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# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
from __future__ import annotations
from typing import Any, Optional, Sequence, Type, Union
from pydantic import BaseModel
from camel.configs.base_config import BaseConfig
from camel.types import NOT_GIVEN, NotGiven
class DeepSeekConfig(BaseConfig):
r"""Defines the parameters for generating chat completions using the
DeepSeek 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): Controls the diversity and focus of the
generated results. Higher values make the output more diverse,
while lower values make it more focused. (default: :obj:`1.0`)
response_format (object, optional): Specifies the format of the
returned content. The available values are `{"type": "text"}` or
`{"type": "json_object"}`. Setting it to `{"type": "json_object"}`
will output a standard JSON string.
(default: :obj:`{"type": "text"}`)
stream (bool, optional): If set, partial message deltas will be sent.
Tokens will be sent as data-only server-sent events (SSE) as
they become available, with the stream terminated by a
data: [DONE] message. (default: :obj:`False`)
stop (Union[str, list[str]], optional): Up to 16 sequences where
the API will stop generating further tokens. (default: :obj:`None`)
max_tokens (int, optional): The maximum number of tokens that can
be generated 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 -2.0 and 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. (default: :obj:`0.0`)
frequency_penalty (float, optional): Number between -2.0 and 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. (default: :obj:`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.
(default: :obj:`None`)
tool_choice (Union[dict[str, str], str], optional): Controls which
(if any) tool is called by the model. "none" means the model
will not call any tool and instead generates a message. "auto"
means the model can pick between generating a message or calling
one or more tools. "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. "none" is the default when no tools
are present. "auto" is the default if tools are present.
(default: :obj:`"auto"`)
logprobs (bool, optional): Whether to return log probabilities of
the output tokens or not. If true, returns the log probabilities
of each output token returned in the content of message.
(default: :obj:`False`)
top_logprobs (int, optional): An integer between 0 and 20 specifying
the number of most likely tokens to return at each token
position, each with an associated log probability. logprobs
must be set to true if this parameter is used.
(default: :obj:`None`)
include_usage (bool, optional): When streaming, specifies whether to
include usage information in `stream_options`. (default:
:obj:`True`)
"""
temperature: float = 0.2 # deepseek default: 1.0
top_p: float = 1.0
stream: bool = False
stop: Union[str, Sequence[str], NotGiven] = NOT_GIVEN
max_tokens: Union[int, NotGiven] = NOT_GIVEN
presence_penalty: float = 0.0
response_format: Union[Type[BaseModel], dict, NotGiven] = NOT_GIVEN
frequency_penalty: float = 0.0
tool_choice: Optional[Union[dict[str, str], str]] = None
logprobs: bool = False
top_logprobs: Optional[int] = None
def __init__(self, include_usage: bool = True, **kwargs):
super().__init__(**kwargs)
# Only set stream_options when stream is True
# Otherwise, it will raise error when calling the API
if self.stream:
self.stream_options = {"include_usage": include_usage}
def as_dict(self) -> dict[str, Any]:
r"""Convert the current configuration to a dictionary.
This method converts the current configuration object to a dictionary
representation, which can be used for serialization or other purposes.
Returns:
dict[str, Any]: A dictionary representation of the current
configuration.
"""
config_dict = self.model_dump()
if self.tools:
from camel.toolkits import FunctionTool
tools_schema = []
for tool in self.tools:
if not isinstance(tool, FunctionTool):
raise ValueError(
f"The tool {tool} should "
"be an instance of `FunctionTool`."
)
tools_schema.append(tool.get_openai_tool_schema())
config_dict["tools"] = NOT_GIVEN
return config_dict
DEEPSEEK_API_PARAMS = {param for param in DeepSeekConfig.model_fields.keys()}
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