fix：修复上下文消息构建顺序，确保AI正确理解对话上下文

消息顺序调整为：历史消息 → 知识库内容 → 当前用户消息 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
docs：更新技术栈版本号并清理文档
2026-04-10 02:07:33 +00:00 · 2026-04-07 22:13:32 +08:00 · 2026-04-07 21:04:31 +08:00 · 2026-04-07 10:04:05 +08:00 · 2026-04-05 21:36:53 +08:00 · 2026-04-05 21:34:41 +08:00
83 changed files with 2785 additions and 1551 deletions
--- a/README.md
+++ b/README.md
@@ -19,7 +19,7 @@

 ### 企业级AI助手平台

-*开箱即用的全栈AI平台，支持多智能体协同、Supervisor模式编排、多种决策模型，提供先进的RAG技术和可视化流程编排能力*
+*开箱即用的全栈AI平台，支持多智能体协同、Supervisor模式编排、多种决策模式、RAG技术和流程编排能力*

 **[English](README_EN.md)** | **[📖 使用文档](https://doc.pandarobot.chat)** |
 **[🚀 在线体验](https://web.pandarobot.chat)** | **[🐛 问题反馈](https://github.com/ageerle/ruoyi-ai/issues)** | **[💡 功能建议](https://github.com/ageerle/ruoyi-ai/issues)**
@@ -27,17 +27,15 @@
 </div>


-
-
 ## ✨ 核心亮点

-|     模块     | 现有能力 | 扩展方向                   |
-|:----------:|---|------------------------|
-|  **模型管理**  | 多模型接入(OpenAI/DeepSeek/通义/智谱)、多模态理解、Coze/DIFY/FastGPT平台集成 | 自动模式、容错机制、计费管理         |
-|  **知识管理**  | 本地RAG + 向量库(Milvus/Weaviate)  + 文档解析        | 多模态、知识出处、知识图谱、重排序    |
-|  **工具管理**  | Mcp协议集成、Skills能力 + 可扩展工具生态                             | 工具插件市场、 |
-|  **流程编排**  | 可视化工作流设计器、节点拖拽编排、SSE流式执行,目前已经支持模型调用,邮件发送,人工审核等节点  | 更多节点类型                 |
-|  **多智能体**  | 基于Langchain4j的Agent框架、Supervisor模式编排,支持多种决策模型          | 智能体可配置                 |
+|     模块     | 现有能力 
+|:----------:|---
+|  **模型管理**  | 多模型接入(OpenAI/DeepSeek/通义/智谱)、多模态理解、Coze/DIFY/FastGPT平台集成 
+|  **知识管理**  | 本地RAG + 向量库(Milvus/Weaviate/Qdrant)  + 文档解析        
+|  **工具管理**  | Mcp协议集成、Skills能力 + 可扩展工具生态                             
+|  **流程编排**  | 可视化工作流设计器、节点拖拽编排、SSE流式执行,目前已经支持模型调用,邮件发送,人工审核等节点  
+|  **多智能体**  | 基于Langchain4j的Agent框架、Supervisor模式编排,支持多种决策模型          

 ## 🚀 快速体验

@@ -64,12 +62,16 @@
 ## 🛠️ 技术架构

 ### 核心框架
- **后端架构**：Spring Boot 4.0 + Spring ai 2.0 + Langchain4j
- **数据存储**：MySQL 8.0 + Redis + 向量数据库（Milvus/Weaviate）
+- **后端架构**：Spring Boot 3.5.8 + Langchain4j
+- **数据存储**：MySQL 8.0 + Redis + 向量数据库（Milvus/Weaviate/Qdrant）
 - **前端技术**：Vue 3 + Vben Admin + element-plus-x
 - **安全认证**：Sa-Token + JWT 双重保障


+- **文档处理**：PDF、Word、Excel 解析，图像智能分析
+- **实时通信**：WebSocket 实时通信，SSE 流式响应
+- **系统监控**：完善的日志体系、性能监控、服务健康检查
+
 ## 🐳 Docker 部署

 本项目提供两种 Docker 部署方式：
@@ -220,9 +222,6 @@ docker-compose -f docker-compose-all.yaml restart [服务名]
  算力和模型 API 服务
 - [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_ruoyi) - 万卡RTX40系GPU+海内外主流模型API服务，秒级响应，按量计费，新客免费用。

-## 优秀开源项目及社区推荐
- [imaiwork](https://gitee.com/tsinghua-open/imaiwork) - AI手机开源版，AI获客手机项目，基于无障碍模式，RPA，比豆包AI手机更强大。
-
 ## 💬 社区交流

 <div align="center">
@@ -246,30 +245,6 @@ docker-compose -f docker-compose-all.yaml restart [服务名]
 </div>

 ---
-
-
-## 📺 视频教程
-
-<div align="center">
-
-<table>
-<tr>
-<td align="center">
-<img src="docs/image/dy.png" alt="微信二维码" width="200" height="200"><br>
-<strong>打开抖音扫一扫</strong><br>
-<em>获取免费视频教程</em>
-</td>
-<td align="center">
-<img src="docs/image/bibi.png" alt="QQ群二维码" width="200" height="200"><br>
-<strong>打开B站扫一扫</strong><br>
-<em>获取免费视频教程</em>
-</td>
-
-</tr>
-</table>
-
-</div>
-
 <div align="center">

 **[⭐ 点个Star支持一下](https://github.com/ageerle/ruoyi-ai)** • **[ Fork 开始贡献](https://github.com/ageerle/ruoyi-ai/fork)** • **[📚 English](README_EN.md)** • **[📖 查看完整文档](https://doc.pandarobot.chat)**
--- a/README_EN.md
+++ b/README_EN.md
@@ -32,14 +32,13 @@

 ## ✨ Core Features

-| Module | Current Capabilities | Extension Direction |
-|:---:|---|---|
-| **Model Management** | Multi-model integration (OpenAI/DeepSeek/Tongyi/Zhipu), multi-modal understanding, Coze/DIFY/FastGPT platform integration | Auto mode, fault tolerance |
-| **Knowledge Base** | Local RAG + Vector DB (Milvus/Weaviate) + Knowledge Graph + Document parsing + Reranking | Audio/video parsing, knowledge source |
-| **Tool Management** | MCP protocol integration, Skills capability + Extensible tool ecosystem | Tool plugin marketplace, toolAgent auto-loading |
-| **Workflow Orchestration** | Visual workflow designer, drag-and-drop node orchestration, SSE streaming execution, currently supports model (with RAG) calls, email sending, manual review nodes | More node types |
-| **Multi-Agent** | Agent framework based on Langchain4j, Supervisor mode orchestration, supports multiple decision models | Configurable agents |
-| **AI Coding** | Intelligent code analysis, project scaffolding generation, Copilot assistant | Code generation optimization |
+| Module | Current Capabilities |
+|:---:|---|
+| **Model Management** | Multi-model integration (OpenAI/DeepSeek/Tongyi/Zhipu), multi-modal understanding, Coze/DIFY/FastGPT platform integration |
+| **Knowledge Base** | Local RAG + Vector DB (Milvus/Weaviate/Qdrant) + Document parsing |
+| **Tool Management** | MCP protocol integration, Skills capability + Extensible tool ecosystem |
+| **Workflow Orchestration** | Visual workflow designer, drag-and-drop node orchestration, SSE streaming execution, currently supports model calls, email sending, manual review nodes |
+| **Multi-Agent** | Agent framework based on Langchain4j, Supervisor mode orchestration, supports multiple decision models |

 ## 🚀 Quick Start

@@ -59,19 +58,134 @@
 | 🛠️ Admin Panel | [ruoyi-admin](https://github.com/ageerle/ruoyi-admin) | [ruoyi-admin](https://gitee.com/ageerle/ruoyi-admin) | [ruoyi-admin](https://gitcode.com/ageerle/ruoyi-admin) |

 ### Partner Projects
-| Project Name           | GitHub Repository                                             | Gitee Repository
+| Project Name           | GitHub Repository                                             | Gitee Repository |
 |----------------|-------------------------------------------------------|------------------------------------------------------|
 | element-plus-x | [element-plus-x](https://github.com/element-plus-x/Element-Plus-X)       | [element-plus-x](https://gitee.com/he-jiayue/element-plus-x)       |

 ## 🛠️ Technical Architecture

 ### Core Framework
- **Backend**: Spring Boot 4.0 + Spring AI 2.0 + Langchain4j
- **Data Storage**: MySQL 8.0 + Redis + Vector Databases (Milvus/Weaviate)
+- **Backend**: Spring Boot 3.5.8 + Langchain4j
+- **Data Storage**: MySQL 8.0 + Redis + Vector Databases (Milvus/Weaviate/Qdrant)
 - **Frontend**: Vue 3 + Vben Admin + element-plus-x
 - **Security**: Sa-Token + JWT dual-layer security


+- **Document Processing**: PDF, Word, Excel parsing, intelligent image analysis
+- **Real-time Communication**: WebSocket real-time communication, SSE streaming response
+- **System Monitoring**: Comprehensive logging system, performance monitoring, service health checks
+
+## 🐳 Docker Deployment
+
+This project provides two Docker deployment methods:
+
+### Method 1: One-click Start All Services (Recommended)
+
+Use `docker-compose-all.yaml` to start all services at once (including backend, admin panel, user frontend, and dependencies):
+
+```bash
+# Clone the repository
+git clone https://github.com/ageerle/ruoyi-ai.git
+cd ruoyi-ai
+
+# Start all services (pull pre-built images from registry)
+docker-compose -f docker-compose-all.yaml up -d
+
+# Check service status
+docker-compose -f docker-compose-all.yaml ps
+
+# Access services
+# Admin Panel: http://localhost:25666 (admin / admin123)
+# User Frontend: http://localhost:25137
+# Backend API: http://localhost:26039
+```
+
+### Method 2: Step-by-step Deployment (Source Build)
+
+If you need to build backend services from source, follow these steps:
+
+#### Step 1: Deploy Backend Service
+
+```bash
+# Enter backend project directory
+cd ruoyi-ai
+
+# Start backend service (build from source)
+docker-compose up -d --build
+
+# Wait for backend service to start
+docker-compose logs -f backend
+```
+
+#### Step 2: Deploy Admin Panel
+
+```bash
+# Enter admin panel project directory
+cd ruoyi-admin
+
+# Build and start admin panel
+docker-compose up -d --build
+
+# Access admin panel
+# URL: http://localhost:5666
+```
+
+#### Step 3: Deploy User Frontend (Optional)
+
+```bash
+# Enter user frontend project directory
+cd ruoyi-web
+
+# Build and start user frontend
+docker-compose up -d --build
+
+# Access user frontend
+# URL: http://localhost:5137
+```
+
+### Service Ports
+
+| Service | One-click Port | Step-by-step Port | Description |
+|------|-------------|-------------|------|
+| Admin Panel | 25666 | 5666 | Admin backend access |
+| User Frontend | 25137 | 5137 | User frontend access |
+| Backend Service | 26039 | 6039 | Backend API service |
+| MySQL | 23306 | 23306 | Database service |
+| Redis | 26379 | 6379 | Cache service |
+| Weaviate | 28080 | 28080 | Vector database |
+| MinIO API | 29000 | 9000 | Object storage API |
+| MinIO Console | 29090 | 9090 | Object storage console |
+
+### Image Registry
+
+All images are hosted on Alibaba Cloud Container Registry:
+
+```
+crpi-31mraxd99y2gqdgr.cn-beijing.personal.cr.aliyuncs.com/ruoyi_ai
+```
+
+Available images:
+- `mysql:v3` - MySQL database (includes initialization SQL)
+- `redis:6.2` - Redis cache
+- `weaviate:1.30.0` - Vector database
+- `minio:latest` - Object storage
+- `ruoyi-ai-backend:latest` - Backend service
+- `ruoyi-ai-admin:latest` - Admin frontend
+- `ruoyi-ai-web:latest` - User frontend
+
+### Common Commands
+
+```bash
+# Stop all services
+docker-compose -f docker-compose-all.yaml down
+
+# View service logs
+docker-compose -f docker-compose-all.yaml logs -f [service-name]
+
+# Restart a service
+docker-compose -f docker-compose-all.yaml restart [service-name]
+```
+
 ## 📚 Documentation

 Want to learn more about installation, deployment, configuration, and secondary development?
@@ -109,14 +223,13 @@ Thanks to the following excellent open-source projects for their support:
 - [PPIO Cloud](https://ppinfra.com/user/register?invited_by=P8QTUY&utm_source=github_ruoyi-ai) - Provides cost-effective GPU computing and model API services
 - [Youyun Intelligent Computing](https://www.compshare.cn/?ytag=GPU_YY-gh_ruoyi) - Thousands of RTX40 series GPUs + mainstream models API services, second-level response, pay-per-use, free for new customers.

