* 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Fixes outdated docs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)
* feat(together_ai/completion): handle together ai completion calls
* fix: handle list of int / list of list of int for text completion calls
* fix(utils.py): check if base model in bedrock converse model list
Fixes https://github.com/BerriAI/litellm/issues/6003
* test(test_optional_params.py): add unit tests for bedrock optional param mapping
Fixes https://github.com/BerriAI/litellm/issues/6003
* feat(utils.py): enable passing dummy tool call for anthropic/bedrock calls if tool_use blocks exist
Fixes https://github.com/BerriAI/litellm/issues/5388
* fixed an issue with tool use of claude models with anthropic and bedrock (#6013)
* fix(utils.py): handle empty schema for anthropic/bedrock
Fixes https://github.com/BerriAI/litellm/issues/6012
* fix: fix linting errors
* fix: fix linting errors
* fix: fix linting errors
* fix(proxy_cli.py): fix import route for app + health checks path (#6026)
* (testing): Enable testing us.anthropic.claude-3-haiku-20240307-v1:0. (#6018)
* fix(proxy_cli.py): fix import route for app + health checks gettsburg.wav
Fixes https://github.com/BerriAI/litellm/issues/5999
---------
Co-authored-by: David Manouchehri <david.manouchehri@ai.moda>
---------
Co-authored-by: Ved Patwardhan <54766411+vedpatwardhan@users.noreply.github.com>
Co-authored-by: David Manouchehri <david.manouchehri@ai.moda>
* fix drop_params_from_unprocessable_entity_error
* fix drop_params_from_unprocessable_entity_error for async azure ai requests
* fix extra body reading azure ai studio
* 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
* add max_completion_tokens
* add max_completion_tokens
* add max_completion_tokens support for OpenAI models
* add max_completion_tokens param
* add max_completion_tokens for bedrock converse models
* add test for converse maxTokens
* fix openai o1 param mapping test
* move test optional params
* add max_completion_tokens for anthropic api
* fix conftest
* add max_completion tokens for vertex ai partner models
* add max_completion_tokens for fireworks ai
* add max_completion_tokens for hf rest api
* add test for param mapping
* add param mapping for vertex, gemini + testing
* predibase is the most unstable and unusable llm api in prod, can't handle our ci/cd
* add max_completion_tokens to openai supported params
* fix fireworks ai param mapping
