pages_needed - 1}/obj-{last_index}.jsonl" + + def test_file_list_stops_at_the_openai_listing_ceiling(self, monkeypatch): + import respx + + import litellm + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + + with respx.mock: + route = self._mock_oversized_listing(respx) + files = litellm.file_list( + custom_llm_provider="bedrock", + purpose="batch", + **_trusted_bucket_snapshot(s3_bucket_name="my-bucket"), + ) + + self._assert_capped_listing(route, files) + + @pytest.mark.asyncio + async def test_afile_list_stops_at_the_openai_listing_ceiling(self, monkeypatch): + import respx + + import litellm + + monkeypatch.delenv("AWS_S3_BUCKET_NAME", raising=False) + monkeypatch.delenv("AWS_S3_OUTPUT_BUCKET_NAME", raising=False) + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + litellm.in_memory_llm_clients_cache.flush_cache() + + with respx.mock: + route = self._mock_oversized_listing(respx) + files = await litellm.afile_list( + custom_llm_provider="bedrock", + purpose="batch", + **_trusted_bucket_snapshot(s3_bucket_name="my-bucket"), + ) + + self._assert_capped_listing(route, files) + + def test_file_list_end_to_end_surfaces_the_s3_error_body(self, monkeypatch): + import httpx + import respx + + import litellm + from litellm.llms.bedrock.common_utils import BedrockError + + monkeypatch.setenv("AWS_S3_BUCKET_NAME", "my-bucket") + + with respx.mock: + respx.get(self.BUCKET_URL, params__contains=self.BATCH_QUERY).mock( + return_value=httpx.Response(403, text="AccessDenied") + ) + with pytest.raises(BedrockError) as denied: + litellm.file_list(custom_llm_provider="bedrock", purpose="batch", **_bedrock_s3_params()) + + assert denied.value.status_code == 403 + assert "AccessDenied" in denied.value.message diff --git a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py index 0ea5b7ad4a1..ac3a43b742f 100644 --- a/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py +++ b/tests/test_litellm/llms/bedrock/realtime/test_bedrock_realtime_handler.py @@ -1,3 +1,4 @@ +import asyncio import json import sys import types @@ -7,6 +8,7 @@ from unittest.mock import MagicMock import pytest import litellm +from litellm.constants import REALTIME_SESSION_SUCCESS_LOGGED_KEY from litellm.llms.bedrock.common_utils import BedrockError from litellm.llms.bedrock.realtime.handler import BedrockRealtime from litellm.llms.bedrock.realtime.transformation import BedrockRealtimeConfig @@ -51,16 +53,39 @@ class FakeBedrockStream: def __init__(self, input_stream=None): self.input_stream = input_stream if input_stream is not None else FakeInputStream() + async def await_output(self): + return (None, EndedBedrockReceiver()) + + +class ServiceUnavailableException(Exception): + """Named like the modeled AWS SDK error so the handler maps it to HTTP 503""" + + +class ModelStreamErrorException(Exception): + """Named like the modeled AWS SDK error so the handler maps it to HTTP 424""" + + +class UnavailableBedrockStream: + """Lazy duplex stream whose HTTP response only fails once the output is awaited""" + + def __init__(self): + self.input_stream = FakeInputStream() + + async def await_output(self): + raise ServiceUnavailableException("fault injected: Bedrock realtime unavailable") + class FakeLogging: def __init__(self, trace_id="trace-nova-sonic"): self.litellm_trace_id = trace_id + self.model_call_details = {} class DisconnectingClientWS: def __init__(self, messages): self._messages = list(messages) self.sent_to_client = [] + self.scope = {} async def receive_text(self): if self._messages: @@ -93,6 +118,7 @@ class RealtimeClientWS: def __init__(self): self.closed = False self.sent_to_client = [] + self.scope = {} async def receive_text(self): raise RuntimeError("client disconnected") @@ -104,6 +130,25 @@ class RealtimeClientWS: self.closed = True +class ConnectedClientWS(RealtimeClientWS): + """Client that sends its scripted messages and then stays connected until the server closes it""" + + def __init__(self, messages): + super().__init__() + self._messages = list(messages) + self._closed_event = asyncio.Event() + + async def receive_text(self): + if self._messages: + return self._messages.pop(0) + await self._closed_event.wait() + raise RuntimeError("client disconnected") + + async def close(self, code=None, reason=None): + self.closed = True + self._closed_event.set() + + class ScriptedBedrockReceiver: def __init__(self, payloads): self._payloads = list(payloads) @@ -115,10 +160,48 @@ class ScriptedBedrockReceiver: return SimpleNamespace(value=SimpleNamespace(bytes_=payload.encode("utf-8"))) -class ScriptedBedrockStream: +class BreakingBedrockReceiver(ScriptedBedrockReceiver): + """Delivers its payloads, then the provider stream breaks instead of ending normally""" + + async def receive(self): + if not self._payloads: + await asyncio.sleep(0) + raise ModelStreamErrorException("Nova Sonic stream broke") + return await super().receive() + + +class DrainedThenOpenBedrockReceiver(ScriptedBedrockReceiver): + """Delivers its payloads, flags `drained`, then stays open like a live Nova Sonic turn""" + def __init__(self, payloads): + super().__init__(payloads) + self.drained = asyncio.Event() + + async def receive(self): + if not self._payloads: + self.drained.set() + await asyncio.Event().wait() + return await super().receive() + + +class ResetOnAudioInputStream(FakeInputStream): + """Accepts session setup, then the provider resets the input side once the first response was delivered""" + + def __init__(self, drained): + super().__init__() + self._drained = drained + + async def send(self, event): + if "audioInput" in json.loads(event.value.bytes_.decode("utf-8")).get("event", {}): + await self._drained.wait() + raise RuntimeError("bedrock input stream reset") + self.sent.append(event) + + +class ScriptedBedrockStream: + def __init__(self, payloads, receiver_type=ScriptedBedrockReceiver): self.input_stream = FakeInputStream() - self._receiver = ScriptedBedrockReceiver(payloads) + self._receiver = receiver_type(payloads) async def await_output(self): return (None, self._receiver) @@ -163,6 +246,11 @@ def stub_aws_sdk_client(monkeypatch): async def invoke_model_with_bidirectional_stream(self, operation_input): captured["operation_input"] = operation_input + if captured.get("streams"): + stream = captured["streams"].pop(0) + if isinstance(stream, Exception): + raise stream + return stream return ScriptedBedrockStream(captured.get("scripted_payloads", [])) package = types.ModuleType("aws_sdk_bedrock_runtime") @@ -263,7 +351,8 @@ class TestBedrockRealtimeHandler: [json.dumps({"type": "session.update", "session": {"instructions": "You are helpful."}})] ) - await handler._forward_client_to_bedrock(client_ws, stream, config, "amazon.nova-sonic-v1:0", {}) + with pytest.raises(RuntimeError, match="bedrock send failed"): + await handler._forward_client_to_bedrock(client_ws, stream, config, "amazon.nova-sonic-v1:0", {}) assert stream.input_stream.closed @@ -464,6 +553,198 @@ class TestBedrockRealtimeSessionLifecycle: assert client_ws.sent_to_client == [] +class TestBedrockRealtimeProviderFailurePropagation: + """Deferred Nova Sonic failures must escape async_realtime so the router can fall back / cool down (LIT-6484)""" + + SESSION_UPDATE = json.dumps({"type": "session.update", "session": {"instructions": "hi", "modalities": ["text"]}}) + AWS_PARAMS = {"aws_region_name": "us-east-1", "aws_access_key_id": "k", "aws_secret_access_key": "s"} + + @pytest.mark.asyncio + async def test_readiness_failure_escapes_and_fallback_replays_session_update(self, stub_aws_sdk_client): + handler = BedrockRealtime() + websocket = ConnectedClientWS([self.SESSION_UPDATE]) + healthy_stream = ScriptedBedrockStream([]) + eager_failure = ServiceUnavailableException("fault injected before the stream was returned") + stub_aws_sdk_client["streams"] = [UnavailableBedrockStream(), eager_failure, healthy_stream] + + with pytest.raises(BedrockError) as failure: + await handler.async_realtime( + model="amazon.nova-sonic-v1:0", websocket=websocket, logging_obj=FakeLogging(), **self.AWS_PARAMS + ) + + assert failure.value.status_code == 503 + assert [json.loads(m)["type"] for m in websocket.sent_to_client] == ["session.created"] + assert not websocket.closed, "the proxy route owns the client-facing error event and 1011 close" + + with pytest.raises(ServiceUnavailableException): + await handler.async_realtime( + model="amazon.nova-sonic-v1:0", websocket=websocket, logging_obj=FakeLogging(), **self.AWS_PARAMS + ) + + await handler.async_realtime( + model="amazon.nova-sonic-v1:0", websocket=websocket, logging_obj=FakeLogging(), **self.AWS_PARAMS + ) + + assert [json.loads(m)["type"] for m in websocket.sent_to_client] == ["session.created", "session.updated"] + replayed = [json.loads(chunk.value.bytes_.decode("utf-8")) for chunk in healthy_stream.input_stream.sent] + assert [next(iter(event["event"])) for event in replayed][:2] == ["sessionStart", "promptStart"] + assert websocket.closed + + TEXT_TURN = ( + json.dumps({"event": {"contentStart": {"role": "ASSISTANT", "type": "TEXT"}}}), + json.dumps({"event": {"textOutput": {"content": "Hi"}}}), + json.dumps({"event": {"contentEnd": {"stopReason": "END_TURN"}}}), + ) + + @pytest.fixture + def spend_dispatch(self, monkeypatch): + import litellm.llms.bedrock.realtime.handler as handler_module + + dispatched = {} + + class RecordingLogging(FakeLogging): + async def dispatch_success_handlers(self, result=None, prefer_async_handlers=False, **kwargs): + dispatched["events"] = result + + class RecordingLoggingWorker: + def ensure_initialized_and_enqueue(self, coro): + dispatched["coro"] = coro + + monkeypatch.setattr(handler_module, "GLOBAL_LOGGING_WORKER", RecordingLoggingWorker()) + dispatched["logging_obj"] = RecordingLogging() + return dispatched + + @pytest.mark.asyncio + async def test_mid_stream_failure_escapes_keeps_partial_spend_and_blocks_replay( + self, stub_aws_sdk_client, spend_dispatch + ): + handler = BedrockRealtime() + websocket = ConnectedClientWS([self.SESSION_UPDATE]) + stream = ScriptedBedrockStream(self.TEXT_TURN, receiver_type=BreakingBedrockReceiver) + stub_aws_sdk_client["streams"] = [stream] + + with pytest.raises(BedrockError) as failure: + await handler.async_realtime( + model="amazon.nova-sonic-v1:0", + websocket=websocket, + logging_obj=spend_dispatch["logging_obj"], + **self.AWS_PARAMS, + ) + + assert failure.value.status_code == 424 + await spend_dispatch["coro"] + assert [event["type"] for event in spend_dispatch["events"]] == ["response.done"] + assert "response.done" in [json.loads(m)["type"] for m in websocket.sent_to_client] + flushed = [json.loads(chunk.value.bytes_.decode("utf-8")) for chunk in stream.input_stream.sent] + assert [next(iter(event["event"])) for event in flushed][-2:] == ["promptEnd", "sessionEnd"] + assert stream.input_stream.closed + + with pytest.raises(BedrockError) as replay: + await handler.async_realtime( + model="amazon.nova-sonic-v1:0", + websocket=websocket, + logging_obj=spend_dispatch["logging_obj"], + **self.AWS_PARAMS, + ) + + assert replay.value.status_code == 400, "a committed session must not be silently restarted on a fallback" + assert not litellm._should_retry(replay.value.status_code), "the router must not retry the replay refusal" + assert "Nova Sonic stream broke" in replay.value.message, "the router surfaces the last attempt's error" + + @pytest.mark.asyncio + async def test_input_side_failure_keeps_spend_for_responses_already_delivered( + self, stub_aws_sdk_client, spend_dispatch + ): + receiver = DrainedThenOpenBedrockReceiver(self.TEXT_TURN) + stream = ScriptedBedrockStream(self.TEXT_TURN, receiver_type=lambda _payloads: receiver) + stream.input_stream = ResetOnAudioInputStream(receiver.drained) + stub_aws_sdk_client["streams"] = [stream] + websocket = ConnectedClientWS( + [self.SESSION_UPDATE, json.dumps({"type": "input_audio_buffer.append", "audio": "AAAA"})] + ) + + with pytest.raises(RuntimeError, match="bedrock input stream reset"): + await BedrockRealtime().async_realtime( + model="amazon.nova-sonic-v1:0", + websocket=websocket, + logging_obj=spend_dispatch["logging_obj"], + **self.AWS_PARAMS, + ) + + assert "response.done" in [json.loads(m)["type"] for m in websocket.sent_to_client] + await spend_dispatch["coro"] + assert [event["type"] for event in spend_dispatch["events"]] == ["response.done"] + + @pytest.mark.asyncio + async def test_success_dispatch_stamps_the_ownership_marker_only_when_spend_was_logged( + self, stub_aws_sdk_client, spend_dispatch + ): + stub_aws_sdk_client["streams"] = [ScriptedBedrockStream(self.TEXT_TURN)] + await BedrockRealtime().async_realtime( + model="amazon.nova-sonic-v1:0", + websocket=ConnectedClientWS([self.SESSION_UPDATE]), + logging_obj=spend_dispatch["logging_obj"], + **self.AWS_PARAMS, + ) + await spend_dispatch["coro"] + assert [event["type"] for event in spend_dispatch["events"]] == ["response.done"] + assert spend_dispatch["logging_obj"].model_call_details.get(REALTIME_SESSION_SUCCESS_LOGGED_KEY) is True + + idle_logging = FakeLogging() + stub_aws_sdk_client["streams"] = [ScriptedBedrockStream([])] + await BedrockRealtime().async_realtime( + model="amazon.nova-sonic-v1:0", + websocket=ConnectedClientWS([self.SESSION_UPDATE]), + logging_obj=idle_logging, + **self.AWS_PARAMS, + ) + assert REALTIME_SESSION_SUCCESS_LOGGED_KEY not in idle_logging.model_call_details + + @pytest.mark.asyncio + async def test_stream_failure_after_client_disconnect_is_not_a_provider_failure(self, stub_aws_sdk_client): + stream = ScriptedBedrockStream([], receiver_type=BreakingBedrockReceiver) + stub_aws_sdk_client["streams"] = [stream] + + await BedrockRealtime().async_realtime( + model="amazon.nova-sonic-v1:0", websocket=RealtimeClientWS(), logging_obj=FakeLogging(), **self.AWS_PARAMS + ) + + assert stream.input_stream.closed + + @pytest.mark.asyncio + async def test_client_disconnect_ends_the_session_while_bedrock_output_stays_open(self, stub_aws_sdk_client): + receiver = DrainedThenOpenBedrockReceiver([]) + stream = ScriptedBedrockStream([], receiver_type=lambda _payloads: receiver) + stub_aws_sdk_client["streams"] = [stream] + + await asyncio.wait_for( + BedrockRealtime().async_realtime( + model="amazon.nova-sonic-v1:0", + websocket=RealtimeClientWS(), + logging_obj=FakeLogging(), + **self.AWS_PARAMS, + ), + timeout=1, + ) + + assert receiver.drained.is_set(), "the handler must have been waiting on the open provider stream" + assert stream.input_stream.closed + + @pytest.mark.asyncio + async def test_session_updated_is_not_sent_before_bedrock_is_ready(self, stub_aws_models): + handler = BedrockRealtime() + stream = UnavailableBedrockStream() + client_ws = DisconnectingClientWS([self.SESSION_UPDATE]) + + with pytest.raises(ServiceUnavailableException): + await handler._forward_client_to_bedrock( + client_ws, stream, BedrockRealtimeConfig(), "amazon.nova-sonic-v1:0", {}, FakeLogging() + ) + + assert client_ws.sent_to_client == [] + assert stream.input_stream.closed + + class TestBedrockRealtimeAwsAuth: """AWS auth params passed via litellm_params must reach the Smithy client config (LIT-3923 regression)""" diff --git a/tests/test_litellm/llms/bedrock/test_web_identity_session_policy.py b/tests/test_litellm/llms/bedrock/test_web_identity_session_policy.py index 3ea840519f9..cbb69b4ceed 100644 --- a/tests/test_litellm/llms/bedrock/test_web_identity_session_policy.py +++ b/tests/test_litellm/llms/bedrock/test_web_identity_session_policy.py @@ -32,9 +32,14 @@ action. import base64 import json from datetime import datetime, timedelta, timezone +from types import MappingProxyType +from typing import Final from unittest.mock import MagicMock, patch import pytest +from pydantic import TypeAdapter + +from litellm.llms.bedrock.base_aws_llm import WebIdentitySessionPolicy, _SessionPolicyStatement # Actions the Claude Platform on AWS service is documented to call. # Source: AWS IAM action reference + the #27678 surface area. @@ -49,9 +54,9 @@ _CLAUDE_PLATFORM_ACTIONS = { } -def _captured_policy() -> dict: - """Run _auth_with_web_identity_token under mocks + return the parsed - Policy dict that was actually sent to STS.""" +def _captured_policy_document() -> str: + """Run _auth_with_web_identity_token under mocks + return the Policy + JSON document that was actually sent to STS.""" from litellm.llms.bedrock.base_aws_llm import BaseAWSLLM base = BaseAWSLLM() @@ -84,11 +89,21 @@ def _captured_policy() -> dict: mock_sts.assume_role_with_web_identity.assert_called_once() kwargs = mock_sts.assume_role_with_web_identity.call_args.kwargs - policy_str = kwargs["Policy"] - return json.loads(policy_str) + return kwargs["Policy"] -def _statement_by_sid(policy: dict, sid: str) -> dict: +_SESSION_POLICY_ADAPTER: Final = TypeAdapter(WebIdentitySessionPolicy) + + +def _captured_policy() -> WebIdentitySessionPolicy: + return _SESSION_POLICY_ADAPTER.validate_python(json.loads(_captured_policy_document())) + + +def _granted_actions(policy: WebIdentitySessionPolicy) -> frozenset[str]: + return frozenset(action for stmt in policy["Statement"] for action in stmt["Action"]) + + +def _statement_by_sid(policy: WebIdentitySessionPolicy, sid: str) -> _SessionPolicyStatement: for stmt in policy["Statement"]: if stmt.get("Sid") == sid: return stmt @@ -102,7 +117,6 @@ class TestWebIdentitySessionPolicyShape: def test_policy_parses_as_valid_iam_document(self): policy = _captured_policy() assert policy["Version"] == "2012-10-17" - assert isinstance(policy["Statement"], list) assert len(policy["Statement"]) >= 2 def test_bedrock_statement_actions_preserved(self): @@ -137,16 +151,7 @@ class TestClaudePlatformActionsCovered: @pytest.mark.parametrize("action", sorted(_CLAUDE_PLATFORM_ACTIONS)) def test_claude_platform_action_present(self, action: str): - policy = _captured_policy() - # Action may live in any Statement — search across all. - all_actions: set = set() - for stmt in policy["Statement"]: - stmt_actions = stmt.get("Action") - if isinstance(stmt_actions, str): - all_actions.add(stmt_actions) - elif isinstance(stmt_actions, list): - all_actions.update(stmt_actions) - assert action in all_actions, ( + assert action in _granted_actions(_captured_policy()), ( f"{action} missing from session policy — " f"bedrock/claude_platform/* requests will 403 on OIDC auth" ) @@ -179,15 +184,7 @@ class TestBedrockMantleActionsCovered: action" even when the role's identity policy grants it.""" def test_bedrock_mantle_create_inference_present(self): - policy = _captured_policy() - all_actions: set = set() - for stmt in policy["Statement"]: - stmt_actions = stmt.get("Action") - if isinstance(stmt_actions, str): - all_actions.add(stmt_actions) - elif isinstance(stmt_actions, list): - all_actions.update(stmt_actions) - assert "bedrock-mantle:CreateInference" in all_actions, ( + assert "bedrock-mantle:CreateInference" in _granted_actions(_captured_policy()), ( "bedrock-mantle:CreateInference missing from session policy — " "bedrock_mantle/* requests will 403 on OIDC/WIF auth" ) @@ -233,7 +230,7 @@ class TestInvalidIdentityTokenSurfacesAudience: operator can diagnose the mismatch without enabling LITELLM_LOG=DEBUG on a prod instance.""" - _AUD = "https://guidepoint.litellm-prod.ai" + _AUD = "https://gateway.example.com" _ISS = "https://accounts.google.com" _STS_MESSAGE = ( "An error occurred (InvalidIdentityToken) when calling the " @@ -308,3 +305,44 @@ class TestPolicyTransportConditions: "ClaudePlatformLiteLLM must require aws:SecureTransport=true " "to keep parity with the bedrock statement" ) + + +_STS_SESSION_POLICY_PLAINTEXT_LIMIT: Final = 2048 + +_BEDROCK_ROUTE_ACTIONS: Final = MappingProxyType( + { + "model/{model_id}/invoke": "bedrock:InvokeModel", + "model/{model_id}/invoke-with-response-stream": "bedrock:InvokeModelWithResponseStream", + "model/{model_id}/converse": "bedrock:InvokeModel", + "model/{model_id}/converse-stream": "bedrock:InvokeModelWithResponseStream", + "model/{model_id}/count-tokens": "bedrock:CountTokens", + "guardrail/{guardrail_id}/version/{version}/apply": "bedrock:ApplyGuardrail", + "rerank": "bedrock:Rerank", + "knowledgebases/{knowledge_base_id}/retrieve": "bedrock:Retrieve", + "knowledgebases": "bedrock:ListKnowledgeBases", + "agents/{agent_id}/agentAliases/{alias_id}/sessions/{session_id}/text": "bedrock:InvokeAgent", + "runtimes/{agent_runtime_arn}/invocations": "bedrock-agentcore:InvokeAgentRuntime", + "runtimes/{agent_runtime_arn}/invocations with X-Amzn-Bedrock-AgentCore-Runtime-User-Id": ( + "bedrock-agentcore:InvokeAgentRuntimeForUser" + ), + "mcp": "bedrock-agentcore:InvokeGateway", + } +) + + +class TestSessionPolicyGrantsEveryBedrockRoute: + """LIT-7348: ``/rerank`` authorizes against ``bedrock:Rerank``, which the + ceiling never granted, so rerank 403d on web identity auth while static + credentials and IRSA worked. Each route the bedrock package signs with the + web identity session maps to the IAM action it authorizes against, and the + ceiling must grant every one of them.""" + + @pytest.mark.parametrize(("route", "action"), sorted(_BEDROCK_ROUTE_ACTIONS.items())) + def test_route_action_is_granted_by_the_ceiling(self, route: str, action: str): + assert action in _granted_actions(_captured_policy()), ( + f"/{route} authorizes against {action}, which the session policy does not grant, " + "so it 403s on web identity auth" + ) + + def test_policy_document_fits_the_sts_plaintext_limit(self): + assert len(_captured_policy_document()) <= _STS_SESSION_POLICY_PLAINTEXT_LIMIT diff --git a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py index 40566261c84..a7aefa714aa 100644 --- a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py +++ b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_responses_transformation.py @@ -773,6 +773,12 @@ class TestBedrockMantleCodexAdditionalTools: assert body["input"] == codex_agentic_items assert "tools" not in body + def test_input_without_additional_tools_sanitizes_tools_on_the_caller_params_object(self): + params = {"tools": [{"type": "function", "name": "wait", "parameters": '{"type": "object"}'}]} + body = self._transform(input=[self._USER_MESSAGE], params=params) + assert body["tools"][0]["parameters"] == {"type": "object"} + assert params["tools"][0]["parameters"] == {"type": "object"} + def test_malformed_additional_tools_item_without_tools_list_is_stripped(self): body = self._transform( input=[ diff --git a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py index e83a844c87e..c948dfb3553 100644 --- a/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py +++ b/tests/test_litellm/llms/bedrock_mantle/test_bedrock_mantle_transformation.py @@ -7,7 +7,7 @@ API docs: https://docs.aws.amazon.com/bedrock/latest/userguide/bedrock-mantle.ht import json import asyncio -from unittest.mock import patch +from unittest.mock import Mock, patch import httpx @@ -151,6 +151,27 @@ class TestBedrockMantleConfig: # /openai/v1 base per the AWS model card. assert api_base == "https://bedrock-mantle.us-east-2.api.aws/openai/v1" + def test_region_prefixed_model_routes_to_that_region(self, monkeypatch, local_cost_map): + for var in ("BEDROCK_MANTLE_REGION", "BEDROCK_MANTLE_API_BASE", "AWS_REGION", "AWS_REGION_NAME"): + monkeypatch.delenv(var, raising=False) + cfg = BedrockMantleChatConfig() + api_base, _ = cfg._get_openai_compatible_provider_info(None, None, model="us-gov-west-1/xai.grok-4.3") + assert api_base == "https://bedrock-mantle.us-gov-west-1.api.aws/openai/v1" + + def test_aws_region_name_param_beats_model_region_prefix(self, monkeypatch, local_cost_map): + from litellm.types.router import GenericLiteLLMParams + + for var in ("BEDROCK_MANTLE_REGION", "BEDROCK_MANTLE_API_BASE", "AWS_REGION", "AWS_REGION_NAME"): + monkeypatch.delenv(var, raising=False) + cfg = BedrockMantleChatConfig() + api_base, _ = cfg._get_openai_compatible_provider_info( + None, + None, + litellm_params=GenericLiteLLMParams(aws_region_name="us-east-1"), + model="us-gov-west-1/xai.grok-4.3", + ) + assert api_base == "https://bedrock-mantle.us-east-1.api.aws/openai/v1" + def test_default_api_base_fallback_to_us_east_1(self, monkeypatch): monkeypatch.delenv("BEDROCK_MANTLE_REGION", raising=False) monkeypatch.delenv("BEDROCK_MANTLE_API_BASE", raising=False) @@ -686,6 +707,120 @@ class TestBedrockMantleProviderResolution: assert model == "openai.gpt-oss-20b" + def test_get_llm_provider_strips_region_prefix(self, monkeypatch, local_cost_map): + for var in ("BEDROCK_MANTLE_REGION", "BEDROCK_MANTLE_API_BASE", "AWS_REGION", "AWS_REGION_NAME"): + monkeypatch.delenv(var, raising=False) + model, provider, _, api_base = litellm.get_llm_provider("bedrock_mantle/us-gov-west-1/xai.grok-4.3") + assert provider == "bedrock_mantle" + assert model == "xai.grok-4.3" + assert api_base == "https://bedrock-mantle.us-gov-west-1.api.aws/openai/v1" + + def test_completion_region_prefixed_model_sends_bare_model_to_that_region(self, monkeypatch, local_cost_map): + from litellm.llms.custom_httpx.http_handler import HTTPHandler + + for var in ( + "BEDROCK_MANTLE_API_KEY", + "AWS_BEARER_TOKEN_BEDROCK", + "BEDROCK_MANTLE_API_BASE", + "BEDROCK_MANTLE_REGION", + "AWS_REGION_NAME", + "AWS_REGION", + "AWS_PROFILE", + ): + monkeypatch.delenv(var, raising=False) + monkeypatch.setenv("AWS_ACCESS_KEY_ID", "AKIAEXAMPLE") + monkeypatch.setenv("AWS_SECRET_ACCESS_KEY", "c2VjcmV0LXRlc3Qtc2VjcmV0LXRlc3Qtc2VjcmV0") + + def respond(request: httpx.Request) -> httpx.Response: + return httpx.Response( + status_code=200, + json={ + "id": "chatcmpl-test", + "object": "chat.completion", + "created": 1733529600, + "model": "xai.grok-4.3", + "choices": [{"index": 0, "message": {"role": "assistant", "content": "ok"}, "finish_reason": "stop"}], + "usage": {"prompt_tokens": 38, "completion_tokens": 20, "total_tokens": 58}, + }, + request=request, + ) + + handler = Mock(side_effect=respond) + response = litellm.completion( + model="bedrock_mantle/us-gov-west-1/xai.grok-4.3", + messages=[{"role": "user", "content": "hello"}], + client=HTTPHandler(client=httpx.Client(transport=httpx.MockTransport(handler))), + ) + + gov = litellm.model_cost["bedrock_mantle/us-gov-west-1/xai.grok-4.3"] + sent = handler.call_args.args[0] + assert str(sent.url) == "https://bedrock-mantle.us-gov-west-1.api.aws/openai/v1/chat/completions" + assert json.loads(sent.content)["model"] == "xai.grok-4.3" + assert "/us-gov-west-1/bedrock/aws4_request" in sent.headers["Authorization"] + assert response._hidden_params["response_cost"] == pytest.approx( + 38 * gov["input_cost_per_token"] + 20 * gov["output_cost_per_token"] + ) + + def test_responses_region_prefixed_model_prices_from_that_region_over_env_region(self, monkeypatch, local_cost_map): + from litellm.llms.custom_httpx.http_handler import HTTPHandler + + for var in ( + "BEDROCK_MANTLE_API_KEY", + "AWS_BEARER_TOKEN_BEDROCK", + "BEDROCK_MANTLE_API_BASE", + "BEDROCK_MANTLE_REGION", + "AWS_REGION", + "AWS_PROFILE", + ): + monkeypatch.delenv(var, raising=False) + monkeypatch.setenv("AWS_REGION_NAME", "us-east-1") + monkeypatch.setenv("AWS_ACCESS_KEY_ID", "AKIAEXAMPLE") + monkeypatch.setenv("AWS_SECRET_ACCESS_KEY", "c2VjcmV0LXRlc3Qtc2VjcmV0LXRlc3Qtc2VjcmV0") + + def respond(request: httpx.Request) -> httpx.Response: + return httpx.Response( + status_code=200, + json={ + "id": "resp_test", + "object": "response", + "created_at": 1733529600, + "status": "completed", + "model": "xai.grok-4.3", + "output": [ + { + "type": "message", + "id": "msg_test", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "ok", "annotations": []}], + } + ], + "parallel_tool_calls": True, + "tool_choice": "auto", + "tools": [], + "top_p": 1.0, + "usage": {"input_tokens": 38, "output_tokens": 20, "total_tokens": 58}, + }, + request=request, + ) + + handler = Mock(side_effect=respond) + response = litellm.responses( + model="bedrock_mantle/us-gov-west-1/xai.grok-4.3", + input="hello", + client=HTTPHandler(client=httpx.Client(transport=httpx.MockTransport(handler))), + ) + + gov = litellm.model_cost["bedrock_mantle/us-gov-west-1/xai.grok-4.3"] + sent = handler.call_args.args[0] + assert str(sent.url) == "https://bedrock-mantle.us-gov-west-1.api.aws/openai/v1/responses" + assert json.loads(sent.content)["model"] == "xai.grok-4.3" + assert "/us-gov-west-1/bedrock/aws4_request" in sent.headers["Authorization"] + assert response._hidden_params["response_cost"] == pytest.approx( + 38 * gov["input_cost_per_token"] + 20 * gov["output_cost_per_token"] + ) + + class TestBedrockMantlePricing: """Tests that verify Bedrock Mantle uses correct AWS Bedrock pricing, not OpenAI pricing.""" diff --git a/tests/test_litellm/llms/databricks/chat/test_databricks_chat_transformation.py b/tests/test_litellm/llms/databricks/chat/test_databricks_chat_transformation.py index caf7bed7385..52bb89fed5a 100644 --- a/tests/test_litellm/llms/databricks/chat/test_databricks_chat_transformation.py +++ b/tests/test_litellm/llms/databricks/chat/test_databricks_chat_transformation.py @@ -5,6 +5,12 @@ from fastapi.testclient import TestClient from unittest.mock import MagicMock, patch +import litellm +from litellm.constants import ( + DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET, + DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET, + DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET, +) from litellm.llms.databricks.chat.transformation import ( DatabricksChatResponseIterator, DatabricksConfig, @@ -12,6 +18,12 @@ from litellm.llms.databricks.chat.transformation import ( ) +@pytest.fixture() +def _use_local_model_cost_map(monkeypatch): + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url="")) + + def test_transform_choices(): config = DatabricksConfig() databricks_choices = [ @@ -532,6 +544,115 @@ def test_map_openai_params_upgrades_legacy_thinking_on_adaptive_only_claude( assert mapped.get("output_config") == expected_output_config +def _map_reasoning_effort(model: str, reasoning_effort: str): + return DatabricksConfig().map_openai_params( + non_default_params={"reasoning_effort": reasoning_effort}, + optional_params={}, + model=model, + drop_params=False, + ) + + +def test_claude_translates_reasoning_effort_to_thinking(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-claude-3-7-sonnet", "low") + assert params.get("thinking") == { + "type": "enabled", + "budget_tokens": DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET, + } + assert "reasoning_effort" not in params + + +def test_adaptive_claude_translates_reasoning_effort_to_output_config(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-claude-opus-4-7", "high") + assert params.get("thinking") == {"type": "adaptive", "display": "summarized"} + assert params.get("output_config") == {"effort": "high"} + assert "reasoning_effort" not in params + + +def test_unmapped_claude_endpoint_still_translates(_use_local_model_cost_map): + params = _map_reasoning_effort("my-claude-serving-endpoint", "low") + assert params.get("thinking") == { + "type": "enabled", + "budget_tokens": DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET, + } + assert "reasoning_effort" not in params + + +def test_gemini_2_5_low_translates_to_thinking_budget(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-gemini-2-5-flash", "low") + assert params.get("thinking") == { + "type": "enabled", + "budget_tokens": DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET, + } + assert "reasoning_effort" not in params + + +def test_gemini_2_5_medium_translates_to_thinking_budget(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-gemini-2-5-flash", "medium") + assert params.get("thinking") == { + "type": "enabled", + "budget_tokens": DEFAULT_REASONING_EFFORT_MEDIUM_THINKING_BUDGET, + } + assert "reasoning_effort" not in params + + +def test_gemini_2_5_high_translates_to_thinking_budget(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-gemini-2-5-flash", "high") + assert params.get("thinking") == { + "type": "enabled", + "budget_tokens": DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET, + } + assert "reasoning_effort" not in params + + +def test_gemini_2_5_pro_translates_to_thinking_budget(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-gemini-2-5-pro", "high") + assert params.get("thinking") == { + "type": "enabled", + "budget_tokens": DEFAULT_REASONING_EFFORT_HIGH_THINKING_BUDGET, + } + assert "reasoning_effort" not in params + + +def test_gemini_2_5_with_dot_notation_translates(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-gemini-2.5-flash", "low") + assert params.get("thinking") == { + "type": "enabled", + "budget_tokens": DEFAULT_REASONING_EFFORT_LOW_THINKING_BUDGET, + } + assert "reasoning_effort" not in params + + +def test_gemini_2_0_does_not_match(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-gemini-2-0-flash", "low") + assert "thinking" not in params + assert params.get("reasoning_effort") == "low" + + +def test_gemini_2_5_none_drops_thinking_and_reasoning_effort(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-gemini-2-5-flash", "none") + assert "thinking" not in params + assert "reasoning_effort" not in params + + +def test_gemini_3_passes_reasoning_effort_through(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-gemini-3-1-pro", "low") + assert params.get("reasoning_effort") == "low" + assert "thinking" not in params + + +def test_gpt_5_passes_reasoning_effort_through(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-gpt-5-1", "low") + assert params.get("reasoning_effort") == "low" + assert "thinking" not in params + + +def test_gpt_oss_passes_reasoning_effort_through(_use_local_model_cost_map): + params = _map_reasoning_effort("databricks-gpt-oss-120b", "high") + assert params.get("reasoning_effort") == "high" + assert "thinking" not in params + + def _streaming_chunk(usage=None, choices=None): base = { "id": "chatcmpl-test", diff --git a/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py b/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py index 8479397efa7..fb0311ef39b 100644 --- a/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py +++ b/tests/test_litellm/llms/fireworks_ai/chat/test_fireworks_ai_chat_transformation.py @@ -1813,3 +1813,15 @@ def test_streaming_preserves_selected_model_for_private_accounting(): completion_response=assembled, custom_llm_provider="fireworks_ai", ) == pytest.approx(expected_cost) + + +@pytest.mark.parametrize( + "model, expected", + [ + ("deepseek-r1", "fireworks_ai/accounts/fireworks/models/deepseek-r1"), + ("glm-5p3-fast", "fireworks_ai/accounts/fireworks/routers/glm-5p3-fast"), + ("accounts/fireworks/models/deepseek-r1", "fireworks_ai/accounts/fireworks/models/deepseek-r1"), + ], +) +def test_get_model_cost_key_resolves_short_names_to_long_keys(model: str, expected: str) -> None: + assert FireworksAIConfig().get_model_cost_key(model) == expected diff --git a/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py b/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py index 2b3b6343fad..3eb4a70ee15 100644 --- a/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py +++ b/tests/test_litellm/llms/gemini/realtime/test_gemini_realtime_transformation.py @@ -1,4 +1,6 @@ import json +from collections.abc import Mapping +from typing import cast from unittest.mock import MagicMock import pytest @@ -6,6 +8,7 @@ import pytest import litellm from litellm.llms.gemini.realtime.transformation import GeminiRealtimeConfig +from litellm.types.llms.gemini import BidiGenerateContentServerMessage def test_gemini_realtime_transformation_session_created(): @@ -2178,3 +2181,71 @@ def test_unbilled_usage_on_session_close_flushes_trailing_audio(patch_gemini_tra } assert usage == expected assert config.unbilled_usage_on_session_close("gemini-3.5-transcribe-live") is None + + +def _grounded_live_frame(grounding_metadata: Mapping[str, object] | None) -> Mapping[str, object]: + """One Live server frame. Grounding metadata and usageMetadata arrive together, as Vertex sends them.""" + from typing import Final + + server_content: Final = { + "turnComplete": True, + **({} if grounding_metadata is None else {"groundingMetadata": grounding_metadata}), + } + return { + "serverContent": server_content, + "usageMetadata": { + "promptTokenCount": 19, + "candidatesTokenCount": 157, + "totalTokenCount": 176, + "promptTokensDetails": ({"modality": "TEXT", "tokenCount": 19},), + "candidatesTokensDetails": ({"modality": "AUDIO", "tokenCount": 157},), + }, + } + + +def _response_done_input_details(message: Mapping[str, object]) -> Mapping[str, object]: + """The ``input_tokens_details`` a ``response.done`` event carries, read off the emitted event.""" + from typing import Final + + config: Final = GeminiRealtimeConfig() + event: Final = config.transform_response_done_event( + message=cast( # cast-ok: a test fixture stands in for the server frame TypedDict + BidiGenerateContentServerMessage, message + ), + current_response_id="resp_grounding", + current_conversation_id="conv_grounding", + output_items=None, + ) + usage: Final = event["response"]["usage"] + assert usage, "response.done must carry a usage object" + return usage.get("input_tokens_details") or {} + + +def test_gemini_realtime_response_done_counts_web_grounding(): + """Regression: Live reports grounding in the server frames and never in usageMetadata. + + Nothing read those frames on the realtime path, so web_search_requests stayed unset and the + cost path's only trigger for Google's per-query grounding charge never fired. + + The counter is read off the emitted event, which is what the cost path is handed, so this covers + the grounding read and the usage bridge that carries it together + """ + input_details = _response_done_input_details( + _grounded_live_frame( + { + "webSearchQueries": ["who won the 2026 world cup final"], + "groundingChunks": [{"web": {"uri": "https://example.com"}}], + } + ) + ) + + assert input_details.get("web_search_requests") == 1, "a grounded turn must report its query" + assert input_details.get("text_tokens") == 19, "the modality breakdown must survive alongside it" + + +def test_gemini_realtime_response_done_reports_no_grounding_when_none_ran(): + """The counter must stay unset on an ordinary turn, or every session pays a grounding fee.""" + input_details = _response_done_input_details(_grounded_live_frame(None)) + + assert input_details.get("web_search_requests") is None + assert input_details.get("google_maps_grounding_requests") is None diff --git a/tests/test_litellm/llms/meta/realtime/test_meta_realtime_transformation.py b/tests/test_litellm/llms/meta/realtime/test_meta_realtime_transformation.py new file mode 100644 index 00000000000..a5d7e47fb65 --- /dev/null +++ b/tests/test_litellm/llms/meta/realtime/test_meta_realtime_transformation.py @@ -0,0 +1,683 @@ +import base64 +import itertools +import json +from typing import Final +from unittest.mock import MagicMock + +import pytest + +from litellm.llms.meta.realtime.transformation import ( + DEFAULT_MUSE_REALTIME_URL, + MUSE_MODEL, + MetaRealtimeConfig, + MuseEventTransformer, + MuseProtocolError, + MuseSessionConfig, + build_muse_realtime_url, + normalize_access_token, + normalize_language, + parse_session_update, + session_created_event, +) +from litellm.types.llms.meta import MuseMode +from litellm.types.realtime import RealtimeResponseTransformInput + +EMPTY_TRANSFORM_INPUT: Final[RealtimeResponseTransformInput] = { + "session_configuration_request": None, + "current_output_item_id": None, + "current_response_id": None, + "current_delta_chunks": None, + "current_item_chunks": None, + "current_conversation_id": None, + "current_delta_type": None, +} + + +def _event(event_type: str, **fields: object) -> str: + return json.dumps({"type": event_type, **fields}) + + +def _ga_session_update(rate: int = 24_000, turn_detection: object = "server_vad") -> str: + return _event( + "session.update", + session={ + "type": "transcription", + "audio": { + "input": { + "format": {"type": "audio/pcm", "rate": rate}, + "turn_detection": None if turn_detection is None else {"type": turn_detection}, + "transcription": {"model": f"meta/{MUSE_MODEL}"}, + } + }, + }, + ) + + +def _configured(rate: int = 24_000, turn_detection: object = "server_vad", **kwargs: object) -> MetaRealtimeConfig: + config = MetaRealtimeConfig(**kwargs) + config.validate_environment({}, MUSE_MODEL, api_key="secret-token") + config.transform_realtime_request(_ga_session_update(rate, turn_detection), MUSE_MODEL) + return config + + +def _backend_events(config: MetaRealtimeConfig, payload: str) -> list[dict[str, object]]: + response = config.transform_realtime_response(payload, MUSE_MODEL, MagicMock(), EMPTY_TRANSFORM_INPUT)["response"] + assert isinstance(response, list) + return response + + +def test_beta_session_translates_language_and_drops_non_openai_hints(): + config = parse_session_update( + _event( + "session.update", + session={ + "type": "transcription", + "input_audio_format": "pcm16", + "turn_detection": {"type": "server_vad"}, + "input_audio_transcription": { + "model": "meta/muse-voice-transcribe-1.0", + "language": "en-US", + "prompt": "must not become a keyword", + }, + }, + ), + "meta/muse-voice-transcribe-1.0", + ) + + assert config.sample_rate == 24_000 + assert config.packet_bytes == 3_840 + assert config.mode == "ENDPOINTING" + assert config.language_bias == ("English",) + assert config.handshake("Bearer token") == { + "mode": "ENDPOINTING", + "authorization": {"accessToken": "Bearer token"}, + "audioEncoding": "PCM_24KHZ", + "model": MUSE_MODEL, + "partialMode": "CUMULATIVE", + "emitAudioProgress": True, + "languageBias": ("English",), + } + assert "must not become a keyword" not in json.dumps(config.handshake("Bearer token")) + + +def test_ga_session_accepts_16khz_mono_push_to_talk(): + config = parse_session_update( + _event( + "session.update", + session={ + "type": "transcription", + "audio": { + "input": { + "format": {"type": "audio/pcm", "rate": 16000, "channels": 1}, + "turn_detection": None, + "transcription": {"model": MUSE_MODEL, "language": "zh-Hans"}, + } + }, + }, + ), + MUSE_MODEL, + ) + + assert config.sample_rate == 16_000 + assert config.packet_bytes == 2_560 + assert config.mode == "PUSH_TO_TALK" + assert config.language_bias == ("Mandarin Chinese",) + assert config.handshake("Bearer token")["audioEncoding"] == "PCM_16KHZ" + assert "languageBias" not in MuseSessionConfig(MUSE_MODEL, "ENDPOINTING", 24_000, ()).handshake("Bearer token") + + +@pytest.mark.parametrize( + ("source", "expected"), + [ + ("EN_us", "English"), + ("mandarin chinese", "Mandarin Chinese"), + ("fil-PH", "Tagalog"), + ("iw-IL", "Hebrew"), + ("pt-BR", "Portuguese"), + ], +) +def test_language_normalization_uses_official_muse_names(source: str, expected: str): + assert normalize_language(source) == expected + + +@pytest.mark.parametrize( + ("session", "message"), + [ + ({"input_audio_format": "g711_ulaw"}, "requires pcm16"), + ({"audio": {"input": {"format": {"type": "audio/pcm", "rate": 8000}}}}, "16000 Hz or 24000 Hz"), + ( + {"audio": {"input": {"format": {"type": "audio/pcm", "rate": 24000, "channels": 2}}}}, + "requires mono", + ), + ( + {"input_audio_format": "pcm16", "audio": {"input": {"format": {"type": "audio/pcm"}}}}, + "either beta or GA layout", + ), + ({"input_audio_transcription": {"model": "other-model"}}, "cannot be changed"), + ({"input_audio_transcription": {"language": "xx"}}, "unsupported Muse Voice language"), + ({"turn_detection": {"type": "semantic_vad"}}, "server_vad turn detection or null"), + ({"type": "realtime", "audio": {"input": {"turn_detection": {"type": "semantic_vad"}}}}, "server_vad"), + ], +) +def test_session_rejects_unsupported_audio_model_and_hints(session: dict[str, object], message: str): + with pytest.raises(MuseProtocolError, match=message): + parse_session_update(_event("session.update", session={"type": "transcription", **session}), MUSE_MODEL) + + +def test_session_created_event_exposes_openai_transcription_shape(): + config = parse_session_update( + _event( + "session.update", + session={ + "audio": { + "input": { + "format": {"type": "audio/pcm", "rate": 24000}, + "transcription": {"model": MUSE_MODEL, "language": "ja"}, + } + }, + }, + ), + MUSE_MODEL, + ) + + created = session_created_event(config, "provider-session") + + assert created["type"] == "session.created" + assert created["session"]["id"] == "provider-session" + assert created["session"]["type"] == "transcription" + assert created["session"]["audio"]["input"]["turn_detection"] == {"type": "server_vad"} + assert created["session"]["audio"]["input"]["transcription"] == {"model": MUSE_MODEL, "language": "Japanese"} + + +def test_turnless_empty_silence_transcript_is_ignored(): + transformer = MuseEventTransformer() + + assert transformer.transform(json.loads(_event("transcript", transcript="", final=True))) == () + + +def test_transcript_without_speech_start_synthesizes_start_before_delta(): + transformer = MuseEventTransformer() + + events = transformer.transform(json.loads(_event("transcript", turnId="turn-1", transcript="hello", final=False))) + + assert [event["type"] for event in events] == [ + "input_audio_buffer.speech_started", + "conversation.item.input_audio_transcription.delta", + ] + + +def test_cumulative_partials_emit_only_extensions_and_final_is_authoritative(): + transformer = MuseEventTransformer() + + def send(payload: str) -> tuple[dict[str, object], ...]: + return transformer.transform(json.loads(payload)) + + started = send(_event("speechStart", turnId="turn-1")) + first = send(_event("transcript", turnId="turn-1", transcript="hello", final=False)) + extension = send(_event("transcript", turnId="turn-1", transcript="hello world", final=False)) + rewrite = send(_event("transcript", turnId="turn-1", transcript="hullo world", final=False)) + completed = send(_event("speechComplete", turnId="turn-1", transcript="hullo world")) + + assert [event["type"] for event in started] == ["input_audio_buffer.speech_started"] + assert first[0]["delta"] == "hello" + assert extension[0]["delta"] == " world" + assert rewrite == () + assert completed[0]["type"] == "input_audio_buffer.speech_stopped" + assert completed[1]["type"] == "conversation.item.input_audio_transcription.completed" + assert completed[1]["item_id"] == "turn-1" + assert completed[1]["transcript"] == "hullo world" + assert send(_event("speechEnd", turnId="turn-1")) == () + + +def test_speech_end_then_speech_complete_emits_stopped_then_completed(): + transformer = MuseEventTransformer() + + transformer.transform(json.loads(_event("speechStart", turnId="turn-1"))) + stopped = transformer.transform(json.loads(_event("speechEnd", turnId="turn-1"))) + completed = transformer.transform(json.loads(_event("speechComplete", turnId="turn-1", transcript="done"))) + + assert [event["type"] for event in stopped] == ["input_audio_buffer.speech_stopped"] + assert [event["type"] for event in completed] == ["conversation.item.input_audio_transcription.completed"] + assert completed[0]["transcript"] == "done" + + +def test_turnless_partial_between_speech_end_and_speech_complete_stays_on_that_turn(): + transformer = MuseEventTransformer() + transformer.transform(json.loads(_event("speechStart", turnId="turn-1"))) + transformer.transform(json.loads(_event("transcript", transcript="what is", final=False))) + transformer.transform(json.loads(_event("speechEnd", turnId="turn-1"))) + + post_processed = transformer.transform( + json.loads(_event("transcript", transcript="what is the weather", final=False)) + ) + completed = transformer.transform( + json.loads(_event("speechComplete", turnId="turn-1", transcript="What is the weather?")) + ) + + assert _typed(post_processed) == [("conversation.item.input_audio_transcription.delta", "turn-1")] + assert post_processed[0]["delta"] == " the weather" + assert _typed(completed) == [("conversation.item.input_audio_transcription.completed", "turn-1")] + assert completed[0]["transcript"] == "What is the weather?" + + +def _typed(events: tuple[dict[str, object], ...]) -> list[tuple[object, object]]: + return [(event["type"], event["item_id"]) for event in events] + + +def test_overlapping_turns_emit_independently_and_correlate_by_item_id(): + transformer = MuseEventTransformer() + + def send(payload: str) -> list[tuple[object, object]]: + return _typed(transformer.transform(json.loads(payload))) + + assert send(_event("speechStart", turnId="turn-a")) == [("input_audio_buffer.speech_started", "turn-a")] + assert send(_event("speechStart", turnId="turn-b")) == [("input_audio_buffer.speech_started", "turn-b")] + assert send(_event("transcript", turnId="turn-b", transcript="second", final=False)) == [ + ("conversation.item.input_audio_transcription.delta", "turn-b") + ] + assert send(_event("speechComplete", turnId="turn-a", transcript="first")) == [ + ("input_audio_buffer.speech_stopped", "turn-a"), + ("conversation.item.input_audio_transcription.completed", "turn-a"), + ] + assert send(_event("speechEnd", turnId="turn-a")) == [] + assert send(_event("speechEnd", turnId="turn-b")) == [("input_audio_buffer.speech_stopped", "turn-b")] + assert send(_event("speechComplete", turnId="turn-b", transcript="second final")) == [ + ("conversation.item.input_audio_transcription.completed", "turn-b") + ] + + +def test_empty_vad_turn_is_closed_and_does_not_block_the_next_turn(): + transformer = MuseEventTransformer() + + def send(payload: str) -> list[tuple[object, object]]: + return _typed(transformer.transform(json.loads(payload))) + + assert send(_event("speechStart", turnId="noise")) == [("input_audio_buffer.speech_started", "noise")] + assert send(_event("speechEnd", turnId="noise")) == [("input_audio_buffer.speech_stopped", "noise")] + assert send(_event("speechStart", turnId="speech")) == [("input_audio_buffer.speech_started", "speech")] + assert send(_event("transcript", turnId="speech", transcript="hello", final=False)) == [ + ("conversation.item.input_audio_transcription.delta", "speech") + ] + assert send(_event("speechEnd", turnId="speech")) == [("input_audio_buffer.speech_stopped", "speech")] + assert send(_event("speechComplete", turnId="speech", transcript="hello world")) == [ + ("conversation.item.input_audio_transcription.completed", "speech") + ] + + +@pytest.mark.parametrize("transcript", ["", "late words"]) +def test_late_speech_complete_after_an_empty_speech_end_completes_that_item(transcript: str): + transformer = MuseEventTransformer() + transformer.transform(json.loads(_event("speechStart", turnId="turn-1"))) + transformer.transform(json.loads(_event("speechEnd", turnId="turn-1"))) + transformer.transform(json.loads(_event("speechStart", turnId="turn-2"))) + + (completed,) = transformer.transform(json.loads(_event("speechComplete", turnId="turn-1", transcript=transcript))) + + assert completed["type"] == "conversation.item.input_audio_transcription.completed" + assert completed["item_id"] == "turn-1" + assert completed["transcript"] == transcript + + +def test_push_to_talk_speech_complete_closes_the_turn_without_speech_end(): + transformer = MuseEventTransformer() + transformer.configure(MuseSessionConfig(MUSE_MODEL, "PUSH_TO_TALK", 24_000, ())) + + transformer.transform(json.loads(_event("speechStart", turnId="turn-1"))) + transformer.transform(json.loads(_event("transcript", turnId="turn-1", transcript="hel", final=False))) + events = transformer.transform(json.loads(_event("speechComplete", turnId="turn-1", transcript="hello"))) + + assert [event["type"] for event in events] == [ + "input_audio_buffer.speech_stopped", + "conversation.item.input_audio_transcription.completed", + ] + assert events[1]["transcript"] == "hello" + + +_TERMINAL_SIGNALS: Final = { + "speechEnd": _event("speechEnd", turnId="turn-1"), + "speechComplete": _event("speechComplete", turnId="turn-1", transcript="final words"), + "final": _event("transcript", turnId="turn-1", transcript="final words", final=True), +} +_TERMINAL_ORDERINGS: Final = tuple( + ordering for size in (1, 2, 3) for ordering in itertools.permutations(_TERMINAL_SIGNALS, size) +) + + +@pytest.mark.parametrize("mode", ["ENDPOINTING", "PUSH_TO_TALK"]) +@pytest.mark.parametrize("ordering", _TERMINAL_ORDERINGS, ids="-".join) +def test_every_terminal_signal_order_closes_the_turn_exactly_once(mode: MuseMode, ordering: tuple[str, ...]): + transformer = MuseEventTransformer() + transformer.configure(MuseSessionConfig(MUSE_MODEL, mode, 24_000, ())) + transformer.transform(json.loads(_event("speechStart", turnId="turn-1"))) + transformer.transform(json.loads(_event("transcript", turnId="turn-1", transcript="fin", final=False))) + + emitted = [ + event["type"] for signal in ordering for event in transformer.transform(json.loads(_TERMINAL_SIGNALS[signal])) + ] + replayed = [ + event["type"] for signal in ordering for event in transformer.transform(json.loads(_TERMINAL_SIGNALS[signal])) + ] + + has_text = bool(set(ordering) & {"speechComplete", "final"}) + assert emitted == [ + "input_audio_buffer.speech_stopped", + *(["conversation.item.input_audio_transcription.completed"] if has_text else []), + ] + assert replayed == [] + + +def test_push_to_talk_final_transcript_completes_without_speech_end(): + transformer = MuseEventTransformer() + transformer.configure(MuseSessionConfig(MUSE_MODEL, "PUSH_TO_TALK", 24_000, ())) + + events = transformer.transform(json.loads(_event("transcript", transcript="hello there", final=True))) + + assert [event["type"] for event in events] == [ + "input_audio_buffer.speech_started", + "input_audio_buffer.speech_stopped", + "conversation.item.input_audio_transcription.completed", + ] + assert events[2]["transcript"] == "hello there" + assert str(events[0]["item_id"]).startswith("item_") + + +def test_positive_audio_progress_deltas_attach_to_next_completion_and_speaker_is_ignored(): + transformer = MuseEventTransformer() + + def send(payload: str) -> tuple[dict[str, object], ...]: + return transformer.transform(json.loads(payload)) + + send(_event("audioProgress", audioProcessedMs=1000)) + send(_event("audioProgress", audioProcessedMs=750)) + send(_event("audioProgress", audioProcessedMs=1600)) + assert send(_event("speaker", turnId=42, label=" Speaker 2 ")) == () + completed = send(_event("speechComplete", turnId=42, transcript="hello")) + + assert "speaker" not in completed[-1] + assert completed[-1]["usage"] == {"type": "duration", "seconds": 1.6} + assert transformer.take_unbilled_usage() is None + assert send(_event("speechEnd", turnId=42)) == () + + +def test_trailing_audio_progress_is_returned_once(): + transformer = MuseEventTransformer() + + transformer.transform(json.loads(_event("audioProgress", audioProcessedMs=250))) + + assert transformer.take_unbilled_usage() == {"type": "duration", "seconds": 0.25} + assert transformer.take_unbilled_usage() is None + + +def test_finished_turn_ignores_late_duplicates(): + transformer = MuseEventTransformer() + + released = transformer.transform(json.loads(_event("speechComplete", turnId="turn-1", transcript="done"))) + + assert [event["type"] for event in released] == [ + "input_audio_buffer.speech_started", + "input_audio_buffer.speech_stopped", + "conversation.item.input_audio_transcription.completed", + ] + assert transformer.transform(json.loads(_event("speechComplete", turnId="turn-1", transcript="duplicate"))) == () + assert transformer.transform(json.loads(_event("speechEnd", turnId="turn-1"))) == () + assert transformer.transform(json.loads(_event("speechStart", turnId="turn-1"))) == () + assert ( + transformer.transform(json.loads(_event("transcript", turnId="turn-1", transcript="late", final=False))) == () + ) + + +def test_late_duplicate_speech_start_does_not_capture_the_next_turnless_transcript(): + transformer = MuseEventTransformer() + transformer.configure(MuseSessionConfig(MUSE_MODEL, "PUSH_TO_TALK", 24_000, ())) + transformer.transform(json.loads(_event("speechStart", turnId="turn-1"))) + transformer.transform(json.loads(_event("speechComplete", turnId="turn-1", transcript="first"))) + + assert transformer.transform(json.loads(_event("speechStart", turnId="turn-1"))) == () + events = transformer.transform(json.loads(_event("transcript", transcript="second", final=True))) + + assert [event["type"] for event in events] == [ + "input_audio_buffer.speech_started", + "input_audio_buffer.speech_stopped", + "conversation.item.input_audio_transcription.completed", + ] + assert events[2]["transcript"] == "second" + assert events[2]["item_id"] != "turn-1" + + +def test_turn_memory_is_bounded_by_turn_limit(): + transformer = MuseEventTransformer(turn_limit=2) + + transformer.transform(json.loads(_event("speechComplete", turnId="turn-1", transcript="one"))) + transformer.transform(json.loads(_event("speechComplete", turnId="turn-2", transcript="two"))) + assert transformer.transform(json.loads(_event("speechEnd", turnId="turn-1"))) == () + transformer.transform(json.loads(_event("speechComplete", turnId="turn-3", transcript="three"))) + + forgotten = transformer.transform(json.loads(_event("speechEnd", turnId="turn-1"))) + + assert [event["type"] for event in forgotten] == ["input_audio_buffer.speech_stopped"] + + +def test_provider_error_is_sanitized_and_encodable(): + token = "private-token" + provider_body = f"authorization failed for Bearer {token}" + transformed = MuseEventTransformer().transform( + json.loads(_event("error", code="AUTH", message=provider_body, request={"accessToken": token})) + ) + + encoded = json.dumps(transformed[0]) + assert json.loads(encoded)["error"] == { + "type": "server_error", + "message": "Meta Muse realtime transcription failed", + } + assert token not in encoded + assert provider_body not in encoded + + +@pytest.mark.parametrize( + ("raw", "expected"), + [("token", "Bearer token"), (" Bearer token ", "Bearer token"), ("bearer token", "Bearer token")], +) +def test_access_token_normalization_adds_single_bearer_prefix(raw: str, expected: str): + assert normalize_access_token(raw) == expected + + +@pytest.mark.parametrize("raw", ["", " ", "Bearer", " bearer "]) +def test_access_token_normalization_rejects_empty_tokens(raw: str): + with pytest.raises(ValueError, match=r"token|key is required"): + normalize_access_token(raw) + + +@pytest.mark.parametrize( + ("api_base", "expected"), + [ + (None, DEFAULT_MUSE_REALTIME_URL), + ("https://example.test/custom/path?ignored=yes", "wss://example.test/v1/asr/realtime"), + ("wss://example.test:8443/other", "wss://example.test:8443/v1/asr/realtime"), + ], +) +def test_realtime_url_pins_muse_path(api_base: str | None, expected: str): + assert build_muse_realtime_url(api_base) == expected + assert MetaRealtimeConfig().get_complete_url(api_base, f"meta/{MUSE_MODEL}") == expected + + +@pytest.mark.parametrize( + "api_base", + [ + "http://example.test", + "ws://example.test", + "wss://user:pass@example.test", + "wss://example.test/path#fragment", + "not-a-url", + ], +) +def test_realtime_url_rejects_insecure_or_ambiguous_bases(api_base: str): + with pytest.raises(ValueError, match="absolute wss:// or https://"): + build_muse_realtime_url(api_base) + + +def test_unsupported_model_is_rejected_before_connecting(): + with pytest.raises(ValueError, match="Unsupported Meta realtime model: meta/other-model"): + MetaRealtimeConfig().get_complete_url(None, "meta/other-model") + + +def test_missing_api_key_is_rejected(monkeypatch: pytest.MonkeyPatch): + monkeypatch.delenv("META_API_KEY", raising=False) + + with pytest.raises(ValueError, match="api_key is required for Meta API calls"): + MetaRealtimeConfig().validate_environment({}, MUSE_MODEL) + + +def test_bearer_token_travels_only_in_the_json_handshake(): + config = MetaRealtimeConfig() + headers = {"x-existing": "kept"} + + assert config.validate_environment(headers, MUSE_MODEL, api_key="secret-token") == {"x-existing": "kept"} + (handshake,) = config.transform_realtime_request(_ga_session_update(), MUSE_MODEL) + + assert isinstance(handshake, str) + assert json.loads(handshake)["authorization"] == {"accessToken": "Bearer secret-token"} + assert config.is_setup_message(json.loads(handshake)) is True + assert config.is_setup_message({"type": "input_audio_buffer.append"}) is False + assert config.transform_realtime_request(_ga_session_update(), MUSE_MODEL) == () + + +def test_synthetic_session_created_uses_default_transcription_shape(): + created = MetaRealtimeConfig().transform_session_created_event(f"meta/{MUSE_MODEL}", "trace-1") + + assert created["type"] == "session.created" + assert created["session"]["id"] == "trace-1" + assert created["session"]["audio"]["input"]["format"] == {"type": "audio/pcm", "rate": 24000} + assert created["session"]["audio"]["input"]["transcription"] == {"model": MUSE_MODEL} + + +def test_audio_before_session_update_is_rejected(): + config = MetaRealtimeConfig() + config.validate_environment({}, MUSE_MODEL, api_key="secret-token") + + with pytest.raises(MuseProtocolError, match=r"session\.update must configure"): + config.transform_realtime_request(_event("input_audio_buffer.append", audio="AAAA"), MUSE_MODEL) + + +@pytest.mark.parametrize(("rate", "packet_bytes"), [(16_000, 2_560), (24_000, 3_840)]) +def test_pcm_is_packetized_into_raw_binary_frames(rate: int, packet_bytes: int): + config = _configured(rate=rate) + pcm = b"\xff\xfe\x00\x80" * (packet_bytes // 2) + b"\x01\x02\x03\x04" + + frames = config.transform_realtime_request( + _event("input_audio_buffer.append", audio=base64.b64encode(pcm).decode()), MUSE_MODEL + ) + remainder = config.transform_realtime_request(_event("input_audio_buffer.commit"), MUSE_MODEL) + + assert frames == (pcm[:packet_bytes], pcm[packet_bytes : packet_bytes * 2]) + assert remainder == (pcm[packet_bytes * 2 :],) + + +@pytest.mark.parametrize( + ("audio", "message"), + [ + ("not base64!", "valid base64"), + (base64.b64encode(b"\x00").decode(), "complete samples"), + (12, "base64 string"), + ("A" * (4 * ((24_000 * 2 * 4 + 2) // 3) + 4), "four-second backlog"), + ], +) +def test_invalid_audio_appends_are_rejected(audio: object, message: str): + config = _configured() + + with pytest.raises(MuseProtocolError, match=message): + config.transform_realtime_request(_event("input_audio_buffer.append", audio=audio), MUSE_MODEL) + + +@pytest.mark.asyncio +async def test_backend_sends_are_paced_to_real_time(): + sleeps: list[float] = [] + + async def record_sleep(delay: float) -> None: + sleeps.append(delay) + + config = _configured(monotonic=lambda: 10.0, sleep=record_sleep) + packet = b"\x01\x02" * 1_920 + + await config.pace_backend_send(packet) + await config.pace_backend_send(packet) + await config.pace_backend_send(packet) + + assert sleeps == pytest.approx([0.08, 0.16]) + + +def test_endpointing_commit_flushes_without_end_stream_but_end_sends_it_once(): + config = _configured(turn_detection="server_vad") + + assert config.transform_realtime_request(_event("input_audio_buffer.commit"), MUSE_MODEL) == () + assert config.transform_realtime_request(_event("input_audio_buffer.end"), MUSE_MODEL) == ('{"type":"endStream"}',) + assert config.transform_realtime_request(_event("input_audio_buffer.end"), MUSE_MODEL) == () + + +def test_push_to_talk_commit_ends_the_stream_once(): + config = _configured(turn_detection=None) + config.transform_realtime_request( + _event("input_audio_buffer.append", audio=base64.b64encode(b"\x01\x02").decode()), MUSE_MODEL + ) + + assert config.transform_realtime_request(_event("input_audio_buffer.commit"), MUSE_MODEL) == ( + b"\x01\x02", + '{"type":"endStream"}', + ) + assert config.transform_realtime_request(_event("input_audio_buffer.end"), MUSE_MODEL) == () + + +def test_clear_drops_buffered_remainder_and_unknown_events_are_ignored(): + config = _configured() + config.transform_realtime_request( + _event("input_audio_buffer.append", audio=base64.b64encode(b"\x01\x02").decode()), MUSE_MODEL + ) + + assert config.transform_realtime_request(_event("input_audio_buffer.clear"), MUSE_MODEL) == () + assert config.transform_realtime_request(_event("response.create"), MUSE_MODEL) == () + assert config.transform_realtime_request(_event("input_audio_buffer.commit"), MUSE_MODEL) == () + + +def test_provider_ack_becomes_session_created_with_provider_id(): + config = _configured(rate=16_000, turn_detection=None) + + (created,) = _backend_events(config, json.dumps({"sessionId": " provider-session "})) + + assert created["type"] == "session.created" + assert created["session"]["id"] == "provider-session" + assert created["session"]["audio"]["input"]["format"]["rate"] == 16000 + assert created["session"]["audio"]["input"]["turn_detection"] is None + + +def test_provider_turn_events_and_close_usage_flow_through_config(): + config = _configured() + + assert _backend_events(config, json.dumps({"type": "audioProgress", "audioProcessedMs": 1349})) == [] + assert _backend_events(config, _event("speechStart", turnId="t1"))[0]["type"] == "input_audio_buffer.speech_started" + assert _backend_events(config, _event("speechEnd", turnId="t1"))[0]["type"] == "input_audio_buffer.speech_stopped" + completed = _backend_events(config, _event("speechComplete", turnId="t1", transcript="what is the weather")) + + assert [event["type"] for event in completed] == ["conversation.item.input_audio_transcription.completed"] + assert completed[0]["usage"] == {"type": "duration", "seconds": 1.349} + assert config.unbilled_usage_on_session_close(MUSE_MODEL) is None + + assert _backend_events(config, json.dumps({"type": "audioProgress", "audioProcessedMs": 2349})) == [] + assert config.unbilled_usage_on_session_close(MUSE_MODEL) == {"type": "duration", "seconds": 1.0} + + +def test_provider_error_frame_becomes_openai_error_without_leaking_token(): + config = _configured() + + (error,) = _backend_events(config, _event("error", message="bad token secret-token")) + + assert error == { + "type": "error", + "error": {"type": "server_error", "message": "Meta Muse realtime transcription failed"}, + } + assert "secret-token" not in json.dumps(error) + + +def test_invalid_provider_ack_is_rejected(): + config = _configured() + + with pytest.raises(MuseProtocolError, match="invalid handshake response"): + _backend_events(config, json.dumps({"sessionId": ""})) diff --git a/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py b/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py index 5a29a96829f..cb884fb7cc1 100644 --- a/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py +++ b/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py @@ -1893,6 +1893,183 @@ class TestScanOnlyToolResults: assert data["messages"][4]["content"] == "and then?" +class TestNoScannableContentRecordsNotRun: + """LIT-6314: a guardrail whose scoping leaves nothing to scan must still persist an evaluation record""" + + def _system_only_data(self) -> dict: + return {"messages": [{"role": "system", "content": "SYSTEM-PROMPT"}]} + + def _recorded_entries(self, data: dict) -> list: + metadata = data.get("metadata") or data.get("litellm_metadata") or {} + return metadata.get("standard_logging_guardrail_information") or [] + + @pytest.mark.asyncio + async def test_skipped_scan_records_not_run_entry(self): + handler = OpenAIChatCompletionsHandler() + guardrail = MockGuardrail(guardrail_name="skip-system-guardrail") + guardrail.skip_system_message_in_guardrail = True + data = self._system_only_data() + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.last_inputs is None, "nothing survived scoping, apply_guardrail must not run" + entries = self._recorded_entries(data) + assert len(entries) == 1 + assert entries[0]["guardrail_name"] == "skip-system-guardrail" + assert entries[0]["guardrail_status"] == "not_run" + assert entries[0]["guardrail_response"] == "no scannable content after message scoping" + + @pytest.mark.asyncio + @pytest.mark.parametrize("skip_system", [False, True]) + async def test_empty_content_does_not_blame_scoping(self, skip_system: bool): + handler = OpenAIChatCompletionsHandler() + guardrail = MockGuardrail(guardrail_name="unscoped-guardrail") + guardrail.skip_system_message_in_guardrail = skip_system + data = {"messages": [{"role": "user", "content": None}]} + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.last_inputs is None + entries = self._recorded_entries(data) + assert len(entries) == 1 + assert entries[0]["guardrail_status"] == "not_run" + assert entries[0]["guardrail_response"] == "no scannable content" + + @pytest.mark.asyncio + async def test_self_recording_guardrail_is_left_alone(self): + handler = OpenAIChatCompletionsHandler() + guardrail = MockGuardrail(guardrail_name="self-recording-guardrail") + guardrail.skip_system_message_in_guardrail = True + guardrail.records_own_guardrail_information = True + data = self._system_only_data() + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.last_inputs is None + assert self._recorded_entries(data) == [] + + @pytest.mark.asyncio + async def test_scannable_content_records_no_extra_entry(self): + handler = OpenAIChatCompletionsHandler() + guardrail = MockGuardrail(guardrail_name="normal-guardrail") + data = {"messages": [{"role": "user", "content": "hello"}]} + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.last_inputs is not None + assert all(e.get("guardrail_status") != "not_run" for e in self._recorded_entries(data)) + + @pytest.mark.asyncio + async def test_image_only_content_is_not_reported_as_not_run(self): + """Images are only scanned alongside text, so an image-only request is a + pre-existing scan gap, not a message-scoping skip, and must not be labelled one""" + handler = OpenAIChatCompletionsHandler() + guardrail = MockGuardrail(guardrail_name="image-guardrail") + guardrail.skip_system_message_in_guardrail = True + data = { + "messages": [ + {"role": "system", "content": "SYSTEM-PROMPT"}, + { + "role": "user", + "content": [{"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}}], + }, + ] + } + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert self._recorded_entries(data) == [] + + @pytest.mark.asyncio + async def test_scoped_out_image_only_message_is_not_reported_as_not_run(self): + """An image in a skipped role must behave like any other image-only request""" + handler = OpenAIChatCompletionsHandler() + guardrail = MockGuardrail(guardrail_name="image-guardrail") + guardrail.skip_system_message_in_guardrail = True + data = { + "messages": [ + { + "role": "system", + "content": [{"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}}], + }, + ] + } + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.last_inputs is None + assert self._recorded_entries(data) == [] + + @pytest.mark.asyncio + async def test_scoped_out_text_with_image_records_not_run(self): + """Scoping removed text too, so the skip is recorded even though an image sat beside it""" + handler = OpenAIChatCompletionsHandler() + guardrail = MockGuardrail(guardrail_name="image-guardrail") + guardrail.skip_system_message_in_guardrail = True + data = { + "messages": [ + { + "role": "system", + "content": [ + {"type": "text", "text": "Describe this picture."}, + {"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}}, + ], + }, + ] + } + + await handler.process_input_messages(data=data, guardrail_to_apply=guardrail) + + assert guardrail.last_inputs is None + entries = self._recorded_entries(data) + assert len(entries) == 1 + assert entries[0]["guardrail_status"] == "not_run" + assert entries[0]["guardrail_response"] == "no scannable content after message scoping" + + +class ToolDroppingTextGuardrail(CustomGuardrail): + """Answers one text per non-tool message it saw, the way a guardrail that + filters tool rows out before scanning does, and hands back only texts.""" + + def __init__(self): + super().__init__(guardrail_name="tool-dropping-redactor") + + async def apply_guardrail( + self, + inputs: GenericGuardrailAPIInputs, + request_data: dict, + input_type: Literal["request", "response"], + logging_obj: Optional[Any] = None, + ) -> GenericGuardrailAPIInputs: + kept = [m for m in inputs.get("structured_messages") or [] if m.get("role") != "tool"] + return {**inputs, "texts": [str(m.get("content")).replace("POISON", "[BLOCKED]") for m in kept]} + + +class TestPerMessageTextWriteBack: + """Texts that no longer pair one-to-one with what the handler extracted must be + rejected by name instead of sliding onto the wrong messages.""" + + @pytest.mark.asyncio + async def test_fewer_texts_than_extracted_over_a_tool_message_is_rejected(self): + from litellm.llms.base_llm.guardrail_translation.utils import UnappliableRequestRewrite + + handler = OpenAIChatCompletionsHandler() + original_messages = [ + {"role": "system", "content": "SYSTEM-PROMPT"}, + {"role": "user", "content": "fetch the page"}, + {"role": "assistant", "content": "fetching"}, + {"role": "tool", "tool_call_id": "call_1", "content": "page says POISON here"}, + {"role": "user", "content": "and then?"}, + ] + data = {"messages": json.loads(json.dumps(original_messages))} + + with pytest.raises(UnappliableRequestRewrite) as excinfo: + await handler.process_input_messages(data=data, guardrail_to_apply=ToolDroppingTextGuardrail()) + + assert excinfo.value.guardrail_name == "tool-dropping-redactor" + assert data["messages"] == original_messages, "a rejected rewrite must leave the request untouched" + + class TestBuildBlockSseChunks: """build_block_sse_chunks turns a streaming ModifyResponseException into 200 SSE chunks""" diff --git a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py index a4f0a77a9b6..48d86384633 100644 --- a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py +++ b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py @@ -8,7 +8,7 @@ with guardrail transformations. import copy from collections.abc import Callable from typing import Any, List, Literal, Optional, Tuple -from unittest.mock import AsyncMock, MagicMock +from unittest.mock import AsyncMock, MagicMock, patch import logging @@ -31,6 +31,7 @@ from litellm.llms.openai.responses.guardrail_translation.handler import ( OpenAIResponsesHandler, ) from litellm.llms.openai.responses.guardrail_translation.tool_merge import merge_guardrailed_tools +from litellm.proxy.guardrails.guardrail_hooks.generic_guardrail_api import GenericGuardrailAPI from litellm.types.llms.openai import ChatCompletionToolCallChunk from litellm.responses.litellm_completion_transformation.transformation import ( LiteLLMCompletionResponsesConfig, @@ -2338,6 +2339,135 @@ def _parallel_tool_call_input() -> list: ] +SSN = "123-45-6789" +REDACTED_SSN = "" + + +def _redacted(value: object) -> object: + if isinstance(value, str): + return value.replace(SSN, REDACTED_SSN) + if isinstance(value, list): + return [{**part, "text": _redacted(part["text"])} if "text" in part else part for part in value] + return value + + +def _per_message_guardrail_server(structured_messages_in_answer: bool) -> Callable[..., MagicMock]: + """Answers one redacted text per chat row it was shown, the way a guardrail + that scans per message does, and optionally the rewritten rows themselves.""" + + def post(url: str, json: dict, headers: dict) -> MagicMock: + rows = json["structured_messages"] + answer: dict = { + "action": "GUARDRAIL_INTERVENED", + "texts": [_redacted(row["content"]) if isinstance(row.get("content"), str) else "" for row in rows], + } + if structured_messages_in_answer: + answer["structured_messages"] = [{**row, "content": _redacted(row.get("content"))} for row in rows] + response = MagicMock() + response.json.return_value = answer + response.raise_for_status = MagicMock() + return response + + return post + + +def _per_message_redactor() -> GenericGuardrailAPI: + return GenericGuardrailAPI( + api_base="https://guardrail.test", + guardrail_name="per-message-redactor", + event_hook="pre_call", + default_on=True, + ) + + +def _tool_replay_request() -> dict: + return { + "model": "gpt-5.6", + "instructions": "Never repeat the SSN " + SSN + " back.", + "input": [ + {"role": "user", "content": "Look up " + SSN + " for me."}, + {"type": "function_call", "call_id": "call_1", "name": "lookup_customer", "arguments": '{"id": "42"}'}, + {"type": "function_call_output", "call_id": "call_1", "output": '{"ssn": "' + SSN + '"}'}, + ], + } + + +def _string_input_request() -> dict: + return { + "model": "gpt-5.6", + "instructions": "Never repeat the SSN " + SSN + " back.", + "input": "My SSN is " + SSN + ".", + } + + +class TestPerMessageRewriteWriteBack: + """A guardrail that rewrites per chat row hands the rows back as + structured_messages, and the handler lands them on the instructions and the + input items they came from; the same rewrite handed back as texts alone has + no item to land on and is rejected by name instead of sent unrewritten.""" + + @pytest.mark.asyncio + async def test_structured_rows_land_on_instructions_and_tool_output(self): + guardrail = _per_message_redactor() + data = _tool_replay_request() + function_call_item = data["input"][1] + + with patch.object(guardrail.async_handler, "post", side_effect=_per_message_guardrail_server(True)): + result = await OpenAIResponsesHandler().process_input_messages(data, guardrail) + + assert result["instructions"] == "Never repeat the SSN " + REDACTED_SSN + " back." + assert _texts(result["input"][0]) == ["Look up " + REDACTED_SSN + " for me."] + assert result["input"][1] == function_call_item + assert result["input"][2] == { + "type": "function_call_output", + "call_id": "call_1", + "output": '{"ssn": "' + REDACTED_SSN + '"}', + } + + @pytest.mark.asyncio + async def test_texts_only_per_message_answer_is_rejected_by_name(self): + from litellm.llms.base_llm.guardrail_translation.utils import UnappliableRequestRewrite + + guardrail = _per_message_redactor() + data = _tool_replay_request() + original = copy.deepcopy(data) + + with patch.object(guardrail.async_handler, "post", side_effect=_per_message_guardrail_server(False)): + with pytest.raises(UnappliableRequestRewrite) as excinfo: + await OpenAIResponsesHandler().process_input_messages(data, guardrail) + + assert excinfo.value.guardrail_name == "per-message-redactor" + assert data["input"] == original["input"] + assert data["instructions"] == original["instructions"] + + @pytest.mark.asyncio + async def test_structured_rows_land_on_instructions_and_string_input(self): + guardrail = _per_message_redactor() + data = _string_input_request() + + with patch.object(guardrail.async_handler, "post", side_effect=_per_message_guardrail_server(True)): + result = await OpenAIResponsesHandler().process_input_messages(data, guardrail) + + assert result["instructions"] == "Never repeat the SSN " + REDACTED_SSN + " back." + assert [_texts(item) for item in result["input"]] == [["My SSN is " + REDACTED_SSN + "."]] + + @pytest.mark.asyncio + async def test_texts_only_per_message_answer_over_a_string_input_is_rejected_by_name(self): + from litellm.llms.base_llm.guardrail_translation.utils import UnappliableRequestRewrite + + guardrail = _per_message_redactor() + data = _string_input_request() + original = copy.deepcopy(data) + + with patch.object(guardrail.async_handler, "post", side_effect=_per_message_guardrail_server(False)): + with pytest.raises(UnappliableRequestRewrite) as excinfo: + await OpenAIResponsesHandler().process_input_messages(data, guardrail) + + assert excinfo.value.guardrail_name == "per-message-redactor" + assert data["input"] == original["input"] + assert data["instructions"] == original["instructions"] + + class TestProvenancePatching: """The O(n) provenance pass must keep patching rewritten rows in place for the shapes real agent loops produce, and fall back safely everywhere else.""" diff --git a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_tool_merge.py b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_tool_merge.py index 9c236d81f51..bbd0cdf97e3 100644 --- a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_tool_merge.py +++ b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_tool_merge.py @@ -133,7 +133,20 @@ def test_namespace_keeps_a_non_function_member_when_a_function_member_is_edited( assert merged[0]["tools"][1] == custom_member -def test_namespace_keeps_its_non_function_members_when_every_function_member_is_dropped(): +def test_namespace_keeps_its_custom_member_when_every_function_member_is_dropped(): + custom_member = {"type": "custom", "name": "grep", "description": "Grep", "format": {"type": "text"}} + original = [ + {"type": "namespace", "name": "ns", "description": "NS", "tools": [_function("read"), custom_member]}, + _function("a"), + ] + groups = _groups(original) + + merged = merge_guardrailed_tools(original, groups, [groups[0][1], groups[1][0]]) + + assert list(merged) == [{"type": "namespace", "name": "ns", "description": "NS", "tools": [custom_member]}, _function("a")] + + +def test_namespace_custom_member_is_dropped_when_the_guardrail_drops_its_chat_form(): custom_member = {"type": "custom", "name": "grep", "description": "Grep", "format": {"type": "text"}} original = [ {"type": "namespace", "name": "ns", "description": "NS", "tools": [_function("read"), custom_member]}, @@ -143,7 +156,37 @@ def test_namespace_keeps_its_non_function_members_when_every_function_member_is_ merged = merge_guardrailed_tools(original, groups, [groups[1][0]]) - assert list(merged) == [{"type": "namespace", "name": "ns", "description": "NS", "tools": [custom_member]}, _function("a")] + assert list(merged) == [_function("a")] + + +def test_custom_member_description_edit_lands_without_the_namespace_prefix_or_grammar_block(): + grammar = {"type": "grammar", "syntax": "lark", "definition": "start: X"} + custom_member = {"type": "custom", "name": "exec", "description": "Run a command", "format": grammar} + original = [{"type": "namespace", "name": "shell", "description": "Shell", "tools": [custom_member]}] + groups = _groups(original) + assert groups[0][0]["function"]["description"] == "Shell\n\nRun a command\n\nFormat:\n```lark\nstart: X\n```" + edited = copy.deepcopy(_flat(groups)) + edited[0]["function"]["description"] = "Shell\n\nRun a command (guarded)\n\nFormat:\n```lark\nstart: X\n```" + + merged = merge_guardrailed_tools(original, groups, edited) + + guarded_member = {**custom_member, "description": "Run a command (guarded)"} + assert list(merged) == [{"type": "namespace", "name": "shell", "description": "Shell", "tools": [guarded_member]}] + + +def test_text_appended_after_the_grammar_block_lands_on_the_member_without_the_block(): + grammar = {"type": "grammar", "syntax": "lark", "definition": "start: X"} + custom_member = {"type": "custom", "name": "exec", "description": "Run a command", "format": grammar} + original = [{"type": "namespace", "name": "shell", "description": "Shell", "tools": [custom_member]}] + groups = _groups(original) + edited = copy.deepcopy(_flat(groups)) + edited[0]["function"]["description"] = edited[0]["function"]["description"] + " [checked]" + + merged = merge_guardrailed_tools(original, groups, edited) + + assert merged[0]["tools"][0]["description"] == "Run a command [checked]" + reflattened = _flat(_groups(merged)) + assert reflattened[0]["function"]["description"] == "Shell\n\nRun a command [checked]\n\nFormat:\n```lark\nstart: X\n```" def test_member_extras_edited_by_the_guardrail_land_on_that_member(): diff --git a/tests/test_litellm/llms/vertex_ai/batches/test_transformation.py b/tests/test_litellm/llms/vertex_ai/batches/test_transformation.py index 232c6413e78..e6126b02790 100644 --- a/tests/test_litellm/llms/vertex_ai/batches/test_transformation.py +++ b/tests/test_litellm/llms/vertex_ai/batches/test_transformation.py @@ -17,9 +17,9 @@ from unittest.mock import patch import pytest - from litellm.llms.vertex_ai.batches.transformation import ( # noqa: E402 VertexAIBatchTransformation, + vertex_prompt_tokens_details, ) from litellm.llms.vertex_ai.common_utils import ( # noqa: E402 VertexAIError, @@ -41,6 +41,22 @@ ENDPOINT_INPUT_FILE = ( ) +def test_vertex_prompt_tokens_details_rejects_malformed_details(): + assert vertex_prompt_tokens_details({"promptTokensDetails": [1]}) is None + assert vertex_prompt_tokens_details({"promptTokensDetails": [{"modality": "AUDIO"}]}) is None + assert ( + vertex_prompt_tokens_details( + { + "promptTokensDetails": [ + {"modality": "AUDIO", "tokenCount": 1}, + "malformed", + ] + } + ) + is None + ) + + # =========================================================================== # # transform_openai_batch_request_to_vertex_ai_batch_request # =========================================================================== # diff --git a/tests/test_litellm/llms/vertex_ai/gemini_embeddings/test_batch_embed_content_transformation.py b/tests/test_litellm/llms/vertex_ai/gemini_embeddings/test_batch_embed_content_transformation.py index 86b3f0976ab..fd8c2a9cf6a 100644 --- a/tests/test_litellm/llms/vertex_ai/gemini_embeddings/test_batch_embed_content_transformation.py +++ b/tests/test_litellm/llms/vertex_ai/gemini_embeddings/test_batch_embed_content_transformation.py @@ -10,6 +10,7 @@ Covers: import pytest +import litellm from litellm.litellm_core_utils.llm_cost_calc.utils import generic_cost_per_token from litellm.llms.vertex_ai.gemini_embeddings.batch_embed_content_transformation import ( _build_part_for_input, @@ -22,11 +23,19 @@ from litellm.llms.vertex_ai.gemini_embeddings.batch_embed_content_transformation from litellm.types.llms.vertex_ai import VertexAIBatchEmbeddingsResponseObject from litellm.types.utils import EmbeddingResponse - IMAGE_DATA_URI = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAgAAAAIAQMAAAD+wSzIAAAABlBMVEX///+/v7+jQ3Y5AAAADklEQVQI12P4AIX8EAgALgAD/aNpbtEAAAAASUVORK5CYII" GCS_URL = "gs://my-bucket/image.png" +@pytest.fixture(autouse=True) +def _local_model_cost_map(monkeypatch): + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url="")) + litellm.get_model_info.cache_clear() + yield + litellm.get_model_info.cache_clear() + + class TestIsMultimodalInput: def test_text_only_string(self): assert _is_multimodal_input("hello world") is False @@ -324,7 +333,7 @@ class TestProcessEmbedContentResponseUsage: ) assert result.usage.prompt_tokens == 258 assert result.usage.total_tokens == 258 - assert result.usage.prompt_tokens_details.image_count == 1 + assert result.usage.prompt_tokens_details.image_tokens == 258 prompt_cost, _ = generic_cost_per_token( model=self.MODEL, @@ -358,7 +367,7 @@ class TestProcessEmbedContentResponseUsage: ) assert prompt_cost > 0 - def test_video_modality_derives_seconds_and_text_floor(self): + def test_video_modality_preserves_token_count(self): response_json = { "embedding": {"values": [0.1]}, "usageMetadata": { @@ -374,10 +383,8 @@ class TestProcessEmbedContentResponseUsage: response_json=response_json, ) assert result.usage.prompt_tokens == 516 - assert result.usage.prompt_tokens_details.video_length_seconds == pytest.approx( - 2.0 - ) - assert result.usage.prompt_tokens_details.text_tokens == 1 + assert result.usage.prompt_tokens_details.video_tokens == 516 + assert result.usage.prompt_tokens_details.text_tokens == 0 def test_missing_usage_metadata_does_not_estimate_from_base64(self): response_json = {"embedding": {"values": [0.1, 0.2]}} @@ -400,8 +407,7 @@ class TestProcessEmbedContentResponseUsage: ) assert result.usage.prompt_tokens > 0 - def test_file_reference_image_billed_per_image_not_text(self): - """files/... image refs must bill per-image, not at the text token rate.""" + def test_file_reference_image_billed_per_image_token_rate(self): response_json = { "embedding": {"values": [0.1, 0.2, 0.3]}, "usageMetadata": { @@ -422,7 +428,7 @@ class TestProcessEmbedContentResponseUsage: } }, ) - assert result.usage.prompt_tokens_details.image_count == 1 + assert result.usage.prompt_tokens_details.image_tokens == 258 assert result.usage.prompt_tokens_details.text_tokens == 0 prompt_cost, _ = generic_cost_per_token( @@ -430,10 +436,10 @@ class TestProcessEmbedContentResponseUsage: usage=result.usage, custom_llm_provider="vertex_ai", ) - assert prompt_cost == pytest.approx(0.00012) + assert prompt_cost == pytest.approx(258 * 4.5e-7) def test_file_reference_non_image_not_counted_as_image(self): - """A files/... ref resolving to a non-image mime must not be image-counted.""" + """A files/... ref resolving to a non-image mime keeps audio token billing.""" response_json = { "embedding": {"values": [0.1, 0.2]}, "usageMetadata": { @@ -454,21 +460,18 @@ class TestProcessEmbedContentResponseUsage: } }, ) - assert result.usage.prompt_tokens_details.image_count == 0 assert result.usage.prompt_tokens_details.audio_tokens == 64 - assert result.usage.prompt_tokens_details.audio_length_seconds == pytest.approx( - 2.0 - ) + assert result.usage.prompt_tokens_details.image_tokens == 0 prompt_cost, _ = generic_cost_per_token( model=self.MODEL, usage=result.usage, custom_llm_provider="vertex_ai", ) - assert prompt_cost == pytest.approx(2.0 * 0.00016) + assert prompt_cost == pytest.approx(64 * 6.5e-6) def test_video_plus_audio_does_not_double_bill_text(self): - """Video+audio responses must not get video tokens reassigned to text.""" + """Video and audio responses are billed from their respective token counts.""" response_json = { "embedding": {"values": [0.1]}, "usageMetadata": { @@ -486,18 +489,145 @@ class TestProcessEmbedContentResponseUsage: model=self.MODEL, response_json=response_json, ) - assert result.usage.prompt_tokens_details.text_tokens == 1 - assert result.usage.prompt_tokens_details.video_length_seconds == pytest.approx( - 2.0 - ) - assert result.usage.prompt_tokens_details.audio_length_seconds == pytest.approx( - 2.0 - ) + assert result.usage.prompt_tokens_details.text_tokens == 0 + assert result.usage.prompt_tokens_details.video_tokens == 516 + assert result.usage.prompt_tokens_details.audio_tokens == 64 prompt_cost, _ = generic_cost_per_token( model=self.MODEL, usage=result.usage, custom_llm_provider="vertex_ai", ) - # 1 floor text token at 2e-7 + 2s of video at 7.9e-4 + 2s of audio at 1.6e-4 - assert prompt_cost == pytest.approx(1 * 2e-7 + 2 * 0.00079 + 2 * 0.00016) + assert prompt_cost == pytest.approx(516 * 1.2e-5 + 64 * 6.5e-6) + + def test_preview_alias_bills_audio_per_token(self): + response_json = { + "embedding": {"values": [0.1]}, + "usageMetadata": { + "promptTokenCount": 64, + "totalTokenCount": 64, + "promptTokensDetails": [{"modality": "AUDIO", "tokenCount": 64}], + }, + } + result = process_embed_content_response( + input="audio", + model_response=EmbeddingResponse(), + model="gemini-embedding-2-preview", + response_json=response_json, + ) + prompt_cost, _ = generic_cost_per_token( + model="gemini-embedding-2-preview", + usage=result.usage, + custom_llm_provider="vertex_ai", + ) + assert prompt_cost == pytest.approx(64 * 6.5e-6) + + def test_image_without_modality_details_uses_image_rate(self): + response_json = { + "embedding": {"values": [0.1]}, + "usageMetadata": { + "promptTokenCount": 258, + "totalTokenCount": 258, + }, + } + result = process_embed_content_response( + input=IMAGE_DATA_URI, + model_response=EmbeddingResponse(), + model=self.MODEL, + response_json=response_json, + ) + assert result.usage.prompt_tokens_details.image_tokens == 258 + assert result.usage.prompt_tokens_details.text_tokens == 0 + + prompt_cost, _ = generic_cost_per_token( + model=self.MODEL, + usage=result.usage, + custom_llm_provider="vertex_ai", + ) + assert prompt_cost == pytest.approx(258 * 4.5e-7) + + @pytest.mark.parametrize( + "input_value,resolved_files,expected_image_tokens", + [ + (GCS_URL, {}, 258), + ("gs://my-bucket/clip.mp4", {}, 0), + ("gs://my-bucket/unknown.bin", {}, 0), + ("files/image-123", {"files/image-123": {"mime_type": "image/jpeg"}}, 258), + ("files/missing", {}, 0), + ("data:application/octet-stream;base64,abc", {}, 0), + ([[IMAGE_DATA_URI]], {}, 258), + ([], {}, 0), + ], + ) + def test_missing_modality_details_classifies_image_inputs(self, input_value, resolved_files, expected_image_tokens): + response_json = { + "embedding": {"values": [0.1]}, + "usageMetadata": { + "promptTokenCount": 258, + "totalTokenCount": 258, + }, + } + result = process_embed_content_response( + input=input_value, + model_response=EmbeddingResponse(), + model=self.MODEL, + response_json=response_json, + resolved_files=resolved_files, + ) + assert result.usage.prompt_tokens_details.image_tokens == expected_image_tokens + assert result.usage.prompt_tokens_details.text_tokens == 0 + + prompt_cost, _ = generic_cost_per_token( + model=self.MODEL, + usage=result.usage, + custom_llm_provider="vertex_ai", + ) + expected_rate = 4.5e-7 if expected_image_tokens else 2e-7 + assert prompt_cost == pytest.approx(258 * expected_rate) + + def test_mixed_text_and_image_without_modality_details_not_billed_as_image(self): + response_json = { + "embedding": {"values": [0.1]}, + "usageMetadata": { + "promptTokenCount": 270, + "totalTokenCount": 270, + }, + } + result = process_embed_content_response( + input=["a short caption", IMAGE_DATA_URI], + model_response=EmbeddingResponse(), + model=self.MODEL, + response_json=response_json, + ) + assert result.usage.prompt_tokens_details.image_tokens == 0 + + prompt_cost, _ = generic_cost_per_token( + model=self.MODEL, + usage=result.usage, + custom_llm_provider="vertex_ai", + ) + assert prompt_cost == pytest.approx(270 * 2e-7) + + def test_text_without_modality_details_uses_text_rate(self): + response_json = { + "embedding": {"values": [0.1]}, + "usageMetadata": { + "promptTokenCount": 12, + "totalTokenCount": 12, + }, + } + result = process_embed_content_response( + input="a short caption", + model_response=EmbeddingResponse(), + model=self.MODEL, + response_json=response_json, + ) + assert result.usage.prompt_tokens_details.text_tokens == 0 + assert result.usage.prompt_tokens_details.image_tokens == 0 + + prompt_cost, _ = generic_cost_per_token( + model=self.MODEL, + usage=result.usage, + custom_llm_provider="vertex_ai", + ) + assert prompt_cost == pytest.approx(12 * 2e-7) diff --git a/tests/test_litellm/ocr/test_legacy.py b/tests/test_litellm/ocr/test_legacy.py index a30976f89af..4b0b78f5a0f 100644 --- a/tests/test_litellm/ocr/test_legacy.py +++ b/tests/test_litellm/ocr/test_legacy.py @@ -11,7 +11,8 @@ import pytest import litellm from litellm.integrations.custom_logger import CustomLogger -from litellm.llms.base_llm.ocr.transformation import OCRResponse +from litellm.litellm_core_utils.litellm_logging import Logging, use_custom_pricing_for_model +from litellm.llms.base_llm.ocr.transformation import OCRPage, OCRResponse, OCRUsageInfo from litellm.llms.custom_httpx import llm_http_handler from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler from litellm.ocr.legacy import _prepare_ocr_request @@ -198,3 +199,61 @@ def test_generic_azure_connection_still_applies_to_foundry_ocr(monkeypatch: pyte assert prepared.api_key == "generic-key" assert prepared.api_base == "https://generic.example.com" + + +PRICING_OCR_MODEL: Final = "mistral/some-unmapped-ocr-model-for-testing" +PRICING_DOCUMENT: Final = {"type": "document_url", "document_url": "https://example.com/doc.pdf"} + + +def _pricing_logging_obj() -> Logging: + return Logging( + model=PRICING_OCR_MODEL, + messages=[], + stream=False, + call_type="ocr", + start_time=None, + litellm_call_id="test-ocr-request-pricing", + function_id="1234", + ) + + +def _prepare_with_pricing(kwargs: dict[str, object]) -> Logging: + logging_obj: Final = _pricing_logging_obj() + _prepare_ocr_request( + model=PRICING_OCR_MODEL, + document=dict(PRICING_DOCUMENT), + api_key="test-key", + api_base=None, + timeout=None, + custom_llm_provider=None, + extra_headers=None, + kwargs={"litellm_logging_obj": logging_obj, **kwargs}, + ) + return logging_obj + + +def test_prepare_ocr_request_forwards_custom_pricing_to_logging_params() -> None: + logging_obj: Final = _prepare_with_pricing({"ocr_cost_per_page": 0.05, "ocr_cost_per_credit": 0.5}) + + assert logging_obj.litellm_params["ocr_cost_per_page"] == 0.05 + assert logging_obj.litellm_params["ocr_cost_per_credit"] == 0.5 + assert use_custom_pricing_for_model(logging_obj.litellm_params) is True + + +def test_prepare_ocr_request_without_custom_pricing_leaves_logging_params_unpriced() -> None: + logging_obj: Final = _prepare_with_pricing({}) + + assert "ocr_cost_per_page" not in logging_obj.litellm_params + assert use_custom_pricing_for_model(logging_obj.litellm_params) is False + + +def test_direct_ocr_call_bills_request_level_per_page_pricing() -> None: + assert PRICING_OCR_MODEL not in litellm.model_cost + logging_obj: Final = _prepare_with_pricing({"ocr_cost_per_page": 0.05}) + response: Final = OCRResponse( + pages=[OCRPage(index=index, markdown=f"page {index}") for index in range(3)], + model=PRICING_OCR_MODEL, + usage_info=OCRUsageInfo(pages_processed=3), + ) + + assert logging_obj._response_cost_calculator(result=response) == pytest.approx(0.05 * 3) diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/auth/test_user_api_key_auth_mcp.py b/tests/test_litellm/proxy/_experimental/mcp_server/auth/test_user_api_key_auth_mcp.py index c2f4f7163a0..90ce821d62e 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/auth/test_user_api_key_auth_mcp.