-## Outstanding Open-Source Projects and Community Recommendations
- [imaiwork](https://gitee.com/tsinghua-open/imaiwork) - Open-source AI phone, AI customer acquisition phone project, based on accessibility mode and RPA, more powerful than Doubao AI phone.

 ## 💬 Community Chat

 <div align="center">

-**[📱 Join Telegram Group](https://t.me/+LqooQAc5HxRmYmE1)**
+**[📱 Join Telegram Group](
+https://t.me/+LqooQAc5HxRmYmE1)**

 </div>

--- a/docs/docker/qdrant/docker-compose.yml
+++ b/docs/docker/qdrant/docker-compose.yml
@@ -0,0 +1,12 @@
+---
+services:
+  qdrant:
+    image: qdrant/qdrant:latest
+    ports:
+      - 6333:6333
+      - 6334:6334
+    volumes:
+      - qdrant_data:/qdrant/storage
+volumes:
+  qdrant_data:
+...
--- a/docs/docker/ruoyi-ai/Dockerfile.backend
+++ b/docs/docker/ruoyi-ai/Dockerfile.backend
--- a/docs/docker/ruoyi-ai/Dockerfile.mysql
+++ b/docs/docker/ruoyi-ai/Dockerfile.mysql
--- a/docs/docker/ruoyi-ai/docker-compose-all.yaml
+++ b/docs/docker/ruoyi-ai/docker-compose-all.yaml
--- a/docs/docker/ruoyi-ai/docker-compose.yaml
+++ b/docs/docker/ruoyi-ai/docker-compose.yaml
--- a/ruoyi-admin/src/main/java/org/ruoyi/RuoYiAIApplication.java
+++ b/ruoyi-admin/src/main/java/org/ruoyi/RuoYiAIApplication.java
@@ -4,6 +4,9 @@ import org.springframework.boot.SpringApplication;
 import org.springframework.boot.autoconfigure.SpringBootApplication;
 import org.springframework.boot.context.metrics.buffering.BufferingApplicationStartup;

+import java.net.InetSocketAddress;
+import java.net.ServerSocket;
+
 /**
 * 启动程序
 *
@@ -13,10 +16,66 @@ import org.springframework.boot.context.metrics.buffering.BufferingApplicationSt
 public class RuoYiAIApplication {

    public static void main(String[] args) {
+        // killPortProcess(6039);
        SpringApplication application = new SpringApplication(RuoYiAIApplication.class);
        application.setApplicationStartup(new BufferingApplicationStartup(2048));
        application.run(args);
-        System.out.println("(♥◠‿◠)ﾉﾞ     RuoYi-AI启动成功   ლ(´ڡ`ლ)ﾞ");
+        System.out.println("(♥◠‿◠)ﾉﾞ     RuoYi-AI启动成功   ლ(´ڡ`ლ)冢");
+    }
+
+    /**
+     * 检查并终止占用指定端口的进程
+     *
+     * @param port 端口号
+     */
+    private static void killPortProcess(int port) {
+        try {
+            if (!isPortInUse(port)) {
+                return;
+            }
+            System.out.println("端口 " + port + " 已被占用，正在查找并终止进程...");
+
+            ProcessBuilder pb = new ProcessBuilder("netstat", "-ano");
+            Process process = pb.start();
+            java.io.BufferedReader reader = new java.io.BufferedReader(
+                    new java.io.InputStreamReader(process.getInputStream()));
+
+            String line;
+            while ((line = reader.readLine()) != null) {
+                if (line.contains(":" + port + " ") && line.contains("LISTENING")) {
+                    String[] parts = line.trim().split("\\s+");
+                    String pid = parts[parts.length - 1];
+                    System.out.println("找到占用端口 " + port + " 的进程 PID: " + pid + "，正在终止...");
+
+                    ProcessBuilder killPb = new ProcessBuilder("taskkill", "/F", "/PID", pid);
+                    Process killProcess = killPb.start();
+                    int exitCode = killProcess.waitFor();
+                    if (exitCode == 0) {
+                        System.out.println("进程 " + pid + " 已成功终止");
+                    } else {
+                        System.out.println("终止进程 " + pid + " 失败，exitCode: " + exitCode);
+                    }
+                    break;
+                }
+            }
+
+            // 等待一小段时间确保端口释放
+            Thread.sleep(500);
+        } catch (Exception e) {
+            System.out.println("检查/终止端口进程时发生异常: " + e.getMessage());
+        }
+    }
+
+    /**
+     * 检查端口是否被占用
+     */
+    private static boolean isPortInUse(int port) {
+        try (ServerSocket socket = new ServerSocket()) {
+            socket.bind(new InetSocketAddress(port));
+            return false;
+        } catch (Exception e) {
+            return true;
+        }
    }

 }
--- a/ruoyi-admin/src/main/resources/application-dev.yml
+++ b/ruoyi-admin/src/main/resources/application-dev.yml
@@ -58,7 +58,7 @@ spring:
          driverClassName: com.mysql.cj.jdbc.Driver
          # jdbc 所有参数配置参考 https://lionli.blog.csdn.net/article/details/122018562
          # rewriteBatchedStatements=true 批处理优化 大幅提升批量插入更新删除性能(对数据库有性能损耗 使用批量操作应考虑性能问题)
-          url: jdbc:mysql://127.0.0.1:3306/ruoyi-ai-agent?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8&autoReconnect=true&rewriteBatchedStatements=true&allowPublicKeyRetrieval=true&nullCatalogMeansCurrent=true
+          url: jdbc:mysql://127.0.0.1:3306/ruoyi-ai?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8&autoReconnect=true&rewriteBatchedStatements=true&allowPublicKeyRetrieval=true&nullCatalogMeansCurrent=true
          username: root
          password: root
 #        agent:
--- a/ruoyi-admin/src/main/resources/application.yml
+++ b/ruoyi-admin/src/main/resources/application.yml
@@ -275,7 +275,7 @@ warm-flow:

 # 向量库配置
 vector-store:
-  # 向量存储类型 可选(weaviate/milvus)
+  # 向量存储类型 可选(weaviate/milvus/qdrant)
  # 如需修改向量库类型，请修改此配置值!
  type: milvus
  # Weaviate配置
@@ -287,3 +287,10 @@ vector-store:
  milvus:
    url: http://localhost:19530
    collectionname: LocalKnowledge
+  # Qdrant配置
+  qdrant:
+    host: localhost
+    port: 6334
+    collectionname: LocalKnowledge
+    api-key:
+    use-tls: false
--- a/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/domain/dto/ChatMessageDTO.java
+++ b/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/domain/dto/ChatMessageDTO.java
@@ -1,45 +0,0 @@
-package org.ruoyi.common.chat.domain.dto;
-
-import lombok.Data;
-
-/**
- * 聊天消息DTO - 用于上下文传递
- *
- * @author ageerle@163.com
- * @date 2025/12/13
- */
-@Data
-public class ChatMessageDTO {
-
-    /**
-     * 消息角色: system/user/assistant
-     */
-    private String role;
-
-    /**
-     * 消息内容
-     */
-    private String content;
-
-    public static ChatMessageDTO system(String content) {
-        ChatMessageDTO msg = new ChatMessageDTO();
-        msg.role = "system";
-        msg.content = content;
-        return msg;
-    }
-
-    public static ChatMessageDTO user(String content) {
-        ChatMessageDTO msg = new ChatMessageDTO();
-        msg.role = "user";
-        msg.content = content;
-        return msg;
-    }
-
-    public static ChatMessageDTO assistant(String content) {
-        ChatMessageDTO msg = new ChatMessageDTO();
-        msg.role = "assistant";
-        msg.content = content;
-        return msg;
-    }
-}
-
--- a/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/domain/dto/request/ChatRequest.java
+++ b/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/domain/dto/request/ChatRequest.java
@@ -1,11 +1,11 @@
 package org.ruoyi.common.chat.domain.dto.request;

-import dev.langchain4j.data.message.ChatMessage;
+import com.alibaba.fastjson.annotation.JSONField;
+import com.fasterxml.jackson.databind.annotation.JsonSerialize;
+import com.fasterxml.jackson.databind.ser.std.ToStringSerializer;
 import jakarta.validation.constraints.NotEmpty;
 import lombok.Data;
-import org.ruoyi.common.chat.domain.dto.ChatMessageDTO;

-import java.util.List;

 /**
 *  对话请求对象
@@ -16,11 +16,15 @@ import java.util.List;
@Data
 public class ChatRequest {

-    @NotEmpty(message = "对话消息不能为空")
-    private List<ChatMessageDTO> messages;
    @NotEmpty(message = "传入的模型不能为空")
    private String model;

+    /**
+     * 对话消息
+     */
+    @NotEmpty(message = "对话消息不能为空")
+    private String content;
+
    /**
     * 工作流请求体
     */
@@ -31,59 +35,49 @@ public class ChatRequest {
     */
    private ReSumeRunner reSumeRunner;

+    /**
+     * 是否为人机交互用户继续输入
+     */
+    private Boolean isResume = false;
+
    /**
     * 是否启用工作流
     */
-    private Boolean enableWorkFlow;
+    private Boolean enableWorkFlow = false;

    /**
     * 会话id
     */
+    @JsonSerialize(using = ToStringSerializer.class)
+    @JSONField(serializeUsing = String.class)
    private Long sessionId;

-    /**
-     * 应用ID
-     */
-    private String appId;
-
    /**
     * 知识库id
     */
    private String knowledgeId;

    /**
-     * 对话id(每个聊天窗口都不一样)
+     * 应用ID
     */
-    private Long uuid;
+    private String appId;
+

    /**
-     * 是否为人机交互用户继续输入
+     * 对话id(每个聊天窗口都不一样)
     */
-    private Boolean isResume;
+    @JsonSerialize(using = ToStringSerializer.class)
+    @JSONField(serializeUsing = String.class)
+    private Long uuid;

    /**
     * 是否启用深度思考
     */
-    private Boolean enableThinking;
-
-    /**
-     * 是否自动切换模型
-     */
-    private Boolean autoSelectModel;
+    private Boolean enableThinking = false;

    /**
     * 是否支持联网
     */
    private Boolean enableInternet;

-    /**
-     * 会话令牌（为避免在非Web线程中获取Request，入口处注入）
-     */
-    private String token;
-
-    /**
-     * 原生对话对象
-     */
-    private List<ChatMessage> chatMessages;
-
 }
--- a/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/domain/vo/chat/ChatMessageVo.java
+++ b/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/domain/vo/chat/ChatMessageVo.java
@@ -5,8 +5,6 @@ import cn.idev.excel.annotation.ExcelProperty;
 import io.github.linpeilie.annotations.AutoMapper;
 import lombok.Data;
 import org.ruoyi.common.chat.entity.chat.ChatMessage;
-import org.ruoyi.common.excel.annotation.ExcelDictFormat;
-import org.ruoyi.common.excel.convert.ExcelDictConvert;

 import java.io.Serial;
 import java.io.Serializable;
--- a/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/entity/BaseEntity.java
+++ b/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/entity/BaseEntity.java
@@ -6,12 +6,14 @@ import com.baomidou.mybatisplus.annotation.TableId;
 import io.swagger.v3.oas.annotations.media.Schema;
 import lombok.Data;

+import java.io.Serial;
 import java.io.Serializable;
 import java.time.LocalDateTime;

@Data
 public class BaseEntity implements Serializable {

+    @Serial
    private static final long serialVersionUID = 1L;

    @TableId(type = IdType.AUTO)
--- a/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/entity/chat/ChatContext.java
+++ b/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/entity/chat/ChatContext.java
@@ -1,63 +0,0 @@
-package org.ruoyi.common.chat.entity.chat;
-
-import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
-import jakarta.validation.constraints.NotNull;
-import lombok.Builder;
-import lombok.Data;
-import lombok.EqualsAndHashCode;
-import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
-import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
-import org.ruoyi.common.chat.service.chat.IChatService;
-import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
-
-/**
- * 聊天对话上下文对象
- *
- * @author zengxb
- * @date 2026-02-14
- */
-@Data
-@EqualsAndHashCode(callSuper = false)
-@Builder
-public class ChatContext {
-
-    /**
-     * 模型管理视图对象
-     */
-    @NotNull(message = "模型管理视图对象不能为空")
-    private ChatModelVo chatModelVo;
-
-    /**
-     * 对话请求对象
-     */
-    @NotNull(message = "对话请求对象不能为空")
-    private ChatRequest chatRequest;
-
-    /**
-     * SSe连接对象
-     */
-    @NotNull(message = "SSe连接对象不能为空")
-    private SseEmitter emitter;
-
-    /**
-     * 用户ID
-     */
-    @NotNull(message = "用户ID不能为空")
-    private Long userId;
-
-    /**
-     * Token
-     */
-    @NotNull(message = "Token不能为空")
-    private String tokenValue;
-
-    /**
-     * 响应处理器
-     */
-    private StreamingChatResponseHandler handler;
-
-    /**
-     * 聊天服务实例
-     */
-    private IChatService chatService;
-}
--- a/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/service/chat/IChatService.java
+++ b/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/service/chat/IChatService.java
@@ -1,7 +1,8 @@
 package org.ruoyi.common.chat.service.chat;

