修复了bug

src/mais4u/openai_client.py

@@ -1,286 +0,0 @@
-from typing import AsyncGenerator, Dict, List, Optional, Union
-from dataclasses import dataclass
-from openai import AsyncOpenAI
-from openai.types.chat import ChatCompletion, ChatCompletionChunk
-
-
-@dataclass
-class ChatMessage:
-    """聊天消息数据类"""
-
-    role: str
-    content: str
-
-    def to_dict(self) -> Dict[str, str]:
-        return {"role": self.role, "content": self.content}
-
-
-class AsyncOpenAIClient:
-    """异步OpenAI客户端，支持流式传输"""
-
-    def __init__(self, api_key: str, base_url: Optional[str] = None):
-        """
-        初始化客户端
-
-        Args:
-            api_key: OpenAI API密钥
-            base_url: 可选的API基础URL，用于自定义端点
-        """
-        self.client = AsyncOpenAI(
-            api_key=api_key,
-            base_url=base_url,
-            timeout=10.0,  # 设置60秒的全局超时
-        )
-
-    async def chat_completion(
-        self,
-        messages: List[Union[ChatMessage, Dict[str, str]]],
-        model: str = "gpt-3.5-turbo",
-        temperature: float = 0.7,
-        max_tokens: Optional[int] = None,
-        **kwargs,
-    ) -> ChatCompletion:
-        """
-        非流式聊天完成
-
-        Args:
-            messages: 消息列表
-            model: 模型名称
-            temperature: 温度参数
-            max_tokens: 最大token数
-            **kwargs: 其他参数
-
-        Returns:
-            完整的聊天回复
-        """
-        # 转换消息格式
-        formatted_messages = []
-        for msg in messages:
-            if isinstance(msg, ChatMessage):
-                formatted_messages.append(msg.to_dict())
-            else:
-                formatted_messages.append(msg)
-
-        extra_body = {}
-        if kwargs.get("enable_thinking") is not None:
-            extra_body["enable_thinking"] = kwargs.pop("enable_thinking")
-        if kwargs.get("thinking_budget") is not None:
-            extra_body["thinking_budget"] = kwargs.pop("thinking_budget")
-
-        response = await self.client.chat.completions.create(
-            model=model,
-            messages=formatted_messages,
-            temperature=temperature,
-            max_tokens=max_tokens,
-            stream=False,
-            extra_body=extra_body if extra_body else None,
-            **kwargs,
-        )
-
-        return response
-
-    async def chat_completion_stream(
-        self,
-        messages: List[Union[ChatMessage, Dict[str, str]]],
-        model: str = "gpt-3.5-turbo",
-        temperature: float = 0.7,
-        max_tokens: Optional[int] = None,
-        **kwargs,
-    ) -> AsyncGenerator[ChatCompletionChunk, None]:
-        """
-        流式聊天完成
-
-        Args:
-            messages: 消息列表
-            model: 模型名称
-            temperature: 温度参数
-            max_tokens: 最大token数
-            **kwargs: 其他参数
-
-        Yields:
-            ChatCompletionChunk: 流式响应块
-        """
-        # 转换消息格式
-        formatted_messages = []
-        for msg in messages:
-            if isinstance(msg, ChatMessage):
-                formatted_messages.append(msg.to_dict())
-            else:
-                formatted_messages.append(msg)
-
-        extra_body = {}
-        if kwargs.get("enable_thinking") is not None:
-            extra_body["enable_thinking"] = kwargs.pop("enable_thinking")
-        if kwargs.get("thinking_budget") is not None:
-            extra_body["thinking_budget"] = kwargs.pop("thinking_budget")
-
-        stream = await self.client.chat.completions.create(
-            model=model,
-            messages=formatted_messages,
-            temperature=temperature,
-            max_tokens=max_tokens,
-            stream=True,
-            extra_body=extra_body if extra_body else None,
-            **kwargs,
-        )
-
-        async for chunk in stream:
-            yield chunk
-
-    async def get_stream_content(
-        self,
-        messages: List[Union[ChatMessage, Dict[str, str]]],
-        model: str = "gpt-3.5-turbo",
-        temperature: float = 0.7,
-        max_tokens: Optional[int] = None,
-        **kwargs,
-    ) -> AsyncGenerator[str, None]:
-        """
-        获取流式内容（只返回文本内容）
-
-        Args:
-            messages: 消息列表
-            model: 模型名称
-            temperature: 温度参数
-            max_tokens: 最大token数
-            **kwargs: 其他参数
-
-        Yields:
-            str: 文本内容片段