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/auth/test_user_api_key_auth_mcp.py @@ -1483,12 +1483,10 @@ class TestMCPOAuth2AuthFlow: as LiteLLM API keys, causing auth failures and empty tool listings. """ - async def test_oauth2_token_in_authorization_header_fallback(self): + async def test_oauth2_token_in_authorization_header_requires_litellm_admission(self): """ - When only the Authorization header is present with a non-LiteLLM OAuth2 - token AND the target server delegates auth to upstream, LiteLLM skips its - own validation entirely (so the upstream token is never mistaken for a - virtual key) and forwards the bearer upstream. + A bare Authorization token on the legacy delegated mode must establish + a LiteLLM principal rather than entering anonymously. """ from litellm.types.mcp import MCPAuth @@ -1510,6 +1508,7 @@ class TestMCPOAuth2AuthFlow: patch( "litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp.user_api_key_auth", new_callable=AsyncMock, + return_value=UserAPIKeyAuth(user_id="admitted-user"), ) as mock_auth, patch("litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager") as mock_mgr, ): @@ -1524,9 +1523,8 @@ class TestMCPOAuth2AuthFlow: ) = await MCPRequestHandler.process_mcp_request(scope) assert isinstance(auth_result, UserAPIKeyAuth) - # The upstream token is never validated as a LiteLLM key ... - mock_auth.assert_not_called() - # ... and is preserved for upstream forwarding. + assert auth_result.user_id == "admitted-user" + mock_auth.assert_awaited_once() assert oauth2_headers.get("Authorization") == "Bearer atlassian-oauth2-access-token-xyz" async def test_explicit_litellm_key_with_oauth2_authorization(self): @@ -2367,11 +2365,9 @@ class TestMCPDelegateAuthToUpstream: """ Tests for the ``delegate_auth_to_upstream`` per-server flag. - When set on an ``auth_type=oauth2`` MCP server, LiteLLM must skip its own - API-key/SSO check entirely so the client completes PKCE directly with the - upstream MCP server. The gate must fail closed for any non-oauth2 server, - any mixed-target request, and any request where the target cannot be - resolved. + The legacy flag no longer bypasses LiteLLM admission. OAuth discovery may + still use the anonymous cold-start challenge, but a presented bearer must + authenticate to LiteLLM unless a separate admission credential is supplied. """ @staticmethod @@ -2386,6 +2382,13 @@ class TestMCPDelegateAuthToUpstream: delegate_auth_to_upstream=delegate_auth_to_upstream, ) + def test_legacy_delegate_cold_start_fails_closed_without_targets(self): + from litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp import ( + _is_legacy_delegate_cold_start, + ) + + assert _is_legacy_delegate_cold_start(None, client_ip=None) is False + def test_build_mcp_server_table_preserves_delegate_auth_to_upstream(self): """Registry → API list rows must expose delegate_auth_to_upstream for the UI.""" from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( @@ -2439,11 +2442,10 @@ class TestMCPDelegateAuthToUpstream: not_passthrough = passthrough.model_copy(update={"oauth_passthrough": False}) assert manager._build_mcp_server_table(not_passthrough).oauth_passthrough is False - async def test_delegate_skips_litellm_auth_with_no_authorization(self): + async def test_delegate_without_authorization_attempts_litellm_auth_before_cold_start(self): """ - oauth2 + delegate_auth_to_upstream=True, no Authorization header at - all → anonymous UserAPIKeyAuth and ``user_api_key_auth`` is never - called. + A credential-free discovery request attempts LiteLLM admission before + the route emits its RFC 9728 challenge. """ from litellm.types.mcp import MCPAuth @@ -2457,6 +2459,8 @@ class TestMCPDelegateAuthToUpstream: with ( patch( "litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp.user_api_key_auth", + new_callable=AsyncMock, + side_effect=HTTPException(status_code=401, detail="No key provided"), ) as mock_auth, patch("litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager") as mock_mgr, ): @@ -2466,17 +2470,12 @@ class TestMCPDelegateAuthToUpstream: ) auth_result, *_rest = await MCPRequestHandler.process_mcp_request(scope) assert isinstance(auth_result, UserAPIKeyAuth) - mock_auth.assert_not_called() + mock_auth.assert_awaited_once() - async def test_delegate_with_upstream_token_in_authorization_skips_litellm_auth( - self, - ): + async def test_delegate_with_only_upstream_token_requires_litellm_auth(self): """ - oauth2 + delegate_auth_to_upstream=True with an upstream OAuth token in - ``Authorization``: the delegate gate fires before any LiteLLM validation, - so ``user_api_key_auth`` is never called and the bearer is forwarded - upstream untouched. Skipping the doomed validation is what keeps a tool - call that actually succeeds from carrying a phantom 401 auth span. + An upstream token cannot establish a LiteLLM principal and must not + reopen anonymous admission. """ from litellm.types.mcp import MCPAuth @@ -2491,6 +2490,7 @@ class TestMCPDelegateAuthToUpstream: patch( "litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp.user_api_key_auth", new_callable=AsyncMock, + side_effect=HTTPException(status_code=401, detail="Invalid API key"), ) as mock_auth, patch("litellm.proxy._experimental.mcp_server.mcp_server_manager.global_mcp_server_manager") as mock_mgr, ): @@ -2498,17 +2498,11 @@ class TestMCPDelegateAuthToUpstream: auth_type=MCPAuth.oauth2, delegate_auth_to_upstream=True, ) - ( - auth_result, - _, - _, - _, - oauth2_headers, - _, - ) = await MCPRequestHandler.process_mcp_request(scope) - assert isinstance(auth_result, UserAPIKeyAuth) - assert oauth2_headers.get("Authorization") == "Bearer upstream-pkce-token" - mock_auth.assert_not_called() + with pytest.raises(HTTPException) as exc_info: + await MCPRequestHandler.process_mcp_request(scope) + + assert exc_info.value.status_code == 401 + mock_auth.assert_awaited_once() async def test_delegate_off_still_requires_litellm_auth(self): """ @@ -2687,15 +2681,11 @@ class TestMCPDelegateAuthToUpstream: assert auth_result.user_id == "real-user" mock_auth.assert_called_once() - async def test_authorization_bearer_on_delegate_server_treated_as_upstream(self): + async def test_authorization_bearer_on_delegate_server_establishes_litellm_principal(self): """ - On a delegate server the ``Authorization`` header is, by contract, an - upstream token rather than a LiteLLM key — even when it is sk-shaped. It - is forwarded upstream without LiteLLM validation, so ``user_api_key_auth`` - is not called and no LiteLLM identity is resolved. Callers who need - LiteLLM identity / spend tracking on a delegate server must supply - ``x-litellm-api-key`` (see - test_explicit_litellm_key_takes_precedence_over_delegate). + A bare Authorization bearer now follows normal LiteLLM admission. A + separate x-litellm-api-key is required when Authorization is intended + for the upstream server. """ from litellm.types.mcp import MCPAuth @@ -2727,9 +2717,9 @@ class TestMCPDelegateAuthToUpstream: _, ) = await MCPRequestHandler.process_mcp_request(scope) assert isinstance(auth_result, UserAPIKeyAuth) - assert auth_result.user_id is None + assert auth_result.user_id == "real-user" assert oauth2_headers.get("Authorization") == "Bearer sk-1234" - mock_auth.assert_not_called() + mock_auth.assert_awaited_once() async def test_delegate_ignored_for_client_credentials_server(self): """ @@ -2828,13 +2818,10 @@ class TestMCPDelegateAuthToUpstream: assert exc_info.value.status_code == 401 mock_auth.assert_called_once() - async def test_delegate_bypass_for_pure_pkce_server(self): + async def test_delegate_pkce_cold_start_attempts_litellm_auth(self): """ - oauth2 + delegate + oauth2_flow=None and NO stored client credentials - (pure PKCE, the common delegate case) → bypass must still fire. The - shape resolves to a non-M2M flow, so the security gate leaves it alone; - the fail-closed rule targets the M2M shape specifically, not every - unstamped row. + A pure PKCE server may defer a credential-free request to the route's + challenge, but normal LiteLLM admission still runs first. """ from litellm.types.mcp import MCPAuth from litellm.types.mcp_server.mcp_server_manager import MCPServer @@ -2869,13 +2856,12 @@ class TestMCPDelegateAuthToUpstream: ): mock_mgr.get_mcp_server_by_name.return_value = pkce_server auth, *_rest = await MCPRequestHandler.process_mcp_request(scope) - mock_auth.assert_not_called() + mock_auth.assert_awaited_once() assert auth.api_key is None - async def test_delegate_bypass_for_internal_server(self): + async def test_internal_delegate_cold_start_attempts_litellm_auth(self): """ - Delegate + oauth2 interactive servers bypass LiteLLM auth even when - ``available_on_public_internet`` is False (internal MCPs). + Internal delegated servers follow the same admission contract. """ from litellm.types.mcp import MCPAuth from litellm.types.mcp_server.mcp_server_manager import MCPServer @@ -2910,14 +2896,11 @@ class TestMCPDelegateAuthToUpstream: ): mock_mgr.get_mcp_server_by_name.return_value = internal_server auth, *_rest = await MCPRequestHandler.process_mcp_request(scope) - mock_auth.assert_not_called() + mock_auth.assert_awaited_once() assert auth.api_key is None - async def test_get_allowed_servers_excludes_client_credentials_delegate(self): - """ - get_allowed_mcp_servers must not surface M2M (client_credentials) delegate - servers to anonymous callers even if delegate_auth_to_upstream=True. - """ + async def test_get_allowed_servers_excludes_legacy_delegates(self): + """Legacy delegated servers are never added to anonymous access.""" from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( MCPServerManager, ) @@ -2955,102 +2938,7 @@ class TestMCPDelegateAuthToUpstream: ): result = await manager.get_allowed_mcp_servers(None) - assert "pkce-server" in result - assert "m2m-server" not in result - - async def test_get_allowed_servers_excludes_unstamped_m2m_shape_delegate(self): - """ - The anonymous allow-list must also exclude an M2M-shape delegate server whose - oauth2_flow was never stamped (null column, verbatim-read as non-M2M). Reading - the bare has_client_credentials here would surface it to anonymous callers; the - resolved-flow check fails closed on the shape, matching the auth gate. - """ - from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( - MCPServerManager, - ) - from litellm.types.mcp import MCPAuth - from litellm.types.mcp_server.mcp_server_manager import MCPServer - - manager = MCPServerManager() - pkce_server = MCPServer( - server_id="pkce-server", - name="pkce_server", - transport="http", - auth_type=MCPAuth.oauth2, - delegate_auth_to_upstream=True, - available_on_public_internet=True, - ) - unstamped_m2m = MCPServer( - server_id="unstamped-m2m", - name="unstamped_m2m", - transport="http", - auth_type=MCPAuth.oauth2, - delegate_auth_to_upstream=True, - oauth2_flow=None, - client_id="cid", - client_secret="csecret", - token_url="https://idp.example.com/token", - ) - assert unstamped_m2m.has_client_credentials is False - manager.registry = { - pkce_server.server_id: pkce_server, - unstamped_m2m.server_id: unstamped_m2m, - } - - with patch.object( - MCPRequestHandler, - "get_allowed_mcp_servers", - new_callable=AsyncMock, - return_value=[], - ): - result = await manager.get_allowed_mcp_servers(None) - - assert "pkce-server" in result - assert "unstamped-m2m" not in result - - async def test_get_allowed_servers_includes_internal_delegate(self): - """ - Internal-only (available_on_public_internet=False) delegate servers - appear in the anonymous allow-list like public delegate servers. - """ - from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( - MCPServerManager, - ) - from litellm.types.mcp import MCPAuth - from litellm.types.mcp_server.mcp_server_manager import MCPServer - - manager = MCPServerManager() - public_server = MCPServer( - server_id="public-server", - name="public_server", - transport="http", - auth_type=MCPAuth.oauth2, - delegate_auth_to_upstream=True, - available_on_public_internet=True, - ) - internal_server = MCPServer( - server_id="internal-server", - name="internal_server", - transport="http", - auth_type=MCPAuth.oauth2, - delegate_auth_to_upstream=True, - available_on_public_internet=False, - ) - manager.registry = { - public_server.server_id: public_server, - internal_server.server_id: internal_server, - } - - with patch.object( - MCPRequestHandler, - "get_allowed_mcp_servers", - new_callable=AsyncMock, - return_value=[], - ): - result = await manager.get_allowed_mcp_servers(None) - - assert "public-server" in result - assert "internal-server" in result + assert result == [] async def test_true_passthrough_skips_litellm_auth_anonymously(self): """auth_type=true_passthrough performs no admission auth: the caller's Authorization is an diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_hook_extra_headers.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_hook_extra_headers.py index 67948375403..28faf375ab8 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_hook_extra_headers.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_hook_extra_headers.py @@ -597,7 +597,11 @@ class TestHookHeaderMergePriority: "Authorization": "Bearer oauth2-token", "X-OAuth": "yes", }, - raw_headers=None, + raw_headers={ + "x-litellm-api-key": "Bearer sk-litellm-key", + "authorization": "Bearer oauth2-token", + }, + user_api_key_auth=UserAPIKeyAuth(api_key="sk-litellm-key"), proxy_logging_obj=None, hook_extra_headers={ "Authorization": "Bearer hook-jwt", diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py index 7eb4396e60d..f5e4a420496 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server.py @@ -521,6 +521,93 @@ def test_prepare_mcp_server_headers_oauth2_interactive_drops_caller_authorizatio assert extra_headers is None +def test_prepare_mcp_server_headers_legacy_delegate_strips_admission_authorization(): + from litellm.proxy._experimental.mcp_server.server import ( + _prepare_mcp_server_headers, + ) + from litellm.proxy._types import UserAPIKeyAuth + + server = MCPServer( + server_id="legacy-delegate-admission", + name="legacy-delegate", + transport=MCPTransport.http, + auth_type=MCPAuth.oauth2, + delegate_auth_to_upstream=True, + ) + + server_auth_header, extra_headers = _prepare_mcp_server_headers( + server=server, + mcp_server_auth_headers=None, + mcp_auth_header=None, + oauth2_headers={"Authorization": "Bearer sk-litellm-key"}, + raw_headers={"authorization": "Bearer sk-litellm-key"}, + user_api_key_auth=UserAPIKeyAuth(api_key="sk-litellm-key"), + ) + + assert server_auth_header is None + assert extra_headers is None + + +def test_prepare_mcp_server_headers_legacy_delegate_preserves_separate_upstream_authorization(): + from litellm.proxy._experimental.mcp_server.server import ( + _prepare_mcp_server_headers, + ) + from litellm.proxy._types import UserAPIKeyAuth + + server = MCPServer( + server_id="legacy-delegate-dual-credential", + name="legacy-delegate", + transport=MCPTransport.http, + auth_type=MCPAuth.oauth2, + delegate_auth_to_upstream=True, + ) + + server_auth_header, extra_headers = _prepare_mcp_server_headers( + server=server, + mcp_server_auth_headers=None, + mcp_auth_header=None, + oauth2_headers={"Authorization": "Bearer upstream-token"}, + raw_headers={ + "x-litellm-api-key": "Bearer sk-litellm-key", + "authorization": "Bearer upstream-token", + }, + user_api_key_auth=UserAPIKeyAuth(api_key="sk-litellm-key"), + ) + + assert server_auth_header is None + assert extra_headers == {"Authorization": "Bearer upstream-token"} + + +def test_prepare_mcp_server_headers_legacy_delegate_strips_repeated_admission_key(): + from litellm.proxy._experimental.mcp_server.server import ( + _prepare_mcp_server_headers, + ) + from litellm.proxy._types import UserAPIKeyAuth + + server = MCPServer( + server_id="legacy-delegate-repeated-key", + name="legacy-delegate", + transport=MCPTransport.http, + auth_type=MCPAuth.oauth2, + delegate_auth_to_upstream=True, + ) + + server_auth_header, extra_headers = _prepare_mcp_server_headers( + server=server, + mcp_server_auth_headers=None, + mcp_auth_header=None, + oauth2_headers={"Authorization": "Bearer sk-litellm-key"}, + raw_headers={ + "x-litellm-api-key": "Bearer sk-litellm-key", + "authorization": "Bearer sk-litellm-key", + }, + user_api_key_auth=UserAPIKeyAuth(api_key="sk-litellm-key"), + ) + + assert server_auth_header is None + assert extra_headers is None + + def test_prepare_mcp_server_headers_m2m_skips_authorization_from_raw_extra_headers(): """M2M must not merge caller Authorization from raw_headers when extra_headers lists it.""" try: @@ -6157,15 +6244,8 @@ def _patch_delegate_resolver(server: MCPServer, *resolvable_names: str): @pytest.mark.asyncio -async def test_delegate_bad_token_gets_connect_time_401(): - """Regression (LIT-4194): a rejected upstream token on a delegate-auth server - must fail the connect with 401 + ``error="invalid_token"``, not be absorbed - into HTTP 200 + an empty tool list by the tools/list handler. - - Delegate-mode clients send only ``Authorization`` (no ``x-litellm-api-key``), - so ``_get_forwarded_auth_from_scope`` returns None and, before the fix, the - preflight returned early without probing. - """ +async def test_legacy_delegate_bare_token_is_not_probed_upstream(): # test-quality-ok: this removed security-sensitive egress has no return value; non-invocation is the contract + """A bare bearer is an admission credential and must never reach upstream.""" from litellm.proxy._experimental.mcp_server.server import ( _check_passthrough_upstream_auth, ) @@ -6184,48 +6264,6 @@ async def test_delegate_bad_token_gets_connect_time_401(): "litellm.proxy._experimental.mcp_server.server._probe_upstream_auth", new=AsyncMock(return_value=(401, 'Bearer realm="upstream", error="invalid_token"')), ) as probe, - ): - with pytest.raises(HTTPException) as exc_info: - await _check_passthrough_upstream_auth( - scope=scope, - user_api_key_auth=UserAPIKeyAuth(), - mcp_servers=["delegate_test"], - client_ip=None, - ) - - assert exc_info.value.status_code == 401 - challenge = exc_info.value.headers["www-authenticate"] - assert 'error="invalid_token"' in challenge - assert ( - 'resource_metadata="http://localhost:4000/.well-known/oauth-protected-resource/mcp/delegate_test"' in challenge - ) - probe.assert_awaited_once() - probe_url, probe_auth = probe.call_args.args - assert probe_url == "http://upstream:9401/mcp" - assert probe_auth == "Bearer bogus-token" - - -@pytest.mark.asyncio -async def test_delegate_valid_token_passes_preflight(): - """An upstream-accepted token must not be blocked by the delegate preflight.""" - from litellm.proxy._experimental.mcp_server.server import ( - _check_passthrough_upstream_auth, - ) - from litellm.proxy._types import UserAPIKeyAuth - - server = _delegate_auth_mcp_server() - scope = _delegate_scope([(b"authorization", b"Bearer good-token")]) - - with ( - _patch_delegate_resolver(server, "delegate_test"), - patch( - "litellm.proxy._experimental.mcp_server.server._get_allowed_mcp_servers", - new=AsyncMock(return_value=[server]), - ), - patch( - "litellm.proxy._experimental.mcp_server.server._probe_upstream_auth", - new=AsyncMock(return_value=(200, None)), - ) as probe, ): await _check_passthrough_upstream_auth( scope=scope, @@ -6234,43 +6272,103 @@ async def test_delegate_valid_token_passes_preflight(): client_ip=None, ) - probe.assert_awaited_once() + probe.assert_not_awaited() @pytest.mark.asyncio -async def test_delegate_valid_token_forbidden_returns_403(): - """An upstream that accepts the token but forbids the caller (403) must surface - as a bare 403 with no ``WWW-Authenticate`` re-auth hint (a fresh token with the - same scopes would loop), not as an invalid_token challenge.""" +async def test_legacy_delegate_dual_credentials_are_not_probed_upstream(): # test-quality-ok: this removed security-sensitive egress has no return value; non-invocation is the contract + """A separate upstream bearer never triggers the removed legacy probe.""" from litellm.proxy._experimental.mcp_server.server import ( _check_passthrough_upstream_auth, ) from litellm.proxy._types import UserAPIKeyAuth server = _delegate_auth_mcp_server() - scope = _delegate_scope([(b"authorization", b"Bearer scoped-out-token")]) + scope = _delegate_scope( + [ + (b"x-litellm-api-key", b"sk-litellm-proxy-key"), + (b"authorization", b"Bearer upstream-token"), + ] + ) with ( - _patch_delegate_resolver(server, "delegate_test"), - patch( + patch( # test-quality-ok: isolate authorized-server resolution so this test targets the preflight boundary "litellm.proxy._experimental.mcp_server.server._get_allowed_mcp_servers", new=AsyncMock(return_value=[server]), ), - patch( + patch( # test-quality-ok: the removed probe call is the security regression under test "litellm.proxy._experimental.mcp_server.server._probe_upstream_auth", - new=AsyncMock(return_value=(403, None)), - ), + new=AsyncMock(), + ) as probe, ): - with pytest.raises(HTTPException) as exc_info: - await _check_passthrough_upstream_auth( + await _check_passthrough_upstream_auth( + scope=scope, + user_api_key_auth=UserAPIKeyAuth(user_id="admitted-user"), + mcp_servers=["delegate_test"], + client_ip=None, + ) + + probe.assert_not_awaited() + + +@pytest.mark.parametrize( + "probe_status, expected_status", + [(200, None), (401, 401), (403, 403)], +) +@pytest.mark.asyncio +async def test_oauth_passthrough_preflight_preserves_status_contract(probe_status, expected_status): + from litellm.proxy._experimental.mcp_server.server import ( + _check_passthrough_upstream_auth, + ) + from litellm.proxy._types import UserAPIKeyAuth + + server = MCPServer( + server_id="passthrough-id", + name="passthrough_server", + url="https://upstream.example.com/mcp", + transport=MCPTransport.http, + auth_type=MCPAuth.none, + oauth_passthrough=True, + extra_headers=["Authorization"], + ) + scope = _delegate_scope( + [ + (b"x-litellm-api-key", b"sk-litellm-proxy-key"), + (b"authorization", b"Bearer upstream-token"), + ] + ) + + with ( + patch( # test-quality-ok: isolate authorized-server resolution so this test exercises the preflight contract + "litellm.proxy._experimental.mcp_server.server._get_allowed_mcp_servers", + new=AsyncMock(return_value=[server]), + ), + patch( # test-quality-ok: the upstream transport boundary is the behavior being mapped to an HTTP response + "litellm.proxy._experimental.mcp_server.server._probe_upstream_auth", + new=AsyncMock(return_value=(probe_status, None)), + ) as probe, + ): + if expected_status is None: + result = await _check_passthrough_upstream_auth( scope=scope, - user_api_key_auth=UserAPIKeyAuth(), - mcp_servers=["delegate_test"], + user_api_key_auth=UserAPIKeyAuth(user_id="admitted-user"), + mcp_servers=["passthrough_server"], client_ip=None, ) + assert result is None + else: + with pytest.raises(HTTPException) as exc_info: + await _check_passthrough_upstream_auth( + scope=scope, + user_api_key_auth=UserAPIKeyAuth(user_id="admitted-user"), + mcp_servers=["passthrough_server"], + client_ip=None, + ) + assert exc_info.value.status_code == expected_status + if expected_status == 401: + assert "passthrough_server" in exc_info.value.headers["www-authenticate"] - assert exc_info.value.status_code == 403 - assert not (exc_info.value.headers or {}) + probe.assert_awaited_once_with("https://upstream.example.com/mcp", "Bearer upstream-token") @pytest.mark.asyncio @@ -6428,123 +6526,6 @@ async def test_delegate_not_probed_when_named_only_via_server_id(): probe.assert_not_awaited() -@pytest.mark.asyncio -async def test_delegate_preflight_with_unpatched_probe(): - """Integration across the preflight and the unpatched ``_probe_upstream_auth``, - mocked only at the httpx-client boundary (tests/test_litellm is mocked-only; the - real-network proof lives in the PR's live-proxy evidence). The mock honors the - ``AsyncHTTPHandler.post`` contract by raising ``httpx.HTTPStatusError`` on the - upstream 401, so the production ``except httpx.HTTPStatusError`` branch is the one - exercised. A rejected token surfaces as the connect-time 401 challenge; an - accepted token passes untouched, and the caller's bearer reaches the delegate URL.""" - import httpx - - from litellm.proxy._experimental.mcp_server.server import ( - _check_passthrough_upstream_auth, - ) - from litellm.proxy._types import UserAPIKeyAuth - - accepted = MagicMock() - accepted.status_code = 200 - accepted.headers = {} - rejected = MagicMock() - rejected.status_code = 401 - rejected.headers = {"www-authenticate": 'Bearer realm="stub-upstream", error="invalid_token"'} - - async def respond_by_token(url=None, headers=None, json=None, timeout=None, **kwargs): - if headers.get("Authorization") == "Bearer good-token": - return accepted - raise httpx.HTTPStatusError( - "401 Unauthorized", - request=httpx.Request("POST", url), - response=rejected, - ) - - mock_client = MagicMock() - mock_client.post = AsyncMock(side_effect=respond_by_token) - - server = _delegate_auth_mcp_server() - - with ( - _patch_delegate_resolver(server, "delegate_test"), - patch( - "litellm.proxy._experimental.mcp_server.server._get_allowed_mcp_servers", - new=AsyncMock(return_value=[server]), - ), - patch( - "litellm.proxy._experimental.mcp_server.server.get_async_httpx_client", - return_value=mock_client, - ), - ): - with pytest.raises(HTTPException) as exc_info: - await _check_passthrough_upstream_auth( - scope=_delegate_scope([(b"authorization", b"Bearer bogus-token")]), - user_api_key_auth=UserAPIKeyAuth(), - mcp_servers=["delegate_test"], - client_ip=None, - ) - - await _check_passthrough_upstream_auth( - scope=_delegate_scope([(b"authorization", b"Bearer good-token")]), - user_api_key_auth=UserAPIKeyAuth(), - mcp_servers=["delegate_test"], - client_ip=None, - ) - - assert exc_info.value.status_code == 401 - challenge = exc_info.value.headers["www-authenticate"] - assert 'error="invalid_token"' in challenge - assert ( - 'resource_metadata="http://localhost:4000/.well-known/oauth-protected-resource/mcp/delegate_test"' in challenge - ) - probed_urls = [call.kwargs["url"] for call in mock_client.post.await_args_list] - assert probed_urls == ["http://upstream:9401/mcp", "http://upstream:9401/mcp"] - - -@pytest.mark.asyncio -async def test_delegate_challenge_echoes_requested_alias(): - """An alias-routed delegate request must be probed, and the challenge must echo - the requested alias (not the canonical server name) so the resource_metadata - URL matches what the tokenless preemptive challenge emits for the same route.""" - from litellm.proxy._experimental.mcp_server.server import ( - _check_passthrough_upstream_auth, - ) - from litellm.proxy._types import UserAPIKeyAuth - - server = _delegate_auth_mcp_server().model_copy(update={"alias": "dt-alias"}) - scope = { - "type": "http", - "method": "POST", - "path": "/mcp/dt-alias", - "scheme": "http", - "server": ("localhost", 4000), - "headers": [(b"authorization", b"Bearer bogus-token")], - } - - with ( - _patch_delegate_resolver(server, "dt-alias"), - patch( - "litellm.proxy._experimental.mcp_server.server._get_allowed_mcp_servers", - new=AsyncMock(return_value=[server]), - ), - patch( - "litellm.proxy._experimental.mcp_server.server._probe_upstream_auth", - new=AsyncMock(return_value=(401, 'Bearer error="invalid_token"')), - ), - ): - with pytest.raises(HTTPException) as exc_info: - await _check_passthrough_upstream_auth( - scope=scope, - user_api_key_auth=UserAPIKeyAuth(), - mcp_servers=["dt-alias"], - client_ip=None, - ) - - challenge = exc_info.value.headers["www-authenticate"] - assert 'error="invalid_token"' in challenge - assert 'resource_metadata="http://localhost:4000/.well-known/oauth-protected-resource/mcp/dt-alias"' in challenge - - @pytest.mark.asyncio async def test_delegate_probe_not_fanned_out_to_access_group_members(): """A single access-group name passes the one-target route gate but must not fan @@ -6578,41 +6559,6 @@ async def test_delegate_probe_not_fanned_out_to_access_group_members(): probe.assert_not_awaited() -def test_is_delegate_upstream_probe_target_fails_closed_on_m2m_shape(): - """An unstamped M2M-shape row (null ``oauth2_flow`` + client credentials) - resolves to ``client_credentials`` and must not be probed with the caller's - bearer; its stored client credentials drive egress instead.""" - from litellm.proxy._experimental.mcp_server.server import ( - _is_delegate_upstream_probe_target, - ) - - assert _is_delegate_upstream_probe_target(_delegate_auth_mcp_server()) is True - - m2m_shape = MCPServer( - server_id="delegate-m2m", - name="delegate_m2m", - url="http://upstream:9401/mcp", - transport=MCPTransport.http, - auth_type=MCPAuth.oauth2, - delegate_auth_to_upstream=True, - oauth2_flow=None, - token_url="http://idp:9000/token", - client_id="client", - client_secret="secret", - ) - assert _is_delegate_upstream_probe_target(m2m_shape) is False - - non_delegate = MCPServer( - server_id="oauth2-plain", - name="oauth2_plain", - url="http://upstream:9401/mcp", - transport=MCPTransport.http, - auth_type=MCPAuth.oauth2, - oauth2_flow="authorization_code", - ) - assert _is_delegate_upstream_probe_target(non_delegate) is False - - @pytest.mark.asyncio async def test_create_mcp_client_sampling_disabled_by_default(): """Sampling callback must be None when allow_sampling is not set (default False).""" diff --git a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py index d2987c5112e..d56f08c4e79 100644 --- a/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py +++ b/tests/test_litellm/proxy/_experimental/mcp_server/test_mcp_server_manager.py @@ -3390,6 +3390,72 @@ class TestMCPServerManager: ) assert not extra_headers or "authorization" not in {k.lower() for k in extra_headers} + @pytest.mark.asyncio + async def test_call_regular_mcp_tool_legacy_delegate_never_forwards_admission_key(self): + from litellm.proxy._types import UserAPIKeyAuth + + server = MCPServer( + server_id="server-legacy-delegate-leak", + name="legacy-delegate", + url="https://example.com", + transport=MCPTransport.http, + auth_type=MCPAuth.oauth2, + delegate_auth_to_upstream=True, + ) + extra_headers = await self._capture_call_extra_headers( + server, + oauth2_headers={"Authorization": "Bearer sk-litellm-key"}, + raw_headers={"authorization": "Bearer sk-litellm-key"}, + user_api_key_auth=UserAPIKeyAuth(api_key="sk-litellm-key"), + ) + assert not extra_headers or "authorization" not in {k.lower() for k in extra_headers} + + @pytest.mark.asyncio + async def test_call_regular_mcp_tool_legacy_delegate_forwards_separate_authorization(self): + from litellm.proxy._types import UserAPIKeyAuth + + server = MCPServer( + server_id="server-legacy-delegate-dual-credential", + name="legacy-delegate", + url="https://example.com", + transport=MCPTransport.http, + auth_type=MCPAuth.oauth2, + delegate_auth_to_upstream=True, + ) + extra_headers = await self._capture_call_extra_headers( + server, + oauth2_headers={"Authorization": "Bearer upstream-token"}, + raw_headers={ + "x-litellm-api-key": "Bearer sk-litellm-key", + "authorization": "Bearer upstream-token", + }, + user_api_key_auth=UserAPIKeyAuth(api_key="sk-litellm-key"), + ) + assert extra_headers == {"Authorization": "Bearer upstream-token"} + + @pytest.mark.asyncio + async def test_call_regular_mcp_tool_legacy_delegate_strips_repeated_admission_key(self): + from litellm.proxy._types import UserAPIKeyAuth + + server = MCPServer( + server_id="server-legacy-delegate-repeated-key", + name="legacy-delegate", + url="https://example.com", + transport=MCPTransport.http, + auth_type=MCPAuth.oauth2, + delegate_auth_to_upstream=True, + ) + extra_headers = await self._capture_call_extra_headers( + server, + oauth2_headers={"Authorization": "Bearer sk-litellm-key"}, + raw_headers={ + "x-litellm-api-key": "Bearer sk-litellm-key", + "authorization": "Bearer sk-litellm-key", + }, + user_api_key_auth=UserAPIKeyAuth(api_key="sk-litellm-key"), + ) + assert not extra_headers or "authorization" not in {k.lower() for k in extra_headers} + def test_should_strip_caller_authorization_new_modes(self): from litellm.proxy._types import UserAPIKeyAuth @@ -6916,51 +6982,6 @@ class TestMCPServerManager: == expected_server_ids ) - @pytest.mark.asyncio - async def test_get_allowed_mcp_servers_anonymous_delegate_requires_oauth2(self): - """Anonymous delegated auth listing should only include oauth2 servers.""" - from litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp import ( - MCPRequestHandler, - ) - - manager = MCPServerManager() - oauth_delegate_server = MCPServer( - server_id="oauth-delegate", - name="oauth_delegate", - transport=MCPTransport.http, - auth_type=MCPAuth.oauth2, - delegate_auth_to_upstream=True, - ) - api_key_delegate_server = MCPServer( - server_id="api-key-delegate", - name="api_key_delegate", - transport=MCPTransport.http, - auth_type=MCPAuth.api_key, - delegate_auth_to_upstream=True, - ) - oauth_non_delegate_server = MCPServer( - server_id="oauth-non-delegate", - name="oauth_non_delegate", - transport=MCPTransport.http, - auth_type=MCPAuth.oauth2, - delegate_auth_to_upstream=False, - ) - manager.registry = { - oauth_delegate_server.server_id: oauth_delegate_server, - api_key_delegate_server.server_id: api_key_delegate_server, - oauth_non_delegate_server.server_id: oauth_non_delegate_server, - } - - with patch.object( - MCPRequestHandler, - "get_allowed_mcp_servers", - new_callable=AsyncMock, - return_value=[], - ): - result = await manager.get_allowed_mcp_servers(None) - - assert set(result) == {"oauth-delegate"} - def test_get_mcp_server_from_tool_name_uses_server_name_not_name(self): """ Test that _get_mcp_server_from_tool_name uses server.server_name instead of server.name @@ -8088,9 +8109,9 @@ class TestMCPServerTokenExchangeColumns: assert rebuilt_table.token_exchange_profile == "entra_obo" -class TestInternalDelegatePkceWarningLog: +class TestLegacyDelegateAuthWarningLog: @pytest.mark.asyncio - async def test_build_mcp_server_logs_on_internal_delegate_interactive(self, caplog): + async def test_build_mcp_server_logs_deprecation_for_internal_delegate(self, caplog): caplog.set_level(logging.WARNING, logger="LiteLLM") manager = MCPServerManager() table_record = LiteLLM_MCPServerTable( @@ -8106,11 +8127,11 @@ class TestInternalDelegatePkceWarningLog: ) await manager.build_mcp_server_from_table(table_record) combined = " ".join(r.getMessage() for r in caplog.records) - assert "internal-only" in combined + assert "deprecated auth_type=oauth2" in combined assert "delegate_auth_to_upstream=true" in combined @pytest.mark.asyncio - async def test_build_mcp_server_no_internal_delegate_log_when_public(self, caplog): + async def test_build_mcp_server_logs_deprecation_for_public_delegate(self, caplog): caplog.set_level(logging.WARNING, logger="LiteLLM") manager = MCPServerManager() table_record = LiteLLM_MCPServerTable( @@ -8126,12 +8147,13 @@ class TestInternalDelegatePkceWarningLog: ) await manager.build_mcp_server_from_table(table_record) combined = " ".join(r.getMessage() for r in caplog.records) - assert "internal-only" not in combined + assert "deprecated auth_type=oauth2" in combined + assert "auth_type=oauth_delegate" in combined def test_warn_skipped_for_client_credentials(self, caplog): caplog.set_level(logging.WARNING, logger="LiteLLM") from litellm.proxy._experimental.mcp_server.mcp_server_manager import ( - _warn_internal_delegate_pkce_if_applicable, + _warn_legacy_delegate_auth_if_applicable, ) server = MCPServer( @@ -8144,9 +8166,9 @@ class TestInternalDelegatePkceWarningLog: available_on_public_internet=False, delegate_auth_to_upstream=True, ) - _warn_internal_delegate_pkce_if_applicable(server, source="test") + _warn_legacy_delegate_auth_if_applicable(server, source="test") combined = " ".join(r.getMessage() for r in caplog.records) - assert "internal-only" not in combined + assert "deprecated auth_type=oauth2" not in combined class TestHasClientCredentialsOAuth2Flow: diff --git a/tests/test_litellm/proxy/analytics_endpoints/test_analytics_endpoints.py b/tests/test_litellm/proxy/analytics_endpoints/test_analytics_endpoints.py index 4072f83511e..ea528878db8 100644 --- a/tests/test_litellm/proxy/analytics_endpoints/test_analytics_endpoints.py +++ b/tests/test_litellm/proxy/analytics_endpoints/test_analytics_endpoints.py @@ -12,10 +12,13 @@ from unittest.mock import AsyncMock, MagicMock import pytest from fastapi import HTTPException +from litellm.proxy._types import LiteLLMRoutes from litellm.proxy.analytics_endpoints.analytics_endpoints import get_global_activity from litellm.proxy.analytics_endpoints.cache_activity import ( ERROR_BREAKDOWN_SQL, GROUPS_SQL, + KEY_ALIAS_OPTIONS_SQL, + MODEL_OPTIONS_SQL, CacheActivityGroup, compute_totals, ) @@ -112,6 +115,21 @@ async def test_filters_are_passed_to_sql_as_json_arrays(mock_prisma: MagicMock): assert call.args[4] == json.dumps(["gpt-5.1", "claude-opus-4-8"]) +@pytest.mark.asyncio +async def test_every_query_excludes_the_same_info_routes(mock_prisma: MagicMock): + """Regression for LIT-5884: failed info-route calls are spend-logged but are not inference traffic, so + the groups, error breakdown and both filter-option queries all receive the same exclusion list. What + the SQL does with it is covered against Postgres in tests/proxy_behavior/spend/test_cache_activity.py.""" + await get_global_activity(start_date="2026-07-01", end_date="2026-07-27", key_aliases=[], models=[]) + + exclusions_by_query = {call.args[0]: json.loads(call.args[-1]) for call in mock_prisma.db.query_raw.call_args_list} + assert set(exclusions_by_query) == {GROUPS_SQL, ERROR_BREAKDOWN_SQL, KEY_ALIAS_OPTIONS_SQL, MODEL_OPTIONS_SQL} + for excluded_call_types in exclusions_by_query.values(): + assert excluded_call_types == LiteLLMRoutes.info_routes.value + assert {"/model/info", "/v1/models", "/key/info"} <= set(excluded_call_types) + assert "" not in excluded_call_types + + @pytest.mark.asyncio async def test_rejects_malformed_dates_with_400(mock_prisma: MagicMock): with pytest.raises(HTTPException) as exc_info: diff --git a/tests/test_litellm/proxy/auth/test_auth_checks.py b/tests/test_litellm/proxy/auth/test_auth_checks.py index d9a065db3cb..5f87f2def93 100644 --- a/tests/test_litellm/proxy/auth/test_auth_checks.py +++ b/tests/test_litellm/proxy/auth/test_auth_checks.py @@ -5527,7 +5527,9 @@ async def _run_internal_user_budget_alert( with ( patch("litellm.proxy.proxy_server.prisma_client", None), # test-quality-ok: common_checks has no database seam - patch("litellm.proxy.proxy_server.get_current_spend", _get_spend), # test-quality-ok: common_checks imports it locally + patch( # test-quality-ok: common_checks imports get_current_spend locally + "litellm.proxy.proxy_server.get_current_spend", _get_spend + ), patch.object(slack_alerting, "send_alert", send_alert), ): error: Final = await _check_for_error() @@ -6390,6 +6392,409 @@ async def test_get_team_membership_db_fetch_returns_validated_membership(): assert result.spend == 1.5 +@pytest.mark.asyncio +async def test_get_team_membership_negative_caches_a_missing_row(): + """ + Regression (LIT-7358): a member with no LiteLLM_TeamMembership row is the common lite-login case, + and the session-token refresh reads this loader on every request. Before the fix a missing row + returned None without caching, so every request re-queried the DB. The miss must be cached so the + second request serves from cache and never touches the DB. + """ + from litellm.proxy.auth.auth_checks import get_team_membership + from litellm.proxy.common_utils.user_api_key_cache import ( + NO_TEAM_MEMBERSHIP_SENTINEL, + team_membership_reservation_cache_key, + ) + + mock_prisma_client = MagicMock() + mock_prisma_client.db.litellm_teammembership.find_unique = AsyncMock(return_value=None) + + cache = UserApiKeyCache() + + first = await get_team_membership( + user_id="u-1", team_id="t-1", prisma_client=mock_prisma_client, user_api_key_cache=cache + ) + second = await get_team_membership( + user_id="u-1", team_id="t-1", prisma_client=mock_prisma_client, user_api_key_cache=cache + ) + + assert first is None + assert second is None + mock_prisma_client.db.litellm_teammembership.find_unique.assert_awaited_once() + cached = await cache.async_get_cache(key=team_membership_reservation_cache_key(user_id="u-1", team_id="t-1")) + assert cached == NO_TEAM_MEMBERSHIP_SENTINEL + + +@pytest.mark.asyncio +async def test_get_team_membership_reads_sentinel_as_no_membership_not_a_model(): + """ + The negative-cache sentinel is a plain string sharing the key a serialized membership uses. + A pre-seeded sentinel must read back as None (no DB read), never be mistaken for a membership. + """ + from litellm.proxy.auth.auth_checks import get_team_membership + from litellm.proxy.common_utils.user_api_key_cache import ( + NO_TEAM_MEMBERSHIP_SENTINEL, + team_membership_reservation_cache_key, + ) + + cache = UserApiKeyCache() + await cache.async_set_cache( + key=team_membership_reservation_cache_key(user_id="u-1", team_id="t-1"), + value=NO_TEAM_MEMBERSHIP_SENTINEL, + ) + + mock_prisma_client = MagicMock() + mock_prisma_client.db.litellm_teammembership.find_unique = AsyncMock(return_value=None) + + result = await get_team_membership( + user_id="u-1", team_id="t-1", prisma_client=mock_prisma_client, user_api_key_cache=cache + ) + + assert result is None + mock_prisma_client.db.litellm_teammembership.find_unique.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_get_team_membership_coalesces_parallel_db_fetches(): + from litellm.proxy.auth.auth_checks import get_team_membership + + started = asyncio.Event() + release = asyncio.Event() + membership_row = MagicMock() + membership_row.dict = lambda: {"user_id": "u-parallel", "team_id": "t-parallel", "spend": 1.0} + + async def _slow_find_unique(*args, **kwargs): + started.set() + await release.wait() + return membership_row + + mock_prisma_client = MagicMock() + mock_prisma_client.db.litellm_teammembership.find_unique = AsyncMock(side_effect=_slow_find_unique) + cache = UserApiKeyCache() + + async def _load(): + return await get_team_membership( + user_id="u-parallel", + team_id="t-parallel", + prisma_client=mock_prisma_client, + user_api_key_cache=cache, + ) + + first = asyncio.create_task(_load()) + second = asyncio.create_task(_load()) + await started.wait() + await asyncio.sleep(0) + release.set() + results = await asyncio.gather(first, second) + + assert results[0] is not None and results[1] is not None + assert results[0].user_id == "u-parallel" + assert results[1].user_id == "u-parallel" + mock_prisma_client.db.litellm_teammembership.find_unique.assert_awaited_once() + + +@pytest.mark.asyncio +async def test_get_team_membership_invalidation_waits_for_in_flight_load_then_evicts_it(): + from litellm.proxy._types import LiteLLM_TeamMembership + from litellm.proxy.auth.auth_checks import get_team_membership, invalidate_team_member_spend_state + from litellm.proxy.common_utils.cache_pydantic_utils import CacheCodec + from litellm.proxy.common_utils.user_api_key_cache import team_membership_reservation_cache_key + + started = asyncio.Event() + release_stale = asyncio.Event() + rows = iter(("budget-old", "budget-new")) + + async def _find_unique(*args, **kwargs): + budget_id = next(rows) + row = MagicMock() + row.dict = lambda: {"user_id": "u-inv", "team_id": "t-inv", "spend": 1.0, "budget_id": budget_id} + if budget_id == "budget-old": + started.set() + await release_stale.wait() + return row + + mock_prisma_client = MagicMock() + mock_prisma_client.db.litellm_teammembership.find_unique = AsyncMock(side_effect=_find_unique) + cache = UserApiKeyCache() + _key = team_membership_reservation_cache_key(user_id="u-inv", team_id="t-inv") + + async def _load(): + return await get_team_membership( + user_id="u-inv", team_id="t-inv", prisma_client=mock_prisma_client, user_api_key_cache=cache + ) + + stale = asyncio.create_task(_load()) + await asyncio.wait_for(started.wait(), timeout=2) + invalidation = asyncio.create_task( + invalidate_team_member_spend_state(user_id="u-inv", team_id="t-inv", user_api_key_cache=cache) + ) + for _ in range(5): + await asyncio.sleep(0) + assert not invalidation.done() + + release_stale.set() + await asyncio.wait_for(invalidation, timeout=2) + stale_result = await stale + assert stale_result is not None and stale_result.budget_id == "budget-old" + assert await cache.async_get_cache(key=_key) is None + + fresh_result = await _load() + assert fresh_result is not None and fresh_result.budget_id == "budget-new" + assert mock_prisma_client.db.litellm_teammembership.find_unique.await_count == 2 + cached = CacheCodec.deserialize(await cache.async_get_cache(key=_key), model_type=LiteLLM_TeamMembership) + assert cached is not None and cached.budget_id == "budget-new" + again = await _load() + assert again is not None and again.budget_id == "budget-new" + assert mock_prisma_client.db.litellm_teammembership.find_unique.await_count == 2 + + +@pytest.mark.asyncio +async def test_get_team_membership_invalidation_during_cache_write_evicts_stale_entry(): + from litellm.proxy.auth.auth_checks import get_team_membership, invalidate_team_member_spend_state + from litellm.proxy.common_utils.user_api_key_cache import team_membership_reservation_cache_key + + write_started = asyncio.Event() + release_write = asyncio.Event() + + class _SlowWriteCache(UserApiKeyCache): + async def async_set_cache(self, key, value, local_only=False, **kwargs): + write_started.set() + await release_write.wait() + return await super().async_set_cache(key, value, local_only=local_only, **kwargs) + + row = MagicMock() + row.dict = lambda: {"user_id": "u-w", "team_id": "t-w", "spend": 1.0, "budget_id": "budget-old"} + mock_prisma_client = MagicMock() + mock_prisma_client.db.litellm_teammembership.find_unique = AsyncMock(return_value=row) + cache = _SlowWriteCache() + + stale = asyncio.create_task( + get_team_membership(user_id="u-w", team_id="t-w", prisma_client=mock_prisma_client, user_api_key_cache=cache) + ) + await asyncio.wait_for(write_started.wait(), timeout=2) + invalidation = asyncio.create_task( + invalidate_team_member_spend_state(user_id="u-w", team_id="t-w", user_api_key_cache=cache) + ) + for _ in range(5): + await asyncio.sleep(0) + assert not invalidation.done() + + release_write.set() + await asyncio.wait_for(invalidation, timeout=2) + stale_result = await stale + + assert stale_result is not None and stale_result.budget_id == "budget-old" + assert await cache.async_get_cache(key=team_membership_reservation_cache_key(user_id="u-w", team_id="t-w")) is None + + +@pytest.mark.asyncio +async def test_common_checks_calls_get_team_membership_once_per_request(): + from fastapi import Request + + from litellm.proxy.auth.auth_checks import common_checks + + team = LiteLLM_TeamTable(team_id="t-once") + token = UserAPIKeyAuth(token="k-once", user_id="u-once", team_id="t-once", models=["gpt-4o-mini"]) + membership = MagicMock() + membership.litellm_budget_table = None + membership.spend = 0.0 + + with ( + patch( # test-quality-ok: common_checks imports prisma_client from proxy_server + "litellm.proxy.proxy_server.prisma_client", MagicMock() + ), + patch( # test-quality-ok: common_checks imports user_api_key_cache from proxy_server + "litellm.proxy.proxy_server.user_api_key_cache", UserApiKeyCache() + ), + patch( # test-quality-ok: counts membership loads; common_checks has no membership seam + "litellm.proxy.auth.auth_checks.get_team_membership", + new_callable=AsyncMock, + return_value=membership, + ) as load_membership, + patch( # test-quality-ok: common_checks imports get_current_spend locally + "litellm.proxy.proxy_server.get_current_spend", new_callable=AsyncMock, return_value=0.0 + ), + ): + result = await common_checks( + request_body={"model": "gpt-4o-mini", "messages": [{"role": "user", "content": "hi"}]}, + team_object=team, + user_object=LiteLLM_UserTable(user_id="u-once"), + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/chat/completions", + llm_router=None, + proxy_logging_obj=MagicMock(), + valid_token=token, + request=MagicMock(spec=Request), + ) + + assert result is True + assert load_membership.await_count == 1 + + +@pytest.mark.asyncio +async def test_common_checks_skips_membership_load_when_no_check_reads_it(): + from fastapi import Request + + from litellm.proxy.auth.auth_checks import common_checks + + team = LiteLLM_TeamTable(team_id="t-lazy") + token = UserAPIKeyAuth(token="k-lazy", user_id="u-lazy", team_id="t-lazy") + + with ( + patch( # test-quality-ok: common_checks imports prisma_client from proxy_server + "litellm.proxy.proxy_server.prisma_client", MagicMock() + ), + patch( # test-quality-ok: common_checks imports user_api_key_cache from proxy_server + "litellm.proxy.proxy_server.user_api_key_cache", UserApiKeyCache() + ), + patch( # test-quality-ok: counts membership loads; common_checks has no membership seam + "litellm.proxy.auth.auth_checks.get_team_membership", + new_callable=AsyncMock, + ) as load_membership, + ): + result = await common_checks( + request_body={}, + team_object=team, + user_object=LiteLLM_UserTable(user_id="u-lazy"), + end_user_object=None, + global_proxy_spend=None, + general_settings={}, + route="/key/info", + llm_router=None, + proxy_logging_obj=MagicMock(), + valid_token=token, + request=MagicMock(spec=Request), + ) + + assert result is True + load_membership.assert_not_awaited() + + +@pytest.mark.asyncio +async def test_get_team_membership_db_error_returns_none_and_retries_next_call(): + from litellm.proxy.auth.auth_checks import get_team_membership + from litellm.proxy.common_utils.user_api_key_cache import team_membership_reservation_cache_key + + membership_row = MagicMock() + membership_row.dict = lambda: {"user_id": "u-fail", "team_id": "t-fail", "spend": 1.0} + mock_prisma_client = MagicMock() + mock_prisma_client.db.litellm_teammembership.find_unique = AsyncMock( + side_effect=[RuntimeError("db down"), membership_row] + ) + cache = UserApiKeyCache() + + failed = await get_team_membership( + user_id="u-fail", + team_id="t-fail", + prisma_client=mock_prisma_client, + user_api_key_cache=cache, + ) + cached_after_failure = await cache.async_get_cache( + key=team_membership_reservation_cache_key(user_id="u-fail", team_id="t-fail") + ) + recovered = await get_team_membership( + user_id="u-fail", + team_id="t-fail", + prisma_client=mock_prisma_client, + user_api_key_cache=cache, + ) + + assert failed is None + assert cached_after_failure is None + assert recovered is not None + assert recovered.user_id == "u-fail" + assert mock_prisma_client.db.litellm_teammembership.find_unique.await_count == 2 + + +@pytest.mark.asyncio +async def test_get_team_membership_string_prisma_client_returns_none(): + from litellm.proxy.auth.auth_checks import get_team_membership + + result = await get_team_membership( + user_id="u-str", + team_id="t-str", + prisma_client="hello-world", + user_api_key_cache=UserApiKeyCache(), + ) + assert result is None + + +@pytest.mark.asyncio +async def test_get_team_membership_waiter_cancel_does_not_cancel_shared_load(): + from litellm.proxy.auth.auth_checks import get_team_membership + + started = asyncio.Event() + release = asyncio.Event() + membership_row = MagicMock() + membership_row.dict = lambda: {"user_id": "u-shield", "team_id": "t-shield", "spend": 1.0} + + async def _slow_find_unique(*args, **kwargs): + started.set() + await release.wait() + return membership_row + + mock_prisma_client = MagicMock() + mock_prisma_client.db.litellm_teammembership.find_unique = AsyncMock(side_effect=_slow_find_unique) + cache = UserApiKeyCache() + + async def _load(): + return await get_team_membership( + user_id="u-shield", + team_id="t-shield", + prisma_client=mock_prisma_client, + user_api_key_cache=cache, + ) + + owner = asyncio.create_task(_load()) + await started.wait() + waiter = asyncio.create_task(_load()) + await asyncio.sleep(0) + waiter.cancel() + with pytest.raises(asyncio.CancelledError): + await waiter + release.set() + result = await owner + + assert result is not None + assert result.user_id == "u-shield" + mock_prisma_client.db.litellm_teammembership.find_unique.assert_awaited_once() + + +@pytest.mark.asyncio +async def test_invalidate_team_member_spend_state_evicts_the_negative_cache_sentinel(): + """ + A member who later gains a per-member budget writes a membership row and calls + invalidate_team_member_spend_state. That must drop a cached "no membership" sentinel so the next + request re-reads the DB and honors the new budget instead of serving the stale miss until TTL. + """ + from litellm.proxy.auth.auth_checks import get_team_membership, invalidate_team_member_spend_state + from litellm.proxy.common_utils.user_api_key_cache import team_membership_reservation_cache_key + + cache = UserApiKeyCache() + membership_row = MagicMock() + membership_row.dict = lambda: {"user_id": "u-1", "team_id": "t-1", "spend": 0.0} + + mock_prisma_client = MagicMock() + mock_prisma_client.db.litellm_teammembership.find_unique = AsyncMock(side_effect=[None, membership_row]) + + before = await get_team_membership( + user_id="u-1", team_id="t-1", prisma_client=mock_prisma_client, user_api_key_cache=cache + ) + assert before is None + + await invalidate_team_member_spend_state(user_id="u-1", team_id="t-1", user_api_key_cache=cache) + assert await cache.async_get_cache(key=team_membership_reservation_cache_key(user_id="u-1", team_id="t-1")) is None + + after = await get_team_membership( + user_id="u-1", team_id="t-1", prisma_client=mock_prisma_client, user_api_key_cache=cache + ) + assert after is not None + assert after.user_id == "u-1" + assert mock_prisma_client.db.litellm_teammembership.find_unique.await_count == 2 + + @pytest.mark.asyncio async def test_get_access_object_db_fetch_returns_validated_access_group(): from litellm.proxy._types import LiteLLM_AccessGroupTable diff --git a/tests/test_litellm/proxy/auth/test_auth_utils.py b/tests/test_litellm/proxy/auth/test_auth_utils.py index cdf1f897707..bd6a14cad21 100644 --- a/tests/test_litellm/proxy/auth/test_auth_utils.py +++ b/tests/test_litellm/proxy/auth/test_auth_utils.py @@ -433,6 +433,232 @@ def test_get_model_from_request_no_request_extracts_model(): ) +def _cache_prediction_router(): + from litellm.router import Router + + return Router(model_list=[ + { + "model_name": group, + "litellm_params": {"model": "anthropic/claude-sonnet-5", "api_key": "test-provider-key"}, + "model_info": {"id": deployment_id, "team_id": team_id}, + } + for group, deployment_id, team_id in ( + ("current-group", "current-id", None), ("candidate-group", "candidate-id", None), + ("own-group", "own-id", "prediction-team"), ("foreign-group", "foreign-id", "foreign-team"), + ) + ]) + + +@pytest.mark.parametrize("candidate,team_id,expected", [ + ("candidate-id", None, ["current-group", "candidate-group"]), + ("current-id", None, "current-group"), + ("missing-id", None, None), + ("candidate-group", None, None), + ("own-id", None, None), + ("own-id", "prediction-team", ["current-group", "own-group"]), + ("foreign-id", "prediction-team", None), +]) +def test_cache_prediction_auth_resolves_only_exact_deployment_ids(candidate, team_id, expected): + assert get_model_from_request( + request_data={ + "current_deployment_id": "current-id", "candidate_deployment_id": candidate, + "request": {"model": "caller-controlled-provider-model"}, + }, + route="/cost/predict-cache", + llm_router=_cache_prediction_router(), + team_id=team_id, + ) == expected + + +def _cache_prediction_auth_app( + monkeypatch, allowed_routes, user_models, metadata=None, *, team_id=None, key_models=None, team_models=None +): + import importlib + from unittest.mock import AsyncMock + + from fastapi import FastAPI + + import litellm.proxy.proxy_server as proxy_server + from litellm.caching.dual_cache import DualCache + from litellm.proxy._types import LiteLLM_TeamTableCachedObj, LiteLLM_UserTable, LitellmUserRoles, ProxyException + from litellm.proxy.auth import auth_checks + from litellm.proxy.hooks.parallel_request_limiter_v3 import _PROXY_MaxParallelRequestsHandler_v3 + from litellm.proxy.management_endpoints import prompt_cache_prediction as endpoint + from litellm.proxy.utils import InternalUsageCache, ProxyLogging + + auth = importlib.import_module("litellm.proxy.auth.user_api_key_auth") + router = _cache_prediction_router() + allowed_models = ["current-group", "candidate-group", "own-group"] + token = UserAPIKeyAuth( + api_key="test-proxy-key-hash", user_id="prediction-user", user_role=LitellmUserRoles.INTERNAL_USER, + models=allowed_models if key_models is None else key_models, team_id=team_id, + team_models=allowed_models if team_models is None else team_models, + allowed_routes=allowed_routes, metadata=metadata or {}, + ) + user = LiteLLM_UserTable( + user_id=token.user_id, user_role=LitellmUserRoles.INTERNAL_USER.value, models=user_models, + ) + async def authenticate(request, request_data, **_headers): + await auth._enforce_key_and_fallback_model_access( + valid_token=token, request_data=request_data, route=request.url.path, request=request, + llm_model_list=router.get_model_list(), llm_router=router, + ) + return token + + monkeypatch.setattr(auth, "_user_api_key_auth_builder", authenticate) + monkeypatch.setattr(auth, "get_user_object", AsyncMock(return_value=user)) + team = LiteLLM_TeamTableCachedObj(team_id=team_id, models=token.team_models) if team_id else None + monkeypatch.setattr(auth, "get_team_object", AsyncMock(return_value=team)) + monkeypatch.setattr(auth_checks, "get_team_object", AsyncMock(return_value=team)) + monkeypatch.setattr(auth_checks, "get_team_membership", AsyncMock(return_value=None)) + monkeypatch.setattr(auth, "get_global_proxy_spend", AsyncMock(return_value=0)) + monkeypatch.setattr(proxy_server, "master_key", "test-master-key") + monkeypatch.setattr(proxy_server, "user_custom_auth", None) + monkeypatch.setattr(proxy_server, "general_settings", {}) + monkeypatch.setattr(proxy_server, "llm_router", router) + monkeypatch.setattr(proxy_server, "llm_model_list", router.get_model_list()) + monkeypatch.setattr(proxy_server, "prisma_client", None) + monkeypatch.setattr(proxy_server, "user_api_key_cache", DualCache()) + logging = ProxyLogging(user_api_key_cache=DualCache()) + logging.proxy_hook_mapping["parallel_request_limiter"] = _PROXY_MaxParallelRequestsHandler_v3( + InternalUsageCache(dual_cache=DualCache()) + ) + monkeypatch.setattr(proxy_server, "proxy_logging_obj", logging) + counts = AsyncMock(return_value=6_000) + monkeypatch.setattr(endpoint, "count_prompt_tokens", counts) + app = FastAPI() + app.include_router(endpoint.router) + app.add_exception_handler(ProxyException, proxy_server.openai_exception_handler) + return app, counts + + +def _cache_prediction_payload(candidate="candidate-id", current="current-id"): + return { + "current_deployment_id": current, "candidate_deployment_id": candidate, + "request": {"messages": [{"role": "user", "content": [{ + "type": "text", "text": "Stable cached context", + "cache_control": {"type": "ephemeral"}, + }]}]}, + } + + +@pytest.mark.asyncio +@pytest.mark.parametrize("allowed_routes,user_models,candidate,status_code", [ + (["/chat/completions"], ["current-group", "candidate-group"], "candidate-id", 403), + (["/cost/predict-cache"], ["current-group"], "candidate-id", 403), + (["/cost/*"], ["current-group", "candidate-group"], "candidate-id", 200), + (["/cost/predict-cache"], ["current-group"], "current-id", 200), + (["/cost/predict-cache"], ["current-group"], "missing-id", 404), +]) +async def test_cache_prediction_authorizes_route_and_personal_models_before_provider_counts( + monkeypatch, allowed_routes, user_models, candidate, status_code +): + import httpx + + app, counts = _cache_prediction_auth_app(monkeypatch, allowed_routes, user_models) + async with httpx.AsyncClient(transport=httpx.ASGITransport(app=app), base_url="http://test") as client: + response = await client.post("/cost/predict-cache", json=_cache_prediction_payload(candidate)) + + assert response.status_code == status_code, response.text + if status_code == 200: + assert counts.await_count == (2 if candidate == "current-id" else 4) + else: + assert counts.await_count == 0 + + +@pytest.mark.asyncio +@pytest.mark.parametrize("arm", ["current_deployment_id", "candidate_deployment_id"]) +@pytest.mark.parametrize("team_id,key_models,user_models,team_models", [ + (None, ["*"], ["*"], None), + (None, ["current-group", "candidate-group"], ["*"], None), + (None, ["*"], ["current-group", "candidate-group"], None), + ("prediction-team", ["*"], ["*"], ["current-group", "candidate-group"]), +]) +async def test_cache_prediction_hides_foreign_and_missing_ids_before_model_authorization( + monkeypatch, arm, team_id, key_models, user_models, team_models +): + import httpx + + app, counts = _cache_prediction_auth_app( + monkeypatch, ["/cost/predict-cache"], user_models, + team_id=team_id, key_models=key_models, team_models=team_models, + ) + async with httpx.AsyncClient(transport=httpx.ASGITransport(app=app), base_url="http://test") as client: + missing = await client.post("/cost/predict-cache", json={**_cache_prediction_payload(), arm: "missing-id"}) + foreign = await client.post("/cost/predict-cache", json={**_cache_prediction_payload(), arm: "foreign-id"}) + + assert missing.status_code == foreign.status_code == 404, foreign.text + assert missing.json() == foreign.json() == {"detail": "Deployment not found"} + assert counts.await_count == 0 + + +@pytest.mark.asyncio +@pytest.mark.parametrize("arm", ["current_deployment_id", "candidate_deployment_id"]) +@pytest.mark.parametrize("key_models,team_models,status_code", [ + (["*"], ["*"], 200), + (["current-group", "candidate-group"], ["*"], 403), + (["*"], ["current-group", "candidate-group"], 403), +]) +async def test_cache_prediction_checks_each_visible_team_deployment_model( + monkeypatch, arm, key_models, team_models, status_code +): + import httpx + + app, counts = _cache_prediction_auth_app( + monkeypatch, ["/cost/predict-cache"], ["*"], + team_id="prediction-team", key_models=key_models, team_models=team_models, + ) + async with httpx.AsyncClient(transport=httpx.ASGITransport(app=app), base_url="http://test") as client: + response = await client.post("/cost/predict-cache", json={**_cache_prediction_payload(), arm: "own-id"}) + + assert response.status_code == status_code, response.text + assert counts.await_count == (4 if status_code == 200 else 0) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("arm", ["current_deployment_id", "candidate_deployment_id"]) +async def test_cache_prediction_checks_each_visible_personal_deployment_model(monkeypatch, arm): + import httpx + + app, counts = _cache_prediction_auth_app(monkeypatch, ["/cost/predict-cache"], ["current-group"]) + async with httpx.AsyncClient(transport=httpx.ASGITransport(app=app), base_url="http://test") as client: + response = await client.post( + "/cost/predict-cache", json={**_cache_prediction_payload(candidate="current-id"), arm: "candidate-id"} + ) + + assert response.status_code == 403, response.text + assert response.json()["error"]["type"] == "user_model_access_denied" + assert counts.await_count == 0 + + +@pytest.mark.asyncio +@pytest.mark.parametrize("header_tag,key_tags,limit,status_code,provider_calls", [ + ("limited", [], 1, 429, 1), + (None, ["limited"], 1, 429, 1), + ("limited", ["limited"], 4, 200, 4), + ("unlimited", [], 1, 200, 4), +]) +async def test_cache_prediction_preserves_authenticated_header_and_key_tag_rpm( + monkeypatch, header_tag, key_tags, limit, status_code, provider_calls +): + import httpx + + app, counts = _cache_prediction_auth_app( + monkeypatch, ["/cost/predict-cache"], ["current-group", "candidate-group"], + metadata={"tag_rpm_limit": {"limited": limit}, "tags": key_tags}, + ) + headers = {"x-litellm-tags": header_tag} if header_tag else {} + async with httpx.AsyncClient(transport=httpx.ASGITransport(app=app), base_url="http://test") as client: + response = await client.post("/cost/predict-cache", json=_cache_prediction_payload(), headers=headers) + assert response.status_code == status_code, response.text + assert counts.await_count == provider_calls + if limit == 4: + exhausted = await client.post("/cost/predict-cache", json=_cache_prediction_payload(), headers=headers) + assert exhausted.status_code == 429, exhausted.text + assert counts.await_count == 4 + assert all("metadata" not in call.args[2] for call in counts.await_args_list) + + def test_get_model_from_request_supports_google_model_names_with_slashes(): assert ( get_model_from_request( diff --git a/tests/test_litellm/proxy/auth/test_model_access_group_budgets.py b/tests/test_litellm/proxy/auth/test_model_access_group_budgets.py index fb82d8708fd..7506bd031d9 100644 --- a/tests/test_litellm/proxy/auth/test_model_access_group_budgets.py +++ b/tests/test_litellm/proxy/auth/test_model_access_group_budgets.py @@ -31,6 +31,7 @@ from litellm.proxy.auth.auth_checks import ( ) from litellm.proxy.common_utils.reset_budget_job import _model_access_group_counter_key from litellm.proxy.common_utils.user_api_key_cache import ( + NO_TEAM_MEMBERSHIP_SENTINEL, UserApiKeyCache, model_access_group_registry_cache_key, model_access_group_spend_counter_key, @@ -95,6 +96,11 @@ async def _cache( ), model_type=LiteLLM_TeamMembership, ) + else: + await cache.async_set_cache( + key=team_membership_reservation_cache_key(user_id=USER_ID, team_id=TEAM_ID), + value=NO_TEAM_MEMBERSHIP_SENTINEL, + ) if org_models: await cache.async_set_cache( key=f"org_id:{ORG_ID}", @@ -314,9 +320,7 @@ class _RecordingPrismaClient: def __init__(self, *rows: _MagBudgetRow) -> None: self.rows = {row.access_group_name: row for row in rows} self.batches: list[list[str]] = [] - self.db = SimpleNamespace( - litellm_modelaccessgroupbudgettable=SimpleNamespace(find_many=self._find_many) - ) + self.db = SimpleNamespace(litellm_modelaccessgroupbudgettable=SimpleNamespace(find_many=self._find_many)) async def _find_many(self, **kwargs): requested = list(kwargs["where"]["access_group_name"]["in"]) @@ -345,7 +349,9 @@ async def _enforce( read, seen = _spend_reader(spend_by_counter_key or {}) # The check takes its client and cache as arguments, injected just below. get_current_spend is the # one collaborator it reaches by a lazy `from litellm.proxy.proxy_server import`, with no parameter. - with patch("litellm.proxy.proxy_server.get_current_spend", read): # test-quality-ok: get_current_spend is lazily imported inside _model_access_group_max_budget_check and has no injection point + with patch( # test-quality-ok: get_current_spend is lazily imported inside the budget check + "litellm.proxy.proxy_server.get_current_spend", read + ): await _model_access_group_max_budget_check( matched_model_access_groups=matched, prisma_client=prisma_client if prisma_client is not None else _RecordingPrismaClient(*rows), @@ -491,9 +497,7 @@ async def test_a_second_request_serves_the_budget_row_from_cache(): async def test_a_database_error_does_not_block_the_request(): class _FailingPrismaClient: def __init__(self) -> None: - self.db = SimpleNamespace( - litellm_modelaccessgroupbudgettable=SimpleNamespace(find_many=self._boom) - ) + self.db = SimpleNamespace(litellm_modelaccessgroupbudgettable=SimpleNamespace(find_many=self._boom)) async def _boom(self, **kwargs): raise RuntimeError("database unavailable") @@ -507,11 +511,15 @@ async def _common_checks_with_over_budget_group(*, skip_budget_checks: bool) -> read, _ = _spend_reader({MODEL_ACCESS_GROUP_COUNTER_KEY: 99.0}) with ( - # common_checks resolves all three off the proxy_server module at call time; its signature - # has no client, cache or spend-reader parameter to pass them through instead. - patch("litellm.proxy.proxy_server.prisma_client", prisma_client), # test-quality-ok: common_checks lazily imports prisma_client from proxy_server and takes no client parameter - patch("litellm.proxy.proxy_server.user_api_key_cache", cache), # test-quality-ok: common_checks lazily imports user_api_key_cache from proxy_server and takes no cache parameter - patch("litellm.proxy.proxy_server.get_current_spend", read), # test-quality-ok: get_current_spend is lazily imported inside the budget check and has no injection point + patch( # test-quality-ok: common_checks lazily imports prisma_client from proxy_server + "litellm.proxy.proxy_server.prisma_client", prisma_client + ), + patch( # test-quality-ok: common_checks lazily imports user_api_key_cache from proxy_server + "litellm.proxy.proxy_server.user_api_key_cache", cache + ), + patch( # test-quality-ok: get_current_spend is lazily imported inside the budget check + "litellm.proxy.proxy_server.get_current_spend", read + ), ): return await common_checks( request_body={"model": "gpt-4o", "messages": []}, @@ -524,7 +532,9 @@ async def _common_checks_with_over_budget_group(*, skip_budget_checks: bool) -> llm_router=Router(model_list=MODEL_LIST), proxy_logging_obj=ProxyLogging(user_api_key_cache=cache), valid_token=UserAPIKeyAuth(api_key="hashed", models=["tier-a"], user_id=USER_ID), - request=SimpleNamespace(method="POST", headers={}, query_params={}, url=SimpleNamespace(path="/v1/chat/completions")), + request=SimpleNamespace( + method="POST", headers={}, query_params={}, url=SimpleNamespace(path="/v1/chat/completions") + ), skip_budget_checks=skip_budget_checks, ) diff --git a/tests/test_litellm/proxy/auth/test_resolvers_grants.py b/tests/test_litellm/proxy/auth/test_resolvers_grants.py new file mode 100644 index 00000000000..3f6d943bf98 --- /dev/null +++ b/tests/test_litellm/proxy/auth/test_resolvers_grants.py @@ -0,0 +1,201 @@ +from fastapi import HTTPException +import pytest + +from litellm.proxy._types import ( + LiteLLM_TeamMembership, + LiteLLM_TeamTableCachedObj, + LiteLLM_UserTable, + ProxyException, +) +from litellm.proxy.auth.auth_checks import TeamNotFoundError, UserNotFoundError +from litellm.proxy.auth.resolvers.grants import ( + GrantResolver, + LookupDegraded, + NotAMember, + ResolvedGrants, + TeamGone, + UserGone, + UserLookup, + raise_public, + user_models, +) + +USER_ID = "user-1" +TEAM_ID = "team-1" + + +class _Loaders: + """Fake row readers standing in for the ``auth_checks`` loaders, recording every call they receive.""" + + def __init__(self, *, user=None, team=None, membership=None, user_error=None, team_error=None): + self._user = user + self._team = team + self._membership = membership + self._user_error = user_error + self._team_error = team_error + self.user_calls = [] + self.team_calls = [] + self.membership_calls = [] + + async def load_user(self, **kwargs): + self.user_calls.append(kwargs) + if self._user_error is not None: + raise self._user_error + return self._user + + async def load_team(self, **kwargs): + self.team_calls.append(kwargs) + if self._team_error is not None: + raise self._team_error + return self._team + + async def load_membership(self, **kwargs): + self.membership_calls.append(kwargs) + return self._membership + + def resolver(self) -> GrantResolver: + return GrantResolver( + object(), + object(), + load_user=self.load_user, + load_team=self.load_team, + load_membership=self.load_membership, + ) + + +def _user(teams=(TEAM_ID,), user_id=USER_ID) -> LiteLLM_UserTable: + return LiteLLM_UserTable(user_id=user_id, user_role="internal_user", teams=list(teams), models=["gpt-5.5"]) + + +def _team(models=("gpt-5.5",)) -> LiteLLM_TeamTableCachedObj: + return LiteLLM_TeamTableCachedObj(team_id=TEAM_ID, team_alias="alias", models=list(models)) + + +async def test_resolve_returns_live_rows_for_a_member(): + membership = LiteLLM_TeamMembership(user_id=USER_ID, team_id=TEAM_ID, spend=1.5) + loaders = _Loaders(user=_user(), team=_team(models=("new-a", "new-b")), membership=membership) + + outcome = await loaders.resolver().resolve(UserLookup(user_id=USER_ID), team_id=TEAM_ID) + + assert outcome == ResolvedGrants( + user_object=_user(), + team_object=_team(models=("new-a", "new-b")), + team_membership=membership, + effective_user_id=USER_ID, + ) + assert loaders.team_calls[0]["team_id"] == TEAM_ID + assert loaders.membership_calls[0]["user_id"] == USER_ID + assert loaders.membership_calls[0]["team_id"] == TEAM_ID + + +async def test_resolve_denies_a_user_removed_from_the_team_without_reading_the_team(): + loaders = _Loaders(user=_user(teams=("other-team",)), team=_team()) + + outcome = await loaders.resolver().resolve(UserLookup(user_id=USER_ID), team_id=TEAM_ID) + + assert outcome == NotAMember(user_id=USER_ID, team_id=TEAM_ID) + assert loaders.team_calls == [] + + +async def test_resolve_reports_a_deleted_user(): + loaders = _Loaders(user_error=UserNotFoundError(user_id=USER_ID), team=_team()) + + outcome = await loaders.resolver().resolve(UserLookup(user_id=USER_ID), team_id=TEAM_ID) + + assert outcome == UserGone(user_id=USER_ID) + assert loaders.team_calls == [] + + +async def test_resolve_reports_a_deleted_team(): + loaders = _Loaders(user=_user(), team_error=TeamNotFoundError(team_id=TEAM_ID)) + + outcome = await loaders.resolver().resolve(UserLookup(user_id=USER_ID), team_id=TEAM_ID) + + assert outcome == TeamGone(team_id=TEAM_ID) + + +@pytest.mark.parametrize( + "loaders", + [ + _Loaders(user_error=Exception("No db connected")), + _Loaders(user=_user(), team_error=HTTPException(status_code=500, detail="db timeout")), + ], + ids=["user-read-failed", "team-read-failed"], +) +async def test_resolve_marks_an_unreadable_row_as_degraded_not_denied(loaders): + outcome = await loaders.resolver().resolve(UserLookup(user_id=USER_ID), team_id=TEAM_ID) + + assert isinstance(outcome, LookupDegraded) + + +async def test_resolve_without_a_team_skips_team_and_membership_reads(): + loaders = _Loaders(user=_user(teams=())) + + outcome = await loaders.resolver().resolve(UserLookup(user_id=USER_ID), team_id=None) + + assert outcome == ResolvedGrants( + user_object=_user(teams=()), team_object=None, team_membership=None, effective_user_id=USER_ID + ) + assert loaders.team_calls == [] + assert loaders.membership_calls == [] + + +async def test_resolve_identity_reads_membership_under_the_matched_rows_id(): + legacy_uuid = "bb8ab11f-09aa-47ae-b063-6e80506ac3bc" + loaders = _Loaders(user=_user(user_id=legacy_uuid)) + + user_object, _membership, effective_user_id = await loaders.resolver().resolve_identity( + UserLookup(user_id="matt@example.com", user_email="matt@example.com", sso_user_id="matt@example.com"), + team_id=TEAM_ID, + ) + + assert user_object is not None and user_object.user_id == legacy_uuid + assert effective_user_id == legacy_uuid + assert loaders.membership_calls[0]["user_id"] == legacy_uuid + assert loaders.user_calls[0]["user_email"] == "matt@example.com" + + +async def test_resolve_identity_without_a_user_id_reads_nothing(): + loaders = _Loaders(user=_user()) + + outcome = await loaders.resolver().resolve_identity(UserLookup(user_id=None), team_id=TEAM_ID) + + assert outcome == (None, None, None) + assert loaders.user_calls == [] + assert loaders.membership_calls == [] + + +async def test_resolve_identity_lets_loader_errors_surface(): + loaders = _Loaders(user_error=UserNotFoundError(user_id=USER_ID)) + + with pytest.raises(UserNotFoundError): + await loaders.resolver().resolve_identity(UserLookup(user_id=USER_ID), team_id=None) + + +def test_raise_public_maps_a_deleted_user_to_401(): + with pytest.raises(ProxyException) as exc_info: + raise_public(UserGone(user_id=USER_ID)) + assert exc_info.value.code == "401" + assert USER_ID in exc_info.value.message + + +def test_raise_public_maps_a_removed_member_to_403(): + with pytest.raises(HTTPException) as exc_info: + raise_public(NotAMember(user_id=USER_ID, team_id=TEAM_ID)) + assert exc_info.value.status_code == 403 + assert TEAM_ID in str(exc_info.value.detail) + + +def test_raise_public_maps_a_deleted_team_to_404(): + with pytest.raises(TeamNotFoundError) as exc_info: + raise_public(TeamGone(team_id=TEAM_ID)) + assert exc_info.value.status_code == 404 + + +@pytest.mark.parametrize( + ("stored", "expected"), + [(["gpt-5.5", "claude-opus-5"], ("gpt-5.5", "claude-opus-5")), ([], ()), ([{"not": "a model"}], ())], + ids=["models", "empty", "unusable-column"], +) +def test_user_models_reads_the_column_as_a_tuple_of_names(stored, expected): + assert user_models(LiteLLM_UserTable(user_id=USER_ID, models=stored)) == expected diff --git a/tests/test_litellm/proxy/auth/test_route_checks.py b/tests/test_litellm/proxy/auth/test_route_checks.py index c8b3d789665..0950b56bf03 100644 --- a/tests/test_litellm/proxy/auth/test_route_checks.py +++ b/tests/test_litellm/proxy/auth/test_route_checks.py @@ -1,5 +1,6 @@ import os from datetime import datetime +from typing import Final from unittest.mock import MagicMock, patch @@ -3919,10 +3920,15 @@ def test_claude_code_marketplace_routes_open_to_internal_users(route): @pytest.mark.parametrize("user_role", [None, LitellmUserRoles.INTERNAL_USER.value, LitellmUserRoles.INTERNAL_USER_VIEW_ONLY.value]) -def test_auto_router_session_is_reachable_by_any_key_but_benchmarks_stays_admin_only(user_role): - valid_token = UserAPIKeyAuth(api_key="hash-of-caller", user_role=user_role) - request = MagicMock(spec=Request) - request.query_params = {"session_id": "sess-1"} +@pytest.mark.parametrize("allowed_routes", [None, ["llm_api_routes"]]) +def test_auto_router_session_is_reachable_by_any_key_but_benchmarks_stays_admin_only( + user_role: str | None, allowed_routes: list[str] | None +) -> None: + valid_token: Final = UserAPIKeyAuth(api_key="hash-of-caller", user_role=user_role, allowed_routes=allowed_routes) + request: Final = Request({"type": "http", "method": "GET", "query_string": b"session_id=sess-1"}) + + assert RouteChecks.should_call_route("/auto_router/session", valid_token, request) is True + assert RouteChecks.is_llm_api_route("/auto_router/session") is False RouteChecks.non_proxy_admin_allowed_routes_check( user_obj=None, @@ -3941,3 +3947,36 @@ def test_auto_router_session_is_reachable_by_any_key_but_benchmarks_stays_admin_ valid_token=valid_token, request_data={}, ) + + +@pytest.mark.parametrize( + "route,method,allowed_routes", + [ + ("/auto_router/session", method, ["llm_api_routes"]) + for method in ("POST", "PUT", "PATCH", "DELETE", "HEAD", "OPTIONS", None) + ] + + [ + (route, "GET", ["llm_api_routes"]) + for route in ( + "/auto_router/benchmarks", + "/auto_router/test_routing", + "/auto_router/validate_complexity_router_config", + "/auto_router/session/other", + "/auto_router/sessions", + ) + ] + + [ + ("/auto_router/session", "GET", allowed_routes) + for allowed_routes in (["/v1/messages"], ["info_routes"], ["openai_routes"]) + ], +) +def test_auto_router_session_read_grant_rejects_other_methods_paths_and_scopes( + route: str, method: str | None, allowed_routes: list[str] +) -> None: + valid_token: Final = UserAPIKeyAuth(api_key="hash-of-caller", allowed_routes=allowed_routes) + request: Final = Request({"type": "http", "method": method}) if method is not None else None + + with pytest.raises(HTTPException) as error: + RouteChecks.should_call_route(route, valid_token, request) + + assert error.value.status_code == 403 diff --git a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py index 0cdbcde6abc..c9ae105d982 100644 --- a/tests/test_litellm/proxy/auth/test_user_api_key_auth.py +++ b/tests/test_litellm/proxy/auth/test_user_api_key_auth.py @@ -13,7 +13,7 @@ from unittest.mock import ANY, AsyncMock, MagicMock, patch import pytest -from fastapi import status +from fastapi import HTTPException, status import litellm import litellm.proxy.proxy_server @@ -32,7 +32,7 @@ from litellm.proxy._types import ( JWTRoutingOverride, ) from litellm.proxy.auth.handle_jwt import JWTHandler -from litellm.proxy.auth.auth_checks import get_key_object, _cache_key_object +from litellm.proxy.auth.auth_checks import TeamNotFoundError, UserNotFoundError, get_key_object, _cache_key_object from litellm.proxy.auth.route_checks import RouteChecks from litellm.proxy.auth.user_api_key_auth import ( _check_key_model_budget_with_fallback, @@ -6266,6 +6266,192 @@ async def test_non_admin_cli_session_token_reaches_production_auth_path(monkeypa assert result.is_session_token is True +SESSION_TEAM_ID = "team-abc" +SESSION_USER_ID = "member-1" + + +def _mint_session_token( + monkeypatch, + *, + role=LitellmUserRoles.INTERNAL_USER, + team_id=SESSION_TEAM_ID, + team_models=("stale-model",), + models=(), +): + """Mint a ``lite login`` token carrying the grants as they were at login time.""" + monkeypatch.delenv("EXPERIMENTAL_UI_LOGIN", raising=False) + monkeypatch.setenv("LITELLM_SALT_KEY", "sk-salt-cli-test") + from litellm.proxy.auth.auth_checks import ExperimentalUIJWTToken + + user_info = LiteLLM_UserTable( + user_id=SESSION_USER_ID, user_email="user@example.com", user_role=role.value, models=list(models) + ) + return ExperimentalUIJWTToken.get_cli_jwt_auth_token( + user_info, team_id=team_id, team_alias="stale-alias", team_models=list(team_models) + ) + + +def _session_user_row(*, teams=(SESSION_TEAM_ID,), role=LitellmUserRoles.INTERNAL_USER, models=()): + return LiteLLM_UserTable(user_id=SESSION_USER_ID, user_role=role.value, teams=list(teams), models=list(models)) + + +async def _authenticate_session_token_against_db( + cli_token, *, user_row=None, team_row=None, membership_row=None, user_error=None, team_error=None +): + """Drive the real builder for a session token with the DB row readers replaced by the given rows or + errors. Returns the ``_return_user_api_key_auth_obj`` mock so the caller can read the token it was + handed; a denial surfaces as the exception the builder raises.""" + import litellm.proxy.proxy_server as _proxy_server_mod + from fastapi import Request + from starlette.datastructures import URL + + attrs = _proxy_attrs_for_db_lookup() + attrs["prisma_client"].db.litellm_teammembership.find_first = AsyncMock(return_value=None) + originals = {a: getattr(_proxy_server_mod, a, None) for a in attrs} + assemble = AsyncMock(return_value=UserAPIKeyAuth(user_id=SESSION_USER_ID, is_session_token=True)) + try: + for k, v in attrs.items(): + setattr(_proxy_server_mod, k, v) + request = Request(scope={"type": "http"}) + request._url = URL(url="/chat/completions") + with ( + patch( # test-quality-ok: the builder has no injection seam for its assembler yet + "litellm.proxy.auth.user_api_key_auth._return_user_api_key_auth_obj", assemble + ), + patch( # test-quality-ok: the builder reads its DB row loaders off module globals + "litellm.proxy.auth.user_api_key_auth.get_user_object", + AsyncMock(return_value=user_row, side_effect=user_error), + ), + patch( # test-quality-ok: the builder reads its DB row loaders off module globals + "litellm.proxy.auth.user_api_key_auth.get_team_object", + AsyncMock(return_value=team_row, side_effect=team_error), + ), + patch( # test-quality-ok: the builder reads its DB row loaders off module globals + "litellm.proxy.auth.user_api_key_auth.get_team_membership", + AsyncMock(return_value=membership_row), + ), + ): + await _user_api_key_auth_builder( + request=request, + api_key=f"Bearer {cli_token}", + azure_api_key_header="", + anthropic_api_key_header=None, + google_ai_studio_api_key_header=None, + azure_apim_header=None, + request_data={}, + ) + finally: + for k, v in originals.items(): + setattr(_proxy_server_mod, k, v) + return assemble + + +@pytest.mark.asyncio +async def test_session_token_reads_team_grants_from_the_live_team_row(monkeypatch): + """LIT-7358: a lite login token snapshots the team's models at login, so adding a model to the team did + nothing for that CLI until the user logged in again. The team row has to be re-read on every request.""" + from litellm.models.team import LiteLLM_ModelTable + from litellm.proxy._types import LiteLLM_TeamMembership, LiteLLM_TeamTableCachedObj + + cli_token = _mint_session_token(monkeypatch, team_models=("stale-model",)) + live_team = LiteLLM_TeamTableCachedObj( + team_id=SESSION_TEAM_ID, + team_alias="renamed-team", + models=["gpt-5.5", "claude-opus-5"], + litellm_model_table=LiteLLM_ModelTable(model_aliases={"fast": "gpt-5.5"}, created_by="a", updated_by="a"), + ) + membership = LiteLLM_TeamMembership(user_id=SESSION_USER_ID, team_id=SESSION_TEAM_ID, spend=2.5) + + assemble = await _authenticate_session_token_against_db( + cli_token, user_row=_session_user_row(), team_row=live_team, membership_row=membership + ) + + token = assemble.call_args.kwargs["valid_token_dict"] + assert token["team_models"] == ["gpt-5.5", "claude-opus-5"] + assert token["team_alias"] == "renamed-team" + assert token["team_model_aliases"] == {"fast": "gpt-5.5"} + assert token["team_member_spend"] == 2.5 + assert token["is_session_token"] is True + + +@pytest.mark.asyncio +async def test_session_token_without_a_team_reads_models_from_the_live_user_row(monkeypatch): + cli_token = _mint_session_token(monkeypatch, team_id=None, team_models=(), models=("stale-model",)) + + assemble = await _authenticate_session_token_against_db( + cli_token, user_row=_session_user_row(teams=(), models=("gpt-5.5",)) + ) + + assert assemble.call_args.kwargs["valid_token_dict"]["models"] == ["gpt-5.5"] + + +@pytest.mark.asyncio +async def test_demoted_admin_session_token_loses_admin_on_the_next_request(monkeypatch): + """The role baked into the token used to send a former admin down the admin early return forever.""" + from litellm.proxy._types import LiteLLM_TeamTableCachedObj + + cli_token = _mint_session_token(monkeypatch, role=LitellmUserRoles.PROXY_ADMIN) + + assemble = await _authenticate_session_token_against_db( + cli_token, + user_row=_session_user_row(role=LitellmUserRoles.INTERNAL_USER), + team_row=LiteLLM_TeamTableCachedObj(team_id=SESSION_TEAM_ID, models=["gpt-5.5"]), + ) + + assemble.assert_awaited_once() + assert assemble.call_args.kwargs["valid_token_dict"]["user_role"] == LitellmUserRoles.INTERNAL_USER + + +@pytest.mark.asyncio +async def test_session_token_is_refused_once_the_user_leaves_the_team(monkeypatch): + cli_token = _mint_session_token(monkeypatch) + + with pytest.raises(ProxyException) as exc_info: + await _authenticate_session_token_against_db(cli_token, user_row=_session_user_row(teams=("other-team",))) + + assert exc_info.value.code == str(status.HTTP_403_FORBIDDEN) + assert SESSION_TEAM_ID in exc_info.value.message + + +@pytest.mark.asyncio +async def test_session_token_is_refused_once_the_user_is_deleted(monkeypatch): + cli_token = _mint_session_token(monkeypatch) + + with pytest.raises(ProxyException) as exc_info: + await _authenticate_session_token_against_db(cli_token, user_error=UserNotFoundError(user_id=SESSION_USER_ID)) + + assert exc_info.value.code == str(status.HTTP_401_UNAUTHORIZED) + assert exc_info.value.type == ProxyErrorTypes.auth_error + + +@pytest.mark.asyncio +async def test_session_token_is_refused_once_the_team_is_deleted(monkeypatch): + cli_token = _mint_session_token(monkeypatch) + + with pytest.raises(ProxyException) as exc_info: + await _authenticate_session_token_against_db( + cli_token, user_row=_session_user_row(), team_error=TeamNotFoundError(team_id=SESSION_TEAM_ID) + ) + + assert exc_info.value.code == str(status.HTTP_404_NOT_FOUND) + + +@pytest.mark.asyncio +async def test_session_token_keeps_minted_grants_when_the_team_row_cannot_be_read(monkeypatch): + """A DB hiccup says nothing about the caller, so the grants minted at login stand for that request.""" + from fastapi import HTTPException + + cli_token = _mint_session_token(monkeypatch, team_models=("stale-model",)) + + assemble = await _authenticate_session_token_against_db( + cli_token, user_row=_session_user_row(), team_error=HTTPException(status_code=500, detail="db timeout") + ) + + token = assemble.call_args.kwargs["valid_token_dict"] + assert token["team_models"] == ["stale-model"] + assert token["team_alias"] == "stale-alias" + + @pytest.mark.asyncio async def test_cli_session_token_authenticates_when_jwt_auth_enabled_without_license(monkeypatch): """A lite login token is an encrypted (non-JWT) session blob. With @@ -7442,3 +7628,226 @@ async def test_claude_view_never_reinterprets_explicit_names(monkeypatch, layer) assert data["model"] == ("foo" if layer == "unclaimed" else encoded) await _normalize_claude_model(data, token, request, "/v1/messages") assert data["model"] == ("foo" if layer == "unclaimed" else encoded) + + +ISSUER_ONE = "https://issuer-one.example.com" +ISSUER_TWO = "https://issuer-two.example.com" + + +def _per_issuer_virtual_key_jwt_handler( + global_claim_field: str | None, global_behavior: str = "fallback_team_mapping" +) -> MagicMock: + jwt_handler = MagicMock() + jwt_handler.is_jwt.return_value = True + jwt_handler.litellm_jwtauth = LiteLLM_JWTAuth( + virtual_key_claim_field=global_claim_field, + unregistered_jwt_client_behavior=global_behavior, + issuers=[ + { + "issuer": ISSUER_ONE, + "jwks_url": f"{ISSUER_ONE}/keys", + "audience": "audience-one", + "team_id_jwt_field": "sub", + }, + { + "issuer": ISSUER_TWO, + "jwks_url": f"{ISSUER_TWO}/keys", + "audience": "audience-two", + "virtual_key_claim_field": "sub", + "unregistered_jwt_client_behavior": "reject", + }, + ], + ) + return jwt_handler + + +def _fake_prisma_with_jwt_key_mapping(hashed_token: str | None) -> tuple[SimpleNamespace, AsyncMock]: + find_first = AsyncMock(return_value=None if hashed_token is None else SimpleNamespace(token=hashed_token)) + prisma_client = SimpleNamespace(db=SimpleNamespace(litellm_jwtkeymapping=SimpleNamespace(find_first=find_first))) + return prisma_client, find_first + + +def _mapping_where(claim_name: str, claim_value: str) -> dict[str, str | bool]: + return {"jwt_claim_name": claim_name, "jwt_claim_value": claim_value, "is_active": True} + + +@pytest.mark.asyncio +async def test_per_issuer_virtual_key_claim_field_selects_the_issuer_mapping_for_the_db_lookup(): + from litellm.proxy.auth.user_api_key_auth import _resolve_jwt_to_virtual_key + + jwt_handler = _per_issuer_virtual_key_jwt_handler(global_claim_field=None) + prisma_client, find_first = _fake_prisma_with_jwt_key_mapping("hashed-mapped-key") + user_api_key_cache = DualCache() + await user_api_key_cache.async_set_cache( + key="hashed-mapped-key", + value=UserAPIKeyAuth(token="hashed-mapped-key", api_key="hashed-mapped-key", team_id="svc-team"), + ) + + resolved = await _resolve_jwt_to_virtual_key( + jwt_claims={JWTHandler.LITELLM_JWT_ISSUER_CLAIM: ISSUER_TWO, "sub": "svc-account-7"}, + jwt_handler=jwt_handler, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=None, + proxy_logging_obj=MagicMock(), + ) + + find_first.assert_awaited_once_with(where=_mapping_where("sub", "svc-account-7")) + assert isinstance(resolved, UserAPIKeyAuth) + assert resolved.token == "hashed-mapped-key" + assert resolved.team_id == "svc-team" + assert await user_api_key_cache.async_get_cache("jwt_key_mapping:sub:svc-account-7") == "hashed-mapped-key" + + +@pytest.mark.asyncio +async def test_per_issuer_reject_behavior_does_not_leak_into_the_team_issuer(): + from litellm.proxy.auth.user_api_key_auth import _resolve_jwt_to_virtual_key + + jwt_handler = _per_issuer_virtual_key_jwt_handler(global_claim_field=None) + prisma_client, find_first = _fake_prisma_with_jwt_key_mapping(None) + + team_issuer_result = await _resolve_jwt_to_virtual_key( + jwt_claims={JWTHandler.LITELLM_JWT_ISSUER_CLAIM: ISSUER_ONE, "sub": "team-alpha"}, + jwt_handler=jwt_handler, + prisma_client=prisma_client, + user_api_key_cache=DualCache(), + parent_otel_span=None, + proxy_logging_obj=MagicMock(), + ) + assert team_issuer_result is None + find_first.assert_not_awaited() + + with pytest.raises(HTTPException) as exc: + await _resolve_jwt_to_virtual_key( + jwt_claims={JWTHandler.LITELLM_JWT_ISSUER_CLAIM: ISSUER_TWO, "sub": "unknown-svc"}, + jwt_handler=jwt_handler, + prisma_client=prisma_client, + user_api_key_cache=DualCache(), + parent_otel_span=None, + proxy_logging_obj=MagicMock(), + ) + + assert exc.value.status_code == 403 + assert "No registered mapping for sub='unknown-svc'" in str(exc.value.detail) + find_first.assert_awaited_once_with(where=_mapping_where("sub", "unknown-svc")) + + +@pytest.mark.asyncio +async def test_proxy_admin_sentinel_cached_by_another_issuer_does_not_bypass_reject(): + from litellm.proxy.auth.user_api_key_auth import _JWT_PROXY_ADMIN_SENTINEL, _resolve_jwt_to_virtual_key + + jwt_handler = _per_issuer_virtual_key_jwt_handler(global_claim_field="sub", global_behavior="auto_register") + prisma_client, find_first = _fake_prisma_with_jwt_key_mapping(None) + user_api_key_cache = DualCache() + await user_api_key_cache.async_set_cache(key="jwt_key_mapping:sub:admin-7", value=_JWT_PROXY_ADMIN_SENTINEL) + + auto_register_issuer_result = await _resolve_jwt_to_virtual_key( + jwt_claims={JWTHandler.LITELLM_JWT_ISSUER_CLAIM: ISSUER_ONE, "sub": "admin-7"}, + jwt_handler=jwt_handler, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=None, + proxy_logging_obj=MagicMock(), + ) + assert auto_register_issuer_result is None + find_first.assert_not_awaited() + + with pytest.raises(HTTPException) as exc: + await _resolve_jwt_to_virtual_key( + jwt_claims={JWTHandler.LITELLM_JWT_ISSUER_CLAIM: ISSUER_TWO, "sub": "admin-7"}, + jwt_handler=jwt_handler, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=None, + proxy_logging_obj=MagicMock(), + ) + + assert exc.value.status_code == 403 + assert "No registered mapping for sub='admin-7'" in str(exc.value.detail) + find_first.assert_awaited_once_with(where=_mapping_where("sub", "admin-7")) + + +@pytest.mark.asyncio +async def test_issuer_without_virtual_key_claim_field_falls_back_to_the_global_field(): + from litellm.proxy.auth.user_api_key_auth import _resolve_jwt_to_virtual_key + + jwt_handler = _per_issuer_virtual_key_jwt_handler(global_claim_field="client_id") + prisma_client, find_first = _fake_prisma_with_jwt_key_mapping(None) + + with_claim = await _resolve_jwt_to_virtual_key( + jwt_claims={JWTHandler.LITELLM_JWT_ISSUER_CLAIM: ISSUER_ONE, "sub": "team-alpha", "client_id": "app-9"}, + jwt_handler=jwt_handler, + prisma_client=prisma_client, + user_api_key_cache=DualCache(), + parent_otel_span=None, + proxy_logging_obj=MagicMock(), + ) + without_claim = await _resolve_jwt_to_virtual_key( + jwt_claims={JWTHandler.LITELLM_JWT_ISSUER_CLAIM: ISSUER_ONE, "sub": "team-alpha"}, + jwt_handler=jwt_handler, + prisma_client=prisma_client, + user_api_key_cache=DualCache(), + parent_otel_span=None, + proxy_logging_obj=MagicMock(), + ) + + assert with_claim is None + assert without_claim is None + find_first.assert_awaited_once_with(where=_mapping_where("client_id", "app-9")) + + +@pytest.mark.asyncio +async def test_auth_flow_enters_virtual_key_mapping_when_only_an_issuer_configures_the_claim_field(): + jwt_token = "eyJhbGciOiJSUzI1NiJ9.eyJzdWIiOiJzdmMtYWNjb3VudC03In0.signature" + jwt_handler = _per_issuer_virtual_key_jwt_handler(global_claim_field=None) + jwt_handler.auth_jwt = AsyncMock( + return_value={JWTHandler.LITELLM_JWT_ISSUER_CLAIM: ISSUER_TWO, "sub": "svc-account-7"} + ) + mapped_key = UserAPIKeyAuth(token="hashed-mapped-key", api_key="hashed-mapped-key", team_id="svc-team") + + mock_request = MagicMock() + mock_request.url.path = "/v1/chat/completions" + mock_request.method = "POST" + mock_request.headers = {"authorization": f"Bearer {jwt_token}"} + mock_request.query_params = {} + mock_request.state = SimpleNamespace() + + with ( + patch( # test-quality-ok: the builder reads proxy settings from module globals, no injection seam + "litellm.proxy.proxy_server.general_settings", {"enable_jwt_auth": True} + ), + patch("litellm.proxy.proxy_server.premium_user", True), # test-quality-ok: module-global proxy state + patch("litellm.proxy.proxy_server.master_key", "sk-master"), # test-quality-ok: module-global proxy state + patch("litellm.proxy.proxy_server.prisma_client", MagicMock()), # test-quality-ok: module-global proxy state + patch( # test-quality-ok: module-global proxy state + "litellm.proxy.proxy_server.user_api_key_cache", DualCache() + ), + patch( # test-quality-ok: module-global proxy state + "litellm.proxy.proxy_server.proxy_logging_obj", MagicMock() + ), + patch("litellm.proxy.proxy_server.jwt_handler", jwt_handler), # test-quality-ok: module-global proxy state + patch( # test-quality-ok: the regression is whether the builder reaches this seam at all + "litellm.proxy.auth.user_api_key_auth._resolve_jwt_to_virtual_key", + new_callable=AsyncMock, + return_value=mapped_key, + ) as resolve_mock, + patch( # test-quality-ok: a mapped key must short-circuit standard JWT auth; reaching it is the failure + "litellm.proxy.auth.user_api_key_auth.JWTAuthManager.auth_builder", + new_callable=AsyncMock, + side_effect=AssertionError("standard JWT auth must not run for a mapped virtual key"), + ), + ): + result = await _user_api_key_auth_builder( + request=mock_request, + api_key=jwt_token, + azure_api_key_header="", + anthropic_api_key_header=None, + google_ai_studio_api_key_header=None, + azure_apim_header=None, + request_data={"model": "gpt-4o-mini"}, + ) + + resolve_mock.assert_awaited_once() + assert resolve_mock.await_args.kwargs["jwt_claims"][JWTHandler.LITELLM_JWT_ISSUER_CLAIM] == ISSUER_TWO + assert result.api_key == "hashed-mapped-key" + assert result.team_id == "svc-team" diff --git a/tests/test_litellm/proxy/client/cli/test_pi.py b/tests/test_litellm/proxy/client/cli/test_pi.py index 03e5d7dd197..6bb49566580 100644 --- a/tests/test_litellm/proxy/client/cli/test_pi.py +++ b/tests/test_litellm/proxy/client/cli/test_pi.py @@ -20,6 +20,13 @@ from litellm.proxy.client.cli.commands.pi import ( ) +def test_listing_failure_is_str_enum(): + assert issubclass(ListingFailure, str) + assert ListingFailure.REJECTED.value == "rejected" + assert ListingFailure("rejected") is ListingFailure.REJECTED + assert str(ListingFailure.REJECTED.value) == "rejected" + + class _FakeResponse: def __init__(self, status_code, payload=None): self.status_code = status_code diff --git a/tests/test_litellm/proxy/client/cli/test_statusline_script.py b/tests/test_litellm/proxy/client/cli/test_statusline_script.py index 691764fbef4..39d0e24d7b0 100644 --- a/tests/test_litellm/proxy/client/cli/test_statusline_script.py +++ b/tests/test_litellm/proxy/client/cli/test_statusline_script.py @@ -8,6 +8,7 @@ import re import subprocess import sys from pathlib import Path +from typing import Final import pytest @@ -251,11 +252,52 @@ class TestRender: def test_savings_header_and_bars_against_the_routers_baseline(self, config_dir): text = render("claude-sonnet-5", RECORDED, config_dir, use_color=False, bar_width=10) assert text.splitlines() == [ - "claude-auto · Routed to: claude-sonnet-5 -63% vs Claude Opus 5", - "LiteLLM ████░░░░░░ $0.14", + "Routed to: claude-sonnet-5 -63% vs Claude Opus 5", + "claude-auto ████░░░░░░ $0.14", "Claude Opus 5 ██████████ $0.38", ] + def test_a_long_router_name_keeps_both_cost_bars_aligned(self, config_dir: Path) -> None: + session: Final = RECORDED._replace(router_name="engineering-smart-router") + text: Final = render("claude-sonnet-5", session, config_dir, use_color=False, bar_width=10) + assert text.splitlines()[1:] == [ + "engineering-smart-router ████░░░░░░ $0.14", + "Claude Opus 5 ██████████ $0.38", + ] + + @pytest.mark.parametrize( + ("router_name", "baseline_name", "router_padding", "baseline_padding"), + ( + ("路由-router", "Claude Opus 5", 3, 1), + ("智能模型路由器", "Claude Opus 5", 1, 2), + ("ＡＢＣ-router", "Claude Opus 5", 1, 1), + ("cafe\u0301-router", "Claude Opus 5", 3, 1), + ("a\u20dd-router", "Claude Opus 5", 6, 1), + ("カ\u3099-router", "Claude Opus 5", 5, 1), + ("auto", "基準モデル", 7, 1), + ("auto", "cafe\u0301", 1, 1), + ), + ) + @pytest.mark.parametrize("use_color", (False, True)) + def test_unicode_labels_align_cost_bars_by_terminal_columns( + self, + config_dir: Path, + router_name: str, + baseline_name: str, + router_padding: int, + baseline_padding: int, + use_color: bool, + ) -> None: + (config_dir / "cache" / "gateway-models.json").write_text( + json.dumps({"models": [{"id": "claude-opus-5", "display_name": baseline_name}]}) + ) + session: Final = RECORDED._replace(router_name=router_name) + text: Final = ANSI.sub("", render("claude-sonnet-5", session, config_dir, use_color, bar_width=10)) + assert text.splitlines()[1:] == [ + f"{router_name}{' ' * router_padding}████░░░░░░ $0.14", + f"{baseline_name}{' ' * baseline_padding}██████████ $0.38", + ] + def test_control_characters_in_any_externally_sourced_label_never_reach_the_terminal(self, tmp_path, config_dir): # The transcript, the proxy payload and Claude Code's model cache all feed labels straight into a # terminal, and none is under this script's control. Only the control bytes are dropped (ESC, BEL, @@ -288,7 +330,7 @@ class TestRender: assert "+25% vs Claude Opus 5" in render("m", dearer, config_dir, use_color=False) def test_without_a_baseline_only_the_routed_line_shows(self, config_dir): - assert render("m", RECORDED._replace(baseline_model=None), config_dir, False) == "claude-auto · Routed to: m" + assert render("m", RECORDED._replace(baseline_model=None), config_dir, False) == "Routed to: m" assert render("m", None, config_dir, False) == "Routed to: m" def test_color_wraps_the_same_text(self, config_dir): @@ -297,16 +339,32 @@ class TestRender: class TestClaudeCodeMode: - def test_the_transcript_names_the_routed_model_and_the_proxy_adds_the_savings(self, tmp_path, transcript, config_dir): - seen = [] + @pytest.mark.parametrize("transcript_model", ("claude-auto", "anthropic/claude-opus-5")) + def test_the_session_names_the_routed_model_even_when_the_transcript_differs( + self, tmp_path: Path, config_dir: Path, transcript_model: str + ) -> None: + transcript: Final = tmp_path / "session.jsonl" + transcript.write_text(_assistant_line(transcript_model) + "\n") - def fetch(credentials, session_id): - seen.append((credentials, session_id)) + def fetch(credentials: Credentials, session_id: str) -> Fetched: + assert credentials == Credentials("http://127.0.0.1:4000", "sk-virtual") + assert session_id == SESSION_ID return Fetched(RECORDED, definitive=True) - text = _run(_payload(transcript), _env(tmp_path, config_dir), fetch) - assert text.startswith("claude-auto · Routed to: claude-sonnet-5 -63% vs Claude Opus 5\n") - assert seen == [(Credentials("http://127.0.0.1:4000", "sk-virtual"), SESSION_ID)] + text: Final = _run(_payload(transcript), _env(tmp_path, config_dir), fetch) + assert text.startswith("Routed to: claude-sonnet-5 -63% vs Claude Opus 5\n") + assert text.splitlines()[1].startswith("claude-auto ") + + def test_a_discovered_display_name_labels_the_sessions_model( + self, tmp_path: Path, transcript: Path, config_dir: Path + ) -> None: + session: Final = RECORDED._replace(last_model="anthropic/claude-opus-5") + + def fetch(credentials: Credentials, session_id: str) -> Fetched: + return Fetched(session, definitive=True) + + text: Final = _run(_payload(transcript), _env(tmp_path, config_dir), fetch) + assert text.startswith("Routed to: Claude Opus 5 -63% vs Claude Opus 5\n") def test_an_unrecorded_session_degrades_to_the_routed_line(self, tmp_path, transcript, config_dir): assert _run(_payload(transcript), _env(tmp_path, config_dir), lambda c, s: Fetched(None, True)) == ( @@ -362,7 +420,8 @@ class TestCodexMode: out = _run({"hook_event_name": "Stop", "session_id": SESSION_ID, "transcript_path": "/nope"}, env, fetch) message = json.loads(out)["systemMessage"] - assert message.splitlines()[1] == "claude-auto · Routed to: claude-sonnet-5 -63% vs Claude Opus 5" + assert message.splitlines()[1] == "Routed to: claude-sonnet-5 -63% vs Claude Opus 5" + assert message.splitlines()[2].startswith("claude-auto ") assert message.startswith("\n") assert seen == [Credentials("http://127.0.0.1:4000", "sk-codex")] diff --git a/tests/test_litellm/proxy/common_utils/test_load_config_utils.py b/tests/test_litellm/proxy/common_utils/test_load_config_utils.py index 524c260e94a..1042dbe9653 100644 --- a/tests/test_litellm/proxy/common_utils/test_load_config_utils.py +++ b/tests/test_litellm/proxy/common_utils/test_load_config_utils.py @@ -1,9 +1,18 @@ +import asyncio +import logging +import re +import threading from unittest.mock import MagicMock, mock_open, patch import pytest import yaml -from litellm.proxy.common_utils.load_config_utils import get_file_contents_from_s3 +from litellm.proxy.common_utils.load_config_utils import ( + gcs_config_bucket, + get_config_from_bucket, + get_file_contents_from_s3, + resolve_bucket_includes, +) class TestGetFileContentsFromS3: @@ -83,3 +92,385 @@ class TestGetFileContentsFromS3: # Verify yaml.safe_load was called with the decoded content mock_yaml_load.assert_called_once_with(yaml_content) + + +class TestBucketConfigIncludes: + + @staticmethod + def _bucket(objects): + async def fetch(object_key): + return objects.get(object_key) + + return fetch + + @pytest.mark.asyncio + async def test_include_resolves_against_the_config_objects_prefix(self): + merged = await resolve_bucket_includes( + config={"include": ["model_config.yaml"], "general_settings": {"master_key": "sk-1234"}}, + object_key="configs/prod/config.yaml", + fetch=self._bucket( + {"configs/prod/model_config.yaml": {"model_list": [{"model_name": "gpt-4o-mini"}]}} + ), + ) + + assert merged == { + "general_settings": {"master_key": "sk-1234"}, + "model_list": [{"model_name": "gpt-4o-mini"}], + } + + @pytest.mark.asyncio + async def test_include_with_a_leading_slash_reads_from_the_bucket_root(self): + merged = await resolve_bucket_includes( + config={"include": ["/shared/models.yaml"]}, + object_key="configs/prod/config.yaml", + fetch=self._bucket({"shared/models.yaml": {"model_list": [{"model_name": "shared"}]}}), + ) + + assert merged == {"model_list": [{"model_name": "shared"}]} + + @pytest.mark.asyncio + async def test_include_walks_out_of_the_prefix_with_dot_dot(self): + merged = await resolve_bucket_includes( + config={"include": ["../shared/models.yaml"]}, + object_key="configs/prod/config.yaml", + fetch=self._bucket({"configs/shared/models.yaml": {"model_list": [{"model_name": "shared"}]}}), + ) + + assert merged == {"model_list": [{"model_name": "shared"}]} + + @pytest.mark.asyncio + async def test_included_configs_may_declare_further_includes(self): + merged = await resolve_bucket_includes( + config={"include": ["models.yaml"]}, + object_key="configs/config.yaml", + fetch=self._bucket( + { + "configs/models.yaml": { + "include": ["extra/more_models.yaml"], + "model_list": [{"model_name": "first"}], + }, + "configs/extra/more_models.yaml": {"model_list": [{"model_name": "second"}]}, + } + ), + ) + + assert merged == {"model_list": [{"model_name": "first"}, {"model_name": "second"}]} + + @pytest.mark.asyncio + async def test_a_nested_include_resolves_against_the_object_that_declares_it(self): + merged = await resolve_bucket_includes( + config={"include": ["shared/models.yaml"]}, + object_key="configs/config.yaml", + fetch=self._bucket( + { + "configs/shared/models.yaml": { + "include": ["more_models.yaml"], + "model_list": [{"model_name": "first"}], + }, + "configs/shared/more_models.yaml": {"model_list": [{"model_name": "second"}]}, + "configs/more_models.yaml": {"model_list": [{"model_name": "wrong-prefix"}]}, + } + ), + ) + + assert merged == {"model_list": [{"model_name": "first"}, {"model_name": "second"}]} + + @pytest.mark.asyncio + async def test_an_object_pulled_in_twice_is_merged_once(self): + merged = await resolve_bucket_includes( + config={"include": ["a.yaml", "b.yaml"]}, + object_key="configs/config.yaml", + fetch=self._bucket( + { + "configs/a.yaml": {"include": ["shared.yaml"]}, + "configs/b.yaml": {"include": ["./shared.yaml"]}, + "configs/shared.yaml": {"model_list": [{"model_name": "shared"}]}, + } + ), + ) + + assert merged == {"model_list": [{"model_name": "shared"}]} + + @pytest.mark.asyncio + async def test_a_cycle_between_included_objects_terminates(self): + merged = await asyncio.wait_for( + resolve_bucket_includes( + config={"include": ["a.yaml"]}, + object_key="configs/config.yaml", + fetch=self._bucket( + { + "configs/a.yaml": {"include": ["b.yaml"], "model_list": [{"model_name": "from-a"}]}, + "configs/b.yaml": {"include": ["a.yaml"], "model_list": [{"model_name": "from-b"}]}, + } + ), + ), + timeout=10, + ) + + assert merged == {"model_list": [{"model_name": "from-a"}, {"model_name": "from-b"}]} + + @pytest.mark.asyncio + async def test_list_values_are_extended_and_other_values_are_overridden(self): + merged = await resolve_bucket_includes( + config={ + "include": ["models.yaml"], + "model_list": [{"model_name": "from-root"}], + "litellm_settings": {"drop_params": True}, + }, + object_key="config.yaml", + fetch=self._bucket( + { + "models.yaml": { + "model_list": [{"model_name": "from-include"}], + "litellm_settings": {"num_retries": 3}, + } + } + ), + ) + + assert merged == { + "model_list": [{"model_name": "from-root"}, {"model_name": "from-include"}], + "litellm_settings": {"num_retries": 3}, + } + + @pytest.mark.asyncio + async def test_a_missing_included_object_fails_loudly_with_its_key(self): + with pytest.raises(FileNotFoundError, match=re.escape("configs/prod/model_config.yaml")): + await resolve_bucket_includes( + config={"include": ["model_config.yaml"]}, + object_key="configs/prod/config.yaml", + fetch=self._bucket({}), + ) + + @pytest.mark.asyncio + async def test_a_non_list_include_fails_loudly(self): + with pytest.raises(ValueError, match="'include' must be a list of file paths"): + await resolve_bucket_includes( + config={"include": "model_config.yaml"}, + object_key="config.yaml", + fetch=self._bucket({}), + ) + + @pytest.mark.asyncio + async def test_get_config_from_bucket_merges_includes_over_s3(self, monkeypatch): + objects = { + "lit6982/config.yaml": { + "include": ["model_config.yaml"], + "general_settings": {"master_key": "sk-1234"}, + }, + "lit6982/model_config.yaml": {"model_list": [{"model_name": "included-model"}]}, + } + monkeypatch.setattr( + "litellm.proxy.common_utils.load_config_utils.s3_object_reader", + lambda bucket_name: objects.get, + ) + + config = await get_config_from_bucket( + bucket_type="s3", bucket_name="litellm-configs", object_key="lit6982/config.yaml" + ) + + assert config == { + "general_settings": {"master_key": "sk-1234"}, + "model_list": [{"model_name": "included-model"}], + } + + @pytest.mark.asyncio + async def test_the_blocking_s3_work_runs_off_the_event_loop_thread(self, monkeypatch): + loop_thread = threading.current_thread() + threads = [] + + def build_reader(bucket_name): + threads.append(threading.current_thread()) + + def read(object_key): + threads.append(threading.current_thread()) + return {"model_list": [{"model_name": "a-model"}]} + + return read + + monkeypatch.setattr("litellm.proxy.common_utils.load_config_utils.s3_object_reader", build_reader) + + await get_config_from_bucket(bucket_type="s3", bucket_name="litellm-configs", object_key="config.yaml") + + assert len(threads) == 2 and loop_thread not in threads + + @pytest.mark.asyncio + async def test_one_s3_client_serves_the_whole_include_tree(self, monkeypatch): + objects = { + "lit6982/config.yaml": {"include": ["model_config.yaml"]}, + "lit6982/model_config.yaml": {"model_list": [{"model_name": "included-model"}]}, + } + readers = [] + + def build_reader(bucket_name): + requested = [] + readers.append(requested) + + def read(object_key): + requested.append(object_key) + return objects.get(object_key) + + return read + + monkeypatch.setattr("litellm.proxy.common_utils.load_config_utils.s3_object_reader", build_reader) + + await get_config_from_bucket( + bucket_type="s3", bucket_name="litellm-configs", object_key="lit6982/config.yaml" + ) + + assert readers == [["lit6982/config.yaml", "lit6982/model_config.yaml"]] + + @pytest.mark.asyncio + async def test_an_empty_included_object_merges_as_an_empty_config(self, monkeypatch): + objects = { + "lit6982/config.yaml": "include:\n - empty.yaml\nmodel_list:\n - model_name: only-model\n", + "lit6982/empty.yaml": "", + } + + class FakeGCSBucket: + async def download_gcs_object(self, object_key): + return objects[object_key].encode("utf-8") + + monkeypatch.setattr( + "litellm.proxy.common_utils.load_config_utils.gcs_config_bucket", + lambda bucket_name: FakeGCSBucket(), + ) + + config = await get_config_from_bucket( + bucket_type="gcs", bucket_name="litellm-configs", object_key="lit6982/config.yaml" + ) + + assert config == {"model_list": [{"model_name": "only-model"}]} + + @pytest.mark.asyncio + async def test_get_config_from_bucket_merges_includes_over_gcs(self, monkeypatch): + objects = { + "lit6982/config.yaml": { + "include": ["model_config.yaml"], + "general_settings": {"master_key": "sk-1234"}, + }, + "lit6982/model_config.yaml": {"model_list": [{"model_name": "included-model"}]}, + } + + buckets = [] + + class FakeGCSBucket: + def __init__(self): + self.requested = [] + buckets.append(self) + + async def download_gcs_object(self, object_key): + self.requested.append(object_key) + return yaml.dump(objects[object_key]).encode("utf-8") + + monkeypatch.setattr( + "litellm.proxy.common_utils.load_config_utils.gcs_config_bucket", + lambda bucket_name: FakeGCSBucket(), + ) + + config = await get_config_from_bucket( + bucket_type="gcs", bucket_name="litellm-configs", object_key="lit6982/config.yaml" + ) + + assert config == { + "general_settings": {"master_key": "sk-1234"}, + "model_list": [{"model_name": "included-model"}], + } + assert [bucket.requested for bucket in buckets] == [ + ["lit6982/config.yaml", "lit6982/model_config.yaml"] + ] + + @pytest.mark.asyncio + async def test_get_config_from_bucket_returns_none_when_the_root_object_is_missing(self, monkeypatch): + monkeypatch.setattr( + "litellm.proxy.common_utils.load_config_utils.s3_object_reader", + lambda bucket_name: (lambda object_key: None), + ) + + assert ( + await get_config_from_bucket( + bucket_type="s3", bucket_name="litellm-configs", object_key="missing.yaml" + ) + is None + ) + + @pytest.mark.asyncio + async def test_an_object_pulled_in_twice_is_read_once(self): + objects = { + "configs/a.yaml": {"include": ["shared.yaml"]}, + "configs/b.yaml": {"include": ["./shared.yaml"]}, + "configs/shared.yaml": {"model_list": [{"model_name": "shared"}]}, + } + requested = [] + + async def fetch(object_key): + requested.append(object_key) + return objects.get(object_key) + + await resolve_bucket_includes( + config={"include": ["a.yaml", "b.yaml"]}, + object_key="configs/config.yaml", + fetch=fetch, + ) + + assert requested == ["configs/a.yaml", "configs/b.yaml", "configs/shared.yaml"] + + @pytest.mark.asyncio + async def test_an_empty_root_object_does_not_boot_an_empty_proxy(self, monkeypatch): + class FakeGCSBucket: + async def download_gcs_object(self, object_key): + return b"" + + monkeypatch.setattr( + "litellm.proxy.common_utils.load_config_utils.gcs_config_bucket", + lambda bucket_name: FakeGCSBucket(), + ) + + config = await get_config_from_bucket( + bucket_type="gcs", bucket_name="litellm-configs", object_key="lit6982/config.yaml" + ) + + assert config is None + + @pytest.mark.asyncio + async def test_an_object_that_is_not_valid_yaml_is_reported_as_a_yaml_error(self, monkeypatch, caplog): + class FakeGCSBucket: + async def download_gcs_object(self, object_key): + return b"model_list: [\n" + + monkeypatch.setattr( + "litellm.proxy.common_utils.load_config_utils.gcs_config_bucket", + lambda bucket_name: FakeGCSBucket(), + ) + + with caplog.at_level(logging.ERROR, logger="LiteLLM Proxy"): + config = await get_config_from_bucket( + bucket_type="gcs", bucket_name="litellm-configs", object_key="lit6982/config.yaml" + ) + + assert config is None + assert [ + record + for record in caplog.records + if "not valid YAML" in record.getMessage() and "lit6982/config.yaml" in record.getMessage() + ] + + +class TestGCSConfigBucketClient: + @pytest.mark.asyncio + async def test_reading_a_config_from_gcs_does_not_need_an_enterprise_license(self, monkeypatch): + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", False) + + bucket = gcs_config_bucket("litellm-configs") + + assert bucket is not None + assert bucket.BUCKET_NAME == "litellm-configs" + + @pytest.mark.asyncio + async def test_reading_a_config_from_gcs_starts_no_background_task(self, monkeypatch): + monkeypatch.setattr("litellm.proxy.proxy_server.premium_user", True) + running_before = asyncio.all_tasks() + + gcs_config_bucket("litellm-configs") + + assert asyncio.all_tasks() - running_before == set() diff --git a/tests/test_litellm/proxy/common_utils/test_openai_error_payload.py b/tests/test_litellm/proxy/common_utils/test_openai_error_payload.py index 8b653ddfb71..90850840ab4 100644 --- a/tests/test_litellm/proxy/common_utils/test_openai_error_payload.py +++ b/tests/test_litellm/proxy/common_utils/test_openai_error_payload.py @@ -143,3 +143,18 @@ def test_a_status_carried_by_an_exception_drives_the_type_it_reports(): exc = HTTPException(status_code=403, detail="blocked by policy") assert openai_error_type(exc, error_status_code(exc, 400)) == "permission_error" + + +def test_a_stringified_none_type_or_param_is_treated_as_absent(): + from litellm.exceptions import BadRequestError + + carried = BadRequestError( + message="Content blocked", + model="claude-haiku-4-5", + llm_provider="litellm_proxy", + body={"message": "Content blocked", "type": "None", "param": "None", "code": "400"}, + ) + + assert carried.type == "None" + assert openai_error_type(carried, 400) == "invalid_request_error" + assert openai_error_param(carried) is None diff --git a/tests/test_litellm/proxy/common_utils/test_prompt_cache_pricing.py b/tests/test_litellm/proxy/common_utils/test_prompt_cache_pricing.py new file mode 100644 index 00000000000..994684a6005 --- /dev/null +++ b/tests/test_litellm/proxy/common_utils/test_prompt_cache_pricing.py @@ -0,0 +1,105 @@ +from typing import Final + +import pytest + +import litellm +from litellm.proxy.common_utils.prompt_cache_pricing import price_cache_tokens +from litellm.types.management_endpoints.prompt_cache_prediction import CacheTokenBuckets + + +@pytest.mark.parametrize( + ("model", "expected"), + [("anthropic/claude-sonnet-4-5", 1.26), ("anthropic/claude-sonnet-4-6", 0.63)], +) +def test_prices_all_cache_buckets_at_total_context_tier(model: str, expected: float) -> None: + tokens: Final = CacheTokenBuckets( + uncached_input_tokens=100_000, + cache_read_input_tokens=50_000, + cache_creation_5m_input_tokens=20_000, + cache_creation_1h_input_tokens=40_000, + ) + assert price_cache_tokens(model, "unconfigured-deployment", tokens) == pytest.approx(expected) + + +@pytest.mark.parametrize(("total", "expected"), [(200_000, 0.387), (200_001, 0.774006)]) +def test_long_context_tier_starts_above_threshold(total: int, expected: float) -> None: + tokens: Final = CacheTokenBuckets( + uncached_input_tokens=total - 100_000, + cache_creation_1h_input_tokens=10_000, + cache_read_input_tokens=90_000, + ) + actual: Final = price_cache_tokens("anthropic/claude-sonnet-4-5", "unconfigured-deployment", tokens) + assert actual == pytest.approx(expected) + + +def test_deployment_tariff_wins_without_proxy_discounts_or_margins(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setattr(litellm, "model_cost", litellm.model_cost.copy()) + litellm.Router( + model_list=[ + { + "model_name": "cache-pricing-test", + "litellm_params": { + "model": "anthropic/claude-sonnet-4-6", + "api_key": "test-only", + "input_cost_per_token": 0.00001, + "output_cost_per_token": 0.00002, + "cache_read_input_token_cost": 0.000001, + "cache_creation_input_token_cost": 0.0000125, + "cache_creation_input_token_cost_above_1hr": 0.00002, + }, + "model_info": {"id": "cache-pricing-test-a"}, + } + ] + ) + monkeypatch.setattr(litellm, "cost_discount_config", {"anthropic": 0.5}) + monkeypatch.setattr(litellm, "cost_margin_config", {"global": {"percentage": 0.3, "fixed_amount": 1.0}}) + tokens: Final = CacheTokenBuckets( + uncached_input_tokens=3_000, + cache_read_input_tokens=4_000, + cache_creation_5m_input_tokens=1_000, + cache_creation_1h_input_tokens=2_000, + ) + assert price_cache_tokens("anthropic/claude-sonnet-4-6", "cache-pricing-test-a", tokens) == pytest.approx(0.0865) + + +@pytest.mark.parametrize("rate", [None, -1.0, float("nan"), float("inf"), "0.00001", True]) +def test_unknown_for_absent_or_invalid_active_cache_rate(monkeypatch: pytest.MonkeyPatch, rate: object) -> None: + monkeypatch.setitem( + litellm.model_cost, + "cache-pricing-invalid", + { + "litellm_provider": "anthropic", + "mode": "chat", + "input_cost_per_token": 0.00001, + "output_cost_per_token": 0.00002, + "cache_creation_input_token_cost_above_1hr": rate, + }, + ) + tokens: Final = CacheTokenBuckets(cache_creation_1h_input_tokens=4_000) + assert price_cache_tokens("anthropic/claude-sonnet-4-6", "cache-pricing-invalid", tokens) is None + + +def test_missing_input_price_is_unknown_even_when_get_model_info_defaults_to_zero( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setitem(litellm.model_cost, "cache-pricing-missing", {"litellm_provider": "anthropic", "mode": "chat"}) + tokens: Final = CacheTokenBuckets(uncached_input_tokens=4_000) + assert price_cache_tokens("cache-pricing-missing", "unconfigured-deployment", tokens) is None + + +def test_explicit_free_pricing_is_not_unknown(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setitem( + litellm.model_cost, + "cache-pricing-free", + { + "litellm_provider": "anthropic", + "mode": "chat", + "input_cost_per_token": 0.0, + "output_cost_per_token": 0.0, + "cache_read_input_token_cost": 0.0, + "cache_creation_input_token_cost": 0.0, + "cache_creation_input_token_cost_above_1hr": 0.0, + }, + ) + tokens: Final = CacheTokenBuckets(uncached_input_tokens=100, cache_read_input_tokens=5_000) + assert price_cache_tokens("anthropic/claude-sonnet-4-6", "cache-pricing-free", tokens) == 0.0 diff --git a/tests/test_litellm/proxy/common_utils/test_scheduled_job_stagger.py b/tests/test_litellm/proxy/common_utils/test_scheduled_job_stagger.py index 54e0aa74a25..3eabfc5c840 100644 --- a/tests/test_litellm/proxy/common_utils/test_scheduled_job_stagger.py +++ b/tests/test_litellm/proxy/common_utils/test_scheduled_job_stagger.py @@ -64,6 +64,10 @@ def _stagger(scheduler: AsyncIOScheduler, identity: str = "pod-a:1", **overrides return apply_scheduled_job_stagger(scheduler=scheduler, settings=_settings(**overrides), identity=identity) +def _trigger_of(scheduler: AsyncIOScheduler, job_id: str): + return next(job.trigger for job in scheduler.get_jobs() if job.id == job_id) + + def _fire_times(trigger, start: datetime, steps: int) -> tuple[datetime, ...]: """The fire times APScheduler would produce, each computed from the one before it""" return tuple( @@ -133,22 +137,24 @@ def test_default_cron_is_staggered_and_keeps_its_offset_on_every_later_fire(): applied = _stagger(scheduler) assert applied[PTU_ROLLUP_JOB_ID] > 0 - trigger = next(job.trigger for job in scheduler.get_jobs() if job.id == PTU_ROLLUP_JOB_ID) - fires = _fire_times(trigger, datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc), 3) + start = datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc) + fires = _fire_times(_trigger_of(scheduler, PTU_ROLLUP_JOB_ID), start, 3) expected = timedelta(minutes=15) + timedelta(seconds=applied[PTU_ROLLUP_JOB_ID]) assert [fire - fire.replace(hour=0, minute=0, second=0, microsecond=0) for fire in fires] == [expected] * 3 -async def test_explicit_offset_overrides_the_derived_one_and_zero_pins_a_job(): +def test_explicit_offset_overrides_the_derived_one_and_zero_pins_a_job(): scheduler = _with_jobs(_scheduler()) applied = _stagger(scheduler, offsets={"periodic_reload_job": 0, PTU_ROLLUP_JOB_ID: 7}) - unstaggered = _next_run_times(_with_jobs(_scheduler())) - staggered = _next_run_times(scheduler) assert applied["periodic_reload_job"] == 0 assert applied[PTU_ROLLUP_JOB_ID] == 7 - assert staggered[PTU_ROLLUP_JOB_ID] - unstaggered[PTU_ROLLUP_JOB_ID] == timedelta(seconds=7) + + start = datetime(2026, 1, 1, 12, 0, tzinfo=timezone.utc) + staggered = _trigger_of(scheduler, PTU_ROLLUP_JOB_ID) + unstaggered = _trigger_of(_with_jobs(_scheduler()), PTU_ROLLUP_JOB_ID) + assert _fire_times(staggered, start, 1)[0] - _fire_times(unstaggered, start, 1)[0] == timedelta(seconds=7) async def test_disabling_the_stagger_leaves_every_schedule_untouched(): diff --git a/tests/test_litellm/proxy/db/conftest.py b/tests/test_litellm/proxy/db/conftest.py index d3226b0ec50..bcb7794a20d 100644 --- a/tests/test_litellm/proxy/db/conftest.py +++ b/tests/test_litellm/proxy/db/conftest.py @@ -35,6 +35,14 @@ DB_ENV_KEYS = ( _db_env_snapshot_key = pytest.StashKey[dict[str, Optional[str]]]() +def _is_zombie(pid: int) -> bool: + try: + stat: Final = Path(f"/proc/{pid}/stat").read_text() + except OSError: + return False + return stat.rpartition(")")[2].split()[0] == "Z" + + def _db_env_snapshot() -> dict[str, Optional[str]]: return {key: os.environ.get(key) for key in DB_ENV_KEYS} @@ -136,6 +144,8 @@ class FakePrismaCli: os.kill(pid, 0) except ProcessLookupError: return True + if _is_zombie(pid): + return True time.sleep(0.05) return False diff --git a/tests/test_litellm/proxy/db/test_health_check_latest.py b/tests/test_litellm/proxy/db/test_health_check_latest.py index 529e4d8f2e9..6322891ae9e 100644 --- a/tests/test_litellm/proxy/db/test_health_check_latest.py +++ b/tests/test_litellm/proxy/db/test_health_check_latest.py @@ -8,6 +8,7 @@ from litellm.proxy.db.health_check_latest import ( LATEST_HEALTH_CHECKS_SQL, fetch_latest_health_checks, fetch_latest_health_checks_for_models, + query_latest_health_checks, ) @@ -83,6 +84,15 @@ async def test_fetch_all_degrades_to_no_rows_when_the_query_fails(): assert await fetch_latest_health_checks(prisma) == () +@pytest.mark.asyncio +async def test_query_all_raises_when_the_query_fails_instead_of_reading_as_an_empty_table(): + """The background save decides what to write from this read; a failure has to be told apart from no rows.""" + prisma = _prisma([]) + prisma.db.query_raw.side_effect = RuntimeError("db down") + with pytest.raises(RuntimeError, match="db down"): + await query_latest_health_checks(prisma) + + @pytest.mark.asyncio async def test_fetch_all_degrades_to_no_rows_for_a_malformed_row(): assert await fetch_latest_health_checks(_prisma([{"unexpected": "shape"}])) == () diff --git a/tests/test_litellm/proxy/db/test_spend_log_tool_index.py b/tests/test_litellm/proxy/db/test_spend_log_tool_index.py index 9c4fbbf41aa..282c2a7cfaa 100644 --- a/tests/test_litellm/proxy/db/test_spend_log_tool_index.py +++ b/tests/test_litellm/proxy/db/test_spend_log_tool_index.py @@ -1,15 +1,17 @@ """ Tests for the tool usage writer: ToolUsageTransaction construction (invoked tools -only) and the flush that writes LiteLLM_SpendLogToolIndex plus the -LiteLLM_DailyToolSpend rollup in one transaction. +only) and the flush that writes LiteLLM_SpendLogToolIndex in bounded statements +plus the LiteLLM_DailyToolSpend rollup in one transaction. """ from types import SimpleNamespace from typing import Any from unittest.mock import AsyncMock, MagicMock +import httpx import pytest +from litellm.proxy.db import spend_log_tool_index from litellm.proxy.db.spend_log_tool_index import ( ToolUsageTransaction, build_tool_usage_transaction, @@ -35,11 +37,24 @@ class _FakeBatcher: return None +def _prisma(batch_: MagicMock) -> MagicMock: + prisma = MagicMock() + prisma.db.batch_ = batch_ + prisma.db.litellm_spendlogtoolindex.create_many = AsyncMock() + return prisma + + def _prisma_with_batcher() -> tuple[MagicMock, _FakeBatcher]: batcher = _FakeBatcher() - prisma = MagicMock() - prisma.db.batch_ = MagicMock(return_value=batcher) - return prisma, batcher + return _prisma(MagicMock(return_value=batcher)), batcher + + +def _index_rows_written(prisma: MagicMock) -> list[tuple[str, str]]: + return [ + (row["request_id"], row["tool_name"]) + for call in prisma.db.litellm_spendlogtoolindex.create_many.call_args_list + for row in call.kwargs["data"] + ] class TestBuildToolUsageTransaction: @@ -228,9 +243,8 @@ class TestFlushToolUsageTransactions: prisma_client=prisma, transactions=[_transaction("r1", tool_names=("tool_a", "tool_b"), spend=0.10, total_tokens=100)], ) - index_rows = batcher.litellm_spendlogtoolindex.create_many.call_args.kwargs["data"] - assert [(r["request_id"], r["tool_name"]) for r in index_rows] == [("r1", "tool_a"), ("r1", "tool_b")] - assert batcher.litellm_spendlogtoolindex.create_many.call_args.kwargs["skip_duplicates"] is True + assert _index_rows_written(prisma) == [("r1", "tool_a"), ("r1", "tool_b")] + assert prisma.db.litellm_spendlogtoolindex.create_many.call_args.kwargs["skip_duplicates"] is True upserts = { c.kwargs["where"]["date_tool_name"]["tool_name"]: c.kwargs["data"] @@ -267,19 +281,46 @@ class TestFlushToolUsageTransactions: assert data["update"]["request_count"] == {"increment": 2} @pytest.mark.asyncio - async def test_index_rows_and_rollup_share_one_transaction(self): - # Both writes go through the same batch_() so a failed flush cannot leave - # index rows without their rollup increments (or vice versa); increments - # are not idempotent, so partial states must be unreachable. + async def test_index_rows_are_written_in_bounded_statements_outside_the_rollup_transaction(self, monkeypatch): + monkeypatch.setattr(spend_log_tool_index, "SPEND_LOG_WRITE_BATCH_MAX_ROWS", 100) prisma, batcher = _prisma_with_batcher() - await flush_tool_usage_transactions( - prisma_client=prisma, - transactions=[_transaction("r1")], - ) + tool_names = tuple(f"tool_{i}" for i in range(50)) + transactions = [_transaction(f"r{i}", tool_names=tool_names) for i in range(5)] + await flush_tool_usage_transactions(prisma_client=prisma, transactions=transactions) + + statements = prisma.db.litellm_spendlogtoolindex.create_many.call_args_list + assert [len(call.kwargs["data"]) for call in statements] == [100, 100, 50] + assert all(call.kwargs["skip_duplicates"] is True for call in statements) + assert _index_rows_written(prisma) == [ + (txn.request_id, tool_name) for txn in transactions for tool_name in tool_names + ] + batcher.litellm_spendlogtoolindex.create_many.assert_not_called() + prisma.db.batch_.assert_called_once() + assert batcher.litellm_dailytoolspend.upsert.call_count == len(tool_names) + + @pytest.mark.asyncio + async def test_index_connection_error_is_retried_before_the_rollup_is_attempted(self, monkeypatch): + prisma, batcher = _prisma_with_batcher() + prisma.db.litellm_spendlogtoolindex.create_many = AsyncMock(side_effect=[httpx.ConnectError("down"), None]) + + async def fake_sleep(seconds: float) -> None: + return None + + monkeypatch.setattr("litellm.proxy.db.spend_log_tool_index.asyncio.sleep", fake_sleep) + await flush_tool_usage_transactions(prisma_client=prisma, transactions=[_transaction("r1")]) + assert prisma.db.litellm_spendlogtoolindex.create_many.await_count == 2 prisma.db.batch_.assert_called_once() - batcher.litellm_spendlogtoolindex.create_many.assert_called_once() batcher.litellm_dailytoolspend.upsert.assert_called_once() + @pytest.mark.asyncio + async def test_ambiguous_index_error_drops_the_batch_without_touching_the_rollup(self): + prisma, _ = _prisma_with_batcher() + prisma.db.litellm_spendlogtoolindex.create_many = AsyncMock(side_effect=httpx.ReadTimeout("ambiguous")) + with pytest.raises(httpx.ReadTimeout): + await flush_tool_usage_transactions(prisma_client=prisma, transactions=[_transaction("r1")]) + prisma.db.litellm_spendlogtoolindex.create_many.assert_awaited_once() + prisma.db.batch_.assert_not_called() + @pytest.mark.asyncio async def test_empty_batch_touches_nothing(self): prisma, _ = _prisma_with_batcher() @@ -290,11 +331,8 @@ class TestFlushToolUsageTransactions: async def test_connection_errors_retry_and_succeed(self, monkeypatch): # A failed batch commits nothing, so retrying a connection error cannot # double-count; the flush must retry rather than drop the batch. - import httpx - batcher = _FakeBatcher() - prisma = MagicMock() - prisma.db.batch_ = MagicMock(side_effect=[httpx.ConnectError("down"), batcher]) + prisma = _prisma(MagicMock(side_effect=[httpx.ConnectError("down"), batcher])) sleeps: list[float] = [] async def fake_sleep(seconds: float) -> None: @@ -308,10 +346,7 @@ class TestFlushToolUsageTransactions: @pytest.mark.asyncio async def test_connection_errors_exhaust_retries_then_raise(self, monkeypatch): - import httpx - - prisma = MagicMock() - prisma.db.batch_ = MagicMock(side_effect=httpx.ConnectError("down")) + prisma = _prisma(MagicMock(side_effect=httpx.ConnectError("down"))) async def fake_sleep(seconds: float) -> None: return None @@ -325,8 +360,7 @@ class TestFlushToolUsageTransactions: @pytest.mark.asyncio async def test_non_connection_errors_do_not_retry(self): - prisma = MagicMock() - prisma.db.batch_ = MagicMock(side_effect=ValueError("bad data")) + prisma = _prisma(MagicMock(side_effect=ValueError("bad data"))) with pytest.raises(ValueError, match="bad data"): await flush_tool_usage_transactions(prisma_client=prisma, transactions=[_transaction("r1")]) prisma.db.batch_.assert_called_once() @@ -338,11 +372,8 @@ class TestFlushToolUsageTransactions: # unknown; the engine can leave the transaction open on the pooled # connection, so a retry's statements would stack into it and one # commit would apply both increment sets. These must never retry. - import httpx - error = getattr(httpx, ambiguous_error)("ambiguous") - prisma = MagicMock() - prisma.db.batch_ = MagicMock(side_effect=error) + prisma = _prisma(MagicMock(side_effect=error)) with pytest.raises((httpx.ReadTimeout, httpx.ReadError)): await flush_tool_usage_transactions(prisma_client=prisma, transactions=[_transaction("r1")]) prisma.db.batch_.assert_called_once() diff --git a/tests/test_litellm/proxy/discovery_endpoints/test_agent_skills_archive.py b/tests/test_litellm/proxy/discovery_endpoints/test_agent_skills_archive.py new file mode 100644 index 00000000000..dd5ac230aac --- /dev/null +++ b/tests/test_litellm/proxy/discovery_endpoints/test_agent_skills_archive.py @@ -0,0 +1,106 @@ +import hashlib +import io +import zipfile + +from litellm.proxy.discovery_endpoints.agent_skills_archive import ( + MAX_ARCHIVE_ENTRIES, + build_skill_archive, +) + +MANIFEST = b"""--- +name: pdf-summarizer +description: Summarize a PDF into an executive brief. +--- + +Read the PDF, then write the brief. +""" + + +def zip_bytes(files: dict[str, bytes]) -> bytes: + buffer = io.BytesIO() + with zipfile.ZipFile(buffer, "w", zipfile.ZIP_DEFLATED) as archive: + for name, content in files.items(): + archive.writestr(name, content) + return buffer.getvalue() + + +def entries_of(content: bytes) -> dict[str, bytes]: + with zipfile.ZipFile(io.BytesIO(content)) as archive: + return {name: archive.read(name) for name in archive.namelist()} + + +def test_single_top_level_folder_is_stripped_so_skill_md_sits_at_the_root(): + archive = build_skill_archive( + zip_bytes( + { + "pdf-summarizer/SKILL.md": MANIFEST, + "pdf-summarizer/reference.md": b"page citations", + "pdf-summarizer/scripts/extract.py": b"print('hi')", + } + ) + ) + + assert archive is not None + assert entries_of(archive.content) == { + "SKILL.md": MANIFEST, + "reference.md": b"page citations", + "scripts/extract.py": b"print('hi')", + } + + +def test_digest_covers_the_repacked_bytes_and_is_stable_across_builds(): + upload = zip_bytes({"pdf-summarizer/SKILL.md": MANIFEST, "pdf-summarizer/reference.md": b"page citations"}) + + first = build_skill_archive(upload) + second = build_skill_archive(upload) + + assert first is not None and second is not None + assert first.digest == f"sha256:{hashlib.sha256(first.content).hexdigest()}" + assert first.content == second.content + + +def test_an_upload_that_is_already_flat_keeps_every_file_where_it_is(): + archive = build_skill_archive(zip_bytes({"SKILL.md": MANIFEST, "reference.md": b"page citations"})) + + assert archive is not None + assert sorted(entries_of(archive.content)) == ["SKILL.md", "reference.md"] + + +def test_manifest_frontmatter_supplies_the_declared_name_and_description(): + archive = build_skill_archive(zip_bytes({"pdf-summarizer/SKILL.md": MANIFEST})) + + assert archive is not None + assert archive.declared_name == "pdf-summarizer" + assert archive.declared_description == "Summarize a PDF into an executive brief." + + +def test_a_manifest_without_frontmatter_declares_nothing(): + archive = build_skill_archive(zip_bytes({"pdf-summarizer/SKILL.md": b"just prose, no frontmatter"})) + + assert archive is not None + assert archive.declared_name is None + assert archive.declared_description is None + + +def test_a_manifest_buried_below_the_stripped_folder_is_not_installable(): + assert build_skill_archive(zip_bytes({"pdf-summarizer/nested/SKILL.md": MANIFEST})) is None + + +def test_an_upload_with_no_manifest_is_not_installable(): + assert build_skill_archive(zip_bytes({"pdf-summarizer/reference.md": b"page citations"})) is None + + +def test_a_non_zip_upload_is_not_installable(): + assert build_skill_archive(MANIFEST) is None + + +def test_a_path_traversal_entry_is_not_installable(): + assert build_skill_archive(zip_bytes({"SKILL.md": MANIFEST, "../escape.md": b"nope"})) is None + + +def test_an_upload_over_the_entry_cap_is_not_installable(): + files = {"pdf-summarizer/SKILL.md": MANIFEST} | { + f"pdf-summarizer/file-{index}.md": b"x" for index in range(MAX_ARCHIVE_ENTRIES) + } + + assert build_skill_archive(zip_bytes(files)) is None diff --git a/tests/test_litellm/proxy/discovery_endpoints/test_agent_skills_endpoints.py b/tests/test_litellm/proxy/discovery_endpoints/test_agent_skills_endpoints.py new file mode 100644 index 00000000000..ea889e75ae8 --- /dev/null +++ b/tests/test_litellm/proxy/discovery_endpoints/test_agent_skills_endpoints.py @@ -0,0 +1,211 @@ +import hashlib +import io +import zipfile +from datetime import datetime, timezone + +import pytest +from fastapi import FastAPI +from fastapi.testclient import TestClient + +import litellm +from litellm.models.skills import LiteLLM_SkillsTable +from litellm.proxy.discovery_endpoints.agent_skills_endpoints import ( + router, + stored_skill, + stored_skills, +) +from litellm.types.proxy.discovery_endpoints.agent_skills_endpoints import ( + AGENT_SKILLS_DISCOVERY_SCHEMA_URL, +) + +WELL_KNOWN_PATHS = ("/.well-known/agent-skills/index.json", "/.well-known/skills/index.json") + +MANIFEST = b"""--- +name: pdf-summarizer +description: Summarize a PDF into an executive brief. +--- + +Read the PDF, then write the brief. +""" + + +def zip_bytes(files: dict[str, bytes]) -> bytes: + buffer = io.BytesIO() + with zipfile.ZipFile(buffer, "w", zipfile.ZIP_DEFLATED) as archive: + for name, content in files.items(): + archive.writestr(name, content) + return buffer.getvalue() + + +def skill( + skill_id: str, + *, + display_title: str | None = "PDF Summarizer", + description: str | None = None, + files: dict[str, bytes] | None = None, + updated_at: datetime | None = None, +) -> LiteLLM_SkillsTable: + return LiteLLM_SkillsTable( + skill_id=skill_id, + display_title=display_title, + description=description, + file_content=zip_bytes(files if files is not None else {"pdf-summarizer/SKILL.md": MANIFEST}), + updated_at=updated_at, + ) + + +def client_for(*skills: LiteLLM_SkillsTable) -> TestClient: + app = FastAPI() + app.include_router(router) + + def _skills() -> tuple[LiteLLM_SkillsTable, ...]: + return skills + + def _skill(skill_id: str) -> LiteLLM_SkillsTable | None: + return next((candidate for candidate in skills if candidate.skill_id == skill_id), None) + + app.dependency_overrides[stored_skills] = _skills + app.dependency_overrides[stored_skill] = _skill + return TestClient(app) + + +@pytest.fixture +def index_enabled(monkeypatch): + monkeypatch.setattr(litellm, "public_skills_index", True) + + +def test_discovery_is_absent_until_public_skills_index_is_enabled(monkeypatch): + monkeypatch.setattr(litellm, "public_skills_index", False) + client = client_for(skill("litellm_skill_1")) + + for path in WELL_KNOWN_PATHS: + assert client.get(path).status_code == 404 + assert client.get("/v1/skills/litellm_skill_1/archive").status_code == 404 + + +@pytest.mark.parametrize("path", WELL_KNOWN_PATHS) +def test_index_publishes_each_stored_skill_in_the_v0_2_0_shape(index_enabled, path): + client = client_for(skill("litellm_skill_1")) + + body = client.get(path).json() + + assert body["$schema"] == AGENT_SKILLS_DISCOVERY_SCHEMA_URL + assert len(body["skills"]) == 1 + entry = body["skills"][0] + assert entry["name"] == "pdf-summarizer" + assert entry["type"] == "archive" + assert entry["description"] == "Summarize a PDF into an executive brief." + assert entry["url"].endswith("/v1/skills/litellm_skill_1/archive") + assert entry["digest"].startswith("sha256:") + + +def test_index_digest_matches_the_bytes_the_archive_route_serves(index_enabled): + client = client_for(skill("litellm_skill_1")) + + entry = client.get(WELL_KNOWN_PATHS[0]).json()["skills"][0] + downloaded = client.get(entry["url"]) + + assert downloaded.status_code == 200 + assert downloaded.headers["content-type"] == "application/zip" + assert entry["digest"] == f"sha256:{hashlib.sha256(downloaded.content).hexdigest()}" + + +def test_install_name_falls_back_to_the_manifest_name_without_a_display_title(index_enabled): + client = client_for(skill("litellm_skill_1", display_title=None)) + + assert client.get(WELL_KNOWN_PATHS[0]).json()["skills"][0]["name"] == "pdf-summarizer" + + +@pytest.mark.parametrize( + "manifest, stored_description, expected", + [ + (MANIFEST, "registry copy", "Summarize a PDF into an executive brief."), + (b"no frontmatter here", "registry copy", "registry copy"), + (b"no frontmatter here", None, "PDF Summarizer"), + ], +) +def test_description_prefers_the_manifest_then_the_registry_then_the_title( + index_enabled, manifest, stored_description, expected +): + client = client_for( + skill( + "litellm_skill_1", + description=stored_description, + files={"pdf-summarizer/SKILL.md": manifest}, + ) + ) + + assert client.get(WELL_KNOWN_PATHS[0]).json()["skills"][0]["description"] == expected + + +def test_skills_sharing_a_title_get_distinct_install_names(index_enabled): + client = client_for( + skill("litellm_skill_2", files={"pdf-summarizer/SKILL.md": b"second"}), + skill("litellm_skill_1", files={"pdf-summarizer/SKILL.md": b"first"}), + ) + + names = [entry["name"] for entry in client.get(WELL_KNOWN_PATHS[0]).json()["skills"]] + + assert names == ["pdf-summarizer", "pdf-summarizer-2"] + + +def test_uploads_without_a_root_manifest_are_left_out_of_the_index(index_enabled): + client = client_for( + skill("litellm_skill_1"), + skill("litellm_skill_2", files={"pdf-summarizer/reference.md": b"no manifest"}), + ) + + body = client.get(WELL_KNOWN_PATHS[0]).json() + + assert [entry["url"].split("/")[-2] for entry in body["skills"]] == ["litellm_skill_1"] + assert client.get("/v1/skills/litellm_skill_2/archive").status_code == 404 + + +def test_archive_route_404s_for_a_skill_that_does_not_exist(index_enabled): + client = client_for(skill("litellm_skill_1")) + + assert client.get("/v1/skills/litellm_skill_missing/archive").status_code == 404 + + +def test_a_stored_skill_is_repacked_once_per_version(index_enabled): + stamp = datetime(2026, 9, 6, 9, 0, tzinfo=timezone.utc) + first = client_for(skill("litellm_skill_cached", files={"s/SKILL.md": MANIFEST}, updated_at=stamp)) + published = first.get(WELL_KNOWN_PATHS[0]).json()["skills"][0]["digest"] + + unchanged_row = client_for( + skill("litellm_skill_cached", files={"s/SKILL.md": MANIFEST, "s/extra.md": b"rewritten"}, updated_at=stamp) + ) + + assert unchanged_row.get(WELL_KNOWN_PATHS[0]).json()["skills"][0]["digest"] == published + assert hashlib.sha256(unchanged_row.get("/v1/skills/litellm_skill_cached/archive").content).hexdigest() == ( + published.removeprefix("sha256:") + ) + + +def test_a_skill_edited_since_the_last_read_is_republished(index_enabled): + stamp = datetime(2026, 9, 6, 9, 0, tzinfo=timezone.utc) + before = client_for(skill("litellm_skill_edited", files={"s/SKILL.md": MANIFEST}, updated_at=stamp)) + published = before.get(WELL_KNOWN_PATHS[0]).json()["skills"][0]["digest"] + + after = client_for( + skill( + "litellm_skill_edited", + files={"s/SKILL.md": MANIFEST, "s/extra.md": b"rewritten"}, + updated_at=datetime(2026, 9, 6, 10, 0, tzinfo=timezone.utc), + ) + ) + republished = after.get(WELL_KNOWN_PATHS[0]).json()["skills"][0]["digest"] + + assert republished != published + assert hashlib.sha256(after.get("/v1/skills/litellm_skill_edited/archive").content).hexdigest() == ( + republished.removeprefix("sha256:") + ) + + +def test_openapi_declares_the_archive_route_as_a_zip_download(index_enabled): + schema = client_for(skill("litellm_skill_1")).get("/openapi.json").json() + + content = schema["paths"]["/v1/skills/{skill_id}/archive"]["get"]["responses"]["200"]["content"] + + assert "application/zip" in content + assert "application/json" not in content diff --git a/tests/test_litellm/proxy/discovery_endpoints/test_ui_discovery_endpoints.py b/tests/test_litellm/proxy/discovery_endpoints/test_ui_discovery_endpoints.py index c3f7b0100d8..64a2eb69325 100644 --- a/tests/test_litellm/proxy/discovery_endpoints/test_ui_discovery_endpoints.py +++ b/tests/test_litellm/proxy/discovery_endpoints/test_ui_discovery_endpoints.py @@ -340,6 +340,7 @@ def test_ui_discovery_endpoints_hide_default_credentials_hint_default_false(): patch.dict(os.environ, {"DISABLE_ADMIN_UI": "false"}, clear=False), ): os.environ.pop("LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", None) + os.environ.pop("UI_PASSWORD", None) response = client.get("/.well-known/litellm-ui-config") @@ -348,6 +349,43 @@ def test_ui_discovery_endpoints_hide_default_credentials_hint_default_false(): assert data["hide_default_credentials_hint"] is False +def test_ui_discovery_endpoints_hide_default_credentials_hint_when_ui_password_set(): + app = FastAPI() + app.include_router(router) + client = TestClient(app) + + with patch.dict(os.environ, {"UI_PASSWORD": "s3cret-pass", "DISABLE_ADMIN_UI": "false"}, clear=False): + os.environ.pop("LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", None) + + response = client.get("/.well-known/litellm-ui-config") + + assert response.status_code == 200 + assert response.json()["hide_default_credentials_hint"] is True + + +@pytest.mark.parametrize( + "env_overrides", + [ + pytest.param({"UI_USERNAME": "opsadmin"}, id="username_only_keeps_master_key_password"), + pytest.param({"UI_PASSWORD": ""}, id="empty_password_is_not_set"), + ], +) +def test_ui_discovery_endpoints_keeps_default_credentials_hint_without_real_ui_password(env_overrides): + app = FastAPI() + app.include_router(router) + client = TestClient(app) + + with patch.dict(os.environ, {"DISABLE_ADMIN_UI": "false", **env_overrides}, clear=False): + os.environ.pop("LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", None) + if "UI_PASSWORD" not in env_overrides: + os.environ.pop("UI_PASSWORD", None) + + response = client.get("/.well-known/litellm-ui-config") + + assert response.status_code == 200 + assert response.json()["hide_default_credentials_hint"] is False + + def test_ui_discovery_endpoints_hide_default_credentials_hint_via_env_var(): """LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT=true hides the login-page credentials card.""" app = FastAPI() diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py index c0762edec92..d173c5f5c70 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_bedrock_guardrails.py @@ -2375,8 +2375,12 @@ _GROUNDING_QUERY_TEXT = "What is the capital of Japan?" _GROUNDING_RESPONSE_TEXT = "The capital of Japan is Tokyo." -def _grounding_guardrail() -> BedrockGuardrail: - return BedrockGuardrail(guardrailIdentifier="test-guardrail", guardrailVersion="DRAFT") +def _grounding_guardrail(from_messages: bool = False) -> BedrockGuardrail: + return BedrockGuardrail( + guardrailIdentifier="test-guardrail", + guardrailVersion="DRAFT", + contextual_grounding_from_messages=from_messages, + ) def _grounding_messages() -> list: @@ -2418,9 +2422,11 @@ def _input_request(messages: list) -> dict: return _grounding_guardrail().convert_to_bedrock_format(source="INPUT", messages=messages) -def _output_request(messages: list, response=None) -> dict: +def _output_request(messages: list, response=None, from_messages: bool = False) -> dict: """Arrange a guardrail and act: build the Bedrock OUTPUT payload.""" - return _grounding_guardrail().convert_to_bedrock_format(source="OUTPUT", response=response, messages=messages) + return _grounding_guardrail(from_messages).convert_to_bedrock_format( + source="OUTPUT", response=response, messages=messages + ) def test_grounding_input_strips_grounding_and_query_qualifiers(): @@ -2474,6 +2480,131 @@ def test_grounding_output_keeps_legacy_payload_without_tags(): assert actual_request == expected_request +def test_grounding_output_derives_source_and_query_from_plain_messages(): + """Flag on: untagged system + user text is sent as grounding_source + query.""" + messages = [ + {"role": "system", "content": _GROUNDING_SOURCE_TEXT}, + {"role": "user", "content": _GROUNDING_QUERY_TEXT}, + ] + expected_request = { + "source": "OUTPUT", + "content": [_GROUNDING_SOURCE_BLOCK, _QUERY_BLOCK, _GUARD_BLOCK], + } + + actual_request = _output_request(messages, _model_response(_GROUNDING_RESPONSE_TEXT), from_messages=True) + + assert actual_request == expected_request + + +def test_grounding_output_plain_messages_stay_legacy_when_flag_is_off(): + """Default config: plain system + user text is never sent as grounding context.""" + messages = [ + {"role": "system", "content": _GROUNDING_SOURCE_TEXT}, + {"role": "user", "content": _GROUNDING_QUERY_TEXT}, + ] + expected_request = {"source": "OUTPUT", "content": [{"text": {"text": _GROUNDING_RESPONSE_TEXT}}]} + + actual_request = _output_request(messages, _model_response(_GROUNDING_RESPONSE_TEXT)) + + assert actual_request == expected_request + + +def test_grounding_output_derived_query_is_latest_user_turn_only(): + """Only the latest user turn is the query; system and developer turns are the source.""" + developer_text = "Answer in one sentence." + messages = [ + {"role": "system", "content": _GROUNDING_SOURCE_TEXT}, + {"role": "developer", "content": [{"type": "text", "text": developer_text}]}, + {"role": "user", "content": "Hi"}, + {"role": "assistant", "content": "Hello, how can I help?"}, + {"role": "user", "content": _GROUNDING_QUERY_TEXT}, + ] + expected_request = { + "source": "OUTPUT", + "content": [ + _GROUNDING_SOURCE_BLOCK, + {"text": {"text": developer_text, "qualifiers": ["grounding_source"]}}, + _QUERY_BLOCK, + _GUARD_BLOCK, + ], + } + + actual_request = _output_request(messages, _model_response(_GROUNDING_RESPONSE_TEXT), from_messages=True) + + assert actual_request == expected_request + + +@pytest.mark.parametrize( + "messages", + [ + pytest.param([{"role": "system", "content": _GROUNDING_SOURCE_TEXT}], id="system-without-user"), + pytest.param( + [ + {"role": "tool", "content": _GROUNDING_SOURCE_TEXT, "tool_call_id": "c1"}, + {"role": "user", "content": _GROUNDING_QUERY_TEXT}, + ], + id="tool-result-is-not-a-source", + ), + pytest.param( + [ + {"role": "system", "content": ""}, + {"role": "user", "content": _GROUNDING_QUERY_TEXT}, + ], + id="empty-system-prompt", + ), + pytest.param( + [ + {"role": "system", "content": _GROUNDING_SOURCE_TEXT}, + {"role": "user", "content": [{"type": "image_url", "image_url": {"url": "https://x.test/a.png"}}]}, + ], + id="image-only-user-turn", + ), + ], +) +def test_grounding_output_stays_legacy_when_plain_source_or_query_is_missing(messages): + """Bedrock rejects a source without a query and vice versa, so send neither.""" + expected_request = {"source": "OUTPUT", "content": [{"text": {"text": _GROUNDING_RESPONSE_TEXT}}]} + + actual_request = _output_request(messages, _model_response(_GROUNDING_RESPONSE_TEXT), from_messages=True) + + assert actual_request == expected_request + + +def test_grounding_output_explicit_tags_take_precedence_over_plain_messages(): + """Tagged blocks win: untagged text around them is not added as source or query.""" + messages = [ + {"role": "system", "content": "You are a helpful assistant."}, + *_grounding_messages(), + {"role": "user", "content": "Please be brief."}, + ] + expected_request = { + "source": "OUTPUT", + "content": [_GROUNDING_SOURCE_BLOCK, _QUERY_BLOCK, _GUARD_BLOCK], + } + + actual_request = _output_request(messages, _model_response(_GROUNDING_RESPONSE_TEXT), from_messages=True) + + assert actual_request == expected_request + + +def test_grounding_input_ignores_plain_message_derivation(): + """INPUT scans never derive grounding qualifiers from plain messages.""" + messages = [ + {"role": "system", "content": _GROUNDING_SOURCE_TEXT}, + {"role": "user", "content": _GROUNDING_QUERY_TEXT}, + ] + expected_request = { + "source": "INPUT", + "content": [{"text": {"text": _GROUNDING_SOURCE_TEXT}}, {"text": {"text": _GROUNDING_QUERY_TEXT}}], + } + + actual_request = _grounding_guardrail(from_messages=True).convert_to_bedrock_format( + source="INPUT", messages=messages + ) + + assert actual_request == expected_request + + def test_grounding_output_combines_multiple_sources(): """Every grounding_source block is emitted; Bedrock combines them into one corpus.""" uk_source_text = "London is the capital of UK." @@ -2597,6 +2728,56 @@ async def test_grounding_output_blocked_raises_400(): assert exc_info.value.status_code == 400 +@pytest.mark.asyncio +@pytest.mark.parametrize( + "from_messages, request_messages", + [ + ( + True, + [ + {"role": "system", "content": _GROUNDING_SOURCE_TEXT}, + {"role": "user", "content": _GROUNDING_QUERY_TEXT}, + ], + ), + ( + False, + [ + {"role": "system", "content": [{"type": "grounding_source", "text": _GROUNDING_SOURCE_TEXT}]}, + {"role": "user", "content": [{"type": "query", "text": _GROUNDING_QUERY_TEXT}]}, + ], + ), + ], + ids=["plain-messages-flag-on", "tagged-messages-flag-off"], +) +async def test_apply_guardrail_response_forwards_request_messages_for_grounding(from_messages, request_messages): + guardrail = _grounding_guardrail(from_messages=from_messages) + expected_request = { + "source": "OUTPUT", + "content": [_GROUNDING_SOURCE_BLOCK, _QUERY_BLOCK, _GUARD_BLOCK], + } + + mock_credentials = MagicMock() + mock_credentials.access_key = "test-access-key" + mock_credentials.secret_key = "test-secret-key" + mock_credentials.token = None + + with ( + patch.object(guardrail.async_handler, "post", new_callable=AsyncMock) as mock_post, + patch.object(guardrail, "_load_credentials", return_value=(mock_credentials, "us-east-1")), + patch.object(guardrail, "_prepare_request", return_value=MagicMock()) as mock_prepare, + ): + mock_post.return_value = _passing_bedrock_httpx_response(_GROUNDING_RESPONSE_TEXT) + + await guardrail.apply_guardrail( + inputs={"texts": [_GROUNDING_RESPONSE_TEXT]}, + request_data={"messages": request_messages}, + input_type="response", + ) + + assert mock_prepare.call_count == 1 + assert json.loads(json.dumps(mock_prepare.call_args.kwargs["data"])) == expected_request + + ############################################################################### # LIT-4186: disable_exception_on_block regression tests # diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_crowdstrike_aidr.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_crowdstrike_aidr.py index a9ca13a463d..9849ad7ec88 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_crowdstrike_aidr.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_crowdstrike_aidr.py @@ -1820,7 +1820,7 @@ async def test_unalignable_rewrite_is_rejected_never_sent_unredacted( Skipping the write-back would hand the model the unredacted text, so a guardrail could be bypassed by adding ``instructions`` or a tool call. """ - from litellm.proxy.policy_engine.pipeline_executor import UnappliableRequestRewrite + from litellm.llms.base_llm.guardrail_translation.utils import UnappliableRequestRewrite data: dict[str, object] = {"model": "gpt-4o", "input": responses_input} if instructions is not None: diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_generic_guardrail_api.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_generic_guardrail_api.py index 83cc9ae8bb9..a5e79f84ef1 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_generic_guardrail_api.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_generic_guardrail_api.py @@ -582,6 +582,145 @@ class TestGuardrailActions: assert result_images is None +class TestStructuredMessagesInResponse: + """A guardrail server that rewrites per chat row answers with the rewritten + rows as structured_messages, which the endpoint handlers write back by row.""" + + @pytest.mark.asyncio + async def test_returned_rows_are_handed_back_as_structured_messages( + self, generic_guardrail, mock_request_data_input + ): + rewritten_rows = [ + {"role": "system", "content": "Never repeat an SSN."}, + {"role": "user", "content": "Look up [REDACTED] for me."}, + {"role": "tool", "tool_call_id": "call_1", "content": '{"ssn": "[REDACTED]"}'}, + ] + mock_response = MagicMock() + mock_response.json.return_value = { + "action": "GUARDRAIL_INTERVENED", + "texts": ["Never repeat an SSN.", "Look up [REDACTED] for me.", '{"ssn": "[REDACTED]"}'], + "structured_messages": rewritten_rows, + } + mock_response.raise_for_status = MagicMock() + + with patch.object(generic_guardrail.async_handler, "post", return_value=mock_response): + guardrailed_inputs = await generic_guardrail.apply_guardrail( + inputs={"texts": ["Look up 123-45-6789 for me."]}, + request_data=mock_request_data_input, + input_type="request", + ) + + assert guardrailed_inputs["structured_messages"] == rewritten_rows + assert guardrailed_inputs["texts"] == mock_response.json.return_value["texts"] + + @pytest.mark.asyncio + async def test_rows_echoed_back_as_shown_keep_their_original_keys( + self, generic_guardrail, mock_request_data_input + ): + tool_call_row = { + "role": "assistant", + "content": None, + "tool_calls": [ + {"id": "call_1", "type": "function", "function": {"name": "lookup", "arguments": "{}"}, "index": 0} + ], + } + original_rows = [ + {"role": "user", "content": "Look up 123-45-6789 for me.", "name": "pat"}, + tool_call_row, + {"role": "tool", "tool_call_id": "call_1", "content": '{"ssn": "123-45-6789"}'}, + ] + + def echo_with_tool_output_redacted(url, json, headers): + shown_rows = json["structured_messages"] + assert "index" not in shown_rows[1]["tool_calls"][0] + assert "name" not in shown_rows[0] + answer = MagicMock() + answer.json.return_value = { + "action": "GUARDRAIL_INTERVENED", + "texts": ["Look up 123-45-6789 for me."], + "structured_messages": [ + shown_rows[0], + shown_rows[1], + {**shown_rows[2], "content": '{"ssn": "[REDACTED]"}'}, + ], + } + answer.raise_for_status = MagicMock() + return answer + + with patch.object(generic_guardrail.async_handler, "post", side_effect=echo_with_tool_output_redacted): + guardrailed_inputs = await generic_guardrail.apply_guardrail( + inputs={"texts": ["Look up 123-45-6789 for me."], "structured_messages": original_rows}, + request_data=mock_request_data_input, + input_type="request", + ) + + returned_rows = guardrailed_inputs["structured_messages"] + assert returned_rows[0] is original_rows[0] + assert returned_rows[1] is tool_call_row + assert returned_rows[2] == {"role": "tool", "tool_call_id": "call_1", "content": '{"ssn": "[REDACTED]"}'} + + @pytest.mark.asyncio + async def test_rows_all_echoed_back_as_shown_leave_the_rewrite_to_texts( + self, generic_guardrail, mock_request_data_input + ): + """A server written against the texts contract that echoes the request rows back + untouched while rewriting texts still gets its texts rewrite applied.""" + original_rows = [ + {"role": "system", "content": "Never repeat an SSN."}, + {"role": "user", "content": "Look up 123-45-6789 for me."}, + ] + + def echo_rows_and_rewrite_texts(url, json, headers): + answer = MagicMock() + answer.json.return_value = { + "action": "NONE", + "texts": [text.replace("123-45-6789", "[REDACTED]") for text in json["texts"]], + "structured_messages": json["structured_messages"], + } + answer.raise_for_status = MagicMock() + return answer + + with patch.object(generic_guardrail.async_handler, "post", side_effect=echo_rows_and_rewrite_texts): + guardrailed_inputs = await generic_guardrail.apply_guardrail( + inputs={ + "texts": ["Never repeat an SSN.", "Look up 123-45-6789 for me."], + "structured_messages": original_rows, + }, + request_data=mock_request_data_input, + input_type="request", + ) + + assert "structured_messages" not in guardrailed_inputs + assert guardrailed_inputs["texts"] == ["Never repeat an SSN.", "Look up [REDACTED] for me."] + + @pytest.mark.asyncio + @pytest.mark.parametrize( + "structured_messages", + [[], [{"content": "a row with no role"}], "not a list"], + ids=["empty", "no_role", "not_a_list"], + ) + async def test_rows_that_are_not_chat_messages_are_ignored( + self, generic_guardrail, mock_request_data_input, structured_messages + ): + mock_response = MagicMock() + mock_response.json.return_value = { + "action": "GUARDRAIL_INTERVENED", + "texts": ["[REDACTED]"], + "structured_messages": structured_messages, + } + mock_response.raise_for_status = MagicMock() + + with patch.object(generic_guardrail.async_handler, "post", return_value=mock_response): + guardrailed_inputs = await generic_guardrail.apply_guardrail( + inputs={"texts": ["Look up 123-45-6789 for me."]}, + request_data=mock_request_data_input, + input_type="request", + ) + + assert "structured_messages" not in guardrailed_inputs + assert guardrailed_inputs["texts"] == ["[REDACTED]"] + + class TestImageSupport: """Test image handling in guardrail requests""" diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py index d8eeb8d2b8a..d4531398ba1 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_headroom.py @@ -1797,12 +1797,8 @@ PARTS_MESSAGES = [ { "role": "user", "content": [ - {"type": "text", "text": "Earlier turn.", "cache_control": {"type": "ephemeral"}}, - { - "type": "text", - "text": "Second block. " + "B" * 5000, - "cache_control": {"type": "ephemeral", "ttl": "1h"}, - }, + {"type": "text", "text": "Earlier turn."}, + {"type": "text", "text": "Second block. " + "B" * 5000}, ], }, { @@ -1891,14 +1887,9 @@ async def test_apply_guardrail_restores_rewritten_all_text_row( messages = result["structured_messages"] history_content = messages[1]["content"] - # Rewritten all-text row collapses to one part carrying the LAST declared - # breakpoint: an Anthropic breakpoint caches the prefix ending at its - # part, so after the merge the last one (and its TTL) still describes the - # row. assert isinstance(history_content, list) assert len(history_content) == 1 assert history_content[0]["text"] == "compressed history. Retrieve more: hash=b573993006976af767214fac" - assert history_content[0]["cache_control"] == {"type": "ephemeral", "ttl": "1h"} # Mixed row passes through byte-identical. assert messages[2]["content"] == PARTS_MESSAGES[2]["content"] # The service-declared hash still drives retrieve-tool injection on a restored row. @@ -2523,6 +2514,35 @@ async def test_history_is_still_compressed(guardrail: HeadroomGuardrail): assert messages[3] == compressed_history[1] +CACHE_MARKED_HISTORY_MESSAGES = [ + {"role": "system", "content": "You are Claude Code. " + "S" * 5000}, + {"role": "user", "content": "old question " + "Q" * 5000}, + { + "role": "assistant", + "content": "Reading the file now.", + "tool_calls": [{"id": "old_1", "type": "function", "function": {"name": "Read", "arguments": "{}"}}], + }, + { + "role": "tool", + "tool_call_id": "old_1", + "content": [{"type": "text", "text": "large cached file body " + "F" * 5000}], + "cache_control": {"type": "ephemeral"}, + }, + {"role": "assistant", "content": "Summarized the file for you."}, + {"role": "user", "content": "live instruction"}, +] + + +@pytest.mark.asyncio +async def test_mid_history_cache_control_row_is_never_sent_for_compression(guardrail: HeadroomGuardrail): + wire, result = await _wire_and_result(guardrail, CACHE_MARKED_HISTORY_MESSAGES) + + cached_row = CACHE_MARKED_HISTORY_MESSAGES[3] + assert cached_row not in wire + assert not any(row.get("tool_call_id") == "old_1" for row in wire) + assert result["structured_messages"][3] == cached_row + + # --------------------------------------------------------------------------- # #38558: a client that runs its own tool loop (e.g. Claude Code via the MCP # gateway) executes headroom_retrieve and echoes the recovered original content diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_model_armor.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_model_armor.py index 47089b7b1b1..5aa3c7dfc17 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_model_armor.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_model_armor.py @@ -2,6 +2,8 @@ import asyncio import base64 import io import json +from collections.abc import Iterator, Sequence +from typing import cast from unittest.mock import AsyncMock, MagicMock, Mock, patch import pytest @@ -14,7 +16,7 @@ import litellm import litellm.types.utils from litellm._logging import verbose_proxy_logger from litellm.caching import DualCache -from litellm.llms.custom_httpx.http_handler import MaskedHTTPStatusError +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, MaskedHTTPStatusError from litellm.proxy.guardrails.anthropic_sse import anthropic_sse_error_frames from litellm.proxy._types import UserAPIKeyAuth from litellm.proxy.guardrails.guardrail_hooks.model_armor import ModelArmorGuardrail @@ -4929,3 +4931,390 @@ def test_every_responses_delta_event_is_in_the_scanned_set(): } assert not missing assert "response.mcp_call_arguments.delta" in _RESPONSES_DELTA_EVENT_TYPES + + +def _clean_armor_response() -> dict[str, object]: + return { + "sanitizationResult": { + "filterMatchState": "NO_MATCH_FOUND", + "filterResults": {}, + } + } + + +def _flagged_armor_response() -> dict[str, object]: + return { + "sanitizationResult": { + "filterMatchState": "MATCH_FOUND", + "filterResults": {"rai": {"raiFilterResult": {"matchState": "MATCH_FOUND"}}}, + } + } + + +class _FakeArmorHandler(AsyncHTTPHandler): + def __init__(self, responses: Sequence[dict[str, object] | Exception]): + self.responses: Iterator[dict[str, object] | Exception] = iter(responses) + self.calls: list[dict[str, object]] = [] + self.raise_on_call: Exception | None = None + + async def post( + self, + url: str, + json: dict[str, object] | None = None, + headers: dict[str, str] | None = None, + **kwargs: object, + ) -> httpx.Response: + if self.raise_on_call is not None: + raise self.raise_on_call + if json is not None: + self.calls.append(json) + response: dict[str, object] | Exception = next(self.responses) + if isinstance(response, Exception): + raise response + return httpx.Response(200, json=response, request=httpx.Request("POST", url)) + + +async def _async_token_provider() -> tuple[str, str]: + return ("test-token", "test-project") + + +def _logging_only_guardrail( + responses: Sequence[dict[str, object] | Exception] = (_clean_armor_response(), _clean_armor_response()), +) -> ModelArmorGuardrail: + handler = _FakeArmorHandler(responses) + guardrail = ModelArmorGuardrail( + template_id="test-template", + project_id="test-project", + location="us-central1", + guardrail_name="model-armor-logging", + event_hook=GuardrailEventHooks.logging_only, + async_handler=handler, + access_token_provider=_async_token_provider, + ) + return guardrail + + +def _logged_kwargs() -> dict[str, object]: + return { + "model": "gpt-4o", + "messages": [{"role": "user", "content": "hi"}], + "litellm_call_id": "call-1", + "litellm_params": {"metadata": {}}, + "optional_params": {}, + "standard_logging_object": {"guardrail_information": None}, + } + + +def _chat_response(text: str) -> litellm.ModelResponse: + return litellm.ModelResponse( + choices=[ + litellm.types.utils.Choices( + message=litellm.types.utils.Message(role="assistant", content=text) + ) + ] + ) + + +def _stream_chunk(text: str) -> litellm.ModelResponseStream: + return litellm.ModelResponseStream( + choices=[ + litellm.types.utils.StreamingChoices( + delta=litellm.types.utils.Delta(content=text) + ) + ] + ) + + +def _metadata_entries(kwargs: dict[str, object]) -> list[dict[str, object]]: + standard_logging_object = cast(dict[str, object], kwargs["standard_logging_object"]) + entries = standard_logging_object.get("guardrail_information") or [] + return cast(list[dict[str, object]], entries) + + +def test_logging_only_mode_is_accepted_and_keeps_native_hooks(): + guardrail = _logging_only_guardrail() + assert guardrail.event_hook == GuardrailEventHooks.logging_only + assert guardrail.use_native_lifecycle_hooks is True + assert GuardrailEventHooks.logging_only in ModelArmorGuardrail.get_supported_event_hooks() + + post_call_guardrail = ModelArmorGuardrail( + template_id="test-template", + project_id="test-project", + location="us-central1", + guardrail_name="model-armor-post", + event_hook=GuardrailEventHooks.post_call, + ) + assert post_call_guardrail._deployment_hook_target() is post_call_guardrail + + +@pytest.mark.asyncio +async def test_logging_only_stream_yields_chunks_without_waiting_for_scan(): + """A logging_only guardrail must pass stream chunks straight through; the scan happens + afterwards on the assembled response via async_logging_hook.""" + guardrail = _logging_only_guardrail( + [_clean_armor_response(), _clean_armor_response()] + ) + handler = cast(_FakeArmorHandler, guardrail.async_handler) + handler.raise_on_call = AssertionError("logging_only must not scan the stream") + + produced = 0 + + async def gen(): + nonlocal produced + for i in range(3): + produced += 1 + yield _stream_chunk(f"chunk-{i} ") + + hook_iter = guardrail.async_post_call_streaming_iterator_hook( + user_api_key_dict=UserAPIKeyAuth(), + response=gen(), + request_data={"metadata": {}, "guardrails": ["model-armor-logging"]}, + ) + first = await hook_iter.