* fix(gemini): normalize response_schema on native generateContent
The /v1beta/models/{model}:generateContent passthrough forwarded
generationConfig.response_schema verbatim, so schemas containing $defs,
$ref, anyOf-with-null, default, or title were rejected by Gemini even
though /chat/completions already handles them.
GoogleGenAIConfig.transform_generate_content_request now calls a new
_normalize_response_schema helper that mirrors the chat/completions
path: Gemini 2.0+ models get the schema promoted to responseJsonSchema
via _build_json_schema (preserving $defs/$ref natively), older models
keep responseSchema but the schema is flattened with
_build_vertex_schema. VertexAIGoogleGenAIConfig (which overrides the
transform entirely) calls the same helper before building the request.
* fix(gemini): preserve caller-supplied responseJsonSchema when responseSchema co-present
Previously, when both responseJsonSchema and responseSchema were present
on Gemini 2.0+, _normalize_response_schema processed responseJsonSchema
first (no-op normalization) then unconditionally promoted responseSchema
to responseJsonSchema, clobbering the caller-supplied value.
Now skip the promotion (and drop the redundant responseSchema) when the
caller already supplied responseJsonSchema.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* chore: strip restating comments from response-schema normalize
Drop the docstring on _normalize_response_schema and the two inline
comments that just restated what the surrounding code/asserts already
say. Function name + variable names carry the intent; PR description
covers the why-it-exists context.
* perf(gemini): drop redundant deepcopy on responseJsonSchema normalize
_build_json_schema is a no-op (returns its argument unchanged), so the
deepcopy + round-trip on the responseJsonSchema branch allocated a full
schema copy on every request with no observable effect. Forward the
caller's value as-is, and just move the popped responseSchema value when
promoting on Gemini 2.0+.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* style: remove unneeded comment
* fix(gemini): drop unsupported responseJsonSchema for older models
* test(gemini): add parity test between native and chat schema normalization
Per @Sameerlite review: lock the two Gemini schema-normalization paths
together. If either GoogleGenAIConfig._normalize_response_schema (native
generateContent) or VertexGeminiConfig.apply_response_schema_transformation
(/chat/completions) drifts, the parity test fails — forcing both to be
updated together.
* fix(google_genai): preserve key naming convention in _normalize_response_schema
When the input schema key is snake_case (response_schema), the promoted
JSON schema key should also be snake_case (response_json_schema) instead
of mixing in camelCase (responseJsonSchema). This matters for the Vertex
AI google_genai path which converts all keys to snake_case before
calling _normalize_response_schema.
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
OpenAI returns 'The model dall-e-3 does not exist' for the test account,
breaking test_openai_img_gen_health_check and test_image_generation.
Switch to gpt-image-1, matching the existing TestOpenAIGPTImage1 pattern.
LazyFeatureMiddleware compared the raw scope path against registered
prefixes (e.g. /policies), so requests under a server root path like
/api/v1/policies/... never matched, the feature never loaded, and the
endpoint returned 404. Strip the configured root path before matching,
normalizing trailing slashes and enforcing a component boundary so
/api does not falsely match /apiv2.
1. Missing litellm_request child span when proxy parent in metadata:
_get_span_context now returns (ctx, None) for the metadata-injected
proxy parent so the primary span is always emitted as a child of ctx.
Proxy span lifecycle managed by new _end_proxy_span_from_kwargs.
2. open_telemetry_logger overwrite by later handlers:
_init_otel_logger_on_litellm_proxy now uses first-registered-wins —
only assigns proxy_server.open_telemetry_logger when currently None.
3. Duplicate litellm_request success spans in streaming paths:
Added _mark_success_span_once with per-handler dedupe key stored in
kwargs metadata, suppressing the second span when both sync and async
success callbacks fire for the same request.
Co-authored-by: Yassin Kortam <yassinkortam@g.ucla.edu>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
`apply_client_tag_policy_pre_auth` overwrote string-typed metadata
with `{}` before merging header tags, dropping any tags inside. A
caller could send `metadata='{"tags":["over-budget"]}'` plus
`x-litellm-tags: within-budget` and bypass `_tag_max_budget_check`
on the body tag. Parse the string via `safe_json_loads` first so
existing tags survive the merge.
