* fix(triton/completion/transformation.py): remove bad_words / stop words from triton call
parameter 'bad_words' has invalid type. It should be either 'int', 'bool', or 'string'.
* fix(proxy_track_cost_callback.py): add debug logging for track cost callback error
* feat(fireworks_ai/chat): handle tool calling with fireworks ai correctly
Fixes https://github.com/BerriAI/litellm/issues/7209
* fix(utils.py): handle none type in message
* fix: fix model name in test
* fix(utils.py): fix validate check for openai messages
* fix: fix model returned
* fix(main.py): fix text completion routing
* test: update testing
* test: skip test - cohere having RBAC issues
* build(model_prices_and_context_window.json): add vertex ai gemini-2.5-flash pricing
* build(model_prices_and_context_window.json): add gemini reasoning token pricing
* fix(vertex_and_google_ai_studio_gemini.py): support counting thinking tokens for gemini
allows accurate cost calc
* fix(utils.py): add reasoning token cost calc to generic cost calc
ensures gemini-2.5-flash cost calculation is accurate
* build(model_prices_and_context_window.json): mark gemini-2.5-flash as 'supports_reasoning'
* feat(gemini/): support 'thinking' + 'reasoning_effort' params + new unit tests
allow controlling thinking effort for gemini-2.5-flash models
* test: update unit testing
* feat(vertex_and_google_ai_studio_gemini.py): return reasoning content if given in gemini response
* test: update model name
* fix: fix ruff check
* test(test_spend_management_endpoints.py): update tests to be less sensitive to new keys / updates to usage object
* fix(vertex_and_google_ai_studio_gemini.py): fix translation
* initial commit for azure responses api support
* update get complete url
* fixes for responses API
* working azure responses API
* working responses API
* test suite for responses API
* azure responses API test suite
* fix test with complete url
* fix test refactor
* test fix metadata checks
* fix code quality check
* feat(llm_passthrough_endpoints.py): expose new `/vertex_ai/discovery/` endpoint
Allows calling vertex ai discovery endpoints via passthrough
For agentbuilder api calls
* refactor(llm_passthrough_endpoints.py): use common _base_vertex_proxy_route
Prevents duplicate code
* feat(llm_passthrough_endpoints.py): add vertex endpoint specific passthrough handlers
* fix(llm_http_handler.py): fix fake streaming
allows groq to work with llm_http_handler
* fix(groq.py): migrate groq to openai like config
ensures json mode handling works correctly
* Simple fix for #9339 - upgrade the underlying library and cache the azure storage client (#9965)
* fix - use constants for caching azure storage client
---------
Co-authored-by: Adrian Lyjak <adrian@chatmeter.com>
* feat(llm_passthrough_endpoints.py): support mistral passthrough
Closes https://github.com/BerriAI/litellm/issues/9051
* feat(llm_passthrough_endpoints.py): initial commit for adding vllm passthrough route
* feat(vllm/common_utils.py): add new vllm model info route
make it possible to use vllm passthrough route via factory function
* fix(llm_passthrough_endpoints.py): add all methods to vllm passthrough route
* fix: fix linting error
* fix: fix linting error
* fix: fix ruff check
* fix(proxy/_types.py): add new passthrough routes
* docs(config_settings.md): add mistral env vars to docs
* fix(azure/common_utils.py): check for azure tenant id, client id, client secret in env var
Fixes https://github.com/BerriAI/litellm/issues/9598#issuecomment-2801966027
* fix(azure/gpt_transformation.py): fix passing response_format to azure when api year = 2025
Fixes https://github.com/BerriAI/litellm/issues/9703
* test: monkeypatch azure api version in test
* test: update testing
* test: fix test
* test: update test
* docs(config_settings.md): document env vars
* fix(openai.py): ensure openai file object shows up on logs
* fix(managed_files.py): return unified file id as b64 str
allows retrieve file id to work as expected
* fix(managed_files.py): apply decoded file id transformation
* fix: add unit test for file id + decode logic
* fix: initial commit for litellm_proxy support with CRUD Endpoints
* fix(managed_files.py): support retrieve file operation
* fix(managed_files.py): support for DELETE endpoint for files
* fix(managed_files.py): retrieve file content support
supports retrieve file content api from openai
* fix: fix linting error
* test: update tests
* fix: fix linting error
* fix(files/main.py): pass litellm params to azure route
