Introduce the ExceptionCheckers class to encapsulate methods for checking error conditions in exception strings, specifically for identifying rate limit errors. Update the Fireworks AI exception mapping tests to cover various scenarios, including standard 429 errors and text-based detection, ensuring accurate mapping to RateLimitError. Enhance test coverage for both positive and negative cases of rate limit detection.
* fix(huggingface): use get() instead of pop() for input_type parameter
Fixes embedding generation for HuggingFace models where input_type override
is required (e.g. BAAI/bge-m3). The pop() method was mutating optional_params
and removing input_type before downstream functions could access it.
* Add unit tests to catch regression
* Move tests around
* fix(convert_dict_to_response.py): handle None values in usage field for gpt-image-1
* test: add tests for handling None and partial values in usage fields for gpt-image-1 responses
- Renamed SSOSettingsResponse to inherit from a new base class SettingsResponse for better structure.
- Introduced InternalUserSettingsResponse and DefaultTeamSettingsResponse models for internal user and default team settings.
- Updated endpoint responses to use field_schema instead of schema for consistency.
- Enhanced test cases to validate the new response structure and ensure proper functionality of SSO settings.
* fix(anthropic/): fix regression when passing file url's to the 'file_id' parameter
add test and ensure anthropic file url's are correctly sent as 'document' blocks
* fix(vertex_and_google_ai_studio.py): Use same usage calculation function as non-streaming
Closes https://github.com/BerriAI/litellm/issues/10667
* test(test_vertex_and_google_ai_studio_gemini.py): update test
* fix(ui_sso.py): update user as proxy admin in db table, when checking for proxy_admin_id
Fixes issue where existing internal user, unable to make calls when set as proxy admin id
* fix(utils.py): fix custom base path
* Fixes issue with team_endpoints on member budget update
* refactored location of budget membership fix
* added test for _upsert_budget_membership func
* 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
