Source code for camel.configs

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from abc import ABC
from dataclasses import asdict, dataclass, field
from typing import Any, Dict, List, Optional, Sequence, Union

from camel.functions import OpenAIFunction


[docs]@dataclass(frozen=True) class BaseConfig(ABC): pass
[docs]@dataclass(frozen=True) class ChatGPTConfig(BaseConfig): r"""Defines the parameters for generating chat completions using the OpenAI API. Args: 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:`0.2`) 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:`1.0`) n (int, optional): How many chat completion choices to generate for each input message. (default: :obj:`1`) stream (bool, optional): If True, partial message deltas will be sent as data-only server-sent events as they become available. (default: :obj:`False`) 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:`0.0`) 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:`0.0`) logit_bias (dict, optional): Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from :obj:`-100` to :obj:`100`. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between:obj:` -1` and :obj:`1` should decrease or increase likelihood of selection; values like :obj:`-100` or :obj:`100` should result in a ban or exclusive selection of the relevant token. (default: :obj:`{}`) user (str, optional): A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. (default: :obj:`""`) """ temperature: float = 0.2 # openai default: 1.0 top_p: float = 1.0 n: int = 1 stream: bool = False stop: Optional[Union[str, Sequence[str]]] = None max_tokens: Optional[int] = None presence_penalty: float = 0.0 frequency_penalty: float = 0.0 logit_bias: Dict = field(default_factory=dict) user: str = ""
[docs]@dataclass(frozen=True) class FunctionCallingConfig(ChatGPTConfig): r"""Defines the parameters for generating chat completions using the OpenAI API with functions included. Args: functions (List[Dict[str, Any]]): A list of functions the model may generate JSON inputs for. function_call (Union[Dict[str, str], str], optional): Controls how the model responds to function calls. :obj:`"none"` means the model does not call a function, and responds to the end-user. :obj:`"auto"` means the model can pick between an end-user or calling a function. Specifying a particular function via :obj:`{"name": "my_function"}` forces the model to call that function. (default: :obj:`"auto"`) """ functions: List[Dict[str, Any]] = field(default_factory=list) function_call: Union[Dict[str, str], str] = "auto"
[docs] @classmethod def from_openai_function_list( cls, function_list: List[OpenAIFunction], function_call: Union[Dict[str, str], str] = "auto", kwargs: Optional[Dict[str, Any]] = None, ): r"""Class method for creating an instance given the function-related arguments. Args: function_list (List[OpenAIFunction]): The list of function objects to be loaded into this configuration and passed to the model. function_call (Union[Dict[str, str], str], optional): Controls how the model responds to function calls, as specified in the creator's documentation. kwargs (Optional[Dict[str, Any]]): The extra modifications to be made on the original settings defined in :obj:`ChatGPTConfig`. Return: FunctionCallingConfig: A new instance which loads the given function list into a list of dictionaries and the input :obj:`function_call` argument. """ return cls( functions=[func.as_dict() for func in function_list], function_call=function_call, **(kwargs or {}), )
[docs]@dataclass(frozen=True) class OpenSourceConfig(BaseConfig): r"""Defines parameters for setting up open-source models and includes parameters to be passed to chat completion function of OpenAI API. Args: model_path (str): The path to a local folder containing the model files or the model card in HuggingFace hub. server_url (str): The URL to the server running the model inference which will be used as the API base of OpenAI API. api_params (ChatGPTConfig): An instance of :obj:ChatGPTConfig to contain the arguments to be passed to OpenAI API. """ model_path: str server_url: str api_params: ChatGPTConfig = ChatGPTConfig()
OPENAI_API_PARAMS = {param for param in asdict(ChatGPTConfig()).keys()} OPENAI_API_PARAMS_WITH_FUNCTIONS = { param for param in asdict(FunctionCallingConfig()).keys() }