* bump: version 1.86.0 → 1.86.1
* chore: refresh uv.lock for 1.86.1
* fix(team): keep team_alias cache in sync on _cache_team_object writes (#28737)
* fix(team): keep team_alias cache in sync on _cache_team_object writes
_cache_team_object wrote only to the team_id:<id> cache key, but the
JWT auth path that uses team_alias_jwt_field reads from a separate
team_alias:<alias> key (get_team_object_by_alias caches under both
keys on miss, but reads only the alias-keyed one). After any
team-mutation endpoint (team_model_add, team_model_delete,
update_team, the two access-group writes) the team_id cache was
refreshed but the team_alias cache stayed stale until TTL — JWT
callers using team_alias_jwt_field kept seeing the pre-mutation
team for the full cache window.
Mirror the write under the alias key inside _cache_team_object so
every existing caller stays in sync without further changes. Skip
the alias write when team_alias is None/empty so we don't collide
across alias-less teams.
Surfaced testing the LIT-3244 cherry-pick on patch/1.86.0: the
LIT-3244 fix correctly invalidated the team_id cache but the
customer's JWT used team_alias_jwt_field, so they kept hitting the
stale alias-keyed entry.
* fix(team): delete (not overwrite) team_alias cache on _cache_team_object
The prior shape of this PR wrote both team_id:<id> AND team_alias:<alias>
from _cache_team_object. team_alias is NOT unique in the schema
(no @unique on LiteLLM_TeamTable.team_alias), and get_team_object_by_alias
enforces uniqueness on its own DB-fetch path (len(teams) > 1 raises).
Writing the alias-keyed cache from the generic refresh path bypassed
that check: a team admin renaming their team to collide with another
team's alias could silently overwrite the cached team for JWT-by-alias
auth, swapping the resolved team under that alias for the cache window.
Switch the alias-keyed operation from a write to a delete (mirroring
the dual-cache delete pattern in _delete_cache_key_object). After every
team write, the next JWT-by-alias reader cache-misses and falls through
to get_team_object_by_alias, which (a) re-fetches the fresh team from
DB, closing the LIT-3244 staleness gap that motivated this PR, and
(b) enforces alias uniqueness before populating either cache key.
team_id:<id> writes are unchanged — team_id is the table PK and is
guaranteed unique.
Surfaced in veria-ai review on #28739.
* fix(managed-files): anchor model_id regex so it doesn't match llm_output_file_model_id
extract_model_id_from_unified_id used `re.search(r"model_id,([^;]+)", ...)`
which substring-matches the `model_id,` inside the file-ID encoding's
`llm_output_file_model_id,<deployment_uuid>` field. parse_unified_id
then fed that deployment UUID back into the auth path as a model
candidate via _extract_models_from_managed_resource_id, and every
team-BYOK file attach 403'd with:
team not allowed to access model. This team can only access
models=['openai/*']. Tried to access <deployment-uuid>
The team's models list correctly contains the public name (`openai/*`)
that target_model_names matches, but the bogus UUID candidate fails
the wildcard check first.
Anchor the regex to a field boundary (`(?:^|;)model_id,`) so it
matches the legitimate top-level `model_id,<value>` field on
vector_store unified IDs and skips substring matches inside other
fields. File-IDs (which have no top-level `model_id` field) now
return None and contribute no spurious UUID candidate.
Surfaced reproducing LIT-3244 on patch/1.86.0 with the customer's
exact flow: team with openai/* BYOK deployment, JWT-scoped user,
POST /v1/vector_stores/{id}/files attaching a file uploaded with
target_model_names=openai/gpt-4o.
* fix(proxy): hydrate wildcard discovery credentials (#28284)
* fix(proxy): hydrate wildcard discovery credentials
* fix(proxy): constrain wildcard credential hydration
* chore(tests): migrate Bedrock CI to AWS account 941277531214 (#28728)
* chore(tests): migrate Bedrock CI from AWS account 888602223428 to 941277531214
The original account (888602223428) was put under a security restriction by
AWS after a root access key leaked in a PR comment. While that account works
its way through the AWS Support unlock process, Bedrock-touching CI tests have
been migrated to a fresh account (941277531214).
