deep-swarm/camel/models/openai_model.py

# ========= 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 retry import retry
from loguru import logger
import requests
import openai

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=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

    @retry((requests.exceptions.RequestException, openai.APIError), delay=5, logger=logger)
    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,
        ]:
            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]

            # ! O1 mini and O1 preview do not support tools and system message
            if self.model_type in [ModelType.O1_MINI, ModelType.O1_PREVIEW]:
                # convert system message into user message
                if messages[0]['role'] == "system":
                    system_content = messages[0]['content']
                    # delete the first message, and concat
                    messages = messages[1:]
                    messages[0]['content'] = f"{system_content}\n\n{messages[0]['content']}"
                
                if 'tools' in self.model_config_dict:
                    del self.model_config_dict['tools']

        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)

        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."
                )

    @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)