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LMStudioConfig

class LMStudioConfig(BaseConfig):

Defines the parameters for generating chat completions using OpenAI compatibility.

Parameters:

  • temperature (float, optional): Sampling temperature to use, between :obj:0 and :obj:2. Higher values make the output more random, while lower values make it more focused and deterministic. (default: :obj:None)
  • top_p (float, optional): An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So :obj:0.1 means only the tokens comprising the top 10% probability mass are considered. (default: :obj:None)
  • response_format (object, optional): An object specifying the format that the model must output. Compatible with GPT-4 Turbo and all GPT-3.5 Turbo models newer than gpt-3.5-turbo-1106. Setting to {"type": "json_object"} enables JSON mode, which guarantees the message the model generates is valid JSON. Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly “stuck” request. Also note that the message content may be partially cut off if finish_reason=“length”, which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.
  • stream (bool, optional): If True, partial message deltas will be sent as data-only server-sent events as they become available. (default: :obj:None)
  • stop (str or list, optional): Up to :obj:4 sequences where the API will stop generating further tokens. (default: :obj:None)
  • max_tokens (int, optional): The maximum number of tokens to generate in the chat completion. The total length of input tokens and generated tokens is limited by the model’s context length. (default: :obj:None)
  • presence_penalty (float, optional): Number between :obj:-2.0 and :obj:2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model’s likelihood to talk about new topics. See more information about frequency and presence penalties. (default: :obj:None)
  • frequency_penalty (float, optional): Number between :obj:-2.0 and :obj:2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim. See more information about frequency and presence penalties. (default: :obj:None)
  • tools (list[FunctionTool], optional): A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
  • tool_choice (Union[dict[str, str], str], optional): Controls which (if any) tool is called by the model. :obj:"none" means the model will not call any tool and instead generates a message. :obj:"auto" means the model can pick between generating a message or calling one or more tools. :obj:"required" means the model must call one or more tools. Specifying a particular tool via {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool. :obj:"none" is the default when no tools are present. :obj:"auto" is the default if tools are present.