-        """
-        async for chunk in self.chat_completion_stream(
-            messages=messages, model=model, temperature=temperature, max_tokens=max_tokens, **kwargs
-        ):
-            if chunk.choices and chunk.choices[0].delta.content:
-                yield chunk.choices[0].delta.content
-
-    async def collect_stream_response(
-        self,
-        messages: List[Union[ChatMessage, Dict[str, str]]],
-        model: str = "gpt-3.5-turbo",
-        temperature: float = 0.7,
-        max_tokens: Optional[int] = None,
-        **kwargs,
-    ) -> str:
-        """
-        收集完整的流式响应
-
-        Args:
-            messages: 消息列表
-            model: 模型名称
-            temperature: 温度参数
-            max_tokens: 最大token数
-            **kwargs: 其他参数
-
-        Returns:
-            str: 完整的响应文本
-        """
-        full_response = ""
-        async for content in self.get_stream_content(
-            messages=messages, model=model, temperature=temperature, max_tokens=max_tokens, **kwargs
-        ):
-            full_response += content
-
-        return full_response
-
-    async def close(self):
-        """关闭客户端"""
-        await self.client.close()
-
-    async def __aenter__(self):
-        """异步上下文管理器入口"""
-        return self
-
-    async def __aexit__(self, exc_type, exc_val, exc_tb):
-        """异步上下文管理器退出"""
-        await self.close()
-
-
-class ConversationManager:
-    """对话管理器，用于管理对话历史"""
-
-    def __init__(self, client: AsyncOpenAIClient, system_prompt: Optional[str] = None):
-        """
-        初始化对话管理器
-
-        Args:
-            client: OpenAI客户端实例
-            system_prompt: 系统提示词
-        """
-        self.client = client
-        self.messages: List[ChatMessage] = []
-
-        if system_prompt:
-            self.messages.append(ChatMessage(role="system", content=system_prompt))
-
-    def add_user_message(self, content: str):
-        """添加用户消息"""
-        self.messages.append(ChatMessage(role="user", content=content))
-
-    def add_assistant_message(self, content: str):
-        """添加助手消息"""
-        self.messages.append(ChatMessage(role="assistant", content=content))
-
-    async def send_message_stream(
-        self, content: str, model: str = "gpt-3.5-turbo", **kwargs
-    ) -> AsyncGenerator[str, None]:
-        """
-        发送消息并获取流式响应
-
-        Args:
-            content: 用户消息内容
-            model: 模型名称
-            **kwargs: 其他参数
-
-        Yields:
-            str: 响应内容片段
-        """
-        self.add_user_message(content)
-
-        response_content = ""
-        async for chunk in self.client.get_stream_content(messages=self.messages, model=model, **kwargs):
-            response_content += chunk
-            yield chunk
-
-        self.add_assistant_message(response_content)
-
-    async def send_message(self, content: str, model: str = "gpt-3.5-turbo", **kwargs) -> str:
-        """
-        发送消息并获取完整响应
-
-        Args:
-            content: 用户消息内容
-            model: 模型名称
-            **kwargs: 其他参数
-
-        Returns:
-            str: 完整响应
-        """
-        self.add_user_message(content)
-
-        response = await self.client.chat_completion(messages=self.messages, model=model, **kwargs)
-
-        response_content = response.choices[0].message.content
-        self.add_assistant_message(response_content)
-
-        return response_content
-
-    def clear_history(self, keep_system: bool = True):
-        """
-        清除对话历史
-
-        Args:
-            keep_system: 是否保留系统消息
-        """
-        if keep_system and self.messages and self.messages[0].role == "system":
-            self.messages = [self.messages[0]]
-        else:
-            self.messages = []
-
-    def get_message_count(self) -> int:
-        """获取消息数量"""
-        return len(self.messages)
-
-    def get_conversation_history(self) -> List[Dict[str, str]]:
-        """获取对话历史"""
-        return [msg.to_dict() for msg in self.messages]

src/mais4u/s4u_config.py

@@ -6,7 +6,6 @@ from tomlkit import TOMLDocument
 from tomlkit.items import Table
 from dataclasses import dataclass, fields, MISSING, field
 from typing import TypeVar, Type, Any, get_origin, get_args, Literal
-from src.mais4u.constant_s4u import ENABLE_S4U
 from src.common.logger import get_logger
 
 logger = get_logger("s4u_config")