The special name check (all_team_servers, all_proxy_servers) was an elif
after the server_id-is-not-None check, making it unreachable since special
names are non-None strings. Split into separate if blocks so the special
name guard runs before the duplicate-ID check.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The team MCP manager feature was reverted in PR #24255, so the test
needs to go back to the original single auth failure test that expects
a 403 for non-admin users.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The test_create_mcp_server_auth_failure test expected a 403 for non-admin
users, but the team MCP manager feature changed the auth flow to first
check for team_id (400) before checking permissions. Split into two tests:
one for missing team_id (400) and one for non-manager rejection (403).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Fixes CI failure in test_api_docs.py which validates that all Pydantic
model fields are documented in endpoint docstrings.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Add pytest.importorskip("mcp") at module level so tests skip cleanly
in CI environments without the mcp package (instead of ImportError)
- Import LiteLLM_TeamTableCachedObj into MCP_AVAILABLE block so type
annotations resolve for static analysis and get_type_hints()
- Remove string quotes from type annotations now that the import exists
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(moonshot): preserve reasoning_content on Pydantic Message objects in multi-turn tool calls
The condition 'reasoning_content not in msg' doesn't work correctly for
Pydantic Message objects because they don't support the 'in' operator
like dicts do. This caused reasoning_content to be stripped from
assistant messages in multi-turn conversation history.
Changed the condition to use msg.get('reasoning_content') instead,
which works correctly for both dicts and Pydantic models.
Fixes#23765
* added newline eof
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Update tests/test_litellm/llms/moonshot/test_moonshot_chat_transformation.py
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
* Simplify assertions in test_moonshot_chat_transformation
Removed redundant assertions for non-assistant messages.
---------
Co-authored-by: BillionClaw <267901332+BillionClaw@users.noreply.github.com>
Co-authored-by: Aarish Alam <arishalam121@gmail.com>
Co-authored-by: greptile-apps[bot] <165735046+greptile-apps[bot]@users.noreply.github.com>
- Set output_cost_per_second to 0.0 (was 0.0001) for whisper-1 and
azure/whisper-1: transcription is billed on input duration only,
not output duration
- Fix cost_per_second() in openai/cost_calculation.py: change elif to if
so input_cost_per_second is evaluated independently of output_cost_per_second,
and remove the erroneous completion_cost = 0.0 assignment that masked
any previously-set output cost
- Add TestCostPerSecondArithmetic unit tests covering both cost fields,
the None-guard, and zero-duration edge case
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
The Gemini REST API documents the embedding task type parameter as
camelCase `taskType`. The existing transformation functions convert
`dimensions` to `outputDimensionality` but miss the parallel
`task_type` to `taskType` conversion. This adds that conversion to
both `transform_openai_input_gemini_content` (batchEmbedContents path)
and `transform_openai_input_gemini_embed_content` (embedContent path).
Fixes#24190
Sameer Kankute