Changes:
- Replace 26 hardcoded references to 888602223428 with 941277531214 across
8 files (provisioned-model ARNs, imported-model ARNs, AgentCore runtime
ARNs, batch execution role ARN, and example proxy config).
- The provisioned-model and imported-model ARNs are referenced only from
mocked unit tests — no AWS resources to recreate.
- The batch execution IAM role has been recreated in the new account with
the same name and equivalent permissions.
- The two AgentCore runtimes (hosted_agent_r9jvp-3ySZuRHjLC,
hosted_agent_13sf6-cALnp38iZD) are being recreated in the new account
under the same names — see tools/agentcore-deploy/ in a follow-up.
CircleCI env vars AWS_ACCESS_KEY_ID / AWS_SECRET_ACCESS_KEY / AWS_REGION_NAME
were updated separately via the CircleCI API to point at the new account.
Smoke-tested locally against the new account:
aws bedrock-runtime converse --region us-west-2 \
--model-id us.anthropic.claude-sonnet-4-5-20250929-v1:0 \
--messages '[{"role":"user","content":[{"text":"ping"}]}]'
→ 200, model returned 'pong'
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* chore(tests): refresh AgentCore ARN suffixes to match newly-deployed runtimes
The first migration commit replaced just the account ID, but AgentCore
auto-assigns a random 10-char suffix to every runtime on creation — we
can't reuse the original suffixes (`3ySZuRHjLC`, `cALnp38iZD`) in the
new account. Updated the AgentCore-runtime ARNs in the three files that
reference real runtime IDs (not the mock-based unit-test ARNs).
Deployed runtimes:
arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_r9jvp-Rq79QFC2fp
arn:aws:bedrock-agentcore:us-west-2:941277531214:runtime/hosted_agent_13sf6-4046UzHSwy
Both runtimes are status=READY and pass a smoke invoke:
$ aws bedrock-agentcore invoke-agent-runtime --agent-runtime-arn ... --payload '{"prompt":"ping"}'
→ 200, {"result": "echo: ping"}
The agent is a minimal echo (see /tmp/agentcore_deploy/agent.py for the
deploy artifacts). Tests that only verify the SDK wiring will pass; if any
test asserts on agent output content, swap the echo for the real agent.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
* chore(tests): point Bedrock batch tests at new-account S3 bucket
The account migration (888602223428 -> 941277531214) was a flat
account-ID swap, which only rewrites ARNs that embed the account
number. S3 bucket names carry no account ID, so the live Bedrock
batch tests still uploaded to `litellm-proxy` — a bucket that lives
in the old account. S3 names are globally unique, and the old account
still holds that name, so it can't be recreated in the new account.
Rename to `litellm-proxy-941277531214` (account-ID suffix guarantees
global uniqueness). The bucket must be created in 941277531214 and the
batch execution role granted s3:GetObject/PutObject/ListBucket on it
before this job is run in CI.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* chore(tests): point live S3 logging test at new-account bucket
Same account-ID-free blind spot as the batch bucket: `load-testing-oct`
lives in the old account and its name can't be reused globally. The
`logging_testing` CI job is wired into the workflow and runs
test_basic_s3_logging, which uploads to this bucket with the CI env
creds, then lists and deletes objects — a live dependency.
Rename to `load-testing-oct-941277531214`. The bucket must exist in the
new account with the CI IAM principal granted
s3:PutObject/GetObject/ListBucket/DeleteObject before this job runs.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* chore(tests): repoint Bedrock guardrail IDs to new-account guardrails
The migration left guardrail IDs untouched (no account ID in them), so
all live guardrail tests failed with "guardrail identifier or version
does not exist" against 941277531214. Recreated both guardrails in the
new account and updated the hardcoded IDs:
- wf0hkdb5x07f -> zgkmukebruil (PII mask: PHONE + CREDIT_DEBIT_CARD,
with explicit inputAction=ANONYMIZE so masking applies to INPUT,
which is the source litellm's moderation hook sends)
- ff6ujrregl1q -> 4w3d1di3snt5 (blocks "coffee"; blocked message set
to the exact string the tests assert on)
Updated test_bedrock_guardrails.py, otel_test_config.yaml, and the
guardrailConfig in test_bedrock_completion.py. Verified locally: the 5
previously-failing guardrail tests now pass.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(bedrock): migrate legacy models to current inference profiles
The new CI account (941277531214) cannot invoke legacy Bedrock models
(AWS gates them: "marked by provider as Legacy... not actively using in
the last 30 days"). Migrated the live-call tests:
- anthropic.claude-3-sonnet-20240229 -> us.anthropic.claude-sonnet-4-5-20250929-v1:0
- anthropic.claude-3-haiku-20240307 -> us.anthropic.claude-haiku-4-5-20251001-v1:0
Current Claude models on Bedrock require the us. inference-profile prefix
(bare on-demand ids are rejected).
