* Fix Vertex AI function calling invoke: use JSON format instead of protobuf text format. (#6702)
* test: test tool_call conversion when arguments is empty dict
Fixes https://github.com/BerriAI/litellm/issues/6833
* fix(openai_like/handler.py): return more descriptive error message
Fixes https://github.com/BerriAI/litellm/issues/6812
* test: skip overloaded model
* docs(anthropic.md): update anthropic docs to show how to route to any new model
* feat(groq/): fake stream when 'response_format' param is passed
Groq doesn't support streaming when response_format is set
* feat(groq/): add response_format support for groq
Closes https://github.com/BerriAI/litellm/issues/6845
* fix(o1_handler.py): remove fake streaming for o1
Closes https://github.com/BerriAI/litellm/issues/6801
* build(model_prices_and_context_window.json): add groq llama3.2b model pricing
Closes https://github.com/BerriAI/litellm/issues/6807
* fix(utils.py): fix handling ollama response format param
Fixes https://github.com/BerriAI/litellm/issues/6848#issuecomment-2491215485
* docs(sidebars.js): refactor chat endpoint placement
* fix: fix linting errors
* test: fix test
* test: fix test
* fix(openai_like/handler): handle max retries
* fix(streaming_handler.py): fix streaming check for openai-compatible providers
* test: update test
* test: correctly handle model is overloaded error
* test: update test
* test: fix test
* test: mark flaky test
---------
Co-authored-by: Guowang Li <Guowang@users.noreply.github.com>
* feat(customer_endpoints.py): support passing budget duration via `/customer/new` endpoint
Closes https://github.com/BerriAI/litellm/issues/5651
* docs: add missing params to swagger + api documentation test
* docs: add documentation for all key endpoints
documents all params on swagger
* docs(internal_user_endpoints.py): document all /user/new params
Ensures all params are documented
* docs(team_endpoints.py): add missing documentation for team endpoints
Ensures 100% param documentation on swagger
* docs(organization_endpoints.py): document all org params
Adds documentation for all params in org endpoint
* docs(customer_endpoints.py): add coverage for all params on /customer endpoints
ensures all /customer/* params are documented
* ci(config.yml): add endpoint doc testing to ci/cd
* fix: fix internal_user_endpoints.py
* fix(internal_user_endpoints.py): support 'duration' param
* fix(partner_models/main.py): fix anthropic re-raise exception on vertex
* fix: fix pydantic obj
* build(model_prices_and_context_window.json): add new vertex claude model names
vertex claude changed model names - causes cost tracking errors
* fix(anthropic/chat/transformation.py): add json schema as values: json_schema
fixes passing pydantic obj to anthropic
Fixes https://github.com/BerriAI/litellm/issues/6766
* (feat): Add timestamp_granularities parameter to transcription API (#6457)
* Add timestamp_granularities parameter to transcription API
* add param to the local test
* fix(databricks/chat.py): handle max_retries optional param handling for openai-like calls
Fixes issue with calling finetuned vertex ai models via databricks route
* build(ui/): add team admins via proxy ui
* fix: fix linting error
* test: fix test
* docs(vertex.md): refactor docs
* test: handle overloaded anthropic model error
* test: remove duplicate test
* test: fix test
* test: update test to handle model overloaded error
---------
Co-authored-by: Show <35062952+BrunooShow@users.noreply.github.com>
* Update organization_endpoints.py to be able to list organizations (#6473)
* Update organization_endpoints.py to be able to list organizations
* Update test_organizations.py
* Update test_organizations.py
add test for list
* Update test_organizations.py
correct indentation
* Add unreleased Claude 3.5 Haiku models. (#6476)
---------
Co-authored-by: superpoussin22 <vincent.nadal@orange.fr>
Co-authored-by: David Manouchehri <david.manouchehri@ai.moda>
* fix(__init__.py): add 'watsonx_text' as mapped llm api route
Fixes https://github.com/BerriAI/litellm/issues/6663
