Merge branch 'feature/kfc' of https://github.com/MoFox-Studio/MoFox-Core into feature/kfc

src/chat/message_manager/distribution_manager.py

@@ -52,6 +52,11 @@ class StreamLoopManager:
 
         # 流循环启动锁：防止并发启动同一个流的多个循环任务
         self._stream_start_locks: dict[str, asyncio.Lock] = {}
+        
+        # 死锁检测：记录每个流的最后活动时间
+        self._stream_last_activity: dict[str, float] = {}
+        self._deadlock_detector_task: asyncio.Task | None = None
+        self._deadlock_threshold_seconds: float = 120.0  # 2分钟无活动视为可能死锁
 
         logger.info(f"流循环管理器初始化完成 (最大并发流数: {self.max_concurrent_streams})")
 
@@ -62,6 +67,60 @@ class StreamLoopManager:
             return
 
         self.is_running = True
+        
+        # 启动死锁检测器
+        self._deadlock_detector_task = asyncio.create_task(
+            self._deadlock_detector_loop(),
+            name="deadlock_detector"
+        )
+        logger.info("死锁检测器已启动")
+    
+    async def _deadlock_detector_loop(self) -> None:
+        """死锁检测循环 - 定期检查所有流的活动状态"""
+        while self.is_running:
+            try:
+                await asyncio.sleep(30.0)  # 每30秒检查一次
+                
+                current_time = time.time()
+                suspected_deadlocks = []
+                
+                # 检查所有活跃流的最后活动时间
+                for stream_id, last_activity in list(self._stream_last_activity.items()):
+                    inactive_seconds = current_time - last_activity
+                    if inactive_seconds > self._deadlock_threshold_seconds:
+                        suspected_deadlocks.append((stream_id, inactive_seconds))
+                
+                if suspected_deadlocks:
+                    logger.warning(
+                        f"🔴 [死锁检测] 发现 {len(suspected_deadlocks)} 个可能卡住的流:\n" +
+                        "\n".join([
+                            f"  - stream={sid[:8]}, 无活动时间={inactive:.1f}s"
+                            for sid, inactive in suspected_deadlocks
+                        ])
+                    )
+                    
+                    # 打印当前所有 asyncio 任务的状态
+                    all_tasks = asyncio.all_tasks()
+                    stream_loop_tasks = [t for t in all_tasks if t.get_name().startswith("stream_loop_")]
+                    logger.warning(
+                        f"🔴 [死锁检测] 当前流循环任务状态:\n" +
+                        "\n".join([
+                            f"  - {t.get_name()}: done={t.done()}, cancelled={t.cancelled()}"
+                            for t in stream_loop_tasks
+                        ])
+                    )
+                else:
+                    # 每5分钟报告一次正常状态
+                    if int(current_time) % 300 < 30:
+                        active_count = len(self._stream_last_activity)
+                        if active_count > 0:
+                            logger.info(f"🟢 [死锁检测] 所有 {active_count} 个流正常运行中")
+                            
+            except asyncio.CancelledError:
+                logger.info("死锁检测器被取消")
+                break
+            except Exception as e:
+                logger.error(f"死锁检测器出错: {e}")
 
     async def stop(self) -> None:
         """停止流循环管理器"""
@@ -69,6 +128,15 @@ class StreamLoopManager:
             return
 
         self.is_running = False
+        
+        # 停止死锁检测器
+        if self._deadlock_detector_task and not self._deadlock_detector_task.done():
+            self._deadlock_detector_task.cancel()
+            try:
+                await self._deadlock_detector_task
+            except asyncio.CancelledError:
+                pass
+            logger.info("死锁检测器已停止")
 