Also drop the empty `tests/test_litellm/proxy/credential_endpoints/`
directory — the cascade-rename tests it held imported a function
that was never implemented (out of scope for this PR).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
``model_dump(exclude_unset=True)`` in ``prepare_key_update_data``
includes any field the caller explicitly set, even when the value is
``None``. The previous guard short-circuited on ``getattr(data,
'user_id', None) is None``, which conflated "field omitted" (safe)
with "field explicitly set to null" (writes NULL to the token row,
detaching the key from its user and bypassing user-row role
checks).
Switch the omitted-vs-set distinction to ``data.model_fields_set``;
treat explicit-null and explicit-empty-string identically as a
removal attempt, both 403-rejected for non-admin callers.
Parametrized regression adds ``explicit_null_blocked`` alongside the
existing ``rebind_blocked`` / ``empty_blocked`` / ``same_user_id_allowed``
cases.
Removes the allow_client_tags metadata check from apply_client_tag_policy_pre_auth so
x-litellm-tags headers are always merged into request metadata, matching the post-auth
behavior in add_litellm_data_to_request. Updates pre-call tests accordingly and adds a
new test suite covering cascading credential renames into model rows.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Previous wording read "User=<new_owner> is not allowed to update the
key to belong to user=<current_owner>" — easy to misread as "caller
wants to keep the key on its current owner". Reframe as
"Non-admin caller is not allowed to rebind the key from
user=<existing> to user=<incoming>" so the direction of the failed
operation is unambiguous.
Same shape preserved (HTTPException 403); only the ``detail`` string
changes. Regression test substring updated.
A non-admin caller could rebind their own key's ``user_id`` via
``/key/regenerate``. ``_execute_virtual_key_regeneration`` had org/team
guards but no ``user_id`` guard, and ``prepare_key_update_data`` did not
strip the field — it survived ``model_dump(exclude_unset=True)`` into
the Prisma update. On the next request,
``_return_user_api_key_auth_obj`` resolved the rebound ``user_id``
against ``litellm_usertable`` and returned ``PROXY_ADMIN`` whenever
the target row's ``user_role`` was admin (e.g. the default
``user_id="default_user_id"`` created on first password-UI login).
``/key/update`` had the equivalent guard inline at
``_validate_update_key_data``; extract it to a shared helper
``_validate_caller_can_change_key_ownership`` and call from both
``/key/update`` and ``_execute_virtual_key_regeneration``. Future
regenerate-style endpoints inherit the guard for free.
Also tighten the premium gate that allowed the master-key rotation
branch to skip the enterprise check. The previous predicate was
``data.new_master_key is not None`` — a field-presence test, not an
identity check. Any non-premium caller could send any value in that
field and the premium check would no-op. Verify the caller actually
holds the master key via ``_is_master_key`` before allowing the
non-premium path.
Tests:
- ``test_regenerate_user_id_rebind_guard`` — parametrized table over
cross-user rebind (blocked), empty-string removal (blocked), and
same-user no-op rebind (allowed).
- ``test_regenerate_premium_gate_requires_actual_master_key`` /
``test_regenerate_premium_gate_allows_actual_master_key_holder`` —
ensure the premium check requires the caller actually present the
master key, and that legitimate master-key rotation still works.
* fix(proxy): resolve cache handling issues in _lookup_deprecated_key
- Updated the in-memory cache for deprecated key lookups to store a 3-tuple (active_token_id, cache_expires_at_ts, revoke_at_ts) instead of a 2-tuple, ensuring proper unpacking and backward compatibility.
- Removed duplicate cache reads and added logic to handle legacy cache entries gracefully.
- Enhanced unit tests to cover scenarios for cache hits, DB misses, and respect for revoke_at timestamps, ensuring robust handling of the grace-period key-rotation feature.
* refactor(proxy): streamline cache handling in _lookup_deprecated_key
- Simplified the cache retrieval logic by directly unpacking the 3-tuple cache entries, removing the need for backward compatibility checks for 2-tuple entries.
- Updated unit tests to ensure that pre-warmed 3-tuple cache entries are served correctly without unnecessary database lookups.
* chore(ci): add new unit test for deprecated key grace period
- Included `test_deprecated_key_grace_period.py` in the CI workflow to enhance coverage for deprecated key handling scenarios.
