* fix(view_users.tsx): add time tracking logic to debounce search - prevent new queries from being overwritten by previous ones
* fix(internal_user_endpoints.py): add sort functionality to user list endpoint
* feat(internal_user_endpoints.py): support sort by on `/user/list`
* fix(view_users.tsx): enable global sorting
allows finding user with highest spend
* feat(view_users.tsx): support filtering by sso user id
* test(search_users.spec.ts): add tests to ensure filtering works
* test: add more unit testing
* style(internal_user_endpoints.py): add response model to `/user/list` endpoint
make sure we maintain consistent response spec
* fix(key_management_endpoints.py): return 'created_at' and 'updated_at' on `/key/generate`
Show 'created_at' on UI when key created
* test(test_keys.py): add e2e test to ensure created at is always returned
* fix(view_users.tsx): support global search by user email
allows easier search
* test(search_users.spec.ts): add e2e test ensure user search works on admin ui
* fix(view_users.tsx): support filtering user by role and user id
More powerful filtering on internal users table
* fix(view_users.tsx): allow filtering users by team
* style(view_users.tsx): cleanup ui to show filters in consistent style
* refactor(view_users.tsx): cleanup to just use 1 variable for the data
* fix(view_users.tsx): cleanup use effect hooks
* fix(internal_user_endpoints.py): fix check to pass testing
* test: update tests
* test: update tests
* Revert "test: update tests"
This reverts commit 6553eeb232.
* fix(view_userts.tsx): add back in 'previous' and 'next' tabs for pagination
* feat(sidebars): add new item for agentops integration in Logging & Observability category
* Update agentops_integration.md to enhance title formatting and remove redundant section
* Enhance AgentOps integration in documentation and codebase by removing LiteLLMCallbackHandler references, adding environment variable configurations, and updating logging initialization for AgentOps support.
* Update AgentOps integration documentation to include instructions for obtaining API keys and clarify environment variable setup.
* Add unit tests for AgentOps integration and improve error handling in token fetching
* Add unit tests for AgentOps configuration and token fetching functionality
* Corrected agentops test directory
* Linting fix
* chore: add OpenTelemetry dependencies to pyproject.toml
* chore: update OpenTelemetry dependencies and add new packages in pyproject.toml and poetry.lock
* fix(user_dashboard.tsx): initial commit using user id from jwt instead of url
* fix(proxy_server.py): remove user id from url
fixes security issue around sharing url's
* fix(user_dashboard.tsx): handle user id being null
* fix(router.py): handle edge case where user sets 'model_group' inside 'model_info'
* fix(key_management_endpoints.py): security fix - return hashed token in 'token' field
Ensures when creating a key on UI - only hashed token shown
* test(test_key_management_endpoints.py): add unit test
* test: update test
* fix(common_daily_activity.py): support empty entity id field
allows returning empty response when user is not admin and does not belong to any team
* test(test_common_daily_activity.py): add unit testing
* 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
