* chore(pangea-guardrail): Fix typo in debug message.
* docs(pangea-guardrail): Fix YAML example in pangea.md (README)."
* docs(pangea-guardrail): Update pangea.md (README).
* chore(pangea-guardrail): Format with Black.
* build(model_prices_and_context_window.json): add 'claude-opus-4' on vertexai (no @)
* build(model_prices_and_context_window.json): add claude sonnet 4 without 2
*@
* feat(internal_user_endpoints.py): assign user to orgs on user creation
allows user to be a member of orgs on creation - work to enable default orgs on UI
* fix(internal_user_endpoints.py): fix http_request
* 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
* Feature/lasso guardrail (#9002)
* first version of lasso guardrail in litellm
* update to the new Lasso API
* change prod api_base and kill the request when lasso detect issue.
* change test for now api, local test pass
* add async tests
* all tests pass
* add docs for the new lasso guardrail
* Remove support for modes other than pre_call in Lasso guardrail
* code structure and naming
* only pre_call docs
* fix lint errors
* move test to the new location follows the same directory structure as litellm/.
* add lasso guard
* docs lasso docs
* add lasso guardrail
* fix lasso guardrail
---------
Co-authored-by: oroxenberg <oro@lasso.security>
* fix: fixes for transfer encoding error on aiohttp transport
* Update tests/test_litellm/llms/custom_httpx/test_aiohttp_transport.py
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update web_search.md to include new supported providers and models, enhance web search options, and improve documentation for using web search with various AI models.
* Update LiteLLM version in web_search.md to reflect the latest stable release.
* Fix formatting in web_search.md for model declaration consistency.
* docs(web_search.md): add configuration options for web search in config.yaml
This update introduces sections for setting default and custom web search options in the proxy config file, including examples for different models and context sizes. A note clarifies that users can override these settings in API requests.
* fix(streaming_handler.py): maintain same 'created' across all chunks
Fixes https://github.com/BerriAI/litellm/issues/11437
* test: add unit test to ensure created is always the same across all chunks
* fix(types/utils.py): set a tool call id, if missing in delta tool call
Ensures stream chunk builder can reconstruct tool calls correctly
Fixes https://github.com/BerriAI/litellm/issues/11262
* fix(responses/transformation.py): support passing mcp server tool call to anthropic
allows switching between openai and anthropic for mcp tool calling
* fix(ollama/chat/transformation.py): set tool call id's when missing
* fix(onboarding_link.tsx): fix adding ui/invitation id
* fix(onboarding_link.tsx): update invitation link function to handle w/ and w/out custom server path cases
* fix(model_checks.py): ensure team only models returned when all proxy models set for team
* feat(anthropic/): initial commit adding working mcp tool call support
pass in mcp tool via `tools` and litellm will handle translating it to the right anthropic param
* feat(anthropic/): map openai mcp tool to anthropic mcp tool
allows usage within responses api
* fix(databricks/transformation.py): fix databricks linting error
* test(test_anthropic_chat_transformation.py): fix test
* test: update test
* fix(anthropic/chat/transformation.py): add dummy tool call