Add 58 unit tests across 5 files in ui/litellm-dashboard/src/components/policies/:
- build_attachment_data.test.ts: pure logic tests for global vs specific scope
- impact_preview_alert.test.tsx: rendering for global scope warning and specific scope counts/tags
- PolicySelector.test.tsx: pure function tests for getPolicyOptionEntries/policyVersionRef + component fetch/disable behavior
- policy_info.test.tsx: loading, not-found, policy details rendering, admin gating, onClose/onEdit callbacks
- attachment_table.test.tsx: loading/empty states, row rendering, scope badges, delete admin gating
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: don't close HTTP/SDK clients on LLMClientCache eviction
Removing the _remove_key override that eagerly called aclose()/close()
on evicted clients. Evicted clients may still be held by in-flight
streaming requests; closing them causes:
RuntimeError: Cannot send a request, as the client has been closed.
This is a regression from commit fb72979432. Clients that are no longer
referenced will be garbage-collected naturally. Explicit shutdown cleanup
happens via close_litellm_async_clients().
Fixes production crashes after the 1-hour cache TTL expires.
* test: update LLMClientCache unit tests for no-close-on-eviction behavior
Flip the assertions: evicted clients must NOT be closed. Replace
test_remove_key_closes_async_client → test_remove_key_does_not_close_async_client
and equivalents for sync/eviction paths.
Add test_remove_key_removes_plain_values for non-client cache entries.
Remove test_background_tasks_cleaned_up_after_completion (no more _background_tasks).
Remove test_remove_key_no_event_loop variant that depended on old behavior.
* test: add e2e tests for OpenAI SDK client surviving cache eviction
Add two new e2e tests using real AsyncOpenAI clients:
- test_evicted_openai_sdk_client_stays_usable: verifies size-based eviction
doesn't close the client
- test_ttl_expired_openai_sdk_client_stays_usable: verifies TTL expiry
eviction doesn't close the client
Both tests sleep after eviction so any create_task()-based close would
have time to run, making the regression detectable.
Also expand the module docstring to explain why the sleep is required.
* docs(AGENTS.md): add rule — never close HTTP/SDK clients on cache eviction
* docs(CLAUDE.md): add HTTP client cache safety guideline
* Include user_email in new user creation within get_user_object
Enhance the get_user_object function to include user_email in the parameters when creating a new user. This change is accompanied by a new test to verify that user_email is correctly included during the upsert process.
* Improve error handling in test_get_user_object by logging exceptions
Updated the test_get_user_object_upsert_includes_user_email function to log exceptions when they occur, enhancing the visibility of potential issues during testing. This change helps in diagnosing failures related to the mock LiteLLM_UserTable.
* fix(passthrough): raise_for_status in _async_streaming to propagate Azure 429s
* address greptile review feedback (greploop iteration 1)
Guard data/json args when content is provided to avoid httpx ValueError
* address greptile review feedback (greploop iteration 2)
Use bare raise to preserve original traceback in _async_streaming exception handler
* address greptile review feedback (greploop iteration 3)
Close httpx streaming response on error to prevent connection pool exhaustion
* address greptile review feedback (greploop iteration 4)
Guard aclose() call to prevent masking original exception; add explicit test for content param forwarding
* address greptile review feedback (greploop iteration 5)
Pass content to sign_request so AWS body-hash signing is correct when content is the sole body source
* revert sign_request content change - request_data expects dict, not bytes
Bedrock's sign_request calls json.dumps(request_data) — passing content bytes
would TypeError. sign_request should only receive data/json (dict), not raw bytes.
All operational/diagnostic messages in WebSearchInterceptionLogger are now
debug-level to avoid flooding production logs while still remaining available
when verbose logging is enabled.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
PR #22890 used cast(str, ...) / cast(Optional[str], ...) for the return
statements; this PR's approach uses str() for explicit runtime coercion
(addressing Greptile's concern). Keep the str() version and drop the
now-unused cast import.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Per Sameerlite's review: warning-level logs trigger Slack alerts.
All 6 remaining .warning() calls were operational/fallback messages,
not actual errors. Changed to .info() to match the first fix at L510.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Documents exactly how every request and response field gets translated
when LiteLLM routes an Anthropic /v1/messages call through the OpenAI
Responses API path (for OpenAI/Azure targets). Covers messages content
block mapping, tools, tool_choice, thinking→reasoning, context_management,
and the reverse response translation. Wired into the /v1/messages sidebar.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- CreateBatchRequest.output_expires_after: drop Optional since total=False
already makes the key absent-or-present; Optional[T] incorrectly allowed
the key to exist with value None, which is incompatible with the OpenAI
SDK's OutputExpiresAfter | NotGiven expectation on batches.create()
- cost_tracking_settings._resolve_model_for_cost_lookup: replace implicit
object-to-str returns with explicit str() calls so the function is safe
even if the surrounding truthiness guards are later weakened
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
PR #22850 (BYOK MCP servers) accidentally re-declared spec_path which was
already added by PR #22820, causing Prisma schema validation to fail with
error P1012 "Field is already defined".
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- batches/main.py: import FileExpiresAfter, cast output_expires_after on assignment
- openai/openai.py, azure/batches/handler.py: add # type: ignore[arg-type] on
batches.create / batches.retrieve TypedDict unpacking calls
- searchapi/transformation.py: cast optional_params["country"] to str before .lower()
- openrouter/image_edit/transformation.py: cast iterated value to str for size/quality params
- spend_log_cleanup.py: narrow bool | None to bool with `or False`
- cost_tracking_settings.py: cast base_model/resolved_model to str and
custom_llm_provider to Optional[str] in return statements
- text_moderation.py: suppress misc TypedDict ** expansion error; use cast for response
- prompt_shield.py: use cast instead of TypedDict(**response_json) construction
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
gemini/gemini-live-2.5-flash-preview-native-audio-09-2025 uses mode='realtime'
but the schema in test_aaamodel_prices_and_context_window_json_is_valid did
not include 'realtime' as a valid enum value, causing a ValidationError.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- a2a_protocol/main.py: replace bare assert with descriptive RuntimeError
in _execute_a2a_send_with_retry so retry exhaustion gives a clear message
- fine_tuning/main.py: fix _resolve_fine_tuning_timeout return type from
float to Union[float, httpx.Timeout] to accurately reflect the passthrough path
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Vertex AI does not support the output_config parameter in its API.
This parameter is being added by Anthropic/Gemini transformations but needs
to be removed before sending requests to Vertex AI endpoints.
This fix addresses the "Extra inputs are not permitted" error (issue #22312)
when using Claude models with structured outputs on Vertex AI.
Changes:
- Drop output_config in Gemini model transformation
- Drop output_config in Anthropic partner model transformation
- Drop output_config in Anthropic experimental pass-through transformation
- Add comprehensive tests to verify output_config is dropped
Fixes: #22312
Made-with: Cursor
Adds bedrock_mantle_models to the model_list union and models_by_provider
dict so models are discoverable via litellm.model_list and
litellm.models_by_provider["bedrock_mantle"].
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Azure AI Foundry's Anthropic endpoint does not support the scope field in
cache_control. Strip it from both system and messages before sending.
Made-with: Cursor
Bedrock does not support the scope field in cache_control (e.g. 'global' for
cross-request caching). Only type and ttl are supported per AWS docs.
- Remove scope from cache_control in both system and messages
- Extend _remove_ttl_from_cache_control to process system blocks
- Add test for scope removal
Made-with: Cursor
