* fix(proxy_server.py): working swagger on custom base
removes the swagger monkey patch - this seems to render the swagger on custom base paths
* fix(ui/): working custom auth uptil login success event
* fix(ui/): working custom server root path for login
* fix(proxy_server.py): create typed dict for ui returned token
allows better documentation of expected params
* refactor(proxy_server.py): refactor all ui login endpoints to use same returned ui token object
* feat(ui_sso.py): add server root path to ui token
* feat(ui_sso.py): allows ui to call correct endpoint
* fix(networking.tsx): update proxy base url with custom root path
* fix(networking.tsx): handle updating proxy base url for non-local instances
* refactor: remove uneccessary references to proxybaseurl in ui code - reduce potential for errors
* fix: fix linting error
* fix(onboarding_link.tsx): fix onboarding link when custom server path is set
* feat(ui_discovery_endpoints.py): add new public .well-known/ route for litellm ui config
returns the server root path and proxy base url for constructing api calls
* feat(_types.py): add litellm well known config as public route
allows ui to query it
* fix(/_types.py): add .well-known config to as public route
* fix(page.tsx): create pattern for loading in ui config before making network requests
ensures requests are formatted correctly
* fix(page.tsx): call credential endpoint once ui config is loaded
* fix(page.tsx): route correctly to litellm dashboard from new user login
* fix(page.tsx): remove hardcoded `/litellm` for /sso/key/generate request
* fix(proxy_server.py): re-add moderations endpoint
* fix(proxy_server.py): mount __next__ at / and /litellm
allows it to work when proxy is mounted on root
* docs(contributing.md): remove /ui on ui doc - it will now run on root
* docs(custom_root_ui.md): add docs on custom root path
- Changed hardcoded model "whisper-1" to dynamic model extraction in AzureAudioTranscription and OpenAIAudioTranscription classes.
- Added tests to ensure correct model mapping for various transcription models, including GPT-4o and Azure whisper-1.
* feat: Add presidio_language parameter for PII analysis configuration via yaml config files
- Introduced presidio_language parameter in guardrail_initializers and guardrail_hooks to allow language specification for Presidio PII analysis via yaml config files
- Updated PresidioPresidioConfigModelUserInterface to include presidio_language with a default value of "en".
- Added tests to verify language configuration functionality, ensuring correct language usage in analyze requests.
* docs: Enhance PII masking documentation with language support details
- Added information on configuring the default language for PII analysis using the `presidio_language` parameter in both the UI and YAML configuration.
- Included supported language codes (English, Spanish, German) and their precedence in language settings.
- Provided examples for default language configuration and per-request language overrides to clarify usage.
- Updated model_prices_and_context_window.json to include embed-v4.0 with relevant pricing and metadata.
- Added embed-v4.0 to cohere_embedding_models in constants.py.
- Implemented comprehensive tests for Cohere Embed v4.0 in test_cohere.py, covering basic functionality, input types, error handling, and optional parameters.
* Add support for DataRobot as a router in LiteLLM
* Updates to logic
* Changes to make things work better
* Capitalize bearer
* Revert change
* Undo and simplify things
* Add basic testing
* Add some extra handling
* More tests
* Lowercase
* Fix
* Comment
* Add local test_completion for datarobot
* Sync repo to main
* Update get_complete_url to accept deployments
* Migrate to OpenAILike
* Mock datarobot in test
* Migrate everything to OpenAI LIke
* Apply fixes and changes from review
* Update docs
* Update env vars
* Move tests
* fix(base_routing_strategy.py): compress increments to redis - reduces write ops
* fix(base_routing_strategy.py): make get and reset in memory keys atomic
* fix(base_routing_strategy.py): don't reset keys - causes discrepency on subsequent requests to instance
* fix(parallel_request_limiter.py): retrieve values of previous slots from cache
more accurate rate limiting with sliding window
* fix: fix test
* fix: fix linting error
* feat: Add Gemini TTS audio parameter support
- Add is_model_gemini_audio_model() method to detect TTS models
- Include 'audio' parameter in supported params for TTS models
- Map OpenAI audio parameter to Gemini speechConfig format
- Add _extract_audio_response_from_parts() method to transform audio
output to openai format
* updated unit-test to use pcm16
* - created typedict for speechconfig
- simplified gemini tts model detection
- moved gemini_tts test to test_litellm
* simplified is_model_gemini_audio_model more
* feat(parallel_request_limiter_v2.py): add sliding window logic
allows rate limiting to work across minutes
* fix(parallel_request_limiter_v2.py): decrement usage on rate limit error
* fix(base_routing_strategy.py): fix merge from redis - preserve values in in-memory cache during gap b/w push to redis and read from redis
* fix(base_routing_strategy.py): catch the delta change during redis sync
ensures values are kept in sync
* fix(parallel_request_limiter_v2.py): update tpm tracking to use slot key logic
* fix: fix linting error
* test: update testing
* test: update tests
* test: skip on rate limit or internal server errors
* test: use pytest fixture instead
* test: bump mistral model
* fix(utils.py): support non default params for audio transcription
allows passing provider specific params straight through on transcription calls
* fix(gpt_transformation.py): fix o_series model routing
call _transform_request on async event
* refactor: refactor tests
* test(test_azure_chat_o_series_transformation.py): add unit test for azure o series error
* test: update test