* fix(opentelemetry.py): fix passing parallel tool calls to otel
Fixes https://github.com/BerriAI/litellm/issues/6677
* refactor(test_opentelemetry_unit_tests.py): create a base set of unit tests for all logging integrations - test for parallel tool call handling
reduces bugs in repo
* fix(__init__.py): update provider-model mapping to include all known provider-model mappings
Fixes https://github.com/BerriAI/litellm/issues/6669
* feat(anthropic): support passing document in llm api call
* docs(anthropic.md): add pdf anthropic call to docs + expose new 'supports_pdf_input' function
* fix(factory.py): fix linting error
* add bedrock image gen async support
* added async support for bedrock image gen
* move image gen testing
* add AmazonStability3Config
* add AmazonStability3Config config
* update AmazonStabilityConfig
* update get_optional_params_image_gen
* use 1 helper for _get_request_body
* add transform_response_dict_to_openai_response for stability3
* test sd3-large-v1:0
* unit testing for bedrock image gen
* fix load_vertex_ai_credentials
* fix test_aimage_generation_vertex_ai
* add stability.sd3-large-v1:0 to model cost map
* add stability.stability.sd3-large-v1:0 to docs
* Adding supports_response_schema to gpt-4o-2024-08-06 models
* o1 models do not support vision
---------
Co-authored-by: Emerson Gomes <emerson.gomes@thalesgroup.com>
* fix(azure.py): handle /openai/deployment in azure api base
* fix(factory.py): fix faulty anthropic tool result translation check
Fixes https://github.com/BerriAI/litellm/issues/6422
* fix(gpt_transformation.py): add support for parallel_tool_calls to azure
Fixes https://github.com/BerriAI/litellm/issues/6440
* fix(factory.py): support anthropic prompt caching for tool results
* fix(vertex_ai/common_utils): don't pop non-null required field
Fixes https://github.com/BerriAI/litellm/issues/6426
* feat(vertex_ai.py): support code_execution tool call for vertex ai + gemini
Closes https://github.com/BerriAI/litellm/issues/6434
* build(model_prices_and_context_window.json): Add 'supports_assistant_prefill' for bedrock claude-3-5-sonnet v2 models
Closes https://github.com/BerriAI/litellm/issues/6437
* fix(types/utils.py): fix linting
* test: update test to include required fields
* test: fix test
* test: handle flaky test
* test: remove e2e test - hitting gemini rate limits
* fix(utils.py): support passing dynamic api base to validate_environment
Returns True if just api base is required and api base is passed
* fix(litellm_pre_call_utils.py): feature flag sending client headers to llm api
Fixes https://github.com/BerriAI/litellm/issues/6410
* fix(anthropic/chat/transformation.py): return correct error message
* fix(http_handler.py): add error response text in places where we expect it
* fix(factory.py): handle base case of no non-system messages to bedrock
Fixes https://github.com/BerriAI/litellm/issues/6411
* feat(cohere/embed): Support cohere image embeddings
Closes https://github.com/BerriAI/litellm/issues/6413
* fix(__init__.py): fix linting error
* docs(supported_embedding.md): add image embedding example to docs
* feat(cohere/embed): use cohere embedding returned usage for cost calc
* build(model_prices_and_context_window.json): add embed-english-v3.0 details (image cost + 'supports_image_input' flag)
* fix(cohere_transformation.py): fix linting error
* test(test_proxy_server.py): cleanup test
* test: cleanup test
* fix: fix linting errors
* 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>
* docs(prompt_caching.md): add prompt caching cost calc example to docs
* docs(prompt_caching.md): add proxy examples to docs
* feat(utils.py): expose new helper `supports_prompt_caching()` to check if a model supports prompt caching
* docs(prompt_caching.md): add docs on checking model support for prompt caching
* build: fix invalid json
In model_prices_and_context_window.json, openrouter/* models all have litellm_provider set as "openrouter", except for four openrouter/openai/* models, which were set to "openai".
