Files
hzhub/hzhub-ai
大壮 c2513849b4 feat: 添加ERP服务和系统服务,完善员工门户功能
## 新增服务模块

### 1. ERP服务 (hzhub-erp)
- 新增独立的ERP数据适配服务
- 支持SQL Server 2008 R2数据源
- 提供动态API配置管理系统
- 包含客户管理、销售数据等业务接口

### 2. 系统服务 (hzhub-system)
- 新增独立的系统管理服务
- 用户、角色、权限、部门、菜单管理
- 租户管理、操作日志、在线用户监控
- 工作流引擎(warm-flow)集成
- 企业微信审批同步功能

### 3. API网关 (hzhub-gateway)
- 新增Spring Cloud Gateway网关服务
- JWT认证、路由分发、限流熔断
- XSS防护、请求日志记录
- 统一入口端口8080

## 后台管理功能增强

### ERP动态API管理
- 新增动态API配置管理界面
- API测试、文档预览、统计监控
- 错误日志查看、缓存管理
- 从数据库表自动导入API配置

### 系统管理增强
- 企业微信配置管理
- 企业微信审批同步配置
- 部门和用户管理优化

## 员工门户功能完善

### 业务页面
- 审批中心:工作流审批、待办任务
- CRM管理:客户关系管理
- 经销商管理:经销商数据展示
- 供应链管理:采购、库存、销售
- BI报表:数据可视化分析
- ERP数据探索:SQL Server数据查询

### 个人中心
- 基本设置:个人信息管理
- 安全设置:密码修改、登录日志
- 锁屏功能:自动锁屏、手动锁屏

### 其他功能
- 标签页管理:多标签页导航
- 页面缓存:keepAlive缓存机制
- 会话超时:自动检测并提示

## 经销商门户

### 页面路由
- 新增经销商管理页面路由
- AI聊天界面完善

## 文档更新

- ERP API数据库初始化指南
- ERP API前端完整实现文档
- ERP API测试和验证指南
- Gateway路由迁移计划
- 项目配置文档更新

## 部署脚本

- 统一启动/停止/重启脚本
- Docker Compose配置优化
- Nginx配置文件更新

## 技术栈

- 后端: Spring Boot 3.5.8, Java 17
- 前端: Vue 3, TypeScript, Element Plus, Vben Admin
- 工作流: warm-flow 1.8.2
- 网关: Spring Cloud Gateway
- 数据库: MySQL 8.0, SQL Server 2008 R2
- 缓存: Redis 7
- 向量库: Weaviate 1.25.0

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-08 08:00:19 +00:00
..

HZHub AI

Contributors Forks Stargazers Issues MIT License

GitHub Trending

HZHub AI Logo

Enterprise-Grade AI Assistant Platform

An out-of-the-box full-stack AI platform supporting multi-agent collaboration, Supervisor mode orchestration, and multiple decision models, with advanced RAG technology and visual workflow orchestration capabilities

中文 | 📖 Documentation | 🚀 Live Demo | 🐛 Report Issues | 💡 Feature Requests

Core Features

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) + 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

Live Demo

Platform URL Account
User Frontend web.pandarobot.chat admin / admin123
Admin Panel admin.pandarobot.chat admin / admin123

Project Repositories

Module GitHub Repository Gitee Repository GitCode Repository
🔧 Backend hzhub-ai hzhub-ai hzhub-ai
🎨 User Frontend hzhub-portal hzhub-portal hzhub-portal
🛠️ Admin Panel hzhub-admin hzhub-admin hzhub-admin

Partner Projects

Project Name GitHub Repository Gitee Repository
element-plus-x element-plus-x 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)

  • 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:

Use docker-compose-all.yaml to start all services at once (including backend, admin panel, user frontend, and dependencies):

# Clone the repository
git clone https://github.com/ageerle/hzhub-ai.git
cd hzhub-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

# Enter backend project directory
cd hzhub-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

# Enter admin panel project directory
cd hzhub-admin

# Build and start admin panel
docker-compose up -d --build

# Access admin panel
# URL: http://localhost:5666

Step 3: Deploy User Frontend (Optional)

# Enter user frontend project directory
cd hzhub-portal

# 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
  • hzhub-ai-backend:latest - Backend service
  • hzhub-ai-admin:latest - Admin frontend
  • hzhub-ai-web:latest - User frontend

Common Commands

# 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?

👉 Complete Documentation

Experiencing issues with knowledge base or RAG responses?

👉 RAG Troubleshooting Guide


🤝 Contributing

We warmly welcome community contributions! Whether you are a seasoned developer or just getting started, you can contribute to the project 💪

How to Contribute

  1. Fork the project to your account
  2. Create a branch (git checkout -b feature/new-feature-name)
  3. Commit your changes (git commit -m 'Add new feature')
  4. Push to the branch (git push origin feature/new-feature-name)
  5. Create a Pull Request

💡 Tip: We recommend submitting PRs to GitHub, we will automatically sync to other code hosting platforms

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

🙏 Acknowledgments

Thanks to the following excellent open-source projects for their support:

🌐 Ecosystem Partners

  • PPIO Cloud - Provides cost-effective GPU computing and model API services
  • Youyun Intelligent Computing - Thousands of RTX40 series GPUs + mainstream models API services, second-level response, pay-per-use, free for new customers.

💬 Community Chat


Star to SupportFork to Contribute📚 中文📖 Complete Documentation

Built with ❤️, maintained by the HZHub AI open-source community