forked from phoenix/litellm-mirror
(feat) embedding() remove junk params
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parent
0b4e10e068
commit
b3bca98561
1 changed files with 10 additions and 9 deletions
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@ -1672,11 +1672,7 @@ def embedding(
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model,
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input=[],
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# Optional params
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azure=False,
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force_timeout=60,
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litellm_call_id=None,
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litellm_logging_obj=None,
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logger_fn=None,
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timeout=600, # default to 10 minutes
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# set api_base, api_version, api_key
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api_base: Optional[str] = None,
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api_version: Optional[str] = None,
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@ -1684,6 +1680,9 @@ def embedding(
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api_type: Optional[str] = None,
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caching: bool=False,
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custom_llm_provider=None,
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litellm_call_id=None,
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litellm_logging_obj=None,
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logger_fn=None,
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**kwargs
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):
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"""
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@ -1692,8 +1691,7 @@ def embedding(
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Parameters:
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- model: The embedding model to use.
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- input: The input for which embeddings are to be generated.
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- azure: A boolean indicating whether to use the Azure API for embedding.
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- force_timeout: The timeout value for the API call.
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- timeout: The timeout value for the API call, default 10 mins
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- litellm_call_id: The call ID for litellm logging.
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- litellm_logging_obj: The litellm logging object.
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- logger_fn: The logger function.
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@ -1710,11 +1708,12 @@ def embedding(
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Raises:
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- exception_type: If an exception occurs during the API call.
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"""
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azure = kwargs.get("azure", None)
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model, custom_llm_provider, dynamic_api_key, api_base = get_llm_provider(model=model, custom_llm_provider=custom_llm_provider, api_base=api_base)
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try:
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response = None
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logging = litellm_logging_obj
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logging.update_environment_variables(model=model, user="", optional_params={}, litellm_params={"force_timeout": force_timeout, "azure": azure, "litellm_call_id": litellm_call_id, "logger_fn": logger_fn})
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logging.update_environment_variables(model=model, user="", optional_params={}, litellm_params={"timeout": timeout, "azure": azure, "litellm_call_id": litellm_call_id, "logger_fn": logger_fn})
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if azure == True or custom_llm_provider == "azure":
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# azure configs
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api_type = get_secret("AZURE_API_TYPE") or "azure"
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@ -1751,8 +1750,9 @@ def embedding(
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api_version=api_version,
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azure_ad_token=azure_ad_token,
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logging_obj=logging,
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timeout=timeout,
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model_response=EmbeddingResponse(),
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optional_params=kwargs
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optional_params=kwargs,
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)
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elif model in litellm.open_ai_embedding_models:
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api_base = (
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@ -1784,6 +1784,7 @@ def embedding(
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api_base=api_base,
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api_key=api_key,
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logging_obj=logging,
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timeout=timeout,
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model_response=EmbeddingResponse(),
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optional_params=kwargs
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)
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