# File: backend/app/api/v1/endpoints/chat.py (更新)
# Description: 聊天功能的 API 路由 (使用 ChatService)

from fastapi import APIRouter, HTTPException, Depends
from app.models.pydantic_models import ChatRequest, ChatResponse
# 导入 ChatService 实例
from app.services.chat_service import chat_service_instance, ChatService

router = APIRouter()

# --- (可选) 使用 FastAPI 的依赖注入来获取 ChatService 实例 ---
# 这样更符合 FastAPI 的风格，方便测试和替换实现
# async def get_chat_service() -> ChatService:
#     return chat_service_instance

@router.post("/", response_model=ChatResponse)
async def handle_chat_message(
    request: ChatRequest,
    # chat_service: ChatService = Depends(get_chat_service) # 使用依赖注入
):
  """
  处理用户发送的聊天消息，并使用 LangChain 获取 AI 回复
  """
  user_message = request.message
  # session_id = request.session_id # 如果 ChatRequest 中包含 session_id
  print(f"接收到用户消息: {user_message}")

  try:
    # --- 调用 ChatService 获取 AI 回复 ---
    # 使用全局实例 (简单方式)
    ai_reply = await chat_service_instance.get_ai_reply(user_message)
    # 或者使用依赖注入获取的实例
    # ai_reply = await chat_service.get_ai_reply(user_message, session_id)

    print(f"发送 AI 回复: {ai_reply}")
    return ChatResponse(reply=ai_reply)

  except Exception as e:
    # 如果 ChatService 抛出异常，捕获并返回 HTTP 500 错误
    print(f"处理聊天消息时发生错误: {e}")
    raise HTTPException(status_code=500, detail=str(e))