__anext__() + assert produced == 1 + chunks = [first] + async for chunk in hook_iter: + chunks.append(chunk) + assert len(chunks) == 3 + assert handler.calls == [] + handler.raise_on_call = None + + response = _chat_response("all clear") + kwargs = _logged_kwargs() + out_kwargs, out_result = await guardrail.async_logging_hook( + kwargs=kwargs, result=response, call_type="acompletion" + ) + assert out_result is response + entries = _metadata_entries(out_kwargs) + assert len(entries) >= 1 + entry = entries[-1] + assert entry["guardrail_status"] == "success" + assert entry["guardrail_mode"] == "logging_only" + assert entry["guardrail_provider"] == "model_armor" + + +@pytest.mark.asyncio +async def test_logging_only_records_flagged_verdict_without_altering_response(): + guardrail = _logging_only_guardrail( + [_flagged_armor_response(), _flagged_armor_response()] + ) + response = _chat_response("flagged output") + kwargs = _logged_kwargs() + + out_kwargs, out_result = await guardrail.async_logging_hook( + kwargs=kwargs, result=response, call_type="acompletion" + ) + + assert out_result is response + entries = _metadata_entries(out_kwargs) + assert entries[-1]["guardrail_status"] == "guardrail_flagged" + assert entries[-1]["guardrail_mode"] == "logging_only" + + +@pytest.mark.asyncio +async def test_logging_only_records_model_armor_api_error(): + guardrail = _logging_only_guardrail( + [ + ModelArmorAPIError("Model Armor API error (upstream 500)"), + ModelArmorAPIError("Model Armor API error (upstream 500)"), + ] + ) + response = _chat_response("some output") + kwargs = _logged_kwargs() + + out_kwargs, out_result = await guardrail.async_logging_hook( + kwargs=kwargs, result=response, call_type="acompletion" + ) + + assert out_result is response + entries = _metadata_entries(out_kwargs) + assert entries[-1]["guardrail_status"] == "guardrail_failed_to_respond" + + +@pytest.mark.asyncio +async def test_logging_only_scans_assembled_responses_api_stream(): + """The terminal ResponseCompletedEvent is an envelope; the scan must run on the + assembled ResponsesAPIResponse kept in kwargs.""" + from openai.types.responses import ResponseOutputMessage, ResponseOutputText + + from litellm.types.llms.openai import ( + ResponseCompletedEvent, + ResponsesAPIResponse, + ResponsesAPIStreamEvents, + ) + + assembled = ResponsesAPIResponse( + id="resp-1", + created_at=1700000000, + output=[ + ResponseOutputMessage( + id="msg-1", + type="message", + role="assistant", + status="completed", + content=[ + ResponseOutputText( + annotations=[], text="assembled output text", type="output_text" + ) + ], + ) + ], + ) + event = ResponseCompletedEvent( + type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED, response=assembled + ) + + guardrail = _logging_only_guardrail() + kwargs = _logged_kwargs() + del kwargs["messages"] + kwargs["input"] = "hello" + kwargs["async_complete_streaming_response"] = assembled + + out_kwargs, _ = await guardrail.async_logging_hook( + kwargs=kwargs, result=event, call_type="aresponses" + ) + + handler = cast(_FakeArmorHandler, guardrail.async_handler) + response_scans = [call for call in handler.calls if "modelResponseData" in call] + assert response_scans, "expected a model_response scan of the assembled response" + assert "assembled output text" in response_scans[0]["modelResponseData"]["text"] + assert _metadata_entries(out_kwargs) + + +@pytest.mark.asyncio +async def test_logging_only_scans_anthropic_messages_model_response(): + """/v1/messages logs a ModelResponse; the output scan must extract the assistant text.""" + guardrail = _logging_only_guardrail() + kwargs = _logged_kwargs() + kwargs["messages"] = [{"role": "user", "content": [{"type": "text", "text": "hi"}]}] + response = _chat_response("anthropic assembled text") + + out_kwargs, out_result = await guardrail.async_logging_hook( + kwargs=kwargs, result=response, call_type="anthropic_messages" + ) + + assert out_result is response + handler = cast(_FakeArmorHandler, guardrail.async_handler) + response_scans = [call for call in handler.calls if "modelResponseData" in call] + assert response_scans + assert "anthropic assembled text" in response_scans[0]["modelResponseData"]["text"] + assert _metadata_entries(out_kwargs) + + +@pytest.mark.asyncio +async def test_logging_only_skips_output_scan_when_no_assembled_response(): + guardrail = _logging_only_guardrail() + kwargs = _logged_kwargs() + + await guardrail.async_logging_hook(kwargs=kwargs, result=None, call_type="acompletion") + + handler = cast(_FakeArmorHandler, guardrail.async_handler) + assert all("modelResponseData" not in call for call in handler.calls) + + +@pytest.mark.asyncio +async def test_native_post_call_mode_ignores_logging_hook(): + handler = _FakeArmorHandler([_clean_armor_response()]) + guardrail = ModelArmorGuardrail( + template_id="test-template", + project_id="test-project", + location="us-central1", + guardrail_name="model-armor-post", + event_hook=GuardrailEventHooks.post_call, + async_handler=handler, + access_token_provider=_async_token_provider, + ) + response = _chat_response("some output") + kwargs = _logged_kwargs() + + out_kwargs, out_result = await guardrail.async_logging_hook( + kwargs=kwargs, result=response, call_type="acompletion" + ) + + assert out_kwargs is kwargs + assert out_result is response + assert handler.calls == [] + + +@pytest.mark.asyncio +async def test_apply_guardrail_records_flagged_without_raising(): + guardrail = _logging_only_guardrail([_flagged_armor_response()]) + request_data = {"metadata": {}} + inputs = {"texts": ["forbidden output"]} + + result = await guardrail.apply_guardrail( + inputs=inputs, + request_data=request_data, + input_type="response", + ) + + assert result == inputs + entries = request_data["metadata"]["standard_logging_guardrail_information"] + assert entries[-1]["guardrail_status"] == "guardrail_flagged" + + +@pytest.mark.asyncio +async def test_logging_only_records_transport_error(): + guardrail = _logging_only_guardrail([httpx.ConnectError("boom"), httpx.ConnectError("boom")]) + response = _chat_response("some output") + kwargs = _logged_kwargs() + + out_kwargs, out_result = await guardrail.async_logging_hook( + kwargs=kwargs, result=response, call_type="acompletion" + ) + + assert out_result is response + entries = _metadata_entries(out_kwargs) + failed = [e for e in entries if e["guardrail_status"] == "guardrail_failed_to_respond"] + assert failed + assert all(e["guardrail_provider"] == "model_armor" for e in failed) + + +@pytest.mark.asyncio +async def test_logging_only_flagged_prompt_still_scans_response(): + """A flagged input scan must not abort the output scan; both verdicts are recorded.""" + guardrail = _logging_only_guardrail( + [_flagged_armor_response(), _flagged_armor_response()] + ) + response = _chat_response("flagged output") + kwargs = _logged_kwargs() + + out_kwargs, _ = await guardrail.async_logging_hook( + kwargs=kwargs, result=response, call_type="acompletion" + ) + + handler = cast(_FakeArmorHandler, guardrail.async_handler) + sources = ["user_prompt" if "userPromptData" in call else "model_response" for call in handler.calls] + assert sources == ["user_prompt", "model_response"] + entries = _metadata_entries(out_kwargs) + flagged = [e for e in entries if e["guardrail_status"] == "guardrail_flagged"] + assert len(flagged) == 2 + + +@pytest.mark.asyncio +async def test_apply_guardrail_raises_on_flagged_when_not_logging_only(): + """The /guardrails/apply_guardrail endpoint calls apply_guardrail directly; a + non-logging_only instance must signal the block so flagged text is not returned as clean.""" + handler = _FakeArmorHandler([_flagged_armor_response()]) + guardrail = ModelArmorGuardrail( + template_id="test-template", + project_id="test-project", + location="us-central1", + guardrail_name="model-armor-pre", + event_hook=GuardrailEventHooks.pre_call, + async_handler=handler, + access_token_provider=_async_token_provider, + ) + request_data = {"metadata": {}} + + with pytest.raises(HTTPException) as exc_info: + await guardrail.apply_guardrail( + inputs={"texts": ["forbidden prompt"]}, + request_data=request_data, + input_type="request", + ) + + assert exc_info.value.status_code == 400 + entries = request_data["metadata"]["standard_logging_guardrail_information"] + flagged = [e for e in entries if e["guardrail_status"] == "guardrail_flagged"] + assert len(flagged) == 1 diff --git a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_panw_prisma_airs.py b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_panw_prisma_airs.py index 3d7c6e06d94..f25727ebd9a 100644 --- a/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_panw_prisma_airs.py +++ b/tests/test_litellm/proxy/guardrails/guardrail_hooks/test_panw_prisma_airs.py @@ -4620,46 +4620,27 @@ class TestPanwAirsLatestRoleMessageOnly: @pytest.mark.asyncio async def test_anthropic_system_plus_multiturn_no_fallback(self): - """Anthropic with top-level system + multi-turn messages[] - — latest-user works, no scan-all fallback. + """Anthropic with a top-level system prompt and multi-turn messages[] + scans only the latest user turn, with no scan-all fallback. - Key scenario: Anthropic top-level `system` field causes - structured_messages to have an injected system entry, but - request_data["messages"] does NOT include it. + The Anthropic handler hoists the top-level `system` field into both + `texts` and `structured_messages`, so the latest-user walk has to + count the same entries the framework flattened. """ - handler = PanwPrismaAirsHandler( - guardrail_name="test_panw_airs", - api_key="test_api_key", - profile_name="test_profile", - default_on=True, + from litellm.llms.anthropic.chat.guardrail_translation.handler import ( + AnthropicMessagesHandler, ) - # Original Anthropic messages (no system in messages array) - original_messages = [ - {"role": "user", "content": "First user turn"}, - {"role": "assistant", "content": "First assistant turn"}, - {"role": "user", "content": "Latest user turn"}, - ] - - # texts extracted from original_messages (3 text entries) - texts = ["First user turn", "First assistant turn", "Latest user turn"] - - # structured_messages has an INJECTED system message from translation - structured_messages = [ - {"role": "system", "content": "You are a helpful assistant."}, - {"role": "user", "content": "First user turn"}, - {"role": "assistant", "content": "First assistant turn"}, - {"role": "user", "content": "Latest user turn"}, - ] - - inputs: GenericGuardrailAPIInputs = { - "texts": texts, - "structured_messages": structured_messages, - } + handler = make_handler() request_data = { "litellm_call_id": "test-call-id", "model": "anthropic/claude-sonnet-4-20250514", - "messages": original_messages, + "system": "You are a helpful assistant.", + "messages": [ + {"role": "user", "content": "First user turn"}, + {"role": "assistant", "content": "First assistant turn"}, + {"role": "user", "content": "Latest user turn"}, + ], "proxy_server_request": { "url": "http://localhost:4000/v1/messages", }, @@ -4670,13 +4651,11 @@ class TestPanwAirsLatestRoleMessageOnly: ) as mock_api: mock_api.return_value = {"action": "allow", "category": "benign"} - await handler.apply_guardrail( - inputs=inputs, - request_data=request_data, - input_type="request", + await AnthropicMessagesHandler().process_input_messages( + data=request_data, + guardrail_to_apply=handler, ) - # Should scan ONLY the latest user message, not fall back to scan-all assert mock_api.call_count == 1 assert mock_api.call_args.kwargs["content"] == "Latest user turn" diff --git a/tests/test_litellm/proxy/guardrails/test_deferred_guardrail_logging.py b/tests/test_litellm/proxy/guardrails/test_deferred_guardrail_logging.py index c550a0a41d2..6295469c066 100644 --- a/tests/test_litellm/proxy/guardrails/test_deferred_guardrail_logging.py +++ b/tests/test_litellm/proxy/guardrails/test_deferred_guardrail_logging.py @@ -16,14 +16,21 @@ Streaming: CSW.__anext__ stores args on logging_obj at stream end. import asyncio import logging -from typing import Any, Final +from collections.abc import Callable, Mapping +from datetime import datetime +from typing import Any, Final, cast from unittest.mock import AsyncMock, MagicMock, patch +import httpx import pytest +import respx import litellm from litellm.caching.caching import DualCache +from litellm.litellm_core_utils.litellm_logging import Logging +from litellm.types.utils import StandardLoggingPayload +from litellm.utils import _dispatch_success_logging from litellm.integrations.custom_guardrail import CustomGuardrail from litellm.integrations.custom_logger import CustomLogger from litellm.proxy._types import UserAPIKeyAuth @@ -54,6 +61,27 @@ def _attach_mock_success_dispatch(mock_logging_obj, async_success_fn): mock_logging_obj.async_success_handler = async_success_fn +async def _wait_until(condition: Callable[[], bool]) -> None: + """Give the logging worker a bounded window to run what the closure enqueued.""" + for _ in range(200): + if condition(): + return + await asyncio.sleep(0.01) + + +class _RecordingLogger(CustomLogger): + """Keeps what the async success callback was handed, the way a spend logger sees it.""" + + def __init__(self) -> None: + super().__init__() + self.standard_logging_object: StandardLoggingPayload | None = None + + async def async_log_success_event( + self, kwargs: Mapping[str, object], response_obj: object, start_time: datetime, end_time: datetime + ) -> None: + self.standard_logging_object = cast(StandardLoggingPayload, kwargs["standard_logging_object"]) + + class PostCallGuardrail(CustomGuardrail): """A post-call guardrail.""" @@ -259,6 +287,120 @@ async def test_deferred_flag_stores_and_executes_closure(): pass +@pytest.mark.asyncio +async def test_deferred_slot_keeps_the_innermost_wrapper_result(): + """Nested @client wrappers exit through _dispatch_success_logging with one shared logging + object. The deferred slot must keep the first stored result, the way the immediate path's + has_logged dedupe keeps the first fired task, so the spend log reads usage from the + innermost provider-shaped response and never from an outer wrapper's translation of it.""" + logging_obj: Final = MagicMock() + logging_obj._defer_async_logging = True + logging_obj._enqueue_deferred_logging = None + logging_obj.async_success_handler = AsyncMock() + inner_result: Final = object() + outer_result: Final = object() + + for result in (inner_result, outer_result): + _dispatch_success_logging( + logging_obj=logging_obj, + result=result, + start_time=datetime.now(), + end_time=datetime.now(), + is_completion_with_fallbacks=False, + is_litellm_internal_call=False, + ) + + logging_obj._enqueue_deferred_logging() + await _wait_until(lambda: logging_obj.async_success_handler.await_count > 0) + + logging_obj.async_success_handler.assert_awaited_once() + assert logging_obj.async_success_handler.await_args.kwargs["result"] is inner_result + assert logging_obj.handle_sync_success_callbacks_for_async_calls.call_count == 2 + + +@pytest.mark.asyncio +async def test_deferred_anthropic_messages_bridged_to_the_responses_api_logs_the_provider_usage( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch +): + """/v1/messages on an Azure gpt-5.4+ deployment with function tools runs three nested + wrappers: anthropic_messages, the chat adapter's acompletion, and the Responses bridge + acompletion hands the call to, which retags the call as ``responses``. With logging + deferred for a post-call guardrail the stored closure must carry the innermost provider + response: logging the Anthropic-shaped reply under Responses semantics books this + 7,336-token prompt as 3 tokens, since Anthropic's input_tokens excludes the cache hit.""" + monkeypatch.setattr(litellm, "disable_aiohttp_transport", True) + monkeypatch.setenv("DISABLE_AIOHTTP_TRANSPORT", "True") + litellm.in_memory_llm_clients_cache.flush_cache() + respx_mock.post(url__regex=r"https://deferred-nested\.openai\.azure\.com/openai/.*responses.*").mock( + return_value=httpx.Response( + 200, + json={ + "id": "resp_deferred_nested", + "object": "response", + "created_at": 1, + "status": "completed", + "model": "gpt-5.4-nano", + "output": [ + { + "type": "message", + "id": "msg_deferred_nested", + "status": "completed", + "role": "assistant", + "content": [{"type": "output_text", "text": "Hello!", "annotations": []}], + } + ], + "usage": { + "input_tokens": 7336, + "input_tokens_details": {"cached_tokens": 7333}, + "output_tokens": 23, + "output_tokens_details": {"reasoning_tokens": 0}, + "total_tokens": 7359, + }, + }, + ) + ) + recorder: Final = _RecordingLogger() + logging_obj: Final = Logging( + model="azure/gpt-5.4-nano", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type="anthropic_messages", + start_time=datetime.now(), + litellm_call_id="deferred-nested-anthropic-messages", + function_id="deferred-nested-anthropic-messages", + dynamic_async_success_callbacks=[recorder], + ) + logging_obj._defer_async_logging = True + + response: Final = await litellm.anthropic_messages( + model="azure/gpt-5.4-nano", + messages=[{"role": "user", "content": "hi"}], + max_tokens=16, + tools=[ + { + "name": "lookup_volume", + "description": "Look up a storage volume by name", + "input_schema": {"type": "object", "properties": {"name": {"type": "string"}}, "required": ["name"]}, + } + ], + api_key="sk-deferred-nested", + api_base="https://deferred-nested.openai.azure.com", + api_version="2025-04-01-preview", + litellm_logging_obj=logging_obj, + ) + assert response["content"] == [{"type": "text", "text": "Hello!"}] + assert response["usage"]["input_tokens"] == 3 + assert response["usage"]["cache_read_input_tokens"] == 7333 + + logging_obj._enqueue_deferred_logging() + await _wait_until(lambda: recorder.standard_logging_object is not None) + + assert recorder.standard_logging_object is not None + assert recorder.standard_logging_object["prompt_tokens"] == 7336 + assert recorder.standard_logging_object["metadata"]["usage_object"]["prompt_tokens_details"]["cached_tokens"] == 7333 + assert recorder.standard_logging_object["response_cost"] == pytest.approx(3 * 2e-7 + 7333 * 2e-8 + 23 * 1.25e-6) + + # --------------------------------------------------------------------------- # 3. Non-streaming regression: without flag, create_task fires normally # --------------------------------------------------------------------------- diff --git a/tests/test_litellm/proxy/guardrails/test_init_guardrails.py b/tests/test_litellm/proxy/guardrails/test_init_guardrails.py index ceb084b4a4d..8377db57b6e 100644 --- a/tests/test_litellm/proxy/guardrails/test_init_guardrails.py +++ b/tests/test_litellm/proxy/guardrails/test_init_guardrails.py @@ -71,6 +71,52 @@ def test_initialize_bedrock_forwards_chunk_budget_chars(): assert initialized[-1].chunk_budget_chars == 60_000 +def test_initialize_bedrock_forwards_contextual_grounding_from_messages(): + """`contextual_grounding_from_messages: true` in config.yaml must make the post-call + payload carry the plain system prompt and user turn as grounding_source and query.""" + import litellm + from litellm.proxy.guardrails.guardrail_hooks.bedrock_guardrails import BedrockGuardrail + from litellm.types.utils import Choices, Message, ModelResponse + + test_guardrail = { + "guardrail_name": "test_bedrock_grounding_from_messages", + "litellm_params": { + "guardrail": SupportedGuardrailIntegrations.BEDROCK.value, + "mode": "post_call", + "guardrailIdentifier": "test-guardrail", + "guardrailVersion": "DRAFT", + "contextual_grounding_from_messages": True, + }, + } + messages = [ + {"role": "system", "content": "Returns are accepted for 30 days."}, + {"role": "user", "content": "How long is the return window?"}, + ] + response = ModelResponse( + choices=[Choices(index=0, message=Message(role="assistant", content="30 days."), finish_reason="stop")] + ) + expected_request = { + "source": "OUTPUT", + "content": [ + {"text": {"text": "Returns are accepted for 30 days.", "qualifiers": ["grounding_source"]}}, + {"text": {"text": "How long is the return window?", "qualifiers": ["query"]}}, + {"text": {"text": "30 days.", "qualifiers": ["guard_content"]}}, + ], + } + + guardrail_handler = InMemoryGuardrailHandler() + guardrail_handler.initialize_guardrail(guardrail=test_guardrail) + + initialized = [ + callback + for callback in litellm.callbacks + if isinstance(callback, BedrockGuardrail) and callback.guardrail_name == "test_bedrock_grounding_from_messages" + ] + assert initialized, "bedrock guardrail was not registered as a callback" + actual_request = initialized[-1].convert_to_bedrock_format(source="OUTPUT", response=response, messages=messages) + assert json.loads(json.dumps(actual_request)) == expected_request + + def test_initialize_guardrail_preserves_guardrail_info(): """ Regression (LIT-2529): initialize_guardrail must carry guardrail_info into the diff --git a/tests/test_litellm/proxy/guardrails/test_prompt_security_guardrails.py b/tests/test_litellm/proxy/guardrails/test_prompt_security_guardrails.py index e650f796f29..3218632a8d2 100644 --- a/tests/test_litellm/proxy/guardrails/test_prompt_security_guardrails.py +++ b/tests/test_litellm/proxy/guardrails/test_prompt_security_guardrails.py @@ -1,5 +1,6 @@ import asyncio import base64 +from collections.abc import Mapping, Sequence from unittest.mock import AsyncMock, patch import pytest @@ -12,6 +13,7 @@ from litellm.proxy.guardrails.guardrail_hooks.prompt_security.prompt_security im PromptSecurityGuardrailMissingSecrets, ) from litellm.proxy.guardrails.init_guardrails import init_guardrails_v2 +from litellm.types.llms.openai import AllMessageValues def test_prompt_security_guard_config(monkeypatch: pytest.MonkeyPatch): @@ -174,6 +176,123 @@ async def test_apply_guardrail_modify_request(monkeypatch: pytest.MonkeyPatch): assert result["texts"] == ["User prompt with PII: SSN [REDACTED]"] +def _modify_response(modified_messages: Sequence[Mapping[str, object]]) -> Response: + mock_response = Response( + json={"result": {"prompt": {"action": "modify", "modified_messages": modified_messages}}}, + status_code=200, + request=Request(method="POST", url="https://test.prompt.security/api/protect"), + ) + mock_response.raise_for_status = lambda: None + return mock_response + + +def _tool_replay_messages() -> list[AllMessageValues]: + return [ + {"role": "system", "content": "Never echo an SSN like 123-45-6789."}, + { + "role": "user", + "content": [ + {"type": "text", "text": "Look up 123-45-6789"}, + {"type": "image_url", "image_url": {"url": "https://example.com/id-card.png"}}, + ], + }, + { + "role": "assistant", + "content": None, + "tool_calls": [ + {"id": "call_1", "type": "function", "function": {"name": "lookup", "arguments": "{}"}} + ], + }, + {"role": "tool", "tool_call_id": "call_1", "content": '{"ssn": "123-45-6789"}'}, + {"role": "user", "content": "Summarize what you found."}, + ] + + +@pytest.mark.asyncio +async def test_modify_returns_structured_messages_with_tool_rows_kept(monkeypatch: pytest.MonkeyPatch): + """A per-message modify verdict comes back as structured_messages so the + endpoint handler can write it back by message, with the rows Prompt Security + never saw (tool results) and the non-text parts (images) left in place.""" + monkeypatch.setenv("PROMPT_SECURITY_API_KEY", "test-key") + monkeypatch.setenv("PROMPT_SECURITY_API_BASE", "https://test.prompt.security") + guardrail = PromptSecurityGuardrail(guardrail_name="test-guard", event_hook="pre_call", default_on=True) + messages = _tool_replay_messages() + inputs = {"texts": ["Look up 123-45-6789", "Summarize what you found."], "structured_messages": messages} + modified_messages = [ + {"role": "system", "content": "Never echo an SSN like [REDACTED]."}, + {"role": "user", "content": [{"type": "text", "text": "Look up [REDACTED]"}]}, + {"role": "assistant", "content": None}, + {"role": "user", "content": "Summarize what you found."}, + ] + + with patch.object(guardrail.async_handler, "post", return_value=_modify_response(modified_messages)): + result = await guardrail.apply_guardrail( + inputs=inputs, request_data={"messages": messages}, input_type="request" + ) + + assert result["structured_messages"] == [ + {"role": "system", "content": "Never echo an SSN like [REDACTED]."}, + { + "role": "user", + "content": [ + {"type": "text", "text": "Look up [REDACTED]"}, + {"type": "image_url", "image_url": {"url": "https://example.com/id-card.png"}}, + ], + }, + messages[2], + messages[3], + {"role": "user", "content": "Summarize what you found."}, + ] + assert result["structured_messages"] is not messages + assert result["texts"] == [ + "Never echo an SSN like [REDACTED].", + "Look up [REDACTED]", + "Summarize what you found.", + ] + + +@pytest.mark.asyncio +async def test_modify_with_unexpected_message_count_keeps_texts_only(monkeypatch: pytest.MonkeyPatch): + monkeypatch.setenv("PROMPT_SECURITY_API_KEY", "test-key") + monkeypatch.setenv("PROMPT_SECURITY_API_BASE", "https://test.prompt.security") + guardrail = PromptSecurityGuardrail(guardrail_name="test-guard", event_hook="pre_call", default_on=True) + messages = _tool_replay_messages() + inputs = {"texts": ["Look up 123-45-6789", "Summarize what you found."], "structured_messages": messages} + modified_messages = [{"role": "user", "content": "Look up [REDACTED]"}] + + with patch.object(guardrail.async_handler, "post", return_value=_modify_response(modified_messages)): + result = await guardrail.apply_guardrail( + inputs=inputs, request_data={"messages": messages}, input_type="request" + ) + + assert result["structured_messages"] is messages + assert result["texts"] == ["Look up [REDACTED]"] + + +@pytest.mark.asyncio +async def test_modify_keeps_empty_text_parts_as_slots(monkeypatch: pytest.MonkeyPatch): + """The chat handler counts an empty text part as a slot, so a modify verdict + that echoes the empty part still lines up with the row and its texts.""" + monkeypatch.setenv("PROMPT_SECURITY_API_KEY", "test-key") + monkeypatch.setenv("PROMPT_SECURITY_API_BASE", "https://test.prompt.security") + guardrail = PromptSecurityGuardrail(guardrail_name="test-guard", event_hook="pre_call", default_on=True) + messages: list[AllMessageValues] = [ + {"role": "user", "content": [{"type": "text", "text": "Look up 123-45-6789"}, {"type": "text", "text": ""}]} + ] + inputs = {"texts": ["Look up 123-45-6789", ""], "structured_messages": messages} + modified_messages = [ + {"role": "user", "content": [{"type": "text", "text": "Look up [REDACTED]"}, {"type": "text", "text": ""}]} + ] + + with patch.object(guardrail.async_handler, "post", return_value=_modify_response(modified_messages)): + result = await guardrail.apply_guardrail( + inputs=inputs, request_data={"messages": messages}, input_type="request" + ) + + assert result["structured_messages"] == modified_messages + assert result["texts"] == ["Look up [REDACTED]", ""] + + @pytest.mark.asyncio async def test_apply_guardrail_allow_request(monkeypatch: pytest.MonkeyPatch): """Test that apply_guardrail allows safe prompts""" @@ -497,6 +616,98 @@ async def test_file_sanitization_modify_can_rewrite_when_blocking_disabled(monke assert base64.b64decode(result["file"]["data"]) == b"name,email\nAlice,[REDACTED]\n" +@pytest.mark.asyncio +async def test_file_sanitization_keeps_polling_through_queued_statuses(monkeypatch: pytest.MonkeyPatch): + monkeypatch.setenv("PROMPT_SECURITY_API_KEY", "test-key") + monkeypatch.setenv("PROMPT_SECURITY_API_BASE", "https://test.prompt.security") + + guardrail = PromptSecurityGuardrail(guardrail_name="test-guard", event_hook="pre_call", default_on=True) + guardrail.poll_interval = 0 + upload_response = Response( + json={"jobId": "queued-job"}, + status_code=200, + request=Request(method="POST", url="https://test.prompt.security/api/sanitizeFile"), + ) + poll_request = Request(method="GET", url="https://test.prompt.security/api/sanitizeFile") + poll_responses = [ + Response(json={"status": "created"}, status_code=200, request=poll_request), + Response(json={"status": "in progress"}, status_code=200, request=poll_request), + Response( + json={"status": "done", "content": "clean", "metadata": {"action": "allow", "violations": []}}, + status_code=200, + request=poll_request, + ), + ] + + with patch.object(guardrail.async_handler, "post", AsyncMock(return_value=upload_response)): + with patch.object(guardrail.async_handler, "get", AsyncMock(side_effect=poll_responses)) as poll_mock: + result = await guardrail.sanitize_file_content(b"image-content", "image.png") + + assert poll_mock.await_count == 3 + assert result["action"] == "allow" + assert result["content"] == "clean" + + +@pytest.mark.asyncio +async def test_file_sanitization_never_finishing_job_times_out(monkeypatch: pytest.MonkeyPatch): + monkeypatch.setenv("PROMPT_SECURITY_API_KEY", "test-key") + monkeypatch.setenv("PROMPT_SECURITY_API_BASE", "https://test.prompt.security") + + guardrail = PromptSecurityGuardrail( + guardrail_name="test-guard", event_hook="pre_call", default_on=True, file_sanitization_fail_open=False + ) + guardrail.poll_interval = 0 + guardrail.max_poll_attempts = 3 + upload_response = Response( + json={"jobId": "stuck-job"}, + status_code=200, + request=Request(method="POST", url="https://test.prompt.security/api/sanitizeFile"), + ) + poll_response = Response( + json={"status": "created"}, + status_code=200, + request=Request(method="GET", url="https://test.prompt.security/api/sanitizeFile"), + ) + + with patch.object(guardrail.async_handler, "post", AsyncMock(return_value=upload_response)): + with patch.object(guardrail.async_handler, "get", AsyncMock(return_value=poll_response)) as poll_mock: + with pytest.raises(HTTPException) as exc_info: + await guardrail.sanitize_file_content(b"file-content", "document.pdf") + + assert poll_mock.await_count == 3 + assert exc_info.value.status_code == 408 + assert exc_info.value.detail == "File sanitization timeout" + + +@pytest.mark.asyncio +@pytest.mark.parametrize("poll_body", [{"status": "failed"}, {}]) +async def test_file_sanitization_terminal_failure_does_not_fail_open(monkeypatch: pytest.MonkeyPatch, poll_body): + monkeypatch.setenv("PROMPT_SECURITY_API_KEY", "test-key") + monkeypatch.setenv("PROMPT_SECURITY_API_BASE", "https://test.prompt.security") + + guardrail = PromptSecurityGuardrail(guardrail_name="test-guard", event_hook="pre_call", default_on=True) + guardrail.poll_interval = 0 + upload_response = Response( + json={"jobId": "failed-job"}, + status_code=200, + request=Request(method="POST", url="https://test.prompt.security/api/sanitizeFile"), + ) + poll_response = Response( + json=poll_body, + status_code=200, + request=Request(method="GET", url="https://test.prompt.security/api/sanitizeFile"), + ) + + with patch.object(guardrail.async_handler, "post", AsyncMock(return_value=upload_response)): + with patch.object(guardrail.async_handler, "get", AsyncMock(return_value=poll_response)) as poll_mock: + with pytest.raises(HTTPException) as exc_info: + await guardrail.sanitize_file_content(b"file-content", "document.pdf") + + assert poll_mock.await_count == 1 + assert exc_info.value.status_code == 500 + assert exc_info.value.detail == f"Unexpected sanitization status: {poll_body.get('status')}" + + @pytest.mark.asyncio @pytest.mark.parametrize( "timeout", diff --git a/tests/test_litellm/proxy/guardrails/test_usage_endpoints.py b/tests/test_litellm/proxy/guardrails/test_usage_endpoints.py index 644b213d3a3..db87e12ac88 100644 --- a/tests/test_litellm/proxy/guardrails/test_usage_endpoints.py +++ b/tests/test_litellm/proxy/guardrails/test_usage_endpoints.py @@ -682,3 +682,67 @@ async def test_detail_prev_trend_query_is_bounded(): prev_wheres = [w for w in wheres if "lt" in w.get("date", {})] assert prev_wheres assert all("gte" in w["date"] for w in prev_wheres) + + +@pytest.mark.asyncio +async def test_logs_report_not_run_entries_as_not_run_not_passed(): + """LIT-6314: a guardrail that never scanned must not be reported as a pass in the drill-down.""" + index_row = MagicMock() + index_row.request_id = "req-nr" + index_row.guardrail_id = "db-1" + index_row.start_time = datetime(2026, 4, 22) + spend_log = MagicMock() + spend_log.request_id = "req-nr" + spend_log.model = "gpt-4o-mini" + spend_log.startTime = datetime(2026, 4, 22) + spend_log.metadata = { + "guardrail_information": [ + {"guardrail_name": "db-1", "guardrail_status": "not_run", "duration": 0.0}, + ] + } + prisma = _prisma(find_unique=_db_row(), index_find_many=[index_row]) + prisma.db.litellm_spendlogs.find_many = AsyncMock(return_value=[spend_log]) + handler = _config_handler() + p1, p2 = _patches(prisma, handler) + with p1, p2: + resp = await guardrails_usage_logs( + guardrail_id="db-1", + policy_id=None, + page=1, + page_size=50, + action=None, + start_date=START, + end_date=END, + user_api_key_dict=ADMIN, + ) + assert [log.action for log in resp.logs] == ["not_run"] + + +@pytest.mark.asyncio +async def test_logs_action_passed_filter_excludes_not_run_entries(): + """LIT-6314: filtering the drill-down for passes must not return unscanned requests.""" + index_row = MagicMock() + index_row.request_id = "req-nr" + index_row.guardrail_id = "db-1" + index_row.start_time = datetime(2026, 4, 22) + spend_log = MagicMock() + spend_log.request_id = "req-nr" + spend_log.model = "gpt-4o-mini" + spend_log.startTime = datetime(2026, 4, 22) + spend_log.metadata = {"guardrail_information": [{"guardrail_name": "db-1", "guardrail_status": "not_run"}]} + prisma = _prisma(find_unique=_db_row(), index_find_many=[index_row]) + prisma.db.litellm_spendlogs.find_many = AsyncMock(return_value=[spend_log]) + handler = _config_handler() + p1, p2 = _patches(prisma, handler) + with p1, p2: + resp = await guardrails_usage_logs( + guardrail_id="db-1", + policy_id=None, + page=1, + page_size=50, + action="passed", + start_date=START, + end_date=END, + user_api_key_dict=ADMIN, + ) + assert resp.logs == [] diff --git a/tests/test_litellm/proxy/guardrails/test_usage_tracking.py b/tests/test_litellm/proxy/guardrails/test_usage_tracking.py index 110de7dbe70..69ec098b840 100644 --- a/tests/test_litellm/proxy/guardrails/test_usage_tracking.py +++ b/tests/test_litellm/proxy/guardrails/test_usage_tracking.py @@ -6,6 +6,7 @@ from unittest.mock import AsyncMock, MagicMock import httpx import pytest +from litellm.proxy.guardrails import usage_tracking from litellm.proxy.guardrails.usage_tracking import ( _MAX_PENDING_ROWS, PendingRollups, @@ -348,6 +349,95 @@ async def test_zero_and_non_int_usage_counters_are_skipped(): } +@pytest.mark.asyncio +async def test_not_run_entries_are_indexed_but_not_counted_as_evaluations(): + """ + LIT-6314 records a not_run entry when message scoping leaves a guardrail + nothing to scan. The guardrail never evaluated the request, so counting it + as a passed evaluation would inflate daily pass rates; it still gets an + index row so per-request drill-down finds the spend log. + """ + prisma = _prisma() + logs = [_payload("r1", guardrail_status="not_run"), _payload("r2")] + + await process_spend_logs_guardrail_usage(prisma, logs) + + metrics_create = prisma.db.litellm_dailyguardrailmetrics.upsert.call_args.kwargs["data"]["create"] + assert metrics_create["requests_evaluated"] == 1 + assert metrics_create["passed_count"] == 1 + index_rows = prisma.db.litellm_spendlogguardrailindex.create_many.call_args.kwargs["data"] + assert sorted(row["request_id"] for row in index_rows) == ["r1", "r2"] + + +@pytest.mark.asyncio +async def test_not_run_entry_shares_index_key_with_evaluated_sibling_of_same_name(): + """ + The not_run entry from the shared base guardrail carries only guardrail_name, + while the evaluated entry from the same guardrail (e.g. content filter on the + output of a logging_only run) carries its guardrail_id. Keying them differently + lists one request twice in the monitor, once as not_run and once as passed. + """ + prisma = _prisma() + payload = _payload("r1") + payload["metadata"] = json.dumps( + { + "guardrail_information": [ + {"guardrail_name": "cf", "guardrail_status": "not_run"}, + { + "guardrail_name": "cf", + "guardrail_id": "cf-uuid", + "policy_id": "pol-1", + "guardrail_status": "success", + }, + {"guardrail_name": "other", "guardrail_status": "not_run"}, + ] + } + ) + + await process_spend_logs_guardrail_usage(prisma, [payload]) + + index_rows = prisma.db.litellm_spendlogguardrailindex.create_many.call_args.kwargs["data"] + assert sorted((row["guardrail_id"], row["policy_id"]) for row in index_rows) == [ + ("cf-uuid", "pol-1"), + ("other", None), + ] + metrics_create = prisma.db.litellm_dailyguardrailmetrics.upsert.call_args.kwargs["data"]["create"] + assert (metrics_create["guardrail_id"], metrics_create["requests_evaluated"]) == ("cf-uuid", 1) + + +@pytest.mark.asyncio +async def test_malformed_not_run_entry_does_not_drop_the_batch(): + prisma = _prisma() + payload = _payload("r1") + payload["metadata"] = json.dumps( + { + "guardrail_information": [ + {"guardrail_name": ["not", "a", "string"], "guardrail_status": "success"}, + {"guardrail_name": "", "guardrail_id": "cf-uuid", "guardrail_status": "success"}, + {"guardrail_status": "success"}, + ] + } + ) + + await process_spend_logs_guardrail_usage(prisma, [payload]) + + index_rows = prisma.db.litellm_spendlogguardrailindex.create_many.call_args.kwargs["data"] + assert [row["guardrail_id"] for row in index_rows] == ["cf-uuid"] + metrics_create = prisma.db.litellm_dailyguardrailmetrics.upsert.call_args.kwargs["data"]["create"] + assert (metrics_create["guardrail_id"], metrics_create["requests_evaluated"]) == ("cf-uuid", 1) + + +@pytest.mark.asyncio +async def test_batch_of_only_not_run_entries_writes_no_metrics_row(): + prisma = _prisma() + + await process_spend_logs_guardrail_usage(prisma, [_payload("r1", guardrail_status="not_run")]) + + assert prisma.db.litellm_dailyguardrailmetrics.upsert.call_count == 0 + index_rows = prisma.db.litellm_spendlogguardrailindex.create_many.call_args.kwargs["data"] + assert [row["request_id"] for row in index_rows] == ["r1"] + + @pytest.mark.asyncio async def test_payload_without_request_id_is_skipped_like_the_metrics_path(): prisma = _prisma() @@ -511,3 +601,56 @@ async def test_requeued_cost_is_added_to_the_next_flush(): costs = _cost_upserts(recovered) assert costs["contentPolicyUnits"] == (pytest.approx(0.45), 0) assert costs["someFutureCounter"] == (0.0, 7) + + +def _fan_out_payload(request_id: str, guardrail_ids: tuple[str, ...]) -> dict[str, Any]: + return { + "request_id": request_id, + "startTime": datetime(2026, 8, 17, 12, 0, tzinfo=timezone.utc), + "team_id": "team-a", + "api_key": "hashed-key-1", + "metadata": json.dumps( + {"guardrail_information": [{"guardrail_id": gid, "guardrail_status": "success"} for gid in guardrail_ids]} + ), + } + + +def _index_rows_written(prisma: MagicMock) -> list[tuple[str, str]]: + return [ + (row["request_id"], row["guardrail_id"]) + for call in prisma.db.litellm_spendlogguardrailindex.create_many.call_args_list + for row in call.kwargs["data"] + ] + + +@pytest.mark.asyncio +async def test_index_rows_are_written_in_row_bounded_statements(monkeypatch): + """ + LIT-5931: the drain caps logs, not logs x guardrails, so a fan-out must be + split into statements the query engine can afford instead of one create_many. + """ + monkeypatch.setattr(usage_tracking, "SPEND_LOG_WRITE_BATCH_MAX_ROWS", 100) + prisma = _prisma() + guardrail_ids = tuple(f"guard-{i}" for i in range(50)) + logs = [_fan_out_payload(f"r{i}", guardrail_ids) for i in range(5)] + + await process_spend_logs_guardrail_usage(prisma, logs, pending=PendingRollups()) + + statements = prisma.db.litellm_spendlogguardrailindex.create_many.call_args_list + assert [len(call.kwargs["data"]) for call in statements] == [100, 100, 50] + assert all(call.kwargs["skip_duplicates"] is True for call in statements) + assert _index_rows_written(prisma) == [(f"r{i}", gid) for i in range(5) for gid in guardrail_ids] + + +@pytest.mark.asyncio +async def test_one_failing_index_statement_does_not_drop_the_others_or_the_rollup(monkeypatch): + monkeypatch.setattr(usage_tracking, "SPEND_LOG_WRITE_BATCH_MAX_ROWS", 100) + prisma = _prisma() + prisma.db.litellm_spendlogguardrailindex.create_many.side_effect = [None, httpx.ReadTimeout("ambiguous"), None] + guardrail_ids = tuple(f"guard-{i}" for i in range(50)) + logs = [_fan_out_payload(f"r{i}", guardrail_ids) for i in range(5)] + + await process_spend_logs_guardrail_usage(prisma, logs, pending=PendingRollups()) + + assert prisma.db.litellm_spendlogguardrailindex.create_many.await_count == 3 + assert prisma.db.litellm_dailyguardrailmetrics.upsert.await_count == len(guardrail_ids) diff --git a/tests/test_litellm/proxy/health_endpoints/test_health_endpoints.py b/tests/test_litellm/proxy/health_endpoints/test_health_endpoints.py index 1ab50cc30de..761cd0685f2 100644 --- a/tests/test_litellm/proxy/health_endpoints/test_health_endpoints.py +++ b/tests/test_litellm/proxy/health_endpoints/test_health_endpoints.py @@ -1195,6 +1195,61 @@ async def test_health_services_endpoint_newrelic_allows_proxy_admin(admin_role): mock_instance.async_health_check.assert_awaited_once() +@pytest.mark.asyncio +@pytest.mark.parametrize( + "role", + [ + None, + LitellmUserRoles.INTERNAL_USER, + LitellmUserRoles.INTERNAL_USER_VIEW_ONLY, + LitellmUserRoles.TEAM, + LitellmUserRoles.CUSTOMER, + ], +) +async def test_health_services_endpoint_webhook_blocks_non_admin(role): + """ + /health/services?service=webhook fires a real budget_crossed alert for the + caller's user_id and writes the same dedup cache entry the auth-time user + budget alert uses, so a non-admin could suppress their own real alert for + the cache TTL. Only proxy admins may trigger it. + """ + mock_proxy_logging = MagicMock() + mock_proxy_logging.budget_alerts = AsyncMock() + user_api_key_dict = UserAPIKeyAuth(token="non-admin-token", user_id="non-admin-user", user_role=role) + + with patch( # test-quality-ok: endpoint reads proxy_server module globals, same pattern as sibling tests + "litellm.proxy.proxy_server.proxy_logging_obj", + mock_proxy_logging, + ): + with pytest.raises(ProxyException) as exc_info: + await health_services_endpoint(user_api_key_dict=user_api_key_dict, service="webhook") + + assert str(exc_info.value.code) == "403" + mock_proxy_logging.budget_alerts.assert_not_awaited() + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "admin_role", + [LitellmUserRoles.PROXY_ADMIN, LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY], +) +async def test_health_services_endpoint_webhook_allows_proxy_admin(admin_role): + mock_proxy_logging = MagicMock() + mock_proxy_logging.budget_alerts = AsyncMock() + user_api_key_dict = UserAPIKeyAuth(token="admin-token", user_id="admin-user", user_role=admin_role) + + with patch( # test-quality-ok: endpoint reads proxy_server module globals, same pattern as sibling tests + "litellm.proxy.proxy_server.proxy_logging_obj", + mock_proxy_logging, + ): + await health_services_endpoint(user_api_key_dict=user_api_key_dict, service="webhook") + + mock_proxy_logging.budget_alerts.assert_awaited_once() + sent = mock_proxy_logging.budget_alerts.await_args.kwargs + assert sent["type"] == "user_budget" + assert sent["user_info"].user_id == "admin-user" + + @pytest.fixture(scope="function") def proxy_client(monkeypatch): """ diff --git a/tests/test_litellm/proxy/hooks/test_parallel_request_limiter_v3.py b/tests/test_litellm/proxy/hooks/test_parallel_request_limiter_v3.py index 10c0bb88a82..48f980086fd 100644 --- a/tests/test_litellm/proxy/hooks/test_parallel_request_limiter_v3.py +++ b/tests/test_litellm/proxy/hooks/test_parallel_request_limiter_v3.py @@ -6284,3 +6284,248 @@ async def test_an_open_circuit_breaker_reads_the_sliding_window_locally_without_ assert isinstance(values, list) assert [record.getMessage() for record in caplog.records if record.levelno >= logging.WARNING] == [] assert any("circuit breaker is open" in record.getMessage() for record in caplog.records) + + +@pytest.mark.parametrize( + "limits, request_data, counter_scope", + [ + ({"rpm_limit": 1}, {}, "api_key"), + ({"user_id": "u", "user_rpm_limit": 1}, {}, "user"), + ({"team_id": "t", "team_rpm_limit": 1}, {}, "team"), + ( + {"team_id": "t", "user_id": "u", "team_member_rpm_limit": 1}, + {}, + "team_member", + ), + ({"end_user_id": "e", "end_user_rpm_limit": 1}, {}, "end_user"), + ( + {"metadata": {"model_rpm_limit": {"test-model": 1}}}, + {}, + "model_per_key", + ), + ( + {"metadata": {"tag_rpm_limit": {"test-tag": 1}}}, + {"metadata": {"tags": ["test-tag"]}}, + "tag_per_key", + ), + ( + { + "team_id": "t", + "metadata": {"model_rpm_limit": {"test-model": 100}}, + "team_metadata": {"model_rpm_limit": {"test-model": 1}}, + }, + {}, + "model_per_team", + ), + ( + {"project_id": "p", "project_metadata": {"model_rpm_limit": {"test-model": 1}}}, + {}, + "model_per_project", + ), + ({"org_id": "o", "organization_rpm_limit": 1}, {}, "organization"), + ( + {"org_id": "o", "organization_metadata": {"model_rpm_limit": {"test-model": 1}}}, + {}, + "model_per_organization", + ), + ], +) +@pytest.mark.parametrize("request_kind", ["count", "generation"]) +@pytest.mark.asyncio +async def test_request_capacity_enforces_shared_rpm_scopes( + limits, request_data, counter_scope, request_kind +): + cache = DualCache() + handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(cache)) + auth = UserAPIKeyAuth(api_key=hash_token("sk-count-rpm"), **limits) + async def request(): + if request_kind == "generation": + await handler.async_pre_call_hook( + user_api_key_dict=auth, + cache=cache, + data={**request_data, "model": "test-model"}, + call_type="acompletion", + ) + return + async with handler.request_capacity(auth, "test-model", request_data=request_data): + pass + + await request() + with pytest.raises(HTTPException) as exc: + await request() + assert exc.value.status_code == 429 + assert counter_scope in str(exc.value.detail) + + +@pytest.mark.asyncio +async def test_request_capacity_keeps_dynamic_rpm_policy(monkeypatch): + import litellm.proxy.proxy_server as proxy_server + + router = Router(model_list=[{ + "model_name": "test-model", + "litellm_params": {"model": "openai/gpt-test", "api_key": "test-key"}, + "model_info": {"id": "test-deployment"}, + }]) + monkeypatch.setattr(proxy_server, "llm_router", router) + handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(DualCache())) + auth = UserAPIKeyAuth( + api_key=hash_token("sk-count-dynamic"), + rpm_limit=1, + metadata={"rpm_limit_type": "dynamic"}, + ) + for _ in range(2): + async with handler.request_capacity(auth, "test-model"): + pass + router.cache.set_cache("test-deployment:fails", 100, ttl=60, local_only=True) + async with handler.request_capacity(auth, "test-model"): + pass + with pytest.raises(HTTPException) as exc: + async with handler.request_capacity(auth, "test-model"): + pytest.fail("dynamic RPM must enforce after deployment failures") + assert exc.value.status_code == 429 + + +@pytest.mark.asyncio +async def test_request_capacity_skips_tokens_and_preserves_parent_stash(): + cache = DualCache() + handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(cache)) + auth = UserAPIKeyAuth( + api_key=hash_token("sk-count-tpm"), + rpm_limit=5, + tpm_limit=1, + max_parallel_requests=1, + project_id="p", + project_metadata={ + "model_tpm_limit": {"test-model": 1}, + "model_itpm_limit": {"test-model": 1}, + "model_otpm_limit": {"test-model": 1}, + }, + ) + token_scopes = ( + ("api_key", auth.api_key), + ("model_per_project", "p:test-model"), + ("model_per_project_itpm", "p:test-model"), + ("model_per_project_otpm", "p:test-model"), + ) + for scope, value in token_scopes: + token_key = handler.create_rate_limit_keys(scope, value, "tokens") + await cache.async_set_cache(token_key, 100, ttl=60) + await cache.async_set_cache(f"{{{scope}:{value}}}:window", int(time.time()), ttl=60) + parent = get_or_create_request_stash() + parent.reserved_tokens = 123 + parent.parallel_slot = ParallelSlotAcquisition(slot_id="parent", counter_keys=["parent-gauge"]) + for _ in range(2): + async with handler.request_capacity(auth, "test-model"): + assert get_request_stash() is parent + assert parent.parallel_slot["slot_id"] == "parent" + assert parent.reserved_tokens == 123 + for scope, value in token_scopes: + assert await cache.async_get_cache(handler.create_rate_limit_keys(scope, value, "tokens")) == 100 + + +@pytest.mark.parametrize("exit_mode", ["success", "failure", "cancel"]) +@pytest.mark.asyncio +async def test_request_capacity_releases_exact_parallel_slot(exit_mode): + cache = DualCache() + handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(cache)) + auth = UserAPIKeyAuth(api_key=hash_token("sk-count-parallel"), max_parallel_requests=1) + entered = asyncio.Event() + finish = asyncio.Event() + + async def provider(): + async with handler.request_capacity(auth, "test-model"): + entered.set() + await finish.wait() + if exit_mode == "failure": + raise RuntimeError("provider failed") + + task = asyncio.create_task(provider()) + await asyncio.wait_for(entered.wait(), timeout=2) + try: + for _ in range(2): + with pytest.raises(HTTPException) as exc: + async with handler.request_capacity(auth, "test-model"): + pytest.fail("rejected request freed the occupied slot") + assert exc.value.status_code == 429 + finally: + if exit_mode == "cancel": + task.cancel() + else: + finish.set() + if exit_mode == "success": + await task + else: + with pytest.raises(asyncio.CancelledError if exit_mode == "cancel" else RuntimeError): + await task + async with handler.request_capacity(auth, "test-model"): + pass + + +class _DelayedCapacityUsageCache: + def __init__(self): + self.delegate = InternalUsageCache(DualCache()) + self.dual_cache = self.delegate.dual_cache + self.acquired = asyncio.Event() + self.finish_admission = asyncio.Event() + self.releasing = asyncio.Event() + self.finish_release = asyncio.Event() + + async def async_get_cache(self, *args, **kwargs): + return await self.delegate.async_get_cache(*args, **kwargs) + + async def async_batch_get_cache(self, *args, **kwargs): + return await self.delegate.async_batch_get_cache(*args, **kwargs) + + async def async_set_cache(self, key, value, **kwargs): + await self.delegate.async_set_cache(key=key, value=value, **kwargs) + if not key.endswith(":max_parallel_requests"): + return + if value: + self.acquired.set() + await self.finish_admission.wait() + else: + self.releasing.set() + await self.finish_release.wait() + + +@pytest.mark.asyncio +async def test_request_capacity_finishes_admission_and_release_despite_repeated_cancel(): + cache = _DelayedCapacityUsageCache() + handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=cache) + auth = UserAPIKeyAuth(api_key=hash_token("sk-count-cancel-admission"), max_parallel_requests=1) + + async def provider(): + async with handler.request_capacity(auth, "test-model"): + pytest.fail("cancelled admission entered provider body") + + task = asyncio.create_task(provider()) + await asyncio.wait_for(cache.acquired.wait(), timeout=2) + task.cancel() + await asyncio.sleep(0) + cache.finish_admission.set() + await asyncio.wait_for(cache.releasing.wait(), timeout=2) + task.cancel() + await asyncio.sleep(0) + task.cancel() + await asyncio.sleep(0) + assert not task.done() + cache.finish_release.set() + with pytest.raises(asyncio.CancelledError): + await asyncio.wait_for(task, timeout=2) + async with handler.request_capacity(auth, "test-model"): + pass + + +@pytest.mark.asyncio +async def test_request_capacity_rejection_keeps_existing_redis_mirror(): + cache = DualCache() + handler = _PROXY_MaxParallelRequestsHandler(internal_usage_cache=InternalUsageCache(cache)) + auth = UserAPIKeyAuth(api_key=hash_token("sk-count-mirror"), max_parallel_requests=1) + counter_key = handler.create_rate_limit_keys("api_key", auth.api_key, "max_parallel_requests") + await cache.async_set_cache(counter_key, 1, ttl=60, local_only=True) + for _ in range(2): + with pytest.raises(HTTPException) as exc: + async with handler.request_capacity(auth, "test-model"): + pytest.fail("rejection released another request's mirrored slot") + assert exc.value.status_code == 429 + assert await cache.async_get_cache(counter_key, local_only=True) == 1 diff --git a/tests/test_litellm/proxy/hooks/test_prompt_cache_observer.py b/tests/test_litellm/proxy/hooks/test_prompt_cache_observer.py new file mode 100644 index 00000000000..82af3e9a6ef --- /dev/null +++ b/tests/test_litellm/proxy/hooks/test_prompt_cache_observer.py @@ -0,0 +1,300 @@ +import asyncio +import json +import time +from datetime import datetime + +import httpx +import pytest + +import litellm +from litellm.caching.dual_cache import DualCache +from litellm.llms.anthropic.chat.transformation import AnthropicConfig +from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler +from litellm.llms.anthropic.prompt_cache_prediction import cache_scope, parse_prompt +from litellm.proxy.hooks.prompt_cache_prediction import ( + PromptCacheObserver, + lookup, +) +from litellm.proxy.utils import InternalUsageCache +from litellm.types.utils import ModelResponse + +MODEL = "claude-sonnet-5" +CALLER = "a" * 64 +DEPLOYMENT = "native-deployment" +KEY = "test-provider-key" + + +def body(ttl="5m", texts=("private cache prefix",)): + return { + "model": MODEL, + "max_tokens": 2, + "system": "private system instructions", + "tools": [{"name": "lookup", "input_schema": {"type": "object"}}], + "messages": [{"role": "user", "content": [ + {"type": "text", "text": text, **( + {"cache_control": {"type": "ephemeral", "ttl": ttl}} + if index == len(texts) - 1 else {} + )} + for index, text in enumerate(texts) + ]}], + } + + +def usage(ttl="5m", read=100, write=200): + return { + "input_tokens": 11, + "output_tokens": 2, + "cache_read_input_tokens": read, + "cache_creation_input_tokens": write, + "cache_creation": { + "ephemeral_5m_input_tokens": write if ttl == "5m" else 0, + "ephemeral_1h_input_tokens": write if ttl == "1h" else 0, + }, + } + + +def event(request_body, started=1000.0, headers=None, **overrides): + request = httpx.Request( + "POST", "https://api.anthropic.com/v1/messages", json=request_body, + headers={"x-api-key": KEY, "anthropic-version": "2023-06-01", **(headers or {})}, + ) + return { + "call_type": "anthropic_messages", + "custom_llm_provider": "anthropic", + "cache_hit": False, + "httpx_response": httpx.Response(200, request=request), + "first_api_call_start_time": datetime.fromtimestamp(started), + "standard_logging_object": { + "status": "success", "model_id": DEPLOYMENT, + "metadata": {"user_api_key_hash": CALLER}, + }, + **overrides, + } + + +async def observe(cache, request_body=None, native_usage=None, now=1010.0, **overrides): + observer = PromptCacheObserver(InternalUsageCache(dual_cache=cache), clock=lambda: now) + response = ModelResponse( + model=MODEL, + usage=AnthropicConfig().calculate_usage(native_usage or usage(), reasoning_content=None), + ) + await observer.async_log_success_event( + event(request_body or body(), **overrides), response, + datetime.fromtimestamp(now), datetime.fromtimestamp(now), + ) + + +def scope(**overrides): + return cache_scope(**{ + "caller_key_hash": CALLER, "deployment_id": DEPLOYMENT, + "provider_key": KEY, "model": MODEL, **overrides, + }) + + +@pytest.mark.parametrize("ttl,expires", [("5m", 1300), ("1h", 4600)]) +@pytest.mark.asyncio +async def test_observed_cache_count_and_request_start_expiry_survive_as_stale(ttl, expires): + cache = DualCache() + request_body = body(ttl=ttl) + await observe(cache, request_body, usage(ttl=ttl)) + prefix = parse_prompt(request_body) + observed = await lookup(cache, scope(), prefix, now=1200) + assert observed.cached_tokens == 300 + assert observed.observed_at == 1010 + assert observed.expires_at == expires + assert await lookup(cache, scope(), prefix, now=expires) == observed + saved = json.dumps(cache.in_memory_cache.cache_dict) + assert "private cache prefix" not in saved + assert "private system instructions" not in saved + assert KEY not in saved + assert CALLER not in saved + + +@pytest.mark.parametrize("changed", [ + {"caller_key_hash": "b" * 64}, {"deployment_id": "other"}, + {"provider_key": "rotated"}, {"model": "claude-opus-5"}, + {"anthropic_version": "different"}, +]) +@pytest.mark.asyncio +async def test_cache_evidence_is_isolated_by_every_scope_dimension(changed): + cache = DualCache() + await observe(cache) + assert await lookup(cache, scope(**changed), parse_prompt(body()), now=1010) is None + + +@pytest.mark.asyncio +async def test_append_only_prefix_finds_prior_evidence_but_edit_or_context_change_does_not(): + cache = DualCache() + await observe(cache) + extended = parse_prompt(body(texts=("private cache prefix", "new turn"))) + prior = await lookup(cache, scope(), extended, now=1010) + assert prior.cached_tokens == 300 + assert prior.fingerprint != extended.fingerprint + for changed in ( + body(texts=("edited prefix", "new turn")), + {**body(), "system": "different system"}, + {**body(), "tools": [{"name": "other", "input_schema": {"type": "object"}}]}, + body(ttl="1h"), + ): + assert await lookup(cache, scope(), parse_prompt(changed), now=1010) is None + outside_lookback = parse_prompt(body(texts=("private cache prefix", *[str(i) for i in range(20)]))) + assert await lookup(cache, scope(), outside_lookback, now=1010) is None + + +@pytest.mark.parametrize("change", [ + {"thinking": {"type": "enabled", "budget_tokens": 1024}}, + {"tool_choice": {"type": "auto"}}, + {"cache_control": {"type": "ephemeral"}}, + {"tools": [{"type": "web_search_20250305", "name": "web_search"}]}, + {"system": [{"type": "text", "text": "system", "cache_control": {"type": "ephemeral"}}]}, + {"messages": [{"role": "user", "content": [{"type": "image", "source": {}}]}]}, + {"messages": [{"role": "user", "content": "no breakpoint"}]}, +]) +def test_unsupported_or_ambiguous_shapes_have_no_cache_identity(change): + assert parse_prompt({**body(), **change}) is None + duplicate = body() + duplicate["messages"][0]["content"].append(duplicate["messages"][0]["content"][0]) + assert parse_prompt(duplicate) is None + + +@pytest.mark.parametrize("overrides", [ + {"cache_hit": True}, {"call_type": "completion"}, + {"custom_llm_provider": "bedrock"}, {"stream": True}, + {"headers": {"anthropic-beta": "unverified-feature"}}, + {"headers": {"x-custom-header": "unverified"}}, + {"standard_logging_object": {"status": "success", "model_id": DEPLOYMENT, "metadata": {}}}, +]) +@pytest.mark.asyncio +async def test_unverified_source_never_creates_observations(overrides): + cache = DualCache() + await observe(cache, **overrides) + assert await lookup(cache, scope(), parse_prompt(body()), now=1010) is None + + +@pytest.mark.parametrize("native_usage", [ + usage(write=0), + {**usage(), "cache_creation": None}, + {**usage(), "cache_creation": {"ephemeral_5m_input_tokens": 199, "ephemeral_1h_input_tokens": 0}}, + usage(ttl="1h"), + {**usage(), "cache_creation_input_tokens": -200}, +]) +@pytest.mark.asyncio +async def test_missing_or_contradictory_telemetry_cannot_create_observations(native_usage): + cache = DualCache() + await observe(cache, native_usage=native_usage) + assert await lookup(cache, scope(), parse_prompt(body()), now=1010) is None + + +@pytest.mark.asyncio +async def test_pure_read_refresh_requires_prior_matching_evidence(): + cache = DualCache() + await observe(cache, native_usage=usage(read=300, write=0)) + assert await lookup(cache, scope(), parse_prompt(body()), now=1010) is None + await observe(cache) + await observe(cache, native_usage=usage(read=300, write=0), started=1100, now=1110) + assert (await lookup(cache, scope(), parse_prompt(body()), now=1110)).expires_at == 1400 + + +class RecordingObserver(PromptCacheObserver): + def __init__(self, cache): + super().__init__(InternalUsageCache(dual_cache=cache)) + self.finished = asyncio.Event() + + async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): + await super().async_log_success_event(kwargs, response_obj, start_time, end_time) + self.finished.set() + + +def native_response(): + return { + "id": "msg_prediction", "type": "message", "role": "assistant", "model": MODEL, + "content": [{"type": "text", "text": "ok"}], "stop_reason": "end_turn", + "stop_sequence": None, "usage": usage(ttl="1h"), + } + + +def stream_response(completed, provider_error=False): + response = native_response() + events = [ + {"type": "message_start", "message": {**response, "content": [], "stop_reason": None}}, + {"type": "content_block_start", "index": 0, "content_block": {"type": "text", "text": ""}}, + {"type": "content_block_delta", "index": 0, "delta": {"type": "text_delta", "text": "ok"}}, + {"type": "content_block_stop", "index": 0}, + {"type": "message_delta", "delta": {"stop_reason": "end_turn"}, "usage": {"output_tokens": 2}}, + ] + if completed: + events.append({"type": "message_stop"}) + if provider_error: + events.append({"type": "error", "error": {"type": "overloaded_error", "message": "temporary failure"}}) + return "".join(f"event: {item['type']}\ndata: {json.dumps(item)}\n\n" for item in events) + + +class TransportChunks(httpx.AsyncByteStream): + def __init__(self, payload, chunk_size, fragment_error_only=False): + self.payload = payload.encode() + self.chunk_size = chunk_size or len(self.payload) + self.prefix_length = self.payload.index(b"event: error") if fragment_error_only else 0 + + async def __aiter__(self): + if self.prefix_length: + yield self.payload[:self.prefix_length] + for offset in range(self.prefix_length, len(self.payload), self.chunk_size): + yield self.payload[offset:offset + self.chunk_size] + + +@pytest.mark.parametrize("stream,completed,provider_error,transport", [ + (False, True, False, "whole"), + (True, True, False, "whole"), + (True, False, False, "whole"), + (True, True, True, "whole"), + (True, True, False, "fragmented"), + (True, False, False, "fragmented"), + (True, True, True, "fragmented"), + (True, True, True, "fragmented_error"), + (True, True, False, "unterminated"), +]) +@pytest.mark.asyncio +async def test_native_production_callback_records_only_completed_wire_requests(stream, completed, provider_error, transport): + cache = DualCache() + observer = RecordingObserver(cache) + litellm.logging_callback_manager.add_litellm_callback(observer) + + def provider(request): + if stream: + payload = stream_response(completed, provider_error) + if transport == "unterminated": + payload = payload.removesuffix("\n\n") + return httpx.Response( + 200, request=request, headers={"content-type": "text/event-stream"}, + stream=TransportChunks( + payload, 1 if transport.startswith("fragmented") else None, + fragment_error_only=transport == "fragmented_error", + ), + ) + return httpx.Response(200, request=request, json=native_response()) + + client = AsyncHTTPHandler() + await client.client.aclose() + client.client = httpx.AsyncClient(transport=httpx.MockTransport(provider)) + try: + request_body = body(ttl="1h") + before = time.time() + result = await litellm.anthropic_messages( + **{**request_body, "model": f"anthropic/{MODEL}"}, + api_key=KEY, client=client, stream=stream, model_info={"id": DEPLOYMENT}, + litellm_metadata={"user_api_key_hash": CALLER, "model_info": {"id": DEPLOYMENT}}, + ) + if stream: + async for _ in result: + pass + await asyncio.wait_for(observer.finished.wait(), timeout=5) + found = await lookup(cache, scope(), parse_prompt(request_body)) + if completed and not provider_error and transport != "unterminated": + assert found is not None + assert found.cached_tokens == 300 + assert before + 3600 <= found.expires_at <= time.time() + 3600 + else: + assert found is None + finally: + litellm.logging_callback_manager.remove_callback_from_all_lists(observer) + await client.client.aclose() diff --git a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py index fad137af66b..395ce68ec54 100644 --- a/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py +++ b/tests/test_litellm/proxy/hooks/test_proxy_track_cost_callback.py @@ -19,6 +19,7 @@ from litellm.proxy.hooks.proxy_track_cost_callback import ( run_spend_event, ) from litellm.proxy.route_llm_request import ProxyModelNotFoundError +from litellm.proxy.utils import ProxyUpdateSpend from litellm.proxy.spend_tracking.spend_event import SpendEventDecodeError, build_spend_event, decode_spend_event from litellm.proxy.spend_tracking.spend_event_producer import SpendEventProducer, UnixAddress from litellm.proxy.spend_tracking.spend_tracking_utils import get_logging_payload @@ -1912,14 +1913,15 @@ async def test_track_cost_callback_keeps_guardrail_cost_on_cache_hit(): ("allm_passthrough_route", True), ("aretrieve_batch", True), ("acompletion", False), - ("call_mcp_tool", False), + ("call_mcp_tool", True), (None, False), ], ) def test_should_track_cost_callback_pass_through_without_owner(call_type, expected): """Regression for LIT-3782: unauthenticated pass-through requests (auth=false) carry no key/user/team/end-user, yet must still be tracked so they land in - LiteLLM_SpendLogs. Other call types with no owner stay untracked. + LiteLLM_SpendLogs. Explicit MCP passthrough calls require the same handling. + Other call types with no owner stay untracked. aretrieve_batch is included for the same reason: CheckBatchCost's synthetic logging_obj for a completed managed batch only ever carries @@ -1939,10 +1941,26 @@ def test_should_track_cost_callback_pass_through_without_owner(call_type, expect ) +def test_should_track_cost_callback_respects_disabled_spend_updates(monkeypatch): + monkeypatch.setattr(ProxyUpdateSpend, "disable_spend_updates", staticmethod(lambda: True)) + + assert ( + _should_track_cost_callback( + user_api_key="key", + user_id="user", + team_id="team", + end_user_id="end-user", + call_type="call_mcp_tool", + ) + is False + ) + + @pytest.mark.parametrize( "call_type, expect_spend_log", [ ("pass_through_endpoint", True), + ("call_mcp_tool", True), ("aretrieve_batch", True), ("acompletion", False), (None, False), @@ -1953,8 +1971,8 @@ async def test_track_cost_callback_logs_unauthenticated_pass_through_request(cal """Regression for LIT-3782: a pass-through request with auth=false reaches the cost callback with no key/user/team/end-user. Before the fix the spend-log write was skipped and the request never appeared in request/usage logs. It - must now be written for pass-through call types while other unauthenticated - calls remain skipped. + must now be written for pass-through and MCP tool call types while other + unauthenticated calls remain skipped. aretrieve_batch is included because CheckBatchCost's completed-batch cost event reaches this same callback with no attributable key/user/team when diff --git a/tests/test_litellm/proxy/management_endpoints/test_common_daily_activity.py b/tests/test_litellm/proxy/management_endpoints/test_common_daily_activity.py index 6cd900cb041..71896a18f48 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_common_daily_activity.py +++ b/tests/test_litellm/proxy/management_endpoints/test_common_daily_activity.py @@ -613,6 +613,7 @@ def test_key_metadata_includes_recovered_user_email(): "dirty-key": { "key_alias": "batch-worker", "team_id": "team-1", + "user_id": "alice", "user_email": "alice@example.com", } }, @@ -620,6 +621,7 @@ def test_key_metadata_includes_recovered_user_email(): ) assert meta.key_alias == "batch-worker" + assert meta.user_id == "alice" assert meta.user_email == "alice@example.com" @@ -848,9 +850,11 @@ async def test_aggregated_activity_preserves_metadata_for_deleted_keys(): mock_deleted_key.token = "deleted-key-hash" mock_deleted_key.key_alias = "toto-test-2" mock_deleted_key.team_id = "69cd4b77-b095-4489-8c46-4f2f31d840a2" + mock_deleted_key.user_id = "deleted-key-owner" mock_prisma.db.litellm_deletedverificationtoken = MagicMock() mock_prisma.db.litellm_deletedverificationtoken.find_many = AsyncMock(return_value=[mock_deleted_key]) + mock_prisma.db.litellm_usertable.find_many = AsyncMock(return_value=[]) result = await get_daily_activity_aggregated( prisma_client=mock_prisma, @@ -871,6 +875,7 @@ async def test_aggregated_activity_preserves_metadata_for_deleted_keys(): key_data = chat_endpoint.api_key_breakdown["deleted-key-hash"] assert key_data.metadata.key_alias == "toto-test-2" assert key_data.metadata.team_id == "69cd4b77-b095-4489-8c46-4f2f31d840a2" + assert key_data.metadata.user_id == "deleted-key-owner" assert key_data.metrics.spend == 10.0 diff --git a/tests/test_litellm/proxy/management_endpoints/test_common_utils.py b/tests/test_litellm/proxy/management_endpoints/test_common_utils.py index da8fc760787..7352ca0e9ee 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_common_utils.py +++ b/tests/test_litellm/proxy/management_endpoints/test_common_utils.py @@ -8,6 +8,10 @@ users can intentionally clear previously-set fields. """ from datetime import datetime, timezone +from types import SimpleNamespace + +from fastapi import HTTPException +from litellm import Router from unittest.mock import AsyncMock, MagicMock, patch import pytest @@ -1120,3 +1124,41 @@ class TestUpdateMetadataFieldsPremiumCheck: } _update_metadata_fields(updated_kv) mock_check.assert_called() + + +@pytest.mark.asyncio +@pytest.mark.parametrize("db_model,stored_name,owner,public_name,error", [ + (False, None, None, None, None), + (True, "group", None, None, None), + (True, None, None, None, "Unknown deployment ID in router weights: id"), + (False, "renamed", None, None, "Deployment id does not belong to model group group"), + (False, None, "other-team", None, "Unknown deployment ID in router weights: id"), + (True, "internal", "team", "group", None), + (True, "group", "team", "public", "Deployment id does not belong to model group group"), + (True, "group", None, "unrelated-public-name", None), +]) +async def test_router_weights_validate_current_deployment_scope( + db_model: bool, stored_name: str | None, owner: str | None, + public_name: str | None, error: str | None, +) -> None: + from litellm.proxy.management_endpoints.router_weights import validate_router_settings_weights + + info = {"team_id": owner, "team_public_model_name": public_name} + router = Router(model_list=[{ + "model_name": "group", + "litellm_params": {"model": "openai/gpt-5.4-mini", "api_key": "test"}, + "model_info": {"id": "id", "db_model": db_model, **info}, + }]) + rows = [SimpleNamespace(model_id="id", model_name=stored_name, model_info=info)] if stored_name else [] + table = SimpleNamespace(find_many=AsyncMock(return_value=rows)) + db = SimpleNamespace(db=SimpleNamespace(litellm_proxymodeltable=table)) + validation = validate_router_settings_weights( + {"weights": {"group": {"id": 1}}}, team_id="team", prisma_client=db, llm_router=router, + ) + if error: + with pytest.raises(HTTPException, match=error) as exc: + await validation + assert exc.value.status_code == 400 + assert exc.value.detail == error + else: + await validation diff --git a/tests/test_litellm/proxy/management_endpoints/test_compliance_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_compliance_endpoints.py index dcbe515d5de..8382a5ada96 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_compliance_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_compliance_endpoints.py @@ -2,10 +2,8 @@ Unit tests for compliance check endpoints (EU AI Act and GDPR). """ - import pytest - from litellm.proxy.compliance_checks import ComplianceChecker from litellm.types.proxy.compliance_endpoints import ComplianceCheckRequest @@ -591,3 +589,37 @@ class TestModeMatching: continue if matched: assert mode in _guaranteed_modes(g_mode), (g_mode, mode) + + +class TestNotRunGuardrails: + """LIT-6314 logs a not_run entry for a guardrail that message scoping left nothing to scan.""" + + def test_not_run_alone_never_evidences_compliance(self): + data = ComplianceCheckRequest( + request_id="req-601", + user_id="user-1", + model="gpt-4", + timestamp="2026-02-17T00:00:00Z", + guardrail_information=[ + {"guardrail_name": "pii_detection", "guardrail_status": "not_run", "guardrail_mode": "pre_call"}, + ], + ) + results = {c.check_name: c.passed for c in ComplianceChecker(data).check_eu_ai_act()} + assert results["Guardrails applied"] is False + assert results["Content screened before LLM"] is False + assert results["Audit record complete"] is False + + def test_not_run_sibling_does_not_fail_a_passing_request(self): + data = ComplianceCheckRequest( + request_id="req-602", + user_id="user-1", + model="gpt-4", + timestamp="2026-02-17T00:00:00Z", + pii_detected=True, + guardrail_information=[ + {"guardrail_name": "pii_detection", "guardrail_status": "success", "guardrail_mode": "pre_call"}, + {"guardrail_name": "system_only", "guardrail_status": "not_run", "guardrail_mode": "pre_call"}, + ], + ) + results = {c.check_name: c.passed for c in ComplianceChecker(data).check_gdpr()} + assert results["Sensitive data protected"] is True diff --git a/tests/test_litellm/proxy/management_endpoints/test_cost_tracking_settings.py b/tests/test_litellm/proxy/management_endpoints/test_cost_tracking_settings.py index 7ece35ceedf..c73d29e78b2 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_cost_tracking_settings.py +++ b/tests/test_litellm/proxy/management_endpoints/test_cost_tracking_settings.py @@ -975,8 +975,9 @@ class TestEstimateCostCacheAndReasoningTokens: @pytest.mark.asyncio async def test_a_model_without_cache_or_reasoning_prices_estimates_what_the_proxy_bills(self, monkeypatch): - """The cost calculator bills cache tokens of a cost-map model without cache prices at zero - and its reasoning tokens at the output rate. The estimate reports those effective rates.""" + """The cost calculator bills cache reads of a cost-map model without cache prices at zero, + its cache writes at the input rate, and its reasoning tokens at the output rate. The estimate + reports those effective rates.""" monkeypatch.setitem( litellm.model_cost, A_MAPPED_MODEL, @@ -986,12 +987,14 @@ class TestEstimateCostCacheAndReasoningTokens: response = await _estimate_with_cache_and_reasoning(None, model=A_MAPPED_MODEL) assert response.cache_read_cost_per_request == 0.0 - assert response.cache_creation_cost_per_request == 0.0 + assert response.cache_creation_cost_per_request == pytest.approx(CACHE_CREATION_TOKENS * 5e-6) assert response.reasoning_cost_per_request == pytest.approx(REASONING_TOKENS * 6e-6) - assert response.input_cost_per_request == pytest.approx(TEXT_INPUT_TOKENS * 5e-6) - assert response.cost_per_request == pytest.approx(TEXT_INPUT_TOKENS * 5e-6 + OUTPUT_TOKENS * 6e-6) + assert response.input_cost_per_request == pytest.approx((TEXT_INPUT_TOKENS + CACHE_CREATION_TOKENS) * 5e-6) + assert response.cost_per_request == pytest.approx( + (TEXT_INPUT_TOKENS + CACHE_CREATION_TOKENS) * 5e-6 + OUTPUT_TOKENS * 6e-6 + ) assert response.cache_read_input_token_cost == 0.0 - assert response.cache_creation_input_token_cost == 0.0 + assert response.cache_creation_input_token_cost == pytest.approx(5e-6) assert response.output_cost_per_reasoning_token == pytest.approx(6e-6) @pytest.mark.asyncio diff --git a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py index df58424095f..c590a24203c 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_key_management_endpoints.py @@ -1,6 +1,7 @@ from collections.abc import Mapping from contextlib import ExitStack from typing import Final +from types import SimpleNamespace import json from datetime import datetime, timedelta, timezone @@ -22,6 +23,7 @@ from litellm.proxy._types import ( LiteLLM_ObjectPermissionBase, LiteLLM_OrganizationTable, LiteLLM_ProjectTableCachedObj, + LiteLLM_TeamTable, LiteLLM_TeamTableCachedObj, LiteLLM_UserTable, LiteLLM_VerificationToken, @@ -6423,7 +6425,7 @@ def test_build_key_filter_conditions_key_alias_narrows_team_admin_visibility(): admin_team_ids=["team-a"], member_team_ids=["team-a"], include_created_by_keys=False, - use_substring_matching=True, + use_key_alias_substring_matching=True, ) assert {"key_alias": {"contains": "member-key", "mode": "insensitive"}} in where_substring["AND"], ( f"substring key_alias not ANDed: {where_substring}" @@ -6623,6 +6625,9 @@ async def test_generate_key_with_router_settings(monkeypatch): return_value=[] ) mock_prisma_client.db.litellm_verificationtoken.count = AsyncMock(return_value=0) + mock_prisma_client.db.litellm_proxymodeltable.find_many = AsyncMock(return_value=[ + SimpleNamespace(model_id="weighted-id", model_name="gpt-4", model_info={}) + ]) monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma_client) @@ -6638,6 +6643,7 @@ async def test_generate_key_with_router_settings(monkeypatch): "routing_strategy": "usage-based", "num_retries": 3, "model_group_retry_policy": {"gpt-4": {"RateLimitErrorRetries": 5}}, + "weights": {"gpt-4": {"weighted-id": 1}}, } request_data = GenerateKeyRequest( @@ -6687,21 +6693,37 @@ async def test_generate_key_with_router_settings(monkeypatch): # Verify router_settings matches input (regardless of serialization state) assert actual_settings == router_settings_data + mock_prisma_client.insert_data.reset_mock() + with pytest.raises(ProxyException, match="Unknown deployment ID"): + await generate_key_fn( + data=GenerateKeyRequest(router_settings={"weights": {"gpt-4": {"unknown-id": 1}}}), + user_api_key_dict=UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN, user_id="user-router-1"), + ) + mock_prisma_client.insert_data.assert_not_awaited() @pytest.mark.asyncio -async def test_update_key_with_router_settings(monkeypatch): +@pytest.mark.parametrize("request_type", [UpdateKeyRequest, RegenerateKeyRequest]) +@pytest.mark.parametrize("target_team", ["new-team", None]) +async def test_update_key_with_router_settings( + monkeypatch: pytest.MonkeyPatch, + request_type: type[UpdateKeyRequest | RegenerateKeyRequest], target_team: str | None, +) -> None: """ Test that /key/update correctly handles router_settings by: 1. Accepting router_settings as a dict parameter 2. Serializing router_settings to JSON when updating database 3. Updating router_settings in the key record """ - from litellm.proxy._types import LiteLLM_VerificationToken, UpdateKeyRequest + from litellm.proxy._types import LiteLLM_VerificationToken from litellm.proxy.management_endpoints.key_management_endpoints import ( prepare_key_update_data, ) + model = SimpleNamespace(model_id="weighted-id", model_name="gpt-4", model_info={}) + table = SimpleNamespace(find_many=AsyncMock(return_value=[model])) + db = SimpleNamespace(db=SimpleNamespace(litellm_proxymodeltable=table)) + # Mock existing key existing_key = LiteLLM_VerificationToken( token="test-token-router", @@ -6718,14 +6740,16 @@ async def test_update_key_with_router_settings(monkeypatch): router_settings_data = { "routing_strategy": "latency-based", "num_retries": 2, + "weights": {"gpt-4": {"weighted-id": 1}}, } - update_request = UpdateKeyRequest( + update_request = request_type( key="test-token-router", router_settings=router_settings_data ) result = await prepare_key_update_data( - data=update_request, existing_key_row=existing_key + data=update_request, existing_key_row=existing_key, + prisma_client=db, llm_router=None, ) # Verify router_settings is serialized to JSON string @@ -6736,6 +6760,28 @@ async def test_update_key_with_router_settings(monkeypatch): deserialized_settings = json.loads(result["router_settings"]) assert deserialized_settings == router_settings_data + with pytest.raises(HTTPException, match="Unknown deployment ID"): + await prepare_key_update_data( + request_type(key=existing_key.token, router_settings={"weights": {"gpt-4": {"unknown-id": 1}}}), + existing_key, + prisma_client=db, llm_router=None, + ) + existing_key.team_id = "old-team" + existing_key.router_settings = router_settings_data + move = request_type(key=existing_key.token, team_id=target_team) + retained = await prepare_key_update_data(move, existing_key, prisma_client=db, llm_router=None) + assert retained["team_id"] == target_team + assert "router_settings" not in retained + model.model_info = {"team_id": "old-team"} + with pytest.raises(HTTPException, match="Unknown deployment ID"): + await prepare_key_update_data(move, existing_key, prisma_client=db, llm_router=None) + cleared = await prepare_key_update_data( + request_type(key=existing_key.token, team_id=target_team, router_settings={}), existing_key, + prisma_client=db, llm_router=None, + ) + assert cleared["team_id"] == target_team + assert json.loads(cleared["router_settings"]) == {} + @pytest.mark.asyncio async def test_validate_max_budget(): @@ -9368,7 +9414,7 @@ async def test_build_key_filter_team_id_scoped(): async def test_build_key_filter_admin_substring_matching(): """ Admin callers get substring (contains + insensitive) matching for user_id - and key_alias when use_substring_matching=True. + and key_alias when both substring flags are set. """ from litellm.proxy.management_endpoints.key_management_endpoints import ( _build_key_filter_conditions, @@ -9388,6 +9434,7 @@ async def test_build_key_filter_admin_substring_matching(): member_team_ids=None, include_created_by_keys=False, use_substring_matching=True, + use_key_alias_substring_matching=True, ) assert where["AND"][0]["user_id"] == {"contains": user_id, "mode": "insensitive"} @@ -16165,8 +16212,8 @@ async def test_list_keys_admin_substring_opt_in(): @pytest.mark.asyncio async def test_list_keys_non_admin_cannot_opt_into_substring(): - """substring_matching is admin-only: a non-admin requesting it still gets - exact matching, scoped to their own user_id.""" + """user_id substring matching is admin-only: a non-admin requesting it still + gets exact matching, scoped to their own user_id.""" user = UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER, user_id="alice") kwargs = await _list_keys_capture_helper_kwargs( user, user_id=None, substring_matching=True @@ -16175,6 +16222,108 @@ async def test_list_keys_non_admin_cannot_opt_into_substring(): assert kwargs["user_id"] == "alice" +def _prisma_where_matches(row, where): + for field, expected in where.items(): + if field == "AND": + if not all(_prisma_where_matches(row, child) for child in expected): + return False + elif field == "OR": + if not any(_prisma_where_matches(row, child) for child in expected): + return False + elif isinstance(expected, dict): + value = getattr(row, field) + if "in" in expected and value not in expected["in"]: + return False + if "not" in expected and value == expected["not"]: + return False + if "contains" in expected: + haystack, needle = value or "", expected["contains"] + if expected.get("mode") == "insensitive": + haystack, needle = haystack.lower(), needle.lower() + if needle not in haystack: + return False + elif getattr(row, field) != expected: + return False + return True + + +class _InMemoryVerificationTokenTable: + def __init__(self, rows): + self.rows = rows + + async def find_many(self, where, **kwargs): + return [row for row in self.rows if _prisma_where_matches(row, where)] + + async def count(self, where): + return len(await self.find_many(where)) + + +def _team_key(token, key_alias, user_id): + return LiteLLM_VerificationToken(token=token, key_alias=key_alias, user_id=user_id, team_id="team-a") + + +_TEAM_A_KEYS = ( + _team_key("tok-alice-first", "app_llmhub_first.last", "alice"), + _team_key("tok-alice-other", "alice_other_key", "alice"), + _team_key("tok-bob-first", "bob_First_key", "bob"), + _team_key("tok-svc-first", "service_first_key", None), +) + + +def _list_team_a_keys_as(user_role, members_with_roles, query): + from fastapi import FastAPI + + from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + from litellm.proxy.management_endpoints.key_management_endpoints import router + + mock_prisma_client = AsyncMock() + mock_prisma_client.db.litellm_verificationtoken = _InMemoryVerificationTokenTable(_TEAM_A_KEYS) + mock_prisma_client.db.litellm_usertable.find_unique = AsyncMock( + return_value=LiteLLM_UserTable(user_id="alice", teams=["team-a"], organization_memberships=[]) + ) + mock_prisma_client.db.litellm_teamtable.find_many = AsyncMock( + return_value=[LiteLLM_TeamTable(team_id="team-a", members_with_roles=members_with_roles)] + ) + test_app = FastAPI() + test_app.include_router(router) + test_app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth(user_role=user_role, user_id="alice") + with patch( # test-quality-ok: /key/list reads the prisma client from the proxy_server module global, no injection point + "litellm.proxy.proxy_server.prisma_client", mock_prisma_client + ): + response = TestClient(test_app).get( + f"/key/list?team_id=team-a&include_team_keys=true&include_created_by_keys=true&{query}" + ) + assert response.status_code == 200, response.text + return sorted(response.json()["keys"]) + + +_ALICE_TEAM_ADMIN = [Member(user_id="alice", role="admin"), Member(user_id="bob", role="user")] +_ALICE_TEAM_MEMBER = [Member(user_id="alice", role="user"), Member(user_id="bob", role="user")] + + +@pytest.mark.parametrize( + "user_role", + [LitellmUserRoles.INTERNAL_USER, LitellmUserRoles.INTERNAL_USER_VIEW_ONLY, LitellmUserRoles.TEAM], +) +def test_list_keys_team_admin_key_alias_substring_returns_every_matching_team_key(user_role): + keys = _list_team_a_keys_as(user_role, _ALICE_TEAM_ADMIN, "key_alias=first&substring_matching=true") + assert keys == ["tok-alice-first", "tok-bob-first", "tok-svc-first"] + + +def test_list_keys_team_member_key_alias_substring_stays_within_own_visibility(): + keys = _list_team_a_keys_as( + LitellmUserRoles.INTERNAL_USER, _ALICE_TEAM_MEMBER, "key_alias=first&substring_matching=true" + ) + assert keys == ["tok-alice-first", "tok-svc-first"] + + +def test_list_keys_key_alias_stays_exact_without_substring_matching(): + assert _list_team_a_keys_as(LitellmUserRoles.INTERNAL_USER, _ALICE_TEAM_ADMIN, "key_alias=first") == [] + assert _list_team_a_keys_as( + LitellmUserRoles.INTERNAL_USER, _ALICE_TEAM_ADMIN, "key_alias=app_llmhub_first.last" + ) == ["tok-alice-first"] + + @pytest.mark.asyncio async def test_list_keys_search_is_honored_for_non_admin(): """LIT-4741: unlike substring_matching, `search` is not admin-gated. A non-admin's diff --git a/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py index c66095dc1fd..c3ad66397ea 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_model_management_endpoints.py @@ -3666,6 +3666,204 @@ class TestUpdateDBModelClearPricing: assert info["cache_creation_input_token_cost"] == 0.000003 +class TestModelInfoServerDerivedPricingFilter: + """LIT-5292. `/model/info` fills a deployment's missing pricing in from the cost map + so the Admin UI has a rate to display. Clients echo that whole blob back on save, so + without a write-path filter an unrelated edit persists the display value as a real + per-deployment override and no cost map refresh can move the deployment again. + + A deployment's own pricing rides `litellm_params`, which stays writable. + """ + + def test_echoed_cost_map_pricing_is_not_persisted(self): + """The ticket's repro: a deployment with no override, edited for an unrelated + reason, must not gain one from the pricing the form was displaying.""" + from litellm.proxy.management_endpoints.model_management_endpoints import ( + update_db_model, + ) + from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo + + db_model = Deployment( + model_name="haiku", + litellm_params=LiteLLM_Params(model="bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0"), + model_info=ModelInfo(id="dep-unpriced-0"), + ) + + result = update_db_model( + db_model=db_model, + updated_patch=updateDeployment( + model_info=ModelInfo( + id="dep-unpriced-0", + access_groups=["prod"], + input_cost_per_token=0.0000008, + output_cost_per_token=0.000004, + cache_read_input_token_cost=0.00000008, + ) + ), + ) + + info = json.loads(result["model_info"]) + params = json.loads(result["litellm_params"]) + assert info["access_groups"] == ["prod"] + for field in ("input_cost_per_token", "output_cost_per_token", "cache_read_input_token_cost"): + assert field not in info, f"{field} was persisted as a per-deployment override" + assert field not in params + + def test_tiered_above_threshold_pricing_is_dropped(self): + """Tiered rates ride `get_model_info` on a pattern match and are declared on no + model, so a filter built only from the declared pricing fields would miss them.""" + from litellm.proxy.management_endpoints.model_management_endpoints import ( + update_db_model, + ) + from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo + + db_model = Deployment( + model_name="sonnet", + litellm_params=LiteLLM_Params(model="claude-sonnet-4-5"), + model_info=ModelInfo(id="dep-tiered-0"), + ) + + result = update_db_model( + db_model=db_model, + updated_patch=updateDeployment( + model_info=ModelInfo( + id="dep-tiered-0", + input_cost_per_token_above_200k_tokens=0.000006, + cache_creation_input_token_cost_above_1hr_above_200k_tokens=0.000012, + ) + ), + ) + + info = json.loads(result["model_info"]) + assert "input_cost_per_token_above_200k_tokens" not in info + assert "cache_creation_input_token_cost_above_1hr_above_200k_tokens" not in info + + def test_output_vector_size_and_client_owned_fields_survive(self): + """`output_vector_size` sits on the pricing model but is an embedding dimension, + not a rate. It and the operator-owned keys stay writable.""" + from litellm.proxy.management_endpoints.model_management_endpoints import ( + update_db_model, + ) + from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo + + db_model = Deployment( + model_name="embed", + litellm_params=LiteLLM_Params(model="openai/text-embedding-3-large"), + model_info=ModelInfo(id="dep-embed-0"), + ) + + result = update_db_model( + db_model=db_model, + updated_patch=updateDeployment( + model_info=ModelInfo( + id="dep-embed-0", + output_vector_size=3072, + base_model="azure/text-embedding-3-large", + tier="paid", + team_id="team-1", + access_groups=["research"], + my_custom_key="my_custom_value", + ) + ), + ) + + info = json.loads(result["model_info"]) + assert info["output_vector_size"] == 3072 + assert info["base_model"] == "azure/text-embedding-3-large" + assert info["tier"] == "paid" + assert info["team_id"] == "team-1" + assert info["access_groups"] == ["research"] + assert info["my_custom_key"] == "my_custom_value" + + def test_litellm_params_pricing_still_persists(self): + """The supported way to set a deployment override is untouched.""" + from litellm.proxy.management_endpoints.model_management_endpoints import ( + update_db_model, + ) + from litellm.types.router import ( + Deployment, + LiteLLM_Params, + ModelInfo, + updateLiteLLMParams, + ) + + db_model = Deployment( + model_name="haiku", + litellm_params=LiteLLM_Params(model="bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0"), + model_info=ModelInfo(id="dep-priced-0"), + ) + + result = update_db_model( + db_model=db_model, + updated_patch=updateDeployment( + litellm_params=updateLiteLLMParams(input_cost_per_token=0.00000123), + model_info=ModelInfo(id="dep-priced-0", input_cost_per_token=0.0000008), + ), + ) + + params = json.loads(result["litellm_params"]) + assert params["input_cost_per_token"] == 0.00000123 + + @pytest.mark.asyncio + async def test_add_new_model_drops_echoed_pricing_and_keeps_identity(self): + """The create path filters too, and rebuilding the blob must not mint a fresh id + or flip `db_model`, which would detach the row from its router deployment.""" + from litellm.proxy.management_endpoints.model_management_endpoints import ( + add_new_model, + ) + + model_id = "dep-create-0" + db_row = LiteLLM_ProxyModelTable( + model_id=model_id, + model_name="haiku", + litellm_params={"model": "bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0"}, + model_info={"id": model_id}, + created_by="test-admin", + updated_by="test-admin", + ) + + mock_prisma = MagicMock() + mock_prisma.db = MagicMock() + mock_prisma.db.litellm_proxymodeltable = AsyncMock() + mock_prisma.db.litellm_proxymodeltable.create = AsyncMock(return_value=db_row) + + mock_proxy_config = MagicMock() + mock_proxy_config.add_deployment = AsyncMock(return_value=ReconcileOutcome(still_desired=None, live_after=None)) + + mock_router = MagicMock() + mock_router.get_model_ids.return_value = [model_id] + + _PS = "litellm.proxy.proxy_server" + _ENCRYPT = "litellm.proxy.management_endpoints.model_management_endpoints.encrypt_value_helper" + with ( + patch(f"{_PS}.prisma_client", mock_prisma), + patch(f"{_PS}.store_model_in_db", True), + patch(f"{_PS}.proxy_config", mock_proxy_config), + patch(f"{_PS}.proxy_logging_obj", MagicMock()), + patch(f"{_PS}.general_settings", {}), + patch(f"{_PS}.premium_user", True), + patch(f"{_PS}.llm_router", mock_router), + patch(_ENCRYPT, side_effect=lambda value, **kwargs: value), + ): + await add_new_model( + model_params=Deployment( + model_name="haiku", + litellm_params=LiteLLM_Params(model="bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0"), + model_info={ + "id": model_id, + "access_groups": ["prod"], + "input_cost_per_token": 0.0000008, + }, + ), + user_api_key_dict=UserAPIKeyAuth(user_id="test-admin", user_role=LitellmUserRoles.PROXY_ADMIN), + ) + + written = json.loads(mock_prisma.db.litellm_proxymodeltable.create.call_args.kwargs["data"]["model_info"]) + assert "input_cost_per_token" not in written + assert written["id"] == model_id, "filtering must not mint a fresh deployment id" + assert written["access_groups"] == ["prod"] + + class TestGetModelInfoWithIdBlocked: """`ProxyConfig.get_model_info_with_id` must propagate the DB-level `blocked` column into the in-memory `model_info` dict so the router filter can read it.""" diff --git a/tests/test_litellm/proxy/management_endpoints/test_prompt_cache_prediction.py b/tests/test_litellm/proxy/management_endpoints/test_prompt_cache_prediction.py new file mode 100644 index 00000000000..0ec277be884 --- /dev/null +++ b/tests/test_litellm/proxy/management_endpoints/test_prompt_cache_prediction.py @@ -0,0 +1,698 @@ +import asyncio +import time +from collections.abc import Iterator, Mapping +from dataclasses import dataclass +from typing import Final, Literal + +import httpx +import pytest +from fastapi import FastAPI, Request +from pydantic import JsonValue + +import litellm +from litellm.caching.caching import DualCache +from litellm.integrations.custom_logger import CustomLogger +from litellm.proxy._types import ProxyException, UserAPIKeyAuth +from litellm.proxy.common_utils.http_parsing_utils import _read_request_body, _safe_set_request_parsed_body +from litellm.proxy.hooks.parallel_request_limiter_v3 import _PROXY_MaxParallelRequestsHandler_v3 +from litellm.llms.anthropic.prompt_cache_prediction import PromptPrefix, cache_scope, parse_prompt +from litellm.proxy.hooks.prompt_cache_prediction import ( + CacheObservation, + _cache_key, +) +from litellm.proxy.management_endpoints import prompt_cache_prediction as endpoint +from litellm.proxy.utils import InternalUsageCache +from litellm.types.management_endpoints.prompt_cache_prediction import CachePredictionResponse +from litellm.types.router import Deployment, LiteLLM_Params, ModelInfo + + +_PROVIDER_KEY: Final = "cache-prediction-test-provider-key" +_CALLER: Final = "cache-prediction-test-caller-hash" + + +@pytest.fixture(autouse=True) +def anthropic_endpoint_environment(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.delenv("ANTHROPIC_API_BASE", raising=False) + monkeypatch.delenv("ANTHROPIC_BASE_URL", raising=False) + + +def _body(ttl: str = "5m", *, extended: bool = False) -> dict[str, JsonValue]: + blocks: Final[list[JsonValue]] = [ + {"type": "text", "text": "Stable context"}, + *([{"type": "text", "text": "Appended context"}] if extended else []), + ] + return { + "max_tokens": 10, + "system": "Follow the project conventions", + "messages": [ + { + "role": "user", + "content": [ + *blocks[:-1], + {**blocks[-1], "cache_control": {"type": "ephemeral", "ttl": ttl}}, + {"type": "text", "text": "Follow-up question"}, + ], + } + ], + } + + +def _prefix(body: Mapping[str, JsonValue]) -> PromptPrefix: + prefix: Final = parse_prompt(body) + assert prefix is not None + return prefix + + +def _deployment( + deployment_id: str = "sonnet", + model: str = "claude-sonnet-5", + *, + team_id: str | None = None, + api_base: str | None = None, +) -> Deployment: + return Deployment( + model_name=deployment_id, + litellm_params=LiteLLM_Params(model=f"anthropic/{model}", api_key=_PROVIDER_KEY, api_base=api_base), + model_info=ModelInfo(id=deployment_id, team_id=team_id), + ) + + +@dataclass(frozen=True) +class Counts: + total: int | None = 6_000 + prefix: int | None = 5_000 + + async def __call__(self, model: str, api_key: str, body: Mapping[str, JsonValue]) -> int | None: + assert api_key == _PROVIDER_KEY + assert model.startswith("claude-") + return self.total if "max_tokens" in body else self.prefix + + +async def _observe( + cache: DualCache, + body: Mapping[str, JsonValue], + *, + deployment_id: str = "sonnet", + model: str = "claude-sonnet-5", + cached_tokens: int = 5_000, + expired: bool = False, + caller: str = _CALLER, +) -> None: + prefix: Final = _prefix(body) + now: Final = time.time() + observation: Final = CacheObservation( + fingerprint=prefix.fingerprint, + cached_tokens=cached_tokens, + observed_at=now - 400 if expired else now - 10, + expires_at=now - 100 if expired else now + 290, + ) + scope: Final = cache_scope(caller, deployment_id, _PROVIDER_KEY, model) + await cache.async_set_cache(_cache_key(scope, prefix.fingerprint), observation.model_dump_json(), ttl=3_600) + + +@pytest.mark.asyncio +@pytest.mark.parametrize(("ttl", "cold_cost"), [("5m", 0.0145), ("1h", 0.022)]) +async def test_unobserved_cache_prices_cold_and_warm_bounds(ttl: str, cold_cost: float) -> None: + body: Final = _body(ttl) + arm: Final = await endpoint.predict_arm(_deployment(), body, _prefix(body), _CALLER, DualCache(), Counts()) + + assert arm.cache_state == "unknown" + assert arm.reason == "no_compatible_observation" + assert arm.evidence is None + assert arm.estimate is not None and arm.cold is not None and arm.warm is not None + assert arm.estimate.input_cost == pytest.approx(cold_cost) + assert arm.cold.input_cost == pytest.approx(cold_cost) + assert arm.warm.input_cost == pytest.approx(0.003) + assert arm.cold.tokens.uncached_input_tokens == 1_000 + assert arm.cold.tokens.cache_read_input_tokens == 0 + assert arm.cold.tokens.cache_creation_5m_input_tokens == (5_000 if ttl == "5m" else 0) + assert arm.cold.tokens.cache_creation_1h_input_tokens == (5_000 if ttl == "1h" else 0) + assert arm.warm.tokens.cache_read_input_tokens == 5_000 + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("cached_tokens", "warm_cost", "cold_cost"), [(5_400, 0.00228, 0.0147), (4_600, 0.00372, 0.0143)] +) +@pytest.mark.parametrize("expired", [False, True]) +async def test_exact_prefix_conserves_total_with_observed_count_in_all_scenarios( + cached_tokens: int, warm_cost: float, cold_cost: float, expired: bool +) -> None: + cache: Final = DualCache() + body: Final = _body() + await _observe(cache, body, cached_tokens=cached_tokens, expired=expired) + arm: Final = await endpoint.predict_arm(_deployment(), body, _prefix(body), _CALLER, cache, Counts()) + + assert arm.cache_state == ("stale" if expired else "warm") + assert arm.evidence is not None + assert arm.estimate is not None and arm.warm is not None and arm.cold is not None + assert arm.warm.tokens.cache_read_input_tokens == cached_tokens + assert arm.warm.tokens.cache_creation_5m_input_tokens == 0 + assert arm.cold.tokens.cache_creation_5m_input_tokens == cached_tokens + assert arm.cold.tokens.cache_read_input_tokens == 0 + for scenario in (arm.estimate, arm.cold, arm.warm): + assert scenario.tokens.total_tokens == 6_000 + assert scenario.tokens.uncached_input_tokens == 6_000 - cached_tokens + assert arm.warm.input_cost == pytest.approx(warm_cost) + assert arm.cold.input_cost == pytest.approx(cold_cost) + assert arm.estimate.input_cost == pytest.approx(cold_cost if expired else warm_cost) + + +@pytest.mark.asyncio +async def test_observed_prefix_larger_than_full_request_returns_unknown() -> None: + cache: Final = DualCache() + body: Final = _body() + await _observe(cache, body, cached_tokens=6_001) + arm: Final = await endpoint.predict_arm(_deployment(), body, _prefix(body), _CALLER, cache, Counts()) + + assert arm.cache_state == "unknown" + assert arm.reason == "inconsistent_prefix_token_count" + assert arm.estimate is None and arm.cold is None and arm.warm is None + + +@pytest.mark.asyncio +@pytest.mark.parametrize(("ttl", "expected"), [("5m", 0.0053), ("1h", 0.0068)]) +async def test_append_only_prefix_reads_old_tokens_and_writes_extension(ttl: str, expected: float) -> None: + cache: Final = DualCache() + await _observe(cache, _body(ttl), cached_tokens=4_000) + body: Final = _body(ttl, extended=True) + arm: Final = await endpoint.predict_arm(_deployment(), body, _prefix(body), _CALLER, cache, Counts()) + + assert arm.cache_state == "partial" + assert arm.estimate is not None + assert arm.estimate.tokens.cache_read_input_tokens == 4_000 + assert arm.estimate.tokens.cache_creation_5m_input_tokens == (1_000 if ttl == "5m" else 0) + assert arm.estimate.tokens.cache_creation_1h_input_tokens == (1_000 if ttl == "1h" else 0) + assert arm.estimate.input_cost == pytest.approx(expected) + + +@pytest.mark.asyncio +async def test_expired_observation_estimates_a_cold_rebuild() -> None: + cache: Final = DualCache() + body: Final = _body() + await _observe(cache, body, expired=True) + arm: Final = await endpoint.predict_arm(_deployment(), body, _prefix(body), _CALLER, cache, Counts()) + + assert arm.cache_state == "stale" + assert arm.reason == "observation_expired" + assert arm.evidence is not None and arm.evidence.expires_at < time.time() + assert arm.estimate is not None and arm.cold is not None + assert arm.estimate.tokens.cache_read_input_tokens == 0 + assert arm.estimate.tokens.cache_creation_5m_input_tokens == 5_000 + assert arm.estimate.input_cost == arm.cold.input_cost + + +@pytest.mark.asyncio +async def test_below_model_minimum_prices_all_input_as_uncached() -> None: + body: Final = _body() + arm: Final = await endpoint.predict_arm( + _deployment(), body, _prefix(body), _CALLER, DualCache(), Counts(total=1_500, prefix=1_000) + ) + + assert arm.cache_state == "disabled" + assert arm.reason == "below_cache_minimum" + assert arm.estimate is not None + assert arm.estimate.tokens.uncached_input_tokens == 1_500 + assert arm.estimate.tokens.cache_read_input_tokens == 0 + assert arm.estimate.tokens.cache_creation_5m_input_tokens == 0 + assert arm.estimate.input_cost == pytest.approx(0.003) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("counts", [Counts(total=None), Counts(prefix=None), Counts(total=4_000)]) +async def test_unavailable_or_inconsistent_token_counts_return_null_estimates(counts: Counts) -> None: + body: Final = _body() + arm: Final = await endpoint.predict_arm(_deployment(), body, _prefix(body), _CALLER, DualCache(), counts) + + assert arm.cache_state == "unknown" + assert arm.reason == "token_count_unavailable" + assert arm.estimate is None and arm.cold is None and arm.warm is None + + +@pytest.mark.asyncio +@pytest.mark.parametrize("counts", [Counts(), Counts(total=1_500, prefix=1_000)]) +async def test_missing_prices_return_unknown_and_null_estimates( + monkeypatch: pytest.MonkeyPatch, counts: Counts +) -> None: + monkeypatch.setitem( + litellm.model_cost, + "claude-cache-unpriced-5", + {"litellm_provider": "anthropic", "mode": "chat"}, + ) + body: Final = _body() + arm: Final = await endpoint.predict_arm( + _deployment("cache-prediction-unpriced", "claude-cache-unpriced-5"), + body, + _prefix(body), + _CALLER, + DualCache(), + counts, + ) + + assert arm.cache_state == "unknown" + assert arm.reason == "pricing_unavailable" + assert arm.estimate is None and arm.cold is None and arm.warm is None + + +@pytest.mark.asyncio +async def test_custom_api_base_from_environment_returns_unknown_before_counting( + monkeypatch: pytest.MonkeyPatch, +) -> None: + monkeypatch.setenv("ANTHROPIC_API_BASE", "https://custom.invalid") + body: Final = _body() + arm: Final = await endpoint.predict_arm( + _deployment(), body, _prefix(body), _CALLER, DualCache(), _unexpected_count + ) + + assert arm.cache_state == "unknown" + assert arm.reason == "unsupported_provider_endpoint" + assert arm.estimate is None and arm.cold is None and arm.warm is None + + +@pytest.mark.asyncio +async def test_explicit_official_api_base_overrides_custom_environment(monkeypatch: pytest.MonkeyPatch) -> None: + monkeypatch.setenv("ANTHROPIC_API_BASE", "https://custom.invalid") + body: Final = _body() + arm: Final = await endpoint.predict_arm( + _deployment(api_base="https://api.anthropic.com"), body, _prefix(body), _CALLER, DualCache(), Counts() + ) + + assert arm.cache_state == "unknown" + assert arm.reason == "no_compatible_observation" + assert arm.estimate is not None + assert arm.estimate.input_cost == pytest.approx(0.0145) + + +@dataclass(frozen=True) +class _ProxyLogging: + internal_usage_cache: InternalUsageCache + parallel_limiter: CustomLogger | None + + def get_proxy_hook(self, hook: str) -> CustomLogger | None: + return self.parallel_limiter if hook == "parallel_request_limiter" else None + + +def _app( + monkeypatch: pytest.MonkeyPatch, + cache: DualCache, + *, + caller: UserAPIKeyAuth | None = None, + current_team: str | None = None, + candidate_team: str | None = None, + counts: endpoint.TokenCounter = Counts(), + limiter: CustomLogger | Literal["default"] | None = "default", +) -> FastAPI: + import litellm.proxy.proxy_server as proxy_server + + model_list: Final = [ + _deployment("opus", "claude-opus-5", team_id=current_team).model_dump(exclude_unset=True), + _deployment("sonnet", team_id=candidate_team).model_dump(exclude_unset=True), + ] + router: Final = litellm.Router(model_list=model_list) + monkeypatch.setattr(proxy_server, "llm_router", router) + monkeypatch.setattr(proxy_server, "llm_model_list", model_list) + monkeypatch.setattr(endpoint, "count_prompt_tokens", counts) + app: Final = FastAPI() + app.include_router(endpoint.router) + app.add_exception_handler(ProxyException, proxy_server.openai_exception_handler) + if caller is not None: + usage_cache: Final = InternalUsageCache(cache) + configured_limiter: Final = ( + _PROXY_MaxParallelRequestsHandler_v3(usage_cache) if isinstance(limiter, str) else limiter + ) + monkeypatch.setattr(proxy_server, "proxy_logging_obj", _ProxyLogging(usage_cache, configured_limiter)) + app.dependency_overrides[endpoint.user_api_key_auth] = lambda: caller + return app + + +async def _post( + app: FastAPI, + body: Mapping[str, JsonValue], + *, + current_deployment_id: str = "opus", + candidate_deployment_id: str = "sonnet", +) -> httpx.Response: + async with httpx.AsyncClient(transport=httpx.ASGITransport(app=app), base_url="http://test") as client: + return await client.post( + "/cost/predict-cache", + json={ + "current_deployment_id": current_deployment_id, + "candidate_deployment_id": candidate_deployment_id, + "request": body, + }, + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + ("warm_deployment", "warm_model", "expected_delta", "expected_penalty"), + [("sonnet", "claude-sonnet-5", -0.03325, 0.0), ("opus", "claude-opus-5", 0.007, 0.0115)], +) +async def test_switch_delta_accounts_for_each_deployment_cache( + monkeypatch: pytest.MonkeyPatch, + warm_deployment: str, + warm_model: str, + expected_delta: float, + expected_penalty: float, +) -> None: + cache: Final = DualCache() + body: Final = _body() + await _observe(cache, body, deployment_id=warm_deployment, model=warm_model) + app: Final = _app(monkeypatch, cache, caller=UserAPIKeyAuth(api_key=_CALLER)) + response: Final = await _post(app, body) + + assert response.status_code == 200, response.text + result: Final = CachePredictionResponse.model_validate(response.json()) + assert result.switch_delta == pytest.approx(expected_delta) + assert result.cache_rebuild_penalty == pytest.approx(expected_penalty) + assert result.cache_guarantee is False + assert result.pricing_basis == "input_before_discounts_and_margins" + if warm_deployment == "sonnet": + assert result.switch.cache_state == "warm" + assert result.stay.cache_state == "unknown" + else: + assert result.stay.cache_state == "warm" + assert result.switch.cache_state == "unknown" + + +@pytest.mark.asyncio +async def test_missing_caller_identity_cannot_reuse_observations(monkeypatch: pytest.MonkeyPatch) -> None: + cache: Final = DualCache() + body: Final = _body() + await _observe(cache, body) + response: Final = await _post( + _app(monkeypatch, cache, caller=UserAPIKeyAuth(api_key=None), counts=_unexpected_count), body + ) + + assert response.status_code == 200, response.text + result: Final = CachePredictionResponse.model_validate(response.json()) + assert result.stay.reason == result.switch.reason == "caller_identity_unavailable" + assert result.stay.estimate is None and result.switch.estimate is None + assert result.switch_delta is None and result.cache_rebuild_penalty is None + + +@pytest.mark.asyncio +async def test_unauthenticated_request_is_rejected(monkeypatch: pytest.MonkeyPatch) -> None: + import litellm.proxy.proxy_server as proxy_server + + monkeypatch.setattr(proxy_server, "master_key", "cache-prediction-test-master-key") + response: Final = await _post(_app(monkeypatch, DualCache()), _body()) + assert response.status_code == 401, response.text + + +@pytest.mark.asyncio +@pytest.mark.parametrize("arm", ["current", "candidate"]) +@pytest.mark.parametrize("caller_team", [None, "own-team"]) +@pytest.mark.parametrize("restricted", [False, True]) +async def test_foreign_and_missing_deployments_have_identical_authenticated_responses( + monkeypatch: pytest.MonkeyPatch, arm: str, caller_team: str | None, restricted: bool +) -> None: + allowed: Final = ("sonnet",) if arm == "current" else ("opus",) + app: Final = _app( + monkeypatch, + DualCache(), + caller=UserAPIKeyAuth(api_key=_CALLER, team_id=caller_team, models=list(allowed) if restricted else []), + current_team="foreign-team" if arm == "current" else None, + candidate_team="foreign-team" if arm == "candidate" else None, + counts=_unexpected_count, + ) + foreign: Final = await _post(app, _body()) + missing: Final = await _post( + app, + _body(), + current_deployment_id="missing-deployment" if arm == "current" else "opus", + candidate_deployment_id="missing-deployment" if arm == "candidate" else "sonnet", + ) + + assert foreign.status_code == missing.status_code == 404 + assert foreign.json() == missing.json() == {"detail": "Deployment not found"} + + +@pytest.mark.asyncio +@pytest.mark.parametrize("deployment_team", [None, "own-team"]) +async def test_visible_public_and_own_team_deployments_remain_available( + monkeypatch: pytest.MonkeyPatch, deployment_team: str | None +) -> None: + app: Final = _app( + monkeypatch, + DualCache(), + caller=UserAPIKeyAuth(api_key=_CALLER, team_id="own-team"), + current_team=deployment_team, + candidate_team=deployment_team, + ) + response: Final = await _post(app, _body()) + + assert response.status_code == 200, response.text + result: Final = CachePredictionResponse.model_validate(response.json()) + assert result.stay.estimate is not None and result.switch.estimate is not None + + +@pytest.mark.asyncio +@pytest.mark.parametrize("arm", ["current", "candidate"]) +async def test_visible_deployment_outside_key_model_permissions_is_forbidden( + monkeypatch: pytest.MonkeyPatch, arm: str +) -> None: + allowed: Final = "sonnet" if arm == "current" else "opus" + denied: Final = "opus" if arm == "current" else "sonnet" + app: Final = _app(monkeypatch, DualCache(), caller=UserAPIKeyAuth(api_key=_CALLER, models=[allowed])) + response: Final = await _post(app, _body()) + assert response.status_code == 403, response.text + assert denied in response.text + + +@pytest.mark.asyncio +async def test_other_callers_warm_cache_is_not_prediction_evidence(monkeypatch: pytest.MonkeyPatch) -> None: + cache: Final = DualCache() + body: Final = _body() + await _observe(cache, body, caller="other-caller") + response: Final = await _post(_app(monkeypatch, cache, caller=UserAPIKeyAuth(api_key=_CALLER)), body) + + assert response.status_code == 200, response.text + result: Final = CachePredictionResponse.model_validate(response.json()) + assert result.switch.cache_state == "unknown" + assert result.switch.reason == "no_compatible_observation" + assert result.switch.evidence is None + assert result.switch.estimate is not None + assert result.switch.estimate.tokens.cache_read_input_tokens == 0 + + +@pytest.mark.asyncio +async def test_count_failure_nulls_switch_comparison(monkeypatch: pytest.MonkeyPatch) -> None: + app: Final = _app( + monkeypatch, DualCache(), caller=UserAPIKeyAuth(api_key=_CALLER), counts=Counts(total=None) + ) + response: Final = await _post(app, _body()) + + assert response.status_code == 200, response.text + result: Final = CachePredictionResponse.model_validate(response.json()) + assert result.stay.reason == result.switch.reason == "token_count_unavailable" + assert result.stay.estimate is None and result.switch.estimate is None + assert result.switch_delta is None and result.cache_rebuild_penalty is None + + +@pytest.mark.asyncio +@pytest.mark.parametrize("limiter", [None, CustomLogger()]) +async def test_missing_or_unsupported_limiter_returns_unknown_before_counting( + monkeypatch: pytest.MonkeyPatch, limiter: CustomLogger | None +) -> None: + app: Final = _app( + monkeypatch, DualCache(), caller=UserAPIKeyAuth(api_key=_CALLER), counts=_unexpected_count, limiter=limiter + ) + response: Final = await _post(app, _body()) + + assert response.status_code == 200, response.text + result: Final = CachePredictionResponse.model_validate(response.json()) + assert result.stay.reason == result.switch.reason == "limiter_unavailable" + assert result.stay.estimate is None and result.switch.estimate is None + assert result.switch_delta is None and result.cache_rebuild_penalty is None + + +@pytest.mark.asyncio +async def test_occupied_parallel_capacity_rejects_before_provider_count(monkeypatch: pytest.MonkeyPatch) -> None: + cache: Final = DualCache() + limiter: Final = _PROXY_MaxParallelRequestsHandler_v3(InternalUsageCache(cache)) + caller: Final = UserAPIKeyAuth(api_key=_CALLER, max_parallel_requests=1) + app: Final = _app(monkeypatch, cache, caller=caller, counts=_unexpected_count, limiter=limiter) + async with limiter.request_capacity(caller, "opus"): + response: Final = await _post(app, _body()) + + assert response.status_code == 429, response.text + assert "max_parallel_requests" in response.text + recovered: Final = await _post(_app(monkeypatch, cache, caller=caller, limiter=limiter), _body()) + assert recovered.status_code == 200, recovered.text + + +@pytest.mark.asyncio +async def test_each_count_consumes_the_deployment_group_rpm_limit(monkeypatch: pytest.MonkeyPatch) -> None: + calls: Final = asyncio.Queue[str]() + + async def count(model: str, api_key: str, body: Mapping[str, JsonValue]) -> int | None: + calls.put_nowait(model) + return await Counts()(model, api_key, body) + + caller: Final = UserAPIKeyAuth(api_key=_CALLER, metadata={"model_rpm_limit": {"sonnet": 1}}) + app: Final = _app(monkeypatch, DualCache(), caller=caller, counts=count) + response: Final = await _post(app, _body()) + + assert response.status_code == 429, response.text + assert calls.qsize() == 3 + assert tuple(calls.get_nowait() for _ in range(3)) == ( + "claude-opus-5", "claude-opus-5", "claude-sonnet-5" + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("metadata_key", ["metadata", "litellm_metadata"]) +async def test_each_count_preserves_auth_cached_request_tag_limits( + monkeypatch: pytest.MonkeyPatch, metadata_key: str +) -> None: + calls: Final = asyncio.Queue[str]() + caller: Final = UserAPIKeyAuth(api_key=_CALLER, metadata={"tag_rpm_limit": {"cache-cost": 1}}) + + async def count(model: str, api_key: str, body: Mapping[str, JsonValue]) -> int | None: + calls.put_nowait(model) + return await Counts()(model, api_key, body) + + async def authenticated_request(request: Request) -> UserAPIKeyAuth: + data: Final = await _read_request_body(request) + _safe_set_request_parsed_body(request, {**data, metadata_key: {"tags": ["cache-cost"]}}) + return caller + + app: Final = _app(monkeypatch, DualCache(), caller=caller, counts=count) + app.dependency_overrides[endpoint.user_api_key_auth] = authenticated_request + response: Final = await _post(app, _body()) + + assert response.status_code == 429, response.text + assert "tag_per_key" in response.text + assert calls.qsize() == 1 + assert calls.get_nowait() == "claude-opus-5" + + +@pytest.mark.asyncio +async def test_provider_counter_failure_releases_parallel_capacity(monkeypatch: pytest.MonkeyPatch) -> None: + cache: Final = DualCache() + limiter: Final = _PROXY_MaxParallelRequestsHandler_v3(InternalUsageCache(cache)) + caller: Final = UserAPIKeyAuth(api_key=_CALLER, max_parallel_requests=1) + + async def fail_count(model: str, api_key: str, body: Mapping[str, JsonValue]) -> int | None: + raise RuntimeError("provider counter failed") + + app: Final = _app(monkeypatch, cache, caller=caller, counts=fail_count, limiter=limiter) + with pytest.raises(RuntimeError, match="provider counter failed"): + await _post(app, _body()) + recovered: Final = await _post(_app(monkeypatch, cache, caller=caller, limiter=limiter), _body()) + assert recovered.status_code == 200, recovered.text + assert recovered.json()["switch"]["estimate"]["input_cost"] == pytest.approx(0.0145) + + +@pytest.mark.asyncio +async def test_cancelled_provider_counter_releases_parallel_capacity(monkeypatch: pytest.MonkeyPatch) -> None: + cache: Final = DualCache() + limiter: Final = _PROXY_MaxParallelRequestsHandler_v3(InternalUsageCache(cache)) + caller: Final = UserAPIKeyAuth(api_key=_CALLER, max_parallel_requests=1) + started: Final = asyncio.Event() + release: Final = asyncio.Event() + + async def wait_count(model: str, api_key: str, body: Mapping[str, JsonValue]) -> int | None: + started.set() + await release.wait() + return await Counts()(model, api_key, body) + + app: Final = _app(monkeypatch, cache, caller=caller, counts=wait_count, limiter=limiter) + pending: Final = asyncio.create_task(_post(app, _body())) + try: + await asyncio.wait_for(started.wait(), timeout=5) + pending.cancel() + with pytest.raises(asyncio.CancelledError): + await pending + release.set() + recovered: Final = await asyncio.wait_for(_post(app, _body()), timeout=5) + assert recovered.status_code == 200, recovered.text + assert recovered.json()["switch"]["estimate"]["input_cost"] == pytest.approx(0.0145) + finally: + pending.cancel() + release.set() + await asyncio.gather(pending, return_exceptions=True) + + +async def _unexpected_count(model: str, api_key: str, body: Mapping[str, JsonValue]) -> int | None: + pytest.fail("Unsupported prediction must return before contacting the token counter") + + +class RequestMutator(CustomLogger): + async def async_pre_call_hook( + self, user_api_key_dict: UserAPIKeyAuth, cache: DualCache, data: dict[str, object], call_type: str + ) -> dict[str, object]: + return {**data, "system": "Injected policy"} + + +@pytest.fixture +def request_mutator() -> Iterator[RequestMutator]: + callback: Final = RequestMutator() + litellm.logging_callback_manager.add_litellm_callback(callback) + try: + yield callback + finally: + litellm.logging_callback_manager.remove_callback_from_all_lists(callback) + + +@pytest.mark.asyncio +async def test_request_transform_callback_returns_unknown_before_token_counting( + monkeypatch: pytest.MonkeyPatch, request_mutator: RequestMutator +) -> None: + app: Final = _app( + monkeypatch, DualCache(), caller=UserAPIKeyAuth(api_key=_CALLER), counts=_unexpected_count + ) + response: Final = await _post(app, _body()) + + assert response.status_code == 200, response.text + result: Final = CachePredictionResponse.model_validate(response.json()) + assert result.stay.cache_state == result.switch.cache_state == "unknown" + assert result.stay.reason == result.switch.reason == "unsupported_request_transform" + assert result.stay.estimate is None and result.switch.estimate is None + assert result.switch_delta is None and result.cache_rebuild_penalty is None + + +@pytest.mark.asyncio +async def test_key_config_returns_unknown_before_token_counting(monkeypatch: pytest.MonkeyPatch) -> None: + app: Final = _app( + monkeypatch, + DualCache(), + caller=UserAPIKeyAuth(api_key=_CALLER, config={"model_list": []}), + counts=_unexpected_count, + ) + response: Final = await _post(app, _body()) + + assert response.status_code == 200, response.text + result: Final = CachePredictionResponse.model_validate(response.json()) + assert result.stay.cache_state == result.switch.cache_state == "unknown" + assert result.stay.reason == result.switch.reason == "unsupported_request_transform" + assert result.stay.estimate is None and result.switch.estimate is None + assert result.switch_delta is None and result.cache_rebuild_penalty is None + + +@pytest.mark.parametrize("headers", [ + {"anthropic-version": "2099-01-01"}, + {"anthropic-beta": "future-feature"}, +]) +@pytest.mark.asyncio +async def test_unsupported_provider_headers_cannot_reuse_default_version_evidence( + monkeypatch: pytest.MonkeyPatch, headers: dict[str, str] +) -> None: + cache: Final = DualCache() + await _observe(cache, _body(), deployment_id="sonnet") + app: Final = _app( + monkeypatch, cache, caller=UserAPIKeyAuth(api_key=_CALLER), counts=_unexpected_count + ) + async with httpx.AsyncClient(transport=httpx.ASGITransport(app=app), base_url="http://test") as client: + response: Final = await client.post( + "/cost/predict-cache", + headers=headers, + json={"current_deployment_id": "opus", "candidate_deployment_id": "sonnet", "request": _body()}, + ) + assert response.status_code == 200, response.text + result: Final = CachePredictionResponse.model_validate(response.json()) + assert result.stay.cache_state == result.switch.cache_state == "unknown" + assert result.stay.reason == result.switch.reason == "unsupported_provider_headers" + assert result.stay.estimate is None and result.switch.estimate is None + assert result.switch_delta is None and result.cache_rebuild_penalty is None diff --git a/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py b/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py index 2fb496d6231..a2f534fbe4d 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py +++ b/tests/test_litellm/proxy/management_endpoints/test_team_endpoints.py @@ -3937,6 +3937,7 @@ async def test_list_team_v2_org_admin_sees_org_teams(): mock_db.litellm_teamtable.find_many = AsyncMock(return_value=[mock_team]) mock_db.litellm_teamtable.count = AsyncMock(return_value=1) mock_db.litellm_verificationtoken.group_by = AsyncMock(return_value=[]) + mock_db.litellm_usertable.find_unique = AsyncMock(return_value=mock_user) result = await list_team_v2( http_request=mock_request, @@ -4036,6 +4037,7 @@ async def test_list_team_v2_org_admin_own_user_id_sees_all_org_teams(): ) mock_db.litellm_teamtable.count = AsyncMock(return_value=2) mock_db.litellm_verificationtoken.group_by = AsyncMock(return_value=[]) + mock_db.litellm_usertable.find_unique = AsyncMock(return_value=mock_user) # UI sends the caller's own user_id for non-Admin roles result = await list_team_v2( @@ -4055,10 +4057,217 @@ async def test_list_team_v2_org_admin_own_user_id_sees_all_org_teams(): assert result["total"] == 2 assert len(result["teams"]) == 2 - # Verify the where clause scopes by org only — no team_id filter + # Verify the where clause scopes by org OR own membership — no + # top-level team_id filter that would hide org teams they aren't in where = mock_db.litellm_teamtable.find_many.call_args.kwargs["where"] - assert where["organization_id"] == {"in": ["org_A"]} + assert where["AND"] == [ + {"OR": [{"organization_id": {"in": ["org_A"]}}, {"team_id": {"in": ["team_1"]}}]} + ] assert "team_id" not in where + assert "organization_id" not in where + + +def _team_where_matches(team, where) -> bool: + for key, cond in where.items(): + if key == "AND": + if not all(_team_where_matches(team, c) for c in cond): + return False + elif key == "OR": + if not any(_team_where_matches(team, c) for c in cond): + return False + else: + value = getattr(team, key) + if not isinstance(cond, dict): + if value != cond: + return False + elif "in" in cond and value not in cond["in"]: + return False + elif "contains" in cond and cond["contains"].lower() not in (value or "").lower(): + return False + return True + + +def _org_membership(user_id: str, organization_id: str, user_role: str) -> LiteLLM_OrganizationMembershipTable: + return LiteLLM_OrganizationMembershipTable( + user_id=user_id, + organization_id=organization_id, + user_role=user_role, + spend=0.0, + created_at=datetime.now(), + updated_at=datetime.now(), + ) + + +@pytest.mark.asyncio +async def test_list_team_v2_org_admin_own_query_keeps_memberships_in_other_orgs(monkeypatch): + """ + /v2/team/list: an org admin of org_A who is a member of a team in org_B + gets that team back on a self query (with and without user_id, with and + without search), alongside every org_A team. The membership half of the + union comes from the DB, so a stale cached user object cannot hide it. + A query for another user stays scoped to org_A. + + Regression test for LIT-3723. + """ + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache + from litellm.proxy.management_endpoints.team_endpoints import list_team_v2 + + org_admin = UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER, user_id="org_admin_user") + cache = UserApiKeyCache() + await cache.async_set_cache( + key="org_admin_user", + value=LiteLLM_UserTable( + user_id="org_admin_user", + teams=["team_in_org_A"], + organization_memberships=[ + _org_membership("org_admin_user", "org_A", "org_admin"), + _org_membership("org_admin_user", "org_B", "internal_user"), + ], + ), + model_type=LiteLLM_UserTable, + ) + await cache.async_set_cache( + key="other_user", + value=LiteLLM_UserTable( + user_id="other_user", + teams=["other_team_in_org_A", "team_in_org_B", "unrelated_team_in_org_B"], + organization_memberships=[_org_membership("other_user", "org_B", "internal_user")], + ), + model_type=LiteLLM_UserTable, + ) + + def team(team_id, organization_id, *member_ids): + return LiteLLM_TeamTable( + team_id=team_id, + team_alias=team_id, + organization_id=organization_id, + members_with_roles=[Member(user_id=m, role="user") for m in member_ids], + ) + + all_teams = [ + team("team_in_org_A", "org_A", "org_admin_user"), + team("other_team_in_org_A", "org_A", "other_user"), + team("team_in_org_B", "org_B", "org_admin_user", "other_user"), + team("unrelated_team_in_org_B", "org_B", "other_user"), + ] + + async def find_many(where=None, **kwargs): + return [t for t in all_teams if where is None or _team_where_matches(t, where)] + + async def count(where=None, **kwargs): + return len(await find_many(where)) + + prisma_client = MagicMock() + prisma_client.db.litellm_teamtable.find_many = AsyncMock(side_effect=find_many) + prisma_client.db.litellm_teamtable.count = AsyncMock(side_effect=count) + prisma_client.db.litellm_verificationtoken.group_by = AsyncMock(return_value=[]) + prisma_client.db.litellm_usertable.find_unique = AsyncMock( + return_value=LiteLLM_UserTable( + user_id="org_admin_user", + teams=["team_in_org_A", "team_in_org_B"], + organization_memberships=[ + _org_membership("org_admin_user", "org_A", "org_admin"), + _org_membership("org_admin_user", "org_B", "internal_user"), + ], + ) + ) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", prisma_client) + monkeypatch.setattr("litellm.proxy.proxy_server.user_api_key_cache", cache) + proxy_logging_obj = MagicMock() + proxy_logging_obj.service_logging_obj.async_service_success_hook = AsyncMock() + monkeypatch.setattr("litellm.proxy.proxy_server.proxy_logging_obj", proxy_logging_obj) + + async def list_teams(user_id, search=None): + result = await list_team_v2( + http_request=MagicMock(), + user_id=user_id, + organization_id=None, + team_id=None, + team_alias=None, + search=search, + user_api_key_dict=org_admin, + page=1, + page_size=10, + sort_by=None, + sort_order="asc", + status=None, + ) + assert result["total"] == len(result["teams"]) + return [t.team_id for t in result["teams"]] + + own_view = ["team_in_org_A", "other_team_in_org_A", "team_in_org_B"] + assert await list_teams("org_admin_user") == own_view + assert await list_teams(None) == own_view + assert await list_teams("org_admin_user", search="team_in_org_B") == ["team_in_org_B"] + assert await list_teams("other_user") == ["other_team_in_org_A"] + prisma_client.db.litellm_usertable.find_unique.assert_awaited_with( + where={"user_id": "org_admin_user"}, include={"organization_memberships": True} + ) + + prisma_client.db.litellm_usertable.find_unique.side_effect = RuntimeError("db down") + with pytest.raises(ValueError, match="db down"): + await list_teams("org_admin_user") + + +@pytest.mark.asyncio +async def test_list_team_v1_org_admin_own_query_keeps_memberships_in_other_orgs(): + """ + /team/list: an org admin of org_A listing their own teams sees every team + they belong to, including the org_B one. The bare admin listing stays the + org_A view and a query for another user stays scoped to org_A. + + Regression test for LIT-3723. + """ + from litellm.proxy.common_utils.user_api_key_cache import UserApiKeyCache + from litellm.proxy.management_endpoints.team_endpoints import _authorize_and_filter_teams + + org_admin = UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER, user_id="org_admin_user") + cache = UserApiKeyCache() + await cache.async_set_cache( + key="org_admin_user", + value=LiteLLM_UserTable( + user_id="org_admin_user", + teams=["team_in_org_A", "team_in_org_B"], + organization_memberships=[_org_membership("org_admin_user", "org_A", "org_admin")], + ), + model_type=LiteLLM_UserTable, + ) + + def team(team_id, organization_id, *member_ids): + return SimpleNamespace( + team_id=team_id, + organization_id=organization_id, + members_with_roles=[{"user_id": m, "role": "user"} for m in member_ids], + ) + + all_teams = [ + team("team_in_org_A", "org_A", "org_admin_user"), + team("other_team_in_org_A", "org_A", "other_user"), + team("team_in_org_B", "org_B", "org_admin_user", "other_user"), + team("unrelated_team_in_org_B", "org_B", "other_user"), + ] + + async def find_many(where=None, **kwargs): + if where is None: + return all_teams + return [t for t in all_teams if t.organization_id in where["organization_id"]["in"]] + + prisma_client = MagicMock() + prisma_client.db.litellm_teamtable.find_many = AsyncMock(side_effect=find_many) + + async def list_teams(user_id): + teams = await _authorize_and_filter_teams( + user_api_key_dict=org_admin, + user_id=user_id, + prisma_client=prisma_client, + user_api_key_cache=cache, + proxy_logging_obj=MagicMock(), + ) + return [t.team_id for t in teams] + + assert await list_teams("org_admin_user") == ["team_in_org_A", "team_in_org_B"] + assert await list_teams(None) == ["team_in_org_A", "other_team_in_org_A"] + assert await list_teams("other_user") == ["other_team_in_org_A"] @pytest.mark.asyncio @@ -9267,6 +9476,9 @@ async def test_new_team_with_router_settings(mock_db_client, mock_admin_auth): mock_db_client.get_data = AsyncMock(return_value=None) mock_db_client.update_data = AsyncMock(return_value=MagicMock()) mock_db_client.db = MagicMock() + mock_db_client.db.litellm_proxymodeltable.find_many = AsyncMock(return_value=[ + SimpleNamespace(model_id="weighted-id", model_name="group", model_info={}) + ]) # Mock model table creation mock_db_client.db.litellm_modeltable = MagicMock() @@ -9302,6 +9514,7 @@ async def test_new_team_with_router_settings(mock_db_client, mock_admin_auth): # Test router_settings with sample data router_settings_data = { + "weights": {"group": {"weighted-id": 1}}, "routing_strategy": "usage-based", "num_retries": 3, "retry_policy": {"max_retries": 5}, @@ -9335,6 +9548,12 @@ async def test_new_team_with_router_settings(mock_db_client, mock_admin_auth): deserialized_settings = json.loads(team_data["router_settings"]) assert deserialized_settings == router_settings_data + mock_team_create.reset_mock() + team_request.router_settings = {"weights": {"group": {"unknown-id": 1}}} + with pytest.raises(ProxyException, match="Unknown deployment ID"): + await new_team(data=team_request, http_request=dummy_request, user_api_key_dict=mock_admin_auth) + mock_team_create.assert_not_awaited() + @pytest.mark.asyncio async def test_get_team_daily_activity_member_with_permission_sees_all_spend( @@ -9530,6 +9749,9 @@ async def test_update_team_with_router_settings( # Configure mocked prisma client mock_db_client.jsonify_team_object = lambda db_data: db_data mock_db_client.db = MagicMock() + mock_db_client.db.litellm_proxymodeltable.find_many = AsyncMock(return_value=[ + SimpleNamespace(model_id="weighted-id", model_name="group", model_info={}) + ]) # Mock existing team row existing_team_mock = MagicMock() @@ -9564,6 +9786,7 @@ async def test_update_team_with_router_settings( # Test router_settings with updated data router_settings_data = { + "weights": {"group": {"weighted-id": 1}}, "routing_strategy": "latency-based", "num_retries": 2, } @@ -9596,6 +9819,12 @@ async def test_update_team_with_router_settings( deserialized_settings = json.loads(team_data["router_settings"]) assert deserialized_settings == router_settings_data + mock_team_update.reset_mock() + team_update_request.router_settings = {"weights": {"group": {"unknown-id": 1}}} + with pytest.raises(ProxyException, match="Unknown deployment ID"): + await update_team(data=team_update_request, http_request=dummy_request, user_api_key_dict=mock_admin_auth) + mock_team_update.assert_not_awaited() + @pytest.mark.asyncio async def test_get_team_daily_activity_non_admin_filters_by_user_api_keys( @@ -13941,6 +14170,52 @@ async def test_team_member_update_skips_invalidation_when_no_budget_fields_sent( assert real_spend_counter_cache.in_memory_cache.get_cache(key="spend:team_member:member-1:team-1") == 1.5 +@pytest.mark.asyncio +async def test_evict_created_membership_caches_drops_the_negative_sentinel(): + """ + Regression: a membership-create path (/team/member_add, the /team/update budget backfill) must + evict any cached "no membership" sentinel a prior session-token read left, so a per-member budget + attached at create time is enforced on the next request instead of after the membership cache TTL. + Uses a real cache so the assertion is that the sentinel is actually gone, not that a mock was called. + """ + from litellm.proxy.common_utils.user_api_key_cache import ( + NO_TEAM_MEMBERSHIP_SENTINEL, + UserApiKeyCache, + team_membership_reservation_cache_key, + ) + from litellm.proxy.management_endpoints.team_endpoints import _evict_created_membership_caches + + cache = UserApiKeyCache() + kept_key = team_membership_reservation_cache_key(user_id="carol", team_id="team-eviction") + evicted_key = team_membership_reservation_cache_key(user_id="bob", team_id="team-eviction") + await cache.async_set_cache(key=kept_key, value=NO_TEAM_MEMBERSHIP_SENTINEL) + await cache.async_set_cache(key=evicted_key, value=NO_TEAM_MEMBERSHIP_SENTINEL) + + await _evict_created_membership_caches(user_ids=("bob",), team_id="team-eviction", user_api_key_cache=cache) + + assert await cache.async_get_cache(key=evicted_key) is None + assert await cache.async_get_cache(key=kept_key) == NO_TEAM_MEMBERSHIP_SENTINEL + + +def test_member_user_ids_keeps_only_string_user_ids(): + """ + The /team/update backfill feeds Prisma-deserialized member dicts here; a row can be missing + user_id or carry a non-string value. Only real string ids may reach invalidate_team_member_spend_state, + so those get eviction and the malformed rows are dropped rather than crashing the update. + """ + from litellm.proxy.management_endpoints.team_endpoints import _member_user_ids + + members = [ + {"user_id": "alice", "role": "admin"}, + {"role": "user"}, + {"user_id": None, "role": "user"}, + {"user_id": 123, "role": "user"}, + {"user_id": "bob", "role": "user"}, + ] + + assert _member_user_ids(members) == ("alice", "bob") + + def _team_spend_by_user_team(team_id: str, team_alias: str, member: Member, permissions: list[str]) -> MagicMock: team = MagicMock(spec=LiteLLM_TeamTable) team.team_id = team_id @@ -14111,3 +14386,123 @@ async def test_get_team_spend_by_user_rejects_bad_input(mock_db_client, team_ids assert exc_info.value.status_code == 400 assert expected_error in str(exc_info.value.detail) mock_db_client.db.query_raw.assert_not_called() + + +class _TeamRowWithOrganization(LiteLLM_TeamTable): + litellm_organization_table: LiteLLM_OrganizationTable | None = None + + +@pytest.mark.parametrize( + "organization, expected_models", + [ + ( + LiteLLM_OrganizationTable( + organization_id="org-1", + budget_id="budget-1", + models=["all-proxy-models"], + created_by="admin", + updated_by="admin", + ), + ["all-proxy-models"], + ), + ( + LiteLLM_OrganizationTable( + organization_id="org-1", + budget_id="budget-1", + models=["gpt-4o"], + created_by="admin", + updated_by="admin", + ), + ["gpt-4o"], + ), + (None, None), + ], +) +@pytest.mark.asyncio +async def test_team_info_returns_parent_organization_models(organization, expected_models): + """/team/info must report the parent org's model ceiling. + + A team admin who is not an org admin gets a 403 from /organization/info, so this + is the only read that can tell the Admin UI whether the org allows all proxy + models. Without it the team edit form hides the "All Proxy Models" option and a + team admin cannot grant their team everything on the proxy. + """ + from fastapi import Request + + from litellm.proxy.management_endpoints import team_endpoints + + team_row = _TeamRowWithOrganization( + team_id="team-1", + organization_id="org-1" if organization is not None else None, + litellm_organization_table=organization, + ) + + mock_prisma = MagicMock() + mock_prisma.db.litellm_teamtable.find_unique = AsyncMock(return_value=team_row) + mock_prisma.get_data = AsyncMock(return_value=[]) + + memberships = AsyncMock(return_value=[]) + + with ( + patch("litellm.proxy.proxy_server.prisma_client", mock_prisma), # test-quality-ok: no seam on team_info + patch.object(team_endpoints, "get_all_team_memberships", memberships), # test-quality-ok: no seam on team_info + ): + response = await team_endpoints.team_info( + http_request=MagicMock(spec=Request), + team_id="team-1", + user_api_key_dict=UserAPIKeyAuth(user_role=LitellmUserRoles.PROXY_ADMIN), + ) + + assert response["team_info"].organization_models == expected_models + + +@pytest.mark.parametrize( + "caller, expected_models", + [ + (UserAPIKeyAuth(user_id="admin-1", user_role=LitellmUserRoles.INTERNAL_USER), ["gpt-4o"]), + (UserAPIKeyAuth(user_id="member-1", user_role=LitellmUserRoles.INTERNAL_USER), None), + (UserAPIKeyAuth(team_id="team-1"), None), + ], +) +@pytest.mark.asyncio +async def test_team_info_reports_parent_organization_models_only_to_team_managers(caller, expected_models): + """Plain members and team keys can read their team, but not the org's wider allow-list.""" + from fastapi import Request + + from litellm.proxy.management_endpoints import team_endpoints + + team_row = _TeamRowWithOrganization( + team_id="team-1", + organization_id="org-1", + members_with_roles=[ + Member(user_id="admin-1", role="admin"), + Member(user_id="member-1", role="user"), + ], + litellm_organization_table=LiteLLM_OrganizationTable( + organization_id="org-1", + budget_id="budget-1", + models=["gpt-4o"], + created_by="admin", + updated_by="admin", + ), + ) + + mock_prisma = MagicMock() + mock_prisma.db.litellm_teamtable.find_unique = AsyncMock(return_value=team_row) + mock_prisma.db.litellm_usertable.find_many = AsyncMock(return_value=[]) + mock_prisma.get_data = AsyncMock(return_value=[]) + + with ( + patch("litellm.proxy.proxy_server.prisma_client", mock_prisma), # test-quality-ok: no seam on team_info + patch.object(team_endpoints, "get_all_team_memberships", AsyncMock(return_value=[])), # test-quality-ok: no seam on team_info + patch.object( # test-quality-ok: no seam on team_info + team_endpoints, "_is_user_org_admin_for_team", AsyncMock(return_value=False) + ), + ): + response = await team_endpoints.team_info( + http_request=MagicMock(spec=Request), + team_id="team-1", + user_api_key_dict=caller, + ) + + assert response["team_info"].organization_models == expected_models diff --git a/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py b/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py index 2050e65d2a1..1230c548281 100644 --- a/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py +++ b/tests/test_litellm/proxy/management_endpoints/test_ui_sso.py @@ -8334,6 +8334,7 @@ async def _render_legacy_login_page(env_overrides, general_settings): "GOOGLE_CLIENT_ID", "GENERIC_CLIENT_ID", "LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", + "UI_PASSWORD", ): os.environ.pop(var, None) os.environ.update(env_overrides) @@ -8386,6 +8387,20 @@ async def test_legacy_login_page_hides_credentials_hint_via_general_settings(): assert "MASTER_KEY" not in body +@pytest.mark.asyncio +async def test_legacy_login_page_hides_credentials_hint_when_ui_password_set(): + response = await _render_legacy_login_page( + env_overrides={"UI_PASSWORD": "s3cret-pass"}, + general_settings={}, + ) + + body = response.body.decode() + assert response.status_code == 200 + assert "Default Credentials" not in body + assert "MASTER_KEY" not in body + assert 'name="username"' in body + + @pytest.mark.asyncio async def test_saml_callback_blocked_when_admin_ui_disabled(): """An IdP-initiated assertion must not mint a UI session when the admin UI is diff --git a/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py b/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py index 5f1e7e1fe0c..5d8222162a2 100644 --- a/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py +++ b/tests/test_litellm/proxy/openai_files_endpoint/test_files_endpoint.py @@ -2441,6 +2441,63 @@ def test_list_files_resolves_wildcard_deployment_credentials( proxy_logging_obj.post_call_failure_hook.assert_not_called() +def test_list_files_by_model_returns_an_openai_page_for_a_provider_listing( + mocker: MockerFixture, monkeypatch, llm_router: Router +): + import litellm.proxy.proxy_server as ps + from litellm.proxy._types import LitellmUserRoles + from litellm.types.llms.openai import FileListPage + + proxy_logging_obj = setup_proxy_logging_object(monkeypatch, llm_router) + monkeypatch.setattr("litellm.proxy.proxy_server.master_key", None) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) + monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", llm_router) + proxy_logging_obj.update_request_status = mocker.AsyncMock() + proxy_logging_obj.post_call_success_hook = mocker.AsyncMock(return_value=None) + proxy_logging_obj.post_call_failure_hook = mocker.AsyncMock() + + listed_files = [ + OpenAIFileObject( + id=f"file-{index}", + bytes=index, + created_at=index, + filename=f"{index}.jsonl", + object="file", + purpose="batch", + status="uploaded", + ) + for index in (1, 2) + ] + + async def _mock_afile_list(**kwargs): + return list(listed_files) + + monkeypatch.setattr(litellm, "afile_list", _mock_afile_list) + + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + api_key="test-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + user_id="test-user", + ) + + try: + response = client.get( + "/v1/files?target_model_names=gpt-3.5-turbo", + headers={"Authorization": "Bearer test-key"}, + ) + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + assert response.status_code == 200, response.text + body = response.json() + assert body["object"] == "list" + assert [listed["id"] for listed in body["data"]] == ["file-1", "file-2"] + assert (body["first_id"], body["last_id"], body["has_more"]) == ("file-1", "file-2", False) + hook_response = proxy_logging_obj.post_call_success_hook.call_args.kwargs["response"] + assert isinstance(hook_response, FileListPage) + assert [listed.id for listed in hook_response.data] == ["file-1", "file-2"] + + def test_list_files_model_routing_does_not_forward_custom_llm_provider_twice( mocker: MockerFixture, monkeypatch, llm_router: Router ): @@ -4646,6 +4703,108 @@ def test_create_file_blocked_extension_unset_allows_everything(monkeypatch, llm_ assert len(forwarded_calls) == 1 +@pytest.mark.parametrize( + "filename", + ["payload.exe", "notes.txt", "README"], + ids=["other_extension", "text_extension", "no_extension"], +) +def test_create_file_extension_outside_allowlist_rejected_before_forwarding( + monkeypatch, llm_router: Router, filename: str +): + import litellm.proxy.proxy_server as ps + + forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router) + monkeypatch.setitem(ps.general_settings, "allowed_file_extensions", [".jsonl"]) + + try: + response = client.post( + "/v1/files", + files={"file": (filename, b"MZ\x90\x00", "application/octet-stream")}, + data={"purpose": "user_data"}, + headers={"Authorization": "Bearer test-key"}, + ) + finally: + _teardown_batch_upload_endpoint() + + assert response.status_code == 400, response.text + error = response.json()["error"] + assert error["type"] == "invalid_request_error" + assert error["param"] == "file" + assert "allowed_file_extensions" in error["message"] + assert forwarded_calls == [] + + +def test_create_file_allowed_extension_forwards_case_insensitively(monkeypatch, llm_router: Router): + import litellm.proxy.proxy_server as ps + + forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router) + monkeypatch.setitem(ps.general_settings, "allowed_file_extensions", [".JSONL"]) + + try: + response = client.post( + "/v1/files", + files={"file": ("input.jsonl", b'{"custom_id": "1"}\n', "application/jsonl")}, + data={"purpose": "user_data"}, + headers={"Authorization": "Bearer test-key"}, + ) + finally: + _teardown_batch_upload_endpoint() + + assert response.status_code == 200, response.text + assert len(forwarded_calls) == 1 + + +def test_create_file_empty_allowlist_rejects_every_upload(monkeypatch, llm_router: Router): + import litellm.proxy.proxy_server as ps + + forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router) + monkeypatch.setitem(ps.general_settings, "allowed_file_extensions", []) + + try: + response = client.post( + "/v1/files", + files={"file": ("input.jsonl", b'{"custom_id": "1"}\n', "application/jsonl")}, + data={"purpose": "user_data"}, + headers={"Authorization": "Bearer test-key"}, + ) + finally: + _teardown_batch_upload_endpoint() + + assert response.status_code == 400, response.text + assert "allowed_file_extensions" in response.json()["error"]["message"] + assert forwarded_calls == [] + + +def test_create_file_allowlist_runs_before_blocklist(monkeypatch, llm_router: Router): + import litellm.proxy.proxy_server as ps + + forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router) + monkeypatch.setitem(ps.general_settings, "allowed_file_extensions", [".jsonl"]) + monkeypatch.setitem(ps.general_settings, "blocked_file_extensions", [".exe", ".jsonl"]) + + try: + denied_by_allowlist = client.post( + "/v1/files", + files={"file": ("payload.exe", b"MZ\x90\x00", "application/octet-stream")}, + data={"purpose": "user_data"}, + headers={"Authorization": "Bearer test-key"}, + ) + denied_by_blocklist = client.post( + "/v1/files", + files={"file": ("input.jsonl", b'{"custom_id": "1"}\n', "application/jsonl")}, + data={"purpose": "user_data"}, + headers={"Authorization": "Bearer test-key"}, + ) + finally: + _teardown_batch_upload_endpoint() + + assert denied_by_allowlist.status_code == 400, denied_by_allowlist.text + assert "allowed_file_extensions" in denied_by_allowlist.json()["error"]["message"] + assert denied_by_blocklist.status_code == 400, denied_by_blocklist.text + assert "blocked_file_extensions" in denied_by_blocklist.json()["error"]["message"] + assert forwarded_calls == [] + + def test_create_file_path_traversal_filename_rejected_before_forwarding(monkeypatch, llm_router: Router): """A filename carrying a directory-traversal component must never reach storage or the provider.""" forwarded_calls = _setup_batch_upload_endpoint(monkeypatch, llm_router) @@ -4668,6 +4827,249 @@ def test_create_file_path_traversal_filename_rejected_before_forwarding(monkeypa assert forwarded_calls == [] +def test_list_files_target_model_names_passes_trusted_bedrock_credentials( + mocker: MockerFixture, monkeypatch +): + """ + GET /v1/files?target_model_names= must hand the deployment's + immutable credential snapshot to litellm.afile_list, since Bedrock resolves + the S3 bucket to list from that snapshot rather than from request params. + """ + from types import MappingProxyType + + import litellm.proxy.proxy_server as ps + from litellm.proxy._types import LitellmUserRoles + + bedrock_router = Router( + model_list=[ + { + "model_name": "bedrock-claude", + "litellm_params": { + "model": "bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0", + "aws_access_key_id": "AKIAEXAMPLE", + "aws_secret_access_key": "secret", + "aws_region_name": "us-west-2", + "s3_bucket_name": "my-bucket", + }, + }, + ] + ) + + proxy_logging_obj = setup_proxy_logging_object(monkeypatch, bedrock_router) + monkeypatch.setattr("litellm.proxy.proxy_server.master_key", None) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) + monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", bedrock_router) + proxy_logging_obj.update_request_status = mocker.AsyncMock() + proxy_logging_obj.post_call_success_hook = mocker.AsyncMock(return_value=[]) + proxy_logging_obj.post_call_failure_hook = mocker.AsyncMock() + + captured_kwargs: dict = {} + + async def _mock_afile_list(**kwargs): + captured_kwargs.update(kwargs) + return [] + + monkeypatch.setattr(litellm, "afile_list", _mock_afile_list) + + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + api_key="test-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + user_id="test-user", + ) + + try: + response = client.get( + "/v1/files?target_model_names=bedrock-claude&purpose=batch", + headers={"Authorization": "Bearer test-key"}, + ) + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + assert response.status_code == 200, response.text + assert captured_kwargs["custom_llm_provider"] == "bedrock" + assert captured_kwargs["purpose"] == "batch" + trusted_credentials = captured_kwargs["_litellm_internal_model_credentials"] + assert isinstance(trusted_credentials, MappingProxyType) + assert trusted_credentials["s3_bucket_name"] == "my-bucket" + proxy_logging_obj.post_call_failure_hook.assert_not_called() + + +def test_delete_file_answers_400_for_an_id_outside_the_configured_bucket(mocker: MockerFixture, monkeypatch): + from urllib.parse import quote + + import litellm.proxy.proxy_server as ps + from litellm.proxy._types import LitellmUserRoles + + bedrock_router = Router( + model_list=[ + { + "model_name": "bedrock-claude", + "litellm_params": { + "model": "bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0", + "aws_access_key_id": "AKIAEXAMPLE", + "aws_secret_access_key": "secret", + "aws_region_name": "us-west-2", + "s3_bucket_name": "my-bucket", + }, + }, + ] + ) + + proxy_logging_obj = setup_proxy_logging_object(monkeypatch, bedrock_router) + monkeypatch.setattr("litellm.proxy.proxy_server.master_key", None) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) + monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", bedrock_router) + proxy_logging_obj.update_request_status = mocker.AsyncMock() + proxy_logging_obj.post_call_success_hook = mocker.AsyncMock(return_value=[]) + proxy_logging_obj.post_call_failure_hook = mocker.AsyncMock() + + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + api_key="test-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + user_id="test-user", + ) + foreign_file_id: Final = quote("s3://other-bucket/litellm-bedrock-files/job-123/input.jsonl", safe="") + + try: + with respx.mock: + response = client.delete( + f"/v1/files/{foreign_file_id}?model=bedrock-claude", + headers={"Authorization": "Bearer test-key"}, + ) + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + assert response.status_code == 400, response.text + assert "configured storage bucket" in response.json()["error"]["message"] + + +def _cloud_files_router() -> Router: + return Router( + model_list=[ + { + "model_name": "bedrock-claude", + "litellm_params": { + "model": "bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0", + "aws_access_key_id": "AKIAEXAMPLE", + "aws_secret_access_key": "secret", + "aws_region_name": "us-west-2", + "s3_bucket_name": "my-bucket", + }, + }, + { + "model_name": "vertex-gemini", + "litellm_params": { + "model": "vertex_ai/gemini-3.8-flash", + "vertex_project": "my-project", + "vertex_location": "us-central1", + "gcs_bucket_name": "my-gcs-bucket", + }, + }, + ] + ) + + +RAW_S3_FILE_ID: Final = "s3://my-bucket/litellm-batch-outputs/job-123/abc/input.jsonl.out" +RAW_GCS_FILE_ID: Final = "gs://my-gcs-bucket/litellm-vertex-files/publishers/google/models/gemini-3.8-flash/abc123" + + +@pytest.mark.parametrize( + ("route_prefix", "raw_file_id", "model_name"), + ( + ("/bedrock/v1/files", RAW_S3_FILE_ID, "bedrock-claude"), + ("/v1/files", RAW_S3_FILE_ID, "bedrock-claude"), + ("/files", RAW_S3_FILE_ID, "bedrock-claude"), + ("/vertex_ai/v1/files", RAW_GCS_FILE_ID, "vertex-gemini"), + ), +) +def test_delete_file_answers_403_for_a_raw_cloud_id_from_a_non_admin_key( + mocker: MockerFixture, monkeypatch, route_prefix: str, raw_file_id: str, model_name: str +): + from urllib.parse import quote + + import litellm.proxy.proxy_server as ps + from litellm.proxy._types import LitellmUserRoles + + bedrock_router = _cloud_files_router() + proxy_logging_obj = setup_proxy_logging_object(monkeypatch, bedrock_router) + monkeypatch.setattr("litellm.proxy.proxy_server.master_key", None) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) + monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", bedrock_router) + proxy_logging_obj.update_request_status = mocker.AsyncMock() + proxy_logging_obj.post_call_failure_hook = mocker.AsyncMock() + afile_delete = mocker.AsyncMock() + monkeypatch.setattr(litellm, "afile_delete", afile_delete) + + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + api_key="test-key", + user_role=LitellmUserRoles.INTERNAL_USER, + user_id="test-user", + models=["bedrock-claude", "vertex-gemini"], + ) + + try: + response = client.delete( + f"{route_prefix}/{quote(raw_file_id, safe='')}?model={model_name}", + headers={"Authorization": "Bearer test-key"}, + ) + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + assert response.status_code == 403, response.text + assert "proxy admin" in response.json()["error"]["message"] + afile_delete.assert_not_called() + + +def test_delete_file_forwards_a_raw_cloud_id_from_a_proxy_admin_key(mocker: MockerFixture, monkeypatch): + from urllib.parse import quote + + import litellm.proxy.proxy_server as ps + from litellm.proxy._types import LitellmUserRoles + + bedrock_router = _cloud_files_router() + proxy_logging_obj = setup_proxy_logging_object(monkeypatch, bedrock_router) + monkeypatch.setattr("litellm.proxy.proxy_server.master_key", None) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) + monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", bedrock_router) + proxy_logging_obj.update_request_status = mocker.AsyncMock() + proxy_logging_obj.post_call_failure_hook = mocker.AsyncMock() + + captured_kwargs: dict = {} + + async def _mock_afile_delete(**kwargs): + captured_kwargs.update(kwargs) + return OpenAIFileObject( + id=RAW_S3_FILE_ID, + object="file", + bytes=2, + created_at=1234567890, + filename="input.jsonl.out", + purpose="batch_output", + status="processed", + ) + + monkeypatch.setattr(litellm, "afile_delete", _mock_afile_delete) + + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + api_key="test-key", + user_role=LitellmUserRoles.PROXY_ADMIN, + user_id="test-user", + ) + + try: + response = client.delete( + f"/bedrock/v1/files/{quote(RAW_S3_FILE_ID, safe='')}?model=bedrock-claude", + headers={"Authorization": "Bearer test-key"}, + ) + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + assert response.status_code == 200, response.text + assert captured_kwargs.get("file_id") == RAW_S3_FILE_ID + assert captured_kwargs.get("custom_llm_provider") == "bedrock" + proxy_logging_obj.post_call_failure_hook.assert_not_called() + + def _setup_managed_file_route_answering_404( mocker: MockerFixture, monkeypatch: pytest.MonkeyPatch, llm_router: Router ) -> None: diff --git a/tests/test_litellm/proxy/openai_files_endpoint/test_general_upload_validation.py b/tests/test_litellm/proxy/openai_files_endpoint/test_general_upload_validation.py index 9f7dd914e4a..b742e1aa9b6 100644 --- a/tests/test_litellm/proxy/openai_files_endpoint/test_general_upload_validation.py +++ b/tests/test_litellm/proxy/openai_files_endpoint/test_general_upload_validation.py @@ -1,4 +1,5 @@ import io +from pathlib import Path import pytest @@ -6,11 +7,14 @@ from litellm.proxy._types import ProxyException from litellm.proxy.openai_files_endpoints.general_upload_validation import ( MB, UploadedFileBlockedExtension, + UploadedFileExtensionNotAllowed, UploadedFileTooLarge, UploadedFileUnsafeFilename, + check_allowed_extension, check_blocked_extension, check_unsafe_filename, check_upload_file_size, + coerce_optional_str_list_setting, raise_upload_validation_failure, ) @@ -79,6 +83,44 @@ def test_no_filename_skips_extension_check(): assert check_blocked_extension(None, (".exe",)) is None +def test_allowed_extension_passes(): + assert check_allowed_extension("batch.jsonl", (".jsonl", ".pdf")) is None + + +@pytest.mark.parametrize("filename", ["payload.exe", "notes.txt", "archive.tar.gz"]) +def test_extension_outside_allowlist_rejected(filename): + assert check_allowed_extension(filename, (".jsonl", ".pdf")) == UploadedFileExtensionNotAllowed( + extension=Path(filename).suffix + ) + + +def test_allowed_extension_match_is_case_insensitive_for_upload(): + assert check_allowed_extension("batch.JSONL", (".jsonl",)) is None + + +def test_allowed_extension_match_is_case_insensitive_for_configured_value(): + assert check_allowed_extension("batch.jsonl", (".JSONL",)) is None + + +@pytest.mark.parametrize("filename", ["README", "", None, "../../"]) +def test_no_extension_rejected_when_allowlist_set(filename): + assert check_allowed_extension(filename, (".jsonl",)) == UploadedFileExtensionNotAllowed(extension="") + + +def test_empty_allowlist_rejects_everything(): + assert check_allowed_extension("batch.jsonl", ()) == UploadedFileExtensionNotAllowed(extension=".jsonl") + + +def test_unset_allowlist_skips_check(): + assert check_allowed_extension("payload.exe", None) is None + + +def test_coerce_str_list_setting_keeps_unset_and_empty_distinct(): + assert coerce_optional_str_list_setting(None) is None + assert coerce_optional_str_list_setting([]) == () + assert coerce_optional_str_list_setting([".jsonl"]) == (".jsonl",) + + def test_path_traversal_filename_rejected(): assert check_unsafe_filename("../../etc/passwd") == UploadedFileUnsafeFilename(filename="../../etc/passwd") @@ -112,6 +154,16 @@ def test_ordinary_filenames_allowed(filename): "413", ("15.0 MB", "max_file_size_mb", "10 MB", "not forwarded"), ), + ( + UploadedFileExtensionNotAllowed(extension=".exe"), + "400", + (".exe", "allowed_file_extensions", "not forwarded"), + ), + ( + UploadedFileExtensionNotAllowed(extension=""), + "400", + ("without an extension", "allowed_file_extensions", "not forwarded"), + ), ( UploadedFileBlockedExtension(extension=".exe"), "400", diff --git a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py index d721be62efe..2d7397594aa 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_anthropic_passthrough_logging_handler.py @@ -7,6 +7,7 @@ from unittest.mock import AsyncMock, MagicMock, patch import pytest +from litellm.integrations.custom_logger import CustomLogger from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj from litellm.proxy.pass_through_endpoints.llm_provider_handlers.anthropic_passthrough_logging_handler import ( AnthropicPassthroughLoggingHandler, @@ -1551,6 +1552,7 @@ class TestInterruptedStreamOutputTokenRecovery: return f"event: {event}\ndata: {json.dumps(data)}\n\n".encode() _MODEL = "claude-3-5-haiku-20241022" + _PRICED_MODEL = "claude-sonnet-5" _OUTPUT_TEXT = ( "The history of computing spans centuries, beginning with mechanical " "calculators and the abacus, advancing through Charles Babbage's " @@ -1559,7 +1561,7 @@ class TestInterruptedStreamOutputTokenRecovery: "century that gave rise to the modern information age." ) - def _interrupted_chunks(self, *, placeholder_output_tokens: int = 2): + def _interrupted_chunks(self, *, placeholder_output_tokens: int = 2, model: str | None = None): from litellm.proxy.pass_through_endpoints.streaming_handler import ( PassThroughStreamingHandler, ) @@ -1574,7 +1576,7 @@ class TestInterruptedStreamOutputTokenRecovery: "id": "msg_interrupted", "type": "message", "role": "assistant", - "model": self._MODEL, + "model": model or self._MODEL, "content": [], "stop_reason": None, "stop_sequence": None, @@ -1676,6 +1678,81 @@ class TestInterruptedStreamOutputTokenRecovery: # provider count is preserved verbatim. assert usage.completion_tokens == final + @pytest.mark.asyncio + async def test_interrupted_stream_logs_cost_of_recovered_tokens(self): + """ + Regression (LIT-6872): stream_chunk_builder stamps usage.cost and + _hidden_params["response_cost"] from the message_start placeholder before + the interrupted stream is re-tokenized, and the success handler prefers + that hidden cost over the recomputed one. The logged cost must price the + recovered completion tokens, not the placeholder. + """ + import litellm + + class _SuccessRecorder(CustomLogger): + def __init__(self): + super().__init__() + self.success_kwargs: list = [] + + async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): + self.success_kwargs.append(kwargs) + + recorder = _SuccessRecorder() + logging_obj = LiteLLMLoggingObj( + model=self._PRICED_MODEL, + messages=[{"role": "user", "content": "hi"}], + stream=True, + call_type="pass_through_endpoint", + start_time=datetime.now(), + litellm_call_id="lit-6872", + function_id="lit-6872", + dynamic_async_success_callbacks=[recorder], + ) + logging_obj.update_environment_variables( + model=self._PRICED_MODEL, + user="", + optional_params={}, + litellm_params={"custom_llm_provider": "anthropic"}, + custom_llm_provider="anthropic", + ) + placeholder = 1 + handled = AnthropicPassthroughLoggingHandler._handle_logging_anthropic_collected_chunks( + litellm_logging_obj=logging_obj, + passthrough_success_handler_obj=MagicMock(), + url_route="/anthropic/v1/messages", + request_body={"model": self._PRICED_MODEL, "stream": True}, + endpoint_type="messages", + start_time=datetime.now(), + all_chunks=self._interrupted_chunks(placeholder_output_tokens=placeholder, model=self._PRICED_MODEL), + end_time=datetime.now(), + ) + await logging_obj.dispatch_success_handlers( + result=handled["result"], + start_time=datetime.now(), + end_time=datetime.now(), + cache_hit=False, + prefer_async_handlers=True, + **handled["kwargs"], + ) + for _ in range(300): + if recorder.success_kwargs: + break + await asyncio.sleep(0.01) + + assert len(recorder.success_kwargs) == 1 + logged = recorder.success_kwargs[0]["standard_logging_object"] + recovered_tokens = handled["result"].usage.completion_tokens + assert recovered_tokens > placeholder + assert logged["completion_tokens"] == recovered_tokens + prompt_cost, completion_cost = litellm.cost_per_token( + model=self._PRICED_MODEL, prompt_tokens=29, completion_tokens=recovered_tokens + ) + _, placeholder_completion_cost = litellm.cost_per_token( + model=self._PRICED_MODEL, prompt_tokens=29, completion_tokens=placeholder + ) + assert logged["response_cost"] == pytest.approx(prompt_cost + completion_cost) + assert logged["response_cost"] > prompt_cost + placeholder_completion_cost + class TestStreamFalseDeduplication: """ diff --git a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_openai_passthrough_logging_handler.py b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_openai_passthrough_logging_handler.py index a3d3ae32169..3d42301ed11 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_openai_passthrough_logging_handler.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/llm_provider_handlers/test_openai_passthrough_logging_handler.py @@ -1832,8 +1832,10 @@ class TestOpenAIPassthroughResponsesStreamingSpendLog: def setup_method(self): self.start_time = datetime.now() self.end_time = datetime.now() + + def _expected_spend(self) -> float: rates = litellm.model_cost[self.MODEL_MAP_KEY] - self.expected_spend = ( + return ( self.INPUT_TOKENS * rates["input_cost_per_token"] + self.OUTPUT_TOKENS * rates["output_cost_per_token"] ) @@ -1914,7 +1916,7 @@ class TestOpenAIPassthroughResponsesStreamingSpendLog: logging_obj.model_call_details["custom_llm_provider"] = "openai" return logging_obj - def test_streamed_responses_passthrough_spend_log_is_priced(self): + def test_streamed_responses_passthrough_spend_log_is_priced(self, local_model_cost_map): """The spend row books the same tokens, spend and `resp_` id as the buffered call.""" result = OpenAIPassthroughLoggingHandler._handle_logging_openai_collected_chunks( litellm_logging_obj=self._logging_obj(), @@ -1942,7 +1944,7 @@ class TestOpenAIPassthroughResponsesStreamingSpendLog: assert spend_log_row["prompt_tokens"] == self.INPUT_TOKENS assert spend_log_row["completion_tokens"] == self.OUTPUT_TOKENS assert spend_log_row["total_tokens"] == self.INPUT_TOKENS + self.OUTPUT_TOKENS - assert spend_log_row["spend"] == self.expected_spend + assert spend_log_row["spend"] == pytest.approx(self._expected_spend()) assert spend_log_row["request_id"] == self.RESPONSE_ID assert spend_log_row["model"] == "gpt-4o-mini" @@ -1967,7 +1969,6 @@ class TestOpenAIPassthroughEmbeddingsSpendLog: def setup_method(self): self.start_time = datetime.now() self.end_time = datetime.now() - self.expected_spend = self.PROMPT_TOKENS * litellm.model_cost[self.MODEL]["input_cost_per_token"] self.response_body = { "object": "list", "data": [{"object": "embedding", "index": 0, "embedding": [0.0, 1.0]}], @@ -1976,6 +1977,9 @@ class TestOpenAIPassthroughEmbeddingsSpendLog: } self.request_body = {"model": self.MODEL, "input": "hello"} + def _expected_spend(self) -> float: + return self.PROMPT_TOKENS * litellm.model_cost[self.MODEL]["input_cost_per_token"] + def _create_mock_httpx_response(self) -> httpx.Response: mock_response = MagicMock(spec=httpx.Response) mock_response.status_code = 200 @@ -2001,7 +2005,7 @@ class TestOpenAIPassthroughEmbeddingsSpendLog: ) return logging_obj - def test_embeddings_passthrough_spend_log_is_priced(self): + def test_embeddings_passthrough_spend_log_is_priced(self, local_model_cost_map): """The dispatched call books prompt tokens and cost onto the spend row.""" dispatched = PassThroughEndpointLogging().normalize_llm_passthrough_logging_payload( httpx_response=self._create_mock_httpx_response(), @@ -2020,7 +2024,7 @@ class TestOpenAIPassthroughEmbeddingsSpendLog: ) assert dispatched["standard_logging_response_object"] is not None - assert dispatched["kwargs"]["response_cost"] == self.expected_spend + assert dispatched["kwargs"]["response_cost"] == pytest.approx(self._expected_spend()) spend_log_row = get_logging_payload( kwargs=dispatched["kwargs"], @@ -2031,7 +2035,7 @@ class TestOpenAIPassthroughEmbeddingsSpendLog: assert spend_log_row["prompt_tokens"] == self.PROMPT_TOKENS assert spend_log_row["total_tokens"] == self.PROMPT_TOKENS - assert spend_log_row["spend"] == self.expected_spend + assert spend_log_row["spend"] == pytest.approx(self._expected_spend()) assert spend_log_row["model"] == self.MODEL assert spend_log_row["custom_llm_provider"] == "openai" assert spend_log_row["request_id"] == self.CALL_ID diff --git a/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py b/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py index d57bed430c1..11066d4ed38 100644 --- a/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py +++ b/tests/test_litellm/proxy/pass_through_endpoints/test_pass_through_endpoints.py @@ -5030,6 +5030,100 @@ async def test_websocket_passthrough_rewrites_gateway_alias_setup_model(): assert sent_setup["model"] == "projects/proj-db/locations/global/publishers/google/models/gemini-live-2.5-flash" +@pytest.mark.parametrize( + "setup_model", + ["gemini-live-2.5-flash", "models/gemini-live-2.5-flash", "publishers/google/models/gemini-live-2.5-flash"], +) +def test_vertex_live_setup_model_resolves_before_extraction(setup_model): + """A bare gateway alias left the session logged as ``unknown`` at zero cost. + + The model was read off the raw client frame, and the extractor only yields a name when the string + already contains ``/models/``. The rewriter qualifies it a few lines later for the upstream, so a + client that addressed the gateway the documented way, by alias, logged no model and therefore + resolved no cost-map entry. Resolving first is what puts the real name on the logging object. + """ + from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import ( + _build_vertex_live_setup_model_rewriter, + ) + from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( + _extract_model_from_vertex_ai_setup, + _resolved_vertex_live_setup, + ) + + rewriter = _build_vertex_live_setup_model_rewriter( + vertex_project="proj-db", vertex_location="global", llm_router=None + ) + setup_data = {"model": setup_model} + + resolved = _extract_model_from_vertex_ai_setup(_resolved_vertex_live_setup(setup_data, rewriter)) + + assert resolved == "gemini-live-2.5-flash", "an unresolved setup model logs the session as 'unknown'" + + +@pytest.mark.asyncio +async def test_websocket_passthrough_logs_a_bare_alias_setup_model(): + """End to end through the relay: a bare alias must reach the logging object as a real model name. + + This is the call-site half of the fix. The helper tests above pass even if extraction moves back + before the rewrite, so this one drives the real websocket relay and asserts on what got logged, + which is the name the cost map is looked up by. An unbilled session logs ``unknown``. + """ + from litellm.proxy.pass_through_endpoints.llm_passthrough_endpoints import ( + _build_vertex_live_setup_model_rewriter, + ) + + upstream_ws = RecordingUpstreamWebSocket() + setup_frame = json.dumps({"setup": {"model": "gemini-live-2.5-flash"}}) + websocket = _client_websocket( + AsyncMock( + side_effect=[ + {"type": "websocket.receive", "text": setup_frame}, + {"type": "websocket.disconnect"}, + ] + ) + ) + built = [] + real_logging = litellm.litellm_core_utils.litellm_logging.Logging + + def _capture(*args, **kwargs): + obj = real_logging(*args, **kwargs) + built.append(obj) + return obj + + with _patched_websocket_passthrough_environment(upstream_ws): + with patch("litellm.litellm_core_utils.litellm_logging.Logging", side_effect=_capture): + await websocket_passthrough_request( + websocket=websocket, + target="wss://aiplatform.googleapis.com/ws/google.cloud.aiplatform.v1.LlmBidiService/BidiGenerateContent", + custom_headers={"Authorization": "Bearer token"}, + user_api_key_dict=UserAPIKeyAuth(), + forward_headers=False, + endpoint="/vertex_ai/live", + accept_websocket=False, + setup_model_rewriter=_build_vertex_live_setup_model_rewriter( + vertex_project="proj-db", vertex_location="global", llm_router=None + ), + ) + + assert built, "the relay should have built a logging object" + assert built[0].model == "gemini-live-2.5-flash", "a bare alias must not log as 'unknown'" + + +def test_vertex_live_setup_resolution_is_inert_without_a_rewriter(): + """Non-Live passthrough routes pass no rewriter, so the frame must be handed over untouched.""" + from litellm.proxy.pass_through_endpoints.pass_through_endpoints import ( + _extract_model_from_vertex_ai_setup, + _resolved_vertex_live_setup, + ) + + setup_data = {"model": "projects/p/locations/global/publishers/google/models/gemini-live-2.5-flash"} + + assert _resolved_vertex_live_setup(setup_data, None) is setup_data + assert _extract_model_from_vertex_ai_setup(_resolved_vertex_live_setup(setup_data, None)) == ( + "gemini-live-2.5-flash" + ) + + @pytest.mark.asyncio @pytest.mark.parametrize("rcvd_close", [None, "abnormal", "no_status"]) async def test_websocket_passthrough_does_not_relay_unsendable_upstream_close(rcvd_close): diff --git a/tests/test_litellm/proxy/proxy_server/test_proxy_config.py b/tests/test_litellm/proxy/proxy_server/test_proxy_config.py index e79448d0620..d6851116324 100644 --- a/tests/test_litellm/proxy/proxy_server/test_proxy_config.py +++ b/tests/test_litellm/proxy/proxy_server/test_proxy_config.py @@ -8,6 +8,7 @@ Pins covered: from __future__ import annotations +import asyncio import json import logging import os @@ -712,22 +713,124 @@ async def test_ProxyConfig__get_config_from_file_missing_path_raises(): # --------------------------------------------------------------------------- -def test_ProxyConfig__process_includes_merges_files(tmp_path): +@pytest.mark.asyncio +async def test_ProxyConfig__process_includes_merges_files(tmp_path): inc = tmp_path / "models.yaml" inc.write_text("model_list:\n - model_name: gpt-4\n") pc = ProxyConfig() cfg = {"include": ["models.yaml"], "model_list": [], "litellm_settings": {}} - result = pc._process_includes(cfg, base_dir=str(tmp_path)) + result = await pc._process_includes(cfg, config_file_path=str(tmp_path / "config.yaml")) assert result == { "model_list": [{"model_name": "gpt-4"}], "litellm_settings": {}, } -def test_ProxyConfig__process_includes_missing_file_raises(tmp_path): +@pytest.mark.asyncio +async def test_ProxyConfig__process_includes_missing_file_raises(tmp_path): pc = ProxyConfig() with pytest.raises(FileNotFoundError): - pc._process_includes({"include": ["nope.yaml"]}, base_dir=str(tmp_path)) + await pc._process_includes({"include": ["nope.yaml"]}, config_file_path=str(tmp_path / "config.yaml")) + + +@pytest.mark.asyncio +async def test_ProxyConfig__process_includes_follows_nested_includes(tmp_path): + (tmp_path / "models.yaml").write_text("include:\n - more_models.yaml\nmodel_list:\n - model_name: first\n") + (tmp_path / "more_models.yaml").write_text("model_list:\n - model_name: second\n") + result = await ProxyConfig()._process_includes( + {"include": ["models.yaml"]}, config_file_path=str(tmp_path / "config.yaml") + ) + assert result == {"model_list": [{"model_name": "first"}, {"model_name": "second"}]} + + +@pytest.mark.asyncio +async def test_ProxyConfig__process_includes_resolves_a_nested_include_next_to_its_own_file(tmp_path): + (tmp_path / "shared").mkdir() + (tmp_path / "shared" / "models.yaml").write_text( + "include:\n - more_models.yaml\nmodel_list:\n - model_name: first\n" + ) + (tmp_path / "shared" / "more_models.yaml").write_text("model_list:\n - model_name: second\n") + (tmp_path / "more_models.yaml").write_text("model_list:\n - model_name: wrong-directory\n") + + result = await ProxyConfig()._process_includes( + {"include": ["shared/models.yaml"]}, config_file_path=str(tmp_path / "config.yaml") + ) + + assert result == {"model_list": [{"model_name": "first"}, {"model_name": "second"}]} + + +@pytest.mark.asyncio +async def test_ProxyConfig__process_includes_still_reads_a_nested_include_left_beside_the_root_config(tmp_path): + (tmp_path / "shared").mkdir() + (tmp_path / "shared" / "models.yaml").write_text( + "include:\n - more_models.yaml\nmodel_list:\n - model_name: first\n" + ) + (tmp_path / "more_models.yaml").write_text("model_list:\n - model_name: second\n") + + result = await ProxyConfig()._process_includes( + {"include": ["shared/models.yaml"]}, config_file_path=str(tmp_path / "config.yaml") + ) + + assert result == {"model_list": [{"model_name": "first"}, {"model_name": "second"}]} + + +@pytest.mark.asyncio +async def test_ProxyConfig__process_includes_names_both_files_when_a_nested_include_matches_two(tmp_path, caplog): + (tmp_path / "shared").mkdir() + (tmp_path / "shared" / "models.yaml").write_text( + "include:\n - more_models.yaml\nmodel_list:\n - model_name: first\n" + ) + (tmp_path / "shared" / "more_models.yaml").write_text("model_list:\n - model_name: next-to-the-declaring-file\n") + (tmp_path / "more_models.yaml").write_text("model_list:\n - model_name: next-to-the-root-config\n") + + with caplog.at_level(logging.WARNING, logger="LiteLLM Proxy"): + result = await ProxyConfig()._process_includes( + {"include": ["shared/models.yaml"]}, config_file_path=str(tmp_path / "config.yaml") + ) + + assert result == {"model_list": [{"model_name": "first"}, {"model_name": "next-to-the-declaring-file"}]} + assert [ + record + for record in caplog.records + if str(tmp_path / "shared" / "more_models.yaml") in record.getMessage() + and str(tmp_path / "more_models.yaml") in record.getMessage() + ] + + +@pytest.mark.asyncio +async def test_ProxyConfig__process_includes_merges_a_shared_file_once(tmp_path): + (tmp_path / "shared.yaml").write_text("model_list:\n - model_name: shared\n") + (tmp_path / "a.yaml").write_text("include:\n - shared.yaml\n") + (tmp_path / "b.yaml").write_text("include:\n - ./shared.yaml\n") + + result = await ProxyConfig()._process_includes( + {"include": ["a.yaml", "b.yaml"]}, config_file_path=str(tmp_path / "config.yaml") + ) + + assert result == {"model_list": [{"model_name": "shared"}]} + + +@pytest.mark.asyncio +async def test_ProxyConfig__process_includes_names_the_file_when_it_is_not_a_mapping(tmp_path): + (tmp_path / "models.yaml").write_text("- model_name: gpt-4\n") + + with pytest.raises(ValueError, match=re.escape(str(tmp_path / "models.yaml"))): + await ProxyConfig()._process_includes( + {"include": ["models.yaml"]}, config_file_path=str(tmp_path / "config.yaml") + ) + + +@pytest.mark.asyncio +async def test_ProxyConfig__process_includes_terminates_on_a_cycle(tmp_path): + (tmp_path / "a.yaml").write_text("include:\n - b.yaml\nmodel_list:\n - model_name: from-a\n") + (tmp_path / "b.yaml").write_text("include:\n - a.yaml\nmodel_list:\n - model_name: from-b\n") + + result = await asyncio.wait_for( + ProxyConfig()._process_includes({"include": ["a.yaml"]}, config_file_path=str(tmp_path / "config.yaml")), + timeout=10, + ) + + assert result == {"model_list": [{"model_name": "from-a"}, {"model_name": "from-b"}]} # --------------------------------------------------------------------------- @@ -1044,6 +1147,31 @@ async def test_ProxyConfig_get_config_loads_from_file(tmp_path, monkeypatch): } +@pytest.mark.asyncio +async def test_ProxyConfig_get_config_from_a_bucket_merges_includes(monkeypatch): + objects = { + "lit6982/config.yaml": { + "include": ["model_config.yaml"], + "general_settings": {"master_key": "sk-1234"}, + }, + "lit6982/model_config.yaml": {"model_list": [{"model_name": "included-model"}]}, + } + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) + monkeypatch.setattr("litellm.proxy.proxy_server.store_model_in_db", False) + monkeypatch.setattr( + "litellm.proxy.common_utils.load_config_utils.s3_object_reader", + lambda bucket_name: objects.get, + ) + monkeypatch.setenv("LITELLM_CONFIG_BUCKET_NAME", "litellm-configs") + monkeypatch.setenv("LITELLM_CONFIG_BUCKET_OBJECT_KEY", "lit6982/config.yaml") + monkeypatch.setenv("LITELLM_CONFIG_BUCKET_TYPE", "s3") + + cfg = await ProxyConfig().get_config() + + assert cfg["model_list"] == [{"model_name": "included-model"}] + assert "include" not in cfg + + @pytest.mark.asyncio async def test_ProxyConfig_get_config_missing_file_raises(monkeypatch): monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) @@ -3341,6 +3469,30 @@ async def test_ProxyConfig__update_general_settings_cleared_db_max_batch_file_si assert ps.general_settings.get("max_batch_file_size_mb") is None +@pytest.mark.asyncio +async def test_ProxyConfig__update_general_settings_applies_db_allowed_file_extensions(monkeypatch): + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) + pc = ProxyConfig() + await pc._update_general_settings({"allowed_file_extensions": [".jsonl"]}) + from litellm.proxy import proxy_server as ps + + assert ps.general_settings.get("allowed_file_extensions") == [".jsonl"] + + +@pytest.mark.asyncio +async def test_ProxyConfig__update_general_settings_yaml_allowed_file_extensions_wins_over_db(monkeypatch): + monkeypatch.setattr( + "litellm.proxy.proxy_server.general_settings", + {"allowed_file_extensions": [".pdf"]}, + ) + pc = ProxyConfig() + pc._yaml_general_settings_keys = {"allowed_file_extensions"} + await pc._update_general_settings({"allowed_file_extensions": [".jsonl"]}) + from litellm.proxy import proxy_server as ps + + assert ps.general_settings.get("allowed_file_extensions") == [".pdf"] + + @pytest.mark.asyncio async def test_ProxyConfig__update_general_settings_none_input_noop(): pc = ProxyConfig() diff --git a/tests/test_litellm/proxy/proxy_server/test_routes_login_sso.py b/tests/test_litellm/proxy/proxy_server/test_routes_login_sso.py index 45460dcecf1..79c23b11f3e 100644 --- a/tests/test_litellm/proxy/proxy_server/test_routes_login_sso.py +++ b/tests/test_litellm/proxy/proxy_server/test_routes_login_sso.py @@ -97,6 +97,7 @@ def test_fallback_login_returns_html_form_with_ui_username_set(client, monkeypat def test_fallback_login_shows_credentials_hint_by_default(client, monkeypatch): """Control: without the flag, /fallback/login still renders the hint.""" monkeypatch.delenv("UI_USERNAME", raising=False) + monkeypatch.delenv("UI_PASSWORD", raising=False) monkeypatch.delenv("LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", raising=False) response = client.get("/fallback/login") assert response.status_code == 200 @@ -104,6 +105,16 @@ def test_fallback_login_shows_credentials_hint_by_default(client, monkeypatch): assert "MASTER_KEY" in response.text +def test_fallback_login_hides_credentials_hint_when_ui_password_set(client, monkeypatch): + monkeypatch.setenv("UI_PASSWORD", "s3cret-pass") + monkeypatch.delenv("LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT", raising=False) + response = client.get("/fallback/login") + assert response.status_code == 200 + assert "Default Credentials" not in response.text + assert "MASTER_KEY" not in response.text + assert 'name="username"' in response.text + + def test_fallback_login_hides_credentials_hint_via_env_flag(client, monkeypatch): """Pin: LITELLM_HIDE_DEFAULT_CREDENTIALS_HINT removes the hint on /fallback/login.""" monkeypatch.delenv("UI_USERNAME", raising=False) diff --git a/tests/test_litellm/proxy/proxy_server/test_spend_counters.py b/tests/test_litellm/proxy/proxy_server/test_spend_counters.py index 6eac53df645..68462065393 100644 --- a/tests/test_litellm/proxy/proxy_server/test_spend_counters.py +++ b/tests/test_litellm/proxy/proxy_server/test_spend_counters.py @@ -1180,6 +1180,24 @@ async def test_apply_spend_counter_increments_open_breaker_invalidates_and_retur fake_cache.in_memory_cache.set_cache.assert_not_called() +@pytest.mark.asyncio +async def test_apply_spend_counter_increments_redis_timeout_invalidates_and_returns(monkeypatch): + """A Redis timeout invalidates the counters and returns without reaching the cost callback's error path.""" + from redis.exceptions import TimeoutError as RedisTimeoutError + + fake_cache = _make_spend_counter_cache() + fake_cache.redis_cache.async_increment_pipeline = AsyncMock( + side_effect=RedisTimeoutError("Timeout reading from 127.0.0.1:6379") + ) + monkeypatch.setattr(ps, "spend_counter_cache", fake_cache) + + await ps._apply_spend_counter_increments(_two_pending_increments()) + + deleted_keys = sorted(call.kwargs["key"] for call in fake_cache.in_memory_cache.delete_cache.call_args_list) + assert deleted_keys == ["spend:key:k", "spend:team:t"] + fake_cache.in_memory_cache.set_cache.assert_not_called() + + @pytest.mark.asyncio async def test_apply_spend_counter_increments_other_redis_error_invalidates_and_raises(monkeypatch): fake_cache = _make_spend_counter_cache() diff --git a/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py b/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py index bc346874e0d..baa032f75e6 100644 --- a/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py +++ b/tests/test_litellm/proxy/proxy_server/test_team_model_name_translation.py @@ -9,6 +9,7 @@ rows instead of the internal routing key `model_name_{team_id}_{uuid}`. from __future__ import annotations +import json from unittest.mock import AsyncMock, MagicMock import pytest @@ -238,7 +239,7 @@ async def test_model_info_v1_list_path_translates_team_model_name(monkeypatch): ) resp = await ps.model_info_v1(user_api_key_dict=admin, litellm_model_id=None) - names = [m["model_name"] for m in resp["data"]] + names = [m["model_name"] for m in json.loads(resp.body)["data"]] assert "team-claude-sonnet" in names assert "model_name_team-abc-123_4a6b8" not in names @@ -271,7 +272,7 @@ async def test_model_info_v1_unrestricted_key_returns_all_deployments(monkeypatc ) resp = await ps.model_info_v1(user_api_key_dict=caller, litellm_model_id=None) - assert [m["model_name"] for m in resp["data"]] == ["gpt-4"] + assert [m["model_name"] for m in json.loads(resp.body)["data"]] == ["gpt-4"] @pytest.mark.asyncio @@ -303,7 +304,7 @@ async def test_model_info_v1_restricted_key_filters_deployments(monkeypatch): ) resp = await ps.model_info_v1(user_api_key_dict=caller, litellm_model_id=None) - assert [m["model_name"] for m in resp["data"]] == ["gpt-4"] + assert [m["model_name"] for m in json.loads(resp.body)["data"]] == ["gpt-4"] def _other_team_row() -> dict: @@ -367,10 +368,11 @@ async def test_model_info_v1_unrestricted_key_hides_other_team_byok(monkeypatch) ) resp = await ps.model_info_v1(user_api_key_dict=caller, litellm_model_id=None) - returned_ids = {m["model_info"]["id"] for m in resp["data"]} + data = json.loads(resp.body)["data"] + returned_ids = {m["model_info"]["id"] for m in data} assert returned_ids == {"global-id-1", "byok-id-1"} assert "byok-id-other" not in returned_ids - names = [m["model_name"] for m in resp["data"]] + names = [m["model_name"] for m in data] assert "team-claude-sonnet" in names assert "gpt-4" in names @@ -412,7 +414,7 @@ async def test_model_info_v1_service_key_hides_all_team_byok(monkeypatch): ) resp = await ps.model_info_v1(user_api_key_dict=caller, litellm_model_id=None) - assert [m["model_info"]["id"] for m in resp["data"]] == ["global-id-1"] + assert [m["model_info"]["id"] for m in json.loads(resp.body)["data"]] == ["global-id-1"] @pytest.mark.asyncio @@ -466,7 +468,7 @@ async def test_model_info_v1_team_key_sees_own_byok_regardless_of_user_lookup( ) resp = await ps.model_info_v1(user_api_key_dict=caller, litellm_model_id=None) - assert [m["model_info"]["id"] for m in resp["data"]] == ["byok-id-1", "global-id-1"] + assert [m["model_info"]["id"] for m in json.loads(resp.body)["data"]] == ["byok-id-1", "global-id-1"] @pytest.mark.asyncio @@ -509,7 +511,7 @@ async def test_model_info_v1_user_team_membership_grants_byok(monkeypatch): ) resp = await ps.model_info_v1(user_api_key_dict=caller, litellm_model_id=None) - assert [m["model_info"]["id"] for m in resp["data"]] == [ + assert [m["model_info"]["id"] for m in json.loads(resp.body)["data"]] == [ "byok-id-other", "global-id-1", ] @@ -557,7 +559,7 @@ async def test_model_info_v1_populates_access_via_team_ids(monkeypatch): ) resp = await ps.model_info_v1(user_api_key_dict=admin, litellm_model_id=None) - by_id = {m["model_info"]["id"]: m for m in resp["data"]} + by_id = {m["model_info"]["id"]: m for m in json.loads(resp.body)["data"]} assert by_id["byok-id-1"]["model_info"]["access_via_team_ids"] == [team_id] assert by_id["byok-id-1"]["model_info"]["direct_access"] is False assert by_id["global-id-1"]["model_info"]["direct_access"] is True @@ -816,7 +818,7 @@ async def test_model_info_v1_litellm_model_id_include_team_models_filters_inacce include_team_models=True, ) - assert resp["data"] == [] + assert json.loads(resp.body)["data"] == [] @pytest.mark.asyncio @@ -852,7 +854,7 @@ async def test_model_info_v1_litellm_model_id_team_id_applies_team_filter(monkey teamId="other-team", ) - assert resp["data"] == [] + assert json.loads(resp.body)["data"] == [] team_filter.assert_awaited_once() assert team_filter.await_args.kwargs["team_id"] == "other-team" assert team_filter.await_args.kwargs["all_models"] == [team_row] diff --git a/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py b/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py index 6e43ac4a12b..8283ee8395a 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py +++ b/tests/test_litellm/proxy/spend_tracking/test_spend_management_endpoints.py @@ -124,7 +124,10 @@ def _reconstruct_ui_where_from_sql(sql_query, params): sess = re.fullmatch(r"session_id LIKE \$(\d+)", cond) status = re.fullmatch(r"status = \$(\d+)", cond) api_key_not_in = re.fullmatch(r"api_key NOT IN \(\$(\d+), \$(\d+)\)", cond) - if gte: + req_or_call = re.fullmatch(r"\(request_id = \$(\d+) OR litellm_call_id = \$\1\)", cond) + if req_or_call: + where["request_id_or_call_id"] = params[int(req_or_call.group(1)) - 1] + elif gte: date_bounds["gte"] = _iso(params[int(gte.group(1)) - 1]) elif lte: date_bounds["lte"] = _iso(params[int(lte.group(1)) - 1]) @@ -213,6 +216,8 @@ def make_ui_spend_logs_mock_prisma(mock_spend_logs, filter_fn, team_lookup_fn=No query_observer(sql_query, params) if "mcp_tool_call_count" in sql_query: return [] + if 'SELECT DISTINCT "user", team_id' in sql_query: + return _emulate_spend_log_owner_lookup(mock_spend_logs, sql_query, params) filtered = filter_fn(_reconstruct_ui_where_from_sql(sql_query, params)) total = len(filtered) if "COUNT(*)" in sql_query: @@ -220,7 +225,13 @@ def make_ui_spend_logs_mock_prisma(mock_spend_logs, filter_fn, team_lookup_fn=No return [{"total_count": min(total, cap_plus_one)}] page_size = params[-2] if len(params) >= 2 else 50 skip = params[-1] if len(params) >= 1 else 0 - return [row for row in filtered[skip : skip + page_size]] + exact_first = re.search(r"ORDER BY \(request_id = \$(\d+)\) DESC", sql_query) + ordered = ( + sorted(filtered, key=lambda row: row["request_id"] == params[int(exact_first.group(1)) - 1], reverse=True) + if exact_first + else filtered + ) + return [row for row in ordered[skip : skip + page_size]] class MockPrismaClient: def __init__(self): @@ -424,37 +435,173 @@ def test_can_user_view_spend_log_false_for_other_roles(): assert spend_management_endpoints._can_user_view_spend_log(auth) is False +def _emulate_spend_log_owner_lookup(rows, sql_query, params): + """Emulate the ownership lookup SQL over an in-memory spend-log corpus, + honoring DISTINCT and any literal LIMIT the query carries so a capped or + non-distinct query produces the truncated result it would in Postgres.""" + lookup_id = params[0] + matches = [ + {"user": row.get("user"), "team_id": row.get("team_id")} + for row in rows + if lookup_id in (row.get("request_id"), row.get("litellm_call_id")) + ] + if "DISTINCT" in sql_query: + deduped = [] + for match in matches: + if match not in deduped: + deduped.append(match) + matches = deduped + limit = re.search(r"LIMIT\s+(\d+)", sql_query, re.IGNORECASE) + if limit is not None: + matches = matches[: int(limit.group(1))] + return matches + + +def _make_owner_lookup_prisma(rows): + class MockDB: + async def query_raw(self, sql_query, *params): + return _emulate_spend_log_owner_lookup(rows, sql_query, params) + + class MockPrisma: + def __init__(self): + self.db = MockDB() + + return MockPrisma() + + @pytest.mark.asyncio async def test_assert_user_can_view_request_id_rejects_both_users_none(): """ API keys with user_id=None must not be treated as owning a log whose user field is None (avoid None == None bypass). """ - - class MockRow: - user = None - team_id = None - - class MockSpendLogs: - async def find_unique(self, where, include=None): - return MockRow() - - class MockDB: - def __init__(self): - self.litellm_spendlogs = MockSpendLogs() - - class MockPrisma: - def __init__(self): - self.db = MockDB() + prisma = _make_owner_lookup_prisma( + [{"request_id": "req-none-user", "litellm_call_id": None, "user": None, "team_id": None}] + ) auth = UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER, user_id=None) with pytest.raises(HTTPException) as exc_info: await spend_management_endpoints._assert_user_can_view_request_id( - MockPrisma(), auth, "req-none-user" + prisma, auth, "req-none-user" ) assert exc_info.value.status_code == 403 +@pytest.mark.asyncio +async def test_assert_user_can_view_request_id_rejects_when_no_match_is_owned(): + """An id whose every matching row belongs to other tenants is refused outright, + so the relaxed date window of an id lookup cannot reach a foreign row.""" + prisma = _make_owner_lookup_prisma( + [ + {"request_id": "foreign-request", "litellm_call_id": "shared-id", "user": "tenant_a", "team_id": None}, + {"request_id": "shared-id", "litellm_call_id": "other-call-id", "user": "tenant_b", "team_id": None}, + ] + ) + + auth = UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER, user_id="caller") + with pytest.raises(HTTPException) as exc_info: + await spend_management_endpoints._assert_user_can_view_request_id(prisma, auth, "shared-id") + assert exc_info.value.status_code == 403 + + +@pytest.mark.asyncio +async def test_assert_user_can_view_request_id_allows_owner_despite_foreign_collision(): + """ + litellm_call_id comes from the client-settable x-litellm-call-id header, so + another tenant can mint a row whose call id equals the caller's request_id. + That collision must not lock the caller out of their own row: the pre-check + passes once one match is theirs, and the scoped data queries keep the foreign + row out of the result. Regression for the every-match-must-be-owned rule that + let any tenant deny another's lookup by reusing their id. + """ + prisma = _make_owner_lookup_prisma( + [ + { + "request_id": "attacker-own-request", + "litellm_call_id": "victim-request-id", + "user": "attacker", + "team_id": None, + }, + { + "request_id": "victim-request-id", + "litellm_call_id": "victim-call-id", + "user": "victim", + "team_id": None, + }, + ] + ) + + auth = UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER, user_id="victim") + result = await spend_management_endpoints._assert_user_can_view_request_id(prisma, auth, "victim-request-id") + + assert result is None + + +@pytest.mark.asyncio +async def test_assert_user_can_view_request_id_finds_owner_past_any_row_cap(): + """ + An attacker can mint hundreds of rows carrying the victim's request_id as + their litellm_call_id, so a capped or sampled ownership read could exhaust + its cap on attacker-owned rows and never see the victim's own row, locking + the victim out of their lookup. The ownership read must consider every + matching row's owner no matter how many rows match. Regression for the + find_many(take=100) sample the first fix used. + """ + rows = [ + { + "request_id": f"attacker-request-{i}", + "litellm_call_id": "victim-request-id", + "user": "attacker", + "team_id": None, + } + for i in range(150) + ] + rows.append( + { + "request_id": "victim-request-id", + "litellm_call_id": "victim-call-id", + "user": "victim", + "team_id": None, + } + ) + prisma = _make_owner_lookup_prisma(rows) + + auth = UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER, user_id="victim") + result = await spend_management_endpoints._assert_user_can_view_request_id(prisma, auth, "victim-request-id") + + assert result is None + + +@pytest.mark.asyncio +async def test_assert_user_can_view_request_id_allows_when_every_match_is_owned(): + """The same ambiguous id matching more than one row is fine when every match + belongs to the caller (e.g. two of the caller's own requests happen to share + a request_id/litellm_call_id pairing); only a foreign match should block it.""" + prisma = _make_owner_lookup_prisma( + [ + { + "request_id": "shared-request-id", + "litellm_call_id": "caller-call-a", + "user": "caller", + "team_id": None, + }, + { + "request_id": "caller-request-b", + "litellm_call_id": "shared-request-id", + "user": "caller", + "team_id": None, + }, + ] + ) + + auth = UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER, user_id="caller") + result = await spend_management_endpoints._assert_user_can_view_request_id( + prisma, auth, "shared-request-id" + ) + + assert result is None + + @pytest.mark.asyncio async def test_assert_user_can_view_request_id_rejects_missing_row(): """ @@ -462,24 +609,11 @@ async def test_assert_user_can_view_request_id_rejects_missing_row(): authorize reading the payload from cold storage; a missing row is not the same as an owned row. """ - - class MockSpendLogs: - async def find_unique(self, where, include=None): - return None - - class MockDB: - def __init__(self): - self.litellm_spendlogs = MockSpendLogs() - - class MockPrisma: - def __init__(self): - self.db = MockDB() + prisma = _make_owner_lookup_prisma([]) auth = UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER, user_id="user_1") with pytest.raises(HTTPException) as exc_info: - await spend_management_endpoints._assert_user_can_view_request_id( - MockPrisma(), auth, "req-missing-row" - ) + await spend_management_endpoints._assert_user_can_view_request_id(prisma, auth, "req-missing-row") assert exc_info.value.status_code == 403 @@ -507,6 +641,7 @@ def test_ui_view_request_response_forbids_non_admin_without_db(client, monkeypat ignored_keys = [ "request_id", + "litellm_call_id", "metadata.litellm_call_id", "session_id", "startTime", @@ -2216,7 +2351,10 @@ async def test_ui_view_spend_logs_request_id_lookup_ignores_date_window( def filter_fn(where): captured["where"] = where rows = _filter_logs_by_date_range(mock_spend_logs, where) - if where.get("request_id"): + rid_either = where.get("request_id_or_call_id") + if rid_either: + rows = [r for r in rows if rid_either in (r["request_id"], r.get("litellm_call_id"))] + elif where.get("request_id"): rows = [r for r in rows if r["request_id"] == where["request_id"]] return rows @@ -2246,9 +2384,82 @@ async def test_ui_view_spend_logs_request_id_lookup_ignores_date_window( data = response.json() assert data["total"] == 1 assert data["data"][0]["request_id"] == "req-old" - # Query dropped the time window and scoped solely by the primary key. + # Query dropped the time window and scoped solely by the id lookup. assert "startTime" not in captured["where"] - assert captured["where"]["request_id"] == "req-old" + assert captured["where"]["request_id_or_call_id"] == "req-old" + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + +@pytest.mark.asyncio +async def test_ui_view_spend_logs_request_id_lookup_matches_litellm_call_id( + client, monkeypatch +): + """ + LIT-6302: success rows are keyed by the upstream provider response id, so a + lookup with the x-litellm-call-id response header value found nothing. The id + lookup now matches request_id OR litellm_call_id, resolving the header value. + """ + today = datetime.datetime.now(timezone.utc) + mock_spend_logs = [ + { + "id": "log_provider_keyed", + "request_id": "chatcmpl-9ZKMURhVYSi9D6r6PJ9vLcayIK0Vm", + "litellm_call_id": "b980eea9-5cd9-4099-93cd-8291e46c76fd", + "api_key": "sk-test-key", + "user": "test_user_1", + "team_id": "team1", + "spend": 0.05, + "startTime": today.isoformat(), + "model": "gpt-4", + }, + { + "id": "log_other", + "request_id": "chatcmpl-other", + "litellm_call_id": "11111111-2222-3333-4444-555555555555", + "api_key": "sk-test-key", + "user": "test_user_1", + "team_id": "team1", + "spend": 0.01, + "startTime": today.isoformat(), + "model": "gpt-4", + }, + ] + + def filter_fn(where): + rid_either = where.get("request_id_or_call_id") + if rid_either: + return [ + r + for r in mock_spend_logs + if rid_either in (r["request_id"], r.get("litellm_call_id")) + ] + if where.get("request_id"): + return [ + r for r in mock_spend_logs if r["request_id"] == where["request_id"] + ] + return list(mock_spend_logs) + + monkeypatch.setattr( + "litellm.proxy.proxy_server.prisma_client", + make_ui_spend_logs_mock_prisma(mock_spend_logs, filter_fn), + ) + + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN + ) + try: + response = client.get( + "/spend/logs/ui", + params={"request_id": "b980eea9-5cd9-4099-93cd-8291e46c76fd"}, + headers={"Authorization": "Bearer sk-test"}, + ) + assert response.status_code == 200 + data = response.json() + assert data["total"] == 1 + assert ( + data["data"][0]["request_id"] == "chatcmpl-9ZKMURhVYSi9D6r6PJ9vLcayIK0Vm" + ) finally: app.dependency_overrides.pop(ps.user_api_key_auth, None) @@ -2303,23 +2514,18 @@ async def test_ui_view_spend_logs_request_id_blocks_non_owner(client, monkeypatc """A non-admin looking up a request_id they do not own is rejected (403), so the relaxed date window cannot read another tenant's log by id.""" - class _ForeignRow: - user = "other_user" - team_id = None + prisma = _make_owner_lookup_prisma( + [ + { + "request_id": "foreign-req", + "litellm_call_id": None, + "user": "other_user", + "team_id": None, + } + ] + ) - class _SpendLogs: - async def find_unique(self, where, include=None): - return _ForeignRow() - - class _DB: - def __init__(self): - self.litellm_spendlogs = _SpendLogs() - - class _Prisma: - def __init__(self): - self.db = _DB() - - monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", _Prisma()) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", prisma) app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( user_role=LitellmUserRoles.INTERNAL_USER, user_id="user_1" ) @@ -2335,13 +2541,437 @@ async def test_ui_view_spend_logs_request_id_blocks_non_owner(client, monkeypatc @pytest.mark.asyncio -async def test_ui_view_spend_logs_request_id_owner_scoped_by_id_only( +async def test_ui_view_spend_logs_request_id_collision_serves_only_callers_rows(client, monkeypatch): + """Two tenants share one id: the attacker minted a row whose client-set + litellm_call_id equals the victim's request_id. Each side's lookup of that id + returns only their own row, so the collision neither leaks the other tenant's + row nor denies the victim theirs (Veria: identifier collision could deny access).""" + now_iso = datetime.datetime.now(timezone.utc).isoformat() + corpus = [ + { + "id": "log_attacker", + "request_id": "attacker-req", + "litellm_call_id": "victim-req", + "api_key": "sk-attacker-key", + "user": "attacker_user", + "team_id": None, + "spend": 0.05, + "startTime": now_iso, + "model": "gpt-4", + }, + { + "id": "log_victim", + "request_id": "victim-req", + "litellm_call_id": "victim-call-id", + "api_key": "sk-victim-key", + "user": "victim_user", + "team_id": None, + "spend": 0.07, + "startTime": now_iso, + "model": "gpt-4", + }, + ] + + def filter_fn(where): + rid_either = where.get("request_id_or_call_id") + rows = [r for r in corpus if rid_either in (r["request_id"], r["litellm_call_id"])] + return [r for r in rows if where.get("user") is None or r["user"] == where["user"]] + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", make_ui_spend_logs_mock_prisma(corpus, filter_fn)) + try: + for caller, own_request_id, other in ( + ("victim_user", "victim-req", "attacker_user"), + ("attacker_user", "attacker-req", "victim_user"), + ): + app.dependency_overrides[ps.user_api_key_auth] = lambda caller=caller: UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, user_id=caller + ) + response = client.get( + "/spend/logs/ui", + params={"request_id": "victim-req"}, + headers={"Authorization": "Bearer sk-test"}, + ) + assert response.status_code == 200, response.text + data = response.json() + assert data["total"] == 1 + assert data["data"][0]["request_id"] == own_request_id + assert other not in response.text + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + +@pytest.mark.asyncio +async def test_ui_view_spend_logs_id_lookup_scopes_every_non_admin_role(client, monkeypatch): + """An org admin reaches /spend/logs/ui without the internal-user row scope. An + id lookup still fetches only rows they own, so another tenant's row carrying + that id as its client-set litellm_call_id neither leaks nor turns the + org admin's own lookup into a 403 (Bugbot: non-internal id lookup 403s on collision).""" + now_iso = datetime.datetime.now(timezone.utc).isoformat() + corpus = [ + { + "id": "log_attacker", + "request_id": "attacker-req", + "litellm_call_id": "victim-req", + "api_key": "sk-attacker-key", + "user": "attacker_user", + "team_id": None, + "spend": 0.05, + "startTime": now_iso, + "model": "gpt-4", + }, + { + "id": "log_victim", + "request_id": "victim-req", + "litellm_call_id": "victim-call-id", + "api_key": "sk-victim-key", + "user": "victim_user", + "team_id": None, + "spend": 0.07, + "startTime": now_iso, + "model": "gpt-4", + }, + ] + + def filter_fn(where): + rid_either = where.get("request_id_or_call_id") + rows = [r for r in corpus if rid_either in (r["request_id"], r["litellm_call_id"])] + return [r for r in rows if where.get("user") is None or r["user"] == where["user"]] + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", make_ui_spend_logs_mock_prisma(corpus, filter_fn)) + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.ORG_ADMIN, user_id="victim_user" + ) + try: + response = client.get( + "/spend/logs/ui", + params={"request_id": "victim-req"}, + headers={"Authorization": "Bearer sk-test"}, + ) + assert response.status_code == 200, response.text + data = response.json() + assert data["total"] == 1 + assert [row["request_id"] for row in data["data"]] == ["victim-req"] + assert "attacker_user" not in response.text + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + +@pytest.mark.asyncio +async def test_ui_view_spend_logs_request_id_rejects_foreign_row_inserted_after_owner_check(client, monkeypatch): + """The SQL scope keeps foreign rows out of an id lookup; this backstop covers a + row the scope did not filter (the mock ignores it on purpose). The rows actually + fetched are ownership-checked again, so the lookup answers 403 instead of serving + the other tenant's row.""" + now_iso = datetime.datetime.now(timezone.utc).isoformat() + owned_row = { + "id": "log_owned", + "request_id": "attacker-req", + "litellm_call_id": "shared-id", + "api_key": "sk-test-key", + "user": "user_1", + "team_id": None, + "spend": 0.05, + "startTime": now_iso, + "model": "gpt-4", + } + foreign_row = { + "id": "log_foreign", + "request_id": "shared-id", + "litellm_call_id": None, + "api_key": "sk-victim-key", + "user": "victim_user", + "team_id": None, + "spend": 0.07, + "startTime": now_iso, + "model": "gpt-4", + } + + mock_prisma = make_ui_spend_logs_mock_prisma([owned_row], lambda where: [owned_row, foreign_row]) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma) + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, user_id="user_1" + ) + try: + response = client.get( + "/spend/logs/ui", + params={"request_id": "shared-id"}, + headers={"Authorization": "Bearer sk-test"}, + ) + assert response.status_code == 403 + assert "victim_user" not in response.text + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + +def _make_payload_lookup_prisma(rows): + """Emulate the detail endpoint's SQL over an in-memory corpus: the owner + pre-check, the caller scope on ``"user"`` and permitted teams, and the + exact-request_id-first ordering with LIMIT 1.""" + + class MockDB: + async def query_raw(self, sql_query, *params): + if 'SELECT DISTINCT "user", team_id' in sql_query: + return _emulate_spend_log_owner_lookup(rows, sql_query, params) + lookup_id = params[0] + matches = [r for r in rows if lookup_id in (r["request_id"], r["litellm_call_id"])] + if '"user" = $2' in sql_query: + team_ids = params[2] if "ANY($3::text[])" in sql_query else () + matches = [r for r in matches if r["user"] == params[1] or r["team_id"] in team_ids] + if "ORDER BY (request_id = $1) DESC" in sql_query: + matches = sorted(matches, key=lambda r: r["request_id"] == lookup_id, reverse=True) + return matches[:1] + + class MockPrisma: + def __init__(self): + self.db = MockDB() + + return MockPrisma() + + +def _payload_row(request_id, litellm_call_id, user, prompt): + return { + "request_id": request_id, + "litellm_call_id": litellm_call_id, + "messages": [{"role": "user", "content": prompt}], + "response": {"id": request_id}, + "proxy_server_request": None, + "metadata": None, + "user": user, + "team_id": None, + } + + +@pytest.mark.asyncio +async def test_ui_view_request_response_collision_serves_callers_own_row(client, monkeypatch): + """The attacker's row carries the victim's request_id as its client-set call id + and was written first. Each tenant's detail lookup of that id serves only their + own payload, and an admin's lookup resolves the exact request_id match rather + than whichever colliding row the database happens to return first.""" + prisma = _make_payload_lookup_prisma( + [ + _payload_row("attacker-req", "victim-req", "attacker_user", "attacker prompt"), + _payload_row("victim-req", "victim-call-id", "victim_user", "victim prompt"), + ] + ) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", prisma) + try: + for role, user_id, own_prompt, other_prompt in ( + (LitellmUserRoles.INTERNAL_USER, "victim_user", "victim prompt", "attacker prompt"), + (LitellmUserRoles.INTERNAL_USER, "attacker_user", "attacker prompt", "victim prompt"), + (LitellmUserRoles.PROXY_ADMIN, "admin", "victim prompt", "attacker prompt"), + ): + app.dependency_overrides[ps.user_api_key_auth] = lambda role=role, user_id=user_id: UserAPIKeyAuth( + user_role=role, user_id=user_id + ) + response = client.get("/spend/logs/ui/victim-req", headers={"Authorization": "Bearer sk-test"}) + assert response.status_code == 200, response.text + assert own_prompt in response.text + assert other_prompt not in response.text + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + +@pytest.mark.asyncio +async def test_ui_view_request_response_rejects_foreign_row_inserted_after_owner_check(client, monkeypatch): + """Backstop behind the SQL scope on the detail endpoint (the mock ignores the + scope on purpose): the payload row fetched by id is itself ownership-checked, so + a foreign row the scope did not filter cannot have its payload served.""" + + class MockDB: + async def query_raw(self, sql_query, *params): + if 'SELECT DISTINCT "user", team_id' in sql_query: + return [{"user": "user_1", "team_id": None}] + return [ + { + "messages": [{"role": "user", "content": "victim prompt"}], + "response": {"id": "resp-1"}, + "proxy_server_request": None, + "metadata": None, + "user": "victim_user", + "team_id": None, + } + ] + + class MockPrisma: + def __init__(self): + self.db = MockDB() + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", MockPrisma()) + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, user_id="user_1" + ) + try: + response = client.get( + "/spend/logs/ui/shared-id", + headers={"Authorization": "Bearer sk-test"}, + ) + assert response.status_code == 403 + assert "victim prompt" not in response.text + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + +@pytest.mark.asyncio +async def test_ui_view_request_response_custom_logger_denies_foreign_payload_owner(client, monkeypatch): + """The custom-logger payload comes straight from cold storage, written independently + of the spend-log table and able to outlive its row. When an id lookup matches no row, + the DB owner pre-check has nothing to verify, so the payload is authorized against the + owner recorded inside it. A foreign tenant's stored payload is denied even though no + spend-log row exists for the pre-check to catch.""" + + class MockDB: + async def query_raw(self, sql_query, *params): + return [] + + class MockPrisma: + def __init__(self): + self.db = MockDB() + + class ColdStorageLogger: + async def get_request_response_payload(self, request_id, start_time_utc, end_time_utc): + return { + "messages": [{"role": "user", "content": "victim prompt"}], + "response": {"id": "r"}, + "metadata": {"user_api_key_user_id": "victim_user", "user_api_key_team_id": None}, + } + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", MockPrisma()) + monkeypatch.setattr( + litellm.logging_callback_manager, + "get_active_additional_logging_utils_from_custom_logger", + lambda: [ColdStorageLogger()], + ) + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, user_id="user_1" + ) + try: + response = client.get( + "/spend/logs/ui/shared-id", + params={"start_date": "2026-01-01 00:00:00"}, + headers={"Authorization": "Bearer sk-test"}, + ) + assert response.status_code == 403 + assert "victim prompt" not in response.text + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + +@pytest.mark.asyncio +async def test_ui_view_request_response_custom_logger_is_keyed_by_callers_own_request_id(client, monkeypatch): + """Cold storage is keyed by the provider request_id. The caller's row carries the + lookup id only as its client-set litellm_call_id while another tenant's row owns + that id as its request_id. The custom logger is asked for the caller's own stored + request_id, so the caller gets their payload rather than a 403 from the foreign + payload's owner check, and the foreign payload is never fetched.""" + prisma = _make_payload_lookup_prisma( + [ + _payload_row("shared-id", "other-call-id", "other_user", "other tenant prompt"), + _payload_row("caller-req", "shared-id", "caller_user", "caller prompt"), + ] + ) + cold_storage = { + "shared-id": { + "messages": [{"role": "user", "content": "other tenant prompt"}], + "response": {"id": "shared-id"}, + "metadata": {"user_api_key_user_id": "other_user", "user_api_key_team_id": None}, + }, + "caller-req": { + "messages": [{"role": "user", "content": "caller prompt"}], + "response": {"id": "caller-req"}, + "metadata": {"user_api_key_user_id": "caller_user", "user_api_key_team_id": None}, + }, + } + requested_ids = [] + + class ColdStorageLogger: + async def get_request_response_payload(self, request_id, start_time_utc, end_time_utc): + requested_ids.append(request_id) + return cold_storage.get(request_id) + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", prisma) + monkeypatch.setattr( + litellm.logging_callback_manager, + "get_active_additional_logging_utils_from_custom_logger", + lambda: [ColdStorageLogger()], + ) + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.INTERNAL_USER, user_id="caller_user" + ) + try: + response = client.get("/spend/logs/ui/shared-id", headers={"Authorization": "Bearer sk-test"}) + assert response.status_code == 200, response.text + assert "caller prompt" in response.text + assert "other tenant prompt" not in response.text + assert requested_ids == ["caller-req"] + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + +@pytest.mark.asyncio +@pytest.mark.parametrize("group_by_session", [False, True]) +async def test_ui_view_spend_logs_id_lookup_lists_exact_request_id_row_first(client, monkeypatch, group_by_session): + """The dashboard's deep link fetches a single row for ``?log_id=``. When a newer + row carries that id as its client-set litellm_call_id, the row whose request_id + is the id still comes first, so the link opens the request it names. The + session-grouped page orders its representatives the same way.""" + today = datetime.datetime.now(timezone.utc) + corpus = [ + { + "id": "log_colliding", + "request_id": "colliding-req", + "litellm_call_id": "victim-req", + "api_key": "sk-test-key", + "user": "other_user", + "team_id": None, + "spend": 0.01, + "startTime": today.isoformat(), + "model": "gpt-4", + }, + { + "id": "log_victim", + "request_id": "victim-req", + "litellm_call_id": "victim-call-id", + "api_key": "sk-test-key", + "user": "victim_user", + "team_id": None, + "spend": 0.02, + "startTime": (today - datetime.timedelta(minutes=5)).isoformat(), + "model": "gpt-4", + }, + ] + + def filter_fn(where): + rows = _filter_logs_by_date_range(corpus, where) + rid_either = where.get("request_id_or_call_id") + if rid_either: + return [r for r in rows if rid_either in (r["request_id"], r["litellm_call_id"])] + return rows + + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", make_ui_spend_logs_mock_prisma(corpus, filter_fn)) + app.dependency_overrides[ps.user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, user_id="admin" + ) + try: + response = client.get( + "/spend/logs/ui", + params={"request_id": "victim-req", "page_size": 1, "group_by_session": str(group_by_session).lower()}, + headers={"Authorization": "Bearer sk-test"}, + ) + assert response.status_code == 200, response.text + data = response.json() + assert data["total"] == 2 + assert [row["request_id"] for row in data["data"]] == ["victim-req"] + finally: + app.dependency_overrides.pop(ps.user_api_key_auth, None) + + +@pytest.mark.asyncio +async def test_ui_view_spend_logs_request_id_owner_lookup_drops_window_keeps_scope( client, monkeypatch ): - """A non-admin owner looking up their own request_id resolves across all time. - The ownership check authorizes the single row, so the query drops both the date - window and the general user/team scoping and filters by the primary key alone; - without that skip an internal user would have a `user`/`OR` clause added.""" + """A non-admin owner looking up their own request_id resolves across all time: + the query drops the date window the dashboard sends, while the caller's own-user + scope stays on the id lookup so a colliding foreign row can never be served.""" today = datetime.datetime.now(timezone.utc) mock_spend_logs = [ { @@ -2361,20 +2991,14 @@ async def test_ui_view_spend_logs_request_id_owner_scoped_by_id_only( def filter_fn(where): captured["where"] = where rows = _filter_logs_by_date_range(mock_spend_logs, where) - if where.get("request_id"): + rid_either = where.get("request_id_or_call_id") + if rid_either: + rows = [r for r in rows if rid_either in (r["request_id"], r.get("litellm_call_id"))] + elif where.get("request_id"): rows = [r for r in rows if r["request_id"] == where["request_id"]] return rows mock_prisma = make_ui_spend_logs_mock_prisma(mock_spend_logs, filter_fn) - - class _OwnedRow: - user = "user_1" - team_id = "team1" - - async def _find_unique(where, include=None): - return _OwnedRow() - - mock_prisma.db.find_unique = _find_unique monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", mock_prisma) # A 5-day window that EXCLUDES the 90-day-old log, as the dashboard sends. @@ -2399,9 +3023,8 @@ async def test_ui_view_spend_logs_request_id_owner_scoped_by_id_only( assert data["total"] == 1 assert data["data"][0]["request_id"] == "req-old" assert "startTime" not in captured["where"] - assert captured["where"]["request_id"] == "req-old" - assert "user" not in captured["where"] - assert "OR" not in captured["where"] + assert captured["where"]["request_id_or_call_id"] == "req-old" + assert captured["where"]["user"] == "user_1" finally: app.dependency_overrides.pop(ps.user_api_key_auth, None) @@ -5095,7 +5718,7 @@ async def test_view_spend_logs_internal_user_combines_user_with_request_id( where = mock_client.db.captured_where assert where is not None assert where["user"] == "internal-user-2" - assert where["request_id"] == "req-abc" + assert where["OR"] == ({"request_id": "req-abc"}, {"litellm_call_id": "req-abc"}) finally: app.dependency_overrides.pop(ps.user_api_key_auth, None) @@ -5122,7 +5745,7 @@ async def test_view_spend_logs_non_date_range_combines_user_with_request_id( where = mock_client.db.captured_where assert where is not None assert where["user"] == "internal-user-3" - assert where["request_id"] == "req-xyz" + assert where["OR"] == ({"request_id": "req-xyz"}, {"litellm_call_id": "req-xyz"}) finally: app.dependency_overrides.pop(ps.user_api_key_auth, None) @@ -7052,25 +7675,19 @@ async def test_ui_view_spend_logs_search_returns_flat_rows_when_grouping_by_sess def _fake_prisma_with_owned_spend_log(owner_user_id, messages_json, response_json): - class _Row: - user = owner_user_id - team_id = None - - class _SpendLogs: - async def find_unique(self, where, include=None): - return _Row() - class _DB: - def __init__(self): - self.litellm_spendlogs = _SpendLogs() - - async def query_raw(self, _sql, *_args): + async def query_raw(self, sql, *_args): + if 'SELECT DISTINCT "user", team_id' in sql: + return [{"user": owner_user_id, "team_id": None}] return [ { + "request_id": "req-owned-by-user-a", "messages": messages_json, "response": response_json, "proxy_server_request": "{}", "metadata": "{}", + "user": owner_user_id, + "team_id": None, } ] @@ -7127,8 +7744,8 @@ def test_ui_view_request_response_internal_user_non_owner_forbidden(client, monk """ A different internal_user requesting someone else's row is forbidden; guards against _assert_user_can_view_request_id being skipped in the - detail-drawer handler. Also proves the handler stops before it ever asks - a custom logger or the DB for the payload. + detail-drawer handler. Also proves the handler stops at the owner lookup, + before it ever asks a custom logger or the DB for the payload. """ messages_json = json.dumps([{"role": "user", "content": "hi"}]) response_json = json.dumps({"choices": [{"message": {"content": "hello"}}]}) @@ -7160,7 +7777,7 @@ def test_ui_view_request_response_internal_user_non_owner_forbidden(client, monk ) assert response.status_code == 403 assert custom_logger.requested_ids == [] - assert query_raw_calls == [] + assert [args[0] for args, _kwargs in query_raw_calls if "messages" in args[0]] == [] finally: app.dependency_overrides.pop(ps.user_api_key_auth, None) @@ -7171,24 +7788,27 @@ def test_ui_view_request_response_internal_user_missing_row_forbidden(client, mo request_id with no spend-log row (e.g. pruned by retention) must be denied before the handler ever consults a custom logger, otherwise a non-admin who guesses/obtains a request_id could read another tenant's - payload out of cold storage. Fails if `if row is None: return` is - reintroduced. + payload out of cold storage, and an existing payload that is not theirs + would still confirm the id exists. Even a payload recorded as the caller's + own is never fetched once the row is gone. Fails if an empty owner lookup + is allowed to fall through to the loggers. """ - class _SpendLogs: - async def find_unique(self, where, include=None): - return None - class _DB: - def __init__(self): - self.litellm_spendlogs = _SpendLogs() + async def query_raw(self, _sql, *_args): + return [] from types import SimpleNamespace fake_prisma = SimpleNamespace(db=_DB()) monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", fake_prisma) - custom_logger = _RecordingAdditionalLoggingUtils({"messages": "should-not-be-returned"}) + custom_logger = _RecordingAdditionalLoggingUtils( + { + "messages": "should-not-be-returned", + "metadata": {"user_api_key_user_id": "user_a", "user_api_key_team_id": None}, + } + ) monkeypatch.setattr( litellm.logging_callback_manager, "get_active_additional_logging_utils_from_custom_logger", diff --git a/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py b/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py index e9bbaf0c96e..a72b4e28143 100644 --- a/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py +++ b/tests/test_litellm/proxy/spend_tracking/test_spend_tracking_utils.py @@ -1329,6 +1329,33 @@ def test_get_logging_payload_includes_agent_id_from_kwargs(): assert payload["agent_id"] == test_agent_id, f"Expected agent_id '{test_agent_id}', got '{payload.get('agent_id')}'" +def test_get_logging_payload_populates_litellm_call_id_alongside_provider_request_id(): + """ + LIT-6302: request_id stays the provider response id, so clients holding the + x-litellm-call-id header value could never find their row. The payload now + also carries litellm_call_id as its own column for lookups by either id. + """ + call_id = "b980eea9-5cd9-4099-93cd-8291e46c76fd" + + payload = get_logging_payload( + kwargs={ + "model": "gpt-4o-mini", + "litellm_call_id": call_id, + "litellm_params": {"metadata": {"user_api_key": "test-key"}}, + }, + response_obj=litellm.ModelResponse( + id="chatcmpl-provider-id", + choices=[], + usage=litellm.Usage(prompt_tokens=1, completion_tokens=1, total_tokens=2), + ), + start_time=datetime.datetime.now(timezone.utc), + end_time=datetime.datetime.now(timezone.utc), + ) + + assert payload["request_id"] == "chatcmpl-provider-id" + assert payload["litellm_call_id"] == call_id + + @patch("litellm.proxy.proxy_server.master_key", None) @patch("litellm.proxy.proxy_server.general_settings", {}) def test_get_logging_payload_includes_overhead_in_spend_logs_metadata(): diff --git a/tests/test_litellm/proxy/test__types.py b/tests/test_litellm/proxy/test__types.py index 26bb1533da4..9e1486ce90f 100644 --- a/tests/test_litellm/proxy/test__types.py +++ b/tests/test_litellm/proxy/test__types.py @@ -277,3 +277,61 @@ def test_team_membership_budget_table_present_still_works(): } result = LiteLLM_TeamMembership.model_validate(data) assert result.litellm_budget_table is None + + +def test_a_jwt_issuer_can_override_the_virtual_key_claim_field_while_other_issuers_keep_the_global_one(): + from litellm.proxy._types import LiteLLM_JWTAuth, UnregisteredJWTClientBehavior + + jwt_auth = LiteLLM_JWTAuth( + virtual_key_claim_field="client_id", + issuers=[ + { + "issuer": "https://team-idp.example.com", + "jwks_url": "https://team-idp.example.com/keys", + "audience": "litellm", + "team_id_jwt_field": "sub", + }, + { + "issuer": "https://service-idp.example.com", + "jwks_url": "https://service-idp.example.com/keys", + "audience": "litellm", + "virtual_key_claim_field": "sub", + "unregistered_jwt_client_behavior": "reject", + }, + ], + ) + + assert jwt_auth.get_virtual_key_claim_field("https://service-idp.example.com") == "sub" + assert jwt_auth.get_unregistered_jwt_client_behavior("https://service-idp.example.com") is ( + UnregisteredJWTClientBehavior.REJECT + ) + assert jwt_auth.get_virtual_key_claim_field("https://team-idp.example.com") == "client_id" + assert jwt_auth.get_unregistered_jwt_client_behavior("https://team-idp.example.com") is ( + UnregisteredJWTClientBehavior.FALLBACK_TEAM_MAPPING + ) + assert jwt_auth.get_virtual_key_claim_field(None) == "client_id" + assert jwt_auth.get_virtual_key_claim_field("https://unknown-idp.example.com") == "client_id" + + +@pytest.mark.parametrize( + ("global_field", "issuer_field", "is_configured"), + ((None, None, False), ("sub", None, True), (None, "sub", True)), +) +def test_virtual_key_mapping_counts_as_configured_when_any_issuer_sets_the_claim_field( + global_field, issuer_field, is_configured +): + from litellm.proxy._types import LiteLLM_JWTAuth + + jwt_auth = LiteLLM_JWTAuth( + virtual_key_claim_field=global_field, + issuers=[ + { + "issuer": "https://idp.example.com", + "jwks_url": "https://idp.example.com/keys", + "audience": "litellm", + "virtual_key_claim_field": issuer_field, + } + ], + ) + + assert jwt_auth.is_virtual_key_mapping_configured() is is_configured diff --git a/tests/test_litellm/proxy/test_common_request_processing.py b/tests/test_litellm/proxy/test_common_request_processing.py index efbb5eedad4..cabfcc9918f 100644 --- a/tests/test_litellm/proxy/test_common_request_processing.py +++ b/tests/test_litellm/proxy/test_common_request_processing.py @@ -13,7 +13,7 @@ from fastapi.responses import JSONResponse, StreamingResponse import litellm from litellm._uuid import uuid -from litellm.constants import RETURN_RAW_MODEL_NAME_METADATA_KEY +from litellm.constants import MAX_LITELLM_CALL_ID_LENGTH, RETURN_RAW_MODEL_NAME_METADATA_KEY from litellm.integrations.custom_logger import CustomLogger from litellm.integrations.opentelemetry import UserAPIKeyAuth from litellm.proxy.common_request_processing import ( @@ -30,6 +30,7 @@ from litellm.proxy.common_request_processing import ( _has_attribute_error_in_chain, _is_azure_model_router_request, open_sse_before_first_byte, + resolve_litellm_call_id, ttft_keepalive_interval, _override_openai_response_model, _parse_event_data_for_error, @@ -1401,6 +1402,51 @@ class TestProxyBaseLLMRequestProcessing: assert "x-litellm-key-spend" in headers_7 assert float(headers_7["x-litellm-key-spend"]) == 0.001 # Should use original spend on error + @pytest.mark.parametrize( + ("hidden_params", "request_data", "expected_call_id"), + [ + ( + {"litellm_call_id": "call-from-hidden-params"}, + {"litellm_call_id": "call-from-request"}, + "call-from-hidden-params", + ), + ({}, {"litellm_call_id": "call-from-request"}, "call-from-request"), + ({"model_id": "m-1"}, {"litellm_call_id": "call-from-request"}, "call-from-request"), + ], + ) + def test_get_custom_headers_call_id_falls_back_to_hidden_params_then_request_data( + self, hidden_params, request_data, expected_call_id + ): + mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth) + mock_user_api_key_dict.tpm_limit = None + mock_user_api_key_dict.rpm_limit = None + mock_user_api_key_dict.max_budget = None + mock_user_api_key_dict.spend = 0.0 + + headers = ProxyBaseLLMRequestProcessing.get_custom_headers( + user_api_key_dict=mock_user_api_key_dict, + hidden_params=hidden_params, + request_data=request_data, + ) + + assert headers["x-litellm-call-id"] == expected_call_id + + def test_get_custom_headers_explicit_call_id_wins_over_fallbacks(self): + mock_user_api_key_dict = MagicMock(spec=UserAPIKeyAuth) + mock_user_api_key_dict.tpm_limit = None + mock_user_api_key_dict.rpm_limit = None + mock_user_api_key_dict.max_budget = None + mock_user_api_key_dict.spend = 0.0 + + headers = ProxyBaseLLMRequestProcessing.get_custom_headers( + user_api_key_dict=mock_user_api_key_dict, + call_id="explicit-call-id", + hidden_params={"litellm_call_id": "call-from-hidden-params"}, + request_data={"litellm_call_id": "call-from-request"}, + ) + + assert headers["x-litellm-call-id"] == "explicit-call-id" + @pytest.mark.asyncio async def test_queue_time_seconds_is_set_in_metadata(self, monkeypatch): """ @@ -3878,6 +3924,39 @@ class TestHandleLLMApiExceptionRetryAfter: assert proxy_exc.headers["retry-after"] == "43" assert proxy_exc.headers["x-custom"] == "1" + async def test_handle_llm_api_exception_names_cooldown_when_every_deployment_is_cooled_down(self): + from litellm.types.router import RouterRateLimitError + + exc = RouterRateLimitError( + model="gpt-4", + cooldown_time=120, + enable_pre_call_checks=False, + cooldown_list=["dep-a", "dep-b"], + model_ids=["dep-a", "dep-b"], + ) + proxy_exc = await self._invoke(exc) + body = proxy_exc.to_dict() + assert body["type"] == "all_deployments_in_cooldown" + assert body["code"] == "429" + assert "All deployments for selected model are in cooldown" in body["message"] + assert proxy_exc.headers["retry-after"] == "120" + + async def test_handle_llm_api_exception_keeps_rate_limit_type_when_cooldown_is_partial(self): + from litellm.types.router import RouterRateLimitError + + exc = RouterRateLimitError( + model="gpt-4", + cooldown_time=120, + enable_pre_call_checks=False, + cooldown_list=["dep-a"], + model_ids=["dep-a", "dep-b"], + ) + proxy_exc = await self._invoke(exc) + body = proxy_exc.to_dict() + assert body["type"] == "rate_limit_error" + assert body["code"] == "429" + assert "All deployments for selected model are in cooldown" not in body["message"] + class TestHandleLLMApiExceptionFramingHeaders: """HTTP-framing headers on the provider exception must be stripped before the @@ -6883,6 +6962,45 @@ class TestModelDeploymentsSupportStreamOptions: assert self._support(None, None) is False +@pytest.mark.asyncio +@pytest.mark.parametrize("key_settings, expected", [ + (None, {"group": {"team": 100}}), + ({"weights": {"group": {"key": 100}}}, {"group": {"key": 100}}), + ({"timeout": 30}, None), + ({"weights": {"group": {"key": "legacy"}}}, None), +]) +async def test_saved_weights_override_caller_input_and_preserve_key_precedence( + monkeypatch: pytest.MonkeyPatch, + key_settings: dict[str, int | dict[str, dict[str, int | str]]] | None, + expected: dict[str, dict[str, int]] | None, +) -> None: + from litellm.proxy import proxy_server + + monkeypatch.setattr(proxy_server, "prisma_client", None) + monkeypatch.setattr(proxy_server, "get_team_object", AsyncMock( + return_value=SimpleNamespace(router_settings={"weights": {"group": {"team": 100}}}) + )) + forged = {"group": {"caller": 100}} + processor = ProxyBaseLLMRequestProcessing(data={ + "model": "group", "weights": forged, "_router_weights": forged, + "router_settings_override": {"weights": forged}, + }) + logging = MagicMock(spec=ProxyLogging) + logging.pre_call_hook = AsyncMock(side_effect=lambda **kwargs: kwargs["data"]) + data, _ = await processor.common_processing_pre_call_logic( + request=Request({"type": "http", "method": "POST", "path": "/v1/chat/completions", "headers": []}), + general_settings={}, + user_api_key_dict=ProxyUserAPIKeyAuth(api_key="hash", team_id="team-a", router_settings=key_settings), + proxy_logging_obj=logging, + proxy_config=proxy_server.ProxyConfig(), + route_type="acompletion", + llm_router=litellm.Router(model_list=[]), + ) + assert "weights" not in data + assert data.get("_router_weights") == expected + assert logging.pre_call_hook.call_args.kwargs["data"].get("_router_weights") == expected + + class TestPerRequestModelGroupAlias: """``router_settings.model_group_alias`` on a key or team has to be resolved by the proxy: the Router resolves aliases from its own shared instance @@ -8060,6 +8178,19 @@ def test_log_llm_api_exception_traceback_only_for_unexpected_errors(exc, expect_ assert (records[0].exc_info is not None) is expect_traceback +class TestResolveLitellmCallId: + def test_client_call_id_within_the_bound_is_kept(self): + assert resolve_litellm_call_id("req-abc-123") == "req-abc-123" + at_bound: Final = "y" * MAX_LITELLM_CALL_ID_LENGTH + assert resolve_litellm_call_id(at_bound) == at_bound + + @pytest.mark.parametrize("client_call_id", [None, "", "x" * (MAX_LITELLM_CALL_ID_LENGTH + 1), "z" * 3000]) + def test_missing_empty_or_oversized_client_call_id_gets_a_generated_uuid(self, client_call_id): + resolved: Final = resolve_litellm_call_id(client_call_id) + assert resolved != client_call_id + assert uuid.UUID(resolved).version == 4 + + class _FailureHookRecorder: """Stands in for ProxyLogging.post_call_failure_hook, recording what the detached-failure closure hands it.""" @@ -8386,6 +8517,41 @@ async def test_handle_llm_api_exception_forwards_provider_headers_on_http_status assert exc_info.value.headers["llm_provider-x-amzn-requestid"] == "req-passthrough-500" +@pytest.mark.asyncio +async def test_handle_llm_api_exception_forwards_litellm_response_headers_when_response_is_synthetic(): + """Exception mapping hands the proxy a mapped error whose ``response`` is a synthetic empty + ``httpx.Response`` and parks the provider's real headers on ``litellm_response_headers``. + The client must still get the provider request id, as it does on a 200. + """ + import httpx + + from litellm.proxy._types import ProxyException, UserAPIKeyAuth + + mapped = litellm.BadRequestError( + message="OpenAIException - max_tokens is too large: 999999999.", + model="gpt-4o-mini", + llm_provider="openai", + ) + mapped.litellm_response_headers = httpx.Headers({"x-request-id": "req_openai_400"}) + assert dict(mapped.response.headers) == {} + + processor = ProxyBaseLLMRequestProcessing(data={}) + proxy_logging_obj = MagicMock() + proxy_logging_obj.post_call_failure_hook = AsyncMock(return_value=None) + proxy_logging_obj.post_call_response_headers_hook = AsyncMock(return_value={}) + + with pytest.raises(ProxyException) as exc_info: + await processor._handle_llm_api_exception( + e=mapped, + user_api_key_dict=UserAPIKeyAuth(api_key="sk-test"), + proxy_logging_obj=proxy_logging_obj, + ) + + assert exc_info.value.code == "400" + assert "max_tokens is too large: 999999999." in exc_info.value.message + assert exc_info.value.headers["llm_provider-x-request-id"] == "req_openai_400" + + class TestBackgroundResponseRetrievalGovernance: """LIT-7175: retrieving a background Response attaches the model's post_call policy pipelines.""" diff --git a/tests/test_litellm/proxy/test_health_check_functions.py b/tests/test_litellm/proxy/test_health_check_functions.py index c0c853ae2c5..7d6c5d3cebe 100644 --- a/tests/test_litellm/proxy/test_health_check_functions.py +++ b/tests/test_litellm/proxy/test_health_check_functions.py @@ -374,7 +374,7 @@ async def test_save_background_health_checks_to_db(): """Test the main background health check save function""" mock_prisma = MagicMock() mock_prisma.save_health_check_result = AsyncMock() - mock_prisma.get_all_latest_health_checks = AsyncMock(return_value=[]) + mock_prisma.db.query_raw = AsyncMock(return_value=[]) model_list = [ { @@ -398,9 +398,9 @@ async def test_save_background_health_checks_to_db(): "background_health_check", ) - # Should call get_all_latest_health_checks and save_health_check_result, and report completion + # Should read the latest rows and save_health_check_result, and report completion assert persisted is True - mock_prisma.get_all_latest_health_checks.assert_called_once() + mock_prisma.db.query_raw.assert_awaited_once() mock_prisma.save_health_check_result.assert_called_once() call_kwargs = mock_prisma.save_health_check_result.call_args[1] @@ -493,7 +493,7 @@ def _one_model_setup(): @pytest.mark.asyncio async def test_save_background_health_checks_to_db_returns_false_when_a_write_fails(): mock_prisma = MagicMock() - mock_prisma.get_all_latest_health_checks = AsyncMock(return_value=[]) + mock_prisma.db.query_raw = AsyncMock(return_value=[]) mock_prisma.save_health_check_result = AsyncMock(return_value=None) model_list, healthy_endpoints, unhealthy_endpoints = _one_model_setup() @@ -504,6 +504,23 @@ async def test_save_background_health_checks_to_db_returns_false_when_a_write_fa assert (persisted, mock_prisma.save_health_check_result.await_count) == (False, 1) +@pytest.mark.asyncio +async def test_save_background_health_checks_to_db_writes_nothing_when_the_latest_row_read_fails(mock_prisma): + """ + A failed dedup read must not read as an empty table. Treated that way, every model was written on every + cycle by every pod while the read kept failing, which is what filled the table in production. + """ + mock_prisma.db.query_raw = AsyncMock(side_effect=RuntimeError("db down")) + mock_prisma.save_health_check_result = AsyncMock(return_value={"id": "row"}) + model_list, healthy_endpoints, unhealthy_endpoints = _one_model_setup() + + persisted = await _save_background_health_checks_to_db( + mock_prisma, model_list, healthy_endpoints, unhealthy_endpoints, 1234567890.0, "background_health_check" + ) + + assert (persisted, mock_prisma.save_health_check_result.await_count) == (False, 0) + + @pytest.mark.asyncio async def test_save_background_health_checks_to_db_no_prisma(): """Test graceful handling when no prisma client""" @@ -515,7 +532,7 @@ async def test_save_background_health_checks_to_db_no_prisma(): async def test_save_background_health_checks_to_db_exception_handling(): """Test exception handling in background health check save""" mock_prisma = MagicMock() - mock_prisma.get_all_latest_health_checks = AsyncMock(side_effect=Exception("DB Error")) + mock_prisma.db.query_raw = AsyncMock(side_effect=Exception("DB Error")) model_list = [ { diff --git a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py index 37b983d709a..099afa57eec 100644 --- a/tests/test_litellm/proxy/test_litellm_pre_call_utils.py +++ b/tests/test_litellm/proxy/test_litellm_pre_call_utils.py @@ -957,6 +957,8 @@ async def test_add_litellm_data_to_request_strips_user_control_fields(): "litellm_gateway_injected_cache": "forged-deployment-id", "metadata": copy.deepcopy(malicious_metadata), "litellm_metadata": copy.deepcopy(malicious_metadata), + "weights": {"gpt-3.5-turbo": {"forged-deployment-id": 100}}, + "_router_weights": {"gpt-3.5-turbo": {"forged-deployment-id": 100}}, } updated = await add_litellm_data_to_request( @@ -974,6 +976,10 @@ async def test_add_litellm_data_to_request_strips_user_control_fields(): assert "enable_prompt_caching" not in updated assert "routing_decision" not in updated assert "litellm_gateway_injected_cache" not in updated + assert "weights" not in updated + assert "_router_weights" not in updated + assert "weights" not in updated["proxy_server_request"]["body"] + assert "_router_weights" not in updated["proxy_server_request"]["body"] stripped_keys = { "disable_global_guardrails", @@ -7346,13 +7352,14 @@ def _reserved_stamp_key(key_metadata: dict | None = None) -> UserAPIKeyAuth: _PLANTED_STAMPS = { "attempted_fallbacks": 99, "original_model_group": "spoofed-group", + "request_retry_count": -100, "_client_output_ceiling": {"api_base": "https://attacker.example"}, "client_key": "client_value", } @pytest.mark.asyncio -async def test_add_litellm_data_to_request_strips_router_reserved_stamps_from_both_buckets(): +async def test_add_litellm_data_to_request_strips_router_reserved_stamps_from_both_buckets() -> None: """attempted_fallbacks and original_model_group are router-written facts the spend row reads back; a client planting them in either bucket is dropped at the boundary so the router never sees a reserved key it did not write.""" @@ -7378,11 +7385,12 @@ async def test_add_litellm_data_to_request_strips_router_reserved_stamps_from_bo assert "attempted_fallbacks" not in updated["metadata"] assert "original_model_group" not in updated["metadata"] assert "_client_output_ceiling" not in updated["metadata"] + assert "request_retry_count" not in updated["metadata"] assert updated["metadata"]["client_key"] == "client_value" @pytest.mark.asyncio -async def test_add_litellm_data_to_request_strips_router_reserved_stamps_from_json_string_litellm_metadata(): +async def test_add_litellm_data_to_request_strips_router_reserved_stamps_from_json_string_litellm_metadata() -> None: from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request data = { @@ -7403,11 +7411,12 @@ async def test_add_litellm_data_to_request_strips_router_reserved_stamps_from_js assert "litellm_metadata" not in updated assert "attempted_fallbacks" not in updated["metadata"] assert "original_model_group" not in updated["metadata"] + assert "request_retry_count" not in updated["metadata"] assert updated["metadata"]["client_key"] == "client_value" @pytest.mark.asyncio -async def test_add_litellm_data_to_request_strips_router_reserved_stamps_despite_pricing_override_opt_in(): +async def test_add_litellm_data_to_request_strips_router_reserved_stamps_despite_pricing_override_opt_in() -> None: """The pricing strip is gated on allow_client_pricing_override; the reserved-stamp strip is not, because no key or team setting makes a client-written fallback count valid.""" from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request @@ -7431,6 +7440,7 @@ async def test_add_litellm_data_to_request_strips_router_reserved_stamps_despite assert updated["metadata"]["model_info"] == {"input_cost_per_token": 0.0} assert "attempted_fallbacks" not in updated["metadata"] assert "original_model_group" not in updated["metadata"] + assert "request_retry_count" not in updated["metadata"] @pytest.mark.asyncio diff --git a/tests/test_litellm/proxy/test_model_info_default_limits.py b/tests/test_litellm/proxy/test_model_info_default_limits.py index 8111a7af006..4426252cb6c 100644 --- a/tests/test_litellm/proxy/test_model_info_default_limits.py +++ b/tests/test_litellm/proxy/test_model_info_default_limits.py @@ -3,6 +3,7 @@ Tests verifying that default_api_key_tpm_limit and default_api_key_rpm_limit set litellm_params are returned by the /model/info endpoint. """ +import json from typing import Optional from unittest.mock import MagicMock, patch @@ -128,8 +129,9 @@ class TestModelInfoEndpointWithRouter: litellm_model_id="some-model-id", ) - assert len(response["data"]) == 1 - litellm_params = response["data"][0]["litellm_params"] + data = json.loads(response.body)["data"] + assert len(data) == 1 + litellm_params = data[0]["litellm_params"] assert litellm_params.get("default_api_key_tpm_limit") == 100 assert litellm_params.get("default_api_key_rpm_limit") == 200 @@ -171,7 +173,8 @@ class TestModelInfoEndpointWithRouter: litellm_model_id=None, ) - assert len(response["data"]) >= 1 - litellm_params = response["data"][0]["litellm_params"] + data = json.loads(response.body)["data"] + assert len(data) >= 1 + litellm_params = data[0]["litellm_params"] assert litellm_params.get("default_api_key_tpm_limit") == 100 assert litellm_params.get("default_api_key_rpm_limit") == 200 diff --git a/tests/test_litellm/proxy/test_model_list_healthy_only.py b/tests/test_litellm/proxy/test_model_list_healthy_only.py index 03eaa2e79c9..718c7e41da8 100644 --- a/tests/test_litellm/proxy/test_model_list_healthy_only.py +++ b/tests/test_litellm/proxy/test_model_list_healthy_only.py @@ -6,6 +6,7 @@ per-request `healthy_only` query parameter and the proxy-wide (`model_info_v1`). """ +import json from unittest.mock import AsyncMock, MagicMock import pytest @@ -275,7 +276,7 @@ async def test_model_info_v1_healthy_only_hides_unhealthy_deployments( litellm_model_id=None, healthy_only=True, ) - assert [m["model_name"] for m in response["data"]] == ["gpt-4"] + assert [m["model_name"] for m in json.loads(response.body)["data"]] == ["gpt-4"] @pytest.mark.asyncio @@ -286,7 +287,7 @@ async def test_model_info_v1_general_setting_hides_unhealthy_deployments(patched user_api_key_dict=_admin_key(), litellm_model_id=None, ) - assert [m["model_name"] for m in response["data"]] == ["gpt-4"] + assert [m["model_name"] for m in json.loads(response.body)["data"]] == ["gpt-4"] @pytest.mark.asyncio @@ -297,7 +298,7 @@ async def test_model_info_v1_default_keeps_unhealthy_deployments( user_api_key_dict=_admin_key(), litellm_model_id=None, ) - assert [m["model_name"] for m in response["data"]] == ["gpt-4", "claude-sonnet"] + assert [m["model_name"] for m in json.loads(response.body)["data"]] == ["gpt-4", "claude-sonnet"] patched_model_info_v1.async_get_fully_unhealthy_model_names.assert_not_awaited() @@ -318,4 +319,4 @@ async def test_model_info_v1_litellm_model_id_lookup_ignores_health_filter(patch user_api_key_dict=_admin_key(), litellm_model_id="unhealthy-id", ) - assert [m["model_name"] for m in response["data"]] == ["claude-sonnet"] + assert [m["model_name"] for m in json.loads(response.body)["data"]] == ["claude-sonnet"] diff --git a/tests/test_litellm/proxy/test_prisma_migration.py b/tests/test_litellm/proxy/test_prisma_migration.py index 729adcfb9e0..3fc69b34213 100644 --- a/tests/test_litellm/proxy/test_prisma_migration.py +++ b/tests/test_litellm/proxy/test_prisma_migration.py @@ -1,4 +1,6 @@ import os +import sys +from pathlib import Path from unittest.mock import MagicMock, patch import pytest @@ -64,3 +66,34 @@ class TestPrismaMigration: prisma_migration.main() mock_subprocess_run.assert_not_called() + + @patch("litellm.proxy.prisma_migration.subprocess.run") # test-quality-ok: the spawned argv is the behavior under test + @patch("litellm.proxy.prisma_migration.run_server") # test-quality-ok: run_server boots the whole proxy + def test_prisma_generate_runs_through_the_module_when_the_cli_is_not_on_path( + self, mock_run_server: MagicMock, mock_subprocess_run: MagicMock, tmp_path: Path + ) -> None: + mock_subprocess_run.return_value = MagicMock(returncode=0, stdout="", stderr="") + empty_bin: Path = tmp_path / "emptybin" + empty_bin.mkdir() + + with patch.dict(os.environ, {"PATH": str(empty_bin)}, clear=True): + assert prisma_migration.main() == 0 + + assert mock_subprocess_run.call_args.args[0] == (sys.executable, "-m", "prisma", "generate") + + @patch("litellm.proxy.prisma_migration.subprocess.run") # test-quality-ok: the spawned argv is the behavior under test + @patch("litellm.proxy.prisma_migration.run_server") # test-quality-ok: run_server boots the whole proxy + def test_prisma_generate_runs_the_console_script_when_it_is_on_path( + self, mock_run_server: MagicMock, mock_subprocess_run: MagicMock, tmp_path: Path + ) -> None: + mock_subprocess_run.return_value = MagicMock(returncode=0, stdout="", stderr="") + bin_dir: Path = tmp_path / "bin" + bin_dir.mkdir() + script: Path = bin_dir / "prisma" + script.write_text("#!/bin/sh\nexit 0\n") + script.chmod(0o755) + + with patch.dict(os.environ, {"PATH": str(bin_dir)}, clear=True): + assert prisma_migration.main() == 0 + + assert mock_subprocess_run.call_args.args[0] == ("prisma", "generate") diff --git a/tests/test_litellm/proxy/test_proxy_cli.py b/tests/test_litellm/proxy/test_proxy_cli.py index c76ff189a8a..e25e6a59884 100644 --- a/tests/test_litellm/proxy/test_proxy_cli.py +++ b/tests/test_litellm/proxy/test_proxy_cli.py @@ -1940,6 +1940,66 @@ class TestRunServerDbSetup: use_migrate=False, use_v2_resolver=False ) + @patch("atexit.register") + @patch("litellm.proxy.db.prisma_client.PrismaManager.setup_database") # test-quality-ok: run_server always wires the DB; same isolation as the sibling CLI tests above + @patch("litellm.proxy.db.check_migration.check_prisma_schema_diff") # test-quality-ok: run_server always wires the DB; same isolation as the sibling CLI tests above + @patch("litellm.proxy.db.prisma_client.should_update_prisma_schema") # test-quality-ok: run_server always wires the DB; same isolation as the sibling CLI tests above + def test_migrations_run_when_the_prisma_cli_is_not_on_path( + self, + mock_should_update_schema, + mock_check_schema_diff, + mock_setup_database, + mock_atexit_register, + tmp_path, + capsys, + ): + from litellm.proxy.proxy_cli import run_server + + mock_should_update_schema.return_value = True + empty_bin = tmp_path / "emptybin" + empty_bin.mkdir() + + mock_proxy_module = MagicMock( + app=MagicMock(), + ProxyConfig=MagicMock(), + KeyManagementSettings=MagicMock(), + save_worker_config=MagicMock(), + ) + + clean_env = { + k: v + for k, v in os.environ.items() + if k not in ("DATABASE_URL", "DIRECT_URL") + } + clean_env["DATABASE_URL"] = "postgresql://test:test@localhost:5432/test" + clean_env["PATH"] = str(empty_bin) + + with ( + patch.dict(os.environ, clean_env, clear=True), + patch.dict( + "sys.modules", + { + "proxy_server": mock_proxy_module, + "litellm.proxy.proxy_server": mock_proxy_module, + }, + ), + patch( # test-quality-ok: same isolation as the sibling CLI tests above + "litellm.proxy.proxy_cli.ProxyInitializationHelpers._get_default_unvicorn_init_args" + ) as mock_get_args, + ): + mock_get_args.return_value = { + "app": "litellm.proxy.proxy_server:app", + "host": "localhost", + "port": 8000, + } + + run_server.main(["--local", "--skip_server_startup"], standalone_mode=False) + + assert "prisma CLI is neither on PATH" not in capsys.readouterr().out + mock_setup_database.assert_called_once_with( + use_migrate=True, use_v2_resolver=False + ) + @patch("subprocess.run") @patch("atexit.register") @patch("litellm.proxy.db.prisma_client.PrismaManager.setup_database") diff --git a/tests/test_litellm/proxy/test_proxy_server.py b/tests/test_litellm/proxy/test_proxy_server.py index 03a24ec5e98..04173ced776 100644 --- a/tests/test_litellm/proxy/test_proxy_server.py +++ b/tests/test_litellm/proxy/test_proxy_server.py @@ -15,10 +15,12 @@ from unittest import mock from unittest.mock import AsyncMock, MagicMock, create_autospec, mock_open, patch import click +import fastapi.routing import httpx import pytest import yaml from fastapi import FastAPI +from fastapi.encoders import jsonable_encoder from fastapi.staticfiles import StaticFiles from fastapi.testclient import TestClient @@ -31,6 +33,7 @@ from litellm.litellm_core_utils.get_model_cost_map import ModelCostMapReloaded from litellm.caching.dual_cache import DualCache from litellm.proxy._types import LitellmUserRoles, TokenCountRequest, UserAPIKeyAuth from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy.hooks.parallel_request_limiter_v3 import RequestRateLimiterStash from litellm.proxy.proxy_server import app, initialize from litellm.utils import _invalidate_model_cost_lowercase_map @@ -5247,6 +5250,8 @@ async def test_model_info_v1_oci_secrets_not_leaked(): result = await model_info_v1(user_api_key_dict=mock_user_api_key_dict, litellm_model_id=None) # Verify the result structure + result_str = result.body.decode() + result = json.loads(result_str) assert "data" in result assert len(result["data"]) == 1 @@ -5269,13 +5274,96 @@ async def test_model_info_v1_oci_secrets_not_leaked(): assert litellm_params["model"].startswith("oci/"), "model should retain its full value" # Verify that actual secret values are not present in the response - result_str = str(result) assert "ocid1.api_key.oc1..aaaaaaaa7kbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbk" not in result_str assert "aa:bb:cc:dd:ee:ff:11:22:33:44:55:66:77:88:99:00" not in result_str assert "ocid1.tenancy.oc1..aaaaaaaa7kbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbkbk" not in result_str assert "/path/to/oci_api_key.pem" not in result_str +def test_model_info_v1_list_skips_fastapi_jsonable_encoder(monkeypatch): + """ + /model/info serializes its multi-megabyte listing itself with orjson. FastAPI must not + re-walk the payload through `jsonable_encoder`, while values orjson cannot encode natively + still come out as JSON. + """ + created_at = datetime(2026, 1, 2, 3, 4, 5, tzinfo=timezone.utc) + model_data = { + "model_name": "gpt-4o", + "litellm_params": {"model": "openai/gpt-4o", "api_key": "sk-secret-value"}, + "model_info": { + "id": "db-row-1", + "db_model": True, + "created_at": created_at, + "supported_regions": frozenset({"eu"}), + }, + } + mock_router = MagicMock() + mock_router.model_list = [model_data] + mock_router.get_model_list_from_model_alias.return_value = [] + mock_router.get_model_names.return_value = ["gpt-4o"] + mock_router.get_model_access_groups.return_value = {} + mock_router.get_deployment.return_value = None + monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", mock_router) + monkeypatch.setattr("litellm.proxy.proxy_server.llm_model_list", [model_data]) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {"infer_model_from_keys": False}) + monkeypatch.setattr("litellm.proxy.proxy_server.user_model", None) + + encoder_spy = MagicMock(wraps=jsonable_encoder) + monkeypatch.setattr(fastapi.routing, "jsonable_encoder", encoder_spy) + + original_overrides = app.dependency_overrides.copy() + app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234", models=[], team_models=[] + ) + client = TestClient(app) + try: + response = client.get("/model/info") + finally: + app.dependency_overrides = original_overrides + + assert response.status_code == 200 + assert response.headers["content-type"] == "application/json" + rows = response.json()["data"] + assert [row["model_name"] for row in rows] == ["gpt-4o"] + assert rows[0]["model_info"]["created_at"] == created_at.isoformat() + assert rows[0]["model_info"]["supported_regions"] == ["eu"] + assert "sk-secret-value" not in response.text + assert encoder_spy.call_count == 0 + + +def test_model_info_v1_cli_model_returns_single_deployment_as_json(monkeypatch): + """ + A proxy started with `litellm --model ` answers /model/info with one deployment + object under `data`, serialized the same way as the listing. + """ + monkeypatch.setattr("litellm.proxy.proxy_server.user_model", "gpt-4o") + monkeypatch.setattr("litellm.proxy.proxy_server.llm_router", None) + monkeypatch.setattr("litellm.proxy.proxy_server.llm_model_list", None) + monkeypatch.setattr("litellm.proxy.proxy_server.prisma_client", None) + monkeypatch.setattr("litellm.proxy.proxy_server.general_settings", {}) + + encoder_spy = MagicMock(wraps=jsonable_encoder) + monkeypatch.setattr(fastapi.routing, "jsonable_encoder", encoder_spy) + + original_overrides = app.dependency_overrides.copy() + app.dependency_overrides[user_api_key_auth] = lambda: UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234", models=[], team_models=[] + ) + client = TestClient(app) + try: + response = client.get("/model/info") + finally: + app.dependency_overrides = original_overrides + + assert response.status_code == 200 + assert response.headers["content-type"] == "application/json" + deployment = response.json()["data"] + assert deployment["model_name"] == "*" + assert deployment["litellm_params"]["model"] == "gpt-4o" + assert encoder_spy.call_count == 0 + + def test_add_callback_from_db_to_in_memory_litellm_callbacks(): """ Test that _add_callback_from_db_to_in_memory_litellm_callbacks correctly adds callbacks @@ -9912,6 +10000,7 @@ async def _lit6973_drive_realtime_session( reservation: dict, *, backend_logged_success: bool, + backend_logged_failure: bool = False, phase_one_exit: str | None = None, websocket: MagicMock | None = None, ) -> MagicMock: @@ -9919,8 +10008,9 @@ async def _lit6973_drive_realtime_session( phase_one_exit picks a rejection before the relay: "model_access" makes the key/model check raise ProxyException, "pre_call" makes pre-call processing - (rate limits, guardrails) raise. Neither reaches route_request, so no success - log can own the reservation and the endpoint has to release it on that exit. + (rate limits, guardrails) raise, "pre_call_cancelled" cancels the task inside + pre-call processing. None reaches route_request, so no success log can own the + reservation and the endpoint has to release it on that exit. route_request resolves normally in both cases: the relay owns the session once route_request returns. A successful session enqueues its success cost @@ -9930,7 +10020,7 @@ async def _lit6973_drive_realtime_session( logging object carries a real model_call_details dict so the stamp is observable, and the reservation has empty entries so the real release touches no counter store.""" - from litellm.litellm_core_utils.realtime_streaming import REALTIME_SESSION_SUCCESS_LOGGED_KEY + from litellm.constants import REALTIME_SESSION_FAILURE_LOGGED_KEY, REALTIME_SESSION_SUCCESS_LOGGED_KEY from litellm.proxy import proxy_server as ps user_api_key_dict: Final = UserAPIKeyAuth(api_key="sk-test", token="hashed-token") @@ -9942,6 +10032,8 @@ async def _lit6973_drive_realtime_session( async def fake_llm_call() -> None: if backend_logged_success: logging_obj.model_call_details[REALTIME_SESSION_SUCCESS_LOGGED_KEY] = True + if backend_logged_failure: + logging_obj.model_call_details[REALTIME_SESSION_FAILURE_LOGGED_KEY] = True from litellm.proxy._types import ProxyException @@ -9950,7 +10042,13 @@ async def _lit6973_drive_realtime_session( if phase_one_exit == "model_access" else None ) - pre_call_error: Final = Exception("Rate limit exceeded") if phase_one_exit == "pre_call" else None + pre_call_error: Final = ( + asyncio.CancelledError() + if phase_one_exit == "pre_call_cancelled" + else Exception("Rate limit exceeded") + if phase_one_exit == "pre_call" + else None + ) pre_call: Final = AsyncMock( side_effect=pre_call_error, return_value=({"model": "vertex_ai/gemini-live-2.5-flash"}, logging_obj) ) @@ -10068,6 +10166,114 @@ async def test_successful_realtime_session_leaves_the_reservation_for_the_cost_c assert reservation["finalized"] is False +_LIT6463_COUNTER_KEY: Final = "{api_key:hashed-token}:max_parallel_requests" + + +async def _lit6463_drive_realtime_session_holding_a_max_parallel_slot( + *, + backend_logged_success: bool, + backend_logged_failure: bool = False, + phase_one_exit: str | None = None, +) -> tuple[DualCache, RequestRateLimiterStash]: + """Run the realtime endpoint with a real v3 limiter registered and the request's + stash already holding slot-1 of a two-slot counter, the state pre-call leaves + behind. Returns the limiter's cache and the stash so the test can read what the + endpoint did to the slot.""" + from litellm.proxy import proxy_server as ps + from litellm.proxy.hooks.parallel_request_limiter_v3 import ( + _PROXY_MaxParallelRequestsHandler_v3, + _request_stash, + ) + from litellm.proxy.utils import InternalUsageCache + + dual_cache: Final = DualCache() + await dual_cache.async_set_cache( + key=_LIT6463_COUNTER_KEY, value={"slot-1": 1.0, "slot-2": 2.0}, local_only=True + ) + limiter: Final = _PROXY_MaxParallelRequestsHandler_v3(internal_usage_cache=InternalUsageCache(dual_cache)) + stash: Final = RequestRateLimiterStash( + parallel_slot={"slot_id": "slot-1", "counter_keys": [_LIT6463_COUNTER_KEY]} + ) + reservation: Final = {"reserved_cost": 0.55, "input_cost": 0.0, "finalized": False, "entries": []} + + stash_token: Final = _request_stash.set(stash) + try: + hooks: Final = patch.dict( # test-quality-ok: registers the real limiter the route's release reads + ps.proxy_logging_obj.proxy_hook_mapping, {"parallel_request_limiter": limiter} + ) + expected_exit: Final = ( + pytest.raises(asyncio.CancelledError) + if phase_one_exit == "pre_call_cancelled" + else contextlib.nullcontext() + ) + with hooks, expected_exit: + await _lit6973_drive_realtime_session( + reservation, + backend_logged_success=backend_logged_success, + backend_logged_failure=backend_logged_failure, + phase_one_exit=phase_one_exit, + ) + finally: + _request_stash.reset(stash_token) + return dual_cache, stash + + +@pytest.mark.asyncio +@pytest.mark.parametrize("phase_one_exit", [None, "pre_call", "pre_call_cancelled"]) +async def test_realtime_session_ending_without_llm_callbacks_releases_the_max_parallel_slot( + phase_one_exit: str | None, +): + """The rate limiter acquires the key's max_parallel_requests slot in pre-call and + only frees it from the LLM success/failure callbacks. A realtime session that ends + without either callback (Bedrock closes without usage events, a later pre-call hook + rejects the session, or the task is cancelled while still in pre-call) has to be + released by the route itself, or the slot stays occupied until its TTL and the key's + next session is refused with a 429.""" + dual_cache, stash = await _lit6463_drive_realtime_session_holding_a_max_parallel_slot( + backend_logged_success=False, phase_one_exit=phase_one_exit + ) + + assert await dual_cache.async_get_cache(key=_LIT6463_COUNTER_KEY, local_only=True) == {"slot-2": 2.0} + assert stash.parallel_slot is None + + +@pytest.mark.asyncio +async def test_successful_realtime_session_leaves_the_max_parallel_slot_for_the_limiter_callback(): + """A session that enqueued its success callback hands the slot to the limiter's + own success handler, which runs on the logging worker. If the route also released + it, the two releases would race on the same stashed acquisition and, under the + limiter's integer in-memory fallback, double-decrement the counter so the key + admits more sessions than max_parallel_requests allows. With the success stamp + present the route leaves the slot and the stash alone.""" + dual_cache, stash = await _lit6463_drive_realtime_session_holding_a_max_parallel_slot( + backend_logged_success=True + ) + + assert await dual_cache.async_get_cache(key=_LIT6463_COUNTER_KEY, local_only=True) == { + "slot-1": 1.0, + "slot-2": 2.0, + } + assert stash.parallel_slot == {"slot_id": "slot-1", "counter_keys": [_LIT6463_COUNTER_KEY]} + + +@pytest.mark.asyncio +async def test_refused_realtime_session_leaves_the_max_parallel_slot_for_the_limiter_failure_callback(): + """An upstream refusal before any frame enqueues the failure callback instead, and + the limiter's failure handler releases the slot from the logging worker just like + the success handler does. The route sees no success stamp, so it still settles the + budget reservation, but it must leave the slot to that callback or the two releases + race on the same acquisition.""" + dual_cache, stash = await _lit6463_drive_realtime_session_holding_a_max_parallel_slot( + backend_logged_success=False, backend_logged_failure=True + ) + + assert await dual_cache.async_get_cache(key=_LIT6463_COUNTER_KEY, local_only=True) == { + "slot-1": 1.0, + "slot-2": 2.0, + } + assert stash.parallel_slot == {"slot_id": "slot-1", "counter_keys": [_LIT6463_COUNTER_KEY]} + + @pytest.mark.asyncio async def test_release_or_invalidate_falls_back_to_invalidating_the_counters(): """If releasing the reservation itself fails (e.g. the counter store is down), @@ -12589,6 +12795,45 @@ async def test_moderations_reraises_proxy_exception_unwrapped(): mock_logging.post_call_failure_hook.assert_awaited_once() +@pytest.mark.asyncio +async def test_moderations_response_carries_litellm_call_id_header(): + from fastapi import Response + + from litellm.types.utils import ModerationCreateResponse + + call_id = "moderation-call-id-123" + moderation_response = ModerationCreateResponse(id="modr-1", model="omni-moderation-latest", results=[]) + moderation_response._hidden_params = {"litellm_call_id": call_id, "model_id": "mod-deployment-1"} + + async def fake_llm_call(): + return moderation_response + + async def passthrough_add_litellm_data(data, **kwargs): + return {**data, "litellm_call_id": call_id} + + request = MagicMock() + request.body = AsyncMock(return_value=b'{"input": "hi"}') + fastapi_response = Response() + user_api_key_dict = UserAPIKeyAuth(api_key="sk-test", spend=0.0) + + with ( + patch.object(proxy_server_module, "add_litellm_data_to_request", new=passthrough_add_litellm_data), # test-quality-ok: the route reads this module global, no injection point + patch.object(proxy_server_module, "route_request", new=AsyncMock(return_value=fake_llm_call())), # test-quality-ok: fakes the provider call so the response headers assembled by the real route are observable + patch.object(proxy_server_module, "proxy_logging_obj") as mock_logging, # test-quality-ok: module global, no injection point + ): + mock_logging.pre_call_hook = AsyncMock(side_effect=lambda user_api_key_dict, data, call_type: data) + mock_logging.update_request_status = AsyncMock() + result = await proxy_server_module.moderations( + request=request, + fastapi_response=fastapi_response, + user_api_key_dict=user_api_key_dict, + ) + + assert result is moderation_response + assert fastapi_response.headers["x-litellm-call-id"] == call_id + assert fastapi_response.headers["x-litellm-model-id"] == "mod-deployment-1" + + @pytest.mark.asyncio async def test_init_agents_in_db_rebuilds_registry_under_agent_reconcile_lock(monkeypatch): from litellm.proxy.agent_endpoints.agent_registry import ( diff --git a/tests/test_litellm/proxy/test_proxy_types.py b/tests/test_litellm/proxy/test_proxy_types.py index 634b90e445a..5d5273be243 100644 --- a/tests/test_litellm/proxy/test_proxy_types.py +++ b/tests/test_litellm/proxy/test_proxy_types.py @@ -276,3 +276,13 @@ def test_a_server_only_marker_is_not_taken_from_the_caller(field, forged, defaul auth = UserAPIKeyAuth(api_key="sk-1234", **{field: forged}) assert getattr(auth, field) == default + + +@pytest.mark.parametrize("weight", [True, "1", -1, 0, float("inf")]) +def test_key_and_team_weights_reject_invalid_numeric_values(weight: bool | str | int | float) -> None: + from pydantic import ValidationError + from litellm.proxy._types import GenerateKeyRequest, NewTeamRequest + + for request_type in (GenerateKeyRequest, NewTeamRequest): + with pytest.raises(ValidationError): + request_type(router_settings={"weights": {"group": {"id": weight}}}) diff --git a/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py b/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py index a2a57931d26..8b2b6b4c6ca 100644 --- a/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py +++ b/tests/test_litellm/proxy/utils/proxy_logging/test_post_call_failure_hook.py @@ -33,9 +33,7 @@ def test_is_proxy_only_llm_api_truth_table(proxy_logging): snapshot. Covers no-route, non-LLM route, HTTPException on LLM route, and auth-error short-circuit.""" snapshot = { - "no_route": proxy_logging._is_proxy_only_llm_api_error( - original_exception=Exception(), route=None - ), + "no_route": proxy_logging._is_proxy_only_llm_api_error(original_exception=Exception(), route=None), "non_llm_route": proxy_logging._is_proxy_only_llm_api_error( original_exception=HTTPException(status_code=429, detail="rate"), route="/random/path", @@ -158,9 +156,7 @@ async def test_post_call_failure_hook_non_http_exception_in_callback_swallowed( @pytest.mark.asyncio -async def test_handle_logging_proxy_only_path_uses_existing_logging_obj( - proxy_logging, make_user_api_key_auth -): +async def test_handle_logging_proxy_only_path_uses_existing_logging_obj(proxy_logging, make_user_api_key_auth): logging_obj = MagicMock() logging_obj.call_type = "acompletion" logging_obj.model_call_details = {} @@ -183,10 +179,7 @@ async def test_handle_logging_proxy_only_path_uses_existing_logging_obj( snapshot = { "input_logged": "messages" in logging_obj.model_call_details, "call_type_normalized": logging_obj.call_type, - "marker_present": logging_obj.model_call_details.get( - LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL - ) - is True, + "marker_present": logging_obj.model_call_details.get(LITELLM_LOGGING_NO_UPSTREAM_LLM_CALL) is True, "async_failure_called": logging_obj.async_failure_handler.called, } assert snapshot == { @@ -198,9 +191,7 @@ async def test_handle_logging_proxy_only_path_uses_existing_logging_obj( @pytest.mark.asyncio -async def test_handle_logging_proxy_only_path_skips_for_pass_through( - proxy_logging, make_user_api_key_auth -): +async def test_handle_logging_proxy_only_path_skips_for_pass_through(proxy_logging, make_user_api_key_auth): from litellm.types.utils import CallTypes logging_obj = MagicMock() @@ -248,9 +239,7 @@ async def test_handle_logging_proxy_only_path_no_logging_obj_creates_one( @pytest.mark.asyncio -async def test_handle_logging_proxy_only_path_propagates_async_failure_raises( - proxy_logging, make_user_api_key_auth -): +async def test_handle_logging_proxy_only_path_propagates_async_failure_raises(proxy_logging, make_user_api_key_auth): logging_obj = MagicMock() logging_obj.call_type = "acompletion" logging_obj.model_call_details = {} @@ -267,3 +256,65 @@ async def test_handle_logging_proxy_only_path_propagates_async_failure_raises( route="/chat/completions", original_exception=Exception("x"), ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "route, request_data, expected_call_type", + [ + ("/v1/chat/completions", {}, "acompletion"), + ("/chat/completions", {"model": "m", "messages": [{"role": "user", "content": "hi"}]}, "acompletion"), + ("/v1/messages", {"model": "m", "messages": [{"role": "user", "content": "hi"}]}, "anthropic_messages"), + ("/v1/responses", {"model": "m", "input": "hi"}, "aresponses"), + ("/v1/embeddings", {"model": "m", "input": ["hi"]}, "aembedding"), + ("/model/info", {}, "/model/info"), + ], +) +async def test_post_call_failure_hook_lifts_route_call_type_for_gate_rejections( + proxy_logging, make_user_api_key_auth, route, request_data, expected_call_type +): + """Regression for LIT-5884: the matched route, not the body shape, sets the + spend-log call_type for requests rejected before dispatch.""" + proxy_logging.alert_types = [] + await proxy_logging.post_call_failure_hook( + request_data=request_data, + original_exception=Exception("Authentication Error, No api key passed in."), + user_api_key_dict=make_user_api_key_auth(request_route=route), + error_type=ProxyErrorTypes.auth_error, + route=route, + ) + assert request_data["call_type"] == expected_call_type + assert "start_time" in request_data + + +@pytest.mark.asyncio +async def test_post_call_failure_hook_falls_back_to_body_shape_without_a_route(proxy_logging, make_user_api_key_auth): + proxy_logging.alert_types = [] + request_data = {"model": "m", "messages": [{"role": "user", "content": "hi"}]} + await proxy_logging.post_call_failure_hook( + request_data=request_data, + original_exception=Exception("Authentication Error, No api key passed in."), + user_api_key_dict=make_user_api_key_auth(request_route="/chat/completions"), + error_type=ProxyErrorTypes.auth_error, + ) + assert request_data["call_type"] == "acompletion" + + +@pytest.mark.asyncio +@pytest.mark.parametrize("route", ["/v1/files", "/files/file-abc", "/v1/containers"]) +async def test_post_call_failure_hook_keeps_the_route_for_multi_operation_routes( + proxy_logging, make_user_api_key_auth, route +): + """Routes shared by several operations (POST create vs GET list) cannot be attributed without the + method, so a rejected request there is filed under its route, not under whichever operation the + mapping lists first.""" + proxy_logging.alert_types = [] + request_data: dict = {} + await proxy_logging.post_call_failure_hook( + request_data=request_data, + original_exception=Exception("Authentication Error, No api key passed in."), + user_api_key_dict=make_user_api_key_auth(request_route=route), + error_type=ProxyErrorTypes.auth_error, + route=route, + ) + assert request_data["call_type"] == route diff --git a/tests/test_litellm/realtime_api/test_main.py b/tests/test_litellm/realtime_api/test_main.py index 0827bbcdc38..d3d41c5b54b 100644 --- a/tests/test_litellm/realtime_api/test_main.py +++ b/tests/test_litellm/realtime_api/test_main.py @@ -4,7 +4,6 @@ from types import TracebackType from typing import Final from unittest.mock import MagicMock, patch - import pytest import litellm @@ -152,6 +151,33 @@ async def test_vertex_credential_resolution_bounds_a_thread_offloaded_refresh(): assert time.monotonic() - start < 5 +@pytest.mark.asyncio +async def test_meta_realtime_dispatches_to_base_handler_with_meta_config(monkeypatch: pytest.MonkeyPatch): + from litellm.llms.meta.realtime.transformation import MetaRealtimeConfig + + captured: dict[str, object] = {} + + def mock_get_llm_provider(model, api_base, api_key): + return model.removeprefix("meta/"), "meta", None, api_base + + async def mock_async_realtime(**kwargs): + captured.update(kwargs) + + monkeypatch.setattr(realtime_main, "get_llm_provider", mock_get_llm_provider) + monkeypatch.setattr(realtime_main.base_llm_http_handler, "async_realtime", mock_async_realtime) + + await realtime_main._arealtime.