diff --git a/.circleci/config.yml b/.circleci/config.yml index 84d8f48b4be..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" @@ -2912,7 +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 "$(docker ps -aq --filter name=postgres-db --filter name=redis-cache)" + - store_test_results: + path: test-results + - store_artifacts: + path: test-results + workflows: + integration: + jobs: + - integration_contracts: + name: integration-<< matrix.suite >> + matrix: + parameters: + suite: [management, accounting, providers] + filters: + branches: + only: + - main + - /litellm_.*/ build_and_test: jobs: - using_litellm_on_windows: @@ -2921,6 +2986,7 @@ workflows: only: - main - /litellm_.*/ + - provider_replay_harness - base_sdk_install: filters: *main_branches - local_testing_part1: diff --git a/.circleci/scripts/run_integration.sh b/.circleci/scripts/run_integration.sh new file mode 100644 index 00000000000..9fd2e7c32df --- /dev/null +++ b/.circleci/scripts/run_integration.sh @@ -0,0 +1,142 @@ +#!/usr/bin/env bash +set -euo pipefail + +suite="${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/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/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/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/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/__init__.py b/litellm/__init__.py index ccfbf80369f..261457d6889 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -538,7 +538,7 @@ context_window_fallbacks: Optional[List] = None content_policy_fallbacks: Optional[List] = None allowed_fails: int = 3 allow_dynamic_callback_disabling: bool = True -num_retries_per_request: Optional[int] = None # for the request overall (incl. fallbacks + model retries) +num_retries_per_request: Optional[int] = None # cap on Router retries of one model group; resets per fallback hop ####### SECRET MANAGERS ##################### secret_manager_client: Optional[Any] = ( None # list of instantiated key management clients - e.g. azure kv, infisical, etc. 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 d0cefcb6086..b4b2b1a334c 100644 --- a/litellm/caching/redis_cache.py +++ b/litellm/caching/redis_cache.py @@ -15,6 +15,7 @@ import hashlib import inspect import json import logging +import threading import time from collections.abc import Awaitable, Callable, Iterator, Sequence from contextvars import ContextVar @@ -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 @@ -340,7 +342,7 @@ def _explicit_causes(exc: BaseException) -> Iterator[BaseException]: current = current.__cause__ -def _is_redis_timeout_failure(exc: BaseException) -> bool: +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 @@ -414,7 +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) @@ -422,13 +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) @@ -475,7 +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 @@ -492,7 +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 @@ -801,10 +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 @@ -1010,11 +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 @@ -1062,10 +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) @@ -1112,7 +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) @@ -1149,10 +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) @@ -1191,8 +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) @@ -1235,10 +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 @@ -1274,10 +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) @@ -1359,10 +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 @@ -1448,7 +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]: @@ -1526,7 +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 @@ -1645,7 +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 @@ -1870,9 +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 @@ -1949,7 +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( @@ -2017,9 +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 @@ -2095,7 +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( @@ -2206,8 +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 5751e6e46af..c106be688e4 100644 --- a/litellm/constants.py +++ b/litellm/constants.py @@ -227,6 +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) @@ -311,6 +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 @@ -461,6 +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 diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index f5319776213..3dc6d81256b 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -2278,6 +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, @@ -2337,7 +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"] 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/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..6e76bf9d49e 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 + attempted_retries: Final = metadata.get("attempted_retries") + return type(attempted_retries) is int and 0 < attempted_retries and num_retries_per_request <= attempted_retries + + 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/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/llm_cost_calc/utils.py b/litellm/litellm_core_utils/llm_cost_calc/utils.py index 8fc428b38ae..88ea4b602cc 100644 --- a/litellm/litellm_core_utils/llm_cost_calc/utils.py +++ b/litellm/litellm_core_utils/llm_cost_calc/utils.py @@ -956,12 +956,16 @@ def _calculate_input_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" @@ -970,7 +974,9 @@ 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" 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 e3f8786a39a..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 @@ -1153,6 +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..656e9978eff 100644 --- a/litellm/llms/anthropic/chat/guardrail_translation/handler.py +++ b/litellm/llms/anthropic/chat/guardrail_translation/handler.py @@ -44,6 +44,7 @@ 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, @@ -570,6 +571,8 @@ 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) # Step 3: Map guardrail responses back to original message structure await self._apply_guardrail_responses_to_input( messages=messages, 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/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/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/openai/chat/guardrail_translation/handler.py b/litellm/llms/openai/chat/guardrail_translation/handler.py index e8179e9921e..332285722e1 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, 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/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 89d582db151..9f91cf82f41 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -11216,12 +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, @@ -13286,7 +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", @@ -13334,7 +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, @@ -13493,7 +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", @@ -13567,7 +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", @@ -13603,7 +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, @@ -13780,7 +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", @@ -13817,7 +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", @@ -13892,7 +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", @@ -13970,7 +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", @@ -14011,7 +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", @@ -14052,7 +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", @@ -14092,7 +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", @@ -19361,12 +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, @@ -22413,15 +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, @@ -22430,14 +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, @@ -22532,14 +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, @@ -22548,14 +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, @@ -22634,14 +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, @@ -22650,14 +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, @@ -22783,14 +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, @@ -22799,14 +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, @@ -22882,15 +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, @@ -22946,14 +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, @@ -22962,14 +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, @@ -23008,14 +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, @@ -23040,14 +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, @@ -23086,14 +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, @@ -23102,14 +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, @@ -23125,7 +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, @@ -23374,26 +23434,28 @@ "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", @@ -23406,6 +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 }, @@ -23462,14 +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, @@ -23507,6 +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, @@ -23526,6 +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, @@ -23544,6 +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, @@ -23563,6 +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, @@ -23582,6 +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, @@ -23592,15 +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", @@ -23669,13 +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", @@ -23736,8 +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", @@ -23747,7 +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", @@ -23780,6 +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": { @@ -23787,6 +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, @@ -23796,8 +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", @@ -23828,10 +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, @@ -23840,8 +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", @@ -23909,9 +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, @@ -23920,7 +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", @@ -23987,9 +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, @@ -23999,6 +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", @@ -24073,6 +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, @@ -24092,7 +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", @@ -24134,7 +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, @@ -24149,7 +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", @@ -24188,6 +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, @@ -24200,7 +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", @@ -24222,8 +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", @@ -24233,7 +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", @@ -24266,6 +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": { @@ -24417,7 +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" ], @@ -24448,7 +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, @@ -24548,6 +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", @@ -24557,7 +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" @@ -24587,7 +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", @@ -24662,7 +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", @@ -24696,13 +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, @@ -24813,7 +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", @@ -24822,7 +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", @@ -24859,7 +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, @@ -24875,7 +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", @@ -24938,7 +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", @@ -24995,7 +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", @@ -25052,7 +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", @@ -25109,7 +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", @@ -25143,13 +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, @@ -25214,13 +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" ], @@ -25427,7 +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" @@ -25453,10 +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, @@ -25467,25 +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, @@ -25497,17 +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 }, @@ -25539,10 +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, @@ -25555,10 +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, @@ -27141,7 +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", @@ -27151,7 +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", @@ -27189,7 +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, @@ -27202,7 +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" ], @@ -27235,7 +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", @@ -27298,7 +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", @@ -27355,7 +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", @@ -27412,7 +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", @@ -28870,6 +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, @@ -28878,12 +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, @@ -28893,12 +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, @@ -28926,7 +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, @@ -28981,12 +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, @@ -29027,12 +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, @@ -29076,6 +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", @@ -29118,6 +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", @@ -29160,6 +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", @@ -29202,6 +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", @@ -29240,6 +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", @@ -29277,6 +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", @@ -29313,6 +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, @@ -29335,6 +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, @@ -29357,6 +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, @@ -29380,6 +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, @@ -29454,6 +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", @@ -29490,6 +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" ], @@ -29524,6 +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", @@ -29561,6 +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", @@ -29598,6 +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", @@ -29659,7 +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, @@ -29687,7 +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, @@ -29708,6 +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, @@ -29856,15 +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" ], @@ -29996,7 +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, @@ -30006,7 +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" ], @@ -30021,7 +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" ], @@ -30034,7 +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" @@ -30481,6 +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", @@ -30489,6 +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": { @@ -30496,6 +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", @@ -30525,6 +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, @@ -30565,11 +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, @@ -30610,6 +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 }, @@ -30661,6 +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, @@ -30702,11 +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, @@ -30748,6 +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 }, @@ -30841,17 +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" @@ -30880,17 +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" @@ -30956,6 +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", @@ -31092,6 +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", @@ -31160,6 +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", @@ -31227,6 +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", @@ -31290,7 +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 }, @@ -31460,7 +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" @@ -31539,7 +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, @@ -31596,7 +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, @@ -31619,6 +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" @@ -31667,6 +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" @@ -31744,7 +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, @@ -31796,7 +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, @@ -31845,7 +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, @@ -31894,7 +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, @@ -31945,6 +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 }, @@ -31997,6 +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 }, @@ -32046,6 +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 }, @@ -32095,6 +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 }, @@ -32113,6 +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" @@ -32155,6 +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" @@ -32187,6 +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", @@ -32195,6 +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": { @@ -32202,6 +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", @@ -32526,6 +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" ], @@ -32556,6 +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", @@ -32564,6 +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": { @@ -32571,6 +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", @@ -32604,6 +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", @@ -32612,6 +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": { @@ -32619,6 +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", @@ -32650,6 +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", @@ -32658,12 +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", @@ -32696,6 +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", @@ -32704,12 +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", @@ -32742,9 +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" @@ -32755,9 +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" @@ -32778,6 +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" ], @@ -32811,6 +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" ], @@ -32844,6 +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" ], @@ -32879,6 +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" ], @@ -32914,6 +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" ], @@ -32939,6 +33238,7 @@ "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, @@ -32947,6 +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" ], @@ -32981,6 +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" ], @@ -37700,12 +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, @@ -37720,12 +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, @@ -37747,6 +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" @@ -37780,6 +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" @@ -37807,6 +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", @@ -37815,6 +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": { @@ -37822,6 +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", @@ -37851,6 +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", @@ -37859,6 +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": { @@ -37866,6 +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", @@ -37975,12 +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, @@ -37993,12 +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, @@ -38022,6 +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" @@ -38059,6 +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" @@ -38082,10 +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", @@ -38094,6 +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": { @@ -38101,6 +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, @@ -38113,10 +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", @@ -38125,6 +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": { @@ -38132,6 +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, @@ -43294,7 +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, @@ -43305,7 +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, @@ -43314,7 +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, @@ -43485,7 +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", @@ -43497,7 +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", @@ -43544,7 +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, @@ -43606,7 +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, @@ -43630,7 +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, @@ -43664,6 +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, @@ -43686,6 +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, @@ -43697,6 +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, @@ -43713,7 +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", @@ -43725,7 +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", @@ -43733,6 +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, @@ -43759,7 +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, @@ -43773,7 +44110,7 @@ "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, @@ -43793,7 +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, @@ -43809,7 +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, @@ -43826,7 +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, @@ -43874,7 +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, @@ -43890,7 +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, @@ -43904,7 +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, @@ -43919,7 +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, @@ -43944,7 +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, @@ -43959,7 +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": { @@ -43970,7 +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": { @@ -43980,7 +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, @@ -43990,7 +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": { @@ -44000,7 +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, @@ -44010,7 +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, @@ -44042,7 +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, @@ -44067,7 +44404,7 @@ "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, @@ -44103,7 +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": { @@ -44115,7 +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, @@ -44136,7 +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, @@ -44154,7 +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, @@ -44180,7 +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, @@ -44196,7 +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": { @@ -44208,7 +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, @@ -44225,7 +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, @@ -44242,7 +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, @@ -44255,6 +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" ] @@ -44263,6 +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" ] @@ -47605,6 +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, @@ -47614,8 +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", @@ -47647,10 +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, @@ -47659,9 +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, @@ -47680,9 +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, @@ -47691,8 +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, @@ -47710,9 +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, @@ -47722,6 +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", @@ -47796,6 +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, @@ -47816,7 +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", @@ -47858,7 +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, @@ -47874,7 +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", @@ -47913,6 +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, @@ -47925,7 +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", @@ -49588,7 +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, @@ -52685,10 +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, @@ -52753,7 +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, @@ -54652,12 +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" ], @@ -54670,12 +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" ], @@ -54690,24 +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" ] @@ -54726,6 +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, @@ -54753,6 +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, @@ -54780,6 +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" ], @@ -54831,13 +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" @@ -54855,7 +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" @@ -54869,7 +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" @@ -54894,11 +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" @@ -57373,7 +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" @@ -57388,10 +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" @@ -57406,10 +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" @@ -57423,13 +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" ], @@ -57457,7 +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, @@ -57518,7 +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, @@ -57716,8 +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 } @@ -57725,6 +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 @@ -57740,8 +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 } @@ -57757,6 +58144,7 @@ { "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 @@ -57870,6 +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", @@ -57972,14 +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, @@ -57988,14 +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, @@ -58011,26 +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, @@ -58039,14 +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, @@ -58055,14 +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, @@ -58078,7 +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 @@ -58117,19 +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, @@ -58180,12 +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, @@ -58201,7 +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, @@ -58233,7 +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, @@ -58249,7 +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, @@ -58281,7 +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, @@ -58290,12 +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, @@ -58311,7 +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, @@ -58348,7 +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, @@ -61046,14 +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, @@ -61062,13 +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, @@ -61096,7 +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, @@ -61120,7 +61539,7 @@ "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", @@ -61130,7 +61549,7 @@ "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/moonshotai/Kimi-K2.5-fp4": { "input_cost_per_token": 5e-07, @@ -61138,7 +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, @@ -61147,7 +61566,7 @@ "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", @@ -61156,7 +61575,7 @@ "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", @@ -61166,7 +61585,7 @@ "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, @@ -61174,7 +61593,7 @@ "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", @@ -61183,7 +61602,7 @@ "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/Qwen/Qwen3-VL-32B-Instruct": { "deprecation_date": "2026-02-25", @@ -61192,7 +61611,7 @@ "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/Qwen/Qwen3-VL-8B-Instruct": { "deprecation_date": "2026-04-16", @@ -61201,7 +61620,7 @@ "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/mistralai/Ministral-3-14B-Instruct-2512": { "input_cost_per_token": 2e-07, @@ -61209,7 +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, @@ -61217,7 +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, @@ -61225,7 +61644,7 @@ "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", @@ -61234,7 +61653,7 @@ "litellm_provider": "together_ai", "max_input_tokens": 131072, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "cerebras/gemma-4-31b": { "input_cost_per_token": 9.9e-07, @@ -65361,5 +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/litellm/proxy/_lazy_openapi_snapshot.json b/litellm/proxy/_lazy_openapi_snapshot.json index 7a110eff080..fb2f014e3d8 100644 --- a/litellm/proxy/_lazy_openapi_snapshot.json +++ b/litellm/proxy/_lazy_openapi_snapshot.json @@ -11503,6 +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 49e0247aad9..ffc41a9d7ae 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -887,6 +887,7 @@ 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, @@ -2635,9 +2636,13 @@ 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, @@ -4414,6 +4419,9 @@ 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): diff --git a/litellm/proxy/auth/auth_checks.py b/litellm/proxy/auth/auth_checks.py index 576585ee9a3..6d61ad4d3e8 100644 --- a/litellm/proxy/auth/auth_checks.py +++ b/litellm/proxy/auth/auth_checks.py @@ -123,6 +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 @@ -327,9 +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. @@ -880,6 +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 ( @@ -887,6 +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) @@ -936,6 +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 @@ -987,6 +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. @@ -1096,6 +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 @@ -2141,7 +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, @@ -2155,54 +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: Final[object] = await user_api_key_cache.async_get_cache(key=_key) - if cached == NO_TEAM_MEMBERSHIP_SENTINEL: - return None - cached_membership_obj: Final = CacheCodec.deserialize(cached, model_type=LiteLLM_TeamMembership) - if cached_membership_obj is not None: - return cached_membership_obj + 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 - # 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}, + 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, ) + ) + _team_membership_inflight[_key] = task - if response 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), - ) - return None + def _clear_inflight(_done: object) -> None: + if _team_membership_inflight.get(_key) is task: + _team_membership_inflight.pop(_key, 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: @@ -2375,13 +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, @@ -2668,6 +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 @@ -4122,18 +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) @@ -4169,6 +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 ( @@ -4180,6 +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( @@ -4274,6 +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. @@ -4319,6 +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 ) @@ -4334,6 +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.""" @@ -4350,6 +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) @@ -4363,7 +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]: @@ -4410,7 +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: @@ -5152,6 +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 ( @@ -5160,23 +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): @@ -5195,7 +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 @@ -5224,6 +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. @@ -5234,22 +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/resolvers/grants.py b/litellm/proxy/auth/resolvers/grants.py index eb39d2a6812..cbfe21924ec 100644 --- a/litellm/proxy/auth/resolvers/grants.py +++ b/litellm/proxy/auth/resolvers/grants.py @@ -28,11 +28,11 @@ from litellm.proxy._types import ( ) from litellm.proxy.auth.auth_checks import ( TeamNotFoundError, - UserNotFoundError, 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 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 22826f48b52..25570ab220a 100644 --- a/litellm/proxy/auth/user_api_key_auth.py +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -191,6 +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, @@ -199,6 +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, ) @@ -217,7 +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]"): @@ -1652,6 +1654,7 @@ 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: @@ -1692,6 +1695,7 @@ async def _user_api_key_auth_builder( route=route, request=request, llm_router=llm_router, + team_id=valid_token.team_id, ) ), ) @@ -2091,6 +2095,7 @@ 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: @@ -2209,6 +2214,7 @@ 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) @@ -2239,6 +2245,7 @@ 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) @@ -2734,6 +2741,7 @@ 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 @@ -2850,12 +2858,14 @@ 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) @@ -3301,6 +3311,7 @@ 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: @@ -3408,6 +3419,7 @@ 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) @@ -3449,6 +3461,7 @@ 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..cb867cf9e61 100644 --- a/litellm/proxy/client/cli/README.md +++ b/litellm/proxy/client/cli/README.md @@ -585,7 +585,9 @@ LiteLLM ████████░░░░░░░░░░░░░░ 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..5493586f627 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 @@ -348,7 +346,8 @@ 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 fc603701e44..0ad86479aac 100644 --- a/litellm/proxy/common_request_processing.py +++ b/litellm/proxy/common_request_processing.py @@ -1571,6 +1571,9 @@ 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, @@ -1598,7 +1601,7 @@ 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, @@ -3452,15 +3455,13 @@ 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/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/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/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/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/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/health_endpoints/_health_endpoints.py b/litellm/proxy/health_endpoints/_health_endpoints.py index db6ec754c6e..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, @@ -876,7 +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/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/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/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/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py index 0b7f69bbb7f..9350d2cd691 100644 --- a/litellm/proxy/management_endpoints/team_endpoints.py +++ b/litellm/proxy/management_endpoints/team_endpoints.py @@ -156,6 +156,7 @@ 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 +180,7 @@ 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 +431,26 @@ 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( @@ -4368,6 +4369,20 @@ 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: @@ -4439,7 +4454,11 @@ 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 @@ -4448,9 +4467,12 @@ 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 ## @@ -4510,7 +4532,10 @@ 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( @@ -4857,6 +4882,26 @@ 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, @@ -4867,12 +4912,16 @@ 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. """ @@ -4895,6 +4944,11 @@ 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} @@ -5026,66 +5080,72 @@ 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( @@ -5163,7 +5223,7 @@ 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, @@ -5195,6 +5255,7 @@ 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, ) @@ -5291,17 +5352,16 @@ 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( @@ -5328,33 +5388,30 @@ 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..091dccf1433 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, 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/files_endpoints.py b/litellm/proxy/openai_files_endpoints/files_endpoints.py index 07cdc33e306..ae6e222a863 100644 --- a/litellm/proxy/openai_files_endpoints/files_endpoints.py +++ b/litellm/proxy/openai_files_endpoints/files_endpoints.py @@ -78,6 +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, @@ -473,6 +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: 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/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/proxy_server.py b/litellm/proxy/proxy_server.py index d9f8e04ebda..1c931863a2f 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, @@ -365,6 +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, @@ -3450,8 +3453,10 @@ 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: @@ -7065,6 +7070,9 @@ 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") @@ -11893,6 +11901,13 @@ 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, @@ -11912,6 +11927,7 @@ 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") @@ -12015,6 +12031,9 @@ 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: @@ -12044,12 +12063,10 @@ 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) ###################################################################### @@ -15033,6 +15050,13 @@ 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"], @@ -15080,7 +15104,7 @@ 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 @@ -15128,7 +15152,7 @@ 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( @@ -15179,7 +15203,7 @@ 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 @@ -15247,7 +15271,7 @@ 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( @@ -15816,10 +15840,7 @@ 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, @@ -17036,6 +17057,7 @@ _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", diff --git a/litellm/proxy/spend_tracking/spend_tracking_utils.py b/litellm/proxy/spend_tracking/spend_tracking_utils.py index 3ef21996b9c..