* docs(deploy.md): move docker recommendation to `main-stable`
* feat(enterprise/internal_user_endpoints.py): expose endpoint for checking available premium users
* feat(usage_indictor.tsx): add new element to help track remaining premium users
* feat(usage_indicator.tsx): show premium user remaining usage
allows users with user caps to know how much is left
* fix(vertex_and_google_ai_studio_gemini.py): bubble up stream is not finished, even if stop reason is given
prevents early completion of stream
Closes https://github.com/BerriAI/litellm/issues/11549
* fix(streaming_handler.py): respect is_finished = False in hidden params
internal logic for preventing ending stream early
* fix(litellm_license.py): add function to check if user is over limit
* fix(internal_user_endpoints.py): add function to check if user is over limit
* refactor: move test
* docs(customer_endpoints.py): document new param
* fix(vertex_and_google_ai_studio_gemini.py): handle both camel case and underscores in the tool for vertex ai code execution
support vertex ai code execution
* docs(vertex.md): add code execution example to vertex ai
* fix(vertex_ai/common_utils.py): when anyof in field, just select anyof - don't include other k,v pairs - vertex throws error
Fixes https://github.com/BerriAI/litellm/issues/11164
* fix(common_utils.py): add title field inside anyof - to retain some description
Addresses https://github.com/BerriAI/litellm/issues/11164#issuecomment-2914728385
* fix: add flag for disabling use_aiohttp_transport
* feat: add _create_async_transport
* feat: fixes for transport
* add httpx-aiohttp
* feat: fixes for transport
* refactor: fixes for transport
* build: fix deps
* fixes: test fixes
* fix: ensure aiohttp does not auto set content type
* test: test fixes
* feat: add LiteLLMAiohttpTransport
* fix: fixes for responses API handling
* test: fixes for responses API handling
* test: fixes for responses API handling
* feat: fixes for transport
* fix: base embedding handler
* test: test_async_http_handler_force_ipv4
* test: fix failing deepeval test
* fix: add YARL for bedrock urls
* fix: issues with transport
* fix: comment out linting issues
* test fix
* test: XAI is unstable
* test: fixes for using respx
* test: XAI fixes
* test: XAI fixes
* test: infinity testing fixes
* docs(config_settings.md): document param
* test: test_openai_image_edit_litellm_sdk
* test: remove deprecated test
* bump respx==0.22.0
* test: test_xai_message_name_filtering
* test: fix anthropic test after bumping httpx
* use n 4 for mapped tests (#11109)
* fix: use 1 session per event loop
* test: test_client_session_helper
* fix: linting error
* fix: resolving GET requests on httpx 0.28.1
* test fixes proxy unit tests
* fix: add ssl verify settings
* fix: proxy unit tests
* fix: refactor
* tests: basic unit tests for aiohttp transports
* tests: fixes xai
---------
Co-authored-by: Krrish Dholakia <krrishdholakia@gmail.com>
* refactor(vertex_llm_base.py): Prevent credential misrouting for projects
Fixes https://github.com/BerriAI/litellm/issues/7904
* fix: passing unit tests
* fix(vertex_llm_base.py): common auth logic across sync + async vertex ai calls
prevents credential caching issue across both flows
* test: fix test
* fix(vertex_llm_base.py): handle project id in default cause
* fix(factory.py): don't pass cache control if not set
bedrock invoke does not support this
* test: fix test
* fix(vertex_llm_base.py): add .exception message in load_auth
* fix: fix ruff error
* test(tests): add unit testing for litellm_proxy integration
* fix(cost_calculator.py): fix tracking cost in sdk when calling proxy
* fix(main.py): respect litellm.api_base on `vertex_ai/` and `gemini/` routes
* fix(main.py): consistently support custom api base across gemini + vertexai on embedding + completion
* feat(vertex_ai/): test
* fix: fix linting error
* test: set api base as None before starting loadtest
* fix(transformation.py): support a 'format' parameter for image's