* fix(proxy): remove unnecessary check for revoke_at in _lookup_deprecated_key
- Eliminated the redundant check for None on revoke_at, streamlining the logic for handling deprecated keys in the cache. This change enhances the efficiency of the key lookup process.
* test(proxy): add end-to-end tests for deprecated key lookup behavior
- Introduced a new test class `TestDeprecatedKeyLookupDbE2E` to validate the behavior of deprecated key lookups against a real Prisma-backed database.
- The test ensures that old key hashes resolve correctly and that repeated lookups utilize the in-memory cache without errors.
- Cleaned up the `_lookup_deprecated_key` function by removing an unnecessary check for `revoke_at`, enhancing the efficiency of the key lookup process.
Caller-supplied tags (`x-litellm-tags` header, body `tags`, `metadata.tags`)
were silently dropped unless the key/team had
`metadata.allow_client_tags: true` set. Restore the documented behavior:
tags from the request always flow into `metadata.tags` and union with any
admin-configured static tags from key/team/project metadata.
Removes the `allow_client_tags` opt-in flag from the pre-call pipeline.
The flag was only ever read here; it has no schema or endpoint footprint,
so leftover values in existing key metadata are inert.
Test cleanup mirrors the simplification: drop the three tests that
verified the strip-when-not-opted-in path, drop the `allow_client_tags`
fixture lines from the merge/union tests.
Second wave of failures from the 2026-05-12 DALL-E shutdown:
- tests/image_gen_tests/test_image_edits.py::TestOpenAIImageEditDallE2
and tests/image_gen_tests/test_image_generation.py::TestOpenAIDalle3
are explicitly named for the deprecated models and can't pass; remove.
gpt-image-1 coverage already exists in sibling classes.
- tests/local_testing/test_router.py image gen tests use dall-e-3 only
as a routing example; swap to gpt-image-1.
- tests/local_testing/test_custom_callback_input.py image_generation
success/failure paths swapped to gpt-image-1.
DALL-E 2 and DALL-E 3 were removed from the OpenAI API on 2026-05-12,
causing e2e image-generation tests to fail with "model does not exist".
Swap all live-API DALL-E references in proxy-backed tests to gpt-image-1
and update the dall-e-2 alias in proxy_server_config.yaml to point at
openai/gpt-image-1 (preserves any historical dall-e-2 callers).
* chore: reject bare str at file-input sinks to prevent local-file read (#27667)
Squash-merged by litellm-agent from stuxf's PR.
* fix: use os.PathLike in ocr sink and check truthy reasoningSummary for bridge
- ocr/main.py: widen Path check to os.PathLike for consistency with other sinks
- main.py: bridge condition checks truthiness of reasoning_summary, not just None
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
* fix: remove unused pathlib.Path import in ocr/main.py
---------
Co-authored-by: yuneng-jiang <yuneng@berri.ai>
Co-authored-by: ryan-crabbe-berri <ryan@berri.ai>
Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
Second wave of failures from the 2026-05-12 DALL-E shutdown:
- tests/image_gen_tests/test_image_edits.py::TestOpenAIImageEditDallE2
and tests/image_gen_tests/test_image_generation.py::TestOpenAIDalle3
are explicitly named for the deprecated models and can't pass; remove.
gpt-image-1 coverage already exists in sibling classes.
- tests/local_testing/test_router.py image gen tests use dall-e-3 only
as a routing example; swap to gpt-image-1.
- tests/local_testing/test_custom_callback_input.py image_generation
success/failure paths swapped to gpt-image-1.
DALL-E 2 and DALL-E 3 were removed from the OpenAI API on 2026-05-12,
causing e2e image-generation tests to fail with "model does not exist".
Swap all live-API DALL-E references in proxy-backed tests to gpt-image-1
and update the dall-e-2 alias in proxy_server_config.yaml to point at
openai/gpt-image-1 (preserves any historical dall-e-2 callers).
Caller-supplied tags (`x-litellm-tags` header, body `tags`, `metadata.tags`)
were silently dropped unless the key/team had
`metadata.allow_client_tags: true` set. Restore the documented behavior:
tags from the request always flow into `metadata.tags` and union with any
admin-configured static tags from key/team/project metadata.
Removes the `allow_client_tags` opt-in flag from the pre-call pipeline.
The flag was only ever read here; it has no schema or endpoint footprint,
so leftover values in existing key metadata are inert.
