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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. ========= | |
| 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 ( | |
| ChatCompletion, | |
| ChatCompletionChunk, | |
| ModelType, | |
| ) | |
| from camel.utils import ( | |
| BaseTokenCounter, | |
| OpenAITokenCounter, | |
| api_keys_required, | |
| ) | |
| 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`) | |
| """ | |
| 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=5000, | |
| max_retries=3, | |
| base_url=self._url, | |
| api_key=self._api_key, | |
| ) | |
| 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 | |
| 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, | |
| ModelType.O3_MINI, | |
| ModelType.O3 | |
| ]: | |
| # 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= 'deepseek-chat' if self._url == 'https://api.deepseek.com' else self.model_type, | |
| # **self.model_config_dict, | |
| # ) | |
| return self._to_chat_completion(response) | |
| # response = self._client.chat.completions.create( | |
| # messages=messages, | |
| # model= 'deepseek-chat' if self._url == 'https://api.deepseek.com' else self.model_type, | |
| # **self.model_config_dict, | |
| # ) | |
| response = self._client.chat.completions.create( | |
| messages=messages, | |
| model=self.model_type, | |
| **self.model_config_dict, | |
| ) | |
| return response | |
| 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." | |
| ) | |
| 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) | |