I suppose they must be set to "openrouter", so one can know it should use the openrouter API for this model.
* LiteLLM Minor Fixes & Improvements (09/26/2024) (#5925)
* fix(litellm_logging.py): don't initialize prometheus_logger if non premium user
Prevents bad error messages in logs
Fixes https://github.com/BerriAI/litellm/issues/5897
* Add Support for Custom Providers in Vision and Function Call Utils (#5688)
* Add Support for Custom Providers in Vision and Function Call Utils Lookup
* Remove parallel function call due to missing model info param
* Add Unit Tests for Vision and Function Call Changes
* fix-#5920: set header value to string to fix "'int' object has no att… (#5922)
* LiteLLM Minor Fixes & Improvements (09/24/2024) (#5880)
* LiteLLM Minor Fixes & Improvements (09/23/2024) (#5842)
* feat(auth_utils.py): enable admin to allow client-side credentials to be passed
Makes it easier for devs to experiment with finetuned fireworks ai models
* feat(router.py): allow setting configurable_clientside_auth_params for a model
Closes https://github.com/BerriAI/litellm/issues/5843
* build(model_prices_and_context_window.json): fix anthropic claude-3-5-sonnet max output token limit
Fixes https://github.com/BerriAI/litellm/issues/5850
* fix(azure_ai/): support content list for azure ai
Fixes https://github.com/BerriAI/litellm/issues/4237
* fix(litellm_logging.py): always set saved_cache_cost
Set to 0 by default
* fix(fireworks_ai/cost_calculator.py): add fireworks ai default pricing
handles calling 405b+ size models
* fix(slack_alerting.py): fix error alerting for failed spend tracking
Fixes regression with slack alerting error monitoring
* fix(vertex_and_google_ai_studio_gemini.py): handle gemini no candidates in streaming chunk error
* docs(bedrock.md): add llama3-1 models
* test: fix tests
* fix(azure_ai/chat): fix transformation for azure ai calls
* feat(azure_ai/embed): Add azure ai embeddings support
Closes https://github.com/BerriAI/litellm/issues/5861
* fix(azure_ai/embed): enable async embedding
* feat(azure_ai/embed): support azure ai multimodal embeddings
* fix(azure_ai/embed): support async multi modal embeddings
* feat(together_ai/embed): support together ai embedding calls
* feat(rerank/main.py): log source documents for rerank endpoints to langfuse
improves rerank endpoint logging
* fix(langfuse.py): support logging `/audio/speech` input to langfuse
* test(test_embedding.py): fix test
* test(test_completion_cost.py): fix helper util
* fix-#5920: set header value to string to fix "'int' object has no attribute 'encode'"
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* Revert "fix-#5920: set header value to string to fix "'int' object has no att…" (#5926)
This reverts commit a554ae2695.
* build(model_prices_and_context_window.json): add azure ai cohere rerank model pricing
Enables cost tracking for azure ai cohere rerank models
* fix(litellm_logging.py): fix debug log to be clearer
Closes https://github.com/BerriAI/litellm/issues/5909
* test(test_utils.py): fix test name
* fix(azure_ai/cost_calculator.py): support cost tracking for azure ai rerank models
* fix(azure_ai): fix azure ai base model cost tracking for rerank endpoints
* fix(converse_handler.py): support new llama 3-2 models
Fixes https://github.com/BerriAI/litellm/issues/5901
* fix(litellm_logging.py): ensure response is redacted for standard message logging
Fixes https://github.com/BerriAI/litellm/issues/5890#issuecomment-2378242360
* fix(cost_calculator.py): use 'get_model_info' for cohere rerank cost calculation
allows user to set custom cost for model
* fix(config.yml): fix docker hub auht
* build(config.yml): add docker auth to all tests
* fix(db/create_views.py): fix linting error
* fix(main.py): fix circular import
* fix(azure_ai/__init__.py): fix circular import
* fix(main.py): fix import
* fix: fix linting errors
