- Reorder team_public_model_name assignment to happen before model_name mutation for clarity
- Add comment explaining no-rename fast-exit case in _update_existing_team_model_assignment
- Add comment explaining final patch_data.model_name = None applies to all code paths
Made-with: Cursor
- Cache LITELLM_ENABLE_TEAM_STALE_ALIAS_BYPASS at module level to avoid hot-path secret lookups
- Add clarifying comments for should_include_deployment team isolation logic
- Add negative assertion for update_team.assert_not_called() in test
- Add docstring clarification for _get_team_deployments helper pattern
- Add explicit assertion message in test_get_model_list_alias_optimization
Made-with: Cursor
- Add deduplication guard in _update_team_model_index to prevent duplicate indices
- Add wildcard comment in map_team_model for clarity
- Add monkeypatch to test_team_alias_stale_bypass_disabled_by_default for determinism
- Extract _get_team_deployments helper to centralize DB access pattern
- Add clarifying comments for team_public_model_name assignment ordering
Made-with: Cursor
- Check alias target pattern to detect stale team aliases
- Fix PrismaClient type annotation to Optional
- Eliminate in-place mutation in index update logic
Made-with: Cursor
- Use O(1) team index lookup instead of map_team_model in alias guard
- Fix MockPrismaClient to validate where clause filters
- Add comment explaining DB query trade-off for team deployments
Made-with: Cursor
- Skip model_aliases rewrite if model resolves to team deployments
- Add test coverage for sibling-preservation branch
- Update MockPrismaClient to support sibling deployment scenarios
Made-with: Cursor
- Add clarifying comments to test assertions
- Query prisma DB instead of in-memory router to avoid stale state
- Prevents incorrect deletion of old public name when siblings exist
Made-with: Cursor
Guard should_include_deployment fallback to only return deployments
matching the requested team_id, preventing public-name collisions
from leaking deployments across teams
Made-with: Cursor
- Add None guard for original_model_name in _add_team_model_to_db
- Remove stale old public name when renaming team model
- Add comment clarifying team deployment early-return priority
Made-with: Cursor
Remove temporary fire-emoji router logs used for local verification while keeping team sibling deployment routing behavior unchanged.
Made-with: Cursor
Remove team model_alias rewrites and resolve team deployments by team_public_model_name with team_id so sibling deployments stay in the routing candidate pool, with explicit logs showing candidate selection before load balancing.
Made-with: Cursor
Use a deterministic internal model_name for team-scoped deployments so sibling deployments with the same public model share a routing group. This makes team alias writes idempotent and preserves multi-deployment failover/load balancing behavior.
Made-with: Cursor
- Add cancel/retrieve overrides in AzureOpenAIFineTuningAPI to normalize responses
- Expand _AZURE_STATUS_MAP to handle all known Azure statuses
- Add "pending" to OpenAIFileObject.status allowed values
- Fix async test mock to return awaitable LiteLLMFineTuningJob
- Add test_openai_file_object_accepts_pending_status
Made-with: Cursor
- Move trainingType injection to AzureOpenAIFineTuningAPI handler
- Guard normalization with is_azure flag to only apply to Azure responses
- Override acreate_fine_tuning_job in Azure handler to use is_azure=True
- Update test to directly test _ensure_training_type method
- Add test for OpenAI unchanged behavior
Made-with: Cursor
- Default trainingType=1 for Azure when omitted to avoid misleading "base model does not support fine-tuning" error
- Normalize Azure FineTuningJob responses (pending→queued, null fields→defaults) to match OpenAI schema
- Add pending status support to OpenAIFileObject for Azure file uploads
- Add test coverage for trainingType default and response normalization
Made-with: Cursor
Addresses Greptile review feedback: replace direct litellm.model_cost
lookup with the standard _supports_factory infrastructure used by
supports_reasoning, supports_native_streaming, etc.
- Add supports_native_structured_output() utility in litellm/utils.py
- Add supports_native_structured_output field to ModelInfoBase type
- Wire field into _get_model_info_helper return dict
- Delegate from Bedrock _supports_native_structured_outputs to utility
- Add field to JSON schema validator in test_utils.py
Main has two duplicate keys for vertex_ai/gemini-embedding-2-preview.
Our JSON round-trip collapsed them to the second (text-only) entry, but
PR #23599 intentionally keeps the first (multimodal pricing) entry.
Restore the multimodal entry to avoid conflicts.
Wrap cost-map-dependent tests in try/finally to restore
os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] and litellm.model_cost,
preventing test-ordering sensitivity.
Integration tested 28/28 (10 sync + 10 streaming + extras) on the
native outputConfig.textFormat path in us-west-2. deepseek.v3.2 does
not support native structured output (Bedrock returns 400).
Integration testing confirmed gemma-3 (4b/12b/27b) ignores the JSON
schema and returns free text, and nemotron-nano (9b/12b) errors with
"Tool calling is not supported in streaming mode" even on sync calls.
Remove the flag so these models fall back to the tool-call approach.
Also fix test assertions to match (nemotron-nano-3-30b is supported,
gemma-3 and nemotron-nano-12b are not).
Move the source of truth for which Bedrock models support native structured
outputs (outputConfig.textFormat) from a hardcoded substring set
(BEDROCK_NATIVE_STRUCTURED_OUTPUT_MODELS) to the cost JSON via a new
"supports_native_structured_output" flag. This makes it possible to add
support for new models (including Claude Sonnet 4.6, which was missing)
by updating the JSON alone, with no code changes needed.