cohere.command-r-plus has no working replacement (all Cohere is legacy-
gated in the new account): swapped to claude-haiku-4-5 in provider-
agnostic param lists. amazon.titan-image-generator skipped (no working
replacement). Mocked/transformation/cost tests that reference the legacy
strings are intentionally left unchanged. Verified live against the new
account.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(bedrock): repoint SageMaker + Knowledge Base to new-account resources
These referenced account-scoped resources by hardcoded id that only
existed in the old account, so the migration's account-ID swap missed
them. Recreated in 941277531214 and repointed:
- SageMaker endpoint jumpstart-dft-hf-textgeneration1-mp-20240815-185614
-> litellm-ci-textgen (gpt2 on a TGI container, ml.g5.xlarge)
- Bedrock Knowledge Base T37J8R4WTM -> LCYXFBR2TU (OpenSearch Serverless
vector store + titan-embed-text-v2, seeded with a LiteLLM doc)
Verified live: test_sagemaker.py (12 passed) and
test_bedrock_knowledgebase_hook.py (12 passed).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(reasoning_effort_grid): skip bedrock claude-opus-4-7 cells (not entitled on 941277531214)
claude-opus-4-7 is listed in the new Bedrock CI account's foundation
models but invoke is denied (AccessDeniedException: "not available for
this account"). Bedrock access to the flagship Opus requires an AWS
Sales request, not the self-serve model-access toggle, so it can't be
enabled inline with the rest of the account migration.
Add an optional `skip_reason` to ModelEntry and set it on the
bedrock-claude-opus-4-7 entry; the grid test honors it via pytest.skip.
Cell count (231) and route coverage are unchanged, so the structural
asserts still pass. Restore coverage by deleting the one skip_reason
line once access is granted.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(bedrock): swap/skip legacy-gated models unavailable on new CI account
The migrated AWS account (941277531214) cannot access several models that
the old account could, so the remaining red CI jobs were hitting real
Bedrock "Access denied / Legacy" and "account not authorized" errors:
- image_gen: skip both Nova Canvas test classes (amazon.nova-canvas-v1:0 is
legacy-gated), matching the existing titan skip.
- batches: skip test_async_file_and_batch (Bedrock batch inference is not
authorized on the new account; requires an AWS support case).
- litellm_overhead: swap legacy claude-3-5-haiku for the active
us.anthropic.claude-haiku-4-5 inference profile.
- test_completion_claude_3_function_call: swap legacy claude-3-sonnet for the
active us.anthropic.claude-sonnet-4-5 inference profile.
https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa
* test(bedrock): fix remaining e2e legacy-model + batch failures on new CI account
- e2e_openai_endpoints: skip test_bedrock_batches_api (Bedrock batch inference
is not authorized on account 941277531214) and migrate the missed
s3_bucket_name in oai_misc_config.yaml to litellm-proxy-941277531214.