Test cleanup mirrors the simplification: drop the three tests that
verified the strip-when-not-opted-in path, drop the `allow_client_tags`
fixture lines from the merge/union tests.
The enterprise package is installed as `litellm_enterprise` (per
enterprise/pyproject.toml), but several tests imported it as
`enterprise.litellm_enterprise.*` — a path that only resolves
because the repo root happens to sit on sys.path, letting Python's
implicit namespace package machinery discover `enterprise/` as a
directory.
This breaks any test runner that relocates source (e.g. the
mutation-testing workflow, which copies tests under `mutants/`) and
also caused two `patch()` strings to target a module path that does
not match what production code imports — meaning those mocks were
never actually patching the production module's attribute.
Replace `from enterprise.litellm_enterprise.` with the canonical
`from litellm_enterprise.` across 6 test files, and fix two
`patch()` target strings (and one `sys.modules` patch key in the
SSO test) to match.
* feat(ui): search teams by team ID alongside name
The Teams page search box only matched team_alias, so pasting a team UUID
returned zero results. Detect when the input is a full UUID and route it
to the team_id filter instead; otherwise keep the existing alias substring
search. Placeholder now reads "Search teams by name or ID...".
Resolves LIT-2648
* refactor: search teams via backend OR clause, drop client-side UUID detection
Adds a `search` query param to /v2/team/list that ORs across team_id
(exact) and team_alias (case-insensitive contains), so the search box
sends one param regardless of input format. Removes the isLikelyTeamId
helper and the client-side branching it fed.
* fix: invalidate cached tag object on tag budget reset (#27481) (#27572)
Squash-merged by litellm-agent from oss-agent-shin's PR.
* chore(mcp): tighten stdio server registration paths (#27570)
Squash-merged by litellm-agent from stuxf's PR.
* fix(proxy): clear MCP OpenAPI mappings on server eviction; widen budget cache invalidation
Evict OpenAPI tools from global_mcp_tool_registry and strip tool_name_to_mcp_server_name_mapping entries when a server leaves the runtime registry (remove_server and approval-status eviction). Invalidate user_api_key_cache for keys, orgs, and team members on budget-tier spend resets alongside tags.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(mcp): align update_server eviction with remove_server name fallback
Document budget-reset test assertion flip (cross-pod cache staleness).
Greptile: eviction now pops by server_id then server_name like remove_server;
test docstring explains assert_not_awaited -> assert_any_await change.
Co-authored-by: Cursor <cursoragent@cursor.com>
* Fix org budget cache invalidation
---------
Co-authored-by: oss-agent-shin <ext-agent-shin@berri.ai>
Co-authored-by: stuxf <70670632+stuxf@users.noreply.github.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
Greptile flagged that the strict isinstance(dict) guard in
_encryption_boundary_key would silently return None for any non-dict input,
including a LiteLLM_Params Pydantic instance, which exposes a custom .get()
method and is intended to be used dict-style in some router paths. If such
an instance ever flowed into healthy_deployments, the guard would drop every
candidate from boundary matching and fall through to the full deployment
pool, i.e. trigger the exact invalid_encrypted_content failure this check
exists to prevent.
Loosen the guard to accept any object exposing a callable .get(): plain
dicts (the common case) and LiteLLM_Params-style Pydantic instances. The
function still returns None for non-dict-like values (None, lists, strings,
ints, bare objects).
Adds regression tests covering:
- LiteLLM_Params Pydantic instance resolves to the same boundary tuple as
an equivalent plain dict
- non-dict-like values and dicts missing required fields still return None
When a Responses API follow-up switches model_name (e.g. gpt-5.3-codex ->
gpt-5.4, or to a LiteLLM-side alias of the same Azure deployment), the
router has already filtered healthy_deployments to the new group, so the
originating model_id is no longer present. The encrypted_content_affinity
check would log "decoded deployment not found" and fall back to the full
deployment pool, where simple-shuffle could land on a different Azure
resource and trip a 400 invalid_encrypted_content.
Fall back to pinning by the originating deployment's encryption boundary
(api_base + api_key) when the model_id miss is across model groups. The
encrypted_content travels with the Azure resource, not the model_name,
so any deployment on the same resource accepts it.
