330 lines
11 KiB
Python
330 lines
11 KiB
Python
# -*- coding: utf-8 -*-
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"""
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小程序 CHAT 路由 —— CHAT-1/2/3/4 端点。
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替代原 xcx_ai_chat.py（/api/ai/*），统一迁移到 /api/xcx/chat/* 路径。
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端点清单：
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- GET /api/xcx/chat/history — CHAT-1 对话历史列表
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- GET /api/xcx/chat/{chat_id}/messages — CHAT-2a 通过 chatId 查询消息
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- GET /api/xcx/chat/messages?contextType=&contextId= — CHAT-2b 通过上下文查询消息
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- POST /api/xcx/chat/{chat_id}/messages — CHAT-3 发送消息（同步回复）
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- POST /api/xcx/chat/stream — CHAT-4 SSE 流式端点
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所有端点使用 require_approved() 权限检查。
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"""
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from __future__ import annotations
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import json
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import logging
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import os
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from fastapi import APIRouter, Depends, HTTPException, Query, status
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from fastapi.responses import StreamingResponse
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from app.ai.bailian_client import BailianClient
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from app.auth.dependencies import CurrentUser
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from app.database import get_connection
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from app.middleware.permission import require_approved
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from app.schemas.xcx_chat import (
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ChatHistoryItem,
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ChatHistoryResponse,
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ChatMessageItem,
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ChatMessagesResponse,
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ChatStreamRequest,
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MessageBrief,
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ReferenceCard,
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SendMessageRequest,
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SendMessageResponse,
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)
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from app.services.chat_service import ChatService
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/xcx/chat", tags=["小程序 CHAT"])
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# ── CHAT-1: 对话历史列表 ─────────────────────────────────────
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@router.get("/history", response_model=ChatHistoryResponse)
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async def list_chat_history(
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page: int = Query(1, ge=1),
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page_size: int = Query(20, ge=1, le=100),
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user: CurrentUser = Depends(require_approved()),
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) -> ChatHistoryResponse:
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"""CHAT-1: 查询当前用户的对话历史列表，按最后消息时间倒序。"""
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svc = ChatService()
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items, total = svc.get_chat_history(
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user_id=user.user_id,
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site_id=user.site_id,
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page=page,
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page_size=page_size,
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)
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return ChatHistoryResponse(
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items=[ChatHistoryItem(**item) for item in items],
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total=total,
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page=page,
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page_size=page_size,
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)
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# ── CHAT-2b: 通过上下文查询消息 ─────────────────────────────
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# ⚠️ 必须在 /{chat_id}/messages 之前注册，否则 "messages" 会被当作 chat_id 路径参数
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@router.get("/messages", response_model=ChatMessagesResponse)
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async def get_chat_messages_by_context(
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context_type: str = Query(..., alias="contextType"),
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context_id: str = Query(..., alias="contextId"),
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page: int = Query(1, ge=1),
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page_size: int = Query(50, ge=1, le=100),
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user: CurrentUser = Depends(require_approved()),
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) -> ChatMessagesResponse:
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"""CHAT-2b: 通过上下文类型和 ID 查询消息（自动查找/创建对话）。"""
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svc = ChatService()
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# 按复用规则查找或创建对话
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chat_id = svc.get_or_create_session(
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user_id=user.user_id,
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site_id=user.site_id,
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context_type=context_type,
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context_id=context_id if context_id else None,
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)
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messages, total, resolved_chat_id = svc.get_messages(
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chat_id=chat_id,
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user_id=user.user_id,
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site_id=user.site_id,
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page=page,
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page_size=page_size,
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)
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return ChatMessagesResponse(
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chat_id=resolved_chat_id,
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items=[_to_message_item(m) for m in messages],
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total=total,
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page=page,
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page_size=page_size,
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)
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# ── CHAT-2a: 通过 chatId 查询消息 ───────────────────────────
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@router.get("/{chat_id}/messages", response_model=ChatMessagesResponse)
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async def get_chat_messages(
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chat_id: int,
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page: int = Query(1, ge=1),
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page_size: int = Query(50, ge=1, le=100),
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user: CurrentUser = Depends(require_approved()),
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) -> ChatMessagesResponse:
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"""CHAT-2a: 通过 chatId 查询对话消息列表，按 createdAt 正序。"""
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svc = ChatService()
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messages, total, resolved_chat_id = svc.get_messages(
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chat_id=chat_id,
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user_id=user.user_id,
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site_id=user.site_id,
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page=page,
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page_size=page_size,
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)
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return ChatMessagesResponse(
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chat_id=resolved_chat_id,
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items=[_to_message_item(m) for m in messages],
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total=total,
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page=page,
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page_size=page_size,
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)
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# ── CHAT-4: SSE 流式端点 ────────────────────────────────────
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# ⚠️ 必须在 /{chat_id}/messages 之前注册，否则 "stream" 会被当作 chat_id 路径参数
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@router.post("/stream")
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async def chat_stream(
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body: ChatStreamRequest,
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user: CurrentUser = Depends(require_approved()),
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) -> StreamingResponse:
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"""CHAT-4: SSE 流式对话端点。
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接收用户消息，通过百炼 API 流式返回 AI 回复。
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SSE 事件类型：message（逐 token）/ done（完成）/ error（错误）。
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chatId 归属验证：不属于当前用户返回 HTTP 403（普通 JSON 错误，非 SSE）。
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"""
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if not body.content or not body.content.strip():
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raise HTTPException(
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status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
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detail="消息内容不能为空",
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)
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svc = ChatService()
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content = body.content.strip()
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# 归属验证（在 SSE 流开始前完成，失败时返回普通 HTTP 错误）
