AIChatRoom/backend/adapters/base_adapter.py

"""
AI适配器基类
定义统一的AI调用接口
"""
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional, AsyncGenerator
from datetime import datetime


@dataclass
class ChatMessage:
    """聊天消息"""
    role: str                   # system, user, assistant
    content: str                # 消息内容
    name: Optional[str] = None  # 发送者名称（可选）
    
    def to_dict(self) -> Dict[str, Any]:
        """转换为字典"""
        d = {"role": self.role, "content": self.content}
        if self.name:
            d["name"] = self.name
        return d


@dataclass
class AdapterResponse:
    """适配器响应"""
    success: bool                           # 是否成功
    content: str = ""                       # 响应内容
    error: Optional[str] = None             # 错误信息
    
    # 统计信息
    prompt_tokens: int = 0                  # 输入token数
    completion_tokens: int = 0              # 输出token数
    total_tokens: int = 0                   # 总token数
    
    # 元数据
    model: str = ""                         # 使用的模型
    finish_reason: str = ""                 # 结束原因
    latency_ms: float = 0.0                 # 延迟(毫秒)
    
    # 工具调用结果
    tool_calls: List[Dict[str, Any]] = field(default_factory=list)
    
    def __post_init__(self):
        if self.total_tokens == 0:
            self.total_tokens = self.prompt_tokens + self.completion_tokens


class BaseAdapter(ABC):
    """
    AI适配器基类
    所有AI提供商适配器必须继承此类
    """
    
    def __init__(
        self,
        api_key: str,
        base_url: str,
        model: str,
        use_proxy: bool = False,
        proxy_config: Optional[Dict[str, Any]] = None,
        timeout: int = 60,
        **kwargs
    ):
        """
        初始化适配器
        
        Args:
            api_key: API密钥
            base_url: API基础URL
            model: 模型名称
            use_proxy: 是否使用代理
            proxy_config: 代理配置
            timeout: 超时时间(秒)
            **kwargs: 额外参数
        """
        self.api_key = api_key
        self.base_url = base_url
        self.model = model
        self.use_proxy = use_proxy
        self.proxy_config = proxy_config or {}
        self.timeout = timeout
        self.extra_params = kwargs
    
    @abstractmethod
    async def chat(
        self,
        messages: List[ChatMessage],
        temperature: float = 0.7,
        max_tokens: int = 2000,
        **kwargs
    ) -> AdapterResponse:
        """
        发送聊天请求
        
        Args:
            messages: 消息列表
            temperature: 温度参数
            max_tokens: 最大token数
            **kwargs: 额外参数
            
        Returns:
            适配器响应
        """
        pass
    
    @abstractmethod
    async def chat_stream(
        self,
        messages: List[ChatMessage],
        temperature: float = 0.7,
        max_tokens: int = 2000,
        **kwargs
    ) -> AsyncGenerator[str, None]:
        """
        发送流式聊天请求
        
        Args:
            messages: 消息列表
            temperature: 温度参数
            max_tokens: 最大token数
            **kwargs: 额外参数
            
        Yields:
            响应内容片段
        """
        pass
    
    @abstractmethod
    async def test_connection(self) -> Dict[str, Any]:
        """
        测试API连接
        
        Returns:
            测试结果字典，包含 success, message, latency_ms
        """
        pass
    
    def _build_messages(
        self,
        messages: List[ChatMessage]
    ) -> List[Dict[str, Any]]:
        """
        构建消息列表
        
        Args:
            messages: ChatMessage列表
            
        Returns:
            字典格式的消息列表
        """
        return [msg.to_dict() for msg in messages]
    
    def _calculate_latency(self, start_time: datetime) -> float:
        """
        计算延迟
        
        Args:
            start_time: 开始时间
            
        Returns:
            延迟毫秒数
        """
        return (datetime.utcnow() - start_time).total_seconds() * 1000