* refactor: comment out circuit breaker
causes incorrect rate limiting in high traffic
* fix(base_routing_strategy.py): don't reset value if redis val is lower than current in-memory value
Fixes issue where redis might be trailing in-memory value
* fix(parallel_request_limiter_v2.py): if in-memory higher than redis, don't reset value; add previous slot keys to redis increment to correctly 'get' them
* fix(parallel_request_limiter_v3.py): v3 implementation of parallel request limiter
does not use background redis syncing - increments redis in call
simplify rate limiting logic, to improve accuracy
* fix: fix ruff errors
* fix(parallel_request_limiter_v3.py): don't decrement limit on post call success - causes double decrements
* fix(parallel_request_limiter_v3.py): working accurate multi-instance logic
ensured just 100 requests allowed on 100 users, 10 ramp up, 100 rpm limit key, 2 instances
* fix(parallel_request_limiter_v3.py): working accurate rate limiting with time window resets
allows rate limiting to work across multiple windows
* test: add unit tests for v3 rate limiter
* fix(parallel_request_limiter_v3.py): return window value into in-memory cache
allows in-memory cache checks to be used correctly
* refactor(parallel_request_limiter_v3.py): refactor rate limiting to work for multiple window/counter key pairs
enables using for user/team/model rate limiting
* feat(parallel_request_limiter_v3.py): working rate limiting, across key/user/team/end-user
* fix(parallel_request_limiter_v3.py): add model specific rate limiting
* fix(parallel_request_limiter_v3.py): ignore if no rate limits set
skip unecessary rate limit checks - if no limits set
* fix(parallel_request_limiter_v3.py): initial commit bringing token rate limits back
* fix(parallel_request_limiter_v3.py): increment by value in list + update assertions to handle tokens + max parallel requests
* test(parallel_request_limiter_v3.py): more testing
* fix(parallel_request_limiter.py): working in-memory cache limiter
* fix(redis_cache.py): ignore linting error - use safe hasattr
* fix(parallel_request_limiter_v3.py): fix linting error
* refactor: remove redundant parallel_Request_limiter_v2.py
old / inaccurate implementation
* test: update tests
* style: cleanup
* test: update test
* docs(config_settings.md): document new env var
* test(test_base_routing_strategy.py): update test
* 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.
* 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
* 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
* 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.
* 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
Krrish Dholakia