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from __future__ import annotations |
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from typing import Any, Optional, Union |
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from camel.configs.base_config import BaseConfig |
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class RekaConfig(BaseConfig): |
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r"""Defines the parameters for generating chat completions using the |
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Reka API. |
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Reference: https://docs.reka.ai/api-reference/chat/create |
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Args: |
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temperature (Optional[float], optional): temperature the temperature |
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to use for sampling, e.g. 0.5. |
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top_p (Optional[float], optional): the cumulative probability of |
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tokens to generate, e.g. 0.9. Defaults to None. |
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top_k (Optional[int], optional): Parameter which forces the model to |
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only consider the tokens with the `top_k` highest probabilities at |
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the next step. Defaults to 1024. |
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max_tokens (Optional[int], optional): the maximum number of tokens to |
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generate, e.g. 100. Defaults to None. |
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stop (Optional[Union[str,list[str]]]): Stop generation if this token |
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is detected. Or if one of these tokens is detected when providing |
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a string list. |
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seed (Optional[int], optional): the random seed to use for sampling, e. |
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g. 42. Defaults to None. |
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presence_penalty (float, optional): Number between :obj:`-2.0` and |
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:obj:`2.0`. Positive values penalize new tokens based on whether |
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they appear in the text so far, increasing the model's likelihood |
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to talk about new topics. See more information about frequency and |
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presence penalties. (default: :obj:`0.0`) |
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frequency_penalty (float, optional): Number between :obj:`-2.0` and |
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:obj:`2.0`. Positive values penalize new tokens based on their |
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existing frequency in the text so far, decreasing the model's |
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likelihood to repeat the same line verbatim. See more information |
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about frequency and presence penalties. (default: :obj:`0.0`) |
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use_search_engine (Optional[bool]): Whether to consider using search |
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engine to complete the request. Note that even if this is set to |
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`True`, the model might decide to not use search. |
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""" |
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temperature: Optional[float] = None |
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top_p: Optional[float] = None |
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top_k: Optional[int] = None |
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max_tokens: Optional[int] = None |
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stop: Optional[Union[str, list[str]]] = None |
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seed: Optional[int] = None |
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frequency_penalty: float = 0.0 |
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presence_penalty: float = 0.0 |
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use_search_engine: Optional[bool] = False |
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def as_dict(self) -> dict[str, Any]: |
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config_dict = super().as_dict() |
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if "tools" in config_dict: |
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del config_dict["tools"] |
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return config_dict |
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REKA_API_PARAMS = {param for param in RekaConfig().model_fields.keys()} |
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