* 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
* Update mistral-medium prices and context sizes
While testing the Mistral model, I noticed a discrepancy in the pricing shown on the logs screen. After reviewing the code, I confirmed that the pricing values were incorrect.
This PR corrects the input and output token pricing for the latest Mistral model and adds the newly released mistral-medium-2505 version.
* Adds tool calling flag to mistral-medium
* Adds mistral-medium price updates to the main model price file
* Update model_prices_and_context_window_backup.json
sets mistral medium alias to the old values as it probably points to the old version.
* Update model_prices_and_context_window.json
* Update model_prices_and_context_window_backup.json
* Update model_prices_and_context_window.json
* added accordian for models tag
* remove margin top
* match badge styles same as on teams page
* add badge accordian for organizations
* badges fixed on keys page
* fixed for singular and plural
* fix merge conflict
* 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
Krrish Dholakia