Source code for camel.models.openai_model

# ========= 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.
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#
#     http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
import os
import warnings
from typing import Any, Dict, List, Optional, Union

from openai import OpenAI, Stream

from camel.configs import OPENAI_API_PARAMS, ChatGPTConfig
from camel.messages import OpenAIMessage
from camel.models import BaseModelBackend
from camel.types import (
    NOT_GIVEN,
    ChatCompletion,
    ChatCompletionChunk,
    ModelType,
)
from camel.utils import (
    BaseTokenCounter,
    OpenAITokenCounter,
    api_keys_required,
)


[docs] class OpenAIModel(BaseModelBackend): r"""OpenAI API in a unified BaseModelBackend interface. Args: model_type (Union[ModelType, str]): Model for which a backend is created, one of GPT_* series. model_config_dict (Optional[Dict[str, Any]], optional): A dictionary that will be fed into:obj:`openai.ChatCompletion.create()`. If :obj:`None`, :obj:`ChatGPTConfig().as_dict()` will be used. (default: :obj:`None`) api_key (Optional[str], optional): The API key for authenticating with the OpenAI service. (default: :obj:`None`) url (Optional[str], optional): The url to the OpenAI service. (default: :obj:`None`) token_counter (Optional[BaseTokenCounter], optional): Token counter to use for the model. If not provided, :obj:`OpenAITokenCounter` will be used. (default: :obj:`None`) """ @api_keys_required( [ ("api_key", "OPENAI_API_KEY"), ] ) def __init__( self, model_type: Union[ModelType, str], model_config_dict: Optional[Dict[str, Any]] = None, api_key: Optional[str] = None, url: Optional[str] = None, token_counter: Optional[BaseTokenCounter] = None, ) -> None: if model_config_dict is None: model_config_dict = ChatGPTConfig().as_dict() api_key = api_key or os.environ.get("OPENAI_API_KEY") url = url or os.environ.get("OPENAI_API_BASE_URL") super().__init__( model_type, model_config_dict, api_key, url, token_counter ) self._client = OpenAI( timeout=180, max_retries=3, base_url=self._url, api_key=self._api_key, ) @property def token_counter(self) -> BaseTokenCounter: r"""Initialize the token counter for the model backend. Returns: BaseTokenCounter: The token counter following the model's tokenization style. """ if not self._token_counter: self._token_counter = OpenAITokenCounter(self.model_type) return self._token_counter
[docs] def run( self, messages: List[OpenAIMessage], ) -> Union[ChatCompletion, Stream[ChatCompletionChunk]]: r"""Runs inference of OpenAI chat completion. Args: messages (List[OpenAIMessage]): Message list with the chat history in OpenAI API format. Returns: Union[ChatCompletion, Stream[ChatCompletionChunk]]: `ChatCompletion` in the non-stream mode, or `Stream[ChatCompletionChunk]` in the stream mode. """ # o1-preview and o1-mini have Beta limitations # reference: https://platform.openai.com/docs/guides/reasoning if self.model_type in [ ModelType.O1, ModelType.O1_MINI, ModelType.O1_PREVIEW, ]: warnings.warn( "Warning: You are using an O1 model (O1_MINI or O1_PREVIEW), " "which has certain limitations, reference: " "`https://platform.openai.com/docs/guides/reasoning`.", UserWarning, ) # Check and remove unsupported parameters and reset the fixed # parameters unsupported_keys = [ "temperature", "top_p", "presence_penalty", "frequency_penalty", "logprobs", "top_logprobs", "logit_bias", ] for key in unsupported_keys: if key in self.model_config_dict: del self.model_config_dict[key] if self.model_config_dict.get("response_format"): # stream is not supported in beta.chat.completions.parse if "stream" in self.model_config_dict: del self.model_config_dict["stream"] response = self._client.beta.chat.completions.parse( messages=messages, model=self.model_type, **self.model_config_dict, ) return self._to_chat_completion(response) # Removing 'strict': True from the dictionary for # client.chat.completions.create if self.model_config_dict.get('tools') is not NOT_GIVEN: for tool in self.model_config_dict.get('tools', []): function_dict = tool.get('function', {}) if 'strict' in function_dict: del function_dict['strict'] response = self._client.chat.completions.create( messages=messages, model=self.model_type, **self.model_config_dict, ) return response
[docs] def check_model_config(self): r"""Check whether the model configuration contains any unexpected arguments to OpenAI API. Raises: ValueError: If the model configuration dictionary contains any unexpected arguments to OpenAI API. """ for param in self.model_config_dict: if param not in OPENAI_API_PARAMS: raise ValueError( f"Unexpected argument `{param}` is " "input into OpenAI model backend." )
@property def stream(self) -> bool: r"""Returns whether the model is in stream mode, which sends partial results each time. Returns: bool: Whether the model is in stream mode. """ return self.model_config_dict.get('stream', False)