+import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
 import jakarta.validation.Valid;
-import org.ruoyi.common.chat.entity.chat.ChatContext;
+import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
 import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;

 /**
@@ -12,10 +13,15 @@ public interface IChatService {
    /**
     * 客户端发送对话消息到服务端
     */
-    SseEmitter chat(@Valid ChatContext chatContext);
+    SseEmitter chat(@Valid ChatRequest chatRequest);

    /**
-     * 获取服务提供商名称
+     * 支持外部 handler 的对话接口（跨模块调用）
+     * 同时发送到 SSE 和外部 handler
+     *
+     * @param chatRequest    聊天请求
+     * @param externalHandler 外部响应处理器（可为 null）
     */
-    String getProviderName();
+    void chat(@Valid ChatRequest chatRequest, StreamingChatResponseHandler externalHandler);
+
 }
--- a/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/service/chatMessage/AbstractChatMessageService.java
+++ b/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/service/chatMessage/AbstractChatMessageService.java
@@ -1,58 +0,0 @@
-package org.ruoyi.common.chat.service.chatMessage;
-
-import org.ruoyi.common.chat.domain.bo.chat.ChatMessageBo;
-import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
-import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
-import org.springframework.beans.factory.annotation.Autowired;
-
-/**
- * 聊天信息抽象基类 - 保存聊天信息
- *
- * @author Zengxb
- * @date 2026-02-24
- */
-public abstract class AbstractChatMessageService {
-
-    /**
-     * 创建日志对象
-     */
-    Logger log = LoggerFactory.getLogger(AbstractChatMessageService.class);
-
-    @Autowired
-    private IChatMessageService chatMessageService;
-
-    /**
-     * 保存聊天信息
-     */
-    public void saveChatMessage(ChatRequest chatRequest, Long userId, String content, String role, ChatModelVo chatModelVo){
-        try {
-            // 验证必要的上下文信息
-            if (chatRequest == null || userId == null) {
-                log.warn("缺少必要的聊天上下文信息，无法保存消息");
-                return;
-            }
-
-            // 创建ChatMessageBo对象
-            ChatMessageBo messageBO = new ChatMessageBo();
-            messageBO.setUserId(userId);
-            messageBO.setSessionId(chatRequest.getSessionId());
-            messageBO.setContent(content);
-            messageBO.setRole(role);
-            messageBO.setModelName(chatRequest.getModel());
-            messageBO.setRemark(null);
-
-            chatMessageService.insertByBo(messageBO);
-        } catch (Exception e) {
-            log.error("保存{}聊天消息时出错: {}", getProviderName(), e.getMessage(), e);
-        }
-    }
-
-    /**
-     * 获取服务提供商名称
-     */
-    protected String getProviderName(){
-        return "默认工作流大模型";
-    }
-}
--- a/ruoyi-common/ruoyi-common-sse/src/main/java/org/ruoyi/common/sse/core/SseEmitterManager.java
+++ b/ruoyi-common/ruoyi-common-sse/src/main/java/org/ruoyi/common/sse/core/SseEmitterManager.java
@@ -2,9 +2,11 @@ package org.ruoyi.common.sse.core;

 import cn.hutool.core.collection.CollUtil;
 import cn.hutool.core.map.MapUtil;
+import cn.hutool.json.JSONUtil;
 import lombok.extern.slf4j.Slf4j;
 import org.ruoyi.common.core.utils.SpringUtils;
 import org.ruoyi.common.redis.utils.RedisUtils;
+import org.ruoyi.common.sse.dto.SseEventDto;
 import org.ruoyi.common.sse.dto.SseMessageDto;
 import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;

@@ -65,7 +67,7 @@ public class SseEmitterManager {
        emitter.onCompletion(() -> {
            SseEmitter remove = emitters.remove(token);
            if (remove != null) {
-//                remove.complete();
+               remove.complete();
            }
        });
        emitter.onTimeout(() -> {
@@ -174,9 +176,11 @@ public class SseEmitterManager {
        if (MapUtil.isNotEmpty(emitters)) {
            for (Map.Entry<String, SseEmitter> entry : emitters.entrySet()) {
                try {
+                    // 格式化为标准SSE JSON格式
+                    SseEventDto eventDto = SseEventDto.content(message);
                    entry.getValue().send(SseEmitter.event()
                        .name("message")
-                        .data(message));
+                        .data(JSONUtil.toJsonStr(eventDto)));
                } catch (Exception e) {
                    SseEmitter remove = emitters.remove(entry.getKey());
                    if (remove != null) {
@@ -189,6 +193,33 @@ public class SseEmitterManager {
        }
    }

+    /**
+     * 向指定的用户会话发送结构化事件
+     *
+     * @param userId    要发送消息的用户id
+     * @param eventDto  SSE事件对象
+     */
+    public void sendEvent(Long userId, SseEventDto eventDto) {
+        Map<String, SseEmitter> emitters = USER_TOKEN_EMITTERS.get(userId);
+        if (MapUtil.isNotEmpty(emitters)) {
+            for (Map.Entry<String, SseEmitter> entry : emitters.entrySet()) {
+                try {
+                    entry.getValue().send(SseEmitter.event()
+                        .name(eventDto.getEvent())
+                        .data(JSONUtil.toJsonStr(eventDto)));
+                } catch (Exception e) {
+                    SseEmitter remove = emitters.remove(entry.getKey());
+                    if (remove != null) {
+                        remove.complete();
+                    }
+                }
+            }
+        } else {
+            USER_TOKEN_EMITTERS.remove(userId);
+        }
+    }
+
+
    /**
     * 本机全用户会话发送消息
     *
--- a/ruoyi-common/ruoyi-common-sse/src/main/java/org/ruoyi/common/sse/dto/SseEventDto.java
+++ b/ruoyi-common/ruoyi-common-sse/src/main/java/org/ruoyi/common/sse/dto/SseEventDto.java
@@ -0,0 +1,92 @@
+package org.ruoyi.common.sse.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Builder;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+import java.io.Serial;
+import java.io.Serializable;
+
+/**
+ * SSE 事件数据传输对象
+ * <p>
+ * 标准的 SSE 消息格式，支持不同事件类型
+ *
+ * @author ageerle@163.com
+ * @date 2025/03/19
+ */
+@Data
+@Builder
+@NoArgsConstructor
+@AllArgsConstructor
+public class SseEventDto implements Serializable {
+
+    @Serial
+    private static final long serialVersionUID = 1L;
+
+    /**
+     * 事件类型
+     */
+    private String event;
+
+    /**
+     * 消息内容
+     */
+    private String content;
+
+    /**
+     * 推理内容（深度思考模式）
+     */
+    private String reasoningContent;
+
+    /**
+     * 错误信息
+     */
+    private String error;
+
+    /**
+     * 是否完成
+     */
+    private Boolean done;
+
+    /**
+     * 创建内容事件
+     */
+    public static SseEventDto content(String content) {
+        return SseEventDto.builder()
+            .event("content")
+            .content(content)
+            .build();
+    }
+
+    /**
+     * 创建推理内容事件
+     */
+    public static SseEventDto reasoning(String reasoningContent) {
+        return SseEventDto.builder()
+            .event("reasoning")
+            .reasoningContent(reasoningContent)
+            .build();
+    }
+
+    /**
+     * 创建完成事件
+     */
+    public static SseEventDto done() {
+        return SseEventDto.builder()
+            .event("done")
+            .done(true)
+            .build();
+    }
+
+    /**
+     * 创建错误事件
+     */
+    public static SseEventDto error(String error) {
+        return SseEventDto.builder()
+            .event("error")
+            .error(error)
+            .build();
+    }
+}
--- a/ruoyi-common/ruoyi-common-sse/src/main/java/org/ruoyi/common/sse/utils/SseMessageUtils.java
+++ b/ruoyi-common/ruoyi-common-sse/src/main/java/org/ruoyi/common/sse/utils/SseMessageUtils.java
@@ -1,10 +1,12 @@
 package org.ruoyi.common.sse.utils;

+import java.util.Collections;
 import lombok.AccessLevel;
 import lombok.NoArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
 import org.ruoyi.common.core.utils.SpringUtils;
 import org.ruoyi.common.sse.core.SseEmitterManager;
+import org.ruoyi.common.sse.dto.SseEventDto;
 import org.ruoyi.common.sse.dto.SseMessageDto;

 /**
@@ -27,6 +29,7 @@ public class SseMessageUtils {

    /**
     * 向指定的SSE会话发送消息
+     * 通过 Redis Pub/Sub 广播，确保跨模块消息可达
     *
     * @param userId  要发送消息的用户id
     * @param message 要发送的消息内容
@@ -35,7 +38,11 @@ public class SseMessageUtils {
        if (!isEnable()) {
            return;
        }
-        MANAGER.sendMessage(userId, message);
+        // 通过 Redis 广播，让所有模块的 SseTopicListener 接收并转发到本地 SSE 连接
+        SseMessageDto dto = new SseMessageDto();
+        dto.setMessage(message);
+        dto.setUserIds(Collections.singletonList(userId));
+        MANAGER.publishMessage(dto);
    }

    /**
@@ -86,6 +93,58 @@ public class SseMessageUtils {
        MANAGER.disconnect(userId, tokenValue);
    }

+    /**
+     * 向指定的SSE会话发送结构化事件
+     *
+     * @param userId   要发送消息的用户id
+     * @param eventDto SSE事件对象
+     */
+    public static void sendEvent(Long userId, SseEventDto eventDto) {
+        if (!isEnable()) {
+            return;
+        }
+        MANAGER.sendEvent(userId, eventDto);
+    }
+
+    /**
+     * 发送内容事件
+     *
+     * @param userId  用户ID
+     * @param content 内容
+     */
+    public static void sendContent(Long userId, String content) {
+        sendEvent(userId, SseEventDto.content(content));
+    }
+
+    /**
+     * 发送推理内容事件
+     *
+     * @param userId           用户ID
+     * @param reasoningContent 推理内容
+     */
+    public static void sendReasoning(Long userId, String reasoningContent) {
+        sendEvent(userId, SseEventDto.reasoning(reasoningContent));
+    }
+
+    /**
+     * 发送完成事件
+     *
+     * @param userId 用户ID
+     */
+    public static void sendDone(Long userId) {
+        sendEvent(userId, SseEventDto.done());
+    }
+
+    /**
+     * 发送错误事件
+     *
+     * @param userId 用户ID
+     * @param error  错误信息
+     */
+    public static void sendError(Long userId, String error) {
+        sendEvent(userId, SseEventDto.error(error));
+    }
+
    /**
     * 是否开启
     */
--- a/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/service/WorkflowComponentService.java
+++ b/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/service/WorkflowComponentService.java
@@ -98,7 +98,7 @@ public class WorkflowComponentService extends ServiceImpl<WorkflowComponentMappe
        return baseMapper.selectPage(new Page<>(currentPage, pageSize), wrapper);
    }

-    @Cacheable(cacheNames = WORKFLOW_COMPONENTS)
+    // @Cacheable(cacheNames = WORKFLOW_COMPONENTS)
    public List<WorkflowComponent> getAllEnable() {
        return ChainWrappers.lambdaQueryChain(baseMapper)
                .eq(WorkflowComponent::getIsEnable, true)
--- a/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/util/WorkflowMessageUtil.java
+++ b/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/util/WorkflowMessageUtil.java
@@ -64,7 +64,8 @@ public class WorkflowMessageUtil {
            ChatRequest chatRequest = new ChatRequest();
            chatRequest.setSessionId(sessionId);
            WorkflowUtil workflowUtil = SpringUtils.getBean(WorkflowUtil.class);
-            workflowUtil.saveChatMessage(chatRequest, userId, message, RoleType.WORKFLOW.getName(), new ChatModelVo());
+            // todo 保存消息
+            //workflowUtil.saveChatMessage(chatRequest, userId, message, RoleType.WORKFLOW.getName(), new ChatModelVo());
        }
    }

