Address Greptile review: test_resolve_jwks_url_resolves_oidc_discovery_document
also used the inconsistent patch.object pattern.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The patch.object with new_callable=AsyncMock can behave inconsistently
across Python versions, causing mock_response.status_code to return a
MagicMock instead of the assigned value. Direct assignment is simpler
and more reliable.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The CompletionTokensDetailsWrapper type now includes video_tokens field,
but this test's expected dict was not updated to include it.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The Gemini API requires role="user" on function_response content blocks
(added in commit 273cf12afa), but these tests were never updated to match.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Two independent fixes for pre-existing test failures on main:
1. Anthropic streaming: The sync __next__ method used a simple
holding_chunk pattern that lost chunks when multiple events needed
to be returned. Refactored to use the same chunk_queue approach as
the async __anext__ method. Also fixed tests that used ModelResponse
(which defaults finish_reason to 'stop') instead of ModelResponseStream.
2. Azure GPT-5.1 logprobs: The base OpenAI class includes logprobs for
gpt-5.1+ models, but Azure hasn't verified support for gpt-5.1.
Added explicit removal of logprobs/top_logprobs for gpt-5.1 (non-5.2)
models in the Azure config.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Only release distributed lock in finally if it was actually acquired;
prevents spurious Redis release_lock calls on early returns
- Treat bare integer maximum_spend_logs_retention_period as days (e.g. 3 → "3d")
instead of silently failing with a ValueError
- Elevate "Skipping cleanup" log from info to error so misconfigured
retention settings are visible without verbose logging
- Add tests for all three fixes
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add created_at field to MCPServer type (was missing)
- Map created_at from LiteLLM_MCPServerTable in build_mcp_server_from_table()
- Use server.created_at and server.updated_at instead of datetime.now() in _build_mcp_server_table() and health check table builder
- Add regression tests to verify timestamps are preserved through round-trip conversions
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Custom user-added routes (e.g. /ldap/ngs/ready) used with Depends(user_api_key_auth) were being rejected as admin-only after _run_post_custom_auth_checks was introduced in commit 14badde13c.
The route authorization check in common_checks is designed for LiteLLM's own management routes. Custom auth flows that add their own routes should be trusted since the custom auth function already validated the request. Budget and expiry checks still run.
Add skip_route_check parameter to common_checks() and pass skip_route_check=True from _run_post_custom_auth_checks() to skip route authorization while preserving budget/team/model checks.
Regression test added: test_common_checks_skip_route_check_for_custom_auth
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
* feat(guardrails): team-based guardrail registration and approval workflow
Add team-based guardrail submission system where teams can register
Generic Guardrail API guardrails for admin review. Includes:
- POST /guardrails/register endpoint for team-scoped submissions
- Admin review endpoints (list/get/approve/reject submissions)
- Team Guardrails tab in the UI dashboard
- extra_headers support for forwarding client headers to guardrail APIs
- Prisma schema migration for status, submitted_at, reviewed_at fields
- Documentation for team-based guardrails and static/dynamic headers
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(guardrails): address review feedback - SSRF, silent failure, redundant query
- Validate api_base URL scheme (http/https only) and hostname in
register_guardrail to prevent SSRF via team submissions
- Return warning field in approve response when in-memory initialization
fails so admins know the guardrail won't work until next sync cycle
- Eliminate redundant DB query in list_guardrail_submissions by fetching
all team guardrails once and deriving both filtered list and summary
counts from the single result set
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(guardrails): add pending_review status guard to reject endpoint
Prevent rejecting already-active or already-rejected guardrails, which
would create a DB/memory inconsistency (active in memory but rejected
in DB). Now mirrors the approve endpoint's status check.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
OpenRouter supports the Responses API at /api/v1/responses with
encrypted_content for multi-turn stateless reasoning workflows.
Without native registration, requests fall through to the chat
completion bridge, which uses a different format (reasoning_details)
and drops encrypted_content entirely.
This adds OpenRouterResponsesAPIConfig to route requests directly to
OpenRouter's Responses API endpoint, preserving encrypted_content.
Fixes https://github.com/BerriAI/litellm/issues/22189
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
The _resolve_jwks_url method checks response.status_code != 200, but
MagicMock returns a MagicMock object for status_code which is always
truthy (!= 200). Explicitly set mock_response.status_code = 200 so the
tests exercise the intended code path.
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* Add CrowdStrike AIDR guardrail hook
* fixup! use apply_guardrail event hook
* fixup! update imports
* fix(guardrails): include AI response in CrowdStrike AIDR output events
Issue:
_build_guard_input_for_response() was:
- Sending only the original user input (messages).
- Not sending the AI provider response.
This fix will:
- Extract response.choices from the ModelResponse object and include them in guard_input payload.
- Thus, ensure AIDR output rules receive the AI-generated content for analysis.
- Fix and update tests.
* fix(guardrails): prevent duplicate input events in CrowdStrike AIDR guardrail
Issue:
The CrowdStrike AIDR guardrail was running on during_call hooks wihtout event_hook configured.
This fix will:
- Set event_hook to ["pre_call", "post_call"] (AIDR admins will control what policy is applied)
This change will:
- Require default_on parameter
- Prevent duplicate API calls to AIDR for the same input
- Avoid unchecked AI provider API calls on during_call hook
* docs: add CrowdStrike AIDR to the list of Guardrails under Integrations
* docs: update CrowdStrike AIDR documentation page
---------
Co-authored-by: Konstantin Lapine <konstantin.lapine@crowdstrike.com>
Fixes NameError at runtime when ChatGPTToolCallNormalizer is
instantiated. The imports were missed when type hints were changed
from Python 3.10+ syntax (dict[], str | None) to typing module
syntax (Dict[], Optional[str]).
The previous check in _get_openai_compatible_provider_info() ran after
the model name was already split, so it never caught the second
get_llm_provider() call from the anthropic_messages bridge.
Moved the check to get_llm_provider() before the provider-list
stripping, using a pattern-based approach (custom_llm_provider ==
"openrouter" and model.startswith("openrouter/")) instead of a
hardcoded set. This covers all current and future native OpenRouter
models.
Updated tests to verify the bridge double-call scenario with
custom_llm_provider passed through.
