Merge branch 'refs/heads/develop' into fix/memory_bug_fix

# Conflicts:
#	api/app/services/user_memory_service.py

api/app/controllers/workflow_controller.py

@@ -39,11 +39,11 @@ router = APIRouter(prefix="/apps", tags=["workflow"])
 @router.post("/{app_id}/workflow")
 @cur_workspace_access_guard()
 async def create_workflow_config(
-    app_id: Annotated[uuid.UUID, Path(description="应用 ID")],
-    config: WorkflowConfigCreate,
-    db: Annotated[Session, Depends(get_db)],
-    current_user: Annotated[User, Depends(get_current_user)],
-    service: Annotated[WorkflowService, Depends(get_workflow_service)]
+        app_id: Annotated[uuid.UUID, Path(description="应用 ID")],
+        config: WorkflowConfigCreate,
+        db: Annotated[Session, Depends(get_db)],
+        current_user: Annotated[User, Depends(get_current_user)],
+        service: Annotated[WorkflowService, Depends(get_workflow_service)]
 ):
     """创建工作流配置
 
@@ -96,6 +96,7 @@ async def create_workflow_config(
             msg=f"创建工作流配置失败: {str(e)}"
         )
 
+
 #
 # @router.get("/{app_id}/workflow")
 # async def get_workflow_config(
@@ -199,10 +200,10 @@ async def create_workflow_config(
 
 @router.delete("/{app_id}/workflow")
 async def delete_workflow_config(
-    app_id: Annotated[uuid.UUID, Path(description="应用 ID")],
-    db: Annotated[Session, Depends(get_db)],
-    current_user: Annotated[User, Depends(get_current_user)],
-    service: Annotated[WorkflowService, Depends(get_workflow_service)]
+        app_id: Annotated[uuid.UUID, Path(description="应用 ID")],
+        db: Annotated[Session, Depends(get_db)],
+        current_user: Annotated[User, Depends(get_current_user)],
+        service: Annotated[WorkflowService, Depends(get_workflow_service)]
 ):
     """删除工作流配置
 
@@ -243,11 +244,11 @@ async def delete_workflow_config(
 
 @router.post("/{app_id}/workflow/validate")
 async def validate_workflow_config(
-    app_id: Annotated[uuid.UUID, Path(description="应用 ID")],
-    db: Annotated[Session, Depends(get_db)],
-    current_user: Annotated[User, Depends(get_current_user)],
-    service: Annotated[WorkflowService, Depends(get_workflow_service)],
-    for_publish: Annotated[bool, Query(description="是否为发布验证")] = False
+        app_id: Annotated[uuid.UUID, Path(description="应用 ID")],
+        db: Annotated[Session, Depends(get_db)],
+        current_user: Annotated[User, Depends(get_current_user)],
+        service: Annotated[WorkflowService, Depends(get_workflow_service)],
+        for_publish: Annotated[bool, Query(description="是否为发布验证")] = False
 ):
     """验证工作流配置
 
@@ -312,12 +313,12 @@ async def validate_workflow_config(
 
 @router.get("/{app_id}/workflow/executions")
 async def get_workflow_executions(
-    app_id: Annotated[uuid.UUID, Path(description="应用 ID")],
-    db: Annotated[Session, Depends(get_db)],
-    current_user: Annotated[User, Depends(get_current_user)],
-    service: Annotated[WorkflowService, Depends(get_workflow_service)],
-    limit: Annotated[int, Query(ge=1, le=100)] = 50,
-    offset: Annotated[int, Query(ge=0)] = 0
+        app_id: Annotated[uuid.UUID, Path(description="应用 ID")],
+        db: Annotated[Session, Depends(get_db)],
+        current_user: Annotated[User, Depends(get_current_user)],
+        service: Annotated[WorkflowService, Depends(get_workflow_service)],
+        limit: Annotated[int, Query(ge=1, le=100)] = 50,
+        offset: Annotated[int, Query(ge=0)] = 0
 ):
     """获取工作流执行记录列表
 
@@ -365,10 +366,10 @@ async def get_workflow_executions(
 
 @router.get("/workflow/executions/{execution_id}")
 async def get_workflow_execution(
-    execution_id: Annotated[str, Path(description="执行 ID")],
-    db: Annotated[Session, Depends(get_db)],
-    current_user: Annotated[User, Depends(get_current_user)],
-    service: Annotated[WorkflowService, Depends(get_workflow_service)]
+        execution_id: Annotated[str, Path(description="执行 ID")],
+        db: Annotated[Session, Depends(get_db)],
+        current_user: Annotated[User, Depends(get_current_user)],
+        service: Annotated[WorkflowService, Depends(get_workflow_service)]
 ):
     """获取工作流执行详情
 
@@ -417,16 +418,14 @@ async def get_workflow_execution(
         )
 
 
-
 # ==================== 工作流执行 ====================
-
 @router.post("/{app_id}/workflow/run")
 async def run_workflow(
-    app_id: Annotated[uuid.UUID, Path(description="应用 ID")],
-    request: WorkflowExecutionRequest,
-    db: Annotated[Session, Depends(get_db)],
-    current_user: Annotated[User, Depends(get_current_user)],
-    service: Annotated[WorkflowService, Depends(get_workflow_service)]
+        app_id: Annotated[uuid.UUID, Path(description="应用 ID")],
+        request: WorkflowExecutionRequest,
+        db: Annotated[Session, Depends(get_db)],
+        current_user: Annotated[User, Depends(get_current_user)],
+        service: Annotated[WorkflowService, Depends(get_workflow_service)]
 ):
     """执行工作流
 
@@ -487,22 +486,22 @@ async def run_workflow(
                 """
                 try:
                     async for event in await service.run_workflow(
-                        app_id=app_id,
-                        input_data=input_data,
-                        triggered_by=current_user.id,
-                        conversation_id=uuid.UUID(request.conversation_id) if request.conversation_id else None,
-                        stream=True
+                            app_id=app_id,
+                            input_data=input_data,
+                            triggered_by=current_user.id,
+                            conversation_id=uuid.UUID(request.conversation_id) if request.conversation_id else None,
+                            stream=True
                     ):
                         # 提取事件类型和数据
                         event_type = event.get("event", "message")
                         event_data = event.get("data", {})
-                        
+
                         # 转换为标准 SSE 格式（字符串）
                         # event: <type>
                         # data: <json>
                         sse_message = f"event: {event_type}\ndata: {json.dumps(event_data)}\n\n"
                         yield sse_message
-                        
+
                 except Exception as e:
                     logger.error(f"流式执行异常: {e}", exc_info=True)
                     # 发送错误事件
@@ -554,10 +553,10 @@ async def run_workflow(
 
 @router.post("/workflow/executions/{execution_id}/cancel")
 async def cancel_workflow_execution(
-    execution_id: Annotated[str, Path(description="执行 ID")],
-    db: Annotated[Session, Depends(get_db)],
-    current_user: Annotated[User, Depends(get_current_user)],
-    service: Annotated[WorkflowService, Depends(get_workflow_service)]
+        execution_id: Annotated[str, Path(description="执行 ID")],
+        db: Annotated[Session, Depends(get_db)],
+        current_user: Annotated[User, Depends(get_current_user)],
+        service: Annotated[WorkflowService, Depends(get_workflow_service)]
 ):
     """取消工作流执行
 
@@ -602,7 +601,7 @@ async def cancel_workflow_execution(
 
     except BusinessException as e:
         logger.warning(f"取消工作流执行失败: {e.message}")
-        return fail(code=e.error_code, msg=e.message)
+        return fail(code=e.code, msg=e.message)
     except Exception as e:
         logger.error(f"取消工作流执行异常: {e}", exc_info=True)
         return fail(

api/app/core/config.py

@@ -7,17 +7,18 @@ from dotenv import load_dotenv
 
 load_dotenv()
 
+
 class Settings:
     ENABLE_SINGLE_WORKSPACE: bool = os.getenv("ENABLE_SINGLE_WORKSPACE", "true").lower() == "true"
     # API Keys Configuration
     OPENAI_API_KEY: str = os.getenv("OPENAI_API_KEY", "")
     DASHSCOPE_API_KEY: str = os.getenv("DASHSCOPE_API_KEY", "")
-    
+
     # Neo4j Configuration (记忆系统数据库)
     NEO4J_URI: str = os.getenv("NEO4J_URI", "bolt://1.94.111.67:7687")
     NEO4J_USERNAME: str = os.getenv("NEO4J_USERNAME", "neo4j")
     NEO4J_PASSWORD: str = os.getenv("NEO4J_PASSWORD", "")
-    
+
     # Database configuration (Postgres)
     DB_HOST: str = os.getenv("DB_HOST", "127.0.0.1")
     DB_PORT: int = int(os.getenv("DB_PORT", "5432"))
@@ -37,7 +38,7 @@ class Settings:
     REDIS_PORT: int = int(os.getenv("REDIS_PORT", "6379"))
     REDIS_DB: int = int(os.getenv("REDIS_DB", "1"))
     REDIS_PASSWORD: str = os.getenv("REDIS_PASSWORD", "")
-    
+
     # ElasticSearch configuration
     ELASTICSEARCH_HOST: str = os.getenv("ELASTICSEARCH_HOST", "https://127.0.0.1")
     ELASTICSEARCH_PORT: int = int(os.getenv("ELASTICSEARCH_PORT", "9200"))
@@ -48,7 +49,7 @@ class Settings:
     ELASTICSEARCH_REQUEST_TIMEOUT: int = int(os.getenv("ELASTICSEARCH_REQUEST_TIMEOUT", "100000"))
     ELASTICSEARCH_RETRY_ON_TIMEOUT: bool = os.getenv("ELASTICSEARCH_RETRY_ON_TIMEOUT", "True").lower() == "true"
     ELASTICSEARCH_MAX_RETRIES: int = int(os.getenv("ELASTICSEARCH_MAX_RETRIES", "10"))
-    
+
     # Xinference configuration
     XINFERENCE_URL: str = os.getenv("XINFERENCE_URL", "http://127.0.0.1")
 
@@ -57,17 +58,17 @@ class Settings:
     LANGCHAIN_TRACING: bool = os.getenv("LANGCHAIN_TRACING", "false").lower() == "true"
     LANGCHAIN_API_KEY: str = os.getenv("LANGCHAIN_API_KEY", "")
     LANGCHAIN_ENDPOINT: str = os.getenv("LANGCHAIN_ENDPOINT", "")
-    
+
     # LLM Request Configuration
     LLM_TIMEOUT: float = float(os.getenv("LLM_TIMEOUT", "120.0"))
     LLM_MAX_RETRIES: int = int(os.getenv("LLM_MAX_RETRIES", "2"))
-    
+
     # JWT Token Configuration
     SECRET_KEY: str = os.getenv("SECRET_KEY", "a_default_secret_key_that_is_long_and_random")
     ALGORITHM: str = "HS256"
     ACCESS_TOKEN_EXPIRE_MINUTES: int = int(os.getenv("ACCESS_TOKEN_EXPIRE_MINUTES", "30"))
     REFRESH_TOKEN_EXPIRE_DAYS: int = int(os.getenv("REFRESH_TOKEN_EXPIRE_DAYS", "7"))
-    
+
     # Single Sign-On configuration
     ENABLE_SINGLE_SESSION: bool = os.getenv("ENABLE_SINGLE_SESSION", "false").lower() == "true"
 
@@ -86,19 +87,19 @@ class Settings:
     LANGFUSE_PUBLIC_KEY: str = os.getenv("LANGFUSE_PUBLIC_KEY", "")
     LANGFUSE_SECRET_KEY: str = os.getenv("LANGFUSE_SECRET_KEY", "")
     LANGFUSE_HOST: str = os.getenv("LANGFUSE_HOST", "")
-    
+
     # Server Configuration
     SERVER_IP: str = os.getenv("SERVER_IP", "127.0.0.1")
 
     # ========================================================================
     # Internal Configuration (not in .env, used by application code)
     # ========================================================================
-    
+
     # Superuser settings (internal defaults)
     FIRST_SUPERUSER_EMAIL: str = os.getenv("FIRST_SUPERUSER_EMAIL", "admin@example.com")
     FIRST_SUPERUSER_USERNAME: str = os.getenv("FIRST_SUPERUSER_USERNAME", "admin")
     FIRST_SUPERUSER_PASSWORD: str = os.getenv("FIRST_SUPERUSER_PASSWORD", "admin_password")
-    
+
     # Generic File Upload (internal)
     GENERIC_FILE_PATH: str = os.getenv("GENERIC_FILE_PATH", "/uploads")
     ENABLE_FILE_COMPRESSION: bool = os.getenv("ENABLE_FILE_COMPRESSION", "false").lower() == "true"
@@ -123,7 +124,7 @@ class Settings:
     LOG_BACKUP_COUNT: int = int(os.getenv("LOG_BACKUP_COUNT", "5"))
     LOG_TO_CONSOLE: bool = os.getenv("LOG_TO_CONSOLE", "true").lower() == "true"
     LOG_TO_FILE: bool = os.getenv("LOG_TO_FILE", "true").lower() == "true"
-    
+
     # Sensitive Data Filtering
     ENABLE_SENSITIVE_DATA_FILTER: bool = os.getenv("ENABLE_SENSITIVE_DATA_FILTER", "true").lower() == "true"
 
@@ -142,7 +143,6 @@ class Settings:
     LOG_STREAM_BUFFER_SIZE: int = int(os.getenv("LOG_STREAM_BUFFER_SIZE", "8192"))  # 8KB
     LOG_FILE_MAX_SIZE_MB: int = int(os.getenv("LOG_FILE_MAX_SIZE_MB", "10"))  # 10MB
 
-
     # Celery configuration (internal)
     CELERY_BROKER: int = int(os.getenv("CELERY_BROKER", "1"))
     CELERY_BACKEND: int = int(os.getenv("CELERY_BACKEND", "2"))
@@ -150,15 +150,15 @@ class Settings:
     HEALTH_CHECK_SECONDS: float = float(os.getenv("HEALTH_CHECK_SECONDS", "600"))
     MEMORY_INCREMENT_INTERVAL_HOURS: float = float(os.getenv("MEMORY_INCREMENT_INTERVAL_HOURS", "24"))
     DEFAULT_WORKSPACE_ID: Optional[str] = os.getenv("DEFAULT_WORKSPACE_ID", None)
-    REFLECTION_INTERVAL_TIME:Optional[str] = int(os.getenv("REFLECTION_INTERVAL_TIME", 30))
-    
+    REFLECTION_INTERVAL_TIME: Optional[str] = int(os.getenv("REFLECTION_INTERVAL_TIME", 30))
+
     # Memory Cache Regeneration Configuration
     MEMORY_CACHE_REGENERATION_HOURS: int = int(os.getenv("MEMORY_CACHE_REGENERATION_HOURS", "24"))
 
     # Memory Module Configuration (internal)
     MEMORY_OUTPUT_DIR: str = os.getenv("MEMORY_OUTPUT_DIR", "logs/memory-output")
     MEMORY_CONFIG_DIR: str = os.getenv("MEMORY_CONFIG_DIR", "app/core/memory")
-    
+
     # Tool Management Configuration
     TOOL_CONFIG_DIR: str = os.getenv("TOOL_CONFIG_DIR", "app/core/tools")
     TOOL_EXECUTION_TIMEOUT: int = int(os.getenv("TOOL_EXECUTION_TIMEOUT", "60"))
@@ -167,7 +167,10 @@ class Settings:
 
     # official environment system version
     SYSTEM_VERSION: str = os.getenv("SYSTEM_VERSION", "v0.2.0")
-    
+
+    # workflow config
+    WORKFLOW_NODE_TIMEOUT: int = int(os.getenv("WORKFLOW_NODE_TIMEOUT", 600))
+
     def get_memory_output_path(self, filename: str = "") -> str:
         """
         Get the full path for memory module output files.
@@ -182,7 +185,7 @@ class Settings:
         if filename:
             return str(base_path / filename)
         return str(base_path)
-    
+
     def ensure_memory_output_dir(self) -> None:
         """
         Ensure the memory output directory exists.

api/app/core/memory/agent/mcp_server/tools/summary_tools.py

@@ -425,15 +425,9 @@ async def Input_Summary(
 
     try:
         # Extract services from context
-        template_service = get_context_resource(ctx, "template_service")
         session_service = get_context_resource(ctx, "session_service")
         search_service = get_context_resource(ctx, "search_service")
 
-        # Get LLM client from memory_config
-        with get_db_context() as db:
-            factory = MemoryClientFactory(db)
-            llm_client = factory.get_llm_client_from_config(memory_config)
-
         # Resolve session ID
         sessionid = Resolve_username(usermessages) or ""
         sessionid = sessionid.replace('call_id_', '')
@@ -539,31 +533,11 @@ async def Input_Summary(
             )
             retrieve_info, question, raw_results = "", query, []
 
+        # Return retrieved information directly without LLM processing
+        # Use the raw retrieved info as the answer
+        aimessages = retrieve_info if retrieve_info else "信息不足，无法回答"
 
-        # Render template
-        system_prompt = await template_service.render_template(
-            template_name='Retrieve_Summary_prompt.jinja2',
-            operation_name='input_summary',
-            query=query,
-            history=history,
-            retrieve_info=retrieve_info
-        )
-
-        # Call LLM with structured response
-        try:
-            structured = await llm_client.response_structured(
-                messages=[{"role": "system", "content": system_prompt}],
-                response_model=RetrieveSummaryResponse
-            )
-            aimessages = structured.data.query_answer or "信息不足，无法回答"
-        except Exception as e:
-            logger.error(
-                f"Input_Summary: response_structured failed, using default answer: {e}",
-                exc_info=True
-            )
-            aimessages = "信息不足，无法回答"
-
-        logger.info(f"Quick answer summary: {storage_type}--{user_rag_memory_id}--{aimessages}")
+        logger.info(f"Quick answer (no LLM): {storage_type}--{user_rag_memory_id}--{aimessages[:500]}...")
 
         # Emit intermediate output for frontend
         return {

api/app/core/tools/custom/schema_parser.py

@@ -10,9 +10,6 @@ from app.core.logging_config import get_business_logger
 
 logger = get_business_logger()
 
-# 为了兼容性，创建别名
-# SchemaParser = OpenAPISchemaParser = None
-
 
 class OpenAPISchemaParser:
     """OpenAPI Schema解析器 - 解析OpenAPI 3.0规范"""
@@ -213,7 +210,9 @@ class OpenAPISchemaParser:
                 
                 if not isinstance(operation, dict):
                     continue
-                
+
+                summary = operation.get("summary", "")
+
                 # 生成操作ID
                 operation_id = operation.get("operationId")
                 if not operation_id:
@@ -223,7 +222,7 @@ class OpenAPISchemaParser:
                 operations[operation_id] = {
                     "method": method.upper(),
                     "path": path,
-                    "summary": operation.get("summary", ""),
+                    "summary": summary if summary else operation_id,
                     "description": operation.get("description", ""),
                     "parameters": self._extract_parameters(operation),
                     "request_body": self._extract_request_body(operation),

api/app/core/tools/langchain_adapter.py

@@ -232,7 +232,7 @@ class LangchainAdapter:
             # 添加验证约束
             if param.enum:
                 # 枚举值约束
-                field_kwargs["regex"] = f"^({'|'.join(map(str, param.enum))})$"
+                field_kwargs["pattern"] = f"^({'|'.join(map(str, param.enum))})$"
             
             if param.minimum is not None:
                 field_kwargs["ge"] = param.minimum
@@ -241,7 +241,7 @@ class LangchainAdapter:
                 field_kwargs["le"] = param.maximum
             
             if param.pattern:
-                field_kwargs["regex"] = param.pattern
+                field_kwargs["pattern"] = param.pattern
             
             fields[param.name] = Field(**field_kwargs)
             annotations[param.name] = python_type

api/app/core/tools/mcp/client.py

@@ -27,20 +27,22 @@ class SimpleMCPClient:
         
         # 确定连接类型
         self.is_websocket = server_url.startswith(("ws://", "wss://"))
+        self.is_sse = "/sse" in server_url.lower()
         
         # 连接状态
         self._websocket = None
         self._session = None
         self._request_id = 0
         self._pending_requests = {}
+        self._server_capabilities = {}
+        self._endpoint_url = None  # SSE endpoint URL
+        self._sse_task = None
     
     async def __aenter__(self):
-        """异步上下文管理器入口"""
         await self.connect()
         return self
     
     async def __aexit__(self, exc_type, exc_val, exc_tb):
-        """异步上下文管理器出口"""
         await self.disconnect()
     
     async def connect(self):
@@ -57,47 +59,157 @@ class SimpleMCPClient:
     async def disconnect(self):
         """断开连接"""
         try:
+            if self._sse_task:
+                self._sse_task.cancel()
             if self._websocket:
                 await self._websocket.close()
                 self._websocket = None
-            
             if self._session:
                 await self._session.close()
                 self._session = None
-                
         except Exception as e:
             logger.error(f"断开连接失败: {e}")
     
     async def _connect_websocket(self):
         """WebSocket 连接"""
         headers = self._build_headers()
-        
         self._websocket = await websockets.connect(
             self.server_url,
             extra_headers=headers,
             timeout=self.timeout
         )
-        
-        # 启动消息处理
         asyncio.create_task(self._handle_websocket_messages())
-        
-        # 发送初始化消息
         await self._send_initialize()
     
     async def _connect_http(self):
         """HTTP 连接"""
         headers = self._build_headers()
         timeout = aiohttp.ClientTimeout(total=self.timeout)
+        self._session = aiohttp.ClientSession(headers=headers, timeout=timeout)
         
-        self._session = aiohttp.ClientSession(
-            headers=headers,
-            timeout=timeout
-        )
-        
-        # 对于 ModelScope MCP 服务，需要先发送初始化请求
-        if "modelscope.net" in self.server_url:
+        if self.is_sse:
+            await self._initialize_sse_session()
+        elif "modelscope.net" in self.server_url:
             await self._initialize_modelscope_session()
     
+    async def _initialize_sse_session(self):
+        """初始化 SSE MCP 会话 - 参考 Dify 实现"""
+        try:
+            # 建立 SSE 连接
+            response = await self._session.get(
+                self.server_url,
+                headers={"Accept": "text/event-stream"}
+            )
+            
+            if response.status != 200:
+                error_text = await response.text()
+                raise MCPConnectionError(f"SSE 连接失败 {response.status}: {error_text}")
+            
+            # 启动 SSE 读取任务
+            self._sse_task = asyncio.create_task(self._read_sse_stream(response))
+            
+            # 等待获取 endpoint URL
+            for _ in range(10):
+                if self._endpoint_url:
+                    break
+                await asyncio.sleep(1)
+            
+            if not self._endpoint_url:
+                raise MCPConnectionError("未能获取 endpoint URL")
+            
+            # 发送 initialize 请求到 endpoint
+            init_request = {
+                "jsonrpc": "2.0",
+                "id": self._get_request_id(),
+                "method": "initialize",
+                "params": {
+                    "protocolVersion": "2024-11-05",
+                    "capabilities": {"tools": {}},
+                    "clientInfo": {"name": "MemoryBear", "version": "1.0.0"}
+                }
+            }
+            
+            init_response = await self._send_sse_request(init_request)
+            if "error" in init_response:
+                raise MCPConnectionError(f"初始化失败: {init_response['error']}")
+            
+            result = init_response.get("result", {})
+            self._server_capabilities = result.get("capabilities", {})
+            
+            # 发送 initialized 通知
+            await self._send_sse_notification({"jsonrpc": "2.0", "method": "notifications/initialized"})
+                    
+        except aiohttp.ClientError as e:
+            raise MCPConnectionError(f"初始化连接失败: {e}")
+    
+    async def _read_sse_stream(self, response):
+        """读取 SSE 流"""
+        try:
+            async for line in response.content:
+                line = line.decode('utf-8').strip()
+                
+                if line.startswith('event:'):
+                    continue
+                
+                if line.startswith('data:'):
+                    data = line[5:].strip()  # 去除 'data:' 后的空格
+                    if not data or data == '[DONE]':
+                        continue
+                    
+                    try:
+                        # 处理 endpoint 事件（相对路径或绝对路径）
+                        if not self._endpoint_url:
+                            # 如果是相对路径，拼接成完整 URL
+                            if data.startswith('/'):
+                                from urllib.parse import urlparse, urlunparse
+                                parsed = urlparse(self.server_url)
+                                self._endpoint_url = f"{parsed.scheme}://{parsed.netloc}{data}"
+                            else:
+                                self._endpoint_url = data
+                            logger.info(f"获取到 endpoint URL: {self._endpoint_url}")
+                            continue
+                        
+                        # 处理 message 事件
+                        message = json.loads(data)
+                        request_id = message.get("id")
+                        if request_id and request_id in self._pending_requests:
+                            future = self._pending_requests.pop(request_id)
+                            if not future.done():
+                                future.set_result(message)
+                    except json.JSONDecodeError:
+                        continue
+        except Exception as e:
+            logger.error(f"SSE 流读取错误: {e}")
+    
+    async def _send_sse_request(self, request: Dict[str, Any]) -> Dict[str, Any]:
+        """通过 SSE endpoint 发送请求"""
+        if not self._endpoint_url:
+            raise MCPConnectionError("endpoint URL 未初始化")
+        
+        request_id = request["id"]
+        future = asyncio.Future()
+        self._pending_requests[request_id] = future
+        
+        try:
+            async with self._session.post(self._endpoint_url, json=request) as response:
+                if response.status != 200:
+                    error_text = await response.text()
+                    raise MCPConnectionError(f"请求失败 {response.status}: {error_text}")
+            
+            return await asyncio.wait_for(future, timeout=self.timeout)
+        except asyncio.TimeoutError:
+            self._pending_requests.pop(request_id, None)
+            raise MCPConnectionError("请求超时")
+    
+    async def _send_sse_notification(self, notification: Dict[str, Any]):
+        """发送通知（无需响应）"""
+        if not self._endpoint_url:
+            raise MCPConnectionError("endpoint URL 未初始化")
+        
+        async with self._session.post(self._endpoint_url, json=notification) as response:
+            if response.status != 200:
+                logger.warning(f"通知发送失败: {response.status}")
+    
     async def _initialize_modelscope_session(self):
         """初始化 ModelScope MCP 会话"""
         init_request = {
@@ -107,18 +219,12 @@ class SimpleMCPClient:
             "params": {
                 "protocolVersion": "2024-11-05",
                 "capabilities": {"tools": {}},
-                "clientInfo": {
-                    "name": "MemoryBear",
-                    "version": "1.0.0"
-                }
+                "clientInfo": {"name": "MemoryBear", "version": "1.0.0"}
             }
         }
         
         try:
-            async with self._session.post(
-                self.server_url,
-                json=init_request
-            ) as response:
+            async with self._session.post(self.server_url, json=init_request) as response:
                 if response.status != 200:
                     error_text = await response.text()
                     raise MCPConnectionError(f"初始化失败 {response.status}: {error_text}")
@@ -127,21 +233,16 @@ class SimpleMCPClient:
                 if "error" in init_response:
                     raise MCPConnectionError(f"初始化失败: {init_response['error']}")
                 
-                # 获取 session ID
                 session_id = response.headers.get("Mcp-Session-Id") or response.headers.get("mcp-session-id")
                 if session_id:
                     self._session.headers.update({"Mcp-Session-Id": session_id})
                     
-                    # 发送 initialized 通知
                     initialized_notification = {
                         "jsonrpc": "2.0",
                         "method": "notifications/initialized"
                     }
                     
-                    async with self._session.post(
-                        self.server_url,
-                        json=initialized_notification
-                    ) as notif_response:
+                    async with self._session.post(self.server_url, json=initialized_notification):
                         pass
                     
         except aiohttp.ClientError as e:
@@ -149,12 +250,18 @@ class SimpleMCPClient:
     
     def _build_headers(self) -> Dict[str, str]:
         """构建请求头"""
+        # 基础 headers
         headers = {
             "Content-Type": "application/json",
             "Accept": "application/json, text/event-stream"
         }
         
-        # 添加认证头
+        # 合并 connection_config 中的自定义 headers
+        custom_headers = self.connection_config.get("headers", {})
+        if custom_headers:
+            headers.update(custom_headers)
+        
+        # 处理认证配置（认证 headers 优先级更高）
         auth_config = self.connection_config.get("auth_config", {})
         auth_type = self.connection_config.get("auth_type", "none")
         
@@ -178,7 +285,7 @@ class SimpleMCPClient:
         return headers
     
     async def _send_initialize(self):
-        """发送初始化消息"""
+        """发送初始化消息（WebSocket）"""
         init_message = {
             "jsonrpc": "2.0",
             "id": self._get_request_id(),
@@ -186,124 +293,90 @@ class SimpleMCPClient:
             "params": {
                 "protocolVersion": "2024-11-05",
                 "capabilities": {"tools": {}},
-                "clientInfo": {
-                    "name": "MemoryBear",
-                    "version": "1.0.0"
-                }
+                "clientInfo": {"name": "MemoryBear", "version": "1.0.0"}
             }
         }
         
         await self._websocket.send(json.dumps(init_message))
+        response = await self._websocket.recv()
+        response_data = json.loads(response)
         
-        # 等待初始化响应
-        response = await asyncio.wait_for(
-            self._websocket.recv(),
-            timeout=self.timeout
-        )
+        if "error" in response_data:
+            raise MCPConnectionError(f"初始化失败: {response_data['error']}")
         
-        init_response = json.loads(response)
-        if "error" in init_response:
-            raise MCPConnectionError(f"初始化失败: {init_response['error']}")
+        result = response_data.get("result", {})
+        self._server_capabilities = result.get("capabilities", {})
+        
+        await self._websocket.send(json.dumps({
+            "jsonrpc": "2.0",
+            "method": "notifications/initialized"
+        }))
+    
+    async def list_tools(self) -> List[Dict[str, Any]]:
+        """获取工具列表"""
+        request = {
+            "jsonrpc": "2.0",
+            "id": self._get_request_id(),
+            "method": "tools/list"
+        }
+        
+        if self.is_websocket:
+            await self._websocket.send(json.dumps(request))
+            response = await self._websocket.recv()
+            response_data = json.loads(response)
+        elif self.is_sse:
+            response_data = await self._send_sse_request(request)
+        else:
+            async with self._session.post(self.server_url, json=request) as response:
+                response_data = await response.json()
+        
+        if "error" in response_data:
+            raise MCPConnectionError(f"获取工具列表失败: {response_data['error']}")
+        
+        result = response_data.get("result", {})
+        return result.get("tools", [])
+    
+    async def call_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Any:
+        """调用工具"""
+        request = {
+            "jsonrpc": "2.0",
+            "id": self._get_request_id(),
+            "method": "tools/call",
+            "params": {"name": tool_name, "arguments": arguments}
+        }
+        
+        if self.is_websocket:
+            await self._websocket.send(json.dumps(request))
+            response = await self._websocket.recv()
+            response_data = json.loads(response)
+        elif self.is_sse:
+            response_data = await self._send_sse_request(request)
+        else:
+            async with self._session.post(self.server_url, json=request) as response:
+                response_data = await response.json()
+        
+        if "error" in response_data:
+            error = response_data["error"]
+            raise MCPConnectionError(f"工具调用失败: {error.get('message', '未知错误')}")
+        
+        return response_data.get("result", {})
+    
+    def _get_request_id(self) -> int:
+        """生成请求 ID"""
+        self._request_id += 1
+        return self._request_id
     
     async def _handle_websocket_messages(self):
         """处理 WebSocket 消息"""
         try:
-            while self._websocket and not self._websocket.closed:
-                try:
-                    message = await self._websocket.recv()
-                    data = json.loads(message)
-                    
-                    # 处理响应
-                    if "id" in data:
-                        request_id = str(data["id"])
-                        if request_id in self._pending_requests:
-                            future = self._pending_requests.pop(request_id)
-                            if not future.done():
-                                future.set_result(data)
-                    
-                except ConnectionClosed:
-                    break
-                except Exception as e:
-                    logger.error(f"处理WebSocket消息失败: {e}")
-                    
+            async for message in self._websocket:
+                data = json.loads(message)
+                request_id = data.get("id")
+                if request_id and request_id in self._pending_requests:
+                    future = self._pending_requests.pop(request_id)
+                    if not future.done():
+                        future.set_result(data)
+        except ConnectionClosed:
+            logger.info("WebSocket 连接已关闭")
         except Exception as e:
-            logger.error(f"WebSocket消息处理异常: {e}")
-    
-    async def call_tool(self, tool_name: str, arguments: Dict[str, Any]) -> Any:
-        """调用工具"""
-        request_data = {
-            "jsonrpc": "2.0",
-            "id": self._get_request_id(),
-            "method": "tools/call",
-            "params": {
-                "name": tool_name,
-                "arguments": arguments
-            }
-        }
-        
-        if self.is_websocket:
-            response = await self._send_websocket_request(request_data)
-        else:
-            response = await self._send_http_request(request_data)
-        
-        if "error" in response:
-            error = response["error"]
-            raise MCPConnectionError(f"工具调用失败: {error.get('message', '未知错误')}")
-        
-        return response.get("result", {})
-    
-    async def list_tools(self) -> List[Dict[str, Any]]:
-        """获取工具列表"""
-        request_data = {
-            "jsonrpc": "2.0",
-            "id": self._get_request_id(),
-            "method": "tools/list",
-            "params": {}
-        }
-        
-        if self.is_websocket:
-            response = await self._send_websocket_request(request_data)
-        else:
-            response = await self._send_http_request(request_data)
-        
-        if "error" in response:
-            error = response["error"]
-            raise MCPConnectionError(f"获取工具列表失败: {error.get('message', '未知错误')}")
-        
-        result = response.get("result", {})
-        return result.get("tools", [])
-    
-    async def _send_websocket_request(self, request_data: Dict[str, Any]) -> Dict[str, Any]:
-        """发送WebSocket请求"""
-        request_id = str(request_data["id"])
-        future = asyncio.Future()
-        self._pending_requests[request_id] = future
-        
-        try:
-            await self._websocket.send(json.dumps(request_data))
-            response = await asyncio.wait_for(future, timeout=self.timeout)
-            return response
-        except asyncio.TimeoutError:
-            self._pending_requests.pop(request_id, None)
-            raise
-    
-    async def _send_http_request(self, request_data: Dict[str, Any]) -> Dict[str, Any]:
-        """发送HTTP请求"""
-        try:
-            async with self._session.post(
-                self.server_url,
-                json=request_data
-            ) as response:
-                if response.status != 200:
-                    error_text = await response.text()
-                    raise MCPConnectionError(f"HTTP请求失败 {response.status}: {error_text}")
-                
-                return await response.json()
-                
-        except aiohttp.ClientError as e:
-            raise MCPConnectionError(f"HTTP请求失败: {e}")
-    
-    def _get_request_id(self) -> str:
-        """获取请求ID"""
-        self._request_id += 1
-        return f"req_{self._request_id}_{int(time.time() * 1000)}"
+            logger.error(f"WebSocket 消息处理错误: {e}")

api/app/core/workflow/executor.py

@@ -74,6 +74,7 @@ class WorkflowExecutor:
             初始化的工作流状态
         """
         user_message = input_data.get("message") or ""
+        conversation_messages = input_data.get("conv_messages") or []
 
         # 会话变量处理：从配置文件获取变量定义列表，转换为字典（name -> default value）
         config_variables_list = self.workflow_config.get("variables") or []
@@ -114,7 +115,7 @@ class WorkflowExecutor:
         }
 
         return {
-            "messages": [('user', user_message)],
+            "messages": conversation_messages,
             "variables": variables,
             "node_outputs": {},
             "runtime_vars": {},  # 运行时节点变量（简化版，供快速访问）

api/app/core/workflow/nodes/base_node.py

@@ -7,13 +7,13 @@
 import asyncio
 import logging
 from abc import ABC, abstractmethod
-from operator import add
 from typing import Any
 
-from langchain_core.messages import AnyMessage, AIMessage
+from langchain_core.messages import AIMessage
 from langgraph.config import get_stream_writer
 from typing_extensions import TypedDict, Annotated
 
+from app.core.config import settings
 from app.core.workflow.variable_pool import VariablePool
 
 logger = logging.getLogger(__name__)
@@ -25,7 +25,7 @@ class WorkflowState(TypedDict):
     The state object passed between nodes in a workflow, containing messages, variables, node outputs, etc.
     """
     # List of messages (append mode)
-    messages: Annotated[list[tuple[str, str]], add]
+    messages: list[dict[str, str]]
 
     # Set of loop node IDs, used for assigning values in loop nodes
     cycle_nodes: list
@@ -154,7 +154,7 @@ class BaseNode(ABC):
         Returns:
             超时时间
         """
-        return 60
+        return settings.WORKFLOW_NODE_TIMEOUT
         # return self.error_handling.get("timeout", 60)
 
     async def run(self, state: WorkflowState) -> dict[str, Any]:
@@ -203,6 +203,7 @@ class BaseNode(ABC):
             # 返回包装后的输出和运行时变量
             return {
                 **wrapped_output,
+                "messages": state["messages"],
                 "variables": state["variables"],
                 "runtime_vars": {
                     self.node_id: runtime_var
@@ -356,6 +357,7 @@ class BaseNode(ABC):
             # Build complete state update (including node_outputs, runtime_vars, and final streaming buffer)
             state_update = {
                 **final_output,
+                "messages": state["messages"],
                 "variables": state["variables"],
                 "runtime_vars": {
                     self.node_id: runtime_var

api/app/core/workflow/nodes/end/node.py

@@ -6,7 +6,6 @@ End 节点实现
 
 import logging
 import re
-import asyncio
 
 from app.core.workflow.nodes.base_node import BaseNode, WorkflowState
 from app.core.workflow.nodes.enums import NodeType
@@ -38,7 +37,23 @@ class EndNode(BaseNode):
         # 如果配置了输出模板，使用模板渲染；否则使用默认输出
         if output_template:
             output = self._render_template(output_template, state, strict=False)
+            state['messages'].extend([
+                {
+                    "role": "user",
+                    "content": self.get_variable("sys.message", state)
+                },
+                {
+                    "role": "assistant",
+                    "content": output
+                }
+            ])
         else:
+            state['messages'].extend([
+                {
+                    "role": "user",
+                    "content": self.get_variable("sys.message", state)
+                },
+            ])
             output = "工作流已完成"
 
         # 统计信息（用于日志）
@@ -166,6 +181,12 @@ class EndNode(BaseNode):
                 "chunk_index": 1,
                 "is_suffix": False
             })
+            state['messages'].extend([
+                {
+                    "role": "user",
+                    "content": self.get_variable("sys.message", state)
+                }
+            ])
             yield {"__final__": True, "result": output}
             return
 
@@ -176,7 +197,6 @@ class EndNode(BaseNode):
                 source_node_id = edge.get("source")
                 # Check if the source node is an LLM node
                 for node in self.workflow_config.get("nodes", []):
-                    print("="*50)
                     logger.info(f"节点 {self.node_id} 的类型 {node.get("type")}")
                     if node.get("id") == source_node_id and node.get("type") == NodeType.LLM:
                         direct_upstream_llm_nodes.append(source_node_id)
@@ -216,12 +236,24 @@ class EndNode(BaseNode):
             })
             logger.info(f"节点 {self.node_id} 已通过 writer 发送完整内容")
 
+            state['messages'].extend([
+                {
+                    "role": "user",
+                    "content": self.get_variable("sys.message", state)
+                },
+                {
+                    "role": "assistant",
+                    "content": output
+                }
+            ])
+
             # yield completion marker
             yield {"__final__": True, "result": output}
             return
 
         # Has reference to direct upstream LLM node, only output the part after that reference (suffix)
-        logger.info(f"节点 {self.node_id} 检测到直接上游 LLM 节点引用，只输出后缀部分（从索引 {upstream_llm_ref_index + 1} 开始）")
+        logger.info(
+            f"节点 {self.node_id} 检测到直接上游 LLM 节点引用，只输出后缀部分（从索引 {upstream_llm_ref_index + 1} 开始）")
 
         # Collect suffix parts
         suffix_parts = []
@@ -258,6 +290,17 @@ class EndNode(BaseNode):
         # 构建完整输出（用于返回，包含前缀 + 动态内容 + 后缀）
         full_output = self._render_template(output_template, state, strict=False)
 
+        state['messages'].extend([
+            {
+                "role": "user",
+                "content": self.get_variable("sys.message", state)
+            },
+            {
+                "role": "assistant",
+                "content": full_output
+            }
+        ])
+
         logger.info(f"[后缀调试] 节点 {self.node_id} 后缀部分数量: {len(suffix_parts)}")
         logger.info(f"[后缀调试] 后缀内容: '{suffix}'")
         logger.info(f"[后缀调试] 后缀长度: {len(suffix)}")
@@ -280,7 +323,8 @@ class EndNode(BaseNode):
             })
             logger.info(f"节点 {self.node_id} 已通过 writer 发送后缀，full_content 长度: {len(full_output)}")
         else:
-            logger.warning(f"[后缀调试] 节点 {self.node_id} 后缀为空，不发送！upstream_llm_ref_index={upstream_llm_ref_index}, parts数量={len(parts)}")
+            logger.warning(f"[后缀调试] 节点 {self.node_id} 后缀为空，不发送！"
+                           f"upstream_llm_ref_index={upstream_llm_ref_index}, parts数量={len(parts)}")
 
         # 统计信息
         node_outputs = state.get("node_outputs", {})

api/app/core/workflow/nodes/llm/config.py

@@ -11,12 +11,12 @@ class MessageConfig(BaseModel):
     """消息配置"""
 
     role: str = Field(
-        ...,
+        default='user',
         description="消息角色：system, user, assistant"
     )
 
     content: str = Field(
-        ...,
+        default="",
         description="消息内容，支持模板变量，如：{{ sys.message }}"
     )
 
@@ -30,6 +30,23 @@ class MessageConfig(BaseModel):
         return v.lower()
 
 
+class MemoryWindowSetting(BaseModel):
+    enable: bool = Field(
+        default=False,
+        description="启用记忆"
+    )
+
+    enable_window: bool = Field(
+        default=False,
+        description="启用记忆窗口"
+    )
+
+    window_size: int = Field(
+        default=20,
+        description="记忆窗口大小"
+    )
+
+
 class LLMNodeConfig(BaseNodeConfig):
     """LLM 节点配置
     
@@ -48,6 +65,11 @@ class LLMNodeConfig(BaseNodeConfig):
         description="上下文"
     )
 
+    memory: MemoryWindowSetting = Field(
+        ...,
+        description="对话上下文窗口"
+    )
+
     # 简单模式
     prompt: str | None = Field(
         default=None,

api/app/core/workflow/nodes/llm/node.py

@@ -85,28 +85,31 @@ class LLMNode(BaseNode):
         """
 
         # 1. 处理消息格式（优先使用 messages）
-        messages_config = self.config.get("messages")
+        messages_config = self.typed_config.messages
 
         if messages_config:
             # 使用 LangChain 消息格式
             messages = []
             for msg_config in messages_config:
-                role = msg_config.get("role", "user").lower()
-                content_template = msg_config.get("content", "")
+                role = msg_config.role.lower()
+                content_template = msg_config.content
                 content_template = self._render_context(content_template, state)
                 content = self._render_template(content_template, state)
 
                 # 根据角色创建对应的消息对象
                 if role == "system":
-                    messages.append(SystemMessage(content=content))
+                    messages.append({"role": "system", "content": content})
                 elif role in ["user", "human"]:
-                    messages.append(HumanMessage(content=content))
+                    messages.append({"role": "user", "content": content})
                 elif role in ["ai", "assistant"]:
-                    messages.append(AIMessage(content=content))
+                    messages.append({"role": "assistant", "content": content})
                 else:
                     logger.warning(f"未知的消息角色: {role}，默认使用 user")
-                    messages.append(HumanMessage(content=content))
+                    messages.append({"role": "user", "content": content})
 
+            if self.typed_config.memory.enable:
+                # if self.typed_config.memory.enable_window:
+                messages = messages[:-1] + state["messages"][-self.typed_config.memory.window_size:] + messages[-1:]
             prompt_or_messages = messages
         else:
             # 使用简单的 prompt 格式（向后兼容）
@@ -189,7 +192,7 @@ class LLMNode(BaseNode):
         return {
             "prompt": prompt_or_messages if isinstance(prompt_or_messages, str) else None,
             "messages": [
-                {"role": msg.__class__.__name__.replace("Message", "").lower(), "content": msg.content}
+                {"role": msg.get("role"), "content": msg.get("content", "")}
                 for msg in prompt_or_messages
             ] if isinstance(prompt_or_messages, list) else None,
             "config": {

api/app/core/workflow/nodes/memory/node.py

@@ -3,8 +3,9 @@ from typing import Any
 from app.core.workflow.nodes import WorkflowState
 from app.core.workflow.nodes.base_node import BaseNode
 from app.core.workflow.nodes.memory.config import MemoryReadNodeConfig, MemoryWriteNodeConfig
-from app.db import get_db_read, get_db_context
+from app.db import get_db_read
 from app.services.memory_agent_service import MemoryAgentService
+from app.tasks import write_message_task
 
 
 class MemoryReadNode(BaseNode):
@@ -15,11 +16,8 @@ class MemoryReadNode(BaseNode):
     async def execute(self, state: WorkflowState) -> Any:
         self.typed_config = MemoryReadNodeConfig(**self.config)
         with get_db_read() as db:
-            workspace_id = self.get_variable('sys.workspace_id', state)
             end_user_id = self.get_variable("sys.user_id", state)
 
-            if not workspace_id:
-                raise RuntimeError("Workspace id is required")
             if not end_user_id:
                 raise RuntimeError("End user id is required")
 
@@ -41,20 +39,17 @@ class MemoryWriteNode(BaseNode):
         self.typed_config = MemoryWriteNodeConfig(**self.config)
 
     async def execute(self, state: WorkflowState) -> Any:
-        with get_db_context() as db:
-            workspace_id = self.get_variable('sys.workspace_id', state)
-            end_user_id = self.get_variable("sys.user_id", state)
+        end_user_id = self.get_variable("sys.user_id", state)
 
-            if not workspace_id:
-                raise RuntimeError("Workspace id is required")
-            if not end_user_id:
-                raise RuntimeError("End user id is required")
+        if not end_user_id:
+            raise RuntimeError("End user id is required")
 
-            return await MemoryAgentService().write_memory(
-                group_id=end_user_id,
-                message=self._render_template(self.typed_config.message, state),
-                config_id=str(self.typed_config.config_id),
-                db=db,
-                storage_type="neo4j",
-                user_rag_memory_id=""
-            )
+        write_message_task.delay(
+            end_user_id,
+            self._render_template(self.typed_config.message, state),
+            str(self.typed_config.config_id),
+            "neo4j",
+            ""
+        )
+
+        return "success"

api/app/schemas/app_schema.py

@@ -41,6 +41,7 @@ class ToolConfig(BaseModel):
     tool_id: Optional[str] = Field(default=None, description="工具ID")
     operation: Optional[str] = Field(default=None, description="工具特定配置")
 
+
 class ToolOldConfig(BaseModel):
     """工具配置"""
     enabled: bool = Field(default=False, description="是否启用该工具")
@@ -348,6 +349,7 @@ class AppChatRequest(BaseModel):
     variables: Optional[Dict[str, Any]] = Field(default=None, description="自定义变量参数值")
     stream: bool = Field(default=False, description="是否流式返回")
 
+
 class DraftRunRequest(BaseModel):
     """试运行请求"""
     message: str = Field(..., description="用户消息")

api/app/services/app_chat_service.py

@@ -14,6 +14,7 @@ from app.core.exceptions import BusinessException
 from app.core.logging_config import get_business_logger
 from app.db import get_db, get_db_context
 from app.models import MultiAgentConfig, AgentConfig, WorkflowConfig
+from app.schemas import DraftRunRequest
 from app.services.tool_service import ToolService
 from app.repositories.tool_repository import ToolRepository
 from app.db import get_db
@@ -59,7 +60,7 @@ class AppChatService:
 
         # 获取模型配置ID
         model_config_id = config.default_model_config_id
-        api_key_obj = ModelApiKeyService.get_a_api_key(self.db ,model_config_id)
+        api_key_obj = ModelApiKeyService.get_a_api_key(self.db, model_config_id)
         # 处理系统提示词（支持变量替换）
         system_prompt = config.system_prompt
         if variables:
@@ -210,7 +211,7 @@ class AppChatService:
 
             # 获取模型配置ID
             model_config_id = config.default_model_config_id
-            api_key_obj = ModelApiKeyService.get_a_api_key(self.db ,model_config_id)
+            api_key_obj = ModelApiKeyService.get_a_api_key(self.db, model_config_id)
             # 处理系统提示词（支持变量替换）
             system_prompt = config.system_prompt
             if variables:
@@ -511,7 +512,6 @@ class AppChatService:
                 }
             )
 
-
         except (GeneratorExit, asyncio.CancelledError):
             # 生成器被关闭或任务被取消，正常退出
             logger.debug("多 Agent 流式聊天被中断")
@@ -537,83 +537,19 @@ class AppChatService:
     ) -> Dict[str, Any]:
         """聊天（非流式）"""
         workflow_service = WorkflowService(self.db)
-
-        input_data = {"message":message, "variables": variables,
-                      "conversation_id": str(conversation_id)}
-        inconfig = workflow_service.get_workflow_config(app_id)
-
-        # 2. 创建执行记录
-        execution = workflow_service.create_execution(
-            workflow_config_id=inconfig.id,
-            app_id=app_id,
-            trigger_type="manual",
-            triggered_by=None,
-            conversation_id=conversation_id,
-            input_data=input_data
+        payload = DraftRunRequest(
+            message=message,
+            variables=variables,
+            conversation_id=str(conversation_id),
+            stream=True,
+            user_id=user_id
+        )
+        return await workflow_service.run(
+            app_id=app_id,
+            payload=payload,
+            config=config,
+            workspace_id=workspace_id,
         )
-
-        # 3. 构建工作流配置字典
-        workflow_config_dict = {
-            "nodes": config.nodes,
-            "edges": config.edges,
-            "variables": config.variables,
-            "execution_config": config.execution_config
-        }
-
-        # 4. 获取工作空间 ID（从 app 获取）
-
-        # 5. 执行工作流
-        from app.core.workflow.executor import execute_workflow
-
-        try:
-            # 更新状态为运行中
-            workflow_service.update_execution_status(execution.execution_id, "running")
-
-            result = await execute_workflow(
-                workflow_config=workflow_config_dict,
-                input_data=input_data,
-                execution_id=execution.execution_id,
-                workspace_id=str(workspace_id),
-                user_id=user_id
-            )
-
-            # 更新执行结果
-            if result.get("status") == "completed":
-                workflow_service.update_execution_status(
-                    execution.execution_id,
-                    "completed",
-                    output_data=result.get("node_outputs", {})
-                )
-            else:
-                workflow_service.update_execution_status(
-                    execution.execution_id,
-                    "failed",
-                    error_message=result.get("error")
-                )
-
-            # 返回增强的响应结构
-            return {
-                "execution_id": execution.execution_id,
-                "status": result.get("status"),
-                "output": result.get("output"),  # 最终输出（字符串）
-                "output_data": result.get("node_outputs", {}),  # 所有节点输出（详细数据）
-                "conversation_id": result.get("conversation_id"),  # 所有节点输出（详细数据）payload.,  # 会话 ID
-                "error_message": result.get("error"),
-                "elapsed_time": result.get("elapsed_time"),
-                "token_usage": result.get("token_usage")
-            }
-
-        except Exception as e:
-            logger.error(f"工作流执行失败: execution_id={execution.execution_id}, error={e}", exc_info=True)
-            workflow_service.update_execution_status(
-                execution.execution_id,
-                "failed",
-                error_message=str(e)
-            )
-            raise BusinessException(
-                code=BizCode.INTERNAL_ERROR,
-                message=f"工作流执行失败: {str(e)}"
-            )
 
     async def workflow_chat_stream(
             self,
@@ -632,62 +568,21 @@ class AppChatService:
     ) -> AsyncGenerator[str, None]:
         """聊天（流式）"""
         workflow_service = WorkflowService(self.db)
-        input_data = {"message": message, "variables": variables,
-                      "conversation_id": str(conversation_id)}
-        inconfig = workflow_service.get_workflow_config(app_id)
-        # 2. 创建执行记录
-        execution = workflow_service.create_execution(
-            workflow_config_id=inconfig.id,
-            app_id=app_id,
-            trigger_type="manual",
-            triggered_by=None,
-            conversation_id=conversation_id,
-            input_data=input_data
+        payload = DraftRunRequest(
+            message=message,
+            variables=variables,
+            conversation_id=str(conversation_id),
+            stream=True,
+            user_id=user_id
         )
+        async for event in workflow_service.run_stream(
+                app_id=app_id,
+                payload=payload,
+                config=config,
+                workspace_id=workspace_id,
+        ):
+            yield event
 
-        # 3. 构建工作流配置字典
-        workflow_config_dict = {
-            "nodes": config.nodes,
-            "edges": config.edges,
-            "variables": config.variables,
-            "execution_config": config.execution_config
-        }
-
-        # 4. 获取工作空间 ID（从 app 获取）
-
-        # 5. 流式执行工作流
-
-        try:
-            # 更新状态为运行中
-            workflow_service.update_execution_status(execution.execution_id, "running")
-
-
-            # 调用流式执行（executor 会发送 workflow_start 和 workflow_end 事件）
-            async for event in workflow_service._run_workflow_stream(
-                    workflow_config=workflow_config_dict,
-                    input_data=input_data,
-                    execution_id=execution.execution_id,
-                    workspace_id=str(workspace_id),
-                    user_id=user_id
-            ):
-                # 直接转发 executor 的事件（已经是正确的格式）
-                yield event
-
-        except Exception as e:
-            logger.error(f"工作流流式执行失败: execution_id={execution.execution_id}, error={e}", exc_info=True)
-            workflow_service.update_execution_status(
-                execution.execution_id,
-                "failed",
-                error_message=str(e)
-            )
-            # 发送错误事件
-            yield {
-                "event": "error",
-                "data": {
-                    "execution_id": execution.execution_id,
-                    "error": str(e)
-                }
-            }
 
 # ==================== 依赖注入函数 ====================
 

api/app/services/user_memory_service.py

@@ -13,12 +13,14 @@ from typing import Any, Dict, List, Optional, Tuple
 from app.core.logging_config import get_logger
 from app.core.memory.utils.llm.llm_utils import MemoryClientFactory
 from app.db import get_db_context
+from app.repositories.conversation_repository import ConversationRepository
 from app.repositories.end_user_repository import EndUserRepository
 from app.repositories.neo4j.neo4j_connector import Neo4jConnector
-from app.schemas.memory_episodic_schema import type_mapping, EmotionType, EmotionSubject
-
+from app.services.implicit_memory_service import ImplicitMemoryService
 from app.services.memory_base_service import MemoryBaseService
 from app.services.memory_config_service import MemoryConfigService
+from app.services.memory_perceptual_service import MemoryPerceptualService
+from app.services.memory_short_service import ShortService
 from pydantic import BaseModel, Field
 from sqlalchemy.orm import Session
 
@@ -1198,18 +1200,17 @@ async def analytics_memory_types(
     end_user_id: Optional[str] = None
 ) -> List[Dict[str, Any]]:
     """
-    统计9种记忆类型的数量和百分比
+    统计8种记忆类型的数量和百分比
     
     计算规则：
-    1. 感知记忆 (PERCEPTUAL_MEMORY) = statement + entity
-    2. 工作记忆 (WORKING_MEMORY) = chunk + entity
-    3. 短期记忆 (SHORT_TERM_MEMORY) = chunk
-    4. 长期记忆 (LONG_TERM_MEMORY) = entity
-    5. 显性记忆 (EXPLICIT_MEMORY) = 情景记忆 + 语义记忆（通过 MemoryBaseService.get_explicit_memory_count 获取）
-    6. 隐性记忆 (IMPLICIT_MEMORY) = 1/3 * entity
-    7. 情绪记忆 (EMOTIONAL_MEMORY) = 情绪标签统计总数（通过 MemoryBaseService.get_emotional_memory_count 获取）
-    8. 情景记忆 (EPISODIC_MEMORY) = memory_summary（通过 MemoryBaseService.get_episodic_memory_count 获取）
-    9. 遗忘记忆 (FORGET_MEMORY) = 激活值低于阈值的节点数（通过 MemoryBaseService.get_forget_memory_count 获取）
+    1. 感知记忆 (PERCEPTUAL_MEMORY) = 通过 MemoryPerceptualService.get_memory_count 获取的 total_count
+    2. 工作记忆 (WORKING_MEMORY) = 会话数量（通过 ConversationRepository.get_conversation_by_user_id 获取）
+    3. 短期记忆 (SHORT_TERM_MEMORY) = /short_term 接口返回的问答对数量
+    4. 显性记忆 (EXPLICIT_MEMORY) = 情景记忆 + 语义记忆（通过 MemoryBaseService.get_explicit_memory_count 获取）
+    5. 隐性记忆 (IMPLICIT_MEMORY) = Statement 节点数量的三分之一
+    6. 情绪记忆 (EMOTIONAL_MEMORY) = 情绪标签统计总数（通过 MemoryBaseService.get_emotional_memory_count 获取）
+    7. 情景记忆 (EPISODIC_MEMORY) = memory_summary（通过 MemoryBaseService.get_episodic_memory_count 获取）
+    8. 遗忘记忆 (FORGET_MEMORY) = 激活值低于阈值的节点数（通过 MemoryBaseService.get_forget_memory_count 获取）
     
     Args:
         db: 数据库会话
@@ -1229,7 +1230,6 @@ async def analytics_memory_types(
         - PERCEPTUAL_MEMORY: 感知记忆
         - WORKING_MEMORY: 工作记忆
         - SHORT_TERM_MEMORY: 短期记忆
-        - LONG_TERM_MEMORY: 长期记忆
         - EXPLICIT_MEMORY: 显性记忆
         - IMPLICIT_MEMORY: 隐性记忆
         - EMOTIONAL_MEMORY: 情绪记忆
@@ -1239,40 +1239,78 @@ async def analytics_memory_types(
     # 初始化基础服务
     base_service = MemoryBaseService()
     
-    # 定义需要查询的基础节点类型
-    node_types = {
-        "Statement": "Statement",
-        "Entity": "ExtractedEntity",
-        "Chunk": "Chunk"
-    }
+    # 初始化感知记忆服务
+    perceptual_service = MemoryPerceptualService(db)
     
-    # 存储每种节点类型的计数
-    node_counts = {}
+    # 获取感知记忆数量
+    if end_user_id:
+        perceptual_stats = perceptual_service.get_memory_count(uuid.UUID(end_user_id))
+        perceptual_count = perceptual_stats.get("total", 0)
+    else:
+        perceptual_count = 0
     
-    # 查询每种节点类型的数量
-    for key, node_type in node_types.items():
-        if end_user_id:
-            query = f"""
-            MATCH (n:{node_type})
+    # 获取工作记忆数量（基于会话数量）
+    work_count = 0
+    if end_user_id:
+        try:
+            conversation_repo = ConversationRepository(db)
+            conversations = conversation_repo.get_conversation_by_user_id(
+                user_id=uuid.UUID(end_user_id),
+                limit=100,  # 获取更多会话以准确统计
+                is_activate=True
+            )
+            work_count = len(conversations)
+            logger.debug(f"工作记忆数量（会话数）: {work_count} (end_user_id={end_user_id})")
+        except Exception as e:
+            logger.warning(f"获取会话数量失败，工作记忆数量设为0: {str(e)}")
+            work_count = 0
+    
+    # 获取隐性记忆数量（基于 Statement 节点数量的三分之一）
+    implicit_count = 0
+    if end_user_id:
+        try:
+            # 查询 Statement 节点数量
+            query = """
+            MATCH (n:Statement)
             WHERE n.group_id = $group_id
             RETURN count(n) as count
             """
             result = await _neo4j_connector.execute_query(query, group_id=end_user_id)
-        else:
-            query = f"""
-            MATCH (n:{node_type})
-            RETURN count(n) as count
-            """
-            result = await _neo4j_connector.execute_query(query)
-        
-        # 提取计数结果
-        count = result[0]["count"] if result and len(result) > 0 else 0
-        node_counts[key] = count
+            statement_count = result[0]["count"] if result and len(result) > 0 else 0
+            # 取三分之一作为隐性记忆数量
+            implicit_count = round(statement_count / 3)
+            logger.debug(f"隐性记忆数量（Statement数量的1/3）: {implicit_count} (Statement总数={statement_count}, end_user_id={end_user_id})")
+        except Exception as e:
+            logger.warning(f"获取Statement数量失败，隐性记忆数量设为0: {str(e)}")
+            implicit_count = 0
     
-    # 获取各节点类型的数量
-    statement_count = node_counts.get("Statement", 0)
-    entity_count = node_counts.get("Entity", 0)
-    chunk_count = node_counts.get("Chunk", 0)
+    # 原有的基于行为习惯的统计方式（已注释）
+    # implicit_count = 0
+    # if end_user_id:
+    #     try:
+    #         implicit_service = ImplicitMemoryService(db, end_user_id)
+    #         behavior_habits = await implicit_service.get_behavior_habits(
+    #             user_id=end_user_id
+    #         )
+    #         implicit_count = len(behavior_habits)
+    #         logger.debug(f"隐性记忆数量（行为习惯数）: {implicit_count} (end_user_id={end_user_id})")
+    #     except Exception as e:
+    #         logger.warning(f"获取行为习惯数量失败，隐性记忆数量设为0: {str(e)}")
+    #         implicit_count = 0
+    
+    # 获取短期记忆数量（基于 /short_term 接口返回的问答对数量）
+    short_term_count = 0
+    if end_user_id:
+        try:
+            short_term_service = ShortService(end_user_id)
+            short_term_data = short_term_service.get_short_databasets()
+            # 统计 short_term 数组的长度
+            if short_term_data:
+                short_term_count = len(short_term_data)
+            logger.debug(f"短期记忆数量（问答对数）: {short_term_count} (end_user_id={end_user_id})")
+        except Exception as e:
+            logger.warning(f"获取短期记忆数量失败，短期记忆数量设为0: {str(e)}")
+            short_term_count = 0
     
     # 获取用户的遗忘阈值配置
     forgetting_threshold = 0.3  # 默认值
@@ -1298,17 +1336,16 @@ async def analytics_memory_types(
     # 使用 MemoryBaseService 的共享方法获取特殊记忆类型的数量
     episodic_count = await base_service.get_episodic_memory_count(end_user_id)
     explicit_count = await base_service.get_explicit_memory_count(end_user_id)
-    emotion_count = await base_service.get_emotional_memory_count(end_user_id, statement_count)
+    emotion_count = await base_service.get_emotional_memory_count(end_user_id, perceptual_count)
     forget_count = await base_service.get_forget_memory_count(end_user_id, forgetting_threshold)
     
-    # 按规则计算9种记忆类型的数量（使用英文枚举作为key）
+    # 按规则计算8种记忆类型的数量（使用英文枚举作为key）
     memory_counts = {
-        "PERCEPTUAL_MEMORY": statement_count + entity_count,      # 感知记忆
-        "WORKING_MEMORY": chunk_count + entity_count,             # 工作记忆
-        "SHORT_TERM_MEMORY": chunk_count,                         # 短期记忆
-        "LONG_TERM_MEMORY": entity_count,                         # 长期记忆
+        "PERCEPTUAL_MEMORY": perceptual_count,                    # 感知记忆
+        "WORKING_MEMORY": work_count,                             # 工作记忆（基于会话数量）
+        "SHORT_TERM_MEMORY": short_term_count,                    # 短期记忆（基于问答对数量）
         "EXPLICIT_MEMORY": explicit_count,                        # 显性记忆（情景记忆 + 语义记忆）
-        "IMPLICIT_MEMORY": entity_count // 3,                     # 隐性记忆 (1/3 entity)
+        "IMPLICIT_MEMORY": implicit_count,                        # 隐性记忆（Statement数量的1/3）
         "EMOTIONAL_MEMORY": emotion_count,                        # 情绪记忆（使用情绪标签统计）
         "EPISODIC_MEMORY": episodic_count,                        # 情景记忆
         "FORGET_MEMORY": forget_count                             # 遗忘记忆（激活值低于阈值）

api/app/services/workflow_service.py

@@ -2,12 +2,11 @@
 工作流服务层
 """
 import datetime
-import json
 import logging
 import uuid
-import datetime
 from typing import Any, Annotated, AsyncGenerator
 
+from deprecated import deprecated
 from fastapi import Depends
 from sqlalchemy.orm import Session
 
@@ -16,15 +15,16 @@ from app.core.exceptions import BusinessException
 from app.core.workflow.validator import validate_workflow_config
 from app.db import get_db, get_db_context
 from app.models.workflow_model import WorkflowConfig, WorkflowExecution
+from app.repositories.conversation_repository import MessageRepository
+from app.models.conversation_model import Message
 from app.repositories.end_user_repository import EndUserRepository
-from app.services.multi_agent_service import convert_uuids_to_str
 from app.repositories.workflow_repository import (
     WorkflowConfigRepository,
     WorkflowExecutionRepository,
     WorkflowNodeExecutionRepository
 )
 from app.schemas import DraftRunRequest
-from app.utils.sse_utils import format_sse_message
+from app.services.multi_agent_service import convert_uuids_to_str
 
 logger = logging.getLogger(__name__)
 
@@ -37,6 +37,7 @@ class WorkflowService:
         self.config_repo = WorkflowConfigRepository(db)
         self.execution_repo = WorkflowExecutionRepository(db)
         self.node_execution_repo = WorkflowNodeExecutionRepository(db)
+        self.message_repo = MessageRepository(db)
 
     # ==================== 配置管理 ====================
 
@@ -418,14 +419,13 @@ class WorkflowService:
         """运行工作流
 
         Args:
+            workspace_id:
+            config:
+            payload:
             app_id: 应用 ID
-            input_data: 输入数据（包含 message 和 variables）
-            triggered_by: 触发用户 ID
-            conversation_id: 会话 ID（可选）
-            stream: 是否流式返回
 
         Returns:
-            执行结果（非流式）或生成器（流式）
+            执行结果（非流式）
 
         Raises:
             BusinessException: 配置不存在或执行失败时抛出
@@ -438,7 +438,8 @@ class WorkflowService:
                 code=BizCode.CONFIG_MISSING,
                 message=f"工作流配置不存在: app_id={app_id}"
             )
-        input_data = {"message": payload.message, "variables": payload.variables, "conversation_id": payload.conversation_id}
+        input_data = {"message": payload.message, "variables": payload.variables,
+                      "conversation_id": payload.conversation_id}
 
         # 转换 user_id 为 UUID
         triggered_by_uuid = None
@@ -461,7 +462,7 @@ class WorkflowService:
             workflow_config_id=config.id,
             app_id=app_id,
             trigger_type="manual",
-            triggered_by=triggered_by_uuid,
+            triggered_by=None,
             conversation_id=conversation_id_uuid,
             input_data=input_data
         )
@@ -500,8 +501,11 @@ class WorkflowService:
                         variables = last_state.get("variables", {})
                         conv_vars = variables.get("conv", {})
                         input_data["conv"] = conv_vars
+                        input_data["conv_messages"] = last_state.get("messages") or []
                         break
 
+            init_message_length = len(input_data.get("conv_messages", []))
+
             result = await execute_workflow(
                 workflow_config=workflow_config_dict,
                 input_data=input_data,
@@ -517,6 +521,17 @@ class WorkflowService:
                     "completed",
                     output_data=result
                 )
+                final_messages = result.get("messages", [])[init_message_length:]
+                for message in final_messages:
+                    message_obj = Message(
+                        conversation_id=conversation_id_uuid,
+                        role=message["role"],
+                        content=message["content"],
+                    )
+                    self.message_repo.add_message(message_obj)
+                self.db.commit()
+                logger.info(f"Workflow Run Success, "
+                            f"execution_id: {execution.execution_id}, message count: {len(final_messages)}")
             else:
                 self.update_execution_status(
                     execution.execution_id,
@@ -529,6 +544,7 @@ class WorkflowService:
                 "execution_id": execution.execution_id,
                 "status": result.get("status"),
                 "variables": result.get("variables"),
+                "messages": result.get("messages"),
                 "output": result.get("output"),  # 最终输出（字符串）
                 "output_data": result.get("node_outputs", {}),  # 所有节点输出（详细数据）
                 "conversation_id": result.get("conversation_id"),  # 所有节点输出（详细数据）payload.,  # 会话 ID
@@ -559,6 +575,7 @@ class WorkflowService:
         """运行工作流（流式）
 
         Args:
+            workspace_id:
             app_id: 应用 ID
             payload: 请求对象（包含 message, variables, conversation_id 等）
             config: 存储类型（可选）
@@ -601,7 +618,7 @@ class WorkflowService:
             workflow_config_id=config.id,
             app_id=app_id,
             trigger_type="manual",
-            triggered_by=triggered_by_uuid,
+            triggered_by=None,
             conversation_id=conversation_id_uuid,
             input_data=input_data
         )
@@ -638,17 +655,46 @@ class WorkflowService:
                         variables = last_state.get("variables", {})
                         conv_vars = variables.get("conv", {})
                         input_data["conv"] = conv_vars
+                        input_data["conv_messages"] = last_state.get("messages") or []
                         break
+            init_message_length = len(input_data.get("conv_messages", []))
+            from app.core.workflow.executor import execute_workflow_stream
 
-            # 调用流式执行（executor 会发送 workflow_start 和 workflow_end 事件）
-            async for event in self._run_workflow_stream(
+            async for event in execute_workflow_stream(
                     workflow_config=workflow_config_dict,
                     input_data=input_data,
                     execution_id=execution.execution_id,
                     workspace_id=str(workspace_id),
                     user_id=end_user_id
             ):
-                # 直接转发 executor 的事件（已经是正确的格式）
+                if event.get("event") == "workflow_end":
+
+                    status = event.get("data", {}).get("status")
+                    if status == "completed":
+                        self.update_execution_status(
+                            execution.execution_id,
+                            "completed",
+                            output_data=event.get("data")
+                        )
+                        final_messages = event.get("data", {}).get("messages", [])[init_message_length:]
+                        for message in final_messages:
+                            message_obj = Message(
+                                conversation_id=conversation_id_uuid,
+                                role=message["role"],
+                                content=message["content"],
+                            )
+                            self.message_repo.add_message(message_obj)
+                        self.db.commit()
+                        logger.info(f"Workflow Run Success, "
+                                    f"execution_id: {execution.execution_id}, message count: {len(final_messages)}")
+                    elif status == "failed":
+                        self.update_execution_status(
+                            execution.execution_id,
+                            "failed",
+                            output_data=event.get("data")
+                        )
+                    else:
+                        logger.error(f"unexpect workflow run status, status: {status}")
                 yield event
 
         except Exception as e:
@@ -667,6 +713,8 @@ class WorkflowService:
                 }
             }
 
+    @deprecated(reason="This method is deprecated. "
+                       "Please use WorkflowService.run / run_stream instead.")
     async def run_workflow(
             self,
             app_id: uuid.UUID,
@@ -819,6 +867,7 @@ class WorkflowService:
 
         return clean_value(event)
 
+    @deprecated(reason="This method is deprecated. Please use WorkflowService.run_stream instead.")
     async def _run_workflow_stream(
             self,
             workflow_config: dict[str, Any],

api/pyproject.toml

@@ -136,7 +136,8 @@ dependencies = [
     "markdown-to-json==2.1.1",
     "valkey==6.0.2",
     "python-calamine>=0.4.0",
-    "xlrd==2.0.2"
+    "xlrd==2.0.2",
+    "deprecated>=1.3.1",
 ]
 
 [tool.pytest.ini_options]

web/src/components/Chat/ChatContent.tsx

@@ -55,7 +55,7 @@ const ChatContent: FC<ChatContentProps> = ({
                   </div>
                 }
                 {/* 消息气泡框 */}
-                <div className={clsx('rb:border rb:text-left rb:rounded-lg rb:mt-1.5 rb:leading-4.5 rb:p-[10px_12px_2px_12px] rb:inline-block rb:max-w-100 rb:wrap-break-word', contentClassNames, {
+                <div className={clsx('rb:border rb:text-left rb:rounded-lg rb:mt-1.5 rb:leading-4.5 rb:p-[10px_12px_2px_12px] rb:inline-block rb:max-w-[520px] rb:wrap-break-word', contentClassNames, {
                   // 错误消息样式（内容为null且非助手消息）
                   'rb:border-[rgba(255,93,52,0.30)] rb:bg-[rgba(255,93,52,0.08)] rb:text-[#FF5D34]': errorDesc && item.role === 'assistant' && item.content === null,
                   // 助手消息样式
@@ -68,7 +68,7 @@ const ChatContent: FC<ChatContentProps> = ({
                 </div>
                 {/* 底部标签（如时间戳、用户名等） */}
                 {labelPosition === 'bottom' &&
-                  <div className="rb:text-[#5B6167] rb:text-[12px] rb:leading-4 rb:font-regular">
+                  <div className="rb:text-[#5B6167] rb:text-[12px] rb:leading-4 rb:font-regular rb:mt-2">
                     {labelFormat(item)}
                   </div>
                 }

web/src/i18n/en.ts

@@ -1265,6 +1265,7 @@ export const en = {
       emotionLine: 'Emotion Changes Over Time',
       interaction: 'Interaction Frequency & Relationship Stages',
       timelines_memory: 'All',
+      Chunk: 'Chunk',
       MemorySummary: 'Long-term Accumulation',
       Statement: 'Emotional Memory',
       ExtractedEntity: 'Episodic Memory',
@@ -1786,6 +1787,9 @@ Memory Bear: After the rebellion, regional warlordism intensified for several re
           temperature: 'Temperature',
           max_tokens: 'Max Tokens',
           context: 'Context',
+          memory: 'Memory',
+          enable_window: 'Memory Window',
+          inner: 'Built-in',
         },
         start: {
           variables: 'Input Fields',

web/src/i18n/zh.ts

@@ -1343,6 +1343,7 @@ export const zh = {
       emotionLine: '情绪随时间变化',
       interaction: '互动频率 & 关系阶段',
       timelines_memory: '全部',
+      Chunk: '工作记忆',
       MemorySummary: '长期沉淀',
       Statement: '情绪记忆',
       ExtractedEntity: '情景记忆',
@@ -1883,6 +1884,9 @@ export const zh = {
           temperature: '温度',
           max_tokens: '最大令牌数',
           context: '上下文',
+          memory: '记忆',
+          enable_window: '记忆窗口',
+          inner: '内置',
         },
         start: {
           variables: '输入字段',

web/src/views/ApplicationConfig/Agent.tsx

@@ -176,6 +176,9 @@ const Agent = forwardRef<AgentRef>((_props, ref) => {
       if (response?.knowledge_retrieval?.knowledge_bases?.length) {
         getDefaultKnowledgeList(response)
       }
+      if (response?.tools?.length) {
+        setToolList(response?.tools)
+      }
     }).finally(() => {
       setLoading(false)
     })

web/src/views/ApplicationConfig/components/ToolList.tsx

@@ -79,8 +79,6 @@ const ToolList: FC<{ data: ToolOption[]; onUpdate: (config: ToolOption[]) => voi
     }
   }, [data])
 
-  console.log('toolList', toolList)
-
   const handleAddTool = () => {
     toolModalRef.current?.handleOpen()
   }

web/src/views/Conversation/index.tsx

@@ -259,9 +259,10 @@ const Conversation: FC = () => {
       </div>
 
       <div className="rb:relative rb:h-screen rb:px-4 rb:flex-[1_1_auto]">
+        <div className='rb:w-[760px]  rb:h-screen rb:mx-auto rb:pt-10'>
         <Chat
-          empty={<Empty url={AnalysisEmptyIcon} className="rb:h-full" subTitle={t('memoryConversation.emptyDesc')} />}
-          contentClassName="rb:h-[calc(100%-152px)]"
+          empty={<Empty url={BgImg} className="rb:h-full" size={[320,180]} subTitle={t('memoryConversation.emptyDesc')} />}
+          contentClassName="rb:h-[calc(100%-152px)] "
           data={chatList}
           streamLoading={streamLoading}
           loading={loading}
@@ -290,6 +291,7 @@ const Conversation: FC = () => {
             </Flex>
           </Form>
         </Chat>
+        </div>
       </div>
     </Flex>
   )

web/src/views/Workflow/components/AddChatVariable/index.tsx

@@ -1,6 +1,5 @@
-import React, { useState, useImperativeHandle, forwardRef, useRef } from 'react';
-import { Button, Input, Space, Typography, Tooltip, message, List } from 'antd';
-import { PlusOutlined, EditOutlined, DeleteOutlined } from '@ant-design/icons';
+import { useState, useImperativeHandle, forwardRef, useRef } from 'react';
+import { Button, Space, List } from 'antd';
 import { useTranslation } from 'react-i18next';
 import type { ChatVariable, AddChatVariableRef } from '../../types';
 import type { ChatVariableModalRef } from './types'

web/src/views/Workflow/components/Properties/HttpRequest/EditableTable.tsx

@@ -131,7 +131,7 @@ const EditableTable: React.FC<EditableTableProps> = ({
           const AddButton = ({ block = false }: { block?: boolean }) => (
             <Button 
               type={block ? "dashed" : "text"} 
-              icon={<PlusOutlined />} 
+              icon={block ? undefined : <PlusOutlined />} 
               onClick={() => add(createNewRow())} 
               size="small"
               block={block}

web/src/views/Workflow/components/Properties/MemoryConfig/index.tsx

@@ -0,0 +1,69 @@
+import { type FC } from "react";
+import { useTranslation } from 'react-i18next'
+import { Form, Row, Col, Divider, Switch, Slider } from 'antd'
+import type { Suggestion } from '../../Editor/plugin/AutocompletePlugin'
+import MessageEditor from '../MessageEditor'
+
+const MemoryConfig: FC<{ options: Suggestion[]; parentName: string; }> = ({
+  options,
+  parentName
+}) => {
+  const { t } = useTranslation()
+  const form = Form.useFormInstance();
+  const values = Form.useWatch([], form) || {}
+
+  console.log('MemoryConfig', values)
+  
+  const handleChangeEnable = (value: boolean) => {
+    if (value) {
+      form.setFieldsValue({
+        memory: {
+          ...form.getFieldValue(parentName),
+          enable_window: false,
+          window_size: 20,
+          messages: "{{sys.message}}"
+        }
+      })
+    }
+  }
+
+  return (
+    <>
+      {values?.memory?.enable && <>
+        <div className="rb:flex rb:items-center rb:justify-between rb:py-1.5 rb:px-2 rb:bg-[#F6F8FC] rb:rounded-md rb:mb-2">
+          {t('workflow.config.llm.memory')}
+          <span>{t('workflow.config.llm.inner')}</span>
+        </div>
+        <Form.Item layout="horizontal" name={[parentName, 'messages']}>
+          <MessageEditor
+            title="USER"
+            isArray={false}
+            parentName={[parentName, 'messages']}
+            options={options}
+          />
+        </Form.Item>
+
+        <Divider />
+      </>}
+      <Form.Item layout="horizontal" name={[parentName, 'enable']} label={t('workflow.config.llm.memory')}>
+        <Switch onChange={handleChangeEnable} />
+      </Form.Item>
+      {values?.memory?.enable && <>
+        <Row className="rb:mb-3">
+          <Col span={10}>
+            <Form.Item layout="horizontal" name={[parentName, 'enable_window']} noStyle>
+              <Switch />
+            </Form.Item>
+            <span className="rb:ml-2">{t('workflow.config.llm.enable_window')}</span>
+          </Col>
+          <Col span={14}>
+            <Form.Item layout="horizontal" name={[parentName, 'window_size']} noStyle>
+              <Slider min={1} max={100} step={1} className="rb:my-0!" disabled={!values?.memory?.enable_window} />
+            </Form.Item>
+          </Col>
+        </Row>
+      </>}
+    </>
+  );
+};
+export default MemoryConfig;

web/src/views/Workflow/components/Properties/MessageEditor.tsx

@@ -127,7 +127,7 @@ const MessageEditor: FC<MessageEditor> = ({
               </Space>
             );
           })}
-          <Form.Item>
+          <Form.Item noStyle>
             <Button type="dashed" onClick={() => handleAdd(add)} block>
               +{t('workflow.addMessage')}
             </Button>

web/src/views/Workflow/components/Properties/index.tsx

@@ -22,6 +22,7 @@ import ConditionList from './ConditionList'
 import CycleVarsList from './CycleVarsList'
 import AssignmentList from './AssignmentList'
 import ToolConfig from './ToolConfig'
+import MemoryConfig from './MemoryConfig'
 // import { calculateVariableList } from './utils/variableListCalculator'
 
 interface PropertiesProps {
@@ -1230,6 +1231,20 @@ const Properties: FC<PropertiesProps> = ({
                     </Form.Item>
                   )
                 }
+                if (config.type === 'memoryConfig') {
+                  return (
+                    <Form.Item
+                      key={key}
+                      name={key}
+                      noStyle
+                    >
+                      <MemoryConfig
+                        parentName={key}
+                        options={getFilteredVariableList('llm')}
+                      />
+                    </Form.Item>
+                  )
+                }
 
                 return (
                   <Form.Item 

web/src/views/Workflow/constant.ts

@@ -135,6 +135,14 @@ export const nodeLibrary: NodeLibrary[] = [
                 readonly: true
               },
             ]
+          },
+          memory: {
+            type: 'memoryConfig',
+            defaultValue: {
+              enable: false,
+              enable_window: false,
+              window_size: 20
+            }
           }
         }
       },
@@ -750,10 +758,6 @@ export const outputVariable: { [key: string]: OutputVariable } = {
       { name: "body", type: "string" },
       { name: "status_code", type: "number" },
     ],
-    error: [
-      { name: "error_message", type: "string" },
-      { name: "error_type", type: "string" },
-    ]
   },
   'tool': {
     default: [

web/src/views/Workflow/hooks/useWorkflowGraph.ts

@@ -6,7 +6,7 @@ import { Graph, Node, MiniMap, Snapline, Clipboard, Keyboard, type Edge } from '
 import { register } from '@antv/x6-react-shape';
 
 import { nodeRegisterLibrary, graphNodeLibrary, nodeLibrary, portMarkup, portAttrs } from '../constant';
-import type { WorkflowConfig, NodeProperties } from '../types';
+import type { WorkflowConfig, NodeProperties, ChatVariable } from '../types';
 import { getWorkflowConfig, saveWorkflowConfig } from '@/api/application'
 import type { PortMetadata } from '@antv/x6/lib/model/port';
 
@@ -35,6 +35,8 @@ export interface UseWorkflowGraphReturn {
   copyEvent: () => boolean | void;
   parseEvent: () => boolean | void;
   handleSave: (flag?: boolean) => Promise<unknown>;
+  chatVariables: ChatVariable[];
+  setChatVariables: React.Dispatch<React.SetStateAction<ChatVariable[]>>;
 }
 
 export const edge_color = '#155EEF';
@@ -54,6 +56,7 @@ export const useWorkflowGraph = ({
   const [canRedo, setCanRedo] = useState(false);
   const [isHandMode, setIsHandMode] = useState(false);
   const [config, setConfig] = useState<WorkflowConfig | null>(null);
+  const [chatVariables, setChatVariables] = useState<ChatVariable[]>([])
 
   useEffect(() => {
     getConfig()
@@ -63,16 +66,15 @@ export const useWorkflowGraph = ({
     getWorkflowConfig(id)
       .then(res => {
         const { variables, ...rest } = res as WorkflowConfig
-        setConfig({
-          ...rest,
-          variables: variables.map(v => {
-            const { default: _, ...cleanV } = v
-            return {
-              ...cleanV,
-              defaultValue: v.default ?? ''
-            }
-          })
+        const initChatVariables = variables.map(v => {
+          const { default: _, ...cleanV } = v
+          return {
+            ...cleanV,
+            defaultValue: v.default ?? ''
+          }
         })
+        setChatVariables(initChatVariables)
+        setConfig({ ...rest, variables: initChatVariables })
       })
   }
 
@@ -94,7 +96,17 @@ export const useWorkflowGraph = ({
 
         if (nodeLibraryConfig?.config) {
           Object.keys(nodeLibraryConfig.config).forEach(key => {
-            if (key === 'knowledge_retrieval' && nodeLibraryConfig.config && nodeLibraryConfig.config[key]) {
+            if (key === 'memory' && nodeLibraryConfig.config && nodeLibraryConfig.config[key]) {
+              const { memory, messages } = config as any;
+              if (memory?.enable && messages && messages.length > 0) {
+                const lastMessage = messages[messages.length - 1]
+                nodeLibraryConfig.config[key].defaultValue = {
+                  ...memory,
+                  messages: lastMessage.content
+                }
+                nodeLibraryConfig.config.messages.defaultValue.splice(-1, 1)
+              }
+            } else if (key === 'knowledge_retrieval' && nodeLibraryConfig.config && nodeLibraryConfig.config[key]) {
               const { query, ...rest } = config
               nodeLibraryConfig.config[key].defaultValue = {
                 ...rest
@@ -917,13 +929,13 @@ export const useWorkflowGraph = ({
 
       const params = {
         ...config,
-        variables: config.variables.map(v => {
-            const { defaultValue, ...cleanV } = v
-            return {
-              ...cleanV,
-              default: defaultValue ?? ''
-            }
-          }),
+        variables: chatVariables.map(v => {
+          const { defaultValue, ...cleanV } = v
+          return {
+            ...cleanV,
+            default: defaultValue ?? ''
+          }
+        }),
         nodes: nodes.map((node: Node) => {
           const data = node.getData();
           const position = node.getPosition();
@@ -931,7 +943,15 @@ export const useWorkflowGraph = ({
 
           if (data.config) {
             Object.keys(data.config).forEach(key => {
-              if (data.config[key] && 'defaultValue' in data.config[key] && key === 'group_variables') {
+              if (key === 'memory' && data.config[key] && 'defaultValue' in data.config[key]) {
+                const { messages, ...rest } = data.config[key].defaultValue
+                let memoryMessage = { role: 'USER', content: data.config[key].defaultValue.messages }
+                itemConfig = {
+                  ...itemConfig,
+                  messages: rest.enable ? [...itemConfig.messages, memoryMessage] : itemConfig.messages,
+                  memory: { ...rest },
+                }
+              } else if (data.config[key] && 'defaultValue' in data.config[key] && key === 'group_variables') {
                 let group_variables = data.config.group.defaultValue ? {} : data.config[key].defaultValue
                 if (data.config.group.defaultValue) {
                   data.config[key].defaultValue.map((vo: any) => {
@@ -1077,5 +1097,7 @@ export const useWorkflowGraph = ({
     copyEvent,
     parseEvent,
     handleSave,
+    chatVariables,
+    setChatVariables
   };
 };

web/src/views/Workflow/index.tsx

@@ -8,7 +8,7 @@ import PortClickHandler from './components/PortClickHandler';
 import { useWorkflowGraph } from './hooks/useWorkflowGraph';
 import type { WorkflowRef } from '@/views/ApplicationConfig/types'
 import Chat from './components/Chat/Chat';
-import type { ChatRef, AddChatVariableRef, ChatVariable } from './types'
+import type { ChatRef, AddChatVariableRef } from './types'
 import arrowIcon from '@/assets/images/workflow/arrow.png'
 import AddChatVariable from './components/AddChatVariable';
 
@@ -21,7 +21,6 @@ const Workflow = forwardRef<WorkflowRef>((_props, ref) => {
   // 使用自定义Hook初始化工作流图
   const {
     config,
-    setConfig,
     graphRef,
     selectedNode,
     setSelectedNode,
@@ -38,6 +37,8 @@ const Workflow = forwardRef<WorkflowRef>((_props, ref) => {
     copyEvent,
     parseEvent,
     handleSave,
+    chatVariables,
+    setChatVariables
   } = useWorkflowGraph({ containerRef, miniMapRef });
 
   const onDragOver = (event: React.DragEvent) => {
@@ -52,15 +53,6 @@ const Workflow = forwardRef<WorkflowRef>((_props, ref) => {
   const addVariable = () => {
     addChatVariableRef.current?.handleOpen()
   }
-  const handleUpdateChatVariable = (variables: ChatVariable[]) => {
-    setConfig(prev => {
-      if (!prev) return null
-      return {
-        ...prev,
-        variables
-      }
-    })
-  }
 
   useImperativeHandle(ref, () => ({
     handleSave,
@@ -125,8 +117,8 @@ const Workflow = forwardRef<WorkflowRef>((_props, ref) => {
 
       <AddChatVariable
         ref={addChatVariableRef}
-        variables={config?.variables}
-        onChange={handleUpdateChatVariable}
+        variables={chatVariables}
+        onChange={setChatVariables}
       />
     </div>
   );