--- a/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/WorkflowUtil.java
+++ b/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/WorkflowUtil.java
@@ -4,23 +4,18 @@ import cn.hutool.core.collection.CollStreamUtil;
 import cn.hutool.core.collection.CollUtil;
 import cn.hutool.core.util.StrUtil;
 import dev.langchain4j.data.message.ChatMessage;
-import dev.langchain4j.data.message.SystemMessage;
 import dev.langchain4j.data.message.UserMessage;
 import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
 import jakarta.annotation.Resource;
 import lombok.extern.slf4j.Slf4j;
 import org.bsc.langgraph4j.langchain4j.generators.StreamingChatGenerator;
 import org.bsc.langgraph4j.state.AgentState;
-import org.ruoyi.common.chat.enums.RoleType;
 import org.ruoyi.common.chat.service.chat.IChatModelService;
 import org.ruoyi.common.chat.service.chat.IChatService;
-import org.ruoyi.common.chat.service.chatMessage.AbstractChatMessageService;
 import org.ruoyi.common.chat.service.image.IImageGenerationService;
 import org.ruoyi.common.chat.domain.dto.request.ChatRequest;
-import org.ruoyi.common.chat.entity.chat.ChatContext;
 import org.ruoyi.common.chat.entity.image.ImageContext;
 import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
-import org.ruoyi.common.chat.factory.ChatServiceFactory;
 import org.ruoyi.common.chat.factory.ImageServiceFactory;
 import org.ruoyi.workflow.base.NodeInputConfigTypeHandler;
 import org.ruoyi.workflow.entity.WorkflowNode;
@@ -29,9 +24,7 @@ import org.ruoyi.workflow.util.JsonUtil;
 import org.ruoyi.workflow.workflow.data.NodeIOData;
 import org.ruoyi.workflow.workflow.data.NodeIODataContent;
 import org.ruoyi.workflow.workflow.def.WfNodeParamRef;
-import org.springframework.stereotype.Component;
 import org.springframework.stereotype.Service;
-import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;

 import java.util.*;

@@ -39,10 +32,7 @@ import static org.ruoyi.workflow.cosntant.AdiConstant.WorkflowConstant.DEFAULT_O

@Slf4j
@Service
-public class WorkflowUtil extends AbstractChatMessageService {
-
-    @Resource
-    private ChatServiceFactory chatServiceFactory;
+public class WorkflowUtil{

    @Resource
    private ImageServiceFactory imageServiceFactory;
@@ -50,6 +40,9 @@ public class WorkflowUtil extends AbstractChatMessageService {
    @Resource
    private IChatModelService chatModelService;

+    @Resource
+    private IChatService chatService;
+
    public static String renderTemplate(String template, List<NodeIOData> values) {
        // 🔒 关键修复：如果 template 为 null，直接返回 null 或空字符串
        if (template == null) {
@@ -112,54 +105,23 @@ public class WorkflowUtil extends AbstractChatMessageService {
    }

    public void streamingInvokeLLM(WfState wfState, WfNodeState state, WorkflowNode node, String modelName,
-                                   List<SystemMessage> systemMessage, String nodeMessageTemplate) {
+                                   String prompt, String nodeMessageTemplate) {
        log.info("stream invoke, modelName: {}", modelName);

-        // 根据模型名称查询模型信息
-        ChatModelVo chatModelVo = chatModelService.selectModelByName(modelName);
-        if (chatModelVo == null) {
-            throw new IllegalArgumentException("模型不存在: " + modelName);
-        }
-
-        // 路由服务提供商
-        String category = chatModelVo.getProviderCode();
-        // 根据 category 获取对应的 ChatService（不使用计费代理，工作流场景单独计费）
-        IChatService chatService = chatServiceFactory.getOriginalService(category);
-
        // 获取用户信息和Token以及SSe连接对象（对话接口需要使用）
        Long sessionId = wfState.getSessionId();
-        Long userId = wfState.getUserId();
-        String tokenValue = wfState.getTokenValue();
-        SseEmitter sseEmitter = wfState.getSseEmitter();
-
-        // 构建 ruoyi-ai 的 ChatRequest
-        List<ChatMessage> chatMessages = new ArrayList<>();
-        addUserMessage(node, state.getInputs(), chatMessages);
-        chatMessages.addAll(systemMessage);
-
        // 定义模型调用对象
        ChatRequest chatRequest = new ChatRequest();
-        // 目前工作流深度思考成员变量只能写死
        chatRequest.setSessionId(sessionId);
        chatRequest.setEnableThinking(false);
        chatRequest.setModel(modelName);
-        chatRequest.setChatMessages(chatMessages);
+        chatRequest.setContent(prompt);

        // 构建流式生成器
        StreamingChatGenerator<AgentState> streamingGenerator = StreamingChatGenerator.builder()
            .mapResult(response -> {
                String responseTxt = response.aiMessage().text();
                log.info("llm response:{}", responseTxt);
-
-                // 会话ID不为空时插入数据库
-                if (sessionId != null){
-                    // 获取模板消息拼接信息体
-                    String message = nodeMessageTemplate + responseTxt;
-                    // 保存助手回复消息
-                    saveChatMessage(chatRequest, userId, message, RoleType.ASSISTANT.getName(), chatModelVo);
-                    log.info("{}消息结束，已保存到数据库", getProviderName());
-                }
-
                // 传递所有输入数据 + 添加 LLM 输出
                wfState.getNodeStateByNodeUuid(node.getUuid()).ifPresent(item -> {
                    List<NodeIOData> outputs = new ArrayList<>(item.getInputs());
@@ -174,21 +136,13 @@ public class WorkflowUtil extends AbstractChatMessageService {
            .startingState(state)
            .build();

-        // 构建流式回调响应器
-        StreamingChatResponseHandler handler = streamingGenerator.handler();
+        // 获取 StreamingChatGenerator 的 handler，用于处理流式响应
+        StreamingChatResponseHandler workflowHandler = streamingGenerator.handler();

-        //构建聊天对话上下文参数
-        ChatContext chatContext = ChatContext.builder()
-            .chatModelVo(chatModelVo)
-            .chatRequest(chatRequest)
-            .emitter(sseEmitter)
-            .userId(userId)
-            .tokenValue(tokenValue)
-            .handler(handler)
-            .build();
+        // 调用 Chat 服务，传入 workflow 的 handler
+        // 消息会同时发送到 SSE（前端）和 workflowHandler（工作流处理）
+        chatService.chat(chatRequest, workflowHandler);

-        // 使用工作流专用方法
-        chatService.chat(chatContext);
        wfState.getNodeToStreamingGenerator().put(node.getUuid(), streamingGenerator);
    }

--- a/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/node/answer/LLMAnswerNode.java
+++ b/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/node/answer/LLMAnswerNode.java
@@ -46,13 +46,11 @@ public class LLMAnswerNode extends AbstractWfNode {
        // 调用LLM
        WorkflowUtil workflowUtil = SpringUtil.getBean(WorkflowUtil.class);
        String modelName = nodeConfigObj.getModelName();
-        // 转换系统信息结构
-        List<SystemMessage> systemMessage = List.of(new SystemMessage(prompt));
        // 获取节点模板提示词信息
        String nodeMessageTemplate = WorkflowMessageUtil.getNodeMessageTemplate(NodeMessageTemplateEnum.LLM_RESPONSE.getValue());
        // 发送SSE驱动事件消息
        WorkflowMessageUtil.sendEmitterMessage(wfState.getSseEmitter(), node, nodeMessageTemplate);
-        workflowUtil.streamingInvokeLLM(wfState, state, node, modelName, systemMessage, nodeMessageTemplate);
+        workflowUtil.streamingInvokeLLM(wfState, state, node, modelName, prompt, nodeMessageTemplate);
        return new NodeProcessResult();
    }
 }
--- a/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/node/keywordExtractor/KeywordExtractorNode.java
+++ b/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/node/keywordExtractor/KeywordExtractorNode.java
@@ -67,13 +67,12 @@ public class KeywordExtractorNode extends AbstractWfNode {
        // 调用 LLM 进行关键词提取
        WorkflowUtil workflowUtil = SpringUtil.getBean(WorkflowUtil.class);
        String modelName = config.getModelName();
-        List<SystemMessage> systemMessage = List.of(new SystemMessage(prompt));
        // 获取节点模板提示词信息
        String nodeMessageTemplate = WorkflowMessageUtil.getNodeMessageTemplate(NodeMessageTemplateEnum.KEYWORD_EXTRACTOR.getValue());
        // 发送SSE事件消息
        WorkflowMessageUtil.sendEmitterMessage(wfState.getSseEmitter(), node, nodeMessageTemplate);
        // 使用流式调用
-        workflowUtil.streamingInvokeLLM(wfState, state, node, modelName, systemMessage, nodeMessageTemplate);
+        workflowUtil.streamingInvokeLLM(wfState, state, node, modelName, prompt, nodeMessageTemplate);
        return new NodeProcessResult();
    }

--- a/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/node/knowledgeRetrieval/KnowledgeRetrievalNode.java
+++ b/ruoyi-modules/ruoyi-aiflow/src/main/java/org/ruoyi/workflow/workflow/node/knowledgeRetrieval/KnowledgeRetrievalNode.java
@@ -151,7 +151,6 @@ public class KnowledgeRetrievalNode extends AbstractWfNode {

            // 使用WorkflowUtil调用LLM（流式）
            WorkflowUtil workflowUtil = SpringUtil.getBean(WorkflowUtil.class);
-            List<SystemMessage> systemMessage = List.of(new SystemMessage(prompt));

            // 调用流式LLM
            String modelName = StringUtils.isNotBlank(config.getModelName()) ? config.getModelName() : "deepseek-chat";
@@ -161,7 +160,7 @@ public class KnowledgeRetrievalNode extends AbstractWfNode {
                tempState,
                tempNode,
                modelName,
-                systemMessage,
+                prompt,
                ""
            );