         # 取消所有流循环
         try:
@@ -214,11 +282,24 @@ class StreamLoopManager:
         """
         task_id = id(asyncio.current_task())
         logger.info(f"🔄 [流工作器] stream={stream_id[:8]}, 任务ID={task_id}, 启动")
+        
+        # 死锁检测：记录循环次数和上次活动时间
+        loop_count = 0
+        
+        # 注册到活动跟踪
+        self._stream_last_activity[stream_id] = time.time()
 
         try:
             while self.is_running:
+                loop_count += 1
+                loop_start_time = time.time()
+                
+                # 更新活动时间（死锁检测用）
+                self._stream_last_activity[stream_id] = loop_start_time
+                
                 try:
                     # 1. 获取流上下文
+                    logger.debug(f"🔍 [流工作器] stream={stream_id[:8]}, 循环#{loop_count}, 获取上下文...")
                     context = await self._get_stream_context(stream_id)
                     if not context:
                         logger.warning(f"⚠️ [流工作器] stream={stream_id[:8]}, 无法获取流上下文")
@@ -226,6 +307,7 @@ class StreamLoopManager:
                         continue
 
                     # 2. 检查是否有消息需要处理
+                    logger.debug(f"🔍 [流工作器] stream={stream_id[:8]}, 循环#{loop_count}, 刷新缓存消息...")
                     await self._flush_cached_messages_to_unread(stream_id)
                     unread_count = self._get_unread_count(context)
                     force_dispatch = self._needs_force_dispatch_for_context(context, unread_count)
@@ -245,11 +327,36 @@ class StreamLoopManager:
                             logger.debug(f"更新流能量失败 {stream_id}: {e}")
 
                         # 4. 激活chatter处理
+                        logger.debug(f"🔍 [流工作器] stream={stream_id[:8]}, 循环#{loop_count}, 开始chatter处理...")
                         try:
-                            success = await asyncio.wait_for(self._process_stream_messages(stream_id, context), global_config.chat.thinking_timeout)
+                            # 在长时间处理期间定期更新活动时间，避免死锁检测误报
+                            async def process_with_activity_update():
+                                process_task = asyncio.create_task(
+                                    self._process_stream_messages(stream_id, context)
+                                )
+                                activity_update_interval = 30.0  # 每30秒更新一次
+                                while not process_task.done():
+                                    try:
+                                        # 等待任务完成或超时
+                                        await asyncio.wait_for(
+                                            asyncio.shield(process_task),
+                                            timeout=activity_update_interval
+                                        )
+                                    except asyncio.TimeoutError:
+                                        # 任务仍在运行，更新活动时间
+                                        self._stream_last_activity[stream_id] = time.time()
+                                        logger.debug(f"🔄 [流工作器] stream={stream_id[:8]}, 处理中，更新活动时间")
+                                return await process_task
+                            
+                            success = await asyncio.wait_for(
+                                process_with_activity_update(),
+                                global_config.chat.thinking_timeout
+                            )
                         except asyncio.TimeoutError:
                             logger.warning(f"⏱️ [流工作器] stream={stream_id[:8]}, 任务ID={task_id}, 处理超时")
                             success = False
+                        logger.debug(f"🔍 [流工作器] stream={stream_id[:8]}, 循环#{loop_count}, chatter处理完成, success={success}")
+                        
                         # 更新统计
                         self.stats["total_process_cycles"] += 1
                         if success:
@@ -263,6 +370,7 @@ class StreamLoopManager:
                             logger.warning(f"❌ [流工作器] stream={stream_id[:8]}, 任务ID={task_id}, 处理失败")
 
                     # 5. 计算下次检查间隔
+                    logger.debug(f"🔍 [流工作器] stream={stream_id[:8]}, 循环#{loop_count}, 计算间隔...")
                     interval = await self._calculate_interval(stream_id, has_messages)
 
                     # 6. sleep等待下次检查
@@ -271,7 +379,22 @@ class StreamLoopManager:
                     if last_interval is None or abs(interval - last_interval) > 0.01:
                         logger.info(f"流 {stream_id} 等待周期变化: {interval:.2f}s")
                         self._last_intervals[stream_id] = interval
-                    await asyncio.sleep(interval)
+                    
+                    loop_duration = time.time() - loop_start_time
+                    logger.debug(f"🔍 [流工作器] stream={stream_id[:8]}, 循环#{loop_count} 完成, 耗时={loop_duration:.2f}s, 即将sleep {interval:.2f}s")
+                    
+                    # 使用分段sleep，每隔一段时间更新活动时间，避免死锁检测误报
+                    # 当间隔较长时（如等待用户回复），分段更新活动时间
+                    remaining_sleep = interval
+                    activity_update_interval = 30.0  # 每30秒更新一次活动时间
+                    while remaining_sleep > 0:
+                        sleep_chunk = min(remaining_sleep, activity_update_interval)
+                        await asyncio.sleep(sleep_chunk)
+                        remaining_sleep -= sleep_chunk
+                        # 更新活动时间，表明流仍在正常运行（只是在等待）
+                        self._stream_last_activity[stream_id] = time.time()
+                    
+                    logger.debug(f"🔍 [流工作器] stream={stream_id[:8]}, 循环#{loop_count} sleep结束, 开始下一循环")
 