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svc._verify_ownership(body.chat_id, user.user_id, user.site_id)
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# 存入用户消息（P5 PRD 合规：发送时即写入）
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user_msg_id, user_created_at = svc._save_message(body.chat_id, "user", content)
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async def event_generator():
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"""SSE 事件生成器。
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事件格式：
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- event: message\\ndata: {"token": "..."}\\n\\n
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- event: done\\ndata: {"messageId": ..., "createdAt": "..."}\\n\\n
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- event: error\\ndata: {"message": "..."}\\n\\n
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"""
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full_reply_parts: list[str] = []
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try:
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bailian = _get_bailian_client()
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# 获取历史消息作为上下文
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messages = _build_ai_messages(body.chat_id)
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# 流式调用百炼 API
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async for chunk in bailian.chat_stream(messages):
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full_reply_parts.append(chunk)
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yield f"event: message\ndata: {json.dumps({'token': chunk}, ensure_ascii=False)}\n\n"
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# 流结束：拼接完整回复并持久化
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full_reply = "".join(full_reply_parts)
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estimated_tokens = len(full_reply)
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ai_msg_id, ai_created_at = svc._save_message(
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body.chat_id, "assistant", full_reply, tokens_used=estimated_tokens,
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)
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svc._update_session_metadata(body.chat_id, full_reply)
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# 发送 done 事件
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done_data = json.dumps(
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{"messageId": ai_msg_id, "createdAt": ai_created_at},
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ensure_ascii=False,
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)
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yield f"event: done\ndata: {done_data}\n\n"
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except Exception as e:
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logger.error("SSE 流式对话异常: %s", e, exc_info=True)
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# 如果已有部分回复，仍然持久化
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if full_reply_parts:
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partial = "".join(full_reply_parts)
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try:
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svc._save_message(body.chat_id, "assistant", partial)
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svc._update_session_metadata(body.chat_id, partial)
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except Exception:
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logger.error("持久化部分回复失败", exc_info=True)
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error_data = json.dumps(
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{"message": "AI 服务暂时不可用"},
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ensure_ascii=False,
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)
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yield f"event: error\ndata: {error_data}\n\n"
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return StreamingResponse(
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event_generator(),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no",
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},
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)
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# ── CHAT-3: 发送消息（同步回复） ─────────────────────────────
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@router.post("/{chat_id}/messages", response_model=SendMessageResponse)
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async def send_message(
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chat_id: int,
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body: SendMessageRequest,
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user: CurrentUser = Depends(require_approved()),
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) -> SendMessageResponse:
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"""CHAT-3: 发送用户消息并获取同步 AI 回复。
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chatId 归属验证：不属于当前用户返回 HTTP 403。
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AI 失败时返回错误提示消息（HTTP 200）。
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"""
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if not body.content or not body.content.strip():
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raise HTTPException(
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status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
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detail="消息内容不能为空",
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)
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svc = ChatService()
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result = await svc.send_message_sync(
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chat_id=chat_id,
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content=body.content.strip(),
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user_id=user.user_id,
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site_id=user.site_id,
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)
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return SendMessageResponse(
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user_message=MessageBrief(**result["user_message"]),
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ai_reply=MessageBrief(**result["ai_reply"]),
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)
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# ── 辅助函数 ─────────────────────────────────────────────────
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def _to_message_item(msg: dict) -> ChatMessageItem:
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"""将 chat_service 返回的消息 dict 转换为 ChatMessageItem。"""
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ref_card = msg.get("reference_card")
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reference_card = ReferenceCard(**ref_card) if ref_card and isinstance(ref_card, dict) else None
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return ChatMessageItem(
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id=msg["id"],
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role=msg["role"],
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content=msg["content"],
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created_at=msg["created_at"],
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reference_card=reference_card,
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)
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def _get_bailian_client() -> BailianClient:
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"""从环境变量构建 BailianClient，缺失时报错。"""
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api_key = os.environ.get("BAILIAN_API_KEY")
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base_url = os.environ.get("BAILIAN_BASE_URL")
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model = os.environ.get("BAILIAN_MODEL")
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if not api_key or not base_url or not model:
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raise RuntimeError(
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"百炼 API 环境变量缺失，需要 BAILIAN_API_KEY、BAILIAN_BASE_URL、BAILIAN_MODEL"
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)
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return BailianClient(api_key=api_key, base_url=base_url, model=model)
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def _build_ai_messages(chat_id: int) -> list[dict]:
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"""构建发送给 AI 的消息列表（含历史上下文）。"""
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conn = get_connection()
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try:
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with conn.cursor() as cur:
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cur.execute(
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"""
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SELECT role, content FROM biz.ai_messages
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WHERE conversation_id = %s
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ORDER BY created_at ASC
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""",
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(chat_id,),
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)
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history = cur.fetchall()
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finally:
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conn.close()
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messages: list[dict] = []
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# 取最近 20 条
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recent = history[-20:] if len(history) > 20 else history
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for role, msg_content in recent:
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messages.append({"role": role, "content": msg_content})
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# 如果没有 system 消息，添加默认 system prompt
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if not messages or messages[0]["role"] != "system":
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system_prompt = {
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"role": "system",
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"content": json.dumps(
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{"task": "你是台球门店的 AI 助手，根据用户的问题和当前页面上下文提供帮助。"},
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ensure_ascii=False,
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),
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}
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messages.insert(0, system_prompt)
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return messages
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