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fix(utils.py): read env variables for known openai-compatible api's (e.g. perplexity), dynamically from th eenvironment
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4 changed files with 9 additions and 7 deletions
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@ -257,7 +257,7 @@ def completion(
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if deployment_id != None: # azure llms
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model=deployment_id
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custom_llm_provider="azure"
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model, custom_llm_provider = get_llm_provider(model=model, custom_llm_provider=custom_llm_provider, api_base=api_base)
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model, custom_llm_provider, dynamic_api_key = get_llm_provider(model=model, custom_llm_provider=custom_llm_provider, api_base=api_base)
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model_api_key = get_api_key(llm_provider=custom_llm_provider, dynamic_api_key=api_key) # get the api key from the environment if required for the model
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if model_api_key and "sk-litellm" in model_api_key:
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api_base = "https://proxy.litellm.ai"
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@ -391,6 +391,7 @@ def completion(
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# set API KEY
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api_key = (
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api_key or
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dynamic_api_key or # allows us to read env variables for compatible openai api's like perplexity
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litellm.api_key or
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litellm.openai_key or
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get_secret("OPENAI_API_KEY")
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@ -1371,7 +1372,7 @@ def embedding(
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caching=False,
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custom_llm_provider=None,
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):
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model, custom_llm_provider = get_llm_provider(model, custom_llm_provider)
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model, custom_llm_provider, dynamic_api_key = get_llm_provider(model, custom_llm_provider)
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try:
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response = None
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logging = litellm_logging_obj
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@ -1405,15 +1405,16 @@ def get_optional_params( # use the openai defaults
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def get_llm_provider(model: str, custom_llm_provider: Optional[str] = None, api_base: Optional[str] = None):
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try:
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dynamic_api_key = None
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# check if llm provider provided
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if custom_llm_provider:
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return model, custom_llm_provider
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return model, custom_llm_provider, dynamic_api_key
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# check if llm provider part of model name
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if model.split("/",1)[0] in litellm.provider_list:
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custom_llm_provider = model.split("/", 1)[0]
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model = model.split("/", 1)[1]
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return model, custom_llm_provider
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return model, custom_llm_provider, dynamic_api_key
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# check if api base is a known openai compatible endpoint
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if api_base:
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@ -1421,8 +1422,8 @@ def get_llm_provider(model: str, custom_llm_provider: Optional[str] = None, api_
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if endpoint in api_base:
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custom_llm_provider = "custom_openai"
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if endpoint == "api.perplexity.ai":
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litellm.api_key = os.getenv("PERPLEXITYAI_API_KEY")
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return model, custom_llm_provider
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dynamic_api_key = os.getenv("PERPLEXITYAI_API_KEY")
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return model, custom_llm_provider, dynamic_api_key
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# check if model in known model provider list -> for huggingface models, raise exception as they don't have a fixed provider (can be togetherai, anyscale, baseten, runpod, et.)
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## openai - chatcompletion + text completion
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@ -1479,7 +1480,7 @@ def get_llm_provider(model: str, custom_llm_provider: Optional[str] = None, api_
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print("\033[1;31mProvider List: https://docs.litellm.ai/docs/providers\033[0m")
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print()
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raise ValueError(f"LLM Provider NOT provided. Pass in the LLM provider you are trying to call. E.g. For 'Huggingface' inference endpoints pass in `completion(model='huggingface/{model}',..)` Learn more: https://docs.litellm.ai/docs/providers")
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return model, custom_llm_provider
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return model, custom_llm_provider, dynamic_api_key
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except Exception as e:
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raise e
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