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# http://www.apache.org/licenses/LICENSE-2.0
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# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
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()
}