__wrapped__( + model="meta/muse-voice-transcribe-1.0", + websocket=MagicMock(), + litellm_logging_obj=FakeLogging(), + query_params={"model": "meta/muse-voice-transcribe-1.0", "intent": "transcription"}, + ) + + assert isinstance(captured["provider_config"], MetaRealtimeConfig) + assert captured["model"] == "muse-voice-transcribe-1.0" + assert captured["query_params"] == {"model": "muse-voice-transcribe-1.0", "intent": "transcription"} + + @pytest.mark.asyncio async def test_arealtime_vertex_branch_resolves_credentials_under_a_bound(monkeypatch): """The wiring half of the regression: the vertex branch of _arealtime must diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_handler.py b/tests/test_litellm/responses/litellm_completion_transformation/test_handler.py index 2cfec6a1844..b78dabbfe48 100644 --- a/tests/test_litellm/responses/litellm_completion_transformation/test_handler.py +++ b/tests/test_litellm/responses/litellm_completion_transformation/test_handler.py @@ -68,3 +68,105 @@ async def test_async_fallback_tags_skip_responses_api_bridge(): await coro assert captured.get("_skip_responses_api_bridge") is True + + +_CODEX_ADDITIONAL_TOOLS_ITEM = { + "type": "additional_tools", + "id": "at_codex", + "role": "developer", + "tools": [ + { + "type": "namespace", + "name": "functions", + "description": "", + "tools": [ + { + "type": "custom", + "name": "exec", + "description": "Runs a shell command.", + "format": {"type": "grammar", "syntax": "lark", "definition": "start: /.+/"}, + }, + { + "type": "function", + "name": "wait", + "description": "Waits for a background command.", + "parameters": {"type": "object", "properties": {"id": {"type": "string"}}}, + }, + ], + } + ], +} +_CODEX_INPUT = [_CODEX_ADDITIONAL_TOOLS_ITEM, {"type": "message", "role": "user", "content": "Run ls"}] + + +def test_sync_fallback_hoists_additional_tools_input_items_into_chat_tools(): + handler = LiteLLMCompletionTransformationHandler() + captured: dict = {} + + def fake_completion(**kwargs): + captured.update(kwargs) + raise _StopForwarding() + + with patch("litellm.completion", fake_completion): # test-quality-ok: no DI seam; the file stubs this same boundary + with pytest.raises(_StopForwarding): + handler.response_api_handler( + model="bedrock/us.openai.gpt-5.6", + input=_CODEX_INPUT, + responses_api_request={}, + custom_llm_provider="bedrock", + _is_async=False, + ) + + assert [message["role"] for message in captured["messages"]] == ["user"] + functions_by_name = {tool["function"]["name"]: tool["function"] for tool in captured["tools"]} + assert set(functions_by_name) == {"exec", "functions__wait"} + assert set(functions_by_name["exec"]["parameters"]["properties"]) == {"content"} + + +@pytest.mark.asyncio +async def test_async_fallback_returns_hoisted_nested_custom_tool_call_as_custom_tool_call(): + from litellm.responses.litellm_completion_transformation.transformation import TOOL_CALLS_CACHE + from litellm.types.utils import ChatCompletionMessageToolCall, Choices, Function, Message, ModelResponse + + handler = LiteLLMCompletionTransformationHandler() + tool_call_id = "call_exec_hoisted" + + async def fake_acompletion(**kwargs): + return ModelResponse( + id="chatcmpl-exec", + created=1, + model="us.openai.gpt-5.6", + object="chat.completion", + choices=[ + Choices( + finish_reason="tool_calls", + index=0, + message=Message( + content=None, + role="assistant", + tool_calls=[ + ChatCompletionMessageToolCall( + id=tool_call_id, + type="function", + function=Function(name="exec", arguments='{"content": "ls"}'), + ) + ], + ), + ) + ], + ) + + try: + with patch("litellm.acompletion", fake_acompletion): # test-quality-ok: no DI seam; file stubs this boundary + response = await handler.response_api_handler( + model="bedrock/us.openai.gpt-5.6", + input=_CODEX_INPUT, + responses_api_request={}, + custom_llm_provider="bedrock", + _is_async=True, + ) + finally: + TOOL_CALLS_CACHE.delete_cache(key=tool_call_id) + + tool_calls = [(item.type, item.name, item.input) for item in response.output if item.type == "custom_tool_call"] + assert tool_calls == [("custom_tool_call", "exec", "ls")] diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py index 342ec4435a7..0ed101952be 100644 --- a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py +++ b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py @@ -2506,6 +2506,7 @@ class TestToolTransformation: "tools": [ "ignored", {"type": "namespace", "name": "ignored"}, + {"type": "web_search", "name": "ignored"}, { "type": "function", "name": "spawn_agent", @@ -2527,6 +2528,210 @@ class TestToolTransformation: "type": "object", } + def test_transform_nested_namespace_custom_tool_becomes_a_content_function_under_its_short_name(self): + namespace_tool = { + "type": "namespace", + "name": "functions", + "description": "Codex shell tools.", + "tools": [ + { + "type": "custom", + "name": "exec", + "description": "Runs a shell command.", + "format": {"type": "grammar", "syntax": "lark", "definition": "start: /.+/"}, + }, + ], + } + + result_tools, _ = ( + LiteLLMCompletionResponsesConfig.transform_responses_api_tools_to_chat_completion_tools( + tools=[namespace_tool] + ) + ) + + assert len(result_tools) == 1 + function = result_tools[0]["function"] + assert function["name"] == "exec" + assert function["description"].startswith("Codex shell tools.") + assert "Runs a shell command." in function["description"] + assert "start: /.+/" in function["description"] + assert function["parameters"]["required"] == ["content"] + assert function["parameters"]["properties"]["content"]["type"] == "string" + + @pytest.mark.parametrize( + "model, custom_llm_provider", + [ + ("bedrock/converse/global.anthropic.claude-sonnet-5", "bedrock_converse"), + ("anthropic.claude-sonnet-4-5-20250929-v1:0", "bedrock"), + ("claude-sonnet-5", "vertex_ai"), + ("gemini-3.1-pro-preview", "vertex_ai"), + ("moonshotai.kimi-k2-thinking", "bedrock_mantle"), + ], + ) + def test_reasoning_summary_still_yields_a_string_reasoning_effort(self, model, custom_llm_provider): + """ + A Responses request carrying ``reasoning.summary`` must still reach a chat provider as a + plain ``reasoning_effort`` string. ``summary`` is Responses-only, and forwarding the whole + object turns reasoning off: Bedrock Converse and Vertex silently discard a non-string + ``reasoning_effort``, and Bedrock Mantle rejects the request outright. + """ + responses_api_request = {"reasoning": {"effort": "medium", "summary": "auto"}} + + result = LiteLLMCompletionResponsesConfig.transform_responses_api_request_to_chat_completion_request( + model=model, + input="hi", + responses_api_request=responses_api_request, + custom_llm_provider=custom_llm_provider, + ) + + assert result["reasoning_effort"] == "medium" + + @pytest.mark.parametrize( + "model, custom_llm_provider", + [ + ("gpt-5.4-pro", "azure_ai"), + ("gpt-5", "openai"), + ("gpt-5.1", "openai"), + ("gpt-5", "azure"), + ], + ) + def test_bridged_model_carries_the_summary_as_an_alias(self, model, custom_llm_provider): + """ + ``summary`` reaches a bridged model through the ``reasoning_summary`` alias, never smuggled + inside ``reasoning_effort``. ``litellm.completion`` reads that alias back with + ``peek_reasoning_summary_aliases`` and reassembles ``{effort, summary}``, so the far end + gets the same object it always did while no chat provider ever sees a non-string effort. + """ + result = LiteLLMCompletionResponsesConfig.transform_responses_api_request_to_chat_completion_request( + model=model, + input="hi", + responses_api_request={"reasoning": {"effort": "medium", "summary": "auto"}}, + custom_llm_provider=custom_llm_provider, + ) + + assert result["reasoning_effort"] == "medium" + assert result["reasoning_summary"] == "auto" + + @pytest.mark.parametrize( + "model, custom_llm_provider", + [ + ("gpt-5", "openai"), + ("gpt-5.1", "openai"), + ("gpt-5", "azure"), + ], + ) + def test_gpt_5_summary_survives_the_bridge_it_claims_to_take(self, model, custom_llm_provider): + """ + Regression for the probe disagreeing with the real decision. The transform asked + ``responses_api_bridge_check`` with ``reasoning_summary`` taken straight off the Responses + object, but ``litellm.completion`` reads it from ``optional_params`` via + ``peek_reasoning_summary_aliases``, which the bridged request never populated. So these + models answered "bridging" to the probe and "not bridging" for real, and the object landed + on Chat Completions, which only takes a string. Emitting the alias makes the two agree. + """ + from litellm.main import responses_api_bridge_check + from litellm.utils import get_optional_params, peek_reasoning_summary_aliases + + result = LiteLLMCompletionResponsesConfig.transform_responses_api_request_to_chat_completion_request( + model=model, + input="hi", + responses_api_request={"reasoning": {"effort": "medium", "summary": "auto"}}, + custom_llm_provider=custom_llm_provider, + ) + optional_params = get_optional_params( + model=model, + custom_llm_provider=custom_llm_provider, + reasoning_effort=result["reasoning_effort"], + reasoning_summary=result["reasoning_summary"], + ) + model_info, _ = responses_api_bridge_check( + model=model, + custom_llm_provider=custom_llm_provider, + reasoning_effort=result["reasoning_effort"], + reasoning_summary=peek_reasoning_summary_aliases(optional_params), + ) + + assert model_info.get("mode") == "responses" + + def test_a_failing_bridge_probe_falls_back_to_the_string_effort(self, monkeypatch): + """ + The probe is a capability question, so a model-info lookup blowing up must not fail the + request. It degrades to the chat-safe form: a string effort and no alias. + """ + import litellm.main + + def _boom(**_kwargs): + raise RuntimeError("model info unavailable") + + monkeypatch.setattr(litellm.main, "responses_api_bridge_check", _boom) + + result = LiteLLMCompletionResponsesConfig.transform_responses_api_request_to_chat_completion_request( + model="gpt-5.4-pro", + input="hi", + responses_api_request={"reasoning": {"effort": "medium", "summary": "auto"}}, + custom_llm_provider="azure_ai", + ) + + assert result["reasoning_effort"] == "medium" + assert "reasoning_summary" not in result + + @pytest.mark.parametrize( + "reasoning, expected", + [ + ({"effort": "high"}, "high"), + ("low", "low"), + ({"summary": "auto"}, None), + ({}, None), + (None, None), + ], + ) + def test_reasoning_param_shapes_map_to_reasoning_effort(self, reasoning, expected): + """ + An object without ``effort`` carries nothing Chat Completions can use, so no + ``reasoning_effort`` is sent at all (the bridge drops None-valued params). + """ + result = LiteLLMCompletionResponsesConfig.transform_responses_api_request_to_chat_completion_request( + model="anthropic.claude-sonnet-4-5-20250929-v1:0", + input="hi", + responses_api_request={"reasoning": reasoning}, + custom_llm_provider="bedrock", + ) + + assert result.get("reasoning_effort") == expected + assert ("reasoning_effort" in result) is (expected is not None) + + @pytest.mark.parametrize( + "model, expected_thinking", + [ + ("global.anthropic.claude-sonnet-5", {"type": "adaptive"}), + ( + "anthropic.claude-sonnet-4-5-20250929-v1:0", + {"type": "enabled", "budget_tokens": 2048}, + ), + ], + ) + def test_reasoning_summary_still_enables_thinking_on_bedrock(self, model, expected_thinking): + """ + End to end through Bedrock Converse's own param mapping: the effort a Responses request asks + for must survive into ``thinking``, whether the model takes an adaptive effort or a legacy + token budget. Forwarding the object instead leaves ``thinking`` unset and the model never + reasons, which is the failure this guards. + """ + from litellm.llms.bedrock.chat.converse_transformation import AmazonConverseConfig + + bridged = LiteLLMCompletionResponsesConfig.transform_responses_api_request_to_chat_completion_request( + model=model, + input="hi", + responses_api_request={"reasoning": {"effort": "medium", "summary": "auto"}}, + custom_llm_provider="bedrock", + ) + + mapped = AmazonConverseConfig().map_openai_params( + {"reasoning_effort": bridged["reasoning_effort"]}, {}, model, True + ) + + assert expected_thinking.items() <= mapped["thinking"].items() + def test_bedrock_anthropic_responses_tools_yield_only_function_toolspec(self): """ End-to-end (no network) of the LIT-3858 acceptance criterion: the mixed tools array @@ -2615,6 +2820,7 @@ class TestUsageTransformation: assert response_usage.input_tokens_details is not None assert response_usage.input_tokens_details.cached_tokens == 5 assert response_usage.input_tokens_details.text_tokens == 8 + assert "cache_write_tokens" not in response_usage.input_tokens_details.model_dump() def test_transform_usage_with_cached_tokens_gemini(self): """Test that cached_tokens from Gemini are properly transformed to input_tokens_details""" @@ -2677,6 +2883,7 @@ class TestUsageTransformation: assert response_usage.input_tokens_details is not None assert response_usage.input_tokens_details.cached_tokens == 100 assert getattr(response_usage.input_tokens_details, "cache_write_tokens", None) == 800 + assert response_usage.input_tokens_details.model_dump()["cache_write_tokens"] == 800 def test_transform_usage_with_reasoning_tokens_gemini(self): """Test that reasoning_tokens from Gemini are properly transformed to output_tokens_details""" @@ -3612,6 +3819,143 @@ class TestEnsureOutputItemContentPartAdded: assert added.item.name == "spawn_agent" assert added.item.namespace == "collaboration" + def test_streaming_nested_custom_tool_call_comes_back_as_custom_tool_call(self): + from litellm.responses.litellm_completion_transformation.custom_tools import extract_custom_tool_names + + iterator = self._make_iterator() + iterator.responses_api_request = { + "tools": [ + { + "type": "namespace", + "name": "functions", + "tools": [ + { + "type": "custom", + "name": "exec", + "format": {"type": "grammar", "syntax": "lark", "definition": "start: /.+/"}, + } + ], + } + ] + } + iterator._custom_tool_names = extract_custom_tool_names(iterator.responses_api_request.get("tools")) + iterator._namespace_tool_names = LiteLLMCompletionResponsesConfig.namespace_tool_name_map( + iterator.responses_api_request.get("tools") + ) + + iterator._queue_tool_call_delta_events( + [{"index": 0, "id": "call_exec", "function": {"name": "exec", "arguments": '{"content":"ls"}'}}] + ) + iterator._queue_final_tool_call_done_events( + ModelResponse( + id="chatcmpl-exec", + created=1, + model="us.openai.gpt-5.6", + object="chat.completion", + choices=[ + Choices( + finish_reason="tool_calls", + index=0, + message=Message( + content=None, + role="assistant", + tool_calls=[ + ChatCompletionMessageToolCall( + id="call_exec", + type="function", + function=Function(name="exec", arguments='{"content":"ls"}'), + ) + ], + ), + ) + ], + ) + ) + + added = iterator._pending_tool_events[0] + assert added.item.type == "custom_tool_call" + assert added.item.name == "exec" + done = iterator._pending_tool_events[-1] + assert done.item.type == "custom_tool_call" + assert done.item.input == "ls" + + def test_streaming_namespaced_function_sharing_a_nested_custom_short_name_stays_a_function_call(self): + from litellm.responses.litellm_completion_transformation.custom_tools import extract_custom_tool_names + + iterator = self._make_iterator() + iterator.responses_api_request = { + "tools": [ + { + "type": "namespace", + "name": "alpha", + "tools": [ + { + "type": "custom", + "name": "run", + "format": {"type": "grammar", "syntax": "lark", "definition": "start: /.+/"}, + } + ], + }, + { + "type": "namespace", + "name": "beta", + "tools": [ + { + "type": "function", + "name": "run", + "parameters": {"type": "object", "properties": {"job_id": {"type": "string"}}}, + } + ], + }, + ] + } + iterator._custom_tool_names = extract_custom_tool_names(iterator.responses_api_request.get("tools")) + iterator._namespace_tool_names = LiteLLMCompletionResponsesConfig.namespace_tool_name_map( + iterator.responses_api_request.get("tools") + ) + function_call = {"id": "call_fn", "function": {"name": "beta__run", "arguments": '{"job_id":"42"}'}} + custom_call = {"id": "call_custom", "function": {"name": "run", "arguments": '{"content":"echo hi"}'}} + + iterator._queue_tool_call_delta_events([{"index": 0, **function_call}, {"index": 1, **custom_call}]) + iterator._queue_final_tool_call_done_events( + ModelResponse( + id="chatcmpl-run", + created=1, + model="us.openai.gpt-5.6", + object="chat.completion", + choices=[ + Choices( + finish_reason="tool_calls", + index=0, + message=Message( + content=None, + role="assistant", + tool_calls=[ + ChatCompletionMessageToolCall( + id=call["id"], type="function", function=Function(**call["function"]) + ) + for call in (function_call, custom_call) + ], + ), + ) + ], + ) + ) + + items = [ + event.item + for event in iterator._pending_tool_events + if event.type in ("response.output_item.added", "response.output_item.done") + ] + function_items = [item for item in items if item.call_id == "call_fn"] + custom_items = [item for item in items if item.call_id == "call_custom"] + assert len(function_items) == 2 and len(custom_items) == 2 + assert all((item.type, item.name, item.namespace) == ("function_call", "run", "beta") for item in function_items) + assert function_items[-1].arguments == '{"job_id":"42"}' + assert all(item.type == "custom_tool_call" and item.name == "run" for item in custom_items) + assert all(getattr(item, "namespace", None) is None for item in custom_items) + assert custom_items[-1].input == "echo hi" + def test_streaming_unqualified_namespace_tool_calls_restore_namespace(self): """A unique nested tool name without the namespace still maps back.""" iterator = self._make_iterator() diff --git a/tests/test_litellm/responses/test_additional_tools.py b/tests/test_litellm/responses/test_additional_tools.py new file mode 100644 index 00000000000..bef3b27eacd --- /dev/null +++ b/tests/test_litellm/responses/test_additional_tools.py @@ -0,0 +1,48 @@ +from litellm.responses.additional_tools import hoist_additional_tools + +_EXEC_TOOL = {"type": "custom", "name": "exec", "format": {"type": "grammar", "syntax": "lark", "definition": "start: /.+/"}} +_WAIT_TOOL = {"type": "function", "name": "wait", "parameters": {"type": "object", "properties": {}}} +_TOP_LEVEL_TOOL = {"type": "function", "name": "top_level", "parameters": {"type": "object", "properties": {}}} +_USER_MESSAGE = {"type": "message", "role": "user", "content": "Run ls"} + + +def test_string_input_passes_through_with_existing_tools(): + hoisted = hoist_additional_tools("hello", [_TOP_LEVEL_TOOL]) + + assert hoisted.input == "hello" + assert hoisted.tools == (_TOP_LEVEL_TOOL,) + assert hoisted.hoisted == () + + +def test_input_without_additional_tools_items_is_returned_untouched(): + request_input = [_USER_MESSAGE] + + hoisted = hoist_additional_tools(request_input, None) + + assert hoisted.input is request_input + assert hoisted.tools == () + assert hoisted.hoisted == () + + +def test_additional_tools_items_are_stripped_and_appended_after_top_level_tools_in_item_order(): + request_input = [ + {"type": "additional_tools", "id": "at_1", "role": "developer", "tools": [_EXEC_TOOL]}, + _USER_MESSAGE, + {"type": "additional_tools", "id": "at_2", "role": "developer", "tools": [_WAIT_TOOL]}, + ] + + hoisted = hoist_additional_tools(request_input, [_TOP_LEVEL_TOOL]) + + assert hoisted.input == [_USER_MESSAGE] + assert hoisted.tools == (_TOP_LEVEL_TOOL, _EXEC_TOOL, _WAIT_TOOL) + assert hoisted.hoisted == (_EXEC_TOOL, _WAIT_TOOL) + + +def test_additional_tools_item_without_a_tools_list_is_stripped_and_contributes_nothing(): + request_input = [{"type": "additional_tools", "id": "at_1", "role": "developer", "tools": "exec"}, _USER_MESSAGE] + + hoisted = hoist_additional_tools(request_input, None) + + assert hoisted.input == [_USER_MESSAGE] + assert hoisted.tools == () + assert hoisted.hoisted == () diff --git a/tests/test_litellm/responses/test_custom_tool_call.py b/tests/test_litellm/responses/test_custom_tool_call.py index e80301c3b2f..2ed71ee3ecf 100644 --- a/tests/test_litellm/responses/test_custom_tool_call.py +++ b/tests/test_litellm/responses/test_custom_tool_call.py @@ -55,6 +55,24 @@ class TestCustomToolUtilities: names = extract_custom_tool_names(tools) assert names == set() + def test_extract_custom_tool_names_walks_namespace_tools(self): + tools = [ + {"type": "function", "name": "regular_tool"}, + { + "type": "namespace", + "name": "functions", + "tools": [ + {"type": "custom", "name": "exec"}, + {"type": "function", "name": "wait"}, + "ignored", + ], + }, + {"type": "namespace", "name": "empty", "tools": "not-a-list"}, + ] + + names = extract_custom_tool_names(tools) + assert names == {"exec"} + def test_extract_custom_tool_names_none(self): """Test extraction with None input.""" names = extract_custom_tool_names(None) diff --git a/tests/test_litellm/responses/test_responses_utils.py b/tests/test_litellm/responses/test_responses_utils.py index 9d9eefdceb3..4d06b5e7bdc 100644 --- a/tests/test_litellm/responses/test_responses_utils.py +++ b/tests/test_litellm/responses/test_responses_utils.py @@ -577,6 +577,47 @@ class TestResponseAPILoggingUtils: assert result.completion_tokens_details is not None assert result.completion_tokens_details.reasoning_tokens == 4 + def test_transform_realtime_usage_dict_keeps_cached_tokens_details(self): + usage = { + "input_tokens": 283, + "output_tokens": 0, + "total_tokens": 283, + "input_token_details": { + "text_tokens": 116, + "audio_tokens": 167, + "cached_tokens": 192, + "cached_tokens_details": {"text_tokens": 64, "audio_tokens": 128}, + }, + } + + result = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(usage) + + assert result.prompt_tokens_details is not None + assert result.prompt_tokens_details.cached_tokens == 192 + assert result.prompt_tokens_details.cached_tokens_details is not None + assert result.prompt_tokens_details.cached_tokens_details.audio_tokens == 128 + assert result.prompt_tokens_details.cached_tokens_details.text_tokens == 64 + + def test_transform_response_api_usage_object_keeps_cached_tokens_details(self): + usage = ResponseAPIUsage( + input_tokens=283, + output_tokens=0, + total_tokens=283, + input_tokens_details={ + "text_tokens": 116, + "audio_tokens": 167, + "cached_tokens": 192, + "cached_tokens_details": {"text_tokens": 64, "audio_tokens": 128}, + }, + ) + + result = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(usage) + + assert result.prompt_tokens_details is not None + assert result.prompt_tokens_details.cached_tokens_details is not None + assert result.prompt_tokens_details.cached_tokens_details.audio_tokens == 128 + assert result.prompt_tokens_details.cached_tokens_details.text_tokens == 64 + class TestResponsesAPIProviderSpecificParams: """ diff --git a/tests/test_litellm/responses/test_streaming_iterator_error_events.py b/tests/test_litellm/responses/test_streaming_iterator_error_events.py index ad74861c096..3d7c220804a 100644 --- a/tests/test_litellm/responses/test_streaming_iterator_error_events.py +++ b/tests/test_litellm/responses/test_streaming_iterator_error_events.py @@ -1,9 +1,14 @@ """ Regression: in-stream error events (type="error", type="response.failed") must raise instead of being returned as benign chunks, mirroring chat streaming -semantics (_handle_stream_fallback_error): non-retriable 4xx (except 429) -raise litellm.APIError directly; 429 and 5xx are wrapped in -MidStreamFallbackError so the Router's mid-stream fallback machinery fires. +semantics (_handle_stream_fallback_error). The event's code, type and status go +through litellm.exception_type, so each event raises the same typed exception +the non-streaming path raises for that provider error: non-retriable 4xx +(except 429) raise that typed exception directly, so a context-length event +surfaces as ContextWindowExceededError(400) with no MidStreamFallbackError +wrapping, while 429, 5xx and ContentPolicyViolationError are wrapped in +MidStreamFallbackError so the Router's mid-stream fallback machinery fires and +its content_policy_fallbacks dispatch sees the trigger it matches on. Status mapping must consider both the OpenAI error `type` (e.g. "invalid_request_error") and `code` (e.g. "invalid_prompt", @@ -66,12 +71,12 @@ def test_maybe_raise_for_error_event_wraps_unknown_error_in_mid_stream_fallback( with pytest.raises(MidStreamFallbackError) as exc_info: iterator._maybe_raise_for_error_event(chunk) assert exc_info.value.status_code == 500 - assert isinstance(exc_info.value.original_exception, litellm.APIError) + assert isinstance(exc_info.value.original_exception, litellm.InternalServerError) assert exc_info.value.original_exception.status_code == 500 def test_maybe_raise_for_error_event_maps_rate_limit_code_to_429_mid_stream_fallback(): - """429 is retriable: it must be wrapped so the Router can fall back, carrying the mapped APIError.""" + """429 is retriable: it must be wrapped so the Router can fall back, carrying the mapped RateLimitError.""" iterator = _make_iterator() chunk = _make_error_chunk("tokens", "rate_limit_exceeded", "Too many requests") with pytest.raises(MidStreamFallbackError) as exc_info: @@ -79,15 +84,15 @@ def test_maybe_raise_for_error_event_maps_rate_limit_code_to_429_mid_stream_fall assert exc_info.value.status_code == 429 assert exc_info.value.generated_content == "" assert exc_info.value.is_pre_first_chunk is True - assert isinstance(exc_info.value.original_exception, litellm.APIError) + assert isinstance(exc_info.value.original_exception, litellm.RateLimitError) assert exc_info.value.original_exception.status_code == 429 def test_maybe_raise_for_error_event_maps_invalid_request_type_to_400(): - """Client errors classified via the `type` field must raise APIError directly (no fallback).""" + """Client errors classified via the `type` field must raise BadRequestError directly (no fallback).""" iterator = _make_iterator() chunk = _make_error_chunk("invalid_request_error", "invalid_prompt", "bad request") - with pytest.raises(litellm.APIError) as exc_info: + with pytest.raises(litellm.BadRequestError) as exc_info: iterator._maybe_raise_for_error_event(chunk) assert exc_info.value.status_code == 400 assert not isinstance(exc_info.value, MidStreamFallbackError) @@ -99,12 +104,86 @@ def test_maybe_raise_for_error_event_maps_context_length_code_to_400(): chunk = Mock() chunk.type = "error" chunk.error = {"code": "context_length_exceeded", "message": "too long"} - with pytest.raises(litellm.APIError) as exc_info: + with pytest.raises(litellm.BadRequestError) as exc_info: iterator._maybe_raise_for_error_event(chunk) assert exc_info.value.status_code == 400 assert not isinstance(exc_info.value, MidStreamFallbackError) +def test_maybe_raise_for_error_event_raises_context_window_exceeded_directly(): + """A context-length error event maps to ContextWindowExceededError exactly like the non-streaming + path and, being a non-retriable client error, is raised directly rather than wrapped for mid-stream + fallback, preserving the direct-SDK 400 contract from issue #15785.""" + iterator = _make_iterator() + chunk = _make_error_chunk( + "invalid_request_error", + "context_length_exceeded", + "This model's maximum context length is 128000 tokens. However, your messages resulted in 130000 tokens.", + ) + with pytest.raises(litellm.ContextWindowExceededError) as exc_info: + iterator._maybe_raise_for_error_event(chunk) + assert exc_info.value.status_code == 400 + assert not isinstance(exc_info.value, MidStreamFallbackError) + assert "maximum context length" in str(exc_info.value) + + +CONTENT_POLICY_MESSAGE = "This content was flagged for possible cybersecurity risk. The response was halted mid-stream." + + +@pytest.mark.parametrize("custom_llm_provider", ["openai", "azure"]) +def test_maybe_raise_for_error_event_wraps_content_policy_violation_for_content_policy_fallbacks( + custom_llm_provider: str, +): + """Regression: a content_policy_violation error event used to raise a bare APIError, so the Router's + content_policy_fallbacks never fired. It must map to ContentPolicyViolationError (the same exception the + non-streaming path raises) and be wrapped so the Router's mid-stream fallback catches it.""" + iterator = _make_iterator() + iterator.custom_llm_provider = custom_llm_provider + chunk = _make_error_chunk("invalid_request_error", "content_policy_violation", CONTENT_POLICY_MESSAGE) + with pytest.raises(MidStreamFallbackError) as exc_info: + iterator._maybe_raise_for_error_event(chunk) + assert isinstance(exc_info.value.original_exception, litellm.ContentPolicyViolationError) + assert exc_info.value.original_exception.status_code == 400 + assert exc_info.value.status_code == 400 + assert exc_info.value.is_pre_first_chunk is True + assert CONTENT_POLICY_MESSAGE in str(exc_info.value.original_exception) + + +def test_maybe_raise_for_response_failed_event_wraps_content_policy_violation(): + iterator = _make_iterator() + chunk = _make_failed_chunk( + {"type": "invalid_request_error", "code": "content_policy_violation", "message": CONTENT_POLICY_MESSAGE} + ) + with pytest.raises(MidStreamFallbackError) as exc_info: + iterator._maybe_raise_for_error_event(chunk) + assert isinstance(exc_info.value.original_exception, litellm.ContentPolicyViolationError) + + +@pytest.mark.parametrize( + "error_type,error_code,expected_exception", + [ + ("invalid_request_error", "content_policy_violation", litellm.ContentPolicyViolationError), + ("tokens", "rate_limit_exceeded", litellm.RateLimitError), + ("invalid_request_error", "insufficient_quota", litellm.RateLimitError), + ("server_error", "internal_error", litellm.InternalServerError), + ("invalid_request_error", "invalid_prompt", litellm.BadRequestError), + ("invalid_request_error", "model_not_found", litellm.NotFoundError), + ("server_error", "vector_store_timeout", litellm.Timeout), + ], +) +def test_error_event_raises_the_same_typed_exception_as_the_non_streaming_path( + error_type: str, error_code: str, expected_exception: type[Exception] +): + iterator = _make_iterator() + chunk = _make_error_chunk(error_type, error_code, "provider message") + with pytest.raises((MidStreamFallbackError, expected_exception)) as exc_info: + iterator._maybe_raise_for_error_event(chunk) + raised = exc_info.value + typed_exception = raised.original_exception if isinstance(raised, MidStreamFallbackError) else raised + assert type(typed_exception) is expected_exception + assert "provider message" in str(typed_exception) + + def test_maybe_raise_for_error_event_maps_insufficient_quota_to_429(): """OpenAI returns HTTP 429 for insufficient_quota; it must not map to 400 even though its type is invalid_request_error-adjacent, and it must be wrapped for fallback.""" @@ -113,6 +192,7 @@ def test_maybe_raise_for_error_event_maps_insufficient_quota_to_429(): with pytest.raises(MidStreamFallbackError) as exc_info: iterator._maybe_raise_for_error_event(chunk) assert exc_info.value.status_code == 429 + assert isinstance(exc_info.value.original_exception, litellm.RateLimitError) def test_maybe_raise_for_error_event_passes_through_normal_chunk(): @@ -186,10 +266,40 @@ async def test_async_iterator_raises_mid_stream_fallback_on_rate_limit_error_eve assert exc_info.value.status_code == 429 assert exc_info.value.is_pre_first_chunk is True assert exc_info.value.generated_content == "" - assert isinstance(exc_info.value.original_exception, litellm.APIError) + assert isinstance(exc_info.value.original_exception, litellm.RateLimitError) assert exc_info.value.original_exception.status_code == 429 +@pytest.mark.asyncio +async def test_async_iterator_content_policy_violation_after_first_chunk_carries_generated_content(): + """The customer's case: text streams, then the provider halts the stream with a + content_policy_violation error event. The iterator must surface ContentPolicyViolationError + inside MidStreamFallbackError, together with the text already streamed.""" + iterator = _make_async_iterator_with_events( + [ + {"type": "response.output_text.delta", "delta": "partial "}, + { + "type": "error", + "error": { + "type": "invalid_request_error", + "code": "content_policy_violation", + "message": CONTENT_POLICY_MESSAGE, + }, + }, + ] + ) + + stream = aiter(iterator) + first_chunk = await anext(stream) + assert first_chunk is not None + + with pytest.raises(MidStreamFallbackError) as exc_info: + await anext(stream) + assert isinstance(exc_info.value.original_exception, litellm.ContentPolicyViolationError) + assert exc_info.value.is_pre_first_chunk is False + assert exc_info.value.generated_content == "partial " + + @pytest.mark.asyncio async def test_async_iterator_error_after_first_chunk_carries_generated_content(): """An error after streamed output must expose the accumulated text so the router's @@ -205,14 +315,13 @@ async def test_async_iterator_error_after_first_chunk_carries_generated_content( ] ) - chunks = [] - async def _drain(): - async for chunk in iterator: - chunks.append(chunk) + stream = aiter(iterator) + first_chunk = await anext(stream) + second_chunk = await anext(stream) + assert first_chunk is not None and second_chunk is not None with pytest.raises(MidStreamFallbackError) as exc_info: - await _drain() - assert len(chunks) == 2 + await anext(stream) assert exc_info.value.status_code == 500 assert exc_info.value.is_pre_first_chunk is False assert exc_info.value.generated_content == "hello world" @@ -265,7 +374,7 @@ def test_handle_logging_failed_response_maps_rate_limit_to_429(): ): iterator._handle_logging_failed_response() logged_exception = mock_run_async.call_args.kwargs["exception"] - assert isinstance(logged_exception, litellm.APIError) + assert isinstance(logged_exception, litellm.RateLimitError) assert logged_exception.status_code == 429 assert "throttled" in str(logged_exception) @@ -282,10 +391,28 @@ def test_handle_logging_failed_response_maps_type_field_to_400(): ): iterator._handle_logging_failed_response() logged_exception = mock_run_async.call_args.kwargs["exception"] - assert isinstance(logged_exception, litellm.APIError) + assert isinstance(logged_exception, litellm.BadRequestError) assert logged_exception.status_code == 400 +def test_handle_logging_failed_response_logs_content_policy_violation(): + """Failure logging must record the same typed exception the stream raises, so logging + integrations see a content policy violation instead of a generic APIError.""" + iterator = _make_iterator() + iterator.completed_response = _make_failed_chunk( + {"type": "invalid_request_error", "code": "content_policy_violation", "message": CONTENT_POLICY_MESSAGE} + ) + with ( + patch.object(import_module("litellm.responses.streaming_iterator"), "run_async_function") as mock_run_async, + patch.object(import_module("litellm.responses.streaming_iterator"), "executor"), + ): + iterator._handle_logging_failed_response() + logged_exception = mock_run_async.call_args.kwargs["exception"] + assert isinstance(logged_exception, litellm.ContentPolicyViolationError) + assert logged_exception.status_code == 400 + assert CONTENT_POLICY_MESSAGE in str(logged_exception) + + def test_handle_logging_failed_response_records_usage_and_cost(): """Usage on a response.failed event must reach failure spend accounting via combined_usage_object.""" iterator = _make_iterator() @@ -357,7 +484,7 @@ def test_sync_iterator_raises_mid_stream_fallback_on_rate_limit_error_event(): for _ in iterator: pass assert exc_info.value.status_code == 429 - assert isinstance(exc_info.value.original_exception, litellm.APIError) + assert isinstance(exc_info.value.original_exception, litellm.RateLimitError) def test_every_openai_sdk_response_error_code_has_explicit_status_mapping(): @@ -413,7 +540,7 @@ def test_maybe_raise_for_response_failed_event_maps_image_code_to_400(): chunk = Mock() chunk.type = "response.failed" chunk.response = mock_response_obj - with pytest.raises(litellm.APIError) as exc_info: + with pytest.raises(litellm.BadRequestError) as exc_info: iterator._maybe_raise_for_error_event(chunk) assert exc_info.value.status_code == 400 assert not isinstance(exc_info.value, MidStreamFallbackError) diff --git a/tests/test_litellm/router_strategy/test_simple_shuffle.py b/tests/test_litellm/router_strategy/test_simple_shuffle.py index 165c1751f63..abf02860a50 100644 --- a/tests/test_litellm/router_strategy/test_simple_shuffle.py +++ b/tests/test_litellm/router_strategy/test_simple_shuffle.py @@ -1,4 +1,5 @@ from collections import Counter +from inspect import isawaitable import pytest @@ -52,3 +53,52 @@ async def test_uniform_pick_when_every_configured_weight_is_zero(): assert counts["unweighted"] > 0 assert counts["standby"] > 0 + + +@pytest.mark.asyncio +@pytest.mark.parametrize("selector", [ + "get_available_deployment", "async_get_available_deployment", + "get_available_deployment_for_pass_through", "async_get_available_deployment_for_pass_through", +]) +async def test_scoped_weights_are_request_local_and_respect_eligibility(selector: str) -> None: + router = Router(model_list=[ + { + **_deployment(deployment_id, { + "weight": 100 if deployment_id == "global" else 0, "use_in_pass_through": True, + }), + "model_name": f"model_name_{team_id}_{deployment_id}", + "model_info": { + "id": deployment_id, "team_id": team_id, "team_public_model_name": "test-model", "blocked": blocked, + }, + } + for deployment_id, team_id, blocked in ( + ("global", "team-a", False), ("scoped", "team-a", False), + ("blocked", "team-a", True), ("foreign", "other-team", False), + ) + ], num_retries=0) + + for weights, expected in ( + ({"test-model": {"global": 0, "scoped": 100, "blocked": 100, "foreign": 100}}, "scoped"), + ({"test-model": {"global": 100, "scoped": 0}}, "global"), + ({"test-model": {"foreign": 100}}, "global"), + ({"test-model": {"blocked": 100}}, "global"), + (None, "global"), + ): + result = getattr(router, selector)( + model="test-model", + request_kwargs={"metadata": {"user_api_key_team_id": "team-a"}, "_router_weights": weights}, + ) + deployment = await result if isawaitable(result) else result + assert deployment["model_info"]["id"] == expected + + +def test_scoped_weights_approximate_the_configured_split() -> None: + router = Router(model_list=[_deployment("primary"), _deployment("secondary")], num_retries=0) + counts = Counter( + router.get_available_deployment( + model="test-model", + request_kwargs={"_router_weights": {"test-model": {"primary": 80, "secondary": 20}}}, + )["model_info"]["id"] + for _ in range(1000) + ) + assert 700 < counts["primary"] < 900 diff --git a/tests/test_litellm/router_utils/pre_call_checks/test_encrypted_content_affinity_check.py b/tests/test_litellm/router_utils/pre_call_checks/test_encrypted_content_affinity_check.py index ea8e2eacaa6..b93b8c1cdfc 100644 --- a/tests/test_litellm/router_utils/pre_call_checks/test_encrypted_content_affinity_check.py +++ b/tests/test_litellm/router_utils/pre_call_checks/test_encrypted_content_affinity_check.py @@ -21,6 +21,7 @@ from unittest.mock import AsyncMock, patch import pytest import litellm +from litellm.models.credentials import CredentialItem from litellm.responses.utils import ResponsesAPIRequestUtils from litellm.types.llms.openai import ResponsesAPIResponse @@ -1082,6 +1083,173 @@ def test_boundary_key_accepts_pydantic_litellm_params_instance(): ) +def test_boundary_key_resolves_missing_values_from_named_credential(): + from litellm.router_utils.pre_call_checks.encrypted_content_affinity_check import ( + EncryptedContentAffinityCheck, + ) + + with ( + patch.object( # test-quality-ok: credential registry is the direct dependency under test + litellm, + "credential_list", + [ + CredentialItem( + credential_name="account-a", + credential_values={ + "api_base": "https://account-a.example.com", + "api_key": "credential-key-a", + }, + credential_info={}, + ) + ], + ) + ): + boundary = EncryptedContentAffinityCheck._encryption_boundary_key({"litellm_credential_name": "account-a"}) + + assert boundary == ("https://account-a.example.com", "credential-key-a") + + +def test_boundary_key_matches_named_credential_precedence(): + from litellm.router_utils.pre_call_checks.encrypted_content_affinity_check import ( + EncryptedContentAffinityCheck, + ) + + with ( + patch.object( # test-quality-ok: credential registry is the direct dependency under test + litellm, + "credential_list", + [ + CredentialItem( + credential_name="account-a", + credential_values={ + "api_base": "https://credential.example.com", + "api_key": "credential-key-a", + }, + credential_info={}, + ) + ], + ) + ): + boundary = EncryptedContentAffinityCheck._encryption_boundary_key( + { + "api_base": "https://deployment.example.com", + "api_key": "deployment-key", + "litellm_credential_name": "account-a", + } + ) + + assert boundary == ("https://credential.example.com", "credential-key-a") + + +def test_boundary_key_resolves_credential_when_explicit_values_are_empty(): + from litellm.router_utils.pre_call_checks.encrypted_content_affinity_check import ( + EncryptedContentAffinityCheck, + ) + + with ( + patch.object( # test-quality-ok: credential registry is the direct dependency under test + litellm, + "credential_list", + [ + CredentialItem( + credential_name="account-a", + credential_values={ + "api_base": "https://credential.example.com", + "api_key": "credential-key-a", + }, + credential_info={}, + ) + ], + ) + ): + boundary = EncryptedContentAffinityCheck._encryption_boundary_key( + { + "api_base": "", + "api_key": "", + "litellm_credential_name": "account-a", + } + ) + + assert boundary == ("https://credential.example.com", "credential-key-a") + + +def test_boundary_fallback_matches_deployments_with_same_named_credential_values(): + from litellm.router_utils.pre_call_checks.encrypted_content_affinity_check import ( + EncryptedContentAffinityCheck, + ) + + with ( + patch.object( # test-quality-ok: credential registry is the direct dependency under test + litellm, + "credential_list", + [ + CredentialItem( + credential_name="account-a", + credential_values={ + "api_base": "https://account-a.example.com", + "api_key": "credential-key-a", + }, + credential_info={}, + ), + CredentialItem( + credential_name="account-a-peer", + credential_values={ + "api_base": "https://account-a.example.com", + "api_key": "credential-key-a", + }, + credential_info={}, + ), + CredentialItem( + credential_name="account-b", + credential_values={ + "api_base": "https://account-b.example.com", + "api_key": "credential-key-b", + }, + credential_info={}, + ), + ], + ) + ): + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-5.3-codex", + "litellm_params": { + "model": "azure/gpt-5.3-codex", + "litellm_credential_name": "account-a", + }, + "model_info": {"id": "origin"}, + } + ], + num_retries=0, + ) + check = EncryptedContentAffinityCheck(router=router) + healthy_deployments = [ + { + "model_info": {"id": "peer-same-boundary"}, + "litellm_params": { + "model": "azure/gpt-5.4", + "litellm_credential_name": "account-a-peer", + }, + }, + { + "model_info": {"id": "peer-different-boundary"}, + "litellm_params": { + "model": "azure/gpt-5.4", + "litellm_credential_name": "account-b", + }, + }, + ] + + matches, originating = check._find_deployments_on_same_encryption_boundary( + healthy_deployments=healthy_deployments, + model_id="origin", + ) + + assert originating is not None + assert [deployment["model_info"]["id"] for deployment in matches] == ["peer-same-boundary"] + + def test_boundary_key_rejects_non_dict_like_inputs(): """ Inputs that don't expose ``.get()`` (None, lists, strings, ints) -> None. diff --git a/tests/test_litellm/router_utils/test_cooldown_handlers.py b/tests/test_litellm/router_utils/test_cooldown_handlers.py index 7ee0ed3701b..6fed4be5909 100644 --- a/tests/test_litellm/router_utils/test_cooldown_handlers.py +++ b/tests/test_litellm/router_utils/test_cooldown_handlers.py @@ -437,3 +437,67 @@ class TestRoutingGroupCooldownAlternatives: ) is False ) + + +class TestTeamModelCooldownAlternatives: + def _router(self, team_deployments: int, blocked_ids: frozenset[str] = frozenset()) -> litellm.Router: + return litellm.Router( + model_list=[ + { + "model_name": f"model_name_team-1_{i}", + "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "sk-test"}, + "model_info": { + "id": f"team-deploy-{i}", + "team_id": "team-1", + "team_public_model_name": "team-gpt-4o-mini", + "blocked": f"team-deploy-{i}" in blocked_ids, + }, + } + for i in range(team_deployments) + ] + ) + + def test_429_on_team_deployment_with_sibling_cools_down(self): + from litellm.router_utils.cooldown_handlers import _should_cooldown_deployment + + router = self._router(team_deployments=2) + assert ( + _should_cooldown_deployment( + litellm_router_instance=router, + deployment="team-deploy-0", + exception_status=429, + original_exception=Exception("rate limited"), + requested_model_group="team-gpt-4o-mini", + ) + is True + ) + + def test_429_on_only_team_deployment_keeps_single_deployment_exemption(self): + from litellm.router_utils.cooldown_handlers import _should_cooldown_deployment + + router = self._router(team_deployments=1) + assert ( + _should_cooldown_deployment( + litellm_router_instance=router, + deployment="team-deploy-0", + exception_status=429, + original_exception=Exception("rate limited"), + requested_model_group="team-gpt-4o-mini", + ) + is False + ) + + def test_429_with_only_a_blocked_sibling_keeps_single_deployment_exemption(self): + from litellm.router_utils.cooldown_handlers import _should_cooldown_deployment + + router = self._router(team_deployments=2, blocked_ids=frozenset({"team-deploy-1"})) + assert ( + _should_cooldown_deployment( + litellm_router_instance=router, + deployment="team-deploy-0", + exception_status=429, + original_exception=Exception("rate limited"), + requested_model_group="team-gpt-4o-mini", + ) + is False + ) diff --git a/tests/test_litellm/rust_bridge/test_lifecycle.py b/tests/test_litellm/rust_bridge/test_lifecycle.py new file mode 100644 index 00000000000..d73385621d5 --- /dev/null +++ b/tests/test_litellm/rust_bridge/test_lifecycle.py @@ -0,0 +1,33 @@ +from typing import Final + +import pytest + +import litellm +from litellm.rust_bridge.lifecycle import check_limits + + +@pytest.mark.parametrize("metadata_key", ["metadata", "litellm_metadata"]) +@pytest.mark.parametrize( + "cap, request_retry_count, refused", + [(5, 5, True), (5, 4, False), (0, 0, False), (0, 1, True)], + ids=[ + "cap-above-four-reached", + "cap-above-four-not-reached", + "first-attempt-passes-cap-of-zero", + "cap-of-zero-refuses-first-retry", + ], +) +def test_check_limits_reads_request_retry_count( + monkeypatch: pytest.MonkeyPatch, metadata_key: str, cap: int, request_retry_count: int, refused: bool +) -> None: + monkeypatch.setattr(litellm, "num_retries_per_request", cap) + monkeypatch.setattr(litellm, "max_budget", None) + kwargs: Final = { + "model": "mistral/mistral-ocr-latest", + metadata_key: {"request_retry_count": request_retry_count}, + } + if refused: + with pytest.raises(RuntimeError, match="Max retries per request hit!"): + check_limits(kwargs) + else: + check_limits(kwargs) diff --git a/tests/test_litellm/test_assert_ci_coverage.py b/tests/test_litellm/test_assert_ci_coverage.py index d948c1a4155..69db2411742 100644 --- a/tests/test_litellm/test_assert_ci_coverage.py +++ b/tests/test_litellm/test_assert_ci_coverage.py @@ -9,8 +9,12 @@ the question neither covers: whether the job that globs a file then deselects it """ import importlib.util +import json import sys from pathlib import Path +from typing import Final + +import yaml _REPO_ROOT = Path(__file__).resolve().parents[2] _MODULE_PATH = _REPO_ROOT / ".github" / "scripts" / "assert_ci_coverage.py" @@ -20,6 +24,56 @@ sys.modules[_spec.name] = coverage # @dataclass(slots=True) rebuilds via sys.mo _spec.loader.exec_module(coverage) +def test_integration_manifest_requires_exclusive_scheduled_circleci_owner(tmp_path: Path) -> None: + test_path: Final = "tests/integration/management/test_contract.py" + test_file: Final = tmp_path / test_path + test_file.parent.mkdir(parents=True) + test_file.write_text("def test_contract(): pass\n") + (tmp_path / "tests/integration/contracts.json").write_text( + json.dumps({"groups": {"management": ["management"]}, "tests": {f"{test_path}::test_contract": ["mgmt.test"]}}) + ) + paths, findings = coverage._integration_ownership(tmp_path) + assert not paths + assert [finding.detail for finding in findings] == ["dedicated CircleCI runner is missing"] + circle: Final = tmp_path / ".circleci/config.yml" + circle.parent.mkdir() + circle.write_text( + yaml.safe_dump( + { + "jobs": { + "integration_contracts": { + "steps": [{"run": {"command": "bash .circleci/scripts/run_integration.sh management"}}] + } + }, + "workflows": {"integration": {"jobs": [{"integration_contracts": {"suite": "management"}}]}}, + } + ) + ) + paths, findings = coverage._integration_ownership(tmp_path) + assert paths == frozenset({test_path}) + assert findings == () + configured: Final = yaml.safe_load(circle.read_text()) + configured["workflows"]["integration"]["jobs"] = [ + {"integration_contracts": {"matrix": {"parameters": {"suite": ["providers"]}}}} + ] + circle.write_text(yaml.safe_dump(configured)) + _, findings = coverage._integration_ownership(tmp_path) + assert [(finding.subject, finding.detail) for finding in findings] == [ + ("management", "canonical integration group is not scheduled by CircleCI") + ] + configured["workflows"]["integration"]["jobs"][0]["integration_contracts"]["matrix"]["parameters"]["suite"] = [ + "management" + ] + circle.write_text(yaml.safe_dump(configured)) + workflow: Final = tmp_path / ".github/workflows/test.yml" + workflow.parent.mkdir(parents=True) + workflow.write_text(yaml.safe_dump({"jobs": {"tests": {"steps": [{"run": "pytest tests/integration"}]}}})) + _, findings = coverage._integration_ownership(tmp_path) + assert [(finding.subject, finding.detail) for finding in findings] == [ + (test_path, "integration contract is also selected by GitHub Actions") + ] + + def test_an_ancestor_directory_covers_a_file_but_does_not_name_it(): # The whole point of the split: `tests/x` answers "does it run?" but not # "which shard owns it?" — accepting it for the latter is how a new child diff --git a/tests/test_litellm/test_auto_update_price_and_context_window_file.py b/tests/test_litellm/test_auto_update_price_and_context_window_file.py new file mode 100644 index 00000000000..435747e9a09 --- /dev/null +++ b/tests/test_litellm/test_auto_update_price_and_context_window_file.py @@ -0,0 +1,222 @@ +"""Unit tests for the Friendli transform in +`.github/scripts/auto_update_price_and_context_window_file.py`.""" + +from __future__ import annotations + +import importlib.util +import sys +from pathlib import Path + +import pytest + +SCRIPT_PATH = ( + Path(__file__).resolve().parents[2] + / ".github" + / "scripts" + / "auto_update_price_and_context_window_file.py" +) + + +@pytest.fixture(scope="module") +def sync_module(): + spec = importlib.util.spec_from_file_location( + "auto_update_price_and_context_window_file", SCRIPT_PATH + ) + assert spec and spec.loader, f"Could not load spec for {SCRIPT_PATH}" + module = importlib.util.module_from_spec(spec) + sys.modules["auto_update_price_and_context_window_file"] = module + spec.loader.exec_module(module) + return module + + +def _reasoning_model(**overrides: object) -> dict: + model = { + "id": "zai-org/GLM-Test", + "base_model": "zhipuai/glm-test", + "context_length": 1048576, + "max_completion_tokens": 131072, + "pricing": {"input": "0.00000015", "output": "0.0000005", "input_cache_read": "0.00000003"}, + "reasoning": True, + "reasoning_options": [{"type": "effort", "values": ["max", "high", "low"]}], + "functionality": { + "tool_call": True, + "parallel_tool_call": True, + "structured_output": True, + "system_messages": True, + "tool_choice": True, + }, + "input_modalities": ["text", "image", "video"], + "mode": "chat", + } + model.update(overrides) + return model + + +def test_transform_emits_declared_effort_levels_in_canonical_order(sync_module): + entry = sync_module.transform_friendli_data([_reasoning_model()], {})[ + "friendliai/zai-org/GLM-Test" + ] + assert entry["supports_reasoning"] is True + assert entry["reasoning_effort_levels"] == ["low", "high", "max"] + assert not any(k.endswith("_reasoning_effort") for k in entry) + + +def test_transform_reasoning_model_without_effort_options_declares_empty_levels(sync_module): + model = _reasoning_model(reasoning_options=[{"type": "budget_tokens", "values": []}]) + entry = sync_module.transform_friendli_data([model], {})["friendliai/zai-org/GLM-Test"] + assert entry["reasoning_effort_levels"] == [] + + +def test_transform_non_reasoning_model_declares_no_levels(sync_module): + model = _reasoning_model(reasoning=False, reasoning_options=[]) + entry = sync_module.transform_friendli_data([model], {})["friendliai/zai-org/GLM-Test"] + assert entry["supports_reasoning"] is False + assert "reasoning_effort_levels" not in entry + + +def test_transform_max_tokens_mirrors_output_cap_not_context(sync_module): + entry = sync_module.transform_friendli_data([_reasoning_model()], {})[ + "friendliai/zai-org/GLM-Test" + ] + assert entry["max_input_tokens"] == 1048576 + assert entry["max_output_tokens"] == 131072 + assert entry["max_tokens"] == entry["max_output_tokens"] + + +def test_transform_prompt_caching_follows_cache_pricing(sync_module): + cached = sync_module.transform_friendli_data([_reasoning_model()], {})[ + "friendliai/zai-org/GLM-Test" + ] + assert cached["supports_prompt_caching"] is True + assert cached["cache_read_input_token_cost"] == 3e-08 + + uncached_model = _reasoning_model(pricing={"input": "0.00000014", "output": "0.0000004"}) + uncached = sync_module.transform_friendli_data([uncached_model], {})[ + "friendliai/zai-org/GLM-Test" + ] + assert uncached["supports_prompt_caching"] is False + assert "cache_read_input_token_cost" not in uncached + + +def test_transform_modalities_set_vision_image_and_video_flags(sync_module): + entry = sync_module.transform_friendli_data([_reasoning_model()], {})[ + "friendliai/zai-org/GLM-Test" + ] + assert entry["supports_vision"] is True + assert entry["supports_image_input"] is True + assert entry["supports_video_input"] is True + + text_only = _reasoning_model(input_modalities=["text"]) + entry_text = sync_module.transform_friendli_data([text_only], {})[ + "friendliai/zai-org/GLM-Test" + ] + assert entry_text["supports_vision"] is False + assert entry_text["supports_image_input"] is False + assert entry_text["supports_video_input"] is False + + +def test_transform_skips_rows_without_valid_token_prices_so_priced_local_entries_survive(sync_module): + local = { + "friendliai/zai-org/GLM-Test": { + "litellm_provider": "friendliai", + "input_cost_per_token": 1.5e-07, + "output_cost_per_token": 5e-07, + } + } + unpriced_rows = [ + _reasoning_model(pricing={}), + _reasoning_model(pricing=None), + _reasoning_model(pricing={"input": "0.00000015"}), + _reasoning_model(pricing={"output": "0.0000005"}), + _reasoning_model(pricing={"input": "not-a-number", "output": "0.0000005"}), + _reasoning_model(pricing={"input": "-0.00000015", "output": "0.0000005"}), + _reasoning_model(pricing={"input": "inf", "output": "0.0000005"}), + _reasoning_model(pricing={"input": "nan", "output": "0.0000005"}), + ] + remote = sync_module.transform_friendli_data(unpriced_rows, local) + assert remote == {} + sync_module.sync_local_data_with_remote(local, remote, replace_keys=frozenset(remote)) + assert local["friendliai/zai-org/GLM-Test"]["input_cost_per_token"] == 1.5e-07 + assert local["friendliai/zai-org/GLM-Test"]["output_cost_per_token"] == 5e-07 + + +def test_transform_keeps_zero_priced_rows(sync_module): + free_model = _reasoning_model(pricing={"input": "0", "output": "0"}) + entry = sync_module.transform_friendli_data([free_model], {})["friendliai/zai-org/GLM-Test"] + assert entry["input_cost_per_token"] == 0.0 + assert entry["output_cost_per_token"] == 0.0 + + +def test_transforms_survive_failed_fetch(sync_module): + assert sync_module.transform_friendli_data(None, {}) == {} + assert sync_module.transform_friendli_data([], {}) == {} + assert sync_module.transform_openrouter_data(None) == {} + assert sync_module.transform_vercel_ai_gateway_data(None) == {} + + +def test_vercel_transform_skips_rows_without_token_pricing_or_limits(sync_module): + rows = [ + { + "id": "wan-video", + "pricing": {"video_duration_pricing": [{"resolution": "720p", "cost_per_second": "0.1"}]}, + }, + { + "id": "qwen3-embedding", + "context_window": 32768, + "max_tokens": 32768, + "pricing": {"input": "0.00000001"}, + }, + { + "id": "no-limits-chat", + "pricing": {"input": "0.000001", "output": "0.000002"}, + }, + { + "id": "good-chat", + "context_window": 128000, + "max_tokens": 8192, + "pricing": {"input": "0.000001", "output": "0.000002"}, + }, + ] + transformed = sync_module.transform_vercel_ai_gateway_data(rows) + assert list(transformed) == ["vercel_ai_gateway/good-chat"] + assert transformed["vercel_ai_gateway/good-chat"]["input_cost_per_token"] == 1e-06 + assert transformed["vercel_ai_gateway/good-chat"]["output_cost_per_token"] == 2e-06 + + +def test_sync_replaces_friendli_entries_so_dropped_cache_pricing_does_not_survive(sync_module): + local = { + "friendliai/zai-org/GLM-Test": { + "litellm_provider": "friendliai", + "cache_read_input_token_cost": 3e-08, + "supports_prompt_caching": True, + } + } + uncached_model = _reasoning_model(pricing={"input": "0.00000014", "output": "0.0000004"}) + remote = sync_module.transform_friendli_data([uncached_model], local) + sync_module.sync_local_data_with_remote(local, remote, replace_keys=frozenset(remote)) + synced = local["friendliai/zai-org/GLM-Test"] + assert "cache_read_input_token_cost" not in synced + assert synced["supports_prompt_caching"] is False + + +def test_sync_still_merges_entries_outside_replace_keys(sync_module): + local = {"openrouter/some-model": {"input_cost_per_token": 1e-06, "supports_vision": True}} + remote = {"openrouter/some-model": {"input_cost_per_token": 2e-06}} + sync_module.sync_local_data_with_remote(local, remote) + assert local["openrouter/some-model"] == {"input_cost_per_token": 2e-06, "supports_vision": True} + + +def test_transform_inherits_allowlisted_keys_from_base_model_entry(sync_module): + local = { + "zhipuai/glm-test": { + "supports_pdf_input": True, + "supports_assistant_prefill": True, + "input_cost_per_token": 9e-06, + } + } + entry = sync_module.transform_friendli_data([_reasoning_model()], local)[ + "friendliai/zai-org/GLM-Test" + ] + assert entry["supports_pdf_input"] is True + assert entry["supports_assistant_prefill"] is True + assert entry["input_cost_per_token"] == 1.5e-07 diff --git a/tests/test_litellm/test_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py index f610821e06a..8c3436d3108 100644 --- a/tests/test_litellm/test_cost_calculator.py +++ b/tests/test_litellm/test_cost_calculator.py @@ -17,6 +17,9 @@ from litellm.cost_calculator import ( handle_realtime_stream_cost_calculation, response_cost_calculator, ) +from litellm.litellm_core_utils.litellm_logging import Logging +from litellm.llms.base_llm.ocr.transformation import OCRPage, OCRResponse, OCRUsageInfo +from litellm.types.llms.base import CachedTokensDetails from litellm.types.llms.openai import OpenAIRealtimeStreamList from litellm.types.rerank import RerankResponse from litellm.types.utils import ( @@ -3906,6 +3909,57 @@ def _batch_cache_usage() -> Usage: ) +def test_batch_cost_calculator_prices_multimodal_tokens_at_modality_rates(): + from litellm.cost_calculator import batch_cost_calculator + + model_info: ModelInfo = { + "input_cost_per_token_batches": 1e-7, + "input_cost_per_audio_token_batches": 3.25e-6, + "input_cost_per_image_token_batches": 2.25e-7, + "input_cost_per_video_token_batches": 6e-6, + } + usage = Usage( + prompt_tokens=100, + completion_tokens=0, + total_tokens=100, + prompt_tokens_details=PromptTokensDetailsWrapper( + audio_tokens=64, + image_tokens=10, + video_tokens=6, + ), + ) + + prompt_cost, _ = batch_cost_calculator( + usage=usage, + model="gemini-embedding-2", + custom_llm_provider="vertex_ai", + model_info=model_info, + ) + + assert prompt_cost == pytest.approx(20 * 1e-7 + 64 * 3.25e-6 + 10 * 2.25e-7 + 6 * 6e-6) + + +def test_batch_cost_calculator_falls_back_to_text_batch_rate_for_modalities(): + from litellm.cost_calculator import batch_cost_calculator + + model_info: ModelInfo = {"input_cost_per_token_batches": 1e-7} + usage = Usage( + prompt_tokens=100, + completion_tokens=0, + total_tokens=100, + prompt_tokens_details=PromptTokensDetailsWrapper(audio_tokens=64), + ) + + prompt_cost, _ = batch_cost_calculator( + usage=usage, + model="gemini-embedding-2", + custom_llm_provider="vertex_ai", + model_info=model_info, + ) + + assert prompt_cost == pytest.approx(100 * 1e-7) + + def test_batch_cost_calculator_prices_cache_creation_tokens_at_cache_write_rate(): """ LIT-4008 regression: anthropic batch usage is dominated by cache tokens. @@ -4311,6 +4365,59 @@ def test_select_model_name_applies_region_to_private_provider_response_model(_lo assert selected == "bedrock/us-east-1/anthropic.claude-v2:1" +def test_completion_cost_region_name_prices_mantle_on_the_regional_row(_local_model_cost_map): + """completion_cost(region_name=...) must price a Bedrock Mantle call from the + bedrock_mantle// row when one exists, for the bare and the provider-prefixed + model alike, and keep the flat row for regions without their own row.""" + + response = litellm.ModelResponse( + id="x", + choices=[{"index": 0, "message": {"role": "assistant", "content": "hi"}, "finish_reason": "stop"}], + model="xai.grok-4.3", + usage={"prompt_tokens": 38, "completion_tokens": 20, "total_tokens": 58}, + ) + gov = litellm.model_cost["bedrock_mantle/us-gov-west-1/xai.grok-4.3"] + flat = litellm.model_cost["bedrock_mantle/xai.grok-4.3"] + expected_gov = 38 * gov["input_cost_per_token"] + 20 * gov["output_cost_per_token"] + expected_flat = 38 * flat["input_cost_per_token"] + 20 * flat["output_cost_per_token"] + assert expected_gov != expected_flat + + for model in ("xai.grok-4.3", "bedrock_mantle/xai.grok-4.3"): + assert litellm.completion_cost( + completion_response=response, + model=model, + custom_llm_provider="bedrock_mantle", + region_name="us-gov-west-1", + ) == pytest.approx(expected_gov) + assert litellm.completion_cost( + completion_response=response, + model=model, + custom_llm_provider="bedrock_mantle", + region_name="eu-west-1", + ) == pytest.approx(expected_flat) + assert litellm.completion_cost( + completion_response=response, model="xai.grok-4.3", custom_llm_provider="bedrock_mantle" + ) == pytest.approx(expected_flat) + + +def test_cost_per_token_region_name_applies_to_provider_prefixed_model(_local_model_cost_map): + """A provider-prefixed model must still find its bedrock_mantle// row instead of + composing the region key with the provider segment twice.""" + + prompt_cost, completion_cost = litellm.cost_per_token( + model="bedrock_mantle/xai.grok-4.3", + prompt_tokens=38, + completion_tokens=20, + custom_llm_provider="bedrock_mantle", + region_name="us-gov-west-1", + ) + gov = litellm.model_cost["bedrock_mantle/us-gov-west-1/xai.grok-4.3"] + + assert prompt_cost + completion_cost == pytest.approx( + 38 * gov["input_cost_per_token"] + 20 * gov["output_cost_per_token"] + ) + + def test_select_model_name_keeps_base_model_free_of_region(_local_model_cost_map): """An explicit base_model keeps pricing on that model's own key even when the request carries a region with different regional rates, so the private provider model never widens region pricing.""" @@ -4327,6 +4434,29 @@ def test_select_model_name_keeps_base_model_free_of_region(_local_model_cost_map assert selected == "bedrock/moonshotai.kimi-k2.5" +def test_completion_cost_base_model_ignores_regional_row(_local_model_cost_map): + """A deployment with base_model set is priced from that model's own row even when the response + carries a region whose regional row charges different rates.""" + + response = litellm.ModelResponse( + id="x", + choices=[{"index": 0, "message": {"role": "assistant", "content": "hi"}, "finish_reason": "stop"}], + model="my-bedrock-deployment", + usage={"prompt_tokens": 1000, "completion_tokens": 0, "total_tokens": 1000}, + ) + response._hidden_params = {"custom_llm_provider": "bedrock", "region_name": "eu-central-1"} + flat = litellm.model_cost["anthropic.claude-instant-v1"] + regional = litellm.model_cost["bedrock/eu-central-1/anthropic.claude-instant-v1"] + assert flat["input_cost_per_token"] != regional["input_cost_per_token"] + + assert litellm.completion_cost( + completion_response=response, + model="my-bedrock-deployment", + custom_llm_provider="bedrock", + base_model="anthropic.claude-instant-v1", + ) == pytest.approx(1000 * flat["input_cost_per_token"]) + + def test_completion_cost_nonzero_for_slash_alias_model_name(_local_model_cost_map): """End-to-end cost through a "/"-containing alias must price above zero (#38069).""" @@ -4768,3 +4898,331 @@ def test_collect_and_combine_realtime_usage_stores_partitioned_text_tokens() -> assert combined.completion_tokens_details.reasoning_tokens == 95 assert combined.completion_tokens_details.text_tokens == 38 assert combined.completion_tokens_details.audio_tokens == 0 + + +def test_realtime_combine_sums_nested_cached_tokens_details(): + results: OpenAIRealtimeStreamList = [ + { + "type": "response.done", + "response": { + "usage": { + "input_tokens": 283, + "output_tokens": 0, + "total_tokens": 283, + "input_token_details": { + "text_tokens": 116, + "audio_tokens": 167, + "cached_tokens": 192, + "cached_tokens_details": {"text_tokens": 64, "audio_tokens": 128}, + }, + } + }, + }, + { + "type": "response.done", + "response": { + "usage": { + "input_tokens": 150, + "output_tokens": 0, + "total_tokens": 150, + "input_token_details": { + "text_tokens": 50, + "audio_tokens": 100, + "cached_tokens": 100, + "cached_tokens_details": {"audio_tokens": 100}, + }, + } + }, + }, + ] + + combined = RealtimeAPITokenUsageProcessor.collect_and_combine_usage_from_realtime_stream_results( + results=results, + ) + + assert combined.prompt_tokens_details is not None + assert combined.prompt_tokens_details.cached_tokens == 292 + assert combined.prompt_tokens_details.cached_tokens_details is not None + assert combined.prompt_tokens_details.cached_tokens_details.audio_tokens == 228 + assert combined.prompt_tokens_details.cached_tokens_details.text_tokens == 64 + assert combined.prompt_tokens_details.cached_tokens_details.image_tokens is None + + +@pytest.mark.parametrize("details_first", [True, False]) +def test_realtime_combine_keeps_cached_split_when_only_one_usage_has_details(details_first: bool): + with_details: Final = { + "type": "response.done", + "response": { + "usage": { + "input_tokens": 283, + "output_tokens": 0, + "total_tokens": 283, + "input_token_details": { + "text_tokens": 116, + "audio_tokens": 167, + "cached_tokens": 192, + "cached_tokens_details": {"text_tokens": 64, "audio_tokens": 128}, + }, + } + }, + } + without_details: Final = { + "type": "response.done", + "response": { + "usage": { + "input_tokens": 150, + "output_tokens": 0, + "total_tokens": 150, + "input_token_details": {"text_tokens": 50, "audio_tokens": 100, "cached_tokens": 100}, + } + }, + } + results: OpenAIRealtimeStreamList = ( + [with_details, without_details] if details_first else [without_details, with_details] + ) + + combined = RealtimeAPITokenUsageProcessor.collect_and_combine_usage_from_realtime_stream_results( + results=results, + ) + + assert combined.prompt_tokens_details is not None + assert combined.prompt_tokens_details.cached_tokens == 292 + assert combined.prompt_tokens_details.cached_tokens_details == CachedTokensDetails(text_tokens=64, audio_tokens=128) + + +def test_usage_without_cached_tokens_details_omits_key(): + usage = Usage( + prompt_tokens=10, + completion_tokens=5, + total_tokens=15, + prompt_tokens_details=PromptTokensDetailsWrapper(text_tokens=10), + ) + + dumped = usage.prompt_tokens_details.model_dump() + assert "cached_tokens_details" not in dumped + assert "cached_tokens_details" not in usage.prompt_tokens_details.model_dump_json() + + +UNMAPPED_OCR_MODEL: Final = "azure_ai/some-unmapped-ocr-model-for-testing" +MAPPED_OCR_MODEL: Final = "mistral/mistral-ocr-4-0" + + +def _ocr_response(model: str, pages_processed: int, credits: float | None = None) -> OCRResponse: + return OCRResponse( + pages=[OCRPage(index=index, markdown=f"page {index}") for index in range(pages_processed)], + model=model, + usage_info=OCRUsageInfo(pages_processed=pages_processed, credits=credits), + ) + + +def _ocr_logging_obj(litellm_params: dict[str, object]) -> Logging: + logging_obj: Final = Logging( + model=UNMAPPED_OCR_MODEL, + messages=[], + stream=False, + call_type="ocr", + start_time=None, + litellm_call_id="test-ocr-custom-pricing", + function_id="1234", + ) + logging_obj.update_environment_variables(litellm_params=litellm_params, optional_params={}) + return logging_obj + + +@pytest.mark.parametrize("pages_processed", [1, 3, 10]) +def test_ocr_cost_uses_deployment_per_page_pricing_for_unmapped_model(pages_processed: int): + from litellm.cost_calculator import ocr_cost + + assert UNMAPPED_OCR_MODEL not in litellm.model_cost + cost, _ = ocr_cost( + model=UNMAPPED_OCR_MODEL, + custom_llm_provider="azure_ai", + response=_ocr_response(UNMAPPED_OCR_MODEL, pages_processed=pages_processed), + model_info={"ocr_cost_per_page": 0.004}, + ) + assert cost == pytest.approx(0.004 * pages_processed) + + +def test_ocr_cost_uses_deployment_annotation_only_pricing_for_unmapped_model(): + from litellm.cost_calculator import ocr_cost + + assert UNMAPPED_OCR_MODEL not in litellm.model_cost + response: Final = OCRResponse( + pages=[OCRPage(index=index, markdown=f"page {index}") for index in range(3)], + model=UNMAPPED_OCR_MODEL, + usage_info=OCRUsageInfo(pages_processed=3, pages_processed_annotation=2), + ) + cost, _ = ocr_cost( + model=UNMAPPED_OCR_MODEL, + custom_llm_provider="azure_ai", + response=response, + model_info={"annotation_cost_per_page": 0.01}, + ) + assert cost == pytest.approx(0.01 * 2) + + +def test_ocr_cost_annotation_only_override_keeps_mapped_per_page_rate(): + from litellm.cost_calculator import ocr_cost + + map_price: Final = litellm.model_cost[MAPPED_OCR_MODEL]["ocr_cost_per_page"] + response: Final = OCRResponse( + pages=[OCRPage(index=index, markdown=f"page {index}") for index in range(3)], + model=MAPPED_OCR_MODEL, + usage_info=OCRUsageInfo(pages_processed=3, pages_processed_annotation=2), + ) + cost, _ = ocr_cost( + model=MAPPED_OCR_MODEL, + custom_llm_provider="mistral", + response=response, + model_info={"annotation_cost_per_page": 0.01}, + ) + assert cost == pytest.approx(map_price * 3 + 0.01 * 2) + + +def test_ocr_cost_uses_deployment_per_credit_pricing_for_unmapped_model(): + from litellm.cost_calculator import ocr_cost + + cost, _ = ocr_cost( + model=UNMAPPED_OCR_MODEL, + custom_llm_provider="azure_ai", + response=_ocr_response(UNMAPPED_OCR_MODEL, pages_processed=2, credits=4), + model_info={"ocr_cost_per_credit": 0.25}, + ) + assert cost == pytest.approx(0.25 * 4) + + +def test_ocr_cost_unmapped_model_without_deployment_pricing_bills_zero(): + from litellm.cost_calculator import ocr_cost + + cost, _ = ocr_cost( + model=UNMAPPED_OCR_MODEL, + custom_llm_provider="azure_ai", + response=_ocr_response(UNMAPPED_OCR_MODEL, pages_processed=5), + model_info={"id": "some-deployment-id"}, + ) + assert cost == 0.0 + + +@pytest.mark.usefixtures("_local_model_cost_map") +def test_ocr_cost_deployment_pricing_overrides_cost_map_for_mapped_model(): + from litellm.cost_calculator import ocr_cost + + map_price: Final = litellm.get_model_info(MAPPED_OCR_MODEL)["ocr_cost_per_page"] + assert map_price is not None + override_price: Final = map_price * 10 + + cost, _ = ocr_cost( + model=MAPPED_OCR_MODEL, + custom_llm_provider="mistral", + response=_ocr_response(MAPPED_OCR_MODEL, pages_processed=2), + model_info={"ocr_cost_per_page": override_price}, + ) + assert cost == pytest.approx(override_price * 2) + + +@pytest.mark.usefixtures("_local_model_cost_map") +def test_ocr_cost_falls_through_to_cost_map_when_deployment_has_no_ocr_pricing(): + from litellm.cost_calculator import ocr_cost + + map_price: Final = litellm.get_model_info(MAPPED_OCR_MODEL)["ocr_cost_per_page"] + assert map_price is not None + + cost, _ = ocr_cost( + model=MAPPED_OCR_MODEL, + custom_llm_provider="mistral", + response=_ocr_response(MAPPED_OCR_MODEL, pages_processed=2), + model_info={"id": "some-deployment-id"}, + ) + assert cost == pytest.approx(map_price * 2) + + +@pytest.mark.usefixtures("_local_model_cost_map") +def test_ocr_cost_ignores_deployment_credit_pricing_when_response_reports_no_credits(): + from litellm.cost_calculator import ocr_cost + + map_price: Final = litellm.get_model_info(MAPPED_OCR_MODEL)["ocr_cost_per_page"] + assert map_price is not None + + cost, _ = ocr_cost( + model=MAPPED_OCR_MODEL, + custom_llm_provider="mistral", + response=_ocr_response(MAPPED_OCR_MODEL, pages_processed=2), + model_info={"ocr_cost_per_credit": 0.5}, + ) + assert cost == pytest.approx(map_price * 2) + + +@pytest.mark.parametrize("metadata_key", ["metadata", "litellm_metadata"]) +def test_completion_cost_ocr_reads_deployment_pricing_from_logging_metadata(metadata_key: str): + logging_obj = _ocr_logging_obj({metadata_key: {"model_info": {"ocr_cost_per_page": 0.004}}}) + + cost = completion_cost( + completion_response=_ocr_response(UNMAPPED_OCR_MODEL, pages_processed=3), + model=UNMAPPED_OCR_MODEL, + custom_llm_provider="azure_ai", + call_type="ocr", + custom_pricing=True, + litellm_logging_obj=logging_obj, + ) + assert cost == pytest.approx(0.004 * 3) + + +def test_completion_cost_ocr_prefers_pricing_registered_under_router_model_id(monkeypatch: pytest.MonkeyPatch): + deployment_id: Final = "ocr-deployment-priced-through-litellm-params" + monkeypatch.setitem( + litellm.model_cost, deployment_id, {"mode": "ocr", "litellm_provider": "azure_ai", "ocr_cost_per_page": 0.05} + ) + logging_obj = _ocr_logging_obj({"metadata": {"model_info": {"mode": "ocr"}}}) + + cost = completion_cost( + completion_response=_ocr_response(UNMAPPED_OCR_MODEL, pages_processed=3), + model=UNMAPPED_OCR_MODEL, + custom_llm_provider="azure_ai", + call_type="ocr", + custom_pricing=True, + router_model_id=deployment_id, + litellm_logging_obj=logging_obj, + ) + assert cost == pytest.approx(0.05 * 3) + + +def test_completion_cost_ocr_bills_request_level_pricing_for_direct_sdk_call(): + logging_obj = _ocr_logging_obj({"ocr_cost_per_page": 0.05}) + + cost = completion_cost( + completion_response=_ocr_response(UNMAPPED_OCR_MODEL, pages_processed=3), + model=UNMAPPED_OCR_MODEL, + custom_llm_provider="azure_ai", + call_type="ocr", + custom_pricing=True, + litellm_logging_obj=logging_obj, + ) + assert cost == pytest.approx(0.05 * 3) + + +def test_completion_cost_ocr_request_level_pricing_fills_in_deployment_model_info_without_ocr_pricing(): + logging_obj = _ocr_logging_obj({"ocr_cost_per_page": 0.05, "metadata": {"model_info": {"mode": "ocr"}}}) + + cost = completion_cost( + completion_response=_ocr_response(UNMAPPED_OCR_MODEL, pages_processed=3), + model=UNMAPPED_OCR_MODEL, + custom_llm_provider="azure_ai", + call_type="ocr", + custom_pricing=True, + litellm_logging_obj=logging_obj, + ) + assert cost == pytest.approx(0.05 * 3) + + +def test_completion_cost_ocr_ignores_deployment_pricing_without_custom_pricing_flag(): + logging_obj = _ocr_logging_obj({"metadata": {"model_info": {"ocr_cost_per_page": 0.004}}}) + + cost = completion_cost( + completion_response=_ocr_response(UNMAPPED_OCR_MODEL, pages_processed=3), + model=UNMAPPED_OCR_MODEL, + custom_llm_provider="azure_ai", + call_type="ocr", + custom_pricing=False, + litellm_logging_obj=logging_obj, + ) + assert cost == 0.0 diff --git a/tests/test_litellm/test_logging.py b/tests/test_litellm/test_logging.py index bf3757e6886..57c39280a9f 100644 --- a/tests/test_litellm/test_logging.py +++ b/tests/test_litellm/test_logging.py @@ -17,6 +17,7 @@ from litellm._logging import ( _MAX_SCRUBBED_ACCESS_ARG, _PLAIN_LOG_FORMAT, ALL_LOGGERS, + AccessLogPathFilter, AccessLogRedactionFilter, CorrelationContextFilter, CorrelationPlainFormatter, @@ -1178,3 +1179,72 @@ def test_access_redaction_survives_the_uvicorn_json_log_config(): lg.handlers[:] = handlers lg.setLevel(level) lg.propagate = True + + +_DISABLED_ACCESS_LOG_PATHS_RAW = " /health/liveliness , ,/metrics/" + + +@pytest.mark.parametrize( + "full_path", + [ + "/health/liveliness", + "/health/liveliness?x=1", + "/health/liveliness?probe=" + "x" * _MAX_SCRUBBED_ACCESS_ARG, + "/metrics/", + "/metrics/?format=prometheus&job=a", + ], +) +def test_uvicorn_access_logger_drops_a_configured_path(monkeypatch, full_path): + monkeypatch.setenv("LITELLM_DISABLE_ACCESS_LOG_PATHS", _DISABLED_ACCESS_LOG_PATHS_RAW) + assert _emit_access_line(full_path) == "" + + +@pytest.mark.parametrize( + "full_path", + ["/v1/chat/completions", "/health", "/health/liveliness/", "/metrics", "/v1/models?health=/health/liveliness"], +) +def test_uvicorn_access_logger_keeps_an_unconfigured_path(monkeypatch, full_path): + monkeypatch.setenv("LITELLM_DISABLE_ACCESS_LOG_PATHS", _DISABLED_ACCESS_LOG_PATHS_RAW) + assert f'"GET {full_path} HTTP/1.1" 200' in _emit_access_line(full_path) + + +@pytest.mark.parametrize("raw", [None, "", " , ,"]) +def test_uvicorn_access_logger_keeps_every_line_when_no_path_is_configured(monkeypatch, raw): + if raw is None: + monkeypatch.delenv("LITELLM_DISABLE_ACCESS_LOG_PATHS", raising=False) + else: + monkeypatch.setenv("LITELLM_DISABLE_ACCESS_LOG_PATHS", raw) + assert '"GET /health/liveliness HTTP/1.1" 200' in _emit_access_line("/health/liveliness") + + +def test_access_log_path_filter_survives_the_uvicorn_json_log_config(monkeypatch): + import logging.config + + monkeypatch.setenv("LITELLM_DISABLE_ACCESS_LOG_PATHS", _DISABLED_ACCESS_LOG_PATHS_RAW) + names = ("uvicorn", "uvicorn.error", "uvicorn.access") + saved = tuple((logging.getLogger(n), logging.getLogger(n).handlers[:], logging.getLogger(n).level) for n in names) + try: + logging.config.dictConfig(_get_uvicorn_json_log_config()) + + assert _emit_access_line("/health/liveliness?x=1") == "" + assert '"GET /v1/models HTTP/1.1" 200' in _emit_access_line("/v1/models") + finally: + for lg, handlers, level in saved: + lg.handlers[:] = handlers + lg.setLevel(level) + lg.propagate = True + + +@pytest.mark.parametrize("args", [None, ("127.0.0.1:1", "GET", 42)]) +def test_access_log_path_filter_keeps_a_record_without_a_string_path_arg(monkeypatch, args): + monkeypatch.setenv("LITELLM_DISABLE_ACCESS_LOG_PATHS", "/health/liveliness") + record = logging.LogRecord( + name="uvicorn.access", + level=logging.INFO, + pathname="", + lineno=0, + msg='127.0.0.1:1 - "GET /health/liveliness HTTP/1.1" 200', + args=args, + exc_info=None, + ) + assert AccessLogPathFilter().filter(record) is True diff --git a/tests/test_litellm/test_main.py b/tests/test_litellm/test_main.py index f71225c6fc5..3dccb2b35bf 100644 --- a/tests/test_litellm/test_main.py +++ b/tests/test_litellm/test_main.py @@ -874,15 +874,25 @@ def test_responses_api_bridge_check_gpt_5_4_tools_with_default_reasoning_routes_ assert model_info.get("mode") == "responses" -@pytest.mark.parametrize("model_name", ["gpt-5.6-sol", "gpt-5.6-luna", "gpt-5.6-terra"]) +@pytest.mark.parametrize( + "model_name, expected_mode", + [ + pytest.param("gpt-5.6-sol", "responses", id="above-boundary-bridges"), + pytest.param("gpt-5.1", None, id="below-boundary-stays-chat"), + ], +) def test_responses_api_bridge_check_gpt_5_6_tools_with_default_reasoning_routes_to_responses( - monkeypatch, model_name + monkeypatch, model_name, expected_mode ): """ - The whole gpt-5.6 family must bridge on function tools alone. The bridge used to - require an explicit reasoning_effort, so a gpt-5.6 call carrying tools and no effort - was rejected with "Function tools with reasoning_effort are not supported for - gpt-5.6-sol in /v1/chat/completions". + gpt-5.6 must bridge on function tools alone. The bridge used to require an explicit + reasoning_effort, so a gpt-5.6 call carrying tools and no effort was rejected with + "Function tools with reasoning_effort are not supported for gpt-5.6-sol in + /v1/chat/completions". + + Paired with a model below the gpt-5.4 boundary, which must still stay on chat. The + gate parses the version and drops any suffix, so the family members bridge + identically and only the boundary distinguishes behaviour. """ import litellm from litellm.main import responses_api_bridge_check @@ -901,7 +911,7 @@ def test_responses_api_bridge_check_gpt_5_6_tools_with_default_reasoning_routes_ ) assert model == model_name - assert model_info.get("mode") == "responses" + assert model_info.get("mode") == expected_mode def test_responses_api_bridge_check_gpt_5_4_tools_with_reasoning_none_stays_chat(): @@ -3311,15 +3321,19 @@ def local_cost_map(monkeypatch): """The prices these tests assert are the checked-in ones. Setting the environment variable alone does not reload the map, so pin the map itself. - ``get_model_info`` is lru_cached, so pinning ``model_cost`` is not enough on its - own: a cached entry warmed against the network-fetched map keeps its old prices - and ``completion_cost`` bills at those while the assertions read the pinned map. - Clear on the way in and out so entries never leak across tests in either direction.""" + Prices are read through two separate lru_caches, so pinning ``model_cost`` is not + enough on its own: an entry warmed against the network-fetched map keeps its old + prices and billing reads those while the assertions read the pinned map. + ``_invalidate_model_cost_lowercase_map`` clears both caches, where + ``get_model_info.cache_clear`` reaches only one. Invalidate on the way in and out + so entries never leak across tests in either direction.""" + from litellm.utils import _invalidate_model_cost_lowercase_map + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url="")) - litellm.get_model_info.cache_clear() + _invalidate_model_cost_lowercase_map() yield - litellm.get_model_info.cache_clear() + _invalidate_model_cost_lowercase_map() def test_a_streamed_response_bills_the_usage_the_provider_reported(local_cost_map): @@ -3781,3 +3795,58 @@ def test_azure_ai_speech_on_a_foundry_host_uses_the_azure_openai_deployment_rout assert route.called assert response.content == b"mp3-bytes" + + +FORWARDED_CLIENT_HEADERS: Final = {"x-forwarded-for": "10.0.0.1", "x-amzn-trace-id": "Root=1-lit7694"} + + +def _chat_completion_json() -> Mapping[str, object]: + return { + "id": "chatcmpl-lit7694", + "object": "chat.completion", + "created": 1, + "model": "gpt-5.4", + "choices": [{"index": 0, "message": {"role": "assistant", "content": "ok"}, "finish_reason": "stop"}], + "usage": {"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2}, + } + + +def _chat_completion_sse() -> bytes: + chunk: Final = { + "id": "chatcmpl-lit7694", + "object": "chat.completion.chunk", + "created": 1, + "model": "gpt-5.4", + "choices": [{"index": 0, "delta": {"role": "assistant", "content": "ok"}, "finish_reason": "stop"}], + } + return f"data: {json.dumps(chunk)}\n\ndata: [DONE]\n\n".encode() + + +@pytest.mark.parametrize("stream", [False, True]) +def test_bridged_responses_with_openai_http_handler_keeps_forwarded_headers_out_of_the_body( + respx_mock: respx.MockRouter, monkeypatch: pytest.MonkeyPatch, stream: bool +): + monkeypatch.setenv("EXPERIMENTAL_OPENAI_BASE_LLM_HTTP_HANDLER", "true") + route: Final = respx_mock.post("https://api.openai.com/v1/chat/completions").mock( + return_value=httpx.Response(200, content=_chat_completion_sse(), headers={"content-type": "text/event-stream"}) + if stream + else httpx.Response(200, json=_chat_completion_json()) + ) + + response: Final = litellm.responses( + model="openai/gpt-5.4", + input="Reply with the single word ok", + stream=stream, + use_chat_completions_api=True, + headers=dict(FORWARDED_CLIENT_HEADERS), + api_key="sk-test", + ) + if stream: + list(response) + + assert route.called + request: Final = route.calls.last.request + body: Final = json.loads(request.content) + assert "extra_headers" not in body + assert body["model"] == "gpt-5.4" + assert {k: request.headers[k] for k in FORWARDED_CLIENT_HEADERS} == FORWARDED_CLIENT_HEADERS diff --git a/tests/test_litellm/test_model_prices_schema.py b/tests/test_litellm/test_model_prices_schema.py index 0b9dbd23097..e562797fbe8 100644 --- a/tests/test_litellm/test_model_prices_schema.py +++ b/tests/test_litellm/test_model_prices_schema.py @@ -221,6 +221,14 @@ def test_chat_latest_declares_the_one_effort_openai_accepts(prices: dict): assert resolve_supported_reasoning_efforts(prices["chat-latest"], deployment_is_mapped=True) == ("medium",) +@pytest.mark.parametrize("key", ["azure/gpt-chat-latest", "azure/chat-latest", "azure/us/gpt-chat-latest"]) +def test_azure_gpt_chat_latest_declares_the_one_effort_azure_accepts(prices: dict, key: str): + """Azure answers every reasoning_effort on a gpt-chat-latest deployment except medium with + "Unsupported value ... Supported values are: 'medium'", the same fixed level OpenAI's chat-latest + carries, so the Foundry product name and the OpenAI API name both declare that one level.""" + assert resolve_supported_reasoning_efforts(prices[key], deployment_is_mapped=True) == ("medium",) + + BEDROCK_OPENAI_GPT_MARKERS: Final = ("openai.gpt-5.4", "openai.gpt-5.5", "openai.gpt-5.6", "openai.gpt-6-astra") BEDROCK_PROVIDERS: Final = frozenset(("bedrock", "bedrock_converse", "bedrock_mantle")) BEDROCK_ROW_PREFIXES: Final = ("bedrock_mantle/", "us.", "global.") diff --git a/tests/test_litellm/test_router.py b/tests/test_litellm/test_router.py index f5e9b2091a0..0485da3eba9 100644 --- a/tests/test_litellm/test_router.py +++ b/tests/test_litellm/test_router.py @@ -896,6 +896,46 @@ def test_arouter_test_team_model(): assert result is not None +def test_team_model_has_alternatives(): + def team_deployment( + deployment_id: str, team_id: str, public_model_name: str, blocked: bool = False + ) -> DeploymentTypedDict: + return { + "model_name": f"model_name_{team_id}_{deployment_id}", + "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "sk-test"}, + "model_info": { + "id": deployment_id, + "team_id": team_id, + "team_public_model_name": public_model_name, + "blocked": blocked, + }, + } + + router = litellm.Router( + model_list=[ + team_deployment("team-a-1", "team-a", "shared-model"), + team_deployment("team-a-2", "team-a", "shared-model"), + team_deployment("team-a-solo", "team-a", "solo-model"), + team_deployment("team-b-1", "team-b", "shared-model"), + team_deployment("team-c-1", "team-c", "paused-sibling-model"), + team_deployment("team-c-paused", "team-c", "paused-sibling-model", blocked=True), + { + "model_name": "plain-model", + "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "sk-test"}, + "model_info": {"id": "plain-1"}, + }, + ], + ) + + assert router.team_model_has_alternatives("team-a-1") is True + assert router.team_model_has_alternatives("team-a-2") is True + assert router.team_model_has_alternatives("team-a-solo") is False + assert router.team_model_has_alternatives("team-b-1") is False + assert router.team_model_has_alternatives("team-c-1") is False + assert