* test: update json
* fix: fix mutiple keyword error
* fix(helicone.py): add helicone api base support
Fixes https://github.com/BerriAI/litellm/issues/10825
* test: add unit test for cache hit response on embedding calls
* fix(caching_handler.py): fix handling cache hit on embedding when input is string
Fixes LIT-197
* docs(helicone_integration.md): document new helicone api base param
* fix: init commit for object permissions
* fix: init commit for object permissions
* fix: add vector_store_id to permissions
* fix vector store selector
* feat:add vector store permission mgmt
* feat: ui add allowed vector stores dropdown
* feat: add new vector store object permissions
* testing: key mgmt
* fix: stor vector store permissions on team
* ui select vector store for teams
* ui add vector store settings for orgs
* feat: allow setting org vector store permissions
* test: adding team permissions for vector stores
* feat: MCP Servers with CRUD operations (#10699)
* feat: mcp CRUD operations with authn/authz
* feat: mcp server UI
* mcp server page with overview, mcp tools, and settings page
* Adding MCP Server flow
* prisma generate before test
* UI callbacks add/remove with api server refetch
* test fix: poetry run prisma
* feat: mcp server db and config connection
* fix: MCPTool filter on description when not present
* feat: mcp on UI and integrated with list tools
* feat: Update mcp server endpoint
* tests: Unit and integration tests for mcp management endpoints
* fix: docs and ensuring global_mcp_manage up to date
* ui: remove the mcp tools view
* fix: ruff lint
* fix: unit -> integration test area
* fix(ui): remove left nav menu of previous tools
---------
Co-authored-by: wagnerjt <wagnerjt@github.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* fix: sync DB MCP tools with in memory
* fix: sync DB MCP tools with in memory
* fix: stop using prisma.models
* fix: code qa check
* fix: import MCP
* fix: code QA checks
* fix: code QA checks
* fixes - only list tools for the specific MCP server
* fix: only list MCP tools for selected server
* fix linting error
---------
Co-authored-by: Tyler Wagner <wagnerjt@users.noreply.github.com>
Co-authored-by: wagnerjt <wagnerjt@github.com>
* added support for custom scope in get_azure_ad_token_provider
* if AZURE_FEDERATED_TOKEN_FILE not set, use azure_token_provider to retrive token with the oidc audiances as scope
* fix bug where oidc audience that contains "/" won't be extract correctly
* added tests for get_secret with oidc
* moved tests to litellm tests folder
* tes file naming aligned with source code
* renamed test_main because it caused issue in the test in github workflow
* updated docs
* moved docs to the end of file
* fix aws region in example config
* renamed test file
* added support for custom scope in get_azure_ad_token_provider
* if AZURE_FEDERATED_TOKEN_FILE not set, use azure_token_provider to retrive token with the oidc audiances as scope
* fix bug where oidc audience that contains "/" won't be extract correctly
* added tests for get_secret with oidc
* moved tests to litellm tests folder
* tes file naming aligned with source code
* renamed test_main because it caused issue in the test in github workflow
* updated docs
* moved docs to the end of file
* fix aws region in example config
* renamed test file
* fix merge conflict resolution error
* added support for custom scope in get_azure_ad_token_provider
* if AZURE_FEDERATED_TOKEN_FILE not set, use azure_token_provider to retrive token with the oidc audiances as scope
* fix bug where oidc audience that contains "/" won't be extract correctly
* added tests for get_secret with oidc
* moved tests to litellm tests folder
* tes file naming aligned with source code
* renamed test_main because it caused issue in the test in github workflow
* updated docs
* moved docs to the end of file
* fix aws region in example config
* renamed test file
* added tests for get_secret with oidc
* moved tests to litellm tests folder
* tes file naming aligned with source code
* renamed test_main because it caused issue in the test in github workflow
* updated docs
* moved docs to the end of file
* renamed test file
* fix merge conflict resolution error
* fix(anthropic/chat/handler.py): Fixes https://github.com/BerriAI/litellm/issues/10328
Adopts changes from https://github.com/BerriAI/litellm/pull/10329
* fix(vertex_and_google_ai_studio.py): don't set 'include thoughts' if thinking budget = 0
VertexAI raises errors
* fix(vertex_llm_base.py): new function for deciding the api base, handles 'global' api base
Fixes https://github.com/BerriAI/litellm/issues/11190
* fix(vertex_ai/partner_models): fix instrumentation for custom api base check
* refactor(vertex_ai/partner): refactor function to keep below 50 LOC
* fix(vertex_ai/gemini): remove parallel tool calls error for >1 tool - just ignore (prevent call from failing)
* fix: fix linting error
* added Pangea as a guardrail vendor
* Adding output recipe, cleaning up some imports
* Add Pangea guardrails tests
* Add docs and sidebar
* Move to use async_precall_hook instead of moderation hook
* Update to "new" format (accept mode)
Add response for redaction, support transforming request / response
based off the original type of call (/v1/completions,
/v1/chat/completions)
* Fix tests
* Fix unused imports
* Fix .md
---------
Co-authored-by: michael weinberger <michael.lee.weinberger@gmail.com>
* 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
* feat(codestral/completion): return litellm latency overhead for codestral
enables easier debugging of latency issues
* fix(types/utils.py): support _response_ms on hidden params model dump
Fixes issue where 'x-litellm-overhead-duration-ms' wasn't being returned on text c
ompletion calls
* fix(types/utils.py): add '__contains__' support for chatcompletiondeltatool call
Fixes https://github.com/BerriAI/litellm/issues/7099
* fix: fix linting error
* fix: fix linting error