- build_and_test: swap legacy bedrock claude-3-sonnet for the active
us.anthropic.claude-sonnet-4-5 inference profile in the proxy structured
output e2e test.
https://claude.ai/code/session_01Y7zgHYu9GX29YRwV4yiWAa
* test(bedrock): make opus-4-7 + batch cells fail loudly and mock image-gen (#28791)
Replace the silent skips added for the new CI account with noisier behavior:
- reasoning-effort grid: opus-4-7 cells now fail (when AWS creds are present)
instead of skipping, so the missing entitlement stays visible in CI; they
still skip when AWS creds are absent (local dev)
- Bedrock batch inference tests: drop the skip so they run and fail until
batch access is granted
- Titan + Nova Canvas image-gen tests: mock the Bedrock HTTP call so the
transform + cost-tracking path stays under test without live model access
https://claude.ai/code/session_01MT7SWDnXUjv6e6EPG7BDjT
Co-authored-by: Claude <noreply@anthropic.com>
* test(bedrock): use pytest.xfail for known-failing opus-4-7 cells
Replace pytest.fail with pytest.xfail when a model has a fail_reason,
so known-broken cells stay visible as XFAIL without keeping CI red.
Co-authored-by: Yassin Kortam <yassin@berri.ai>
---------
Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local>
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
---------
Co-authored-by: Dibyo Mukherjee <dibyo@adobe.com>
Co-authored-by: Mateo Wang <277851410+mateo-berri@users.noreply.github.com>
Co-authored-by: Mateo <mateo@Mateos-MacBook-Pro.local>
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Yassin Kortam <yassin@berri.ai>
openai 2.34.0 began rejecting an explicitly-passed empty-string api_key
at client construction (raises OpenAIError before any request), which
broke tests/local_testing/test_exceptions.py::test_exception_with_headers
and related cases after uv.lock floated openai 2.33.0 -> 2.36.0.
Pin back to 2.33.0 (within the existing pyproject >=2.20.0,<3.0.0 range)
as a temporary stopgap; longer-term fix to follow.
Split the monolithic LiteLLM proxy into independently scalable Kubernetes components to allow separate horizontal scaling of the LLM data plane and management API surfaces
- Add DatabaseURLSettings pydantic-settings model that assembles DATABASE_URL (and optional DATABASE_URL_READ_REPLICA) from discrete DATABASE_* env vars before Prisma initializes, supporting both IAM token auth (minting short-lived RDS tokens) and password auth; replaces the CLI-only path that componentized entrypoints bypass
- Add gateway component (port 4000) that trims the proxy route table to the LLM data-plane surface (chat, embeddings, completions, audio, realtime, provider passthroughs, health/metrics) via an allowlist applied inside the lifespan context so plugin-registered routes are captured
- Add backend component (port 4001) that exposes the management/admin surface (keys, users, teams, orgs, spend analytics, model management, SSO, audit logs) with a complementary allowlist
- Add ui component — Next.js static export served by nginx (port 3000) with RSC payload routing, asset prefix aliasing, and SPA fallback for dashboard routes
- Add migrations component with dedicated Dockerfile that runs prisma migrate deploy via a Helm pre-install/pre-upgrade Job, eliminating per-pod schema contention on the Prisma advisory lock
- Add Helm chart (helm/litellm) with separate Deployments, Services, HPAs, and ConfigMap for each component; shared _helpers.tpl emits DATABASE_*, IAM_TOKEN_DB_AUTH, REDIS_*, and DISABLE_SCHEMA_UPDATE env vars from chart values; ingress template routes traffic to the correct component by path prefix
- Add comprehensive tests for DatabaseURLSettings covering IAM auth, password auth, read replica fallbacks, operator-pinned URL preservation, and percent-encoding; add coverage test asserting gateway + backend allowlist union equals the full proxy route set
- Add pydantic-settings>=2.14.1 as a proxy extra dependency and update liccheck allowlist
Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu>
Our `uv.lock` already resolves jinja2 to 3.1.6, so Docker / CI installs
get that version. The `pyproject.toml` floor was lagging at 3.1.0,
which means downstream consumers using `--resolution=lowest-direct` or
older constraint files can land on 3.1.0-3.1.5 instead of the version
we actually test against.
Aligns the declared floor with the resolved version so external
installers see the same baseline our test matrix exercises.
`uv lock` diff is metadata-only (no resolved-version drift).
* feat(audio_transcription): add NVIDIA Riva STT provider
Adds nvidia_riva as a new audio transcription provider, supporting both
NVCF-hosted and self-hosted Riva ASR deployments via gRPC streaming.
