Source code for camel.configs.aiml_config

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# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
from __future__ import annotations

from typing import Sequence, Type, Union

from pydantic import BaseModel, Field

from camel.configs.base_config import BaseConfig
from camel.types import NOT_GIVEN, NotGiven




class AIMLConfig(BaseConfig):
    r"""Defines the parameters for generating chat completions using the
    AIML API.

    Args:
        temperature (float, optional): Determines the degree of randomness
            in the response. (default: :obj:`0.7`)
        top_p (float, optional): The top_p (nucleus) parameter is used to
            dynamically adjust the number of choices for each predicted token
            based on the cumulative probabilities. (default: :obj:`0.7`)
        n (int, optional): Number of generations to return. (default::obj:`1`)
        response_format (object, optional): An object specifying the format
            that the model must output.
        stream (bool, optional): If set, tokens are returned as Server-Sent
            Events as they are made 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.
            (default: :obj:`None`)
        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:`{}`)
        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`)
        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`)
        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.
    """

    temperature: float = 0.7
    top_p: float = 0.7
    n: int = 1
    stream: bool = False
    stop: Union[str, Sequence[str], NotGiven] = NOT_GIVEN
    max_tokens: Union[int, NotGiven] = NOT_GIVEN
    logit_bias: dict = Field(default_factory=dict)
    response_format: Union[Type[BaseModel], dict, NotGiven] = NOT_GIVEN
    presence_penalty: float = 0.0
    frequency_penalty: float = 0.0



AIML_API_PARAMS = {param for param in AIMLConfig.model_fields.keys()}