--- a/ruoyi-modules/ruoyi-aiflow/流程编排模块说明.md
+++ b/ruoyi-modules/ruoyi-aiflow/流程编排模块说明.md
@@ -0,0 +1,425 @@
+# Ruoyi-AI 流程编排模块详细说明文档
+
+## 概述
+
+Ruoyi-AI 工作流模块是一个基于 LangGraph4j 的智能工作流引擎，支持可视化工作流设计、AI 模型集成、条件分支、人机交互等高级功能。该模块采用微服务架构，提供完整的
+RESTful API 和流式响应支持。
+
+## 模块架构
+
+### 1. 核心依赖
+
+- **LangGraph4j**: 1.5.3 - 工作流图执行引擎
+- **LangChain4j**: 1.11.0 - AI 模型集成框架
+- **Spring Boot**: 3.5.8 - 应用框架
+- **MyBatis Plus**: 数据访问层
+- **Redis**: 缓存和状态管理
+- **OpenAPI**: API 文档
+
+## 核心功能
+
+### 1. 工作流管理
+
+#### 1.1 工作流定义
+
+- **创建工作流**: 支持自定义标题、描述、公开性设置
+- **编辑工作流**: 可视化节点编辑、连接线配置
+- **版本控制**: 支持工作流的版本管理和回滚
+- **权限管理**: 支持公开/私有工作流设置
+
+#### 1.2 工作流执行
+
+- **流式执行**: 基于 SSE 的实时流式响应
+- **状态管理**: 完整的执行状态跟踪
+- **错误处理**: 详细的错误信息和异常处理
+- **中断恢复**: 支持工作流中断和恢复执行
+
+### 2. 节点类型
+
+#### 2.1 基础节点
+
+- **Start**: 开始节点，定义工作流入口
+- **End**: 结束节点，定义工作流出口
+
+
+#### 2.2 AI 模型节点
+
+- **Answer**: 大语言模型问答节点
+- **Dalle3**: DALL-E 3 图像生成
+- **Tongyiwanx**: 通义万相图像生成
+- **Classifier**: 内容分类节点
+
+#### 2.3 数据处理节点
+
+- **DocumentExtractor**: 文档信息提取
+- **KeywordExtractor**: 关键词提取
+- **FaqExtractor**: 常见问题提取
+- **KnowledgeRetrieval**: 知识库检索
+
+#### 2.4 控制流节点
+
+- **Switcher**: 条件分支节点
+- **HumanFeedback**: 人机交互节点
+
+#### 2.5 外部集成节点
+
+- **Google**: Google 搜索集成
+- **MailSend**: 邮件发送
+- **HttpRequest**: HTTP 请求
+- **Template**: 模板转换
+
+### 3. 数据流管理
+
+#### 3.1 输入输出定义
+
+```java
+// 节点输入输出数据结构
+public class NodeIOData {
+    private String name;           // 参数名称
+    private NodeIODataContent content; // 参数内容
+}
+
+// 支持的数据类型
+public enum WfIODataTypeEnum {
+    TEXT,        // 文本
+    NUMBER,      // 数字
+    BOOLEAN,     // 布尔值
+    FILES,       // 文件
+    OPTIONS      // 选项
+}
+```
+
+#### 3.2 参数引用
+
+- **节点间引用**: 支持上游节点输出作为下游节点输入
+- **参数映射**: 自动处理参数名称映射
+- **类型转换**: 自动进行数据类型转换
+
+## 数据库设计
+
+### 1. 核心表结构
+
+#### 1.1 工作流定义表 (t_workflow)
+
+```sql
+CREATE TABLE t_workflow (
+    id          BIGINT AUTO_INCREMENT PRIMARY KEY,
+    uuid        VARCHAR(32)  NOT NULL DEFAULT '',
+    title       VARCHAR(100) NOT NULL DEFAULT '',
+    remark      TEXT         NOT NULL DEFAULT '',
+    user_id     BIGINT       NOT NULL DEFAULT 0,
+    is_public   TINYINT(1)   NOT NULL DEFAULT 0,
+    is_enable   TINYINT(1)   NOT NULL DEFAULT 1,
+    create_time DATETIME     NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    update_time DATETIME     NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
+    is_deleted  TINYINT(1)   NOT NULL DEFAULT 0
+);
+```
+
+#### 1.2 工作流节点表 (t_workflow_node)
+
+```sql
+CREATE TABLE t_workflow_node (
+    id                    BIGINT AUTO_INCREMENT PRIMARY KEY,
+    uuid                  VARCHAR(32)  NOT NULL DEFAULT '',
+    workflow_id           BIGINT       NOT NULL DEFAULT 0,
+    workflow_component_id BIGINT       NOT NULL DEFAULT 0,
+    user_id               BIGINT       NOT NULL DEFAULT 0,
+    title                 VARCHAR(100) NOT NULL DEFAULT '',
+    remark                VARCHAR(500) NOT NULL DEFAULT '',
+    input_config          JSON         NOT NULL DEFAULT ('{}'),
+    node_config           JSON         NOT NULL DEFAULT ('{}'),
+    position_x            DOUBLE       NOT NULL DEFAULT 0,
+    position_y            DOUBLE       NOT NULL DEFAULT 0,
+    create_time           DATETIME     NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    update_time           DATETIME     NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
+    is_deleted            TINYINT(1)   NOT NULL DEFAULT 0
+);
+```
+
+#### 1.3 工作流边表 (t_workflow_edge)
+
+```sql
+CREATE TABLE t_workflow_edge (
+    id               BIGINT AUTO_INCREMENT PRIMARY KEY,
+    uuid             VARCHAR(32) NOT NULL DEFAULT '',
+    workflow_id      BIGINT      NOT NULL DEFAULT 0,
+    source_node_uuid VARCHAR(32) NOT NULL DEFAULT '',
+    source_handle    VARCHAR(32) NOT NULL DEFAULT '',
+    target_node_uuid VARCHAR(32) NOT NULL DEFAULT '',
+    create_time      DATETIME    NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    update_time      DATETIME    NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
+    is_deleted       TINYINT(1)  NOT NULL DEFAULT 0
+);
+```
+
+#### 1.4 工作流运行时表 (t_workflow_runtime)
+
+```sql
+CREATE TABLE t_workflow_runtime (
+    id            BIGINT AUTO_INCREMENT PRIMARY KEY,
+    uuid          VARCHAR(32)  NOT NULL DEFAULT '',
+    user_id       BIGINT       NOT NULL DEFAULT 0,
+    workflow_id   BIGINT       NOT NULL DEFAULT 0,
+    input         JSON         NOT NULL DEFAULT ('{}'),
+    output        JSON         NOT NULL DEFAULT ('{}'),
+    status        SMALLINT     NOT NULL DEFAULT 1,
+    status_remark VARCHAR(250) NOT NULL DEFAULT '',
+    create_time   DATETIME     NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    update_time   DATETIME     NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
+    is_deleted    TINYINT(1)   NOT NULL DEFAULT 0
+);
+```
+
+#### 1.5 工作流组件表 (t_workflow_component)
+
+```sql
+CREATE TABLE t_workflow_component (
+    id            BIGINT AUTO_INCREMENT PRIMARY KEY,
+    uuid          VARCHAR(32)  DEFAULT '' NOT NULL,
+    name          VARCHAR(32)  DEFAULT '' NOT NULL,
+    title         VARCHAR(100) DEFAULT '' NOT NULL,
+    remark        TEXT                   NOT NULL,
+    display_order INT          DEFAULT 0 NOT NULL,
+    is_enable     TINYINT(1)   DEFAULT 0 NOT NULL,
+    create_time   DATETIME     DEFAULT CURRENT_TIMESTAMP NOT NULL,
+    update_time   DATETIME     DEFAULT CURRENT_TIMESTAMP NOT NULL,
+    is_deleted    TINYINT(1)   DEFAULT 0 NOT NULL
+);
+```
+
+## API 接口
+
+### 1. 工作流管理接口
+
+#### 1.1 基础操作
+
+```http
+# 创建工作流
+POST /workflow/add
+Content-Type: application/json
+{
+    "title": "工作流标题",
+    "remark": "工作流描述",
+    "isPublic": false
+}
+
+# 更新工作流
+POST /workflow/update
+Content-Type: application/json
+{
+    "uuid": "工作流UUID",
+    "title": "新标题",
+    "remark": "新描述"
+}
+
+# 删除工作流
+POST /workflow/del/{uuid}
+
+# 启用/禁用工作流
+POST /workflow/enable/{uuid}?enable=true
+```
+
+#### 1.2 搜索和查询
+
+```http
+# 搜索我的工作流
+GET /workflow/mine/search?keyword=关键词&isPublic=true&currentPage=1&pageSize=10
+
+# 搜索公开工作流
+GET /workflow/public/search?keyword=关键词&currentPage=1&pageSize=10
+
+# 获取工作流组件列表
+GET /workflow/public/component/list
+```
+
+### 2. 工作流执行接口
+
+#### 2.1 流式执行
+
+```http
+# 流式执行工作流
+POST /workflow/run
+Content-Type: application/json
+Accept: text/event-stream
+{
+    "uuid": "工作流UUID",
+    "inputs": [
+        {
+            "name": "input",
+            "content": {
+                "type": 1,
+                "textContent": "用户输入内容"
+            }
+        }
+    ]
+}
+```
+
+#### 2.2 运行时管理
+
+```http
+# 恢复中断的工作流
+POST /workflow/runtime/resume/{runtimeUuid}
+Content-Type: application/json
+{
+    "feedbackContent": "用户反馈内容"
+}
+
+# 查询工作流执行历史
+GET /workflow/runtime/page?wfUuid=工作流UUID&currentPage=1&pageSize=10
+
+# 查询运行时节点详情
+GET /workflow/runtime/nodes/{runtimeUuid}
+
+# 清理运行时数据
+POST /workflow/runtime/clear?wfUuid=工作流UUID
+```
+
+### 3. 管理端接口
+
+#### 3.1 工作流管理
+
+```http
+# 搜索所有工作流
+POST /admin/workflow/search
+Content-Type: application/json
+{
+    "title": "搜索关键词",
+    "isPublic": true,
+    "isEnable": true
+}
+
+# 启用/禁用工作流
+POST /admin/workflow/enable?uuid=工作流UUID&isEnable=true
+```
+
+## 核心实现
+
+### 1. 工作流引擎 (WorkflowEngine)
+
+工作流引擎是整个模块的核心，负责：
+
+- 工作流图的构建和编译
+- 节点执行调度
+- 状态管理和持久化
+- 流式输出处理
+
+```java
+public class WorkflowEngine {
+    // 核心执行方法
+    public void run(User user, List<ObjectNode> userInputs, SseEmitter sseEmitter) {
+        // 1. 验证工作流状态
+        // 2. 创建运行时实例
+        // 3. 构建状态图
+        // 4. 执行工作流
+        // 5. 处理流式输出
+    }
+    
+    // 恢复执行方法
+    public void resume(String userInput) {
+        // 1. 更新状态
+        // 2. 继续执行
+    }
+}
+```
+
+### 2. 节点工厂 (WfNodeFactory)
+
+节点工厂负责根据组件类型创建对应的节点实例：
+
+```java
+public class WfNodeFactory {
+    public static AbstractWfNode create(WorkflowComponent component, 
+                                      WorkflowNode node, 
+                                      WfState wfState, 
+                                      WfNodeState nodeState) {
+        // 根据组件类型创建对应的节点实例
+        switch (component.getName()) {
+            case "Answer":
+                return new LLMAnswerNode(component, node, wfState, nodeState);
+            case "Switcher":
+                return new SwitcherNode(component, node, wfState, nodeState);
+            // ... 其他节点类型
+        }
+    }
+}
+```
+
+### 3. 图构建器 (WorkflowGraphBuilder)
+
+图构建器负责将工作流定义转换为可执行的状态图：
+
+```java
+public class WorkflowGraphBuilder {
+    public StateGraph<WfNodeState> build(WorkflowNode startNode) {
+        // 1. 构建编译节点树
+        // 2. 转换为状态图
+        // 3. 添加节点和边
+        // 4. 处理条件分支
+        // 5. 处理并行执行
+    }
+}
+```
+
+## 流式响应机制
+
+### 1. SSE 事件类型
+
+工作流执行过程中会发送多种类型的 SSE 事件：
+
+```javascript
+// 节点开始执行
+[NODE_RUN_节点UUID] - 节点执行开始事件
+
+// 节点输入数据
+[NODE_INPUT_节点UUID] - 节点输入数据事件
+
+// 节点输出数据
+[NODE_OUTPUT_节点UUID] - 节点输出数据事件
+
+// 流式内容块
+[NODE_CHUNK_节点UUID] - 流式内容块事件
+
+// 等待用户输入
+[NODE_WAIT_FEEDBACK_BY_节点UUID] - 等待用户输入事件
+```
+
+### 2. 流式处理流程
+
+1. **初始化**: 创建工作流运行时实例
+2. **节点执行**: 逐个执行工作流节点
+3. **实时输出**: 通过 SSE 实时推送执行结果
+4. **状态更新**: 实时更新节点和工作流状态
+5. **错误处理**: 捕获并处理执行过程中的错误
+
+## 扩展开发
+
+### 1. 自定义节点开发
+
+要开发自定义工作流节点，需要：
+
+1. **创建节点类**：继承 `AbstractWfNode`
+2. **实现处理逻辑**：重写 `onProcess()` 方法
+3. **定义配置类**：创建节点配置类
+4. **注册组件**：在组件表中注册新组件
+
+```java
+public class CustomNode extends AbstractWfNode {
+    @Override
+    protected NodeProcessResult onProcess() {
+        // 实现自定义处理逻辑
+        List<NodeIOData> outputs = new ArrayList<>();
+        // ... 处理逻辑
+        return NodeProcessResult.success(outputs);
+    }
+}
+```
+
+### 2. 自定义组件注册
+
+```sql
+-- 在 t_workflow_component 表中添加新组件
+INSERT INTO t_workflow_component (uuid, name, title, remark, is_enable) 
+VALUES (REPLACE(UUID(), '-', ''), 'CustomNode', '自定义节点', '自定义节点描述', true);
+```
--- a/ruoyi-modules/ruoyi-chat/docs/MCP工具模块接口文档.md
+++ b/ruoyi-modules/ruoyi-chat/docs/MCP工具模块接口文档.md
--- a/ruoyi-modules/ruoyi-chat/pom.xml
+++ b/ruoyi-modules/ruoyi-chat/pom.xml
@@ -19,6 +19,11 @@
            <artifactId>ruoyi-common-chat</artifactId>
        </dependency>

+        <dependency>
+            <groupId>org.ruoyi</groupId>
+            <artifactId>ruoyi-common-sse</artifactId>
+        </dependency>
+
        <dependency>
            <groupId>org.ruoyi</groupId>
            <artifactId>ruoyi-common-sensitive</artifactId>
@@ -86,6 +91,12 @@
            <version>${langchain4j.community.version}</version>
        </dependency>

+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j-qdrant</artifactId>
+            <version>${langchain4j.community.version}</version>
+        </dependency>
+
        <dependency>
            <groupId>dev.langchain4j</groupId>
            <artifactId>langchain4j-mcp</artifactId>
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/ChartGenerationAgent.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/ChartGenerationAgent.java
@@ -6,7 +6,7 @@ import dev.langchain4j.service.UserMessage;
 import dev.langchain4j.service.V;


-public interface ChartGenerationAgent extends Agent {
+public interface ChartGenerationAgent {

    @SystemMessage("""
            You are a chart generation specialist. Your only task is to generate Apache ECharts
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/EchartsAgent.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/EchartsAgent.java
@@ -14,7 +14,7 @@ public interface EchartsAgent {