LIT-2531
* fix(tests): drop deprecated OpenAI-Beta realtime header
OpenAI deprecated the 'OpenAI-Beta: realtime=v1' header; the live
service now returns code 4000 invalid_beta with
"Unknown beta requested: 'realtime'.". Two integration tests in
tests/llm_translation/realtime/test_realtime_guardrails_openai.py
hardcoded the header and started failing across all PRs.
Library code is unaffected: the OpenAI realtime handler only
forwards 'OpenAI-Beta: realtime=v1' upstream when the proxy *client*
sends it (litellm/llms/openai/realtime/handler.py). Default proxy
behavior uses the GA protocol.
Connect to OpenAI without the deprecated header, and accept the GA
event name 'response.output_audio_transcript.delta' alongside the
beta-protocol name 'response.audio_transcript.delta' for the
transcript-delta assertion.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(logging): post_call tolerates non-JSON-serializable values
post_call() did json.dumps(original_response) without default=str, so
any provider passing a dict containing datetime/Decimal/etc. would
raise TypeError. Bedrock batch retrieval hits this with
get_model_invocation_job() responses that include datetime fields
(submitTime, lastModifiedTime, endTime), failing
tests/batches_tests/test_bedrock_files_and_batches.py::test_async_file_and_batch
across all PRs.
Pass default=str so non-serializable values fall back to str().
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* fix(tests): mock boto3 in bedrock retrieve batch test
The test patched AsyncHTTPHandler.get, but the bedrock retrieve
handler uses boto3.client('bedrock').get_model_invocation_job
directly, so the real AWS call was being made on every run, failing
with AccessDeniedException because the hardcoded test ARN belongs to
a different AWS account.
- Mock boto3.client and BedrockBatchesConfig.get_credentials so the
test never touches AWS.
- Use status=Completed in the mock response so output_file_id is
populated (the handler intentionally leaves it None for
non-completed jobs).
- Assert the predicted per-job output object URI (matches what the
handler actually returns) instead of the bare output prefix.
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* docs(tests): include GA event name in guardrail-block test docstring
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Mateo Wang <mateo-berri@users.noreply.github.com>
* feat(bedrock): support retrieve for model-invocation-job batch ARNs
`bedrock.retrieve_batch` previously only handled `:async-invoke/` ARNs
(Twelve Labs Marengo embeddings). The `:model-invocation-job/` ARNs
returned by `CreateModelInvocationJob` (the bulk batch inference API
behind `bedrock.create_batch`) fell through and returned a misleading
data-plane error, leaving created jobs unretrievable through the
LiteLLM batches API.
The two ARN families live on different AWS service endpoints
(`bedrock-runtime` data plane vs `bedrock` control plane), so they need
distinct handlers. This adds:
* `BedrockBatchesHandler._handle_model_invocation_job_status` — calls
the control plane via boto3 (`bedrock:GetModelInvocationJob`),
reusing `BaseAWSLLM.get_credentials` for credential resolution so
model_list / env / role-assumption configs continue to apply. The
response is reshaped into a `LiteLLMBatch` with the same status
mapping `transform_create_batch_response` already uses.
* Output-file-URI prediction. Bedrock surfaces the user-supplied
`s3OutputDataConfig.s3Uri` *prefix* in `GetModelInvocationJob`, but
results actually land at `<prefix>/<job-id>/<basename(input)>.out`.
We compute that single-file URI client-side and surface it as
`output_file_id`, so OpenAI-style `client.files.content(...)` works
without an extra `ListObjectsV2` round-trip. The bare prefix stays
in metadata for callers that want the manifest.
* Dispatch in `litellm/batches/main.py` for the new ARN family,
alongside the existing async-invoke branch.
* Unit tests covering ARN parsing, output-URI prediction (incl. edge
cases), the full status mapping, region resolution precedence, and
failure-message propagation.
Note: `request_counts` is intentionally `(0, 0, 0)` —
`GetModelInvocationJob` does not report per-record counts; getting
accurate numbers requires parsing `manifest.json.out` from the output
S3 prefix, which is left to callers.
Made-with: Cursor
* fix(bedrock): address PR feedback on model-invocation-job retrieve
Addresses Greptile P2 findings on #26834:
1. Use the bare job id (not the full ARN) when constructing the
`api_base` URL for `pre_call` logging. Passing the full ARN double-
counts the `model-invocation-job/` segment and embeds colons in the
path, producing misleading log lines.