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, diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index c095586b6c9..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 @@ -6404,7 +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/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/router.py b/litellm/router.py index 8865543badd..1665583386f 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) @@ -8374,31 +8378,30 @@ 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 """ + 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) kwargs[_metadata_var]["previous_models"] = breadcrumbs # rebind-ok: the logging object already holds this dict return kwargs @@ -13878,6 +13881,7 @@ 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": @@ -13910,6 +13914,7 @@ 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( @@ -13987,6 +13992,11 @@ 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) @@ -14024,6 +14034,7 @@ 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 @@ -14057,6 +14068,7 @@ 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_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/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/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/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/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/router.py b/litellm/types/router.py index c7363502017..0aefc07ae4b 100644 --- a/litellm/types/router.py +++ b/litellm/types/router.py @@ -645,6 +645,7 @@ 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" @@ -868,6 +869,11 @@ 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, @@ -875,12 +881,25 @@ 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) @@ -889,6 +908,14 @@ 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/utils.py b/litellm/types/utils.py index 1d73542c9bb..2e8b20edf7a 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -283,8 +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 @@ -3583,7 +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 @@ -3761,6 +3767,16 @@ 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", diff --git a/litellm/utils.py b/litellm/utils.py index 04139a124b6..b2715b41739 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 @@ -254,6 +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"}) # +-----------------------------------------------+ # | | @@ -1260,15 +1262,6 @@ 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]]: """ @@ -1500,6 +1493,8 @@ 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() @@ -1510,12 +1505,8 @@ 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) @@ -1574,12 +1565,8 @@ 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( @@ -5819,6 +5806,14 @@ 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, @@ -5928,10 +5923,13 @@ 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), @@ -6265,7 +6263,7 @@ 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: diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 89d582db151..9f91cf82f41 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -11216,12 +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, @@ -13286,7 +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", @@ -13334,7 +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, @@ -13493,7 +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", @@ -13567,7 +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", @@ -13603,7 +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, @@ -13780,7 +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", @@ -13817,7 +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", @@ -13892,7 +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", @@ -13970,7 +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", @@ -14011,7 +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", @@ -14052,7 +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", @@ -14092,7 +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", @@ -19361,12 +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, @@ -22413,15 +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, @@ -22430,14 +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, @@ -22532,14 +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, @@ -22548,14 +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, @@ -22634,14 +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, @@ -22650,14 +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, @@ -22783,14 +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, @@ -22799,14 +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, @@ -22882,15 +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, @@ -22946,14 +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, @@ -22962,14 +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, @@ -23008,14 +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, @@ -23040,14 +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, @@ -23086,14 +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, @@ -23102,14 +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, @@ -23125,7 +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, @@ -23374,26 +23434,28 @@ "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", @@ -23406,6 +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 }, @@ -23462,14 +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, @@ -23507,6 +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, @@ -23526,6 +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, @@ -23544,6 +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, @@ -23563,6 +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, @@ -23582,6 +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, @@ -23592,15 +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", @@ -23669,13 +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", @@ -23736,8 +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", @@ -23747,7 +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", @@ -23780,6 +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": { @@ -23787,6 +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, @@ -23796,8 +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", @@ -23828,10 +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, @@ -23840,8 +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", @@ -23909,9 +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, @@ -23920,7 +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", @@ -23987,9 +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, @@ -23999,6 +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", @@ -24073,6 +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, @@ -24092,7 +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", @@ -24134,7 +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, @@ -24149,7 +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", @@ -24188,6 +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, @@ -24200,7 +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", @@ -24222,8 +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", @@ -24233,7 +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", @@ -24266,6 +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": { @@ -24417,7 +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" ], @@ -24448,7 +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, @@ -24548,6 +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", @@ -24557,7 +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" @@ -24587,7 +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", @@ -24662,7 +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", @@ -24696,13 +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, @@ -24813,7 +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", @@ -24822,7 +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", @@ -24859,7 +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, @@ -24875,7 +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", @@ -24938,7 +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", @@ -24995,7 +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", @@ -25052,7 +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", @@ -25109,7 +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", @@ -25143,13 +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, @@ -25214,13 +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" ], @@ -25427,7 +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" @@ -25453,10 +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, @@ -25467,25 +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, @@ -25497,17 +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 }, @@ -25539,10 +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, @@ -25555,10 +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, @@ -27141,7 +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", @@ -27151,7 +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", @@ -27189,7 +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, @@ -27202,7 +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" ], @@ -27235,7 +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", @@ -27298,7 +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", @@ -27355,7 +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", @@ -27412,7 +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", @@ -28870,6 +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, @@ -28878,12 +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, @@ -28893,12 +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, @@ -28926,7 +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, @@ -28981,12 +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, @@ -29027,12 +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, @@ -29076,6 +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", @@ -29118,6 +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", @@ -29160,6 +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", @@ -29202,6 +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", @@ -29240,6 +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", @@ -29277,6 +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", @@ -29313,6 +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, @@ -29335,6 +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, @@ -29357,6 +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, @@ -29380,6 +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, @@ -29454,6 +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", @@ -29490,6 +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" ], @@ -29524,6 +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", @@ -29561,6 +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", @@ -29598,6 +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", @@ -29659,7 +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, @@ -29687,7 +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, @@ -29708,6 +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, @@ -29856,15 +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" ], @@ -29996,7 +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, @@ -30006,7 +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" ], @@ -30021,7 +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" ], @@ -30034,7 +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" @@ -30481,6 +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", @@ -30489,6 +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": { @@ -30496,6 +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", @@ -30525,6 +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, @@ -30565,11 +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, @@ -30610,6 +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 }, @@ -30661,6 +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, @@ -30702,11 +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, @@ -30748,6 +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 }, @@ -30841,17 +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" @@ -30880,17 +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" @@ -30956,6 +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", @@ -31092,6 +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", @@ -31160,6 +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", @@ -31227,6 +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", @@ -31290,7 +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 }, @@ -31460,7 +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" @@ -31539,7 +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, @@ -31596,7 +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, @@ -31619,6 +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" @@ -31667,6 +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" @@ -31744,7 +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, @@ -31796,7 +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, @@ -31845,7 +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, @@ -31894,7 +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, @@ -31945,6 +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 }, @@ -31997,6 +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 }, @@ -32046,6 +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 }, @@ -32095,6 +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 }, @@ -32113,6 +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" @@ -32155,6 +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" @@ -32187,6 +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", @@ -32195,6 +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": { @@ -32202,6 +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", @@ -32526,6 +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" ], @@ -32556,6 +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", @@ -32564,6 +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": { @@ -32571,6 +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", @@ -32604,6 +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", @@ -32612,6 +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": { @@ -32619,6 +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", @@ -32650,6 +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", @@ -32658,12 +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", @@ -32696,6 +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", @@ -32704,12 +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", @@ -32742,9 +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" @@ -32755,9 +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" @@ -32778,6 +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" ], @@ -32811,6 +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" ], @@ -32844,6 +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" ], @@ -32879,6 +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" ], @@ -32914,6 +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" ], @@ -32939,6 +33238,7 @@ "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, @@ -32947,6 +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" ], @@ -32981,6 +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" ], @@ -37700,12 +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, @@ -37720,12 +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, @@ -37747,6 +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" @@ -37780,6 +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" @@ -37807,6 +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", @@ -37815,6 +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": { @@ -37822,6 +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", @@ -37851,6 +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", @@ -37859,6 +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": { @@ -37866,6 +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", @@ -37975,12 +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, @@ -37993,12 +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, @@ -38022,6 +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" @@ -38059,6 +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" @@ -38082,10 +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", @@ -38094,6 +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": { @@ -38101,6 +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, @@ -38113,10 +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", @@ -38125,6 +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": { @@ -38132,6 +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, @@ -43294,7 +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, @@ -43305,7 +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, @@ -43314,7 +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, @@ -43485,7 +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", @@ -43497,7 +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", @@ -43544,7 +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, @@ -43606,7 +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, @@ -43630,7 +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, @@ -43664,6 +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, @@ -43686,6 +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, @@ -43697,6 +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, @@ -43713,7 +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", @@ -43725,7 +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", @@ -43733,6 +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, @@ -43759,7 +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, @@ -43773,7 +44110,7 @@ "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, @@ -43793,7 +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, @@ -43809,7 +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, @@ -43826,7 +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, @@ -43874,7 +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, @@ -43890,7 +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, @@ -43904,7 +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, @@ -43919,7 +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, @@ -43944,7 +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, @@ -43959,7 +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": { @@ -43970,7 +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": { @@ -43980,7 +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, @@ -43990,7 +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": { @@ -44000,7 +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, @@ -44010,7 +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, @@ -44042,7 +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, @@ -44067,7 +44404,7 @@ "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, @@ -44103,7 +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": { @@ -44115,7 +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, @@ -44136,7 +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, @@ -44154,7 +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, @@ -44180,7 +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, @@ -44196,7 +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": { @@ -44208,7 +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, @@ -44225,7 +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, @@ -44242,7 +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, @@ -44255,6 +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" ] @@ -44263,6 +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" ] @@ -47605,6 +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, @@ -47614,8 +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", @@ -47647,10 +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, @@ -47659,9 +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, @@ -47680,9 +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, @@ -47691,8 +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, @@ -47710,9 +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, @@ -47722,6 +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", @@ -47796,6 +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, @@ -47816,7 +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", @@ -47858,7 +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, @@ -47874,7 +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", @@ -47913,6 +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, @@ -47925,7 +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", @@ -49588,7 +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, @@ -52685,10 +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, @@ -52753,7 +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, @@ -54652,12 +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" ], @@ -54670,12 +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" ], @@ -54690,24 +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" ] @@ -54726,6 +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, @@ -54753,6 +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, @@ -54780,6 +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" ], @@ -54831,13 +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" @@ -54855,7 +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" @@ -54869,7 +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" @@ -54894,11 +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" @@ -57373,7 +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" @@ -57388,10 +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" @@ -57406,10 +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" @@ -57423,13 +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" ], @@ -57457,7 +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, @@ -57518,7 +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, @@ -57716,8 +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 } @@ -57725,6 +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 @@ -57740,8 +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 } @@ -57757,6 +58144,7 @@ { "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 @@ -57870,6 +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", @@ -57972,14 +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, @@ -57988,14 +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, @@ -58011,26 +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, @@ -58039,14 +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, @@ -58055,14 +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, @@ -58078,7 +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 @@ -58117,19 +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, @@ -58180,12 +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, @@ -58201,7 +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, @@ -58233,7 +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, @@ -58249,7 +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, @@ -58281,7 +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, @@ -58290,12 +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, @@ -58311,7 +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, @@ -58348,7 +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, @@ -61046,14 +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, @@ -61062,13 +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, @@ -61096,7 +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, @@ -61120,7 +61539,7 @@ "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", @@ -61130,7 +61549,7 @@ "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/moonshotai/Kimi-K2.5-fp4": { "input_cost_per_token": 5e-07, @@ -61138,7 +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, @@ -61147,7 +61566,7 @@ "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", @@ -61156,7 +61575,7 @@ "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", @@ -61166,7 +61585,7 @@ "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, @@ -61174,7 +61593,7 @@ "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", @@ -61183,7 +61602,7 @@ "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/Qwen/Qwen3-VL-32B-Instruct": { "deprecation_date": "2026-02-25", @@ -61192,7 +61611,7 @@ "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/Qwen/Qwen3-VL-8B-Instruct": { "deprecation_date": "2026-04-16", @@ -61201,7 +61620,7 @@ "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/mistralai/Ministral-3-14B-Instruct-2512": { "input_cost_per_token": 2e-07, @@ -61209,7 +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, @@ -61217,7 +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, @@ -61225,7 +61644,7 @@ "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", @@ -61234,7 +61653,7 @@ "litellm_provider": "together_ai", "max_input_tokens": 131072, "mode": "chat", - "source": "https://api.together.xyz/v1/models" + "source": "https://api.together.ai/v1/models" }, "cerebras/gemma-4-31b": { "input_cost_per_token": 9.9e-07, @@ -65361,5 +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 d1ac3e67b2b..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 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/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/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/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..67370c98274 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): @@ -292,6 +294,22 @@ 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 +337,7 @@ 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 +432,7 @@ 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 +441,7 @@ 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: 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/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..6fca1268ebc 100644 --- a/tests/e2e/models.py +++ b/tests/e2e/models.py @@ -1091,13 +1091,13 @@ 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 +1135,7 @@ 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 +1176,7 @@ 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 +1189,7 @@ class UserUpdateBody(BaseModel): class UserInfoParams(BaseModel): - user_id: str + user_id: str | None = None class UserData(BaseModel): @@ -1240,16 +1242,36 @@ 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/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/proxy_behavior/auth/test_auth_object_prefetch.py b/tests/proxy_behavior/auth/test_auth_object_prefetch.py index 59e9585a296..cfa958500af 100644 --- a/tests/proxy_behavior/auth/test_auth_object_prefetch.py +++ b/tests/proxy_behavior/auth/test_auth_object_prefetch.py @@ -66,6 +66,7 @@ async def test_join_binds_the_membership_to_the_requested_team(prisma): 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( 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..5b06c5fdb01 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 @@ -628,17 +629,29 @@ 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, metadata_key): + """log_retry appends one flat record per failed attempt and copies neither the request kwargs nor + the request metadata into it""" router = Router(model_list=model_list) 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=litellm.RateLimitError(message="slow down", llm_provider="openai", model="gpt-3.5-turbo"), ) - 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, + } + ] 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 c1e3240adb7..