                 except asyncio.CancelledError:
                     logger.info(f"🛑 [流工作器] stream={stream_id[:8]}, 任务ID={task_id}, 被取消")
@@ -293,6 +416,9 @@ class StreamLoopManager:
 
             # 清理间隔记录
             self._last_intervals.pop(stream_id, None)
+            
+            # 清理活动跟踪
+            self._stream_last_activity.pop(stream_id, None)
 
             logger.info(f"🏁 [流工作器] stream={stream_id[:8]}, 任务ID={task_id}, 循环结束")
 

src/memory_graph/storage/vector_store.py

@@ -1,9 +1,13 @@
 """
 向量存储层：基于 ChromaDB 的语义向量存储
+
+注意：ChromaDB 是同步库，所有操作都必须使用 asyncio.to_thread() 包装
+以避免阻塞 asyncio 事件循环导致死锁。
 """
 
 from __future__ import annotations
 
+import asyncio
 from pathlib import Path
 from typing import Any
 
@@ -53,22 +57,30 @@ class VectorStore:
             import chromadb
             from chromadb.config import Settings
 
-            # 创建持久化客户端
-            self.client = chromadb.PersistentClient(
-                path=str(self.data_dir / "chroma"),
-                settings=Settings(
-                    anonymized_telemetry=False,
-                    allow_reset=True,
-                ),
-            )
+            # 创建持久化客户端 - 同步操作需要在线程中执行
+            def _create_client():
+                return chromadb.PersistentClient(
+                    path=str(self.data_dir / "chroma"),
+                    settings=Settings(
+                        anonymized_telemetry=False,
+                        allow_reset=True,
+                    ),
+                )
+            
+            self.client = await asyncio.to_thread(_create_client)
 
-            # 获取或创建集合
-            self.collection = self.client.get_or_create_collection(
-                name=self.collection_name,
-                metadata={"description": "Memory graph node embeddings"},
-            )
+            # 获取或创建集合 - 同步操作需要在线程中执行
+            def _get_or_create_collection():
+                return self.client.get_or_create_collection(
+                    name=self.collection_name,
+                    metadata={"description": "Memory graph node embeddings"},
+                )
+            
+            self.collection = await asyncio.to_thread(_get_or_create_collection)
 
-            logger.debug(f"ChromaDB 初始化完成，集合包含 {self.collection.count()} 个节点")
+            # count() 也是同步操作
+            count = await asyncio.to_thread(self.collection.count)
+            logger.debug(f"ChromaDB 初始化完成，集合包含 {count} 个节点")
 
         except Exception as e:
             logger.error(f"初始化 ChromaDB 失败: {e}")
@@ -106,12 +118,16 @@ class VectorStore:
                 else:
                     metadata[key] = str(value)
 
-            self.collection.add(
-                ids=[node.id],
-                embeddings=[node.embedding.tolist()],
-                metadatas=[metadata],
-                documents=[node.content],  # 文本内容用于检索
-            )
+            # ChromaDB add() 是同步阻塞操作，必须在线程中执行
+            def _add_node():
+                self.collection.add(
+                    ids=[node.id],
+                    embeddings=[node.embedding.tolist()],
+                    metadatas=[metadata],
+                    documents=[node.content],
+                )
+            
+            await asyncio.to_thread(_add_node)
 
             logger.debug(f"添加节点到向量存储: {node}")
 
@@ -155,12 +171,16 @@ class VectorStore:
                         metadata[key] = str(value)
                 metadatas.append(metadata)
 