* test: fix test
* fix(proxy_server.py): pass premium user value on startup
used for prometheus init
---------
Co-authored-by: Cole Murray <colemurray.cs@gmail.com>
Co-authored-by: bravomark <62681807+bravomark@users.noreply.github.com>
* handle streaming for azure ai studio error
* [Perf Proxy] parallel request limiter - use one cache update call (#5932)
* fix parallel request limiter - use one cache update call
* ci/cd run again
* run ci/cd again
* use docker username password
* fix config.yml
* fix config
* fix config
* fix config.yml
* ci/cd run again
* use correct typing for batch set cache
* fix async_set_cache_pipeline
* fix only check user id tpm / rpm limits when limits set
* fix test_openai_azure_embedding_with_oidc_and_cf
* test: fix test
* test(test_rerank.py): fix test
---------
Co-authored-by: Cole Murray <colemurray.cs@gmail.com>
Co-authored-by: bravomark <62681807+bravomark@users.noreply.github.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
* LiteLLM Minor Fixes & Improvements (09/23/2024) (#5842)
* feat(auth_utils.py): enable admin to allow client-side credentials to be passed
Makes it easier for devs to experiment with finetuned fireworks ai models
* feat(router.py): allow setting configurable_clientside_auth_params for a model
Closes https://github.com/BerriAI/litellm/issues/5843
* build(model_prices_and_context_window.json): fix anthropic claude-3-5-sonnet max output token limit
Fixes https://github.com/BerriAI/litellm/issues/5850
* fix(azure_ai/): support content list for azure ai
Fixes https://github.com/BerriAI/litellm/issues/4237
* fix(litellm_logging.py): always set saved_cache_cost
Set to 0 by default
* fix(fireworks_ai/cost_calculator.py): add fireworks ai default pricing
handles calling 405b+ size models
* fix(slack_alerting.py): fix error alerting for failed spend tracking
Fixes regression with slack alerting error monitoring
* fix(vertex_and_google_ai_studio_gemini.py): handle gemini no candidates in streaming chunk error
* docs(bedrock.md): add llama3-1 models
* test: fix tests
* fix(azure_ai/chat): fix transformation for azure ai calls
* feat(azure_ai/embed): Add azure ai embeddings support
Closes https://github.com/BerriAI/litellm/issues/5861
* fix(azure_ai/embed): enable async embedding
* feat(azure_ai/embed): support azure ai multimodal embeddings
* fix(azure_ai/embed): support async multi modal embeddings
* feat(together_ai/embed): support together ai embedding calls
* feat(rerank/main.py): log source documents for rerank endpoints to langfuse
improves rerank endpoint logging
* fix(langfuse.py): support logging `/audio/speech` input to langfuse
* test(test_embedding.py): fix test
* test(test_completion_cost.py): fix helper util
* LiteLLM Minor Fixes & Improvements (09/23/2024) (#5842)
* feat(auth_utils.py): enable admin to allow client-side credentials to be passed
Makes it easier for devs to experiment with finetuned fireworks ai models
* feat(router.py): allow setting configurable_clientside_auth_params for a model
Closes https://github.com/BerriAI/litellm/issues/5843
* build(model_prices_and_context_window.json): fix anthropic claude-3-5-sonnet max output token limit
Fixes https://github.com/BerriAI/litellm/issues/5850
* fix(azure_ai/): support content list for azure ai
Fixes https://github.com/BerriAI/litellm/issues/4237
* fix(litellm_logging.py): always set saved_cache_cost
Set to 0 by default
* fix(fireworks_ai/cost_calculator.py): add fireworks ai default pricing
handles calling 405b+ size models
* fix(slack_alerting.py): fix error alerting for failed spend tracking
Fixes regression with slack alerting error monitoring
* fix(vertex_and_google_ai_studio_gemini.py): handle gemini no candidates in streaming chunk error
* docs(bedrock.md): add llama3-1 models
* test: fix tests
* fix(azure_ai/chat): fix transformation for azure ai calls