* test: fix test
* fix(litellm_proxy/chat/transformation.py): support 'thinking' param
Fixes https://github.com/BerriAI/litellm/issues/9380
* feat(azure/gpt_transformation.py): add azure audio model support
Closes https://github.com/BerriAI/litellm/issues/6305
* fix(utils.py): use provider_config in common functions
* fix(utils.py): add missing provider configs to get_chat_provider_config
* test: fix test
* fix: fix path
* feat(utils.py): make bedrock invoke nova config baseconfig compatible
* fix: fix linting errors
* fix(azure_ai/transformation.py): remove buggy optional param filtering for azure ai
Removes incorrect check for support tool choice when calling azure ai - prevented calling models with response_format unless on litell model cost map
* fix(amazon_cohere_transformation.py): fix bedrock invoke cohere transformation to inherit from coherechatconfig
* test: fix azure ai tool choice mapping
* fix: fix model cost map to add 'supports_tool_choice' to cohere models
* fix(get_supported_openai_params.py): check if custom llm provider in llm providers
* fix(get_supported_openai_params.py): fix llm provider in list check
* fix: fix ruff check errors
* fix: support defs when calling bedrock nova
* fix(factory.py): fix test
* test: move test to just checking async
* fix(transformation.py): handle function call with no schema
* fix(utils.py): handle pydantic base model in message tool calls
Fix https://github.com/BerriAI/litellm/issues/9321
* fix(vertex_and_google_ai_studio.py): handle tools=[]
Fixes https://github.com/BerriAI/litellm/issues/9080
* test: remove max token restriction
* test: fix basic test
* fix(get_supported_openai_params.py): fix check
* fix(converse_transformation.py): support fake streaming for meta.llama3-3-70b-instruct-v1:0
* fix: fix test
* fix: parse out empty dictionary on dbrx streaming + tool calls
* fix(handle-'strict'-param-when-calling-fireworks-ai): fireworks ai does not support 'strict' param
* fix: fix ruff check
'
* fix: handle no strict in function
* fix: revert bedrock change - handle in separate PR
* fix(vertex_ai.py): common_utils.py
move to only passing in accepted keys by vertex ai
prevent json schema compatible keys like $id, and $comment from causing vertex ai openapi calls to fail
* fix(test_vertex.py): add testing to ensure only accepted schema params passed in
* fix(common_utils.py): fix linting error
* test: update test
* test: accept function
* 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
* Add date picker to usage tab + Add reasoning_content token tracking across all providers on streaming (#9722)
* feat(new_usage.tsx): add date picker for new usage tab
allow user to look back on their usage data
* feat(anthropic/chat/transformation.py): report reasoning tokens in completion token details
allows usage tracking on how many reasoning tokens are actually being used
* feat(streaming_chunk_builder.py): return reasoning_tokens in anthropic/openai streaming response
allows tracking reasoning_token usage across providers
* Fix update team metadata + fix bulk adding models on Ui (#9721)
* fix(handle_add_model_submit.tsx): fix bulk adding models
* fix(team_info.tsx): fix team metadata update
Fixes https://github.com/BerriAI/litellm/issues/9689
* (v0) Unified file id - allow calling multiple providers with same file id (#9718)
* feat(files_endpoints.py): initial commit adding 'target_model_names' support
allow developer to specify all the models they want to call with the file
* feat(files_endpoints.py): return unified files endpoint
* test(test_files_endpoints.py): add validation test - if invalid purpose submitted
* feat: more updates
* feat: initial working commit of unified file id translation
* fix: additional fixes
* fix(router.py): remove model replace logic in jsonl on acreate_file
enables file upload to work for chat completion requests as well
* fix(files_endpoints.py): remove whitespace around model name
* fix(azure/handler.py): return acreate_file with correct response type
* fix: fix linting errors
* test: fix mock test to run on github actions
* fix: fix ruff errors
* fix: fix file too large error
* fix(utils.py): remove redundant var
* test: modify test to work on github actions
* test: update tests
* test: more debug logs to understand ci/cd issue
* test: fix test for respx
* test: skip mock respx test
fails on ci/cd - not clear why
* fix: fix ruff check
* fix: fix test
* fix(model_connection_test.tsx): fix linting error
* test: update unit tests