    @SystemMessage("""
        You are a data visualization assistant that generates Echarts chart configurations.
-        
+
        CRITICAL OUTPUT REQUIREMENTS:
        - Return Echarts JSON wrapped in markdown code block
        - Use this exact format: ```json\n{...}\n```
@@ -81,7 +81,7 @@ public interface EchartsAgent {
        """)
    @UserMessage("""
        Generate an Echarts chart for: {{query}}
-        
+
        IMPORTANT: Return the Echarts configuration JSON wrapped in markdown code block (```json...```).
        """)
    @Agent("Data visualization assistant that returns Echarts JSON configurations for frontend rendering")
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/GetNameInfo.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/GetNameInfo.java
@@ -1,38 +0,0 @@
-package org.ruoyi.agent;
-
-import dev.langchain4j.agentic.Agent;
-import dev.langchain4j.service.SystemMessage;
-import dev.langchain4j.service.UserMessage;
-import dev.langchain4j.service.V;
-
-/**
- * User Name Retrieval Agent
- * A simple assistant that retrieves user names using the get_name tool.
- */
-public interface GetNameInfo {
-
-    @SystemMessage("""
-        You are a user identity assistant. You MUST always use tools to get information.
-
-        MANDATORY REQUIREMENTS:
-        - You MUST call the get_user_name_by_id tool for ANY question about names or identity
-        - NEVER respond without calling the get_user_name_by_id tool first
-        - Return ONLY the exact string returned by the get_user_name_by_id tool
-        - Do not make up names like "John Doe" or any other default names
-        - Do not use your knowledge to answer - ALWAYS use the tool
-
-        Your workflow:
-        1. Extract userId from the query (if mentioned), or use "1" as default
-        2. ALWAYS call the get_user_name_by_id tool with the userId parameter
-        3. Return the exact result as plain text with no additions
-
-        CRITICAL: If you don't call the get_user_name_by_id tool, your response is wrong.
-        """)
-    @UserMessage("""
-        Get the user name using the get_user_name_by_id tool. Query: {{query}}
-
-        IMPORTANT: Return only the exact result from the tool.
-        """)
-    @Agent("User identity assistant that returns user name from get_name tool")
-    String search(@V("query") String query);
-}
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/McpAgent.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/McpAgent.java
@@ -1,42 +0,0 @@
-package org.ruoyi.agent;
-
-import dev.langchain4j.agentic.Agent;
-import dev.langchain4j.service.SystemMessage;
-import dev.langchain4j.service.UserMessage;
-import dev.langchain4j.service.V;
-
-public interface McpAgent extends Agent {
-
-    /**
-     * 系统提示词：通用工具调用智能体
-     * 不限定具体工具类型，让 LangChain4j 自动传递工具描述给 LLM
-     */
-    @SystemMessage("""
-        你是一个AI助手，可以通过调用各种工具来帮助用户完成不同的任务。
-
-        【工具使用规则】
-        1. 根据用户的请求，判断需要使用哪些工具
-        2. 仔细阅读每个工具的描述，确保理解工具的功能和参数要求
-        3. 使用正确的参数调用工具
-        4. 如果工具执行失败，向用户友好地说明错误原因，并尝试提供替代方案
-        5. 对于复杂任务，可以分步骤使用多个工具完成
-        6. 将工具执行结果以清晰易懂的方式呈现给用户
-
-        【响应格式】
-        - 直接回答用户的问题
-        - 如果使用了工具，说明使用了什么工具以及结果
-        - 如果遇到错误，提供友好的错误信息和解决建议
-        """)
-
-    @UserMessage("""
-        {{query}}
-        """)
-
-    @Agent("通用工具调用智能体")
-    /**
-     * 智能体对外调用入口
-     * @param query 用户的自然语言请求
-     * @return 处理结果
-     */
-    String callMcpTool(@V("query") String query);
-}
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/SqlAgent.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/SqlAgent.java
@@ -11,7 +11,7 @@ import dev.langchain4j.service.V;
 * and returning relevant data and analysis results.
 *
 */
-public interface SqlAgent extends Agent {
+public interface SqlAgent {

    @SystemMessage("""
        This agent is designed for MySQL 5.7
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/WebSearchAgent.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/WebSearchAgent.java
@@ -10,7 +10,7 @@ import dev.langchain4j.service.V;
 * A web search assistant that answers natural language questions by searching the internet
 * and returning relevant information from web pages.
 */
-public interface WebSearchAgent extends Agent {
+public interface WebSearchAgent {

    @SystemMessage("""
        You are a web search assistant. Answer questions by searching and retrieving web content.
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/tool/ExecuteSqlQueryTool.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/agent/tool/ExecuteSqlQueryTool.java
@@ -43,7 +43,7 @@ public class ExecuteSqlQueryTool implements BuiltinToolProvider {
    @Tool("Execute a SELECT SQL query and return the results. Example: SELECT * FROM sys_user")
    public String executeSql(String sql) {
        // 2. 手动推入数据源上下文
-        DynamicDataSourceContextHolder.push("agent");
+//        DynamicDataSourceContextHolder.push("agent");
        if (sql == null || sql.trim().isEmpty()) {
            return "Error: SQL query cannot be empty";
        }
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/config/VectorStoreProperties.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/config/VectorStoreProperties.java
@@ -59,4 +59,37 @@ public class VectorStoreProperties {
         */
        private String collectionname;
    }
+
+    /**
+     * Qdrant配置
+     */
+    private Qdrant qdrant = new Qdrant();
+
+    @Data
+    public static class Qdrant {
+        /**
+         * 主机地址
+         */
+        private String host = "localhost";
+
+        /**
+         * gRPC端口
+         */
+        private int port = 6334;
+
+        /**
+         * 集合名称
+         */
+        private String collectionname = "LocalKnowledge";
+
+        /**
+         * API密钥（可选）
+         */
+        private String apiKey;
+
+        /**
+         * 是否启用TLS
+         */
+        private boolean useTls = false;
+    }
 }
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/controller/chat/ChatController.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/controller/chat/ChatController.java
@@ -30,8 +30,8 @@ public class ChatController {
     */
    @PostMapping("/send")
    @ResponseBody
-    public SseEmitter sseChat(@RequestBody @Valid ChatRequest chatRequest, HttpServletRequest request) {
-        return chatService.sseChat(chatRequest,request);
+    public SseEmitter sseChat(@RequestBody @Valid ChatRequest chatRequest) {
+        return chatService.sseChat(chatRequest);
    }

 }
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/controller/chat/ChatMessageController.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/controller/chat/ChatMessageController.java
@@ -8,7 +8,7 @@ import jakarta.validation.constraints.*;
 import cn.dev33.satoken.annotation.SaCheckPermission;
 import org.ruoyi.common.chat.domain.bo.chat.ChatMessageBo;
 import org.ruoyi.common.chat.domain.vo.chat.ChatMessageVo;
-import org.ruoyi.common.chat.service.chatMessage.IChatMessageService;
+import org.ruoyi.service.chat.IChatMessageService;
 import org.springframework.web.bind.annotation.*;
 import org.springframework.validation.annotation.Validated;
 import org.ruoyi.common.idempotent.annotation.RepeatSubmit;
--- a/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/factory/ChatServiceFactory.java
+++ b/ruoyi-common/ruoyi-common-chat/src/main/java/org/ruoyi/common/chat/factory/ChatServiceFactory.java
@@ -1,6 +1,7 @@
-package org.ruoyi.common.chat.factory;
+package org.ruoyi.factory;

 import org.ruoyi.common.chat.service.chat.IChatService;
+import org.ruoyi.service.chat.AbstractChatService;
 import org.springframework.beans.BeansException;
 import org.springframework.context.ApplicationContext;
 import org.springframework.context.ApplicationContextAware;
@@ -18,13 +19,13 @@ import java.util.concurrent.ConcurrentHashMap;
@Component
 public class ChatServiceFactory implements ApplicationContextAware {

-    private final Map<String, IChatService> chatServiceMap = new ConcurrentHashMap<>();
+    private final Map<String, AbstractChatService> chatServiceMap = new ConcurrentHashMap<>();

    @Override
    public void setApplicationContext(ApplicationContext applicationContext) throws BeansException {
        // 初始化时收集所有IChatService的实现
-        Map<String, IChatService> serviceMap = applicationContext.getBeansOfType(IChatService.class);
-        for (IChatService service : serviceMap.values()) {
+        Map<String, AbstractChatService> serviceMap = applicationContext.getBeansOfType(AbstractChatService.class);
+        for (AbstractChatService service : serviceMap.values()) {
            if (service != null ) {
                chatServiceMap.put(service.getProviderName(), service);
            }
@@ -35,8 +36,8 @@ public class ChatServiceFactory implements ApplicationContextAware {
    /**
     * 获取原始服务（不包装代理）
     */
-    public IChatService getOriginalService(String category) {
-        IChatService service = chatServiceMap.get(category);
+    public AbstractChatService getOriginalService(String category) {
+        AbstractChatService service = chatServiceMap.get(category);
        if (service == null) {
            throw new IllegalArgumentException("不支持的模型类别: " + category);
        }
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/EmbeddingModelFactory.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/EmbeddingModelFactory.java
@@ -2,8 +2,9 @@ package org.ruoyi.factory;

 import lombok.RequiredArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
-import org.ruoyi.common.chat.service.chat.IChatModelService;
 import org.ruoyi.common.chat.domain.vo.chat.ChatModelVo;
+import org.ruoyi.common.chat.service.chat.IChatModelService;
+import org.ruoyi.observability.EmbeddingModelListenerProvider;
 import org.ruoyi.service.embed.BaseEmbedModelService;
 import org.ruoyi.service.embed.MultiModalEmbedModelService;
 import org.springframework.beans.factory.NoSuchBeanDefinitionException;
@@ -27,6 +28,7 @@ public class EmbeddingModelFactory {
    private final ApplicationContext applicationContext;

    private final IChatModelService chatModelService;
+    private final EmbeddingModelListenerProvider embeddingModelListenerProvider;

    // 模型缓存，使用ConcurrentHashMap保证线程安全
    private final Map<String, BaseEmbedModelService> modelCache = new ConcurrentHashMap<>();
@@ -109,6 +111,8 @@ public class EmbeddingModelFactory {
            BaseEmbedModelService model = applicationContext.getBean(factory, BaseEmbedModelService.class);
            // 配置模型参数
            model.configure(config);
+            // 增加嵌入模型监听器
+            model.addListeners(embeddingModelListenerProvider.getEmbeddingModelListeners());
            log.info("成功创建嵌入模型: factory={}, modelId={}", config.getProviderCode(), config.getId());
            return model;
        } catch (NoSuchBeanDefinitionException e) {
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/ResourceLoaderFactory.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/ResourceLoaderFactory.java
@@ -1,6 +1,7 @@
 package org.ruoyi.factory;

 import lombok.AllArgsConstructor;
+import org.apache.commons.lang3.StringUtils;
 import org.ruoyi.constant.FileTypeConstants;
 import org.ruoyi.service.knowledge.ResourceLoader;
 import org.ruoyi.service.knowledge.impl.loader.*;
@@ -16,6 +17,7 @@ public class ResourceLoaderFactory {
    private final ExcelTextSplitter excelTextSplitter;

    public ResourceLoader getLoaderByFileType(String fileType) {
+        fileType = StringUtils.removeStart(fileType, ".");
        if (FileTypeConstants.isTextFile(fileType)) {
            return new TextFileLoader(characterTextSplitter);
        } else if (FileTypeConstants.isWord(fileType)) {
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/VectorStoreStrategyFactory.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/factory/VectorStoreStrategyFactory.java
@@ -7,6 +7,7 @@ import lombok.extern.slf4j.Slf4j;
 import org.ruoyi.config.VectorStoreProperties;
 import org.ruoyi.service.vector.VectorStoreService;
 import org.ruoyi.service.vector.impl.MilvusVectorStoreStrategy;
+import org.ruoyi.service.vector.impl.QdrantVectorStoreStrategy;
 import org.ruoyi.service.vector.impl.WeaviateVectorStoreStrategy;
 import org.springframework.stereotype.Component;

@@ -27,6 +28,7 @@ public class VectorStoreStrategyFactory {
    private final VectorStoreProperties vectorStoreProperties;
    private final WeaviateVectorStoreStrategy weaviateStrategy;
    private final MilvusVectorStoreStrategy milvusStrategy;
+    private final QdrantVectorStoreStrategy qdrantStrategy;

    private Map<String, VectorStoreService> strategies;

@@ -35,6 +37,7 @@ public class VectorStoreStrategyFactory {
        strategies = new HashMap<>();
        strategies.put("weaviate", weaviateStrategy);
        strategies.put("milvus", milvusStrategy);
+        strategies.put("qdrant", qdrantStrategy);
        log.info("向量库策略工厂初始化完成，支持的策略: {}", strategies.keySet());
    }