- Auto-resamples input audio to 16 kHz mono LINEAR_PCM (soundfile + numpy,
audioread fallback) so callers can send any common format.
- Maps OpenAI params: language (en -> en-US), response_format (text/json/
verbose_json), timestamp_granularities=["word"] -> enable_word_time_offsets,
word offsets converted ms -> s for verbose_json.
- Auth: NVCF when nvcf_function_id is set (SSL on by default), self-hosted
otherwise (SSL off by default), with explicit use_ssl override.
- gRPC errors wrapped via NvidiaRivaException -> litellm exception classes.
- Optional deps gated behind [stt-nvidia-riva] extra (nvidia-riva-client,
soundfile, audioread, numpy).
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(nvidia_riva): address PR review feedback
- handler: forward call-level `timeout` to streaming_response_generator
(kwarg-detected via inspect for older riva-client compat) so a stalled
Riva server cannot block the caller indefinitely.
- audio_utils: spill bytes to a tempfile before audioread.audio_open;
most audioread backends (FFmpeg, GStreamer) require a real filesystem
path and previously raised TypeError on BytesIO, breaking the mp3/m4a
fallback path.
- audio_utils: prefer soxr / scipy.signal.resample_poly for resampling
(anti-aliased polyphase) when installed, falling back to linear only
as a last resort. Avoids aliasing on 44.1/48 kHz -> 16 kHz downsamples.
- transformation: bare `es` now maps to es-ES (Castilian) instead of
es-US, matching BCP-47 conventions.
Co-authored-by: Cursor <cursoragent@cursor.com>
* chore: trigger CI re-run [stabilize loop 1/3]
* Update litellm/llms/nvidia_riva/audio_transcription/transformation.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* chore: trigger CI re-run [stabilize loop 1/3]
* fix code qa
* fix lint
* fix mypy
* fix mypy
* Fix NVIDIA Riva ASR service lookup
* Fix NVIDIA Riva transcription payload logging
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: oss-pr-review-agent-shin[bot] <281797381+oss-pr-review-agent-shin[bot]@users.noreply.github.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
Removing the new check-dependency-floors.yml workflow. It only fires when
pyproject.toml changes, which is rare; for those PRs, a maintainer can
run the same check by hand with one command. Documented that command in
a pyproject.toml comment next to the deps.
Also adds the missing upper bound on importlib-metadata (>=8.0.0,<9.0)
for consistency with every other entry in the list.
CI matrix on Python 3.13 caught three floors that predate cp313 prebuilt
wheels and would force users into a Rust/C build:
- tiktoken: 0.7.0 -> 0.8.0 (cp313 wheels start at 0.8)
- tokenizers: 0.20.0 -> 0.21.0 (cp313 wheels start at 0.21; sdist's
pyproject.toml pre-0.21 is also malformed for modern build backends)
- pydantic: 2.5.0 -> 2.10.0 (pydantic-core cp313 wheels start at 2.27,
shipped with pydantic 2.10)
Verified locally on Python 3.10 and 3.13: install at lowest-direct +
import litellm + import every openai-namespace symbol the codebase uses
all pass.
The 12 core `[project.dependencies]` entries in pyproject.toml were exact
`==` pins, a side effect of the Poetry → uv migration. This forces every
downstream package that lists litellm as a dependency to downgrade common
runtime libraries (openai, pydantic, aiohttp, click, jsonschema, ...) to
the exact versions we ship. Customers have flagged this as a coexistence
blocker.
Switch to lower-bounded ranges with upper bounds where the upstream
package is pre-1.0 or has a known breaking-major-version policy.
Reproducibility for our Docker proxy and CI continues to come from
`uv.lock`, which is regenerated here as a metadata-only diff (no
resolved versions or hashes change).
Inspired by #26157 (which got stranded on `litellm_oss_staging_04_21_2026`
when the forward-merge to internal staging in #26216 was closed). Floors
in this PR are tighter than #26157's: they were validated by installing
litellm at `--resolution=lowest-direct` and importing the openai-namespace
symbols the codebase actually uses.
