With tzdata installed, the environment variable `TZ` will be respected by Python's datetime module. This means that users can specify the timezone they want LiteLLM to use.
Co-authored-by: Simon Stone <sipreuss@gmail.com>
* Add LiteLLM Managed file support for `retrieve`, `list` and `cancel` finetuning jobs (#11033)
* 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
* feat(managed_files.py): support managed files for cancel ft job endpoint
* feat(managed_files.py): support managed files for cancel ft job endpoint
* feat(fine_tuning_endpoints/endpoints.py): add managed files support to list finetuning jobs
* feat(finetuning_endpoints/main): add managed files support for retrieving ft job
Makes it easier to control permissions for ft endpoint
* LiteLLM Managed Files - Enforce validation check if user can access finetuning job (#11034)
* 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
* feat(managed_files.py): support managed files for cancel ft job endpoint
* feat(managed_files.py): support managed files for cancel ft job endpoint
* feat(fine_tuning_endpoints/endpoints.py): add managed files support to list finetuning jobs
* feat(finetuning_endpoints/main): add managed files support for retrieving ft job
Makes it easier to control permissions for ft endpoint
* feat(managed_files.py): store create fine-tune / batch response object in db
storing this allows us to filter files returned on list based on what user created
* feat(managed_files.py): Ensures users can't retrieve / modify each others jobs
* fix: fix check
* fix: fix ruff check errors
* test: update to handle testing
* fix: suppress linting warning - openai 'seed' is none on azure
* test: update tests
* test: update test
* 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
Martin Liu