* docs(bedrock.md): clarify bedrock auth in litellm docs
* fix(convert_dict_to_response.py): Fixes https://github.com/BerriAI/litellm/issues/6387
* feat(pattern_match_deployments.py): more robust handling for wildcard routes (model_name: custom_route/* -> openai/*)
Enables user to expose custom routes to users with dynamic handling
* test: add more testing
* docs(custom_pricing.md): add debug tutorial for custom pricing
* test: skip codestral test - unreachable backend
* test: fix test
* fix(pattern_matching_deployments.py): fix typing
* test: cleanup codestral tests - backend api unavailable
* (refactor) prometheus async_log_success_event to be under 100 LOC (#6416)
* unit testig for prometheus
* unit testing for success metrics
* use 1 helper for _increment_token_metrics
* use helper for _increment_remaining_budget_metrics
* use _increment_remaining_budget_metrics
* use _increment_top_level_request_and_spend_metrics
* use helper for _set_latency_metrics
* remove noqa violation
* fix test prometheus
* test prometheus
* unit testing for all prometheus helper functions
* fix prom unit tests
* fix unit tests prometheus
* fix unit test prom
* (refactor) router - use static methods for client init utils (#6420)
* use InitalizeOpenAISDKClient
* use InitalizeOpenAISDKClient static method
* fix # noqa: PLR0915
* (code cleanup) remove unused and undocumented logging integrations - litedebugger, berrispend (#6406)
* code cleanup remove unused and undocumented code files
* fix unused logging integrations cleanup
* bump: version 1.50.3 → 1.50.4
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* feat(litellm_logging.py): refactor standard_logging_payload function to be <50 LOC
fixes issue where usage information was not following typed values
* fix(litellm_logging.py): fix completion start time handling
* unit testig for prometheus
* unit testing for success metrics
* use 1 helper for _increment_token_metrics
* use helper for _increment_remaining_budget_metrics
* use _increment_remaining_budget_metrics
* use _increment_top_level_request_and_spend_metrics
* use helper for _set_latency_metrics
* remove noqa violation
* fix test prometheus
* test prometheus
* unit testing for all prometheus helper functions
* fix prom unit tests
* fix unit tests prometheus
* fix unit test prom
* fix(utils.py): add 'disallowed_special' for token counting on .encode()
Fixes error when '<
endoftext
>' in string
* Revert "(fix) standard logging metadata + add unit testing (#6366)" (#6381)
This reverts commit 8359cb6fa9.
* add new 35 mode lcard (#6378)
* Add claude 3 5 sonnet 20241022 models for all provides (#6380)
* Add Claude 3.5 v2 on Amazon Bedrock and Vertex AI.
* added anthropic/claude-3-5-sonnet-20241022
* add new 35 mode lcard
---------
Co-authored-by: Paul Gauthier <paul@paulg.com>
Co-authored-by: lowjiansheng <15527690+lowjiansheng@users.noreply.github.com>
* test(skip-flaky-google-context-caching-test): google is not reliable. their sample code is also not working
* Fix metadata being overwritten in speech() (#6295)
* fix: adding missing redis cluster kwargs (#6318)
Co-authored-by: Ali Arian <ali.arian@breadfinancial.com>
* Add support for `max_completion_tokens` in Azure OpenAI (#6376)
Now that Azure supports `max_completion_tokens`, no need for special handling for this param and let it pass thru. More details: https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models?tabs=python-secure#api-support
* build(model_prices_and_context_window.json): add voyage-finance-2 pricing
Closes https://github.com/BerriAI/litellm/issues/6371
* build(model_prices_and_context_window.json): fix llama3.1 pricing model name on map
Closes https://github.com/BerriAI/litellm/issues/6310
* feat(realtime_streaming.py): just log specific events
Closes https://github.com/BerriAI/litellm/issues/6267
* fix(utils.py): more robust checking if unmapped vertex anthropic model belongs to that family of models
Fixes https://github.com/BerriAI/litellm/issues/6383
* Fix Ollama stream handling for tool calls with None content (#6155)
* test(test_max_completions): update test now that azure supports 'max_completion_tokens'
* fix(handler.py): fix linting error