Floor highlights vs #26157:
- openai >= 2.20 (was 2.0) — Responses API symbols + `Omit` need a 2.x mid-range floor
- httpx >= 0.28, < 1.0 (was no upper) — pre-1.0
- importlib-metadata >= 8.0 (was 6.0) — stay in tested major
- tokenizers >= 0.20, < 1.0 (was 0.19, no upper) — pre-1.0
- aiohttp >= 3.10, < 4.0 (was no upper) — bound major
- pydantic >= 2.5, < 3.0 — kept
- All other floors: keep tested major, add upper bound
Adds a `check-dependency-floors.yml` GitHub Actions workflow that
installs litellm at `--resolution=lowest-direct` on Python 3.10 and 3.13
and import-checks every openai symbol the codebase uses, so a future
floor regression fails fast in CI rather than silently in the field.
Per Yuneng's feedback, use a single @pytest.mark.vcr marker so one record
sweep populates cassettes for every marked test across all providers,
instead of forcing each test to bind to a hard-coded cassette path.
Changes vs. the initial scaffolding:
- Add 'pytest-recording==0.13.4' on top of vcrpy. Adopt its layout:
cassettes live at 'cassettes/<test_module>/<test_name>.yaml', resolved
automatically. New tests just decorate with '@pytest.mark.vcr' — no
imports or path bookkeeping.
- Move the shared filter/match config into a 'vcr_config' fixture in
'tests/llm_translation/conftest.py' (consumed by pytest-recording for
every marked test in the dir). Drop the standalone 'vcr_config.py'.
- Bulk record / replay via the standard '--record-mode' CLI flag:
'make test-llm-translation-record' now sweeps every '@pytest.mark.vcr'
test under tests/llm_translation in one shot. Optional 'TARGET=' var
scopes to a single file.
- Move existing cassettes to the per-test paths and update the local
in-process Anthropic regenerator to write to the same paths.
- Refresh README + Makefile target docs to match the sweep workflow.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Live LLM e2e tests have been draining provider billing accounts and going
flaky on outages (LIT-2683). This change introduces vcrpy-backed cassette
replay so CI can exercise the same end-to-end LiteLLM transformation paths
without hitting the live provider:
- Add 'vcrpy==8.1.1' to the dev dependency group.
- New 'tests/llm_translation/vcr_config.py' centralises the VCR config:
filters auth/secret headers and per-request response headers, matches on
method+URI+body, and exposes 'LITELLM_VCR_RECORD_MODE' for re-recording.
- New 'tests/llm_translation/test_anthropic_completion_vcr.py' demonstrates
the pattern with one non-streaming and one streaming Anthropic test that
replay from cassettes shipped under 'cassettes/'.
- New 'tests/llm_translation/cassettes/_record_anthropic_fixtures.py' lets
contributors regenerate the canned Anthropic cassettes against a local
in-process mock (no API key required), and 'cassettes/README.md' documents
the full record/replay/refresh workflow.
- New 'make test-llm-translation-record FILE=...' Makefile target to refresh
cassettes against the live API.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
- Dockerfile: pin the unscoped `brace-expansion@5.0.5` alongside
`@isaacs/brace-expansion@5.0.1`. The scoped package only has 5.0.0
and 5.0.1 published; CVE-2026-33750's fix (5.0.5) is on the unscoped
package which npm also vendors. The override loop now swaps both.
- Revert `black` 26.3.1 -> 24.10.0, `pytest` 9.0.3 -> 8.3.5, and
`pytest-asyncio` 1.3.0 -> 1.2.0. The major-version bumps cause CI
lint (black reformats hundreds of files) and code-quality
(liccheck.ini has no entry for the new versions) failures. Both
CVEs are dev-only; skipping leaves no runtime exposure.
* bump litellm-proxy-extras version to 0.4.67
* bump litellm-proxy-extras pin to 0.4.67 in litellm pyproject
* regenerate uv.lock for litellm-proxy-extras 0.4.67
* bump litellm-enterprise version to 0.1.38
* bump litellm-enterprise pin to 0.1.38 in litellm pyproject
* regenerate uv.lock for litellm-enterprise 0.1.38
All three dependency bumps in this PR resolve on Python 3.10, so there
is no need to jump the floor all the way to 3.11. Also restore the
py3.10-specific lunary==1.4.36 pin that was collapsed when the floor
was temporarily at 3.11.
