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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
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25 changed files with 1675 additions and 340 deletions
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@ -774,3 +774,21 @@ def test_usage_object_null_tokens():
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usage_obj = litellm.Usage(prompt_tokens=2, completion_tokens=None, total_tokens=2)
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assert usage_obj.completion_tokens == 0
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def test_is_base64_encoded():
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import base64
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import requests
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litellm.set_verbose = True
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url = "https://dummyimage.com/100/100/fff&text=Test+image"
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response = requests.get(url)
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file_data = response.content
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encoded_file = base64.b64encode(file_data).decode("utf-8")
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base64_image = f"data:image/png;base64,{encoded_file}"
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from litellm.utils import is_base64_encoded
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assert is_base64_encoded(s=base64_image) is True
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