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* 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 |
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