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Low Jian Sheng <15527690+lowjiansheng@users.noreply.github.com>
Co-authored-by: David Manouchehri <david.manouchehri@ai.moda>
Co-authored-by: Paul Gauthier <paul@paulg.com>
Co-authored-by: John HU <hszqqq12@gmail.com>
Co-authored-by: Ali Arian <113945203+ali-arian@users.noreply.github.com>
Co-authored-by: Ali Arian <ali.arian@breadfinancial.com>
Co-authored-by: Anand Taralika <46954145+taralika@users.noreply.github.com>
Co-authored-by: Nolan Tremelling <34580718+NolanTrem@users.noreply.github.com>
* arize use helper for get_arize_opentelemetry_config
* use helper to get Arize OTEL config
* arize add helpers for arize
* docs allow using arize http endpoint
* fix importing OTEL for Arize
* use static methods for ArizeLogger
* fix ArizeLogger tests
* feat(proxy_cli.py): add new 'log_config' cli param
Allows passing logging.conf to uvicorn on startup
* docs(cli.md): add logging conf to uvicorn cli docs
* fix(get_llm_provider_logic.py): fix default api base for litellm_proxy
Fixes https://github.com/BerriAI/litellm/issues/6332
* feat(openai_like/embedding): Add support for jina ai embeddings
Closes https://github.com/BerriAI/litellm/issues/6337
* docs(deploy.md): update entrypoint.sh filepath post-refactor
Fixes outdated docs
* feat(prometheus.py): emit time_to_first_token metric on prometheus
Closes https://github.com/BerriAI/litellm/issues/6334
* fix(prometheus.py): only emit time to first token metric if stream is True
enables more accurate ttft usage
* test: handle vertex api instability
* fix(get_llm_provider_logic.py): fix import
* fix(openai.py): fix deepinfra default api base
* fix(anthropic/transformation.py): remove anthropic beta header (#6361)
* refactor(redis_cache.py): use a default cache value when writing to redis
prevent redis from blowing up in high traffic
* refactor(redis_cache.py): refactor all cache writes to use self.get_ttl
ensures default ttl always used when writing to redis
Prevents redis db from blowing up in prod
* fix get_response_headers
* unit testing for get headers
* unit testing for anthropic / azure openai headers
* increase test coverage for test_completion_response_ratelimit_headers
* fix test rate limit headers
* feat(custom_logger.py): expose new `async_dataset_hook` for modifying/rejecting argilla items before logging
Allows user more control on what gets logged to argilla for annotations
* feat(google_ai_studio_endpoints.py): add new `/azure/*` pass through route
enables pass-through for azure provider
* feat(utils.py): support checking ollama `/api/show` endpoint for retrieving ollama model info
Fixes https://github.com/BerriAI/litellm/issues/6322
* fix(user_api_key_auth.py): add `/key/delete` to an allowed_ui_routes
Fixes https://github.com/BerriAI/litellm/issues/6236
* fix(user_api_key_auth.py): remove type ignore
* fix(user_api_key_auth.py): route ui vs. api token checks differently
Fixes https://github.com/BerriAI/litellm/issues/6238
* feat(internal_user_endpoints.py): support setting models as a default internal user param
Closes https://github.com/BerriAI/litellm/issues/6239
* fix(user_api_key_auth.py): fix exception string
* fix(user_api_key_auth.py): fix error string
* fix: fix test
* refactor(main.py): streaming_chunk_builder
use <100 lines of code
refactor each component into a separate function - easier to maintain + test
* fix(utils.py): handle choices being None
openai pydantic schema updated
* fix(main.py): fix linting error
* feat(streaming_chunk_builder_utils.py): update stream chunk builder to support rebuilding audio chunks from openai
* test(test_custom_callback_input.py): test message redaction works for audio output
* fix(streaming_chunk_builder_utils.py): return anthropic token usage info directly
* fix(stream_chunk_builder_utils.py): run validation check before entering chunk processor
* fix(main.py): fix import
* refactor - use helpers for name space and hashing
* use openai to get the relevant supported params
* use helpers for getting cache key
* fix test caching
* use get/set helpers for preset cache keys
* make get_cache_key under 100 LOC
* fix _get_model_param_value
* fix _get_caching_group
* fix linting error
* add unit testing for get cache key
* test_generate_streaming_content
