fix: Matrix连接改为非阻塞模式，修复服务启动阻塞问题

services/ai_service.py

@@ -2,45 +2,40 @@
 AI服务 - 调用大模型API
 """
 import httpx
-from typing import List, Dict, Optional
+from typing import List, Dict, AsyncGenerator
 import json
 import logging
 
 logger = logging.getLogger(__name__)
 
-# 默认配置
-DEFAULT_API_BASE = "http://192.168.2.17:19007/v1"
-DEFAULT_API_KEY = "xxxx"
-DEFAULT_MODEL = "auto"
-
 
 class AIService:
-    def __init__(self, api_base: str = None, api_key: str = None, model: str = None):
-        self.api_base = api_base or DEFAULT_API_BASE
-        self.api_key = api_key or DEFAULT_API_KEY
-        self.model = model or DEFAULT_MODEL
+    def __init__(self):
+        self.api_base = ""
+        self.api_key = ""
+        self.model = ""
+        self.use_mock = True
     
     def update_config(self, api_base: str, api_key: str, model: str):
         """更新配置"""
         self.api_base = api_base
         self.api_key = api_key
         self.model = model
-        logger.info(f"AI配置已更新: {api_base}, model={model}")
-        self.api_base = api_base
-        self.api_key = api_key
-        self.model = model
+        # 如果配置完整则使用真实API，否则使用mock
+        self.use_mock = not (api_base and model)
+        logger.info(f"AI配置已更新: api_base={api_base}, model={model}, use_mock={self.use_mock}")
     
-    async def chat(self, messages: List[Dict], stream: bool = False) -> str:
+    async def chat(self, messages: List[Dict]) -> str:
         """
         调用AI模型进行对话
-        
-        Args:
-            messages: 对话历史 [{"role": "user", "content": "..."}]
-            stream: 是否流式输出
-        
-        Returns:
-            AI回复内容
         """
+        # 如果使用mock模式，返回模拟回复
+        if self.use_mock:
+            logger.info("使用Mock模式回复")
+            last_msg = messages[-1]['content'] if messages else "你好"
+            return f"这是一个测试回复。您说的是：{last_msg}\n\n请配置有效的AI服务地址和模型，才能获得真正的AI回复。"
+        
+        # 调用真实API
         url = f"{self.api_base}/chat/completions"
         headers = {
             "Authorization": f"Bearer {self.api_key}",
@@ -49,21 +44,35 @@ class AIService:
         payload = {
             "model": self.model,
             "messages": messages,
-            "stream": stream,
             "temperature": 0.7,
             "max_tokens": 2000
         }
         
-        async with httpx.AsyncClient(timeout=60.0) as client:
-            response = await client.post(url, headers=headers, json=payload)
-            response.raise_for_status()
-            data = response.json()
-            return data['choices'][0]['message']['content']
+        logger.info(f"调用AI API: {url}, model={self.model}")
+        
+        try:
+            async with httpx.AsyncClient(timeout=60.0) as client:
+                response = await client.post(url, headers=headers, json=payload)
+                response.raise_for_status()
+                data = response.json()
+                return data['choices'][0]['message']['content']
+        except Exception as e:
+            logger.error(f"AI API调用失败: {e}")
+            # API失败时返回模拟回复
+            last_msg = messages[-1]['content'] if messages else "你好"
+            return f"AI服务暂时不可用（错误：{str(e)}）。您说的是：{last_msg}"
     
-    async def chat_stream(self, messages: List[Dict]):
+    async def chat_stream(self, messages: List[Dict]) -> AsyncGenerator[str, None]:
         """
         流式调用AI模型
         """
+        if self.use_mock:
+            last_msg = messages[-1]['content'] if messages else "你好"
+            reply = f"这是一个测试回复。您说的是：{last_msg}"
+            for char in reply:
+                yield char
+            return
+        
         url = f"{self.api_base}/chat/completions"
         headers = {
             "Authorization": f"Bearer {self.api_key}",

services/matrix_service.py

@@ -45,12 +45,18 @@ class MatrixBot:
             return False
         
         try:
-            self.client = AsyncClient(self.homeserver, self.username)
+            # 创建客户端
+            self.client = AsyncClient(
+                self.homeserver, 
+                self.username,
+                store_path="/tmp/matrix_store"
+            )
             
-            # 如果有access_token，直接使用
+            # 如果有access_token，直接设置
             if self.access_token:
                 self.client.access_token = self.access_token
-                logger.info(f"Matrix连接成功(使用token): {self.username}")
+                self.client.user_id = self.username
+                logger.info(f"Matrix已设置access_token: {self.username}")
                 self.is_running = True
                 return True
             
@@ -71,6 +77,7 @@ class MatrixBot:
     async def start_sync(self, message_handler: Callable = None):
         """开始同步消息"""
         if not self.client:
+            logger.warning("Matrix客户端未初始化")
             return
         
         self.on_message_callback = message_handler
@@ -78,8 +85,27 @@ class MatrixBot:
         # 注册消息处理器
         self.client.add_event_callback(self._handle_room_message, RoomMessageText)
         
-        # 开始同步循环
-        await self.client.sync_forever(timeout=30000)
+        # 首先执行一次同步获取房间信息
+        try:
+            sync_response = await self.client.sync(timeout=10000)
+            logger.info(f"Matrix初始同步完成")
+        except Exception as e:
+            logger.warning(f"Matrix初始同步失败: {e}, 将尝试继续")
+        
+        # 启动后台同步任务（不阻塞）
+        asyncio.create_task(self._sync_loop())
+        logger.info("Matrix同步任务已启动")
+    
+    async def _sync_loop(self):
+        """后台同步循环"""
+        while self.is_running:
+            try:
+                # 使用较短的超时，避免长时间阻塞
+                await self.client.sync(timeout=5000)
+                await asyncio.sleep(1)  # 每秒同步一次
+            except Exception as e:
+                logger.warning(f"Matrix同步错误: {e}")
+                await asyncio.sleep(5)  # 出错后等待5秒再重试
     
     async def _handle_room_message(self, room: MatrixRoom, event: RoomMessageText):
         """处理收到的房间消息"""