Now that requires-python starts at 3.11, the "python_version >= '3.9'"
and ">= '3.10'" markers are unconditionally true, and the "< '3.10'"
entries for psycopg, Pillow, pyarrow, langchain, lunary, and pylint can
never resolve. Drop the dead markers and remove the unreachable pins so
the dependency list reflects what actually gets installed.
Bumps orjson, fastapi-sso, and python-multipart to their latest releases
in the proxy extra, and raises the project python floor to 3.11 so the
updated pins can resolve. CI already runs on 3.11 / 3.12 / 3.13 and the
Docker images ship python 3.13, so the floor change aligns the declared
support range with what is actually tested and shipped.
langgraph-prebuilt 1.0.9 imports ExecutionInfo and ServerInfo from
langgraph.runtime, but those symbols are not exported until
langgraph 1.1.0. Our pin of langgraph==1.0.10 allows
langgraph-prebuilt<1.1.0,>=1.0.8, and uv resolves to 1.0.9 (the
latest in range), which breaks at import time in every test that
touches langgraph.prebuilt (e.g. tests/pass_through_tests/test_mcp_routes.py):
ImportError: cannot import name 'ExecutionInfo' from 'langgraph.runtime'
Pinning langgraph-prebuilt to 1.0.8 pairs correctly with
langgraph==1.0.10 and restores the import path.
Noma v1 resolved application_id from user_api_key_alias when no explicit
value was set (PR #16832). Noma v2 (PR #21400) was rewritten from scratch
and this fallback was not ported, causing all requests from shared LiteLLM
instances to appear as a single generic "litellm" application in the Noma
dashboard — breaking per-user traceability.
Fix: after checking dynamic_params and self.application_id, fall back to
user_api_key_alias from litellm_metadata or metadata. This matches the
pattern used by PromptSecurityGuardrail._resolve_key_alias_from_request_data()
and restores the v1 behavior where each API key gets its own application
entry in the Noma dashboard.
Fixes#25794
Co-authored-by: Brendan Smith-Elion <brendan.smith-elion@arcadia.io>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
1. exclude-newer: change from absolute "2026-04-10" to relative "3 days".
All pinned deps were published before the 3-day cutoff. Re-locked so
uv lock --check passes in test-mcp.yml and test-linting.yml.
2. test_eager_tiktoken_load: run all 10 env var values in a single
subprocess instead of spawning 10 separate processes. Each cold
import litellm takes ~78s on CI, so the old loop took ~13 min on a
single xdist worker. Now takes ~78s total.
3. proxy-db remaining timeout: increase from 20 to 30 minutes. The
remaining group has 51 test files and was consistently timing out at
71% across all branches (pre-existing issue, not migration-related).
1. Cap requires-python to <3.14 — no deps ship 3.14 wheels yet, and
uv's cross-version resolver fails on the Python 3.14 split.
2. Change exclude-newer from relative "30 days" to absolute "2026-04-10"
so the lockfile stays reproducible. The relative date caused
cryptography==46.0.7 (published April 8) to fall outside the window.
3. Parametrize test_eager_loading_env_var_values instead of looping —
with xdist the 6 subprocess cases can run in parallel instead of all
running sequentially on one worker (~13 min → ~2 min).
Also removed redundant case variants (Yes/YES/On/ON) that test the
same str_to_bool code path.
