* fix(team_endpoints.py): ensure user id correctly added when new team created with user email as member
Fixes issue where user not correctly added to team on /team/new
* fix(internal_user_endpoints.py): make user email validation check case insensitive
Fixes issue where uppercase email was added even when lowercase email existed
* test: update test
* build: move build_and_test to use prisma migrate
* feat(proxy_setting_endpoints.py): encrypt env var before storing in db
Ensures env var can be read when loaded in from DB
Fixes issue when trying to add SSO from admin UI
* test: update tests
* Check content and order of trimmed messages
* Assert tool calls are preserved if below max_tokens
* Unreverse order of tool calls
* Return tool calls alongside other messages
* Write test for trimming untokenizable field
* Return original messages in case of exception
* feat: add input_fidelity parameter for OpenAI image generation
- Add input_fidelity to OpenAIImageGenerationOptionalParams type
- Update image_generation function signature to accept input_fidelity
- Add input_fidelity to default_params in get_optional_params_image_gen
- Include input_fidelity in openai_params list for proper handling
- Update documentation with input_fidelity parameter description
- Add test for input_fidelity parameter functionality
This enables control over how closely the model follows the input prompt
for gpt-image-1 model, improving prompt adherence and image quality.
* feat: add input_fidelity to optional parameters for image generation
- Include input_fidelity in the list of OpenAIImageGenerationOptionalParams
- This addition enhances the flexibility of image generation by allowing control over input fidelity.
* test: enhance test for gpt-image-1 with input_fidelity parameter
- Update test_gpt_image_1_with_input_fidelity to include mocking of OpenAI response
- Validate that the OpenAI client is called with correct parameters, including input_fidelity
- Improve response validation to ensure expected output structure and values
* fix: Handle circular references in spend tracking metadata JSON serialization
- Fixes issue #12634 where circular references in metadata caused
ValueError: Circular reference detected when logging spend data
- Adds _safe_json_dumps() function that detects and handles circular
references by replacing them with placeholder strings
- Maintains full functionality for normal objects while preventing
crashes from circular references
- Adds comprehensive tests for circular reference handling
- Critical fix for v1.74.3 stable release
* fix: Replace bare except clauses with specific Exception handling
- Fixes E722 linting errors in _safe_json_dumps function
- Maintains same error handling behavior while following best practices
- All tests continue to pass
* refactor: Use existing safe_dumps utility instead of custom implementation
- Replace custom _safe_json_dumps() with existing safe_dumps() from litellm_core_utils
- Remove duplicate code and leverage existing circular reference handling
- Update tests to use safe_dumps function
- Maintains same functionality while reducing code duplication
- All tests continue to pass
* fix(proxy_server.py): fixes for handling team only models via `/v2/model/info`
ensures team only models show up on the correct team on `Models + Endpoints`
* test: update tests
* fix(router.py): use more descriptive error message
* fix(proxy/_types.py): note `/team/member_update` is a self-managed route
route has it's own logic for rbac - enables team admins to update member permissions
Fixes issue where team admins on UI could not update member permissions
* fix(token_counter.py): move log line to being '.debug' instead of '.error'
Fixes https://github.com/BerriAI/litellm/issues/12269
* (#11794) use upsert for managed object table rather than create to avoid UniqueViolationError
* (#11794) use upsert for managed object table rather than create to avoid UniqueViolationError
* fix(bedrock): auto-generate session name when only aws_role_name is provided
Fixes#12583 - AWS role assumption not working correctly when aws_role_name
is provided without aws_session_name.
Previously, if only aws_role_name was provided in the config without
aws_session_name, the code would fall back to using environment credentials
instead of assuming the specified role. This was problematic in EKS/IRSA
environments where users want to assume a different role.
The fix:
- When aws_role_name is provided without aws_session_name, we now
auto-generate a session name with format 'litellm-session-{timestamp}'
- This ensures role assumption happens as expected
- Added comprehensive test coverage for this scenario
* style: format test file with black
---------
Co-authored-by: openhands <openhands@all-hands.dev>
* fix(anthropic): fix streaming + response_format + tools bug
- Fix _handle_json_mode_chunk to only convert response_format tools to content
- Regular user tools now remain as proper tool_calls in streaming mode
- Add comprehensive test for the fix
- Resolves issue where all tools were incorrectly converted to content chunks
Before: All tools converted to content with different indices
After: Only response_format tool converted, regular tools remain as tool_calls
* fix(anthropic): improve streaming + response_format + tools handling
* fix: lint error (too many statements)
* fix(anthropic): correct finish_reason for streaming response_format tools
- Add ttl parameter to cache_control for Gemini models
- Support Google's TTL format (e.g., '3600s', '7200s')
- Implement robust TTL extraction and validation
- Extract TTL before system message transformation to handle all cases
- Add comprehensive test suite with 17 test cases in tests/test_litellm/
- Update documentation with TTL usage examples
- Maintain backward compatibility with existing cache_control usage
Fixes#9810
* feat(route_checks.py): allow admin to disable proxy management endpoints on instance
useful for preventing multiple instances from doing admin actions
* docs(scaling_multiple_instances.md): add architecture doc on scaling multiple litellm instances
provide guidance on scaling proxy
* docs(scaling_multiple_instances.md): add doc on scaling across multiple regions for litellm
* fix(route_checks.py): allow disabling llm api endpoints on an instance
allows pure admin instance to exist
* refactor(enterprise/route_checks.py): refactor env var checks
* refactor: finish refactoring
* docs(control_plane_and_data_plane.md): refactor docs
* test: update tests
Added cache_read_input_token_cost (25% of regular input cost) to all 39 Gemini 2.x models
to properly support implicit context caching cost calculations. Previously, cached tokens
were being charged at full price instead of the discounted rate.
Fixes#11156
* [Feat] New LLM API Integration - Add Moonshot API (Kimi) (#12551)
* Add Moonshot AI provider support to LiteLLM
Co-authored-by: ishaan <ishaan@berri.ai>
* Refactor Moonshot provider params handling and transformation logic
Co-authored-by: ishaan <ishaan@berri.ai>
* fix constants
* add Moonshot AI
* fix get_supported_openai_params
* handle kimi temp
* add tool choice handling
* test moonshot unit tests
* fix kimi
* fix linting
* Add pricing information for Moonshot AI's kimi-k2 model (#12566)
* Add pricing information for Moonshot AI's kimi-k2 model
* Update model name to kimi-k2-0711-preview
- Changed model name from moonshot/kimi-k2 to moonshot/kimi-k2-0711-preview
- This reflects the specific model version as requested
* Update moonshot_models list to match model_context JSON
---------
Co-authored-by: openhands <openhands@all-hands.dev>
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: ishaan <ishaan@berri.ai>
Co-authored-by: Xingyao Wang <xingyao@all-hands.dev>
Co-authored-by: openhands <openhands@all-hands.dev>
* update docs
* docs moonshot
* fixes model cost map
* fix map_openai_params
---------
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: ishaan <ishaan@berri.ai>
Co-authored-by: Xingyao Wang <xingyao@all-hands.dev>
Co-authored-by: openhands <openhands@all-hands.dev>
* just use 1 param for mcp groups
* fix just use 1 param for access groups
* test_get_tools_from_mcp_servers
* docs access groups
* group MCPs
* test fix
* fix screenshots on docs
* TestMCPAccessGroupsE2E
* update img
* fix MCP connect
