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community: aligning ChatLiteLLM default parameters with litellm (#30360)
**Description:** Since `ChatLiteLLM` is forwarding most parameters to `litellm.completion(...)`, there is no reason to set other default values than the ones defined by `litellm`. In the case of parameter 'n', it also provokes an issue when trying to call a serverless endpoint on Azure, as it is considered an extra parameter. So we need to keep it optional. We can debate about backward compatibility of this change: in my opinion, there should not be big issues since from my experience, calling `litellm.completion()` without these parameters works fine. **Issue:** - #29679 **Dependencies:** None
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@ -259,7 +259,7 @@ class ChatLiteLLM(BaseChatModel):
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organization: Optional[str] = None
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custom_llm_provider: Optional[str] = None
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request_timeout: Optional[Union[float, Tuple[float, float]]] = None
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temperature: Optional[float] = 1
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temperature: Optional[float] = None
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"""Run inference with this temperature. Must be in the closed
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interval [0.0, 1.0]."""
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model_kwargs: Dict[str, Any] = Field(default_factory=dict)
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@ -270,12 +270,12 @@ class ChatLiteLLM(BaseChatModel):
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top_k: Optional[int] = None
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"""Decode using top-k sampling: consider the set of top_k most probable tokens.
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Must be positive."""
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n: int = 1
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n: Optional[int] = None
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"""Number of chat completions to generate for each prompt. Note that the API may
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not return the full n completions if duplicates are generated."""
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max_tokens: Optional[int] = None
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max_retries: int = 6
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max_retries: int = 1
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@property
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def _default_params(self) -> Dict[str, Any]:
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