-            self.collection.add(
-                ids=[n.id for n in valid_nodes],
-                embeddings=[n.embedding.tolist() for n in valid_nodes],  # type: ignore
-                metadatas=metadatas,
-                documents=[n.content for n in valid_nodes],
-            )
+            # ChromaDB add() 是同步阻塞操作，必须在线程中执行
+            def _add_batch():
+                self.collection.add(
+                    ids=[n.id for n in valid_nodes],
+                    embeddings=[n.embedding.tolist() for n in valid_nodes],  # type: ignore
+                    metadatas=metadatas,
+                    documents=[n.content for n in valid_nodes],
+                )
+            
+            await asyncio.to_thread(_add_batch)
 
         except Exception as e:
             logger.error(f"批量添加节点失败: {e}")
@@ -194,12 +214,15 @@ class VectorStore:
             if node_types:
                 where_filter = {"node_type": {"$in": [nt.value for nt in node_types]}}
 
-            # 执行查询
-            results = self.collection.query(
-                query_embeddings=[query_embedding.tolist()],
-                n_results=limit,
-                where=where_filter,
-            )
+            # ChromaDB query() 是同步阻塞操作，必须在线程中执行
+            def _query():
+                return self.collection.query(
+                    query_embeddings=[query_embedding.tolist()],
+                    n_results=limit,
+                    where=where_filter,
+                )
+            
+            results = await asyncio.to_thread(_query)
 
             # 解析结果
             import orjson
@@ -360,7 +383,11 @@ class VectorStore:
             raise RuntimeError("向量存储未初始化")
 
         try:
-            result = self.collection.get(ids=[node_id], include=["metadatas", "embeddings"])
+            # ChromaDB get() 是同步阻塞操作，必须在线程中执行
+            def _get():
+                return self.collection.get(ids=[node_id], include=["metadatas", "embeddings"])
+            
+            result = await asyncio.to_thread(_get)
 
             # 修复：直接检查 ids 列表是否非空（避免 numpy 数组的布尔值歧义）
             if result is not None:
@@ -392,7 +419,11 @@ class VectorStore:
             raise RuntimeError("向量存储未初始化")
 
         try:
-            self.collection.delete(ids=[node_id])
+            # ChromaDB delete() 是同步阻塞操作，必须在线程中执行
+            def _delete():
+                self.collection.delete(ids=[node_id])
+            
+            await asyncio.to_thread(_delete)
             logger.debug(f"删除节点: {node_id}")
 
         except Exception as e:
@@ -411,7 +442,11 @@ class VectorStore:
             raise RuntimeError("向量存储未初始化")
 
         try:
-            self.collection.update(ids=[node_id], embeddings=[embedding.tolist()])
+            # ChromaDB update() 是同步阻塞操作，必须在线程中执行
+            def _update():
+                self.collection.update(ids=[node_id], embeddings=[embedding.tolist()])
+            
+            await asyncio.to_thread(_update)
             logger.debug(f"更新节点 embedding: {node_id}")
 
         except Exception as e:
@@ -419,10 +454,16 @@ class VectorStore:
             raise
 
     def get_total_count(self) -> int:
-        """获取向量存储中的节点总数"""
+        """获取向量存储中的节点总数（同步方法，谨慎在 async 上下文中使用）"""
         if not self.collection:
             return 0
         return self.collection.count()
+    
+    async def get_total_count_async(self) -> int:
+        """异步获取向量存储中的节点总数"""
+        if not self.collection:
+            return 0
+        return await asyncio.to_thread(self.collection.count)
 
     async def clear(self) -> None:
         """清空向量存储（危险操作，仅用于测试）"""
@@ -430,12 +471,15 @@ class VectorStore:
             return
 
         try:
-            # 删除并重新创建集合
-            self.client.delete_collection(self.collection_name)
-            self.collection = self.client.get_or_create_collection(
-                name=self.collection_name,
-                metadata={"description": "Memory graph node embeddings"},
-            )
+            # ChromaDB delete_collection 和 get_or_create_collection 都是同步阻塞操作
+            def _clear():
+                self.client.delete_collection(self.collection_name)
+                return self.client.get_or_create_collection(
+                    name=self.collection_name,
+                    metadata={"description": "Memory graph node embeddings"},
+                )
+            
+            self.collection = await asyncio.to_thread(_clear)
             logger.warning(f"向量存储已清空: {self.collection_name}")
 
         except Exception as e: