refactor(mem0): optimize connection pool and async memory handling

- Fix mem0 connection pool exhausted error with proper pooling
- Convert memory operations to async tasks
- Optimize docker-compose configuration
- Add skill upload functionality
- Reduce cache size for better performance
- Update dependencies

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

agent/agent_config.py

@@ -105,9 +105,7 @@ class AgentConfig:
         enable_thinking = request.enable_thinking and "<guidelines>" in request.system_prompt
 
         # 从请求中获取 Mem0 配置，如果没有则使用全局配置
-        enable_memori = getattr(request, 'enable_memori', None)
+        enable_memori = getattr(request, 'enable_memori', MEM0_ENABLED)
-        if enable_memori is None:
-            enable_memori = MEM0_ENABLED
 
         config = cls(
             bot_id=request.bot_id,
@@ -171,10 +169,7 @@ class AgentConfig:
         enable_thinking = request.enable_thinking and "<guidelines>" in bot_config.get("system_prompt")
 
         # 从请求或后端配置中获取 Mem0 配置
-        enable_memori = getattr(request, 'enable_memori', None)
+        enable_memori = getattr(request, 'enable_memori', MEM0_ENABLED)
-        if enable_memori is None:
-            enable_memori = bot_config.get("enable_memori", MEM0_ENABLED)
-
 
         config = cls(
             bot_id=request.bot_id,

agent/db_pool_manager.py

@@ -12,6 +12,7 @@ from psycopg2 import pool as psycopg2_pool
 from utils.settings import (
     CHECKPOINT_DB_URL,
     CHECKPOINT_POOL_SIZE,
+    MEM0_POOL_SIZE,
     CHECKPOINT_CLEANUP_ENABLED,
     CHECKPOINT_CLEANUP_INTERVAL_HOURS,
     CHECKPOINT_CLEANUP_INACTIVE_DAYS,
@@ -62,7 +63,7 @@ class DBPoolManager:
             await self._pool.open()
 
             # 2. 创建同步 psycopg2 连接池（供 Mem0 使用）
-            self._sync_pool = self._create_sync_pool(CHECKPOINT_DB_URL, CHECKPOINT_POOL_SIZE)
+            self._sync_pool = self._create_sync_pool(CHECKPOINT_DB_URL, MEM0_POOL_SIZE)
 
             self._initialized = True
             logger.info("PostgreSQL connection pool initialized successfully")

agent/mem0_manager.py

@@ -5,11 +5,16 @@ Mem0 连接和实例管理器
 
 import logging
 import asyncio
+import threading
+import concurrent.futures
 from typing import Any, Dict, List, Optional, Literal
+from collections import OrderedDict
 from embedding.manager import GlobalModelManager, get_model_manager
 import json_repair
 from psycopg2 import pool
-
+from utils.settings import (
+    MEM0_POOL_SIZE
+)
 from .mem0_config import Mem0Config
 
 logger = logging.getLogger("app")
@@ -27,7 +32,9 @@ class CustomMem0Embedding:
     这样 Mem0 就不需要再次加载同一个模型，节省内存
     """
 
-    _model_manager = None  # 缓存 GlobalModelManager 实例
+    _model = None  # 类变量，缓存模型实例
+    _lock = threading.Lock()  # 线程安全锁
+    _executor = None  # 线程池执行器
 
     def __init__(self, config: Optional[Any] = None):
         """初始化自定义 Embedding"""
@@ -41,6 +48,41 @@ class CustomMem0Embedding:
         """获取 embedding 维度"""
         return 384  # gte-tiny 的维度
 
+    def _get_model_sync(self):
+        """同步获取模型，避免 asyncio.run()"""
+        # 首先尝试从 manager 获取已加载的模型
+        manager = get_model_manager()
+        model = manager.get_model_sync()
+
+        if model is not None:
+            # 缓存模型
+            CustomMem0Embedding._model = model
+            return model
+
+        # 如果模型未加载，使用线程池运行异步初始化
+        if CustomMem0Embedding._executor is None:
+            CustomMem0Embedding._executor = concurrent.futures.ThreadPoolExecutor(
+                max_workers=1,
+                thread_name_prefix="mem0_embed"
+            )
+
+        # 在独立线程中运行异步代码
+        def run_async_in_thread():
+            loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(loop)
+            try:
+                result = loop.run_until_complete(manager.get_model())
+                return result
+            finally:
+                loop.close()
+
+        future = CustomMem0Embedding._executor.submit(run_async_in_thread)
+        model = future.result(timeout=30)  # 30秒超时
+
+        # 缓存模型
+        CustomMem0Embedding._model = model
+        return model
+
     def embed(self, text, memory_action: Optional[Literal["add", "search", "update"]] = None):
         """
         获取文本的 embedding 向量（同步方法，供 Mem0 调用）
@@ -52,8 +94,13 @@ class CustomMem0Embedding:
         Returns:
             list: embedding 向量
         """
-        manager = get_model_manager()
+        # 线程安全地获取模型
-        model = asyncio.run(manager.get_model())
+        if CustomMem0Embedding._model is None:
+            with CustomMem0Embedding._lock:
+                if CustomMem0Embedding._model is None:
+                    self._get_model_sync()
+
+        model = CustomMem0Embedding._model
         embeddings = model.encode(text, convert_to_numpy=True)
         return embeddings.tolist()
 
@@ -136,8 +183,9 @@ class Mem0Manager:
         """
         self._sync_pool = sync_pool
 
-        # 缓存 Mem0 实例: key = f"{user_id}:{agent_id}"
+        # 使用 OrderedDict 实现 LRU 缓存，最多保留 50 个实例
-        self._instances: Dict[str, Any] = {}
+        self._instances: OrderedDict[str, Any] = OrderedDict()
+        self._max_instances = MEM0_POOL_SIZE/2  # 最大缓存实例数
         self._initialized = False
 
     async def initialize(self) -> None:
@@ -194,10 +242,16 @@ class Mem0Manager:
             llm_suffix = f":{id(config.llm_instance)}"
         cache_key = f"{user_id}:{agent_id}{llm_suffix}"
 
-        # 检查缓存
+        # 检查缓存（同时移动到末尾表示最近使用）
         if cache_key in self._instances:
+            self._instances.move_to_end(cache_key)
             return self._instances[cache_key]
 
+        # 检查缓存大小，超过则移除最旧的
+        if len(self._instances) >= self._max_instances:
+            removed_key, _ = self._instances.popitem(last=False)
+            logger.debug(f"Mem0 instance cache full, removed oldest entry: {removed_key}")
+
         # 创建新实例
         mem0_instance = await self._create_mem0_instance(
             user_id=user_id,
@@ -206,7 +260,7 @@ class Mem0Manager:
             config=config,
         )
 
-        # 缓存实例
+        # 缓存实例（新实例自动在末尾）
         self._instances[cache_key] = mem0_instance
         return mem0_instance
 

agent/mem0_middleware.py

@@ -3,7 +3,9 @@ Mem0 Agent 中间件
 实现记忆召回和存储的 AgentMiddleware
 """
 
+import asyncio
 import logging
+import threading
 from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional
 
 from langchain.agents.middleware import AgentMiddleware, AgentState, ModelRequest
@@ -123,8 +125,6 @@ class Mem0Middleware(AgentMiddleware):
             return None
 
         try:
-            import asyncio
-
             # 提取用户查询
             query = self._extract_user_query(state)
             if not query:
@@ -216,6 +216,8 @@ class Mem0Middleware(AgentMiddleware):
     def after_agent(self, state: AgentState, runtime: Runtime) -> None:
         """Agent 执行后：触发记忆增强（同步版本）
 
+        使用后台线程执行，避免阻塞主流程
+
         Args:
             state: Agent 状态
             runtime: 运行时上下文
@@ -224,16 +226,21 @@ class Mem0Middleware(AgentMiddleware):
             return
 
         try:
-            import asyncio
+            # 在后台线程中执行，完全不阻塞主流程
-
+            thread = threading.Thread(
-            # 触发后台增强任务
+                target=self._trigger_augmentation_sync,
-            asyncio.create_task(self._trigger_augmentation_async(state, runtime))
+                args=(state, runtime),
+                daemon=True,
+            )
+            thread.start()
         except Exception as e:
             logger.error(f"Error in Mem0Middleware.after_agent: {e}")
 
     async def aafter_agent(self, state: AgentState, runtime: Runtime) -> None:
         """Agent 执行后：触发记忆增强（异步版本）
 
+        使用后台线程执行，避免阻塞事件循环
+
         Args:
             state: Agent 状态
             runtime: 运行时上下文
@@ -242,10 +249,57 @@ class Mem0Middleware(AgentMiddleware):
             return
 
         try:
-            await self._trigger_augmentation_async(state, runtime)
+            # 在后台线程中执行，完全不阻塞事件循环
+            thread = threading.Thread(
+                target=self._trigger_augmentation_sync,
+                args=(state, runtime),
+                daemon=True,
+            )
+            thread.start()
         except Exception as e:
             logger.error(f"Error in Mem0Middleware.aafter_agent: {e}")
 
+    def _trigger_augmentation_sync(self, state: AgentState, runtime: Runtime) -> None:
+        """触发记忆增强任务（同步版本，在线程中执行）
+
+        从对话中提取信息并存储到 Mem0（用户级别，跨会话）
+
+        Args:
+            state: Agent 状态
+            runtime: 运行时上下文
+        """
+        try:
+            # 获取 attribution 参数
+            user_id, agent_id = self.config.get_attribution_tuple()
+
+            # 提取用户查询和 Agent 响应
+            user_query = self._extract_user_query(state)
+            agent_response = self._extract_agent_response(state)
+
+            # 将对话作为记忆存储（用户级别）
+            if user_query and agent_response:
+                conversation_text = f"User: {user_query}\nAssistant: {agent_response}"
+
+                # 在新的事件循环中运行异步代码（因为在线程中）
+                loop = asyncio.new_event_loop()
+                asyncio.set_event_loop(loop)
+                try:
+                    loop.run_until_complete(
+                        self.mem0_manager.add_memory(
+                            text=conversation_text,
+                            user_id=user_id,
+                            agent_id=agent_id,
+                            metadata={"type": "conversation"},
+                            config=self.config,
+                        )
+                    )
+                    logger.debug(f"Stored conversation as memory for user={user_id}, agent={agent_id}")
+                finally:
+                    loop.close()
+
+        except Exception as e:
+            logger.error(f"Error in _trigger_augmentation_sync: {e}")
+
     async def _trigger_augmentation_async(self, state: AgentState, runtime: Runtime) -> None:
         """触发记忆增强任务
 

docker-compose-with-pgsql.yml

@@ -2,7 +2,7 @@ version: "3.8"
 
 services:
   postgres:
-    image: postgres:16-alpine
+    image: pgvector/pgvector:pg16
     container_name: qwen-agent-postgres
     environment:
       - POSTGRES_USER=postgres
@@ -37,6 +37,7 @@ services:
     volumes:
       # 挂载项目数据目录
       - ./projects:/app/projects
+      - ./models:/app/models
     depends_on:
       postgres:
         condition: service_healthy

embedding/manager.py

@@ -108,6 +108,16 @@ class GlobalModelManager:
             logger.error(f"文本编码失败: {e}")
             raise
     
+    def get_model_sync(self) -> Optional[SentenceTransformer]:
+        """同步获取模型实例（供同步上下文使用）
+
+        如果模型未加载，返回 None。调用者应确保先通过异步方法初始化模型。
+
+        Returns:
+            已加载的 SentenceTransformer 模型，或 None
+        """
+        return self._model
+
     def get_model_info(self) -> Dict[str, Any]:
         """获取模型信息"""
         return {

poetry.lock

@@ -1773,21 +1773,21 @@ tiktoken = ">=0.7.0,<1.0.0"
 
 [[package]]
 name = "langgraph"
-version = "1.0.4"
+version = "1.0.6"
 description = "Building stateful, multi-actor applications with LLMs"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "langgraph-1.0.4-py3-none-any.whl", hash = "sha256:b1a835ceb0a8d69b9db48075e1939e28b1ad70ee23fa3fa8f90149904778bacf"},
+    {file = "langgraph-1.0.6-py3-none-any.whl", hash = "sha256:bcfce190974519c72e29f6e5b17f0023914fd6f936bfab8894083215b271eb89"},
-    {file = "langgraph-1.0.4.tar.gz", hash = "sha256:86d08e25d7244340f59c5200fa69fdd11066aa999b3164b531e2a20036fac156"},
+    {file = "langgraph-1.0.6.tar.gz", hash = "sha256:dd8e754c76d34a07485308d7117221acf63990e7de8f46ddf5fe256b0a22e6c5"},
 ]
 
 [package.dependencies]
 langchain-core = ">=0.1"
-langgraph-checkpoint = ">=2.1.0,<4.0.0"
+langgraph-checkpoint = ">=2.1.0,<5.0.0"
 langgraph-prebuilt = ">=1.0.2,<1.1.0"
-langgraph-sdk = ">=0.2.2,<0.3.0"
+langgraph-sdk = ">=0.3.0,<0.4.0"
 pydantic = ">=2.7.4"
 xxhash = ">=3.5.0"
 
@@ -1843,14 +1843,14 @@ langgraph-checkpoint = ">=2.1.0,<4.0.0"
 
 [[package]]
 name = "langgraph-sdk"
-version = "0.2.15"
+version = "0.3.3"
 description = "SDK for interacting with LangGraph API"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "langgraph_sdk-0.2.15-py3-none-any.whl", hash = "sha256:746566a5d89aa47160eccc17d71682a78771c754126f6c235a68353d61ed7462"},
+    {file = "langgraph_sdk-0.3.3-py3-none-any.whl", hash = "sha256:a52ebaf09d91143e55378bb2d0b033ed98f57f48c9ad35c8f81493b88705fc7b"},
-    {file = "langgraph_sdk-0.2.15.tar.gz", hash = "sha256:8faaafe2c1193b89f782dd66c591060cd67862aa6aaf283749b7846f331d5334"},
+    {file = "langgraph_sdk-0.3.3.tar.gz", hash = "sha256:c34c3dce3b6848755eb61f0c94369d1ba04aceeb1b76015db1ea7362c544fb26"},
 ]
 
 [package.dependencies]

public/index.html

@@ -220,17 +220,15 @@
             color: var(--text);
         }
     </style>
-    <script src="https://unpkg.com/lucide@latest/dist/umd/lucide.js"></script>
-
     <!-- Fonts -->
     <link rel="preconnect" href="https://fonts.googleapis.com">
     <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
     <link href="https://fonts.googleapis.com/css2?family=Open+Sans:wght@300;400;500;600;700&family=Poppins:wght@400;500;600;700&display=swap" rel="stylesheet">
     <!-- Highlight.js -->
-    <link rel="stylesheet" href="https://cdn.staticfile.net/highlight.js/11.9.0/styles/github.min.css">
+    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/styles/github.min.css">
-    <script src="https://cdn.staticfile.net/highlight.js/11.9.0/highlight.min.js"></script>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/highlight.js/11.9.0/highlight.min.js"></script>
     <!-- Marked.js -->
-    <script src="https://cdn.staticfile.net/marked/4.3.0/marked.min.js"></script>
+    <script src="https://cdn.jsdelivr.net/npm/marked@4.3.0/marked.min.js"></script>
     <!-- Lucide Icons -->
     <script src="https://unpkg.com/lucide@latest/dist/umd/lucide.js"></script>
 
@@ -1911,6 +1909,13 @@
                             <label class="settings-label" for="user-identifier">用户标识</label>
                             <input type="text" id="user-identifier" class="settings-input" placeholder="输入用户标识...">
                         </div>
+                        <div class="settings-group">
+                            <div class="settings-checkbox-wrapper">
+                                <input type="checkbox" id="enable-memori" class="settings-checkbox">
+                                <label class="settings-label" for="enable-memori" style="margin-bottom: 0;">启用记忆存储</label>
+                            </div>
+                            <p style="font-size: 11px; color: var(--text-muted); margin-top: 4px;">启用后，AI 会记住对话中的信息以提供更个性化的回复</p>
+                        </div>
                     </div>
                 </div>
 
@@ -2842,6 +2847,7 @@
                     'dataset-ids': document.getElementById('dataset-ids').value,
                     'system-prompt': document.getElementById('system-prompt').value,
                     'user-identifier': document.getElementById('user-identifier').value,
+                    'enable-memori': document.getElementById('enable-memori').checked,
                     'skills': selectedSkills.join(','),
                     'mcp-settings': mcpSettingsValue,
                     'tool-response': document.getElementById('tool-response').checked
@@ -3235,6 +3241,7 @@
                     systemPrompt: getValue('system-prompt'),
                     sessionId,
                     userIdentifier: getValue('user-identifier'),
+                    enableMemori: getChecked('enable-memori'),
                     skills,
                     mcpSettings,
                     toolResponse: getChecked('tool-response')
@@ -3492,6 +3499,7 @@
                 if (settings.systemPrompt) requestBody.system_prompt = settings.systemPrompt;
                 if (settings.sessionId) requestBody.session_id = settings.sessionId;
                 if (settings.userIdentifier) requestBody.user_identifier = settings.userIdentifier;
+                if (settings.enableMemori) requestBody.enable_memori = settings.enableMemori;
                 if (settings.skills?.length) requestBody.skills = settings.skills;
                 if (settings.datasetIds?.length) requestBody.dataset_ids = settings.datasetIds;
                 if (settings.mcpSettings?.length) requestBody.mcp_settings = settings.mcpSettings;

requirements.txt

@@ -64,8 +64,8 @@ langchain==1.1.3 ; python_version >= "3.12" and python_version < "4.0"
 langgraph-checkpoint-postgres==2.0.25 ; python_version >= "3.12" and python_version < "4.0"
 langgraph-checkpoint==2.1.2 ; python_version >= "3.12" and python_version < "4.0"
 langgraph-prebuilt==1.0.5 ; python_version >= "3.12" and python_version < "4.0"
-langgraph-sdk==0.2.15 ; python_version >= "3.12" and python_version < "4.0"
+langgraph-sdk==0.3.3 ; python_version >= "3.12" and python_version < "4.0"
-langgraph==1.0.4 ; python_version >= "3.12" and python_version < "4.0"
+langgraph==1.0.6 ; python_version >= "3.12" and python_version < "4.0"
 langsmith==0.4.59 ; python_version >= "3.12" and python_version < "4.0"
 markdown-it-py==4.0.0 ; python_version >= "3.12" and python_version < "4.0"
 markdownify==1.2.2 ; python_version >= "3.12" and python_version < "4.0"

routes/skill_manager.py

@@ -199,6 +199,73 @@ async def safe_extract_zip(zip_path: str, extract_dir: str) -> None:
         raise HTTPException(status_code=400, detail=f"无效的 zip 文件: {str(e)}")
 
 
+async def validate_and_rename_skill_folder(
+    extract_dir: str,
+    has_top_level_dirs: bool
+) -> str:
+    """验证并重命名解压后的 skill 文件夹
+
+    检查解压后文件夹名称是否与 SKILL.md 中的 name 匹配，
+    如果不匹配则重命名文件夹。
+
+    Args:
+        extract_dir: 解压目标目录
+        has_top_level_dirs: zip 是否包含顶级目录
+
+    Returns:
+        str: 最终的解压路径（可能因为重命名而改变）
+    """
+    try:
+        if has_top_level_dirs:
+            # zip 包含目录，检查每个目录
+            for folder_name in os.listdir(extract_dir):
+                folder_path = os.path.join(extract_dir, folder_name)
+                if os.path.isdir(folder_path):
+                    skill_md_path = os.path.join(folder_path, 'SKILL.md')
+                    if os.path.exists(skill_md_path):
+                        metadata = await asyncio.to_thread(
+                            parse_skill_frontmatter, skill_md_path
+                        )
+                        if metadata and 'name' in metadata:
+                            expected_name = metadata['name']
+                            if folder_name != expected_name:
+                                new_folder_path = os.path.join(extract_dir, expected_name)
+                                await asyncio.to_thread(
+                                    shutil.move, folder_path, new_folder_path
+                                )
+                                logger.info(
+                                    f"Renamed skill folder: {folder_name} -> {expected_name}"
+                                )
+            return extract_dir
+        else:
+            # zip 直接包含文件，检查当前目录的 SKILL.md
+            skill_md_path = os.path.join(extract_dir, 'SKILL.md')
+            if os.path.exists(skill_md_path):
+                metadata = await asyncio.to_thread(
+                    parse_skill_frontmatter, skill_md_path
+                )
+                if metadata and 'name' in metadata:
+                    expected_name = metadata['name']
+                    # 获取当前文件夹名称
+                    current_name = os.path.basename(extract_dir)
+                    if current_name != expected_name:
+                        parent_dir = os.path.dirname(extract_dir)
+                        new_folder_path = os.path.join(parent_dir, expected_name)
+                        await asyncio.to_thread(
+                            shutil.move, extract_dir, new_folder_path
+                        )
+                        logger.info(
+                            f"Renamed skill folder: {current_name} -> {expected_name}"
+                        )
+                        return new_folder_path
+            return extract_dir
+
+    except Exception as e:
+        logger.warning(f"Failed to validate/rename skill folder: {e}")
+        # 不抛出异常，允许上传继续
+        return extract_dir
+
+
 async def save_upload_file_async(file: UploadFile, destination: str) -> None:
     """异步保存上传文件到目标路径"""
     async with aiofiles.open(destination, 'wb') as f:
@@ -453,13 +520,24 @@ async def upload_skill(file: UploadFile = File(...), bot_id: Optional[str] = For
         await safe_extract_zip(file_path, extract_target)
         logger.info(f"Extracted to: {extract_target}")
 
+        # 验证并重命名文件夹以匹配 SKILL.md 中的 name
+        final_extract_path = await validate_and_rename_skill_folder(
+            extract_target, has_top_level_dirs
+        )
+
+        # 获取最终的 skill 名称
+        if has_top_level_dirs:
+            final_skill_name = folder_name
+        else:
+            final_skill_name = os.path.basename(final_extract_path)
+
         return {
             "success": True,
             "message": f"Skill文件上传并解压成功",
             "file_path": file_path,
-            "extract_path": extract_target,
+            "extract_path": final_extract_path,
             "original_filename": original_filename,
-            "skill_name": folder_name
+            "skill_name": final_skill_name
         }
 
     except HTTPException:

utils/settings.py

@@ -54,6 +54,7 @@ CHECKPOINT_DB_URL = os.getenv("CHECKPOINT_DB_URL", "postgresql://moshui:@localho
 # 连接池大小
 # 同时可以持有的最大连接数
 CHECKPOINT_POOL_SIZE = int(os.getenv("CHECKPOINT_POOL_SIZE", "20"))
+MEM0_POOL_SIZE = int(os.getenv("MEM0_POOL_SIZE", "20"))
 
 # Checkpoint 自动清理配置
 # 是否启用自动清理旧 session