* 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>
* 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>
* refactor: move gemini translation logic inside the transformation.py file
easier to isolate the gemini translation logic
* fix(gemini-transformation): support multiple tool calls in message body
Merges https://github.com/BerriAI/litellm/pull/6487/files
* test(test_vertex.py): add remaining tests from https://github.com/BerriAI/litellm/pull/6487
* fix(gemini-transformation): return tool calls for multiple tool calls
* fix: support passing logprobs param for vertex + gemini
* feat(vertex_ai): add logprobs support for gemini calls
* fix(anthropic/chat/transformation.py): fix disable parallel tool use flag
* fix: fix linting error
* fix(_logging.py): log stacktrace information in json logs
Closes https://github.com/BerriAI/litellm/issues/6497
* fix(utils.py): fix mem leak for async stream + completion
Uses a global executor pool instead of creating a new thread on each request
Fixes https://github.com/BerriAI/litellm/issues/6404
* fix(factory.py): handle tool call + content in assistant message for bedrock
* fix: fix import
* fix(factory.py): maintain support for content as a str in assistant response
* fix: fix import
* test: cleanup test
* fix(vertex_and_google_ai_studio/): return none for content if no str value
* test: retry flaky tests
* (UI) Fix viewing members, keys in a team + added testing (#6514)
* fix listing teams on ui
* LiteLLM Minor Fixes & Improvements (10/28/2024) (#6475)
* fix(anthropic/chat/transformation.py): support anthropic disable_parallel_tool_use param
Fixes https://github.com/BerriAI/litellm/issues/6456
* feat(anthropic/chat/transformation.py): support anthropic computer tool use
Closes https://github.com/BerriAI/litellm/issues/6427
* fix(vertex_ai/common_utils.py): parse out '$schema' when calling vertex ai
Fixes issue when trying to call vertex from vercel sdk
* fix(main.py): add 'extra_headers' support for azure on all translation endpoints
Fixes https://github.com/BerriAI/litellm/issues/6465
* fix: fix linting errors
* fix(transformation.py): handle no beta headers for anthropic
* test: cleanup test
* fix: fix linting error
* fix: fix linting errors
* fix: fix linting errors
* fix(transformation.py): handle dummy tool call
* fix(main.py): fix linting error
* fix(azure.py): pass required param
* LiteLLM Minor Fixes & Improvements (10/24/2024) (#6441)
* 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
* Litellm dev 10 26 2024 (#6472)
* docs(exception_mapping.md): add missing exception types
Fixes https://github.com/Aider-AI/aider/issues/2120#issuecomment-2438971183
* fix(main.py): register custom model pricing with specific key
Ensure custom model pricing is registered to the specific model+provider key combination
* test: make testing more robust for custom pricing
* fix(redis_cache.py): instrument otel logging for sync redis calls
ensures complete coverage for all redis cache calls
* (Testing) Add unit testing for DualCache - ensure in memory cache is used when expected (#6471)
* test test_dual_cache_get_set
* unit testing for dual cache
* fix async_set_cache_sadd
* test_dual_cache_local_only
* redis otel tracing + async support for latency routing (#6452)
* docs(exception_mapping.md): add missing exception types
Fixes https://github.com/Aider-AI/aider/issues/2120#issuecomment-2438971183
* fix(main.py): register custom model pricing with specific key
Ensure custom model pricing is registered to the specific model+provider key combination
* test: make testing more robust for custom pricing
* fix(redis_cache.py): instrument otel logging for sync redis calls
ensures complete coverage for all redis cache calls
* refactor: pass parent_otel_span for redis caching calls in router
allows for more observability into what calls are causing latency issues
* test: update tests with new params
* refactor: ensure e2e otel tracing for router
* refactor(router.py): add more otel tracing acrosss router
catch all latency issues for router requests
* fix: fix linting error
* fix(router.py): fix linting error
* fix: fix test
* test: fix tests
* fix(dual_cache.py): pass ttl to redis cache
* fix: fix param
* fix(dual_cache.py): set default value for parent_otel_span
* fix(transformation.py): support 'response_format' for anthropic calls
* fix(transformation.py): check for cache_control inside 'function' block
* fix: fix linting error
* fix: fix linting errors
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
---------
Co-authored-by: Krish Dholakia <krrishdholakia@gmail.com>
* ui new build
* Add retry strat (#6520)
Signed-off-by: dbczumar <corey.zumar@databricks.com>
* (fix) slack alerting - don't spam the failed cost tracking alert for the same model (#6543)
* fix use failing_model as cache key for failed_tracking_alert
* fix use standard logging payload for getting response cost
* fix kwargs.get("response_cost")
* fix getting response cost
* (feat) add XAI ChatCompletion Support (#6373)
* init commit for XAI
* add full logic for xai chat completion
* test_completion_xai
* docs xAI
* add xai/grok-beta
* test_xai_chat_config_get_openai_compatible_provider_info
* test_xai_chat_config_map_openai_params
* add xai streaming test
---------
Signed-off-by: dbczumar <corey.zumar@databricks.com>
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
Co-authored-by: Corey Zumar <39497902+dbczumar@users.noreply.github.com>
* 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)
* use vertex llm as base class for embeddings
* use correct vertex class in main.py
* set_headers in vertex llm base
* add types for vertex embedding requests
* add embedding handler for vertex
* use async mode for vertex embedding tests
* use vertexAI textEmbeddingConfig
* fix linting
* add sync and async mode testing for vertex ai embeddings