allow user to specify mime type
* fix: pass mimetype via 'format' param
* feat(gemini/chat/transformation.py): support 'format' param for gemini
* fix(factory.py): support 'format' param on sync bedrock converse calls
* feat(bedrock/converse_transformation.py): support 'format' param for bedrock async calls
* refactor(factory.py): move to supporting 'format' param in base helper
ensures consistency in param support
* feat(gpt_transformation.py): filter out 'format' param
don't send invalid param to openai
* fix(gpt_transformation.py): fix translation
* fix: fix translation error
* Litellm dev 01 29 2025 p4 (#8107)
* fix(key_management_endpoints.py): always get db team
Fixes https://github.com/BerriAI/litellm/issues/7983
* test(test_key_management.py): add unit test enforcing check_db_only is always true on key generate checks
* test: fix test
* test: skip gemini thinking
* Litellm dev 01 29 2025 p3 (#8106)
* fix(__init__.py): reduces size of __init__.py and reduces scope for errors by using correct param
* refactor(__init__.py): refactor init by cleaning up redundant params
* refactor(__init__.py): move more constants into constants.py
cleanup root
* refactor(__init__.py): more cleanup
* feat(__init__.py): expose new 'disable_hf_tokenizer_download' param
enables hf model usage in offline env
* docs(config_settings.md): document new disable_hf_tokenizer_download param
* fix: fix linting error
* fix: fix unsafe comparison
* test: fix test
* docs(public_teams.md): add doc showing how to expose public teams for users to join
* docs: add beta disclaimer on public teams
* test: update tests
* test: initial test to enforce all functions in user_api_key_auth.py have direct testing
* test(test_user_api_key_auth.py): add is_allowed_route unit test
* test(test_user_api_key_auth.py): add more tests
* test(test_user_api_key_auth.py): add complete testing coverage for all functions in `user_api_key_auth.py`
* test(test_db_schema_changes.py): add a unit test to ensure all db schema changes are backwards compatible
gives user an easy rollback path
* test: fix schema compatibility test filepath
* test: fix test
* feat(pass_through_endpoints.py): fix anthropic end user cost tracking
* fix(anthropic/chat/transformation.py): use returned provider model for anthropic
handles anthropic `-latest` tag in request body throwing cost calculation errors
ensures we can be accurate in our model cost tracking
* feat(model_prices_and_context_window.json): add gemini-2.0-flash-thinking-exp pricing
* test: update test to use assumption that user_api_key_dict can get anthropic user id
* test: fix test
* fix: fix test
* fix(anthropic_pass_through.py): uncomment previous anthropic end-user cost tracking code block
can't guarantee user api key dict always has end user id - too many code paths
* fix(user_api_key_auth.py): this allows end user id from request body to always be read and set in auth object
* fix(auth_check.py): fix linting error
* test: fix auth check
* fix(auth_utils.py): fix get end user id to handle metadata = None
* fix(prometheus.py): support streaming end user litellm_proxy_total_requests_metric tracking
* fix(prometheus.py): add 'requested_model' and 'end_user_id' to 'litellm_request_total_latency_metric_bucket'
enables latency tracking by end user + requested model
* fix(prometheus.py): add end user, user and requested model metrics to 'litellm_llm_api_latency_metric'
* test: update prometheus unit tests
* test(test_prometheus.py): update tests
* test(test_prometheus.py): fix test
* test: reorder test
* fix(utils.py): e2e azure tts cost tracking working
moves tts response obj to include hidden params (allows for litellm call id, etc. to be sent in response headers) ; fixes spend_Tracking_utils logging payload to account for non-base model use-case
Fixes https://github.com/BerriAI/litellm/issues/7223
* fix: fix linting errors
* build(model_prices_and_context_window.json): add bedrock llama 3.3
Closes https://github.com/BerriAI/litellm/issues/7329
* fix(openai.py): fix return type for sync openai httpx response
* test: update test
* fix(spend_tracking_utils.py): fix if check
* fix(spend_tracking_utils.py): fix if check
* test: improve debugging for test
* fix: fix import
* fix(factory.py): skip empty text blocks for bedrock user messages
Fixes https://github.com/BerriAI/litellm/issues/7169
* Add support for Gemini 2.0 GoogleSearch tool (#7257)
* Add support for google_search tool in gemini 2.0
* Add/modify tests
* Fix grounding check
* Remove 2.0 grounding test; exclude experimental model in VERTEX_MODELS_TO_NOT_TEST
* Swap order of tools
* DFix formatting
* fix(get_api_base.py): return api base in streaming response
Fixes https://github.com/BerriAI/litellm/issues/7249
Closes https://github.com/BerriAI/litellm/pull/7250
* fix(cost_calculator.py): only set base model to model if not none
Fixes https://github.com/BerriAI/litellm/issues/7223
* fix(cost_calculator.py): enforce stricter order when picking model for cost calculation
* fix(cost_calculator.py): fix '_select_model_name_for_cost_calc' to return model name with region name prefix if provided
* fix(utils.py): fix 'get_model_info()' to handle edge case where model name starts with custom llm provider AND custom llm provider is given
* fix(cost_calculator.py): handle `custom_llm_provider-` scenario
* fix(cost_calculator.py): e2e working tts cost tracking
ensures initial message is passed in, to cost calculator
* fix(factory.py): suppress linting errors
* fix(cost_calculator.py): strip llm provider from model name after selecting cost calc model
* fix(litellm_logging.py): store initial request in 'input' field + accept base_model to be passed in litellm_params directly
* test: handle none env var value in flaky test
* fix(litellm_logging.py): fix linting errors
---------
Co-authored-by: Sam B <samlingx@gmail.com>
* feat(base_llm): initial commit for common base config class
Addresses code qa critique https://github.com/andrewyng/aisuite/issues/113#issuecomment-2512369132
* feat(base_llm/): add transform request/response abstract methods to base config class
* feat(cohere-+-clarifai): refactor integrations to use common base config class
* fix: fix linting errors
* refactor(anthropic/): move anthropic + vertex anthropic to use base config
* test: fix xai test
* test: fix tests
* fix: fix linting errors
* test: comment out WIP test
* fix(transformation.py): fix is pdf used check
* fix: fix linting error
* Fix Vertex AI function calling invoke: use JSON format instead of protobuf text format. (#6702)
* test: test tool_call conversion when arguments is empty dict
Fixes https://github.com/BerriAI/litellm/issues/6833
* fix(openai_like/handler.py): return more descriptive error message
Fixes https://github.com/BerriAI/litellm/issues/6812
* test: skip overloaded model
* docs(anthropic.md): update anthropic docs to show how to route to any new model
* feat(groq/): fake stream when 'response_format' param is passed
Groq doesn't support streaming when response_format is set
* feat(groq/): add response_format support for groq
Closes https://github.com/BerriAI/litellm/issues/6845
* fix(o1_handler.py): remove fake streaming for o1
Closes https://github.com/BerriAI/litellm/issues/6801
* build(model_prices_and_context_window.json): add groq llama3.2b model pricing
Closes https://github.com/BerriAI/litellm/issues/6807
* fix(utils.py): fix handling ollama response format param
Fixes https://github.com/BerriAI/litellm/issues/6848#issuecomment-2491215485
* docs(sidebars.js): refactor chat endpoint placement
* fix: fix linting errors
* test: fix test
* test: fix test
* fix(openai_like/handler): handle max retries
* fix(streaming_handler.py): fix streaming check for openai-compatible providers
* test: update test
* test: correctly handle model is overloaded error
* test: update test
* test: fix test
* test: mark flaky test
---------
Co-authored-by: Guowang Li <Guowang@users.noreply.github.com>