2. Drop the `or output_prefix` fallback when `_predict_output_file_uri`
returns None. A bare prefix is not a downloadable object and surfacing
it as `output_file_id` re-creates the very NoSuchKey bug this handler
exists to fix. The bare prefix is still preserved in
`metadata["output_s3_uri"]` for callers that want to do their own S3
listing or read `manifest.json.out`.
`metadata["output_file_uri"]` uses "" rather than None to satisfy the
OpenAI Batch metadata schema (`dict[str, str]`); callers should branch
on the typed `output_file_id` field instead.
Also expands test coverage on the new code path:
- new "stay None" regression test for the prediction-fail case
- pre_call/post_call logging hook assertions (incl. the bare-id URL)
- explicit cancelled_at / expired_at coverage
- _to_epoch type-handling matrix and the boto3 ImportError branch
- defensive _extract_region_from_bedrock_arn exception path
- empty-basename case for _predict_output_file_uri
Patch coverage on the changed lines is now 100% (the only remaining
uncovered lines in the file belong to the pre-existing
`_handle_async_invoke_status` method, which this PR does not touch).
Made-with: Cursor
* test(bedrock): cover retrieve_batch dispatch for both ARN families
Codecov flagged 8 uncovered lines on `litellm/batches/main.py` after
this PR refactored the Bedrock dispatch into a single guard with two
sub-branches (`async-invoke` + `model-invocation-job`). Existing tests
exercised the handlers directly but not the dispatch in `main.py`.
Adds `tests/test_litellm/batches/test_retrieve_batch_bedrock_dispatch.py`
with 6 mocked tests that exercise `litellm.retrieve_batch` end-to-end
for the dispatch logic:
- async-invoke ARN routes to `_handle_async_invoke_status`
- async-invoke ARN with no region falls back to "us-east-1" (preserves
prior behavior on this branch)
- model-invocation-job ARN routes to the new
`_handle_model_invocation_job_status` handler
- model-invocation-job ARN with no region forwards None (so the new
handler can sniff region from the ARN itself, rather than getting
silently routed to us-east-1)
- unrelated bedrock ARN family falls through to the generic
provider-config retrieve path (neither special handler invoked)
- non-bedrock batch ids skip the bedrock dispatch entirely
Both handlers are mocked at the import site so the tests don't hit
AWS — the focus here is purely the new dispatch logic in main.py.
Co-authored-by: Cursor <cursoragent@cursor.com>
* test(bedrock): move retrieve_batch dispatch test to tests/test_litellm/
The dispatch test landed under `tests/test_litellm/batches/`, a new
directory that no upstream `test-unit-*.yml` workflow's `test-path`
allow-list includes. As a result, the test was never executed in CI
and codecov reported `litellm/batches/main.py` patch coverage at
11.11% (8 lines uncovered) — the lines belonging to this PR's
dispatch refactor itself.
Move the file up one level so it matches the
`tests/test_litellm/test_*.py` glob that `test-unit-misc.yml`
already runs, and adjust `sys.path.insert` for the new depth.
The companion handler tests under
`tests/test_litellm/llms/bedrock/batches/test_handler.py` are
unaffected — they're picked up by the `llms` directory in
`test-unit-llm-providers.yml`.
Made-with: Cursor
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(responses): map chat tool_choice to Responses API when bridging from completions
OpenAI /v1/responses rejects tool_choice.function. Normalize forced-function
choice from chat shape to {type, name} in LiteLLMResponsesTransformationHandler.
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(responses): strip tool_choice.function when top-level name is set
---------
Co-authored-by: Cursor <cursoragent@cursor.com>
Anthropic rejects tool_use/tool_result when tools is omitted. Always map
and attach the dummy tool in transform_request so CLIs work without
litellm.modify_params.
- Add unit test for transform_request dummy tool with modify_params off
- Adjust parallel function calling integration expectations: Bedrock
Converse still requires modify_params for this path
Co-authored-by: Cursor <cursoragent@cursor.com>
Reject fnmatch wildcards on non-scope claims when the claim string contains
whitespace so malformed iss values cannot match patterns like trusted.*.
Merge every entry when team_id_jwt_field resolves to a list instead of
keeping only the first element.
Co-authored-by: Cursor <cursoragent@cursor.com>