router.team_model_has_alternatives("plain-1") is False + assert router.team_model_has_alternatives("missing-deployment") is False + + def test_arouter_ignore_invalid_deployments(): """ Test that router.ignore_invalid_deployments is set to True @@ -3654,6 +3694,111 @@ async def test_aresponses_streaming_iterator_fallback(): assert call_kwargs["disable_fallbacks"] is False +@pytest.mark.asyncio +async def test_aresponses_streaming_content_policy_error_event_routes_to_content_policy_fallback(): + """Regression: a mid-stream content_policy_violation error event never reached + content_policy_fallbacks. The iterator raised a bare APIError the wrapper does not + catch, and even once wrapped, the MidStreamFallbackError envelope was handed to the + fallback dispatch, whose isinstance branch on ContentPolicyViolationError never matched. + The stream below is the customer's shape: a raw OpenAI error event with code + content_policy_violation, transformed by the real OpenAI config, and the router must + call the content_policy_fallbacks target, not the general fallbacks one.""" + from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig + from litellm.responses.streaming_iterator import ResponsesAPIStreamingIterator + + router = litellm.Router( + model_list=[ + {"model_name": "primary", "litellm_params": {"model": "openai/gpt-5.4", "api_key": "k1"}}, + { + "model_name": "content-fallback", + "litellm_params": {"model": "gemini/gemini-2.5-flash", "api_key": "k2"}, + }, + {"model_name": "general-fallback", "litellm_params": {"model": "openai/gpt-5-mini", "api_key": "k3"}}, + ], + fallbacks=[{"primary": ["general-fallback"]}], + content_policy_fallbacks=[{"primary": ["content-fallback"]}], + ) + error_event = { + "type": "error", + "sequence_number": 2, + "error": { + "type": "invalid_request_error", + "code": "content_policy_violation", + "message": "This content was flagged for possible cybersecurity risk. The response was halted mid-stream.", + "param": None, + }, + } + + async def aiter_bytes(): + yield f"data: {json.dumps(error_event)}\n\n".encode() + + raw_response = MagicMock() + raw_response.headers = {} + raw_response.aiter_bytes = aiter_bytes + logging_obj = MagicMock(spec=LiteLLMLogging) + logging_obj.model_call_details = {"litellm_params": {}} + logging_obj.completion_start_time = None + source = ResponsesAPIStreamingIterator( + response=raw_response, + model="gpt-5.4", + responses_api_provider_config=OpenAIResponsesAPIConfig(), + logging_obj=logging_obj, + custom_llm_provider="openai", + ) + fallback_chunks = [MagicMock(type="response.output_text.delta"), MagicMock(type="response.completed")] + fallback_call = AsyncMock(return_value=_AsyncList(fallback_chunks)) + + wrapped = await router._aresponses_streaming_iterator( + response=source, + initial_kwargs={ + "model": "primary", + "stream": True, + "input": "Hi", + "original_generic_function": fallback_call, + }, + ) + collected = [chunk async for chunk in wrapped] + + assert collected == fallback_chunks + fallback_call.assert_awaited_once() + assert fallback_call.await_args.kwargs["model"] == "gemini/gemini-2.5-flash" + + +@pytest.mark.asyncio +async def test_aresponses_streaming_iterator_unwraps_content_policy_trigger_for_fallback_dispatch(): + """The fallback dispatch matches on the trigger's own type, so the wrapper must hand it the + ContentPolicyViolationError carried inside MidStreamFallbackError, not the envelope.""" + router = _make_router_with_fallback("openai/gpt-5.4", "openai/gpt-5-mini") + content_policy_error = litellm.ContentPolicyViolationError( + message="flagged mid-stream", llm_provider="openai", model="openai/gpt-5.4" + ) + src = _make_responses_iterator( + chunks=[MagicMock(type="response.created")], + error=MidStreamFallbackError( + message=str(content_policy_error), + model="openai/gpt-5.4", + llm_provider="openai", + original_exception=content_policy_error, + is_pre_first_chunk=True, + ), + model="openai/gpt-5.4", + ) + + with patch.object( + router, + "async_function_with_fallbacks_common_utils", + new=AsyncMock(return_value=_AsyncList([MagicMock(type="response.completed")])), + ) as mock_fallback_utils: + wrapped = await router._aresponses_streaming_iterator( + response=src, + initial_kwargs={"model": "openai/gpt-5.4", "stream": True, "input": "Hi"}, + ) + [chunk async for chunk in wrapped] + + mock_fallback_utils.assert_awaited_once() + assert mock_fallback_utils.await_args.kwargs["e"] is content_policy_error + + @pytest.mark.asyncio @pytest.mark.parametrize( "fallback_headers", @@ -5625,6 +5770,41 @@ def test_get_deployment_credentials_with_provider_preserves_aws_auth_params(): assert credentials.get(key) == value, key +def test_get_deployment_credentials_preserves_azure_entra_id_params(): + entra_params = { + "tenant_id": "deployment-tenant", + "client_id": "deployment-client", + "client_secret": "deployment-client-secret", + "azure_scope": "https://cognitiveservices.azure.us/.default", + "azure_username": "deployment-user", + "azure_password": "deployment-password", + } + router = litellm.Router( + model_list=[ + { + "model_name": "azure-entra-model", + "litellm_params": { + "model": "azure/gpt-5.4", + "api_base": "https://example.openai.azure.com/", + "api_version": "2024-10-21", + **entra_params, + }, + "model_info": {"id": "azure-entra-model-id"}, + } + ], + ) + + credentials = router.get_deployment_credentials(model_id="azure-entra-model-id") + credentials_with_provider = router.get_deployment_credentials_with_provider(model_id="azure-entra-model-id") + + assert credentials is not None + assert credentials_with_provider is not None + assert "api_key" not in credentials + for key, value in entra_params.items(): + assert credentials.get(key) == value, key + assert credentials_with_provider.get(key) == value, key + + def _team_wildcard_model(api_key: str, model_id: str = "team-wildcard-id") -> dict: return { "model_name": f"model_name_team-1_{model_id}", @@ -7700,6 +7880,52 @@ def test_get_available_deployment_raises_when_addressed_dict_is_blocked(): router.get_available_deployment(model="dep-0", request_kwargs={}) +def _cool_down(router: Router, *deployment_ids: str) -> None: + for deployment_id in deployment_ids: + router.cooldown_cache.add_deployment_to_cooldown( + model_id=deployment_id, + original_exception=litellm.RateLimitError(message="upstream 429", llm_provider="openai", model="gpt-4o"), + exception_status=429, + cooldown_time=60, + ) + + +async def _select_deployment(router: Router, use_async: bool) -> None: + if use_async: + await router.async_get_available_deployment(model="gpt-4o", request_kwargs={}) + return + router.get_available_deployment(model="gpt-4o", request_kwargs={}) + + +@pytest.mark.parametrize("use_async", [False, True], ids=["sync", "async"]) +@pytest.mark.asyncio +async def test_get_available_deployment_names_cooldown_when_every_deployment_is_cooled_down(use_async: bool): + from litellm.types.router import RouterErrors, RouterRateLimitError + + router: Final = _router_with_two_deployments([False, False]) + _cool_down(router, "dep-0", "dep-1") + with pytest.raises(RouterRateLimitError) as exc_info: + await _select_deployment(router, use_async) + assert exc_info.value.all_deployments_in_cooldown is True + assert exc_info.value.type == "all_deployments_in_cooldown" + assert RouterErrors.all_deployments_in_cooldown.value in str(exc_info.value) + assert str(exc_info.value).startswith("No deployments available for selected model, Try again in ") + + +@pytest.mark.parametrize("use_async", [False, True], ids=["sync", "async"]) +@pytest.mark.asyncio +async def test_get_available_deployment_keeps_generic_error_when_cooldown_is_partial(use_async: bool): + from litellm.types.router import RouterErrors, RouterRateLimitError + + router: Final = _router_with_two_deployments([False, True]) + _cool_down(router, "dep-0") + with pytest.raises(RouterRateLimitError) as exc_info: + await _select_deployment(router, use_async) + assert exc_info.value.all_deployments_in_cooldown is False + assert exc_info.value.type == "rate_limit_error" + assert RouterErrors.all_deployments_in_cooldown.value not in str(exc_info.value) + + def _router_with_two_pass_through_deployments(blocked_flags): import litellm @@ -7737,6 +7963,24 @@ def test_get_available_deployment_for_pass_through_raises_when_dict_blocked(): ) +def test_get_available_deployment_for_pass_through_names_cooldown_despite_healthy_non_pass_through(): + from litellm.types.router import RouterRateLimitError + + router: Final = _router_with_two_pass_through_deployments([False, False]) + router.add_deployment( + Deployment( + model_name="gpt-4o", + litellm_params=LiteLLM_Params(model="openai/gpt-4o-plain", api_key="sk-fake-for-tests"), + model_info=ModelInfo(id="plain-0"), + ) + ) + _cool_down(router, "pt-0", "pt-1") + with pytest.raises(RouterRateLimitError) as exc_info: + router.get_available_deployment_for_pass_through(model="gpt-4o", request_kwargs={}) + assert exc_info.value.all_deployments_in_cooldown is True + assert exc_info.value.type == "all_deployments_in_cooldown" + + def test_initialize_deployment_for_pass_through_keeps_bedrock_iam_deployment(): """ Bedrock deployments using IAM/OIDC auth have no api_key; pass-through @@ -10607,6 +10851,7 @@ def _cyclic_fallback_router(num_retries=0): "api_key": "sk-fake", "mock_response": "litellm.InternalServerError", }, + "model_info": {"id": f"{group}-deployment"}, } for group in groups ], @@ -10656,28 +10901,37 @@ async def test_cyclic_fallback_graph_does_not_amplify_one_request(): assert sum(len(message) for message in capture.messages) < 5_000 +_FLAT_ATTEMPT_RECORD_KEYS = frozenset( + {"model_group", "deployment_id", "exception_type", "exception_string", "attempted_retries"} +) +_BREADCRUMB_CREDENTIAL_CANARY = "Bearer sk-ant-oat01-RETRY-BREADCRUMB-CANARY-doNotShip" + + @pytest.mark.asyncio -async def test_retry_breadcrumbs_do_not_carry_the_walk_state(): - """log_retry copies every kwarg into previous_models, which reaches spend logs and - logging callbacks. The set of already-attempted groups is router-internal walk state - with no diagnostic value there, and it is the one entry that is not a plain scalar. - A retry has to be configured for the walk state to reach log_retry at all.""" +async def test_retry_records_are_flat_and_name_the_failed_group_on_fallback_hops(): + """Each failed attempt leaves a flat record in previous_models, which reaches spend logs and + logging callbacks. Nothing downstream reads the failed attempt's kwargs or metadata, and copying + them is what carried client credentials and multiplied the payload on every retry. A fallback hop + calls log_retry too, so the record has to name the group that failed, not the one taken next.""" router = _cyclic_fallback_router(num_retries=1) capture = _LogCapture(logging.ERROR) recorder = _FallbackAttemptRecorder() await _drive_cyclic_fallback(router, capture, recorder) - breadcrumbs = [breadcrumb for hop in recorder.breadcrumbs_per_target for breadcrumb in hop] - assert breadcrumbs, "no retry breadcrumbs were recorded" - assert any( - "fallback_depth" in breadcrumb for breadcrumb in breadcrumbs - ), "no breadcrumb carried router walk state, so this test cannot see the leak" - for breadcrumb in breadcrumbs: - assert "attempted_targets" not in breadcrumb - - -_BREADCRUMB_CREDENTIAL_CANARY = "Bearer sk-ant-oat01-RETRY-BREADCRUMB-CANARY-doNotShip" + records = [record for hop in recorder.breadcrumbs_per_target for record in hop] + assert records, "no retry records were recorded" + for record in records: + assert set(record) == _FLAT_ATTEMPT_RECORD_KEYS + assert record["exception_type"] == "InternalServerError" + assert record["deployment_id"] == f"{record['model_group']}-deployment" + group_failed_before_hop = {"group-b": "group-a", "group-c": "group-b", "group-d": "group-c"} + for failed_target, hop_records in zip(recorder.failed_targets, recorder.breadcrumbs_per_target): + groups = [record["model_group"] for record in hop_records] + first_own_attempt = groups.index(failed_target) + assert groups[first_own_attempt - 1] == group_failed_before_hop[failed_target] + assert set(groups[first_own_attempt:]) == {failed_target} + assert [record["attempted_retries"] for record in hop_records[first_own_attempt:]][:2] == [0, 1] @pytest.mark.parametrize( @@ -10703,22 +10957,20 @@ _BREADCRUMB_CREDENTIAL_CANARY = "Bearer sk-ant-oat01-RETRY-BREADCRUMB-CANARY-doN ], ) @pytest.mark.asyncio -async def test_retry_breadcrumbs_never_carry_a_forwarded_credential(container_key, request_kwargs): - """log_retry copies kwargs into previous_models, which reaches spend logs and logging callbacks. - Any of these kwargs can carry a client's forwarded Authorization token or a provider key, and a - breadcrumb has no diagnostic use for the raw secret. A denylist of key names is always one new - credential kwarg behind, so log_retry scrubs credential-named values by pattern instead: the - container still reaches the breadcrumb, but the raw secret never does, whatever key holds it.""" +async def test_retry_records_never_carry_a_forwarded_credential(container_key, request_kwargs): + """previous_models reaches spend logs and logging callbacks. Any request kwarg can carry a client's + forwarded Authorization token or a provider key, so the record must not carry request kwargs at + all: neither the credential-bearing container nor the raw secret, whatever key holds it.""" router = _cyclic_fallback_router(num_retries=1) capture = _LogCapture(logging.ERROR) metadata = {} await _drive_cyclic_fallback(router, capture, metadata=metadata, **request_kwargs) - breadcrumbs = metadata["previous_models"] - assert breadcrumbs, "no retry breadcrumbs were recorded" - dumped = json.dumps(breadcrumbs, default=str) - assert container_key in dumped, "the credential-bearing kwarg never reached the breadcrumb, so this test cannot see the leak" + records = metadata["previous_models"] + assert records, "no retry records were recorded" + dumped = json.dumps(records) + assert container_key not in dumped assert _BREADCRUMB_CREDENTIAL_CANARY not in dumped @@ -10738,12 +10990,12 @@ def _always_failing_router(num_retries): ) -async def _fail_one_proxy_shaped_request(router, request_marker): +async def _fail_one_proxy_shaped_request(router, request_marker, expected_error=litellm.InternalServerError): """The proxy hands the router a metadata dict and a proxy_server_request whose body is a shallow copy of the request, so body["metadata"] is the very same dict the router later stamps previous_models onto.""" metadata = {"request_marker": request_marker} - with pytest.raises(litellm.InternalServerError): + with pytest.raises(expected_error): await router.acompletion( model="broken-group", messages=[{"role": "user", "content": "hi"}], @@ -10769,34 +11021,109 @@ def _nested_breadcrumb_lists(node): @pytest.mark.asyncio -async def test_retry_breadcrumbs_stay_per_request_and_flat_across_failing_requests(): - """Every failed attempt appends a breadcrumb to metadata["previous_models"], and the proxy's +async def test_retry_records_stay_per_request_and_flat_across_failing_requests(): + """Every failed attempt appends a record to metadata["previous_models"], and the proxy's request snapshot aliases that same metadata dict. Kept on the Router and copied wholesale, - each breadcrumb embedded every earlier one from every earlier request, so the breadcrumb + each breadcrumb once embedded every earlier one from every earlier request, so the breadcrumb tree, and with it the debug repr of the kwargs, roughly doubled on each failed attempt until a single-worker proxy spent minutes in the redaction regex and stopped answering.""" router = _always_failing_router(num_retries=2) - breadcrumbs_per_request = [ + records_per_request = [ await _fail_one_proxy_shaped_request(router, f"request-{request_number}") for request_number in range(1, 7) ] - for request_number, breadcrumbs in enumerate(breadcrumbs_per_request, start=1): - assert len(breadcrumbs) == 3, "one initial attempt plus two retries failed, each leaving one breadcrumb" - assert {breadcrumb["metadata"]["request_marker"] for breadcrumb in breadcrumbs} == {f"request-{request_number}"} - for breadcrumb in breadcrumbs: - assert _nested_breadcrumb_lists(breadcrumb) == [] - assert len({len(repr(breadcrumbs)) for breadcrumbs in breadcrumbs_per_request}) == 1 + for records in records_per_request: + assert [record["attempted_retries"] for record in records] == [0, 1, 2] + for record in records: + assert set(record) == _FLAT_ATTEMPT_RECORD_KEYS + assert _nested_breadcrumb_lists(record) == [] + assert len({len(repr(records)) for records in records_per_request}) == 1 @pytest.mark.asyncio -async def test_retry_breadcrumbs_keep_only_the_last_four_attempts(): +async def test_retry_records_keep_only_the_last_four_attempts(): router = _always_failing_router(num_retries=6) - breadcrumbs = await _fail_one_proxy_shaped_request(router, "request-1") + records = await _fail_one_proxy_shaped_request(router, "request-1") - assert len(breadcrumbs) == 4 - assert [breadcrumb["metadata"]["attempted_retries"] for breadcrumb in breadcrumbs] == [3, 4, 5, 6] + assert [record["attempted_retries"] for record in records] == [3, 4, 5, 6] + + +@pytest.mark.asyncio +async def test_num_retries_per_request_stops_retries_at_caps_above_four(monkeypatch): + monkeypatch.setattr(litellm, "num_retries_per_request", 5) + router = _always_failing_router(num_retries=6) + + records = await _fail_one_proxy_shaped_request(router, "request-1", expected_error=litellm.APIConnectionError) + + assert [record["attempted_retries"] for record in records] == [3, 4, 5, 6] + assert ["Max retries per request hit!" in record["exception_string"] for record in records] == [ + False, + False, + True, + True, + ] + + +def _failing_group_with_healthy_fallback_router(num_retries: int) -> litellm.Router: + return litellm.Router( + model_list=[ + { + "model_name": "broken-group", + "litellm_params": { + "model": "openai/gpt-4o-mini", + "api_key": "sk-fake", + "mock_response": "litellm.InternalServerError", + }, + }, + { + "model_name": "healthy-group", + "litellm_params": {"model": "openai/gpt-4o-mini", "api_key": "sk-fake", "mock_response": "ok"}, + }, + ], + fallbacks=[{"broken-group": ["healthy-group"]}], + num_retries=num_retries, + ) + + +@pytest.mark.asyncio +@pytest.mark.parametrize( + "cap, planted_count, hop_refused", + [(2, None, True), (4, None, False), (2, -100, True)], + ids=["cap-spent-before-the-hop", "cap-not-reached-by-the-hop", "planted-negative-count-does-not-lift-the-cap"], +) +async def test_num_retries_per_request_counts_retries_across_fallback_hops( + monkeypatch: pytest.MonkeyPatch, cap: int, planted_count: int | None, hop_refused: bool +) -> None: + """num_retries_per_request caps the retries of one request, fallback hops included. Each hop starts a + fresh per-hop attempted_retries at zero, so a cap read from that counter let every hop retry from zero + and a request could spend far more retries than the cap allows. A caller who plants a negative count + in the request metadata must not push the cap further away either.""" + monkeypatch.setattr(litellm, "num_retries_per_request", cap) + router = _failing_group_with_healthy_fallback_router(num_retries=1) + recorder = _FallbackAttemptRecorder() + litellm.callbacks.append(recorder) + try: + metadata = {} if planted_count is None else {"request_retry_count": planted_count} + request = router.acompletion( + model="broken-group", messages=[{"role": "user", "content": "hi"}], metadata=metadata + ) + if not hop_refused: + assert (await request).choices[0].message.content == "ok" + return + with pytest.raises(litellm.InternalServerError): + await request + finally: + litellm.callbacks.remove(recorder) + + assert recorder.failed_targets == ["healthy-group"] + hop_refusals = [ + record["attempted_retries"] + for record in recorder.breadcrumbs_per_target[0] + if record["model_group"] == "healthy-group" and "Max retries per request hit!" in record["exception_string"] + ] + assert hop_refusals == [0, 1] @pytest.mark.asyncio diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index 835e87aff88..8bf8489fc52 100644 --- a/tests/test_litellm/test_utils.py +++ b/tests/test_litellm/test_utils.py @@ -7,8 +7,8 @@ import os import queue import threading from datetime import datetime, timedelta, timezone -from collections.abc import Iterator -from concurrent.futures import ThreadPoolExecutor +from collections.abc import Callable, Iterator +from concurrent.futures import Future, ThreadPoolExecutor from typing import Final from unittest.mock import AsyncMock, MagicMock, patch @@ -29,6 +29,8 @@ from litellm._logging import ( verbose_logger, ) from litellm.integrations.custom_logger import CustomLogger +from litellm.litellm_core_utils.get_litellm_params import get_litellm_params +from litellm.litellm_core_utils.thread_pool_executor import executor as logging_executor from litellm.proxy.utils import is_valid_api_key from litellm.types.utils import ( CallTypes, @@ -890,7 +892,10 @@ def validate_model_cost_values(model_data, exceptions=None): "input_cost_per_video_per_second_above_8s_interval", "input_cost_per_video_per_second_above_15s_interval", "input_cost_per_video_per_second_above_128k_tokens", + "input_cost_per_audio_token_batches", + "input_cost_per_image_token_batches", "input_cost_per_token_batches", + "input_cost_per_video_token_batches", "output_cost_per_token_batches", "input_cost_per_token_cache_hit", "cache_creation_input_token_cost", @@ -1039,7 +1044,10 @@ def test_aaamodel_prices_and_context_window_json_is_valid(): "input_cost_per_second": {"type": "number"}, "input_cost_per_token": {"type": "number"}, "input_cost_per_token_above_128k_tokens": {"type": "number"}, + "input_cost_per_audio_token_batches": {"type": "number"}, + "input_cost_per_image_token_batches": {"type": "number"}, "input_cost_per_token_batches": {"type": "number"}, + "input_cost_per_video_token_batches": {"type": "number"}, "input_cost_per_token_cache_hit": {"type": "number"}, "input_cost_per_video_per_second": {"type": "number"}, "input_cost_per_video_per_second_above_8s_interval": {"type": "number"}, @@ -1150,6 +1158,7 @@ def test_aaamodel_prices_and_context_window_json_is_valid(): "enum": ["none", "minimal", "low", "medium", "high", "xhigh"], }, "supports_adaptive_thinking": {"type": "boolean"}, + "supports_anthropic_thinking_payload": {"type": "boolean"}, "supports_legacy_thinking": {"type": "boolean"}, "thinking_always_on": {"type": "boolean"}, "supports_mid_conversation_system": {"type": "boolean"}, @@ -2943,7 +2952,7 @@ def test_model_info_for_openrouter_kimi_k2_5(): def test_gemini_embedding_2_ga_in_cost_map(): - """GA and Vertex preview gemini-embedding-2 entries align with multimodal unit pricing.""" + """GA and Vertex preview gemini-embedding-2 entries align with multimodal token pricing.""" import json from pathlib import Path @@ -2965,9 +2974,15 @@ def test_gemini_embedding_2_ga_in_cost_map(): assert info.get("mode") == "embedding" assert info.get("supports_multimodal") is True assert info.get("input_cost_per_token") == 2e-07 - assert info.get("input_cost_per_image") == 0.00012 - assert info.get("input_cost_per_audio_per_second") == 0.00016 - assert info.get("input_cost_per_video_per_second") == 0.00079 + assert info.get("input_cost_per_audio_token") == 6.5e-06 + assert info.get("input_cost_per_image_token") == 4.5e-07 + assert info.get("input_cost_per_video_token") == 1.2e-05 + assert info.get("input_cost_per_audio_token_batches") == 3.25e-06 + assert info.get("input_cost_per_image_token_batches") == 2.25e-07 + assert info.get("input_cost_per_video_token_batches") == 6e-06 + assert "input_cost_per_image" not in info + assert "input_cost_per_audio_per_second" not in info + assert "input_cost_per_video_per_second" not in info if provider in ("vertex_ai-embedding-models", "vertex_ai"): assert ( info.get("uses_embed_content") is True @@ -4061,6 +4076,56 @@ class TestMetadataNoneHandling: assert metadata == {} +_RETRY_CAP_CASES: Final = ( + pytest.param(5, {"request_retry_count": 5}, True, id="cap-above-four-reached"), + pytest.param(5, {"request_retry_count": 4}, False, id="cap-above-four-not-reached"), + pytest.param(0, {"request_retry_count": 0}, False, id="first-attempt-passes-cap-of-zero"), + pytest.param(0, {"request_retry_count": 1}, True, id="cap-of-zero-refuses-first-retry"), + pytest.param(0, {"attempted_retries": 1}, False, id="per-hop-attempted-retries-is-not-the-cap"), + pytest.param(5, {"previous_models": ("a", "b", "c", "d", "e")}, False, id="breadcrumb-count-is-not-the-cap"), + pytest.param(5, None, False, id="metadata-none"), +) + + +def _capped_completion_kwargs(metadata_key: str, metadata: object) -> dict[str, object]: + return { + "model": "openai/gpt-4o-mini", + "messages": [{"role": "user", "content": "hi"}], + "api_key": "sk-fake", + "mock_response": "ok", + metadata_key: metadata, + } + + +@pytest.mark.parametrize("metadata_key", ["metadata", "litellm_metadata"]) +@pytest.mark.parametrize("cap, metadata, refused", _RETRY_CAP_CASES) +def test_num_retries_per_request_reads_request_retry_count_sync( + monkeypatch: pytest.MonkeyPatch, metadata_key: str, cap: int, metadata: object, refused: bool +) -> None: + monkeypatch.setattr(litellm, "num_retries_per_request", cap) + kwargs: Final = _capped_completion_kwargs(metadata_key, metadata) + if refused: + with pytest.raises(Exception, match="Max retries per request hit!"): + litellm.completion(**kwargs) + else: + assert litellm.completion(**kwargs).choices[0].message.content == "ok" + + +@pytest.mark.asyncio +@pytest.mark.parametrize("metadata_key", ["metadata", "litellm_metadata"]) +@pytest.mark.parametrize("cap, metadata, refused", _RETRY_CAP_CASES) +async def test_num_retries_per_request_reads_request_retry_count_async( + monkeypatch: pytest.MonkeyPatch, metadata_key: str, cap: int, metadata: object, refused: bool +) -> None: + monkeypatch.setattr(litellm, "num_retries_per_request", cap) + kwargs: Final = _capped_completion_kwargs(metadata_key, metadata) + if refused: + with pytest.raises(Exception, match="Max retries per request hit!"): + await litellm.acompletion(**kwargs) + else: + assert (await litellm.acompletion(**kwargs)).choices[0].message.content == "ok" + + class TestValidateAndFixThinkingParam: """Tests for validate_and_fix_thinking_param.""" @@ -4448,6 +4513,75 @@ def test_fireworks_models_in_backup_cost_map(): ), f"short-form {short_key} does not match long-form {long_key}" +@pytest.fixture +def fireworks_short_model_cost_map(monkeypatch: pytest.MonkeyPatch) -> Iterator[None]: + monkeypatch.setattr( + litellm, + "model_cost", + { + "fireworks_ai/accounts/fireworks/models/glm-5p3": { + "input_cost_per_token": 1e-6, + "output_cost_per_token": 2e-6, + "litellm_provider": "fireworks_ai", + "mode": "chat", + "max_tokens": 100, + }, + "fireworks_ai/accounts/fireworks/routers/glm-5p3-fast": { + "input_cost_per_token": 2.1e-6, + "output_cost_per_token": 6.6e-6, + "litellm_provider": "fireworks_ai", + "mode": "chat", + }, + "fireworks_ai/nomic-ai/nomic-embed-text-v1.5": { + "input_cost_per_token": 8e-9, + "output_cost_per_token": 0.0, + "litellm_provider": "fireworks_ai", + "mode": "embedding", + }, + }, + ) + litellm.get_model_info.cache_clear() + yield + litellm.get_model_info.cache_clear() + + +def test_fireworks_short_model_names_resolve_to_long_cost_map_keys(fireworks_short_model_cost_map: None) -> None: + model_info = litellm.get_model_info("fireworks_ai/glm-5p3") + assert model_info["key"] == "fireworks_ai/accounts/fireworks/models/glm-5p3" + assert model_info["input_cost_per_token"] == 1e-6 + assert model_info["max_tokens"] == 100 + + model_info = litellm.get_model_info("glm-5p3", custom_llm_provider="fireworks_ai") + assert model_info["key"] == "fireworks_ai/accounts/fireworks/models/glm-5p3" + + model_info = litellm.get_model_info("fireworks_ai/glm-5p3-fast") + assert model_info["key"] == "fireworks_ai/accounts/fireworks/routers/glm-5p3-fast" + assert model_info["input_cost_per_token"] == 2.1e-6 + + model_info = litellm.get_model_info("fireworks_ai/nomic-ai/nomic-embed-text-v1.5") + assert model_info["key"] == "fireworks_ai/nomic-ai/nomic-embed-text-v1.5" + + with pytest.raises(Exception, match="isn't mapped"): + litellm.get_model_info("fireworks_ai/does-not-exist") + + +def test_fireworks_short_model_names_price_with_completion_cost(fireworks_short_model_cost_map: None) -> None: + from litellm.types.utils import ModelResponse + + response = ModelResponse( + model="fireworks_ai/glm-5p3", + usage=Usage(prompt_tokens=10, completion_tokens=5, total_tokens=15), + ) + + cost = litellm.completion_cost( + completion_response=response, + model="fireworks_ai/glm-5p3", + custom_llm_provider="fireworks_ai", + ) + + assert cost == pytest.approx(10 * 1e-6 + 5 * 2e-6) + + class TestBedrockBaseModelLabelKeepsTools: """Regression for #29618: a Bedrock deployment whose ``base_model`` is a friendly label must not silently drop ``tools``/``tool_choice`` under ``drop_params``.""" @@ -4514,6 +4648,16 @@ def test_aws_bedrock_project_id_excluded_from_bedrock_optional_params(): assert result["aws_region_name"] == "us-east-1" +@pytest.mark.parametrize("filter_name", [ + "get_non_default_completion_params", "get_non_default_transcription_params", "filter_out_litellm_params", +]) +def test_scoped_weights_are_excluded_from_provider_params(filter_name: str) -> None: + filtered = getattr(litellm.utils, filter_name)( + {"provider_option": "kept", "_router_weights": {"group": {"deployment": 100}}} + ) + assert filtered == {"provider_option": "kept"} + + class TestGetOptionalParamsTencent: """Tests that tencent provider uses TencentChatConfig for parameter mapping.""" @@ -5273,6 +5417,26 @@ def test_websearch_interception_control_fields_never_reach_the_provider(): assert set(WEBSEARCH_INTERNAL_CONTROL_FIELDS) <= set(all_litellm_params) +def test_get_litellm_params_keys_never_reach_the_provider(): + """Bridges (chat <-> Responses, agentic loop follow-ups) forward litellm_params as + `completion()` kwargs. Any key the param builder does not recognize is swept into + extra_body, and OpenAI rejects the call with `Unknown parameter: 'model_alias_map'`. + """ + litellm_param_keys = frozenset(get_litellm_params()) - {"drop_params"} + kwargs = { + "a_real_provider_specific_param": 1, + "model_alias_map": {"alias": "gpt-5.4"}, + **{key: "configured-value" for key in litellm_param_keys - {"model_alias_map"}}, + } + + non_default = get_non_default_completion_params(kwargs) + + assert non_default == {"a_real_provider_specific_param": 1}, ( + "litellm params leaked into the provider params: " + f"{sorted(set(non_default) - {'a_real_provider_specific_param'})}" + ) + + def test_bedrock_batch_params_never_reach_the_provider(): """A Bedrock managed-batch deployment carries aws_batch_role_arn / s3_* / bedrock_tags in its litellm_params, and the same deployment also serves chat. @@ -6374,6 +6538,53 @@ async def test_acompletion_finishes_response_metadata_before_handing_the_respons assert snapshot["api_base"] +class _GatedSyncLoggingHookRecorder(CustomLogger): + def __init__(self) -> None: + super().__init__() + self.seen: Final = queue.SimpleQueue[str | None]() + self.release: Final = threading.Event() + + def logging_hook( + self, kwargs: dict[str, object], result: object, call_type: str + ) -> tuple[dict[str, object], object]: + self.seen.put(result.id if isinstance(result, litellm.ModelResponse) else None) + self.release.wait(timeout=5) + return kwargs, result + + +@pytest.mark.asyncio +async def test_acompletion_runs_a_custom_logger_sync_logging_hook_exactly_once(monkeypatch: pytest.MonkeyPatch) -> None: + def legacy_sync_callback( + kwargs: dict[str, object], response: litellm.ModelResponse, start_time: datetime, end_time: datetime + ) -> None: + pass + + recorder: Final = _GatedSyncLoggingHookRecorder() + monkeypatch.setattr(litellm, "success_callback", [legacy_sync_callback, recorder]) + logging_futures: Final = queue.SimpleQueue[Future[object]]() + real_submit: Final = logging_executor.submit + + def submit_and_track(fn: Callable[..., object], *args: object, **kwargs: object) -> Future[object]: + future: Final = real_submit(fn, *args, **kwargs) + logging_futures.put(future) + return future + + with patch( # test-quality-ok: wraps the real submit only to collect the futures to join, the pool still runs + "litellm.litellm_core_utils.litellm_logging.executor.submit", side_effect=submit_and_track + ): + response: Final = await litellm.acompletion( + model="gpt-5.5", + messages=[{"role": "user", "content": "hi"}], + mock_response="Hello there!", + num_retries=0, + ) + await asyncio.sleep(0) + recorder.release.set() + for _ in range(logging_futures.qsize()): + logging_futures.get_nowait().result(timeout=5) + assert [recorder.seen.get_nowait() for _ in range(recorder.seen.qsize())] == [response.id] + + def test_completion_finishes_response_metadata_before_handing_the_response_to_the_logging_thread(): with _recording_hidden_params_at_submit("litellm.utils.executor.submit") as seen: litellm.completion( @@ -6385,3 +6596,11 @@ def test_completion_finishes_response_metadata_before_handing_the_response_to_th assert snapshot["litellm_call_id"] assert snapshot["response_cost"] is not None assert snapshot["api_base"] + + +def test_get_model_info_carries_cache_read_input_audio_token_cost(monkeypatch): + monkeypatch.setenv("LITELLM_LOCAL_MODEL_COST_MAP", "True") + monkeypatch.setattr(litellm, "model_cost", litellm.get_model_cost_map(url="")) + info = litellm.get_model_info("gpt-realtime-2.1-mini", custom_llm_provider="openai") + assert info["cache_read_input_audio_token_cost"] == 3e-07 + assert info["cache_read_input_token_cost"] == 6e-08 diff --git a/tests/test_litellm_rust/ocr/test_lifecycle.py b/tests/test_litellm_rust/ocr/test_lifecycle.py index 1acad5527d8..dfcd63d3019 100644 --- a/tests/test_litellm_rust/ocr/test_lifecycle.py +++ b/tests/test_litellm_rust/ocr/test_lifecycle.py @@ -79,6 +79,20 @@ async def test_proxy_metadata_remains_python_owned(ocr_server: RecordingServer) assert "metadata" not in ocr_server.requests[0].body +@pytest.mark.asyncio +async def test_request_level_custom_pricing_reaches_logging_params_and_bills_the_call( + ocr_server: RecordingServer, +) -> None: + recorder: Final = RecordingLogger() + response: Final = await call_aocr(ocr_server, callbacks=[recorder], ocr_cost_per_page=0.05) + events: Final = await recorder.wait_for_async("async_log_success_event") + + assert response.usage_info is not None and response.usage_info.pages_processed == 1 + assert events[0].kwargs["litellm_params"]["ocr_cost_per_page"] == 0.05 + assert response._hidden_params["response_cost"] == pytest.approx(0.05) + assert "ocr_cost_per_page" not in ocr_server.requests[0].body + + @pytest.mark.asyncio async def test_response_replacement_finalized_before_dispatch_in_caller_task(ocr_server: RecordingServer) -> None: caller: Final = asyncio.current_task() @@ -792,7 +806,7 @@ async def test_shared_call_limits_still_reject_before_reading_ocr_file( monkeypatch.setattr(litellm, "_current_cost", 2) monkeypatch.setattr(litellm, "num_retries_per_request", 1 if limit == "retries" else None) expected: Final = litellm.BudgetExceededError if limit == "budget" else RuntimeError - arguments: Final = {"document": {"type": "file", "file": File()}, "metadata": {"previous_models": ["earlier"]}} + arguments: Final = {"document": {"type": "file", "file": File()}, "metadata": {"request_retry_count": 1}} with pytest.raises(expected, match=r"Budget has been exceeded|Max retries per request hit"): await call_aocr(ocr_server, **arguments) if asynchronous else call_ocr(ocr_server, **arguments) assert reads == [] diff --git a/ui/litellm-dashboard/eslint-suppressions.json b/ui/litellm-dashboard/eslint-suppressions.json index e2a08a40bcb..773854d29e6 100644 --- a/ui/litellm-dashboard/eslint-suppressions.json +++ b/ui/litellm-dashboard/eslint-suppressions.json @@ -2322,7 +2322,7 @@ }, "src/components/view_logs/GuardrailViewer/GuardrailViewer.tsx": { "no-nested-ternary": { - "count": 4 + "count": 3 } }, "src/components/view_logs/LogDetailsDrawer/LogDetailsDrawer.tsx": { diff --git a/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_dashboard.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_dashboard.test.tsx index deb819fdc04..3447602dd79 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_dashboard.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_dashboard.test.tsx @@ -236,6 +236,35 @@ describe("CacheDashboard cache analytics charts", () => { expect(screen.queryByText(/Failed requests by error code/)).not.toBeInTheDocument(); }); + it("explains the Unknown bucket only when a group has no recorded endpoint", async () => { + const { rerender } = renderDashboard(); + await screen.findByText(REQUESTS_CHART_TITLE); + expect(screen.queryByText(/recorded no endpoint/)).not.toBeInTheDocument(); + + useCacheActivity.mockReturnValue({ + data: { + ...cacheActivity, + groups: [ + ...cacheActivity.groups, + { + call_type: "Unknown", + api_requests: 0, + cache_hits: 0, + failed_requests: 121000, + cached_completion_tokens: 0, + generated_completion_tokens: 0, + }, + ], + }, + refetch: vi.fn(), + }); + rerender(); + + expect( + within(cardTitled(REQUESTS_CHART_TITLE)).getByText(/Unknown groups spend logs that recorded no endpoint/), + ).toHaveTextContent("not necessarily LLM API requests"); + }); + it("formats y-axis ticks with compact notation", async () => { renderDashboard(); const { requestsCard, tokensCard } = await findChartCards(); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_dashboard.tsx b/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_dashboard.tsx index befc0b3c5ca..29819adf524 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_dashboard.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/caching/_components/cache_dashboard.tsx @@ -35,6 +35,11 @@ const REQUEST_SERIES = { failed: "Failed requests", } as const; +const UNKNOWN_CALL_TYPE = "Unknown"; + +const UNKNOWN_CALL_TYPE_NOTE = + "Unknown groups spend logs that recorded no endpoint. Older proxy versions wrote those for requests rejected before routing, so they are not necessarily LLM API requests."; + const toChartDatum = (group: CacheActivityGroup) => ({ name: group.call_type, [REQUEST_SERIES.apiRequests]: group.api_requests, @@ -103,6 +108,7 @@ const CacheDashboard: React.FC = ({ accessToken, token, userRole const uniqueApiKeys = activity?.filter_options.key_aliases ?? []; const uniqueModels = activity?.filter_options.models ?? []; const chartData = (activity?.groups ?? []).map(toChartDatum); + const hasUnknownGroup = (activity?.groups ?? []).some((group) => group.call_type === UNKNOWN_CALL_TYPE); const activeDrilldownCallType = resolveDrilldownCallType(errorDrilldownCallType, activity?.groups ?? []); const handleRefreshClick = () => { @@ -288,6 +294,7 @@ const CacheDashboard: React.FC = ({ accessToken, token, userRole

Click a red failed-requests segment to see which error codes caused those failures.

+ {hasUnknownGroup &&

{UNKNOWN_CALL_TYPE_NOTE}

} ) => ({ id: l.id as string, timestamp: l.timestamp as string, - action: l.action as "blocked" | "passed" | "flagged", + action: l.action as LogEntry["action"], score: l.score as number | undefined, model: l.model as string | undefined, input_snippet: l.input_snippet as string | undefined, diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.test.ts index eccd8a80748..56e45216ec5 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.test.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.test.ts @@ -328,7 +328,8 @@ describe("useTeam", () => { }); it("should return team data when query is successful", async () => { - (teamInfoCall as any).mockResolvedValue(mockTeams[0]); + // /team/info answers with an envelope; the hook is typed as the team itself. + (teamInfoCall as any).mockResolvedValue({ team_id: "team-1", team_info: mockTeams[0], keys: [] }); const { result } = renderHook(() => useTeam("team-1"), { wrapper }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.ts b/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.ts index 14e95bcd543..05025adc5e6 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.ts +++ b/ui/litellm-dashboard/src/app/(dashboard)/hooks/teams/useTeams.ts @@ -163,7 +163,8 @@ export const useTeam = (teamId?: string) => { throw new Error("Missing auth or teamId"); } - return teamInfoCall(accessToken, teamId); + const { team_info } = (await teamInfoCall(accessToken, teamId)) as { team_info: Team }; + return team_info; }, initialData: () => { diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.tsx index b4e300d9fc3..ccb9f90f9a3 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTab.tsx @@ -48,7 +48,7 @@ const AllModelsTab = ({ setSelectedTeamId, }: AllModelsTabProps) => { const { data: modelCostMapData, isLoading: isLoadingModelCostMap } = useModelCostMap(); - const { accessToken, userId, userRole } = useAuthorized(); + const { accessToken, userId, userRole, isViewOnly } = useAuthorized(); const { data: teams, isLoading: isLoadingTeams } = useTeams(); const queryClient = useQueryClient(); @@ -281,6 +281,7 @@ const AllModelsTab = ({ availableModelAccessGroups={availableModelAccessGroups} userRole={userRole} userID={userId} + isViewOnly={isViewOnly} onModelIdClick={setSelectedModelId} onTeamIdClick={setSelectedTeamId} onDeleteClick={handleDeleteClick} diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTable.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTable.test.tsx index 8ba71e82d48..726070c4bb6 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTable.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTable.test.tsx @@ -59,6 +59,7 @@ const baseProps = { availableModelAccessGroups: ["sales-team"], userRole: "Admin", userID: "alice", + isViewOnly: false, onModelIdClick: vi.fn(), onTeamIdClick: vi.fn(), onDeleteClick: vi.fn(), @@ -254,6 +255,17 @@ describe("AllModelsTable", () => { expect(onTogglePauseClick).not.toHaveBeenCalled(); }); + it("does not let a view-only admin toggle a model", async () => { + const user = userEvent.setup(); + const onTogglePauseClick = vi.fn(); + render(); + + const toggle = screen.getByTestId("model-pause-toggle-model-1"); + expect(toggle).toHaveAttribute("data-disabled"); + await user.click(toggle); + expect(onTogglePauseClick).not.toHaveBeenCalled(); + }); + it("does not let anyone toggle a config model", async () => { const user = userEvent.setup(); const onTogglePauseClick = vi.fn(); @@ -309,6 +321,17 @@ describe("AllModelsTable", () => { expect(onDeleteClick).not.toHaveBeenCalled(); }); + it("blocks a view-only admin from deleting a DB model they created", async () => { + const user = userEvent.setup(); + const onDeleteClick = vi.fn(); + render(); + + const deleteButton = screen.getByTestId("model-delete-model-1"); + expect(deleteButton).toBeDisabled(); + await user.click(deleteButton); + expect(onDeleteClick).not.toHaveBeenCalled(); + }); + it("blocks deleting a config model", async () => { const user = userEvent.setup(); const onDeleteClick = vi.fn(); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTable.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTable.tsx index 8482d0832c3..f46130d2386 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTable.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/AllModelsTable.tsx @@ -73,6 +73,7 @@ interface AllModelsTableProps { availableModelAccessGroups: string[]; userRole: string; userID: string; + isViewOnly: boolean; onModelIdClick: (modelId: string) => void; onTeamIdClick: (teamId: string) => void; onDeleteClick: (modelId: string) => void; @@ -120,6 +121,7 @@ export function AllModelsTable({ availableModelAccessGroups, userRole, userID, + isViewOnly, onModelIdClick, onTeamIdClick, onDeleteClick, @@ -132,6 +134,7 @@ export function AllModelsTable({ const columnDeps = { userRole, userID, + isViewOnly, onModelIdClick, onTeamIdClick, onDeleteClick, @@ -139,7 +142,7 @@ export function AllModelsTable({ pausingModelId, }; return getModelsTableColumns(columnDeps); - }, [userRole, userID, onModelIdClick, onTeamIdClick, onDeleteClick, onTogglePauseClick, pausingModelId]); + }, [userRole, userID, isViewOnly, onModelIdClick, onTeamIdClick, onDeleteClick, onTogglePauseClick, pausingModelId]); const modelGroupOptions = useMemo( () => [ diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/ModelsTableColumns.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/ModelsTableColumns.tsx index f3ae687447e..0cc1207e547 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/ModelsTableColumns.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/components/ModelsTableColumns.tsx @@ -247,6 +247,7 @@ interface ModelRowActionsProps { model: ModelData; userRole: string; userID: string; + isViewOnly: boolean; isPausing: boolean; onDeleteClick?: (modelId: string) => void; onTogglePauseClick?: (modelId: string, blocked: boolean) => void | Promise; @@ -256,14 +257,15 @@ function ModelRowActions({ model, userRole, userID, + isViewOnly, isPausing, onDeleteClick, onTogglePauseClick, }: ModelRowActionsProps) { const modelId = model.model_info?.id; const isConfigModel = !model.model_info?.db_model; - const isAdmin = userRole === "Admin"; - const canEditModel = isAdmin || model.model_info?.created_by === userID; + const isAdmin = userRole === "Admin" && !isViewOnly; + const canEditModel = !isViewOnly && (isAdmin || model.model_info?.created_by === userID); const isBlocked = model.model_info?.blocked === true; const isPauseToggleable = !isConfigModel && isAdmin && Boolean(onTogglePauseClick); @@ -340,6 +342,7 @@ function ModelRowActions({ export interface ModelsTableColumnDeps { userRole: string; userID: string; + isViewOnly: boolean; onModelIdClick: (modelId: string) => void; onTeamIdClick: (teamId: string) => void; onDeleteClick?: (modelId: string) => void; @@ -350,6 +353,7 @@ export interface ModelsTableColumnDeps { export const getModelsTableColumns = ({ userRole, userID, + isViewOnly, onModelIdClick, onTeamIdClick, onDeleteClick, @@ -479,6 +483,7 @@ export const getModelsTableColumns = ({ model={row.original} userRole={userRole} userID={userID} + isViewOnly={isViewOnly} isPausing={pausingModelId === row.original.model_info?.id} onDeleteClick={onDeleteClick} onTogglePauseClick={onTogglePauseClick} diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx index 84a05113177..105f6ff3043 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.test.tsx @@ -14,6 +14,7 @@ vi.mock("./panels/HealthStatusPanel", () => ({ default: () =>
({ default: () =>
})); vi.mock("./panels/ModelGroupAliasPanel", () => ({ default: () =>
})); vi.mock("./panels/PriceDataPanel", () => ({ default: () =>
})); +vi.mock("./panels/AccessGroupBudgetsPanel", () => ({ default: () =>
})); const detailState = { modelId: null as string | null, teamId: null as string | null }; vi.mock("./detailNavigation", () => ({ @@ -25,7 +26,11 @@ vi.mock("@/components/model_info_view", () => ({ default: ({ modelId }: { modelId: string }) =>
model:{modelId}
, })); vi.mock("@/components/team/TeamInfo", () => ({ - default: ({ teamId }: { teamId: string }) =>
team:{teamId}
, + default: ({ teamId, is_team_admin }: { teamId: string; is_team_admin: boolean }) => ( +
+ team:{teamId} +
+ ), })); const mockUseAuthorized = vi.fn(); @@ -95,10 +100,19 @@ describe("ModelsAndEndpointsPage", () => { expect(screen.queryByRole("tab", { name: "All Models" })).not.toBeInTheDocument(); }); - it("renders the team detail overlay from the ?team drill-in", () => { + it("renders the team detail overlay from the ?team drill-in with admin edit rights", () => { detailState.teamId = "team-9"; renderPage(); expect(screen.getByTestId("team-info")).toHaveTextContent("team:team-9"); + expect(screen.getByTestId("team-info")).toHaveAttribute("data-team-admin", "true"); + }); + + it("opens the ?team drill-in without edit rights for a view-only admin", () => { + mockUseAuthorized.mockReturnValue(VIEW_ONLY_ADMIN); + detailState.teamId = "team-9"; + renderPage(); + expect(screen.getByTestId("team-info")).toHaveTextContent("team:team-9"); + expect(screen.getByTestId("team-info")).toHaveAttribute("data-team-admin", "false"); }); it("hides admin-only tabs for a non-admin user", () => { @@ -108,6 +122,35 @@ describe("ModelsAndEndpointsPage", () => { expect(screen.queryByRole("tab", { name: "Health Status" })).not.toBeInTheDocument(); }); + it("keeps the full admin tab order for a real admin", () => { + renderPage(); + expect(screen.getAllByRole("tab").map((tab) => tab.textContent)).toEqual([ + "All Models", + "Add Model", + "Auto-Routers Beta", + "LLM Credentials", + "Pass-Through Endpoints", + "Health Status", + "Model Retry Settings", + "Model Group Alias", + "Model Access Group Budgets Beta", + "Price Data Reload", + ]); + }); + + it("hides the admin write-form tabs from a view-only admin, keeping the read views", () => { + mockUseAuthorized.mockReturnValue(VIEW_ONLY_ADMIN); + renderPage(); + expect(screen.getByRole("tab", { name: "All Models" })).toBeInTheDocument(); + expect(screen.getByRole("tab", { name: "Health Status" })).toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: "LLM Credentials" })).not.toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: "Pass-Through Endpoints" })).not.toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: "Model Retry Settings" })).not.toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: "Model Group Alias" })).not.toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: /Model Access Group Budgets/ })).not.toBeInTheDocument(); + expect(screen.queryByRole("tab", { name: "Price Data Reload" })).not.toBeInTheDocument(); + }); + // POST /model/new 403s a proxy_admin_viewer, so the form's tab must not render for one. it("hides the Add Model tab for a view-only admin session", () => { mockUseAuthorized.mockReturnValue(VIEW_ONLY_ADMIN); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.tsx b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.tsx index 34c9d87004e..4d6a90fc56e 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/models-and-endpoints/page.tsx @@ -106,19 +106,16 @@ export default function ModelsAndEndpointsPage() { "", ...(canCreate ? (["add"] as const) : []), ...(isAdmin || canCreate ? (["auto-routers"] as const) : []), - ...(isAdmin - ? ([ - "llm-credentials", - "pass-through", - "health", - "retry-settings", - "model-group-alias", - "access-group-budgets", - "price-data", - ] as const) + // effectiveSessionRole reports proxy_admin_viewer as "Admin", so isAdmin alone would show a + // viewer these write-only panels; only the raw-role isViewOnly separates them. Health Status + // stays: it is the bucket's one read view, and viewers keep read parity with admins. + ...(isAdmin && !isViewOnly ? (["llm-credentials", "pass-through"] as const) : []), + ...(isAdmin ? (["health"] as const) : []), + ...(isAdmin && !isViewOnly + ? (["retry-settings", "model-group-alias", "access-group-budgets", "price-data"] as const) : []), ], - [canCreate, isAdmin], + [canCreate, isAdmin, isViewOnly], ); const allModelsLabel = isAdmin ? "All Models" : "Your Models"; @@ -148,7 +145,7 @@ export default function ModelsAndEndpointsPage() { teamId={teamId} onClose={close} accessToken={accessToken} - is_team_admin={userRole === "Admin"} + is_team_admin={userRole === "Admin" && !isViewOnly} is_proxy_admin={userRole === "Proxy Admin"} userModels={allModelsOnProxy} editTeam={false} diff --git a/ui/litellm-dashboard/src/app/(dashboard)/projects/_components/ProjectDetailsPage.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/projects/_components/ProjectDetailsPage.test.tsx index cf6576ce6e9..d22ac0d8742 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/projects/_components/ProjectDetailsPage.test.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/projects/_components/ProjectDetailsPage.test.tsx @@ -242,13 +242,11 @@ describe("ProjectDetail", () => { it("should show team information when team data is available", () => { mockUseTeam.mockReturnValue({ data: { - team_info: { - team_id: "team-1", - team_alias: "Engineering", - models: ["gpt-4"], - spend: 50, - members_with_roles: [], - }, + team_id: "team-1", + team_alias: "Engineering", + models: ["gpt-4"], + spend: 50, + members_with_roles: [], }, isLoading: false, }); diff --git a/ui/litellm-dashboard/src/app/(dashboard)/projects/_components/ProjectDetailsPage.tsx b/ui/litellm-dashboard/src/app/(dashboard)/projects/_components/ProjectDetailsPage.tsx index f94240f3c9e..2585b67c81b 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/projects/_components/ProjectDetailsPage.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/projects/_components/ProjectDetailsPage.tsx @@ -14,16 +14,6 @@ import { UiLoadingSpinner } from "@/components/ui/ui-loading-spinner"; import { EditProjectModal } from "./ProjectModals/EditProjectModal"; import { ProjectKeysSection } from "./ProjectKeysSection"; -interface TeamInfoShape { - team_id: string; - team_alias?: string; - models?: string[]; - max_budget?: number | null; - budget_duration?: string | null; - spend?: number; - members_with_roles?: { user_id: string; role: string }[]; -} - interface ProjectDetailProps { projectId: string; onBack: () => void; @@ -33,10 +23,7 @@ const utilisationTone = (percent: number) => (percent >= 90 ? "over" : percent > export function ProjectDetail({ projectId, onBack }: ProjectDetailProps) { const { data: project, isLoading } = useProjectDetails(projectId); - const { data: teamData } = useTeam(project?.team_id ?? undefined); - // teamInfoCall returns { team_id, team_info: {...}, keys, team_memberships } - const teamInfo: TeamInfoShape | undefined = ((teamData as unknown as { team_info?: TeamInfoShape })?.team_info ?? - teamData) as TeamInfoShape | undefined; + const { data: teamInfo } = useTeam(project?.team_id ?? undefined); const [isEditModalVisible, setIsEditModalVisible] = useState(false); const spend = project?.spend ?? 0; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/usage/_components/components/EntityUsage/EntityUsage.tsx b/ui/litellm-dashboard/src/app/(dashboard)/usage/_components/components/EntityUsage/EntityUsage.tsx index 273e478528e..6c15b3c418d 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/usage/_components/components/EntityUsage/EntityUsage.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/usage/_components/components/EntityUsage/EntityUsage.tsx @@ -42,6 +42,7 @@ import { valueFormatterSpend } from "@/components/UsagePage/utils/value_formatte import EndpointUsage from "../EndpointUsage/EndpointUsage"; import ModelViewToggle, { ModelViewType } from "../ModelViewToggle"; import TopKeyView from "@/components/UsagePage/components/EntityUsage/TopKeyView"; +import KeyActivityPanel from "@/components/UsagePage/components/KeyActivityPanel"; import TopModelView from "./TopModelView"; import TeamUserSpendCard from "./TeamUserSpendCard"; @@ -654,7 +655,7 @@ const EntityUsage: React.FC = ({ { key: "keys", label: "Key Activity", - content: , + content: , }, { key: "endpoints", label: "Endpoint Activity", content: }, ]; diff --git a/ui/litellm-dashboard/src/app/(dashboard)/usage/_components/components/UsagePageView.tsx b/ui/litellm-dashboard/src/app/(dashboard)/usage/_components/components/UsagePageView.tsx index a92d1209567..de353948db9 100644 --- a/ui/litellm-dashboard/src/app/(dashboard)/usage/_components/components/UsagePageView.tsx +++ b/ui/litellm-dashboard/src/app/(dashboard)/usage/_components/components/UsagePageView.tsx @@ -30,6 +30,7 @@ import { ActivityMetrics, processActivityData } from "@/components/activity_metr import CloudZeroExportModal from "@/components/cloudzero_export_modal"; import UserDropdown from "@/components/common_components/UserDropdown"; import EntityUsageExportModal from "@/components/EntityUsageExport"; +import KeyActivityPanel from "@/components/UsagePage/components/KeyActivityPanel"; import { Team } from "@/components/key_team_helpers/key_list"; import { gatewayDailyActivityCall, @@ -886,7 +887,7 @@ const UsagePage: React.FC = ({ teams, organizations }) => { - + diff --git a/ui/litellm-dashboard/src/components/GuardrailsMonitor/LogViewer.test.tsx b/ui/litellm-dashboard/src/components/GuardrailsMonitor/LogViewer.test.tsx new file mode 100644 index 00000000000..083b1e5f3e2 --- /dev/null +++ b/ui/litellm-dashboard/src/components/GuardrailsMonitor/LogViewer.test.tsx @@ -0,0 +1,110 @@ +import userEvent from "@testing-library/user-event"; +import React from "react"; +import { beforeEach, describe, expect, it, vi } from "vitest"; + +import { renderWithProviders, screen, testQueryClient, waitFor, within } from "../../../tests/test-utils"; +import type { LogEntry as SpendLogEntry } from "@/components/view_logs/columns"; +import { LogViewer } from "./LogViewer"; + +vi.mock("@/components/networking", async (importOriginal) => { + const actual = await importOriginal(); + return { ...actual, uiSpendLogsCall: vi.fn() }; +}); + +vi.mock("@/components/view_logs/LogDetailsDrawer", () => ({ + LogDetailsDrawer: function LogDetailsDrawerMock({ + open, + logEntry, + }: { + open: boolean; + logEntry?: { request_id: string } | null; + }) { + return ( +
+ {open ? "open" : "closed"} +
+ ); + }, +})); + +import { uiSpendLogsCall } from "@/components/networking"; + +const spendLog = (overrides: Partial): SpendLogEntry => ({ + request_id: "req-1", + api_key: "key-1", + team_id: "team-1", + model: "gpt-4o", + model_id: "model-1", + call_type: "acompletion", + spend: 0.01, + total_tokens: 10, + prompt_tokens: 5, + completion_tokens: 5, + startTime: "2026-09-02T09:50:13Z", + endTime: "2026-09-02T09:50:14Z", + cache_hit: "false", + messages: [], + response: {}, + ...overrides, +}); + +const guardrailLog = { + id: "provider-victim", + timestamp: "2026-09-02 09:50:13", + action: "passed" as const, + input_snippet: "victim prompt", +}; + +describe("GuardrailsMonitor LogViewer drawer", () => { + beforeEach(() => { + vi.mocked(uiSpendLogsCall).mockReset(); + testQueryClient.clear(); + }); + + it("opens the row whose request_id is the clicked log id even when a newer row carries that id as its call id", async () => { + vi.mocked(uiSpendLogsCall).mockResolvedValue({ + data: [ + spendLog({ request_id: "provider-attacker", litellm_call_id: "provider-victim" }), + spendLog({ request_id: "provider-victim", litellm_call_id: "call-victim" }), + ], + total: 2, + }); + + renderWithProviders(); + await userEvent.click(screen.getByText("victim prompt")); + + await waitFor(() => { + expect(screen.getByTestId("log-details-drawer")).toHaveAttribute("data-log-id", "provider-victim"); + }); + expect(vi.mocked(uiSpendLogsCall)).toHaveBeenCalledWith( + expect.objectContaining({ params: { request_id: "provider-victim" } }), + ); + }); + + it("falls back to the first returned row when none carries the clicked id as its request_id", async () => { + vi.mocked(uiSpendLogsCall).mockResolvedValue({ + data: [spendLog({ request_id: "provider-other", litellm_call_id: "provider-victim" })], + total: 1, + }); + + renderWithProviders(); + await userEvent.click(screen.getByText("victim prompt")); + + await waitFor(() => { + expect(screen.getByTestId("log-details-drawer")).toHaveAttribute("data-log-id", "provider-other"); + }); + }); +}); + +describe("GuardrailsMonitor LogViewer not_run rows", () => { + it("renders a not_run log as a neutral Not run badge instead of a pass or failure", () => { + renderWithProviders( + , + ); + + const row = screen.getByRole("button", { name: /system prompt only/ }); + expect(within(row).getByText("Not run")).toHaveClass("text-muted-foreground"); + expect(within(row).queryByText("Passed")).not.toBeInTheDocument(); + expect(within(row).queryByText("Blocked")).not.toBeInTheDocument(); + }); +}); diff --git a/ui/litellm-dashboard/src/components/GuardrailsMonitor/LogViewer.tsx b/ui/litellm-dashboard/src/components/GuardrailsMonitor/LogViewer.tsx index 8d073feae82..2abd699ba86 100644 --- a/ui/litellm-dashboard/src/components/GuardrailsMonitor/LogViewer.tsx +++ b/ui/litellm-dashboard/src/components/GuardrailsMonitor/LogViewer.tsx @@ -1,4 +1,4 @@ -import { CircleCheck, ChevronDown, TriangleAlert, X } from "lucide-react"; +import { CircleCheck, ChevronDown, MinusCircle, TriangleAlert, X } from "lucide-react"; import { useQuery } from "@tanstack/react-query"; import moment from "moment"; import React, { useState } from "react"; @@ -10,9 +10,16 @@ import type { LogEntry as ViewLogsLogEntry } from "@/components/view_logs/column import type { LogEntry } from "./mockData"; const actionConfig: Record< - "blocked" | "passed" | "flagged", + "blocked" | "passed" | "flagged" | "not_run", { icon: React.ElementType; color: string; bg: string; border: string; label: string } > = { + not_run: { + icon: MinusCircle, + color: "text-muted-foreground", + bg: "bg-muted", + border: "border-border", + label: "Not run", + }, blocked: { icon: X, color: "text-destructive", @@ -92,7 +99,8 @@ export function LogViewer({ enabled: Boolean(accessToken && selectedRequestId && drawerOpen), }); - const selectedLog: ViewLogsLogEntry | null = fullLogResponse?.data?.[0] ?? null; + const selectedLog: ViewLogsLogEntry | null = + fullLogResponse?.data?.find((log) => log.request_id === selectedRequestId) ?? fullLogResponse?.data?.[0] ?? null; const handleLogClick = (log: LogEntry) => { setSelectedRequestId(log.id); diff --git a/ui/litellm-dashboard/src/components/GuardrailsMonitor/mockData.ts b/ui/litellm-dashboard/src/components/GuardrailsMonitor/mockData.ts index 2b42f7907f1..591d5cd3edd 100644 --- a/ui/litellm-dashboard/src/components/GuardrailsMonitor/mockData.ts +++ b/ui/litellm-dashboard/src/components/GuardrailsMonitor/mockData.ts @@ -10,7 +10,7 @@ export interface LogEntry { input_snippet?: string; output_snippet?: string; score?: number; - action: "blocked" | "passed" | "flagged"; + action: "blocked" | "passed" | "flagged" | "not_run"; model?: string; reason?: string; latency_ms?: number; diff --git a/ui/litellm-dashboard/src/components/ModelInfoEditForm.tsx b/ui/litellm-dashboard/src/components/ModelInfoEditForm.tsx index d56e65237eb..fb4d90b5ea2 100644 --- a/ui/litellm-dashboard/src/components/ModelInfoEditForm.tsx +++ b/ui/litellm-dashboard/src/components/ModelInfoEditForm.tsx @@ -271,6 +271,7 @@ const displayCost = (localModelData: any, field: TouchedPricingField): string => interface ModelInfoEditFormProps { localModelData: any; modelData: { model_info: { team_id?: string | null } & Record }; + teamAlias: string | null; accessToken: string | null; isEditing: boolean; isSaving: boolean; @@ -341,6 +342,7 @@ const ChipList: React.FC<{ values: unknown; emptyLabel: string }> = ({ values, e const ModelInfoEditForm: React.FC = ({ localModelData, modelData, + teamAlias, accessToken, isEditing, isSaving, @@ -799,8 +801,12 @@ const ModelInfoEditForm: React.FC = ({
- Team ID - {modelData.model_info.team_id || "Not Set"} + Team + + {teamAlias + ? `${teamAlias} (${modelData.model_info.team_id})` + : modelData.model_info.team_id || "Not Set"} +
diff --git a/ui/litellm-dashboard/src/components/ModelSelect/ModelSelect.test.tsx b/ui/litellm-dashboard/src/components/ModelSelect/ModelSelect.test.tsx index 34a21122027..93a43d5e533 100644 --- a/ui/litellm-dashboard/src/components/ModelSelect/ModelSelect.test.tsx +++ b/ui/litellm-dashboard/src/components/ModelSelect/ModelSelect.test.tsx @@ -415,6 +415,139 @@ describe("ModelSelect", () => { } }); + it("should take the org model ceiling from the team when /organization/info is not readable", async () => { + const testCases = [ + { + name: "org allows all proxy models", + organizationModels: ["all-proxy-models"], + shouldShowSentinel: true, + offered: ["gpt-4", "claude-3"], + notOffered: [] as string[], + }, + { + name: "org places no ceiling at all", + organizationModels: [], + shouldShowSentinel: true, + offered: ["gpt-4", "claude-3"], + notOffered: [] as string[], + }, + { + name: "org restricts the team to one model", + organizationModels: ["gpt-4"], + shouldShowSentinel: false, + offered: ["gpt-4"], + notOffered: ["claude-3"], + }, + ]; + + for (const testCase of testCases) { + const user = userEvent.setup(); + // A team admin gets a 403 from /organization/info, so the org query never resolves. + mockUseOrganization.mockReturnValue({ data: undefined, isLoading: false } as any); + mockUseTeam.mockReturnValue({ + data: { team_id: "team-1", organization_models: testCase.organizationModels }, + isLoading: false, + } as any); + + const { unmount } = renderWithProviders( + , + ); + + await openModelList(user); + if (testCase.shouldShowSentinel) { + expectOffered("All Proxy Models"); + } else { + expectNotOffered("All Proxy Models"); + } + expectOffered("No Default Models"); + testCase.offered.forEach(expectOffered); + testCase.notOffered.forEach(expectNotOffered); + + unmount(); + } + }); + + it("should stay in the loading state while a list-seeded team is still fetching its org ceiling", () => { + mockUseOrganization.mockReturnValue({ data: undefined, isLoading: false } as any); + mockUseTeam.mockReturnValue({ + data: { team_id: "team-1", models: [] }, + isLoading: false, + isFetching: true, + } as any); + + renderWithProviders( + , + ); + + expect(screen.queryAllByRole("combobox")).toHaveLength(0); + }); + + it("should not hold the loading state on a background refetch once the org ceiling is known", async () => { + const user = userEvent.setup(); + mockUseOrganization.mockReturnValue({ data: undefined, isLoading: false } as any); + mockUseTeam.mockReturnValue({ + data: { team_id: "team-1", organization_models: ["all-proxy-models"] }, + isLoading: false, + isFetching: true, + } as any); + + renderWithProviders( + , + ); + + await openModelList(user); + expectOffered("All Proxy Models"); + }); + + it("should offer no models for an org team when neither the team nor the org reports a ceiling", async () => { + const testCases = [ + { name: "/team/info withheld the ceiling", team: { team_id: "team-1", organization_models: null } }, + { name: "/team/info failed after the list seeded the team", team: { team_id: "team-1", models: [] } }, + ]; + + for (const testCase of testCases) { + const user = userEvent.setup(); + mockUseOrganization.mockReturnValue({ data: undefined, isLoading: false } as any); + mockUseTeam.mockReturnValue({ data: testCase.team, isLoading: false, isFetching: false } as any); + + const { unmount } = renderWithProviders( + , + ); + + await openModelList(user); + expectNotOffered("All Proxy Models"); + expectOffered("No Default Models"); + expectNotOffered("gpt-4"); + expectNotOffered("claude-3"); + + unmount(); + } + }); + it("should use custom dataTestId when provided", async () => { renderWithProviders( + organizationModels.length === 0 || organizationModels.includes(MODEL_SELECT_ALL_PROXY_MODELS_SPECIAL_VALUE.value); + +// useTeam seeds from the team list, which omits organization_models; /team/info is the only source of the org ceiling. +const isAwaitingOrganizationModels = (team: Team | undefined, isFetchingTeam: boolean) => + isFetchingTeam && team !== undefined && team.organization_models === undefined; + const contextFilters: Record string[]> = { user: ({ allProxyModels, userModels, options }) => { if (!userModels) return []; @@ -82,18 +89,10 @@ const contextFilters: Record { - if (selectedOrganization) { - if ( - selectedOrganization.models.includes(MODEL_SELECT_ALL_PROXY_MODELS_SPECIAL_VALUE.value) || - selectedOrganization.models.length === 0 - ) { - return allProxyModels; - } - return allProxyModels.filter((model) => selectedOrganization.models.includes(model)); - } - - return allProxyModels ?? []; + team: ({ allProxyModels, organizationID, organizationModels }) => { + if (organizationModels === undefined) return organizationID ? [] : allProxyModels; + if (isUncappedModelCeiling(organizationModels)) return allProxyModels; + return allProxyModels.filter((model) => organizationModels.includes(model)); }, organization: ({ allProxyModels }) => { @@ -108,7 +107,7 @@ const contextFilters: Record { const deduplicatedProxyModels = Array.from(new Map(allProxyModels.map((m) => [m.id, m])).values()).map( (model) => model.id, @@ -118,7 +117,13 @@ const filterModels = ( const filterFn = contextFilters[ctx.context]; if (!filterFn) return []; - return filterFn({ allProxyModels: deduplicatedProxyModels, ...extra, options: ctx.options }); + const filterArgs: FilterContextArgs = { + allProxyModels: deduplicatedProxyModels, + organizationID: ctx.organizationID, + ...extra, + options: ctx.options, + }; + return filterFn(filterArgs); }; export const ModelSelect = (props: ModelSelectProps) => { @@ -126,16 +131,17 @@ export const ModelSelect = (props: ModelSelectProps) => { const { id, teamID, organizationID, options, context, dataTestId, value = [], onChange, style } = props; const { showAllProxyModelsOverride, includeSpecialOptions } = options || {}; const { data: allProxyModels, isLoading: isLoadingAllProxyModels } = useAllProxyModels(); - const { data: team, isLoading: isLoadingTeam } = useTeam(teamID); + const { data: team, isLoading: isLoadingTeam, isFetching: isFetchingTeam } = useTeam(teamID); const { data: organization, isLoading: isLoadingOrganization } = useOrganization(organizationID); const { data: currentUser, isLoading: isCurrentUserLoading } = useCurrentUser(); const isSpecialOption = (value: string) => MODEL_SENTINEL_OPTIONS.some((sv) => sv.value === value); const hasSpecialOptionSelected = value.some(isSpecialOption); - const isLoading = isLoadingAllProxyModels || isLoadingTeam || isLoadingOrganization || isCurrentUserLoading; - const organizationHasAllProxyModels = - organization?.models.includes(MODEL_SELECT_ALL_PROXY_MODELS_SPECIAL_VALUE.value) || - organization?.models.length === 0; + const isTeamPending = isLoadingTeam || isAwaitingOrganizationModels(team, isFetchingTeam); + const isLoading = isLoadingAllProxyModels || isTeamPending || isLoadingOrganization || isCurrentUserLoading; + // The org's ceiling rides on /team/info, which a team admin may read; /organization/info 403s for them. + const organizationModels = team?.organization_models ?? organization?.models; + const organizationHasAllProxyModels = organizationModels !== undefined && isUncappedModelCeiling(organizationModels); const shouldShowAllProxyModels = showAllProxyModelsOverride || (organizationHasAllProxyModels && includeSpecialOptions) || context === "global"; @@ -159,8 +165,7 @@ export const ModelSelect = (props: ModelSelectProps) => { }; const filteredModels = filterModels(allProxyModels?.data ?? [], props, { - selectedTeam: team, - selectedOrganization: organization, + organizationModels, userModels: currentUser?.models, }); diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/KeyActivityPanel.test.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/KeyActivityPanel.test.tsx new file mode 100644 index 00000000000..693ac20a360 --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/components/KeyActivityPanel.test.tsx @@ -0,0 +1,71 @@ +import { fireEvent, render, screen } from "@testing-library/react"; +import { describe, expect, it, vi } from "vitest"; + +import type { ModelActivityData } from "../types"; +import KeyActivityPanel from "./KeyActivityPanel"; + +vi.mock("@/components/activity_metrics", () => ({ + ActivityMetrics: ({ modelMetrics }: { modelMetrics: Record }) => ( +
    + {Object.keys(modelMetrics).map((hash) => ( +
  • {hash}
    • + ))} +
+ ), +})); + +function activity(label: string, user_email: string | null, user_id: string | null): ModelActivityData { + return { + label, + key_metadata: { key_alias: label, team_id: "team-1", user_id, user_email }, + total_requests: 1, + total_successful_requests: 1, + total_failed_requests: 0, + total_cache_read_input_tokens: 0, + total_cache_creation_input_tokens: 0, + total_tokens: 10, + prompt_tokens: 5, + completion_tokens: 5, + total_spend: 0.01, + top_api_keys: [], + top_models: [], + daily_data: [], + }; +} + +const keyMetrics: Record = { + "hash-alice": activity("alice-key", "alice@example.com", "user-alice"), + "hash-bob": activity("bob-key", "bob@example.com", "user-bob"), +}; + +describe("KeyActivityPanel", () => { + it("renders every key and the full count before searching", () => { + render(); + expect(screen.getByTestId("rendered-keys")).toHaveTextContent("hash-alicehash-bob"); + expect(screen.getByText("Showing 2 of 2 keys")).toBeInTheDocument(); + }); + + it("narrows the rendered keys to those matching the user email", () => { + render(); + fireEvent.change(screen.getByLabelText("Search keys"), { target: { value: "bob@example.com" } }); + expect(screen.getByTestId("rendered-keys")).toHaveTextContent("hash-bob"); + expect(screen.getByTestId("rendered-keys")).not.toHaveTextContent("hash-alice"); + expect(screen.getByText("Showing 1 of 2 keys")).toBeInTheDocument(); + }); + + it("shows an empty state instead of zeroed metrics when nothing matches", () => { + render(); + fireEvent.change(screen.getByLabelText("Search keys"), { target: { value: "carol" } }); + expect(screen.queryByTestId("rendered-keys")).not.toBeInTheDocument(); + expect(screen.getByText('No keys match "carol" in this date range')).toBeInTheDocument(); + }); + + it("clears the search and restores every key", () => { + render(); + fireEvent.change(screen.getByLabelText("Search keys"), { target: { value: "user-alice" } }); + expect(screen.getByTestId("rendered-keys")).toHaveTextContent("hash-alice"); + fireEvent.click(screen.getByLabelText("Clear key search")); + expect(screen.getByLabelText("Search keys")).toHaveValue(""); + expect(screen.getByTestId("rendered-keys")).toHaveTextContent("hash-alicehash-bob"); + }); +}); diff --git a/ui/litellm-dashboard/src/components/UsagePage/components/KeyActivityPanel.tsx b/ui/litellm-dashboard/src/components/UsagePage/components/KeyActivityPanel.tsx new file mode 100644 index 00000000000..8287a04d0c7 --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/components/KeyActivityPanel.tsx @@ -0,0 +1,58 @@ +import { Search, X } from "lucide-react"; +import React, { useMemo, useState } from "react"; + +import { ActivityMetrics } from "@/components/activity_metrics"; +import { InputGroup, InputGroupAddon, InputGroupButton, InputGroupInput } from "@/components/ui/input-group"; + +import { filterKeyActivity } from "../keyActivityFilter"; +import type { ModelActivityData } from "../types"; + +interface KeyActivityPanelProps { + keyMetrics: Record; + hidePromptCachingMetrics?: boolean; +} + +const KeyActivityPanel: React.FC = ({ keyMetrics, hidePromptCachingMetrics = false }) => { + const [query, setQuery] = useState(""); + const filtered = useMemo(() => filterKeyActivity(keyMetrics, query), [keyMetrics, query]); + const totalKeys = Object.keys(keyMetrics).length; + const shownKeys = Object.keys(filtered).length; + const isFiltering = query.trim() !== ""; + + return ( +
+
+ + + + + setQuery(e.target.value)} + /> + {isFiltering && ( + + setQuery("")}> + + + + )} + + + Showing {shownKeys.toLocaleString()} of {totalKeys.toLocaleString()} keys + +
+ {isFiltering && totalKeys > 0 && shownKeys === 0 ? ( +

+ No keys match "{query.trim()}" in this date range +

+ ) : ( + + )} +
+ ); +}; + +export default KeyActivityPanel; diff --git a/ui/litellm-dashboard/src/components/UsagePage/keyActivityFilter.test.ts b/ui/litellm-dashboard/src/components/UsagePage/keyActivityFilter.test.ts new file mode 100644 index 00000000000..ce181f6b0c6 --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/keyActivityFilter.test.ts @@ -0,0 +1,91 @@ +import { describe, expect, it } from "vitest"; + +import { filterKeyActivity, keyActivityMatches } from "./keyActivityFilter"; +import type { KeyMetadata, ModelActivityData } from "./types"; + +function activity(label: string, key_metadata?: KeyMetadata): ModelActivityData { + return { + label, + key_metadata, + total_requests: 1, + total_successful_requests: 1, + total_failed_requests: 0, + total_cache_read_input_tokens: 0, + total_cache_creation_input_tokens: 0, + total_tokens: 10, + prompt_tokens: 5, + completion_tokens: 5, + total_spend: 0.01, + top_api_keys: [], + top_models: [], + daily_data: [], + }; +} + +const aliceMeta: KeyMetadata = { + key_alias: "alice-batch", + team_id: "team-research", + user_id: "user-alice-1234", + user_email: "alice@example.com", +}; +const bobMeta: KeyMetadata = { + key_alias: null, + team_id: "team-research", + user_id: "user-bob-5678", + user_email: "bob@example.com", +}; +const alice = activity("alice-batch (team: research)", aliceMeta); +const bob = activity("bob@example.com (team: research)", bobMeta); +const orphan = activity("key-hash-deadbeef", { key_alias: null, team_id: null }); + +const keyMetrics: Record = { + "hash-alice": alice, + "hash-bob": bob, + deadbeef: orphan, +}; + +describe("keyActivityMatches", () => { + it("matches every key on an empty or whitespace query", () => { + expect(keyActivityMatches("deadbeef", orphan, "")).toBe(true); + expect(keyActivityMatches("deadbeef", orphan, " ")).toBe(true); + }); + + it("matches key alias case-insensitively", () => { + expect(keyActivityMatches("hash-alice", alice, "ALICE-batch")).toBe(true); + expect(keyActivityMatches("hash-bob", bob, "alice-batch")).toBe(false); + }); + + it("matches user email", () => { + expect(keyActivityMatches("hash-bob", bob, "bob@example")).toBe(true); + expect(keyActivityMatches("hash-alice", alice, "bob@example")).toBe(false); + }); + + it("matches user id", () => { + expect(keyActivityMatches("hash-alice", alice, "user-alice-1234")).toBe(true); + expect(keyActivityMatches("hash-bob", bob, "user-alice-1234")).toBe(false); + }); + + it("matches the key hash when the key has no alias or user metadata", () => { + expect(keyActivityMatches("deadbeef", orphan, "dead")).toBe(true); + expect(keyActivityMatches("deadbeef", orphan, "alice")).toBe(false); + }); + + it("trims surrounding whitespace from the query", () => { + expect(keyActivityMatches("hash-alice", alice, " alice@example.com ")).toBe(true); + }); +}); + +describe("filterKeyActivity", () => { + it("returns the same object when the query is blank", () => { + expect(filterKeyActivity(keyMetrics, "")).toBe(keyMetrics); + }); + + it("keeps only the keys matching the query, preserving their hashes", () => { + expect(Object.keys(filterKeyActivity(keyMetrics, "example.com"))).toEqual(["hash-alice", "hash-bob"]); + expect(filterKeyActivity(keyMetrics, "user-bob")).toEqual({ "hash-bob": bob }); + }); + + it("returns an empty record when nothing matches", () => { + expect(filterKeyActivity(keyMetrics, "nobody")).toEqual({}); + }); +}); diff --git a/ui/litellm-dashboard/src/components/UsagePage/keyActivityFilter.ts b/ui/litellm-dashboard/src/components/UsagePage/keyActivityFilter.ts new file mode 100644 index 00000000000..1e9a654fb2e --- /dev/null +++ b/ui/litellm-dashboard/src/components/UsagePage/keyActivityFilter.ts @@ -0,0 +1,20 @@ +import type { ModelActivityData } from "./types"; + +export function keyActivityMatches(apiKey: string, data: ModelActivityData, query: string): boolean { + const needle = query.trim().toLowerCase(); + if (needle === "") return true; + const meta = data.key_metadata; + return [apiKey, data.label, meta?.key_alias, meta?.user_id, meta?.user_email].some( + (field) => field?.toLowerCase().includes(needle) ?? false, + ); +} + +export function filterKeyActivity( + keyMetrics: Record, + query: string, +): Record { + if (query.trim() === "") return keyMetrics; + return Object.fromEntries( + Object.entries(keyMetrics).filter(([apiKey, data]) => keyActivityMatches(apiKey, data, query)), + ); +} diff --git a/ui/litellm-dashboard/src/components/UsagePage/types.ts b/ui/litellm-dashboard/src/components/UsagePage/types.ts index a10e9e68c4d..fd4f1350020 100644 --- a/ui/litellm-dashboard/src/components/UsagePage/types.ts +++ b/ui/litellm-dashboard/src/components/UsagePage/types.ts @@ -46,6 +46,7 @@ export interface KeyMetricWithMetadata { export interface KeyMetadata { key_alias: string | null; team_id: string | null; + user_id?: string | null; user_email?: string | null; tags?: { tag: string; usage: number }[]; } @@ -70,6 +71,7 @@ export interface TopModelData { export interface ModelActivityData { label: string; + key_metadata?: KeyMetadata; total_requests: number; total_successful_requests: number; total_failed_requests: number; diff --git a/ui/litellm-dashboard/src/components/activity_metrics.test.tsx b/ui/litellm-dashboard/src/components/activity_metrics.test.tsx index b0fc8dc7866..914fe1872b6 100644 --- a/ui/litellm-dashboard/src/components/activity_metrics.test.tsx +++ b/ui/litellm-dashboard/src/components/activity_metrics.test.tsx @@ -655,6 +655,23 @@ describe("processActivityData", () => { expect(result["key1"].label).toBe("test-key-1 (team_id: team1)"); }); + it("retains the api key metadata so key activity can be searched by user", () => { + const metadata = { key_alias: "test-key-1", team_id: "team1", user_id: "user-1", user_email: "user1@example.com" }; + const withUser: { results: DailyData[] } = { + results: [ + createMockDailyData("2025-01-01", mockDailyActivity.results[0].metrics, { + ...EMPTY_BREAKDOWN, + api_keys: { key1: createMockKeyMetricWithMetadata(metadata, mockDailyActivity.results[0].metrics) }, + }), + ], + }; + + const result = processActivityData(withUser, "api_keys", MOCK_TEAMS); + + expect(result["key1"].key_metadata).toEqual(metadata); + expect(processActivityData(withUser, "models")["key1"]).toBeUndefined(); + }); + it("should process data for models key with data", () => { const dailyActivityWithModels: { results: DailyData[] } = { results: [ diff --git a/ui/litellm-dashboard/src/components/activity_metrics.tsx b/ui/litellm-dashboard/src/components/activity_metrics.tsx index f4348fb65ae..7c40a91be29 100644 --- a/ui/litellm-dashboard/src/components/activity_metrics.tsx +++ b/ui/litellm-dashboard/src/components/activity_metrics.tsx @@ -461,6 +461,7 @@ export const processActivityData = ( : key === "entities" ? (modelData as any).metadata?.agent_name || (modelData as any).metadata?.team_alias || model : model, + ...(key === "api_keys" ? { key_metadata: (modelData as KeyMetricWithMetadata).metadata } : {}), total_requests: 0, total_successful_requests: 0, total_failed_requests: 0, diff --git a/ui/litellm-dashboard/src/components/key_team_helpers/key_list.tsx b/ui/litellm-dashboard/src/components/key_team_helpers/key_list.tsx index a6cc940c7fd..d92e23af078 100644 --- a/ui/litellm-dashboard/src/components/key_team_helpers/key_list.tsx +++ b/ui/litellm-dashboard/src/components/key_team_helpers/key_list.tsx @@ -27,6 +27,8 @@ export interface Team { access_group_models?: string[]; access_group_mcp_server_ids?: string[]; access_group_agent_ids?: string[]; + // Parent org's model ceiling. undefined = no org / not loaded; [] or ["all-proxy-models"] = no ceiling. + organization_models?: string[] | null; } export interface KeyResponse { diff --git a/ui/litellm-dashboard/src/components/model_info_view.test.tsx b/ui/litellm-dashboard/src/components/model_info_view.test.tsx index 3db9418dfb9..f714b8e5c4a 100644 --- a/ui/litellm-dashboard/src/components/model_info_view.test.tsx +++ b/ui/litellm-dashboard/src/components/model_info_view.test.tsx @@ -42,6 +42,11 @@ vi.mock("@/app/(dashboard)/hooks/models/useModelCostMap", () => ({ useModelCostMap: (...args: any[]) => mockUseModelCostMap(...args), })); +const mockUseTeams = vi.fn(); +vi.mock("@/app/(dashboard)/hooks/teams/useTeams", () => ({ + useTeams: () => mockUseTeams(), +})); + const mockUsePtuCostAttributionEnabled = vi.fn(); vi.mock("@/app/(dashboard)/hooks/uiSettings/usePtuCostAttributionEnabled", () => ({ usePtuCostAttributionEnabled: () => mockUsePtuCostAttributionEnabled(), @@ -102,6 +107,7 @@ describe("ModelInfoView", () => { }); vi.clearAllMocks(); mockUsePtuCostAttributionEnabled.mockReturnValue(false); + mockUseTeams.mockReturnValue({ data: undefined, isLoading: false, error: null }); mockUseModelsInfo.mockReturnValue({ data: { @@ -1305,6 +1311,78 @@ describe("ModelInfoView", () => { }); }); + describe("team alias", () => { + const teamModel = { + ...defaultModelData, + model_info: { ...defaultModelData.model_info, team_id: "team-1" }, + }; + + beforeEach(() => { + mockUseModelsInfo.mockReturnValue({ data: { data: [teamModel] }, isLoading: false, error: null }); + mockModelInfoV1Call.mockResolvedValue({ data: [teamModel] }); + }); + + const readRawJson = async (user: ReturnType) => { + await user.click(await screen.findByRole("tab", { name: /raw json/i })); + const pre = await screen.findByText(/"model_name": "GPT-4"/, { selector: "pre" }); + return JSON.parse(pre.textContent ?? ""); + }; + + it("shows the team alias next to the team id and adds team_alias to the raw JSON", async () => { + mockUseTeams.mockReturnValue({ + data: [ + { team_id: "team-0", team_alias: "other" }, + { team_id: "team-1", team_alias: "alpha" }, + ], + isLoading: false, + error: null, + }); + const user = userEvent.setup(); + render(, { wrapper }); + + expect(await screen.findByText("alpha (team-1)")).toBeInTheDocument(); + + const raw = await readRawJson(user); + expect(raw.model_info).toMatchObject({ team_id: "team-1", team_alias: "alpha" }); + const keys = Object.keys(raw.model_info); + expect(keys.indexOf("team_alias")).toBe(keys.indexOf("team_id") + 1); + }); + + it("falls back to the bare team id when the team is not in the caller's team list", async () => { + mockUseTeams.mockReturnValue({ + data: [{ team_id: "team-0", team_alias: "other" }], + isLoading: false, + error: null, + }); + const user = userEvent.setup(); + render(, { wrapper }); + + expect(await screen.findByText("team-1")).toBeInTheDocument(); + + const raw = await readRawJson(user); + expect(raw.model_info.team_id).toBe("team-1"); + expect(raw.model_info).not.toHaveProperty("team_alias"); + }); + + it("shows Not Set and no team_alias for a model without a team", async () => { + mockUseModelsInfo.mockReturnValue({ data: { data: [defaultModelData] }, isLoading: false, error: null }); + mockModelInfoV1Call.mockResolvedValue({ data: [defaultModelData] }); + mockUseTeams.mockReturnValue({ + data: [{ team_id: "team-1", team_alias: "alpha" }], + isLoading: false, + error: null, + }); + const user = userEvent.setup(); + render(, { wrapper }); + + expect(await screen.findByText("Team")).toBeInTheDocument(); + expect(screen.queryByText(/alpha/)).not.toBeInTheDocument(); + + const raw = await readRawJson(user); + expect(raw.model_info).not.toHaveProperty("team_alias"); + }); + }); + it("renders the provider card logo from the bundled provider map", async () => { render(, { wrapper }); diff --git a/ui/litellm-dashboard/src/components/model_info_view.tsx b/ui/litellm-dashboard/src/components/model_info_view.tsx index 35afcdb2985..f25416327c0 100644 --- a/ui/litellm-dashboard/src/components/model_info_view.tsx +++ b/ui/litellm-dashboard/src/components/model_info_view.tsx @@ -169,6 +169,12 @@ export default function ModelInfoView({ // Keep modelData variable name for backwards compatibility const modelData = transformedModelData; + const teamAlias = teams?.find((team) => team.team_id === modelData?.model_info?.team_id)?.team_alias || null; + const rawModelInfoEntries = Object.entries(modelData?.model_info ?? {}).flatMap((entry) => + entry[0] === "team_id" && teamAlias ? [entry, ["team_alias", teamAlias]] : [entry], + ); + const rawModelData = modelData && { ...modelData, model_info: Object.fromEntries(rawModelInfoEntries) }; + const canEditModel = canModifyModel({ userRole, userID, isViewOnly }, teams ?? null, { teamId: modelData?.model_info?.team_id, isDbModel: modelData?.model_info?.db_model === true, @@ -765,6 +771,7 @@ export default function ModelInfoView({ - 
{JSON.stringify(modelData, null, 2)}
+ 
+                {JSON.stringify(rawModelData, null, 2)}
+
diff --git a/ui/litellm-dashboard/src/components/templates/KeyEditViewControls.tsx b/ui/litellm-dashboard/src/components/templates/KeyEditViewControls.tsx index f5d5562ccfe..39542882798 100644 --- a/ui/litellm-dashboard/src/components/templates/KeyEditViewControls.tsx +++ b/ui/litellm-dashboard/src/components/templates/KeyEditViewControls.tsx @@ -1,12 +1,15 @@ import React from "react"; -import { Control } from "react-hook-form"; +import { Control, UseFormReturn } from "react-hook-form"; import { Select, SelectContent, SelectItem, SelectTrigger, SelectValue } from "@/components/ui/select"; +import { Textarea } from "@/components/ui/textarea"; import { Tooltip, TooltipContent, TooltipTrigger } from "@/components/ui/tooltip"; import { CircleHelp } from "lucide-react"; import { FormField } from "@/components/shared/form/FormField"; +import { toast } from "@/lib/toast"; import AgentSelector from "../agent_management/AgentSelector"; import NumericalInput from "../shared/numerical_input"; import SkillSelector from "../skills/SkillSelector"; +import { moveTagsOutOfMetadataJson } from "./keyEditFieldNormalizers"; import { AgentsAndGroups, KeyEditFormValues } from "./keyEditFormValues"; export const labelWithHint = (label: React.ReactNode, hint: string): React.ReactNode => ( @@ -85,6 +88,42 @@ export const KeyAgentAndSkillFields = ({ ); +type KeyEditForm = Pick< + UseFormReturn, + "control" | "getValues" | "setValue" +>; + +export const moveMetadataTagsToTagsField = (form: KeyEditForm): void => { + const moved = moveTagsOutOfMetadataJson(form.getValues("metadata"), form.getValues("tags")); + if (moved === null) return; + form.setValue("metadata", moved.metadata, { shouldDirty: true }); + form.setValue("tags", moved.tags, { shouldDirty: true }); + if (moved.movedTags.length > 0) { + toast.info(`Moved ${moved.movedTags.join(", ")} from metadata to the Tags field`); + } +}; + +export const KeyMetadataField = ({ form }: { form: KeyEditForm }) => ( + + {(field) => ( +