* feat: initial commit adding managed file support to fine tuning endpoints
* feat(fine_tuning/endpoints.py): working call to openai finetuning route
Uses litellm managed files for finetuning api support
* feat(fine-tuning/main.py): refactor to use LiteLLMFineTuningJob pydantic object
includes 'hidden_params'
* fix: initial commit adding unified finetuning id support
return a unified finetuning id we can use to understand which deployment to route the ft request to
* test: fix test
* feat(managed_files.py): return unified finetuning job id on create finetuning job
enables retrieve, delete to work with litellm managed files
* test: update test
* fix: fix linting error
* fix: fix ruff linting error
* test: fix check
* fix: handle dict objects in Anthropic streaming response
Fix issue where dictionary objects in Anthropic streaming responses
were not properly converted to SSE format strings before being yielded,
causing AttributeError: 'dict' object has no attribute 'encode'
* fix: refactor Anthropic streaming response handling
- Added STREAM_SSE_DATA_PREFIX constant in constants.py
- Created return_anthropic_chunk helper function for better maintainability
- Using safe_dumps from safe_json_dumps.py for improved JSON serialization
- Added unit test for dictionary object handling in streaming response
* fix: correct patch path in anthropic_endpoints test
* Refresh VoyageAI models and prices and context
* Refresh VoyageAI models and prices and context
* Refresh VoyageAI models and prices and context
* Updating the available VoyageAI models in the docs
* Updating the available VoyageAI models in the docs
* fix(internal_user_endpoints.py): allow resetting spend/max budget on user update
Fixes https://github.com/BerriAI/litellm/issues/10495
* fix(internal_user_endpoints.py): correctly return set spend for user on /user/new
* fix(auth_checks.py): check redis for key object before checking in-memory
allows for quicker updates
* feat(internal_user_endpoints.py): update cache object when user is updated + check redis on user values being updated
* fix(auth_checks.py): use redis cache when user updated
* fix: set default value of 'expires' to None
* fix: trace route on prometheus metrics
* fix: show route on prometheus metrics for total fails
* test: trace route on metrics
* fix: tests for route in prom metrics
* test: fix test metrics
* test: fix test_proxy_failure_metrics
* Add support for supports_computer_use in model info
* Corrected list of supports_computer_use models
* Further fix computer use compatible claude models, fix existing test that predated supports_computer_use in the model list
* Move computer use test case into existing test_utils file
* Moved tests in to test_utils.py
* feat(key_management_endpoints.py): add validation checks for migrating key to team
Ensures requests with migrated key can actually succeed
Prevent migrated keys from failing in prod due to team missing required permissions
* fix(mistral/): fix image url handling for mistral on async call
* fix(key_management_endpoints.py): improve check for running team validation on key update
* feat(model_info_view.tsx): enable updating model info for existing models on UI
Fixes LIT-154
* fix(model_info_view.tsx): instantly show model info updates on UI
* feat(proxy_server.py): enable flag on `/models` to include model access groups
This enables admin to assign model access groups to keys/teams on UI
* feat(ui/): add model access groups on ui dropdown when creating teams + keys
* refactor(parallel_request_limiter_v2.py): Migrate multi instance rate limiting to OSS
Closes https://github.com/BerriAI/litellm/issues/10052
* feat(key_edit_view.tsx): initial commit enabling reassigning keys to teams
* style(key_edit_view.tsx): cleaner implementation with teams in dropdown
* fix(all_keys_table.tsx): set max width to keys column
* feat(all_keys_table.tsx): show last updated at column for key
Ishaan Jaff