* build: migrate packaging metadata to uv
* ci: move automation and local tooling to uv
* docker: migrate image builds and runtime setup to uv
* docs: update install and deployment guidance for uv
* chore: align auxiliary scripts and tests with uv
* test: harden test_litellm isolation
* fix: keep release and health check images self-contained
* build: pin uv tooling and health check deps
* test: isolate bedrock image request formatting from suite state
* test: cover sandbox executor requirements flow
* ci: fix circleci no-op command steps
* ci: fix circleci publish workflow parsing
* fix: stabilize remaining uv migration CI checks
* ci: increase matrix test timeout headroom
* fix: restore published docker and license coverage
* fix: restore proxy runtime build parity
* fix: restore proxy extras parity and venv migrations
* ci: persist uv path across circleci steps
* fix: keep psycopg binary in default test env
* docker: preserve prisma cache across stages
* test: run local proxy checks through uv python
* build: restore runtime deps moved into ci
* build: refresh uv lock after upstream merge
* fix: restore module import in test_check_migration after merge
The conflict resolution imported only the function but the test body
references check_migration as a module throughout.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix: revert dependency promotions, remove nodejs-wheel-binaries, fix Docker layer caching
- Move google-generativeai, Pillow, tenacity back to ci group (they are
lazily imported and bloat the base SDK install needlessly)
- Remove nodejs-wheel-binaries from extra_proxy and proxy-dev (redundant
in Docker where system Node.js is already installed via apk)
- Remove all nodejs-wheel node replacement and venv npm patching blocks
from Dockerfiles since the wheel is no longer installed
- Add --no-default-groups to CodSpeed benchmark workflow so the benchmark
environment matches the old minimal pip install footprint
- Apply standard uv two-phase Docker pattern: copy metadata first, install
deps (cached layer), then copy source and install project
- Replace CircleCI enterprise no-op with proper uv sync command
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* chore: regenerate uv.lock after removing nodejs-wheel-binaries
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(ci): use cache/restore instead of cache to prevent cache poisoning
The old workflow used actions/cache/restore (read-only). The uv migration
changed it to actions/cache (read-write), which zizmor flags as a cache
poisoning risk. Restore the safer read-only variant.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(ci): disable setup-uv built-in cache to silence cache-poisoning alert
The setup-uv action enables caching by default, which zizmor flags as a
cache poisoning risk. Disable it since we already use a read-only
cache/restore step.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(ci): disable setup-uv cache in publish workflow
Silences zizmor cache-poisoning alert. Publishing workflow runs
infrequently on protected branches so caching adds no real benefit.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(test): remove duplicate verbose_logger mock in test_check_migration
The logger was patched twice — first via mocker.patch() then via
mocker.patch.object(autospec=True). The second call fails because
autospec cannot inspect an already-mocked attribute. Remove the
redundant first patch.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* fix(ci): free disk space before Docker build in test-server-root-path
The Dockerfile.non_root build ran out of disk on the CI runner. Remove
Android SDK, .NET, Boost, and GHC toolchains (~12GB) to free space.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
* Update CLAUDE.md with qwen3 tool_calls bug fix instructions (#18922)
* fix(ollama): set finish_reason to "tool_calls" when tool_calls present
When qwen3 models return tool_calls through Ollama, the finish_reason
was incorrectly left as "stop" instead of being set to "tool_calls".
This caused clients to miss the tool_calls in the response.
Added _get_finish_reason helper method following OpenAI provider's
pattern, and fixed both streaming and non-streaming response paths.
Fixes: https://github.com/BerriAI/litellm/issues/18922
* fix(ollama): pass tools directly without model capability check
The previous code tried to check model capability via get_model_info()
which made network calls to localhost:11434. When Ollama is remote,
this fails and falls back to JSON format, breaking tool calling.
Ollama 0.4+ supports native tool calling - let Ollama handle
model capability detection instead of LiteLLM.
Fixes#18922
* fix(ollama): transform tool_calls response to OpenAI format
Ollama returns tool_calls with arguments as dict, but OpenAI format
requires arguments to be a JSON string. Also ensures 'type': 'function'
field is present.
Completes the fix for #18922
* fix(ollama): set finish_reason to "tool_calls" when tool_calls present
Fixes#18922
Two issues addressed:
1. Remove broken model capability check
- get_model_info() fails when Ollama runs on remote server
- Broken fallback triggered JSON prompt injection
- Now passes tools directly - Ollama 0.4+ handles detection
2. Set finish_reason correctly
- Was hardcoded to "stop" even with tool_calls present
- Clients use this to know how to process the response
- Now returns "tool_calls" when tool_calls are in response
Both streaming and non-streaming responses are fixed.
Tests:
- All 14 existing Ollama tests pass
- Added 3 focused tests for the fixes
