Merge pull request #113 from SuanmoSuanyangTechnology/feature/workflow-llm-memory

feat(workflow): add session context memory support to LLM nodes

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/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],