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 +1205,117 @@ 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. @@ -1241,7 +1352,7 @@ async def test_pool_wait_timeout_is_a_timeout_failure_not_hard_connectivity(): 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 + from litellm.caching.redis_cache import is_redis_timeout_failure def raise_chained_from_timeout() -> None: try: @@ -1260,9 +1371,9 @@ def test_timeout_classification_follows_the_explicit_cause_chain_only(): 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 + 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: 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/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_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 2fadb1fd959..854bc9bbb81 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 @@ -74,6 +74,108 @@ 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 @@ -4560,7 +4662,7 @@ 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), ] 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 b6e656f282a..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} @@ -722,3 +869,58 @@ def test_shipped_openai_reasoning_rule_skips_non_reasoning_gpt_ids(shipped_cost_ 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_realtime_streaming.py b/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py index 2a33d84ec78..7e6d4d24905 100644 --- a/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py +++ b/tests/test_litellm/litellm_core_utils/test_realtime_streaming.py @@ -10,9 +10,9 @@ 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, ) @@ -3399,6 +3399,26 @@ async def test_refused_session_does_not_stamp_the_reservation_ownership_marker() 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 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..0882b329c49 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 @@ -2272,6 +2272,58 @@ 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 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_rejected_by_name(self): + from litellm.llms.base_llm.guardrail_translation.utils import UnappliableRequestRewrite + + 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."}], + } + 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_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/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/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/openai/chat/guardrail_translation/test_openai_guardrail_handler.py b/tests/test_litellm/llms/openai/chat/guardrail_translation/test_openai_guardrail_handler.py index 754c89d3d20..617fba587b2 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 @@ -1981,6 +1981,49 @@ class TestNoScannableContentRecordsNotRun: assert self._recorded_entries(data) == [] +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/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/proxy/auth/test_auth_checks.py b/tests/test_litellm/proxy/auth/test_auth_checks.py index ea2c925212d..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() @@ -6419,9 +6421,7 @@ async def test_get_team_membership_negative_caches_a_missing_row(): 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") - ) + 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 @@ -6454,6 +6454,314 @@ async def test_get_team_membership_reads_sentinel_as_no_membership_not_a_model() 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(): """ @@ -6477,10 +6785,7 @@ async def test_invalidate_team_member_spend_state_evicts_the_negative_cache_sent 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 - ) + 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 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_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/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..5c0cf6b5703 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 @@ -297,16 +298,31 @@ 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) + text: Final = _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)] + + 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("claude-auto · 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)) == ( 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/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/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/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/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/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 0e1831614ac..9a4badab8a9 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 @@ -14157,3 +14366,123 @@ 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 b696d9ebe5f..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 @@ -4703,6 +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) 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/proxy_server/test_proxy_config.py b/tests/test_litellm/proxy/proxy_server/test_proxy_config.py index e109b650da7..d6851116324 100644 --- a/tests/test_litellm/proxy/proxy_server/test_proxy_config.py +++ b/tests/test_litellm/proxy/proxy_server/test_proxy_config.py @@ -3469,6 +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/test_common_request_processing.py b/tests/test_litellm/proxy/test_common_request_processing.py index 69e89d1c604..812fd8ed47d 100644 --- a/tests/test_litellm/proxy/test_common_request_processing.py +++ b/tests/test_litellm/proxy/test_common_request_processing.py @@ -1402,6 +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): """ @@ -3879,6 +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 @@ -8400,6 +8478,41 @@ 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_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_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/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_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..1f0b5591c2b --- /dev/null +++ b/tests/test_litellm/rust_bridge/test_lifecycle.py @@ -0,0 +1,30 @@ +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, attempted_retries, 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_attempted_retries( + monkeypatch: pytest.MonkeyPatch, metadata_key: str, cap: int, attempted_retries: 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: {"attempted_retries": attempted_retries}} + 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_cost_calculator.py b/tests/test_litellm/test_cost_calculator.py index 68e9b6143a0..8c3436d3108 100644 --- a/tests/test_litellm/test_cost_calculator.py +++ b/tests/test_litellm/test_cost_calculator.py @@ -3909,6 +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. 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 4f7a51eb531..3dccb2b35bf 100644 --- a/tests/test_litellm/test_main.py +++ b/tests/test_litellm/test_main.py @@ -3795,3 +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_router.py b/tests/test_litellm/test_router.py index b8a0d70f5bc..3cabcd71627 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", @@ -7735,6 +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 @@ -7772,6 +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 @@ -10642,6 +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 ], @@ -10691,28 +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( @@ -10738,22 +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 @@ -10773,12 +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"}], @@ -10804,34 +11021,49 @@ 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, + ] @pytest.mark.asyncio diff --git a/tests/test_litellm/test_utils.py b/tests/test_litellm/test_utils.py index 2ace005a8e2..d5feda6f892 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"}, @@ -2944,7 +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 @@ -2966,9 +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 @@ -4062,6 +4076,51 @@ class TestMetadataNoneHandling: assert metadata == {} +_RETRY_CAP_CASES: Final = ( + pytest.param(5, {"attempted_retries": 5}, True, id="cap-above-four-reached"), + pytest.param(5, {"attempted_retries": 4}, False, id="cap-above-four-not-reached"), + pytest.param(0, {"attempted_retries": 0}, False, id="first-attempt-passes-cap-of-zero"), + pytest.param(0, {"attempted_retries": 1}, True, id="cap-of-zero-refuses-first-retry"), + 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_attempted_retries_sync(monkeypatch, metadata_key, cap, metadata, refused): + 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_attempted_retries_async(monkeypatch, metadata_key, cap, metadata, refused): + 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.""" @@ -5343,6 +5402,26 @@ 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. @@ -6444,6 +6523,53 @@ 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( diff --git a/tests/test_litellm_rust/ocr/test_lifecycle.py b/tests/test_litellm_rust/ocr/test_lifecycle.py index e7ebc5b3018..77d9ef167d0 100644 --- a/tests/test_litellm_rust/ocr/test_lifecycle.py +++ b/tests/test_litellm_rust/ocr/test_lifecycle.py @@ -806,7 +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": {"attempted_retries": 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/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)/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/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/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) => ( +