--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/ChatModelListenerProvider.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/ChatModelListenerProvider.java
@@ -0,0 +1,41 @@
+package org.ruoyi.observability;
+
+import cn.hutool.core.collection.CollUtil;
+import dev.langchain4j.model.chat.listener.ChatModelListener;
+import dev.langchain4j.model.embedding.listener.EmbeddingModelListener;
+import lombok.Getter;
+import org.springframework.context.annotation.Lazy;
+import org.springframework.lang.Nullable;
+import org.springframework.stereotype.Component;
+
+import java.util.Collections;
+import java.util.List;
+
+/**
+ * LangChain4j 监听器共享提供者。
+ * <p>
+ * 供所有 {@link dev.langchain4j.model.chat.StreamingChatModel} 构建器使用，
+ * 将可观测性监听器注入到模型实例中。
+ *
+ * @author evo
+ */
+@Component
+@Getter
+@Lazy
+public class ChatModelListenerProvider {
+
+    private final List<ChatModelListener> chatModelListeners;
+    private final List<EmbeddingModelListener> embeddingModelListeners;
+
+    public ChatModelListenerProvider(@Nullable List<ChatModelListener> chatModelListeners,
+                                     @Nullable List<EmbeddingModelListener> embeddingModelListeners) {
+        if (CollUtil.isEmpty(chatModelListeners)) {
+            chatModelListeners = Collections.emptyList();
+        }
+        if (CollUtil.isEmpty(embeddingModelListeners)) {
+            embeddingModelListeners = Collections.emptyList();
+        }
+        this.chatModelListeners = chatModelListeners;
+        this.embeddingModelListeners = embeddingModelListeners;
+    }
+}
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/EmbeddingModelListenerProvider.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/EmbeddingModelListenerProvider.java
@@ -0,0 +1,34 @@
+package org.ruoyi.observability;
+
+import cn.hutool.core.collection.CollUtil;
+import dev.langchain4j.model.embedding.listener.EmbeddingModelListener;
+import lombok.Getter;
+import org.springframework.context.annotation.Lazy;
+import org.springframework.lang.Nullable;
+import org.springframework.stereotype.Component;
+
+import java.util.Collections;
+import java.util.List;
+
+/**
+ * EmbeddingModel 监听器共享提供者。
+ * <p>
+ * 供所有 {@link dev.langchain4j.model.embedding.EmbeddingModel} 构建器使用，
+ * 将可观测性监听器注入到模型实例中。
+ *
+ * @author evo
+ */
+@Component
+@Getter
+@Lazy
+public class EmbeddingModelListenerProvider {
+
+    private final List<EmbeddingModelListener> embeddingModelListeners;
+
+    public EmbeddingModelListenerProvider(@Nullable List<EmbeddingModelListener> embeddingModelListeners) {
+        if (CollUtil.isEmpty(embeddingModelListeners)) {
+            embeddingModelListeners = Collections.emptyList();
+        }
+        this.embeddingModelListeners = embeddingModelListeners;
+    }
+}
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/LangChain4jObservabilityConfig.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/LangChain4jObservabilityConfig.java
@@ -0,0 +1,129 @@
+package org.ruoyi.observability;
+
+import dev.langchain4j.Experimental;
+import dev.langchain4j.mcp.client.McpClientListener;
+import dev.langchain4j.model.chat.listener.ChatModelListener;
+import dev.langchain4j.model.embedding.listener.EmbeddingModelListener;
+import dev.langchain4j.observability.api.AiServiceListenerRegistrar;
+import dev.langchain4j.observability.api.listener.*;
+import jakarta.annotation.PostConstruct;
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+
+import java.util.List;
+
+/**
+ * LangChain4j 可观测性配置类。
+ * <p>
+ * 负责注册所有 langchain4j 的监听器：
+ * <ul>
+ *   <li>{@link AiServiceListener} - AI服务级别的事件监听器（通过 AiServiceListenerRegistrar 注册）</li>
+ *   <li>{@link ChatModelListener} - ChatModel 级别的监听器（注入到模型构建器）</li>
+ *   <li>{@link EmbeddingModelListener} - EmbeddingModel 级别的监听器（注入到模型构建器）</li>
+ * </ul>
+ *
+ * @author evo
+ */
+@Configuration
+@RequiredArgsConstructor
+@Slf4j
+public class LangChain4jObservabilityConfig {
+
+    private final AiServiceListenerRegistrar registrar = AiServiceListenerRegistrar.newInstance();
+
+    /**
+     * 注册 AI 服务级别的事件监听器
+     */
+    @PostConstruct
+    public void registerAiServiceListeners() {
+        log.info("正在注册 LangChain4j AI Service 事件监听器...");
+        registrar.register(
+            new MyAiServiceStartedListener(),
+            new MyAiServiceRequestIssuedListener(),
+            new MyAiServiceResponseReceivedListener(),
+            new MyAiServiceCompletedListener(),
+            new MyAiServiceErrorListener(),
+            new MyInputGuardrailExecutedListener(),
+            new MyOutputGuardrailExecutedListener(),
+            new MyToolExecutedEventListener()
+        );
+        log.info("LangChain4j AI Service 事件监听器注册完成");
+    }
+
+    // ==================== AI Service 监听器 Beans ====================
+
+    @Bean
+    public AiServiceStartedListener aiServiceStartedListener() {
+        return new MyAiServiceStartedListener();
+    }
+
+    @Bean
+    public AiServiceRequestIssuedListener aiServiceRequestIssuedListener() {
+        return new MyAiServiceRequestIssuedListener();
+    }
+
+    @Bean
+    public AiServiceResponseReceivedListener aiServiceResponseReceivedListener() {
+        return new MyAiServiceResponseReceivedListener();
+    }
+
+    @Bean
+    public AiServiceCompletedListener aiServiceCompletedListener() {
+        return new MyAiServiceCompletedListener();
+    }
+
+    @Bean
+    public AiServiceErrorListener aiServiceErrorListener() {
+        return new MyAiServiceErrorListener();
+    }
+
+    @Bean
+    public InputGuardrailExecutedListener inputGuardrailExecutedListener() {
+        return new MyInputGuardrailExecutedListener();
+    }
+
+    @Bean
+    public OutputGuardrailExecutedListener outputGuardrailExecutedListener() {
+        return new MyOutputGuardrailExecutedListener();
+    }
+
+    @Bean
+    public ToolExecutedEventListener toolExecutedEventListener() {
+        return new MyToolExecutedEventListener();
+    }
+
+    // ==================== ChatModel 监听器 ====================
+
+    @Bean
+    public ChatModelListener chatModelListener() {
+        return new MyChatModelListener();
+    }
+
+    @Bean
+    public List<ChatModelListener> chatModelListeners() {
+        return List.of(new MyChatModelListener());
+    }
+
+    // ==================== EmbeddingModel 监听器 ====================
+
+    @Bean
+    @Experimental
+    public EmbeddingModelListener embeddingModelListener() {
+        return new MyEmbeddingModelListener();
+    }
+
+    @Bean
+    @Experimental
+    public List<EmbeddingModelListener> embeddingModelListeners() {
+        return List.of(new MyEmbeddingModelListener());
+    }
+
+    // ==================== MCP Client 监听器 ====================
+
+    @Bean
+    public McpClientListener mcpClientListener() {
+        return new MyMcpClientListener();
+    }
+}
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/MyAgentListener.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/MyAgentListener.java
@@ -0,0 +1,145 @@
+package org.ruoyi.observability;
+
+import dev.langchain4j.agentic.observability.AgentInvocationError;
+import dev.langchain4j.agentic.observability.AgentRequest;
+import dev.langchain4j.agentic.observability.AgentResponse;
+import dev.langchain4j.agentic.planner.AgentInstance;
+import dev.langchain4j.agentic.scope.AgenticScope;
+import dev.langchain4j.service.tool.BeforeToolExecution;
+import dev.langchain4j.service.tool.ToolExecution;
+import lombok.extern.slf4j.Slf4j;
+
+import java.util.Map;
+import java.util.concurrent.atomic.AtomicReference;
+
+/**
+ * 自定义的 AgentListener 的监听器。
+ * 监听 Agent 相关的所有可观测性事件，包括：
+ * <ul>
+ *   <li>Agent 调用前/后的生命周期事件</li>
+ *   <li>Agent 执行错误事件</li>
+ *   <li>AgenticScope 的创建/销毁事件</li>
+ *   <li>工具执行前/后的生命周期事件</li>
+ * </ul>
+ *
+ * @author evo
+ */
+@Slf4j
+public class MyAgentListener implements dev.langchain4j.agentic.observability.AgentListener {
+
+    /** 最终捕获到的思考结果（主 Agent 完成后写入，供外部获取） */
+    private final AtomicReference<String> sharedOutputRef = new AtomicReference<>();
+
+    public String getCapturedResult() {
+        return sharedOutputRef.get();
+    }
+
+    // ==================== Agent 调用生命周期 ====================
+
+    @Override
+    public void beforeAgentInvocation(AgentRequest agentRequest) {
+        AgentInstance agent = agentRequest.agent();
+        AgenticScope scope = agentRequest.agenticScope();
+        Map<String, Object> inputs = agentRequest.inputs();
+
+        log.info("【Agent调用前】Agent名称: {}", agent.name());
+        log.info("【Agent调用前】Agent ID: {}", agent.agentId());
+        log.info("【Agent调用前】Agent类型: {}", agent.type().getName());
+        log.info("【Agent调用前】Agent描述: {}", agent.description());
+        log.info("【Agent调用前】Planner类型: {}", agent.plannerType());
+        log.info("【Agent调用前】输出类型: {}", agent.outputType());
+        log.info("【Agent调用前】输出Key: {}", agent.outputKey());
+        log.info("【Agent调用前】是否为异步: {}", agent.async());
+        log.info("【Agent调用前】是否为叶子节点: {}", agent.leaf());
+        log.info("【Agent调用前】Agent参数列表:");
+        for (var arg : agent.arguments()) {
+            log.info("  - 参数名: {}, 类型: {}, 默认值: {}",
+                    arg.name(), arg.rawType().getName(), arg.defaultValue());
+        }
+        log.info("【Agent调用前】Agent输入参数: {}", inputs);
+        log.info("【Agent调用前】AgenticScope memoryId: {}", scope.memoryId());
+        log.info("【Agent调用前】AgenticScope当前状态: {}", scope.state());
+        log.info("【Agent调用前】Agent调用历史记录数: {}", scope.agentInvocations().size());
+
+        // 打印嵌套的子Agent信息
+        if (!agent.subagents().isEmpty()) {
+            log.info("【Agent调用前】子Agent列表:");
+            for (AgentInstance sub : agent.subagents()) {
+                log.info("  - 子Agent: {} ({})", sub.name(), sub.type().getName());
+            }
+        }
+
+        // 打印父Agent信息
+        if (agent.parent() != null) {
+            log.info("【Agent调用前】父Agent: {}", agent.parent().name());
+        }
+    }
+
+    @Override
+    public void afterAgentInvocation(AgentResponse agentResponse) {
+        AgentInstance agent = agentResponse.agent();
+        Map<String, Object> inputs = agentResponse.inputs();
+        Object output = agentResponse.output();
+        String outputStr = output != null ? output.toString() : "";
+
+        log.info("【Agent调用后】Agent名称: {}", agent.name());
+        log.info("【Agent调用后】Agent ID: {}", agent.agentId());
+        log.info("【Agent调用后】Agent输入参数: {}", inputs);
+        log.info("【Agent调用后】Agent输出结果: {}", output);
+        log.info("【Agent调用后】是否为叶子节点: {}", agent.leaf());
+
+        // 捕获主 Agent 的最终输出，供外部获取
+        if ("invoke".equals(agent.agentId()) && !outputStr.isEmpty()) {
+            sharedOutputRef.set(outputStr);
+            log.info("【Agent调用后】已捕获主Agent输出: {}", outputStr);
+        }
+    }
+
+    @Override
+    public void onAgentInvocationError(AgentInvocationError error) {
+        AgentInstance agent = error.agent();
+        Map<String, Object> inputs = error.inputs();
+        Throwable throwable = error.error();
+
+        log.error("【Agent执行错误】Agent名称: {}", agent.name());
+        log.error("【Agent执行错误】Agent ID: {}", agent.agentId());
+        log.error("【Agent执行错误】Agent类型: {}", agent.type().getName());
+        log.error("【Agent执行错误】Agent输入参数: {}", inputs);
+        log.error("【Agent执行错误】错误类型: {}", throwable.getClass().getName());
+        log.error("【Agent执行错误】错误信息: {}", throwable.getMessage(), throwable);
+    }
+
+    // ==================== AgenticScope 生命周期 ====================
+
+    @Override
+    public void afterAgenticScopeCreated(AgenticScope agenticScope) {
+        log.info("【AgenticScope已创建】memoryId: {}", agenticScope.memoryId());
+        log.info("【AgenticScope已创建】初始状态: {}", agenticScope.state());
+    }
+
+    @Override
+    public void beforeAgenticScopeDestroyed(AgenticScope agenticScope) {
+        log.info("【AgenticScope即将销毁】memoryId: {}", agenticScope.memoryId());
+        log.info("【AgenticScope即将销毁】最终状态: {}", agenticScope.state());
+        log.info("【AgenticScope即将销毁】总调用次数: {}", agenticScope.agentInvocations().size());
+    }
+
+    // ==================== 工具执行生命周期 ====================
+
+    @Override
+    public void beforeToolExecution(BeforeToolExecution beforeToolExecution) {
+        var toolRequest = beforeToolExecution.request();
+        log.info("【工具执行前】工具请求ID: {}", toolRequest.id());
+        log.info("【工具执行前】工具名称: {}", toolRequest.name());
+        log.info("【工具执行前】工具参数: {}", toolRequest.arguments());
+    }
+
+    @Override
+    public void afterToolExecution(ToolExecution toolExecution) {
+        var toolRequest = toolExecution.request();
+        log.info("【工具执行后】工具请求ID: {}", toolRequest.id());
+        log.info("【工具执行后】工具名称: {}", toolRequest.name());
+        log.info("【工具执行后】工具执行结果: {}", toolExecution.result());
+        log.info("【工具执行后】工具执行是否失败: {}", toolExecution.hasFailed());
+    }
+}
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/MyAiServiceCompletedListener.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/MyAiServiceCompletedListener.java
@@ -0,0 +1,41 @@
+package org.ruoyi.observability;
+
+import dev.langchain4j.invocation.InvocationContext;
+import dev.langchain4j.observability.api.event.AiServiceCompletedEvent;
+import dev.langchain4j.observability.api.listener.AiServiceCompletedListener;
+import lombok.extern.slf4j.Slf4j;
+
+import java.time.Instant;
+import java.util.List;
+import java.util.Optional;
+import java.util.UUID;
+
+/**
+ * 自定义的 AiServiceCompletedEvent 的监听器。
+ * 它表示在 AI 服务调用完成时发生的事件。
+ *
+ * @author evo
+ */
+@Slf4j
+public class MyAiServiceCompletedListener implements AiServiceCompletedListener {
+
+    @Override
+    public void onEvent(AiServiceCompletedEvent event) {
+        InvocationContext invocationContext = event.invocationContext();
+        Optional<Object> result = event.result();
+        UUID invocationId = invocationContext.invocationId();
+        String aiServiceInterfaceName = invocationContext.interfaceName();
+        String aiServiceMethodName = invocationContext.methodName();
+        List<Object> aiServiceMethodArgs = invocationContext.methodArguments();
+        Object chatMemoryId = invocationContext.chatMemoryId();
+        Instant eventTimestamp = invocationContext.timestamp();
+
+        log.info("【AI服务完成】调用唯一标识符: {}", invocationId);
+        log.info("【AI服务完成】AI服务接口名: {}", aiServiceInterfaceName);
+        log.info("【AI服务完成】调用的方法名: {}", aiServiceMethodName);
+        log.info("【AI服务完成】AI服务方法参数: {}", aiServiceMethodArgs);
+        log.info("【AI服务完成】聊天记忆ID: {}", chatMemoryId);
+        log.info("【AI服务完成】调用发生的时间: {}", eventTimestamp);
+        log.info("【AI服务完成】调用结果: {}", result);
+    }
+}
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/MyAiServiceErrorListener.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/MyAiServiceErrorListener.java
@@ -0,0 +1,33 @@
+package org.ruoyi.observability;
+
+import dev.langchain4j.invocation.InvocationContext;
+import dev.langchain4j.observability.api.event.AiServiceErrorEvent;
+import dev.langchain4j.observability.api.listener.AiServiceErrorListener;
+import lombok.extern.slf4j.Slf4j;
+
+import java.util.UUID;
+
+/**
+ * 自定义的 AiServiceErrorEvent 的监听器。
+ * 它表示在 AI 服务调用失败时发生的事件。
+ *
+ * @author evo
+ */
+@Slf4j
+public class MyAiServiceErrorListener implements AiServiceErrorListener {
+
+    @Override
+    public void onEvent(AiServiceErrorEvent event) {
+        InvocationContext invocationContext = event.invocationContext();
+        UUID invocationId = invocationContext.invocationId();
+        String aiServiceInterfaceName = invocationContext.interfaceName();
+        String aiServiceMethodName = invocationContext.methodName();
+        Throwable error = event.error();
+
+        log.error("【AI服务错误】调用唯一标识符: {}", invocationId);
+        log.error("【AI服务错误】AI服务接口名: {}", aiServiceInterfaceName);
+        log.error("【AI服务错误】调用的方法名: {}", aiServiceMethodName);
+        log.error("【AI服务错误】错误类型: {}", error.getClass().getName());
+        log.error("【AI服务错误】错误信息: {}", error.getMessage(), error);
+    }
+}
--- a/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/MyAiServiceRequestIssuedListener.java
+++ b/ruoyi-modules/ruoyi-chat/src/main/java/org/ruoyi/observability/MyAiServiceRequestIssuedListener.java
@@ -0,0 +1,33 @@
+package org.ruoyi.observability;
+
+import dev.langchain4j.invocation.InvocationContext;
+import dev.langchain4j.model.chat.request.ChatRequest;
+import dev.langchain4j.observability.api.event.AiServiceRequestIssuedEvent;
+import dev.langchain4j.observability.api.listener.AiServiceRequestIssuedListener;
+import lombok.extern.slf4j.Slf4j;
+
+import java.util.UUID;
+
+/**
+ * 自定义的 AiServiceRequestIssuedEvent 的监听器。
+ * 它表示在向 LLM 发送请求之前发生的事件。
+ *
+ * @author evo
+ */
+@Slf4j
+public class MyAiServiceRequestIssuedListener implements AiServiceRequestIssuedListener {
+
+    @Override
+    public void onEvent(AiServiceRequestIssuedEvent event) {
+        InvocationContext invocationContext = event.invocationContext();
+        UUID invocationId = invocationContext.invocationId();
+        String aiServiceInterfaceName = invocationContext.interfaceName();
+        String aiServiceMethodName = invocationContext.methodName();
+        ChatRequest request = event.request();
+
+        log.info("【请求已发出】调用唯一标识符: {}", invocationId);
+        log.info("【请求已发出】AI服务接口名: {}", aiServiceInterfaceName);
+        log.info("【请求已发出】调用的方法名: {}", aiServiceMethodName);
+        log.info("【请求已发出】发送给LLM的请求: {}", request);
+    }
+}
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
wangle	bf7b5eac72	fix：修复上下文消息构建顺序，确保AI正确理解对话上下文消息顺序调整为：历史消息 → 知识库内容 → 当前用户消息 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-07 22:13:32 +08:00
wangle	d602b805bd	docs：更新技术栈版本号并清理文档 - 更新后端架构版本为 Spring Boot 3.5.8 + Langchain4j - 删除 rag-failures.md 和文件上传接口文档 - 重命名 mcp-api-spec.md 为 MCP工具模块接口文档.md Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-04-07 21:04:31 +08:00
ageerle	9cf18904bb	Merge pull request #284 from MuSan-Li/main 添加可观测性功能	2026-04-07 10:04:05 +08:00
evo	2f39fa0f53	feat：调整可观测性监听器逻辑	2026-04-05 21:36:53 +08:00
evo	d2005cfa48	feat：调整可观测性监听器逻辑	2026-04-05 21:34:41 +08:00
evo	4e38f853f3	feat：修复登录校验 & 调整主启动类的kill port 逻辑	2026-04-02 10:07:26 +08:00
evo	3cfb185dde	feat：增加可观测性监听器调整思考输出监听日志	2026-04-01 23:11:54 +08:00
evo	ef99c540bb	feat：增加可观测性的相关监听器 & 修复前端问答报错outputkey问题	2026-04-01 22:32:01 +08:00
ageerle	3071bfd0f9	Merge pull request #282 from Anush008/main docs: Docker Compose setup for Qdrant	2026-03-28 20:33:25 +08:00
Anush008	7bb938c145	docs: Docker Compose setup for Qdrant	2026-03-28 13:37:53 +05:30
ageerle	75b21d3633	Merge pull request #281 from Anush008/main feat: Adds support for Qdrant vector search	2026-03-27 21:51:03 +08:00
Anush008	7ed9d8def4	chore: Rename METADATA_DOC_ID_KEY	2026-03-27 18:36:30 +05:30
Anush008	63ed7ddb02	feat: Adds support for Qdrant vector search	2026-03-27 18:31:05 +05:30
ageerle	11696a016d	fix: 修复文件类型匹配和知识库切割配置问题 1. 修复 ResourceLoaderFactory 文件扩展名匹配问题 - 去除扩展名前导点，确保 .pdf 能正确匹配 PDF 解析器 - 修复 PDF/Word/Excel 等文件走错解析逻辑的问题 2. 优化文本切割器动态配置 - CharacterTextSplitter 和 ExcelTextSplitter 支持从知识库读取配置 - 根据 kid 查询 separator、textBlockSize、overlapChar - 查询失败时降级使用默认配置 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-25 18:51:01 +08:00
ageerle	1a10104751	docs: 更新README文档，同步中英文版本 - 移除优秀开源项目推荐章节 - 英文版添加Docker部署完整文档 - 英文版添加技术架构详细描述 - 英文版添加RAG排查手册链接 - 统一核心功能表格格式 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-21 13:02:46 +08:00
ageerle	f95cb17933	chore: 删除ruoyi-modules-api模块 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-21 12:31:09 +08:00
ageerle	0687b49542	Merge branch 'v3.0.0' into main 合并 v3.0.0 分支到 main，包含以下主要更新： - 重构聊天模块架构，引入Handler模式 - 添加 Docker 部署支持 - 恢复 MCP 模块功能 - 工作流与大模型聊天对话整合 - 多项 bug 修复和文档更新 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-21 12:15:40 +08:00
ageerle	27ad00ac3a	refactor: 抽离特殊聊天模式处理逻辑 - 将工作流、人机交互恢复、思考模式处理逻辑抽离为独立方法 - 新增 handleSpecialChatModes 方法统一处理特殊模式 - 新增 handleThinkingMode 方法专门处理思考模式 - 简化 sseChat 方法结构，提高代码可读性 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-20 10:38:54 +08:00
ageerle	c84d6247b0	refactor: 重构聊天模块架构 - 删除废弃的ChatMessageDTO、ChatContext、AbstractChatMessageService等类 - 迁移ChatServiceFactory和IChatMessageService到ruoyi-chat模块 - 重构ChatHandler体系，移除DefaultChatHandler和ChatContextBuilder - 优化SSE消息处理，新增SseEventDto - 简化各AI服务提供商实现类代码 - 优化工作流节点消息处理逻辑 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-20 01:20:41 +08:00
ageerle	f582f38570	docs: 整理Docker配置文件并更新文档 - 将Docker相关配置文件移动到docs/docker/ruoyi-ai/目录 - 更新README.md核心亮点表格格式 - 新增流程编排模块详细说明文档 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-19 15:22:47 +08:00
ageerle	a8bd4b47a0	chore: 移除项目文档和技术交流链接 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-06 11:44:07 +08:00
ageerle	a59ddf6070	refactor: 重构Issue模板为通用格式 - 删除企业合作登记模板 - 新增漏洞报告模板 - 新增想法建议模板 - 新增自定义模板 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-06 11:39:06 +08:00
ageerle	797ecbb054	feat: 新增联系人/联系方式字段并添加填写示例 - 新增联系人/联系方式字段，支持登记后主动联系 - 在可复制模板中添加完整填写示例 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-06 11:30:15 +08:00
ageerle	b6b78afea9	refactor: 优化企业合作登记模板格式 - 改为评论登记模式，用户在Issue下评论填写 - 提供格式预览和可复制模板 - 新增公司Logo和项目Logo字段 - 移除联系方式模块，保护隐私 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-06 11:20:31 +08:00
ageerle	02240f3fd0	feat: 添加企业AI应用合作登记Issue模板 - 新增企业合作登记模板，用于收集企业AI应用需求 - 包含基本信息、AI应用需求、联系方式三个模块 - 预设筛选字段便于评估合作匹配度 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	2026-03-06 11:07:25 +08:00
ageerle	a916f14efc	Merge pull request #268 from onestardao/main docs: add structured RAG 16-problem troubleshooting guide and README entry	2026-03-03 10:40:32 +08:00
PSBigBig × MiniPS	523628ade6	docs: add structured RAG 16-problem troubleshooting guide and README entry	2026-03-02 19:01:59 +08:00
PSBigBig × MiniPS	2259a2f717	docs: add structured RAG 16-problem troubleshooting guide and README entry This commit introduces a structured RAG troubleshooting guide based on a fixed 16-problem failure map. Changes include: 1. Added a dedicated RAG troubleshooting document: - docs/troubleshooting/rag-failures.md - Includes full 16-problem map (No.1–No.16) with layer tags [IN]/[RE]/[ST]/[OP] - Adds symptom-based entry points - Adds layer-based diagnostics section - Adds issue reporting template referencing No.X labels 2. Updated README.md: - Added entry link under the "使用文档" section - Direct link to the new RAG troubleshooting guide - Keeps README structure and tone consistent No functional changes. Documentation only.	2026-03-02 18:51:36 +08:00
PSBigBig × MiniPS	8df37274da	docs: add RAG answer troubleshooting guide	2026-03-02 17:44:59 +08:00
PSBigBig × MiniPS	393057ab24	docs: add RAG answer troubleshooting guide	2026-03-02 17:41:47 +08:00
ageerle	ee8c882b6f	Merge pull request #256 from StevenJack666/main 修改AI工作流后端逻辑	2026-02-11 17:03:31 +08:00
zhang	69ec2a33a4	init	2026-02-09 17:47:18 +08:00
zhang	1cd8ae1cd9	人机交互节点逻辑修改	2026-02-09 17:43:29 +08:00